diff --git a/Plotly Plots.ipynb b/Plotly Plots.ipynb
new file mode 100644
index 000000000..e272ff34f
--- /dev/null
+++ b/Plotly Plots.ipynb	
@@ -0,0 +1,178385 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "        <script type=\"text/javascript\">\n",
+       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
+       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
+       "        if (typeof require !== 'undefined') {\n",
+       "        require.undef(\"plotly\");\n",
+       "        define('plotly', function(require, exports, module) {\n",
+       "            /**\n",
+       "* plotly.js v1.52.2\n",
+       "* Copyright 2012-2020, Plotly, Inc.\n",
+       "* All rights reserved.\n",
+       "* Licensed under the MIT license\n",
+       "*/\n",
+       "!function(t){if(\"object\"==typeof exports&&\"undefined\"!=typeof module)module.exports=t();else if(\"function\"==typeof define&&define.amd)define([],t);else{(\"undefined\"!=typeof window?window:\"undefined\"!=typeof global?global:\"undefined\"!=typeof self?self:this).Plotly=t()}}(function(){return function(){return function t(e,r,n){function a(o,s){if(!r[o]){if(!e[o]){var l=\"function\"==typeof require&&require;if(!s&&l)return l(o,!0);if(i)return i(o,!0);var c=new Error(\"Cannot find module '\"+o+\"'\");throw c.code=\"MODULE_NOT_FOUND\",c}var u=r[o]={exports:{}};e[o][0].call(u.exports,function(t){return a(e[o][1][t]||t)},u,u.exports,t,e,r,n)}return r[o].exports}for(var i=\"function\"==typeof require&&require,o=0;o<n.length;o++)a(n[o]);return a}}()({1:[function(t,e,r){\"use strict\";var n=t(\"../src/lib\"),a={\"X,X div\":\"direction:ltr;font-family:'Open Sans', verdana, arial, sans-serif;margin:0;padding:0;\",\"X input,X button\":\"font-family:'Open Sans', verdana, arial, sans-serif;\",\"X input:focus,X button:focus\":\"outline:none;\",\"X a\":\"text-decoration:none;\",\"X a:hover\":\"text-decoration:none;\",\"X .crisp\":\"shape-rendering:crispEdges;\",\"X .user-select-none\":\"-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;-o-user-select:none;user-select:none;\",\"X svg\":\"overflow:hidden;\",\"X svg a\":\"fill:#447adb;\",\"X svg a:hover\":\"fill:#3c6dc5;\",\"X .main-svg\":\"position:absolute;top:0;left:0;pointer-events:none;\",\"X .main-svg .draglayer\":\"pointer-events:all;\",\"X .cursor-default\":\"cursor:default;\",\"X .cursor-pointer\":\"cursor:pointer;\",\"X .cursor-crosshair\":\"cursor:crosshair;\",\"X .cursor-move\":\"cursor:move;\",\"X .cursor-col-resize\":\"cursor:col-resize;\",\"X .cursor-row-resize\":\"cursor:row-resize;\",\"X .cursor-ns-resize\":\"cursor:ns-resize;\",\"X .cursor-ew-resize\":\"cursor:ew-resize;\",\"X .cursor-sw-resize\":\"cursor:sw-resize;\",\"X .cursor-s-resize\":\"cursor:s-resize;\",\"X .cursor-se-resize\":\"cursor:se-resize;\",\"X .cursor-w-resize\":\"cursor:w-resize;\",\"X .cursor-e-resize\":\"cursor:e-resize;\",\"X .cursor-nw-resize\":\"cursor:nw-resize;\",\"X .cursor-n-resize\":\"cursor:n-resize;\",\"X .cursor-ne-resize\":\"cursor:ne-resize;\",\"X .cursor-grab\":\"cursor:-webkit-grab;cursor:grab;\",\"X .modebar\":\"position:absolute;top:2px;right:2px;\",\"X .ease-bg\":\"-webkit-transition:background-color 0.3s ease 0s;-moz-transition:background-color 0.3s ease 0s;-ms-transition:background-color 0.3s ease 0s;-o-transition:background-color 0.3s ease 0s;transition:background-color 0.3s ease 0s;\",\"X .modebar--hover>:not(.watermark)\":\"opacity:0;-webkit-transition:opacity 0.3s ease 0s;-moz-transition:opacity 0.3s ease 0s;-ms-transition:opacity 0.3s ease 0s;-o-transition:opacity 0.3s ease 0s;transition:opacity 0.3s ease 0s;\",\"X:hover .modebar--hover .modebar-group\":\"opacity:1;\",\"X .modebar-group\":\"float:left;display:inline-block;box-sizing:border-box;padding-left:8px;position:relative;vertical-align:middle;white-space:nowrap;\",\"X .modebar-btn\":\"position:relative;font-size:16px;padding:3px 4px;height:22px;cursor:pointer;line-height:normal;box-sizing:border-box;\",\"X .modebar-btn svg\":\"position:relative;top:2px;\",\"X .modebar.vertical\":\"display:flex;flex-direction:column;flex-wrap:wrap;align-content:flex-end;max-height:100%;\",\"X .modebar.vertical svg\":\"top:-1px;\",\"X .modebar.vertical .modebar-group\":\"display:block;float:none;padding-left:0px;padding-bottom:8px;\",\"X .modebar.vertical .modebar-group .modebar-btn\":\"display:block;text-align:center;\",\"X [data-title]:before,X [data-title]:after\":\"position:absolute;-webkit-transform:translate3d(0, 0, 0);-moz-transform:translate3d(0, 0, 0);-ms-transform:translate3d(0, 0, 0);-o-transform:translate3d(0, 0, 0);transform:translate3d(0, 0, 0);display:none;opacity:0;z-index:1001;pointer-events:none;top:110%;right:50%;\",\"X [data-title]:hover:before,X [data-title]:hover:after\":\"display:block;opacity:1;\",\"X [data-title]:before\":\"content:'';position:absolute;background:transparent;border:6px solid transparent;z-index:1002;margin-top:-12px;border-bottom-color:#69738a;margin-right:-6px;\",\"X [data-title]:after\":\"content:attr(data-title);background:#69738a;color:white;padding:8px 10px;font-size:12px;line-height:12px;white-space:nowrap;margin-right:-18px;border-radius:2px;\",\"X .vertical [data-title]:before,X .vertical [data-title]:after\":\"top:0%;right:200%;\",\"X .vertical [data-title]:before\":\"border:6px solid transparent;border-left-color:#69738a;margin-top:8px;margin-right:-30px;\",\"X .select-outline\":\"fill:none;stroke-width:1;shape-rendering:crispEdges;\",\"X .select-outline-1\":\"stroke:white;\",\"X .select-outline-2\":\"stroke:black;stroke-dasharray:2px 2px;\",Y:\"font-family:'Open Sans';position:fixed;top:50px;right:20px;z-index:10000;font-size:10pt;max-width:180px;\",\"Y p\":\"margin:0;\",\"Y .notifier-note\":\"min-width:180px;max-width:250px;border:1px solid #fff;z-index:3000;margin:0;background-color:#8c97af;background-color:rgba(140,151,175,0.9);color:#fff;padding:10px;overflow-wrap:break-word;word-wrap:break-word;-ms-hyphens:auto;-webkit-hyphens:auto;hyphens:auto;\",\"Y .notifier-close\":\"color:#fff;opacity:0.8;float:right;padding:0 5px;background:none;border:none;font-size:20px;font-weight:bold;line-height:20px;\",\"Y .notifier-close:hover\":\"color:#444;text-decoration:none;cursor:pointer;\"};for(var i in a){var o=i.replace(/^,/,\" ,\").replace(/X/g,\".js-plotly-plot .plotly\").replace(/Y/g,\".plotly-notifier\");n.addStyleRule(o,a[i])}},{\"../src/lib\":717}],2:[function(t,e,r){\"use strict\";e.exports=t(\"../src/transforms/aggregate\")},{\"../src/transforms/aggregate\":1297}],3:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/bar\")},{\"../src/traces/bar\":864}],4:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/barpolar\")},{\"../src/traces/barpolar\":877}],5:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/box\")},{\"../src/traces/box\":887}],6:[function(t,e,r){\"use strict\";e.exports=t(\"../src/components/calendars\")},{\"../src/components/calendars\":590}],7:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/candlestick\")},{\"../src/traces/candlestick\":896}],8:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/carpet\")},{\"../src/traces/carpet\":915}],9:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/choropleth\")},{\"../src/traces/choropleth\":929}],10:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/choroplethmapbox\")},{\"../src/traces/choroplethmapbox\":936}],11:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/cone\")},{\"../src/traces/cone\":942}],12:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/contour\")},{\"../src/traces/contour\":957}],13:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/contourcarpet\")},{\"../src/traces/contourcarpet\":968}],14:[function(t,e,r){\"use strict\";e.exports=t(\"../src/core\")},{\"../src/core\":695}],15:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/densitymapbox\")},{\"../src/traces/densitymapbox\":976}],16:[function(t,e,r){\"use strict\";e.exports=t(\"../src/transforms/filter\")},{\"../src/transforms/filter\":1298}],17:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/funnel\")},{\"../src/traces/funnel\":986}],18:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/funnelarea\")},{\"../src/traces/funnelarea\":995}],19:[function(t,e,r){\"use strict\";e.exports=t(\"../src/transforms/groupby\")},{\"../src/transforms/groupby\":1299}],20:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/heatmap\")},{\"../src/traces/heatmap\":1008}],21:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/heatmapgl\")},{\"../src/traces/heatmapgl\":1017}],22:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/histogram\")},{\"../src/traces/histogram\":1029}],23:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/histogram2d\")},{\"../src/traces/histogram2d\":1035}],24:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/histogram2dcontour\")},{\"../src/traces/histogram2dcontour\":1039}],25:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/image\")},{\"../src/traces/image\":1046}],26:[function(t,e,r){\"use strict\";var n=t(\"./core\");n.register([t(\"./bar\"),t(\"./box\"),t(\"./heatmap\"),t(\"./histogram\"),t(\"./histogram2d\"),t(\"./histogram2dcontour\"),t(\"./contour\"),t(\"./scatterternary\"),t(\"./violin\"),t(\"./funnel\"),t(\"./waterfall\"),t(\"./image\"),t(\"./pie\"),t(\"./sunburst\"),t(\"./treemap\"),t(\"./funnelarea\"),t(\"./scatter3d\"),t(\"./surface\"),t(\"./isosurface\"),t(\"./volume\"),t(\"./mesh3d\"),t(\"./cone\"),t(\"./streamtube\"),t(\"./scattergeo\"),t(\"./choropleth\"),t(\"./scattergl\"),t(\"./splom\"),t(\"./pointcloud\"),t(\"./heatmapgl\"),t(\"./parcoords\"),t(\"./parcats\"),t(\"./scattermapbox\"),t(\"./choroplethmapbox\"),t(\"./densitymapbox\"),t(\"./sankey\"),t(\"./indicator\"),t(\"./table\"),t(\"./carpet\"),t(\"./scattercarpet\"),t(\"./contourcarpet\"),t(\"./ohlc\"),t(\"./candlestick\"),t(\"./scatterpolar\"),t(\"./scatterpolargl\"),t(\"./barpolar\")]),n.register([t(\"./aggregate\"),t(\"./filter\"),t(\"./groupby\"),t(\"./sort\")]),n.register([t(\"./calendars\")]),e.exports=n},{\"./aggregate\":2,\"./bar\":3,\"./barpolar\":4,\"./box\":5,\"./calendars\":6,\"./candlestick\":7,\"./carpet\":8,\"./choropleth\":9,\"./choroplethmapbox\":10,\"./cone\":11,\"./contour\":12,\"./contourcarpet\":13,\"./core\":14,\"./densitymapbox\":15,\"./filter\":16,\"./funnel\":17,\"./funnelarea\":18,\"./groupby\":19,\"./heatmap\":20,\"./heatmapgl\":21,\"./histogram\":22,\"./histogram2d\":23,\"./histogram2dcontour\":24,\"./image\":25,\"./indicator\":27,\"./isosurface\":28,\"./mesh3d\":29,\"./ohlc\":30,\"./parcats\":31,\"./parcoords\":32,\"./pie\":33,\"./pointcloud\":34,\"./sankey\":35,\"./scatter3d\":36,\"./scattercarpet\":37,\"./scattergeo\":38,\"./scattergl\":39,\"./scattermapbox\":40,\"./scatterpolar\":41,\"./scatterpolargl\":42,\"./scatterternary\":43,\"./sort\":44,\"./splom\":45,\"./streamtube\":46,\"./sunburst\":47,\"./surface\":48,\"./table\":49,\"./treemap\":50,\"./violin\":51,\"./volume\":52,\"./waterfall\":53}],27:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/indicator\")},{\"../src/traces/indicator\":1054}],28:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/isosurface\")},{\"../src/traces/isosurface\":1060}],29:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/mesh3d\")},{\"../src/traces/mesh3d\":1065}],30:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/ohlc\")},{\"../src/traces/ohlc\":1070}],31:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/parcats\")},{\"../src/traces/parcats\":1079}],32:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/parcoords\")},{\"../src/traces/parcoords\":1089}],33:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/pie\")},{\"../src/traces/pie\":1100}],34:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/pointcloud\")},{\"../src/traces/pointcloud\":1109}],35:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/sankey\")},{\"../src/traces/sankey\":1115}],36:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/scatter3d\")},{\"../src/traces/scatter3d\":1152}],37:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/scattercarpet\")},{\"../src/traces/scattercarpet\":1159}],38:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/scattergeo\")},{\"../src/traces/scattergeo\":1167}],39:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/scattergl\")},{\"../src/traces/scattergl\":1180}],40:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/scattermapbox\")},{\"../src/traces/scattermapbox\":1190}],41:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/scatterpolar\")},{\"../src/traces/scatterpolar\":1198}],42:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/scatterpolargl\")},{\"../src/traces/scatterpolargl\":1205}],43:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/scatterternary\")},{\"../src/traces/scatterternary\":1213}],44:[function(t,e,r){\"use strict\";e.exports=t(\"../src/transforms/sort\")},{\"../src/transforms/sort\":1301}],45:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/splom\")},{\"../src/traces/splom\":1222}],46:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/streamtube\")},{\"../src/traces/streamtube\":1230}],47:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/sunburst\")},{\"../src/traces/sunburst\":1238}],48:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/surface\")},{\"../src/traces/surface\":1247}],49:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/table\")},{\"../src/traces/table\":1255}],50:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/treemap\")},{\"../src/traces/treemap\":1264}],51:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/violin\")},{\"../src/traces/violin\":1276}],52:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/volume\")},{\"../src/traces/volume\":1284}],53:[function(t,e,r){\"use strict\";e.exports=t(\"../src/traces/waterfall\")},{\"../src/traces/waterfall\":1292}],54:[function(t,e,r){\"use strict\";e.exports=function(t){var e=(t=t||{}).eye||[0,0,1],r=t.center||[0,0,0],s=t.up||[0,1,0],l=t.distanceLimits||[0,1/0],c=t.mode||\"turntable\",u=n(),h=a(),f=i();return u.setDistanceLimits(l[0],l[1]),u.lookAt(0,e,r,s),h.setDistanceLimits(l[0],l[1]),h.lookAt(0,e,r,s),f.setDistanceLimits(l[0],l[1]),f.lookAt(0,e,r,s),new o({turntable:u,orbit:h,matrix:f},c)};var n=t(\"turntable-camera-controller\"),a=t(\"orbit-camera-controller\"),i=t(\"matrix-camera-controller\");function o(t,e){this._controllerNames=Object.keys(t),this._controllerList=this._controllerNames.map(function(e){return t[e]}),this._mode=e,this._active=t[e],this._active||(this._mode=\"turntable\",this._active=t.turntable),this.modes=this._controllerNames,this.computedMatrix=this._active.computedMatrix,this.computedEye=this._active.computedEye,this.computedUp=this._active.computedUp,this.computedCenter=this._active.computedCenter,this.computedRadius=this._active.computedRadius}var s=o.prototype;[[\"flush\",1],[\"idle\",1],[\"lookAt\",4],[\"rotate\",4],[\"pan\",4],[\"translate\",4],[\"setMatrix\",2],[\"setDistanceLimits\",2],[\"setDistance\",2]].forEach(function(t){for(var e=t[0],r=[],n=0;n<t[1];++n)r.push(\"a\"+n);var a=\"var cc=this._controllerList;for(var i=0;i<cc.length;++i){cc[i].\"+t[0]+\"(\"+r.join()+\")}\";s[e]=Function.apply(null,r.concat(a))}),s.recalcMatrix=function(t){this._active.recalcMatrix(t)},s.getDistance=function(t){return this._active.getDistance(t)},s.getDistanceLimits=function(t){return this._active.getDistanceLimits(t)},s.lastT=function(){return this._active.lastT()},s.setMode=function(t){if(t!==this._mode){var e=this._controllerNames.indexOf(t);if(!(e<0)){var r=this._active,n=this._controllerList[e],a=Math.max(r.lastT(),n.lastT());r.recalcMatrix(a),n.setMatrix(a,r.computedMatrix),this._active=n,this._mode=t,this.computedMatrix=this._active.computedMatrix,this.computedEye=this._active.computedEye,this.computedUp=this._active.computedUp,this.computedCenter=this._active.computedCenter,this.computedRadius=this._active.computedRadius}}},s.getMode=function(){return this._mode}},{\"matrix-camera-controller\":435,\"orbit-camera-controller\":458,\"turntable-camera-controller\":541}],55:[function(t,e,r){var n,a;n=this,a=function(t,e,r,n,a){\"use strict\";function i(t){return t.target.depth}function o(t,e){return t.sourceLinks.length?t.depth:e-1}function s(t){return function(){return t}}a=a&&a.hasOwnProperty(\"default\")?a.default:a;var l=\"function\"==typeof Symbol&&\"symbol\"==typeof Symbol.iterator?function(t){return typeof t}:function(t){return t&&\"function\"==typeof Symbol&&t.constructor===Symbol&&t!==Symbol.prototype?\"symbol\":typeof t};function c(t,e){return h(t.source,e.source)||t.index-e.index}function u(t,e){return h(t.target,e.target)||t.index-e.index}function h(t,e){return t.partOfCycle===e.partOfCycle?t.y0-e.y0:\"top\"===t.circularLinkType||\"bottom\"===e.circularLinkType?-1:1}function f(t){return t.value}function p(t){return(t.y0+t.y1)/2}function d(t){return p(t.source)}function g(t){return p(t.target)}function v(t){return t.index}function m(t){return t.nodes}function y(t){return t.links}function x(t,e){var r=t.get(e);if(!r)throw new Error(\"missing: \"+e);return r}function b(t,e){return e(t)}var _=25,w=10,k=.3;function T(t,e){var r=0,n=0;t.links.forEach(function(a){a.circular&&(a.source.circularLinkType||a.target.circularLinkType?a.circularLinkType=a.source.circularLinkType?a.source.circularLinkType:a.target.circularLinkType:a.circularLinkType=r<n?\"top\":\"bottom\",\"top\"==a.circularLinkType?r+=1:n+=1,t.nodes.forEach(function(t){b(t,e)!=b(a.source,e)&&b(t,e)!=b(a.target,e)||(t.circularLinkType=a.circularLinkType)}))}),t.links.forEach(function(t){t.circular&&(t.source.circularLinkType==t.target.circularLinkType&&(t.circularLinkType=t.source.circularLinkType),Y(t,e)&&(t.circularLinkType=t.source.circularLinkType))})}function M(t){var e=Math.abs(t.y1-t.y0),r=Math.abs(t.target.x0-t.source.x1);return Math.atan(r/e)}function A(t,e){var r=0;t.sourceLinks.forEach(function(t){r=t.circular&&!Y(t,e)?r+1:r});var n=0;return t.targetLinks.forEach(function(t){n=t.circular&&!Y(t,e)?n+1:n}),r+n}function S(t){var e=t.source.sourceLinks,r=0;e.forEach(function(t){r=t.circular?r+1:r});var n=t.target.targetLinks,a=0;return n.forEach(function(t){a=t.circular?a+1:a}),!(r>1||a>1)}function E(t,e,r){return t.sort(C),t.forEach(function(n,a){var i,o,s=0;if(Y(n,r)&&S(n))n.circularPathData.verticalBuffer=s+n.width/2;else{for(var l=0;l<a;l++)if(i=t[a],o=t[l],!(i.source.column<o.target.column||i.target.column>o.source.column)){var c=t[l].circularPathData.verticalBuffer+t[l].width/2+e;s=c>s?c:s}n.circularPathData.verticalBuffer=s+n.width/2}}),t}function L(t,r,a,i){var o=e.min(t.links,function(t){return t.source.y0});t.links.forEach(function(t){t.circular&&(t.circularPathData={})}),E(t.links.filter(function(t){return\"top\"==t.circularLinkType}),r,i),E(t.links.filter(function(t){return\"bottom\"==t.circularLinkType}),r,i),t.links.forEach(function(e){if(e.circular){if(e.circularPathData.arcRadius=e.width+w,e.circularPathData.leftNodeBuffer=5,e.circularPathData.rightNodeBuffer=5,e.circularPathData.sourceWidth=e.source.x1-e.source.x0,e.circularPathData.sourceX=e.source.x0+e.circularPathData.sourceWidth,e.circularPathData.targetX=e.target.x0,e.circularPathData.sourceY=e.y0,e.circularPathData.targetY=e.y1,Y(e,i)&&S(e))e.circularPathData.leftSmallArcRadius=w+e.width/2,e.circularPathData.leftLargeArcRadius=w+e.width/2,e.circularPathData.rightSmallArcRadius=w+e.width/2,e.circularPathData.rightLargeArcRadius=w+e.width/2,\"bottom\"==e.circularLinkType?(e.circularPathData.verticalFullExtent=e.source.y1+_+e.circularPathData.verticalBuffer,e.circularPathData.verticalLeftInnerExtent=e.circularPathData.verticalFullExtent-e.circularPathData.leftLargeArcRadius,e.circularPathData.verticalRightInnerExtent=e.circularPathData.verticalFullExtent-e.circularPathData.rightLargeArcRadius):(e.circularPathData.verticalFullExtent=e.source.y0-_-e.circularPathData.verticalBuffer,e.circularPathData.verticalLeftInnerExtent=e.circularPathData.verticalFullExtent+e.circularPathData.leftLargeArcRadius,e.circularPathData.verticalRightInnerExtent=e.circularPathData.verticalFullExtent+e.circularPathData.rightLargeArcRadius);else{var s=e.source.column,l=e.circularLinkType,c=t.links.filter(function(t){return t.source.column==s&&t.circularLinkType==l});\"bottom\"==e.circularLinkType?c.sort(O):c.sort(P);var u=0;c.forEach(function(t,n){t.circularLinkID==e.circularLinkID&&(e.circularPathData.leftSmallArcRadius=w+e.width/2+u,e.circularPathData.leftLargeArcRadius=w+e.width/2+n*r+u),u+=t.width}),s=e.target.column,c=t.links.filter(function(t){return t.target.column==s&&t.circularLinkType==l}),\"bottom\"==e.circularLinkType?c.sort(I):c.sort(z),u=0,c.forEach(function(t,n){t.circularLinkID==e.circularLinkID&&(e.circularPathData.rightSmallArcRadius=w+e.width/2+u,e.circularPathData.rightLargeArcRadius=w+e.width/2+n*r+u),u+=t.width}),\"bottom\"==e.circularLinkType?(e.circularPathData.verticalFullExtent=Math.max(a,e.source.y1,e.target.y1)+_+e.circularPathData.verticalBuffer,e.circularPathData.verticalLeftInnerExtent=e.circularPathData.verticalFullExtent-e.circularPathData.leftLargeArcRadius,e.circularPathData.verticalRightInnerExtent=e.circularPathData.verticalFullExtent-e.circularPathData.rightLargeArcRadius):(e.circularPathData.verticalFullExtent=o-_-e.circularPathData.verticalBuffer,e.circularPathData.verticalLeftInnerExtent=e.circularPathData.verticalFullExtent+e.circularPathData.leftLargeArcRadius,e.circularPathData.verticalRightInnerExtent=e.circularPathData.verticalFullExtent+e.circularPathData.rightLargeArcRadius)}e.circularPathData.leftInnerExtent=e.circularPathData.sourceX+e.circularPathData.leftNodeBuffer,e.circularPathData.rightInnerExtent=e.circularPathData.targetX-e.circularPathData.rightNodeBuffer,e.circularPathData.leftFullExtent=e.circularPathData.sourceX+e.circularPathData.leftLargeArcRadius+e.circularPathData.leftNodeBuffer,e.circularPathData.rightFullExtent=e.circularPathData.targetX-e.circularPathData.rightLargeArcRadius-e.circularPathData.rightNodeBuffer}if(e.circular)e.path=function(t){var e=\"\";e=\"top\"==t.circularLinkType?\"M\"+t.circularPathData.sourceX+\" \"+t.circularPathData.sourceY+\" L\"+t.circularPathData.leftInnerExtent+\" \"+t.circularPathData.sourceY+\" A\"+t.circularPathData.leftLargeArcRadius+\" \"+t.circularPathData.leftSmallArcRadius+\" 0 0 0 \"+t.circularPathData.leftFullExtent+\" \"+(t.circularPathData.sourceY-t.circularPathData.leftSmallArcRadius)+\" L\"+t.circularPathData.leftFullExtent+\" \"+t.circularPathData.verticalLeftInnerExtent+\" A\"+t.circularPathData.leftLargeArcRadius+\" \"+t.circularPathData.leftLargeArcRadius+\" 0 0 0 \"+t.circularPathData.leftInnerExtent+\" \"+t.circularPathData.verticalFullExtent+\" L\"+t.circularPathData.rightInnerExtent+\" \"+t.circularPathData.verticalFullExtent+\" A\"+t.circularPathData.rightLargeArcRadius+\" \"+t.circularPathData.rightLargeArcRadius+\" 0 0 0 \"+t.circularPathData.rightFullExtent+\" \"+t.circularPathData.verticalRightInnerExtent+\" L\"+t.circularPathData.rightFullExtent+\" \"+(t.circularPathData.targetY-t.circularPathData.rightSmallArcRadius)+\" A\"+t.circularPathData.rightLargeArcRadius+\" \"+t.circularPathData.rightSmallArcRadius+\" 0 0 0 \"+t.circularPathData.rightInnerExtent+\" \"+t.circularPathData.targetY+\" L\"+t.circularPathData.targetX+\" \"+t.circularPathData.targetY:\"M\"+t.circularPathData.sourceX+\" \"+t.circularPathData.sourceY+\" L\"+t.circularPathData.leftInnerExtent+\" \"+t.circularPathData.sourceY+\" A\"+t.circularPathData.leftLargeArcRadius+\" \"+t.circularPathData.leftSmallArcRadius+\" 0 0 1 \"+t.circularPathData.leftFullExtent+\" \"+(t.circularPathData.sourceY+t.circularPathData.leftSmallArcRadius)+\" L\"+t.circularPathData.leftFullExtent+\" \"+t.circularPathData.verticalLeftInnerExtent+\" A\"+t.circularPathData.leftLargeArcRadius+\" \"+t.circularPathData.leftLargeArcRadius+\" 0 0 1 \"+t.circularPathData.leftInnerExtent+\" \"+t.circularPathData.verticalFullExtent+\" L\"+t.circularPathData.rightInnerExtent+\" \"+t.circularPathData.verticalFullExtent+\" A\"+t.circularPathData.rightLargeArcRadius+\" \"+t.circularPathData.rightLargeArcRadius+\" 0 0 1 \"+t.circularPathData.rightFullExtent+\" \"+t.circularPathData.verticalRightInnerExtent+\" L\"+t.circularPathData.rightFullExtent+\" \"+(t.circularPathData.targetY+t.circularPathData.rightSmallArcRadius)+\" A\"+t.circularPathData.rightLargeArcRadius+\" \"+t.circularPathData.rightSmallArcRadius+\" 0 0 1 \"+t.circularPathData.rightInnerExtent+\" \"+t.circularPathData.targetY+\" L\"+t.circularPathData.targetX+\" \"+t.circularPathData.targetY;return e}(e);else{var h=n.linkHorizontal().source(function(t){return[t.source.x0+(t.source.x1-t.source.x0),t.y0]}).target(function(t){return[t.target.x0,t.y1]});e.path=h(e)}})}function C(t,e){return D(t)==D(e)?\"bottom\"==t.circularLinkType?O(t,e):P(t,e):D(e)-D(t)}function P(t,e){return t.y0-e.y0}function O(t,e){return e.y0-t.y0}function z(t,e){return t.y1-e.y1}function I(t,e){return e.y1-t.y1}function D(t){return t.target.column-t.source.column}function R(t){return t.target.x0-t.source.x1}function F(t,e){var r=M(t),n=R(e)/Math.tan(r);return\"up\"==G(t)?t.y1+n:t.y1-n}function B(t,e){var r=M(t),n=R(e)/Math.tan(r);return\"up\"==G(t)?t.y1-n:t.y1+n}function N(t,e,r,n){t.links.forEach(function(a){if(!a.circular&&a.target.column-a.source.column>1){var i=a.source.column+1,o=a.target.column-1,s=1,l=o-i+1;for(s=1;i<=o;i++,s++)t.nodes.forEach(function(o){if(o.column==i){var c,u=s/(l+1),h=Math.pow(1-u,3),f=3*u*Math.pow(1-u,2),p=3*Math.pow(u,2)*(1-u),d=Math.pow(u,3),g=h*a.y0+f*a.y0+p*a.y1+d*a.y1,v=g-a.width/2,m=g+a.width/2;v>o.y0&&v<o.y1?(c=o.y1-v+10,c=\"bottom\"==o.circularLinkType?c:-c,o=V(o,c,e,r),t.nodes.forEach(function(t){b(t,n)!=b(o,n)&&t.column==o.column&&j(o,t)&&V(t,c,e,r)})):m>o.y0&&m<o.y1?(c=m-o.y0+10,o=V(o,c,e,r),t.nodes.forEach(function(t){b(t,n)!=b(o,n)&&t.column==o.column&&t.y0<o.y1&&t.y1>o.y1&&V(t,c,e,r)})):v<o.y0&&m>o.y1&&(c=m-o.y0+10,o=V(o,c,e,r),t.nodes.forEach(function(t){b(t,n)!=b(o,n)&&t.column==o.column&&t.y0<o.y1&&t.y1>o.y1&&V(t,c,e,r)}))}})}})}function j(t,e){return t.y0>e.y0&&t.y0<e.y1||(t.y1>e.y0&&t.y1<e.y1||t.y0<e.y0&&t.y1>e.y1)}function V(t,e,r,n){return t.y0+e>=r&&t.y1+e<=n&&(t.y0=t.y0+e,t.y1=t.y1+e,t.targetLinks.forEach(function(t){t.y1=t.y1+e}),t.sourceLinks.forEach(function(t){t.y0=t.y0+e})),t}function U(t,e,r,n){t.nodes.forEach(function(a){n&&a.y+(a.y1-a.y0)>e&&(a.y=a.y-(a.y+(a.y1-a.y0)-e));var i=t.links.filter(function(t){return b(t.source,r)==b(a,r)}),o=i.length;o>1&&i.sort(function(t,e){if(!t.circular&&!e.circular){if(t.target.column==e.target.column)return t.y1-e.y1;if(!H(t,e))return t.y1-e.y1;if(t.target.column>e.target.column){var r=B(e,t);return t.y1-r}if(e.target.column>t.target.column)return B(t,e)-e.y1}return t.circular&&!e.circular?\"top\"==t.circularLinkType?-1:1:e.circular&&!t.circular?\"top\"==e.circularLinkType?1:-1:t.circular&&e.circular?t.circularLinkType===e.circularLinkType&&\"top\"==t.circularLinkType?t.target.column===e.target.column?t.target.y1-e.target.y1:e.target.column-t.target.column:t.circularLinkType===e.circularLinkType&&\"bottom\"==t.circularLinkType?t.target.column===e.target.column?e.target.y1-t.target.y1:t.target.column-e.target.column:\"top\"==t.circularLinkType?-1:1:void 0});var s=a.y0;i.forEach(function(t){t.y0=s+t.width/2,s+=t.width}),i.forEach(function(t,e){if(\"bottom\"==t.circularLinkType){for(var r=e+1,n=0;r<o;r++)n+=i[r].width;t.y0=a.y1-n-t.width/2}})})}function q(t,e,r){t.nodes.forEach(function(e){var n=t.links.filter(function(t){return b(t.target,r)==b(e,r)}),a=n.length;a>1&&n.sort(function(t,e){if(!t.circular&&!e.circular){if(t.source.column==e.source.column)return t.y0-e.y0;if(!H(t,e))return t.y0-e.y0;if(e.source.column<t.source.column){var r=F(e,t);return t.y0-r}if(t.source.column<e.source.column)return F(t,e)-e.y0}return t.circular&&!e.circular?\"top\"==t.circularLinkType?-1:1:e.circular&&!t.circular?\"top\"==e.circularLinkType?1:-1:t.circular&&e.circular?t.circularLinkType===e.circularLinkType&&\"top\"==t.circularLinkType?t.source.column===e.source.column?t.source.y1-e.source.y1:t.source.column-e.source.column:t.circularLinkType===e.circularLinkType&&\"bottom\"==t.circularLinkType?t.source.column===e.source.column?t.source.y1-e.source.y1:e.source.column-t.source.column:\"top\"==t.circularLinkType?-1:1:void 0});var i=e.y0;n.forEach(function(t){t.y1=i+t.width/2,i+=t.width}),n.forEach(function(t,r){if(\"bottom\"==t.circularLinkType){for(var i=r+1,o=0;i<a;i++)o+=n[i].width;t.y1=e.y1-o-t.width/2}})})}function H(t,e){return G(t)==G(e)}function G(t){return t.y0-t.y1>0?\"up\":\"down\"}function Y(t,e){return b(t.source,e)==b(t.target,e)}t.sankeyCircular=function(){var t,n,i=0,b=0,M=1,S=1,E=24,C=v,P=o,O=m,z=y,I=32,D=2,R=null;function F(){var o={nodes:O.apply(null,arguments),links:z.apply(null,arguments)};!function(t){t.nodes.forEach(function(t,e){t.index=e,t.sourceLinks=[],t.targetLinks=[]});var e=r.map(t.nodes,C);t.links.forEach(function(t,r){t.index=r;var n=t.source,a=t.target;\"object\"!==(\"undefined\"==typeof n?\"undefined\":l(n))&&(n=t.source=x(e,n)),\"object\"!==(\"undefined\"==typeof a?\"undefined\":l(a))&&(a=t.target=x(e,a)),n.sourceLinks.push(t),a.targetLinks.push(t)})}(o),function(t,e,r){var n=0;if(null===r){for(var i=[],o=0;o<t.links.length;o++){var s=t.links[o],l=s.source.index,c=s.target.index;i[l]||(i[l]=[]),i[c]||(i[c]=[]),-1===i[l].indexOf(c)&&i[l].push(c)}var u=a(i);u.sort(function(t,e){return t.length-e.length});var h={};for(o=0;o<u.length;o++){var f=u[o],p=f.slice(-2);h[p[0]]||(h[p[0]]={}),h[p[0]][p[1]]=!0}t.links.forEach(function(t){var e=t.target.index,r=t.source.index;e===r||h[r]&&h[r][e]?(t.circular=!0,t.circularLinkID=n,n+=1):t.circular=!1})}else t.links.forEach(function(t){t.source[r]<t.target[r]?t.circular=!1:(t.circular=!0,t.circularLinkID=n,n+=1)})}(o,0,R),function(t){t.nodes.forEach(function(t){t.partOfCycle=!1,t.value=Math.max(e.sum(t.sourceLinks,f),e.sum(t.targetLinks,f)),t.sourceLinks.forEach(function(e){e.circular&&(t.partOfCycle=!0,t.circularLinkType=e.circularLinkType)}),t.targetLinks.forEach(function(e){e.circular&&(t.partOfCycle=!0,t.circularLinkType=e.circularLinkType)})})}(o),function(t){var e,r,n;for(e=t.nodes,r=[],n=0;e.length;++n,e=r,r=[])e.forEach(function(t){t.depth=n,t.sourceLinks.forEach(function(t){r.indexOf(t.target)<0&&!t.circular&&r.push(t.target)})});for(e=t.nodes,r=[],n=0;e.length;++n,e=r,r=[])e.forEach(function(t){t.height=n,t.targetLinks.forEach(function(t){r.indexOf(t.source)<0&&!t.circular&&r.push(t.source)})});t.nodes.forEach(function(t){t.column=Math.floor(P.call(null,t,n))})}(o),T(o,C),function(a,o,s){var l=r.nest().key(function(t){return t.column}).sortKeys(e.ascending).entries(a.nodes).map(function(t){return t.values});(function(r){if(n){var o=1/0;l.forEach(function(t){var e=S*n/(t.length+1);o=e<o?e:o}),t=o}var s=e.min(l,function(r){return(S-b-(r.length-1)*t)/e.sum(r,f)});s*=k,a.links.forEach(function(t){t.width=t.value*s});var c=function(t){var r=0,n=0,a=0,i=0,o=e.max(t.nodes,function(t){return t.column});return t.links.forEach(function(t){t.circular&&(\"top\"==t.circularLinkType?r+=t.width:n+=t.width,0==t.target.column&&(i+=t.width),t.source.column==o&&(a+=t.width))}),{top:r=r>0?r+_+w:r,bottom:n=n>0?n+_+w:n,left:i=i>0?i+_+w:i,right:a=a>0?a+_+w:a}}(a),u=function(t,r){var n=e.max(t.nodes,function(t){return t.column}),a=M-i,o=S-b,s=a+r.right+r.left,l=o+r.top+r.bottom,c=a/s,u=o/l;return i=i*c+r.left,M=0==r.right?M:M*c,b=b*u+r.top,S*=u,t.nodes.forEach(function(t){t.x0=i+t.column*((M-i-E)/n),t.x1=t.x0+E}),u}(a,c);s*=u,a.links.forEach(function(t){t.width=t.value*s}),l.forEach(function(t){var e=t.length;t.forEach(function(t,n){t.depth==l.length-1&&1==e?(t.y0=S/2-t.value*s,t.y1=t.y0+t.value*s):0==t.depth&&1==e?(t.y0=S/2-t.value*s,t.y1=t.y0+t.value*s):t.partOfCycle?0==A(t,r)?(t.y0=S/2+n,t.y1=t.y0+t.value*s):\"top\"==t.circularLinkType?(t.y0=b+n,t.y1=t.y0+t.value*s):(t.y0=S-t.value*s-n,t.y1=t.y0+t.value*s):0==c.top||0==c.bottom?(t.y0=(S-b)/e*n,t.y1=t.y0+t.value*s):(t.y0=(S-b)/2-e/2+n,t.y1=t.y0+t.value*s)})})})(s),m();for(var c=1,u=o;u>0;--u)v(c*=.99,s),m();function v(t,r){var n=l.length;l.forEach(function(a){var i=a.length,o=a[0].depth;a.forEach(function(a){var s;if(a.sourceLinks.length||a.targetLinks.length)if(a.partOfCycle&&A(a,r)>0);else if(0==o&&1==i)s=a.y1-a.y0,a.y0=S/2-s/2,a.y1=S/2+s/2;else if(o==n-1&&1==i)s=a.y1-a.y0,a.y0=S/2-s/2,a.y1=S/2+s/2;else{var l=e.mean(a.sourceLinks,g),c=e.mean(a.targetLinks,d),u=((l&&c?(l+c)/2:l||c)-p(a))*t;a.y0+=u,a.y1+=u}})})}function m(){l.forEach(function(e){var r,n,a,i=b,o=e.length;for(e.sort(h),a=0;a<o;++a)r=e[a],(n=i-r.y0)>0&&(r.y0+=n,r.y1+=n),i=r.y1+t;if((n=i-t-S)>0)for(i=r.y0-=n,r.y1-=n,a=o-2;a>=0;--a)r=e[a],(n=r.y1+t-i)>0&&(r.y0-=n,r.y1-=n),i=r.y0})}}(o,I,C),B(o);for(var s=0;s<4;s++)U(o,S,C),q(o,0,C),N(o,b,S,C),U(o,S,C),q(o,0,C);return function(t,r,n){var a=t.nodes,i=t.links,o=!1,s=!1;if(i.forEach(function(t){\"top\"==t.circularLinkType?o=!0:\"bottom\"==t.circularLinkType&&(s=!0)}),0==o||0==s){var l=e.min(a,function(t){return t.y0}),c=e.max(a,function(t){return t.y1}),u=c-l,h=n-r,f=h/u;a.forEach(function(t){var e=(t.y1-t.y0)*f;t.y0=(t.y0-l)*f,t.y1=t.y0+e}),i.forEach(function(t){t.y0=(t.y0-l)*f,t.y1=(t.y1-l)*f,t.width=t.width*f})}}(o,b,S),L(o,D,S,C),o}function B(t){t.nodes.forEach(function(t){t.sourceLinks.sort(u),t.targetLinks.sort(c)}),t.nodes.forEach(function(t){var e=t.y0,r=e,n=t.y1,a=n;t.sourceLinks.forEach(function(t){t.circular?(t.y0=n-t.width/2,n-=t.width):(t.y0=e+t.width/2,e+=t.width)}),t.targetLinks.forEach(function(t){t.circular?(t.y1=a-t.width/2,a-=t.width):(t.y1=r+t.width/2,r+=t.width)})})}return F.nodeId=function(t){return arguments.length?(C=\"function\"==typeof t?t:s(t),F):C},F.nodeAlign=function(t){return arguments.length?(P=\"function\"==typeof t?t:s(t),F):P},F.nodeWidth=function(t){return arguments.length?(E=+t,F):E},F.nodePadding=function(e){return arguments.length?(t=+e,F):t},F.nodes=function(t){return arguments.length?(O=\"function\"==typeof t?t:s(t),F):O},F.links=function(t){return arguments.length?(z=\"function\"==typeof t?t:s(t),F):z},F.size=function(t){return arguments.length?(i=b=0,M=+t[0],S=+t[1],F):[M-i,S-b]},F.extent=function(t){return arguments.length?(i=+t[0][0],M=+t[1][0],b=+t[0][1],S=+t[1][1],F):[[i,b],[M,S]]},F.iterations=function(t){return arguments.length?(I=+t,F):I},F.circularLinkGap=function(t){return arguments.length?(D=+t,F):D},F.nodePaddingRatio=function(t){return arguments.length?(n=+t,F):n},F.sortNodes=function(t){return arguments.length?(R=t,F):R},F.update=function(t){return T(t,C),B(t),t.links.forEach(function(t){t.circular&&(t.circularLinkType=t.y0+t.y1<S?\"top\":\"bottom\",t.source.circularLinkType=t.circularLinkType,t.target.circularLinkType=t.circularLinkType)}),U(t,S,C,!1),q(t,0,C),L(t,D,S,C),t},F},t.sankeyCenter=function(t){return t.targetLinks.length?t.depth:t.sourceLinks.length?e.min(t.sourceLinks,i)-1:0},t.sankeyLeft=function(t){return t.depth},t.sankeyRight=function(t,e){return e-1-t.height},t.sankeyJustify=o,Object.defineProperty(t,\"__esModule\",{value:!0})},\"object\"==typeof r&&\"undefined\"!=typeof e?a(r,t(\"d3-array\"),t(\"d3-collection\"),t(\"d3-shape\"),t(\"elementary-circuits-directed-graph\")):a(n.d3=n.d3||{},n.d3,n.d3,n.d3,null)},{\"d3-array\":154,\"d3-collection\":155,\"d3-shape\":163,\"elementary-circuits-directed-graph\":175}],56:[function(t,e,r){var n,a;n=this,a=function(t,e,r,n){\"use strict\";function a(t){return t.target.depth}function i(t,e){return t.sourceLinks.length?t.depth:e-1}function o(t){return function(){return t}}function s(t,e){return c(t.source,e.source)||t.index-e.index}function l(t,e){return c(t.target,e.target)||t.index-e.index}function c(t,e){return t.y0-e.y0}function u(t){return t.value}function h(t){return(t.y0+t.y1)/2}function f(t){return h(t.source)*t.value}function p(t){return h(t.target)*t.value}function d(t){return t.index}function g(t){return t.nodes}function v(t){return t.links}function m(t,e){var r=t.get(e);if(!r)throw new Error(\"missing: \"+e);return r}function y(t){return[t.source.x1,t.y0]}function x(t){return[t.target.x0,t.y1]}t.sankey=function(){var t=0,n=0,a=1,y=1,x=24,b=8,_=d,w=i,k=g,T=v,M=32,A=2/3;function S(){var i={nodes:k.apply(null,arguments),links:T.apply(null,arguments)};return function(t){t.nodes.forEach(function(t,e){t.index=e,t.sourceLinks=[],t.targetLinks=[]});var e=r.map(t.nodes,_);t.links.forEach(function(t,r){t.index=r;var n=t.source,a=t.target;\"object\"!=typeof n&&(n=t.source=m(e,n)),\"object\"!=typeof a&&(a=t.target=m(e,a)),n.sourceLinks.push(t),a.targetLinks.push(t)})}(i),function(t){t.nodes.forEach(function(t){t.value=Math.max(e.sum(t.sourceLinks,u),e.sum(t.targetLinks,u))})}(i),function(e){var r,n,i;for(r=e.nodes,n=[],i=0;r.length;++i,r=n,n=[])r.forEach(function(t){t.depth=i,t.sourceLinks.forEach(function(t){n.indexOf(t.target)<0&&n.push(t.target)})});for(r=e.nodes,n=[],i=0;r.length;++i,r=n,n=[])r.forEach(function(t){t.height=i,t.targetLinks.forEach(function(t){n.indexOf(t.source)<0&&n.push(t.source)})});var o=(a-t-x)/(i-1);e.nodes.forEach(function(e){e.x1=(e.x0=t+Math.max(0,Math.min(i-1,Math.floor(w.call(null,e,i))))*o)+x})}(i),function(t){var a=r.nest().key(function(t){return t.x0}).sortKeys(e.ascending).entries(t.nodes).map(function(t){return t.values});(function(){var r=e.max(a,function(t){return t.length}),i=A*(y-n)/(r-1);b>i&&(b=i);var o=e.min(a,function(t){return(y-n-(t.length-1)*b)/e.sum(t,u)});a.forEach(function(t){t.forEach(function(t,e){t.y1=(t.y0=e)+t.value*o})}),t.links.forEach(function(t){t.width=t.value*o})})(),d();for(var i=1,o=M;o>0;--o)l(i*=.99),d(),s(i),d();function s(t){a.forEach(function(r){r.forEach(function(r){if(r.targetLinks.length){var n=(e.sum(r.targetLinks,f)/e.sum(r.targetLinks,u)-h(r))*t;r.y0+=n,r.y1+=n}})})}function l(t){a.slice().reverse().forEach(function(r){r.forEach(function(r){if(r.sourceLinks.length){var n=(e.sum(r.sourceLinks,p)/e.sum(r.sourceLinks,u)-h(r))*t;r.y0+=n,r.y1+=n}})})}function d(){a.forEach(function(t){var e,r,a,i=n,o=t.length;for(t.sort(c),a=0;a<o;++a)e=t[a],(r=i-e.y0)>0&&(e.y0+=r,e.y1+=r),i=e.y1+b;if((r=i-b-y)>0)for(i=e.y0-=r,e.y1-=r,a=o-2;a>=0;--a)e=t[a],(r=e.y1+b-i)>0&&(e.y0-=r,e.y1-=r),i=e.y0})}}(i),E(i),i}function E(t){t.nodes.forEach(function(t){t.sourceLinks.sort(l),t.targetLinks.sort(s)}),t.nodes.forEach(function(t){var e=t.y0,r=e;t.sourceLinks.forEach(function(t){t.y0=e+t.width/2,e+=t.width}),t.targetLinks.forEach(function(t){t.y1=r+t.width/2,r+=t.width})})}return S.update=function(t){return E(t),t},S.nodeId=function(t){return arguments.length?(_=\"function\"==typeof t?t:o(t),S):_},S.nodeAlign=function(t){return arguments.length?(w=\"function\"==typeof t?t:o(t),S):w},S.nodeWidth=function(t){return arguments.length?(x=+t,S):x},S.nodePadding=function(t){return arguments.length?(b=+t,S):b},S.nodes=function(t){return arguments.length?(k=\"function\"==typeof t?t:o(t),S):k},S.links=function(t){return arguments.length?(T=\"function\"==typeof t?t:o(t),S):T},S.size=function(e){return arguments.length?(t=n=0,a=+e[0],y=+e[1],S):[a-t,y-n]},S.extent=function(e){return arguments.length?(t=+e[0][0],a=+e[1][0],n=+e[0][1],y=+e[1][1],S):[[t,n],[a,y]]},S.iterations=function(t){return arguments.length?(M=+t,S):M},S},t.sankeyCenter=function(t){return t.targetLinks.length?t.depth:t.sourceLinks.length?e.min(t.sourceLinks,a)-1:0},t.sankeyLeft=function(t){return t.depth},t.sankeyRight=function(t,e){return e-1-t.height},t.sankeyJustify=i,t.sankeyLinkHorizontal=function(){return n.linkHorizontal().source(y).target(x)},Object.defineProperty(t,\"__esModule\",{value:!0})},\"object\"==typeof r&&\"undefined\"!=typeof e?a(r,t(\"d3-array\"),t(\"d3-collection\"),t(\"d3-shape\")):a(n.d3=n.d3||{},n.d3,n.d3,n.d3)},{\"d3-array\":154,\"d3-collection\":155,\"d3-shape\":163}],57:[function(t,e,r){\"use strict\";Object.defineProperty(r,\"__esModule\",{value:!0});var n=t(\"@turf/meta\"),a=6378137;function i(t){var e=0;if(t&&t.length>0){e+=Math.abs(o(t[0]));for(var r=1;r<t.length;r++)e-=Math.abs(o(t[r]))}return e}function o(t){var e,r,n,i,o,l,c=0,u=t.length;if(u>2){for(l=0;l<u;l++)l===u-2?(n=u-2,i=u-1,o=0):l===u-1?(n=u-1,i=0,o=1):(n=l,i=l+1,o=l+2),e=t[n],r=t[i],c+=(s(t[o][0])-s(e[0]))*Math.sin(s(r[1]));c=c*a*a/2}return c}function s(t){return t*Math.PI/180}r.default=function(t){return n.geomReduce(t,function(t,e){return t+function(t){var e,r=0;switch(t.type){case\"Polygon\":return i(t.coordinates);case\"MultiPolygon\":for(e=0;e<t.coordinates.length;e++)r+=i(t.coordinates[e]);return r;case\"Point\":case\"MultiPoint\":case\"LineString\":case\"MultiLineString\":return 0}return 0}(e)},0)}},{\"@turf/meta\":61}],58:[function(t,e,r){\"use strict\";Object.defineProperty(r,\"__esModule\",{value:!0});var n=t(\"@turf/meta\");r.default=function(t){var e=[1/0,1/0,-1/0,-1/0];return n.coordEach(t,function(t){e[0]>t[0]&&(e[0]=t[0]),e[1]>t[1]&&(e[1]=t[1]),e[2]<t[0]&&(e[2]=t[0]),e[3]<t[1]&&(e[3]=t[1])}),e}},{\"@turf/meta\":61}],59:[function(t,e,r){\"use strict\";Object.defineProperty(r,\"__esModule\",{value:!0});var n=t(\"@turf/meta\"),a=t(\"@turf/helpers\");r.default=function(t,e){void 0===e&&(e={});var r=0,i=0,o=0;return n.coordEach(t,function(t){r+=t[0],i+=t[1],o++}),a.point([r/o,i/o],e.properties)}},{\"@turf/helpers\":60,\"@turf/meta\":61}],60:[function(t,e,r){\"use strict\";function n(t,e,r){void 0===r&&(r={});var n={type:\"Feature\"};return(0===r.id||r.id)&&(n.id=r.id),r.bbox&&(n.bbox=r.bbox),n.properties=e||{},n.geometry=t,n}function a(t,e,r){return void 0===r&&(r={}),n({type:\"Point\",coordinates:t},e,r)}function i(t,e,r){void 0===r&&(r={});for(var a=0,i=t;a<i.length;a++){var o=i[a];if(o.length<4)throw new Error(\"Each LinearRing of a Polygon must have 4 or more Positions.\");for(var s=0;s<o[o.length-1].length;s++)if(o[o.length-1][s]!==o[0][s])throw new Error(\"First and last Position are not equivalent.\")}return n({type:\"Polygon\",coordinates:t},e,r)}function o(t,e,r){if(void 0===r&&(r={}),t.length<2)throw new Error(\"coordinates must be an array of two or more positions\");return n({type:\"LineString\",coordinates:t},e,r)}function s(t,e){void 0===e&&(e={});var r={type:\"FeatureCollection\"};return e.id&&(r.id=e.id),e.bbox&&(r.bbox=e.bbox),r.features=t,r}function l(t,e,r){return void 0===r&&(r={}),n({type:\"MultiLineString\",coordinates:t},e,r)}function c(t,e,r){return void 0===r&&(r={}),n({type:\"MultiPoint\",coordinates:t},e,r)}function u(t,e,r){return void 0===r&&(r={}),n({type:\"MultiPolygon\",coordinates:t},e,r)}function h(t,e){void 0===e&&(e=\"kilometers\");var n=r.factors[e];if(!n)throw new Error(e+\" units is invalid\");return t*n}function f(t,e){void 0===e&&(e=\"kilometers\");var n=r.factors[e];if(!n)throw new Error(e+\" units is invalid\");return t/n}function p(t){return 180*(t%(2*Math.PI))/Math.PI}function d(t){return!isNaN(t)&&null!==t&&!Array.isArray(t)&&!/^\\s*$/.test(t)}Object.defineProperty(r,\"__esModule\",{value:!0}),r.earthRadius=6371008.8,r.factors={centimeters:100*r.earthRadius,centimetres:100*r.earthRadius,degrees:r.earthRadius/111325,feet:3.28084*r.earthRadius,inches:39.37*r.earthRadius,kilometers:r.earthRadius/1e3,kilometres:r.earthRadius/1e3,meters:r.earthRadius,metres:r.earthRadius,miles:r.earthRadius/1609.344,millimeters:1e3*r.earthRadius,millimetres:1e3*r.earthRadius,nauticalmiles:r.earthRadius/1852,radians:1,yards:r.earthRadius/1.0936},r.unitsFactors={centimeters:100,centimetres:100,degrees:1/111325,feet:3.28084,inches:39.37,kilometers:.001,kilometres:.001,meters:1,metres:1,miles:1/1609.344,millimeters:1e3,millimetres:1e3,nauticalmiles:1/1852,radians:1/r.earthRadius,yards:1/1.0936},r.areaFactors={acres:247105e-9,centimeters:1e4,centimetres:1e4,feet:10.763910417,inches:1550.003100006,kilometers:1e-6,kilometres:1e-6,meters:1,metres:1,miles:3.86e-7,millimeters:1e6,millimetres:1e6,yards:1.195990046},r.feature=n,r.geometry=function(t,e,r){switch(void 0===r&&(r={}),t){case\"Point\":return a(e).geometry;case\"LineString\":return o(e).geometry;case\"Polygon\":return i(e).geometry;case\"MultiPoint\":return c(e).geometry;case\"MultiLineString\":return l(e).geometry;case\"MultiPolygon\":return u(e).geometry;default:throw new Error(t+\" is invalid\")}},r.point=a,r.points=function(t,e,r){return void 0===r&&(r={}),s(t.map(function(t){return a(t,e)}),r)},r.polygon=i,r.polygons=function(t,e,r){return void 0===r&&(r={}),s(t.map(function(t){return i(t,e)}),r)},r.lineString=o,r.lineStrings=function(t,e,r){return void 0===r&&(r={}),s(t.map(function(t){return o(t,e)}),r)},r.featureCollection=s,r.multiLineString=l,r.multiPoint=c,r.multiPolygon=u,r.geometryCollection=function(t,e,r){return void 0===r&&(r={}),n({type:\"GeometryCollection\",geometries:t},e,r)},r.round=function(t,e){if(void 0===e&&(e=0),e&&!(e>=0))throw new Error(\"precision must be a positive number\");var r=Math.pow(10,e||0);return Math.round(t*r)/r},r.radiansToLength=h,r.lengthToRadians=f,r.lengthToDegrees=function(t,e){return p(f(t,e))},r.bearingToAzimuth=function(t){var e=t%360;return e<0&&(e+=360),e},r.radiansToDegrees=p,r.degreesToRadians=function(t){return t%360*Math.PI/180},r.convertLength=function(t,e,r){if(void 0===e&&(e=\"kilometers\"),void 0===r&&(r=\"kilometers\"),!(t>=0))throw new Error(\"length must be a positive number\");return h(f(t,e),r)},r.convertArea=function(t,e,n){if(void 0===e&&(e=\"meters\"),void 0===n&&(n=\"kilometers\"),!(t>=0))throw new Error(\"area must be a positive number\");var a=r.areaFactors[e];if(!a)throw new Error(\"invalid original units\");var i=r.areaFactors[n];if(!i)throw new Error(\"invalid final units\");return t/a*i},r.isNumber=d,r.isObject=function(t){return!!t&&t.constructor===Object},r.validateBBox=function(t){if(!t)throw new Error(\"bbox is required\");if(!Array.isArray(t))throw new Error(\"bbox must be an Array\");if(4!==t.length&&6!==t.length)throw new Error(\"bbox must be an Array of 4 or 6 numbers\");t.forEach(function(t){if(!d(t))throw new Error(\"bbox must only contain numbers\")})},r.validateId=function(t){if(!t)throw new Error(\"id is required\");if(-1===[\"string\",\"number\"].indexOf(typeof t))throw new Error(\"id must be a number or a string\")},r.radians2degrees=function(){throw new Error(\"method has been renamed to `radiansToDegrees`\")},r.degrees2radians=function(){throw new Error(\"method has been renamed to `degreesToRadians`\")},r.distanceToDegrees=function(){throw new Error(\"method has been renamed to `lengthToDegrees`\")},r.distanceToRadians=function(){throw new Error(\"method has been renamed to `lengthToRadians`\")},r.radiansToDistance=function(){throw new Error(\"method has been renamed to `radiansToLength`\")},r.bearingToAngle=function(){throw new Error(\"method has been renamed to `bearingToAzimuth`\")},r.convertDistance=function(){throw new Error(\"method has been renamed to `convertLength`\")}},{}],61:[function(t,e,r){\"use strict\";Object.defineProperty(r,\"__esModule\",{value:!0});var n=t(\"@turf/helpers\");function a(t,e,r){if(null!==t)for(var n,i,o,s,l,c,u,h,f=0,p=0,d=t.type,g=\"FeatureCollection\"===d,v=\"Feature\"===d,m=g?t.features.length:1,y=0;y<m;y++){l=(h=!!(u=g?t.features[y].geometry:v?t.geometry:t)&&\"GeometryCollection\"===u.type)?u.geometries.length:1;for(var x=0;x<l;x++){var b=0,_=0;if(null!==(s=h?u.geometries[x]:u)){c=s.coordinates;var w=s.type;switch(f=!r||\"Polygon\"!==w&&\"MultiPolygon\"!==w?0:1,w){case null:break;case\"Point\":if(!1===e(c,p,y,b,_))return!1;p++,b++;break;case\"LineString\":case\"MultiPoint\":for(n=0;n<c.length;n++){if(!1===e(c[n],p,y,b,_))return!1;p++,\"MultiPoint\"===w&&b++}\"LineString\"===w&&b++;break;case\"Polygon\":case\"MultiLineString\":for(n=0;n<c.length;n++){for(i=0;i<c[n].length-f;i++){if(!1===e(c[n][i],p,y,b,_))return!1;p++}\"MultiLineString\"===w&&b++,\"Polygon\"===w&&_++}\"Polygon\"===w&&b++;break;case\"MultiPolygon\":for(n=0;n<c.length;n++){for(_=0,i=0;i<c[n].length;i++){for(o=0;o<c[n][i].length-f;o++){if(!1===e(c[n][i][o],p,y,b,_))return!1;p++}_++}b++}break;case\"GeometryCollection\":for(n=0;n<s.geometries.length;n++)if(!1===a(s.geometries[n],e,r))return!1;break;default:throw new Error(\"Unknown Geometry Type\")}}}}}function i(t,e){var r;switch(t.type){case\"FeatureCollection\":for(r=0;r<t.features.length&&!1!==e(t.features[r].properties,r);r++);break;case\"Feature\":e(t.properties,0)}}function o(t,e){if(\"Feature\"===t.type)e(t,0);else if(\"FeatureCollection\"===t.type)for(var r=0;r<t.features.length&&!1!==e(t.features[r],r);r++);}function s(t,e){var r,n,a,i,o,s,l,c,u,h,f=0,p=\"FeatureCollection\"===t.type,d=\"Feature\"===t.type,g=p?t.features.length:1;for(r=0;r<g;r++){for(s=p?t.features[r].geometry:d?t.geometry:t,c=p?t.features[r].properties:d?t.properties:{},u=p?t.features[r].bbox:d?t.bbox:void 0,h=p?t.features[r].id:d?t.id:void 0,o=(l=!!s&&\"GeometryCollection\"===s.type)?s.geometries.length:1,a=0;a<o;a++)if(null!==(i=l?s.geometries[a]:s))switch(i.type){case\"Point\":case\"LineString\":case\"MultiPoint\":case\"Polygon\":case\"MultiLineString\":case\"MultiPolygon\":if(!1===e(i,f,c,u,h))return!1;break;case\"GeometryCollection\":for(n=0;n<i.geometries.length;n++)if(!1===e(i.geometries[n],f,c,u,h))return!1;break;default:throw new Error(\"Unknown Geometry Type\")}else if(!1===e(null,f,c,u,h))return!1;f++}}function l(t,e){s(t,function(t,r,a,i,o){var s,l=null===t?null:t.type;switch(l){case null:case\"Point\":case\"LineString\":case\"Polygon\":return!1!==e(n.feature(t,a,{bbox:i,id:o}),r,0)&&void 0}switch(l){case\"MultiPoint\":s=\"Point\";break;case\"MultiLineString\":s=\"LineString\";break;case\"MultiPolygon\":s=\"Polygon\"}for(var c=0;c<t.coordinates.length;c++){var u={type:s,coordinates:t.coordinates[c]};if(!1===e(n.feature(u,a),r,c))return!1}})}function c(t,e){l(t,function(t,r,i){var o=0;if(t.geometry){var s=t.geometry.type;if(\"Point\"!==s&&\"MultiPoint\"!==s){var l,c=0,u=0,h=0;return!1!==a(t,function(a,s,f,p,d){if(void 0===l||r>c||p>u||d>h)return l=a,c=r,u=p,h=d,void(o=0);var g=n.lineString([l,a],t.properties);if(!1===e(g,r,i,d,o))return!1;o++,l=a})&&void 0}}})}function u(t,e){if(!t)throw new Error(\"geojson is required\");l(t,function(t,r,a){if(null!==t.geometry){var i=t.geometry.type,o=t.geometry.coordinates;switch(i){case\"LineString\":if(!1===e(t,r,a,0,0))return!1;break;case\"Polygon\":for(var s=0;s<o.length;s++)if(!1===e(n.lineString(o[s],t.properties),r,a,s))return!1}}})}r.coordEach=a,r.coordReduce=function(t,e,r,n){var i=r;return a(t,function(t,n,a,o,s){i=0===n&&void 0===r?t:e(i,t,n,a,o,s)},n),i},r.propEach=i,r.propReduce=function(t,e,r){var n=r;return i(t,function(t,a){n=0===a&&void 0===r?t:e(n,t,a)}),n},r.featureEach=o,r.featureReduce=function(t,e,r){var n=r;return o(t,function(t,a){n=0===a&&void 0===r?t:e(n,t,a)}),n},r.coordAll=function(t){var e=[];return a(t,function(t){e.push(t)}),e},r.geomEach=s,r.geomReduce=function(t,e,r){var n=r;return s(t,function(t,a,i,o,s){n=0===a&&void 0===r?t:e(n,t,a,i,o,s)}),n},r.flattenEach=l,r.flattenReduce=function(t,e,r){var n=r;return l(t,function(t,a,i){n=0===a&&0===i&&void 0===r?t:e(n,t,a,i)}),n},r.segmentEach=c,r.segmentReduce=function(t,e,r){var n=r,a=!1;return c(t,function(t,i,o,s,l){n=!1===a&&void 0===r?t:e(n,t,i,o,s,l),a=!0}),n},r.lineEach=u,r.lineReduce=function(t,e,r){var n=r;return u(t,function(t,a,i,o){n=0===a&&void 0===r?t:e(n,t,a,i,o)}),n},r.findSegment=function(t,e){if(e=e||{},!n.isObject(e))throw new Error(\"options is invalid\");var r,a=e.featureIndex||0,i=e.multiFeatureIndex||0,o=e.geometryIndex||0,s=e.segmentIndex||0,l=e.properties;switch(t.type){case\"FeatureCollection\":a<0&&(a=t.features.length+a),l=l||t.features[a].properties,r=t.features[a].geometry;break;case\"Feature\":l=l||t.properties,r=t.geometry;break;case\"Point\":case\"MultiPoint\":return null;case\"LineString\":case\"Polygon\":case\"MultiLineString\":case\"MultiPolygon\":r=t;break;default:throw new Error(\"geojson is invalid\")}if(null===r)return null;var c=r.coordinates;switch(r.type){case\"Point\":case\"MultiPoint\":return null;case\"LineString\":return s<0&&(s=c.length+s-1),n.lineString([c[s],c[s+1]],l,e);case\"Polygon\":return o<0&&(o=c.length+o),s<0&&(s=c[o].length+s-1),n.lineString([c[o][s],c[o][s+1]],l,e);case\"MultiLineString\":return i<0&&(i=c.length+i),s<0&&(s=c[i].length+s-1),n.lineString([c[i][s],c[i][s+1]],l,e);case\"MultiPolygon\":return i<0&&(i=c.length+i),o<0&&(o=c[i].length+o),s<0&&(s=c[i][o].length-s-1),n.lineString([c[i][o][s],c[i][o][s+1]],l,e)}throw new Error(\"geojson is invalid\")},r.findPoint=function(t,e){if(e=e||{},!n.isObject(e))throw new Error(\"options is invalid\");var r,a=e.featureIndex||0,i=e.multiFeatureIndex||0,o=e.geometryIndex||0,s=e.coordIndex||0,l=e.properties;switch(t.type){case\"FeatureCollection\":a<0&&(a=t.features.length+a),l=l||t.features[a].properties,r=t.features[a].geometry;break;case\"Feature\":l=l||t.properties,r=t.geometry;break;case\"Point\":case\"MultiPoint\":return null;case\"LineString\":case\"Polygon\":case\"MultiLineString\":case\"MultiPolygon\":r=t;break;default:throw new Error(\"geojson is invalid\")}if(null===r)return null;var c=r.coordinates;switch(r.type){case\"Point\":return n.point(c,l,e);case\"MultiPoint\":return i<0&&(i=c.length+i),n.point(c[i],l,e);case\"LineString\":return s<0&&(s=c.length+s),n.point(c[s],l,e);case\"Polygon\":return o<0&&(o=c.length+o),s<0&&(s=c[o].length+s),n.point(c[o][s],l,e);case\"MultiLineString\":return i<0&&(i=c.length+i),s<0&&(s=c[i].length+s),n.point(c[i][s],l,e);case\"MultiPolygon\":return i<0&&(i=c.length+i),o<0&&(o=c[i].length+o),s<0&&(s=c[i][o].length-s),n.point(c[i][o][s],l,e)}throw new Error(\"geojson is invalid\")}},{\"@turf/helpers\":60}],62:[function(t,e,r){\"use strict\";var n=\"undefined\"==typeof WeakMap?t(\"weak-map\"):WeakMap,a=t(\"gl-buffer\"),i=t(\"gl-vao\"),o=new n;e.exports=function(t){var e=o.get(t),r=e&&(e._triangleBuffer.handle||e._triangleBuffer.buffer);if(!r||!t.isBuffer(r)){var n=a(t,new Float32Array([-1,-1,-1,4,4,-1]));(e=i(t,[{buffer:n,type:t.FLOAT,size:2}]))._triangleBuffer=n,o.set(t,e)}e.bind(),t.drawArrays(t.TRIANGLES,0,3),e.unbind()}},{\"gl-buffer\":244,\"gl-vao\":329,\"weak-map\":551}],63:[function(t,e,r){e.exports=function(t){var e=0,r=0,n=0,a=0;return t.map(function(t){var i=(t=t.slice())[0],o=i.toUpperCase();if(i!=o)switch(t[0]=o,i){case\"a\":t[6]+=n,t[7]+=a;break;case\"v\":t[1]+=a;break;case\"h\":t[1]+=n;break;default:for(var s=1;s<t.length;)t[s++]+=n,t[s++]+=a}switch(o){case\"Z\":n=e,a=r;break;case\"H\":n=t[1];break;case\"V\":a=t[1];break;case\"M\":n=e=t[1],a=r=t[2];break;default:n=t[t.length-2],a=t[t.length-1]}return t})}},{}],64:[function(t,e,r){var n=t(\"pad-left\");e.exports=function(t,e,r){e=\"number\"==typeof e?e:1,r=r||\": \";var a=t.split(/\\r?\\n/),i=String(a.length+e-1).length;return a.map(function(t,a){var o=a+e,s=String(o).length,l=n(o,i-s);return l+r+t}).join(\"\\n\")}},{\"pad-left\":459}],65:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.length;if(0===e)return[];if(1===e)return[0];for(var r=t[0].length,n=[t[0]],i=[0],o=1;o<e;++o)if(n.push(t[o]),a(n,r)){if(i.push(o),i.length===r+1)return i}else n.pop();return i};var n=t(\"robust-orientation\");function a(t,e){for(var r=new Array(e+1),a=0;a<t.length;++a)r[a]=t[a];for(a=0;a<=t.length;++a){for(var i=t.length;i<=e;++i){for(var o=new Array(e),s=0;s<e;++s)o[s]=Math.pow(i+1-a,s);r[i]=o}if(n.apply(void 0,r))return!0}return!1}},{\"robust-orientation\":509}],66:[function(t,e,r){\"use strict\";e.exports=function(t,e){return n(e).filter(function(r){for(var n=new Array(r.length),i=0;i<r.length;++i)n[i]=e[r[i]];return a(n)*t<1})};var n=t(\"delaunay-triangulate\"),a=t(\"circumradius\")},{circumradius:116,\"delaunay-triangulate\":167}],67:[function(t,e,r){e.exports=function(t,e){return a(n(t,e))};var n=t(\"alpha-complex\"),a=t(\"simplicial-complex-boundary\")},{\"alpha-complex\":66,\"simplicial-complex-boundary\":516}],68:[function(t,e,r){\"use strict\";e.exports=function(t,e){if(!t||null==t.length)throw Error(\"Argument should be an array\");e=null==e?1:Math.floor(e);for(var r=Array(2*e),n=0;n<e;n++){for(var a=-1/0,i=1/0,o=n,s=t.length;o<s;o+=e)t[o]>a&&(a=t[o]),t[o]<i&&(i=t[o]);r[n]=i,r[e+n]=a}return r}},{}],69:[function(t,e,r){e.exports=function(t,e){var r=\"number\"==typeof t,n=\"number\"==typeof e;r&&!n?(e=t,t=0):r||n||(t=0,e=0);var a=(e|=0)-(t|=0);if(a<0)throw new Error(\"array length must be positive\");for(var i=new Array(a),o=0,s=t;o<a;o++,s++)i[o]=s;return i}},{}],70:[function(t,e,r){(function(r){\"use strict\";var n=t(\"object-assign\");function a(t,e){if(t===e)return 0;for(var r=t.length,n=e.length,a=0,i=Math.min(r,n);a<i;++a)if(t[a]!==e[a]){r=t[a],n=e[a];break}return r<n?-1:n<r?1:0}function i(t){return r.Buffer&&\"function\"==typeof r.Buffer.isBuffer?r.Buffer.isBuffer(t):!(null==t||!t._isBuffer)}var o=t(\"util/\"),s=Object.prototype.hasOwnProperty,l=Array.prototype.slice,c=\"foo\"===function(){}.name;function u(t){return Object.prototype.toString.call(t)}function h(t){return!i(t)&&(\"function\"==typeof r.ArrayBuffer&&(\"function\"==typeof ArrayBuffer.isView?ArrayBuffer.isView(t):!!t&&(t instanceof DataView||!!(t.buffer&&t.buffer instanceof ArrayBuffer))))}var f=e.exports=y,p=/\\s*function\\s+([^\\(\\s]*)\\s*/;function d(t){if(o.isFunction(t)){if(c)return t.name;var e=t.toString().match(p);return e&&e[1]}}function g(t,e){return\"string\"==typeof t?t.length<e?t:t.slice(0,e):t}function v(t){if(c||!o.isFunction(t))return o.inspect(t);var e=d(t);return\"[Function\"+(e?\": \"+e:\"\")+\"]\"}function m(t,e,r,n,a){throw new f.AssertionError({message:r,actual:t,expected:e,operator:n,stackStartFunction:a})}function y(t,e){t||m(t,!0,e,\"==\",f.ok)}function x(t,e,r,n){if(t===e)return!0;if(i(t)&&i(e))return 0===a(t,e);if(o.isDate(t)&&o.isDate(e))return t.getTime()===e.getTime();if(o.isRegExp(t)&&o.isRegExp(e))return t.source===e.source&&t.global===e.global&&t.multiline===e.multiline&&t.lastIndex===e.lastIndex&&t.ignoreCase===e.ignoreCase;if(null!==t&&\"object\"==typeof t||null!==e&&\"object\"==typeof e){if(h(t)&&h(e)&&u(t)===u(e)&&!(t instanceof Float32Array||t instanceof Float64Array))return 0===a(new Uint8Array(t.buffer),new Uint8Array(e.buffer));if(i(t)!==i(e))return!1;var s=(n=n||{actual:[],expected:[]}).actual.indexOf(t);return-1!==s&&s===n.expected.indexOf(e)||(n.actual.push(t),n.expected.push(e),function(t,e,r,n){if(null==t||null==e)return!1;if(o.isPrimitive(t)||o.isPrimitive(e))return t===e;if(r&&Object.getPrototypeOf(t)!==Object.getPrototypeOf(e))return!1;var a=b(t),i=b(e);if(a&&!i||!a&&i)return!1;if(a)return t=l.call(t),e=l.call(e),x(t,e,r);var s,c,u=k(t),h=k(e);if(u.length!==h.length)return!1;for(u.sort(),h.sort(),c=u.length-1;c>=0;c--)if(u[c]!==h[c])return!1;for(c=u.length-1;c>=0;c--)if(s=u[c],!x(t[s],e[s],r,n))return!1;return!0}(t,e,r,n))}return r?t===e:t==e}function b(t){return\"[object Arguments]\"==Object.prototype.toString.call(t)}function _(t,e){if(!t||!e)return!1;if(\"[object RegExp]\"==Object.prototype.toString.call(e))return e.test(t);try{if(t instanceof e)return!0}catch(t){}return!Error.isPrototypeOf(e)&&!0===e.call({},t)}function w(t,e,r,n){var a;if(\"function\"!=typeof e)throw new TypeError('\"block\" argument must be a function');\"string\"==typeof r&&(n=r,r=null),a=function(t){var e;try{t()}catch(t){e=t}return e}(e),n=(r&&r.name?\" (\"+r.name+\").\":\".\")+(n?\" \"+n:\".\"),t&&!a&&m(a,r,\"Missing expected exception\"+n);var i=\"string\"==typeof n,s=!t&&a&&!r;if((!t&&o.isError(a)&&i&&_(a,r)||s)&&m(a,r,\"Got unwanted exception\"+n),t&&a&&r&&!_(a,r)||!t&&a)throw a}f.AssertionError=function(t){var e;this.name=\"AssertionError\",this.actual=t.actual,this.expected=t.expected,this.operator=t.operator,t.message?(this.message=t.message,this.generatedMessage=!1):(this.message=g(v((e=this).actual),128)+\" \"+e.operator+\" \"+g(v(e.expected),128),this.generatedMessage=!0);var r=t.stackStartFunction||m;if(Error.captureStackTrace)Error.captureStackTrace(this,r);else{var n=new Error;if(n.stack){var a=n.stack,i=d(r),o=a.indexOf(\"\\n\"+i);if(o>=0){var s=a.indexOf(\"\\n\",o+1);a=a.substring(s+1)}this.stack=a}}},o.inherits(f.AssertionError,Error),f.fail=m,f.ok=y,f.equal=function(t,e,r){t!=e&&m(t,e,r,\"==\",f.equal)},f.notEqual=function(t,e,r){t==e&&m(t,e,r,\"!=\",f.notEqual)},f.deepEqual=function(t,e,r){x(t,e,!1)||m(t,e,r,\"deepEqual\",f.deepEqual)},f.deepStrictEqual=function(t,e,r){x(t,e,!0)||m(t,e,r,\"deepStrictEqual\",f.deepStrictEqual)},f.notDeepEqual=function(t,e,r){x(t,e,!1)&&m(t,e,r,\"notDeepEqual\",f.notDeepEqual)},f.notDeepStrictEqual=function t(e,r,n){x(e,r,!0)&&m(e,r,n,\"notDeepStrictEqual\",t)},f.strictEqual=function(t,e,r){t!==e&&m(t,e,r,\"===\",f.strictEqual)},f.notStrictEqual=function(t,e,r){t===e&&m(t,e,r,\"!==\",f.notStrictEqual)},f.throws=function(t,e,r){w(!0,t,e,r)},f.doesNotThrow=function(t,e,r){w(!1,t,e,r)},f.ifError=function(t){if(t)throw t},f.strict=n(function t(e,r){e||m(e,!0,r,\"==\",t)},f,{equal:f.strictEqual,deepEqual:f.deepStrictEqual,notEqual:f.notStrictEqual,notDeepEqual:f.notDeepStrictEqual}),f.strict.strict=f.strict;var k=Object.keys||function(t){var e=[];for(var r in t)s.call(t,r)&&e.push(r);return e}}).call(this,\"undefined\"!=typeof global?global:\"undefined\"!=typeof self?self:\"undefined\"!=typeof window?window:{})},{\"object-assign\":456,\"util/\":73}],71:[function(t,e,r){\"function\"==typeof Object.create?e.exports=function(t,e){t.super_=e,t.prototype=Object.create(e.prototype,{constructor:{value:t,enumerable:!1,writable:!0,configurable:!0}})}:e.exports=function(t,e){t.super_=e;var r=function(){};r.prototype=e.prototype,t.prototype=new r,t.prototype.constructor=t}},{}],72:[function(t,e,r){e.exports=function(t){return t&&\"object\"==typeof t&&\"function\"==typeof t.copy&&\"function\"==typeof t.fill&&\"function\"==typeof t.readUInt8}},{}],73:[function(t,e,r){(function(e,n){var a=/%[sdj%]/g;r.format=function(t){if(!m(t)){for(var e=[],r=0;r<arguments.length;r++)e.push(s(arguments[r]));return e.join(\" \")}r=1;for(var n=arguments,i=n.length,o=String(t).replace(a,function(t){if(\"%%\"===t)return\"%\";if(r>=i)return t;switch(t){case\"%s\":return String(n[r++]);case\"%d\":return Number(n[r++]);case\"%j\":try{return JSON.stringify(n[r++])}catch(t){return\"[Circular]\"}default:return t}}),l=n[r];r<i;l=n[++r])g(l)||!b(l)?o+=\" \"+l:o+=\" \"+s(l);return o},r.deprecate=function(t,a){if(y(n.process))return function(){return r.deprecate(t,a).apply(this,arguments)};if(!0===e.noDeprecation)return t;var i=!1;return function(){if(!i){if(e.throwDeprecation)throw new Error(a);e.traceDeprecation?console.trace(a):console.error(a),i=!0}return t.apply(this,arguments)}};var i,o={};function s(t,e){var n={seen:[],stylize:c};return arguments.length>=3&&(n.depth=arguments[2]),arguments.length>=4&&(n.colors=arguments[3]),d(e)?n.showHidden=e:e&&r._extend(n,e),y(n.showHidden)&&(n.showHidden=!1),y(n.depth)&&(n.depth=2),y(n.colors)&&(n.colors=!1),y(n.customInspect)&&(n.customInspect=!0),n.colors&&(n.stylize=l),u(n,t,n.depth)}function l(t,e){var r=s.styles[e];return r?\"\\x1b[\"+s.colors[r][0]+\"m\"+t+\"\\x1b[\"+s.colors[r][1]+\"m\":t}function c(t,e){return t}function u(t,e,n){if(t.customInspect&&e&&k(e.inspect)&&e.inspect!==r.inspect&&(!e.constructor||e.constructor.prototype!==e)){var a=e.inspect(n,t);return m(a)||(a=u(t,a,n)),a}var i=function(t,e){if(y(e))return t.stylize(\"undefined\",\"undefined\");if(m(e)){var r=\"'\"+JSON.stringify(e).replace(/^\"|\"$/g,\"\").replace(/'/g,\"\\\\'\").replace(/\\\\\"/g,'\"')+\"'\";return t.stylize(r,\"string\")}if(v(e))return t.stylize(\"\"+e,\"number\");if(d(e))return t.stylize(\"\"+e,\"boolean\");if(g(e))return t.stylize(\"null\",\"null\")}(t,e);if(i)return i;var o=Object.keys(e),s=function(t){var e={};return t.forEach(function(t,r){e[t]=!0}),e}(o);if(t.showHidden&&(o=Object.getOwnPropertyNames(e)),w(e)&&(o.indexOf(\"message\")>=0||o.indexOf(\"description\")>=0))return h(e);if(0===o.length){if(k(e)){var l=e.name?\": \"+e.name:\"\";return t.stylize(\"[Function\"+l+\"]\",\"special\")}if(x(e))return t.stylize(RegExp.prototype.toString.call(e),\"regexp\");if(_(e))return t.stylize(Date.prototype.toString.call(e),\"date\");if(w(e))return h(e)}var c,b=\"\",T=!1,M=[\"{\",\"}\"];(p(e)&&(T=!0,M=[\"[\",\"]\"]),k(e))&&(b=\" [Function\"+(e.name?\": \"+e.name:\"\")+\"]\");return x(e)&&(b=\" \"+RegExp.prototype.toString.call(e)),_(e)&&(b=\" \"+Date.prototype.toUTCString.call(e)),w(e)&&(b=\" \"+h(e)),0!==o.length||T&&0!=e.length?n<0?x(e)?t.stylize(RegExp.prototype.toString.call(e),\"regexp\"):t.stylize(\"[Object]\",\"special\"):(t.seen.push(e),c=T?function(t,e,r,n,a){for(var i=[],o=0,s=e.length;o<s;++o)S(e,String(o))?i.push(f(t,e,r,n,String(o),!0)):i.push(\"\");return a.forEach(function(a){a.match(/^\\d+$/)||i.push(f(t,e,r,n,a,!0))}),i}(t,e,n,s,o):o.map(function(r){return f(t,e,n,s,r,T)}),t.seen.pop(),function(t,e,r){if(t.reduce(function(t,e){return 0,e.indexOf(\"\\n\")>=0&&0,t+e.replace(/\\u001b\\[\\d\\d?m/g,\"\").length+1},0)>60)return r[0]+(\"\"===e?\"\":e+\"\\n \")+\" \"+t.join(\",\\n  \")+\" \"+r[1];return r[0]+e+\" \"+t.join(\", \")+\" \"+r[1]}(c,b,M)):M[0]+b+M[1]}function h(t){return\"[\"+Error.prototype.toString.call(t)+\"]\"}function f(t,e,r,n,a,i){var o,s,l;if((l=Object.getOwnPropertyDescriptor(e,a)||{value:e[a]}).get?s=l.set?t.stylize(\"[Getter/Setter]\",\"special\"):t.stylize(\"[Getter]\",\"special\"):l.set&&(s=t.stylize(\"[Setter]\",\"special\")),S(n,a)||(o=\"[\"+a+\"]\"),s||(t.seen.indexOf(l.value)<0?(s=g(r)?u(t,l.value,null):u(t,l.value,r-1)).indexOf(\"\\n\")>-1&&(s=i?s.split(\"\\n\").map(function(t){return\"  \"+t}).join(\"\\n\").substr(2):\"\\n\"+s.split(\"\\n\").map(function(t){return\"   \"+t}).join(\"\\n\")):s=t.stylize(\"[Circular]\",\"special\")),y(o)){if(i&&a.match(/^\\d+$/))return s;(o=JSON.stringify(\"\"+a)).match(/^\"([a-zA-Z_][a-zA-Z_0-9]*)\"$/)?(o=o.substr(1,o.length-2),o=t.stylize(o,\"name\")):(o=o.replace(/'/g,\"\\\\'\").replace(/\\\\\"/g,'\"').replace(/(^\"|\"$)/g,\"'\"),o=t.stylize(o,\"string\"))}return o+\": \"+s}function p(t){return Array.isArray(t)}function d(t){return\"boolean\"==typeof t}function g(t){return null===t}function v(t){return\"number\"==typeof t}function m(t){return\"string\"==typeof t}function y(t){return void 0===t}function x(t){return b(t)&&\"[object RegExp]\"===T(t)}function b(t){return\"object\"==typeof t&&null!==t}function _(t){return b(t)&&\"[object Date]\"===T(t)}function w(t){return b(t)&&(\"[object Error]\"===T(t)||t instanceof Error)}function k(t){return\"function\"==typeof t}function T(t){return Object.prototype.toString.call(t)}function M(t){return t<10?\"0\"+t.toString(10):t.toString(10)}r.debuglog=function(t){if(y(i)&&(i=e.env.NODE_DEBUG||\"\"),t=t.toUpperCase(),!o[t])if(new RegExp(\"\\\\b\"+t+\"\\\\b\",\"i\").test(i)){var n=e.pid;o[t]=function(){var e=r.format.apply(r,arguments);console.error(\"%s %d: %s\",t,n,e)}}else o[t]=function(){};return o[t]},r.inspect=s,s.colors={bold:[1,22],italic:[3,23],underline:[4,24],inverse:[7,27],white:[37,39],grey:[90,39],black:[30,39],blue:[34,39],cyan:[36,39],green:[32,39],magenta:[35,39],red:[31,39],yellow:[33,39]},s.styles={special:\"cyan\",number:\"yellow\",boolean:\"yellow\",undefined:\"grey\",null:\"bold\",string:\"green\",date:\"magenta\",regexp:\"red\"},r.isArray=p,r.isBoolean=d,r.isNull=g,r.isNullOrUndefined=function(t){return null==t},r.isNumber=v,r.isString=m,r.isSymbol=function(t){return\"symbol\"==typeof t},r.isUndefined=y,r.isRegExp=x,r.isObject=b,r.isDate=_,r.isError=w,r.isFunction=k,r.isPrimitive=function(t){return null===t||\"boolean\"==typeof t||\"number\"==typeof t||\"string\"==typeof t||\"symbol\"==typeof t||\"undefined\"==typeof t},r.isBuffer=t(\"./support/isBuffer\");var A=[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"];function S(t,e){return Object.prototype.hasOwnProperty.call(t,e)}r.log=function(){var t,e;console.log(\"%s - %s\",(t=new Date,e=[M(t.getHours()),M(t.getMinutes()),M(t.getSeconds())].join(\":\"),[t.getDate(),A[t.getMonth()],e].join(\" \")),r.format.apply(r,arguments))},r.inherits=t(\"inherits\"),r._extend=function(t,e){if(!e||!b(e))return t;for(var r=Object.keys(e),n=r.length;n--;)t[r[n]]=e[r[n]];return t}}).call(this,t(\"_process\"),\"undefined\"!=typeof global?global:\"undefined\"!=typeof self?self:\"undefined\"!=typeof window?window:{})},{\"./support/isBuffer\":72,_process:484,inherits:71}],74:[function(t,e,r){e.exports=function(t){return atob(t)}},{}],75:[function(t,e,r){\"use strict\";e.exports=function(t,e){for(var r=e.length,i=new Array(r+1),o=0;o<r;++o){for(var s=new Array(r+1),l=0;l<=r;++l)s[l]=t[l][o];i[o]=s}i[r]=new Array(r+1);for(var o=0;o<=r;++o)i[r][o]=1;for(var c=new Array(r+1),o=0;o<r;++o)c[o]=e[o];c[r]=1;var u=n(i,c),h=a(u[r+1]);0===h&&(h=1);for(var f=new Array(r+1),o=0;o<=r;++o)f[o]=a(u[o])/h;return f};var n=t(\"robust-linear-solve\");function a(t){for(var e=0,r=0;r<t.length;++r)e+=t[r];return e}},{\"robust-linear-solve\":508}],76:[function(t,e,r){\"use strict\";r.byteLength=function(t){var e=c(t),r=e[0],n=e[1];return 3*(r+n)/4-n},r.toByteArray=function(t){var e,r,n=c(t),o=n[0],s=n[1],l=new i(function(t,e,r){return 3*(e+r)/4-r}(0,o,s)),u=0,h=s>0?o-4:o;for(r=0;r<h;r+=4)e=a[t.charCodeAt(r)]<<18|a[t.charCodeAt(r+1)]<<12|a[t.charCodeAt(r+2)]<<6|a[t.charCodeAt(r+3)],l[u++]=e>>16&255,l[u++]=e>>8&255,l[u++]=255&e;2===s&&(e=a[t.charCodeAt(r)]<<2|a[t.charCodeAt(r+1)]>>4,l[u++]=255&e);1===s&&(e=a[t.charCodeAt(r)]<<10|a[t.charCodeAt(r+1)]<<4|a[t.charCodeAt(r+2)]>>2,l[u++]=e>>8&255,l[u++]=255&e);return l},r.fromByteArray=function(t){for(var e,r=t.length,a=r%3,i=[],o=0,s=r-a;o<s;o+=16383)i.push(u(t,o,o+16383>s?s:o+16383));1===a?(e=t[r-1],i.push(n[e>>2]+n[e<<4&63]+\"==\")):2===a&&(e=(t[r-2]<<8)+t[r-1],i.push(n[e>>10]+n[e>>4&63]+n[e<<2&63]+\"=\"));return i.join(\"\")};for(var n=[],a=[],i=\"undefined\"!=typeof Uint8Array?Uint8Array:Array,o=\"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/\",s=0,l=o.length;s<l;++s)n[s]=o[s],a[o.charCodeAt(s)]=s;function c(t){var e=t.length;if(e%4>0)throw new Error(\"Invalid string. Length must be a multiple of 4\");var r=t.indexOf(\"=\");return-1===r&&(r=e),[r,r===e?0:4-r%4]}function u(t,e,r){for(var a,i,o=[],s=e;s<r;s+=3)a=(t[s]<<16&16711680)+(t[s+1]<<8&65280)+(255&t[s+2]),o.push(n[(i=a)>>18&63]+n[i>>12&63]+n[i>>6&63]+n[63&i]);return o.join(\"\")}a[\"-\".charCodeAt(0)]=62,a[\"_\".charCodeAt(0)]=63},{}],77:[function(t,e,r){\"use strict\";var n=t(\"./lib/rationalize\");e.exports=function(t,e){return n(t[0].mul(e[1]).add(e[0].mul(t[1])),t[1].mul(e[1]))}},{\"./lib/rationalize\":87}],78:[function(t,e,r){\"use strict\";e.exports=function(t,e){return t[0].mul(e[1]).cmp(e[0].mul(t[1]))}},{}],79:[function(t,e,r){\"use strict\";var n=t(\"./lib/rationalize\");e.exports=function(t,e){return n(t[0].mul(e[1]),t[1].mul(e[0]))}},{\"./lib/rationalize\":87}],80:[function(t,e,r){\"use strict\";var n=t(\"./is-rat\"),a=t(\"./lib/is-bn\"),i=t(\"./lib/num-to-bn\"),o=t(\"./lib/str-to-bn\"),s=t(\"./lib/rationalize\"),l=t(\"./div\");e.exports=function t(e,r){if(n(e))return r?l(e,t(r)):[e[0].clone(),e[1].clone()];var c=0;var u,h;if(a(e))u=e.clone();else if(\"string\"==typeof e)u=o(e);else{if(0===e)return[i(0),i(1)];if(e===Math.floor(e))u=i(e);else{for(;e!==Math.floor(e);)e*=Math.pow(2,256),c-=256;u=i(e)}}if(n(r))u.mul(r[1]),h=r[0].clone();else if(a(r))h=r.clone();else if(\"string\"==typeof r)h=o(r);else if(r)if(r===Math.floor(r))h=i(r);else{for(;r!==Math.floor(r);)r*=Math.pow(2,256),c+=256;h=i(r)}else h=i(1);c>0?u=u.ushln(c):c<0&&(h=h.ushln(-c));return s(u,h)}},{\"./div\":79,\"./is-rat\":81,\"./lib/is-bn\":85,\"./lib/num-to-bn\":86,\"./lib/rationalize\":87,\"./lib/str-to-bn\":88}],81:[function(t,e,r){\"use strict\";var n=t(\"./lib/is-bn\");e.exports=function(t){return Array.isArray(t)&&2===t.length&&n(t[0])&&n(t[1])}},{\"./lib/is-bn\":85}],82:[function(t,e,r){\"use strict\";var n=t(\"bn.js\");e.exports=function(t){return t.cmp(new n(0))}},{\"bn.js\":96}],83:[function(t,e,r){\"use strict\";var n=t(\"./bn-sign\");e.exports=function(t){var e=t.length,r=t.words,a=0;if(1===e)a=r[0];else if(2===e)a=r[0]+67108864*r[1];else for(var i=0;i<e;i++){var o=r[i];a+=o*Math.pow(67108864,i)}return n(t)*a}},{\"./bn-sign\":82}],84:[function(t,e,r){\"use strict\";var n=t(\"double-bits\"),a=t(\"bit-twiddle\").countTrailingZeros;e.exports=function(t){var e=a(n.lo(t));if(e<32)return e;var r=a(n.hi(t));if(r>20)return 52;return r+32}},{\"bit-twiddle\":94,\"double-bits\":169}],85:[function(t,e,r){\"use strict\";t(\"bn.js\");e.exports=function(t){return t&&\"object\"==typeof t&&Boolean(t.words)}},{\"bn.js\":96}],86:[function(t,e,r){\"use strict\";var n=t(\"bn.js\"),a=t(\"double-bits\");e.exports=function(t){var e=a.exponent(t);return e<52?new n(t):new n(t*Math.pow(2,52-e)).ushln(e-52)}},{\"bn.js\":96,\"double-bits\":169}],87:[function(t,e,r){\"use strict\";var n=t(\"./num-to-bn\"),a=t(\"./bn-sign\");e.exports=function(t,e){var r=a(t),i=a(e);if(0===r)return[n(0),n(1)];if(0===i)return[n(0),n(0)];i<0&&(t=t.neg(),e=e.neg());var o=t.gcd(e);if(o.cmpn(1))return[t.div(o),e.div(o)];return[t,e]}},{\"./bn-sign\":82,\"./num-to-bn\":86}],88:[function(t,e,r){\"use strict\";var n=t(\"bn.js\");e.exports=function(t){return new n(t)}},{\"bn.js\":96}],89:[function(t,e,r){\"use strict\";var n=t(\"./lib/rationalize\");e.exports=function(t,e){return n(t[0].mul(e[0]),t[1].mul(e[1]))}},{\"./lib/rationalize\":87}],90:[function(t,e,r){\"use strict\";var n=t(\"./lib/bn-sign\");e.exports=function(t){return n(t[0])*n(t[1])}},{\"./lib/bn-sign\":82}],91:[function(t,e,r){\"use strict\";var n=t(\"./lib/rationalize\");e.exports=function(t,e){return n(t[0].mul(e[1]).sub(t[1].mul(e[0])),t[1].mul(e[1]))}},{\"./lib/rationalize\":87}],92:[function(t,e,r){\"use strict\";var n=t(\"./lib/bn-to-num\"),a=t(\"./lib/ctz\");e.exports=function(t){var e=t[0],r=t[1];if(0===e.cmpn(0))return 0;var i=e.abs().divmod(r.abs()),o=i.div,s=n(o),l=i.mod,c=e.negative!==r.negative?-1:1;if(0===l.cmpn(0))return c*s;if(s){var u=a(s)+4,h=n(l.ushln(u).divRound(r));return c*(s+h*Math.pow(2,-u))}var f=r.bitLength()-l.bitLength()+53,h=n(l.ushln(f).divRound(r));return f<1023?c*h*Math.pow(2,-f):(h*=Math.pow(2,-1023),c*h*Math.pow(2,1023-f))}},{\"./lib/bn-to-num\":83,\"./lib/ctz\":84}],93:[function(t,e,r){\"use strict\";function n(t,e,r,n,a,i){var o=[\"function \",t,\"(a,l,h,\",n.join(\",\"),\"){\",i?\"\":\"var i=\",r?\"l-1\":\"h+1\",\";while(l<=h){var m=(l+h)>>>1,x=a\",a?\".get(m)\":\"[m]\"];return i?e.indexOf(\"c\")<0?o.push(\";if(x===y){return m}else if(x<=y){\"):o.push(\";var p=c(x,y);if(p===0){return m}else if(p<=0){\"):o.push(\";if(\",e,\"){i=m;\"),r?o.push(\"l=m+1}else{h=m-1}\"):o.push(\"h=m-1}else{l=m+1}\"),o.push(\"}\"),i?o.push(\"return -1};\"):o.push(\"return i};\"),o.join(\"\")}function a(t,e,r,a){return new Function([n(\"A\",\"x\"+t+\"y\",e,[\"y\"],!1,a),n(\"B\",\"x\"+t+\"y\",e,[\"y\"],!0,a),n(\"P\",\"c(x,y)\"+t+\"0\",e,[\"y\",\"c\"],!1,a),n(\"Q\",\"c(x,y)\"+t+\"0\",e,[\"y\",\"c\"],!0,a),\"function dispatchBsearch\",r,\"(a,y,c,l,h){if(a.shape){if(typeof(c)==='function'){return Q(a,(l===undefined)?0:l|0,(h===undefined)?a.shape[0]-1:h|0,y,c)}else{return B(a,(c===undefined)?0:c|0,(l===undefined)?a.shape[0]-1:l|0,y)}}else{if(typeof(c)==='function'){return P(a,(l===undefined)?0:l|0,(h===undefined)?a.length-1:h|0,y,c)}else{return A(a,(c===undefined)?0:c|0,(l===undefined)?a.length-1:l|0,y)}}}return dispatchBsearch\",r].join(\"\"))()}e.exports={ge:a(\">=\",!1,\"GE\"),gt:a(\">\",!1,\"GT\"),lt:a(\"<\",!0,\"LT\"),le:a(\"<=\",!0,\"LE\"),eq:a(\"-\",!0,\"EQ\",!0)}},{}],94:[function(t,e,r){\"use strict\";function n(t){var e=32;return(t&=-t)&&e--,65535&t&&(e-=16),16711935&t&&(e-=8),252645135&t&&(e-=4),858993459&t&&(e-=2),1431655765&t&&(e-=1),e}r.INT_BITS=32,r.INT_MAX=2147483647,r.INT_MIN=-1<<31,r.sign=function(t){return(t>0)-(t<0)},r.abs=function(t){var e=t>>31;return(t^e)-e},r.min=function(t,e){return e^(t^e)&-(t<e)},r.max=function(t,e){return t^(t^e)&-(t<e)},r.isPow2=function(t){return!(t&t-1||!t)},r.log2=function(t){var e,r;return e=(t>65535)<<4,e|=r=((t>>>=e)>255)<<3,e|=r=((t>>>=r)>15)<<2,(e|=r=((t>>>=r)>3)<<1)|(t>>>=r)>>1},r.log10=function(t){return t>=1e9?9:t>=1e8?8:t>=1e7?7:t>=1e6?6:t>=1e5?5:t>=1e4?4:t>=1e3?3:t>=100?2:t>=10?1:0},r.popCount=function(t){return 16843009*((t=(858993459&(t-=t>>>1&1431655765))+(t>>>2&858993459))+(t>>>4)&252645135)>>>24},r.countTrailingZeros=n,r.nextPow2=function(t){return t+=0===t,--t,t|=t>>>1,t|=t>>>2,t|=t>>>4,t|=t>>>8,(t|=t>>>16)+1},r.prevPow2=function(t){return t|=t>>>1,t|=t>>>2,t|=t>>>4,t|=t>>>8,(t|=t>>>16)-(t>>>1)},r.parity=function(t){return t^=t>>>16,t^=t>>>8,t^=t>>>4,27030>>>(t&=15)&1};var a=new Array(256);!function(t){for(var e=0;e<256;++e){var r=e,n=e,a=7;for(r>>>=1;r;r>>>=1)n<<=1,n|=1&r,--a;t[e]=n<<a&255}}(a),r.reverse=function(t){return a[255&t]<<24|a[t>>>8&255]<<16|a[t>>>16&255]<<8|a[t>>>24&255]},r.interleave2=function(t,e){return(t=1431655765&((t=858993459&((t=252645135&((t=16711935&((t&=65535)|t<<8))|t<<4))|t<<2))|t<<1))|(e=1431655765&((e=858993459&((e=252645135&((e=16711935&((e&=65535)|e<<8))|e<<4))|e<<2))|e<<1))<<1},r.deinterleave2=function(t,e){return(t=65535&((t=16711935&((t=252645135&((t=858993459&((t=t>>>e&1431655765)|t>>>1))|t>>>2))|t>>>4))|t>>>16))<<16>>16},r.interleave3=function(t,e,r){return t=1227133513&((t=3272356035&((t=251719695&((t=4278190335&((t&=1023)|t<<16))|t<<8))|t<<4))|t<<2),(t|=(e=1227133513&((e=3272356035&((e=251719695&((e=4278190335&((e&=1023)|e<<16))|e<<8))|e<<4))|e<<2))<<1)|(r=1227133513&((r=3272356035&((r=251719695&((r=4278190335&((r&=1023)|r<<16))|r<<8))|r<<4))|r<<2))<<2},r.deinterleave3=function(t,e){return(t=1023&((t=4278190335&((t=251719695&((t=3272356035&((t=t>>>e&1227133513)|t>>>2))|t>>>4))|t>>>8))|t>>>16))<<22>>22},r.nextCombination=function(t){var e=t|t-1;return e+1|(~e&-~e)-1>>>n(t)+1}},{}],95:[function(t,e,r){\"use strict\";var n=t(\"clamp\");e.exports=function(t,e){e||(e={});var r,o,s,l,c,u,h,f,p,d,g,v=null==e.cutoff?.25:e.cutoff,m=null==e.radius?8:e.radius,y=e.channel||0;if(ArrayBuffer.isView(t)||Array.isArray(t)){if(!e.width||!e.height)throw Error(\"For raw data width and height should be provided by options\");r=e.width,o=e.height,l=t,u=e.stride?e.stride:Math.floor(t.length/r/o)}else window.HTMLCanvasElement&&t instanceof window.HTMLCanvasElement?(h=(f=t).getContext(\"2d\"),r=f.width,o=f.height,p=h.getImageData(0,0,r,o),l=p.data,u=4):window.CanvasRenderingContext2D&&t instanceof window.CanvasRenderingContext2D?(f=t.canvas,h=t,r=f.width,o=f.height,p=h.getImageData(0,0,r,o),l=p.data,u=4):window.ImageData&&t instanceof window.ImageData&&(p=t,r=t.width,o=t.height,l=p.data,u=4);if(s=Math.max(r,o),window.Uint8ClampedArray&&l instanceof window.Uint8ClampedArray||window.Uint8Array&&l instanceof window.Uint8Array)for(c=l,l=Array(r*o),d=0,g=c.length;d<g;d++)l[d]=c[d*u+y]/255;else if(1!==u)throw Error(\"Raw data can have only 1 value per pixel\");var x=Array(r*o),b=Array(r*o),_=Array(s),w=Array(s),k=Array(s+1),T=Array(s);for(d=0,g=r*o;d<g;d++){var M=l[d];x[d]=1===M?0:0===M?a:Math.pow(Math.max(0,.5-M),2),b[d]=1===M?a:0===M?0:Math.pow(Math.max(0,M-.5),2)}i(x,r,o,_,w,T,k),i(b,r,o,_,w,T,k);var A=window.Float32Array?new Float32Array(r*o):new Array(r*o);for(d=0,g=r*o;d<g;d++)A[d]=n(1-((x[d]-b[d])/m+v),0,1);return A};var a=1e20;function i(t,e,r,n,a,i,s){for(var l=0;l<e;l++){for(var c=0;c<r;c++)n[c]=t[c*e+l];for(o(n,a,i,s,r),c=0;c<r;c++)t[c*e+l]=a[c]}for(c=0;c<r;c++){for(l=0;l<e;l++)n[l]=t[c*e+l];for(o(n,a,i,s,e),l=0;l<e;l++)t[c*e+l]=Math.sqrt(a[l])}}function o(t,e,r,n,i){r[0]=0,n[0]=-a,n[1]=+a;for(var o=1,s=0;o<i;o++){for(var l=(t[o]+o*o-(t[r[s]]+r[s]*r[s]))/(2*o-2*r[s]);l<=n[s];)s--,l=(t[o]+o*o-(t[r[s]]+r[s]*r[s]))/(2*o-2*r[s]);r[++s]=o,n[s]=l,n[s+1]=+a}for(o=0,s=0;o<i;o++){for(;n[s+1]<o;)s++;e[o]=(o-r[s])*(o-r[s])+t[r[s]]}}},{clamp:117}],96:[function(t,e,r){!function(e,r){\"use strict\";function n(t,e){if(!t)throw new Error(e||\"Assertion failed\")}function a(t,e){t.super_=e;var r=function(){};r.prototype=e.prototype,t.prototype=new r,t.prototype.constructor=t}function i(t,e,r){if(i.isBN(t))return t;this.negative=0,this.words=null,this.length=0,this.red=null,null!==t&&(\"le\"!==e&&\"be\"!==e||(r=e,e=10),this._init(t||0,e||10,r||\"be\"))}var o;\"object\"==typeof e?e.exports=i:r.BN=i,i.BN=i,i.wordSize=26;try{o=t(\"buffer\").Buffer}catch(t){}function s(t,e,r){for(var n=0,a=Math.min(t.length,r),i=e;i<a;i++){var o=t.charCodeAt(i)-48;n<<=4,n|=o>=49&&o<=54?o-49+10:o>=17&&o<=22?o-17+10:15&o}return n}function l(t,e,r,n){for(var a=0,i=Math.min(t.length,r),o=e;o<i;o++){var s=t.charCodeAt(o)-48;a*=n,a+=s>=49?s-49+10:s>=17?s-17+10:s}return a}i.isBN=function(t){return t instanceof i||null!==t&&\"object\"==typeof t&&t.constructor.wordSize===i.wordSize&&Array.isArray(t.words)},i.max=function(t,e){return t.cmp(e)>0?t:e},i.min=function(t,e){return t.cmp(e)<0?t:e},i.prototype._init=function(t,e,r){if(\"number\"==typeof t)return this._initNumber(t,e,r);if(\"object\"==typeof t)return this._initArray(t,e,r);\"hex\"===e&&(e=16),n(e===(0|e)&&e>=2&&e<=36);var a=0;\"-\"===(t=t.toString().replace(/\\s+/g,\"\"))[0]&&a++,16===e?this._parseHex(t,a):this._parseBase(t,e,a),\"-\"===t[0]&&(this.negative=1),this.strip(),\"le\"===r&&this._initArray(this.toArray(),e,r)},i.prototype._initNumber=function(t,e,r){t<0&&(this.negative=1,t=-t),t<67108864?(this.words=[67108863&t],this.length=1):t<4503599627370496?(this.words=[67108863&t,t/67108864&67108863],this.length=2):(n(t<9007199254740992),this.words=[67108863&t,t/67108864&67108863,1],this.length=3),\"le\"===r&&this._initArray(this.toArray(),e,r)},i.prototype._initArray=function(t,e,r){if(n(\"number\"==typeof t.length),t.length<=0)return this.words=[0],this.length=1,this;this.length=Math.ceil(t.length/3),this.words=new Array(this.length);for(var a=0;a<this.length;a++)this.words[a]=0;var i,o,s=0;if(\"be\"===r)for(a=t.length-1,i=0;a>=0;a-=3)o=t[a]|t[a-1]<<8|t[a-2]<<16,this.words[i]|=o<<s&67108863,this.words[i+1]=o>>>26-s&67108863,(s+=24)>=26&&(s-=26,i++);else if(\"le\"===r)for(a=0,i=0;a<t.length;a+=3)o=t[a]|t[a+1]<<8|t[a+2]<<16,this.words[i]|=o<<s&67108863,this.words[i+1]=o>>>26-s&67108863,(s+=24)>=26&&(s-=26,i++);return this.strip()},i.prototype._parseHex=function(t,e){this.length=Math.ceil((t.length-e)/6),this.words=new Array(this.length);for(var r=0;r<this.length;r++)this.words[r]=0;var n,a,i=0;for(r=t.length-6,n=0;r>=e;r-=6)a=s(t,r,r+6),this.words[n]|=a<<i&67108863,this.words[n+1]|=a>>>26-i&4194303,(i+=24)>=26&&(i-=26,n++);r+6!==e&&(a=s(t,e,r+6),this.words[n]|=a<<i&67108863,this.words[n+1]|=a>>>26-i&4194303),this.strip()},i.prototype._parseBase=function(t,e,r){this.words=[0],this.length=1;for(var n=0,a=1;a<=67108863;a*=e)n++;n--,a=a/e|0;for(var i=t.length-r,o=i%n,s=Math.min(i,i-o)+r,c=0,u=r;u<s;u+=n)c=l(t,u,u+n,e),this.imuln(a),this.words[0]+c<67108864?this.words[0]+=c:this._iaddn(c);if(0!==o){var h=1;for(c=l(t,u,t.length,e),u=0;u<o;u++)h*=e;this.imuln(h),this.words[0]+c<67108864?this.words[0]+=c:this._iaddn(c)}},i.prototype.copy=function(t){t.words=new Array(this.length);for(var e=0;e<this.length;e++)t.words[e]=this.words[e];t.length=this.length,t.negative=this.negative,t.red=this.red},i.prototype.clone=function(){var t=new i(null);return this.copy(t),t},i.prototype._expand=function(t){for(;this.length<t;)this.words[this.length++]=0;return this},i.prototype.strip=function(){for(;this.length>1&&0===this.words[this.length-1];)this.length--;return this._normSign()},i.prototype._normSign=function(){return 1===this.length&&0===this.words[0]&&(this.negative=0),this},i.prototype.inspect=function(){return(this.red?\"<BN-R: \":\"<BN: \")+this.toString(16)+\">\"};var c=[\"\",\"0\",\"00\",\"000\",\"0000\",\"00000\",\"000000\",\"0000000\",\"00000000\",\"000000000\",\"0000000000\",\"00000000000\",\"000000000000\",\"0000000000000\",\"00000000000000\",\"000000000000000\",\"0000000000000000\",\"00000000000000000\",\"000000000000000000\",\"0000000000000000000\",\"00000000000000000000\",\"000000000000000000000\",\"0000000000000000000000\",\"00000000000000000000000\",\"000000000000000000000000\",\"0000000000000000000000000\"],u=[0,0,25,16,12,11,10,9,8,8,7,7,7,7,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5],h=[0,0,33554432,43046721,16777216,48828125,60466176,40353607,16777216,43046721,1e7,19487171,35831808,62748517,7529536,11390625,16777216,24137569,34012224,47045881,64e6,4084101,5153632,6436343,7962624,9765625,11881376,14348907,17210368,20511149,243e5,28629151,33554432,39135393,45435424,52521875,60466176];function f(t,e,r){r.negative=e.negative^t.negative;var n=t.length+e.length|0;r.length=n,n=n-1|0;var a=0|t.words[0],i=0|e.words[0],o=a*i,s=67108863&o,l=o/67108864|0;r.words[0]=s;for(var c=1;c<n;c++){for(var u=l>>>26,h=67108863&l,f=Math.min(c,e.length-1),p=Math.max(0,c-t.length+1);p<=f;p++){var d=c-p|0;u+=(o=(a=0|t.words[d])*(i=0|e.words[p])+h)/67108864|0,h=67108863&o}r.words[c]=0|h,l=0|u}return 0!==l?r.words[c]=0|l:r.length--,r.strip()}i.prototype.toString=function(t,e){var r;if(e=0|e||1,16===(t=t||10)||\"hex\"===t){r=\"\";for(var a=0,i=0,o=0;o<this.length;o++){var s=this.words[o],l=(16777215&(s<<a|i)).toString(16);r=0!==(i=s>>>24-a&16777215)||o!==this.length-1?c[6-l.length]+l+r:l+r,(a+=2)>=26&&(a-=26,o--)}for(0!==i&&(r=i.toString(16)+r);r.length%e!=0;)r=\"0\"+r;return 0!==this.negative&&(r=\"-\"+r),r}if(t===(0|t)&&t>=2&&t<=36){var f=u[t],p=h[t];r=\"\";var d=this.clone();for(d.negative=0;!d.isZero();){var g=d.modn(p).toString(t);r=(d=d.idivn(p)).isZero()?g+r:c[f-g.length]+g+r}for(this.isZero()&&(r=\"0\"+r);r.length%e!=0;)r=\"0\"+r;return 0!==this.negative&&(r=\"-\"+r),r}n(!1,\"Base should be between 2 and 36\")},i.prototype.toNumber=function(){var t=this.words[0];return 2===this.length?t+=67108864*this.words[1]:3===this.length&&1===this.words[2]?t+=4503599627370496+67108864*this.words[1]:this.length>2&&n(!1,\"Number can only safely store up to 53 bits\"),0!==this.negative?-t:t},i.prototype.toJSON=function(){return this.toString(16)},i.prototype.toBuffer=function(t,e){return n(\"undefined\"!=typeof o),this.toArrayLike(o,t,e)},i.prototype.toArray=function(t,e){return this.toArrayLike(Array,t,e)},i.prototype.toArrayLike=function(t,e,r){var a=this.byteLength(),i=r||Math.max(1,a);n(a<=i,\"byte array longer than desired length\"),n(i>0,\"Requested array length <= 0\"),this.strip();var o,s,l=\"le\"===e,c=new t(i),u=this.clone();if(l){for(s=0;!u.isZero();s++)o=u.andln(255),u.iushrn(8),c[s]=o;for(;s<i;s++)c[s]=0}else{for(s=0;s<i-a;s++)c[s]=0;for(s=0;!u.isZero();s++)o=u.andln(255),u.iushrn(8),c[i-s-1]=o}return c},Math.clz32?i.prototype._countBits=function(t){return 32-Math.clz32(t)}:i.prototype._countBits=function(t){var e=t,r=0;return e>=4096&&(r+=13,e>>>=13),e>=64&&(r+=7,e>>>=7),e>=8&&(r+=4,e>>>=4),e>=2&&(r+=2,e>>>=2),r+e},i.prototype._zeroBits=function(t){if(0===t)return 26;var e=t,r=0;return 0==(8191&e)&&(r+=13,e>>>=13),0==(127&e)&&(r+=7,e>>>=7),0==(15&e)&&(r+=4,e>>>=4),0==(3&e)&&(r+=2,e>>>=2),0==(1&e)&&r++,r},i.prototype.bitLength=function(){var t=this.words[this.length-1],e=this._countBits(t);return 26*(this.length-1)+e},i.prototype.zeroBits=function(){if(this.isZero())return 0;for(var t=0,e=0;e<this.length;e++){var r=this._zeroBits(this.words[e]);if(t+=r,26!==r)break}return t},i.prototype.byteLength=function(){return Math.ceil(this.bitLength()/8)},i.prototype.toTwos=function(t){return 0!==this.negative?this.abs().inotn(t).iaddn(1):this.clone()},i.prototype.fromTwos=function(t){return this.testn(t-1)?this.notn(t).iaddn(1).ineg():this.clone()},i.prototype.isNeg=function(){return 0!==this.negative},i.prototype.neg=function(){return this.clone().ineg()},i.prototype.ineg=function(){return this.isZero()||(this.negative^=1),this},i.prototype.iuor=function(t){for(;this.length<t.length;)this.words[this.length++]=0;for(var e=0;e<t.length;e++)this.words[e]=this.words[e]|t.words[e];return this.strip()},i.prototype.ior=function(t){return n(0==(this.negative|t.negative)),this.iuor(t)},i.prototype.or=function(t){return this.length>t.length?this.clone().ior(t):t.clone().ior(this)},i.prototype.uor=function(t){return this.length>t.length?this.clone().iuor(t):t.clone().iuor(this)},i.prototype.iuand=function(t){var e;e=this.length>t.length?t:this;for(var r=0;r<e.length;r++)this.words[r]=this.words[r]&t.words[r];return this.length=e.length,this.strip()},i.prototype.iand=function(t){return n(0==(this.negative|t.negative)),this.iuand(t)},i.prototype.and=function(t){return this.length>t.length?this.clone().iand(t):t.clone().iand(this)},i.prototype.uand=function(t){return this.length>t.length?this.clone().iuand(t):t.clone().iuand(this)},i.prototype.iuxor=function(t){var e,r;this.length>t.length?(e=this,r=t):(e=t,r=this);for(var n=0;n<r.length;n++)this.words[n]=e.words[n]^r.words[n];if(this!==e)for(;n<e.length;n++)this.words[n]=e.words[n];return this.length=e.length,this.strip()},i.prototype.ixor=function(t){return n(0==(this.negative|t.negative)),this.iuxor(t)},i.prototype.xor=function(t){return this.length>t.length?this.clone().ixor(t):t.clone().ixor(this)},i.prototype.uxor=function(t){return this.length>t.length?this.clone().iuxor(t):t.clone().iuxor(this)},i.prototype.inotn=function(t){n(\"number\"==typeof t&&t>=0);var e=0|Math.ceil(t/26),r=t%26;this._expand(e),r>0&&e--;for(var a=0;a<e;a++)this.words[a]=67108863&~this.words[a];return r>0&&(this.words[a]=~this.words[a]&67108863>>26-r),this.strip()},i.prototype.notn=function(t){return this.clone().inotn(t)},i.prototype.setn=function(t,e){n(\"number\"==typeof t&&t>=0);var r=t/26|0,a=t%26;return this._expand(r+1),this.words[r]=e?this.words[r]|1<<a:this.words[r]&~(1<<a),this.strip()},i.prototype.iadd=function(t){var e,r,n;if(0!==this.negative&&0===t.negative)return this.negative=0,e=this.isub(t),this.negative^=1,this._normSign();if(0===this.negative&&0!==t.negative)return t.negative=0,e=this.isub(t),t.negative=1,e._normSign();this.length>t.length?(r=this,n=t):(r=t,n=this);for(var a=0,i=0;i<n.length;i++)e=(0|r.words[i])+(0|n.words[i])+a,this.words[i]=67108863&e,a=e>>>26;for(;0!==a&&i<r.length;i++)e=(0|r.words[i])+a,this.words[i]=67108863&e,a=e>>>26;if(this.length=r.length,0!==a)this.words[this.length]=a,this.length++;else if(r!==this)for(;i<r.length;i++)this.words[i]=r.words[i];return this},i.prototype.add=function(t){var e;return 0!==t.negative&&0===this.negative?(t.negative=0,e=this.sub(t),t.negative^=1,e):0===t.negative&&0!==this.negative?(this.negative=0,e=t.sub(this),this.negative=1,e):this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},i.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r,n,a=this.cmp(t);if(0===a)return this.negative=0,this.length=1,this.words[0]=0,this;a>0?(r=this,n=t):(r=t,n=this);for(var i=0,o=0;o<n.length;o++)i=(e=(0|r.words[o])-(0|n.words[o])+i)>>26,this.words[o]=67108863&e;for(;0!==i&&o<r.length;o++)i=(e=(0|r.words[o])+i)>>26,this.words[o]=67108863&e;if(0===i&&o<r.length&&r!==this)for(;o<r.length;o++)this.words[o]=r.words[o];return this.length=Math.max(this.length,o),r!==this&&(this.negative=1),this.strip()},i.prototype.sub=function(t){return this.clone().isub(t)};var p=function(t,e,r){var n,a,i,o=t.words,s=e.words,l=r.words,c=0,u=0|o[0],h=8191&u,f=u>>>13,p=0|o[1],d=8191&p,g=p>>>13,v=0|o[2],m=8191&v,y=v>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],k=8191&w,T=w>>>13,M=0|o[5],A=8191&M,S=M>>>13,E=0|o[6],L=8191&E,C=E>>>13,P=0|o[7],O=8191&P,z=P>>>13,I=0|o[8],D=8191&I,R=I>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],V=8191&j,U=j>>>13,q=0|s[1],H=8191&q,G=q>>>13,Y=0|s[2],W=8191&Y,X=Y>>>13,Z=0|s[3],J=8191&Z,K=Z>>>13,Q=0|s[4],$=8191&Q,tt=Q>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,at=0|s[6],it=8191&at,ot=at>>>13,st=0|s[7],lt=8191&st,ct=st>>>13,ut=0|s[8],ht=8191&ut,ft=ut>>>13,pt=0|s[9],dt=8191&pt,gt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var vt=(c+(n=Math.imul(h,V))|0)+((8191&(a=(a=Math.imul(h,U))+Math.imul(f,V)|0))<<13)|0;c=((i=Math.imul(f,U))+(a>>>13)|0)+(vt>>>26)|0,vt&=67108863,n=Math.imul(d,V),a=(a=Math.imul(d,U))+Math.imul(g,V)|0,i=Math.imul(g,U);var mt=(c+(n=n+Math.imul(h,H)|0)|0)+((8191&(a=(a=a+Math.imul(h,G)|0)+Math.imul(f,H)|0))<<13)|0;c=((i=i+Math.imul(f,G)|0)+(a>>>13)|0)+(mt>>>26)|0,mt&=67108863,n=Math.imul(m,V),a=(a=Math.imul(m,U))+Math.imul(y,V)|0,i=Math.imul(y,U),n=n+Math.imul(d,H)|0,a=(a=a+Math.imul(d,G)|0)+Math.imul(g,H)|0,i=i+Math.imul(g,G)|0;var yt=(c+(n=n+Math.imul(h,W)|0)|0)+((8191&(a=(a=a+Math.imul(h,X)|0)+Math.imul(f,W)|0))<<13)|0;c=((i=i+Math.imul(f,X)|0)+(a>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(b,V),a=(a=Math.imul(b,U))+Math.imul(_,V)|0,i=Math.imul(_,U),n=n+Math.imul(m,H)|0,a=(a=a+Math.imul(m,G)|0)+Math.imul(y,H)|0,i=i+Math.imul(y,G)|0,n=n+Math.imul(d,W)|0,a=(a=a+Math.imul(d,X)|0)+Math.imul(g,W)|0,i=i+Math.imul(g,X)|0;var xt=(c+(n=n+Math.imul(h,J)|0)|0)+((8191&(a=(a=a+Math.imul(h,K)|0)+Math.imul(f,J)|0))<<13)|0;c=((i=i+Math.imul(f,K)|0)+(a>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(k,V),a=(a=Math.imul(k,U))+Math.imul(T,V)|0,i=Math.imul(T,U),n=n+Math.imul(b,H)|0,a=(a=a+Math.imul(b,G)|0)+Math.imul(_,H)|0,i=i+Math.imul(_,G)|0,n=n+Math.imul(m,W)|0,a=(a=a+Math.imul(m,X)|0)+Math.imul(y,W)|0,i=i+Math.imul(y,X)|0,n=n+Math.imul(d,J)|0,a=(a=a+Math.imul(d,K)|0)+Math.imul(g,J)|0,i=i+Math.imul(g,K)|0;var bt=(c+(n=n+Math.imul(h,$)|0)|0)+((8191&(a=(a=a+Math.imul(h,tt)|0)+Math.imul(f,$)|0))<<13)|0;c=((i=i+Math.imul(f,tt)|0)+(a>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(A,V),a=(a=Math.imul(A,U))+Math.imul(S,V)|0,i=Math.imul(S,U),n=n+Math.imul(k,H)|0,a=(a=a+Math.imul(k,G)|0)+Math.imul(T,H)|0,i=i+Math.imul(T,G)|0,n=n+Math.imul(b,W)|0,a=(a=a+Math.imul(b,X)|0)+Math.imul(_,W)|0,i=i+Math.imul(_,X)|0,n=n+Math.imul(m,J)|0,a=(a=a+Math.imul(m,K)|0)+Math.imul(y,J)|0,i=i+Math.imul(y,K)|0,n=n+Math.imul(d,$)|0,a=(a=a+Math.imul(d,tt)|0)+Math.imul(g,$)|0,i=i+Math.imul(g,tt)|0;var _t=(c+(n=n+Math.imul(h,rt)|0)|0)+((8191&(a=(a=a+Math.imul(h,nt)|0)+Math.imul(f,rt)|0))<<13)|0;c=((i=i+Math.imul(f,nt)|0)+(a>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(L,V),a=(a=Math.imul(L,U))+Math.imul(C,V)|0,i=Math.imul(C,U),n=n+Math.imul(A,H)|0,a=(a=a+Math.imul(A,G)|0)+Math.imul(S,H)|0,i=i+Math.imul(S,G)|0,n=n+Math.imul(k,W)|0,a=(a=a+Math.imul(k,X)|0)+Math.imul(T,W)|0,i=i+Math.imul(T,X)|0,n=n+Math.imul(b,J)|0,a=(a=a+Math.imul(b,K)|0)+Math.imul(_,J)|0,i=i+Math.imul(_,K)|0,n=n+Math.imul(m,$)|0,a=(a=a+Math.imul(m,tt)|0)+Math.imul(y,$)|0,i=i+Math.imul(y,tt)|0,n=n+Math.imul(d,rt)|0,a=(a=a+Math.imul(d,nt)|0)+Math.imul(g,rt)|0,i=i+Math.imul(g,nt)|0;var wt=(c+(n=n+Math.imul(h,it)|0)|0)+((8191&(a=(a=a+Math.imul(h,ot)|0)+Math.imul(f,it)|0))<<13)|0;c=((i=i+Math.imul(f,ot)|0)+(a>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(O,V),a=(a=Math.imul(O,U))+Math.imul(z,V)|0,i=Math.imul(z,U),n=n+Math.imul(L,H)|0,a=(a=a+Math.imul(L,G)|0)+Math.imul(C,H)|0,i=i+Math.imul(C,G)|0,n=n+Math.imul(A,W)|0,a=(a=a+Math.imul(A,X)|0)+Math.imul(S,W)|0,i=i+Math.imul(S,X)|0,n=n+Math.imul(k,J)|0,a=(a=a+Math.imul(k,K)|0)+Math.imul(T,J)|0,i=i+Math.imul(T,K)|0,n=n+Math.imul(b,$)|0,a=(a=a+Math.imul(b,tt)|0)+Math.imul(_,$)|0,i=i+Math.imul(_,tt)|0,n=n+Math.imul(m,rt)|0,a=(a=a+Math.imul(m,nt)|0)+Math.imul(y,rt)|0,i=i+Math.imul(y,nt)|0,n=n+Math.imul(d,it)|0,a=(a=a+Math.imul(d,ot)|0)+Math.imul(g,it)|0,i=i+Math.imul(g,ot)|0;var kt=(c+(n=n+Math.imul(h,lt)|0)|0)+((8191&(a=(a=a+Math.imul(h,ct)|0)+Math.imul(f,lt)|0))<<13)|0;c=((i=i+Math.imul(f,ct)|0)+(a>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(D,V),a=(a=Math.imul(D,U))+Math.imul(R,V)|0,i=Math.imul(R,U),n=n+Math.imul(O,H)|0,a=(a=a+Math.imul(O,G)|0)+Math.imul(z,H)|0,i=i+Math.imul(z,G)|0,n=n+Math.imul(L,W)|0,a=(a=a+Math.imul(L,X)|0)+Math.imul(C,W)|0,i=i+Math.imul(C,X)|0,n=n+Math.imul(A,J)|0,a=(a=a+Math.imul(A,K)|0)+Math.imul(S,J)|0,i=i+Math.imul(S,K)|0,n=n+Math.imul(k,$)|0,a=(a=a+Math.imul(k,tt)|0)+Math.imul(T,$)|0,i=i+Math.imul(T,tt)|0,n=n+Math.imul(b,rt)|0,a=(a=a+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,i=i+Math.imul(_,nt)|0,n=n+Math.imul(m,it)|0,a=(a=a+Math.imul(m,ot)|0)+Math.imul(y,it)|0,i=i+Math.imul(y,ot)|0,n=n+Math.imul(d,lt)|0,a=(a=a+Math.imul(d,ct)|0)+Math.imul(g,lt)|0,i=i+Math.imul(g,ct)|0;var Tt=(c+(n=n+Math.imul(h,ht)|0)|0)+((8191&(a=(a=a+Math.imul(h,ft)|0)+Math.imul(f,ht)|0))<<13)|0;c=((i=i+Math.imul(f,ft)|0)+(a>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(B,V),a=(a=Math.imul(B,U))+Math.imul(N,V)|0,i=Math.imul(N,U),n=n+Math.imul(D,H)|0,a=(a=a+Math.imul(D,G)|0)+Math.imul(R,H)|0,i=i+Math.imul(R,G)|0,n=n+Math.imul(O,W)|0,a=(a=a+Math.imul(O,X)|0)+Math.imul(z,W)|0,i=i+Math.imul(z,X)|0,n=n+Math.imul(L,J)|0,a=(a=a+Math.imul(L,K)|0)+Math.imul(C,J)|0,i=i+Math.imul(C,K)|0,n=n+Math.imul(A,$)|0,a=(a=a+Math.imul(A,tt)|0)+Math.imul(S,$)|0,i=i+Math.imul(S,tt)|0,n=n+Math.imul(k,rt)|0,a=(a=a+Math.imul(k,nt)|0)+Math.imul(T,rt)|0,i=i+Math.imul(T,nt)|0,n=n+Math.imul(b,it)|0,a=(a=a+Math.imul(b,ot)|0)+Math.imul(_,it)|0,i=i+Math.imul(_,ot)|0,n=n+Math.imul(m,lt)|0,a=(a=a+Math.imul(m,ct)|0)+Math.imul(y,lt)|0,i=i+Math.imul(y,ct)|0,n=n+Math.imul(d,ht)|0,a=(a=a+Math.imul(d,ft)|0)+Math.imul(g,ht)|0,i=i+Math.imul(g,ft)|0;var Mt=(c+(n=n+Math.imul(h,dt)|0)|0)+((8191&(a=(a=a+Math.imul(h,gt)|0)+Math.imul(f,dt)|0))<<13)|0;c=((i=i+Math.imul(f,gt)|0)+(a>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,H),a=(a=Math.imul(B,G))+Math.imul(N,H)|0,i=Math.imul(N,G),n=n+Math.imul(D,W)|0,a=(a=a+Math.imul(D,X)|0)+Math.imul(R,W)|0,i=i+Math.imul(R,X)|0,n=n+Math.imul(O,J)|0,a=(a=a+Math.imul(O,K)|0)+Math.imul(z,J)|0,i=i+Math.imul(z,K)|0,n=n+Math.imul(L,$)|0,a=(a=a+Math.imul(L,tt)|0)+Math.imul(C,$)|0,i=i+Math.imul(C,tt)|0,n=n+Math.imul(A,rt)|0,a=(a=a+Math.imul(A,nt)|0)+Math.imul(S,rt)|0,i=i+Math.imul(S,nt)|0,n=n+Math.imul(k,it)|0,a=(a=a+Math.imul(k,ot)|0)+Math.imul(T,it)|0,i=i+Math.imul(T,ot)|0,n=n+Math.imul(b,lt)|0,a=(a=a+Math.imul(b,ct)|0)+Math.imul(_,lt)|0,i=i+Math.imul(_,ct)|0,n=n+Math.imul(m,ht)|0,a=(a=a+Math.imul(m,ft)|0)+Math.imul(y,ht)|0,i=i+Math.imul(y,ft)|0;var At=(c+(n=n+Math.imul(d,dt)|0)|0)+((8191&(a=(a=a+Math.imul(d,gt)|0)+Math.imul(g,dt)|0))<<13)|0;c=((i=i+Math.imul(g,gt)|0)+(a>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,W),a=(a=Math.imul(B,X))+Math.imul(N,W)|0,i=Math.imul(N,X),n=n+Math.imul(D,J)|0,a=(a=a+Math.imul(D,K)|0)+Math.imul(R,J)|0,i=i+Math.imul(R,K)|0,n=n+Math.imul(O,$)|0,a=(a=a+Math.imul(O,tt)|0)+Math.imul(z,$)|0,i=i+Math.imul(z,tt)|0,n=n+Math.imul(L,rt)|0,a=(a=a+Math.imul(L,nt)|0)+Math.imul(C,rt)|0,i=i+Math.imul(C,nt)|0,n=n+Math.imul(A,it)|0,a=(a=a+Math.imul(A,ot)|0)+Math.imul(S,it)|0,i=i+Math.imul(S,ot)|0,n=n+Math.imul(k,lt)|0,a=(a=a+Math.imul(k,ct)|0)+Math.imul(T,lt)|0,i=i+Math.imul(T,ct)|0,n=n+Math.imul(b,ht)|0,a=(a=a+Math.imul(b,ft)|0)+Math.imul(_,ht)|0,i=i+Math.imul(_,ft)|0;var St=(c+(n=n+Math.imul(m,dt)|0)|0)+((8191&(a=(a=a+Math.imul(m,gt)|0)+Math.imul(y,dt)|0))<<13)|0;c=((i=i+Math.imul(y,gt)|0)+(a>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,J),a=(a=Math.imul(B,K))+Math.imul(N,J)|0,i=Math.imul(N,K),n=n+Math.imul(D,$)|0,a=(a=a+Math.imul(D,tt)|0)+Math.imul(R,$)|0,i=i+Math.imul(R,tt)|0,n=n+Math.imul(O,rt)|0,a=(a=a+Math.imul(O,nt)|0)+Math.imul(z,rt)|0,i=i+Math.imul(z,nt)|0,n=n+Math.imul(L,it)|0,a=(a=a+Math.imul(L,ot)|0)+Math.imul(C,it)|0,i=i+Math.imul(C,ot)|0,n=n+Math.imul(A,lt)|0,a=(a=a+Math.imul(A,ct)|0)+Math.imul(S,lt)|0,i=i+Math.imul(S,ct)|0,n=n+Math.imul(k,ht)|0,a=(a=a+Math.imul(k,ft)|0)+Math.imul(T,ht)|0,i=i+Math.imul(T,ft)|0;var Et=(c+(n=n+Math.imul(b,dt)|0)|0)+((8191&(a=(a=a+Math.imul(b,gt)|0)+Math.imul(_,dt)|0))<<13)|0;c=((i=i+Math.imul(_,gt)|0)+(a>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,$),a=(a=Math.imul(B,tt))+Math.imul(N,$)|0,i=Math.imul(N,tt),n=n+Math.imul(D,rt)|0,a=(a=a+Math.imul(D,nt)|0)+Math.imul(R,rt)|0,i=i+Math.imul(R,nt)|0,n=n+Math.imul(O,it)|0,a=(a=a+Math.imul(O,ot)|0)+Math.imul(z,it)|0,i=i+Math.imul(z,ot)|0,n=n+Math.imul(L,lt)|0,a=(a=a+Math.imul(L,ct)|0)+Math.imul(C,lt)|0,i=i+Math.imul(C,ct)|0,n=n+Math.imul(A,ht)|0,a=(a=a+Math.imul(A,ft)|0)+Math.imul(S,ht)|0,i=i+Math.imul(S,ft)|0;var Lt=(c+(n=n+Math.imul(k,dt)|0)|0)+((8191&(a=(a=a+Math.imul(k,gt)|0)+Math.imul(T,dt)|0))<<13)|0;c=((i=i+Math.imul(T,gt)|0)+(a>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,rt),a=(a=Math.imul(B,nt))+Math.imul(N,rt)|0,i=Math.imul(N,nt),n=n+Math.imul(D,it)|0,a=(a=a+Math.imul(D,ot)|0)+Math.imul(R,it)|0,i=i+Math.imul(R,ot)|0,n=n+Math.imul(O,lt)|0,a=(a=a+Math.imul(O,ct)|0)+Math.imul(z,lt)|0,i=i+Math.imul(z,ct)|0,n=n+Math.imul(L,ht)|0,a=(a=a+Math.imul(L,ft)|0)+Math.imul(C,ht)|0,i=i+Math.imul(C,ft)|0;var Ct=(c+(n=n+Math.imul(A,dt)|0)|0)+((8191&(a=(a=a+Math.imul(A,gt)|0)+Math.imul(S,dt)|0))<<13)|0;c=((i=i+Math.imul(S,gt)|0)+(a>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,it),a=(a=Math.imul(B,ot))+Math.imul(N,it)|0,i=Math.imul(N,ot),n=n+Math.imul(D,lt)|0,a=(a=a+Math.imul(D,ct)|0)+Math.imul(R,lt)|0,i=i+Math.imul(R,ct)|0,n=n+Math.imul(O,ht)|0,a=(a=a+Math.imul(O,ft)|0)+Math.imul(z,ht)|0,i=i+Math.imul(z,ft)|0;var Pt=(c+(n=n+Math.imul(L,dt)|0)|0)+((8191&(a=(a=a+Math.imul(L,gt)|0)+Math.imul(C,dt)|0))<<13)|0;c=((i=i+Math.imul(C,gt)|0)+(a>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,lt),a=(a=Math.imul(B,ct))+Math.imul(N,lt)|0,i=Math.imul(N,ct),n=n+Math.imul(D,ht)|0,a=(a=a+Math.imul(D,ft)|0)+Math.imul(R,ht)|0,i=i+Math.imul(R,ft)|0;var Ot=(c+(n=n+Math.imul(O,dt)|0)|0)+((8191&(a=(a=a+Math.imul(O,gt)|0)+Math.imul(z,dt)|0))<<13)|0;c=((i=i+Math.imul(z,gt)|0)+(a>>>13)|0)+(Ot>>>26)|0,Ot&=67108863,n=Math.imul(B,ht),a=(a=Math.imul(B,ft))+Math.imul(N,ht)|0,i=Math.imul(N,ft);var zt=(c+(n=n+Math.imul(D,dt)|0)|0)+((8191&(a=(a=a+Math.imul(D,gt)|0)+Math.imul(R,dt)|0))<<13)|0;c=((i=i+Math.imul(R,gt)|0)+(a>>>13)|0)+(zt>>>26)|0,zt&=67108863;var It=(c+(n=Math.imul(B,dt))|0)+((8191&(a=(a=Math.imul(B,gt))+Math.imul(N,dt)|0))<<13)|0;return c=((i=Math.imul(N,gt))+(a>>>13)|0)+(It>>>26)|0,It&=67108863,l[0]=vt,l[1]=mt,l[2]=yt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=kt,l[8]=Tt,l[9]=Mt,l[10]=At,l[11]=St,l[12]=Et,l[13]=Lt,l[14]=Ct,l[15]=Pt,l[16]=Ot,l[17]=zt,l[18]=It,0!==c&&(l[19]=c,r.length++),r};function d(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(p=f),i.prototype.mulTo=function(t,e){var r=this.length+t.length;return 10===this.length&&10===t.length?p(this,t,e):r<63?f(this,t,e):r<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,a=0,i=0;i<r.length-1;i++){var o=a;a=0;for(var s=67108863&n,l=Math.min(i,e.length-1),c=Math.max(0,i-t.length+1);c<=l;c++){var u=i-c,h=(0|t.words[u])*(0|e.words[c]),f=67108863&h;s=67108863&(f=f+s|0),a+=(o=(o=o+(h/67108864|0)|0)+(f>>>26)|0)>>>26,o&=67108863}r.words[i]=s,n=o,o=a}return 0!==n?r.words[i]=n:r.length--,r.strip()}(this,t,e):d(this,t,e)},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=i.prototype._countBits(t)-1,n=0;n<t;n++)e[n]=this.revBin(n,r,t);return e},g.prototype.revBin=function(t,e,r){if(0===t||t===r-1)return t;for(var n=0,a=0;a<e;a++)n|=(1&t)<<e-a-1,t>>=1;return n},g.prototype.permute=function(t,e,r,n,a,i){for(var o=0;o<i;o++)n[o]=e[t[o]],a[o]=r[t[o]]},g.prototype.transform=function(t,e,r,n,a,i){this.permute(i,t,e,r,n,a);for(var o=1;o<a;o<<=1)for(var s=o<<1,l=Math.cos(2*Math.PI/s),c=Math.sin(2*Math.PI/s),u=0;u<a;u+=s)for(var h=l,f=c,p=0;p<o;p++){var d=r[u+p],g=n[u+p],v=r[u+p+o],m=n[u+p+o],y=h*v-f*m;m=h*m+f*v,v=y,r[u+p]=d+v,n[u+p]=g+m,r[u+p+o]=d-v,n[u+p+o]=g-m,p!==s&&(y=l*h-c*f,f=l*f+c*h,h=y)}},g.prototype.guessLen13b=function(t,e){var r=1|Math.max(e,t),n=1&r,a=0;for(r=r/2|0;r;r>>>=1)a++;return 1<<a+1+n},g.prototype.conjugate=function(t,e,r){if(!(r<=1))for(var n=0;n<r/2;n++){var a=t[n];t[n]=t[r-n-1],t[r-n-1]=a,a=e[n],e[n]=-e[r-n-1],e[r-n-1]=-a}},g.prototype.normalize13b=function(t,e){for(var r=0,n=0;n<e/2;n++){var a=8192*Math.round(t[2*n+1]/e)+Math.round(t[2*n]/e)+r;t[n]=67108863&a,r=a<67108864?0:a/67108864|0}return t},g.prototype.convert13b=function(t,e,r,a){for(var i=0,o=0;o<e;o++)i+=0|t[o],r[2*o]=8191&i,i>>>=13,r[2*o+1]=8191&i,i>>>=13;for(o=2*e;o<a;++o)r[o]=0;n(0===i),n(0==(-8192&i))},g.prototype.stub=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=0;return e},g.prototype.mulp=function(t,e,r){var n=2*this.guessLen13b(t.length,e.length),a=this.makeRBT(n),i=this.stub(n),o=new Array(n),s=new Array(n),l=new Array(n),c=new Array(n),u=new Array(n),h=new Array(n),f=r.words;f.length=n,this.convert13b(t.words,t.length,o,n),this.convert13b(e.words,e.length,c,n),this.transform(o,i,s,l,n,a),this.transform(c,i,u,h,n,a);for(var p=0;p<n;p++){var d=s[p]*u[p]-l[p]*h[p];l[p]=s[p]*h[p]+l[p]*u[p],s[p]=d}return this.conjugate(s,l,n),this.transform(s,l,f,i,n,a),this.conjugate(f,i,n),this.normalize13b(f,n),r.negative=t.negative^e.negative,r.length=t.length+e.length,r.strip()},i.prototype.mul=function(t){var e=new i(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},i.prototype.mulf=function(t){var e=new i(null);return e.words=new Array(this.length+t.length),d(this,t,e)},i.prototype.imul=function(t){return this.clone().mulTo(t,this)},i.prototype.imuln=function(t){n(\"number\"==typeof t),n(t<67108864);for(var e=0,r=0;r<this.length;r++){var a=(0|this.words[r])*t,i=(67108863&a)+(67108863&e);e>>=26,e+=a/67108864|0,e+=i>>>26,this.words[r]=67108863&i}return 0!==e&&(this.words[r]=e,this.length++),this},i.prototype.muln=function(t){return this.clone().imuln(t)},i.prototype.sqr=function(){return this.mul(this)},i.prototype.isqr=function(){return this.imul(this.clone())},i.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r<e.length;r++){var n=r/26|0,a=r%26;e[r]=(t.words[n]&1<<a)>>>a}return e}(t);if(0===e.length)return new i(1);for(var r=this,n=0;n<e.length&&0===e[n];n++,r=r.sqr());if(++n<e.length)for(var a=r.sqr();n<e.length;n++,a=a.sqr())0!==e[n]&&(r=r.mul(a));return r},i.prototype.iushln=function(t){n(\"number\"==typeof t&&t>=0);var e,r=t%26,a=(t-r)/26,i=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e<this.length;e++){var s=this.words[e]&i,l=(0|this.words[e])-s<<r;this.words[e]=l|o,o=s>>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==a){for(e=this.length-1;e>=0;e--)this.words[e+a]=this.words[e];for(e=0;e<a;e++)this.words[e]=0;this.length+=a}return this.strip()},i.prototype.ishln=function(t){return n(0===this.negative),this.iushln(t)},i.prototype.iushrn=function(t,e,r){var a;n(\"number\"==typeof t&&t>=0),a=e?(e-e%26)/26:0;var i=t%26,o=Math.min((t-i)/26,this.length),s=67108863^67108863>>>i<<i,l=r;if(a-=o,a=Math.max(0,a),l){for(var c=0;c<o;c++)l.words[c]=this.words[c];l.length=o}if(0===o);else if(this.length>o)for(this.length-=o,c=0;c<this.length;c++)this.words[c]=this.words[c+o];else this.words[0]=0,this.length=1;var u=0;for(c=this.length-1;c>=0&&(0!==u||c>=a);c--){var h=0|this.words[c];this.words[c]=u<<26-i|h>>>i,u=h&s}return l&&0!==u&&(l.words[l.length++]=u),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},i.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},i.prototype.shln=function(t){return this.clone().ishln(t)},i.prototype.ushln=function(t){return this.clone().iushln(t)},i.prototype.shrn=function(t){return this.clone().ishrn(t)},i.prototype.ushrn=function(t){return this.clone().iushrn(t)},i.prototype.testn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,a=1<<e;return!(this.length<=r)&&!!(this.words[r]&a)},i.prototype.imaskn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,\"imaskn works only with positive numbers\"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var a=67108863^67108863>>>e<<e;this.words[this.length-1]&=a}return this.strip()},i.prototype.maskn=function(t){return this.clone().imaskn(t)},i.prototype.iaddn=function(t){return n(\"number\"==typeof t),n(t<67108864),t<0?this.isubn(-t):0!==this.negative?1===this.length&&(0|this.words[0])<t?(this.words[0]=t-(0|this.words[0]),this.negative=0,this):(this.negative=0,this.isubn(t),this.negative=1,this):this._iaddn(t)},i.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},i.prototype.isubn=function(t){if(n(\"number\"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},i.prototype.addn=function(t){return this.clone().iaddn(t)},i.prototype.subn=function(t){return this.clone().isubn(t)},i.prototype.iabs=function(){return this.negative=0,this},i.prototype.abs=function(){return this.clone().iabs()},i.prototype._ishlnsubmul=function(t,e,r){var a,i,o=t.length+r;this._expand(o);var s=0;for(a=0;a<t.length;a++){i=(0|this.words[a+r])+s;var l=(0|t.words[a])*e;s=((i-=67108863&l)>>26)-(l/67108864|0),this.words[a+r]=67108863&i}for(;a<this.length-r;a++)s=(i=(0|this.words[a+r])+s)>>26,this.words[a+r]=67108863&i;if(0===s)return this.strip();for(n(-1===s),s=0,a=0;a<this.length;a++)s=(i=-(0|this.words[a])+s)>>26,this.words[a]=67108863&i;return this.negative=1,this.strip()},i.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),a=t,o=0|a.words[a.length-1];0!==(r=26-this._countBits(o))&&(a=a.ushln(r),n.iushln(r),o=0|a.words[a.length-1]);var s,l=n.length-a.length;if(\"mod\"!==e){(s=new i(null)).length=l+1,s.words=new Array(s.length);for(var c=0;c<s.length;c++)s.words[c]=0}var u=n.clone()._ishlnsubmul(a,1,l);0===u.negative&&(n=u,s&&(s.words[l]=1));for(var h=l-1;h>=0;h--){var f=67108864*(0|n.words[a.length+h])+(0|n.words[a.length+h-1]);for(f=Math.min(f/o|0,67108863),n._ishlnsubmul(a,f,h);0!==n.negative;)f--,n.negative=0,n._ishlnsubmul(a,1,h),n.isZero()||(n.negative^=1);s&&(s.words[h]=f)}return s&&s.strip(),n.strip(),\"div\"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},i.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new i(0),mod:new i(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),\"mod\"!==e&&(a=s.div.neg()),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:a,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),\"mod\"!==e&&(a=s.div.neg()),{div:a,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new i(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new i(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new i(this.modn(t.words[0]))}:this._wordDiv(t,e);var a,o,s},i.prototype.div=function(t){return this.divmod(t,\"div\",!1).div},i.prototype.mod=function(t){return this.divmod(t,\"mod\",!1).mod},i.prototype.umod=function(t){return this.divmod(t,\"mod\",!0).mod},i.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),a=t.andln(1),i=r.cmp(n);return i<0||1===a&&0===i?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},i.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,a=this.length-1;a>=0;a--)r=(e*r+(0|this.words[a]))%t;return r},i.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var a=(0|this.words[r])+67108864*e;this.words[r]=a/t|0,e=a%t}return this.strip()},i.prototype.divn=function(t){return this.clone().idivn(t)},i.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var a=new i(1),o=new i(0),s=new i(0),l=new i(1),c=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++c;for(var u=r.clone(),h=e.clone();!e.isZero();){for(var f=0,p=1;0==(e.words[0]&p)&&f<26;++f,p<<=1);if(f>0)for(e.iushrn(f);f-- >0;)(a.isOdd()||o.isOdd())&&(a.iadd(u),o.isub(h)),a.iushrn(1),o.iushrn(1);for(var d=0,g=1;0==(r.words[0]&g)&&d<26;++d,g<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(u),l.isub(h)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),a.isub(s),o.isub(l)):(r.isub(e),s.isub(a),l.isub(o))}return{a:s,b:l,gcd:r.iushln(c)}},i.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var a,o=new i(1),s=new i(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var c=0,u=1;0==(e.words[0]&u)&&c<26;++c,u<<=1);if(c>0)for(e.iushrn(c);c-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var h=0,f=1;0==(r.words[0]&f)&&h<26;++h,f<<=1);if(h>0)for(r.iushrn(h);h-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(a=0===e.cmpn(1)?o:s).cmpn(0)<0&&a.iadd(t),a},i.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var a=e.cmp(r);if(a<0){var i=e;e=r,r=i}else if(0===a||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},i.prototype.invm=function(t){return this.egcd(t).a.umod(t)},i.prototype.isEven=function(){return 0==(1&this.words[0])},i.prototype.isOdd=function(){return 1==(1&this.words[0])},i.prototype.andln=function(t){return this.words[0]&t},i.prototype.bincn=function(t){n(\"number\"==typeof t);var e=t%26,r=(t-e)/26,a=1<<e;if(this.length<=r)return this._expand(r+1),this.words[r]|=a,this;for(var i=a,o=r;0!==i&&o<this.length;o++){var s=0|this.words[o];i=(s+=i)>>>26,s&=67108863,this.words[o]=s}return 0!==i&&(this.words[o]=i,this.length++),this},i.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},i.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,\"Number is too big\");var a=0|this.words[0];e=a===t?0:a<t?-1:1}return 0!==this.negative?0|-e:e},i.prototype.cmp=function(t){if(0!==this.negative&&0===t.negative)return-1;if(0===this.negative&&0!==t.negative)return 1;var e=this.ucmp(t);return 0!==this.negative?0|-e:e},i.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=0|this.words[r],a=0|t.words[r];if(n!==a){n<a?e=-1:n>a&&(e=1);break}}return e},i.prototype.gtn=function(t){return 1===this.cmpn(t)},i.prototype.gt=function(t){return 1===this.cmp(t)},i.prototype.gten=function(t){return this.cmpn(t)>=0},i.prototype.gte=function(t){return this.cmp(t)>=0},i.prototype.ltn=function(t){return-1===this.cmpn(t)},i.prototype.lt=function(t){return-1===this.cmp(t)},i.prototype.lten=function(t){return this.cmpn(t)<=0},i.prototype.lte=function(t){return this.cmp(t)<=0},i.prototype.eqn=function(t){return 0===this.cmpn(t)},i.prototype.eq=function(t){return 0===this.cmp(t)},i.red=function(t){return new w(t)},i.prototype.toRed=function(t){return n(!this.red,\"Already a number in reduction context\"),n(0===this.negative,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},i.prototype.fromRed=function(){return n(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},i.prototype._forceRed=function(t){return this.red=t,this},i.prototype.forceRed=function(t){return n(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},i.prototype.redAdd=function(t){return n(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},i.prototype.redIAdd=function(t){return n(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},i.prototype.redSub=function(t){return n(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},i.prototype.redISub=function(t){return n(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},i.prototype.redShl=function(t){return n(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},i.prototype.redMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},i.prototype.redIMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},i.prototype.redSqr=function(){return n(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},i.prototype.redISqr=function(){return n(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},i.prototype.redSqrt=function(){return n(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},i.prototype.redInvm=function(){return n(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},i.prototype.redNeg=function(){return n(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},i.prototype.redPow=function(t){return n(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var v={k256:null,p224:null,p192:null,p25519:null};function m(t,e){this.name=t,this.p=new i(e,16),this.n=this.p.bitLength(),this.k=new i(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function y(){m.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f\")}function x(){m.call(this,\"p224\",\"ffffffff ffffffff ffffffff ffffffff 00000000 00000000 00000001\")}function b(){m.call(this,\"p192\",\"ffffffff ffffffff ffffffff fffffffe ffffffff ffffffff\")}function _(){m.call(this,\"25519\",\"7fffffffffffffff ffffffffffffffff ffffffffffffffff ffffffffffffffed\")}function w(t){if(\"string\"==typeof t){var e=i._prime(t);this.m=e.p,this.prime=e}else n(t.gtn(1),\"modulus must be greater than 1\"),this.m=t,this.prime=null}function k(t){w.call(this,t),this.shift=this.m.bitLength(),this.shift%26!=0&&(this.shift+=26-this.shift%26),this.r=new i(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}m.prototype._tmp=function(){var t=new i(null);return t.words=new Array(Math.ceil(this.n/13)),t},m.prototype.ireduce=function(t){var e,r=t;do{this.split(r,this.tmp),e=(r=(r=this.imulK(r)).iadd(this.tmp)).bitLength()}while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):r.strip(),r},m.prototype.split=function(t,e){t.iushrn(this.n,0,e)},m.prototype.imulK=function(t){return t.imul(this.k)},a(y,m),y.prototype.split=function(t,e){for(var r=Math.min(t.length,9),n=0;n<r;n++)e.words[n]=t.words[n];if(e.length=r,t.length<=9)return t.words[0]=0,void(t.length=1);var a=t.words[9];for(e.words[e.length++]=4194303&a,n=10;n<t.length;n++){var i=0|t.words[n];t.words[n-10]=(4194303&i)<<4|a>>>22,a=i}a>>>=22,t.words[n-10]=a,0===a&&t.length>10?t.length-=10:t.length-=9},y.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e=0,r=0;r<t.length;r++){var n=0|t.words[r];e+=977*n,t.words[r]=67108863&e,e=64*n+(e/67108864|0)}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},a(x,m),a(b,m),a(_,m),_.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*(0|t.words[r])+e,a=67108863&n;n>>>=26,t.words[r]=a,e=n}return 0!==e&&(t.words[t.length++]=e),t},i._prime=function(t){if(v[t])return v[t];var e;if(\"k256\"===t)e=new y;else if(\"p224\"===t)e=new x;else if(\"p192\"===t)e=new b;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);e=new _}return v[t]=e,e},w.prototype._verify1=function(t){n(0===t.negative,\"red works only with positives\"),n(t.red,\"red works only with red numbers\")},w.prototype._verify2=function(t,e){n(0==(t.negative|e.negative),\"red works only with positives\"),n(t.red&&t.red===e.red,\"red works only with red numbers\")},w.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.umod(this.m)._forceRed(this)},w.prototype.neg=function(t){return t.isZero()?t.clone():this.m.sub(t)._forceRed(this)},w.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},w.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},w.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},w.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},w.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.ushln(e))},w.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},w.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},w.prototype.isqr=function(t){return this.imul(t,t.clone())},w.prototype.sqr=function(t){return this.mul(t,t)},w.prototype.sqrt=function(t){if(t.isZero())return t.clone();var e=this.m.andln(3);if(n(e%2==1),3===e){var r=this.m.add(new i(1)).iushrn(2);return this.pow(t,r)}for(var a=this.m.subn(1),o=0;!a.isZero()&&0===a.andln(1);)o++,a.iushrn(1);n(!a.isZero());var s=new i(1).toRed(this),l=s.redNeg(),c=this.m.subn(1).iushrn(1),u=this.m.bitLength();for(u=new i(2*u*u).toRed(this);0!==this.pow(u,c).cmp(l);)u.redIAdd(l);for(var h=this.pow(u,a),f=this.pow(t,a.addn(1).iushrn(1)),p=this.pow(t,a),d=o;0!==p.cmp(s);){for(var g=p,v=0;0!==g.cmp(s);v++)g=g.redSqr();n(v<d);var m=this.pow(h,new i(1).iushln(d-v-1));f=f.redMul(m),h=m.redSqr(),p=p.redMul(h),d=v}return f},w.prototype.invm=function(t){var e=t._invmp(this.m);return 0!==e.negative?(e.negative=0,this.imod(e).redNeg()):this.imod(e)},w.prototype.pow=function(t,e){if(e.isZero())return new i(1).toRed(this);if(0===e.cmpn(1))return t.clone();var r=new Array(16);r[0]=new i(1).toRed(this),r[1]=t;for(var n=2;n<r.length;n++)r[n]=this.mul(r[n-1],t);var a=r[0],o=0,s=0,l=e.bitLength()%26;for(0===l&&(l=26),n=e.length-1;n>=0;n--){for(var c=e.words[n],u=l-1;u>=0;u--){var h=c>>u&1;a!==r[0]&&(a=this.sqr(a)),0!==h||0!==o?(o<<=1,o|=h,(4===++s||0===n&&0===u)&&(a=this.mul(a,r[o]),s=0,o=0)):s=0}l=26}return a},w.prototype.convertTo=function(t){var e=t.umod(this.m);return e===t?e.clone():e},w.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},i.mont=function(t){return new k(t)},a(k,w),k.prototype.convertTo=function(t){return this.imod(t.ushln(this.shift))},k.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},k.prototype.imul=function(t,e){if(t.isZero()||e.isZero())return t.words[0]=0,t.length=1,t;var r=t.imul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),a=r.isub(n).iushrn(this.shift),i=a;return a.cmp(this.m)>=0?i=a.isub(this.m):a.cmpn(0)<0&&(i=a.iadd(this.m)),i._forceRed(this)},k.prototype.mul=function(t,e){if(t.isZero()||e.isZero())return new i(0)._forceRed(this);var r=t.mul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),a=r.isub(n).iushrn(this.shift),o=a;return a.cmp(this.m)>=0?o=a.isub(this.m):a.cmpn(0)<0&&(o=a.iadd(this.m)),o._forceRed(this)},k.prototype.invm=function(t){return this.imod(t._invmp(this.m).mul(this.r2))._forceRed(this)}}(\"undefined\"==typeof e||e,this)},{buffer:105}],97:[function(t,e,r){\"use strict\";e.exports=function(t){var e,r,n,a=t.length,i=0;for(e=0;e<a;++e)i+=t[e].length;var o=new Array(i),s=0;for(e=0;e<a;++e){var l=t[e],c=l.length;for(r=0;r<c;++r){var u=o[s++]=new Array(c-1),h=0;for(n=0;n<c;++n)n!==r&&(u[h++]=l[n]);if(1&r){var f=u[1];u[1]=u[0],u[0]=f}}}return o}},{}],98:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){switch(arguments.length){case 1:return n=[],c(a=t,a,u,!0),n;case 2:return\"function\"==typeof e?c(t,t,e,!0):function(t,e){return n=[],c(t,e,u,!1),n}(t,e);case 3:return c(t,e,r,!1);default:throw new Error(\"box-intersect: Invalid arguments\")}var a};var n,a=t(\"typedarray-pool\"),i=t(\"./lib/sweep\"),o=t(\"./lib/intersect\");function s(t,e){for(var r=0;r<t;++r)if(!(e[r]<=e[r+t]))return!0;return!1}function l(t,e,r,n){for(var a=0,i=0,o=0,l=t.length;o<l;++o){var c=t[o];if(!s(e,c)){for(var u=0;u<2*e;++u)r[a++]=c[u];n[i++]=o}}return i}function c(t,e,r,n){var s=t.length,c=e.length;if(!(s<=0||c<=0)){var u=t[0].length>>>1;if(!(u<=0)){var h,f=a.mallocDouble(2*u*s),p=a.mallocInt32(s);if((s=l(t,u,f,p))>0){if(1===u&&n)i.init(s),h=i.sweepComplete(u,r,0,s,f,p,0,s,f,p);else{var d=a.mallocDouble(2*u*c),g=a.mallocInt32(c);(c=l(e,u,d,g))>0&&(i.init(s+c),h=1===u?i.sweepBipartite(u,r,0,s,f,p,0,c,d,g):o(u,r,n,s,f,p,c,d,g),a.free(d),a.free(g))}a.free(f),a.free(p)}return h}}}function u(t,e){n.push([t,e])}},{\"./lib/intersect\":100,\"./lib/sweep\":104,\"typedarray-pool\":544}],99:[function(t,e,r){\"use strict\";var n=\"d\",a=\"ax\",i=\"vv\",o=\"fp\",s=\"es\",l=\"rs\",c=\"re\",u=\"rb\",h=\"ri\",f=\"rp\",p=\"bs\",d=\"be\",g=\"bb\",v=\"bi\",m=\"bp\",y=\"rv\",x=\"Q\",b=[n,a,i,l,c,u,h,p,d,g,v];function _(t){var e=\"bruteForce\"+(t?\"Full\":\"Partial\"),r=[],_=b.slice();t||_.splice(3,0,o);var w=[\"function \"+e+\"(\"+_.join()+\"){\"];function k(e,o){var _=function(t,e,r){var o=\"bruteForce\"+(t?\"Red\":\"Blue\")+(e?\"Flip\":\"\")+(r?\"Full\":\"\"),_=[\"function \",o,\"(\",b.join(),\"){\",\"var \",s,\"=2*\",n,\";\"],w=\"for(var i=\"+l+\",\"+f+\"=\"+s+\"*\"+l+\";i<\"+c+\";++i,\"+f+\"+=\"+s+\"){var x0=\"+u+\"[\"+a+\"+\"+f+\"],x1=\"+u+\"[\"+a+\"+\"+f+\"+\"+n+\"],xi=\"+h+\"[i];\",k=\"for(var j=\"+p+\",\"+m+\"=\"+s+\"*\"+p+\";j<\"+d+\";++j,\"+m+\"+=\"+s+\"){var y0=\"+g+\"[\"+a+\"+\"+m+\"],\"+(r?\"y1=\"+g+\"[\"+a+\"+\"+m+\"+\"+n+\"],\":\"\")+\"yi=\"+v+\"[j];\";return t?_.push(w,x,\":\",k):_.push(k,x,\":\",w),r?_.push(\"if(y1<x0||x1<y0)continue;\"):e?_.push(\"if(y0<=x0||x1<y0)continue;\"):_.push(\"if(y0<x0||x1<y0)continue;\"),_.push(\"for(var k=\"+a+\"+1;k<\"+n+\";++k){var r0=\"+u+\"[k+\"+f+\"],r1=\"+u+\"[k+\"+n+\"+\"+f+\"],b0=\"+g+\"[k+\"+m+\"],b1=\"+g+\"[k+\"+n+\"+\"+m+\"];if(r1<b0||b1<r0)continue \"+x+\";}var \"+y+\"=\"+i+\"(\"),e?_.push(\"yi,xi\"):_.push(\"xi,yi\"),_.push(\");if(\"+y+\"!==void 0)return \"+y+\";}}}\"),{name:o,code:_.join(\"\")}}(e,o,t);r.push(_.code),w.push(\"return \"+_.name+\"(\"+b.join()+\");\")}w.push(\"if(\"+c+\"-\"+l+\">\"+d+\"-\"+p+\"){\"),t?(k(!0,!1),w.push(\"}else{\"),k(!1,!1)):(w.push(\"if(\"+o+\"){\"),k(!0,!0),w.push(\"}else{\"),k(!0,!1),w.push(\"}}else{if(\"+o+\"){\"),k(!1,!0),w.push(\"}else{\"),k(!1,!1),w.push(\"}\")),w.push(\"}}return \"+e);var T=r.join(\"\")+w.join(\"\");return new Function(T)()}r.partial=_(!1),r.full=_(!0)},{}],100:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,i,u,S,E,L,C){!function(t,e){var r=8*a.log2(e+1)*(t+1)|0,i=a.nextPow2(b*r);w.length<i&&(n.free(w),w=n.mallocInt32(i));var o=a.nextPow2(_*r);k<o&&(n.free(k),k=n.mallocDouble(o))}(t,i+E);var P,O=0,z=2*t;T(O++,0,0,i,0,E,r?16:0,-1/0,1/0),r||T(O++,0,0,E,0,i,1,-1/0,1/0);for(;O>0;){var I=(O-=1)*b,D=w[I],R=w[I+1],F=w[I+2],B=w[I+3],N=w[I+4],j=w[I+5],V=O*_,U=k[V],q=k[V+1],H=1&j,G=!!(16&j),Y=u,W=S,X=L,Z=C;if(H&&(Y=L,W=C,X=u,Z=S),!(2&j&&(F=v(t,D,R,F,Y,W,q),R>=F)||4&j&&(R=m(t,D,R,F,Y,W,U))>=F)){var J=F-R,K=N-B;if(G){if(t*J*(J+K)<p){if(void 0!==(P=l.scanComplete(t,D,e,R,F,Y,W,B,N,X,Z)))return P;continue}}else{if(t*Math.min(J,K)<h){if(void 0!==(P=o(t,D,e,H,R,F,Y,W,B,N,X,Z)))return P;continue}if(t*J*K<f){if(void 0!==(P=l.scanBipartite(t,D,e,H,R,F,Y,W,B,N,X,Z)))return P;continue}}var Q=d(t,D,R,F,Y,W,U,q);if(R<Q)if(t*(Q-R)<h){if(void 0!==(P=s(t,D+1,e,R,Q,Y,W,B,N,X,Z)))return P}else if(D===t-2){if(void 0!==(P=H?l.sweepBipartite(t,e,B,N,X,Z,R,Q,Y,W):l.sweepBipartite(t,e,R,Q,Y,W,B,N,X,Z)))return P}else T(O++,D+1,R,Q,B,N,H,-1/0,1/0),T(O++,D+1,B,N,R,Q,1^H,-1/0,1/0);if(Q<F){var $=c(t,D,B,N,X,Z),tt=X[z*$+D],et=g(t,D,$,N,X,Z,tt);if(et<N&&T(O++,D,Q,F,et,N,(4|H)+(G?16:0),tt,q),B<$&&T(O++,D,Q,F,B,$,(2|H)+(G?16:0),U,tt),$+1===et){if(void 0!==(P=G?A(t,D,e,Q,F,Y,W,$,X,Z[$]):M(t,D,e,H,Q,F,Y,W,$,X,Z[$])))return P}else if($<et){var rt;if(G){if(rt=y(t,D,Q,F,Y,W,tt),Q<rt){var nt=g(t,D,Q,rt,Y,W,tt);if(D===t-2){if(Q<nt&&void 0!==(P=l.sweepComplete(t,e,Q,nt,Y,W,$,et,X,Z)))return P;if(nt<rt&&void 0!==(P=l.sweepBipartite(t,e,nt,rt,Y,W,$,et,X,Z)))return P}else Q<nt&&T(O++,D+1,Q,nt,$,et,16,-1/0,1/0),nt<rt&&(T(O++,D+1,nt,rt,$,et,0,-1/0,1/0),T(O++,D+1,$,et,nt,rt,1,-1/0,1/0))}}else rt=H?x(t,D,Q,F,Y,W,tt):y(t,D,Q,F,Y,W,tt),Q<rt&&(D===t-2?P=H?l.sweepBipartite(t,e,$,et,X,Z,Q,rt,Y,W):l.sweepBipartite(t,e,Q,rt,Y,W,$,et,X,Z):(T(O++,D+1,Q,rt,$,et,H,-1/0,1/0),T(O++,D+1,$,et,Q,rt,1^H,-1/0,1/0)))}}}}};var n=t(\"typedarray-pool\"),a=t(\"bit-twiddle\"),i=t(\"./brute\"),o=i.partial,s=i.full,l=t(\"./sweep\"),c=t(\"./median\"),u=t(\"./partition\"),h=128,f=1<<22,p=1<<22,d=u(\"!(lo>=p0)&&!(p1>=hi)\",[\"p0\",\"p1\"]),g=u(\"lo===p0\",[\"p0\"]),v=u(\"lo<p0\",[\"p0\"]),m=u(\"hi<=p0\",[\"p0\"]),y=u(\"lo<=p0&&p0<=hi\",[\"p0\"]),x=u(\"lo<p0&&p0<=hi\",[\"p0\"]),b=6,_=2,w=n.mallocInt32(1024),k=n.mallocDouble(1024);function T(t,e,r,n,a,i,o,s,l){var c=b*t;w[c]=e,w[c+1]=r,w[c+2]=n,w[c+3]=a,w[c+4]=i,w[c+5]=o;var u=_*t;k[u]=s,k[u+1]=l}function M(t,e,r,n,a,i,o,s,l,c,u){var h=2*t,f=l*h,p=c[f+e];t:for(var d=a,g=a*h;d<i;++d,g+=h){var v=o[g+e],m=o[g+e+t];if(!(p<v||m<p)&&(!n||p!==v)){for(var y,x=s[d],b=e+1;b<t;++b){v=o[g+b],m=o[g+b+t];var _=c[f+b],w=c[f+b+t];if(m<_||w<v)continue t}if(void 0!==(y=n?r(u,x):r(x,u)))return y}}}function A(t,e,r,n,a,i,o,s,l,c){var u=2*t,h=s*u,f=l[h+e];t:for(var p=n,d=n*u;p<a;++p,d+=u){var g=o[p];if(g!==c){var v=i[d+e],m=i[d+e+t];if(!(f<v||m<f)){for(var y=e+1;y<t;++y){v=i[d+y],m=i[d+y+t];var x=l[h+y],b=l[h+y+t];if(m<x||b<v)continue t}var _=r(g,c);if(void 0!==_)return _}}}}},{\"./brute\":99,\"./median\":101,\"./partition\":102,\"./sweep\":104,\"bit-twiddle\":94,\"typedarray-pool\":544}],101:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,o,s,l){if(o<=r+1)return r;var c=r,u=o,h=o+r>>>1,f=2*t,p=h,d=s[f*h+e];for(;c<u;){if(u-c<a){i(t,e,c,u,s,l),d=s[f*h+e];break}var g=u-c,v=Math.random()*g+c|0,m=s[f*v+e],y=Math.random()*g+c|0,x=s[f*y+e],b=Math.random()*g+c|0,_=s[f*b+e];m<=x?_>=x?(p=y,d=x):m>=_?(p=v,d=m):(p=b,d=_):x>=_?(p=y,d=x):_>=m?(p=v,d=m):(p=b,d=_);for(var w=f*(u-1),k=f*p,T=0;T<f;++T,++w,++k){var M=s[w];s[w]=s[k],s[k]=M}var A=l[u-1];l[u-1]=l[p],l[p]=A,p=n(t,e,c,u-1,s,l,d);for(var w=f*(u-1),k=f*p,T=0;T<f;++T,++w,++k){var M=s[w];s[w]=s[k],s[k]=M}var A=l[u-1];if(l[u-1]=l[p],l[p]=A,h<p){for(u=p-1;c<u&&s[f*(u-1)+e]===d;)u-=1;u+=1}else{if(!(p<h))break;for(c=p+1;c<u&&s[f*c+e]===d;)c+=1}}return n(t,e,r,h,s,l,s[f*h+e])};var n=t(\"./partition\")(\"lo<p0\",[\"p0\"]),a=8;function i(t,e,r,n,a,i){for(var o=2*t,s=o*(r+1)+e,l=r+1;l<n;++l,s+=o)for(var c=a[s],u=l,h=o*(l-1);u>r&&a[h+e]>c;--u,h-=o){for(var f=h,p=h+o,d=0;d<o;++d,++f,++p){var g=a[f];a[f]=a[p],a[p]=g}var v=i[u];i[u]=i[u-1],i[u-1]=v}}},{\"./partition\":102}],102:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=\"abcdef\".split(\"\").concat(e),a=[];t.indexOf(\"lo\")>=0&&a.push(\"lo=e[k+n]\");t.indexOf(\"hi\")>=0&&a.push(\"hi=e[k+o]\");return r.push(n.replace(\"_\",a.join()).replace(\"$\",t)),Function.apply(void 0,r)};var n=\"for(var j=2*a,k=j*c,l=k,m=c,n=b,o=a+b,p=c;d>p;++p,k+=j){var _;if($)if(m===p)m+=1,l+=j;else{for(var s=0;j>s;++s){var t=e[k+s];e[k+s]=e[l],e[l++]=t}var u=f[p];f[p]=f[m],f[m++]=u}}return m\"},{}],103:[function(t,e,r){\"use strict\";e.exports=function(t,e){e<=4*n?a(0,e-1,t):function t(e,r,h){var f=(r-e+1)/6|0,p=e+f,d=r-f,g=e+r>>1,v=g-f,m=g+f,y=p,x=v,b=g,_=m,w=d,k=e+1,T=r-1,M=0;c(y,x,h)&&(M=y,y=x,x=M);c(_,w,h)&&(M=_,_=w,w=M);c(y,b,h)&&(M=y,y=b,b=M);c(x,b,h)&&(M=x,x=b,b=M);c(y,_,h)&&(M=y,y=_,_=M);c(b,_,h)&&(M=b,b=_,_=M);c(x,w,h)&&(M=x,x=w,w=M);c(x,b,h)&&(M=x,x=b,b=M);c(_,w,h)&&(M=_,_=w,w=M);var A=h[2*x];var S=h[2*x+1];var E=h[2*_];var L=h[2*_+1];var C=2*y;var P=2*b;var O=2*w;var z=2*p;var I=2*g;var D=2*d;for(var R=0;R<2;++R){var F=h[C+R],B=h[P+R],N=h[O+R];h[z+R]=F,h[I+R]=B,h[D+R]=N}o(v,e,h);o(m,r,h);for(var j=k;j<=T;++j)if(u(j,A,S,h))j!==k&&i(j,k,h),++k;else if(!u(j,E,L,h))for(;;){if(u(T,E,L,h)){u(T,A,S,h)?(s(j,k,T,h),++k,--T):(i(j,T,h),--T);break}if(--T<j)break}l(e,k-1,A,S,h);l(r,T+1,E,L,h);k-2-e<=n?a(e,k-2,h):t(e,k-2,h);r-(T+2)<=n?a(T+2,r,h):t(T+2,r,h);T-k<=n?a(k,T,h):t(k,T,h)}(0,e-1,t)};var n=32;function a(t,e,r){for(var n=2*(t+1),a=t+1;a<=e;++a){for(var i=r[n++],o=r[n++],s=a,l=n-2;s-- >t;){var c=r[l-2],u=r[l-1];if(c<i)break;if(c===i&&u<o)break;r[l]=c,r[l+1]=u,l-=2}r[l]=i,r[l+1]=o}}function i(t,e,r){e*=2;var n=r[t*=2],a=r[t+1];r[t]=r[e],r[t+1]=r[e+1],r[e]=n,r[e+1]=a}function o(t,e,r){e*=2,r[t*=2]=r[e],r[t+1]=r[e+1]}function s(t,e,r,n){e*=2,r*=2;var a=n[t*=2],i=n[t+1];n[t]=n[e],n[t+1]=n[e+1],n[e]=n[r],n[e+1]=n[r+1],n[r]=a,n[r+1]=i}function l(t,e,r,n,a){e*=2,a[t*=2]=a[e],a[e]=r,a[t+1]=a[e+1],a[e+1]=n}function c(t,e,r){e*=2;var n=r[t*=2],a=r[e];return!(n<a)&&(n!==a||r[t+1]>r[e+1])}function u(t,e,r,n){var a=n[t*=2];return a<e||a===e&&n[t+1]<r}},{}],104:[function(t,e,r){\"use strict\";e.exports={init:function(t){var e=a.nextPow2(t);s.length<e&&(n.free(s),s=n.mallocInt32(e));l.length<e&&(n.free(l),l=n.mallocInt32(e));c.length<e&&(n.free(c),c=n.mallocInt32(e));u.length<e&&(n.free(u),u=n.mallocInt32(e));h.length<e&&(n.free(h),h=n.mallocInt32(e));f.length<e&&(n.free(f),f=n.mallocInt32(e));var r=8*e;p.length<r&&(n.free(p),p=n.mallocDouble(r))},sweepBipartite:function(t,e,r,n,a,h,f,v,m,y){for(var x=0,b=2*t,_=t-1,w=b-1,k=r;k<n;++k){var T=h[k],M=b*k;p[x++]=a[M+_],p[x++]=-(T+1),p[x++]=a[M+w],p[x++]=T}for(var k=f;k<v;++k){var T=y[k]+o,A=b*k;p[x++]=m[A+_],p[x++]=-T,p[x++]=m[A+w],p[x++]=T}var S=x>>>1;i(p,S);for(var E=0,L=0,k=0;k<S;++k){var C=0|p[2*k+1];if(C>=o)d(c,u,L--,C=C-o|0);else if(C>=0)d(s,l,E--,C);else if(C<=-o){C=-C-o|0;for(var P=0;P<E;++P){var O=e(s[P],C);if(void 0!==O)return O}g(c,u,L++,C)}else{C=-C-1|0;for(var P=0;P<L;++P){var O=e(C,c[P]);if(void 0!==O)return O}g(s,l,E++,C)}}},sweepComplete:function(t,e,r,n,a,o,v,m,y,x){for(var b=0,_=2*t,w=t-1,k=_-1,T=r;T<n;++T){var M=o[T]+1<<1,A=_*T;p[b++]=a[A+w],p[b++]=-M,p[b++]=a[A+k],p[b++]=M}for(var T=v;T<m;++T){var M=x[T]+1<<1,S=_*T;p[b++]=y[S+w],p[b++]=1|-M,p[b++]=y[S+k],p[b++]=1|M}var E=b>>>1;i(p,E);for(var L=0,C=0,P=0,T=0;T<E;++T){var O=0|p[2*T+1],z=1&O;if(T<E-1&&O>>1==p[2*T+3]>>1&&(z=2,T+=1),O<0){for(var I=-(O>>1)-1,D=0;D<P;++D){var R=e(h[D],I);if(void 0!==R)return R}if(0!==z)for(var D=0;D<L;++D){var R=e(s[D],I);if(void 0!==R)return R}if(1!==z)for(var D=0;D<C;++D){var R=e(c[D],I);if(void 0!==R)return R}0===z?g(s,l,L++,I):1===z?g(c,u,C++,I):2===z&&g(h,f,P++,I)}else{var I=(O>>1)-1;0===z?d(s,l,L--,I):1===z?d(c,u,C--,I):2===z&&d(h,f,P--,I)}}},scanBipartite:function(t,e,r,n,a,c,u,h,f,v,m,y){var x=0,b=2*t,_=e,w=e+t,k=1,T=1;n?T=o:k=o;for(var M=a;M<c;++M){var A=M+k,S=b*M;p[x++]=u[S+_],p[x++]=-A,p[x++]=u[S+w],p[x++]=A}for(var M=f;M<v;++M){var A=M+T,E=b*M;p[x++]=m[E+_],p[x++]=-A}var L=x>>>1;i(p,L);for(var C=0,M=0;M<L;++M){var P=0|p[2*M+1];if(P<0){var A=-P,O=!1;if(A>=o?(O=!n,A-=o):(O=!!n,A-=1),O)g(s,l,C++,A);else{var z=y[A],I=b*A,D=m[I+e+1],R=m[I+e+1+t];t:for(var F=0;F<C;++F){var B=s[F],N=b*B;if(!(R<u[N+e+1]||u[N+e+1+t]<D)){for(var j=e+2;j<t;++j)if(m[I+j+t]<u[N+j]||u[N+j+t]<m[I+j])continue t;var V,U=h[B];if(void 0!==(V=n?r(z,U):r(U,z)))return V}}}}else d(s,l,C--,P-k)}},scanComplete:function(t,e,r,n,a,l,c,u,h,f,d){for(var g=0,v=2*t,m=e,y=e+t,x=n;x<a;++x){var b=x+o,_=v*x;p[g++]=l[_+m],p[g++]=-b,p[g++]=l[_+y],p[g++]=b}for(var x=u;x<h;++x){var b=x+1,w=v*x;p[g++]=f[w+m],p[g++]=-b}var k=g>>>1;i(p,k);for(var T=0,x=0;x<k;++x){var M=0|p[2*x+1];if(M<0){var b=-M;if(b>=o)s[T++]=b-o;else{var A=d[b-=1],S=v*b,E=f[S+e+1],L=f[S+e+1+t];t:for(var C=0;C<T;++C){var P=s[C],O=c[P];if(O===A)break;var z=v*P;if(!(L<l[z+e+1]||l[z+e+1+t]<E)){for(var I=e+2;I<t;++I)if(f[S+I+t]<l[z+I]||l[z+I+t]<f[S+I])continue t;var D=r(O,A);if(void 0!==D)return D}}}}else{for(var b=M-o,C=T-1;C>=0;--C)if(s[C]===b){for(var I=C+1;I<T;++I)s[I-1]=s[I];break}--T}}}};var n=t(\"typedarray-pool\"),a=t(\"bit-twiddle\"),i=t(\"./sort\"),o=1<<28,s=n.mallocInt32(1024),l=n.mallocInt32(1024),c=n.mallocInt32(1024),u=n.mallocInt32(1024),h=n.mallocInt32(1024),f=n.mallocInt32(1024),p=n.mallocDouble(8192);function d(t,e,r,n){var a=e[n],i=t[r-1];t[a]=i,e[i]=a}function g(t,e,r,n){t[r]=n,e[n]=r}},{\"./sort\":103,\"bit-twiddle\":94,\"typedarray-pool\":544}],105:[function(t,e,r){},{}],106:[function(t,e,r){var n=Object.create||function(t){var e=function(){};return e.prototype=t,new e},a=Object.keys||function(t){var e=[];for(var r in t)Object.prototype.hasOwnProperty.call(t,r)&&e.push(r);return r},i=Function.prototype.bind||function(t){var e=this;return function(){return e.apply(t,arguments)}};function o(){this._events&&Object.prototype.hasOwnProperty.call(this,\"_events\")||(this._events=n(null),this._eventsCount=0),this._maxListeners=this._maxListeners||void 0}e.exports=o,o.EventEmitter=o,o.prototype._events=void 0,o.prototype._maxListeners=void 0;var s,l=10;try{var c={};Object.defineProperty&&Object.defineProperty(c,\"x\",{value:0}),s=0===c.x}catch(t){s=!1}function u(t){return void 0===t._maxListeners?o.defaultMaxListeners:t._maxListeners}function h(t,e,r,a){var i,o,s;if(\"function\"!=typeof r)throw new TypeError('\"listener\" argument must be a function');if((o=t._events)?(o.newListener&&(t.emit(\"newListener\",e,r.listener?r.listener:r),o=t._events),s=o[e]):(o=t._events=n(null),t._eventsCount=0),s){if(\"function\"==typeof s?s=o[e]=a?[r,s]:[s,r]:a?s.unshift(r):s.push(r),!s.warned&&(i=u(t))&&i>0&&s.length>i){s.warned=!0;var l=new Error(\"Possible EventEmitter memory leak detected. \"+s.length+' \"'+String(e)+'\" listeners added. Use emitter.setMaxListeners() to increase limit.');l.name=\"MaxListenersExceededWarning\",l.emitter=t,l.type=e,l.count=s.length,\"object\"==typeof console&&console.warn&&console.warn(\"%s: %s\",l.name,l.message)}}else s=o[e]=r,++t._eventsCount;return t}function f(){if(!this.fired)switch(this.target.removeListener(this.type,this.wrapFn),this.fired=!0,arguments.length){case 0:return this.listener.call(this.target);case 1:return this.listener.call(this.target,arguments[0]);case 2:return this.listener.call(this.target,arguments[0],arguments[1]);case 3:return this.listener.call(this.target,arguments[0],arguments[1],arguments[2]);default:for(var t=new Array(arguments.length),e=0;e<t.length;++e)t[e]=arguments[e];this.listener.apply(this.target,t)}}function p(t,e,r){var n={fired:!1,wrapFn:void 0,target:t,type:e,listener:r},a=i.call(f,n);return a.listener=r,n.wrapFn=a,a}function d(t,e,r){var n=t._events;if(!n)return[];var a=n[e];return a?\"function\"==typeof a?r?[a.listener||a]:[a]:r?function(t){for(var e=new Array(t.length),r=0;r<e.length;++r)e[r]=t[r].listener||t[r];return e}(a):v(a,a.length):[]}function g(t){var e=this._events;if(e){var r=e[t];if(\"function\"==typeof r)return 1;if(r)return r.length}return 0}function v(t,e){for(var r=new Array(e),n=0;n<e;++n)r[n]=t[n];return r}s?Object.defineProperty(o,\"defaultMaxListeners\",{enumerable:!0,get:function(){return l},set:function(t){if(\"number\"!=typeof t||t<0||t!=t)throw new TypeError('\"defaultMaxListeners\" must be a positive number');l=t}}):o.defaultMaxListeners=l,o.prototype.setMaxListeners=function(t){if(\"number\"!=typeof t||t<0||isNaN(t))throw new TypeError('\"n\" argument must be a positive number');return this._maxListeners=t,this},o.prototype.getMaxListeners=function(){return u(this)},o.prototype.emit=function(t){var e,r,n,a,i,o,s=\"error\"===t;if(o=this._events)s=s&&null==o.error;else if(!s)return!1;if(s){if(arguments.length>1&&(e=arguments[1]),e instanceof Error)throw e;var l=new Error('Unhandled \"error\" event. ('+e+\")\");throw l.context=e,l}if(!(r=o[t]))return!1;var c=\"function\"==typeof r;switch(n=arguments.length){case 1:!function(t,e,r){if(e)t.call(r);else for(var n=t.length,a=v(t,n),i=0;i<n;++i)a[i].call(r)}(r,c,this);break;case 2:!function(t,e,r,n){if(e)t.call(r,n);else for(var a=t.length,i=v(t,a),o=0;o<a;++o)i[o].call(r,n)}(r,c,this,arguments[1]);break;case 3:!function(t,e,r,n,a){if(e)t.call(r,n,a);else for(var i=t.length,o=v(t,i),s=0;s<i;++s)o[s].call(r,n,a)}(r,c,this,arguments[1],arguments[2]);break;case 4:!function(t,e,r,n,a,i){if(e)t.call(r,n,a,i);else for(var o=t.length,s=v(t,o),l=0;l<o;++l)s[l].call(r,n,a,i)}(r,c,this,arguments[1],arguments[2],arguments[3]);break;default:for(a=new Array(n-1),i=1;i<n;i++)a[i-1]=arguments[i];!function(t,e,r,n){if(e)t.apply(r,n);else for(var a=t.length,i=v(t,a),o=0;o<a;++o)i[o].apply(r,n)}(r,c,this,a)}return!0},o.prototype.addListener=function(t,e){return h(this,t,e,!1)},o.prototype.on=o.prototype.addListener,o.prototype.prependListener=function(t,e){return h(this,t,e,!0)},o.prototype.once=function(t,e){if(\"function\"!=typeof e)throw new TypeError('\"listener\" argument must be a function');return this.on(t,p(this,t,e)),this},o.prototype.prependOnceListener=function(t,e){if(\"function\"!=typeof e)throw new TypeError('\"listener\" argument must be a function');return this.prependListener(t,p(this,t,e)),this},o.prototype.removeListener=function(t,e){var r,a,i,o,s;if(\"function\"!=typeof e)throw new TypeError('\"listener\" argument must be a function');if(!(a=this._events))return this;if(!(r=a[t]))return this;if(r===e||r.listener===e)0==--this._eventsCount?this._events=n(null):(delete a[t],a.removeListener&&this.emit(\"removeListener\",t,r.listener||e));else if(\"function\"!=typeof r){for(i=-1,o=r.length-1;o>=0;o--)if(r[o]===e||r[o].listener===e){s=r[o].listener,i=o;break}if(i<0)return this;0===i?r.shift():function(t,e){for(var r=e,n=r+1,a=t.length;n<a;r+=1,n+=1)t[r]=t[n];t.pop()}(r,i),1===r.length&&(a[t]=r[0]),a.removeListener&&this.emit(\"removeListener\",t,s||e)}return this},o.prototype.removeAllListeners=function(t){var e,r,i;if(!(r=this._events))return this;if(!r.removeListener)return 0===arguments.length?(this._events=n(null),this._eventsCount=0):r[t]&&(0==--this._eventsCount?this._events=n(null):delete r[t]),this;if(0===arguments.length){var o,s=a(r);for(i=0;i<s.length;++i)\"removeListener\"!==(o=s[i])&&this.removeAllListeners(o);return this.removeAllListeners(\"removeListener\"),this._events=n(null),this._eventsCount=0,this}if(\"function\"==typeof(e=r[t]))this.removeListener(t,e);else if(e)for(i=e.length-1;i>=0;i--)this.removeListener(t,e[i]);return this},o.prototype.listeners=function(t){return d(this,t,!0)},o.prototype.rawListeners=function(t){return d(this,t,!1)},o.listenerCount=function(t,e){return\"function\"==typeof t.listenerCount?t.listenerCount(e):g.call(t,e)},o.prototype.listenerCount=g,o.prototype.eventNames=function(){return this._eventsCount>0?Reflect.ownKeys(this._events):[]}},{}],107:[function(t,e,r){(function(e){\"use strict\";var n=t(\"base64-js\"),a=t(\"ieee754\"),i=\"function\"==typeof Symbol&&\"function\"==typeof Symbol.for?Symbol.for(\"nodejs.util.inspect.custom\"):null;r.Buffer=e,r.SlowBuffer=function(t){+t!=t&&(t=0);return e.alloc(+t)},r.INSPECT_MAX_BYTES=50;var o=2147483647;function s(t){if(t>o)throw new RangeError('The value \"'+t+'\" is invalid for option \"size\"');var r=new Uint8Array(t);return Object.setPrototypeOf(r,e.prototype),r}function e(t,e,r){if(\"number\"==typeof t){if(\"string\"==typeof e)throw new TypeError('The \"string\" argument must be of type string. Received type number');return u(t)}return l(t,e,r)}function l(t,r,n){if(\"string\"==typeof t)return function(t,r){\"string\"==typeof r&&\"\"!==r||(r=\"utf8\");if(!e.isEncoding(r))throw new TypeError(\"Unknown encoding: \"+r);var n=0|p(t,r),a=s(n),i=a.write(t,r);i!==n&&(a=a.slice(0,i));return a}(t,r);if(ArrayBuffer.isView(t))return h(t);if(null==t)throw new TypeError(\"The first argument must be one of type string, Buffer, ArrayBuffer, Array, or Array-like Object. Received type \"+typeof t);if(j(t,ArrayBuffer)||t&&j(t.buffer,ArrayBuffer))return function(t,r,n){if(r<0||t.byteLength<r)throw new RangeError('\"offset\" is outside of buffer bounds');if(t.byteLength<r+(n||0))throw new RangeError('\"length\" is outside of buffer bounds');var a;a=void 0===r&&void 0===n?new Uint8Array(t):void 0===n?new Uint8Array(t,r):new Uint8Array(t,r,n);return Object.setPrototypeOf(a,e.prototype),a}(t,r,n);if(\"number\"==typeof t)throw new TypeError('The \"value\" argument must not be of type number. Received type number');var a=t.valueOf&&t.valueOf();if(null!=a&&a!==t)return e.from(a,r,n);var i=function(t){if(e.isBuffer(t)){var r=0|f(t.length),n=s(r);return 0===n.length?n:(t.copy(n,0,0,r),n)}if(void 0!==t.length)return\"number\"!=typeof t.length||V(t.length)?s(0):h(t);if(\"Buffer\"===t.type&&Array.isArray(t.data))return h(t.data)}(t);if(i)return i;if(\"undefined\"!=typeof Symbol&&null!=Symbol.toPrimitive&&\"function\"==typeof t[Symbol.toPrimitive])return e.from(t[Symbol.toPrimitive](\"string\"),r,n);throw new TypeError(\"The first argument must be one of type string, Buffer, ArrayBuffer, Array, or Array-like Object. Received type \"+typeof t)}function c(t){if(\"number\"!=typeof t)throw new TypeError('\"size\" argument must be of type number');if(t<0)throw new RangeError('The value \"'+t+'\" is invalid for option \"size\"')}function u(t){return c(t),s(t<0?0:0|f(t))}function h(t){for(var e=t.length<0?0:0|f(t.length),r=s(e),n=0;n<e;n+=1)r[n]=255&t[n];return r}function f(t){if(t>=o)throw new RangeError(\"Attempt to allocate Buffer larger than maximum size: 0x\"+o.toString(16)+\" bytes\");return 0|t}function p(t,r){if(e.isBuffer(t))return t.length;if(ArrayBuffer.isView(t)||j(t,ArrayBuffer))return t.byteLength;if(\"string\"!=typeof t)throw new TypeError('The \"string\" argument must be one of type string, Buffer, or ArrayBuffer. Received type '+typeof t);var n=t.length,a=arguments.length>2&&!0===arguments[2];if(!a&&0===n)return 0;for(var i=!1;;)switch(r){case\"ascii\":case\"latin1\":case\"binary\":return n;case\"utf8\":case\"utf-8\":return F(t).length;case\"ucs2\":case\"ucs-2\":case\"utf16le\":case\"utf-16le\":return 2*n;case\"hex\":return n>>>1;case\"base64\":return B(t).length;default:if(i)return a?-1:F(t).length;r=(\"\"+r).toLowerCase(),i=!0}}function d(t,e,r){var n=t[e];t[e]=t[r],t[r]=n}function g(t,r,n,a,i){if(0===t.length)return-1;if(\"string\"==typeof n?(a=n,n=0):n>2147483647?n=2147483647:n<-2147483648&&(n=-2147483648),V(n=+n)&&(n=i?0:t.length-1),n<0&&(n=t.length+n),n>=t.length){if(i)return-1;n=t.length-1}else if(n<0){if(!i)return-1;n=0}if(\"string\"==typeof r&&(r=e.from(r,a)),e.isBuffer(r))return 0===r.length?-1:v(t,r,n,a,i);if(\"number\"==typeof r)return r&=255,\"function\"==typeof Uint8Array.prototype.indexOf?i?Uint8Array.prototype.indexOf.call(t,r,n):Uint8Array.prototype.lastIndexOf.call(t,r,n):v(t,[r],n,a,i);throw new TypeError(\"val must be string, number or Buffer\")}function v(t,e,r,n,a){var i,o=1,s=t.length,l=e.length;if(void 0!==n&&(\"ucs2\"===(n=String(n).toLowerCase())||\"ucs-2\"===n||\"utf16le\"===n||\"utf-16le\"===n)){if(t.length<2||e.length<2)return-1;o=2,s/=2,l/=2,r/=2}function c(t,e){return 1===o?t[e]:t.readUInt16BE(e*o)}if(a){var u=-1;for(i=r;i<s;i++)if(c(t,i)===c(e,-1===u?0:i-u)){if(-1===u&&(u=i),i-u+1===l)return u*o}else-1!==u&&(i-=i-u),u=-1}else for(r+l>s&&(r=s-l),i=r;i>=0;i--){for(var h=!0,f=0;f<l;f++)if(c(t,i+f)!==c(e,f)){h=!1;break}if(h)return i}return-1}function m(t,e,r,n){r=Number(r)||0;var a=t.length-r;n?(n=Number(n))>a&&(n=a):n=a;var i=e.length;n>i/2&&(n=i/2);for(var o=0;o<n;++o){var s=parseInt(e.substr(2*o,2),16);if(V(s))return o;t[r+o]=s}return o}function y(t,e,r,n){return N(F(e,t.length-r),t,r,n)}function x(t,e,r,n){return N(function(t){for(var e=[],r=0;r<t.length;++r)e.push(255&t.charCodeAt(r));return e}(e),t,r,n)}function b(t,e,r,n){return x(t,e,r,n)}function _(t,e,r,n){return N(B(e),t,r,n)}function w(t,e,r,n){return N(function(t,e){for(var r,n,a,i=[],o=0;o<t.length&&!((e-=2)<0);++o)r=t.charCodeAt(o),n=r>>8,a=r%256,i.push(a),i.push(n);return i}(e,t.length-r),t,r,n)}function k(t,e,r){return 0===e&&r===t.length?n.fromByteArray(t):n.fromByteArray(t.slice(e,r))}function T(t,e,r){r=Math.min(t.length,r);for(var n=[],a=e;a<r;){var i,o,s,l,c=t[a],u=null,h=c>239?4:c>223?3:c>191?2:1;if(a+h<=r)switch(h){case 1:c<128&&(u=c);break;case 2:128==(192&(i=t[a+1]))&&(l=(31&c)<<6|63&i)>127&&(u=l);break;case 3:i=t[a+1],o=t[a+2],128==(192&i)&&128==(192&o)&&(l=(15&c)<<12|(63&i)<<6|63&o)>2047&&(l<55296||l>57343)&&(u=l);break;case 4:i=t[a+1],o=t[a+2],s=t[a+3],128==(192&i)&&128==(192&o)&&128==(192&s)&&(l=(15&c)<<18|(63&i)<<12|(63&o)<<6|63&s)>65535&&l<1114112&&(u=l)}null===u?(u=65533,h=1):u>65535&&(u-=65536,n.push(u>>>10&1023|55296),u=56320|1023&u),n.push(u),a+=h}return function(t){var e=t.length;if(e<=M)return String.fromCharCode.apply(String,t);var r=\"\",n=0;for(;n<e;)r+=String.fromCharCode.apply(String,t.slice(n,n+=M));return r}(n)}r.kMaxLength=o,e.TYPED_ARRAY_SUPPORT=function(){try{var t=new Uint8Array(1),e={foo:function(){return 42}};return Object.setPrototypeOf(e,Uint8Array.prototype),Object.setPrototypeOf(t,e),42===t.foo()}catch(t){return!1}}(),e.TYPED_ARRAY_SUPPORT||\"undefined\"==typeof console||\"function\"!=typeof console.error||console.error(\"This browser lacks typed array (Uint8Array) support which is required by `buffer` v5.x. Use `buffer` v4.x if you require old browser support.\"),Object.defineProperty(e.prototype,\"parent\",{enumerable:!0,get:function(){if(e.isBuffer(this))return this.buffer}}),Object.defineProperty(e.prototype,\"offset\",{enumerable:!0,get:function(){if(e.isBuffer(this))return this.byteOffset}}),\"undefined\"!=typeof Symbol&&null!=Symbol.species&&e[Symbol.species]===e&&Object.defineProperty(e,Symbol.species,{value:null,configurable:!0,enumerable:!1,writable:!1}),e.poolSize=8192,e.from=function(t,e,r){return l(t,e,r)},Object.setPrototypeOf(e.prototype,Uint8Array.prototype),Object.setPrototypeOf(e,Uint8Array),e.alloc=function(t,e,r){return function(t,e,r){return c(t),t<=0?s(t):void 0!==e?\"string\"==typeof r?s(t).fill(e,r):s(t).fill(e):s(t)}(t,e,r)},e.allocUnsafe=function(t){return u(t)},e.allocUnsafeSlow=function(t){return u(t)},e.isBuffer=function(t){return null!=t&&!0===t._isBuffer&&t!==e.prototype},e.compare=function(t,r){if(j(t,Uint8Array)&&(t=e.from(t,t.offset,t.byteLength)),j(r,Uint8Array)&&(r=e.from(r,r.offset,r.byteLength)),!e.isBuffer(t)||!e.isBuffer(r))throw new TypeError('The \"buf1\", \"buf2\" arguments must be one of type Buffer or Uint8Array');if(t===r)return 0;for(var n=t.length,a=r.length,i=0,o=Math.min(n,a);i<o;++i)if(t[i]!==r[i]){n=t[i],a=r[i];break}return n<a?-1:a<n?1:0},e.isEncoding=function(t){switch(String(t).toLowerCase()){case\"hex\":case\"utf8\":case\"utf-8\":case\"ascii\":case\"latin1\":case\"binary\":case\"base64\":case\"ucs2\":case\"ucs-2\":case\"utf16le\":case\"utf-16le\":return!0;default:return!1}},e.concat=function(t,r){if(!Array.isArray(t))throw new TypeError('\"list\" argument must be an Array of Buffers');if(0===t.length)return e.alloc(0);var n;if(void 0===r)for(r=0,n=0;n<t.length;++n)r+=t[n].length;var a=e.allocUnsafe(r),i=0;for(n=0;n<t.length;++n){var o=t[n];if(j(o,Uint8Array)&&(o=e.from(o)),!e.isBuffer(o))throw new TypeError('\"list\" argument must be an Array of Buffers');o.copy(a,i),i+=o.length}return a},e.byteLength=p,e.prototype._isBuffer=!0,e.prototype.swap16=function(){var t=this.length;if(t%2!=0)throw new RangeError(\"Buffer size must be a multiple of 16-bits\");for(var e=0;e<t;e+=2)d(this,e,e+1);return this},e.prototype.swap32=function(){var t=this.length;if(t%4!=0)throw new RangeError(\"Buffer size must be a multiple of 32-bits\");for(var e=0;e<t;e+=4)d(this,e,e+3),d(this,e+1,e+2);return this},e.prototype.swap64=function(){var t=this.length;if(t%8!=0)throw new RangeError(\"Buffer size must be a multiple of 64-bits\");for(var e=0;e<t;e+=8)d(this,e,e+7),d(this,e+1,e+6),d(this,e+2,e+5),d(this,e+3,e+4);return this},e.prototype.toString=function(){var t=this.length;return 0===t?\"\":0===arguments.length?T(this,0,t):function(t,e,r){var n=!1;if((void 0===e||e<0)&&(e=0),e>this.length)return\"\";if((void 0===r||r>this.length)&&(r=this.length),r<=0)return\"\";if((r>>>=0)<=(e>>>=0))return\"\";for(t||(t=\"utf8\");;)switch(t){case\"hex\":return E(this,e,r);case\"utf8\":case\"utf-8\":return T(this,e,r);case\"ascii\":return A(this,e,r);case\"latin1\":case\"binary\":return S(this,e,r);case\"base64\":return k(this,e,r);case\"ucs2\":case\"ucs-2\":case\"utf16le\":case\"utf-16le\":return L(this,e,r);default:if(n)throw new TypeError(\"Unknown encoding: \"+t);t=(t+\"\").toLowerCase(),n=!0}}.apply(this,arguments)},e.prototype.toLocaleString=e.prototype.toString,e.prototype.equals=function(t){if(!e.isBuffer(t))throw new TypeError(\"Argument must be a Buffer\");return this===t||0===e.compare(this,t)},e.prototype.inspect=function(){var t=\"\",e=r.INSPECT_MAX_BYTES;return t=this.toString(\"hex\",0,e).replace(/(.{2})/g,\"$1 \").trim(),this.length>e&&(t+=\" ... \"),\"<Buffer \"+t+\">\"},i&&(e.prototype[i]=e.prototype.inspect),e.prototype.compare=function(t,r,n,a,i){if(j(t,Uint8Array)&&(t=e.from(t,t.offset,t.byteLength)),!e.isBuffer(t))throw new TypeError('The \"target\" argument must be one of type Buffer or Uint8Array. Received type '+typeof t);if(void 0===r&&(r=0),void 0===n&&(n=t?t.length:0),void 0===a&&(a=0),void 0===i&&(i=this.length),r<0||n>t.length||a<0||i>this.length)throw new RangeError(\"out of range index\");if(a>=i&&r>=n)return 0;if(a>=i)return-1;if(r>=n)return 1;if(this===t)return 0;for(var o=(i>>>=0)-(a>>>=0),s=(n>>>=0)-(r>>>=0),l=Math.min(o,s),c=this.slice(a,i),u=t.slice(r,n),h=0;h<l;++h)if(c[h]!==u[h]){o=c[h],s=u[h];break}return o<s?-1:s<o?1:0},e.prototype.includes=function(t,e,r){return-1!==this.indexOf(t,e,r)},e.prototype.indexOf=function(t,e,r){return g(this,t,e,r,!0)},e.prototype.lastIndexOf=function(t,e,r){return g(this,t,e,r,!1)},e.prototype.write=function(t,e,r,n){if(void 0===e)n=\"utf8\",r=this.length,e=0;else if(void 0===r&&\"string\"==typeof e)n=e,r=this.length,e=0;else{if(!isFinite(e))throw new Error(\"Buffer.write(string, encoding, offset[, length]) is no longer supported\");e>>>=0,isFinite(r)?(r>>>=0,void 0===n&&(n=\"utf8\")):(n=r,r=void 0)}var a=this.length-e;if((void 0===r||r>a)&&(r=a),t.length>0&&(r<0||e<0)||e>this.length)throw new RangeError(\"Attempt to write outside buffer bounds\");n||(n=\"utf8\");for(var i=!1;;)switch(n){case\"hex\":return m(this,t,e,r);case\"utf8\":case\"utf-8\":return y(this,t,e,r);case\"ascii\":return x(this,t,e,r);case\"latin1\":case\"binary\":return b(this,t,e,r);case\"base64\":return _(this,t,e,r);case\"ucs2\":case\"ucs-2\":case\"utf16le\":case\"utf-16le\":return w(this,t,e,r);default:if(i)throw new TypeError(\"Unknown encoding: \"+n);n=(\"\"+n).toLowerCase(),i=!0}},e.prototype.toJSON=function(){return{type:\"Buffer\",data:Array.prototype.slice.call(this._arr||this,0)}};var M=4096;function A(t,e,r){var n=\"\";r=Math.min(t.length,r);for(var a=e;a<r;++a)n+=String.fromCharCode(127&t[a]);return n}function S(t,e,r){var n=\"\";r=Math.min(t.length,r);for(var a=e;a<r;++a)n+=String.fromCharCode(t[a]);return n}function E(t,e,r){var n=t.length;(!e||e<0)&&(e=0),(!r||r<0||r>n)&&(r=n);for(var a=\"\",i=e;i<r;++i)a+=R(t[i]);return a}function L(t,e,r){for(var n=t.slice(e,r),a=\"\",i=0;i<n.length;i+=2)a+=String.fromCharCode(n[i]+256*n[i+1]);return a}function C(t,e,r){if(t%1!=0||t<0)throw new RangeError(\"offset is not uint\");if(t+e>r)throw new RangeError(\"Trying to access beyond buffer length\")}function P(t,r,n,a,i,o){if(!e.isBuffer(t))throw new TypeError('\"buffer\" argument must be a Buffer instance');if(r>i||r<o)throw new RangeError('\"value\" argument is out of bounds');if(n+a>t.length)throw new RangeError(\"Index out of range\")}function O(t,e,r,n,a,i){if(r+n>t.length)throw new RangeError(\"Index out of range\");if(r<0)throw new RangeError(\"Index out of range\")}function z(t,e,r,n,i){return e=+e,r>>>=0,i||O(t,0,r,4),a.write(t,e,r,n,23,4),r+4}function I(t,e,r,n,i){return e=+e,r>>>=0,i||O(t,0,r,8),a.write(t,e,r,n,52,8),r+8}e.prototype.slice=function(t,r){var n=this.length;(t=~~t)<0?(t+=n)<0&&(t=0):t>n&&(t=n),(r=void 0===r?n:~~r)<0?(r+=n)<0&&(r=0):r>n&&(r=n),r<t&&(r=t);var a=this.subarray(t,r);return Object.setPrototypeOf(a,e.prototype),a},e.prototype.readUIntLE=function(t,e,r){t>>>=0,e>>>=0,r||C(t,e,this.length);for(var n=this[t],a=1,i=0;++i<e&&(a*=256);)n+=this[t+i]*a;return n},e.prototype.readUIntBE=function(t,e,r){t>>>=0,e>>>=0,r||C(t,e,this.length);for(var n=this[t+--e],a=1;e>0&&(a*=256);)n+=this[t+--e]*a;return n},e.prototype.readUInt8=function(t,e){return t>>>=0,e||C(t,1,this.length),this[t]},e.prototype.readUInt16LE=function(t,e){return t>>>=0,e||C(t,2,this.length),this[t]|this[t+1]<<8},e.prototype.readUInt16BE=function(t,e){return t>>>=0,e||C(t,2,this.length),this[t]<<8|this[t+1]},e.prototype.readUInt32LE=function(t,e){return t>>>=0,e||C(t,4,this.length),(this[t]|this[t+1]<<8|this[t+2]<<16)+16777216*this[t+3]},e.prototype.readUInt32BE=function(t,e){return t>>>=0,e||C(t,4,this.length),16777216*this[t]+(this[t+1]<<16|this[t+2]<<8|this[t+3])},e.prototype.readIntLE=function(t,e,r){t>>>=0,e>>>=0,r||C(t,e,this.length);for(var n=this[t],a=1,i=0;++i<e&&(a*=256);)n+=this[t+i]*a;return n>=(a*=128)&&(n-=Math.pow(2,8*e)),n},e.prototype.readIntBE=function(t,e,r){t>>>=0,e>>>=0,r||C(t,e,this.length);for(var n=e,a=1,i=this[t+--n];n>0&&(a*=256);)i+=this[t+--n]*a;return i>=(a*=128)&&(i-=Math.pow(2,8*e)),i},e.prototype.readInt8=function(t,e){return t>>>=0,e||C(t,1,this.length),128&this[t]?-1*(255-this[t]+1):this[t]},e.prototype.readInt16LE=function(t,e){t>>>=0,e||C(t,2,this.length);var r=this[t]|this[t+1]<<8;return 32768&r?4294901760|r:r},e.prototype.readInt16BE=function(t,e){t>>>=0,e||C(t,2,this.length);var r=this[t+1]|this[t]<<8;return 32768&r?4294901760|r:r},e.prototype.readInt32LE=function(t,e){return t>>>=0,e||C(t,4,this.length),this[t]|this[t+1]<<8|this[t+2]<<16|this[t+3]<<24},e.prototype.readInt32BE=function(t,e){return t>>>=0,e||C(t,4,this.length),this[t]<<24|this[t+1]<<16|this[t+2]<<8|this[t+3]},e.prototype.readFloatLE=function(t,e){return t>>>=0,e||C(t,4,this.length),a.read(this,t,!0,23,4)},e.prototype.readFloatBE=function(t,e){return t>>>=0,e||C(t,4,this.length),a.read(this,t,!1,23,4)},e.prototype.readDoubleLE=function(t,e){return t>>>=0,e||C(t,8,this.length),a.read(this,t,!0,52,8)},e.prototype.readDoubleBE=function(t,e){return t>>>=0,e||C(t,8,this.length),a.read(this,t,!1,52,8)},e.prototype.writeUIntLE=function(t,e,r,n){(t=+t,e>>>=0,r>>>=0,n)||P(this,t,e,r,Math.pow(2,8*r)-1,0);var a=1,i=0;for(this[e]=255&t;++i<r&&(a*=256);)this[e+i]=t/a&255;return e+r},e.prototype.writeUIntBE=function(t,e,r,n){(t=+t,e>>>=0,r>>>=0,n)||P(this,t,e,r,Math.pow(2,8*r)-1,0);var a=r-1,i=1;for(this[e+a]=255&t;--a>=0&&(i*=256);)this[e+a]=t/i&255;return e+r},e.prototype.writeUInt8=function(t,e,r){return t=+t,e>>>=0,r||P(this,t,e,1,255,0),this[e]=255&t,e+1},e.prototype.writeUInt16LE=function(t,e,r){return t=+t,e>>>=0,r||P(this,t,e,2,65535,0),this[e]=255&t,this[e+1]=t>>>8,e+2},e.prototype.writeUInt16BE=function(t,e,r){return t=+t,e>>>=0,r||P(this,t,e,2,65535,0),this[e]=t>>>8,this[e+1]=255&t,e+2},e.prototype.writeUInt32LE=function(t,e,r){return t=+t,e>>>=0,r||P(this,t,e,4,4294967295,0),this[e+3]=t>>>24,this[e+2]=t>>>16,this[e+1]=t>>>8,this[e]=255&t,e+4},e.prototype.writeUInt32BE=function(t,e,r){return t=+t,e>>>=0,r||P(this,t,e,4,4294967295,0),this[e]=t>>>24,this[e+1]=t>>>16,this[e+2]=t>>>8,this[e+3]=255&t,e+4},e.prototype.writeIntLE=function(t,e,r,n){if(t=+t,e>>>=0,!n){var a=Math.pow(2,8*r-1);P(this,t,e,r,a-1,-a)}var i=0,o=1,s=0;for(this[e]=255&t;++i<r&&(o*=256);)t<0&&0===s&&0!==this[e+i-1]&&(s=1),this[e+i]=(t/o>>0)-s&255;return e+r},e.prototype.writeIntBE=function(t,e,r,n){if(t=+t,e>>>=0,!n){var a=Math.pow(2,8*r-1);P(this,t,e,r,a-1,-a)}var i=r-1,o=1,s=0;for(this[e+i]=255&t;--i>=0&&(o*=256);)t<0&&0===s&&0!==this[e+i+1]&&(s=1),this[e+i]=(t/o>>0)-s&255;return e+r},e.prototype.writeInt8=function(t,e,r){return t=+t,e>>>=0,r||P(this,t,e,1,127,-128),t<0&&(t=255+t+1),this[e]=255&t,e+1},e.prototype.writeInt16LE=function(t,e,r){return t=+t,e>>>=0,r||P(this,t,e,2,32767,-32768),this[e]=255&t,this[e+1]=t>>>8,e+2},e.prototype.writeInt16BE=function(t,e,r){return t=+t,e>>>=0,r||P(this,t,e,2,32767,-32768),this[e]=t>>>8,this[e+1]=255&t,e+2},e.prototype.writeInt32LE=function(t,e,r){return t=+t,e>>>=0,r||P(this,t,e,4,2147483647,-2147483648),this[e]=255&t,this[e+1]=t>>>8,this[e+2]=t>>>16,this[e+3]=t>>>24,e+4},e.prototype.writeInt32BE=function(t,e,r){return t=+t,e>>>=0,r||P(this,t,e,4,2147483647,-2147483648),t<0&&(t=4294967295+t+1),this[e]=t>>>24,this[e+1]=t>>>16,this[e+2]=t>>>8,this[e+3]=255&t,e+4},e.prototype.writeFloatLE=function(t,e,r){return z(this,t,e,!0,r)},e.prototype.writeFloatBE=function(t,e,r){return z(this,t,e,!1,r)},e.prototype.writeDoubleLE=function(t,e,r){return I(this,t,e,!0,r)},e.prototype.writeDoubleBE=function(t,e,r){return I(this,t,e,!1,r)},e.prototype.copy=function(t,r,n,a){if(!e.isBuffer(t))throw new TypeError(\"argument should be a Buffer\");if(n||(n=0),a||0===a||(a=this.length),r>=t.length&&(r=t.length),r||(r=0),a>0&&a<n&&(a=n),a===n)return 0;if(0===t.length||0===this.length)return 0;if(r<0)throw new RangeError(\"targetStart out of bounds\");if(n<0||n>=this.length)throw new RangeError(\"Index out of range\");if(a<0)throw new RangeError(\"sourceEnd out of bounds\");a>this.length&&(a=this.length),t.length-r<a-n&&(a=t.length-r+n);var i=a-n;if(this===t&&\"function\"==typeof Uint8Array.prototype.copyWithin)this.copyWithin(r,n,a);else if(this===t&&n<r&&r<a)for(var o=i-1;o>=0;--o)t[o+r]=this[o+n];else Uint8Array.prototype.set.call(t,this.subarray(n,a),r);return i},e.prototype.fill=function(t,r,n,a){if(\"string\"==typeof t){if(\"string\"==typeof r?(a=r,r=0,n=this.length):\"string\"==typeof n&&(a=n,n=this.length),void 0!==a&&\"string\"!=typeof a)throw new TypeError(\"encoding must be a string\");if(\"string\"==typeof a&&!e.isEncoding(a))throw new TypeError(\"Unknown encoding: \"+a);if(1===t.length){var i=t.charCodeAt(0);(\"utf8\"===a&&i<128||\"latin1\"===a)&&(t=i)}}else\"number\"==typeof t?t&=255:\"boolean\"==typeof t&&(t=Number(t));if(r<0||this.length<r||this.length<n)throw new RangeError(\"Out of range index\");if(n<=r)return this;var o;if(r>>>=0,n=void 0===n?this.length:n>>>0,t||(t=0),\"number\"==typeof t)for(o=r;o<n;++o)this[o]=t;else{var s=e.isBuffer(t)?t:e.from(t,a),l=s.length;if(0===l)throw new TypeError('The value \"'+t+'\" is invalid for argument \"value\"');for(o=0;o<n-r;++o)this[o+r]=s[o%l]}return this};var D=/[^+/0-9A-Za-z-_]/g;function R(t){return t<16?\"0\"+t.toString(16):t.toString(16)}function F(t,e){var r;e=e||1/0;for(var n=t.length,a=null,i=[],o=0;o<n;++o){if((r=t.charCodeAt(o))>55295&&r<57344){if(!a){if(r>56319){(e-=3)>-1&&i.push(239,191,189);continue}if(o+1===n){(e-=3)>-1&&i.push(239,191,189);continue}a=r;continue}if(r<56320){(e-=3)>-1&&i.push(239,191,189),a=r;continue}r=65536+(a-55296<<10|r-56320)}else a&&(e-=3)>-1&&i.push(239,191,189);if(a=null,r<128){if((e-=1)<0)break;i.push(r)}else if(r<2048){if((e-=2)<0)break;i.push(r>>6|192,63&r|128)}else if(r<65536){if((e-=3)<0)break;i.push(r>>12|224,r>>6&63|128,63&r|128)}else{if(!(r<1114112))throw new Error(\"Invalid code point\");if((e-=4)<0)break;i.push(r>>18|240,r>>12&63|128,r>>6&63|128,63&r|128)}}return i}function B(t){return n.toByteArray(function(t){if((t=(t=t.split(\"=\")[0]).trim().replace(D,\"\")).length<2)return\"\";for(;t.length%4!=0;)t+=\"=\";return t}(t))}function N(t,e,r,n){for(var a=0;a<n&&!(a+r>=e.length||a>=t.length);++a)e[a+r]=t[a];return a}function j(t,e){return t instanceof e||null!=t&&null!=t.constructor&&null!=t.constructor.name&&t.constructor.name===e.name}function V(t){return t!=t}}).call(this,t(\"buffer\").Buffer)},{\"base64-js\":76,buffer:107,ieee754:414}],108:[function(t,e,r){\"use strict\";var n=t(\"./lib/monotone\"),a=t(\"./lib/triangulation\"),i=t(\"./lib/delaunay\"),o=t(\"./lib/filter\");function s(t){return[Math.min(t[0],t[1]),Math.max(t[0],t[1])]}function l(t,e){return t[0]-e[0]||t[1]-e[1]}function c(t,e,r){return e in t?t[e]:r}e.exports=function(t,e,r){Array.isArray(e)?(r=r||{},e=e||[]):(r=e||{},e=[]);var u=!!c(r,\"delaunay\",!0),h=!!c(r,\"interior\",!0),f=!!c(r,\"exterior\",!0),p=!!c(r,\"infinity\",!1);if(!h&&!f||0===t.length)return[];var d=n(t,e);if(u||h!==f||p){for(var g=a(t.length,function(t){return t.map(s).sort(l)}(e)),v=0;v<d.length;++v){var m=d[v];g.addTriangle(m[0],m[1],m[2])}return u&&i(t,g),f?h?p?o(g,0,p):g.cells():o(g,1,p):o(g,-1)}return d}},{\"./lib/delaunay\":109,\"./lib/filter\":110,\"./lib/monotone\":111,\"./lib/triangulation\":112}],109:[function(t,e,r){\"use strict\";var n=t(\"robust-in-sphere\")[4];t(\"binary-search-bounds\");function a(t,e,r,a,i,o){var s=e.opposite(a,i);if(!(s<0)){if(i<a){var l=a;a=i,i=l,l=o,o=s,s=l}e.isConstraint(a,i)||n(t[a],t[i],t[o],t[s])<0&&r.push(a,i)}}e.exports=function(t,e){for(var r=[],i=t.length,o=e.stars,s=0;s<i;++s)for(var l=o[s],c=1;c<l.length;c+=2){var u=l[c];if(!(u<s)&&!e.isConstraint(s,u)){for(var h=l[c-1],f=-1,p=1;p<l.length;p+=2)if(l[p-1]===u){f=l[p];break}f<0||n(t[s],t[u],t[h],t[f])<0&&r.push(s,u)}}for(;r.length>0;){for(var u=r.pop(),s=r.pop(),h=-1,f=-1,l=o[s],d=1;d<l.length;d+=2){var g=l[d-1],v=l[d];g===u?f=v:v===u&&(h=g)}h<0||f<0||(n(t[s],t[u],t[h],t[f])>=0||(e.flip(s,u),a(t,e,r,h,s,f),a(t,e,r,s,f,h),a(t,e,r,f,u,h),a(t,e,r,u,h,f)))}}},{\"binary-search-bounds\":113,\"robust-in-sphere\":507}],110:[function(t,e,r){\"use strict\";var n,a=t(\"binary-search-bounds\");function i(t,e,r,n,a,i,o){this.cells=t,this.neighbor=e,this.flags=n,this.constraint=r,this.active=a,this.next=i,this.boundary=o}function o(t,e){return t[0]-e[0]||t[1]-e[1]||t[2]-e[2]}e.exports=function(t,e,r){var n=function(t,e){for(var r=t.cells(),n=r.length,a=0;a<n;++a){var s=r[a],l=s[0],c=s[1],u=s[2];c<u?c<l&&(s[0]=c,s[1]=u,s[2]=l):u<l&&(s[0]=u,s[1]=l,s[2]=c)}r.sort(o);for(var h=new Array(n),a=0;a<h.length;++a)h[a]=0;var f=[],p=[],d=new Array(3*n),g=new Array(3*n),v=null;e&&(v=[]);for(var m=new i(r,d,g,h,f,p,v),a=0;a<n;++a)for(var s=r[a],y=0;y<3;++y){var l=s[y],c=s[(y+1)%3],x=d[3*a+y]=m.locate(c,l,t.opposite(c,l)),b=g[3*a+y]=t.isConstraint(l,c);x<0&&(b?p.push(a):(f.push(a),h[a]=1),e&&v.push([c,l,-1]))}return m}(t,r);if(0===e)return r?n.cells.concat(n.boundary):n.cells;var a=1,s=n.active,l=n.next,c=n.flags,u=n.cells,h=n.constraint,f=n.neighbor;for(;s.length>0||l.length>0;){for(;s.length>0;){var p=s.pop();if(c[p]!==-a){c[p]=a;u[p];for(var d=0;d<3;++d){var g=f[3*p+d];g>=0&&0===c[g]&&(h[3*p+d]?l.push(g):(s.push(g),c[g]=a))}}}var v=l;l=s,s=v,l.length=0,a=-a}var m=function(t,e,r){for(var n=0,a=0;a<t.length;++a)e[a]===r&&(t[n++]=t[a]);return t.length=n,t}(u,c,e);if(r)return m.concat(n.boundary);return m},i.prototype.locate=(n=[0,0,0],function(t,e,r){var i=t,s=e,l=r;return e<r?e<t&&(i=e,s=r,l=t):r<t&&(i=r,s=t,l=e),i<0?-1:(n[0]=i,n[1]=s,n[2]=l,a.eq(this.cells,n,o))})},{\"binary-search-bounds\":113}],111:[function(t,e,r){\"use strict\";var n=t(\"binary-search-bounds\"),a=t(\"robust-orientation\")[3],i=0,o=1,s=2;function l(t,e,r,n,a){this.a=t,this.b=e,this.idx=r,this.lowerIds=n,this.upperIds=a}function c(t,e,r,n){this.a=t,this.b=e,this.type=r,this.idx=n}function u(t,e){var r=t.a[0]-e.a[0]||t.a[1]-e.a[1]||t.type-e.type;return r||(t.type!==i&&(r=a(t.a,t.b,e.b))?r:t.idx-e.idx)}function h(t,e){return a(t.a,t.b,e)}function f(t,e,r,i,o){for(var s=n.lt(e,i,h),l=n.gt(e,i,h),c=s;c<l;++c){for(var u=e[c],f=u.lowerIds,p=f.length;p>1&&a(r[f[p-2]],r[f[p-1]],i)>0;)t.push([f[p-1],f[p-2],o]),p-=1;f.length=p,f.push(o);var d=u.upperIds;for(p=d.length;p>1&&a(r[d[p-2]],r[d[p-1]],i)<0;)t.push([d[p-2],d[p-1],o]),p-=1;d.length=p,d.push(o)}}function p(t,e){var r;return(r=t.a[0]<e.a[0]?a(t.a,t.b,e.a):a(e.b,e.a,t.a))?r:(r=e.b[0]<t.b[0]?a(t.a,t.b,e.b):a(e.b,e.a,t.b))||t.idx-e.idx}function d(t,e,r){var a=n.le(t,r,p),i=t[a],o=i.upperIds,s=o[o.length-1];i.upperIds=[s],t.splice(a+1,0,new l(r.a,r.b,r.idx,[s],o))}function g(t,e,r){var a=r.a;r.a=r.b,r.b=a;var i=n.eq(t,r,p),o=t[i];t[i-1].upperIds=o.upperIds,t.splice(i,1)}e.exports=function(t,e){for(var r=t.length,n=e.length,a=[],h=0;h<r;++h)a.push(new c(t[h],null,i,h));for(var h=0;h<n;++h){var p=e[h],v=t[p[0]],m=t[p[1]];v[0]<m[0]?a.push(new c(v,m,s,h),new c(m,v,o,h)):v[0]>m[0]&&a.push(new c(m,v,s,h),new c(v,m,o,h))}a.sort(u);for(var y=a[0].a[0]-(1+Math.abs(a[0].a[0]))*Math.pow(2,-52),x=[new l([y,1],[y,0],-1,[],[],[],[])],b=[],h=0,_=a.length;h<_;++h){var w=a[h],k=w.type;k===i?f(b,x,t,w.a,w.idx):k===s?d(x,t,w):g(x,t,w)}return b}},{\"binary-search-bounds\":113,\"robust-orientation\":509}],112:[function(t,e,r){\"use strict\";var n=t(\"binary-search-bounds\");function a(t,e){this.stars=t,this.edges=e}e.exports=function(t,e){for(var r=new Array(t),n=0;n<t;++n)r[n]=[];return new a(r,e)};var i=a.prototype;function o(t,e,r){for(var n=1,a=t.length;n<a;n+=2)if(t[n-1]===e&&t[n]===r)return t[n-1]=t[a-2],t[n]=t[a-1],void(t.length=a-2)}i.isConstraint=function(){var t=[0,0];function e(t,e){return t[0]-e[0]||t[1]-e[1]}return function(r,a){return t[0]=Math.min(r,a),t[1]=Math.max(r,a),n.eq(this.edges,t,e)>=0}}(),i.removeTriangle=function(t,e,r){var n=this.stars;o(n[t],e,r),o(n[e],r,t),o(n[r],t,e)},i.addTriangle=function(t,e,r){var n=this.stars;n[t].push(e,r),n[e].push(r,t),n[r].push(t,e)},i.opposite=function(t,e){for(var r=this.stars[e],n=1,a=r.length;n<a;n+=2)if(r[n]===t)return r[n-1];return-1},i.flip=function(t,e){var r=this.opposite(t,e),n=this.opposite(e,t);this.removeTriangle(t,e,r),this.removeTriangle(e,t,n),this.addTriangle(t,n,r),this.addTriangle(e,r,n)},i.edges=function(){for(var t=this.stars,e=[],r=0,n=t.length;r<n;++r)for(var a=t[r],i=0,o=a.length;i<o;i+=2)e.push([a[i],a[i+1]]);return e},i.cells=function(){for(var t=this.stars,e=[],r=0,n=t.length;r<n;++r)for(var a=t[r],i=0,o=a.length;i<o;i+=2){var s=a[i],l=a[i+1];r<Math.min(s,l)&&e.push([r,s,l])}return e}},{\"binary-search-bounds\":113}],113:[function(t,e,r){\"use strict\";function n(t,e,r,n,a){var i=[\"function \",t,\"(a,l,h,\",n.join(\",\"),\"){\",a?\"\":\"var i=\",r?\"l-1\":\"h+1\",\";while(l<=h){var m=(l+h)>>>1,x=a[m]\"];return a?e.indexOf(\"c\")<0?i.push(\";if(x===y){return m}else if(x<=y){\"):i.push(\";var p=c(x,y);if(p===0){return m}else if(p<=0){\"):i.push(\";if(\",e,\"){i=m;\"),r?i.push(\"l=m+1}else{h=m-1}\"):i.push(\"h=m-1}else{l=m+1}\"),i.push(\"}\"),a?i.push(\"return -1};\"):i.push(\"return i};\"),i.join(\"\")}function a(t,e,r,a){return new Function([n(\"A\",\"x\"+t+\"y\",e,[\"y\"],a),n(\"P\",\"c(x,y)\"+t+\"0\",e,[\"y\",\"c\"],a),\"function dispatchBsearch\",r,\"(a,y,c,l,h){if(typeof(c)==='function'){return P(a,(l===void 0)?0:l|0,(h===void 0)?a.length-1:h|0,y,c)}else{return A(a,(c===void 0)?0:c|0,(l===void 0)?a.length-1:l|0,y)}}return dispatchBsearch\",r].join(\"\"))()}e.exports={ge:a(\">=\",!1,\"GE\"),gt:a(\">\",!1,\"GT\"),lt:a(\"<\",!0,\"LT\"),le:a(\"<=\",!0,\"LE\"),eq:a(\"-\",!0,\"EQ\",!0)}},{}],114:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=1,r=1;r<t.length;++r)for(var n=0;n<r;++n)if(t[r]<t[n])e=-e;else if(t[n]===t[r])return 0;return e}},{}],115:[function(t,e,r){\"use strict\";var n=t(\"dup\"),a=t(\"robust-linear-solve\");function i(t,e){for(var r=0,n=t.length,a=0;a<n;++a)r+=t[a]*e[a];return r}function o(t){var e=t.length;if(0===e)return[];t[0].length;var r=n([t.length+1,t.length+1],1),o=n([t.length+1],1);r[e][e]=0;for(var s=0;s<e;++s){for(var l=0;l<=s;++l)r[l][s]=r[s][l]=2*i(t[s],t[l]);o[s]=i(t[s],t[s])}var c=a(r,o),u=0,h=c[e+1];for(s=0;s<h.length;++s)u+=h[s];var f=new Array(e);for(s=0;s<e;++s){h=c[s];var p=0;for(l=0;l<h.length;++l)p+=h[l];f[s]=p/u}return f}function s(t){if(0===t.length)return[];for(var e=t[0].length,r=n([e]),a=o(t),i=0;i<t.length;++i)for(var s=0;s<e;++s)r[s]+=t[i][s]*a[i];return r}s.barycenetric=o,e.exports=s},{dup:172,\"robust-linear-solve\":508}],116:[function(t,e,r){e.exports=function(t){for(var e=n(t),r=0,a=0;a<t.length;++a)for(var i=t[a],o=0;o<e.length;++o)r+=Math.pow(i[o]-e[o],2);return Math.sqrt(r/t.length)};var n=t(\"circumcenter\")},{circumcenter:115}],117:[function(t,e,r){e.exports=function(t,e,r){return e<r?t<e?e:t>r?r:t:t<r?r:t>e?e:t}},{}],118:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){var n;if(r){n=e;for(var a=new Array(e.length),i=0;i<e.length;++i){var o=e[i];a[i]=[o[0],o[1],r[i]]}e=a}var s=function(t,e,r){var n=d(t,[],p(t));return m(e,n,r),!!n}(t,e,!!r);for(;y(t,e,!!r);)s=!0;if(r&&s){n.length=0,r.length=0;for(var i=0;i<e.length;++i){var o=e[i];n.push([o[0],o[1]]),r.push(o[2])}}return s};var n=t(\"union-find\"),a=t(\"box-intersect\"),i=t(\"robust-segment-intersect\"),o=t(\"big-rat\"),s=t(\"big-rat/cmp\"),l=t(\"big-rat/to-float\"),c=t(\"rat-vec\"),u=t(\"nextafter\"),h=t(\"./lib/rat-seg-intersect\");function f(t){var e=l(t);return[u(e,-1/0),u(e,1/0)]}function p(t){for(var e=new Array(t.length),r=0;r<t.length;++r){var n=t[r];e[r]=[u(n[0],-1/0),u(n[1],-1/0),u(n[0],1/0),u(n[1],1/0)]}return e}function d(t,e,r){for(var i=e.length,o=new n(i),s=[],l=0;l<e.length;++l){var c=e[l],h=f(c[0]),p=f(c[1]);s.push([u(h[0],-1/0),u(p[0],-1/0),u(h[1],1/0),u(p[1],1/0)])}a(s,function(t,e){o.link(t,e)});var d=!0,g=new Array(i);for(l=0;l<i;++l){(m=o.find(l))!==l&&(d=!1,t[m]=[Math.min(t[l][0],t[m][0]),Math.min(t[l][1],t[m][1])])}if(d)return null;var v=0;for(l=0;l<i;++l){var m;(m=o.find(l))===l?(g[l]=v,t[v++]=t[l]):g[l]=-1}t.length=v;for(l=0;l<i;++l)g[l]<0&&(g[l]=g[o.find(l)]);return g}function g(t,e){return t[0]-e[0]||t[1]-e[1]}function v(t,e){var r=t[0]-e[0]||t[1]-e[1];return r||(t[2]<e[2]?-1:t[2]>e[2]?1:0)}function m(t,e,r){if(0!==t.length){if(e)for(var n=0;n<t.length;++n){var a=e[(o=t[n])[0]],i=e[o[1]];o[0]=Math.min(a,i),o[1]=Math.max(a,i)}else for(n=0;n<t.length;++n){var o;a=(o=t[n])[0],i=o[1];o[0]=Math.min(a,i),o[1]=Math.max(a,i)}r?t.sort(v):t.sort(g);var s=1;for(n=1;n<t.length;++n){var l=t[n-1],c=t[n];(c[0]!==l[0]||c[1]!==l[1]||r&&c[2]!==l[2])&&(t[s++]=c)}t.length=s}}function y(t,e,r){var n=function(t,e){for(var r=new Array(e.length),n=0;n<e.length;++n){var a=e[n],i=t[a[0]],o=t[a[1]];r[n]=[u(Math.min(i[0],o[0]),-1/0),u(Math.min(i[1],o[1]),-1/0),u(Math.max(i[0],o[0]),1/0),u(Math.max(i[1],o[1]),1/0)]}return r}(t,e),f=function(t,e,r){var n=[];return a(r,function(r,a){var o=e[r],s=e[a];if(o[0]!==s[0]&&o[0]!==s[1]&&o[1]!==s[0]&&o[1]!==s[1]){var l=t[o[0]],c=t[o[1]],u=t[s[0]],h=t[s[1]];i(l,c,u,h)&&n.push([r,a])}}),n}(t,e,n),g=p(t),v=function(t,e,r,n){var o=[];return a(r,n,function(r,n){var a=e[r];if(a[0]!==n&&a[1]!==n){var s=t[n],l=t[a[0]],c=t[a[1]];i(l,c,s,s)&&o.push([r,n])}}),o}(t,e,n,g),y=d(t,function(t,e,r,n,a){var i,u,f=t.map(function(t){return[o(t[0]),o(t[1])]});for(i=0;i<r.length;++i){var p=r[i];u=p[0];var d=p[1],g=e[u],v=e[d],m=h(c(t[g[0]]),c(t[g[1]]),c(t[v[0]]),c(t[v[1]]));if(m){var y=t.length;t.push([l(m[0]),l(m[1])]),f.push(m),n.push([u,y],[d,y])}}for(n.sort(function(t,e){if(t[0]!==e[0])return t[0]-e[0];var r=f[t[1]],n=f[e[1]];return s(r[0],n[0])||s(r[1],n[1])}),i=n.length-1;i>=0;--i){var x=e[u=(S=n[i])[0]],b=x[0],_=x[1],w=t[b],k=t[_];if((w[0]-k[0]||w[1]-k[1])<0){var T=b;b=_,_=T}x[0]=b;var M,A=x[1]=S[1];for(a&&(M=x[2]);i>0&&n[i-1][0]===u;){var S,E=(S=n[--i])[1];a?e.push([A,E,M]):e.push([A,E]),A=E}a?e.push([A,_,M]):e.push([A,_])}return f}(t,e,f,v,r));return m(e,y,r),!!y||(f.length>0||v.length>0)}},{\"./lib/rat-seg-intersect\":119,\"big-rat\":80,\"big-rat/cmp\":78,\"big-rat/to-float\":92,\"box-intersect\":98,nextafter:453,\"rat-vec\":488,\"robust-segment-intersect\":512,\"union-find\":545}],119:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n){var i=s(e,t),h=s(n,r),f=u(i,h);if(0===o(f))return null;var p=s(t,r),d=u(h,p),g=a(d,f),v=c(i,g);return l(t,v)};var n=t(\"big-rat/mul\"),a=t(\"big-rat/div\"),i=t(\"big-rat/sub\"),o=t(\"big-rat/sign\"),s=t(\"rat-vec/sub\"),l=t(\"rat-vec/add\"),c=t(\"rat-vec/muls\");function u(t,e){return i(n(t[0],e[1]),n(t[1],e[0]))}},{\"big-rat/div\":79,\"big-rat/mul\":89,\"big-rat/sign\":90,\"big-rat/sub\":91,\"rat-vec/add\":487,\"rat-vec/muls\":489,\"rat-vec/sub\":490}],120:[function(t,e,r){\"use strict\";var n=t(\"clamp\");function a(t,e){null==e&&(e=!0);var r=t[0],a=t[1],i=t[2],o=t[3];return null==o&&(o=e?1:255),e&&(r*=255,a*=255,i*=255,o*=255),16777216*(r=255&n(r,0,255))+((a=255&n(a,0,255))<<16)+((i=255&n(i,0,255))<<8)+(o=255&n(o,0,255))}e.exports=a,e.exports.to=a,e.exports.from=function(t,e){var r=(t=+t)>>>24,n=(16711680&t)>>>16,a=(65280&t)>>>8,i=255&t;return!1===e?[r,n,a,i]:[r/255,n/255,a/255,i/255]}},{clamp:117}],121:[function(t,e,r){\"use strict\";e.exports={aliceblue:[240,248,255],antiquewhite:[250,235,215],aqua:[0,255,255],aquamarine:[127,255,212],azure:[240,255,255],beige:[245,245,220],bisque:[255,228,196],black:[0,0,0],blanchedalmond:[255,235,205],blue:[0,0,255],blueviolet:[138,43,226],brown:[165,42,42],burlywood:[222,184,135],cadetblue:[95,158,160],chartreuse:[127,255,0],chocolate:[210,105,30],coral:[255,127,80],cornflowerblue:[100,149,237],cornsilk:[255,248,220],crimson:[220,20,60],cyan:[0,255,255],darkblue:[0,0,139],darkcyan:[0,139,139],darkgoldenrod:[184,134,11],darkgray:[169,169,169],darkgreen:[0,100,0],darkgrey:[169,169,169],darkkhaki:[189,183,107],darkmagenta:[139,0,139],darkolivegreen:[85,107,47],darkorange:[255,140,0],darkorchid:[153,50,204],darkred:[139,0,0],darksalmon:[233,150,122],darkseagreen:[143,188,143],darkslateblue:[72,61,139],darkslategray:[47,79,79],darkslategrey:[47,79,79],darkturquoise:[0,206,209],darkviolet:[148,0,211],deeppink:[255,20,147],deepskyblue:[0,191,255],dimgray:[105,105,105],dimgrey:[105,105,105],dodgerblue:[30,144,255],firebrick:[178,34,34],floralwhite:[255,250,240],forestgreen:[34,139,34],fuchsia:[255,0,255],gainsboro:[220,220,220],ghostwhite:[248,248,255],gold:[255,215,0],goldenrod:[218,165,32],gray:[128,128,128],green:[0,128,0],greenyellow:[173,255,47],grey:[128,128,128],honeydew:[240,255,240],hotpink:[255,105,180],indianred:[205,92,92],indigo:[75,0,130],ivory:[255,255,240],khaki:[240,230,140],lavender:[230,230,250],lavenderblush:[255,240,245],lawngreen:[124,252,0],lemonchiffon:[255,250,205],lightblue:[173,216,230],lightcoral:[240,128,128],lightcyan:[224,255,255],lightgoldenrodyellow:[250,250,210],lightgray:[211,211,211],lightgreen:[144,238,144],lightgrey:[211,211,211],lightpink:[255,182,193],lightsalmon:[255,160,122],lightseagreen:[32,178,170],lightskyblue:[135,206,250],lightslategray:[119,136,153],lightslategrey:[119,136,153],lightsteelblue:[176,196,222],lightyellow:[255,255,224],lime:[0,255,0],limegreen:[50,205,50],linen:[250,240,230],magenta:[255,0,255],maroon:[128,0,0],mediumaquamarine:[102,205,170],mediumblue:[0,0,205],mediumorchid:[186,85,211],mediumpurple:[147,112,219],mediumseagreen:[60,179,113],mediumslateblue:[123,104,238],mediumspringgreen:[0,250,154],mediumturquoise:[72,209,204],mediumvioletred:[199,21,133],midnightblue:[25,25,112],mintcream:[245,255,250],mistyrose:[255,228,225],moccasin:[255,228,181],navajowhite:[255,222,173],navy:[0,0,128],oldlace:[253,245,230],olive:[128,128,0],olivedrab:[107,142,35],orange:[255,165,0],orangered:[255,69,0],orchid:[218,112,214],palegoldenrod:[238,232,170],palegreen:[152,251,152],paleturquoise:[175,238,238],palevioletred:[219,112,147],papayawhip:[255,239,213],peachpuff:[255,218,185],peru:[205,133,63],pink:[255,192,203],plum:[221,160,221],powderblue:[176,224,230],purple:[128,0,128],rebeccapurple:[102,51,153],red:[255,0,0],rosybrown:[188,143,143],royalblue:[65,105,225],saddlebrown:[139,69,19],salmon:[250,128,114],sandybrown:[244,164,96],seagreen:[46,139,87],seashell:[255,245,238],sienna:[160,82,45],silver:[192,192,192],skyblue:[135,206,235],slateblue:[106,90,205],slategray:[112,128,144],slategrey:[112,128,144],snow:[255,250,250],springgreen:[0,255,127],steelblue:[70,130,180],tan:[210,180,140],teal:[0,128,128],thistle:[216,191,216],tomato:[255,99,71],turquoise:[64,224,208],violet:[238,130,238],wheat:[245,222,179],white:[255,255,255],whitesmoke:[245,245,245],yellow:[255,255,0],yellowgreen:[154,205,50]}},{}],122:[function(t,e,r){\"use strict\";var n=t(\"color-rgba\"),a=t(\"clamp\"),i=t(\"dtype\");e.exports=function(t,e){\"float\"!==e&&e||(e=\"array\"),\"uint\"===e&&(e=\"uint8\"),\"uint_clamped\"===e&&(e=\"uint8_clamped\");var r=new(i(e))(4),o=\"uint8\"!==e&&\"uint8_clamped\"!==e;return t.length&&\"string\"!=typeof t||((t=n(t))[0]/=255,t[1]/=255,t[2]/=255),function(t){return t instanceof Uint8Array||t instanceof Uint8ClampedArray||!!(Array.isArray(t)&&(t[0]>1||0===t[0])&&(t[1]>1||0===t[1])&&(t[2]>1||0===t[2])&&(!t[3]||t[3]>1))}(t)?(r[0]=t[0],r[1]=t[1],r[2]=t[2],r[3]=null!=t[3]?t[3]:255,o&&(r[0]/=255,r[1]/=255,r[2]/=255,r[3]/=255),r):(o?(r[0]=t[0],r[1]=t[1],r[2]=t[2],r[3]=null!=t[3]?t[3]:1):(r[0]=a(Math.floor(255*t[0]),0,255),r[1]=a(Math.floor(255*t[1]),0,255),r[2]=a(Math.floor(255*t[2]),0,255),r[3]=null==t[3]?255:a(Math.floor(255*t[3]),0,255)),r)}},{clamp:117,\"color-rgba\":124,dtype:171}],123:[function(t,e,r){(function(r){\"use strict\";var n=t(\"color-name\"),a=t(\"is-plain-obj\"),i=t(\"defined\");e.exports=function(t){var e,s,l=[],c=1;if(\"string\"==typeof t)if(n[t])l=n[t].slice(),s=\"rgb\";else if(\"transparent\"===t)c=0,s=\"rgb\",l=[0,0,0];else if(/^#[A-Fa-f0-9]+$/.test(t)){var u=t.slice(1),h=u.length,f=h<=4;c=1,f?(l=[parseInt(u[0]+u[0],16),parseInt(u[1]+u[1],16),parseInt(u[2]+u[2],16)],4===h&&(c=parseInt(u[3]+u[3],16)/255)):(l=[parseInt(u[0]+u[1],16),parseInt(u[2]+u[3],16),parseInt(u[4]+u[5],16)],8===h&&(c=parseInt(u[6]+u[7],16)/255)),l[0]||(l[0]=0),l[1]||(l[1]=0),l[2]||(l[2]=0),s=\"rgb\"}else if(e=/^((?:rgb|hs[lvb]|hwb|cmyk?|xy[zy]|gray|lab|lchu?v?|[ly]uv|lms)a?)\\s*\\(([^\\)]*)\\)/.exec(t)){var p=e[1],d=\"rgb\"===p,u=p.replace(/a$/,\"\");s=u;var h=\"cmyk\"===u?4:\"gray\"===u?1:3;l=e[2].trim().split(/\\s*,\\s*/).map(function(t,e){if(/%$/.test(t))return e===h?parseFloat(t)/100:\"rgb\"===u?255*parseFloat(t)/100:parseFloat(t);if(\"h\"===u[e]){if(/deg$/.test(t))return parseFloat(t);if(void 0!==o[t])return o[t]}return parseFloat(t)}),p===u&&l.push(1),c=d?1:void 0===l[h]?1:l[h],l=l.slice(0,h)}else t.length>10&&/[0-9](?:\\s|\\/)/.test(t)&&(l=t.match(/([0-9]+)/g).map(function(t){return parseFloat(t)}),s=t.match(/([a-z])/gi).join(\"\").toLowerCase());else if(isNaN(t))if(a(t)){var g=i(t.r,t.red,t.R,null);null!==g?(s=\"rgb\",l=[g,i(t.g,t.green,t.G),i(t.b,t.blue,t.B)]):(s=\"hsl\",l=[i(t.h,t.hue,t.H),i(t.s,t.saturation,t.S),i(t.l,t.lightness,t.L,t.b,t.brightness)]),c=i(t.a,t.alpha,t.opacity,1),null!=t.opacity&&(c/=100)}else(Array.isArray(t)||r.ArrayBuffer&&ArrayBuffer.isView&&ArrayBuffer.isView(t))&&(l=[t[0],t[1],t[2]],s=\"rgb\",c=4===t.length?t[3]:1);else s=\"rgb\",l=[t>>>16,(65280&t)>>>8,255&t];return{space:s,values:l,alpha:c}};var o={red:0,orange:60,yellow:120,green:180,blue:240,purple:300}}).call(this,\"undefined\"!=typeof global?global:\"undefined\"!=typeof self?self:\"undefined\"!=typeof window?window:{})},{\"color-name\":121,defined:166,\"is-plain-obj\":424}],124:[function(t,e,r){\"use strict\";var n=t(\"color-parse\"),a=t(\"color-space/hsl\"),i=t(\"clamp\");e.exports=function(t){var e,r=n(t);return r.space?((e=Array(3))[0]=i(r.values[0],0,255),e[1]=i(r.values[1],0,255),e[2]=i(r.values[2],0,255),\"h\"===r.space[0]&&(e=a.rgb(e)),e.push(i(r.alpha,0,1)),e):[]}},{clamp:117,\"color-parse\":123,\"color-space/hsl\":125}],125:[function(t,e,r){\"use strict\";var n=t(\"./rgb\");e.exports={name:\"hsl\",min:[0,0,0],max:[360,100,100],channel:[\"hue\",\"saturation\",\"lightness\"],alias:[\"HSL\"],rgb:function(t){var e,r,n,a,i,o=t[0]/360,s=t[1]/100,l=t[2]/100;if(0===s)return[i=255*l,i,i];e=2*l-(r=l<.5?l*(1+s):l+s-l*s),a=[0,0,0];for(var c=0;c<3;c++)(n=o+1/3*-(c-1))<0?n++:n>1&&n--,i=6*n<1?e+6*(r-e)*n:2*n<1?r:3*n<2?e+(r-e)*(2/3-n)*6:e,a[c]=255*i;return a}},n.hsl=function(t){var e,r,n=t[0]/255,a=t[1]/255,i=t[2]/255,o=Math.min(n,a,i),s=Math.max(n,a,i),l=s-o;return s===o?e=0:n===s?e=(a-i)/l:a===s?e=2+(i-n)/l:i===s&&(e=4+(n-a)/l),(e=Math.min(60*e,360))<0&&(e+=360),r=(o+s)/2,[e,100*(s===o?0:r<=.5?l/(s+o):l/(2-s-o)),100*r]}},{\"./rgb\":126}],126:[function(t,e,r){\"use strict\";e.exports={name:\"rgb\",min:[0,0,0],max:[255,255,255],channel:[\"red\",\"green\",\"blue\"],alias:[\"RGB\"]}},{}],127:[function(t,e,r){e.exports={jet:[{index:0,rgb:[0,0,131]},{index:.125,rgb:[0,60,170]},{index:.375,rgb:[5,255,255]},{index:.625,rgb:[255,255,0]},{index:.875,rgb:[250,0,0]},{index:1,rgb:[128,0,0]}],hsv:[{index:0,rgb:[255,0,0]},{index:.169,rgb:[253,255,2]},{index:.173,rgb:[247,255,2]},{index:.337,rgb:[0,252,4]},{index:.341,rgb:[0,252,10]},{index:.506,rgb:[1,249,255]},{index:.671,rgb:[2,0,253]},{index:.675,rgb:[8,0,253]},{index:.839,rgb:[255,0,251]},{index:.843,rgb:[255,0,245]},{index:1,rgb:[255,0,6]}],hot:[{index:0,rgb:[0,0,0]},{index:.3,rgb:[230,0,0]},{index:.6,rgb:[255,210,0]},{index:1,rgb:[255,255,255]}],cool:[{index:0,rgb:[0,255,255]},{index:1,rgb:[255,0,255]}],spring:[{index:0,rgb:[255,0,255]},{index:1,rgb:[255,255,0]}],summer:[{index:0,rgb:[0,128,102]},{index:1,rgb:[255,255,102]}],autumn:[{index:0,rgb:[255,0,0]},{index:1,rgb:[255,255,0]}],winter:[{index:0,rgb:[0,0,255]},{index:1,rgb:[0,255,128]}],bone:[{index:0,rgb:[0,0,0]},{index:.376,rgb:[84,84,116]},{index:.753,rgb:[169,200,200]},{index:1,rgb:[255,255,255]}],copper:[{index:0,rgb:[0,0,0]},{index:.804,rgb:[255,160,102]},{index:1,rgb:[255,199,127]}],greys:[{index:0,rgb:[0,0,0]},{index:1,rgb:[255,255,255]}],yignbu:[{index:0,rgb:[8,29,88]},{index:.125,rgb:[37,52,148]},{index:.25,rgb:[34,94,168]},{index:.375,rgb:[29,145,192]},{index:.5,rgb:[65,182,196]},{index:.625,rgb:[127,205,187]},{index:.75,rgb:[199,233,180]},{index:.875,rgb:[237,248,217]},{index:1,rgb:[255,255,217]}],greens:[{index:0,rgb:[0,68,27]},{index:.125,rgb:[0,109,44]},{index:.25,rgb:[35,139,69]},{index:.375,rgb:[65,171,93]},{index:.5,rgb:[116,196,118]},{index:.625,rgb:[161,217,155]},{index:.75,rgb:[199,233,192]},{index:.875,rgb:[229,245,224]},{index:1,rgb:[247,252,245]}],yiorrd:[{index:0,rgb:[128,0,38]},{index:.125,rgb:[189,0,38]},{index:.25,rgb:[227,26,28]},{index:.375,rgb:[252,78,42]},{index:.5,rgb:[253,141,60]},{index:.625,rgb:[254,178,76]},{index:.75,rgb:[254,217,118]},{index:.875,rgb:[255,237,160]},{index:1,rgb:[255,255,204]}],bluered:[{index:0,rgb:[0,0,255]},{index:1,rgb:[255,0,0]}],rdbu:[{index:0,rgb:[5,10,172]},{index:.35,rgb:[106,137,247]},{index:.5,rgb:[190,190,190]},{index:.6,rgb:[220,170,132]},{index:.7,rgb:[230,145,90]},{index:1,rgb:[178,10,28]}],picnic:[{index:0,rgb:[0,0,255]},{index:.1,rgb:[51,153,255]},{index:.2,rgb:[102,204,255]},{index:.3,rgb:[153,204,255]},{index:.4,rgb:[204,204,255]},{index:.5,rgb:[255,255,255]},{index:.6,rgb:[255,204,255]},{index:.7,rgb:[255,153,255]},{index:.8,rgb:[255,102,204]},{index:.9,rgb:[255,102,102]},{index:1,rgb:[255,0,0]}],rainbow:[{index:0,rgb:[150,0,90]},{index:.125,rgb:[0,0,200]},{index:.25,rgb:[0,25,255]},{index:.375,rgb:[0,152,255]},{index:.5,rgb:[44,255,150]},{index:.625,rgb:[151,255,0]},{index:.75,rgb:[255,234,0]},{index:.875,rgb:[255,111,0]},{index:1,rgb:[255,0,0]}],portland:[{index:0,rgb:[12,51,131]},{index:.25,rgb:[10,136,186]},{index:.5,rgb:[242,211,56]},{index:.75,rgb:[242,143,56]},{index:1,rgb:[217,30,30]}],blackbody:[{index:0,rgb:[0,0,0]},{index:.2,rgb:[230,0,0]},{index:.4,rgb:[230,210,0]},{index:.7,rgb:[255,255,255]},{index:1,rgb:[160,200,255]}],earth:[{index:0,rgb:[0,0,130]},{index:.1,rgb:[0,180,180]},{index:.2,rgb:[40,210,40]},{index:.4,rgb:[230,230,50]},{index:.6,rgb:[120,70,20]},{index:1,rgb:[255,255,255]}],electric:[{index:0,rgb:[0,0,0]},{index:.15,rgb:[30,0,100]},{index:.4,rgb:[120,0,100]},{index:.6,rgb:[160,90,0]},{index:.8,rgb:[230,200,0]},{index:1,rgb:[255,250,220]}],alpha:[{index:0,rgb:[255,255,255,0]},{index:1,rgb:[255,255,255,1]}],viridis:[{index:0,rgb:[68,1,84]},{index:.13,rgb:[71,44,122]},{index:.25,rgb:[59,81,139]},{index:.38,rgb:[44,113,142]},{index:.5,rgb:[33,144,141]},{index:.63,rgb:[39,173,129]},{index:.75,rgb:[92,200,99]},{index:.88,rgb:[170,220,50]},{index:1,rgb:[253,231,37]}],inferno:[{index:0,rgb:[0,0,4]},{index:.13,rgb:[31,12,72]},{index:.25,rgb:[85,15,109]},{index:.38,rgb:[136,34,106]},{index:.5,rgb:[186,54,85]},{index:.63,rgb:[227,89,51]},{index:.75,rgb:[249,140,10]},{index:.88,rgb:[249,201,50]},{index:1,rgb:[252,255,164]}],magma:[{index:0,rgb:[0,0,4]},{index:.13,rgb:[28,16,68]},{index:.25,rgb:[79,18,123]},{index:.38,rgb:[129,37,129]},{index:.5,rgb:[181,54,122]},{index:.63,rgb:[229,80,100]},{index:.75,rgb:[251,135,97]},{index:.88,rgb:[254,194,135]},{index:1,rgb:[252,253,191]}],plasma:[{index:0,rgb:[13,8,135]},{index:.13,rgb:[75,3,161]},{index:.25,rgb:[125,3,168]},{index:.38,rgb:[168,34,150]},{index:.5,rgb:[203,70,121]},{index:.63,rgb:[229,107,93]},{index:.75,rgb:[248,148,65]},{index:.88,rgb:[253,195,40]},{index:1,rgb:[240,249,33]}],warm:[{index:0,rgb:[125,0,179]},{index:.13,rgb:[172,0,187]},{index:.25,rgb:[219,0,170]},{index:.38,rgb:[255,0,130]},{index:.5,rgb:[255,63,74]},{index:.63,rgb:[255,123,0]},{index:.75,rgb:[234,176,0]},{index:.88,rgb:[190,228,0]},{index:1,rgb:[147,255,0]}],cool:[{index:0,rgb:[125,0,179]},{index:.13,rgb:[116,0,218]},{index:.25,rgb:[98,74,237]},{index:.38,rgb:[68,146,231]},{index:.5,rgb:[0,204,197]},{index:.63,rgb:[0,247,146]},{index:.75,rgb:[0,255,88]},{index:.88,rgb:[40,255,8]},{index:1,rgb:[147,255,0]}],\"rainbow-soft\":[{index:0,rgb:[125,0,179]},{index:.1,rgb:[199,0,180]},{index:.2,rgb:[255,0,121]},{index:.3,rgb:[255,108,0]},{index:.4,rgb:[222,194,0]},{index:.5,rgb:[150,255,0]},{index:.6,rgb:[0,255,55]},{index:.7,rgb:[0,246,150]},{index:.8,rgb:[50,167,222]},{index:.9,rgb:[103,51,235]},{index:1,rgb:[124,0,186]}],bathymetry:[{index:0,rgb:[40,26,44]},{index:.13,rgb:[59,49,90]},{index:.25,rgb:[64,76,139]},{index:.38,rgb:[63,110,151]},{index:.5,rgb:[72,142,158]},{index:.63,rgb:[85,174,163]},{index:.75,rgb:[120,206,163]},{index:.88,rgb:[187,230,172]},{index:1,rgb:[253,254,204]}],cdom:[{index:0,rgb:[47,15,62]},{index:.13,rgb:[87,23,86]},{index:.25,rgb:[130,28,99]},{index:.38,rgb:[171,41,96]},{index:.5,rgb:[206,67,86]},{index:.63,rgb:[230,106,84]},{index:.75,rgb:[242,149,103]},{index:.88,rgb:[249,193,135]},{index:1,rgb:[254,237,176]}],chlorophyll:[{index:0,rgb:[18,36,20]},{index:.13,rgb:[25,63,41]},{index:.25,rgb:[24,91,59]},{index:.38,rgb:[13,119,72]},{index:.5,rgb:[18,148,80]},{index:.63,rgb:[80,173,89]},{index:.75,rgb:[132,196,122]},{index:.88,rgb:[175,221,162]},{index:1,rgb:[215,249,208]}],density:[{index:0,rgb:[54,14,36]},{index:.13,rgb:[89,23,80]},{index:.25,rgb:[110,45,132]},{index:.38,rgb:[120,77,178]},{index:.5,rgb:[120,113,213]},{index:.63,rgb:[115,151,228]},{index:.75,rgb:[134,185,227]},{index:.88,rgb:[177,214,227]},{index:1,rgb:[230,241,241]}],\"freesurface-blue\":[{index:0,rgb:[30,4,110]},{index:.13,rgb:[47,14,176]},{index:.25,rgb:[41,45,236]},{index:.38,rgb:[25,99,212]},{index:.5,rgb:[68,131,200]},{index:.63,rgb:[114,156,197]},{index:.75,rgb:[157,181,203]},{index:.88,rgb:[200,208,216]},{index:1,rgb:[241,237,236]}],\"freesurface-red\":[{index:0,rgb:[60,9,18]},{index:.13,rgb:[100,17,27]},{index:.25,rgb:[142,20,29]},{index:.38,rgb:[177,43,27]},{index:.5,rgb:[192,87,63]},{index:.63,rgb:[205,125,105]},{index:.75,rgb:[216,162,148]},{index:.88,rgb:[227,199,193]},{index:1,rgb:[241,237,236]}],oxygen:[{index:0,rgb:[64,5,5]},{index:.13,rgb:[106,6,15]},{index:.25,rgb:[144,26,7]},{index:.38,rgb:[168,64,3]},{index:.5,rgb:[188,100,4]},{index:.63,rgb:[206,136,11]},{index:.75,rgb:[220,174,25]},{index:.88,rgb:[231,215,44]},{index:1,rgb:[248,254,105]}],par:[{index:0,rgb:[51,20,24]},{index:.13,rgb:[90,32,35]},{index:.25,rgb:[129,44,34]},{index:.38,rgb:[159,68,25]},{index:.5,rgb:[182,99,19]},{index:.63,rgb:[199,134,22]},{index:.75,rgb:[212,171,35]},{index:.88,rgb:[221,210,54]},{index:1,rgb:[225,253,75]}],phase:[{index:0,rgb:[145,105,18]},{index:.13,rgb:[184,71,38]},{index:.25,rgb:[186,58,115]},{index:.38,rgb:[160,71,185]},{index:.5,rgb:[110,97,218]},{index:.63,rgb:[50,123,164]},{index:.75,rgb:[31,131,110]},{index:.88,rgb:[77,129,34]},{index:1,rgb:[145,105,18]}],salinity:[{index:0,rgb:[42,24,108]},{index:.13,rgb:[33,50,162]},{index:.25,rgb:[15,90,145]},{index:.38,rgb:[40,118,137]},{index:.5,rgb:[59,146,135]},{index:.63,rgb:[79,175,126]},{index:.75,rgb:[120,203,104]},{index:.88,rgb:[193,221,100]},{index:1,rgb:[253,239,154]}],temperature:[{index:0,rgb:[4,35,51]},{index:.13,rgb:[23,51,122]},{index:.25,rgb:[85,59,157]},{index:.38,rgb:[129,79,143]},{index:.5,rgb:[175,95,130]},{index:.63,rgb:[222,112,101]},{index:.75,rgb:[249,146,66]},{index:.88,rgb:[249,196,65]},{index:1,rgb:[232,250,91]}],turbidity:[{index:0,rgb:[34,31,27]},{index:.13,rgb:[65,50,41]},{index:.25,rgb:[98,69,52]},{index:.38,rgb:[131,89,57]},{index:.5,rgb:[161,112,59]},{index:.63,rgb:[185,140,66]},{index:.75,rgb:[202,174,88]},{index:.88,rgb:[216,209,126]},{index:1,rgb:[233,246,171]}],\"velocity-blue\":[{index:0,rgb:[17,32,64]},{index:.13,rgb:[35,52,116]},{index:.25,rgb:[29,81,156]},{index:.38,rgb:[31,113,162]},{index:.5,rgb:[50,144,169]},{index:.63,rgb:[87,173,176]},{index:.75,rgb:[149,196,189]},{index:.88,rgb:[203,221,211]},{index:1,rgb:[254,251,230]}],\"velocity-green\":[{index:0,rgb:[23,35,19]},{index:.13,rgb:[24,64,38]},{index:.25,rgb:[11,95,45]},{index:.38,rgb:[39,123,35]},{index:.5,rgb:[95,146,12]},{index:.63,rgb:[152,165,18]},{index:.75,rgb:[201,186,69]},{index:.88,rgb:[233,216,137]},{index:1,rgb:[255,253,205]}],cubehelix:[{index:0,rgb:[0,0,0]},{index:.07,rgb:[22,5,59]},{index:.13,rgb:[60,4,105]},{index:.2,rgb:[109,1,135]},{index:.27,rgb:[161,0,147]},{index:.33,rgb:[210,2,142]},{index:.4,rgb:[251,11,123]},{index:.47,rgb:[255,29,97]},{index:.53,rgb:[255,54,69]},{index:.6,rgb:[255,85,46]},{index:.67,rgb:[255,120,34]},{index:.73,rgb:[255,157,37]},{index:.8,rgb:[241,191,57]},{index:.87,rgb:[224,220,93]},{index:.93,rgb:[218,241,142]},{index:1,rgb:[227,253,198]}]}},{}],128:[function(t,e,r){\"use strict\";var n=t(\"./colorScale\"),a=t(\"lerp\");function i(t){return[t[0]/255,t[1]/255,t[2]/255,t[3]]}function o(t){for(var e,r=\"#\",n=0;n<3;++n)r+=(\"00\"+(e=(e=t[n]).toString(16))).substr(e.length);return r}function s(t){return\"rgba(\"+t.join(\",\")+\")\"}e.exports=function(t){var e,r,l,c,u,h,f,p,d,g;t||(t={});p=(t.nshades||72)-1,f=t.format||\"hex\",(h=t.colormap)||(h=\"jet\");if(\"string\"==typeof h){if(h=h.toLowerCase(),!n[h])throw Error(h+\" not a supported colorscale\");u=n[h]}else{if(!Array.isArray(h))throw Error(\"unsupported colormap option\",h);u=h.slice()}if(u.length>p+1)throw new Error(h+\" map requires nshades to be at least size \"+u.length);d=Array.isArray(t.alpha)?2!==t.alpha.length?[1,1]:t.alpha.slice():\"number\"==typeof t.alpha?[t.alpha,t.alpha]:[1,1];e=u.map(function(t){return Math.round(t.index*p)}),d[0]=Math.min(Math.max(d[0],0),1),d[1]=Math.min(Math.max(d[1],0),1);var v=u.map(function(t,e){var r=u[e].index,n=u[e].rgb.slice();return 4===n.length&&n[3]>=0&&n[3]<=1?n:(n[3]=d[0]+(d[1]-d[0])*r,n)}),m=[];for(g=0;g<e.length-1;++g){c=e[g+1]-e[g],r=v[g],l=v[g+1];for(var y=0;y<c;y++){var x=y/c;m.push([Math.round(a(r[0],l[0],x)),Math.round(a(r[1],l[1],x)),Math.round(a(r[2],l[2],x)),a(r[3],l[3],x)])}}m.push(u[u.length-1].rgb.concat(d[1])),\"hex\"===f?m=m.map(o):\"rgbaString\"===f?m=m.map(s):\"float\"===f&&(m=m.map(i));return m}},{\"./colorScale\":127,lerp:427}],129:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,i){var o=n(e,r,i);if(0===o){var s=a(n(t,e,r)),c=a(n(t,e,i));if(s===c){if(0===s){var u=l(t,e,r),h=l(t,e,i);return u===h?0:u?1:-1}return 0}return 0===c?s>0?-1:l(t,e,i)?-1:1:0===s?c>0?1:l(t,e,r)?1:-1:a(c-s)}var f=n(t,e,r);if(f>0)return o>0&&n(t,e,i)>0?1:-1;if(f<0)return o>0||n(t,e,i)>0?1:-1;var p=n(t,e,i);return p>0?1:l(t,e,r)?1:-1};var n=t(\"robust-orientation\"),a=t(\"signum\"),i=t(\"two-sum\"),o=t(\"robust-product\"),s=t(\"robust-sum\");function l(t,e,r){var n=i(t[0],-e[0]),a=i(t[1],-e[1]),l=i(r[0],-e[0]),c=i(r[1],-e[1]),u=s(o(n,l),o(a,c));return u[u.length-1]>=0}},{\"robust-orientation\":509,\"robust-product\":510,\"robust-sum\":514,signum:515,\"two-sum\":543}],130:[function(t,e,r){e.exports=function(t,e){var r=t.length,i=t.length-e.length;if(i)return i;switch(r){case 0:return 0;case 1:return t[0]-e[0];case 2:return t[0]+t[1]-e[0]-e[1]||n(t[0],t[1])-n(e[0],e[1]);case 3:var o=t[0]+t[1],s=e[0]+e[1];if(i=o+t[2]-(s+e[2]))return i;var l=n(t[0],t[1]),c=n(e[0],e[1]);return n(l,t[2])-n(c,e[2])||n(l+t[2],o)-n(c+e[2],s);case 4:var u=t[0],h=t[1],f=t[2],p=t[3],d=e[0],g=e[1],v=e[2],m=e[3];return u+h+f+p-(d+g+v+m)||n(u,h,f,p)-n(d,g,v,m,d)||n(u+h,u+f,u+p,h+f,h+p,f+p)-n(d+g,d+v,d+m,g+v,g+m,v+m)||n(u+h+f,u+h+p,u+f+p,h+f+p)-n(d+g+v,d+g+m,d+v+m,g+v+m);default:for(var y=t.slice().sort(a),x=e.slice().sort(a),b=0;b<r;++b)if(i=y[b]-x[b])return i;return 0}};var n=Math.min;function a(t,e){return t-e}},{}],131:[function(t,e,r){\"use strict\";var n=t(\"compare-cell\"),a=t(\"cell-orientation\");e.exports=function(t,e){return n(t,e)||a(t)-a(e)}},{\"cell-orientation\":114,\"compare-cell\":130}],132:[function(t,e,r){\"use strict\";var n=t(\"./lib/ch1d\"),a=t(\"./lib/ch2d\"),i=t(\"./lib/chnd\");e.exports=function(t){var e=t.length;if(0===e)return[];if(1===e)return[[0]];var r=t[0].length;if(0===r)return[];if(1===r)return n(t);if(2===r)return a(t);return i(t,r)}},{\"./lib/ch1d\":133,\"./lib/ch2d\":134,\"./lib/chnd\":135}],133:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=0,r=0,n=1;n<t.length;++n)t[n][0]<t[e][0]&&(e=n),t[n][0]>t[r][0]&&(r=n);return e<r?[[e],[r]]:e>r?[[r],[e]]:[[e]]}},{}],134:[function(t,e,r){\"use strict\";e.exports=function(t){var e=n(t),r=e.length;if(r<=2)return[];for(var a=new Array(r),i=e[r-1],o=0;o<r;++o){var s=e[o];a[o]=[i,s],i=s}return a};var n=t(\"monotone-convex-hull-2d\")},{\"monotone-convex-hull-2d\":436}],135:[function(t,e,r){\"use strict\";e.exports=function(t,e){try{return n(t,!0)}catch(s){var r=a(t);if(r.length<=e)return[];var i=function(t,e){for(var r=t.length,n=new Array(r),a=0;a<e.length;++a)n[a]=t[e[a]];for(var i=e.length,a=0;a<r;++a)e.indexOf(a)<0&&(n[i++]=t[a]);return n}(t,r),o=n(i,!0);return function(t,e){for(var r=t.length,n=e.length,a=0;a<r;++a)for(var i=t[a],o=0;o<i.length;++o){var s=i[o];if(s<n)i[o]=e[s];else{s-=n;for(var l=0;l<n;++l)s>=e[l]&&(s+=1);i[o]=s}}return t}(o,r)}};var n=t(\"incremental-convex-hull\"),a=t(\"affine-hull\")},{\"affine-hull\":65,\"incremental-convex-hull\":415}],136:[function(t,e,r){e.exports={AFG:\"afghan\",ALA:\"\\\\b\\\\wland\",ALB:\"albania\",DZA:\"algeria\",ASM:\"^(?=.*americ).*samoa\",AND:\"andorra\",AGO:\"angola\",AIA:\"anguill?a\",ATA:\"antarctica\",ATG:\"antigua\",ARG:\"argentin\",ARM:\"armenia\",ABW:\"^(?!.*bonaire).*\\\\baruba\",AUS:\"australia\",AUT:\"^(?!.*hungary).*austria|\\\\baustri.*\\\\bemp\",AZE:\"azerbaijan\",BHS:\"bahamas\",BHR:\"bahrain\",BGD:\"bangladesh|^(?=.*east).*paki?stan\",BRB:\"barbados\",BLR:\"belarus|byelo\",BEL:\"^(?!.*luxem).*belgium\",BLZ:\"belize|^(?=.*british).*honduras\",BEN:\"benin|dahome\",BMU:\"bermuda\",BTN:\"bhutan\",BOL:\"bolivia\",BES:\"^(?=.*bonaire).*eustatius|^(?=.*carib).*netherlands|\\\\bbes.?islands\",BIH:\"herzegovina|bosnia\",BWA:\"botswana|bechuana\",BVT:\"bouvet\",BRA:\"brazil\",IOT:\"british.?indian.?ocean\",BRN:\"brunei\",BGR:\"bulgaria\",BFA:\"burkina|\\\\bfaso|upper.?volta\",BDI:\"burundi\",CPV:\"verde\",KHM:\"cambodia|kampuchea|khmer\",CMR:\"cameroon\",CAN:\"canada\",CYM:\"cayman\",CAF:\"\\\\bcentral.african.republic\",TCD:\"\\\\bchad\",CHL:\"\\\\bchile\",CHN:\"^(?!.*\\\\bmac)(?!.*\\\\bhong)(?!.*\\\\btai)(?!.*\\\\brep).*china|^(?=.*peo)(?=.*rep).*china\",CXR:\"christmas\",CCK:\"\\\\bcocos|keeling\",COL:\"colombia\",COM:\"comoro\",COG:\"^(?!.*\\\\bdem)(?!.*\\\\bd[\\\\.]?r)(?!.*kinshasa)(?!.*zaire)(?!.*belg)(?!.*l.opoldville)(?!.*free).*\\\\bcongo\",COK:\"\\\\bcook\",CRI:\"costa.?rica\",CIV:\"ivoire|ivory\",HRV:\"croatia\",CUB:\"\\\\bcuba\",CUW:\"^(?!.*bonaire).*\\\\bcura(c|\\xe7)ao\",CYP:\"cyprus\",CSK:\"czechoslovakia\",CZE:\"^(?=.*rep).*czech|czechia|bohemia\",COD:\"\\\\bdem.*congo|congo.*\\\\bdem|congo.*\\\\bd[\\\\.]?r|\\\\bd[\\\\.]?r.*congo|belgian.?congo|congo.?free.?state|kinshasa|zaire|l.opoldville|drc|droc|rdc\",DNK:\"denmark\",DJI:\"djibouti\",DMA:\"dominica(?!n)\",DOM:\"dominican.rep\",ECU:\"ecuador\",EGY:\"egypt\",SLV:\"el.?salvador\",GNQ:\"guine.*eq|eq.*guine|^(?=.*span).*guinea\",ERI:\"eritrea\",EST:\"estonia\",ETH:\"ethiopia|abyssinia\",FLK:\"falkland|malvinas\",FRO:\"faroe|faeroe\",FJI:\"fiji\",FIN:\"finland\",FRA:\"^(?!.*\\\\bdep)(?!.*martinique).*france|french.?republic|\\\\bgaul\",GUF:\"^(?=.*french).*guiana\",PYF:\"french.?polynesia|tahiti\",ATF:\"french.?southern\",GAB:\"gabon\",GMB:\"gambia\",GEO:\"^(?!.*south).*georgia\",DDR:\"german.?democratic.?republic|democratic.?republic.*germany|east.germany\",DEU:\"^(?!.*east).*germany|^(?=.*\\\\bfed.*\\\\brep).*german\",GHA:\"ghana|gold.?coast\",GIB:\"gibraltar\",GRC:\"greece|hellenic|hellas\",GRL:\"greenland\",GRD:\"grenada\",GLP:\"guadeloupe\",GUM:\"\\\\bguam\",GTM:\"guatemala\",GGY:\"guernsey\",GIN:\"^(?!.*eq)(?!.*span)(?!.*bissau)(?!.*portu)(?!.*new).*guinea\",GNB:\"bissau|^(?=.*portu).*guinea\",GUY:\"guyana|british.?guiana\",HTI:\"haiti\",HMD:\"heard.*mcdonald\",VAT:\"holy.?see|vatican|papal.?st\",HND:\"^(?!.*brit).*honduras\",HKG:\"hong.?kong\",HUN:\"^(?!.*austr).*hungary\",ISL:\"iceland\",IND:\"india(?!.*ocea)\",IDN:\"indonesia\",IRN:\"\\\\biran|persia\",IRQ:\"\\\\biraq|mesopotamia\",IRL:\"(^ireland)|(^republic.*ireland)\",IMN:\"^(?=.*isle).*\\\\bman\",ISR:\"israel\",ITA:\"italy\",JAM:\"jamaica\",JPN:\"japan\",JEY:\"jersey\",JOR:\"jordan\",KAZ:\"kazak\",KEN:\"kenya|british.?east.?africa|east.?africa.?prot\",KIR:\"kiribati\",PRK:\"^(?=.*democrat|people|north|d.*p.*.r).*\\\\bkorea|dprk|korea.*(d.*p.*r)\",KWT:\"kuwait\",KGZ:\"kyrgyz|kirghiz\",LAO:\"\\\\blaos?\\\\b\",LVA:\"latvia\",LBN:\"lebanon\",LSO:\"lesotho|basuto\",LBR:\"liberia\",LBY:\"libya\",LIE:\"liechtenstein\",LTU:\"lithuania\",LUX:\"^(?!.*belg).*luxem\",MAC:\"maca(o|u)\",MDG:\"madagascar|malagasy\",MWI:\"malawi|nyasa\",MYS:\"malaysia\",MDV:\"maldive\",MLI:\"\\\\bmali\\\\b\",MLT:\"\\\\bmalta\",MHL:\"marshall\",MTQ:\"martinique\",MRT:\"mauritania\",MUS:\"mauritius\",MYT:\"\\\\bmayotte\",MEX:\"\\\\bmexic\",FSM:\"fed.*micronesia|micronesia.*fed\",MCO:\"monaco\",MNG:\"mongolia\",MNE:\"^(?!.*serbia).*montenegro\",MSR:\"montserrat\",MAR:\"morocco|\\\\bmaroc\",MOZ:\"mozambique\",MMR:\"myanmar|burma\",NAM:\"namibia\",NRU:\"nauru\",NPL:\"nepal\",NLD:\"^(?!.*\\\\bant)(?!.*\\\\bcarib).*netherlands\",ANT:\"^(?=.*\\\\bant).*(nether|dutch)\",NCL:\"new.?caledonia\",NZL:\"new.?zealand\",NIC:\"nicaragua\",NER:\"\\\\bniger(?!ia)\",NGA:\"nigeria\",NIU:\"niue\",NFK:\"norfolk\",MNP:\"mariana\",NOR:\"norway\",OMN:\"\\\\boman|trucial\",PAK:\"^(?!.*east).*paki?stan\",PLW:\"palau\",PSE:\"palestin|\\\\bgaza|west.?bank\",PAN:\"panama\",PNG:\"papua|new.?guinea\",PRY:\"paraguay\",PER:\"peru\",PHL:\"philippines\",PCN:\"pitcairn\",POL:\"poland\",PRT:\"portugal\",PRI:\"puerto.?rico\",QAT:\"qatar\",KOR:\"^(?!.*d.*p.*r)(?!.*democrat)(?!.*people)(?!.*north).*\\\\bkorea(?!.*d.*p.*r)\",MDA:\"moldov|b(a|e)ssarabia\",REU:\"r(e|\\xe9)union\",ROU:\"r(o|u|ou)mania\",RUS:\"\\\\brussia|soviet.?union|u\\\\.?s\\\\.?s\\\\.?r|socialist.?republics\",RWA:\"rwanda\",BLM:\"barth(e|\\xe9)lemy\",SHN:\"helena\",KNA:\"kitts|\\\\bnevis\",LCA:\"\\\\blucia\",MAF:\"^(?=.*collectivity).*martin|^(?=.*france).*martin(?!ique)|^(?=.*french).*martin(?!ique)\",SPM:\"miquelon\",VCT:\"vincent\",WSM:\"^(?!.*amer).*samoa\",SMR:\"san.?marino\",STP:\"\\\\bs(a|\\xe3)o.?tom(e|\\xe9)\",SAU:\"\\\\bsa\\\\w*.?arabia\",SEN:\"senegal\",SRB:\"^(?!.*monte).*serbia\",SYC:\"seychell\",SLE:\"sierra\",SGP:\"singapore\",SXM:\"^(?!.*martin)(?!.*saba).*maarten\",SVK:\"^(?!.*cze).*slovak\",SVN:\"slovenia\",SLB:\"solomon\",SOM:\"somali\",ZAF:\"south.africa|s\\\\\\\\..?africa\",SGS:\"south.?georgia|sandwich\",SSD:\"\\\\bs\\\\w*.?sudan\",ESP:\"spain\",LKA:\"sri.?lanka|ceylon\",SDN:\"^(?!.*\\\\bs(?!u)).*sudan\",SUR:\"surinam|dutch.?guiana\",SJM:\"svalbard\",SWZ:\"swaziland\",SWE:\"sweden\",CHE:\"switz|swiss\",SYR:\"syria\",TWN:\"taiwan|taipei|formosa|^(?!.*peo)(?=.*rep).*china\",TJK:\"tajik\",THA:\"thailand|\\\\bsiam\",MKD:\"macedonia|fyrom\",TLS:\"^(?=.*leste).*timor|^(?=.*east).*timor\",TGO:\"togo\",TKL:\"tokelau\",TON:\"tonga\",TTO:\"trinidad|tobago\",TUN:\"tunisia\",TUR:\"turkey\",TKM:\"turkmen\",TCA:\"turks\",TUV:\"tuvalu\",UGA:\"uganda\",UKR:\"ukrain\",ARE:\"emirates|^u\\\\.?a\\\\.?e\\\\.?$|united.?arab.?em\",GBR:\"united.?kingdom|britain|^u\\\\.?k\\\\.?$\",TZA:\"tanzania\",USA:\"united.?states\\\\b(?!.*islands)|\\\\bu\\\\.?s\\\\.?a\\\\.?\\\\b|^\\\\s*u\\\\.?s\\\\.?\\\\b(?!.*islands)\",UMI:\"minor.?outlying.?is\",URY:\"uruguay\",UZB:\"uzbek\",VUT:\"vanuatu|new.?hebrides\",VEN:\"venezuela\",VNM:\"^(?!.*republic).*viet.?nam|^(?=.*socialist).*viet.?nam\",VGB:\"^(?=.*\\\\bu\\\\.?\\\\s?k).*virgin|^(?=.*brit).*virgin|^(?=.*kingdom).*virgin\",VIR:\"^(?=.*\\\\bu\\\\.?\\\\s?s).*virgin|^(?=.*states).*virgin\",WLF:\"futuna|wallis\",ESH:\"western.sahara\",YEM:\"^(?!.*arab)(?!.*north)(?!.*sana)(?!.*peo)(?!.*dem)(?!.*south)(?!.*aden)(?!.*\\\\bp\\\\.?d\\\\.?r).*yemen\",YMD:\"^(?=.*peo).*yemen|^(?!.*rep)(?=.*dem).*yemen|^(?=.*south).*yemen|^(?=.*aden).*yemen|^(?=.*\\\\bp\\\\.?d\\\\.?r).*yemen\",YUG:\"yugoslavia\",ZMB:\"zambia|northern.?rhodesia\",EAZ:\"zanzibar\",ZWE:\"zimbabwe|^(?!.*northern).*rhodesia\"}},{}],137:[function(t,e,r){e.exports=[\"xx-small\",\"x-small\",\"small\",\"medium\",\"large\",\"x-large\",\"xx-large\",\"larger\",\"smaller\"]},{}],138:[function(t,e,r){e.exports=[\"normal\",\"condensed\",\"semi-condensed\",\"extra-condensed\",\"ultra-condensed\",\"expanded\",\"semi-expanded\",\"extra-expanded\",\"ultra-expanded\"]},{}],139:[function(t,e,r){e.exports=[\"normal\",\"italic\",\"oblique\"]},{}],140:[function(t,e,r){e.exports=[\"normal\",\"bold\",\"bolder\",\"lighter\",\"100\",\"200\",\"300\",\"400\",\"500\",\"600\",\"700\",\"800\",\"900\"]},{}],141:[function(t,e,r){\"use strict\";e.exports={parse:t(\"./parse\"),stringify:t(\"./stringify\")}},{\"./parse\":143,\"./stringify\":144}],142:[function(t,e,r){\"use strict\";var n=t(\"css-font-size-keywords\");e.exports={isSize:function(t){return/^[\\d\\.]/.test(t)||-1!==t.indexOf(\"/\")||-1!==n.indexOf(t)}}},{\"css-font-size-keywords\":137}],143:[function(t,e,r){\"use strict\";var n=t(\"unquote\"),a=t(\"css-global-keywords\"),i=t(\"css-system-font-keywords\"),o=t(\"css-font-weight-keywords\"),s=t(\"css-font-style-keywords\"),l=t(\"css-font-stretch-keywords\"),c=t(\"string-split-by\"),u=t(\"./lib/util\").isSize;e.exports=f;var h=f.cache={};function f(t){if(\"string\"!=typeof t)throw new Error(\"Font argument must be a string.\");if(h[t])return h[t];if(\"\"===t)throw new Error(\"Cannot parse an empty string.\");if(-1!==i.indexOf(t))return h[t]={system:t};for(var e,r={style:\"normal\",variant:\"normal\",weight:\"normal\",stretch:\"normal\",lineHeight:\"normal\",size:\"1rem\",family:[\"serif\"]},f=c(t,/\\s+/);e=f.shift();){if(-1!==a.indexOf(e))return[\"style\",\"variant\",\"weight\",\"stretch\"].forEach(function(t){r[t]=e}),h[t]=r;if(-1===s.indexOf(e))if(\"normal\"!==e&&\"small-caps\"!==e)if(-1===l.indexOf(e)){if(-1===o.indexOf(e)){if(u(e)){var d=c(e,\"/\");if(r.size=d[0],null!=d[1]?r.lineHeight=p(d[1]):\"/\"===f[0]&&(f.shift(),r.lineHeight=p(f.shift())),!f.length)throw new Error(\"Missing required font-family.\");return r.family=c(f.join(\" \"),/\\s*,\\s*/).map(n),h[t]=r}throw new Error(\"Unknown or unsupported font token: \"+e)}r.weight=e}else r.stretch=e;else r.variant=e;else r.style=e}throw new Error(\"Missing required font-size.\")}function p(t){var e=parseFloat(t);return e.toString()===t?e:t}},{\"./lib/util\":142,\"css-font-stretch-keywords\":138,\"css-font-style-keywords\":139,\"css-font-weight-keywords\":140,\"css-global-keywords\":145,\"css-system-font-keywords\":146,\"string-split-by\":528,unquote:547}],144:[function(t,e,r){\"use strict\";var n=t(\"pick-by-alias\"),a=t(\"./lib/util\").isSize,i=g(t(\"css-global-keywords\")),o=g(t(\"css-system-font-keywords\")),s=g(t(\"css-font-weight-keywords\")),l=g(t(\"css-font-style-keywords\")),c=g(t(\"css-font-stretch-keywords\")),u={normal:1,\"small-caps\":1},h={serif:1,\"sans-serif\":1,monospace:1,cursive:1,fantasy:1,\"system-ui\":1},f=\"1rem\",p=\"serif\";function d(t,e){if(t&&!e[t]&&!i[t])throw Error(\"Unknown keyword `\"+t+\"`\");return t}function g(t){for(var e={},r=0;r<t.length;r++)e[t[r]]=1;return e}e.exports=function(t){if((t=n(t,{style:\"style fontstyle fontStyle font-style slope distinction\",variant:\"variant font-variant fontVariant fontvariant var capitalization\",weight:\"weight w font-weight fontWeight fontweight\",stretch:\"stretch font-stretch fontStretch fontstretch width\",size:\"size s font-size fontSize fontsize height em emSize\",lineHeight:\"lh line-height lineHeight lineheight leading\",family:\"font family fontFamily font-family fontfamily type typeface face\",system:\"system reserved default global\"})).system)return t.system&&d(t.system,o),t.system;if(d(t.style,l),d(t.variant,u),d(t.weight,s),d(t.stretch,c),null==t.size&&(t.size=f),\"number\"==typeof t.size&&(t.size+=\"px\"),!a)throw Error(\"Bad size value `\"+t.size+\"`\");t.family||(t.family=p),Array.isArray(t.family)&&(t.family.length||(t.family=[p]),t.family=t.family.map(function(t){return h[t]?t:'\"'+t+'\"'}).join(\", \"));var e=[];return e.push(t.style),t.variant!==t.style&&e.push(t.variant),t.weight!==t.variant&&t.weight!==t.style&&e.push(t.weight),t.stretch!==t.weight&&t.stretch!==t.variant&&t.stretch!==t.style&&e.push(t.stretch),e.push(t.size+(null==t.lineHeight||\"normal\"===t.lineHeight||t.lineHeight+\"\"==\"1\"?\"\":\"/\"+t.lineHeight)),e.push(t.family),e.filter(Boolean).join(\" \")}},{\"./lib/util\":142,\"css-font-stretch-keywords\":138,\"css-font-style-keywords\":139,\"css-font-weight-keywords\":140,\"css-global-keywords\":145,\"css-system-font-keywords\":146,\"pick-by-alias\":467}],145:[function(t,e,r){e.exports=[\"inherit\",\"initial\",\"unset\"]},{}],146:[function(t,e,r){e.exports=[\"caption\",\"icon\",\"menu\",\"message-box\",\"small-caption\",\"status-bar\"]},{}],147:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,a,i){var o=a-1,s=a*a,l=o*o,c=(1+2*a)*l,u=a*l,h=s*(3-2*a),f=s*o;if(t.length){i||(i=new Array(t.length));for(var p=t.length-1;p>=0;--p)i[p]=c*t[p]+u*e[p]+h*r[p]+f*n[p];return i}return c*t+u*e+h*r+f*n},e.exports.derivative=function(t,e,r,n,a,i){var o=6*a*a-6*a,s=3*a*a-4*a+1,l=-6*a*a+6*a,c=3*a*a-2*a;if(t.length){i||(i=new Array(t.length));for(var u=t.length-1;u>=0;--u)i[u]=o*t[u]+s*e[u]+l*r[u]+c*n[u];return i}return o*t+s*e+l*r[u]+c*n}},{}],148:[function(t,e,r){\"use strict\";var n=t(\"./lib/thunk.js\");function a(){this.argTypes=[],this.shimArgs=[],this.arrayArgs=[],this.arrayBlockIndices=[],this.scalarArgs=[],this.offsetArgs=[],this.offsetArgIndex=[],this.indexArgs=[],this.shapeArgs=[],this.funcName=\"\",this.pre=null,this.body=null,this.post=null,this.debug=!1}e.exports=function(t){var e=new a;e.pre=t.pre,e.body=t.body,e.post=t.post;var r=t.args.slice(0);e.argTypes=r;for(var i=0;i<r.length;++i){var o=r[i];if(\"array\"===o||\"object\"==typeof o&&o.blockIndices){if(e.argTypes[i]=\"array\",e.arrayArgs.push(i),e.arrayBlockIndices.push(o.blockIndices?o.blockIndices:0),e.shimArgs.push(\"array\"+i),i<e.pre.args.length&&e.pre.args[i].count>0)throw new Error(\"cwise: pre() block may not reference array args\");if(i<e.post.args.length&&e.post.args[i].count>0)throw new Error(\"cwise: post() block may not reference array args\")}else if(\"scalar\"===o)e.scalarArgs.push(i),e.shimArgs.push(\"scalar\"+i);else if(\"index\"===o){if(e.indexArgs.push(i),i<e.pre.args.length&&e.pre.args[i].count>0)throw new Error(\"cwise: pre() block may not reference array index\");if(i<e.body.args.length&&e.body.args[i].lvalue)throw new Error(\"cwise: body() block may not write to array index\");if(i<e.post.args.length&&e.post.args[i].count>0)throw new Error(\"cwise: post() block may not reference array index\")}else if(\"shape\"===o){if(e.shapeArgs.push(i),i<e.pre.args.length&&e.pre.args[i].lvalue)throw new Error(\"cwise: pre() block may not write to array shape\");if(i<e.body.args.length&&e.body.args[i].lvalue)throw new Error(\"cwise: body() block may not write to array shape\");if(i<e.post.args.length&&e.post.args[i].lvalue)throw new Error(\"cwise: post() block may not write to array shape\")}else{if(\"object\"!=typeof o||!o.offset)throw new Error(\"cwise: Unknown argument type \"+r[i]);e.argTypes[i]=\"offset\",e.offsetArgs.push({array:o.array,offset:o.offset}),e.offsetArgIndex.push(i)}}if(e.arrayArgs.length<=0)throw new Error(\"cwise: No array arguments specified\");if(e.pre.args.length>r.length)throw new Error(\"cwise: Too many arguments in pre() block\");if(e.body.args.length>r.length)throw new Error(\"cwise: Too many arguments in body() block\");if(e.post.args.length>r.length)throw new Error(\"cwise: Too many arguments in post() block\");return e.debug=!!t.printCode||!!t.debug,e.funcName=t.funcName||\"cwise\",e.blockSize=t.blockSize||64,n(e)}},{\"./lib/thunk.js\":150}],149:[function(t,e,r){\"use strict\";var n=t(\"uniq\");function a(t,e,r){var n,a,i=t.length,o=e.arrayArgs.length,s=e.indexArgs.length>0,l=[],c=[],u=0,h=0;for(n=0;n<i;++n)c.push([\"i\",n,\"=0\"].join(\"\"));for(a=0;a<o;++a)for(n=0;n<i;++n)h=u,u=t[n],0===n?c.push([\"d\",a,\"s\",n,\"=t\",a,\"p\",u].join(\"\")):c.push([\"d\",a,\"s\",n,\"=(t\",a,\"p\",u,\"-s\",h,\"*t\",a,\"p\",h,\")\"].join(\"\"));for(c.length>0&&l.push(\"var \"+c.join(\",\")),n=i-1;n>=0;--n)u=t[n],l.push([\"for(i\",n,\"=0;i\",n,\"<s\",u,\";++i\",n,\"){\"].join(\"\"));for(l.push(r),n=0;n<i;++n){for(h=u,u=t[n],a=0;a<o;++a)l.push([\"p\",a,\"+=d\",a,\"s\",n].join(\"\"));s&&(n>0&&l.push([\"index[\",h,\"]-=s\",h].join(\"\")),l.push([\"++index[\",u,\"]\"].join(\"\"))),l.push(\"}\")}return l.join(\"\\n\")}function i(t,e,r){for(var n=t.body,a=[],i=[],o=0;o<t.args.length;++o){var s=t.args[o];if(!(s.count<=0)){var l=new RegExp(s.name,\"g\"),c=\"\",u=e.arrayArgs.indexOf(o);switch(e.argTypes[o]){case\"offset\":var h=e.offsetArgIndex.indexOf(o);u=e.offsetArgs[h].array,c=\"+q\"+h;case\"array\":c=\"p\"+u+c;var f=\"l\"+o,p=\"a\"+u;if(0===e.arrayBlockIndices[u])1===s.count?\"generic\"===r[u]?s.lvalue?(a.push([\"var \",f,\"=\",p,\".get(\",c,\")\"].join(\"\")),n=n.replace(l,f),i.push([p,\".set(\",c,\",\",f,\")\"].join(\"\"))):n=n.replace(l,[p,\".get(\",c,\")\"].join(\"\")):n=n.replace(l,[p,\"[\",c,\"]\"].join(\"\")):\"generic\"===r[u]?(a.push([\"var \",f,\"=\",p,\".get(\",c,\")\"].join(\"\")),n=n.replace(l,f),s.lvalue&&i.push([p,\".set(\",c,\",\",f,\")\"].join(\"\"))):(a.push([\"var \",f,\"=\",p,\"[\",c,\"]\"].join(\"\")),n=n.replace(l,f),s.lvalue&&i.push([p,\"[\",c,\"]=\",f].join(\"\")));else{for(var d=[s.name],g=[c],v=0;v<Math.abs(e.arrayBlockIndices[u]);v++)d.push(\"\\\\s*\\\\[([^\\\\]]+)\\\\]\"),g.push(\"$\"+(v+1)+\"*t\"+u+\"b\"+v);if(l=new RegExp(d.join(\"\"),\"g\"),c=g.join(\"+\"),\"generic\"===r[u])throw new Error(\"cwise: Generic arrays not supported in combination with blocks!\");n=n.replace(l,[p,\"[\",c,\"]\"].join(\"\"))}break;case\"scalar\":n=n.replace(l,\"Y\"+e.scalarArgs.indexOf(o));break;case\"index\":n=n.replace(l,\"index\");break;case\"shape\":n=n.replace(l,\"shape\")}}}return[a.join(\"\\n\"),n,i.join(\"\\n\")].join(\"\\n\").trim()}function o(t){for(var e=new Array(t.length),r=!0,n=0;n<t.length;++n){var a=t[n],i=a.match(/\\d+/);i=i?i[0]:\"\",0===a.charAt(0)?e[n]=\"u\"+a.charAt(1)+i:e[n]=a.charAt(0)+i,n>0&&(r=r&&e[n]===e[n-1])}return r?e[0]:e.join(\"\")}e.exports=function(t,e){for(var r=e[1].length-Math.abs(t.arrayBlockIndices[0])|0,s=new Array(t.arrayArgs.length),l=new Array(t.arrayArgs.length),c=0;c<t.arrayArgs.length;++c)l[c]=e[2*c],s[c]=e[2*c+1];var u=[],h=[],f=[],p=[],d=[];for(c=0;c<t.arrayArgs.length;++c){t.arrayBlockIndices[c]<0?(f.push(0),p.push(r),u.push(r),h.push(r+t.arrayBlockIndices[c])):(f.push(t.arrayBlockIndices[c]),p.push(t.arrayBlockIndices[c]+r),u.push(0),h.push(t.arrayBlockIndices[c]));for(var g=[],v=0;v<s[c].length;v++)f[c]<=s[c][v]&&s[c][v]<p[c]&&g.push(s[c][v]-f[c]);d.push(g)}var m=[\"SS\"],y=[\"'use strict'\"],x=[];for(v=0;v<r;++v)x.push([\"s\",v,\"=SS[\",v,\"]\"].join(\"\"));for(c=0;c<t.arrayArgs.length;++c){for(m.push(\"a\"+c),m.push(\"t\"+c),m.push(\"p\"+c),v=0;v<r;++v)x.push([\"t\",c,\"p\",v,\"=t\",c,\"[\",f[c]+v,\"]\"].join(\"\"));for(v=0;v<Math.abs(t.arrayBlockIndices[c]);++v)x.push([\"t\",c,\"b\",v,\"=t\",c,\"[\",u[c]+v,\"]\"].join(\"\"))}for(c=0;c<t.scalarArgs.length;++c)m.push(\"Y\"+c);if(t.shapeArgs.length>0&&x.push(\"shape=SS.slice(0)\"),t.indexArgs.length>0){var b=new Array(r);for(c=0;c<r;++c)b[c]=\"0\";x.push([\"index=[\",b.join(\",\"),\"]\"].join(\"\"))}for(c=0;c<t.offsetArgs.length;++c){var _=t.offsetArgs[c],w=[];for(v=0;v<_.offset.length;++v)0!==_.offset[v]&&(1===_.offset[v]?w.push([\"t\",_.array,\"p\",v].join(\"\")):w.push([_.offset[v],\"*t\",_.array,\"p\",v].join(\"\")));0===w.length?x.push(\"q\"+c+\"=0\"):x.push([\"q\",c,\"=\",w.join(\"+\")].join(\"\"))}var k=n([].concat(t.pre.thisVars).concat(t.body.thisVars).concat(t.post.thisVars));for((x=x.concat(k)).length>0&&y.push(\"var \"+x.join(\",\")),c=0;c<t.arrayArgs.length;++c)y.push(\"p\"+c+\"|=0\");t.pre.body.length>3&&y.push(i(t.pre,t,l));var T=i(t.body,t,l),M=function(t){for(var e=0,r=t[0].length;e<r;){for(var n=1;n<t.length;++n)if(t[n][e]!==t[0][e])return e;++e}return e}(d);M<r?y.push(function(t,e,r,n){for(var i=e.length,o=r.arrayArgs.length,s=r.blockSize,l=r.indexArgs.length>0,c=[],u=0;u<o;++u)c.push([\"var offset\",u,\"=p\",u].join(\"\"));for(u=t;u<i;++u)c.push([\"for(var j\"+u+\"=SS[\",e[u],\"]|0;j\",u,\">0;){\"].join(\"\")),c.push([\"if(j\",u,\"<\",s,\"){\"].join(\"\")),c.push([\"s\",e[u],\"=j\",u].join(\"\")),c.push([\"j\",u,\"=0\"].join(\"\")),c.push([\"}else{s\",e[u],\"=\",s].join(\"\")),c.push([\"j\",u,\"-=\",s,\"}\"].join(\"\")),l&&c.push([\"index[\",e[u],\"]=j\",u].join(\"\"));for(u=0;u<o;++u){for(var h=[\"offset\"+u],f=t;f<i;++f)h.push([\"j\",f,\"*t\",u,\"p\",e[f]].join(\"\"));c.push([\"p\",u,\"=(\",h.join(\"+\"),\")\"].join(\"\"))}for(c.push(a(e,r,n)),u=t;u<i;++u)c.push(\"}\");return c.join(\"\\n\")}(M,d[0],t,T)):y.push(a(d[0],t,T)),t.post.body.length>3&&y.push(i(t.post,t,l)),t.debug&&console.log(\"-----Generated cwise routine for \",e,\":\\n\"+y.join(\"\\n\")+\"\\n----------\");var A=[t.funcName||\"unnamed\",\"_cwise_loop_\",s[0].join(\"s\"),\"m\",M,o(l)].join(\"\");return new Function([\"function \",A,\"(\",m.join(\",\"),\"){\",y.join(\"\\n\"),\"} return \",A].join(\"\"))()}},{uniq:546}],150:[function(t,e,r){\"use strict\";var n=t(\"./compile.js\");e.exports=function(t){var e=[\"'use strict'\",\"var CACHED={}\"],r=[],a=t.funcName+\"_cwise_thunk\";e.push([\"return function \",a,\"(\",t.shimArgs.join(\",\"),\"){\"].join(\"\"));for(var i=[],o=[],s=[[\"array\",t.arrayArgs[0],\".shape.slice(\",Math.max(0,t.arrayBlockIndices[0]),t.arrayBlockIndices[0]<0?\",\"+t.arrayBlockIndices[0]+\")\":\")\"].join(\"\")],l=[],c=[],u=0;u<t.arrayArgs.length;++u){var h=t.arrayArgs[u];r.push([\"t\",h,\"=array\",h,\".dtype,\",\"r\",h,\"=array\",h,\".order\"].join(\"\")),i.push(\"t\"+h),i.push(\"r\"+h),o.push(\"t\"+h),o.push(\"r\"+h+\".join()\"),s.push(\"array\"+h+\".data\"),s.push(\"array\"+h+\".stride\"),s.push(\"array\"+h+\".offset|0\"),u>0&&(l.push(\"array\"+t.arrayArgs[0]+\".shape.length===array\"+h+\".shape.length+\"+(Math.abs(t.arrayBlockIndices[0])-Math.abs(t.arrayBlockIndices[u]))),c.push(\"array\"+t.arrayArgs[0]+\".shape[shapeIndex+\"+Math.max(0,t.arrayBlockIndices[0])+\"]===array\"+h+\".shape[shapeIndex+\"+Math.max(0,t.arrayBlockIndices[u])+\"]\"))}for(t.arrayArgs.length>1&&(e.push(\"if (!(\"+l.join(\" && \")+\")) throw new Error('cwise: Arrays do not all have the same dimensionality!')\"),e.push(\"for(var shapeIndex=array\"+t.arrayArgs[0]+\".shape.length-\"+Math.abs(t.arrayBlockIndices[0])+\"; shapeIndex--\\x3e0;) {\"),e.push(\"if (!(\"+c.join(\" && \")+\")) throw new Error('cwise: Arrays do not all have the same shape!')\"),e.push(\"}\")),u=0;u<t.scalarArgs.length;++u)s.push(\"scalar\"+t.scalarArgs[u]);return r.push([\"type=[\",o.join(\",\"),\"].join()\"].join(\"\")),r.push(\"proc=CACHED[type]\"),e.push(\"var \"+r.join(\",\")),e.push([\"if(!proc){\",\"CACHED[type]=proc=compile([\",i.join(\",\"),\"])}\",\"return proc(\",s.join(\",\"),\")}\"].join(\"\")),t.debug&&console.log(\"-----Generated thunk:\\n\"+e.join(\"\\n\")+\"\\n----------\"),new Function(\"compile\",e.join(\"\\n\"))(n.bind(void 0,t))}},{\"./compile.js\":149}],151:[function(t,e,r){e.exports=t(\"cwise-compiler\")},{\"cwise-compiler\":148}],152:[function(t,e,r){\"use strict\";var n,a=t(\"es5-ext/object/copy\"),i=t(\"es5-ext/object/normalize-options\"),o=t(\"es5-ext/object/valid-callable\"),s=t(\"es5-ext/object/map\"),l=t(\"es5-ext/object/valid-callable\"),c=t(\"es5-ext/object/valid-value\"),u=Function.prototype.bind,h=Object.defineProperty,f=Object.prototype.hasOwnProperty;n=function(t,e,r){var n,i=c(e)&&l(e.value);return delete(n=a(e)).writable,delete n.value,n.get=function(){return!r.overwriteDefinition&&f.call(this,t)?i:(e.value=u.call(i,r.resolveContext?r.resolveContext(this):this),h(this,t,e),this[t])},n},e.exports=function(t){var e=i(arguments[1]);return null!=e.resolveContext&&o(e.resolveContext),s(t,function(t,r){return n(r,t,e)})}},{\"es5-ext/object/copy\":192,\"es5-ext/object/map\":201,\"es5-ext/object/normalize-options\":202,\"es5-ext/object/valid-callable\":206,\"es5-ext/object/valid-value\":208}],153:[function(t,e,r){\"use strict\";var n=t(\"es5-ext/object/assign\"),a=t(\"es5-ext/object/normalize-options\"),i=t(\"es5-ext/object/is-callable\"),o=t(\"es5-ext/string/#/contains\");(e.exports=function(t,e){var r,i,s,l,c;return arguments.length<2||\"string\"!=typeof t?(l=e,e=t,t=null):l=arguments[2],null==t?(r=s=!0,i=!1):(r=o.call(t,\"c\"),i=o.call(t,\"e\"),s=o.call(t,\"w\")),c={value:e,configurable:r,enumerable:i,writable:s},l?n(a(l),c):c}).gs=function(t,e,r){var s,l,c,u;return\"string\"!=typeof t?(c=r,r=e,e=t,t=null):c=arguments[3],null==e?e=void 0:i(e)?null==r?r=void 0:i(r)||(c=r,r=void 0):(c=e,e=r=void 0),null==t?(s=!0,l=!1):(s=o.call(t,\"c\"),l=o.call(t,\"e\")),u={get:e,set:r,configurable:s,enumerable:l},c?n(a(c),u):u}},{\"es5-ext/object/assign\":189,\"es5-ext/object/is-callable\":195,\"es5-ext/object/normalize-options\":202,\"es5-ext/string/#/contains\":209}],154:[function(t,e,r){var n;n=this,function(t){\"use strict\";function e(t,e){return t<e?-1:t>e?1:t>=e?0:NaN}function r(t){var r;return 1===t.length&&(r=t,t=function(t,n){return e(r(t),n)}),{left:function(e,r,n,a){for(null==n&&(n=0),null==a&&(a=e.length);n<a;){var i=n+a>>>1;t(e[i],r)<0?n=i+1:a=i}return n},right:function(e,r,n,a){for(null==n&&(n=0),null==a&&(a=e.length);n<a;){var i=n+a>>>1;t(e[i],r)>0?a=i:n=i+1}return n}}}var n=r(e),a=n.right,i=n.left;function o(t,e){return[t,e]}function s(t){return null===t?NaN:+t}function l(t,e){var r,n,a=t.length,i=0,o=-1,l=0,c=0;if(null==e)for(;++o<a;)isNaN(r=s(t[o]))||(c+=(n=r-l)*(r-(l+=n/++i)));else for(;++o<a;)isNaN(r=s(e(t[o],o,t)))||(c+=(n=r-l)*(r-(l+=n/++i)));if(i>1)return c/(i-1)}function c(t,e){var r=l(t,e);return r?Math.sqrt(r):r}function u(t,e){var r,n,a,i=t.length,o=-1;if(null==e){for(;++o<i;)if(null!=(r=t[o])&&r>=r)for(n=a=r;++o<i;)null!=(r=t[o])&&(n>r&&(n=r),a<r&&(a=r))}else for(;++o<i;)if(null!=(r=e(t[o],o,t))&&r>=r)for(n=a=r;++o<i;)null!=(r=e(t[o],o,t))&&(n>r&&(n=r),a<r&&(a=r));return[n,a]}var h=Array.prototype,f=h.slice,p=h.map;function d(t){return function(){return t}}function g(t){return t}function v(t,e,r){t=+t,e=+e,r=(a=arguments.length)<2?(e=t,t=0,1):a<3?1:+r;for(var n=-1,a=0|Math.max(0,Math.ceil((e-t)/r)),i=new Array(a);++n<a;)i[n]=t+n*r;return i}var m=Math.sqrt(50),y=Math.sqrt(10),x=Math.sqrt(2);function b(t,e,r){var n=(e-t)/Math.max(0,r),a=Math.floor(Math.log(n)/Math.LN10),i=n/Math.pow(10,a);return a>=0?(i>=m?10:i>=y?5:i>=x?2:1)*Math.pow(10,a):-Math.pow(10,-a)/(i>=m?10:i>=y?5:i>=x?2:1)}function _(t,e,r){var n=Math.abs(e-t)/Math.max(0,r),a=Math.pow(10,Math.floor(Math.log(n)/Math.LN10)),i=n/a;return i>=m?a*=10:i>=y?a*=5:i>=x&&(a*=2),e<t?-a:a}function w(t){return Math.ceil(Math.log(t.length)/Math.LN2)+1}function k(t,e,r){if(null==r&&(r=s),n=t.length){if((e=+e)<=0||n<2)return+r(t[0],0,t);if(e>=1)return+r(t[n-1],n-1,t);var n,a=(n-1)*e,i=Math.floor(a),o=+r(t[i],i,t);return o+(+r(t[i+1],i+1,t)-o)*(a-i)}}function T(t,e){var r,n,a=t.length,i=-1;if(null==e){for(;++i<a;)if(null!=(r=t[i])&&r>=r)for(n=r;++i<a;)null!=(r=t[i])&&n>r&&(n=r)}else for(;++i<a;)if(null!=(r=e(t[i],i,t))&&r>=r)for(n=r;++i<a;)null!=(r=e(t[i],i,t))&&n>r&&(n=r);return n}function M(t){if(!(a=t.length))return[];for(var e=-1,r=T(t,A),n=new Array(r);++e<r;)for(var a,i=-1,o=n[e]=new Array(a);++i<a;)o[i]=t[i][e];return n}function A(t){return t.length}t.bisect=a,t.bisectRight=a,t.bisectLeft=i,t.ascending=e,t.bisector=r,t.cross=function(t,e,r){var n,a,i,s,l=t.length,c=e.length,u=new Array(l*c);for(null==r&&(r=o),n=i=0;n<l;++n)for(s=t[n],a=0;a<c;++a,++i)u[i]=r(s,e[a]);return u},t.descending=function(t,e){return e<t?-1:e>t?1:e>=t?0:NaN},t.deviation=c,t.extent=u,t.histogram=function(){var t=g,e=u,r=w;function n(n){var i,o,s=n.length,l=new Array(s);for(i=0;i<s;++i)l[i]=t(n[i],i,n);var c=e(l),u=c[0],h=c[1],f=r(l,u,h);Array.isArray(f)||(f=_(u,h,f),f=v(Math.ceil(u/f)*f,h,f));for(var p=f.length;f[0]<=u;)f.shift(),--p;for(;f[p-1]>h;)f.pop(),--p;var d,g=new Array(p+1);for(i=0;i<=p;++i)(d=g[i]=[]).x0=i>0?f[i-1]:u,d.x1=i<p?f[i]:h;for(i=0;i<s;++i)u<=(o=l[i])&&o<=h&&g[a(f,o,0,p)].push(n[i]);return g}return n.value=function(e){return arguments.length?(t=\"function\"==typeof e?e:d(e),n):t},n.domain=function(t){return arguments.length?(e=\"function\"==typeof t?t:d([t[0],t[1]]),n):e},n.thresholds=function(t){return arguments.length?(r=\"function\"==typeof t?t:Array.isArray(t)?d(f.call(t)):d(t),n):r},n},t.thresholdFreedmanDiaconis=function(t,r,n){return t=p.call(t,s).sort(e),Math.ceil((n-r)/(2*(k(t,.75)-k(t,.25))*Math.pow(t.length,-1/3)))},t.thresholdScott=function(t,e,r){return Math.ceil((r-e)/(3.5*c(t)*Math.pow(t.length,-1/3)))},t.thresholdSturges=w,t.max=function(t,e){var r,n,a=t.length,i=-1;if(null==e){for(;++i<a;)if(null!=(r=t[i])&&r>=r)for(n=r;++i<a;)null!=(r=t[i])&&r>n&&(n=r)}else for(;++i<a;)if(null!=(r=e(t[i],i,t))&&r>=r)for(n=r;++i<a;)null!=(r=e(t[i],i,t))&&r>n&&(n=r);return n},t.mean=function(t,e){var r,n=t.length,a=n,i=-1,o=0;if(null==e)for(;++i<n;)isNaN(r=s(t[i]))?--a:o+=r;else for(;++i<n;)isNaN(r=s(e(t[i],i,t)))?--a:o+=r;if(a)return o/a},t.median=function(t,r){var n,a=t.length,i=-1,o=[];if(null==r)for(;++i<a;)isNaN(n=s(t[i]))||o.push(n);else for(;++i<a;)isNaN(n=s(r(t[i],i,t)))||o.push(n);return k(o.sort(e),.5)},t.merge=function(t){for(var e,r,n,a=t.length,i=-1,o=0;++i<a;)o+=t[i].length;for(r=new Array(o);--a>=0;)for(e=(n=t[a]).length;--e>=0;)r[--o]=n[e];return r},t.min=T,t.pairs=function(t,e){null==e&&(e=o);for(var r=0,n=t.length-1,a=t[0],i=new Array(n<0?0:n);r<n;)i[r]=e(a,a=t[++r]);return i},t.permute=function(t,e){for(var r=e.length,n=new Array(r);r--;)n[r]=t[e[r]];return n},t.quantile=k,t.range=v,t.scan=function(t,r){if(n=t.length){var n,a,i=0,o=0,s=t[o];for(null==r&&(r=e);++i<n;)(r(a=t[i],s)<0||0!==r(s,s))&&(s=a,o=i);return 0===r(s,s)?o:void 0}},t.shuffle=function(t,e,r){for(var n,a,i=(null==r?t.length:r)-(e=null==e?0:+e);i;)a=Math.random()*i--|0,n=t[i+e],t[i+e]=t[a+e],t[a+e]=n;return t},t.sum=function(t,e){var r,n=t.length,a=-1,i=0;if(null==e)for(;++a<n;)(r=+t[a])&&(i+=r);else for(;++a<n;)(r=+e(t[a],a,t))&&(i+=r);return i},t.ticks=function(t,e,r){var n,a,i,o,s=-1;if(r=+r,(t=+t)==(e=+e)&&r>0)return[t];if((n=e<t)&&(a=t,t=e,e=a),0===(o=b(t,e,r))||!isFinite(o))return[];if(o>0)for(t=Math.ceil(t/o),e=Math.floor(e/o),i=new Array(a=Math.ceil(e-t+1));++s<a;)i[s]=(t+s)*o;else for(t=Math.floor(t*o),e=Math.ceil(e*o),i=new Array(a=Math.ceil(t-e+1));++s<a;)i[s]=(t-s)/o;return n&&i.reverse(),i},t.tickIncrement=b,t.tickStep=_,t.transpose=M,t.variance=l,t.zip=function(){return M(arguments)},Object.defineProperty(t,\"__esModule\",{value:!0})}(\"object\"==typeof r&&\"undefined\"!=typeof e?r:n.d3=n.d3||{})},{}],155:[function(t,e,r){var n;n=this,function(t){\"use strict\";function e(){}function r(t,r){var n=new e;if(t instanceof e)t.each(function(t,e){n.set(e,t)});else if(Array.isArray(t)){var a,i=-1,o=t.length;if(null==r)for(;++i<o;)n.set(i,t[i]);else for(;++i<o;)n.set(r(a=t[i],i,t),a)}else if(t)for(var s in t)n.set(s,t[s]);return n}function n(){return{}}function a(t,e,r){t[e]=r}function i(){return r()}function o(t,e,r){t.set(e,r)}function s(){}e.prototype=r.prototype={constructor:e,has:function(t){return\"$\"+t in this},get:function(t){return this[\"$\"+t]},set:function(t,e){return this[\"$\"+t]=e,this},remove:function(t){var e=\"$\"+t;return e in this&&delete this[e]},clear:function(){for(var t in this)\"$\"===t[0]&&delete this[t]},keys:function(){var t=[];for(var e in this)\"$\"===e[0]&&t.push(e.slice(1));return t},values:function(){var t=[];for(var e in this)\"$\"===e[0]&&t.push(this[e]);return t},entries:function(){var t=[];for(var e in this)\"$\"===e[0]&&t.push({key:e.slice(1),value:this[e]});return t},size:function(){var t=0;for(var e in this)\"$\"===e[0]&&++t;return t},empty:function(){for(var t in this)if(\"$\"===t[0])return!1;return!0},each:function(t){for(var e in this)\"$\"===e[0]&&t(this[e],e.slice(1),this)}};var l=r.prototype;function c(t,e){var r=new s;if(t instanceof s)t.each(function(t){r.add(t)});else if(t){var n=-1,a=t.length;if(null==e)for(;++n<a;)r.add(t[n]);else for(;++n<a;)r.add(e(t[n],n,t))}return r}s.prototype=c.prototype={constructor:s,has:l.has,add:function(t){return this[\"$\"+(t+=\"\")]=t,this},remove:l.remove,clear:l.clear,values:l.keys,size:l.size,empty:l.empty,each:l.each},t.nest=function(){var t,e,s,l=[],c=[];function u(n,a,i,o){if(a>=l.length)return null!=t&&n.sort(t),null!=e?e(n):n;for(var s,c,h,f=-1,p=n.length,d=l[a++],g=r(),v=i();++f<p;)(h=g.get(s=d(c=n[f])+\"\"))?h.push(c):g.set(s,[c]);return g.each(function(t,e){o(v,e,u(t,a,i,o))}),v}return s={object:function(t){return u(t,0,n,a)},map:function(t){return u(t,0,i,o)},entries:function(t){return function t(r,n){if(++n>l.length)return r;var a,i=c[n-1];return null!=e&&n>=l.length?a=r.entries():(a=[],r.each(function(e,r){a.push({key:r,values:t(e,n)})})),null!=i?a.sort(function(t,e){return i(t.key,e.key)}):a}(u(t,0,i,o),0)},key:function(t){return l.push(t),s},sortKeys:function(t){return c[l.length-1]=t,s},sortValues:function(e){return t=e,s},rollup:function(t){return e=t,s}}},t.set=c,t.map=r,t.keys=function(t){var e=[];for(var r in t)e.push(r);return e},t.values=function(t){var e=[];for(var r in t)e.push(t[r]);return e},t.entries=function(t){var e=[];for(var r in t)e.push({key:r,value:t[r]});return e},Object.defineProperty(t,\"__esModule\",{value:!0})}(\"object\"==typeof r&&\"undefined\"!=typeof e?r:n.d3=n.d3||{})},{}],156:[function(t,e,r){var n;n=this,function(t){\"use strict\";function e(t,e,r){t.prototype=e.prototype=r,r.constructor=t}function r(t,e){var r=Object.create(t.prototype);for(var n in e)r[n]=e[n];return r}function n(){}var a=\"\\\\s*([+-]?\\\\d+)\\\\s*\",i=\"\\\\s*([+-]?\\\\d*\\\\.?\\\\d+(?:[eE][+-]?\\\\d+)?)\\\\s*\",o=\"\\\\s*([+-]?\\\\d*\\\\.?\\\\d+(?:[eE][+-]?\\\\d+)?)%\\\\s*\",s=/^#([0-9a-f]{3,8})$/,l=new RegExp(\"^rgb\\\\(\"+[a,a,a]+\"\\\\)$\"),c=new RegExp(\"^rgb\\\\(\"+[o,o,o]+\"\\\\)$\"),u=new RegExp(\"^rgba\\\\(\"+[a,a,a,i]+\"\\\\)$\"),h=new RegExp(\"^rgba\\\\(\"+[o,o,o,i]+\"\\\\)$\"),f=new RegExp(\"^hsl\\\\(\"+[i,o,o]+\"\\\\)$\"),p=new RegExp(\"^hsla\\\\(\"+[i,o,o,i]+\"\\\\)$\"),d={aliceblue:15792383,antiquewhite:16444375,aqua:65535,aquamarine:8388564,azure:15794175,beige:16119260,bisque:16770244,black:0,blanchedalmond:16772045,blue:255,blueviolet:9055202,brown:10824234,burlywood:14596231,cadetblue:6266528,chartreuse:8388352,chocolate:13789470,coral:16744272,cornflowerblue:6591981,cornsilk:16775388,crimson:14423100,cyan:65535,darkblue:139,darkcyan:35723,darkgoldenrod:12092939,darkgray:11119017,darkgreen:25600,darkgrey:11119017,darkkhaki:12433259,darkmagenta:9109643,darkolivegreen:5597999,darkorange:16747520,darkorchid:10040012,darkred:9109504,darksalmon:15308410,darkseagreen:9419919,darkslateblue:4734347,darkslategray:3100495,darkslategrey:3100495,darkturquoise:52945,darkviolet:9699539,deeppink:16716947,deepskyblue:49151,dimgray:6908265,dimgrey:6908265,dodgerblue:2003199,firebrick:11674146,floralwhite:16775920,forestgreen:2263842,fuchsia:16711935,gainsboro:14474460,ghostwhite:16316671,gold:16766720,goldenrod:14329120,gray:8421504,green:32768,greenyellow:11403055,grey:8421504,honeydew:15794160,hotpink:16738740,indianred:13458524,indigo:4915330,ivory:16777200,khaki:15787660,lavender:15132410,lavenderblush:16773365,lawngreen:8190976,lemonchiffon:16775885,lightblue:11393254,lightcoral:15761536,lightcyan:14745599,lightgoldenrodyellow:16448210,lightgray:13882323,lightgreen:9498256,lightgrey:13882323,lightpink:16758465,lightsalmon:16752762,lightseagreen:2142890,lightskyblue:8900346,lightslategray:7833753,lightslategrey:7833753,lightsteelblue:11584734,lightyellow:16777184,lime:65280,limegreen:3329330,linen:16445670,magenta:16711935,maroon:8388608,mediumaquamarine:6737322,mediumblue:205,mediumorchid:12211667,mediumpurple:9662683,mediumseagreen:3978097,mediumslateblue:8087790,mediumspringgreen:64154,mediumturquoise:4772300,mediumvioletred:13047173,midnightblue:1644912,mintcream:16121850,mistyrose:16770273,moccasin:16770229,navajowhite:16768685,navy:128,oldlace:16643558,olive:8421376,olivedrab:7048739,orange:16753920,orangered:16729344,orchid:14315734,palegoldenrod:15657130,palegreen:10025880,paleturquoise:11529966,palevioletred:14381203,papayawhip:16773077,peachpuff:16767673,peru:13468991,pink:16761035,plum:14524637,powderblue:11591910,purple:8388736,rebeccapurple:6697881,red:16711680,rosybrown:12357519,royalblue:4286945,saddlebrown:9127187,salmon:16416882,sandybrown:16032864,seagreen:3050327,seashell:16774638,sienna:10506797,silver:12632256,skyblue:8900331,slateblue:6970061,slategray:7372944,slategrey:7372944,snow:16775930,springgreen:65407,steelblue:4620980,tan:13808780,teal:32896,thistle:14204888,tomato:16737095,turquoise:4251856,violet:15631086,wheat:16113331,white:16777215,whitesmoke:16119285,yellow:16776960,yellowgreen:10145074};function g(){return this.rgb().formatHex()}function v(){return this.rgb().formatRgb()}function m(t){var e,r;return t=(t+\"\").trim().toLowerCase(),(e=s.exec(t))?(r=e[1].length,e=parseInt(e[1],16),6===r?y(e):3===r?new w(e>>8&15|e>>4&240,e>>4&15|240&e,(15&e)<<4|15&e,1):8===r?new w(e>>24&255,e>>16&255,e>>8&255,(255&e)/255):4===r?new w(e>>12&15|e>>8&240,e>>8&15|e>>4&240,e>>4&15|240&e,((15&e)<<4|15&e)/255):null):(e=l.exec(t))?new w(e[1],e[2],e[3],1):(e=c.exec(t))?new w(255*e[1]/100,255*e[2]/100,255*e[3]/100,1):(e=u.exec(t))?x(e[1],e[2],e[3],e[4]):(e=h.exec(t))?x(255*e[1]/100,255*e[2]/100,255*e[3]/100,e[4]):(e=f.exec(t))?A(e[1],e[2]/100,e[3]/100,1):(e=p.exec(t))?A(e[1],e[2]/100,e[3]/100,e[4]):d.hasOwnProperty(t)?y(d[t]):\"transparent\"===t?new w(NaN,NaN,NaN,0):null}function y(t){return new w(t>>16&255,t>>8&255,255&t,1)}function x(t,e,r,n){return n<=0&&(t=e=r=NaN),new w(t,e,r,n)}function b(t){return t instanceof n||(t=m(t)),t?new w((t=t.rgb()).r,t.g,t.b,t.opacity):new w}function _(t,e,r,n){return 1===arguments.length?b(t):new w(t,e,r,null==n?1:n)}function w(t,e,r,n){this.r=+t,this.g=+e,this.b=+r,this.opacity=+n}function k(){return\"#\"+M(this.r)+M(this.g)+M(this.b)}function T(){var t=this.opacity;return(1===(t=isNaN(t)?1:Math.max(0,Math.min(1,t)))?\"rgb(\":\"rgba(\")+Math.max(0,Math.min(255,Math.round(this.r)||0))+\", \"+Math.max(0,Math.min(255,Math.round(this.g)||0))+\", \"+Math.max(0,Math.min(255,Math.round(this.b)||0))+(1===t?\")\":\", \"+t+\")\")}function M(t){return((t=Math.max(0,Math.min(255,Math.round(t)||0)))<16?\"0\":\"\")+t.toString(16)}function A(t,e,r,n){return n<=0?t=e=r=NaN:r<=0||r>=1?t=e=NaN:e<=0&&(t=NaN),new L(t,e,r,n)}function S(t){if(t instanceof L)return new L(t.h,t.s,t.l,t.opacity);if(t instanceof n||(t=m(t)),!t)return new L;if(t instanceof L)return t;var e=(t=t.rgb()).r/255,r=t.g/255,a=t.b/255,i=Math.min(e,r,a),o=Math.max(e,r,a),s=NaN,l=o-i,c=(o+i)/2;return l?(s=e===o?(r-a)/l+6*(r<a):r===o?(a-e)/l+2:(e-r)/l+4,l/=c<.5?o+i:2-o-i,s*=60):l=c>0&&c<1?0:s,new L(s,l,c,t.opacity)}function E(t,e,r,n){return 1===arguments.length?S(t):new L(t,e,r,null==n?1:n)}function L(t,e,r,n){this.h=+t,this.s=+e,this.l=+r,this.opacity=+n}function C(t,e,r){return 255*(t<60?e+(r-e)*t/60:t<180?r:t<240?e+(r-e)*(240-t)/60:e)}e(n,m,{copy:function(t){return Object.assign(new this.constructor,this,t)},displayable:function(){return this.rgb().displayable()},hex:g,formatHex:g,formatHsl:function(){return S(this).formatHsl()},formatRgb:v,toString:v}),e(w,_,r(n,{brighter:function(t){return t=null==t?1/.7:Math.pow(1/.7,t),new w(this.r*t,this.g*t,this.b*t,this.opacity)},darker:function(t){return t=null==t?.7:Math.pow(.7,t),new w(this.r*t,this.g*t,this.b*t,this.opacity)},rgb:function(){return this},displayable:function(){return-.5<=this.r&&this.r<255.5&&-.5<=this.g&&this.g<255.5&&-.5<=this.b&&this.b<255.5&&0<=this.opacity&&this.opacity<=1},hex:k,formatHex:k,formatRgb:T,toString:T})),e(L,E,r(n,{brighter:function(t){return t=null==t?1/.7:Math.pow(1/.7,t),new L(this.h,this.s,this.l*t,this.opacity)},darker:function(t){return t=null==t?.7:Math.pow(.7,t),new L(this.h,this.s,this.l*t,this.opacity)},rgb:function(){var t=this.h%360+360*(this.h<0),e=isNaN(t)||isNaN(this.s)?0:this.s,r=this.l,n=r+(r<.5?r:1-r)*e,a=2*r-n;return new w(C(t>=240?t-240:t+120,a,n),C(t,a,n),C(t<120?t+240:t-120,a,n),this.opacity)},displayable:function(){return(0<=this.s&&this.s<=1||isNaN(this.s))&&0<=this.l&&this.l<=1&&0<=this.opacity&&this.opacity<=1},formatHsl:function(){var t=this.opacity;return(1===(t=isNaN(t)?1:Math.max(0,Math.min(1,t)))?\"hsl(\":\"hsla(\")+(this.h||0)+\", \"+100*(this.s||0)+\"%, \"+100*(this.l||0)+\"%\"+(1===t?\")\":\", \"+t+\")\")}}));var P=Math.PI/180,O=180/Math.PI,z=.96422,I=1,D=.82521,R=4/29,F=6/29,B=3*F*F,N=F*F*F;function j(t){if(t instanceof U)return new U(t.l,t.a,t.b,t.opacity);if(t instanceof Z)return J(t);t instanceof w||(t=b(t));var e,r,n=Y(t.r),a=Y(t.g),i=Y(t.b),o=q((.2225045*n+.7168786*a+.0606169*i)/I);return n===a&&a===i?e=r=o:(e=q((.4360747*n+.3850649*a+.1430804*i)/z),r=q((.0139322*n+.0971045*a+.7141733*i)/D)),new U(116*o-16,500*(e-o),200*(o-r),t.opacity)}function V(t,e,r,n){return 1===arguments.length?j(t):new U(t,e,r,null==n?1:n)}function U(t,e,r,n){this.l=+t,this.a=+e,this.b=+r,this.opacity=+n}function q(t){return t>N?Math.pow(t,1/3):t/B+R}function H(t){return t>F?t*t*t:B*(t-R)}function G(t){return 255*(t<=.0031308?12.92*t:1.055*Math.pow(t,1/2.4)-.055)}function Y(t){return(t/=255)<=.04045?t/12.92:Math.pow((t+.055)/1.055,2.4)}function W(t){if(t instanceof Z)return new Z(t.h,t.c,t.l,t.opacity);if(t instanceof U||(t=j(t)),0===t.a&&0===t.b)return new Z(NaN,0<t.l&&t.l<100?0:NaN,t.l,t.opacity);var e=Math.atan2(t.b,t.a)*O;return new Z(e<0?e+360:e,Math.sqrt(t.a*t.a+t.b*t.b),t.l,t.opacity)}function X(t,e,r,n){return 1===arguments.length?W(t):new Z(t,e,r,null==n?1:n)}function Z(t,e,r,n){this.h=+t,this.c=+e,this.l=+r,this.opacity=+n}function J(t){if(isNaN(t.h))return new U(t.l,0,0,t.opacity);var e=t.h*P;return new U(t.l,Math.cos(e)*t.c,Math.sin(e)*t.c,t.opacity)}e(U,V,r(n,{brighter:function(t){return new U(this.l+18*(null==t?1:t),this.a,this.b,this.opacity)},darker:function(t){return new U(this.l-18*(null==t?1:t),this.a,this.b,this.opacity)},rgb:function(){var t=(this.l+16)/116,e=isNaN(this.a)?t:t+this.a/500,r=isNaN(this.b)?t:t-this.b/200;return new w(G(3.1338561*(e=z*H(e))-1.6168667*(t=I*H(t))-.4906146*(r=D*H(r))),G(-.9787684*e+1.9161415*t+.033454*r),G(.0719453*e-.2289914*t+1.4052427*r),this.opacity)}})),e(Z,X,r(n,{brighter:function(t){return new Z(this.h,this.c,this.l+18*(null==t?1:t),this.opacity)},darker:function(t){return new Z(this.h,this.c,this.l-18*(null==t?1:t),this.opacity)},rgb:function(){return J(this).rgb()}}));var K=-.14861,Q=1.78277,$=-.29227,tt=-.90649,et=1.97294,rt=et*tt,nt=et*Q,at=Q*$-tt*K;function it(t,e,r,n){return 1===arguments.length?function(t){if(t instanceof ot)return new ot(t.h,t.s,t.l,t.opacity);t instanceof w||(t=b(t));var e=t.r/255,r=t.g/255,n=t.b/255,a=(at*n+rt*e-nt*r)/(at+rt-nt),i=n-a,o=(et*(r-a)-$*i)/tt,s=Math.sqrt(o*o+i*i)/(et*a*(1-a)),l=s?Math.atan2(o,i)*O-120:NaN;return new ot(l<0?l+360:l,s,a,t.opacity)}(t):new ot(t,e,r,null==n?1:n)}function ot(t,e,r,n){this.h=+t,this.s=+e,this.l=+r,this.opacity=+n}e(ot,it,r(n,{brighter:function(t){return t=null==t?1/.7:Math.pow(1/.7,t),new ot(this.h,this.s,this.l*t,this.opacity)},darker:function(t){return t=null==t?.7:Math.pow(.7,t),new ot(this.h,this.s,this.l*t,this.opacity)},rgb:function(){var t=isNaN(this.h)?0:(this.h+120)*P,e=+this.l,r=isNaN(this.s)?0:this.s*e*(1-e),n=Math.cos(t),a=Math.sin(t);return new w(255*(e+r*(K*n+Q*a)),255*(e+r*($*n+tt*a)),255*(e+r*(et*n)),this.opacity)}})),t.color=m,t.cubehelix=it,t.gray=function(t,e){return new U(t,0,0,null==e?1:e)},t.hcl=X,t.hsl=E,t.lab=V,t.lch=function(t,e,r,n){return 1===arguments.length?W(t):new Z(r,e,t,null==n?1:n)},t.rgb=_,Object.defineProperty(t,\"__esModule\",{value:!0})}(\"object\"==typeof r&&\"undefined\"!=typeof e?r:(n=n||self).d3=n.d3||{})},{}],157:[function(t,e,r){var n;n=this,function(t){\"use strict\";var e={value:function(){}};function r(){for(var t,e=0,r=arguments.length,a={};e<r;++e){if(!(t=arguments[e]+\"\")||t in a)throw new Error(\"illegal type: \"+t);a[t]=[]}return new n(a)}function n(t){this._=t}function a(t,e){for(var r,n=0,a=t.length;n<a;++n)if((r=t[n]).name===e)return r.value}function i(t,r,n){for(var a=0,i=t.length;a<i;++a)if(t[a].name===r){t[a]=e,t=t.slice(0,a).concat(t.slice(a+1));break}return null!=n&&t.push({name:r,value:n}),t}n.prototype=r.prototype={constructor:n,on:function(t,e){var r,n,o=this._,s=(n=o,(t+\"\").trim().split(/^|\\s+/).map(function(t){var e=\"\",r=t.indexOf(\".\");if(r>=0&&(e=t.slice(r+1),t=t.slice(0,r)),t&&!n.hasOwnProperty(t))throw new Error(\"unknown type: \"+t);return{type:t,name:e}})),l=-1,c=s.length;if(!(arguments.length<2)){if(null!=e&&\"function\"!=typeof e)throw new Error(\"invalid callback: \"+e);for(;++l<c;)if(r=(t=s[l]).type)o[r]=i(o[r],t.name,e);else if(null==e)for(r in o)o[r]=i(o[r],t.name,null);return this}for(;++l<c;)if((r=(t=s[l]).type)&&(r=a(o[r],t.name)))return r},copy:function(){var t={},e=this._;for(var r in e)t[r]=e[r].slice();return new n(t)},call:function(t,e){if((r=arguments.length-2)>0)for(var r,n,a=new Array(r),i=0;i<r;++i)a[i]=arguments[i+2];if(!this._.hasOwnProperty(t))throw new Error(\"unknown type: \"+t);for(i=0,r=(n=this._[t]).length;i<r;++i)n[i].value.apply(e,a)},apply:function(t,e,r){if(!this._.hasOwnProperty(t))throw new Error(\"unknown type: \"+t);for(var n=this._[t],a=0,i=n.length;a<i;++a)n[a].value.apply(e,r)}},t.dispatch=r,Object.defineProperty(t,\"__esModule\",{value:!0})}(\"object\"==typeof r&&\"undefined\"!=typeof e?r:n.d3=n.d3||{})},{}],158:[function(t,e,r){var n,a;n=this,a=function(t,e,r,n,a){\"use strict\";var i=function(t){return function(){return t}},o=function(){return 1e-6*(Math.random()-.5)};function s(t){return t.x+t.vx}function l(t){return t.y+t.vy}function c(t){return t.index}function u(t,e){var r=t.get(e);if(!r)throw new Error(\"missing: \"+e);return r}function h(t){return t.x}function f(t){return t.y}var p=10,d=Math.PI*(3-Math.sqrt(5));t.forceCenter=function(t,e){var r;function n(){var n,a,i=r.length,o=0,s=0;for(n=0;n<i;++n)o+=(a=r[n]).x,s+=a.y;for(o=o/i-t,s=s/i-e,n=0;n<i;++n)(a=r[n]).x-=o,a.y-=s}return null==t&&(t=0),null==e&&(e=0),n.initialize=function(t){r=t},n.x=function(e){return arguments.length?(t=+e,n):t},n.y=function(t){return arguments.length?(e=+t,n):e},n},t.forceCollide=function(t){var r,n,a=1,c=1;function u(){for(var t,i,u,f,p,d,g,v=r.length,m=0;m<c;++m)for(i=e.quadtree(r,s,l).visitAfter(h),t=0;t<v;++t)u=r[t],d=n[u.index],g=d*d,f=u.x+u.vx,p=u.y+u.vy,i.visit(y);function y(t,e,r,n,i){var s=t.data,l=t.r,c=d+l;if(!s)return e>f+c||n<f-c||r>p+c||i<p-c;if(s.index>u.index){var h=f-s.x-s.vx,v=p-s.y-s.vy,m=h*h+v*v;m<c*c&&(0===h&&(m+=(h=o())*h),0===v&&(m+=(v=o())*v),m=(c-(m=Math.sqrt(m)))/m*a,u.vx+=(h*=m)*(c=(l*=l)/(g+l)),u.vy+=(v*=m)*c,s.vx-=h*(c=1-c),s.vy-=v*c)}}}function h(t){if(t.data)return t.r=n[t.data.index];for(var e=t.r=0;e<4;++e)t[e]&&t[e].r>t.r&&(t.r=t[e].r)}function f(){if(r){var e,a,i=r.length;for(n=new Array(i),e=0;e<i;++e)a=r[e],n[a.index]=+t(a,e,r)}}return\"function\"!=typeof t&&(t=i(null==t?1:+t)),u.initialize=function(t){r=t,f()},u.iterations=function(t){return arguments.length?(c=+t,u):c},u.strength=function(t){return arguments.length?(a=+t,u):a},u.radius=function(e){return arguments.length?(t=\"function\"==typeof e?e:i(+e),f(),u):t},u},t.forceLink=function(t){var e,n,a,s,l,h=c,f=function(t){return 1/Math.min(s[t.source.index],s[t.target.index])},p=i(30),d=1;function g(r){for(var a=0,i=t.length;a<d;++a)for(var s,c,u,h,f,p,g,v=0;v<i;++v)c=(s=t[v]).source,h=(u=s.target).x+u.vx-c.x-c.vx||o(),f=u.y+u.vy-c.y-c.vy||o(),h*=p=((p=Math.sqrt(h*h+f*f))-n[v])/p*r*e[v],f*=p,u.vx-=h*(g=l[v]),u.vy-=f*g,c.vx+=h*(g=1-g),c.vy+=f*g}function v(){if(a){var i,o,c=a.length,f=t.length,p=r.map(a,h);for(i=0,s=new Array(c);i<f;++i)(o=t[i]).index=i,\"object\"!=typeof o.source&&(o.source=u(p,o.source)),\"object\"!=typeof o.target&&(o.target=u(p,o.target)),s[o.source.index]=(s[o.source.index]||0)+1,s[o.target.index]=(s[o.target.index]||0)+1;for(i=0,l=new Array(f);i<f;++i)o=t[i],l[i]=s[o.source.index]/(s[o.source.index]+s[o.target.index]);e=new Array(f),m(),n=new Array(f),y()}}function m(){if(a)for(var r=0,n=t.length;r<n;++r)e[r]=+f(t[r],r,t)}function y(){if(a)for(var e=0,r=t.length;e<r;++e)n[e]=+p(t[e],e,t)}return null==t&&(t=[]),g.initialize=function(t){a=t,v()},g.links=function(e){return arguments.length?(t=e,v(),g):t},g.id=function(t){return arguments.length?(h=t,g):h},g.iterations=function(t){return arguments.length?(d=+t,g):d},g.strength=function(t){return arguments.length?(f=\"function\"==typeof t?t:i(+t),m(),g):f},g.distance=function(t){return arguments.length?(p=\"function\"==typeof t?t:i(+t),y(),g):p},g},t.forceManyBody=function(){var t,r,n,a,s=i(-30),l=1,c=1/0,u=.81;function p(a){var i,o=t.length,s=e.quadtree(t,h,f).visitAfter(g);for(n=a,i=0;i<o;++i)r=t[i],s.visit(v)}function d(){if(t){var e,r,n=t.length;for(a=new Array(n),e=0;e<n;++e)r=t[e],a[r.index]=+s(r,e,t)}}function g(t){var e,r,n,i,o,s=0,l=0;if(t.length){for(n=i=o=0;o<4;++o)(e=t[o])&&(r=Math.abs(e.value))&&(s+=e.value,l+=r,n+=r*e.x,i+=r*e.y);t.x=n/l,t.y=i/l}else{(e=t).x=e.data.x,e.y=e.data.y;do{s+=a[e.data.index]}while(e=e.next)}t.value=s}function v(t,e,i,s){if(!t.value)return!0;var h=t.x-r.x,f=t.y-r.y,p=s-e,d=h*h+f*f;if(p*p/u<d)return d<c&&(0===h&&(d+=(h=o())*h),0===f&&(d+=(f=o())*f),d<l&&(d=Math.sqrt(l*d)),r.vx+=h*t.value*n/d,r.vy+=f*t.value*n/d),!0;if(!(t.length||d>=c)){(t.data!==r||t.next)&&(0===h&&(d+=(h=o())*h),0===f&&(d+=(f=o())*f),d<l&&(d=Math.sqrt(l*d)));do{t.data!==r&&(p=a[t.data.index]*n/d,r.vx+=h*p,r.vy+=f*p)}while(t=t.next)}}return p.initialize=function(e){t=e,d()},p.strength=function(t){return arguments.length?(s=\"function\"==typeof t?t:i(+t),d(),p):s},p.distanceMin=function(t){return arguments.length?(l=t*t,p):Math.sqrt(l)},p.distanceMax=function(t){return arguments.length?(c=t*t,p):Math.sqrt(c)},p.theta=function(t){return arguments.length?(u=t*t,p):Math.sqrt(u)},p},t.forceRadial=function(t,e,r){var n,a,o,s=i(.1);function l(t){for(var i=0,s=n.length;i<s;++i){var l=n[i],c=l.x-e||1e-6,u=l.y-r||1e-6,h=Math.sqrt(c*c+u*u),f=(o[i]-h)*a[i]*t/h;l.vx+=c*f,l.vy+=u*f}}function c(){if(n){var e,r=n.length;for(a=new Array(r),o=new Array(r),e=0;e<r;++e)o[e]=+t(n[e],e,n),a[e]=isNaN(o[e])?0:+s(n[e],e,n)}}return\"function\"!=typeof t&&(t=i(+t)),null==e&&(e=0),null==r&&(r=0),l.initialize=function(t){n=t,c()},l.strength=function(t){return arguments.length?(s=\"function\"==typeof t?t:i(+t),c(),l):s},l.radius=function(e){return arguments.length?(t=\"function\"==typeof e?e:i(+e),c(),l):t},l.x=function(t){return arguments.length?(e=+t,l):e},l.y=function(t){return arguments.length?(r=+t,l):r},l},t.forceSimulation=function(t){var e,i=1,o=.001,s=1-Math.pow(o,1/300),l=0,c=.6,u=r.map(),h=a.timer(g),f=n.dispatch(\"tick\",\"end\");function g(){v(),f.call(\"tick\",e),i<o&&(h.stop(),f.call(\"end\",e))}function v(){var e,r,n=t.length;for(i+=(l-i)*s,u.each(function(t){t(i)}),e=0;e<n;++e)null==(r=t[e]).fx?r.x+=r.vx*=c:(r.x=r.fx,r.vx=0),null==r.fy?r.y+=r.vy*=c:(r.y=r.fy,r.vy=0)}function m(){for(var e,r=0,n=t.length;r<n;++r){if((e=t[r]).index=r,isNaN(e.x)||isNaN(e.y)){var a=p*Math.sqrt(r),i=r*d;e.x=a*Math.cos(i),e.y=a*Math.sin(i)}(isNaN(e.vx)||isNaN(e.vy))&&(e.vx=e.vy=0)}}function y(e){return e.initialize&&e.initialize(t),e}return null==t&&(t=[]),m(),e={tick:v,restart:function(){return h.restart(g),e},stop:function(){return h.stop(),e},nodes:function(r){return arguments.length?(t=r,m(),u.each(y),e):t},alpha:function(t){return arguments.length?(i=+t,e):i},alphaMin:function(t){return arguments.length?(o=+t,e):o},alphaDecay:function(t){return arguments.length?(s=+t,e):+s},alphaTarget:function(t){return arguments.length?(l=+t,e):l},velocityDecay:function(t){return arguments.length?(c=1-t,e):1-c},force:function(t,r){return arguments.length>1?(null==r?u.remove(t):u.set(t,y(r)),e):u.get(t)},find:function(e,r,n){var a,i,o,s,l,c=0,u=t.length;for(null==n?n=1/0:n*=n,c=0;c<u;++c)(o=(a=e-(s=t[c]).x)*a+(i=r-s.y)*i)<n&&(l=s,n=o);return l},on:function(t,r){return arguments.length>1?(f.on(t,r),e):f.on(t)}}},t.forceX=function(t){var e,r,n,a=i(.1);function o(t){for(var a,i=0,o=e.length;i<o;++i)(a=e[i]).vx+=(n[i]-a.x)*r[i]*t}function s(){if(e){var i,o=e.length;for(r=new Array(o),n=new Array(o),i=0;i<o;++i)r[i]=isNaN(n[i]=+t(e[i],i,e))?0:+a(e[i],i,e)}}return\"function\"!=typeof t&&(t=i(null==t?0:+t)),o.initialize=function(t){e=t,s()},o.strength=function(t){return arguments.length?(a=\"function\"==typeof t?t:i(+t),s(),o):a},o.x=function(e){return arguments.length?(t=\"function\"==typeof e?e:i(+e),s(),o):t},o},t.forceY=function(t){var e,r,n,a=i(.1);function o(t){for(var a,i=0,o=e.length;i<o;++i)(a=e[i]).vy+=(n[i]-a.y)*r[i]*t}function s(){if(e){var i,o=e.length;for(r=new Array(o),n=new Array(o),i=0;i<o;++i)r[i]=isNaN(n[i]=+t(e[i],i,e))?0:+a(e[i],i,e)}}return\"function\"!=typeof t&&(t=i(null==t?0:+t)),o.initialize=function(t){e=t,s()},o.strength=function(t){return arguments.length?(a=\"function\"==typeof t?t:i(+t),s(),o):a},o.y=function(e){return arguments.length?(t=\"function\"==typeof e?e:i(+e),s(),o):t},o},Object.defineProperty(t,\"__esModule\",{value:!0})},\"object\"==typeof r&&\"undefined\"!=typeof e?a(r,t(\"d3-quadtree\"),t(\"d3-collection\"),t(\"d3-dispatch\"),t(\"d3-timer\")):a(n.d3=n.d3||{},n.d3,n.d3,n.d3,n.d3)},{\"d3-collection\":155,\"d3-dispatch\":157,\"d3-quadtree\":162,\"d3-timer\":164}],159:[function(t,e,r){var n;n=this,function(t){\"use strict\";function e(t,e){return t.parent===e.parent?1:2}function r(t,e){return t+e.x}function n(t,e){return Math.max(t,e.y)}function a(t){var e=0,r=t.children,n=r&&r.length;if(n)for(;--n>=0;)e+=r[n].value;else e=1;t.value=e}function i(t,e){var r,n,a,i,s,u=new c(t),h=+t.value&&(u.value=t.value),f=[u];for(null==e&&(e=o);r=f.pop();)if(h&&(r.value=+r.data.value),(a=e(r.data))&&(s=a.length))for(r.children=new Array(s),i=s-1;i>=0;--i)f.push(n=r.children[i]=new c(a[i])),n.parent=r,n.depth=r.depth+1;return u.eachBefore(l)}function o(t){return t.children}function s(t){t.data=t.data.data}function l(t){var e=0;do{t.height=e}while((t=t.parent)&&t.height<++e)}function c(t){this.data=t,this.depth=this.height=0,this.parent=null}c.prototype=i.prototype={constructor:c,count:function(){return this.eachAfter(a)},each:function(t){var e,r,n,a,i=this,o=[i];do{for(e=o.reverse(),o=[];i=e.pop();)if(t(i),r=i.children)for(n=0,a=r.length;n<a;++n)o.push(r[n])}while(o.length);return this},eachAfter:function(t){for(var e,r,n,a=this,i=[a],o=[];a=i.pop();)if(o.push(a),e=a.children)for(r=0,n=e.length;r<n;++r)i.push(e[r]);for(;a=o.pop();)t(a);return this},eachBefore:function(t){for(var e,r,n=this,a=[n];n=a.pop();)if(t(n),e=n.children)for(r=e.length-1;r>=0;--r)a.push(e[r]);return this},sum:function(t){return this.eachAfter(function(e){for(var r=+t(e.data)||0,n=e.children,a=n&&n.length;--a>=0;)r+=n[a].value;e.value=r})},sort:function(t){return this.eachBefore(function(e){e.children&&e.children.sort(t)})},path:function(t){for(var e=this,r=function(t,e){if(t===e)return t;var r=t.ancestors(),n=e.ancestors(),a=null;for(t=r.pop(),e=n.pop();t===e;)a=t,t=r.pop(),e=n.pop();return a}(e,t),n=[e];e!==r;)e=e.parent,n.push(e);for(var a=n.length;t!==r;)n.splice(a,0,t),t=t.parent;return n},ancestors:function(){for(var t=this,e=[t];t=t.parent;)e.push(t);return e},descendants:function(){var t=[];return this.each(function(e){t.push(e)}),t},leaves:function(){var t=[];return this.eachBefore(function(e){e.children||t.push(e)}),t},links:function(){var t=this,e=[];return t.each(function(r){r!==t&&e.push({source:r.parent,target:r})}),e},copy:function(){return i(this).eachBefore(s)}};var u=Array.prototype.slice;function h(t){for(var e,r,n=0,a=(t=function(t){for(var e,r,n=t.length;n;)r=Math.random()*n--|0,e=t[n],t[n]=t[r],t[r]=e;return t}(u.call(t))).length,i=[];n<a;)e=t[n],r&&d(r,e)?++n:(r=v(i=f(i,e)),n=0);return r}function f(t,e){var r,n;if(g(e,t))return[e];for(r=0;r<t.length;++r)if(p(e,t[r])&&g(m(t[r],e),t))return[t[r],e];for(r=0;r<t.length-1;++r)for(n=r+1;n<t.length;++n)if(p(m(t[r],t[n]),e)&&p(m(t[r],e),t[n])&&p(m(t[n],e),t[r])&&g(y(t[r],t[n],e),t))return[t[r],t[n],e];throw new Error}function p(t,e){var r=t.r-e.r,n=e.x-t.x,a=e.y-t.y;return r<0||r*r<n*n+a*a}function d(t,e){var r=t.r-e.r+1e-6,n=e.x-t.x,a=e.y-t.y;return r>0&&r*r>n*n+a*a}function g(t,e){for(var r=0;r<e.length;++r)if(!d(t,e[r]))return!1;return!0}function v(t){switch(t.length){case 1:return{x:(e=t[0]).x,y:e.y,r:e.r};case 2:return m(t[0],t[1]);case 3:return y(t[0],t[1],t[2])}var e}function m(t,e){var r=t.x,n=t.y,a=t.r,i=e.x,o=e.y,s=e.r,l=i-r,c=o-n,u=s-a,h=Math.sqrt(l*l+c*c);return{x:(r+i+l/h*u)/2,y:(n+o+c/h*u)/2,r:(h+a+s)/2}}function y(t,e,r){var n=t.x,a=t.y,i=t.r,o=e.x,s=e.y,l=e.r,c=r.x,u=r.y,h=r.r,f=n-o,p=n-c,d=a-s,g=a-u,v=l-i,m=h-i,y=n*n+a*a-i*i,x=y-o*o-s*s+l*l,b=y-c*c-u*u+h*h,_=p*d-f*g,w=(d*b-g*x)/(2*_)-n,k=(g*v-d*m)/_,T=(p*x-f*b)/(2*_)-a,M=(f*m-p*v)/_,A=k*k+M*M-1,S=2*(i+w*k+T*M),E=w*w+T*T-i*i,L=-(A?(S+Math.sqrt(S*S-4*A*E))/(2*A):E/S);return{x:n+w+k*L,y:a+T+M*L,r:L}}function x(t,e,r){var n,a,i,o,s=t.x-e.x,l=t.y-e.y,c=s*s+l*l;c?(a=e.r+r.r,a*=a,o=t.r+r.r,a>(o*=o)?(n=(c+o-a)/(2*c),i=Math.sqrt(Math.max(0,o/c-n*n)),r.x=t.x-n*s-i*l,r.y=t.y-n*l+i*s):(n=(c+a-o)/(2*c),i=Math.sqrt(Math.max(0,a/c-n*n)),r.x=e.x+n*s-i*l,r.y=e.y+n*l+i*s)):(r.x=e.x+r.r,r.y=e.y)}function b(t,e){var r=t.r+e.r-1e-6,n=e.x-t.x,a=e.y-t.y;return r>0&&r*r>n*n+a*a}function _(t){var e=t._,r=t.next._,n=e.r+r.r,a=(e.x*r.r+r.x*e.r)/n,i=(e.y*r.r+r.y*e.r)/n;return a*a+i*i}function w(t){this._=t,this.next=null,this.previous=null}function k(t){if(!(a=t.length))return 0;var e,r,n,a,i,o,s,l,c,u,f;if((e=t[0]).x=0,e.y=0,!(a>1))return e.r;if(r=t[1],e.x=-r.r,r.x=e.r,r.y=0,!(a>2))return e.r+r.r;x(r,e,n=t[2]),e=new w(e),r=new w(r),n=new w(n),e.next=n.previous=r,r.next=e.previous=n,n.next=r.previous=e;t:for(s=3;s<a;++s){x(e._,r._,n=t[s]),n=new w(n),l=r.next,c=e.previous,u=r._.r,f=e._.r;do{if(u<=f){if(b(l._,n._)){r=l,e.next=r,r.previous=e,--s;continue t}u+=l._.r,l=l.next}else{if(b(c._,n._)){(e=c).next=r,r.previous=e,--s;continue t}f+=c._.r,c=c.previous}}while(l!==c.next);for(n.previous=e,n.next=r,e.next=r.previous=r=n,i=_(e);(n=n.next)!==r;)(o=_(n))<i&&(e=n,i=o);r=e.next}for(e=[r._],n=r;(n=n.next)!==r;)e.push(n._);for(n=h(e),s=0;s<a;++s)(e=t[s]).x-=n.x,e.y-=n.y;return n.r}function T(t){if(\"function\"!=typeof t)throw new Error;return t}function M(){return 0}function A(t){return function(){return t}}function S(t){return Math.sqrt(t.value)}function E(t){return function(e){e.children||(e.r=Math.max(0,+t(e)||0))}}function L(t,e){return function(r){if(n=r.children){var n,a,i,o=n.length,s=t(r)*e||0;if(s)for(a=0;a<o;++a)n[a].r+=s;if(i=k(n),s)for(a=0;a<o;++a)n[a].r-=s;r.r=i+s}}}function C(t){return function(e){var r=e.parent;e.r*=t,r&&(e.x=r.x+t*e.x,e.y=r.y+t*e.y)}}function P(t){t.x0=Math.round(t.x0),t.y0=Math.round(t.y0),t.x1=Math.round(t.x1),t.y1=Math.round(t.y1)}function O(t,e,r,n,a){for(var i,o=t.children,s=-1,l=o.length,c=t.value&&(n-e)/t.value;++s<l;)(i=o[s]).y0=r,i.y1=a,i.x0=e,i.x1=e+=i.value*c}var z=\"$\",I={depth:-1},D={};function R(t){return t.id}function F(t){return t.parentId}function B(t,e){return t.parent===e.parent?1:2}function N(t){var e=t.children;return e?e[0]:t.t}function j(t){var e=t.children;return e?e[e.length-1]:t.t}function V(t,e,r){var n=r/(e.i-t.i);e.c-=n,e.s+=r,t.c+=n,e.z+=r,e.m+=r}function U(t,e,r){return t.a.parent===e.parent?t.a:r}function q(t,e){this._=t,this.parent=null,this.children=null,this.A=null,this.a=this,this.z=0,this.m=0,this.c=0,this.s=0,this.t=null,this.i=e}function H(t,e,r,n,a){for(var i,o=t.children,s=-1,l=o.length,c=t.value&&(a-r)/t.value;++s<l;)(i=o[s]).x0=e,i.x1=n,i.y0=r,i.y1=r+=i.value*c}q.prototype=Object.create(c.prototype);var G=(1+Math.sqrt(5))/2;function Y(t,e,r,n,a,i){for(var o,s,l,c,u,h,f,p,d,g,v,m=[],y=e.children,x=0,b=0,_=y.length,w=e.value;x<_;){l=a-r,c=i-n;do{u=y[b++].value}while(!u&&b<_);for(h=f=u,v=u*u*(g=Math.max(c/l,l/c)/(w*t)),d=Math.max(f/v,v/h);b<_;++b){if(u+=s=y[b].value,s<h&&(h=s),s>f&&(f=s),v=u*u*g,(p=Math.max(f/v,v/h))>d){u-=s;break}d=p}m.push(o={value:u,dice:l<c,children:y.slice(x,b)}),o.dice?O(o,r,n,a,w?n+=c*u/w:i):H(o,r,n,w?r+=l*u/w:a,i),w-=u,x=b}return m}var W=function t(e){function r(t,r,n,a,i){Y(e,t,r,n,a,i)}return r.ratio=function(e){return t((e=+e)>1?e:1)},r}(G),X=function t(e){function r(t,r,n,a,i){if((o=t._squarify)&&o.ratio===e)for(var o,s,l,c,u,h=-1,f=o.length,p=t.value;++h<f;){for(l=(s=o[h]).children,c=s.value=0,u=l.length;c<u;++c)s.value+=l[c].value;s.dice?O(s,r,n,a,n+=(i-n)*s.value/p):H(s,r,n,r+=(a-r)*s.value/p,i),p-=s.value}else t._squarify=o=Y(e,t,r,n,a,i),o.ratio=e}return r.ratio=function(e){return t((e=+e)>1?e:1)},r}(G);t.cluster=function(){var t=e,a=1,i=1,o=!1;function s(e){var s,l=0;e.eachAfter(function(e){var a=e.children;a?(e.x=function(t){return t.reduce(r,0)/t.length}(a),e.y=function(t){return 1+t.reduce(n,0)}(a)):(e.x=s?l+=t(e,s):0,e.y=0,s=e)});var c=function(t){for(var e;e=t.children;)t=e[0];return t}(e),u=function(t){for(var e;e=t.children;)t=e[e.length-1];return t}(e),h=c.x-t(c,u)/2,f=u.x+t(u,c)/2;return e.eachAfter(o?function(t){t.x=(t.x-e.x)*a,t.y=(e.y-t.y)*i}:function(t){t.x=(t.x-h)/(f-h)*a,t.y=(1-(e.y?t.y/e.y:1))*i})}return s.separation=function(e){return arguments.length?(t=e,s):t},s.size=function(t){return arguments.length?(o=!1,a=+t[0],i=+t[1],s):o?null:[a,i]},s.nodeSize=function(t){return arguments.length?(o=!0,a=+t[0],i=+t[1],s):o?[a,i]:null},s},t.hierarchy=i,t.pack=function(){var t=null,e=1,r=1,n=M;function a(a){return a.x=e/2,a.y=r/2,t?a.eachBefore(E(t)).eachAfter(L(n,.5)).eachBefore(C(1)):a.eachBefore(E(S)).eachAfter(L(M,1)).eachAfter(L(n,a.r/Math.min(e,r))).eachBefore(C(Math.min(e,r)/(2*a.r))),a}return a.radius=function(e){return arguments.length?(t=null==(r=e)?null:T(r),a):t;var r},a.size=function(t){return arguments.length?(e=+t[0],r=+t[1],a):[e,r]},a.padding=function(t){return arguments.length?(n=\"function\"==typeof t?t:A(+t),a):n},a},t.packEnclose=h,t.packSiblings=function(t){return k(t),t},t.partition=function(){var t=1,e=1,r=0,n=!1;function a(a){var i=a.height+1;return a.x0=a.y0=r,a.x1=t,a.y1=e/i,a.eachBefore(function(t,e){return function(n){n.children&&O(n,n.x0,t*(n.depth+1)/e,n.x1,t*(n.depth+2)/e);var a=n.x0,i=n.y0,o=n.x1-r,s=n.y1-r;o<a&&(a=o=(a+o)/2),s<i&&(i=s=(i+s)/2),n.x0=a,n.y0=i,n.x1=o,n.y1=s}}(e,i)),n&&a.eachBefore(P),a}return a.round=function(t){return arguments.length?(n=!!t,a):n},a.size=function(r){return arguments.length?(t=+r[0],e=+r[1],a):[t,e]},a.padding=function(t){return arguments.length?(r=+t,a):r},a},t.stratify=function(){var t=R,e=F;function r(r){var n,a,i,o,s,u,h,f=r.length,p=new Array(f),d={};for(a=0;a<f;++a)n=r[a],s=p[a]=new c(n),null!=(u=t(n,a,r))&&(u+=\"\")&&(d[h=z+(s.id=u)]=h in d?D:s);for(a=0;a<f;++a)if(s=p[a],null!=(u=e(r[a],a,r))&&(u+=\"\")){if(!(o=d[z+u]))throw new Error(\"missing: \"+u);if(o===D)throw new Error(\"ambiguous: \"+u);o.children?o.children.push(s):o.children=[s],s.parent=o}else{if(i)throw new Error(\"multiple roots\");i=s}if(!i)throw new Error(\"no root\");if(i.parent=I,i.eachBefore(function(t){t.depth=t.parent.depth+1,--f}).eachBefore(l),i.parent=null,f>0)throw new Error(\"cycle\");return i}return r.id=function(e){return arguments.length?(t=T(e),r):t},r.parentId=function(t){return arguments.length?(e=T(t),r):e},r},t.tree=function(){var t=B,e=1,r=1,n=null;function a(a){var l=function(t){for(var e,r,n,a,i,o=new q(t,0),s=[o];e=s.pop();)if(n=e._.children)for(e.children=new Array(i=n.length),a=i-1;a>=0;--a)s.push(r=e.children[a]=new q(n[a],a)),r.parent=e;return(o.parent=new q(null,0)).children=[o],o}(a);if(l.eachAfter(i),l.parent.m=-l.z,l.eachBefore(o),n)a.eachBefore(s);else{var c=a,u=a,h=a;a.eachBefore(function(t){t.x<c.x&&(c=t),t.x>u.x&&(u=t),t.depth>h.depth&&(h=t)});var f=c===u?1:t(c,u)/2,p=f-c.x,d=e/(u.x+f+p),g=r/(h.depth||1);a.eachBefore(function(t){t.x=(t.x+p)*d,t.y=t.depth*g})}return a}function i(e){var r=e.children,n=e.parent.children,a=e.i?n[e.i-1]:null;if(r){!function(t){for(var e,r=0,n=0,a=t.children,i=a.length;--i>=0;)(e=a[i]).z+=r,e.m+=r,r+=e.s+(n+=e.c)}(e);var i=(r[0].z+r[r.length-1].z)/2;a?(e.z=a.z+t(e._,a._),e.m=e.z-i):e.z=i}else a&&(e.z=a.z+t(e._,a._));e.parent.A=function(e,r,n){if(r){for(var a,i=e,o=e,s=r,l=i.parent.children[0],c=i.m,u=o.m,h=s.m,f=l.m;s=j(s),i=N(i),s&&i;)l=N(l),(o=j(o)).a=e,(a=s.z+h-i.z-c+t(s._,i._))>0&&(V(U(s,e,n),e,a),c+=a,u+=a),h+=s.m,c+=i.m,f+=l.m,u+=o.m;s&&!j(o)&&(o.t=s,o.m+=h-u),i&&!N(l)&&(l.t=i,l.m+=c-f,n=e)}return n}(e,a,e.parent.A||n[0])}function o(t){t._.x=t.z+t.parent.m,t.m+=t.parent.m}function s(t){t.x*=e,t.y=t.depth*r}return a.separation=function(e){return arguments.length?(t=e,a):t},a.size=function(t){return arguments.length?(n=!1,e=+t[0],r=+t[1],a):n?null:[e,r]},a.nodeSize=function(t){return arguments.length?(n=!0,e=+t[0],r=+t[1],a):n?[e,r]:null},a},t.treemap=function(){var t=W,e=!1,r=1,n=1,a=[0],i=M,o=M,s=M,l=M,c=M;function u(t){return t.x0=t.y0=0,t.x1=r,t.y1=n,t.eachBefore(h),a=[0],e&&t.eachBefore(P),t}function h(e){var r=a[e.depth],n=e.x0+r,u=e.y0+r,h=e.x1-r,f=e.y1-r;h<n&&(n=h=(n+h)/2),f<u&&(u=f=(u+f)/2),e.x0=n,e.y0=u,e.x1=h,e.y1=f,e.children&&(r=a[e.depth+1]=i(e)/2,n+=c(e)-r,u+=o(e)-r,(h-=s(e)-r)<n&&(n=h=(n+h)/2),(f-=l(e)-r)<u&&(u=f=(u+f)/2),t(e,n,u,h,f))}return u.round=function(t){return arguments.length?(e=!!t,u):e},u.size=function(t){return arguments.length?(r=+t[0],n=+t[1],u):[r,n]},u.tile=function(e){return arguments.length?(t=T(e),u):t},u.padding=function(t){return arguments.length?u.paddingInner(t).paddingOuter(t):u.paddingInner()},u.paddingInner=function(t){return arguments.length?(i=\"function\"==typeof t?t:A(+t),u):i},u.paddingOuter=function(t){return arguments.length?u.paddingTop(t).paddingRight(t).paddingBottom(t).paddingLeft(t):u.paddingTop()},u.paddingTop=function(t){return arguments.length?(o=\"function\"==typeof t?t:A(+t),u):o},u.paddingRight=function(t){return arguments.length?(s=\"function\"==typeof t?t:A(+t),u):s},u.paddingBottom=function(t){return arguments.length?(l=\"function\"==typeof t?t:A(+t),u):l},u.paddingLeft=function(t){return arguments.length?(c=\"function\"==typeof t?t:A(+t),u):c},u},t.treemapBinary=function(t,e,r,n,a){var i,o,s=t.children,l=s.length,c=new Array(l+1);for(c[0]=o=i=0;i<l;++i)c[i+1]=o+=s[i].value;!function t(e,r,n,a,i,o,l){if(e>=r-1){var u=s[e];return u.x0=a,u.y0=i,u.x1=o,void(u.y1=l)}for(var h=c[e],f=n/2+h,p=e+1,d=r-1;p<d;){var g=p+d>>>1;c[g]<f?p=g+1:d=g}f-c[p-1]<c[p]-f&&e+1<p&&--p;var v=c[p]-h,m=n-v;if(o-a>l-i){var y=(a*m+o*v)/n;t(e,p,v,a,i,y,l),t(p,r,m,y,i,o,l)}else{var x=(i*m+l*v)/n;t(e,p,v,a,i,o,x),t(p,r,m,a,x,o,l)}}(0,l,t.value,e,r,n,a)},t.treemapDice=O,t.treemapResquarify=X,t.treemapSlice=H,t.treemapSliceDice=function(t,e,r,n,a){(1&t.depth?H:O)(t,e,r,n,a)},t.treemapSquarify=W,Object.defineProperty(t,\"__esModule\",{value:!0})}(\"object\"==typeof r&&\"undefined\"!=typeof e?r:(n=n||self).d3=n.d3||{})},{}],160:[function(t,e,r){var n,a;n=this,a=function(t,e){\"use strict\";function r(t,e,r,n,a){var i=t*t,o=i*t;return((1-3*t+3*i-o)*e+(4-6*i+3*o)*r+(1+3*t+3*i-3*o)*n+o*a)/6}function n(t){var e=t.length-1;return function(n){var a=n<=0?n=0:n>=1?(n=1,e-1):Math.floor(n*e),i=t[a],o=t[a+1],s=a>0?t[a-1]:2*i-o,l=a<e-1?t[a+2]:2*o-i;return r((n-a/e)*e,s,i,o,l)}}function a(t){var e=t.length;return function(n){var a=Math.floor(((n%=1)<0?++n:n)*e),i=t[(a+e-1)%e],o=t[a%e],s=t[(a+1)%e],l=t[(a+2)%e];return r((n-a/e)*e,i,o,s,l)}}function i(t){return function(){return t}}function o(t,e){return function(r){return t+r*e}}function s(t,e){var r=e-t;return r?o(t,r>180||r<-180?r-360*Math.round(r/360):r):i(isNaN(t)?e:t)}function l(t){return 1==(t=+t)?c:function(e,r){return r-e?function(t,e,r){return t=Math.pow(t,r),e=Math.pow(e,r)-t,r=1/r,function(n){return Math.pow(t+n*e,r)}}(e,r,t):i(isNaN(e)?r:e)}}function c(t,e){var r=e-t;return r?o(t,r):i(isNaN(t)?e:t)}var u=function t(r){var n=l(r);function a(t,r){var a=n((t=e.rgb(t)).r,(r=e.rgb(r)).r),i=n(t.g,r.g),o=n(t.b,r.b),s=c(t.opacity,r.opacity);return function(e){return t.r=a(e),t.g=i(e),t.b=o(e),t.opacity=s(e),t+\"\"}}return a.gamma=t,a}(1);function h(t){return function(r){var n,a,i=r.length,o=new Array(i),s=new Array(i),l=new Array(i);for(n=0;n<i;++n)a=e.rgb(r[n]),o[n]=a.r||0,s[n]=a.g||0,l[n]=a.b||0;return o=t(o),s=t(s),l=t(l),a.opacity=1,function(t){return a.r=o(t),a.g=s(t),a.b=l(t),a+\"\"}}}var f=h(n),p=h(a);function d(t,e){e||(e=[]);var r,n=t?Math.min(e.length,t.length):0,a=e.slice();return function(i){for(r=0;r<n;++r)a[r]=t[r]*(1-i)+e[r]*i;return a}}function g(t){return ArrayBuffer.isView(t)&&!(t instanceof DataView)}function v(t,e){var r,n=e?e.length:0,a=t?Math.min(n,t.length):0,i=new Array(a),o=new Array(n);for(r=0;r<a;++r)i[r]=k(t[r],e[r]);for(;r<n;++r)o[r]=e[r];return function(t){for(r=0;r<a;++r)o[r]=i[r](t);return o}}function m(t,e){var r=new Date;return t=+t,e=+e,function(n){return r.setTime(t*(1-n)+e*n),r}}function y(t,e){return t=+t,e=+e,function(r){return t*(1-r)+e*r}}function x(t,e){var r,n={},a={};for(r in null!==t&&\"object\"==typeof t||(t={}),null!==e&&\"object\"==typeof e||(e={}),e)r in t?n[r]=k(t[r],e[r]):a[r]=e[r];return function(t){for(r in n)a[r]=n[r](t);return a}}var b=/[-+]?(?:\\d+\\.?\\d*|\\.?\\d+)(?:[eE][-+]?\\d+)?/g,_=new RegExp(b.source,\"g\");function w(t,e){var r,n,a,i=b.lastIndex=_.lastIndex=0,o=-1,s=[],l=[];for(t+=\"\",e+=\"\";(r=b.exec(t))&&(n=_.exec(e));)(a=n.index)>i&&(a=e.slice(i,a),s[o]?s[o]+=a:s[++o]=a),(r=r[0])===(n=n[0])?s[o]?s[o]+=n:s[++o]=n:(s[++o]=null,l.push({i:o,x:y(r,n)})),i=_.lastIndex;return i<e.length&&(a=e.slice(i),s[o]?s[o]+=a:s[++o]=a),s.length<2?l[0]?function(t){return function(e){return t(e)+\"\"}}(l[0].x):function(t){return function(){return t}}(e):(e=l.length,function(t){for(var r,n=0;n<e;++n)s[(r=l[n]).i]=r.x(t);return s.join(\"\")})}function k(t,r){var n,a=typeof r;return null==r||\"boolean\"===a?i(r):(\"number\"===a?y:\"string\"===a?(n=e.color(r))?(r=n,u):w:r instanceof e.color?u:r instanceof Date?m:g(r)?d:Array.isArray(r)?v:\"function\"!=typeof r.valueOf&&\"function\"!=typeof r.toString||isNaN(r)?x:y)(t,r)}var T,M,A,S,E=180/Math.PI,L={translateX:0,translateY:0,rotate:0,skewX:0,scaleX:1,scaleY:1};function C(t,e,r,n,a,i){var o,s,l;return(o=Math.sqrt(t*t+e*e))&&(t/=o,e/=o),(l=t*r+e*n)&&(r-=t*l,n-=e*l),(s=Math.sqrt(r*r+n*n))&&(r/=s,n/=s,l/=s),t*n<e*r&&(t=-t,e=-e,l=-l,o=-o),{translateX:a,translateY:i,rotate:Math.atan2(e,t)*E,skewX:Math.atan(l)*E,scaleX:o,scaleY:s}}function P(t,e,r,n){function a(t){return t.length?t.pop()+\" \":\"\"}return function(i,o){var s=[],l=[];return i=t(i),o=t(o),function(t,n,a,i,o,s){if(t!==a||n!==i){var l=o.push(\"translate(\",null,e,null,r);s.push({i:l-4,x:y(t,a)},{i:l-2,x:y(n,i)})}else(a||i)&&o.push(\"translate(\"+a+e+i+r)}(i.translateX,i.translateY,o.translateX,o.translateY,s,l),function(t,e,r,i){t!==e?(t-e>180?e+=360:e-t>180&&(t+=360),i.push({i:r.push(a(r)+\"rotate(\",null,n)-2,x:y(t,e)})):e&&r.push(a(r)+\"rotate(\"+e+n)}(i.rotate,o.rotate,s,l),function(t,e,r,i){t!==e?i.push({i:r.push(a(r)+\"skewX(\",null,n)-2,x:y(t,e)}):e&&r.push(a(r)+\"skewX(\"+e+n)}(i.skewX,o.skewX,s,l),function(t,e,r,n,i,o){if(t!==r||e!==n){var s=i.push(a(i)+\"scale(\",null,\",\",null,\")\");o.push({i:s-4,x:y(t,r)},{i:s-2,x:y(e,n)})}else 1===r&&1===n||i.push(a(i)+\"scale(\"+r+\",\"+n+\")\")}(i.scaleX,i.scaleY,o.scaleX,o.scaleY,s,l),i=o=null,function(t){for(var e,r=-1,n=l.length;++r<n;)s[(e=l[r]).i]=e.x(t);return s.join(\"\")}}}var O=P(function(t){return\"none\"===t?L:(T||(T=document.createElement(\"DIV\"),M=document.documentElement,A=document.defaultView),T.style.transform=t,t=A.getComputedStyle(M.appendChild(T),null).getPropertyValue(\"transform\"),M.removeChild(T),C(+(t=t.slice(7,-1).split(\",\"))[0],+t[1],+t[2],+t[3],+t[4],+t[5]))},\"px, \",\"px)\",\"deg)\"),z=P(function(t){return null==t?L:(S||(S=document.createElementNS(\"http://www.w3.org/2000/svg\",\"g\")),S.setAttribute(\"transform\",t),(t=S.transform.baseVal.consolidate())?C((t=t.matrix).a,t.b,t.c,t.d,t.e,t.f):L)},\", \",\")\",\")\"),I=Math.SQRT2,D=2,R=4,F=1e-12;function B(t){return((t=Math.exp(t))+1/t)/2}function N(t){return function(r,n){var a=t((r=e.hsl(r)).h,(n=e.hsl(n)).h),i=c(r.s,n.s),o=c(r.l,n.l),s=c(r.opacity,n.opacity);return function(t){return r.h=a(t),r.s=i(t),r.l=o(t),r.opacity=s(t),r+\"\"}}}var j=N(s),V=N(c);function U(t){return function(r,n){var a=t((r=e.hcl(r)).h,(n=e.hcl(n)).h),i=c(r.c,n.c),o=c(r.l,n.l),s=c(r.opacity,n.opacity);return function(t){return r.h=a(t),r.c=i(t),r.l=o(t),r.opacity=s(t),r+\"\"}}}var q=U(s),H=U(c);function G(t){return function r(n){function a(r,a){var i=t((r=e.cubehelix(r)).h,(a=e.cubehelix(a)).h),o=c(r.s,a.s),s=c(r.l,a.l),l=c(r.opacity,a.opacity);return function(t){return r.h=i(t),r.s=o(t),r.l=s(Math.pow(t,n)),r.opacity=l(t),r+\"\"}}return n=+n,a.gamma=r,a}(1)}var Y=G(s),W=G(c);t.interpolate=k,t.interpolateArray=function(t,e){return(g(e)?d:v)(t,e)},t.interpolateBasis=n,t.interpolateBasisClosed=a,t.interpolateCubehelix=Y,t.interpolateCubehelixLong=W,t.interpolateDate=m,t.interpolateDiscrete=function(t){var e=t.length;return function(r){return t[Math.max(0,Math.min(e-1,Math.floor(r*e)))]}},t.interpolateHcl=q,t.interpolateHclLong=H,t.interpolateHsl=j,t.interpolateHslLong=V,t.interpolateHue=function(t,e){var r=s(+t,+e);return function(t){var e=r(t);return e-360*Math.floor(e/360)}},t.interpolateLab=function(t,r){var n=c((t=e.lab(t)).l,(r=e.lab(r)).l),a=c(t.a,r.a),i=c(t.b,r.b),o=c(t.opacity,r.opacity);return function(e){return t.l=n(e),t.a=a(e),t.b=i(e),t.opacity=o(e),t+\"\"}},t.interpolateNumber=y,t.interpolateNumberArray=d,t.interpolateObject=x,t.interpolateRgb=u,t.interpolateRgbBasis=f,t.interpolateRgbBasisClosed=p,t.interpolateRound=function(t,e){return t=+t,e=+e,function(r){return Math.round(t*(1-r)+e*r)}},t.interpolateString=w,t.interpolateTransformCss=O,t.interpolateTransformSvg=z,t.interpolateZoom=function(t,e){var r,n,a=t[0],i=t[1],o=t[2],s=e[0],l=e[1],c=e[2],u=s-a,h=l-i,f=u*u+h*h;if(f<F)n=Math.log(c/o)/I,r=function(t){return[a+t*u,i+t*h,o*Math.exp(I*t*n)]};else{var p=Math.sqrt(f),d=(c*c-o*o+R*f)/(2*o*D*p),g=(c*c-o*o-R*f)/(2*c*D*p),v=Math.log(Math.sqrt(d*d+1)-d),m=Math.log(Math.sqrt(g*g+1)-g);n=(m-v)/I,r=function(t){var e,r=t*n,s=B(v),l=o/(D*p)*(s*(e=I*r+v,((e=Math.exp(2*e))-1)/(e+1))-function(t){return((t=Math.exp(t))-1/t)/2}(v));return[a+l*u,i+l*h,o*s/B(I*r+v)]}}return r.duration=1e3*n,r},t.piecewise=function(t,e){for(var r=0,n=e.length-1,a=e[0],i=new Array(n<0?0:n);r<n;)i[r]=t(a,a=e[++r]);return function(t){var e=Math.max(0,Math.min(n-1,Math.floor(t*=n)));return i[e](t-e)}},t.quantize=function(t,e){for(var r=new Array(e),n=0;n<e;++n)r[n]=t(n/(e-1));return r},Object.defineProperty(t,\"__esModule\",{value:!0})},\"object\"==typeof r&&\"undefined\"!=typeof e?a(r,t(\"d3-color\")):a((n=n||self).d3=n.d3||{},n.d3)},{\"d3-color\":156}],161:[function(t,e,r){var n;n=this,function(t){\"use strict\";var e=Math.PI,r=2*e,n=r-1e-6;function a(){this._x0=this._y0=this._x1=this._y1=null,this._=\"\"}function i(){return new a}a.prototype=i.prototype={constructor:a,moveTo:function(t,e){this._+=\"M\"+(this._x0=this._x1=+t)+\",\"+(this._y0=this._y1=+e)},closePath:function(){null!==this._x1&&(this._x1=this._x0,this._y1=this._y0,this._+=\"Z\")},lineTo:function(t,e){this._+=\"L\"+(this._x1=+t)+\",\"+(this._y1=+e)},quadraticCurveTo:function(t,e,r,n){this._+=\"Q\"+ +t+\",\"+ +e+\",\"+(this._x1=+r)+\",\"+(this._y1=+n)},bezierCurveTo:function(t,e,r,n,a,i){this._+=\"C\"+ +t+\",\"+ +e+\",\"+ +r+\",\"+ +n+\",\"+(this._x1=+a)+\",\"+(this._y1=+i)},arcTo:function(t,r,n,a,i){t=+t,r=+r,n=+n,a=+a,i=+i;var o=this._x1,s=this._y1,l=n-t,c=a-r,u=o-t,h=s-r,f=u*u+h*h;if(i<0)throw new Error(\"negative radius: \"+i);if(null===this._x1)this._+=\"M\"+(this._x1=t)+\",\"+(this._y1=r);else if(f>1e-6)if(Math.abs(h*l-c*u)>1e-6&&i){var p=n-o,d=a-s,g=l*l+c*c,v=p*p+d*d,m=Math.sqrt(g),y=Math.sqrt(f),x=i*Math.tan((e-Math.acos((g+f-v)/(2*m*y)))/2),b=x/y,_=x/m;Math.abs(b-1)>1e-6&&(this._+=\"L\"+(t+b*u)+\",\"+(r+b*h)),this._+=\"A\"+i+\",\"+i+\",0,0,\"+ +(h*p>u*d)+\",\"+(this._x1=t+_*l)+\",\"+(this._y1=r+_*c)}else this._+=\"L\"+(this._x1=t)+\",\"+(this._y1=r);else;},arc:function(t,a,i,o,s,l){t=+t,a=+a;var c=(i=+i)*Math.cos(o),u=i*Math.sin(o),h=t+c,f=a+u,p=1^l,d=l?o-s:s-o;if(i<0)throw new Error(\"negative radius: \"+i);null===this._x1?this._+=\"M\"+h+\",\"+f:(Math.abs(this._x1-h)>1e-6||Math.abs(this._y1-f)>1e-6)&&(this._+=\"L\"+h+\",\"+f),i&&(d<0&&(d=d%r+r),d>n?this._+=\"A\"+i+\",\"+i+\",0,1,\"+p+\",\"+(t-c)+\",\"+(a-u)+\"A\"+i+\",\"+i+\",0,1,\"+p+\",\"+(this._x1=h)+\",\"+(this._y1=f):d>1e-6&&(this._+=\"A\"+i+\",\"+i+\",0,\"+ +(d>=e)+\",\"+p+\",\"+(this._x1=t+i*Math.cos(s))+\",\"+(this._y1=a+i*Math.sin(s))))},rect:function(t,e,r,n){this._+=\"M\"+(this._x0=this._x1=+t)+\",\"+(this._y0=this._y1=+e)+\"h\"+ +r+\"v\"+ +n+\"h\"+-r+\"Z\"},toString:function(){return this._}},t.path=i,Object.defineProperty(t,\"__esModule\",{value:!0})}(\"object\"==typeof r&&\"undefined\"!=typeof e?r:n.d3=n.d3||{})},{}],162:[function(t,e,r){var n;n=this,function(t){\"use strict\";function e(t,e,r,n){if(isNaN(e)||isNaN(r))return t;var a,i,o,s,l,c,u,h,f,p=t._root,d={data:n},g=t._x0,v=t._y0,m=t._x1,y=t._y1;if(!p)return t._root=d,t;for(;p.length;)if((c=e>=(i=(g+m)/2))?g=i:m=i,(u=r>=(o=(v+y)/2))?v=o:y=o,a=p,!(p=p[h=u<<1|c]))return a[h]=d,t;if(s=+t._x.call(null,p.data),l=+t._y.call(null,p.data),e===s&&r===l)return d.next=p,a?a[h]=d:t._root=d,t;do{a=a?a[h]=new Array(4):t._root=new Array(4),(c=e>=(i=(g+m)/2))?g=i:m=i,(u=r>=(o=(v+y)/2))?v=o:y=o}while((h=u<<1|c)==(f=(l>=o)<<1|s>=i));return a[f]=p,a[h]=d,t}var r=function(t,e,r,n,a){this.node=t,this.x0=e,this.y0=r,this.x1=n,this.y1=a};function n(t){return t[0]}function a(t){return t[1]}function i(t,e,r){var i=new o(null==e?n:e,null==r?a:r,NaN,NaN,NaN,NaN);return null==t?i:i.addAll(t)}function o(t,e,r,n,a,i){this._x=t,this._y=e,this._x0=r,this._y0=n,this._x1=a,this._y1=i,this._root=void 0}function s(t){for(var e={data:t.data},r=e;t=t.next;)r=r.next={data:t.data};return e}var l=i.prototype=o.prototype;l.copy=function(){var t,e,r=new o(this._x,this._y,this._x0,this._y0,this._x1,this._y1),n=this._root;if(!n)return r;if(!n.length)return r._root=s(n),r;for(t=[{source:n,target:r._root=new Array(4)}];n=t.pop();)for(var a=0;a<4;++a)(e=n.source[a])&&(e.length?t.push({source:e,target:n.target[a]=new Array(4)}):n.target[a]=s(e));return r},l.add=function(t){var r=+this._x.call(null,t),n=+this._y.call(null,t);return e(this.cover(r,n),r,n,t)},l.addAll=function(t){var r,n,a,i,o=t.length,s=new Array(o),l=new Array(o),c=1/0,u=1/0,h=-1/0,f=-1/0;for(n=0;n<o;++n)isNaN(a=+this._x.call(null,r=t[n]))||isNaN(i=+this._y.call(null,r))||(s[n]=a,l[n]=i,a<c&&(c=a),a>h&&(h=a),i<u&&(u=i),i>f&&(f=i));for(h<c&&(c=this._x0,h=this._x1),f<u&&(u=this._y0,f=this._y1),this.cover(c,u).cover(h,f),n=0;n<o;++n)e(this,s[n],l[n],t[n]);return this},l.cover=function(t,e){if(isNaN(t=+t)||isNaN(e=+e))return this;var r=this._x0,n=this._y0,a=this._x1,i=this._y1;if(isNaN(r))a=(r=Math.floor(t))+1,i=(n=Math.floor(e))+1;else{if(!(r>t||t>a||n>e||e>i))return this;var o,s,l=a-r,c=this._root;switch(s=(e<(n+i)/2)<<1|t<(r+a)/2){case 0:do{(o=new Array(4))[s]=c,c=o}while(i=n+(l*=2),t>(a=r+l)||e>i);break;case 1:do{(o=new Array(4))[s]=c,c=o}while(i=n+(l*=2),(r=a-l)>t||e>i);break;case 2:do{(o=new Array(4))[s]=c,c=o}while(n=i-(l*=2),t>(a=r+l)||n>e);break;case 3:do{(o=new Array(4))[s]=c,c=o}while(n=i-(l*=2),(r=a-l)>t||n>e)}this._root&&this._root.length&&(this._root=c)}return this._x0=r,this._y0=n,this._x1=a,this._y1=i,this},l.data=function(){var t=[];return this.visit(function(e){if(!e.length)do{t.push(e.data)}while(e=e.next)}),t},l.extent=function(t){return arguments.length?this.cover(+t[0][0],+t[0][1]).cover(+t[1][0],+t[1][1]):isNaN(this._x0)?void 0:[[this._x0,this._y0],[this._x1,this._y1]]},l.find=function(t,e,n){var a,i,o,s,l,c,u,h=this._x0,f=this._y0,p=this._x1,d=this._y1,g=[],v=this._root;for(v&&g.push(new r(v,h,f,p,d)),null==n?n=1/0:(h=t-n,f=e-n,p=t+n,d=e+n,n*=n);c=g.pop();)if(!(!(v=c.node)||(i=c.x0)>p||(o=c.y0)>d||(s=c.x1)<h||(l=c.y1)<f))if(v.length){var m=(i+s)/2,y=(o+l)/2;g.push(new r(v[3],m,y,s,l),new r(v[2],i,y,m,l),new r(v[1],m,o,s,y),new r(v[0],i,o,m,y)),(u=(e>=y)<<1|t>=m)&&(c=g[g.length-1],g[g.length-1]=g[g.length-1-u],g[g.length-1-u]=c)}else{var x=t-+this._x.call(null,v.data),b=e-+this._y.call(null,v.data),_=x*x+b*b;if(_<n){var w=Math.sqrt(n=_);h=t-w,f=e-w,p=t+w,d=e+w,a=v.data}}return a},l.remove=function(t){if(isNaN(i=+this._x.call(null,t))||isNaN(o=+this._y.call(null,t)))return this;var e,r,n,a,i,o,s,l,c,u,h,f,p=this._root,d=this._x0,g=this._y0,v=this._x1,m=this._y1;if(!p)return this;if(p.length)for(;;){if((c=i>=(s=(d+v)/2))?d=s:v=s,(u=o>=(l=(g+m)/2))?g=l:m=l,e=p,!(p=p[h=u<<1|c]))return this;if(!p.length)break;(e[h+1&3]||e[h+2&3]||e[h+3&3])&&(r=e,f=h)}for(;p.data!==t;)if(n=p,!(p=p.next))return this;return(a=p.next)&&delete p.next,n?(a?n.next=a:delete n.next,this):e?(a?e[h]=a:delete e[h],(p=e[0]||e[1]||e[2]||e[3])&&p===(e[3]||e[2]||e[1]||e[0])&&!p.length&&(r?r[f]=p:this._root=p),this):(this._root=a,this)},l.removeAll=function(t){for(var e=0,r=t.length;e<r;++e)this.remove(t[e]);return this},l.root=function(){return this._root},l.size=function(){var t=0;return this.visit(function(e){if(!e.length)do{++t}while(e=e.next)}),t},l.visit=function(t){var e,n,a,i,o,s,l=[],c=this._root;for(c&&l.push(new r(c,this._x0,this._y0,this._x1,this._y1));e=l.pop();)if(!t(c=e.node,a=e.x0,i=e.y0,o=e.x1,s=e.y1)&&c.length){var u=(a+o)/2,h=(i+s)/2;(n=c[3])&&l.push(new r(n,u,h,o,s)),(n=c[2])&&l.push(new r(n,a,h,u,s)),(n=c[1])&&l.push(new r(n,u,i,o,h)),(n=c[0])&&l.push(new r(n,a,i,u,h))}return this},l.visitAfter=function(t){var e,n=[],a=[];for(this._root&&n.push(new r(this._root,this._x0,this._y0,this._x1,this._y1));e=n.pop();){var i=e.node;if(i.length){var o,s=e.x0,l=e.y0,c=e.x1,u=e.y1,h=(s+c)/2,f=(l+u)/2;(o=i[0])&&n.push(new r(o,s,l,h,f)),(o=i[1])&&n.push(new r(o,h,l,c,f)),(o=i[2])&&n.push(new r(o,s,f,h,u)),(o=i[3])&&n.push(new r(o,h,f,c,u))}a.push(e)}for(;e=a.pop();)t(e.node,e.x0,e.y0,e.x1,e.y1);return this},l.x=function(t){return arguments.length?(this._x=t,this):this._x},l.y=function(t){return arguments.length?(this._y=t,this):this._y},t.quadtree=i,Object.defineProperty(t,\"__esModule\",{value:!0})}(\"object\"==typeof r&&\"undefined\"!=typeof e?r:n.d3=n.d3||{})},{}],163:[function(t,e,r){var n,a;n=this,a=function(t,e){\"use strict\";function r(t){return function(){return t}}var n=Math.abs,a=Math.atan2,i=Math.cos,o=Math.max,s=Math.min,l=Math.sin,c=Math.sqrt,u=1e-12,h=Math.PI,f=h/2,p=2*h;function d(t){return t>=1?f:t<=-1?-f:Math.asin(t)}function g(t){return t.innerRadius}function v(t){return t.outerRadius}function m(t){return t.startAngle}function y(t){return t.endAngle}function x(t){return t&&t.padAngle}function b(t,e,r,n,a,i,s){var l=t-r,u=e-n,h=(s?i:-i)/c(l*l+u*u),f=h*u,p=-h*l,d=t+f,g=e+p,v=r+f,m=n+p,y=(d+v)/2,x=(g+m)/2,b=v-d,_=m-g,w=b*b+_*_,k=a-i,T=d*m-v*g,M=(_<0?-1:1)*c(o(0,k*k*w-T*T)),A=(T*_-b*M)/w,S=(-T*b-_*M)/w,E=(T*_+b*M)/w,L=(-T*b+_*M)/w,C=A-y,P=S-x,O=E-y,z=L-x;return C*C+P*P>O*O+z*z&&(A=E,S=L),{cx:A,cy:S,x01:-f,y01:-p,x11:A*(a/k-1),y11:S*(a/k-1)}}function _(t){this._context=t}function w(t){return new _(t)}function k(t){return t[0]}function T(t){return t[1]}function M(){var t=k,n=T,a=r(!0),i=null,o=w,s=null;function l(r){var l,c,u,h=r.length,f=!1;for(null==i&&(s=o(u=e.path())),l=0;l<=h;++l)!(l<h&&a(c=r[l],l,r))===f&&((f=!f)?s.lineStart():s.lineEnd()),f&&s.point(+t(c,l,r),+n(c,l,r));if(u)return s=null,u+\"\"||null}return l.x=function(e){return arguments.length?(t=\"function\"==typeof e?e:r(+e),l):t},l.y=function(t){return arguments.length?(n=\"function\"==typeof t?t:r(+t),l):n},l.defined=function(t){return arguments.length?(a=\"function\"==typeof t?t:r(!!t),l):a},l.curve=function(t){return arguments.length?(o=t,null!=i&&(s=o(i)),l):o},l.context=function(t){return arguments.length?(null==t?i=s=null:s=o(i=t),l):i},l}function A(){var t=k,n=null,a=r(0),i=T,o=r(!0),s=null,l=w,c=null;function u(r){var u,h,f,p,d,g=r.length,v=!1,m=new Array(g),y=new Array(g);for(null==s&&(c=l(d=e.path())),u=0;u<=g;++u){if(!(u<g&&o(p=r[u],u,r))===v)if(v=!v)h=u,c.areaStart(),c.lineStart();else{for(c.lineEnd(),c.lineStart(),f=u-1;f>=h;--f)c.point(m[f],y[f]);c.lineEnd(),c.areaEnd()}v&&(m[u]=+t(p,u,r),y[u]=+a(p,u,r),c.point(n?+n(p,u,r):m[u],i?+i(p,u,r):y[u]))}if(d)return c=null,d+\"\"||null}function h(){return M().defined(o).curve(l).context(s)}return u.x=function(e){return arguments.length?(t=\"function\"==typeof e?e:r(+e),n=null,u):t},u.x0=function(e){return arguments.length?(t=\"function\"==typeof e?e:r(+e),u):t},u.x1=function(t){return arguments.length?(n=null==t?null:\"function\"==typeof t?t:r(+t),u):n},u.y=function(t){return arguments.length?(a=\"function\"==typeof t?t:r(+t),i=null,u):a},u.y0=function(t){return arguments.length?(a=\"function\"==typeof t?t:r(+t),u):a},u.y1=function(t){return arguments.length?(i=null==t?null:\"function\"==typeof t?t:r(+t),u):i},u.lineX0=u.lineY0=function(){return h().x(t).y(a)},u.lineY1=function(){return h().x(t).y(i)},u.lineX1=function(){return h().x(n).y(a)},u.defined=function(t){return arguments.length?(o=\"function\"==typeof t?t:r(!!t),u):o},u.curve=function(t){return arguments.length?(l=t,null!=s&&(c=l(s)),u):l},u.context=function(t){return arguments.length?(null==t?s=c=null:c=l(s=t),u):s},u}function S(t,e){return e<t?-1:e>t?1:e>=t?0:NaN}function E(t){return t}_.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._point=0},lineEnd:function(){(this._line||0!==this._line&&1===this._point)&&this._context.closePath(),this._line=1-this._line},point:function(t,e){switch(t=+t,e=+e,this._point){case 0:this._point=1,this._line?this._context.lineTo(t,e):this._context.moveTo(t,e);break;case 1:this._point=2;default:this._context.lineTo(t,e)}}};var L=P(w);function C(t){this._curve=t}function P(t){function e(e){return new C(t(e))}return e._curve=t,e}function O(t){var e=t.curve;return t.angle=t.x,delete t.x,t.radius=t.y,delete t.y,t.curve=function(t){return arguments.length?e(P(t)):e()._curve},t}function z(){return O(M().curve(L))}function I(){var t=A().curve(L),e=t.curve,r=t.lineX0,n=t.lineX1,a=t.lineY0,i=t.lineY1;return t.angle=t.x,delete t.x,t.startAngle=t.x0,delete t.x0,t.endAngle=t.x1,delete t.x1,t.radius=t.y,delete t.y,t.innerRadius=t.y0,delete t.y0,t.outerRadius=t.y1,delete t.y1,t.lineStartAngle=function(){return O(r())},delete t.lineX0,t.lineEndAngle=function(){return O(n())},delete t.lineX1,t.lineInnerRadius=function(){return O(a())},delete t.lineY0,t.lineOuterRadius=function(){return O(i())},delete t.lineY1,t.curve=function(t){return arguments.length?e(P(t)):e()._curve},t}function D(t,e){return[(e=+e)*Math.cos(t-=Math.PI/2),e*Math.sin(t)]}C.prototype={areaStart:function(){this._curve.areaStart()},areaEnd:function(){this._curve.areaEnd()},lineStart:function(){this._curve.lineStart()},lineEnd:function(){this._curve.lineEnd()},point:function(t,e){this._curve.point(e*Math.sin(t),e*-Math.cos(t))}};var R=Array.prototype.slice;function F(t){return t.source}function B(t){return t.target}function N(t){var n=F,a=B,i=k,o=T,s=null;function l(){var r,l=R.call(arguments),c=n.apply(this,l),u=a.apply(this,l);if(s||(s=r=e.path()),t(s,+i.apply(this,(l[0]=c,l)),+o.apply(this,l),+i.apply(this,(l[0]=u,l)),+o.apply(this,l)),r)return s=null,r+\"\"||null}return l.source=function(t){return arguments.length?(n=t,l):n},l.target=function(t){return arguments.length?(a=t,l):a},l.x=function(t){return arguments.length?(i=\"function\"==typeof t?t:r(+t),l):i},l.y=function(t){return arguments.length?(o=\"function\"==typeof t?t:r(+t),l):o},l.context=function(t){return arguments.length?(s=null==t?null:t,l):s},l}function j(t,e,r,n,a){t.moveTo(e,r),t.bezierCurveTo(e=(e+n)/2,r,e,a,n,a)}function V(t,e,r,n,a){t.moveTo(e,r),t.bezierCurveTo(e,r=(r+a)/2,n,r,n,a)}function U(t,e,r,n,a){var i=D(e,r),o=D(e,r=(r+a)/2),s=D(n,r),l=D(n,a);t.moveTo(i[0],i[1]),t.bezierCurveTo(o[0],o[1],s[0],s[1],l[0],l[1])}var q={draw:function(t,e){var r=Math.sqrt(e/h);t.moveTo(r,0),t.arc(0,0,r,0,p)}},H={draw:function(t,e){var r=Math.sqrt(e/5)/2;t.moveTo(-3*r,-r),t.lineTo(-r,-r),t.lineTo(-r,-3*r),t.lineTo(r,-3*r),t.lineTo(r,-r),t.lineTo(3*r,-r),t.lineTo(3*r,r),t.lineTo(r,r),t.lineTo(r,3*r),t.lineTo(-r,3*r),t.lineTo(-r,r),t.lineTo(-3*r,r),t.closePath()}},G=Math.sqrt(1/3),Y=2*G,W={draw:function(t,e){var r=Math.sqrt(e/Y),n=r*G;t.moveTo(0,-r),t.lineTo(n,0),t.lineTo(0,r),t.lineTo(-n,0),t.closePath()}},X=Math.sin(h/10)/Math.sin(7*h/10),Z=Math.sin(p/10)*X,J=-Math.cos(p/10)*X,K={draw:function(t,e){var r=Math.sqrt(.8908130915292852*e),n=Z*r,a=J*r;t.moveTo(0,-r),t.lineTo(n,a);for(var i=1;i<5;++i){var o=p*i/5,s=Math.cos(o),l=Math.sin(o);t.lineTo(l*r,-s*r),t.lineTo(s*n-l*a,l*n+s*a)}t.closePath()}},Q={draw:function(t,e){var r=Math.sqrt(e),n=-r/2;t.rect(n,n,r,r)}},$=Math.sqrt(3),tt={draw:function(t,e){var r=-Math.sqrt(e/(3*$));t.moveTo(0,2*r),t.lineTo(-$*r,-r),t.lineTo($*r,-r),t.closePath()}},et=-.5,rt=Math.sqrt(3)/2,nt=1/Math.sqrt(12),at=3*(nt/2+1),it={draw:function(t,e){var r=Math.sqrt(e/at),n=r/2,a=r*nt,i=n,o=r*nt+r,s=-i,l=o;t.moveTo(n,a),t.lineTo(i,o),t.lineTo(s,l),t.lineTo(et*n-rt*a,rt*n+et*a),t.lineTo(et*i-rt*o,rt*i+et*o),t.lineTo(et*s-rt*l,rt*s+et*l),t.lineTo(et*n+rt*a,et*a-rt*n),t.lineTo(et*i+rt*o,et*o-rt*i),t.lineTo(et*s+rt*l,et*l-rt*s),t.closePath()}},ot=[q,H,W,Q,K,tt,it];function st(){}function lt(t,e,r){t._context.bezierCurveTo((2*t._x0+t._x1)/3,(2*t._y0+t._y1)/3,(t._x0+2*t._x1)/3,(t._y0+2*t._y1)/3,(t._x0+4*t._x1+e)/6,(t._y0+4*t._y1+r)/6)}function ct(t){this._context=t}function ut(t){this._context=t}function ht(t){this._context=t}function ft(t,e){this._basis=new ct(t),this._beta=e}ct.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._y0=this._y1=NaN,this._point=0},lineEnd:function(){switch(this._point){case 3:lt(this,this._x1,this._y1);case 2:this._context.lineTo(this._x1,this._y1)}(this._line||0!==this._line&&1===this._point)&&this._context.closePath(),this._line=1-this._line},point:function(t,e){switch(t=+t,e=+e,this._point){case 0:this._point=1,this._line?this._context.lineTo(t,e):this._context.moveTo(t,e);break;case 1:this._point=2;break;case 2:this._point=3,this._context.lineTo((5*this._x0+this._x1)/6,(5*this._y0+this._y1)/6);default:lt(this,t,e)}this._x0=this._x1,this._x1=t,this._y0=this._y1,this._y1=e}},ut.prototype={areaStart:st,areaEnd:st,lineStart:function(){this._x0=this._x1=this._x2=this._x3=this._x4=this._y0=this._y1=this._y2=this._y3=this._y4=NaN,this._point=0},lineEnd:function(){switch(this._point){case 1:this._context.moveTo(this._x2,this._y2),this._context.closePath();break;case 2:this._context.moveTo((this._x2+2*this._x3)/3,(this._y2+2*this._y3)/3),this._context.lineTo((this._x3+2*this._x2)/3,(this._y3+2*this._y2)/3),this._context.closePath();break;case 3:this.point(this._x2,this._y2),this.point(this._x3,this._y3),this.point(this._x4,this._y4)}},point:function(t,e){switch(t=+t,e=+e,this._point){case 0:this._point=1,this._x2=t,this._y2=e;break;case 1:this._point=2,this._x3=t,this._y3=e;break;case 2:this._point=3,this._x4=t,this._y4=e,this._context.moveTo((this._x0+4*this._x1+t)/6,(this._y0+4*this._y1+e)/6);break;default:lt(this,t,e)}this._x0=this._x1,this._x1=t,this._y0=this._y1,this._y1=e}},ht.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._y0=this._y1=NaN,this._point=0},lineEnd:function(){(this._line||0!==this._line&&3===this._point)&&this._context.closePath(),this._line=1-this._line},point:function(t,e){switch(t=+t,e=+e,this._point){case 0:this._point=1;break;case 1:this._point=2;break;case 2:this._point=3;var r=(this._x0+4*this._x1+t)/6,n=(this._y0+4*this._y1+e)/6;this._line?this._context.lineTo(r,n):this._context.moveTo(r,n);break;case 3:this._point=4;default:lt(this,t,e)}this._x0=this._x1,this._x1=t,this._y0=this._y1,this._y1=e}},ft.prototype={lineStart:function(){this._x=[],this._y=[],this._basis.lineStart()},lineEnd:function(){var t=this._x,e=this._y,r=t.length-1;if(r>0)for(var n,a=t[0],i=e[0],o=t[r]-a,s=e[r]-i,l=-1;++l<=r;)n=l/r,this._basis.point(this._beta*t[l]+(1-this._beta)*(a+n*o),this._beta*e[l]+(1-this._beta)*(i+n*s));this._x=this._y=null,this._basis.lineEnd()},point:function(t,e){this._x.push(+t),this._y.push(+e)}};var pt=function t(e){function r(t){return 1===e?new ct(t):new ft(t,e)}return r.beta=function(e){return t(+e)},r}(.85);function dt(t,e,r){t._context.bezierCurveTo(t._x1+t._k*(t._x2-t._x0),t._y1+t._k*(t._y2-t._y0),t._x2+t._k*(t._x1-e),t._y2+t._k*(t._y1-r),t._x2,t._y2)}function gt(t,e){this._context=t,this._k=(1-e)/6}gt.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._x2=this._y0=this._y1=this._y2=NaN,this._point=0},lineEnd:function(){switch(this._point){case 2:this._context.lineTo(this._x2,this._y2);break;case 3:dt(this,this._x1,this._y1)}(this._line||0!==this._line&&1===this._point)&&this._context.closePath(),this._line=1-this._line},point:function(t,e){switch(t=+t,e=+e,this._point){case 0:this._point=1,this._line?this._context.lineTo(t,e):this._context.moveTo(t,e);break;case 1:this._point=2,this._x1=t,this._y1=e;break;case 2:this._point=3;default:dt(this,t,e)}this._x0=this._x1,this._x1=this._x2,this._x2=t,this._y0=this._y1,this._y1=this._y2,this._y2=e}};var vt=function t(e){function r(t){return new gt(t,e)}return r.tension=function(e){return t(+e)},r}(0);function mt(t,e){this._context=t,this._k=(1-e)/6}mt.prototype={areaStart:st,areaEnd:st,lineStart:function(){this._x0=this._x1=this._x2=this._x3=this._x4=this._x5=this._y0=this._y1=this._y2=this._y3=this._y4=this._y5=NaN,this._point=0},lineEnd:function(){switch(this._point){case 1:this._context.moveTo(this._x3,this._y3),this._context.closePath();break;case 2:this._context.lineTo(this._x3,this._y3),this._context.closePath();break;case 3:this.point(this._x3,this._y3),this.point(this._x4,this._y4),this.point(this._x5,this._y5)}},point:function(t,e){switch(t=+t,e=+e,this._point){case 0:this._point=1,this._x3=t,this._y3=e;break;case 1:this._point=2,this._context.moveTo(this._x4=t,this._y4=e);break;case 2:this._point=3,this._x5=t,this._y5=e;break;default:dt(this,t,e)}this._x0=this._x1,this._x1=this._x2,this._x2=t,this._y0=this._y1,this._y1=this._y2,this._y2=e}};var yt=function t(e){function r(t){return new mt(t,e)}return r.tension=function(e){return t(+e)},r}(0);function xt(t,e){this._context=t,this._k=(1-e)/6}xt.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._x2=this._y0=this._y1=this._y2=NaN,this._point=0},lineEnd:function(){(this._line||0!==this._line&&3===this._point)&&this._context.closePath(),this._line=1-this._line},point:function(t,e){switch(t=+t,e=+e,this._point){case 0:this._point=1;break;case 1:this._point=2;break;case 2:this._point=3,this._line?this._context.lineTo(this._x2,this._y2):this._context.moveTo(this._x2,this._y2);break;case 3:this._point=4;default:dt(this,t,e)}this._x0=this._x1,this._x1=this._x2,this._x2=t,this._y0=this._y1,this._y1=this._y2,this._y2=e}};var bt=function t(e){function r(t){return new xt(t,e)}return r.tension=function(e){return t(+e)},r}(0);function _t(t,e,r){var n=t._x1,a=t._y1,i=t._x2,o=t._y2;if(t._l01_a>u){var s=2*t._l01_2a+3*t._l01_a*t._l12_a+t._l12_2a,l=3*t._l01_a*(t._l01_a+t._l12_a);n=(n*s-t._x0*t._l12_2a+t._x2*t._l01_2a)/l,a=(a*s-t._y0*t._l12_2a+t._y2*t._l01_2a)/l}if(t._l23_a>u){var c=2*t._l23_2a+3*t._l23_a*t._l12_a+t._l12_2a,h=3*t._l23_a*(t._l23_a+t._l12_a);i=(i*c+t._x1*t._l23_2a-e*t._l12_2a)/h,o=(o*c+t._y1*t._l23_2a-r*t._l12_2a)/h}t._context.bezierCurveTo(n,a,i,o,t._x2,t._y2)}function wt(t,e){this._context=t,this._alpha=e}wt.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._x2=this._y0=this._y1=this._y2=NaN,this._l01_a=this._l12_a=this._l23_a=this._l01_2a=this._l12_2a=this._l23_2a=this._point=0},lineEnd:function(){switch(this._point){case 2:this._context.lineTo(this._x2,this._y2);break;case 3:this.point(this._x2,this._y2)}(this._line||0!==this._line&&1===this._point)&&this._context.closePath(),this._line=1-this._line},point:function(t,e){if(t=+t,e=+e,this._point){var r=this._x2-t,n=this._y2-e;this._l23_a=Math.sqrt(this._l23_2a=Math.pow(r*r+n*n,this._alpha))}switch(this._point){case 0:this._point=1,this._line?this._context.lineTo(t,e):this._context.moveTo(t,e);break;case 1:this._point=2;break;case 2:this._point=3;default:_t(this,t,e)}this._l01_a=this._l12_a,this._l12_a=this._l23_a,this._l01_2a=this._l12_2a,this._l12_2a=this._l23_2a,this._x0=this._x1,this._x1=this._x2,this._x2=t,this._y0=this._y1,this._y1=this._y2,this._y2=e}};var kt=function t(e){function r(t){return e?new wt(t,e):new gt(t,0)}return r.alpha=function(e){return t(+e)},r}(.5);function Tt(t,e){this._context=t,this._alpha=e}Tt.prototype={areaStart:st,areaEnd:st,lineStart:function(){this._x0=this._x1=this._x2=this._x3=this._x4=this._x5=this._y0=this._y1=this._y2=this._y3=this._y4=this._y5=NaN,this._l01_a=this._l12_a=this._l23_a=this._l01_2a=this._l12_2a=this._l23_2a=this._point=0},lineEnd:function(){switch(this._point){case 1:this._context.moveTo(this._x3,this._y3),this._context.closePath();break;case 2:this._context.lineTo(this._x3,this._y3),this._context.closePath();break;case 3:this.point(this._x3,this._y3),this.point(this._x4,this._y4),this.point(this._x5,this._y5)}},point:function(t,e){if(t=+t,e=+e,this._point){var r=this._x2-t,n=this._y2-e;this._l23_a=Math.sqrt(this._l23_2a=Math.pow(r*r+n*n,this._alpha))}switch(this._point){case 0:this._point=1,this._x3=t,this._y3=e;break;case 1:this._point=2,this._context.moveTo(this._x4=t,this._y4=e);break;case 2:this._point=3,this._x5=t,this._y5=e;break;default:_t(this,t,e)}this._l01_a=this._l12_a,this._l12_a=this._l23_a,this._l01_2a=this._l12_2a,this._l12_2a=this._l23_2a,this._x0=this._x1,this._x1=this._x2,this._x2=t,this._y0=this._y1,this._y1=this._y2,this._y2=e}};var Mt=function t(e){function r(t){return e?new Tt(t,e):new mt(t,0)}return r.alpha=function(e){return t(+e)},r}(.5);function At(t,e){this._context=t,this._alpha=e}At.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._x2=this._y0=this._y1=this._y2=NaN,this._l01_a=this._l12_a=this._l23_a=this._l01_2a=this._l12_2a=this._l23_2a=this._point=0},lineEnd:function(){(this._line||0!==this._line&&3===this._point)&&this._context.closePath(),this._line=1-this._line},point:function(t,e){if(t=+t,e=+e,this._point){var r=this._x2-t,n=this._y2-e;this._l23_a=Math.sqrt(this._l23_2a=Math.pow(r*r+n*n,this._alpha))}switch(this._point){case 0:this._point=1;break;case 1:this._point=2;break;case 2:this._point=3,this._line?this._context.lineTo(this._x2,this._y2):this._context.moveTo(this._x2,this._y2);break;case 3:this._point=4;default:_t(this,t,e)}this._l01_a=this._l12_a,this._l12_a=this._l23_a,this._l01_2a=this._l12_2a,this._l12_2a=this._l23_2a,this._x0=this._x1,this._x1=this._x2,this._x2=t,this._y0=this._y1,this._y1=this._y2,this._y2=e}};var St=function t(e){function r(t){return e?new At(t,e):new xt(t,0)}return r.alpha=function(e){return t(+e)},r}(.5);function Et(t){this._context=t}function Lt(t){return t<0?-1:1}function Ct(t,e,r){var n=t._x1-t._x0,a=e-t._x1,i=(t._y1-t._y0)/(n||a<0&&-0),o=(r-t._y1)/(a||n<0&&-0),s=(i*a+o*n)/(n+a);return(Lt(i)+Lt(o))*Math.min(Math.abs(i),Math.abs(o),.5*Math.abs(s))||0}function Pt(t,e){var r=t._x1-t._x0;return r?(3*(t._y1-t._y0)/r-e)/2:e}function Ot(t,e,r){var n=t._x0,a=t._y0,i=t._x1,o=t._y1,s=(i-n)/3;t._context.bezierCurveTo(n+s,a+s*e,i-s,o-s*r,i,o)}function zt(t){this._context=t}function It(t){this._context=new Dt(t)}function Dt(t){this._context=t}function Rt(t){this._context=t}function Ft(t){var e,r,n=t.length-1,a=new Array(n),i=new Array(n),o=new Array(n);for(a[0]=0,i[0]=2,o[0]=t[0]+2*t[1],e=1;e<n-1;++e)a[e]=1,i[e]=4,o[e]=4*t[e]+2*t[e+1];for(a[n-1]=2,i[n-1]=7,o[n-1]=8*t[n-1]+t[n],e=1;e<n;++e)r=a[e]/i[e-1],i[e]-=r,o[e]-=r*o[e-1];for(a[n-1]=o[n-1]/i[n-1],e=n-2;e>=0;--e)a[e]=(o[e]-a[e+1])/i[e];for(i[n-1]=(t[n]+a[n-1])/2,e=0;e<n-1;++e)i[e]=2*t[e+1]-a[e+1];return[a,i]}function Bt(t,e){this._context=t,this._t=e}function Nt(t,e){if((a=t.length)>1)for(var r,n,a,i=1,o=t[e[0]],s=o.length;i<a;++i)for(n=o,o=t[e[i]],r=0;r<s;++r)o[r][1]+=o[r][0]=isNaN(n[r][1])?n[r][0]:n[r][1]}function jt(t){for(var e=t.length,r=new Array(e);--e>=0;)r[e]=e;return r}function Vt(t,e){return t[e]}function Ut(t){var e=t.map(qt);return jt(t).sort(function(t,r){return e[t]-e[r]})}function qt(t){for(var e,r=-1,n=0,a=t.length,i=-1/0;++r<a;)(e=+t[r][1])>i&&(i=e,n=r);return n}function Ht(t){var e=t.map(Gt);return jt(t).sort(function(t,r){return e[t]-e[r]})}function Gt(t){for(var e,r=0,n=-1,a=t.length;++n<a;)(e=+t[n][1])&&(r+=e);return r}Et.prototype={areaStart:st,areaEnd:st,lineStart:function(){this._point=0},lineEnd:function(){this._point&&this._context.closePath()},point:function(t,e){t=+t,e=+e,this._point?this._context.lineTo(t,e):(this._point=1,this._context.moveTo(t,e))}},zt.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._y0=this._y1=this._t0=NaN,this._point=0},lineEnd:function(){switch(this._point){case 2:this._context.lineTo(this._x1,this._y1);break;case 3:Ot(this,this._t0,Pt(this,this._t0))}(this._line||0!==this._line&&1===this._point)&&this._context.closePath(),this._line=1-this._line},point:function(t,e){var r=NaN;if(e=+e,(t=+t)!==this._x1||e!==this._y1){switch(this._point){case 0:this._point=1,this._line?this._context.lineTo(t,e):this._context.moveTo(t,e);break;case 1:this._point=2;break;case 2:this._point=3,Ot(this,Pt(this,r=Ct(this,t,e)),r);break;default:Ot(this,this._t0,r=Ct(this,t,e))}this._x0=this._x1,this._x1=t,this._y0=this._y1,this._y1=e,this._t0=r}}},(It.prototype=Object.create(zt.prototype)).point=function(t,e){zt.prototype.point.call(this,e,t)},Dt.prototype={moveTo:function(t,e){this._context.moveTo(e,t)},closePath:function(){this._context.closePath()},lineTo:function(t,e){this._context.lineTo(e,t)},bezierCurveTo:function(t,e,r,n,a,i){this._context.bezierCurveTo(e,t,n,r,i,a)}},Rt.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x=[],this._y=[]},lineEnd:function(){var t=this._x,e=this._y,r=t.length;if(r)if(this._line?this._context.lineTo(t[0],e[0]):this._context.moveTo(t[0],e[0]),2===r)this._context.lineTo(t[1],e[1]);else for(var n=Ft(t),a=Ft(e),i=0,o=1;o<r;++i,++o)this._context.bezierCurveTo(n[0][i],a[0][i],n[1][i],a[1][i],t[o],e[o]);(this._line||0!==this._line&&1===r)&&this._context.closePath(),this._line=1-this._line,this._x=this._y=null},point:function(t,e){this._x.push(+t),this._y.push(+e)}},Bt.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x=this._y=NaN,this._point=0},lineEnd:function(){0<this._t&&this._t<1&&2===this._point&&this._context.lineTo(this._x,this._y),(this._line||0!==this._line&&1===this._point)&&this._context.closePath(),this._line>=0&&(this._t=1-this._t,this._line=1-this._line)},point:function(t,e){switch(t=+t,e=+e,this._point){case 0:this._point=1,this._line?this._context.lineTo(t,e):this._context.moveTo(t,e);break;case 1:this._point=2;default:if(this._t<=0)this._context.lineTo(this._x,e),this._context.lineTo(t,e);else{var r=this._x*(1-this._t)+t*this._t;this._context.lineTo(r,this._y),this._context.lineTo(r,e)}}this._x=t,this._y=e}},t.arc=function(){var t=g,o=v,_=r(0),w=null,k=m,T=y,M=x,A=null;function S(){var r,g,v,m=+t.apply(this,arguments),y=+o.apply(this,arguments),x=k.apply(this,arguments)-f,S=T.apply(this,arguments)-f,E=n(S-x),L=S>x;if(A||(A=r=e.path()),y<m&&(g=y,y=m,m=g),y>u)if(E>p-u)A.moveTo(y*i(x),y*l(x)),A.arc(0,0,y,x,S,!L),m>u&&(A.moveTo(m*i(S),m*l(S)),A.arc(0,0,m,S,x,L));else{var C,P,O=x,z=S,I=x,D=S,R=E,F=E,B=M.apply(this,arguments)/2,N=B>u&&(w?+w.apply(this,arguments):c(m*m+y*y)),j=s(n(y-m)/2,+_.apply(this,arguments)),V=j,U=j;if(N>u){var q=d(N/m*l(B)),H=d(N/y*l(B));(R-=2*q)>u?(I+=q*=L?1:-1,D-=q):(R=0,I=D=(x+S)/2),(F-=2*H)>u?(O+=H*=L?1:-1,z-=H):(F=0,O=z=(x+S)/2)}var G=y*i(O),Y=y*l(O),W=m*i(D),X=m*l(D);if(j>u){var Z,J=y*i(z),K=y*l(z),Q=m*i(I),$=m*l(I);if(E<h&&(Z=function(t,e,r,n,a,i,o,s){var l=r-t,c=n-e,h=o-a,f=s-i,p=f*l-h*c;if(!(p*p<u))return[t+(p=(h*(e-i)-f*(t-a))/p)*l,e+p*c]}(G,Y,Q,$,J,K,W,X))){var tt=G-Z[0],et=Y-Z[1],rt=J-Z[0],nt=K-Z[1],at=1/l(((v=(tt*rt+et*nt)/(c(tt*tt+et*et)*c(rt*rt+nt*nt)))>1?0:v<-1?h:Math.acos(v))/2),it=c(Z[0]*Z[0]+Z[1]*Z[1]);V=s(j,(m-it)/(at-1)),U=s(j,(y-it)/(at+1))}}F>u?U>u?(C=b(Q,$,G,Y,y,U,L),P=b(J,K,W,X,y,U,L),A.moveTo(C.cx+C.x01,C.cy+C.y01),U<j?A.arc(C.cx,C.cy,U,a(C.y01,C.x01),a(P.y01,P.x01),!L):(A.arc(C.cx,C.cy,U,a(C.y01,C.x01),a(C.y11,C.x11),!L),A.arc(0,0,y,a(C.cy+C.y11,C.cx+C.x11),a(P.cy+P.y11,P.cx+P.x11),!L),A.arc(P.cx,P.cy,U,a(P.y11,P.x11),a(P.y01,P.x01),!L))):(A.moveTo(G,Y),A.arc(0,0,y,O,z,!L)):A.moveTo(G,Y),m>u&&R>u?V>u?(C=b(W,X,J,K,m,-V,L),P=b(G,Y,Q,$,m,-V,L),A.lineTo(C.cx+C.x01,C.cy+C.y01),V<j?A.arc(C.cx,C.cy,V,a(C.y01,C.x01),a(P.y01,P.x01),!L):(A.arc(C.cx,C.cy,V,a(C.y01,C.x01),a(C.y11,C.x11),!L),A.arc(0,0,m,a(C.cy+C.y11,C.cx+C.x11),a(P.cy+P.y11,P.cx+P.x11),L),A.arc(P.cx,P.cy,V,a(P.y11,P.x11),a(P.y01,P.x01),!L))):A.arc(0,0,m,D,I,L):A.lineTo(W,X)}else A.moveTo(0,0);if(A.closePath(),r)return A=null,r+\"\"||null}return S.centroid=function(){var e=(+t.apply(this,arguments)+ +o.apply(this,arguments))/2,r=(+k.apply(this,arguments)+ +T.apply(this,arguments))/2-h/2;return[i(r)*e,l(r)*e]},S.innerRadius=function(e){return arguments.length?(t=\"function\"==typeof e?e:r(+e),S):t},S.outerRadius=function(t){return arguments.length?(o=\"function\"==typeof t?t:r(+t),S):o},S.cornerRadius=function(t){return arguments.length?(_=\"function\"==typeof t?t:r(+t),S):_},S.padRadius=function(t){return arguments.length?(w=null==t?null:\"function\"==typeof t?t:r(+t),S):w},S.startAngle=function(t){return arguments.length?(k=\"function\"==typeof t?t:r(+t),S):k},S.endAngle=function(t){return arguments.length?(T=\"function\"==typeof t?t:r(+t),S):T},S.padAngle=function(t){return arguments.length?(M=\"function\"==typeof t?t:r(+t),S):M},S.context=function(t){return arguments.length?(A=null==t?null:t,S):A},S},t.area=A,t.line=M,t.pie=function(){var t=E,e=S,n=null,a=r(0),i=r(p),o=r(0);function s(r){var s,l,c,u,h,f=r.length,d=0,g=new Array(f),v=new Array(f),m=+a.apply(this,arguments),y=Math.min(p,Math.max(-p,i.apply(this,arguments)-m)),x=Math.min(Math.abs(y)/f,o.apply(this,arguments)),b=x*(y<0?-1:1);for(s=0;s<f;++s)(h=v[g[s]=s]=+t(r[s],s,r))>0&&(d+=h);for(null!=e?g.sort(function(t,r){return e(v[t],v[r])}):null!=n&&g.sort(function(t,e){return n(r[t],r[e])}),s=0,c=d?(y-f*b)/d:0;s<f;++s,m=u)l=g[s],u=m+((h=v[l])>0?h*c:0)+b,v[l]={data:r[l],index:s,value:h,startAngle:m,endAngle:u,padAngle:x};return v}return s.value=function(e){return arguments.length?(t=\"function\"==typeof e?e:r(+e),s):t},s.sortValues=function(t){return arguments.length?(e=t,n=null,s):e},s.sort=function(t){return arguments.length?(n=t,e=null,s):n},s.startAngle=function(t){return arguments.length?(a=\"function\"==typeof t?t:r(+t),s):a},s.endAngle=function(t){return arguments.length?(i=\"function\"==typeof t?t:r(+t),s):i},s.padAngle=function(t){return arguments.length?(o=\"function\"==typeof t?t:r(+t),s):o},s},t.areaRadial=I,t.radialArea=I,t.lineRadial=z,t.radialLine=z,t.pointRadial=D,t.linkHorizontal=function(){return N(j)},t.linkVertical=function(){return N(V)},t.linkRadial=function(){var t=N(U);return t.angle=t.x,delete t.x,t.radius=t.y,delete t.y,t},t.symbol=function(){var t=r(q),n=r(64),a=null;function i(){var r;if(a||(a=r=e.path()),t.apply(this,arguments).draw(a,+n.apply(this,arguments)),r)return a=null,r+\"\"||null}return i.type=function(e){return arguments.length?(t=\"function\"==typeof e?e:r(e),i):t},i.size=function(t){return arguments.length?(n=\"function\"==typeof t?t:r(+t),i):n},i.context=function(t){return arguments.length?(a=null==t?null:t,i):a},i},t.symbols=ot,t.symbolCircle=q,t.symbolCross=H,t.symbolDiamond=W,t.symbolSquare=Q,t.symbolStar=K,t.symbolTriangle=tt,t.symbolWye=it,t.curveBasisClosed=function(t){return new ut(t)},t.curveBasisOpen=function(t){return new ht(t)},t.curveBasis=function(t){return new ct(t)},t.curveBundle=pt,t.curveCardinalClosed=yt,t.curveCardinalOpen=bt,t.curveCardinal=vt,t.curveCatmullRomClosed=Mt,t.curveCatmullRomOpen=St,t.curveCatmullRom=kt,t.curveLinearClosed=function(t){return new Et(t)},t.curveLinear=w,t.curveMonotoneX=function(t){return new zt(t)},t.curveMonotoneY=function(t){return new It(t)},t.curveNatural=function(t){return new Rt(t)},t.curveStep=function(t){return new Bt(t,.5)},t.curveStepAfter=function(t){return new Bt(t,1)},t.curveStepBefore=function(t){return new Bt(t,0)},t.stack=function(){var t=r([]),e=jt,n=Nt,a=Vt;function i(r){var i,o,s=t.apply(this,arguments),l=r.length,c=s.length,u=new Array(c);for(i=0;i<c;++i){for(var h,f=s[i],p=u[i]=new Array(l),d=0;d<l;++d)p[d]=h=[0,+a(r[d],f,d,r)],h.data=r[d];p.key=f}for(i=0,o=e(u);i<c;++i)u[o[i]].index=i;return n(u,o),u}return i.keys=function(e){return arguments.length?(t=\"function\"==typeof e?e:r(R.call(e)),i):t},i.value=function(t){return arguments.length?(a=\"function\"==typeof t?t:r(+t),i):a},i.order=function(t){return arguments.length?(e=null==t?jt:\"function\"==typeof t?t:r(R.call(t)),i):e},i.offset=function(t){return arguments.length?(n=null==t?Nt:t,i):n},i},t.stackOffsetExpand=function(t,e){if((n=t.length)>0){for(var r,n,a,i=0,o=t[0].length;i<o;++i){for(a=r=0;r<n;++r)a+=t[r][i][1]||0;if(a)for(r=0;r<n;++r)t[r][i][1]/=a}Nt(t,e)}},t.stackOffsetDiverging=function(t,e){if((s=t.length)>1)for(var r,n,a,i,o,s,l=0,c=t[e[0]].length;l<c;++l)for(i=o=0,r=0;r<s;++r)(a=(n=t[e[r]][l])[1]-n[0])>=0?(n[0]=i,n[1]=i+=a):a<0?(n[1]=o,n[0]=o+=a):n[0]=i},t.stackOffsetNone=Nt,t.stackOffsetSilhouette=function(t,e){if((r=t.length)>0){for(var r,n=0,a=t[e[0]],i=a.length;n<i;++n){for(var o=0,s=0;o<r;++o)s+=t[o][n][1]||0;a[n][1]+=a[n][0]=-s/2}Nt(t,e)}},t.stackOffsetWiggle=function(t,e){if((a=t.length)>0&&(n=(r=t[e[0]]).length)>0){for(var r,n,a,i=0,o=1;o<n;++o){for(var s=0,l=0,c=0;s<a;++s){for(var u=t[e[s]],h=u[o][1]||0,f=(h-(u[o-1][1]||0))/2,p=0;p<s;++p){var d=t[e[p]];f+=(d[o][1]||0)-(d[o-1][1]||0)}l+=h,c+=f*h}r[o-1][1]+=r[o-1][0]=i,l&&(i-=c/l)}r[o-1][1]+=r[o-1][0]=i,Nt(t,e)}},t.stackOrderAppearance=Ut,t.stackOrderAscending=Ht,t.stackOrderDescending=function(t){return Ht(t).reverse()},t.stackOrderInsideOut=function(t){var e,r,n=t.length,a=t.map(Gt),i=Ut(t),o=0,s=0,l=[],c=[];for(e=0;e<n;++e)r=i[e],o<s?(o+=a[r],l.push(r)):(s+=a[r],c.push(r));return c.reverse().concat(l)},t.stackOrderNone=jt,t.stackOrderReverse=function(t){return jt(t).reverse()},Object.defineProperty(t,\"__esModule\",{value:!0})},\"object\"==typeof r&&\"undefined\"!=typeof e?a(r,t(\"d3-path\")):a(n.d3=n.d3||{},n.d3)},{\"d3-path\":161}],164:[function(t,e,r){var n;n=this,function(t){\"use strict\";var e,r,n=0,a=0,i=0,o=1e3,s=0,l=0,c=0,u=\"object\"==typeof performance&&performance.now?performance:Date,h=\"object\"==typeof window&&window.requestAnimationFrame?window.requestAnimationFrame.bind(window):function(t){setTimeout(t,17)};function f(){return l||(h(p),l=u.now()+c)}function p(){l=0}function d(){this._call=this._time=this._next=null}function g(t,e,r){var n=new d;return n.restart(t,e,r),n}function v(){f(),++n;for(var t,r=e;r;)(t=l-r._time)>=0&&r._call.call(null,t),r=r._next;--n}function m(){l=(s=u.now())+c,n=a=0;try{v()}finally{n=0,function(){var t,n,a=e,i=1/0;for(;a;)a._call?(i>a._time&&(i=a._time),t=a,a=a._next):(n=a._next,a._next=null,a=t?t._next=n:e=n);r=t,x(i)}(),l=0}}function y(){var t=u.now(),e=t-s;e>o&&(c-=e,s=t)}function x(t){n||(a&&(a=clearTimeout(a)),t-l>24?(t<1/0&&(a=setTimeout(m,t-u.now()-c)),i&&(i=clearInterval(i))):(i||(s=u.now(),i=setInterval(y,o)),n=1,h(m)))}d.prototype=g.prototype={constructor:d,restart:function(t,n,a){if(\"function\"!=typeof t)throw new TypeError(\"callback is not a function\");a=(null==a?f():+a)+(null==n?0:+n),this._next||r===this||(r?r._next=this:e=this,r=this),this._call=t,this._time=a,x()},stop:function(){this._call&&(this._call=null,this._time=1/0,x())}},t.now=f,t.timer=g,t.timerFlush=v,t.timeout=function(t,e,r){var n=new d;return e=null==e?0:+e,n.restart(function(r){n.stop(),t(r+e)},e,r),n},t.interval=function(t,e,r){var n=new d,a=e;return null==e?(n.restart(t,e,r),n):(e=+e,r=null==r?f():+r,n.restart(function i(o){o+=a,n.restart(i,a+=e,r),t(o)},e,r),n)},Object.defineProperty(t,\"__esModule\",{value:!0})}(\"object\"==typeof r&&\"undefined\"!=typeof e?r:n.d3=n.d3||{})},{}],165:[function(t,e,r){!function(){var t={version:\"3.5.17\"},r=[].slice,n=function(t){return r.call(t)},a=this.document;function i(t){return t&&(t.ownerDocument||t.document||t).documentElement}function o(t){return t&&(t.ownerDocument&&t.ownerDocument.defaultView||t.document&&t||t.defaultView)}if(a)try{n(a.documentElement.childNodes)[0].nodeType}catch(t){n=function(t){for(var e=t.length,r=new Array(e);e--;)r[e]=t[e];return r}}if(Date.now||(Date.now=function(){return+new Date}),a)try{a.createElement(\"DIV\").style.setProperty(\"opacity\",0,\"\")}catch(t){var s=this.Element.prototype,l=s.setAttribute,c=s.setAttributeNS,u=this.CSSStyleDeclaration.prototype,h=u.setProperty;s.setAttribute=function(t,e){l.call(this,t,e+\"\")},s.setAttributeNS=function(t,e,r){c.call(this,t,e,r+\"\")},u.setProperty=function(t,e,r){h.call(this,t,e+\"\",r)}}function f(t,e){return t<e?-1:t>e?1:t>=e?0:NaN}function p(t){return null===t?NaN:+t}function d(t){return!isNaN(t)}function g(t){return{left:function(e,r,n,a){for(arguments.length<3&&(n=0),arguments.length<4&&(a=e.length);n<a;){var i=n+a>>>1;t(e[i],r)<0?n=i+1:a=i}return n},right:function(e,r,n,a){for(arguments.length<3&&(n=0),arguments.length<4&&(a=e.length);n<a;){var i=n+a>>>1;t(e[i],r)>0?a=i:n=i+1}return n}}}t.ascending=f,t.descending=function(t,e){return e<t?-1:e>t?1:e>=t?0:NaN},t.min=function(t,e){var r,n,a=-1,i=t.length;if(1===arguments.length){for(;++a<i;)if(null!=(n=t[a])&&n>=n){r=n;break}for(;++a<i;)null!=(n=t[a])&&r>n&&(r=n)}else{for(;++a<i;)if(null!=(n=e.call(t,t[a],a))&&n>=n){r=n;break}for(;++a<i;)null!=(n=e.call(t,t[a],a))&&r>n&&(r=n)}return r},t.max=function(t,e){var r,n,a=-1,i=t.length;if(1===arguments.length){for(;++a<i;)if(null!=(n=t[a])&&n>=n){r=n;break}for(;++a<i;)null!=(n=t[a])&&n>r&&(r=n)}else{for(;++a<i;)if(null!=(n=e.call(t,t[a],a))&&n>=n){r=n;break}for(;++a<i;)null!=(n=e.call(t,t[a],a))&&n>r&&(r=n)}return r},t.extent=function(t,e){var r,n,a,i=-1,o=t.length;if(1===arguments.length){for(;++i<o;)if(null!=(n=t[i])&&n>=n){r=a=n;break}for(;++i<o;)null!=(n=t[i])&&(r>n&&(r=n),a<n&&(a=n))}else{for(;++i<o;)if(null!=(n=e.call(t,t[i],i))&&n>=n){r=a=n;break}for(;++i<o;)null!=(n=e.call(t,t[i],i))&&(r>n&&(r=n),a<n&&(a=n))}return[r,a]},t.sum=function(t,e){var r,n=0,a=t.length,i=-1;if(1===arguments.length)for(;++i<a;)d(r=+t[i])&&(n+=r);else for(;++i<a;)d(r=+e.call(t,t[i],i))&&(n+=r);return n},t.mean=function(t,e){var r,n=0,a=t.length,i=-1,o=a;if(1===arguments.length)for(;++i<a;)d(r=p(t[i]))?n+=r:--o;else for(;++i<a;)d(r=p(e.call(t,t[i],i)))?n+=r:--o;if(o)return n/o},t.quantile=function(t,e){var r=(t.length-1)*e+1,n=Math.floor(r),a=+t[n-1],i=r-n;return i?a+i*(t[n]-a):a},t.median=function(e,r){var n,a=[],i=e.length,o=-1;if(1===arguments.length)for(;++o<i;)d(n=p(e[o]))&&a.push(n);else for(;++o<i;)d(n=p(r.call(e,e[o],o)))&&a.push(n);if(a.length)return t.quantile(a.sort(f),.5)},t.variance=function(t,e){var r,n,a=t.length,i=0,o=0,s=-1,l=0;if(1===arguments.length)for(;++s<a;)d(r=p(t[s]))&&(o+=(n=r-i)*(r-(i+=n/++l)));else for(;++s<a;)d(r=p(e.call(t,t[s],s)))&&(o+=(n=r-i)*(r-(i+=n/++l)));if(l>1)return o/(l-1)},t.deviation=function(){var e=t.variance.apply(this,arguments);return e?Math.sqrt(e):e};var v=g(f);function m(t){return t.length}t.bisectLeft=v.left,t.bisect=t.bisectRight=v.right,t.bisector=function(t){return g(1===t.length?function(e,r){return f(t(e),r)}:t)},t.shuffle=function(t,e,r){(i=arguments.length)<3&&(r=t.length,i<2&&(e=0));for(var n,a,i=r-e;i;)a=Math.random()*i--|0,n=t[i+e],t[i+e]=t[a+e],t[a+e]=n;return t},t.permute=function(t,e){for(var r=e.length,n=new Array(r);r--;)n[r]=t[e[r]];return n},t.pairs=function(t){for(var e=0,r=t.length-1,n=t[0],a=new Array(r<0?0:r);e<r;)a[e]=[n,n=t[++e]];return a},t.transpose=function(e){if(!(i=e.length))return[];for(var r=-1,n=t.min(e,m),a=new Array(n);++r<n;)for(var i,o=-1,s=a[r]=new Array(i);++o<i;)s[o]=e[o][r];return a},t.zip=function(){return t.transpose(arguments)},t.keys=function(t){var e=[];for(var r in t)e.push(r);return e},t.values=function(t){var e=[];for(var r in t)e.push(t[r]);return e},t.entries=function(t){var e=[];for(var r in t)e.push({key:r,value:t[r]});return e},t.merge=function(t){for(var e,r,n,a=t.length,i=-1,o=0;++i<a;)o+=t[i].length;for(r=new Array(o);--a>=0;)for(e=(n=t[a]).length;--e>=0;)r[--o]=n[e];return r};var y=Math.abs;function x(t,e){for(var r in e)Object.defineProperty(t.prototype,r,{value:e[r],enumerable:!1})}function b(){this._=Object.create(null)}t.range=function(t,e,r){if(arguments.length<3&&(r=1,arguments.length<2&&(e=t,t=0)),(e-t)/r==1/0)throw new Error(\"infinite range\");var n,a=[],i=function(t){var e=1;for(;t*e%1;)e*=10;return e}(y(r)),o=-1;if(t*=i,e*=i,(r*=i)<0)for(;(n=t+r*++o)>e;)a.push(n/i);else for(;(n=t+r*++o)<e;)a.push(n/i);return a},t.map=function(t,e){var r=new b;if(t instanceof b)t.forEach(function(t,e){r.set(t,e)});else if(Array.isArray(t)){var n,a=-1,i=t.length;if(1===arguments.length)for(;++a<i;)r.set(a,t[a]);else for(;++a<i;)r.set(e.call(t,n=t[a],a),n)}else for(var o in t)r.set(o,t[o]);return r};var _=\"__proto__\",w=\"\\0\";function k(t){return(t+=\"\")===_||t[0]===w?w+t:t}function T(t){return(t+=\"\")[0]===w?t.slice(1):t}function M(t){return k(t)in this._}function A(t){return(t=k(t))in this._&&delete this._[t]}function S(){var t=[];for(var e in this._)t.push(T(e));return t}function E(){var t=0;for(var e in this._)++t;return t}function L(){for(var t in this._)return!1;return!0}function C(){this._=Object.create(null)}function P(t){return t}function O(t,e,r){return function(){var n=r.apply(e,arguments);return n===e?t:n}}function z(t,e){if(e in t)return e;e=e.charAt(0).toUpperCase()+e.slice(1);for(var r=0,n=I.length;r<n;++r){var a=I[r]+e;if(a in t)return a}}x(b,{has:M,get:function(t){return this._[k(t)]},set:function(t,e){return this._[k(t)]=e},remove:A,keys:S,values:function(){var t=[];for(var e in this._)t.push(this._[e]);return t},entries:function(){var t=[];for(var e in this._)t.push({key:T(e),value:this._[e]});return t},size:E,empty:L,forEach:function(t){for(var e in this._)t.call(this,T(e),this._[e])}}),t.nest=function(){var e,r,n={},a=[],i=[];function o(t,i,s){if(s>=a.length)return r?r.call(n,i):e?i.sort(e):i;for(var l,c,u,h,f=-1,p=i.length,d=a[s++],g=new b;++f<p;)(h=g.get(l=d(c=i[f])))?h.push(c):g.set(l,[c]);return t?(c=t(),u=function(e,r){c.set(e,o(t,r,s))}):(c={},u=function(e,r){c[e]=o(t,r,s)}),g.forEach(u),c}return n.map=function(t,e){return o(e,t,0)},n.entries=function(e){return function t(e,r){if(r>=a.length)return e;var n=[],o=i[r++];return e.forEach(function(e,a){n.push({key:e,values:t(a,r)})}),o?n.sort(function(t,e){return o(t.key,e.key)}):n}(o(t.map,e,0),0)},n.key=function(t){return a.push(t),n},n.sortKeys=function(t){return i[a.length-1]=t,n},n.sortValues=function(t){return e=t,n},n.rollup=function(t){return r=t,n},n},t.set=function(t){var e=new C;if(t)for(var r=0,n=t.length;r<n;++r)e.add(t[r]);return e},x(C,{has:M,add:function(t){return this._[k(t+=\"\")]=!0,t},remove:A,values:S,size:E,empty:L,forEach:function(t){for(var e in this._)t.call(this,T(e))}}),t.behavior={},t.rebind=function(t,e){for(var r,n=1,a=arguments.length;++n<a;)t[r=arguments[n]]=O(t,e,e[r]);return t};var I=[\"webkit\",\"ms\",\"moz\",\"Moz\",\"o\",\"O\"];function D(){}function R(){}function F(t){var e=[],r=new b;function n(){for(var r,n=e,a=-1,i=n.length;++a<i;)(r=n[a].on)&&r.apply(this,arguments);return t}return n.on=function(n,a){var i,o=r.get(n);return arguments.length<2?o&&o.on:(o&&(o.on=null,e=e.slice(0,i=e.indexOf(o)).concat(e.slice(i+1)),r.remove(n)),a&&e.push(r.set(n,{on:a})),t)},n}function B(){t.event.preventDefault()}function N(){for(var e,r=t.event;e=r.sourceEvent;)r=e;return r}function j(e){for(var r=new R,n=0,a=arguments.length;++n<a;)r[arguments[n]]=F(r);return r.of=function(n,a){return function(i){try{var o=i.sourceEvent=t.event;i.target=e,t.event=i,r[i.type].apply(n,a)}finally{t.event=o}}},r}t.dispatch=function(){for(var t=new R,e=-1,r=arguments.length;++e<r;)t[arguments[e]]=F(t);return t},R.prototype.on=function(t,e){var r=t.indexOf(\".\"),n=\"\";if(r>=0&&(n=t.slice(r+1),t=t.slice(0,r)),t)return arguments.length<2?this[t].on(n):this[t].on(n,e);if(2===arguments.length){if(null==e)for(t in this)this.hasOwnProperty(t)&&this[t].on(n,null);return this}},t.event=null,t.requote=function(t){return t.replace(V,\"\\\\$&\")};var V=/[\\\\\\^\\$\\*\\+\\?\\|\\[\\]\\(\\)\\.\\{\\}]/g,U={}.__proto__?function(t,e){t.__proto__=e}:function(t,e){for(var r in e)t[r]=e[r]};function q(t){return U(t,W),t}var H=function(t,e){return e.querySelector(t)},G=function(t,e){return e.querySelectorAll(t)},Y=function(t,e){var r=t.matches||t[z(t,\"matchesSelector\")];return(Y=function(t,e){return r.call(t,e)})(t,e)};\"function\"==typeof Sizzle&&(H=function(t,e){return Sizzle(t,e)[0]||null},G=Sizzle,Y=Sizzle.matchesSelector),t.selection=function(){return t.select(a.documentElement)};var W=t.selection.prototype=[];function X(t){return\"function\"==typeof t?t:function(){return H(t,this)}}function Z(t){return\"function\"==typeof t?t:function(){return G(t,this)}}W.select=function(t){var e,r,n,a,i=[];t=X(t);for(var o=-1,s=this.length;++o<s;){i.push(e=[]),e.parentNode=(n=this[o]).parentNode;for(var l=-1,c=n.length;++l<c;)(a=n[l])?(e.push(r=t.call(a,a.__data__,l,o)),r&&\"__data__\"in a&&(r.__data__=a.__data__)):e.push(null)}return q(i)},W.selectAll=function(t){var e,r,a=[];t=Z(t);for(var i=-1,o=this.length;++i<o;)for(var s=this[i],l=-1,c=s.length;++l<c;)(r=s[l])&&(a.push(e=n(t.call(r,r.__data__,l,i))),e.parentNode=r);return q(a)};var J=\"http://www.w3.org/1999/xhtml\",K={svg:\"http://www.w3.org/2000/svg\",xhtml:J,xlink:\"http://www.w3.org/1999/xlink\",xml:\"http://www.w3.org/XML/1998/namespace\",xmlns:\"http://www.w3.org/2000/xmlns/\"};function Q(e,r){return e=t.ns.qualify(e),null==r?e.local?function(){this.removeAttributeNS(e.space,e.local)}:function(){this.removeAttribute(e)}:\"function\"==typeof r?e.local?function(){var t=r.apply(this,arguments);null==t?this.removeAttributeNS(e.space,e.local):this.setAttributeNS(e.space,e.local,t)}:function(){var t=r.apply(this,arguments);null==t?this.removeAttribute(e):this.setAttribute(e,t)}:e.local?function(){this.setAttributeNS(e.space,e.local,r)}:function(){this.setAttribute(e,r)}}function $(t){return t.trim().replace(/\\s+/g,\" \")}function tt(e){return new RegExp(\"(?:^|\\\\s+)\"+t.requote(e)+\"(?:\\\\s+|$)\",\"g\")}function et(t){return(t+\"\").trim().split(/^|\\s+/)}function rt(t,e){var r=(t=et(t).map(nt)).length;return\"function\"==typeof e?function(){for(var n=-1,a=e.apply(this,arguments);++n<r;)t[n](this,a)}:function(){for(var n=-1;++n<r;)t[n](this,e)}}function nt(t){var e=tt(t);return function(r,n){if(a=r.classList)return n?a.add(t):a.remove(t);var a=r.getAttribute(\"class\")||\"\";n?(e.lastIndex=0,e.test(a)||r.setAttribute(\"class\",$(a+\" \"+t))):r.setAttribute(\"class\",$(a.replace(e,\" \")))}}function at(t,e,r){return null==e?function(){this.style.removeProperty(t)}:\"function\"==typeof e?function(){var n=e.apply(this,arguments);null==n?this.style.removeProperty(t):this.style.setProperty(t,n,r)}:function(){this.style.setProperty(t,e,r)}}function it(t,e){return null==e?function(){delete this[t]}:\"function\"==typeof e?function(){var r=e.apply(this,arguments);null==r?delete this[t]:this[t]=r}:function(){this[t]=e}}function ot(e){return\"function\"==typeof e?e:(e=t.ns.qualify(e)).local?function(){return this.ownerDocument.createElementNS(e.space,e.local)}:function(){var t=this.ownerDocument,r=this.namespaceURI;return r===J&&t.documentElement.namespaceURI===J?t.createElement(e):t.createElementNS(r,e)}}function st(){var t=this.parentNode;t&&t.removeChild(this)}function lt(t){return{__data__:t}}function ct(t){return function(){return Y(this,t)}}function ut(t,e){for(var r=0,n=t.length;r<n;r++)for(var a,i=t[r],o=0,s=i.length;o<s;o++)(a=i[o])&&e(a,o,r);return t}function ht(t){return U(t,ft),t}t.ns={prefix:K,qualify:function(t){var e=t.indexOf(\":\"),r=t;return e>=0&&\"xmlns\"!==(r=t.slice(0,e))&&(t=t.slice(e+1)),K.hasOwnProperty(r)?{space:K[r],local:t}:t}},W.attr=function(e,r){if(arguments.length<2){if(\"string\"==typeof e){var n=this.node();return(e=t.ns.qualify(e)).local?n.getAttributeNS(e.space,e.local):n.getAttribute(e)}for(r in e)this.each(Q(r,e[r]));return this}return this.each(Q(e,r))},W.classed=function(t,e){if(arguments.length<2){if(\"string\"==typeof t){var r=this.node(),n=(t=et(t)).length,a=-1;if(e=r.classList){for(;++a<n;)if(!e.contains(t[a]))return!1}else for(e=r.getAttribute(\"class\");++a<n;)if(!tt(t[a]).test(e))return!1;return!0}for(e in t)this.each(rt(e,t[e]));return this}return this.each(rt(t,e))},W.style=function(t,e,r){var n=arguments.length;if(n<3){if(\"string\"!=typeof t){for(r in n<2&&(e=\"\"),t)this.each(at(r,t[r],e));return this}if(n<2){var a=this.node();return o(a).getComputedStyle(a,null).getPropertyValue(t)}r=\"\"}return this.each(at(t,e,r))},W.property=function(t,e){if(arguments.length<2){if(\"string\"==typeof t)return this.node()[t];for(e in t)this.each(it(e,t[e]));return this}return this.each(it(t,e))},W.text=function(t){return arguments.length?this.each(\"function\"==typeof t?function(){var e=t.apply(this,arguments);this.textContent=null==e?\"\":e}:null==t?function(){this.textContent=\"\"}:function(){this.textContent=t}):this.node().textContent},W.html=function(t){return arguments.length?this.each(\"function\"==typeof t?function(){var e=t.apply(this,arguments);this.innerHTML=null==e?\"\":e}:null==t?function(){this.innerHTML=\"\"}:function(){this.innerHTML=t}):this.node().innerHTML},W.append=function(t){return t=ot(t),this.select(function(){return this.appendChild(t.apply(this,arguments))})},W.insert=function(t,e){return t=ot(t),e=X(e),this.select(function(){return this.insertBefore(t.apply(this,arguments),e.apply(this,arguments)||null)})},W.remove=function(){return this.each(st)},W.data=function(t,e){var r,n,a=-1,i=this.length;if(!arguments.length){for(t=new Array(i=(r=this[0]).length);++a<i;)(n=r[a])&&(t[a]=n.__data__);return t}function o(t,r){var n,a,i,o=t.length,u=r.length,h=Math.min(o,u),f=new Array(u),p=new Array(u),d=new Array(o);if(e){var g,v=new b,m=new Array(o);for(n=-1;++n<o;)(a=t[n])&&(v.has(g=e.call(a,a.__data__,n))?d[n]=a:v.set(g,a),m[n]=g);for(n=-1;++n<u;)(a=v.get(g=e.call(r,i=r[n],n)))?!0!==a&&(f[n]=a,a.__data__=i):p[n]=lt(i),v.set(g,!0);for(n=-1;++n<o;)n in m&&!0!==v.get(m[n])&&(d[n]=t[n])}else{for(n=-1;++n<h;)a=t[n],i=r[n],a?(a.__data__=i,f[n]=a):p[n]=lt(i);for(;n<u;++n)p[n]=lt(r[n]);for(;n<o;++n)d[n]=t[n]}p.update=f,p.parentNode=f.parentNode=d.parentNode=t.parentNode,s.push(p),l.push(f),c.push(d)}var s=ht([]),l=q([]),c=q([]);if(\"function\"==typeof t)for(;++a<i;)o(r=this[a],t.call(r,r.parentNode.__data__,a));else for(;++a<i;)o(r=this[a],t);return l.enter=function(){return s},l.exit=function(){return c},l},W.datum=function(t){return arguments.length?this.property(\"__data__\",t):this.property(\"__data__\")},W.filter=function(t){var e,r,n,a=[];\"function\"!=typeof t&&(t=ct(t));for(var i=0,o=this.length;i<o;i++){a.push(e=[]),e.parentNode=(r=this[i]).parentNode;for(var s=0,l=r.length;s<l;s++)(n=r[s])&&t.call(n,n.__data__,s,i)&&e.push(n)}return q(a)},W.order=function(){for(var t=-1,e=this.length;++t<e;)for(var r,n=this[t],a=n.length-1,i=n[a];--a>=0;)(r=n[a])&&(i&&i!==r.nextSibling&&i.parentNode.insertBefore(r,i),i=r);return this},W.sort=function(t){t=function(t){arguments.length||(t=f);return function(e,r){return e&&r?t(e.__data__,r.__data__):!e-!r}}.apply(this,arguments);for(var e=-1,r=this.length;++e<r;)this[e].sort(t);return this.order()},W.each=function(t){return ut(this,function(e,r,n){t.call(e,e.__data__,r,n)})},W.call=function(t){var e=n(arguments);return t.apply(e[0]=this,e),this},W.empty=function(){return!this.node()},W.node=function(){for(var t=0,e=this.length;t<e;t++)for(var r=this[t],n=0,a=r.length;n<a;n++){var i=r[n];if(i)return i}return null},W.size=function(){var t=0;return ut(this,function(){++t}),t};var ft=[];function pt(e,r,a){var i=\"__on\"+e,o=e.indexOf(\".\"),s=gt;o>0&&(e=e.slice(0,o));var l=dt.get(e);function c(){var t=this[i];t&&(this.removeEventListener(e,t,t.$),delete this[i])}return l&&(e=l,s=vt),o?r?function(){var t=s(r,n(arguments));c.call(this),this.addEventListener(e,this[i]=t,t.$=a),t._=r}:c:r?D:function(){var r,n=new RegExp(\"^__on([^.]+)\"+t.requote(e)+\"$\");for(var a in this)if(r=a.match(n)){var i=this[a];this.removeEventListener(r[1],i,i.$),delete this[a]}}}t.selection.enter=ht,t.selection.enter.prototype=ft,ft.append=W.append,ft.empty=W.empty,ft.node=W.node,ft.call=W.call,ft.size=W.size,ft.select=function(t){for(var e,r,n,a,i,o=[],s=-1,l=this.length;++s<l;){n=(a=this[s]).update,o.push(e=[]),e.parentNode=a.parentNode;for(var c=-1,u=a.length;++c<u;)(i=a[c])?(e.push(n[c]=r=t.call(a.parentNode,i.__data__,c,s)),r.__data__=i.__data__):e.push(null)}return q(o)},ft.insert=function(t,e){var r,n,a;return arguments.length<2&&(r=this,e=function(t,e,i){var o,s=r[i].update,l=s.length;for(i!=a&&(a=i,n=0),e>=n&&(n=e+1);!(o=s[n])&&++n<l;);return o}),W.insert.call(this,t,e)},t.select=function(t){var e;return\"string\"==typeof t?(e=[H(t,a)]).parentNode=a.documentElement:(e=[t]).parentNode=i(t),q([e])},t.selectAll=function(t){var e;return\"string\"==typeof t?(e=n(G(t,a))).parentNode=a.documentElement:(e=n(t)).parentNode=null,q([e])},W.on=function(t,e,r){var n=arguments.length;if(n<3){if(\"string\"!=typeof t){for(r in n<2&&(e=!1),t)this.each(pt(r,t[r],e));return this}if(n<2)return(n=this.node()[\"__on\"+t])&&n._;r=!1}return this.each(pt(t,e,r))};var dt=t.map({mouseenter:\"mouseover\",mouseleave:\"mouseout\"});function gt(e,r){return function(n){var a=t.event;t.event=n,r[0]=this.__data__;try{e.apply(this,r)}finally{t.event=a}}}function vt(t,e){var r=gt(t,e);return function(t){var e=t.relatedTarget;e&&(e===this||8&e.compareDocumentPosition(this))||r.call(this,t)}}a&&dt.forEach(function(t){\"on\"+t in a&&dt.remove(t)});var mt,yt=0;function xt(e){var r=\".dragsuppress-\"+ ++yt,n=\"click\"+r,a=t.select(o(e)).on(\"touchmove\"+r,B).on(\"dragstart\"+r,B).on(\"selectstart\"+r,B);if(null==mt&&(mt=!(\"onselectstart\"in e)&&z(e.style,\"userSelect\")),mt){var s=i(e).style,l=s[mt];s[mt]=\"none\"}return function(t){if(a.on(r,null),mt&&(s[mt]=l),t){var e=function(){a.on(n,null)};a.on(n,function(){B(),e()},!0),setTimeout(e,0)}}}t.mouse=function(t){return _t(t,N())};var bt=this.navigator&&/WebKit/.test(this.navigator.userAgent)?-1:0;function _t(e,r){r.changedTouches&&(r=r.changedTouches[0]);var n=e.ownerSVGElement||e;if(n.createSVGPoint){var a=n.createSVGPoint();if(bt<0){var i=o(e);if(i.scrollX||i.scrollY){var s=(n=t.select(\"body\").append(\"svg\").style({position:\"absolute\",top:0,left:0,margin:0,padding:0,border:\"none\"},\"important\"))[0][0].getScreenCTM();bt=!(s.f||s.e),n.remove()}}return bt?(a.x=r.pageX,a.y=r.pageY):(a.x=r.clientX,a.y=r.clientY),[(a=a.matrixTransform(e.getScreenCTM().inverse())).x,a.y]}var l=e.getBoundingClientRect();return[r.clientX-l.left-e.clientLeft,r.clientY-l.top-e.clientTop]}function wt(){return t.event.changedTouches[0].identifier}t.touch=function(t,e,r){if(arguments.length<3&&(r=e,e=N().changedTouches),e)for(var n,a=0,i=e.length;a<i;++a)if((n=e[a]).identifier===r)return _t(t,n)},t.behavior.drag=function(){var e=j(i,\"drag\",\"dragstart\",\"dragend\"),r=null,n=s(D,t.mouse,o,\"mousemove\",\"mouseup\"),a=s(wt,t.touch,P,\"touchmove\",\"touchend\");function i(){this.on(\"mousedown.drag\",n).on(\"touchstart.drag\",a)}function s(n,a,i,o,s){return function(){var l,c=t.event.target.correspondingElement||t.event.target,u=this.parentNode,h=e.of(this,arguments),f=0,p=n(),d=\".drag\"+(null==p?\"\":\"-\"+p),g=t.select(i(c)).on(o+d,function(){var t,e,r=a(u,p);if(!r)return;t=r[0]-m[0],e=r[1]-m[1],f|=t|e,m=r,h({type:\"drag\",x:r[0]+l[0],y:r[1]+l[1],dx:t,dy:e})}).on(s+d,function(){if(!a(u,p))return;g.on(o+d,null).on(s+d,null),v(f),h({type:\"dragend\"})}),v=xt(c),m=a(u,p);l=r?[(l=r.apply(this,arguments)).x-m[0],l.y-m[1]]:[0,0],h({type:\"dragstart\"})}}return i.origin=function(t){return arguments.length?(r=t,i):r},t.rebind(i,e,\"on\")},t.touches=function(t,e){return arguments.length<2&&(e=N().touches),e?n(e).map(function(e){var r=_t(t,e);return r.identifier=e.identifier,r}):[]};var kt=1e-6,Tt=kt*kt,Mt=Math.PI,At=2*Mt,St=At-kt,Et=Mt/2,Lt=Mt/180,Ct=180/Mt;function Pt(t){return t>0?1:t<0?-1:0}function Ot(t,e,r){return(e[0]-t[0])*(r[1]-t[1])-(e[1]-t[1])*(r[0]-t[0])}function zt(t){return t>1?0:t<-1?Mt:Math.acos(t)}function It(t){return t>1?Et:t<-1?-Et:Math.asin(t)}function Dt(t){return((t=Math.exp(t))+1/t)/2}function Rt(t){return(t=Math.sin(t/2))*t}var Ft=Math.SQRT2;t.interpolateZoom=function(t,e){var r,n,a=t[0],i=t[1],o=t[2],s=e[0],l=e[1],c=e[2],u=s-a,h=l-i,f=u*u+h*h;if(f<Tt)n=Math.log(c/o)/Ft,r=function(t){return[a+t*u,i+t*h,o*Math.exp(Ft*t*n)]};else{var p=Math.sqrt(f),d=(c*c-o*o+4*f)/(2*o*2*p),g=(c*c-o*o-4*f)/(2*c*2*p),v=Math.log(Math.sqrt(d*d+1)-d),m=Math.log(Math.sqrt(g*g+1)-g);n=(m-v)/Ft,r=function(t){var e,r=t*n,s=Dt(v),l=o/(2*p)*(s*(e=Ft*r+v,((e=Math.exp(2*e))-1)/(e+1))-function(t){return((t=Math.exp(t))-1/t)/2}(v));return[a+l*u,i+l*h,o*s/Dt(Ft*r+v)]}}return r.duration=1e3*n,r},t.behavior.zoom=function(){var e,r,n,i,s,l,c,u,h,f={x:0,y:0,k:1},p=[960,500],d=jt,g=250,v=0,m=\"mousedown.zoom\",y=\"mousemove.zoom\",x=\"mouseup.zoom\",b=\"touchstart.zoom\",_=j(w,\"zoomstart\",\"zoom\",\"zoomend\");function w(t){t.on(m,P).on(Nt+\".zoom\",z).on(\"dblclick.zoom\",I).on(b,O)}function k(t){return[(t[0]-f.x)/f.k,(t[1]-f.y)/f.k]}function T(t){f.k=Math.max(d[0],Math.min(d[1],t))}function M(t,e){e=function(t){return[t[0]*f.k+f.x,t[1]*f.k+f.y]}(e),f.x+=t[0]-e[0],f.y+=t[1]-e[1]}function A(e,n,a,i){e.__chart__={x:f.x,y:f.y,k:f.k},T(Math.pow(2,i)),M(r=n,a),e=t.select(e),g>0&&(e=e.transition().duration(g)),e.call(w.event)}function S(){c&&c.domain(l.range().map(function(t){return(t-f.x)/f.k}).map(l.invert)),h&&h.domain(u.range().map(function(t){return(t-f.y)/f.k}).map(u.invert))}function E(t){v++||t({type:\"zoomstart\"})}function L(t){S(),t({type:\"zoom\",scale:f.k,translate:[f.x,f.y]})}function C(t){--v||(t({type:\"zoomend\"}),r=null)}function P(){var e=this,r=_.of(e,arguments),n=0,a=t.select(o(e)).on(y,function(){n=1,M(t.mouse(e),i),L(r)}).on(x,function(){a.on(y,null).on(x,null),s(n),C(r)}),i=k(t.mouse(e)),s=xt(e);ps.call(e),E(r)}function O(){var e,r=this,n=_.of(r,arguments),a={},i=0,o=\".zoom-\"+t.event.changedTouches[0].identifier,l=\"touchmove\"+o,c=\"touchend\"+o,u=[],h=t.select(r),p=xt(r);function d(){var n=t.touches(r);return e=f.k,n.forEach(function(t){t.identifier in a&&(a[t.identifier]=k(t))}),n}function g(){var e=t.event.target;t.select(e).on(l,v).on(c,y),u.push(e);for(var n=t.event.changedTouches,o=0,h=n.length;o<h;++o)a[n[o].identifier]=null;var p=d(),g=Date.now();if(1===p.length){if(g-s<500){var m=p[0];A(r,m,a[m.identifier],Math.floor(Math.log(f.k)/Math.LN2)+1),B()}s=g}else if(p.length>1){m=p[0];var x=p[1],b=m[0]-x[0],_=m[1]-x[1];i=b*b+_*_}}function v(){var o,l,c,u,h=t.touches(r);ps.call(r);for(var f=0,p=h.length;f<p;++f,u=null)if(c=h[f],u=a[c.identifier]){if(l)break;o=c,l=u}if(u){var d=(d=c[0]-o[0])*d+(d=c[1]-o[1])*d,g=i&&Math.sqrt(d/i);o=[(o[0]+c[0])/2,(o[1]+c[1])/2],l=[(l[0]+u[0])/2,(l[1]+u[1])/2],T(g*e)}s=null,M(o,l),L(n)}function y(){if(t.event.touches.length){for(var e=t.event.changedTouches,r=0,i=e.length;r<i;++r)delete a[e[r].identifier];for(var s in a)return void d()}t.selectAll(u).on(o,null),h.on(m,P).on(b,O),p(),C(n)}g(),E(n),h.on(m,null).on(b,g)}function z(){var a=_.of(this,arguments);i?clearTimeout(i):(ps.call(this),e=k(r=n||t.mouse(this)),E(a)),i=setTimeout(function(){i=null,C(a)},50),B(),T(Math.pow(2,.002*Bt())*f.k),M(r,e),L(a)}function I(){var e=t.mouse(this),r=Math.log(f.k)/Math.LN2;A(this,e,k(e),t.event.shiftKey?Math.ceil(r)-1:Math.floor(r)+1)}return Nt||(Nt=\"onwheel\"in a?(Bt=function(){return-t.event.deltaY*(t.event.deltaMode?120:1)},\"wheel\"):\"onmousewheel\"in a?(Bt=function(){return t.event.wheelDelta},\"mousewheel\"):(Bt=function(){return-t.event.detail},\"MozMousePixelScroll\")),w.event=function(e){e.each(function(){var e=_.of(this,arguments),n=f;vs?t.select(this).transition().each(\"start.zoom\",function(){f=this.__chart__||{x:0,y:0,k:1},E(e)}).tween(\"zoom:zoom\",function(){var a=p[0],i=p[1],o=r?r[0]:a/2,s=r?r[1]:i/2,l=t.interpolateZoom([(o-f.x)/f.k,(s-f.y)/f.k,a/f.k],[(o-n.x)/n.k,(s-n.y)/n.k,a/n.k]);return function(t){var r=l(t),n=a/r[2];this.__chart__=f={x:o-r[0]*n,y:s-r[1]*n,k:n},L(e)}}).each(\"interrupt.zoom\",function(){C(e)}).each(\"end.zoom\",function(){C(e)}):(this.__chart__=f,E(e),L(e),C(e))})},w.translate=function(t){return arguments.length?(f={x:+t[0],y:+t[1],k:f.k},S(),w):[f.x,f.y]},w.scale=function(t){return arguments.length?(f={x:f.x,y:f.y,k:null},T(+t),S(),w):f.k},w.scaleExtent=function(t){return arguments.length?(d=null==t?jt:[+t[0],+t[1]],w):d},w.center=function(t){return arguments.length?(n=t&&[+t[0],+t[1]],w):n},w.size=function(t){return arguments.length?(p=t&&[+t[0],+t[1]],w):p},w.duration=function(t){return arguments.length?(g=+t,w):g},w.x=function(t){return arguments.length?(c=t,l=t.copy(),f={x:0,y:0,k:1},w):c},w.y=function(t){return arguments.length?(h=t,u=t.copy(),f={x:0,y:0,k:1},w):h},t.rebind(w,_,\"on\")};var Bt,Nt,jt=[0,1/0];function Vt(){}function Ut(t,e,r){return this instanceof Ut?(this.h=+t,this.s=+e,void(this.l=+r)):arguments.length<2?t instanceof Ut?new Ut(t.h,t.s,t.l):ue(\"\"+t,he,Ut):new Ut(t,e,r)}t.color=Vt,Vt.prototype.toString=function(){return this.rgb()+\"\"},t.hsl=Ut;var qt=Ut.prototype=new Vt;function Ht(t,e,r){var n,a;function i(t){return Math.round(255*function(t){return t>360?t-=360:t<0&&(t+=360),t<60?n+(a-n)*t/60:t<180?a:t<240?n+(a-n)*(240-t)/60:n}(t))}return t=isNaN(t)?0:(t%=360)<0?t+360:t,e=isNaN(e)?0:e<0?0:e>1?1:e,n=2*(r=r<0?0:r>1?1:r)-(a=r<=.5?r*(1+e):r+e-r*e),new ie(i(t+120),i(t),i(t-120))}function Gt(e,r,n){return this instanceof Gt?(this.h=+e,this.c=+r,void(this.l=+n)):arguments.length<2?e instanceof Gt?new Gt(e.h,e.c,e.l):ee(e instanceof Xt?e.l:(e=fe((e=t.rgb(e)).r,e.g,e.b)).l,e.a,e.b):new Gt(e,r,n)}qt.brighter=function(t){return t=Math.pow(.7,arguments.length?t:1),new Ut(this.h,this.s,this.l/t)},qt.darker=function(t){return t=Math.pow(.7,arguments.length?t:1),new Ut(this.h,this.s,t*this.l)},qt.rgb=function(){return Ht(this.h,this.s,this.l)},t.hcl=Gt;var Yt=Gt.prototype=new Vt;function Wt(t,e,r){return isNaN(t)&&(t=0),isNaN(e)&&(e=0),new Xt(r,Math.cos(t*=Lt)*e,Math.sin(t)*e)}function Xt(t,e,r){return this instanceof Xt?(this.l=+t,this.a=+e,void(this.b=+r)):arguments.length<2?t instanceof Xt?new Xt(t.l,t.a,t.b):t instanceof Gt?Wt(t.h,t.c,t.l):fe((t=ie(t)).r,t.g,t.b):new Xt(t,e,r)}Yt.brighter=function(t){return new Gt(this.h,this.c,Math.min(100,this.l+Zt*(arguments.length?t:1)))},Yt.darker=function(t){return new Gt(this.h,this.c,Math.max(0,this.l-Zt*(arguments.length?t:1)))},Yt.rgb=function(){return Wt(this.h,this.c,this.l).rgb()},t.lab=Xt;var Zt=18,Jt=.95047,Kt=1,Qt=1.08883,$t=Xt.prototype=new Vt;function te(t,e,r){var n=(t+16)/116,a=n+e/500,i=n-r/200;return new ie(ae(3.2404542*(a=re(a)*Jt)-1.5371385*(n=re(n)*Kt)-.4985314*(i=re(i)*Qt)),ae(-.969266*a+1.8760108*n+.041556*i),ae(.0556434*a-.2040259*n+1.0572252*i))}function ee(t,e,r){return t>0?new Gt(Math.atan2(r,e)*Ct,Math.sqrt(e*e+r*r),t):new Gt(NaN,NaN,t)}function re(t){return t>.206893034?t*t*t:(t-4/29)/7.787037}function ne(t){return t>.008856?Math.pow(t,1/3):7.787037*t+4/29}function ae(t){return Math.round(255*(t<=.00304?12.92*t:1.055*Math.pow(t,1/2.4)-.055))}function ie(t,e,r){return this instanceof ie?(this.r=~~t,this.g=~~e,void(this.b=~~r)):arguments.length<2?t instanceof ie?new ie(t.r,t.g,t.b):ue(\"\"+t,ie,Ht):new ie(t,e,r)}function oe(t){return new ie(t>>16,t>>8&255,255&t)}function se(t){return oe(t)+\"\"}$t.brighter=function(t){return new Xt(Math.min(100,this.l+Zt*(arguments.length?t:1)),this.a,this.b)},$t.darker=function(t){return new Xt(Math.max(0,this.l-Zt*(arguments.length?t:1)),this.a,this.b)},$t.rgb=function(){return te(this.l,this.a,this.b)},t.rgb=ie;var le=ie.prototype=new Vt;function ce(t){return t<16?\"0\"+Math.max(0,t).toString(16):Math.min(255,t).toString(16)}function ue(t,e,r){var n,a,i,o=0,s=0,l=0;if(n=/([a-z]+)\\((.*)\\)/.exec(t=t.toLowerCase()))switch(a=n[2].split(\",\"),n[1]){case\"hsl\":return r(parseFloat(a[0]),parseFloat(a[1])/100,parseFloat(a[2])/100);case\"rgb\":return e(de(a[0]),de(a[1]),de(a[2]))}return(i=ge.get(t))?e(i.r,i.g,i.b):(null==t||\"#\"!==t.charAt(0)||isNaN(i=parseInt(t.slice(1),16))||(4===t.length?(o=(3840&i)>>4,o|=o>>4,s=240&i,s|=s>>4,l=15&i,l|=l<<4):7===t.length&&(o=(16711680&i)>>16,s=(65280&i)>>8,l=255&i)),e(o,s,l))}function he(t,e,r){var n,a,i=Math.min(t/=255,e/=255,r/=255),o=Math.max(t,e,r),s=o-i,l=(o+i)/2;return s?(a=l<.5?s/(o+i):s/(2-o-i),n=t==o?(e-r)/s+(e<r?6:0):e==o?(r-t)/s+2:(t-e)/s+4,n*=60):(n=NaN,a=l>0&&l<1?0:n),new Ut(n,a,l)}function fe(t,e,r){var n=ne((.4124564*(t=pe(t))+.3575761*(e=pe(e))+.1804375*(r=pe(r)))/Jt),a=ne((.2126729*t+.7151522*e+.072175*r)/Kt);return Xt(116*a-16,500*(n-a),200*(a-ne((.0193339*t+.119192*e+.9503041*r)/Qt)))}function pe(t){return(t/=255)<=.04045?t/12.92:Math.pow((t+.055)/1.055,2.4)}function de(t){var e=parseFloat(t);return\"%\"===t.charAt(t.length-1)?Math.round(2.55*e):e}le.brighter=function(t){t=Math.pow(.7,arguments.length?t:1);var e=this.r,r=this.g,n=this.b,a=30;return e||r||n?(e&&e<a&&(e=a),r&&r<a&&(r=a),n&&n<a&&(n=a),new ie(Math.min(255,e/t),Math.min(255,r/t),Math.min(255,n/t))):new ie(a,a,a)},le.darker=function(t){return new ie((t=Math.pow(.7,arguments.length?t:1))*this.r,t*this.g,t*this.b)},le.hsl=function(){return he(this.r,this.g,this.b)},le.toString=function(){return\"#\"+ce(this.r)+ce(this.g)+ce(this.b)};var ge=t.map({aliceblue:15792383,antiquewhite:16444375,aqua:65535,aquamarine:8388564,azure:15794175,beige:16119260,bisque:16770244,black:0,blanchedalmond:16772045,blue:255,blueviolet:9055202,brown:10824234,burlywood:14596231,cadetblue:6266528,chartreuse:8388352,chocolate:13789470,coral:16744272,cornflowerblue:6591981,cornsilk:16775388,crimson:14423100,cyan:65535,darkblue:139,darkcyan:35723,darkgoldenrod:12092939,darkgray:11119017,darkgreen:25600,darkgrey:11119017,darkkhaki:12433259,darkmagenta:9109643,darkolivegreen:5597999,darkorange:16747520,darkorchid:10040012,darkred:9109504,darksalmon:15308410,darkseagreen:9419919,darkslateblue:4734347,darkslategray:3100495,darkslategrey:3100495,darkturquoise:52945,darkviolet:9699539,deeppink:16716947,deepskyblue:49151,dimgray:6908265,dimgrey:6908265,dodgerblue:2003199,firebrick:11674146,floralwhite:16775920,forestgreen:2263842,fuchsia:16711935,gainsboro:14474460,ghostwhite:16316671,gold:16766720,goldenrod:14329120,gray:8421504,green:32768,greenyellow:11403055,grey:8421504,honeydew:15794160,hotpink:16738740,indianred:13458524,indigo:4915330,ivory:16777200,khaki:15787660,lavender:15132410,lavenderblush:16773365,lawngreen:8190976,lemonchiffon:16775885,lightblue:11393254,lightcoral:15761536,lightcyan:14745599,lightgoldenrodyellow:16448210,lightgray:13882323,lightgreen:9498256,lightgrey:13882323,lightpink:16758465,lightsalmon:16752762,lightseagreen:2142890,lightskyblue:8900346,lightslategray:7833753,lightslategrey:7833753,lightsteelblue:11584734,lightyellow:16777184,lime:65280,limegreen:3329330,linen:16445670,magenta:16711935,maroon:8388608,mediumaquamarine:6737322,mediumblue:205,mediumorchid:12211667,mediumpurple:9662683,mediumseagreen:3978097,mediumslateblue:8087790,mediumspringgreen:64154,mediumturquoise:4772300,mediumvioletred:13047173,midnightblue:1644912,mintcream:16121850,mistyrose:16770273,moccasin:16770229,navajowhite:16768685,navy:128,oldlace:16643558,olive:8421376,olivedrab:7048739,orange:16753920,orangered:16729344,orchid:14315734,palegoldenrod:15657130,palegreen:10025880,paleturquoise:11529966,palevioletred:14381203,papayawhip:16773077,peachpuff:16767673,peru:13468991,pink:16761035,plum:14524637,powderblue:11591910,purple:8388736,rebeccapurple:6697881,red:16711680,rosybrown:12357519,royalblue:4286945,saddlebrown:9127187,salmon:16416882,sandybrown:16032864,seagreen:3050327,seashell:16774638,sienna:10506797,silver:12632256,skyblue:8900331,slateblue:6970061,slategray:7372944,slategrey:7372944,snow:16775930,springgreen:65407,steelblue:4620980,tan:13808780,teal:32896,thistle:14204888,tomato:16737095,turquoise:4251856,violet:15631086,wheat:16113331,white:16777215,whitesmoke:16119285,yellow:16776960,yellowgreen:10145074});function ve(t){return\"function\"==typeof t?t:function(){return t}}function me(t){return function(e,r,n){return 2===arguments.length&&\"function\"==typeof r&&(n=r,r=null),ye(e,r,t,n)}}function ye(e,r,a,i){var o={},s=t.dispatch(\"beforesend\",\"progress\",\"load\",\"error\"),l={},c=new XMLHttpRequest,u=null;function h(){var t,e=c.status;if(!e&&function(t){var e=t.responseType;return e&&\"text\"!==e?t.response:t.responseText}(c)||e>=200&&e<300||304===e){try{t=a.call(o,c)}catch(t){return void s.error.call(o,t)}s.load.call(o,t)}else s.error.call(o,c)}return!this.XDomainRequest||\"withCredentials\"in c||!/^(http(s)?:)?\\/\\//.test(e)||(c=new XDomainRequest),\"onload\"in c?c.onload=c.onerror=h:c.onreadystatechange=function(){c.readyState>3&&h()},c.onprogress=function(e){var r=t.event;t.event=e;try{s.progress.call(o,c)}finally{t.event=r}},o.header=function(t,e){return t=(t+\"\").toLowerCase(),arguments.length<2?l[t]:(null==e?delete l[t]:l[t]=e+\"\",o)},o.mimeType=function(t){return arguments.length?(r=null==t?null:t+\"\",o):r},o.responseType=function(t){return arguments.length?(u=t,o):u},o.response=function(t){return a=t,o},[\"get\",\"post\"].forEach(function(t){o[t]=function(){return o.send.apply(o,[t].concat(n(arguments)))}}),o.send=function(t,n,a){if(2===arguments.length&&\"function\"==typeof n&&(a=n,n=null),c.open(t,e,!0),null==r||\"accept\"in l||(l.accept=r+\",*/*\"),c.setRequestHeader)for(var i in l)c.setRequestHeader(i,l[i]);return null!=r&&c.overrideMimeType&&c.overrideMimeType(r),null!=u&&(c.responseType=u),null!=a&&o.on(\"error\",a).on(\"load\",function(t){a(null,t)}),s.beforesend.call(o,c),c.send(null==n?null:n),o},o.abort=function(){return c.abort(),o},t.rebind(o,s,\"on\"),null==i?o:o.get(function(t){return 1===t.length?function(e,r){t(null==e?r:null)}:t}(i))}ge.forEach(function(t,e){ge.set(t,oe(e))}),t.functor=ve,t.xhr=me(P),t.dsv=function(t,e){var r=new RegExp('[\"'+t+\"\\n]\"),n=t.charCodeAt(0);function a(t,r,n){arguments.length<3&&(n=r,r=null);var a=ye(t,e,null==r?i:o(r),n);return a.row=function(t){return arguments.length?a.response(null==(r=t)?i:o(t)):r},a}function i(t){return a.parse(t.responseText)}function o(t){return function(e){return a.parse(e.responseText,t)}}function s(e){return e.map(l).join(t)}function l(t){return r.test(t)?'\"'+t.replace(/\\\"/g,'\"\"')+'\"':t}return a.parse=function(t,e){var r;return a.parseRows(t,function(t,n){if(r)return r(t,n-1);var a=new Function(\"d\",\"return {\"+t.map(function(t,e){return JSON.stringify(t)+\": d[\"+e+\"]\"}).join(\",\")+\"}\");r=e?function(t,r){return e(a(t),r)}:a})},a.parseRows=function(t,e){var r,a,i={},o={},s=[],l=t.length,c=0,u=0;function h(){if(c>=l)return o;if(a)return a=!1,i;var e=c;if(34===t.charCodeAt(e)){for(var r=e;r++<l;)if(34===t.charCodeAt(r)){if(34!==t.charCodeAt(r+1))break;++r}return c=r+2,13===(s=t.charCodeAt(r+1))?(a=!0,10===t.charCodeAt(r+2)&&++c):10===s&&(a=!0),t.slice(e+1,r).replace(/\"\"/g,'\"')}for(;c<l;){var s,u=1;if(10===(s=t.charCodeAt(c++)))a=!0;else if(13===s)a=!0,10===t.charCodeAt(c)&&(++c,++u);else if(s!==n)continue;return t.slice(e,c-u)}return t.slice(e)}for(;(r=h())!==o;){for(var f=[];r!==i&&r!==o;)f.push(r),r=h();e&&null==(f=e(f,u++))||s.push(f)}return s},a.format=function(e){if(Array.isArray(e[0]))return a.formatRows(e);var r=new C,n=[];return e.forEach(function(t){for(var e in t)r.has(e)||n.push(r.add(e))}),[n.map(l).join(t)].concat(e.map(function(e){return n.map(function(t){return l(e[t])}).join(t)})).join(\"\\n\")},a.formatRows=function(t){return t.map(s).join(\"\\n\")},a},t.csv=t.dsv(\",\",\"text/csv\"),t.tsv=t.dsv(\"\\t\",\"text/tab-separated-values\");var xe,be,_e,we,ke=this[z(this,\"requestAnimationFrame\")]||function(t){setTimeout(t,17)};function Te(t,e,r){var n=arguments.length;n<2&&(e=0),n<3&&(r=Date.now());var a={c:t,t:r+e,n:null};return be?be.n=a:xe=a,be=a,_e||(we=clearTimeout(we),_e=1,ke(Me)),a}function Me(){var t=Ae(),e=Se()-t;e>24?(isFinite(e)&&(clearTimeout(we),we=setTimeout(Me,e)),_e=0):(_e=1,ke(Me))}function Ae(){for(var t=Date.now(),e=xe;e;)t>=e.t&&e.c(t-e.t)&&(e.c=null),e=e.n;return t}function Se(){for(var t,e=xe,r=1/0;e;)e.c?(e.t<r&&(r=e.t),e=(t=e).n):e=t?t.n=e.n:xe=e.n;return be=t,r}function Ee(t,e){return e-(t?Math.ceil(Math.log(t)/Math.LN10):1)}t.timer=function(){Te.apply(this,arguments)},t.timer.flush=function(){Ae(),Se()},t.round=function(t,e){return e?Math.round(t*(e=Math.pow(10,e)))/e:Math.round(t)};var Le=[\"y\",\"z\",\"a\",\"f\",\"p\",\"n\",\"\\xb5\",\"m\",\"\",\"k\",\"M\",\"G\",\"T\",\"P\",\"E\",\"Z\",\"Y\"].map(function(t,e){var r=Math.pow(10,3*y(8-e));return{scale:e>8?function(t){return t/r}:function(t){return t*r},symbol:t}});function Ce(e){var r=e.decimal,n=e.thousands,a=e.grouping,i=e.currency,o=a&&n?function(t,e){for(var r=t.length,i=[],o=0,s=a[0],l=0;r>0&&s>0&&(l+s+1>e&&(s=Math.max(1,e-l)),i.push(t.substring(r-=s,r+s)),!((l+=s+1)>e));)s=a[o=(o+1)%a.length];return i.reverse().join(n)}:P;return function(e){var n=Pe.exec(e),a=n[1]||\" \",s=n[2]||\">\",l=n[3]||\"-\",c=n[4]||\"\",u=n[5],h=+n[6],f=n[7],p=n[8],d=n[9],g=1,v=\"\",m=\"\",y=!1,x=!0;switch(p&&(p=+p.substring(1)),(u||\"0\"===a&&\"=\"===s)&&(u=a=\"0\",s=\"=\"),d){case\"n\":f=!0,d=\"g\";break;case\"%\":g=100,m=\"%\",d=\"f\";break;case\"p\":g=100,m=\"%\",d=\"r\";break;case\"b\":case\"o\":case\"x\":case\"X\":\"#\"===c&&(v=\"0\"+d.toLowerCase());case\"c\":x=!1;case\"d\":y=!0,p=0;break;case\"s\":g=-1,d=\"r\"}\"$\"===c&&(v=i[0],m=i[1]),\"r\"!=d||p||(d=\"g\"),null!=p&&(\"g\"==d?p=Math.max(1,Math.min(21,p)):\"e\"!=d&&\"f\"!=d||(p=Math.max(0,Math.min(20,p)))),d=Oe.get(d)||ze;var b=u&&f;return function(e){var n=m;if(y&&e%1)return\"\";var i=e<0||0===e&&1/e<0?(e=-e,\"-\"):\"-\"===l?\"\":l;if(g<0){var c=t.formatPrefix(e,p);e=c.scale(e),n=c.symbol+m}else e*=g;var _,w,k=(e=d(e,p)).lastIndexOf(\".\");if(k<0){var T=x?e.lastIndexOf(\"e\"):-1;T<0?(_=e,w=\"\"):(_=e.substring(0,T),w=e.substring(T))}else _=e.substring(0,k),w=r+e.substring(k+1);!u&&f&&(_=o(_,1/0));var M=v.length+_.length+w.length+(b?0:i.length),A=M<h?new Array(M=h-M+1).join(a):\"\";return b&&(_=o(A+_,A.length?h-w.length:1/0)),i+=v,e=_+w,(\"<\"===s?i+e+A:\">\"===s?A+i+e:\"^\"===s?A.substring(0,M>>=1)+i+e+A.substring(M):i+(b?e:A+e))+n}}}t.formatPrefix=function(e,r){var n=0;return(e=+e)&&(e<0&&(e*=-1),r&&(e=t.round(e,Ee(e,r))),n=1+Math.floor(1e-12+Math.log(e)/Math.LN10),n=Math.max(-24,Math.min(24,3*Math.floor((n-1)/3)))),Le[8+n/3]};var Pe=/(?:([^{])?([<>=^]))?([+\\- ])?([$#])?(0)?(\\d+)?(,)?(\\.-?\\d+)?([a-z%])?/i,Oe=t.map({b:function(t){return t.toString(2)},c:function(t){return String.fromCharCode(t)},o:function(t){return t.toString(8)},x:function(t){return t.toString(16)},X:function(t){return t.toString(16).toUpperCase()},g:function(t,e){return t.toPrecision(e)},e:function(t,e){return t.toExponential(e)},f:function(t,e){return t.toFixed(e)},r:function(e,r){return(e=t.round(e,Ee(e,r))).toFixed(Math.max(0,Math.min(20,Ee(e*(1+1e-15),r))))}});function ze(t){return t+\"\"}var Ie=t.time={},De=Date;function Re(){this._=new Date(arguments.length>1?Date.UTC.apply(this,arguments):arguments[0])}Re.prototype={getDate:function(){return this._.getUTCDate()},getDay:function(){return this._.getUTCDay()},getFullYear:function(){return this._.getUTCFullYear()},getHours:function(){return this._.getUTCHours()},getMilliseconds:function(){return this._.getUTCMilliseconds()},getMinutes:function(){return this._.getUTCMinutes()},getMonth:function(){return this._.getUTCMonth()},getSeconds:function(){return this._.getUTCSeconds()},getTime:function(){return this._.getTime()},getTimezoneOffset:function(){return 0},valueOf:function(){return this._.valueOf()},setDate:function(){Fe.setUTCDate.apply(this._,arguments)},setDay:function(){Fe.setUTCDay.apply(this._,arguments)},setFullYear:function(){Fe.setUTCFullYear.apply(this._,arguments)},setHours:function(){Fe.setUTCHours.apply(this._,arguments)},setMilliseconds:function(){Fe.setUTCMilliseconds.apply(this._,arguments)},setMinutes:function(){Fe.setUTCMinutes.apply(this._,arguments)},setMonth:function(){Fe.setUTCMonth.apply(this._,arguments)},setSeconds:function(){Fe.setUTCSeconds.apply(this._,arguments)},setTime:function(){Fe.setTime.apply(this._,arguments)}};var Fe=Date.prototype;function Be(t,e,r){function n(e){var r=t(e),n=i(r,1);return e-r<n-e?r:n}function a(r){return e(r=t(new De(r-1)),1),r}function i(t,r){return e(t=new De(+t),r),t}function o(t,n,i){var o=a(t),s=[];if(i>1)for(;o<n;)r(o)%i||s.push(new Date(+o)),e(o,1);else for(;o<n;)s.push(new Date(+o)),e(o,1);return s}t.floor=t,t.round=n,t.ceil=a,t.offset=i,t.range=o;var s=t.utc=Ne(t);return s.floor=s,s.round=Ne(n),s.ceil=Ne(a),s.offset=Ne(i),s.range=function(t,e,r){try{De=Re;var n=new Re;return n._=t,o(n,e,r)}finally{De=Date}},t}function Ne(t){return function(e,r){try{De=Re;var n=new Re;return n._=e,t(n,r)._}finally{De=Date}}}function je(e){var r=e.dateTime,n=e.date,a=e.time,i=e.periods,o=e.days,s=e.shortDays,l=e.months,c=e.shortMonths;function u(t){var e=t.length;function r(r){for(var n,a,i,o=[],s=-1,l=0;++s<e;)37===t.charCodeAt(s)&&(o.push(t.slice(l,s)),null!=(a=Ve[n=t.charAt(++s)])&&(n=t.charAt(++s)),(i=_[n])&&(n=i(r,null==a?\"e\"===n?\" \":\"0\":a)),o.push(n),l=s+1);return o.push(t.slice(l,s)),o.join(\"\")}return r.parse=function(e){var r={y:1900,m:0,d:1,H:0,M:0,S:0,L:0,Z:null};if(h(r,t,e,0)!=e.length)return null;\"p\"in r&&(r.H=r.H%12+12*r.p);var n=null!=r.Z&&De!==Re,a=new(n?Re:De);return\"j\"in r?a.setFullYear(r.y,0,r.j):\"W\"in r||\"U\"in r?(\"w\"in r||(r.w=\"W\"in r?1:0),a.setFullYear(r.y,0,1),a.setFullYear(r.y,0,\"W\"in r?(r.w+6)%7+7*r.W-(a.getDay()+5)%7:r.w+7*r.U-(a.getDay()+6)%7)):a.setFullYear(r.y,r.m,r.d),a.setHours(r.H+(r.Z/100|0),r.M+r.Z%100,r.S,r.L),n?a._:a},r.toString=function(){return t},r}function h(t,e,r,n){for(var a,i,o,s=0,l=e.length,c=r.length;s<l;){if(n>=c)return-1;if(37===(a=e.charCodeAt(s++))){if(o=e.charAt(s++),!(i=w[o in Ve?e.charAt(s++):o])||(n=i(t,r,n))<0)return-1}else if(a!=r.charCodeAt(n++))return-1}return n}u.utc=function(t){var e=u(t);function r(t){try{var r=new(De=Re);return r._=t,e(r)}finally{De=Date}}return r.parse=function(t){try{De=Re;var r=e.parse(t);return r&&r._}finally{De=Date}},r.toString=e.toString,r},u.multi=u.utc.multi=lr;var f=t.map(),p=Ge(o),d=Ye(o),g=Ge(s),v=Ye(s),m=Ge(l),y=Ye(l),x=Ge(c),b=Ye(c);i.forEach(function(t,e){f.set(t.toLowerCase(),e)});var _={a:function(t){return s[t.getDay()]},A:function(t){return o[t.getDay()]},b:function(t){return c[t.getMonth()]},B:function(t){return l[t.getMonth()]},c:u(r),d:function(t,e){return He(t.getDate(),e,2)},e:function(t,e){return He(t.getDate(),e,2)},H:function(t,e){return He(t.getHours(),e,2)},I:function(t,e){return He(t.getHours()%12||12,e,2)},j:function(t,e){return He(1+Ie.dayOfYear(t),e,3)},L:function(t,e){return He(t.getMilliseconds(),e,3)},m:function(t,e){return He(t.getMonth()+1,e,2)},M:function(t,e){return He(t.getMinutes(),e,2)},p:function(t){return i[+(t.getHours()>=12)]},S:function(t,e){return He(t.getSeconds(),e,2)},U:function(t,e){return He(Ie.sundayOfYear(t),e,2)},w:function(t){return t.getDay()},W:function(t,e){return He(Ie.mondayOfYear(t),e,2)},x:u(n),X:u(a),y:function(t,e){return He(t.getFullYear()%100,e,2)},Y:function(t,e){return He(t.getFullYear()%1e4,e,4)},Z:or,\"%\":function(){return\"%\"}},w={a:function(t,e,r){g.lastIndex=0;var n=g.exec(e.slice(r));return n?(t.w=v.get(n[0].toLowerCase()),r+n[0].length):-1},A:function(t,e,r){p.lastIndex=0;var n=p.exec(e.slice(r));return n?(t.w=d.get(n[0].toLowerCase()),r+n[0].length):-1},b:function(t,e,r){x.lastIndex=0;var n=x.exec(e.slice(r));return n?(t.m=b.get(n[0].toLowerCase()),r+n[0].length):-1},B:function(t,e,r){m.lastIndex=0;var n=m.exec(e.slice(r));return n?(t.m=y.get(n[0].toLowerCase()),r+n[0].length):-1},c:function(t,e,r){return h(t,_.c.toString(),e,r)},d:tr,e:tr,H:rr,I:rr,j:er,L:ir,m:$e,M:nr,p:function(t,e,r){var n=f.get(e.slice(r,r+=2).toLowerCase());return null==n?-1:(t.p=n,r)},S:ar,U:Xe,w:We,W:Ze,x:function(t,e,r){return h(t,_.x.toString(),e,r)},X:function(t,e,r){return h(t,_.X.toString(),e,r)},y:Ke,Y:Je,Z:Qe,\"%\":sr};return u}Ie.year=Be(function(t){return(t=Ie.day(t)).setMonth(0,1),t},function(t,e){t.setFullYear(t.getFullYear()+e)},function(t){return t.getFullYear()}),Ie.years=Ie.year.range,Ie.years.utc=Ie.year.utc.range,Ie.day=Be(function(t){var e=new De(2e3,0);return e.setFullYear(t.getFullYear(),t.getMonth(),t.getDate()),e},function(t,e){t.setDate(t.getDate()+e)},function(t){return t.getDate()-1}),Ie.days=Ie.day.range,Ie.days.utc=Ie.day.utc.range,Ie.dayOfYear=function(t){var e=Ie.year(t);return Math.floor((t-e-6e4*(t.getTimezoneOffset()-e.getTimezoneOffset()))/864e5)},[\"sunday\",\"monday\",\"tuesday\",\"wednesday\",\"thursday\",\"friday\",\"saturday\"].forEach(function(t,e){e=7-e;var r=Ie[t]=Be(function(t){return(t=Ie.day(t)).setDate(t.getDate()-(t.getDay()+e)%7),t},function(t,e){t.setDate(t.getDate()+7*Math.floor(e))},function(t){var r=Ie.year(t).getDay();return Math.floor((Ie.dayOfYear(t)+(r+e)%7)/7)-(r!==e)});Ie[t+\"s\"]=r.range,Ie[t+\"s\"].utc=r.utc.range,Ie[t+\"OfYear\"]=function(t){var r=Ie.year(t).getDay();return Math.floor((Ie.dayOfYear(t)+(r+e)%7)/7)}}),Ie.week=Ie.sunday,Ie.weeks=Ie.sunday.range,Ie.weeks.utc=Ie.sunday.utc.range,Ie.weekOfYear=Ie.sundayOfYear;var Ve={\"-\":\"\",_:\" \",0:\"0\"},Ue=/^\\s*\\d+/,qe=/^%/;function He(t,e,r){var n=t<0?\"-\":\"\",a=(n?-t:t)+\"\",i=a.length;return n+(i<r?new Array(r-i+1).join(e)+a:a)}function Ge(e){return new RegExp(\"^(?:\"+e.map(t.requote).join(\"|\")+\")\",\"i\")}function Ye(t){for(var e=new b,r=-1,n=t.length;++r<n;)e.set(t[r].toLowerCase(),r);return e}function We(t,e,r){Ue.lastIndex=0;var n=Ue.exec(e.slice(r,r+1));return n?(t.w=+n[0],r+n[0].length):-1}function Xe(t,e,r){Ue.lastIndex=0;var n=Ue.exec(e.slice(r));return n?(t.U=+n[0],r+n[0].length):-1}function Ze(t,e,r){Ue.lastIndex=0;var n=Ue.exec(e.slice(r));return n?(t.W=+n[0],r+n[0].length):-1}function Je(t,e,r){Ue.lastIndex=0;var n=Ue.exec(e.slice(r,r+4));return n?(t.y=+n[0],r+n[0].length):-1}function Ke(t,e,r){Ue.lastIndex=0;var n,a=Ue.exec(e.slice(r,r+2));return a?(t.y=(n=+a[0])+(n>68?1900:2e3),r+a[0].length):-1}function Qe(t,e,r){return/^[+-]\\d{4}$/.test(e=e.slice(r,r+5))?(t.Z=-e,r+5):-1}function $e(t,e,r){Ue.lastIndex=0;var n=Ue.exec(e.slice(r,r+2));return n?(t.m=n[0]-1,r+n[0].length):-1}function tr(t,e,r){Ue.lastIndex=0;var n=Ue.exec(e.slice(r,r+2));return n?(t.d=+n[0],r+n[0].length):-1}function er(t,e,r){Ue.lastIndex=0;var n=Ue.exec(e.slice(r,r+3));return n?(t.j=+n[0],r+n[0].length):-1}function rr(t,e,r){Ue.lastIndex=0;var n=Ue.exec(e.slice(r,r+2));return n?(t.H=+n[0],r+n[0].length):-1}function nr(t,e,r){Ue.lastIndex=0;var n=Ue.exec(e.slice(r,r+2));return n?(t.M=+n[0],r+n[0].length):-1}function ar(t,e,r){Ue.lastIndex=0;var n=Ue.exec(e.slice(r,r+2));return n?(t.S=+n[0],r+n[0].length):-1}function ir(t,e,r){Ue.lastIndex=0;var n=Ue.exec(e.slice(r,r+3));return n?(t.L=+n[0],r+n[0].length):-1}function or(t){var e=t.getTimezoneOffset(),r=e>0?\"-\":\"+\",n=y(e)/60|0,a=y(e)%60;return r+He(n,\"0\",2)+He(a,\"0\",2)}function sr(t,e,r){qe.lastIndex=0;var n=qe.exec(e.slice(r,r+1));return n?r+n[0].length:-1}function lr(t){for(var e=t.length,r=-1;++r<e;)t[r][0]=this(t[r][0]);return function(e){for(var r=0,n=t[r];!n[1](e);)n=t[++r];return n[0](e)}}t.locale=function(t){return{numberFormat:Ce(t),timeFormat:je(t)}};var cr=t.locale({decimal:\".\",thousands:\",\",grouping:[3],currency:[\"$\",\"\"],dateTime:\"%a %b %e %X %Y\",date:\"%m/%d/%Y\",time:\"%H:%M:%S\",periods:[\"AM\",\"PM\"],days:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],shortDays:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],months:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],shortMonths:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"]});function ur(){}t.format=cr.numberFormat,t.geo={},ur.prototype={s:0,t:0,add:function(t){fr(t,this.t,hr),fr(hr.s,this.s,this),this.s?this.t+=hr.t:this.s=hr.t},reset:function(){this.s=this.t=0},valueOf:function(){return this.s}};var hr=new ur;function fr(t,e,r){var n=r.s=t+e,a=n-t,i=n-a;r.t=t-i+(e-a)}function pr(t,e){t&&gr.hasOwnProperty(t.type)&&gr[t.type](t,e)}t.geo.stream=function(t,e){t&&dr.hasOwnProperty(t.type)?dr[t.type](t,e):pr(t,e)};var dr={Feature:function(t,e){pr(t.geometry,e)},FeatureCollection:function(t,e){for(var r=t.features,n=-1,a=r.length;++n<a;)pr(r[n].geometry,e)}},gr={Sphere:function(t,e){e.sphere()},Point:function(t,e){t=t.coordinates,e.point(t[0],t[1],t[2])},MultiPoint:function(t,e){for(var r=t.coordinates,n=-1,a=r.length;++n<a;)t=r[n],e.point(t[0],t[1],t[2])},LineString:function(t,e){vr(t.coordinates,e,0)},MultiLineString:function(t,e){for(var r=t.coordinates,n=-1,a=r.length;++n<a;)vr(r[n],e,0)},Polygon:function(t,e){mr(t.coordinates,e)},MultiPolygon:function(t,e){for(var r=t.coordinates,n=-1,a=r.length;++n<a;)mr(r[n],e)},GeometryCollection:function(t,e){for(var r=t.geometries,n=-1,a=r.length;++n<a;)pr(r[n],e)}};function vr(t,e,r){var n,a=-1,i=t.length-r;for(e.lineStart();++a<i;)n=t[a],e.point(n[0],n[1],n[2]);e.lineEnd()}function mr(t,e){var r=-1,n=t.length;for(e.polygonStart();++r<n;)vr(t[r],e,1);e.polygonEnd()}t.geo.area=function(e){return yr=0,t.geo.stream(e,Pr),yr};var yr,xr,br,_r,wr,kr,Tr,Mr,Ar,Sr,Er,Lr,Cr=new ur,Pr={sphere:function(){yr+=4*Mt},point:D,lineStart:D,lineEnd:D,polygonStart:function(){Cr.reset(),Pr.lineStart=Or},polygonEnd:function(){var t=2*Cr;yr+=t<0?4*Mt+t:t,Pr.lineStart=Pr.lineEnd=Pr.point=D}};function Or(){var t,e,r,n,a;function i(t,e){e=e*Lt/2+Mt/4;var i=(t*=Lt)-r,o=i>=0?1:-1,s=o*i,l=Math.cos(e),c=Math.sin(e),u=a*c,h=n*l+u*Math.cos(s),f=u*o*Math.sin(s);Cr.add(Math.atan2(f,h)),r=t,n=l,a=c}Pr.point=function(o,s){Pr.point=i,r=(t=o)*Lt,n=Math.cos(s=(e=s)*Lt/2+Mt/4),a=Math.sin(s)},Pr.lineEnd=function(){i(t,e)}}function zr(t){var e=t[0],r=t[1],n=Math.cos(r);return[n*Math.cos(e),n*Math.sin(e),Math.sin(r)]}function Ir(t,e){return t[0]*e[0]+t[1]*e[1]+t[2]*e[2]}function Dr(t,e){return[t[1]*e[2]-t[2]*e[1],t[2]*e[0]-t[0]*e[2],t[0]*e[1]-t[1]*e[0]]}function Rr(t,e){t[0]+=e[0],t[1]+=e[1],t[2]+=e[2]}function Fr(t,e){return[t[0]*e,t[1]*e,t[2]*e]}function Br(t){var e=Math.sqrt(t[0]*t[0]+t[1]*t[1]+t[2]*t[2]);t[0]/=e,t[1]/=e,t[2]/=e}function Nr(t){return[Math.atan2(t[1],t[0]),It(t[2])]}function jr(t,e){return y(t[0]-e[0])<kt&&y(t[1]-e[1])<kt}t.geo.bounds=function(){var e,r,n,a,i,o,s,l,c,u,h,f={point:p,lineStart:g,lineEnd:v,polygonStart:function(){f.point=m,f.lineStart=x,f.lineEnd=b,c=0,Pr.polygonStart()},polygonEnd:function(){Pr.polygonEnd(),f.point=p,f.lineStart=g,f.lineEnd=v,Cr<0?(e=-(n=180),r=-(a=90)):c>kt?a=90:c<-kt&&(r=-90),h[0]=e,h[1]=n}};function p(t,i){u.push(h=[e=t,n=t]),i<r&&(r=i),i>a&&(a=i)}function d(t,o){var s=zr([t*Lt,o*Lt]);if(l){var c=Dr(l,s),u=Dr([c[1],-c[0],0],c);Br(u),u=Nr(u);var h=t-i,f=h>0?1:-1,d=u[0]*Ct*f,g=y(h)>180;if(g^(f*i<d&&d<f*t))(v=u[1]*Ct)>a&&(a=v);else if(g^(f*i<(d=(d+360)%360-180)&&d<f*t)){var v;(v=-u[1]*Ct)<r&&(r=v)}else o<r&&(r=o),o>a&&(a=o);g?t<i?_(e,t)>_(e,n)&&(n=t):_(t,n)>_(e,n)&&(e=t):n>=e?(t<e&&(e=t),t>n&&(n=t)):t>i?_(e,t)>_(e,n)&&(n=t):_(t,n)>_(e,n)&&(e=t)}else p(t,o);l=s,i=t}function g(){f.point=d}function v(){h[0]=e,h[1]=n,f.point=p,l=null}function m(t,e){if(l){var r=t-i;c+=y(r)>180?r+(r>0?360:-360):r}else o=t,s=e;Pr.point(t,e),d(t,e)}function x(){Pr.lineStart()}function b(){m(o,s),Pr.lineEnd(),y(c)>kt&&(e=-(n=180)),h[0]=e,h[1]=n,l=null}function _(t,e){return(e-=t)<0?e+360:e}function w(t,e){return t[0]-e[0]}function k(t,e){return e[0]<=e[1]?e[0]<=t&&t<=e[1]:t<e[0]||e[1]<t}return function(i){if(a=n=-(e=r=1/0),u=[],t.geo.stream(i,f),c=u.length){u.sort(w);for(var o=1,s=[g=u[0]];o<c;++o)k((p=u[o])[0],g)||k(p[1],g)?(_(g[0],p[1])>_(g[0],g[1])&&(g[1]=p[1]),_(p[0],g[1])>_(g[0],g[1])&&(g[0]=p[0])):s.push(g=p);for(var l,c,p,d=-1/0,g=(o=0,s[c=s.length-1]);o<=c;g=p,++o)p=s[o],(l=_(g[1],p[0]))>d&&(d=l,e=p[0],n=g[1])}return u=h=null,e===1/0||r===1/0?[[NaN,NaN],[NaN,NaN]]:[[e,r],[n,a]]}}(),t.geo.centroid=function(e){xr=br=_r=wr=kr=Tr=Mr=Ar=Sr=Er=Lr=0,t.geo.stream(e,Vr);var r=Sr,n=Er,a=Lr,i=r*r+n*n+a*a;return i<Tt&&(r=Tr,n=Mr,a=Ar,br<kt&&(r=_r,n=wr,a=kr),(i=r*r+n*n+a*a)<Tt)?[NaN,NaN]:[Math.atan2(n,r)*Ct,It(a/Math.sqrt(i))*Ct]};var Vr={sphere:D,point:Ur,lineStart:Hr,lineEnd:Gr,polygonStart:function(){Vr.lineStart=Yr},polygonEnd:function(){Vr.lineStart=Hr}};function Ur(t,e){t*=Lt;var r=Math.cos(e*=Lt);qr(r*Math.cos(t),r*Math.sin(t),Math.sin(e))}function qr(t,e,r){_r+=(t-_r)/++xr,wr+=(e-wr)/xr,kr+=(r-kr)/xr}function Hr(){var t,e,r;function n(n,a){n*=Lt;var i=Math.cos(a*=Lt),o=i*Math.cos(n),s=i*Math.sin(n),l=Math.sin(a),c=Math.atan2(Math.sqrt((c=e*l-r*s)*c+(c=r*o-t*l)*c+(c=t*s-e*o)*c),t*o+e*s+r*l);br+=c,Tr+=c*(t+(t=o)),Mr+=c*(e+(e=s)),Ar+=c*(r+(r=l)),qr(t,e,r)}Vr.point=function(a,i){a*=Lt;var o=Math.cos(i*=Lt);t=o*Math.cos(a),e=o*Math.sin(a),r=Math.sin(i),Vr.point=n,qr(t,e,r)}}function Gr(){Vr.point=Ur}function Yr(){var t,e,r,n,a;function i(t,e){t*=Lt;var i=Math.cos(e*=Lt),o=i*Math.cos(t),s=i*Math.sin(t),l=Math.sin(e),c=n*l-a*s,u=a*o-r*l,h=r*s-n*o,f=Math.sqrt(c*c+u*u+h*h),p=r*o+n*s+a*l,d=f&&-zt(p)/f,g=Math.atan2(f,p);Sr+=d*c,Er+=d*u,Lr+=d*h,br+=g,Tr+=g*(r+(r=o)),Mr+=g*(n+(n=s)),Ar+=g*(a+(a=l)),qr(r,n,a)}Vr.point=function(o,s){t=o,e=s,Vr.point=i,o*=Lt;var l=Math.cos(s*=Lt);r=l*Math.cos(o),n=l*Math.sin(o),a=Math.sin(s),qr(r,n,a)},Vr.lineEnd=function(){i(t,e),Vr.lineEnd=Gr,Vr.point=Ur}}function Wr(t,e){function r(r,n){return r=t(r,n),e(r[0],r[1])}return t.invert&&e.invert&&(r.invert=function(r,n){return(r=e.invert(r,n))&&t.invert(r[0],r[1])}),r}function Xr(){return!0}function Zr(t,e,r,n,a){var i=[],o=[];if(t.forEach(function(t){if(!((e=t.length-1)<=0)){var e,r=t[0],n=t[e];if(jr(r,n)){a.lineStart();for(var s=0;s<e;++s)a.point((r=t[s])[0],r[1]);a.lineEnd()}else{var l=new Kr(r,t,null,!0),c=new Kr(r,null,l,!1);l.o=c,i.push(l),o.push(c),l=new Kr(n,t,null,!1),c=new Kr(n,null,l,!0),l.o=c,i.push(l),o.push(c)}}}),o.sort(e),Jr(i),Jr(o),i.length){for(var s=0,l=r,c=o.length;s<c;++s)o[s].e=l=!l;for(var u,h,f=i[0];;){for(var p=f,d=!0;p.v;)if((p=p.n)===f)return;u=p.z,a.lineStart();do{if(p.v=p.o.v=!0,p.e){if(d)for(s=0,c=u.length;s<c;++s)a.point((h=u[s])[0],h[1]);else n(p.x,p.n.x,1,a);p=p.n}else{if(d)for(s=(u=p.p.z).length-1;s>=0;--s)a.point((h=u[s])[0],h[1]);else n(p.x,p.p.x,-1,a);p=p.p}u=(p=p.o).z,d=!d}while(!p.v);a.lineEnd()}}}function Jr(t){if(e=t.length){for(var e,r,n=0,a=t[0];++n<e;)a.n=r=t[n],r.p=a,a=r;a.n=r=t[0],r.p=a}}function Kr(t,e,r,n){this.x=t,this.z=e,this.o=r,this.e=n,this.v=!1,this.n=this.p=null}function Qr(e,r,n,a){return function(i,o){var s,l=r(o),c=i.invert(a[0],a[1]),u={point:h,lineStart:p,lineEnd:d,polygonStart:function(){u.point=b,u.lineStart=_,u.lineEnd=w,s=[],g=[]},polygonEnd:function(){u.point=h,u.lineStart=p,u.lineEnd=d,s=t.merge(s);var e=function(t,e){var r=t[0],n=t[1],a=[Math.sin(r),-Math.cos(r),0],i=0,o=0;Cr.reset();for(var s=0,l=e.length;s<l;++s){var c=e[s],u=c.length;if(u)for(var h=c[0],f=h[0],p=h[1]/2+Mt/4,d=Math.sin(p),g=Math.cos(p),v=1;;){v===u&&(v=0);var m=(t=c[v])[0],y=t[1]/2+Mt/4,x=Math.sin(y),b=Math.cos(y),_=m-f,w=_>=0?1:-1,k=w*_,T=k>Mt,M=d*x;if(Cr.add(Math.atan2(M*w*Math.sin(k),g*b+M*Math.cos(k))),i+=T?_+w*At:_,T^f>=r^m>=r){var A=Dr(zr(h),zr(t));Br(A);var S=Dr(a,A);Br(S);var E=(T^_>=0?-1:1)*It(S[2]);(n>E||n===E&&(A[0]||A[1]))&&(o+=T^_>=0?1:-1)}if(!v++)break;f=m,d=x,g=b,h=t}}return(i<-kt||i<kt&&Cr<-kt)^1&o}(c,g);s.length?(x||(o.polygonStart(),x=!0),Zr(s,en,e,n,o)):e&&(x||(o.polygonStart(),x=!0),o.lineStart(),n(null,null,1,o),o.lineEnd()),x&&(o.polygonEnd(),x=!1),s=g=null},sphere:function(){o.polygonStart(),o.lineStart(),n(null,null,1,o),o.lineEnd(),o.polygonEnd()}};function h(t,r){var n=i(t,r);e(t=n[0],r=n[1])&&o.point(t,r)}function f(t,e){var r=i(t,e);l.point(r[0],r[1])}function p(){u.point=f,l.lineStart()}function d(){u.point=h,l.lineEnd()}var g,v,m=tn(),y=r(m),x=!1;function b(t,e){v.push([t,e]);var r=i(t,e);y.point(r[0],r[1])}function _(){y.lineStart(),v=[]}function w(){b(v[0][0],v[0][1]),y.lineEnd();var t,e=y.clean(),r=m.buffer(),n=r.length;if(v.pop(),g.push(v),v=null,n)if(1&e){var a,i=-1;if((n=(t=r[0]).length-1)>0){for(x||(o.polygonStart(),x=!0),o.lineStart();++i<n;)o.point((a=t[i])[0],a[1]);o.lineEnd()}}else n>1&&2&e&&r.push(r.pop().concat(r.shift())),s.push(r.filter($r))}return u}}function $r(t){return t.length>1}function tn(){var t,e=[];return{lineStart:function(){e.push(t=[])},point:function(e,r){t.push([e,r])},lineEnd:D,buffer:function(){var r=e;return e=[],t=null,r},rejoin:function(){e.length>1&&e.push(e.pop().concat(e.shift()))}}}function en(t,e){return((t=t.x)[0]<0?t[1]-Et-kt:Et-t[1])-((e=e.x)[0]<0?e[1]-Et-kt:Et-e[1])}var rn=Qr(Xr,function(t){var e,r=NaN,n=NaN,a=NaN;return{lineStart:function(){t.lineStart(),e=1},point:function(i,o){var s=i>0?Mt:-Mt,l=y(i-r);y(l-Mt)<kt?(t.point(r,n=(n+o)/2>0?Et:-Et),t.point(a,n),t.lineEnd(),t.lineStart(),t.point(s,n),t.point(i,n),e=0):a!==s&&l>=Mt&&(y(r-a)<kt&&(r-=a*kt),y(i-s)<kt&&(i-=s*kt),n=function(t,e,r,n){var a,i,o=Math.sin(t-r);return y(o)>kt?Math.atan((Math.sin(e)*(i=Math.cos(n))*Math.sin(r)-Math.sin(n)*(a=Math.cos(e))*Math.sin(t))/(a*i*o)):(e+n)/2}(r,n,i,o),t.point(a,n),t.lineEnd(),t.lineStart(),t.point(s,n),e=0),t.point(r=i,n=o),a=s},lineEnd:function(){t.lineEnd(),r=n=NaN},clean:function(){return 2-e}}},function(t,e,r,n){var a;if(null==t)a=r*Et,n.point(-Mt,a),n.point(0,a),n.point(Mt,a),n.point(Mt,0),n.point(Mt,-a),n.point(0,-a),n.point(-Mt,-a),n.point(-Mt,0),n.point(-Mt,a);else if(y(t[0]-e[0])>kt){var i=t[0]<e[0]?Mt:-Mt;a=r*i/2,n.point(-i,a),n.point(0,a),n.point(i,a)}else n.point(e[0],e[1])},[-Mt,-Mt/2]);function nn(t,e,r,n){return function(a){var i,o=a.a,s=a.b,l=o.x,c=o.y,u=0,h=1,f=s.x-l,p=s.y-c;if(i=t-l,f||!(i>0)){if(i/=f,f<0){if(i<u)return;i<h&&(h=i)}else if(f>0){if(i>h)return;i>u&&(u=i)}if(i=r-l,f||!(i<0)){if(i/=f,f<0){if(i>h)return;i>u&&(u=i)}else if(f>0){if(i<u)return;i<h&&(h=i)}if(i=e-c,p||!(i>0)){if(i/=p,p<0){if(i<u)return;i<h&&(h=i)}else if(p>0){if(i>h)return;i>u&&(u=i)}if(i=n-c,p||!(i<0)){if(i/=p,p<0){if(i>h)return;i>u&&(u=i)}else if(p>0){if(i<u)return;i<h&&(h=i)}return u>0&&(a.a={x:l+u*f,y:c+u*p}),h<1&&(a.b={x:l+h*f,y:c+h*p}),a}}}}}}var an=1e9;function on(e,r,n,a){return function(l){var c,u,h,f,p,d,g,v,m,y,x,b=l,_=tn(),w=nn(e,r,n,a),k={point:A,lineStart:function(){k.point=S,u&&u.push(h=[]);y=!0,m=!1,g=v=NaN},lineEnd:function(){c&&(S(f,p),d&&m&&_.rejoin(),c.push(_.buffer()));k.point=A,m&&l.lineEnd()},polygonStart:function(){l=_,c=[],u=[],x=!0},polygonEnd:function(){l=b,c=t.merge(c);var r=function(t){for(var e=0,r=u.length,n=t[1],a=0;a<r;++a)for(var i,o=1,s=u[a],l=s.length,c=s[0];o<l;++o)i=s[o],c[1]<=n?i[1]>n&&Ot(c,i,t)>0&&++e:i[1]<=n&&Ot(c,i,t)<0&&--e,c=i;return 0!==e}([e,a]),n=x&&r,i=c.length;(n||i)&&(l.polygonStart(),n&&(l.lineStart(),T(null,null,1,l),l.lineEnd()),i&&Zr(c,o,r,T,l),l.polygonEnd()),c=u=h=null}};function T(t,o,l,c){var u=0,h=0;if(null==t||(u=i(t,l))!==(h=i(o,l))||s(t,o)<0^l>0)do{c.point(0===u||3===u?e:n,u>1?a:r)}while((u=(u+l+4)%4)!==h);else c.point(o[0],o[1])}function M(t,i){return e<=t&&t<=n&&r<=i&&i<=a}function A(t,e){M(t,e)&&l.point(t,e)}function S(t,e){var r=M(t=Math.max(-an,Math.min(an,t)),e=Math.max(-an,Math.min(an,e)));if(u&&h.push([t,e]),y)f=t,p=e,d=r,y=!1,r&&(l.lineStart(),l.point(t,e));else if(r&&m)l.point(t,e);else{var n={a:{x:g,y:v},b:{x:t,y:e}};w(n)?(m||(l.lineStart(),l.point(n.a.x,n.a.y)),l.point(n.b.x,n.b.y),r||l.lineEnd(),x=!1):r&&(l.lineStart(),l.point(t,e),x=!1)}g=t,v=e,m=r}return k};function i(t,a){return y(t[0]-e)<kt?a>0?0:3:y(t[0]-n)<kt?a>0?2:1:y(t[1]-r)<kt?a>0?1:0:a>0?3:2}function o(t,e){return s(t.x,e.x)}function s(t,e){var r=i(t,1),n=i(e,1);return r!==n?r-n:0===r?e[1]-t[1]:1===r?t[0]-e[0]:2===r?t[1]-e[1]:e[0]-t[0]}}function sn(t){var e=0,r=Mt/3,n=Pn(t),a=n(e,r);return a.parallels=function(t){return arguments.length?n(e=t[0]*Mt/180,r=t[1]*Mt/180):[e/Mt*180,r/Mt*180]},a}function ln(t,e){var r=Math.sin(t),n=(r+Math.sin(e))/2,a=1+r*(2*n-r),i=Math.sqrt(a)/n;function o(t,e){var r=Math.sqrt(a-2*n*Math.sin(e))/n;return[r*Math.sin(t*=n),i-r*Math.cos(t)]}return o.invert=function(t,e){var r=i-e;return[Math.atan2(t,r)/n,It((a-(t*t+r*r)*n*n)/(2*n))]},o}t.geo.clipExtent=function(){var t,e,r,n,a,i,o={stream:function(t){return a&&(a.valid=!1),(a=i(t)).valid=!0,a},extent:function(s){return arguments.length?(i=on(t=+s[0][0],e=+s[0][1],r=+s[1][0],n=+s[1][1]),a&&(a.valid=!1,a=null),o):[[t,e],[r,n]]}};return o.extent([[0,0],[960,500]])},(t.geo.conicEqualArea=function(){return sn(ln)}).raw=ln,t.geo.albers=function(){return t.geo.conicEqualArea().rotate([96,0]).center([-.6,38.7]).parallels([29.5,45.5]).scale(1070)},t.geo.albersUsa=function(){var e,r,n,a,i=t.geo.albers(),o=t.geo.conicEqualArea().rotate([154,0]).center([-2,58.5]).parallels([55,65]),s=t.geo.conicEqualArea().rotate([157,0]).center([-3,19.9]).parallels([8,18]),l={point:function(t,r){e=[t,r]}};function c(t){var i=t[0],o=t[1];return e=null,r(i,o),e||(n(i,o),e)||a(i,o),e}return c.invert=function(t){var e=i.scale(),r=i.translate(),n=(t[0]-r[0])/e,a=(t[1]-r[1])/e;return(a>=.12&&a<.234&&n>=-.425&&n<-.214?o:a>=.166&&a<.234&&n>=-.214&&n<-.115?s:i).invert(t)},c.stream=function(t){var e=i.stream(t),r=o.stream(t),n=s.stream(t);return{point:function(t,a){e.point(t,a),r.point(t,a),n.point(t,a)},sphere:function(){e.sphere(),r.sphere(),n.sphere()},lineStart:function(){e.lineStart(),r.lineStart(),n.lineStart()},lineEnd:function(){e.lineEnd(),r.lineEnd(),n.lineEnd()},polygonStart:function(){e.polygonStart(),r.polygonStart(),n.polygonStart()},polygonEnd:function(){e.polygonEnd(),r.polygonEnd(),n.polygonEnd()}}},c.precision=function(t){return arguments.length?(i.precision(t),o.precision(t),s.precision(t),c):i.precision()},c.scale=function(t){return arguments.length?(i.scale(t),o.scale(.35*t),s.scale(t),c.translate(i.translate())):i.scale()},c.translate=function(t){if(!arguments.length)return i.translate();var e=i.scale(),u=+t[0],h=+t[1];return r=i.translate(t).clipExtent([[u-.455*e,h-.238*e],[u+.455*e,h+.238*e]]).stream(l).point,n=o.translate([u-.307*e,h+.201*e]).clipExtent([[u-.425*e+kt,h+.12*e+kt],[u-.214*e-kt,h+.234*e-kt]]).stream(l).point,a=s.translate([u-.205*e,h+.212*e]).clipExtent([[u-.214*e+kt,h+.166*e+kt],[u-.115*e-kt,h+.234*e-kt]]).stream(l).point,c},c.scale(1070)};var cn,un,hn,fn,pn,dn,gn={point:D,lineStart:D,lineEnd:D,polygonStart:function(){un=0,gn.lineStart=vn},polygonEnd:function(){gn.lineStart=gn.lineEnd=gn.point=D,cn+=y(un/2)}};function vn(){var t,e,r,n;function a(t,e){un+=n*t-r*e,r=t,n=e}gn.point=function(i,o){gn.point=a,t=r=i,e=n=o},gn.lineEnd=function(){a(t,e)}}var mn={point:function(t,e){t<hn&&(hn=t);t>pn&&(pn=t);e<fn&&(fn=e);e>dn&&(dn=e)},lineStart:D,lineEnd:D,polygonStart:D,polygonEnd:D};function yn(){var t=xn(4.5),e=[],r={point:n,lineStart:function(){r.point=a},lineEnd:o,polygonStart:function(){r.lineEnd=s},polygonEnd:function(){r.lineEnd=o,r.point=n},pointRadius:function(e){return t=xn(e),r},result:function(){if(e.length){var t=e.join(\"\");return e=[],t}}};function n(r,n){e.push(\"M\",r,\",\",n,t)}function a(t,n){e.push(\"M\",t,\",\",n),r.point=i}function i(t,r){e.push(\"L\",t,\",\",r)}function o(){r.point=n}function s(){e.push(\"Z\")}return r}function xn(t){return\"m0,\"+t+\"a\"+t+\",\"+t+\" 0 1,1 0,\"+-2*t+\"a\"+t+\",\"+t+\" 0 1,1 0,\"+2*t+\"z\"}var bn,_n={point:wn,lineStart:kn,lineEnd:Tn,polygonStart:function(){_n.lineStart=Mn},polygonEnd:function(){_n.point=wn,_n.lineStart=kn,_n.lineEnd=Tn}};function wn(t,e){_r+=t,wr+=e,++kr}function kn(){var t,e;function r(r,n){var a=r-t,i=n-e,o=Math.sqrt(a*a+i*i);Tr+=o*(t+r)/2,Mr+=o*(e+n)/2,Ar+=o,wn(t=r,e=n)}_n.point=function(n,a){_n.point=r,wn(t=n,e=a)}}function Tn(){_n.point=wn}function Mn(){var t,e,r,n;function a(t,e){var a=t-r,i=e-n,o=Math.sqrt(a*a+i*i);Tr+=o*(r+t)/2,Mr+=o*(n+e)/2,Ar+=o,Sr+=(o=n*t-r*e)*(r+t),Er+=o*(n+e),Lr+=3*o,wn(r=t,n=e)}_n.point=function(i,o){_n.point=a,wn(t=r=i,e=n=o)},_n.lineEnd=function(){a(t,e)}}function An(t){var e=4.5,r={point:n,lineStart:function(){r.point=a},lineEnd:o,polygonStart:function(){r.lineEnd=s},polygonEnd:function(){r.lineEnd=o,r.point=n},pointRadius:function(t){return e=t,r},result:D};function n(r,n){t.moveTo(r+e,n),t.arc(r,n,e,0,At)}function a(e,n){t.moveTo(e,n),r.point=i}function i(e,r){t.lineTo(e,r)}function o(){r.point=n}function s(){t.closePath()}return r}function Sn(t){var e=.5,r=Math.cos(30*Lt),n=16;function a(e){return(n?function(e){var r,a,o,s,l,c,u,h,f,p,d,g,v={point:m,lineStart:y,lineEnd:b,polygonStart:function(){e.polygonStart(),v.lineStart=_},polygonEnd:function(){e.polygonEnd(),v.lineStart=y}};function m(r,n){r=t(r,n),e.point(r[0],r[1])}function y(){h=NaN,v.point=x,e.lineStart()}function x(r,a){var o=zr([r,a]),s=t(r,a);i(h,f,u,p,d,g,h=s[0],f=s[1],u=r,p=o[0],d=o[1],g=o[2],n,e),e.point(h,f)}function b(){v.point=m,e.lineEnd()}function _(){y(),v.point=w,v.lineEnd=k}function w(t,e){x(r=t,e),a=h,o=f,s=p,l=d,c=g,v.point=x}function k(){i(h,f,u,p,d,g,a,o,r,s,l,c,n,e),v.lineEnd=b,b()}return v}:function(e){return Ln(e,function(r,n){r=t(r,n),e.point(r[0],r[1])})})(e)}function i(n,a,o,s,l,c,u,h,f,p,d,g,v,m){var x=u-n,b=h-a,_=x*x+b*b;if(_>4*e&&v--){var w=s+p,k=l+d,T=c+g,M=Math.sqrt(w*w+k*k+T*T),A=Math.asin(T/=M),S=y(y(T)-1)<kt||y(o-f)<kt?(o+f)/2:Math.atan2(k,w),E=t(S,A),L=E[0],C=E[1],P=L-n,O=C-a,z=b*P-x*O;(z*z/_>e||y((x*P+b*O)/_-.5)>.3||s*p+l*d+c*g<r)&&(i(n,a,o,s,l,c,L,C,S,w/=M,k/=M,T,v,m),m.point(L,C),i(L,C,S,w,k,T,u,h,f,p,d,g,v,m))}}return a.precision=function(t){return arguments.length?(n=(e=t*t)>0&&16,a):Math.sqrt(e)},a}function En(t){this.stream=t}function Ln(t,e){return{point:e,sphere:function(){t.sphere()},lineStart:function(){t.lineStart()},lineEnd:function(){t.lineEnd()},polygonStart:function(){t.polygonStart()},polygonEnd:function(){t.polygonEnd()}}}function Cn(t){return Pn(function(){return t})()}function Pn(e){var r,n,a,i,o,s,l=Sn(function(t,e){return[(t=r(t,e))[0]*c+i,o-t[1]*c]}),c=150,u=480,h=250,f=0,p=0,d=0,g=0,v=0,m=rn,x=P,b=null,_=null;function w(t){return[(t=a(t[0]*Lt,t[1]*Lt))[0]*c+i,o-t[1]*c]}function k(t){return(t=a.invert((t[0]-i)/c,(o-t[1])/c))&&[t[0]*Ct,t[1]*Ct]}function T(){a=Wr(n=Dn(d,g,v),r);var t=r(f,p);return i=u-t[0]*c,o=h+t[1]*c,M()}function M(){return s&&(s.valid=!1,s=null),w}return w.stream=function(t){return s&&(s.valid=!1),(s=On(m(n,l(x(t))))).valid=!0,s},w.clipAngle=function(t){return arguments.length?(m=null==t?(b=t,rn):function(t){var e=Math.cos(t),r=e>0,n=y(e)>kt;return Qr(a,function(t){var e,s,l,c,u;return{lineStart:function(){c=l=!1,u=1},point:function(h,f){var p,d=[h,f],g=a(h,f),v=r?g?0:o(h,f):g?o(h+(h<0?Mt:-Mt),f):0;if(!e&&(c=l=g)&&t.lineStart(),g!==l&&(p=i(e,d),(jr(e,p)||jr(d,p))&&(d[0]+=kt,d[1]+=kt,g=a(d[0],d[1]))),g!==l)u=0,g?(t.lineStart(),p=i(d,e),t.point(p[0],p[1])):(p=i(e,d),t.point(p[0],p[1]),t.lineEnd()),e=p;else if(n&&e&&r^g){var m;v&s||!(m=i(d,e,!0))||(u=0,r?(t.lineStart(),t.point(m[0][0],m[0][1]),t.point(m[1][0],m[1][1]),t.lineEnd()):(t.point(m[1][0],m[1][1]),t.lineEnd(),t.lineStart(),t.point(m[0][0],m[0][1])))}!g||e&&jr(e,d)||t.point(d[0],d[1]),e=d,l=g,s=v},lineEnd:function(){l&&t.lineEnd(),e=null},clean:function(){return u|(c&&l)<<1}}},Nn(t,6*Lt),r?[0,-t]:[-Mt,t-Mt]);function a(t,r){return Math.cos(t)*Math.cos(r)>e}function i(t,r,n){var a=[1,0,0],i=Dr(zr(t),zr(r)),o=Ir(i,i),s=i[0],l=o-s*s;if(!l)return!n&&t;var c=e*o/l,u=-e*s/l,h=Dr(a,i),f=Fr(a,c);Rr(f,Fr(i,u));var p=h,d=Ir(f,p),g=Ir(p,p),v=d*d-g*(Ir(f,f)-1);if(!(v<0)){var m=Math.sqrt(v),x=Fr(p,(-d-m)/g);if(Rr(x,f),x=Nr(x),!n)return x;var b,_=t[0],w=r[0],k=t[1],T=r[1];w<_&&(b=_,_=w,w=b);var M=w-_,A=y(M-Mt)<kt;if(!A&&T<k&&(b=k,k=T,T=b),A||M<kt?A?k+T>0^x[1]<(y(x[0]-_)<kt?k:T):k<=x[1]&&x[1]<=T:M>Mt^(_<=x[0]&&x[0]<=w)){var S=Fr(p,(-d+m)/g);return Rr(S,f),[x,Nr(S)]}}}function o(e,n){var a=r?t:Mt-t,i=0;return e<-a?i|=1:e>a&&(i|=2),n<-a?i|=4:n>a&&(i|=8),i}}((b=+t)*Lt),M()):b},w.clipExtent=function(t){return arguments.length?(_=t,x=t?on(t[0][0],t[0][1],t[1][0],t[1][1]):P,M()):_},w.scale=function(t){return arguments.length?(c=+t,T()):c},w.translate=function(t){return arguments.length?(u=+t[0],h=+t[1],T()):[u,h]},w.center=function(t){return arguments.length?(f=t[0]%360*Lt,p=t[1]%360*Lt,T()):[f*Ct,p*Ct]},w.rotate=function(t){return arguments.length?(d=t[0]%360*Lt,g=t[1]%360*Lt,v=t.length>2?t[2]%360*Lt:0,T()):[d*Ct,g*Ct,v*Ct]},t.rebind(w,l,\"precision\"),function(){return r=e.apply(this,arguments),w.invert=r.invert&&k,T()}}function On(t){return Ln(t,function(e,r){t.point(e*Lt,r*Lt)})}function zn(t,e){return[t,e]}function In(t,e){return[t>Mt?t-At:t<-Mt?t+At:t,e]}function Dn(t,e,r){return t?e||r?Wr(Fn(t),Bn(e,r)):Fn(t):e||r?Bn(e,r):In}function Rn(t){return function(e,r){return[(e+=t)>Mt?e-At:e<-Mt?e+At:e,r]}}function Fn(t){var e=Rn(t);return e.invert=Rn(-t),e}function Bn(t,e){var r=Math.cos(t),n=Math.sin(t),a=Math.cos(e),i=Math.sin(e);function o(t,e){var o=Math.cos(e),s=Math.cos(t)*o,l=Math.sin(t)*o,c=Math.sin(e),u=c*r+s*n;return[Math.atan2(l*a-u*i,s*r-c*n),It(u*a+l*i)]}return o.invert=function(t,e){var o=Math.cos(e),s=Math.cos(t)*o,l=Math.sin(t)*o,c=Math.sin(e),u=c*a-l*i;return[Math.atan2(l*a+c*i,s*r+u*n),It(u*r-s*n)]},o}function Nn(t,e){var r=Math.cos(t),n=Math.sin(t);return function(a,i,o,s){var l=o*e;null!=a?(a=jn(r,a),i=jn(r,i),(o>0?a<i:a>i)&&(a+=o*At)):(a=t+o*At,i=t-.5*l);for(var c,u=a;o>0?u>i:u<i;u-=l)s.point((c=Nr([r,-n*Math.cos(u),-n*Math.sin(u)]))[0],c[1])}}function jn(t,e){var r=zr(e);r[0]-=t,Br(r);var n=zt(-r[1]);return((-r[2]<0?-n:n)+2*Math.PI-kt)%(2*Math.PI)}function Vn(e,r,n){var a=t.range(e,r-kt,n).concat(r);return function(t){return a.map(function(e){return[t,e]})}}function Un(e,r,n){var a=t.range(e,r-kt,n).concat(r);return function(t){return a.map(function(e){return[e,t]})}}function qn(t){return t.source}function Hn(t){return t.target}t.geo.path=function(){var e,r,n,a,i,o=4.5;function s(e){return e&&(\"function\"==typeof o&&a.pointRadius(+o.apply(this,arguments)),i&&i.valid||(i=n(a)),t.geo.stream(e,i)),a.result()}function l(){return i=null,s}return s.area=function(e){return cn=0,t.geo.stream(e,n(gn)),cn},s.centroid=function(e){return _r=wr=kr=Tr=Mr=Ar=Sr=Er=Lr=0,t.geo.stream(e,n(_n)),Lr?[Sr/Lr,Er/Lr]:Ar?[Tr/Ar,Mr/Ar]:kr?[_r/kr,wr/kr]:[NaN,NaN]},s.bounds=function(e){return pn=dn=-(hn=fn=1/0),t.geo.stream(e,n(mn)),[[hn,fn],[pn,dn]]},s.projection=function(t){return arguments.length?(n=(e=t)?t.stream||(r=t,a=Sn(function(t,e){return r([t*Ct,e*Ct])}),function(t){return On(a(t))}):P,l()):e;var r,a},s.context=function(t){return arguments.length?(a=null==(r=t)?new yn:new An(t),\"function\"!=typeof o&&a.pointRadius(o),l()):r},s.pointRadius=function(t){return arguments.length?(o=\"function\"==typeof t?t:(a.pointRadius(+t),+t),s):o},s.projection(t.geo.albersUsa()).context(null)},t.geo.transform=function(t){return{stream:function(e){var r=new En(e);for(var n in t)r[n]=t[n];return r}}},En.prototype={point:function(t,e){this.stream.point(t,e)},sphere:function(){this.stream.sphere()},lineStart:function(){this.stream.lineStart()},lineEnd:function(){this.stream.lineEnd()},polygonStart:function(){this.stream.polygonStart()},polygonEnd:function(){this.stream.polygonEnd()}},t.geo.projection=Cn,t.geo.projectionMutator=Pn,(t.geo.equirectangular=function(){return Cn(zn)}).raw=zn.invert=zn,t.geo.rotation=function(t){function e(e){return(e=t(e[0]*Lt,e[1]*Lt))[0]*=Ct,e[1]*=Ct,e}return t=Dn(t[0]%360*Lt,t[1]*Lt,t.length>2?t[2]*Lt:0),e.invert=function(e){return(e=t.invert(e[0]*Lt,e[1]*Lt))[0]*=Ct,e[1]*=Ct,e},e},In.invert=zn,t.geo.circle=function(){var t,e,r=[0,0],n=6;function a(){var t=\"function\"==typeof r?r.apply(this,arguments):r,n=Dn(-t[0]*Lt,-t[1]*Lt,0).invert,a=[];return e(null,null,1,{point:function(t,e){a.push(t=n(t,e)),t[0]*=Ct,t[1]*=Ct}}),{type:\"Polygon\",coordinates:[a]}}return a.origin=function(t){return arguments.length?(r=t,a):r},a.angle=function(r){return arguments.length?(e=Nn((t=+r)*Lt,n*Lt),a):t},a.precision=function(r){return arguments.length?(e=Nn(t*Lt,(n=+r)*Lt),a):n},a.angle(90)},t.geo.distance=function(t,e){var r,n=(e[0]-t[0])*Lt,a=t[1]*Lt,i=e[1]*Lt,o=Math.sin(n),s=Math.cos(n),l=Math.sin(a),c=Math.cos(a),u=Math.sin(i),h=Math.cos(i);return Math.atan2(Math.sqrt((r=h*o)*r+(r=c*u-l*h*s)*r),l*u+c*h*s)},t.geo.graticule=function(){var e,r,n,a,i,o,s,l,c,u,h,f,p=10,d=p,g=90,v=360,m=2.5;function x(){return{type:\"MultiLineString\",coordinates:b()}}function b(){return t.range(Math.ceil(a/g)*g,n,g).map(h).concat(t.range(Math.ceil(l/v)*v,s,v).map(f)).concat(t.range(Math.ceil(r/p)*p,e,p).filter(function(t){return y(t%g)>kt}).map(c)).concat(t.range(Math.ceil(o/d)*d,i,d).filter(function(t){return y(t%v)>kt}).map(u))}return x.lines=function(){return b().map(function(t){return{type:\"LineString\",coordinates:t}})},x.outline=function(){return{type:\"Polygon\",coordinates:[h(a).concat(f(s).slice(1),h(n).reverse().slice(1),f(l).reverse().slice(1))]}},x.extent=function(t){return arguments.length?x.majorExtent(t).minorExtent(t):x.minorExtent()},x.majorExtent=function(t){return arguments.length?(a=+t[0][0],n=+t[1][0],l=+t[0][1],s=+t[1][1],a>n&&(t=a,a=n,n=t),l>s&&(t=l,l=s,s=t),x.precision(m)):[[a,l],[n,s]]},x.minorExtent=function(t){return arguments.length?(r=+t[0][0],e=+t[1][0],o=+t[0][1],i=+t[1][1],r>e&&(t=r,r=e,e=t),o>i&&(t=o,o=i,i=t),x.precision(m)):[[r,o],[e,i]]},x.step=function(t){return arguments.length?x.majorStep(t).minorStep(t):x.minorStep()},x.majorStep=function(t){return arguments.length?(g=+t[0],v=+t[1],x):[g,v]},x.minorStep=function(t){return arguments.length?(p=+t[0],d=+t[1],x):[p,d]},x.precision=function(t){return arguments.length?(m=+t,c=Vn(o,i,90),u=Un(r,e,m),h=Vn(l,s,90),f=Un(a,n,m),x):m},x.majorExtent([[-180,-90+kt],[180,90-kt]]).minorExtent([[-180,-80-kt],[180,80+kt]])},t.geo.greatArc=function(){var e,r,n=qn,a=Hn;function i(){return{type:\"LineString\",coordinates:[e||n.apply(this,arguments),r||a.apply(this,arguments)]}}return i.distance=function(){return t.geo.distance(e||n.apply(this,arguments),r||a.apply(this,arguments))},i.source=function(t){return arguments.length?(n=t,e=\"function\"==typeof t?null:t,i):n},i.target=function(t){return arguments.length?(a=t,r=\"function\"==typeof t?null:t,i):a},i.precision=function(){return arguments.length?i:0},i},t.geo.interpolate=function(t,e){return r=t[0]*Lt,n=t[1]*Lt,a=e[0]*Lt,i=e[1]*Lt,o=Math.cos(n),s=Math.sin(n),l=Math.cos(i),c=Math.sin(i),u=o*Math.cos(r),h=o*Math.sin(r),f=l*Math.cos(a),p=l*Math.sin(a),d=2*Math.asin(Math.sqrt(Rt(i-n)+o*l*Rt(a-r))),g=1/Math.sin(d),(v=d?function(t){var e=Math.sin(t*=d)*g,r=Math.sin(d-t)*g,n=r*u+e*f,a=r*h+e*p,i=r*s+e*c;return[Math.atan2(a,n)*Ct,Math.atan2(i,Math.sqrt(n*n+a*a))*Ct]}:function(){return[r*Ct,n*Ct]}).distance=d,v;var r,n,a,i,o,s,l,c,u,h,f,p,d,g,v},t.geo.length=function(e){return bn=0,t.geo.stream(e,Gn),bn};var Gn={sphere:D,point:D,lineStart:function(){var t,e,r;function n(n,a){var i=Math.sin(a*=Lt),o=Math.cos(a),s=y((n*=Lt)-t),l=Math.cos(s);bn+=Math.atan2(Math.sqrt((s=o*Math.sin(s))*s+(s=r*i-e*o*l)*s),e*i+r*o*l),t=n,e=i,r=o}Gn.point=function(a,i){t=a*Lt,e=Math.sin(i*=Lt),r=Math.cos(i),Gn.point=n},Gn.lineEnd=function(){Gn.point=Gn.lineEnd=D}},lineEnd:D,polygonStart:D,polygonEnd:D};function Yn(t,e){function r(e,r){var n=Math.cos(e),a=Math.cos(r),i=t(n*a);return[i*a*Math.sin(e),i*Math.sin(r)]}return r.invert=function(t,r){var n=Math.sqrt(t*t+r*r),a=e(n),i=Math.sin(a),o=Math.cos(a);return[Math.atan2(t*i,n*o),Math.asin(n&&r*i/n)]},r}var Wn=Yn(function(t){return Math.sqrt(2/(1+t))},function(t){return 2*Math.asin(t/2)});(t.geo.azimuthalEqualArea=function(){return Cn(Wn)}).raw=Wn;var Xn=Yn(function(t){var e=Math.acos(t);return e&&e/Math.sin(e)},P);function Zn(t,e){var r=Math.cos(t),n=function(t){return Math.tan(Mt/4+t/2)},a=t===e?Math.sin(t):Math.log(r/Math.cos(e))/Math.log(n(e)/n(t)),i=r*Math.pow(n(t),a)/a;if(!a)return Qn;function o(t,e){i>0?e<-Et+kt&&(e=-Et+kt):e>Et-kt&&(e=Et-kt);var r=i/Math.pow(n(e),a);return[r*Math.sin(a*t),i-r*Math.cos(a*t)]}return o.invert=function(t,e){var r=i-e,n=Pt(a)*Math.sqrt(t*t+r*r);return[Math.atan2(t,r)/a,2*Math.atan(Math.pow(i/n,1/a))-Et]},o}function Jn(t,e){var r=Math.cos(t),n=t===e?Math.sin(t):(r-Math.cos(e))/(e-t),a=r/n+t;if(y(n)<kt)return zn;function i(t,e){var r=a-e;return[r*Math.sin(n*t),a-r*Math.cos(n*t)]}return i.invert=function(t,e){var r=a-e;return[Math.atan2(t,r)/n,a-Pt(n)*Math.sqrt(t*t+r*r)]},i}(t.geo.azimuthalEquidistant=function(){return Cn(Xn)}).raw=Xn,(t.geo.conicConformal=function(){return sn(Zn)}).raw=Zn,(t.geo.conicEquidistant=function(){return sn(Jn)}).raw=Jn;var Kn=Yn(function(t){return 1/t},Math.atan);function Qn(t,e){return[t,Math.log(Math.tan(Mt/4+e/2))]}function $n(t){var e,r=Cn(t),n=r.scale,a=r.translate,i=r.clipExtent;return r.scale=function(){var t=n.apply(r,arguments);return t===r?e?r.clipExtent(null):r:t},r.translate=function(){var t=a.apply(r,arguments);return t===r?e?r.clipExtent(null):r:t},r.clipExtent=function(t){var o=i.apply(r,arguments);if(o===r){if(e=null==t){var s=Mt*n(),l=a();i([[l[0]-s,l[1]-s],[l[0]+s,l[1]+s]])}}else e&&(o=null);return o},r.clipExtent(null)}(t.geo.gnomonic=function(){return Cn(Kn)}).raw=Kn,Qn.invert=function(t,e){return[t,2*Math.atan(Math.exp(e))-Et]},(t.geo.mercator=function(){return $n(Qn)}).raw=Qn;var ta=Yn(function(){return 1},Math.asin);(t.geo.orthographic=function(){return Cn(ta)}).raw=ta;var ea=Yn(function(t){return 1/(1+t)},function(t){return 2*Math.atan(t)});function ra(t,e){return[Math.log(Math.tan(Mt/4+e/2)),-t]}function na(t){return t[0]}function aa(t){return t[1]}function ia(t){for(var e=t.length,r=[0,1],n=2,a=2;a<e;a++){for(;n>1&&Ot(t[r[n-2]],t[r[n-1]],t[a])<=0;)--n;r[n++]=a}return r.slice(0,n)}function oa(t,e){return t[0]-e[0]||t[1]-e[1]}(t.geo.stereographic=function(){return Cn(ea)}).raw=ea,ra.invert=function(t,e){return[-e,2*Math.atan(Math.exp(t))-Et]},(t.geo.transverseMercator=function(){var t=$n(ra),e=t.center,r=t.rotate;return t.center=function(t){return t?e([-t[1],t[0]]):[(t=e())[1],-t[0]]},t.rotate=function(t){return t?r([t[0],t[1],t.length>2?t[2]+90:90]):[(t=r())[0],t[1],t[2]-90]},r([0,0,90])}).raw=ra,t.geom={},t.geom.hull=function(t){var e=na,r=aa;if(arguments.length)return n(t);function n(t){if(t.length<3)return[];var n,a=ve(e),i=ve(r),o=t.length,s=[],l=[];for(n=0;n<o;n++)s.push([+a.call(this,t[n],n),+i.call(this,t[n],n),n]);for(s.sort(oa),n=0;n<o;n++)l.push([s[n][0],-s[n][1]]);var c=ia(s),u=ia(l),h=u[0]===c[0],f=u[u.length-1]===c[c.length-1],p=[];for(n=c.length-1;n>=0;--n)p.push(t[s[c[n]][2]]);for(n=+h;n<u.length-f;++n)p.push(t[s[u[n]][2]]);return p}return n.x=function(t){return arguments.length?(e=t,n):e},n.y=function(t){return arguments.length?(r=t,n):r},n},t.geom.polygon=function(t){return U(t,sa),t};var sa=t.geom.polygon.prototype=[];function la(t,e,r){return(r[0]-e[0])*(t[1]-e[1])<(r[1]-e[1])*(t[0]-e[0])}function ca(t,e,r,n){var a=t[0],i=r[0],o=e[0]-a,s=n[0]-i,l=t[1],c=r[1],u=e[1]-l,h=n[1]-c,f=(s*(l-c)-h*(a-i))/(h*o-s*u);return[a+f*o,l+f*u]}function ua(t){var e=t[0],r=t[t.length-1];return!(e[0]-r[0]||e[1]-r[1])}sa.area=function(){for(var t,e=-1,r=this.length,n=this[r-1],a=0;++e<r;)t=n,n=this[e],a+=t[1]*n[0]-t[0]*n[1];return.5*a},sa.centroid=function(t){var e,r,n=-1,a=this.length,i=0,o=0,s=this[a-1];for(arguments.length||(t=-1/(6*this.area()));++n<a;)e=s,s=this[n],r=e[0]*s[1]-s[0]*e[1],i+=(e[0]+s[0])*r,o+=(e[1]+s[1])*r;return[i*t,o*t]},sa.clip=function(t){for(var e,r,n,a,i,o,s=ua(t),l=-1,c=this.length-ua(this),u=this[c-1];++l<c;){for(e=t.slice(),t.length=0,a=this[l],i=e[(n=e.length-s)-1],r=-1;++r<n;)la(o=e[r],u,a)?(la(i,u,a)||t.push(ca(i,o,u,a)),t.push(o)):la(i,u,a)&&t.push(ca(i,o,u,a)),i=o;s&&t.push(t[0]),u=a}return t};var ha,fa,pa,da,ga,va=[],ma=[];function ya(){Ra(this),this.edge=this.site=this.circle=null}function xa(t){var e=va.pop()||new ya;return e.site=t,e}function ba(t){La(t),pa.remove(t),va.push(t),Ra(t)}function _a(t){var e=t.circle,r=e.x,n=e.cy,a={x:r,y:n},i=t.P,o=t.N,s=[t];ba(t);for(var l=i;l.circle&&y(r-l.circle.x)<kt&&y(n-l.circle.cy)<kt;)i=l.P,s.unshift(l),ba(l),l=i;s.unshift(l),La(l);for(var c=o;c.circle&&y(r-c.circle.x)<kt&&y(n-c.circle.cy)<kt;)o=c.N,s.push(c),ba(c),c=o;s.push(c),La(c);var u,h=s.length;for(u=1;u<h;++u)c=s[u],l=s[u-1],za(c.edge,l.site,c.site,a);l=s[0],(c=s[h-1]).edge=Oa(l.site,c.site,null,a),Ea(l),Ea(c)}function wa(t){for(var e,r,n,a,i=t.x,o=t.y,s=pa._;s;)if((n=ka(s,o)-i)>kt)s=s.L;else{if(!((a=i-Ta(s,o))>kt)){n>-kt?(e=s.P,r=s):a>-kt?(e=s,r=s.N):e=r=s;break}if(!s.R){e=s;break}s=s.R}var l=xa(t);if(pa.insert(e,l),e||r){if(e===r)return La(e),r=xa(e.site),pa.insert(l,r),l.edge=r.edge=Oa(e.site,l.site),Ea(e),void Ea(r);if(r){La(e),La(r);var c=e.site,u=c.x,h=c.y,f=t.x-u,p=t.y-h,d=r.site,g=d.x-u,v=d.y-h,m=2*(f*v-p*g),y=f*f+p*p,x=g*g+v*v,b={x:(v*y-p*x)/m+u,y:(f*x-g*y)/m+h};za(r.edge,c,d,b),l.edge=Oa(c,t,null,b),r.edge=Oa(t,d,null,b),Ea(e),Ea(r)}else l.edge=Oa(e.site,l.site)}}function ka(t,e){var r=t.site,n=r.x,a=r.y,i=a-e;if(!i)return n;var o=t.P;if(!o)return-1/0;var s=(r=o.site).x,l=r.y,c=l-e;if(!c)return s;var u=s-n,h=1/i-1/c,f=u/c;return h?(-f+Math.sqrt(f*f-2*h*(u*u/(-2*c)-l+c/2+a-i/2)))/h+n:(n+s)/2}function Ta(t,e){var r=t.N;if(r)return ka(r,e);var n=t.site;return n.y===e?n.x:1/0}function Ma(t){this.site=t,this.edges=[]}function Aa(t,e){return e.angle-t.angle}function Sa(){Ra(this),this.x=this.y=this.arc=this.site=this.cy=null}function Ea(t){var e=t.P,r=t.N;if(e&&r){var n=e.site,a=t.site,i=r.site;if(n!==i){var o=a.x,s=a.y,l=n.x-o,c=n.y-s,u=i.x-o,h=2*(l*(v=i.y-s)-c*u);if(!(h>=-Tt)){var f=l*l+c*c,p=u*u+v*v,d=(v*f-c*p)/h,g=(l*p-u*f)/h,v=g+s,m=ma.pop()||new Sa;m.arc=t,m.site=a,m.x=d+o,m.y=v+Math.sqrt(d*d+g*g),m.cy=v,t.circle=m;for(var y=null,x=ga._;x;)if(m.y<x.y||m.y===x.y&&m.x<=x.x){if(!x.L){y=x.P;break}x=x.L}else{if(!x.R){y=x;break}x=x.R}ga.insert(y,m),y||(da=m)}}}}function La(t){var e=t.circle;e&&(e.P||(da=e.N),ga.remove(e),ma.push(e),Ra(e),t.circle=null)}function Ca(t,e){var r=t.b;if(r)return!0;var n,a,i=t.a,o=e[0][0],s=e[1][0],l=e[0][1],c=e[1][1],u=t.l,h=t.r,f=u.x,p=u.y,d=h.x,g=h.y,v=(f+d)/2,m=(p+g)/2;if(g===p){if(v<o||v>=s)return;if(f>d){if(i){if(i.y>=c)return}else i={x:v,y:l};r={x:v,y:c}}else{if(i){if(i.y<l)return}else i={x:v,y:c};r={x:v,y:l}}}else if(a=m-(n=(f-d)/(g-p))*v,n<-1||n>1)if(f>d){if(i){if(i.y>=c)return}else i={x:(l-a)/n,y:l};r={x:(c-a)/n,y:c}}else{if(i){if(i.y<l)return}else i={x:(c-a)/n,y:c};r={x:(l-a)/n,y:l}}else if(p<g){if(i){if(i.x>=s)return}else i={x:o,y:n*o+a};r={x:s,y:n*s+a}}else{if(i){if(i.x<o)return}else i={x:s,y:n*s+a};r={x:o,y:n*o+a}}return t.a=i,t.b=r,!0}function Pa(t,e){this.l=t,this.r=e,this.a=this.b=null}function Oa(t,e,r,n){var a=new Pa(t,e);return ha.push(a),r&&za(a,t,e,r),n&&za(a,e,t,n),fa[t.i].edges.push(new Ia(a,t,e)),fa[e.i].edges.push(new Ia(a,e,t)),a}function za(t,e,r,n){t.a||t.b?t.l===r?t.b=n:t.a=n:(t.a=n,t.l=e,t.r=r)}function Ia(t,e,r){var n=t.a,a=t.b;this.edge=t,this.site=e,this.angle=r?Math.atan2(r.y-e.y,r.x-e.x):t.l===e?Math.atan2(a.x-n.x,n.y-a.y):Math.atan2(n.x-a.x,a.y-n.y)}function Da(){this._=null}function Ra(t){t.U=t.C=t.L=t.R=t.P=t.N=null}function Fa(t,e){var r=e,n=e.R,a=r.U;a?a.L===r?a.L=n:a.R=n:t._=n,n.U=a,r.U=n,r.R=n.L,r.R&&(r.R.U=r),n.L=r}function Ba(t,e){var r=e,n=e.L,a=r.U;a?a.L===r?a.L=n:a.R=n:t._=n,n.U=a,r.U=n,r.L=n.R,r.L&&(r.L.U=r),n.R=r}function Na(t){for(;t.L;)t=t.L;return t}function ja(t,e){var r,n,a,i=t.sort(Va).pop();for(ha=[],fa=new Array(t.length),pa=new Da,ga=new Da;;)if(a=da,i&&(!a||i.y<a.y||i.y===a.y&&i.x<a.x))i.x===r&&i.y===n||(fa[i.i]=new Ma(i),wa(i),r=i.x,n=i.y),i=t.pop();else{if(!a)break;_a(a.arc)}e&&(function(t){for(var e,r=ha,n=nn(t[0][0],t[0][1],t[1][0],t[1][1]),a=r.length;a--;)(!Ca(e=r[a],t)||!n(e)||y(e.a.x-e.b.x)<kt&&y(e.a.y-e.b.y)<kt)&&(e.a=e.b=null,r.splice(a,1))}(e),function(t){for(var e,r,n,a,i,o,s,l,c,u,h=t[0][0],f=t[1][0],p=t[0][1],d=t[1][1],g=fa,v=g.length;v--;)if((i=g[v])&&i.prepare())for(l=(s=i.edges).length,o=0;o<l;)n=(u=s[o].end()).x,a=u.y,e=(c=s[++o%l].start()).x,r=c.y,(y(n-e)>kt||y(a-r)>kt)&&(s.splice(o,0,new Ia((m=i.site,x=u,b=y(n-h)<kt&&d-a>kt?{x:h,y:y(e-h)<kt?r:d}:y(a-d)<kt&&f-n>kt?{x:y(r-d)<kt?e:f,y:d}:y(n-f)<kt&&a-p>kt?{x:f,y:y(e-f)<kt?r:p}:y(a-p)<kt&&n-h>kt?{x:y(r-p)<kt?e:h,y:p}:null,_=void 0,_=new Pa(m,null),_.a=x,_.b=b,ha.push(_),_),i.site,null)),++l);var m,x,b,_}(e));var o={cells:fa,edges:ha};return pa=ga=ha=fa=null,o}function Va(t,e){return e.y-t.y||e.x-t.x}Ma.prototype.prepare=function(){for(var t,e=this.edges,r=e.length;r--;)(t=e[r].edge).b&&t.a||e.splice(r,1);return e.sort(Aa),e.length},Ia.prototype={start:function(){return this.edge.l===this.site?this.edge.a:this.edge.b},end:function(){return this.edge.l===this.site?this.edge.b:this.edge.a}},Da.prototype={insert:function(t,e){var r,n,a;if(t){if(e.P=t,e.N=t.N,t.N&&(t.N.P=e),t.N=e,t.R){for(t=t.R;t.L;)t=t.L;t.L=e}else t.R=e;r=t}else this._?(t=Na(this._),e.P=null,e.N=t,t.P=t.L=e,r=t):(e.P=e.N=null,this._=e,r=null);for(e.L=e.R=null,e.U=r,e.C=!0,t=e;r&&r.C;)r===(n=r.U).L?(a=n.R)&&a.C?(r.C=a.C=!1,n.C=!0,t=n):(t===r.R&&(Fa(this,r),r=(t=r).U),r.C=!1,n.C=!0,Ba(this,n)):(a=n.L)&&a.C?(r.C=a.C=!1,n.C=!0,t=n):(t===r.L&&(Ba(this,r),r=(t=r).U),r.C=!1,n.C=!0,Fa(this,n)),r=t.U;this._.C=!1},remove:function(t){t.N&&(t.N.P=t.P),t.P&&(t.P.N=t.N),t.N=t.P=null;var e,r,n,a=t.U,i=t.L,o=t.R;if(r=i?o?Na(o):i:o,a?a.L===t?a.L=r:a.R=r:this._=r,i&&o?(n=r.C,r.C=t.C,r.L=i,i.U=r,r!==o?(a=r.U,r.U=t.U,t=r.R,a.L=t,r.R=o,o.U=r):(r.U=a,a=r,t=r.R)):(n=t.C,t=r),t&&(t.U=a),!n)if(t&&t.C)t.C=!1;else{do{if(t===this._)break;if(t===a.L){if((e=a.R).C&&(e.C=!1,a.C=!0,Fa(this,a),e=a.R),e.L&&e.L.C||e.R&&e.R.C){e.R&&e.R.C||(e.L.C=!1,e.C=!0,Ba(this,e),e=a.R),e.C=a.C,a.C=e.R.C=!1,Fa(this,a),t=this._;break}}else if((e=a.L).C&&(e.C=!1,a.C=!0,Ba(this,a),e=a.L),e.L&&e.L.C||e.R&&e.R.C){e.L&&e.L.C||(e.R.C=!1,e.C=!0,Fa(this,e),e=a.L),e.C=a.C,a.C=e.L.C=!1,Ba(this,a),t=this._;break}e.C=!0,t=a,a=a.U}while(!t.C);t&&(t.C=!1)}}},t.geom.voronoi=function(t){var e=na,r=aa,n=e,a=r,i=Ua;if(t)return o(t);function o(t){var e=new Array(t.length),r=i[0][0],n=i[0][1],a=i[1][0],o=i[1][1];return ja(s(t),i).cells.forEach(function(i,s){var l=i.edges,c=i.site;(e[s]=l.length?l.map(function(t){var e=t.start();return[e.x,e.y]}):c.x>=r&&c.x<=a&&c.y>=n&&c.y<=o?[[r,o],[a,o],[a,n],[r,n]]:[]).point=t[s]}),e}function s(t){return t.map(function(t,e){return{x:Math.round(n(t,e)/kt)*kt,y:Math.round(a(t,e)/kt)*kt,i:e}})}return o.links=function(t){return ja(s(t)).edges.filter(function(t){return t.l&&t.r}).map(function(e){return{source:t[e.l.i],target:t[e.r.i]}})},o.triangles=function(t){var e=[];return ja(s(t)).cells.forEach(function(r,n){for(var a,i,o,s,l=r.site,c=r.edges.sort(Aa),u=-1,h=c.length,f=c[h-1].edge,p=f.l===l?f.r:f.l;++u<h;)f,a=p,p=(f=c[u].edge).l===l?f.r:f.l,n<a.i&&n<p.i&&(o=a,s=p,((i=l).x-s.x)*(o.y-i.y)-(i.x-o.x)*(s.y-i.y)<0)&&e.push([t[n],t[a.i],t[p.i]])}),e},o.x=function(t){return arguments.length?(n=ve(e=t),o):e},o.y=function(t){return arguments.length?(a=ve(r=t),o):r},o.clipExtent=function(t){return arguments.length?(i=null==t?Ua:t,o):i===Ua?null:i},o.size=function(t){return arguments.length?o.clipExtent(t&&[[0,0],t]):i===Ua?null:i&&i[1]},o};var Ua=[[-1e6,-1e6],[1e6,1e6]];function qa(t){return t.x}function Ha(t){return t.y}function Ga(e,r){e=t.rgb(e),r=t.rgb(r);var n=e.r,a=e.g,i=e.b,o=r.r-n,s=r.g-a,l=r.b-i;return function(t){return\"#\"+ce(Math.round(n+o*t))+ce(Math.round(a+s*t))+ce(Math.round(i+l*t))}}function Ya(t,e){var r,n={},a={};for(r in t)r in e?n[r]=Ka(t[r],e[r]):a[r]=t[r];for(r in e)r in t||(a[r]=e[r]);return function(t){for(r in n)a[r]=n[r](t);return a}}function Wa(t,e){return t=+t,e=+e,function(r){return t*(1-r)+e*r}}function Xa(t,e){var r,n,a,i=Za.lastIndex=Ja.lastIndex=0,o=-1,s=[],l=[];for(t+=\"\",e+=\"\";(r=Za.exec(t))&&(n=Ja.exec(e));)(a=n.index)>i&&(a=e.slice(i,a),s[o]?s[o]+=a:s[++o]=a),(r=r[0])===(n=n[0])?s[o]?s[o]+=n:s[++o]=n:(s[++o]=null,l.push({i:o,x:Wa(r,n)})),i=Ja.lastIndex;return i<e.length&&(a=e.slice(i),s[o]?s[o]+=a:s[++o]=a),s.length<2?l[0]?(e=l[0].x,function(t){return e(t)+\"\"}):function(){return e}:(e=l.length,function(t){for(var r,n=0;n<e;++n)s[(r=l[n]).i]=r.x(t);return s.join(\"\")})}t.geom.delaunay=function(e){return t.geom.voronoi().triangles(e)},t.geom.quadtree=function(t,e,r,n,a){var i,o=na,s=aa;if(i=arguments.length)return o=qa,s=Ha,3===i&&(a=r,n=e,r=e=0),l(t);function l(t){var l,c,u,h,f,p,d,g,v,m=ve(o),x=ve(s);if(null!=e)p=e,d=r,g=n,v=a;else if(g=v=-(p=d=1/0),c=[],u=[],f=t.length,i)for(h=0;h<f;++h)(l=t[h]).x<p&&(p=l.x),l.y<d&&(d=l.y),l.x>g&&(g=l.x),l.y>v&&(v=l.y),c.push(l.x),u.push(l.y);else for(h=0;h<f;++h){var b=+m(l=t[h],h),_=+x(l,h);b<p&&(p=b),_<d&&(d=_),b>g&&(g=b),_>v&&(v=_),c.push(b),u.push(_)}var w=g-p,k=v-d;function T(t,e,r,n,a,i,o,s){if(!isNaN(r)&&!isNaN(n))if(t.leaf){var l=t.x,c=t.y;if(null!=l)if(y(l-r)+y(c-n)<.01)M(t,e,r,n,a,i,o,s);else{var u=t.point;t.x=t.y=t.point=null,M(t,u,l,c,a,i,o,s),M(t,e,r,n,a,i,o,s)}else t.x=r,t.y=n,t.point=e}else M(t,e,r,n,a,i,o,s)}function M(t,e,r,n,a,i,o,s){var l=.5*(a+o),c=.5*(i+s),u=r>=l,h=n>=c,f=h<<1|u;t.leaf=!1,u?a=l:o=l,h?i=c:s=c,T(t=t.nodes[f]||(t.nodes[f]={leaf:!0,nodes:[],point:null,x:null,y:null}),e,r,n,a,i,o,s)}w>k?v=d+w:g=p+k;var A={leaf:!0,nodes:[],point:null,x:null,y:null,add:function(t){T(A,t,+m(t,++h),+x(t,h),p,d,g,v)}};if(A.visit=function(t){!function t(e,r,n,a,i,o){if(!e(r,n,a,i,o)){var s=.5*(n+i),l=.5*(a+o),c=r.nodes;c[0]&&t(e,c[0],n,a,s,l),c[1]&&t(e,c[1],s,a,i,l),c[2]&&t(e,c[2],n,l,s,o),c[3]&&t(e,c[3],s,l,i,o)}}(t,A,p,d,g,v)},A.find=function(t){return function(t,e,r,n,a,i,o){var s,l=1/0;return function t(c,u,h,f,p){if(!(u>i||h>o||f<n||p<a)){if(d=c.point){var d,g=e-c.x,v=r-c.y,m=g*g+v*v;if(m<l){var y=Math.sqrt(l=m);n=e-y,a=r-y,i=e+y,o=r+y,s=d}}for(var x=c.nodes,b=.5*(u+f),_=.5*(h+p),w=(r>=_)<<1|e>=b,k=w+4;w<k;++w)if(c=x[3&w])switch(3&w){case 0:t(c,u,h,b,_);break;case 1:t(c,b,h,f,_);break;case 2:t(c,u,_,b,p);break;case 3:t(c,b,_,f,p)}}}(t,n,a,i,o),s}(A,t[0],t[1],p,d,g,v)},h=-1,null==e){for(;++h<f;)T(A,t[h],c[h],u[h],p,d,g,v);--h}else t.forEach(A.add);return c=u=t=l=null,A}return l.x=function(t){return arguments.length?(o=t,l):o},l.y=function(t){return arguments.length?(s=t,l):s},l.extent=function(t){return arguments.length?(null==t?e=r=n=a=null:(e=+t[0][0],r=+t[0][1],n=+t[1][0],a=+t[1][1]),l):null==e?null:[[e,r],[n,a]]},l.size=function(t){return arguments.length?(null==t?e=r=n=a=null:(e=r=0,n=+t[0],a=+t[1]),l):null==e?null:[n-e,a-r]},l},t.interpolateRgb=Ga,t.interpolateObject=Ya,t.interpolateNumber=Wa,t.interpolateString=Xa;var Za=/[-+]?(?:\\d+\\.?\\d*|\\.?\\d+)(?:[eE][-+]?\\d+)?/g,Ja=new RegExp(Za.source,\"g\");function Ka(e,r){for(var n,a=t.interpolators.length;--a>=0&&!(n=t.interpolators[a](e,r)););return n}function Qa(t,e){var r,n=[],a=[],i=t.length,o=e.length,s=Math.min(t.length,e.length);for(r=0;r<s;++r)n.push(Ka(t[r],e[r]));for(;r<i;++r)a[r]=t[r];for(;r<o;++r)a[r]=e[r];return function(t){for(r=0;r<s;++r)a[r]=n[r](t);return a}}t.interpolate=Ka,t.interpolators=[function(t,e){var r=typeof e;return(\"string\"===r?ge.has(e.toLowerCase())||/^(#|rgb\\(|hsl\\()/i.test(e)?Ga:Xa:e instanceof Vt?Ga:Array.isArray(e)?Qa:\"object\"===r&&isNaN(e)?Ya:Wa)(t,e)}],t.interpolateArray=Qa;var $a=function(){return P},ti=t.map({linear:$a,poly:function(t){return function(e){return Math.pow(e,t)}},quad:function(){return ai},cubic:function(){return ii},sin:function(){return si},exp:function(){return li},circle:function(){return ci},elastic:function(t,e){var r;arguments.length<2&&(e=.45);arguments.length?r=e/At*Math.asin(1/t):(t=1,r=e/4);return function(n){return 1+t*Math.pow(2,-10*n)*Math.sin((n-r)*At/e)}},back:function(t){t||(t=1.70158);return function(e){return e*e*((t+1)*e-t)}},bounce:function(){return ui}}),ei=t.map({in:P,out:ri,\"in-out\":ni,\"out-in\":function(t){return ni(ri(t))}});function ri(t){return function(e){return 1-t(1-e)}}function ni(t){return function(e){return.5*(e<.5?t(2*e):2-t(2-2*e))}}function ai(t){return t*t}function ii(t){return t*t*t}function oi(t){if(t<=0)return 0;if(t>=1)return 1;var e=t*t,r=e*t;return 4*(t<.5?r:3*(t-e)+r-.75)}function si(t){return 1-Math.cos(t*Et)}function li(t){return Math.pow(2,10*(t-1))}function ci(t){return 1-Math.sqrt(1-t*t)}function ui(t){return t<1/2.75?7.5625*t*t:t<2/2.75?7.5625*(t-=1.5/2.75)*t+.75:t<2.5/2.75?7.5625*(t-=2.25/2.75)*t+.9375:7.5625*(t-=2.625/2.75)*t+.984375}function hi(t,e){return e-=t,function(r){return Math.round(t+e*r)}}function fi(t){var e,r,n,a=[t.a,t.b],i=[t.c,t.d],o=di(a),s=pi(a,i),l=di(((e=i)[0]+=(n=-s)*(r=a)[0],e[1]+=n*r[1],e))||0;a[0]*i[1]<i[0]*a[1]&&(a[0]*=-1,a[1]*=-1,o*=-1,s*=-1),this.rotate=(o?Math.atan2(a[1],a[0]):Math.atan2(-i[0],i[1]))*Ct,this.translate=[t.e,t.f],this.scale=[o,l],this.skew=l?Math.atan2(s,l)*Ct:0}function pi(t,e){return t[0]*e[0]+t[1]*e[1]}function di(t){var e=Math.sqrt(pi(t,t));return e&&(t[0]/=e,t[1]/=e),e}t.ease=function(t){var e,n=t.indexOf(\"-\"),a=n>=0?t.slice(0,n):t,i=n>=0?t.slice(n+1):\"in\";return a=ti.get(a)||$a,i=ei.get(i)||P,e=i(a.apply(null,r.call(arguments,1))),function(t){return t<=0?0:t>=1?1:e(t)}},t.interpolateHcl=function(e,r){e=t.hcl(e),r=t.hcl(r);var n=e.h,a=e.c,i=e.l,o=r.h-n,s=r.c-a,l=r.l-i;isNaN(s)&&(s=0,a=isNaN(a)?r.c:a);isNaN(o)?(o=0,n=isNaN(n)?r.h:n):o>180?o-=360:o<-180&&(o+=360);return function(t){return Wt(n+o*t,a+s*t,i+l*t)+\"\"}},t.interpolateHsl=function(e,r){e=t.hsl(e),r=t.hsl(r);var n=e.h,a=e.s,i=e.l,o=r.h-n,s=r.s-a,l=r.l-i;isNaN(s)&&(s=0,a=isNaN(a)?r.s:a);isNaN(o)?(o=0,n=isNaN(n)?r.h:n):o>180?o-=360:o<-180&&(o+=360);return function(t){return Ht(n+o*t,a+s*t,i+l*t)+\"\"}},t.interpolateLab=function(e,r){e=t.lab(e),r=t.lab(r);var n=e.l,a=e.a,i=e.b,o=r.l-n,s=r.a-a,l=r.b-i;return function(t){return te(n+o*t,a+s*t,i+l*t)+\"\"}},t.interpolateRound=hi,t.transform=function(e){var r=a.createElementNS(t.ns.prefix.svg,\"g\");return(t.transform=function(t){if(null!=t){r.setAttribute(\"transform\",t);var e=r.transform.baseVal.consolidate()}return new fi(e?e.matrix:gi)})(e)},fi.prototype.toString=function(){return\"translate(\"+this.translate+\")rotate(\"+this.rotate+\")skewX(\"+this.skew+\")scale(\"+this.scale+\")\"};var gi={a:1,b:0,c:0,d:1,e:0,f:0};function vi(t){return t.length?t.pop()+\",\":\"\"}function mi(e,r){var n=[],a=[];return e=t.transform(e),r=t.transform(r),function(t,e,r,n){if(t[0]!==e[0]||t[1]!==e[1]){var a=r.push(\"translate(\",null,\",\",null,\")\");n.push({i:a-4,x:Wa(t[0],e[0])},{i:a-2,x:Wa(t[1],e[1])})}else(e[0]||e[1])&&r.push(\"translate(\"+e+\")\")}(e.translate,r.translate,n,a),function(t,e,r,n){t!==e?(t-e>180?e+=360:e-t>180&&(t+=360),n.push({i:r.push(vi(r)+\"rotate(\",null,\")\")-2,x:Wa(t,e)})):e&&r.push(vi(r)+\"rotate(\"+e+\")\")}(e.rotate,r.rotate,n,a),function(t,e,r,n){t!==e?n.push({i:r.push(vi(r)+\"skewX(\",null,\")\")-2,x:Wa(t,e)}):e&&r.push(vi(r)+\"skewX(\"+e+\")\")}(e.skew,r.skew,n,a),function(t,e,r,n){if(t[0]!==e[0]||t[1]!==e[1]){var a=r.push(vi(r)+\"scale(\",null,\",\",null,\")\");n.push({i:a-4,x:Wa(t[0],e[0])},{i:a-2,x:Wa(t[1],e[1])})}else 1===e[0]&&1===e[1]||r.push(vi(r)+\"scale(\"+e+\")\")}(e.scale,r.scale,n,a),e=r=null,function(t){for(var e,r=-1,i=a.length;++r<i;)n[(e=a[r]).i]=e.x(t);return n.join(\"\")}}function yi(t,e){return e=(e-=t=+t)||1/e,function(r){return(r-t)/e}}function xi(t,e){return e=(e-=t=+t)||1/e,function(r){return Math.max(0,Math.min(1,(r-t)/e))}}function bi(t){for(var e=t.source,r=t.target,n=function(t,e){if(t===e)return t;var r=_i(t),n=_i(e),a=r.pop(),i=n.pop(),o=null;for(;a===i;)o=a,a=r.pop(),i=n.pop();return o}(e,r),a=[e];e!==n;)e=e.parent,a.push(e);for(var i=a.length;r!==n;)a.splice(i,0,r),r=r.parent;return a}function _i(t){for(var e=[],r=t.parent;null!=r;)e.push(t),t=r,r=r.parent;return e.push(t),e}function wi(t){t.fixed|=2}function ki(t){t.fixed&=-7}function Ti(t){t.fixed|=4,t.px=t.x,t.py=t.y}function Mi(t){t.fixed&=-5}t.interpolateTransform=mi,t.layout={},t.layout.bundle=function(){return function(t){for(var e=[],r=-1,n=t.length;++r<n;)e.push(bi(t[r]));return e}},t.layout.chord=function(){var e,r,n,a,i,o,s,l={},c=0;function u(){var l,u,f,p,d,g={},v=[],m=t.range(a),y=[];for(e=[],r=[],l=0,p=-1;++p<a;){for(u=0,d=-1;++d<a;)u+=n[p][d];v.push(u),y.push(t.range(a)),l+=u}for(i&&m.sort(function(t,e){return i(v[t],v[e])}),o&&y.forEach(function(t,e){t.sort(function(t,r){return o(n[e][t],n[e][r])})}),l=(At-c*a)/l,u=0,p=-1;++p<a;){for(f=u,d=-1;++d<a;){var x=m[p],b=y[x][d],_=n[x][b],w=u,k=u+=_*l;g[x+\"-\"+b]={index:x,subindex:b,startAngle:w,endAngle:k,value:_}}r[x]={index:x,startAngle:f,endAngle:u,value:v[x]},u+=c}for(p=-1;++p<a;)for(d=p-1;++d<a;){var T=g[p+\"-\"+d],M=g[d+\"-\"+p];(T.value||M.value)&&e.push(T.value<M.value?{source:M,target:T}:{source:T,target:M})}s&&h()}function h(){e.sort(function(t,e){return s((t.source.value+t.target.value)/2,(e.source.value+e.target.value)/2)})}return l.matrix=function(t){return arguments.length?(a=(n=t)&&n.length,e=r=null,l):n},l.padding=function(t){return arguments.length?(c=t,e=r=null,l):c},l.sortGroups=function(t){return arguments.length?(i=t,e=r=null,l):i},l.sortSubgroups=function(t){return arguments.length?(o=t,e=null,l):o},l.sortChords=function(t){return arguments.length?(s=t,e&&h(),l):s},l.chords=function(){return e||u(),e},l.groups=function(){return r||u(),r},l},t.layout.force=function(){var e,r,n,a,i,o,s={},l=t.dispatch(\"start\",\"tick\",\"end\"),c=[1,1],u=.9,h=Ai,f=Si,p=-30,d=Ei,g=.1,v=.64,m=[],y=[];function x(t){return function(e,r,n,a){if(e.point!==t){var i=e.cx-t.x,o=e.cy-t.y,s=a-r,l=i*i+o*o;if(s*s/v<l){if(l<d){var c=e.charge/l;t.px-=i*c,t.py-=o*c}return!0}if(e.point&&l&&l<d){c=e.pointCharge/l;t.px-=i*c,t.py-=o*c}}return!e.charge}}function b(e){e.px=t.event.x,e.py=t.event.y,s.resume()}return s.tick=function(){if((n*=.99)<.005)return e=null,l.end({type:\"end\",alpha:n=0}),!0;var r,s,h,f,d,v,b,_,w,k=m.length,T=y.length;for(s=0;s<T;++s)f=(h=y[s]).source,(v=(_=(d=h.target).x-f.x)*_+(w=d.y-f.y)*w)&&(_*=v=n*i[s]*((v=Math.sqrt(v))-a[s])/v,w*=v,d.x-=_*(b=f.weight+d.weight?f.weight/(f.weight+d.weight):.5),d.y-=w*b,f.x+=_*(b=1-b),f.y+=w*b);if((b=n*g)&&(_=c[0]/2,w=c[1]/2,s=-1,b))for(;++s<k;)(h=m[s]).x+=(_-h.x)*b,h.y+=(w-h.y)*b;if(p)for(!function t(e,r,n){var a=0,i=0;e.charge=0;if(!e.leaf)for(var o,s=e.nodes,l=s.length,c=-1;++c<l;)null!=(o=s[c])&&(t(o,r,n),e.charge+=o.charge,a+=o.charge*o.cx,i+=o.charge*o.cy);if(e.point){e.leaf||(e.point.x+=Math.random()-.5,e.point.y+=Math.random()-.5);var u=r*n[e.point.index];e.charge+=e.pointCharge=u,a+=u*e.point.x,i+=u*e.point.y}e.cx=a/e.charge;e.cy=i/e.charge}(r=t.geom.quadtree(m),n,o),s=-1;++s<k;)(h=m[s]).fixed||r.visit(x(h));for(s=-1;++s<k;)(h=m[s]).fixed?(h.x=h.px,h.y=h.py):(h.x-=(h.px-(h.px=h.x))*u,h.y-=(h.py-(h.py=h.y))*u);l.tick({type:\"tick\",alpha:n})},s.nodes=function(t){return arguments.length?(m=t,s):m},s.links=function(t){return arguments.length?(y=t,s):y},s.size=function(t){return arguments.length?(c=t,s):c},s.linkDistance=function(t){return arguments.length?(h=\"function\"==typeof t?t:+t,s):h},s.distance=s.linkDistance,s.linkStrength=function(t){return arguments.length?(f=\"function\"==typeof t?t:+t,s):f},s.friction=function(t){return arguments.length?(u=+t,s):u},s.charge=function(t){return arguments.length?(p=\"function\"==typeof t?t:+t,s):p},s.chargeDistance=function(t){return arguments.length?(d=t*t,s):Math.sqrt(d)},s.gravity=function(t){return arguments.length?(g=+t,s):g},s.theta=function(t){return arguments.length?(v=t*t,s):Math.sqrt(v)},s.alpha=function(t){return arguments.length?(t=+t,n?t>0?n=t:(e.c=null,e.t=NaN,e=null,l.end({type:\"end\",alpha:n=0})):t>0&&(l.start({type:\"start\",alpha:n=t}),e=Te(s.tick)),s):n},s.start=function(){var t,e,r,n=m.length,l=y.length,u=c[0],d=c[1];for(t=0;t<n;++t)(r=m[t]).index=t,r.weight=0;for(t=0;t<l;++t)\"number\"==typeof(r=y[t]).source&&(r.source=m[r.source]),\"number\"==typeof r.target&&(r.target=m[r.target]),++r.source.weight,++r.target.weight;for(t=0;t<n;++t)r=m[t],isNaN(r.x)&&(r.x=g(\"x\",u)),isNaN(r.y)&&(r.y=g(\"y\",d)),isNaN(r.px)&&(r.px=r.x),isNaN(r.py)&&(r.py=r.y);if(a=[],\"function\"==typeof h)for(t=0;t<l;++t)a[t]=+h.call(this,y[t],t);else for(t=0;t<l;++t)a[t]=h;if(i=[],\"function\"==typeof f)for(t=0;t<l;++t)i[t]=+f.call(this,y[t],t);else for(t=0;t<l;++t)i[t]=f;if(o=[],\"function\"==typeof p)for(t=0;t<n;++t)o[t]=+p.call(this,m[t],t);else for(t=0;t<n;++t)o[t]=p;function g(r,a){if(!e){for(e=new Array(n),c=0;c<n;++c)e[c]=[];for(c=0;c<l;++c){var i=y[c];e[i.source.index].push(i.target),e[i.target.index].push(i.source)}}for(var o,s=e[t],c=-1,u=s.length;++c<u;)if(!isNaN(o=s[c][r]))return o;return Math.random()*a}return s.resume()},s.resume=function(){return s.alpha(.1)},s.stop=function(){return s.alpha(0)},s.drag=function(){if(r||(r=t.behavior.drag().origin(P).on(\"dragstart.force\",wi).on(\"drag.force\",b).on(\"dragend.force\",ki)),!arguments.length)return r;this.on(\"mouseover.force\",Ti).on(\"mouseout.force\",Mi).call(r)},t.rebind(s,l,\"on\")};var Ai=20,Si=1,Ei=1/0;function Li(e,r){return t.rebind(e,r,\"sort\",\"children\",\"value\"),e.nodes=e,e.links=Di,e}function Ci(t,e){for(var r=[t];null!=(t=r.pop());)if(e(t),(a=t.children)&&(n=a.length))for(var n,a;--n>=0;)r.push(a[n])}function Pi(t,e){for(var r=[t],n=[];null!=(t=r.pop());)if(n.push(t),(i=t.children)&&(a=i.length))for(var a,i,o=-1;++o<a;)r.push(i[o]);for(;null!=(t=n.pop());)e(t)}function Oi(t){return t.children}function zi(t){return t.value}function Ii(t,e){return e.value-t.value}function Di(e){return t.merge(e.map(function(t){return(t.children||[]).map(function(e){return{source:t,target:e}})}))}t.layout.hierarchy=function(){var t=Ii,e=Oi,r=zi;function n(a){var i,o=[a],s=[];for(a.depth=0;null!=(i=o.pop());)if(s.push(i),(c=e.call(n,i,i.depth))&&(l=c.length)){for(var l,c,u;--l>=0;)o.push(u=c[l]),u.parent=i,u.depth=i.depth+1;r&&(i.value=0),i.children=c}else r&&(i.value=+r.call(n,i,i.depth)||0),delete i.children;return Pi(a,function(e){var n,a;t&&(n=e.children)&&n.sort(t),r&&(a=e.parent)&&(a.value+=e.value)}),s}return n.sort=function(e){return arguments.length?(t=e,n):t},n.children=function(t){return arguments.length?(e=t,n):e},n.value=function(t){return arguments.length?(r=t,n):r},n.revalue=function(t){return r&&(Ci(t,function(t){t.children&&(t.value=0)}),Pi(t,function(t){var e;t.children||(t.value=+r.call(n,t,t.depth)||0),(e=t.parent)&&(e.value+=t.value)})),t},n},t.layout.partition=function(){var e=t.layout.hierarchy(),r=[1,1];function n(t,n){var a=e.call(this,t,n);return function t(e,r,n,a){var i=e.children;if(e.x=r,e.y=e.depth*a,e.dx=n,e.dy=a,i&&(o=i.length)){var o,s,l,c=-1;for(n=e.value?n/e.value:0;++c<o;)t(s=i[c],r,l=s.value*n,a),r+=l}}(a[0],0,r[0],r[1]/function t(e){var r=e.children,n=0;if(r&&(a=r.length))for(var a,i=-1;++i<a;)n=Math.max(n,t(r[i]));return 1+n}(a[0])),a}return n.size=function(t){return arguments.length?(r=t,n):r},Li(n,e)},t.layout.pie=function(){var e=Number,r=Ri,n=0,a=At,i=0;function o(s){var l,c=s.length,u=s.map(function(t,r){return+e.call(o,t,r)}),h=+(\"function\"==typeof n?n.apply(this,arguments):n),f=(\"function\"==typeof a?a.apply(this,arguments):a)-h,p=Math.min(Math.abs(f)/c,+(\"function\"==typeof i?i.apply(this,arguments):i)),d=p*(f<0?-1:1),g=t.sum(u),v=g?(f-c*d)/g:0,m=t.range(c),y=[];return null!=r&&m.sort(r===Ri?function(t,e){return u[e]-u[t]}:function(t,e){return r(s[t],s[e])}),m.forEach(function(t){y[t]={data:s[t],value:l=u[t],startAngle:h,endAngle:h+=l*v+d,padAngle:p}}),y}return o.value=function(t){return arguments.length?(e=t,o):e},o.sort=function(t){return arguments.length?(r=t,o):r},o.startAngle=function(t){return arguments.length?(n=t,o):n},o.endAngle=function(t){return arguments.length?(a=t,o):a},o.padAngle=function(t){return arguments.length?(i=t,o):i},o};var Ri={};function Fi(t){return t.x}function Bi(t){return t.y}function Ni(t,e,r){t.y0=e,t.y=r}t.layout.stack=function(){var e=P,r=Ui,n=qi,a=Ni,i=Fi,o=Bi;function s(l,c){if(!(p=l.length))return l;var u=l.map(function(t,r){return e.call(s,t,r)}),h=u.map(function(t){return t.map(function(t,e){return[i.call(s,t,e),o.call(s,t,e)]})}),f=r.call(s,h,c);u=t.permute(u,f),h=t.permute(h,f);var p,d,g,v,m=n.call(s,h,c),y=u[0].length;for(g=0;g<y;++g)for(a.call(s,u[0][g],v=m[g],h[0][g][1]),d=1;d<p;++d)a.call(s,u[d][g],v+=h[d-1][g][1],h[d][g][1]);return l}return s.values=function(t){return arguments.length?(e=t,s):e},s.order=function(t){return arguments.length?(r=\"function\"==typeof t?t:ji.get(t)||Ui,s):r},s.offset=function(t){return arguments.length?(n=\"function\"==typeof t?t:Vi.get(t)||qi,s):n},s.x=function(t){return arguments.length?(i=t,s):i},s.y=function(t){return arguments.length?(o=t,s):o},s.out=function(t){return arguments.length?(a=t,s):a},s};var ji=t.map({\"inside-out\":function(e){var r,n,a=e.length,i=e.map(Hi),o=e.map(Gi),s=t.range(a).sort(function(t,e){return i[t]-i[e]}),l=0,c=0,u=[],h=[];for(r=0;r<a;++r)n=s[r],l<c?(l+=o[n],u.push(n)):(c+=o[n],h.push(n));return h.reverse().concat(u)},reverse:function(e){return t.range(e.length).reverse()},default:Ui}),Vi=t.map({silhouette:function(t){var e,r,n,a=t.length,i=t[0].length,o=[],s=0,l=[];for(r=0;r<i;++r){for(e=0,n=0;e<a;e++)n+=t[e][r][1];n>s&&(s=n),o.push(n)}for(r=0;r<i;++r)l[r]=(s-o[r])/2;return l},wiggle:function(t){var e,r,n,a,i,o,s,l,c,u=t.length,h=t[0],f=h.length,p=[];for(p[0]=l=c=0,r=1;r<f;++r){for(e=0,a=0;e<u;++e)a+=t[e][r][1];for(e=0,i=0,s=h[r][0]-h[r-1][0];e<u;++e){for(n=0,o=(t[e][r][1]-t[e][r-1][1])/(2*s);n<e;++n)o+=(t[n][r][1]-t[n][r-1][1])/s;i+=o*t[e][r][1]}p[r]=l-=a?i/a*s:0,l<c&&(c=l)}for(r=0;r<f;++r)p[r]-=c;return p},expand:function(t){var e,r,n,a=t.length,i=t[0].length,o=1/a,s=[];for(r=0;r<i;++r){for(e=0,n=0;e<a;e++)n+=t[e][r][1];if(n)for(e=0;e<a;e++)t[e][r][1]/=n;else for(e=0;e<a;e++)t[e][r][1]=o}for(r=0;r<i;++r)s[r]=0;return s},zero:qi});function Ui(e){return t.range(e.length)}function qi(t){for(var e=-1,r=t[0].length,n=[];++e<r;)n[e]=0;return n}function Hi(t){for(var e,r=1,n=0,a=t[0][1],i=t.length;r<i;++r)(e=t[r][1])>a&&(n=r,a=e);return n}function Gi(t){return t.reduce(Yi,0)}function Yi(t,e){return t+e[1]}function Wi(t,e){return Xi(t,Math.ceil(Math.log(e.length)/Math.LN2+1))}function Xi(t,e){for(var r=-1,n=+t[0],a=(t[1]-n)/e,i=[];++r<=e;)i[r]=a*r+n;return i}function Zi(e){return[t.min(e),t.max(e)]}function Ji(t,e){return t.value-e.value}function Ki(t,e){var r=t._pack_next;t._pack_next=e,e._pack_prev=t,e._pack_next=r,r._pack_prev=e}function Qi(t,e){t._pack_next=e,e._pack_prev=t}function $i(t,e){var r=e.x-t.x,n=e.y-t.y,a=t.r+e.r;return.999*a*a>r*r+n*n}function to(t){if((e=t.children)&&(l=e.length)){var e,r,n,a,i,o,s,l,c=1/0,u=-1/0,h=1/0,f=-1/0;if(e.forEach(eo),(r=e[0]).x=-r.r,r.y=0,x(r),l>1&&((n=e[1]).x=n.r,n.y=0,x(n),l>2))for(no(r,n,a=e[2]),x(a),Ki(r,a),r._pack_prev=a,Ki(a,n),n=r._pack_next,i=3;i<l;i++){no(r,n,a=e[i]);var p=0,d=1,g=1;for(o=n._pack_next;o!==n;o=o._pack_next,d++)if($i(o,a)){p=1;break}if(1==p)for(s=r._pack_prev;s!==o._pack_prev&&!$i(s,a);s=s._pack_prev,g++);p?(d<g||d==g&&n.r<r.r?Qi(r,n=o):Qi(r=s,n),i--):(Ki(r,a),n=a,x(a))}var v=(c+u)/2,m=(h+f)/2,y=0;for(i=0;i<l;i++)(a=e[i]).x-=v,a.y-=m,y=Math.max(y,a.r+Math.sqrt(a.x*a.x+a.y*a.y));t.r=y,e.forEach(ro)}function x(t){c=Math.min(t.x-t.r,c),u=Math.max(t.x+t.r,u),h=Math.min(t.y-t.r,h),f=Math.max(t.y+t.r,f)}}function eo(t){t._pack_next=t._pack_prev=t}function ro(t){delete t._pack_next,delete t._pack_prev}function no(t,e,r){var n=t.r+r.r,a=e.x-t.x,i=e.y-t.y;if(n&&(a||i)){var o=e.r+r.r,s=a*a+i*i,l=.5+((n*=n)-(o*=o))/(2*s),c=Math.sqrt(Math.max(0,2*o*(n+s)-(n-=s)*n-o*o))/(2*s);r.x=t.x+l*a+c*i,r.y=t.y+l*i-c*a}else r.x=t.x+n,r.y=t.y}function ao(t,e){return t.parent==e.parent?1:2}function io(t){var e=t.children;return e.length?e[0]:t.t}function oo(t){var e,r=t.children;return(e=r.length)?r[e-1]:t.t}function so(t,e,r){var n=r/(e.i-t.i);e.c-=n,e.s+=r,t.c+=n,e.z+=r,e.m+=r}function lo(t,e,r){return t.a.parent===e.parent?t.a:r}function co(t){return{x:t.x,y:t.y,dx:t.dx,dy:t.dy}}function uo(t,e){var r=t.x+e[3],n=t.y+e[0],a=t.dx-e[1]-e[3],i=t.dy-e[0]-e[2];return a<0&&(r+=a/2,a=0),i<0&&(n+=i/2,i=0),{x:r,y:n,dx:a,dy:i}}function ho(t){var e=t[0],r=t[t.length-1];return e<r?[e,r]:[r,e]}function fo(t){return t.rangeExtent?t.rangeExtent():ho(t.range())}function po(t,e,r,n){var a=r(t[0],t[1]),i=n(e[0],e[1]);return function(t){return i(a(t))}}function go(t,e){var r,n=0,a=t.length-1,i=t[n],o=t[a];return o<i&&(r=n,n=a,a=r,r=i,i=o,o=r),t[n]=e.floor(i),t[a]=e.ceil(o),t}function vo(t){return t?{floor:function(e){return Math.floor(e/t)*t},ceil:function(e){return Math.ceil(e/t)*t}}:mo}t.layout.histogram=function(){var e=!0,r=Number,n=Zi,a=Wi;function i(i,o){for(var s,l,c=[],u=i.map(r,this),h=n.call(this,u,o),f=a.call(this,h,u,o),p=(o=-1,u.length),d=f.length-1,g=e?1:1/p;++o<d;)(s=c[o]=[]).dx=f[o+1]-(s.x=f[o]),s.y=0;if(d>0)for(o=-1;++o<p;)(l=u[o])>=h[0]&&l<=h[1]&&((s=c[t.bisect(f,l,1,d)-1]).y+=g,s.push(i[o]));return c}return i.value=function(t){return arguments.length?(r=t,i):r},i.range=function(t){return arguments.length?(n=ve(t),i):n},i.bins=function(t){return arguments.length?(a=\"number\"==typeof t?function(e){return Xi(e,t)}:ve(t),i):a},i.frequency=function(t){return arguments.length?(e=!!t,i):e},i},t.layout.pack=function(){var e,r=t.layout.hierarchy().sort(Ji),n=0,a=[1,1];function i(t,i){var o=r.call(this,t,i),s=o[0],l=a[0],c=a[1],u=null==e?Math.sqrt:\"function\"==typeof e?e:function(){return e};if(s.x=s.y=0,Pi(s,function(t){t.r=+u(t.value)}),Pi(s,to),n){var h=n*(e?1:Math.max(2*s.r/l,2*s.r/c))/2;Pi(s,function(t){t.r+=h}),Pi(s,to),Pi(s,function(t){t.r-=h})}return function t(e,r,n,a){var i=e.children;e.x=r+=a*e.x;e.y=n+=a*e.y;e.r*=a;if(i)for(var o=-1,s=i.length;++o<s;)t(i[o],r,n,a)}(s,l/2,c/2,e?1:1/Math.max(2*s.r/l,2*s.r/c)),o}return i.size=function(t){return arguments.length?(a=t,i):a},i.radius=function(t){return arguments.length?(e=null==t||\"function\"==typeof t?t:+t,i):e},i.padding=function(t){return arguments.length?(n=+t,i):n},Li(i,r)},t.layout.tree=function(){var e=t.layout.hierarchy().sort(null).value(null),r=ao,n=[1,1],a=null;function i(t,i){var c=e.call(this,t,i),u=c[0],h=function(t){var e,r={A:null,children:[t]},n=[r];for(;null!=(e=n.pop());)for(var a,i=e.children,o=0,s=i.length;o<s;++o)n.push((i[o]=a={_:i[o],parent:e,children:(a=i[o].children)&&a.slice()||[],A:null,a:null,z:0,m:0,c:0,s:0,t:null,i:o}).a=a);return r.children[0]}(u);if(Pi(h,o),h.parent.m=-h.z,Ci(h,s),a)Ci(u,l);else{var f=u,p=u,d=u;Ci(u,function(t){t.x<f.x&&(f=t),t.x>p.x&&(p=t),t.depth>d.depth&&(d=t)});var g=r(f,p)/2-f.x,v=n[0]/(p.x+r(p,f)/2+g),m=n[1]/(d.depth||1);Ci(u,function(t){t.x=(t.x+g)*v,t.y=t.depth*m})}return c}function o(t){var e=t.children,n=t.parent.children,a=t.i?n[t.i-1]:null;if(e.length){!function(t){var e,r=0,n=0,a=t.children,i=a.length;for(;--i>=0;)(e=a[i]).z+=r,e.m+=r,r+=e.s+(n+=e.c)}(t);var i=(e[0].z+e[e.length-1].z)/2;a?(t.z=a.z+r(t._,a._),t.m=t.z-i):t.z=i}else a&&(t.z=a.z+r(t._,a._));t.parent.A=function(t,e,n){if(e){for(var a,i=t,o=t,s=e,l=i.parent.children[0],c=i.m,u=o.m,h=s.m,f=l.m;s=oo(s),i=io(i),s&&i;)l=io(l),(o=oo(o)).a=t,(a=s.z+h-i.z-c+r(s._,i._))>0&&(so(lo(s,t,n),t,a),c+=a,u+=a),h+=s.m,c+=i.m,f+=l.m,u+=o.m;s&&!oo(o)&&(o.t=s,o.m+=h-u),i&&!io(l)&&(l.t=i,l.m+=c-f,n=t)}return n}(t,a,t.parent.A||n[0])}function s(t){t._.x=t.z+t.parent.m,t.m+=t.parent.m}function l(t){t.x*=n[0],t.y=t.depth*n[1]}return i.separation=function(t){return arguments.length?(r=t,i):r},i.size=function(t){return arguments.length?(a=null==(n=t)?l:null,i):a?null:n},i.nodeSize=function(t){return arguments.length?(a=null==(n=t)?null:l,i):a?n:null},Li(i,e)},t.layout.cluster=function(){var e=t.layout.hierarchy().sort(null).value(null),r=ao,n=[1,1],a=!1;function i(i,o){var s,l=e.call(this,i,o),c=l[0],u=0;Pi(c,function(e){var n=e.children;n&&n.length?(e.x=function(t){return t.reduce(function(t,e){return t+e.x},0)/t.length}(n),e.y=function(e){return 1+t.max(e,function(t){return t.y})}(n)):(e.x=s?u+=r(e,s):0,e.y=0,s=e)});var h=function t(e){var r=e.children;return r&&r.length?t(r[0]):e}(c),f=function t(e){var r,n=e.children;return n&&(r=n.length)?t(n[r-1]):e}(c),p=h.x-r(h,f)/2,d=f.x+r(f,h)/2;return Pi(c,a?function(t){t.x=(t.x-c.x)*n[0],t.y=(c.y-t.y)*n[1]}:function(t){t.x=(t.x-p)/(d-p)*n[0],t.y=(1-(c.y?t.y/c.y:1))*n[1]}),l}return i.separation=function(t){return arguments.length?(r=t,i):r},i.size=function(t){return arguments.length?(a=null==(n=t),i):a?null:n},i.nodeSize=function(t){return arguments.length?(a=null!=(n=t),i):a?n:null},Li(i,e)},t.layout.treemap=function(){var e,r=t.layout.hierarchy(),n=Math.round,a=[1,1],i=null,o=co,s=!1,l=\"squarify\",c=.5*(1+Math.sqrt(5));function u(t,e){for(var r,n,a=-1,i=t.length;++a<i;)n=(r=t[a]).value*(e<0?0:e),r.area=isNaN(n)||n<=0?0:n}function h(t){var e=t.children;if(e&&e.length){var r,n,a,i=o(t),s=[],c=e.slice(),f=1/0,g=\"slice\"===l?i.dx:\"dice\"===l?i.dy:\"slice-dice\"===l?1&t.depth?i.dy:i.dx:Math.min(i.dx,i.dy);for(u(c,i.dx*i.dy/t.value),s.area=0;(a=c.length)>0;)s.push(r=c[a-1]),s.area+=r.area,\"squarify\"!==l||(n=p(s,g))<=f?(c.pop(),f=n):(s.area-=s.pop().area,d(s,g,i,!1),g=Math.min(i.dx,i.dy),s.length=s.area=0,f=1/0);s.length&&(d(s,g,i,!0),s.length=s.area=0),e.forEach(h)}}function f(t){var e=t.children;if(e&&e.length){var r,n=o(t),a=e.slice(),i=[];for(u(a,n.dx*n.dy/t.value),i.area=0;r=a.pop();)i.push(r),i.area+=r.area,null!=r.z&&(d(i,r.z?n.dx:n.dy,n,!a.length),i.length=i.area=0);e.forEach(f)}}function p(t,e){for(var r,n=t.area,a=0,i=1/0,o=-1,s=t.length;++o<s;)(r=t[o].area)&&(r<i&&(i=r),r>a&&(a=r));return e*=e,(n*=n)?Math.max(e*a*c/n,n/(e*i*c)):1/0}function d(t,e,r,a){var i,o=-1,s=t.length,l=r.x,c=r.y,u=e?n(t.area/e):0;if(e==r.dx){for((a||u>r.dy)&&(u=r.dy);++o<s;)(i=t[o]).x=l,i.y=c,i.dy=u,l+=i.dx=Math.min(r.x+r.dx-l,u?n(i.area/u):0);i.z=!0,i.dx+=r.x+r.dx-l,r.y+=u,r.dy-=u}else{for((a||u>r.dx)&&(u=r.dx);++o<s;)(i=t[o]).x=l,i.y=c,i.dx=u,c+=i.dy=Math.min(r.y+r.dy-c,u?n(i.area/u):0);i.z=!1,i.dy+=r.y+r.dy-c,r.x+=u,r.dx-=u}}function g(t){var n=e||r(t),i=n[0];return i.x=i.y=0,i.value?(i.dx=a[0],i.dy=a[1]):i.dx=i.dy=0,e&&r.revalue(i),u([i],i.dx*i.dy/i.value),(e?f:h)(i),s&&(e=n),n}return g.size=function(t){return arguments.length?(a=t,g):a},g.padding=function(t){if(!arguments.length)return i;function e(e){return uo(e,t)}var r;return o=null==(i=t)?co:\"function\"==(r=typeof t)?function(e){var r=t.call(g,e,e.depth);return null==r?co(e):uo(e,\"number\"==typeof r?[r,r,r,r]:r)}:\"number\"===r?(t=[t,t,t,t],e):e,g},g.round=function(t){return arguments.length?(n=t?Math.round:Number,g):n!=Number},g.sticky=function(t){return arguments.length?(s=t,e=null,g):s},g.ratio=function(t){return arguments.length?(c=t,g):c},g.mode=function(t){return arguments.length?(l=t+\"\",g):l},Li(g,r)},t.random={normal:function(t,e){var r=arguments.length;return r<2&&(e=1),r<1&&(t=0),function(){var r,n,a;do{a=(r=2*Math.random()-1)*r+(n=2*Math.random()-1)*n}while(!a||a>1);return t+e*r*Math.sqrt(-2*Math.log(a)/a)}},logNormal:function(){var e=t.random.normal.apply(t,arguments);return function(){return Math.exp(e())}},bates:function(e){var r=t.random.irwinHall(e);return function(){return r()/e}},irwinHall:function(t){return function(){for(var e=0,r=0;r<t;r++)e+=Math.random();return e}}},t.scale={};var mo={floor:P,ceil:P};function yo(e,r,n,a){var i=[],o=[],s=0,l=Math.min(e.length,r.length)-1;for(e[l]<e[0]&&(e=e.slice().reverse(),r=r.slice().reverse());++s<=l;)i.push(n(e[s-1],e[s])),o.push(a(r[s-1],r[s]));return function(r){var n=t.bisect(e,r,1,l)-1;return o[n](i[n](r))}}function xo(e,r){return t.rebind(e,r,\"range\",\"rangeRound\",\"interpolate\",\"clamp\")}function bo(t,e){return go(t,vo(_o(t,e)[2])),go(t,vo(_o(t,e)[2])),t}function _o(t,e){null==e&&(e=10);var r=ho(t),n=r[1]-r[0],a=Math.pow(10,Math.floor(Math.log(n/e)/Math.LN10)),i=e/n*a;return i<=.15?a*=10:i<=.35?a*=5:i<=.75&&(a*=2),r[0]=Math.ceil(r[0]/a)*a,r[1]=Math.floor(r[1]/a)*a+.5*a,r[2]=a,r}function wo(e,r){return t.range.apply(t,_o(e,r))}function ko(e,r,n){var a=_o(e,r);if(n){var i=Pe.exec(n);if(i.shift(),\"s\"===i[8]){var o=t.formatPrefix(Math.max(y(a[0]),y(a[1])));return i[7]||(i[7]=\".\"+Mo(o.scale(a[2]))),i[8]=\"f\",n=t.format(i.join(\"\")),function(t){return n(o.scale(t))+o.symbol}}i[7]||(i[7]=\".\"+function(t,e){var r=Mo(e[2]);return t in To?Math.abs(r-Mo(Math.max(y(e[0]),y(e[1]))))+ +(\"e\"!==t):r-2*(\"%\"===t)}(i[8],a)),n=i.join(\"\")}else n=\",.\"+Mo(a[2])+\"f\";return t.format(n)}t.scale.linear=function(){return function t(e,r,n,a){var i,o;function s(){var t=Math.min(e.length,r.length)>2?yo:po,s=a?xi:yi;return i=t(e,r,s,n),o=t(r,e,s,Ka),l}function l(t){return i(t)}l.invert=function(t){return o(t)};l.domain=function(t){return arguments.length?(e=t.map(Number),s()):e};l.range=function(t){return arguments.length?(r=t,s()):r};l.rangeRound=function(t){return l.range(t).interpolate(hi)};l.clamp=function(t){return arguments.length?(a=t,s()):a};l.interpolate=function(t){return arguments.length?(n=t,s()):n};l.ticks=function(t){return wo(e,t)};l.tickFormat=function(t,r){return ko(e,t,r)};l.nice=function(t){return bo(e,t),s()};l.copy=function(){return t(e,r,n,a)};return s()}([0,1],[0,1],Ka,!1)};var To={s:1,g:1,p:1,r:1,e:1};function Mo(t){return-Math.floor(Math.log(t)/Math.LN10+.01)}t.scale.log=function(){return function e(r,n,a,i){function o(t){return(a?Math.log(t<0?0:t):-Math.log(t>0?0:-t))/Math.log(n)}function s(t){return a?Math.pow(n,t):-Math.pow(n,-t)}function l(t){return r(o(t))}l.invert=function(t){return s(r.invert(t))};l.domain=function(t){return arguments.length?(a=t[0]>=0,r.domain((i=t.map(Number)).map(o)),l):i};l.base=function(t){return arguments.length?(n=+t,r.domain(i.map(o)),l):n};l.nice=function(){var t=go(i.map(o),a?Math:So);return r.domain(t),i=t.map(s),l};l.ticks=function(){var t=ho(i),e=[],r=t[0],l=t[1],c=Math.floor(o(r)),u=Math.ceil(o(l)),h=n%1?2:n;if(isFinite(u-c)){if(a){for(;c<u;c++)for(var f=1;f<h;f++)e.push(s(c)*f);e.push(s(c))}else for(e.push(s(c));c++<u;)for(var f=h-1;f>0;f--)e.push(s(c)*f);for(c=0;e[c]<r;c++);for(u=e.length;e[u-1]>l;u--);e=e.slice(c,u)}return e};l.tickFormat=function(e,r){if(!arguments.length)return Ao;arguments.length<2?r=Ao:\"function\"!=typeof r&&(r=t.format(r));var a=Math.max(1,n*e/l.ticks().length);return function(t){var e=t/s(Math.round(o(t)));return e*n<n-.5&&(e*=n),e<=a?r(t):\"\"}};l.copy=function(){return e(r.copy(),n,a,i)};return xo(l,r)}(t.scale.linear().domain([0,1]),10,!0,[1,10])};var Ao=t.format(\".0e\"),So={floor:function(t){return-Math.ceil(-t)},ceil:function(t){return-Math.floor(-t)}};function Eo(t){return function(e){return e<0?-Math.pow(-e,t):Math.pow(e,t)}}t.scale.pow=function(){return function t(e,r,n){var a=Eo(r),i=Eo(1/r);function o(t){return e(a(t))}o.invert=function(t){return i(e.invert(t))};o.domain=function(t){return arguments.length?(e.domain((n=t.map(Number)).map(a)),o):n};o.ticks=function(t){return wo(n,t)};o.tickFormat=function(t,e){return ko(n,t,e)};o.nice=function(t){return o.domain(bo(n,t))};o.exponent=function(t){return arguments.length?(a=Eo(r=t),i=Eo(1/r),e.domain(n.map(a)),o):r};o.copy=function(){return t(e.copy(),r,n)};return xo(o,e)}(t.scale.linear(),1,[0,1])},t.scale.sqrt=function(){return t.scale.pow().exponent(.5)},t.scale.ordinal=function(){return function e(r,n){var a,i,o;function s(t){return i[((a.get(t)||(\"range\"===n.t?a.set(t,r.push(t)):NaN))-1)%i.length]}function l(e,n){return t.range(r.length).map(function(t){return e+n*t})}s.domain=function(t){if(!arguments.length)return r;r=[],a=new b;for(var e,i=-1,o=t.length;++i<o;)a.has(e=t[i])||a.set(e,r.push(e));return s[n.t].apply(s,n.a)};s.range=function(t){return arguments.length?(i=t,o=0,n={t:\"range\",a:arguments},s):i};s.rangePoints=function(t,e){arguments.length<2&&(e=0);var a=t[0],c=t[1],u=r.length<2?(a=(a+c)/2,0):(c-a)/(r.length-1+e);return i=l(a+u*e/2,u),o=0,n={t:\"rangePoints\",a:arguments},s};s.rangeRoundPoints=function(t,e){arguments.length<2&&(e=0);var a=t[0],c=t[1],u=r.length<2?(a=c=Math.round((a+c)/2),0):(c-a)/(r.length-1+e)|0;return i=l(a+Math.round(u*e/2+(c-a-(r.length-1+e)*u)/2),u),o=0,n={t:\"rangeRoundPoints\",a:arguments},s};s.rangeBands=function(t,e,a){arguments.length<2&&(e=0),arguments.length<3&&(a=e);var c=t[1]<t[0],u=t[c-0],h=t[1-c],f=(h-u)/(r.length-e+2*a);return i=l(u+f*a,f),c&&i.reverse(),o=f*(1-e),n={t:\"rangeBands\",a:arguments},s};s.rangeRoundBands=function(t,e,a){arguments.length<2&&(e=0),arguments.length<3&&(a=e);var c=t[1]<t[0],u=t[c-0],h=t[1-c],f=Math.floor((h-u)/(r.length-e+2*a));return i=l(u+Math.round((h-u-(r.length-e)*f)/2),f),c&&i.reverse(),o=Math.round(f*(1-e)),n={t:\"rangeRoundBands\",a:arguments},s};s.rangeBand=function(){return o};s.rangeExtent=function(){return ho(n.a[0])};s.copy=function(){return e(r,n)};return s.domain(r)}([],{t:\"range\",a:[[]]})},t.scale.category10=function(){return t.scale.ordinal().range(Lo)},t.scale.category20=function(){return t.scale.ordinal().range(Co)},t.scale.category20b=function(){return t.scale.ordinal().range(Po)},t.scale.category20c=function(){return t.scale.ordinal().range(Oo)};var Lo=[2062260,16744206,2924588,14034728,9725885,9197131,14907330,8355711,12369186,1556175].map(se),Co=[2062260,11454440,16744206,16759672,2924588,10018698,14034728,16750742,9725885,12955861,9197131,12885140,14907330,16234194,8355711,13092807,12369186,14408589,1556175,10410725].map(se),Po=[3750777,5395619,7040719,10264286,6519097,9216594,11915115,13556636,9202993,12426809,15186514,15190932,8666169,11356490,14049643,15177372,8077683,10834324,13528509,14589654].map(se),Oo=[3244733,7057110,10406625,13032431,15095053,16616764,16625259,16634018,3253076,7652470,10607003,13101504,7695281,10394312,12369372,14342891,6513507,9868950,12434877,14277081].map(se);function zo(){return 0}t.scale.quantile=function(){return function e(r,n){var a;function i(){var e=0,i=n.length;for(a=[];++e<i;)a[e-1]=t.quantile(r,e/i);return o}function o(e){if(!isNaN(e=+e))return n[t.bisect(a,e)]}o.domain=function(t){return arguments.length?(r=t.map(p).filter(d).sort(f),i()):r};o.range=function(t){return arguments.length?(n=t,i()):n};o.quantiles=function(){return a};o.invertExtent=function(t){return(t=n.indexOf(t))<0?[NaN,NaN]:[t>0?a[t-1]:r[0],t<a.length?a[t]:r[r.length-1]]};o.copy=function(){return e(r,n)};return i()}([],[])},t.scale.quantize=function(){return function t(e,r,n){var a,i;function o(t){return n[Math.max(0,Math.min(i,Math.floor(a*(t-e))))]}function s(){return a=n.length/(r-e),i=n.length-1,o}o.domain=function(t){return arguments.length?(e=+t[0],r=+t[t.length-1],s()):[e,r]};o.range=function(t){return arguments.length?(n=t,s()):n};o.invertExtent=function(t){return[t=(t=n.indexOf(t))<0?NaN:t/a+e,t+1/a]};o.copy=function(){return t(e,r,n)};return s()}(0,1,[0,1])},t.scale.threshold=function(){return function e(r,n){function a(e){if(e<=e)return n[t.bisect(r,e)]}a.domain=function(t){return arguments.length?(r=t,a):r};a.range=function(t){return arguments.length?(n=t,a):n};a.invertExtent=function(t){return t=n.indexOf(t),[r[t-1],r[t]]};a.copy=function(){return e(r,n)};return a}([.5],[0,1])},t.scale.identity=function(){return function t(e){function r(t){return+t}r.invert=r;r.domain=r.range=function(t){return arguments.length?(e=t.map(r),r):e};r.ticks=function(t){return wo(e,t)};r.tickFormat=function(t,r){return ko(e,t,r)};r.copy=function(){return t(e)};return r}([0,1])},t.svg={},t.svg.arc=function(){var t=Do,e=Ro,r=zo,n=Io,a=Fo,i=Bo,o=No;function s(){var s=Math.max(0,+t.apply(this,arguments)),c=Math.max(0,+e.apply(this,arguments)),u=a.apply(this,arguments)-Et,h=i.apply(this,arguments)-Et,f=Math.abs(h-u),p=u>h?0:1;if(c<s&&(d=c,c=s,s=d),f>=St)return l(c,p)+(s?l(s,1-p):\"\")+\"Z\";var d,g,v,m,y,x,b,_,w,k,T,M,A=0,S=0,E=[];if((m=(+o.apply(this,arguments)||0)/2)&&(v=n===Io?Math.sqrt(s*s+c*c):+n.apply(this,arguments),p||(S*=-1),c&&(S=It(v/c*Math.sin(m))),s&&(A=It(v/s*Math.sin(m)))),c){y=c*Math.cos(u+S),x=c*Math.sin(u+S),b=c*Math.cos(h-S),_=c*Math.sin(h-S);var L=Math.abs(h-u-2*S)<=Mt?0:1;if(S&&jo(y,x,b,_)===p^L){var C=(u+h)/2;y=c*Math.cos(C),x=c*Math.sin(C),b=_=null}}else y=x=0;if(s){w=s*Math.cos(h-A),k=s*Math.sin(h-A),T=s*Math.cos(u+A),M=s*Math.sin(u+A);var P=Math.abs(u-h+2*A)<=Mt?0:1;if(A&&jo(w,k,T,M)===1-p^P){var O=(u+h)/2;w=s*Math.cos(O),k=s*Math.sin(O),T=M=null}}else w=k=0;if(f>kt&&(d=Math.min(Math.abs(c-s)/2,+r.apply(this,arguments)))>.001){g=s<c^p?0:1;var z=d,I=d;if(f<Mt){var D=null==T?[w,k]:null==b?[y,x]:ca([y,x],[T,M],[b,_],[w,k]),R=y-D[0],F=x-D[1],B=b-D[0],N=_-D[1],j=1/Math.sin(Math.acos((R*B+F*N)/(Math.sqrt(R*R+F*F)*Math.sqrt(B*B+N*N)))/2),V=Math.sqrt(D[0]*D[0]+D[1]*D[1]);I=Math.min(d,(s-V)/(j-1)),z=Math.min(d,(c-V)/(j+1))}if(null!=b){var U=Vo(null==T?[w,k]:[T,M],[y,x],c,z,p),q=Vo([b,_],[w,k],c,z,p);d===z?E.push(\"M\",U[0],\"A\",z,\",\",z,\" 0 0,\",g,\" \",U[1],\"A\",c,\",\",c,\" 0 \",1-p^jo(U[1][0],U[1][1],q[1][0],q[1][1]),\",\",p,\" \",q[1],\"A\",z,\",\",z,\" 0 0,\",g,\" \",q[0]):E.push(\"M\",U[0],\"A\",z,\",\",z,\" 0 1,\",g,\" \",q[0])}else E.push(\"M\",y,\",\",x);if(null!=T){var H=Vo([y,x],[T,M],s,-I,p),G=Vo([w,k],null==b?[y,x]:[b,_],s,-I,p);d===I?E.push(\"L\",G[0],\"A\",I,\",\",I,\" 0 0,\",g,\" \",G[1],\"A\",s,\",\",s,\" 0 \",p^jo(G[1][0],G[1][1],H[1][0],H[1][1]),\",\",1-p,\" \",H[1],\"A\",I,\",\",I,\" 0 0,\",g,\" \",H[0]):E.push(\"L\",G[0],\"A\",I,\",\",I,\" 0 0,\",g,\" \",H[0])}else E.push(\"L\",w,\",\",k)}else E.push(\"M\",y,\",\",x),null!=b&&E.push(\"A\",c,\",\",c,\" 0 \",L,\",\",p,\" \",b,\",\",_),E.push(\"L\",w,\",\",k),null!=T&&E.push(\"A\",s,\",\",s,\" 0 \",P,\",\",1-p,\" \",T,\",\",M);return E.push(\"Z\"),E.join(\"\")}function l(t,e){return\"M0,\"+t+\"A\"+t+\",\"+t+\" 0 1,\"+e+\" 0,\"+-t+\"A\"+t+\",\"+t+\" 0 1,\"+e+\" 0,\"+t}return s.innerRadius=function(e){return arguments.length?(t=ve(e),s):t},s.outerRadius=function(t){return arguments.length?(e=ve(t),s):e},s.cornerRadius=function(t){return arguments.length?(r=ve(t),s):r},s.padRadius=function(t){return arguments.length?(n=t==Io?Io:ve(t),s):n},s.startAngle=function(t){return arguments.length?(a=ve(t),s):a},s.endAngle=function(t){return arguments.length?(i=ve(t),s):i},s.padAngle=function(t){return arguments.length?(o=ve(t),s):o},s.centroid=function(){var r=(+t.apply(this,arguments)+ +e.apply(this,arguments))/2,n=(+a.apply(this,arguments)+ +i.apply(this,arguments))/2-Et;return[Math.cos(n)*r,Math.sin(n)*r]},s};var Io=\"auto\";function Do(t){return t.innerRadius}function Ro(t){return t.outerRadius}function Fo(t){return t.startAngle}function Bo(t){return t.endAngle}function No(t){return t&&t.padAngle}function jo(t,e,r,n){return(t-r)*e-(e-n)*t>0?0:1}function Vo(t,e,r,n,a){var i=t[0]-e[0],o=t[1]-e[1],s=(a?n:-n)/Math.sqrt(i*i+o*o),l=s*o,c=-s*i,u=t[0]+l,h=t[1]+c,f=e[0]+l,p=e[1]+c,d=(u+f)/2,g=(h+p)/2,v=f-u,m=p-h,y=v*v+m*m,x=r-n,b=u*p-f*h,_=(m<0?-1:1)*Math.sqrt(Math.max(0,x*x*y-b*b)),w=(b*m-v*_)/y,k=(-b*v-m*_)/y,T=(b*m+v*_)/y,M=(-b*v+m*_)/y,A=w-d,S=k-g,E=T-d,L=M-g;return A*A+S*S>E*E+L*L&&(w=T,k=M),[[w-l,k-c],[w*r/x,k*r/x]]}function Uo(t){var e=na,r=aa,n=Xr,a=Ho,i=a.key,o=.7;function s(i){var s,l=[],c=[],u=-1,h=i.length,f=ve(e),p=ve(r);function d(){l.push(\"M\",a(t(c),o))}for(;++u<h;)n.call(this,s=i[u],u)?c.push([+f.call(this,s,u),+p.call(this,s,u)]):c.length&&(d(),c=[]);return c.length&&d(),l.length?l.join(\"\"):null}return s.x=function(t){return arguments.length?(e=t,s):e},s.y=function(t){return arguments.length?(r=t,s):r},s.defined=function(t){return arguments.length?(n=t,s):n},s.interpolate=function(t){return arguments.length?(i=\"function\"==typeof t?a=t:(a=qo.get(t)||Ho).key,s):i},s.tension=function(t){return arguments.length?(o=t,s):o},s}t.svg.line=function(){return Uo(P)};var qo=t.map({linear:Ho,\"linear-closed\":Go,step:function(t){var e=0,r=t.length,n=t[0],a=[n[0],\",\",n[1]];for(;++e<r;)a.push(\"H\",(n[0]+(n=t[e])[0])/2,\"V\",n[1]);r>1&&a.push(\"H\",n[0]);return a.join(\"\")},\"step-before\":Yo,\"step-after\":Wo,basis:Jo,\"basis-open\":function(t){if(t.length<4)return Ho(t);var e,r=[],n=-1,a=t.length,i=[0],o=[0];for(;++n<3;)e=t[n],i.push(e[0]),o.push(e[1]);r.push(Ko(ts,i)+\",\"+Ko(ts,o)),--n;for(;++n<a;)e=t[n],i.shift(),i.push(e[0]),o.shift(),o.push(e[1]),es(r,i,o);return r.join(\"\")},\"basis-closed\":function(t){var e,r,n=-1,a=t.length,i=a+4,o=[],s=[];for(;++n<4;)r=t[n%a],o.push(r[0]),s.push(r[1]);e=[Ko(ts,o),\",\",Ko(ts,s)],--n;for(;++n<i;)r=t[n%a],o.shift(),o.push(r[0]),s.shift(),s.push(r[1]),es(e,o,s);return e.join(\"\")},bundle:function(t,e){var r=t.length-1;if(r)for(var n,a,i=t[0][0],o=t[0][1],s=t[r][0]-i,l=t[r][1]-o,c=-1;++c<=r;)n=t[c],a=c/r,n[0]=e*n[0]+(1-e)*(i+a*s),n[1]=e*n[1]+(1-e)*(o+a*l);return Jo(t)},cardinal:function(t,e){return t.length<3?Ho(t):t[0]+Xo(t,Zo(t,e))},\"cardinal-open\":function(t,e){return t.length<4?Ho(t):t[1]+Xo(t.slice(1,-1),Zo(t,e))},\"cardinal-closed\":function(t,e){return t.length<3?Go(t):t[0]+Xo((t.push(t[0]),t),Zo([t[t.length-2]].concat(t,[t[1]]),e))},monotone:function(t){return t.length<3?Ho(t):t[0]+Xo(t,function(t){var e,r,n,a,i=[],o=function(t){var e=0,r=t.length-1,n=[],a=t[0],i=t[1],o=n[0]=rs(a,i);for(;++e<r;)n[e]=(o+(o=rs(a=i,i=t[e+1])))/2;return n[e]=o,n}(t),s=-1,l=t.length-1;for(;++s<l;)e=rs(t[s],t[s+1]),y(e)<kt?o[s]=o[s+1]=0:(r=o[s]/e,n=o[s+1]/e,(a=r*r+n*n)>9&&(a=3*e/Math.sqrt(a),o[s]=a*r,o[s+1]=a*n));s=-1;for(;++s<=l;)a=(t[Math.min(l,s+1)][0]-t[Math.max(0,s-1)][0])/(6*(1+o[s]*o[s])),i.push([a||0,o[s]*a||0]);return i}(t))}});function Ho(t){return t.length>1?t.join(\"L\"):t+\"Z\"}function Go(t){return t.join(\"L\")+\"Z\"}function Yo(t){for(var e=0,r=t.length,n=t[0],a=[n[0],\",\",n[1]];++e<r;)a.push(\"V\",(n=t[e])[1],\"H\",n[0]);return a.join(\"\")}function Wo(t){for(var e=0,r=t.length,n=t[0],a=[n[0],\",\",n[1]];++e<r;)a.push(\"H\",(n=t[e])[0],\"V\",n[1]);return a.join(\"\")}function Xo(t,e){if(e.length<1||t.length!=e.length&&t.length!=e.length+2)return Ho(t);var r=t.length!=e.length,n=\"\",a=t[0],i=t[1],o=e[0],s=o,l=1;if(r&&(n+=\"Q\"+(i[0]-2*o[0]/3)+\",\"+(i[1]-2*o[1]/3)+\",\"+i[0]+\",\"+i[1],a=t[1],l=2),e.length>1){s=e[1],i=t[l],l++,n+=\"C\"+(a[0]+o[0])+\",\"+(a[1]+o[1])+\",\"+(i[0]-s[0])+\",\"+(i[1]-s[1])+\",\"+i[0]+\",\"+i[1];for(var c=2;c<e.length;c++,l++)i=t[l],s=e[c],n+=\"S\"+(i[0]-s[0])+\",\"+(i[1]-s[1])+\",\"+i[0]+\",\"+i[1]}if(r){var u=t[l];n+=\"Q\"+(i[0]+2*s[0]/3)+\",\"+(i[1]+2*s[1]/3)+\",\"+u[0]+\",\"+u[1]}return n}function Zo(t,e){for(var r,n=[],a=(1-e)/2,i=t[0],o=t[1],s=1,l=t.length;++s<l;)r=i,i=o,o=t[s],n.push([a*(o[0]-r[0]),a*(o[1]-r[1])]);return n}function Jo(t){if(t.length<3)return Ho(t);var e=1,r=t.length,n=t[0],a=n[0],i=n[1],o=[a,a,a,(n=t[1])[0]],s=[i,i,i,n[1]],l=[a,\",\",i,\"L\",Ko(ts,o),\",\",Ko(ts,s)];for(t.push(t[r-1]);++e<=r;)n=t[e],o.shift(),o.push(n[0]),s.shift(),s.push(n[1]),es(l,o,s);return t.pop(),l.push(\"L\",n),l.join(\"\")}function Ko(t,e){return t[0]*e[0]+t[1]*e[1]+t[2]*e[2]+t[3]*e[3]}qo.forEach(function(t,e){e.key=t,e.closed=/-closed$/.test(t)});var Qo=[0,2/3,1/3,0],$o=[0,1/3,2/3,0],ts=[0,1/6,2/3,1/6];function es(t,e,r){t.push(\"C\",Ko(Qo,e),\",\",Ko(Qo,r),\",\",Ko($o,e),\",\",Ko($o,r),\",\",Ko(ts,e),\",\",Ko(ts,r))}function rs(t,e){return(e[1]-t[1])/(e[0]-t[0])}function ns(t){for(var e,r,n,a=-1,i=t.length;++a<i;)r=(e=t[a])[0],n=e[1]-Et,e[0]=r*Math.cos(n),e[1]=r*Math.sin(n);return t}function as(t){var e=na,r=na,n=0,a=aa,i=Xr,o=Ho,s=o.key,l=o,c=\"L\",u=.7;function h(s){var h,f,p,d=[],g=[],v=[],m=-1,y=s.length,x=ve(e),b=ve(n),_=e===r?function(){return f}:ve(r),w=n===a?function(){return p}:ve(a);function k(){d.push(\"M\",o(t(v),u),c,l(t(g.reverse()),u),\"Z\")}for(;++m<y;)i.call(this,h=s[m],m)?(g.push([f=+x.call(this,h,m),p=+b.call(this,h,m)]),v.push([+_.call(this,h,m),+w.call(this,h,m)])):g.length&&(k(),g=[],v=[]);return g.length&&k(),d.length?d.join(\"\"):null}return h.x=function(t){return arguments.length?(e=r=t,h):r},h.x0=function(t){return arguments.length?(e=t,h):e},h.x1=function(t){return arguments.length?(r=t,h):r},h.y=function(t){return arguments.length?(n=a=t,h):a},h.y0=function(t){return arguments.length?(n=t,h):n},h.y1=function(t){return arguments.length?(a=t,h):a},h.defined=function(t){return arguments.length?(i=t,h):i},h.interpolate=function(t){return arguments.length?(s=\"function\"==typeof t?o=t:(o=qo.get(t)||Ho).key,l=o.reverse||o,c=o.closed?\"M\":\"L\",h):s},h.tension=function(t){return arguments.length?(u=t,h):u},h}function is(t){return t.radius}function os(t){return[t.x,t.y]}function ss(){return 64}function ls(){return\"circle\"}function cs(t){var e=Math.sqrt(t/Mt);return\"M0,\"+e+\"A\"+e+\",\"+e+\" 0 1,1 0,\"+-e+\"A\"+e+\",\"+e+\" 0 1,1 0,\"+e+\"Z\"}t.svg.line.radial=function(){var t=Uo(ns);return t.radius=t.x,delete t.x,t.angle=t.y,delete t.y,t},Yo.reverse=Wo,Wo.reverse=Yo,t.svg.area=function(){return as(P)},t.svg.area.radial=function(){var t=as(ns);return t.radius=t.x,delete t.x,t.innerRadius=t.x0,delete t.x0,t.outerRadius=t.x1,delete t.x1,t.angle=t.y,delete t.y,t.startAngle=t.y0,delete t.y0,t.endAngle=t.y1,delete t.y1,t},t.svg.chord=function(){var t=qn,e=Hn,r=is,n=Fo,a=Bo;function i(r,n){var a,i,c=o(this,t,r,n),u=o(this,e,r,n);return\"M\"+c.p0+s(c.r,c.p1,c.a1-c.a0)+(i=u,(a=c).a0==i.a0&&a.a1==i.a1?l(c.r,c.p1,c.r,c.p0):l(c.r,c.p1,u.r,u.p0)+s(u.r,u.p1,u.a1-u.a0)+l(u.r,u.p1,c.r,c.p0))+\"Z\"}function o(t,e,i,o){var s=e.call(t,i,o),l=r.call(t,s,o),c=n.call(t,s,o)-Et,u=a.call(t,s,o)-Et;return{r:l,a0:c,a1:u,p0:[l*Math.cos(c),l*Math.sin(c)],p1:[l*Math.cos(u),l*Math.sin(u)]}}function s(t,e,r){return\"A\"+t+\",\"+t+\" 0 \"+ +(r>Mt)+\",1 \"+e}function l(t,e,r,n){return\"Q 0,0 \"+n}return i.radius=function(t){return arguments.length?(r=ve(t),i):r},i.source=function(e){return arguments.length?(t=ve(e),i):t},i.target=function(t){return arguments.length?(e=ve(t),i):e},i.startAngle=function(t){return arguments.length?(n=ve(t),i):n},i.endAngle=function(t){return arguments.length?(a=ve(t),i):a},i},t.svg.diagonal=function(){var t=qn,e=Hn,r=os;function n(n,a){var i=t.call(this,n,a),o=e.call(this,n,a),s=(i.y+o.y)/2,l=[i,{x:i.x,y:s},{x:o.x,y:s},o];return\"M\"+(l=l.map(r))[0]+\"C\"+l[1]+\" \"+l[2]+\" \"+l[3]}return n.source=function(e){return arguments.length?(t=ve(e),n):t},n.target=function(t){return arguments.length?(e=ve(t),n):e},n.projection=function(t){return arguments.length?(r=t,n):r},n},t.svg.diagonal.radial=function(){var e=t.svg.diagonal(),r=os,n=e.projection;return e.projection=function(t){return arguments.length?n(function(t){return function(){var e=t.apply(this,arguments),r=e[0],n=e[1]-Et;return[r*Math.cos(n),r*Math.sin(n)]}}(r=t)):r},e},t.svg.symbol=function(){var t=ls,e=ss;function r(r,n){return(us.get(t.call(this,r,n))||cs)(e.call(this,r,n))}return r.type=function(e){return arguments.length?(t=ve(e),r):t},r.size=function(t){return arguments.length?(e=ve(t),r):e},r};var us=t.map({circle:cs,cross:function(t){var e=Math.sqrt(t/5)/2;return\"M\"+-3*e+\",\"+-e+\"H\"+-e+\"V\"+-3*e+\"H\"+e+\"V\"+-e+\"H\"+3*e+\"V\"+e+\"H\"+e+\"V\"+3*e+\"H\"+-e+\"V\"+e+\"H\"+-3*e+\"Z\"},diamond:function(t){var e=Math.sqrt(t/(2*fs)),r=e*fs;return\"M0,\"+-e+\"L\"+r+\",0 0,\"+e+\" \"+-r+\",0Z\"},square:function(t){var e=Math.sqrt(t)/2;return\"M\"+-e+\",\"+-e+\"L\"+e+\",\"+-e+\" \"+e+\",\"+e+\" \"+-e+\",\"+e+\"Z\"},\"triangle-down\":function(t){var e=Math.sqrt(t/hs),r=e*hs/2;return\"M0,\"+r+\"L\"+e+\",\"+-r+\" \"+-e+\",\"+-r+\"Z\"},\"triangle-up\":function(t){var e=Math.sqrt(t/hs),r=e*hs/2;return\"M0,\"+-r+\"L\"+e+\",\"+r+\" \"+-e+\",\"+r+\"Z\"}});t.svg.symbolTypes=us.keys();var hs=Math.sqrt(3),fs=Math.tan(30*Lt);W.transition=function(t){for(var e,r,n=vs||++xs,a=ws(t),i=[],o=ms||{time:Date.now(),ease:oi,delay:0,duration:250},s=-1,l=this.length;++s<l;){i.push(e=[]);for(var c=this[s],u=-1,h=c.length;++u<h;)(r=c[u])&&ks(r,u,a,n,o),e.push(r)}return gs(i,a,n)},W.interrupt=function(t){return this.each(null==t?ps:ds(ws(t)))};var ps=ds(ws());function ds(t){return function(){var e,r,n;(e=this[t])&&(n=e[r=e.active])&&(n.timer.c=null,n.timer.t=NaN,--e.count?delete e[r]:delete this[t],e.active+=.5,n.event&&n.event.interrupt.call(this,this.__data__,n.index))}}function gs(t,e,r){return U(t,ys),t.namespace=e,t.id=r,t}var vs,ms,ys=[],xs=0;function bs(t,e,r,n){var a=t.id,i=t.namespace;return ut(t,\"function\"==typeof r?function(t,o,s){t[i][a].tween.set(e,n(r.call(t,t.__data__,o,s)))}:(r=n(r),function(t){t[i][a].tween.set(e,r)}))}function _s(t){return null==t&&(t=\"\"),function(){this.textContent=t}}function ws(t){return null==t?\"__transition__\":\"__transition_\"+t+\"__\"}function ks(t,e,r,n,a){var i,o,s,l,c,u=t[r]||(t[r]={active:0,count:0}),h=u[n];function f(r){var a=u.active,f=u[a];for(var d in f&&(f.timer.c=null,f.timer.t=NaN,--u.count,delete u[a],f.event&&f.event.interrupt.call(t,t.__data__,f.index)),u)if(+d<n){var g=u[d];g.timer.c=null,g.timer.t=NaN,--u.count,delete u[d]}o.c=p,Te(function(){return o.c&&p(r||1)&&(o.c=null,o.t=NaN),1},0,i),u.active=n,h.event&&h.event.start.call(t,t.__data__,e),c=[],h.tween.forEach(function(r,n){(n=n.call(t,t.__data__,e))&&c.push(n)}),l=h.ease,s=h.duration}function p(a){for(var i=a/s,o=l(i),f=c.length;f>0;)c[--f].call(t,o);if(i>=1)return h.event&&h.event.end.call(t,t.__data__,e),--u.count?delete u[n]:delete t[r],1}h||(i=a.time,o=Te(function(t){var e=h.delay;if(o.t=e+i,e<=t)return f(t-e);o.c=f},0,i),h=u[n]={tween:new b,time:i,timer:o,delay:a.delay,duration:a.duration,ease:a.ease,index:e},a=null,++u.count)}ys.call=W.call,ys.empty=W.empty,ys.node=W.node,ys.size=W.size,t.transition=function(e,r){return e&&e.transition?vs?e.transition(r):e:t.selection().transition(e)},t.transition.prototype=ys,ys.select=function(t){var e,r,n,a=this.id,i=this.namespace,o=[];t=X(t);for(var s=-1,l=this.length;++s<l;){o.push(e=[]);for(var c=this[s],u=-1,h=c.length;++u<h;)(n=c[u])&&(r=t.call(n,n.__data__,u,s))?(\"__data__\"in n&&(r.__data__=n.__data__),ks(r,u,i,a,n[i][a]),e.push(r)):e.push(null)}return gs(o,i,a)},ys.selectAll=function(t){var e,r,n,a,i,o=this.id,s=this.namespace,l=[];t=Z(t);for(var c=-1,u=this.length;++c<u;)for(var h=this[c],f=-1,p=h.length;++f<p;)if(n=h[f]){i=n[s][o],r=t.call(n,n.__data__,f,c),l.push(e=[]);for(var d=-1,g=r.length;++d<g;)(a=r[d])&&ks(a,d,s,o,i),e.push(a)}return gs(l,s,o)},ys.filter=function(t){var e,r,n=[];\"function\"!=typeof t&&(t=ct(t));for(var a=0,i=this.length;a<i;a++){n.push(e=[]);for(var o,s=0,l=(o=this[a]).length;s<l;s++)(r=o[s])&&t.call(r,r.__data__,s,a)&&e.push(r)}return gs(n,this.namespace,this.id)},ys.tween=function(t,e){var r=this.id,n=this.namespace;return arguments.length<2?this.node()[n][r].tween.get(t):ut(this,null==e?function(e){e[n][r].tween.remove(t)}:function(a){a[n][r].tween.set(t,e)})},ys.attr=function(e,r){if(arguments.length<2){for(r in e)this.attr(r,e[r]);return this}var n=\"transform\"==e?mi:Ka,a=t.ns.qualify(e);function i(){this.removeAttribute(a)}function o(){this.removeAttributeNS(a.space,a.local)}return bs(this,\"attr.\"+e,r,a.local?function(t){return null==t?o:(t+=\"\",function(){var e,r=this.getAttributeNS(a.space,a.local);return r!==t&&(e=n(r,t),function(t){this.setAttributeNS(a.space,a.local,e(t))})})}:function(t){return null==t?i:(t+=\"\",function(){var e,r=this.getAttribute(a);return r!==t&&(e=n(r,t),function(t){this.setAttribute(a,e(t))})})})},ys.attrTween=function(e,r){var n=t.ns.qualify(e);return this.tween(\"attr.\"+e,n.local?function(t,e){var a=r.call(this,t,e,this.getAttributeNS(n.space,n.local));return a&&function(t){this.setAttributeNS(n.space,n.local,a(t))}}:function(t,e){var a=r.call(this,t,e,this.getAttribute(n));return a&&function(t){this.setAttribute(n,a(t))}})},ys.style=function(t,e,r){var n=arguments.length;if(n<3){if(\"string\"!=typeof t){for(r in n<2&&(e=\"\"),t)this.style(r,t[r],e);return this}r=\"\"}function a(){this.style.removeProperty(t)}return bs(this,\"style.\"+t,e,function(e){return null==e?a:(e+=\"\",function(){var n,a=o(this).getComputedStyle(this,null).getPropertyValue(t);return a!==e&&(n=Ka(a,e),function(e){this.style.setProperty(t,n(e),r)})})})},ys.styleTween=function(t,e,r){return arguments.length<3&&(r=\"\"),this.tween(\"style.\"+t,function(n,a){var i=e.call(this,n,a,o(this).getComputedStyle(this,null).getPropertyValue(t));return i&&function(e){this.style.setProperty(t,i(e),r)}})},ys.text=function(t){return bs(this,\"text\",t,_s)},ys.remove=function(){var t=this.namespace;return this.each(\"end.transition\",function(){var e;this[t].count<2&&(e=this.parentNode)&&e.removeChild(this)})},ys.ease=function(e){var r=this.id,n=this.namespace;return arguments.length<1?this.node()[n][r].ease:(\"function\"!=typeof e&&(e=t.ease.apply(t,arguments)),ut(this,function(t){t[n][r].ease=e}))},ys.delay=function(t){var e=this.id,r=this.namespace;return arguments.length<1?this.node()[r][e].delay:ut(this,\"function\"==typeof t?function(n,a,i){n[r][e].delay=+t.call(n,n.__data__,a,i)}:(t=+t,function(n){n[r][e].delay=t}))},ys.duration=function(t){var e=this.id,r=this.namespace;return arguments.length<1?this.node()[r][e].duration:ut(this,\"function\"==typeof t?function(n,a,i){n[r][e].duration=Math.max(1,t.call(n,n.__data__,a,i))}:(t=Math.max(1,t),function(n){n[r][e].duration=t}))},ys.each=function(e,r){var n=this.id,a=this.namespace;if(arguments.length<2){var i=ms,o=vs;try{vs=n,ut(this,function(t,r,i){ms=t[a][n],e.call(t,t.__data__,r,i)})}finally{ms=i,vs=o}}else ut(this,function(i){var o=i[a][n];(o.event||(o.event=t.dispatch(\"start\",\"end\",\"interrupt\"))).on(e,r)});return this},ys.transition=function(){for(var t,e,r,n=this.id,a=++xs,i=this.namespace,o=[],s=0,l=this.length;s<l;s++){o.push(t=[]);for(var c,u=0,h=(c=this[s]).length;u<h;u++)(e=c[u])&&ks(e,u,i,a,{time:(r=e[i][n]).time,ease:r.ease,delay:r.delay+r.duration,duration:r.duration}),t.push(e)}return gs(o,i,a)},t.svg.axis=function(){var e,r=t.scale.linear(),a=Ts,i=6,o=6,s=3,l=[10],c=null;function u(n){n.each(function(){var n,u=t.select(this),h=this.__chart__||r,f=this.__chart__=r.copy(),p=null==c?f.ticks?f.ticks.apply(f,l):f.domain():c,d=null==e?f.tickFormat?f.tickFormat.apply(f,l):P:e,g=u.selectAll(\".tick\").data(p,f),v=g.enter().insert(\"g\",\".domain\").attr(\"class\",\"tick\").style(\"opacity\",kt),m=t.transition(g.exit()).style(\"opacity\",kt).remove(),y=t.transition(g.order()).style(\"opacity\",1),x=Math.max(i,0)+s,b=fo(f),_=u.selectAll(\".domain\").data([0]),w=(_.enter().append(\"path\").attr(\"class\",\"domain\"),t.transition(_));v.append(\"line\"),v.append(\"text\");var k,T,M,A,S=v.select(\"line\"),E=y.select(\"line\"),L=g.select(\"text\").text(d),C=v.select(\"text\"),O=y.select(\"text\"),z=\"top\"===a||\"left\"===a?-1:1;if(\"bottom\"===a||\"top\"===a?(n=As,k=\"x\",M=\"y\",T=\"x2\",A=\"y2\",L.attr(\"dy\",z<0?\"0em\":\".71em\").style(\"text-anchor\",\"middle\"),w.attr(\"d\",\"M\"+b[0]+\",\"+z*o+\"V0H\"+b[1]+\"V\"+z*o)):(n=Ss,k=\"y\",M=\"x\",T=\"y2\",A=\"x2\",L.attr(\"dy\",\".32em\").style(\"text-anchor\",z<0?\"end\":\"start\"),w.attr(\"d\",\"M\"+z*o+\",\"+b[0]+\"H0V\"+b[1]+\"H\"+z*o)),S.attr(A,z*i),C.attr(M,z*x),E.attr(T,0).attr(A,z*i),O.attr(k,0).attr(M,z*x),f.rangeBand){var I=f,D=I.rangeBand()/2;h=f=function(t){return I(t)+D}}else h.rangeBand?h=f:m.call(n,f,h);v.call(n,h,f),y.call(n,f,f)})}return u.scale=function(t){return arguments.length?(r=t,u):r},u.orient=function(t){return arguments.length?(a=t in Ms?t+\"\":Ts,u):a},u.ticks=function(){return arguments.length?(l=n(arguments),u):l},u.tickValues=function(t){return arguments.length?(c=t,u):c},u.tickFormat=function(t){return arguments.length?(e=t,u):e},u.tickSize=function(t){var e=arguments.length;return e?(i=+t,o=+arguments[e-1],u):i},u.innerTickSize=function(t){return arguments.length?(i=+t,u):i},u.outerTickSize=function(t){return arguments.length?(o=+t,u):o},u.tickPadding=function(t){return arguments.length?(s=+t,u):s},u.tickSubdivide=function(){return arguments.length&&u},u};var Ts=\"bottom\",Ms={top:1,right:1,bottom:1,left:1};function As(t,e,r){t.attr(\"transform\",function(t){var n=e(t);return\"translate(\"+(isFinite(n)?n:r(t))+\",0)\"})}function Ss(t,e,r){t.attr(\"transform\",function(t){var n=e(t);return\"translate(0,\"+(isFinite(n)?n:r(t))+\")\"})}t.svg.brush=function(){var e,r,n=j(f,\"brushstart\",\"brush\",\"brushend\"),a=null,i=null,s=[0,0],l=[0,0],c=!0,u=!0,h=Ls[0];function f(e){e.each(function(){var e=t.select(this).style(\"pointer-events\",\"all\").style(\"-webkit-tap-highlight-color\",\"rgba(0,0,0,0)\").on(\"mousedown.brush\",v).on(\"touchstart.brush\",v),r=e.selectAll(\".background\").data([0]);r.enter().append(\"rect\").attr(\"class\",\"background\").style(\"visibility\",\"hidden\").style(\"cursor\",\"crosshair\"),e.selectAll(\".extent\").data([0]).enter().append(\"rect\").attr(\"class\",\"extent\").style(\"cursor\",\"move\");var n=e.selectAll(\".resize\").data(h,P);n.exit().remove(),n.enter().append(\"g\").attr(\"class\",function(t){return\"resize \"+t}).style(\"cursor\",function(t){return Es[t]}).append(\"rect\").attr(\"x\",function(t){return/[ew]$/.test(t)?-3:null}).attr(\"y\",function(t){return/^[ns]/.test(t)?-3:null}).attr(\"width\",6).attr(\"height\",6).style(\"visibility\",\"hidden\"),n.style(\"display\",f.empty()?\"none\":null);var o,s=t.transition(e),l=t.transition(r);a&&(o=fo(a),l.attr(\"x\",o[0]).attr(\"width\",o[1]-o[0]),d(s)),i&&(o=fo(i),l.attr(\"y\",o[0]).attr(\"height\",o[1]-o[0]),g(s)),p(s)})}function p(t){t.selectAll(\".resize\").attr(\"transform\",function(t){return\"translate(\"+s[+/e$/.test(t)]+\",\"+l[+/^s/.test(t)]+\")\"})}function d(t){t.select(\".extent\").attr(\"x\",s[0]),t.selectAll(\".extent,.n>rect,.s>rect\").attr(\"width\",s[1]-s[0])}function g(t){t.select(\".extent\").attr(\"y\",l[0]),t.selectAll(\".extent,.e>rect,.w>rect\").attr(\"height\",l[1]-l[0])}function v(){var h,v,m=this,y=t.select(t.event.target),x=n.of(m,arguments),b=t.select(m),_=y.datum(),w=!/^(n|s)$/.test(_)&&a,k=!/^(e|w)$/.test(_)&&i,T=y.classed(\"extent\"),M=xt(m),A=t.mouse(m),S=t.select(o(m)).on(\"keydown.brush\",function(){32==t.event.keyCode&&(T||(h=null,A[0]-=s[1],A[1]-=l[1],T=2),B())}).on(\"keyup.brush\",function(){32==t.event.keyCode&&2==T&&(A[0]+=s[1],A[1]+=l[1],T=0,B())});if(t.event.changedTouches?S.on(\"touchmove.brush\",C).on(\"touchend.brush\",O):S.on(\"mousemove.brush\",C).on(\"mouseup.brush\",O),b.interrupt().selectAll(\"*\").interrupt(),T)A[0]=s[0]-A[0],A[1]=l[0]-A[1];else if(_){var E=+/w$/.test(_),L=+/^n/.test(_);v=[s[1-E]-A[0],l[1-L]-A[1]],A[0]=s[E],A[1]=l[L]}else t.event.altKey&&(h=A.slice());function C(){var e=t.mouse(m),r=!1;v&&(e[0]+=v[0],e[1]+=v[1]),T||(t.event.altKey?(h||(h=[(s[0]+s[1])/2,(l[0]+l[1])/2]),A[0]=s[+(e[0]<h[0])],A[1]=l[+(e[1]<h[1])]):h=null),w&&P(e,a,0)&&(d(b),r=!0),k&&P(e,i,1)&&(g(b),r=!0),r&&(p(b),x({type:\"brush\",mode:T?\"move\":\"resize\"}))}function P(t,n,a){var i,o,f=fo(n),p=f[0],d=f[1],g=A[a],v=a?l:s,m=v[1]-v[0];if(T&&(p-=g,d-=m+g),i=(a?u:c)?Math.max(p,Math.min(d,t[a])):t[a],T?o=(i+=g)+m:(h&&(g=Math.max(p,Math.min(d,2*h[a]-i))),g<i?(o=i,i=g):o=g),v[0]!=i||v[1]!=o)return a?r=null:e=null,v[0]=i,v[1]=o,!0}function O(){C(),b.style(\"pointer-events\",\"all\").selectAll(\".resize\").style(\"display\",f.empty()?\"none\":null),t.select(\"body\").style(\"cursor\",null),S.on(\"mousemove.brush\",null).on(\"mouseup.brush\",null).on(\"touchmove.brush\",null).on(\"touchend.brush\",null).on(\"keydown.brush\",null).on(\"keyup.brush\",null),M(),x({type:\"brushend\"})}b.style(\"pointer-events\",\"none\").selectAll(\".resize\").style(\"display\",null),t.select(\"body\").style(\"cursor\",y.style(\"cursor\")),x({type:\"brushstart\"}),C()}return f.event=function(a){a.each(function(){var a=n.of(this,arguments),i={x:s,y:l,i:e,j:r},o=this.__chart__||i;this.__chart__=i,vs?t.select(this).transition().each(\"start.brush\",function(){e=o.i,r=o.j,s=o.x,l=o.y,a({type:\"brushstart\"})}).tween(\"brush:brush\",function(){var t=Qa(s,i.x),n=Qa(l,i.y);return e=r=null,function(e){s=i.x=t(e),l=i.y=n(e),a({type:\"brush\",mode:\"resize\"})}}).each(\"end.brush\",function(){e=i.i,r=i.j,a({type:\"brush\",mode:\"resize\"}),a({type:\"brushend\"})}):(a({type:\"brushstart\"}),a({type:\"brush\",mode:\"resize\"}),a({type:\"brushend\"}))})},f.x=function(t){return arguments.length?(h=Ls[!(a=t)<<1|!i],f):a},f.y=function(t){return arguments.length?(h=Ls[!a<<1|!(i=t)],f):i},f.clamp=function(t){return arguments.length?(a&&i?(c=!!t[0],u=!!t[1]):a?c=!!t:i&&(u=!!t),f):a&&i?[c,u]:a?c:i?u:null},f.extent=function(t){var n,o,c,u,h;return arguments.length?(a&&(n=t[0],o=t[1],i&&(n=n[0],o=o[0]),e=[n,o],a.invert&&(n=a(n),o=a(o)),o<n&&(h=n,n=o,o=h),n==s[0]&&o==s[1]||(s=[n,o])),i&&(c=t[0],u=t[1],a&&(c=c[1],u=u[1]),r=[c,u],i.invert&&(c=i(c),u=i(u)),u<c&&(h=c,c=u,u=h),c==l[0]&&u==l[1]||(l=[c,u])),f):(a&&(e?(n=e[0],o=e[1]):(n=s[0],o=s[1],a.invert&&(n=a.invert(n),o=a.invert(o)),o<n&&(h=n,n=o,o=h))),i&&(r?(c=r[0],u=r[1]):(c=l[0],u=l[1],i.invert&&(c=i.invert(c),u=i.invert(u)),u<c&&(h=c,c=u,u=h))),a&&i?[[n,c],[o,u]]:a?[n,o]:i&&[c,u])},f.clear=function(){return f.empty()||(s=[0,0],l=[0,0],e=r=null),f},f.empty=function(){return!!a&&s[0]==s[1]||!!i&&l[0]==l[1]},t.rebind(f,n,\"on\")};var Es={n:\"ns-resize\",e:\"ew-resize\",s:\"ns-resize\",w:\"ew-resize\",nw:\"nwse-resize\",ne:\"nesw-resize\",se:\"nwse-resize\",sw:\"nesw-resize\"},Ls=[[\"n\",\"e\",\"s\",\"w\",\"nw\",\"ne\",\"se\",\"sw\"],[\"e\",\"w\"],[\"n\",\"s\"],[]],Cs=Ie.format=cr.timeFormat,Ps=Cs.utc,Os=Ps(\"%Y-%m-%dT%H:%M:%S.%LZ\");function zs(t){return t.toISOString()}function Is(e,r,n){function a(t){return e(t)}function i(e,n){var a=(e[1]-e[0])/n,i=t.bisect(Rs,a);return i==Rs.length?[r.year,_o(e.map(function(t){return t/31536e6}),n)[2]]:i?r[a/Rs[i-1]<Rs[i]/a?i-1:i]:[Ns,_o(e,n)[2]]}return a.invert=function(t){return Ds(e.invert(t))},a.domain=function(t){return arguments.length?(e.domain(t),a):e.domain().map(Ds)},a.nice=function(t,e){var r=a.domain(),n=ho(r),o=null==t?i(n,10):\"number\"==typeof t&&i(n,t);function s(r){return!isNaN(r)&&!t.range(r,Ds(+r+1),e).length}return o&&(t=o[0],e=o[1]),a.domain(go(r,e>1?{floor:function(e){for(;s(e=t.floor(e));)e=Ds(e-1);return e},ceil:function(e){for(;s(e=t.ceil(e));)e=Ds(+e+1);return e}}:t))},a.ticks=function(t,e){var r=ho(a.domain()),n=null==t?i(r,10):\"number\"==typeof t?i(r,t):!t.range&&[{range:t},e];return n&&(t=n[0],e=n[1]),t.range(r[0],Ds(+r[1]+1),e<1?1:e)},a.tickFormat=function(){return n},a.copy=function(){return Is(e.copy(),r,n)},xo(a,e)}function Ds(t){return new Date(t)}Cs.iso=Date.prototype.toISOString&&+new Date(\"2000-01-01T00:00:00.000Z\")?zs:Os,zs.parse=function(t){var e=new Date(t);return isNaN(e)?null:e},zs.toString=Os.toString,Ie.second=Be(function(t){return new De(1e3*Math.floor(t/1e3))},function(t,e){t.setTime(t.getTime()+1e3*Math.floor(e))},function(t){return t.getSeconds()}),Ie.seconds=Ie.second.range,Ie.seconds.utc=Ie.second.utc.range,Ie.minute=Be(function(t){return new De(6e4*Math.floor(t/6e4))},function(t,e){t.setTime(t.getTime()+6e4*Math.floor(e))},function(t){return t.getMinutes()}),Ie.minutes=Ie.minute.range,Ie.minutes.utc=Ie.minute.utc.range,Ie.hour=Be(function(t){var e=t.getTimezoneOffset()/60;return new De(36e5*(Math.floor(t/36e5-e)+e))},function(t,e){t.setTime(t.getTime()+36e5*Math.floor(e))},function(t){return t.getHours()}),Ie.hours=Ie.hour.range,Ie.hours.utc=Ie.hour.utc.range,Ie.month=Be(function(t){return(t=Ie.day(t)).setDate(1),t},function(t,e){t.setMonth(t.getMonth()+e)},function(t){return t.getMonth()}),Ie.months=Ie.month.range,Ie.months.utc=Ie.month.utc.range;var Rs=[1e3,5e3,15e3,3e4,6e4,3e5,9e5,18e5,36e5,108e5,216e5,432e5,864e5,1728e5,6048e5,2592e6,7776e6,31536e6],Fs=[[Ie.second,1],[Ie.second,5],[Ie.second,15],[Ie.second,30],[Ie.minute,1],[Ie.minute,5],[Ie.minute,15],[Ie.minute,30],[Ie.hour,1],[Ie.hour,3],[Ie.hour,6],[Ie.hour,12],[Ie.day,1],[Ie.day,2],[Ie.week,1],[Ie.month,1],[Ie.month,3],[Ie.year,1]],Bs=Cs.multi([[\".%L\",function(t){return t.getMilliseconds()}],[\":%S\",function(t){return t.getSeconds()}],[\"%I:%M\",function(t){return t.getMinutes()}],[\"%I %p\",function(t){return t.getHours()}],[\"%a %d\",function(t){return t.getDay()&&1!=t.getDate()}],[\"%b %d\",function(t){return 1!=t.getDate()}],[\"%B\",function(t){return t.getMonth()}],[\"%Y\",Xr]]),Ns={range:function(e,r,n){return t.range(Math.ceil(e/n)*n,+r,n).map(Ds)},floor:P,ceil:P};Fs.year=Ie.year,Ie.scale=function(){return Is(t.scale.linear(),Fs,Bs)};var js=Fs.map(function(t){return[t[0].utc,t[1]]}),Vs=Ps.multi([[\".%L\",function(t){return t.getUTCMilliseconds()}],[\":%S\",function(t){return t.getUTCSeconds()}],[\"%I:%M\",function(t){return t.getUTCMinutes()}],[\"%I %p\",function(t){return t.getUTCHours()}],[\"%a %d\",function(t){return t.getUTCDay()&&1!=t.getUTCDate()}],[\"%b %d\",function(t){return 1!=t.getUTCDate()}],[\"%B\",function(t){return t.getUTCMonth()}],[\"%Y\",Xr]]);function Us(t){return JSON.parse(t.responseText)}function qs(t){var e=a.createRange();return e.selectNode(a.body),e.createContextualFragment(t.responseText)}js.year=Ie.year.utc,Ie.scale.utc=function(){return Is(t.scale.linear(),js,Vs)},t.text=me(function(t){return t.responseText}),t.json=function(t,e){return ye(t,\"application/json\",Us,e)},t.html=function(t,e){return ye(t,\"text/html\",qs,e)},t.xml=me(function(t){return t.responseXML}),\"object\"==typeof e&&e.exports?e.exports=t:this.d3=t}()},{}],166:[function(t,e,r){e.exports=function(){for(var t=0;t<arguments.length;t++)if(void 0!==arguments[t])return arguments[t]}},{}],167:[function(t,e,r){\"use strict\";var n=t(\"incremental-convex-hull\"),a=t(\"uniq\");function i(t,e){this.point=t,this.index=e}function o(t,e){for(var r=t.point,n=e.point,a=r.length,i=0;i<a;++i){var o=n[i]-r[i];if(o)return o}return 0}e.exports=function(t,e){var r=t.length;if(0===r)return[];var s=t[0].length;if(s<1)return[];if(1===s)return function(t,e,r){if(1===t)return r?[[-1,0]]:[];var n=e.map(function(t,e){return[t[0],e]});n.sort(function(t,e){return t[0]-e[0]});for(var a=new Array(t-1),i=1;i<t;++i){var o=n[i-1],s=n[i];a[i-1]=[o[1],s[1]]}r&&a.push([-1,a[0][1]],[a[t-1][1],-1]);return a}(r,t,e);for(var l=new Array(r),c=1,u=0;u<r;++u){for(var h=t[u],f=new Array(s+1),p=0,d=0;d<s;++d){var g=h[d];f[d]=g,p+=g*g}f[s]=p,l[u]=new i(f,u),c=Math.max(p,c)}a(l,o),r=l.length;for(var v=new Array(r+s+1),m=new Array(r+s+1),y=(s+1)*(s+1)*c,x=new Array(s+1),u=0;u<=s;++u)x[u]=0;x[s]=y,v[0]=x.slice(),m[0]=-1;for(var u=0;u<=s;++u){var f=x.slice();f[u]=1,v[u+1]=f,m[u+1]=-1}for(var u=0;u<r;++u){var b=l[u];v[u+s+1]=b.point,m[u+s+1]=b.index}var _=n(v,!1);_=e?_.filter(function(t){for(var e=0,r=0;r<=s;++r){var n=m[t[r]];if(n<0&&++e>=2)return!1;t[r]=n}return!0}):_.filter(function(t){for(var e=0;e<=s;++e){var r=m[t[e]];if(r<0)return!1;t[e]=r}return!0});if(1&s)for(var u=0;u<_.length;++u){var b=_[u],f=b[0];b[0]=b[1],b[1]=f}return _}},{\"incremental-convex-hull\":415,uniq:546}],168:[function(t,e,r){\"use strict\";e.exports=i;var n=(i.canvas=document.createElement(\"canvas\")).getContext(\"2d\"),a=o([32,126]);function i(t,e){Array.isArray(t)&&(t=t.join(\", \"));var r,i={},s=16,l=.05;e&&(2===e.length&&\"number\"==typeof e[0]?r=o(e):Array.isArray(e)?r=e:(e.o?r=o(e.o):e.pairs&&(r=e.pairs),e.fontSize&&(s=e.fontSize),null!=e.threshold&&(l=e.threshold))),r||(r=a),n.font=s+\"px \"+t;for(var c=0;c<r.length;c++){var u=r[c],h=n.measureText(u[0]).width+n.measureText(u[1]).width,f=n.measureText(u).width;if(Math.abs(h-f)>s*l){var p=(f-h)/s;i[u]=1e3*p}}return i}function o(t){for(var e=[],r=t[0];r<=t[1];r++)for(var n=String.fromCharCode(r),a=t[0];a<t[1];a++){var i=n+String.fromCharCode(a);e.push(i)}return e}i.createPairs=o,i.ascii=a},{}],169:[function(t,e,r){(function(t){var r=!1;if(\"undefined\"!=typeof Float64Array){var n=new Float64Array(1),a=new Uint32Array(n.buffer);if(n[0]=1,r=!0,1072693248===a[1]){e.exports=function(t){return n[0]=t,[a[0],a[1]]},e.exports.pack=function(t,e){return a[0]=t,a[1]=e,n[0]},e.exports.lo=function(t){return n[0]=t,a[0]},e.exports.hi=function(t){return n[0]=t,a[1]}}else if(1072693248===a[0]){e.exports=function(t){return n[0]=t,[a[1],a[0]]},e.exports.pack=function(t,e){return a[1]=t,a[0]=e,n[0]},e.exports.lo=function(t){return n[0]=t,a[1]},e.exports.hi=function(t){return n[0]=t,a[0]}}else r=!1}if(!r){var i=new t(8);e.exports=function(t){return i.writeDoubleLE(t,0,!0),[i.readUInt32LE(0,!0),i.readUInt32LE(4,!0)]},e.exports.pack=function(t,e){return i.writeUInt32LE(t,0,!0),i.writeUInt32LE(e,4,!0),i.readDoubleLE(0,!0)},e.exports.lo=function(t){return i.writeDoubleLE(t,0,!0),i.readUInt32LE(0,!0)},e.exports.hi=function(t){return i.writeDoubleLE(t,0,!0),i.readUInt32LE(4,!0)}}e.exports.sign=function(t){return e.exports.hi(t)>>>31},e.exports.exponent=function(t){return(e.exports.hi(t)<<1>>>21)-1023},e.exports.fraction=function(t){var r=e.exports.lo(t),n=e.exports.hi(t),a=1048575&n;return 2146435072&n&&(a+=1<<20),[r,a]},e.exports.denormalized=function(t){return!(2146435072&e.exports.hi(t))}}).call(this,t(\"buffer\").Buffer)},{buffer:107}],170:[function(t,e,r){var n=t(\"abs-svg-path\"),a=t(\"normalize-svg-path\"),i={M:\"moveTo\",C:\"bezierCurveTo\"};e.exports=function(t,e){t.beginPath(),a(n(e)).forEach(function(e){var r=e[0],n=e.slice(1);t[i[r]].apply(t,n)}),t.closePath()}},{\"abs-svg-path\":63,\"normalize-svg-path\":454}],171:[function(t,e,r){e.exports=function(t){switch(t){case\"int8\":return Int8Array;case\"int16\":return Int16Array;case\"int32\":return Int32Array;case\"uint8\":return Uint8Array;case\"uint16\":return Uint16Array;case\"uint32\":return Uint32Array;case\"float32\":return Float32Array;case\"float64\":return Float64Array;case\"array\":return Array;case\"uint8_clamped\":return Uint8ClampedArray}}},{}],172:[function(t,e,r){\"use strict\";e.exports=function(t,e){switch(\"undefined\"==typeof e&&(e=0),typeof t){case\"number\":if(t>0)return function(t,e){var r,n;for(r=new Array(t),n=0;n<t;++n)r[n]=e;return r}(0|t,e);break;case\"object\":if(\"number\"==typeof t.length)return function t(e,r,n){var a=0|e[n];if(a<=0)return[];var i,o=new Array(a);if(n===e.length-1)for(i=0;i<a;++i)o[i]=r;else for(i=0;i<a;++i)o[i]=t(e,r,n+1);return o}(t,e,0)}return[]}},{}],173:[function(t,e,r){\"use strict\";function n(t,e,r){r=r||2;var n,s,l,c,u,p,d,v=e&&e.length,m=v?e[0]*r:t.length,y=a(t,0,m,r,!0),x=[];if(!y||y.next===y.prev)return x;if(v&&(y=function(t,e,r,n){var o,s,l,c,u,p=[];for(o=0,s=e.length;o<s;o++)l=e[o]*n,c=o<s-1?e[o+1]*n:t.length,(u=a(t,l,c,n,!1))===u.next&&(u.steiner=!0),p.push(g(u));for(p.sort(h),o=0;o<p.length;o++)f(p[o],r),r=i(r,r.next);return r}(t,e,y,r)),t.length>80*r){n=l=t[0],s=c=t[1];for(var b=r;b<m;b+=r)(u=t[b])<n&&(n=u),(p=t[b+1])<s&&(s=p),u>l&&(l=u),p>c&&(c=p);d=0!==(d=Math.max(l-n,c-s))?1/d:0}return o(y,x,r,n,s,d),x}function a(t,e,r,n,a){var i,o;if(a===E(t,e,r,n)>0)for(i=e;i<r;i+=n)o=M(i,t[i],t[i+1],o);else for(i=r-n;i>=e;i-=n)o=M(i,t[i],t[i+1],o);return o&&x(o,o.next)&&(A(o),o=o.next),o}function i(t,e){if(!t)return t;e||(e=t);var r,n=t;do{if(r=!1,n.steiner||!x(n,n.next)&&0!==y(n.prev,n,n.next))n=n.next;else{if(A(n),(n=e=n.prev)===n.next)break;r=!0}}while(r||n!==e);return e}function o(t,e,r,n,a,h,f){if(t){!f&&h&&function(t,e,r,n){var a=t;do{null===a.z&&(a.z=d(a.x,a.y,e,r,n)),a.prevZ=a.prev,a.nextZ=a.next,a=a.next}while(a!==t);a.prevZ.nextZ=null,a.prevZ=null,function(t){var e,r,n,a,i,o,s,l,c=1;do{for(r=t,t=null,i=null,o=0;r;){for(o++,n=r,s=0,e=0;e<c&&(s++,n=n.nextZ);e++);for(l=c;s>0||l>0&&n;)0!==s&&(0===l||!n||r.z<=n.z)?(a=r,r=r.nextZ,s--):(a=n,n=n.nextZ,l--),i?i.nextZ=a:t=a,a.prevZ=i,i=a;r=n}i.nextZ=null,c*=2}while(o>1)}(a)}(t,n,a,h);for(var p,g,v=t;t.prev!==t.next;)if(p=t.prev,g=t.next,h?l(t,n,a,h):s(t))e.push(p.i/r),e.push(t.i/r),e.push(g.i/r),A(t),t=g.next,v=g.next;else if((t=g)===v){f?1===f?o(t=c(i(t),e,r),e,r,n,a,h,2):2===f&&u(t,e,r,n,a,h):o(i(t),e,r,n,a,h,1);break}}}function s(t){var e=t.prev,r=t,n=t.next;if(y(e,r,n)>=0)return!1;for(var a=t.next.next;a!==t.prev;){if(v(e.x,e.y,r.x,r.y,n.x,n.y,a.x,a.y)&&y(a.prev,a,a.next)>=0)return!1;a=a.next}return!0}function l(t,e,r,n){var a=t.prev,i=t,o=t.next;if(y(a,i,o)>=0)return!1;for(var s=a.x<i.x?a.x<o.x?a.x:o.x:i.x<o.x?i.x:o.x,l=a.y<i.y?a.y<o.y?a.y:o.y:i.y<o.y?i.y:o.y,c=a.x>i.x?a.x>o.x?a.x:o.x:i.x>o.x?i.x:o.x,u=a.y>i.y?a.y>o.y?a.y:o.y:i.y>o.y?i.y:o.y,h=d(s,l,e,r,n),f=d(c,u,e,r,n),p=t.prevZ,g=t.nextZ;p&&p.z>=h&&g&&g.z<=f;){if(p!==t.prev&&p!==t.next&&v(a.x,a.y,i.x,i.y,o.x,o.y,p.x,p.y)&&y(p.prev,p,p.next)>=0)return!1;if(p=p.prevZ,g!==t.prev&&g!==t.next&&v(a.x,a.y,i.x,i.y,o.x,o.y,g.x,g.y)&&y(g.prev,g,g.next)>=0)return!1;g=g.nextZ}for(;p&&p.z>=h;){if(p!==t.prev&&p!==t.next&&v(a.x,a.y,i.x,i.y,o.x,o.y,p.x,p.y)&&y(p.prev,p,p.next)>=0)return!1;p=p.prevZ}for(;g&&g.z<=f;){if(g!==t.prev&&g!==t.next&&v(a.x,a.y,i.x,i.y,o.x,o.y,g.x,g.y)&&y(g.prev,g,g.next)>=0)return!1;g=g.nextZ}return!0}function c(t,e,r){var n=t;do{var a=n.prev,o=n.next.next;!x(a,o)&&b(a,n,n.next,o)&&k(a,o)&&k(o,a)&&(e.push(a.i/r),e.push(n.i/r),e.push(o.i/r),A(n),A(n.next),n=t=o),n=n.next}while(n!==t);return i(n)}function u(t,e,r,n,a,s){var l=t;do{for(var c=l.next.next;c!==l.prev;){if(l.i!==c.i&&m(l,c)){var u=T(l,c);return l=i(l,l.next),u=i(u,u.next),o(l,e,r,n,a,s),void o(u,e,r,n,a,s)}c=c.next}l=l.next}while(l!==t)}function h(t,e){return t.x-e.x}function f(t,e){if(e=function(t,e){var r,n=e,a=t.x,i=t.y,o=-1/0;do{if(i<=n.y&&i>=n.next.y&&n.next.y!==n.y){var s=n.x+(i-n.y)*(n.next.x-n.x)/(n.next.y-n.y);if(s<=a&&s>o){if(o=s,s===a){if(i===n.y)return n;if(i===n.next.y)return n.next}r=n.x<n.next.x?n:n.next}}n=n.next}while(n!==e);if(!r)return null;if(a===o)return r;var l,c=r,u=r.x,h=r.y,f=1/0;n=r;do{a>=n.x&&n.x>=u&&a!==n.x&&v(i<h?a:o,i,u,h,i<h?o:a,i,n.x,n.y)&&(l=Math.abs(i-n.y)/(a-n.x),k(n,t)&&(l<f||l===f&&(n.x>r.x||n.x===r.x&&p(r,n)))&&(r=n,f=l)),n=n.next}while(n!==c);return r}(t,e)){var r=T(e,t);i(r,r.next)}}function p(t,e){return y(t.prev,t,e.prev)<0&&y(e.next,t,t.next)<0}function d(t,e,r,n,a){return(t=1431655765&((t=858993459&((t=252645135&((t=16711935&((t=32767*(t-r)*a)|t<<8))|t<<4))|t<<2))|t<<1))|(e=1431655765&((e=858993459&((e=252645135&((e=16711935&((e=32767*(e-n)*a)|e<<8))|e<<4))|e<<2))|e<<1))<<1}function g(t){var e=t,r=t;do{(e.x<r.x||e.x===r.x&&e.y<r.y)&&(r=e),e=e.next}while(e!==t);return r}function v(t,e,r,n,a,i,o,s){return(a-o)*(e-s)-(t-o)*(i-s)>=0&&(t-o)*(n-s)-(r-o)*(e-s)>=0&&(r-o)*(i-s)-(a-o)*(n-s)>=0}function m(t,e){return t.next.i!==e.i&&t.prev.i!==e.i&&!function(t,e){var r=t;do{if(r.i!==t.i&&r.next.i!==t.i&&r.i!==e.i&&r.next.i!==e.i&&b(r,r.next,t,e))return!0;r=r.next}while(r!==t);return!1}(t,e)&&(k(t,e)&&k(e,t)&&function(t,e){var r=t,n=!1,a=(t.x+e.x)/2,i=(t.y+e.y)/2;do{r.y>i!=r.next.y>i&&r.next.y!==r.y&&a<(r.next.x-r.x)*(i-r.y)/(r.next.y-r.y)+r.x&&(n=!n),r=r.next}while(r!==t);return n}(t,e)&&(y(t.prev,t,e.prev)||y(t,e.prev,e))||x(t,e)&&y(t.prev,t,t.next)>0&&y(e.prev,e,e.next)>0)}function y(t,e,r){return(e.y-t.y)*(r.x-e.x)-(e.x-t.x)*(r.y-e.y)}function x(t,e){return t.x===e.x&&t.y===e.y}function b(t,e,r,n){var a=w(y(t,e,r)),i=w(y(t,e,n)),o=w(y(r,n,t)),s=w(y(r,n,e));return a!==i&&o!==s||(!(0!==a||!_(t,r,e))||(!(0!==i||!_(t,n,e))||(!(0!==o||!_(r,t,n))||!(0!==s||!_(r,e,n)))))}function _(t,e,r){return e.x<=Math.max(t.x,r.x)&&e.x>=Math.min(t.x,r.x)&&e.y<=Math.max(t.y,r.y)&&e.y>=Math.min(t.y,r.y)}function w(t){return t>0?1:t<0?-1:0}function k(t,e){return y(t.prev,t,t.next)<0?y(t,e,t.next)>=0&&y(t,t.prev,e)>=0:y(t,e,t.prev)<0||y(t,t.next,e)<0}function T(t,e){var r=new S(t.i,t.x,t.y),n=new S(e.i,e.x,e.y),a=t.next,i=e.prev;return t.next=e,e.prev=t,r.next=a,a.prev=r,n.next=r,r.prev=n,i.next=n,n.prev=i,n}function M(t,e,r,n){var a=new S(t,e,r);return n?(a.next=n.next,a.prev=n,n.next.prev=a,n.next=a):(a.prev=a,a.next=a),a}function A(t){t.next.prev=t.prev,t.prev.next=t.next,t.prevZ&&(t.prevZ.nextZ=t.nextZ),t.nextZ&&(t.nextZ.prevZ=t.prevZ)}function S(t,e,r){this.i=t,this.x=e,this.y=r,this.prev=null,this.next=null,this.z=null,this.prevZ=null,this.nextZ=null,this.steiner=!1}function E(t,e,r,n){for(var a=0,i=e,o=r-n;i<r;i+=n)a+=(t[o]-t[i])*(t[i+1]+t[o+1]),o=i;return a}e.exports=n,e.exports.default=n,n.deviation=function(t,e,r,n){var a=e&&e.length,i=a?e[0]*r:t.length,o=Math.abs(E(t,0,i,r));if(a)for(var s=0,l=e.length;s<l;s++){var c=e[s]*r,u=s<l-1?e[s+1]*r:t.length;o-=Math.abs(E(t,c,u,r))}var h=0;for(s=0;s<n.length;s+=3){var f=n[s]*r,p=n[s+1]*r,d=n[s+2]*r;h+=Math.abs((t[f]-t[d])*(t[p+1]-t[f+1])-(t[f]-t[p])*(t[d+1]-t[f+1]))}return 0===o&&0===h?0:Math.abs((h-o)/o)},n.flatten=function(t){for(var e=t[0][0].length,r={vertices:[],holes:[],dimensions:e},n=0,a=0;a<t.length;a++){for(var i=0;i<t[a].length;i++)for(var o=0;o<e;o++)r.vertices.push(t[a][i][o]);a>0&&(n+=t[a-1].length,r.holes.push(n))}return r}},{}],174:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=t.length;if(\"number\"!=typeof e){e=0;for(var a=0;a<r;++a){var i=t[a];e=Math.max(e,i[0],i[1])}e=1+(0|e)}e|=0;for(var o=new Array(e),a=0;a<e;++a)o[a]=[];for(var a=0;a<r;++a){var i=t[a];o[i[0]].push(i[1]),o[i[1]].push(i[0])}for(var s=0;s<e;++s)n(o[s],function(t,e){return t-e});return o};var n=t(\"uniq\")},{uniq:546}],175:[function(t,e,r){var n=t(\"strongly-connected-components\");e.exports=function(t){var e,r=[],a=[],i=[],o={},s=[];function l(t){var r,n,u=!1;for(a.push(t),i[t]=!0,r=0;r<s[t].length;r++)(n=s[t][r])===e?(c(e,a),u=!0):i[n]||(u=l(n));if(u)!function t(e){i[e]=!1,o.hasOwnProperty(e)&&Object.keys(o[e]).forEach(function(r){delete o[e][r],i[r]&&t(r)})}(t);else for(r=0;r<s[t].length;r++){n=s[t][r];var h=o[n];h||(h={},o[n]=h),h[n]=!0}return a.pop(),u}function c(t,e){var n=[].concat(e).concat(t);r.push(n)}function u(e){!function(e){for(var r=0;r<t.length;r++)r<e&&(t[r]=[]),t[r]=t[r].filter(function(t){return t>=e})}(e);for(var r,a=n(t).components.filter(function(t){return t.length>1}),i=1/0,o=0;o<a.length;o++)for(var s=0;s<a[o].length;s++)a[o][s]<i&&(i=a[o][s],r=o);var l=a[r];return!!l&&{leastVertex:i,adjList:t.map(function(t,e){return-1===l.indexOf(e)?[]:t.filter(function(t){return-1!==l.indexOf(t)})})}}e=0;for(var h=t.length;e<h;){var f=u(e);if(e=f.leastVertex,s=f.adjList){for(var p=0;p<s.length;p++)for(var d=0;d<s[p].length;d++){var g=s[p][d];i[+g]=!1,o[g]={}}l(e),e+=1}else e=h}return r}},{\"strongly-connected-components\":529}],176:[function(t,e,r){\"use strict\";var n=t(\"../../object/valid-value\");e.exports=function(){return n(this).length=0,this}},{\"../../object/valid-value\":208}],177:[function(t,e,r){\"use strict\";e.exports=t(\"./is-implemented\")()?Array.from:t(\"./shim\")},{\"./is-implemented\":178,\"./shim\":179}],178:[function(t,e,r){\"use strict\";e.exports=function(){var t,e,r=Array.from;return\"function\"==typeof r&&(e=r(t=[\"raz\",\"dwa\"]),Boolean(e&&e!==t&&\"dwa\"===e[1]))}},{}],179:[function(t,e,r){\"use strict\";var n=t(\"es6-symbol\").iterator,a=t(\"../../function/is-arguments\"),i=t(\"../../function/is-function\"),o=t(\"../../number/to-pos-integer\"),s=t(\"../../object/valid-callable\"),l=t(\"../../object/valid-value\"),c=t(\"../../object/is-value\"),u=t(\"../../string/is-string\"),h=Array.isArray,f=Function.prototype.call,p={configurable:!0,enumerable:!0,writable:!0,value:null},d=Object.defineProperty;e.exports=function(t){var e,r,g,v,m,y,x,b,_,w,k=arguments[1],T=arguments[2];if(t=Object(l(t)),c(k)&&s(k),this&&this!==Array&&i(this))e=this;else{if(!k){if(a(t))return 1!==(m=t.length)?Array.apply(null,t):((v=new Array(1))[0]=t[0],v);if(h(t)){for(v=new Array(m=t.length),r=0;r<m;++r)v[r]=t[r];return v}}v=[]}if(!h(t))if(void 0!==(_=t[n])){for(x=s(_).call(t),e&&(v=new e),b=x.next(),r=0;!b.done;)w=k?f.call(k,T,b.value,r):b.value,e?(p.value=w,d(v,r,p)):v[r]=w,b=x.next(),++r;m=r}else if(u(t)){for(m=t.length,e&&(v=new e),r=0,g=0;r<m;++r)w=t[r],r+1<m&&(y=w.charCodeAt(0))>=55296&&y<=56319&&(w+=t[++r]),w=k?f.call(k,T,w,g):w,e?(p.value=w,d(v,g,p)):v[g]=w,++g;m=g}if(void 0===m)for(m=o(t.length),e&&(v=new e(m)),r=0;r<m;++r)w=k?f.call(k,T,t[r],r):t[r],e?(p.value=w,d(v,r,p)):v[r]=w;return e&&(p.value=null,v.length=m),v}},{\"../../function/is-arguments\":180,\"../../function/is-function\":181,\"../../number/to-pos-integer\":187,\"../../object/is-value\":197,\"../../object/valid-callable\":206,\"../../object/valid-value\":208,\"../../string/is-string\":212,\"es6-symbol\":222}],180:[function(t,e,r){\"use strict\";var n=Object.prototype.toString,a=n.call(function(){return arguments}());e.exports=function(t){return n.call(t)===a}},{}],181:[function(t,e,r){\"use strict\";var n=Object.prototype.toString,a=n.call(t(\"./noop\"));e.exports=function(t){return\"function\"==typeof t&&n.call(t)===a}},{\"./noop\":182}],182:[function(t,e,r){\"use strict\";e.exports=function(){}},{}],183:[function(t,e,r){\"use strict\";e.exports=t(\"./is-implemented\")()?Math.sign:t(\"./shim\")},{\"./is-implemented\":184,\"./shim\":185}],184:[function(t,e,r){\"use strict\";e.exports=function(){var t=Math.sign;return\"function\"==typeof t&&(1===t(10)&&-1===t(-20))}},{}],185:[function(t,e,r){\"use strict\";e.exports=function(t){return t=Number(t),isNaN(t)||0===t?t:t>0?1:-1}},{}],186:[function(t,e,r){\"use strict\";var n=t(\"../math/sign\"),a=Math.abs,i=Math.floor;e.exports=function(t){return isNaN(t)?0:0!==(t=Number(t))&&isFinite(t)?n(t)*i(a(t)):t}},{\"../math/sign\":183}],187:[function(t,e,r){\"use strict\";var n=t(\"./to-integer\"),a=Math.max;e.exports=function(t){return a(0,n(t))}},{\"./to-integer\":186}],188:[function(t,e,r){\"use strict\";var n=t(\"./valid-callable\"),a=t(\"./valid-value\"),i=Function.prototype.bind,o=Function.prototype.call,s=Object.keys,l=Object.prototype.propertyIsEnumerable;e.exports=function(t,e){return function(r,c){var u,h=arguments[2],f=arguments[3];return r=Object(a(r)),n(c),u=s(r),f&&u.sort(\"function\"==typeof f?i.call(f,r):void 0),\"function\"!=typeof t&&(t=u[t]),o.call(t,u,function(t,n){return l.call(r,t)?o.call(c,h,r[t],t,r,n):e})}}},{\"./valid-callable\":206,\"./valid-value\":208}],189:[function(t,e,r){\"use strict\";e.exports=t(\"./is-implemented\")()?Object.assign:t(\"./shim\")},{\"./is-implemented\":190,\"./shim\":191}],190:[function(t,e,r){\"use strict\";e.exports=function(){var t,e=Object.assign;return\"function\"==typeof e&&(e(t={foo:\"raz\"},{bar:\"dwa\"},{trzy:\"trzy\"}),t.foo+t.bar+t.trzy===\"razdwatrzy\")}},{}],191:[function(t,e,r){\"use strict\";var n=t(\"../keys\"),a=t(\"../valid-value\"),i=Math.max;e.exports=function(t,e){var r,o,s,l=i(arguments.length,2);for(t=Object(a(t)),s=function(n){try{t[n]=e[n]}catch(t){r||(r=t)}},o=1;o<l;++o)e=arguments[o],n(e).forEach(s);if(void 0!==r)throw r;return t}},{\"../keys\":198,\"../valid-value\":208}],192:[function(t,e,r){\"use strict\";var n=t(\"../array/from\"),a=t(\"./assign\"),i=t(\"./valid-value\");e.exports=function(t){var e=Object(i(t)),r=arguments[1],o=Object(arguments[2]);if(e!==t&&!r)return e;var s={};return r?n(r,function(e){(o.ensure||e in t)&&(s[e]=t[e])}):a(s,t),s}},{\"../array/from\":177,\"./assign\":189,\"./valid-value\":208}],193:[function(t,e,r){\"use strict\";var n,a,i,o,s=Object.create;t(\"./set-prototype-of/is-implemented\")()||(n=t(\"./set-prototype-of/shim\")),e.exports=n?1!==n.level?s:(a={},i={},o={configurable:!1,enumerable:!1,writable:!0,value:void 0},Object.getOwnPropertyNames(Object.prototype).forEach(function(t){i[t]=\"__proto__\"!==t?o:{configurable:!0,enumerable:!1,writable:!0,value:void 0}}),Object.defineProperties(a,i),Object.defineProperty(n,\"nullPolyfill\",{configurable:!1,enumerable:!1,writable:!1,value:a}),function(t,e){return s(null===t?a:t,e)}):s},{\"./set-prototype-of/is-implemented\":204,\"./set-prototype-of/shim\":205}],194:[function(t,e,r){\"use strict\";e.exports=t(\"./_iterate\")(\"forEach\")},{\"./_iterate\":188}],195:[function(t,e,r){\"use strict\";e.exports=function(t){return\"function\"==typeof t}},{}],196:[function(t,e,r){\"use strict\";var n=t(\"./is-value\"),a={function:!0,object:!0};e.exports=function(t){return n(t)&&a[typeof t]||!1}},{\"./is-value\":197}],197:[function(t,e,r){\"use strict\";var n=t(\"../function/noop\")();e.exports=function(t){return t!==n&&null!==t}},{\"../function/noop\":182}],198:[function(t,e,r){\"use strict\";e.exports=t(\"./is-implemented\")()?Object.keys:t(\"./shim\")},{\"./is-implemented\":199,\"./shim\":200}],199:[function(t,e,r){\"use strict\";e.exports=function(){try{return Object.keys(\"primitive\"),!0}catch(t){return!1}}},{}],200:[function(t,e,r){\"use strict\";var n=t(\"../is-value\"),a=Object.keys;e.exports=function(t){return a(n(t)?Object(t):t)}},{\"../is-value\":197}],201:[function(t,e,r){\"use strict\";var n=t(\"./valid-callable\"),a=t(\"./for-each\"),i=Function.prototype.call;e.exports=function(t,e){var r={},o=arguments[2];return n(e),a(t,function(t,n,a,s){r[n]=i.call(e,o,t,n,a,s)}),r}},{\"./for-each\":194,\"./valid-callable\":206}],202:[function(t,e,r){\"use strict\";var n=t(\"./is-value\"),a=Array.prototype.forEach,i=Object.create;e.exports=function(t){var e=i(null);return a.call(arguments,function(t){n(t)&&function(t,e){var r;for(r in t)e[r]=t[r]}(Object(t),e)}),e}},{\"./is-value\":197}],203:[function(t,e,r){\"use strict\";e.exports=t(\"./is-implemented\")()?Object.setPrototypeOf:t(\"./shim\")},{\"./is-implemented\":204,\"./shim\":205}],204:[function(t,e,r){\"use strict\";var n=Object.create,a=Object.getPrototypeOf,i={};e.exports=function(){var t=Object.setPrototypeOf,e=arguments[0]||n;return\"function\"==typeof t&&a(t(e(null),i))===i}},{}],205:[function(t,e,r){\"use strict\";var n,a,i,o,s=t(\"../is-object\"),l=t(\"../valid-value\"),c=Object.prototype.isPrototypeOf,u=Object.defineProperty,h={configurable:!0,enumerable:!1,writable:!0,value:void 0};n=function(t,e){if(l(t),null===e||s(e))return t;throw new TypeError(\"Prototype must be null or an object\")},e.exports=(a=function(){var t,e=Object.create(null),r={},n=Object.getOwnPropertyDescriptor(Object.prototype,\"__proto__\");if(n){try{(t=n.set).call(e,r)}catch(t){}if(Object.getPrototypeOf(e)===r)return{set:t,level:2}}return e.__proto__=r,Object.getPrototypeOf(e)===r?{level:2}:((e={}).__proto__=r,Object.getPrototypeOf(e)===r&&{level:1})}())?(2===a.level?a.set?(o=a.set,i=function(t,e){return o.call(n(t,e),e),t}):i=function(t,e){return n(t,e).__proto__=e,t}:i=function t(e,r){var a;return n(e,r),(a=c.call(t.nullPolyfill,e))&&delete t.nullPolyfill.__proto__,null===r&&(r=t.nullPolyfill),e.__proto__=r,a&&u(t.nullPolyfill,\"__proto__\",h),e},Object.defineProperty(i,\"level\",{configurable:!1,enumerable:!1,writable:!1,value:a.level})):null,t(\"../create\")},{\"../create\":193,\"../is-object\":196,\"../valid-value\":208}],206:[function(t,e,r){\"use strict\";e.exports=function(t){if(\"function\"!=typeof t)throw new TypeError(t+\" is not a function\");return t}},{}],207:[function(t,e,r){\"use strict\";var n=t(\"./is-object\");e.exports=function(t){if(!n(t))throw new TypeError(t+\" is not an Object\");return t}},{\"./is-object\":196}],208:[function(t,e,r){\"use strict\";var n=t(\"./is-value\");e.exports=function(t){if(!n(t))throw new TypeError(\"Cannot use null or undefined\");return t}},{\"./is-value\":197}],209:[function(t,e,r){\"use strict\";e.exports=t(\"./is-implemented\")()?String.prototype.contains:t(\"./shim\")},{\"./is-implemented\":210,\"./shim\":211}],210:[function(t,e,r){\"use strict\";var n=\"razdwatrzy\";e.exports=function(){return\"function\"==typeof n.contains&&(!0===n.contains(\"dwa\")&&!1===n.contains(\"foo\"))}},{}],211:[function(t,e,r){\"use strict\";var n=String.prototype.indexOf;e.exports=function(t){return n.call(this,t,arguments[1])>-1}},{}],212:[function(t,e,r){\"use strict\";var n=Object.prototype.toString,a=n.call(\"\");e.exports=function(t){return\"string\"==typeof t||t&&\"object\"==typeof t&&(t instanceof String||n.call(t)===a)||!1}},{}],213:[function(t,e,r){\"use strict\";var n=Object.create(null),a=Math.random;e.exports=function(){var t;do{t=a().toString(36).slice(2)}while(n[t]);return t}},{}],214:[function(t,e,r){\"use strict\";var n,a=t(\"es5-ext/object/set-prototype-of\"),i=t(\"es5-ext/string/#/contains\"),o=t(\"d\"),s=t(\"es6-symbol\"),l=t(\"./\"),c=Object.defineProperty;n=e.exports=function(t,e){if(!(this instanceof n))throw new TypeError(\"Constructor requires 'new'\");l.call(this,t),e=e?i.call(e,\"key+value\")?\"key+value\":i.call(e,\"key\")?\"key\":\"value\":\"value\",c(this,\"__kind__\",o(\"\",e))},a&&a(n,l),delete n.prototype.constructor,n.prototype=Object.create(l.prototype,{_resolve:o(function(t){return\"value\"===this.__kind__?this.__list__[t]:\"key+value\"===this.__kind__?[t,this.__list__[t]]:t})}),c(n.prototype,s.toStringTag,o(\"c\",\"Array Iterator\"))},{\"./\":217,d:153,\"es5-ext/object/set-prototype-of\":203,\"es5-ext/string/#/contains\":209,\"es6-symbol\":222}],215:[function(t,e,r){\"use strict\";var n=t(\"es5-ext/function/is-arguments\"),a=t(\"es5-ext/object/valid-callable\"),i=t(\"es5-ext/string/is-string\"),o=t(\"./get\"),s=Array.isArray,l=Function.prototype.call,c=Array.prototype.some;e.exports=function(t,e){var r,u,h,f,p,d,g,v,m=arguments[2];if(s(t)||n(t)?r=\"array\":i(t)?r=\"string\":t=o(t),a(e),h=function(){f=!0},\"array\"!==r)if(\"string\"!==r)for(u=t.next();!u.done;){if(l.call(e,m,u.value,h),f)return;u=t.next()}else for(d=t.length,p=0;p<d&&(g=t[p],p+1<d&&(v=g.charCodeAt(0))>=55296&&v<=56319&&(g+=t[++p]),l.call(e,m,g,h),!f);++p);else c.call(t,function(t){return l.call(e,m,t,h),f})}},{\"./get\":216,\"es5-ext/function/is-arguments\":180,\"es5-ext/object/valid-callable\":206,\"es5-ext/string/is-string\":212}],216:[function(t,e,r){\"use strict\";var n=t(\"es5-ext/function/is-arguments\"),a=t(\"es5-ext/string/is-string\"),i=t(\"./array\"),o=t(\"./string\"),s=t(\"./valid-iterable\"),l=t(\"es6-symbol\").iterator;e.exports=function(t){return\"function\"==typeof s(t)[l]?t[l]():n(t)?new i(t):a(t)?new o(t):new i(t)}},{\"./array\":214,\"./string\":219,\"./valid-iterable\":220,\"es5-ext/function/is-arguments\":180,\"es5-ext/string/is-string\":212,\"es6-symbol\":222}],217:[function(t,e,r){\"use strict\";var n,a=t(\"es5-ext/array/#/clear\"),i=t(\"es5-ext/object/assign\"),o=t(\"es5-ext/object/valid-callable\"),s=t(\"es5-ext/object/valid-value\"),l=t(\"d\"),c=t(\"d/auto-bind\"),u=t(\"es6-symbol\"),h=Object.defineProperty,f=Object.defineProperties;e.exports=n=function(t,e){if(!(this instanceof n))throw new TypeError(\"Constructor requires 'new'\");f(this,{__list__:l(\"w\",s(t)),__context__:l(\"w\",e),__nextIndex__:l(\"w\",0)}),e&&(o(e.on),e.on(\"_add\",this._onAdd),e.on(\"_delete\",this._onDelete),e.on(\"_clear\",this._onClear))},delete n.prototype.constructor,f(n.prototype,i({_next:l(function(){var t;if(this.__list__)return this.__redo__&&void 0!==(t=this.__redo__.shift())?t:this.__nextIndex__<this.__list__.length?this.__nextIndex__++:void this._unBind()}),next:l(function(){return this._createResult(this._next())}),_createResult:l(function(t){return void 0===t?{done:!0,value:void 0}:{done:!1,value:this._resolve(t)}}),_resolve:l(function(t){return this.__list__[t]}),_unBind:l(function(){this.__list__=null,delete this.__redo__,this.__context__&&(this.__context__.off(\"_add\",this._onAdd),this.__context__.off(\"_delete\",this._onDelete),this.__context__.off(\"_clear\",this._onClear),this.__context__=null)}),toString:l(function(){return\"[object \"+(this[u.toStringTag]||\"Object\")+\"]\"})},c({_onAdd:l(function(t){t>=this.__nextIndex__||(++this.__nextIndex__,this.__redo__?(this.__redo__.forEach(function(e,r){e>=t&&(this.__redo__[r]=++e)},this),this.__redo__.push(t)):h(this,\"__redo__\",l(\"c\",[t])))}),_onDelete:l(function(t){var e;t>=this.__nextIndex__||(--this.__nextIndex__,this.__redo__&&(-1!==(e=this.__redo__.indexOf(t))&&this.__redo__.splice(e,1),this.__redo__.forEach(function(e,r){e>t&&(this.__redo__[r]=--e)},this)))}),_onClear:l(function(){this.__redo__&&a.call(this.__redo__),this.__nextIndex__=0})}))),h(n.prototype,u.iterator,l(function(){return this}))},{d:153,\"d/auto-bind\":152,\"es5-ext/array/#/clear\":176,\"es5-ext/object/assign\":189,\"es5-ext/object/valid-callable\":206,\"es5-ext/object/valid-value\":208,\"es6-symbol\":222}],218:[function(t,e,r){\"use strict\";var n=t(\"es5-ext/function/is-arguments\"),a=t(\"es5-ext/object/is-value\"),i=t(\"es5-ext/string/is-string\"),o=t(\"es6-symbol\").iterator,s=Array.isArray;e.exports=function(t){return!!a(t)&&(!!s(t)||(!!i(t)||(!!n(t)||\"function\"==typeof t[o])))}},{\"es5-ext/function/is-arguments\":180,\"es5-ext/object/is-value\":197,\"es5-ext/string/is-string\":212,\"es6-symbol\":222}],219:[function(t,e,r){\"use strict\";var n,a=t(\"es5-ext/object/set-prototype-of\"),i=t(\"d\"),o=t(\"es6-symbol\"),s=t(\"./\"),l=Object.defineProperty;n=e.exports=function(t){if(!(this instanceof n))throw new TypeError(\"Constructor requires 'new'\");t=String(t),s.call(this,t),l(this,\"__length__\",i(\"\",t.length))},a&&a(n,s),delete n.prototype.constructor,n.prototype=Object.create(s.prototype,{_next:i(function(){if(this.__list__)return this.__nextIndex__<this.__length__?this.__nextIndex__++:void this._unBind()}),_resolve:i(function(t){var e,r=this.__list__[t];return this.__nextIndex__===this.__length__?r:(e=r.charCodeAt(0))>=55296&&e<=56319?r+this.__list__[this.__nextIndex__++]:r})}),l(n.prototype,o.toStringTag,i(\"c\",\"String Iterator\"))},{\"./\":217,d:153,\"es5-ext/object/set-prototype-of\":203,\"es6-symbol\":222}],220:[function(t,e,r){\"use strict\";var n=t(\"./is-iterable\");e.exports=function(t){if(!n(t))throw new TypeError(t+\" is not iterable\");return t}},{\"./is-iterable\":218}],221:[function(t,e,r){(function(n,a){!function(t,n){\"object\"==typeof r&&\"undefined\"!=typeof e?e.exports=n():t.ES6Promise=n()}(this,function(){\"use strict\";function e(t){return\"function\"==typeof t}var r=Array.isArray?Array.isArray:function(t){return\"[object Array]\"===Object.prototype.toString.call(t)},i=0,o=void 0,s=void 0,l=function(t,e){g[i]=t,g[i+1]=e,2===(i+=2)&&(s?s(v):_())};var c=\"undefined\"!=typeof window?window:void 0,u=c||{},h=u.MutationObserver||u.WebKitMutationObserver,f=\"undefined\"==typeof self&&\"undefined\"!=typeof n&&\"[object process]\"==={}.toString.call(n),p=\"undefined\"!=typeof Uint8ClampedArray&&\"undefined\"!=typeof importScripts&&\"undefined\"!=typeof MessageChannel;function d(){var t=setTimeout;return function(){return t(v,1)}}var g=new Array(1e3);function v(){for(var t=0;t<i;t+=2){(0,g[t])(g[t+1]),g[t]=void 0,g[t+1]=void 0}i=0}var m,y,x,b,_=void 0;function w(t,e){var r=arguments,n=this,a=new this.constructor(M);void 0===a[T]&&U(a);var i,o=n._state;return o?(i=r[o-1],l(function(){return j(o,a,i,n._result)})):R(n,a,t,e),a}function k(t){if(t&&\"object\"==typeof t&&t.constructor===this)return t;var e=new this(M);return O(e,t),e}f?_=function(){return n.nextTick(v)}:h?(y=0,x=new h(v),b=document.createTextNode(\"\"),x.observe(b,{characterData:!0}),_=function(){b.data=y=++y%2}):p?((m=new MessageChannel).port1.onmessage=v,_=function(){return m.port2.postMessage(0)}):_=void 0===c&&\"function\"==typeof t?function(){try{var e=t(\"vertx\");return o=e.runOnLoop||e.runOnContext,function(){o(v)}}catch(t){return d()}}():d();var T=Math.random().toString(36).substring(16);function M(){}var A=void 0,S=1,E=2,L=new B;function C(t){try{return t.then}catch(t){return L.error=t,L}}function P(t,r,n){r.constructor===t.constructor&&n===w&&r.constructor.resolve===k?function(t,e){e._state===S?I(t,e._result):e._state===E?D(t,e._result):R(e,void 0,function(e){return O(t,e)},function(e){return D(t,e)})}(t,r):n===L?D(t,L.error):void 0===n?I(t,r):e(n)?function(t,e,r){l(function(t){var n=!1,a=function(t,e,r,n){try{t.call(e,r,n)}catch(t){return t}}(r,e,function(r){n||(n=!0,e!==r?O(t,r):I(t,r))},function(e){n||(n=!0,D(t,e))},t._label);!n&&a&&(n=!0,D(t,a))},t)}(t,r,n):I(t,r)}function O(t,e){var r;t===e?D(t,new TypeError(\"You cannot resolve a promise with itself\")):\"function\"==typeof(r=e)||\"object\"==typeof r&&null!==r?P(t,e,C(e)):I(t,e)}function z(t){t._onerror&&t._onerror(t._result),F(t)}function I(t,e){t._state===A&&(t._result=e,t._state=S,0!==t._subscribers.length&&l(F,t))}function D(t,e){t._state===A&&(t._state=E,t._result=e,l(z,t))}function R(t,e,r,n){var a=t._subscribers,i=a.length;t._onerror=null,a[i]=e,a[i+S]=r,a[i+E]=n,0===i&&t._state&&l(F,t)}function F(t){var e=t._subscribers,r=t._state;if(0!==e.length){for(var n=void 0,a=void 0,i=t._result,o=0;o<e.length;o+=3)n=e[o],a=e[o+r],n?j(r,n,a,i):a(i);t._subscribers.length=0}}function B(){this.error=null}var N=new B;function j(t,r,n,a){var i=e(n),o=void 0,s=void 0,l=void 0,c=void 0;if(i){if((o=function(t,e){try{return t(e)}catch(t){return N.error=t,N}}(n,a))===N?(c=!0,s=o.error,o=null):l=!0,r===o)return void D(r,new TypeError(\"A promises callback cannot return that same promise.\"))}else o=a,l=!0;r._state!==A||(i&&l?O(r,o):c?D(r,s):t===S?I(r,o):t===E&&D(r,o))}var V=0;function U(t){t[T]=V++,t._state=void 0,t._result=void 0,t._subscribers=[]}function q(t,e){this._instanceConstructor=t,this.promise=new t(M),this.promise[T]||U(this.promise),r(e)?(this._input=e,this.length=e.length,this._remaining=e.length,this._result=new Array(this.length),0===this.length?I(this.promise,this._result):(this.length=this.length||0,this._enumerate(),0===this._remaining&&I(this.promise,this._result))):D(this.promise,new Error(\"Array Methods must be provided an Array\"))}function H(t){this[T]=V++,this._result=this._state=void 0,this._subscribers=[],M!==t&&(\"function\"!=typeof t&&function(){throw new TypeError(\"You must pass a resolver function as the first argument to the promise constructor\")}(),this instanceof H?function(t,e){try{e(function(e){O(t,e)},function(e){D(t,e)})}catch(e){D(t,e)}}(this,t):function(){throw new TypeError(\"Failed to construct 'Promise': Please use the 'new' operator, this object constructor cannot be called as a function.\")}())}function G(){var t=void 0;if(\"undefined\"!=typeof a)t=a;else if(\"undefined\"!=typeof self)t=self;else try{t=Function(\"return this\")()}catch(t){throw new Error(\"polyfill failed because global object is unavailable in this environment\")}var e=t.Promise;if(e){var r=null;try{r=Object.prototype.toString.call(e.resolve())}catch(t){}if(\"[object Promise]\"===r&&!e.cast)return}t.Promise=H}return q.prototype._enumerate=function(){for(var t=this.length,e=this._input,r=0;this._state===A&&r<t;r++)this._eachEntry(e[r],r)},q.prototype._eachEntry=function(t,e){var r=this._instanceConstructor,n=r.resolve;if(n===k){var a=C(t);if(a===w&&t._state!==A)this._settledAt(t._state,e,t._result);else if(\"function\"!=typeof a)this._remaining--,this._result[e]=t;else if(r===H){var i=new r(M);P(i,t,a),this._willSettleAt(i,e)}else this._willSettleAt(new r(function(e){return e(t)}),e)}else this._willSettleAt(n(t),e)},q.prototype._settledAt=function(t,e,r){var n=this.promise;n._state===A&&(this._remaining--,t===E?D(n,r):this._result[e]=r),0===this._remaining&&I(n,this._result)},q.prototype._willSettleAt=function(t,e){var r=this;R(t,void 0,function(t){return r._settledAt(S,e,t)},function(t){return r._settledAt(E,e,t)})},H.all=function(t){return new q(this,t).promise},H.race=function(t){var e=this;return r(t)?new e(function(r,n){for(var a=t.length,i=0;i<a;i++)e.resolve(t[i]).then(r,n)}):new e(function(t,e){return e(new TypeError(\"You must pass an array to race.\"))})},H.resolve=k,H.reject=function(t){var e=new this(M);return D(e,t),e},H._setScheduler=function(t){s=t},H._setAsap=function(t){l=t},H._asap=l,H.prototype={constructor:H,then:w,catch:function(t){return this.then(null,t)}},G(),H.polyfill=G,H.Promise=H,H})}).call(this,t(\"_process\"),\"undefined\"!=typeof global?global:\"undefined\"!=typeof self?self:\"undefined\"!=typeof window?window:{})},{_process:484}],222:[function(t,e,r){\"use strict\";e.exports=t(\"./is-implemented\")()?Symbol:t(\"./polyfill\")},{\"./is-implemented\":223,\"./polyfill\":225}],223:[function(t,e,r){\"use strict\";var n={object:!0,symbol:!0};e.exports=function(){var t;if(\"function\"!=typeof Symbol)return!1;t=Symbol(\"test symbol\");try{String(t)}catch(t){return!1}return!!n[typeof Symbol.iterator]&&(!!n[typeof Symbol.toPrimitive]&&!!n[typeof Symbol.toStringTag])}},{}],224:[function(t,e,r){\"use strict\";e.exports=function(t){return!!t&&(\"symbol\"==typeof t||!!t.constructor&&(\"Symbol\"===t.constructor.name&&\"Symbol\"===t[t.constructor.toStringTag]))}},{}],225:[function(t,e,r){\"use strict\";var n,a,i,o,s=t(\"d\"),l=t(\"./validate-symbol\"),c=Object.create,u=Object.defineProperties,h=Object.defineProperty,f=Object.prototype,p=c(null);if(\"function\"==typeof Symbol){n=Symbol;try{String(n()),o=!0}catch(t){}}var d,g=(d=c(null),function(t){for(var e,r,n=0;d[t+(n||\"\")];)++n;return d[t+=n||\"\"]=!0,h(f,e=\"@@\"+t,s.gs(null,function(t){r||(r=!0,h(this,e,s(t)),r=!1)})),e});i=function(t){if(this instanceof i)throw new TypeError(\"Symbol is not a constructor\");return a(t)},e.exports=a=function t(e){var r;if(this instanceof t)throw new TypeError(\"Symbol is not a constructor\");return o?n(e):(r=c(i.prototype),e=void 0===e?\"\":String(e),u(r,{__description__:s(\"\",e),__name__:s(\"\",g(e))}))},u(a,{for:s(function(t){return p[t]?p[t]:p[t]=a(String(t))}),keyFor:s(function(t){var e;for(e in l(t),p)if(p[e]===t)return e}),hasInstance:s(\"\",n&&n.hasInstance||a(\"hasInstance\")),isConcatSpreadable:s(\"\",n&&n.isConcatSpreadable||a(\"isConcatSpreadable\")),iterator:s(\"\",n&&n.iterator||a(\"iterator\")),match:s(\"\",n&&n.match||a(\"match\")),replace:s(\"\",n&&n.replace||a(\"replace\")),search:s(\"\",n&&n.search||a(\"search\")),species:s(\"\",n&&n.species||a(\"species\")),split:s(\"\",n&&n.split||a(\"split\")),toPrimitive:s(\"\",n&&n.toPrimitive||a(\"toPrimitive\")),toStringTag:s(\"\",n&&n.toStringTag||a(\"toStringTag\")),unscopables:s(\"\",n&&n.unscopables||a(\"unscopables\"))}),u(i.prototype,{constructor:s(a),toString:s(\"\",function(){return this.__name__})}),u(a.prototype,{toString:s(function(){return\"Symbol (\"+l(this).__description__+\")\"}),valueOf:s(function(){return l(this)})}),h(a.prototype,a.toPrimitive,s(\"\",function(){var t=l(this);return\"symbol\"==typeof t?t:t.toString()})),h(a.prototype,a.toStringTag,s(\"c\",\"Symbol\")),h(i.prototype,a.toStringTag,s(\"c\",a.prototype[a.toStringTag])),h(i.prototype,a.toPrimitive,s(\"c\",a.prototype[a.toPrimitive]))},{\"./validate-symbol\":226,d:153}],226:[function(t,e,r){\"use strict\";var n=t(\"./is-symbol\");e.exports=function(t){if(!n(t))throw new TypeError(t+\" is not a symbol\");return t}},{\"./is-symbol\":224}],227:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){var n=e||0,a=r||1;return[[t[12]+t[0],t[13]+t[1],t[14]+t[2],t[15]+t[3]],[t[12]-t[0],t[13]-t[1],t[14]-t[2],t[15]-t[3]],[t[12]+t[4],t[13]+t[5],t[14]+t[6],t[15]+t[7]],[t[12]-t[4],t[13]-t[5],t[14]-t[6],t[15]-t[7]],[n*t[12]+t[8],n*t[13]+t[9],n*t[14]+t[10],n*t[15]+t[11]],[a*t[12]-t[8],a*t[13]-t[9],a*t[14]-t[10],a*t[15]-t[11]]]}},{}],228:[function(t,e,r){\"use strict\";var n=t(\"is-string-blank\");e.exports=function(t){var e=typeof t;if(\"string\"===e){var r=t;if(0===(t=+t)&&n(r))return!1}else if(\"number\"!==e)return!1;return t-t<1}},{\"is-string-blank\":425}],229:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){switch(arguments.length){case 0:return new o([0],[0],0);case 1:if(\"number\"==typeof t){var n=l(t);return new o(n,n,0)}return new o(t,l(t.length),0);case 2:if(\"number\"==typeof e){var n=l(t.length);return new o(t,n,+e)}r=0;case 3:if(t.length!==e.length)throw new Error(\"state and velocity lengths must match\");return new o(t,e,r)}};var n=t(\"cubic-hermite\"),a=t(\"binary-search-bounds\");function i(t,e,r){return Math.min(e,Math.max(t,r))}function o(t,e,r){this.dimension=t.length,this.bounds=[new Array(this.dimension),new Array(this.dimension)];for(var n=0;n<this.dimension;++n)this.bounds[0][n]=-1/0,this.bounds[1][n]=1/0;this._state=t.slice().reverse(),this._velocity=e.slice().reverse(),this._time=[r],this._scratch=[t.slice(),t.slice(),t.slice(),t.slice(),t.slice()]}var s=o.prototype;function l(t){for(var e=new Array(t),r=0;r<t;++r)e[r]=0;return e}s.flush=function(t){var e=a.gt(this._time,t)-1;e<=0||(this._time.splice(0,e),this._state.splice(0,e*this.dimension),this._velocity.splice(0,e*this.dimension))},s.curve=function(t){var e=this._time,r=e.length,o=a.le(e,t),s=this._scratch[0],l=this._state,c=this._velocity,u=this.dimension,h=this.bounds;if(o<0)for(var f=u-1,p=0;p<u;++p,--f)s[p]=l[f];else if(o>=r-1){f=l.length-1;var d=t-e[r-1];for(p=0;p<u;++p,--f)s[p]=l[f]+d*c[f]}else{f=u*(o+1)-1;var g=e[o],v=e[o+1]-g||1,m=this._scratch[1],y=this._scratch[2],x=this._scratch[3],b=this._scratch[4],_=!0;for(p=0;p<u;++p,--f)m[p]=l[f],x[p]=c[f]*v,y[p]=l[f+u],b[p]=c[f+u]*v,_=_&&m[p]===y[p]&&x[p]===b[p]&&0===x[p];if(_)for(p=0;p<u;++p)s[p]=m[p];else n(m,x,y,b,(t-g)/v,s)}var w=h[0],k=h[1];for(p=0;p<u;++p)s[p]=i(w[p],k[p],s[p]);return s},s.dcurve=function(t){var e=this._time,r=e.length,i=a.le(e,t),o=this._scratch[0],s=this._state,l=this._velocity,c=this.dimension;if(i>=r-1)for(var u=s.length-1,h=(e[r-1],0);h<c;++h,--u)o[h]=l[u];else{u=c*(i+1)-1;var f=e[i],p=e[i+1]-f||1,d=this._scratch[1],g=this._scratch[2],v=this._scratch[3],m=this._scratch[4],y=!0;for(h=0;h<c;++h,--u)d[h]=s[u],v[h]=l[u]*p,g[h]=s[u+c],m[h]=l[u+c]*p,y=y&&d[h]===g[h]&&v[h]===m[h]&&0===v[h];if(y)for(h=0;h<c;++h)o[h]=0;else{n.derivative(d,v,g,m,(t-f)/p,o);for(h=0;h<c;++h)o[h]/=p}}return o},s.lastT=function(){var t=this._time;return t[t.length-1]},s.stable=function(){for(var t=this._velocity,e=t.length,r=this.dimension-1;r>=0;--r)if(t[--e])return!1;return!0},s.jump=function(t){var e=this.lastT(),r=this.dimension;if(!(t<e||arguments.length!==r+1)){var n=this._state,a=this._velocity,o=n.length-this.dimension,s=this.bounds,l=s[0],c=s[1];this._time.push(e,t);for(var u=0;u<2;++u)for(var h=0;h<r;++h)n.push(n[o++]),a.push(0);this._time.push(t);for(h=r;h>0;--h)n.push(i(l[h-1],c[h-1],arguments[h])),a.push(0)}},s.push=function(t){var e=this.lastT(),r=this.dimension;if(!(t<e||arguments.length!==r+1)){var n=this._state,a=this._velocity,o=n.length-this.dimension,s=t-e,l=this.bounds,c=l[0],u=l[1],h=s>1e-6?1/s:0;this._time.push(t);for(var f=r;f>0;--f){var p=i(c[f-1],u[f-1],arguments[f]);n.push(p),a.push((p-n[o++])*h)}}},s.set=function(t){var e=this.dimension;if(!(t<this.lastT()||arguments.length!==e+1)){var r=this._state,n=this._velocity,a=this.bounds,o=a[0],s=a[1];this._time.push(t);for(var l=e;l>0;--l)r.push(i(o[l-1],s[l-1],arguments[l])),n.push(0)}},s.move=function(t){var e=this.lastT(),r=this.dimension;if(!(t<=e||arguments.length!==r+1)){var n=this._state,a=this._velocity,o=n.length-this.dimension,s=this.bounds,l=s[0],c=s[1],u=t-e,h=u>1e-6?1/u:0;this._time.push(t);for(var f=r;f>0;--f){var p=arguments[f];n.push(i(l[f-1],c[f-1],n[o++]+p)),a.push(p*h)}}},s.idle=function(t){var e=this.lastT();if(!(t<e)){var r=this.dimension,n=this._state,a=this._velocity,o=n.length-r,s=this.bounds,l=s[0],c=s[1],u=t-e;this._time.push(t);for(var h=r-1;h>=0;--h)n.push(i(l[h],c[h],n[o]+u*a[o])),a.push(0),o+=1}}},{\"binary-search-bounds\":93,\"cubic-hermite\":147}],230:[function(t,e,r){var n=t(\"dtype\");e.exports=function(t,e,r){if(!t)throw new TypeError(\"must specify data as first parameter\");if(r=0|+(r||0),Array.isArray(t)&&t[0]&&\"number\"==typeof t[0][0]){var a,i,o,s,l=t[0].length,c=t.length*l;e&&\"string\"!=typeof e||(e=new(n(e||\"float32\"))(c+r));var u=e.length-r;if(c!==u)throw new Error(\"source length \"+c+\" (\"+l+\"x\"+t.length+\") does not match destination length \"+u);for(a=0,o=r;a<t.length;a++)for(i=0;i<l;i++)e[o++]=null===t[a][i]?NaN:t[a][i]}else if(e&&\"string\"!=typeof e)e.set(t,r);else{var h=n(e||\"float32\");if(Array.isArray(t)||\"array\"===e)for(e=new h(t.length+r),a=0,o=r,s=e.length;o<s;o++,a++)e[o]=null===t[a]?NaN:t[a];else 0===r?e=new h(t):(e=new h(t.length+r)).set(t,r)}return e}},{dtype:171}],231:[function(t,e,r){\"use strict\";var n=t(\"css-font/stringify\"),a=[32,126];e.exports=function(t){var e=(t=t||{}).shape?t.shape:t.canvas?[t.canvas.width,t.canvas.height]:[512,512],r=t.canvas||document.createElement(\"canvas\"),i=t.font,o=\"number\"==typeof t.step?[t.step,t.step]:t.step||[32,32],s=t.chars||a;i&&\"string\"!=typeof i&&(i=n(i));if(Array.isArray(s)){if(2===s.length&&\"number\"==typeof s[0]&&\"number\"==typeof s[1]){for(var l=[],c=s[0],u=0;c<=s[1];c++)l[u++]=String.fromCharCode(c);s=l}}else s=String(s).split(\"\");e=e.slice(),r.width=e[0],r.height=e[1];var h=r.getContext(\"2d\");h.fillStyle=\"#000\",h.fillRect(0,0,r.width,r.height),h.font=i,h.textAlign=\"center\",h.textBaseline=\"middle\",h.fillStyle=\"#fff\";for(var f=o[0]/2,p=o[1]/2,c=0;c<s.length;c++)h.fillText(s[c],f,p),(f+=o[0])>e[0]-o[0]/2&&(f=o[0]/2,p+=o[1]);return r}},{\"css-font/stringify\":144}],232:[function(t,e,r){\"use strict\";function n(t,e){e||(e={}),(\"string\"==typeof t||Array.isArray(t))&&(e.family=t);var r=Array.isArray(e.family)?e.family.join(\", \"):e.family;if(!r)throw Error(\"`family` must be defined\");var s=e.size||e.fontSize||e.em||48,l=e.weight||e.fontWeight||\"\",c=(t=[e.style||e.fontStyle||\"\",l,s].join(\" \")+\"px \"+r,e.origin||\"top\");if(n.cache[r]&&s<=n.cache[r].em)return a(n.cache[r],c);var u=e.canvas||n.canvas,h=u.getContext(\"2d\"),f={upper:void 0!==e.upper?e.upper:\"H\",lower:void 0!==e.lower?e.lower:\"x\",descent:void 0!==e.descent?e.descent:\"p\",ascent:void 0!==e.ascent?e.ascent:\"h\",tittle:void 0!==e.tittle?e.tittle:\"i\",overshoot:void 0!==e.overshoot?e.overshoot:\"O\"},p=Math.ceil(1.5*s);u.height=p,u.width=.5*p,h.font=t;var d={top:0};h.clearRect(0,0,p,p),h.textBaseline=\"top\",h.fillStyle=\"black\",h.fillText(\"H\",0,0);var g=i(h.getImageData(0,0,p,p));h.clearRect(0,0,p,p),h.textBaseline=\"bottom\",h.fillText(\"H\",0,p);var v=i(h.getImageData(0,0,p,p));d.lineHeight=d.bottom=p-v+g,h.clearRect(0,0,p,p),h.textBaseline=\"alphabetic\",h.fillText(\"H\",0,p);var m=p-i(h.getImageData(0,0,p,p))-1+g;d.baseline=d.alphabetic=m,h.clearRect(0,0,p,p),h.textBaseline=\"middle\",h.fillText(\"H\",0,.5*p);var y=i(h.getImageData(0,0,p,p));d.median=d.middle=p-y-1+g-.5*p,h.clearRect(0,0,p,p),h.textBaseline=\"hanging\",h.fillText(\"H\",0,.5*p);var x=i(h.getImageData(0,0,p,p));d.hanging=p-x-1+g-.5*p,h.clearRect(0,0,p,p),h.textBaseline=\"ideographic\",h.fillText(\"H\",0,p);var b=i(h.getImageData(0,0,p,p));if(d.ideographic=p-b-1+g,f.upper&&(h.clearRect(0,0,p,p),h.textBaseline=\"top\",h.fillText(f.upper,0,0),d.upper=i(h.getImageData(0,0,p,p)),d.capHeight=d.baseline-d.upper),f.lower&&(h.clearRect(0,0,p,p),h.textBaseline=\"top\",h.fillText(f.lower,0,0),d.lower=i(h.getImageData(0,0,p,p)),d.xHeight=d.baseline-d.lower),f.tittle&&(h.clearRect(0,0,p,p),h.textBaseline=\"top\",h.fillText(f.tittle,0,0),d.tittle=i(h.getImageData(0,0,p,p))),f.ascent&&(h.clearRect(0,0,p,p),h.textBaseline=\"top\",h.fillText(f.ascent,0,0),d.ascent=i(h.getImageData(0,0,p,p))),f.descent&&(h.clearRect(0,0,p,p),h.textBaseline=\"top\",h.fillText(f.descent,0,0),d.descent=o(h.getImageData(0,0,p,p))),f.overshoot){h.clearRect(0,0,p,p),h.textBaseline=\"top\",h.fillText(f.overshoot,0,0);var _=o(h.getImageData(0,0,p,p));d.overshoot=_-m}for(var w in d)d[w]/=s;return d.em=s,n.cache[r]=d,a(d,c)}function a(t,e){var r={};for(var n in\"string\"==typeof e&&(e=t[e]),t)\"em\"!==n&&(r[n]=t[n]-e);return r}function i(t){for(var e=t.height,r=t.data,n=3;n<r.length;n+=4)if(0!==r[n])return Math.floor(.25*(n-3)/e)}function o(t){for(var e=t.height,r=t.data,n=r.length-1;n>0;n-=4)if(0!==r[n])return Math.floor(.25*(n-3)/e)}e.exports=n,n.canvas=document.createElement(\"canvas\"),n.cache={}},{}],233:[function(t,e,r){\"use strict\";e.exports=function(t){return new c(t||d,null)};var n=0,a=1;function i(t,e,r,n,a,i){this._color=t,this.key=e,this.value=r,this.left=n,this.right=a,this._count=i}function o(t){return new i(t._color,t.key,t.value,t.left,t.right,t._count)}function s(t,e){return new i(t,e.key,e.value,e.left,e.right,e._count)}function l(t){t._count=1+(t.left?t.left._count:0)+(t.right?t.right._count:0)}function c(t,e){this._compare=t,this.root=e}var u=c.prototype;function h(t,e){this.tree=t,this._stack=e}Object.defineProperty(u,\"keys\",{get:function(){var t=[];return this.forEach(function(e,r){t.push(e)}),t}}),Object.defineProperty(u,\"values\",{get:function(){var t=[];return this.forEach(function(e,r){t.push(r)}),t}}),Object.defineProperty(u,\"length\",{get:function(){return this.root?this.root._count:0}}),u.insert=function(t,e){for(var r=this._compare,o=this.root,u=[],h=[];o;){var f=r(t,o.key);u.push(o),h.push(f),o=f<=0?o.left:o.right}u.push(new i(n,t,e,null,null,1));for(var p=u.length-2;p>=0;--p){o=u[p];h[p]<=0?u[p]=new i(o._color,o.key,o.value,u[p+1],o.right,o._count+1):u[p]=new i(o._color,o.key,o.value,o.left,u[p+1],o._count+1)}for(p=u.length-1;p>1;--p){var d=u[p-1];o=u[p];if(d._color===a||o._color===a)break;var g=u[p-2];if(g.left===d)if(d.left===o){if(!(v=g.right)||v._color!==n){if(g._color=n,g.left=d.right,d._color=a,d.right=g,u[p-2]=d,u[p-1]=o,l(g),l(d),p>=3)(m=u[p-3]).left===g?m.left=d:m.right=d;break}d._color=a,g.right=s(a,v),g._color=n,p-=1}else{if(!(v=g.right)||v._color!==n){if(d.right=o.left,g._color=n,g.left=o.right,o._color=a,o.left=d,o.right=g,u[p-2]=o,u[p-1]=d,l(g),l(d),l(o),p>=3)(m=u[p-3]).left===g?m.left=o:m.right=o;break}d._color=a,g.right=s(a,v),g._color=n,p-=1}else if(d.right===o){if(!(v=g.left)||v._color!==n){if(g._color=n,g.right=d.left,d._color=a,d.left=g,u[p-2]=d,u[p-1]=o,l(g),l(d),p>=3)(m=u[p-3]).right===g?m.right=d:m.left=d;break}d._color=a,g.left=s(a,v),g._color=n,p-=1}else{var v;if(!(v=g.left)||v._color!==n){var m;if(d.left=o.right,g._color=n,g.right=o.left,o._color=a,o.right=d,o.left=g,u[p-2]=o,u[p-1]=d,l(g),l(d),l(o),p>=3)(m=u[p-3]).right===g?m.right=o:m.left=o;break}d._color=a,g.left=s(a,v),g._color=n,p-=1}}return u[0]._color=a,new c(r,u[0])},u.forEach=function(t,e,r){if(this.root)switch(arguments.length){case 1:return function t(e,r){var n;if(r.left&&(n=t(e,r.left)))return n;return(n=e(r.key,r.value))||(r.right?t(e,r.right):void 0)}(t,this.root);case 2:return function t(e,r,n,a){if(r(e,a.key)<=0){var i;if(a.left&&(i=t(e,r,n,a.left)))return i;if(i=n(a.key,a.value))return i}if(a.right)return t(e,r,n,a.right)}(e,this._compare,t,this.root);case 3:if(this._compare(e,r)>=0)return;return function t(e,r,n,a,i){var o,s=n(e,i.key),l=n(r,i.key);if(s<=0){if(i.left&&(o=t(e,r,n,a,i.left)))return o;if(l>0&&(o=a(i.key,i.value)))return o}if(l>0&&i.right)return t(e,r,n,a,i.right)}(e,r,this._compare,t,this.root)}},Object.defineProperty(u,\"begin\",{get:function(){for(var t=[],e=this.root;e;)t.push(e),e=e.left;return new h(this,t)}}),Object.defineProperty(u,\"end\",{get:function(){for(var t=[],e=this.root;e;)t.push(e),e=e.right;return new h(this,t)}}),u.at=function(t){if(t<0)return new h(this,[]);for(var e=this.root,r=[];;){if(r.push(e),e.left){if(t<e.left._count){e=e.left;continue}t-=e.left._count}if(!t)return new h(this,r);if(t-=1,!e.right)break;if(t>=e.right._count)break;e=e.right}return new h(this,[])},u.ge=function(t){for(var e=this._compare,r=this.root,n=[],a=0;r;){var i=e(t,r.key);n.push(r),i<=0&&(a=n.length),r=i<=0?r.left:r.right}return n.length=a,new h(this,n)},u.gt=function(t){for(var e=this._compare,r=this.root,n=[],a=0;r;){var i=e(t,r.key);n.push(r),i<0&&(a=n.length),r=i<0?r.left:r.right}return n.length=a,new h(this,n)},u.lt=function(t){for(var e=this._compare,r=this.root,n=[],a=0;r;){var i=e(t,r.key);n.push(r),i>0&&(a=n.length),r=i<=0?r.left:r.right}return n.length=a,new h(this,n)},u.le=function(t){for(var e=this._compare,r=this.root,n=[],a=0;r;){var i=e(t,r.key);n.push(r),i>=0&&(a=n.length),r=i<0?r.left:r.right}return n.length=a,new h(this,n)},u.find=function(t){for(var e=this._compare,r=this.root,n=[];r;){var a=e(t,r.key);if(n.push(r),0===a)return new h(this,n);r=a<=0?r.left:r.right}return new h(this,[])},u.remove=function(t){var e=this.find(t);return e?e.remove():this},u.get=function(t){for(var e=this._compare,r=this.root;r;){var n=e(t,r.key);if(0===n)return r.value;r=n<=0?r.left:r.right}};var f=h.prototype;function p(t,e){t.key=e.key,t.value=e.value,t.left=e.left,t.right=e.right,t._color=e._color,t._count=e._count}function d(t,e){return t<e?-1:t>e?1:0}Object.defineProperty(f,\"valid\",{get:function(){return this._stack.length>0}}),Object.defineProperty(f,\"node\",{get:function(){return this._stack.length>0?this._stack[this._stack.length-1]:null},enumerable:!0}),f.clone=function(){return new h(this.tree,this._stack.slice())},f.remove=function(){var t=this._stack;if(0===t.length)return this.tree;var e=new Array(t.length),r=t[t.length-1];e[e.length-1]=new i(r._color,r.key,r.value,r.left,r.right,r._count);for(var u=t.length-2;u>=0;--u){(r=t[u]).left===t[u+1]?e[u]=new i(r._color,r.key,r.value,e[u+1],r.right,r._count):e[u]=new i(r._color,r.key,r.value,r.left,e[u+1],r._count)}if((r=e[e.length-1]).left&&r.right){var h=e.length;for(r=r.left;r.right;)e.push(r),r=r.right;var f=e[h-1];e.push(new i(r._color,f.key,f.value,r.left,r.right,r._count)),e[h-1].key=r.key,e[h-1].value=r.value;for(u=e.length-2;u>=h;--u)r=e[u],e[u]=new i(r._color,r.key,r.value,r.left,e[u+1],r._count);e[h-1].left=e[h]}if((r=e[e.length-1])._color===n){var d=e[e.length-2];d.left===r?d.left=null:d.right===r&&(d.right=null),e.pop();for(u=0;u<e.length;++u)e[u]._count--;return new c(this.tree._compare,e[0])}if(r.left||r.right){r.left?p(r,r.left):r.right&&p(r,r.right),r._color=a;for(u=0;u<e.length-1;++u)e[u]._count--;return new c(this.tree._compare,e[0])}if(1===e.length)return new c(this.tree._compare,null);for(u=0;u<e.length;++u)e[u]._count--;var g=e[e.length-2];return function(t){for(var e,r,i,c,u=t.length-1;u>=0;--u){if(e=t[u],0===u)return void(e._color=a);if((r=t[u-1]).left===e){if((i=r.right).right&&i.right._color===n)return c=(i=r.right=o(i)).right=o(i.right),r.right=i.left,i.left=r,i.right=c,i._color=r._color,e._color=a,r._color=a,c._color=a,l(r),l(i),u>1&&((h=t[u-2]).left===r?h.left=i:h.right=i),void(t[u-1]=i);if(i.left&&i.left._color===n)return c=(i=r.right=o(i)).left=o(i.left),r.right=c.left,i.left=c.right,c.left=r,c.right=i,c._color=r._color,r._color=a,i._color=a,e._color=a,l(r),l(i),l(c),u>1&&((h=t[u-2]).left===r?h.left=c:h.right=c),void(t[u-1]=c);if(i._color===a){if(r._color===n)return r._color=a,void(r.right=s(n,i));r.right=s(n,i);continue}i=o(i),r.right=i.left,i.left=r,i._color=r._color,r._color=n,l(r),l(i),u>1&&((h=t[u-2]).left===r?h.left=i:h.right=i),t[u-1]=i,t[u]=r,u+1<t.length?t[u+1]=e:t.push(e),u+=2}else{if((i=r.left).left&&i.left._color===n)return c=(i=r.left=o(i)).left=o(i.left),r.left=i.right,i.right=r,i.left=c,i._color=r._color,e._color=a,r._color=a,c._color=a,l(r),l(i),u>1&&((h=t[u-2]).right===r?h.right=i:h.left=i),void(t[u-1]=i);if(i.right&&i.right._color===n)return c=(i=r.left=o(i)).right=o(i.right),r.left=c.right,i.right=c.left,c.right=r,c.left=i,c._color=r._color,r._color=a,i._color=a,e._color=a,l(r),l(i),l(c),u>1&&((h=t[u-2]).right===r?h.right=c:h.left=c),void(t[u-1]=c);if(i._color===a){if(r._color===n)return r._color=a,void(r.left=s(n,i));r.left=s(n,i);continue}var h;i=o(i),r.left=i.right,i.right=r,i._color=r._color,r._color=n,l(r),l(i),u>1&&((h=t[u-2]).right===r?h.right=i:h.left=i),t[u-1]=i,t[u]=r,u+1<t.length?t[u+1]=e:t.push(e),u+=2}}}(e),g.left===r?g.left=null:g.right=null,new c(this.tree._compare,e[0])},Object.defineProperty(f,\"key\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].key},enumerable:!0}),Object.defineProperty(f,\"value\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].value},enumerable:!0}),Object.defineProperty(f,\"index\",{get:function(){var t=0,e=this._stack;if(0===e.length){var r=this.tree.root;return r?r._count:0}e[e.length-1].left&&(t=e[e.length-1].left._count);for(var n=e.length-2;n>=0;--n)e[n+1]===e[n].right&&(++t,e[n].left&&(t+=e[n].left._count));return t},enumerable:!0}),f.next=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.right)for(e=e.right;e;)t.push(e),e=e.left;else for(t.pop();t.length>0&&t[t.length-1].right===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(f,\"hasNext\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].right)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].left===t[e])return!0;return!1}}),f.update=function(t){var e=this._stack;if(0===e.length)throw new Error(\"Can't update empty node!\");var r=new Array(e.length),n=e[e.length-1];r[r.length-1]=new i(n._color,n.key,t,n.left,n.right,n._count);for(var a=e.length-2;a>=0;--a)(n=e[a]).left===e[a+1]?r[a]=new i(n._color,n.key,n.value,r[a+1],n.right,n._count):r[a]=new i(n._color,n.key,n.value,n.left,r[a+1],n._count);return new c(this.tree._compare,r[0])},f.prev=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.left)for(e=e.left;e;)t.push(e),e=e.right;else for(t.pop();t.length>0&&t[t.length-1].left===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(f,\"hasPrev\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].left)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].right===t[e])return!0;return!1}})},{}],234:[function(t,e,r){var n=[.9999999999998099,676.5203681218851,-1259.1392167224028,771.3234287776531,-176.6150291621406,12.507343278686905,-.13857109526572012,9984369578019572e-21,1.5056327351493116e-7],a=607/128,i=[.9999999999999971,57.15623566586292,-59.59796035547549,14.136097974741746,-.4919138160976202,3399464998481189e-20,4652362892704858e-20,-9837447530487956e-20,.0001580887032249125,-.00021026444172410488,.00021743961811521265,-.0001643181065367639,8441822398385275e-20,-26190838401581408e-21,36899182659531625e-22];function o(t){if(t<0)return Number(\"0/0\");for(var e=i[0],r=i.length-1;r>0;--r)e+=i[r]/(t+r);var n=t+a+.5;return.5*Math.log(2*Math.PI)+(t+.5)*Math.log(n)-n+Math.log(e)-Math.log(t)}e.exports=function t(e){if(e<.5)return Math.PI/(Math.sin(Math.PI*e)*t(1-e));if(e>100)return Math.exp(o(e));e-=1;for(var r=n[0],a=1;a<9;a++)r+=n[a]/(e+a);var i=e+7+.5;return Math.sqrt(2*Math.PI)*Math.pow(i,e+.5)*Math.exp(-i)*r},e.exports.log=o},{}],235:[function(t,e,r){e.exports=function(t,e){if(\"string\"!=typeof t)throw new TypeError(\"must specify type string\");if(e=e||{},\"undefined\"==typeof document&&!e.canvas)return null;var r=e.canvas||document.createElement(\"canvas\");\"number\"==typeof e.width&&(r.width=e.width);\"number\"==typeof e.height&&(r.height=e.height);var n,a=e;try{var i=[t];0===t.indexOf(\"webgl\")&&i.push(\"experimental-\"+t);for(var o=0;o<i.length;o++)if(n=r.getContext(i[o],a))return n}catch(t){n=null}return n||null}},{}],236:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=new u(t);return r.update(e),r};var n=t(\"./lib/text.js\"),a=t(\"./lib/lines.js\"),i=t(\"./lib/background.js\"),o=t(\"./lib/cube.js\"),s=t(\"./lib/ticks.js\"),l=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]);function c(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function u(t){this.gl=t,this.pixelRatio=1,this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.autoTicks=!0,this.tickSpacing=[1,1,1],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickAlign=[\"auto\",\"auto\",\"auto\"],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[10,10,10],this.lastCubeProps={cubeEdges:[0,0,0],axis:[0,0,0]},this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=\"sans-serif\",this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelAlign=[\"auto\",\"auto\",\"auto\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[10,10,10],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[0,0,0],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!1,!1,!1],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._firstInit=!0,this._text=null,this._lines=null,this._background=i(t)}var h=u.prototype;function f(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}h.update=function(t){function e(e,r,n){if(n in t){var a,i=t[n],o=this[n];(e?Array.isArray(i)&&Array.isArray(i[0]):Array.isArray(i))?this[n]=a=[r(i[0]),r(i[1]),r(i[2])]:this[n]=a=[r(i),r(i),r(i)];for(var s=0;s<3;++s)if(a[s]!==o[s])return!0}return!1}t=t||{};var r,i=e.bind(this,!1,Number),o=e.bind(this,!1,Boolean),l=e.bind(this,!1,String),c=e.bind(this,!0,function(t){if(Array.isArray(t)){if(3===t.length)return[+t[0],+t[1],+t[2],1];if(4===t.length)return[+t[0],+t[1],+t[2],+t[3]]}return[0,0,0,1]}),u=!1,h=!1;if(\"bounds\"in t)for(var f=t.bounds,p=0;p<2;++p)for(var d=0;d<3;++d)f[p][d]!==this.bounds[p][d]&&(h=!0),this.bounds[p][d]=f[p][d];if(\"ticks\"in t){r=t.ticks,u=!0,this.autoTicks=!1;for(p=0;p<3;++p)this.tickSpacing[p]=0}else i(\"tickSpacing\")&&(this.autoTicks=!0,h=!0);if(this._firstInit&&(\"ticks\"in t||\"tickSpacing\"in t||(this.autoTicks=!0),h=!0,u=!0,this._firstInit=!1),h&&this.autoTicks&&(r=s.create(this.bounds,this.tickSpacing),u=!0),u){for(p=0;p<3;++p)r[p].sort(function(t,e){return t.x-e.x});s.equal(r,this.ticks)?u=!1:this.ticks=r}o(\"tickEnable\"),l(\"tickFont\")&&(u=!0),i(\"tickSize\"),i(\"tickAngle\"),i(\"tickPad\"),c(\"tickColor\");var g=l(\"labels\");l(\"labelFont\")&&(g=!0),o(\"labelEnable\"),i(\"labelSize\"),i(\"labelPad\"),c(\"labelColor\"),o(\"lineEnable\"),o(\"lineMirror\"),i(\"lineWidth\"),c(\"lineColor\"),o(\"lineTickEnable\"),o(\"lineTickMirror\"),i(\"lineTickLength\"),i(\"lineTickWidth\"),c(\"lineTickColor\"),o(\"gridEnable\"),i(\"gridWidth\"),c(\"gridColor\"),o(\"zeroEnable\"),c(\"zeroLineColor\"),i(\"zeroLineWidth\"),o(\"backgroundEnable\"),c(\"backgroundColor\"),this._text?this._text&&(g||u)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=n(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&u&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=a(this.gl,this.bounds,this.ticks))};var p=[new f,new f,new f];function d(t,e,r,n,a){for(var i=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,c=n[e],u=0;u<3;++u)if(e!==u){var h=i,f=s,p=o,d=l;c&1<<u&&(h=s,f=i,p=l,d=o),h[u]=r[0][u],f[u]=r[1][u],a[u]>0?(p[u]=-1,d[u]=0):(p[u]=0,d[u]=1)}}var g=[0,0,0],v={model:l,view:l,projection:l,_ortho:!1};h.isOpaque=function(){return!0},h.isTransparent=function(){return!1},h.drawTransparent=function(t){};var m=[0,0,0],y=[0,0,0],x=[0,0,0];h.draw=function(t){t=t||v;for(var e=this.gl,r=t.model||l,n=t.view||l,a=t.projection||l,i=this.bounds,s=t._ortho||!1,u=o(r,n,a,i,s),h=u.cubeEdges,f=u.axis,b=n[12],_=n[13],w=n[14],k=n[15],T=(s?2:1)*this.pixelRatio*(a[3]*b+a[7]*_+a[11]*w+a[15]*k)/e.drawingBufferHeight,M=0;M<3;++M)this.lastCubeProps.cubeEdges[M]=h[M],this.lastCubeProps.axis[M]=f[M];var A=p;for(M=0;M<3;++M)d(p[M],M,this.bounds,h,f);e=this.gl;var S,E=g;for(M=0;M<3;++M)this.backgroundEnable[M]?E[M]=f[M]:E[M]=0;this._background.draw(r,n,a,i,E,this.backgroundColor),this._lines.bind(r,n,a,this);for(M=0;M<3;++M){var L=[0,0,0];f[M]>0?L[M]=i[1][M]:L[M]=i[0][M];for(var C=0;C<2;++C){var P=(M+1+C)%3,O=(M+1+(1^C))%3;this.gridEnable[P]&&this._lines.drawGrid(P,O,this.bounds,L,this.gridColor[P],this.gridWidth[P]*this.pixelRatio)}for(C=0;C<2;++C){P=(M+1+C)%3,O=(M+1+(1^C))%3;this.zeroEnable[O]&&Math.min(i[0][O],i[1][O])<=0&&Math.max(i[0][O],i[1][O])>=0&&this._lines.drawZero(P,O,this.bounds,L,this.zeroLineColor[O],this.zeroLineWidth[O]*this.pixelRatio)}}for(M=0;M<3;++M){this.lineEnable[M]&&this._lines.drawAxisLine(M,this.bounds,A[M].primalOffset,this.lineColor[M],this.lineWidth[M]*this.pixelRatio),this.lineMirror[M]&&this._lines.drawAxisLine(M,this.bounds,A[M].mirrorOffset,this.lineColor[M],this.lineWidth[M]*this.pixelRatio);var z=c(m,A[M].primalMinor),I=c(y,A[M].mirrorMinor),D=this.lineTickLength;for(C=0;C<3;++C){var R=T/r[5*C];z[C]*=D[C]*R,I[C]*=D[C]*R}this.lineTickEnable[M]&&this._lines.drawAxisTicks(M,A[M].primalOffset,z,this.lineTickColor[M],this.lineTickWidth[M]*this.pixelRatio),this.lineTickMirror[M]&&this._lines.drawAxisTicks(M,A[M].mirrorOffset,I,this.lineTickColor[M],this.lineTickWidth[M]*this.pixelRatio)}this._lines.unbind(),this._text.bind(r,n,a,this.pixelRatio);var F,B;function N(t){(B=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,a=(t+2)%3,i=e[n],o=e[a],s=r[n],l=r[a];i>0&&l>0?N(n):i>0&&l<0?N(n):i<0&&l>0?N(n):i<0&&l<0?N(n):o>0&&s>0?N(a):o>0&&s<0?N(a):o<0&&s>0?N(a):o<0&&s<0&&N(a)}for(M=0;M<3;++M){var V=A[M].primalMinor,U=A[M].mirrorMinor,q=c(x,A[M].primalOffset);for(C=0;C<3;++C)this.lineTickEnable[M]&&(q[C]+=T*V[C]*Math.max(this.lineTickLength[C],0)/r[5*C]);var H=[0,0,0];if(H[M]=1,this.tickEnable[M]){-3600===this.tickAngle[M]?(this.tickAngle[M]=0,this.tickAlign[M]=\"auto\"):this.tickAlign[M]=-1,F=1,\"auto\"===(S=[this.tickAlign[M],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),B=[0,0,0],j(M,V,U);for(C=0;C<3;++C)q[C]+=T*V[C]*this.tickPad[C]/r[5*C];this._text.drawTicks(M,this.tickSize[M],this.tickAngle[M],q,this.tickColor[M],H,B,S)}if(this.labelEnable[M]){F=0,B=[0,0,0],this.labels[M].length>4&&(N(M),F=1),\"auto\"===(S=[this.labelAlign[M],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]);for(C=0;C<3;++C)q[C]+=T*V[C]*this.labelPad[C]/r[5*C];q[M]+=.5*(i[0][M]+i[1][M]),this._text.drawLabel(M,this.labelSize[M],this.labelAngle[M],q,this.labelColor[M],[0,0,0],B,S)}}this._text.unbind()},h.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},{\"./lib/background.js\":237,\"./lib/cube.js\":238,\"./lib/lines.js\":239,\"./lib/text.js\":241,\"./lib/ticks.js\":242}],237:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var c=(l+1)%3,u=(l+2)%3,h=[0,0,0],f=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),h[l]=p,f[l]=p;for(var d=-1;d<=1;d+=2){h[c]=d;for(var g=-1;g<=1;g+=2)h[u]=g,e.push(h[0],h[1],h[2],f[0],f[1],f[2]),s+=1}var v=c;c=u,u=v}var m=n(t,new Float32Array(e)),y=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=a(t,[{buffer:m,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:m,type:t.FLOAT,size:3,offset:12,stride:24}],y),b=i(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,m,x,b)};var n=t(\"gl-buffer\"),a=t(\"gl-vao\"),i=t(\"./shaders\").bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,a,i){for(var o=!1,s=0;s<3;++s)o=o||a[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:a,colors:i},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders\":240,\"gl-buffer\":244,\"gl-vao\":329}],238:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,i,p){a(s,e,t),a(s,r,s);for(var y=0,x=0;x<2;++x){u[2]=i[x][2];for(var b=0;b<2;++b){u[1]=i[b][1];for(var _=0;_<2;++_)u[0]=i[_][0],f(l[y],u,s),y+=1}}for(var w=-1,x=0;x<8;++x){for(var k=l[x][3],T=0;T<3;++T)c[x][T]=l[x][T]/k;p&&(c[x][2]*=-1),k<0&&(w<0?w=x:c[x][2]<c[w][2]&&(w=x))}if(w<0){w=0;for(var M=0;M<3;++M){for(var A=(M+2)%3,S=(M+1)%3,E=-1,L=-1,C=0;C<2;++C){var P=C<<M,O=P+(C<<A)+(1-C<<S),z=P+(1-C<<A)+(C<<S);o(c[P],c[O],c[z],h)<0||(C?E=1:L=1)}if(E<0||L<0)L>E&&(w|=1<<M);else{for(var C=0;C<2;++C){var P=C<<M,O=P+(C<<A)+(1-C<<S),z=P+(1-C<<A)+(C<<S),I=d([l[P],l[O],l[z],l[P+(1<<A)+(1<<S)]]);C?E=I:L=I}L>E&&(w|=1<<M)}}}for(var D=7^w,R=-1,x=0;x<8;++x)x!==w&&x!==D&&(R<0?R=x:c[R][1]>c[x][1]&&(R=x));for(var F=-1,x=0;x<3;++x){var B=R^1<<x;if(B!==w&&B!==D){F<0&&(F=B);var S=c[B];S[0]<c[F][0]&&(F=B)}}for(var N=-1,x=0;x<3;++x){var B=R^1<<x;if(B!==w&&B!==D&&B!==F){N<0&&(N=B);var S=c[B];S[0]>c[N][0]&&(N=B)}}var j=g;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^N)]=R&N;var V=7^N;V===w||V===D?(V=7^F,j[n.log2(N^V)]=V&N):j[n.log2(F^V)]=V&F;for(var U=v,q=w,M=0;M<3;++M)U[M]=q&1<<M?-1:1;return m};var n=t(\"bit-twiddle\"),a=t(\"gl-mat4/multiply\"),i=t(\"split-polygon\"),o=t(\"robust-orientation\"),s=new Array(16),l=new Array(8),c=new Array(8),u=new Array(3),h=[0,0,0];function f(t,e,r){for(var n=0;n<4;++n){t[n]=r[12+n];for(var a=0;a<3;++a)t[n]+=e[a]*r[4*a+n]}}!function(){for(var t=0;t<8;++t)l[t]=[1,1,1,1],c[t]=[1,1,1]}();var p=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]];function d(t){for(var e=0;e<p.length;++e)if((t=i.positive(t,p[e])).length<3)return 0;var r=t[0],n=r[0]/r[3],a=r[1]/r[3],o=0;for(e=1;e+1<t.length;++e){var s=t[e],l=t[e+1],c=s[0]/s[3]-n,u=s[1]/s[3]-a,h=l[0]/l[3]-n,f=l[1]/l[3]-a;o+=Math.abs(c*f-u*h)}return o}var g=[1,1,1],v=[0,0,0],m={cubeEdges:g,axis:v}},{\"bit-twiddle\":94,\"gl-mat4/multiply\":270,\"robust-orientation\":509,\"split-polygon\":526}],239:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){var o=[],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[0,0,0];o.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var h=0;h<3;++h){for(var f=o.length/3|0,d=0;d<r[h].length;++d){var g=+r[h][d].x;o.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}var v=o.length/3|0;s[h]=f,l[h]=v-f;for(var f=o.length/3|0,m=0;m<r[h].length;++m){var g=+r[h][m].x;o.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}var v=o.length/3|0;c[h]=f,u[h]=v-f}var y=n(t,new Float32Array(o)),x=a(t,[{buffer:y,type:t.FLOAT,size:3,stride:0,offset:0}]),b=i(t);return b.attributes.position.location=0,new p(t,y,x,b,l,s,u,c)};var n=t(\"gl-buffer\"),a=t(\"gl-vao\"),i=t(\"./shaders\").line,o=[0,0,0],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[1,1];function h(t){return t[0]=t[1]=t[2]=0,t}function f(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function p(t,e,r,n,a,i,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=a,this.tickOffset=i,this.gridCount=o,this.gridOffset=s}var d=p.prototype;d.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,u[0]=this.gl.drawingBufferWidth,u[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=u,this.vao.bind()},d.unbind=function(){this.vao.unbind()},d.drawAxisLine=function(t,e,r,n,a){var i=h(s);this.shader.uniforms.majorAxis=s,i[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=i;var o,u=f(c,r);u[t]+=e[0][t],this.shader.uniforms.offset=u,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=n,(o=h(l))[(t+2)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6),(o=h(l))[(t+1)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6)},d.drawAxisTicks=function(t,e,r,n,a){if(this.tickCount[t]){var i=h(o);i[t]=1,this.shader.uniforms.majorAxis=i,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=n,this.shader.uniforms.lineWidth=a;var s=h(l);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},d.drawGrid=function(t,e,r,n,a,i){if(this.gridCount[t]){var u=h(s);u[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=u;var p=f(c,n);p[e]+=r[0][e],this.shader.uniforms.offset=p;var d=h(o);d[t]=1,this.shader.uniforms.majorAxis=d;var g=h(l);g[t]=1,this.shader.uniforms.screenAxis=g,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=a,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},d.drawZero=function(t,e,r,n,a,i){var o=h(s);this.shader.uniforms.majorAxis=o,o[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=o;var u=f(c,n);u[t]+=r[0][t],this.shader.uniforms.offset=u;var p=h(l);p[e]=1,this.shader.uniforms.screenAxis=p,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=a,this.vao.draw(this.gl.TRIANGLES,6)},d.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},{\"./shaders\":240,\"gl-buffer\":244,\"gl-vao\":329}],240:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),a=t(\"gl-shader\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n  vec3 major = position.x * majorAxis;\\n  vec3 minor = position.y * minorAxis;\\n\\n  vec3 vPosition = major + minor + offset;\\n  vec3 pPosition = project(vPosition);\\n  vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n  vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\\n\\n  gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);r.line=function(t){return a(t,i,o,null,[{name:\"position\",type:\"vec3\"}])};var s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis, alignDir, alignOpt;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nfloat computeViewAngle(vec3 a, vec3 b) {\\n  vec3 A = project(a);\\n  vec3 B = project(b);\\n\\n  return atan(\\n    (B.y - A.y) * resolution.y,\\n    (B.x - A.x) * resolution.x\\n  );\\n}\\n\\nconst float PI = 3.141592;\\nconst float TWO_PI = 2.0 * PI;\\nconst float HALF_PI = 0.5 * PI;\\nconst float ONE_AND_HALF_PI = 1.5 * PI;\\n\\nint option = int(floor(alignOpt.x + 0.001));\\nfloat hv_ratio =       alignOpt.y;\\nbool enableAlign =    (alignOpt.z != 0.0);\\n\\nfloat mod_angle(float a) {\\n  return mod(a, PI);\\n}\\n\\nfloat positive_angle(float a) {\\n  return mod_angle((a < 0.0) ?\\n    a + TWO_PI :\\n    a\\n  );\\n}\\n\\nfloat look_upwards(float a) {\\n  float b = positive_angle(a);\\n  return ((b > HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\\n    b - PI :\\n    b;\\n}\\n\\nfloat look_horizontal_or_vertical(float a, float ratio) {\\n  // ratio controls the ratio between being horizontal to (vertical + horizontal)\\n  // if ratio is set to 0.5 then it is 50%, 50%.\\n  // when using a higher ratio e.g. 0.75 the result would\\n  // likely be more horizontal than vertical.\\n\\n  float b = positive_angle(a);\\n\\n  return\\n    (b < (      ratio) * HALF_PI) ? 0.0 :\\n    (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\\n    (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\\n    (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\\n                                    0.0;\\n}\\n\\nfloat roundTo(float a, float b) {\\n  return float(b * floor((a + 0.5 * b) / b));\\n}\\n\\nfloat look_round_n_directions(float a, int n) {\\n  float b = positive_angle(a);\\n  float div = TWO_PI / float(n);\\n  float c = roundTo(b, div);\\n  return look_upwards(c);\\n}\\n\\nfloat applyAlignOption(float rawAngle, float delta) {\\n  return\\n    (option >  2) ? look_round_n_directions(rawAngle + delta, option) :       // option 3-n: round to n directions\\n    (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\\n    (option == 1) ? rawAngle + delta :       // use free angle, and flip to align with one direction of the axis\\n    (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\\n    (option ==-1) ? 0.0 :                    // useful for backward compatibility, all texts remains horizontal\\n                    rawAngle;                // otherwise return back raw input angle\\n}\\n\\nbool isAxisTitle = (axis.x == 0.0) &&\\n                   (axis.y == 0.0) &&\\n                   (axis.z == 0.0);\\n\\nvoid main() {\\n  //Compute world offset\\n  float axisDistance = position.z;\\n  vec3 dataPosition = axisDistance * axis + offset;\\n\\n  float beta = angle; // i.e. user defined attributes for each tick\\n\\n  float axisAngle;\\n  float clipAngle;\\n  float flip;\\n\\n  if (enableAlign) {\\n    axisAngle = (isAxisTitle) ? HALF_PI :\\n                      computeViewAngle(dataPosition, dataPosition + axis);\\n    clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\\n\\n    axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\\n    clipAngle += (sin(clipAngle) < 0.0) ? PI : 0.0;\\n\\n    flip = (dot(vec2(cos(axisAngle), sin(axisAngle)),\\n                vec2(sin(clipAngle),-cos(clipAngle))) > 0.0) ? 1.0 : 0.0;\\n\\n    beta += applyAlignOption(clipAngle, flip * PI);\\n  }\\n\\n  //Compute plane offset\\n  vec2 planeCoord = position.xy * pixelScale;\\n\\n  mat2 planeXform = scale * mat2(\\n     cos(beta), sin(beta),\\n    -sin(beta), cos(beta)\\n  );\\n\\n  vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n  //Compute clip position\\n  vec3 clipPosition = project(dataPosition);\\n\\n  //Apply text offset in clip coordinates\\n  clipPosition += vec3(viewOffset, 0.0);\\n\\n  //Done\\n  gl_Position = vec4(clipPosition, 1.0);\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);r.text=function(t){return a(t,s,l,null,[{name:\"position\",type:\"vec3\"}])};var c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n\\n  vec3 signAxis = sign(bounds[1] - bounds[0]);\\n\\n  vec3 realNormal = signAxis * normal;\\n\\n  if(dot(realNormal, enable) > 0.0) {\\n    vec3 minRange = min(bounds[0], bounds[1]);\\n    vec3 maxRange = max(bounds[0], bounds[1]);\\n    vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\\n    gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n  } else {\\n    gl_Position = vec4(0,0,0,0);\\n  }\\n\\n  colorChannel = abs(realNormal);\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 colors[3];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n  gl_FragColor = colorChannel.x * colors[0] +\\n                 colorChannel.y * colors[1] +\\n                 colorChannel.z * colors[2];\\n}\"]);r.bg=function(t){return a(t,c,u,null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},{\"gl-shader\":304,glslify:411}],241:[function(t,e,r){(function(r){\"use strict\";e.exports=function(t,e,r,i,s,l){var u=n(t),h=a(t,[{buffer:u,size:3}]),f=o(t);f.attributes.position.location=0;var p=new c(t,f,u,h);return p.update(e,r,i,s,l),p};var n=t(\"gl-buffer\"),a=t(\"gl-vao\"),i=t(\"vectorize-text\"),o=t(\"./shaders\").text,s=window||r.global||{},l=s.__TEXT_CACHE||{};s.__TEXT_CACHE={};function c(t,e,r,n){this.gl=t,this.shader=e,this.buffer=r,this.vao=n,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}var u=c.prototype,h=[0,0];u.bind=function(t,e,r,n){this.vao.bind(),this.shader.bind();var a=this.shader.uniforms;a.model=t,a.view=e,a.projection=r,a.pixelScale=n,h[0]=this.gl.drawingBufferWidth,h[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=h},u.unbind=function(){this.vao.unbind()},u.update=function(t,e,r,n,a){var o=[];function s(t,e,r,n,a,s){var c=l[r];c||(c=l[r]={});var u=c[e];u||(u=c[e]=function(t,e){try{return i(t,e)}catch(e){return console.warn('error vectorizing text:\"'+t+'\" error:',e),{cells:[],positions:[]}}}(e,{triangles:!0,font:r,textAlign:\"center\",textBaseline:\"middle\",lineSpacing:a,styletags:s}));for(var h=(n||12)/12,f=u.positions,p=u.cells,d=0,g=p.length;d<g;++d)for(var v=p[d],m=2;m>=0;--m){var y=f[v[m]];o.push(h*y[0],-h*y[1],t)}}for(var c=[0,0,0],u=[0,0,0],h=[0,0,0],f=[0,0,0],p={breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},d=0;d<3;++d){h[d]=o.length/3|0,s(.5*(t[0][d]+t[1][d]),e[d],r[d],12,1.25,p),f[d]=(o.length/3|0)-h[d],c[d]=o.length/3|0;for(var g=0;g<n[d].length;++g)n[d][g].text&&s(n[d][g].x,n[d][g].text,n[d][g].font||a,n[d][g].fontSize||12,1.25,p);u[d]=(o.length/3|0)-c[d]}this.buffer.update(o),this.tickOffset=c,this.tickCount=u,this.labelOffset=h,this.labelCount=f},u.drawTicks=function(t,e,r,n,a,i,o,s){this.tickCount[t]&&(this.shader.uniforms.axis=i,this.shader.uniforms.color=a,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t]))},u.drawLabel=function(t,e,r,n,a,i,o,s){this.labelCount[t]&&(this.shader.uniforms.axis=i,this.shader.uniforms.color=a,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.labelCount[t],this.labelOffset[t]))},u.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()}}).call(this,t(\"_process\"))},{\"./shaders\":240,_process:484,\"gl-buffer\":244,\"gl-vao\":329,\"vectorize-text\":549}],242:[function(t,e,r){\"use strict\";function n(t,e){var r=t+\"\",n=r.indexOf(\".\"),a=0;n>=0&&(a=r.length-n-1);var i=Math.pow(10,a),o=Math.round(t*e*i),s=o+\"\";if(s.indexOf(\"e\")>=0)return s;var l=o/i,c=o%i;o<0?(l=0|-Math.ceil(l),c=0|-c):(l=0|Math.floor(l),c|=0);var u=\"\"+l;if(o<0&&(u=\"-\"+u),a){for(var h=\"\"+c;h.length<a;)h=\"0\"+h;return u+\".\"+h}return u}r.create=function(t,e){for(var r=[],a=0;a<3;++a){for(var i=[],o=(t[0][a],t[1][a],0);o*e[a]<=t[1][a];++o)i.push({x:o*e[a],text:n(e[a],o)});for(var o=-1;o*e[a]>=t[0][a];--o)i.push({x:o*e[a],text:n(e[a],o)});r.push(i)}return r},r.equal=function(t,e){for(var r=0;r<3;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;n<t[r].length;++n){var a=t[r][n],i=e[r][n];if(a.x!==i.x||a.text!==i.text||a.font!==i.font||a.fontColor!==i.fontColor||a.fontSize!==i.fontSize||a.dx!==i.dx||a.dy!==i.dy)return!1}}return!0}},{}],243:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,l,h){var f=e.model||c,p=e.view||c,m=e.projection||c,y=e._ortho||!1,x=t.bounds,b=(h=h||i(f,p,m,x,y)).axis;o(u,p,f),o(u,m,u);for(var _=g,w=0;w<3;++w)_[w].lo=1/0,_[w].hi=-1/0,_[w].pixelsPerDataUnit=1/0;var k=n(s(u,u));s(u,u);for(var T=0;T<3;++T){var M=(T+1)%3,A=(T+2)%3,S=v;t:for(var w=0;w<2;++w){var E=[];if(b[T]<0!=!!w){S[T]=x[w][T];for(var L=0;L<2;++L){S[M]=x[L^w][M];for(var C=0;C<2;++C)S[A]=x[C^L^w][A],E.push(S.slice())}for(var P=y?5:4,L=P;L===P;++L){if(0===E.length)continue t;E=a.positive(E,k[L])}for(var L=0;L<E.length;++L)for(var A=E[L],O=d(v,u,A,r,l),C=0;C<3;++C)_[C].lo=Math.min(_[C].lo,A[C]),_[C].hi=Math.max(_[C].hi,A[C]),C!==T&&(_[C].pixelsPerDataUnit=Math.min(_[C].pixelsPerDataUnit,Math.abs(O[C])))}}}return _};var n=t(\"extract-frustum-planes\"),a=t(\"split-polygon\"),i=t(\"./lib/cube.js\"),o=t(\"gl-mat4/multiply\"),s=t(\"gl-mat4/transpose\"),l=t(\"gl-vec4/transformMat4\"),c=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),u=new Float32Array(16);function h(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}var f=[0,0,0,1],p=[0,0,0,1];function d(t,e,r,n,a){for(var i=0;i<3;++i){for(var o=f,s=p,c=0;c<3;++c)s[c]=o[c]=r[c];s[3]=o[3]=1,s[i]+=1,l(s,s,e),s[3]<0&&(t[i]=1/0),o[i]-=1,l(o,o,e),o[3]<0&&(t[i]=1/0);var u=(o[0]/o[3]-s[0]/s[3])*n,h=(o[1]/o[3]-s[1]/s[3])*a;t[i]=.25*Math.sqrt(u*u+h*h)}return t}var g=[new h(1/0,-1/0,1/0),new h(1/0,-1/0,1/0),new h(1/0,-1/0,1/0)],v=[0,0,0]},{\"./lib/cube.js\":238,\"extract-frustum-planes\":227,\"gl-mat4/multiply\":270,\"gl-mat4/transpose\":279,\"gl-vec4/transformMat4\":400,\"split-polygon\":526}],244:[function(t,e,r){\"use strict\";var n=t(\"typedarray-pool\"),a=t(\"ndarray-ops\"),i=t(\"ndarray\"),o=[\"uint8\",\"uint8_clamped\",\"uint16\",\"uint32\",\"int8\",\"int16\",\"int32\",\"float32\"];function s(t,e,r,n,a){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=a}var l=s.prototype;function c(t,e,r,n,a,i){var o=a.length*a.BYTES_PER_ELEMENT;if(i<0)return t.bufferData(e,a,n),o;if(o+i>r)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,i,a),r}function u(t,e){for(var r=n.malloc(t.length,e),a=t.length,i=0;i<a;++i)r[i]=t[i];return r}l.bind=function(){this.gl.bindBuffer(this.type,this.handle)},l.unbind=function(){this.gl.bindBuffer(this.type,null)},l.dispose=function(){this.gl.deleteBuffer(this.handle)},l.update=function(t,e){if(\"number\"!=typeof e&&(e=-1),this.bind(),\"object\"==typeof t&&\"undefined\"!=typeof t.shape){var r=t.dtype;if(o.indexOf(r)<0&&(r=\"float32\"),this.type===this.gl.ELEMENT_ARRAY_BUFFER)r=gl.getExtension(\"OES_element_index_uint\")&&\"uint16\"!==r?\"uint32\":\"uint16\";if(r===t.dtype&&function(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=c(this.gl,this.type,this.length,this.usage,t.data,e):this.length=c(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=i(s,t.shape);a.assign(l,t),this.length=c(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var h;h=this.type===this.gl.ELEMENT_ARRAY_BUFFER?u(t,\"uint16\"):u(t,\"float32\"),this.length=c(this.gl,this.type,this.length,this.usage,e<0?h:h.subarray(0,t.length),e),n.free(h)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=c(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof t&&void 0!==t)throw new Error(\"gl-buffer: Invalid data type\");if(e>=0)throw new Error(\"gl-buffer: Cannot specify offset when resizing buffer\");(t|=0)<=0&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},e.exports=function(t,e,r,n){if(r=r||t.ARRAY_BUFFER,n=n||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error(\"gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER\");if(n!==t.DYNAMIC_DRAW&&n!==t.STATIC_DRAW&&n!==t.STREAM_DRAW)throw new Error(\"gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW\");var a=t.createBuffer(),i=new s(t,r,a,0,n);return i.update(e),i}},{ndarray:452,\"ndarray-ops\":446,\"typedarray-pool\":544}],245:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\");e.exports=function(t,e){var r=t.positions,a=t.vectors,i={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),i;for(var o=0,s=1/0,l=-1/0,c=1/0,u=-1/0,h=1/0,f=-1/0,p=null,d=null,g=[],v=1/0,m=!1,y=0;y<r.length;y++){var x=r[y];s=Math.min(x[0],s),l=Math.max(x[0],l),c=Math.min(x[1],c),u=Math.max(x[1],u),h=Math.min(x[2],h),f=Math.max(x[2],f);var b=a[y];if(n.length(b)>o&&(o=n.length(b)),y){var _=2*n.distance(p,x)/(n.length(d)+n.length(b));_?(v=Math.min(v,_),m=!1):m=!0}m||(p=x,d=b),g.push(b)}var w=[s,c,h],k=[l,u,f];e&&(e[0]=w,e[1]=k),0===o&&(o=1);var T=1/o;isFinite(v)||(v=1),i.vectorScale=v;var M=t.coneSize||.5;t.absoluteConeSize&&(M=t.absoluteConeSize*T),i.coneScale=M;y=0;for(var A=0;y<r.length;y++)for(var S=(x=r[y])[0],E=x[1],L=x[2],C=g[y],P=n.length(C)*T,O=0;O<8;O++){i.positions.push([S,E,L,A++]),i.positions.push([S,E,L,A++]),i.positions.push([S,E,L,A++]),i.positions.push([S,E,L,A++]),i.positions.push([S,E,L,A++]),i.positions.push([S,E,L,A++]),i.vectors.push(C),i.vectors.push(C),i.vectors.push(C),i.vectors.push(C),i.vectors.push(C),i.vectors.push(C),i.vertexIntensity.push(P,P,P),i.vertexIntensity.push(P,P,P);var z=i.positions.length;i.cells.push([z-6,z-5,z-4],[z-3,z-2,z-1])}return i};var a=t(\"./lib/shaders\");e.exports.createMesh=t(\"./create_mesh\"),e.exports.createConeMesh=function(t,r){return e.exports.createMesh(t,r,{shaders:a,traceType:\"cone\"})}},{\"./create_mesh\":246,\"./lib/shaders\":247,\"gl-vec3\":348}],246:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),a=t(\"gl-buffer\"),i=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"gl-mat4/multiply\"),l=t(\"gl-mat4/invert\"),c=t(\"ndarray\"),u=t(\"colormap\"),h=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function f(t,e,r,n,a,i,o,s,l,c,u){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.pickShader=n,this.trianglePositions=a,this.triangleVectors=i,this.triangleColors=s,this.triangleUVs=l,this.triangleIds=o,this.triangleVAO=c,this.triangleCount=0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.traceType=u,this.tubeScale=1,this.coneScale=2,this.vectorScale=1,this.coneOffset=.25,this._model=h,this._view=h,this._projection=h,this._resolution=[1,1]}var p=f.prototype;p.isOpaque=function(){return this.opacity>=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(t){this.pickId=t},p.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=u({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var a=e[n],i=0;i<3;++i)r[4*n+i]=a[i];r[4*n+3]=255*a[3]}return c(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,a=t.vectors;if(n&&r&&a){var i=[],o=[],s=[],l=[],h=[];this.cells=r,this.positions=n,this.vectors=a;var f=t.meshColor||[1,1,1,1],p=t.vertexIntensity,d=1/0,g=-1/0;if(p)if(t.vertexIntensityBounds)d=+t.vertexIntensityBounds[0],g=+t.vertexIntensityBounds[1];else for(var v=0;v<p.length;++v){var m=p[v];d=Math.min(d,m),g=Math.max(g,m)}else for(v=0;v<n.length;++v){m=n[v][2];d=Math.min(d,m),g=Math.max(g,m)}this.intensity=p||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(v=0;v<n.length;++v)for(var y=n[v],x=0;x<3;++x)!isNaN(y[x])&&isFinite(y[x])&&(this.bounds[0][x]=Math.min(this.bounds[0][x],y[x]),this.bounds[1][x]=Math.max(this.bounds[1][x],y[x]));var b=0;t:for(v=0;v<r.length;++v){var _=r[v];switch(_.length){case 3:for(x=0;x<3;++x){y=n[k=_[x]];for(var w=0;w<3;++w)if(isNaN(y[w])||!isFinite(y[w]))continue t}for(x=0;x<3;++x){var k;y=n[k=_[2-x]];i.push(y[0],y[1],y[2],y[3]);var T=a[k];o.push(T[0],T[1],T[2],T[3]||0);var M,A=f;3===A.length?s.push(A[0],A[1],A[2],1):s.push(A[0],A[1],A[2],A[3]),M=p?[(p[k]-d)/(g-d),0]:[(y[2]-d)/(g-d),0],l.push(M[0],M[1]),h.push(v)}b+=1}}this.triangleCount=b,this.trianglePositions.update(i),this.triangleVectors.update(o),this.triangleColors.update(s),this.triangleUVs.update(l),this.triangleIds.update(new Uint32Array(h))}},p.drawTransparent=p.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||h,n=t.view||h,a=t.projection||h,i=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)i[0][o]=Math.max(i[0][o],this.clipBounds[0][o]),i[1][o]=Math.min(i[1][o],this.clipBounds[1][o]);var c={model:r,view:n,projection:a,inverseModel:h.slice(),clipBounds:i,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,texture:0};c.inverseModel=l(c.inverseModel,c.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);s(u,c.view,c.model),s(u,c.projection,u),l(u,u);for(o=0;o<3;++o)c.eyePosition[o]=u[12+o]/u[15];var f=u[15];for(o=0;o<3;++o)f+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];c.lightPosition[o]=p/f}if(this.triangleCount>0){var g=this.triShader;g.bind(),g.uniforms=c,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},p.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||h,n=t.view||h,a=t.projection||h,i=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)i[0][o]=Math.max(i[0][o],this.clipBounds[0][o]),i[1][o]=Math.min(i[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(a),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:a,clipBounds:i,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind())},p.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3),a={position:n,dataCoordinate:n,index:Math.floor(r[1]/48)};return\"cone\"===this.traceType?a.index=Math.floor(r[1]/48):\"streamtube\"===this.traceType&&(a.intensity=this.intensity[r[1]],a.velocity=this.vectors[r[1]].slice(0,3),a.divergence=this.vectors[r[1]][3],a.index=e),a},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()},e.exports=function(t,e,r){var s=r.shaders;1===arguments.length&&(t=(e=t).gl);var l=function(t,e){var r=n(t,e.meshShader.vertex,e.meshShader.fragment,null,e.meshShader.attributes);return r.attributes.position.location=0,r.attributes.color.location=2,r.attributes.uv.location=3,r.attributes.vector.location=4,r}(t,s),u=function(t,e){var r=n(t,e.pickShader.vertex,e.pickShader.fragment,null,e.pickShader.attributes);return r.attributes.position.location=0,r.attributes.id.location=1,r.attributes.vector.location=4,r}(t,s),h=o(t,c(new Uint8Array([255,255,255,255]),[1,1,4]));h.generateMipmap(),h.minFilter=t.LINEAR_MIPMAP_LINEAR,h.magFilter=t.LINEAR;var p=a(t),d=a(t),g=a(t),v=a(t),m=a(t),y=new f(t,h,l,u,p,d,m,g,v,i(t,[{buffer:p,type:t.FLOAT,size:4},{buffer:m,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:g,type:t.FLOAT,size:4},{buffer:v,type:t.FLOAT,size:2},{buffer:d,type:t.FLOAT,size:4}]),r.traceType||\"cone\");return y.update(e),y}},{colormap:128,\"gl-buffer\":244,\"gl-mat4/invert\":268,\"gl-mat4/multiply\":270,\"gl-shader\":304,\"gl-texture2d\":324,\"gl-vao\":329,ndarray:452}],247:[function(t,e,r){var n=t(\"glslify\"),a=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, coneScale, coneOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * conePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(conePosition, 1.0);\\n  vec4 t_position  = view * conePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = conePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),i=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float vectorScale, coneScale, coneOffset;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n  gl_Position = projection * view * conePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);r.meshShader={vertex:a,fragment:i,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec3\"}]},r.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec3\"}]}},{glslify:411}],248:[function(t,e,r){e.exports={0:\"NONE\",1:\"ONE\",2:\"LINE_LOOP\",3:\"LINE_STRIP\",4:\"TRIANGLES\",5:\"TRIANGLE_STRIP\",6:\"TRIANGLE_FAN\",256:\"DEPTH_BUFFER_BIT\",512:\"NEVER\",513:\"LESS\",514:\"EQUAL\",515:\"LEQUAL\",516:\"GREATER\",517:\"NOTEQUAL\",518:\"GEQUAL\",519:\"ALWAYS\",768:\"SRC_COLOR\",769:\"ONE_MINUS_SRC_COLOR\",770:\"SRC_ALPHA\",771:\"ONE_MINUS_SRC_ALPHA\",772:\"DST_ALPHA\",773:\"ONE_MINUS_DST_ALPHA\",774:\"DST_COLOR\",775:\"ONE_MINUS_DST_COLOR\",776:\"SRC_ALPHA_SATURATE\",1024:\"STENCIL_BUFFER_BIT\",1028:\"FRONT\",1029:\"BACK\",1032:\"FRONT_AND_BACK\",1280:\"INVALID_ENUM\",1281:\"INVALID_VALUE\",1282:\"INVALID_OPERATION\",1285:\"OUT_OF_MEMORY\",1286:\"INVALID_FRAMEBUFFER_OPERATION\",2304:\"CW\",2305:\"CCW\",2849:\"LINE_WIDTH\",2884:\"CULL_FACE\",2885:\"CULL_FACE_MODE\",2886:\"FRONT_FACE\",2928:\"DEPTH_RANGE\",2929:\"DEPTH_TEST\",2930:\"DEPTH_WRITEMASK\",2931:\"DEPTH_CLEAR_VALUE\",2932:\"DEPTH_FUNC\",2960:\"STENCIL_TEST\",2961:\"STENCIL_CLEAR_VALUE\",2962:\"STENCIL_FUNC\",2963:\"STENCIL_VALUE_MASK\",2964:\"STENCIL_FAIL\",2965:\"STENCIL_PASS_DEPTH_FAIL\",2966:\"STENCIL_PASS_DEPTH_PASS\",2967:\"STENCIL_REF\",2968:\"STENCIL_WRITEMASK\",2978:\"VIEWPORT\",3024:\"DITHER\",3042:\"BLEND\",3088:\"SCISSOR_BOX\",3089:\"SCISSOR_TEST\",3106:\"COLOR_CLEAR_VALUE\",3107:\"COLOR_WRITEMASK\",3317:\"UNPACK_ALIGNMENT\",3333:\"PACK_ALIGNMENT\",3379:\"MAX_TEXTURE_SIZE\",3386:\"MAX_VIEWPORT_DIMS\",3408:\"SUBPIXEL_BITS\",3410:\"RED_BITS\",3411:\"GREEN_BITS\",3412:\"BLUE_BITS\",3413:\"ALPHA_BITS\",3414:\"DEPTH_BITS\",3415:\"STENCIL_BITS\",3553:\"TEXTURE_2D\",4352:\"DONT_CARE\",4353:\"FASTEST\",4354:\"NICEST\",5120:\"BYTE\",5121:\"UNSIGNED_BYTE\",5122:\"SHORT\",5123:\"UNSIGNED_SHORT\",5124:\"INT\",5125:\"UNSIGNED_INT\",5126:\"FLOAT\",5386:\"INVERT\",5890:\"TEXTURE\",6401:\"STENCIL_INDEX\",6402:\"DEPTH_COMPONENT\",6406:\"ALPHA\",6407:\"RGB\",6408:\"RGBA\",6409:\"LUMINANCE\",6410:\"LUMINANCE_ALPHA\",7680:\"KEEP\",7681:\"REPLACE\",7682:\"INCR\",7683:\"DECR\",7936:\"VENDOR\",7937:\"RENDERER\",7938:\"VERSION\",9728:\"NEAREST\",9729:\"LINEAR\",9984:\"NEAREST_MIPMAP_NEAREST\",9985:\"LINEAR_MIPMAP_NEAREST\",9986:\"NEAREST_MIPMAP_LINEAR\",9987:\"LINEAR_MIPMAP_LINEAR\",10240:\"TEXTURE_MAG_FILTER\",10241:\"TEXTURE_MIN_FILTER\",10242:\"TEXTURE_WRAP_S\",10243:\"TEXTURE_WRAP_T\",10497:\"REPEAT\",10752:\"POLYGON_OFFSET_UNITS\",16384:\"COLOR_BUFFER_BIT\",32769:\"CONSTANT_COLOR\",32770:\"ONE_MINUS_CONSTANT_COLOR\",32771:\"CONSTANT_ALPHA\",32772:\"ONE_MINUS_CONSTANT_ALPHA\",32773:\"BLEND_COLOR\",32774:\"FUNC_ADD\",32777:\"BLEND_EQUATION_RGB\",32778:\"FUNC_SUBTRACT\",32779:\"FUNC_REVERSE_SUBTRACT\",32819:\"UNSIGNED_SHORT_4_4_4_4\",32820:\"UNSIGNED_SHORT_5_5_5_1\",32823:\"POLYGON_OFFSET_FILL\",32824:\"POLYGON_OFFSET_FACTOR\",32854:\"RGBA4\",32855:\"RGB5_A1\",32873:\"TEXTURE_BINDING_2D\",32926:\"SAMPLE_ALPHA_TO_COVERAGE\",32928:\"SAMPLE_COVERAGE\",32936:\"SAMPLE_BUFFERS\",32937:\"SAMPLES\",32938:\"SAMPLE_COVERAGE_VALUE\",32939:\"SAMPLE_COVERAGE_INVERT\",32968:\"BLEND_DST_RGB\",32969:\"BLEND_SRC_RGB\",32970:\"BLEND_DST_ALPHA\",32971:\"BLEND_SRC_ALPHA\",33071:\"CLAMP_TO_EDGE\",33170:\"GENERATE_MIPMAP_HINT\",33189:\"DEPTH_COMPONENT16\",33306:\"DEPTH_STENCIL_ATTACHMENT\",33635:\"UNSIGNED_SHORT_5_6_5\",33648:\"MIRRORED_REPEAT\",33901:\"ALIASED_POINT_SIZE_RANGE\",33902:\"ALIASED_LINE_WIDTH_RANGE\",33984:\"TEXTURE0\",33985:\"TEXTURE1\",33986:\"TEXTURE2\",33987:\"TEXTURE3\",33988:\"TEXTURE4\",33989:\"TEXTURE5\",33990:\"TEXTURE6\",33991:\"TEXTURE7\",33992:\"TEXTURE8\",33993:\"TEXTURE9\",33994:\"TEXTURE10\",33995:\"TEXTURE11\",33996:\"TEXTURE12\",33997:\"TEXTURE13\",33998:\"TEXTURE14\",33999:\"TEXTURE15\",34000:\"TEXTURE16\",34001:\"TEXTURE17\",34002:\"TEXTURE18\",34003:\"TEXTURE19\",34004:\"TEXTURE20\",34005:\"TEXTURE21\",34006:\"TEXTURE22\",34007:\"TEXTURE23\",34008:\"TEXTURE24\",34009:\"TEXTURE25\",34010:\"TEXTURE26\",34011:\"TEXTURE27\",34012:\"TEXTURE28\",34013:\"TEXTURE29\",34014:\"TEXTURE30\",34015:\"TEXTURE31\",34016:\"ACTIVE_TEXTURE\",34024:\"MAX_RENDERBUFFER_SIZE\",34041:\"DEPTH_STENCIL\",34055:\"INCR_WRAP\",34056:\"DECR_WRAP\",34067:\"TEXTURE_CUBE_MAP\",34068:\"TEXTURE_BINDING_CUBE_MAP\",34069:\"TEXTURE_CUBE_MAP_POSITIVE_X\",34070:\"TEXTURE_CUBE_MAP_NEGATIVE_X\",34071:\"TEXTURE_CUBE_MAP_POSITIVE_Y\",34072:\"TEXTURE_CUBE_MAP_NEGATIVE_Y\",34073:\"TEXTURE_CUBE_MAP_POSITIVE_Z\",34074:\"TEXTURE_CUBE_MAP_NEGATIVE_Z\",34076:\"MAX_CUBE_MAP_TEXTURE_SIZE\",34338:\"VERTEX_ATTRIB_ARRAY_ENABLED\",34339:\"VERTEX_ATTRIB_ARRAY_SIZE\",34340:\"VERTEX_ATTRIB_ARRAY_STRIDE\",34341:\"VERTEX_ATTRIB_ARRAY_TYPE\",34342:\"CURRENT_VERTEX_ATTRIB\",34373:\"VERTEX_ATTRIB_ARRAY_POINTER\",34466:\"NUM_COMPRESSED_TEXTURE_FORMATS\",34467:\"COMPRESSED_TEXTURE_FORMATS\",34660:\"BUFFER_SIZE\",34661:\"BUFFER_USAGE\",34816:\"STENCIL_BACK_FUNC\",34817:\"STENCIL_BACK_FAIL\",34818:\"STENCIL_BACK_PASS_DEPTH_FAIL\",34819:\"STENCIL_BACK_PASS_DEPTH_PASS\",34877:\"BLEND_EQUATION_ALPHA\",34921:\"MAX_VERTEX_ATTRIBS\",34922:\"VERTEX_ATTRIB_ARRAY_NORMALIZED\",34930:\"MAX_TEXTURE_IMAGE_UNITS\",34962:\"ARRAY_BUFFER\",34963:\"ELEMENT_ARRAY_BUFFER\",34964:\"ARRAY_BUFFER_BINDING\",34965:\"ELEMENT_ARRAY_BUFFER_BINDING\",34975:\"VERTEX_ATTRIB_ARRAY_BUFFER_BINDING\",35040:\"STREAM_DRAW\",35044:\"STATIC_DRAW\",35048:\"DYNAMIC_DRAW\",35632:\"FRAGMENT_SHADER\",35633:\"VERTEX_SHADER\",35660:\"MAX_VERTEX_TEXTURE_IMAGE_UNITS\",35661:\"MAX_COMBINED_TEXTURE_IMAGE_UNITS\",35663:\"SHADER_TYPE\",35664:\"FLOAT_VEC2\",35665:\"FLOAT_VEC3\",35666:\"FLOAT_VEC4\",35667:\"INT_VEC2\",35668:\"INT_VEC3\",35669:\"INT_VEC4\",35670:\"BOOL\",35671:\"BOOL_VEC2\",35672:\"BOOL_VEC3\",35673:\"BOOL_VEC4\",35674:\"FLOAT_MAT2\",35675:\"FLOAT_MAT3\",35676:\"FLOAT_MAT4\",35678:\"SAMPLER_2D\",35680:\"SAMPLER_CUBE\",35712:\"DELETE_STATUS\",35713:\"COMPILE_STATUS\",35714:\"LINK_STATUS\",35715:\"VALIDATE_STATUS\",35716:\"INFO_LOG_LENGTH\",35717:\"ATTACHED_SHADERS\",35718:\"ACTIVE_UNIFORMS\",35719:\"ACTIVE_UNIFORM_MAX_LENGTH\",35720:\"SHADER_SOURCE_LENGTH\",35721:\"ACTIVE_ATTRIBUTES\",35722:\"ACTIVE_ATTRIBUTE_MAX_LENGTH\",35724:\"SHADING_LANGUAGE_VERSION\",35725:\"CURRENT_PROGRAM\",36003:\"STENCIL_BACK_REF\",36004:\"STENCIL_BACK_VALUE_MASK\",36005:\"STENCIL_BACK_WRITEMASK\",36006:\"FRAMEBUFFER_BINDING\",36007:\"RENDERBUFFER_BINDING\",36048:\"FRAMEBUFFER_ATTACHMENT_OBJECT_TYPE\",36049:\"FRAMEBUFFER_ATTACHMENT_OBJECT_NAME\",36050:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_LEVEL\",36051:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_CUBE_MAP_FACE\",36053:\"FRAMEBUFFER_COMPLETE\",36054:\"FRAMEBUFFER_INCOMPLETE_ATTACHMENT\",36055:\"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT\",36057:\"FRAMEBUFFER_INCOMPLETE_DIMENSIONS\",36061:\"FRAMEBUFFER_UNSUPPORTED\",36064:\"COLOR_ATTACHMENT0\",36096:\"DEPTH_ATTACHMENT\",36128:\"STENCIL_ATTACHMENT\",36160:\"FRAMEBUFFER\",36161:\"RENDERBUFFER\",36162:\"RENDERBUFFER_WIDTH\",36163:\"RENDERBUFFER_HEIGHT\",36164:\"RENDERBUFFER_INTERNAL_FORMAT\",36168:\"STENCIL_INDEX8\",36176:\"RENDERBUFFER_RED_SIZE\",36177:\"RENDERBUFFER_GREEN_SIZE\",36178:\"RENDERBUFFER_BLUE_SIZE\",36179:\"RENDERBUFFER_ALPHA_SIZE\",36180:\"RENDERBUFFER_DEPTH_SIZE\",36181:\"RENDERBUFFER_STENCIL_SIZE\",36194:\"RGB565\",36336:\"LOW_FLOAT\",36337:\"MEDIUM_FLOAT\",36338:\"HIGH_FLOAT\",36339:\"LOW_INT\",36340:\"MEDIUM_INT\",36341:\"HIGH_INT\",36346:\"SHADER_COMPILER\",36347:\"MAX_VERTEX_UNIFORM_VECTORS\",36348:\"MAX_VARYING_VECTORS\",36349:\"MAX_FRAGMENT_UNIFORM_VECTORS\",37440:\"UNPACK_FLIP_Y_WEBGL\",37441:\"UNPACK_PREMULTIPLY_ALPHA_WEBGL\",37442:\"CONTEXT_LOST_WEBGL\",37443:\"UNPACK_COLORSPACE_CONVERSION_WEBGL\",37444:\"BROWSER_DEFAULT_WEBGL\"}},{}],249:[function(t,e,r){var n=t(\"./1.0/numbers\");e.exports=function(t){return n[t]}},{\"./1.0/numbers\":248}],250:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),o=a(e,[{buffer:r,type:e.FLOAT,size:3,offset:0,stride:40},{buffer:r,type:e.FLOAT,size:4,offset:12,stride:40},{buffer:r,type:e.FLOAT,size:3,offset:28,stride:40}]),l=i(e);l.attributes.position.location=0,l.attributes.color.location=1,l.attributes.offset.location=2;var c=new s(e,r,o,l);return c.update(t),c};var n=t(\"gl-buffer\"),a=t(\"gl-vao\"),i=t(\"./shaders/index\"),o=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function s(t,e,r,n){this.gl=t,this.shader=n,this.buffer=e,this.vao=r,this.pixelRatio=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lineWidth=[1,1,1],this.capSize=[10,10,10],this.lineCount=[0,0,0],this.lineOffset=[0,0,0],this.opacity=1,this.hasAlpha=!1}var l=s.prototype;function c(t,e){for(var r=0;r<3;++r)t[0][r]=Math.min(t[0][r],e[r]),t[1][r]=Math.max(t[1][r],e[r])}l.isOpaque=function(){return!this.hasAlpha},l.isTransparent=function(){return this.hasAlpha},l.drawTransparent=l.draw=function(t){var e=this.gl,r=this.shader.uniforms;this.shader.bind();var n=r.view=t.view||o,a=r.projection=t.projection||o;r.model=t.model||o,r.clipBounds=this.clipBounds,r.opacity=this.opacity;var i=n[12],s=n[13],l=n[14],c=n[15],u=(t._ortho||!1?2:1)*this.pixelRatio*(a[3]*i+a[7]*s+a[11]*l+a[15]*c)/e.drawingBufferHeight;this.vao.bind();for(var h=0;h<3;++h)e.lineWidth(this.lineWidth[h]*this.pixelRatio),r.capSize=this.capSize[h]*u,this.lineCount[h]&&e.drawArrays(e.LINES,this.lineOffset[h],this.lineCount[h]);this.vao.unbind()};var u=function(){for(var t=new Array(3),e=0;e<3;++e){for(var r=[],n=1;n<=2;++n)for(var a=-1;a<=1;a+=2){var i=[0,0,0];i[(n+e)%3]=a,r.push(i)}t[e]=r}return t}();function h(t,e,r,n){for(var a=u[n],i=0;i<a.length;++i){var o=a[i];t.push(e[0],e[1],e[2],r[0],r[1],r[2],r[3],o[0],o[1],o[2])}return a.length}l.update=function(t){\"lineWidth\"in(t=t||{})&&(this.lineWidth=t.lineWidth,Array.isArray(this.lineWidth)||(this.lineWidth=[this.lineWidth,this.lineWidth,this.lineWidth])),\"capSize\"in t&&(this.capSize=t.capSize,Array.isArray(this.capSize)||(this.capSize=[this.capSize,this.capSize,this.capSize])),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var e=t.color||[[0,0,0],[0,0,0],[0,0,0]],r=t.position,n=t.error;if(Array.isArray(e[0])||(e=[e,e,e]),r&&n){var a=[],i=r.length,o=0;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.lineCount=[0,0,0];for(var s=0;s<3;++s){this.lineOffset[s]=o;t:for(var l=0;l<i;++l){for(var u=r[l],f=0;f<3;++f)if(isNaN(u[f])||!isFinite(u[f]))continue t;var p=n[l],d=e[s];if(Array.isArray(d[0])&&(d=e[l]),3===d.length?d=[d[0],d[1],d[2],1]:4===d.length&&(d=[d[0],d[1],d[2],d[3]],!this.hasAlpha&&d[3]<1&&(this.hasAlpha=!0)),!isNaN(p[0][s])&&!isNaN(p[1][s])){var g;if(p[0][s]<0)(g=u.slice())[s]+=p[0][s],a.push(u[0],u[1],u[2],d[0],d[1],d[2],d[3],0,0,0,g[0],g[1],g[2],d[0],d[1],d[2],d[3],0,0,0),c(this.bounds,g),o+=2+h(a,g,d,s);if(p[1][s]>0)(g=u.slice())[s]+=p[1][s],a.push(u[0],u[1],u[2],d[0],d[1],d[2],d[3],0,0,0,g[0],g[1],g[2],d[0],d[1],d[2],d[3],0,0,0),c(this.bounds,g),o+=2+h(a,g,d,s)}}this.lineCount[s]=o-this.lineOffset[s]}this.buffer.update(a)}},l.dispose=function(){this.shader.dispose(),this.buffer.dispose(),this.vao.dispose()}},{\"./shaders/index\":251,\"gl-buffer\":244,\"gl-vao\":329}],251:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),a=t(\"gl-shader\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, offset;\\nattribute vec4 color;\\nuniform mat4 model, view, projection;\\nuniform float capSize;\\nvarying vec4 fragColor;\\nvarying vec3 fragPosition;\\n\\nvoid main() {\\n  vec4 worldPosition  = model * vec4(position, 1.0);\\n  worldPosition       = (worldPosition / worldPosition.w) + vec4(capSize * offset, 0.0);\\n  gl_Position         = projection * view * worldPosition;\\n  fragColor           = color;\\n  fragPosition        = position;\\n}\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float opacity;\\nvarying vec3 fragPosition;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if (\\n    outOfRange(clipBounds[0], clipBounds[1], fragPosition) ||\\n    fragColor.a * opacity == 0.\\n  ) discard;\\n\\n  gl_FragColor = opacity * fragColor;\\n}\"]);e.exports=function(t){return a(t,i,o,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"offset\",type:\"vec3\"}])}},{\"gl-shader\":304,glslify:411}],252:[function(t,e,r){\"use strict\";var n=t(\"gl-texture2d\");e.exports=function(t,e,r,n){a||(a=t.FRAMEBUFFER_UNSUPPORTED,i=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,o=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,s=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var c=t.getExtension(\"WEBGL_draw_buffers\");!l&&c&&function(t,e){var r=t.getParameter(e.MAX_COLOR_ATTACHMENTS_WEBGL);l=new Array(r+1);for(var n=0;n<=r;++n){for(var a=new Array(r),i=0;i<n;++i)a[i]=t.COLOR_ATTACHMENT0+i;for(var i=n;i<r;++i)a[i]=t.NONE;l[n]=a}}(t,c);Array.isArray(e)&&(n=r,r=0|e[1],e=0|e[0]);if(\"number\"!=typeof e)throw new Error(\"gl-fbo: Missing shape parameter\");var u=t.getParameter(t.MAX_RENDERBUFFER_SIZE);if(e<0||e>u||r<0||r>u)throw new Error(\"gl-fbo: Parameters are too large for FBO\");var h=1;if(\"color\"in(n=n||{})){if((h=Math.max(0|n.color,0))<0)throw new Error(\"gl-fbo: Must specify a nonnegative number of colors\");if(h>1){if(!c)throw new Error(\"gl-fbo: Multiple draw buffer extension not supported\");if(h>t.getParameter(c.MAX_COLOR_ATTACHMENTS_WEBGL))throw new Error(\"gl-fbo: Context does not support \"+h+\" draw buffers\")}}var f=t.UNSIGNED_BYTE,p=t.getExtension(\"OES_texture_float\");if(n.float&&h>0){if(!p)throw new Error(\"gl-fbo: Context does not support floating point textures\");f=t.FLOAT}else n.preferFloat&&h>0&&p&&(f=t.FLOAT);var g=!0;\"depth\"in n&&(g=!!n.depth);var v=!1;\"stencil\"in n&&(v=!!n.stencil);return new d(t,e,r,f,h,g,v,c)};var a,i,o,s,l=null;function c(t){return[t.getParameter(t.FRAMEBUFFER_BINDING),t.getParameter(t.RENDERBUFFER_BINDING),t.getParameter(t.TEXTURE_BINDING_2D)]}function u(t,e){t.bindFramebuffer(t.FRAMEBUFFER,e[0]),t.bindRenderbuffer(t.RENDERBUFFER,e[1]),t.bindTexture(t.TEXTURE_2D,e[2])}function h(t){switch(t){case a:throw new Error(\"gl-fbo: Framebuffer unsupported\");case i:throw new Error(\"gl-fbo: Framebuffer incomplete attachment\");case o:throw new Error(\"gl-fbo: Framebuffer incomplete dimensions\");case s:throw new Error(\"gl-fbo: Framebuffer incomplete missing attachment\");default:throw new Error(\"gl-fbo: Framebuffer failed for unspecified reason\")}}function f(t,e,r,a,i,o){if(!a)return null;var s=n(t,e,r,i,a);return s.magFilter=t.NEAREST,s.minFilter=t.NEAREST,s.mipSamples=1,s.bind(),t.framebufferTexture2D(t.FRAMEBUFFER,o,t.TEXTURE_2D,s.handle,0),s}function p(t,e,r,n,a){var i=t.createRenderbuffer();return t.bindRenderbuffer(t.RENDERBUFFER,i),t.renderbufferStorage(t.RENDERBUFFER,n,e,r),t.framebufferRenderbuffer(t.FRAMEBUFFER,a,t.RENDERBUFFER,i),i}function d(t,e,r,n,a,i,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(a);for(var d=0;d<a;++d)this.color[d]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=i,this._useStencil=o;var g=this,v=[0|e,0|r];Object.defineProperties(v,{0:{get:function(){return g._shape[0]},set:function(t){return g.width=t}},1:{get:function(){return g._shape[1]},set:function(t){return g.height=t}}}),this._shapeVector=v,function(t){var e=c(t.gl),r=t.gl,n=t.handle=r.createFramebuffer(),a=t._shape[0],i=t._shape[1],o=t.color.length,s=t._ext,d=t._useStencil,g=t._useDepth,v=t._colorType;r.bindFramebuffer(r.FRAMEBUFFER,n);for(var m=0;m<o;++m)t.color[m]=f(r,a,i,v,r.RGBA,r.COLOR_ATTACHMENT0+m);0===o?(t._color_rb=p(r,a,i,r.RGBA4,r.COLOR_ATTACHMENT0),s&&s.drawBuffersWEBGL(l[0])):o>1&&s.drawBuffersWEBGL(l[o]);var y=r.getExtension(\"WEBGL_depth_texture\");y?d?t.depth=f(r,a,i,y.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):g&&(t.depth=f(r,a,i,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):g&&d?t._depth_rb=p(r,a,i,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):g?t._depth_rb=p(r,a,i,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=p(r,a,i,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){for(t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null),m=0;m<t.color.length;++m)t.color[m].dispose(),t.color[m]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),u(r,e),h(x)}u(r,e)}(this)}var g=d.prototype;function v(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var n=t.gl,a=n.getParameter(n.MAX_RENDERBUFFER_SIZE);if(e<0||e>a||r<0||r>a)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var i=c(n),o=0;o<t.color.length;++o)t.color[o].shape=t._shape;t._color_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._color_rb),n.renderbufferStorage(n.RENDERBUFFER,n.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&n.renderbufferStorage(n.RENDERBUFFER,n.STENCIL_INDEX,t._shape[0],t._shape[1])),n.bindFramebuffer(n.FRAMEBUFFER,t.handle);var s=n.checkFramebufferStatus(n.FRAMEBUFFER);s!==n.FRAMEBUFFER_COMPLETE&&(t.dispose(),u(n,i),h(s)),u(n,i)}}Object.defineProperties(g,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return v(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return v(this,t|=0,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t|=0,v(this,this._shape[0],t),t},enumerable:!1}}),g.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},g.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},{\"gl-texture2d\":324}],253:[function(t,e,r){var n=t(\"sprintf-js\").sprintf,a=t(\"gl-constants/lookup\"),i=t(\"glsl-shader-name\"),o=t(\"add-line-numbers\");e.exports=function(t,e,r){\"use strict\";var s=i(e)||\"of unknown name (see npm glsl-shader-name)\",l=\"unknown type\";void 0!==r&&(l=r===a.FRAGMENT_SHADER?\"fragment\":\"vertex\");for(var c=n(\"Error compiling %s shader %s:\\n\",l,s),u=n(\"%s%s\",c,t),h=t.split(\"\\n\"),f={},p=0;p<h.length;p++){var d=h[p];if(\"\"!==d&&\"\\0\"!==d){var g=parseInt(d.split(\":\")[2]);if(isNaN(g))throw new Error(n(\"Could not parse error: %s\",d));f[g]=d}}for(var v=o(e).split(\"\\n\"),p=0;p<v.length;p++)if(f[p+3]||f[p+2]||f[p+1]){var m=v[p];if(c+=m+\"\\n\",f[p+1]){var y=f[p+1];y=y.substr(y.split(\":\",3).join(\":\").length+1).trim(),c+=n(\"^^^ %s\\n\\n\",y)}}return{long:c.trim(),short:u.trim()}}},{\"add-line-numbers\":64,\"gl-constants/lookup\":249,\"glsl-shader-name\":403,\"sprintf-js\":527}],254:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=t.gl,n=o(r,l.vertex,l.fragment),a=o(r,l.pickVertex,l.pickFragment),i=s(r),u=s(r),h=s(r),f=s(r),p=new c(t,n,a,i,u,h,f);return p.update(e),t.addObject(p),p};var n=t(\"binary-search-bounds\"),a=t(\"iota-array\"),i=t(\"typedarray-pool\"),o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"./lib/shaders\");function c(t,e,r,n,a,i,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.weightBuffer=a,this.colorBuffer=i,this.idBuffer=o,this.xData=[],this.yData=[],this.shape=[0,0],this.bounds=[1/0,1/0,-1/0,-1/0],this.pickOffset=0}var u,h=c.prototype,f=[0,0,1,0,0,1,1,0,1,1,0,1];h.draw=(u=[1,0,0,0,1,0,0,0,1],function(){var t=this.plot,e=this.shader,r=this.bounds,n=this.numVertices;if(!(n<=0)){var a=t.gl,i=t.dataBox,o=r[2]-r[0],s=r[3]-r[1],l=i[2]-i[0],c=i[3]-i[1];u[0]=2*o/l,u[4]=2*s/c,u[6]=2*(r[0]-i[0])/l-1,u[7]=2*(r[1]-i[1])/c-1,e.bind();var h=e.uniforms;h.viewTransform=u,h.shape=this.shape;var f=e.attributes;this.positionBuffer.bind(),f.position.pointer(),this.weightBuffer.bind(),f.weight.pointer(a.UNSIGNED_BYTE,!1),this.colorBuffer.bind(),f.color.pointer(a.UNSIGNED_BYTE,!0),a.drawArrays(a.TRIANGLES,0,n)}}),h.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,a=this.pickShader,i=this.bounds,o=this.numVertices;if(!(o<=0)){var s=n.gl,l=n.dataBox,c=i[2]-i[0],u=i[3]-i[1],h=l[2]-l[0],f=l[3]-l[1];t[0]=2*c/h,t[4]=2*u/f,t[6]=2*(i[0]-l[0])/h-1,t[7]=2*(i[1]-l[1])/f-1;for(var p=0;p<4;++p)e[p]=r>>8*p&255;this.pickOffset=r,a.bind();var d=a.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var g=a.attributes;return this.positionBuffer.bind(),g.position.pointer(),this.weightBuffer.bind(),g.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),g.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),h.pick=function(t,e,r){var n=this.pickOffset,a=this.shape[0]*this.shape[1];if(r<n||r>=n+a)return null;var i=r-n,o=this.xData,s=this.yData;return{object:this,pointId:i,dataCoord:[o[i%this.shape[0]],s[i/this.shape[0]|0]]}},h.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||a(e[0]),o=t.y||a(e[1]),s=t.z||new Float32Array(e[0]*e[1]);this.xData=r,this.yData=o;var l=t.colorLevels||[0],c=t.colorValues||[0,0,0,1],u=l.length,h=this.bounds,p=h[0]=r[0],d=h[1]=o[0],g=1/((h[2]=r[r.length-1])-p),v=1/((h[3]=o[o.length-1])-d),m=e[0],y=e[1];this.shape=[m,y];var x=(m-1)*(y-1)*(f.length>>>1);this.numVertices=x;for(var b=i.mallocUint8(4*x),_=i.mallocFloat32(2*x),w=i.mallocUint8(2*x),k=i.mallocUint32(x),T=0,M=0;M<y-1;++M)for(var A=v*(o[M]-d),S=v*(o[M+1]-d),E=0;E<m-1;++E)for(var L=g*(r[E]-p),C=g*(r[E+1]-p),P=0;P<f.length;P+=2){var O,z,I,D,R=f[P],F=f[P+1],B=s[(M+F)*m+(E+R)],N=n.le(l,B);if(N<0)O=c[0],z=c[1],I=c[2],D=c[3];else if(N===u-1)O=c[4*u-4],z=c[4*u-3],I=c[4*u-2],D=c[4*u-1];else{var j=(B-l[N])/(l[N+1]-l[N]),V=1-j,U=4*N,q=4*(N+1);O=V*c[U]+j*c[q],z=V*c[U+1]+j*c[q+1],I=V*c[U+2]+j*c[q+2],D=V*c[U+3]+j*c[q+3]}b[4*T]=255*O,b[4*T+1]=255*z,b[4*T+2]=255*I,b[4*T+3]=255*D,_[2*T]=.5*L+.5*C,_[2*T+1]=.5*A+.5*S,w[2*T]=R,w[2*T+1]=F,k[T]=M*m+E,T+=1}this.positionBuffer.update(_),this.weightBuffer.update(w),this.colorBuffer.update(b),this.idBuffer.update(k),i.free(_),i.free(b),i.free(w),i.free(k)},h.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.weightBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":255,\"binary-search-bounds\":256,\"gl-buffer\":244,\"gl-shader\":304,\"iota-array\":418,\"typedarray-pool\":544}],255:[function(t,e,r){\"use strict\";var n=t(\"glslify\");e.exports={fragment:n([\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\"]),vertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 color;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  fragColor = color;\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"]),pickFragment:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nuniform vec2 shape;\\nuniform vec4 pickOffset;\\n\\nvoid main() {\\n  vec2 d = step(.5, vWeight);\\n  vec4 id = fragId + pickOffset;\\n  id.x += d.x + d.y*shape.x;\\n\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  gl_FragColor = id/255.;\\n}\\n\"]),pickVertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nvoid main() {\\n  vWeight = weight;\\n\\n  fragId = pickId;\\n\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"])}},{glslify:411}],256:[function(t,e,r){arguments[4][113][0].apply(r,arguments)},{dup:113}],257:[function(t,e,r){var n=t(\"glslify\"),a=t(\"gl-shader\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  vec4 startPoint = project(position);\\n  vec4 endPoint   = project(nextPosition);\\n\\n  vec2 A = startPoint.xy / startPoint.w;\\n  vec2 B =   endPoint.xy /   endPoint.w;\\n\\n  float clipAngle = atan(\\n    (B.y - A.y) * screenShape.y,\\n    (B.x - A.x) * screenShape.x\\n  );\\n\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(\\n    sin(clipAngle),\\n    -cos(clipAngle)\\n  ) / screenShape;\\n\\n  gl_Position = vec4(startPoint.xy + startPoint.w * offset, startPoint.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3      clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float     dashScale;\\nuniform float     opacity;\\n\\nvarying vec3    worldPosition;\\nvarying float   pixelArcLength;\\nvarying vec4    fragColor;\\n\\nvoid main() {\\n  if (\\n    outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\\n    fragColor.a * opacity == 0.\\n  ) discard;\\n\\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n  if(dashWeight < 0.5) {\\n    discard;\\n  }\\n  gl_FragColor = fragColor * opacity;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\nlowp vec4 encode_float_1540259130(highp float v) {\\n  highp float av = abs(v);\\n\\n  //Handle special cases\\n  if(av < FLOAT_MIN) {\\n    return vec4(0.0, 0.0, 0.0, 0.0);\\n  } else if(v > FLOAT_MAX) {\\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n  } else if(v < -FLOAT_MAX) {\\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n  }\\n\\n  highp vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  highp float e = floor(log2(av));\\n  highp float m = av * pow(2.0, -e) - 1.0;\\n  \\n  //Unpack mantissa\\n  c[1] = floor(128.0 * m);\\n  m -= c[1] / 128.0;\\n  c[2] = floor(32768.0 * m);\\n  m -= c[2] / 32768.0;\\n  c[3] = floor(8388608.0 * m);\\n  \\n  //Unpack exponent\\n  highp float ebias = e + 127.0;\\n  c[0] = floor(ebias / 2.0);\\n  ebias -= c[0] * 2.0;\\n  c[1] += floor(ebias) * 128.0; \\n\\n  //Unpack sign bit\\n  c[0] += 128.0 * step(0.0, -v);\\n\\n  //Scale back to range\\n  return c / 255.0;\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\\n\\n  gl_FragColor = vec4(pickId/255.0, encode_float_1540259130(pixelArcLength).xyz);\\n}\"]),l=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];r.createShader=function(t){return a(t,i,o,null,l)},r.createPickShader=function(t){return a(t,i,s,null,l)}},{\"gl-shader\":304,glslify:411}],258:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=u(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=h(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),c=a(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),f=l(new Array(1024),[256,1,4]),p=0;p<1024;++p)f.data[p]=255;var d=i(e,f);d.wrap=e.REPEAT;var g=new v(e,r,o,s,c,d);return g.update(t),g};var n=t(\"gl-buffer\"),a=t(\"gl-vao\"),i=t(\"gl-texture2d\"),o=t(\"glsl-read-float\"),s=t(\"binary-search-bounds\"),l=t(\"ndarray\"),c=t(\"./lib/shaders\"),u=c.createShader,h=c.createPickShader,f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function p(t,e){for(var r=0,n=0;n<3;++n){var a=t[n]-e[n];r+=a*a}return Math.sqrt(r)}function d(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function g(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function v(t,e,r,n,a,i){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=a,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=i,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var m=v.prototype;m.isTransparent=function(){return this.hasAlpha},m.isOpaque=function(){return!this.hasAlpha},m.pickSlots=1,m.setPickBase=function(t){this.pickId=t},m.drawTransparent=m.draw=function(t){if(this.vertexCount){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||f,view:t.view||f,projection:t.projection||f,clipBounds:d(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},m.drawPick=function(t){if(this.vertexCount){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||f,view:t.view||f,projection:t.projection||f,pickId:this.pickId,clipBounds:d(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},m.update=function(t){var e,r;this.dirty=!0;var n=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var a=[],i=[],o=[],c=0,u=0,h=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],f=t.position||t.positions;if(f){var d=t.color||t.colors||[0,0,0,1],g=t.lineWidth||1,v=!1;t:for(e=1;e<f.length;++e){var m,y,x,b=f[e-1],_=f[e];for(i.push(c),o.push(b.slice()),r=0;r<3;++r){if(isNaN(b[r])||isNaN(_[r])||!isFinite(b[r])||!isFinite(_[r])){if(!n&&a.length>0){for(var w=0;w<24;++w)a.push(a[a.length-12]);u+=2,v=!0}continue t}h[0][r]=Math.min(h[0][r],b[r],_[r]),h[1][r]=Math.max(h[1][r],b[r],_[r])}Array.isArray(d[0])?(m=d.length>e-1?d[e-1]:d.length>0?d[d.length-1]:[0,0,0,1],y=d.length>e?d[e]:d.length>0?d[d.length-1]:[0,0,0,1]):m=y=d,3===m.length&&(m=[m[0],m[1],m[2],1]),3===y.length&&(y=[y[0],y[1],y[2],1]),!this.hasAlpha&&m[3]<1&&(this.hasAlpha=!0),x=Array.isArray(g)?g.length>e-1?g[e-1]:g.length>0?g[g.length-1]:[0,0,0,1]:g;var k=c;if(c+=p(b,_),v){for(r=0;r<2;++r)a.push(b[0],b[1],b[2],_[0],_[1],_[2],k,x,m[0],m[1],m[2],m[3]);u+=2,v=!1}a.push(b[0],b[1],b[2],_[0],_[1],_[2],k,x,m[0],m[1],m[2],m[3],b[0],b[1],b[2],_[0],_[1],_[2],k,-x,m[0],m[1],m[2],m[3],_[0],_[1],_[2],b[0],b[1],b[2],c,-x,y[0],y[1],y[2],y[3],_[0],_[1],_[2],b[0],b[1],b[2],c,x,y[0],y[1],y[2],y[3]),u+=4}}if(this.buffer.update(a),i.push(c),o.push(f[f.length-1].slice()),this.bounds=h,this.vertexCount=u,this.points=o,this.arcLength=i,\"dashes\"in t){var T=t.dashes.slice();for(T.unshift(0),e=1;e<T.length;++e)T[e]=T[e-1]+T[e];var M=l(new Array(1024),[256,1,4]);for(e=0;e<256;++e){for(r=0;r<4;++r)M.set(e,0,r,0);1&s.le(T,T[T.length-1]*e/255)?M.set(e,0,0,0):M.set(e,0,0,255)}this.texture.setPixels(M)}},m.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},m.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=o(t.value[0],t.value[1],t.value[2],0),r=s.le(this.arcLength,e);if(r<0)return null;if(r===this.arcLength.length-1)return new g(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],a=this.points[Math.min(r+1,this.points.length-1)],i=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),l=1-i,c=[0,0,0],u=0;u<3;++u)c[u]=l*n[u]+i*a[u];var h=Math.min(i<.5?r:r+1,this.points.length-1);return new g(e,c,h,this.points[h])}},{\"./lib/shaders\":257,\"binary-search-bounds\":259,\"gl-buffer\":244,\"gl-texture2d\":324,\"gl-vao\":329,\"glsl-read-float\":402,ndarray:452}],259:[function(t,e,r){arguments[4][113][0].apply(r,arguments)},{dup:113}],260:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],a=e[2],i=e[3],o=r*i-a*n;return o?(o=1/o,t[0]=i*o,t[1]=-n*o,t[2]=-a*o,t[3]=r*o,t):null}},{}],261:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],a=e[2],i=e[3],o=e[4],s=e[5],l=e[6],c=e[7],u=e[8],h=u*o-s*c,f=-u*i+s*l,p=c*i-o*l,d=r*h+n*f+a*p;return d?(d=1/d,t[0]=h*d,t[1]=(-u*n+a*c)*d,t[2]=(s*n-a*o)*d,t[3]=f*d,t[4]=(u*r-a*l)*d,t[5]=(-s*r+a*i)*d,t[6]=p*d,t[7]=(-c*r+n*l)*d,t[8]=(o*r-n*i)*d,t):null}},{}],262:[function(t,e,r){e.exports=function(t){var e=new Float32Array(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e}},{}],263:[function(t,e,r){e.exports=function(){var t=new Float32Array(16);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],264:[function(t,e,r){e.exports=function(t){var e=t[0],r=t[1],n=t[2],a=t[3],i=t[4],o=t[5],s=t[6],l=t[7],c=t[8],u=t[9],h=t[10],f=t[11],p=t[12],d=t[13],g=t[14],v=t[15];return(e*o-r*i)*(h*v-f*g)-(e*s-n*i)*(u*v-f*d)+(e*l-a*i)*(u*g-h*d)+(r*s-n*o)*(c*v-f*p)-(r*l-a*o)*(c*g-h*p)+(n*l-a*s)*(c*d-u*p)}},{}],265:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],a=e[2],i=e[3],o=r+r,s=n+n,l=a+a,c=r*o,u=n*o,h=n*s,f=a*o,p=a*s,d=a*l,g=i*o,v=i*s,m=i*l;return t[0]=1-h-d,t[1]=u+m,t[2]=f-v,t[3]=0,t[4]=u-m,t[5]=1-c-d,t[6]=p+g,t[7]=0,t[8]=f+v,t[9]=p-g,t[10]=1-c-h,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],266:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],a=e[1],i=e[2],o=e[3],s=n+n,l=a+a,c=i+i,u=n*s,h=n*l,f=n*c,p=a*l,d=a*c,g=i*c,v=o*s,m=o*l,y=o*c;return t[0]=1-(p+g),t[1]=h+y,t[2]=f-m,t[3]=0,t[4]=h-y,t[5]=1-(u+g),t[6]=d+v,t[7]=0,t[8]=f+m,t[9]=d-v,t[10]=1-(u+p),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}},{}],267:[function(t,e,r){e.exports=function(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],268:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],a=e[2],i=e[3],o=e[4],s=e[5],l=e[6],c=e[7],u=e[8],h=e[9],f=e[10],p=e[11],d=e[12],g=e[13],v=e[14],m=e[15],y=r*s-n*o,x=r*l-a*o,b=r*c-i*o,_=n*l-a*s,w=n*c-i*s,k=a*c-i*l,T=u*g-h*d,M=u*v-f*d,A=u*m-p*d,S=h*v-f*g,E=h*m-p*g,L=f*m-p*v,C=y*L-x*E+b*S+_*A-w*M+k*T;if(!C)return null;return C=1/C,t[0]=(s*L-l*E+c*S)*C,t[1]=(a*E-n*L-i*S)*C,t[2]=(g*k-v*w+m*_)*C,t[3]=(f*w-h*k-p*_)*C,t[4]=(l*A-o*L-c*M)*C,t[5]=(r*L-a*A+i*M)*C,t[6]=(v*b-d*k-m*x)*C,t[7]=(u*k-f*b+p*x)*C,t[8]=(o*E-s*A+c*T)*C,t[9]=(n*A-r*E-i*T)*C,t[10]=(d*w-g*b+m*y)*C,t[11]=(h*b-u*w-p*y)*C,t[12]=(s*M-o*S-l*T)*C,t[13]=(r*S-n*M+a*T)*C,t[14]=(g*x-d*_-v*y)*C,t[15]=(u*_-h*x+f*y)*C,t}},{}],269:[function(t,e,r){var n=t(\"./identity\");e.exports=function(t,e,r,a){var i,o,s,l,c,u,h,f,p,d,g=e[0],v=e[1],m=e[2],y=a[0],x=a[1],b=a[2],_=r[0],w=r[1],k=r[2];if(Math.abs(g-_)<1e-6&&Math.abs(v-w)<1e-6&&Math.abs(m-k)<1e-6)return n(t);h=g-_,f=v-w,p=m-k,d=1/Math.sqrt(h*h+f*f+p*p),i=x*(p*=d)-b*(f*=d),o=b*(h*=d)-y*p,s=y*f-x*h,(d=Math.sqrt(i*i+o*o+s*s))?(i*=d=1/d,o*=d,s*=d):(i=0,o=0,s=0);l=f*s-p*o,c=p*i-h*s,u=h*o-f*i,(d=Math.sqrt(l*l+c*c+u*u))?(l*=d=1/d,c*=d,u*=d):(l=0,c=0,u=0);return t[0]=i,t[1]=l,t[2]=h,t[3]=0,t[4]=o,t[5]=c,t[6]=f,t[7]=0,t[8]=s,t[9]=u,t[10]=p,t[11]=0,t[12]=-(i*g+o*v+s*m),t[13]=-(l*g+c*v+u*m),t[14]=-(h*g+f*v+p*m),t[15]=1,t}},{\"./identity\":267}],270:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],a=e[1],i=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],h=e[8],f=e[9],p=e[10],d=e[11],g=e[12],v=e[13],m=e[14],y=e[15],x=r[0],b=r[1],_=r[2],w=r[3];return t[0]=x*n+b*s+_*h+w*g,t[1]=x*a+b*l+_*f+w*v,t[2]=x*i+b*c+_*p+w*m,t[3]=x*o+b*u+_*d+w*y,x=r[4],b=r[5],_=r[6],w=r[7],t[4]=x*n+b*s+_*h+w*g,t[5]=x*a+b*l+_*f+w*v,t[6]=x*i+b*c+_*p+w*m,t[7]=x*o+b*u+_*d+w*y,x=r[8],b=r[9],_=r[10],w=r[11],t[8]=x*n+b*s+_*h+w*g,t[9]=x*a+b*l+_*f+w*v,t[10]=x*i+b*c+_*p+w*m,t[11]=x*o+b*u+_*d+w*y,x=r[12],b=r[13],_=r[14],w=r[15],t[12]=x*n+b*s+_*h+w*g,t[13]=x*a+b*l+_*f+w*v,t[14]=x*i+b*c+_*p+w*m,t[15]=x*o+b*u+_*d+w*y,t}},{}],271:[function(t,e,r){e.exports=function(t,e,r,n,a,i,o){var s=1/(e-r),l=1/(n-a),c=1/(i-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*c,t[11]=0,t[12]=(e+r)*s,t[13]=(a+n)*l,t[14]=(o+i)*c,t[15]=1,t}},{}],272:[function(t,e,r){e.exports=function(t,e,r,n,a){var i=1/Math.tan(e/2),o=1/(n-a);return t[0]=i/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=i,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(a+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*a*n*o,t[15]=0,t}},{}],273:[function(t,e,r){e.exports=function(t,e,r,n){var a,i,o,s,l,c,u,h,f,p,d,g,v,m,y,x,b,_,w,k,T,M,A,S,E=n[0],L=n[1],C=n[2],P=Math.sqrt(E*E+L*L+C*C);if(Math.abs(P)<1e-6)return null;E*=P=1/P,L*=P,C*=P,a=Math.sin(r),i=Math.cos(r),o=1-i,s=e[0],l=e[1],c=e[2],u=e[3],h=e[4],f=e[5],p=e[6],d=e[7],g=e[8],v=e[9],m=e[10],y=e[11],x=E*E*o+i,b=L*E*o+C*a,_=C*E*o-L*a,w=E*L*o-C*a,k=L*L*o+i,T=C*L*o+E*a,M=E*C*o+L*a,A=L*C*o-E*a,S=C*C*o+i,t[0]=s*x+h*b+g*_,t[1]=l*x+f*b+v*_,t[2]=c*x+p*b+m*_,t[3]=u*x+d*b+y*_,t[4]=s*w+h*k+g*T,t[5]=l*w+f*k+v*T,t[6]=c*w+p*k+m*T,t[7]=u*w+d*k+y*T,t[8]=s*M+h*A+g*S,t[9]=l*M+f*A+v*S,t[10]=c*M+p*A+m*S,t[11]=u*M+d*A+y*S,e!==t&&(t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t}},{}],274:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),a=Math.cos(r),i=e[4],o=e[5],s=e[6],l=e[7],c=e[8],u=e[9],h=e[10],f=e[11];e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[4]=i*a+c*n,t[5]=o*a+u*n,t[6]=s*a+h*n,t[7]=l*a+f*n,t[8]=c*a-i*n,t[9]=u*a-o*n,t[10]=h*a-s*n,t[11]=f*a-l*n,t}},{}],275:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),a=Math.cos(r),i=e[0],o=e[1],s=e[2],l=e[3],c=e[8],u=e[9],h=e[10],f=e[11];e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=i*a-c*n,t[1]=o*a-u*n,t[2]=s*a-h*n,t[3]=l*a-f*n,t[8]=i*n+c*a,t[9]=o*n+u*a,t[10]=s*n+h*a,t[11]=l*n+f*a,t}},{}],276:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),a=Math.cos(r),i=e[0],o=e[1],s=e[2],l=e[3],c=e[4],u=e[5],h=e[6],f=e[7];e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=i*a+c*n,t[1]=o*a+u*n,t[2]=s*a+h*n,t[3]=l*a+f*n,t[4]=c*a-i*n,t[5]=u*a-o*n,t[6]=h*a-s*n,t[7]=f*a-l*n,t}},{}],277:[function(t,e,r){e.exports=function(t,e,r){var n=r[0],a=r[1],i=r[2];return t[0]=e[0]*n,t[1]=e[1]*n,t[2]=e[2]*n,t[3]=e[3]*n,t[4]=e[4]*a,t[5]=e[5]*a,t[6]=e[6]*a,t[7]=e[7]*a,t[8]=e[8]*i,t[9]=e[9]*i,t[10]=e[10]*i,t[11]=e[11]*i,t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t}},{}],278:[function(t,e,r){e.exports=function(t,e,r){var n,a,i,o,s,l,c,u,h,f,p,d,g=r[0],v=r[1],m=r[2];e===t?(t[12]=e[0]*g+e[4]*v+e[8]*m+e[12],t[13]=e[1]*g+e[5]*v+e[9]*m+e[13],t[14]=e[2]*g+e[6]*v+e[10]*m+e[14],t[15]=e[3]*g+e[7]*v+e[11]*m+e[15]):(n=e[0],a=e[1],i=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],h=e[8],f=e[9],p=e[10],d=e[11],t[0]=n,t[1]=a,t[2]=i,t[3]=o,t[4]=s,t[5]=l,t[6]=c,t[7]=u,t[8]=h,t[9]=f,t[10]=p,t[11]=d,t[12]=n*g+s*v+h*m+e[12],t[13]=a*g+l*v+f*m+e[13],t[14]=i*g+c*v+p*m+e[14],t[15]=o*g+u*v+d*m+e[15]);return t}},{}],279:[function(t,e,r){e.exports=function(t,e){if(t===e){var r=e[1],n=e[2],a=e[3],i=e[6],o=e[7],s=e[11];t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=r,t[6]=e[9],t[7]=e[13],t[8]=n,t[9]=i,t[11]=e[14],t[12]=a,t[13]=o,t[14]=s}else t[0]=e[0],t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=e[1],t[5]=e[5],t[6]=e[9],t[7]=e[13],t[8]=e[2],t[9]=e[6],t[10]=e[10],t[11]=e[14],t[12]=e[3],t[13]=e[7],t[14]=e[11],t[15]=e[15];return t}},{}],280:[function(t,e,r){\"use strict\";e.exports=function(t,e){switch(e.length){case 0:break;case 1:t[0]=1/e[0];break;case 4:n(t,e);break;case 9:a(t,e);break;case 16:i(t,e);break;default:throw new Error(\"currently supports matrices up to 4x4\")}return t};var n=t(\"gl-mat2/invert\"),a=t(\"gl-mat3/invert\"),i=t(\"gl-mat4/invert\")},{\"gl-mat2/invert\":260,\"gl-mat3/invert\":261,\"gl-mat4/invert\":268}],281:[function(t,e,r){\"use strict\";var n=t(\"barycentric\"),a=t(\"polytope-closest-point/lib/closest_point_2d.js\");function i(t,e){for(var r=[0,0,0,0],n=0;n<4;++n)for(var a=0;a<4;++a)r[a]+=t[4*n+a]*e[n];return r}function o(t,e,r,n,a){for(var o=i(n,i(r,i(e,[t[0],t[1],t[2],1]))),s=0;s<3;++s)o[s]/=o[3];return[.5*a[0]*(1+o[0]),.5*a[1]*(1-o[1])]}function s(t,e){for(var r=[0,0,0],n=0;n<t.length;++n)for(var a=t[n],i=e[n],o=0;o<3;++o)r[o]+=i*a[o];return r}e.exports=function(t,e,r,i,l,c){if(1===t.length)return[0,t[0].slice()];for(var u=new Array(t.length),h=0;h<t.length;++h)u[h]=o(t[h],r,i,l,c);for(var f=0,p=1/0,h=0;h<u.length;++h){for(var d=0,g=0;g<2;++g)d+=Math.pow(u[h][g]-e[g],2);d<p&&(p=d,f=h)}for(var v=function(t,e){if(2===t.length){for(var r=0,i=0,o=0;o<2;++o)r+=Math.pow(e[o]-t[0][o],2),i+=Math.pow(e[o]-t[1][o],2);return r=Math.sqrt(r),i=Math.sqrt(i),r+i<1e-6?[1,0]:[i/(r+i),r/(i+r)]}if(3===t.length){var s=[0,0];return a(t[0],t[1],t[2],e,s),n(t,s)}return[]}(u,e),m=0,h=0;h<3;++h){if(v[h]<-.001||v[h]>1.0001)return null;m+=v[h]}if(Math.abs(m-1)>.001)return null;return[f,s(t,v),v]}},{barycentric:75,\"polytope-closest-point/lib/closest_point_2d.js\":483}],282:[function(t,e,r){var n=t(\"glslify\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n           , view\\n           , projection\\n           , inverseModel;\\nuniform vec3 eyePosition\\n           , lightPosition;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  gl_Position      = project(position);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * vec4(position , 1.0);\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal  = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  f_color          = color;\\n  f_data           = position;\\n  f_uv             = uv;\\n}\\n\"]),i=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n            , fresnel\\n            , kambient\\n            , kdiffuse\\n            , kspecular;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (f_color.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], f_data)\\n  ) discard;\\n\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\\n\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * f_color.a;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_color = color;\\n  f_data  = position;\\n  f_uv    = uv;\\n}\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\\n\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\\n  } else {\\n    gl_Position = projection * view * model * vec4(position, 1.0);\\n  }\\n  gl_PointSize = pointSize;\\n  f_color = color;\\n  f_uv = uv;\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\\n  if(dot(pointR, pointR) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_id        = id;\\n  f_position  = position;\\n}\"]),h=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]),f=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3  position;\\nattribute float pointSize;\\nattribute vec4  id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\\n  } else {\\n    gl_Position  = projection * view * model * vec4(position, 1.0);\\n    gl_PointSize = pointSize;\\n  }\\n  f_id         = id;\\n  f_position   = position;\\n}\"]),p=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n}\"]),d=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n  gl_FragColor = vec4(contourColor, 1.0);\\n}\\n\"]);r.meshShader={vertex:a,fragment:i,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.wireShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.pointShader={vertex:l,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},r.pickShader={vertex:u,fragment:h,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},r.pointPickShader={vertex:f,fragment:h,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},r.contourShader={vertex:p,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},{glslify:411}],283:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),a=t(\"gl-buffer\"),i=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"normals\"),l=t(\"gl-mat4/multiply\"),c=t(\"gl-mat4/invert\"),u=t(\"ndarray\"),h=t(\"colormap\"),f=t(\"simplicial-complex-contour\"),p=t(\"typedarray-pool\"),d=t(\"./lib/shaders\"),g=t(\"./lib/closest-point\"),v=d.meshShader,m=d.wireShader,y=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function k(t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g,v,m,y,x,b,_,k,T,M,A,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=a,this.pickShader=i,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=u,this.triangleNormals=f,this.triangleUVs=h,this.triangleIds=c,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=v,this.edgeUVs=m,this.edgeIds=g,this.edgeVAO=y,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=k,this.pointSizes=T,this.pointIds=b,this.pointVAO=M,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=A,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var T=k.prototype;function M(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function A(t){var e=n(t,y.vertex,y.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function S(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function E(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function L(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}T.isOpaque=function(){return!this.hasAlpha},T.isTransparent=function(){return this.hasAlpha},T.pickSlots=1,T.setPickBase=function(t){this.pickId=t},T.highlight=function(t){if(t&&this.contourEnable){for(var e=f(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,a=e.vertexWeights,i=r.length,o=p.mallocFloat32(6*i),s=0,l=0;l<i;++l)for(var c=r[l],u=0;u<2;++u){var h=c[0];2===c.length&&(h=c[u]);for(var d=n[h][0],g=n[h][1],v=a[h],m=1-v,y=this.positions[d],x=this.positions[g],b=0;b<3;++b)o[s++]=v*y[b]+m*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},T.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=t.opacity,this.opacity<1&&(this.hasAlpha=!0)),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale,this.hasAlpha=!0),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t,e){for(var r=h({colormap:t,nshades:256,format:\"rgba\"}),n=new Uint8Array(1024),a=0;a<256;++a){for(var i=r[a],o=0;o<3;++o)n[4*a+o]=i[o];n[4*a+3]=e?255*M(a/255,e):255*i[3]}return u(n,[256,256,4],[4,0,1])}(t.colormap,this.opacityscale)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var a=[],i=[],l=[],c=[],f=[],p=[],d=[],g=[],v=[],m=[],y=[],x=[],b=[],_=[];this.cells=r,this.positions=n;var w=t.vertexNormals,k=t.cellNormals,T=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,A=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!k&&(k=s.faceNormals(r,n,A)),k||w||(w=s.vertexNormals(r,n,T));var S=t.vertexColors,E=t.cellColors,L=t.meshColor||[1,1,1,1],C=t.vertexUVs,P=t.vertexIntensity,O=t.cellUVs,z=t.cellIntensity,I=1/0,D=-1/0;if(!C&&!O)if(P)if(t.vertexIntensityBounds)I=+t.vertexIntensityBounds[0],D=+t.vertexIntensityBounds[1];else for(var R=0;R<P.length;++R){var F=P[R];I=Math.min(I,F),D=Math.max(D,F)}else if(z)if(t.cellIntensityBounds)I=+t.cellIntensityBounds[0],D=+t.cellIntensityBounds[1];else for(R=0;R<z.length;++R){F=z[R];I=Math.min(I,F),D=Math.max(D,F)}else for(R=0;R<n.length;++R){F=n[R][2];I=Math.min(I,F),D=Math.max(D,F)}this.intensity=P||(z||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n)),this.pickVertex=!(z||E);var B=t.pointSizes,N=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(R=0;R<n.length;++R)for(var j=n[R],V=0;V<3;++V)!isNaN(j[V])&&isFinite(j[V])&&(this.bounds[0][V]=Math.min(this.bounds[0][V],j[V]),this.bounds[1][V]=Math.max(this.bounds[1][V],j[V]));var U=0,q=0,H=0;t:for(R=0;R<r.length;++R){var G=r[R];switch(G.length){case 1:for(j=n[W=G[0]],V=0;V<3;++V)if(isNaN(j[V])||!isFinite(j[V]))continue t;m.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:L,this.opacityscale&&P?i.push(X[0],X[1],X[2],this.opacity*M((P[W]-I)/(D-I),this.opacityscale)):3===X.length?y.push(X[0],X[1],X[2],this.opacity):(y.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=C?C[W]:P?[(P[W]-I)/(D-I),0]:O?O[R]:z?[(z[R]-I)/(D-I),0]:[(j[2]-I)/(D-I),0],x.push(Z[0],Z[1]),B?b.push(B[W]):b.push(N),_.push(R),H+=1;break;case 2:for(V=0;V<2;++V){j=n[W=G[V]];for(var Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t}for(V=0;V<2;++V){j=n[W=G[V]];p.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:L,this.opacityscale&&P?i.push(X[0],X[1],X[2],this.opacity*M((P[W]-I)/(D-I),this.opacityscale)):3===X.length?d.push(X[0],X[1],X[2],this.opacity):(d.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=C?C[W]:P?[(P[W]-I)/(D-I),0]:O?O[R]:z?[(z[R]-I)/(D-I),0]:[(j[2]-I)/(D-I),0],g.push(Z[0],Z[1]),v.push(R)}q+=1;break;case 3:for(V=0;V<3;++V)for(j=n[W=G[V]],Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t;for(V=0;V<3;++V){var W,X,Z,J;j=n[W=G[2-V]];a.push(j[0],j[1],j[2]),(X=S?S[W]:E?E[R]:L)?this.opacityscale&&P?i.push(X[0],X[1],X[2],this.opacity*M((P[W]-I)/(D-I),this.opacityscale)):3===X.length?i.push(X[0],X[1],X[2],this.opacity):(i.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)):i.push(.5,.5,.5,1),Z=C?C[W]:P?[(P[W]-I)/(D-I),0]:O?O[R]:z?[(z[R]-I)/(D-I),0]:[(j[2]-I)/(D-I),0],c.push(Z[0],Z[1]),J=w?w[W]:k[R],l.push(J[0],J[1],J[2]),f.push(R)}U+=1}}this.pointCount=H,this.edgeCount=q,this.triangleCount=U,this.pointPositions.update(m),this.pointColors.update(y),this.pointUVs.update(x),this.pointSizes.update(b),this.pointIds.update(new Uint32Array(_)),this.edgePositions.update(p),this.edgeColors.update(d),this.edgeUVs.update(g),this.edgeIds.update(new Uint32Array(v)),this.trianglePositions.update(a),this.triangleColors.update(i),this.triangleUVs.update(c),this.triangleNormals.update(l),this.triangleIds.update(new Uint32Array(f))}},T.drawTransparent=T.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,a=t.projection||w,i=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)i[0][o]=Math.max(i[0][o],this.clipBounds[0][o]),i[1][o]=Math.min(i[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:a,inverseModel:w.slice(),clipBounds:i,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],contourColor:this.contourColor,texture:0};s.inverseModel=c(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);l(u,s.view,s.model),l(u,s.projection,u),c(u,u);for(o=0;o<3;++o)s.eyePosition[o]=u[12+o]/u[15];var h,f=u[15];for(o=0;o<3;++o)f+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];s.lightPosition[o]=p/f}this.triangleCount>0&&((h=this.triShader).bind(),h.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind());this.edgeCount>0&&this.lineWidth>0&&((h=this.lineShader).bind(),h.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind());this.pointCount>0&&((h=this.pointShader).bind(),h.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind());this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((h=this.contourShader).bind(),h.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},T.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,a=t.projection||w,i=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)i[0][o]=Math.max(i[0][o],this.clipBounds[0][o]),i[1][o]=Math.min(i[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(a),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:a,clipBounds:i,pickId:this.pickId/255};((s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0)&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},T.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,a=new Array(r.length),i=0;i<r.length;++i)a[i]=n[r[i]];var o=t.coord[0],s=t.coord[1];if(!this.pickVertex){var l=this.positions[r[0]],c=this.positions[r[1]],u=this.positions[r[2]],h=[(l[0]+c[0]+u[0])/3,(l[1]+c[1]+u[1])/3,(l[2]+c[2]+u[2])/3];return{_cellCenter:!0,position:[o,s],index:e,cell:r,cellId:e,intensity:this.intensity[e],dataCoordinate:h}}var f=g(a,[o*this.pixelRatio,this._resolution[1]-s*this.pixelRatio],this._model,this._view,this._projection,this._resolution);if(!f)return null;var p=f[2],d=0;for(i=0;i<r.length;++i)d+=p[i]*this.intensity[r[i]];return{position:f[1],index:r[f[0]],cell:r,cellId:e,intensity:d,dataCoordinate:this.positions[r[f[0]]]}},T.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=function(t,e){if(1===arguments.length&&(t=(e=t).gl),!(t.getExtension(\"OES_standard_derivatives\")||t.getExtension(\"MOZ_OES_standard_derivatives\")||t.getExtension(\"WEBKIT_OES_standard_derivatives\")))throw new Error(\"derivatives not supported\");var r=function(t){var e=n(t,v.vertex,v.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}(t),s=function(t){var e=n(t,m.vertex,m.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}(t),l=A(t),c=S(t),h=E(t),f=L(t),p=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));p.generateMipmap(),p.minFilter=t.LINEAR_MIPMAP_LINEAR,p.magFilter=t.LINEAR;var d=a(t),g=a(t),y=a(t),x=a(t),b=a(t),_=i(t,[{buffer:d,type:t.FLOAT,size:3},{buffer:b,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:g,type:t.FLOAT,size:4},{buffer:y,type:t.FLOAT,size:2},{buffer:x,type:t.FLOAT,size:3}]),w=a(t),T=a(t),M=a(t),C=a(t),P=i(t,[{buffer:w,type:t.FLOAT,size:3},{buffer:C,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:T,type:t.FLOAT,size:4},{buffer:M,type:t.FLOAT,size:2}]),O=a(t),z=a(t),I=a(t),D=a(t),R=a(t),F=i(t,[{buffer:O,type:t.FLOAT,size:3},{buffer:R,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:z,type:t.FLOAT,size:4},{buffer:I,type:t.FLOAT,size:2},{buffer:D,type:t.FLOAT,size:1}]),B=a(t),N=new k(t,p,r,s,l,c,h,f,d,b,g,y,x,_,w,C,T,M,P,O,R,z,I,D,F,B,i(t,[{buffer:B,type:t.FLOAT,size:3}]));return N.update(e),N}},{\"./lib/closest-point\":281,\"./lib/shaders\":282,colormap:128,\"gl-buffer\":244,\"gl-mat4/invert\":268,\"gl-mat4/multiply\":270,\"gl-shader\":304,\"gl-texture2d\":324,\"gl-vao\":329,ndarray:452,normals:455,\"simplicial-complex-contour\":517,\"typedarray-pool\":544}],284:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[0,0,0,1,1,0,1,1]),s=a(e,i.boxVert,i.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),a=t(\"gl-shader\"),i=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawBox=(s=[0,0],l=[0,0],function(t,e,r,n,a){var i=this.plot,o=this.shader,c=i.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,o.uniforms.lo=s,o.uniforms.hi=l,o.uniforms.color=a,c.drawArrays(c.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":287,\"gl-buffer\":244,\"gl-shader\":304}],285:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),i=a(e,o.gridVert,o.gridFrag),l=a(e,o.tickVert,o.gridFrag);return new s(t,r,i,l)};var n=t(\"gl-buffer\"),a=t(\"gl-shader\"),i=t(\"binary-search-bounds\"),o=t(\"./shaders\");function s(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function l(t,e){return t-e}var c,u,h,f,p,d=s.prototype;d.draw=(c=[0,0],u=[0,0],h=[0,0],function(){for(var t=this.plot,e=this.vbo,r=this.shader,n=this.ticks,a=t.gl,i=t._tickBounds,o=t.dataBox,s=t.viewBox,l=t.gridLineWidth,f=t.gridLineColor,p=t.gridLineEnable,d=t.pixelRatio,g=0;g<2;++g){var v=i[g],m=i[g+2]-v,y=.5*(o[g+2]+o[g]),x=o[g+2]-o[g];u[g]=2*m/x,c[g]=2*(v-y)/x}r.bind(),e.bind(),r.attributes.dataCoord.pointer(),r.uniforms.dataShift=c,r.uniforms.dataScale=u;var b=0;for(g=0;g<2;++g){h[0]=h[1]=0,h[g]=1,r.uniforms.dataAxis=h,r.uniforms.lineWidth=l[g]/(s[g+2]-s[g])*d,r.uniforms.color=f[g];var _=6*n[g].length;p[g]&&_&&a.drawArrays(a.TRIANGLES,b,_),b+=_}}),d.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],a=[0,0],o=[0,0];return function(){for(var s=this.plot,c=this.vbo,u=this.tickShader,h=this.ticks,f=s.gl,p=s._tickBounds,d=s.dataBox,g=s.viewBox,v=s.pixelRatio,m=s.screenBox,y=m[2]-m[0],x=m[3]-m[1],b=g[2]-g[0],_=g[3]-g[1],w=0;w<2;++w){var k=p[w],T=p[w+2]-k,M=.5*(d[w+2]+d[w]),A=d[w+2]-d[w];e[w]=2*T/A,t[w]=2*(k-M)/A}e[0]*=b/y,t[0]*=b/y,e[1]*=_/x,t[1]*=_/x,u.bind(),c.bind(),u.attributes.dataCoord.pointer();var S=u.uniforms;S.dataShift=t,S.dataScale=e;var E=s.tickMarkLength,L=s.tickMarkWidth,C=s.tickMarkColor,P=6*h[0].length,O=Math.min(i.ge(h[0],(d[0]-p[0])/(p[2]-p[0]),l),h[0].length),z=Math.min(i.gt(h[0],(d[2]-p[0])/(p[2]-p[0]),l),h[0].length),I=0+6*O,D=6*Math.max(0,z-O),R=Math.min(i.ge(h[1],(d[1]-p[1])/(p[3]-p[1]),l),h[1].length),F=Math.min(i.gt(h[1],(d[3]-p[1])/(p[3]-p[1]),l),h[1].length),B=P+6*R,N=6*Math.max(0,F-R);a[0]=2*(g[0]-E[1])/y-1,a[1]=(g[3]+g[1])/x-1,o[0]=E[1]*v/y,o[1]=L[1]*v/x,N&&(S.color=C[1],S.tickScale=o,S.dataAxis=n,S.screenOffset=a,f.drawArrays(f.TRIANGLES,B,N)),a[0]=(g[2]+g[0])/y-1,a[1]=2*(g[1]-E[0])/x-1,o[0]=L[0]*v/y,o[1]=E[0]*v/x,D&&(S.color=C[0],S.tickScale=o,S.dataAxis=r,S.screenOffset=a,f.drawArrays(f.TRIANGLES,I,D)),a[0]=2*(g[2]+E[3])/y-1,a[1]=(g[3]+g[1])/x-1,o[0]=E[3]*v/y,o[1]=L[3]*v/x,N&&(S.color=C[3],S.tickScale=o,S.dataAxis=n,S.screenOffset=a,f.drawArrays(f.TRIANGLES,B,N)),a[0]=(g[2]+g[0])/y-1,a[1]=2*(g[3]+E[2])/x-1,o[0]=L[2]*v/y,o[1]=E[2]*v/x,D&&(S.color=C[2],S.tickScale=o,S.dataAxis=r,S.screenOffset=a,f.drawArrays(f.TRIANGLES,I,D))}}(),d.update=(f=[1,1,-1,-1,1,-1],p=[1,-1,1,1,-1,-1],function(t){for(var e=t.ticks,r=t.bounds,n=new Float32Array(18*(e[0].length+e[1].length)),a=(this.plot.zeroLineEnable,0),i=[[],[]],o=0;o<2;++o)for(var s=i[o],l=e[o],c=r[o],u=r[o+2],h=0;h<l.length;++h){var d=(l[h].x-c)/(u-c);s.push(d);for(var g=0;g<6;++g)n[a++]=d,n[a++]=f[g],n[a++]=p[g]}this.ticks=i,this.vbo.update(n)}),d.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},{\"./shaders\":287,\"binary-search-bounds\":289,\"gl-buffer\":244,\"gl-shader\":304}],286:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[-1,-1,-1,1,1,-1,1,1]),s=a(e,i.lineVert,i.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),a=t(\"gl-shader\"),i=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawLine=(s=[0,0],l=[0,0],function(t,e,r,n,a,i){var o=this.plot,c=this.shader,u=o.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,c.uniforms.start=s,c.uniforms.end=l,c.uniforms.width=a*o.pixelRatio,c.uniforms.color=i,u.drawArrays(u.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":287,\"gl-buffer\":244,\"gl-shader\":304}],287:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),a=n([\"precision lowp float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = vec4(color.xyz * color.w, color.w);\\n}\\n\"]);e.exports={lineVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 start, end;\\nuniform float width;\\n\\nvec2 perp(vec2 v) {\\n  return vec2(v.y, -v.x);\\n}\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  vec2 delta = normalize(perp(start - end));\\n  vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\\n  gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\\n}\\n\"]),lineFrag:a,textVert:n([\"#define GLSLIFY 1\\nattribute vec3 textCoordinate;\\n\\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\\nuniform float angle;\\n\\nvoid main() {\\n  float dataOffset  = textCoordinate.z;\\n  vec2 glyphOffset  = textCoordinate.xy;\\n  mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\\n  vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\\n    glyphMatrix * glyphOffset * textScale + screenOffset;\\n  gl_Position = vec4(screenCoordinate, 0, 1);\\n}\\n\"]),textFrag:a,gridVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale;\\nuniform float lineWidth;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\\n  gl_Position = vec4(pos, 0, 1);\\n}\\n\"]),gridFrag:a,boxVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 lo, hi;\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\\n}\\n\"]),tickVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\\n}\\n\"])}},{glslify:411}],288:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),i=a(e,s.textVert,s.textFrag);return new l(t,r,i)};var n=t(\"gl-buffer\"),a=t(\"gl-shader\"),i=t(\"text-cache\"),o=t(\"binary-search-bounds\"),s=t(\"./shaders\");function l(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}var c,u,h,f,p,d,g=l.prototype;g.drawTicks=(c=[0,0],u=[0,0],h=[0,0],function(t){var e=this.plot,r=this.shader,n=this.tickX[t],a=this.tickOffset[t],i=e.gl,s=e.viewBox,l=e.dataBox,f=e.screenBox,p=e.pixelRatio,d=e.tickEnable,g=e.tickPad,v=e.tickColor,m=e.tickAngle,y=e.labelEnable,x=e.labelPad,b=e.labelColor,_=e.labelAngle,w=this.labelOffset[t],k=this.labelCount[t],T=o.lt(n,l[t]),M=o.le(n,l[t+2]);c[0]=c[1]=0,c[t]=1,u[t]=(s[2+t]+s[t])/(f[2+t]-f[t])-1;var A=2/f[2+(1^t)]-f[1^t];u[1^t]=A*s[1^t]-1,d[t]&&(u[1^t]-=A*p*g[t],T<M&&a[M]>a[T]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=v[t],r.uniforms.angle=m[t],i.drawArrays(i.TRIANGLES,a[T],a[M]-a[T]))),y[t]&&k&&(u[1^t]-=A*p*x[t],r.uniforms.dataAxis=h,r.uniforms.screenOffset=u,r.uniforms.color=b[t],r.uniforms.angle=_[t],i.drawArrays(i.TRIANGLES,w,k)),u[1^t]=A*s[2+(1^t)]-1,d[t+2]&&(u[1^t]+=A*p*g[t+2],T<M&&a[M]>a[T]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=v[t+2],r.uniforms.angle=m[t+2],i.drawArrays(i.TRIANGLES,a[T],a[M]-a[T]))),y[t+2]&&k&&(u[1^t]+=A*p*x[t+2],r.uniforms.dataAxis=h,r.uniforms.screenOffset=u,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],i.drawArrays(i.TRIANGLES,w,k))}),g.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,a=r.gl,i=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,c=r.pixelRatio;if(this.titleCount){for(var u=0;u<2;++u)e[u]=2*(o[u]*c-i[u])/(i[2+u]-i[u])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,a.drawArrays(a.TRIANGLES,this.titleOffset,this.titleCount)}}}(),g.bind=(f=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,a=t.screenBox,i=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,c=.5*(n[o+2]+n[o]),u=n[o+2]-n[o],h=i[o],g=i[o+2]-h,v=a[o],m=a[o+2]-v;p[o]=2*l/u*g/m,f[o]=2*(s-c)/u*g/m}d[1]=2*t.pixelRatio/(a[3]-a[1]),d[0]=d[1]*(a[3]-a[1])/(a[2]-a[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=f,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),g.update=function(t){var e,r,n,a,o,s=[],l=t.ticks,c=t.bounds;for(o=0;o<2;++o){var u=[Math.floor(s.length/3)],h=[-1/0],f=l[o];for(e=0;e<f.length;++e){var p=f[e],d=p.x,g=p.text,v=p.font||\"sans-serif\";a=p.fontSize||12;for(var m=1/(c[o+2]-c[o]),y=c[o],x=g.split(\"\\n\"),b=0;b<x.length;b++)for(n=i(v,x[b]).data,r=0;r<n.length;r+=2)s.push(n[r]*a,-n[r+1]*a-b*a*1.2,(d-y)*m);u.push(Math.floor(s.length/3)),h.push(d)}this.tickOffset[o]=u,this.tickX[o]=h}for(o=0;o<2;++o){for(this.labelOffset[o]=Math.floor(s.length/3),n=i(t.labelFont[o],t.labels[o],{textAlign:\"center\"}).data,a=t.labelSize[o],e=0;e<n.length;e+=2)s.push(n[e]*a,-n[e+1]*a,0);this.labelCount[o]=Math.floor(s.length/3)-this.labelOffset[o]}for(this.titleOffset=Math.floor(s.length/3),n=i(t.titleFont,t.title).data,a=t.titleSize,e=0;e<n.length;e+=2)s.push(n[e]*a,-n[e+1]*a,0);this.titleCount=Math.floor(s.length/3)-this.titleOffset,this.vbo.update(s)},g.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":287,\"binary-search-bounds\":289,\"gl-buffer\":244,\"gl-shader\":304,\"text-cache\":535}],289:[function(t,e,r){arguments[4][113][0].apply(r,arguments)},{dup:113}],290:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[e.drawingBufferWidth,e.drawingBufferHeight]),c=new l(e,r);return c.grid=a(c),c.text=i(c),c.line=o(c),c.box=s(c),c.update(t),c};var n=t(\"gl-select-static\"),a=t(\"./lib/grid\"),i=t(\"./lib/text\"),o=t(\"./lib/line\"),s=t(\"./lib/box\");function l(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-1/0,-1/0],this.static=!1,this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}var c=l.prototype;function u(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function h(t,e){return t.x-e.x}c.setDirty=function(){this.dirty=this.pickDirty=!0},c.setOverlayDirty=function(){this.dirty=!0},c.nextDepthValue=function(){return this._depthCounter++/65536},c.draw=function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,a=this.pixelRatio,i=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){if(this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),this.borderColor){t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var c=this.borderColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT)}t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var u=this.backgroundColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT),i.draw();var h=this.zeroLineEnable,f=this.zeroLineColor,p=this.zeroLineWidth;if(h[0]||h[1]){o.bind();for(var d=0;d<2;++d)if(h[d]&&n[d]<=0&&n[d+2]>=0){var g=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(g,e[1],g,e[3],p[d],f[d]):o.drawLine(e[0],g,e[2],g,p[d],f[d])}}for(d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var v=this.borderLineEnable,m=this.borderLineWidth,y=this.borderLineColor;for(v[1]&&o.drawLine(r[0],r[1]-.5*m[1]*a,r[0],r[3]+.5*m[3]*a,m[1],y[1]),v[0]&&o.drawLine(r[0]-.5*m[0]*a,r[1],r[2]+.5*m[2]*a,r[1],m[0],y[0]),v[3]&&o.drawLine(r[2],r[1]-.5*m[1]*a,r[2],r[3]+.5*m[3]*a,m[3],y[3]),v[2]&&o.drawLine(r[0]-.5*m[0]*a,r[3],r[2]+.5*m[2]*a,r[3],m[2],y[2]),s.bind(),d=0;d<2;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();var x=this.overlays;for(d=0;d<x.length;++d)x[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}},c.drawPick=function(){if(!this.static){var t=this.pickBuffer;this.gl,this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}},c.pick=function(t,e){if(!this.static){var r=this.pixelRatio,n=this.pickPixelRatio,a=this.viewBox,i=0|Math.round((t-a[0]/r)*n),o=0|Math.round((e-a[1]/r)*n),s=this.pickBuffer.query(i,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),c=this.objects,u=0;u<c.length;++u){var h=c[u].pick(i,o,l);if(h)return h}return null}},c.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},c.setDataBox=function(t){var e=this.dataBox;(e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3])&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},c.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},c.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,a=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/a,10,10/a]),this.borderColor=!1!==t.borderColor&&(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=u(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=u(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=u(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t&&!t.titleEnable),this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=u(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=u(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=u(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var i=t.ticks||[[],[]],o=this._tickBounds;o[0]=o[1]=1/0,o[2]=o[3]=-1/0;for(var s=0;s<2;++s){var l=i[s].slice(0);0!==l.length&&(l.sort(h),o[s]=Math.min(o[s],l[0].x),o[s+2]=Math.max(o[s+2],l[l.length-1].x))}this.grid.update({bounds:o,ticks:i}),this.text.update({bounds:o,ticks:i,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.static=!!t.static,this.setDirty()},c.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},c.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},c.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},c.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},c.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{\"./lib/box\":284,\"./lib/grid\":285,\"./lib/line\":286,\"./lib/text\":288,\"gl-select-static\":303}],291:[function(t,e,r){\"use strict\";e.exports=function(t,e){t=t||document.body,e=e||{};var r=[.01,1/0];\"distanceLimits\"in e&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]);\"zoomMin\"in e&&(r[0]=e.zoomMin);\"zoomMax\"in e&&(r[1]=e.zoomMax);var c=a({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),u=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],h=0,f=t.clientWidth,p=t.clientHeight,d={keyBindingMode:\"rotate\",enableWheel:!0,view:c,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:c.modes,_ortho:e._ortho||e.projection&&\"orthographic\"===e.projection.type||!1,tick:function(){var e=n(),r=this.delay,a=e-2*r;c.idle(e-r),c.recalcMatrix(a),c.flush(e-(100+2*r));for(var i=!0,o=c.computedMatrix,s=0;s<16;++s)i=i&&u[s]===o[s],u[s]=o[s];var l=t.clientWidth===f&&t.clientHeight===p;return f=t.clientWidth,p=t.clientHeight,i?!l:(h=Math.exp(c.computedRadius[0]),!0)},lookAt:function(t,e,r){c.lookAt(c.lastT(),t,e,r)},rotate:function(t,e,r){c.rotate(c.lastT(),t,e,r)},pan:function(t,e,r){c.pan(c.lastT(),t,e,r)},translate:function(t,e,r){c.translate(c.lastT(),t,e,r)}};return Object.defineProperties(d,{matrix:{get:function(){return c.computedMatrix},set:function(t){return c.setMatrix(c.lastT(),t),c.computedMatrix},enumerable:!0},mode:{get:function(){return c.getMode()},set:function(t){var e=c.computedUp.slice(),r=c.computedEye.slice(),a=c.computedCenter.slice();if(c.setMode(t),\"turntable\"===t){var i=n();c._active.lookAt(i,r,a,e),c._active.lookAt(i+500,r,a,[0,0,1]),c._active.flush(i)}return c.getMode()},enumerable:!0},center:{get:function(){return c.computedCenter},set:function(t){return c.lookAt(c.lastT(),null,t),c.computedCenter},enumerable:!0},eye:{get:function(){return c.computedEye},set:function(t){return c.lookAt(c.lastT(),t),c.computedEye},enumerable:!0},up:{get:function(){return c.computedUp},set:function(t){return c.lookAt(c.lastT(),null,null,t),c.computedUp},enumerable:!0},distance:{get:function(){return h},set:function(t){return c.setDistance(c.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return c.getDistanceLimits(r)},set:function(t){return c.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener(\"contextmenu\",function(t){return t.preventDefault(),!1}),d._lastX=-1,d._lastY=-1,d._lastMods={shift:!1,control:!1,alt:!1,meta:!1},d.enableMouseListeners=function(){function e(e,r,a,i){var o=d.keyBindingMode;if(!1!==o){var s=\"rotate\"===o,l=\"pan\"===o,u=\"zoom\"===o,f=!!i.control,p=!!i.alt,g=!!i.shift,v=!!(1&e),m=!!(2&e),y=!!(4&e),x=1/t.clientHeight,b=x*(r-d._lastX),_=x*(a-d._lastY),w=d.flipX?1:-1,k=d.flipY?1:-1,T=Math.PI*d.rotateSpeed,M=n();if(-1!==d._lastX&&-1!==d._lastY&&((s&&v&&!f&&!p&&!g||v&&!f&&!p&&g)&&c.rotate(M,w*T*b,-k*T*_,0),(l&&v&&!f&&!p&&!g||m||v&&f&&!p&&!g)&&c.pan(M,-d.translateSpeed*b*h,d.translateSpeed*_*h,0),u&&v&&!f&&!p&&!g||y||v&&!f&&p&&!g)){var A=-d.zoomSpeed*_/window.innerHeight*(M-c.lastT())*100;c.pan(M,0,0,h*(Math.exp(A)-1))}return d._lastX=r,d._lastY=a,d._lastMods=i,!0}}d.mouseListener=i(t,e),t.addEventListener(\"touchstart\",function(r){var n=s(r.changedTouches[0],t);e(0,n[0],n[1],d._lastMods),e(1,n[0],n[1],d._lastMods),r.preventDefault()},!!l&&{passive:!1}),t.addEventListener(\"touchmove\",function(r){var n=s(r.changedTouches[0],t);e(1,n[0],n[1],d._lastMods),r.preventDefault()},!!l&&{passive:!1}),t.addEventListener(\"touchend\",function(t){e(0,d._lastX,d._lastY,d._lastMods),t.preventDefault()},!!l&&{passive:!1}),d.wheelListener=o(t,function(t,e){if(!1!==d.keyBindingMode&&d.enableWheel){var r=d.flipX?1:-1,a=d.flipY?1:-1,i=n();if(Math.abs(t)>Math.abs(e))c.rotate(i,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*a*e/window.innerHeight*(i-c.lastT())/20;c.pan(i,0,0,h*(Math.exp(o)-1))}}},!0)},d.enableMouseListeners(),d};var n=t(\"right-now\"),a=t(\"3d-view\"),i=t(\"mouse-change\"),o=t(\"mouse-wheel\"),s=t(\"mouse-event-offset\"),l=t(\"has-passive-events\")},{\"3d-view\":54,\"has-passive-events\":413,\"mouse-change\":437,\"mouse-event-offset\":438,\"mouse-wheel\":440,\"right-now\":503}],292:[function(t,e,r){var n=t(\"glslify\"),a=t(\"gl-shader\"),i=n([\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n  uv = position;\\n  gl_Position = vec4(position, 0, 1);\\n}\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n  vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n  gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\"]);e.exports=function(t){return a(t,i,o,null,[{name:\"position\",type:\"vec2\"}])}},{\"gl-shader\":304,glslify:411}],293:[function(t,e,r){\"use strict\";var n=t(\"./camera.js\"),a=t(\"gl-axes3d\"),i=t(\"gl-axes3d/properties\"),o=t(\"gl-spikes3d\"),s=t(\"gl-select-static\"),l=t(\"gl-fbo\"),c=t(\"a-big-triangle\"),u=t(\"mouse-change\"),h=t(\"gl-mat4/perspective\"),f=t(\"gl-mat4/ortho\"),p=t(\"./lib/shader\"),d=t(\"is-mobile\")({tablet:!0});function g(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function v(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}if(e>0){r=Math.round(Math.pow(10,e));return Math.ceil(t/r)*r}return Math.ceil(t)}function m(t){return\"boolean\"!=typeof t||t}e.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;if(!e)if(e=document.createElement(\"canvas\"),t.container){var r=t.container;r.appendChild(e)}else document.body.appendChild(e);var y=t.gl;y||(t.glOptions&&(d=!!t.glOptions.preserveDrawingBuffer),y=function(t,e){var r=null;try{(r=t.getContext(\"webgl\",e))||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:d}));if(!y)throw new Error(\"webgl not supported\");var x=t.bounds||[[-10,-10,-10],[10,10,10]],b=new g,_=l(y,y.drawingBufferWidth,y.drawingBufferHeight,{preferFloat:!d}),w=p(y),k=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&\"orthographic\"===t.camera.projection.type||!1,T={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||\"turntable\",_ortho:k},M=t.axes||{},A=a(y,M);A.enable=!M.disable;var S=t.spikes||{},E=o(y,S),L=[],C=[],P=[],O=[],z=!0,I=!0,D=new Array(16),R=new Array(16),F={view:null,projection:D,model:R,_ortho:!1},I=!0,B=[y.drawingBufferWidth,y.drawingBufferHeight],N=t.cameraObject||n(e,T),j={gl:y,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:b,camera:N,axes:A,axesPixels:null,spikes:E,bounds:x,objects:L,shape:B,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:m(t.autoResize),autoBounds:m(t.autoBounds),autoScale:!!t.autoScale,autoCenter:m(t.autoCenter),clipToBounds:m(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:F,oncontextloss:null,mouseListener:null,_stopped:!1,getAspectratio:function(){return{x:this.aspect[0],y:this.aspect[1],z:this.aspect[2]}},setAspectratio:function(t){this.aspect[0]=t.x,this.aspect[1]=t.y,this.aspect[2]=t.z},setBounds:function(t,e){this.bounds[0][t]=e.min,this.bounds[1][t]=e.max},setClearColor:function(t){this.clearColor=t},clearRGBA:function(){this.gl.clearColor(this.clearColor[0],this.clearColor[1],this.clearColor[2],this.clearColor[3]),this.gl.clear(this.gl.COLOR_BUFFER_BIT|this.gl.DEPTH_BUFFER_BIT)}},V=[y.drawingBufferWidth/j.pixelRatio|0,y.drawingBufferHeight/j.pixelRatio|0];function U(){if(!j._stopped&&j.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var a=0|Math.ceil(r*j.pixelRatio),i=0|Math.ceil(n*j.pixelRatio);if(a!==e.width||i!==e.height){e.width=a,e.height=i;var o=e.style;o.position=o.position||\"absolute\",o.left=\"0px\",o.top=\"0px\",o.width=r+\"px\",o.height=n+\"px\",z=!0}}}j.autoResize&&U();function q(){for(var t=L.length,e=O.length,r=0;r<e;++r)P[r]=0;t:for(var r=0;r<t;++r){var n=L[r],a=n.pickSlots;if(a){for(var i=0;i<e;++i)if(P[i]+a<255){C[r]=i,n.setPickBase(P[i]+1),P[i]+=a;continue t}var o=s(y,B);C[r]=e,O.push(o),P.push(a),n.setPickBase(1),e+=1}else C[r]=-1}for(;e>0&&0===P[e-1];)P.pop(),O.pop().dispose()}function H(){if(j.contextLost)return!0;y.isContextLost()&&(j.contextLost=!0,j.mouseListener.enabled=!1,j.selection.object=null,j.oncontextloss&&j.oncontextloss())}window.addEventListener(\"resize\",U),j.update=function(t){j._stopped||(t=t||{},z=!0,I=!0)},j.add=function(t){j._stopped||(t.axes=A,L.push(t),C.push(-1),z=!0,I=!0,q())},j.remove=function(t){if(!j._stopped){var e=L.indexOf(t);e<0||(L.splice(e,1),C.pop(),z=!0,I=!0,q())}},j.dispose=function(){if(!j._stopped&&(j._stopped=!0,window.removeEventListener(\"resize\",U),e.removeEventListener(\"webglcontextlost\",H),j.mouseListener.enabled=!1,!j.contextLost)){A.dispose(),E.dispose();for(var t=0;t<L.length;++t)L[t].dispose();_.dispose();for(var t=0;t<O.length;++t)O[t].dispose();w.dispose(),y=null,A=null,E=null,L=[]}},j._mouseRotating=!1,j._prevButtons=0,j.enableMouseListeners=function(){j.mouseListener=u(e,function(t,e,r){if(!j._stopped){var n=O.length,a=L.length,i=b.object;b.distance=1/0,b.mouse[0]=e,b.mouse[1]=r,b.object=null,b.screen=null,b.dataCoordinate=b.dataPosition=null;var o=!1;if(t&&j._prevButtons)j._mouseRotating=!0;else{j._mouseRotating&&(I=!0),j._mouseRotating=!1;for(var s=0;s<n;++s){var l=O[s].query(e,V[1]-r-1,j.pickRadius);if(l){if(l.distance>b.distance)continue;for(var c=0;c<a;++c){var u=L[c];if(C[c]===s){var h=u.pick(l);h&&(b.buttons=t,b.screen=l.coord,b.distance=l.distance,b.object=u,b.index=h.distance,b.dataPosition=h.position,b.dataCoordinate=h.dataCoordinate,b.data=h,o=!0)}}}}}i&&i!==b.object&&(i.highlight&&i.highlight(null),z=!0),b.object&&(b.object.highlight&&b.object.highlight(b.data),z=!0),(o=o||b.object!==i)&&j.onselect&&j.onselect(b),1&t&&!(1&j._prevButtons)&&j.onclick&&j.onclick(b),j._prevButtons=t}})},e.addEventListener(\"webglcontextlost\",H);var G=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],Y=[G[0].slice(),G[1].slice()];function W(){if(!H()){U();var t=j.camera.tick();F.view=j.camera.matrix,z=z||t,I=I||t,A.pixelRatio=j.pixelRatio,E.pixelRatio=j.pixelRatio;var e=L.length,r=G[0],n=G[1];r[0]=r[1]=r[2]=1/0,n[0]=n[1]=n[2]=-1/0;for(var a=0;a<e;++a){var o=L[a];o.pixelRatio=j.pixelRatio,o.axes=j.axes,z=z||!!o.dirty,I=I||!!o.dirty;var s=o.bounds;if(s)for(var l=s[0],u=s[1],p=0;p<3;++p)r[p]=Math.min(r[p],l[p]),n[p]=Math.max(n[p],u[p])}var d=j.bounds;if(j.autoBounds)for(var p=0;p<3;++p){if(n[p]<r[p])r[p]=-1,n[p]=1;else{r[p]===n[p]&&(r[p]-=1,n[p]+=1);var g=.05*(n[p]-r[p]);r[p]=r[p]-g,n[p]=n[p]+g}d[0][p]=r[p],d[1][p]=n[p]}for(var m=!1,p=0;p<3;++p)m=m||Y[0][p]!==d[0][p]||Y[1][p]!==d[1][p],Y[0][p]=d[0][p],Y[1][p]=d[1][p];if(I=I||m,z=z||m){if(m){for(var x=[0,0,0],a=0;a<3;++a)x[a]=v((d[1][a]-d[0][a])/10);A.autoTicks?A.update({bounds:d,tickSpacing:x}):A.update({bounds:d})}var T=y.drawingBufferWidth,M=y.drawingBufferHeight;B[0]=T,B[1]=M,V[0]=0|Math.max(T/j.pixelRatio,1),V[1]=0|Math.max(M/j.pixelRatio,1),function(t,e){var r=t.bounds,n=t.cameraParams,a=n.projection,i=n.model,o=t.gl.drawingBufferWidth,s=t.gl.drawingBufferHeight,l=t.zNear,c=t.zFar,u=t.fovy,p=o/s;e?(f(a,-p,p,-1,1,l,c),n._ortho=!0):(h(a,u,p,l,c),n._ortho=!1);for(var d=0;d<16;++d)i[d]=0;i[15]=1;for(var g=0,d=0;d<3;++d)g=Math.max(g,r[1][d]-r[0][d]);for(var d=0;d<3;++d)t.autoScale?i[5*d]=t.aspect[d]/(r[1][d]-r[0][d]):i[5*d]=1/g,t.autoCenter&&(i[12+d]=.5*-i[5*d]*(r[0][d]+r[1][d]))}(j,k);for(var a=0;a<e;++a){var o=L[a];o.axesBounds=d,j.clipToBounds&&(o.clipBounds=d)}b.object&&(j.snapToData?E.position=b.dataCoordinate:E.position=b.dataPosition,E.bounds=d),I&&(I=!1,function(){if(H())return;y.colorMask(!0,!0,!0,!0),y.depthMask(!0),y.disable(y.BLEND),y.enable(y.DEPTH_TEST),y.depthFunc(y.LEQUAL);for(var t=L.length,e=O.length,r=0;r<e;++r){var n=O[r];n.shape=V,n.begin();for(var a=0;a<t;++a)if(C[a]===r){var i=L[a];i.drawPick&&(i.pixelRatio=1,i.drawPick(F))}n.end()}}()),j.axesPixels=i(j.axes,F,T,M),j.onrender&&j.onrender(),y.bindFramebuffer(y.FRAMEBUFFER,null),y.viewport(0,0,T,M),j.clearRGBA(),y.depthMask(!0),y.colorMask(!0,!0,!0,!0),y.enable(y.DEPTH_TEST),y.depthFunc(y.LEQUAL),y.disable(y.BLEND),y.disable(y.CULL_FACE);var S=!1;A.enable&&(S=S||A.isTransparent(),A.draw(F)),E.axes=A,b.object&&E.draw(F),y.disable(y.CULL_FACE);for(var a=0;a<e;++a){var o=L[a];o.axes=A,o.pixelRatio=j.pixelRatio,o.isOpaque&&o.isOpaque()&&o.draw(F),o.isTransparent&&o.isTransparent()&&(S=!0)}if(S){_.shape=B,_.bind(),y.clear(y.DEPTH_BUFFER_BIT),y.colorMask(!1,!1,!1,!1),y.depthMask(!0),y.depthFunc(y.LESS),A.enable&&A.isTransparent()&&A.drawTransparent(F);for(var a=0;a<e;++a){var o=L[a];o.isOpaque&&o.isOpaque()&&o.draw(F)}y.enable(y.BLEND),y.blendEquation(y.FUNC_ADD),y.blendFunc(y.ONE,y.ONE_MINUS_SRC_ALPHA),y.colorMask(!0,!0,!0,!0),y.depthMask(!1),y.clearColor(0,0,0,0),y.clear(y.COLOR_BUFFER_BIT),A.isTransparent()&&A.drawTransparent(F);for(var a=0;a<e;++a){var o=L[a];o.isTransparent&&o.isTransparent()&&o.drawTransparent(F)}y.bindFramebuffer(y.FRAMEBUFFER,null),y.blendFunc(y.ONE,y.ONE_MINUS_SRC_ALPHA),y.disable(y.DEPTH_TEST),w.bind(),_.color[0].bind(0),w.uniforms.accumBuffer=0,c(y),y.disable(y.BLEND)}z=!1;for(var a=0;a<e;++a)L[a].dirty=!1}}}return j.enableMouseListeners(),function t(){j._stopped||j.contextLost||(W(),requestAnimationFrame(t))}(),j.redraw=function(){j._stopped||(z=!0,W())},j},createCamera:n}},{\"./camera.js\":291,\"./lib/shader\":292,\"a-big-triangle\":62,\"gl-axes3d\":236,\"gl-axes3d/properties\":243,\"gl-fbo\":252,\"gl-mat4/ortho\":271,\"gl-mat4/perspective\":272,\"gl-select-static\":303,\"gl-spikes3d\":313,\"is-mobile\":422,\"mouse-change\":437}],294:[function(t,e,r){var n=t(\"glslify\");r.pointVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform float pointCloud;\\n\\nhighp float rand(vec2 co) {\\n  highp float a = 12.9898;\\n  highp float b = 78.233;\\n  highp float c = 43758.5453;\\n  highp float d = dot(co.xy, vec2(a, b));\\n  highp float e = mod(d, 3.14);\\n  return fract(sin(e) * c);\\n}\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n    // if we don't jitter the point size a bit, overall point cloud\\n    // saturation 'jumps' on zooming, which is disturbing and confusing\\n  gl_PointSize = pointSize * ((19.5 + rand(position)) / 20.0);\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    // get the same square surface as circle would be\\n    gl_PointSize *= 0.886;\\n  }\\n}\"]),r.pointFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\nuniform float pointCloud;\\n\\nvoid main() {\\n  float radius;\\n  vec4 baseColor;\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    if(centerFraction == 1.0) {\\n      gl_FragColor = color;\\n    } else {\\n      gl_FragColor = mix(borderColor, color, centerFraction);\\n    }\\n  } else {\\n    radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n    if(radius > 1.0) {\\n      discard;\\n    }\\n    baseColor = mix(borderColor, color, step(radius, centerFraction));\\n    gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n  }\\n}\\n\"]),r.pickVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  fragId = id;\\n}\\n\"]),r.pickFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\\n\"])},{glslify:411}],295:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),a=t(\"gl-buffer\"),i=t(\"typedarray-pool\"),o=t(\"./lib/shader\");function s(t,e,r,n,a){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=a,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}e.exports=function(t,e){var r=t.gl,i=a(r),l=a(r),c=n(r,o.pointVertex,o.pointFragment),u=n(r,o.pickVertex,o.pickFragment),h=new s(t,i,l,c,u);return h.update(e),t.addObject(h),h};var l,c,u=s.prototype;u.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},u.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r(\"sizeMin\",.5),this.sizeMax=r(\"sizeMax\",20),this.color=r(\"color\",[1,0,0,1]).slice(),this.areaRatio=r(\"areaRatio\",1),this.borderColor=r(\"borderColor\",[0,0,0,1]).slice(),this.blend=r(\"blend\",!1);var n=t.positions.length>>>1,a=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=a?s:i.mallocFloat32(s.length),c=o?t.idToIndex:i.mallocInt32(n);if(a||l.set(s),!o)for(l.set(s),e=0;e<n;e++)c[e]=e;this.points=s,this.offsetBuffer.update(l),this.pickBuffer.update(c),a||i.free(l),o||i.free(c),this.pointCount=n,this.pickOffset=0},u.unifiedDraw=(l=[1,0,0,0,1,0,0,0,1],c=[0,0,0,0],function(t){var e=void 0!==t,r=e?this.pickShader:this.shader,n=this.plot.gl,a=this.plot.dataBox;if(0===this.pointCount)return t;var i=a[2]-a[0],o=a[3]-a[1],s=function(t,e){var r,n=0,a=t.length>>>1;for(r=0;r<a;r++){var i=t[2*r],o=t[2*r+1];i>=e[0]&&i<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,a),u=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/i,l[4]=2/o,l[6]=-2*a[0]/i-1,l[7]=-2*a[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=u<5,r.uniforms.pointSize=u,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(c[0]=255&t,c[1]=t>>8&255,c[2]=t>>16&255,c[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=c,this.pickOffset=t);var h=n.getParameter(n.BLEND),f=n.getParameter(n.DITHER);return h&&!this.blend&&n.disable(n.BLEND),f&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),h&&!this.blend&&n.enable(n.BLEND),f&&n.enable(n.DITHER),t+this.pointCount}),u.draw=u.unifiedDraw,u.drawPick=u.unifiedDraw,u.pick=function(t,e,r){var n=this.pickOffset,a=this.pointCount;if(r<n||r>=n+a)return null;var i=r-n,o=this.points;return{object:this,pointId:i,dataCoord:[o[2*i],o[2*i+1]]}}},{\"./lib/shader\":294,\"gl-buffer\":244,\"gl-shader\":304,\"typedarray-pool\":544}],296:[function(t,e,r){e.exports=function(t,e,r,n){var a,i,o,s,l,c=e[0],u=e[1],h=e[2],f=e[3],p=r[0],d=r[1],g=r[2],v=r[3];(i=c*p+u*d+h*g+f*v)<0&&(i=-i,p=-p,d=-d,g=-g,v=-v);1-i>1e-6?(a=Math.acos(i),o=Math.sin(a),s=Math.sin((1-n)*a)/o,l=Math.sin(n*a)/o):(s=1-n,l=n);return t[0]=s*c+l*p,t[1]=s*u+l*d,t[2]=s*h+l*g,t[3]=s*f+l*v,t}},{}],297:[function(t,e,r){\"use strict\";e.exports=function(t){return t||0===t?t.toString():\"\"}},{}],298:[function(t,e,r){\"use strict\";var n=t(\"vectorize-text\");e.exports=function(t,e,r){var i=a[e];i||(i=a[e]={});if(t in i)return i[t];var o={textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},s=n(t,o);o.triangles=!1;var l,c,u=n(t,o);if(r&&1!==r){for(l=0;l<s.positions.length;++l)for(c=0;c<s.positions[l].length;++c)s.positions[l][c]/=r;for(l=0;l<u.positions.length;++l)for(c=0;c<u.positions[l].length;++c)u.positions[l][c]/=r}var h=[[1/0,1/0],[-1/0,-1/0]],f=u.positions.length;for(l=0;l<f;++l){var p=u.positions[l];for(c=0;c<2;++c)h[0][c]=Math.min(h[0][c],p[c]),h[1][c]=Math.max(h[1][c],p[c])}return i[t]=[s,u,h]};var a={}},{\"vectorize-text\":549}],299:[function(t,e,r){var n=t(\"gl-shader\"),a=t(\"glslify\"),i=a([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = 1.0;\\n    if(distance(highlightId, id) < 0.0001) {\\n      scale = highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1);\\n    vec4 viewPosition = view * worldPosition;\\n    viewPosition = viewPosition / viewPosition.w;\\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),o=a([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = pixelRatio;\\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n      scale *= highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1.0);\\n    vec4 viewPosition = view * worldPosition;\\n    vec4 clipPosition = projection * viewPosition;\\n    clipPosition /= clipPosition.w;\\n\\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),s=a([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float lscale = pixelRatio * scale;\\n    if(distance(highlightId, id) < 0.0001) {\\n      lscale *= highlightScale;\\n    }\\n\\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = dataPosition;\\n  }\\n}\\n\"]),l=a([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (\\n    outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\\n    interpColor.a * opacity == 0.\\n  ) discard;\\n  gl_FragColor = interpColor * opacity;\\n}\\n\"]),c=a([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\\n\\n  gl_FragColor = vec4(pickGroup, pickId.bgr);\\n}\"]),u=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],h={vertex:i,fragment:l,attributes:u},f={vertex:o,fragment:l,attributes:u},p={vertex:s,fragment:l,attributes:u},d={vertex:i,fragment:c,attributes:u},g={vertex:o,fragment:c,attributes:u},v={vertex:s,fragment:c,attributes:u};function m(t,e){var r=n(t,e),a=r.attributes;return a.position.location=0,a.color.location=1,a.glyph.location=2,a.id.location=3,r}r.createPerspective=function(t){return m(t,h)},r.createOrtho=function(t){return m(t,f)},r.createProject=function(t){return m(t,p)},r.createPickPerspective=function(t){return m(t,d)},r.createPickOrtho=function(t){return m(t,g)},r.createPickProject=function(t){return m(t,v)}},{\"gl-shader\":304,glslify:411}],300:[function(t,e,r){\"use strict\";var n=t(\"is-string-blank\"),a=t(\"gl-buffer\"),i=t(\"gl-vao\"),o=t(\"typedarray-pool\"),s=t(\"gl-mat4/multiply\"),l=t(\"./lib/shaders\"),c=t(\"./lib/glyphs\"),u=t(\"./lib/get-simple-string\"),h=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function f(t,e){var r=t[0],n=t[1],a=t[2],i=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*a+e[12]*i,t[1]=e[1]*r+e[5]*n+e[9]*a+e[13]*i,t[2]=e[2]*r+e[6]*n+e[10]*a+e[14]*i,t[3]=e[3]*r+e[7]*n+e[11]*a+e[15]*i,t}function p(t,e,r,n){return f(n,n),f(n,n),f(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function g(t){return!0===t?1:t>1?1:t}function v(t,e,r,n,a,i,o,s,l,c,u,h){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=a,this.colorBuffer=i,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=u,this.pickProjectShader=h,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}e.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),c=l.createPickOrtho(e),u=l.createPickProject(e),h=a(e),f=a(e),p=a(e),d=a(e),g=i(e,[{buffer:h,size:3,type:e.FLOAT},{buffer:f,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),m=new v(e,r,n,o,h,f,p,d,g,s,c,u);return m.update(t),m};var m=v.prototype;m.pickSlots=1,m.setPickBase=function(t){this.pickId=t},m.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},m.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var y=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],k=h.slice(),T=[0,0,0],M=[[0,0,0],[0,0,0]];function A(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function L(t,e,r,n){var a,i=e.axesProject,o=e.gl,l=t.uniforms,c=r.model||h,u=r.view||h,f=r.projection||h,d=e.axesBounds,g=function(t){for(var e=M,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);a=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],y[0]=2/o.drawingBufferWidth,y[1]=2/o.drawingBufferHeight,t.bind(),l.view=u,l.projection=f,l.screenSize=y,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=g,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var v=0;v<3;++v)if(i[v]){l.scale=e.projectScale[v],l.opacity=e.projectOpacity[v];for(var m=k,L=0;L<16;++L)m[L]=0;for(L=0;L<4;++L)m[5*L]=1;m[5*v]=0,a[v]<0?m[12+v]=d[0][v]:m[12+v]=d[1][v],s(m,c,m),l.model=m;var C=(v+1)%3,P=(v+2)%3,O=A(x),z=A(b);O[C]=1,z[P]=1;var I=p(0,0,0,S(_,O)),D=p(0,0,0,S(w,z));if(Math.abs(I[1])>Math.abs(D[1])){var R=I;I=D,D=R,R=O,O=z,z=R;var F=C;C=P,P=F}I[0]<0&&(O[C]=-1),D[1]>0&&(z[P]=-1);var B=0,N=0;for(L=0;L<4;++L)B+=Math.pow(c[4*C+L],2),N+=Math.pow(c[4*P+L],2);O[C]/=Math.sqrt(B),z[P]/=Math.sqrt(N),l.axes[0]=O,l.axes[1]=z,l.fragClipBounds[0]=E(T,g[0],v,-1e8),l.fragClipBounds[1]=E(T,g[1],v,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}var C=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function P(t,e,r,n,a,i,o){var s=r.gl;if((i===r.projectHasAlpha||o)&&L(e,r,n,a),i===r.hasAlpha||o){t.bind();var l=t.uniforms;l.model=n.model||h,l.view=n.view||h,l.projection=n.projection||h,y[0]=2/s.drawingBufferWidth,y[1]=2/s.drawingBufferHeight,l.screenSize=y,l.highlightId=r.highlightId,l.highlightScale=r.highlightScale,l.fragClipBounds=C,l.clipBounds=r.axes.bounds,l.opacity=r.opacity,l.pickGroup=r.pickId/255,l.pixelRatio=a,r.vao.bind(),r.vao.draw(s.TRIANGLES,r.vertexCount),r.lineWidth>0&&(s.lineWidth(r.lineWidth*a),r.vao.draw(s.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function O(t,e,r,a){var i;i=Array.isArray(t)?e<t.length?t[e]:void 0:t,i=u(i);var o=!0;n(i)&&(i=\"\\u25bc\",o=!1);var s=c(i,r,a);return{mesh:s[0],lines:s[1],bounds:s[2],visible:o}}m.draw=function(t){P(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!1,!1)},m.drawTransparent=function(t){P(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!0,!1)},m.drawPick=function(t){P(this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader,this.pickProjectShader,this,t,1,!0,!0)},m.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var a=0;a<3;++a)n.position[a]=n.dataCoordinate[a]=r[a];return n},m.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,a=e>>16&255;this.highlightId=[r/255,n/255,a/255,0]}else this.highlightId=[1,1,1,1]},m.update=function(t){if(\"perspective\"in(t=t||{})&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(this.projectHasAlpha=!1,\"projectOpacity\"in t){if(Array.isArray(t.projectOpacity))this.projectOpacity=t.projectOpacity.slice();else{r=+t.projectOpacity;this.projectOpacity=[r,r,r]}for(var n=0;n<3;++n)this.projectOpacity[n]=g(this.projectOpacity[n]),this.projectOpacity[n]<1&&(this.projectHasAlpha=!0)}this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=g(t.opacity),this.opacity<1&&(this.hasAlpha=!0)),this.dirty=!0;var a,i,s=t.position,l=t.font||\"normal\",c=t.alignment||[0,0];if(2===c.length)a=c[0],i=c[1];else{a=[],i=[];for(n=0;n<c.length;++n)a[n]=c[n][0],i[n]=c[n][1]}var u=[1/0,1/0,1/0],h=[-1/0,-1/0,-1/0],f=t.glyph,p=t.color,d=t.size,v=t.angle,m=t.lineColor,y=-1,x=0,b=0,_=0;if(s.length){_=s.length;t:for(n=0;n<_;++n){for(var w=s[n],k=0;k<3;++k)if(isNaN(w[k])||!isFinite(w[k]))continue t;var T=(N=O(f,n,l,this.pixelRatio)).mesh,M=N.lines,A=N.bounds;x+=3*T.cells.length,b+=2*M.edges.length}}var S=x+b,E=o.mallocFloat(3*S),L=o.mallocFloat(4*S),C=o.mallocFloat(2*S),P=o.mallocUint32(S);if(S>0){var z=0,I=x,D=[0,0,0,1],R=[0,0,0,1],F=Array.isArray(p)&&Array.isArray(p[0]),B=Array.isArray(m)&&Array.isArray(m[0]);t:for(n=0;n<_;++n){y+=1;for(w=s[n],k=0;k<3;++k){if(isNaN(w[k])||!isFinite(w[k]))continue t;h[k]=Math.max(h[k],w[k]),u[k]=Math.min(u[k],w[k])}T=(N=O(f,n,l,this.pixelRatio)).mesh,M=N.lines,A=N.bounds;var N,j=N.visible;if(j)if(Array.isArray(p)){if(3===(V=F?n<p.length?p[n]:[0,0,0,0]:p).length){for(k=0;k<3;++k)D[k]=V[k];D[3]=1}else if(4===V.length){for(k=0;k<4;++k)D[k]=V[k];!this.hasAlpha&&V[3]<1&&(this.hasAlpha=!0)}}else D[0]=D[1]=D[2]=0,D[3]=1;else D=[1,1,1,0];if(j)if(Array.isArray(m)){var V;if(3===(V=B?n<m.length?m[n]:[0,0,0,0]:m).length){for(k=0;k<3;++k)R[k]=V[k];R[k]=1}else if(4===V.length){for(k=0;k<4;++k)R[k]=V[k];!this.hasAlpha&&V[3]<1&&(this.hasAlpha=!0)}}else R[0]=R[1]=R[2]=0,R[3]=1;else R=[1,1,1,0];var U=.5;j?Array.isArray(d)?U=n<d.length?+d[n]:12:d?U=+d:this.useOrtho&&(U=12):U=0;var q=0;Array.isArray(v)?q=n<v.length?+v[n]:0:v&&(q=+v);var H=Math.cos(q),G=Math.sin(q);for(w=s[n],k=0;k<3;++k)h[k]=Math.max(h[k],w[k]),u[k]=Math.min(u[k],w[k]);var Y=a,W=i;Y=0;Array.isArray(a)?Y=n<a.length?a[n]:0:a&&(Y=a);W=0;Array.isArray(i)?W=n<i.length?i[n]:0:i&&(W=i);var X=[Y*=Y>0?1-A[0][0]:Y<0?1+A[1][0]:1,W*=W>0?1-A[0][1]:W<0?1+A[1][1]:1],Z=T.cells||[],J=T.positions||[];for(k=0;k<Z.length;++k)for(var K=Z[k],Q=0;Q<3;++Q){for(var $=0;$<3;++$)E[3*z+$]=w[$];for($=0;$<4;++$)L[4*z+$]=D[$];P[z]=y;var tt=J[K[Q]];C[2*z]=U*(H*tt[0]-G*tt[1]+X[0]),C[2*z+1]=U*(G*tt[0]+H*tt[1]+X[1]),z+=1}for(Z=M.edges,J=M.positions,k=0;k<Z.length;++k)for(K=Z[k],Q=0;Q<2;++Q){for($=0;$<3;++$)E[3*I+$]=w[$];for($=0;$<4;++$)L[4*I+$]=R[$];P[I]=y;tt=J[K[Q]];C[2*I]=U*(H*tt[0]-G*tt[1]+X[0]),C[2*I+1]=U*(G*tt[0]+H*tt[1]+X[1]),I+=1}}}this.bounds=[u,h],this.points=s,this.pointCount=s.length,this.vertexCount=x,this.lineVertexCount=b,this.pointBuffer.update(E),this.colorBuffer.update(L),this.glyphBuffer.update(C),this.idBuffer.update(P),o.free(E),o.free(L),o.free(C),o.free(P)},m.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},{\"./lib/get-simple-string\":297,\"./lib/glyphs\":298,\"./lib/shaders\":299,\"gl-buffer\":244,\"gl-mat4/multiply\":270,\"gl-vao\":329,\"is-string-blank\":425,\"typedarray-pool\":544}],301:[function(t,e,r){\"use strict\";var n=t(\"glslify\");r.boxVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 vertex;\\n\\nuniform vec2 cornerA, cornerB;\\n\\nvoid main() {\\n  gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\\n}\\n\"]),r.boxFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = color;\\n}\\n\"])},{glslify:411}],302:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),a=t(\"gl-buffer\"),i=t(\"./lib/shaders\");function o(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-1/0,-1/0],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}e.exports=function(t,e){var r=t.gl,s=a(r,[0,0,0,1,1,0,1,1]),l=n(r,i.boxVertex,i.boxFragment),c=new o(t,s,l);return c.update(e),t.addOverlay(c),c};var s=o.prototype;s.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),a=(this.outerFill,this.outerColor),i=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,c=t.viewBox,u=t.pixelRatio,h=(e[0]-l[0])*(c[2]-c[0])/(l[2]-l[0])+c[0],f=(e[1]-l[1])*(c[3]-c[1])/(l[3]-l[1])+c[1],p=(e[2]-l[0])*(c[2]-c[0])/(l[2]-l[0])+c[0],d=(e[3]-l[1])*(c[3]-c[1])/(l[3]-l[1])+c[1];if(h=Math.max(h,c[0]),f=Math.max(f,c[1]),p=Math.min(p,c[2]),d=Math.min(d,c[3]),!(p<h||d<f)){o.bind();var g=s[2]-s[0],v=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,g,f,a),o.drawBox(0,f,h,d,a),o.drawBox(0,d,g,v,a),o.drawBox(p,f,g,d,a)),this.innerFill&&o.drawBox(h,f,p,d,n),r>0){var m=r*u;o.drawBox(h-m,f-m,p+m,f+m,i),o.drawBox(h-m,d-m,p+m,d+m,i),o.drawBox(h-m,f-m,h+m,d+m,i),o.drawBox(p-m,f-m,p+m,d+m,i)}}}},s.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},s.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},{\"./lib/shaders\":301,\"gl-buffer\":244,\"gl-shader\":304}],303:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=e[0],i=e[1],o=n(t,r,i,{}),s=a.mallocUint8(r*i*4);return new c(t,o,s)};var n=t(\"gl-fbo\"),a=t(\"typedarray-pool\"),i=t(\"ndarray\"),o=t(\"bit-twiddle\").nextPow2,s=t(\"cwise/lib/wrapper\")({args:[\"array\",{offset:[0,0,1],array:0},{offset:[0,0,2],array:0},{offset:[0,0,3],array:0},\"scalar\",\"scalar\",\"index\"],pre:{body:\"{this_closestD2=1e8,this_closestX=-1,this_closestY=-1}\",args:[],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[]},body:{body:\"{if(_inline_16_arg0_<255||_inline_16_arg1_<255||_inline_16_arg2_<255||_inline_16_arg3_<255){var _inline_16_l=_inline_16_arg4_-_inline_16_arg6_[0],_inline_16_a=_inline_16_arg5_-_inline_16_arg6_[1],_inline_16_f=_inline_16_l*_inline_16_l+_inline_16_a*_inline_16_a;_inline_16_f<this_closestD2&&(this_closestD2=_inline_16_f,this_closestX=_inline_16_arg6_[0],this_closestY=_inline_16_arg6_[1])}}\",args:[{name:\"_inline_16_arg0_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_16_arg1_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_16_arg2_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_16_arg3_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_16_arg4_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_16_arg5_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_16_arg6_\",lvalue:!1,rvalue:!0,count:4}],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[\"_inline_16_a\",\"_inline_16_f\",\"_inline_16_l\"]},post:{body:\"{return[this_closestX,this_closestY,this_closestD2]}\",args:[],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[]},debug:!1,funcName:\"cwise\",blockSize:64});function l(t,e,r,n,a){this.coord=[t,e],this.id=r,this.value=n,this.distance=a}function c(t,e,r){this.gl=t,this.fbo=e,this.buffer=r,this._readTimeout=null;var n=this;this._readCallback=function(){n.gl&&(e.bind(),t.readPixels(0,0,e.shape[0],e.shape[1],t.RGBA,t.UNSIGNED_BYTE,n.buffer),n._readTimeout=null)}}var u=c.prototype;Object.defineProperty(u,\"shape\",{get:function(){return this.gl?this.fbo.shape.slice():[0,0]},set:function(t){if(this.gl){this.fbo.shape=t;var e=this.fbo.shape[0],r=this.fbo.shape[1];if(r*e*4>this.buffer.length){a.free(this.buffer);for(var n=this.buffer=a.mallocUint8(o(r*e*4)),i=0;i<r*e*4;++i)n[i]=255}return t}}}),u.begin=function(){var t=this.gl;this.shape;t&&(this.fbo.bind(),t.clearColor(1,1,1,1),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT))},u.end=function(){var t=this.gl;t&&(t.bindFramebuffer(t.FRAMEBUFFER,null),this._readTimeout||clearTimeout(this._readTimeout),this._readTimeout=setTimeout(this._readCallback,1))},u.query=function(t,e,r){if(!this.gl)return null;var n=this.fbo.shape.slice();t|=0,e|=0,\"number\"!=typeof r&&(r=1);var a=0|Math.min(Math.max(t-r,0),n[0]),o=0|Math.min(Math.max(t+r,0),n[0]),c=0|Math.min(Math.max(e-r,0),n[1]),u=0|Math.min(Math.max(e+r,0),n[1]);if(o<=a||u<=c)return null;var h=[o-a,u-c],f=i(this.buffer,[h[0],h[1],4],[4,4*n[0],1],4*(a+n[0]*c)),p=s(f.hi(h[0],h[1],1),r,r),d=p[0],g=p[1];return d<0||Math.pow(this.radius,2)<p[2]?null:new l(d+a|0,g+c|0,f.get(d,g,0),[f.get(d,g,1),f.get(d,g,2),f.get(d,g,3)],Math.sqrt(p[2]))},u.dispose=function(){this.gl&&(this.fbo.dispose(),a.free(this.buffer),this.gl=null,this._readTimeout&&clearTimeout(this._readTimeout))}},{\"bit-twiddle\":94,\"cwise/lib/wrapper\":151,\"gl-fbo\":252,ndarray:452,\"typedarray-pool\":544}],304:[function(t,e,r){\"use strict\";var n=t(\"./lib/create-uniforms\"),a=t(\"./lib/create-attributes\"),i=t(\"./lib/reflect\"),o=t(\"./lib/shader-cache\"),s=t(\"./lib/runtime-reflect\"),l=t(\"./lib/GLError\");function c(t){this.gl=t,this.gl.lastAttribCount=0,this._vref=this._fref=this._relink=this.vertShader=this.fragShader=this.program=this.attributes=this.uniforms=this.types=null}var u=c.prototype;function h(t,e){return t.name<e.name?-1:1}u.bind=function(){var t;this.program||this._relink();var e=this.gl.getProgramParameter(this.program,this.gl.ACTIVE_ATTRIBUTES),r=this.gl.lastAttribCount;if(e>r)for(t=r;t<e;t++)this.gl.enableVertexAttribArray(t);else if(r>e)for(t=e;t<r;t++)this.gl.disableVertexAttribArray(t);this.gl.lastAttribCount=e,this.gl.useProgram(this.program)},u.dispose=function(){for(var t=this.gl.lastAttribCount,e=0;e<t;e++)this.gl.disableVertexAttribArray(e);this.gl.lastAttribCount=0,this._fref&&this._fref.dispose(),this._vref&&this._vref.dispose(),this.attributes=this.types=this.vertShader=this.fragShader=this.program=this._relink=this._fref=this._vref=null},u.update=function(t,e,r,c){if(!e||1===arguments.length){var u=t;t=u.vertex,e=u.fragment,r=u.uniforms,c=u.attributes}var f=this,p=f.gl,d=f._vref;f._vref=o.shader(p,p.VERTEX_SHADER,t),d&&d.dispose(),f.vertShader=f._vref.shader;var g=this._fref;if(f._fref=o.shader(p,p.FRAGMENT_SHADER,e),g&&g.dispose(),f.fragShader=f._fref.shader,!r||!c){var v=p.createProgram();if(p.attachShader(v,f.fragShader),p.attachShader(v,f.vertShader),p.linkProgram(v),!p.getProgramParameter(v,p.LINK_STATUS)){var m=p.getProgramInfoLog(v);throw new l(m,\"Error linking program:\"+m)}r=r||s.uniforms(p,v),c=c||s.attributes(p,v),p.deleteProgram(v)}(c=c.slice()).sort(h);var y,x=[],b=[],_=[];for(y=0;y<c.length;++y){var w=c[y];if(w.type.indexOf(\"mat\")>=0){for(var k=0|w.type.charAt(w.type.length-1),T=new Array(k),M=0;M<k;++M)T[M]=_.length,b.push(w.name+\"[\"+M+\"]\"),\"number\"==typeof w.location?_.push(w.location+M):Array.isArray(w.location)&&w.location.length===k&&\"number\"==typeof w.location[M]?_.push(0|w.location[M]):_.push(-1);x.push({name:w.name,type:w.type,locations:T})}else x.push({name:w.name,type:w.type,locations:[_.length]}),b.push(w.name),\"number\"==typeof w.location?_.push(0|w.location):_.push(-1)}var A=0;for(y=0;y<_.length;++y)if(_[y]<0){for(;_.indexOf(A)>=0;)A+=1;_[y]=A}var S=new Array(r.length);function E(){f.program=o.program(p,f._vref,f._fref,b,_);for(var t=0;t<r.length;++t)S[t]=p.getUniformLocation(f.program,r[t].name)}E(),f._relink=E,f.types={uniforms:i(r),attributes:i(c)},f.attributes=a(p,f,x,_),Object.defineProperty(f,\"uniforms\",n(p,f,r,S))},e.exports=function(t,e,r,n,a){var i=new c(t);return i.update(e,r,n,a),i}},{\"./lib/GLError\":305,\"./lib/create-attributes\":306,\"./lib/create-uniforms\":307,\"./lib/reflect\":308,\"./lib/runtime-reflect\":309,\"./lib/shader-cache\":310}],305:[function(t,e,r){function n(t,e,r){this.shortMessage=e||\"\",this.longMessage=r||\"\",this.rawError=t||\"\",this.message=\"gl-shader: \"+(e||t||\"\")+(r?\"\\n\"+r:\"\"),this.stack=(new Error).stack}n.prototype=new Error,n.prototype.name=\"GLError\",n.prototype.constructor=n,e.exports=n},{}],306:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,a){for(var i={},l=0,c=r.length;l<c;++l){var u=r[l],h=u.name,f=u.type,p=u.locations;switch(f){case\"bool\":case\"int\":case\"float\":o(t,e,p[0],a,1,i,h);break;default:if(f.indexOf(\"vec\")>=0){var d=f.charCodeAt(f.length-1)-48;if(d<2||d>4)throw new n(\"\",\"Invalid data type for attribute \"+h+\": \"+f);o(t,e,p[0],a,d,i,h)}else{if(!(f.indexOf(\"mat\")>=0))throw new n(\"\",\"Unknown data type for attribute \"+h+\": \"+f);var d=f.charCodeAt(f.length-1)-48;if(d<2||d>4)throw new n(\"\",\"Invalid data type for attribute \"+h+\": \"+f);s(t,e,p,a,d,i,h)}}}return i};var n=t(\"./GLError\");function a(t,e,r,n,a,i){this._gl=t,this._wrapper=e,this._index=r,this._locations=n,this._dimension=a,this._constFunc=i}var i=a.prototype;function o(t,e,r,n,i,o,s){for(var l=[\"gl\",\"v\"],c=[],u=0;u<i;++u)l.push(\"x\"+u),c.push(\"x\"+u);l.push(\"if(x0.length===void 0){return gl.vertexAttrib\"+i+\"f(v,\"+c.join()+\")}else{return gl.vertexAttrib\"+i+\"fv(v,x0)}\");var h=Function.apply(null,l),f=new a(t,e,r,n,i,h);Object.defineProperty(o,s,{set:function(e){return t.disableVertexAttribArray(n[r]),h(t,n[r],e),e},get:function(){return f},enumerable:!0})}function s(t,e,r,n,a,i,s){for(var l=new Array(a),c=new Array(a),u=0;u<a;++u)o(t,e,r[u],n,a,l,u),c[u]=l[u];Object.defineProperty(l,\"location\",{set:function(t){if(Array.isArray(t))for(var e=0;e<a;++e)c[e].location=t[e];else for(e=0;e<a;++e)c[e].location=t+e;return t},get:function(){for(var t=new Array(a),e=0;e<a;++e)t[e]=n[r[e]];return t},enumerable:!0}),l.pointer=function(e,i,o,s){e=e||t.FLOAT,i=!!i,o=o||a*a,s=s||0;for(var l=0;l<a;++l){var c=n[r[l]];t.vertexAttribPointer(c,a,e,i,o,s+l*a),t.enableVertexAttribArray(c)}};var h=new Array(a),f=t[\"vertexAttrib\"+a+\"fv\"];Object.defineProperty(i,s,{set:function(e){for(var i=0;i<a;++i){var o=n[r[i]];if(t.disableVertexAttribArray(o),Array.isArray(e[0]))f.call(t,o,e[i]);else{for(var s=0;s<a;++s)h[s]=e[a*i+s];f.call(t,o,h)}}return e},get:function(){return l},enumerable:!0})}i.pointer=function(t,e,r,n){var a=this._gl,i=this._locations[this._index];a.vertexAttribPointer(i,this._dimension,t||a.FLOAT,!!e,r||0,n||0),a.enableVertexAttribArray(i)},i.set=function(t,e,r,n){return this._constFunc(this._locations[this._index],t,e,r,n)},Object.defineProperty(i,\"location\",{get:function(){return this._locations[this._index]},set:function(t){return t!==this._locations[this._index]&&(this._locations[this._index]=0|t,this._wrapper.program=null),0|t}})},{\"./GLError\":305}],307:[function(t,e,r){\"use strict\";var n=t(\"./reflect\"),a=t(\"./GLError\");function i(t){return new Function(\"y\",\"return function(){return y}\")(t)}function o(t,e){for(var r=new Array(t),n=0;n<t;++n)r[n]=e;return r}e.exports=function(t,e,r,s){function l(t,e,r){switch(r){case\"bool\":case\"int\":case\"sampler2D\":case\"samplerCube\":return\"gl.uniform1i(locations[\"+e+\"],obj\"+t+\")\";case\"float\":return\"gl.uniform1f(locations[\"+e+\"],obj\"+t+\")\";default:var n=r.indexOf(\"vec\");if(!(0<=n&&n<=1&&r.length===4+n)){if(0===r.indexOf(\"mat\")&&4===r.length){var i=r.charCodeAt(r.length-1)-48;if(i<2||i>4)throw new a(\"\",\"Invalid uniform dimension type for matrix \"+name+\": \"+r);return\"gl.uniformMatrix\"+i+\"fv(locations[\"+e+\"],false,obj\"+t+\")\"}throw new a(\"\",\"Unknown uniform data type for \"+name+\": \"+r)}var i=r.charCodeAt(r.length-1)-48;if(i<2||i>4)throw new a(\"\",\"Invalid data type\");switch(r.charAt(0)){case\"b\":case\"i\":return\"gl.uniform\"+i+\"iv(locations[\"+e+\"],obj\"+t+\")\";case\"v\":return\"gl.uniform\"+i+\"fv(locations[\"+e+\"],obj\"+t+\")\";default:throw new a(\"\",\"Unrecognized data type for vector \"+name+\": \"+r)}}}function c(e){for(var n=[\"return function updateProperty(obj){\"],a=function t(e,r){if(\"object\"!=typeof r)return[[e,r]];var n=[];for(var a in r){var i=r[a],o=e;parseInt(a)+\"\"===a?o+=\"[\"+a+\"]\":o+=\".\"+a,\"object\"==typeof i?n.push.apply(n,t(o,i)):n.push([o,i])}return n}(\"\",e),i=0;i<a.length;++i){var o=a[i],c=o[0],u=o[1];s[u]&&n.push(l(c,u,r[u].type))}n.push(\"return obj}\");var h=new Function(\"gl\",\"locations\",n.join(\"\\n\"));return h(t,s)}function u(n,l,u){if(\"object\"==typeof u){var f=h(u);Object.defineProperty(n,l,{get:i(f),set:c(u),enumerable:!0,configurable:!1})}else s[u]?Object.defineProperty(n,l,{get:(p=u,d=new Function(\"gl\",\"wrapper\",\"locations\",\"return function(){return gl.getUniform(wrapper.program,locations[\"+p+\"])}\"),d(t,e,s)),set:c(u),enumerable:!0,configurable:!1}):n[l]=function(t){switch(t){case\"bool\":return!1;case\"int\":case\"sampler2D\":case\"samplerCube\":case\"float\":return 0;default:var e=t.indexOf(\"vec\");if(0<=e&&e<=1&&t.length===4+e){var r=t.charCodeAt(t.length-1)-48;if(r<2||r>4)throw new a(\"\",\"Invalid data type\");return\"b\"===t.charAt(0)?o(r,!1):o(r,0)}if(0===t.indexOf(\"mat\")&&4===t.length){var r=t.charCodeAt(t.length-1)-48;if(r<2||r>4)throw new a(\"\",\"Invalid uniform dimension type for matrix \"+name+\": \"+t);return o(r*r,0)}throw new a(\"\",\"Unknown uniform data type for \"+name+\": \"+t)}}(r[u].type);var p,d}function h(t){var e;if(Array.isArray(t)){e=new Array(t.length);for(var r=0;r<t.length;++r)u(e,r,t[r])}else for(var n in e={},t)u(e,n,t[n]);return e}var f=n(r,!0);return{get:i(h(f)),set:c(f),enumerable:!0,configurable:!0}}},{\"./GLError\":305,\"./reflect\":308}],308:[function(t,e,r){\"use strict\";e.exports=function(t,e){for(var r={},n=0;n<t.length;++n)for(var a=t[n].name,i=a.split(\".\"),o=r,s=0;s<i.length;++s){var l=i[s].split(\"[\");if(l.length>1){l[0]in o||(o[l[0]]=[]),o=o[l[0]];for(var c=1;c<l.length;++c){var u=parseInt(l[c]);c<l.length-1||s<i.length-1?(u in o||(c<l.length-1?o[u]=[]:o[u]={}),o=o[u]):o[u]=e?n:t[n].type}}else s<i.length-1?(l[0]in o||(o[l[0]]={}),o=o[l[0]]):o[l[0]]=e?n:t[n].type}return r}},{}],309:[function(t,e,r){\"use strict\";r.uniforms=function(t,e){for(var r=t.getProgramParameter(e,t.ACTIVE_UNIFORMS),n=[],a=0;a<r;++a){var o=t.getActiveUniform(e,a);if(o){var s=i(t,o.type);if(o.size>1)for(var l=0;l<o.size;++l)n.push({name:o.name.replace(\"[0]\",\"[\"+l+\"]\"),type:s});else n.push({name:o.name,type:s})}}return n},r.attributes=function(t,e){for(var r=t.getProgramParameter(e,t.ACTIVE_ATTRIBUTES),n=[],a=0;a<r;++a){var o=t.getActiveAttrib(e,a);o&&n.push({name:o.name,type:i(t,o.type)})}return n};var n={FLOAT:\"float\",FLOAT_VEC2:\"vec2\",FLOAT_VEC3:\"vec3\",FLOAT_VEC4:\"vec4\",INT:\"int\",INT_VEC2:\"ivec2\",INT_VEC3:\"ivec3\",INT_VEC4:\"ivec4\",BOOL:\"bool\",BOOL_VEC2:\"bvec2\",BOOL_VEC3:\"bvec3\",BOOL_VEC4:\"bvec4\",FLOAT_MAT2:\"mat2\",FLOAT_MAT3:\"mat3\",FLOAT_MAT4:\"mat4\",SAMPLER_2D:\"sampler2D\",SAMPLER_CUBE:\"samplerCube\"},a=null;function i(t,e){if(!a){var r=Object.keys(n);a={};for(var i=0;i<r.length;++i){var o=r[i];a[t[o]]=n[o]}}return a[e]}},{}],310:[function(t,e,r){\"use strict\";r.shader=function(t,e,r){return u(t).getShaderReference(e,r)},r.program=function(t,e,r,n,a){return u(t).getProgram(e,r,n,a)};var n=t(\"./GLError\"),a=t(\"gl-format-compiler-error\"),i=new(\"undefined\"==typeof WeakMap?t(\"weakmap-shim\"):WeakMap),o=0;function s(t,e,r,n,a,i,o){this.id=t,this.src=e,this.type=r,this.shader=n,this.count=i,this.programs=[],this.cache=o}function l(t){this.gl=t,this.shaders=[{},{}],this.programs={}}s.prototype.dispose=function(){if(0==--this.count){for(var t=this.cache,e=t.gl,r=this.programs,n=0,a=r.length;n<a;++n){var i=t.programs[r[n]];i&&(delete t.programs[n],e.deleteProgram(i))}e.deleteShader(this.shader),delete t.shaders[this.type===e.FRAGMENT_SHADER|0][this.src]}};var c=l.prototype;function u(t){var e=i.get(t);return e||(e=new l(t),i.set(t,e)),e}c.getShaderReference=function(t,e){var r=this.gl,i=this.shaders[t===r.FRAGMENT_SHADER|0],l=i[e];if(l&&r.isShader(l.shader))l.count+=1;else{var c=function(t,e,r){var i=t.createShader(e);if(t.shaderSource(i,r),t.compileShader(i),!t.getShaderParameter(i,t.COMPILE_STATUS)){var o=t.getShaderInfoLog(i);try{var s=a(o,r,e)}catch(t){throw console.warn(\"Failed to format compiler error: \"+t),new n(o,\"Error compiling shader:\\n\"+o)}throw new n(o,s.short,s.long)}return i}(r,t,e);l=i[e]=new s(o++,e,t,c,[],1,this)}return l},c.getProgram=function(t,e,r,a){var i=[t.id,e.id,r.join(\":\"),a.join(\":\")].join(\"@\"),o=this.programs[i];return o&&this.gl.isProgram(o)||(this.programs[i]=o=function(t,e,r,a,i){var o=t.createProgram();t.attachShader(o,e),t.attachShader(o,r);for(var s=0;s<a.length;++s)t.bindAttribLocation(o,i[s],a[s]);if(t.linkProgram(o),!t.getProgramParameter(o,t.LINK_STATUS)){var l=t.getProgramInfoLog(o);throw new n(l,\"Error linking program: \"+l)}return o}(this.gl,t.shader,e.shader,r,a),t.programs.push(i),e.programs.push(i)),o}},{\"./GLError\":305,\"gl-format-compiler-error\":253,\"weakmap-shim\":554}],311:[function(t,e,r){\"use strict\";function n(t){this.plot=t,this.enable=[!0,!0,!1,!1],this.width=[1,1,1,1],this.color=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.center=[1/0,1/0]}e.exports=function(t,e){var r=new n(t);return r.update(e),t.addOverlay(r),r};var a=n.prototype;a.update=function(t){t=t||{},this.enable=(t.enable||[!0,!0,!1,!1]).slice(),this.width=(t.width||[1,1,1,1]).slice(),this.color=(t.color||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]).map(function(t){return t.slice()}),this.center=(t.center||[1/0,1/0]).slice(),this.plot.setOverlayDirty()},a.draw=function(){var t=this.enable,e=this.width,r=this.color,n=this.center,a=this.plot,i=a.line,o=a.dataBox,s=a.viewBox;if(i.bind(),o[0]<=n[0]&&n[0]<=o[2]&&o[1]<=n[1]&&n[1]<=o[3]){var l=s[0]+(n[0]-o[0])/(o[2]-o[0])*(s[2]-s[0]),c=s[1]+(n[1]-o[1])/(o[3]-o[1])*(s[3]-s[1]);t[0]&&i.drawLine(l,c,s[0],c,e[0],r[0]),t[1]&&i.drawLine(l,c,l,s[1],e[1],r[1]),t[2]&&i.drawLine(l,c,s[2],c,e[2],r[2]),t[3]&&i.drawLine(l,c,l,s[3],e[3],r[3])}},a.dispose=function(){this.plot.removeOverlay(this)}},{}],312:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),a=t(\"gl-shader\"),i=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, color;\\nattribute float weight;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 coordinates[3];\\nuniform vec4 colors[3];\\nuniform vec2 screenShape;\\nuniform float lineWidth;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vertexPosition = mix(coordinates[0],\\n    mix(coordinates[2], coordinates[1], 0.5 * (position + 1.0)), abs(position));\\n\\n  vec4 clipPos = projection * view * model * vec4(vertexPosition, 1.0);\\n  vec2 clipOffset = (projection * view * model * vec4(color, 0.0)).xy;\\n  vec2 delta = weight * clipOffset * screenShape;\\n  vec2 lineOffset = normalize(vec2(delta.y, -delta.x)) / screenShape;\\n\\n  gl_Position   = vec4(clipPos.xy + clipPos.w * 0.5 * lineWidth * lineOffset, clipPos.z, clipPos.w);\\n  fragColor     = color.x * colors[0] + color.y * colors[1] + color.z * colors[2];\\n}\\n\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\"]);e.exports=function(t){return a(t,i,o,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec3\"},{name:\"weight\",type:\"float\"}])}},{\"gl-shader\":304,glslify:411}],313:[function(t,e,r){\"use strict\";var n=t(\"gl-buffer\"),a=t(\"gl-vao\"),i=t(\"./shaders/index\");e.exports=function(t,e){var r=[];function o(t,e,n,a,i,o){var s=[t,e,n,0,0,0,1];s[a+3]=1,s[a]=i,r.push.apply(r,s),s[6]=-1,r.push.apply(r,s),s[a]=o,r.push.apply(r,s),r.push.apply(r,s),s[6]=1,r.push.apply(r,s),s[a]=i,r.push.apply(r,s)}o(0,0,0,0,0,1),o(0,0,0,1,0,1),o(0,0,0,2,0,1),o(1,0,0,1,-1,1),o(1,0,0,2,-1,1),o(0,1,0,0,-1,1),o(0,1,0,2,-1,1),o(0,0,1,0,-1,1),o(0,0,1,1,-1,1);var l=n(t,r),c=a(t,[{type:t.FLOAT,buffer:l,size:3,offset:0,stride:28},{type:t.FLOAT,buffer:l,size:3,offset:12,stride:28},{type:t.FLOAT,buffer:l,size:1,offset:24,stride:28}]),u=i(t);u.attributes.position.location=0,u.attributes.color.location=1,u.attributes.weight.location=2;var h=new s(t,l,c,u);return h.update(e),h};var o=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function s(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n,this.pixelRatio=1,this.bounds=[[-1e3,-1e3,-1e3],[1e3,1e3,1e3]],this.position=[0,0,0],this.lineWidth=[2,2,2],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.enabled=[!0,!0,!0],this.drawSides=[!0,!0,!0],this.axes=null}var l=s.prototype,c=[0,0,0],u=[0,0,0],h=[0,0];l.isTransparent=function(){return!1},l.drawTransparent=function(t){},l.draw=function(t){var e=this.gl,r=this.vao,n=this.shader;r.bind(),n.bind();var a,i=t.model||o,s=t.view||o,l=t.projection||o;this.axes&&(a=this.axes.lastCubeProps.axis);for(var f=c,p=u,d=0;d<3;++d)a&&a[d]<0?(f[d]=this.bounds[0][d],p[d]=this.bounds[1][d]):(f[d]=this.bounds[1][d],p[d]=this.bounds[0][d]);h[0]=e.drawingBufferWidth,h[1]=e.drawingBufferHeight,n.uniforms.model=i,n.uniforms.view=s,n.uniforms.projection=l,n.uniforms.coordinates=[this.position,f,p],n.uniforms.colors=this.colors,n.uniforms.screenShape=h;for(d=0;d<3;++d)n.uniforms.lineWidth=this.lineWidth[d]*this.pixelRatio,this.enabled[d]&&(r.draw(e.TRIANGLES,6,6*d),this.drawSides[d]&&r.draw(e.TRIANGLES,12,18+12*d));r.unbind()},l.update=function(t){t&&(\"bounds\"in t&&(this.bounds=t.bounds),\"position\"in t&&(this.position=t.position),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"colors\"in t&&(this.colors=t.colors),\"enabled\"in t&&(this.enabled=t.enabled),\"drawSides\"in t&&(this.drawSides=t.drawSides))},l.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders/index\":312,\"gl-buffer\":244,\"gl-vao\":329}],314:[function(t,e,r){var n=t(\"glslify\"),a=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n  float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, tubeScale;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * tubePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(tubePosition, 1.0);\\n  vec4 t_position  = view * tubePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = tubePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),i=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n  float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float tubeScale;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  gl_Position = projection * view * tubePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);r.meshShader={vertex:a,fragment:i,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec4\"}]},r.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec4\"}]}},{glslify:411}],315:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\"),a=t(\"gl-vec4\"),i=[\"xyz\",\"xzy\",\"yxz\",\"yzx\",\"zxy\",\"zyx\"],o=function(t,e,r,i){for(var o=0,s=0;s<t.length;s++)for(var l=t[s].velocities,c=0;c<l.length;c++)o=Math.max(o,n.length(l[c]));var u=t.map(function(t){return function(t,e,r,i){for(var o=t.points,s=t.velocities,l=t.divergences,c=[],u=[],h=[],f=[],p=[],d=[],g=0,v=0,m=a.create(),y=a.create(),x=0;x<o.length;x++){var b=o[x],_=s[x],w=l[x];0===e&&(w=.05*r),v=n.length(_)/i,m=a.create(),n.copy(m,_),m[3]=w;for(var k=0;k<8;k++)p[k]=[b[0],b[1],b[2],k];if(f.length>0)for(k=0;k<8;k++){var T=(k+1)%8;c.push(f[k],p[k],p[T],p[T],f[T],f[k]),h.push(y,m,m,m,y,y),d.push(g,v,v,v,g,g);var M=c.length;u.push([M-6,M-5,M-4],[M-3,M-2,M-1])}var A=f;f=p,p=A;var S=y;y=m,m=S;var E=g;g=v,v=E}return{positions:c,cells:u,vectors:h,vertexIntensity:d}}(t,r,i,o)}),h=[],f=[],p=[],d=[];for(s=0;s<u.length;s++){var g=u[s],v=h.length;h=h.concat(g.positions),p=p.concat(g.vectors),d=d.concat(g.vertexIntensity);for(c=0;c<g.cells.length;c++){var m=g.cells[c],y=[];f.push(y);for(var x=0;x<m.length;x++)y.push(m[x]+v)}}return{positions:h,cells:f,vectors:p,vertexIntensity:d,colormap:e}},s=function(t,e){var r,n=t.length;for(r=0;r<n;r++){var a=t[r];if(a===e)return r;if(a>e)return r-1}return r},l=function(t,e,r){return t<e?e:t>r?r:t},c=function(t){var e=1/0;t.sort(function(t,e){return t-e});for(var r=t.length,n=1;n<r;n++){var a=Math.abs(t[n]-t[n-1]);a<e&&(e=a)}return e};e.exports=function(t,e){var r=t.startingPositions,a=t.maxLength||1e3,u=t.tubeSize||1,h=t.absoluteTubeSize,f=t.gridFill||\"+x+y+z\",p={};-1!==f.indexOf(\"-x\")&&(p.reversedX=!0),-1!==f.indexOf(\"-y\")&&(p.reversedY=!0),-1!==f.indexOf(\"-z\")&&(p.reversedZ=!0),p.filled=i.indexOf(f.replace(/-/g,\"\").replace(/\\+/g,\"\"));var d=t.getVelocity||function(e){return function(t,e,r){var a=e.vectors,i=e.meshgrid,o=t[0],c=t[1],u=t[2],h=i[0].length,f=i[1].length,p=i[2].length,d=s(i[0],o),g=s(i[1],c),v=s(i[2],u),m=d+1,y=g+1,x=v+1;if(d=l(d,0,h-1),m=l(m,0,h-1),g=l(g,0,f-1),y=l(y,0,f-1),v=l(v,0,p-1),x=l(x,0,p-1),d<0||g<0||v<0||m>h-1||y>f-1||x>p-1)return n.create();var b,_,w,k,T,M,A=i[0][d],S=i[0][m],E=i[1][g],L=i[1][y],C=i[2][v],P=(o-A)/(S-A),O=(c-E)/(L-E),z=(u-C)/(i[2][x]-C);switch(isFinite(P)||(P=.5),isFinite(O)||(O=.5),isFinite(z)||(z=.5),r.reversedX&&(d=h-1-d,m=h-1-m),r.reversedY&&(g=f-1-g,y=f-1-y),r.reversedZ&&(v=p-1-v,x=p-1-x),r.filled){case 5:T=v,M=x,w=g*p,k=y*p,b=d*p*f,_=m*p*f;break;case 4:T=v,M=x,b=d*p,_=m*p,w=g*p*h,k=y*p*h;break;case 3:w=g,k=y,T=v*f,M=x*f,b=d*f*p,_=m*f*p;break;case 2:w=g,k=y,b=d*f,_=m*f,T=v*f*h,M=x*f*h;break;case 1:b=d,_=m,T=v*h,M=x*h,w=g*h*p,k=y*h*p;break;default:b=d,_=m,w=g*h,k=y*h,T=v*h*f,M=x*h*f}var I=a[b+w+T],D=a[b+w+M],R=a[b+k+T],F=a[b+k+M],B=a[_+w+T],N=a[_+w+M],j=a[_+k+T],V=a[_+k+M],U=n.create(),q=n.create(),H=n.create(),G=n.create();n.lerp(U,I,B,P),n.lerp(q,D,N,P),n.lerp(H,R,j,P),n.lerp(G,F,V,P);var Y=n.create(),W=n.create();n.lerp(Y,U,H,O),n.lerp(W,q,G,O);var X=n.create();return n.lerp(X,Y,W,z),X}(e,t,p)},g=t.getDivergence||function(t,e){var r=n.create(),a=1e-4;n.add(r,t,[a,0,0]);var i=d(r);n.subtract(i,i,e),n.scale(i,i,1e4),n.add(r,t,[0,a,0]);var o=d(r);n.subtract(o,o,e),n.scale(o,o,1e4),n.add(r,t,[0,0,a]);var s=d(r);return n.subtract(s,s,e),n.scale(s,s,1e4),n.add(r,i,o),n.add(r,r,s),r},v=[],m=e[0][0],y=e[0][1],x=e[0][2],b=e[1][0],_=e[1][1],w=e[1][2],k=function(t){var e=t[0],r=t[1],n=t[2];return!(e<m||e>b||r<y||r>_||n<x||n>w)},T=10*n.distance(e[0],e[1])/a,M=T*T,A=1,S=0,E=r.length;E>1&&(A=function(t){for(var e=[],r=[],n=[],a={},i={},o={},s=t.length,l=0;l<s;l++){var u=t[l],h=u[0],f=u[1],p=u[2];a[h]||(e.push(h),a[h]=!0),i[f]||(r.push(f),i[f]=!0),o[p]||(n.push(p),o[p]=!0)}var d=c(e),g=c(r),v=c(n),m=Math.min(d,g,v);return isFinite(m)?m:1}(r));for(var L=0;L<E;L++){var C=n.create();n.copy(C,r[L]);var P=[C],O=[],z=d(C),I=C;O.push(z);var D=[],R=g(C,z),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F),v.push({points:P,velocities:O,divergences:D});for(var B=0;B<100*a&&P.length<a&&k(C);){B++;var N=n.clone(z),j=n.squaredLength(N);if(0===j)break;if(j>M&&n.scale(N,N,T/Math.sqrt(j)),n.add(N,N,C),z=d(N),n.squaredDistance(I,N)-M>-1e-4*M){P.push(N),I=N,O.push(z);R=g(N,z),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F)}C=N}}var V=o(v,t.colormap,S,A);return h?V.tubeScale=h:(0===S&&(S=1),V.tubeScale=.5*u*A/S),V};var u=t(\"./lib/shaders\"),h=t(\"gl-cone3d\").createMesh;e.exports.createTubeMesh=function(t,e){return h(t,e,{shaders:u,traceType:\"streamtube\"})}},{\"./lib/shaders\":314,\"gl-cone3d\":245,\"gl-vec3\":348,\"gl-vec4\":384}],316:[function(t,e,r){var n=t(\"gl-shader\"),a=t(\"glslify\"),i=a([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute vec3 f;\\nattribute vec3 normal;\\n\\nuniform vec3 objectOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 localCoordinate = vec3(uv.zw, f.x);\\n  worldCoordinate = objectOffset + localCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n  vec4 clipPosition = projection * view * worldPosition;\\n  gl_Position = clipPosition;\\n  kill = f.y;\\n  value = f.z;\\n  planeCoordinate = uv.xy;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * worldPosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  lightDirection = lightPosition - cameraCoordinate.xyz;\\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\\n\"]),o=a([\"precision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat beckmannSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform float vertexColor;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  if ((kill > 0.0) ||\\n      (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\\n\\n  vec3 N = normalize(surfaceNormal);\\n  vec3 V = normalize(eyeDirection);\\n  vec3 L = normalize(lightDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  //decide how to interpolate color \\u2014 in vertex or in fragment\\n  vec4 surfaceColor =\\n    step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) +\\n    step(.5, vertexColor) * vColor;\\n\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\\n}\\n\"]),s=a([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute float f;\\n\\nuniform vec3 objectOffset;\\nuniform mat3 permutation;\\nuniform mat4 model, view, projection;\\nuniform float height, zOffset;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 dataCoordinate = permutation * vec3(uv.xy, height);\\n  worldCoordinate = objectOffset + dataCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n\\n  vec4 clipPosition = projection * view * worldPosition;\\n  clipPosition.z += zOffset;\\n\\n  gl_Position = clipPosition;\\n  value = f + objectOffset.z;\\n  kill = -1.0;\\n  planeCoordinate = uv.zw;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Don't do lighting for contours\\n  surfaceNormal   = vec3(1,0,0);\\n  eyeDirection    = vec3(0,1,0);\\n  lightDirection  = vec3(0,0,1);\\n}\\n\"]),l=a([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n  float vh = 255.0 * v;\\n  float upper = floor(vh);\\n  float lower = fract(vh);\\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n  if ((kill > 0.0) ||\\n      (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\\n\\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\\n\"]);r.createShader=function(t){var e=n(t,i,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,i,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,s,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},r.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},{\"gl-shader\":304,glslify:411}],317:[function(t,e,r){arguments[4][113][0].apply(r,arguments)},{dup:113}],318:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=y(e),n=b(e),s=x(e),l=_(e),c=a(e),u=i(e,[{buffer:c,size:4,stride:w,offset:0},{buffer:c,size:3,stride:w,offset:16},{buffer:c,size:3,stride:w,offset:28}]),h=a(e),f=i(e,[{buffer:h,size:4,stride:20,offset:0},{buffer:h,size:1,stride:20,offset:16}]),p=a(e),d=i(e,[{buffer:p,size:2,type:e.FLOAT}]),g=o(e,1,S,e.RGBA,e.UNSIGNED_BYTE);g.minFilter=e.LINEAR,g.magFilter=e.LINEAR;var v=new E(e,[0,0],[[0,0,0],[0,0,0]],r,n,c,u,g,s,l,h,f,p,d,[0,0,0]),m={levels:[[],[],[]]};for(var k in t)m[k]=t[k];return m.colormap=m.colormap||\"jet\",v.update(m),v};var n=t(\"bit-twiddle\"),a=t(\"gl-buffer\"),i=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"typedarray-pool\"),l=t(\"colormap\"),c=t(\"ndarray-ops\"),u=t(\"ndarray-pack\"),h=t(\"ndarray\"),f=t(\"surface-nets\"),p=t(\"gl-mat4/multiply\"),d=t(\"gl-mat4/invert\"),g=t(\"binary-search-bounds\"),v=t(\"ndarray-gradient\"),m=t(\"./lib/shaders\"),y=m.createShader,x=m.createContourShader,b=m.createPickShader,_=m.createPickContourShader,w=40,k=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],T=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],M=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];function A(t,e,r,n,a){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=a}!function(){for(var t=0;t<3;++t){var e=M[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();var S=256;function E(t,e,r,n,a,i,o,l,c,u,f,p,d,g,v){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=v,this.intensityBounds=[],this._shader=n,this._pickShader=a,this._coordinateBuffer=i,this._vao=o,this._colorMap=l,this._contourShader=c,this._contourPickShader=u,this._contourBuffer=f,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new A([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=g,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[h(s.mallocFloat(1024),[0,0]),h(s.mallocFloat(1024),[0,0]),h(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var L=E.prototype;L.isTransparent=function(){return this.opacity<1},L.isOpaque=function(){if(this.opacity>=1)return!0;for(var t=0;t<3;++t)if(this._contourCounts[t].length>0||this._dynamicCounts[t]>0)return!0;return!1},L.pickSlots=1,L.setPickBase=function(t){this.pickId=t};var C=[0,0,0],P={showSurface:!1,showContour:!1,projections:[k.slice(),k.slice(),k.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function O(t,e){var r,n,a,i=e.axes&&e.axes.lastCubeProps.axis||C,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=P.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(i[r]>0)][r],p(l,t.model,l);var c=P.clipBounds[r];for(a=0;a<2;++a)for(n=0;n<3;++n)c[a][n]=t.clipBounds[a][n];c[0][r]=-1e8,c[1][r]=1e8}return P.showSurface=o,P.showContour=s,P}var z={model:k,view:k,projection:k,inverseModel:k.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},I=k.slice(),D=[1,0,0,0,1,0,0,0,1];function R(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=z;n.model=t.model||k,n.view=t.view||k,n.projection=t.projection||k,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var a=0;a<2;++a)for(var i=n.clipBounds[a],o=0;o<3;++o)i[o]=Math.min(Math.max(this.clipBounds[a][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=D,n.vertexColor=this.vertexColor;var s=I;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),a=0;a<3;++a)n.eyePosition[a]=s[12+a]/s[15];var l=s[15];for(a=0;a<3;++a)l+=this.lightPosition[a]*s[4*a+3];for(a=0;a<3;++a){var c=s[12+a];for(o=0;o<3;++o)c+=s[4*o+a]*this.lightPosition[o];n.lightPosition[a]=c/l}var u=O(n,this);if(u.showSurface&&e===this.opacity<1){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),a=0;a<3;++a)this.surfaceProject[a]&&this.vertexCount&&(this._shader.uniforms.model=u.projections[a],this._shader.uniforms.clipBounds=u.clipBounds[a],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(u.showContour&&!e){var h=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,h.bind(),h.uniforms=n;var f=this._contourVAO;for(f.bind(),a=0;a<3;++a)for(h.uniforms.permutation=M[a],r.lineWidth(this.contourWidth[a]*this.pixelRatio),o=0;o<this.contourLevels[a].length;++o)o===this.highlightLevel[a]?(h.uniforms.contourColor=this.highlightColor[a],h.uniforms.contourTint=this.highlightTint[a]):0!==o&&o-1!==this.highlightLevel[a]||(h.uniforms.contourColor=this.contourColor[a],h.uniforms.contourTint=this.contourTint[a]),this._contourCounts[a][o]&&(h.uniforms.height=this.contourLevels[a][o],f.draw(r.LINES,this._contourCounts[a][o],this._contourOffsets[a][o]));for(a=0;a<3;++a)for(h.uniforms.model=u.projections[a],h.uniforms.clipBounds=u.clipBounds[a],o=0;o<3;++o)if(this.contourProject[a][o]){h.uniforms.permutation=M[o],r.lineWidth(this.contourWidth[o]*this.pixelRatio);for(var g=0;g<this.contourLevels[o].length;++g)g===this.highlightLevel[o]?(h.uniforms.contourColor=this.highlightColor[o],h.uniforms.contourTint=this.highlightTint[o]):0!==g&&g-1!==this.highlightLevel[o]||(h.uniforms.contourColor=this.contourColor[o],h.uniforms.contourTint=this.contourTint[o]),this._contourCounts[o][g]&&(h.uniforms.height=this.contourLevels[o][g],f.draw(r.LINES,this._contourCounts[o][g],this._contourOffsets[o][g]))}for(f.unbind(),(f=this._dynamicVAO).bind(),a=0;a<3;++a)if(0!==this._dynamicCounts[a])for(h.uniforms.model=n.model,h.uniforms.clipBounds=n.clipBounds,h.uniforms.permutation=M[a],r.lineWidth(this.dynamicWidth[a]*this.pixelRatio),h.uniforms.contourColor=this.dynamicColor[a],h.uniforms.contourTint=this.dynamicTint[a],h.uniforms.height=this.dynamicLevel[a],f.draw(r.LINES,this._dynamicCounts[a],this._dynamicOffsets[a]),o=0;o<3;++o)this.contourProject[o][a]&&(h.uniforms.model=u.projections[o],h.uniforms.clipBounds=u.clipBounds[o],f.draw(r.LINES,this._dynamicCounts[a],this._dynamicOffsets[a]));f.unbind()}}L.draw=function(t){return R.call(this,t,!1)},L.drawTransparent=function(t){return R.call(this,t,!0)};var F={model:k,view:k,projection:k,inverseModel:k,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,objectOffset:[0,0,0],permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};function B(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function N(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function j(t){if(Array.isArray(t)){if(Array.isArray(t))return[N(t[0]),N(t[1]),N(t[2])];var e=N(t);return[e.slice(),e.slice(),e.slice()]}}L.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=F;r.model=t.model||k,r.view=t.view||k,r.projection=t.projection||k,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.objectOffset=this.objectOffset,r.permutation=D;for(var n=0;n<2;++n)for(var a=r.clipBounds[n],i=0;i<3;++i)a[i]=Math.min(Math.max(this.clipBounds[n][i],-1e8),1e8);var o=O(r,this);if(o.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount),n=0;n<3;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=o.projections[n],this._pickShader.uniforms.clipBounds=o.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(o.showContour){var s=this._contourPickShader;s.bind(),s.uniforms=r;var l=this._contourVAO;for(l.bind(),i=0;i<3;++i)for(e.lineWidth(this.contourWidth[i]*this.pixelRatio),s.uniforms.permutation=M[i],n=0;n<this.contourLevels[i].length;++n)this._contourCounts[i][n]&&(s.uniforms.height=this.contourLevels[i][n],l.draw(e.LINES,this._contourCounts[i][n],this._contourOffsets[i][n]));for(n=0;n<3;++n)for(s.uniforms.model=o.projections[n],s.uniforms.clipBounds=o.clipBounds[n],i=0;i<3;++i)if(this.contourProject[n][i]){s.uniforms.permutation=M[i],e.lineWidth(this.contourWidth[i]*this.pixelRatio);for(var c=0;c<this.contourLevels[i].length;++c)this._contourCounts[i][c]&&(s.uniforms.height=this.contourLevels[i][c],l.draw(e.LINES,this._contourCounts[i][c],this._contourOffsets[i][c]))}l.unbind()}},L.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,a=Math.floor(n),i=n-a,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;a+=1,s+=1;var c=r.position;c[0]=c[1]=c[2]=0;for(var u=0;u<2;++u)for(var h=u?i:1-i,f=0;f<2;++f)for(var p=a+u,d=s+f,v=h*(f?l:1-l),m=0;m<3;++m)c[m]+=this._field[m].get(p,d)*v;for(var y=this._pickResult.level,x=0;x<3;++x)if(y[x]=g.le(this.contourLevels[x],c[x]),y[x]<0)this.contourLevels[x].length>0&&(y[x]=0);else if(y[x]<this.contourLevels[x].length-1){var b=this.contourLevels[x][y[x]],_=this.contourLevels[x][y[x]+1];Math.abs(b-c[x])>Math.abs(_-c[x])&&(y[x]+=1)}for(r.index[0]=i<.5?a:a+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],m=0;m<3;++m)r.dataCoordinate[m]=this._field[m].get(r.index[0],r.index[1]);return r},L.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();c.assign(t.lo(1,1).hi(r[0],r[1]),e),c.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),c.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),c.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),c.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},L.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=B(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=B(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=B(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=j(t.contourColor)),\"contourProject\"in t&&(this.contourProject=B(t.contourProject,function(t){return B(t,Boolean)})),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=j(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=B(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=B(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0);var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var a=(e.shape[0]+2)*(e.shape[1]+2);a>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(a))),this._field[2]=h(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var i=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=h(this._field[o].data,[i[0]+2,i[1]+2]);if(t.coords){var p=t.coords;if(!Array.isArray(p)||3!==p.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var d=p[o];for(b=0;b<2;++b)if(d.shape[b]!==i[b])throw new Error(\"gl-surface: coords have incorrect shape\");this.padField(this._field[o],d)}}else if(t.ticks){var g=t.ticks;if(!Array.isArray(g)||2!==g.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var m=g[o];if((Array.isArray(m)||m.length)&&(m=h(m)),m.shape[0]!==i[o])throw new Error(\"gl-surface: invalid tick length\");var y=h(m.data,i);y.stride[o]=m.stride[0],y.stride[1^o]=0,this.padField(this._field[o],y)}}else{for(o=0;o<2;++o){var x=[0,0];x[o]=1,this._field[o]=h(this._field[o].data,[i[0]+2,i[1]+2],x,0)}this._field[0].set(0,0,0);for(var b=0;b<i[0];++b)this._field[0].set(b+1,0,b);for(this._field[0].set(i[0]+1,0,i[0]-1),this._field[1].set(0,0,0),b=0;b<i[1];++b)this._field[1].set(0,b+1,b);this._field[1].set(0,i[1]+1,i[1]-1)}var _=this._field,w=h(s.mallocFloat(3*_[2].size*2),[3,i[0]+2,i[1]+2,2]);for(o=0;o<3;++o)v(w.pick(o),_[o],\"mirror\");var k=h(s.mallocFloat(3*_[2].size),[i[0]+2,i[1]+2,3]);for(o=0;o<i[0]+2;++o)for(b=0;b<i[1]+2;++b){var M=w.get(0,o,b,0),A=w.get(0,o,b,1),E=w.get(1,o,b,0),L=w.get(1,o,b,1),C=w.get(2,o,b,0),P=w.get(2,o,b,1),O=E*P-L*C,z=C*A-P*M,I=M*L-A*E,D=Math.sqrt(O*O+z*z+I*I);D<1e-8?(D=Math.max(Math.abs(O),Math.abs(z),Math.abs(I)))<1e-8?(I=1,z=O=0,D=1):D=1/D:D=1/Math.sqrt(D),k.set(o,b,0,O*D),k.set(o,b,1,z*D),k.set(o,b,2,I*D)}s.free(w.data);var R=[1/0,1/0,1/0],F=[-1/0,-1/0,-1/0],N=1/0,V=-1/0,U=(i[0]-1)*(i[1]-1)*6,q=s.mallocFloat(n.nextPow2(10*U)),H=0,G=0;for(o=0;o<i[0]-1;++o)t:for(b=0;b<i[1]-1;++b){for(var Y=0;Y<2;++Y)for(var W=0;W<2;++W)for(var X=0;X<3;++X){var Z=this._field[X].get(1+o+Y,1+b+W);if(isNaN(Z)||!isFinite(Z))continue t}for(X=0;X<6;++X){var J=o+T[X][0],K=b+T[X][1],Q=this._field[0].get(J+1,K+1),$=this._field[1].get(J+1,K+1);Z=this._field[2].get(J+1,K+1),O=k.get(J+1,K+1,0),z=k.get(J+1,K+1,1),I=k.get(J+1,K+1,2),t.intensity&&(tt=t.intensity.get(J,K));var tt=t.intensity?t.intensity.get(J,K):Z+this.objectOffset[2];q[H++]=J,q[H++]=K,q[H++]=Q,q[H++]=$,q[H++]=Z,q[H++]=0,q[H++]=tt,q[H++]=O,q[H++]=z,q[H++]=I,R[0]=Math.min(R[0],Q+this.objectOffset[0]),R[1]=Math.min(R[1],$+this.objectOffset[1]),R[2]=Math.min(R[2],Z+this.objectOffset[2]),N=Math.min(N,tt),F[0]=Math.max(F[0],Q+this.objectOffset[0]),F[1]=Math.max(F[1],$+this.objectOffset[1]),F[2]=Math.max(F[2],Z+this.objectOffset[2]),V=Math.max(V,tt),G+=1}}for(t.intensityBounds&&(N=+t.intensityBounds[0],V=+t.intensityBounds[1]),o=6;o<H;o+=10)q[o]=(q[o]-N)/(V-N);this._vertexCount=G,this._coordinateBuffer.update(q.subarray(0,H)),s.freeFloat(q),s.free(k.data),this.bounds=[R,F],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===N&&this.intensityBounds[1]===V||(r=!0),this.intensityBounds=[N,V]}if(\"levels\"in t){var et=t.levels;for(et=Array.isArray(et[0])?et.slice():[[],[],et],o=0;o<3;++o)et[o]=et[o].slice(),et[o].sort(function(t,e){return t-e});for(o=0;o<3;++o)for(b=0;b<et[o].length;++b)et[o][b]-=this.objectOffset[o];t:for(o=0;o<3;++o){if(et[o].length!==this.contourLevels[o].length){r=!0;break}for(b=0;b<et[o].length;++b)if(et[o][b]!==this.contourLevels[o][b]){r=!0;break t}}this.contourLevels=et}if(r){_=this._field,i=this.shape;for(var rt=[],nt=0;nt<3;++nt){var at=this.contourLevels[nt],it=[],ot=[],st=[0,0,0];for(o=0;o<at.length;++o){var lt=f(this._field[nt],at[o]);it.push(rt.length/5|0),G=0;t:for(b=0;b<lt.cells.length;++b){var ct=lt.cells[b];for(X=0;X<2;++X){var ut=lt.positions[ct[X]],ht=ut[0],ft=0|Math.floor(ht),pt=ht-ft,dt=ut[1],gt=0|Math.floor(dt),vt=dt-gt,mt=!1;e:for(var yt=0;yt<3;++yt){st[yt]=0;var xt=(nt+yt+1)%3;for(Y=0;Y<2;++Y){var bt=Y?pt:1-pt;for(J=0|Math.min(Math.max(ft+Y,0),i[0]),W=0;W<2;++W){var _t=W?vt:1-vt;if(K=0|Math.min(Math.max(gt+W,0),i[1]),Z=yt<2?this._field[xt].get(J,K):(this.intensity.get(J,K)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(Z)||isNaN(Z)){mt=!0;break e}var wt=bt*_t;st[yt]+=wt*Z}}}if(mt){if(X>0){for(var kt=0;kt<5;++kt)rt.pop();G-=1}continue t}rt.push(st[0],st[1],ut[0],ut[1],st[2]),G+=1}}ot.push(G)}this._contourOffsets[nt]=it,this._contourCounts[nt]=ot}var Tt=s.mallocFloat(rt.length);for(o=0;o<rt.length;++o)Tt[o]=rt[o];this._contourBuffer.update(Tt),s.freeFloat(Tt)}t.colormap&&this._colorMap.setPixels(function(t){var e=u([l({colormap:t,nshades:S,format:\"rgba\"}).map(function(t){return[t[0],t[1],t[2],255*t[3]]})]);return c.divseq(e,255),e}(t.colormap))},L.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},L.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,a=this.shape,i=s.mallocFloat(12*a[0]*a[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,c=(o+2)%3,u=this._field[o],h=this._field[l],p=this._field[c],d=f(u,r[o]),g=d.cells,v=d.positions;for(this._dynamicOffsets[o]=n,e=0;e<g.length;++e)for(var m=g[e],y=0;y<2;++y){var x=v[m[y]],b=+x[0],_=0|b,w=0|Math.min(_+1,a[0]),k=b-_,T=1-k,M=+x[1],A=0|M,S=0|Math.min(A+1,a[1]),E=M-A,L=1-E,C=T*L,P=T*E,O=k*L,z=k*E,I=C*h.get(_,A)+P*h.get(_,S)+O*h.get(w,A)+z*h.get(w,S),D=C*p.get(_,A)+P*p.get(_,S)+O*p.get(w,A)+z*p.get(w,S);if(isNaN(I)||isNaN(D)){y&&(n-=1);break}i[2*n+0]=I,i[2*n+1]=D,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(i.subarray(0,2*n)),s.freeFloat(i)}}},{\"./lib/shaders\":316,\"binary-search-bounds\":317,\"bit-twiddle\":94,colormap:128,\"gl-buffer\":244,\"gl-mat4/invert\":268,\"gl-mat4/multiply\":270,\"gl-texture2d\":324,\"gl-vao\":329,ndarray:452,\"ndarray-gradient\":443,\"ndarray-ops\":446,\"ndarray-pack\":447,\"surface-nets\":530,\"typedarray-pool\":544}],319:[function(t,e,r){\"use strict\";var n=t(\"css-font\"),a=t(\"pick-by-alias\"),i=t(\"regl\"),o=t(\"gl-util/context\"),s=t(\"es6-weak-map\"),l=t(\"color-normalize\"),c=t(\"font-atlas\"),u=t(\"typedarray-pool\"),h=t(\"parse-rect\"),f=t(\"is-plain-obj\"),p=t(\"parse-unit\"),d=t(\"to-px\"),g=t(\"detect-kerning\"),v=t(\"object-assign\"),m=t(\"font-measure\"),y=t(\"flatten-vertex-data\"),x=t(\"bit-twiddle\").nextPow2,b=new s,_=!1;if(document.body){var w=document.body.appendChild(document.createElement(\"div\"));w.style.font=\"italic small-caps bold condensed 16px/2 cursive\",getComputedStyle(w).fontStretch&&(_=!0),document.body.removeChild(w)}var k=function(t){!function(t){return\"function\"==typeof t&&t._gl&&t.prop&&t.texture&&t.buffer}(t)?this.gl=o(t):(t={regl:t},this.gl=t.regl._gl),this.shader=b.get(this.gl),this.shader?this.regl=this.shader.regl:this.regl=t.regl||i({gl:this.gl}),this.charBuffer=this.regl.buffer({type:\"uint8\",usage:\"stream\"}),this.sizeBuffer=this.regl.buffer({type:\"float\",usage:\"stream\"}),this.shader||(this.shader=this.createShader(),b.set(this.gl,this.shader)),this.batch=[],this.fontSize=[],this.font=[],this.fontAtlas=[],this.draw=this.shader.draw.bind(this),this.render=function(){this.regl._refresh(),this.draw(this.batch)},this.canvas=this.gl.canvas,this.update(f(t)?t:{})};k.prototype.createShader=function(){var t=this.regl,e=t({blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},stencil:{enable:!1},depth:{enable:!1},count:t.prop(\"count\"),offset:t.prop(\"offset\"),attributes:{charOffset:{offset:4,stride:8,buffer:t.this(\"sizeBuffer\")},width:{offset:0,stride:8,buffer:t.this(\"sizeBuffer\")},char:t.this(\"charBuffer\"),position:t.this(\"position\")},uniforms:{atlasSize:function(t,e){return[e.atlas.width,e.atlas.height]},atlasDim:function(t,e){return[e.atlas.cols,e.atlas.rows]},atlas:function(t,e){return e.atlas.texture},charStep:function(t,e){return e.atlas.step},em:function(t,e){return e.atlas.em},color:t.prop(\"color\"),opacity:t.prop(\"opacity\"),viewport:t.this(\"viewportArray\"),scale:t.this(\"scale\"),align:t.prop(\"align\"),baseline:t.prop(\"baseline\"),translate:t.this(\"translate\"),positionOffset:t.prop(\"positionOffset\")},primitive:\"points\",viewport:t.this(\"viewport\"),vert:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tattribute float width, charOffset, char;\\n\\t\\t\\tattribute vec2 position;\\n\\t\\t\\tuniform float fontSize, charStep, em, align, baseline;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tuniform vec4 color;\\n\\t\\t\\tuniform vec2 atlasSize, atlasDim, scale, translate, positionOffset;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\t\"+(k.normalViewport?\"\":\"vec2 positionOffset = vec2(positionOffset.x,- positionOffset.y);\")+\"\\n\\n\\t\\t\\t\\tvec2 offset = floor(em * (vec2(align + charOffset, baseline)\\n\\t\\t\\t\\t\\t+ positionOffset))\\n\\t\\t\\t\\t\\t/ (viewport.zw * scale.xy);\\n\\n\\t\\t\\t\\tvec2 position = (position + translate) * scale;\\n\\t\\t\\t\\tposition += offset * scale;\\n\\n\\t\\t\\t\\t\"+(k.normalViewport?\"position.y = 1. - position.y;\":\"\")+\"\\n\\n\\t\\t\\t\\tcharCoord = position * viewport.zw + viewport.xy;\\n\\n\\t\\t\\t\\tgl_Position = vec4(position * 2. - 1., 0, 1);\\n\\n\\t\\t\\t\\tgl_PointSize = charStep;\\n\\n\\t\\t\\t\\tcharId.x = mod(char, atlasDim.x);\\n\\t\\t\\t\\tcharId.y = floor(char / atlasDim.x);\\n\\n\\t\\t\\t\\tcharWidth = width * em;\\n\\n\\t\\t\\t\\tfontColor = color / 255.;\\n\\t\\t\\t}\",frag:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tuniform sampler2D atlas;\\n\\t\\t\\tuniform float fontSize, charStep, opacity;\\n\\t\\t\\tuniform vec2 atlasSize;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\n\\t\\t\\tfloat lightness(vec4 color) {\\n\\t\\t\\t\\treturn color.r * 0.299 + color.g * 0.587 + color.b * 0.114;\\n\\t\\t\\t}\\n\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\tvec2 uv = gl_FragCoord.xy - charCoord + charStep * .5;\\n\\t\\t\\t\\tfloat halfCharStep = floor(charStep * .5 + .5);\\n\\n\\t\\t\\t\\t// invert y and shift by 1px (FF expecially needs that)\\n\\t\\t\\t\\tuv.y = charStep - uv.y;\\n\\n\\t\\t\\t\\t// ignore points outside of character bounding box\\n\\t\\t\\t\\tfloat halfCharWidth = ceil(charWidth * .5);\\n\\t\\t\\t\\tif (floor(uv.x) > halfCharStep + halfCharWidth ||\\n\\t\\t\\t\\t\\tfloor(uv.x) < halfCharStep - halfCharWidth) return;\\n\\n\\t\\t\\t\\tuv += charId * charStep;\\n\\t\\t\\t\\tuv = uv / atlasSize;\\n\\n\\t\\t\\t\\tvec4 color = fontColor;\\n\\t\\t\\t\\tvec4 mask = texture2D(atlas, uv);\\n\\n\\t\\t\\t\\tfloat maskY = lightness(mask);\\n\\t\\t\\t\\t// float colorY = lightness(color);\\n\\t\\t\\t\\tcolor.a *= maskY;\\n\\t\\t\\t\\tcolor.a *= opacity;\\n\\n\\t\\t\\t\\t// color.a += .1;\\n\\n\\t\\t\\t\\t// antialiasing, see yiq color space y-channel formula\\n\\t\\t\\t\\t// color.rgb += (1. - color.rgb) * (1. - mask.rgb);\\n\\n\\t\\t\\t\\tgl_FragColor = color;\\n\\t\\t\\t}\"});return{regl:t,draw:e,atlas:{}}},k.prototype.update=function(t){var e=this;if(\"string\"==typeof t)t={text:t};else if(!t)return;null!=(t=a(t,{position:\"position positions coord coords coordinates\",font:\"font fontFace fontface typeface cssFont css-font family fontFamily\",fontSize:\"fontSize fontsize size font-size\",text:\"text texts chars characters value values symbols\",align:\"align alignment textAlign textbaseline\",baseline:\"baseline textBaseline textbaseline\",direction:\"dir direction textDirection\",color:\"color colour fill fill-color fillColor textColor textcolor\",kerning:\"kerning kern\",range:\"range dataBox\",viewport:\"vp viewport viewBox viewbox viewPort\",opacity:\"opacity alpha transparency visible visibility opaque\",offset:\"offset positionOffset padding shift indent indentation\"},!0)).opacity&&(Array.isArray(t.opacity)?this.opacity=t.opacity.map(function(t){return parseFloat(t)}):this.opacity=parseFloat(t.opacity)),null!=t.viewport&&(this.viewport=h(t.viewport),k.normalViewport&&(this.viewport.y=this.canvas.height-this.viewport.y-this.viewport.height),this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null==this.viewport&&(this.viewport={x:0,y:0,width:this.gl.drawingBufferWidth,height:this.gl.drawingBufferHeight},this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null!=t.kerning&&(this.kerning=t.kerning),null!=t.offset&&(\"number\"==typeof t.offset&&(t.offset=[t.offset,0]),this.positionOffset=y(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),this.font.length||t.font||(t.font=k.baseFontSize+\"px sans-serif\");var r,i=!1,o=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach(function(t,r){if(\"string\"==typeof t)try{t=n.parse(t)}catch(e){t=n.parse(k.baseFontSize+\"px \"+t)}else t=n.parse(n.stringify(t));var a=n.stringify({size:k.baseFontSize,family:t.family,stretch:_?t.stretch:void 0,variant:t.variant,weight:t.weight,style:t.style}),s=p(t.size),l=Math.round(s[0]*d(s[1]));if(l!==e.fontSize[r]&&(o=!0,e.fontSize[r]=l),!(e.font[r]&&a==e.font[r].baseString||(i=!0,e.font[r]=k.fonts[a],e.font[r]))){var c=t.family.join(\", \"),u=[t.style];t.style!=t.variant&&u.push(t.variant),t.variant!=t.weight&&u.push(t.weight),_&&t.weight!=t.stretch&&u.push(t.stretch),e.font[r]={baseString:a,family:c,weight:t.weight,stretch:t.stretch,style:t.style,variant:t.variant,width:{},kerning:{},metrics:m(c,{origin:\"top\",fontSize:k.baseFontSize,fontStyle:u.join(\" \")})},k.fonts[a]=e.font[r]}}),(i||o)&&this.font.forEach(function(r,a){var i=n.stringify({size:e.fontSize[a],family:r.family,stretch:_?r.stretch:void 0,variant:r.variant,weight:r.weight,style:r.style});if(e.fontAtlas[a]=e.shader.atlas[i],!e.fontAtlas[a]){var o=r.metrics;e.shader.atlas[i]=e.fontAtlas[a]={fontString:i,step:2*Math.ceil(e.fontSize[a]*o.bottom*.5),em:e.fontSize[a],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:e.regl.texture()}}null==t.text&&(t.text=e.text)}),\"string\"==typeof t.text&&t.position&&t.position.length>2){for(var s=Array(.5*t.position.length),f=0;f<s.length;f++)s[f]=t.text;t.text=s}if(null!=t.text||i){if(this.textOffsets=[0],Array.isArray(t.text)){this.count=t.text[0].length,this.counts=[this.count];for(var b=1;b<t.text.length;b++)this.textOffsets[b]=this.textOffsets[b-1]+t.text[b-1].length,this.count+=t.text[b].length,this.counts.push(t.text[b].length);this.text=t.text.join(\"\")}else this.text=t.text,this.count=this.text.length,this.counts=[this.count];r=[],this.font.forEach(function(t,n){k.atlasContext.font=t.baseString;for(var a=e.fontAtlas[n],i=0;i<e.text.length;i++){var o=e.text.charAt(i);if(null==a.ids[o]&&(a.ids[o]=a.chars.length,a.chars.push(o),r.push(o)),null==t.width[o]&&(t.width[o]=k.atlasContext.measureText(o).width/k.baseFontSize,e.kerning)){var s=[];for(var l in t.width)s.push(l+o,o+l);v(t.kerning,g(t.family,{pairs:s}))}}})}if(t.position)if(t.position.length>2){for(var w=!t.position[0].length,T=u.mallocFloat(2*this.count),M=0,A=0;M<this.counts.length;M++){var S=this.counts[M];if(w)for(var E=0;E<S;E++)T[A++]=t.position[2*M],T[A++]=t.position[2*M+1];else for(var L=0;L<S;L++)T[A++]=t.position[M][0],T[A++]=t.position[M][1]}this.position.call?this.position({type:\"float\",data:T}):this.position=this.regl.buffer({type:\"float\",data:T}),u.freeFloat(T)}else this.position.destroy&&this.position.destroy(),this.position={constant:t.position};if(t.text||i){var C=u.mallocUint8(this.count),P=u.mallocFloat(2*this.count);this.textWidth=[];for(var O=0,z=0;O<this.counts.length;O++){for(var I=this.counts[O],D=this.font[O]||this.font[0],R=this.fontAtlas[O]||this.fontAtlas[0],F=0;F<I;F++){var B=this.text.charAt(z),N=this.text.charAt(z-1);if(C[z]=R.ids[B],P[2*z]=D.width[B],F){var j=P[2*z-2],V=P[2*z],U=P[2*z-1]+.5*j+.5*V;if(this.kerning){var q=D.kerning[N+B];q&&(U+=.001*q)}P[2*z+1]=U}else P[2*z+1]=.5*P[2*z];z++}this.textWidth.push(P.length?.5*P[2*z-2]+P[2*z-1]:0)}t.align||(t.align=this.align),this.charBuffer({data:C,type:\"uint8\",usage:\"stream\"}),this.sizeBuffer({data:P,type:\"float\",usage:\"stream\"}),u.freeUint8(C),u.freeFloat(P),r.length&&this.font.forEach(function(t,r){var n=e.fontAtlas[r],a=n.step,i=Math.floor(k.maxAtlasSize/a),o=Math.min(i,n.chars.length),s=Math.ceil(n.chars.length/o),l=x(o*a),u=x(s*a);n.width=l,n.height=u,n.rows=s,n.cols=o,n.em&&n.texture({data:c({canvas:k.atlasCanvas,font:n.fontString,chars:n.chars,shape:[l,u],step:[a,a]})})})}if(t.align&&(this.align=t.align,this.alignOffset=this.textWidth.map(function(t,r){var n=Array.isArray(e.align)?e.align.length>1?e.align[r]:e.align[0]:e.align;if(\"number\"==typeof n)return n;switch(n){case\"right\":case\"end\":return-t;case\"center\":case\"centre\":case\"middle\":return.5*-t}return 0})),null==this.baseline&&null==t.baseline&&(t.baseline=0),null!=t.baseline&&(this.baseline=t.baseline,Array.isArray(this.baseline)||(this.baseline=[this.baseline]),this.baselineOffset=this.baseline.map(function(t,r){var n=(e.font[r]||e.font[0]).metrics,a=0;return a+=.5*n.bottom,a+=\"number\"==typeof t?t-n.baseline:-n[t],k.normalViewport||(a*=-1),a})),null!=t.color)if(t.color||(t.color=\"transparent\"),\"string\"!=typeof t.color&&isNaN(t.color)){var H;if(\"number\"==typeof t.color[0]&&t.color.length>this.counts.length){var G=t.color.length;H=u.mallocUint8(G);for(var Y=(t.color.subarray||t.color.slice).bind(t.color),W=0;W<G;W+=4)H.set(l(Y(W,W+4),\"uint8\"),W)}else{var X=t.color.length;H=u.mallocUint8(4*X);for(var Z=0;Z<X;Z++)H.set(l(t.color[Z]||0,\"uint8\"),4*Z)}this.color=H}else this.color=l(t.color,\"uint8\");if(t.position||t.text||t.color||t.baseline||t.align||t.font||t.offset||t.opacity)if(this.color.length>4||this.baselineOffset.length>1||this.align&&this.align.length>1||this.fontAtlas.length>1||this.positionOffset.length>2){var J=Math.max(.5*this.position.length||0,.25*this.color.length||0,this.baselineOffset.length||0,this.alignOffset.length||0,this.font.length||0,this.opacity.length||0,.5*this.positionOffset.length||0);this.batch=Array(J);for(var K=0;K<this.batch.length;K++)this.batch[K]={count:this.counts.length>1?this.counts[K]:this.counts[0],offset:this.textOffsets.length>1?this.textOffsets[K]:this.textOffsets[0],color:this.color?this.color.length<=4?this.color:this.color.subarray(4*K,4*K+4):[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[K]:this.opacity,baseline:null!=this.baselineOffset[K]?this.baselineOffset[K]:this.baselineOffset[0],align:this.align?null!=this.alignOffset[K]?this.alignOffset[K]:this.alignOffset[0]:0,atlas:this.fontAtlas[K]||this.fontAtlas[0],positionOffset:this.positionOffset.length>2?this.positionOffset.subarray(2*K,2*K+2):this.positionOffset}}else this.count?this.batch=[{count:this.count,offset:0,color:this.color||[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[0]:this.opacity,baseline:this.baselineOffset[0],align:this.alignOffset?this.alignOffset[0]:0,atlas:this.fontAtlas[0],positionOffset:this.positionOffset}]:this.batch=[]},k.prototype.destroy=function(){},k.prototype.kerning=!0,k.prototype.position={constant:new Float32Array(2)},k.prototype.translate=null,k.prototype.scale=null,k.prototype.font=null,k.prototype.text=\"\",k.prototype.positionOffset=[0,0],k.prototype.opacity=1,k.prototype.color=new Uint8Array([0,0,0,255]),k.prototype.alignOffset=[0,0],k.normalViewport=!1,k.maxAtlasSize=1024,k.atlasCanvas=document.createElement(\"canvas\"),k.atlasContext=k.atlasCanvas.getContext(\"2d\",{alpha:!1}),k.baseFontSize=64,k.fonts={},e.exports=k},{\"bit-twiddle\":94,\"color-normalize\":122,\"css-font\":141,\"detect-kerning\":168,\"es6-weak-map\":320,\"flatten-vertex-data\":230,\"font-atlas\":231,\"font-measure\":232,\"gl-util/context\":325,\"is-plain-obj\":424,\"object-assign\":456,\"parse-rect\":461,\"parse-unit\":463,\"pick-by-alias\":467,regl:501,\"to-px\":538,\"typedarray-pool\":544}],320:[function(t,e,r){\"use strict\";e.exports=t(\"./is-implemented\")()?WeakMap:t(\"./polyfill\")},{\"./is-implemented\":321,\"./polyfill\":323}],321:[function(t,e,r){\"use strict\";e.exports=function(){var t,e;if(\"function\"!=typeof WeakMap)return!1;try{t=new WeakMap([[e={},\"one\"],[{},\"two\"],[{},\"three\"]])}catch(t){return!1}return\"[object WeakMap]\"===String(t)&&(\"function\"==typeof t.set&&(t.set({},1)===t&&(\"function\"==typeof t.delete&&(\"function\"==typeof t.has&&\"one\"===t.get(e)))))}},{}],322:[function(t,e,r){\"use strict\";e.exports=\"function\"==typeof WeakMap&&\"[object WeakMap]\"===Object.prototype.toString.call(new WeakMap)},{}],323:[function(t,e,r){\"use strict\";var n,a=t(\"es5-ext/object/is-value\"),i=t(\"es5-ext/object/set-prototype-of\"),o=t(\"es5-ext/object/valid-object\"),s=t(\"es5-ext/object/valid-value\"),l=t(\"es5-ext/string/random-uniq\"),c=t(\"d\"),u=t(\"es6-iterator/get\"),h=t(\"es6-iterator/for-of\"),f=t(\"es6-symbol\").toStringTag,p=t(\"./is-native-implemented\"),d=Array.isArray,g=Object.defineProperty,v=Object.prototype.hasOwnProperty,m=Object.getPrototypeOf;e.exports=n=function(){var t,e=arguments[0];if(!(this instanceof n))throw new TypeError(\"Constructor requires 'new'\");return t=p&&i&&WeakMap!==n?i(new WeakMap,m(this)):this,a(e)&&(d(e)||(e=u(e))),g(t,\"__weakMapData__\",c(\"c\",\"$weakMap$\"+l())),e?(h(e,function(e){s(e),t.set(e[0],e[1])}),t):t},p&&(i&&i(n,WeakMap),n.prototype=Object.create(WeakMap.prototype,{constructor:c(n)})),Object.defineProperties(n.prototype,{delete:c(function(t){return!!v.call(o(t),this.__weakMapData__)&&(delete t[this.__weakMapData__],!0)}),get:c(function(t){if(v.call(o(t),this.__weakMapData__))return t[this.__weakMapData__]}),has:c(function(t){return v.call(o(t),this.__weakMapData__)}),set:c(function(t,e){return g(o(t),this.__weakMapData__,c(\"c\",e)),this}),toString:c(function(){return\"[object WeakMap]\"})}),g(n.prototype,f,c(\"c\",\"WeakMap\"))},{\"./is-native-implemented\":322,d:153,\"es5-ext/object/is-value\":197,\"es5-ext/object/set-prototype-of\":203,\"es5-ext/object/valid-object\":207,\"es5-ext/object/valid-value\":208,\"es5-ext/string/random-uniq\":213,\"es6-iterator/for-of\":215,\"es6-iterator/get\":216,\"es6-symbol\":222}],324:[function(t,e,r){\"use strict\";var n=t(\"ndarray\"),a=t(\"ndarray-ops\"),i=t(\"typedarray-pool\");e.exports=function(t){if(arguments.length<=1)throw new Error(\"gl-texture2d: Missing arguments for texture2d constructor\");o||function(t){o=[t.LINEAR,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_NEAREST],s=[t.NEAREST,t.LINEAR,t.NEAREST_MIPMAP_NEAREST,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_LINEAR],l=[t.REPEAT,t.CLAMP_TO_EDGE,t.MIRRORED_REPEAT]}(t);if(\"number\"==typeof arguments[1])return v(t,arguments[1],arguments[2],arguments[3]||t.RGBA,arguments[4]||t.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return v(t,0|arguments[1][0],0|arguments[1][1],arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(\"object\"==typeof arguments[1]){var e=arguments[1],r=c(e)?e:e.raw;if(r)return function(t,e,r,n,a,i){var o=g(t);return t.texImage2D(t.TEXTURE_2D,0,a,a,i,e),new f(t,o,r,n,a,i)}(t,r,0|e.width,0|e.height,arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(e.shape&&e.data&&e.stride)return function(t,e){var r=e.dtype,o=e.shape.slice(),s=t.getParameter(t.MAX_TEXTURE_SIZE);if(o[0]<0||o[0]>s||o[1]<0||o[1]>s)throw new Error(\"gl-texture2d: Invalid texture size\");var l=d(o,e.stride.slice()),c=0;\"float32\"===r?c=t.FLOAT:\"float64\"===r?(c=t.FLOAT,l=!1,r=\"float32\"):\"uint8\"===r?c=t.UNSIGNED_BYTE:(c=t.UNSIGNED_BYTE,l=!1,r=\"uint8\");var h,p,v=0;if(2===o.length)v=t.LUMINANCE,o=[o[0],o[1],1],e=n(e.data,o,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==o.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===o[2])v=t.ALPHA;else if(2===o[2])v=t.LUMINANCE_ALPHA;else if(3===o[2])v=t.RGB;else{if(4!==o[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");v=t.RGBA}}c!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(c=t.UNSIGNED_BYTE,l=!1);var m=e.size;if(l)h=0===e.offset&&e.data.length===m?e.data:e.data.subarray(e.offset,e.offset+m);else{var y=[o[2],o[2]*o[0],1];p=i.malloc(m,r);var x=n(p,o,y,0);\"float32\"!==r&&\"float64\"!==r||c!==t.UNSIGNED_BYTE?a.assign(x,e):u(x,e),h=p.subarray(0,m)}var b=g(t);t.texImage2D(t.TEXTURE_2D,0,v,o[0],o[1],0,v,c,h),l||i.free(p);return new f(t,b,o[0],o[1],v,c)}(t,e)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")};var o=null,s=null,l=null;function c(t){return\"undefined\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\"undefined\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\"undefined\"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement||\"undefined\"!=typeof ImageData&&t instanceof ImageData}var u=function(t,e){a.muls(t,e,255)};function h(t,e,r){var n=t.gl,a=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>a||r<0||r>a)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function f(t,e,r,n,a,i){this.gl=t,this.handle=e,this.format=a,this.type=i,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}var p=f.prototype;function d(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function g(t){var e=t.createTexture();return t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function v(t,e,r,n,a){var i=t.getParameter(t.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture shape\");if(a===t.FLOAT&&!t.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var o=g(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,a,null),new f(t,o,e,r,n,a)}Object.defineProperties(p,{minFilter:{get:function(){return this._minFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,t),this._minFilter=t}},magFilter:{get:function(){return this._magFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,t),this._magFilter=t}},mipSamples:{get:function(){return this._anisoSamples},set:function(t){var e=this._anisoSamples;if(this._anisoSamples=0|Math.max(t,1),e!==this._anisoSamples){var r=this.gl.getExtension(\"EXT_texture_filter_anisotropic\");r&&this.gl.texParameterf(this.gl.TEXTURE_2D,r.TEXTURE_MAX_ANISOTROPY_EXT,this._anisoSamples)}return this._anisoSamples}},wrapS:{get:function(){return this._wrapS},set:function(t){if(this.bind(),l.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_S,t),this._wrapS=t}},wrapT:{get:function(){return this._wrapT},set:function(t){if(this.bind(),l.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_T,t),this._wrapT=t}},wrap:{get:function(){return this._wrapVector},set:function(t){if(Array.isArray(t)||(t=[t,t]),2!==t.length)throw new Error(\"gl-texture2d: Must specify wrap mode for rows and columns\");for(var e=0;e<2;++e)if(l.indexOf(t[e])<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);this._wrapS=t[0],this._wrapT=t[1];var r=this.gl;return this.bind(),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_S,this._wrapS),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_T,this._wrapT),t}},shape:{get:function(){return this._shapeVector},set:function(t){if(Array.isArray(t)){if(2!==t.length)throw new Error(\"gl-texture2d: Invalid texture shape\")}else t=[0|t,0|t];return h(this,0|t[0],0|t[1]),[0|t[0],0|t[1]]}},width:{get:function(){return this._shape[0]},set:function(t){return h(this,t|=0,this._shape[1]),t}},height:{get:function(){return this._shape[1]},set:function(t){return t|=0,h(this,this._shape[0],t),t}}}),p.bind=function(t){var e=this.gl;return void 0!==t&&e.activeTexture(e.TEXTURE0+(0|t)),e.bindTexture(e.TEXTURE_2D,this.handle),void 0!==t?0|t:e.getParameter(e.ACTIVE_TEXTURE)-e.TEXTURE0},p.dispose=function(){this.gl.deleteTexture(this.handle)},p.generateMipmap=function(){this.bind(),this.gl.generateMipmap(this.gl.TEXTURE_2D);for(var t=Math.min(this._shape[0],this._shape[1]),e=0;t>0;++e,t>>>=1)this._mipLevels.indexOf(e)<0&&this._mipLevels.push(e)},p.setPixels=function(t,e,r,o){var s=this.gl;this.bind(),Array.isArray(e)?(o=r,r=0|e[1],e=0|e[0]):(e=e||0,r=r||0),o=o||0;var l=c(t)?t:t.raw;if(l){this._mipLevels.indexOf(o)<0?(s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,this.type,l),this._mipLevels.push(o)):s.texSubImage2D(s.TEXTURE_2D,o,e,r,this.format,this.type,l)}else{if(!(t.shape&&t.stride&&t.data))throw new Error(\"gl-texture2d: Unsupported data type\");if(t.shape.length<2||e+t.shape[1]>this._shape[1]>>>o||r+t.shape[0]>this._shape[0]>>>o||e<0||r<0)throw new Error(\"gl-texture2d: Texture dimensions are out of bounds\");!function(t,e,r,o,s,l,c,h){var f=h.dtype,p=h.shape.slice();if(p.length<2||p.length>3)throw new Error(\"gl-texture2d: Invalid ndarray, must be 2d or 3d\");var g=0,v=0,m=d(p,h.stride.slice());\"float32\"===f?g=t.FLOAT:\"float64\"===f?(g=t.FLOAT,m=!1,f=\"float32\"):\"uint8\"===f?g=t.UNSIGNED_BYTE:(g=t.UNSIGNED_BYTE,m=!1,f=\"uint8\");if(2===p.length)v=t.LUMINANCE,p=[p[0],p[1],1],h=n(h.data,p,[h.stride[0],h.stride[1],1],h.offset);else{if(3!==p.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===p[2])v=t.ALPHA;else if(2===p[2])v=t.LUMINANCE_ALPHA;else if(3===p[2])v=t.RGB;else{if(4!==p[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");v=t.RGBA}p[2]}v!==t.LUMINANCE&&v!==t.ALPHA||s!==t.LUMINANCE&&s!==t.ALPHA||(v=s);if(v!==s)throw new Error(\"gl-texture2d: Incompatible texture format for setPixels\");var y=h.size,x=c.indexOf(o)<0;x&&c.push(o);if(g===l&&m)0===h.offset&&h.data.length===y?x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,h.data):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,h.data):x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,h.data.subarray(h.offset,h.offset+y)):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,h.data.subarray(h.offset,h.offset+y));else{var b;b=l===t.FLOAT?i.mallocFloat32(y):i.mallocUint8(y);var _=n(b,p,[p[2],p[2]*p[0],1]);g===t.FLOAT&&l===t.UNSIGNED_BYTE?u(_,h):a.assign(_,h),x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,b.subarray(0,y)):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,b.subarray(0,y)),l===t.FLOAT?i.freeFloat32(b):i.freeUint8(b)}}(s,e,r,o,this.format,this.type,this._mipLevels,t)}}},{ndarray:452,\"ndarray-ops\":446,\"typedarray-pool\":544}],325:[function(t,e,r){(function(r){\"use strict\";var n=t(\"pick-by-alias\");function a(t){if(t.container)if(t.container==document.body)document.body.style.width||(t.canvas.width=t.width||t.pixelRatio*r.innerWidth),document.body.style.height||(t.canvas.height=t.height||t.pixelRatio*r.innerHeight);else{var e=t.container.getBoundingClientRect();t.canvas.width=t.width||e.right-e.left,t.canvas.height=t.height||e.bottom-e.top}}function i(t){return\"function\"==typeof t.getContext&&\"width\"in t&&\"height\"in t}function o(){var t=document.createElement(\"canvas\");return t.style.position=\"absolute\",t.style.top=0,t.style.left=0,t}e.exports=function(t){var e;if(t?\"string\"==typeof t&&(t={container:t}):t={},i(t)?t={container:t}:t=\"string\"==typeof(e=t).nodeName&&\"function\"==typeof e.appendChild&&\"function\"==typeof e.getBoundingClientRect?{container:t}:function(t){return\"function\"==typeof t.drawArrays||\"function\"==typeof t.drawElements}(t)?{gl:t}:n(t,{container:\"container target element el canvas holder parent parentNode wrapper use ref root node\",gl:\"gl context webgl glContext\",attrs:\"attributes attrs contextAttributes\",pixelRatio:\"pixelRatio pxRatio px ratio pxratio pixelratio\",width:\"w width\",height:\"h height\"},!0),t.pixelRatio||(t.pixelRatio=r.pixelRatio||1),t.gl)return t.gl;if(t.canvas&&(t.container=t.canvas.parentNode),t.container){if(\"string\"==typeof t.container){var s=document.querySelector(t.container);if(!s)throw Error(\"Element \"+t.container+\" is not found\");t.container=s}i(t.container)?(t.canvas=t.container,t.container=t.canvas.parentNode):t.canvas||(t.canvas=o(),t.container.appendChild(t.canvas),a(t))}else if(!t.canvas){if(\"undefined\"==typeof document)throw Error(\"Not DOM environment. Use headless-gl.\");t.container=document.body||document.documentElement,t.canvas=o(),t.container.appendChild(t.canvas),a(t)}if(!t.gl)try{t.gl=t.canvas.getContext(\"webgl\",t.attrs)}catch(e){try{t.gl=t.canvas.getContext(\"experimental-webgl\",t.attrs)}catch(e){t.gl=t.canvas.getContext(\"webgl-experimental\",t.attrs)}}return t.gl}}).call(this,\"undefined\"!=typeof global?global:\"undefined\"!=typeof self?self:\"undefined\"!=typeof window?window:{})},{\"pick-by-alias\":467}],326:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){e?e.bind():t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,null);var n=0|t.getParameter(t.MAX_VERTEX_ATTRIBS);if(r){if(r.length>n)throw new Error(\"gl-vao: Too many vertex attributes\");for(var a=0;a<r.length;++a){var i=r[a];if(i.buffer){var o=i.buffer,s=i.size||4,l=i.type||t.FLOAT,c=!!i.normalized,u=i.stride||0,h=i.offset||0;o.bind(),t.enableVertexAttribArray(a),t.vertexAttribPointer(a,s,l,c,u,h)}else{if(\"number\"==typeof i)t.vertexAttrib1f(a,i);else if(1===i.length)t.vertexAttrib1f(a,i[0]);else if(2===i.length)t.vertexAttrib2f(a,i[0],i[1]);else if(3===i.length)t.vertexAttrib3f(a,i[0],i[1],i[2]);else{if(4!==i.length)throw new Error(\"gl-vao: Invalid vertex attribute\");t.vertexAttrib4f(a,i[0],i[1],i[2],i[3])}t.disableVertexAttribArray(a)}}for(;a<n;++a)t.disableVertexAttribArray(a)}else for(t.bindBuffer(t.ARRAY_BUFFER,null),a=0;a<n;++a)t.disableVertexAttribArray(a)}},{}],327:[function(t,e,r){\"use strict\";var n=t(\"./do-bind.js\");function a(t){this.gl=t,this._elements=null,this._attributes=null,this._elementsType=t.UNSIGNED_SHORT}a.prototype.bind=function(){n(this.gl,this._elements,this._attributes)},a.prototype.update=function(t,e,r){this._elements=e,this._attributes=t,this._elementsType=r||this.gl.UNSIGNED_SHORT},a.prototype.dispose=function(){},a.prototype.unbind=function(){},a.prototype.draw=function(t,e,r){r=r||0;var n=this.gl;this._elements?n.drawElements(t,e,this._elementsType,r):n.drawArrays(t,r,e)},e.exports=function(t){return new a(t)}},{\"./do-bind.js\":326}],328:[function(t,e,r){\"use strict\";var n=t(\"./do-bind.js\");function a(t,e,r,n,a,i){this.location=t,this.dimension=e,this.a=r,this.b=n,this.c=a,this.d=i}function i(t,e,r){this.gl=t,this._ext=e,this.handle=r,this._attribs=[],this._useElements=!1,this._elementsType=t.UNSIGNED_SHORT}a.prototype.bind=function(t){switch(this.dimension){case 1:t.vertexAttrib1f(this.location,this.a);break;case 2:t.vertexAttrib2f(this.location,this.a,this.b);break;case 3:t.vertexAttrib3f(this.location,this.a,this.b,this.c);break;case 4:t.vertexAttrib4f(this.location,this.a,this.b,this.c,this.d)}},i.prototype.bind=function(){this._ext.bindVertexArrayOES(this.handle);for(var t=0;t<this._attribs.length;++t)this._attribs[t].bind(this.gl)},i.prototype.unbind=function(){this._ext.bindVertexArrayOES(null)},i.prototype.dispose=function(){this._ext.deleteVertexArrayOES(this.handle)},i.prototype.update=function(t,e,r){if(this.bind(),n(this.gl,e,t),this.unbind(),this._attribs.length=0,t)for(var i=0;i<t.length;++i){var o=t[i];\"number\"==typeof o?this._attribs.push(new a(i,1,o)):Array.isArray(o)&&this._attribs.push(new a(i,o.length,o[0],o[1],o[2],o[3]))}this._useElements=!!e,this._elementsType=r||this.gl.UNSIGNED_SHORT},i.prototype.draw=function(t,e,r){r=r||0;var n=this.gl;this._useElements?n.drawElements(t,e,this._elementsType,r):n.drawArrays(t,r,e)},e.exports=function(t,e){return new i(t,e,e.createVertexArrayOES())}},{\"./do-bind.js\":326}],329:[function(t,e,r){\"use strict\";var n=t(\"./lib/vao-native.js\"),a=t(\"./lib/vao-emulated.js\");function i(t){this.bindVertexArrayOES=t.bindVertexArray.bind(t),this.createVertexArrayOES=t.createVertexArray.bind(t),this.deleteVertexArrayOES=t.deleteVertexArray.bind(t)}e.exports=function(t,e,r,o){var s,l=t.createVertexArray?new i(t):t.getExtension(\"OES_vertex_array_object\");return(s=l?n(t,l):a(t)).update(e,r,o),s}},{\"./lib/vao-emulated.js\":327,\"./lib/vao-native.js\":328}],330:[function(t,e,r){e.exports=function(t,e,r){return t[0]=e[0]+r[0],t[1]=e[1]+r[1],t[2]=e[2]+r[2],t}},{}],331:[function(t,e,r){e.exports=function(t,e){var r=n(t[0],t[1],t[2]),o=n(e[0],e[1],e[2]);a(r,r),a(o,o);var s=i(r,o);return s>1?0:Math.acos(s)};var n=t(\"./fromValues\"),a=t(\"./normalize\"),i=t(\"./dot\")},{\"./dot\":341,\"./fromValues\":347,\"./normalize\":358}],332:[function(t,e,r){e.exports=function(t,e){return t[0]=Math.ceil(e[0]),t[1]=Math.ceil(e[1]),t[2]=Math.ceil(e[2]),t}},{}],333:[function(t,e,r){e.exports=function(t){var e=new Float32Array(3);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e}},{}],334:[function(t,e,r){e.exports=function(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}},{}],335:[function(t,e,r){e.exports=function(){var t=new Float32Array(3);return t[0]=0,t[1]=0,t[2]=0,t}},{}],336:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],a=e[1],i=e[2],o=r[0],s=r[1],l=r[2];return t[0]=a*l-i*s,t[1]=i*o-n*l,t[2]=n*s-a*o,t}},{}],337:[function(t,e,r){e.exports=t(\"./distance\")},{\"./distance\":338}],338:[function(t,e,r){e.exports=function(t,e){var r=e[0]-t[0],n=e[1]-t[1],a=e[2]-t[2];return Math.sqrt(r*r+n*n+a*a)}},{}],339:[function(t,e,r){e.exports=t(\"./divide\")},{\"./divide\":340}],340:[function(t,e,r){e.exports=function(t,e,r){return t[0]=e[0]/r[0],t[1]=e[1]/r[1],t[2]=e[2]/r[2],t}},{}],341:[function(t,e,r){e.exports=function(t,e){return t[0]*e[0]+t[1]*e[1]+t[2]*e[2]}},{}],342:[function(t,e,r){e.exports=1e-6},{}],343:[function(t,e,r){e.exports=function(t,e){var r=t[0],a=t[1],i=t[2],o=e[0],s=e[1],l=e[2];return Math.abs(r-o)<=n*Math.max(1,Math.abs(r),Math.abs(o))&&Math.abs(a-s)<=n*Math.max(1,Math.abs(a),Math.abs(s))&&Math.abs(i-l)<=n*Math.max(1,Math.abs(i),Math.abs(l))};var n=t(\"./epsilon\")},{\"./epsilon\":342}],344:[function(t,e,r){e.exports=function(t,e){return t[0]===e[0]&&t[1]===e[1]&&t[2]===e[2]}},{}],345:[function(t,e,r){e.exports=function(t,e){return t[0]=Math.floor(e[0]),t[1]=Math.floor(e[1]),t[2]=Math.floor(e[2]),t}},{}],346:[function(t,e,r){e.exports=function(t,e,r,a,i,o){var s,l;e||(e=3);r||(r=0);l=a?Math.min(a*e+r,t.length):t.length;for(s=r;s<l;s+=e)n[0]=t[s],n[1]=t[s+1],n[2]=t[s+2],i(n,n,o),t[s]=n[0],t[s+1]=n[1],t[s+2]=n[2];return t};var n=t(\"./create\")()},{\"./create\":335}],347:[function(t,e,r){e.exports=function(t,e,r){var n=new Float32Array(3);return n[0]=t,n[1]=e,n[2]=r,n}},{}],348:[function(t,e,r){e.exports={EPSILON:t(\"./epsilon\"),create:t(\"./create\"),clone:t(\"./clone\"),angle:t(\"./angle\"),fromValues:t(\"./fromValues\"),copy:t(\"./copy\"),set:t(\"./set\"),equals:t(\"./equals\"),exactEquals:t(\"./exactEquals\"),add:t(\"./add\"),subtract:t(\"./subtract\"),sub:t(\"./sub\"),multiply:t(\"./multiply\"),mul:t(\"./mul\"),divide:t(\"./divide\"),div:t(\"./div\"),min:t(\"./min\"),max:t(\"./max\"),floor:t(\"./floor\"),ceil:t(\"./ceil\"),round:t(\"./round\"),scale:t(\"./scale\"),scaleAndAdd:t(\"./scaleAndAdd\"),distance:t(\"./distance\"),dist:t(\"./dist\"),squaredDistance:t(\"./squaredDistance\"),sqrDist:t(\"./sqrDist\"),length:t(\"./length\"),len:t(\"./len\"),squaredLength:t(\"./squaredLength\"),sqrLen:t(\"./sqrLen\"),negate:t(\"./negate\"),inverse:t(\"./inverse\"),normalize:t(\"./normalize\"),dot:t(\"./dot\"),cross:t(\"./cross\"),lerp:t(\"./lerp\"),random:t(\"./random\"),transformMat4:t(\"./transformMat4\"),transformMat3:t(\"./transformMat3\"),transformQuat:t(\"./transformQuat\"),rotateX:t(\"./rotateX\"),rotateY:t(\"./rotateY\"),rotateZ:t(\"./rotateZ\"),forEach:t(\"./forEach\")}},{\"./add\":330,\"./angle\":331,\"./ceil\":332,\"./clone\":333,\"./copy\":334,\"./create\":335,\"./cross\":336,\"./dist\":337,\"./distance\":338,\"./div\":339,\"./divide\":340,\"./dot\":341,\"./epsilon\":342,\"./equals\":343,\"./exactEquals\":344,\"./floor\":345,\"./forEach\":346,\"./fromValues\":347,\"./inverse\":349,\"./len\":350,\"./length\":351,\"./lerp\":352,\"./max\":353,\"./min\":354,\"./mul\":355,\"./multiply\":356,\"./negate\":357,\"./normalize\":358,\"./random\":359,\"./rotateX\":360,\"./rotateY\":361,\"./rotateZ\":362,\"./round\":363,\"./scale\":364,\"./scaleAndAdd\":365,\"./set\":366,\"./sqrDist\":367,\"./sqrLen\":368,\"./squaredDistance\":369,\"./squaredLength\":370,\"./sub\":371,\"./subtract\":372,\"./transformMat3\":373,\"./transformMat4\":374,\"./transformQuat\":375}],349:[function(t,e,r){e.exports=function(t,e){return t[0]=1/e[0],t[1]=1/e[1],t[2]=1/e[2],t}},{}],350:[function(t,e,r){e.exports=t(\"./length\")},{\"./length\":351}],351:[function(t,e,r){e.exports=function(t){var e=t[0],r=t[1],n=t[2];return Math.sqrt(e*e+r*r+n*n)}},{}],352:[function(t,e,r){e.exports=function(t,e,r,n){var a=e[0],i=e[1],o=e[2];return t[0]=a+n*(r[0]-a),t[1]=i+n*(r[1]-i),t[2]=o+n*(r[2]-o),t}},{}],353:[function(t,e,r){e.exports=function(t,e,r){return t[0]=Math.max(e[0],r[0]),t[1]=Math.max(e[1],r[1]),t[2]=Math.max(e[2],r[2]),t}},{}],354:[function(t,e,r){e.exports=function(t,e,r){return t[0]=Math.min(e[0],r[0]),t[1]=Math.min(e[1],r[1]),t[2]=Math.min(e[2],r[2]),t}},{}],355:[function(t,e,r){e.exports=t(\"./multiply\")},{\"./multiply\":356}],356:[function(t,e,r){e.exports=function(t,e,r){return t[0]=e[0]*r[0],t[1]=e[1]*r[1],t[2]=e[2]*r[2],t}},{}],357:[function(t,e,r){e.exports=function(t,e){return t[0]=-e[0],t[1]=-e[1],t[2]=-e[2],t}},{}],358:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],a=e[2],i=r*r+n*n+a*a;i>0&&(i=1/Math.sqrt(i),t[0]=e[0]*i,t[1]=e[1]*i,t[2]=e[2]*i);return t}},{}],359:[function(t,e,r){e.exports=function(t,e){e=e||1;var r=2*Math.random()*Math.PI,n=2*Math.random()-1,a=Math.sqrt(1-n*n)*e;return t[0]=Math.cos(r)*a,t[1]=Math.sin(r)*a,t[2]=n*e,t}},{}],360:[function(t,e,r){e.exports=function(t,e,r,n){var a=r[1],i=r[2],o=e[1]-a,s=e[2]-i,l=Math.sin(n),c=Math.cos(n);return t[0]=e[0],t[1]=a+o*c-s*l,t[2]=i+o*l+s*c,t}},{}],361:[function(t,e,r){e.exports=function(t,e,r,n){var a=r[0],i=r[2],o=e[0]-a,s=e[2]-i,l=Math.sin(n),c=Math.cos(n);return t[0]=a+s*l+o*c,t[1]=e[1],t[2]=i+s*c-o*l,t}},{}],362:[function(t,e,r){e.exports=function(t,e,r,n){var a=r[0],i=r[1],o=e[0]-a,s=e[1]-i,l=Math.sin(n),c=Math.cos(n);return t[0]=a+o*c-s*l,t[1]=i+o*l+s*c,t[2]=e[2],t}},{}],363:[function(t,e,r){e.exports=function(t,e){return t[0]=Math.round(e[0]),t[1]=Math.round(e[1]),t[2]=Math.round(e[2]),t}},{}],364:[function(t,e,r){e.exports=function(t,e,r){return t[0]=e[0]*r,t[1]=e[1]*r,t[2]=e[2]*r,t}},{}],365:[function(t,e,r){e.exports=function(t,e,r,n){return t[0]=e[0]+r[0]*n,t[1]=e[1]+r[1]*n,t[2]=e[2]+r[2]*n,t}},{}],366:[function(t,e,r){e.exports=function(t,e,r,n){return t[0]=e,t[1]=r,t[2]=n,t}},{}],367:[function(t,e,r){e.exports=t(\"./squaredDistance\")},{\"./squaredDistance\":369}],368:[function(t,e,r){e.exports=t(\"./squaredLength\")},{\"./squaredLength\":370}],369:[function(t,e,r){e.exports=function(t,e){var r=e[0]-t[0],n=e[1]-t[1],a=e[2]-t[2];return r*r+n*n+a*a}},{}],370:[function(t,e,r){e.exports=function(t){var e=t[0],r=t[1],n=t[2];return e*e+r*r+n*n}},{}],371:[function(t,e,r){e.exports=t(\"./subtract\")},{\"./subtract\":372}],372:[function(t,e,r){e.exports=function(t,e,r){return t[0]=e[0]-r[0],t[1]=e[1]-r[1],t[2]=e[2]-r[2],t}},{}],373:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],a=e[1],i=e[2];return t[0]=n*r[0]+a*r[3]+i*r[6],t[1]=n*r[1]+a*r[4]+i*r[7],t[2]=n*r[2]+a*r[5]+i*r[8],t}},{}],374:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],a=e[1],i=e[2],o=r[3]*n+r[7]*a+r[11]*i+r[15];return o=o||1,t[0]=(r[0]*n+r[4]*a+r[8]*i+r[12])/o,t[1]=(r[1]*n+r[5]*a+r[9]*i+r[13])/o,t[2]=(r[2]*n+r[6]*a+r[10]*i+r[14])/o,t}},{}],375:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],a=e[1],i=e[2],o=r[0],s=r[1],l=r[2],c=r[3],u=c*n+s*i-l*a,h=c*a+l*n-o*i,f=c*i+o*a-s*n,p=-o*n-s*a-l*i;return t[0]=u*c+p*-o+h*-l-f*-s,t[1]=h*c+p*-s+f*-o-u*-l,t[2]=f*c+p*-l+u*-s-h*-o,t}},{}],376:[function(t,e,r){e.exports=function(t,e,r){return t[0]=e[0]+r[0],t[1]=e[1]+r[1],t[2]=e[2]+r[2],t[3]=e[3]+r[3],t}},{}],377:[function(t,e,r){e.exports=function(t){var e=new Float32Array(4);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e}},{}],378:[function(t,e,r){e.exports=function(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t}},{}],379:[function(t,e,r){e.exports=function(){var t=new Float32Array(4);return t[0]=0,t[1]=0,t[2]=0,t[3]=0,t}},{}],380:[function(t,e,r){e.exports=function(t,e){var r=e[0]-t[0],n=e[1]-t[1],a=e[2]-t[2],i=e[3]-t[3];return Math.sqrt(r*r+n*n+a*a+i*i)}},{}],381:[function(t,e,r){e.exports=function(t,e,r){return t[0]=e[0]/r[0],t[1]=e[1]/r[1],t[2]=e[2]/r[2],t[3]=e[3]/r[3],t}},{}],382:[function(t,e,r){e.exports=function(t,e){return t[0]*e[0]+t[1]*e[1]+t[2]*e[2]+t[3]*e[3]}},{}],383:[function(t,e,r){e.exports=function(t,e,r,n){var a=new Float32Array(4);return a[0]=t,a[1]=e,a[2]=r,a[3]=n,a}},{}],384:[function(t,e,r){e.exports={create:t(\"./create\"),clone:t(\"./clone\"),fromValues:t(\"./fromValues\"),copy:t(\"./copy\"),set:t(\"./set\"),add:t(\"./add\"),subtract:t(\"./subtract\"),multiply:t(\"./multiply\"),divide:t(\"./divide\"),min:t(\"./min\"),max:t(\"./max\"),scale:t(\"./scale\"),scaleAndAdd:t(\"./scaleAndAdd\"),distance:t(\"./distance\"),squaredDistance:t(\"./squaredDistance\"),length:t(\"./length\"),squaredLength:t(\"./squaredLength\"),negate:t(\"./negate\"),inverse:t(\"./inverse\"),normalize:t(\"./normalize\"),dot:t(\"./dot\"),lerp:t(\"./lerp\"),random:t(\"./random\"),transformMat4:t(\"./transformMat4\"),transformQuat:t(\"./transformQuat\")}},{\"./add\":376,\"./clone\":377,\"./copy\":378,\"./create\":379,\"./distance\":380,\"./divide\":381,\"./dot\":382,\"./fromValues\":383,\"./inverse\":385,\"./length\":386,\"./lerp\":387,\"./max\":388,\"./min\":389,\"./multiply\":390,\"./negate\":391,\"./normalize\":392,\"./random\":393,\"./scale\":394,\"./scaleAndAdd\":395,\"./set\":396,\"./squaredDistance\":397,\"./squaredLength\":398,\"./subtract\":399,\"./transformMat4\":400,\"./transformQuat\":401}],385:[function(t,e,r){e.exports=function(t,e){return t[0]=1/e[0],t[1]=1/e[1],t[2]=1/e[2],t[3]=1/e[3],t}},{}],386:[function(t,e,r){e.exports=function(t){var e=t[0],r=t[1],n=t[2],a=t[3];return Math.sqrt(e*e+r*r+n*n+a*a)}},{}],387:[function(t,e,r){e.exports=function(t,e,r,n){var a=e[0],i=e[1],o=e[2],s=e[3];return t[0]=a+n*(r[0]-a),t[1]=i+n*(r[1]-i),t[2]=o+n*(r[2]-o),t[3]=s+n*(r[3]-s),t}},{}],388:[function(t,e,r){e.exports=function(t,e,r){return t[0]=Math.max(e[0],r[0]),t[1]=Math.max(e[1],r[1]),t[2]=Math.max(e[2],r[2]),t[3]=Math.max(e[3],r[3]),t}},{}],389:[function(t,e,r){e.exports=function(t,e,r){return t[0]=Math.min(e[0],r[0]),t[1]=Math.min(e[1],r[1]),t[2]=Math.min(e[2],r[2]),t[3]=Math.min(e[3],r[3]),t}},{}],390:[function(t,e,r){e.exports=function(t,e,r){return t[0]=e[0]*r[0],t[1]=e[1]*r[1],t[2]=e[2]*r[2],t[3]=e[3]*r[3],t}},{}],391:[function(t,e,r){e.exports=function(t,e){return t[0]=-e[0],t[1]=-e[1],t[2]=-e[2],t[3]=-e[3],t}},{}],392:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],a=e[2],i=e[3],o=r*r+n*n+a*a+i*i;o>0&&(o=1/Math.sqrt(o),t[0]=r*o,t[1]=n*o,t[2]=a*o,t[3]=i*o);return t}},{}],393:[function(t,e,r){var n=t(\"./normalize\"),a=t(\"./scale\");e.exports=function(t,e){return e=e||1,t[0]=Math.random(),t[1]=Math.random(),t[2]=Math.random(),t[3]=Math.random(),n(t,t),a(t,t,e),t}},{\"./normalize\":392,\"./scale\":394}],394:[function(t,e,r){e.exports=function(t,e,r){return t[0]=e[0]*r,t[1]=e[1]*r,t[2]=e[2]*r,t[3]=e[3]*r,t}},{}],395:[function(t,e,r){e.exports=function(t,e,r,n){return t[0]=e[0]+r[0]*n,t[1]=e[1]+r[1]*n,t[2]=e[2]+r[2]*n,t[3]=e[3]+r[3]*n,t}},{}],396:[function(t,e,r){e.exports=function(t,e,r,n,a){return t[0]=e,t[1]=r,t[2]=n,t[3]=a,t}},{}],397:[function(t,e,r){e.exports=function(t,e){var r=e[0]-t[0],n=e[1]-t[1],a=e[2]-t[2],i=e[3]-t[3];return r*r+n*n+a*a+i*i}},{}],398:[function(t,e,r){e.exports=function(t){var e=t[0],r=t[1],n=t[2],a=t[3];return e*e+r*r+n*n+a*a}},{}],399:[function(t,e,r){e.exports=function(t,e,r){return t[0]=e[0]-r[0],t[1]=e[1]-r[1],t[2]=e[2]-r[2],t[3]=e[3]-r[3],t}},{}],400:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],a=e[1],i=e[2],o=e[3];return t[0]=r[0]*n+r[4]*a+r[8]*i+r[12]*o,t[1]=r[1]*n+r[5]*a+r[9]*i+r[13]*o,t[2]=r[2]*n+r[6]*a+r[10]*i+r[14]*o,t[3]=r[3]*n+r[7]*a+r[11]*i+r[15]*o,t}},{}],401:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],a=e[1],i=e[2],o=r[0],s=r[1],l=r[2],c=r[3],u=c*n+s*i-l*a,h=c*a+l*n-o*i,f=c*i+o*a-s*n,p=-o*n-s*a-l*i;return t[0]=u*c+p*-o+h*-l-f*-s,t[1]=h*c+p*-s+f*-o-u*-l,t[2]=f*c+p*-l+u*-s-h*-o,t[3]=e[3],t}},{}],402:[function(t,e,r){e.exports=function(t,e,r,i){return n[0]=i,n[1]=r,n[2]=e,n[3]=t,a[0]};var n=new Uint8Array(4),a=new Float32Array(n.buffer)},{}],403:[function(t,e,r){var n=t(\"glsl-tokenizer\"),a=t(\"atob-lite\");e.exports=function(t){for(var e=Array.isArray(t)?t:n(t),r=0;r<e.length;r++){var i=e[r];if(\"preprocessor\"===i.type){var o=i.data.match(/\\#define\\s+SHADER_NAME(_B64)?\\s+(.+)$/);if(o&&o[2]){var s=o[1],l=o[2];return(s?a(l):l).trim()}}}}},{\"atob-lite\":74,\"glsl-tokenizer\":410}],404:[function(t,e,r){e.exports=function(t){var e,r,k,T=0,M=0,A=l,S=[],E=[],L=1,C=0,P=0,O=!1,z=!1,I=\"\",D=i,R=n;\"300 es\"===(t=t||{}).version&&(D=s,R=o);return function(t){return E=[],null!==t?function(t){var r;T=0,k=(I+=t).length;for(;e=I[T],T<k;){switch(r=T,A){case u:T=V();break;case h:case f:T=j();break;case p:T=U();break;case d:T=G();break;case _:T=H();break;case g:T=Y();break;case c:T=W();break;case x:T=N();break;case l:T=B()}if(r!==T)switch(I[r]){case\"\\n\":C=0,++L;break;default:++C}}return M+=T,I=I.slice(T),E}(t.replace?t.replace(/\\r\\n/g,\"\\n\"):t):function(t){S.length&&F(S.join(\"\"));return A=b,F(\"(eof)\"),E}()};function F(t){t.length&&E.push({type:w[A],data:t,position:P,line:L,column:C})}function B(){return S=S.length?[]:S,\"/\"===r&&\"*\"===e?(P=M+T-1,A=u,r=e,T+1):\"/\"===r&&\"/\"===e?(P=M+T-1,A=h,r=e,T+1):\"#\"===e?(A=f,P=M+T,T):/\\s/.test(e)?(A=x,P=M+T,T):(O=/\\d/.test(e),z=/[^\\w_]/.test(e),P=M+T,A=O?d:z?p:c,T)}function N(){return/[^\\s]/g.test(e)?(F(S.join(\"\")),A=l,T):(S.push(e),r=e,T+1)}function j(){return\"\\r\"!==e&&\"\\n\"!==e||\"\\\\\"===r?(S.push(e),r=e,T+1):(F(S.join(\"\")),A=l,T)}function V(){return\"/\"===e&&\"*\"===r?(S.push(e),F(S.join(\"\")),A=l,T+1):(S.push(e),r=e,T+1)}function U(){if(\".\"===r&&/\\d/.test(e))return A=g,T;if(\"/\"===r&&\"*\"===e)return A=u,T;if(\"/\"===r&&\"/\"===e)return A=h,T;if(\".\"===e&&S.length){for(;q(S););return A=g,T}if(\";\"===e||\")\"===e||\"(\"===e){if(S.length)for(;q(S););return F(e),A=l,T+1}var t=2===S.length&&\"=\"!==e;if(/[\\w_\\d\\s]/.test(e)||t){for(;q(S););return A=l,T}return S.push(e),r=e,T+1}function q(t){for(var e,r,n=0;;){if(e=a.indexOf(t.slice(0,t.length+n).join(\"\")),r=a[e],-1===e){if(n--+t.length>0)continue;r=t.slice(0,1).join(\"\")}return F(r),P+=r.length,(S=S.slice(r.length)).length}}function H(){return/[^a-fA-F0-9]/.test(e)?(F(S.join(\"\")),A=l,T):(S.push(e),r=e,T+1)}function G(){return\".\"===e?(S.push(e),A=g,r=e,T+1):/[eE]/.test(e)?(S.push(e),A=g,r=e,T+1):\"x\"===e&&1===S.length&&\"0\"===S[0]?(A=_,S.push(e),r=e,T+1):/[^\\d]/.test(e)?(F(S.join(\"\")),A=l,T):(S.push(e),r=e,T+1)}function Y(){return\"f\"===e&&(S.push(e),r=e,T+=1),/[eE]/.test(e)?(S.push(e),r=e,T+1):\"-\"===e&&/[eE]/.test(r)?(S.push(e),r=e,T+1):/[^\\d]/.test(e)?(F(S.join(\"\")),A=l,T):(S.push(e),r=e,T+1)}function W(){if(/[^\\d\\w_]/.test(e)){var t=S.join(\"\");return A=R.indexOf(t)>-1?y:D.indexOf(t)>-1?m:v,F(S.join(\"\")),A=l,T}return S.push(e),r=e,T+1}};var n=t(\"./lib/literals\"),a=t(\"./lib/operators\"),i=t(\"./lib/builtins\"),o=t(\"./lib/literals-300es\"),s=t(\"./lib/builtins-300es\"),l=999,c=9999,u=0,h=1,f=2,p=3,d=4,g=5,v=6,m=7,y=8,x=9,b=10,_=11,w=[\"block-comment\",\"line-comment\",\"preprocessor\",\"operator\",\"integer\",\"float\",\"ident\",\"builtin\",\"keyword\",\"whitespace\",\"eof\",\"integer\"]},{\"./lib/builtins\":406,\"./lib/builtins-300es\":405,\"./lib/literals\":408,\"./lib/literals-300es\":407,\"./lib/operators\":409}],405:[function(t,e,r){var n=t(\"./builtins\");n=n.slice().filter(function(t){return!/^(gl\\_|texture)/.test(t)}),e.exports=n.concat([\"gl_VertexID\",\"gl_InstanceID\",\"gl_Position\",\"gl_PointSize\",\"gl_FragCoord\",\"gl_FrontFacing\",\"gl_FragDepth\",\"gl_PointCoord\",\"gl_MaxVertexAttribs\",\"gl_MaxVertexUniformVectors\",\"gl_MaxVertexOutputVectors\",\"gl_MaxFragmentInputVectors\",\"gl_MaxVertexTextureImageUnits\",\"gl_MaxCombinedTextureImageUnits\",\"gl_MaxTextureImageUnits\",\"gl_MaxFragmentUniformVectors\",\"gl_MaxDrawBuffers\",\"gl_MinProgramTexelOffset\",\"gl_MaxProgramTexelOffset\",\"gl_DepthRangeParameters\",\"gl_DepthRange\",\"trunc\",\"round\",\"roundEven\",\"isnan\",\"isinf\",\"floatBitsToInt\",\"floatBitsToUint\",\"intBitsToFloat\",\"uintBitsToFloat\",\"packSnorm2x16\",\"unpackSnorm2x16\",\"packUnorm2x16\",\"unpackUnorm2x16\",\"packHalf2x16\",\"unpackHalf2x16\",\"outerProduct\",\"transpose\",\"determinant\",\"inverse\",\"texture\",\"textureSize\",\"textureProj\",\"textureLod\",\"textureOffset\",\"texelFetch\",\"texelFetchOffset\",\"textureProjOffset\",\"textureLodOffset\",\"textureProjLod\",\"textureProjLodOffset\",\"textureGrad\",\"textureGradOffset\",\"textureProjGrad\",\"textureProjGradOffset\"])},{\"./builtins\":406}],406:[function(t,e,r){e.exports=[\"abs\",\"acos\",\"all\",\"any\",\"asin\",\"atan\",\"ceil\",\"clamp\",\"cos\",\"cross\",\"dFdx\",\"dFdy\",\"degrees\",\"distance\",\"dot\",\"equal\",\"exp\",\"exp2\",\"faceforward\",\"floor\",\"fract\",\"gl_BackColor\",\"gl_BackLightModelProduct\",\"gl_BackLightProduct\",\"gl_BackMaterial\",\"gl_BackSecondaryColor\",\"gl_ClipPlane\",\"gl_ClipVertex\",\"gl_Color\",\"gl_DepthRange\",\"gl_DepthRangeParameters\",\"gl_EyePlaneQ\",\"gl_EyePlaneR\",\"gl_EyePlaneS\",\"gl_EyePlaneT\",\"gl_Fog\",\"gl_FogCoord\",\"gl_FogFragCoord\",\"gl_FogParameters\",\"gl_FragColor\",\"gl_FragCoord\",\"gl_FragData\",\"gl_FragDepth\",\"gl_FragDepthEXT\",\"gl_FrontColor\",\"gl_FrontFacing\",\"gl_FrontLightModelProduct\",\"gl_FrontLightProduct\",\"gl_FrontMaterial\",\"gl_FrontSecondaryColor\",\"gl_LightModel\",\"gl_LightModelParameters\",\"gl_LightModelProducts\",\"gl_LightProducts\",\"gl_LightSource\",\"gl_LightSourceParameters\",\"gl_MaterialParameters\",\"gl_MaxClipPlanes\",\"gl_MaxCombinedTextureImageUnits\",\"gl_MaxDrawBuffers\",\"gl_MaxFragmentUniformComponents\",\"gl_MaxLights\",\"gl_MaxTextureCoords\",\"gl_MaxTextureImageUnits\",\"gl_MaxTextureUnits\",\"gl_MaxVaryingFloats\",\"gl_MaxVertexAttribs\",\"gl_MaxVertexTextureImageUnits\",\"gl_MaxVertexUniformComponents\",\"gl_ModelViewMatrix\",\"gl_ModelViewMatrixInverse\",\"gl_ModelViewMatrixInverseTranspose\",\"gl_ModelViewMatrixTranspose\",\"gl_ModelViewProjectionMatrix\",\"gl_ModelViewProjectionMatrixInverse\",\"gl_ModelViewProjectionMatrixInverseTranspose\",\"gl_ModelViewProjectionMatrixTranspose\",\"gl_MultiTexCoord0\",\"gl_MultiTexCoord1\",\"gl_MultiTexCoord2\",\"gl_MultiTexCoord3\",\"gl_MultiTexCoord4\",\"gl_MultiTexCoord5\",\"gl_MultiTexCoord6\",\"gl_MultiTexCoord7\",\"gl_Normal\",\"gl_NormalMatrix\",\"gl_NormalScale\",\"gl_ObjectPlaneQ\",\"gl_ObjectPlaneR\",\"gl_ObjectPlaneS\",\"gl_ObjectPlaneT\",\"gl_Point\",\"gl_PointCoord\",\"gl_PointParameters\",\"gl_PointSize\",\"gl_Position\",\"gl_ProjectionMatrix\",\"gl_ProjectionMatrixInverse\",\"gl_ProjectionMatrixInverseTranspose\",\"gl_ProjectionMatrixTranspose\",\"gl_SecondaryColor\",\"gl_TexCoord\",\"gl_TextureEnvColor\",\"gl_TextureMatrix\",\"gl_TextureMatrixInverse\",\"gl_TextureMatrixInverseTranspose\",\"gl_TextureMatrixTranspose\",\"gl_Vertex\",\"greaterThan\",\"greaterThanEqual\",\"inversesqrt\",\"length\",\"lessThan\",\"lessThanEqual\",\"log\",\"log2\",\"matrixCompMult\",\"max\",\"min\",\"mix\",\"mod\",\"normalize\",\"not\",\"notEqual\",\"pow\",\"radians\",\"reflect\",\"refract\",\"sign\",\"sin\",\"smoothstep\",\"sqrt\",\"step\",\"tan\",\"texture2D\",\"texture2DLod\",\"texture2DProj\",\"texture2DProjLod\",\"textureCube\",\"textureCubeLod\",\"texture2DLodEXT\",\"texture2DProjLodEXT\",\"textureCubeLodEXT\",\"texture2DGradEXT\",\"texture2DProjGradEXT\",\"textureCubeGradEXT\"]},{}],407:[function(t,e,r){var n=t(\"./literals\");e.exports=n.slice().concat([\"layout\",\"centroid\",\"smooth\",\"case\",\"mat2x2\",\"mat2x3\",\"mat2x4\",\"mat3x2\",\"mat3x3\",\"mat3x4\",\"mat4x2\",\"mat4x3\",\"mat4x4\",\"uint\",\"uvec2\",\"uvec3\",\"uvec4\",\"samplerCubeShadow\",\"sampler2DArray\",\"sampler2DArrayShadow\",\"isampler2D\",\"isampler3D\",\"isamplerCube\",\"isampler2DArray\",\"usampler2D\",\"usampler3D\",\"usamplerCube\",\"usampler2DArray\",\"coherent\",\"restrict\",\"readonly\",\"writeonly\",\"resource\",\"atomic_uint\",\"noperspective\",\"patch\",\"sample\",\"subroutine\",\"common\",\"partition\",\"active\",\"filter\",\"image1D\",\"image2D\",\"image3D\",\"imageCube\",\"iimage1D\",\"iimage2D\",\"iimage3D\",\"iimageCube\",\"uimage1D\",\"uimage2D\",\"uimage3D\",\"uimageCube\",\"image1DArray\",\"image2DArray\",\"iimage1DArray\",\"iimage2DArray\",\"uimage1DArray\",\"uimage2DArray\",\"image1DShadow\",\"image2DShadow\",\"image1DArrayShadow\",\"image2DArrayShadow\",\"imageBuffer\",\"iimageBuffer\",\"uimageBuffer\",\"sampler1DArray\",\"sampler1DArrayShadow\",\"isampler1D\",\"isampler1DArray\",\"usampler1D\",\"usampler1DArray\",\"isampler2DRect\",\"usampler2DRect\",\"samplerBuffer\",\"isamplerBuffer\",\"usamplerBuffer\",\"sampler2DMS\",\"isampler2DMS\",\"usampler2DMS\",\"sampler2DMSArray\",\"isampler2DMSArray\",\"usampler2DMSArray\"])},{\"./literals\":408}],408:[function(t,e,r){e.exports=[\"precision\",\"highp\",\"mediump\",\"lowp\",\"attribute\",\"const\",\"uniform\",\"varying\",\"break\",\"continue\",\"do\",\"for\",\"while\",\"if\",\"else\",\"in\",\"out\",\"inout\",\"float\",\"int\",\"void\",\"bool\",\"true\",\"false\",\"discard\",\"return\",\"mat2\",\"mat3\",\"mat4\",\"vec2\",\"vec3\",\"vec4\",\"ivec2\",\"ivec3\",\"ivec4\",\"bvec2\",\"bvec3\",\"bvec4\",\"sampler1D\",\"sampler2D\",\"sampler3D\",\"samplerCube\",\"sampler1DShadow\",\"sampler2DShadow\",\"struct\",\"asm\",\"class\",\"union\",\"enum\",\"typedef\",\"template\",\"this\",\"packed\",\"goto\",\"switch\",\"default\",\"inline\",\"noinline\",\"volatile\",\"public\",\"static\",\"extern\",\"external\",\"interface\",\"long\",\"short\",\"double\",\"half\",\"fixed\",\"unsigned\",\"input\",\"output\",\"hvec2\",\"hvec3\",\"hvec4\",\"dvec2\",\"dvec3\",\"dvec4\",\"fvec2\",\"fvec3\",\"fvec4\",\"sampler2DRect\",\"sampler3DRect\",\"sampler2DRectShadow\",\"sizeof\",\"cast\",\"namespace\",\"using\"]},{}],409:[function(t,e,r){e.exports=[\"<<=\",\">>=\",\"++\",\"--\",\"<<\",\">>\",\"<=\",\">=\",\"==\",\"!=\",\"&&\",\"||\",\"+=\",\"-=\",\"*=\",\"/=\",\"%=\",\"&=\",\"^^\",\"^=\",\"|=\",\"(\",\")\",\"[\",\"]\",\".\",\"!\",\"~\",\"*\",\"/\",\"%\",\"+\",\"-\",\"<\",\">\",\"&\",\"^\",\"|\",\"?\",\":\",\"=\",\",\",\";\",\"{\",\"}\"]},{}],410:[function(t,e,r){var n=t(\"./index\");e.exports=function(t,e){var r=n(e),a=[];return a=(a=a.concat(r(t))).concat(r(null))}},{\"./index\":404}],411:[function(t,e,r){e.exports=function(t){\"string\"==typeof t&&(t=[t]);for(var e=[].slice.call(arguments,1),r=[],n=0;n<t.length-1;n++)r.push(t[n],e[n]||\"\");return r.push(t[n]),r.join(\"\")}},{}],412:[function(t,e,r){(function(r){\"use strict\";var n,a=t(\"is-browser\");n=\"function\"==typeof r.matchMedia?!r.matchMedia(\"(hover: none)\").matches:a,e.exports=n}).call(this,\"undefined\"!=typeof global?global:\"undefined\"!=typeof self?self:\"undefined\"!=typeof window?window:{})},{\"is-browser\":419}],413:[function(t,e,r){\"use strict\";var n=t(\"is-browser\");e.exports=n&&function(){var t=!1;try{var e=Object.defineProperty({},\"passive\",{get:function(){t=!0}});window.addEventListener(\"test\",null,e),window.removeEventListener(\"test\",null,e)}catch(e){t=!1}return t}()},{\"is-browser\":419}],414:[function(t,e,r){r.read=function(t,e,r,n,a){var i,o,s=8*a-n-1,l=(1<<s)-1,c=l>>1,u=-7,h=r?a-1:0,f=r?-1:1,p=t[e+h];for(h+=f,i=p&(1<<-u)-1,p>>=-u,u+=s;u>0;i=256*i+t[e+h],h+=f,u-=8);for(o=i&(1<<-u)-1,i>>=-u,u+=n;u>0;o=256*o+t[e+h],h+=f,u-=8);if(0===i)i=1-c;else{if(i===l)return o?NaN:1/0*(p?-1:1);o+=Math.pow(2,n),i-=c}return(p?-1:1)*o*Math.pow(2,i-n)},r.write=function(t,e,r,n,a,i){var o,s,l,c=8*i-a-1,u=(1<<c)-1,h=u>>1,f=23===a?Math.pow(2,-24)-Math.pow(2,-77):0,p=n?0:i-1,d=n?1:-1,g=e<0||0===e&&1/e<0?1:0;for(e=Math.abs(e),isNaN(e)||e===1/0?(s=isNaN(e)?1:0,o=u):(o=Math.floor(Math.log(e)/Math.LN2),e*(l=Math.pow(2,-o))<1&&(o--,l*=2),(e+=o+h>=1?f/l:f*Math.pow(2,1-h))*l>=2&&(o++,l/=2),o+h>=u?(s=0,o=u):o+h>=1?(s=(e*l-1)*Math.pow(2,a),o+=h):(s=e*Math.pow(2,h-1)*Math.pow(2,a),o=0));a>=8;t[r+p]=255&s,p+=d,s/=256,a-=8);for(o=o<<a|s,c+=a;c>0;t[r+p]=255&o,p+=d,o/=256,c-=8);t[r+p-d]|=128*g}},{}],415:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=t.length;if(0===r)throw new Error(\"Must have at least d+1 points\");var a=t[0].length;if(r<=a)throw new Error(\"Must input at least d+1 points\");var o=t.slice(0,a+1),s=n.apply(void 0,o);if(0===s)throw new Error(\"Input not in general position\");for(var l=new Array(a+1),u=0;u<=a;++u)l[u]=u;s<0&&(l[0]=1,l[1]=0);for(var h=new i(l,new Array(a+1),!1),f=h.adjacent,p=new Array(a+2),u=0;u<=a;++u){for(var d=l.slice(),g=0;g<=a;++g)g===u&&(d[g]=-1);var v=d[0];d[0]=d[1],d[1]=v;var m=new i(d,new Array(a+1),!0);f[u]=m,p[u]=m}p[a+1]=h;for(var u=0;u<=a;++u)for(var d=f[u].vertices,y=f[u].adjacent,g=0;g<=a;++g){var x=d[g];if(x<0)y[g]=h;else for(var b=0;b<=a;++b)f[b].vertices.indexOf(x)<0&&(y[g]=f[b])}for(var _=new c(a,o,p),w=!!e,u=a+1;u<r;++u)_.insert(t[u],w);return _.boundary()};var n=t(\"robust-orientation\"),a=t(\"simplicial-complex\").compareCells;function i(t,e,r){this.vertices=t,this.adjacent=e,this.boundary=r,this.lastVisited=-1}function o(t,e,r){this.vertices=t,this.cell=e,this.index=r}function s(t,e){return a(t.vertices,e.vertices)}i.prototype.flip=function(){var t=this.vertices[0];this.vertices[0]=this.vertices[1],this.vertices[1]=t;var e=this.adjacent[0];this.adjacent[0]=this.adjacent[1],this.adjacent[1]=e};var l=[];function c(t,e,r){this.dimension=t,this.vertices=e,this.simplices=r,this.interior=r.filter(function(t){return!t.boundary}),this.tuple=new Array(t+1);for(var a=0;a<=t;++a)this.tuple[a]=this.vertices[a];var i=l[t];i||(i=l[t]=function(t){for(var e=[\"function orient(){var tuple=this.tuple;return test(\"],r=0;r<=t;++r)r>0&&e.push(\",\"),e.push(\"tuple[\",r,\"]\");e.push(\")}return orient\");var a=new Function(\"test\",e.join(\"\")),i=n[t+1];return i||(i=n),a(i)}(t)),this.orient=i}var u=c.prototype;u.handleBoundaryDegeneracy=function(t,e){var r=this.dimension,n=this.vertices.length-1,a=this.tuple,i=this.vertices,o=[t];for(t.lastVisited=-n;o.length>0;){(t=o.pop()).vertices;for(var s=t.adjacent,l=0;l<=r;++l){var c=s[l];if(c.boundary&&!(c.lastVisited<=-n)){for(var u=c.vertices,h=0;h<=r;++h){var f=u[h];a[h]=f<0?e:i[f]}var p=this.orient();if(p>0)return c;c.lastVisited=-n,0===p&&o.push(c)}}}return null},u.walk=function(t,e){var r=this.vertices.length-1,n=this.dimension,a=this.vertices,i=this.tuple,o=e?this.interior.length*Math.random()|0:this.interior.length-1,s=this.interior[o];t:for(;!s.boundary;){for(var l=s.vertices,c=s.adjacent,u=0;u<=n;++u)i[u]=a[l[u]];s.lastVisited=r;for(u=0;u<=n;++u){var h=c[u];if(!(h.lastVisited>=r)){var f=i[u];i[u]=t;var p=this.orient();if(i[u]=f,p<0){s=h;continue t}h.boundary?h.lastVisited=-r:h.lastVisited=r}}return}return s},u.addPeaks=function(t,e){var r=this.vertices.length-1,n=this.dimension,a=this.vertices,l=this.tuple,c=this.interior,u=this.simplices,h=[e];e.lastVisited=r,e.vertices[e.vertices.indexOf(-1)]=r,e.boundary=!1,c.push(e);for(var f=[];h.length>0;){var p=(e=h.pop()).vertices,d=e.adjacent,g=p.indexOf(r);if(!(g<0))for(var v=0;v<=n;++v)if(v!==g){var m=d[v];if(m.boundary&&!(m.lastVisited>=r)){var y=m.vertices;if(m.lastVisited!==-r){for(var x=0,b=0;b<=n;++b)y[b]<0?(x=b,l[b]=t):l[b]=a[y[b]];if(this.orient()>0){y[x]=r,m.boundary=!1,c.push(m),h.push(m),m.lastVisited=r;continue}m.lastVisited=-r}var _=m.adjacent,w=p.slice(),k=d.slice(),T=new i(w,k,!0);u.push(T);var M=_.indexOf(e);if(!(M<0)){_[M]=T,k[g]=m,w[v]=-1,k[v]=e,d[v]=T,T.flip();for(b=0;b<=n;++b){var A=w[b];if(!(A<0||A===r)){for(var S=new Array(n-1),E=0,L=0;L<=n;++L){var C=w[L];C<0||L===b||(S[E++]=C)}f.push(new o(S,T,b))}}}}}}f.sort(s);for(v=0;v+1<f.length;v+=2){var P=f[v],O=f[v+1],z=P.index,I=O.index;z<0||I<0||(P.cell.adjacent[P.index]=O.cell,O.cell.adjacent[O.index]=P.cell)}},u.insert=function(t,e){var r=this.vertices;r.push(t);var n=this.walk(t,e);if(n){for(var a=this.dimension,i=this.tuple,o=0;o<=a;++o){var s=n.vertices[o];i[o]=s<0?t:r[s]}var l=this.orient(i);l<0||(0!==l||(n=this.handleBoundaryDegeneracy(n,t)))&&this.addPeaks(t,n)}},u.boundary=function(){for(var t=this.dimension,e=[],r=this.simplices,n=r.length,a=0;a<n;++a){var i=r[a];if(i.boundary){for(var o=new Array(t),s=i.vertices,l=0,c=0,u=0;u<=t;++u)s[u]>=0?o[l++]=s[u]:c=1&u;if(c===(1&t)){var h=o[0];o[0]=o[1],o[1]=h}e.push(o)}}return e}},{\"robust-orientation\":509,\"simplicial-complex\":519}],416:[function(t,e,r){\"use strict\";var n=t(\"binary-search-bounds\"),a=0,i=1;function o(t,e,r,n,a){this.mid=t,this.left=e,this.right=r,this.leftPoints=n,this.rightPoints=a,this.count=(e?e.count:0)+(r?r.count:0)+n.length}e.exports=function(t){if(!t||0===t.length)return new x(null);return new x(y(t))};var s=o.prototype;function l(t,e){t.mid=e.mid,t.left=e.left,t.right=e.right,t.leftPoints=e.leftPoints,t.rightPoints=e.rightPoints,t.count=e.count}function c(t,e){var r=y(e);t.mid=r.mid,t.left=r.left,t.right=r.right,t.leftPoints=r.leftPoints,t.rightPoints=r.rightPoints,t.count=r.count}function u(t,e){var r=t.intervals([]);r.push(e),c(t,r)}function h(t,e){var r=t.intervals([]),n=r.indexOf(e);return n<0?a:(r.splice(n,1),c(t,r),i)}function f(t,e,r){for(var n=0;n<t.length&&t[n][0]<=e;++n){var a=r(t[n]);if(a)return a}}function p(t,e,r){for(var n=t.length-1;n>=0&&t[n][1]>=e;--n){var a=r(t[n]);if(a)return a}}function d(t,e){for(var r=0;r<t.length;++r){var n=e(t[r]);if(n)return n}}function g(t,e){return t-e}function v(t,e){var r=t[0]-e[0];return r||t[1]-e[1]}function m(t,e){var r=t[1]-e[1];return r||t[0]-e[0]}function y(t){if(0===t.length)return null;for(var e=[],r=0;r<t.length;++r)e.push(t[r][0],t[r][1]);e.sort(g);var n=e[e.length>>1],a=[],i=[],s=[];for(r=0;r<t.length;++r){var l=t[r];l[1]<n?a.push(l):n<l[0]?i.push(l):s.push(l)}var c=s,u=s.slice();return c.sort(v),u.sort(m),new o(n,y(a),y(i),c,u)}function x(t){this.root=t}s.intervals=function(t){return t.push.apply(t,this.leftPoints),this.left&&this.left.intervals(t),this.right&&this.right.intervals(t),t},s.insert=function(t){var e=this.count-this.leftPoints.length;if(this.count+=1,t[1]<this.mid)this.left?4*(this.left.count+1)>3*(e+1)?u(this,t):this.left.insert(t):this.left=y([t]);else if(t[0]>this.mid)this.right?4*(this.right.count+1)>3*(e+1)?u(this,t):this.right.insert(t):this.right=y([t]);else{var r=n.ge(this.leftPoints,t,v),a=n.ge(this.rightPoints,t,m);this.leftPoints.splice(r,0,t),this.rightPoints.splice(a,0,t)}},s.remove=function(t){var e=this.count-this.leftPoints;if(t[1]<this.mid)return this.left?4*(this.right?this.right.count:0)>3*(e-1)?h(this,t):2===(c=this.left.remove(t))?(this.left=null,this.count-=1,i):(c===i&&(this.count-=1),c):a;if(t[0]>this.mid)return this.right?4*(this.left?this.left.count:0)>3*(e-1)?h(this,t):2===(c=this.right.remove(t))?(this.right=null,this.count-=1,i):(c===i&&(this.count-=1),c):a;if(1===this.count)return this.leftPoints[0]===t?2:a;if(1===this.leftPoints.length&&this.leftPoints[0]===t){if(this.left&&this.right){for(var r=this,o=this.left;o.right;)r=o,o=o.right;if(r===this)o.right=this.right;else{var s=this.left,c=this.right;r.count-=o.count,r.right=o.left,o.left=s,o.right=c}l(this,o),this.count=(this.left?this.left.count:0)+(this.right?this.right.count:0)+this.leftPoints.length}else this.left?l(this,this.left):l(this,this.right);return i}for(s=n.ge(this.leftPoints,t,v);s<this.leftPoints.length&&this.leftPoints[s][0]===t[0];++s)if(this.leftPoints[s]===t){this.count-=1,this.leftPoints.splice(s,1);for(c=n.ge(this.rightPoints,t,m);c<this.rightPoints.length&&this.rightPoints[c][1]===t[1];++c)if(this.rightPoints[c]===t)return this.rightPoints.splice(c,1),i}return a},s.queryPoint=function(t,e){if(t<this.mid){if(this.left)if(r=this.left.queryPoint(t,e))return r;return f(this.leftPoints,t,e)}if(t>this.mid){var r;if(this.right)if(r=this.right.queryPoint(t,e))return r;return p(this.rightPoints,t,e)}return d(this.leftPoints,e)},s.queryInterval=function(t,e,r){var n;if(t<this.mid&&this.left&&(n=this.left.queryInterval(t,e,r)))return n;if(e>this.mid&&this.right&&(n=this.right.queryInterval(t,e,r)))return n;return e<this.mid?f(this.leftPoints,e,r):t>this.mid?p(this.rightPoints,t,r):d(this.leftPoints,r)};var b=x.prototype;b.insert=function(t){this.root?this.root.insert(t):this.root=new o(t[0],null,null,[t],[t])},b.remove=function(t){if(this.root){var e=this.root.remove(t);return 2===e&&(this.root=null),e!==a}return!1},b.queryPoint=function(t,e){if(this.root)return this.root.queryPoint(t,e)},b.queryInterval=function(t,e,r){if(t<=e&&this.root)return this.root.queryInterval(t,e,r)},Object.defineProperty(b,\"count\",{get:function(){return this.root?this.root.count:0}}),Object.defineProperty(b,\"intervals\",{get:function(){return this.root?this.root.intervals([]):[]}})},{\"binary-search-bounds\":93}],417:[function(t,e,r){\"use strict\";e.exports=function(t,e){e=e||new Array(t.length);for(var r=0;r<t.length;++r)e[t[r]]=r;return e}},{}],418:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=new Array(t),r=0;r<t;++r)e[r]=r;return e}},{}],419:[function(t,e,r){e.exports=!0},{}],420:[function(t,e,r){function n(t){return!!t.constructor&&\"function\"==typeof t.constructor.isBuffer&&t.constructor.isBuffer(t)}e.exports=function(t){return null!=t&&(n(t)||function(t){return\"function\"==typeof t.readFloatLE&&\"function\"==typeof t.slice&&n(t.slice(0,0))}(t)||!!t._isBuffer)}},{}],421:[function(t,e,r){\"use strict\";e.exports=\"undefined\"!=typeof navigator&&(/MSIE/.test(navigator.userAgent)||/Trident\\//.test(navigator.appVersion))},{}],422:[function(t,e,r){\"use strict\";e.exports=i,e.exports.isMobile=i,e.exports.default=i;var n=/(android|bb\\d+|meego).+mobile|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series[46]0|symbian|treo|up\\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino/i,a=/(android|bb\\d+|meego).+mobile|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series[46]0|symbian|treo|up\\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino|android|ipad|playbook|silk/i;function i(t){t||(t={});var e=t.ua;return e||\"undefined\"==typeof navigator||(e=navigator.userAgent),e&&e.headers&&\"string\"==typeof e.headers[\"user-agent\"]&&(e=e.headers[\"user-agent\"]),\"string\"==typeof e&&(t.tablet?a.test(e):n.test(e))}},{}],423:[function(t,e,r){\"use strict\";e.exports=function(t){var e=typeof t;return null!==t&&(\"object\"===e||\"function\"===e)}},{}],424:[function(t,e,r){\"use strict\";var n=Object.prototype.toString;e.exports=function(t){var e;return\"[object Object]\"===n.call(t)&&(null===(e=Object.getPrototypeOf(t))||e===Object.getPrototypeOf({}))}},{}],425:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e,r=t.length,n=0;n<r;n++)if(((e=t.charCodeAt(n))<9||e>13)&&32!==e&&133!==e&&160!==e&&5760!==e&&6158!==e&&(e<8192||e>8205)&&8232!==e&&8233!==e&&8239!==e&&8287!==e&&8288!==e&&12288!==e&&65279!==e)return!1;return!0}},{}],426:[function(t,e,r){\"use strict\";e.exports=function(t){return\"string\"==typeof t&&(t=t.trim(),!!(/^[mzlhvcsqta]\\s*[-+.0-9][^mlhvzcsqta]+/i.test(t)&&/[\\dz]$/i.test(t)&&t.length>4))}},{}],427:[function(t,e,r){e.exports=function(t,e,r){return t*(1-r)+e*r}},{}],428:[function(t,e,r){var n,a;n=this,a=function(){\"use strict\";var t,e,r;function n(n,a){if(t)if(e){var i=\"var sharedChunk = {}; (\"+t+\")(sharedChunk); (\"+e+\")(sharedChunk);\",o={};t(o),(r=a(o)).workerUrl=window.URL.createObjectURL(new Blob([i],{type:\"text/javascript\"}))}else e=a;else t=a}return n(0,function(t){function e(t,e){return t(e={exports:{}},e.exports),e.exports}var r=n;function n(t,e,r,n){this.cx=3*t,this.bx=3*(r-t)-this.cx,this.ax=1-this.cx-this.bx,this.cy=3*e,this.by=3*(n-e)-this.cy,this.ay=1-this.cy-this.by,this.p1x=t,this.p1y=n,this.p2x=r,this.p2y=n}n.prototype.sampleCurveX=function(t){return((this.ax*t+this.bx)*t+this.cx)*t},n.prototype.sampleCurveY=function(t){return((this.ay*t+this.by)*t+this.cy)*t},n.prototype.sampleCurveDerivativeX=function(t){return(3*this.ax*t+2*this.bx)*t+this.cx},n.prototype.solveCurveX=function(t,e){var r,n,a,i,o;for(void 0===e&&(e=1e-6),a=t,o=0;o<8;o++){if(i=this.sampleCurveX(a)-t,Math.abs(i)<e)return a;var s=this.sampleCurveDerivativeX(a);if(Math.abs(s)<1e-6)break;a-=i/s}if((a=t)<(r=0))return r;if(a>(n=1))return n;for(;r<n;){if(i=this.sampleCurveX(a),Math.abs(i-t)<e)return a;t>i?r=a:n=a,a=.5*(n-r)+r}return a},n.prototype.solve=function(t,e){return this.sampleCurveY(this.solveCurveX(t,e))};var a=i;function i(t,e){this.x=t,this.y=e}function o(t,e){if(Array.isArray(t)){if(!Array.isArray(e)||t.length!==e.length)return!1;for(var r=0;r<t.length;r++)if(!o(t[r],e[r]))return!1;return!0}if(\"object\"==typeof t&&null!==t&&null!==e){if(\"object\"!=typeof e)return!1;if(Object.keys(t).length!==Object.keys(e).length)return!1;for(var n in t)if(!o(t[n],e[n]))return!1;return!0}return t===e}function s(t,e,n,a){var i=new r(t,e,n,a);return function(t){return i.solve(t)}}i.prototype={clone:function(){return new i(this.x,this.y)},add:function(t){return this.clone()._add(t)},sub:function(t){return this.clone()._sub(t)},multByPoint:function(t){return this.clone()._multByPoint(t)},divByPoint:function(t){return this.clone()._divByPoint(t)},mult:function(t){return this.clone()._mult(t)},div:function(t){return this.clone()._div(t)},rotate:function(t){return this.clone()._rotate(t)},rotateAround:function(t,e){return this.clone()._rotateAround(t,e)},matMult:function(t){return this.clone()._matMult(t)},unit:function(){return this.clone()._unit()},perp:function(){return this.clone()._perp()},round:function(){return this.clone()._round()},mag:function(){return Math.sqrt(this.x*this.x+this.y*this.y)},equals:function(t){return this.x===t.x&&this.y===t.y},dist:function(t){return Math.sqrt(this.distSqr(t))},distSqr:function(t){var e=t.x-this.x,r=t.y-this.y;return e*e+r*r},angle:function(){return Math.atan2(this.y,this.x)},angleTo:function(t){return Math.atan2(this.y-t.y,this.x-t.x)},angleWith:function(t){return this.angleWithSep(t.x,t.y)},angleWithSep:function(t,e){return Math.atan2(this.x*e-this.y*t,this.x*t+this.y*e)},_matMult:function(t){var e=t[0]*this.x+t[1]*this.y,r=t[2]*this.x+t[3]*this.y;return this.x=e,this.y=r,this},_add:function(t){return this.x+=t.x,this.y+=t.y,this},_sub:function(t){return this.x-=t.x,this.y-=t.y,this},_mult:function(t){return this.x*=t,this.y*=t,this},_div:function(t){return this.x/=t,this.y/=t,this},_multByPoint:function(t){return this.x*=t.x,this.y*=t.y,this},_divByPoint:function(t){return this.x/=t.x,this.y/=t.y,this},_unit:function(){return this._div(this.mag()),this},_perp:function(){var t=this.y;return this.y=this.x,this.x=-t,this},_rotate:function(t){var e=Math.cos(t),r=Math.sin(t),n=e*this.x-r*this.y,a=r*this.x+e*this.y;return this.x=n,this.y=a,this},_rotateAround:function(t,e){var r=Math.cos(t),n=Math.sin(t),a=e.x+r*(this.x-e.x)-n*(this.y-e.y),i=e.y+n*(this.x-e.x)+r*(this.y-e.y);return this.x=a,this.y=i,this},_round:function(){return this.x=Math.round(this.x),this.y=Math.round(this.y),this}},i.convert=function(t){return t instanceof i?t:Array.isArray(t)?new i(t[0],t[1]):t};var l=s(.25,.1,.25,1);function c(t,e,r){return Math.min(r,Math.max(e,t))}function u(t,e,r){var n=r-e,a=((t-e)%n+n)%n+e;return a===e?r:a}function h(t){for(var e=[],r=arguments.length-1;r-- >0;)e[r]=arguments[r+1];for(var n=0,a=e;n<a.length;n+=1){var i=a[n];for(var o in i)t[o]=i[o]}return t}var f=1;function p(){return f++}function d(){return function t(e){return e?(e^16*Math.random()>>e/4).toString(16):([1e7]+-[1e3]+-4e3+-8e3+-1e11).replace(/[018]/g,t)}()}function g(t){return!!t&&/^[0-9a-f]{8}-[0-9a-f]{4}-[4][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$/i.test(t)}function v(t,e){t.forEach(function(t){e[t]&&(e[t]=e[t].bind(e))})}function m(t,e){return-1!==t.indexOf(e,t.length-e.length)}function y(t,e,r){var n={};for(var a in t)n[a]=e.call(r||this,t[a],a,t);return n}function x(t,e,r){var n={};for(var a in t)e.call(r||this,t[a],a,t)&&(n[a]=t[a]);return n}function b(t){return Array.isArray(t)?t.map(b):\"object\"==typeof t&&t?y(t,b):t}var _={};function w(t){_[t]||(\"undefined\"!=typeof console&&console.warn(t),_[t]=!0)}function k(t,e,r){return(r.y-t.y)*(e.x-t.x)>(e.y-t.y)*(r.x-t.x)}function T(t){for(var e=0,r=0,n=t.length,a=n-1,i=void 0,o=void 0;r<n;a=r++)i=t[r],e+=((o=t[a]).x-i.x)*(i.y+o.y);return e}function M(t){var e={};if(t.replace(/(?:^|(?:\\s*\\,\\s*))([^\\x00-\\x20\\(\\)<>@\\,;\\:\\\\\"\\/\\[\\]\\?\\=\\{\\}\\x7F]+)(?:\\=(?:([^\\x00-\\x20\\(\\)<>@\\,;\\:\\\\\"\\/\\[\\]\\?\\=\\{\\}\\x7F]+)|(?:\\\"((?:[^\"\\\\]|\\\\.)*)\\\")))?/g,function(t,r,n,a){var i=n||a;return e[r]=!i||i.toLowerCase(),\"\"}),e[\"max-age\"]){var r=parseInt(e[\"max-age\"],10);isNaN(r)?delete e[\"max-age\"]:e[\"max-age\"]=r}return e}function A(t){try{var e=self[t];return e.setItem(\"_mapbox_test_\",1),e.removeItem(\"_mapbox_test_\"),!0}catch(t){return!1}}var S,E,L,C,P=self.performance&&self.performance.now?self.performance.now.bind(self.performance):Date.now.bind(Date),O=self.requestAnimationFrame||self.mozRequestAnimationFrame||self.webkitRequestAnimationFrame||self.msRequestAnimationFrame,z=self.cancelAnimationFrame||self.mozCancelAnimationFrame||self.webkitCancelAnimationFrame||self.msCancelAnimationFrame,I={now:P,frame:function(t){var e=O(t);return{cancel:function(){return z(e)}}},getImageData:function(t){var e=self.document.createElement(\"canvas\"),r=e.getContext(\"2d\");if(!r)throw new Error(\"failed to create canvas 2d context\");return e.width=t.width,e.height=t.height,r.drawImage(t,0,0,t.width,t.height),r.getImageData(0,0,t.width,t.height)},resolveURL:function(t){return S||(S=self.document.createElement(\"a\")),S.href=t,S.href},hardwareConcurrency:self.navigator.hardwareConcurrency||4,get devicePixelRatio(){return self.devicePixelRatio},get prefersReducedMotion(){return!!self.matchMedia&&(null==E&&(E=self.matchMedia(\"(prefers-reduced-motion: reduce)\")),E.matches)}},D={API_URL:\"https://api.mapbox.com\",get EVENTS_URL(){return this.API_URL?0===this.API_URL.indexOf(\"https://api.mapbox.cn\")?\"https://events.mapbox.cn/events/v2\":0===this.API_URL.indexOf(\"https://api.mapbox.com\")?\"https://events.mapbox.com/events/v2\":null:null},FEEDBACK_URL:\"https://apps.mapbox.com/feedback\",REQUIRE_ACCESS_TOKEN:!0,ACCESS_TOKEN:null,MAX_PARALLEL_IMAGE_REQUESTS:16},R={supported:!1,testSupport:function(t){!F&&C&&(B?N(t):L=t)}},F=!1,B=!1;function N(t){var e=t.createTexture();t.bindTexture(t.TEXTURE_2D,e);try{if(t.texImage2D(t.TEXTURE_2D,0,t.RGBA,t.RGBA,t.UNSIGNED_BYTE,C),t.isContextLost())return;R.supported=!0}catch(t){}t.deleteTexture(e),F=!0}self.document&&((C=self.document.createElement(\"img\")).onload=function(){L&&N(L),L=null,B=!0},C.onerror=function(){F=!0,L=null},C.src=\"data:image/webp;base64,UklGRh4AAABXRUJQVlA4TBEAAAAvAQAAAAfQ//73v/+BiOh/AAA=\");var j=\"01\",V=function(t,e){this._transformRequestFn=t,this._customAccessToken=e,this._createSkuToken()};function U(t){return 0===t.indexOf(\"mapbox:\")}V.prototype._createSkuToken=function(){var t=function(){for(var t=\"\",e=0;e<10;e++)t+=\"0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ\"[Math.floor(62*Math.random())];return{token:[\"1\",j,t].join(\"\"),tokenExpiresAt:Date.now()+432e5}}();this._skuToken=t.token,this._skuTokenExpiresAt=t.tokenExpiresAt},V.prototype._isSkuTokenExpired=function(){return Date.now()>this._skuTokenExpiresAt},V.prototype.transformRequest=function(t,e){return this._transformRequestFn&&this._transformRequestFn(t,e)||{url:t}},V.prototype.normalizeStyleURL=function(t,e){if(!U(t))return t;var r=Y(t);return r.path=\"/styles/v1\"+r.path,this._makeAPIURL(r,this._customAccessToken||e)},V.prototype.normalizeGlyphsURL=function(t,e){if(!U(t))return t;var r=Y(t);return r.path=\"/fonts/v1\"+r.path,this._makeAPIURL(r,this._customAccessToken||e)},V.prototype.normalizeSourceURL=function(t,e){if(!U(t))return t;var r=Y(t);return r.path=\"/v4/\"+r.authority+\".json\",r.params.push(\"secure\"),this._makeAPIURL(r,this._customAccessToken||e)},V.prototype.normalizeSpriteURL=function(t,e,r,n){var a=Y(t);return U(t)?(a.path=\"/styles/v1\"+a.path+\"/sprite\"+e+r,this._makeAPIURL(a,this._customAccessToken||n)):(a.path+=\"\"+e+r,W(a))},V.prototype.normalizeTileURL=function(t,e,r){if(this._isSkuTokenExpired()&&this._createSkuToken(),!e||!U(e))return t;var n=Y(t),a=I.devicePixelRatio>=2||512===r?\"@2x\":\"\",i=R.supported?\".webp\":\"$1\";return n.path=n.path.replace(/(\\.(png|jpg)\\d*)(?=$)/,\"\"+a+i),n.path=n.path.replace(/^.+\\/v4\\//,\"/\"),n.path=\"/v4\"+n.path,D.REQUIRE_ACCESS_TOKEN&&(D.ACCESS_TOKEN||this._customAccessToken)&&this._skuToken&&n.params.push(\"sku=\"+this._skuToken),this._makeAPIURL(n,this._customAccessToken)},V.prototype.canonicalizeTileURL=function(t){var e=Y(t);if(!e.path.match(/(^\\/v4\\/)/)||!e.path.match(/\\.[\\w]+$/))return t;var r=\"mapbox://tiles/\";r+=e.path.replace(\"/v4/\",\"\");var n=e.params.filter(function(t){return!t.match(/^access_token=/)});return n.length&&(r+=\"?\"+n.join(\"&\")),r},V.prototype.canonicalizeTileset=function(t,e){if(!U(e))return t.tiles||[];for(var r=[],n=0,a=t.tiles;n<a.length;n+=1){var i=a[n],o=this.canonicalizeTileURL(i);r.push(o)}return r},V.prototype._makeAPIURL=function(t,e){var r=\"See https://www.mapbox.com/api-documentation/#access-tokens-and-token-scopes\",n=Y(D.API_URL);if(t.protocol=n.protocol,t.authority=n.authority,\"/\"!==n.path&&(t.path=\"\"+n.path+t.path),!D.REQUIRE_ACCESS_TOKEN)return W(t);if(!(e=e||D.ACCESS_TOKEN))throw new Error(\"An API access token is required to use Mapbox GL. \"+r);if(\"s\"===e[0])throw new Error(\"Use a public access token (pk.*) with Mapbox GL, not a secret access token (sk.*). \"+r);return t.params=t.params.filter(function(t){return-1===t.indexOf(\"access_token\")}),t.params.push(\"access_token=\"+e),W(t)};var q=/^((https?:)?\\/\\/)?([^\\/]+\\.)?mapbox\\.c(n|om)(\\/|\\?|$)/i;function H(t){return q.test(t)}var G=/^(\\w+):\\/\\/([^\\/?]*)(\\/[^?]+)?\\??(.+)?/;function Y(t){var e=t.match(G);if(!e)throw new Error(\"Unable to parse URL object\");return{protocol:e[1],authority:e[2],path:e[3]||\"/\",params:e[4]?e[4].split(\"&\"):[]}}function W(t){var e=t.params.length?\"?\"+t.params.join(\"&\"):\"\";return t.protocol+\"://\"+t.authority+t.path+e}function X(t){if(!t)return null;var e,r=t.split(\".\");if(!r||3!==r.length)return null;try{return JSON.parse((e=r[1],decodeURIComponent(self.atob(e).split(\"\").map(function(t){return\"%\"+(\"00\"+t.charCodeAt(0).toString(16)).slice(-2)}).join(\"\"))))}catch(t){return null}}var Z=function(t){this.type=t,this.anonId=null,this.eventData={},this.queue=[],this.pendingRequest=null};Z.prototype.getStorageKey=function(t){var e,r=X(D.ACCESS_TOKEN),n=\"\";return r&&r.u?(e=r.u,n=self.btoa(encodeURIComponent(e).replace(/%([0-9A-F]{2})/g,function(t,e){return String.fromCharCode(Number(\"0x\"+e))}))):n=D.ACCESS_TOKEN||\"\",t?\"mapbox.eventData.\"+t+\":\"+n:\"mapbox.eventData:\"+n},Z.prototype.fetchEventData=function(){var t=A(\"localStorage\"),e=this.getStorageKey(),r=this.getStorageKey(\"uuid\");if(t)try{var n=self.localStorage.getItem(e);n&&(this.eventData=JSON.parse(n));var a=self.localStorage.getItem(r);a&&(this.anonId=a)}catch(t){w(\"Unable to read from LocalStorage\")}},Z.prototype.saveEventData=function(){var t=A(\"localStorage\"),e=this.getStorageKey(),r=this.getStorageKey(\"uuid\");if(t)try{self.localStorage.setItem(r,this.anonId),Object.keys(this.eventData).length>=1&&self.localStorage.setItem(e,JSON.stringify(this.eventData))}catch(t){w(\"Unable to write to LocalStorage\")}},Z.prototype.processRequests=function(t){},Z.prototype.postEvent=function(t,e,r,n){var a=this;if(D.EVENTS_URL){var i=Y(D.EVENTS_URL);i.params.push(\"access_token=\"+(n||D.ACCESS_TOKEN||\"\"));var o={event:this.type,created:new Date(t).toISOString(),sdkIdentifier:\"mapbox-gl-js\",sdkVersion:\"1.3.2\",skuId:j,userId:this.anonId},s=e?h(o,e):o,l={url:W(i),headers:{\"Content-Type\":\"text/plain\"},body:JSON.stringify([s])};this.pendingRequest=mt(l,function(t){a.pendingRequest=null,r(t),a.saveEventData(),a.processRequests(n)})}},Z.prototype.queueRequest=function(t,e){this.queue.push(t),this.processRequests(e)};var J,K=function(t){function e(){t.call(this,\"map.load\"),this.success={},this.skuToken=\"\"}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.postMapLoadEvent=function(t,e,r,n){this.skuToken=r,(D.EVENTS_URL&&n||D.ACCESS_TOKEN&&Array.isArray(t)&&t.some(function(t){return U(t)||H(t)}))&&this.queueRequest({id:e,timestamp:Date.now()},n)},e.prototype.processRequests=function(t){var e=this;if(!this.pendingRequest&&0!==this.queue.length){var r=this.queue.shift(),n=r.id,a=r.timestamp;n&&this.success[n]||(this.anonId||this.fetchEventData(),g(this.anonId)||(this.anonId=d()),this.postEvent(a,{skuToken:this.skuToken},function(t){t||n&&(e.success[n]=!0)},t))}},e}(Z),Q=new(function(t){function e(e){t.call(this,\"appUserTurnstile\"),this._customAccessToken=e}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.postTurnstileEvent=function(t,e){D.EVENTS_URL&&D.ACCESS_TOKEN&&Array.isArray(t)&&t.some(function(t){return U(t)||H(t)})&&this.queueRequest(Date.now(),e)},e.prototype.processRequests=function(t){var e=this;if(!this.pendingRequest&&0!==this.queue.length){this.anonId&&this.eventData.lastSuccess&&this.eventData.tokenU||this.fetchEventData();var r=X(D.ACCESS_TOKEN),n=r?r.u:D.ACCESS_TOKEN,a=n!==this.eventData.tokenU;g(this.anonId)||(this.anonId=d(),a=!0);var i=this.queue.shift();if(this.eventData.lastSuccess){var o=new Date(this.eventData.lastSuccess),s=new Date(i),l=(i-this.eventData.lastSuccess)/864e5;a=a||l>=1||l<-1||o.getDate()!==s.getDate()}else a=!0;if(!a)return this.processRequests();this.postEvent(i,{\"enabled.telemetry\":!1},function(t){t||(e.eventData.lastSuccess=i,e.eventData.tokenU=n)},t)}},e}(Z)),$=Q.postTurnstileEvent.bind(Q),tt=new K,et=tt.postMapLoadEvent.bind(tt),rt=\"mapbox-tiles\",nt=500,at=50,it=42e4;function ot(t){var e=t.indexOf(\"?\");return e<0?t:t.slice(0,e)}var st=1/0,lt={Unknown:\"Unknown\",Style:\"Style\",Source:\"Source\",Tile:\"Tile\",Glyphs:\"Glyphs\",SpriteImage:\"SpriteImage\",SpriteJSON:\"SpriteJSON\",Image:\"Image\"};\"function\"==typeof Object.freeze&&Object.freeze(lt);var ct=function(t){function e(e,r,n){401===r&&H(n)&&(e+=\": you may have provided an invalid Mapbox access token. See https://www.mapbox.com/api-documentation/#access-tokens-and-token-scopes\"),t.call(this,e),this.status=r,this.url=n,this.name=this.constructor.name,this.message=e}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.toString=function(){return this.name+\": \"+this.message+\" (\"+this.status+\"): \"+this.url},e}(Error);function ut(){return\"undefined\"!=typeof WorkerGlobalScope&&\"undefined\"!=typeof self&&self instanceof WorkerGlobalScope}var ht=ut()?function(){return self.worker&&self.worker.referrer}:function(){return(\"blob:\"===self.location.protocol?self.parent:self).location.href};function ft(t,e){var r,n=new self.AbortController,a=new self.Request(t.url,{method:t.method||\"GET\",body:t.body,credentials:t.credentials,headers:t.headers,referrer:ht(),signal:n.signal}),i=!1,o=!1,s=(r=a.url).indexOf(\"sku=\")>0&&H(r);\"json\"===t.type&&a.headers.set(\"Accept\",\"application/json\");var l=function(r,n,i){if(!o){if(r&&\"SecurityError\"!==r.message&&w(r),n&&i)return c(n);var l=Date.now();self.fetch(a).then(function(r){if(r.ok){var n=s?r.clone():null;return c(r,n,l)}return e(new ct(r.statusText,r.status,t.url))}).catch(function(t){20!==t.code&&e(new Error(t.message))})}},c=function(r,n,s){(\"arrayBuffer\"===t.type?r.arrayBuffer():\"json\"===t.type?r.json():r.text()).then(function(t){o||(n&&s&&function(t,e,r){if(self.caches){var n={status:e.status,statusText:e.statusText,headers:new self.Headers};e.headers.forEach(function(t,e){return n.headers.set(e,t)});var a=M(e.headers.get(\"Cache-Control\")||\"\");a[\"no-store\"]||(a[\"max-age\"]&&n.headers.set(\"Expires\",new Date(r+1e3*a[\"max-age\"]).toUTCString()),new Date(n.headers.get(\"Expires\")).getTime()-r<it||function(t,e){if(void 0===J)try{new Response(new ReadableStream),J=!0}catch(t){J=!1}J?e(t.body):t.blob().then(e)}(e,function(e){var r=new self.Response(e,n);self.caches.open(rt).then(function(e){return e.put(ot(t.url),r)}).catch(function(t){return w(t.message)})}))}}(a,n,s),i=!0,e(null,t,r.headers.get(\"Cache-Control\"),r.headers.get(\"Expires\")))}).catch(function(t){return e(new Error(t.message))})};return s?function(t,e){if(!self.caches)return e(null);var r=ot(t.url);self.caches.open(rt).then(function(t){t.match(r).then(function(n){var a=function(t){if(!t)return!1;var e=new Date(t.headers.get(\"Expires\")),r=M(t.headers.get(\"Cache-Control\")||\"\");return e>Date.now()&&!r[\"no-cache\"]}(n);t.delete(r),a&&t.put(r,n.clone()),e(null,n,a)}).catch(e)}).catch(e)}(a,l):l(null,null),{cancel:function(){o=!0,i||n.abort()}}}var pt,dt,gt=function(t,e){if(r=t.url,!(/^file:/.test(r)||/^file:/.test(ht())&&!/^\\w+:/.test(r))){if(self.fetch&&self.Request&&self.AbortController&&self.Request.prototype.hasOwnProperty(\"signal\"))return ft(t,e);if(ut()&&self.worker&&self.worker.actor)return self.worker.actor.send(\"getResource\",t,e)}var r;return function(t,e){var r=new self.XMLHttpRequest;for(var n in r.open(t.method||\"GET\",t.url,!0),\"arrayBuffer\"===t.type&&(r.responseType=\"arraybuffer\"),t.headers)r.setRequestHeader(n,t.headers[n]);return\"json\"===t.type&&(r.responseType=\"text\",r.setRequestHeader(\"Accept\",\"application/json\")),r.withCredentials=\"include\"===t.credentials,r.onerror=function(){e(new Error(r.statusText))},r.onload=function(){if((r.status>=200&&r.status<300||0===r.status)&&null!==r.response){var n=r.response;if(\"json\"===t.type)try{n=JSON.parse(r.response)}catch(t){return e(t)}e(null,n,r.getResponseHeader(\"Cache-Control\"),r.getResponseHeader(\"Expires\"))}else e(new ct(r.statusText,r.status,t.url))},r.send(t.body),{cancel:function(){return r.abort()}}}(t,e)},vt=function(t,e){return gt(h(t,{type:\"arrayBuffer\"}),e)},mt=function(t,e){return gt(h(t,{method:\"POST\"}),e)};pt=[],dt=0;var yt=function(t,e){if(dt>=D.MAX_PARALLEL_IMAGE_REQUESTS){var r={requestParameters:t,callback:e,cancelled:!1,cancel:function(){this.cancelled=!0}};return pt.push(r),r}dt++;var n=!1,a=function(){if(!n)for(n=!0,dt--;pt.length&&dt<D.MAX_PARALLEL_IMAGE_REQUESTS;){var t=pt.shift(),e=t.requestParameters,r=t.callback;t.cancelled||(t.cancel=yt(e,r).cancel)}},i=vt(t,function(t,r,n,i){if(a(),t)e(t);else if(r){var o=new self.Image,s=self.URL||self.webkitURL;o.onload=function(){e(null,o),s.revokeObjectURL(o.src)},o.onerror=function(){return e(new Error(\"Could not load image. Please make sure to use a supported image type such as PNG or JPEG. Note that SVGs are not supported.\"))};var l=new self.Blob([new Uint8Array(r)],{type:\"image/png\"});o.cacheControl=n,o.expires=i,o.src=r.byteLength?s.createObjectURL(l):\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAAC0lEQVQYV2NgAAIAAAUAAarVyFEAAAAASUVORK5CYII=\"}});return{cancel:function(){i.cancel(),a()}}};function xt(t,e,r){r[t]&&-1!==r[t].indexOf(e)||(r[t]=r[t]||[],r[t].push(e))}function bt(t,e,r){if(r&&r[t]){var n=r[t].indexOf(e);-1!==n&&r[t].splice(n,1)}}var _t=function(t,e){void 0===e&&(e={}),h(this,e),this.type=t},wt=function(t){function e(e,r){void 0===r&&(r={}),t.call(this,\"error\",h({error:e},r))}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(_t),kt=function(){};kt.prototype.on=function(t,e){return this._listeners=this._listeners||{},xt(t,e,this._listeners),this},kt.prototype.off=function(t,e){return bt(t,e,this._listeners),bt(t,e,this._oneTimeListeners),this},kt.prototype.once=function(t,e){return this._oneTimeListeners=this._oneTimeListeners||{},xt(t,e,this._oneTimeListeners),this},kt.prototype.fire=function(t,e){\"string\"==typeof t&&(t=new _t(t,e||{}));var r=t.type;if(this.listens(r)){t.target=this;for(var n=0,a=this._listeners&&this._listeners[r]?this._listeners[r].slice():[];n<a.length;n+=1)a[n].call(this,t);for(var i=0,o=this._oneTimeListeners&&this._oneTimeListeners[r]?this._oneTimeListeners[r].slice():[];i<o.length;i+=1){var s=o[i];bt(r,s,this._oneTimeListeners),s.call(this,t)}var l=this._eventedParent;l&&(h(t,\"function\"==typeof this._eventedParentData?this._eventedParentData():this._eventedParentData),l.fire(t))}else t instanceof wt&&console.error(t.error);return this},kt.prototype.listens=function(t){return this._listeners&&this._listeners[t]&&this._listeners[t].length>0||this._oneTimeListeners&&this._oneTimeListeners[t]&&this._oneTimeListeners[t].length>0||this._eventedParent&&this._eventedParent.listens(t)},kt.prototype.setEventedParent=function(t,e){return this._eventedParent=t,this._eventedParentData=e,this};var Tt={$version:8,$root:{version:{required:!0,type:\"enum\",values:[8]},name:{type:\"string\"},metadata:{type:\"*\"},center:{type:\"array\",value:\"number\"},zoom:{type:\"number\"},bearing:{type:\"number\",default:0,period:360,units:\"degrees\"},pitch:{type:\"number\",default:0,units:\"degrees\"},light:{type:\"light\"},sources:{required:!0,type:\"sources\"},sprite:{type:\"string\"},glyphs:{type:\"string\"},transition:{type:\"transition\"},layers:{required:!0,type:\"array\",value:\"layer\"}},sources:{\"*\":{type:\"source\"}},source:[\"source_vector\",\"source_raster\",\"source_raster_dem\",\"source_geojson\",\"source_video\",\"source_image\"],source_vector:{type:{required:!0,type:\"enum\",values:{vector:{}}},url:{type:\"string\"},tiles:{type:\"array\",value:\"string\"},bounds:{type:\"array\",value:\"number\",length:4,default:[-180,-85.051129,180,85.051129]},scheme:{type:\"enum\",values:{xyz:{},tms:{}},default:\"xyz\"},minzoom:{type:\"number\",default:0},maxzoom:{type:\"number\",default:22},attribution:{type:\"string\"},\"*\":{type:\"*\"}},source_raster:{type:{required:!0,type:\"enum\",values:{raster:{}}},url:{type:\"string\"},tiles:{type:\"array\",value:\"string\"},bounds:{type:\"array\",value:\"number\",length:4,default:[-180,-85.051129,180,85.051129]},minzoom:{type:\"number\",default:0},maxzoom:{type:\"number\",default:22},tileSize:{type:\"number\",default:512,units:\"pixels\"},scheme:{type:\"enum\",values:{xyz:{},tms:{}},default:\"xyz\"},attribution:{type:\"string\"},\"*\":{type:\"*\"}},source_raster_dem:{type:{required:!0,type:\"enum\",values:{\"raster-dem\":{}}},url:{type:\"string\"},tiles:{type:\"array\",value:\"string\"},bounds:{type:\"array\",value:\"number\",length:4,default:[-180,-85.051129,180,85.051129]},minzoom:{type:\"number\",default:0},maxzoom:{type:\"number\",default:22},tileSize:{type:\"number\",default:512,units:\"pixels\"},attribution:{type:\"string\"},encoding:{type:\"enum\",values:{terrarium:{},mapbox:{}},default:\"mapbox\"},\"*\":{type:\"*\"}},source_geojson:{type:{required:!0,type:\"enum\",values:{geojson:{}}},data:{type:\"*\"},maxzoom:{type:\"number\",default:18},attribution:{type:\"string\"},buffer:{type:\"number\",default:128,maximum:512,minimum:0},tolerance:{type:\"number\",default:.375},cluster:{type:\"boolean\",default:!1},clusterRadius:{type:\"number\",default:50,minimum:0},clusterMaxZoom:{type:\"number\"},clusterProperties:{type:\"*\"},lineMetrics:{type:\"boolean\",default:!1},generateId:{type:\"boolean\",default:!1}},source_video:{type:{required:!0,type:\"enum\",values:{video:{}}},urls:{required:!0,type:\"array\",value:\"string\"},coordinates:{required:!0,type:\"array\",length:4,value:{type:\"array\",length:2,value:\"number\"}}},source_image:{type:{required:!0,type:\"enum\",values:{image:{}}},url:{required:!0,type:\"string\"},coordinates:{required:!0,type:\"array\",length:4,value:{type:\"array\",length:2,value:\"number\"}}},layer:{id:{type:\"string\",required:!0},type:{type:\"enum\",values:{fill:{},line:{},symbol:{},circle:{},heatmap:{},\"fill-extrusion\":{},raster:{},hillshade:{},background:{}},required:!0},metadata:{type:\"*\"},source:{type:\"string\"},\"source-layer\":{type:\"string\"},minzoom:{type:\"number\",minimum:0,maximum:24},maxzoom:{type:\"number\",minimum:0,maximum:24},filter:{type:\"filter\"},layout:{type:\"layout\"},paint:{type:\"paint\"}},layout:[\"layout_fill\",\"layout_line\",\"layout_circle\",\"layout_heatmap\",\"layout_fill-extrusion\",\"layout_symbol\",\"layout_raster\",\"layout_hillshade\",\"layout_background\"],layout_background:{visibility:{type:\"enum\",values:{visible:{},none:{}},default:\"visible\",\"property-type\":\"constant\"}},layout_fill:{\"fill-sort-key\":{type:\"number\",expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},visibility:{type:\"enum\",values:{visible:{},none:{}},default:\"visible\",\"property-type\":\"constant\"}},layout_circle:{\"circle-sort-key\":{type:\"number\",expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},visibility:{type:\"enum\",values:{visible:{},none:{}},default:\"visible\",\"property-type\":\"constant\"}},layout_heatmap:{visibility:{type:\"enum\",values:{visible:{},none:{}},default:\"visible\",\"property-type\":\"constant\"}},\"layout_fill-extrusion\":{visibility:{type:\"enum\",values:{visible:{},none:{}},default:\"visible\",\"property-type\":\"constant\"}},layout_line:{\"line-cap\":{type:\"enum\",values:{butt:{},round:{},square:{}},default:\"butt\",expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"line-join\":{type:\"enum\",values:{bevel:{},round:{},miter:{}},default:\"miter\",expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"line-miter-limit\":{type:\"number\",default:2,requires:[{\"line-join\":\"miter\"}],expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"line-round-limit\":{type:\"number\",default:1.05,requires:[{\"line-join\":\"round\"}],expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"line-sort-key\":{type:\"number\",expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},visibility:{type:\"enum\",values:{visible:{},none:{}},default:\"visible\",\"property-type\":\"constant\"}},layout_symbol:{\"symbol-placement\":{type:\"enum\",values:{point:{},line:{},\"line-center\":{}},default:\"point\",expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"symbol-spacing\":{type:\"number\",default:250,minimum:1,units:\"pixels\",requires:[{\"symbol-placement\":\"line\"}],expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"symbol-avoid-edges\":{type:\"boolean\",default:!1,expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"symbol-sort-key\":{type:\"number\",expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"symbol-z-order\":{type:\"enum\",values:{auto:{},\"viewport-y\":{},source:{}},default:\"auto\",expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"icon-allow-overlap\":{type:\"boolean\",default:!1,requires:[\"icon-image\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"icon-ignore-placement\":{type:\"boolean\",default:!1,requires:[\"icon-image\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"icon-optional\":{type:\"boolean\",default:!1,requires:[\"icon-image\",\"text-field\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"icon-rotation-alignment\":{type:\"enum\",values:{map:{},viewport:{},auto:{}},default:\"auto\",requires:[\"icon-image\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"icon-size\":{type:\"number\",default:1,minimum:0,units:\"factor of the original icon size\",requires:[\"icon-image\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"icon-text-fit\":{type:\"enum\",values:{none:{},width:{},height:{},both:{}},default:\"none\",requires:[\"icon-image\",\"text-field\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"icon-text-fit-padding\":{type:\"array\",value:\"number\",length:4,default:[0,0,0,0],units:\"pixels\",requires:[\"icon-image\",\"text-field\",{\"icon-text-fit\":[\"both\",\"width\",\"height\"]}],expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"icon-image\":{type:\"string\",tokens:!0,expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"icon-rotate\":{type:\"number\",default:0,period:360,units:\"degrees\",requires:[\"icon-image\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"icon-padding\":{type:\"number\",default:2,minimum:0,units:\"pixels\",requires:[\"icon-image\"],expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"icon-keep-upright\":{type:\"boolean\",default:!1,requires:[\"icon-image\",{\"icon-rotation-alignment\":\"map\"},{\"symbol-placement\":[\"line\",\"line-center\"]}],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"icon-offset\":{type:\"array\",value:\"number\",length:2,default:[0,0],requires:[\"icon-image\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"icon-anchor\":{type:\"enum\",values:{center:{},left:{},right:{},top:{},bottom:{},\"top-left\":{},\"top-right\":{},\"bottom-left\":{},\"bottom-right\":{}},default:\"center\",requires:[\"icon-image\"],expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"icon-pitch-alignment\":{type:\"enum\",values:{map:{},viewport:{},auto:{}},default:\"auto\",requires:[\"icon-image\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"text-pitch-alignment\":{type:\"enum\",values:{map:{},viewport:{},auto:{}},default:\"auto\",requires:[\"text-field\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"text-rotation-alignment\":{type:\"enum\",values:{map:{},viewport:{},auto:{}},default:\"auto\",requires:[\"text-field\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"text-field\":{type:\"formatted\",default:\"\",tokens:!0,expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"text-font\":{type:\"array\",value:\"string\",default:[\"Open Sans Regular\",\"Arial Unicode MS Regular\"],requires:[\"text-field\"],expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"text-size\":{type:\"number\",default:16,minimum:0,units:\"pixels\",requires:[\"text-field\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"text-max-width\":{type:\"number\",default:10,minimum:0,units:\"ems\",requires:[\"text-field\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"text-line-height\":{type:\"number\",default:1.2,units:\"ems\",requires:[\"text-field\"],expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"text-letter-spacing\":{type:\"number\",default:0,units:\"ems\",requires:[\"text-field\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"text-justify\":{type:\"enum\",values:{auto:{},left:{},center:{},right:{}},default:\"center\",requires:[\"text-field\"],expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"text-radial-offset\":{type:\"number\",units:\"ems\",default:0,requires:[\"text-field\"],\"property-type\":\"data-driven\",expression:{interpolated:!0,parameters:[\"zoom\",\"feature\"]}},\"text-variable-anchor\":{type:\"array\",value:\"enum\",values:{center:{},left:{},right:{},top:{},bottom:{},\"top-left\":{},\"top-right\":{},\"bottom-left\":{},\"bottom-right\":{}},requires:[\"text-field\",{\"symbol-placement\":[\"point\"]}],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"text-anchor\":{type:\"enum\",values:{center:{},left:{},right:{},top:{},bottom:{},\"top-left\":{},\"top-right\":{},\"bottom-left\":{},\"bottom-right\":{}},default:\"center\",requires:[\"text-field\",{\"!\":\"text-variable-anchor\"}],expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"text-max-angle\":{type:\"number\",default:45,units:\"degrees\",requires:[\"text-field\",{\"symbol-placement\":[\"line\",\"line-center\"]}],expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"text-writing-mode\":{type:\"array\",value:\"enum\",values:{horizontal:{},vertical:{}},requires:[\"text-field\",{\"symbol-placement\":[\"point\"]}],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"text-rotate\":{type:\"number\",default:0,period:360,units:\"degrees\",requires:[\"text-field\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"text-padding\":{type:\"number\",default:2,minimum:0,units:\"pixels\",requires:[\"text-field\"],expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"text-keep-upright\":{type:\"boolean\",default:!0,requires:[\"text-field\",{\"text-rotation-alignment\":\"map\"},{\"symbol-placement\":[\"line\",\"line-center\"]}],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"text-transform\":{type:\"enum\",values:{none:{},uppercase:{},lowercase:{}},default:\"none\",requires:[\"text-field\"],expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"text-offset\":{type:\"array\",value:\"number\",units:\"ems\",length:2,default:[0,0],requires:[\"text-field\",{\"!\":\"text-radial-offset\"},{\"!\":\"text-variable-anchor\"}],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"data-driven\"},\"text-allow-overlap\":{type:\"boolean\",default:!1,requires:[\"text-field\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"text-ignore-placement\":{type:\"boolean\",default:!1,requires:[\"text-field\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"text-optional\":{type:\"boolean\",default:!1,requires:[\"text-field\",\"icon-image\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},visibility:{type:\"enum\",values:{visible:{},none:{}},default:\"visible\",\"property-type\":\"constant\"}},layout_raster:{visibility:{type:\"enum\",values:{visible:{},none:{}},default:\"visible\",\"property-type\":\"constant\"}},layout_hillshade:{visibility:{type:\"enum\",values:{visible:{},none:{}},default:\"visible\",\"property-type\":\"constant\"}},filter:{type:\"array\",value:\"*\"},filter_operator:{type:\"enum\",values:{\"==\":{},\"!=\":{},\">\":{},\">=\":{},\"<\":{},\"<=\":{},in:{},\"!in\":{},all:{},any:{},none:{},has:{},\"!has\":{}}},geometry_type:{type:\"enum\",values:{Point:{},LineString:{},Polygon:{}}},function:{expression:{type:\"expression\"},stops:{type:\"array\",value:\"function_stop\"},base:{type:\"number\",default:1,minimum:0},property:{type:\"string\",default:\"$zoom\"},type:{type:\"enum\",values:{identity:{},exponential:{},interval:{},categorical:{}},default:\"exponential\"},colorSpace:{type:\"enum\",values:{rgb:{},lab:{},hcl:{}},default:\"rgb\"},default:{type:\"*\",required:!1}},function_stop:{type:\"array\",minimum:0,maximum:22,value:[\"number\",\"color\"],length:2},expression:{type:\"array\",value:\"*\",minimum:1},expression_name:{type:\"enum\",values:{let:{group:\"Variable binding\"},var:{group:\"Variable binding\"},literal:{group:\"Types\"},array:{group:\"Types\"},at:{group:\"Lookup\"},case:{group:\"Decision\"},match:{group:\"Decision\"},coalesce:{group:\"Decision\"},step:{group:\"Ramps, scales, curves\"},interpolate:{group:\"Ramps, scales, curves\"},\"interpolate-hcl\":{group:\"Ramps, scales, curves\"},\"interpolate-lab\":{group:\"Ramps, scales, curves\"},ln2:{group:\"Math\"},pi:{group:\"Math\"},e:{group:\"Math\"},typeof:{group:\"Types\"},string:{group:\"Types\"},number:{group:\"Types\"},boolean:{group:\"Types\"},object:{group:\"Types\"},collator:{group:\"Types\"},format:{group:\"Types\"},\"number-format\":{group:\"Types\"},\"to-string\":{group:\"Types\"},\"to-number\":{group:\"Types\"},\"to-boolean\":{group:\"Types\"},\"to-rgba\":{group:\"Color\"},\"to-color\":{group:\"Types\"},rgb:{group:\"Color\"},rgba:{group:\"Color\"},get:{group:\"Lookup\"},has:{group:\"Lookup\"},length:{group:\"Lookup\"},properties:{group:\"Feature data\"},\"feature-state\":{group:\"Feature data\"},\"geometry-type\":{group:\"Feature data\"},id:{group:\"Feature data\"},zoom:{group:\"Zoom\"},\"heatmap-density\":{group:\"Heatmap\"},\"line-progress\":{group:\"Feature data\"},accumulated:{group:\"Feature data\"},\"+\":{group:\"Math\"},\"*\":{group:\"Math\"},\"-\":{group:\"Math\"},\"/\":{group:\"Math\"},\"%\":{group:\"Math\"},\"^\":{group:\"Math\"},sqrt:{group:\"Math\"},log10:{group:\"Math\"},ln:{group:\"Math\"},log2:{group:\"Math\"},sin:{group:\"Math\"},cos:{group:\"Math\"},tan:{group:\"Math\"},asin:{group:\"Math\"},acos:{group:\"Math\"},atan:{group:\"Math\"},min:{group:\"Math\"},max:{group:\"Math\"},round:{group:\"Math\"},abs:{group:\"Math\"},ceil:{group:\"Math\"},floor:{group:\"Math\"},\"==\":{group:\"Decision\"},\"!=\":{group:\"Decision\"},\">\":{group:\"Decision\"},\"<\":{group:\"Decision\"},\">=\":{group:\"Decision\"},\"<=\":{group:\"Decision\"},all:{group:\"Decision\"},any:{group:\"Decision\"},\"!\":{group:\"Decision\"},\"is-supported-script\":{group:\"String\"},upcase:{group:\"String\"},downcase:{group:\"String\"},concat:{group:\"String\"},\"resolved-locale\":{group:\"String\"}}},light:{anchor:{type:\"enum\",default:\"viewport\",values:{map:{},viewport:{}},\"property-type\":\"data-constant\",transition:!1,expression:{interpolated:!1,parameters:[\"zoom\"]}},position:{type:\"array\",default:[1.15,210,30],length:3,value:\"number\",\"property-type\":\"data-constant\",transition:!0,expression:{interpolated:!0,parameters:[\"zoom\"]}},color:{type:\"color\",\"property-type\":\"data-constant\",default:\"#ffffff\",expression:{interpolated:!0,parameters:[\"zoom\"]},transition:!0},intensity:{type:\"number\",\"property-type\":\"data-constant\",default:.5,minimum:0,maximum:1,expression:{interpolated:!0,parameters:[\"zoom\"]},transition:!0}},paint:[\"paint_fill\",\"paint_line\",\"paint_circle\",\"paint_heatmap\",\"paint_fill-extrusion\",\"paint_symbol\",\"paint_raster\",\"paint_hillshade\",\"paint_background\"],paint_fill:{\"fill-antialias\":{type:\"boolean\",default:!0,expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"fill-opacity\":{type:\"number\",default:1,minimum:0,maximum:1,transition:!0,expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"fill-color\":{type:\"color\",default:\"#000000\",transition:!0,requires:[{\"!\":\"fill-pattern\"}],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"fill-outline-color\":{type:\"color\",transition:!0,requires:[{\"!\":\"fill-pattern\"},{\"fill-antialias\":!0}],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"fill-translate\":{type:\"array\",value:\"number\",length:2,default:[0,0],transition:!0,units:\"pixels\",expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"fill-translate-anchor\":{type:\"enum\",values:{map:{},viewport:{}},default:\"map\",requires:[\"fill-translate\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"fill-pattern\":{type:\"string\",transition:!0,expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"cross-faded-data-driven\"}},\"paint_fill-extrusion\":{\"fill-extrusion-opacity\":{type:\"number\",default:1,minimum:0,maximum:1,transition:!0,expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"fill-extrusion-color\":{type:\"color\",default:\"#000000\",transition:!0,requires:[{\"!\":\"fill-extrusion-pattern\"}],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"fill-extrusion-translate\":{type:\"array\",value:\"number\",length:2,default:[0,0],transition:!0,units:\"pixels\",expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"fill-extrusion-translate-anchor\":{type:\"enum\",values:{map:{},viewport:{}},default:\"map\",requires:[\"fill-extrusion-translate\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"fill-extrusion-pattern\":{type:\"string\",transition:!0,expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"cross-faded-data-driven\"},\"fill-extrusion-height\":{type:\"number\",default:0,minimum:0,units:\"meters\",transition:!0,expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"fill-extrusion-base\":{type:\"number\",default:0,minimum:0,units:\"meters\",transition:!0,requires:[\"fill-extrusion-height\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"fill-extrusion-vertical-gradient\":{type:\"boolean\",default:!0,transition:!1,expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"}},paint_line:{\"line-opacity\":{type:\"number\",default:1,minimum:0,maximum:1,transition:!0,expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"line-color\":{type:\"color\",default:\"#000000\",transition:!0,requires:[{\"!\":\"line-pattern\"}],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"line-translate\":{type:\"array\",value:\"number\",length:2,default:[0,0],transition:!0,units:\"pixels\",expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"line-translate-anchor\":{type:\"enum\",values:{map:{},viewport:{}},default:\"map\",requires:[\"line-translate\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"line-width\":{type:\"number\",default:1,minimum:0,transition:!0,units:\"pixels\",expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"line-gap-width\":{type:\"number\",default:0,minimum:0,transition:!0,units:\"pixels\",expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"line-offset\":{type:\"number\",default:0,transition:!0,units:\"pixels\",expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"line-blur\":{type:\"number\",default:0,minimum:0,transition:!0,units:\"pixels\",expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"line-dasharray\":{type:\"array\",value:\"number\",minimum:0,transition:!0,units:\"line widths\",requires:[{\"!\":\"line-pattern\"}],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"cross-faded\"},\"line-pattern\":{type:\"string\",transition:!0,expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]},\"property-type\":\"cross-faded-data-driven\"},\"line-gradient\":{type:\"color\",transition:!1,requires:[{\"!\":\"line-dasharray\"},{\"!\":\"line-pattern\"},{source:\"geojson\",has:{lineMetrics:!0}}],expression:{interpolated:!0,parameters:[\"line-progress\"]},\"property-type\":\"color-ramp\"}},paint_circle:{\"circle-radius\":{type:\"number\",default:5,minimum:0,transition:!0,units:\"pixels\",expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"circle-color\":{type:\"color\",default:\"#000000\",transition:!0,expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"circle-blur\":{type:\"number\",default:0,transition:!0,expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"circle-opacity\":{type:\"number\",default:1,minimum:0,maximum:1,transition:!0,expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"circle-translate\":{type:\"array\",value:\"number\",length:2,default:[0,0],transition:!0,units:\"pixels\",expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"circle-translate-anchor\":{type:\"enum\",values:{map:{},viewport:{}},default:\"map\",requires:[\"circle-translate\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"circle-pitch-scale\":{type:\"enum\",values:{map:{},viewport:{}},default:\"map\",expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"circle-pitch-alignment\":{type:\"enum\",values:{map:{},viewport:{}},default:\"viewport\",expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"circle-stroke-width\":{type:\"number\",default:0,minimum:0,transition:!0,units:\"pixels\",expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"circle-stroke-color\":{type:\"color\",default:\"#000000\",transition:!0,expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"circle-stroke-opacity\":{type:\"number\",default:1,minimum:0,maximum:1,transition:!0,expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"}},paint_heatmap:{\"heatmap-radius\":{type:\"number\",default:30,minimum:1,transition:!0,units:\"pixels\",expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"heatmap-weight\":{type:\"number\",default:1,minimum:0,transition:!1,expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"heatmap-intensity\":{type:\"number\",default:1,minimum:0,transition:!0,expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"heatmap-color\":{type:\"color\",default:[\"interpolate\",[\"linear\"],[\"heatmap-density\"],0,\"rgba(0, 0, 255, 0)\",.1,\"royalblue\",.3,\"cyan\",.5,\"lime\",.7,\"yellow\",1,\"red\"],transition:!1,expression:{interpolated:!0,parameters:[\"heatmap-density\"]},\"property-type\":\"color-ramp\"},\"heatmap-opacity\":{type:\"number\",default:1,minimum:0,maximum:1,transition:!0,expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"}},paint_symbol:{\"icon-opacity\":{type:\"number\",default:1,minimum:0,maximum:1,transition:!0,requires:[\"icon-image\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"icon-color\":{type:\"color\",default:\"#000000\",transition:!0,requires:[\"icon-image\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"icon-halo-color\":{type:\"color\",default:\"rgba(0, 0, 0, 0)\",transition:!0,requires:[\"icon-image\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"icon-halo-width\":{type:\"number\",default:0,minimum:0,transition:!0,units:\"pixels\",requires:[\"icon-image\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"icon-halo-blur\":{type:\"number\",default:0,minimum:0,transition:!0,units:\"pixels\",requires:[\"icon-image\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"icon-translate\":{type:\"array\",value:\"number\",length:2,default:[0,0],transition:!0,units:\"pixels\",requires:[\"icon-image\"],expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"icon-translate-anchor\":{type:\"enum\",values:{map:{},viewport:{}},default:\"map\",requires:[\"icon-image\",\"icon-translate\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"text-opacity\":{type:\"number\",default:1,minimum:0,maximum:1,transition:!0,requires:[\"text-field\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"text-color\":{type:\"color\",default:\"#000000\",transition:!0,overridable:!0,requires:[\"text-field\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"text-halo-color\":{type:\"color\",default:\"rgba(0, 0, 0, 0)\",transition:!0,requires:[\"text-field\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"text-halo-width\":{type:\"number\",default:0,minimum:0,transition:!0,units:\"pixels\",requires:[\"text-field\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"text-halo-blur\":{type:\"number\",default:0,minimum:0,transition:!0,units:\"pixels\",requires:[\"text-field\"],expression:{interpolated:!0,parameters:[\"zoom\",\"feature\",\"feature-state\"]},\"property-type\":\"data-driven\"},\"text-translate\":{type:\"array\",value:\"number\",length:2,default:[0,0],transition:!0,units:\"pixels\",requires:[\"text-field\"],expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"text-translate-anchor\":{type:\"enum\",values:{map:{},viewport:{}},default:\"map\",requires:[\"text-field\",\"text-translate\"],expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"}},paint_raster:{\"raster-opacity\":{type:\"number\",default:1,minimum:0,maximum:1,transition:!0,expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"raster-hue-rotate\":{type:\"number\",default:0,period:360,transition:!0,units:\"degrees\",expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"raster-brightness-min\":{type:\"number\",default:0,minimum:0,maximum:1,transition:!0,expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"raster-brightness-max\":{type:\"number\",default:1,minimum:0,maximum:1,transition:!0,expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"raster-saturation\":{type:\"number\",default:0,minimum:-1,maximum:1,transition:!0,expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"raster-contrast\":{type:\"number\",default:0,minimum:-1,maximum:1,transition:!0,expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"raster-resampling\":{type:\"enum\",values:{linear:{},nearest:{}},default:\"linear\",expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"raster-fade-duration\":{type:\"number\",default:300,minimum:0,transition:!1,units:\"milliseconds\",expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"}},paint_hillshade:{\"hillshade-illumination-direction\":{type:\"number\",default:335,minimum:0,maximum:359,transition:!1,expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"hillshade-illumination-anchor\":{type:\"enum\",values:{map:{},viewport:{}},default:\"viewport\",expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"hillshade-exaggeration\":{type:\"number\",default:.5,minimum:0,maximum:1,transition:!0,expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"hillshade-shadow-color\":{type:\"color\",default:\"#000000\",transition:!0,expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"hillshade-highlight-color\":{type:\"color\",default:\"#FFFFFF\",transition:!0,expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"hillshade-accent-color\":{type:\"color\",default:\"#000000\",transition:!0,expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"}},paint_background:{\"background-color\":{type:\"color\",default:\"#000000\",transition:!0,requires:[{\"!\":\"background-pattern\"}],expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"},\"background-pattern\":{type:\"string\",transition:!0,expression:{interpolated:!1,parameters:[\"zoom\"]},\"property-type\":\"cross-faded\"},\"background-opacity\":{type:\"number\",default:1,minimum:0,maximum:1,transition:!0,expression:{interpolated:!0,parameters:[\"zoom\"]},\"property-type\":\"data-constant\"}},transition:{duration:{type:\"number\",default:300,minimum:0,units:\"milliseconds\"},delay:{type:\"number\",default:0,minimum:0,units:\"milliseconds\"}},\"property-type\":{\"data-driven\":{type:\"property-type\"},\"cross-faded\":{type:\"property-type\"},\"cross-faded-data-driven\":{type:\"property-type\"},\"color-ramp\":{type:\"property-type\"},\"data-constant\":{type:\"property-type\"},constant:{type:\"property-type\"}}},Mt=function(t,e,r,n){this.message=(t?t+\": \":\"\")+r,n&&(this.identifier=n),null!=e&&e.__line__&&(this.line=e.__line__)};function At(t){var e=t.key,r=t.value;return r?[new Mt(e,r,\"constants have been deprecated as of v8\")]:[]}function St(t){for(var e=[],r=arguments.length-1;r-- >0;)e[r]=arguments[r+1];for(var n=0,a=e;n<a.length;n+=1){var i=a[n];for(var o in i)t[o]=i[o]}return t}function Et(t){return t instanceof Number||t instanceof String||t instanceof Boolean}function Lt(t){return Et(t)?t.valueOf():t}function Ct(t){if(Array.isArray(t))return t.map(Ct);if(t instanceof Object&&!Et(t)){var e={};for(var r in t)e[r]=Ct(t[r]);return e}return Lt(t)}var Pt=function(t){function e(e,r){t.call(this,r),this.message=r,this.key=e}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Error),Ot=function(t,e){void 0===e&&(e=[]),this.parent=t,this.bindings={};for(var r=0,n=e;r<n.length;r+=1){var a=n[r],i=a[0],o=a[1];this.bindings[i]=o}};Ot.prototype.concat=function(t){return new Ot(this,t)},Ot.prototype.get=function(t){if(this.bindings[t])return this.bindings[t];if(this.parent)return this.parent.get(t);throw new Error(t+\" not found in scope.\")},Ot.prototype.has=function(t){return!!this.bindings[t]||!!this.parent&&this.parent.has(t)};var zt={kind:\"null\"},It={kind:\"number\"},Dt={kind:\"string\"},Rt={kind:\"boolean\"},Ft={kind:\"color\"},Bt={kind:\"object\"},Nt={kind:\"value\"},jt={kind:\"collator\"},Vt={kind:\"formatted\"};function Ut(t,e){return{kind:\"array\",itemType:t,N:e}}function qt(t){if(\"array\"===t.kind){var e=qt(t.itemType);return\"number\"==typeof t.N?\"array<\"+e+\", \"+t.N+\">\":\"value\"===t.itemType.kind?\"array\":\"array<\"+e+\">\"}return t.kind}var Ht=[zt,It,Dt,Rt,Ft,Vt,Bt,Ut(Nt)];function Gt(t,e){if(\"error\"===e.kind)return null;if(\"array\"===t.kind){if(\"array\"===e.kind&&(0===e.N&&\"value\"===e.itemType.kind||!Gt(t.itemType,e.itemType))&&(\"number\"!=typeof t.N||t.N===e.N))return null}else{if(t.kind===e.kind)return null;if(\"value\"===t.kind)for(var r=0,n=Ht;r<n.length;r+=1)if(!Gt(n[r],e))return null}return\"Expected \"+qt(t)+\" but found \"+qt(e)+\" instead.\"}var Yt=e(function(t,e){var r={transparent:[0,0,0,0],aliceblue:[240,248,255,1],antiquewhite:[250,235,215,1],aqua:[0,255,255,1],aquamarine:[127,255,212,1],azure:[240,255,255,1],beige:[245,245,220,1],bisque:[255,228,196,1],black:[0,0,0,1],blanchedalmond:[255,235,205,1],blue:[0,0,255,1],blueviolet:[138,43,226,1],brown:[165,42,42,1],burlywood:[222,184,135,1],cadetblue:[95,158,160,1],chartreuse:[127,255,0,1],chocolate:[210,105,30,1],coral:[255,127,80,1],cornflowerblue:[100,149,237,1],cornsilk:[255,248,220,1],crimson:[220,20,60,1],cyan:[0,255,255,1],darkblue:[0,0,139,1],darkcyan:[0,139,139,1],darkgoldenrod:[184,134,11,1],darkgray:[169,169,169,1],darkgreen:[0,100,0,1],darkgrey:[169,169,169,1],darkkhaki:[189,183,107,1],darkmagenta:[139,0,139,1],darkolivegreen:[85,107,47,1],darkorange:[255,140,0,1],darkorchid:[153,50,204,1],darkred:[139,0,0,1],darksalmon:[233,150,122,1],darkseagreen:[143,188,143,1],darkslateblue:[72,61,139,1],darkslategray:[47,79,79,1],darkslategrey:[47,79,79,1],darkturquoise:[0,206,209,1],darkviolet:[148,0,211,1],deeppink:[255,20,147,1],deepskyblue:[0,191,255,1],dimgray:[105,105,105,1],dimgrey:[105,105,105,1],dodgerblue:[30,144,255,1],firebrick:[178,34,34,1],floralwhite:[255,250,240,1],forestgreen:[34,139,34,1],fuchsia:[255,0,255,1],gainsboro:[220,220,220,1],ghostwhite:[248,248,255,1],gold:[255,215,0,1],goldenrod:[218,165,32,1],gray:[128,128,128,1],green:[0,128,0,1],greenyellow:[173,255,47,1],grey:[128,128,128,1],honeydew:[240,255,240,1],hotpink:[255,105,180,1],indianred:[205,92,92,1],indigo:[75,0,130,1],ivory:[255,255,240,1],khaki:[240,230,140,1],lavender:[230,230,250,1],lavenderblush:[255,240,245,1],lawngreen:[124,252,0,1],lemonchiffon:[255,250,205,1],lightblue:[173,216,230,1],lightcoral:[240,128,128,1],lightcyan:[224,255,255,1],lightgoldenrodyellow:[250,250,210,1],lightgray:[211,211,211,1],lightgreen:[144,238,144,1],lightgrey:[211,211,211,1],lightpink:[255,182,193,1],lightsalmon:[255,160,122,1],lightseagreen:[32,178,170,1],lightskyblue:[135,206,250,1],lightslategray:[119,136,153,1],lightslategrey:[119,136,153,1],lightsteelblue:[176,196,222,1],lightyellow:[255,255,224,1],lime:[0,255,0,1],limegreen:[50,205,50,1],linen:[250,240,230,1],magenta:[255,0,255,1],maroon:[128,0,0,1],mediumaquamarine:[102,205,170,1],mediumblue:[0,0,205,1],mediumorchid:[186,85,211,1],mediumpurple:[147,112,219,1],mediumseagreen:[60,179,113,1],mediumslateblue:[123,104,238,1],mediumspringgreen:[0,250,154,1],mediumturquoise:[72,209,204,1],mediumvioletred:[199,21,133,1],midnightblue:[25,25,112,1],mintcream:[245,255,250,1],mistyrose:[255,228,225,1],moccasin:[255,228,181,1],navajowhite:[255,222,173,1],navy:[0,0,128,1],oldlace:[253,245,230,1],olive:[128,128,0,1],olivedrab:[107,142,35,1],orange:[255,165,0,1],orangered:[255,69,0,1],orchid:[218,112,214,1],palegoldenrod:[238,232,170,1],palegreen:[152,251,152,1],paleturquoise:[175,238,238,1],palevioletred:[219,112,147,1],papayawhip:[255,239,213,1],peachpuff:[255,218,185,1],peru:[205,133,63,1],pink:[255,192,203,1],plum:[221,160,221,1],powderblue:[176,224,230,1],purple:[128,0,128,1],rebeccapurple:[102,51,153,1],red:[255,0,0,1],rosybrown:[188,143,143,1],royalblue:[65,105,225,1],saddlebrown:[139,69,19,1],salmon:[250,128,114,1],sandybrown:[244,164,96,1],seagreen:[46,139,87,1],seashell:[255,245,238,1],sienna:[160,82,45,1],silver:[192,192,192,1],skyblue:[135,206,235,1],slateblue:[106,90,205,1],slategray:[112,128,144,1],slategrey:[112,128,144,1],snow:[255,250,250,1],springgreen:[0,255,127,1],steelblue:[70,130,180,1],tan:[210,180,140,1],teal:[0,128,128,1],thistle:[216,191,216,1],tomato:[255,99,71,1],turquoise:[64,224,208,1],violet:[238,130,238,1],wheat:[245,222,179,1],white:[255,255,255,1],whitesmoke:[245,245,245,1],yellow:[255,255,0,1],yellowgreen:[154,205,50,1]};function n(t){return(t=Math.round(t))<0?0:t>255?255:t}function a(t){return t<0?0:t>1?1:t}function i(t){return\"%\"===t[t.length-1]?n(parseFloat(t)/100*255):n(parseInt(t))}function o(t){return\"%\"===t[t.length-1]?a(parseFloat(t)/100):a(parseFloat(t))}function s(t,e,r){return r<0?r+=1:r>1&&(r-=1),6*r<1?t+(e-t)*r*6:2*r<1?e:3*r<2?t+(e-t)*(2/3-r)*6:t}try{e.parseCSSColor=function(t){var e,a=t.replace(/ /g,\"\").toLowerCase();if(a in r)return r[a].slice();if(\"#\"===a[0])return 4===a.length?(e=parseInt(a.substr(1),16))>=0&&e<=4095?[(3840&e)>>4|(3840&e)>>8,240&e|(240&e)>>4,15&e|(15&e)<<4,1]:null:7===a.length&&(e=parseInt(a.substr(1),16))>=0&&e<=16777215?[(16711680&e)>>16,(65280&e)>>8,255&e,1]:null;var l=a.indexOf(\"(\"),c=a.indexOf(\")\");if(-1!==l&&c+1===a.length){var u=a.substr(0,l),h=a.substr(l+1,c-(l+1)).split(\",\"),f=1;switch(u){case\"rgba\":if(4!==h.length)return null;f=o(h.pop());case\"rgb\":return 3!==h.length?null:[i(h[0]),i(h[1]),i(h[2]),f];case\"hsla\":if(4!==h.length)return null;f=o(h.pop());case\"hsl\":if(3!==h.length)return null;var p=(parseFloat(h[0])%360+360)%360/360,d=o(h[1]),g=o(h[2]),v=g<=.5?g*(d+1):g+d-g*d,m=2*g-v;return[n(255*s(m,v,p+1/3)),n(255*s(m,v,p)),n(255*s(m,v,p-1/3)),f];default:return null}}return null}}catch(t){}}).parseCSSColor,Wt=function(t,e,r,n){void 0===n&&(n=1),this.r=t,this.g=e,this.b=r,this.a=n};Wt.parse=function(t){if(t){if(t instanceof Wt)return t;if(\"string\"==typeof t){var e=Yt(t);if(e)return new Wt(e[0]/255*e[3],e[1]/255*e[3],e[2]/255*e[3],e[3])}}},Wt.prototype.toString=function(){var t=this.toArray(),e=t[0],r=t[1],n=t[2],a=t[3];return\"rgba(\"+Math.round(e)+\",\"+Math.round(r)+\",\"+Math.round(n)+\",\"+a+\")\"},Wt.prototype.toArray=function(){var t=this.r,e=this.g,r=this.b,n=this.a;return 0===n?[0,0,0,0]:[255*t/n,255*e/n,255*r/n,n]},Wt.black=new Wt(0,0,0,1),Wt.white=new Wt(1,1,1,1),Wt.transparent=new Wt(0,0,0,0),Wt.red=new Wt(1,0,0,1);var Xt=function(t,e,r){this.sensitivity=t?e?\"variant\":\"case\":e?\"accent\":\"base\",this.locale=r,this.collator=new Intl.Collator(this.locale?this.locale:[],{sensitivity:this.sensitivity,usage:\"search\"})};Xt.prototype.compare=function(t,e){return this.collator.compare(t,e)},Xt.prototype.resolvedLocale=function(){return new Intl.Collator(this.locale?this.locale:[]).resolvedOptions().locale};var Zt=function(t,e,r,n){this.text=t,this.scale=e,this.fontStack=r,this.textColor=n},Jt=function(t){this.sections=t};function Kt(t,e,r,n){return\"number\"==typeof t&&t>=0&&t<=255&&\"number\"==typeof e&&e>=0&&e<=255&&\"number\"==typeof r&&r>=0&&r<=255?void 0===n||\"number\"==typeof n&&n>=0&&n<=1?null:\"Invalid rgba value [\"+[t,e,r,n].join(\", \")+\"]: 'a' must be between 0 and 1.\":\"Invalid rgba value [\"+(\"number\"==typeof n?[t,e,r,n]:[t,e,r]).join(\", \")+\"]: 'r', 'g', and 'b' must be between 0 and 255.\"}function Qt(t){if(null===t)return zt;if(\"string\"==typeof t)return Dt;if(\"boolean\"==typeof t)return Rt;if(\"number\"==typeof t)return It;if(t instanceof Wt)return Ft;if(t instanceof Xt)return jt;if(t instanceof Jt)return Vt;if(Array.isArray(t)){for(var e,r=t.length,n=0,a=t;n<a.length;n+=1){var i=Qt(a[n]);if(e){if(e===i)continue;e=Nt;break}e=i}return Ut(e||Nt,r)}return Bt}function $t(t){var e=typeof t;return null===t?\"\":\"string\"===e||\"number\"===e||\"boolean\"===e?String(t):t instanceof Wt||t instanceof Jt?t.toString():JSON.stringify(t)}Jt.fromString=function(t){return new Jt([new Zt(t,null,null,null)])},Jt.prototype.toString=function(){return this.sections.map(function(t){return t.text}).join(\"\")},Jt.prototype.serialize=function(){for(var t=[\"format\"],e=0,r=this.sections;e<r.length;e+=1){var n=r[e];t.push(n.text);var a={};n.fontStack&&(a[\"text-font\"]=[\"literal\",n.fontStack.split(\",\")]),n.scale&&(a[\"font-scale\"]=n.scale),n.textColor&&(a[\"text-color\"]=[\"rgba\"].concat(n.textColor.toArray())),t.push(a)}return t};var te=function(t,e){this.type=t,this.value=e};te.parse=function(t,e){if(2!==t.length)return e.error(\"'literal' expression requires exactly one argument, but found \"+(t.length-1)+\" instead.\");if(!function t(e){if(null===e)return!0;if(\"string\"==typeof e)return!0;if(\"boolean\"==typeof e)return!0;if(\"number\"==typeof e)return!0;if(e instanceof Wt)return!0;if(e instanceof Xt)return!0;if(e instanceof Jt)return!0;if(Array.isArray(e)){for(var r=0,n=e;r<n.length;r+=1)if(!t(n[r]))return!1;return!0}if(\"object\"==typeof e){for(var a in e)if(!t(e[a]))return!1;return!0}return!1}(t[1]))return e.error(\"invalid value\");var r=t[1],n=Qt(r),a=e.expectedType;return\"array\"!==n.kind||0!==n.N||!a||\"array\"!==a.kind||\"number\"==typeof a.N&&0!==a.N||(n=a),new te(n,r)},te.prototype.evaluate=function(){return this.value},te.prototype.eachChild=function(){},te.prototype.possibleOutputs=function(){return[this.value]},te.prototype.serialize=function(){return\"array\"===this.type.kind||\"object\"===this.type.kind?[\"literal\",this.value]:this.value instanceof Wt?[\"rgba\"].concat(this.value.toArray()):this.value instanceof Jt?this.value.serialize():this.value};var ee=function(t){this.name=\"ExpressionEvaluationError\",this.message=t};ee.prototype.toJSON=function(){return this.message};var re={string:Dt,number:It,boolean:Rt,object:Bt},ne=function(t,e){this.type=t,this.args=e};ne.parse=function(t,e){if(t.length<2)return e.error(\"Expected at least one argument.\");var r,n=1,a=t[0];if(\"array\"===a){var i,o;if(t.length>2){var s=t[1];if(\"string\"!=typeof s||!(s in re)||\"object\"===s)return e.error('The item type argument of \"array\" must be one of string, number, boolean',1);i=re[s],n++}else i=Nt;if(t.length>3){if(null!==t[2]&&(\"number\"!=typeof t[2]||t[2]<0||t[2]!==Math.floor(t[2])))return e.error('The length argument to \"array\" must be a positive integer literal',2);o=t[2],n++}r=Ut(i,o)}else r=re[a];for(var l=[];n<t.length;n++){var c=e.parse(t[n],n,Nt);if(!c)return null;l.push(c)}return new ne(r,l)},ne.prototype.evaluate=function(t){for(var e=0;e<this.args.length;e++){var r=this.args[e].evaluate(t);if(!Gt(this.type,Qt(r)))return r;if(e===this.args.length-1)throw new ee(\"Expected value to be of type \"+qt(this.type)+\", but found \"+qt(Qt(r))+\" instead.\")}return null},ne.prototype.eachChild=function(t){this.args.forEach(t)},ne.prototype.possibleOutputs=function(){var t;return(t=[]).concat.apply(t,this.args.map(function(t){return t.possibleOutputs()}))},ne.prototype.serialize=function(){var t=this.type,e=[t.kind];if(\"array\"===t.kind){var r=t.itemType;if(\"string\"===r.kind||\"number\"===r.kind||\"boolean\"===r.kind){e.push(r.kind);var n=t.N;(\"number\"==typeof n||this.args.length>1)&&e.push(n)}}return e.concat(this.args.map(function(t){return t.serialize()}))};var ae=function(t){this.type=Vt,this.sections=t};ae.parse=function(t,e){if(t.length<3)return e.error(\"Expected at least two arguments.\");if((t.length-1)%2!=0)return e.error(\"Expected an even number of arguments.\");for(var r=[],n=1;n<t.length-1;n+=2){var a=e.parse(t[n],1,Nt);if(!a)return null;var i=a.type.kind;if(\"string\"!==i&&\"value\"!==i&&\"null\"!==i)return e.error(\"Formatted text type must be 'string', 'value', or 'null'.\");var o=t[n+1];if(\"object\"!=typeof o||Array.isArray(o))return e.error(\"Format options argument must be an object.\");var s=null;if(o[\"font-scale\"]&&!(s=e.parse(o[\"font-scale\"],1,It)))return null;var l=null;if(o[\"text-font\"]&&!(l=e.parse(o[\"text-font\"],1,Ut(Dt))))return null;var c=null;if(o[\"text-color\"]&&!(c=e.parse(o[\"text-color\"],1,Ft)))return null;r.push({text:a,scale:s,font:l,textColor:c})}return new ae(r)},ae.prototype.evaluate=function(t){return new Jt(this.sections.map(function(e){return new Zt($t(e.text.evaluate(t)),e.scale?e.scale.evaluate(t):null,e.font?e.font.evaluate(t).join(\",\"):null,e.textColor?e.textColor.evaluate(t):null)}))},ae.prototype.eachChild=function(t){for(var e=0,r=this.sections;e<r.length;e+=1){var n=r[e];t(n.text),n.scale&&t(n.scale),n.font&&t(n.font),n.textColor&&t(n.textColor)}},ae.prototype.possibleOutputs=function(){return[void 0]},ae.prototype.serialize=function(){for(var t=[\"format\"],e=0,r=this.sections;e<r.length;e+=1){var n=r[e];t.push(n.text.serialize());var a={};n.scale&&(a[\"font-scale\"]=n.scale.serialize()),n.font&&(a[\"text-font\"]=n.font.serialize()),n.textColor&&(a[\"text-color\"]=n.textColor.serialize()),t.push(a)}return t};var ie={\"to-boolean\":Rt,\"to-color\":Ft,\"to-number\":It,\"to-string\":Dt},oe=function(t,e){this.type=t,this.args=e};oe.parse=function(t,e){if(t.length<2)return e.error(\"Expected at least one argument.\");var r=t[0];if((\"to-boolean\"===r||\"to-string\"===r)&&2!==t.length)return e.error(\"Expected one argument.\");for(var n=ie[r],a=[],i=1;i<t.length;i++){var o=e.parse(t[i],i,Nt);if(!o)return null;a.push(o)}return new oe(n,a)},oe.prototype.evaluate=function(t){if(\"boolean\"===this.type.kind)return Boolean(this.args[0].evaluate(t));if(\"color\"===this.type.kind){for(var e,r,n=0,a=this.args;n<a.length;n+=1){if(r=null,(e=a[n].evaluate(t))instanceof Wt)return e;if(\"string\"==typeof e){var i=t.parseColor(e);if(i)return i}else if(Array.isArray(e)&&!(r=e.length<3||e.length>4?\"Invalid rbga value \"+JSON.stringify(e)+\": expected an array containing either three or four numeric values.\":Kt(e[0],e[1],e[2],e[3])))return new Wt(e[0]/255,e[1]/255,e[2]/255,e[3])}throw new ee(r||\"Could not parse color from value '\"+(\"string\"==typeof e?e:String(JSON.stringify(e)))+\"'\")}if(\"number\"===this.type.kind){for(var o=null,s=0,l=this.args;s<l.length;s+=1){if(null===(o=l[s].evaluate(t)))return 0;var c=Number(o);if(!isNaN(c))return c}throw new ee(\"Could not convert \"+JSON.stringify(o)+\" to number.\")}return\"formatted\"===this.type.kind?Jt.fromString($t(this.args[0].evaluate(t))):$t(this.args[0].evaluate(t))},oe.prototype.eachChild=function(t){this.args.forEach(t)},oe.prototype.possibleOutputs=function(){var t;return(t=[]).concat.apply(t,this.args.map(function(t){return t.possibleOutputs()}))},oe.prototype.serialize=function(){if(\"formatted\"===this.type.kind)return new ae([{text:this.args[0],scale:null,font:null,textColor:null}]).serialize();var t=[\"to-\"+this.type.kind];return this.eachChild(function(e){t.push(e.serialize())}),t};var se=[\"Unknown\",\"Point\",\"LineString\",\"Polygon\"],le=function(){this.globals=null,this.feature=null,this.featureState=null,this.formattedSection=null,this._parseColorCache={}};le.prototype.id=function(){return this.feature&&\"id\"in this.feature?this.feature.id:null},le.prototype.geometryType=function(){return this.feature?\"number\"==typeof this.feature.type?se[this.feature.type]:this.feature.type:null},le.prototype.properties=function(){return this.feature&&this.feature.properties||{}},le.prototype.parseColor=function(t){var e=this._parseColorCache[t];return e||(e=this._parseColorCache[t]=Wt.parse(t)),e};var ce=function(t,e,r,n){this.name=t,this.type=e,this._evaluate=r,this.args=n};ce.prototype.evaluate=function(t){return this._evaluate(t,this.args)},ce.prototype.eachChild=function(t){this.args.forEach(t)},ce.prototype.possibleOutputs=function(){return[void 0]},ce.prototype.serialize=function(){return[this.name].concat(this.args.map(function(t){return t.serialize()}))},ce.parse=function(t,e){var r,n=t[0],a=ce.definitions[n];if(!a)return e.error('Unknown expression \"'+n+'\". If you wanted a literal array, use [\"literal\", [...]].',0);for(var i=Array.isArray(a)?a[0]:a.type,o=Array.isArray(a)?[[a[1],a[2]]]:a.overloads,s=o.filter(function(e){var r=e[0];return!Array.isArray(r)||r.length===t.length-1}),l=null,c=0,u=s;c<u.length;c+=1){var h=u[c],f=h[0],p=h[1];l=new ge(e.registry,e.path,null,e.scope);for(var d=[],g=!1,v=1;v<t.length;v++){var m=t[v],y=Array.isArray(f)?f[v-1]:f.type,x=l.parse(m,1+d.length,y);if(!x){g=!0;break}d.push(x)}if(!g)if(Array.isArray(f)&&f.length!==d.length)l.error(\"Expected \"+f.length+\" arguments, but found \"+d.length+\" instead.\");else{for(var b=0;b<d.length;b++){var _=Array.isArray(f)?f[b]:f.type,w=d[b];l.concat(b+1).checkSubtype(_,w.type)}if(0===l.errors.length)return new ce(n,i,p,d)}}if(1===s.length)(r=e.errors).push.apply(r,l.errors);else{for(var k=(s.length?s:o).map(function(t){var e;return e=t[0],Array.isArray(e)?\"(\"+e.map(qt).join(\", \")+\")\":\"(\"+qt(e.type)+\"...)\"}).join(\" | \"),T=[],M=1;M<t.length;M++){var A=e.parse(t[M],1+T.length);if(!A)return null;T.push(qt(A.type))}e.error(\"Expected arguments of type \"+k+\", but found (\"+T.join(\", \")+\") instead.\")}return null},ce.register=function(t,e){for(var r in ce.definitions=e,e)t[r]=ce};var ue=function(t,e,r){this.type=jt,this.locale=r,this.caseSensitive=t,this.diacriticSensitive=e};function he(t){if(t instanceof ce){if(\"get\"===t.name&&1===t.args.length)return!1;if(\"feature-state\"===t.name)return!1;if(\"has\"===t.name&&1===t.args.length)return!1;if(\"properties\"===t.name||\"geometry-type\"===t.name||\"id\"===t.name)return!1;if(/^filter-/.test(t.name))return!1}var e=!0;return t.eachChild(function(t){e&&!he(t)&&(e=!1)}),e}function fe(t){if(t instanceof ce&&\"feature-state\"===t.name)return!1;var e=!0;return t.eachChild(function(t){e&&!fe(t)&&(e=!1)}),e}function pe(t,e){if(t instanceof ce&&e.indexOf(t.name)>=0)return!1;var r=!0;return t.eachChild(function(t){r&&!pe(t,e)&&(r=!1)}),r}ue.parse=function(t,e){if(2!==t.length)return e.error(\"Expected one argument.\");var r=t[1];if(\"object\"!=typeof r||Array.isArray(r))return e.error(\"Collator options argument must be an object.\");var n=e.parse(void 0!==r[\"case-sensitive\"]&&r[\"case-sensitive\"],1,Rt);if(!n)return null;var a=e.parse(void 0!==r[\"diacritic-sensitive\"]&&r[\"diacritic-sensitive\"],1,Rt);if(!a)return null;var i=null;return r.locale&&!(i=e.parse(r.locale,1,Dt))?null:new ue(n,a,i)},ue.prototype.evaluate=function(t){return new Xt(this.caseSensitive.evaluate(t),this.diacriticSensitive.evaluate(t),this.locale?this.locale.evaluate(t):null)},ue.prototype.eachChild=function(t){t(this.caseSensitive),t(this.diacriticSensitive),this.locale&&t(this.locale)},ue.prototype.possibleOutputs=function(){return[void 0]},ue.prototype.serialize=function(){var t={};return t[\"case-sensitive\"]=this.caseSensitive.serialize(),t[\"diacritic-sensitive\"]=this.diacriticSensitive.serialize(),this.locale&&(t.locale=this.locale.serialize()),[\"collator\",t]};var de=function(t,e){this.type=e.type,this.name=t,this.boundExpression=e};de.parse=function(t,e){if(2!==t.length||\"string\"!=typeof t[1])return e.error(\"'var' expression requires exactly one string literal argument.\");var r=t[1];return e.scope.has(r)?new de(r,e.scope.get(r)):e.error('Unknown variable \"'+r+'\". Make sure \"'+r+'\" has been bound in an enclosing \"let\" expression before using it.',1)},de.prototype.evaluate=function(t){return this.boundExpression.evaluate(t)},de.prototype.eachChild=function(){},de.prototype.possibleOutputs=function(){return[void 0]},de.prototype.serialize=function(){return[\"var\",this.name]};var ge=function(t,e,r,n,a){void 0===e&&(e=[]),void 0===n&&(n=new Ot),void 0===a&&(a=[]),this.registry=t,this.path=e,this.key=e.map(function(t){return\"[\"+t+\"]\"}).join(\"\"),this.scope=n,this.errors=a,this.expectedType=r};function ve(t,e){for(var r,n,a=t.length-1,i=0,o=a,s=0;i<=o;)if(r=t[s=Math.floor((i+o)/2)],n=t[s+1],r<=e){if(s===a||e<n)return s;i=s+1}else{if(!(r>e))throw new ee(\"Input is not a number.\");o=s-1}return 0}ge.prototype.parse=function(t,e,r,n,a){return void 0===a&&(a={}),e?this.concat(e,r,n)._parse(t,a):this._parse(t,a)},ge.prototype._parse=function(t,e){function r(t,e,r){return\"assert\"===r?new ne(e,[t]):\"coerce\"===r?new oe(e,[t]):t}if(null!==t&&\"string\"!=typeof t&&\"boolean\"!=typeof t&&\"number\"!=typeof t||(t=[\"literal\",t]),Array.isArray(t)){if(0===t.length)return this.error('Expected an array with at least one element. If you wanted a literal array, use [\"literal\", []].');var n=t[0];if(\"string\"!=typeof n)return this.error(\"Expression name must be a string, but found \"+typeof n+' instead. If you wanted a literal array, use [\"literal\", [...]].',0),null;var a=this.registry[n];if(a){var i=a.parse(t,this);if(!i)return null;if(this.expectedType){var o=this.expectedType,s=i.type;if(\"string\"!==o.kind&&\"number\"!==o.kind&&\"boolean\"!==o.kind&&\"object\"!==o.kind&&\"array\"!==o.kind||\"value\"!==s.kind)if(\"color\"!==o.kind&&\"formatted\"!==o.kind||\"value\"!==s.kind&&\"string\"!==s.kind){if(this.checkSubtype(o,s))return null}else i=r(i,o,e.typeAnnotation||\"coerce\");else i=r(i,o,e.typeAnnotation||\"assert\")}if(!(i instanceof te)&&function t(e){if(e instanceof de)return t(e.boundExpression);if(e instanceof ce&&\"error\"===e.name)return!1;if(e instanceof ue)return!1;var r=e instanceof oe||e instanceof ne,n=!0;return e.eachChild(function(e){n=r?n&&t(e):n&&e instanceof te}),!!n&&(he(e)&&pe(e,[\"zoom\",\"heatmap-density\",\"line-progress\",\"accumulated\",\"is-supported-script\"]))}(i)){var l=new le;try{i=new te(i.type,i.evaluate(l))}catch(t){return this.error(t.message),null}}return i}return this.error('Unknown expression \"'+n+'\". If you wanted a literal array, use [\"literal\", [...]].',0)}return void 0===t?this.error(\"'undefined' value invalid. Use null instead.\"):\"object\"==typeof t?this.error('Bare objects invalid. Use [\"literal\", {...}] instead.'):this.error(\"Expected an array, but found \"+typeof t+\" instead.\")},ge.prototype.concat=function(t,e,r){var n=\"number\"==typeof t?this.path.concat(t):this.path,a=r?this.scope.concat(r):this.scope;return new ge(this.registry,n,e||null,a,this.errors)},ge.prototype.error=function(t){for(var e=[],r=arguments.length-1;r-- >0;)e[r]=arguments[r+1];var n=\"\"+this.key+e.map(function(t){return\"[\"+t+\"]\"}).join(\"\");this.errors.push(new Pt(n,t))},ge.prototype.checkSubtype=function(t,e){var r=Gt(t,e);return r&&this.error(r),r};var me=function(t,e,r){this.type=t,this.input=e,this.labels=[],this.outputs=[];for(var n=0,a=r;n<a.length;n+=1){var i=a[n],o=i[0],s=i[1];this.labels.push(o),this.outputs.push(s)}};function ye(t,e,r){return t*(1-r)+e*r}me.parse=function(t,e){if(t.length-1<4)return e.error(\"Expected at least 4 arguments, but found only \"+(t.length-1)+\".\");if((t.length-1)%2!=0)return e.error(\"Expected an even number of arguments.\");var r=e.parse(t[1],1,It);if(!r)return null;var n=[],a=null;e.expectedType&&\"value\"!==e.expectedType.kind&&(a=e.expectedType);for(var i=1;i<t.length;i+=2){var o=1===i?-1/0:t[i],s=t[i+1],l=i,c=i+1;if(\"number\"!=typeof o)return e.error('Input/output pairs for \"step\" expressions must be defined using literal numeric values (not computed expressions) for the input values.',l);if(n.length&&n[n.length-1][0]>=o)return e.error('Input/output pairs for \"step\" expressions must be arranged with input values in strictly ascending order.',l);var u=e.parse(s,c,a);if(!u)return null;a=a||u.type,n.push([o,u])}return new me(a,r,n)},me.prototype.evaluate=function(t){var e=this.labels,r=this.outputs;if(1===e.length)return r[0].evaluate(t);var n=this.input.evaluate(t);if(n<=e[0])return r[0].evaluate(t);var a=e.length;return n>=e[a-1]?r[a-1].evaluate(t):r[ve(e,n)].evaluate(t)},me.prototype.eachChild=function(t){t(this.input);for(var e=0,r=this.outputs;e<r.length;e+=1)t(r[e])},me.prototype.possibleOutputs=function(){var t;return(t=[]).concat.apply(t,this.outputs.map(function(t){return t.possibleOutputs()}))},me.prototype.serialize=function(){for(var t=[\"step\",this.input.serialize()],e=0;e<this.labels.length;e++)e>0&&t.push(this.labels[e]),t.push(this.outputs[e].serialize());return t};var xe=Object.freeze({number:ye,color:function(t,e,r){return new Wt(ye(t.r,e.r,r),ye(t.g,e.g,r),ye(t.b,e.b,r),ye(t.a,e.a,r))},array:function(t,e,r){return t.map(function(t,n){return ye(t,e[n],r)})}}),be=.95047,_e=1,we=1.08883,ke=4/29,Te=6/29,Me=3*Te*Te,Ae=Te*Te*Te,Se=Math.PI/180,Ee=180/Math.PI;function Le(t){return t>Ae?Math.pow(t,1/3):t/Me+ke}function Ce(t){return t>Te?t*t*t:Me*(t-ke)}function Pe(t){return 255*(t<=.0031308?12.92*t:1.055*Math.pow(t,1/2.4)-.055)}function Oe(t){return(t/=255)<=.04045?t/12.92:Math.pow((t+.055)/1.055,2.4)}function ze(t){var e=Oe(t.r),r=Oe(t.g),n=Oe(t.b),a=Le((.4124564*e+.3575761*r+.1804375*n)/be),i=Le((.2126729*e+.7151522*r+.072175*n)/_e);return{l:116*i-16,a:500*(a-i),b:200*(i-Le((.0193339*e+.119192*r+.9503041*n)/we)),alpha:t.a}}function Ie(t){var e=(t.l+16)/116,r=isNaN(t.a)?e:e+t.a/500,n=isNaN(t.b)?e:e-t.b/200;return e=_e*Ce(e),r=be*Ce(r),n=we*Ce(n),new Wt(Pe(3.2404542*r-1.5371385*e-.4985314*n),Pe(-.969266*r+1.8760108*e+.041556*n),Pe(.0556434*r-.2040259*e+1.0572252*n),t.alpha)}function De(t,e,r){var n=e-t;return t+r*(n>180||n<-180?n-360*Math.round(n/360):n)}var Re={forward:ze,reverse:Ie,interpolate:function(t,e,r){return{l:ye(t.l,e.l,r),a:ye(t.a,e.a,r),b:ye(t.b,e.b,r),alpha:ye(t.alpha,e.alpha,r)}}},Fe={forward:function(t){var e=ze(t),r=e.l,n=e.a,a=e.b,i=Math.atan2(a,n)*Ee;return{h:i<0?i+360:i,c:Math.sqrt(n*n+a*a),l:r,alpha:t.a}},reverse:function(t){var e=t.h*Se,r=t.c;return Ie({l:t.l,a:Math.cos(e)*r,b:Math.sin(e)*r,alpha:t.alpha})},interpolate:function(t,e,r){return{h:De(t.h,e.h,r),c:ye(t.c,e.c,r),l:ye(t.l,e.l,r),alpha:ye(t.alpha,e.alpha,r)}}},Be=Object.freeze({lab:Re,hcl:Fe}),Ne=function(t,e,r,n,a){this.type=t,this.operator=e,this.interpolation=r,this.input=n,this.labels=[],this.outputs=[];for(var i=0,o=a;i<o.length;i+=1){var s=o[i],l=s[0],c=s[1];this.labels.push(l),this.outputs.push(c)}};function je(t,e,r,n){var a=n-r,i=t-r;return 0===a?0:1===e?i/a:(Math.pow(e,i)-1)/(Math.pow(e,a)-1)}Ne.interpolationFactor=function(t,e,n,a){var i=0;if(\"exponential\"===t.name)i=je(e,t.base,n,a);else if(\"linear\"===t.name)i=je(e,1,n,a);else if(\"cubic-bezier\"===t.name){var o=t.controlPoints;i=new r(o[0],o[1],o[2],o[3]).solve(je(e,1,n,a))}return i},Ne.parse=function(t,e){var r=t[0],n=t[1],a=t[2],i=t.slice(3);if(!Array.isArray(n)||0===n.length)return e.error(\"Expected an interpolation type expression.\",1);if(\"linear\"===n[0])n={name:\"linear\"};else if(\"exponential\"===n[0]){var o=n[1];if(\"number\"!=typeof o)return e.error(\"Exponential interpolation requires a numeric base.\",1,1);n={name:\"exponential\",base:o}}else{if(\"cubic-bezier\"!==n[0])return e.error(\"Unknown interpolation type \"+String(n[0]),1,0);var s=n.slice(1);if(4!==s.length||s.some(function(t){return\"number\"!=typeof t||t<0||t>1}))return e.error(\"Cubic bezier interpolation requires four numeric arguments with values between 0 and 1.\",1);n={name:\"cubic-bezier\",controlPoints:s}}if(t.length-1<4)return e.error(\"Expected at least 4 arguments, but found only \"+(t.length-1)+\".\");if((t.length-1)%2!=0)return e.error(\"Expected an even number of arguments.\");if(!(a=e.parse(a,2,It)))return null;var l=[],c=null;\"interpolate-hcl\"===r||\"interpolate-lab\"===r?c=Ft:e.expectedType&&\"value\"!==e.expectedType.kind&&(c=e.expectedType);for(var u=0;u<i.length;u+=2){var h=i[u],f=i[u+1],p=u+3,d=u+4;if(\"number\"!=typeof h)return e.error('Input/output pairs for \"interpolate\" expressions must be defined using literal numeric values (not computed expressions) for the input values.',p);if(l.length&&l[l.length-1][0]>=h)return e.error('Input/output pairs for \"interpolate\" expressions must be arranged with input values in strictly ascending order.',p);var g=e.parse(f,d,c);if(!g)return null;c=c||g.type,l.push([h,g])}return\"number\"===c.kind||\"color\"===c.kind||\"array\"===c.kind&&\"number\"===c.itemType.kind&&\"number\"==typeof c.N?new Ne(c,r,n,a,l):e.error(\"Type \"+qt(c)+\" is not interpolatable.\")},Ne.prototype.evaluate=function(t){var e=this.labels,r=this.outputs;if(1===e.length)return r[0].evaluate(t);var n=this.input.evaluate(t);if(n<=e[0])return r[0].evaluate(t);var a=e.length;if(n>=e[a-1])return r[a-1].evaluate(t);var i=ve(e,n),o=e[i],s=e[i+1],l=Ne.interpolationFactor(this.interpolation,n,o,s),c=r[i].evaluate(t),u=r[i+1].evaluate(t);return\"interpolate\"===this.operator?xe[this.type.kind.toLowerCase()](c,u,l):\"interpolate-hcl\"===this.operator?Fe.reverse(Fe.interpolate(Fe.forward(c),Fe.forward(u),l)):Re.reverse(Re.interpolate(Re.forward(c),Re.forward(u),l))},Ne.prototype.eachChild=function(t){t(this.input);for(var e=0,r=this.outputs;e<r.length;e+=1)t(r[e])},Ne.prototype.possibleOutputs=function(){var t;return(t=[]).concat.apply(t,this.outputs.map(function(t){return t.possibleOutputs()}))},Ne.prototype.serialize=function(){var t;t=\"linear\"===this.interpolation.name?[\"linear\"]:\"exponential\"===this.interpolation.name?1===this.interpolation.base?[\"linear\"]:[\"exponential\",this.interpolation.base]:[\"cubic-bezier\"].concat(this.interpolation.controlPoints);for(var e=[this.operator,t,this.input.serialize()],r=0;r<this.labels.length;r++)e.push(this.labels[r],this.outputs[r].serialize());return e};var Ve=function(t,e){this.type=t,this.args=e};Ve.parse=function(t,e){if(t.length<2)return e.error(\"Expectected at least one argument.\");var r=null,n=e.expectedType;n&&\"value\"!==n.kind&&(r=n);for(var a=[],i=0,o=t.slice(1);i<o.length;i+=1){var s=o[i],l=e.parse(s,1+a.length,r,void 0,{typeAnnotation:\"omit\"});if(!l)return null;r=r||l.type,a.push(l)}var c=n&&a.some(function(t){return Gt(n,t.type)});return new Ve(c?Nt:r,a)},Ve.prototype.evaluate=function(t){for(var e=null,r=0,n=this.args;r<n.length&&null===(e=n[r].evaluate(t));r+=1);return e},Ve.prototype.eachChild=function(t){this.args.forEach(t)},Ve.prototype.possibleOutputs=function(){var t;return(t=[]).concat.apply(t,this.args.map(function(t){return t.possibleOutputs()}))},Ve.prototype.serialize=function(){var t=[\"coalesce\"];return this.eachChild(function(e){t.push(e.serialize())}),t};var Ue=function(t,e){this.type=e.type,this.bindings=[].concat(t),this.result=e};Ue.prototype.evaluate=function(t){return this.result.evaluate(t)},Ue.prototype.eachChild=function(t){for(var e=0,r=this.bindings;e<r.length;e+=1)t(r[e][1]);t(this.result)},Ue.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 3 arguments, but found \"+(t.length-1)+\" instead.\");for(var r=[],n=1;n<t.length-1;n+=2){var a=t[n];if(\"string\"!=typeof a)return e.error(\"Expected string, but found \"+typeof a+\" instead.\",n);if(/[^a-zA-Z0-9_]/.test(a))return e.error(\"Variable names must contain only alphanumeric characters or '_'.\",n);var i=e.parse(t[n+1],n+1);if(!i)return null;r.push([a,i])}var o=e.parse(t[t.length-1],t.length-1,e.expectedType,r);return o?new Ue(r,o):null},Ue.prototype.possibleOutputs=function(){return this.result.possibleOutputs()},Ue.prototype.serialize=function(){for(var t=[\"let\"],e=0,r=this.bindings;e<r.length;e+=1){var n=r[e],a=n[0],i=n[1];t.push(a,i.serialize())}return t.push(this.result.serialize()),t};var qe=function(t,e,r){this.type=t,this.index=e,this.input=r};qe.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,It),n=e.parse(t[2],2,Ut(e.expectedType||Nt));if(!r||!n)return null;var a=n.type;return new qe(a.itemType,r,n)},qe.prototype.evaluate=function(t){var e=this.index.evaluate(t),r=this.input.evaluate(t);if(e<0)throw new ee(\"Array index out of bounds: \"+e+\" < 0.\");if(e>=r.length)throw new ee(\"Array index out of bounds: \"+e+\" > \"+(r.length-1)+\".\");if(e!==Math.floor(e))throw new ee(\"Array index must be an integer, but found \"+e+\" instead.\");return r[e]},qe.prototype.eachChild=function(t){t(this.index),t(this.input)},qe.prototype.possibleOutputs=function(){return[void 0]},qe.prototype.serialize=function(){return[\"at\",this.index.serialize(),this.input.serialize()]};var He=function(t,e,r,n,a,i){this.inputType=t,this.type=e,this.input=r,this.cases=n,this.outputs=a,this.otherwise=i};He.parse=function(t,e){if(t.length<5)return e.error(\"Expected at least 4 arguments, but found only \"+(t.length-1)+\".\");if(t.length%2!=1)return e.error(\"Expected an even number of arguments.\");var r,n;e.expectedType&&\"value\"!==e.expectedType.kind&&(n=e.expectedType);for(var a={},i=[],o=2;o<t.length-1;o+=2){var s=t[o],l=t[o+1];Array.isArray(s)||(s=[s]);var c=e.concat(o);if(0===s.length)return c.error(\"Expected at least one branch label.\");for(var u=0,h=s;u<h.length;u+=1){var f=h[u];if(\"number\"!=typeof f&&\"string\"!=typeof f)return c.error(\"Branch labels must be numbers or strings.\");if(\"number\"==typeof f&&Math.abs(f)>Number.MAX_SAFE_INTEGER)return c.error(\"Branch labels must be integers no larger than \"+Number.MAX_SAFE_INTEGER+\".\");if(\"number\"==typeof f&&Math.floor(f)!==f)return c.error(\"Numeric branch labels must be integer values.\");if(r){if(c.checkSubtype(r,Qt(f)))return null}else r=Qt(f);if(void 0!==a[String(f)])return c.error(\"Branch labels must be unique.\");a[String(f)]=i.length}var p=e.parse(l,o,n);if(!p)return null;n=n||p.type,i.push(p)}var d=e.parse(t[1],1,Nt);if(!d)return null;var g=e.parse(t[t.length-1],t.length-1,n);return g?\"value\"!==d.type.kind&&e.concat(1).checkSubtype(r,d.type)?null:new He(r,n,d,a,i,g):null},He.prototype.evaluate=function(t){var e=this.input.evaluate(t);return(Qt(e)===this.inputType&&this.outputs[this.cases[e]]||this.otherwise).evaluate(t)},He.prototype.eachChild=function(t){t(this.input),this.outputs.forEach(t),t(this.otherwise)},He.prototype.possibleOutputs=function(){var t;return(t=[]).concat.apply(t,this.outputs.map(function(t){return t.possibleOutputs()})).concat(this.otherwise.possibleOutputs())},He.prototype.serialize=function(){for(var t=this,e=[\"match\",this.input.serialize()],r=[],n={},a=0,i=Object.keys(this.cases).sort();a<i.length;a+=1){var o=i[a];void 0===(h=n[this.cases[o]])?(n[this.cases[o]]=r.length,r.push([this.cases[o],[o]])):r[h][1].push(o)}for(var s=function(e){return\"number\"===t.inputType.kind?Number(e):e},l=0,c=r;l<c.length;l+=1){var u=c[l],h=u[0],f=u[1];1===f.length?e.push(s(f[0])):e.push(f.map(s)),e.push(this.outputs[outputIndex$1].serialize())}return e.push(this.otherwise.serialize()),e};var Ge=function(t,e,r){this.type=t,this.branches=e,this.otherwise=r};function Ye(t,e){return\"==\"===t||\"!=\"===t?\"boolean\"===e.kind||\"string\"===e.kind||\"number\"===e.kind||\"null\"===e.kind||\"value\"===e.kind:\"string\"===e.kind||\"number\"===e.kind||\"value\"===e.kind}function We(t,e,r,n){return 0===n.compare(e,r)}function Xe(t,e,r){var n=\"==\"!==t&&\"!=\"!==t;return function(){function a(t,e,r){this.type=Rt,this.lhs=t,this.rhs=e,this.collator=r,this.hasUntypedArgument=\"value\"===t.type.kind||\"value\"===e.type.kind}return a.parse=function(t,e){if(3!==t.length&&4!==t.length)return e.error(\"Expected two or three arguments.\");var r=t[0],i=e.parse(t[1],1,Nt);if(!i)return null;if(!Ye(r,i.type))return e.concat(1).error('\"'+r+\"\\\" comparisons are not supported for type '\"+qt(i.type)+\"'.\");var o=e.parse(t[2],2,Nt);if(!o)return null;if(!Ye(r,o.type))return e.concat(2).error('\"'+r+\"\\\" comparisons are not supported for type '\"+qt(o.type)+\"'.\");if(i.type.kind!==o.type.kind&&\"value\"!==i.type.kind&&\"value\"!==o.type.kind)return e.error(\"Cannot compare types '\"+qt(i.type)+\"' and '\"+qt(o.type)+\"'.\");n&&(\"value\"===i.type.kind&&\"value\"!==o.type.kind?i=new ne(o.type,[i]):\"value\"!==i.type.kind&&\"value\"===o.type.kind&&(o=new ne(i.type,[o])));var s=null;if(4===t.length){if(\"string\"!==i.type.kind&&\"string\"!==o.type.kind&&\"value\"!==i.type.kind&&\"value\"!==o.type.kind)return e.error(\"Cannot use collator to compare non-string types.\");if(!(s=e.parse(t[3],3,jt)))return null}return new a(i,o,s)},a.prototype.evaluate=function(a){var i=this.lhs.evaluate(a),o=this.rhs.evaluate(a);if(n&&this.hasUntypedArgument){var s=Qt(i),l=Qt(o);if(s.kind!==l.kind||\"string\"!==s.kind&&\"number\"!==s.kind)throw new ee('Expected arguments for \"'+t+'\" to be (string, string) or (number, number), but found ('+s.kind+\", \"+l.kind+\") instead.\")}if(this.collator&&!n&&this.hasUntypedArgument){var c=Qt(i),u=Qt(o);if(\"string\"!==c.kind||\"string\"!==u.kind)return e(a,i,o)}return this.collator?r(a,i,o,this.collator.evaluate(a)):e(a,i,o)},a.prototype.eachChild=function(t){t(this.lhs),t(this.rhs),this.collator&&t(this.collator)},a.prototype.possibleOutputs=function(){return[!0,!1]},a.prototype.serialize=function(){var e=[t];return this.eachChild(function(t){e.push(t.serialize())}),e},a}()}Ge.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 3 arguments, but found only \"+(t.length-1)+\".\");if(t.length%2!=0)return e.error(\"Expected an odd number of arguments.\");var r;e.expectedType&&\"value\"!==e.expectedType.kind&&(r=e.expectedType);for(var n=[],a=1;a<t.length-1;a+=2){var i=e.parse(t[a],a,Rt);if(!i)return null;var o=e.parse(t[a+1],a+1,r);if(!o)return null;n.push([i,o]),r=r||o.type}var s=e.parse(t[t.length-1],t.length-1,r);return s?new Ge(r,n,s):null},Ge.prototype.evaluate=function(t){for(var e=0,r=this.branches;e<r.length;e+=1){var n=r[e],a=n[0],i=n[1];if(a.evaluate(t))return i.evaluate(t)}return this.otherwise.evaluate(t)},Ge.prototype.eachChild=function(t){for(var e=0,r=this.branches;e<r.length;e+=1){var n=r[e],a=n[0],i=n[1];t(a),t(i)}t(this.otherwise)},Ge.prototype.possibleOutputs=function(){var t;return(t=[]).concat.apply(t,this.branches.map(function(t){return t[0],t[1].possibleOutputs()})).concat(this.otherwise.possibleOutputs())},Ge.prototype.serialize=function(){var t=[\"case\"];return this.eachChild(function(e){t.push(e.serialize())}),t};var Ze=Xe(\"==\",function(t,e,r){return e===r},We),Je=Xe(\"!=\",function(t,e,r){return e!==r},function(t,e,r,n){return!We(0,e,r,n)}),Ke=Xe(\"<\",function(t,e,r){return e<r},function(t,e,r,n){return n.compare(e,r)<0}),Qe=Xe(\">\",function(t,e,r){return e>r},function(t,e,r,n){return n.compare(e,r)>0}),$e=Xe(\"<=\",function(t,e,r){return e<=r},function(t,e,r,n){return n.compare(e,r)<=0}),tr=Xe(\">=\",function(t,e,r){return e>=r},function(t,e,r,n){return n.compare(e,r)>=0}),er=function(t,e,r,n,a){this.type=Dt,this.number=t,this.locale=e,this.currency=r,this.minFractionDigits=n,this.maxFractionDigits=a};er.parse=function(t,e){if(3!==t.length)return e.error(\"Expected two arguments.\");var r=e.parse(t[1],1,It);if(!r)return null;var n=t[2];if(\"object\"!=typeof n||Array.isArray(n))return e.error(\"NumberFormat options argument must be an object.\");var a=null;if(n.locale&&!(a=e.parse(n.locale,1,Dt)))return null;var i=null;if(n.currency&&!(i=e.parse(n.currency,1,Dt)))return null;var o=null;if(n[\"min-fraction-digits\"]&&!(o=e.parse(n[\"min-fraction-digits\"],1,It)))return null;var s=null;return n[\"max-fraction-digits\"]&&!(s=e.parse(n[\"max-fraction-digits\"],1,It))?null:new er(r,a,i,o,s)},er.prototype.evaluate=function(t){return new Intl.NumberFormat(this.locale?this.locale.evaluate(t):[],{style:this.currency?\"currency\":\"decimal\",currency:this.currency?this.currency.evaluate(t):void 0,minimumFractionDigits:this.minFractionDigits?this.minFractionDigits.evaluate(t):void 0,maximumFractionDigits:this.maxFractionDigits?this.maxFractionDigits.evaluate(t):void 0}).format(this.number.evaluate(t))},er.prototype.eachChild=function(t){t(this.number),this.locale&&t(this.locale),this.currency&&t(this.currency),this.minFractionDigits&&t(this.minFractionDigits),this.maxFractionDigits&&t(this.maxFractionDigits)},er.prototype.possibleOutputs=function(){return[void 0]},er.prototype.serialize=function(){var t={};return this.locale&&(t.locale=this.locale.serialize()),this.currency&&(t.currency=this.currency.serialize()),this.minFractionDigits&&(t[\"min-fraction-digits\"]=this.minFractionDigits.serialize()),this.maxFractionDigits&&(t[\"max-fraction-digits\"]=this.maxFractionDigits.serialize()),[\"number-format\",this.number.serialize(),t]};var rr=function(t){this.type=It,this.input=t};rr.parse=function(t,e){if(2!==t.length)return e.error(\"Expected 1 argument, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1);return r?\"array\"!==r.type.kind&&\"string\"!==r.type.kind&&\"value\"!==r.type.kind?e.error(\"Expected argument of type string or array, but found \"+qt(r.type)+\" instead.\"):new rr(r):null},rr.prototype.evaluate=function(t){var e=this.input.evaluate(t);if(\"string\"==typeof e)return e.length;if(Array.isArray(e))return e.length;throw new ee(\"Expected value to be of type string or array, but found \"+qt(Qt(e))+\" instead.\")},rr.prototype.eachChild=function(t){t(this.input)},rr.prototype.possibleOutputs=function(){return[void 0]},rr.prototype.serialize=function(){var t=[\"length\"];return this.eachChild(function(e){t.push(e.serialize())}),t};var nr={\"==\":Ze,\"!=\":Je,\">\":Qe,\"<\":Ke,\">=\":tr,\"<=\":$e,array:ne,at:qe,boolean:ne,case:Ge,coalesce:Ve,collator:ue,format:ae,interpolate:Ne,\"interpolate-hcl\":Ne,\"interpolate-lab\":Ne,length:rr,let:Ue,literal:te,match:He,number:ne,\"number-format\":er,object:ne,step:me,string:ne,\"to-boolean\":oe,\"to-color\":oe,\"to-number\":oe,\"to-string\":oe,var:de};function ar(t,e){var r=e[0],n=e[1],a=e[2],i=e[3];r=r.evaluate(t),n=n.evaluate(t),a=a.evaluate(t);var o=i?i.evaluate(t):1,s=Kt(r,n,a,o);if(s)throw new ee(s);return new Wt(r/255*o,n/255*o,a/255*o,o)}function ir(t,e){return t in e}function or(t,e){var r=e[t];return void 0===r?null:r}function sr(t){return{type:t}}function lr(t){return{result:\"success\",value:t}}function cr(t){return{result:\"error\",value:t}}function ur(t){return\"data-driven\"===t[\"property-type\"]||\"cross-faded-data-driven\"===t[\"property-type\"]}function hr(t){return!!t.expression&&t.expression.parameters.indexOf(\"zoom\")>-1}function fr(t){return!!t.expression&&t.expression.interpolated}function pr(t){return t instanceof Number?\"number\":t instanceof String?\"string\":t instanceof Boolean?\"boolean\":Array.isArray(t)?\"array\":null===t?\"null\":typeof t}function dr(t){return\"object\"==typeof t&&null!==t&&!Array.isArray(t)}function gr(t){return t}function vr(t,e,r){return void 0!==t?t:void 0!==e?e:void 0!==r?r:void 0}function mr(t,e,r,n,a){return vr(typeof r===a?n[r]:void 0,t.default,e.default)}function yr(t,e,r){if(\"number\"!==pr(r))return vr(t.default,e.default);var n=t.stops.length;if(1===n)return t.stops[0][1];if(r<=t.stops[0][0])return t.stops[0][1];if(r>=t.stops[n-1][0])return t.stops[n-1][1];var a=ve(t.stops.map(function(t){return t[0]}),r);return t.stops[a][1]}function xr(t,e,r){var n=void 0!==t.base?t.base:1;if(\"number\"!==pr(r))return vr(t.default,e.default);var a=t.stops.length;if(1===a)return t.stops[0][1];if(r<=t.stops[0][0])return t.stops[0][1];if(r>=t.stops[a-1][0])return t.stops[a-1][1];var i=ve(t.stops.map(function(t){return t[0]}),r),o=function(t,e,r,n){var a=n-r,i=t-r;return 0===a?0:1===e?i/a:(Math.pow(e,i)-1)/(Math.pow(e,a)-1)}(r,n,t.stops[i][0],t.stops[i+1][0]),s=t.stops[i][1],l=t.stops[i+1][1],c=xe[e.type]||gr;if(t.colorSpace&&\"rgb\"!==t.colorSpace){var u=Be[t.colorSpace];c=function(t,e){return u.reverse(u.interpolate(u.forward(t),u.forward(e),o))}}return\"function\"==typeof s.evaluate?{evaluate:function(){for(var t=[],e=arguments.length;e--;)t[e]=arguments[e];var r=s.evaluate.apply(void 0,t),n=l.evaluate.apply(void 0,t);if(void 0!==r&&void 0!==n)return c(r,n,o)}}:c(s,l,o)}function br(t,e,r){return\"color\"===e.type?r=Wt.parse(r):\"formatted\"===e.type?r=Jt.fromString(r.toString()):pr(r)===e.type||\"enum\"===e.type&&e.values[r]||(r=void 0),vr(r,t.default,e.default)}ce.register(nr,{error:[{kind:\"error\"},[Dt],function(t,e){var r=e[0];throw new ee(r.evaluate(t))}],typeof:[Dt,[Nt],function(t,e){return qt(Qt(e[0].evaluate(t)))}],\"to-rgba\":[Ut(It,4),[Ft],function(t,e){return e[0].evaluate(t).toArray()}],rgb:[Ft,[It,It,It],ar],rgba:[Ft,[It,It,It,It],ar],has:{type:Rt,overloads:[[[Dt],function(t,e){return ir(e[0].evaluate(t),t.properties())}],[[Dt,Bt],function(t,e){var r=e[0],n=e[1];return ir(r.evaluate(t),n.evaluate(t))}]]},get:{type:Nt,overloads:[[[Dt],function(t,e){return or(e[0].evaluate(t),t.properties())}],[[Dt,Bt],function(t,e){var r=e[0],n=e[1];return or(r.evaluate(t),n.evaluate(t))}]]},\"feature-state\":[Nt,[Dt],function(t,e){return or(e[0].evaluate(t),t.featureState||{})}],properties:[Bt,[],function(t){return t.properties()}],\"geometry-type\":[Dt,[],function(t){return t.geometryType()}],id:[Nt,[],function(t){return t.id()}],zoom:[It,[],function(t){return t.globals.zoom}],\"heatmap-density\":[It,[],function(t){return t.globals.heatmapDensity||0}],\"line-progress\":[It,[],function(t){return t.globals.lineProgress||0}],accumulated:[Nt,[],function(t){return void 0===t.globals.accumulated?null:t.globals.accumulated}],\"+\":[It,sr(It),function(t,e){for(var r=0,n=0,a=e;n<a.length;n+=1)r+=a[n].evaluate(t);return r}],\"*\":[It,sr(It),function(t,e){for(var r=1,n=0,a=e;n<a.length;n+=1)r*=a[n].evaluate(t);return r}],\"-\":{type:It,overloads:[[[It,It],function(t,e){var r=e[0],n=e[1];return r.evaluate(t)-n.evaluate(t)}],[[It],function(t,e){return-e[0].evaluate(t)}]]},\"/\":[It,[It,It],function(t,e){var r=e[0],n=e[1];return r.evaluate(t)/n.evaluate(t)}],\"%\":[It,[It,It],function(t,e){var r=e[0],n=e[1];return r.evaluate(t)%n.evaluate(t)}],ln2:[It,[],function(){return Math.LN2}],pi:[It,[],function(){return Math.PI}],e:[It,[],function(){return Math.E}],\"^\":[It,[It,It],function(t,e){var r=e[0],n=e[1];return Math.pow(r.evaluate(t),n.evaluate(t))}],sqrt:[It,[It],function(t,e){var r=e[0];return Math.sqrt(r.evaluate(t))}],log10:[It,[It],function(t,e){var r=e[0];return Math.log(r.evaluate(t))/Math.LN10}],ln:[It,[It],function(t,e){var r=e[0];return Math.log(r.evaluate(t))}],log2:[It,[It],function(t,e){var r=e[0];return Math.log(r.evaluate(t))/Math.LN2}],sin:[It,[It],function(t,e){var r=e[0];return Math.sin(r.evaluate(t))}],cos:[It,[It],function(t,e){var r=e[0];return Math.cos(r.evaluate(t))}],tan:[It,[It],function(t,e){var r=e[0];return Math.tan(r.evaluate(t))}],asin:[It,[It],function(t,e){var r=e[0];return Math.asin(r.evaluate(t))}],acos:[It,[It],function(t,e){var r=e[0];return Math.acos(r.evaluate(t))}],atan:[It,[It],function(t,e){var r=e[0];return Math.atan(r.evaluate(t))}],min:[It,sr(It),function(t,e){return Math.min.apply(Math,e.map(function(e){return e.evaluate(t)}))}],max:[It,sr(It),function(t,e){return Math.max.apply(Math,e.map(function(e){return e.evaluate(t)}))}],abs:[It,[It],function(t,e){var r=e[0];return Math.abs(r.evaluate(t))}],round:[It,[It],function(t,e){var r=e[0].evaluate(t);return r<0?-Math.round(-r):Math.round(r)}],floor:[It,[It],function(t,e){var r=e[0];return Math.floor(r.evaluate(t))}],ceil:[It,[It],function(t,e){var r=e[0];return Math.ceil(r.evaluate(t))}],\"filter-==\":[Rt,[Dt,Nt],function(t,e){var r=e[0],n=e[1];return t.properties()[r.value]===n.value}],\"filter-id-==\":[Rt,[Nt],function(t,e){var r=e[0];return t.id()===r.value}],\"filter-type-==\":[Rt,[Dt],function(t,e){var r=e[0];return t.geometryType()===r.value}],\"filter-<\":[Rt,[Dt,Nt],function(t,e){var r=e[0],n=e[1],a=t.properties()[r.value],i=n.value;return typeof a==typeof i&&a<i}],\"filter-id-<\":[Rt,[Nt],function(t,e){var r=e[0],n=t.id(),a=r.value;return typeof n==typeof a&&n<a}],\"filter->\":[Rt,[Dt,Nt],function(t,e){var r=e[0],n=e[1],a=t.properties()[r.value],i=n.value;return typeof a==typeof i&&a>i}],\"filter-id->\":[Rt,[Nt],function(t,e){var r=e[0],n=t.id(),a=r.value;return typeof n==typeof a&&n>a}],\"filter-<=\":[Rt,[Dt,Nt],function(t,e){var r=e[0],n=e[1],a=t.properties()[r.value],i=n.value;return typeof a==typeof i&&a<=i}],\"filter-id-<=\":[Rt,[Nt],function(t,e){var r=e[0],n=t.id(),a=r.value;return typeof n==typeof a&&n<=a}],\"filter->=\":[Rt,[Dt,Nt],function(t,e){var r=e[0],n=e[1],a=t.properties()[r.value],i=n.value;return typeof a==typeof i&&a>=i}],\"filter-id->=\":[Rt,[Nt],function(t,e){var r=e[0],n=t.id(),a=r.value;return typeof n==typeof a&&n>=a}],\"filter-has\":[Rt,[Nt],function(t,e){return e[0].value in t.properties()}],\"filter-has-id\":[Rt,[],function(t){return null!==t.id()}],\"filter-type-in\":[Rt,[Ut(Dt)],function(t,e){return e[0].value.indexOf(t.geometryType())>=0}],\"filter-id-in\":[Rt,[Ut(Nt)],function(t,e){return e[0].value.indexOf(t.id())>=0}],\"filter-in-small\":[Rt,[Dt,Ut(Nt)],function(t,e){var r=e[0];return e[1].value.indexOf(t.properties()[r.value])>=0}],\"filter-in-large\":[Rt,[Dt,Ut(Nt)],function(t,e){var r=e[0],n=e[1];return function(t,e,r,n){for(;r<=n;){var a=r+n>>1;if(e[a]===t)return!0;e[a]>t?n=a-1:r=a+1}return!1}(t.properties()[r.value],n.value,0,n.value.length-1)}],all:{type:Rt,overloads:[[[Rt,Rt],function(t,e){var r=e[0],n=e[1];return r.evaluate(t)&&n.evaluate(t)}],[sr(Rt),function(t,e){for(var r=0,n=e;r<n.length;r+=1)if(!n[r].evaluate(t))return!1;return!0}]]},any:{type:Rt,overloads:[[[Rt,Rt],function(t,e){var r=e[0],n=e[1];return r.evaluate(t)||n.evaluate(t)}],[sr(Rt),function(t,e){for(var r=0,n=e;r<n.length;r+=1)if(n[r].evaluate(t))return!0;return!1}]]},\"!\":[Rt,[Rt],function(t,e){return!e[0].evaluate(t)}],\"is-supported-script\":[Rt,[Dt],function(t,e){var r=e[0],n=t.globals&&t.globals.isSupportedScript;return!n||n(r.evaluate(t))}],upcase:[Dt,[Dt],function(t,e){return e[0].evaluate(t).toUpperCase()}],downcase:[Dt,[Dt],function(t,e){return e[0].evaluate(t).toLowerCase()}],concat:[Dt,sr(Nt),function(t,e){return e.map(function(e){return $t(e.evaluate(t))}).join(\"\")}],\"resolved-locale\":[Dt,[jt],function(t,e){return e[0].evaluate(t).resolvedLocale()}]});var _r=function(t,e){this.expression=t,this._warningHistory={},this._evaluator=new le,this._defaultValue=e?function(t){return\"color\"===t.type&&dr(t.default)?new Wt(0,0,0,0):\"color\"===t.type?Wt.parse(t.default)||null:void 0===t.default?null:t.default}(e):null,this._enumValues=e&&\"enum\"===e.type?e.values:null};function wr(t){return Array.isArray(t)&&t.length>0&&\"string\"==typeof t[0]&&t[0]in nr}function kr(t,e){var r=new ge(nr,[],e?function(t){var e={color:Ft,string:Dt,number:It,enum:Dt,boolean:Rt,formatted:Vt};return\"array\"===t.type?Ut(e[t.value]||Nt,t.length):e[t.type]}(e):void 0),n=r.parse(t,void 0,void 0,void 0,e&&\"string\"===e.type?{typeAnnotation:\"coerce\"}:void 0);return n?lr(new _r(n,e)):cr(r.errors)}_r.prototype.evaluateWithoutErrorHandling=function(t,e,r,n){return this._evaluator.globals=t,this._evaluator.feature=e,this._evaluator.featureState=r,this._evaluator.formattedSection=n,this.expression.evaluate(this._evaluator)},_r.prototype.evaluate=function(t,e,r,n){this._evaluator.globals=t,this._evaluator.feature=e||null,this._evaluator.featureState=r||null,this._evaluator.formattedSection=n||null;try{var a=this.expression.evaluate(this._evaluator);if(null==a)return this._defaultValue;if(this._enumValues&&!(a in this._enumValues))throw new ee(\"Expected value to be one of \"+Object.keys(this._enumValues).map(function(t){return JSON.stringify(t)}).join(\", \")+\", but found \"+JSON.stringify(a)+\" instead.\");return a}catch(t){return this._warningHistory[t.message]||(this._warningHistory[t.message]=!0,\"undefined\"!=typeof console&&console.warn(t.message)),this._defaultValue}};var Tr=function(t,e){this.kind=t,this._styleExpression=e,this.isStateDependent=\"constant\"!==t&&!fe(e.expression)};Tr.prototype.evaluateWithoutErrorHandling=function(t,e,r,n){return this._styleExpression.evaluateWithoutErrorHandling(t,e,r,n)},Tr.prototype.evaluate=function(t,e,r,n){return this._styleExpression.evaluate(t,e,r,n)};var Mr=function(t,e,r,n){this.kind=t,this.zoomStops=r,this._styleExpression=e,this.isStateDependent=\"camera\"!==t&&!fe(e.expression),this.interpolationType=n};function Ar(t,e){if(\"error\"===(t=kr(t,e)).result)return t;var r=t.value.expression,n=he(r);if(!n&&!ur(e))return cr([new Pt(\"\",\"data expressions not supported\")]);var a=pe(r,[\"zoom\"]);if(!a&&!hr(e))return cr([new Pt(\"\",\"zoom expressions not supported\")]);var i=function t(e){var r=null;if(e instanceof Ue)r=t(e.result);else if(e instanceof Ve)for(var n=0,a=e.args;n<a.length;n+=1){var i=a[n];if(r=t(i))break}else(e instanceof me||e instanceof Ne)&&e.input instanceof ce&&\"zoom\"===e.input.name&&(r=e);return r instanceof Pt?r:(e.eachChild(function(e){var n=t(e);n instanceof Pt?r=n:!r&&n?r=new Pt(\"\",'\"zoom\" expression may only be used as input to a top-level \"step\" or \"interpolate\" expression.'):r&&n&&r!==n&&(r=new Pt(\"\",'Only one zoom-based \"step\" or \"interpolate\" subexpression may be used in an expression.'))}),r)}(r);if(!i&&!a)return cr([new Pt(\"\",'\"zoom\" expression may only be used as input to a top-level \"step\" or \"interpolate\" expression.')]);if(i instanceof Pt)return cr([i]);if(i instanceof Ne&&!fr(e))return cr([new Pt(\"\",'\"interpolate\" expressions cannot be used with this property')]);if(!i)return lr(new Tr(n?\"constant\":\"source\",t.value));var o=i instanceof Ne?i.interpolation:void 0;return lr(new Mr(n?\"camera\":\"composite\",t.value,i.labels,o))}Mr.prototype.evaluateWithoutErrorHandling=function(t,e,r,n){return this._styleExpression.evaluateWithoutErrorHandling(t,e,r,n)},Mr.prototype.evaluate=function(t,e,r,n){return this._styleExpression.evaluate(t,e,r,n)},Mr.prototype.interpolationFactor=function(t,e,r){return this.interpolationType?Ne.interpolationFactor(this.interpolationType,t,e,r):0};var Sr=function(t,e){this._parameters=t,this._specification=e,St(this,function t(e,r){var n,a,i,o=\"color\"===r.type,s=e.stops&&\"object\"==typeof e.stops[0][0],l=s||void 0!==e.property,c=s||!l,u=e.type||(fr(r)?\"exponential\":\"interval\");if(o&&((e=St({},e)).stops&&(e.stops=e.stops.map(function(t){return[t[0],Wt.parse(t[1])]})),e.default?e.default=Wt.parse(e.default):e.default=Wt.parse(r.default)),e.colorSpace&&\"rgb\"!==e.colorSpace&&!Be[e.colorSpace])throw new Error(\"Unknown color space: \"+e.colorSpace);if(\"exponential\"===u)n=xr;else if(\"interval\"===u)n=yr;else if(\"categorical\"===u){n=mr,a=Object.create(null);for(var h=0,f=e.stops;h<f.length;h+=1){var p=f[h];a[p[0]]=p[1]}i=typeof e.stops[0][0]}else{if(\"identity\"!==u)throw new Error('Unknown function type \"'+u+'\"');n=br}if(s){for(var d={},g=[],v=0;v<e.stops.length;v++){var m=e.stops[v],y=m[0].zoom;void 0===d[y]&&(d[y]={zoom:y,type:e.type,property:e.property,default:e.default,stops:[]},g.push(y)),d[y].stops.push([m[0].value,m[1]])}for(var x=[],b=0,_=g;b<_.length;b+=1){var w=_[b];x.push([d[w].zoom,t(d[w],r)])}var k={name:\"linear\"};return{kind:\"composite\",interpolationType:k,interpolationFactor:Ne.interpolationFactor.bind(void 0,k),zoomStops:x.map(function(t){return t[0]}),evaluate:function(t,n){var a=t.zoom;return xr({stops:x,base:e.base},r,a).evaluate(a,n)}}}if(c){var T=\"exponential\"===u?{name:\"exponential\",base:void 0!==e.base?e.base:1}:null;return{kind:\"camera\",interpolationType:T,interpolationFactor:Ne.interpolationFactor.bind(void 0,T),zoomStops:e.stops.map(function(t){return t[0]}),evaluate:function(t){var o=t.zoom;return n(e,r,o,a,i)}}}return{kind:\"source\",evaluate:function(t,o){var s=o&&o.properties?o.properties[e.property]:void 0;return void 0===s?vr(e.default,r.default):n(e,r,s,a,i)}}}(this._parameters,this._specification))};function Er(t){var e=t.key,r=t.value,n=t.valueSpec||{},a=t.objectElementValidators||{},i=t.style,o=t.styleSpec,s=[],l=pr(r);if(\"object\"!==l)return[new Mt(e,r,\"object expected, \"+l+\" found\")];for(var c in r){var u=c.split(\".\")[0],h=n[u]||n[\"*\"],f=void 0;if(a[u])f=a[u];else if(n[u])f=Qr;else if(a[\"*\"])f=a[\"*\"];else{if(!n[\"*\"]){s.push(new Mt(e,r[c],'unknown property \"'+c+'\"'));continue}f=Qr}s=s.concat(f({key:(e?e+\".\":e)+c,value:r[c],valueSpec:h,style:i,styleSpec:o,object:r,objectKey:c},r))}for(var p in n)a[p]||n[p].required&&void 0===n[p].default&&void 0===r[p]&&s.push(new Mt(e,r,'missing required property \"'+p+'\"'));return s}function Lr(t){var e=t.value,r=t.valueSpec,n=t.style,a=t.styleSpec,i=t.key,o=t.arrayElementValidator||Qr;if(\"array\"!==pr(e))return[new Mt(i,e,\"array expected, \"+pr(e)+\" found\")];if(r.length&&e.length!==r.length)return[new Mt(i,e,\"array length \"+r.length+\" expected, length \"+e.length+\" found\")];if(r[\"min-length\"]&&e.length<r[\"min-length\"])return[new Mt(i,e,\"array length at least \"+r[\"min-length\"]+\" expected, length \"+e.length+\" found\")];var s={type:r.value,values:r.values};a.$version<7&&(s.function=r.function),\"object\"===pr(r.value)&&(s=r.value);for(var l=[],c=0;c<e.length;c++)l=l.concat(o({array:e,arrayIndex:c,value:e[c],valueSpec:s,style:n,styleSpec:a,key:i+\"[\"+c+\"]\"}));return l}function Cr(t){var e=t.key,r=t.value,n=t.valueSpec,a=pr(r);return\"number\"!==a?[new Mt(e,r,\"number expected, \"+a+\" found\")]:\"minimum\"in n&&r<n.minimum?[new Mt(e,r,r+\" is less than the minimum value \"+n.minimum)]:\"maximum\"in n&&r>n.maximum?[new Mt(e,r,r+\" is greater than the maximum value \"+n.maximum)]:[]}function Pr(t){var e,r,n,a=t.valueSpec,i=Lt(t.value.type),o={},s=\"categorical\"!==i&&void 0===t.value.property,l=!s,c=\"array\"===pr(t.value.stops)&&\"array\"===pr(t.value.stops[0])&&\"object\"===pr(t.value.stops[0][0]),u=Er({key:t.key,value:t.value,valueSpec:t.styleSpec.function,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{stops:function(t){if(\"identity\"===i)return[new Mt(t.key,t.value,'identity function may not have a \"stops\" property')];var e=[],r=t.value;return e=e.concat(Lr({key:t.key,value:r,valueSpec:t.valueSpec,style:t.style,styleSpec:t.styleSpec,arrayElementValidator:h})),\"array\"===pr(r)&&0===r.length&&e.push(new Mt(t.key,r,\"array must have at least one stop\")),e},default:function(t){return Qr({key:t.key,value:t.value,valueSpec:a,style:t.style,styleSpec:t.styleSpec})}}});return\"identity\"===i&&s&&u.push(new Mt(t.key,t.value,'missing required property \"property\"')),\"identity\"===i||t.value.stops||u.push(new Mt(t.key,t.value,'missing required property \"stops\"')),\"exponential\"===i&&t.valueSpec.expression&&!fr(t.valueSpec)&&u.push(new Mt(t.key,t.value,\"exponential functions not supported\")),t.styleSpec.$version>=8&&(l&&!ur(t.valueSpec)?u.push(new Mt(t.key,t.value,\"property functions not supported\")):s&&!hr(t.valueSpec)&&u.push(new Mt(t.key,t.value,\"zoom functions not supported\"))),\"categorical\"!==i&&!c||void 0!==t.value.property||u.push(new Mt(t.key,t.value,'\"property\" property is required')),u;function h(t){var e=[],i=t.value,s=t.key;if(\"array\"!==pr(i))return[new Mt(s,i,\"array expected, \"+pr(i)+\" found\")];if(2!==i.length)return[new Mt(s,i,\"array length 2 expected, length \"+i.length+\" found\")];if(c){if(\"object\"!==pr(i[0]))return[new Mt(s,i,\"object expected, \"+pr(i[0])+\" found\")];if(void 0===i[0].zoom)return[new Mt(s,i,\"object stop key must have zoom\")];if(void 0===i[0].value)return[new Mt(s,i,\"object stop key must have value\")];if(n&&n>Lt(i[0].zoom))return[new Mt(s,i[0].zoom,\"stop zoom values must appear in ascending order\")];Lt(i[0].zoom)!==n&&(n=Lt(i[0].zoom),r=void 0,o={}),e=e.concat(Er({key:s+\"[0]\",value:i[0],valueSpec:{zoom:{}},style:t.style,styleSpec:t.styleSpec,objectElementValidators:{zoom:Cr,value:f}}))}else e=e.concat(f({key:s+\"[0]\",value:i[0],valueSpec:{},style:t.style,styleSpec:t.styleSpec},i));return wr(Ct(i[1]))?e.concat([new Mt(s+\"[1]\",i[1],\"expressions are not allowed in function stops.\")]):e.concat(Qr({key:s+\"[1]\",value:i[1],valueSpec:a,style:t.style,styleSpec:t.styleSpec}))}function f(t,n){var s=pr(t.value),l=Lt(t.value),c=null!==t.value?t.value:n;if(e){if(s!==e)return[new Mt(t.key,c,s+\" stop domain type must match previous stop domain type \"+e)]}else e=s;if(\"number\"!==s&&\"string\"!==s&&\"boolean\"!==s)return[new Mt(t.key,c,\"stop domain value must be a number, string, or boolean\")];if(\"number\"!==s&&\"categorical\"!==i){var u=\"number expected, \"+s+\" found\";return ur(a)&&void 0===i&&(u+='\\nIf you intended to use a categorical function, specify `\"type\": \"categorical\"`.'),[new Mt(t.key,c,u)]}return\"categorical\"!==i||\"number\"!==s||isFinite(l)&&Math.floor(l)===l?\"categorical\"!==i&&\"number\"===s&&void 0!==r&&l<r?[new Mt(t.key,c,\"stop domain values must appear in ascending order\")]:(r=l,\"categorical\"===i&&l in o?[new Mt(t.key,c,\"stop domain values must be unique\")]:(o[l]=!0,[])):[new Mt(t.key,c,\"integer expected, found \"+l)]}}function Or(t){var e=(\"property\"===t.expressionContext?Ar:kr)(Ct(t.value),t.valueSpec);if(\"error\"===e.result)return e.value.map(function(e){return new Mt(\"\"+t.key+e.key,t.value,e.message)});var r=e.value.expression||e.value._styleExpression.expression;if(\"property\"===t.expressionContext&&\"text-font\"===t.propertyKey&&-1!==r.possibleOutputs().indexOf(void 0))return[new Mt(t.key,t.value,'Invalid data expression for \"'+t.propertyKey+'\". Output values must be contained as literals within the expression.')];if(\"property\"===t.expressionContext&&\"layout\"===t.propertyType&&!fe(r))return[new Mt(t.key,t.value,'\"feature-state\" data expressions are not supported with layout properties.')];if(\"filter\"===t.expressionContext&&!fe(r))return[new Mt(t.key,t.value,'\"feature-state\" data expressions are not supported with filters.')];if(t.expressionContext&&0===t.expressionContext.indexOf(\"cluster\")){if(!pe(r,[\"zoom\",\"feature-state\"]))return[new Mt(t.key,t.value,'\"zoom\" and \"feature-state\" expressions are not supported with cluster properties.')];if(\"cluster-initial\"===t.expressionContext&&!he(r))return[new Mt(t.key,t.value,\"Feature data expressions are not supported with initial expression part of cluster properties.\")]}return[]}function zr(t){var e=t.key,r=t.value,n=t.valueSpec,a=[];return Array.isArray(n.values)?-1===n.values.indexOf(Lt(r))&&a.push(new Mt(e,r,\"expected one of [\"+n.values.join(\", \")+\"], \"+JSON.stringify(r)+\" found\")):-1===Object.keys(n.values).indexOf(Lt(r))&&a.push(new Mt(e,r,\"expected one of [\"+Object.keys(n.values).join(\", \")+\"], \"+JSON.stringify(r)+\" found\")),a}function Ir(t){if(!0===t||!1===t)return!0;if(!Array.isArray(t)||0===t.length)return!1;switch(t[0]){case\"has\":return t.length>=2&&\"$id\"!==t[1]&&\"$type\"!==t[1];case\"in\":case\"!in\":case\"!has\":case\"none\":return!1;case\"==\":case\"!=\":case\">\":case\">=\":case\"<\":case\"<=\":return 3!==t.length||Array.isArray(t[1])||Array.isArray(t[2]);case\"any\":case\"all\":for(var e=0,r=t.slice(1);e<r.length;e+=1){var n=r[e];if(!Ir(n)&&\"boolean\"!=typeof n)return!1}return!0;default:return!0}}Sr.deserialize=function(t){return new Sr(t._parameters,t._specification)},Sr.serialize=function(t){return{_parameters:t._parameters,_specification:t._specification}};var Dr={type:\"boolean\",default:!1,transition:!1,\"property-type\":\"data-driven\",expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]}};function Rr(t){if(null==t)return function(){return!0};Ir(t)||(t=Br(t));var e=kr(t,Dr);if(\"error\"===e.result)throw new Error(e.value.map(function(t){return t.key+\": \"+t.message}).join(\", \"));return function(t,r){return e.value.evaluate(t,r)}}function Fr(t,e){return t<e?-1:t>e?1:0}function Br(t){if(!t)return!0;var e,r=t[0];return t.length<=1?\"any\"!==r:\"==\"===r?Nr(t[1],t[2],\"==\"):\"!=\"===r?Ur(Nr(t[1],t[2],\"==\")):\"<\"===r||\">\"===r||\"<=\"===r||\">=\"===r?Nr(t[1],t[2],r):\"any\"===r?(e=t.slice(1),[\"any\"].concat(e.map(Br))):\"all\"===r?[\"all\"].concat(t.slice(1).map(Br)):\"none\"===r?[\"all\"].concat(t.slice(1).map(Br).map(Ur)):\"in\"===r?jr(t[1],t.slice(2)):\"!in\"===r?Ur(jr(t[1],t.slice(2))):\"has\"===r?Vr(t[1]):\"!has\"!==r||Ur(Vr(t[1]))}function Nr(t,e,r){switch(t){case\"$type\":return[\"filter-type-\"+r,e];case\"$id\":return[\"filter-id-\"+r,e];default:return[\"filter-\"+r,t,e]}}function jr(t,e){if(0===e.length)return!1;switch(t){case\"$type\":return[\"filter-type-in\",[\"literal\",e]];case\"$id\":return[\"filter-id-in\",[\"literal\",e]];default:return e.length>200&&!e.some(function(t){return typeof t!=typeof e[0]})?[\"filter-in-large\",t,[\"literal\",e.sort(Fr)]]:[\"filter-in-small\",t,[\"literal\",e]]}}function Vr(t){switch(t){case\"$type\":return!0;case\"$id\":return[\"filter-has-id\"];default:return[\"filter-has\",t]}}function Ur(t){return[\"!\",t]}function qr(t){return Ir(Ct(t.value))?Or(St({},t,{expressionContext:\"filter\",valueSpec:{value:\"boolean\"}})):function t(e){var r=e.value,n=e.key;if(\"array\"!==pr(r))return[new Mt(n,r,\"array expected, \"+pr(r)+\" found\")];var a,i=e.styleSpec,o=[];if(r.length<1)return[new Mt(n,r,\"filter array must have at least 1 element\")];switch(o=o.concat(zr({key:n+\"[0]\",value:r[0],valueSpec:i.filter_operator,style:e.style,styleSpec:e.styleSpec})),Lt(r[0])){case\"<\":case\"<=\":case\">\":case\">=\":r.length>=2&&\"$type\"===Lt(r[1])&&o.push(new Mt(n,r,'\"$type\" cannot be use with operator \"'+r[0]+'\"'));case\"==\":case\"!=\":3!==r.length&&o.push(new Mt(n,r,'filter array for operator \"'+r[0]+'\" must have 3 elements'));case\"in\":case\"!in\":r.length>=2&&\"string\"!==(a=pr(r[1]))&&o.push(new Mt(n+\"[1]\",r[1],\"string expected, \"+a+\" found\"));for(var s=2;s<r.length;s++)a=pr(r[s]),\"$type\"===Lt(r[1])?o=o.concat(zr({key:n+\"[\"+s+\"]\",value:r[s],valueSpec:i.geometry_type,style:e.style,styleSpec:e.styleSpec})):\"string\"!==a&&\"number\"!==a&&\"boolean\"!==a&&o.push(new Mt(n+\"[\"+s+\"]\",r[s],\"string, number, or boolean expected, \"+a+\" found\"));break;case\"any\":case\"all\":case\"none\":for(var l=1;l<r.length;l++)o=o.concat(t({key:n+\"[\"+l+\"]\",value:r[l],style:e.style,styleSpec:e.styleSpec}));break;case\"has\":case\"!has\":a=pr(r[1]),2!==r.length?o.push(new Mt(n,r,'filter array for \"'+r[0]+'\" operator must have 2 elements')):\"string\"!==a&&o.push(new Mt(n+\"[1]\",r[1],\"string expected, \"+a+\" found\"))}return o}(t)}function Hr(t,e){var r=t.key,n=t.style,a=t.styleSpec,i=t.value,o=t.objectKey,s=a[e+\"_\"+t.layerType];if(!s)return[];var l=o.match(/^(.*)-transition$/);if(\"paint\"===e&&l&&s[l[1]]&&s[l[1]].transition)return Qr({key:r,value:i,valueSpec:a.transition,style:n,styleSpec:a});var c,u=t.valueSpec||s[o];if(!u)return[new Mt(r,i,'unknown property \"'+o+'\"')];if(\"string\"===pr(i)&&ur(u)&&!u.tokens&&(c=/^{([^}]+)}$/.exec(i)))return[new Mt(r,i,'\"'+o+'\" does not support interpolation syntax\\nUse an identity property function instead: `{ \"type\": \"identity\", \"property\": '+JSON.stringify(c[1])+\" }`.\")];var h=[];return\"symbol\"===t.layerType&&(\"text-field\"===o&&n&&!n.glyphs&&h.push(new Mt(r,i,'use of \"text-field\" requires a style \"glyphs\" property')),\"text-font\"===o&&dr(Ct(i))&&\"identity\"===Lt(i.type)&&h.push(new Mt(r,i,'\"text-font\" does not support identity functions'))),h.concat(Qr({key:t.key,value:i,valueSpec:u,style:n,styleSpec:a,expressionContext:\"property\",propertyType:e,propertyKey:o}))}function Gr(t){return Hr(t,\"paint\")}function Yr(t){return Hr(t,\"layout\")}function Wr(t){var e=[],r=t.value,n=t.key,a=t.style,i=t.styleSpec;r.type||r.ref||e.push(new Mt(n,r,'either \"type\" or \"ref\" is required'));var o,s=Lt(r.type),l=Lt(r.ref);if(r.id)for(var c=Lt(r.id),u=0;u<t.arrayIndex;u++){var h=a.layers[u];Lt(h.id)===c&&e.push(new Mt(n,r.id,'duplicate layer id \"'+r.id+'\", previously used at line '+h.id.__line__))}if(\"ref\"in r)[\"type\",\"source\",\"source-layer\",\"filter\",\"layout\"].forEach(function(t){t in r&&e.push(new Mt(n,r[t],'\"'+t+'\" is prohibited for ref layers'))}),a.layers.forEach(function(t){Lt(t.id)===l&&(o=t)}),o?o.ref?e.push(new Mt(n,r.ref,\"ref cannot reference another ref layer\")):s=Lt(o.type):e.push(new Mt(n,r.ref,'ref layer \"'+l+'\" not found'));else if(\"background\"!==s)if(r.source){var f=a.sources&&a.sources[r.source],p=f&&Lt(f.type);f?\"vector\"===p&&\"raster\"===s?e.push(new Mt(n,r.source,'layer \"'+r.id+'\" requires a raster source')):\"raster\"===p&&\"raster\"!==s?e.push(new Mt(n,r.source,'layer \"'+r.id+'\" requires a vector source')):\"vector\"!==p||r[\"source-layer\"]?\"raster-dem\"===p&&\"hillshade\"!==s?e.push(new Mt(n,r.source,\"raster-dem source can only be used with layer type 'hillshade'.\")):\"line\"!==s||!r.paint||!r.paint[\"line-gradient\"]||\"geojson\"===p&&f.lineMetrics||e.push(new Mt(n,r,'layer \"'+r.id+'\" specifies a line-gradient, which requires a GeoJSON source with `lineMetrics` enabled.')):e.push(new Mt(n,r,'layer \"'+r.id+'\" must specify a \"source-layer\"')):e.push(new Mt(n,r.source,'source \"'+r.source+'\" not found'))}else e.push(new Mt(n,r,'missing required property \"source\"'));return e=e.concat(Er({key:n,value:r,valueSpec:i.layer,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{\"*\":function(){return[]},type:function(){return Qr({key:n+\".type\",value:r.type,valueSpec:i.layer.type,style:t.style,styleSpec:t.styleSpec,object:r,objectKey:\"type\"})},filter:qr,layout:function(t){return Er({layer:r,key:t.key,value:t.value,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{\"*\":function(t){return Yr(St({layerType:s},t))}}})},paint:function(t){return Er({layer:r,key:t.key,value:t.value,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{\"*\":function(t){return Gr(St({layerType:s},t))}}})}}}))}function Xr(t){var e=t.value,r=t.key,n=t.styleSpec,a=t.style;if(!e.type)return[new Mt(r,e,'\"type\" is required')];var i,o=Lt(e.type);switch(o){case\"vector\":case\"raster\":case\"raster-dem\":return Er({key:r,value:e,valueSpec:n[\"source_\"+o.replace(\"-\",\"_\")],style:t.style,styleSpec:n});case\"geojson\":if(i=Er({key:r,value:e,valueSpec:n.source_geojson,style:a,styleSpec:n}),e.cluster)for(var s in e.clusterProperties){var l=e.clusterProperties[s],c=l[0],u=l[1],h=\"string\"==typeof c?[c,[\"accumulated\"],[\"get\",s]]:c;i.push.apply(i,Or({key:r+\".\"+s+\".map\",value:u,expressionContext:\"cluster-map\"})),i.push.apply(i,Or({key:r+\".\"+s+\".reduce\",value:h,expressionContext:\"cluster-reduce\"}))}return i;case\"video\":return Er({key:r,value:e,valueSpec:n.source_video,style:a,styleSpec:n});case\"image\":return Er({key:r,value:e,valueSpec:n.source_image,style:a,styleSpec:n});case\"canvas\":return[new Mt(r,null,\"Please use runtime APIs to add canvas sources, rather than including them in stylesheets.\",\"source.canvas\")];default:return zr({key:r+\".type\",value:e.type,valueSpec:{values:[\"vector\",\"raster\",\"raster-dem\",\"geojson\",\"video\",\"image\"]},style:a,styleSpec:n})}}function Zr(t){var e=t.value,r=t.styleSpec,n=r.light,a=t.style,i=[],o=pr(e);if(void 0===e)return i;if(\"object\"!==o)return i.concat([new Mt(\"light\",e,\"object expected, \"+o+\" found\")]);for(var s in e){var l=s.match(/^(.*)-transition$/);i=l&&n[l[1]]&&n[l[1]].transition?i.concat(Qr({key:s,value:e[s],valueSpec:r.transition,style:a,styleSpec:r})):n[s]?i.concat(Qr({key:s,value:e[s],valueSpec:n[s],style:a,styleSpec:r})):i.concat([new Mt(s,e[s],'unknown property \"'+s+'\"')])}return i}function Jr(t){var e=t.value,r=t.key,n=pr(e);return\"string\"!==n?[new Mt(r,e,\"string expected, \"+n+\" found\")]:[]}var Kr={\"*\":function(){return[]},array:Lr,boolean:function(t){var e=t.value,r=t.key,n=pr(e);return\"boolean\"!==n?[new Mt(r,e,\"boolean expected, \"+n+\" found\")]:[]},number:Cr,color:function(t){var e=t.key,r=t.value,n=pr(r);return\"string\"!==n?[new Mt(e,r,\"color expected, \"+n+\" found\")]:null===Yt(r)?[new Mt(e,r,'color expected, \"'+r+'\" found')]:[]},constants:At,enum:zr,filter:qr,function:Pr,layer:Wr,object:Er,source:Xr,light:Zr,string:Jr,formatted:function(t){return 0===Jr(t).length?[]:Or(t)}};function Qr(t){var e=t.value,r=t.valueSpec,n=t.styleSpec;return r.expression&&dr(Lt(e))?Pr(t):r.expression&&wr(Ct(e))?Or(t):r.type&&Kr[r.type]?Kr[r.type](t):Er(St({},t,{valueSpec:r.type?n[r.type]:r}))}function $r(t){var e=t.value,r=t.key,n=Jr(t);return n.length?n:(-1===e.indexOf(\"{fontstack}\")&&n.push(new Mt(r,e,'\"glyphs\" url must include a \"{fontstack}\" token')),-1===e.indexOf(\"{range}\")&&n.push(new Mt(r,e,'\"glyphs\" url must include a \"{range}\" token')),n)}function tn(t,e){e=e||Tt;var r=[];return r=r.concat(Qr({key:\"\",value:t,valueSpec:e.$root,styleSpec:e,style:t,objectElementValidators:{glyphs:$r,\"*\":function(){return[]}}})),t.constants&&(r=r.concat(At({key:\"constants\",value:t.constants,style:t,styleSpec:e}))),en(r)}function en(t){return[].concat(t).sort(function(t,e){return t.line-e.line})}function rn(t){return function(){for(var e=[],r=arguments.length;r--;)e[r]=arguments[r];return en(t.apply(this,e))}}tn.source=rn(Xr),tn.light=rn(Zr),tn.layer=rn(Wr),tn.filter=rn(qr),tn.paintProperty=rn(Gr),tn.layoutProperty=rn(Yr);var nn=tn,an=nn.light,on=nn.paintProperty,sn=nn.layoutProperty;function ln(t,e){var r=!1;if(e&&e.length)for(var n=0,a=e;n<a.length;n+=1){var i=a[n];t.fire(new wt(new Error(i.message))),r=!0}return r}var cn=hn,un=3;function hn(t,e,r){var n=this.cells=[];if(t instanceof ArrayBuffer){this.arrayBuffer=t;var a=new Int32Array(this.arrayBuffer);t=a[0],e=a[1],r=a[2],this.d=e+2*r;for(var i=0;i<this.d*this.d;i++){var o=a[un+i],s=a[un+i+1];n.push(o===s?null:a.subarray(o,s))}var l=a[un+n.length],c=a[un+n.length+1];this.keys=a.subarray(l,c),this.bboxes=a.subarray(c),this.insert=this._insertReadonly}else{this.d=e+2*r;for(var u=0;u<this.d*this.d;u++)n.push([]);this.keys=[],this.bboxes=[]}this.n=e,this.extent=t,this.padding=r,this.scale=e/t,this.uid=0;var h=r/e*t;this.min=-h,this.max=t+h}hn.prototype.insert=function(t,e,r,n,a){this._forEachCell(e,r,n,a,this._insertCell,this.uid++),this.keys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(a)},hn.prototype._insertReadonly=function(){throw\"Cannot insert into a GridIndex created from an ArrayBuffer.\"},hn.prototype._insertCell=function(t,e,r,n,a,i){this.cells[a].push(i)},hn.prototype.query=function(t,e,r,n,a){var i=this.min,o=this.max;if(t<=i&&e<=i&&o<=r&&o<=n&&!a)return Array.prototype.slice.call(this.keys);var s=[];return this._forEachCell(t,e,r,n,this._queryCell,s,{},a),s},hn.prototype._queryCell=function(t,e,r,n,a,i,o,s){var l=this.cells[a];if(null!==l)for(var c=this.keys,u=this.bboxes,h=0;h<l.length;h++){var f=l[h];if(void 0===o[f]){var p=4*f;(s?s(u[p+0],u[p+1],u[p+2],u[p+3]):t<=u[p+2]&&e<=u[p+3]&&r>=u[p+0]&&n>=u[p+1])?(o[f]=!0,i.push(c[f])):o[f]=!1}}},hn.prototype._forEachCell=function(t,e,r,n,a,i,o,s){for(var l=this._convertToCellCoord(t),c=this._convertToCellCoord(e),u=this._convertToCellCoord(r),h=this._convertToCellCoord(n),f=l;f<=u;f++)for(var p=c;p<=h;p++){var d=this.d*p+f;if((!s||s(this._convertFromCellCoord(f),this._convertFromCellCoord(p),this._convertFromCellCoord(f+1),this._convertFromCellCoord(p+1)))&&a.call(this,t,e,r,n,d,i,o,s))return}},hn.prototype._convertFromCellCoord=function(t){return(t-this.padding)/this.scale},hn.prototype._convertToCellCoord=function(t){return Math.max(0,Math.min(this.d-1,Math.floor(t*this.scale)+this.padding))},hn.prototype.toArrayBuffer=function(){if(this.arrayBuffer)return this.arrayBuffer;for(var t=this.cells,e=un+this.cells.length+1+1,r=0,n=0;n<this.cells.length;n++)r+=this.cells[n].length;var a=new Int32Array(e+r+this.keys.length+this.bboxes.length);a[0]=this.extent,a[1]=this.n,a[2]=this.padding;for(var i=e,o=0;o<t.length;o++){var s=t[o];a[un+o]=i,a.set(s,i),i+=s.length}return a[un+t.length]=i,a.set(this.keys,i),i+=this.keys.length,a[un+t.length+1]=i,a.set(this.bboxes,i),i+=this.bboxes.length,a.buffer};var fn=self.ImageData,pn={};function dn(t,e,r){void 0===r&&(r={}),Object.defineProperty(e,\"_classRegistryKey\",{value:t,writeable:!1}),pn[t]={klass:e,omit:r.omit||[],shallow:r.shallow||[]}}for(var gn in dn(\"Object\",Object),cn.serialize=function(t,e){var r=t.toArrayBuffer();return e&&e.push(r),{buffer:r}},cn.deserialize=function(t){return new cn(t.buffer)},dn(\"Grid\",cn),dn(\"Color\",Wt),dn(\"Error\",Error),dn(\"StylePropertyFunction\",Sr),dn(\"StyleExpression\",_r,{omit:[\"_evaluator\"]}),dn(\"ZoomDependentExpression\",Mr),dn(\"ZoomConstantExpression\",Tr),dn(\"CompoundExpression\",ce,{omit:[\"_evaluate\"]}),nr)nr[gn]._classRegistryKey||dn(\"Expression_\"+gn,nr[gn]);function vn(t,e){if(null==t||\"boolean\"==typeof t||\"number\"==typeof t||\"string\"==typeof t||t instanceof Boolean||t instanceof Number||t instanceof String||t instanceof Date||t instanceof RegExp)return t;if(t instanceof ArrayBuffer)return e&&e.push(t),t;if(ArrayBuffer.isView(t)){var r=t;return e&&e.push(r.buffer),r}if(t instanceof fn)return e&&e.push(t.data.buffer),t;if(Array.isArray(t)){for(var n=[],a=0,i=t;a<i.length;a+=1){var o=i[a];n.push(vn(o,e))}return n}if(\"object\"==typeof t){var s=t.constructor,l=s._classRegistryKey;if(!l)throw new Error(\"can't serialize object of unregistered class\");var c=s.serialize?s.serialize(t,e):{};if(!s.serialize){for(var u in t)if(t.hasOwnProperty(u)&&!(pn[l].omit.indexOf(u)>=0)){var h=t[u];c[u]=pn[l].shallow.indexOf(u)>=0?h:vn(h,e)}t instanceof Error&&(c.message=t.message)}if(c.$name)throw new Error(\"$name property is reserved for worker serialization logic.\");return\"Object\"!==l&&(c.$name=l),c}throw new Error(\"can't serialize object of type \"+typeof t)}function mn(t){if(null==t||\"boolean\"==typeof t||\"number\"==typeof t||\"string\"==typeof t||t instanceof Boolean||t instanceof Number||t instanceof String||t instanceof Date||t instanceof RegExp||t instanceof ArrayBuffer||ArrayBuffer.isView(t)||t instanceof fn)return t;if(Array.isArray(t))return t.map(mn);if(\"object\"==typeof t){var e=t.$name||\"Object\",r=pn[e].klass;if(!r)throw new Error(\"can't deserialize unregistered class \"+e);if(r.deserialize)return r.deserialize(t);for(var n=Object.create(r.prototype),a=0,i=Object.keys(t);a<i.length;a+=1){var o=i[a];if(\"$name\"!==o){var s=t[o];n[o]=pn[e].shallow.indexOf(o)>=0?s:mn(s)}}return n}throw new Error(\"can't deserialize object of type \"+typeof t)}var yn=function(){this.first=!0};yn.prototype.update=function(t,e){var r=Math.floor(t);return this.first?(this.first=!1,this.lastIntegerZoom=r,this.lastIntegerZoomTime=0,this.lastZoom=t,this.lastFloorZoom=r,!0):(this.lastFloorZoom>r?(this.lastIntegerZoom=r+1,this.lastIntegerZoomTime=e):this.lastFloorZoom<r&&(this.lastIntegerZoom=r,this.lastIntegerZoomTime=e),t!==this.lastZoom&&(this.lastZoom=t,this.lastFloorZoom=r,!0))};var xn={\"Latin-1 Supplement\":function(t){return t>=128&&t<=255},Arabic:function(t){return t>=1536&&t<=1791},\"Arabic Supplement\":function(t){return t>=1872&&t<=1919},\"Arabic Extended-A\":function(t){return t>=2208&&t<=2303},\"Hangul Jamo\":function(t){return t>=4352&&t<=4607},\"Unified Canadian Aboriginal Syllabics\":function(t){return t>=5120&&t<=5759},Khmer:function(t){return t>=6016&&t<=6143},\"Unified Canadian Aboriginal Syllabics Extended\":function(t){return t>=6320&&t<=6399},\"General Punctuation\":function(t){return t>=8192&&t<=8303},\"Letterlike Symbols\":function(t){return t>=8448&&t<=8527},\"Number Forms\":function(t){return t>=8528&&t<=8591},\"Miscellaneous Technical\":function(t){return t>=8960&&t<=9215},\"Control Pictures\":function(t){return t>=9216&&t<=9279},\"Optical Character Recognition\":function(t){return t>=9280&&t<=9311},\"Enclosed Alphanumerics\":function(t){return t>=9312&&t<=9471},\"Geometric Shapes\":function(t){return t>=9632&&t<=9727},\"Miscellaneous Symbols\":function(t){return t>=9728&&t<=9983},\"Miscellaneous Symbols and Arrows\":function(t){return t>=11008&&t<=11263},\"CJK Radicals Supplement\":function(t){return t>=11904&&t<=12031},\"Kangxi Radicals\":function(t){return t>=12032&&t<=12255},\"Ideographic Description Characters\":function(t){return t>=12272&&t<=12287},\"CJK Symbols and Punctuation\":function(t){return t>=12288&&t<=12351},Hiragana:function(t){return t>=12352&&t<=12447},Katakana:function(t){return t>=12448&&t<=12543},Bopomofo:function(t){return t>=12544&&t<=12591},\"Hangul Compatibility Jamo\":function(t){return t>=12592&&t<=12687},Kanbun:function(t){return t>=12688&&t<=12703},\"Bopomofo Extended\":function(t){return t>=12704&&t<=12735},\"CJK Strokes\":function(t){return t>=12736&&t<=12783},\"Katakana Phonetic Extensions\":function(t){return t>=12784&&t<=12799},\"Enclosed CJK Letters and Months\":function(t){return t>=12800&&t<=13055},\"CJK Compatibility\":function(t){return t>=13056&&t<=13311},\"CJK Unified Ideographs Extension A\":function(t){return t>=13312&&t<=19903},\"Yijing Hexagram Symbols\":function(t){return t>=19904&&t<=19967},\"CJK Unified Ideographs\":function(t){return t>=19968&&t<=40959},\"Yi Syllables\":function(t){return t>=40960&&t<=42127},\"Yi Radicals\":function(t){return t>=42128&&t<=42191},\"Hangul Jamo Extended-A\":function(t){return t>=43360&&t<=43391},\"Hangul Syllables\":function(t){return t>=44032&&t<=55215},\"Hangul Jamo Extended-B\":function(t){return t>=55216&&t<=55295},\"Private Use Area\":function(t){return t>=57344&&t<=63743},\"CJK Compatibility Ideographs\":function(t){return t>=63744&&t<=64255},\"Arabic Presentation Forms-A\":function(t){return t>=64336&&t<=65023},\"Vertical Forms\":function(t){return t>=65040&&t<=65055},\"CJK Compatibility Forms\":function(t){return t>=65072&&t<=65103},\"Small Form Variants\":function(t){return t>=65104&&t<=65135},\"Arabic Presentation Forms-B\":function(t){return t>=65136&&t<=65279},\"Halfwidth and Fullwidth Forms\":function(t){return t>=65280&&t<=65519}};function bn(t){for(var e=0,r=t;e<r.length;e+=1)if(wn(r[e].charCodeAt(0)))return!0;return!1}function _n(t){return!(xn.Arabic(t)||xn[\"Arabic Supplement\"](t)||xn[\"Arabic Extended-A\"](t)||xn[\"Arabic Presentation Forms-A\"](t)||xn[\"Arabic Presentation Forms-B\"](t))}function wn(t){return!!(746===t||747===t||!(t<4352)&&(xn[\"Bopomofo Extended\"](t)||xn.Bopomofo(t)||xn[\"CJK Compatibility Forms\"](t)&&!(t>=65097&&t<=65103)||xn[\"CJK Compatibility Ideographs\"](t)||xn[\"CJK Compatibility\"](t)||xn[\"CJK Radicals Supplement\"](t)||xn[\"CJK Strokes\"](t)||!(!xn[\"CJK Symbols and Punctuation\"](t)||t>=12296&&t<=12305||t>=12308&&t<=12319||12336===t)||xn[\"CJK Unified Ideographs Extension A\"](t)||xn[\"CJK Unified Ideographs\"](t)||xn[\"Enclosed CJK Letters and Months\"](t)||xn[\"Hangul Compatibility Jamo\"](t)||xn[\"Hangul Jamo Extended-A\"](t)||xn[\"Hangul Jamo Extended-B\"](t)||xn[\"Hangul Jamo\"](t)||xn[\"Hangul Syllables\"](t)||xn.Hiragana(t)||xn[\"Ideographic Description Characters\"](t)||xn.Kanbun(t)||xn[\"Kangxi Radicals\"](t)||xn[\"Katakana Phonetic Extensions\"](t)||xn.Katakana(t)&&12540!==t||!(!xn[\"Halfwidth and Fullwidth Forms\"](t)||65288===t||65289===t||65293===t||t>=65306&&t<=65310||65339===t||65341===t||65343===t||t>=65371&&t<=65503||65507===t||t>=65512&&t<=65519)||!(!xn[\"Small Form Variants\"](t)||t>=65112&&t<=65118||t>=65123&&t<=65126)||xn[\"Unified Canadian Aboriginal Syllabics\"](t)||xn[\"Unified Canadian Aboriginal Syllabics Extended\"](t)||xn[\"Vertical Forms\"](t)||xn[\"Yijing Hexagram Symbols\"](t)||xn[\"Yi Syllables\"](t)||xn[\"Yi Radicals\"](t)))}function kn(t){return!(wn(t)||function(t){return!!(xn[\"Latin-1 Supplement\"](t)&&(167===t||169===t||174===t||177===t||188===t||189===t||190===t||215===t||247===t)||xn[\"General Punctuation\"](t)&&(8214===t||8224===t||8225===t||8240===t||8241===t||8251===t||8252===t||8258===t||8263===t||8264===t||8265===t||8273===t)||xn[\"Letterlike Symbols\"](t)||xn[\"Number Forms\"](t)||xn[\"Miscellaneous Technical\"](t)&&(t>=8960&&t<=8967||t>=8972&&t<=8991||t>=8996&&t<=9e3||9003===t||t>=9085&&t<=9114||t>=9150&&t<=9165||9167===t||t>=9169&&t<=9179||t>=9186&&t<=9215)||xn[\"Control Pictures\"](t)&&9251!==t||xn[\"Optical Character Recognition\"](t)||xn[\"Enclosed Alphanumerics\"](t)||xn[\"Geometric Shapes\"](t)||xn[\"Miscellaneous Symbols\"](t)&&!(t>=9754&&t<=9759)||xn[\"Miscellaneous Symbols and Arrows\"](t)&&(t>=11026&&t<=11055||t>=11088&&t<=11097||t>=11192&&t<=11243)||xn[\"CJK Symbols and Punctuation\"](t)||xn.Katakana(t)||xn[\"Private Use Area\"](t)||xn[\"CJK Compatibility Forms\"](t)||xn[\"Small Form Variants\"](t)||xn[\"Halfwidth and Fullwidth Forms\"](t)||8734===t||8756===t||8757===t||t>=9984&&t<=10087||t>=10102&&t<=10131||65532===t||65533===t)}(t))}function Tn(t,e){return!(!e&&(t>=1424&&t<=2303||xn[\"Arabic Presentation Forms-A\"](t)||xn[\"Arabic Presentation Forms-B\"](t))||t>=2304&&t<=3583||t>=3840&&t<=4255||xn.Khmer(t))}var Mn,An=!1,Sn=null,En=!1,Ln=new kt,Cn={applyArabicShaping:null,processBidirectionalText:null,processStyledBidirectionalText:null,isLoaded:function(){return En||null!=Cn.applyArabicShaping}},Pn=function(t,e){this.zoom=t,e?(this.now=e.now,this.fadeDuration=e.fadeDuration,this.zoomHistory=e.zoomHistory,this.transition=e.transition):(this.now=0,this.fadeDuration=0,this.zoomHistory=new yn,this.transition={})};Pn.prototype.isSupportedScript=function(t){return function(t,e){for(var r=0,n=t;r<n.length;r+=1)if(!Tn(n[r].charCodeAt(0),e))return!1;return!0}(t,Cn.isLoaded())},Pn.prototype.crossFadingFactor=function(){return 0===this.fadeDuration?1:Math.min((this.now-this.zoomHistory.lastIntegerZoomTime)/this.fadeDuration,1)},Pn.prototype.getCrossfadeParameters=function(){var t=this.zoom,e=t-Math.floor(t),r=this.crossFadingFactor();return t>this.zoomHistory.lastIntegerZoom?{fromScale:2,toScale:1,t:e+(1-e)*r}:{fromScale:.5,toScale:1,t:1-(1-r)*e}};var On=function(t,e){this.property=t,this.value=e,this.expression=function(t,e){if(dr(t))return new Sr(t,e);if(wr(t)){var r=Ar(t,e);if(\"error\"===r.result)throw new Error(r.value.map(function(t){return t.key+\": \"+t.message}).join(\", \"));return r.value}var n=t;return\"string\"==typeof t&&\"color\"===e.type&&(n=Wt.parse(t)),{kind:\"constant\",evaluate:function(){return n}}}(void 0===e?t.specification.default:e,t.specification)};On.prototype.isDataDriven=function(){return\"source\"===this.expression.kind||\"composite\"===this.expression.kind},On.prototype.possiblyEvaluate=function(t){return this.property.possiblyEvaluate(this,t)};var zn=function(t){this.property=t,this.value=new On(t,void 0)};zn.prototype.transitioned=function(t,e){return new Dn(this.property,this.value,e,h({},t.transition,this.transition),t.now)},zn.prototype.untransitioned=function(){return new Dn(this.property,this.value,null,{},0)};var In=function(t){this._properties=t,this._values=Object.create(t.defaultTransitionablePropertyValues)};In.prototype.getValue=function(t){return b(this._values[t].value.value)},In.prototype.setValue=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new zn(this._values[t].property)),this._values[t].value=new On(this._values[t].property,null===e?void 0:b(e))},In.prototype.getTransition=function(t){return b(this._values[t].transition)},In.prototype.setTransition=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new zn(this._values[t].property)),this._values[t].transition=b(e)||void 0},In.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],a=this.getValue(n);void 0!==a&&(t[n]=a);var i=this.getTransition(n);void 0!==i&&(t[n+\"-transition\"]=i)}return t},In.prototype.transitioned=function(t,e){for(var r=new Rn(this._properties),n=0,a=Object.keys(this._values);n<a.length;n+=1){var i=a[n];r._values[i]=this._values[i].transitioned(t,e._values[i])}return r},In.prototype.untransitioned=function(){for(var t=new Rn(this._properties),e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e];t._values[n]=this._values[n].untransitioned()}return t};var Dn=function(t,e,r,n,a){this.property=t,this.value=e,this.begin=a+n.delay||0,this.end=this.begin+n.duration||0,t.specification.transition&&(n.delay||n.duration)&&(this.prior=r)};Dn.prototype.possiblyEvaluate=function(t){var e=t.now||0,r=this.value.possiblyEvaluate(t),n=this.prior;if(n){if(e>this.end)return this.prior=null,r;if(this.value.isDataDriven())return this.prior=null,r;if(e<this.begin)return n.possiblyEvaluate(t);var a=(e-this.begin)/(this.end-this.begin);return this.property.interpolate(n.possiblyEvaluate(t),r,function(t){if(a<=0)return 0;if(a>=1)return 1;var e=a*a,r=e*a;return 4*(a<.5?r:3*(a-e)+r-.75)}())}return r};var Rn=function(t){this._properties=t,this._values=Object.create(t.defaultTransitioningPropertyValues)};Rn.prototype.possiblyEvaluate=function(t){for(var e=new Nn(this._properties),r=0,n=Object.keys(this._values);r<n.length;r+=1){var a=n[r];e._values[a]=this._values[a].possiblyEvaluate(t)}return e},Rn.prototype.hasTransition=function(){for(var t=0,e=Object.keys(this._values);t<e.length;t+=1){var r=e[t];if(this._values[r].prior)return!0}return!1};var Fn=function(t){this._properties=t,this._values=Object.create(t.defaultPropertyValues)};Fn.prototype.getValue=function(t){return b(this._values[t].value)},Fn.prototype.setValue=function(t,e){this._values[t]=new On(this._values[t].property,null===e?void 0:b(e))},Fn.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],a=this.getValue(n);void 0!==a&&(t[n]=a)}return t},Fn.prototype.possiblyEvaluate=function(t){for(var e=new Nn(this._properties),r=0,n=Object.keys(this._values);r<n.length;r+=1){var a=n[r];e._values[a]=this._values[a].possiblyEvaluate(t)}return e};var Bn=function(t,e,r){this.property=t,this.value=e,this.parameters=r};Bn.prototype.isConstant=function(){return\"constant\"===this.value.kind},Bn.prototype.constantOr=function(t){return\"constant\"===this.value.kind?this.value.value:t},Bn.prototype.evaluate=function(t,e){return this.property.evaluate(this.value,this.parameters,t,e)};var Nn=function(t){this._properties=t,this._values=Object.create(t.defaultPossiblyEvaluatedValues)};Nn.prototype.get=function(t){return this._values[t]};var jn=function(t){this.specification=t};jn.prototype.possiblyEvaluate=function(t,e){return t.expression.evaluate(e)},jn.prototype.interpolate=function(t,e,r){var n=xe[this.specification.type];return n?n(t,e,r):t};var Vn=function(t,e){this.specification=t,this.overrides=e};Vn.prototype.possiblyEvaluate=function(t,e){return\"constant\"===t.expression.kind||\"camera\"===t.expression.kind?new Bn(this,{kind:\"constant\",value:t.expression.evaluate(e)},e):new Bn(this,t.expression,e)},Vn.prototype.interpolate=function(t,e,r){if(\"constant\"!==t.value.kind||\"constant\"!==e.value.kind)return t;if(void 0===t.value.value||void 0===e.value.value)return new Bn(this,{kind:\"constant\",value:void 0},t.parameters);var n=xe[this.specification.type];return n?new Bn(this,{kind:\"constant\",value:n(t.value.value,e.value.value,r)},t.parameters):t},Vn.prototype.evaluate=function(t,e,r,n){return\"constant\"===t.kind?t.value:t.evaluate(e,r,n)};var Un=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(t,e){if(void 0===t.value)return new Bn(this,{kind:\"constant\",value:void 0},e);if(\"constant\"===t.expression.kind){var r=t.expression.evaluate(e),n=this._calculate(r,r,r,e);return new Bn(this,{kind:\"constant\",value:n},e)}if(\"camera\"===t.expression.kind){var a=this._calculate(t.expression.evaluate({zoom:e.zoom-1}),t.expression.evaluate({zoom:e.zoom}),t.expression.evaluate({zoom:e.zoom+1}),e);return new Bn(this,{kind:\"constant\",value:a},e)}return new Bn(this,t.expression,e)},e.prototype.evaluate=function(t,e,r,n){if(\"source\"===t.kind){var a=t.evaluate(e,r,n);return this._calculate(a,a,a,e)}return\"composite\"===t.kind?this._calculate(t.evaluate({zoom:Math.floor(e.zoom)-1},r,n),t.evaluate({zoom:Math.floor(e.zoom)},r,n),t.evaluate({zoom:Math.floor(e.zoom)+1},r,n),e):t.value},e.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},e.prototype.interpolate=function(t){return t},e}(Vn),qn=function(t){this.specification=t};qn.prototype.possiblyEvaluate=function(t,e){if(void 0!==t.value){if(\"constant\"===t.expression.kind){var r=t.expression.evaluate(e);return this._calculate(r,r,r,e)}return this._calculate(t.expression.evaluate(new Pn(Math.floor(e.zoom-1),e)),t.expression.evaluate(new Pn(Math.floor(e.zoom),e)),t.expression.evaluate(new Pn(Math.floor(e.zoom+1),e)),e)}},qn.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},qn.prototype.interpolate=function(t){return t};var Hn=function(t){this.specification=t};Hn.prototype.possiblyEvaluate=function(t,e){return!!t.expression.evaluate(e)},Hn.prototype.interpolate=function(){return!1};var Gn=function(t){for(var e in this.properties=t,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[],t){var r=t[e];r.specification.overridable&&this.overridableProperties.push(e);var n=this.defaultPropertyValues[e]=new On(r,void 0),a=this.defaultTransitionablePropertyValues[e]=new zn(r);this.defaultTransitioningPropertyValues[e]=a.untransitioned(),this.defaultPossiblyEvaluatedValues[e]=n.possiblyEvaluate({})}};dn(\"DataDrivenProperty\",Vn),dn(\"DataConstantProperty\",jn),dn(\"CrossFadedDataDrivenProperty\",Un),dn(\"CrossFadedProperty\",qn),dn(\"ColorRampProperty\",Hn);var Yn=function(t){function e(e,r){if(t.call(this),this.id=e.id,this.type=e.type,this._featureFilter=function(){return!0},\"custom\"!==e.type&&(e=e,this.metadata=e.metadata,this.minzoom=e.minzoom,this.maxzoom=e.maxzoom,\"background\"!==e.type&&(this.source=e.source,this.sourceLayer=e[\"source-layer\"],this.filter=e.filter),r.layout&&(this._unevaluatedLayout=new Fn(r.layout)),r.paint)){for(var n in this._transitionablePaint=new In(r.paint),e.paint)this.setPaintProperty(n,e.paint[n],{validate:!1});for(var a in e.layout)this.setLayoutProperty(a,e.layout[a],{validate:!1});this._transitioningPaint=this._transitionablePaint.untransitioned()}}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getCrossfadeParameters=function(){return this._crossfadeParameters},e.prototype.getLayoutProperty=function(t){return\"visibility\"===t?this.visibility:this._unevaluatedLayout.getValue(t)},e.prototype.setLayoutProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".layout.\"+t;if(this._validate(sn,n,t,e,r))return}\"visibility\"!==t?this._unevaluatedLayout.setValue(t,e):this.visibility=e},e.prototype.getPaintProperty=function(t){return m(t,\"-transition\")?this._transitionablePaint.getTransition(t.slice(0,-\"-transition\".length)):this._transitionablePaint.getValue(t)},e.prototype.setPaintProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".paint.\"+t;if(this._validate(on,n,t,e,r))return!1}if(m(t,\"-transition\"))return this._transitionablePaint.setTransition(t.slice(0,-\"-transition\".length),e||void 0),!1;var a=this._transitionablePaint._values[t],i=\"cross-faded-data-driven\"===a.property.specification[\"property-type\"],o=a.value.isDataDriven(),s=a.value;this._transitionablePaint.setValue(t,e),this._handleSpecialPaintPropertyUpdate(t);var l=this._transitionablePaint._values[t].value;return l.isDataDriven()||o||i||this._handleOverridablePaintPropertyUpdate(t,s,l)},e.prototype._handleSpecialPaintPropertyUpdate=function(t){},e.prototype._handleOverridablePaintPropertyUpdate=function(t,e,r){return!1},e.prototype.isHidden=function(t){return!!(this.minzoom&&t<this.minzoom)||!!(this.maxzoom&&t>=this.maxzoom)||\"none\"===this.visibility},e.prototype.updateTransitions=function(t){this._transitioningPaint=this._transitionablePaint.transitioned(t,this._transitioningPaint)},e.prototype.hasTransition=function(){return this._transitioningPaint.hasTransition()},e.prototype.recalculate=function(t){t.getCrossfadeParameters&&(this._crossfadeParameters=t.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(t)),this.paint=this._transitioningPaint.possiblyEvaluate(t)},e.prototype.serialize=function(){var t={id:this.id,type:this.type,source:this.source,\"source-layer\":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(t.layout=t.layout||{},t.layout.visibility=this.visibility),x(t,function(t,e){return!(void 0===t||\"layout\"===e&&!Object.keys(t).length||\"paint\"===e&&!Object.keys(t).length)})},e.prototype._validate=function(t,e,r,n,a){return void 0===a&&(a={}),(!a||!1!==a.validate)&&ln(this,t.call(nn,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:Tt,style:{glyphs:!0,sprite:!0}}))},e.prototype.is3D=function(){return!1},e.prototype.isTileClipped=function(){return!1},e.prototype.hasOffscreenPass=function(){return!1},e.prototype.resize=function(){},e.prototype.isStateDependent=function(){for(var t in this.paint._values){var e=this.paint.get(t);if(e instanceof Bn&&ur(e.property.specification)&&(\"source\"===e.value.kind||\"composite\"===e.value.kind)&&e.value.isStateDependent)return!0}return!1},e}(kt),Wn={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array},Xn=function(t,e){this._structArray=t,this._pos1=e*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8},Zn=function(){this.isTransferred=!1,this.capacity=-1,this.resize(0)};function Jn(t,e){void 0===e&&(e=1);var r=0,n=0;return{members:t.map(function(t){var a,i=(a=t.type,Wn[a].BYTES_PER_ELEMENT),o=r=Kn(r,Math.max(e,i)),s=t.components||1;return n=Math.max(n,i),r+=i*s,{name:t.name,type:t.type,components:s,offset:o}}),size:Kn(r,Math.max(n,e)),alignment:e}}function Kn(t,e){return Math.ceil(t/e)*e}Zn.serialize=function(t,e){return t._trim(),e&&(t.isTransferred=!0,e.push(t.arrayBuffer)),{length:t.length,arrayBuffer:t.arrayBuffer}},Zn.deserialize=function(t){var e=Object.create(this.prototype);return e.arrayBuffer=t.arrayBuffer,e.length=t.length,e.capacity=t.arrayBuffer.byteLength/e.bytesPerElement,e._refreshViews(),e},Zn.prototype._trim=function(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())},Zn.prototype.clear=function(){this.length=0},Zn.prototype.resize=function(t){this.reserve(t),this.length=t},Zn.prototype.reserve=function(t){if(t>this.capacity){this.capacity=Math.max(t,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);var e=this.uint8;this._refreshViews(),e&&this.uint8.set(e)}},Zn.prototype._refreshViews=function(){throw new Error(\"_refreshViews() must be implemented by each concrete StructArray layout\")};var Qn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.int16[n+0]=e,this.int16[n+1]=r,t},e}(Zn);Qn.prototype.bytesPerElement=4,dn(\"StructArrayLayout2i4\",Qn);var $n=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,a){var i=4*t;return this.int16[i+0]=e,this.int16[i+1]=r,this.int16[i+2]=n,this.int16[i+3]=a,t},e}(Zn);$n.prototype.bytesPerElement=8,dn(\"StructArrayLayout4i8\",$n);var ta=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a,i){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,a,i)},e.prototype.emplace=function(t,e,r,n,a,i,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=a,this.int16[s+4]=i,this.int16[s+5]=o,t},e}(Zn);ta.prototype.bytesPerElement=12,dn(\"StructArrayLayout2i4i12\",ta);var ea=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a,i){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,a,i)},e.prototype.emplace=function(t,e,r,n,a,i,o){var s=4*t,l=8*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.uint8[l+4]=n,this.uint8[l+5]=a,this.uint8[l+6]=i,this.uint8[l+7]=o,t},e}(Zn);ea.prototype.bytesPerElement=8,dn(\"StructArrayLayout2i4ub8\",ea);var ra=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a,i,o,s){var l=this.length;return this.resize(l+1),this.emplace(l,t,e,r,n,a,i,o,s)},e.prototype.emplace=function(t,e,r,n,a,i,o,s,l){var c=8*t;return this.uint16[c+0]=e,this.uint16[c+1]=r,this.uint16[c+2]=n,this.uint16[c+3]=a,this.uint16[c+4]=i,this.uint16[c+5]=o,this.uint16[c+6]=s,this.uint16[c+7]=l,t},e}(Zn);ra.prototype.bytesPerElement=16,dn(\"StructArrayLayout8ui16\",ra);var na=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a,i,o,s){var l=this.length;return this.resize(l+1),this.emplace(l,t,e,r,n,a,i,o,s)},e.prototype.emplace=function(t,e,r,n,a,i,o,s,l){var c=8*t;return this.int16[c+0]=e,this.int16[c+1]=r,this.int16[c+2]=n,this.int16[c+3]=a,this.uint16[c+4]=i,this.uint16[c+5]=o,this.uint16[c+6]=s,this.uint16[c+7]=l,t},e}(Zn);na.prototype.bytesPerElement=16,dn(\"StructArrayLayout4i4ui16\",na);var aa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var a=3*t;return this.float32[a+0]=e,this.float32[a+1]=r,this.float32[a+2]=n,t},e}(Zn);aa.prototype.bytesPerElement=12,dn(\"StructArrayLayout3f12\",aa);var ia=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.uint32[r+0]=e,t},e}(Zn);ia.prototype.bytesPerElement=4,dn(\"StructArrayLayout1ul4\",ia);var oa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a,i,o,s,l,c,u){var h=this.length;return this.resize(h+1),this.emplace(h,t,e,r,n,a,i,o,s,l,c,u)},e.prototype.emplace=function(t,e,r,n,a,i,o,s,l,c,u,h){var f=12*t,p=6*t;return this.int16[f+0]=e,this.int16[f+1]=r,this.int16[f+2]=n,this.int16[f+3]=a,this.int16[f+4]=i,this.int16[f+5]=o,this.uint32[p+3]=s,this.uint16[f+8]=l,this.uint16[f+9]=c,this.int16[f+10]=u,this.int16[f+11]=h,t},e}(Zn);oa.prototype.bytesPerElement=24,dn(\"StructArrayLayout6i1ul2ui2i24\",oa);var sa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a,i){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,a,i)},e.prototype.emplace=function(t,e,r,n,a,i,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=a,this.int16[s+4]=i,this.int16[s+5]=o,t},e}(Zn);sa.prototype.bytesPerElement=12,dn(\"StructArrayLayout2i2i2i12\",sa);var la=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,a){var i=12*t,o=3*t;return this.uint8[i+0]=e,this.uint8[i+1]=r,this.float32[o+1]=n,this.float32[o+2]=a,t},e}(Zn);la.prototype.bytesPerElement=12,dn(\"StructArrayLayout2ub2f12\",la);var ca=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g){var v=this.length;return this.resize(v+1),this.emplace(v,t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g)},e.prototype.emplace=function(t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g,v){var m=22*t,y=11*t,x=44*t;return this.int16[m+0]=e,this.int16[m+1]=r,this.uint16[m+2]=n,this.uint16[m+3]=a,this.uint32[y+2]=i,this.uint32[y+3]=o,this.uint32[y+4]=s,this.uint16[m+10]=l,this.uint16[m+11]=c,this.uint16[m+12]=u,this.float32[y+7]=h,this.float32[y+8]=f,this.uint8[x+36]=p,this.uint8[x+37]=d,this.uint8[x+38]=g,this.uint32[y+10]=v,t},e}(Zn);ca.prototype.bytesPerElement=44,dn(\"StructArrayLayout2i2ui3ul3ui2f3ub1ul44\",ca);var ua=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g,v,m,y,x){var b=this.length;return this.resize(b+1),this.emplace(b,t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g,v,m,y,x)},e.prototype.emplace=function(t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g,v,m,y,x,b){var _=24*t,w=12*t;return this.int16[_+0]=e,this.int16[_+1]=r,this.int16[_+2]=n,this.int16[_+3]=a,this.int16[_+4]=i,this.int16[_+5]=o,this.uint16[_+6]=s,this.uint16[_+7]=l,this.uint16[_+8]=c,this.uint16[_+9]=u,this.uint16[_+10]=h,this.uint16[_+11]=f,this.uint16[_+12]=p,this.uint16[_+13]=d,this.uint16[_+14]=g,this.uint16[_+15]=v,this.uint16[_+16]=m,this.uint32[w+9]=y,this.float32[w+10]=x,this.float32[w+11]=b,t},e}(Zn);ua.prototype.bytesPerElement=48,dn(\"StructArrayLayout6i11ui1ul2f48\",ua);var ha=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.float32[r+0]=e,t},e}(Zn);ha.prototype.bytesPerElement=4,dn(\"StructArrayLayout1f4\",ha);var fa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var a=3*t;return this.int16[a+0]=e,this.int16[a+1]=r,this.int16[a+2]=n,t},e}(Zn);fa.prototype.bytesPerElement=6,dn(\"StructArrayLayout3i6\",fa);var pa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var a=2*t,i=4*t;return this.uint32[a+0]=e,this.uint16[i+2]=r,this.uint16[i+3]=n,t},e}(Zn);pa.prototype.bytesPerElement=8,dn(\"StructArrayLayout1ul2ui8\",pa);var da=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var a=3*t;return this.uint16[a+0]=e,this.uint16[a+1]=r,this.uint16[a+2]=n,t},e}(Zn);da.prototype.bytesPerElement=6,dn(\"StructArrayLayout3ui6\",da);var ga=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.uint16[n+0]=e,this.uint16[n+1]=r,t},e}(Zn);ga.prototype.bytesPerElement=4,dn(\"StructArrayLayout2ui4\",ga);var va=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.uint16[r+0]=e,t},e}(Zn);va.prototype.bytesPerElement=2,dn(\"StructArrayLayout1ui2\",va);var ma=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.float32[n+0]=e,this.float32[n+1]=r,t},e}(Zn);ma.prototype.bytesPerElement=8,dn(\"StructArrayLayout2f8\",ma);var ya=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,a){var i=4*t;return this.float32[i+0]=e,this.float32[i+1]=r,this.float32[i+2]=n,this.float32[i+3]=a,t},e}(Zn);ya.prototype.bytesPerElement=16,dn(\"StructArrayLayout4f16\",ya);var xa=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorPointX:{configurable:!0},anchorPointY:{configurable:!0},x1:{configurable:!0},y1:{configurable:!0},x2:{configurable:!0},y2:{configurable:!0},featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0},radius:{configurable:!0},signedDistanceFromAnchor:{configurable:!0},anchorPoint:{configurable:!0}};return r.anchorPointX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorPointX.set=function(t){this._structArray.int16[this._pos2+0]=t},r.anchorPointY.get=function(){return this._structArray.int16[this._pos2+1]},r.anchorPointY.set=function(t){this._structArray.int16[this._pos2+1]=t},r.x1.get=function(){return this._structArray.int16[this._pos2+2]},r.x1.set=function(t){this._structArray.int16[this._pos2+2]=t},r.y1.get=function(){return this._structArray.int16[this._pos2+3]},r.y1.set=function(t){this._structArray.int16[this._pos2+3]=t},r.x2.get=function(){return this._structArray.int16[this._pos2+4]},r.x2.set=function(t){this._structArray.int16[this._pos2+4]=t},r.y2.get=function(){return this._structArray.int16[this._pos2+5]},r.y2.set=function(t){this._structArray.int16[this._pos2+5]=t},r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.featureIndex.set=function(t){this._structArray.uint32[this._pos4+3]=t},r.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+8]},r.sourceLayerIndex.set=function(t){this._structArray.uint16[this._pos2+8]=t},r.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.bucketIndex.set=function(t){this._structArray.uint16[this._pos2+9]=t},r.radius.get=function(){return this._structArray.int16[this._pos2+10]},r.radius.set=function(t){this._structArray.int16[this._pos2+10]=t},r.signedDistanceFromAnchor.get=function(){return this._structArray.int16[this._pos2+11]},r.signedDistanceFromAnchor.set=function(t){this._structArray.int16[this._pos2+11]=t},r.anchorPoint.get=function(){return new a(this.anchorPointX,this.anchorPointY)},Object.defineProperties(e.prototype,r),e}(Xn);xa.prototype.size=24;var ba=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new xa(this,t)},e}(oa);dn(\"CollisionBoxArray\",ba);var _a=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},glyphStartIndex:{configurable:!0},numGlyphs:{configurable:!0},vertexStartIndex:{configurable:!0},lineStartIndex:{configurable:!0},lineLength:{configurable:!0},segment:{configurable:!0},lowerSize:{configurable:!0},upperSize:{configurable:!0},lineOffsetX:{configurable:!0},lineOffsetY:{configurable:!0},writingMode:{configurable:!0},placedOrientation:{configurable:!0},hidden:{configurable:!0},crossTileID:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorX.set=function(t){this._structArray.int16[this._pos2+0]=t},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.anchorY.set=function(t){this._structArray.int16[this._pos2+1]=t},r.glyphStartIndex.get=function(){return this._structArray.uint16[this._pos2+2]},r.glyphStartIndex.set=function(t){this._structArray.uint16[this._pos2+2]=t},r.numGlyphs.get=function(){return this._structArray.uint16[this._pos2+3]},r.numGlyphs.set=function(t){this._structArray.uint16[this._pos2+3]=t},r.vertexStartIndex.get=function(){return this._structArray.uint32[this._pos4+2]},r.vertexStartIndex.set=function(t){this._structArray.uint32[this._pos4+2]=t},r.lineStartIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.lineStartIndex.set=function(t){this._structArray.uint32[this._pos4+3]=t},r.lineLength.get=function(){return this._structArray.uint32[this._pos4+4]},r.lineLength.set=function(t){this._structArray.uint32[this._pos4+4]=t},r.segment.get=function(){return this._structArray.uint16[this._pos2+10]},r.segment.set=function(t){this._structArray.uint16[this._pos2+10]=t},r.lowerSize.get=function(){return this._structArray.uint16[this._pos2+11]},r.lowerSize.set=function(t){this._structArray.uint16[this._pos2+11]=t},r.upperSize.get=function(){return this._structArray.uint16[this._pos2+12]},r.upperSize.set=function(t){this._structArray.uint16[this._pos2+12]=t},r.lineOffsetX.get=function(){return this._structArray.float32[this._pos4+7]},r.lineOffsetX.set=function(t){this._structArray.float32[this._pos4+7]=t},r.lineOffsetY.get=function(){return this._structArray.float32[this._pos4+8]},r.lineOffsetY.set=function(t){this._structArray.float32[this._pos4+8]=t},r.writingMode.get=function(){return this._structArray.uint8[this._pos1+36]},r.writingMode.set=function(t){this._structArray.uint8[this._pos1+36]=t},r.placedOrientation.get=function(){return this._structArray.uint8[this._pos1+37]},r.placedOrientation.set=function(t){this._structArray.uint8[this._pos1+37]=t},r.hidden.get=function(){return this._structArray.uint8[this._pos1+38]},r.hidden.set=function(t){this._structArray.uint8[this._pos1+38]=t},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+10]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+10]=t},Object.defineProperties(e.prototype,r),e}(Xn);_a.prototype.size=44;var wa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new _a(this,t)},e}(ca);dn(\"PlacedSymbolArray\",wa);var ka=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},rightJustifiedTextSymbolIndex:{configurable:!0},centerJustifiedTextSymbolIndex:{configurable:!0},leftJustifiedTextSymbolIndex:{configurable:!0},verticalPlacedTextSymbolIndex:{configurable:!0},key:{configurable:!0},textBoxStartIndex:{configurable:!0},textBoxEndIndex:{configurable:!0},verticalTextBoxStartIndex:{configurable:!0},verticalTextBoxEndIndex:{configurable:!0},iconBoxStartIndex:{configurable:!0},iconBoxEndIndex:{configurable:!0},featureIndex:{configurable:!0},numHorizontalGlyphVertices:{configurable:!0},numVerticalGlyphVertices:{configurable:!0},numIconVertices:{configurable:!0},crossTileID:{configurable:!0},textBoxScale:{configurable:!0},radialTextOffset:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorX.set=function(t){this._structArray.int16[this._pos2+0]=t},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.anchorY.set=function(t){this._structArray.int16[this._pos2+1]=t},r.rightJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+2]},r.rightJustifiedTextSymbolIndex.set=function(t){this._structArray.int16[this._pos2+2]=t},r.centerJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+3]},r.centerJustifiedTextSymbolIndex.set=function(t){this._structArray.int16[this._pos2+3]=t},r.leftJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+4]},r.leftJustifiedTextSymbolIndex.set=function(t){this._structArray.int16[this._pos2+4]=t},r.verticalPlacedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+5]},r.verticalPlacedTextSymbolIndex.set=function(t){this._structArray.int16[this._pos2+5]=t},r.key.get=function(){return this._structArray.uint16[this._pos2+6]},r.key.set=function(t){this._structArray.uint16[this._pos2+6]=t},r.textBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+7]},r.textBoxStartIndex.set=function(t){this._structArray.uint16[this._pos2+7]=t},r.textBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+8]},r.textBoxEndIndex.set=function(t){this._structArray.uint16[this._pos2+8]=t},r.verticalTextBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.verticalTextBoxStartIndex.set=function(t){this._structArray.uint16[this._pos2+9]=t},r.verticalTextBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+10]},r.verticalTextBoxEndIndex.set=function(t){this._structArray.uint16[this._pos2+10]=t},r.iconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+11]},r.iconBoxStartIndex.set=function(t){this._structArray.uint16[this._pos2+11]=t},r.iconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+12]},r.iconBoxEndIndex.set=function(t){this._structArray.uint16[this._pos2+12]=t},r.featureIndex.get=function(){return this._structArray.uint16[this._pos2+13]},r.featureIndex.set=function(t){this._structArray.uint16[this._pos2+13]=t},r.numHorizontalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+14]},r.numHorizontalGlyphVertices.set=function(t){this._structArray.uint16[this._pos2+14]=t},r.numVerticalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+15]},r.numVerticalGlyphVertices.set=function(t){this._structArray.uint16[this._pos2+15]=t},r.numIconVertices.get=function(){return this._structArray.uint16[this._pos2+16]},r.numIconVertices.set=function(t){this._structArray.uint16[this._pos2+16]=t},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+9]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+9]=t},r.textBoxScale.get=function(){return this._structArray.float32[this._pos4+10]},r.textBoxScale.set=function(t){this._structArray.float32[this._pos4+10]=t},r.radialTextOffset.get=function(){return this._structArray.float32[this._pos4+11]},r.radialTextOffset.set=function(t){this._structArray.float32[this._pos4+11]=t},Object.defineProperties(e.prototype,r),e}(Xn);ka.prototype.size=48;var Ta=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new ka(this,t)},e}(ua);dn(\"SymbolInstanceArray\",Ta);var Ma=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={offsetX:{configurable:!0}};return r.offsetX.get=function(){return this._structArray.float32[this._pos4+0]},r.offsetX.set=function(t){this._structArray.float32[this._pos4+0]=t},Object.defineProperties(e.prototype,r),e}(Xn);Ma.prototype.size=4;var Aa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getoffsetX=function(t){return this.float32[1*t+0]},e.prototype.get=function(t){return new Ma(this,t)},e}(ha);dn(\"GlyphOffsetArray\",Aa);var Sa=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={x:{configurable:!0},y:{configurable:!0},tileUnitDistanceFromAnchor:{configurable:!0}};return r.x.get=function(){return this._structArray.int16[this._pos2+0]},r.x.set=function(t){this._structArray.int16[this._pos2+0]=t},r.y.get=function(){return this._structArray.int16[this._pos2+1]},r.y.set=function(t){this._structArray.int16[this._pos2+1]=t},r.tileUnitDistanceFromAnchor.get=function(){return this._structArray.int16[this._pos2+2]},r.tileUnitDistanceFromAnchor.set=function(t){this._structArray.int16[this._pos2+2]=t},Object.defineProperties(e.prototype,r),e}(Xn);Sa.prototype.size=6;var Ea=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getx=function(t){return this.int16[3*t+0]},e.prototype.gety=function(t){return this.int16[3*t+1]},e.prototype.gettileUnitDistanceFromAnchor=function(t){return this.int16[3*t+2]},e.prototype.get=function(t){return new Sa(this,t)},e}(fa);dn(\"SymbolLineVertexArray\",Ea);var La=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0}};return r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+0]},r.featureIndex.set=function(t){this._structArray.uint32[this._pos4+0]=t},r.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+2]},r.sourceLayerIndex.set=function(t){this._structArray.uint16[this._pos2+2]=t},r.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+3]},r.bucketIndex.set=function(t){this._structArray.uint16[this._pos2+3]=t},Object.defineProperties(e.prototype,r),e}(Xn);La.prototype.size=8;var Ca=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new La(this,t)},e}(pa);dn(\"FeatureIndexArray\",Ca);var Pa=Jn([{name:\"a_pos\",components:2,type:\"Int16\"}],4).members,Oa=function(t){void 0===t&&(t=[]),this.segments=t};function za(t,e){return 256*(t=c(Math.floor(t),0,255))+c(Math.floor(e),0,255)}Oa.prototype.prepareSegment=function(t,e,r,n){var a=this.segments[this.segments.length-1];return t>Oa.MAX_VERTEX_ARRAY_LENGTH&&w(\"Max vertices per segment is \"+Oa.MAX_VERTEX_ARRAY_LENGTH+\": bucket requested \"+t),(!a||a.vertexLength+t>Oa.MAX_VERTEX_ARRAY_LENGTH||a.sortKey!==n)&&(a={vertexOffset:e.length,primitiveOffset:r.length,vertexLength:0,primitiveLength:0},void 0!==n&&(a.sortKey=n),this.segments.push(a)),a},Oa.prototype.get=function(){return this.segments},Oa.prototype.destroy=function(){for(var t=0,e=this.segments;t<e.length;t+=1){var r=e[t];for(var n in r.vaos)r.vaos[n].destroy()}},Oa.simpleSegment=function(t,e,r,n){return new Oa([{vertexOffset:t,primitiveOffset:e,vertexLength:r,primitiveLength:n,vaos:{},sortKey:0}])},Oa.MAX_VERTEX_ARRAY_LENGTH=Math.pow(2,16)-1,dn(\"SegmentVector\",Oa);var Ia=function(){this.ids=[],this.positions=[],this.indexed=!1};function Da(t,e,r){var n=t[e];t[e]=t[r],t[r]=n}Ia.prototype.add=function(t,e,r,n){this.ids.push(t),this.positions.push(e,r,n)},Ia.prototype.getPositions=function(t){for(var e=0,r=this.ids.length-1;e<r;){var n=e+r>>1;this.ids[n]>=t?r=n:e=n+1}for(var a=[];this.ids[e]===t;){var i=this.positions[3*e],o=this.positions[3*e+1],s=this.positions[3*e+2];a.push({index:i,start:o,end:s}),e++}return a},Ia.serialize=function(t,e){var r=new Float64Array(t.ids),n=new Uint32Array(t.positions);return function t(e,r,n,a){if(!(n>=a)){for(var i=e[n+a>>1],o=n-1,s=a+1;;){do{o++}while(e[o]<i);do{s--}while(e[s]>i);if(o>=s)break;Da(e,o,s),Da(r,3*o,3*s),Da(r,3*o+1,3*s+1),Da(r,3*o+2,3*s+2)}t(e,r,n,s),t(e,r,s+1,a)}}(r,n,0,r.length-1),e.push(r.buffer,n.buffer),{ids:r,positions:n}},Ia.deserialize=function(t){var e=new Ia;return e.ids=t.ids,e.positions=t.positions,e.indexed=!0,e},dn(\"FeaturePositionMap\",Ia);var Ra=function(t,e){this.gl=t.gl,this.location=e},Fa=function(t){function e(e,r){t.call(this,e,r),this.current=0}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){this.current!==t&&(this.current=t,this.gl.uniform1i(this.location,t))},e}(Ra),Ba=function(t){function e(e,r){t.call(this,e,r),this.current=0}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){this.current!==t&&(this.current=t,this.gl.uniform1f(this.location,t))},e}(Ra),Na=function(t){function e(e,r){t.call(this,e,r),this.current=[0,0]}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){t[0]===this.current[0]&&t[1]===this.current[1]||(this.current=t,this.gl.uniform2f(this.location,t[0],t[1]))},e}(Ra),ja=function(t){function e(e,r){t.call(this,e,r),this.current=[0,0,0]}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){t[0]===this.current[0]&&t[1]===this.current[1]&&t[2]===this.current[2]||(this.current=t,this.gl.uniform3f(this.location,t[0],t[1],t[2]))},e}(Ra),Va=function(t){function e(e,r){t.call(this,e,r),this.current=[0,0,0,0]}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){t[0]===this.current[0]&&t[1]===this.current[1]&&t[2]===this.current[2]&&t[3]===this.current[3]||(this.current=t,this.gl.uniform4f(this.location,t[0],t[1],t[2],t[3]))},e}(Ra),Ua=function(t){function e(e,r){t.call(this,e,r),this.current=Wt.transparent}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){t.r===this.current.r&&t.g===this.current.g&&t.b===this.current.b&&t.a===this.current.a||(this.current=t,this.gl.uniform4f(this.location,t.r,t.g,t.b,t.a))},e}(Ra),qa=new Float32Array(16),Ha=function(t){function e(e,r){t.call(this,e,r),this.current=qa}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){if(t[12]!==this.current[12]||t[0]!==this.current[0])return this.current=t,void this.gl.uniformMatrix4fv(this.location,!1,t);for(var e=1;e<16;e++)if(t[e]!==this.current[e]){this.current=t,this.gl.uniformMatrix4fv(this.location,!1,t);break}},e}(Ra);function Ga(t){return[za(255*t.r,255*t.g),za(255*t.b,255*t.a)]}var Ya=function(t,e,r){this.value=t,this.names=e,this.uniformNames=this.names.map(function(t){return\"u_\"+t}),this.type=r,this.maxValue=-1/0};Ya.prototype.defines=function(){return this.names.map(function(t){return\"#define HAS_UNIFORM_u_\"+t})},Ya.prototype.setConstantPatternPositions=function(){},Ya.prototype.populatePaintArray=function(){},Ya.prototype.updatePaintArray=function(){},Ya.prototype.upload=function(){},Ya.prototype.destroy=function(){},Ya.prototype.setUniforms=function(t,e,r,n){e.set(n.constantOr(this.value))},Ya.prototype.getBinding=function(t,e){return\"color\"===this.type?new Ua(t,e):new Ba(t,e)},Ya.serialize=function(t){var e=t.value,r=t.names,n=t.type;return{value:vn(e),names:r,type:n}},Ya.deserialize=function(t){var e=t.value,r=t.names,n=t.type;return new Ya(mn(e),r,n)};var Wa=function(t,e,r){this.value=t,this.names=e,this.uniformNames=this.names.map(function(t){return\"u_\"+t}),this.type=r,this.maxValue=-1/0,this.patternPositions={patternTo:null,patternFrom:null}};Wa.prototype.defines=function(){return this.names.map(function(t){return\"#define HAS_UNIFORM_u_\"+t})},Wa.prototype.populatePaintArray=function(){},Wa.prototype.updatePaintArray=function(){},Wa.prototype.upload=function(){},Wa.prototype.destroy=function(){},Wa.prototype.setConstantPatternPositions=function(t,e){this.patternPositions.patternTo=t.tlbr,this.patternPositions.patternFrom=e.tlbr},Wa.prototype.setUniforms=function(t,e,r,n,a){var i=this.patternPositions;\"u_pattern_to\"===a&&i.patternTo&&e.set(i.patternTo),\"u_pattern_from\"===a&&i.patternFrom&&e.set(i.patternFrom)},Wa.prototype.getBinding=function(t,e){return new Va(t,e)};var Xa=function(t,e,r,n){this.expression=t,this.names=e,this.type=r,this.uniformNames=this.names.map(function(t){return\"a_\"+t}),this.maxValue=-1/0,this.paintVertexAttributes=e.map(function(t){return{name:\"a_\"+t,type:\"Float32\",components:\"color\"===r?2:1,offset:0}}),this.paintVertexArray=new n};Xa.prototype.defines=function(){return[]},Xa.prototype.setConstantPatternPositions=function(){},Xa.prototype.populatePaintArray=function(t,e,r,n){var a=this.paintVertexArray,i=a.length;a.reserve(t);var o=this.expression.evaluate(new Pn(0),e,{},n);if(\"color\"===this.type)for(var s=Ga(o),l=i;l<t;l++)a.emplaceBack(s[0],s[1]);else{for(var c=i;c<t;c++)a.emplaceBack(o);this.maxValue=Math.max(this.maxValue,o)}},Xa.prototype.updatePaintArray=function(t,e,r,n){var a=this.paintVertexArray,i=this.expression.evaluate({zoom:0},r,n);if(\"color\"===this.type)for(var o=Ga(i),s=t;s<e;s++)a.emplace(s,o[0],o[1]);else{for(var l=t;l<e;l++)a.emplace(l,i);this.maxValue=Math.max(this.maxValue,i)}},Xa.prototype.upload=function(t){this.paintVertexArray&&this.paintVertexArray.arrayBuffer&&(this.paintVertexBuffer&&this.paintVertexBuffer.buffer?this.paintVertexBuffer.updateData(this.paintVertexArray):this.paintVertexBuffer=t.createVertexBuffer(this.paintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent))},Xa.prototype.destroy=function(){this.paintVertexBuffer&&this.paintVertexBuffer.destroy()},Xa.prototype.setUniforms=function(t,e){e.set(0)},Xa.prototype.getBinding=function(t,e){return new Ba(t,e)};var Za=function(t,e,r,n,a,i){this.expression=t,this.names=e,this.uniformNames=this.names.map(function(t){return\"u_\"+t+\"_t\"}),this.type=r,this.useIntegerZoom=n,this.zoom=a,this.maxValue=-1/0;var o=i;this.paintVertexAttributes=e.map(function(t){return{name:\"a_\"+t,type:\"Float32\",components:\"color\"===r?4:2,offset:0}}),this.paintVertexArray=new o};Za.prototype.defines=function(){return[]},Za.prototype.setConstantPatternPositions=function(){},Za.prototype.populatePaintArray=function(t,e,r,n){var a=this.paintVertexArray,i=a.length;a.reserve(t);var o=this.expression.evaluate(new Pn(this.zoom),e,{},n),s=this.expression.evaluate(new Pn(this.zoom+1),e,{},n);if(\"color\"===this.type)for(var l=Ga(o),c=Ga(s),u=i;u<t;u++)a.emplaceBack(l[0],l[1],c[0],c[1]);else{for(var h=i;h<t;h++)a.emplaceBack(o,s);this.maxValue=Math.max(this.maxValue,o,s)}},Za.prototype.updatePaintArray=function(t,e,r,n){var a=this.paintVertexArray,i=this.expression.evaluate({zoom:this.zoom},r,n),o=this.expression.evaluate({zoom:this.zoom+1},r,n);if(\"color\"===this.type)for(var s=Ga(i),l=Ga(o),c=t;c<e;c++)a.emplace(c,s[0],s[1],l[0],l[1]);else{for(var u=t;u<e;u++)a.emplace(u,i,o);this.maxValue=Math.max(this.maxValue,i,o)}},Za.prototype.upload=function(t){this.paintVertexArray&&this.paintVertexArray.arrayBuffer&&(this.paintVertexBuffer&&this.paintVertexBuffer.buffer?this.paintVertexBuffer.updateData(this.paintVertexArray):this.paintVertexBuffer=t.createVertexBuffer(this.paintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent))},Za.prototype.destroy=function(){this.paintVertexBuffer&&this.paintVertexBuffer.destroy()},Za.prototype.interpolationFactor=function(t){return this.useIntegerZoom?this.expression.interpolationFactor(Math.floor(t),this.zoom,this.zoom+1):this.expression.interpolationFactor(t,this.zoom,this.zoom+1)},Za.prototype.setUniforms=function(t,e,r){e.set(this.interpolationFactor(r.zoom))},Za.prototype.getBinding=function(t,e){return new Ba(t,e)};var Ja=function(t,e,r,n,a,i,o){this.expression=t,this.names=e,this.type=r,this.uniformNames=this.names.map(function(t){return\"u_\"+t+\"_t\"}),this.useIntegerZoom=n,this.zoom=a,this.maxValue=-1/0,this.layerId=o,this.paintVertexAttributes=e.map(function(t){return{name:\"a_\"+t,type:\"Uint16\",components:4,offset:0}}),this.zoomInPaintVertexArray=new i,this.zoomOutPaintVertexArray=new i};Ja.prototype.defines=function(){return[]},Ja.prototype.setConstantPatternPositions=function(){},Ja.prototype.populatePaintArray=function(t,e,r){var n=this.zoomInPaintVertexArray,a=this.zoomOutPaintVertexArray,i=this.layerId,o=n.length;if(n.reserve(t),a.reserve(t),r&&e.patterns&&e.patterns[i]){var s=e.patterns[i],l=s.min,c=s.mid,u=s.max,h=r[l],f=r[c],p=r[u];if(!h||!f||!p)return;for(var d=o;d<t;d++)n.emplaceBack(f.tl[0],f.tl[1],f.br[0],f.br[1],h.tl[0],h.tl[1],h.br[0],h.br[1]),a.emplaceBack(f.tl[0],f.tl[1],f.br[0],f.br[1],p.tl[0],p.tl[1],p.br[0],p.br[1])}},Ja.prototype.updatePaintArray=function(t,e,r,n,a){var i=this.zoomInPaintVertexArray,o=this.zoomOutPaintVertexArray,s=this.layerId;if(a&&r.patterns&&r.patterns[s]){var l=r.patterns[s],c=l.min,u=l.mid,h=l.max,f=a[c],p=a[u],d=a[h];if(!f||!p||!d)return;for(var g=t;g<e;g++)i.emplace(g,p.tl[0],p.tl[1],p.br[0],p.br[1],f.tl[0],f.tl[1],f.br[0],f.br[1]),o.emplace(g,p.tl[0],p.tl[1],p.br[0],p.br[1],d.tl[0],d.tl[1],d.br[0],d.br[1])}},Ja.prototype.upload=function(t){this.zoomInPaintVertexArray&&this.zoomInPaintVertexArray.arrayBuffer&&this.zoomOutPaintVertexArray&&this.zoomOutPaintVertexArray.arrayBuffer&&(this.zoomInPaintVertexBuffer=t.createVertexBuffer(this.zoomInPaintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent),this.zoomOutPaintVertexBuffer=t.createVertexBuffer(this.zoomOutPaintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent))},Ja.prototype.destroy=function(){this.zoomOutPaintVertexBuffer&&this.zoomOutPaintVertexBuffer.destroy(),this.zoomInPaintVertexBuffer&&this.zoomInPaintVertexBuffer.destroy()},Ja.prototype.setUniforms=function(t,e){e.set(0)},Ja.prototype.getBinding=function(t,e){return new Ba(t,e)};var Ka=function(){this.binders={},this.cacheKey=\"\",this._buffers=[],this._featureMap=new Ia,this._bufferOffset=0};Ka.createDynamic=function(t,e,r){var n=new Ka,a=[];for(var i in t.paint._values)if(r(i)){var o=t.paint.get(i);if(o instanceof Bn&&ur(o.property.specification)){var s=$a(i,t.type),l=o.property.specification.type,c=o.property.useIntegerZoom;if(\"cross-faded\"===o.property.specification[\"property-type\"]||\"cross-faded-data-driven\"===o.property.specification[\"property-type\"])if(\"constant\"===o.value.kind)n.binders[i]=new Wa(o.value.value,s,l),a.push(\"/u_\"+i);else{var u=ti(i,l,\"source\");n.binders[i]=new Ja(o.value,s,l,c,e,u,t.id),a.push(\"/a_\"+i)}else if(\"constant\"===o.value.kind)n.binders[i]=new Ya(o.value.value,s,l),a.push(\"/u_\"+i);else if(\"source\"===o.value.kind){var h=ti(i,l,\"source\");n.binders[i]=new Xa(o.value,s,l,h),a.push(\"/a_\"+i)}else{var f=ti(i,l,\"composite\");n.binders[i]=new Za(o.value,s,l,c,e,f),a.push(\"/z_\"+i)}}}return n.cacheKey=a.sort().join(\"\"),n},Ka.prototype.populatePaintArrays=function(t,e,r,n,a){for(var i in this.binders)this.binders[i].populatePaintArray(t,e,n,a);void 0!==e.id&&this._featureMap.add(+e.id,r,this._bufferOffset,t),this._bufferOffset=t},Ka.prototype.setConstantPatternPositions=function(t,e){for(var r in this.binders)this.binders[r].setConstantPatternPositions(t,e)},Ka.prototype.updatePaintArrays=function(t,e,r,n){var a=!1;for(var i in t)for(var o=0,s=this._featureMap.getPositions(+i);o<s.length;o+=1){var l=s[o],c=e.feature(l.index);for(var u in this.binders){var h=this.binders[u];if(!(h instanceof Ya||h instanceof Wa)&&!0===h.expression.isStateDependent){var f=r.paint.get(u);h.expression=f.value,h.updatePaintArray(l.start,l.end,c,t[i],n),a=!0}}}return a},Ka.prototype.defines=function(){var t=[];for(var e in this.binders)t.push.apply(t,this.binders[e].defines());return t},Ka.prototype.getPaintVertexBuffers=function(){return this._buffers},Ka.prototype.getUniforms=function(t,e){var r=[];for(var n in this.binders)for(var a=this.binders[n],i=0,o=a.uniformNames;i<o.length;i+=1){var s=o[i];if(e[s]){var l=a.getBinding(t,e[s]);r.push({name:s,property:n,binding:l})}}return r},Ka.prototype.setUniforms=function(t,e,r,n){for(var a=0,i=e;a<i.length;a+=1){var o=i[a],s=o.name,l=o.property,c=o.binding;this.binders[l].setUniforms(t,c,n,r.get(l),s)}},Ka.prototype.updatePatternPaintBuffers=function(t){var e=[];for(var r in this.binders){var n=this.binders[r];if(n instanceof Ja){var a=2===t.fromScale?n.zoomInPaintVertexBuffer:n.zoomOutPaintVertexBuffer;a&&e.push(a)}else(n instanceof Xa||n instanceof Za)&&n.paintVertexBuffer&&e.push(n.paintVertexBuffer)}this._buffers=e},Ka.prototype.upload=function(t){for(var e in this.binders)this.binders[e].upload(t);var r=[];for(var n in this.binders){var a=this.binders[n];(a instanceof Xa||a instanceof Za)&&a.paintVertexBuffer&&r.push(a.paintVertexBuffer)}this._buffers=r},Ka.prototype.destroy=function(){for(var t in this.binders)this.binders[t].destroy()};var Qa=function(t,e,r,n){void 0===n&&(n=function(){return!0}),this.programConfigurations={};for(var a=0,i=e;a<i.length;a+=1){var o=i[a];this.programConfigurations[o.id]=Ka.createDynamic(o,r,n),this.programConfigurations[o.id].layoutAttributes=t}this.needsUpload=!1};function $a(t,e){return{\"text-opacity\":[\"opacity\"],\"icon-opacity\":[\"opacity\"],\"text-color\":[\"fill_color\"],\"icon-color\":[\"fill_color\"],\"text-halo-color\":[\"halo_color\"],\"icon-halo-color\":[\"halo_color\"],\"text-halo-blur\":[\"halo_blur\"],\"icon-halo-blur\":[\"halo_blur\"],\"text-halo-width\":[\"halo_width\"],\"icon-halo-width\":[\"halo_width\"],\"line-gap-width\":[\"gapwidth\"],\"line-pattern\":[\"pattern_to\",\"pattern_from\"],\"fill-pattern\":[\"pattern_to\",\"pattern_from\"],\"fill-extrusion-pattern\":[\"pattern_to\",\"pattern_from\"]}[t]||[t.replace(e+\"-\",\"\").replace(/-/g,\"_\")]}function ti(t,e,r){var n={color:{source:ma,composite:ya},number:{source:ha,composite:ma}},a=function(t){return{\"line-pattern\":{source:ra,composite:ra},\"fill-pattern\":{source:ra,composite:ra},\"fill-extrusion-pattern\":{source:ra,composite:ra}}[t]}(t);return a&&a[r]||n[e][r]}Qa.prototype.populatePaintArrays=function(t,e,r,n,a){for(var i in this.programConfigurations)this.programConfigurations[i].populatePaintArrays(t,e,r,n,a);this.needsUpload=!0},Qa.prototype.updatePaintArrays=function(t,e,r,n){for(var a=0,i=r;a<i.length;a+=1){var o=i[a];this.needsUpload=this.programConfigurations[o.id].updatePaintArrays(t,e,o,n)||this.needsUpload}},Qa.prototype.get=function(t){return this.programConfigurations[t]},Qa.prototype.upload=function(t){if(this.needsUpload){for(var e in this.programConfigurations)this.programConfigurations[e].upload(t);this.needsUpload=!1}},Qa.prototype.destroy=function(){for(var t in this.programConfigurations)this.programConfigurations[t].destroy()},dn(\"ConstantBinder\",Ya),dn(\"CrossFadedConstantBinder\",Wa),dn(\"SourceExpressionBinder\",Xa),dn(\"CrossFadedCompositeBinder\",Ja),dn(\"CompositeExpressionBinder\",Za),dn(\"ProgramConfiguration\",Ka,{omit:[\"_buffers\"]}),dn(\"ProgramConfigurationSet\",Qa);var ei=8192,ri=(15,{min:-1*Math.pow(2,14),max:Math.pow(2,14)-1});function ni(t){for(var e=ei/t.extent,r=t.loadGeometry(),n=0;n<r.length;n++)for(var a=r[n],i=0;i<a.length;i++){var o=a[i];o.x=Math.round(o.x*e),o.y=Math.round(o.y*e),(o.x<ri.min||o.x>ri.max||o.y<ri.min||o.y>ri.max)&&(w(\"Geometry exceeds allowed extent, reduce your vector tile buffer size\"),o.x=c(o.x,ri.min,ri.max),o.y=c(o.y,ri.min,ri.max))}return r}function ai(t,e,r,n,a){t.emplaceBack(2*e+(n+1)/2,2*r+(a+1)/2)}var ii=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map(function(t){return t.id}),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new Qn,this.indexArray=new da,this.segments=new Oa,this.programConfigurations=new Qa(Pa,t.layers,t.zoom),this.stateDependentLayerIds=this.layers.filter(function(t){return t.isStateDependent()}).map(function(t){return t.id})};function oi(t,e){for(var r=0;r<t.length;r++)if(gi(e,t[r]))return!0;for(var n=0;n<e.length;n++)if(gi(t,e[n]))return!0;return!!ui(t,e)}function si(t,e,r){return!!gi(t,e)||!!fi(e,t,r)}function li(t,e){if(1===t.length)return di(e,t[0]);for(var r=0;r<e.length;r++)for(var n=e[r],a=0;a<n.length;a++)if(gi(t,n[a]))return!0;for(var i=0;i<t.length;i++)if(di(e,t[i]))return!0;for(var o=0;o<e.length;o++)if(ui(t,e[o]))return!0;return!1}function ci(t,e,r){if(t.length>1){if(ui(t,e))return!0;for(var n=0;n<e.length;n++)if(fi(e[n],t,r))return!0}for(var a=0;a<t.length;a++)if(fi(t[a],e,r))return!0;return!1}function ui(t,e){if(0===t.length||0===e.length)return!1;for(var r=0;r<t.length-1;r++)for(var n=t[r],a=t[r+1],i=0;i<e.length-1;i++)if(hi(n,a,e[i],e[i+1]))return!0;return!1}function hi(t,e,r,n){return k(t,r,n)!==k(e,r,n)&&k(t,e,r)!==k(t,e,n)}function fi(t,e,r){var n=r*r;if(1===e.length)return t.distSqr(e[0])<n;for(var a=1;a<e.length;a++)if(pi(t,e[a-1],e[a])<n)return!0;return!1}function pi(t,e,r){var n=e.distSqr(r);if(0===n)return t.distSqr(e);var a=((t.x-e.x)*(r.x-e.x)+(t.y-e.y)*(r.y-e.y))/n;return a<0?t.distSqr(e):a>1?t.distSqr(r):t.distSqr(r.sub(e)._mult(a)._add(e))}function di(t,e){for(var r,n,a,i=!1,o=0;o<t.length;o++)for(var s=0,l=(r=t[o]).length-1;s<r.length;l=s++)n=r[s],a=r[l],n.y>e.y!=a.y>e.y&&e.x<(a.x-n.x)*(e.y-n.y)/(a.y-n.y)+n.x&&(i=!i);return i}function gi(t,e){for(var r=!1,n=0,a=t.length-1;n<t.length;a=n++){var i=t[n],o=t[a];i.y>e.y!=o.y>e.y&&e.x<(o.x-i.x)*(e.y-i.y)/(o.y-i.y)+i.x&&(r=!r)}return r}function vi(t,e,r){var n=r[0],a=r[2];if(t.x<n.x&&e.x<n.x||t.x>a.x&&e.x>a.x||t.y<n.y&&e.y<n.y||t.y>a.y&&e.y>a.y)return!1;var i=k(t,e,r[0]);return i!==k(t,e,r[1])||i!==k(t,e,r[2])||i!==k(t,e,r[3])}function mi(t,e,r){var n=e.paint.get(t).value;return\"constant\"===n.kind?n.value:r.programConfigurations.get(e.id).binders[t].maxValue}function yi(t){return Math.sqrt(t[0]*t[0]+t[1]*t[1])}function xi(t,e,r,n,i){if(!e[0]&&!e[1])return t;var o=a.convert(e)._mult(i);\"viewport\"===r&&o._rotate(-n);for(var s=[],l=0;l<t.length;l++){var c=t[l];s.push(c.sub(o))}return s}ii.prototype.populate=function(t,e){var r=this.layers[0],n=[],a=null;\"circle\"===r.type&&(a=r.layout.get(\"circle-sort-key\"));for(var i=0,o=t;i<o.length;i+=1){var s=o[i],l=s.feature,c=s.index,u=s.sourceLayerIndex;if(this.layers[0]._featureFilter(new Pn(this.zoom),l)){var h=ni(l),f=a?a.evaluate(l,{}):void 0,p={id:l.id,properties:l.properties,type:l.type,sourceLayerIndex:u,index:c,geometry:h,patterns:{},sortKey:f};n.push(p)}}a&&n.sort(function(t,e){return t.sortKey-e.sortKey});for(var d=0,g=n;d<g.length;d+=1){var v=g[d],m=v,y=m.geometry,x=m.index,b=m.sourceLayerIndex,_=t[x].feature;this.addFeature(v,y,x),e.featureIndex.insert(_,y,x,b,this.index)}},ii.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},ii.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},ii.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},ii.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Pa),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},ii.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},ii.prototype.addFeature=function(t,e,r){for(var n=0,a=e;n<a.length;n+=1)for(var i=0,o=a[n];i<o.length;i+=1){var s=o[i],l=s.x,c=s.y;if(!(l<0||l>=ei||c<0||c>=ei)){var u=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray,t.sortKey),h=u.vertexLength;ai(this.layoutVertexArray,l,c,-1,-1),ai(this.layoutVertexArray,l,c,1,-1),ai(this.layoutVertexArray,l,c,1,1),ai(this.layoutVertexArray,l,c,-1,1),this.indexArray.emplaceBack(h,h+1,h+2),this.indexArray.emplaceBack(h,h+3,h+2),u.vertexLength+=4,u.primitiveLength+=2}}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,{})},dn(\"CircleBucket\",ii,{omit:[\"layers\"]});var bi,_i=new Gn({\"circle-sort-key\":new Vn(Tt.layout_circle[\"circle-sort-key\"])}),wi={paint:new Gn({\"circle-radius\":new Vn(Tt.paint_circle[\"circle-radius\"]),\"circle-color\":new Vn(Tt.paint_circle[\"circle-color\"]),\"circle-blur\":new Vn(Tt.paint_circle[\"circle-blur\"]),\"circle-opacity\":new Vn(Tt.paint_circle[\"circle-opacity\"]),\"circle-translate\":new jn(Tt.paint_circle[\"circle-translate\"]),\"circle-translate-anchor\":new jn(Tt.paint_circle[\"circle-translate-anchor\"]),\"circle-pitch-scale\":new jn(Tt.paint_circle[\"circle-pitch-scale\"]),\"circle-pitch-alignment\":new jn(Tt.paint_circle[\"circle-pitch-alignment\"]),\"circle-stroke-width\":new Vn(Tt.paint_circle[\"circle-stroke-width\"]),\"circle-stroke-color\":new Vn(Tt.paint_circle[\"circle-stroke-color\"]),\"circle-stroke-opacity\":new Vn(Tt.paint_circle[\"circle-stroke-opacity\"])}),layout:_i},ki=\"undefined\"!=typeof Float32Array?Float32Array:Array;function Ti(t,e,r){var n=e[0],a=e[1],i=e[2],o=e[3];return t[0]=r[0]*n+r[4]*a+r[8]*i+r[12]*o,t[1]=r[1]*n+r[5]*a+r[9]*i+r[13]*o,t[2]=r[2]*n+r[6]*a+r[10]*i+r[14]*o,t[3]=r[3]*n+r[7]*a+r[11]*i+r[15]*o,t}Math.hypot||(Math.hypot=function(){for(var t=arguments,e=0,r=arguments.length;r--;)e+=t[r]*t[r];return Math.sqrt(e)}),bi=new ki(3),ki!=Float32Array&&(bi[0]=0,bi[1]=0,bi[2]=0),function(){var t=new ki(4);ki!=Float32Array&&(t[0]=0,t[1]=0,t[2]=0,t[3]=0)}();var Mi=function(t){function e(e){t.call(this,e,wi)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.createBucket=function(t){return new ii(t)},e.prototype.queryRadius=function(t){var e=t;return mi(\"circle-radius\",this,e)+mi(\"circle-stroke-width\",this,e)+yi(this.paint.get(\"circle-translate\"))},e.prototype.queryIntersectsFeature=function(t,e,r,n,a,i,o,s){for(var l=xi(t,this.paint.get(\"circle-translate\"),this.paint.get(\"circle-translate-anchor\"),i.angle,o),c=this.paint.get(\"circle-radius\").evaluate(e,r)+this.paint.get(\"circle-stroke-width\").evaluate(e,r),u=\"map\"===this.paint.get(\"circle-pitch-alignment\"),h=u?l:function(t,e){return l.map(function(t){return Ai(t,e)})}(0,s),f=u?c*o:c,p=0,d=n;p<d.length;p+=1)for(var g=0,v=d[p];g<v.length;g+=1){var m=v[g],y=u?m:Ai(m,s),x=f,b=Ti([],[m.x,m.y,0,1],s);if(\"viewport\"===this.paint.get(\"circle-pitch-scale\")&&\"map\"===this.paint.get(\"circle-pitch-alignment\")?x*=b[3]/i.cameraToCenterDistance:\"map\"===this.paint.get(\"circle-pitch-scale\")&&\"viewport\"===this.paint.get(\"circle-pitch-alignment\")&&(x*=i.cameraToCenterDistance/b[3]),si(h,y,x))return!0}return!1},e}(Yn);function Ai(t,e){var r=Ti([],[t.x,t.y,0,1],e);return new a(r[0]/r[3],r[1]/r[3])}var Si=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(ii);function Ei(t,e,r,n){var a=e.width,i=e.height;if(n){if(n instanceof Uint8ClampedArray)n=new Uint8Array(n.buffer);else if(n.length!==a*i*r)throw new RangeError(\"mismatched image size\")}else n=new Uint8Array(a*i*r);return t.width=a,t.height=i,t.data=n,t}function Li(t,e,r){var n=e.width,a=e.height;if(n!==t.width||a!==t.height){var i=Ei({},{width:n,height:a},r);Ci(t,i,{x:0,y:0},{x:0,y:0},{width:Math.min(t.width,n),height:Math.min(t.height,a)},r),t.width=n,t.height=a,t.data=i.data}}function Ci(t,e,r,n,a,i){if(0===a.width||0===a.height)return e;if(a.width>t.width||a.height>t.height||r.x>t.width-a.width||r.y>t.height-a.height)throw new RangeError(\"out of range source coordinates for image copy\");if(a.width>e.width||a.height>e.height||n.x>e.width-a.width||n.y>e.height-a.height)throw new RangeError(\"out of range destination coordinates for image copy\");for(var o=t.data,s=e.data,l=0;l<a.height;l++)for(var c=((r.y+l)*t.width+r.x)*i,u=((n.y+l)*e.width+n.x)*i,h=0;h<a.width*i;h++)s[u+h]=o[c+h];return e}dn(\"HeatmapBucket\",Si,{omit:[\"layers\"]});var Pi=function(t,e){Ei(this,t,1,e)};Pi.prototype.resize=function(t){Li(this,t,1)},Pi.prototype.clone=function(){return new Pi({width:this.width,height:this.height},new Uint8Array(this.data))},Pi.copy=function(t,e,r,n,a){Ci(t,e,r,n,a,1)};var Oi=function(t,e){Ei(this,t,4,e)};Oi.prototype.resize=function(t){Li(this,t,4)},Oi.prototype.replace=function(t,e){e?this.data.set(t):t instanceof Uint8ClampedArray?this.data=new Uint8Array(t.buffer):this.data=t},Oi.prototype.clone=function(){return new Oi({width:this.width,height:this.height},new Uint8Array(this.data))},Oi.copy=function(t,e,r,n,a){Ci(t,e,r,n,a,4)},dn(\"AlphaImage\",Pi),dn(\"RGBAImage\",Oi);var zi={paint:new Gn({\"heatmap-radius\":new Vn(Tt.paint_heatmap[\"heatmap-radius\"]),\"heatmap-weight\":new Vn(Tt.paint_heatmap[\"heatmap-weight\"]),\"heatmap-intensity\":new jn(Tt.paint_heatmap[\"heatmap-intensity\"]),\"heatmap-color\":new Hn(Tt.paint_heatmap[\"heatmap-color\"]),\"heatmap-opacity\":new jn(Tt.paint_heatmap[\"heatmap-opacity\"])})};function Ii(t,e){for(var r=new Uint8Array(1024),n={},a=0,i=0;a<256;a++,i+=4){n[e]=a/255;var o=t.evaluate(n);r[i+0]=Math.floor(255*o.r/o.a),r[i+1]=Math.floor(255*o.g/o.a),r[i+2]=Math.floor(255*o.b/o.a),r[i+3]=Math.floor(255*o.a)}return new Oi({width:256,height:1},r)}var Di=function(t){function e(e){t.call(this,e,zi),this._updateColorRamp()}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.createBucket=function(t){return new Si(t)},e.prototype._handleSpecialPaintPropertyUpdate=function(t){\"heatmap-color\"===t&&this._updateColorRamp()},e.prototype._updateColorRamp=function(){var t=this._transitionablePaint._values[\"heatmap-color\"].value.expression;this.colorRamp=Ii(t,\"heatmapDensity\"),this.colorRampTexture=null},e.prototype.resize=function(){this.heatmapFbo&&(this.heatmapFbo.destroy(),this.heatmapFbo=null)},e.prototype.queryRadius=function(){return 0},e.prototype.queryIntersectsFeature=function(){return!1},e.prototype.hasOffscreenPass=function(){return 0!==this.paint.get(\"heatmap-opacity\")&&\"none\"!==this.visibility},e}(Yn),Ri={paint:new Gn({\"hillshade-illumination-direction\":new jn(Tt.paint_hillshade[\"hillshade-illumination-direction\"]),\"hillshade-illumination-anchor\":new jn(Tt.paint_hillshade[\"hillshade-illumination-anchor\"]),\"hillshade-exaggeration\":new jn(Tt.paint_hillshade[\"hillshade-exaggeration\"]),\"hillshade-shadow-color\":new jn(Tt.paint_hillshade[\"hillshade-shadow-color\"]),\"hillshade-highlight-color\":new jn(Tt.paint_hillshade[\"hillshade-highlight-color\"]),\"hillshade-accent-color\":new jn(Tt.paint_hillshade[\"hillshade-accent-color\"])})},Fi=function(t){function e(e){t.call(this,e,Ri)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.hasOffscreenPass=function(){return 0!==this.paint.get(\"hillshade-exaggeration\")&&\"none\"!==this.visibility},e}(Yn),Bi=Jn([{name:\"a_pos\",components:2,type:\"Int16\"}],4).members,Ni=Vi,ji=Vi;function Vi(t,e,r){r=r||2;var n,a,i,o,s,l,c,u=e&&e.length,h=u?e[0]*r:t.length,f=Ui(t,0,h,r,!0),p=[];if(!f||f.next===f.prev)return p;if(u&&(f=function(t,e,r,n){var a,i,o,s=[];for(a=0,i=e.length;a<i;a++)(o=Ui(t,e[a]*n,a<i-1?e[a+1]*n:t.length,n,!1))===o.next&&(o.steiner=!0),s.push($i(o));for(s.sort(Zi),a=0;a<s.length;a++)Ji(s[a],r),r=qi(r,r.next);return r}(t,e,f,r)),t.length>80*r){n=i=t[0],a=o=t[1];for(var d=r;d<h;d+=r)(s=t[d])<n&&(n=s),(l=t[d+1])<a&&(a=l),s>i&&(i=s),l>o&&(o=l);c=0!==(c=Math.max(i-n,o-a))?1/c:0}return Hi(f,p,r,n,a,c),p}function Ui(t,e,r,n,a){var i,o;if(a===fo(t,e,r,n)>0)for(i=e;i<r;i+=n)o=co(i,t[i],t[i+1],o);else for(i=r-n;i>=e;i-=n)o=co(i,t[i],t[i+1],o);return o&&no(o,o.next)&&(uo(o),o=o.next),o}function qi(t,e){if(!t)return t;e||(e=t);var r,n=t;do{if(r=!1,n.steiner||!no(n,n.next)&&0!==ro(n.prev,n,n.next))n=n.next;else{if(uo(n),(n=e=n.prev)===n.next)break;r=!0}}while(r||n!==e);return e}function Hi(t,e,r,n,a,i,o){if(t){!o&&i&&function(t,e,r,n){var a=t;do{null===a.z&&(a.z=Qi(a.x,a.y,e,r,n)),a.prevZ=a.prev,a.nextZ=a.next,a=a.next}while(a!==t);a.prevZ.nextZ=null,a.prevZ=null,function(t){var e,r,n,a,i,o,s,l,c=1;do{for(r=t,t=null,i=null,o=0;r;){for(o++,n=r,s=0,e=0;e<c&&(s++,n=n.nextZ);e++);for(l=c;s>0||l>0&&n;)0!==s&&(0===l||!n||r.z<=n.z)?(a=r,r=r.nextZ,s--):(a=n,n=n.nextZ,l--),i?i.nextZ=a:t=a,a.prevZ=i,i=a;r=n}i.nextZ=null,c*=2}while(o>1)}(a)}(t,n,a,i);for(var s,l,c=t;t.prev!==t.next;)if(s=t.prev,l=t.next,i?Yi(t,n,a,i):Gi(t))e.push(s.i/r),e.push(t.i/r),e.push(l.i/r),uo(t),t=l.next,c=l.next;else if((t=l)===c){o?1===o?Hi(t=Wi(qi(t),e,r),e,r,n,a,i,2):2===o&&Xi(t,e,r,n,a,i):Hi(qi(t),e,r,n,a,i,1);break}}}function Gi(t){var e=t.prev,r=t,n=t.next;if(ro(e,r,n)>=0)return!1;for(var a=t.next.next;a!==t.prev;){if(to(e.x,e.y,r.x,r.y,n.x,n.y,a.x,a.y)&&ro(a.prev,a,a.next)>=0)return!1;a=a.next}return!0}function Yi(t,e,r,n){var a=t.prev,i=t,o=t.next;if(ro(a,i,o)>=0)return!1;for(var s=a.x<i.x?a.x<o.x?a.x:o.x:i.x<o.x?i.x:o.x,l=a.y<i.y?a.y<o.y?a.y:o.y:i.y<o.y?i.y:o.y,c=a.x>i.x?a.x>o.x?a.x:o.x:i.x>o.x?i.x:o.x,u=a.y>i.y?a.y>o.y?a.y:o.y:i.y>o.y?i.y:o.y,h=Qi(s,l,e,r,n),f=Qi(c,u,e,r,n),p=t.prevZ,d=t.nextZ;p&&p.z>=h&&d&&d.z<=f;){if(p!==t.prev&&p!==t.next&&to(a.x,a.y,i.x,i.y,o.x,o.y,p.x,p.y)&&ro(p.prev,p,p.next)>=0)return!1;if(p=p.prevZ,d!==t.prev&&d!==t.next&&to(a.x,a.y,i.x,i.y,o.x,o.y,d.x,d.y)&&ro(d.prev,d,d.next)>=0)return!1;d=d.nextZ}for(;p&&p.z>=h;){if(p!==t.prev&&p!==t.next&&to(a.x,a.y,i.x,i.y,o.x,o.y,p.x,p.y)&&ro(p.prev,p,p.next)>=0)return!1;p=p.prevZ}for(;d&&d.z<=f;){if(d!==t.prev&&d!==t.next&&to(a.x,a.y,i.x,i.y,o.x,o.y,d.x,d.y)&&ro(d.prev,d,d.next)>=0)return!1;d=d.nextZ}return!0}function Wi(t,e,r){var n=t;do{var a=n.prev,i=n.next.next;!no(a,i)&&ao(a,n,n.next,i)&&so(a,i)&&so(i,a)&&(e.push(a.i/r),e.push(n.i/r),e.push(i.i/r),uo(n),uo(n.next),n=t=i),n=n.next}while(n!==t);return qi(n)}function Xi(t,e,r,n,a,i){var o=t;do{for(var s=o.next.next;s!==o.prev;){if(o.i!==s.i&&eo(o,s)){var l=lo(o,s);return o=qi(o,o.next),l=qi(l,l.next),Hi(o,e,r,n,a,i),void Hi(l,e,r,n,a,i)}s=s.next}o=o.next}while(o!==t)}function Zi(t,e){return t.x-e.x}function Ji(t,e){if(e=function(t,e){var r,n=e,a=t.x,i=t.y,o=-1/0;do{if(i<=n.y&&i>=n.next.y&&n.next.y!==n.y){var s=n.x+(i-n.y)*(n.next.x-n.x)/(n.next.y-n.y);if(s<=a&&s>o){if(o=s,s===a){if(i===n.y)return n;if(i===n.next.y)return n.next}r=n.x<n.next.x?n:n.next}}n=n.next}while(n!==e);if(!r)return null;if(a===o)return r;var l,c=r,u=r.x,h=r.y,f=1/0;n=r;do{a>=n.x&&n.x>=u&&a!==n.x&&to(i<h?a:o,i,u,h,i<h?o:a,i,n.x,n.y)&&(l=Math.abs(i-n.y)/(a-n.x),so(n,t)&&(l<f||l===f&&(n.x>r.x||n.x===r.x&&Ki(r,n)))&&(r=n,f=l)),n=n.next}while(n!==c);return r}(t,e)){var r=lo(e,t);qi(r,r.next)}}function Ki(t,e){return ro(t.prev,t,e.prev)<0&&ro(e.next,t,t.next)<0}function Qi(t,e,r,n,a){return(t=1431655765&((t=858993459&((t=252645135&((t=16711935&((t=32767*(t-r)*a)|t<<8))|t<<4))|t<<2))|t<<1))|(e=1431655765&((e=858993459&((e=252645135&((e=16711935&((e=32767*(e-n)*a)|e<<8))|e<<4))|e<<2))|e<<1))<<1}function $i(t){var e=t,r=t;do{(e.x<r.x||e.x===r.x&&e.y<r.y)&&(r=e),e=e.next}while(e!==t);return r}function to(t,e,r,n,a,i,o,s){return(a-o)*(e-s)-(t-o)*(i-s)>=0&&(t-o)*(n-s)-(r-o)*(e-s)>=0&&(r-o)*(i-s)-(a-o)*(n-s)>=0}function eo(t,e){return t.next.i!==e.i&&t.prev.i!==e.i&&!function(t,e){var r=t;do{if(r.i!==t.i&&r.next.i!==t.i&&r.i!==e.i&&r.next.i!==e.i&&ao(r,r.next,t,e))return!0;r=r.next}while(r!==t);return!1}(t,e)&&(so(t,e)&&so(e,t)&&function(t,e){var r=t,n=!1,a=(t.x+e.x)/2,i=(t.y+e.y)/2;do{r.y>i!=r.next.y>i&&r.next.y!==r.y&&a<(r.next.x-r.x)*(i-r.y)/(r.next.y-r.y)+r.x&&(n=!n),r=r.next}while(r!==t);return n}(t,e)&&(ro(t.prev,t,e.prev)||ro(t,e.prev,e))||no(t,e)&&ro(t.prev,t,t.next)>0&&ro(e.prev,e,e.next)>0)}function ro(t,e,r){return(e.y-t.y)*(r.x-e.x)-(e.x-t.x)*(r.y-e.y)}function no(t,e){return t.x===e.x&&t.y===e.y}function ao(t,e,r,n){var a=oo(ro(t,e,r)),i=oo(ro(t,e,n)),o=oo(ro(r,n,t)),s=oo(ro(r,n,e));return a!==i&&o!==s||!(0!==a||!io(t,r,e))||!(0!==i||!io(t,n,e))||!(0!==o||!io(r,t,n))||!(0!==s||!io(r,e,n))}function io(t,e,r){return e.x<=Math.max(t.x,r.x)&&e.x>=Math.min(t.x,r.x)&&e.y<=Math.max(t.y,r.y)&&e.y>=Math.min(t.y,r.y)}function oo(t){return t>0?1:t<0?-1:0}function so(t,e){return ro(t.prev,t,t.next)<0?ro(t,e,t.next)>=0&&ro(t,t.prev,e)>=0:ro(t,e,t.prev)<0||ro(t,t.next,e)<0}function lo(t,e){var r=new ho(t.i,t.x,t.y),n=new ho(e.i,e.x,e.y),a=t.next,i=e.prev;return t.next=e,e.prev=t,r.next=a,a.prev=r,n.next=r,r.prev=n,i.next=n,n.prev=i,n}function co(t,e,r,n){var a=new ho(t,e,r);return n?(a.next=n.next,a.prev=n,n.next.prev=a,n.next=a):(a.prev=a,a.next=a),a}function uo(t){t.next.prev=t.prev,t.prev.next=t.next,t.prevZ&&(t.prevZ.nextZ=t.nextZ),t.nextZ&&(t.nextZ.prevZ=t.prevZ)}function ho(t,e,r){this.i=t,this.x=e,this.y=r,this.prev=null,this.next=null,this.z=null,this.prevZ=null,this.nextZ=null,this.steiner=!1}function fo(t,e,r,n){for(var a=0,i=e,o=r-n;i<r;i+=n)a+=(t[o]-t[i])*(t[i+1]+t[o+1]),o=i;return a}function po(t,e,r,n,a){!function t(e,r,n,a,i){for(;a>n;){if(a-n>600){var o=a-n+1,s=r-n+1,l=Math.log(o),c=.5*Math.exp(2*l/3),u=.5*Math.sqrt(l*c*(o-c)/o)*(s-o/2<0?-1:1);t(e,r,Math.max(n,Math.floor(r-s*c/o+u)),Math.min(a,Math.floor(r+(o-s)*c/o+u)),i)}var h=e[r],f=n,p=a;for(go(e,n,r),i(e[a],h)>0&&go(e,n,a);f<p;){for(go(e,f,p),f++,p--;i(e[f],h)<0;)f++;for(;i(e[p],h)>0;)p--}0===i(e[n],h)?go(e,n,p):go(e,++p,a),p<=r&&(n=p+1),r<=p&&(a=p-1)}}(t,e,r||0,n||t.length-1,a||vo)}function go(t,e,r){var n=t[e];t[e]=t[r],t[r]=n}function vo(t,e){return t<e?-1:t>e?1:0}function mo(t,e){var r=t.length;if(r<=1)return[t];for(var n,a,i=[],o=0;o<r;o++){var s=T(t[o]);0!==s&&(t[o].area=Math.abs(s),void 0===a&&(a=s<0),a===s<0?(n&&i.push(n),n=[t[o]]):n.push(t[o]))}if(n&&i.push(n),e>1)for(var l=0;l<i.length;l++)i[l].length<=e||(po(i[l],e,1,i[l].length-1,yo),i[l]=i[l].slice(0,e));return i}function yo(t,e){return e.area-t.area}function xo(t,e,r){for(var n=r.patternDependencies,a=!1,i=0,o=e;i<o.length;i+=1){var s=o[i].paint.get(t+\"-pattern\");s.isConstant()||(a=!0);var l=s.constantOr(null);l&&(a=!0,n[l.to]=!0,n[l.from]=!0)}return a}function bo(t,e,r,n,a){for(var i=a.patternDependencies,o=0,s=e;o<s.length;o+=1){var l=s[o],c=l.paint.get(t+\"-pattern\").value;if(\"constant\"!==c.kind){var u=c.evaluate({zoom:n-1},r,{}),h=c.evaluate({zoom:n},r,{}),f=c.evaluate({zoom:n+1},r,{});i[u]=!0,i[h]=!0,i[f]=!0,r.patterns[l.id]={min:u,mid:h,max:f}}}return r}Vi.deviation=function(t,e,r,n){var a=e&&e.length,i=a?e[0]*r:t.length,o=Math.abs(fo(t,0,i,r));if(a)for(var s=0,l=e.length;s<l;s++){var c=e[s]*r,u=s<l-1?e[s+1]*r:t.length;o-=Math.abs(fo(t,c,u,r))}var h=0;for(s=0;s<n.length;s+=3){var f=n[s]*r,p=n[s+1]*r,d=n[s+2]*r;h+=Math.abs((t[f]-t[d])*(t[p+1]-t[f+1])-(t[f]-t[p])*(t[d+1]-t[f+1]))}return 0===o&&0===h?0:Math.abs((h-o)/o)},Vi.flatten=function(t){for(var e=t[0][0].length,r={vertices:[],holes:[],dimensions:e},n=0,a=0;a<t.length;a++){for(var i=0;i<t[a].length;i++)for(var o=0;o<e;o++)r.vertices.push(t[a][i][o]);a>0&&(n+=t[a-1].length,r.holes.push(n))}return r},Ni.default=ji;var _o=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map(function(t){return t.id}),this.index=t.index,this.hasPattern=!1,this.patternFeatures=[],this.layoutVertexArray=new Qn,this.indexArray=new da,this.indexArray2=new ga,this.programConfigurations=new Qa(Bi,t.layers,t.zoom),this.segments=new Oa,this.segments2=new Oa,this.stateDependentLayerIds=this.layers.filter(function(t){return t.isStateDependent()}).map(function(t){return t.id})};_o.prototype.populate=function(t,e){this.hasPattern=xo(\"fill\",this.layers,e);for(var r=this.layers[0].layout.get(\"fill-sort-key\"),n=[],a=0,i=t;a<i.length;a+=1){var o=i[a],s=o.feature,l=o.index,c=o.sourceLayerIndex;if(this.layers[0]._featureFilter(new Pn(this.zoom),s)){var u=ni(s),h=r?r.evaluate(s,{}):void 0,f={id:s.id,properties:s.properties,type:s.type,sourceLayerIndex:c,index:l,geometry:u,patterns:{},sortKey:h};n.push(f)}}r&&n.sort(function(t,e){return t.sortKey-e.sortKey});for(var p=0,d=n;p<d.length;p+=1){var g=d[p],v=g,m=v.geometry,y=v.index,x=v.sourceLayerIndex;if(this.hasPattern){var b=bo(\"fill\",this.layers,g,this.zoom,e);this.patternFeatures.push(b)}else this.addFeature(g,m,y,{});var _=t[y].feature;e.featureIndex.insert(_,m,y,x,this.index)}},_o.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},_o.prototype.addFeatures=function(t,e){for(var r=0,n=this.patternFeatures;r<n.length;r+=1){var a=n[r];this.addFeature(a,a.geometry,a.index,e)}},_o.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},_o.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},_o.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Bi),this.indexBuffer=t.createIndexBuffer(this.indexArray),this.indexBuffer2=t.createIndexBuffer(this.indexArray2)),this.programConfigurations.upload(t),this.uploaded=!0},_o.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.indexBuffer2.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.segments2.destroy())},_o.prototype.addFeature=function(t,e,r,n){for(var a=0,i=mo(e,500);a<i.length;a+=1){for(var o=i[a],s=0,l=0,c=o;l<c.length;l+=1)s+=c[l].length;for(var u=this.segments.prepareSegment(s,this.layoutVertexArray,this.indexArray),h=u.vertexLength,f=[],p=[],d=0,g=o;d<g.length;d+=1){var v=g[d];if(0!==v.length){v!==o[0]&&p.push(f.length/2);var m=this.segments2.prepareSegment(v.length,this.layoutVertexArray,this.indexArray2),y=m.vertexLength;this.layoutVertexArray.emplaceBack(v[0].x,v[0].y),this.indexArray2.emplaceBack(y+v.length-1,y),f.push(v[0].x),f.push(v[0].y);for(var x=1;x<v.length;x++)this.layoutVertexArray.emplaceBack(v[x].x,v[x].y),this.indexArray2.emplaceBack(y+x-1,y+x),f.push(v[x].x),f.push(v[x].y);m.vertexLength+=v.length,m.primitiveLength+=v.length}}for(var b=Ni(f,p),_=0;_<b.length;_+=3)this.indexArray.emplaceBack(h+b[_],h+b[_+1],h+b[_+2]);u.vertexLength+=s,u.primitiveLength+=b.length/3}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,n)},dn(\"FillBucket\",_o,{omit:[\"layers\",\"patternFeatures\"]});var wo=new Gn({\"fill-sort-key\":new Vn(Tt.layout_fill[\"fill-sort-key\"])}),ko={paint:new Gn({\"fill-antialias\":new jn(Tt.paint_fill[\"fill-antialias\"]),\"fill-opacity\":new Vn(Tt.paint_fill[\"fill-opacity\"]),\"fill-color\":new Vn(Tt.paint_fill[\"fill-color\"]),\"fill-outline-color\":new Vn(Tt.paint_fill[\"fill-outline-color\"]),\"fill-translate\":new jn(Tt.paint_fill[\"fill-translate\"]),\"fill-translate-anchor\":new jn(Tt.paint_fill[\"fill-translate-anchor\"]),\"fill-pattern\":new Un(Tt.paint_fill[\"fill-pattern\"])}),layout:wo},To=function(t){function e(e){t.call(this,e,ko)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.recalculate=function(e){t.prototype.recalculate.call(this,e);var r=this.paint._values[\"fill-outline-color\"];\"constant\"===r.value.kind&&void 0===r.value.value&&(this.paint._values[\"fill-outline-color\"]=this.paint._values[\"fill-color\"])},e.prototype.createBucket=function(t){return new _o(t)},e.prototype.queryRadius=function(){return yi(this.paint.get(\"fill-translate\"))},e.prototype.queryIntersectsFeature=function(t,e,r,n,a,i,o){return li(xi(t,this.paint.get(\"fill-translate\"),this.paint.get(\"fill-translate-anchor\"),i.angle,o),n)},e.prototype.isTileClipped=function(){return!0},e}(Yn),Mo=Jn([{name:\"a_pos\",components:2,type:\"Int16\"},{name:\"a_normal_ed\",components:4,type:\"Int16\"}],4).members,Ao=So;function So(t,e,r,n,a){this.properties={},this.extent=r,this.type=0,this._pbf=t,this._geometry=-1,this._keys=n,this._values=a,t.readFields(Eo,this,e)}function Eo(t,e,r){1==t?e.id=r.readVarint():2==t?function(t,e){for(var r=t.readVarint()+t.pos;t.pos<r;){var n=e._keys[t.readVarint()],a=e._values[t.readVarint()];e.properties[n]=a}}(r,e):3==t?e.type=r.readVarint():4==t&&(e._geometry=r.pos)}function Lo(t){for(var e,r,n=0,a=0,i=t.length,o=i-1;a<i;o=a++)e=t[a],n+=((r=t[o]).x-e.x)*(e.y+r.y);return n}So.types=[\"Unknown\",\"Point\",\"LineString\",\"Polygon\"],So.prototype.loadGeometry=function(){var t=this._pbf;t.pos=this._geometry;for(var e,r=t.readVarint()+t.pos,n=1,i=0,o=0,s=0,l=[];t.pos<r;){if(i<=0){var c=t.readVarint();n=7&c,i=c>>3}if(i--,1===n||2===n)o+=t.readSVarint(),s+=t.readSVarint(),1===n&&(e&&l.push(e),e=[]),e.push(new a(o,s));else{if(7!==n)throw new Error(\"unknown command \"+n);e&&e.push(e[0].clone())}}return e&&l.push(e),l},So.prototype.bbox=function(){var t=this._pbf;t.pos=this._geometry;for(var e=t.readVarint()+t.pos,r=1,n=0,a=0,i=0,o=1/0,s=-1/0,l=1/0,c=-1/0;t.pos<e;){if(n<=0){var u=t.readVarint();r=7&u,n=u>>3}if(n--,1===r||2===r)(a+=t.readSVarint())<o&&(o=a),a>s&&(s=a),(i+=t.readSVarint())<l&&(l=i),i>c&&(c=i);else if(7!==r)throw new Error(\"unknown command \"+r)}return[o,l,s,c]},So.prototype.toGeoJSON=function(t,e,r){var n,a,i=this.extent*Math.pow(2,r),o=this.extent*t,s=this.extent*e,l=this.loadGeometry(),c=So.types[this.type];function u(t){for(var e=0;e<t.length;e++){var r=t[e],n=180-360*(r.y+s)/i;t[e]=[360*(r.x+o)/i-180,360/Math.PI*Math.atan(Math.exp(n*Math.PI/180))-90]}}switch(this.type){case 1:var h=[];for(n=0;n<l.length;n++)h[n]=l[n][0];u(l=h);break;case 2:for(n=0;n<l.length;n++)u(l[n]);break;case 3:for(l=function(t){var e=t.length;if(e<=1)return[t];for(var r,n,a=[],i=0;i<e;i++){var o=Lo(t[i]);0!==o&&(void 0===n&&(n=o<0),n===o<0?(r&&a.push(r),r=[t[i]]):r.push(t[i]))}return r&&a.push(r),a}(l),n=0;n<l.length;n++)for(a=0;a<l[n].length;a++)u(l[n][a])}1===l.length?l=l[0]:c=\"Multi\"+c;var f={type:\"Feature\",geometry:{type:c,coordinates:l},properties:this.properties};return\"id\"in this&&(f.id=this.id),f};var Co=Po;function Po(t,e){this.version=1,this.name=null,this.extent=4096,this.length=0,this._pbf=t,this._keys=[],this._values=[],this._features=[],t.readFields(Oo,this,e),this.length=this._features.length}function Oo(t,e,r){15===t?e.version=r.readVarint():1===t?e.name=r.readString():5===t?e.extent=r.readVarint():2===t?e._features.push(r.pos):3===t?e._keys.push(r.readString()):4===t&&e._values.push(function(t){for(var e=null,r=t.readVarint()+t.pos;t.pos<r;){var n=t.readVarint()>>3;e=1===n?t.readString():2===n?t.readFloat():3===n?t.readDouble():4===n?t.readVarint64():5===n?t.readVarint():6===n?t.readSVarint():7===n?t.readBoolean():null}return e}(r))}function zo(t,e,r){if(3===t){var n=new Co(r,r.readVarint()+r.pos);n.length&&(e[n.name]=n)}}Po.prototype.feature=function(t){if(t<0||t>=this._features.length)throw new Error(\"feature index out of bounds\");this._pbf.pos=this._features[t];var e=this._pbf.readVarint()+this._pbf.pos;return new Ao(this._pbf,e,this.extent,this._keys,this._values)};var Io={VectorTile:function(t,e){this.layers=t.readFields(zo,{},e)},VectorTileFeature:Ao,VectorTileLayer:Co},Do=Io.VectorTileFeature.types,Ro=Math.pow(2,13);function Fo(t,e,r,n,a,i,o,s){t.emplaceBack(e,r,2*Math.floor(n*Ro)+o,a*Ro*2,i*Ro*2,Math.round(s))}var Bo=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map(function(t){return t.id}),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new ta,this.indexArray=new da,this.programConfigurations=new Qa(Mo,t.layers,t.zoom),this.segments=new Oa,this.stateDependentLayerIds=this.layers.filter(function(t){return t.isStateDependent()}).map(function(t){return t.id})};function No(t,e){return t.x===e.x&&(t.x<0||t.x>ei)||t.y===e.y&&(t.y<0||t.y>ei)}function jo(t){return t.every(function(t){return t.x<0})||t.every(function(t){return t.x>ei})||t.every(function(t){return t.y<0})||t.every(function(t){return t.y>ei})}Bo.prototype.populate=function(t,e){this.features=[],this.hasPattern=xo(\"fill-extrusion\",this.layers,e);for(var r=0,n=t;r<n.length;r+=1){var a=n[r],i=a.feature,o=a.index,s=a.sourceLayerIndex;if(this.layers[0]._featureFilter(new Pn(this.zoom),i)){var l=ni(i),c={sourceLayerIndex:s,index:o,geometry:l,properties:i.properties,type:i.type,patterns:{}};void 0!==i.id&&(c.id=i.id),this.hasPattern?this.features.push(bo(\"fill-extrusion\",this.layers,c,this.zoom,e)):this.addFeature(c,l,o,{}),e.featureIndex.insert(i,l,o,s,this.index,!0)}}},Bo.prototype.addFeatures=function(t,e){for(var r=0,n=this.features;r<n.length;r+=1){var a=n[r],i=a.geometry;this.addFeature(a,i,a.index,e)}},Bo.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},Bo.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},Bo.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},Bo.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Mo),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},Bo.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},Bo.prototype.addFeature=function(t,e,r,n){for(var a=0,i=mo(e,500);a<i.length;a+=1){for(var o=i[a],s=0,l=0,c=o;l<c.length;l+=1)s+=c[l].length;for(var u=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray),h=0,f=o;h<f.length;h+=1){var p=f[h];if(0!==p.length&&!jo(p))for(var d=0,g=0;g<p.length;g++){var v=p[g];if(g>=1){var m=p[g-1];if(!No(v,m)){u.vertexLength+4>Oa.MAX_VERTEX_ARRAY_LENGTH&&(u=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));var y=v.sub(m)._perp()._unit(),x=m.dist(v);d+x>32768&&(d=0),Fo(this.layoutVertexArray,v.x,v.y,y.x,y.y,0,0,d),Fo(this.layoutVertexArray,v.x,v.y,y.x,y.y,0,1,d),d+=x,Fo(this.layoutVertexArray,m.x,m.y,y.x,y.y,0,0,d),Fo(this.layoutVertexArray,m.x,m.y,y.x,y.y,0,1,d);var b=u.vertexLength;this.indexArray.emplaceBack(b,b+2,b+1),this.indexArray.emplaceBack(b+1,b+2,b+3),u.vertexLength+=4,u.primitiveLength+=2}}}}if(u.vertexLength+s>Oa.MAX_VERTEX_ARRAY_LENGTH&&(u=this.segments.prepareSegment(s,this.layoutVertexArray,this.indexArray)),\"Polygon\"===Do[t.type]){for(var _=[],w=[],k=u.vertexLength,T=0,M=o;T<M.length;T+=1){var A=M[T];if(0!==A.length){A!==o[0]&&w.push(_.length/2);for(var S=0;S<A.length;S++){var E=A[S];Fo(this.layoutVertexArray,E.x,E.y,0,0,1,1,0),_.push(E.x),_.push(E.y)}}}for(var L=Ni(_,w),C=0;C<L.length;C+=3)this.indexArray.emplaceBack(k+L[C],k+L[C+2],k+L[C+1]);u.primitiveLength+=L.length/3,u.vertexLength+=s}}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,n)},dn(\"FillExtrusionBucket\",Bo,{omit:[\"layers\",\"features\"]});var Vo={paint:new Gn({\"fill-extrusion-opacity\":new jn(Tt[\"paint_fill-extrusion\"][\"fill-extrusion-opacity\"]),\"fill-extrusion-color\":new Vn(Tt[\"paint_fill-extrusion\"][\"fill-extrusion-color\"]),\"fill-extrusion-translate\":new jn(Tt[\"paint_fill-extrusion\"][\"fill-extrusion-translate\"]),\"fill-extrusion-translate-anchor\":new jn(Tt[\"paint_fill-extrusion\"][\"fill-extrusion-translate-anchor\"]),\"fill-extrusion-pattern\":new Un(Tt[\"paint_fill-extrusion\"][\"fill-extrusion-pattern\"]),\"fill-extrusion-height\":new Vn(Tt[\"paint_fill-extrusion\"][\"fill-extrusion-height\"]),\"fill-extrusion-base\":new Vn(Tt[\"paint_fill-extrusion\"][\"fill-extrusion-base\"]),\"fill-extrusion-vertical-gradient\":new jn(Tt[\"paint_fill-extrusion\"][\"fill-extrusion-vertical-gradient\"])})},Uo=function(t){function e(e){t.call(this,e,Vo)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.createBucket=function(t){return new Bo(t)},e.prototype.queryRadius=function(){return yi(this.paint.get(\"fill-extrusion-translate\"))},e.prototype.is3D=function(){return!0},e.prototype.queryIntersectsFeature=function(t,e,r,n,i,o,s,l){var c=xi(t,this.paint.get(\"fill-extrusion-translate\"),this.paint.get(\"fill-extrusion-translate-anchor\"),o.angle,s),u=this.paint.get(\"fill-extrusion-height\").evaluate(e,r),h=this.paint.get(\"fill-extrusion-base\").evaluate(e,r),f=function(t,e,r,n){for(var i=[],o=0,s=t;o<s.length;o+=1){var l=s[o],c=[l.x,l.y,0,1];Ti(c,c,e),i.push(new a(c[0]/c[3],c[1]/c[3]))}return i}(c,l),p=function(t,e,r,n){for(var i=[],o=[],s=n[8]*e,l=n[9]*e,c=n[10]*e,u=n[11]*e,h=n[8]*r,f=n[9]*r,p=n[10]*r,d=n[11]*r,g=0,v=t;g<v.length;g+=1){for(var m=[],y=[],x=0,b=v[g];x<b.length;x+=1){var _=b[x],w=_.x,k=_.y,T=n[0]*w+n[4]*k+n[12],M=n[1]*w+n[5]*k+n[13],A=n[2]*w+n[6]*k+n[14],S=n[3]*w+n[7]*k+n[15],E=A+c,L=S+u,C=T+h,P=M+f,O=A+p,z=S+d,I=new a((T+s)/L,(M+l)/L);I.z=E/L,m.push(I);var D=new a(C/z,P/z);D.z=O/z,y.push(D)}i.push(m),o.push(y)}return[i,o]}(n,h,u,l);return function(t,e,r){var n=1/0;li(r,e)&&(n=Ho(r,e[0]));for(var a=0;a<e.length;a++)for(var i=e[a],o=t[a],s=0;s<i.length-1;s++){var l=i[s],c=i[s+1],u=o[s],h=[l,c,o[s+1],u,l];oi(r,h)&&(n=Math.min(n,Ho(r,h)))}return n!==1/0&&n}(p[0],p[1],f)},e}(Yn);function qo(t,e){return t.x*e.x+t.y*e.y}function Ho(t,e){if(1===t.length){var r=e[0],n=e[1],a=e[3],i=t[0],o=n.sub(r),s=a.sub(r),l=i.sub(r),c=qo(o,o),u=qo(o,s),h=qo(s,s),f=qo(l,o),p=qo(l,s),d=c*h-u*u,g=(h*f-u*p)/d,v=(c*p-u*f)/d,m=1-g-v;return r.z*m+n.z*g+a.z*v}for(var y=1/0,x=0,b=e;x<b.length;x+=1){var _=b[x];y=Math.min(y,_.z)}return y}var Go=Jn([{name:\"a_pos_normal\",components:2,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint8\"}],4).members,Yo=Io.VectorTileFeature.types,Wo=Math.cos(Math.PI/180*37.5),Xo=Math.pow(2,14)/.5,Zo=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map(function(t){return t.id}),this.index=t.index,this.hasPattern=!1,this.patternFeatures=[],this.layoutVertexArray=new ea,this.indexArray=new da,this.programConfigurations=new Qa(Go,t.layers,t.zoom),this.segments=new Oa,this.stateDependentLayerIds=this.layers.filter(function(t){return t.isStateDependent()}).map(function(t){return t.id})};Zo.prototype.populate=function(t,e){this.hasPattern=xo(\"line\",this.layers,e);for(var r=this.layers[0].layout.get(\"line-sort-key\"),n=[],a=0,i=t;a<i.length;a+=1){var o=i[a],s=o.feature,l=o.index,c=o.sourceLayerIndex;if(this.layers[0]._featureFilter(new Pn(this.zoom),s)){var u=ni(s),h=r?r.evaluate(s,{}):void 0,f={id:s.id,properties:s.properties,type:s.type,sourceLayerIndex:c,index:l,geometry:u,patterns:{},sortKey:h};n.push(f)}}r&&n.sort(function(t,e){return t.sortKey-e.sortKey});for(var p=0,d=n;p<d.length;p+=1){var g=d[p],v=g,m=v.geometry,y=v.index,x=v.sourceLayerIndex;if(this.hasPattern){var b=bo(\"line\",this.layers,g,this.zoom,e);this.patternFeatures.push(b)}else this.addFeature(g,m,y,{});var _=t[y].feature;e.featureIndex.insert(_,m,y,x,this.index)}},Zo.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},Zo.prototype.addFeatures=function(t,e){for(var r=0,n=this.patternFeatures;r<n.length;r+=1){var a=n[r];this.addFeature(a,a.geometry,a.index,e)}},Zo.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},Zo.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},Zo.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Go),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},Zo.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},Zo.prototype.addFeature=function(t,e,r,n){for(var a=this.layers[0].layout,i=a.get(\"line-join\").evaluate(t,{}),o=a.get(\"line-cap\"),s=a.get(\"line-miter-limit\"),l=a.get(\"line-round-limit\"),c=0,u=e;c<u.length;c+=1){var h=u[c];this.addLine(h,t,i,o,s,l,r,n)}},Zo.prototype.addLine=function(t,e,r,n,a,i,o,s){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,e.properties&&e.properties.hasOwnProperty(\"mapbox_clip_start\")&&e.properties.hasOwnProperty(\"mapbox_clip_end\")){this.clipStart=+e.properties.mapbox_clip_start,this.clipEnd=+e.properties.mapbox_clip_end;for(var l=0;l<t.length-1;l++)this.totalDistance+=t[l].dist(t[l+1])}for(var c=\"Polygon\"===Yo[e.type],u=t.length;u>=2&&t[u-1].equals(t[u-2]);)u--;for(var h=0;h<u-1&&t[h].equals(t[h+1]);)h++;if(!(u<(c?3:2))){\"bevel\"===r&&(a=1.05);var f,p=ei/(512*this.overscaling)*15,d=this.segments.prepareSegment(10*u,this.layoutVertexArray,this.indexArray),g=void 0,v=void 0,m=void 0,y=void 0;this.e1=this.e2=-1,c&&(f=t[u-2],y=t[h].sub(f)._unit()._perp());for(var x=h;x<u;x++)if(!(v=c&&x===u-1?t[h+1]:t[x+1])||!t[x].equals(v)){y&&(m=y),f&&(g=f),f=t[x],y=v?v.sub(f)._unit()._perp():m;var b=(m=m||y).add(y);0===b.x&&0===b.y||b._unit();var _=m.x*y.x+m.y*y.y,w=b.x*y.x+b.y*y.y,k=0!==w?1/w:1/0,T=2*Math.sqrt(2-2*w),M=w<Wo&&g&&v,A=m.x*y.y-m.y*y.x>0;if(M&&x>h){var S=f.dist(g);if(S>2*p){var E=f.sub(f.sub(g)._mult(p/S)._round());this.updateDistance(g,E),this.addCurrentVertex(E,m,0,0,d),g=E}}var L=g&&v,C=L?r:c?\"butt\":n;if(L&&\"round\"===C&&(k<i?C=\"miter\":k<=2&&(C=\"fakeround\")),\"miter\"===C&&k>a&&(C=\"bevel\"),\"bevel\"===C&&(k>2&&(C=\"flipbevel\"),k<a&&(C=\"miter\")),g&&this.updateDistance(g,f),\"miter\"===C)b._mult(k),this.addCurrentVertex(f,b,0,0,d);else if(\"flipbevel\"===C){if(k>100)b=y.mult(-1);else{var P=k*m.add(y).mag()/m.sub(y).mag();b._perp()._mult(P*(A?-1:1))}this.addCurrentVertex(f,b,0,0,d),this.addCurrentVertex(f,b.mult(-1),0,0,d)}else if(\"bevel\"===C||\"fakeround\"===C){var O=-Math.sqrt(k*k-1),z=A?O:0,I=A?0:O;if(g&&this.addCurrentVertex(f,m,z,I,d),\"fakeround\"===C)for(var D=Math.round(180*T/Math.PI/20),R=1;R<D;R++){var F=R/D;if(.5!==F){var B=F-.5;F+=F*B*(F-1)*((1.0904+_*(_*(3.55645-1.43519*_)-3.2452))*B*B+(.848013+_*(.215638*_-1.06021)))}var N=y.sub(m)._mult(F)._add(m)._unit()._mult(A?-1:1);this.addHalfVertex(f,N.x,N.y,!1,A,0,d)}v&&this.addCurrentVertex(f,y,-z,-I,d)}else if(\"butt\"===C)this.addCurrentVertex(f,b,0,0,d);else if(\"square\"===C){var j=g?1:-1;this.addCurrentVertex(f,b,j,j,d)}else\"round\"===C&&(g&&(this.addCurrentVertex(f,m,0,0,d),this.addCurrentVertex(f,m,1,1,d,!0)),v&&(this.addCurrentVertex(f,y,-1,-1,d,!0),this.addCurrentVertex(f,y,0,0,d)));if(M&&x<u-1){var V=f.dist(v);if(V>2*p){var U=f.add(v.sub(f)._mult(p/V)._round());this.updateDistance(f,U),this.addCurrentVertex(U,y,0,0,d),f=U}}}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,e,o,s)}},Zo.prototype.addCurrentVertex=function(t,e,r,n,a,i){void 0===i&&(i=!1);var o=e.x+e.y*r,s=e.y-e.x*r,l=-e.x+e.y*n,c=-e.y-e.x*n;this.addHalfVertex(t,o,s,i,!1,r,a),this.addHalfVertex(t,l,c,i,!0,-n,a),this.distance>Xo/2&&0===this.totalDistance&&(this.distance=0,this.addCurrentVertex(t,e,r,n,a,i))},Zo.prototype.addHalfVertex=function(t,e,r,n,a,i,o){var s=t.x,l=t.y,c=.5*this.scaledDistance;this.layoutVertexArray.emplaceBack((s<<1)+(n?1:0),(l<<1)+(a?1:0),Math.round(63*e)+128,Math.round(63*r)+128,1+(0===i?0:i<0?-1:1)|(63&c)<<2,c>>6);var u=o.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,u),o.primitiveLength++),a?this.e2=u:this.e1=u},Zo.prototype.updateDistance=function(t,e){this.distance+=t.dist(e),this.scaledDistance=this.totalDistance>0?(this.clipStart+(this.clipEnd-this.clipStart)*this.distance/this.totalDistance)*(Xo-1):this.distance},dn(\"LineBucket\",Zo,{omit:[\"layers\",\"patternFeatures\"]});var Jo=new Gn({\"line-cap\":new jn(Tt.layout_line[\"line-cap\"]),\"line-join\":new Vn(Tt.layout_line[\"line-join\"]),\"line-miter-limit\":new jn(Tt.layout_line[\"line-miter-limit\"]),\"line-round-limit\":new jn(Tt.layout_line[\"line-round-limit\"]),\"line-sort-key\":new Vn(Tt.layout_line[\"line-sort-key\"])}),Ko={paint:new Gn({\"line-opacity\":new Vn(Tt.paint_line[\"line-opacity\"]),\"line-color\":new Vn(Tt.paint_line[\"line-color\"]),\"line-translate\":new jn(Tt.paint_line[\"line-translate\"]),\"line-translate-anchor\":new jn(Tt.paint_line[\"line-translate-anchor\"]),\"line-width\":new Vn(Tt.paint_line[\"line-width\"]),\"line-gap-width\":new Vn(Tt.paint_line[\"line-gap-width\"]),\"line-offset\":new Vn(Tt.paint_line[\"line-offset\"]),\"line-blur\":new Vn(Tt.paint_line[\"line-blur\"]),\"line-dasharray\":new qn(Tt.paint_line[\"line-dasharray\"]),\"line-pattern\":new Un(Tt.paint_line[\"line-pattern\"]),\"line-gradient\":new Hn(Tt.paint_line[\"line-gradient\"])}),layout:Jo},Qo=new(function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(e,r){return r=new Pn(Math.floor(r.zoom),{now:r.now,fadeDuration:r.fadeDuration,zoomHistory:r.zoomHistory,transition:r.transition}),t.prototype.possiblyEvaluate.call(this,e,r)},e.prototype.evaluate=function(e,r,n,a){return r=h({},r,{zoom:Math.floor(r.zoom)}),t.prototype.evaluate.call(this,e,r,n,a)},e}(Vn))(Ko.paint.properties[\"line-width\"].specification);Qo.useIntegerZoom=!0;var $o=function(t){function e(e){t.call(this,e,Ko)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._handleSpecialPaintPropertyUpdate=function(t){\"line-gradient\"===t&&this._updateGradient()},e.prototype._updateGradient=function(){var t=this._transitionablePaint._values[\"line-gradient\"].value.expression;this.gradient=Ii(t,\"lineProgress\"),this.gradientTexture=null},e.prototype.recalculate=function(e){t.prototype.recalculate.call(this,e),this.paint._values[\"line-floorwidth\"]=Qo.possiblyEvaluate(this._transitioningPaint._values[\"line-width\"].value,e)},e.prototype.createBucket=function(t){return new Zo(t)},e.prototype.queryRadius=function(t){var e=t,r=ts(mi(\"line-width\",this,e),mi(\"line-gap-width\",this,e)),n=mi(\"line-offset\",this,e);return r/2+Math.abs(n)+yi(this.paint.get(\"line-translate\"))},e.prototype.queryIntersectsFeature=function(t,e,r,n,i,o,s){var l=xi(t,this.paint.get(\"line-translate\"),this.paint.get(\"line-translate-anchor\"),o.angle,s),c=s/2*ts(this.paint.get(\"line-width\").evaluate(e,r),this.paint.get(\"line-gap-width\").evaluate(e,r)),u=this.paint.get(\"line-offset\").evaluate(e,r);return u&&(n=function(t,e){for(var r=[],n=new a(0,0),i=0;i<t.length;i++){for(var o=t[i],s=[],l=0;l<o.length;l++){var c=o[l-1],u=o[l],h=o[l+1],f=0===l?n:u.sub(c)._unit()._perp(),p=l===o.length-1?n:h.sub(u)._unit()._perp(),d=f._add(p)._unit(),g=d.x*p.x+d.y*p.y;d._mult(1/g),s.push(d._mult(e)._add(u))}r.push(s)}return r}(n,u*s)),function(t,e,r){for(var n=0;n<e.length;n++){var a=e[n];if(t.length>=3)for(var i=0;i<a.length;i++)if(gi(t,a[i]))return!0;if(ci(t,a,r))return!0}return!1}(l,n,c)},e.prototype.isTileClipped=function(){return!0},e}(Yn);function ts(t,e){return e>0?e+2*t:t}var es=Jn([{name:\"a_pos_offset\",components:4,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint16\"}]),rs=Jn([{name:\"a_projected_pos\",components:3,type:\"Float32\"}],4),ns=(Jn([{name:\"a_fade_opacity\",components:1,type:\"Uint32\"}],4),Jn([{name:\"a_placed\",components:2,type:\"Uint8\"},{name:\"a_shift\",components:2,type:\"Float32\"}])),as=(Jn([{type:\"Int16\",name:\"anchorPointX\"},{type:\"Int16\",name:\"anchorPointY\"},{type:\"Int16\",name:\"x1\"},{type:\"Int16\",name:\"y1\"},{type:\"Int16\",name:\"x2\"},{type:\"Int16\",name:\"y2\"},{type:\"Uint32\",name:\"featureIndex\"},{type:\"Uint16\",name:\"sourceLayerIndex\"},{type:\"Uint16\",name:\"bucketIndex\"},{type:\"Int16\",name:\"radius\"},{type:\"Int16\",name:\"signedDistanceFromAnchor\"}]),Jn([{name:\"a_pos\",components:2,type:\"Int16\"},{name:\"a_anchor_pos\",components:2,type:\"Int16\"},{name:\"a_extrude\",components:2,type:\"Int16\"}],4)),is=Jn([{name:\"a_pos\",components:2,type:\"Int16\"},{name:\"a_anchor_pos\",components:2,type:\"Int16\"},{name:\"a_extrude\",components:2,type:\"Int16\"}],4);function os(t,e,r){return t.sections.forEach(function(t){t.text=function(t,e,r){var n=e.layout.get(\"text-transform\").evaluate(r,{});return\"uppercase\"===n?t=t.toLocaleUpperCase():\"lowercase\"===n&&(t=t.toLocaleLowerCase()),Cn.applyArabicShaping&&(t=Cn.applyArabicShaping(t)),t}(t.text,e,r)}),t}Jn([{type:\"Int16\",name:\"anchorX\"},{type:\"Int16\",name:\"anchorY\"},{type:\"Uint16\",name:\"glyphStartIndex\"},{type:\"Uint16\",name:\"numGlyphs\"},{type:\"Uint32\",name:\"vertexStartIndex\"},{type:\"Uint32\",name:\"lineStartIndex\"},{type:\"Uint32\",name:\"lineLength\"},{type:\"Uint16\",name:\"segment\"},{type:\"Uint16\",name:\"lowerSize\"},{type:\"Uint16\",name:\"upperSize\"},{type:\"Float32\",name:\"lineOffsetX\"},{type:\"Float32\",name:\"lineOffsetY\"},{type:\"Uint8\",name:\"writingMode\"},{type:\"Uint8\",name:\"placedOrientation\"},{type:\"Uint8\",name:\"hidden\"},{type:\"Uint32\",name:\"crossTileID\"}]),Jn([{type:\"Int16\",name:\"anchorX\"},{type:\"Int16\",name:\"anchorY\"},{type:\"Int16\",name:\"rightJustifiedTextSymbolIndex\"},{type:\"Int16\",name:\"centerJustifiedTextSymbolIndex\"},{type:\"Int16\",name:\"leftJustifiedTextSymbolIndex\"},{type:\"Int16\",name:\"verticalPlacedTextSymbolIndex\"},{type:\"Uint16\",name:\"key\"},{type:\"Uint16\",name:\"textBoxStartIndex\"},{type:\"Uint16\",name:\"textBoxEndIndex\"},{type:\"Uint16\",name:\"verticalTextBoxStartIndex\"},{type:\"Uint16\",name:\"verticalTextBoxEndIndex\"},{type:\"Uint16\",name:\"iconBoxStartIndex\"},{type:\"Uint16\",name:\"iconBoxEndIndex\"},{type:\"Uint16\",name:\"featureIndex\"},{type:\"Uint16\",name:\"numHorizontalGlyphVertices\"},{type:\"Uint16\",name:\"numVerticalGlyphVertices\"},{type:\"Uint16\",name:\"numIconVertices\"},{type:\"Uint32\",name:\"crossTileID\"},{type:\"Float32\",name:\"textBoxScale\"},{type:\"Float32\",name:\"radialTextOffset\"}]),Jn([{type:\"Float32\",name:\"offsetX\"}]),Jn([{type:\"Int16\",name:\"x\"},{type:\"Int16\",name:\"y\"},{type:\"Int16\",name:\"tileUnitDistanceFromAnchor\"}]);var ss={\"!\":\"\\ufe15\",\"#\":\"\\uff03\",$:\"\\uff04\",\"%\":\"\\uff05\",\"&\":\"\\uff06\",\"(\":\"\\ufe35\",\")\":\"\\ufe36\",\"*\":\"\\uff0a\",\"+\":\"\\uff0b\",\",\":\"\\ufe10\",\"-\":\"\\ufe32\",\".\":\"\\u30fb\",\"/\":\"\\uff0f\",\":\":\"\\ufe13\",\";\":\"\\ufe14\",\"<\":\"\\ufe3f\",\"=\":\"\\uff1d\",\">\":\"\\ufe40\",\"?\":\"\\ufe16\",\"@\":\"\\uff20\",\"[\":\"\\ufe47\",\"\\\\\":\"\\uff3c\",\"]\":\"\\ufe48\",\"^\":\"\\uff3e\",_:\"\\ufe33\",\"`\":\"\\uff40\",\"{\":\"\\ufe37\",\"|\":\"\\u2015\",\"}\":\"\\ufe38\",\"~\":\"\\uff5e\",\"\\xa2\":\"\\uffe0\",\"\\xa3\":\"\\uffe1\",\"\\xa5\":\"\\uffe5\",\"\\xa6\":\"\\uffe4\",\"\\xac\":\"\\uffe2\",\"\\xaf\":\"\\uffe3\",\"\\u2013\":\"\\ufe32\",\"\\u2014\":\"\\ufe31\",\"\\u2018\":\"\\ufe43\",\"\\u2019\":\"\\ufe44\",\"\\u201c\":\"\\ufe41\",\"\\u201d\":\"\\ufe42\",\"\\u2026\":\"\\ufe19\",\"\\u2027\":\"\\u30fb\",\"\\u20a9\":\"\\uffe6\",\"\\u3001\":\"\\ufe11\",\"\\u3002\":\"\\ufe12\",\"\\u3008\":\"\\ufe3f\",\"\\u3009\":\"\\ufe40\",\"\\u300a\":\"\\ufe3d\",\"\\u300b\":\"\\ufe3e\",\"\\u300c\":\"\\ufe41\",\"\\u300d\":\"\\ufe42\",\"\\u300e\":\"\\ufe43\",\"\\u300f\":\"\\ufe44\",\"\\u3010\":\"\\ufe3b\",\"\\u3011\":\"\\ufe3c\",\"\\u3014\":\"\\ufe39\",\"\\u3015\":\"\\ufe3a\",\"\\u3016\":\"\\ufe17\",\"\\u3017\":\"\\ufe18\",\"\\uff01\":\"\\ufe15\",\"\\uff08\":\"\\ufe35\",\"\\uff09\":\"\\ufe36\",\"\\uff0c\":\"\\ufe10\",\"\\uff0d\":\"\\ufe32\",\"\\uff0e\":\"\\u30fb\",\"\\uff1a\":\"\\ufe13\",\"\\uff1b\":\"\\ufe14\",\"\\uff1c\":\"\\ufe3f\",\"\\uff1e\":\"\\ufe40\",\"\\uff1f\":\"\\ufe16\",\"\\uff3b\":\"\\ufe47\",\"\\uff3d\":\"\\ufe48\",\"\\uff3f\":\"\\ufe33\",\"\\uff5b\":\"\\ufe37\",\"\\uff5c\":\"\\u2015\",\"\\uff5d\":\"\\ufe38\",\"\\uff5f\":\"\\ufe35\",\"\\uff60\":\"\\ufe36\",\"\\uff61\":\"\\ufe12\",\"\\uff62\":\"\\ufe41\",\"\\uff63\":\"\\ufe42\"},ls=24,cs={horizontal:1,vertical:2,horizontalOnly:3},us=function(){this.text=\"\",this.sectionIndex=[],this.sections=[]};function hs(t,e,r,n,a,i,o,s,l,c,u){var h,f=us.fromFeature(t,r);c===cs.vertical&&f.verticalizePunctuation();var p=Cn.processBidirectionalText,d=Cn.processStyledBidirectionalText;if(p&&1===f.sections.length){h=[];for(var g=0,v=p(f.toString(),ms(f,s,n,e));g<v.length;g+=1){var m=v[g],y=new us;y.text=m,y.sections=f.sections;for(var x=0;x<m.length;x++)y.sectionIndex.push(0);h.push(y)}}else if(d){h=[];for(var b=0,_=d(f.text,f.sectionIndex,ms(f,s,n,e));b<_.length;b+=1){var w=_[b],k=new us;k.text=w[0],k.sectionIndex=w[1],k.sections=f.sections,h.push(k)}}else h=function(t,e){for(var r=[],n=t.text,a=0,i=0,o=e;i<o.length;i+=1){var s=o[i];r.push(t.substring(a,s)),a=s}return a<n.length&&r.push(t.substring(a,n.length)),r}(f,ms(f,s,n,e));var T=[],M={positionedGlyphs:T,text:f.toString(),top:l[1],bottom:l[1],left:l[0],right:l[0],writingMode:c,lineCount:h.length,yOffset:-17};return function(t,e,r,n,a,i,o,s,l){for(var c=0,u=t.yOffset,h=0,f=t.positionedGlyphs,p=\"right\"===i?1:\"left\"===i?0:.5,d=0,g=r;d<g.length;d+=1){var v=g[d];v.trim();var m=v.getMaxScale();if(v.length()){for(var y=f.length,x=0;x<v.length();x++){var b=v.getSection(x),_=v.getSectionIndex(x),w=v.getCharCode(x),k=24*(m-b.scale),T=e[b.fontStack],M=T&&T[w];M&&(o===cs.horizontal||!l&&!wn(w)||l&&(fs[w]||(S=w,xn.Arabic(S)||xn[\"Arabic Supplement\"](S)||xn[\"Arabic Extended-A\"](S)||xn[\"Arabic Presentation Forms-A\"](S)||xn[\"Arabic Presentation Forms-B\"](S)))?(f.push({glyph:w,x:c,y:u+k,vertical:!1,scale:b.scale,fontStack:b.fontStack,sectionIndex:_}),c+=M.metrics.advance*b.scale+s):(f.push({glyph:w,x:c,y:u+k,vertical:!0,scale:b.scale,fontStack:b.fontStack,sectionIndex:_}),c+=ls*b.scale+s))}if(f.length!==y){var A=c-s;h=Math.max(A,h),xs(f,e,y,f.length-1,p)}c=0,u+=n*m}else u+=n}var S,E=ys(a),L=E.horizontalAlign,C=E.verticalAlign;!function(t,e,r,n,a,i,o){for(var s=(e-r)*a,l=(-n*o+.5)*i,c=0;c<t.length;c++)t[c].x+=s,t[c].y+=l}(f,p,L,C,h,n,r.length);var P=u-t.yOffset;t.top+=-C*P,t.bottom=t.top+P,t.left+=-L*h,t.right=t.left+h}(M,e,h,a,i,o,c,s,u),!!T.length&&M}us.fromFeature=function(t,e){for(var r=new us,n=0;n<t.sections.length;n++){var a=t.sections[n];r.sections.push({scale:a.scale||1,fontStack:a.fontStack||e}),r.text+=a.text;for(var i=0;i<a.text.length;i++)r.sectionIndex.push(n)}return r},us.prototype.length=function(){return this.text.length},us.prototype.getSection=function(t){return this.sections[this.sectionIndex[t]]},us.prototype.getSectionIndex=function(t){return this.sectionIndex[t]},us.prototype.getCharCode=function(t){return this.text.charCodeAt(t)},us.prototype.verticalizePunctuation=function(){this.text=function(t){for(var e=\"\",r=0;r<t.length;r++){var n=t.charCodeAt(r+1)||null,a=t.charCodeAt(r-1)||null;n&&kn(n)&&!ss[t[r+1]]||a&&kn(a)&&!ss[t[r-1]]||!ss[t[r]]?e+=t[r]:e+=ss[t[r]]}return e}(this.text)},us.prototype.trim=function(){for(var t=0,e=0;e<this.text.length&&fs[this.text.charCodeAt(e)];e++)t++;for(var r=this.text.length,n=this.text.length-1;n>=0&&n>=t&&fs[this.text.charCodeAt(n)];n--)r--;this.text=this.text.substring(t,r),this.sectionIndex=this.sectionIndex.slice(t,r)},us.prototype.substring=function(t,e){var r=new us;return r.text=this.text.substring(t,e),r.sectionIndex=this.sectionIndex.slice(t,e),r.sections=this.sections,r},us.prototype.toString=function(){return this.text},us.prototype.getMaxScale=function(){var t=this;return this.sectionIndex.reduce(function(e,r){return Math.max(e,t.sections[r].scale)},0)};var fs={9:!0,10:!0,11:!0,12:!0,13:!0,32:!0},ps={};function ds(t,e,r,n){var a=Math.pow(t-e,2);return n?t<e?a/2:2*a:a+Math.abs(r)*r}function gs(t,e,r){var n=0;return 10===t&&(n-=1e4),r&&(n+=150),40!==t&&65288!==t||(n+=50),41!==e&&65289!==e||(n+=50),n}function vs(t,e,r,n,a,i){for(var o=null,s=ds(e,r,a,i),l=0,c=n;l<c.length;l+=1){var u=c[l],h=ds(e-u.x,r,a,i)+u.badness;h<=s&&(o=u,s=h)}return{index:t,x:e,priorBreak:o,badness:s}}function ms(t,e,r,n){if(!r)return[];if(!t)return[];for(var a,i=[],o=function(t,e,r,n){for(var a=0,i=0;i<t.length();i++){var o=t.getSection(i),s=n[o.fontStack],l=s&&s[t.getCharCode(i)];l&&(a+=l.metrics.advance*o.scale+e)}return a/Math.max(1,Math.ceil(a/r))}(t,e,r,n),s=t.text.indexOf(\"\\u200b\")>=0,l=0,c=0;c<t.length();c++){var u=t.getSection(c),h=t.getCharCode(c),f=n[u.fontStack],p=f&&f[h];if(p&&!fs[h]&&(l+=p.metrics.advance*u.scale+e),c<t.length()-1){var d=!((a=h)<11904||!(xn[\"Bopomofo Extended\"](a)||xn.Bopomofo(a)||xn[\"CJK Compatibility Forms\"](a)||xn[\"CJK Compatibility Ideographs\"](a)||xn[\"CJK Compatibility\"](a)||xn[\"CJK Radicals Supplement\"](a)||xn[\"CJK Strokes\"](a)||xn[\"CJK Symbols and Punctuation\"](a)||xn[\"CJK Unified Ideographs Extension A\"](a)||xn[\"CJK Unified Ideographs\"](a)||xn[\"Enclosed CJK Letters and Months\"](a)||xn[\"Halfwidth and Fullwidth Forms\"](a)||xn.Hiragana(a)||xn[\"Ideographic Description Characters\"](a)||xn[\"Kangxi Radicals\"](a)||xn[\"Katakana Phonetic Extensions\"](a)||xn.Katakana(a)||xn[\"Vertical Forms\"](a)||xn[\"Yi Radicals\"](a)||xn[\"Yi Syllables\"](a)));(ps[h]||d)&&i.push(vs(c+1,l,o,i,gs(h,t.getCharCode(c+1),d&&s),!1))}}return function t(e){return e?t(e.priorBreak).concat(e.index):[]}(vs(t.length(),l,o,i,0,!0))}function ys(t){var e=.5,r=.5;switch(t){case\"right\":case\"top-right\":case\"bottom-right\":e=1;break;case\"left\":case\"top-left\":case\"bottom-left\":e=0}switch(t){case\"bottom\":case\"bottom-right\":case\"bottom-left\":r=1;break;case\"top\":case\"top-right\":case\"top-left\":r=0}return{horizontalAlign:e,verticalAlign:r}}function xs(t,e,r,n,a){if(a){var i=t[n],o=e[i.fontStack],s=o&&o[i.glyph];if(s)for(var l=s.metrics.advance*i.scale,c=(t[n].x+l)*a,u=r;u<=n;u++)t[u].x-=c}}ps[10]=!0,ps[32]=!0,ps[38]=!0,ps[40]=!0,ps[41]=!0,ps[43]=!0,ps[45]=!0,ps[47]=!0,ps[173]=!0,ps[183]=!0,ps[8203]=!0,ps[8208]=!0,ps[8211]=!0,ps[8231]=!0;var bs=function(t){function e(e,r,n,a){t.call(this,e,r),this.angle=n,void 0!==a&&(this.segment=a)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.clone=function(){return new e(this.x,this.y,this.angle,this.segment)},e}(a);dn(\"Anchor\",bs);var _s=256;function ws(t,e){var r=e.expression;if(\"constant\"===r.kind)return{kind:\"constant\",layoutSize:r.evaluate(new Pn(t+1))};if(\"source\"===r.kind)return{kind:\"source\"};for(var n=r.zoomStops,a=r.interpolationType,i=0;i<n.length&&n[i]<=t;)i++;for(var o=i=Math.max(0,i-1);o<n.length&&n[o]<t+1;)o++;o=Math.min(n.length-1,o);var s=n[i],l=n[o];return\"composite\"===r.kind?{kind:\"composite\",minZoom:s,maxZoom:l,interpolationType:a}:{kind:\"camera\",minZoom:s,maxZoom:l,minSize:r.evaluate(new Pn(s)),maxSize:r.evaluate(new Pn(l)),interpolationType:a}}function ks(t,e,r){var n=e.uSize,a=e.uSizeT,i=r.lowerSize,o=r.upperSize;return\"source\"===t.kind?i/_s:\"composite\"===t.kind?ye(i/_s,o/_s,a):n}function Ts(t,e){var r=0,n=0;if(\"constant\"===t.kind)n=t.layoutSize;else if(\"source\"!==t.kind){var a=t.interpolationType,i=t.minZoom,o=t.maxZoom,s=a?c(Ne.interpolationFactor(a,e,i,o),0,1):0;\"camera\"===t.kind?n=ye(t.minSize,t.maxSize,s):r=s}return{uSizeT:r,uSize:n}}var Ms=Object.freeze({getSizeData:ws,evaluateSizeForFeature:ks,evaluateSizeForZoom:Ts,SIZE_PACK_FACTOR:_s}),As=Io.VectorTileFeature.types,Ss=[{name:\"a_fade_opacity\",components:1,type:\"Uint8\",offset:0}];function Es(t,e,r,n,a,i,o,s){t.emplaceBack(e,r,Math.round(32*n),Math.round(32*a),i,o,s?s[0]:0,s?s[1]:0)}function Ls(t,e,r){t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r)}var Cs=function(t){this.layoutVertexArray=new na,this.indexArray=new da,this.programConfigurations=t,this.segments=new Oa,this.dynamicLayoutVertexArray=new aa,this.opacityVertexArray=new ia,this.placedSymbolArray=new wa};Cs.prototype.upload=function(t,e,r,n){r&&(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,es.members),this.indexBuffer=t.createIndexBuffer(this.indexArray,e),this.dynamicLayoutVertexBuffer=t.createVertexBuffer(this.dynamicLayoutVertexArray,rs.members,!0),this.opacityVertexBuffer=t.createVertexBuffer(this.opacityVertexArray,Ss,!0),this.opacityVertexBuffer.itemSize=1),(r||n)&&this.programConfigurations.upload(t)},Cs.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.dynamicLayoutVertexBuffer.destroy(),this.opacityVertexBuffer.destroy())},dn(\"SymbolBuffers\",Cs);var Ps=function(t,e,r){this.layoutVertexArray=new t,this.layoutAttributes=e,this.indexArray=new r,this.segments=new Oa,this.collisionVertexArray=new la};Ps.prototype.upload=function(t){this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,this.layoutAttributes),this.indexBuffer=t.createIndexBuffer(this.indexArray),this.collisionVertexBuffer=t.createVertexBuffer(this.collisionVertexArray,ns.members,!0)},Ps.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.collisionVertexBuffer.destroy())},dn(\"CollisionBuffers\",Ps);var Os=function(t){this.collisionBoxArray=t.collisionBoxArray,this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map(function(t){return t.id}),this.index=t.index,this.pixelRatio=t.pixelRatio,this.sourceLayerIndex=t.sourceLayerIndex,this.hasPattern=!1,this.hasPaintOverrides=!1;var e=this.layers[0]._unevaluatedLayout._values;this.textSizeData=ws(this.zoom,e[\"text-size\"]),this.iconSizeData=ws(this.zoom,e[\"icon-size\"]);var r=this.layers[0].layout,n=r.get(\"symbol-sort-key\"),a=r.get(\"symbol-z-order\");this.sortFeaturesByKey=\"viewport-y\"!==a&&void 0!==n.constantOr(1);var i=\"viewport-y\"===a||\"auto\"===a&&!this.sortFeaturesByKey;this.sortFeaturesByY=i&&(r.get(\"text-allow-overlap\")||r.get(\"icon-allow-overlap\")||r.get(\"text-ignore-placement\")||r.get(\"icon-ignore-placement\")),\"point\"===r.get(\"symbol-placement\")&&(this.writingModes=r.get(\"text-writing-mode\").map(function(t){return cs[t]})),this.stateDependentLayerIds=this.layers.filter(function(t){return t.isStateDependent()}).map(function(t){return t.id}),this.sourceID=t.sourceID};Os.prototype.createArrays=function(){var t=this.layers[0].layout;this.hasPaintOverrides=Rs.hasPaintOverrides(t),this.text=new Cs(new Qa(es.members,this.layers,this.zoom,function(t){return/^text/.test(t)})),this.icon=new Cs(new Qa(es.members,this.layers,this.zoom,function(t){return/^icon/.test(t)})),this.collisionBox=new Ps(sa,as.members,ga),this.collisionCircle=new Ps(sa,is.members,da),this.glyphOffsetArray=new Aa,this.lineVertexArray=new Ea,this.symbolInstances=new Ta},Os.prototype.calculateGlyphDependencies=function(t,e,r,n,a){for(var i=0;i<t.length;i++)if(e[t.charCodeAt(i)]=!0,(r||n)&&a){var o=ss[t.charAt(i)];o&&(e[o.charCodeAt(0)]=!0)}},Os.prototype.populate=function(t,e){var r=this.layers[0],n=r.layout,a=n.get(\"text-font\"),i=n.get(\"text-field\"),o=n.get(\"icon-image\"),s=(\"constant\"!==i.value.kind||i.value.value.toString().length>0)&&(\"constant\"!==a.value.kind||a.value.value.length>0),l=\"constant\"!==o.value.kind||o.value.value&&o.value.value.length>0,c=n.get(\"symbol-sort-key\");if(this.features=[],s||l){for(var u=e.iconDependencies,h=e.glyphDependencies,f=new Pn(this.zoom),p=0,d=t;p<d.length;p+=1){var g=d[p],v=g.feature,m=g.index,y=g.sourceLayerIndex;if(r._featureFilter(f,v)){var x=void 0;if(s){var b=r.getValueAndResolveTokens(\"text-field\",v);x=os(b instanceof Jt?b:Jt.fromString(b),r,v)}var _=void 0;if(l&&(_=r.getValueAndResolveTokens(\"icon-image\",v)),x||_){var w=this.sortFeaturesByKey?c.evaluate(v,{}):void 0,k={text:x,icon:_,index:m,sourceLayerIndex:y,geometry:ni(v),properties:v.properties,type:As[v.type],sortKey:w};if(void 0!==v.id&&(k.id=v.id),this.features.push(k),_&&(u[_]=!0),x){var T=a.evaluate(v,{}).join(\",\"),M=\"map\"===n.get(\"text-rotation-alignment\")&&\"point\"!==n.get(\"symbol-placement\");this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(cs.vertical)>=0;for(var A=0,S=x.sections;A<S.length;A+=1){var E=S[A],L=bn(x.toString()),C=E.fontStack||T,P=h[C]=h[C]||{};this.calculateGlyphDependencies(E.text,P,M,this.allowVerticalPlacement,L)}}}}}\"line\"===n.get(\"symbol-placement\")&&(this.features=function(t){var e={},r={},n=[],a=0;function i(e){n.push(t[e]),a++}function o(t,e,a){var i=r[t];return delete r[t],r[e]=i,n[i].geometry[0].pop(),n[i].geometry[0]=n[i].geometry[0].concat(a[0]),i}function s(t,r,a){var i=e[r];return delete e[r],e[t]=i,n[i].geometry[0].shift(),n[i].geometry[0]=a[0].concat(n[i].geometry[0]),i}function l(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+\":\"+n.x+\":\"+n.y}for(var c=0;c<t.length;c++){var u=t[c],h=u.geometry,f=u.text?u.text.toString():null;if(f){var p=l(f,h),d=l(f,h,!0);if(p in r&&d in e&&r[p]!==e[d]){var g=s(p,d,h),v=o(p,d,n[g].geometry);delete e[p],delete r[d],r[l(f,n[v].geometry,!0)]=v,n[g].geometry=null}else p in r?o(p,d,h):d in e?s(p,d,h):(i(c),e[p]=a-1,r[d]=a-1)}else i(c)}return n.filter(function(t){return t.geometry})}(this.features)),this.sortFeaturesByKey&&this.features.sort(function(t,e){return t.sortKey-e.sortKey})}},Os.prototype.update=function(t,e,r){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(t,e,this.layers,r),this.icon.programConfigurations.updatePaintArrays(t,e,this.layers,r))},Os.prototype.isEmpty=function(){return 0===this.symbolInstances.length},Os.prototype.uploadPending=function(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload},Os.prototype.upload=function(t){this.uploaded||(this.collisionBox.upload(t),this.collisionCircle.upload(t)),this.text.upload(t,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(t,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0},Os.prototype.destroy=function(){this.text.destroy(),this.icon.destroy(),this.collisionBox.destroy(),this.collisionCircle.destroy()},Os.prototype.addToLineVertexArray=function(t,e){var r=this.lineVertexArray.length;if(void 0!==t.segment){for(var n=t.dist(e[t.segment+1]),a=t.dist(e[t.segment]),i={},o=t.segment+1;o<e.length;o++)i[o]={x:e[o].x,y:e[o].y,tileUnitDistanceFromAnchor:n},o<e.length-1&&(n+=e[o+1].dist(e[o]));for(var s=t.segment||0;s>=0;s--)i[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:a},s>0&&(a+=e[s-1].dist(e[s]));for(var l=0;l<e.length;l++){var c=i[l];this.lineVertexArray.emplaceBack(c.x,c.y,c.tileUnitDistanceFromAnchor)}}return{lineStartIndex:r,lineLength:this.lineVertexArray.length-r}},Os.prototype.addSymbols=function(t,e,r,n,a,i,o,s,l,c){var u=this,h=t.indexArray,f=t.layoutVertexArray,p=t.dynamicLayoutVertexArray,d=t.segments.prepareSegment(4*e.length,t.layoutVertexArray,t.indexArray,i.sortKey),g=this.glyphOffsetArray.length,v=d.vertexLength,m=this.allowVerticalPlacement&&o===cs.vertical?Math.PI/2:0,y=function(t){var e=t.tl,n=t.tr,a=t.bl,i=t.br,o=t.tex,l=d.vertexLength,c=t.glyphOffset[1];Es(f,s.x,s.y,e.x,c+e.y,o.x,o.y,r),Es(f,s.x,s.y,n.x,c+n.y,o.x+o.w,o.y,r),Es(f,s.x,s.y,a.x,c+a.y,o.x,o.y+o.h,r),Es(f,s.x,s.y,i.x,c+i.y,o.x+o.w,o.y+o.h,r),Ls(p,s,m),h.emplaceBack(l,l+1,l+2),h.emplaceBack(l+1,l+2,l+3),d.vertexLength+=4,d.primitiveLength+=2,u.glyphOffsetArray.emplaceBack(t.glyphOffset[0])};if(i.text&&i.text.sections){var x=i.text.sections;if(this.hasPaintOverrides){for(var b,_=function(e,r){void 0===b||b===e&&!r||t.programConfigurations.populatePaintArrays(t.layoutVertexArray.length,i,i.index,{},x[b]),b=e},w=0,k=e;w<k.length;w+=1){var T=k[w];_(T.sectionIndex,!1),y(T)}_(b,!0)}else{for(var M=0,A=e;M<A.length;M+=1)y(A[M]);t.programConfigurations.populatePaintArrays(t.layoutVertexArray.length,i,i.index,{},x[0])}}else{for(var S=0,E=e;S<E.length;S+=1)y(E[S]);t.programConfigurations.populatePaintArrays(t.layoutVertexArray.length,i,i.index,{})}t.placedSymbolArray.emplaceBack(s.x,s.y,g,this.glyphOffsetArray.length-g,v,l,c,s.segment,r?r[0]:0,r?r[1]:0,n[0],n[1],o,0,!1,0)},Os.prototype._addCollisionDebugVertex=function(t,e,r,n,a,i){return e.emplaceBack(0,0),t.emplaceBack(r.x,r.y,n,a,Math.round(i.x),Math.round(i.y))},Os.prototype.addCollisionDebugVertices=function(t,e,r,n,i,o,s,l){var c=i.segments.prepareSegment(4,i.layoutVertexArray,i.indexArray),u=c.vertexLength,h=i.layoutVertexArray,f=i.collisionVertexArray,p=s.anchorX,d=s.anchorY;if(this._addCollisionDebugVertex(h,f,o,p,d,new a(t,e)),this._addCollisionDebugVertex(h,f,o,p,d,new a(r,e)),this._addCollisionDebugVertex(h,f,o,p,d,new a(r,n)),this._addCollisionDebugVertex(h,f,o,p,d,new a(t,n)),c.vertexLength+=4,l){var g=i.indexArray;g.emplaceBack(u,u+1,u+2),g.emplaceBack(u,u+2,u+3),c.primitiveLength+=2}else{var v=i.indexArray;v.emplaceBack(u,u+1),v.emplaceBack(u+1,u+2),v.emplaceBack(u+2,u+3),v.emplaceBack(u+3,u),c.primitiveLength+=4}},Os.prototype.addDebugCollisionBoxes=function(t,e,r){for(var n=t;n<e;n++){var a=this.collisionBoxArray.get(n),i=a.x1,o=a.y1,s=a.x2,l=a.y2,c=a.radius>0;this.addCollisionDebugVertices(i,o,s,l,c?this.collisionCircle:this.collisionBox,a.anchorPoint,r,c)}},Os.prototype.generateCollisionDebugBuffers=function(){for(var t=0;t<this.symbolInstances.length;t++){var e=this.symbolInstances.get(t);this.addDebugCollisionBoxes(e.textBoxStartIndex,e.textBoxEndIndex,e),this.addDebugCollisionBoxes(e.verticalTextBoxStartIndex,e.verticalTextBoxEndIndex,e),this.addDebugCollisionBoxes(e.iconBoxStartIndex,e.iconBoxEndIndex,e)}},Os.prototype._deserializeCollisionBoxesForSymbol=function(t,e,r,n,a,i,o){for(var s={},l=e;l<r;l++){var c=t.get(l);if(0===c.radius){s.textBox={x1:c.x1,y1:c.y1,x2:c.x2,y2:c.y2,anchorPointX:c.anchorPointX,anchorPointY:c.anchorPointY},s.textFeatureIndex=c.featureIndex;break}s.textCircles||(s.textCircles=[],s.textFeatureIndex=c.featureIndex),s.textCircles.push(c.anchorPointX,c.anchorPointY,c.radius,c.signedDistanceFromAnchor,1)}for(var u=n;u<a;u++){var h=t.get(u);if(0===h.radius){s.verticalTextBox={x1:h.x1,y1:h.y1,x2:h.x2,y2:h.y2,anchorPointX:h.anchorPointX,anchorPointY:h.anchorPointY},s.verticalTextFeatureIndex=h.featureIndex;break}}for(var f=i;f<o;f++){var p=t.get(f);if(0===p.radius){s.iconBox={x1:p.x1,y1:p.y1,x2:p.x2,y2:p.y2,anchorPointX:p.anchorPointX,anchorPointY:p.anchorPointY},s.iconFeatureIndex=p.featureIndex;break}}return s},Os.prototype.deserializeCollisionBoxes=function(t){this.collisionArrays=[];for(var e=0;e<this.symbolInstances.length;e++){var r=this.symbolInstances.get(e);this.collisionArrays.push(this._deserializeCollisionBoxesForSymbol(t,r.textBoxStartIndex,r.textBoxEndIndex,r.verticalTextBoxStartIndex,r.verticalTextBoxEndIndex,r.iconBoxStartIndex,r.iconBoxEndIndex))}},Os.prototype.hasTextData=function(){return this.text.segments.get().length>0},Os.prototype.hasIconData=function(){return this.icon.segments.get().length>0},Os.prototype.hasCollisionBoxData=function(){return this.collisionBox.segments.get().length>0},Os.prototype.hasCollisionCircleData=function(){return this.collisionCircle.segments.get().length>0},Os.prototype.addIndicesForPlacedTextSymbol=function(t){for(var e=this.text.placedSymbolArray.get(t),r=e.vertexStartIndex+4*e.numGlyphs,n=e.vertexStartIndex;n<r;n+=4)this.text.indexArray.emplaceBack(n,n+1,n+2),this.text.indexArray.emplaceBack(n+1,n+2,n+3)},Os.prototype.getSortedSymbolIndexes=function(t){if(this.sortedAngle===t&&void 0!==this.symbolInstanceIndexes)return this.symbolInstanceIndexes;for(var e=Math.sin(t),r=Math.cos(t),n=[],a=[],i=[],o=0;o<this.symbolInstances.length;++o){i.push(o);var s=this.symbolInstances.get(o);n.push(0|Math.round(e*s.anchorX+r*s.anchorY)),a.push(s.featureIndex)}return i.sort(function(t,e){return n[t]-n[e]||a[e]-a[t]}),i},Os.prototype.sortFeatures=function(t){var e=this;if(this.sortFeaturesByY&&this.sortedAngle!==t&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r<n.length;r+=1){var a=n[r],i=this.symbolInstances.get(a);this.featureSortOrder.push(i.featureIndex),[i.rightJustifiedTextSymbolIndex,i.centerJustifiedTextSymbolIndex,i.leftJustifiedTextSymbolIndex].forEach(function(t,r,n){t>=0&&n.indexOf(t)===r&&e.addIndicesForPlacedTextSymbol(t)}),i.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedTextSymbol(i.verticalPlacedTextSymbolIndex);var o=this.icon.placedSymbolArray.get(a);if(o.numGlyphs){var s=o.vertexStartIndex;this.icon.indexArray.emplaceBack(s,s+1,s+2),this.icon.indexArray.emplaceBack(s+1,s+2,s+3)}}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},dn(\"SymbolBucket\",Os,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"]}),Os.MAX_GLYPHS=65535,Os.addDynamicAttributes=Ls;var zs=new Gn({\"symbol-placement\":new jn(Tt.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new jn(Tt.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new jn(Tt.layout_symbol[\"symbol-avoid-edges\"]),\"symbol-sort-key\":new Vn(Tt.layout_symbol[\"symbol-sort-key\"]),\"symbol-z-order\":new jn(Tt.layout_symbol[\"symbol-z-order\"]),\"icon-allow-overlap\":new jn(Tt.layout_symbol[\"icon-allow-overlap\"]),\"icon-ignore-placement\":new jn(Tt.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new jn(Tt.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new jn(Tt.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new Vn(Tt.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new jn(Tt.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new jn(Tt.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new Vn(Tt.layout_symbol[\"icon-image\"]),\"icon-rotate\":new Vn(Tt.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new jn(Tt.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new jn(Tt.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new Vn(Tt.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new Vn(Tt.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new jn(Tt.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new jn(Tt.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new jn(Tt.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new Vn(Tt.layout_symbol[\"text-field\"]),\"text-font\":new Vn(Tt.layout_symbol[\"text-font\"]),\"text-size\":new Vn(Tt.layout_symbol[\"text-size\"]),\"text-max-width\":new Vn(Tt.layout_symbol[\"text-max-width\"]),\"text-line-height\":new jn(Tt.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new Vn(Tt.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new Vn(Tt.layout_symbol[\"text-justify\"]),\"text-radial-offset\":new Vn(Tt.layout_symbol[\"text-radial-offset\"]),\"text-variable-anchor\":new jn(Tt.layout_symbol[\"text-variable-anchor\"]),\"text-anchor\":new Vn(Tt.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new jn(Tt.layout_symbol[\"text-max-angle\"]),\"text-writing-mode\":new jn(Tt.layout_symbol[\"text-writing-mode\"]),\"text-rotate\":new Vn(Tt.layout_symbol[\"text-rotate\"]),\"text-padding\":new jn(Tt.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new jn(Tt.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new Vn(Tt.layout_symbol[\"text-transform\"]),\"text-offset\":new Vn(Tt.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new jn(Tt.layout_symbol[\"text-allow-overlap\"]),\"text-ignore-placement\":new jn(Tt.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new jn(Tt.layout_symbol[\"text-optional\"])}),Is={paint:new Gn({\"icon-opacity\":new Vn(Tt.paint_symbol[\"icon-opacity\"]),\"icon-color\":new Vn(Tt.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new Vn(Tt.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new Vn(Tt.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new Vn(Tt.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new jn(Tt.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new jn(Tt.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new Vn(Tt.paint_symbol[\"text-opacity\"]),\"text-color\":new Vn(Tt.paint_symbol[\"text-color\"],{runtimeType:Ft,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),\"text-halo-color\":new Vn(Tt.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new Vn(Tt.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new Vn(Tt.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new jn(Tt.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new jn(Tt.paint_symbol[\"text-translate-anchor\"])}),layout:zs},Ds=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:zt,this.defaultValue=t};Ds.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},Ds.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},Ds.prototype.possibleOutputs=function(){return[void 0]},Ds.prototype.serialize=function(){return null},dn(\"FormatSectionOverride\",Ds,{omit:[\"defaultValue\"]});var Rs=function(t){function e(e){t.call(this,e,Is)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.recalculate=function(e){if(t.prototype.recalculate.call(this,e),\"auto\"===this.layout.get(\"icon-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"icon-rotation-alignment\"]=\"map\":this.layout._values[\"icon-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"text-rotation-alignment\"]=\"map\":this.layout._values[\"text-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-pitch-alignment\")&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")),\"auto\"===this.layout.get(\"icon-pitch-alignment\")&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\")),\"point\"===this.layout.get(\"symbol-placement\")){var r=this.layout.get(\"text-writing-mode\");if(r){for(var n=[],a=0,i=r;a<i.length;a+=1){var o=i[a];n.indexOf(o)<0&&n.push(o)}this.layout._values[\"text-writing-mode\"]=n}else this.layout._values[\"text-writing-mode\"]=[\"horizontal\"]}this._setPaintOverrides()},e.prototype.getValueAndResolveTokens=function(t,e){var r=this.layout.get(t).evaluate(e,{}),n=this._unevaluatedLayout._values[t];return n.isDataDriven()||wr(n.value)?r:function(t,e){return r.replace(/{([^{}]+)}/g,function(e,r){return r in t?String(t[r]):\"\"})}(e.properties)},e.prototype.createBucket=function(t){return new Os(t)},e.prototype.queryRadius=function(){return 0},e.prototype.queryIntersectsFeature=function(){return!1},e.prototype._setPaintOverrides=function(){for(var t=0,r=Is.paint.overridableProperties;t<r.length;t+=1){var n=r[t];if(e.hasPaintOverride(this.layout,n)){var a,i=this.paint.get(n),o=new Ds(i),s=new _r(o,i.property.specification);a=\"constant\"===i.value.kind||\"source\"===i.value.kind?new Tr(\"source\",s):new Mr(\"composite\",s,i.value.zoomStops,i.value._interpolationType),this.paint._values[n]=new Bn(i.property,a,i.parameters)}}},e.prototype._handleOverridablePaintPropertyUpdate=function(t,r,n){return!(!this.layout||r.isDataDriven()||n.isDataDriven())&&e.hasPaintOverride(this.layout,t)},e.hasPaintOverride=function(t,e){var r=t.get(\"text-field\"),n=Is.paint.properties[e],a=!1,i=function(t){for(var e=0,r=t;e<r.length;e+=1){var i=r[e];if(n.overrides&&n.overrides.hasOverride(i))return void(a=!0)}};if(\"constant\"===r.value.kind&&r.value.value instanceof Jt)i(r.value.value.sections);else if(\"source\"===r.value.kind){var o=function(t){if(!a)if(t instanceof te&&Qt(t.value)===Vt){var e=t.value;i(e.sections)}else t instanceof ae?i(t.sections):t.eachChild(o)},s=r.value;s._styleExpression&&o(s._styleExpression.expression)}return a},e.hasPaintOverrides=function(t){for(var r=0,n=Is.paint.overridableProperties;r<n.length;r+=1){var a=n[r];if(e.hasPaintOverride(t,a))return!0}return!1},e}(Yn),Fs={paint:new Gn({\"background-color\":new jn(Tt.paint_background[\"background-color\"]),\"background-pattern\":new qn(Tt.paint_background[\"background-pattern\"]),\"background-opacity\":new jn(Tt.paint_background[\"background-opacity\"])})},Bs=function(t){function e(e){t.call(this,e,Fs)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Yn),Ns={paint:new Gn({\"raster-opacity\":new jn(Tt.paint_raster[\"raster-opacity\"]),\"raster-hue-rotate\":new jn(Tt.paint_raster[\"raster-hue-rotate\"]),\"raster-brightness-min\":new jn(Tt.paint_raster[\"raster-brightness-min\"]),\"raster-brightness-max\":new jn(Tt.paint_raster[\"raster-brightness-max\"]),\"raster-saturation\":new jn(Tt.paint_raster[\"raster-saturation\"]),\"raster-contrast\":new jn(Tt.paint_raster[\"raster-contrast\"]),\"raster-resampling\":new jn(Tt.paint_raster[\"raster-resampling\"]),\"raster-fade-duration\":new jn(Tt.paint_raster[\"raster-fade-duration\"])})},js=function(t){function e(e){t.call(this,e,Ns)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Yn),Vs=function(t){function e(e){t.call(this,e,{}),this.implementation=e}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.is3D=function(){return\"3d\"===this.implementation.renderingMode},e.prototype.hasOffscreenPass=function(){return void 0!==this.implementation.prerender},e.prototype.recalculate=function(){},e.prototype.updateTransitions=function(){},e.prototype.hasTransition=function(){},e.prototype.serialize=function(){},e.prototype.onAdd=function(t){this.implementation.onAdd&&this.implementation.onAdd(t,t.painter.context.gl)},e.prototype.onRemove=function(t){this.implementation.onRemove&&this.implementation.onRemove(t,t.painter.context.gl)},e}(Yn),Us={circle:Mi,heatmap:Di,hillshade:Fi,fill:To,\"fill-extrusion\":Uo,line:$o,symbol:Rs,background:Bs,raster:js};function qs(t){for(var e=0,r=0,n=0,a=t;n<a.length;n+=1){var i=a[n];e+=i.w*i.h,r=Math.max(r,i.w)}t.sort(function(t,e){return e.h-t.h});for(var o=[{x:0,y:0,w:Math.max(Math.ceil(Math.sqrt(e/.95)),r),h:1/0}],s=0,l=0,c=0,u=t;c<u.length;c+=1)for(var h=u[c],f=o.length-1;f>=0;f--){var p=o[f];if(!(h.w>p.w||h.h>p.h)){if(h.x=p.x,h.y=p.y,l=Math.max(l,h.y+h.h),s=Math.max(s,h.x+h.w),h.w===p.w&&h.h===p.h){var d=o.pop();f<o.length&&(o[f]=d)}else h.h===p.h?(p.x+=h.w,p.w-=h.w):h.w===p.w?(p.y+=h.h,p.h-=h.h):(o.push({x:p.x+h.w,y:p.y,w:p.w-h.w,h:h.h}),p.y+=h.h,p.h-=h.h);break}}return{w:s,h:l,fill:e/(s*l)||0}}var Hs=function(t,e){var r=e.pixelRatio,n=e.version;this.paddedRect=t,this.pixelRatio=r,this.version=n},Gs={tl:{configurable:!0},br:{configurable:!0},tlbr:{configurable:!0},displaySize:{configurable:!0}};Gs.tl.get=function(){return[this.paddedRect.x+1,this.paddedRect.y+1]},Gs.br.get=function(){return[this.paddedRect.x+this.paddedRect.w-1,this.paddedRect.y+this.paddedRect.h-1]},Gs.tlbr.get=function(){return this.tl.concat(this.br)},Gs.displaySize.get=function(){return[(this.paddedRect.w-2)/this.pixelRatio,(this.paddedRect.h-2)/this.pixelRatio]},Object.defineProperties(Hs.prototype,Gs);var Ys=function(t,e){var r={},n={};this.haveRenderCallbacks=[];var a=[];this.addImages(t,r,a),this.addImages(e,n,a);var i=qs(a),o=i.w,s=i.h,l=new Oi({width:o||1,height:s||1});for(var c in t){var u=t[c],h=r[c].paddedRect;Oi.copy(u.data,l,{x:0,y:0},{x:h.x+1,y:h.y+1},u.data)}for(var f in e){var p=e[f],d=n[f].paddedRect,g=d.x+1,v=d.y+1,m=p.data.width,y=p.data.height;Oi.copy(p.data,l,{x:0,y:0},{x:g,y:v},p.data),Oi.copy(p.data,l,{x:0,y:y-1},{x:g,y:v-1},{width:m,height:1}),Oi.copy(p.data,l,{x:0,y:0},{x:g,y:v+y},{width:m,height:1}),Oi.copy(p.data,l,{x:m-1,y:0},{x:g-1,y:v},{width:1,height:y}),Oi.copy(p.data,l,{x:0,y:0},{x:g+m,y:v},{width:1,height:y})}this.image=l,this.iconPositions=r,this.patternPositions=n};Ys.prototype.addImages=function(t,e,r){for(var n in t){var a=t[n],i={x:0,y:0,w:a.data.width+2,h:a.data.height+2};r.push(i),e[n]=new Hs(i,a),a.hasRenderCallback&&this.haveRenderCallbacks.push(n)}},Ys.prototype.patchUpdatedImages=function(t,e){for(var r in t.dispatchRenderCallbacks(this.haveRenderCallbacks),t.updatedImages)this.patchUpdatedImage(this.iconPositions[r],t.getImage(r),e),this.patchUpdatedImage(this.patternPositions[r],t.getImage(r),e)},Ys.prototype.patchUpdatedImage=function(t,e,r){if(t&&e&&t.version!==e.version){t.version=e.version;var n=t.tl,a=n[0],i=n[1];r.update(e.data,void 0,{x:a,y:i})}},dn(\"ImagePosition\",Hs),dn(\"ImageAtlas\",Ys);var Ws=self.HTMLImageElement,Xs=self.HTMLCanvasElement,Zs=self.HTMLVideoElement,Js=self.ImageData,Ks=function(t,e,r,n){this.context=t,this.format=r,this.texture=t.gl.createTexture(),this.update(e,n)};Ks.prototype.update=function(t,e,r){var n=t.width,a=t.height,i=!(this.size&&this.size[0]===n&&this.size[1]===a||r),o=this.context,s=o.gl;if(this.useMipmap=Boolean(e&&e.useMipmap),s.bindTexture(s.TEXTURE_2D,this.texture),o.pixelStoreUnpackFlipY.set(!1),o.pixelStoreUnpack.set(1),o.pixelStoreUnpackPremultiplyAlpha.set(this.format===s.RGBA&&(!e||!1!==e.premultiply)),i)this.size=[n,a],t instanceof Ws||t instanceof Xs||t instanceof Zs||t instanceof Js?s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,s.UNSIGNED_BYTE,t):s.texImage2D(s.TEXTURE_2D,0,this.format,n,a,0,this.format,s.UNSIGNED_BYTE,t.data);else{var l=r||{x:0,y:0},c=l.x,u=l.y;t instanceof Ws||t instanceof Xs||t instanceof Zs||t instanceof Js?s.texSubImage2D(s.TEXTURE_2D,0,c,u,s.RGBA,s.UNSIGNED_BYTE,t):s.texSubImage2D(s.TEXTURE_2D,0,c,u,n,a,s.RGBA,s.UNSIGNED_BYTE,t.data)}this.useMipmap&&this.isSizePowerOfTwo()&&s.generateMipmap(s.TEXTURE_2D)},Ks.prototype.bind=function(t,e,r){var n=this.context.gl;n.bindTexture(n.TEXTURE_2D,this.texture),r!==n.LINEAR_MIPMAP_NEAREST||this.isSizePowerOfTwo()||(r=n.LINEAR),t!==this.filter&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,t),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,r||t),this.filter=t),e!==this.wrap&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,e),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,e),this.wrap=e)},Ks.prototype.isSizePowerOfTwo=function(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1==0},Ks.prototype.destroy=function(){this.context.gl.deleteTexture(this.texture),this.texture=null};var Qs=function(t,e,r,n,a){var i,o,s=8*a-n-1,l=(1<<s)-1,c=l>>1,u=-7,h=r?a-1:0,f=r?-1:1,p=t[e+h];for(h+=f,i=p&(1<<-u)-1,p>>=-u,u+=s;u>0;i=256*i+t[e+h],h+=f,u-=8);for(o=i&(1<<-u)-1,i>>=-u,u+=n;u>0;o=256*o+t[e+h],h+=f,u-=8);if(0===i)i=1-c;else{if(i===l)return o?NaN:1/0*(p?-1:1);o+=Math.pow(2,n),i-=c}return(p?-1:1)*o*Math.pow(2,i-n)},$s=function(t,e,r,n,a,i){var o,s,l,c=8*i-a-1,u=(1<<c)-1,h=u>>1,f=23===a?Math.pow(2,-24)-Math.pow(2,-77):0,p=n?0:i-1,d=n?1:-1,g=e<0||0===e&&1/e<0?1:0;for(e=Math.abs(e),isNaN(e)||e===1/0?(s=isNaN(e)?1:0,o=u):(o=Math.floor(Math.log(e)/Math.LN2),e*(l=Math.pow(2,-o))<1&&(o--,l*=2),(e+=o+h>=1?f/l:f*Math.pow(2,1-h))*l>=2&&(o++,l/=2),o+h>=u?(s=0,o=u):o+h>=1?(s=(e*l-1)*Math.pow(2,a),o+=h):(s=e*Math.pow(2,h-1)*Math.pow(2,a),o=0));a>=8;t[r+p]=255&s,p+=d,s/=256,a-=8);for(o=o<<a|s,c+=a;c>0;t[r+p]=255&o,p+=d,o/=256,c-=8);t[r+p-d]|=128*g},tl=el;function el(t){this.buf=ArrayBuffer.isView&&ArrayBuffer.isView(t)?t:new Uint8Array(t||0),this.pos=0,this.type=0,this.length=this.buf.length}function rl(t){return t.type===el.Bytes?t.readVarint()+t.pos:t.pos+1}function nl(t,e,r){return r?4294967296*e+(t>>>0):4294967296*(e>>>0)+(t>>>0)}function al(t,e,r){var n=e<=16383?1:e<=2097151?2:e<=268435455?3:Math.floor(Math.log(e)/(7*Math.LN2));r.realloc(n);for(var a=r.pos-1;a>=t;a--)r.buf[a+n]=r.buf[a]}function il(t,e){for(var r=0;r<t.length;r++)e.writeVarint(t[r])}function ol(t,e){for(var r=0;r<t.length;r++)e.writeSVarint(t[r])}function sl(t,e){for(var r=0;r<t.length;r++)e.writeFloat(t[r])}function ll(t,e){for(var r=0;r<t.length;r++)e.writeDouble(t[r])}function cl(t,e){for(var r=0;r<t.length;r++)e.writeBoolean(t[r])}function ul(t,e){for(var r=0;r<t.length;r++)e.writeFixed32(t[r])}function hl(t,e){for(var r=0;r<t.length;r++)e.writeSFixed32(t[r])}function fl(t,e){for(var r=0;r<t.length;r++)e.writeFixed64(t[r])}function pl(t,e){for(var r=0;r<t.length;r++)e.writeSFixed64(t[r])}function dl(t,e){return(t[e]|t[e+1]<<8|t[e+2]<<16)+16777216*t[e+3]}function gl(t,e,r){t[r]=e,t[r+1]=e>>>8,t[r+2]=e>>>16,t[r+3]=e>>>24}function vl(t,e){return(t[e]|t[e+1]<<8|t[e+2]<<16)+(t[e+3]<<24)}el.Varint=0,el.Fixed64=1,el.Bytes=2,el.Fixed32=5,el.prototype={destroy:function(){this.buf=null},readFields:function(t,e,r){for(r=r||this.length;this.pos<r;){var n=this.readVarint(),a=n>>3,i=this.pos;this.type=7&n,t(a,e,this),this.pos===i&&this.skip(n)}return e},readMessage:function(t,e){return this.readFields(t,e,this.readVarint()+this.pos)},readFixed32:function(){var t=dl(this.buf,this.pos);return this.pos+=4,t},readSFixed32:function(){var t=vl(this.buf,this.pos);return this.pos+=4,t},readFixed64:function(){var t=dl(this.buf,this.pos)+4294967296*dl(this.buf,this.pos+4);return this.pos+=8,t},readSFixed64:function(){var t=dl(this.buf,this.pos)+4294967296*vl(this.buf,this.pos+4);return this.pos+=8,t},readFloat:function(){var t=Qs(this.buf,this.pos,!0,23,4);return this.pos+=4,t},readDouble:function(){var t=Qs(this.buf,this.pos,!0,52,8);return this.pos+=8,t},readVarint:function(t){var e,r,n=this.buf;return e=127&(r=n[this.pos++]),r<128?e:(e|=(127&(r=n[this.pos++]))<<7,r<128?e:(e|=(127&(r=n[this.pos++]))<<14,r<128?e:(e|=(127&(r=n[this.pos++]))<<21,r<128?e:function(t,e,r){var n,a,i=r.buf;if(n=(112&(a=i[r.pos++]))>>4,a<128)return nl(t,n,e);if(n|=(127&(a=i[r.pos++]))<<3,a<128)return nl(t,n,e);if(n|=(127&(a=i[r.pos++]))<<10,a<128)return nl(t,n,e);if(n|=(127&(a=i[r.pos++]))<<17,a<128)return nl(t,n,e);if(n|=(127&(a=i[r.pos++]))<<24,a<128)return nl(t,n,e);if(n|=(1&(a=i[r.pos++]))<<31,a<128)return nl(t,n,e);throw new Error(\"Expected varint not more than 10 bytes\")}(e|=(15&(r=n[this.pos]))<<28,t,this))))},readVarint64:function(){return this.readVarint(!0)},readSVarint:function(){var t=this.readVarint();return t%2==1?(t+1)/-2:t/2},readBoolean:function(){return Boolean(this.readVarint())},readString:function(){var t=this.readVarint()+this.pos,e=function(t,e,r){for(var n=\"\",a=e;a<r;){var i,o,s,l=t[a],c=null,u=l>239?4:l>223?3:l>191?2:1;if(a+u>r)break;1===u?l<128&&(c=l):2===u?128==(192&(i=t[a+1]))&&(c=(31&l)<<6|63&i)<=127&&(c=null):3===u?(i=t[a+1],o=t[a+2],128==(192&i)&&128==(192&o)&&((c=(15&l)<<12|(63&i)<<6|63&o)<=2047||c>=55296&&c<=57343)&&(c=null)):4===u&&(i=t[a+1],o=t[a+2],s=t[a+3],128==(192&i)&&128==(192&o)&&128==(192&s)&&((c=(15&l)<<18|(63&i)<<12|(63&o)<<6|63&s)<=65535||c>=1114112)&&(c=null)),null===c?(c=65533,u=1):c>65535&&(c-=65536,n+=String.fromCharCode(c>>>10&1023|55296),c=56320|1023&c),n+=String.fromCharCode(c),a+=u}return n}(this.buf,this.pos,t);return this.pos=t,e},readBytes:function(){var t=this.readVarint()+this.pos,e=this.buf.subarray(this.pos,t);return this.pos=t,e},readPackedVarint:function(t,e){if(this.type!==el.Bytes)return t.push(this.readVarint(e));var r=rl(this);for(t=t||[];this.pos<r;)t.push(this.readVarint(e));return t},readPackedSVarint:function(t){if(this.type!==el.Bytes)return t.push(this.readSVarint());var e=rl(this);for(t=t||[];this.pos<e;)t.push(this.readSVarint());return t},readPackedBoolean:function(t){if(this.type!==el.Bytes)return t.push(this.readBoolean());var e=rl(this);for(t=t||[];this.pos<e;)t.push(this.readBoolean());return t},readPackedFloat:function(t){if(this.type!==el.Bytes)return t.push(this.readFloat());var e=rl(this);for(t=t||[];this.pos<e;)t.push(this.readFloat());return t},readPackedDouble:function(t){if(this.type!==el.Bytes)return t.push(this.readDouble());var e=rl(this);for(t=t||[];this.pos<e;)t.push(this.readDouble());return t},readPackedFixed32:function(t){if(this.type!==el.Bytes)return t.push(this.readFixed32());var e=rl(this);for(t=t||[];this.pos<e;)t.push(this.readFixed32());return t},readPackedSFixed32:function(t){if(this.type!==el.Bytes)return t.push(this.readSFixed32());var e=rl(this);for(t=t||[];this.pos<e;)t.push(this.readSFixed32());return t},readPackedFixed64:function(t){if(this.type!==el.Bytes)return t.push(this.readFixed64());var e=rl(this);for(t=t||[];this.pos<e;)t.push(this.readFixed64());return t},readPackedSFixed64:function(t){if(this.type!==el.Bytes)return t.push(this.readSFixed64());var e=rl(this);for(t=t||[];this.pos<e;)t.push(this.readSFixed64());return t},skip:function(t){var e=7&t;if(e===el.Varint)for(;this.buf[this.pos++]>127;);else if(e===el.Bytes)this.pos=this.readVarint()+this.pos;else if(e===el.Fixed32)this.pos+=4;else{if(e!==el.Fixed64)throw new Error(\"Unimplemented type: \"+e);this.pos+=8}},writeTag:function(t,e){this.writeVarint(t<<3|e)},realloc:function(t){for(var e=this.length||16;e<this.pos+t;)e*=2;if(e!==this.length){var r=new Uint8Array(e);r.set(this.buf),this.buf=r,this.length=e}},finish:function(){return this.length=this.pos,this.pos=0,this.buf.subarray(0,this.length)},writeFixed32:function(t){this.realloc(4),gl(this.buf,t,this.pos),this.pos+=4},writeSFixed32:function(t){this.realloc(4),gl(this.buf,t,this.pos),this.pos+=4},writeFixed64:function(t){this.realloc(8),gl(this.buf,-1&t,this.pos),gl(this.buf,Math.floor(t*(1/4294967296)),this.pos+4),this.pos+=8},writeSFixed64:function(t){this.realloc(8),gl(this.buf,-1&t,this.pos),gl(this.buf,Math.floor(t*(1/4294967296)),this.pos+4),this.pos+=8},writeVarint:function(t){(t=+t||0)>268435455||t<0?function(t,e){var r,n;if(t>=0?(r=t%4294967296|0,n=t/4294967296|0):(n=~(-t/4294967296),4294967295^(r=~(-t%4294967296))?r=r+1|0:(r=0,n=n+1|0)),t>=0x10000000000000000||t<-0x10000000000000000)throw new Error(\"Given varint doesn't fit into 10 bytes\");e.realloc(10),function(t,e,r){r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos]=127&t}(r,0,e),function(t,e){var r=(7&t)<<4;e.buf[e.pos++]|=r|((t>>>=3)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t)))))}(n,e)}(t,this):(this.realloc(4),this.buf[this.pos++]=127&t|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=t>>>7&127))))},writeSVarint:function(t){this.writeVarint(t<0?2*-t-1:2*t)},writeBoolean:function(t){this.writeVarint(Boolean(t))},writeString:function(t){t=String(t),this.realloc(4*t.length),this.pos++;var e=this.pos;this.pos=function(t,e,r){for(var n,a,i=0;i<e.length;i++){if((n=e.charCodeAt(i))>55295&&n<57344){if(!a){n>56319||i+1===e.length?(t[r++]=239,t[r++]=191,t[r++]=189):a=n;continue}if(n<56320){t[r++]=239,t[r++]=191,t[r++]=189,a=n;continue}n=a-55296<<10|n-56320|65536,a=null}else a&&(t[r++]=239,t[r++]=191,t[r++]=189,a=null);n<128?t[r++]=n:(n<2048?t[r++]=n>>6|192:(n<65536?t[r++]=n>>12|224:(t[r++]=n>>18|240,t[r++]=n>>12&63|128),t[r++]=n>>6&63|128),t[r++]=63&n|128)}return r}(this.buf,t,this.pos);var r=this.pos-e;r>=128&&al(e,r,this),this.pos=e-1,this.writeVarint(r),this.pos+=r},writeFloat:function(t){this.realloc(4),$s(this.buf,t,this.pos,!0,23,4),this.pos+=4},writeDouble:function(t){this.realloc(8),$s(this.buf,t,this.pos,!0,52,8),this.pos+=8},writeBytes:function(t){var e=t.length;this.writeVarint(e),this.realloc(e);for(var r=0;r<e;r++)this.buf[this.pos++]=t[r]},writeRawMessage:function(t,e){this.pos++;var r=this.pos;t(e,this);var n=this.pos-r;n>=128&&al(r,n,this),this.pos=r-1,this.writeVarint(n),this.pos+=n},writeMessage:function(t,e,r){this.writeTag(t,el.Bytes),this.writeRawMessage(e,r)},writePackedVarint:function(t,e){e.length&&this.writeMessage(t,il,e)},writePackedSVarint:function(t,e){e.length&&this.writeMessage(t,ol,e)},writePackedBoolean:function(t,e){e.length&&this.writeMessage(t,cl,e)},writePackedFloat:function(t,e){e.length&&this.writeMessage(t,sl,e)},writePackedDouble:function(t,e){e.length&&this.writeMessage(t,ll,e)},writePackedFixed32:function(t,e){e.length&&this.writeMessage(t,ul,e)},writePackedSFixed32:function(t,e){e.length&&this.writeMessage(t,hl,e)},writePackedFixed64:function(t,e){e.length&&this.writeMessage(t,fl,e)},writePackedSFixed64:function(t,e){e.length&&this.writeMessage(t,pl,e)},writeBytesField:function(t,e){this.writeTag(t,el.Bytes),this.writeBytes(e)},writeFixed32Field:function(t,e){this.writeTag(t,el.Fixed32),this.writeFixed32(e)},writeSFixed32Field:function(t,e){this.writeTag(t,el.Fixed32),this.writeSFixed32(e)},writeFixed64Field:function(t,e){this.writeTag(t,el.Fixed64),this.writeFixed64(e)},writeSFixed64Field:function(t,e){this.writeTag(t,el.Fixed64),this.writeSFixed64(e)},writeVarintField:function(t,e){this.writeTag(t,el.Varint),this.writeVarint(e)},writeSVarintField:function(t,e){this.writeTag(t,el.Varint),this.writeSVarint(e)},writeStringField:function(t,e){this.writeTag(t,el.Bytes),this.writeString(e)},writeFloatField:function(t,e){this.writeTag(t,el.Fixed32),this.writeFloat(e)},writeDoubleField:function(t,e){this.writeTag(t,el.Fixed64),this.writeDouble(e)},writeBooleanField:function(t,e){this.writeVarintField(t,Boolean(e))}};var ml=3;function yl(t,e,r){1===t&&r.readMessage(xl,e)}function xl(t,e,r){if(3===t){var n=r.readMessage(bl,{}),a=n.id,i=n.bitmap,o=n.width,s=n.height,l=n.left,c=n.top,u=n.advance;e.push({id:a,bitmap:new Pi({width:o+2*ml,height:s+2*ml},i),metrics:{width:o,height:s,left:l,top:c,advance:u}})}}function bl(t,e,r){1===t?e.id=r.readVarint():2===t?e.bitmap=r.readBytes():3===t?e.width=r.readVarint():4===t?e.height=r.readVarint():5===t?e.left=r.readSVarint():6===t?e.top=r.readSVarint():7===t&&(e.advance=r.readVarint())}var _l=ml,wl=function(t){var e=this;this._callback=t,this._triggered=!1,\"undefined\"!=typeof MessageChannel&&(this._channel=new MessageChannel,this._channel.port2.onmessage=function(){e._triggered=!1,e._callback()})};wl.prototype.trigger=function(){var t=this;this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout(function(){t._triggered=!1,t._callback()},0))};var kl=function(t,e,r){this.target=t,this.parent=e,this.mapId=r,this.callbacks={},this.tasks={},this.taskQueue=[],this.cancelCallbacks={},v([\"receive\",\"process\"],this),this.invoker=new wl(this.process),this.target.addEventListener(\"message\",this.receive,!1)};function Tl(t,e,r){var n=2*Math.PI*6378137/256/Math.pow(2,r);return[t*n-2*Math.PI*6378137/2,e*n-2*Math.PI*6378137/2]}kl.prototype.send=function(t,e,r,n){var a=this,i=Math.round(1e18*Math.random()).toString(36).substring(0,10);r&&(this.callbacks[i]=r);var o=[];return this.target.postMessage({id:i,type:t,hasCallback:!!r,targetMapId:n,sourceMapId:this.mapId,data:vn(e,o)},o),{cancel:function(){r&&delete a.callbacks[i],a.target.postMessage({id:i,type:\"<cancel>\",targetMapId:n,sourceMapId:a.mapId})}}},kl.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if(\"<cancel>\"===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()},kl.prototype.process=function(){var t=this;if(this.taskQueue.length){var e=this.taskQueue.shift(),r=this.tasks[e];if(delete this.tasks[e],this.taskQueue.length&&this.invoker.trigger(),r)if(\"<response>\"===r.type){var n=this.callbacks[e];delete this.callbacks[e],n&&(r.error?n(mn(r.error)):n(null,mn(r.data)))}else{var a=!1,i=r.hasCallback?function(r,n){a=!0,delete t.cancelCallbacks[e];var i=[];t.target.postMessage({id:e,type:\"<response>\",sourceMapId:t.mapId,error:r?vn(r):null,data:vn(n,i)},i)}:function(t){a=!0},o=null,s=mn(r.data);if(this.parent[r.type])o=this.parent[r.type](r.sourceMapId,s,i);else if(this.parent.getWorkerSource){var l=r.type.split(\".\");o=this.parent.getWorkerSource(r.sourceMapId,l[0],s.source)[l[1]](s,i)}else i(new Error(\"Could not find function \"+r.type));!a&&o&&o.cancel&&(this.cancelCallbacks[e]=o.cancel)}}},kl.prototype.remove=function(){this.target.removeEventListener(\"message\",this.receive,!1)};var Ml=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Ml.prototype.setNorthEast=function(t){return this._ne=t instanceof Al?new Al(t.lng,t.lat):Al.convert(t),this},Ml.prototype.setSouthWest=function(t){return this._sw=t instanceof Al?new Al(t.lng,t.lat):Al.convert(t),this},Ml.prototype.extend=function(t){var e,r,n=this._sw,a=this._ne;if(t instanceof Al)e=t,r=t;else{if(!(t instanceof Ml))return Array.isArray(t)?t.every(Array.isArray)?this.extend(Ml.convert(t)):this.extend(Al.convert(t)):this;if(e=t._sw,r=t._ne,!e||!r)return this}return n||a?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),a.lng=Math.max(r.lng,a.lng),a.lat=Math.max(r.lat,a.lat)):(this._sw=new Al(e.lng,e.lat),this._ne=new Al(r.lng,r.lat)),this},Ml.prototype.getCenter=function(){return new Al((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Ml.prototype.getSouthWest=function(){return this._sw},Ml.prototype.getNorthEast=function(){return this._ne},Ml.prototype.getNorthWest=function(){return new Al(this.getWest(),this.getNorth())},Ml.prototype.getSouthEast=function(){return new Al(this.getEast(),this.getSouth())},Ml.prototype.getWest=function(){return this._sw.lng},Ml.prototype.getSouth=function(){return this._sw.lat},Ml.prototype.getEast=function(){return this._ne.lng},Ml.prototype.getNorth=function(){return this._ne.lat},Ml.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Ml.prototype.toString=function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"},Ml.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Ml.convert=function(t){return!t||t instanceof Ml?t:new Ml(t)};var Al=function(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")};Al.prototype.wrap=function(){return new Al(u(this.lng,-180,180),this.lat)},Al.prototype.toArray=function(){return[this.lng,this.lat]},Al.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},Al.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Ml(new Al(this.lng-r,this.lat-e),new Al(this.lng+r,this.lat+e))},Al.convert=function(t){if(t instanceof Al)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new Al(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&\"object\"==typeof t&&null!==t)return new Al(Number(\"lng\"in t?t.lng:t.lon),Number(t.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: <lng>, lat: <lat>}, an object {lon: <lng>, lat: <lat>}, or an array of [<lng>, <lat>]\")};var Sl=2*Math.PI*6378137;function El(t){return Sl*Math.cos(t*Math.PI/180)}function Ll(t){return(180+t)/360}function Cl(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Pl(t,e){return t/El(e)}function Ol(t){var e=180-360*t;return 360/Math.PI*Math.atan(Math.exp(e*Math.PI/180))-90}var zl=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};zl.fromLngLat=function(t,e){void 0===e&&(e=0);var r=Al.convert(t);return new zl(Ll(r.lng),Cl(r.lat),Pl(e,r.lat))},zl.prototype.toLngLat=function(){return new Al(360*this.x-180,Ol(this.y))},zl.prototype.toAltitude=function(){return this.z*El(Ol(this.y))},zl.prototype.meterInMercatorCoordinateUnits=function(){return 1/Sl*(t=Ol(this.y),1/Math.cos(t*Math.PI/180));var t};var Il=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=Fl(0,t,e,r)};Il.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},Il.prototype.url=function(t,e){var r,n,a,i,o,s=(r=this.x,n=this.y,a=this.z,i=Tl(256*r,256*(n=Math.pow(2,a)-n-1),a),o=Tl(256*(r+1),256*(n+1),a),i[0]+\",\"+i[1]+\",\"+o[0]+\",\"+o[1]),l=function(t,e,r){for(var n,a=\"\",i=t;i>0;i--)a+=(e&(n=1<<i-1)?1:0)+(r&n?2:0);return a}(this.z,this.x,this.y);return t[(this.x+this.y)%t.length].replace(\"{prefix}\",(this.x%16).toString(16)+(this.y%16).toString(16)).replace(\"{z}\",String(this.z)).replace(\"{x}\",String(this.x)).replace(\"{y}\",String(\"tms\"===e?Math.pow(2,this.z)-this.y-1:this.y)).replace(\"{quadkey}\",l).replace(\"{bbox-epsg-3857}\",s)},Il.prototype.getTilePoint=function(t){var e=Math.pow(2,this.z);return new a((t.x*e-this.x)*ei,(t.y*e-this.y)*ei)};var Dl=function(t,e){this.wrap=t,this.canonical=e,this.key=Fl(t,e.z,e.x,e.y)},Rl=function(t,e,r,n,a){this.overscaledZ=t,this.wrap=e,this.canonical=new Il(r,+n,+a),this.key=Fl(e,t,n,a)};function Fl(t,e,r,n){(t*=2)<0&&(t=-1*t-1);var a=1<<e;return 32*(a*a*t+a*n+r)+e}Rl.prototype.equals=function(t){return this.overscaledZ===t.overscaledZ&&this.wrap===t.wrap&&this.canonical.equals(t.canonical)},Rl.prototype.scaledTo=function(t){var e=this.canonical.z-t;return t>this.canonical.z?new Rl(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new Rl(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},Rl.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ<this.overscaledZ&&t.canonical.x===this.canonical.x>>e&&t.canonical.y===this.canonical.y>>e},Rl.prototype.children=function(t){if(this.overscaledZ>=t)return[new Rl(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new Rl(e,this.wrap,e,r,n),new Rl(e,this.wrap,e,r+1,n),new Rl(e,this.wrap,e,r,n+1),new Rl(e,this.wrap,e,r+1,n+1)]},Rl.prototype.isLessThan=function(t){return this.wrap<t.wrap||!(this.wrap>t.wrap)&&(this.overscaledZ<t.overscaledZ||!(this.overscaledZ>t.overscaledZ)&&(this.canonical.x<t.canonical.x||!(this.canonical.x>t.canonical.x)&&this.canonical.y<t.canonical.y))},Rl.prototype.wrapped=function(){return new Rl(this.overscaledZ,0,this.canonical.z,this.canonical.x,this.canonical.y)},Rl.prototype.unwrapTo=function(t){return new Rl(this.overscaledZ,t,this.canonical.z,this.canonical.x,this.canonical.y)},Rl.prototype.overscaleFactor=function(){return Math.pow(2,this.overscaledZ-this.canonical.z)},Rl.prototype.toUnwrapped=function(){return new Dl(this.wrap,this.canonical)},Rl.prototype.toString=function(){return this.overscaledZ+\"/\"+this.canonical.x+\"/\"+this.canonical.y},Rl.prototype.getTilePoint=function(t){return this.canonical.getTilePoint(new zl(t.x-this.wrap,t.y))},dn(\"CanonicalTileID\",Il),dn(\"OverscaledTileID\",Rl,{omit:[\"posMatrix\"]});var Bl=function(t,e,r){if(this.uid=t,e.height!==e.width)throw new RangeError(\"DEM tiles must be square\");if(r&&\"mapbox\"!==r&&\"terrarium\"!==r)return w('\"'+r+'\" is not a valid encoding type. Valid types include \"mapbox\" and \"terrarium\".');var n=this.dim=e.height;this.stride=this.dim+2,this.data=new Int32Array(this.stride*this.stride);for(var a=e.data,i=\"terrarium\"===r?this._unpackTerrarium:this._unpackMapbox,o=0;o<n;o++)for(var s=0;s<n;s++){var l=4*(o*n+s);this.set(s,o,i(a[l],a[l+1],a[l+2]))}for(var c=0;c<n;c++)this.set(-1,c,this.get(0,c)),this.set(n,c,this.get(n-1,c)),this.set(c,-1,this.get(c,0)),this.set(c,n,this.get(c,n-1));this.set(-1,-1,this.get(0,0)),this.set(n,-1,this.get(n-1,0)),this.set(-1,n,this.get(0,n-1)),this.set(n,n,this.get(n-1,n-1))};Bl.prototype.set=function(t,e,r){this.data[this._idx(t,e)]=r+65536},Bl.prototype.get=function(t,e){return this.data[this._idx(t,e)]-65536},Bl.prototype._idx=function(t,e){if(t<-1||t>=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError(\"out of range source coordinates for DEM data\");return(e+1)*this.stride+(t+1)},Bl.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},Bl.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},Bl.prototype.getPixels=function(){return new Oi({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},Bl.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error(\"dem dimension mismatch\");var n=e*this.dim,a=e*this.dim+this.dim,i=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=a-1;break;case 1:a=n+1}switch(r){case-1:i=o-1;break;case 1:o=i+1}for(var s=-e*this.dim,l=-r*this.dim,c=i;c<o;c++)for(var u=n;u<a;u++)this.set(u,c,t.get(u+s,c+l))},dn(\"DEMData\",Bl);var Nl=Jn([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]),jl=function(t){this._stringToNumber={},this._numberToString=[];for(var e=0;e<t.length;e++){var r=t[e];this._stringToNumber[r]=e,this._numberToString[e]=r}};jl.prototype.encode=function(t){return this._stringToNumber[t]},jl.prototype.decode=function(t){return this._numberToString[t]};var Vl=function(t,e,r,n){this.type=\"Feature\",this._vectorTileFeature=t,t._z=e,t._x=r,t._y=n,this.properties=t.properties,null!=t.id&&(this.id=t.id)},Ul={geometry:{configurable:!0}};Ul.geometry.get=function(){return void 0===this._geometry&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry},Ul.geometry.set=function(t){this._geometry=t},Vl.prototype.toJSON=function(){var t={geometry:this.geometry};for(var e in this)\"_geometry\"!==e&&\"_vectorTileFeature\"!==e&&(t[e]=this[e]);return t},Object.defineProperties(Vl.prototype,Ul);var ql=function(){this.state={},this.stateChanges={},this.deletedStates={}};ql.prototype.updateState=function(t,e,r){var n=String(e);if(this.stateChanges[t]=this.stateChanges[t]||{},this.stateChanges[t][n]=this.stateChanges[t][n]||{},h(this.stateChanges[t][n],r),null===this.deletedStates[t])for(var a in this.deletedStates[t]={},this.state[t])a!==n&&(this.deletedStates[t][a]=null);else if(this.deletedStates[t]&&null===this.deletedStates[t][n])for(var i in this.deletedStates[t][n]={},this.state[t][n])r[i]||(this.deletedStates[t][n][i]=null);else for(var o in r)this.deletedStates[t]&&this.deletedStates[t][n]&&null===this.deletedStates[t][n][o]&&delete this.deletedStates[t][n][o]},ql.prototype.removeFeatureState=function(t,e,r){if(null!==this.deletedStates[t]){var n=String(e);if(this.deletedStates[t]=this.deletedStates[t]||{},r&&void 0!==e&&e>=0)null!==this.deletedStates[t][n]&&(this.deletedStates[t][n]=this.deletedStates[t][n]||{},this.deletedStates[t][n][r]=null);else if(void 0!==e&&e>=0)if(this.stateChanges[t]&&this.stateChanges[t][n])for(r in this.deletedStates[t][n]={},this.stateChanges[t][n])this.deletedStates[t][n][r]=null;else this.deletedStates[t][n]=null;else this.deletedStates[t]=null}},ql.prototype.getState=function(t,e){var r=String(e),n=this.state[t]||{},a=this.stateChanges[t]||{},i=h({},n[r],a[r]);if(null===this.deletedStates[t])return{};if(this.deletedStates[t]){var o=this.deletedStates[t][e];if(null===o)return{};for(var s in o)delete i[s]}return i},ql.prototype.initializeTileState=function(t,e){t.setFeatureState(this.state,e)},ql.prototype.coalesceChanges=function(t,e){var r={};for(var n in this.stateChanges){this.state[n]=this.state[n]||{};var a={};for(var i in this.stateChanges[n])this.state[n][i]||(this.state[n][i]={}),h(this.state[n][i],this.stateChanges[n][i]),a[i]=this.state[n][i];r[n]=a}for(var o in this.deletedStates){this.state[o]=this.state[o]||{};var s={};if(null===this.deletedStates[o])for(var l in this.state[o])s[l]={},this.state[o][l]={};else for(var c in this.deletedStates[o]){if(null===this.deletedStates[o][c])this.state[o][c]={};else for(var u=0,f=Object.keys(this.deletedStates[o][c]);u<f.length;u+=1){var p=f[u];delete this.state[o][c][p]}s[c]=this.state[o][c]}r[o]=r[o]||{},h(r[o],s)}if(this.stateChanges={},this.deletedStates={},0!==Object.keys(r).length)for(var d in t)t[d].setFeatureState(r,e)};var Hl=function(t,e,r){this.tileID=t,this.x=t.canonical.x,this.y=t.canonical.y,this.z=t.canonical.z,this.grid=e||new cn(ei,16,0),this.grid3D=new cn(ei,16,0),this.featureIndexArray=r||new Ca};function Gl(t){for(var e=1/0,r=1/0,n=-1/0,a=-1/0,i=0,o=t;i<o.length;i+=1){var s=o[i];e=Math.min(e,s.x),r=Math.min(r,s.y),n=Math.max(n,s.x),a=Math.max(a,s.y)}return{minX:e,minY:r,maxX:n,maxY:a}}function Yl(t,e){return e-t}Hl.prototype.insert=function(t,e,r,n,a,i){var o=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(r,n,a);for(var s=i?this.grid3D:this.grid,l=0;l<e.length;l++){for(var c=e[l],u=[1/0,1/0,-1/0,-1/0],h=0;h<c.length;h++){var f=c[h];u[0]=Math.min(u[0],f.x),u[1]=Math.min(u[1],f.y),u[2]=Math.max(u[2],f.x),u[3]=Math.max(u[3],f.y)}u[0]<ei&&u[1]<ei&&u[2]>=0&&u[3]>=0&&s.insert(o,u[0],u[1],u[2],u[3])}},Hl.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new Io.VectorTile(new tl(this.rawTileData)).layers,this.sourceLayerCoder=new jl(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers},Hl.prototype.query=function(t,e,r){var n=this;this.loadVTLayers();for(var i=t.params||{},o=ei/t.tileSize/t.scale,s=Rr(i.filter),l=t.queryGeometry,c=t.queryPadding*o,u=Gl(l),h=this.grid.query(u.minX-c,u.minY-c,u.maxX+c,u.maxY+c),f=Gl(t.cameraQueryGeometry),p=0,d=this.grid3D.query(f.minX-c,f.minY-c,f.maxX+c,f.maxY+c,function(e,r,n,i){return function(t,e,r,n,i){for(var o=0,s=t;o<s.length;o+=1){var l=s[o];if(e<=l.x&&r<=l.y&&n>=l.x&&i>=l.y)return!0}var c=[new a(e,r),new a(e,i),new a(n,i),new a(n,r)];if(t.length>2)for(var u=0,h=c;u<h.length;u+=1)if(gi(t,h[u]))return!0;for(var f=0;f<t.length-1;f++)if(vi(t[f],t[f+1],c))return!0;return!1}(t.cameraQueryGeometry,e-c,r-c,n+c,i+c)});p<d.length;p+=1){var g=d[p];h.push(g)}h.sort(Yl);for(var v,m={},y=function(a){var c=h[a];if(c!==v){v=c;var u=n.featureIndexArray.get(c),f=null;n.loadMatchingFeature(m,u.bucketIndex,u.sourceLayerIndex,u.featureIndex,s,i.layers,e,function(e,a){f||(f=ni(e));var i={};return e.id&&(i=r.getState(a.sourceLayer||\"_geojsonTileLayer\",e.id)),a.queryIntersectsFeature(l,e,i,f,n.z,t.transform,o,t.pixelPosMatrix)})}},x=0;x<h.length;x++)y(x);return m},Hl.prototype.loadMatchingFeature=function(t,e,r,n,a,i,o,s){var l=this.bucketLayerIDs[e];if(!i||function(t,e){for(var r=0;r<t.length;r++)if(e.indexOf(t[r])>=0)return!0;return!1}(i,l)){var c=this.sourceLayerCoder.decode(r),u=this.vtLayers[c].feature(n);if(a(new Pn(this.tileID.overscaledZ),u))for(var h=0;h<l.length;h++){var f=l[h];if(!(i&&i.indexOf(f)<0)){var p=o[f];if(p){var d=!s||s(u,p);if(d){var g=new Vl(u,this.z,this.x,this.y);g.layer=p.serialize();var v=t[f];void 0===v&&(v=t[f]=[]),v.push({featureIndex:n,feature:g,intersectionZ:d})}}}}}},Hl.prototype.lookupSymbolFeatures=function(t,e,r,n,a,i){var o={};this.loadVTLayers();for(var s=Rr(n),l=0,c=t;l<c.length;l+=1){var u=c[l];this.loadMatchingFeature(o,e,r,u,s,a,i)}return o},Hl.prototype.hasLayer=function(t){for(var e=0,r=this.bucketLayerIDs;e<r.length;e+=1)for(var n=0,a=r[e];n<a.length;n+=1)if(t===a[n])return!0;return!1},dn(\"FeatureIndex\",Hl,{omit:[\"rawTileData\",\"sourceLayerCoder\"]});var Wl=function(t,e){this.tileID=t,this.uid=p(),this.uses=0,this.tileSize=e,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.expiredRequestCount=0,this.state=\"loading\"};function Xl(t,e,r,n,a){if(void 0===e.segment)return!0;for(var i=e,o=e.segment+1,s=0;s>-r/2;){if(--o<0)return!1;s-=t[o].dist(i),i=t[o]}s+=t[o].dist(t[o+1]),o++;for(var l=[],c=0;s<r/2;){var u=t[o-1],h=t[o],f=t[o+1];if(!f)return!1;var p=u.angleTo(h)-h.angleTo(f);for(p=Math.abs((p+3*Math.PI)%(2*Math.PI)-Math.PI),l.push({distance:s,angleDelta:p}),c+=p;s-l[0].distance>n;)c-=l.shift().angleDelta;if(c>a)return!1;o++,s+=h.dist(f)}return!0}function Zl(t){for(var e=0,r=0;r<t.length-1;r++)e+=t[r].dist(t[r+1]);return e}function Jl(t,e,r){return t?.6*e*r:0}function Kl(t,e){return Math.max(t?t.right-t.left:0,e?e.right-e.left:0)}function Ql(t,e,r,n,a,i){for(var o=Jl(r,a,i),s=Kl(r,n)*i,l=0,c=Zl(t)/2,u=0;u<t.length-1;u++){var h=t[u],f=t[u+1],p=h.dist(f);if(l+p>c){var d=(c-l)/p,g=ye(h.x,f.x,d),v=ye(h.y,f.y,d),m=new bs(g,v,f.angleTo(h),u);return m._round(),!o||Xl(t,m,s,o,e)?m:void 0}l+=p}}function $l(t,e,r,n,a,i,o,s,l){var c=Jl(n,i,o),u=Kl(n,a),h=u*o,f=0===t[0].x||t[0].x===l||0===t[0].y||t[0].y===l;return e-h<e/4&&(e=h+e/4),function t(e,r,n,a,i,o,s,l,c){for(var u=o/2,h=Zl(e),f=0,p=r-n,d=[],g=0;g<e.length-1;g++){for(var v=e[g],m=e[g+1],y=v.dist(m),x=m.angleTo(v);p+n<f+y;){var b=((p+=n)-f)/y,_=ye(v.x,m.x,b),w=ye(v.y,m.y,b);if(_>=0&&_<c&&w>=0&&w<c&&p-u>=0&&p+u<=h){var k=new bs(_,w,x,g);k._round(),a&&!Xl(e,k,o,a,i)||d.push(k)}}f+=y}return l||d.length||s||(d=t(e,f/2,n,a,i,o,s,!0,c)),d}(t,f?e/2*s%e:(u/2+2*i)*o*s%e,e,c,r,h,f,!1,l)}Wl.prototype.registerFadeDuration=function(t){var e=t+this.timeAdded;e<I.now()||this.fadeEndTime&&e<this.fadeEndTime||(this.fadeEndTime=e)},Wl.prototype.wasRequested=function(){return\"errored\"===this.state||\"loaded\"===this.state||\"reloading\"===this.state},Wl.prototype.loadVectorData=function(t,e,r){if(this.hasData()&&this.unloadVectorData(),this.state=\"loaded\",t){for(var n in t.featureIndex&&(this.latestFeatureIndex=t.featureIndex,t.rawTileData?(this.latestRawTileData=t.rawTileData,this.latestFeatureIndex.rawTileData=t.rawTileData):this.latestRawTileData&&(this.latestFeatureIndex.rawTileData=this.latestRawTileData)),this.collisionBoxArray=t.collisionBoxArray,this.buckets=function(t,e){var r={};if(!e)return r;for(var n=function(){var t=i[a],n=t.layerIds.map(function(t){return e.getLayer(t)}).filter(Boolean);if(0!==n.length){t.layers=n,t.stateDependentLayerIds&&(t.stateDependentLayers=t.stateDependentLayerIds.map(function(t){return n.filter(function(e){return e.id===t})[0]}));for(var o=0,s=n;o<s.length;o+=1){var l=s[o];r[l.id]=t}}},a=0,i=t;a<i.length;a+=1)n();return r}(t.buckets,e.style),this.hasSymbolBuckets=!1,this.buckets){var a=this.buckets[n];if(a instanceof Os){if(this.hasSymbolBuckets=!0,!r)break;a.justReloaded=!0}}for(var i in this.queryPadding=0,this.buckets){var o=this.buckets[i];this.queryPadding=Math.max(this.queryPadding,e.style.getLayer(i).queryRadius(o))}t.imageAtlas&&(this.imageAtlas=t.imageAtlas),t.glyphAtlasImage&&(this.glyphAtlasImage=t.glyphAtlasImage)}else this.collisionBoxArray=new ba},Wl.prototype.unloadVectorData=function(){for(var t in this.buckets)this.buckets[t].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state=\"unloaded\"},Wl.prototype.unloadDEMData=function(){this.dem=null,this.neighboringTiles=null,this.state=\"unloaded\"},Wl.prototype.getBucket=function(t){return this.buckets[t.id]},Wl.prototype.upload=function(t){for(var e in this.buckets){var r=this.buckets[e];r.uploadPending()&&r.upload(t)}var n=t.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new Ks(t,this.imageAtlas.image,n.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new Ks(t,this.glyphAtlasImage,n.ALPHA),this.glyphAtlasImage=null)},Wl.prototype.prepare=function(t){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(t,this.imageAtlasTexture)},Wl.prototype.queryRenderedFeatures=function(t,e,r,n,a,i,o,s,l){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:r,cameraQueryGeometry:n,scale:a,tileSize:this.tileSize,pixelPosMatrix:l,transform:o,params:i,queryPadding:this.queryPadding*s},t,e):{}},Wl.prototype.querySourceFeatures=function(t,e){if(this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData){var r=this.latestFeatureIndex.loadVTLayers(),n=e?e.sourceLayer:\"\",a=r._geojsonTileLayer||r[n];if(a)for(var i=Rr(e&&e.filter),o=this.tileID.canonical,s=o.z,l=o.x,c=o.y,u={z:s,x:l,y:c},h=0;h<a.length;h++){var f=a.feature(h);if(i(new Pn(this.tileID.overscaledZ),f)){var p=new Vl(f,s,l,c);p.tile=u,t.push(p)}}}},Wl.prototype.clearMask=function(){this.segments&&(this.segments.destroy(),delete this.segments),this.maskedBoundsBuffer&&(this.maskedBoundsBuffer.destroy(),delete this.maskedBoundsBuffer),this.maskedIndexBuffer&&(this.maskedIndexBuffer.destroy(),delete this.maskedIndexBuffer)},Wl.prototype.setMask=function(t,e){if(!o(this.mask,t)&&(this.mask=t,this.clearMask(),!o(t,{0:!0}))){var r=new $n,n=new da;this.segments=new Oa,this.segments.prepareSegment(0,r,n);for(var i=Object.keys(t),s=0;s<i.length;s++){var l=t[+i[s]],c=ei>>l.z,u=new a(l.x*c,l.y*c),h=new a(u.x+c,u.y+c),f=this.segments.prepareSegment(4,r,n);r.emplaceBack(u.x,u.y,u.x,u.y),r.emplaceBack(h.x,u.y,h.x,u.y),r.emplaceBack(u.x,h.y,u.x,h.y),r.emplaceBack(h.x,h.y,h.x,h.y);var p=f.vertexLength;n.emplaceBack(p,p+1,p+2),n.emplaceBack(p+1,p+2,p+3),f.vertexLength+=4,f.primitiveLength+=2}this.maskedBoundsBuffer=e.createVertexBuffer(r,Nl.members),this.maskedIndexBuffer=e.createIndexBuffer(n)}},Wl.prototype.hasData=function(){return\"loaded\"===this.state||\"reloading\"===this.state||\"expired\"===this.state},Wl.prototype.patternsLoaded=function(){return this.imageAtlas&&!!Object.keys(this.imageAtlas.patternPositions).length},Wl.prototype.setExpiryData=function(t){var e=this.expirationTime;if(t.cacheControl){var r=M(t.cacheControl);r[\"max-age\"]&&(this.expirationTime=Date.now()+1e3*r[\"max-age\"])}else t.expires&&(this.expirationTime=new Date(t.expires).getTime());if(this.expirationTime){var n=Date.now(),a=!1;if(this.expirationTime>n)a=!1;else if(e)if(this.expirationTime<e)a=!0;else{var i=this.expirationTime-e;i?this.expirationTime=n+Math.max(i,3e4):a=!0}else a=!0;a?(this.expiredRequestCount++,this.state=\"expired\"):this.expiredRequestCount=0}},Wl.prototype.getExpiryTimeout=function(){if(this.expirationTime)return this.expiredRequestCount?1e3*(1<<Math.min(this.expiredRequestCount-1,31)):Math.min(this.expirationTime-(new Date).getTime(),Math.pow(2,31)-1)},Wl.prototype.setFeatureState=function(t,e){if(this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData&&0!==Object.keys(t).length){var r=this.latestFeatureIndex.loadVTLayers();for(var n in this.buckets){var a=this.buckets[n],i=a.layers[0].sourceLayer||\"_geojsonTileLayer\",o=r[i],s=t[i];o&&s&&0!==Object.keys(s).length&&(a.update(s,o,this.imageAtlas&&this.imageAtlas.patternPositions||{}),e&&e.style&&(this.queryPadding=Math.max(this.queryPadding,e.style.getLayer(n).queryRadius(a))))}}},Wl.prototype.holdingForFade=function(){return void 0!==this.symbolFadeHoldUntil},Wl.prototype.symbolFadeFinished=function(){return!this.symbolFadeHoldUntil||this.symbolFadeHoldUntil<I.now()},Wl.prototype.clearFadeHold=function(){this.symbolFadeHoldUntil=void 0},Wl.prototype.setHoldDuration=function(t){this.symbolFadeHoldUntil=I.now()+t};var tc=function(t,e,r,n,i,o,s,l,c,u,h,f){var p=s.top*l-c,d=s.bottom*l+c,g=s.left*l-c,v=s.right*l+c;if(this.boxStartIndex=t.length,u){var m=d-p,y=v-g;m>0&&(m=Math.max(10*l,m),this._addLineCollisionCircles(t,e,r,r.segment,y,m,n,i,o,h))}else{if(f){var x=new a(g,p),b=new a(v,p),_=new a(g,d),w=new a(v,d),k=f*Math.PI/180;x._rotate(k),b._rotate(k),_._rotate(k),w._rotate(k),g=Math.min(x.x,b.x,_.x,w.x),v=Math.max(x.x,b.x,_.x,w.x),p=Math.min(x.y,b.y,_.y,w.y),d=Math.max(x.y,b.y,_.y,w.y)}t.emplaceBack(r.x,r.y,g,p,v,d,n,i,o,0,0)}this.boxEndIndex=t.length};tc.prototype._addLineCollisionCircles=function(t,e,r,n,a,i,o,s,l,c){var u=i/2,h=Math.floor(a/u)||1,f=1+.4*Math.log(c)/Math.LN2,p=Math.floor(h*f/2),d=-i/2,g=r,v=n+1,m=d,y=-a/2,x=y-a/4;do{if(--v<0){if(m>y)return;v=0;break}m-=e[v].dist(g),g=e[v]}while(m>x);for(var b=e[v].dist(e[v+1]),_=-p;_<h+p;_++){var w=_*u,k=y+w;if(w<0&&(k+=w),w>a&&(k+=w-a),!(k<m)){for(;m+b<k;){if(m+=b,++v+1>=e.length)return;b=e[v].dist(e[v+1])}var T=k-m,M=e[v],A=e[v+1].sub(M)._unit()._mult(T)._add(M)._round(),S=Math.abs(k-d)<u?0:.8*(k-d);t.emplaceBack(A.x,A.y,-i/2,-i/2,i/2,i/2,o,s,l,i/2,S)}}};var ec=function(t,e){if(void 0===t&&(t=[]),void 0===e&&(e=rc),this.data=t,this.length=this.data.length,this.compare=e,this.length>0)for(var r=(this.length>>1)-1;r>=0;r--)this._down(r)};function rc(t,e){return t<e?-1:t>e?1:0}function nc(t,e,r){void 0===e&&(e=1),void 0===r&&(r=!1);for(var n=1/0,i=1/0,o=-1/0,s=-1/0,l=t[0],c=0;c<l.length;c++){var u=l[c];(!c||u.x<n)&&(n=u.x),(!c||u.y<i)&&(i=u.y),(!c||u.x>o)&&(o=u.x),(!c||u.y>s)&&(s=u.y)}var h=o-n,f=s-i,p=Math.min(h,f),d=p/2,g=new ec([],ac);if(0===p)return new a(n,i);for(var v=n;v<o;v+=p)for(var m=i;m<s;m+=p)g.push(new ic(v+d,m+d,d,t));for(var y=function(t){for(var e=0,r=0,n=0,a=t[0],i=0,o=a.length,s=o-1;i<o;s=i++){var l=a[i],c=a[s],u=l.x*c.y-c.x*l.y;r+=(l.x+c.x)*u,n+=(l.y+c.y)*u,e+=3*u}return new ic(r/e,n/e,0,t)}(t),x=g.length;g.length;){var b=g.pop();(b.d>y.d||!y.d)&&(y=b,r&&console.log(\"found best %d after %d probes\",Math.round(1e4*b.d)/1e4,x)),b.max-y.d<=e||(d=b.h/2,g.push(new ic(b.p.x-d,b.p.y-d,d,t)),g.push(new ic(b.p.x+d,b.p.y-d,d,t)),g.push(new ic(b.p.x-d,b.p.y+d,d,t)),g.push(new ic(b.p.x+d,b.p.y+d,d,t)),x+=4)}return r&&(console.log(\"num probes: \"+x),console.log(\"best distance: \"+y.d)),y.p}function ac(t,e){return e.max-t.max}function ic(t,e,r,n){this.p=new a(t,e),this.h=r,this.d=function(t,e){for(var r=!1,n=1/0,a=0;a<e.length;a++)for(var i=e[a],o=0,s=i.length,l=s-1;o<s;l=o++){var c=i[o],u=i[l];c.y>t.y!=u.y>t.y&&t.x<(u.x-c.x)*(t.y-c.y)/(u.y-c.y)+c.x&&(r=!r),n=Math.min(n,pi(t,c,u))}return(r?1:-1)*Math.sqrt(n)}(this.p,n),this.max=this.d+this.h*Math.SQRT2}ec.prototype.push=function(t){this.data.push(t),this.length++,this._up(this.length-1)},ec.prototype.pop=function(){if(0!==this.length){var t=this.data[0],e=this.data.pop();return this.length--,this.length>0&&(this.data[0]=e,this._down(0)),t}},ec.prototype.peek=function(){return this.data[0]},ec.prototype._up=function(t){for(var e=this.data,r=this.compare,n=e[t];t>0;){var a=t-1>>1,i=e[a];if(r(n,i)>=0)break;e[t]=i,t=a}e[t]=n},ec.prototype._down=function(t){for(var e=this.data,r=this.compare,n=this.length>>1,a=e[t];t<n;){var i=1+(t<<1),o=e[i],s=i+1;if(s<this.length&&r(e[s],o)<0&&(i=s,o=e[s]),r(o,a)>=0)break;e[t]=o,t=i}e[t]=a};var oc=e(function(t){t.exports=function(t,e){var r,n,a,i,o,s,l,c;for(r=3&t.length,n=t.length-r,a=e,o=3432918353,s=461845907,c=0;c<n;)l=255&t.charCodeAt(c)|(255&t.charCodeAt(++c))<<8|(255&t.charCodeAt(++c))<<16|(255&t.charCodeAt(++c))<<24,++c,a=27492+(65535&(i=5*(65535&(a=(a^=l=(65535&(l=(l=(65535&l)*o+(((l>>>16)*o&65535)<<16)&4294967295)<<15|l>>>17))*s+(((l>>>16)*s&65535)<<16)&4294967295)<<13|a>>>19))+((5*(a>>>16)&65535)<<16)&4294967295))+((58964+(i>>>16)&65535)<<16);switch(l=0,r){case 3:l^=(255&t.charCodeAt(c+2))<<16;case 2:l^=(255&t.charCodeAt(c+1))<<8;case 1:a^=l=(65535&(l=(l=(65535&(l^=255&t.charCodeAt(c)))*o+(((l>>>16)*o&65535)<<16)&4294967295)<<15|l>>>17))*s+(((l>>>16)*s&65535)<<16)&4294967295}return a^=t.length,a=2246822507*(65535&(a^=a>>>16))+((2246822507*(a>>>16)&65535)<<16)&4294967295,a=3266489909*(65535&(a^=a>>>13))+((3266489909*(a>>>16)&65535)<<16)&4294967295,(a^=a>>>16)>>>0}}),sc=e(function(t){t.exports=function(t,e){for(var r,n=t.length,a=e^n,i=0;n>=4;)r=1540483477*(65535&(r=255&t.charCodeAt(i)|(255&t.charCodeAt(++i))<<8|(255&t.charCodeAt(++i))<<16|(255&t.charCodeAt(++i))<<24))+((1540483477*(r>>>16)&65535)<<16),a=1540483477*(65535&a)+((1540483477*(a>>>16)&65535)<<16)^(r=1540483477*(65535&(r^=r>>>24))+((1540483477*(r>>>16)&65535)<<16)),n-=4,++i;switch(n){case 3:a^=(255&t.charCodeAt(i+2))<<16;case 2:a^=(255&t.charCodeAt(i+1))<<8;case 1:a=1540483477*(65535&(a^=255&t.charCodeAt(i)))+((1540483477*(a>>>16)&65535)<<16)}return a=1540483477*(65535&(a^=a>>>13))+((1540483477*(a>>>16)&65535)<<16),(a^=a>>>15)>>>0}}),lc=oc,cc=oc,uc=sc;lc.murmur3=cc,lc.murmur2=uc;var hc=7;function fc(t,e){var r=0,n=0,a=e/Math.sqrt(2);switch(t){case\"top-right\":case\"top-left\":n=a-hc;break;case\"bottom-right\":case\"bottom-left\":n=-a+hc;break;case\"bottom\":n=-e+hc;break;case\"top\":n=e-hc}switch(t){case\"top-right\":case\"bottom-right\":r=-a;break;case\"top-left\":case\"bottom-left\":r=a;break;case\"left\":r=e;break;case\"right\":r=-e}return[r,n]}function pc(t){switch(t){case\"right\":case\"top-right\":case\"bottom-right\":return\"right\";case\"left\":case\"top-left\":case\"bottom-left\":return\"left\"}return\"center\"}var dc=65535;function gc(t,e,r,n,i,o,s,l,c,u,h,f,p){var d=function(t,e,r,n,i,o,s,l){for(var c=n.layout.get(\"text-rotate\").evaluate(o,{})*Math.PI/180,u=e.positionedGlyphs,h=[],f=0;f<u.length;f++){var p=u[f],d=s[p.fontStack],g=d&&d[p.glyph];if(g){var v=g.rect;if(v){var m=_l+1,y=g.metrics.advance*p.scale/2,x=i?[p.x+y,p.y]:[0,0],b=i?[0,0]:[p.x+y+r[0],p.y+r[1]],_=(i||l)&&p.vertical,w=[0,0];_&&(w=b,b=[0,0]);var k=(g.metrics.left-m)*p.scale-y+b[0],T=(-g.metrics.top-m)*p.scale+b[1],M=k+v.w*p.scale,A=T+v.h*p.scale,S=new a(k,T),E=new a(M,T),L=new a(k,A),C=new a(M,A);if(_){var P=new a(-y,y-e.yOffset),O=-Math.PI/2,z=ls/2-y,I=new a(5-e.yOffset-z,0),D=new(Function.prototype.bind.apply(a,[null].concat(w)));S._rotateAround(O,P)._add(I)._add(D),E._rotateAround(O,P)._add(I)._add(D),L._rotateAround(O,P)._add(I)._add(D),C._rotateAround(O,P)._add(I)._add(D)}if(c){var R=Math.sin(c),F=Math.cos(c),B=[F,-R,R,F];S._matMult(B),E._matMult(B),L._matMult(B),C._matMult(B)}h.push({tl:S,tr:E,bl:L,br:C,tex:v,writingMode:e.writingMode,glyphOffset:x,sectionIndex:p.sectionIndex})}}}return h}(0,r,s,n,i,o,f,t.allowVerticalPlacement),g=t.textSizeData,v=null;\"source\"===g.kind?(v=[_s*n.layout.get(\"text-size\").evaluate(o,{})])[0]>dc&&w(t.layerIds[0]+': Value for \"text-size\" is >= 256. Reduce your \"text-size\".'):\"composite\"===g.kind&&((v=[_s*p.compositeTextSizes[0].evaluate(o,{}),_s*p.compositeTextSizes[1].evaluate(o,{})])[0]>dc||v[1]>dc)&&w(t.layerIds[0]+': Value for \"text-size\" is >= 256. Reduce your \"text-size\".'),t.addSymbols(t.text,d,v,s,i,o,c,e,l.lineStartIndex,l.lineLength);for(var m=0,y=u;m<y.length;m+=1)h[y[m]]=t.text.placedSymbolArray.length-1;return 4*d.length}function vc(t){for(var e in t)return t[e];return null}function mc(t,e,r,n){var a=t.compareText;if(e in a){for(var i=a[e],o=i.length-1;o>=0;o--)if(n.dist(i[o])<r)return!0}else a[e]=[];return a[e].push(n),!1}t.Actor=kl,t.AlphaImage=Pi,t.CanonicalTileID=Il,t.CollisionBoxArray=ba,t.Color=Wt,t.DEMData=Bl,t.DataConstantProperty=jn,t.DictionaryCoder=jl,t.EXTENT=ei,t.ErrorEvent=wt,t.EvaluationParameters=Pn,t.Event=_t,t.Evented=kt,t.FeatureIndex=Hl,t.FillBucket=_o,t.FillExtrusionBucket=Bo,t.ImageAtlas=Ys,t.ImagePosition=Hs,t.LineBucket=Zo,t.LngLat=Al,t.LngLatBounds=Ml,t.MercatorCoordinate=zl,t.ONE_EM=ls,t.OverscaledTileID=Rl,t.Point=a,t.Point$1=a,t.ProgramConfiguration=Ka,t.Properties=Gn,t.Protobuf=tl,t.RGBAImage=Oi,t.RequestManager=V,t.ResourceType=lt,t.SegmentVector=Oa,t.SourceFeatureState=ql,t.StructArrayLayout1ui2=va,t.StructArrayLayout2i4=Qn,t.StructArrayLayout2ui4=ga,t.StructArrayLayout3ui6=da,t.StructArrayLayout4i8=$n,t.SymbolBucket=Os,t.Texture=Ks,t.Tile=Wl,t.Transitionable=In,t.Uniform1f=Ba,t.Uniform1i=Fa,t.Uniform2f=Na,t.Uniform3f=ja,t.Uniform4f=Va,t.UniformColor=Ua,t.UniformMatrix4f=Ha,t.UnwrappedTileID=Dl,t.ValidationError=Mt,t.WritingMode=cs,t.ZoomHistory=yn,t.addDynamicAttributes=Ls,t.asyncAll=function(t,e,r){if(!t.length)return r(null,[]);var n=t.length,a=new Array(t.length),i=null;t.forEach(function(t,o){e(t,function(t,e){t&&(i=t),a[o]=e,0==--n&&r(i,a)})})},t.bezier=s,t.bindAll=v,t.browser=I,t.cacheEntryPossiblyAdded=function(t){++st>at&&(t.getActor().send(\"enforceCacheSizeLimit\",nt),st=0)},t.clamp=c,t.clearTileCache=function(t){var e=self.caches.delete(rt);t&&e.catch(t).then(function(){return t()})},t.clone=function(t){var e=new ki(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e},t.clone$1=b,t.config=D,t.create=function(){var t=new ki(16);return ki!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[11]=0,t[12]=0,t[13]=0,t[14]=0),t[0]=1,t[5]=1,t[10]=1,t[15]=1,t},t.create$1=function(){var t=new ki(9);return ki!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[5]=0,t[6]=0,t[7]=0),t[0]=1,t[4]=1,t[8]=1,t},t.create$2=function(){var t=new ki(4);return ki!=Float32Array&&(t[1]=0,t[2]=0),t[0]=1,t[3]=1,t},t.createCommonjsModule=e,t.createExpression=kr,t.createLayout=Jn,t.createStyleLayer=function(t){return\"custom\"===t.type?new Vs(t):new Us[t.type](t)},t.deepEqual=o,t.ease=l,t.emitValidationErrors=ln,t.endsWith=m,t.enforceCacheSizeLimit=function(t){self.caches&&self.caches.open(rt).then(function(e){e.keys().then(function(r){for(var n=0;n<r.length-t;n++)e.delete(r[n])})})},t.evaluateRadialOffset=fc,t.evaluateSizeForFeature=ks,t.evaluateSizeForZoom=Ts,t.evented=Ln,t.extend=h,t.featureFilter=Rr,t.filterObject=x,t.fromRotation=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=r,t[2]=0,t[3]=-r,t[4]=n,t[5]=0,t[6]=0,t[7]=0,t[8]=1,t},t.getAnchorAlignment=ys,t.getAnchorJustification=pc,t.getArrayBuffer=vt,t.getImage=yt,t.getJSON=function(t,e){return gt(h(t,{type:\"json\"}),e)},t.getReferrer=ht,t.getVideo=function(t,e){var r,n,a=self.document.createElement(\"video\");a.muted=!0,a.onloadstart=function(){e(null,a)};for(var i=0;i<t.length;i++){var o=self.document.createElement(\"source\");r=t[i],n=void 0,(n=self.document.createElement(\"a\")).href=r,(n.protocol!==self.document.location.protocol||n.host!==self.document.location.host)&&(a.crossOrigin=\"Anonymous\"),o.src=t[i],a.appendChild(o)}return{cancel:function(){}}},t.identity=function(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t},t.invert=function(t,e){var r=e[0],n=e[1],a=e[2],i=e[3],o=e[4],s=e[5],l=e[6],c=e[7],u=e[8],h=e[9],f=e[10],p=e[11],d=e[12],g=e[13],v=e[14],m=e[15],y=r*s-n*o,x=r*l-a*o,b=r*c-i*o,_=n*l-a*s,w=n*c-i*s,k=a*c-i*l,T=u*g-h*d,M=u*v-f*d,A=u*m-p*d,S=h*v-f*g,E=h*m-p*g,L=f*m-p*v,C=y*L-x*E+b*S+_*A-w*M+k*T;return C?(C=1/C,t[0]=(s*L-l*E+c*S)*C,t[1]=(a*E-n*L-i*S)*C,t[2]=(g*k-v*w+m*_)*C,t[3]=(f*w-h*k-p*_)*C,t[4]=(l*A-o*L-c*M)*C,t[5]=(r*L-a*A+i*M)*C,t[6]=(v*b-d*k-m*x)*C,t[7]=(u*k-f*b+p*x)*C,t[8]=(o*E-s*A+c*T)*C,t[9]=(n*A-r*E-i*T)*C,t[10]=(d*w-g*b+m*y)*C,t[11]=(h*b-u*w-p*y)*C,t[12]=(s*M-o*S-l*T)*C,t[13]=(r*S-n*M+a*T)*C,t[14]=(g*x-d*_-v*y)*C,t[15]=(u*_-h*x+f*y)*C,t):null},t.isChar=xn,t.isMapboxURL=U,t.keysDifference=function(t,e){var r=[];for(var n in t)n in e||r.push(n);return r},t.makeRequest=gt,t.mapObject=y,t.mercatorXfromLng=Ll,t.mercatorYfromLat=Cl,t.mercatorZfromAltitude=Pl,t.multiply=function(t,e,r){var n=e[0],a=e[1],i=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],h=e[8],f=e[9],p=e[10],d=e[11],g=e[12],v=e[13],m=e[14],y=e[15],x=r[0],b=r[1],_=r[2],w=r[3];return t[0]=x*n+b*s+_*h+w*g,t[1]=x*a+b*l+_*f+w*v,t[2]=x*i+b*c+_*p+w*m,t[3]=x*o+b*u+_*d+w*y,x=r[4],b=r[5],_=r[6],w=r[7],t[4]=x*n+b*s+_*h+w*g,t[5]=x*a+b*l+_*f+w*v,t[6]=x*i+b*c+_*p+w*m,t[7]=x*o+b*u+_*d+w*y,x=r[8],b=r[9],_=r[10],w=r[11],t[8]=x*n+b*s+_*h+w*g,t[9]=x*a+b*l+_*f+w*v,t[10]=x*i+b*c+_*p+w*m,t[11]=x*o+b*u+_*d+w*y,x=r[12],b=r[13],_=r[14],w=r[15],t[12]=x*n+b*s+_*h+w*g,t[13]=x*a+b*l+_*f+w*v,t[14]=x*i+b*c+_*p+w*m,t[15]=x*o+b*u+_*d+w*y,t},t.mvt=Io,t.number=ye,t.ortho=function(t,e,r,n,a,i,o){var s=1/(e-r),l=1/(n-a),c=1/(i-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*c,t[11]=0,t[12]=(e+r)*s,t[13]=(a+n)*l,t[14]=(o+i)*c,t[15]=1,t},t.parseGlyphPBF=function(t){return new tl(t).readFields(yl,[])},t.pbf=tl,t.performSymbolLayout=function(t,e,r,n,i,o){t.createArrays();var s=512*t.overscaling;t.tilePixelRatio=ei/s,t.compareText={},t.iconsNeedLinear=!1;var l=t.layers[0].layout,c=t.layers[0]._unevaluatedLayout._values,u={};if(\"composite\"===t.textSizeData.kind){var h=t.textSizeData,f=h.minZoom,p=h.maxZoom;u.compositeTextSizes=[c[\"text-size\"].possiblyEvaluate(new Pn(f)),c[\"text-size\"].possiblyEvaluate(new Pn(p))]}if(\"composite\"===t.iconSizeData.kind){var d=t.iconSizeData,g=d.minZoom,v=d.maxZoom;u.compositeIconSizes=[c[\"icon-size\"].possiblyEvaluate(new Pn(g)),c[\"icon-size\"].possiblyEvaluate(new Pn(v))]}u.layoutTextSize=c[\"text-size\"].possiblyEvaluate(new Pn(t.zoom+1)),u.layoutIconSize=c[\"icon-size\"].possiblyEvaluate(new Pn(t.zoom+1)),u.textMaxSize=c[\"text-size\"].possiblyEvaluate(new Pn(18));for(var m=l.get(\"text-line-height\")*ls,y=\"map\"===l.get(\"text-rotation-alignment\")&&\"point\"!==l.get(\"symbol-placement\"),x=l.get(\"text-keep-upright\"),b=function(){var o=k[_],s=l.get(\"text-font\").evaluate(o,{}).join(\",\"),c=r,h={horizontal:{},vertical:void 0},f=o.text,p=[0,0];if(f){var d=f.toString(),g=l.get(\"text-letter-spacing\").evaluate(o,{})*ls,v=function(t){for(var e=0,r=d;e<r.length;e+=1)if(!_n(r[e].charCodeAt(0)))return!1;return!0}()?g:0,b=l.get(\"text-anchor\").evaluate(o,{}),T=l.get(\"text-variable-anchor\"),M=l.get(\"text-radial-offset\").evaluate(o,{});T||(p=M?fc(b,M*ls):l.get(\"text-offset\").evaluate(o,{}).map(function(t){return t*ls}));var A=y?\"center\":l.get(\"text-justify\").evaluate(o,{}),S=\"point\"===l.get(\"symbol-placement\")?l.get(\"text-max-width\").evaluate(o,{})*ls:0,E=function(){t.allowVerticalPlacement&&bn(d)&&(h.vertical=hs(f,e,s,S,m,b,\"left\",v,p,cs.vertical,!0))};if(!y&&T){for(var L=\"auto\"===A?T.map(function(t){return pc(t)}):[A],C=!1,P=0;P<L.length;P++){var O=L[P];if(!h.horizontal[O])if(C)h.horizontal[O]=h.horizontal[0];else{var z=hs(f,e,s,S,m,\"center\",O,v,p,cs.horizontal,!1);z&&(h.horizontal[O]=z,C=1===z.lineCount)}}E()}else{\"auto\"===A&&(A=pc(b));var I=hs(f,e,s,S,m,b,A,v,p,cs.horizontal,!1);I&&(h.horizontal[A]=I),E(),bn(d)&&y&&x&&(h.vertical=hs(f,e,s,S,m,b,A,v,p,cs.vertical,!1))}}var D=void 0;if(o.icon){var R=n[o.icon];R&&(D=function(t,e,r){var n=ys(r),a=n.horizontalAlign,i=n.verticalAlign,o=e[0],s=e[1],l=o-t.displaySize[0]*a,c=l+t.displaySize[0],u=s-t.displaySize[1]*i;return{image:t,top:u,bottom:u+t.displaySize[1],left:l,right:c}}(i[o.icon],l.get(\"icon-offset\").evaluate(o,{}),l.get(\"icon-anchor\").evaluate(o,{})),void 0===t.sdfIcons?t.sdfIcons=R.sdf:t.sdfIcons!==R.sdf&&w(\"Style sheet warning: Cannot mix SDF and non-SDF icons in one buffer\"),R.pixelRatio!==t.pixelRatio?t.iconsNeedLinear=!0:0!==l.get(\"icon-rotate\").constantOr(1)&&(t.iconsNeedLinear=!0))}(Object.keys(h.horizontal).length||D)&&function(t,e,r,n,i,o,s){var l=o.layoutTextSize.evaluate(e,{}),c=o.layoutIconSize.evaluate(e,{}),u=o.textMaxSize.evaluate(e,{});void 0===u&&(u=l);var h=t.layers[0].layout,f=h.get(\"icon-offset\").evaluate(e,{}),p=vc(r.horizontal),d=l/24,g=t.tilePixelRatio*d,v=t.tilePixelRatio*u/24,m=t.tilePixelRatio*c,y=t.tilePixelRatio*h.get(\"symbol-spacing\"),x=h.get(\"text-padding\")*t.tilePixelRatio,b=h.get(\"icon-padding\")*t.tilePixelRatio,_=h.get(\"text-max-angle\")/180*Math.PI,k=\"map\"===h.get(\"text-rotation-alignment\")&&\"point\"!==h.get(\"symbol-placement\"),T=\"map\"===h.get(\"icon-rotation-alignment\")&&\"point\"!==h.get(\"symbol-placement\"),M=h.get(\"symbol-placement\"),A=y/2,S=function(l,c){c.x<0||c.x>=ei||c.y<0||c.y>=ei||function(t,e,r,n,i,o,s,l,c,u,h,f,p,d,g,v,m,y,x,b,_){var k,T,M,A=t.addToLineVertexArray(e,r),S=0,E=0,L=0,C={},P=lc(\"\"),O=(o.layout.get(\"text-radial-offset\").evaluate(x,{})||0)*ls;if(t.allowVerticalPlacement&&n.vertical){var z=o.layout.get(\"text-rotate\").evaluate(x,{})+90,I=n.vertical;M=new tc(s,r,e,l,c,u,I,h,f,p,t.overscaling,z)}for(var D in n.horizontal){var R=n.horizontal[D];if(!k){P=lc(R.text);var F=o.layout.get(\"text-rotate\").evaluate(x,{});k=new tc(s,r,e,l,c,u,R,h,f,p,t.overscaling,F)}var B=1===R.lineCount;if(E+=gc(t,e,R,o,p,x,d,A,n.vertical?cs.horizontal:cs.horizontalOnly,B?Object.keys(n.horizontal):[D],C,b,_),B)break}n.vertical&&(L+=gc(t,e,n.vertical,o,p,x,d,A,cs.vertical,[\"vertical\"],C,b,_));var N=k?k.boxStartIndex:t.collisionBoxArray.length,j=k?k.boxEndIndex:t.collisionBoxArray.length,V=M?M.boxStartIndex:t.collisionBoxArray.length,U=M?M.boxEndIndex:t.collisionBoxArray.length;if(i){var q=function(t,e,r,n,i,o){var s,l,c,u,h=e.image,f=r.layout,p=e.top-1/h.pixelRatio,d=e.left-1/h.pixelRatio,g=e.bottom+1/h.pixelRatio,v=e.right+1/h.pixelRatio;if(\"none\"!==f.get(\"icon-text-fit\")&&i){var m=v-d,y=g-p,x=f.get(\"text-size\").evaluate(o,{})/24,b=i.left*x,_=i.right*x,w=i.top*x,k=_-b,T=i.bottom*x-w,M=f.get(\"icon-text-fit-padding\")[0],A=f.get(\"icon-text-fit-padding\")[1],S=f.get(\"icon-text-fit-padding\")[2],E=f.get(\"icon-text-fit-padding\")[3],L=\"width\"===f.get(\"icon-text-fit\")?.5*(T-y):0,C=\"height\"===f.get(\"icon-text-fit\")?.5*(k-m):0,P=\"width\"===f.get(\"icon-text-fit\")||\"both\"===f.get(\"icon-text-fit\")?k:m,O=\"height\"===f.get(\"icon-text-fit\")||\"both\"===f.get(\"icon-text-fit\")?T:y;s=new a(b+C-E,w+L-M),l=new a(b+C+A+P,w+L-M),c=new a(b+C+A+P,w+L+S+O),u=new a(b+C-E,w+L+S+O)}else s=new a(d,p),l=new a(v,p),c=new a(v,g),u=new a(d,g);var z=r.layout.get(\"icon-rotate\").evaluate(o,{})*Math.PI/180;if(z){var I=Math.sin(z),D=Math.cos(z),R=[D,-I,I,D];s._matMult(R),l._matMult(R),u._matMult(R),c._matMult(R)}return[{tl:s,tr:l,bl:u,br:c,tex:h.paddedRect,writingMode:void 0,glyphOffset:[0,0],sectionIndex:0}]}(0,i,o,0,vc(n.horizontal),x),H=o.layout.get(\"icon-rotate\").evaluate(x,{});T=new tc(s,r,e,l,c,u,i,g,v,!1,t.overscaling,H),S=4*q.length;var G=t.iconSizeData,Y=null;\"source\"===G.kind?(Y=[_s*o.layout.get(\"icon-size\").evaluate(x,{})])[0]>dc&&w(t.layerIds[0]+': Value for \"icon-size\" is >= 256. Reduce your \"icon-size\".'):\"composite\"===G.kind&&((Y=[_s*_.compositeIconSizes[0].evaluate(x,{}),_s*_.compositeIconSizes[1].evaluate(x,{})])[0]>dc||Y[1]>dc)&&w(t.layerIds[0]+': Value for \"icon-size\" is >= 256. Reduce your \"icon-size\".'),t.addSymbols(t.icon,q,Y,y,m,x,!1,e,A.lineStartIndex,A.lineLength)}var W=T?T.boxStartIndex:t.collisionBoxArray.length,X=T?T.boxEndIndex:t.collisionBoxArray.length;t.glyphOffsetArray.length>=Os.MAX_GLYPHS&&w(\"Too many glyphs being rendered in a tile. See https://github.com/mapbox/mapbox-gl-js/issues/2907\"),t.symbolInstances.emplaceBack(e.x,e.y,C.right>=0?C.right:-1,C.center>=0?C.center:-1,C.left>=0?C.left:-1,C.vertical||-1,P,N,j,V,U,W,X,l,E,L,S,0,h,O)}(t,c,l,r,n,t.layers[0],t.collisionBoxArray,e.index,e.sourceLayerIndex,t.index,g,x,k,s,m,b,T,f,e,i,o)};if(\"line\"===M)for(var E=0,L=function(t,e,r,n,i){for(var o=[],s=0;s<t.length;s++)for(var l=t[s],c=void 0,u=0;u<l.length-1;u++){var h=l[u],f=l[u+1];h.x<0&&f.x<0||(h.x<0?h=new a(0,h.y+(f.y-h.y)*((0-h.x)/(f.x-h.x)))._round():f.x<0&&(f=new a(0,h.y+(f.y-h.y)*((0-h.x)/(f.x-h.x)))._round()),h.y<0&&f.y<0||(h.y<0?h=new a(h.x+(f.x-h.x)*((0-h.y)/(f.y-h.y)),0)._round():f.y<0&&(f=new a(h.x+(f.x-h.x)*((0-h.y)/(f.y-h.y)),0)._round()),h.x>=n&&f.x>=n||(h.x>=n?h=new a(n,h.y+(f.y-h.y)*((n-h.x)/(f.x-h.x)))._round():f.x>=n&&(f=new a(n,h.y+(f.y-h.y)*((n-h.x)/(f.x-h.x)))._round()),h.y>=i&&f.y>=i||(h.y>=i?h=new a(h.x+(f.x-h.x)*((i-h.y)/(f.y-h.y)),i)._round():f.y>=i&&(f=new a(h.x+(f.x-h.x)*((i-h.y)/(f.y-h.y)),i)._round()),c&&h.equals(c[c.length-1])||(c=[h],o.push(c)),c.push(f)))))}return o}(e.geometry,0,0,ei,ei);E<L.length;E+=1)for(var C=L[E],P=0,O=$l(C,y,_,r.vertical||p,n,24,v,t.overscaling,ei);P<O.length;P+=1){var z=O[P];p&&mc(t,p.text,A,z)||S(C,z)}else if(\"line-center\"===M)for(var I=0,D=e.geometry;I<D.length;I+=1){var R=D[I];if(R.length>1){var F=Ql(R,_,r.vertical||p,n,24,v);F&&S(R,F)}}else if(\"Polygon\"===e.type)for(var B=0,N=mo(e.geometry,0);B<N.length;B+=1){var j=N[B],V=nc(j,16);S(j[0],new bs(V.x,V.y,0))}else if(\"LineString\"===e.type)for(var U=0,q=e.geometry;U<q.length;U+=1){var H=q[U];S(H,new bs(H[0].x,H[0].y,0))}else if(\"Point\"===e.type)for(var G=0,Y=e.geometry;G<Y.length;G+=1)for(var W=0,X=Y[G];W<X.length;W+=1){var Z=X[W];S([Z],new bs(Z.x,Z.y,0))}}(t,o,h,D,c,u,p)},_=0,k=t.features;_<k.length;_+=1)b();o&&t.generateCollisionDebugBuffers()},t.perspective=function(t,e,r,n,a){var i,o=1/Math.tan(e/2);return t[0]=o/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=o,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[11]=-1,t[12]=0,t[13]=0,t[15]=0,null!=a&&a!==1/0?(i=1/(n-a),t[10]=(a+n)*i,t[14]=2*a*n*i):(t[10]=-1,t[14]=-2*n),t},t.pick=function(t,e){for(var r={},n=0;n<e.length;n++){var a=e[n];a in t&&(r[a]=t[a])}return r},t.plugin=Cn,t.polygonIntersectsPolygon=oi,t.postMapLoadEvent=et,t.postTurnstileEvent=$,t.potpack=qs,t.rasterBoundsAttributes=Nl,t.refProperties=[\"type\",\"source\",\"source-layer\",\"minzoom\",\"maxzoom\",\"filter\",\"layout\"],t.register=dn,t.registerForPluginAvailability=function(t){return Sn?t({pluginURL:Sn,completionCallback:Mn}):Ln.once(\"pluginAvailable\",t),t},t.rotate=function(t,e,r){var n=e[0],a=e[1],i=e[2],o=e[3],s=Math.sin(r),l=Math.cos(r);return t[0]=n*l+i*s,t[1]=a*l+o*s,t[2]=n*-s+i*l,t[3]=a*-s+o*l,t},t.rotateX=function(t,e,r){var n=Math.sin(r),a=Math.cos(r),i=e[4],o=e[5],s=e[6],l=e[7],c=e[8],u=e[9],h=e[10],f=e[11];return e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[4]=i*a+c*n,t[5]=o*a+u*n,t[6]=s*a+h*n,t[7]=l*a+f*n,t[8]=c*a-i*n,t[9]=u*a-o*n,t[10]=h*a-s*n,t[11]=f*a-l*n,t},t.rotateZ=function(t,e,r){var n=Math.sin(r),a=Math.cos(r),i=e[0],o=e[1],s=e[2],l=e[3],c=e[4],u=e[5],h=e[6],f=e[7];return e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[0]=i*a+c*n,t[1]=o*a+u*n,t[2]=s*a+h*n,t[3]=l*a+f*n,t[4]=c*a-i*n,t[5]=u*a-o*n,t[6]=h*a-s*n,t[7]=f*a-l*n,t},t.scale=function(t,e,r){var n=r[0],a=r[1],i=r[2];return t[0]=e[0]*n,t[1]=e[1]*n,t[2]=e[2]*n,t[3]=e[3]*n,t[4]=e[4]*a,t[5]=e[5]*a,t[6]=e[6]*a,t[7]=e[7]*a,t[8]=e[8]*i,t[9]=e[9]*i,t[10]=e[10]*i,t[11]=e[11]*i,t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t},t.setCacheLimits=function(t,e){nt=t,at=e},t.setRTLTextPlugin=function(t,e){if(An)throw new Error(\"setRTLTextPlugin cannot be called multiple times.\");An=!0,Sn=I.resolveURL(t),Mn=function(t){t?(An=!1,Sn=null,e&&e(t)):En=!0},Ln.fire(new _t(\"pluginAvailable\",{pluginURL:Sn,completionCallback:Mn}))},t.sphericalToCartesian=function(t){var e=t[0],r=t[1],n=t[2];return r+=90,r*=Math.PI/180,n*=Math.PI/180,{x:e*Math.cos(r)*Math.sin(n),y:e*Math.sin(r)*Math.sin(n),z:e*Math.cos(n)}},t.styleSpec=Tt,t.symbolSize=Ms,t.transformMat3=function(t,e,r){var n=e[0],a=e[1],i=e[2];return t[0]=n*r[0]+a*r[3]+i*r[6],t[1]=n*r[1]+a*r[4]+i*r[7],t[2]=n*r[2]+a*r[5]+i*r[8],t},t.transformMat4=Ti,t.translate=function(t,e,r){var n,a,i,o,s,l,c,u,h,f,p,d,g=r[0],v=r[1],m=r[2];return e===t?(t[12]=e[0]*g+e[4]*v+e[8]*m+e[12],t[13]=e[1]*g+e[5]*v+e[9]*m+e[13],t[14]=e[2]*g+e[6]*v+e[10]*m+e[14],t[15]=e[3]*g+e[7]*v+e[11]*m+e[15]):(n=e[0],a=e[1],i=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],h=e[8],f=e[9],p=e[10],d=e[11],t[0]=n,t[1]=a,t[2]=i,t[3]=o,t[4]=s,t[5]=l,t[6]=c,t[7]=u,t[8]=h,t[9]=f,t[10]=p,t[11]=d,t[12]=n*g+s*v+h*m+e[12],t[13]=a*g+l*v+f*m+e[13],t[14]=i*g+c*v+p*m+e[14],t[15]=o*g+u*v+d*m+e[15]),t},t.uniqueId=p,t.validateCustomStyleLayer=function(t){var e=[],r=t.id;return void 0===r&&e.push({message:\"layers.\"+r+': missing required property \"id\"'}),void 0===t.render&&e.push({message:\"layers.\"+r+': missing required method \"render\"'}),t.renderingMode&&\"2d\"!==t.renderingMode&&\"3d\"!==t.renderingMode&&e.push({message:\"layers.\"+r+': property \"renderingMode\" must be either \"2d\" or \"3d\"'}),e},t.validateLight=an,t.validateStyle=nn,t.values=function(t){var e=[];for(var r in t)e.push(t[r]);return e},t.vectorTile=Io,t.version=\"1.3.2\",t.warnOnce=w,t.webpSupported=R,t.window=self,t.wrap=u}),n(0,function(t){function e(t){var r=typeof t;if(\"number\"===r||\"boolean\"===r||\"string\"===r||null==t)return JSON.stringify(t);if(Array.isArray(t)){for(var n=\"[\",a=0,i=t;a<i.length;a+=1)n+=e(i[a])+\",\";return n+\"]\"}for(var o=Object.keys(t).sort(),s=\"{\",l=0;l<o.length;l++)s+=JSON.stringify(o[l])+\":\"+e(t[o[l]])+\",\";return s+\"}\"}function r(r){for(var n=\"\",a=0,i=t.refProperties;a<i.length;a+=1)n+=\"/\"+e(r[i[a]]);return n}var n=function(t){this.keyCache={},t&&this.replace(t)};n.prototype.replace=function(t){this._layerConfigs={},this._layers={},this.update(t,[])},n.prototype.update=function(e,n){for(var a=this,i=0,o=e;i<o.length;i+=1){var s=o[i];this._layerConfigs[s.id]=s;var l=this._layers[s.id]=t.createStyleLayer(s);l._featureFilter=t.featureFilter(l.filter),this.keyCache[s.id]&&delete this.keyCache[s.id]}for(var c=0,u=n;c<u.length;c+=1){var h=u[c];delete this.keyCache[h],delete this._layerConfigs[h],delete this._layers[h]}this.familiesBySource={};for(var f=0,p=function(t,e){for(var n={},a=0;a<t.length;a++){var i=e&&e[t[a].id]||r(t[a]);e&&(e[t[a].id]=i);var o=n[i];o||(o=n[i]=[]),o.push(t[a])}var s=[];for(var l in n)s.push(n[l]);return s}(t.values(this._layerConfigs),this.keyCache);f<p.length;f+=1){var d=p[f].map(function(t){return a._layers[t.id]}),g=d[0];if(\"none\"!==g.visibility){var v=g.source||\"\",m=this.familiesBySource[v];m||(m=this.familiesBySource[v]={});var y=g.sourceLayer||\"_geojsonTileLayer\",x=m[y];x||(x=m[y]=[]),x.push(d)}}};var a=function(e){var r={},n=[];for(var a in e){var i=e[a],o=r[a]={};for(var s in i){var l=i[+s];if(l&&0!==l.bitmap.width&&0!==l.bitmap.height){var c={x:0,y:0,w:l.bitmap.width+2,h:l.bitmap.height+2};n.push(c),o[s]={rect:c,metrics:l.metrics}}}}var u=t.potpack(n),h=u.w,f=u.h,p=new t.AlphaImage({width:h||1,height:f||1});for(var d in e){var g=e[d];for(var v in g){var m=g[+v];if(m&&0!==m.bitmap.width&&0!==m.bitmap.height){var y=r[d][v].rect;t.AlphaImage.copy(m.bitmap,p,{x:0,y:0},{x:y.x+1,y:y.y+1},m.bitmap)}}}this.image=p,this.positions=r};t.register(\"GlyphAtlas\",a);var i=function(e){this.tileID=new t.OverscaledTileID(e.tileID.overscaledZ,e.tileID.wrap,e.tileID.canonical.z,e.tileID.canonical.x,e.tileID.canonical.y),this.uid=e.uid,this.zoom=e.zoom,this.pixelRatio=e.pixelRatio,this.tileSize=e.tileSize,this.source=e.source,this.overscaling=this.tileID.overscaleFactor(),this.showCollisionBoxes=e.showCollisionBoxes,this.collectResourceTiming=!!e.collectResourceTiming,this.returnDependencies=!!e.returnDependencies};function o(e,r){for(var n=new t.EvaluationParameters(r),a=0,i=e;a<i.length;a+=1)i[a].recalculate(n)}i.prototype.parse=function(e,r,n,i){var s=this;this.status=\"parsing\",this.data=e,this.collisionBoxArray=new t.CollisionBoxArray;var l=new t.DictionaryCoder(Object.keys(e.layers).sort()),c=new t.FeatureIndex(this.tileID);c.bucketLayerIDs=[];var u,h,f,p,d={},g={featureIndex:c,iconDependencies:{},patternDependencies:{},glyphDependencies:{}},v=r.familiesBySource[this.source];for(var m in v){var y=e.layers[m];if(y){1===y.version&&t.warnOnce('Vector tile source \"'+this.source+'\" layer \"'+m+'\" does not use vector tile spec v2 and therefore may have some rendering errors.');for(var x=l.encode(m),b=[],_=0;_<y.length;_++){var w=y.feature(_);b.push({feature:w,index:_,sourceLayerIndex:x})}for(var k=0,T=v[m];k<T.length;k+=1){var M=T[k],A=M[0];A.minzoom&&this.zoom<Math.floor(A.minzoom)||A.maxzoom&&this.zoom>=A.maxzoom||\"none\"!==A.visibility&&(o(M,this.zoom),(d[A.id]=A.createBucket({index:c.bucketLayerIDs.length,layers:M,zoom:this.zoom,pixelRatio:this.pixelRatio,overscaling:this.overscaling,collisionBoxArray:this.collisionBoxArray,sourceLayerIndex:x,sourceID:this.source})).populate(b,g),c.bucketLayerIDs.push(M.map(function(t){return t.id})))}}}var S=t.mapObject(g.glyphDependencies,function(t){return Object.keys(t).map(Number)});Object.keys(S).length?n.send(\"getGlyphs\",{uid:this.uid,stacks:S},function(t,e){u||(u=t,h=e,C.call(s))}):h={};var E=Object.keys(g.iconDependencies);E.length?n.send(\"getImages\",{icons:E},function(t,e){u||(u=t,f=e,C.call(s))}):f={};var L=Object.keys(g.patternDependencies);function C(){if(u)return i(u);if(h&&f&&p){var e=new a(h),r=new t.ImageAtlas(f,p);for(var n in d){var s=d[n];s instanceof t.SymbolBucket?(o(s.layers,this.zoom),t.performSymbolLayout(s,h,e.positions,f,r.iconPositions,this.showCollisionBoxes)):s.hasPattern&&(s instanceof t.LineBucket||s instanceof t.FillBucket||s instanceof t.FillExtrusionBucket)&&(o(s.layers,this.zoom),s.addFeatures(g,r.patternPositions))}this.status=\"done\",i(null,{buckets:t.values(d).filter(function(t){return!t.isEmpty()}),featureIndex:c,collisionBoxArray:this.collisionBoxArray,glyphAtlasImage:e.image,imageAtlas:r,glyphMap:this.returnDependencies?h:null,iconMap:this.returnDependencies?f:null,glyphPositions:this.returnDependencies?e.positions:null})}}L.length?n.send(\"getImages\",{icons:L},function(t,e){u||(u=t,p=e,C.call(s))}):p={},C.call(this)};var s=\"undefined\"!=typeof performance,l={getEntriesByName:function(t){return!!(s&&performance&&performance.getEntriesByName)&&performance.getEntriesByName(t)},mark:function(t){return!!(s&&performance&&performance.mark)&&performance.mark(t)},measure:function(t,e,r){return!!(s&&performance&&performance.measure)&&performance.measure(t,e,r)},clearMarks:function(t){return!!(s&&performance&&performance.clearMarks)&&performance.clearMarks(t)},clearMeasures:function(t){return!!(s&&performance&&performance.clearMeasures)&&performance.clearMeasures(t)}},c=function(t){this._marks={start:[t.url,\"start\"].join(\"#\"),end:[t.url,\"end\"].join(\"#\"),measure:t.url.toString()},l.mark(this._marks.start)};function u(e,r){var n=t.getArrayBuffer(e.request,function(e,n,a,i){e?r(e):n&&r(null,{vectorTile:new t.vectorTile.VectorTile(new t.pbf(n)),rawData:n,cacheControl:a,expires:i})});return function(){n.cancel(),r()}}c.prototype.finish=function(){l.mark(this._marks.end);var t=l.getEntriesByName(this._marks.measure);return 0===t.length&&(l.measure(this._marks.measure,this._marks.start,this._marks.end),t=l.getEntriesByName(this._marks.measure),l.clearMarks(this._marks.start),l.clearMarks(this._marks.end),l.clearMeasures(this._marks.measure)),t},l.Performance=c;var h=function(t,e,r){this.actor=t,this.layerIndex=e,this.loadVectorData=r||u,this.loading={},this.loaded={}};h.prototype.loadTile=function(e,r){var n=this,a=e.uid;this.loading||(this.loading={});var o=!!(e&&e.request&&e.request.collectResourceTiming)&&new l.Performance(e.request),s=this.loading[a]=new i(e);s.abort=this.loadVectorData(e,function(e,i){if(delete n.loading[a],e||!i)return s.status=\"done\",n.loaded[a]=s,r(e);var l=i.rawData,c={};i.expires&&(c.expires=i.expires),i.cacheControl&&(c.cacheControl=i.cacheControl);var u={};if(o){var h=o.finish();h&&(u.resourceTiming=JSON.parse(JSON.stringify(h)))}s.vectorTile=i.vectorTile,s.parse(i.vectorTile,n.layerIndex,n.actor,function(e,n){if(e||!n)return r(e);r(null,t.extend({rawTileData:l.slice(0)},n,c,u))}),n.loaded=n.loaded||{},n.loaded[a]=s})},h.prototype.reloadTile=function(t,e){var r=this.loaded,n=t.uid,a=this;if(r&&r[n]){var i=r[n];i.showCollisionBoxes=t.showCollisionBoxes;var o=function(t,r){var n=i.reloadCallback;n&&(delete i.reloadCallback,i.parse(i.vectorTile,a.layerIndex,a.actor,n)),e(t,r)};\"parsing\"===i.status?i.reloadCallback=o:\"done\"===i.status&&(i.vectorTile?i.parse(i.vectorTile,this.layerIndex,this.actor,o):o())}},h.prototype.abortTile=function(t,e){var r=this.loading,n=t.uid;r&&r[n]&&r[n].abort&&(r[n].abort(),delete r[n]),e()},h.prototype.removeTile=function(t,e){var r=this.loaded,n=t.uid;r&&r[n]&&delete r[n],e()};var f=function(){this.loaded={}};f.prototype.loadTile=function(e,r){var n=e.uid,a=e.encoding,i=e.rawImageData,o=new t.DEMData(n,i,a);this.loaded=this.loaded||{},this.loaded[n]=o,r(null,o)},f.prototype.removeTile=function(t){var e=this.loaded,r=t.uid;e&&e[r]&&delete e[r]};var p={RADIUS:6378137,FLATTENING:1/298.257223563,POLAR_RADIUS:6356752.3142};function d(t){var e=0;if(t&&t.length>0){e+=Math.abs(g(t[0]));for(var r=1;r<t.length;r++)e-=Math.abs(g(t[r]))}return e}function g(t){var e,r,n,a,i,o,s=0,l=t.length;if(l>2){for(o=0;o<l;o++)o===l-2?(n=l-2,a=l-1,i=0):o===l-1?(n=l-1,a=0,i=1):(n=o,a=o+1,i=o+2),e=t[n],r=t[a],s+=(v(t[i][0])-v(e[0]))*Math.sin(v(r[1]));s=s*p.RADIUS*p.RADIUS/2}return s}function v(t){return t*Math.PI/180}var m={geometry:function t(e){var r,n=0;switch(e.type){case\"Polygon\":return d(e.coordinates);case\"MultiPolygon\":for(r=0;r<e.coordinates.length;r++)n+=d(e.coordinates[r]);return n;case\"Point\":case\"MultiPoint\":case\"LineString\":case\"MultiLineString\":return 0;case\"GeometryCollection\":for(r=0;r<e.geometries.length;r++)n+=t(e.geometries[r]);return n}},ring:g};function y(t,e){return function(r){return t(r,e)}}function x(t,e){e=!!e,t[0]=b(t[0],e);for(var r=1;r<t.length;r++)t[r]=b(t[r],!e);return t}function b(t,e){return function(t){return m.ring(t)>=0}(t)===e?t:t.reverse()}var _=t.vectorTile.VectorTileFeature.prototype.toGeoJSON,w=function(e){this._feature=e,this.extent=t.EXTENT,this.type=e.type,this.properties=e.tags,\"id\"in e&&!isNaN(e.id)&&(this.id=parseInt(e.id,10))};w.prototype.loadGeometry=function(){if(1===this._feature.type){for(var e=[],r=0,n=this._feature.geometry;r<n.length;r+=1){var a=n[r];e.push([new t.Point$1(a[0],a[1])])}return e}for(var i=[],o=0,s=this._feature.geometry;o<s.length;o+=1){for(var l=[],c=0,u=s[o];c<u.length;c+=1){var h=u[c];l.push(new t.Point$1(h[0],h[1]))}i.push(l)}return i},w.prototype.toGeoJSON=function(t,e,r){return _.call(this,t,e,r)};var k=function(e){this.layers={_geojsonTileLayer:this},this.name=\"_geojsonTileLayer\",this.extent=t.EXTENT,this.length=e.length,this._features=e};k.prototype.feature=function(t){return new w(this._features[t])};var T=t.vectorTile.VectorTileFeature,M=A;function A(t,e){this.options=e||{},this.features=t,this.length=t.length}function S(t,e){this.id=\"number\"==typeof t.id?t.id:void 0,this.type=t.type,this.rawGeometry=1===t.type?[t.geometry]:t.geometry,this.properties=t.tags,this.extent=e||4096}A.prototype.feature=function(t){return new S(this.features[t],this.options.extent)},S.prototype.loadGeometry=function(){var e=this.rawGeometry;this.geometry=[];for(var r=0;r<e.length;r++){for(var n=e[r],a=[],i=0;i<n.length;i++)a.push(new t.Point$1(n[i][0],n[i][1]));this.geometry.push(a)}return this.geometry},S.prototype.bbox=function(){this.geometry||this.loadGeometry();for(var t=this.geometry,e=1/0,r=-1/0,n=1/0,a=-1/0,i=0;i<t.length;i++)for(var o=t[i],s=0;s<o.length;s++){var l=o[s];e=Math.min(e,l.x),r=Math.max(r,l.x),n=Math.min(n,l.y),a=Math.max(a,l.y)}return[e,n,r,a]},S.prototype.toGeoJSON=T.prototype.toGeoJSON;var E=P,L=P,C=M;function P(e){var r=new t.pbf;return function(t,e){for(var r in t.layers)e.writeMessage(3,O,t.layers[r])}(e,r),r.finish()}function O(t,e){var r;e.writeVarintField(15,t.version||1),e.writeStringField(1,t.name||\"\"),e.writeVarintField(5,t.extent||4096);var n={keys:[],values:[],keycache:{},valuecache:{}};for(r=0;r<t.length;r++)n.feature=t.feature(r),e.writeMessage(2,z,n);var a=n.keys;for(r=0;r<a.length;r++)e.writeStringField(3,a[r]);var i=n.values;for(r=0;r<i.length;r++)e.writeMessage(4,B,i[r])}function z(t,e){var r=t.feature;void 0!==r.id&&e.writeVarintField(1,r.id),e.writeMessage(2,I,t),e.writeVarintField(3,r.type),e.writeMessage(4,F,r)}function I(t,e){var r=t.feature,n=t.keys,a=t.values,i=t.keycache,o=t.valuecache;for(var s in r.properties){var l=i[s];void 0===l&&(n.push(s),l=n.length-1,i[s]=l),e.writeVarint(l);var c=r.properties[s],u=typeof c;\"string\"!==u&&\"boolean\"!==u&&\"number\"!==u&&(c=JSON.stringify(c));var h=u+\":\"+c,f=o[h];void 0===f&&(a.push(c),f=a.length-1,o[h]=f),e.writeVarint(f)}}function D(t,e){return(e<<3)+(7&t)}function R(t){return t<<1^t>>31}function F(t,e){for(var r=t.loadGeometry(),n=t.type,a=0,i=0,o=r.length,s=0;s<o;s++){var l=r[s],c=1;1===n&&(c=l.length),e.writeVarint(D(1,c));for(var u=3===n?l.length-1:l.length,h=0;h<u;h++){1===h&&1!==n&&e.writeVarint(D(2,u-1));var f=l[h].x-a,p=l[h].y-i;e.writeVarint(R(f)),e.writeVarint(R(p)),a+=f,i+=p}3===n&&e.writeVarint(D(7,1))}}function B(t,e){var r=typeof t;\"string\"===r?e.writeStringField(1,t):\"boolean\"===r?e.writeBooleanField(7,t):\"number\"===r&&(t%1!=0?e.writeDoubleField(3,t):t<0?e.writeSVarintField(6,t):e.writeVarintField(5,t))}function N(t,e,r,n){j(t,r,n),j(e,2*r,2*n),j(e,2*r+1,2*n+1)}function j(t,e,r){var n=t[e];t[e]=t[r],t[r]=n}function V(t,e,r,n){var a=t-r,i=e-n;return a*a+i*i}E.fromVectorTileJs=L,E.fromGeojsonVt=function(t,e){e=e||{};var r={};for(var n in t)r[n]=new M(t[n].features,e),r[n].name=n,r[n].version=e.version,r[n].extent=e.extent;return P({layers:r})},E.GeoJSONWrapper=C;var U=function(t){return t[0]},q=function(t){return t[1]},H=function(t,e,r,n,a){void 0===e&&(e=U),void 0===r&&(r=q),void 0===n&&(n=64),void 0===a&&(a=Float64Array),this.nodeSize=n,this.points=t;for(var i=t.length<65536?Uint16Array:Uint32Array,o=this.ids=new i(t.length),s=this.coords=new a(2*t.length),l=0;l<t.length;l++)o[l]=l,s[2*l]=e(t[l]),s[2*l+1]=r(t[l]);!function t(e,r,n,a,i,o){if(!(i-a<=n)){var s=a+i>>1;!function t(e,r,n,a,i,o){for(;i>a;){if(i-a>600){var s=i-a+1,l=n-a+1,c=Math.log(s),u=.5*Math.exp(2*c/3),h=.5*Math.sqrt(c*u*(s-u)/s)*(l-s/2<0?-1:1);t(e,r,n,Math.max(a,Math.floor(n-l*u/s+h)),Math.min(i,Math.floor(n+(s-l)*u/s+h)),o)}var f=r[2*n+o],p=a,d=i;for(N(e,r,a,n),r[2*i+o]>f&&N(e,r,a,i);p<d;){for(N(e,r,p,d),p++,d--;r[2*p+o]<f;)p++;for(;r[2*d+o]>f;)d--}r[2*a+o]===f?N(e,r,a,d):N(e,r,++d,i),d<=n&&(a=d+1),n<=d&&(i=d-1)}}(e,r,s,a,i,o%2),t(e,r,n,a,s-1,o+1),t(e,r,n,s+1,i,o+1)}}(o,s,n,0,o.length-1,0)};H.prototype.range=function(t,e,r,n){return function(t,e,r,n,a,i,o){for(var s,l,c=[0,t.length-1,0],u=[];c.length;){var h=c.pop(),f=c.pop(),p=c.pop();if(f-p<=o)for(var d=p;d<=f;d++)s=e[2*d],l=e[2*d+1],s>=r&&s<=a&&l>=n&&l<=i&&u.push(t[d]);else{var g=Math.floor((p+f)/2);s=e[2*g],l=e[2*g+1],s>=r&&s<=a&&l>=n&&l<=i&&u.push(t[g]);var v=(h+1)%2;(0===h?r<=s:n<=l)&&(c.push(p),c.push(g-1),c.push(v)),(0===h?a>=s:i>=l)&&(c.push(g+1),c.push(f),c.push(v))}}return u}(this.ids,this.coords,t,e,r,n,this.nodeSize)},H.prototype.within=function(t,e,r){return function(t,e,r,n,a,i){for(var o=[0,t.length-1,0],s=[],l=a*a;o.length;){var c=o.pop(),u=o.pop(),h=o.pop();if(u-h<=i)for(var f=h;f<=u;f++)V(e[2*f],e[2*f+1],r,n)<=l&&s.push(t[f]);else{var p=Math.floor((h+u)/2),d=e[2*p],g=e[2*p+1];V(d,g,r,n)<=l&&s.push(t[p]);var v=(c+1)%2;(0===c?r-a<=d:n-a<=g)&&(o.push(h),o.push(p-1),o.push(v)),(0===c?r+a>=d:n+a>=g)&&(o.push(p+1),o.push(u),o.push(v))}}return s}(this.ids,this.coords,t,e,r,this.nodeSize)};var G={minZoom:0,maxZoom:16,radius:40,extent:512,nodeSize:64,log:!1,reduce:null,map:function(t){return t}},Y=function(t){this.options=$(Object.create(G),t),this.trees=new Array(this.options.maxZoom+1)};function W(t,e,r,n,a){return{x:t,y:e,zoom:1/0,id:r,parentId:-1,numPoints:n,properties:a}}function X(t,e){var r=t.geometry.coordinates,n=r[0],a=r[1];return{x:K(n),y:Q(a),zoom:1/0,index:e,parentId:-1}}function Z(t){return{type:\"Feature\",id:t.id,properties:J(t),geometry:{type:\"Point\",coordinates:[(n=t.x,360*(n-.5)),(e=t.y,r=(180-360*e)*Math.PI/180,360*Math.atan(Math.exp(r))/Math.PI-90)]}};var e,r,n}function J(t){var e=t.numPoints,r=e>=1e4?Math.round(e/1e3)+\"k\":e>=1e3?Math.round(e/100)/10+\"k\":e;return $($({},t.properties),{cluster:!0,cluster_id:t.id,point_count:e,point_count_abbreviated:r})}function K(t){return t/360+.5}function Q(t){var e=Math.sin(t*Math.PI/180),r=.5-.25*Math.log((1+e)/(1-e))/Math.PI;return r<0?0:r>1?1:r}function $(t,e){for(var r in e)t[r]=e[r];return t}function tt(t){return t.x}function et(t){return t.y}function rt(t,e,r,n,a,i){var o=a-r,s=i-n;if(0!==o||0!==s){var l=((t-r)*o+(e-n)*s)/(o*o+s*s);l>1?(r=a,n=i):l>0&&(r+=o*l,n+=s*l)}return(o=t-r)*o+(s=e-n)*s}function nt(t,e,r,n){var a={id:void 0===t?null:t,type:e,geometry:r,tags:n,minX:1/0,minY:1/0,maxX:-1/0,maxY:-1/0};return function(t){var e=t.geometry,r=t.type;if(\"Point\"===r||\"MultiPoint\"===r||\"LineString\"===r)at(t,e);else if(\"Polygon\"===r||\"MultiLineString\"===r)for(var n=0;n<e.length;n++)at(t,e[n]);else if(\"MultiPolygon\"===r)for(n=0;n<e.length;n++)for(var a=0;a<e[n].length;a++)at(t,e[n][a])}(a),a}function at(t,e){for(var r=0;r<e.length;r+=3)t.minX=Math.min(t.minX,e[r]),t.minY=Math.min(t.minY,e[r+1]),t.maxX=Math.max(t.maxX,e[r]),t.maxY=Math.max(t.maxY,e[r+1])}function it(t,e,r,n){if(e.geometry){var a=e.geometry.coordinates,i=e.geometry.type,o=Math.pow(r.tolerance/((1<<r.maxZoom)*r.extent),2),s=[],l=e.id;if(r.promoteId?l=e.properties[r.promoteId]:r.generateId&&(l=n||0),\"Point\"===i)ot(a,s);else if(\"MultiPoint\"===i)for(var c=0;c<a.length;c++)ot(a[c],s);else if(\"LineString\"===i)st(a,s,o,!1);else if(\"MultiLineString\"===i){if(r.lineMetrics){for(c=0;c<a.length;c++)s=[],st(a[c],s,o,!1),t.push(nt(l,\"LineString\",s,e.properties));return}lt(a,s,o,!1)}else if(\"Polygon\"===i)lt(a,s,o,!0);else{if(\"MultiPolygon\"!==i){if(\"GeometryCollection\"===i){for(c=0;c<e.geometry.geometries.length;c++)it(t,{id:l,geometry:e.geometry.geometries[c],properties:e.properties},r,n);return}throw new Error(\"Input data is not a valid GeoJSON object.\")}for(c=0;c<a.length;c++){var u=[];lt(a[c],u,o,!0),s.push(u)}}t.push(nt(l,i,s,e.properties))}}function ot(t,e){e.push(ct(t[0])),e.push(ut(t[1])),e.push(0)}function st(t,e,r,n){for(var a,i,o=0,s=0;s<t.length;s++){var l=ct(t[s][0]),c=ut(t[s][1]);e.push(l),e.push(c),e.push(0),s>0&&(o+=n?(a*c-l*i)/2:Math.sqrt(Math.pow(l-a,2)+Math.pow(c-i,2))),a=l,i=c}var u=e.length-3;e[2]=1,function t(e,r,n,a){for(var i,o=a,s=n-r>>1,l=n-r,c=e[r],u=e[r+1],h=e[n],f=e[n+1],p=r+3;p<n;p+=3){var d=rt(e[p],e[p+1],c,u,h,f);if(d>o)i=p,o=d;else if(d===o){var g=Math.abs(p-s);g<l&&(i=p,l=g)}}o>a&&(i-r>3&&t(e,r,i,a),e[i+2]=o,n-i>3&&t(e,i,n,a))}(e,0,u,r),e[u+2]=1,e.size=Math.abs(o),e.start=0,e.end=e.size}function lt(t,e,r,n){for(var a=0;a<t.length;a++){var i=[];st(t[a],i,r,n),e.push(i)}}function ct(t){return t/360+.5}function ut(t){var e=Math.sin(t*Math.PI/180),r=.5-.25*Math.log((1+e)/(1-e))/Math.PI;return r<0?0:r>1?1:r}function ht(t,e,r,n,a,i,o,s){if(n/=e,i>=(r/=e)&&o<n)return t;if(o<r||i>=n)return null;for(var l=[],c=0;c<t.length;c++){var u=t[c],h=u.geometry,f=u.type,p=0===a?u.minX:u.minY,d=0===a?u.maxX:u.maxY;if(p>=r&&d<n)l.push(u);else if(!(d<r||p>=n)){var g=[];if(\"Point\"===f||\"MultiPoint\"===f)ft(h,g,r,n,a);else if(\"LineString\"===f)pt(h,g,r,n,a,!1,s.lineMetrics);else if(\"MultiLineString\"===f)gt(h,g,r,n,a,!1);else if(\"Polygon\"===f)gt(h,g,r,n,a,!0);else if(\"MultiPolygon\"===f)for(var v=0;v<h.length;v++){var m=[];gt(h[v],m,r,n,a,!0),m.length&&g.push(m)}if(g.length){if(s.lineMetrics&&\"LineString\"===f){for(v=0;v<g.length;v++)l.push(nt(u.id,f,g[v],u.tags));continue}\"LineString\"!==f&&\"MultiLineString\"!==f||(1===g.length?(f=\"LineString\",g=g[0]):f=\"MultiLineString\"),\"Point\"!==f&&\"MultiPoint\"!==f||(f=3===g.length?\"Point\":\"MultiPoint\"),l.push(nt(u.id,f,g,u.tags))}}}return l.length?l:null}function ft(t,e,r,n,a){for(var i=0;i<t.length;i+=3){var o=t[i+a];o>=r&&o<=n&&(e.push(t[i]),e.push(t[i+1]),e.push(t[i+2]))}}function pt(t,e,r,n,a,i,o){for(var s,l,c=dt(t),u=0===a?mt:yt,h=t.start,f=0;f<t.length-3;f+=3){var p=t[f],d=t[f+1],g=t[f+2],v=t[f+3],m=t[f+4],y=0===a?p:d,x=0===a?v:m,b=!1;o&&(s=Math.sqrt(Math.pow(p-v,2)+Math.pow(d-m,2))),y<r?x>r&&(l=u(c,p,d,v,m,r),o&&(c.start=h+s*l)):y>n?x<n&&(l=u(c,p,d,v,m,n),o&&(c.start=h+s*l)):vt(c,p,d,g),x<r&&y>=r&&(l=u(c,p,d,v,m,r),b=!0),x>n&&y<=n&&(l=u(c,p,d,v,m,n),b=!0),!i&&b&&(o&&(c.end=h+s*l),e.push(c),c=dt(t)),o&&(h+=s)}var _=t.length-3;p=t[_],d=t[_+1],g=t[_+2],(y=0===a?p:d)>=r&&y<=n&&vt(c,p,d,g),_=c.length-3,i&&_>=3&&(c[_]!==c[0]||c[_+1]!==c[1])&&vt(c,c[0],c[1],c[2]),c.length&&e.push(c)}function dt(t){var e=[];return e.size=t.size,e.start=t.start,e.end=t.end,e}function gt(t,e,r,n,a,i){for(var o=0;o<t.length;o++)pt(t[o],e,r,n,a,i,!1)}function vt(t,e,r,n){t.push(e),t.push(r),t.push(n)}function mt(t,e,r,n,a,i){var o=(i-e)/(n-e);return t.push(i),t.push(r+(a-r)*o),t.push(1),o}function yt(t,e,r,n,a,i){var o=(i-r)/(a-r);return t.push(e+(n-e)*o),t.push(i),t.push(1),o}function xt(t,e){for(var r=[],n=0;n<t.length;n++){var a,i=t[n],o=i.type;if(\"Point\"===o||\"MultiPoint\"===o||\"LineString\"===o)a=bt(i.geometry,e);else if(\"MultiLineString\"===o||\"Polygon\"===o){a=[];for(var s=0;s<i.geometry.length;s++)a.push(bt(i.geometry[s],e))}else if(\"MultiPolygon\"===o)for(a=[],s=0;s<i.geometry.length;s++){for(var l=[],c=0;c<i.geometry[s].length;c++)l.push(bt(i.geometry[s][c],e));a.push(l)}r.push(nt(i.id,o,a,i.tags))}return r}function bt(t,e){var r=[];r.size=t.size,void 0!==t.start&&(r.start=t.start,r.end=t.end);for(var n=0;n<t.length;n+=3)r.push(t[n]+e,t[n+1],t[n+2]);return r}function _t(t,e){if(t.transformed)return t;var r,n,a,i=1<<t.z,o=t.x,s=t.y;for(r=0;r<t.features.length;r++){var l=t.features[r],c=l.geometry,u=l.type;if(l.geometry=[],1===u)for(n=0;n<c.length;n+=2)l.geometry.push(wt(c[n],c[n+1],e,i,o,s));else for(n=0;n<c.length;n++){var h=[];for(a=0;a<c[n].length;a+=2)h.push(wt(c[n][a],c[n][a+1],e,i,o,s));l.geometry.push(h)}}return t.transformed=!0,t}function wt(t,e,r,n,a,i){return[Math.round(r*(t*n-a)),Math.round(r*(e*n-i))]}function kt(t,e,r,n,a){for(var i=e===a.maxZoom?0:a.tolerance/((1<<e)*a.extent),o={features:[],numPoints:0,numSimplified:0,numFeatures:0,source:null,x:r,y:n,z:e,transformed:!1,minX:2,minY:1,maxX:-1,maxY:0},s=0;s<t.length;s++){o.numFeatures++,Tt(o,t[s],i,a);var l=t[s].minX,c=t[s].minY,u=t[s].maxX,h=t[s].maxY;l<o.minX&&(o.minX=l),c<o.minY&&(o.minY=c),u>o.maxX&&(o.maxX=u),h>o.maxY&&(o.maxY=h)}return o}function Tt(t,e,r,n){var a=e.geometry,i=e.type,o=[];if(\"Point\"===i||\"MultiPoint\"===i)for(var s=0;s<a.length;s+=3)o.push(a[s]),o.push(a[s+1]),t.numPoints++,t.numSimplified++;else if(\"LineString\"===i)Mt(o,a,t,r,!1,!1);else if(\"MultiLineString\"===i||\"Polygon\"===i)for(s=0;s<a.length;s++)Mt(o,a[s],t,r,\"Polygon\"===i,0===s);else if(\"MultiPolygon\"===i)for(var l=0;l<a.length;l++){var c=a[l];for(s=0;s<c.length;s++)Mt(o,c[s],t,r,!0,0===s)}if(o.length){var u=e.tags||null;if(\"LineString\"===i&&n.lineMetrics){for(var h in u={},e.tags)u[h]=e.tags[h];u.mapbox_clip_start=a.start/a.size,u.mapbox_clip_end=a.end/a.size}var f={geometry:o,type:\"Polygon\"===i||\"MultiPolygon\"===i?3:\"LineString\"===i||\"MultiLineString\"===i?2:1,tags:u};null!==e.id&&(f.id=e.id),t.features.push(f)}}function Mt(t,e,r,n,a,i){var o=n*n;if(n>0&&e.size<(a?o:n))r.numPoints+=e.length/3;else{for(var s=[],l=0;l<e.length;l+=3)(0===n||e[l+2]>o)&&(r.numSimplified++,s.push(e[l]),s.push(e[l+1])),r.numPoints++;a&&function(t,e){for(var r=0,n=0,a=t.length,i=a-2;n<a;i=n,n+=2)r+=(t[n]-t[i])*(t[n+1]+t[i+1]);if(r>0===e)for(n=0,a=t.length;n<a/2;n+=2){var o=t[n],s=t[n+1];t[n]=t[a-2-n],t[n+1]=t[a-1-n],t[a-2-n]=o,t[a-1-n]=s}}(s,i),t.push(s)}}function At(t,e){var r=(e=this.options=function(t,e){for(var r in e)t[r]=e[r];return t}(Object.create(this.options),e)).debug;if(r&&console.time(\"preprocess data\"),e.maxZoom<0||e.maxZoom>24)throw new Error(\"maxZoom should be in the 0-24 range\");if(e.promoteId&&e.generateId)throw new Error(\"promoteId and generateId cannot be used together.\");var n=function(t,e){var r=[];if(\"FeatureCollection\"===t.type)for(var n=0;n<t.features.length;n++)it(r,t.features[n],e,n);else\"Feature\"===t.type?it(r,t,e):it(r,{geometry:t},e);return r}(t,e);this.tiles={},this.tileCoords=[],r&&(console.timeEnd(\"preprocess data\"),console.log(\"index: maxZoom: %d, maxPoints: %d\",e.indexMaxZoom,e.indexMaxPoints),console.time(\"generate tiles\"),this.stats={},this.total=0),(n=function(t,e){var r=e.buffer/e.extent,n=t,a=ht(t,1,-1-r,r,0,-1,2,e),i=ht(t,1,1-r,2+r,0,-1,2,e);return(a||i)&&(n=ht(t,1,-r,1+r,0,-1,2,e)||[],a&&(n=xt(a,1).concat(n)),i&&(n=n.concat(xt(i,-1)))),n}(n,e)).length&&this.splitTile(n,0,0,0),r&&(n.length&&console.log(\"features: %d, points: %d\",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd(\"generate tiles\"),console.log(\"tiles generated:\",this.total,JSON.stringify(this.stats)))}function St(t,e,r){return 32*((1<<t)*r+e)+t}function Et(t,e){var r=t.tileID.canonical;if(!this._geoJSONIndex)return e(null,null);var n=this._geoJSONIndex.getTile(r.z,r.x,r.y);if(!n)return e(null,null);var a=new k(n.features),i=E(a);0===i.byteOffset&&i.byteLength===i.buffer.byteLength||(i=new Uint8Array(i)),e(null,{vectorTile:a,rawData:i.buffer})}Y.prototype.load=function(t){var e=this.options,r=e.log,n=e.minZoom,a=e.maxZoom,i=e.nodeSize;r&&console.time(\"total time\");var o=\"prepare \"+t.length+\" points\";r&&console.time(o),this.points=t;for(var s=[],l=0;l<t.length;l++)t[l].geometry&&s.push(X(t[l],l));this.trees[a+1]=new H(s,tt,et,i,Float32Array),r&&console.timeEnd(o);for(var c=a;c>=n;c--){var u=+Date.now();s=this._cluster(s,c),this.trees[c]=new H(s,tt,et,i,Float32Array),r&&console.log(\"z%d: %d clusters in %dms\",c,s.length,+Date.now()-u)}return r&&console.timeEnd(\"total time\"),this},Y.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),a=180===t[2]?180:((t[2]+180)%360+360)%360-180,i=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,a=180;else if(r>a){var o=this.getClusters([r,n,180,i],e),s=this.getClusters([-180,n,a,i],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],c=[],u=0,h=l.range(K(r),Q(i),K(a),Q(n));u<h.length;u+=1){var f=h[u],p=l.points[f];c.push(p.numPoints?Z(p):this.points[p.index])}return c},Y.prototype.getChildren=function(t){var e=t>>5,r=t%32,n=\"No cluster with the specified id.\",a=this.trees[r];if(!a)throw new Error(n);var i=a.points[e];if(!i)throw new Error(n);for(var o=this.options.radius/(this.options.extent*Math.pow(2,r-1)),s=[],l=0,c=a.within(i.x,i.y,o);l<c.length;l+=1){var u=c[l],h=a.points[u];h.parentId===t&&s.push(h.numPoints?Z(h):this.points[h.index])}if(0===s.length)throw new Error(n);return s},Y.prototype.getLeaves=function(t,e,r){e=e||10,r=r||0;var n=[];return this._appendLeaves(n,t,e,r,0),n},Y.prototype.getTile=function(t,e,r){var n=this.trees[this._limitZoom(t)],a=Math.pow(2,t),i=this.options,o=i.extent,s=i.radius/o,l=(r-s)/a,c=(r+1+s)/a,u={features:[]};return this._addTileFeatures(n.range((e-s)/a,l,(e+1+s)/a,c),n.points,e,r,a,u),0===e&&this._addTileFeatures(n.range(1-s/a,l,1,c),n.points,a,r,a,u),e===a-1&&this._addTileFeatures(n.range(0,l,s/a,c),n.points,-1,r,a,u),u.features.length?u:null},Y.prototype.getClusterExpansionZoom=function(t){for(var e=t%32-1;e<=this.options.maxZoom;){var r=this.getChildren(t);if(e++,1!==r.length)break;t=r[0].properties.cluster_id}return e},Y.prototype._appendLeaves=function(t,e,r,n,a){for(var i=0,o=this.getChildren(e);i<o.length;i+=1){var s=o[i],l=s.properties;if(l&&l.cluster?a+l.point_count<=n?a+=l.point_count:a=this._appendLeaves(t,l.cluster_id,r,n,a):a<n?a++:t.push(s),t.length===r)break}return a},Y.prototype._addTileFeatures=function(t,e,r,n,a,i){for(var o=0,s=t;o<s.length;o+=1){var l=e[s[o]],c={type:1,geometry:[[Math.round(this.options.extent*(l.x*a-r)),Math.round(this.options.extent*(l.y*a-n))]],tags:l.numPoints?J(l):this.points[l.index].properties},u=l.numPoints?l.id:this.points[l.index].id;void 0!==u&&(c.id=u),i.features.push(c)}},Y.prototype._limitZoom=function(t){return Math.max(this.options.minZoom,Math.min(t,this.options.maxZoom+1))},Y.prototype._cluster=function(t,e){for(var r=[],n=this.options,a=n.radius,i=n.extent,o=n.reduce,s=a/(i*Math.pow(2,e)),l=0;l<t.length;l++){var c=t[l];if(!(c.zoom<=e)){c.zoom=e;for(var u=this.trees[e+1],h=u.within(c.x,c.y,s),f=c.numPoints||1,p=c.x*f,d=c.y*f,g=o&&f>1?this._map(c,!0):null,v=(l<<5)+(e+1),m=0,y=h;m<y.length;m+=1){var x=y[m],b=u.points[x];if(!(b.zoom<=e)){b.zoom=e;var _=b.numPoints||1;p+=b.x*_,d+=b.y*_,f+=_,b.parentId=v,o&&(g||(g=this._map(c,!0)),o(g,this._map(b)))}}1===f?r.push(c):(c.parentId=v,r.push(W(p/f,d/f,v,f,g)))}}return r},Y.prototype._map=function(t,e){if(t.numPoints)return e?$({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?$({},n):n},At.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},At.prototype.splitTile=function(t,e,r,n,a,i,o){for(var s=[t,e,r,n],l=this.options,c=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var u=1<<e,h=St(e,r,n),f=this.tiles[h];if(!f&&(c>1&&console.time(\"creation\"),f=this.tiles[h]=kt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),c)){c>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",e,r,n,f.numFeatures,f.numPoints,f.numSimplified),console.timeEnd(\"creation\"));var p=\"z\"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(f.source=t,a){if(e===l.maxZoom||e===a)continue;var d=1<<a-e;if(r!==Math.floor(i/d)||n!==Math.floor(o/d))continue}else if(e===l.indexMaxZoom||f.numPoints<=l.indexMaxPoints)continue;if(f.source=null,0!==t.length){c>1&&console.time(\"clipping\");var g,v,m,y,x,b,_=.5*l.buffer/l.extent,w=.5-_,k=.5+_,T=1+_;g=v=m=y=null,x=ht(t,u,r-_,r+k,0,f.minX,f.maxX,l),b=ht(t,u,r+w,r+T,0,f.minX,f.maxX,l),t=null,x&&(g=ht(x,u,n-_,n+k,1,f.minY,f.maxY,l),v=ht(x,u,n+w,n+T,1,f.minY,f.maxY,l),x=null),b&&(m=ht(b,u,n-_,n+k,1,f.minY,f.maxY,l),y=ht(b,u,n+w,n+T,1,f.minY,f.maxY,l),b=null),c>1&&console.timeEnd(\"clipping\"),s.push(g||[],e+1,2*r,2*n),s.push(v||[],e+1,2*r,2*n+1),s.push(m||[],e+1,2*r+1,2*n),s.push(y||[],e+1,2*r+1,2*n+1)}}},At.prototype.getTile=function(t,e,r){var n=this.options,a=n.extent,i=n.debug;if(t<0||t>24)return null;var o=1<<t,s=St(t,e=(e%o+o)%o,r);if(this.tiles[s])return _t(this.tiles[s],a);i>1&&console.log(\"drilling down to z%d-%d-%d\",t,e,r);for(var l,c=t,u=e,h=r;!l&&c>0;)c--,u=Math.floor(u/2),h=Math.floor(h/2),l=this.tiles[St(c,u,h)];return l&&l.source?(i>1&&console.log(\"found parent tile z%d-%d-%d\",c,u,h),i>1&&console.time(\"drilling down\"),this.splitTile(l.source,c,u,h,t,e,r),i>1&&console.timeEnd(\"drilling down\"),this.tiles[s]?_t(this.tiles[s],a):null):null};var Lt=function(e){function r(t,r,n){e.call(this,t,r,Et),n&&(this.loadGeoJSON=n)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadData=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=e,this._pendingLoadDataParams=t,this._state&&\"Idle\"!==this._state?this._state=\"NeedsLoadData\":(this._state=\"Coalescing\",this._loadData())},r.prototype._loadData=function(){var e=this;if(this._pendingCallback&&this._pendingLoadDataParams){var r=this._pendingCallback,n=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams;var a=!!(n&&n.request&&n.request.collectResourceTiming)&&new l.Performance(n.request);this.loadGeoJSON(n,function(i,o){if(i||!o)return r(i);if(\"object\"!=typeof o)return r(new Error(\"Input data given to '\"+n.source+\"' is not a valid GeoJSON object.\"));!function t(e,r){switch(e&&e.type||null){case\"FeatureCollection\":return e.features=e.features.map(y(t,r)),e;case\"GeometryCollection\":return e.geometries=e.geometries.map(y(t,r)),e;case\"Feature\":return e.geometry=t(e.geometry,r),e;case\"Polygon\":case\"MultiPolygon\":return function(t,e){return\"Polygon\"===t.type?t.coordinates=x(t.coordinates,e):\"MultiPolygon\"===t.type&&(t.coordinates=t.coordinates.map(y(x,e))),t}(e,r);default:return e}}(o,!0);try{e._geoJSONIndex=n.cluster?new Y(function(e){var r=e.superclusterOptions,n=e.clusterProperties;if(!n||!r)return r;for(var a={},i={},o={accumulated:null,zoom:0},s={properties:null},l=Object.keys(n),c=0,u=l;c<u.length;c+=1){var h=u[c],f=n[h],p=f[0],d=f[1],g=t.createExpression(d),v=t.createExpression(\"string\"==typeof p?[p,[\"accumulated\"],[\"get\",h]]:p);a[h]=g.value,i[h]=v.value}return r.map=function(t){s.properties=t;for(var e={},r=0,n=l;r<n.length;r+=1){var i=n[r];e[i]=a[i].evaluate(o,s)}return e},r.reduce=function(t,e){s.properties=e;for(var r=0,n=l;r<n.length;r+=1){var a=n[r];o.accumulated=t[a],t[a]=i[a].evaluate(o,s)}},r}(n)).load(o.features):new At(o,n.geojsonVtOptions)}catch(i){return r(i)}e.loaded={};var s={};if(a){var l=a.finish();l&&(s.resourceTiming={},s.resourceTiming[n.source]=JSON.parse(JSON.stringify(l)))}r(null,s)})}},r.prototype.coalesce=function(){\"Coalescing\"===this._state?this._state=\"Idle\":\"NeedsLoadData\"===this._state&&(this._state=\"Coalescing\",this._loadData())},r.prototype.reloadTile=function(t,r){var n=this.loaded,a=t.uid;return n&&n[a]?e.prototype.reloadTile.call(this,t,r):this.loadTile(t,r)},r.prototype.loadGeoJSON=function(e,r){if(e.request)t.getJSON(e.request,r);else{if(\"string\"!=typeof e.data)return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"));try{return r(null,JSON.parse(e.data))}catch(t){return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"))}}},r.prototype.removeSource=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),e()},r.prototype.getClusterExpansionZoom=function(t,e){e(null,this._geoJSONIndex.getClusterExpansionZoom(t.clusterId))},r.prototype.getClusterChildren=function(t,e){e(null,this._geoJSONIndex.getChildren(t.clusterId))},r.prototype.getClusterLeaves=function(t,e){e(null,this._geoJSONIndex.getLeaves(t.clusterId,t.limit,t.offset))},r}(h),Ct=function(e){var r=this;this.self=e,this.actor=new t.Actor(e,this),this.layerIndexes={},this.workerSourceTypes={vector:h,geojson:Lt},this.workerSources={},this.demWorkerSources={},this.self.registerWorkerSource=function(t,e){if(r.workerSourceTypes[t])throw new Error('Worker source with name \"'+t+'\" already registered.');r.workerSourceTypes[t]=e},this.self.registerRTLTextPlugin=function(e){if(t.plugin.isLoaded())throw new Error(\"RTL text plugin already registered.\");t.plugin.applyArabicShaping=e.applyArabicShaping,t.plugin.processBidirectionalText=e.processBidirectionalText,t.plugin.processStyledBidirectionalText=e.processStyledBidirectionalText}};return Ct.prototype.setReferrer=function(t,e){this.referrer=e},Ct.prototype.setLayers=function(t,e,r){this.getLayerIndex(t).replace(e),r()},Ct.prototype.updateLayers=function(t,e,r){this.getLayerIndex(t).update(e.layers,e.removedIds),r()},Ct.prototype.loadTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).loadTile(e,r)},Ct.prototype.loadDEMTile=function(t,e,r){this.getDEMWorkerSource(t,e.source).loadTile(e,r)},Ct.prototype.reloadTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).reloadTile(e,r)},Ct.prototype.abortTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).abortTile(e,r)},Ct.prototype.removeTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).removeTile(e,r)},Ct.prototype.removeDEMTile=function(t,e){this.getDEMWorkerSource(t,e.source).removeTile(e)},Ct.prototype.removeSource=function(t,e,r){if(this.workerSources[t]&&this.workerSources[t][e.type]&&this.workerSources[t][e.type][e.source]){var n=this.workerSources[t][e.type][e.source];delete this.workerSources[t][e.type][e.source],void 0!==n.removeSource?n.removeSource(e,r):r()}},Ct.prototype.loadWorkerSource=function(t,e,r){try{this.self.importScripts(e.url),r()}catch(t){r(t.toString())}},Ct.prototype.loadRTLTextPlugin=function(e,r,n){try{t.plugin.isLoaded()||(this.self.importScripts(r),n(t.plugin.isLoaded()?null:new Error(\"RTL Text Plugin failed to import scripts from \"+r)))}catch(t){n(t.toString())}},Ct.prototype.getLayerIndex=function(t){var e=this.layerIndexes[t];return e||(e=this.layerIndexes[t]=new n),e},Ct.prototype.getWorkerSource=function(t,e,r){var n=this;if(this.workerSources[t]||(this.workerSources[t]={}),this.workerSources[t][e]||(this.workerSources[t][e]={}),!this.workerSources[t][e][r]){var a={send:function(e,r,a){n.actor.send(e,r,a,t)}};this.workerSources[t][e][r]=new this.workerSourceTypes[e](a,this.getLayerIndex(t))}return this.workerSources[t][e][r]},Ct.prototype.getDEMWorkerSource=function(t,e){return this.demWorkerSources[t]||(this.demWorkerSources[t]={}),this.demWorkerSources[t][e]||(this.demWorkerSources[t][e]=new f),this.demWorkerSources[t][e]},Ct.prototype.enforceCacheSizeLimit=function(e,r){t.enforceCacheSizeLimit(r)},\"undefined\"!=typeof WorkerGlobalScope&&void 0!==t.window&&t.window instanceof WorkerGlobalScope&&(t.window.worker=new Ct(t.window)),Ct}),n(0,function(t){var e=t.createCommonjsModule(function(t){function e(t){return!!(\"undefined\"!=typeof window&&\"undefined\"!=typeof document&&Array.prototype&&Array.prototype.every&&Array.prototype.filter&&Array.prototype.forEach&&Array.prototype.indexOf&&Array.prototype.lastIndexOf&&Array.prototype.map&&Array.prototype.some&&Array.prototype.reduce&&Array.prototype.reduceRight&&Array.isArray&&Function.prototype&&Function.prototype.bind&&Object.keys&&Object.create&&Object.getPrototypeOf&&Object.getOwnPropertyNames&&Object.isSealed&&Object.isFrozen&&Object.isExtensible&&Object.getOwnPropertyDescriptor&&Object.defineProperty&&Object.defineProperties&&Object.seal&&Object.freeze&&Object.preventExtensions&&\"JSON\"in window&&\"parse\"in JSON&&\"stringify\"in JSON&&function(){if(!(\"Worker\"in window&&\"Blob\"in window&&\"URL\"in window))return!1;var t,e,r=new Blob([\"\"],{type:\"text/javascript\"}),n=URL.createObjectURL(r);try{e=new Worker(n),t=!0}catch(e){t=!1}return e&&e.terminate(),URL.revokeObjectURL(n),t}()&&\"Uint8ClampedArray\"in window&&ArrayBuffer.isView&&function(t){return void 0===r[t]&&(r[t]=function(t){var r=document.createElement(\"canvas\"),n=Object.create(e.webGLContextAttributes);return n.failIfMajorPerformanceCaveat=t,r.probablySupportsContext?r.probablySupportsContext(\"webgl\",n)||r.probablySupportsContext(\"experimental-webgl\",n):r.supportsContext?r.supportsContext(\"webgl\",n)||r.supportsContext(\"experimental-webgl\",n):r.getContext(\"webgl\",n)||r.getContext(\"experimental-webgl\",n)}(t)),r[t]}(t&&t.failIfMajorPerformanceCaveat))}t.exports?t.exports=e:window&&(window.mapboxgl=window.mapboxgl||{},window.mapboxgl.supported=e);var r={};e.webGLContextAttributes={antialias:!1,alpha:!0,stencil:!0,depth:!0}}),r={create:function(e,r,n){var a=t.window.document.createElement(e);return void 0!==r&&(a.className=r),n&&n.appendChild(a),a},createNS:function(e,r){return t.window.document.createElementNS(e,r)}},n=t.window.document.documentElement.style;function a(t){if(!n)return t[0];for(var e=0;e<t.length;e++)if(t[e]in n)return t[e];return t[0]}var i,o=a([\"userSelect\",\"MozUserSelect\",\"WebkitUserSelect\",\"msUserSelect\"]);r.disableDrag=function(){n&&o&&(i=n[o],n[o]=\"none\")},r.enableDrag=function(){n&&o&&(n[o]=i)};var s=a([\"transform\",\"WebkitTransform\"]);r.setTransform=function(t,e){t.style[s]=e};var l=!1;try{var c=Object.defineProperty({},\"passive\",{get:function(){l=!0}});t.window.addEventListener(\"test\",c,c),t.window.removeEventListener(\"test\",c,c)}catch(t){l=!1}r.addEventListener=function(t,e,r,n){void 0===n&&(n={}),\"passive\"in n&&l?t.addEventListener(e,r,n):t.addEventListener(e,r,n.capture)},r.removeEventListener=function(t,e,r,n){void 0===n&&(n={}),\"passive\"in n&&l?t.removeEventListener(e,r,n):t.removeEventListener(e,r,n.capture)};var u=function(e){e.preventDefault(),e.stopPropagation(),t.window.removeEventListener(\"click\",u,!0)};function h(t){var e=t.userImage;return!!(e&&e.render&&e.render())&&(t.data.replace(new Uint8Array(e.data.buffer)),!0)}r.suppressClick=function(){t.window.addEventListener(\"click\",u,!0),t.window.setTimeout(function(){t.window.removeEventListener(\"click\",u,!0)},0)},r.mousePos=function(e,r){var n=e.getBoundingClientRect(),a=t.window.TouchEvent&&r instanceof t.window.TouchEvent?r.touches[0]:r;return new t.Point(a.clientX-n.left-e.clientLeft,a.clientY-n.top-e.clientTop)},r.touchPos=function(e,r){for(var n=e.getBoundingClientRect(),a=[],i=\"touchend\"===r.type?r.changedTouches:r.touches,o=0;o<i.length;o++)a.push(new t.Point(i[o].clientX-n.left-e.clientLeft,i[o].clientY-n.top-e.clientTop));return a},r.mouseButton=function(e){return void 0!==t.window.InstallTrigger&&2===e.button&&e.ctrlKey&&t.window.navigator.platform.toUpperCase().indexOf(\"MAC\")>=0?0:e.button},r.remove=function(t){t.parentNode&&t.parentNode.removeChild(t)};var f=function(e){function r(){e.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new t.RGBAImage({width:1,height:1}),this.dirty=!0}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.isLoaded=function(){return this.loaded},r.prototype.setLoaded=function(t){if(this.loaded!==t&&(this.loaded=t,t)){for(var e=0,r=this.requestors;e<r.length;e+=1){var n=r[e],a=n.ids,i=n.callback;this._notify(a,i)}this.requestors=[]}},r.prototype.getImage=function(t){return this.images[t]},r.prototype.addImage=function(t,e){this.images[t]=e},r.prototype.updateImage=function(t,e){var r=this.images[t];e.version=r.version+1,this.images[t]=e,this.updatedImages[t]=!0},r.prototype.removeImage=function(t){var e=this.images[t];delete this.images[t],delete this.patterns[t],e.userImage&&e.userImage.onRemove&&e.userImage.onRemove()},r.prototype.listImages=function(){return Object.keys(this.images)},r.prototype.getImages=function(t,e){var r=!0;if(!this.isLoaded())for(var n=0,a=t;n<a.length;n+=1){var i=a[n];this.images[i]||(r=!1)}this.isLoaded()||r?this._notify(t,e):this.requestors.push({ids:t,callback:e})},r.prototype._notify=function(e,r){for(var n={},a=0,i=e;a<i.length;a+=1){var o=i[a];this.images[o]||this.fire(new t.Event(\"styleimagemissing\",{id:o}));var s=this.images[o];s?n[o]={data:s.data.clone(),pixelRatio:s.pixelRatio,sdf:s.sdf,version:s.version,hasRenderCallback:Boolean(s.userImage&&s.userImage.render)}:t.warnOnce('Image \"'+o+'\" could not be loaded. Please make sure you have added the image with map.addImage() or a \"sprite\" property in your style. You can provide missing images by listening for the \"styleimagemissing\" map event.')}r(null,n)},r.prototype.getPixelSize=function(){var t=this.atlasImage;return{width:t.width,height:t.height}},r.prototype.getPattern=function(e){var r=this.patterns[e],n=this.getImage(e);if(!n)return null;if(r&&r.position.version===n.version)return r.position;if(r)r.position.version=n.version;else{var a={w:n.data.width+2,h:n.data.height+2,x:0,y:0},i=new t.ImagePosition(a,n);this.patterns[e]={bin:a,position:i}}return this._updatePatternAtlas(),this.patterns[e].position},r.prototype.bind=function(e){var r=e.gl;this.atlasTexture?this.dirty&&(this.atlasTexture.update(this.atlasImage),this.dirty=!1):this.atlasTexture=new t.Texture(e,this.atlasImage,r.RGBA),this.atlasTexture.bind(r.LINEAR,r.CLAMP_TO_EDGE)},r.prototype._updatePatternAtlas=function(){var e=[];for(var r in this.patterns)e.push(this.patterns[r].bin);var n=t.potpack(e),a=n.w,i=n.h,o=this.atlasImage;for(var s in o.resize({width:a||1,height:i||1}),this.patterns){var l=this.patterns[s].bin,c=l.x+1,u=l.y+1,h=this.images[s].data,f=h.width,p=h.height;t.RGBAImage.copy(h,o,{x:0,y:0},{x:c,y:u},{width:f,height:p}),t.RGBAImage.copy(h,o,{x:0,y:p-1},{x:c,y:u-1},{width:f,height:1}),t.RGBAImage.copy(h,o,{x:0,y:0},{x:c,y:u+p},{width:f,height:1}),t.RGBAImage.copy(h,o,{x:f-1,y:0},{x:c-1,y:u},{width:1,height:p}),t.RGBAImage.copy(h,o,{x:0,y:0},{x:c+f,y:u},{width:1,height:p})}this.dirty=!0},r.prototype.beginFrame=function(){this.callbackDispatchedThisFrame={}},r.prototype.dispatchRenderCallbacks=function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e];if(!this.callbackDispatchedThisFrame[n]){this.callbackDispatchedThisFrame[n]=!0;var a=this.images[n];h(a)&&this.updateImage(n,a)}}},r}(t.Evented),p=v,d=v,g=1e20;function v(t,e,r,n,a,i){this.fontSize=t||24,this.buffer=void 0===e?3:e,this.cutoff=n||.25,this.fontFamily=a||\"sans-serif\",this.fontWeight=i||\"normal\",this.radius=r||8;var o=this.size=this.fontSize+2*this.buffer;this.canvas=document.createElement(\"canvas\"),this.canvas.width=this.canvas.height=o,this.ctx=this.canvas.getContext(\"2d\"),this.ctx.font=this.fontWeight+\" \"+this.fontSize+\"px \"+this.fontFamily,this.ctx.textBaseline=\"middle\",this.ctx.fillStyle=\"black\",this.gridOuter=new Float64Array(o*o),this.gridInner=new Float64Array(o*o),this.f=new Float64Array(o),this.d=new Float64Array(o),this.z=new Float64Array(o+1),this.v=new Int16Array(o),this.middle=Math.round(o/2*(navigator.userAgent.indexOf(\"Gecko/\")>=0?1.2:1))}function m(t,e,r,n,a,i,o){for(var s=0;s<e;s++){for(var l=0;l<r;l++)n[l]=t[l*e+s];for(y(n,a,i,o,r),l=0;l<r;l++)t[l*e+s]=a[l]}for(l=0;l<r;l++){for(s=0;s<e;s++)n[s]=t[l*e+s];for(y(n,a,i,o,e),s=0;s<e;s++)t[l*e+s]=Math.sqrt(a[s])}}function y(t,e,r,n,a){r[0]=0,n[0]=-g,n[1]=+g;for(var i=1,o=0;i<a;i++){for(var s=(t[i]+i*i-(t[r[o]]+r[o]*r[o]))/(2*i-2*r[o]);s<=n[o];)o--,s=(t[i]+i*i-(t[r[o]]+r[o]*r[o]))/(2*i-2*r[o]);r[++o]=i,n[o]=s,n[o+1]=+g}for(i=0,o=0;i<a;i++){for(;n[o+1]<i;)o++;e[i]=(i-r[o])*(i-r[o])+t[r[o]]}}v.prototype.draw=function(t){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(t,this.buffer,this.middle);for(var e=this.ctx.getImageData(0,0,this.size,this.size),r=new Uint8ClampedArray(this.size*this.size),n=0;n<this.size*this.size;n++){var a=e.data[4*n+3]/255;this.gridOuter[n]=1===a?0:0===a?g:Math.pow(Math.max(0,.5-a),2),this.gridInner[n]=1===a?g:0===a?0:Math.pow(Math.max(0,a-.5),2)}for(m(this.gridOuter,this.size,this.size,this.f,this.d,this.v,this.z),m(this.gridInner,this.size,this.size,this.f,this.d,this.v,this.z),n=0;n<this.size*this.size;n++){var i=this.gridOuter[n]-this.gridInner[n];r[n]=Math.max(0,Math.min(255,Math.round(255-255*(i/this.radius+this.cutoff))))}return r},p.default=d;var x=function(t,e){this.requestManager=t,this.localIdeographFontFamily=e,this.entries={}};x.prototype.setURL=function(t){this.url=t},x.prototype.getGlyphs=function(e,r){var n=this,a=[];for(var i in e)for(var o=0,s=e[i];o<s.length;o+=1){var l=s[o];a.push({stack:i,id:l})}t.asyncAll(a,function(t,e){var r=t.stack,a=t.id,i=n.entries[r];i||(i=n.entries[r]={glyphs:{},requests:{}});var o=i.glyphs[a];if(void 0===o){if(o=n._tinySDF(i,r,a))return i.glyphs[a]=o,void e(null,{stack:r,id:a,glyph:o});var s=Math.floor(a/256);if(256*s>65535)e(new Error(\"glyphs > 65535 not supported\"));else{var l=i.requests[s];l||(l=i.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,function(t,e){if(e)for(var r in e)n._doesCharSupportLocalGlyph(+r)||(i.glyphs[+r]=e[+r]);for(var a=0,o=l;a<o.length;a+=1)(0,o[a])(t,e);delete i.requests[s]})),l.push(function(t,n){t?e(t):n&&e(null,{stack:r,id:a,glyph:n[a]||null})})}}else e(null,{stack:r,id:a,glyph:o})},function(t,e){if(t)r(t);else if(e){for(var n={},a=0,i=e;a<i.length;a+=1){var o=i[a],s=o.stack,l=o.id,c=o.glyph;(n[s]||(n[s]={}))[l]=c&&{id:c.id,bitmap:c.bitmap.clone(),metrics:c.metrics}}r(null,n)}})},x.prototype._doesCharSupportLocalGlyph=function(e){return!!this.localIdeographFontFamily&&(t.isChar[\"CJK Unified Ideographs\"](e)||t.isChar[\"Hangul Syllables\"](e)||t.isChar.Hiragana(e)||t.isChar.Katakana(e))},x.prototype._tinySDF=function(e,r,n){var a=this.localIdeographFontFamily;if(a&&this._doesCharSupportLocalGlyph(n)){var i=e.tinySDF;if(!i){var o=\"400\";/bold/i.test(r)?o=\"900\":/medium/i.test(r)?o=\"500\":/light/i.test(r)&&(o=\"200\"),i=e.tinySDF=new x.TinySDF(24,3,8,.25,a,o)}return{id:n,bitmap:new t.AlphaImage({width:30,height:30},i.draw(String.fromCharCode(n))),metrics:{width:24,height:24,left:0,top:-8,advance:24}}}},x.loadGlyphRange=function(e,r,n,a,i){var o=256*r,s=o+255,l=a.transformRequest(a.normalizeGlyphsURL(n).replace(\"{fontstack}\",e).replace(\"{range}\",o+\"-\"+s),t.ResourceType.Glyphs);t.getArrayBuffer(l,function(e,r){if(e)i(e);else if(r){for(var n={},a=0,o=t.parseGlyphPBF(r);a<o.length;a+=1){var s=o[a];n[s.id]=s}i(null,n)}})},x.TinySDF=p;var b=function(){this.specification=t.styleSpec.light.position};b.prototype.possiblyEvaluate=function(e,r){return t.sphericalToCartesian(e.expression.evaluate(r))},b.prototype.interpolate=function(e,r,n){return{x:t.number(e.x,r.x,n),y:t.number(e.y,r.y,n),z:t.number(e.z,r.z,n)}};var _=new t.Properties({anchor:new t.DataConstantProperty(t.styleSpec.light.anchor),position:new b,color:new t.DataConstantProperty(t.styleSpec.light.color),intensity:new t.DataConstantProperty(t.styleSpec.light.intensity)}),w=function(e){function r(r){e.call(this),this._transitionable=new t.Transitionable(_),this.setLight(r),this._transitioning=this._transitionable.untransitioned()}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getLight=function(){return this._transitionable.serialize()},r.prototype.setLight=function(e,r){if(void 0===r&&(r={}),!this._validate(t.validateLight,e,r))for(var n in e){var a=e[n];t.endsWith(n,\"-transition\")?this._transitionable.setTransition(n.slice(0,-\"-transition\".length),a):this._transitionable.setValue(n,a)}},r.prototype.updateTransitions=function(t){this._transitioning=this._transitionable.transitioned(t,this._transitioning)},r.prototype.hasTransition=function(){return this._transitioning.hasTransition()},r.prototype.recalculate=function(t){this.properties=this._transitioning.possiblyEvaluate(t)},r.prototype._validate=function(e,r,n){return(!n||!1!==n.validate)&&t.emitValidationErrors(this,e.call(t.validateStyle,t.extend({value:r,style:{glyphs:!0,sprite:!0},styleSpec:t.styleSpec})))},r}(t.Evented),k=function(t,e){this.width=t,this.height=e,this.nextRow=0,this.bytes=4,this.data=new Uint8Array(this.width*this.height*this.bytes),this.positions={}};k.prototype.getDash=function(t,e){var r=t.join(\",\")+String(e);return this.positions[r]||(this.positions[r]=this.addDash(t,e)),this.positions[r]},k.prototype.addDash=function(e,r){var n=r?7:0,a=2*n+1;if(this.nextRow+a>this.height)return t.warnOnce(\"LineAtlas out of space\"),null;for(var i=0,o=0;o<e.length;o++)i+=e[o];for(var s=this.width/i,l=s/2,c=e.length%2==1,u=-n;u<=n;u++)for(var h=this.nextRow+n+u,f=this.width*h,p=c?-e[e.length-1]:0,d=e[0],g=1,v=0;v<this.width;v++){for(;d<v/s;)p=d,d+=e[g],c&&g===e.length-1&&(d+=e[0]),g++;var m=Math.abs(v-p*s),y=Math.abs(v-d*s),x=Math.min(m,y),b=g%2==1,_=void 0;if(r){var w=n?u/n*(l+1):0;if(b){var k=l-Math.abs(w);_=Math.sqrt(x*x+k*k)}else _=l-Math.sqrt(x*x+w*w)}else _=(b?1:-1)*x;this.data[3+4*(f+v)]=Math.max(0,Math.min(255,_+128))}var T={y:(this.nextRow+n+.5)/this.height,height:2*n/this.height,width:i};return this.nextRow+=a,this.dirty=!0,T},k.prototype.bind=function(t){var e=t.gl;this.texture?(e.bindTexture(e.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,e.texSubImage2D(e.TEXTURE_2D,0,0,0,this.width,this.height,e.RGBA,e.UNSIGNED_BYTE,this.data))):(this.texture=e.createTexture(),e.bindTexture(e.TEXTURE_2D,this.texture),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_S,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_T,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texImage2D(e.TEXTURE_2D,0,e.RGBA,this.width,this.height,0,e.RGBA,e.UNSIGNED_BYTE,this.data))};var T=function e(r,n){this.workerPool=r,this.actors=[],this.currentActor=0,this.id=t.uniqueId();for(var a=this.workerPool.acquire(this.id),i=0;i<a.length;i++){var o=a[i],s=new e.Actor(o,n,this.id);s.name=\"Worker \"+i,this.actors.push(s)}};function M(e,r,n){var a=function(a,i){if(a)return n(a);if(i){var o=t.pick(t.extend(i,e),[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\",\"mapbox_logo\",\"bounds\",\"scheme\",\"tileSize\",\"encoding\"]);i.vector_layers&&(o.vectorLayers=i.vector_layers,o.vectorLayerIds=o.vectorLayers.map(function(t){return t.id})),e.url&&(o.tiles=r.canonicalizeTileset(o,e.url)),n(null,o)}};return e.url?t.getJSON(r.transformRequest(r.normalizeSourceURL(e.url),t.ResourceType.Source),a):t.browser.frame(function(){return a(null,e)})}T.prototype.broadcast=function(e,r,n){n=n||function(){},t.asyncAll(this.actors,function(t,n){t.send(e,r,n)},n)},T.prototype.getActor=function(){return this.currentActor=(this.currentActor+1)%this.actors.length,this.actors[this.currentActor]},T.prototype.remove=function(){this.actors.forEach(function(t){t.remove()}),this.actors=[],this.workerPool.release(this.id)},T.Actor=t.Actor;var A=function(e,r,n){this.bounds=t.LngLatBounds.convert(this.validateBounds(e)),this.minzoom=r||0,this.maxzoom=n||24};A.prototype.validateBounds=function(t){return Array.isArray(t)&&4===t.length?[Math.max(-180,t[0]),Math.max(-90,t[1]),Math.min(180,t[2]),Math.min(90,t[3])]:[-180,-90,180,90]},A.prototype.contains=function(e){var r=Math.pow(2,e.z),n=Math.floor(t.mercatorXfromLng(this.bounds.getWest())*r),a=Math.floor(t.mercatorYfromLat(this.bounds.getNorth())*r),i=Math.ceil(t.mercatorXfromLng(this.bounds.getEast())*r),o=Math.ceil(t.mercatorYfromLat(this.bounds.getSouth())*r);return e.x>=n&&e.x<i&&e.y>=a&&e.y<o};var S=function(e){function r(r,n,a,i){if(e.call(this),this.id=r,this.dispatcher=a,this.type=\"vector\",this.minzoom=0,this.maxzoom=22,this.scheme=\"xyz\",this.tileSize=512,this.reparseOverscaled=!0,this.isTileClipped=!0,this._loaded=!1,t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\"])),this._options=t.extend({type:\"vector\"},n),this._collectResourceTiming=n.collectResourceTiming,512!==this.tileSize)throw new Error(\"vector tile sources must have a tileSize of 512\");this.setEventedParent(i)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=M(this._options,this.map._requestManager,function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new A(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles,e.map._requestManager._customAccessToken),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken,e.map._requestManager._customAccessToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))})},r.prototype.loaded=function(){return this._loaded},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.url,null),a={request:this.map._requestManager.transformRequest(n,t.ResourceType.Tile),uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,tileSize:this.tileSize*e.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes};function i(n,a){return delete e.request,e.aborted?r(null):n&&404!==n.status?r(n):(a&&a.resourceTiming&&(e.resourceTiming=a.resourceTiming),this.map._refreshExpiredTiles&&a&&e.setExpiryData(a),e.loadVectorData(a,this.map.painter),t.cacheEntryPossiblyAdded(this.dispatcher),r(null),void(e.reloadCallback&&(this.loadTile(e,e.reloadCallback),e.reloadCallback=null)))}a.request.collectResourceTiming=this._collectResourceTiming,e.actor&&\"expired\"!==e.state?\"loading\"===e.state?e.reloadCallback=r:e.request=e.actor.send(\"reloadTile\",a,i.bind(this)):(e.actor=this.dispatcher.getActor(),e.request=e.actor.send(\"loadTile\",a,i.bind(this)))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.actor&&t.actor.send(\"abortTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.unloadTile=function(t){t.unloadVectorData(),t.actor&&t.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.hasTransition=function(){return!1},r}(t.Evented),E=function(e){function r(r,n,a,i){e.call(this),this.id=r,this.dispatcher=a,this.setEventedParent(i),this.type=\"raster\",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme=\"xyz\",this.tileSize=512,this._loaded=!1,this._options=t.extend({type:\"raster\"},n),t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\"]))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=M(this._options,this.map._requestManager,function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new A(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))})},r.prototype.loaded=function(){return this._loaded},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.loadTile=function(e,r){var n=this,a=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.url,this.tileSize);e.request=t.getImage(this.map._requestManager.transformRequest(a,t.ResourceType.Tile),function(a,i){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(a)e.state=\"errored\",r(a);else if(i){n.map._refreshExpiredTiles&&e.setExpiryData(i),delete i.cacheControl,delete i.expires;var o=n.map.painter.context,s=o.gl;e.texture=n.map.painter.getTileTexture(i.width),e.texture?e.texture.update(i,{useMipmap:!0}):(e.texture=new t.Texture(o,i,s.RGBA,{useMipmap:!0}),e.texture.bind(s.LINEAR,s.CLAMP_TO_EDGE,s.LINEAR_MIPMAP_NEAREST),o.extTextureFilterAnisotropic&&s.texParameterf(s.TEXTURE_2D,o.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,o.extTextureFilterAnisotropicMax)),e.state=\"loaded\",t.cacheEntryPossiblyAdded(n.dispatcher),r(null)}})},r.prototype.abortTile=function(t,e){t.request&&(t.request.cancel(),delete t.request),e()},r.prototype.unloadTile=function(t,e){t.texture&&this.map.painter.saveTileTexture(t.texture),e()},r.prototype.hasTransition=function(){return!1},r}(t.Evented),L=function(e){function r(r,n,a,i){e.call(this,r,n,a,i),this.type=\"raster-dem\",this.maxzoom=22,this._options=t.extend({type:\"raster-dem\"},n),this.encoding=n.encoding||\"mapbox\"}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.serialize=function(){return{type:\"raster-dem\",url:this.url,tileSize:this.tileSize,tiles:this.tiles,bounds:this.bounds,encoding:this.encoding}},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.url,this.tileSize);e.request=t.getImage(this.map._requestManager.transformRequest(n,t.ResourceType.Tile),function(n,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(n)e.state=\"errored\",r(n);else if(a){this.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var i=t.browser.getImageData(a),o={uid:e.uid,coord:e.tileID,source:this.id,rawImageData:i,encoding:this.encoding};e.actor&&\"expired\"!==e.state||(e.actor=this.dispatcher.getActor(),e.actor.send(\"loadDEMTile\",o,function(t,n){t&&(e.state=\"errored\",r(t)),n&&(e.dem=n,e.needsHillshadePrepare=!0,e.state=\"loaded\",r(null))}.bind(this)))}}.bind(this)),e.neighboringTiles=this._getNeighboringTiles(e.tileID)},r.prototype._getNeighboringTiles=function(e){var r=e.canonical,n=Math.pow(2,r.z),a=(r.x-1+n)%n,i=0===r.x?e.wrap-1:e.wrap,o=(r.x+1+n)%n,s=r.x+1===n?e.wrap+1:e.wrap,l={};return l[new t.OverscaledTileID(e.overscaledZ,i,r.z,a,r.y).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y).key]={backfilled:!1},r.y>0&&(l[new t.OverscaledTileID(e.overscaledZ,i,r.z,a,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+1<n&&(l[new t.OverscaledTileID(e.overscaledZ,i,r.z,a,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y+1).key]={backfilled:!1}),l},r.prototype.unloadTile=function(t){t.demTexture&&this.map.painter.saveTileTexture(t.demTexture),t.fbo&&(t.fbo.destroy(),delete t.fbo),t.dem&&delete t.dem,delete t.neighboringTiles,t.state=\"unloaded\",t.actor&&t.actor.send(\"removeDEMTile\",{uid:t.uid,source:this.id})},r}(E),C=function(e){function r(r,n,a,i){e.call(this),this.id=r,this.type=\"geojson\",this.minzoom=0,this.maxzoom=18,this.tileSize=512,this.isTileClipped=!0,this.reparseOverscaled=!0,this._removed=!1,this._loaded=!1,this.actor=a.getActor(),this.setEventedParent(i),this._data=n.data,this._options=t.extend({},n),this._collectResourceTiming=n.collectResourceTiming,this._resourceTiming=[],void 0!==n.maxzoom&&(this.maxzoom=n.maxzoom),n.type&&(this.type=n.type),n.attribution&&(this.attribution=n.attribution);var o=t.EXTENT/this.tileSize;this.workerOptions=t.extend({source:this.id,cluster:n.cluster||!1,geojsonVtOptions:{buffer:(void 0!==n.buffer?n.buffer:128)*o,tolerance:(void 0!==n.tolerance?n.tolerance:.375)*o,extent:t.EXTENT,maxZoom:this.maxzoom,lineMetrics:n.lineMetrics||!1,generateId:n.generateId||!1},superclusterOptions:{maxZoom:void 0!==n.clusterMaxZoom?Math.min(n.clusterMaxZoom,this.maxzoom-1):this.maxzoom-1,extent:t.EXTENT,radius:(n.clusterRadius||50)*o,log:!1},clusterProperties:n.clusterProperties},n.workerOptions)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData(function(r){if(r)e.fire(new t.ErrorEvent(r));else{var n={dataType:\"source\",sourceDataType:\"metadata\"};e._collectResourceTiming&&e._resourceTiming&&e._resourceTiming.length>0&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event(\"data\",n))}})},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData(function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:\"source\",sourceDataType:\"content\"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event(\"data\",n))}}),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send(\"geojson.getClusterExpansionZoom\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send(\"geojson.getClusterChildren\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send(\"geojson.getClusterLeaves\",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),a=this._data;\"string\"==typeof a?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(a),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(a),this.actor.send(this.type+\".loadData\",n,function(t,a){r._removed||a&&a.abandoned||(r._loaded=!0,a&&a.resourceTiming&&a.resourceTiming[r.id]&&(r._resourceTiming=a.resourceTiming[r.id].slice(0)),r.actor.send(r.type+\".coalesce\",{source:n.source},null),e(t))})},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,a=e.actor?\"reloadTile\":\"loadTile\";e.actor=this.actor;var i={type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes};e.request=this.actor.send(a,i,function(t,i){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(i,n.map.painter,\"reloadTile\"===a),r(null))})},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send(\"removeSource\",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),P=function(e){function r(t,r,n,a){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(a),this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),function(a,i){n._loaded=!0,a?n.fire(new t.ErrorEvent(a)):i&&(n.image=i,e&&(n.coordinates=e),r&&r(),n._finishLoading())})},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,function(){e.texture=null}),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,a=-1/0,i=-1/0,o=0,s=e;o<s.length;o+=1){var l=s[o];r=Math.min(r,l.x),n=Math.min(n,l.y),a=Math.max(a,l.x),i=Math.max(i,l.y)}var c=a-r,u=i-n,h=Math.max(c,u),f=Math.max(0,Math.floor(-Math.log(h)/Math.LN2)),p=Math.pow(2,f);return new t.CanonicalTileID(f,Math.floor((r+a)/2*p),Math.floor((n+i)/2*p))}(n),this.minzoom=this.maxzoom=this.tileID.z;var a=n.map(function(t){return r.tileID.getTilePoint(t)._round()});return this._boundsArray=new t.StructArrayLayout4i8,this._boundsArray.emplaceBack(a[0].x,a[0].y,0,0),this._boundsArray.emplaceBack(a[1].x,a[1].y,t.EXTENT,0),this._boundsArray.emplaceBack(a[3].x,a[3].y,0,t.EXTENT),this._boundsArray.emplaceBack(a[2].x,a[2].y,t.EXTENT,t.EXTENT),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})),this},r.prototype.prepare=function(){if(0!==Object.keys(this.tiles).length&&this.image){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,t.rasterBoundsAttributes.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture||(this.texture=new t.Texture(e,this.image,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var a=this.tiles[n];\"loaded\"!==a.state&&(a.state=\"loaded\",a.texture=this.texture)}}},r.prototype.loadTile=function(t,e){this.tileID&&this.tileID.equals(t.tileID.canonical)?(this.tiles[String(t.tileID.wrap)]=t,t.buckets={},e(null)):(t.state=\"errored\",e(null))},r.prototype.serialize=function(){return{type:\"image\",url:this.options.url,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return!1},r}(t.Evented),O=function(e){function r(t,r,n,a){e.call(this,t,r,n,a),this.roundZoom=!0,this.type=\"video\",this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1;var r=this.options;this.urls=[];for(var n=0,a=r.urls;n<a.length;n+=1){var i=a[n];this.urls.push(this.map._requestManager.transformRequest(i,t.ResourceType.Source).url)}t.getVideo(this.urls,function(r,n){e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(e.video=n,e.video.loop=!0,e.video.addEventListener(\"playing\",function(){e.map.triggerRepaint()}),e.map&&e.video.play(),e._finishLoading())})},r.prototype.pause=function(){this.video&&this.video.pause()},r.prototype.play=function(){this.video&&this.video.play()},r.prototype.seek=function(e){if(this.video){var r=this.video.seekable;e<r.start(0)||e>r.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError(\"Playback for this video can be set only between the \"+r.start(0)+\" and \"+r.end(0)+\"-second mark.\"))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,t.rasterBoundsAttributes.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var a=this.tiles[n];\"loaded\"!==a.state&&(a.state=\"loaded\",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(P),z=function(e){function r(r,n,a,i){e.call(this,r,n,a,i),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some(function(t){return!Array.isArray(t)||2!==t.length||t.some(function(t){return\"number\"!=typeof t})})||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"coordinates\"'))),n.animate&&\"boolean\"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'optional \"animate\" property must be a boolean value'))),n.canvas?\"string\"==typeof n.canvas||n.canvas instanceof t.window.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"canvas\"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error(\"Canvas dimensions cannot be less than or equal to zero.\"))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var a in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,t.rasterBoundsAttributes.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var i=this.tiles[a];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"canvas\",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];t<e.length;t+=1){var r=e[t];if(isNaN(r)||r<=0)return!0}return!1},r}(P),I={vector:S,raster:E,\"raster-dem\":L,geojson:C,video:O,image:P,canvas:z},D=function(e,r,n,a){var i=new I[r.type](e,r,n,a);if(i.id!==e)throw new Error(\"Expected Source id to be \"+e+\" instead of \"+i.id);return t.bindAll([\"load\",\"abort\",\"unload\",\"serialize\",\"prepare\"],i),i};function R(e,r){var n=t.identity([]);return t.translate(n,n,[1,1,0]),t.scale(n,n,[.5*e.width,.5*e.height,1]),t.multiply(n,n,e.calculatePosMatrix(r.toUnwrapped()))}function F(t,e,r,n,a){var i=function(t,e,r){if(t)for(var n=0,a=t;n<a.length;n+=1){var i=e[a[n]];if(i&&i.source===r&&\"fill-extrusion\"===i.type)return!0}else for(var o in e){var s=e[o];if(s.source===r&&\"fill-extrusion\"===s.type)return!0}return!1}(n&&n.layers,e,t.id),o=a.maxPitchScaleFactor(),s=t.tilesIn(r,o,i);s.sort(B);for(var l=[],c=0,u=s;c<u.length;c+=1){var h=u[c];l.push({wrappedTileID:h.tileID.wrapped().key,queryResults:h.tile.queryRenderedFeatures(e,t._state,h.queryGeometry,h.cameraQueryGeometry,h.scale,n,a,o,R(t.transform,h.tileID))})}var f=function(t){for(var e={},r={},n=0,a=t;n<a.length;n+=1){var i=a[n],o=i.queryResults,s=i.wrappedTileID,l=r[s]=r[s]||{};for(var c in o)for(var u=o[c],h=l[c]=l[c]||{},f=e[c]=e[c]||[],p=0,d=u;p<d.length;p+=1){var g=d[p];h[g.featureIndex]||(h[g.featureIndex]=!0,f.push(g))}}return e}(l);for(var p in f)f[p].forEach(function(e){var r=e.feature,n=t.getFeatureState(r.layer[\"source-layer\"],r.id);r.source=r.layer.source,r.layer[\"source-layer\"]&&(r.sourceLayer=r.layer[\"source-layer\"]),r.state=n});return f}function B(t,e){var r=t.tileID,n=e.tileID;return r.overscaledZ-n.overscaledZ||r.canonical.y-n.canonical.y||r.wrap-n.wrap||r.canonical.x-n.canonical.x}var N=function(t,e){this.max=t,this.onRemove=e,this.reset()};N.prototype.reset=function(){for(var t in this.data)for(var e=0,r=this.data[t];e<r.length;e+=1){var n=r[e];n.timeout&&clearTimeout(n.timeout),this.onRemove(n.value)}return this.data={},this.order=[],this},N.prototype.add=function(t,e,r){var n=this,a=t.wrapped().key;void 0===this.data[a]&&(this.data[a]=[]);var i={value:e,timeout:void 0};if(void 0!==r&&(i.timeout=setTimeout(function(){n.remove(t,i)},r)),this.data[a].push(i),this.order.push(a),this.order.length>this.max){var o=this._getAndRemoveByKey(this.order[0]);o&&this.onRemove(o)}return this},N.prototype.has=function(t){return t.wrapped().key in this.data},N.prototype.getAndRemove=function(t){return this.has(t)?this._getAndRemoveByKey(t.wrapped().key):null},N.prototype._getAndRemoveByKey=function(t){var e=this.data[t].shift();return e.timeout&&clearTimeout(e.timeout),0===this.data[t].length&&delete this.data[t],this.order.splice(this.order.indexOf(t),1),e.value},N.prototype.get=function(t){return this.has(t)?this.data[t.wrapped().key][0].value:null},N.prototype.remove=function(t,e){if(!this.has(t))return this;var r=t.wrapped().key,n=void 0===e?0:this.data[r].indexOf(e),a=this.data[r][n];return this.data[r].splice(n,1),a.timeout&&clearTimeout(a.timeout),0===this.data[r].length&&delete this.data[r],this.onRemove(a.value),this.order.splice(this.order.indexOf(r),1),this},N.prototype.setMaxSize=function(t){for(this.max=t;this.order.length>this.max;){var e=this._getAndRemoveByKey(this.order[0]);e&&this.onRemove(e)}return this};var j=function(t,e,r){this.context=t;var n=t.gl;this.buffer=n.createBuffer(),this.dynamicDraw=Boolean(r),this.context.unbindVAO(),t.bindElementBuffer.set(this.buffer),n.bufferData(n.ELEMENT_ARRAY_BUFFER,e.arrayBuffer,this.dynamicDraw?n.DYNAMIC_DRAW:n.STATIC_DRAW),this.dynamicDraw||delete e.arrayBuffer};j.prototype.bind=function(){this.context.bindElementBuffer.set(this.buffer)},j.prototype.updateData=function(t){var e=this.context.gl;this.context.unbindVAO(),this.bind(),e.bufferSubData(e.ELEMENT_ARRAY_BUFFER,0,t.arrayBuffer)},j.prototype.destroy=function(){var t=this.context.gl;this.buffer&&(t.deleteBuffer(this.buffer),delete this.buffer)};var V={Int8:\"BYTE\",Uint8:\"UNSIGNED_BYTE\",Int16:\"SHORT\",Uint16:\"UNSIGNED_SHORT\",Int32:\"INT\",Uint32:\"UNSIGNED_INT\",Float32:\"FLOAT\"},U=function(t,e,r,n){this.length=e.length,this.attributes=r,this.itemSize=e.bytesPerElement,this.dynamicDraw=n,this.context=t;var a=t.gl;this.buffer=a.createBuffer(),t.bindVertexBuffer.set(this.buffer),a.bufferData(a.ARRAY_BUFFER,e.arrayBuffer,this.dynamicDraw?a.DYNAMIC_DRAW:a.STATIC_DRAW),this.dynamicDraw||delete e.arrayBuffer};U.prototype.bind=function(){this.context.bindVertexBuffer.set(this.buffer)},U.prototype.updateData=function(t){var e=this.context.gl;this.bind(),e.bufferSubData(e.ARRAY_BUFFER,0,t.arrayBuffer)},U.prototype.enableAttributes=function(t,e){for(var r=0;r<this.attributes.length;r++){var n=this.attributes[r],a=e.attributes[n.name];void 0!==a&&t.enableVertexAttribArray(a)}},U.prototype.setVertexAttribPointers=function(t,e,r){for(var n=0;n<this.attributes.length;n++){var a=this.attributes[n],i=e.attributes[a.name];void 0!==i&&t.vertexAttribPointer(i,a.components,t[V[a.type]],!1,this.itemSize,a.offset+this.itemSize*(r||0))}},U.prototype.destroy=function(){var t=this.context.gl;this.buffer&&(t.deleteBuffer(this.buffer),delete this.buffer)};var q=function(t){this.gl=t.gl,this.default=this.getDefault(),this.current=this.default,this.dirty=!1};q.prototype.get=function(){return this.current},q.prototype.set=function(t){},q.prototype.getDefault=function(){return this.default},q.prototype.setDefault=function(){this.set(this.default)};var H=function(e){function r(){e.apply(this,arguments)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getDefault=function(){return t.Color.transparent},r.prototype.set=function(t){var e=this.current;(t.r!==e.r||t.g!==e.g||t.b!==e.b||t.a!==e.a||this.dirty)&&(this.gl.clearColor(t.r,t.g,t.b,t.a),this.current=t,this.dirty=!1)},r}(q),G=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return 1},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.clearDepth(t),this.current=t,this.dirty=!1)},e}(q),Y=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return 0},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.clearStencil(t),this.current=t,this.dirty=!1)},e}(q),W=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return[!0,!0,!0,!0]},e.prototype.set=function(t){var e=this.current;(t[0]!==e[0]||t[1]!==e[1]||t[2]!==e[2]||t[3]!==e[3]||this.dirty)&&(this.gl.colorMask(t[0],t[1],t[2],t[3]),this.current=t,this.dirty=!1)},e}(q),X=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return!0},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.depthMask(t),this.current=t,this.dirty=!1)},e}(q),Z=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return 255},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.stencilMask(t),this.current=t,this.dirty=!1)},e}(q),J=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return{func:this.gl.ALWAYS,ref:0,mask:255}},e.prototype.set=function(t){var e=this.current;(t.func!==e.func||t.ref!==e.ref||t.mask!==e.mask||this.dirty)&&(this.gl.stencilFunc(t.func,t.ref,t.mask),this.current=t,this.dirty=!1)},e}(q),K=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){var t=this.gl;return[t.KEEP,t.KEEP,t.KEEP]},e.prototype.set=function(t){var e=this.current;(t[0]!==e[0]||t[1]!==e[1]||t[2]!==e[2]||this.dirty)&&(this.gl.stencilOp(t[0],t[1],t[2]),this.current=t,this.dirty=!1)},e}(q),Q=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return!1},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;t?e.enable(e.STENCIL_TEST):e.disable(e.STENCIL_TEST),this.current=t,this.dirty=!1}},e}(q),$=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return[0,1]},e.prototype.set=function(t){var e=this.current;(t[0]!==e[0]||t[1]!==e[1]||this.dirty)&&(this.gl.depthRange(t[0],t[1]),this.current=t,this.dirty=!1)},e}(q),tt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return!1},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;t?e.enable(e.DEPTH_TEST):e.disable(e.DEPTH_TEST),this.current=t,this.dirty=!1}},e}(q),et=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return this.gl.LESS},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.depthFunc(t),this.current=t,this.dirty=!1)},e}(q),rt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return!1},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;t?e.enable(e.BLEND):e.disable(e.BLEND),this.current=t,this.dirty=!1}},e}(q),nt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){var t=this.gl;return[t.ONE,t.ZERO]},e.prototype.set=function(t){var e=this.current;(t[0]!==e[0]||t[1]!==e[1]||this.dirty)&&(this.gl.blendFunc(t[0],t[1]),this.current=t,this.dirty=!1)},e}(q),at=function(e){function r(){e.apply(this,arguments)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getDefault=function(){return t.Color.transparent},r.prototype.set=function(t){var e=this.current;(t.r!==e.r||t.g!==e.g||t.b!==e.b||t.a!==e.a||this.dirty)&&(this.gl.blendColor(t.r,t.g,t.b,t.a),this.current=t,this.dirty=!1)},r}(q),it=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return this.gl.FUNC_ADD},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.blendEquation(t),this.current=t,this.dirty=!1)},e}(q),ot=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return!1},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;t?e.enable(e.CULL_FACE):e.disable(e.CULL_FACE),this.current=t,this.dirty=!1}},e}(q),st=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return this.gl.BACK},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.cullFace(t),this.current=t,this.dirty=!1)},e}(q),lt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return this.gl.CCW},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.frontFace(t),this.current=t,this.dirty=!1)},e}(q),ct=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.useProgram(t),this.current=t,this.dirty=!1)},e}(q),ut=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return this.gl.TEXTURE0},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.activeTexture(t),this.current=t,this.dirty=!1)},e}(q),ht=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){var t=this.gl;return[0,0,t.drawingBufferWidth,t.drawingBufferHeight]},e.prototype.set=function(t){var e=this.current;(t[0]!==e[0]||t[1]!==e[1]||t[2]!==e[2]||t[3]!==e[3]||this.dirty)&&(this.gl.viewport(t[0],t[1],t[2],t[3]),this.current=t,this.dirty=!1)},e}(q),ft=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.bindFramebuffer(e.FRAMEBUFFER,t),this.current=t,this.dirty=!1}},e}(q),pt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.bindRenderbuffer(e.RENDERBUFFER,t),this.current=t,this.dirty=!1}},e}(q),dt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.bindTexture(e.TEXTURE_2D,t),this.current=t,this.dirty=!1}},e}(q),gt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.bindBuffer(e.ARRAY_BUFFER,t),this.current=t,this.dirty=!1}},e}(q),vt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){var e=this.gl;e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,t),this.current=t,this.dirty=!1},e}(q),mt=function(t){function e(e){t.call(this,e),this.vao=e.extVertexArrayObject}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){this.vao&&(t!==this.current||this.dirty)&&(this.vao.bindVertexArrayOES(t),this.current=t,this.dirty=!1)},e}(q),yt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return 4},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.pixelStorei(e.UNPACK_ALIGNMENT,t),this.current=t,this.dirty=!1}},e}(q),xt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return!1},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.pixelStorei(e.UNPACK_PREMULTIPLY_ALPHA_WEBGL,t),this.current=t,this.dirty=!1}},e}(q),bt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return!1},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.pixelStorei(e.UNPACK_FLIP_Y_WEBGL,t),this.current=t,this.dirty=!1}},e}(q),_t=function(t){function e(e,r){t.call(this,e),this.context=e,this.parent=r}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return null},e}(q),wt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.setDirty=function(){this.dirty=!0},e.prototype.set=function(t){if(t!==this.current||this.dirty){this.context.bindFramebuffer.set(this.parent);var e=this.gl;e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0),this.current=t,this.dirty=!1}},e}(_t),kt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){if(t!==this.current||this.dirty){this.context.bindFramebuffer.set(this.parent);var e=this.gl;e.framebufferRenderbuffer(e.FRAMEBUFFER,e.DEPTH_ATTACHMENT,e.RENDERBUFFER,t),this.current=t,this.dirty=!1}},e}(_t),Tt=function(t,e,r){this.context=t,this.width=e,this.height=r;var n=t.gl,a=this.framebuffer=n.createFramebuffer();this.colorAttachment=new wt(t,a),this.depthAttachment=new kt(t,a)};Tt.prototype.destroy=function(){var t=this.context.gl,e=this.colorAttachment.get();e&&t.deleteTexture(e);var r=this.depthAttachment.get();r&&t.deleteRenderbuffer(r),t.deleteFramebuffer(this.framebuffer)};var Mt=function(t,e,r){this.func=t,this.mask=e,this.range=r};Mt.ReadOnly=!1,Mt.ReadWrite=!0,Mt.disabled=new Mt(519,Mt.ReadOnly,[0,1]);var At=function(t,e,r,n,a,i){this.test=t,this.ref=e,this.mask=r,this.fail=n,this.depthFail=a,this.pass=i};At.disabled=new At({func:519,mask:0},0,0,7680,7680,7680);var St=function(t,e,r){this.blendFunction=t,this.blendColor=e,this.mask=r};St.disabled=new St(St.Replace=[1,0],t.Color.transparent,[!1,!1,!1,!1]),St.unblended=new St(St.Replace,t.Color.transparent,[!0,!0,!0,!0]),St.alphaBlended=new St([1,771],t.Color.transparent,[!0,!0,!0,!0]);var Et=function(t,e,r){this.enable=t,this.mode=e,this.frontFace=r};Et.disabled=new Et(!1,1029,2305),Et.backCCW=new Et(!0,1029,2305);var Lt=function(t){this.gl=t,this.extVertexArrayObject=this.gl.getExtension(\"OES_vertex_array_object\"),this.clearColor=new H(this),this.clearDepth=new G(this),this.clearStencil=new Y(this),this.colorMask=new W(this),this.depthMask=new X(this),this.stencilMask=new Z(this),this.stencilFunc=new J(this),this.stencilOp=new K(this),this.stencilTest=new Q(this),this.depthRange=new $(this),this.depthTest=new tt(this),this.depthFunc=new et(this),this.blend=new rt(this),this.blendFunc=new nt(this),this.blendColor=new at(this),this.blendEquation=new it(this),this.cullFace=new ot(this),this.cullFaceSide=new st(this),this.frontFace=new lt(this),this.program=new ct(this),this.activeTexture=new ut(this),this.viewport=new ht(this),this.bindFramebuffer=new ft(this),this.bindRenderbuffer=new pt(this),this.bindTexture=new dt(this),this.bindVertexBuffer=new gt(this),this.bindElementBuffer=new vt(this),this.bindVertexArrayOES=this.extVertexArrayObject&&new mt(this),this.pixelStoreUnpack=new yt(this),this.pixelStoreUnpackPremultiplyAlpha=new xt(this),this.pixelStoreUnpackFlipY=new bt(this),this.extTextureFilterAnisotropic=t.getExtension(\"EXT_texture_filter_anisotropic\")||t.getExtension(\"MOZ_EXT_texture_filter_anisotropic\")||t.getExtension(\"WEBKIT_EXT_texture_filter_anisotropic\"),this.extTextureFilterAnisotropic&&(this.extTextureFilterAnisotropicMax=t.getParameter(this.extTextureFilterAnisotropic.MAX_TEXTURE_MAX_ANISOTROPY_EXT)),this.extTextureHalfFloat=t.getExtension(\"OES_texture_half_float\"),this.extTextureHalfFloat&&t.getExtension(\"OES_texture_half_float_linear\")};Lt.prototype.setDefault=function(){this.unbindVAO(),this.clearColor.setDefault(),this.clearDepth.setDefault(),this.clearStencil.setDefault(),this.colorMask.setDefault(),this.depthMask.setDefault(),this.stencilMask.setDefault(),this.stencilFunc.setDefault(),this.stencilOp.setDefault(),this.stencilTest.setDefault(),this.depthRange.setDefault(),this.depthTest.setDefault(),this.depthFunc.setDefault(),this.blend.setDefault(),this.blendFunc.setDefault(),this.blendColor.setDefault(),this.blendEquation.setDefault(),this.cullFace.setDefault(),this.cullFaceSide.setDefault(),this.frontFace.setDefault(),this.program.setDefault(),this.activeTexture.setDefault(),this.bindFramebuffer.setDefault(),this.pixelStoreUnpack.setDefault(),this.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.pixelStoreUnpackFlipY.setDefault()},Lt.prototype.setDirty=function(){this.clearColor.dirty=!0,this.clearDepth.dirty=!0,this.clearStencil.dirty=!0,this.colorMask.dirty=!0,this.depthMask.dirty=!0,this.stencilMask.dirty=!0,this.stencilFunc.dirty=!0,this.stencilOp.dirty=!0,this.stencilTest.dirty=!0,this.depthRange.dirty=!0,this.depthTest.dirty=!0,this.depthFunc.dirty=!0,this.blend.dirty=!0,this.blendFunc.dirty=!0,this.blendColor.dirty=!0,this.blendEquation.dirty=!0,this.cullFace.dirty=!0,this.cullFaceSide.dirty=!0,this.frontFace.dirty=!0,this.program.dirty=!0,this.activeTexture.dirty=!0,this.viewport.dirty=!0,this.bindFramebuffer.dirty=!0,this.bindRenderbuffer.dirty=!0,this.bindTexture.dirty=!0,this.bindVertexBuffer.dirty=!0,this.bindElementBuffer.dirty=!0,this.extVertexArrayObject&&(this.bindVertexArrayOES.dirty=!0),this.pixelStoreUnpack.dirty=!0,this.pixelStoreUnpackPremultiplyAlpha.dirty=!0,this.pixelStoreUnpackFlipY.dirty=!0},Lt.prototype.createIndexBuffer=function(t,e){return new j(this,t,e)},Lt.prototype.createVertexBuffer=function(t,e,r){return new U(this,t,e,r)},Lt.prototype.createRenderbuffer=function(t,e,r){var n=this.gl,a=n.createRenderbuffer();return this.bindRenderbuffer.set(a),n.renderbufferStorage(n.RENDERBUFFER,t,e,r),this.bindRenderbuffer.set(null),a},Lt.prototype.createFramebuffer=function(t,e){return new Tt(this,t,e)},Lt.prototype.clear=function(t){var e=t.color,r=t.depth,n=this.gl,a=0;e&&(a|=n.COLOR_BUFFER_BIT,this.clearColor.set(e),this.colorMask.set([!0,!0,!0,!0])),void 0!==r&&(a|=n.DEPTH_BUFFER_BIT,this.depthRange.set([0,1]),this.clearDepth.set(r),this.depthMask.set(!0)),n.clear(a)},Lt.prototype.setCullFace=function(t){!1===t.enable?this.cullFace.set(!1):(this.cullFace.set(!0),this.cullFaceSide.set(t.mode),this.frontFace.set(t.frontFace))},Lt.prototype.setDepthMode=function(t){t.func!==this.gl.ALWAYS||t.mask?(this.depthTest.set(!0),this.depthFunc.set(t.func),this.depthMask.set(t.mask),this.depthRange.set(t.range)):this.depthTest.set(!1)},Lt.prototype.setStencilMode=function(t){t.test.func!==this.gl.ALWAYS||t.mask?(this.stencilTest.set(!0),this.stencilMask.set(t.mask),this.stencilOp.set([t.fail,t.depthFail,t.pass]),this.stencilFunc.set({func:t.test.func,ref:t.ref,mask:t.test.mask})):this.stencilTest.set(!1)},Lt.prototype.setColorMode=function(e){t.deepEqual(e.blendFunction,St.Replace)?this.blend.set(!1):(this.blend.set(!0),this.blendFunc.set(e.blendFunction),this.blendColor.set(e.blendColor)),this.colorMask.set(e.mask)},Lt.prototype.unbindVAO=function(){this.extVertexArrayObject&&this.bindVertexArrayOES.set(null)};var Ct=function(e){function r(r,n,a){var i=this;e.call(this),this.id=r,this.dispatcher=a,this.on(\"data\",function(t){\"source\"===t.dataType&&\"metadata\"===t.sourceDataType&&(i._sourceLoaded=!0),i._sourceLoaded&&!i._paused&&\"source\"===t.dataType&&\"content\"===t.sourceDataType&&(i.reload(),i.transform&&i.update(i.transform))}),this.on(\"error\",function(){i._sourceErrored=!0}),this._source=D(r,n,a,this),this._tiles={},this._cache=new N(0,this._unloadTile.bind(this)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._coveredTiles={},this._state=new t.SourceFeatureState}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.onAdd=function(t){this.map=t,this._maxTileCacheSize=t?t._maxTileCacheSize:null,this._source&&this._source.onAdd&&this._source.onAdd(t)},r.prototype.onRemove=function(t){this._source&&this._source.onRemove&&this._source.onRemove(t)},r.prototype.loaded=function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;if(!this._source.loaded())return!1;for(var t in this._tiles){var e=this._tiles[t];if(\"loaded\"!==e.state&&\"errored\"!==e.state)return!1}return!0},r.prototype.getSource=function(){return this._source},r.prototype.pause=function(){this._paused=!0},r.prototype.resume=function(){if(this._paused){var t=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,t&&this.reload(),this.transform&&this.update(this.transform)}},r.prototype._loadTile=function(t,e){return this._source.loadTile(t,e)},r.prototype._unloadTile=function(t){if(this._source.unloadTile)return this._source.unloadTile(t,function(){})},r.prototype._abortTile=function(t){if(this._source.abortTile)return this._source.abortTile(t,function(){})},r.prototype.serialize=function(){return this._source.serialize()},r.prototype.prepare=function(t){for(var e in this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null),this._tiles){var r=this._tiles[e];r.upload(t),r.prepare(this.map.style.imageManager)}},r.prototype.getIds=function(){return Object.keys(this._tiles).map(Number).sort(Pt)},r.prototype.getRenderableIds=function(e){var r=this,n=[];for(var a in this._tiles)this._isIdRenderable(+a,e)&&n.push(+a);return e?n.sort(function(e,n){var a=r._tiles[e].tileID,i=r._tiles[n].tileID,o=new t.Point(a.canonical.x,a.canonical.y)._rotate(r.transform.angle),s=new t.Point(i.canonical.x,i.canonical.y)._rotate(r.transform.angle);return a.overscaledZ-i.overscaledZ||s.y-o.y||s.x-o.x}):n.sort(Pt)},r.prototype.hasRenderableParent=function(t){var e=this.findLoadedParent(t,0);return!!e&&this._isIdRenderable(e.tileID.key)},r.prototype._isIdRenderable=function(t,e){return this._tiles[t]&&this._tiles[t].hasData()&&!this._coveredTiles[t]&&(e||!this._tiles[t].holdingForFade())},r.prototype.reload=function(){if(this._paused)this._shouldReloadOnResume=!0;else for(var t in this._cache.reset(),this._tiles)\"errored\"!==this._tiles[t].state&&this._reloadTile(t,\"reloading\")},r.prototype._reloadTile=function(t,e){var r=this._tiles[t];r&&(\"loading\"!==r.state&&(r.state=e),this._loadTile(r,this._tileLoaded.bind(this,r,t,e)))},r.prototype._tileLoaded=function(e,r,n,a){if(a)return e.state=\"errored\",void(404!==a.status?this._source.fire(new t.ErrorEvent(a,{tile:e})):this.update(this.transform));e.timeAdded=t.browser.now(),\"expired\"===n&&(e.refreshedUponExpiration=!0),this._setTileReloadTimer(r,e),\"raster-dem\"===this.getSource().type&&e.dem&&this._backfillDEM(e),this._state.initializeTileState(e,this.map?this.map.painter:null),this._source.fire(new t.Event(\"data\",{dataType:\"source\",tile:e,coord:e.tileID}))},r.prototype._backfillDEM=function(t){for(var e=this.getRenderableIds(),r=0;r<e.length;r++){var n=e[r];if(t.neighboringTiles&&t.neighboringTiles[n]){var a=this.getTileByID(n);i(t,a),i(a,t)}}function i(t,e){t.needsHillshadePrepare=!0;var r=e.tileID.canonical.x-t.tileID.canonical.x,n=e.tileID.canonical.y-t.tileID.canonical.y,a=Math.pow(2,t.tileID.canonical.z),i=e.tileID.key;0===r&&0===n||Math.abs(n)>1||(Math.abs(r)>1&&(1===Math.abs(r+a)?r+=a:1===Math.abs(r-a)&&(r-=a)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[i]&&(t.neighboringTiles[i].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype.getZoom=function(t){return t.zoom+t.scaleZoom(t.tileSize/this._source.tileSize)},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var a in this._tiles){var i=this._tiles[a];if(!(n[a]||!i.hasData()||i.tileID.overscaledZ<=e||i.tileID.overscaledZ>r)){for(var o=i.tileID;i&&i.tileID.overscaledZ>e+1;){var s=i.tileID.scaledTo(i.tileID.overscaledZ-1);(i=this._tiles[s.key])&&i.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){for(var r=t.overscaledZ-1;r>=e;r--){var n=t.scaledTo(r);if(!n)return;var a=String(n.key),i=this._tiles[a];if(i&&i.hasData())return i;if(this._cache.has(n))return this._cache.get(n)}},r.prototype.updateCacheSize=function(t){var e=(Math.ceil(t.width/this._source.tileSize)+1)*(Math.ceil(t.height/this._source.tileSize)+1),r=Math.floor(5*e),n=\"number\"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,r):r;this._cache.setMaxSize(n)},r.prototype.handleWrapJump=function(t){var e=(t-(void 0===this._prevLng?t:this._prevLng))/360,r=Math.round(e);if(this._prevLng=t,r){var n={};for(var a in this._tiles){var i=this._tiles[a];i.tileID=i.tileID.unwrapTo(i.tileID.wrap+r),n[i.tileID.key]=i}for(var o in this._tiles=n,this._timers)clearTimeout(this._timers[o]),delete this._timers[o];for(var s in this._tiles){var l=this._tiles[s];this._setTileReloadTimer(s,l)}}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var a;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?a=e.getVisibleUnwrappedCoordinates(this._source.tileID).map(function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)}):(a=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(a=a.filter(function(t){return n._source.hasTile(t)}))):a=[];var i=(this._source.roundZoom?Math.round:Math.floor)(this.getZoom(e)),o=Math.max(i-r.maxOverzooming,this._source.minzoom),s=Math.max(i+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(a,i);if(Ot(this._source.type)){for(var c={},u={},h=0,f=Object.keys(l);h<f.length;h+=1){var p=f[h],d=l[p],g=this._tiles[p];if(g&&!(g.fadeEndTime&&g.fadeEndTime<=t.browser.now())){var v=this.findLoadedParent(d,o);v&&(this._addTile(v.tileID),c[v.tileID.key]=v.tileID),u[p]=d}}for(var m in this._retainLoadedChildren(u,i,s,l),c)l[m]||(this._coveredTiles[m]=!0,l[m]=c[m])}for(var y in l)this._tiles[y].clearFadeHold();for(var x=0,b=t.keysDifference(this._tiles,l);x<b.length;x+=1){var _=b[x],w=this._tiles[_];w.hasSymbolBuckets&&!w.holdingForFade()?w.setHoldDuration(this.map._fadeDuration):w.hasSymbolBuckets&&!w.symbolFadeFinished()||this._removeTile(_)}}},r.prototype.releaseSymbolFadeTiles=function(){for(var t in this._tiles)this._tiles[t].holdingForFade()&&this._removeTile(t)},r.prototype._updateRetainedTiles=function(t,e){for(var n={},a={},i=Math.max(e-r.maxOverzooming,this._source.minzoom),o=Math.max(e+r.maxUnderzooming,this._source.minzoom),s={},l=0,c=t;l<c.length;l+=1){var u=c[l],h=this._addTile(u);n[u.key]=u,h.hasData()||e<this._source.maxzoom&&(s[u.key]=u)}this._retainLoadedChildren(s,e,o,n);for(var f=0,p=t;f<p.length;f+=1){var d=p[f],g=this._tiles[d.key];if(!g.hasData()){if(e+1>this._source.maxzoom){var v=d.children(this._source.maxzoom)[0],m=this.getTile(v);if(m&&m.hasData()){n[v.key]=v;continue}}else{var y=d.children(this._source.maxzoom);if(n[y[0].key]&&n[y[1].key]&&n[y[2].key]&&n[y[3].key])continue}for(var x=g.wasRequested(),b=d.overscaledZ-1;b>=i;--b){var _=d.scaledTo(b);if(a[_.key])break;if(a[_.key]=!0,!(g=this.getTile(_))&&x&&(g=this._addTile(_)),g&&(n[_.key]=_,x=g.wasRequested(),g.hasData()))break}}}return n},r.prototype._addTile=function(e){var r=this._tiles[e.key];if(r)return r;(r=this._cache.getAndRemove(e))&&(this._setTileReloadTimer(e.key,r),r.tileID=e,this._state.initializeTileState(r,this.map?this.map.painter:null),this._cacheTimers[e.key]&&(clearTimeout(this._cacheTimers[e.key]),delete this._cacheTimers[e.key],this._setTileReloadTimer(e.key,r)));var n=Boolean(r);return n||(r=new t.Tile(e,this._source.tileSize*e.overscaleFactor()),this._loadTile(r,this._tileLoaded.bind(this,r,e.key,r.state))),r?(r.uses++,this._tiles[e.key]=r,n||this._source.fire(new t.Event(\"dataloading\",{tile:r,coord:r.tileID,dataType:\"source\"})),r):null},r.prototype._setTileReloadTimer=function(t,e){var r=this;t in this._timers&&(clearTimeout(this._timers[t]),delete this._timers[t]);var n=e.getExpiryTimeout();n&&(this._timers[t]=setTimeout(function(){r._reloadTile(t,\"expired\"),delete r._timers[t]},n))},r.prototype._removeTile=function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this._timers[t]&&(clearTimeout(this._timers[t]),delete this._timers[t]),e.uses>0||(e.hasData()&&\"reloading\"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var a=this,i=[],o=this.transform;if(!o)return i;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map(function(t){return o.pointCoordinate(t)}),c=s.map(function(t){return o.pointCoordinate(t)}),u=this.getIds(),h=1/0,f=1/0,p=-1/0,d=-1/0,g=0,v=c;g<v.length;g+=1){var m=v[g];h=Math.min(h,m.x),f=Math.min(f,m.y),p=Math.max(p,m.x),d=Math.max(d,m.y)}for(var y=function(e){var n=a._tiles[u[e]];if(!n.holdingForFade()){var s=n.tileID,g=Math.pow(2,o.zoom-n.tileID.overscaledZ),v=r*n.queryPadding*t.EXTENT/n.tileSize/g,m=[s.getTilePoint(new t.MercatorCoordinate(h,f)),s.getTilePoint(new t.MercatorCoordinate(p,d))];if(m[0].x-v<t.EXTENT&&m[0].y-v<t.EXTENT&&m[1].x+v>=0&&m[1].y+v>=0){var y=l.map(function(t){return s.getTilePoint(t)}),x=c.map(function(t){return s.getTilePoint(t)});i.push({tile:n,tileID:s,queryGeometry:y,cameraQueryGeometry:x,scale:g})}}},x=0;x<u.length;x++)y(x);return i},r.prototype.getVisibleCoordinates=function(t){for(var e=this,r=this.getRenderableIds(t).map(function(t){return e._tiles[t].tileID}),n=0,a=r;n<a.length;n+=1){var i=a[n];i.posMatrix=this.transform.calculatePosMatrix(i.toUnwrapped())}return r},r.prototype.hasTransition=function(){if(this._source.hasTransition())return!0;if(Ot(this._source.type))for(var e in this._tiles){var r=this._tiles[e];if(void 0!==r.fadeEndTime&&r.fadeEndTime>=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.updateState(t,e,r)},r.prototype.removeFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.removeFeatureState(t,e,r)},r.prototype.getFeatureState=function(t,e){return t=t||\"_geojsonTileLayer\",this._state.getState(t,e)},r}(t.Evented);function Pt(t,e){return t%32-e%32||e-t}function Ot(t){return\"raster\"===t||\"image\"===t||\"video\"===t}function zt(){return new t.window.Worker($n.workerUrl)}Ct.maxOverzooming=10,Ct.maxUnderzooming=3;var It=function(){this.active={}};It.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length<It.workerCount;)this.workers.push(new zt);return this.active[t]=!0,this.workers.slice()},It.prototype.release=function(t){delete this.active[t],0===Object.keys(this.active).length&&(this.workers.forEach(function(t){t.terminate()}),this.workers=null)};var Dt,Rt=Math.floor(t.browser.hardwareConcurrency/2);function Ft(e,r){var n={};for(var a in e)\"ref\"!==a&&(n[a]=e[a]);return t.refProperties.forEach(function(t){t in r&&(n[t]=r[t])}),n}function Bt(t){t=t.slice();for(var e=Object.create(null),r=0;r<t.length;r++)e[t[r].id]=t[r];for(var n=0;n<t.length;n++)\"ref\"in t[n]&&(t[n]=Ft(t[n],e[t[n].ref]));return t}It.workerCount=Math.max(Math.min(Rt,6),1);var Nt={setStyle:\"setStyle\",addLayer:\"addLayer\",removeLayer:\"removeLayer\",setPaintProperty:\"setPaintProperty\",setLayoutProperty:\"setLayoutProperty\",setFilter:\"setFilter\",addSource:\"addSource\",removeSource:\"removeSource\",setGeoJSONSourceData:\"setGeoJSONSourceData\",setLayerZoomRange:\"setLayerZoomRange\",setLayerProperty:\"setLayerProperty\",setCenter:\"setCenter\",setZoom:\"setZoom\",setBearing:\"setBearing\",setPitch:\"setPitch\",setSprite:\"setSprite\",setGlyphs:\"setGlyphs\",setTransition:\"setTransition\",setLight:\"setLight\"};function jt(t,e,r){r.push({command:Nt.addSource,args:[t,e[t]]})}function Vt(t,e,r){e.push({command:Nt.removeSource,args:[t]}),r[t]=!0}function Ut(t,e,r,n){Vt(t,r,n),jt(t,e,r)}function qt(e,r,n){var a;for(a in e[n])if(e[n].hasOwnProperty(a)&&\"data\"!==a&&!t.deepEqual(e[n][a],r[n][a]))return!1;for(a in r[n])if(r[n].hasOwnProperty(a)&&\"data\"!==a&&!t.deepEqual(e[n][a],r[n][a]))return!1;return!0}function Ht(e,r,n,a,i,o){var s;for(s in r=r||{},e=e||{})e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[a,s,r[s],i]}));for(s in r)r.hasOwnProperty(s)&&!e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[a,s,r[s],i]}))}function Gt(t){return t.id}function Yt(t,e){return t[e.id]=e,t}var Wt=function(t,e,r){var n=this.boxCells=[],a=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var i=0;i<this.xCellCount*this.yCellCount;i++)n.push([]),a.push([]);this.circleKeys=[],this.boxKeys=[],this.bboxes=[],this.circles=[],this.width=t,this.height=e,this.xScale=this.xCellCount/t,this.yScale=this.yCellCount/e,this.boxUid=0,this.circleUid=0};function Xt(e,r,n,a,i){var o=t.create();return r?(t.scale(o,o,[1/i,1/i,1]),n||t.rotateZ(o,o,a.angle)):t.multiply(o,a.labelPlaneMatrix,e),o}function Zt(e,r,n,a,i){if(r){var o=t.clone(e);return t.scale(o,o,[i,i,1]),n||t.rotateZ(o,o,-a.angle),o}return a.glCoordMatrix}function Jt(e,r){var n=[e.x,e.y,0,1];oe(n,n,r);var a=n[3];return{point:new t.Point(n[0]/a,n[1]/a),signedDistanceFromCamera:a}}function Kt(t,e){var r=t[0]/t[3],n=t[1]/t[3];return r>=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function Qt(e,r,n,a,i,o,s,l){var c=a?e.textSizeData:e.iconSizeData,u=t.evaluateSizeForZoom(c,n.transform.zoom),h=[256/n.width*2+1,256/n.height*2+1],f=a?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;f.clear();for(var p=e.lineVertexArray,d=a?e.text.placedSymbolArray:e.icon.placedSymbolArray,g=n.transform.width/n.transform.height,v=!1,m=0;m<d.length;m++){var y=d.get(m);if(y.hidden||y.writingMode===t.WritingMode.vertical&&!v)ie(y.numGlyphs,f);else{v=!1;var x=[y.anchorX,y.anchorY,0,1];if(t.transformMat4(x,x,r),Kt(x,h)){var b=.5+x[3]/n.transform.cameraToCenterDistance*.5,_=t.evaluateSizeForFeature(c,u,y),w=s?_*b:_/b,k=new t.Point(y.anchorX,y.anchorY),T=Jt(k,i).point,M={},A=ee(y,w,!1,l,r,i,o,e.glyphOffsetArray,p,f,T,k,M,g);v=A.useVertical,(A.notEnoughRoom||v||A.needsFlipping&&ee(y,w,!0,l,r,i,o,e.glyphOffsetArray,p,f,T,k,M,g).notEnoughRoom)&&ie(y.numGlyphs,f)}else ie(y.numGlyphs,f)}}a?e.text.dynamicLayoutVertexBuffer.updateData(f):e.icon.dynamicLayoutVertexBuffer.updateData(f)}function $t(t,e,r,n,a,i,o,s,l,c,u,h){var f=s.glyphStartIndex+s.numGlyphs,p=s.lineStartIndex,d=s.lineStartIndex+s.lineLength,g=e.getoffsetX(s.glyphStartIndex),v=e.getoffsetX(f-1),m=ne(t*g,r,n,a,i,o,s.segment,p,d,l,c,u,h);if(!m)return null;var y=ne(t*v,r,n,a,i,o,s.segment,p,d,l,c,u,h);return y?{first:m,last:y}:null}function te(e,r,n,a){return e===t.WritingMode.horizontal&&Math.abs(n.y-r.y)>Math.abs(n.x-r.x)*a?{useVertical:!0}:(e===t.WritingMode.vertical?r.y<n.y:r.x>n.x)?{needsFlipping:!0}:null}function ee(e,r,n,a,i,o,s,l,c,u,h,f,p,d){var g,v=r/24,m=e.lineOffsetX*v,y=e.lineOffsetY*v;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=$t(v,l,m,y,n,h,f,e,c,o,p,!1);if(!w)return{notEnoughRoom:!0};var k=Jt(w.first.point,s).point,T=Jt(w.last.point,s).point;if(a&&!n){var M=te(e.writingMode,k,T,d);if(M)return M}g=[w.first];for(var A=e.glyphStartIndex+1;A<x-1;A++)g.push(ne(v*l.getoffsetX(A),m,y,n,h,f,e.segment,b,_,c,o,p,!1));g.push(w.last)}else{if(a&&!n){var S=Jt(f,i).point,E=e.lineStartIndex+e.segment+1,L=new t.Point(c.getx(E),c.gety(E)),C=Jt(L,i),P=C.signedDistanceFromCamera>0?C.point:re(f,L,S,1,i),O=te(e.writingMode,S,P,d);if(O)return O}var z=ne(v*l.getoffsetX(e.glyphStartIndex),m,y,n,h,f,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,c,o,p,!1);if(!z)return{notEnoughRoom:!0};g=[z]}for(var I=0,D=g;I<D.length;I+=1){var R=D[I];t.addDynamicAttributes(u,R.point,R.angle)}return{}}function re(t,e,r,n,a){var i=Jt(t.add(t.sub(e)._unit()),a).point,o=r.sub(i);return r.add(o._mult(n/o.mag()))}function ne(e,r,n,a,i,o,s,l,c,u,h,f,p){var d=a?e-r:e+r,g=d>0?1:-1,v=0;a&&(g*=-1,v=Math.PI),g<0&&(v+=Math.PI);for(var m=g>0?l+s:l+s+1,y=m,x=i,b=i,_=0,w=0,k=Math.abs(d);_+w<=k;){if((m+=g)<l||m>=c)return null;if(b=x,void 0===(x=f[m])){var T=new t.Point(u.getx(m),u.gety(m)),M=Jt(T,h);if(M.signedDistanceFromCamera>0)x=f[m]=M.point;else{var A=m-g;x=re(0===_?o:new t.Point(u.getx(A),u.gety(A)),T,b,k-_+1,h)}}_+=w,w=b.dist(x)}var S=(k-_)/w,E=x.sub(b),L=E.mult(S)._add(b);return L._add(E._unit()._perp()._mult(n*g)),{point:L,angle:v+Math.atan2(x.y-b.y,x.x-b.x),tileDistance:p?{prevTileDistance:m-g===y?0:u.gettileUnitDistanceFromAnchor(m-g),lastSegmentViewportDistance:k-_}:null}}Wt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Wt.prototype.insert=function(t,e,r,n,a){this._forEachCell(e,r,n,a,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(a)},Wt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Wt.prototype._insertBoxCell=function(t,e,r,n,a,i){this.boxCells[a].push(i)},Wt.prototype._insertCircleCell=function(t,e,r,n,a,i){this.circleCells[a].push(i)},Wt.prototype._query=function(t,e,r,n,a,i){if(r<0||t>this.width||n<0||e>this.height)return!a&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(a)return!0;for(var s=0;s<this.boxKeys.length;s++)o.push({key:this.boxKeys[s],x1:this.bboxes[4*s],y1:this.bboxes[4*s+1],x2:this.bboxes[4*s+2],y2:this.bboxes[4*s+3]});for(var l=0;l<this.circleKeys.length;l++){var c=this.circles[3*l],u=this.circles[3*l+1],h=this.circles[3*l+2];o.push({key:this.circleKeys[l],x1:c-h,y1:u-h,x2:c+h,y2:u+h})}return i?o.filter(i):o}var f={hitTest:a,seenUids:{box:{},circle:{}}};return this._forEachCell(t,e,r,n,this._queryCell,o,f,i),a?o.length>0:o},Wt.prototype._queryCircle=function(t,e,r,n,a){var i=t-r,o=t+r,s=e-r,l=e+r;if(o<0||i>this.width||l<0||s>this.height)return!n&&[];var c=[],u={hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}};return this._forEachCell(i,s,o,l,this._queryCellCircle,c,u,a),n?c.length>0:c},Wt.prototype.query=function(t,e,r,n,a){return this._query(t,e,r,n,!1,a)},Wt.prototype.hitTest=function(t,e,r,n,a){return this._query(t,e,r,n,!0,a)},Wt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Wt.prototype._queryCell=function(t,e,r,n,a,i,o,s){var l=o.seenUids,c=this.boxCells[a];if(null!==c)for(var u=this.bboxes,h=0,f=c;h<f.length;h+=1){var p=f[h];if(!l.box[p]){l.box[p]=!0;var d=4*p;if(t<=u[d+2]&&e<=u[d+3]&&r>=u[d+0]&&n>=u[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return i.push(!0),!0;i.push({key:this.boxKeys[p],x1:u[d],y1:u[d+1],x2:u[d+2],y2:u[d+3]})}}}var g=this.circleCells[a];if(null!==g)for(var v=this.circles,m=0,y=g;m<y.length;m+=1){var x=y[m];if(!l.circle[x]){l.circle[x]=!0;var b=3*x;if(this._circleAndRectCollide(v[b],v[b+1],v[b+2],t,e,r,n)&&(!s||s(this.circleKeys[x]))){if(o.hitTest)return i.push(!0),!0;var _=v[b],w=v[b+1],k=v[b+2];i.push({key:this.circleKeys[x],x1:_-k,y1:w-k,x2:_+k,y2:w+k})}}}},Wt.prototype._queryCellCircle=function(t,e,r,n,a,i,o,s){var l=o.circle,c=o.seenUids,u=this.boxCells[a];if(null!==u)for(var h=this.bboxes,f=0,p=u;f<p.length;f+=1){var d=p[f];if(!c.box[d]){c.box[d]=!0;var g=4*d;if(this._circleAndRectCollide(l.x,l.y,l.radius,h[g+0],h[g+1],h[g+2],h[g+3])&&(!s||s(this.boxKeys[d])))return i.push(!0),!0}}var v=this.circleCells[a];if(null!==v)for(var m=this.circles,y=0,x=v;y<x.length;y+=1){var b=x[y];if(!c.circle[b]){c.circle[b]=!0;var _=3*b;if(this._circlesCollide(m[_],m[_+1],m[_+2],l.x,l.y,l.radius)&&(!s||s(this.circleKeys[b])))return i.push(!0),!0}}},Wt.prototype._forEachCell=function(t,e,r,n,a,i,o,s){for(var l=this._convertToXCellCoord(t),c=this._convertToYCellCoord(e),u=this._convertToXCellCoord(r),h=this._convertToYCellCoord(n),f=l;f<=u;f++)for(var p=c;p<=h;p++){var d=this.xCellCount*p+f;if(a.call(this,t,e,r,n,d,i,o,s))return}},Wt.prototype._convertToXCellCoord=function(t){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(t*this.xScale)))},Wt.prototype._convertToYCellCoord=function(t){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(t*this.yScale)))},Wt.prototype._circlesCollide=function(t,e,r,n,a,i){var o=n-t,s=a-e,l=r+i;return l*l>o*o+s*s},Wt.prototype._circleAndRectCollide=function(t,e,r,n,a,i,o){var s=(i-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var c=(o-a)/2,u=Math.abs(e-(a+c));if(u>c+r)return!1;if(l<=s||u<=c)return!0;var h=l-s,f=u-c;return h*h+f*f<=r*r};var ae=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function ie(t,e){for(var r=0;r<t;r++){var n=e.length;e.resize(n+4),e.float32.set(ae,3*n)}}function oe(t,e,r){var n=e[0],a=e[1];return t[0]=r[0]*n+r[4]*a+r[12],t[1]=r[1]*n+r[5]*a+r[13],t[3]=r[3]*n+r[7]*a+r[15],t}var se=function(t,e,r){void 0===e&&(e=new Wt(t.width+200,t.height+200,25)),void 0===r&&(r=new Wt(t.width+200,t.height+200,25)),this.transform=t,this.grid=e,this.ignoredGrid=r,this.pitchfactor=Math.cos(t._pitch)*t.cameraToCenterDistance,this.screenRightBoundary=t.width+100,this.screenBottomBoundary=t.height+100,this.gridRightBoundary=t.width+200,this.gridBottomBoundary=t.height+200};function le(t,e,r){t[e+4]=r?1:0}function ce(e,r,n){return r*(t.EXTENT/(e.tileSize*Math.pow(2,n-e.tileID.overscaledZ)))}se.prototype.placeCollisionBox=function(t,e,r,n,a){var i=this.projectAndGetPerspectiveRatio(n,t.anchorPointX,t.anchorPointY),o=r*i.perspectiveRatio,s=t.x1*o+i.point.x,l=t.y1*o+i.point.y,c=t.x2*o+i.point.x,u=t.y2*o+i.point.y;return!this.isInsideGrid(s,l,c,u)||!e&&this.grid.hitTest(s,l,c,u,a)?{box:[],offscreen:!1}:{box:[s,l,c,u],offscreen:this.isOffscreen(s,l,c,u)}},se.prototype.approximateTileDistance=function(t,e,r,n,a){var i=a?1:n/this.pitchfactor,o=t.lastSegmentViewportDistance*r;return t.prevTileDistance+o+(i-1)*o*Math.abs(Math.sin(e))},se.prototype.placeCollisionCircles=function(e,r,n,a,i,o,s,l,c,u,h,f,p){var d=[],g=this.projectAnchor(c,i.anchorX,i.anchorY),v=l/24,m=i.lineOffsetX*l,y=i.lineOffsetY*l,x=new t.Point(i.anchorX,i.anchorY),b=$t(v,s,m,y,!1,Jt(x,u).point,x,i,o,u,{},!0),_=!1,w=!1,k=!0,T=g.perspectiveRatio*a,M=1/(a*n),A=0,S=0;b&&(A=this.approximateTileDistance(b.first.tileDistance,b.first.angle,M,g.cameraDistance,f),S=this.approximateTileDistance(b.last.tileDistance,b.last.angle,M,g.cameraDistance,f));for(var E=0;E<e.length;E+=5){var L=e[E],C=e[E+1],P=e[E+2],O=e[E+3];if(!b||O<-A||O>S)le(e,E,!1);else{var z=this.projectPoint(c,L,C),I=P*T;if(d.length>0){var D=z.x-d[d.length-4],R=z.y-d[d.length-3];if(I*I*2>D*D+R*R&&E+8<e.length){var F=e[E+8];if(F>-A&&F<S){le(e,E,!1);continue}}}var B=E/5;d.push(z.x,z.y,I,B),le(e,E,!0);var N=z.x-I,j=z.y-I,V=z.x+I,U=z.y+I;if(k=k&&this.isOffscreen(N,j,V,U),w=w||this.isInsideGrid(N,j,V,U),!r&&this.grid.hitTestCircle(z.x,z.y,I,p)){if(!h)return{circles:[],offscreen:!1};_=!0}}}return{circles:_||!w?[]:d,offscreen:k}},se.prototype.queryRenderedSymbols=function(e){if(0===e.length||0===this.grid.keysLength()&&0===this.ignoredGrid.keysLength())return{};for(var r=[],n=1/0,a=1/0,i=-1/0,o=-1/0,s=0,l=e;s<l.length;s+=1){var c=l[s],u=new t.Point(c.x+100,c.y+100);n=Math.min(n,u.x),a=Math.min(a,u.y),i=Math.max(i,u.x),o=Math.max(o,u.y),r.push(u)}for(var h={},f={},p=0,d=this.grid.query(n,a,i,o).concat(this.ignoredGrid.query(n,a,i,o));p<d.length;p+=1){var g=d[p],v=g.key;if(void 0===h[v.bucketInstanceId]&&(h[v.bucketInstanceId]={}),!h[v.bucketInstanceId][v.featureIndex]){var m=[new t.Point(g.x1,g.y1),new t.Point(g.x2,g.y1),new t.Point(g.x2,g.y2),new t.Point(g.x1,g.y2)];t.polygonIntersectsPolygon(r,m)&&(h[v.bucketInstanceId][v.featureIndex]=!0,void 0===f[v.bucketInstanceId]&&(f[v.bucketInstanceId]=[]),f[v.bucketInstanceId].push(v.featureIndex))}}return f},se.prototype.insertCollisionBox=function(t,e,r,n,a){var i={bucketInstanceId:r,featureIndex:n,collisionGroupID:a};(e?this.ignoredGrid:this.grid).insert(i,t[0],t[1],t[2],t[3])},se.prototype.insertCollisionCircles=function(t,e,r,n,a){for(var i=e?this.ignoredGrid:this.grid,o={bucketInstanceId:r,featureIndex:n,collisionGroupID:a},s=0;s<t.length;s+=4)i.insertCircle(o,t[s],t[s+1],t[s+2])},se.prototype.projectAnchor=function(t,e,r){var n=[e,r,0,1];return oe(n,n,t),{perspectiveRatio:.5+this.transform.cameraToCenterDistance/n[3]*.5,cameraDistance:n[3]}},se.prototype.projectPoint=function(e,r,n){var a=[r,n,0,1];return oe(a,a,e),new t.Point((a[0]/a[3]+1)/2*this.transform.width+100,(-a[1]/a[3]+1)/2*this.transform.height+100)},se.prototype.projectAndGetPerspectiveRatio=function(e,r,n){var a=[r,n,0,1];return oe(a,a,e),{point:new t.Point((a[0]/a[3]+1)/2*this.transform.width+100,(-a[1]/a[3]+1)/2*this.transform.height+100),perspectiveRatio:.5+this.transform.cameraToCenterDistance/a[3]*.5}},se.prototype.isOffscreen=function(t,e,r,n){return r<100||t>=this.screenRightBoundary||n<100||e>this.screenBottomBoundary},se.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t<this.gridRightBoundary&&n>=0&&e<this.gridBottomBoundary};var ue=function(t,e,r,n){this.opacity=t?Math.max(0,Math.min(1,t.opacity+(t.placed?e:-e))):n&&r?1:0,this.placed=r};ue.prototype.isHidden=function(){return 0===this.opacity&&!this.placed};var he=function(t,e,r,n,a){this.text=new ue(t?t.text:null,e,r,a),this.icon=new ue(t?t.icon:null,e,n,a)};he.prototype.isHidden=function(){return this.text.isHidden()&&this.icon.isHidden()};var fe=function(t,e,r){this.text=t,this.icon=e,this.skipFade=r},pe=function(t,e,r,n,a){this.bucketInstanceId=t,this.featureIndex=e,this.sourceLayerIndex=r,this.bucketIndex=n,this.tileID=a},de=function(t){this.crossSourceCollisions=t,this.maxGroupID=0,this.collisionGroups={}};function ge(e,r,n,a,i){var o=t.getAnchorAlignment(e),s=-(o.horizontalAlign-.5)*r,l=-(o.verticalAlign-.5)*n,c=t.evaluateRadialOffset(e,a);return new t.Point(s+c[0]*i,l+c[1]*i)}de.prototype.get=function(t){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[t]){var e=++this.maxGroupID;this.collisionGroups[t]={ID:e,predicate:function(t){return t.collisionGroupID===e}}}return this.collisionGroups[t]};var ve=function(t,e,r,n){this.transform=t.clone(),this.collisionIndex=new se(this.transform),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=e,this.retainedQueryData={},this.collisionGroups=new de(r),this.prevPlacement=n,n&&(n.prevPlacement=void 0),this.placedOrientations={}};function me(t,e,r,n,a){t.emplaceBack(e?1:0,r?1:0,n||0,a||0),t.emplaceBack(e?1:0,r?1:0,n||0,a||0),t.emplaceBack(e?1:0,r?1:0,n||0,a||0),t.emplaceBack(e?1:0,r?1:0,n||0,a||0)}ve.prototype.placeLayerTile=function(e,r,n,a){var i=r.getBucket(e),o=r.latestFeatureIndex;if(i&&o&&e.id===i.layerIds[0]){var s=r.collisionBoxArray,l=i.layers[0].layout,c=Math.pow(2,this.transform.zoom-r.tileID.overscaledZ),u=r.tileSize/t.EXTENT,h=this.transform.calculatePosMatrix(r.tileID.toUnwrapped()),f=Xt(h,\"map\"===l.get(\"text-pitch-alignment\"),\"map\"===l.get(\"text-rotation-alignment\"),this.transform,ce(r,1,this.transform.zoom)),p=Xt(h,\"map\"===l.get(\"icon-pitch-alignment\"),\"map\"===l.get(\"icon-rotation-alignment\"),this.transform,ce(r,1,this.transform.zoom));this.retainedQueryData[i.bucketInstanceId]=new pe(i.bucketInstanceId,o,i.sourceLayerIndex,i.index,r.tileID),this.placeLayerBucket(i,h,f,p,c,u,n,r.holdingForFade(),a,s)}},ve.prototype.attemptAnchorPlacement=function(e,r,n,a,i,o,s,l,c,u,h,f,p,d,g){var v,m=ge(e,n,a,i,o),y=this.collisionIndex.placeCollisionBox(function(e,r,n,a,i,o){var s=e.x1,l=e.x2,c=e.y1,u=e.y2,h=e.anchorPointX,f=e.anchorPointY,p=new t.Point(r,n);return a&&p._rotate(i?o:-o),{x1:s+p.x,y1:c+p.y,x2:l+p.x,y2:u+p.y,anchorPointX:h,anchorPointY:f}}(r,m.x,m.y,s,l,this.transform.angle),f,c,u,h.predicate);if(y.box.length>0)return this.prevPlacement&&this.prevPlacement.variableOffsets[p.crossTileID]&&this.prevPlacement.placements[p.crossTileID]&&this.prevPlacement.placements[p.crossTileID].text&&(v=this.prevPlacement.variableOffsets[p.crossTileID].anchor),this.variableOffsets[p.crossTileID]={radialOffset:i,width:n,height:a,anchor:e,textBoxScale:o,prevAnchor:v},this.markUsedJustification(d,e,p,g),d.allowVerticalPlacement&&(this.markUsedOrientation(d,g,p),this.placedOrientations[p.crossTileID]=g),y},ve.prototype.placeLayerBucket=function(e,r,n,a,i,o,s,l,c,u){var h=this,f=e.layers[0].layout,p=t.evaluateSizeForZoom(e.textSizeData,this.transform.zoom),d=f.get(\"text-optional\"),g=f.get(\"icon-optional\"),v=f.get(\"text-allow-overlap\"),m=f.get(\"icon-allow-overlap\"),y=v&&(m||!e.hasIconData()||g),x=m&&(v||!e.hasTextData()||d),b=this.collisionGroups.get(e.sourceID),_=\"map\"===f.get(\"text-rotation-alignment\"),w=\"map\"===f.get(\"text-pitch-alignment\"),k=\"viewport-y\"===f.get(\"symbol-z-order\");!e.collisionArrays&&u&&e.deserializeCollisionBoxes(u);var T=function(a,u){if(!c[a.crossTileID])if(l)h.placements[a.crossTileID]=new fe(!1,!1,!1);else{var m,k=!1,T=!1,M=!0,A={box:null,offscreen:null},S={box:null,offscreen:null},E=null,L=null,C=0,P=0,O=0;u.textFeatureIndex&&(C=u.textFeatureIndex),u.verticalTextFeatureIndex&&(P=u.verticalTextFeatureIndex);var z=u.textBox;if(z){var I=function(r){var n=t.WritingMode.horizontal;if(e.allowVerticalPlacement&&!r&&h.prevPlacement){var i=h.prevPlacement.placedOrientations[a.crossTileID];i&&(h.placedOrientations[a.crossTileID]=i,n=i,h.markUsedOrientation(e,n,a))}return n},D=function(r,n){if(e.allowVerticalPlacement&&a.numVerticalGlyphVertices>0&&u.verticalTextBox)for(var i=0,o=e.writingModes;i<o.length&&(o[i]===t.WritingMode.vertical?(A=n(),S=A):A=r(),!(A&&A.box&&A.box.length));i+=1);else A=r()};if(f.get(\"text-variable-anchor\")){var R=f.get(\"text-variable-anchor\");if(h.prevPlacement&&h.prevPlacement.variableOffsets[a.crossTileID]){var F=h.prevPlacement.variableOffsets[a.crossTileID];R.indexOf(F.anchor)>0&&(R=R.filter(function(t){return t!==F.anchor})).unshift(F.anchor)}var B=function(t,n){for(var i=t.x2-t.x1,s=t.y2-t.y1,l=a.textBoxScale,c={box:[],offscreen:!1},u=v?2*R.length:R.length,f=0;f<u;++f){var p=R[f%R.length],d=f>=R.length;if((c=h.attemptAnchorPlacement(p,t,i,s,a.radialTextOffset,l,_,w,o,r,b,d,a,e,n))&&c.box&&c.box.length){k=!0;break}}return c};D(function(){return B(z,t.WritingMode.horizontal)},function(){var r=u.verticalTextBox,n=A&&A.box&&A.box.length;return e.allowVerticalPlacement&&!n&&a.numVerticalGlyphVertices>0&&r?B(r,t.WritingMode.vertical):{box:null,offscreen:null}}),A&&(k=A.box,M=A.offscreen);var N=I(A&&A.box);if(!k&&h.prevPlacement){var j=h.prevPlacement.variableOffsets[a.crossTileID];j&&(h.variableOffsets[a.crossTileID]=j,h.markUsedJustification(e,j.anchor,a,N))}}else{var V=function(t,n){var i=h.collisionIndex.placeCollisionBox(t,f.get(\"text-allow-overlap\"),o,r,b.predicate);return i&&i.box&&i.box.length&&(h.markUsedOrientation(e,n,a),h.placedOrientations[a.crossTileID]=n),i};D(function(){return V(z,t.WritingMode.horizontal)},function(){var r=u.verticalTextBox;return e.allowVerticalPlacement&&a.numVerticalGlyphVertices>0&&r?V(r,t.WritingMode.vertical):{box:null,offscreen:null}}),I(A&&A.box&&A.box.length)}}k=(m=A)&&m.box&&m.box.length>0,M=m&&m.offscreen;var U=u.textCircles;if(U){var q=e.text.placedSymbolArray.get(a.centerJustifiedTextSymbolIndex),H=t.evaluateSizeForFeature(e.textSizeData,p,q);E=h.collisionIndex.placeCollisionCircles(U,f.get(\"text-allow-overlap\"),i,o,q,e.lineVertexArray,e.glyphOffsetArray,H,r,n,s,w,b.predicate),k=f.get(\"text-allow-overlap\")||E.circles.length>0,M=M&&E.offscreen}u.iconFeatureIndex&&(O=u.iconFeatureIndex),u.iconBox&&(T=(L=h.collisionIndex.placeCollisionBox(u.iconBox,f.get(\"icon-allow-overlap\"),o,r,b.predicate)).box.length>0,M=M&&L.offscreen);var G=d||0===a.numHorizontalGlyphVertices&&0===a.numVerticalGlyphVertices,Y=g||0===a.numIconVertices;G||Y?Y?G||(T=T&&k):k=T&&k:T=k=T&&k,k&&m&&m.box&&(S&&S.box&&P?h.collisionIndex.insertCollisionBox(m.box,f.get(\"text-ignore-placement\"),e.bucketInstanceId,P,b.ID):h.collisionIndex.insertCollisionBox(m.box,f.get(\"text-ignore-placement\"),e.bucketInstanceId,C,b.ID)),T&&L&&h.collisionIndex.insertCollisionBox(L.box,f.get(\"icon-ignore-placement\"),e.bucketInstanceId,O,b.ID),k&&E&&h.collisionIndex.insertCollisionCircles(E.circles,f.get(\"text-ignore-placement\"),e.bucketInstanceId,C,b.ID),h.placements[a.crossTileID]=new fe(k||y,T||x,M||e.justReloaded),c[a.crossTileID]=!0}};if(k)for(var M=e.getSortedSymbolIndexes(this.transform.angle),A=M.length-1;A>=0;--A){var S=M[A];T(e.symbolInstances.get(S),e.collisionArrays[S])}else for(var E=0;E<e.symbolInstances.length;++E)T(e.symbolInstances.get(E),e.collisionArrays[E]);e.justReloaded=!1},ve.prototype.markUsedJustification=function(e,r,n,a){var i,o={left:n.leftJustifiedTextSymbolIndex,center:n.centerJustifiedTextSymbolIndex,right:n.rightJustifiedTextSymbolIndex};i=a===t.WritingMode.vertical?n.verticalPlacedTextSymbolIndex:o[t.getAnchorJustification(r)];for(var s=0,l=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex,n.verticalPlacedTextSymbolIndex];s<l.length;s+=1){var c=l[s];c>=0&&(e.text.placedSymbolArray.get(c).crossTileID=i>=0&&c!==i?0:n.crossTileID)}},ve.prototype.markUsedOrientation=function(e,r,n){for(var a=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,i=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o<s.length;o+=1){var l=s[o];e.text.placedSymbolArray.get(l).placedOrientation=a}n.verticalPlacedTextSymbolIndex&&(e.text.placedSymbolArray.get(n.verticalPlacedTextSymbolIndex).placedOrientation=i)},ve.prototype.commit=function(t){this.commitTime=t;var e=this.prevPlacement,r=!1,n=e&&0!==this.fadeDuration?(this.commitTime-e.commitTime)/this.fadeDuration:1,a=e?e.opacities:{},i=e?e.variableOffsets:{},o=e?e.placedOrientations:{};for(var s in this.placements){var l=this.placements[s],c=a[s];c?(this.opacities[s]=new he(c,n,l.text,l.icon),r=r||l.text!==c.text.placed||l.icon!==c.icon.placed):(this.opacities[s]=new he(null,n,l.text,l.icon,l.skipFade),r=r||l.text||l.icon)}for(var u in a){var h=a[u];if(!this.opacities[u]){var f=new he(h,n,!1,!1);f.isHidden()||(this.opacities[u]=f,r=r||h.text.placed||h.icon.placed)}}for(var p in i)this.variableOffsets[p]||!this.opacities[p]||this.opacities[p].isHidden()||(this.variableOffsets[p]=i[p]);for(var d in o)this.placedOrientations[d]||!this.opacities[d]||this.opacities[d].isHidden()||(this.placedOrientations[d]=o[d]);r?this.lastPlacementChangeTime=t:\"number\"!=typeof this.lastPlacementChangeTime&&(this.lastPlacementChangeTime=e?e.lastPlacementChangeTime:t)},ve.prototype.updateLayerOpacities=function(t,e){for(var r={},n=0,a=e;n<a.length;n+=1){var i=a[n],o=i.getBucket(t);o&&i.latestFeatureIndex&&t.id===o.layerIds[0]&&this.updateBucketOpacities(o,r,i.collisionBoxArray)}},ve.prototype.updateBucketOpacities=function(e,r,n){e.hasTextData()&&e.text.opacityVertexArray.clear(),e.hasIconData()&&e.icon.opacityVertexArray.clear(),e.hasCollisionBoxData()&&e.collisionBox.collisionVertexArray.clear(),e.hasCollisionCircleData()&&e.collisionCircle.collisionVertexArray.clear();var a=e.layers[0].layout,i=new he(null,0,!1,!1,!0),o=a.get(\"text-allow-overlap\"),s=a.get(\"icon-allow-overlap\"),l=a.get(\"text-variable-anchor\"),c=\"map\"===a.get(\"text-rotation-alignment\"),u=\"map\"===a.get(\"text-pitch-alignment\"),h=new he(null,0,o&&(s||!e.hasIconData()||a.get(\"icon-optional\")),s&&(o||!e.hasTextData()||a.get(\"text-optional\")),!0);!e.collisionArrays&&n&&(e.hasCollisionBoxData()||e.hasCollisionCircleData())&&e.deserializeCollisionBoxes(n);for(var f=0;f<e.symbolInstances.length;f++){var p=e.symbolInstances.get(f),d=p.numHorizontalGlyphVertices,g=p.numVerticalGlyphVertices,v=p.crossTileID,m=r[v],y=this.opacities[v];m?y=i:y||(y=h,this.opacities[v]=y),r[v]=!0;var x=d>0||g>0,b=p.numIconVertices>0;if(x){for(var _=Me(y.text),w=(d+g)/4,k=0;k<w;k++)e.text.opacityVertexArray.emplaceBack(_);var T=y.text.isHidden()?1:0,M=this.placedOrientations[p.crossTileID],A=M===t.WritingMode.horizontal||M===t.WritingMode.horizontalOnly?1:0,S=M===t.WritingMode.vertical?1:0;[p.rightJustifiedTextSymbolIndex,p.centerJustifiedTextSymbolIndex,p.leftJustifiedTextSymbolIndex].forEach(function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=T||S)}),p.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(p.verticalPlacedTextSymbolIndex).hidden=T||A);var E=this.variableOffsets[p.crossTileID];E&&this.markUsedJustification(e,E.anchor,p,M);var L=this.placedOrientations[p.crossTileID];L&&(this.markUsedJustification(e,\"left\",p,L),this.markUsedOrientation(e,L,p))}if(b){for(var C=Me(y.icon),P=0;P<p.numIconVertices/4;P++)e.icon.opacityVertexArray.emplaceBack(C);e.icon.placedSymbolArray.get(f).hidden=y.icon.isHidden()}if(e.hasCollisionBoxData()||e.hasCollisionCircleData()){var O=e.collisionArrays[f];if(O){if(O.textBox){var z=new t.Point(0,0),I=!0;if(l){var D=this.variableOffsets[v];D?(z=ge(D.anchor,D.width,D.height,D.radialOffset,D.textBoxScale),c&&z._rotate(u?this.transform.angle:-this.transform.angle)):I=!1}me(e.collisionBox.collisionVertexArray,y.text.placed,!I,z.x,z.y)}O.iconBox&&me(e.collisionBox.collisionVertexArray,y.icon.placed,!1);var R=O.textCircles;if(R&&e.hasCollisionCircleData())for(var F=0;F<R.length;F+=5){var B=m||0===R[F+4];me(e.collisionCircle.collisionVertexArray,y.text.placed,B)}}}}e.sortFeatures(this.transform.angle),this.retainedQueryData[e.bucketInstanceId]&&(this.retainedQueryData[e.bucketInstanceId].featureSortOrder=e.featureSortOrder),e.hasTextData()&&e.text.opacityVertexBuffer&&e.text.opacityVertexBuffer.updateData(e.text.opacityVertexArray),e.hasIconData()&&e.icon.opacityVertexBuffer&&e.icon.opacityVertexBuffer.updateData(e.icon.opacityVertexArray),e.hasCollisionBoxData()&&e.collisionBox.collisionVertexBuffer&&e.collisionBox.collisionVertexBuffer.updateData(e.collisionBox.collisionVertexArray),e.hasCollisionCircleData()&&e.collisionCircle.collisionVertexBuffer&&e.collisionCircle.collisionVertexBuffer.updateData(e.collisionCircle.collisionVertexArray)},ve.prototype.symbolFadeChange=function(t){return 0===this.fadeDuration?1:(t-this.commitTime)/this.fadeDuration},ve.prototype.hasTransitions=function(t){return this.stale||t-this.lastPlacementChangeTime<this.fadeDuration},ve.prototype.stillRecent=function(t){return this.commitTime+this.fadeDuration>t},ve.prototype.setStale=function(){this.stale=!0};var ye=Math.pow(2,25),xe=Math.pow(2,24),be=Math.pow(2,17),_e=Math.pow(2,16),we=Math.pow(2,9),ke=Math.pow(2,8),Te=Math.pow(2,1);function Me(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*ye+e*xe+r*be+e*_e+r*we+e*ke+r*Te+e}var Ae=function(){this._currentTileIndex=0,this._seenCrossTileIDs={}};Ae.prototype.continuePlacement=function(t,e,r,n,a){for(;this._currentTileIndex<t.length;){var i=t[this._currentTileIndex];if(e.placeLayerTile(n,i,r,this._seenCrossTileIDs),this._currentTileIndex++,a())return!0}};var Se=function(t,e,r,n,a,i,o){this.placement=new ve(t,a,i,o),this._currentPlacementIndex=e.length-1,this._forceFullPlacement=r,this._showCollisionBoxes=n,this._done=!1};Se.prototype.isDone=function(){return this._done},Se.prototype.continuePlacement=function(e,r,n){for(var a=this,i=t.browser.now(),o=function(){var e=t.browser.now()-i;return!a._forceFullPlacement&&e>2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if(\"symbol\"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new Ae),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},Se.prototype.commit=function(t){return this.placement.commit(t),this.placement};var Ee=512/t.EXTENT/2,Le=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;n<e.length;n++){var a=e.get(n),i=a.key;this.indexedSymbolInstances[i]||(this.indexedSymbolInstances[i]=[]),this.indexedSymbolInstances[i].push({crossTileID:a.crossTileID,coord:this.getScaledCoordinates(a,t)})}};Le.prototype.getScaledCoordinates=function(e,r){var n=r.canonical.z-this.tileID.canonical.z,a=Ee/Math.pow(2,n);return{x:Math.floor((r.canonical.x*t.EXTENT+e.anchorX)*a),y:Math.floor((r.canonical.y*t.EXTENT+e.anchorY)*a)}},Le.prototype.findMatches=function(t,e,r){for(var n=this.tileID.canonical.z<e.canonical.z?1:Math.pow(2,this.tileID.canonical.z-e.canonical.z),a=0;a<t.length;a++){var i=t.get(a);if(!i.crossTileID){var o=this.indexedSymbolInstances[i.key];if(o)for(var s=this.getScaledCoordinates(i,e),l=0,c=o;l<c.length;l+=1){var u=c[l];if(Math.abs(u.coord.x-s.x)<=n&&Math.abs(u.coord.y-s.y)<=n&&!r[u.crossTileID]){r[u.crossTileID]=!0,i.crossTileID=u.crossTileID;break}}}}};var Ce=function(){this.maxCrossTileID=0};Ce.prototype.generate=function(){return++this.maxCrossTileID};var Pe=function(){this.indexes={},this.usedCrossTileIDs={},this.lng=0};Pe.prototype.handleWrapJump=function(t){var e=Math.round((t-this.lng)/360);if(0!==e)for(var r in this.indexes){var n=this.indexes[r],a={};for(var i in n){var o=n[i];o.tileID=o.tileID.unwrapTo(o.tileID.wrap+e),a[o.tileID.key]=o}this.indexes[r]=a}this.lng=t},Pe.prototype.addBucket=function(t,e,r){if(this.indexes[t.overscaledZ]&&this.indexes[t.overscaledZ][t.key]){if(this.indexes[t.overscaledZ][t.key].bucketInstanceId===e.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(t.overscaledZ,this.indexes[t.overscaledZ][t.key])}for(var n=0;n<e.symbolInstances.length;n++)e.symbolInstances.get(n).crossTileID=0;this.usedCrossTileIDs[t.overscaledZ]||(this.usedCrossTileIDs[t.overscaledZ]={});var a=this.usedCrossTileIDs[t.overscaledZ];for(var i in this.indexes){var o=this.indexes[i];if(Number(i)>t.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,a)}else{var c=o[t.scaledTo(Number(i)).key];c&&c.findMatches(e.symbolInstances,t,a)}}for(var u=0;u<e.symbolInstances.length;u++){var h=e.symbolInstances.get(u);h.crossTileID||(h.crossTileID=r.generate(),a[h.crossTileID]=!0)}return void 0===this.indexes[t.overscaledZ]&&(this.indexes[t.overscaledZ]={}),this.indexes[t.overscaledZ][t.key]=new Le(t,e.symbolInstances,e.bucketInstanceId),!0},Pe.prototype.removeBucketCrossTileIDs=function(t,e){for(var r in e.indexedSymbolInstances)for(var n=0,a=e.indexedSymbolInstances[r];n<a.length;n+=1){var i=a[n];delete this.usedCrossTileIDs[t][i.crossTileID]}},Pe.prototype.removeStaleBuckets=function(t){var e=!1;for(var r in this.indexes){var n=this.indexes[r];for(var a in n)t[n[a].bucketInstanceId]||(this.removeBucketCrossTileIDs(r,n[a]),delete n[a],e=!0)}return e};var Oe=function(){this.layerIndexes={},this.crossTileIDs=new Ce,this.maxBucketInstanceId=0,this.bucketsInCurrentPlacement={}};Oe.prototype.addLayer=function(t,e,r){var n=this.layerIndexes[t.id];void 0===n&&(n=this.layerIndexes[t.id]=new Pe);var a=!1,i={};n.handleWrapJump(r);for(var o=0,s=e;o<s.length;o+=1){var l=s[o],c=l.getBucket(t);c&&t.id===c.layerIds[0]&&(c.bucketInstanceId||(c.bucketInstanceId=++this.maxBucketInstanceId),n.addBucket(l.tileID,c,this.crossTileIDs)&&(a=!0),i[c.bucketInstanceId]=!0)}return n.removeStaleBuckets(i)&&(a=!0),a},Oe.prototype.pruneUnusedLayers=function(t){var e={};for(var r in t.forEach(function(t){e[t]=!0}),this.layerIndexes)e[r]||delete this.layerIndexes[r]};var ze=function(e,r){return t.emitValidationErrors(e,r&&r.filter(function(t){return\"source.canvas\"!==t.identifier}))},Ie=t.pick(Nt,[\"addLayer\",\"removeLayer\",\"setPaintProperty\",\"setLayoutProperty\",\"setFilter\",\"addSource\",\"removeSource\",\"setLayerZoomRange\",\"setLight\",\"setTransition\",\"setGeoJSONSourceData\"]),De=t.pick(Nt,[\"setCenter\",\"setZoom\",\"setBearing\",\"setPitch\"]),Re=function(e){function r(n,a){var i=this;void 0===a&&(a={}),e.call(this),this.map=n,this.dispatcher=new T((Dt||(Dt=new It),Dt),this),this.imageManager=new f,this.imageManager.setEventedParent(this),this.glyphManager=new x(n._requestManager,a.localIdeographFontFamily),this.lineAtlas=new k(256,512),this.crossTileSymbolIndex=new Oe,this._layers={},this._order=[],this.sourceCaches={},this.zoomHistory=new t.ZoomHistory,this._loaded=!1,this._resetUpdates(),this.dispatcher.broadcast(\"setReferrer\",t.getReferrer());var o=this;this._rtlTextPluginCallback=r.registerForPluginAvailability(function(t){for(var e in o.dispatcher.broadcast(\"loadRTLTextPlugin\",t.pluginURL,t.completionCallback),o.sourceCaches)o.sourceCaches[e].reload()}),this.on(\"data\",function(t){if(\"source\"===t.dataType&&\"metadata\"===t.sourceDataType){var e=i.sourceCaches[t.sourceId];if(e){var r=e.getSource();if(r&&r.vectorLayerIds)for(var n in i._layers){var a=i._layers[n];a.source===r.id&&i._validateLayer(a)}}}})}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadURL=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"}));var a=\"boolean\"==typeof r.validate?r.validate:!t.isMapboxURL(e);e=this.map._requestManager.normalizeStyleURL(e,r.accessToken);var i=this.map._requestManager.transformRequest(e,t.ResourceType.Style);this._request=t.getJSON(i,function(e,r){n._request=null,e?n.fire(new t.ErrorEvent(e)):r&&n._load(r,a)})},r.prototype.loadJSON=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._request=t.browser.frame(function(){n._request=null,n._load(e,!1!==r.validate)})},r.prototype._load=function(e,r){var n=this;if(!r||!ze(this,t.validateStyle(e))){for(var a in this._loaded=!0,this.stylesheet=e,e.sources)this.addSource(a,e.sources[a],{validate:!1});e.sprite?this._spriteRequest=function(e,r,n){var a,i,o,s=t.browser.devicePixelRatio>1?\"@2x\":\"\",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,\".json\"),t.ResourceType.SpriteJSON),function(t,e){l=null,o||(o=t,a=e,u())}),c=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,\".png\"),t.ResourceType.SpriteImage),function(t,e){c=null,o||(o=t,i=e,u())});function u(){if(o)n(o);else if(a&&i){var e=t.browser.getImageData(i),r={};for(var s in a){var l=a[s],c=l.width,u=l.height,h=l.x,f=l.y,p=l.sdf,d=l.pixelRatio,g=new t.RGBAImage({width:c,height:u});t.RGBAImage.copy(e,g,{x:h,y:f},{x:0,y:0},{width:c,height:u}),r[s]={data:g,pixelRatio:d,sdf:p}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),c&&(c.cancel(),c=null)}}}(e.sprite,this.map._requestManager,function(e,r){if(n._spriteRequest=null,e)n.fire(new t.ErrorEvent(e));else if(r)for(var a in r)n.imageManager.addImage(a,r[a]);n.imageManager.setLoaded(!0),n.fire(new t.Event(\"data\",{dataType:\"style\"}))}):this.imageManager.setLoaded(!0),this.glyphManager.setURL(e.glyphs);var i=Bt(this.stylesheet.layers);this._order=i.map(function(t){return t.id}),this._layers={};for(var o=0,s=i;o<s.length;o+=1){var l=s[o];(l=t.createStyleLayer(l)).setEventedParent(this,{layer:{id:l.id}}),this._layers[l.id]=l}this.dispatcher.broadcast(\"setLayers\",this._serializeLayers(this._order)),this.light=new w(this.stylesheet.light),this.fire(new t.Event(\"data\",{dataType:\"style\"})),this.fire(new t.Event(\"style.load\"))}},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var a=r.getSource();(\"geojson\"===a.type||a.vectorLayerIds&&-1===a.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer \"'+n+'\" does not exist on source \"'+a.id+'\" as specified by style layer \"'+e.id+'\"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var a=n[r],i=this._layers[a];\"custom\"!==i.type&&e.push(i.serialize())}return e},r.prototype.hasTransitions=function(){if(this.light&&this.light.hasTransition())return!0;for(var t in this.sourceCaches)if(this.sourceCaches[t].hasTransition())return!0;for(var e in this._layers)if(this._layers[e].hasTransition())return!0;return!1},r.prototype._checkLoaded=function(){if(!this._loaded)throw new Error(\"Style is not done loading\")},r.prototype.update=function(e){if(this._loaded){var r=this._changed;if(this._changed){var n=Object.keys(this._updatedLayers),a=Object.keys(this._removedLayers);for(var i in(n.length||a.length)&&this._updateWorkerLayers(n,a),this._updatedSources){var o=this._updatedSources[i];\"reload\"===o?this._reloadSource(i):\"clear\"===o&&this._clearSource(i)}for(var s in this._updatedPaintProps)this._layers[s].updateTransitions(e);this.light.updateTransitions(e),this._resetUpdates()}for(var l in this.sourceCaches)this.sourceCaches[l].used=!1;for(var c=0,u=this._order;c<u.length;c+=1){var h=u[c],f=this._layers[h];f.recalculate(e),!f.isHidden(e.zoom)&&f.source&&(this.sourceCaches[f.source].used=!0)}this.light.recalculate(e),this.z=e.zoom,r&&this.fire(new t.Event(\"data\",{dataType:\"style\"}))}},r.prototype._updateWorkerLayers=function(t,e){this.dispatcher.broadcast(\"updateLayers\",{layers:this._serializeLayers(t),removedIds:e})},r.prototype._resetUpdates=function(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={}},r.prototype.setState=function(e){var r=this;if(this._checkLoaded(),ze(this,t.validateStyle(e)))return!1;(e=t.clone$1(e)).layers=Bt(e.layers);var n=function(e,r){if(!e)return[{command:Nt.setStyle,args:[r]}];var n=[];try{if(!t.deepEqual(e.version,r.version))return[{command:Nt.setStyle,args:[r]}];t.deepEqual(e.center,r.center)||n.push({command:Nt.setCenter,args:[r.center]}),t.deepEqual(e.zoom,r.zoom)||n.push({command:Nt.setZoom,args:[r.zoom]}),t.deepEqual(e.bearing,r.bearing)||n.push({command:Nt.setBearing,args:[r.bearing]}),t.deepEqual(e.pitch,r.pitch)||n.push({command:Nt.setPitch,args:[r.pitch]}),t.deepEqual(e.sprite,r.sprite)||n.push({command:Nt.setSprite,args:[r.sprite]}),t.deepEqual(e.glyphs,r.glyphs)||n.push({command:Nt.setGlyphs,args:[r.glyphs]}),t.deepEqual(e.transition,r.transition)||n.push({command:Nt.setTransition,args:[r.transition]}),t.deepEqual(e.light,r.light)||n.push({command:Nt.setLight,args:[r.light]});var a={},i=[];!function(e,r,n,a){var i;for(i in r=r||{},e=e||{})e.hasOwnProperty(i)&&(r.hasOwnProperty(i)||Vt(i,n,a));for(i in r)r.hasOwnProperty(i)&&(e.hasOwnProperty(i)?t.deepEqual(e[i],r[i])||(\"geojson\"===e[i].type&&\"geojson\"===r[i].type&&qt(e,r,i)?n.push({command:Nt.setGeoJSONSourceData,args:[i,r[i].data]}):Ut(i,r,n,a)):jt(i,r,n))}(e.sources,r.sources,i,a);var o=[];e.layers&&e.layers.forEach(function(t){a[t.source]?n.push({command:Nt.removeLayer,args:[t.id]}):o.push(t)}),n=n.concat(i),function(e,r,n){r=r||[];var a,i,o,s,l,c,u,h=(e=e||[]).map(Gt),f=r.map(Gt),p=e.reduce(Yt,{}),d=r.reduce(Yt,{}),g=h.slice(),v=Object.create(null);for(a=0,i=0;a<h.length;a++)o=h[a],d.hasOwnProperty(o)?i++:(n.push({command:Nt.removeLayer,args:[o]}),g.splice(g.indexOf(o,i),1));for(a=0,i=0;a<f.length;a++)o=f[f.length-1-a],g[g.length-1-a]!==o&&(p.hasOwnProperty(o)?(n.push({command:Nt.removeLayer,args:[o]}),g.splice(g.lastIndexOf(o,g.length-i),1)):i++,c=g[g.length-a],n.push({command:Nt.addLayer,args:[d[o],c]}),g.splice(g.length-a,0,o),v[o]=!0);for(a=0;a<f.length;a++)if(s=p[o=f[a]],l=d[o],!v[o]&&!t.deepEqual(s,l))if(t.deepEqual(s.source,l.source)&&t.deepEqual(s[\"source-layer\"],l[\"source-layer\"])&&t.deepEqual(s.type,l.type)){for(u in Ht(s.layout,l.layout,n,o,null,Nt.setLayoutProperty),Ht(s.paint,l.paint,n,o,null,Nt.setPaintProperty),t.deepEqual(s.filter,l.filter)||n.push({command:Nt.setFilter,args:[o,l.filter]}),t.deepEqual(s.minzoom,l.minzoom)&&t.deepEqual(s.maxzoom,l.maxzoom)||n.push({command:Nt.setLayerZoomRange,args:[o,l.minzoom,l.maxzoom]}),s)s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?Ht(s[u],l[u],n,o,u.slice(6),Nt.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Nt.setLayerProperty,args:[o,u,l[u]]}));for(u in l)l.hasOwnProperty(u)&&!s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?Ht(s[u],l[u],n,o,u.slice(6),Nt.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Nt.setLayerProperty,args:[o,u,l[u]]}))}else n.push({command:Nt.removeLayer,args:[o]}),c=g[g.lastIndexOf(o)+1],n.push({command:Nt.addLayer,args:[l,c]})}(o,r.layers,n)}catch(t){console.warn(\"Unable to compute style diff:\",t),n=[{command:Nt.setStyle,args:[r]}]}return n}(this.serialize(),e).filter(function(t){return!(t.command in De)});if(0===n.length)return!1;var a=n.filter(function(t){return!(t.command in Ie)});if(a.length>0)throw new Error(\"Unimplemented: \"+a.map(function(t){return t.command}).join(\", \")+\".\");return n.forEach(function(t){\"setTransition\"!==t.command&&r[t.command].apply(r,t.args)}),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"An image with this name already exists.\")));this.imageManager.addImage(e,r),this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"No image with this name exists.\")));this.imageManager.removeImage(e),this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var a=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error(\"There is already a source with this ID\");if(!r.type)throw new Error(\"The type property must be defined, but the only the following properties were given: \"+Object.keys(r).join(\", \")+\".\");if(!([\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(r.type)>=0&&this._validate(t.validateStyle.source,\"sources.\"+e,r,null,n))){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var i=this.sourceCaches[e]=new Ct(e,r,this.dispatcher);i.style=this,i.setEventedParent(this,function(){return{isSourceLoaded:a.loaded(),source:i.serialize(),sourceId:e}}),i.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error(\"There is no source with this ID\");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source \"'+e+'\" cannot be removed while layer \"'+r+'\" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var a=e.id;if(this.getLayer(a))this.fire(new t.ErrorEvent(new Error('Layer with id \"'+a+'\" already exists on this map')));else{var i;if(\"custom\"===e.type){if(ze(this,t.validateCustomStyleLayer(e)))return;i=t.createStyleLayer(e)}else{if(\"object\"==typeof e.source&&(this.addSource(a,e.source),e=t.clone$1(e),e=t.extend(e,{source:a})),this._validate(t.validateStyle.layer,\"layers.\"+a,e,{arrayIndex:-1},n))return;i=t.createStyleLayer(e),this._validateLayer(i),i.setEventedParent(this,{layer:{id:a}})}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.')));else{if(this._order.splice(o,0,a),this._layerOrderChanged=!0,this._layers[a]=i,this._removedLayers[a]&&i.source&&\"custom\"!==i.type){var s=this._removedLayers[a];delete this._removedLayers[a],s.type!==i.type?this._updatedSources[i.source]=\"clear\":(this._updatedSources[i.source]=\"reload\",this.sourceCaches[i.source].pause())}this._updateLayer(i),i.onAdd&&i.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var a=r?this._order.indexOf(r):this._order.length;r&&-1===a?this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.'))):(this._order.splice(a,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be moved.\")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be removed.\")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var a=this.getLayer(e);a?a.minzoom===r&&a.maxzoom===n||(null!=r&&(a.minzoom=r),null!=n&&(a.maxzoom=n),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot have zoom extent.\")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var a=this.getLayer(e);if(a){if(!t.deepEqual(a.filter,r))return null==r?(a.filter=void 0,void this._updateLayer(a)):void(this._validate(t.validateStyle.filter,\"layers.\"+a.id+\".filter\",r,null,n)||(a.filter=t.clone$1(r),this._updateLayer(a)))}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be filtered.\")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,a){void 0===a&&(a={}),this._checkLoaded();var i=this.getLayer(e);i?t.deepEqual(i.getLayoutProperty(r),n)||(i.setLayoutProperty(r,n,a),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style.\")))},r.prototype.setPaintProperty=function(e,r,n,a){void 0===a&&(a={}),this._checkLoaded();var i=this.getLayer(e);i?t.deepEqual(i.getPaintProperty(r),n)||(i.setPaintProperty(r,n,a)&&this._updateLayer(i),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,a=e.sourceLayer,i=this.sourceCaches[n],o=parseInt(e.id,10);if(void 0!==i){var s=i.getSource().type;\"geojson\"===s&&a?this.fire(new t.ErrorEvent(new Error(\"GeoJSON sources cannot have a sourceLayer parameter.\"))):\"vector\"!==s||a?isNaN(o)||o<0?this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided and non-negative.\"))):i.setFeatureState(a,o,r):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,a=this.sourceCaches[n];if(void 0!==a){var i=a.getSource().type,o=\"vector\"===i?e.sourceLayer:void 0,s=parseInt(e.id,10);\"vector\"!==i||o?void 0!==e.id&&isNaN(s)||s<0?this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be non-negative.\"))):r&&\"string\"!=typeof e.id&&\"number\"!=typeof e.id?this.fire(new t.ErrorEvent(new Error(\"A feature id is requred to remove its specific state property.\"))):a.removeFeatureState(o,s,r):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,a=this.sourceCaches[r],i=parseInt(e.id,10);if(void 0!==a)if(\"vector\"!==a.getSource().type||n){if(!(isNaN(i)||i<0))return a.getFeatureState(n,i);this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided and non-negative.\")))}else this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")));else this.fire(new t.ErrorEvent(new Error(\"The source '\"+r+\"' does not exist in the map's style.\")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,function(t){return t.serialize()}),layers:this._serializeLayers(this._order)},function(t){return void 0!==t})},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&(this._updatedSources[t.source]=\"reload\",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return\"fill-extrusion\"===e._layers[t].type},n={},a=[],i=this._order.length-1;i>=0;i--){var o=this._order[i];if(r(o)){n[o]=i;for(var s=0,l=t;s<l.length;s+=1){var c=l[s][o];if(c)for(var u=0,h=c;u<h.length;u+=1){var f=h[u];a.push(f)}}}}a.sort(function(t,e){return e.intersectionZ-t.intersectionZ});for(var p=[],d=this._order.length-1;d>=0;d--){var g=this._order[d];if(r(g))for(var v=a.length-1;v>=0;v--){var m=a[v].feature;if(n[m.layer.id]<d)break;p.push(m),a.pop()}else for(var y=0,x=t;y<x.length;y+=1){var b=x[y][g];if(b)for(var _=0,w=b;_<w.length;_+=1){var k=w[_];p.push(k.feature)}}}return p},r.prototype.queryRenderedFeatures=function(e,r,n){r&&r.filter&&this._validate(t.validateStyle.filter,\"queryRenderedFeatures.filter\",r.filter,null,r);var a={};if(r&&r.layers){if(!Array.isArray(r.layers))return this.fire(new t.ErrorEvent(new Error(\"parameters.layers must be an Array.\"))),[];for(var i=0,o=r.layers;i<o.length;i+=1){var s=o[i],l=this._layers[s];if(!l)return this.fire(new t.ErrorEvent(new Error(\"The layer '\"+s+\"' does not exist in the map's style and cannot be queried for features.\"))),[];a[l.source]=!0}}var c=[];for(var u in this.sourceCaches)r.layers&&!a[u]||c.push(F(this.sourceCaches[u],this._layers,e,r,n));return this.placement&&c.push(function(t,e,r,n,a,i){for(var o={},s=a.queryRenderedSymbols(r),l=[],c=0,u=Object.keys(s).map(Number);c<u.length;c+=1){var h=u[c];l.push(i[h])}l.sort(B);for(var f=function(){var e=d[p],r=e.featureIndex.lookupSymbolFeatures(s[e.bucketInstanceId],e.bucketIndex,e.sourceLayerIndex,n.filter,n.layers,t);for(var a in r){var i=o[a]=o[a]||[],l=r[a];l.sort(function(t,r){var n=e.featureSortOrder;if(n){var a=n.indexOf(t.featureIndex);return n.indexOf(r.featureIndex)-a}return r.featureIndex-t.featureIndex});for(var c=0,u=l;c<u.length;c+=1){var h=u[c];i.push(h)}}},p=0,d=l;p<d.length;p+=1)f();var g=function(r){o[r].forEach(function(n){var a=n.feature,i=t[r],o=e[i.source].getFeatureState(a.layer[\"source-layer\"],a.id);a.source=a.layer.source,a.layer[\"source-layer\"]&&(a.sourceLayer=a.layer[\"source-layer\"]),a.state=o})};for(var v in o)g(v);return o}(this._layers,this.sourceCaches,e,r,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(c)},r.prototype.querySourceFeatures=function(e,r){r&&r.filter&&this._validate(t.validateStyle.filter,\"querySourceFeatures.filter\",r.filter,null,r);var n=this.sourceCaches[e];return n?function(t,e){for(var r=t.getRenderableIds().map(function(e){return t.getTileByID(e)}),n=[],a={},i=0;i<r.length;i++){var o=r[i],s=o.tileID.canonical.key;a[s]||(a[s]=!0,o.querySourceFeatures(n,e))}return n}(n,r):[]},r.prototype.addSourceType=function(t,e,n){return r.getSourceType(t)?n(new Error('A source type called \"'+t+'\" already exists.')):(r.setSourceType(t,e),e.workerSourceURL?void this.dispatcher.broadcast(\"loadWorkerSource\",{name:t,url:e.workerSourceURL},n):n(null,null))},r.prototype.getLight=function(){return this.light.getLight()},r.prototype.setLight=function(e,r){void 0===r&&(r={}),this._checkLoaded();var n=this.light.getLight(),a=!1;for(var i in e)if(!t.deepEqual(e[i],n[i])){a=!0;break}if(a){var o={now:t.browser.now(),transition:t.extend({duration:300,delay:0},this.stylesheet.transition)};this.light.setLight(e,r),this.light.updateTransitions(o)}},r.prototype._validate=function(e,r,n,a,i){return void 0===i&&(i={}),(!i||!1!==i.validate)&&ze(this,e.call(t.validateStyle,t.extend({key:r,style:this.serialize(),value:n,styleSpec:t.styleSpec},a)))},r.prototype._remove=function(){for(var e in this._request&&(this._request.cancel(),this._request=null),this._spriteRequest&&(this._spriteRequest.cancel(),this._spriteRequest=null),t.evented.off(\"pluginAvailable\",this._rtlTextPluginCallback),this.sourceCaches)this.sourceCaches[e].clearTiles();this.dispatcher.remove()},r.prototype._clearSource=function(t){this.sourceCaches[t].clearTiles()},r.prototype._reloadSource=function(t){this.sourceCaches[t].resume(),this.sourceCaches[t].reload()},r.prototype._updateSources=function(t){for(var e in this.sourceCaches)this.sourceCaches[e].update(t)},r.prototype._generateCollisionBoxes=function(){for(var t in this.sourceCaches)this._reloadSource(t)},r.prototype._updatePlacement=function(e,r,n,a){for(var i=!1,o=!1,s={},l=0,c=this._order;l<c.length;l+=1){var u=c[l],h=this._layers[u];if(\"symbol\"===h.type){if(!s[h.source]){var f=this.sourceCaches[h.source];s[h.source]=f.getRenderableIds(!0).map(function(t){return f.getTileByID(t)}).sort(function(t,e){return e.tileID.overscaledZ-t.tileID.overscaledZ||(t.tileID.isLessThan(e.tileID)?-1:1)})}var p=this.crossTileSymbolIndex.addLayer(h,s[h.source],e.center.lng);i=i||p}}this.crossTileSymbolIndex.pruneUnusedLayers(this._order);var d=this._layerOrderChanged||0===n;if((d||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(t.browser.now()))&&(this.pauseablePlacement=new Se(e,this._order,d,r,n,a,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,s),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(t.browser.now()),o=!0),i&&this.pauseablePlacement.placement.setStale()),o||i)for(var g=0,v=this._order;g<v.length;g+=1){var m=v[g],y=this._layers[m];\"symbol\"===y.type&&this.placement.updateLayerOpacities(y,s[y.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(t.browser.now())},r.prototype._releaseSymbolFadeTiles=function(){for(var t in this.sourceCaches)this.sourceCaches[t].releaseSymbolFadeTiles()},r.prototype.getImages=function(t,e,r){this.imageManager.getImages(e.icons,r)},r.prototype.getGlyphs=function(t,e,r){this.glyphManager.getGlyphs(e.stacks,r)},r.prototype.getResource=function(e,r,n){return t.makeRequest(r,n)},r}(t.Evented);Re.getSourceType=function(t){return I[t]},Re.setSourceType=function(t,e){I[t]=e},Re.registerForPluginAvailability=t.registerForPluginAvailability;var Fe=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2}]),Be=cr(\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\",\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\\nvec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0\\n);}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;}\"),Ne=cr(\"uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),je=cr(\"uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}\"),Ve=cr(\"varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=v_data.xy;float extrude_length=length(extrude);lowp float antialiasblur=v_data.z;float antialiased_blur=-max(blur,antialiasblur);float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main(void) {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,0,1);} else {gl_Position=u_matrix*vec4(circle_center,0,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}lowp float antialiasblur=1.0/u_device_pixel_ratio/(radius+stroke_width);v_data=vec3(extrude.x,extrude.y,antialiasblur);}\"),Ue=cr(\"void main() {gl_FragColor=vec4(1.0);}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),qe=cr(\"uniform highp float u_intensity;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main() {\\n#pragma mapbox: initialize highp float weight\\nfloat d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#pragma mapbox: define mediump float radius\\nconst highp float ZERO=1.0/255.0/16.0;\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main(void) {\\n#pragma mapbox: initialize highp float weight\\n#pragma mapbox: initialize mediump float radius\\nvec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,0,1);gl_Position=u_matrix*pos;}\"),He=cr(\"uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(0.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}\"),Ge=cr(\"varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}\",\"attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}\"),Ye=cr(\"uniform float u_overscale_factor;varying float v_placed;varying float v_notUsed;varying float v_radius;varying vec2 v_extrude;varying vec2 v_extrude_scale;void main() {float alpha=0.5;vec4 color=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {color=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {color*=.2;}float extrude_scale_length=length(v_extrude_scale);float extrude_length=length(v_extrude)*extrude_scale_length;float stroke_width=15.0*extrude_scale_length/u_overscale_factor;float radius=v_radius*extrude_scale_length;float distance_to_edge=abs(extrude_length-radius);float opacity_t=smoothstep(-stroke_width,0.0,-distance_to_edge);gl_FragColor=opacity_t*color;}\",\"attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;varying float v_radius;varying vec2 v_extrude;varying vec2 v_extrude_scale;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);highp float padding_factor=1.2;gl_Position.xy+=a_extrude*u_extrude_scale*padding_factor*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;v_radius=abs(a_extrude.y);v_extrude=a_extrude*padding_factor;v_extrude_scale=u_extrude_scale*u_camera_to_center_distance*collision_perspective_ratio;}\"),We=cr(\"uniform highp vec4 u_color;void main() {gl_FragColor=u_color;}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),Xe=cr(\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_FragColor=color*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);}\"),Ze=cr(\"varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),Je=cr(\"uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec4 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float pixelRatio=u_scale.x;float tileRatio=u_scale.y;float fromScale=u_scale.z;float toScale=u_scale.w;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=vec2((pattern_br_a.x-pattern_tl_a.x)/pixelRatio,(pattern_br_a.y-pattern_tl_a.y)/pixelRatio);vec2 display_size_b=vec2((pattern_br_b.x-pattern_tl_b.x)/pixelRatio,(pattern_br_b.y-pattern_tl_b.y)/pixelRatio);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),Ke=cr(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec4 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float pixelRatio=u_scale.x;float tileZoomRatio=u_scale.y;float fromScale=u_scale.z;float toScale=u_scale.w;vec2 display_size_a=vec2((pattern_br_a.x-pattern_tl_a.x)/pixelRatio,(pattern_br_a.y-pattern_tl_a.y)/pixelRatio);vec2 display_size_b=vec2((pattern_br_b.x-pattern_tl_b.x)/pixelRatio,(pattern_br_b.y-pattern_tl_b.y)/pixelRatio);gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}\"),Qe=cr(\"varying vec4 v_color;void main() {gl_FragColor=v_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\\n#pragma mapbox: define highp float base\\n#pragma mapbox: define highp float height\\n#pragma mapbox: define highp vec4 color\\nvoid main() {\\n#pragma mapbox: initialize highp float base\\n#pragma mapbox: initialize highp float height\\n#pragma mapbox: initialize highp vec4 color\\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}\"),$e=cr(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec4 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float pixelRatio=u_scale.x;float tileRatio=u_scale.y;float fromScale=u_scale.z;float toScale=u_scale.w;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=vec2((pattern_br_a.x-pattern_tl_a.x)/pixelRatio,(pattern_br_a.y-pattern_tl_a.y)/pixelRatio);vec2 display_size_b=vec2((pattern_br_b.x-pattern_tl_b.x)/pixelRatio,(pattern_br_b.y-pattern_tl_b.y)/pixelRatio);base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\\n? a_pos\\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}\"),tr=cr(\"#ifdef GL_ES\\nprecision highp float;\\n#endif\\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform float u_maxzoom;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;return (data.r+data.g*256.0+data.b*256.0*256.0)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggeration=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/ pow(2.0,(u_zoom-u_maxzoom)*exaggeration+19.2562-u_zoom);gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}\"),er=cr(\"uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\\n#define PI 3.141592653589793\\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}\"),rr=cr(\"uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),nr=cr(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,vec2(v_lineprogress,0.5));gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define MAX_LINE_DISTANCE 32767.0\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_lineprogress=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0/MAX_LINE_DISTANCE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),ar=cr(\"uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec4 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float pixelRatio=u_scale.x;float tileZoomRatio=u_scale.y;float fromScale=u_scale.z;float toScale=u_scale.w;vec2 display_size_a=vec2((pattern_br_a.x-pattern_tl_a.x)/pixelRatio,(pattern_br_a.y-pattern_tl_a.y)/pixelRatio);vec2 display_size_b=vec2((pattern_br_b.x-pattern_tl_b.x)/pixelRatio,(pattern_br_b.y-pattern_tl_b.y)/pixelRatio);vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x,1.0);float x_b=mod(v_linesofar/pattern_size_b.x,1.0);float y_a=0.5+(v_normal.y*clamp(v_width2.s,0.0,(pattern_size_a.y+2.0)/2.0)/pattern_size_a.y);float y_b=0.5+(v_normal.y*clamp(v_width2.s,0.0,(pattern_size_b.y+2.0)/2.0)/pattern_size_b.y);vec2 pos_a=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,vec2(x_a,y_a));vec2 pos_b=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,vec2(x_b,y_b));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);}\"),ir=cr(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}\"),or=cr(\"uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}\"),sr=cr(\"uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size[0],a_size[1],u_size_t)/256.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size[0]/256.0;} else if (!u_is_size_zoom_constant && u_is_size_feature_constant) {size=u_size;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}\"),lr=cr(\"#define SDF_PX 8.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size[0],a_size[1],u_size_t)/256.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size[0]/256.0;} else if (!u_is_size_zoom_constant && u_is_size_feature_constant) {size=u_size;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=vec2(tex.x,tex.y);v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}\");function cr(t,e){var r=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,n={};return{fragmentSource:t=t.replace(r,function(t,e,r,a,i){return n[i]=!0,\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\nvarying \"+r+\" \"+a+\" \"+i+\";\\n#else\\nuniform \"+r+\" \"+a+\" u_\"+i+\";\\n#endif\\n\":\"\\n#ifdef HAS_UNIFORM_u_\"+i+\"\\n    \"+r+\" \"+a+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\"}),vertexSource:e=e.replace(r,function(t,e,r,a,i){var o=\"float\"===a?\"vec2\":\"vec4\",s=i.match(/color/)?\"color\":o;return n[i]?\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\nuniform lowp float u_\"+i+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+i+\";\\nvarying \"+r+\" \"+a+\" \"+i+\";\\n#else\\nuniform \"+r+\" \"+a+\" u_\"+i+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\n    \"+i+\" = a_\"+i+\";\\n#else\\n    \"+r+\" \"+a+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\n    \"+i+\" = unpack_mix_\"+s+\"(a_\"+i+\", u_\"+i+\"_t);\\n#else\\n    \"+r+\" \"+a+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\":\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\nuniform lowp float u_\"+i+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+i+\";\\n#else\\nuniform \"+r+\" \"+a+\" u_\"+i+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\n    \"+r+\" \"+a+\" \"+i+\" = a_\"+i+\";\\n#else\\n    \"+r+\" \"+a+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\n    \"+r+\" \"+a+\" \"+i+\" = unpack_mix_\"+s+\"(a_\"+i+\", u_\"+i+\"_t);\\n#else\\n    \"+r+\" \"+a+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\"})}}var ur=Object.freeze({prelude:Be,background:Ne,backgroundPattern:je,circle:Ve,clippingMask:Ue,heatmap:qe,heatmapTexture:He,collisionBox:Ge,collisionCircle:Ye,debug:We,fill:Xe,fillOutline:Ze,fillOutlinePattern:Je,fillPattern:Ke,fillExtrusion:Qe,fillExtrusionPattern:$e,hillshadePrepare:tr,hillshade:er,line:rr,lineGradient:nr,linePattern:ar,lineSDF:ir,raster:or,symbolIcon:sr,symbolSDF:lr}),hr=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};hr.prototype.bind=function(t,e,r,n,a,i,o,s){this.context=t;for(var l=this.boundPaintVertexBuffers.length!==n.length,c=0;!l&&c<n.length;c++)this.boundPaintVertexBuffers[c]!==n[c]&&(l=!0);var u=!this.vao||this.boundProgram!==e||this.boundLayoutVertexBuffer!==r||l||this.boundIndexBuffer!==a||this.boundVertexOffset!==i||this.boundDynamicVertexBuffer!==o||this.boundDynamicVertexBuffer2!==s;!t.extVertexArrayObject||u?this.freshBind(e,r,n,a,i,o,s):(t.bindVertexArrayOES.set(this.vao),o&&o.bind(),a&&a.dynamicDraw&&a.bind(),s&&s.bind())},hr.prototype.freshBind=function(t,e,r,n,a,i,o){var s,l=t.numAttributes,c=this.context,u=c.gl;if(c.extVertexArrayObject)this.vao&&this.destroy(),this.vao=c.extVertexArrayObject.createVertexArrayOES(),c.bindVertexArrayOES.set(this.vao),s=0,this.boundProgram=t,this.boundLayoutVertexBuffer=e,this.boundPaintVertexBuffers=r,this.boundIndexBuffer=n,this.boundVertexOffset=a,this.boundDynamicVertexBuffer=i,this.boundDynamicVertexBuffer2=o;else{s=c.currentNumAttributes||0;for(var h=l;h<s;h++)u.disableVertexAttribArray(h)}e.enableAttributes(u,t);for(var f=0,p=r;f<p.length;f+=1)p[f].enableAttributes(u,t);i&&i.enableAttributes(u,t),o&&o.enableAttributes(u,t),e.bind(),e.setVertexAttribPointers(u,t,a);for(var d=0,g=r;d<g.length;d+=1){var v=g[d];v.bind(),v.setVertexAttribPointers(u,t,a)}i&&(i.bind(),i.setVertexAttribPointers(u,t,a)),n&&n.bind(),o&&(o.bind(),o.setVertexAttribPointers(u,t,a)),c.currentNumAttributes=l},hr.prototype.destroy=function(){this.vao&&(this.context.extVertexArrayObject.deleteVertexArrayOES(this.vao),this.vao=null)};var fr=function(t,e,r,n,a){var i=t.gl;this.program=i.createProgram();var o=r.defines();a&&o.push(\"#define OVERDRAW_INSPECTOR;\");var s=o.concat(Be.fragmentSource,e.fragmentSource).join(\"\\n\"),l=o.concat(Be.vertexSource,e.vertexSource).join(\"\\n\"),c=i.createShader(i.FRAGMENT_SHADER);i.shaderSource(c,s),i.compileShader(c),i.attachShader(this.program,c);var u=i.createShader(i.VERTEX_SHADER);i.shaderSource(u,l),i.compileShader(u),i.attachShader(this.program,u);for(var h=r.layoutAttributes||[],f=0;f<h.length;f++)i.bindAttribLocation(this.program,f,h[f].name);i.linkProgram(this.program),this.numAttributes=i.getProgramParameter(this.program,i.ACTIVE_ATTRIBUTES),this.attributes={};for(var p={},d=0;d<this.numAttributes;d++){var g=i.getActiveAttrib(this.program,d);g&&(this.attributes[g.name]=i.getAttribLocation(this.program,g.name))}for(var v=i.getProgramParameter(this.program,i.ACTIVE_UNIFORMS),m=0;m<v;m++){var y=i.getActiveUniform(this.program,m);y&&(p[y.name]=i.getUniformLocation(this.program,y.name))}this.fixedUniforms=n(t,p),this.binderUniforms=r.getUniforms(t,p)};function pr(e,r,n){var a=1/ce(n,1,r.transform.tileZoom),i=Math.pow(2,n.tileID.overscaledZ),o=n.tileSize*Math.pow(2,r.transform.tileZoom)/i,s=o*(n.tileID.canonical.x+n.tileID.wrap*i),l=o*n.tileID.canonical.y;return{u_image:0,u_texsize:n.imageAtlasTexture.size,u_scale:[t.browser.devicePixelRatio,a,e.fromScale,e.toScale],u_fade:e.t,u_pixel_coord_upper:[s>>16,l>>16],u_pixel_coord_lower:[65535&s,65535&l]}}fr.prototype.draw=function(t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g){var v,m=t.gl;for(var y in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(a),t.setCullFace(i),this.fixedUniforms)this.fixedUniforms[y].set(o[y]);p&&p.setUniforms(t,this.binderUniforms,h,{zoom:f});for(var x=(v={},v[m.LINES]=2,v[m.TRIANGLES]=3,v[m.LINE_STRIP]=1,v)[e],b=0,_=u.get();b<_.length;b+=1){var w=_[b],k=w.vaos||(w.vaos={});(k[s]||(k[s]=new hr)).bind(t,this,l,p?p.getPaintVertexBuffers():[],c,w.vertexOffset,d,g),m.drawElements(e,w.primitiveLength*x,m.UNSIGNED_SHORT,w.primitiveOffset*x*2)}};var dr=function(e,r,n,a){var i=r.style.light,o=i.properties.get(\"position\"),s=[o.x,o.y,o.z],l=t.create$1();\"viewport\"===i.properties.get(\"anchor\")&&t.fromRotation(l,-r.transform.angle),t.transformMat3(s,s,l);var c=i.properties.get(\"color\");return{u_matrix:e,u_lightpos:s,u_lightintensity:i.properties.get(\"intensity\"),u_lightcolor:[c.r,c.g,c.b],u_vertical_gradient:+n,u_opacity:a}},gr=function(e,r,n,a,i,o,s){return t.extend(dr(e,r,n,a),pr(o,r,s),{u_height_factor:-Math.pow(2,i.overscaledZ)/s.tileSize/8})},vr=function(t){return{u_matrix:t}},mr=function(e,r,n,a){return t.extend(vr(e),pr(n,r,a))},yr=function(t,e){return{u_matrix:t,u_world:e}},xr=function(e,r,n,a,i){return t.extend(mr(e,r,n,a),{u_world:i})},br=function(e,r,n,a){var i,o,s=e.transform;if(\"map\"===a.paint.get(\"circle-pitch-alignment\")){var l=ce(n,1,s.zoom);i=!0,o=[l,l]}else i=!1,o=s.pixelsToGLUnits;return{u_camera_to_center_distance:s.cameraToCenterDistance,u_scale_with_map:+(\"map\"===a.paint.get(\"circle-pitch-scale\")),u_matrix:e.translatePosMatrix(r.posMatrix,n,a.paint.get(\"circle-translate\"),a.paint.get(\"circle-translate-anchor\")),u_pitch_with_map:+i,u_device_pixel_ratio:t.browser.devicePixelRatio,u_extrude_scale:o}},_r=function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},wr=function(t,e,r){var n=ce(r,1,e.zoom),a=Math.pow(2,e.zoom-r.tileID.overscaledZ),i=r.tileID.overscaleFactor();return{u_matrix:t,u_camera_to_center_distance:e.cameraToCenterDistance,u_pixels_to_tile_units:n,u_extrude_scale:[e.pixelsToGLUnits[0]/(n*a),e.pixelsToGLUnits[1]/(n*a)],u_overscale_factor:i}},kr=function(t,e){return{u_matrix:t,u_color:e}},Tr=function(t){return{u_matrix:t}},Mr=function(t,e,r,n){return{u_matrix:t,u_extrude_scale:ce(e,1,r),u_intensity:n}},Ar=function(t,e,r){var n=r.paint.get(\"hillshade-shadow-color\"),a=r.paint.get(\"hillshade-highlight-color\"),i=r.paint.get(\"hillshade-accent-color\"),o=r.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);\"viewport\"===r.paint.get(\"hillshade-illumination-anchor\")&&(o-=t.transform.angle);var s=!t.options.moving;return{u_matrix:t.transform.calculatePosMatrix(e.tileID.toUnwrapped(),s),u_image:0,u_latrange:Er(t,e.tileID),u_light:[r.paint.get(\"hillshade-exaggeration\"),o],u_shadow:n,u_highlight:a,u_accent:i}},Sr=function(e,r){var n=e.dem.stride,a=t.create();return t.ortho(a,0,t.EXTENT,-t.EXTENT,0,0,1),t.translate(a,a,[0,-t.EXTENT,0]),{u_matrix:a,u_image:1,u_dimension:[n,n],u_zoom:e.tileID.overscaledZ,u_maxzoom:r}};function Er(e,r){var n=Math.pow(2,r.canonical.z),a=r.canonical.y;return[new t.MercatorCoordinate(0,a/n).toLngLat().lat,new t.MercatorCoordinate(0,(a+1)/n).toLngLat().lat]}var Lr=function(e,r,n){var a=e.transform;return{u_matrix:Ir(e,r,n),u_ratio:1/ce(r,1,a.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_units_to_pixels:[1/a.pixelsToGLUnits[0],1/a.pixelsToGLUnits[1]]}},Cr=function(e,r,n){return t.extend(Lr(e,r,n),{u_image:0})},Pr=function(e,r,n,a){var i=e.transform,o=zr(r,i);return{u_matrix:Ir(e,r,n),u_texsize:r.imageAtlasTexture.size,u_ratio:1/ce(r,1,i.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_image:0,u_scale:[t.browser.devicePixelRatio,o,a.fromScale,a.toScale],u_fade:a.t,u_units_to_pixels:[1/i.pixelsToGLUnits[0],1/i.pixelsToGLUnits[1]]}},Or=function(e,r,n,a,i){var o=e.transform,s=e.lineAtlas,l=zr(r,o),c=\"round\"===n.layout.get(\"line-cap\"),u=s.getDash(a.from,c),h=s.getDash(a.to,c),f=u.width*i.fromScale,p=h.width*i.toScale;return t.extend(Lr(e,r,n),{u_patternscale_a:[l/f,-u.height/2],u_patternscale_b:[l/p,-h.height/2],u_sdfgamma:s.width/(256*Math.min(f,p)*t.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:u.y,u_tex_y_b:h.y,u_mix:i.t})};function zr(t,e){return 1/ce(t,1,e.tileZoom)}function Ir(t,e,r){return t.translatePosMatrix(e.tileID.posMatrix,e,r.paint.get(\"line-translate\"),r.paint.get(\"line-translate-anchor\"))}var Dr=function(t,e,r,n,a){return{u_matrix:t,u_tl_parent:e,u_scale_parent:r,u_buffer_scale:1,u_fade_t:n.mix,u_opacity:n.opacity*a.paint.get(\"raster-opacity\"),u_image0:0,u_image1:1,u_brightness_low:a.paint.get(\"raster-brightness-min\"),u_brightness_high:a.paint.get(\"raster-brightness-max\"),u_saturation_factor:(o=a.paint.get(\"raster-saturation\"),o>0?1-1/(1.001-o):-o),u_contrast_factor:(i=a.paint.get(\"raster-contrast\"),i>0?1/(1-i):1+i),u_spin_weights:Rr(a.paint.get(\"raster-hue-rotate\"))};var i,o};function Rr(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}var Fr=function(t,e,r,n,a,i,o,s,l,c){var u=a.transform;return{u_is_size_zoom_constant:+(\"constant\"===t||\"source\"===t),u_is_size_feature_constant:+(\"constant\"===t||\"camera\"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:u.cameraToCenterDistance,u_pitch:u.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:u.width/u.height,u_fade_change:a.options.fadeDuration?a.symbolFadeChange:1,u_matrix:i,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:c,u_texture:0}},Br=function(e,r,n,a,i,o,s,l,c,u,h){var f=i.transform;return t.extend(Fr(e,r,n,a,i,o,s,l,c,u),{u_gamma_scale:a?Math.cos(f._pitch)*f.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+h})},Nr=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},jr=function(e,r,n,a,i,o){return t.extend(function(t,e,r,n){var a=r.imageManager.getPattern(t.from),i=r.imageManager.getPattern(t.to),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,c=Math.pow(2,n.tileID.overscaledZ),u=n.tileSize*Math.pow(2,r.transform.tileZoom)/c,h=u*(n.tileID.canonical.x+n.tileID.wrap*c),f=u*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:a.tl,u_pattern_br_a:a.br,u_pattern_tl_b:i.tl,u_pattern_br_b:i.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:a.displaySize,u_pattern_size_b:i.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/ce(n,1,r.transform.tileZoom),u_pixel_coord_upper:[h>>16,f>>16],u_pixel_coord_lower:[65535&h,65535&f]}}(a,o,n,i),{u_matrix:e,u_opacity:r})},Vr={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform4f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform4f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform4f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:_r,collisionCircle:_r,debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_maxzoom:new t.Uniform1f(e,r.u_maxzoom)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform4f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1f(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1f(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1f(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function Ur(e,r){for(var n=e.sort(function(t,e){return t.tileID.isLessThan(e.tileID)?-1:e.tileID.isLessThan(t.tileID)?1:0}),a=0;a<n.length;a++){var i={},o=n[a],s=n.slice(a+1);qr(o.tileID.wrapped(),o.tileID,s,new t.OverscaledTileID(0,o.tileID.wrap+1,0,0,0),i),o.setMask(i,r)}}function qr(e,r,n,a,i){for(var o=0;o<n.length;o++){var s=n[o];if(a.isLessThan(s.tileID))break;if(r.key===s.tileID.key)return;if(s.tileID.isChildOf(r)){for(var l=r.children(1/0),c=0;c<l.length;c++)qr(e,l[c],n.slice(o),a,i);return}}var u=r.overscaledZ-e.overscaledZ,h=new t.CanonicalTileID(u,r.canonical.x-(e.canonical.x<<u),r.canonical.y-(e.canonical.y<<u));i[h.key]=i[h.key]||h}function Hr(t,e,r,n,a){for(var i=t.context,o=i.gl,s=a?t.useProgram(\"collisionCircle\"):t.useProgram(\"collisionBox\"),l=0;l<n.length;l++){var c=n[l],u=e.getTile(c),h=u.getBucket(r);if(h){var f=a?h.collisionCircle:h.collisionBox;f&&s.draw(i,a?o.TRIANGLES:o.LINES,Mt.disabled,At.disabled,t.colorModeForRenderPass(),Et.disabled,wr(c.posMatrix,t.transform,u),r.id,f.layoutVertexBuffer,f.indexBuffer,f.segments,null,t.transform.zoom,null,null,f.collisionVertexBuffer)}}}var Gr=t.identity(new Float32Array(16));function Yr(e,r,n,a,i,o){var s=t.getAnchorAlignment(e),l=-(s.horizontalAlign-.5)*r,c=-(s.verticalAlign-.5)*n,u=t.evaluateRadialOffset(e,a);return new t.Point((l/i+u[0])*o,(c/i+u[1])*o)}function Wr(e,r,n,a,i,o,s,l,c,u){var h=e.text.placedSymbolArray,f=e.text.dynamicLayoutVertexArray;f.clear();for(var p=0;p<h.length;p++){var d=h.get(p),g=e.allowVerticalPlacement&&!d.placedOrientation,v=d.hidden||!d.crossTileID||g?null:a[d.crossTileID];if(v){var m=new t.Point(d.anchorX,d.anchorY),y=Jt(m,n?l:s),x=.5+o.cameraToCenterDistance/y.signedDistanceFromCamera*.5,b=i.evaluateSizeForFeature(e.textSizeData,u,d)*x/t.ONE_EM;n&&(b*=e.tilePixelRatio/c);for(var _=v.width,w=v.height,k=v.radialOffset,T=v.textBoxScale,M=Yr(v.anchor,_,w,k,T,b),A=n?Jt(m.add(M),s).point:y.point.add(r?M.rotate(-o.angle):M),S=e.allowVerticalPlacement&&d.placedOrientation===t.WritingMode.vertical?Math.PI/2:0,E=0;E<d.numGlyphs;E++)t.addDynamicAttributes(f,A,S)}else ie(d.numGlyphs,f)}e.text.dynamicLayoutVertexBuffer.updateData(f)}function Xr(e){var r=e.text.placedSymbolArray,n=e.text.dynamicLayoutVertexArray;n.clear();for(var a=0;a<r.length;a++){var i=r.get(a);if(i.hidden||!i.placedOrientation)ie(i.numGlyphs,n);else for(var o=new t.Point(i.anchorX,i.anchorY),s=e.allowVerticalPlacement&&i.placedOrientation===t.WritingMode.vertical?Math.PI/2:0,l=0;l<i.numGlyphs;l++)t.addDynamicAttributes(n,o,s)}e.text.dynamicLayoutVertexBuffer.updateData(n)}function Zr(e,r,n,a,i,o,s,l,c,u,h,f,p){for(var d,g,v=e.context,m=v.gl,y=e.transform,x=\"map\"===l,b=\"map\"===c,_=x&&\"point\"!==n.layout.get(\"symbol-placement\"),w=x&&!b&&!_,k=void 0!==n.layout.get(\"symbol-sort-key\").constantOr(1),T=e.depthModeForSublayer(0,Mt.ReadOnly),M=n.layout.get(\"text-variable-anchor\"),A=[],S=0,E=a;S<E.length;S+=1){var L=E[S],C=r.getTile(L),P=C.getBucket(n);if(P){var O=i?P.text:P.icon;if(O&&O.segments.get().length){var z=O.programConfigurations.get(n.id),I=i||P.sdfIcons,D=i?P.textSizeData:P.iconSizeData;d||(d=e.useProgram(I?\"symbolSDF\":\"symbolIcon\",z),g=t.evaluateSizeForZoom(D,y.zoom)),v.activeTexture.set(m.TEXTURE0);var R=void 0,F=void 0,B=void 0;if(i)F=C.glyphAtlasTexture,B=m.LINEAR,R=C.glyphAtlasTexture.size;else{var N=1!==n.layout.get(\"icon-size\").constantOr(0)||P.iconsNeedLinear,j=b||0!==y.pitch;F=C.imageAtlasTexture,B=I||e.options.rotating||e.options.zooming||N||j?m.LINEAR:m.NEAREST,R=C.imageAtlasTexture.size}var V=ce(C,1,e.transform.zoom),U=Xt(L.posMatrix,b,x,e.transform,V),q=Zt(L.posMatrix,b,x,e.transform,V);if(_)Qt(P,L.posMatrix,e,i,U,q,b,u);else if(i&&g&&M){var H=Math.pow(2,y.zoom-C.tileID.overscaledZ);Wr(P,x,b,p,t.symbolSize,y,U,L.posMatrix,H,g)}else i&&g&&P.allowVerticalPlacement&&Xr(P);var G=e.translatePosMatrix(L.posMatrix,C,o,s),Y=_||i&&M?Gr:U,W=e.translatePosMatrix(q,C,o,s,!0),X=I&&0!==n.paint.get(i?\"text-halo-width\":\"icon-halo-width\").constantOr(1),Z={program:d,buffers:O,uniformValues:I?Br(D.kind,g,w,b,e,G,Y,W,i,R,!0):Fr(D.kind,g,w,b,e,G,Y,W,i,R),atlasTexture:F,atlasInterpolation:B,isSDF:I,hasHalo:X};if(k)for(var J=0,K=O.segments.get();J<K.length;J+=1){var Q=K[J];A.push({segments:new t.SegmentVector([Q]),sortKey:Q.sortKey,state:Z})}else A.push({segments:O.segments,sortKey:0,state:Z})}}}k&&A.sort(function(t,e){return t.sortKey-e.sortKey});for(var $=0,tt=A;$<tt.length;$+=1){var et=tt[$],rt=et.state;if(rt.atlasTexture.bind(rt.atlasInterpolation,m.CLAMP_TO_EDGE),rt.isSDF){var nt=rt.uniformValues;rt.hasHalo&&(nt.u_is_halo=1,Jr(rt.buffers,et.segments,n,e,rt.program,T,h,f,nt)),nt.u_is_halo=0}Jr(rt.buffers,et.segments,n,e,rt.program,T,h,f,rt.uniformValues)}}function Jr(t,e,r,n,a,i,o,s,l){var c=n.context,u=c.gl;a.draw(c,u.TRIANGLES,i,o,s,Et.disabled,l,r.id,t.layoutVertexBuffer,t.indexBuffer,e,r.paint,n.transform.zoom,t.programConfigurations.get(r.id),t.dynamicLayoutVertexBuffer,t.opacityVertexBuffer)}function Kr(t,e,r,n,a,i,o){var s,l,c,u,h,f=t.context.gl,p=r.paint.get(\"fill-pattern\"),d=p&&p.constantOr(1),g=r.getCrossfadeParameters();o?(l=d&&!r.getPaintProperty(\"fill-outline-color\")?\"fillOutlinePattern\":\"fillOutline\",s=f.LINES):(l=d?\"fillPattern\":\"fill\",s=f.TRIANGLES);for(var v=0,m=n;v<m.length;v+=1){var y=m[v],x=e.getTile(y);if(!d||x.patternsLoaded()){var b=x.getBucket(r);if(b){var _=b.programConfigurations.get(r.id),w=t.useProgram(l,_);d&&(t.context.activeTexture.set(f.TEXTURE0),x.imageAtlasTexture.bind(f.LINEAR,f.CLAMP_TO_EDGE),_.updatePatternPaintBuffers(g));var k=p.constantOr(null);if(k&&x.imageAtlas){var T=x.imageAtlas.patternPositions[k.to],M=x.imageAtlas.patternPositions[k.from];T&&M&&_.setConstantPatternPositions(T,M)}var A=t.translatePosMatrix(y.posMatrix,x,r.paint.get(\"fill-translate\"),r.paint.get(\"fill-translate-anchor\"));if(o){u=b.indexBuffer2,h=b.segments2;var S=[f.drawingBufferWidth,f.drawingBufferHeight];c=\"fillOutlinePattern\"===l&&d?xr(A,t,g,x,S):yr(A,S)}else u=b.indexBuffer,h=b.segments,c=d?mr(A,t,g,x):vr(A);w.draw(t.context,s,a,t.stencilModeForClipping(y),i,Et.disabled,c,r.id,b.layoutVertexBuffer,u,h,r.paint,t.transform.zoom,_)}}}}function Qr(t,e,r,n,a,i,o){for(var s=t.context,l=s.gl,c=r.paint.get(\"fill-extrusion-pattern\"),u=c.constantOr(1),h=r.getCrossfadeParameters(),f=r.paint.get(\"fill-extrusion-opacity\"),p=0,d=n;p<d.length;p+=1){var g=d[p],v=e.getTile(g),m=v.getBucket(r);if(m){var y=m.programConfigurations.get(r.id),x=t.useProgram(u?\"fillExtrusionPattern\":\"fillExtrusion\",y);u&&(t.context.activeTexture.set(l.TEXTURE0),v.imageAtlasTexture.bind(l.LINEAR,l.CLAMP_TO_EDGE),y.updatePatternPaintBuffers(h));var b=c.constantOr(null);if(b&&v.imageAtlas){var _=v.imageAtlas.patternPositions[b.to],w=v.imageAtlas.patternPositions[b.from];_&&w&&y.setConstantPatternPositions(_,w)}var k=t.translatePosMatrix(g.posMatrix,v,r.paint.get(\"fill-extrusion-translate\"),r.paint.get(\"fill-extrusion-translate-anchor\")),T=r.paint.get(\"fill-extrusion-vertical-gradient\"),M=u?gr(k,t,T,f,g,h,v):dr(k,t,T,f);x.draw(s,s.gl.TRIANGLES,a,i,o,Et.backCCW,M,r.id,m.layoutVertexBuffer,m.indexBuffer,m.segments,r.paint,t.transform.zoom,y)}}}function $r(t,e,r,n,a,i){var o=t.context,s=o.gl,l=e.fbo;if(l){var c=t.useProgram(\"hillshade\");o.activeTexture.set(s.TEXTURE0),s.bindTexture(s.TEXTURE_2D,l.colorAttachment.get());var u=Ar(t,e,r);e.maskedBoundsBuffer&&e.maskedIndexBuffer&&e.segments?c.draw(o,s.TRIANGLES,n,a,i,Et.disabled,u,r.id,e.maskedBoundsBuffer,e.maskedIndexBuffer,e.segments):c.draw(o,s.TRIANGLES,n,a,i,Et.disabled,u,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}}function tn(e,r,n,a,i,o,s){var l=e.context,c=l.gl;if(r.dem&&r.dem.data){var u=r.dem.dim,h=r.dem.stride,f=r.dem.getPixels();if(l.activeTexture.set(c.TEXTURE1),l.pixelStoreUnpackPremultiplyAlpha.set(!1),r.demTexture=r.demTexture||e.getTileTexture(h),r.demTexture){var p=r.demTexture;p.update(f,{premultiply:!1}),p.bind(c.NEAREST,c.CLAMP_TO_EDGE)}else r.demTexture=new t.Texture(l,f,c.RGBA,{premultiply:!1}),r.demTexture.bind(c.NEAREST,c.CLAMP_TO_EDGE);l.activeTexture.set(c.TEXTURE0);var d=r.fbo;if(!d){var g=new t.Texture(l,{width:u,height:u,data:null},c.RGBA);g.bind(c.LINEAR,c.CLAMP_TO_EDGE),(d=r.fbo=l.createFramebuffer(u,u)).colorAttachment.set(g.texture)}l.bindFramebuffer.set(d.framebuffer),l.viewport.set([0,0,u,u]),e.useProgram(\"hillshadePrepare\").draw(l,c.TRIANGLES,i,o,s,Et.disabled,Sr(r,a),n.id,e.rasterBoundsBuffer,e.quadTriangleIndexBuffer,e.rasterBoundsSegments),r.needsHillshadePrepare=!1}}function en(e,r,n,a,i){var o=a.paint.get(\"raster-fade-duration\");if(o>0){var s=t.browser.now(),l=(s-e.timeAdded)/o,c=r?(s-r.timeAdded)/o:-1,u=n.getSource(),h=i.coveringZoomLevel({tileSize:u.tileSize,roundZoom:u.roundZoom}),f=!r||Math.abs(r.tileID.overscaledZ-h)>Math.abs(e.tileID.overscaledZ-h),p=f&&e.refreshedUponExpiration?1:t.clamp(f?l:1-c,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}function rn(e,r,n){var a=e.context,i=a.gl,o=n.posMatrix,s=e.useProgram(\"debug\"),l=Mt.disabled,c=At.disabled,u=e.colorModeForRenderPass(),h=\"$debug\";s.draw(a,i.LINE_STRIP,l,c,u,Et.disabled,kr(o,t.Color.red),h,e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);for(var f=r.getTileByID(n.key).latestRawTileData,p=f&&f.byteLength||0,d=Math.floor(p/1024),g=r.getTile(n).tileSize,v=512/Math.min(g,512),m=function(t,e,r,n){n=n||1;var a,i,o,s,l,c,u,h,f=[];for(a=0,i=t.length;a<i;a++)if(l=nn[t[a]]){for(h=null,o=0,s=l[1].length;o<s;o+=2)-1===l[1][o]&&-1===l[1][o+1]?h=null:(c=e+l[1][o]*n,u=r-l[1][o+1]*n,h&&f.push(h.x,h.y,c,u),h={x:c,y:u});e+=l[0]*n}return f}(n.toString()+\" \"+d+\"kb\",50,200*v,5*v),y=new t.StructArrayLayout2i4,x=new t.StructArrayLayout2ui4,b=0;b<m.length;b+=2)y.emplaceBack(m[b],m[b+1]),x.emplaceBack(b,b+1);for(var _=a.createVertexBuffer(y,Fe.members),w=a.createIndexBuffer(x),k=t.SegmentVector.simpleSegment(0,0,y.length/2,y.length/2),T=t.EXTENT/(Math.pow(2,e.transform.zoom-n.overscaledZ)*g*v),M=[],A=-1;A<=1;A++)for(var S=-1;S<=1&&(0!==A||0!==S);S++)M.push([A,S]);for(var E=0;E<M.length;E++){var L=M[E];s.draw(a,i.LINES,l,c,u,Et.disabled,kr(t.translate([],o,[T*L[0],T*L[1],0]),t.Color.white),h,_,w,k)}s.draw(a,i.LINES,l,c,u,Et.disabled,kr(o,t.Color.black),h,_,w,k)}var nn={\" \":[16,[]],\"!\":[10,[5,21,5,7,-1,-1,5,2,4,1,5,0,6,1,5,2]],'\"':[16,[4,21,4,14,-1,-1,12,21,12,14]],\"#\":[21,[11,25,4,-7,-1,-1,17,25,10,-7,-1,-1,4,12,18,12,-1,-1,3,6,17,6]],$:[20,[8,25,8,-4,-1,-1,12,25,12,-4,-1,-1,17,18,15,20,12,21,8,21,5,20,3,18,3,16,4,14,5,13,7,12,13,10,15,9,16,8,17,6,17,3,15,1,12,0,8,0,5,1,3,3]],\"%\":[24,[21,21,3,0,-1,-1,8,21,10,19,10,17,9,15,7,14,5,14,3,16,3,18,4,20,6,21,8,21,10,20,13,19,16,19,19,20,21,21,-1,-1,17,7,15,6,14,4,14,2,16,0,18,0,20,1,21,3,21,5,19,7,17,7]],\"&\":[26,[23,12,23,13,22,14,21,14,20,13,19,11,17,6,15,3,13,1,11,0,7,0,5,1,4,2,3,4,3,6,4,8,5,9,12,13,13,14,14,16,14,18,13,20,11,21,9,20,8,18,8,16,9,13,11,10,16,3,18,1,20,0,22,0,23,1,23,2]],\"'\":[10,[5,19,4,20,5,21,6,20,6,18,5,16,4,15]],\"(\":[14,[11,25,9,23,7,20,5,16,4,11,4,7,5,2,7,-2,9,-5,11,-7]],\")\":[14,[3,25,5,23,7,20,9,16,10,11,10,7,9,2,7,-2,5,-5,3,-7]],\"*\":[16,[8,21,8,9,-1,-1,3,18,13,12,-1,-1,13,18,3,12]],\"+\":[26,[13,18,13,0,-1,-1,4,9,22,9]],\",\":[10,[6,1,5,0,4,1,5,2,6,1,6,-1,5,-3,4,-4]],\"-\":[26,[4,9,22,9]],\".\":[10,[5,2,4,1,5,0,6,1,5,2]],\"/\":[22,[20,25,2,-7]],0:[20,[9,21,6,20,4,17,3,12,3,9,4,4,6,1,9,0,11,0,14,1,16,4,17,9,17,12,16,17,14,20,11,21,9,21]],1:[20,[6,17,8,18,11,21,11,0]],2:[20,[4,16,4,17,5,19,6,20,8,21,12,21,14,20,15,19,16,17,16,15,15,13,13,10,3,0,17,0]],3:[20,[5,21,16,21,10,13,13,13,15,12,16,11,17,8,17,6,16,3,14,1,11,0,8,0,5,1,4,2,3,4]],4:[20,[13,21,3,7,18,7,-1,-1,13,21,13,0]],5:[20,[15,21,5,21,4,12,5,13,8,14,11,14,14,13,16,11,17,8,17,6,16,3,14,1,11,0,8,0,5,1,4,2,3,4]],6:[20,[16,18,15,20,12,21,10,21,7,20,5,17,4,12,4,7,5,3,7,1,10,0,11,0,14,1,16,3,17,6,17,7,16,10,14,12,11,13,10,13,7,12,5,10,4,7]],7:[20,[17,21,7,0,-1,-1,3,21,17,21]],8:[20,[8,21,5,20,4,18,4,16,5,14,7,13,11,12,14,11,16,9,17,7,17,4,16,2,15,1,12,0,8,0,5,1,4,2,3,4,3,7,4,9,6,11,9,12,13,13,15,14,16,16,16,18,15,20,12,21,8,21]],9:[20,[16,14,15,11,13,9,10,8,9,8,6,9,4,11,3,14,3,15,4,18,6,20,9,21,10,21,13,20,15,18,16,14,16,9,15,4,13,1,10,0,8,0,5,1,4,3]],\":\":[10,[5,14,4,13,5,12,6,13,5,14,-1,-1,5,2,4,1,5,0,6,1,5,2]],\";\":[10,[5,14,4,13,5,12,6,13,5,14,-1,-1,6,1,5,0,4,1,5,2,6,1,6,-1,5,-3,4,-4]],\"<\":[24,[20,18,4,9,20,0]],\"=\":[26,[4,12,22,12,-1,-1,4,6,22,6]],\">\":[24,[4,18,20,9,4,0]],\"?\":[18,[3,16,3,17,4,19,5,20,7,21,11,21,13,20,14,19,15,17,15,15,14,13,13,12,9,10,9,7,-1,-1,9,2,8,1,9,0,10,1,9,2]],\"@\":[27,[18,13,17,15,15,16,12,16,10,15,9,14,8,11,8,8,9,6,11,5,14,5,16,6,17,8,-1,-1,12,16,10,14,9,11,9,8,10,6,11,5,-1,-1,18,16,17,8,17,6,19,5,21,5,23,7,24,10,24,12,23,15,22,17,20,19,18,20,15,21,12,21,9,20,7,19,5,17,4,15,3,12,3,9,4,6,5,4,7,2,9,1,12,0,15,0,18,1,20,2,21,3,-1,-1,19,16,18,8,18,6,19,5]],A:[18,[9,21,1,0,-1,-1,9,21,17,0,-1,-1,4,7,14,7]],B:[21,[4,21,4,0,-1,-1,4,21,13,21,16,20,17,19,18,17,18,15,17,13,16,12,13,11,-1,-1,4,11,13,11,16,10,17,9,18,7,18,4,17,2,16,1,13,0,4,0]],C:[21,[18,16,17,18,15,20,13,21,9,21,7,20,5,18,4,16,3,13,3,8,4,5,5,3,7,1,9,0,13,0,15,1,17,3,18,5]],D:[21,[4,21,4,0,-1,-1,4,21,11,21,14,20,16,18,17,16,18,13,18,8,17,5,16,3,14,1,11,0,4,0]],E:[19,[4,21,4,0,-1,-1,4,21,17,21,-1,-1,4,11,12,11,-1,-1,4,0,17,0]],F:[18,[4,21,4,0,-1,-1,4,21,17,21,-1,-1,4,11,12,11]],G:[21,[18,16,17,18,15,20,13,21,9,21,7,20,5,18,4,16,3,13,3,8,4,5,5,3,7,1,9,0,13,0,15,1,17,3,18,5,18,8,-1,-1,13,8,18,8]],H:[22,[4,21,4,0,-1,-1,18,21,18,0,-1,-1,4,11,18,11]],I:[8,[4,21,4,0]],J:[16,[12,21,12,5,11,2,10,1,8,0,6,0,4,1,3,2,2,5,2,7]],K:[21,[4,21,4,0,-1,-1,18,21,4,7,-1,-1,9,12,18,0]],L:[17,[4,21,4,0,-1,-1,4,0,16,0]],M:[24,[4,21,4,0,-1,-1,4,21,12,0,-1,-1,20,21,12,0,-1,-1,20,21,20,0]],N:[22,[4,21,4,0,-1,-1,4,21,18,0,-1,-1,18,21,18,0]],O:[22,[9,21,7,20,5,18,4,16,3,13,3,8,4,5,5,3,7,1,9,0,13,0,15,1,17,3,18,5,19,8,19,13,18,16,17,18,15,20,13,21,9,21]],P:[21,[4,21,4,0,-1,-1,4,21,13,21,16,20,17,19,18,17,18,14,17,12,16,11,13,10,4,10]],Q:[22,[9,21,7,20,5,18,4,16,3,13,3,8,4,5,5,3,7,1,9,0,13,0,15,1,17,3,18,5,19,8,19,13,18,16,17,18,15,20,13,21,9,21,-1,-1,12,4,18,-2]],R:[21,[4,21,4,0,-1,-1,4,21,13,21,16,20,17,19,18,17,18,15,17,13,16,12,13,11,4,11,-1,-1,11,11,18,0]],S:[20,[17,18,15,20,12,21,8,21,5,20,3,18,3,16,4,14,5,13,7,12,13,10,15,9,16,8,17,6,17,3,15,1,12,0,8,0,5,1,3,3]],T:[16,[8,21,8,0,-1,-1,1,21,15,21]],U:[22,[4,21,4,6,5,3,7,1,10,0,12,0,15,1,17,3,18,6,18,21]],V:[18,[1,21,9,0,-1,-1,17,21,9,0]],W:[24,[2,21,7,0,-1,-1,12,21,7,0,-1,-1,12,21,17,0,-1,-1,22,21,17,0]],X:[20,[3,21,17,0,-1,-1,17,21,3,0]],Y:[18,[1,21,9,11,9,0,-1,-1,17,21,9,11]],Z:[20,[17,21,3,0,-1,-1,3,21,17,21,-1,-1,3,0,17,0]],\"[\":[14,[4,25,4,-7,-1,-1,5,25,5,-7,-1,-1,4,25,11,25,-1,-1,4,-7,11,-7]],\"\\\\\":[14,[0,21,14,-3]],\"]\":[14,[9,25,9,-7,-1,-1,10,25,10,-7,-1,-1,3,25,10,25,-1,-1,3,-7,10,-7]],\"^\":[16,[6,15,8,18,10,15,-1,-1,3,12,8,17,13,12,-1,-1,8,17,8,0]],_:[16,[0,-2,16,-2]],\"`\":[10,[6,21,5,20,4,18,4,16,5,15,6,16,5,17]],a:[19,[15,14,15,0,-1,-1,15,11,13,13,11,14,8,14,6,13,4,11,3,8,3,6,4,3,6,1,8,0,11,0,13,1,15,3]],b:[19,[4,21,4,0,-1,-1,4,11,6,13,8,14,11,14,13,13,15,11,16,8,16,6,15,3,13,1,11,0,8,0,6,1,4,3]],c:[18,[15,11,13,13,11,14,8,14,6,13,4,11,3,8,3,6,4,3,6,1,8,0,11,0,13,1,15,3]],d:[19,[15,21,15,0,-1,-1,15,11,13,13,11,14,8,14,6,13,4,11,3,8,3,6,4,3,6,1,8,0,11,0,13,1,15,3]],e:[18,[3,8,15,8,15,10,14,12,13,13,11,14,8,14,6,13,4,11,3,8,3,6,4,3,6,1,8,0,11,0,13,1,15,3]],f:[12,[10,21,8,21,6,20,5,17,5,0,-1,-1,2,14,9,14]],g:[19,[15,14,15,-2,14,-5,13,-6,11,-7,8,-7,6,-6,-1,-1,15,11,13,13,11,14,8,14,6,13,4,11,3,8,3,6,4,3,6,1,8,0,11,0,13,1,15,3]],h:[19,[4,21,4,0,-1,-1,4,10,7,13,9,14,12,14,14,13,15,10,15,0]],i:[8,[3,21,4,20,5,21,4,22,3,21,-1,-1,4,14,4,0]],j:[10,[5,21,6,20,7,21,6,22,5,21,-1,-1,6,14,6,-3,5,-6,3,-7,1,-7]],k:[17,[4,21,4,0,-1,-1,14,14,4,4,-1,-1,8,8,15,0]],l:[8,[4,21,4,0]],m:[30,[4,14,4,0,-1,-1,4,10,7,13,9,14,12,14,14,13,15,10,15,0,-1,-1,15,10,18,13,20,14,23,14,25,13,26,10,26,0]],n:[19,[4,14,4,0,-1,-1,4,10,7,13,9,14,12,14,14,13,15,10,15,0]],o:[19,[8,14,6,13,4,11,3,8,3,6,4,3,6,1,8,0,11,0,13,1,15,3,16,6,16,8,15,11,13,13,11,14,8,14]],p:[19,[4,14,4,-7,-1,-1,4,11,6,13,8,14,11,14,13,13,15,11,16,8,16,6,15,3,13,1,11,0,8,0,6,1,4,3]],q:[19,[15,14,15,-7,-1,-1,15,11,13,13,11,14,8,14,6,13,4,11,3,8,3,6,4,3,6,1,8,0,11,0,13,1,15,3]],r:[13,[4,14,4,0,-1,-1,4,8,5,11,7,13,9,14,12,14]],s:[17,[14,11,13,13,10,14,7,14,4,13,3,11,4,9,6,8,11,7,13,6,14,4,14,3,13,1,10,0,7,0,4,1,3,3]],t:[12,[5,21,5,4,6,1,8,0,10,0,-1,-1,2,14,9,14]],u:[19,[4,14,4,4,5,1,7,0,10,0,12,1,15,4,-1,-1,15,14,15,0]],v:[16,[2,14,8,0,-1,-1,14,14,8,0]],w:[22,[3,14,7,0,-1,-1,11,14,7,0,-1,-1,11,14,15,0,-1,-1,19,14,15,0]],x:[17,[3,14,14,0,-1,-1,14,14,3,0]],y:[16,[2,14,8,0,-1,-1,14,14,8,0,6,-4,4,-6,2,-7,1,-7]],z:[17,[14,14,3,0,-1,-1,3,14,14,14,-1,-1,3,0,14,0]],\"{\":[14,[9,25,7,24,6,23,5,21,5,19,6,17,7,16,8,14,8,12,6,10,-1,-1,7,24,6,22,6,20,7,18,8,17,9,15,9,13,8,11,4,9,8,7,9,5,9,3,8,1,7,0,6,-2,6,-4,7,-6,-1,-1,6,8,8,6,8,4,7,2,6,1,5,-1,5,-3,6,-5,7,-6,9,-7]],\"|\":[8,[4,25,4,-7]],\"}\":[14,[5,25,7,24,8,23,9,21,9,19,8,17,7,16,6,14,6,12,8,10,-1,-1,7,24,8,22,8,20,7,18,6,17,5,15,5,13,6,11,10,9,6,7,5,5,5,3,6,1,7,0,8,-2,8,-4,7,-6,-1,-1,8,8,6,6,6,4,7,2,8,1,9,-1,9,-3,8,-5,7,-6,5,-7]],\"~\":[24,[3,6,3,8,4,11,6,12,8,12,10,11,14,8,16,7,18,7,20,8,21,10,-1,-1,3,8,4,10,6,11,8,11,10,10,14,7,16,6,18,6,20,7,21,10,21,12]]},an={symbol:function(t,e,r,n,a){if(\"translucent\"===t.renderPass){var i=At.disabled,o=t.colorModeForRenderPass();0!==r.paint.get(\"icon-opacity\").constantOr(1)&&Zr(t,e,r,n,!1,r.paint.get(\"icon-translate\"),r.paint.get(\"icon-translate-anchor\"),r.layout.get(\"icon-rotation-alignment\"),r.layout.get(\"icon-pitch-alignment\"),r.layout.get(\"icon-keep-upright\"),i,o,a),0!==r.paint.get(\"text-opacity\").constantOr(1)&&Zr(t,e,r,n,!0,r.paint.get(\"text-translate\"),r.paint.get(\"text-translate-anchor\"),r.layout.get(\"text-rotation-alignment\"),r.layout.get(\"text-pitch-alignment\"),r.layout.get(\"text-keep-upright\"),i,o,a),e.map.showCollisionBoxes&&function(t,e,r,n){Hr(t,e,r,n,!1),Hr(t,e,r,n,!0)}(t,e,r,n)}},circle:function(e,r,n,a){if(\"translucent\"===e.renderPass){var i=n.paint.get(\"circle-opacity\"),o=n.paint.get(\"circle-stroke-width\"),s=n.paint.get(\"circle-stroke-opacity\"),l=void 0!==n.layout.get(\"circle-sort-key\").constantOr(1);if(0!==i.constantOr(1)||0!==o.constantOr(1)&&0!==s.constantOr(1)){for(var c=e.context,u=c.gl,h=e.depthModeForSublayer(0,Mt.ReadOnly),f=At.disabled,p=e.colorModeForRenderPass(),d=[],g=0;g<a.length;g++){var v=a[g],m=r.getTile(v),y=m.getBucket(n);if(y){var x=y.programConfigurations.get(n.id),b={programConfiguration:x,program:e.useProgram(\"circle\",x),layoutVertexBuffer:y.layoutVertexBuffer,indexBuffer:y.indexBuffer,uniformValues:br(e,v,m,n)};if(l)for(var _=0,w=y.segments.get();_<w.length;_+=1){var k=w[_];d.push({segments:new t.SegmentVector([k]),sortKey:k.sortKey,state:b})}else d.push({segments:y.segments,sortKey:0,state:b})}}l&&d.sort(function(t,e){return t.sortKey-e.sortKey});for(var T=0,M=d;T<M.length;T+=1){var A=M[T],S=A.state,E=S.programConfiguration,L=S.program,C=S.layoutVertexBuffer,P=S.indexBuffer,O=S.uniformValues,z=A.segments;L.draw(c,u.TRIANGLES,h,f,p,Et.disabled,O,n.id,C,P,z,n.paint,e.transform.zoom,E)}}}},heatmap:function(e,r,n,a){if(0!==n.paint.get(\"heatmap-opacity\"))if(\"offscreen\"===e.renderPass){var i=e.context,o=i.gl,s=e.depthModeForSublayer(0,Mt.ReadOnly),l=At.disabled,c=new St([o.ONE,o.ONE],t.Color.transparent,[!0,!0,!0,!0]);!function(t,e,r){var n=t.gl;t.activeTexture.set(n.TEXTURE1),t.viewport.set([0,0,e.width/4,e.height/4]);var a=r.heatmapFbo;if(a)n.bindTexture(n.TEXTURE_2D,a.colorAttachment.get()),t.bindFramebuffer.set(a.framebuffer);else{var i=n.createTexture();n.bindTexture(n.TEXTURE_2D,i),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,n.LINEAR),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,n.LINEAR),a=r.heatmapFbo=t.createFramebuffer(e.width/4,e.height/4),function t(e,r,n,a){var i=e.gl;i.texImage2D(i.TEXTURE_2D,0,i.RGBA,r.width/4,r.height/4,0,i.RGBA,e.extTextureHalfFloat?e.extTextureHalfFloat.HALF_FLOAT_OES:i.UNSIGNED_BYTE,null),a.colorAttachment.set(n),e.extTextureHalfFloat&&i.checkFramebufferStatus(i.FRAMEBUFFER)!==i.FRAMEBUFFER_COMPLETE&&(e.extTextureHalfFloat=null,a.colorAttachment.setDirty(),t(e,r,n,a))}(t,e,i,a)}}(i,e,n),i.clear({color:t.Color.transparent});for(var u=0;u<a.length;u++){var h=a[u];if(!r.hasRenderableParent(h)){var f=r.getTile(h),p=f.getBucket(n);if(p){var d=p.programConfigurations.get(n.id),g=e.useProgram(\"heatmap\",d),v=e.transform.zoom;g.draw(i,o.TRIANGLES,s,l,c,Et.disabled,Mr(h.posMatrix,f,v,n.paint.get(\"heatmap-intensity\")),n.id,p.layoutVertexBuffer,p.indexBuffer,p.segments,n.paint,e.transform.zoom,d)}}}i.viewport.set([0,0,e.width,e.height])}else\"translucent\"===e.renderPass&&(e.context.setColorMode(e.colorModeForRenderPass()),function(e,r){var n=e.context,a=n.gl,i=r.heatmapFbo;if(i){n.activeTexture.set(a.TEXTURE0),a.bindTexture(a.TEXTURE_2D,i.colorAttachment.get()),n.activeTexture.set(a.TEXTURE1);var o=r.colorRampTexture;o||(o=r.colorRampTexture=new t.Texture(n,r.colorRamp,a.RGBA)),o.bind(a.LINEAR,a.CLAMP_TO_EDGE),e.useProgram(\"heatmapTexture\").draw(n,a.TRIANGLES,Mt.disabled,At.disabled,e.colorModeForRenderPass(),Et.disabled,function(e,r,n,a){var i=t.create();t.ortho(i,0,e.width,e.height,0,0,1);var o=e.context.gl;return{u_matrix:i,u_world:[o.drawingBufferWidth,o.drawingBufferHeight],u_image:n,u_color_ramp:a,u_opacity:r.paint.get(\"heatmap-opacity\")}}(e,r,0,1),r.id,e.viewportBuffer,e.quadTriangleIndexBuffer,e.viewportSegments,r.paint,e.transform.zoom)}}(e,n))},line:function(e,r,n,a){if(\"translucent\"===e.renderPass){var i=n.paint.get(\"line-opacity\"),o=n.paint.get(\"line-width\");if(0!==i.constantOr(1)&&0!==o.constantOr(1)){var s=e.depthModeForSublayer(0,Mt.ReadOnly),l=e.colorModeForRenderPass(),c=n.paint.get(\"line-dasharray\"),u=n.paint.get(\"line-pattern\"),h=u.constantOr(1),f=n.paint.get(\"line-gradient\"),p=n.getCrossfadeParameters(),d=c?\"lineSDF\":h?\"linePattern\":f?\"lineGradient\":\"line\",g=e.context,v=g.gl,m=!0;if(f){g.activeTexture.set(v.TEXTURE0);var y=n.gradientTexture;if(!n.gradient)return;y||(y=n.gradientTexture=new t.Texture(g,n.gradient,v.RGBA)),y.bind(v.LINEAR,v.CLAMP_TO_EDGE)}for(var x=0,b=a;x<b.length;x+=1){var _=b[x],w=r.getTile(_);if(!h||w.patternsLoaded()){var k=w.getBucket(n);if(k){var T=k.programConfigurations.get(n.id),M=e.context.program.get(),A=e.useProgram(d,T),S=m||A.program!==M,E=u.constantOr(null);if(E&&w.imageAtlas){var L=w.imageAtlas.patternPositions[E.to],C=w.imageAtlas.patternPositions[E.from];L&&C&&T.setConstantPatternPositions(L,C)}var P=c?Or(e,w,n,c,p):h?Pr(e,w,n,p):f?Cr(e,w,n):Lr(e,w,n);c&&(S||e.lineAtlas.dirty)?(g.activeTexture.set(v.TEXTURE0),e.lineAtlas.bind(g)):h&&(g.activeTexture.set(v.TEXTURE0),w.imageAtlasTexture.bind(v.LINEAR,v.CLAMP_TO_EDGE),T.updatePatternPaintBuffers(p)),A.draw(g,v.TRIANGLES,s,e.stencilModeForClipping(_),l,Et.disabled,P,n.id,k.layoutVertexBuffer,k.indexBuffer,k.segments,n.paint,e.transform.zoom,T),m=!1}}}}}},fill:function(e,r,n,a){var i=n.paint.get(\"fill-color\"),o=n.paint.get(\"fill-opacity\");if(0!==o.constantOr(1)){var s=e.colorModeForRenderPass(),l=n.paint.get(\"fill-pattern\"),c=e.opaquePassEnabledForLayer()&&!l.constantOr(1)&&1===i.constantOr(t.Color.transparent).a&&1===o.constantOr(0)?\"opaque\":\"translucent\";if(e.renderPass===c){var u=e.depthModeForSublayer(1,\"opaque\"===e.renderPass?Mt.ReadWrite:Mt.ReadOnly);Kr(e,r,n,a,u,s,!1)}if(\"translucent\"===e.renderPass&&n.paint.get(\"fill-antialias\")){var h=e.depthModeForSublayer(n.getPaintProperty(\"fill-outline-color\")?2:0,Mt.ReadOnly);Kr(e,r,n,a,h,s,!0)}}},\"fill-extrusion\":function(t,e,r,n){var a=r.paint.get(\"fill-extrusion-opacity\");if(0!==a&&\"translucent\"===t.renderPass){var i=new Mt(t.context.gl.LEQUAL,Mt.ReadWrite,t.depthRangeFor3D);if(1!==a||r.paint.get(\"fill-extrusion-pattern\").constantOr(1))Qr(t,e,r,n,i,At.disabled,St.disabled),Qr(t,e,r,n,i,t.stencilModeFor3D(),t.colorModeForRenderPass());else{var o=t.colorModeForRenderPass();Qr(t,e,r,n,i,At.disabled,o)}}},hillshade:function(t,e,r,n){if(\"offscreen\"===t.renderPass||\"translucent\"===t.renderPass){for(var a=t.context,i=e.getSource().maxzoom,o=t.depthModeForSublayer(0,Mt.ReadOnly),s=At.disabled,l=t.colorModeForRenderPass(),c=0,u=n;c<u.length;c+=1){var h=u[c],f=e.getTile(h);f.needsHillshadePrepare&&\"offscreen\"===t.renderPass?tn(t,f,r,i,o,s,l):\"translucent\"===t.renderPass&&$r(t,f,r,o,s,l)}a.viewport.set([0,0,t.width,t.height])}},raster:function(t,e,r,n){if(\"translucent\"===t.renderPass&&0!==r.paint.get(\"raster-opacity\"))for(var a=t.context,i=a.gl,o=e.getSource(),s=t.useProgram(\"raster\"),l=At.disabled,c=t.colorModeForRenderPass(),u=n.length&&n[0].overscaledZ,h=!t.options.moving,f=0,p=n;f<p.length;f+=1){var d=p[f],g=t.depthModeForSublayer(d.overscaledZ-u,1===r.paint.get(\"raster-opacity\")?Mt.ReadWrite:Mt.ReadOnly,i.LESS),v=e.getTile(d),m=t.transform.calculatePosMatrix(d.toUnwrapped(),h);v.registerFadeDuration(r.paint.get(\"raster-fade-duration\"));var y=e.findLoadedParent(d,0),x=en(v,y,e,r,t.transform),b=void 0,_=void 0,w=\"nearest\"===r.paint.get(\"raster-resampling\")?i.NEAREST:i.LINEAR;a.activeTexture.set(i.TEXTURE0),v.texture.bind(w,i.CLAMP_TO_EDGE,i.LINEAR_MIPMAP_NEAREST),a.activeTexture.set(i.TEXTURE1),y?(y.texture.bind(w,i.CLAMP_TO_EDGE,i.LINEAR_MIPMAP_NEAREST),b=Math.pow(2,y.tileID.overscaledZ-v.tileID.overscaledZ),_=[v.tileID.canonical.x*b%1,v.tileID.canonical.y*b%1]):v.texture.bind(w,i.CLAMP_TO_EDGE,i.LINEAR_MIPMAP_NEAREST);var k=Dr(m,_||[0,0],b||1,x,r);o instanceof P?s.draw(a,i.TRIANGLES,g,l,c,Et.disabled,k,r.id,o.boundsBuffer,t.quadTriangleIndexBuffer,o.boundsSegments):v.maskedBoundsBuffer&&v.maskedIndexBuffer&&v.segments?s.draw(a,i.TRIANGLES,g,l,c,Et.disabled,k,r.id,v.maskedBoundsBuffer,v.maskedIndexBuffer,v.segments,r.paint,t.transform.zoom):s.draw(a,i.TRIANGLES,g,l,c,Et.disabled,k,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}},background:function(t,e,r){var n=r.paint.get(\"background-color\"),a=r.paint.get(\"background-opacity\");if(0!==a){var i=t.context,o=i.gl,s=t.transform,l=s.tileSize,c=r.paint.get(\"background-pattern\");if(!t.isPatternMissing(c)){var u=!c&&1===n.a&&1===a&&t.opaquePassEnabledForLayer()?\"opaque\":\"translucent\";if(t.renderPass===u){var h=At.disabled,f=t.depthModeForSublayer(0,\"opaque\"===u?Mt.ReadWrite:Mt.ReadOnly),p=t.colorModeForRenderPass(),d=t.useProgram(c?\"backgroundPattern\":\"background\"),g=s.coveringTiles({tileSize:l});c&&(i.activeTexture.set(o.TEXTURE0),t.imageManager.bind(t.context));for(var v=r.getCrossfadeParameters(),m=0,y=g;m<y.length;m+=1){var x=y[m],b=t.transform.calculatePosMatrix(x.toUnwrapped()),_=c?jr(b,a,t,c,{tileID:x,tileSize:l},v):Nr(b,a,n);d.draw(i,o.TRIANGLES,f,h,p,Et.disabled,_,r.id,t.tileExtentBuffer,t.quadTriangleIndexBuffer,t.tileExtentSegments)}}}}},debug:function(t,e,r){for(var n=0;n<r.length;n++)rn(t,e,r[n])},custom:function(t,e,r){var n=t.context,a=r.implementation;if(\"offscreen\"===t.renderPass){var i=a.prerender;i&&(t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),i.call(a,n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState())}else if(\"translucent\"===t.renderPass){t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),n.setStencilMode(At.disabled);var o=\"3d\"===a.renderingMode?new Mt(t.context.gl.LEQUAL,Mt.ReadWrite,t.depthRangeFor3D):t.depthModeForSublayer(0,Mt.ReadOnly);n.setDepthMode(o),a.render(n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState(),n.bindFramebuffer.set(null)}}},on=function(e,r){this.context=new Lt(e),this.transform=r,this._tileTextures={},this.setup(),this.numSublayers=Ct.maxUnderzooming+Ct.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.depthRboNeedsClear=!0,this.emptyProgramConfiguration=new t.ProgramConfiguration,this.crossTileSymbolIndex=new Oe};function sn(t,e){if(t.y>e.y){var r=t;t=e,e=r}return{x0:t.x,y0:t.y,x1:e.x,y1:e.y,dx:e.x-t.x,dy:e.y-t.y}}function ln(t,e,r,n,a){var i=Math.max(r,Math.floor(e.y0)),o=Math.min(n,Math.ceil(e.y1));if(t.x0===e.x0&&t.y0===e.y0?t.x0+e.dy/t.dy*t.dx<e.x1:t.x1-e.dy/t.dy*t.dx<e.x0){var s=t;t=e,e=s}for(var l=t.dx/t.dy,c=e.dx/e.dy,u=t.dx>0,h=e.dx<0,f=i;f<o;f++){var p=l*Math.max(0,Math.min(t.dy,f+u-t.y0))+t.x0,d=c*Math.max(0,Math.min(e.dy,f+h-e.y0))+e.x0;a(Math.floor(d),Math.ceil(p),f)}}function cn(t,e,r,n,a,i){var o,s=sn(t,e),l=sn(e,r),c=sn(r,t);s.dy>l.dy&&(o=s,s=l,l=o),s.dy>c.dy&&(o=s,s=c,c=o),l.dy>c.dy&&(o=l,l=c,c=o),s.dy&&ln(c,s,n,a,i),l.dy&&ln(c,l,n,a,i)}on.prototype.resize=function(e,r){var n=this.context.gl;if(this.width=e*t.browser.devicePixelRatio,this.height=r*t.browser.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var a=0,i=this.style._order;a<i.length;a+=1){var o=i[a];this.style._layers[o].resize()}this.depthRbo&&(n.deleteRenderbuffer(this.depthRbo),this.depthRbo=null)},on.prototype.setup=function(){var e=this.context,r=new t.StructArrayLayout2i4;r.emplaceBack(0,0),r.emplaceBack(t.EXTENT,0),r.emplaceBack(0,t.EXTENT),r.emplaceBack(t.EXTENT,t.EXTENT),this.tileExtentBuffer=e.createVertexBuffer(r,Fe.members),this.tileExtentSegments=t.SegmentVector.simpleSegment(0,0,4,2);var n=new t.StructArrayLayout2i4;n.emplaceBack(0,0),n.emplaceBack(t.EXTENT,0),n.emplaceBack(0,t.EXTENT),n.emplaceBack(t.EXTENT,t.EXTENT),this.debugBuffer=e.createVertexBuffer(n,Fe.members),this.debugSegments=t.SegmentVector.simpleSegment(0,0,4,5);var a=new t.StructArrayLayout4i8;a.emplaceBack(0,0,0,0),a.emplaceBack(t.EXTENT,0,t.EXTENT,0),a.emplaceBack(0,t.EXTENT,0,t.EXTENT),a.emplaceBack(t.EXTENT,t.EXTENT,t.EXTENT,t.EXTENT),this.rasterBoundsBuffer=e.createVertexBuffer(a,t.rasterBoundsAttributes.members),this.rasterBoundsSegments=t.SegmentVector.simpleSegment(0,0,4,2);var i=new t.StructArrayLayout2i4;i.emplaceBack(0,0),i.emplaceBack(1,0),i.emplaceBack(0,1),i.emplaceBack(1,1),this.viewportBuffer=e.createVertexBuffer(i,Fe.members),this.viewportSegments=t.SegmentVector.simpleSegment(0,0,4,2);var o=new t.StructArrayLayout1ui2;o.emplaceBack(0),o.emplaceBack(1),o.emplaceBack(3),o.emplaceBack(2),o.emplaceBack(0),this.tileBorderIndexBuffer=e.createIndexBuffer(o);var s=new t.StructArrayLayout3ui6;s.emplaceBack(0,1,2),s.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=e.createIndexBuffer(s);var l=this.context.gl;this.stencilClearMode=new At({func:l.ALWAYS,mask:0},0,255,l.ZERO,l.ZERO,l.ZERO)},on.prototype.clearStencil=function(){var e=this.context,r=e.gl;this.nextStencilID=1,this.currentStencilSource=void 0;var n=t.create();t.ortho(n,0,this.width,this.height,0,0,1),t.scale(n,n,[r.drawingBufferWidth,r.drawingBufferHeight,0]),this.useProgram(\"clippingMask\").draw(e,r.TRIANGLES,Mt.disabled,this.stencilClearMode,St.disabled,Et.disabled,Tr(n),\"$clipping\",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)},on.prototype._renderTileClippingMasks=function(t,e){if(this.currentStencilSource!==t.source&&t.isTileClipped()&&e&&e.length){this.currentStencilSource=t.source;var r=this.context,n=r.gl;this.nextStencilID+e.length>256&&this.clearStencil(),r.setColorMode(St.disabled),r.setDepthMode(Mt.disabled);var a=this.useProgram(\"clippingMask\");this._tileClippingMaskIDs={};for(var i=0,o=e;i<o.length;i+=1){var s=o[i],l=this._tileClippingMaskIDs[s.key]=this.nextStencilID++;a.draw(r,n.TRIANGLES,Mt.disabled,new At({func:n.ALWAYS,mask:0},l,255,n.KEEP,n.KEEP,n.REPLACE),St.disabled,Et.disabled,Tr(s.posMatrix),\"$clipping\",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}},on.prototype.stencilModeFor3D=function(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new At({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},on.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new At({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},on.prototype.colorModeForRenderPass=function(){var e=this.context.gl;return this._showOverdrawInspector?new St([e.CONSTANT_COLOR,e.ONE],new t.Color(1/8,1/8,1/8,0),[!0,!0,!0,!0]):\"opaque\"===this.renderPass?St.unblended:St.alphaBlended},on.prototype.depthModeForSublayer=function(t,e,r){if(!this.opaquePassEnabledForLayer())return Mt.disabled;var n=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon;return new Mt(r||this.context.gl.LEQUAL,e,[n,n])},on.prototype.opaquePassEnabledForLayer=function(){return this.currentLayer<this.opaquePassCutoff},on.prototype.render=function(e,r){this.style=e,this.options=r,this.lineAtlas=e.lineAtlas,this.imageManager=e.imageManager,this.glyphManager=e.glyphManager,this.symbolFadeChange=e.placement.symbolFadeChange(t.browser.now()),this.imageManager.beginFrame();var n=this.style._order,a=this.style.sourceCaches;for(var i in a){var o=a[i];o.used&&o.prepare(this.context)}var s={},l={},c={};for(var u in a){var h=a[u];s[u]=h.getVisibleCoordinates(),l[u]=s[u].slice().reverse(),c[u]=h.getVisibleCoordinates(!0).reverse()}for(var f in a){var p=a[f],d=p.getSource();if(\"raster\"===d.type||\"raster-dem\"===d.type){for(var g=[],v=0,m=s[f];v<m.length;v+=1){var y=m[v];g.push(p.getTile(y))}Ur(g,this.context)}}this.opaquePassCutoff=1/0;for(var x=0;x<n.length;x++){var b=n[x];if(this.style._layers[b].is3D()){this.opaquePassCutoff=x;break}}this.renderPass=\"offscreen\",this.depthRboNeedsClear=!0;for(var _=0,w=n;_<w.length;_+=1){var k=w[_],T=this.style._layers[k];if(T.hasOffscreenPass()&&!T.isHidden(this.transform.zoom)){var M=l[T.source];(\"custom\"===T.type||M.length)&&this.renderLayer(this,a[T.source],T,M)}}for(this.context.bindFramebuffer.set(null),this.context.clear({color:r.showOverdrawInspector?t.Color.black:t.Color.transparent,depth:1}),this.clearStencil(),this._showOverdrawInspector=r.showOverdrawInspector,this.depthRangeFor3D=[0,1-(e._order.length+2)*this.numSublayers*this.depthEpsilon],this.renderPass=\"opaque\",this.currentLayer=n.length-1;this.currentLayer>=0;this.currentLayer--){var A=this.style._layers[n[this.currentLayer]],S=a[A.source],E=s[A.source];this._renderTileClippingMasks(A,E),this.renderLayer(this,S,A,E)}for(this.renderPass=\"translucent\",this.currentLayer=0;this.currentLayer<n.length;this.currentLayer++){var L=this.style._layers[n[this.currentLayer]],C=a[L.source],P=(\"symbol\"===L.type?c:l)[L.source];this._renderTileClippingMasks(L,s[L.source]),this.renderLayer(this,C,L,P)}if(this.options.showTileBoundaries)for(var O in a){an.debug(this,a[O],s[O]);break}this.context.setDefault()},on.prototype.setupOffscreenDepthRenderbuffer=function(){var t=this.context;this.depthRbo||(this.depthRbo=t.createRenderbuffer(t.gl.DEPTH_COMPONENT16,this.width,this.height))},on.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||(\"background\"===r.type||\"custom\"===r.type||n.length)&&(this.id=r.id,an[r.type](t,e,r,n,this.style.placement.variableOffsets))},on.prototype.translatePosMatrix=function(e,r,n,a,i){if(!n[0]&&!n[1])return e;var o=i?\"map\"===a?this.transform.angle:0:\"viewport\"===a?-this.transform.angle:0;if(o){var s=Math.sin(o),l=Math.cos(o);n=[n[0]*l-n[1]*s,n[0]*s+n[1]*l]}var c=[i?n[0]:ce(r,n[0],this.transform.zoom),i?n[1]:ce(r,n[1],this.transform.zoom),0],u=new Float32Array(16);return t.translate(u,e,c),u},on.prototype.saveTileTexture=function(t){var e=this._tileTextures[t.size[0]];e?e.push(t):this._tileTextures[t.size[0]]=[t]},on.prototype.getTileTexture=function(t){var e=this._tileTextures[t];return e&&e.length>0?e.pop():null},on.prototype.isPatternMissing=function(t){if(!t)return!1;var e=this.imageManager.getPattern(t.from),r=this.imageManager.getPattern(t.to);return!e||!r},on.prototype.useProgram=function(t,e){void 0===e&&(e=this.emptyProgramConfiguration),this.cache=this.cache||{};var r=\"\"+t+(e.cacheKey||\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\");return this.cache[r]||(this.cache[r]=new fr(this.context,ur[t],e,Vr[t],this._showOverdrawInspector)),this.cache[r]},on.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},on.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)};var un=function(e,r,n){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===n||n,this._minZoom=e||0,this._maxZoom=r||22,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._posMatrixCache={},this._alignedPosMatrixCache={}},hn={minZoom:{configurable:!0},maxZoom:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerPoint:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};un.prototype.clone=function(){var t=new un(this._minZoom,this._maxZoom,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._calcMatrices(),t},hn.minZoom.get=function(){return this._minZoom},hn.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},hn.maxZoom.get=function(){return this._maxZoom},hn.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},hn.renderWorldCopies.get=function(){return this._renderWorldCopies},hn.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},hn.worldSize.get=function(){return this.tileSize*this.scale},hn.centerPoint.get=function(){return this.size._div(2)},hn.size.get=function(){return new t.Point(this.width,this.height)},hn.bearing.get=function(){return-this.angle/Math.PI*180},hn.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},hn.pitch.get=function(){return this._pitch/Math.PI*180},hn.pitch.set=function(e){var r=t.clamp(e,0,60)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},hn.fov.get=function(){return this._fov/Math.PI*180},hn.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},hn.zoom.get=function(){return this._zoom},hn.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},hn.center.get=function(){return this._center},hn.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},un.prototype.coveringZoomLevel=function(t){return(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize))},un.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),a=this.pointCoordinate(new t.Point(this.width,0)),i=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,a.x,i.x,o.x)),l=Math.floor(Math.max(n.x,a.x,i.x,o.x)),c=s-1;c<=l+1;c++)0!==c&&r.push(new t.UnwrappedTileID(c,e));return r},un.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&r<e.minzoom)return[];void 0!==e.maxzoom&&r>e.maxzoom&&(r=e.maxzoom);var a=t.MercatorCoordinate.fromLngLat(this.center),i=Math.pow(2,r),o=new t.Point(i*a.x-.5,i*a.y-.5);return function(e,r,n,a){void 0===a&&(a=!0);var i=1<<e,o={};function s(r,s,l){var c,u,h,f;if(l>=0&&l<=i)for(c=r;c<s;c++)u=Math.floor(c/i),h=(c%i+i)%i,0!==u&&!0!==a||(f=new t.OverscaledTileID(n,u,e,h,l),o[f.key]=f)}var l=r.map(function(e){return new t.Point(e.x,e.y)._mult(i)});return cn(l[0],l[1],l[2],0,i,s),cn(l[2],l[3],l[0],0,i,s),Object.keys(o).map(function(t){return o[t]})}(r,[this.pointCoordinate(new t.Point(0,0)),this.pointCoordinate(new t.Point(this.width,0)),this.pointCoordinate(new t.Point(this.width,this.height)),this.pointCoordinate(new t.Point(0,this.height))],e.reparseOverscaled?n:r,this._renderWorldCopies).sort(function(t,e){return o.dist(t.canonical)-o.dist(e.canonical)})},un.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},hn.unmodified.get=function(){return this._unmodified},un.prototype.zoomScale=function(t){return Math.pow(2,t)},un.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},un.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},un.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},hn.point.get=function(){return this.project(this.center)},un.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),a=this.pointCoordinate(this.centerPoint),i=this.locationCoordinate(e),o=new t.MercatorCoordinate(i.x-(n.x-a.x),i.y-(n.y-a.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},un.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},un.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},un.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},un.prototype.coordinateLocation=function(t){return t.toLngLat()},un.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var a=r[3],i=n[3],o=r[0]/a,s=n[0]/i,l=r[1]/a,c=n[1]/i,u=r[2]/a,h=n[2]/i,f=u===h?0:(0-u)/(h-u);return new t.MercatorCoordinate(t.number(o,s,f)/this.worldSize,t.number(l,c,f)/this.worldSize)},un.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},un.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},un.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},un.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},un.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,a=r?this._alignedPosMatrixCache:this._posMatrixCache;if(a[n])return a[n];var i=e.canonical,o=this.worldSize/this.zoomScale(i.z),s=i.x+Math.pow(2,i.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,i.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),a[n]=new Float32Array(l),a[n]},un.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},un.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,a,i=-90,o=90,s=-180,l=180,c=this.size,u=this._unmodified;if(this.latRange){var h=this.latRange;i=t.mercatorYfromLat(h[1])*this.worldSize,e=(o=t.mercatorYfromLat(h[0])*this.worldSize)-i<c.y?c.y/(o-i):0}if(this.lngRange){var f=this.lngRange;s=t.mercatorXfromLng(f[0])*this.worldSize,r=(l=t.mercatorXfromLng(f[1])*this.worldSize)-s<c.x?c.x/(l-s):0}var p=this.point,d=Math.max(r||0,e||0);if(d)return this.center=this.unproject(new t.Point(r?(l+s)/2:p.x,e?(o+i)/2:p.y)),this.zoom+=this.scaleZoom(d),this._unmodified=u,void(this._constraining=!1);if(this.latRange){var g=p.y,v=c.y/2;g-v<i&&(a=i+v),g+v>o&&(a=o-v)}if(this.lngRange){var m=p.x,y=c.x/2;m-y<s&&(n=s+y),m+y>l&&(n=l-y)}void 0===n&&void 0===a||(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==a?a:p.y))),this._unmodified=u,this._constraining=!1}},un.prototype._calcMatrices=function(){if(this.height){this.cameraToCenterDistance=.5/Math.tan(this._fov/2)*this.height;var e=this._fov/2,r=Math.PI/2+this._pitch,n=Math.sin(e)*this.cameraToCenterDistance/Math.sin(Math.PI-r-e),a=this.point,i=a.x,o=a.y,s=1.01*(Math.cos(Math.PI/2-this._pitch)*n+this.cameraToCenterDistance),l=this.height/50,c=new Float64Array(16);t.perspective(c,this._fov,this.width/this.height,l,s),t.scale(c,c,[1,-1,1]),t.translate(c,c,[0,0,-this.cameraToCenterDistance]),t.rotateX(c,c,this._pitch),t.rotateZ(c,c,this.angle),t.translate(c,c,[-i,-o,0]),this.mercatorMatrix=t.scale([],c,[this.worldSize,this.worldSize,this.worldSize]),t.scale(c,c,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=c;var u=this.width%2/2,h=this.height%2/2,f=Math.cos(this.angle),p=Math.sin(this.angle),d=i-Math.round(i)+f*u+p*h,g=o-Math.round(o)+f*h+p*u,v=new Float64Array(c);if(t.translate(v,v,[d>.5?d-1:d,g>.5?g-1:g,0]),this.alignedProjMatrix=v,c=t.create(),t.scale(c,c,[this.width/2,-this.height/2,1]),t.translate(c,c,[1,-1,0]),this.labelPlaneMatrix=c,c=t.create(),t.scale(c,c,[1,-1,1]),t.translate(c,c,[-1,-1,0]),t.scale(c,c,[2/this.width,2/this.height,1]),this.glCoordMatrix=c,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(c=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=c,this._posMatrixCache={},this._alignedPosMatrixCache={}}},un.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},un.prototype.getCameraPoint=function(){var e=this._pitch,r=Math.tan(e)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,r))},un.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,a=r.y,i=r.x,o=r.y,s=0,l=e;s<l.length;s+=1){var c=l[s];n=Math.min(n,c.x),a=Math.min(a,c.y),i=Math.max(i,c.x),o=Math.max(o,c.y)}return[new t.Point(n,a),new t.Point(i,a),new t.Point(i,o),new t.Point(n,o),new t.Point(n,a)]},Object.defineProperties(un.prototype,hn);var fn=function(){var e,r,n,a;t.bindAll([\"_onHashChange\",\"_updateHash\"],this),this._updateHash=(e=this._updateHashUnthrottled.bind(this),300,r=!1,n=null,a=function(){n=null,r&&(e(),n=setTimeout(a,300),r=!1)},function(){return r=!0,n||a(),n})};fn.prototype.addTo=function(e){return this._map=e,t.window.addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this},fn.prototype.remove=function(){return t.window.removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),clearTimeout(this._updateHash()),delete this._map,this},fn.prototype.getHashString=function(t){var e=this._map.getCenter(),r=Math.round(100*this._map.getZoom())/100,n=Math.ceil((r*Math.LN2+Math.log(512/360/.5))/Math.LN10),a=Math.pow(10,n),i=Math.round(e.lng*a)/a,o=Math.round(e.lat*a)/a,s=this._map.getBearing(),l=this._map.getPitch(),c=\"\";return c+=t?\"#/\"+i+\"/\"+o+\"/\"+r:\"#\"+r+\"/\"+o+\"/\"+i,(s||l)&&(c+=\"/\"+Math.round(10*s)/10),l&&(c+=\"/\"+Math.round(l)),c},fn.prototype._onHashChange=function(){var e=t.window.location.hash.replace(\"#\",\"\").split(\"/\");return e.length>=3&&(this._map.jumpTo({center:[+e[2],+e[1]],zoom:+e[0],bearing:+(e[3]||0),pitch:+(e[4]||0)}),!0)},fn.prototype._updateHashUnthrottled=function(){var e=this.getHashString();try{t.window.history.replaceState(t.window.history.state,\"\",e)}catch(t){}};var pn=function(e){function n(n,a,i,o){void 0===o&&(o={});var s=r.mousePos(a.getCanvasContainer(),i),l=a.unproject(s);e.call(this,n,t.extend({point:s,lngLat:l,originalEvent:i},o)),this._defaultPrevented=!1,this.target=a}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var a={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},a.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,a),n}(t.Event),dn=function(e){function n(n,a,i){var o=r.touchPos(a.getCanvasContainer(),i),s=o.map(function(t){return a.unproject(t)}),l=o.reduce(function(t,e,r,n){return t.add(e.div(n.length))},new t.Point(0,0)),c=a.unproject(l);e.call(this,n,{points:o,point:l,lngLats:s,lngLat:c,originalEvent:i}),this._defaultPrevented=!1}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var a={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},a.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,a),n}(t.Event),gn=function(t){function e(e,r,n){t.call(this,e,{originalEvent:n}),this._defaultPrevented=!1}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={defaultPrevented:{configurable:!0}};return e.prototype.preventDefault=function(){this._defaultPrevented=!0},r.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(e.prototype,r),e}(t.Event),vn=function(e){this._map=e,this._el=e.getCanvasContainer(),this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=1/450,t.bindAll([\"_onWheel\",\"_onTimeout\",\"_onScrollFrame\",\"_onScrollFinished\"],this)};vn.prototype.setZoomRate=function(t){this._defaultZoomRate=t},vn.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},vn.prototype.isEnabled=function(){return!!this._enabled},vn.prototype.isActive=function(){return!!this._active},vn.prototype.isZooming=function(){return!!this._zooming},vn.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&\"center\"===t.around)},vn.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},vn.prototype.onWheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),a=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%4.000244140625==0?this._type=\"wheel\":0!==r&&Math.abs(r)<4?this._type=\"trackpad\":a>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(a*r)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this.isActive()||this._start(e)),e.preventDefault()}},vn.prototype._onTimeout=function(t){this._type=\"wheel\",this._delta-=this._lastValue,this.isActive()||this._start(t)},vn.prototype._start=function(e){if(this._delta){this._frameId&&(this._map._cancelRenderFrame(this._frameId),this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0,this._map.fire(new t.Event(\"movestart\",{originalEvent:e})),this._map.fire(new t.Event(\"zoomstart\",{originalEvent:e}))),this._finishTimeout&&clearTimeout(this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=this._map._requestRenderFrame(this._onScrollFrame))}},vn.prototype._onScrollFrame=function(){var e=this;if(this._frameId=null,this.isActive()){var r=this._map.transform;if(0!==this._delta){var n=\"wheel\"===this._type&&Math.abs(this._delta)>4.000244140625?this._wheelZoomRate:this._defaultZoomRate,a=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==a&&(a=1/a);var i=\"number\"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(i*a))),\"wheel\"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o=\"number\"==typeof this._targetZoom?this._targetZoom:r.zoom,s=this._startZoom,l=this._easing,c=!1;if(\"wheel\"===this._type&&s&&l){var u=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),h=l(u);r.zoom=t.number(s,o,h),u<1?this._frameId||(this._frameId=this._map._requestRenderFrame(this._onScrollFrame)):c=!0}else r.zoom=o,c=!0;r.setLocationAtPoint(this._around,this._aroundPoint),this._map.fire(new t.Event(\"move\",{originalEvent:this._lastWheelEvent})),this._map.fire(new t.Event(\"zoom\",{originalEvent:this._lastWheelEvent})),c&&(this._active=!1,this._finishTimeout=setTimeout(function(){e._zooming=!1,e._map.fire(new t.Event(\"zoomend\",{originalEvent:e._lastWheelEvent})),e._map.fire(new t.Event(\"moveend\",{originalEvent:e._lastWheelEvent})),delete e._targetZoom},200))}},vn.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,a=(t.browser.now()-n.start)/n.duration,i=n.easing(a+.01)-n.easing(a),o=.27/Math.sqrt(i*i+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r};var mn=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._container=e.getContainer(),this._clickTolerance=r.clickTolerance||1,t.bindAll([\"_onMouseMove\",\"_onMouseUp\",\"_onKeyDown\"],this)};mn.prototype.isEnabled=function(){return!!this._enabled},mn.prototype.isActive=function(){return!!this._active},mn.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},mn.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},mn.prototype.onMouseDown=function(e){this.isEnabled()&&e.shiftKey&&0===e.button&&(t.window.document.addEventListener(\"mousemove\",this._onMouseMove,!1),t.window.document.addEventListener(\"keydown\",this._onKeyDown,!1),t.window.document.addEventListener(\"mouseup\",this._onMouseUp,!1),r.disableDrag(),this._startPos=this._lastPos=r.mousePos(this._el,e),this._active=!0)},mn.prototype._onMouseMove=function(t){var e=r.mousePos(this._el,t);if(!(this._lastPos.equals(e)||!this._box&&e.dist(this._startPos)<this._clickTolerance)){var n=this._startPos;this._lastPos=e,this._box||(this._box=r.create(\"div\",\"mapboxgl-boxzoom\",this._container),this._container.classList.add(\"mapboxgl-crosshair\"),this._fireEvent(\"boxzoomstart\",t));var a=Math.min(n.x,e.x),i=Math.max(n.x,e.x),o=Math.min(n.y,e.y),s=Math.max(n.y,e.y);r.setTransform(this._box,\"translate(\"+a+\"px,\"+o+\"px)\"),this._box.style.width=i-a+\"px\",this._box.style.height=s-o+\"px\"}},mn.prototype._onMouseUp=function(e){if(0===e.button){var n=this._startPos,a=r.mousePos(this._el,e);this._finish(),r.suppressClick(),n.x===a.x&&n.y===a.y?this._fireEvent(\"boxzoomcancel\",e):this._map.fitScreenCoordinates(n,a,this._map.getBearing(),{linear:!0}).fire(new t.Event(\"boxzoomend\",{originalEvent:e}))}},mn.prototype._onKeyDown=function(t){27===t.keyCode&&(this._finish(),this._fireEvent(\"boxzoomcancel\",t))},mn.prototype._finish=function(){this._active=!1,t.window.document.removeEventListener(\"mousemove\",this._onMouseMove,!1),t.window.document.removeEventListener(\"keydown\",this._onKeyDown,!1),t.window.document.removeEventListener(\"mouseup\",this._onMouseUp,!1),this._container.classList.remove(\"mapboxgl-crosshair\"),this._box&&(r.remove(this._box),this._box=null),r.enableDrag(),delete this._startPos,delete this._lastPos},mn.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,{originalEvent:r}))};var yn=t.bezier(0,0,.25,1),xn=function(e,r){this._map=e,this._el=r.element||e.getCanvasContainer(),this._state=\"disabled\",this._button=r.button||\"right\",this._bearingSnap=r.bearingSnap||0,this._pitchWithRotate=!1!==r.pitchWithRotate,t.bindAll([\"onMouseDown\",\"_onMouseMove\",\"_onMouseUp\",\"_onBlur\",\"_onDragFrame\"],this)};xn.prototype.isEnabled=function(){return\"disabled\"!==this._state},xn.prototype.isActive=function(){return\"active\"===this._state},xn.prototype.enable=function(){this.isEnabled()||(this._state=\"enabled\")},xn.prototype.disable=function(){if(this.isEnabled())switch(this._state){case\"active\":this._state=\"disabled\",this._unbind(),this._deactivate(),this._fireEvent(\"rotateend\"),this._pitchWithRotate&&this._fireEvent(\"pitchend\"),this._fireEvent(\"moveend\");break;case\"pending\":this._state=\"disabled\",this._unbind();break;default:this._state=\"disabled\"}},xn.prototype.onMouseDown=function(e){if(\"enabled\"===this._state){var n=\"touchstart\"===e.type;if(n)this._startTime=Date.now();else if(\"right\"===this._button){if(this._eventButton=r.mouseButton(e),this._eventButton!==(e.ctrlKey?0:2))return}else{if(e.ctrlKey||0!==r.mouseButton(e))return;this._eventButton=0}r.disableDrag(),n?(t.window.document.addEventListener(\"touchmove\",this._onMouseMove,{capture:!0}),t.window.document.addEventListener(\"touchend\",this._onMouseUp)):(t.window.document.addEventListener(\"mousemove\",this._onMouseMove,{capture:!0}),t.window.document.addEventListener(\"mouseup\",this._onMouseUp)),t.window.addEventListener(\"blur\",this._onBlur),this._state=\"pending\",this._inertia=[[t.browser.now(),this._map.getBearing()]],this._startPos=this._prevPos=this._lastPos=r.mousePos(this._el,e),this._center=this._map.transform.centerPoint,e.preventDefault()}},xn.prototype._onMouseMove=function(t){var e=r.mousePos(this._el,t);this._lastPos.equals(e)||(this._lastMoveEvent=t,this._lastPos=e,\"pending\"===this._state&&(this._state=\"active\",this._fireEvent(\"rotatestart\",t),this._fireEvent(\"movestart\",t),this._pitchWithRotate&&this._fireEvent(\"pitchstart\",t)),this._frameId||(this._frameId=this._map._requestRenderFrame(this._onDragFrame)))},xn.prototype._onDragFrame=function(){this._frameId=null;var e=this._lastMoveEvent;if(e){var r=this._map.transform,n=this._prevPos,a=this._lastPos,i=.8*(n.x-a.x),o=-.5*(n.y-a.y),s=r.bearing-i,l=r.pitch-o,c=this._inertia,u=c[c.length-1];this._drainInertiaBuffer(),c.push([t.browser.now(),this._map._normalizeBearing(s,u[1])]),r.bearing=s,this._pitchWithRotate&&(this._fireEvent(\"pitch\",e),r.pitch=l),this._fireEvent(\"rotate\",e),this._fireEvent(\"move\",e),delete this._lastMoveEvent,this._prevPos=this._lastPos}},xn.prototype._onMouseUp=function(t){if(\"touchend\"===t.type&&this._startPos===this._lastPos&&Date.now()-this._startTime<300&&this._el.click(),r.mouseButton(t)===this._eventButton)switch(this._state){case\"active\":this._state=\"enabled\",r.suppressClick(),this._unbind(),this._deactivate(),this._inertialRotate(t);break;case\"pending\":this._state=\"enabled\",this._unbind()}},xn.prototype._onBlur=function(t){switch(this._state){case\"active\":this._state=\"enabled\",this._unbind(),this._deactivate(),this._fireEvent(\"rotateend\",t),this._pitchWithRotate&&this._fireEvent(\"pitchend\",t),this._fireEvent(\"moveend\",t);break;case\"pending\":this._state=\"enabled\",this._unbind()}},xn.prototype._unbind=function(){t.window.document.removeEventListener(\"mousemove\",this._onMouseMove,{capture:!0}),t.window.document.removeEventListener(\"mouseup\",this._onMouseUp),t.window.document.removeEventListener(\"touchmove\",this._onMouseMove,{capture:!0}),t.window.document.removeEventListener(\"touchend\",this._onMouseUp),t.window.removeEventListener(\"blur\",this._onBlur),r.enableDrag()},xn.prototype._deactivate=function(){this._frameId&&(this._map._cancelRenderFrame(this._frameId),this._frameId=null),delete this._lastMoveEvent,delete this._startPos,delete this._prevPos,delete this._lastPos},xn.prototype._inertialRotate=function(t){var e=this;this._fireEvent(\"rotateend\",t),this._drainInertiaBuffer();var r=this._map,n=r.getBearing(),a=this._inertia,i=function(){Math.abs(n)<e._bearingSnap?r.resetNorth({noMoveStart:!0},{originalEvent:t}):e._fireEvent(\"moveend\",t),e._pitchWithRotate&&e._fireEvent(\"pitchend\",t)};if(a.length<2)i();else{var o=a[0],s=a[a.length-1],l=a[a.length-2],c=r._normalizeBearing(n,l[1]),u=s[1]-o[1],h=u<0?-1:1,f=(s[0]-o[0])/1e3;if(0!==u&&0!==f){var p=Math.abs(u*(.25/f));p>180&&(p=180);var d=p/180;c+=h*p*(d/2),Math.abs(r._normalizeBearing(c,0))<this._bearingSnap&&(c=r._normalizeBearing(0,c)),r.rotateTo(c,{duration:1e3*d,easing:yn,noMoveStart:!0},{originalEvent:t})}else i()}},xn.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,r?{originalEvent:r}:{}))},xn.prototype._drainInertiaBuffer=function(){for(var e=this._inertia,r=t.browser.now();e.length>0&&r-e[0][0]>160;)e.shift()};var bn=t.bezier(0,0,.3,1),_n=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._state=\"disabled\",this._clickTolerance=r.clickTolerance||1,t.bindAll([\"_onMove\",\"_onMouseUp\",\"_onTouchEnd\",\"_onBlur\",\"_onDragFrame\"],this)};_n.prototype.isEnabled=function(){return\"disabled\"!==this._state},_n.prototype.isActive=function(){return\"active\"===this._state},_n.prototype.enable=function(){this.isEnabled()||(this._el.classList.add(\"mapboxgl-touch-drag-pan\"),this._state=\"enabled\")},_n.prototype.disable=function(){if(this.isEnabled())switch(this._el.classList.remove(\"mapboxgl-touch-drag-pan\"),this._state){case\"active\":this._state=\"disabled\",this._unbind(),this._deactivate(),this._fireEvent(\"dragend\"),this._fireEvent(\"moveend\");break;case\"pending\":this._state=\"disabled\",this._unbind();break;default:this._state=\"disabled\"}},_n.prototype.onMouseDown=function(e){\"enabled\"===this._state&&(e.ctrlKey||0!==r.mouseButton(e)||(r.addEventListener(t.window.document,\"mousemove\",this._onMove,{capture:!0}),r.addEventListener(t.window.document,\"mouseup\",this._onMouseUp),this._start(e)))},_n.prototype.onTouchStart=function(e){\"enabled\"===this._state&&(e.touches.length>1||(r.addEventListener(t.window.document,\"touchmove\",this._onMove,{capture:!0,passive:!1}),r.addEventListener(t.window.document,\"touchend\",this._onTouchEnd),this._start(e)))},_n.prototype._start=function(e){t.window.addEventListener(\"blur\",this._onBlur),this._state=\"pending\",this._startPos=this._mouseDownPos=this._prevPos=this._lastPos=r.mousePos(this._el,e),this._inertia=[[t.browser.now(),this._startPos]]},_n.prototype._onMove=function(e){e.preventDefault();var n=r.mousePos(this._el,e);this._lastPos.equals(n)||\"pending\"===this._state&&n.dist(this._mouseDownPos)<this._clickTolerance||(this._lastMoveEvent=e,this._lastPos=n,this._drainInertiaBuffer(),this._inertia.push([t.browser.now(),this._lastPos]),\"pending\"===this._state&&(this._state=\"active\",this._fireEvent(\"dragstart\",e),this._fireEvent(\"movestart\",e)),this._frameId||(this._frameId=this._map._requestRenderFrame(this._onDragFrame)))},_n.prototype._onDragFrame=function(){this._frameId=null;var t=this._lastMoveEvent;if(t){var e=this._map.transform;e.setLocationAtPoint(e.pointLocation(this._prevPos),this._lastPos),this._fireEvent(\"drag\",t),this._fireEvent(\"move\",t),this._prevPos=this._lastPos,delete this._lastMoveEvent}},_n.prototype._onMouseUp=function(t){if(0===r.mouseButton(t))switch(this._state){case\"active\":this._state=\"enabled\",r.suppressClick(),this._unbind(),this._deactivate(),this._inertialPan(t);break;case\"pending\":this._state=\"enabled\",this._unbind()}},_n.prototype._onTouchEnd=function(t){switch(this._state){case\"active\":this._state=\"enabled\",this._unbind(),this._deactivate(),this._inertialPan(t);break;case\"pending\":this._state=\"enabled\",this._unbind()}},_n.prototype._onBlur=function(t){switch(this._state){case\"active\":this._state=\"enabled\",this._unbind(),this._deactivate(),this._fireEvent(\"dragend\",t),this._fireEvent(\"moveend\",t);break;case\"pending\":this._state=\"enabled\",this._unbind()}},_n.prototype._unbind=function(){r.removeEventListener(t.window.document,\"touchmove\",this._onMove,{capture:!0,passive:!1}),r.removeEventListener(t.window.document,\"touchend\",this._onTouchEnd),r.removeEventListener(t.window.document,\"mousemove\",this._onMove,{capture:!0}),r.removeEventListener(t.window.document,\"mouseup\",this._onMouseUp),r.removeEventListener(t.window,\"blur\",this._onBlur)},_n.prototype._deactivate=function(){this._frameId&&(this._map._cancelRenderFrame(this._frameId),this._frameId=null),delete this._lastMoveEvent,delete this._startPos,delete this._prevPos,delete this._mouseDownPos,delete this._lastPos},_n.prototype._inertialPan=function(t){this._fireEvent(\"dragend\",t),this._drainInertiaBuffer();var e=this._inertia;if(e.length<2)this._fireEvent(\"moveend\",t);else{var r=e[e.length-1],n=e[0],a=r[1].sub(n[1]),i=(r[0]-n[0])/1e3;if(0===i||r[1].equals(n[1]))this._fireEvent(\"moveend\",t);else{var o=a.mult(.3/i),s=o.mag();s>1400&&(s=1400,o._unit()._mult(s));var l=s/750,c=o.mult(-l/2);this._map.panBy(c,{duration:1e3*l,easing:bn,noMoveStart:!0},{originalEvent:t})}}},_n.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,r?{originalEvent:r}:{}))},_n.prototype._drainInertiaBuffer=function(){for(var e=this._inertia,r=t.browser.now();e.length>0&&r-e[0][0]>160;)e.shift()};var wn=function(e){this._map=e,this._el=e.getCanvasContainer(),t.bindAll([\"_onKeyDown\"],this)};function kn(t){return t*(2-t)}wn.prototype.isEnabled=function(){return!!this._enabled},wn.prototype.enable=function(){this.isEnabled()||(this._el.addEventListener(\"keydown\",this._onKeyDown,!1),this._enabled=!0)},wn.prototype.disable=function(){this.isEnabled()&&(this._el.removeEventListener(\"keydown\",this._onKeyDown),this._enabled=!1)},wn.prototype._onKeyDown=function(t){if(!(t.altKey||t.ctrlKey||t.metaKey)){var e=0,r=0,n=0,a=0,i=0;switch(t.keyCode){case 61:case 107:case 171:case 187:e=1;break;case 189:case 109:case 173:e=-1;break;case 37:t.shiftKey?r=-1:(t.preventDefault(),a=-1);break;case 39:t.shiftKey?r=1:(t.preventDefault(),a=1);break;case 38:t.shiftKey?n=1:(t.preventDefault(),i=-1);break;case 40:t.shiftKey?n=-1:(i=1,t.preventDefault());break;default:return}var o=this._map,s=o.getZoom(),l={duration:300,delayEndEvents:500,easing:kn,zoom:e?Math.round(s)+e*(t.shiftKey?2:1):s,bearing:o.getBearing()+15*r,pitch:o.getPitch()+10*n,offset:[100*-a,100*-i],center:o.getCenter()};o.easeTo(l,{originalEvent:t})}};var Tn=function(e){this._map=e,t.bindAll([\"_onDblClick\",\"_onZoomEnd\"],this)};Tn.prototype.isEnabled=function(){return!!this._enabled},Tn.prototype.isActive=function(){return!!this._active},Tn.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},Tn.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Tn.prototype.onTouchStart=function(t){var e=this;if(this.isEnabled()&&!(t.points.length>1))if(this._tapped){var r=t.points[0],n=this._tappedPoint;if(n&&n.dist(r)<=30){t.originalEvent.preventDefault();var a=function(){e._tapped&&e._zoom(t),e._map.off(\"touchcancel\",i),e._resetTapped()},i=function(){e._map.off(\"touchend\",a),e._resetTapped()};this._map.once(\"touchend\",a),this._map.once(\"touchcancel\",i)}else this._resetTapped()}else this._tappedPoint=t.points[0],this._tapped=setTimeout(function(){e._tapped=null,e._tappedPoint=null},300)},Tn.prototype._resetTapped=function(){clearTimeout(this._tapped),this._tapped=null,this._tappedPoint=null},Tn.prototype.onDblClick=function(t){this.isEnabled()&&(t.originalEvent.preventDefault(),this._zoom(t))},Tn.prototype._zoom=function(t){this._active=!0,this._map.on(\"zoomend\",this._onZoomEnd),this._map.zoomTo(this._map.getZoom()+(t.originalEvent.shiftKey?-1:1),{around:t.lngLat},t)},Tn.prototype._onZoomEnd=function(){this._active=!1,this._map.off(\"zoomend\",this._onZoomEnd)};var Mn=t.bezier(0,0,.15,1),An=function(e){this._map=e,this._el=e.getCanvasContainer(),t.bindAll([\"_onMove\",\"_onEnd\",\"_onTouchFrame\"],this)};An.prototype.isEnabled=function(){return!!this._enabled},An.prototype.enable=function(t){this.isEnabled()||(this._el.classList.add(\"mapboxgl-touch-zoom-rotate\"),this._enabled=!0,this._aroundCenter=!!t&&\"center\"===t.around)},An.prototype.disable=function(){this.isEnabled()&&(this._el.classList.remove(\"mapboxgl-touch-zoom-rotate\"),this._enabled=!1)},An.prototype.disableRotation=function(){this._rotationDisabled=!0},An.prototype.enableRotation=function(){this._rotationDisabled=!1},An.prototype.onStart=function(e){if(this.isEnabled()&&2===e.touches.length){var n=r.mousePos(this._el,e.touches[0]),a=r.mousePos(this._el,e.touches[1]),i=n.add(a).div(2);this._startVec=n.sub(a),this._startAround=this._map.transform.pointLocation(i),this._gestureIntent=void 0,this._inertia=[],r.addEventListener(t.window.document,\"touchmove\",this._onMove,{passive:!1}),r.addEventListener(t.window.document,\"touchend\",this._onEnd)}},An.prototype._getTouchEventData=function(t){var e=r.mousePos(this._el,t.touches[0]),n=r.mousePos(this._el,t.touches[1]),a=e.sub(n);return{vec:a,center:e.add(n).div(2),scale:a.mag()/this._startVec.mag(),bearing:this._rotationDisabled?0:180*a.angleWith(this._startVec)/Math.PI}},An.prototype._onMove=function(e){if(2===e.touches.length){var r=this._getTouchEventData(e),n=r.vec,a=r.scale,i=r.bearing;if(!this._gestureIntent){var o=this._rotationDisabled&&1!==a||Math.abs(1-a)>.15;Math.abs(i)>10?this._gestureIntent=\"rotate\":o&&(this._gestureIntent=\"zoom\"),this._gestureIntent&&(this._map.fire(new t.Event(this._gestureIntent+\"start\",{originalEvent:e})),this._map.fire(new t.Event(\"movestart\",{originalEvent:e})),this._startVec=n)}this._lastTouchEvent=e,this._frameId||(this._frameId=this._map._requestRenderFrame(this._onTouchFrame)),e.preventDefault()}},An.prototype._onTouchFrame=function(){this._frameId=null;var e=this._gestureIntent;if(e){var r=this._map.transform;this._startScale||(this._startScale=r.scale,this._startBearing=r.bearing);var n=this._getTouchEventData(this._lastTouchEvent),a=n.center,i=n.bearing,o=n.scale,s=r.pointLocation(a),l=r.locationPoint(s);\"rotate\"===e&&(r.bearing=this._startBearing+i),r.zoom=r.scaleZoom(this._startScale*o),r.setLocationAtPoint(this._startAround,l),this._map.fire(new t.Event(e,{originalEvent:this._lastTouchEvent})),this._map.fire(new t.Event(\"move\",{originalEvent:this._lastTouchEvent})),this._drainInertiaBuffer(),this._inertia.push([t.browser.now(),o,a])}},An.prototype._onEnd=function(e){r.removeEventListener(t.window.document,\"touchmove\",this._onMove,{passive:!1}),r.removeEventListener(t.window.document,\"touchend\",this._onEnd);var n=this._gestureIntent,a=this._startScale;if(this._frameId&&(this._map._cancelRenderFrame(this._frameId),this._frameId=null),delete this._gestureIntent,delete this._startScale,delete this._startBearing,delete this._lastTouchEvent,n){this._map.fire(new t.Event(n+\"end\",{originalEvent:e})),this._drainInertiaBuffer();var i=this._inertia,o=this._map;if(i.length<2)o.snapToNorth({},{originalEvent:e});else{var s=i[i.length-1],l=i[0],c=o.transform.scaleZoom(a*s[1]),u=o.transform.scaleZoom(a*l[1]),h=c-u,f=(s[0]-l[0])/1e3,p=s[2];if(0!==f&&c!==u){var d=.15*h/f;Math.abs(d)>2.5&&(d=d>0?2.5:-2.5);var g=1e3*Math.abs(d/(12*.15)),v=c+d*g/2e3;v<0&&(v=0),o.easeTo({zoom:v,duration:g,easing:Mn,around:this._aroundCenter?o.getCenter():o.unproject(p),noMoveStart:!0},{originalEvent:e})}else o.snapToNorth({},{originalEvent:e})}}},An.prototype._drainInertiaBuffer=function(){for(var e=this._inertia,r=t.browser.now();e.length>2&&r-e[0][0]>160;)e.shift()};var Sn={scrollZoom:vn,boxZoom:mn,dragRotate:xn,dragPan:_n,keyboard:wn,doubleClickZoom:Tn,touchZoomRotate:An},En=function(e){function r(r,n){e.call(this),this._moving=!1,this._zooming=!1,this.transform=r,this._bearingSnap=n.bearingSnap,t.bindAll([\"_renderFrameCallback\"],this)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getCenter=function(){return new t.LngLat(this.transform.center.lng,this.transform.center.lat)},r.prototype.setCenter=function(t,e){return this.jumpTo({center:t},e)},r.prototype.panBy=function(e,r,n){return e=t.Point.convert(e).mult(-1),this.panTo(this.transform.center,t.extend({offset:e},r),n)},r.prototype.panTo=function(e,r,n){return this.easeTo(t.extend({center:e},r),n)},r.prototype.getZoom=function(){return this.transform.zoom},r.prototype.setZoom=function(t,e){return this.jumpTo({zoom:t},e),this},r.prototype.zoomTo=function(e,r,n){return this.easeTo(t.extend({zoom:e},r),n)},r.prototype.zoomIn=function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},r.prototype.zoomOut=function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},r.prototype.getBearing=function(){return this.transform.bearing},r.prototype.setBearing=function(t,e){return this.jumpTo({bearing:t},e),this},r.prototype.rotateTo=function(e,r,n){return this.easeTo(t.extend({bearing:e},r),n)},r.prototype.resetNorth=function(e,r){return this.rotateTo(0,t.extend({duration:1e3},e),r),this},r.prototype.resetNorthPitch=function(e,r){return this.easeTo(t.extend({bearing:0,pitch:0,duration:1e3},e),r),this},r.prototype.snapToNorth=function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},r.prototype.getPitch=function(){return this.transform.pitch},r.prototype.setPitch=function(t,e){return this.jumpTo({pitch:t},e),this},r.prototype.cameraForBounds=function(e,r){return e=t.LngLatBounds.convert(e),this._cameraForBoxAndBearing(e.getNorthWest(),e.getSouthEast(),0,r)},r.prototype._cameraForBoxAndBearing=function(e,r,n,a){if(\"number\"==typeof(a=t.extend({padding:{top:0,bottom:0,right:0,left:0},offset:[0,0],maxZoom:this.transform.maxZoom},a)).padding){var i=a.padding;a.padding={top:i,bottom:i,right:i,left:i}}if(t.deepEqual(Object.keys(a.padding).sort(function(t,e){return t<e?-1:t>e?1:0}),[\"bottom\",\"left\",\"right\",\"top\"])){var o=this.transform,s=o.project(t.LngLat.convert(e)),l=o.project(t.LngLat.convert(r)),c=s.rotate(-n*Math.PI/180),u=l.rotate(-n*Math.PI/180),h=new t.Point(Math.max(c.x,u.x),Math.max(c.y,u.y)),f=new t.Point(Math.min(c.x,u.x),Math.min(c.y,u.y)),p=h.sub(f),d=(o.width-a.padding.left-a.padding.right)/p.x,g=(o.height-a.padding.top-a.padding.bottom)/p.y;if(!(g<0||d<0)){var v=Math.min(o.scaleZoom(o.scale*Math.min(d,g)),a.maxZoom),m=t.Point.convert(a.offset),y=(a.padding.left-a.padding.right)/2,x=(a.padding.top-a.padding.bottom)/2,b=new t.Point(m.x+y,m.y+x).mult(o.scale/o.zoomScale(v));return{center:o.unproject(s.add(l).div(2).sub(b)),zoom:v,bearing:n}}t.warnOnce(\"Map cannot fit within canvas with the given bounds, padding, and/or offset.\")}else t.warnOnce(\"options.padding must be a positive number, or an Object with keys 'bottom', 'left', 'right', 'top'\")},r.prototype.fitBounds=function(t,e,r){return this._fitInternal(this.cameraForBounds(t,e),e,r)},r.prototype.fitScreenCoordinates=function(e,r,n,a,i){return this._fitInternal(this._cameraForBoxAndBearing(this.transform.pointLocation(t.Point.convert(e)),this.transform.pointLocation(t.Point.convert(r)),n,a),a,i)},r.prototype._fitInternal=function(e,r,n){return e?(r=t.extend(e,r)).linear?this.easeTo(r,n):this.flyTo(r,n):this},r.prototype.jumpTo=function(e,r){this.stop();var n=this.transform,a=!1,i=!1,o=!1;return\"zoom\"in e&&n.zoom!==+e.zoom&&(a=!0,n.zoom=+e.zoom),void 0!==e.center&&(n.center=t.LngLat.convert(e.center)),\"bearing\"in e&&n.bearing!==+e.bearing&&(i=!0,n.bearing=+e.bearing),\"pitch\"in e&&n.pitch!==+e.pitch&&(o=!0,n.pitch=+e.pitch),this.fire(new t.Event(\"movestart\",r)).fire(new t.Event(\"move\",r)),a&&this.fire(new t.Event(\"zoomstart\",r)).fire(new t.Event(\"zoom\",r)).fire(new t.Event(\"zoomend\",r)),i&&this.fire(new t.Event(\"rotatestart\",r)).fire(new t.Event(\"rotate\",r)).fire(new t.Event(\"rotateend\",r)),o&&this.fire(new t.Event(\"pitchstart\",r)).fire(new t.Event(\"pitch\",r)).fire(new t.Event(\"pitchend\",r)),this.fire(new t.Event(\"moveend\",r))},r.prototype.easeTo=function(e,r){var n=this;this.stop(),(!1===(e=t.extend({offset:[0,0],duration:500,easing:t.ease},e)).animate||t.browser.prefersReducedMotion)&&(e.duration=0);var a=this.transform,i=this.getZoom(),o=this.getBearing(),s=this.getPitch(),l=\"zoom\"in e?+e.zoom:i,c=\"bearing\"in e?this._normalizeBearing(e.bearing,o):o,u=\"pitch\"in e?+e.pitch:s,h=a.centerPoint.add(t.Point.convert(e.offset)),f=a.pointLocation(h),p=t.LngLat.convert(e.center||f);this._normalizeCenter(p);var d,g,v=a.project(f),m=a.project(p).sub(v),y=a.zoomScale(l-i);return e.around&&(d=t.LngLat.convert(e.around),g=a.locationPoint(d)),this._zooming=l!==i,this._rotating=o!==c,this._pitching=u!==s,this._prepareEase(r,e.noMoveStart),clearTimeout(this._easeEndTimeoutID),this._ease(function(e){if(n._zooming&&(a.zoom=t.number(i,l,e)),n._rotating&&(a.bearing=t.number(o,c,e)),n._pitching&&(a.pitch=t.number(s,u,e)),d)a.setLocationAtPoint(d,g);else{var f=a.zoomScale(a.zoom-i),p=l>i?Math.min(2,y):Math.max(.5,y),x=Math.pow(p,1-e),b=a.unproject(v.add(m.mult(e*x)).mult(f));a.setLocationAtPoint(a.renderWorldCopies?b.wrap():b,h)}n._fireMoveEvents(r)},function(){e.delayEndEvents?n._easeEndTimeoutID=setTimeout(function(){return n._afterEase(r)},e.delayEndEvents):n._afterEase(r)},e),this},r.prototype._prepareEase=function(e,r){this._moving=!0,r||this.fire(new t.Event(\"movestart\",e)),this._zooming&&this.fire(new t.Event(\"zoomstart\",e)),this._rotating&&this.fire(new t.Event(\"rotatestart\",e)),this._pitching&&this.fire(new t.Event(\"pitchstart\",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event(\"move\",e)),this._zooming&&this.fire(new t.Event(\"zoom\",e)),this._rotating&&this.fire(new t.Event(\"rotate\",e)),this._pitching&&this.fire(new t.Event(\"pitch\",e))},r.prototype._afterEase=function(e){var r=this._zooming,n=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,r&&this.fire(new t.Event(\"zoomend\",e)),n&&this.fire(new t.Event(\"rotateend\",e)),a&&this.fire(new t.Event(\"pitchend\",e)),this.fire(new t.Event(\"moveend\",e))},r.prototype.flyTo=function(e,r){var n=this;if(t.browser.prefersReducedMotion){var a=t.pick(e,[\"center\",\"zoom\",\"bearing\",\"pitch\",\"around\"]);return this.jumpTo(a,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var i=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),c=\"zoom\"in e?t.clamp(+e.zoom,i.minZoom,i.maxZoom):o,u=\"bearing\"in e?this._normalizeBearing(e.bearing,s):s,h=\"pitch\"in e?+e.pitch:l,f=i.zoomScale(c-o),p=i.centerPoint.add(t.Point.convert(e.offset)),d=i.pointLocation(p),g=t.LngLat.convert(e.center||d);this._normalizeCenter(g);var v=i.project(d),m=i.project(g).sub(v),y=e.curve,x=Math.max(i.width,i.height),b=x/f,_=m.mag();if(\"minZoom\"in e){var w=t.clamp(Math.min(e.minZoom,o,c),i.minZoom,i.maxZoom),k=x/i.zoomScale(w-o);y=Math.sqrt(k/_*2)}var T=y*y;function M(t){var e=(b*b-x*x+(t?-1:1)*T*T*_*_)/(2*(t?b:x)*T*_);return Math.log(Math.sqrt(e*e+1)-e)}function A(t){return(Math.exp(t)-Math.exp(-t))/2}function S(t){return(Math.exp(t)+Math.exp(-t))/2}var E=M(0),L=function(t){return S(E)/S(E+y*t)},C=function(t){return x*((S(E)*(A(e=E+y*t)/S(e))-A(E))/T)/_;var e},P=(M(1)-E)/y;if(Math.abs(_)<1e-6||!isFinite(P)){if(Math.abs(x-b)<1e-6)return this.easeTo(e,r);var O=b<x?-1:1;P=Math.abs(Math.log(b/x))/y,C=function(){return 0},L=function(t){return Math.exp(O*y*t)}}if(\"duration\"in e)e.duration=+e.duration;else{var z=\"screenSpeed\"in e?+e.screenSpeed/y:+e.speed;e.duration=1e3*P/z}return e.maxDuration&&e.duration>e.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==u,this._pitching=h!==l,this._prepareEase(r,!1),this._ease(function(e){var a=e*P,f=1/L(a);i.zoom=1===e?c:o+i.scaleZoom(f),n._rotating&&(i.bearing=t.number(s,u,e)),n._pitching&&(i.pitch=t.number(l,h,e));var d=1===e?g:i.unproject(v.add(m.mult(C(a))).mult(f));i.setLocationAtPoint(i.renderWorldCopies?d.wrap():d,p),n._fireMoveEvents(r)},function(){return n._afterEase(r)},e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var t=this._onEaseEnd;delete this._onEaseEnd,t.call(this)}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)<n&&(e-=360),Math.abs(e+360-r)<n&&(e+=360),e},r.prototype._normalizeCenter=function(t){var e=this.transform;if(e.renderWorldCopies&&!e.lngRange){var r=t.lng-e.center.lng;t.lng+=r>180?-360:r<-180?360:0}},r}(t.Evented),Ln=function(e){void 0===e&&(e={}),this.options=e,t.bindAll([\"_updateEditLink\",\"_updateData\",\"_updateCompact\"],this)};Ln.prototype.getDefaultPosition=function(){return\"bottom-right\"},Ln.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-attrib\"),this._innerContainer=r.create(\"div\",\"mapboxgl-ctrl-attrib-inner\",this._container),e&&this._container.classList.add(\"mapboxgl-compact\"),this._updateAttributions(),this._updateEditLink(),this._map.on(\"styledata\",this._updateData),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"moveend\",this._updateEditLink),void 0===e&&(this._map.on(\"resize\",this._updateCompact),this._updateCompact()),this._container},Ln.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"styledata\",this._updateData),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"moveend\",this._updateEditLink),this._map.off(\"resize\",this._updateCompact),this._map=void 0},Ln.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(\".mapbox-improve-map\"));var r=[{key:\"owner\",value:this.styleOwner},{key:\"id\",value:this.styleId},{key:\"access_token\",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce(function(t,e,n){return e.value&&(t+=e.key+\"=\"+e.value+(n<r.length-1?\"&\":\"\")),t},\"?\");e.href=t.config.FEEDBACK_URL+\"/\"+n+(this._map._hash?this._map._hash.getHashString(!0):\"\"),e.rel=\"noopener nofollow\"}},Ln.prototype._updateData=function(t){!t||\"metadata\"!==t.sourceDataType&&\"style\"!==t.dataType||(this._updateAttributions(),this._updateEditLink())},Ln.prototype._updateAttributions=function(){if(this._map.style){var t=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?t=t.concat(this.options.customAttribution.map(function(t){return\"string\"!=typeof t?\"\":t})):\"string\"==typeof this.options.customAttribution&&t.push(this.options.customAttribution)),this._map.style.stylesheet){var e=this._map.style.stylesheet;this.styleOwner=e.owner,this.styleId=e.id}var r=this._map.style.sourceCaches;for(var n in r){var a=r[n];if(a.used){var i=a.getSource();i.attribution&&t.indexOf(i.attribution)<0&&t.push(i.attribution)}}t.sort(function(t,e){return t.length-e.length});var o=(t=t.filter(function(e,r){for(var n=r+1;n<t.length;n++)if(t[n].indexOf(e)>=0)return!1;return!0})).join(\" | \");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove(\"mapboxgl-attrib-empty\")):this._container.classList.add(\"mapboxgl-attrib-empty\"),this._editLink=null)}},Ln.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add(\"mapboxgl-compact\"):this._container.classList.remove(\"mapboxgl-compact\")};var Cn=function(){t.bindAll([\"_updateLogo\"],this),t.bindAll([\"_updateCompact\"],this)};Cn.prototype.onAdd=function(t){this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl\");var e=r.create(\"a\",\"mapboxgl-ctrl-logo\");return e.target=\"_blank\",e.rel=\"noopener nofollow\",e.href=\"https://www.mapbox.com/\",e.setAttribute(\"aria-label\",\"Mapbox logo\"),e.setAttribute(\"rel\",\"noopener nofollow\"),this._container.appendChild(e),this._container.style.display=\"none\",this._map.on(\"sourcedata\",this._updateLogo),this._updateLogo(),this._map.on(\"resize\",this._updateCompact),this._updateCompact(),this._container},Cn.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"sourcedata\",this._updateLogo),this._map.off(\"resize\",this._updateCompact)},Cn.prototype.getDefaultPosition=function(){return\"bottom-left\"},Cn.prototype._updateLogo=function(t){t&&\"metadata\"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?\"block\":\"none\")},Cn.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t)if(t[e].getSource().mapbox_logo)return!0;return!1}},Cn.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add(\"mapboxgl-compact\"):e.classList.remove(\"mapboxgl-compact\")}};var Pn=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};Pn.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},Pn.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;r<n.length;r+=1){var a=n[r];if(a.id===t)return void(a.cancelled=!0)}},Pn.prototype.run=function(){var t=this._currentlyRunning=this._queue;this._queue=[];for(var e=0,r=t;e<r.length;e+=1){var n=r[e];if(!n.cancelled&&(n.callback(),this._cleared))break}this._cleared=!1,this._currentlyRunning=!1},Pn.prototype.clear=function(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]};var On=t.window.HTMLImageElement,zn=t.window.HTMLElement,In={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:0,maxZoom:22,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,bearingSnap:7,clickTolerance:3,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,renderWorldCopies:!0,refreshExpiredTiles:!0,maxTileCacheSize:null,localIdeographFontFamily:\"sans-serif\",transformRequest:null,accessToken:null,fadeDuration:300,crossSourceCollisions:!0},Dn=function(n){function a(e){var a=this;if(null!=(e=t.extend({},In,e)).minZoom&&null!=e.maxZoom&&e.minZoom>e.maxZoom)throw new Error(\"maxZoom must be greater than minZoom\");var i=new un(e.minZoom,e.maxZoom,e.renderWorldCopies);if(n.call(this,i,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new Pn,this._controls=[],this._mapId=t.uniqueId(),this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),\"string\"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error(\"Container '\"+e.container+\"' not found.\")}else{if(!(e.container instanceof zn))throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll([\"_onWindowOnline\",\"_onWindowResize\",\"_contextLost\",\"_contextRestored\"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error(\"Failed to initialize WebGL.\");this.on(\"move\",function(){return a._update(!1)}),this.on(\"moveend\",function(){return a._update(!1)}),this.on(\"zoom\",function(){return a._update(!0)}),void 0!==t.window&&(t.window.addEventListener(\"online\",this._onWindowOnline,!1),t.window.addEventListener(\"resize\",this._onWindowResize,!1)),function(t,e){var n=t.getCanvasContainer(),a=null,i=!1,o=null;for(var s in Sn)t[s]=new Sn[s](t,e),e.interactive&&e[s]&&t[s].enable(e[s]);r.addEventListener(n,\"mouseout\",function(e){t.fire(new pn(\"mouseout\",t,e))}),r.addEventListener(n,\"mousedown\",function(a){i=!0,o=r.mousePos(n,a);var s=new pn(\"mousedown\",t,a);t.fire(s),s.defaultPrevented||(e.interactive&&!t.doubleClickZoom.isActive()&&t.stop(),t.boxZoom.onMouseDown(a),t.boxZoom.isActive()||t.dragPan.isActive()||t.dragRotate.onMouseDown(a),t.boxZoom.isActive()||t.dragRotate.isActive()||t.dragPan.onMouseDown(a))}),r.addEventListener(n,\"mouseup\",function(e){var r=t.dragRotate.isActive();a&&!r&&t.fire(new pn(\"contextmenu\",t,a)),a=null,i=!1,t.fire(new pn(\"mouseup\",t,e))}),r.addEventListener(n,\"mousemove\",function(e){if(!t.dragPan.isActive()&&!t.dragRotate.isActive()){for(var r=e.target;r&&r!==n;)r=r.parentNode;r===n&&t.fire(new pn(\"mousemove\",t,e))}}),r.addEventListener(n,\"mouseover\",function(e){for(var r=e.target;r&&r!==n;)r=r.parentNode;r===n&&t.fire(new pn(\"mouseover\",t,e))}),r.addEventListener(n,\"touchstart\",function(r){var n=new dn(\"touchstart\",t,r);t.fire(n),n.defaultPrevented||(e.interactive&&t.stop(),t.boxZoom.isActive()||t.dragRotate.isActive()||t.dragPan.onTouchStart(r),t.touchZoomRotate.onStart(r),t.doubleClickZoom.onTouchStart(n))},{passive:!1}),r.addEventListener(n,\"touchmove\",function(e){t.fire(new dn(\"touchmove\",t,e))},{passive:!1}),r.addEventListener(n,\"touchend\",function(e){t.fire(new dn(\"touchend\",t,e))}),r.addEventListener(n,\"touchcancel\",function(e){t.fire(new dn(\"touchcancel\",t,e))}),r.addEventListener(n,\"click\",function(a){var i=r.mousePos(n,a);(!o||i.equals(o)||i.dist(o)<e.clickTolerance)&&t.fire(new pn(\"click\",t,a))}),r.addEventListener(n,\"dblclick\",function(e){var r=new pn(\"dblclick\",t,e);t.fire(r),r.defaultPrevented||t.doubleClickZoom.onDblClick(r)}),r.addEventListener(n,\"contextmenu\",function(e){var r=t.dragRotate.isActive();i||r?i&&(a=e):t.fire(new pn(\"contextmenu\",t,e)),(t.dragRotate.isEnabled()||t.listens(\"contextmenu\"))&&e.preventDefault()}),r.addEventListener(n,\"wheel\",function(r){e.interactive&&t.stop();var n=new gn(\"wheel\",t,r);t.fire(n),n.defaultPrevented||t.scrollZoom.onWheel(r)},{passive:!1})}(this,e),this._hash=e.hash&&(new fn).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new Ln({customAttribution:e.customAttribution})),this.addControl(new Cn,e.logoPosition),this.on(\"style.load\",function(){a.transform.unmodified&&a.jumpTo(a.style.stylesheet)}),this.on(\"data\",function(e){a._update(\"style\"===e.dataType),a.fire(new t.Event(e.dataType+\"data\",e))}),this.on(\"dataloading\",function(e){a.fire(new t.Event(e.dataType+\"dataloading\",e))})}n&&(a.__proto__=n),a.prototype=Object.create(n&&n.prototype),a.prototype.constructor=a;var i={showTileBoundaries:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return a.prototype._getMapId=function(){return this._mapId},a.prototype.addControl=function(e,r){if(void 0===r&&e.getDefaultPosition&&(r=e.getDefaultPosition()),void 0===r&&(r=\"top-right\"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.\")));var n=e.onAdd(this);this._controls.push(e);var a=this._controlPositions[r];return-1!==r.indexOf(\"bottom\")?a.insertBefore(n,a.firstChild):a.appendChild(n),this},a.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.\")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},a.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],a=r[1];return this._resizeCanvas(n,a),this.transform.resize(n,a),this.painter.resize(n,a),this.fire(new t.Event(\"movestart\",e)).fire(new t.Event(\"move\",e)).fire(new t.Event(\"resize\",e)).fire(new t.Event(\"moveend\",e)),this},a.prototype.getBounds=function(){return this.transform.getBounds()},a.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},a.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},a.prototype.setMinZoom=function(t){if((t=null==t?0:t)>=0&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()<t&&this.setZoom(t),this;throw new Error(\"minZoom must be between 0 and the current maxZoom, inclusive\")},a.prototype.getMinZoom=function(){return this.transform.minZoom},a.prototype.setMaxZoom=function(t){if((t=null==t?22:t)>=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be greater than the current minZoom\")},a.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},a.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},a.prototype.getMaxZoom=function(){return this.transform.maxZoom},a.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},a.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},a.prototype.isMoving=function(){return this._moving||this.dragPan.isActive()||this.dragRotate.isActive()||this.scrollZoom.isActive()},a.prototype.isZooming=function(){return this._zooming||this.scrollZoom.isZooming()},a.prototype.isRotating=function(){return this._rotating||this.dragRotate.isActive()},a.prototype.on=function(t,e,r){var a=this;if(void 0===r)return n.prototype.on.call(this,t,e);var i=function(){var n;if(\"mouseenter\"===t||\"mouseover\"===t){var i=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=a.getLayer(e)?a.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?i||(i=!0,r.call(a,new pn(t,a,n.originalEvent,{features:o}))):i=!1},mouseout:function(){i=!1}}}}if(\"mouseleave\"===t||\"mouseout\"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(a.getLayer(e)?a.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(a,new pn(t,a,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(a,new pn(t,a,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=a.getLayer(e)?a.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(a,t),delete t.features)},n)}}();for(var o in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(i),i.delegates)this.on(o,i.delegates[o]);return this},a.prototype.off=function(t,e,r){if(void 0===r)return n.prototype.off.call(this,t,e);if(this._delegatedListeners&&this._delegatedListeners[t])for(var a=this._delegatedListeners[t],i=0;i<a.length;i++){var o=a[i];if(o.layer===e&&o.listener===r){for(var s in o.delegates)this.off(s,o.delegates[s]);return a.splice(i,1),this}}return this},a.prototype.queryRenderedFeatures=function(e,r){if(!this.style)return[];var n;if(void 0!==r||void 0===e||e instanceof t.Point||Array.isArray(e)||(r=e,e=void 0),r=r||{},(e=e||[[0,0],[this.transform.width,this.transform.height]])instanceof t.Point||\"number\"==typeof e[0])n=[t.Point.convert(e)];else{var a=t.Point.convert(e[0]),i=t.Point.convert(e[1]);n=[a,new t.Point(i.x,a.y),i,new t.Point(a.x,i.y),a]}return this.style.queryRenderedFeatures(n,r,this.transform)},a.prototype.querySourceFeatures=function(t,e){return this.style.querySourceFeatures(t,e)},a.prototype.setStyle=function(e,r){return!1!==(r=t.extend({},{localIdeographFontFamily:this._localIdeographFontFamily},r)).diff&&r.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&e?(this._diffStyle(e,r),this):(this._localIdeographFontFamily=r.localIdeographFontFamily,this._updateStyle(e,r))},a.prototype._updateStyle=function(t,e){return this.style&&(this.style.setEventedParent(null),this.style._remove()),t?(this.style=new Re(this,e||{}),this.style.setEventedParent(this,{style:this.style}),\"string\"==typeof t?this.style.loadURL(t):this.style.loadJSON(t),this):(delete this.style,this)},a.prototype._diffStyle=function(e,r){var n=this;if(\"string\"==typeof e){var a=this._requestManager.normalizeStyleURL(e),i=this._requestManager.transformRequest(a,t.ResourceType.Style);t.getJSON(i,function(e,a){e?n.fire(new t.ErrorEvent(e)):a&&n._updateDiff(a,r)})}else\"object\"==typeof e&&this._updateDiff(e,r)},a.prototype._updateDiff=function(e,r){try{this.style.setState(e)&&this._update(!0)}catch(n){t.warnOnce(\"Unable to perform style diff: \"+(n.message||n.error||n)+\".  Rebuilding the style from scratch.\"),this._updateStyle(e,r)}},a.prototype.getStyle=function(){if(this.style)return this.style.serialize()},a.prototype.isStyleLoaded=function(){return this.style?this.style.loaded():t.warnOnce(\"There is no style added to the map.\")},a.prototype.addSource=function(t,e){return this.style.addSource(t,e),this._update(!0)},a.prototype.isSourceLoaded=function(e){var r=this.style&&this.style.sourceCaches[e];if(void 0!==r)return r.loaded();this.fire(new t.ErrorEvent(new Error(\"There is no source with ID '\"+e+\"'\")))},a.prototype.areTilesLoaded=function(){var t=this.style&&this.style.sourceCaches;for(var e in t){var r=t[e]._tiles;for(var n in r){var a=r[n];if(\"loaded\"!==a.state&&\"errored\"!==a.state)return!1}}return!0},a.prototype.addSourceType=function(t,e,r){return this.style.addSourceType(t,e,r)},a.prototype.removeSource=function(t){return this.style.removeSource(t),this._update(!0)},a.prototype.getSource=function(t){return this.style.getSource(t)},a.prototype.addImage=function(e,r,n){void 0===n&&(n={});var a=n.pixelRatio;void 0===a&&(a=1);var i=n.sdf;if(void 0===i&&(i=!1),r instanceof On){var o=t.browser.getImageData(r),s=o.width,l=o.height,c=o.data;this.style.addImage(e,{data:new t.RGBAImage({width:s,height:l},c),pixelRatio:a,sdf:i,version:0})}else{if(void 0===r.width||void 0===r.height)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));var u=r.width,h=r.height,f=r.data,p=r;this.style.addImage(e,{data:new t.RGBAImage({width:u,height:h},new Uint8Array(f)),pixelRatio:a,sdf:i,version:0,userImage:p}),p.onAdd&&p.onAdd(this,e)}},a.prototype.updateImage=function(e,r){var n=this.style.getImage(e);if(!n)return this.fire(new t.ErrorEvent(new Error(\"The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.\")));var a=r instanceof On?t.browser.getImageData(r):r,i=a.width,o=a.height,s=a.data;if(void 0===i||void 0===o)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));if(i!==n.data.width||o!==n.data.height)return this.fire(new t.ErrorEvent(new Error(\"The width and height of the updated image must be that same as the previous version of the image\")));var l=!(r instanceof On);n.data.replace(s,l),this.style.updateImage(e,n)},a.prototype.hasImage=function(e){return e?!!this.style.getImage(e):(this.fire(new t.ErrorEvent(new Error(\"Missing required image id\"))),!1)},a.prototype.removeImage=function(t){this.style.removeImage(t)},a.prototype.loadImage=function(e,r){t.getImage(this._requestManager.transformRequest(e,t.ResourceType.Image),r)},a.prototype.listImages=function(){return this.style.listImages()},a.prototype.addLayer=function(t,e){return this.style.addLayer(t,e),this._update(!0)},a.prototype.moveLayer=function(t,e){return this.style.moveLayer(t,e),this._update(!0)},a.prototype.removeLayer=function(t){return this.style.removeLayer(t),this._update(!0)},a.prototype.getLayer=function(t){return this.style.getLayer(t)},a.prototype.setFilter=function(t,e,r){return void 0===r&&(r={}),this.style.setFilter(t,e,r),this._update(!0)},a.prototype.setLayerZoomRange=function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0)},a.prototype.getFilter=function(t){return this.style.getFilter(t)},a.prototype.setPaintProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setPaintProperty(t,e,r,n),this._update(!0)},a.prototype.getPaintProperty=function(t,e){return this.style.getPaintProperty(t,e)},a.prototype.setLayoutProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setLayoutProperty(t,e,r,n),this._update(!0)},a.prototype.getLayoutProperty=function(t,e){return this.style.getLayoutProperty(t,e)},a.prototype.setLight=function(t,e){return void 0===e&&(e={}),this.style.setLight(t,e),this._update(!0)},a.prototype.getLight=function(){return this.style.getLight()},a.prototype.setFeatureState=function(t,e){return this.style.setFeatureState(t,e),this._update()},a.prototype.removeFeatureState=function(t,e){return this.style.removeFeatureState(t,e),this._update()},a.prototype.getFeatureState=function(t){return this.style.getFeatureState(t)},a.prototype.getContainer=function(){return this._container},a.prototype.getCanvasContainer=function(){return this._canvasContainer},a.prototype.getCanvas=function(){return this._canvas},a.prototype._containerDimensions=function(){var t=0,e=0;return this._container&&(t=this._container.clientWidth||400,e=this._container.clientHeight||300),[t,e]},a.prototype._detectMissingCSS=function(){\"rgb(250, 128, 114)\"!==t.window.getComputedStyle(this._missingCSSCanary).getPropertyValue(\"background-color\")&&t.warnOnce(\"This page appears to be missing CSS declarations for Mapbox GL JS, which may cause the map to display incorrectly. Please ensure your page includes mapbox-gl.css, as described in https://www.mapbox.com/mapbox-gl-js/api/.\")},a.prototype._setupContainer=function(){var t=this._container;t.classList.add(\"mapboxgl-map\"),(this._missingCSSCanary=r.create(\"div\",\"mapboxgl-canary\",t)).style.visibility=\"hidden\",this._detectMissingCSS();var e=this._canvasContainer=r.create(\"div\",\"mapboxgl-canvas-container\",t);this._interactive&&e.classList.add(\"mapboxgl-interactive\"),this._canvas=r.create(\"canvas\",\"mapboxgl-canvas\",e),this._canvas.style.position=\"absolute\",this._canvas.addEventListener(\"webglcontextlost\",this._contextLost,!1),this._canvas.addEventListener(\"webglcontextrestored\",this._contextRestored,!1),this._canvas.setAttribute(\"tabindex\",\"0\"),this._canvas.setAttribute(\"aria-label\",\"Map\");var n=this._containerDimensions();this._resizeCanvas(n[0],n[1]);var a=this._controlContainer=r.create(\"div\",\"mapboxgl-control-container\",t),i=this._controlPositions={};[\"top-left\",\"top-right\",\"bottom-left\",\"bottom-right\"].forEach(function(t){i[t]=r.create(\"div\",\"mapboxgl-ctrl-\"+t,a)})},a.prototype._resizeCanvas=function(e,r){var n=t.window.devicePixelRatio||1;this._canvas.width=n*e,this._canvas.height=n*r,this._canvas.style.width=e+\"px\",this._canvas.style.height=r+\"px\"},a.prototype._setupPainter=function(){var r=t.extend({},e.webGLContextAttributes,{failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1}),n=this._canvas.getContext(\"webgl\",r)||this._canvas.getContext(\"experimental-webgl\",r);n?(this.painter=new on(n,this.transform),t.webpSupported.testSupport(n)):this.fire(new t.ErrorEvent(new Error(\"Failed to initialize WebGL\")))},a.prototype._contextLost=function(e){e.preventDefault(),this._frame&&(this._frame.cancel(),this._frame=null),this.fire(new t.Event(\"webglcontextlost\",{originalEvent:e}))},a.prototype._contextRestored=function(e){this._setupPainter(),this.resize(),this._update(),this.fire(new t.Event(\"webglcontextrestored\",{originalEvent:e}))},a.prototype.loaded=function(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()},a.prototype._update=function(t){return this.style?(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this.triggerRepaint(),this):this},a.prototype._requestRenderFrame=function(t){return this._update(),this._renderTaskQueue.add(t)},a.prototype._cancelRenderFrame=function(t){this._renderTaskQueue.remove(t)},a.prototype._render=function(){this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run();var e=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;var r=this.transform.zoom,n=t.browser.now();this.style.zoomHistory.update(r,n);var a=new t.EvaluationParameters(r,{now:n,fadeDuration:this._fadeDuration,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),i=a.crossFadingFactor();1===i&&i===this._crossFadingFactor||(e=!0,this._crossFadingFactor=i),this.style.update(a)}return this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,this._fadeDuration,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:this._fadeDuration}),this.fire(new t.Event(\"render\")),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(new t.Event(\"load\"))),this.style&&(this.style.hasTransitions()||e)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles(),this._sourcesDirty||this._repaint||this._styleDirty||this._placementDirty?this.triggerRepaint():!this.isMoving()&&this.loaded()&&this.fire(new t.Event(\"idle\")),this},a.prototype.remove=function(){this._hash&&this._hash.remove();for(var e=0,r=this._controls;e<r.length;e+=1)r[e].onRemove(this);this._controls=[],this._frame&&(this._frame.cancel(),this._frame=null),this._renderTaskQueue.clear(),this.setStyle(null),void 0!==t.window&&(t.window.removeEventListener(\"resize\",this._onWindowResize,!1),t.window.removeEventListener(\"online\",this._onWindowOnline,!1));var n=this.painter.context.gl.getExtension(\"WEBGL_lose_context\");n&&n.loseContext(),Rn(this._canvasContainer),Rn(this._controlContainer),Rn(this._missingCSSCanary),this._container.classList.remove(\"mapboxgl-map\"),this.fire(new t.Event(\"remove\"))},a.prototype.triggerRepaint=function(){var e=this;this.style&&!this._frame&&(this._frame=t.browser.frame(function(){e._frame=null,e._render()}))},a.prototype._onWindowOnline=function(){this._update()},a.prototype._onWindowResize=function(){this._trackResize&&this.resize()._update()},i.showTileBoundaries.get=function(){return!!this._showTileBoundaries},i.showTileBoundaries.set=function(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())},i.showCollisionBoxes.get=function(){return!!this._showCollisionBoxes},i.showCollisionBoxes.set=function(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,t?this.style._generateCollisionBoxes():this._update())},i.showOverdrawInspector.get=function(){return!!this._showOverdrawInspector},i.showOverdrawInspector.set=function(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())},i.repaint.get=function(){return!!this._repaint},i.repaint.set=function(t){this._repaint!==t&&(this._repaint=t,this.triggerRepaint())},i.vertices.get=function(){return!!this._vertices},i.vertices.set=function(t){this._vertices=t,this._update()},a.prototype._setCacheLimits=function(e,r){t.setCacheLimits(e,r)},i.version.get=function(){return t.version},Object.defineProperties(a.prototype,i),a}(En);function Rn(t){t.parentNode&&t.parentNode.removeChild(t)}var Fn={showCompass:!0,showZoom:!0,visualizePitch:!1},Bn=function(e){var n=this;this.options=t.extend({},Fn,e),this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._container.addEventListener(\"contextmenu\",function(t){return t.preventDefault()}),this.options.showZoom&&(t.bindAll([\"_updateZoomButtons\"],this),this._zoomInButton=this._createButton(\"mapboxgl-ctrl-icon mapboxgl-ctrl-zoom-in\",\"Zoom in\",function(){return n._map.zoomIn()}),this._zoomOutButton=this._createButton(\"mapboxgl-ctrl-icon mapboxgl-ctrl-zoom-out\",\"Zoom out\",function(){return n._map.zoomOut()})),this.options.showCompass&&(t.bindAll([\"_rotateCompassArrow\"],this),this._compass=this._createButton(\"mapboxgl-ctrl-icon mapboxgl-ctrl-compass\",\"Reset bearing to north\",function(){n.options.visualizePitch?n._map.resetNorthPitch():n._map.resetNorth()}),this._compassArrow=r.create(\"span\",\"mapboxgl-ctrl-compass-arrow\",this._compass))};function Nn(e,r,n){if(e=new t.LngLat(e.lng,e.lat),r){var a=new t.LngLat(e.lng-360,e.lat),i=new t.LngLat(e.lng+360,e.lat),o=n.locationPoint(e).distSqr(r);n.locationPoint(a).distSqr(r)<o?e=a:n.locationPoint(i).distSqr(r)<o&&(e=i)}for(;Math.abs(e.lng-n.center.lng)>180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Bn.prototype._updateZoomButtons=function(){var t=this._map.getZoom();t===this._map.getMaxZoom()?this._zoomInButton.classList.add(\"mapboxgl-ctrl-icon-disabled\"):this._zoomInButton.classList.remove(\"mapboxgl-ctrl-icon-disabled\"),t===this._map.getMinZoom()?this._zoomOutButton.classList.add(\"mapboxgl-ctrl-icon-disabled\"):this._zoomOutButton.classList.remove(\"mapboxgl-ctrl-icon-disabled\")},Bn.prototype._rotateCompassArrow=function(){var t=this.options.visualizePitch?\"scale(\"+1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)+\") rotateX(\"+this._map.transform.pitch+\"deg) rotateZ(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\":\"rotate(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\";this._compassArrow.style.transform=t},Bn.prototype.onAdd=function(t){return this._map=t,this.options.showZoom&&(this._map.on(\"zoom\",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this.options.visualizePitch&&this._map.on(\"pitch\",this._rotateCompassArrow),this._map.on(\"rotate\",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new xn(t,{button:\"left\",element:this._compass}),r.addEventListener(this._compass,\"mousedown\",this._handler.onMouseDown),r.addEventListener(this._compass,\"touchstart\",this._handler.onMouseDown,{passive:!1}),this._handler.enable()),this._container},Bn.prototype.onRemove=function(){r.remove(this._container),this.options.showZoom&&this._map.off(\"zoom\",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off(\"pitch\",this._rotateCompassArrow),this._map.off(\"rotate\",this._rotateCompassArrow),r.removeEventListener(this._compass,\"mousedown\",this._handler.onMouseDown),r.removeEventListener(this._compass,\"touchstart\",this._handler.onMouseDown,{passive:!1}),this._handler.disable(),delete this._handler),delete this._map},Bn.prototype._createButton=function(t,e,n){var a=r.create(\"button\",t,this._container);return a.type=\"button\",a.title=e,a.setAttribute(\"aria-label\",e),a.addEventListener(\"click\",n),a};var jn={center:\"translate(-50%,-50%)\",top:\"translate(-50%,0)\",\"top-left\":\"translate(0,0)\",\"top-right\":\"translate(-100%,0)\",bottom:\"translate(-50%,-100%)\",\"bottom-left\":\"translate(0,-100%)\",\"bottom-right\":\"translate(-100%,-100%)\",left:\"translate(0,-50%)\",right:\"translate(-100%,-50%)\"};function Vn(t,e,r){var n=t.classList;for(var a in jn)n.remove(\"mapboxgl-\"+r+\"-anchor-\"+a);n.add(\"mapboxgl-\"+r+\"-anchor-\"+e)}var Un,qn=function(e){function n(n,a){if(e.call(this),(n instanceof t.window.HTMLElement||a)&&(n=t.extend({element:n},a)),t.bindAll([\"_update\",\"_onMove\",\"_onUp\",\"_addDragHandler\",\"_onMapClick\"],this),this._anchor=n&&n.anchor||\"center\",this._color=n&&n.color||\"#3FB1CE\",this._draggable=n&&n.draggable||!1,this._state=\"inactive\",n&&n.element)this._element=n.element,this._offset=t.Point.convert(n&&n.offset||[0,0]);else{this._defaultMarker=!0,this._element=r.create(\"div\");var i=r.createNS(\"http://www.w3.org/2000/svg\",\"svg\");i.setAttributeNS(null,\"display\",\"block\"),i.setAttributeNS(null,\"height\",\"41px\"),i.setAttributeNS(null,\"width\",\"27px\"),i.setAttributeNS(null,\"viewBox\",\"0 0 27 41\");var o=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");o.setAttributeNS(null,\"stroke\",\"none\"),o.setAttributeNS(null,\"stroke-width\",\"1\"),o.setAttributeNS(null,\"fill\",\"none\"),o.setAttributeNS(null,\"fill-rule\",\"evenodd\");var s=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");s.setAttributeNS(null,\"fill-rule\",\"nonzero\");var l=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");l.setAttributeNS(null,\"transform\",\"translate(3.0, 29.0)\"),l.setAttributeNS(null,\"fill\",\"#000000\");for(var c=0,u=[{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"9.5\",ry:\"4.77275007\"},{rx:\"8.5\",ry:\"4.29549936\"},{rx:\"7.5\",ry:\"3.81822308\"},{rx:\"6.5\",ry:\"3.34094679\"},{rx:\"5.5\",ry:\"2.86367051\"},{rx:\"4.5\",ry:\"2.38636864\"}];c<u.length;c+=1){var h=u[c],f=r.createNS(\"http://www.w3.org/2000/svg\",\"ellipse\");f.setAttributeNS(null,\"opacity\",\"0.04\"),f.setAttributeNS(null,\"cx\",\"10.5\"),f.setAttributeNS(null,\"cy\",\"5.80029008\"),f.setAttributeNS(null,\"rx\",h.rx),f.setAttributeNS(null,\"ry\",h.ry),l.appendChild(f)}var p=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");p.setAttributeNS(null,\"fill\",this._color);var d=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");d.setAttributeNS(null,\"d\",\"M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z\"),p.appendChild(d);var g=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");g.setAttributeNS(null,\"opacity\",\"0.25\"),g.setAttributeNS(null,\"fill\",\"#000000\");var v=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");v.setAttributeNS(null,\"d\",\"M13.5,0 C6.0441559,0 0,6.0441559 0,13.5 C0,19.222562 6.7499993,27 12.25,34.5 C13,35.522727 14.016664,35.500004 14.75,34.5 C20.250001,27 27,19.074644 27,13.5 C27,6.0441559 20.955844,0 13.5,0 Z M13.5,1 C20.415404,1 26,6.584596 26,13.5 C26,15.898657 24.495584,19.181431 22.220703,22.738281 C19.945823,26.295132 16.705119,30.142167 13.943359,33.908203 C13.743445,34.180814 13.612715,34.322738 13.5,34.441406 C13.387285,34.322738 13.256555,34.180814 13.056641,33.908203 C10.284481,30.127985 7.4148684,26.314159 5.015625,22.773438 C2.6163816,19.232715 1,15.953538 1,13.5 C1,6.584596 6.584596,1 13.5,1 Z\"),g.appendChild(v);var m=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");m.setAttributeNS(null,\"transform\",\"translate(6.0, 7.0)\"),m.setAttributeNS(null,\"fill\",\"#FFFFFF\");var y=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");y.setAttributeNS(null,\"transform\",\"translate(8.0, 8.0)\");var x=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");x.setAttributeNS(null,\"fill\",\"#000000\"),x.setAttributeNS(null,\"opacity\",\"0.25\"),x.setAttributeNS(null,\"cx\",\"5.5\"),x.setAttributeNS(null,\"cy\",\"5.5\"),x.setAttributeNS(null,\"r\",\"5.4999962\");var b=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");b.setAttributeNS(null,\"fill\",\"#FFFFFF\"),b.setAttributeNS(null,\"cx\",\"5.5\"),b.setAttributeNS(null,\"cy\",\"5.5\"),b.setAttributeNS(null,\"r\",\"5.4999962\"),y.appendChild(x),y.appendChild(b),s.appendChild(l),s.appendChild(p),s.appendChild(g),s.appendChild(m),s.appendChild(y),i.appendChild(s),this._element.appendChild(i),this._offset=t.Point.convert(n&&n.offset||[0,-14])}this._element.classList.add(\"mapboxgl-marker\"),this._element.addEventListener(\"dragstart\",function(t){t.preventDefault()}),Vn(this._element,this._anchor,\"marker\"),this._popup=null}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._element),t.on(\"move\",this._update),t.on(\"moveend\",this._update),this.setDraggable(this._draggable),this._update(),this._map.on(\"click\",this._onMapClick),this},n.prototype.remove=function(){return this._map&&(this._map.off(\"click\",this._onMapClick),this._map.off(\"move\",this._update),this._map.off(\"moveend\",this._update),this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler),this._map.off(\"mouseup\",this._onUp),this._map.off(\"touchend\",this._onUp),this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),delete this._map),r.remove(this._element),this._popup&&this._popup.remove(),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this},n.prototype.getElement=function(){return this._element},n.prototype.setPopup=function(t){if(this._popup&&(this._popup.remove(),this._popup=null),t){if(!(\"offset\"in t.options)){var e=Math.sqrt(Math.pow(13.5,2)/2);t.options.offset=this._defaultMarker?{top:[0,0],\"top-left\":[0,0],\"top-right\":[0,0],bottom:[0,-38.1],\"bottom-left\":[e,-1*(24.6+e)],\"bottom-right\":[-e,-1*(24.6+e)],left:[13.5,-24.6],right:[-13.5,-24.6]}:this._offset}this._popup=t,this._lngLat&&this._popup.setLngLat(this._lngLat)}return this},n.prototype._onMapClick=function(t){var e=t.originalEvent.target,r=this._element;this._popup&&(e===r||r.contains(e))&&this.togglePopup()},n.prototype.getPopup=function(){return this._popup},n.prototype.togglePopup=function(){var t=this._popup;return t?(t.isOpen()?t.remove():t.addTo(this._map),this):this},n.prototype._update=function(t){this._map&&(this._map.transform.renderWorldCopies&&(this._lngLat=Nn(this._lngLat,this._pos,this._map.transform)),this._pos=this._map.project(this._lngLat)._add(this._offset),t&&\"moveend\"!==t.type||(this._pos=this._pos.round()),r.setTransform(this._element,jn[this._anchor]+\" translate(\"+this._pos.x+\"px, \"+this._pos.y+\"px)\"))},n.prototype.getOffset=function(){return this._offset},n.prototype.setOffset=function(e){return this._offset=t.Point.convert(e),this._update(),this},n.prototype._onMove=function(e){this._pos=e.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents=\"none\",\"pending\"===this._state&&(this._state=\"active\",this.fire(new t.Event(\"dragstart\"))),this.fire(new t.Event(\"drag\"))},n.prototype._onUp=function(){this._element.style.pointerEvents=\"auto\",this._positionDelta=null,this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),\"active\"===this._state&&this.fire(new t.Event(\"dragend\")),this._state=\"inactive\"},n.prototype._addDragHandler=function(t){this._element.contains(t.originalEvent.target)&&(t.preventDefault(),this._positionDelta=t.point.sub(this._pos).add(this._offset),this._state=\"pending\",this._map.on(\"mousemove\",this._onMove),this._map.on(\"touchmove\",this._onMove),this._map.once(\"mouseup\",this._onUp),this._map.once(\"touchend\",this._onUp))},n.prototype.setDraggable=function(t){return this._draggable=!!t,this._map&&(t?(this._map.on(\"mousedown\",this._addDragHandler),this._map.on(\"touchstart\",this._addDragHandler)):(this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler))),this},n.prototype.isDraggable=function(){return this._draggable},n}(t.Evented),Hn={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showUserLocation:!0},Gn=function(e){function n(r){e.call(this),this.options=t.extend({},Hn,r),t.bindAll([\"_onSuccess\",\"_onError\",\"_finish\",\"_setupUI\",\"_updateCamera\",\"_updateMarker\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.onAdd=function(e){var n;return this._map=e,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),n=this._setupUI,void 0!==Un?n(Un):void 0!==t.window.navigator.permissions?t.window.navigator.permissions.query({name:\"geolocation\"}).then(function(t){Un=\"denied\"!==t.state,n(Un)}):(Un=!!t.window.navigator.geolocation,n(Un)),this._container},n.prototype.onRemove=function(){void 0!==this._geolocationWatchID&&(t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),r.remove(this._container),this._map=void 0},n.prototype._onSuccess=function(e){if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\")}this.options.showUserLocation&&\"OFF\"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&\"ACTIVE_LOCK\"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"geolocate\",e)),this._finish()},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,a=this._map.getBearing(),i=t.extend({bearing:a},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),i,{geolocateSource:!0})},n.prototype._updateMarker=function(t){t?this._userLocationDotMarker.setLngLat([t.coords.longitude,t.coords.latitude]).addTo(this._map):this._userLocationDotMarker.remove()},n.prototype._onError=function(e){if(this.options.trackUserLocation)if(1===e.code)this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),void 0!==this._geolocationWatchID&&this._clearWatch();else switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\")}\"OFF\"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"error\",e)),this._finish()},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;!1!==e?(this._container.addEventListener(\"contextmenu\",function(t){return t.preventDefault()}),this._geolocateButton=r.create(\"button\",\"mapboxgl-ctrl-icon mapboxgl-ctrl-geolocate\",this._container),this._geolocateButton.type=\"button\",this._geolocateButton.setAttribute(\"aria-label\",\"Geolocate\"),this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=r.create(\"div\",\"mapboxgl-user-location-dot\"),this._userLocationDotMarker=new qn(this._dotElement),this.options.trackUserLocation&&(this._watchState=\"OFF\")),this._geolocateButton.addEventListener(\"click\",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",function(e){e.geolocateSource||\"ACTIVE_LOCK\"!==n._watchState||(n._watchState=\"BACKGROUND\",n._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\"),n._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),n.fire(new t.Event(\"trackuserlocationend\")))})):t.warnOnce(\"Geolocation support is not available, the GeolocateControl will not be visible.\")},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new t.Event(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this.fire(new t.Event(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event(\"trackuserlocationstart\"))}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"BACKGROUND\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break;case\"BACKGROUND_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\")}\"OFF\"===this._watchState&&void 0!==this._geolocationWatchID?this._clearWatch():void 0===this._geolocationWatchID&&(this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,this.options.positionOptions))}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Yn={maxWidth:100,unit:\"metric\"},Wn=function(e){this.options=t.extend({},Yn,e),t.bindAll([\"_onMove\",\"setUnit\"],this)};function Xn(t,e,r){var n,a,i,o,s,l,c=r&&r.maxWidth||100,u=t._container.clientHeight/2,h=(n=t.unproject([0,u]),a=t.unproject([c,u]),i=Math.PI/180,o=n.lat*i,s=a.lat*i,l=Math.sin(o)*Math.sin(s)+Math.cos(o)*Math.cos(s)*Math.cos((a.lng-n.lng)*i),6371e3*Math.acos(Math.min(l,1)));if(r&&\"imperial\"===r.unit){var f=3.2808*h;f>5280?Zn(e,c,f/5280,\"mi\"):Zn(e,c,f,\"ft\")}else r&&\"nautical\"===r.unit?Zn(e,c,h/1852,\"nm\"):Zn(e,c,h,\"m\")}function Zn(t,e,r,n){var a,i,o,s=(a=r,(i=Math.pow(10,(\"\"+Math.floor(a)).length-1))*(o=(o=a/i)>=10?10:o>=5?5:o>=3?3:o>=2?2:o>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(o))),l=s/r;\"m\"===n&&s>=1e3&&(s/=1e3,n=\"km\"),t.style.width=e*l+\"px\",t.innerHTML=s+n}Wn.prototype.getDefaultPosition=function(){return\"bottom-left\"},Wn.prototype._onMove=function(){Xn(this._map,this._container,this.options)},Wn.prototype.onAdd=function(t){return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-scale\",t.getContainer()),this._map.on(\"move\",this._onMove),this._onMove(),this._container},Wn.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"move\",this._onMove),this._map=void 0},Wn.prototype.setUnit=function(t){this.options.unit=t,Xn(this._map,this._container,this.options)};var Jn=function(e){this._fullscreen=!1,e&&e.container&&(e.container instanceof t.window.HTMLElement?this._container=e.container:t.warnOnce(\"Full screen control 'container' must be a DOM element.\")),t.bindAll([\"_onClickFullscreen\",\"_changeIcon\"],this),\"onfullscreenchange\"in t.window.document?this._fullscreenchange=\"fullscreenchange\":\"onmozfullscreenchange\"in t.window.document?this._fullscreenchange=\"mozfullscreenchange\":\"onwebkitfullscreenchange\"in t.window.document?this._fullscreenchange=\"webkitfullscreenchange\":\"onmsfullscreenchange\"in t.window.document&&(this._fullscreenchange=\"MSFullscreenChange\"),this._className=\"mapboxgl-ctrl\"};Jn.prototype.onAdd=function(e){return this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create(\"div\",this._className+\" mapboxgl-ctrl-group\"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display=\"none\",t.warnOnce(\"This device does not support fullscreen mode.\")),this._controlContainer},Jn.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},Jn.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},Jn.prototype._setupUI=function(){(this._fullscreenButton=r.create(\"button\",this._className+\"-icon \"+this._className+\"-fullscreen\",this._controlContainer)).type=\"button\",this._updateTitle(),this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),t.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},Jn.prototype._updateTitle=function(){var t=this._isFullscreen()?\"Exit fullscreen\":\"Enter fullscreen\";this._fullscreenButton.setAttribute(\"aria-label\",t),this._fullscreenButton.title=t},Jn.prototype._isFullscreen=function(){return this._fullscreen},Jn.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(this._className+\"-shrink\"),this._fullscreenButton.classList.toggle(this._className+\"-fullscreen\"),this._updateTitle())},Jn.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var Kn={closeButton:!0,closeOnClick:!0,className:\"\",maxWidth:\"240px\"},Qn=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(Kn),r),t.bindAll([\"_update\",\"_onClickClose\",\"remove\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(e){var r=this;return this._map=e,this.options.closeOnClick&&this._map.on(\"click\",this._onClickClose),this._map.on(\"remove\",this.remove),this._update(),this._trackPointer?(this._map.on(\"mousemove\",function(t){r._update(t.point)}),this._map.on(\"mouseup\",function(t){r._update(t.point)}),this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")):this._map.on(\"move\",this._update),this.fire(new t.Event(\"open\")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"click\",this._onClickClose),this._map.off(\"remove\",this.remove),this._map.off(\"mousemove\"),delete this._map),this.fire(new t.Event(\"close\")),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on(\"move\",this._update),this._map.off(\"mousemove\"),this._container.classList.remove(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.remove(\"mapboxgl-track-pointer\")),this},n.prototype.trackPointer=function(){var t=this;return this._trackPointer=!0,this._pos=null,this._map&&(this._map.off(\"move\",this._update),this._map.on(\"mousemove\",function(e){t._update(e.point)}),this._map.on(\"drag\",function(e){t._update(e.point)}),this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")),this},n.prototype.getElement=function(){return this._container},n.prototype.setText=function(e){return this.setDOMContent(t.window.document.createTextNode(e))},n.prototype.setHTML=function(e){var r,n=t.window.document.createDocumentFragment(),a=t.window.document.createElement(\"body\");for(a.innerHTML=e;r=a.firstChild;)n.appendChild(r);return this.setDOMContent(n)},n.prototype.getMaxWidth=function(){return this._container.style.maxWidth},n.prototype.setMaxWidth=function(t){return this.options.maxWidth=t,this._update(),this},n.prototype.setDOMContent=function(t){return this._createContent(),this._content.appendChild(t),this._update(),this},n.prototype._createContent=function(){this._content&&r.remove(this._content),this._content=r.create(\"div\",\"mapboxgl-popup-content\",this._container),this.options.closeButton&&(this._closeButton=r.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.setAttribute(\"aria-label\",\"Close popup\"),this._closeButton.innerHTML=\"&#215;\",this._closeButton.addEventListener(\"click\",this._onClickClose))},n.prototype._update=function(e){var n=this,a=this._lngLat||this._trackPointer;if(this._map&&a&&this._content&&(this._container||(this._container=r.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=r.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(\" \").forEach(function(t){return n._container.classList.add(t)})),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=Nn(this._lngLat,this._pos,this._map.transform)),!this._trackPointer||e)){var i=this._pos=this._trackPointer&&e?e:this._map.project(this._lngLat),o=this.options.anchor,s=function e(r){if(r){if(\"number\"==typeof r){var n=Math.round(Math.sqrt(.5*Math.pow(r,2)));return{center:new t.Point(0,0),top:new t.Point(0,r),\"top-left\":new t.Point(n,n),\"top-right\":new t.Point(-n,n),bottom:new t.Point(0,-r),\"bottom-left\":new t.Point(n,-n),\"bottom-right\":new t.Point(-n,-n),left:new t.Point(r,0),right:new t.Point(-r,0)}}if(r instanceof t.Point||Array.isArray(r)){var a=t.Point.convert(r);return{center:a,top:a,\"top-left\":a,\"top-right\":a,bottom:a,\"bottom-left\":a,\"bottom-right\":a,left:a,right:a}}return{center:t.Point.convert(r.center||[0,0]),top:t.Point.convert(r.top||[0,0]),\"top-left\":t.Point.convert(r[\"top-left\"]||[0,0]),\"top-right\":t.Point.convert(r[\"top-right\"]||[0,0]),bottom:t.Point.convert(r.bottom||[0,0]),\"bottom-left\":t.Point.convert(r[\"bottom-left\"]||[0,0]),\"bottom-right\":t.Point.convert(r[\"bottom-right\"]||[0,0]),left:t.Point.convert(r.left||[0,0]),right:t.Point.convert(r.right||[0,0])}}return e(new t.Point(0,0))}(this.options.offset);if(!o){var l,c=this._container.offsetWidth,u=this._container.offsetHeight;l=i.y+s.bottom.y<u?[\"top\"]:i.y>this._map.transform.height-u?[\"bottom\"]:[],i.x<c/2?l.push(\"left\"):i.x>this._map.transform.width-c/2&&l.push(\"right\"),o=0===l.length?\"bottom\":l.join(\"-\")}var h=i.add(s[o]).round();r.setTransform(this._container,jn[o]+\" translate(\"+h.x+\"px,\"+h.y+\"px)\"),Vn(this._container,o,\"popup\")}},n.prototype._onClickClose=function(){this.remove()},n}(t.Evented),$n={version:t.version,supported:e,setRTLTextPlugin:t.setRTLTextPlugin,Map:Dn,NavigationControl:Bn,GeolocateControl:Gn,AttributionControl:Ln,ScaleControl:Wn,FullscreenControl:Jn,Popup:Qn,Marker:qn,Style:Re,LngLat:t.LngLat,LngLatBounds:t.LngLatBounds,Point:t.Point,MercatorCoordinate:t.MercatorCoordinate,Evented:t.Evented,config:t.config,get accessToken(){return t.config.ACCESS_TOKEN},set accessToken(e){t.config.ACCESS_TOKEN=e},get baseApiUrl(){return t.config.API_URL},set baseApiUrl(e){t.config.API_URL=e},get workerCount(){return It.workerCount},set workerCount(t){It.workerCount=t},get maxParallelImageRequests(){return t.config.MAX_PARALLEL_IMAGE_REQUESTS},set maxParallelImageRequests(e){t.config.MAX_PARALLEL_IMAGE_REQUESTS=e},clearStorage:function(e){t.clearTileCache(e)},workerUrl:\"\"};return $n}),r},\"object\"==typeof r&&\"undefined\"!=typeof e?e.exports=a():(n=n||self).mapboxgl=a()},{}],429:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=1<<t+1,r=new Array(e),n=0;n<e;++n)r[n]=i(t,n);return r};var n=t(\"convex-hull\");function a(t,e,r){for(var n=new Array(t),a=0;a<t;++a)n[a]=0,a===e&&(n[a]+=.5),a===r&&(n[a]+=.5);return n}function i(t,e){if(0===e||e===(1<<t+1)-1)return[];for(var r=[],i=[],o=0;o<=t;++o)if(e&1<<o){r.push(a(t,o-1,o-1)),i.push(null);for(var s=0;s<=t;++s)~e&1<<s&&(r.push(a(t,o-1,s-1)),i.push([o,s]))}var l=n(r),c=[];t:for(o=0;o<l.length;++o){var u=l[o],h=[];for(s=0;s<u.length;++s){if(!i[u[s]])continue t;h.push(i[u[s]].slice())}c.push(h)}return c}},{\"convex-hull\":132}],430:[function(t,e,r){var n=t(\"./normalize\"),a=t(\"gl-mat4/create\"),i=t(\"gl-mat4/clone\"),o=t(\"gl-mat4/determinant\"),s=t(\"gl-mat4/invert\"),l=t(\"gl-mat4/transpose\"),c={length:t(\"gl-vec3/length\"),normalize:t(\"gl-vec3/normalize\"),dot:t(\"gl-vec3/dot\"),cross:t(\"gl-vec3/cross\")},u=a(),h=a(),f=[0,0,0,0],p=[[0,0,0],[0,0,0],[0,0,0]],d=[0,0,0];function g(t,e,r,n,a){t[0]=e[0]*n+r[0]*a,t[1]=e[1]*n+r[1]*a,t[2]=e[2]*n+r[2]*a}e.exports=function(t,e,r,a,v,m){if(e||(e=[0,0,0]),r||(r=[0,0,0]),a||(a=[0,0,0]),v||(v=[0,0,0,1]),m||(m=[0,0,0,1]),!n(u,t))return!1;if(i(h,u),h[3]=0,h[7]=0,h[11]=0,h[15]=1,Math.abs(o(h)<1e-8))return!1;var y,x,b,_,w,k,T,M=u[3],A=u[7],S=u[11],E=u[12],L=u[13],C=u[14],P=u[15];if(0!==M||0!==A||0!==S){if(f[0]=M,f[1]=A,f[2]=S,f[3]=P,!s(h,h))return!1;l(h,h),y=v,b=h,_=(x=f)[0],w=x[1],k=x[2],T=x[3],y[0]=b[0]*_+b[4]*w+b[8]*k+b[12]*T,y[1]=b[1]*_+b[5]*w+b[9]*k+b[13]*T,y[2]=b[2]*_+b[6]*w+b[10]*k+b[14]*T,y[3]=b[3]*_+b[7]*w+b[11]*k+b[15]*T}else v[0]=v[1]=v[2]=0,v[3]=1;if(e[0]=E,e[1]=L,e[2]=C,function(t,e){t[0][0]=e[0],t[0][1]=e[1],t[0][2]=e[2],t[1][0]=e[4],t[1][1]=e[5],t[1][2]=e[6],t[2][0]=e[8],t[2][1]=e[9],t[2][2]=e[10]}(p,u),r[0]=c.length(p[0]),c.normalize(p[0],p[0]),a[0]=c.dot(p[0],p[1]),g(p[1],p[1],p[0],1,-a[0]),r[1]=c.length(p[1]),c.normalize(p[1],p[1]),a[0]/=r[1],a[1]=c.dot(p[0],p[2]),g(p[2],p[2],p[0],1,-a[1]),a[2]=c.dot(p[1],p[2]),g(p[2],p[2],p[1],1,-a[2]),r[2]=c.length(p[2]),c.normalize(p[2],p[2]),a[1]/=r[2],a[2]/=r[2],c.cross(d,p[1],p[2]),c.dot(p[0],d)<0)for(var O=0;O<3;O++)r[O]*=-1,p[O][0]*=-1,p[O][1]*=-1,p[O][2]*=-1;return m[0]=.5*Math.sqrt(Math.max(1+p[0][0]-p[1][1]-p[2][2],0)),m[1]=.5*Math.sqrt(Math.max(1-p[0][0]+p[1][1]-p[2][2],0)),m[2]=.5*Math.sqrt(Math.max(1-p[0][0]-p[1][1]+p[2][2],0)),m[3]=.5*Math.sqrt(Math.max(1+p[0][0]+p[1][1]+p[2][2],0)),p[2][1]>p[1][2]&&(m[0]=-m[0]),p[0][2]>p[2][0]&&(m[1]=-m[1]),p[1][0]>p[0][1]&&(m[2]=-m[2]),!0}},{\"./normalize\":431,\"gl-mat4/clone\":262,\"gl-mat4/create\":263,\"gl-mat4/determinant\":264,\"gl-mat4/invert\":268,\"gl-mat4/transpose\":279,\"gl-vec3/cross\":336,\"gl-vec3/dot\":341,\"gl-vec3/length\":351,\"gl-vec3/normalize\":358}],431:[function(t,e,r){e.exports=function(t,e){var r=e[15];if(0===r)return!1;for(var n=1/r,a=0;a<16;a++)t[a]=e[a]*n;return!0}},{}],432:[function(t,e,r){var n=t(\"gl-vec3/lerp\"),a=t(\"mat4-recompose\"),i=t(\"mat4-decompose\"),o=t(\"gl-mat4/determinant\"),s=t(\"quat-slerp\"),l=h(),c=h(),u=h();function h(){return{translate:f(),scale:f(1),skew:f(),perspective:[0,0,0,1],quaternion:[0,0,0,1]}}function f(t){return[t||0,t||0,t||0]}e.exports=function(t,e,r,h){if(0===o(e)||0===o(r))return!1;var f=i(e,l.translate,l.scale,l.skew,l.perspective,l.quaternion),p=i(r,c.translate,c.scale,c.skew,c.perspective,c.quaternion);return!(!f||!p||(n(u.translate,l.translate,c.translate,h),n(u.skew,l.skew,c.skew,h),n(u.scale,l.scale,c.scale,h),n(u.perspective,l.perspective,c.perspective,h),s(u.quaternion,l.quaternion,c.quaternion,h),a(t,u.translate,u.scale,u.skew,u.perspective,u.quaternion),0))}},{\"gl-mat4/determinant\":264,\"gl-vec3/lerp\":352,\"mat4-decompose\":430,\"mat4-recompose\":433,\"quat-slerp\":485}],433:[function(t,e,r){var n={identity:t(\"gl-mat4/identity\"),translate:t(\"gl-mat4/translate\"),multiply:t(\"gl-mat4/multiply\"),create:t(\"gl-mat4/create\"),scale:t(\"gl-mat4/scale\"),fromRotationTranslation:t(\"gl-mat4/fromRotationTranslation\")},a=(n.create(),n.create());e.exports=function(t,e,r,i,o,s){return n.identity(t),n.fromRotationTranslation(t,s,e),t[3]=o[0],t[7]=o[1],t[11]=o[2],t[15]=o[3],n.identity(a),0!==i[2]&&(a[9]=i[2],n.multiply(t,t,a)),0!==i[1]&&(a[9]=0,a[8]=i[1],n.multiply(t,t,a)),0!==i[0]&&(a[8]=0,a[4]=i[0],n.multiply(t,t,a)),n.scale(t,t,r),t}},{\"gl-mat4/create\":263,\"gl-mat4/fromRotationTranslation\":266,\"gl-mat4/identity\":267,\"gl-mat4/multiply\":270,\"gl-mat4/scale\":277,\"gl-mat4/translate\":278}],434:[function(t,e,r){\"use strict\";e.exports=Math.log2||function(t){return Math.log(t)*Math.LOG2E}},{}],435:[function(t,e,r){\"use strict\";var n=t(\"binary-search-bounds\"),a=t(\"mat4-interpolate\"),i=t(\"gl-mat4/invert\"),o=t(\"gl-mat4/rotateX\"),s=t(\"gl-mat4/rotateY\"),l=t(\"gl-mat4/rotateZ\"),c=t(\"gl-mat4/lookAt\"),u=t(\"gl-mat4/translate\"),h=(t(\"gl-mat4/scale\"),t(\"gl-vec3/normalize\")),f=[0,0,0];function p(t){this._components=t.slice(),this._time=[0],this.prevMatrix=t.slice(),this.nextMatrix=t.slice(),this.computedMatrix=t.slice(),this.computedInverse=t.slice(),this.computedEye=[0,0,0],this.computedUp=[0,0,0],this.computedCenter=[0,0,0],this.computedRadius=[0],this._limits=[-1/0,1/0]}e.exports=function(t){return new p((t=t||{}).matrix||[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1])};var d=p.prototype;d.recalcMatrix=function(t){var e=this._time,r=n.le(e,t),o=this.computedMatrix;if(!(r<0)){var s=this._components;if(r===e.length-1)for(var l=16*r,c=0;c<16;++c)o[c]=s[l++];else{var u=e[r+1]-e[r],f=(l=16*r,this.prevMatrix),p=!0;for(c=0;c<16;++c)f[c]=s[l++];var d=this.nextMatrix;for(c=0;c<16;++c)d[c]=s[l++],p=p&&f[c]===d[c];if(u<1e-6||p)for(c=0;c<16;++c)o[c]=f[c];else a(o,f,d,(t-e[r])/u)}var g=this.computedUp;g[0]=o[1],g[1]=o[5],g[2]=o[9],h(g,g);var v=this.computedInverse;i(v,o);var m=this.computedEye,y=v[15];m[0]=v[12]/y,m[1]=v[13]/y,m[2]=v[14]/y;var x=this.computedCenter,b=Math.exp(this.computedRadius[0]);for(c=0;c<3;++c)x[c]=m[c]-o[2+4*c]*b}},d.idle=function(t){if(!(t<this.lastT())){for(var e=this._components,r=e.length-16,n=0;n<16;++n)e.push(e[r++]);this._time.push(t)}},d.flush=function(t){var e=n.gt(this._time,t)-2;e<0||(this._time.splice(0,e),this._components.splice(0,16*e))},d.lastT=function(){return this._time[this._time.length-1]},d.lookAt=function(t,e,r,n){this.recalcMatrix(t),e=e||this.computedEye,r=r||f,n=n||this.computedUp,this.setMatrix(t,c(this.computedMatrix,e,r,n));for(var a=0,i=0;i<3;++i)a+=Math.pow(r[i]-e[i],2);a=Math.log(Math.sqrt(a)),this.computedRadius[0]=a},d.rotate=function(t,e,r,n){this.recalcMatrix(t);var a=this.computedInverse;e&&s(a,a,e),r&&o(a,a,r),n&&l(a,a,n),this.setMatrix(t,i(this.computedMatrix,a))};var g=[0,0,0];d.pan=function(t,e,r,n){g[0]=-(e||0),g[1]=-(r||0),g[2]=-(n||0),this.recalcMatrix(t);var a=this.computedInverse;u(a,a,g),this.setMatrix(t,i(a,a))},d.translate=function(t,e,r,n){g[0]=e||0,g[1]=r||0,g[2]=n||0,this.recalcMatrix(t);var a=this.computedMatrix;u(a,a,g),this.setMatrix(t,a)},d.setMatrix=function(t,e){if(!(t<this.lastT())){this._time.push(t);for(var r=0;r<16;++r)this._components.push(e[r])}},d.setDistance=function(t,e){this.computedRadius[0]=e},d.setDistanceLimits=function(t,e){var r=this._limits;r[0]=t,r[1]=e},d.getDistanceLimits=function(t){var e=this._limits;return t?(t[0]=e[0],t[1]=e[1],t):e}},{\"binary-search-bounds\":93,\"gl-mat4/invert\":268,\"gl-mat4/lookAt\":269,\"gl-mat4/rotateX\":274,\"gl-mat4/rotateY\":275,\"gl-mat4/rotateZ\":276,\"gl-mat4/scale\":277,\"gl-mat4/translate\":278,\"gl-vec3/normalize\":358,\"mat4-interpolate\":432}],436:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.length;if(e<3){for(var r=new Array(e),a=0;a<e;++a)r[a]=a;return 2===e&&t[0][0]===t[1][0]&&t[0][1]===t[1][1]?[0]:r}for(var i=new Array(e),a=0;a<e;++a)i[a]=a;i.sort(function(e,r){var n=t[e][0]-t[r][0];return n||t[e][1]-t[r][1]});for(var o=[i[0],i[1]],s=[i[0],i[1]],a=2;a<e;++a){for(var l=i[a],c=t[l],u=o.length;u>1&&n(t[o[u-2]],t[o[u-1]],c)<=0;)u-=1,o.pop();for(o.push(l),u=s.length;u>1&&n(t[s[u-2]],t[s[u-1]],c)>=0;)u-=1,s.pop();s.push(l)}for(var r=new Array(s.length+o.length-2),h=0,a=0,f=o.length;a<f;++a)r[h++]=o[a];for(var p=s.length-2;p>0;--p)r[h++]=s[p];return r};var n=t(\"robust-orientation\")[3]},{\"robust-orientation\":509}],437:[function(t,e,r){\"use strict\";e.exports=function(t,e){e||(e=t,t=window);var r=0,a=0,i=0,o={shift:!1,alt:!1,control:!1,meta:!1},s=!1;function l(t){var e=!1;return\"altKey\"in t&&(e=e||t.altKey!==o.alt,o.alt=!!t.altKey),\"shiftKey\"in t&&(e=e||t.shiftKey!==o.shift,o.shift=!!t.shiftKey),\"ctrlKey\"in t&&(e=e||t.ctrlKey!==o.control,o.control=!!t.ctrlKey),\"metaKey\"in t&&(e=e||t.metaKey!==o.meta,o.meta=!!t.metaKey),e}function c(t,s){var c=n.x(s),u=n.y(s);\"buttons\"in s&&(t=0|s.buttons),(t!==r||c!==a||u!==i||l(s))&&(r=0|t,a=c||0,i=u||0,e&&e(r,a,i,o))}function u(t){c(0,t)}function h(){(r||a||i||o.shift||o.alt||o.meta||o.control)&&(a=i=0,r=0,o.shift=o.alt=o.control=o.meta=!1,e&&e(0,0,0,o))}function f(t){l(t)&&e&&e(r,a,i,o)}function p(t){0===n.buttons(t)?c(0,t):c(r,t)}function d(t){c(r|n.buttons(t),t)}function g(t){c(r&~n.buttons(t),t)}function v(){s||(s=!0,t.addEventListener(\"mousemove\",p),t.addEventListener(\"mousedown\",d),t.addEventListener(\"mouseup\",g),t.addEventListener(\"mouseleave\",u),t.addEventListener(\"mouseenter\",u),t.addEventListener(\"mouseout\",u),t.addEventListener(\"mouseover\",u),t.addEventListener(\"blur\",h),t.addEventListener(\"keyup\",f),t.addEventListener(\"keydown\",f),t.addEventListener(\"keypress\",f),t!==window&&(window.addEventListener(\"blur\",h),window.addEventListener(\"keyup\",f),window.addEventListener(\"keydown\",f),window.addEventListener(\"keypress\",f)))}v();var m={element:t};return Object.defineProperties(m,{enabled:{get:function(){return s},set:function(e){e?v():s&&(s=!1,t.removeEventListener(\"mousemove\",p),t.removeEventListener(\"mousedown\",d),t.removeEventListener(\"mouseup\",g),t.removeEventListener(\"mouseleave\",u),t.removeEventListener(\"mouseenter\",u),t.removeEventListener(\"mouseout\",u),t.removeEventListener(\"mouseover\",u),t.removeEventListener(\"blur\",h),t.removeEventListener(\"keyup\",f),t.removeEventListener(\"keydown\",f),t.removeEventListener(\"keypress\",f),t!==window&&(window.removeEventListener(\"blur\",h),window.removeEventListener(\"keyup\",f),window.removeEventListener(\"keydown\",f),window.removeEventListener(\"keypress\",f)))},enumerable:!0},buttons:{get:function(){return r},enumerable:!0},x:{get:function(){return a},enumerable:!0},y:{get:function(){return i},enumerable:!0},mods:{get:function(){return o},enumerable:!0}}),m};var n=t(\"mouse-event\")},{\"mouse-event\":439}],438:[function(t,e,r){var n={left:0,top:0};e.exports=function(t,e,r){e=e||t.currentTarget||t.srcElement,Array.isArray(r)||(r=[0,0]);var a=t.clientX||0,i=t.clientY||0,o=(s=e,s===window||s===document||s===document.body?n:s.getBoundingClientRect());var s;return r[0]=a-o.left,r[1]=i-o.top,r}},{}],439:[function(t,e,r){\"use strict\";function n(t){return t.target||t.srcElement||window}r.buttons=function(t){if(\"object\"==typeof t){if(\"buttons\"in t)return t.buttons;if(\"which\"in t){if(2===(e=t.which))return 4;if(3===e)return 2;if(e>0)return 1<<e-1}else if(\"button\"in t){var e;if(1===(e=t.button))return 4;if(2===e)return 2;if(e>=0)return 1<<e}}return 0},r.element=n,r.x=function(t){if(\"object\"==typeof t){if(\"offsetX\"in t)return t.offsetX;var e=n(t).getBoundingClientRect();return t.clientX-e.left}return 0},r.y=function(t){if(\"object\"==typeof t){if(\"offsetY\"in t)return t.offsetY;var e=n(t).getBoundingClientRect();return t.clientY-e.top}return 0}},{}],440:[function(t,e,r){\"use strict\";var n=t(\"to-px\");e.exports=function(t,e,r){\"function\"==typeof t&&(r=!!e,e=t,t=window);var a=n(\"ex\",t),i=function(t){r&&t.preventDefault();var n=t.deltaX||0,i=t.deltaY||0,o=t.deltaZ||0,s=t.deltaMode,l=1;switch(s){case 1:l=a;break;case 2:l=window.innerHeight}if(i*=l,o*=l,(n*=l)||i||o)return e(n,i,o,t)};return t.addEventListener(\"wheel\",i),i}},{\"to-px\":538}],441:[function(t,e,r){\"use strict\";var n=t(\"typedarray-pool\");function a(t){return\"a\"+t}function i(t){return\"d\"+t}function o(t,e){return\"c\"+t+\"_\"+e}function s(t){return\"s\"+t}function l(t,e){return\"t\"+t+\"_\"+e}function c(t){return\"o\"+t}function u(t){return\"x\"+t}function h(t){return\"p\"+t}function f(t,e){return\"d\"+t+\"_\"+e}function p(t){return\"i\"+t}function d(t,e){return\"u\"+t+\"_\"+e}function g(t){return\"b\"+t}function v(t){return\"y\"+t}function m(t){return\"e\"+t}function y(t){return\"v\"+t}e.exports=function(t){function e(t){throw new Error(\"ndarray-extract-contour: \"+t)}\"object\"!=typeof t&&e(\"Must specify arguments\");var r=t.order;Array.isArray(r)||e(\"Must specify order\");var A=t.arrayArguments||1;A<1&&e(\"Must have at least one array argument\");var S=t.scalarArguments||0;S<0&&e(\"Scalar arg count must be > 0\");\"function\"!=typeof t.vertex&&e(\"Must specify vertex creation function\");\"function\"!=typeof t.cell&&e(\"Must specify cell creation function\");\"function\"!=typeof t.phase&&e(\"Must specify phase function\");for(var E=t.getters||[],L=new Array(A),C=0;C<A;++C)E.indexOf(C)>=0?L[C]=!0:L[C]=!1;return function(t,e,r,A,S,E){var L=E.length,C=S.length;if(C<2)throw new Error(\"ndarray-extract-contour: Dimension must be at least 2\");for(var P=\"extractContour\"+S.join(\"_\"),O=[],z=[],I=[],D=0;D<L;++D)I.push(a(D));for(var D=0;D<A;++D)I.push(u(D));for(var D=0;D<C;++D)z.push(s(D)+\"=\"+a(0)+\".shape[\"+D+\"]|0\");for(var D=0;D<L;++D){z.push(i(D)+\"=\"+a(D)+\".data\",c(D)+\"=\"+a(D)+\".offset|0\");for(var R=0;R<C;++R)z.push(l(D,R)+\"=\"+a(D)+\".stride[\"+R+\"]|0\")}for(var D=0;D<L;++D){z.push(h(D)+\"=\"+c(D)),z.push(o(D,0));for(var R=1;R<1<<C;++R){for(var F=[],B=0;B<C;++B)R&1<<B&&F.push(\"-\"+l(D,B));z.push(f(D,R)+\"=(\"+F.join(\"\")+\")|0\"),z.push(o(D,R)+\"=0\")}}for(var D=0;D<L;++D)for(var R=0;R<C;++R){var N=[l(D,S[R])];R>0&&N.push(l(D,S[R-1])+\"*\"+s(S[R-1])),z.push(d(D,S[R])+\"=(\"+N.join(\"-\")+\")|0\")}for(var D=0;D<C;++D)z.push(p(D)+\"=0\");z.push(_+\"=0\");for(var j=[\"2\"],D=C-2;D>=0;--D)j.push(s(S[D]));z.push(w+\"=(\"+j.join(\"*\")+\")|0\",b+\"=mallocUint32(\"+w+\")\",x+\"=mallocUint32(\"+w+\")\",k+\"=0\"),z.push(g(0)+\"=0\");for(var R=1;R<1<<C;++R){for(var V=[],U=[],B=0;B<C;++B)R&1<<B&&(0===U.length?V.push(\"1\"):V.unshift(U.join(\"*\"))),U.push(s(S[B]));var q=\"\";V[0].indexOf(s(S[C-2]))<0&&(q=\"-\");var H=M(C,R,S);z.push(m(H)+\"=(-\"+V.join(\"-\")+\")|0\",v(H)+\"=(\"+q+V.join(\"-\")+\")|0\",g(H)+\"=0\")}function G(t,e){O.push(\"for(\",p(S[t]),\"=\",e,\";\",p(S[t]),\"<\",s(S[t]),\";\",\"++\",p(S[t]),\"){\")}function Y(t){for(var e=0;e<L;++e)O.push(h(e),\"+=\",d(e,S[t]),\";\");O.push(\"}\")}function W(){for(var t=1;t<1<<C;++t)O.push(T,\"=\",m(t),\";\",m(t),\"=\",v(t),\";\",v(t),\"=\",T,\";\")}z.push(y(0)+\"=0\",T+\"=0\"),function t(e,r){if(e<0)return void function(t){for(var e=0;e<L;++e)E[e]?O.push(o(e,0),\"=\",i(e),\".get(\",h(e),\");\"):O.push(o(e,0),\"=\",i(e),\"[\",h(e),\"];\");for(var r=[],e=0;e<L;++e)r.push(o(e,0));for(var e=0;e<A;++e)r.push(u(e));O.push(g(0),\"=\",b,\"[\",k,\"]=phase(\",r.join(),\");\");for(var n=1;n<1<<C;++n)O.push(g(n),\"=\",b,\"[\",k,\"+\",m(n),\"];\");for(var a=[],n=1;n<1<<C;++n)a.push(\"(\"+g(0)+\"!==\"+g(n)+\")\");O.push(\"if(\",a.join(\"||\"),\"){\");for(var s=[],e=0;e<C;++e)s.push(p(e));for(var e=0;e<L;++e){s.push(o(e,0));for(var n=1;n<1<<C;++n)E[e]?O.push(o(e,n),\"=\",i(e),\".get(\",h(e),\"+\",f(e,n),\");\"):O.push(o(e,n),\"=\",i(e),\"[\",h(e),\"+\",f(e,n),\"];\"),s.push(o(e,n))}for(var e=0;e<1<<C;++e)s.push(g(e));for(var e=0;e<A;++e)s.push(u(e));O.push(\"vertex(\",s.join(),\");\",y(0),\"=\",x,\"[\",k,\"]=\",_,\"++;\");for(var l=(1<<C)-1,c=g(l),n=0;n<C;++n)if(0==(t&~(1<<n))){for(var d=l^1<<n,v=g(d),w=[],T=d;T>0;T=T-1&d)w.push(x+\"[\"+k+\"+\"+m(T)+\"]\");w.push(y(0));for(var T=0;T<L;++T)1&n?w.push(o(T,l),o(T,d)):w.push(o(T,d),o(T,l));1&n?w.push(c,v):w.push(v,c);for(var T=0;T<A;++T)w.push(u(T));O.push(\"if(\",c,\"!==\",v,\"){\",\"face(\",w.join(),\")}\")}O.push(\"}\",k,\"+=1;\")}(r);!function(t){for(var e=t-1;e>=0;--e)G(e,0);for(var r=[],e=0;e<L;++e)E[e]?r.push(i(e)+\".get(\"+h(e)+\")\"):r.push(i(e)+\"[\"+h(e)+\"]\");for(var e=0;e<A;++e)r.push(u(e));O.push(b,\"[\",k,\"++]=phase(\",r.join(),\");\");for(var e=0;e<t;++e)Y(e);for(var n=0;n<L;++n)O.push(h(n),\"+=\",d(n,S[t]),\";\")}(e);O.push(\"if(\",s(S[e]),\">0){\",p(S[e]),\"=1;\");t(e-1,r|1<<S[e]);for(var n=0;n<L;++n)O.push(h(n),\"+=\",d(n,S[e]),\";\");e===C-1&&(O.push(k,\"=0;\"),W());G(e,2);t(e-1,r);e===C-1&&(O.push(\"if(\",p(S[C-1]),\"&1){\",k,\"=0;}\"),W());Y(e);O.push(\"}\")}(C-1,0),O.push(\"freeUint32(\",x,\");freeUint32(\",b,\");\");var X=[\"'use strict';\",\"function \",P,\"(\",I.join(),\"){\",\"var \",z.join(),\";\",O.join(\"\"),\"}\",\"return \",P].join(\"\");return new Function(\"vertex\",\"face\",\"phase\",\"mallocUint32\",\"freeUint32\",X)(t,e,r,n.mallocUint32,n.freeUint32)}(t.vertex,t.cell,t.phase,S,r,L)};var x=\"V\",b=\"P\",_=\"N\",w=\"Q\",k=\"X\",T=\"T\";function M(t,e,r){for(var n=0,a=0;a<t;++a)e&1<<a&&(n|=1<<r[a]);return n}},{\"typedarray-pool\":544}],442:[function(t,e,r){\"use strict\";var n=t(\"cwise/lib/wrapper\")({args:[\"index\",\"array\",\"scalar\"],pre:{body:\"{}\",args:[],thisVars:[],localVars:[]},body:{body:\"{_inline_1_arg1_=_inline_1_arg2_.apply(void 0,_inline_1_arg0_)}\",args:[{name:\"_inline_1_arg0_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_1_arg1_\",lvalue:!0,rvalue:!1,count:1},{name:\"_inline_1_arg2_\",lvalue:!1,rvalue:!0,count:1}],thisVars:[],localVars:[]},post:{body:\"{}\",args:[],thisVars:[],localVars:[]},debug:!1,funcName:\"cwise\",blockSize:64});e.exports=function(t,e){return n(t,e),t}},{\"cwise/lib/wrapper\":151}],443:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){if(Array.isArray(r)){if(r.length!==e.dimension)throw new Error(\"ndarray-gradient: invalid boundary conditions\")}else r=n(e.dimension,\"string\"==typeof r?r:\"clamp\");if(t.dimension!==e.dimension+1)throw new Error(\"ndarray-gradient: output dimension must be +1 input dimension\");if(t.shape[e.dimension]!==e.dimension)throw new Error(\"ndarray-gradient: output shape must match input shape\");for(var a=0;a<e.dimension;++a)if(t.shape[a]!==e.shape[a])throw new Error(\"ndarray-gradient: shape mismatch\");if(0===e.size)return t;if(e.dimension<=0)return t.set(0),t;return function(t){var e=t.join();if(m=o[e])return m;var r=t.length,n=[\"function gradient(dst,src){var s=src.shape.slice();\"];function a(e){for(var a=r-e.length,i=[],o=[],s=[],l=0;l<r;++l)e.indexOf(l+1)>=0?s.push(\"0\"):e.indexOf(-(l+1))>=0?s.push(\"s[\"+l+\"]-1\"):(s.push(\"-1\"),i.push(\"1\"),o.push(\"s[\"+l+\"]-2\"));var c=\".lo(\"+i.join()+\").hi(\"+o.join()+\")\";if(0===i.length&&(c=\"\"),a>0){n.push(\"if(1\");for(var l=0;l<r;++l)e.indexOf(l+1)>=0||e.indexOf(-(l+1))>=0||n.push(\"&&s[\",l,\"]>2\");n.push(\"){grad\",a,\"(src.pick(\",s.join(),\")\",c);for(var l=0;l<r;++l)e.indexOf(l+1)>=0||e.indexOf(-(l+1))>=0||n.push(\",dst.pick(\",s.join(),\",\",l,\")\",c);n.push(\");\")}for(var l=0;l<e.length;++l){var u=Math.abs(e[l])-1,h=\"dst.pick(\"+s.join()+\",\"+u+\")\"+c;switch(t[u]){case\"clamp\":var f=s.slice(),p=s.slice();e[l]<0?f[u]=\"s[\"+u+\"]-2\":p[u]=\"1\",0===a?n.push(\"if(s[\",u,\"]>1){dst.set(\",s.join(),\",\",u,\",0.5*(src.get(\",f.join(),\")-src.get(\",p.join(),\")))}else{dst.set(\",s.join(),\",\",u,\",0)};\"):n.push(\"if(s[\",u,\"]>1){diff(\",h,\",src.pick(\",f.join(),\")\",c,\",src.pick(\",p.join(),\")\",c,\");}else{zero(\",h,\");};\");break;case\"mirror\":0===a?n.push(\"dst.set(\",s.join(),\",\",u,\",0);\"):n.push(\"zero(\",h,\");\");break;case\"wrap\":var d=s.slice(),g=s.slice();e[l]<0?(d[u]=\"s[\"+u+\"]-2\",g[u]=\"0\"):(d[u]=\"s[\"+u+\"]-1\",g[u]=\"1\"),0===a?n.push(\"if(s[\",u,\"]>2){dst.set(\",s.join(),\",\",u,\",0.5*(src.get(\",d.join(),\")-src.get(\",g.join(),\")))}else{dst.set(\",s.join(),\",\",u,\",0)};\"):n.push(\"if(s[\",u,\"]>2){diff(\",h,\",src.pick(\",d.join(),\")\",c,\",src.pick(\",g.join(),\")\",c,\");}else{zero(\",h,\");};\");break;default:throw new Error(\"ndarray-gradient: Invalid boundary condition\")}}a>0&&n.push(\"};\")}for(var s=0;s<1<<r;++s){for(var h=[],f=0;f<r;++f)s&1<<f&&h.push(f+1);for(var p=0;p<1<<h.length;++p){for(var d=h.slice(),f=0;f<h.length;++f)p&1<<f&&(d[f]=-d[f]);a(d)}}n.push(\"return dst;};return gradient\");for(var g=[\"diff\",\"zero\"],v=[l,c],s=1;s<=r;++s)g.push(\"grad\"+s),v.push(u(s));g.push(n.join(\"\"));var m=Function.apply(void 0,g).apply(void 0,v);return i[e]=m,m}(r)(t,e)};var n=t(\"dup\"),a=t(\"cwise-compiler\"),i={},o={},s={body:\"\",args:[],thisVars:[],localVars:[]},l=a({args:[\"array\",\"array\",\"array\"],pre:s,post:s,body:{args:[{name:\"out\",lvalue:!0,rvalue:!1,count:1},{name:\"left\",lvalue:!1,rvalue:!0,count:1},{name:\"right\",lvalue:!1,rvalue:!0,count:1}],body:\"out=0.5*(left-right)\",thisVars:[],localVars:[]},funcName:\"cdiff\"}),c=a({args:[\"array\"],pre:s,post:s,body:{args:[{name:\"out\",lvalue:!0,rvalue:!1,count:1}],body:\"out=0\",thisVars:[],localVars:[]},funcName:\"zero\"});function u(t){if(t in i)return i[t];for(var e=[],r=0;r<t;++r)e.push(\"out\",r,\"s=0.5*(inp\",r,\"l-inp\",r,\"r);\");var o=[\"array\"],l=[\"junk\"];for(r=0;r<t;++r){o.push(\"array\"),l.push(\"out\"+r+\"s\");var c=n(t);c[r]=-1,o.push({array:0,offset:c.slice()}),c[r]=1,o.push({array:0,offset:c.slice()}),l.push(\"inp\"+r+\"l\",\"inp\"+r+\"r\")}return i[t]=a({args:o,pre:s,post:s,body:{body:e.join(\"\"),args:l.map(function(t){return{name:t,lvalue:0===t.indexOf(\"out\"),rvalue:0===t.indexOf(\"inp\"),count:\"junk\"!==t|0}}),thisVars:[],localVars:[]},funcName:\"fdTemplate\"+t})}},{\"cwise-compiler\":148,dup:172}],444:[function(t,e,r){\"use strict\";var n=t(\"ndarray-warp\"),a=t(\"gl-matrix-invert\");e.exports=function(t,e,r){var i=e.dimension,o=a([],r);return n(t,e,function(t,e){for(var r=0;r<i;++r){t[r]=o[(i+1)*i+r];for(var n=0;n<i;++n)t[r]+=o[(i+1)*n+r]*e[n]}var a=o[(i+1)*(i+1)-1];for(n=0;n<i;++n)a+=o[(i+1)*n+i]*e[n];var s=1/a;for(r=0;r<i;++r)t[r]*=s;return t}),t}},{\"gl-matrix-invert\":280,\"ndarray-warp\":451}],445:[function(t,e,r){\"use strict\";function n(t,e){var r=Math.floor(e),n=e-r,a=0<=r&&r<t.shape[0],i=0<=r+1&&r+1<t.shape[0];return(1-n)*(a?+t.get(r):0)+n*(i?+t.get(r+1):0)}function a(t,e,r){var n=Math.floor(e),a=e-n,i=0<=n&&n<t.shape[0],o=0<=n+1&&n+1<t.shape[0],s=Math.floor(r),l=r-s,c=0<=s&&s<t.shape[1],u=0<=s+1&&s+1<t.shape[1],h=i&&c?t.get(n,s):0,f=i&&u?t.get(n,s+1):0;return(1-l)*((1-a)*h+a*(o&&c?t.get(n+1,s):0))+l*((1-a)*f+a*(o&&u?t.get(n+1,s+1):0))}function i(t,e,r,n){var a=Math.floor(e),i=e-a,o=0<=a&&a<t.shape[0],s=0<=a+1&&a+1<t.shape[0],l=Math.floor(r),c=r-l,u=0<=l&&l<t.shape[1],h=0<=l+1&&l+1<t.shape[1],f=Math.floor(n),p=n-f,d=0<=f&&f<t.shape[2],g=0<=f+1&&f+1<t.shape[2],v=o&&u&&d?t.get(a,l,f):0,m=o&&h&&d?t.get(a,l+1,f):0,y=s&&u&&d?t.get(a+1,l,f):0,x=s&&h&&d?t.get(a+1,l+1,f):0,b=o&&u&&g?t.get(a,l,f+1):0,_=o&&h&&g?t.get(a,l+1,f+1):0;return(1-p)*((1-c)*((1-i)*v+i*y)+c*((1-i)*m+i*x))+p*((1-c)*((1-i)*b+i*(s&&u&&g?t.get(a+1,l,f+1):0))+c*((1-i)*_+i*(s&&h&&g?t.get(a+1,l+1,f+1):0)))}e.exports=function(t,e,r,o){switch(t.shape.length){case 0:return 0;case 1:return n(t,e);case 2:return a(t,e,r);case 3:return i(t,e,r,o);default:return function(t){var e,r,n=0|t.shape.length,a=new Array(n),i=new Array(n),o=new Array(n),s=new Array(n);for(e=0;e<n;++e)r=+arguments[e+1],a[e]=Math.floor(r),i[e]=r-a[e],o[e]=0<=a[e]&&a[e]<t.shape[e],s[e]=0<=a[e]+1&&a[e]+1<t.shape[e];var l,c,u,h=0;t:for(e=0;e<1<<n;++e){for(c=1,u=t.offset,l=0;l<n;++l)if(e&1<<l){if(!s[l])continue t;c*=i[l],u+=t.stride[l]*(a[l]+1)}else{if(!o[l])continue t;c*=1-i[l],u+=t.stride[l]*a[l]}h+=c*t.data[u]}return h}.apply(void 0,arguments)}},e.exports.d1=n,e.exports.d2=a,e.exports.d3=i},{}],446:[function(t,e,r){\"use strict\";var n=t(\"cwise-compiler\"),a={body:\"\",args:[],thisVars:[],localVars:[]};function i(t){if(!t)return a;for(var e=0;e<t.args.length;++e){var r=t.args[e];t.args[e]=0===e?{name:r,lvalue:!0,rvalue:!!t.rvalue,count:t.count||1}:{name:r,lvalue:!1,rvalue:!0,count:1}}return t.thisVars||(t.thisVars=[]),t.localVars||(t.localVars=[]),t}function o(t){for(var e=[],r=0;r<t.args.length;++r)e.push(\"a\"+r);return new Function(\"P\",[\"return function \",t.funcName,\"_ndarrayops(\",e.join(\",\"),\") {P(\",e.join(\",\"),\");return a0}\"].join(\"\"))(function(t){return n({args:t.args,pre:i(t.pre),body:i(t.body),post:i(t.proc),funcName:t.funcName})}(t))}var s={add:\"+\",sub:\"-\",mul:\"*\",div:\"/\",mod:\"%\",band:\"&\",bor:\"|\",bxor:\"^\",lshift:\"<<\",rshift:\">>\",rrshift:\">>>\"};!function(){for(var t in s){var e=s[t];r[t]=o({args:[\"array\",\"array\",\"array\"],body:{args:[\"a\",\"b\",\"c\"],body:\"a=b\"+e+\"c\"},funcName:t}),r[t+\"eq\"]=o({args:[\"array\",\"array\"],body:{args:[\"a\",\"b\"],body:\"a\"+e+\"=b\"},rvalue:!0,funcName:t+\"eq\"}),r[t+\"s\"]=o({args:[\"array\",\"array\",\"scalar\"],body:{args:[\"a\",\"b\",\"s\"],body:\"a=b\"+e+\"s\"},funcName:t+\"s\"}),r[t+\"seq\"]=o({args:[\"array\",\"scalar\"],body:{args:[\"a\",\"s\"],body:\"a\"+e+\"=s\"},rvalue:!0,funcName:t+\"seq\"})}}();var l={not:\"!\",bnot:\"~\",neg:\"-\",recip:\"1.0/\"};!function(){for(var t in l){var e=l[t];r[t]=o({args:[\"array\",\"array\"],body:{args:[\"a\",\"b\"],body:\"a=\"+e+\"b\"},funcName:t}),r[t+\"eq\"]=o({args:[\"array\"],body:{args:[\"a\"],body:\"a=\"+e+\"a\"},rvalue:!0,count:2,funcName:t+\"eq\"})}}();var c={and:\"&&\",or:\"||\",eq:\"===\",neq:\"!==\",lt:\"<\",gt:\">\",leq:\"<=\",geq:\">=\"};!function(){for(var t in c){var e=c[t];r[t]=o({args:[\"array\",\"array\",\"array\"],body:{args:[\"a\",\"b\",\"c\"],body:\"a=b\"+e+\"c\"},funcName:t}),r[t+\"s\"]=o({args:[\"array\",\"array\",\"scalar\"],body:{args:[\"a\",\"b\",\"s\"],body:\"a=b\"+e+\"s\"},funcName:t+\"s\"}),r[t+\"eq\"]=o({args:[\"array\",\"array\"],body:{args:[\"a\",\"b\"],body:\"a=a\"+e+\"b\"},rvalue:!0,count:2,funcName:t+\"eq\"}),r[t+\"seq\"]=o({args:[\"array\",\"scalar\"],body:{args:[\"a\",\"s\"],body:\"a=a\"+e+\"s\"},rvalue:!0,count:2,funcName:t+\"seq\"})}}();var u=[\"abs\",\"acos\",\"asin\",\"atan\",\"ceil\",\"cos\",\"exp\",\"floor\",\"log\",\"round\",\"sin\",\"sqrt\",\"tan\"];!function(){for(var t=0;t<u.length;++t){var e=u[t];r[e]=o({args:[\"array\",\"array\"],pre:{args:[],body:\"this_f=Math.\"+e,thisVars:[\"this_f\"]},body:{args:[\"a\",\"b\"],body:\"a=this_f(b)\",thisVars:[\"this_f\"]},funcName:e}),r[e+\"eq\"]=o({args:[\"array\"],pre:{args:[],body:\"this_f=Math.\"+e,thisVars:[\"this_f\"]},body:{args:[\"a\"],body:\"a=this_f(a)\",thisVars:[\"this_f\"]},rvalue:!0,count:2,funcName:e+\"eq\"})}}();var h=[\"max\",\"min\",\"atan2\",\"pow\"];!function(){for(var t=0;t<h.length;++t){var e=h[t];r[e]=o({args:[\"array\",\"array\",\"array\"],pre:{args:[],body:\"this_f=Math.\"+e,thisVars:[\"this_f\"]},body:{args:[\"a\",\"b\",\"c\"],body:\"a=this_f(b,c)\",thisVars:[\"this_f\"]},funcName:e}),r[e+\"s\"]=o({args:[\"array\",\"array\",\"scalar\"],pre:{args:[],body:\"this_f=Math.\"+e,thisVars:[\"this_f\"]},body:{args:[\"a\",\"b\",\"c\"],body:\"a=this_f(b,c)\",thisVars:[\"this_f\"]},funcName:e+\"s\"}),r[e+\"eq\"]=o({args:[\"array\",\"array\"],pre:{args:[],body:\"this_f=Math.\"+e,thisVars:[\"this_f\"]},body:{args:[\"a\",\"b\"],body:\"a=this_f(a,b)\",thisVars:[\"this_f\"]},rvalue:!0,count:2,funcName:e+\"eq\"}),r[e+\"seq\"]=o({args:[\"array\",\"scalar\"],pre:{args:[],body:\"this_f=Math.\"+e,thisVars:[\"this_f\"]},body:{args:[\"a\",\"b\"],body:\"a=this_f(a,b)\",thisVars:[\"this_f\"]},rvalue:!0,count:2,funcName:e+\"seq\"})}}();var f=[\"atan2\",\"pow\"];!function(){for(var t=0;t<f.length;++t){var e=f[t];r[e+\"op\"]=o({args:[\"array\",\"array\",\"array\"],pre:{args:[],body:\"this_f=Math.\"+e,thisVars:[\"this_f\"]},body:{args:[\"a\",\"b\",\"c\"],body:\"a=this_f(c,b)\",thisVars:[\"this_f\"]},funcName:e+\"op\"}),r[e+\"ops\"]=o({args:[\"array\",\"array\",\"scalar\"],pre:{args:[],body:\"this_f=Math.\"+e,thisVars:[\"this_f\"]},body:{args:[\"a\",\"b\",\"c\"],body:\"a=this_f(c,b)\",thisVars:[\"this_f\"]},funcName:e+\"ops\"}),r[e+\"opeq\"]=o({args:[\"array\",\"array\"],pre:{args:[],body:\"this_f=Math.\"+e,thisVars:[\"this_f\"]},body:{args:[\"a\",\"b\"],body:\"a=this_f(b,a)\",thisVars:[\"this_f\"]},rvalue:!0,count:2,funcName:e+\"opeq\"}),r[e+\"opseq\"]=o({args:[\"array\",\"scalar\"],pre:{args:[],body:\"this_f=Math.\"+e,thisVars:[\"this_f\"]},body:{args:[\"a\",\"b\"],body:\"a=this_f(b,a)\",thisVars:[\"this_f\"]},rvalue:!0,count:2,funcName:e+\"opseq\"})}}(),r.any=n({args:[\"array\"],pre:a,body:{args:[{name:\"a\",lvalue:!1,rvalue:!0,count:1}],body:\"if(a){return true}\",localVars:[],thisVars:[]},post:{args:[],localVars:[],thisVars:[],body:\"return false\"},funcName:\"any\"}),r.all=n({args:[\"array\"],pre:a,body:{args:[{name:\"x\",lvalue:!1,rvalue:!0,count:1}],body:\"if(!x){return false}\",localVars:[],thisVars:[]},post:{args:[],localVars:[],thisVars:[],body:\"return true\"},funcName:\"all\"}),r.sum=n({args:[\"array\"],pre:{args:[],localVars:[],thisVars:[\"this_s\"],body:\"this_s=0\"},body:{args:[{name:\"a\",lvalue:!1,rvalue:!0,count:1}],body:\"this_s+=a\",localVars:[],thisVars:[\"this_s\"]},post:{args:[],localVars:[],thisVars:[\"this_s\"],body:\"return this_s\"},funcName:\"sum\"}),r.prod=n({args:[\"array\"],pre:{args:[],localVars:[],thisVars:[\"this_s\"],body:\"this_s=1\"},body:{args:[{name:\"a\",lvalue:!1,rvalue:!0,count:1}],body:\"this_s*=a\",localVars:[],thisVars:[\"this_s\"]},post:{args:[],localVars:[],thisVars:[\"this_s\"],body:\"return this_s\"},funcName:\"prod\"}),r.norm2squared=n({args:[\"array\"],pre:{args:[],localVars:[],thisVars:[\"this_s\"],body:\"this_s=0\"},body:{args:[{name:\"a\",lvalue:!1,rvalue:!0,count:2}],body:\"this_s+=a*a\",localVars:[],thisVars:[\"this_s\"]},post:{args:[],localVars:[],thisVars:[\"this_s\"],body:\"return this_s\"},funcName:\"norm2squared\"}),r.norm2=n({args:[\"array\"],pre:{args:[],localVars:[],thisVars:[\"this_s\"],body:\"this_s=0\"},body:{args:[{name:\"a\",lvalue:!1,rvalue:!0,count:2}],body:\"this_s+=a*a\",localVars:[],thisVars:[\"this_s\"]},post:{args:[],localVars:[],thisVars:[\"this_s\"],body:\"return Math.sqrt(this_s)\"},funcName:\"norm2\"}),r.norminf=n({args:[\"array\"],pre:{args:[],localVars:[],thisVars:[\"this_s\"],body:\"this_s=0\"},body:{args:[{name:\"a\",lvalue:!1,rvalue:!0,count:4}],body:\"if(-a>this_s){this_s=-a}else if(a>this_s){this_s=a}\",localVars:[],thisVars:[\"this_s\"]},post:{args:[],localVars:[],thisVars:[\"this_s\"],body:\"return this_s\"},funcName:\"norminf\"}),r.norm1=n({args:[\"array\"],pre:{args:[],localVars:[],thisVars:[\"this_s\"],body:\"this_s=0\"},body:{args:[{name:\"a\",lvalue:!1,rvalue:!0,count:3}],body:\"this_s+=a<0?-a:a\",localVars:[],thisVars:[\"this_s\"]},post:{args:[],localVars:[],thisVars:[\"this_s\"],body:\"return this_s\"},funcName:\"norm1\"}),r.sup=n({args:[\"array\"],pre:{body:\"this_h=-Infinity\",args:[],thisVars:[\"this_h\"],localVars:[]},body:{body:\"if(_inline_1_arg0_>this_h)this_h=_inline_1_arg0_\",args:[{name:\"_inline_1_arg0_\",lvalue:!1,rvalue:!0,count:2}],thisVars:[\"this_h\"],localVars:[]},post:{body:\"return this_h\",args:[],thisVars:[\"this_h\"],localVars:[]}}),r.inf=n({args:[\"array\"],pre:{body:\"this_h=Infinity\",args:[],thisVars:[\"this_h\"],localVars:[]},body:{body:\"if(_inline_1_arg0_<this_h)this_h=_inline_1_arg0_\",args:[{name:\"_inline_1_arg0_\",lvalue:!1,rvalue:!0,count:2}],thisVars:[\"this_h\"],localVars:[]},post:{body:\"return this_h\",args:[],thisVars:[\"this_h\"],localVars:[]}}),r.argmin=n({args:[\"index\",\"array\",\"shape\"],pre:{body:\"{this_v=Infinity;this_i=_inline_0_arg2_.slice(0)}\",args:[{name:\"_inline_0_arg0_\",lvalue:!1,rvalue:!1,count:0},{name:\"_inline_0_arg1_\",lvalue:!1,rvalue:!1,count:0},{name:\"_inline_0_arg2_\",lvalue:!1,rvalue:!0,count:1}],thisVars:[\"this_i\",\"this_v\"],localVars:[]},body:{body:\"{if(_inline_1_arg1_<this_v){this_v=_inline_1_arg1_;for(var _inline_1_k=0;_inline_1_k<_inline_1_arg0_.length;++_inline_1_k){this_i[_inline_1_k]=_inline_1_arg0_[_inline_1_k]}}}\",args:[{name:\"_inline_1_arg0_\",lvalue:!1,rvalue:!0,count:2},{name:\"_inline_1_arg1_\",lvalue:!1,rvalue:!0,count:2}],thisVars:[\"this_i\",\"this_v\"],localVars:[\"_inline_1_k\"]},post:{body:\"{return this_i}\",args:[],thisVars:[\"this_i\"],localVars:[]}}),r.argmax=n({args:[\"index\",\"array\",\"shape\"],pre:{body:\"{this_v=-Infinity;this_i=_inline_0_arg2_.slice(0)}\",args:[{name:\"_inline_0_arg0_\",lvalue:!1,rvalue:!1,count:0},{name:\"_inline_0_arg1_\",lvalue:!1,rvalue:!1,count:0},{name:\"_inline_0_arg2_\",lvalue:!1,rvalue:!0,count:1}],thisVars:[\"this_i\",\"this_v\"],localVars:[]},body:{body:\"{if(_inline_1_arg1_>this_v){this_v=_inline_1_arg1_;for(var _inline_1_k=0;_inline_1_k<_inline_1_arg0_.length;++_inline_1_k){this_i[_inline_1_k]=_inline_1_arg0_[_inline_1_k]}}}\",args:[{name:\"_inline_1_arg0_\",lvalue:!1,rvalue:!0,count:2},{name:\"_inline_1_arg1_\",lvalue:!1,rvalue:!0,count:2}],thisVars:[\"this_i\",\"this_v\"],localVars:[\"_inline_1_k\"]},post:{body:\"{return this_i}\",args:[],thisVars:[\"this_i\"],localVars:[]}}),r.random=o({args:[\"array\"],pre:{args:[],body:\"this_f=Math.random\",thisVars:[\"this_f\"]},body:{args:[\"a\"],body:\"a=this_f()\",thisVars:[\"this_f\"]},funcName:\"random\"}),r.assign=o({args:[\"array\",\"array\"],body:{args:[\"a\",\"b\"],body:\"a=b\"},funcName:\"assign\"}),r.assigns=o({args:[\"array\",\"scalar\"],body:{args:[\"a\",\"b\"],body:\"a=b\"},funcName:\"assigns\"}),r.equals=n({args:[\"array\",\"array\"],pre:a,body:{args:[{name:\"x\",lvalue:!1,rvalue:!0,count:1},{name:\"y\",lvalue:!1,rvalue:!0,count:1}],body:\"if(x!==y){return false}\",localVars:[],thisVars:[]},post:{args:[],localVars:[],thisVars:[],body:\"return true\"},funcName:\"equals\"})},{\"cwise-compiler\":148}],447:[function(t,e,r){\"use strict\";var n=t(\"ndarray\"),a=t(\"./doConvert.js\");e.exports=function(t,e){for(var r=[],i=t,o=1;Array.isArray(i);)r.push(i.length),o*=i.length,i=i[0];return 0===r.length?n():(e||(e=n(new Float64Array(o),r)),a(e,t),e)}},{\"./doConvert.js\":448,ndarray:452}],448:[function(t,e,r){e.exports=t(\"cwise-compiler\")({args:[\"array\",\"scalar\",\"index\"],pre:{body:\"{}\",args:[],thisVars:[],localVars:[]},body:{body:\"{\\nvar _inline_1_v=_inline_1_arg1_,_inline_1_i\\nfor(_inline_1_i=0;_inline_1_i<_inline_1_arg2_.length-1;++_inline_1_i) {\\n_inline_1_v=_inline_1_v[_inline_1_arg2_[_inline_1_i]]\\n}\\n_inline_1_arg0_=_inline_1_v[_inline_1_arg2_[_inline_1_arg2_.length-1]]\\n}\",args:[{name:\"_inline_1_arg0_\",lvalue:!0,rvalue:!1,count:1},{name:\"_inline_1_arg1_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_1_arg2_\",lvalue:!1,rvalue:!0,count:4}],thisVars:[],localVars:[\"_inline_1_i\",\"_inline_1_v\"]},post:{body:\"{}\",args:[],thisVars:[],localVars:[]},funcName:\"convert\",blockSize:64})},{\"cwise-compiler\":148}],449:[function(t,e,r){\"use strict\";var n=t(\"typedarray-pool\"),a=32;function i(t){switch(t){case\"uint8\":return[n.mallocUint8,n.freeUint8];case\"uint16\":return[n.mallocUint16,n.freeUint16];case\"uint32\":return[n.mallocUint32,n.freeUint32];case\"int8\":return[n.mallocInt8,n.freeInt8];case\"int16\":return[n.mallocInt16,n.freeInt16];case\"int32\":return[n.mallocInt32,n.freeInt32];case\"float32\":return[n.mallocFloat,n.freeFloat];case\"float64\":return[n.mallocDouble,n.freeDouble];default:return null}}function o(t){for(var e=[],r=0;r<t;++r)e.push(\"s\"+r);for(r=0;r<t;++r)e.push(\"n\"+r);for(r=1;r<t;++r)e.push(\"d\"+r);for(r=1;r<t;++r)e.push(\"e\"+r);for(r=1;r<t;++r)e.push(\"f\"+r);return e}e.exports=function(t,e){var r=[\"'use strict'\"],n=[\"ndarraySortWrapper\",t.join(\"d\"),e].join(\"\");r.push([\"function \",n,\"(\",[\"array\"].join(\",\"),\"){\"].join(\"\"));for(var s=[\"data=array.data,offset=array.offset|0,shape=array.shape,stride=array.stride\"],l=0;l<t.length;++l)s.push([\"s\",l,\"=stride[\",l,\"]|0,n\",l,\"=shape[\",l,\"]|0\"].join(\"\"));var c=new Array(t.length),u=[];for(l=0;l<t.length;++l)0!==(p=t[l])&&(0===u.length?c[p]=\"1\":c[p]=u.join(\"*\"),u.push(\"n\"+p));var h=-1,f=-1;for(l=0;l<t.length;++l){var p,d=t[l];0!==d&&(h>0?s.push([\"d\",d,\"=s\",d,\"-d\",h,\"*n\",h].join(\"\")):s.push([\"d\",d,\"=s\",d].join(\"\")),h=d),0!=(p=t.length-1-l)&&(f>0?s.push([\"e\",p,\"=s\",p,\"-e\",f,\"*n\",f,\",f\",p,\"=\",c[p],\"-f\",f,\"*n\",f].join(\"\")):s.push([\"e\",p,\"=s\",p,\",f\",p,\"=\",c[p]].join(\"\")),f=p)}r.push(\"var \"+s.join(\",\"));var g=[\"0\",\"n0-1\",\"data\",\"offset\"].concat(o(t.length));r.push([\"if(n0<=\",a,\"){\",\"insertionSort(\",g.join(\",\"),\")}else{\",\"quickSort(\",g.join(\",\"),\")}\"].join(\"\")),r.push(\"}return \"+n);var v=new Function(\"insertionSort\",\"quickSort\",r.join(\"\\n\")),m=function(t,e){var r=[\"'use strict'\"],n=[\"ndarrayInsertionSort\",t.join(\"d\"),e].join(\"\"),a=[\"left\",\"right\",\"data\",\"offset\"].concat(o(t.length)),s=i(e),l=[\"i,j,cptr,ptr=left*s0+offset\"];if(t.length>1){for(var c=[],u=1;u<t.length;++u)l.push(\"i\"+u),c.push(\"n\"+u);s?l.push(\"scratch=malloc(\"+c.join(\"*\")+\")\"):l.push(\"scratch=new Array(\"+c.join(\"*\")+\")\"),l.push(\"dptr\",\"sptr\",\"a\",\"b\")}else l.push(\"scratch\");function h(t){return\"generic\"===e?[\"data.get(\",t,\")\"].join(\"\"):[\"data[\",t,\"]\"].join(\"\")}function f(t,r){return\"generic\"===e?[\"data.set(\",t,\",\",r,\")\"].join(\"\"):[\"data[\",t,\"]=\",r].join(\"\")}if(r.push([\"function \",n,\"(\",a.join(\",\"),\"){var \",l.join(\",\")].join(\"\"),\"for(i=left+1;i<=right;++i){\",\"j=i;ptr+=s0\",\"cptr=ptr\"),t.length>1){for(r.push(\"dptr=0;sptr=ptr\"),u=t.length-1;u>=0;--u)0!==(p=t[u])&&r.push([\"for(i\",p,\"=0;i\",p,\"<n\",p,\";++i\",p,\"){\"].join(\"\"));for(r.push(\"scratch[dptr++]=\",h(\"sptr\")),u=0;u<t.length;++u)0!==(p=t[u])&&r.push(\"sptr+=d\"+p,\"}\");for(r.push(\"__g:while(j--\\x3eleft){\",\"dptr=0\",\"sptr=cptr-s0\"),u=1;u<t.length;++u)1===u&&r.push(\"__l:\"),r.push([\"for(i\",u,\"=0;i\",u,\"<n\",u,\";++i\",u,\"){\"].join(\"\"));for(r.push([\"a=\",h(\"sptr\"),\"\\nb=scratch[dptr]\\nif(a<b){break __g}\\nif(a>b){break __l}\"].join(\"\")),u=t.length-1;u>=1;--u)r.push(\"sptr+=e\"+u,\"dptr+=f\"+u,\"}\");for(r.push(\"dptr=cptr;sptr=cptr-s0\"),u=t.length-1;u>=0;--u)0!==(p=t[u])&&r.push([\"for(i\",p,\"=0;i\",p,\"<n\",p,\";++i\",p,\"){\"].join(\"\"));for(r.push(f(\"dptr\",h(\"sptr\"))),u=0;u<t.length;++u)0!==(p=t[u])&&r.push([\"dptr+=d\",p,\";sptr+=d\",p].join(\"\"),\"}\");for(r.push(\"cptr-=s0\\n}\"),r.push(\"dptr=cptr;sptr=0\"),u=t.length-1;u>=0;--u)0!==(p=t[u])&&r.push([\"for(i\",p,\"=0;i\",p,\"<n\",p,\";++i\",p,\"){\"].join(\"\"));for(r.push(f(\"dptr\",\"scratch[sptr++]\")),u=0;u<t.length;++u){var p;0!==(p=t[u])&&r.push(\"dptr+=d\"+p,\"}\")}}else r.push(\"scratch=\"+h(\"ptr\"),\"while((j--\\x3eleft)&&(\"+h(\"cptr-s0\")+\">scratch)){\",f(\"cptr\",h(\"cptr-s0\")),\"cptr-=s0\",\"}\",f(\"cptr\",\"scratch\"));return r.push(\"}\"),t.length>1&&s&&r.push(\"free(scratch)\"),r.push(\"} return \"+n),s?new Function(\"malloc\",\"free\",r.join(\"\\n\"))(s[0],s[1]):new Function(r.join(\"\\n\"))()}(t,e),y=function(t,e,r){var n=[\"'use strict'\"],s=[\"ndarrayQuickSort\",t.join(\"d\"),e].join(\"\"),l=[\"left\",\"right\",\"data\",\"offset\"].concat(o(t.length)),c=i(e),u=0;n.push([\"function \",s,\"(\",l.join(\",\"),\"){\"].join(\"\"));var h=[\"sixth=((right-left+1)/6)|0\",\"index1=left+sixth\",\"index5=right-sixth\",\"index3=(left+right)>>1\",\"index2=index3-sixth\",\"index4=index3+sixth\",\"el1=index1\",\"el2=index2\",\"el3=index3\",\"el4=index4\",\"el5=index5\",\"less=left+1\",\"great=right-1\",\"pivots_are_equal=true\",\"tmp\",\"tmp0\",\"x\",\"y\",\"z\",\"k\",\"ptr0\",\"ptr1\",\"ptr2\",\"comp_pivot1=0\",\"comp_pivot2=0\",\"comp=0\"];if(t.length>1){for(var f=[],p=1;p<t.length;++p)f.push(\"n\"+p),h.push(\"i\"+p);for(p=0;p<8;++p)h.push(\"b_ptr\"+p);h.push(\"ptr3\",\"ptr4\",\"ptr5\",\"ptr6\",\"ptr7\",\"pivot_ptr\",\"ptr_shift\",\"elementSize=\"+f.join(\"*\")),c?h.push(\"pivot1=malloc(elementSize)\",\"pivot2=malloc(elementSize)\"):h.push(\"pivot1=new Array(elementSize),pivot2=new Array(elementSize)\")}else h.push(\"pivot1\",\"pivot2\");function d(t){return[\"(offset+\",t,\"*s0)\"].join(\"\")}function g(t){return\"generic\"===e?[\"data.get(\",t,\")\"].join(\"\"):[\"data[\",t,\"]\"].join(\"\")}function v(t,r){return\"generic\"===e?[\"data.set(\",t,\",\",r,\")\"].join(\"\"):[\"data[\",t,\"]=\",r].join(\"\")}function m(e,r,a){if(1===e.length)n.push(\"ptr0=\"+d(e[0]));else for(var i=0;i<e.length;++i)n.push([\"b_ptr\",i,\"=s0*\",e[i]].join(\"\"));for(r&&n.push(\"pivot_ptr=0\"),n.push(\"ptr_shift=offset\"),i=t.length-1;i>=0;--i)0!==(o=t[i])&&n.push([\"for(i\",o,\"=0;i\",o,\"<n\",o,\";++i\",o,\"){\"].join(\"\"));if(e.length>1)for(i=0;i<e.length;++i)n.push([\"ptr\",i,\"=b_ptr\",i,\"+ptr_shift\"].join(\"\"));for(n.push(a),r&&n.push(\"++pivot_ptr\"),i=0;i<t.length;++i){var o;0!==(o=t[i])&&(e.length>1?n.push(\"ptr_shift+=d\"+o):n.push(\"ptr0+=d\"+o),n.push(\"}\"))}}function y(e,r,a,i){if(1===r.length)n.push(\"ptr0=\"+d(r[0]));else{for(var o=0;o<r.length;++o)n.push([\"b_ptr\",o,\"=s0*\",r[o]].join(\"\"));n.push(\"ptr_shift=offset\")}for(a&&n.push(\"pivot_ptr=0\"),e&&n.push(e+\":\"),o=1;o<t.length;++o)n.push([\"for(i\",o,\"=0;i\",o,\"<n\",o,\";++i\",o,\"){\"].join(\"\"));if(r.length>1)for(o=0;o<r.length;++o)n.push([\"ptr\",o,\"=b_ptr\",o,\"+ptr_shift\"].join(\"\"));for(n.push(i),o=t.length-1;o>=1;--o)a&&n.push(\"pivot_ptr+=f\"+o),r.length>1?n.push(\"ptr_shift+=e\"+o):n.push(\"ptr0+=e\"+o),n.push(\"}\")}function x(){t.length>1&&c&&n.push(\"free(pivot1)\",\"free(pivot2)\")}function b(e,r){var a=\"el\"+e,i=\"el\"+r;if(t.length>1){var o=\"__l\"+ ++u;y(o,[a,i],!1,[\"comp=\",g(\"ptr0\"),\"-\",g(\"ptr1\"),\"\\n\",\"if(comp>0){tmp0=\",a,\";\",a,\"=\",i,\";\",i,\"=tmp0;break \",o,\"}\\n\",\"if(comp<0){break \",o,\"}\"].join(\"\"))}else n.push([\"if(\",g(d(a)),\">\",g(d(i)),\"){tmp0=\",a,\";\",a,\"=\",i,\";\",i,\"=tmp0}\"].join(\"\"))}function _(e,r){t.length>1?m([e,r],!1,v(\"ptr0\",g(\"ptr1\"))):n.push(v(d(e),g(d(r))))}function w(e,r,a){if(t.length>1){var i=\"__l\"+ ++u;y(i,[r],!0,[e,\"=\",g(\"ptr0\"),\"-pivot\",a,\"[pivot_ptr]\\n\",\"if(\",e,\"!==0){break \",i,\"}\"].join(\"\"))}else n.push([e,\"=\",g(d(r)),\"-pivot\",a].join(\"\"))}function k(e,r){t.length>1?m([e,r],!1,[\"tmp=\",g(\"ptr0\"),\"\\n\",v(\"ptr0\",g(\"ptr1\")),\"\\n\",v(\"ptr1\",\"tmp\")].join(\"\")):n.push([\"ptr0=\",d(e),\"\\n\",\"ptr1=\",d(r),\"\\n\",\"tmp=\",g(\"ptr0\"),\"\\n\",v(\"ptr0\",g(\"ptr1\")),\"\\n\",v(\"ptr1\",\"tmp\")].join(\"\"))}function T(e,r,a){t.length>1?(m([e,r,a],!1,[\"tmp=\",g(\"ptr0\"),\"\\n\",v(\"ptr0\",g(\"ptr1\")),\"\\n\",v(\"ptr1\",g(\"ptr2\")),\"\\n\",v(\"ptr2\",\"tmp\")].join(\"\")),n.push(\"++\"+r,\"--\"+a)):n.push([\"ptr0=\",d(e),\"\\n\",\"ptr1=\",d(r),\"\\n\",\"ptr2=\",d(a),\"\\n\",\"++\",r,\"\\n\",\"--\",a,\"\\n\",\"tmp=\",g(\"ptr0\"),\"\\n\",v(\"ptr0\",g(\"ptr1\")),\"\\n\",v(\"ptr1\",g(\"ptr2\")),\"\\n\",v(\"ptr2\",\"tmp\")].join(\"\"))}function M(t,e){k(t,e),n.push(\"--\"+e)}function A(e,r,a){t.length>1?m([e,r],!0,[v(\"ptr0\",g(\"ptr1\")),\"\\n\",v(\"ptr1\",[\"pivot\",a,\"[pivot_ptr]\"].join(\"\"))].join(\"\")):n.push(v(d(e),g(d(r))),v(d(r),\"pivot\"+a))}function S(e,r){n.push([\"if((\",r,\"-\",e,\")<=\",a,\"){\\n\",\"insertionSort(\",e,\",\",r,\",data,offset,\",o(t.length).join(\",\"),\")\\n\",\"}else{\\n\",s,\"(\",e,\",\",r,\",data,offset,\",o(t.length).join(\",\"),\")\\n\",\"}\"].join(\"\"))}function E(e,r,a){t.length>1?(n.push([\"__l\",++u,\":while(true){\"].join(\"\")),m([e],!0,[\"if(\",g(\"ptr0\"),\"!==pivot\",r,\"[pivot_ptr]){break __l\",u,\"}\"].join(\"\")),n.push(a,\"}\")):n.push([\"while(\",g(d(e)),\"===pivot\",r,\"){\",a,\"}\"].join(\"\"))}return n.push(\"var \"+h.join(\",\")),b(1,2),b(4,5),b(1,3),b(2,3),b(1,4),b(3,4),b(2,5),b(2,3),b(4,5),t.length>1?m([\"el1\",\"el2\",\"el3\",\"el4\",\"el5\",\"index1\",\"index3\",\"index5\"],!0,[\"pivot1[pivot_ptr]=\",g(\"ptr1\"),\"\\n\",\"pivot2[pivot_ptr]=\",g(\"ptr3\"),\"\\n\",\"pivots_are_equal=pivots_are_equal&&(pivot1[pivot_ptr]===pivot2[pivot_ptr])\\n\",\"x=\",g(\"ptr0\"),\"\\n\",\"y=\",g(\"ptr2\"),\"\\n\",\"z=\",g(\"ptr4\"),\"\\n\",v(\"ptr5\",\"x\"),\"\\n\",v(\"ptr6\",\"y\"),\"\\n\",v(\"ptr7\",\"z\")].join(\"\")):n.push([\"pivot1=\",g(d(\"el2\")),\"\\n\",\"pivot2=\",g(d(\"el4\")),\"\\n\",\"pivots_are_equal=pivot1===pivot2\\n\",\"x=\",g(d(\"el1\")),\"\\n\",\"y=\",g(d(\"el3\")),\"\\n\",\"z=\",g(d(\"el5\")),\"\\n\",v(d(\"index1\"),\"x\"),\"\\n\",v(d(\"index3\"),\"y\"),\"\\n\",v(d(\"index5\"),\"z\")].join(\"\")),_(\"index2\",\"left\"),_(\"index4\",\"right\"),n.push(\"if(pivots_are_equal){\"),n.push(\"for(k=less;k<=great;++k){\"),w(\"comp\",\"k\",1),n.push(\"if(comp===0){continue}\"),n.push(\"if(comp<0){\"),n.push(\"if(k!==less){\"),k(\"k\",\"less\"),n.push(\"}\"),n.push(\"++less\"),n.push(\"}else{\"),n.push(\"while(true){\"),w(\"comp\",\"great\",1),n.push(\"if(comp>0){\"),n.push(\"great--\"),n.push(\"}else if(comp<0){\"),T(\"k\",\"less\",\"great\"),n.push(\"break\"),n.push(\"}else{\"),M(\"k\",\"great\"),n.push(\"break\"),n.push(\"}\"),n.push(\"}\"),n.push(\"}\"),n.push(\"}\"),n.push(\"}else{\"),n.push(\"for(k=less;k<=great;++k){\"),w(\"comp_pivot1\",\"k\",1),n.push(\"if(comp_pivot1<0){\"),n.push(\"if(k!==less){\"),k(\"k\",\"less\"),n.push(\"}\"),n.push(\"++less\"),n.push(\"}else{\"),w(\"comp_pivot2\",\"k\",2),n.push(\"if(comp_pivot2>0){\"),n.push(\"while(true){\"),w(\"comp\",\"great\",2),n.push(\"if(comp>0){\"),n.push(\"if(--great<k){break}\"),n.push(\"continue\"),n.push(\"}else{\"),w(\"comp\",\"great\",1),n.push(\"if(comp<0){\"),T(\"k\",\"less\",\"great\"),n.push(\"}else{\"),M(\"k\",\"great\"),n.push(\"}\"),n.push(\"break\"),n.push(\"}\"),n.push(\"}\"),n.push(\"}\"),n.push(\"}\"),n.push(\"}\"),n.push(\"}\"),A(\"left\",\"(less-1)\",1),A(\"right\",\"(great+1)\",2),S(\"left\",\"(less-2)\"),S(\"(great+2)\",\"right\"),n.push(\"if(pivots_are_equal){\"),x(),n.push(\"return\"),n.push(\"}\"),n.push(\"if(less<index1&&great>index5){\"),E(\"less\",1,\"++less\"),E(\"great\",2,\"--great\"),n.push(\"for(k=less;k<=great;++k){\"),w(\"comp_pivot1\",\"k\",1),n.push(\"if(comp_pivot1===0){\"),n.push(\"if(k!==less){\"),k(\"k\",\"less\"),n.push(\"}\"),n.push(\"++less\"),n.push(\"}else{\"),w(\"comp_pivot2\",\"k\",2),n.push(\"if(comp_pivot2===0){\"),n.push(\"while(true){\"),w(\"comp\",\"great\",2),n.push(\"if(comp===0){\"),n.push(\"if(--great<k){break}\"),n.push(\"continue\"),n.push(\"}else{\"),w(\"comp\",\"great\",1),n.push(\"if(comp<0){\"),T(\"k\",\"less\",\"great\"),n.push(\"}else{\"),M(\"k\",\"great\"),n.push(\"}\"),n.push(\"break\"),n.push(\"}\"),n.push(\"}\"),n.push(\"}\"),n.push(\"}\"),n.push(\"}\"),n.push(\"}\"),x(),S(\"less\",\"great\"),n.push(\"}return \"+s),t.length>1&&c?new Function(\"insertionSort\",\"malloc\",\"free\",n.join(\"\\n\"))(r,c[0],c[1]):new Function(\"insertionSort\",n.join(\"\\n\"))(r)}(t,e,m);return v(m,y)}},{\"typedarray-pool\":544}],450:[function(t,e,r){\"use strict\";var n=t(\"./lib/compile_sort.js\"),a={};e.exports=function(t){var e=t.order,r=t.dtype,i=[e,r].join(\":\"),o=a[i];return o||(a[i]=o=n(e,r)),o(t),t}},{\"./lib/compile_sort.js\":449}],451:[function(t,e,r){\"use strict\";var n=t(\"ndarray-linear-interpolate\"),a=t(\"cwise/lib/wrapper\")({args:[\"index\",\"array\",\"scalar\",\"scalar\",\"scalar\"],pre:{body:\"{this_warped=new Array(_inline_3_arg4_)}\",args:[{name:\"_inline_3_arg0_\",lvalue:!1,rvalue:!1,count:0},{name:\"_inline_3_arg1_\",lvalue:!1,rvalue:!1,count:0},{name:\"_inline_3_arg2_\",lvalue:!1,rvalue:!1,count:0},{name:\"_inline_3_arg3_\",lvalue:!1,rvalue:!1,count:0},{name:\"_inline_3_arg4_\",lvalue:!1,rvalue:!0,count:1}],thisVars:[\"this_warped\"],localVars:[]},body:{body:\"{_inline_4_arg2_(this_warped,_inline_4_arg0_),_inline_4_arg1_=_inline_4_arg3_.apply(void 0,this_warped)}\",args:[{name:\"_inline_4_arg0_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_4_arg1_\",lvalue:!0,rvalue:!1,count:1},{name:\"_inline_4_arg2_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_4_arg3_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_4_arg4_\",lvalue:!1,rvalue:!1,count:0}],thisVars:[\"this_warped\"],localVars:[]},post:{body:\"{}\",args:[],thisVars:[],localVars:[]},debug:!1,funcName:\"warpND\",blockSize:64}),i=t(\"cwise/lib/wrapper\")({args:[\"index\",\"array\",\"scalar\",\"scalar\",\"scalar\"],pre:{body:\"{this_warped=[0]}\",args:[],thisVars:[\"this_warped\"],localVars:[]},body:{body:\"{_inline_7_arg2_(this_warped,_inline_7_arg0_),_inline_7_arg1_=_inline_7_arg3_(_inline_7_arg4_,this_warped[0])}\",args:[{name:\"_inline_7_arg0_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_7_arg1_\",lvalue:!0,rvalue:!1,count:1},{name:\"_inline_7_arg2_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_7_arg3_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_7_arg4_\",lvalue:!1,rvalue:!0,count:1}],thisVars:[\"this_warped\"],localVars:[]},post:{body:\"{}\",args:[],thisVars:[],localVars:[]},debug:!1,funcName:\"warp1D\",blockSize:64}),o=t(\"cwise/lib/wrapper\")({args:[\"index\",\"array\",\"scalar\",\"scalar\",\"scalar\"],pre:{body:\"{this_warped=[0,0]}\",args:[],thisVars:[\"this_warped\"],localVars:[]},body:{body:\"{_inline_10_arg2_(this_warped,_inline_10_arg0_),_inline_10_arg1_=_inline_10_arg3_(_inline_10_arg4_,this_warped[0],this_warped[1])}\",args:[{name:\"_inline_10_arg0_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_10_arg1_\",lvalue:!0,rvalue:!1,count:1},{name:\"_inline_10_arg2_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_10_arg3_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_10_arg4_\",lvalue:!1,rvalue:!0,count:1}],thisVars:[\"this_warped\"],localVars:[]},post:{body:\"{}\",args:[],thisVars:[],localVars:[]},debug:!1,funcName:\"warp2D\",blockSize:64}),s=t(\"cwise/lib/wrapper\")({args:[\"index\",\"array\",\"scalar\",\"scalar\",\"scalar\"],pre:{body:\"{this_warped=[0,0,0]}\",args:[],thisVars:[\"this_warped\"],localVars:[]},body:{body:\"{_inline_13_arg2_(this_warped,_inline_13_arg0_),_inline_13_arg1_=_inline_13_arg3_(_inline_13_arg4_,this_warped[0],this_warped[1],this_warped[2])}\",args:[{name:\"_inline_13_arg0_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_13_arg1_\",lvalue:!0,rvalue:!1,count:1},{name:\"_inline_13_arg2_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_13_arg3_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_13_arg4_\",lvalue:!1,rvalue:!0,count:1}],thisVars:[\"this_warped\"],localVars:[]},post:{body:\"{}\",args:[],thisVars:[],localVars:[]},debug:!1,funcName:\"warp3D\",blockSize:64});e.exports=function(t,e,r){switch(e.shape.length){case 1:i(t,r,n.d1,e);break;case 2:o(t,r,n.d2,e);break;case 3:s(t,r,n.d3,e);break;default:a(t,r,n.bind(void 0,e),e.shape.length)}return t}},{\"cwise/lib/wrapper\":151,\"ndarray-linear-interpolate\":445}],452:[function(t,e,r){var n=t(\"iota-array\"),a=t(\"is-buffer\"),i=\"undefined\"!=typeof Float64Array;function o(t,e){return t[0]-e[0]}function s(){var t,e=this.stride,r=new Array(e.length);for(t=0;t<r.length;++t)r[t]=[Math.abs(e[t]),t];r.sort(o);var n=new Array(r.length);for(t=0;t<n.length;++t)n[t]=r[t][1];return n}function l(t,e){var r=[\"View\",e,\"d\",t].join(\"\");e<0&&(r=\"View_Nil\"+t);var a=\"generic\"===t;if(-1===e){var i=\"function \"+r+\"(a){this.data=a;};var proto=\"+r+\".prototype;proto.dtype='\"+t+\"';proto.index=function(){return -1};proto.size=0;proto.dimension=-1;proto.shape=proto.stride=proto.order=[];proto.lo=proto.hi=proto.transpose=proto.step=function(){return new \"+r+\"(this.data);};proto.get=proto.set=function(){};proto.pick=function(){return null};return function construct_\"+r+\"(a){return new \"+r+\"(a);}\";return new Function(i)()}if(0===e){i=\"function \"+r+\"(a,d) {this.data = a;this.offset = d};var proto=\"+r+\".prototype;proto.dtype='\"+t+\"';proto.index=function(){return this.offset};proto.dimension=0;proto.size=1;proto.shape=proto.stride=proto.order=[];proto.lo=proto.hi=proto.transpose=proto.step=function \"+r+\"_copy() {return new \"+r+\"(this.data,this.offset)};proto.pick=function \"+r+\"_pick(){return TrivialArray(this.data);};proto.valueOf=proto.get=function \"+r+\"_get(){return \"+(a?\"this.data.get(this.offset)\":\"this.data[this.offset]\")+\"};proto.set=function \"+r+\"_set(v){return \"+(a?\"this.data.set(this.offset,v)\":\"this.data[this.offset]=v\")+\"};return function construct_\"+r+\"(a,b,c,d){return new \"+r+\"(a,d)}\";return new Function(\"TrivialArray\",i)(c[t][0])}i=[\"'use strict'\"];var o=n(e),l=o.map(function(t){return\"i\"+t}),u=\"this.offset+\"+o.map(function(t){return\"this.stride[\"+t+\"]*i\"+t}).join(\"+\"),h=o.map(function(t){return\"b\"+t}).join(\",\"),f=o.map(function(t){return\"c\"+t}).join(\",\");i.push(\"function \"+r+\"(a,\"+h+\",\"+f+\",d){this.data=a\",\"this.shape=[\"+h+\"]\",\"this.stride=[\"+f+\"]\",\"this.offset=d|0}\",\"var proto=\"+r+\".prototype\",\"proto.dtype='\"+t+\"'\",\"proto.dimension=\"+e),i.push(\"Object.defineProperty(proto,'size',{get:function \"+r+\"_size(){return \"+o.map(function(t){return\"this.shape[\"+t+\"]\"}).join(\"*\"),\"}})\"),1===e?i.push(\"proto.order=[0]\"):(i.push(\"Object.defineProperty(proto,'order',{get:\"),e<4?(i.push(\"function \"+r+\"_order(){\"),2===e?i.push(\"return (Math.abs(this.stride[0])>Math.abs(this.stride[1]))?[1,0]:[0,1]}})\"):3===e&&i.push(\"var s0=Math.abs(this.stride[0]),s1=Math.abs(this.stride[1]),s2=Math.abs(this.stride[2]);if(s0>s1){if(s1>s2){return [2,1,0];}else if(s0>s2){return [1,2,0];}else{return [1,0,2];}}else if(s0>s2){return [2,0,1];}else if(s2>s1){return [0,1,2];}else{return [0,2,1];}}})\")):i.push(\"ORDER})\")),i.push(\"proto.set=function \"+r+\"_set(\"+l.join(\",\")+\",v){\"),a?i.push(\"return this.data.set(\"+u+\",v)}\"):i.push(\"return this.data[\"+u+\"]=v}\"),i.push(\"proto.get=function \"+r+\"_get(\"+l.join(\",\")+\"){\"),a?i.push(\"return this.data.get(\"+u+\")}\"):i.push(\"return this.data[\"+u+\"]}\"),i.push(\"proto.index=function \"+r+\"_index(\",l.join(),\"){return \"+u+\"}\"),i.push(\"proto.hi=function \"+r+\"_hi(\"+l.join(\",\")+\"){return new \"+r+\"(this.data,\"+o.map(function(t){return[\"(typeof i\",t,\"!=='number'||i\",t,\"<0)?this.shape[\",t,\"]:i\",t,\"|0\"].join(\"\")}).join(\",\")+\",\"+o.map(function(t){return\"this.stride[\"+t+\"]\"}).join(\",\")+\",this.offset)}\");var p=o.map(function(t){return\"a\"+t+\"=this.shape[\"+t+\"]\"}),d=o.map(function(t){return\"c\"+t+\"=this.stride[\"+t+\"]\"});i.push(\"proto.lo=function \"+r+\"_lo(\"+l.join(\",\")+\"){var b=this.offset,d=0,\"+p.join(\",\")+\",\"+d.join(\",\"));for(var g=0;g<e;++g)i.push(\"if(typeof i\"+g+\"==='number'&&i\"+g+\">=0){d=i\"+g+\"|0;b+=c\"+g+\"*d;a\"+g+\"-=d}\");i.push(\"return new \"+r+\"(this.data,\"+o.map(function(t){return\"a\"+t}).join(\",\")+\",\"+o.map(function(t){return\"c\"+t}).join(\",\")+\",b)}\"),i.push(\"proto.step=function \"+r+\"_step(\"+l.join(\",\")+\"){var \"+o.map(function(t){return\"a\"+t+\"=this.shape[\"+t+\"]\"}).join(\",\")+\",\"+o.map(function(t){return\"b\"+t+\"=this.stride[\"+t+\"]\"}).join(\",\")+\",c=this.offset,d=0,ceil=Math.ceil\");for(g=0;g<e;++g)i.push(\"if(typeof i\"+g+\"==='number'){d=i\"+g+\"|0;if(d<0){c+=b\"+g+\"*(a\"+g+\"-1);a\"+g+\"=ceil(-a\"+g+\"/d)}else{a\"+g+\"=ceil(a\"+g+\"/d)}b\"+g+\"*=d}\");i.push(\"return new \"+r+\"(this.data,\"+o.map(function(t){return\"a\"+t}).join(\",\")+\",\"+o.map(function(t){return\"b\"+t}).join(\",\")+\",c)}\");var v=new Array(e),m=new Array(e);for(g=0;g<e;++g)v[g]=\"a[i\"+g+\"]\",m[g]=\"b[i\"+g+\"]\";i.push(\"proto.transpose=function \"+r+\"_transpose(\"+l+\"){\"+l.map(function(t,e){return t+\"=(\"+t+\"===undefined?\"+e+\":\"+t+\"|0)\"}).join(\";\"),\"var a=this.shape,b=this.stride;return new \"+r+\"(this.data,\"+v.join(\",\")+\",\"+m.join(\",\")+\",this.offset)}\"),i.push(\"proto.pick=function \"+r+\"_pick(\"+l+\"){var a=[],b=[],c=this.offset\");for(g=0;g<e;++g)i.push(\"if(typeof i\"+g+\"==='number'&&i\"+g+\">=0){c=(c+this.stride[\"+g+\"]*i\"+g+\")|0}else{a.push(this.shape[\"+g+\"]);b.push(this.stride[\"+g+\"])}\");return i.push(\"var ctor=CTOR_LIST[a.length+1];return ctor(this.data,a,b,c)}\"),i.push(\"return function construct_\"+r+\"(data,shape,stride,offset){return new \"+r+\"(data,\"+o.map(function(t){return\"shape[\"+t+\"]\"}).join(\",\")+\",\"+o.map(function(t){return\"stride[\"+t+\"]\"}).join(\",\")+\",offset)}\"),new Function(\"CTOR_LIST\",\"ORDER\",i.join(\"\\n\"))(c[t],s)}var c={float32:[],float64:[],int8:[],int16:[],int32:[],uint8:[],uint16:[],uint32:[],array:[],uint8_clamped:[],buffer:[],generic:[]};e.exports=function(t,e,r,n){if(void 0===t)return(0,c.array[0])([]);\"number\"==typeof t&&(t=[t]),void 0===e&&(e=[t.length]);var o=e.length;if(void 0===r){r=new Array(o);for(var s=o-1,u=1;s>=0;--s)r[s]=u,u*=e[s]}if(void 0===n)for(n=0,s=0;s<o;++s)r[s]<0&&(n-=(e[s]-1)*r[s]);for(var h=function(t){if(a(t))return\"buffer\";if(i)switch(Object.prototype.toString.call(t)){case\"[object Float64Array]\":return\"float64\";case\"[object Float32Array]\":return\"float32\";case\"[object Int8Array]\":return\"int8\";case\"[object Int16Array]\":return\"int16\";case\"[object Int32Array]\":return\"int32\";case\"[object Uint8Array]\":return\"uint8\";case\"[object Uint16Array]\":return\"uint16\";case\"[object Uint32Array]\":return\"uint32\";case\"[object Uint8ClampedArray]\":return\"uint8_clamped\"}return Array.isArray(t)?\"array\":\"generic\"}(t),f=c[h];f.length<=o+1;)f.push(l(h,f.length-1));return(0,f[o+1])(t,e,r,n)}},{\"iota-array\":418,\"is-buffer\":420}],453:[function(t,e,r){\"use strict\";var n=t(\"double-bits\"),a=Math.pow(2,-1074),i=-1>>>0;e.exports=function(t,e){if(isNaN(t)||isNaN(e))return NaN;if(t===e)return t;if(0===t)return e<0?-a:a;var r=n.hi(t),o=n.lo(t);e>t==t>0?o===i?(r+=1,o=0):o+=1:0===o?(o=i,r-=1):o-=1;return n.pack(o,r)}},{\"double-bits\":169}],454:[function(t,e,r){var n=Math.PI,a=c(120);function i(t,e,r,n){return[\"C\",t,e,r,n,r,n]}function o(t,e,r,n,a,i){return[\"C\",t/3+2/3*r,e/3+2/3*n,a/3+2/3*r,i/3+2/3*n,a,i]}function s(t,e,r,i,o,c,u,h,f,p){if(p)k=p[0],T=p[1],_=p[2],w=p[3];else{var d=l(t,e,-o);t=d.x,e=d.y;var g=(t-(h=(d=l(h,f,-o)).x))/2,v=(e-(f=d.y))/2,m=g*g/(r*r)+v*v/(i*i);m>1&&(r*=m=Math.sqrt(m),i*=m);var y=r*r,x=i*i,b=(c==u?-1:1)*Math.sqrt(Math.abs((y*x-y*v*v-x*g*g)/(y*v*v+x*g*g)));b==1/0&&(b=1);var _=b*r*v/i+(t+h)/2,w=b*-i*g/r+(e+f)/2,k=Math.asin(((e-w)/i).toFixed(9)),T=Math.asin(((f-w)/i).toFixed(9));(k=t<_?n-k:k)<0&&(k=2*n+k),(T=h<_?n-T:T)<0&&(T=2*n+T),u&&k>T&&(k-=2*n),!u&&T>k&&(T-=2*n)}if(Math.abs(T-k)>a){var M=T,A=h,S=f;T=k+a*(u&&T>k?1:-1);var E=s(h=_+r*Math.cos(T),f=w+i*Math.sin(T),r,i,o,0,u,A,S,[T,M,_,w])}var L=Math.tan((T-k)/4),C=4/3*r*L,P=4/3*i*L,O=[2*t-(t+C*Math.sin(k)),2*e-(e-P*Math.cos(k)),h+C*Math.sin(T),f-P*Math.cos(T),h,f];if(p)return O;E&&(O=O.concat(E));for(var z=0;z<O.length;){var I=l(O[z],O[z+1],o);O[z++]=I.x,O[z++]=I.y}return O}function l(t,e,r){return{x:t*Math.cos(r)-e*Math.sin(r),y:t*Math.sin(r)+e*Math.cos(r)}}function c(t){return t*(n/180)}e.exports=function(t){for(var e,r=[],n=0,a=0,l=0,u=0,h=null,f=null,p=0,d=0,g=0,v=t.length;g<v;g++){var m=t[g],y=m[0];switch(y){case\"M\":l=m[1],u=m[2];break;case\"A\":(m=s(p,d,m[1],m[2],c(m[3]),m[4],m[5],m[6],m[7])).unshift(\"C\"),m.length>7&&(r.push(m.splice(0,7)),m.unshift(\"C\"));break;case\"S\":var x=p,b=d;\"C\"!=e&&\"S\"!=e||(x+=x-n,b+=b-a),m=[\"C\",x,b,m[1],m[2],m[3],m[4]];break;case\"T\":\"Q\"==e||\"T\"==e?(h=2*p-h,f=2*d-f):(h=p,f=d),m=o(p,d,h,f,m[1],m[2]);break;case\"Q\":h=m[1],f=m[2],m=o(p,d,m[1],m[2],m[3],m[4]);break;case\"L\":m=i(p,d,m[1],m[2]);break;case\"H\":m=i(p,d,m[1],d);break;case\"V\":m=i(p,d,p,m[1]);break;case\"Z\":m=i(p,d,l,u)}e=y,p=m[m.length-2],d=m[m.length-1],m.length>4?(n=m[m.length-4],a=m[m.length-3]):(n=p,a=d),r.push(m)}return r}},{}],455:[function(t,e,r){r.vertexNormals=function(t,e,r){for(var n=e.length,a=new Array(n),i=void 0===r?1e-6:r,o=0;o<n;++o)a[o]=[0,0,0];for(o=0;o<t.length;++o)for(var s=t[o],l=0,c=s[s.length-1],u=s[0],h=0;h<s.length;++h){l=c,c=u,u=s[(h+1)%s.length];for(var f=e[l],p=e[c],d=e[u],g=new Array(3),v=0,m=new Array(3),y=0,x=0;x<3;++x)g[x]=f[x]-p[x],v+=g[x]*g[x],m[x]=d[x]-p[x],y+=m[x]*m[x];if(v*y>i){var b=a[c],_=1/Math.sqrt(v*y);for(x=0;x<3;++x){var w=(x+1)%3,k=(x+2)%3;b[x]+=_*(m[w]*g[k]-m[k]*g[w])}}}for(o=0;o<n;++o){b=a[o];var T=0;for(x=0;x<3;++x)T+=b[x]*b[x];if(T>i)for(_=1/Math.sqrt(T),x=0;x<3;++x)b[x]*=_;else for(x=0;x<3;++x)b[x]=0}return a},r.faceNormals=function(t,e,r){for(var n=t.length,a=new Array(n),i=void 0===r?1e-6:r,o=0;o<n;++o){for(var s=t[o],l=new Array(3),c=0;c<3;++c)l[c]=e[s[c]];var u=new Array(3),h=new Array(3);for(c=0;c<3;++c)u[c]=l[1][c]-l[0][c],h[c]=l[2][c]-l[0][c];var f=new Array(3),p=0;for(c=0;c<3;++c){var d=(c+1)%3,g=(c+2)%3;f[c]=u[d]*h[g]-u[g]*h[d],p+=f[c]*f[c]}p=p>i?1/Math.sqrt(p):0;for(c=0;c<3;++c)f[c]*=p;a[o]=f}return a}},{}],456:[function(t,e,r){\"use strict\";var n=Object.getOwnPropertySymbols,a=Object.prototype.hasOwnProperty,i=Object.prototype.propertyIsEnumerable;e.exports=function(){try{if(!Object.assign)return!1;var t=new String(\"abc\");if(t[5]=\"de\",\"5\"===Object.getOwnPropertyNames(t)[0])return!1;for(var e={},r=0;r<10;r++)e[\"_\"+String.fromCharCode(r)]=r;if(\"0123456789\"!==Object.getOwnPropertyNames(e).map(function(t){return e[t]}).join(\"\"))return!1;var n={};return\"abcdefghijklmnopqrst\".split(\"\").forEach(function(t){n[t]=t}),\"abcdefghijklmnopqrst\"===Object.keys(Object.assign({},n)).join(\"\")}catch(t){return!1}}()?Object.assign:function(t,e){for(var r,o,s=function(t){if(null==t)throw new TypeError(\"Object.assign cannot be called with null or undefined\");return Object(t)}(t),l=1;l<arguments.length;l++){for(var c in r=Object(arguments[l]))a.call(r,c)&&(s[c]=r[c]);if(n){o=n(r);for(var u=0;u<o.length;u++)i.call(r,o[u])&&(s[o[u]]=r[o[u]])}}return s}},{}],457:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,a,i,o,s,l,c){var u=e+i+c;if(h>0){var h=Math.sqrt(u+1);t[0]=.5*(o-l)/h,t[1]=.5*(s-n)/h,t[2]=.5*(r-i)/h,t[3]=.5*h}else{var f=Math.max(e,i,c),h=Math.sqrt(2*f-u+1);e>=f?(t[0]=.5*h,t[1]=.5*(a+r)/h,t[2]=.5*(s+n)/h,t[3]=.5*(o-l)/h):i>=f?(t[0]=.5*(r+a)/h,t[1]=.5*h,t[2]=.5*(l+o)/h,t[3]=.5*(s-n)/h):(t[0]=.5*(n+s)/h,t[1]=.5*(o+l)/h,t[2]=.5*h,t[3]=.5*(r-a)/h)}return t}},{}],458:[function(t,e,r){\"use strict\";e.exports=function(t){var e=(t=t||{}).center||[0,0,0],r=t.rotation||[0,0,0,1],n=t.radius||1;e=[].slice.call(e,0,3),u(r=[].slice.call(r,0,4),r);var a=new h(r,e,Math.log(n));a.setDistanceLimits(t.zoomMin,t.zoomMax),(\"eye\"in t||\"up\"in t)&&a.lookAt(0,t.eye,t.center,t.up);return a};var n=t(\"filtered-vector\"),a=t(\"gl-mat4/lookAt\"),i=t(\"gl-mat4/fromQuat\"),o=t(\"gl-mat4/invert\"),s=t(\"./lib/quatFromFrame\");function l(t,e,r){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2))}function c(t,e,r,n){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2)+Math.pow(n,2))}function u(t,e){var r=e[0],n=e[1],a=e[2],i=e[3],o=c(r,n,a,i);o>1e-6?(t[0]=r/o,t[1]=n/o,t[2]=a/o,t[3]=i/o):(t[0]=t[1]=t[2]=0,t[3]=1)}function h(t,e,r){this.radius=n([r]),this.center=n(e),this.rotation=n(t),this.computedRadius=this.radius.curve(0),this.computedCenter=this.center.curve(0),this.computedRotation=this.rotation.curve(0),this.computedUp=[.1,0,0],this.computedEye=[.1,0,0],this.computedMatrix=[.1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],this.recalcMatrix(0)}var f=h.prototype;f.lastT=function(){return Math.max(this.radius.lastT(),this.center.lastT(),this.rotation.lastT())},f.recalcMatrix=function(t){this.radius.curve(t),this.center.curve(t),this.rotation.curve(t);var e=this.computedRotation;u(e,e);var r=this.computedMatrix;i(r,e);var n=this.computedCenter,a=this.computedEye,o=this.computedUp,s=Math.exp(this.computedRadius[0]);a[0]=n[0]+s*r[2],a[1]=n[1]+s*r[6],a[2]=n[2]+s*r[10],o[0]=r[1],o[1]=r[5],o[2]=r[9];for(var l=0;l<3;++l){for(var c=0,h=0;h<3;++h)c+=r[l+4*h]*a[h];r[12+l]=-c}},f.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;n<16;++n)e[n]=r[n];return e}return r},f.idle=function(t){this.center.idle(t),this.radius.idle(t),this.rotation.idle(t)},f.flush=function(t){this.center.flush(t),this.radius.flush(t),this.rotation.flush(t)},f.pan=function(t,e,r,n){e=e||0,r=r||0,n=n||0,this.recalcMatrix(t);var a=this.computedMatrix,i=a[1],o=a[5],s=a[9],c=l(i,o,s);i/=c,o/=c,s/=c;var u=a[0],h=a[4],f=a[8],p=u*i+h*o+f*s,d=l(u-=i*p,h-=o*p,f-=s*p);u/=d,h/=d,f/=d;var g=a[2],v=a[6],m=a[10],y=g*i+v*o+m*s,x=g*u+v*h+m*f,b=l(g-=y*i+x*u,v-=y*o+x*h,m-=y*s+x*f);g/=b,v/=b,m/=b;var _=u*e+i*r,w=h*e+o*r,k=f*e+s*r;this.center.move(t,_,w,k);var T=Math.exp(this.computedRadius[0]);T=Math.max(1e-4,T+n),this.radius.set(t,Math.log(T))},f.rotate=function(t,e,r,n){this.recalcMatrix(t),e=e||0,r=r||0;var a=this.computedMatrix,i=a[0],o=a[4],s=a[8],u=a[1],h=a[5],f=a[9],p=a[2],d=a[6],g=a[10],v=e*i+r*u,m=e*o+r*h,y=e*s+r*f,x=-(d*y-g*m),b=-(g*v-p*y),_=-(p*m-d*v),w=Math.sqrt(Math.max(0,1-Math.pow(x,2)-Math.pow(b,2)-Math.pow(_,2))),k=c(x,b,_,w);k>1e-6?(x/=k,b/=k,_/=k,w/=k):(x=b=_=0,w=1);var T=this.computedRotation,M=T[0],A=T[1],S=T[2],E=T[3],L=M*w+E*x+A*_-S*b,C=A*w+E*b+S*x-M*_,P=S*w+E*_+M*b-A*x,O=E*w-M*x-A*b-S*_;if(n){x=p,b=d,_=g;var z=Math.sin(n)/l(x,b,_);x*=z,b*=z,_*=z,O=O*(w=Math.cos(e))-(L=L*w+O*x+C*_-P*b)*x-(C=C*w+O*b+P*x-L*_)*b-(P=P*w+O*_+L*b-C*x)*_}var I=c(L,C,P,O);I>1e-6?(L/=I,C/=I,P/=I,O/=I):(L=C=P=0,O=1),this.rotation.set(t,L,C,P,O)},f.lookAt=function(t,e,r,n){this.recalcMatrix(t),r=r||this.computedCenter,e=e||this.computedEye,n=n||this.computedUp;var i=this.computedMatrix;a(i,e,r,n);var o=this.computedRotation;s(o,i[0],i[1],i[2],i[4],i[5],i[6],i[8],i[9],i[10]),u(o,o),this.rotation.set(t,o[0],o[1],o[2],o[3]);for(var l=0,c=0;c<3;++c)l+=Math.pow(r[c]-e[c],2);this.radius.set(t,.5*Math.log(Math.max(l,1e-6))),this.center.set(t,r[0],r[1],r[2])},f.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},f.setMatrix=function(t,e){var r=this.computedRotation;s(r,e[0],e[1],e[2],e[4],e[5],e[6],e[8],e[9],e[10]),u(r,r),this.rotation.set(t,r[0],r[1],r[2],r[3]);var n=this.computedMatrix;o(n,e);var a=n[15];if(Math.abs(a)>1e-6){var i=n[12]/a,l=n[13]/a,c=n[14]/a;this.recalcMatrix(t);var h=Math.exp(this.computedRadius[0]);this.center.set(t,i-n[2]*h,l-n[6]*h,c-n[10]*h),this.radius.idle(t)}else this.center.idle(t),this.radius.idle(t)},f.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},f.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-1/0,e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},f.getDistanceLimits=function(t){var e=this.radius.bounds;return t?(t[0]=Math.exp(e[0][0]),t[1]=Math.exp(e[1][0]),t):[Math.exp(e[0][0]),Math.exp(e[1][0])]},f.toJSON=function(){return this.recalcMatrix(this.lastT()),{center:this.computedCenter.slice(),rotation:this.computedRotation.slice(),distance:Math.log(this.computedRadius[0]),zoomMin:this.radius.bounds[0][0],zoomMax:this.radius.bounds[1][0]}},f.fromJSON=function(t){var e=this.lastT(),r=t.center;r&&this.center.set(e,r[0],r[1],r[2]);var n=t.rotation;n&&this.rotation.set(e,n[0],n[1],n[2],n[3]);var a=t.distance;a&&a>0&&this.radius.set(e,Math.log(a)),this.setDistanceLimits(t.zoomMin,t.zoomMax)}},{\"./lib/quatFromFrame\":457,\"filtered-vector\":229,\"gl-mat4/fromQuat\":265,\"gl-mat4/invert\":268,\"gl-mat4/lookAt\":269}],459:[function(t,e,r){\"use strict\";var n=t(\"repeat-string\");e.exports=function(t,e,r){return n(r=\"undefined\"!=typeof r?r+\"\":\" \",e)+t}},{\"repeat-string\":502}],460:[function(t,e,r){\"use strict\";function n(t,e){if(\"string\"!=typeof t)return[t];var r=[t];\"string\"==typeof e||Array.isArray(e)?e={brackets:e}:e||(e={});var n=e.brackets?Array.isArray(e.brackets)?e.brackets:[e.brackets]:[\"{}\",\"[]\",\"()\"],a=e.escape||\"___\",i=!!e.flat;n.forEach(function(t){var e=new RegExp([\"\\\\\",t[0],\"[^\\\\\",t[0],\"\\\\\",t[1],\"]*\\\\\",t[1]].join(\"\")),n=[];function i(e,i,o){var s=r.push(e.slice(t[0].length,-t[1].length))-1;return n.push(s),a+s+a}r.forEach(function(t,n){for(var a,o=0;t!=a;)if(a=t,t=t.replace(e,i),o++>1e4)throw Error(\"References have circular dependency. Please, check them.\");r[n]=t}),n=n.reverse(),r=r.map(function(e){return n.forEach(function(r){e=e.replace(new RegExp(\"(\\\\\"+a+r+\"\\\\\"+a+\")\",\"g\"),t[0]+\"$1\"+t[1])}),e})});var o=new RegExp(\"\\\\\"+a+\"([0-9]+)\\\\\"+a);return i?r:function t(e,r,n){for(var a,i=[],s=0;a=o.exec(e);){if(s++>1e4)throw Error(\"Circular references in parenthesis\");i.push(e.slice(0,a.index)),i.push(t(r[a[1]],r)),e=e.slice(a.index+a[0].length)}return i.push(e),i}(r[0],r)}function a(t,e){if(e&&e.flat){var r,n=e&&e.escape||\"___\",a=t[0];if(!a)return\"\";for(var i=new RegExp(\"\\\\\"+n+\"([0-9]+)\\\\\"+n),o=0;a!=r;){if(o++>1e4)throw Error(\"Circular references in \"+t);r=a,a=a.replace(i,s)}return a}return t.reduce(function t(e,r){return Array.isArray(r)&&(r=r.reduce(t,\"\")),e+r},\"\");function s(e,r){if(null==t[r])throw Error(\"Reference \"+r+\"is undefined\");return t[r]}}function i(t,e){return Array.isArray(t)?a(t,e):n(t,e)}i.parse=n,i.stringify=a,e.exports=i},{}],461:[function(t,e,r){\"use strict\";var n=t(\"pick-by-alias\");e.exports=function(t){var e;arguments.length>1&&(t=arguments);\"string\"==typeof t?t=t.split(/\\s/).map(parseFloat):\"number\"==typeof t&&(t=[t]);t.length&&\"number\"==typeof t[0]?e=1===t.length?{width:t[0],height:t[0],x:0,y:0}:2===t.length?{width:t[0],height:t[1],x:0,y:0}:{x:t[0],y:t[1],width:t[2]-t[0]||0,height:t[3]-t[1]||0}:t&&(t=n(t,{left:\"x l left Left\",top:\"y t top Top\",width:\"w width W Width\",height:\"h height W Width\",bottom:\"b bottom Bottom\",right:\"r right Right\"}),e={x:t.left||0,y:t.top||0},null==t.width?t.right?e.width=t.right-e.x:e.width=0:e.width=t.width,null==t.height?t.bottom?e.height=t.bottom-e.y:e.height=0:e.height=t.height);return e}},{\"pick-by-alias\":467}],462:[function(t,e,r){e.exports=function(t){var e=[];return t.replace(a,function(t,r,a){var o=r.toLowerCase();for(a=function(t){var e=t.match(i);return e?e.map(Number):[]}(a),\"m\"==o&&a.length>2&&(e.push([r].concat(a.splice(0,2))),o=\"l\",r=\"m\"==r?\"l\":\"L\");;){if(a.length==n[o])return a.unshift(r),e.push(a);if(a.length<n[o])throw new Error(\"malformed path data\");e.push([r].concat(a.splice(0,n[o])))}}),e};var n={a:7,c:6,h:1,l:2,m:2,q:4,s:4,t:2,v:1,z:0},a=/([astvzqmhlc])([^astvzqmhlc]*)/gi;var i=/-?[0-9]*\\.?[0-9]+(?:e[-+]?\\d+)?/gi},{}],463:[function(t,e,r){e.exports=function(t,e){e||(e=[0,\"\"]),t=String(t);var r=parseFloat(t,10);return e[0]=r,e[1]=t.match(/[\\d.\\-\\+]*\\s*(.*)/)[1]||\"\",e}},{}],464:[function(t,e,r){(function(t){(function(){var r,n,a,i,o,s;\"undefined\"!=typeof performance&&null!==performance&&performance.now?e.exports=function(){return performance.now()}:\"undefined\"!=typeof t&&null!==t&&t.hrtime?(e.exports=function(){return(r()-o)/1e6},n=t.hrtime,i=(r=function(){var t;return 1e9*(t=n())[0]+t[1]})(),s=1e9*t.uptime(),o=i-s):Date.now?(e.exports=function(){return Date.now()-a},a=Date.now()):(e.exports=function(){return(new Date).getTime()-a},a=(new Date).getTime())}).call(this)}).call(this,t(\"_process\"))},{_process:484}],465:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.length;if(e<n){for(var r=1,i=0;i<e;++i)for(var o=0;o<i;++o)if(t[i]<t[o])r=-r;else if(t[i]===t[o])return 0;return r}for(var s=a.mallocUint8(e),i=0;i<e;++i)s[i]=0;for(var r=1,i=0;i<e;++i)if(!s[i]){var l=1;s[i]=1;for(var o=t[i];o!==i;o=t[o]){if(s[o])return a.freeUint8(s),0;l+=1,s[o]=1}1&l||(r=-r)}return a.freeUint8(s),r};var n=32,a=t(\"typedarray-pool\")},{\"typedarray-pool\":544}],466:[function(t,e,r){\"use strict\";var n=t(\"typedarray-pool\"),a=t(\"invert-permutation\");r.rank=function(t){var e=t.length;switch(e){case 0:case 1:return 0;case 2:return t[1]}var r,i,o,s=n.mallocUint32(e),l=n.mallocUint32(e),c=0;for(a(t,l),o=0;o<e;++o)s[o]=t[o];for(o=e-1;o>0;--o)i=l[o],r=s[o],s[o]=s[i],s[i]=r,l[o]=l[r],l[r]=i,c=(c+r)*o;return n.freeUint32(l),n.freeUint32(s),c},r.unrank=function(t,e,r){switch(t){case 0:return r||[];case 1:return r?(r[0]=0,r):[0];case 2:return r?(e?(r[0]=0,r[1]=1):(r[0]=1,r[1]=0),r):e?[0,1]:[1,0]}var n,a,i,o=1;for((r=r||new Array(t))[0]=0,i=1;i<t;++i)r[i]=i,o=o*i|0;for(i=t-1;i>0;--i)e=e-(n=e/o|0)*o|0,o=o/i|0,a=0|r[i],r[i]=0|r[n],r[n]=0|a;return r}},{\"invert-permutation\":417,\"typedarray-pool\":544}],467:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){var n,i,o={};if(\"string\"==typeof e&&(e=a(e)),Array.isArray(e)){var s={};for(i=0;i<e.length;i++)s[e[i]]=!0;e=s}for(n in e)e[n]=a(e[n]);var l={};for(n in e){var c=e[n];if(Array.isArray(c))for(i=0;i<c.length;i++){var u=c[i];if(r&&(l[u]=!0),u in t){if(o[n]=t[u],r)for(var h=i;h<c.length;h++)l[c[h]]=!0;break}}else n in t&&(e[n]&&(o[n]=t[n]),r&&(l[n]=!0))}if(r)for(n in t)l[n]||(o[n]=t[n]);return o};var n={};function a(t){return n[t]?n[t]:(\"string\"==typeof t&&(t=n[t]=t.split(/\\s*,\\s*|\\s+/)),t)}},{}],468:[function(t,e,r){\"use strict\";e.exports=function(t,e){for(var r=0|e.length,a=t.length,i=[new Array(r),new Array(r)],o=0;o<r;++o)i[0][o]=[],i[1][o]=[];for(var o=0;o<a;++o){var s=t[o];i[0][s[0]].push(s),i[1][s[1]].push(s)}for(var l=[],o=0;o<r;++o)i[0][o].length+i[1][o].length===0&&l.push([o]);function c(t,e){var r=i[e][t[e]];r.splice(r.indexOf(t),1)}function u(t,r,a){for(var o,s,l,u=0;u<2;++u)if(i[u][r].length>0){o=i[u][r][0],l=u;break}s=o[1^l];for(var h=0;h<2;++h)for(var f=i[h][r],p=0;p<f.length;++p){var d=f[p],g=d[1^h],v=n(e[t],e[r],e[s],e[g]);v>0&&(o=d,s=g,l=h)}return a?s:(o&&c(o,l),s)}function h(t,r){var a=i[r][t][0],o=[t];c(a,r);for(var s=a[1^r];;){for(;s!==t;)o.push(s),s=u(o[o.length-2],s,!1);if(i[0][t].length+i[1][t].length===0)break;var l=o[o.length-1],h=t,f=o[1],p=u(l,h,!0);if(n(e[l],e[h],e[f],e[p])<0)break;o.push(t),s=u(l,h)}return o}function f(t,e){return e[1]===e[e.length-1]}for(var o=0;o<r;++o)for(var p=0;p<2;++p){for(var d=[];i[p][o].length>0;){i[0][o].length;var g=h(o,p);f(d,g)?d.push.apply(d,g):(d.length>0&&l.push(d),d=g)}d.length>0&&l.push(d)}return l};var n=t(\"compare-angle\")},{\"compare-angle\":129}],469:[function(t,e,r){\"use strict\";e.exports=function(t,e){for(var r=n(t,e.length),a=new Array(e.length),i=new Array(e.length),o=[],s=0;s<e.length;++s){var l=r[s].length;i[s]=l,a[s]=!0,l<=1&&o.push(s)}for(;o.length>0;){var c=o.pop();a[c]=!1;for(var u=r[c],s=0;s<u.length;++s){var h=u[s];0==--i[h]&&o.push(h)}}for(var f=new Array(e.length),p=[],s=0;s<e.length;++s)if(a[s]){var c=p.length;f[s]=c,p.push(e[s])}else f[s]=-1;for(var d=[],s=0;s<t.length;++s){var g=t[s];a[g[0]]&&a[g[1]]&&d.push([f[g[0]],f[g[1]]])}return[d,p]};var n=t(\"edges-to-adjacency-list\")},{\"edges-to-adjacency-list\":174}],470:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=c(t,e);t=r[0];for(var h=(e=r[1]).length,f=(t.length,n(t,e.length)),p=0;p<h;++p)if(f[p].length%2==1)throw new Error(\"planar-graph-to-polyline: graph must be manifold\");var d=a(t,e);for(var g=(d=d.filter(function(t){for(var r=t.length,n=[0],a=0;a<r;++a){var i=e[t[a]],l=e[t[(a+1)%r]],c=o(-i[0],i[1]),u=o(-i[0],l[1]),h=o(l[0],i[1]),f=o(l[0],l[1]);n=s(n,s(s(c,u),s(h,f)))}return n[n.length-1]>0})).length,v=new Array(g),m=new Array(g),p=0;p<g;++p){v[p]=p;var y=new Array(g),x=d[p].map(function(t){return e[t]}),b=i([x]),_=0;t:for(var w=0;w<g;++w)if(y[w]=0,p!==w){for(var k=d[w],T=k.length,M=0;M<T;++M){var A=b(e[k[M]]);if(0!==A){A<0&&(y[w]=1,_+=1);continue t}}y[w]=1,_+=1}m[p]=[_,p,y]}m.sort(function(t,e){return e[0]-t[0]});for(var p=0;p<g;++p)for(var y=m[p],S=y[1],E=y[2],w=0;w<g;++w)E[w]&&(v[w]=S);for(var L=function(t){for(var e=new Array(t),r=0;r<t;++r)e[r]=[];return e}(g),p=0;p<g;++p)L[p].push(v[p]),L[v[p]].push(p);for(var C={},P=u(h,!1),p=0;p<g;++p)for(var k=d[p],T=k.length,w=0;w<T;++w){var O=k[w],z=k[(w+1)%T],I=Math.min(O,z)+\":\"+Math.max(O,z);if(I in C){var D=C[I];L[D].push(p),L[p].push(D),P[O]=P[z]=!0}else C[I]=p}function R(t){for(var e=t.length,r=0;r<e;++r)if(!P[t[r]])return!1;return!0}for(var F=[],B=u(g,-1),p=0;p<g;++p)v[p]!==p||R(d[p])?B[p]=-1:(F.push(p),B[p]=0);var r=[];for(;F.length>0;){var N=F.pop(),j=L[N];l(j,function(t,e){return t-e});var V,U=j.length,q=B[N];if(0===q){var k=d[N];V=[k]}for(var p=0;p<U;++p){var H=j[p];if(!(B[H]>=0)&&(B[H]=1^q,F.push(H),0===q)){var k=d[H];R(k)||(k.reverse(),V.push(k))}}0===q&&r.push(V)}return r};var n=t(\"edges-to-adjacency-list\"),a=t(\"planar-dual\"),i=t(\"point-in-big-polygon\"),o=t(\"two-product\"),s=t(\"robust-sum\"),l=t(\"uniq\"),c=t(\"./lib/trim-leaves\");function u(t,e){for(var r=new Array(t),n=0;n<t;++n)r[n]=e;return r}},{\"./lib/trim-leaves\":469,\"edges-to-adjacency-list\":174,\"planar-dual\":468,\"point-in-big-polygon\":474,\"robust-sum\":514,\"two-product\":542,uniq:546}],471:[function(t,e,r){\"use strict\";e.exports=t(\"./quad\")},{\"./quad\":473}],472:[function(t,e,r){arguments[4][113][0].apply(r,arguments)},{dup:113}],473:[function(t,e,r){\"use strict\";var n=t(\"binary-search-bounds\"),a=t(\"clamp\"),i=t(\"parse-rect\"),o=t(\"array-bounds\"),s=t(\"pick-by-alias\"),l=t(\"defined\"),c=t(\"flatten-vertex-data\"),u=t(\"is-obj\"),h=t(\"dtype\"),f=t(\"math-log2\"),p=1073741824;function d(t,e){for(var r=e[0],n=e[1],i=1/(e[2]-r),o=1/(e[3]-n),s=new Array(t.length),l=0,c=t.length/2;l<c;l++)s[2*l]=a((t[2*l]-r)*i,0,1),s[2*l+1]=a((t[2*l+1]-n)*o,0,1);return s}e.exports=function(t,e){e||(e={}),t=c(t,\"float64\"),e=s(e,{bounds:\"range bounds dataBox databox\",maxDepth:\"depth maxDepth maxdepth level maxLevel maxlevel levels\",dtype:\"type dtype format out dst output destination\"});var r=l(e.maxDepth,255),a=l(e.bounds,o(t,2));a[0]===a[2]&&a[2]++,a[1]===a[3]&&a[3]++;var g,v=d(t,a),m=t.length>>>1;e.dtype||(e.dtype=\"array\"),\"string\"==typeof e.dtype?g=new(h(e.dtype))(m):e.dtype&&(g=e.dtype,Array.isArray(g)&&(g.length=m));for(var y=0;y<m;++y)g[y]=y;var x=[],b=[],_=[],w=[];!function t(e,n,a,i,o,s){if(!i.length)return null;var l=x[o]||(x[o]=[]);var c=_[o]||(_[o]=[]);var u=b[o]||(b[o]=[]);var h=l.length;o++;if(o>r||s>p){for(var f=0;f<i.length;f++)l.push(i[f]),c.push(s),u.push(null,null,null,null);return h}l.push(i[0]);c.push(s);if(i.length<=1)return u.push(null,null,null,null),h;var d=.5*a;var g=e+d,m=n+d;var y=[],w=[],k=[],T=[];for(var M=1,A=i.length;M<A;M++){var S=i[M],E=v[2*S],L=v[2*S+1];E<g?L<m?y.push(S):w.push(S):L<m?k.push(S):T.push(S)}s<<=2;u.push(t(e,n,d,y,o,s),t(e,m,d,w,o,s+1),t(g,n,d,k,o,s+2),t(g,m,d,T,o,s+3));return h}(0,0,1,g,0,1);for(var k=0,T=0;T<x.length;T++){var M=x[T];if(g.set)g.set(M,k);else for(var A=0,S=M.length;A<S;A++)g[A+k]=M[A];var E=k+x[T].length;w[T]=[k,E],k=E}return g.range=function(){var e,r=[],o=arguments.length;for(;o--;)r[o]=arguments[o];if(u(r[r.length-1])){var c=r.pop();r.length||null==c.x&&null==c.l&&null==c.left||(r=[c],e={}),e=s(c,{level:\"level maxLevel\",d:\"d diam diameter r radius px pxSize pixel pixelSize maxD size minSize\",lod:\"lod details ranges offsets\"})}else e={};r.length||(r=a);var h=i.apply(void 0,r),p=[Math.min(h.x,h.x+h.width),Math.min(h.y,h.y+h.height),Math.max(h.x,h.x+h.width),Math.max(h.y,h.y+h.height)],g=p[0],v=p[1],m=p[2],y=p[3],k=d([g,v,m,y],a),T=k[0],M=k[1],A=k[2],S=k[3],E=l(e.level,x.length);if(null!=e.d){var C;\"number\"==typeof e.d?C=[e.d,e.d]:e.d.length&&(C=e.d),E=Math.min(Math.max(Math.ceil(-f(Math.abs(C[0])/(a[2]-a[0]))),Math.ceil(-f(Math.abs(C[1])/(a[3]-a[1])))),E)}if(E=Math.min(E,x.length),e.lod)return function(t,e,r,a,i){for(var o=[],s=0;s<i;s++){var l=_[s],c=w[s][0],u=L(t,e,s),h=L(r,a,s),f=n.ge(l,u),p=n.gt(l,h,f,l.length-1);o[s]=[f+c,p+c]}return o}(T,M,A,S,E);var P=[];return function e(r,n,a,i,o,s){if(null!==o&&null!==s){var l=r+a,c=n+a;if(!(T>l||M>c||A<r||S<n||i>=E||o===s)){var u=x[i];void 0===s&&(s=u.length);for(var h=o;h<s;h++){var f=u[h],p=t[2*f],d=t[2*f+1];p>=g&&p<=m&&d>=v&&d<=y&&P.push(f)}var _=b[i],w=_[4*o+0],k=_[4*o+1],L=_[4*o+2],C=_[4*o+3],O=function(t,e){for(var r=null,n=0;null===r;)if(r=t[4*e+n],++n>t.length)return null;return r}(_,o+1),z=.5*a,I=i+1;e(r,n,z,I,w,k||L||C||O),e(r,n+z,z,I,k,L||C||O),e(r+z,n,z,I,L,C||O),e(r+z,n+z,z,I,C,O)}}}(0,0,1,0,0,1),P},g;function L(t,e,r){for(var n=1,a=.5,i=.5,o=.5,s=0;s<r;s++)n<<=2,n+=t<a?e<i?0:1:e<i?2:3,o*=.5,a+=t<a?-o:o,i+=e<i?-o:o;return n}}},{\"array-bounds\":68,\"binary-search-bounds\":472,clamp:117,defined:166,dtype:171,\"flatten-vertex-data\":230,\"is-obj\":423,\"math-log2\":434,\"parse-rect\":461,\"pick-by-alias\":467}],474:[function(t,e,r){e.exports=function(t){for(var e=t.length,r=[],i=[],s=0;s<e;++s)for(var u=t[s],h=u.length,f=h-1,p=0;p<h;f=p++){var d=u[f],g=u[p];d[0]===g[0]?i.push([d,g]):r.push([d,g])}if(0===r.length)return 0===i.length?c:(v=l(i),function(t){return v(t[0],t[1])?0:1});var v;var m=a(r),y=function(t,e){return function(r){var a=o.le(e,r[0]);if(a<0)return 1;var i=t[a];if(!i){if(!(a>0&&e[a]===r[0]))return 1;i=t[a-1]}for(var s=1;i;){var l=i.key,c=n(r,l[0],l[1]);if(l[0][0]<l[1][0])if(c<0)i=i.left;else{if(!(c>0))return 0;s=-1,i=i.right}else if(c>0)i=i.left;else{if(!(c<0))return 0;s=1,i=i.right}}return s}}(m.slabs,m.coordinates);return 0===i.length?y:function(t,e){return function(r){return t(r[0],r[1])?0:e(r)}}(l(i),y)};var n=t(\"robust-orientation\")[3],a=t(\"slab-decomposition\"),i=t(\"interval-tree-1d\"),o=t(\"binary-search-bounds\");function s(){return!0}function l(t){for(var e={},r=0;r<t.length;++r){var n=t[r],a=n[0][0],o=n[0][1],l=n[1][1],c=[Math.min(o,l),Math.max(o,l)];a in e?e[a].push(c):e[a]=[c]}var u={},h=Object.keys(e);for(r=0;r<h.length;++r){var f=e[h[r]];u[h[r]]=i(f)}return function(t){return function(e,r){var n=t[e];return!!n&&!!n.queryPoint(r,s)}}(u)}function c(t){return 1}},{\"binary-search-bounds\":93,\"interval-tree-1d\":416,\"robust-orientation\":509,\"slab-decomposition\":525}],475:[function(t,e,r){var n,a=t(\"./lib/build-log\"),i=t(\"./lib/epsilon\"),o=t(\"./lib/intersecter\"),s=t(\"./lib/segment-chainer\"),l=t(\"./lib/segment-selector\"),c=t(\"./lib/geojson\"),u=!1,h=i();function f(t,e,r){var a=n.segments(t),i=n.segments(e),o=r(n.combine(a,i));return n.polygon(o)}n={buildLog:function(t){return!0===t?u=a():!1===t&&(u=!1),!1!==u&&u.list},epsilon:function(t){return h.epsilon(t)},segments:function(t){var e=o(!0,h,u);return t.regions.forEach(e.addRegion),{segments:e.calculate(t.inverted),inverted:t.inverted}},combine:function(t,e){return{combined:o(!1,h,u).calculate(t.segments,t.inverted,e.segments,e.inverted),inverted1:t.inverted,inverted2:e.inverted}},selectUnion:function(t){return{segments:l.union(t.combined,u),inverted:t.inverted1||t.inverted2}},selectIntersect:function(t){return{segments:l.intersect(t.combined,u),inverted:t.inverted1&&t.inverted2}},selectDifference:function(t){return{segments:l.difference(t.combined,u),inverted:t.inverted1&&!t.inverted2}},selectDifferenceRev:function(t){return{segments:l.differenceRev(t.combined,u),inverted:!t.inverted1&&t.inverted2}},selectXor:function(t){return{segments:l.xor(t.combined,u),inverted:t.inverted1!==t.inverted2}},polygon:function(t){return{regions:s(t.segments,h,u),inverted:t.inverted}},polygonFromGeoJSON:function(t){return c.toPolygon(n,t)},polygonToGeoJSON:function(t){return c.fromPolygon(n,h,t)},union:function(t,e){return f(t,e,n.selectUnion)},intersect:function(t,e){return f(t,e,n.selectIntersect)},difference:function(t,e){return f(t,e,n.selectDifference)},differenceRev:function(t,e){return f(t,e,n.selectDifferenceRev)},xor:function(t,e){return f(t,e,n.selectXor)}},\"object\"==typeof window&&(window.PolyBool=n),e.exports=n},{\"./lib/build-log\":476,\"./lib/epsilon\":477,\"./lib/geojson\":478,\"./lib/intersecter\":479,\"./lib/segment-chainer\":481,\"./lib/segment-selector\":482}],476:[function(t,e,r){e.exports=function(){var t,e=0,r=!1;function n(e,r){return t.list.push({type:e,data:r?JSON.parse(JSON.stringify(r)):void 0}),t}return t={list:[],segmentId:function(){return e++},checkIntersection:function(t,e){return n(\"check\",{seg1:t,seg2:e})},segmentChop:function(t,e){return n(\"div_seg\",{seg:t,pt:e}),n(\"chop\",{seg:t,pt:e})},statusRemove:function(t){return n(\"pop_seg\",{seg:t})},segmentUpdate:function(t){return n(\"seg_update\",{seg:t})},segmentNew:function(t,e){return n(\"new_seg\",{seg:t,primary:e})},segmentRemove:function(t){return n(\"rem_seg\",{seg:t})},tempStatus:function(t,e,r){return n(\"temp_status\",{seg:t,above:e,below:r})},rewind:function(t){return n(\"rewind\",{seg:t})},status:function(t,e,r){return n(\"status\",{seg:t,above:e,below:r})},vert:function(e){return e===r?t:(r=e,n(\"vert\",{x:e}))},log:function(t){return\"string\"!=typeof t&&(t=JSON.stringify(t,!1,\"  \")),n(\"log\",{txt:t})},reset:function(){return n(\"reset\")},selected:function(t){return n(\"selected\",{segs:t})},chainStart:function(t){return n(\"chain_start\",{seg:t})},chainRemoveHead:function(t,e){return n(\"chain_rem_head\",{index:t,pt:e})},chainRemoveTail:function(t,e){return n(\"chain_rem_tail\",{index:t,pt:e})},chainNew:function(t,e){return n(\"chain_new\",{pt1:t,pt2:e})},chainMatch:function(t){return n(\"chain_match\",{index:t})},chainClose:function(t){return n(\"chain_close\",{index:t})},chainAddHead:function(t,e){return n(\"chain_add_head\",{index:t,pt:e})},chainAddTail:function(t,e){return n(\"chain_add_tail\",{index:t,pt:e})},chainConnect:function(t,e){return n(\"chain_con\",{index1:t,index2:e})},chainReverse:function(t){return n(\"chain_rev\",{index:t})},chainJoin:function(t,e){return n(\"chain_join\",{index1:t,index2:e})},done:function(){return n(\"done\")}}}},{}],477:[function(t,e,r){e.exports=function(t){\"number\"!=typeof t&&(t=1e-10);var e={epsilon:function(e){return\"number\"==typeof e&&(t=e),t},pointAboveOrOnLine:function(e,r,n){var a=r[0],i=r[1],o=n[0],s=n[1],l=e[0];return(o-a)*(e[1]-i)-(s-i)*(l-a)>=-t},pointBetween:function(e,r,n){var a=e[1]-r[1],i=n[0]-r[0],o=e[0]-r[0],s=n[1]-r[1],l=o*i+a*s;return!(l<t||l-(i*i+s*s)>-t)},pointsSameX:function(e,r){return Math.abs(e[0]-r[0])<t},pointsSameY:function(e,r){return Math.abs(e[1]-r[1])<t},pointsSame:function(t,r){return e.pointsSameX(t,r)&&e.pointsSameY(t,r)},pointsCompare:function(t,r){return e.pointsSameX(t,r)?e.pointsSameY(t,r)?0:t[1]<r[1]?-1:1:t[0]<r[0]?-1:1},pointsCollinear:function(e,r,n){var a=e[0]-r[0],i=e[1]-r[1],o=r[0]-n[0],s=r[1]-n[1];return Math.abs(a*s-o*i)<t},linesIntersect:function(e,r,n,a){var i=r[0]-e[0],o=r[1]-e[1],s=a[0]-n[0],l=a[1]-n[1],c=i*l-o*s;if(Math.abs(c)<t)return!1;var u=e[0]-n[0],h=e[1]-n[1],f=(s*h-l*u)/c,p=(i*h-o*u)/c,d={alongA:0,alongB:0,pt:[e[0]+f*i,e[1]+f*o]};return d.alongA=f<=-t?-2:f<t?-1:f-1<=-t?0:f-1<t?1:2,d.alongB=p<=-t?-2:p<t?-1:p-1<=-t?0:p-1<t?1:2,d},pointInsideRegion:function(e,r){for(var n=e[0],a=e[1],i=r[r.length-1][0],o=r[r.length-1][1],s=!1,l=0;l<r.length;l++){var c=r[l][0],u=r[l][1];u-a>t!=o-a>t&&(i-c)*(a-u)/(o-u)+c-n>t&&(s=!s),i=c,o=u}return s}};return e}},{}],478:[function(t,e,r){var n={toPolygon:function(t,e){function r(e){if(e.length<=0)return t.segments({inverted:!1,regions:[]});function r(e){var r=e.slice(0,e.length-1);return t.segments({inverted:!1,regions:[r]})}for(var n=r(e[0]),a=1;a<e.length;a++)n=t.selectDifference(t.combine(n,r(e[a])));return n}if(\"Polygon\"===e.type)return t.polygon(r(e.coordinates));if(\"MultiPolygon\"===e.type){for(var n=t.segments({inverted:!1,regions:[]}),a=0;a<e.coordinates.length;a++)n=t.selectUnion(t.combine(n,r(e.coordinates[a])));return t.polygon(n)}throw new Error(\"PolyBool: Cannot convert GeoJSON object to PolyBool polygon\")},fromPolygon:function(t,e,r){function n(t,r){return e.pointInsideRegion([.5*(t[0][0]+t[1][0]),.5*(t[0][1]+t[1][1])],r)}function a(t){return{region:t,children:[]}}r=t.polygon(t.segments(r));var i=a(null);function o(t,e){for(var r=0;r<t.children.length;r++){if(n(e,(s=t.children[r]).region))return void o(s,e)}var i=a(e);for(r=0;r<t.children.length;r++){var s;n((s=t.children[r]).region,e)&&(i.children.push(s),t.children.splice(r,1),r--)}t.children.push(i)}for(var s=0;s<r.regions.length;s++){var l=r.regions[s];l.length<3||o(i,l)}function c(t,e){for(var r=0,n=t[t.length-1][0],a=t[t.length-1][1],i=[],o=0;o<t.length;o++){var s=t[o][0],l=t[o][1];i.push([s,l]),r+=l*n-s*a,n=s,a=l}return r<0!==e&&i.reverse(),i.push([i[0][0],i[0][1]]),i}var u=[];function h(t){var e=[c(t.region,!1)];u.push(e);for(var r=0;r<t.children.length;r++)e.push(f(t.children[r]))}function f(t){for(var e=0;e<t.children.length;e++)h(t.children[e]);return c(t.region,!0)}for(s=0;s<i.children.length;s++)h(i.children[s]);return u.length<=0?{type:\"Polygon\",coordinates:[]}:1==u.length?{type:\"Polygon\",coordinates:u[0]}:{type:\"MultiPolygon\",coordinates:u}}};e.exports=n},{}],479:[function(t,e,r){var n=t(\"./linked-list\");e.exports=function(t,e,r){function a(t,e,n){return{id:r?r.segmentId():-1,start:t,end:e,myFill:{above:n.myFill.above,below:n.myFill.below},otherFill:null}}var i=n.create();function o(t,r){i.insertBefore(t,function(n){return function(t,r,n,a,i,o){var s=e.pointsCompare(r,i);return 0!==s?s:e.pointsSame(n,o)?0:t!==a?t?1:-1:e.pointAboveOrOnLine(n,a?i:o,a?o:i)?1:-1}(t.isStart,t.pt,r,n.isStart,n.pt,n.other.pt)<0})}function s(t,e){var r=function(t,e){var r=n.node({isStart:!0,pt:t.start,seg:t,primary:e,other:null,status:null});return o(r,t.end),r}(t,e);return function(t,e,r){var a=n.node({isStart:!1,pt:e.end,seg:e,primary:r,other:t,status:null});t.other=a,o(a,t.pt)}(r,t,e),r}function l(t,e){var n=a(e,t.seg.end,t.seg);return function(t,e){r&&r.segmentChop(t.seg,e),t.other.remove(),t.seg.end=e,t.other.pt=e,o(t.other,t.pt)}(t,e),s(n,t.primary)}function c(a,o){var s=n.create();function c(t){return s.findTransition(function(r){var n,a,i,o,s,l;return n=t,a=r.ev,i=n.seg.start,o=n.seg.end,s=a.seg.start,l=a.seg.end,(e.pointsCollinear(i,s,l)?e.pointsCollinear(o,s,l)?1:e.pointAboveOrOnLine(o,s,l)?1:-1:e.pointAboveOrOnLine(i,s,l)?1:-1)>0})}function u(t,n){var a=t.seg,i=n.seg,o=a.start,s=a.end,c=i.start,u=i.end;r&&r.checkIntersection(a,i);var h=e.linesIntersect(o,s,c,u);if(!1===h){if(!e.pointsCollinear(o,s,c))return!1;if(e.pointsSame(o,u)||e.pointsSame(s,c))return!1;var f=e.pointsSame(o,c),p=e.pointsSame(s,u);if(f&&p)return n;var d=!f&&e.pointBetween(o,c,u),g=!p&&e.pointBetween(s,c,u);if(f)return g?l(n,s):l(t,u),n;d&&(p||(g?l(n,s):l(t,u)),l(n,o))}else 0===h.alongA&&(-1===h.alongB?l(t,c):0===h.alongB?l(t,h.pt):1===h.alongB&&l(t,u)),0===h.alongB&&(-1===h.alongA?l(n,o):0===h.alongA?l(n,h.pt):1===h.alongA&&l(n,s));return!1}for(var h=[];!i.isEmpty();){var f=i.getHead();if(r&&r.vert(f.pt[0]),f.isStart){r&&r.segmentNew(f.seg,f.primary);var p=c(f),d=p.before?p.before.ev:null,g=p.after?p.after.ev:null;function v(){if(d){var t=u(f,d);if(t)return t}return!!g&&u(f,g)}r&&r.tempStatus(f.seg,!!d&&d.seg,!!g&&g.seg);var m,y,x=v();if(x)t?(y=null===f.seg.myFill.below||f.seg.myFill.above!==f.seg.myFill.below)&&(x.seg.myFill.above=!x.seg.myFill.above):x.seg.otherFill=f.seg.myFill,r&&r.segmentUpdate(x.seg),f.other.remove(),f.remove();if(i.getHead()!==f){r&&r.rewind(f.seg);continue}t?(y=null===f.seg.myFill.below||f.seg.myFill.above!==f.seg.myFill.below,f.seg.myFill.below=g?g.seg.myFill.above:a,f.seg.myFill.above=y?!f.seg.myFill.below:f.seg.myFill.below):null===f.seg.otherFill&&(m=g?f.primary===g.primary?g.seg.otherFill.above:g.seg.myFill.above:f.primary?o:a,f.seg.otherFill={above:m,below:m}),r&&r.status(f.seg,!!d&&d.seg,!!g&&g.seg),f.other.status=p.insert(n.node({ev:f}))}else{var b=f.status;if(null===b)throw new Error(\"PolyBool: Zero-length segment detected; your epsilon is probably too small or too large\");if(s.exists(b.prev)&&s.exists(b.next)&&u(b.prev.ev,b.next.ev),r&&r.statusRemove(b.ev.seg),b.remove(),!f.primary){var _=f.seg.myFill;f.seg.myFill=f.seg.otherFill,f.seg.otherFill=_}h.push(f.seg)}i.getHead().remove()}return r&&r.done(),h}return t?{addRegion:function(t){for(var n,a,i,o=t[t.length-1],l=0;l<t.length;l++){n=o,o=t[l];var c=e.pointsCompare(n,o);0!==c&&s((a=c<0?n:o,i=c<0?o:n,{id:r?r.segmentId():-1,start:a,end:i,myFill:{above:null,below:null},otherFill:null}),!0)}},calculate:function(t){return c(t,!1)}}:{calculate:function(t,e,r,n){return t.forEach(function(t){s(a(t.start,t.end,t),!0)}),r.forEach(function(t){s(a(t.start,t.end,t),!1)}),c(e,n)}}}},{\"./linked-list\":480}],480:[function(t,e,r){e.exports={create:function(){var t={root:{root:!0,next:null},exists:function(e){return null!==e&&e!==t.root},isEmpty:function(){return null===t.root.next},getHead:function(){return t.root.next},insertBefore:function(e,r){for(var n=t.root,a=t.root.next;null!==a;){if(r(a))return e.prev=a.prev,e.next=a,a.prev.next=e,void(a.prev=e);n=a,a=a.next}n.next=e,e.prev=n,e.next=null},findTransition:function(e){for(var r=t.root,n=t.root.next;null!==n&&!e(n);)r=n,n=n.next;return{before:r===t.root?null:r,after:n,insert:function(t){return t.prev=r,t.next=n,r.next=t,null!==n&&(n.prev=t),t}}}};return t},node:function(t){return t.prev=null,t.next=null,t.remove=function(){t.prev.next=t.next,t.next&&(t.next.prev=t.prev),t.prev=null,t.next=null},t}}},{}],481:[function(t,e,r){e.exports=function(t,e,r){var n=[],a=[];return t.forEach(function(t){var i=t.start,o=t.end;if(e.pointsSame(i,o))console.warn(\"PolyBool: Warning: Zero-length segment detected; your epsilon is probably too small or too large\");else{r&&r.chainStart(t);for(var s={index:0,matches_head:!1,matches_pt1:!1},l={index:0,matches_head:!1,matches_pt1:!1},c=s,u=0;u<n.length;u++){var h=(v=n[u])[0],f=(v[1],v[v.length-1]);if(v[v.length-2],e.pointsSame(h,i)){if(T(u,!0,!0))break}else if(e.pointsSame(h,o)){if(T(u,!0,!1))break}else if(e.pointsSame(f,i)){if(T(u,!1,!0))break}else if(e.pointsSame(f,o)&&T(u,!1,!1))break}if(c===s)return n.push([i,o]),void(r&&r.chainNew(i,o));if(c===l){r&&r.chainMatch(s.index);var p=s.index,d=s.matches_pt1?o:i,g=s.matches_head,v=n[p],m=g?v[0]:v[v.length-1],y=g?v[1]:v[v.length-2],x=g?v[v.length-1]:v[0],b=g?v[v.length-2]:v[1];return e.pointsCollinear(y,m,d)&&(g?(r&&r.chainRemoveHead(s.index,d),v.shift()):(r&&r.chainRemoveTail(s.index,d),v.pop()),m=y),e.pointsSame(x,d)?(n.splice(p,1),e.pointsCollinear(b,x,m)&&(g?(r&&r.chainRemoveTail(s.index,m),v.pop()):(r&&r.chainRemoveHead(s.index,m),v.shift())),r&&r.chainClose(s.index),void a.push(v)):void(g?(r&&r.chainAddHead(s.index,d),v.unshift(d)):(r&&r.chainAddTail(s.index,d),v.push(d)))}var _=s.index,w=l.index;r&&r.chainConnect(_,w);var k=n[_].length<n[w].length;s.matches_head?l.matches_head?k?(M(_),A(_,w)):(M(w),A(w,_)):A(w,_):l.matches_head?A(_,w):k?(M(_),A(w,_)):(M(w),A(_,w))}function T(t,e,r){return c.index=t,c.matches_head=e,c.matches_pt1=r,c===s?(c=l,!1):(c=null,!0)}function M(t){r&&r.chainReverse(t),n[t].reverse()}function A(t,a){var i=n[t],o=n[a],s=i[i.length-1],l=i[i.length-2],c=o[0],u=o[1];e.pointsCollinear(l,s,c)&&(r&&r.chainRemoveTail(t,s),i.pop(),s=l),e.pointsCollinear(s,c,u)&&(r&&r.chainRemoveHead(a,c),o.shift()),r&&r.chainJoin(t,a),n[t]=i.concat(o),n.splice(a,1)}}),a}},{}],482:[function(t,e,r){function n(t,e,r){var n=[];return t.forEach(function(t){var a=(t.myFill.above?8:0)+(t.myFill.below?4:0)+(t.otherFill&&t.otherFill.above?2:0)+(t.otherFill&&t.otherFill.below?1:0);0!==e[a]&&n.push({id:r?r.segmentId():-1,start:t.start,end:t.end,myFill:{above:1===e[a],below:2===e[a]},otherFill:null})}),r&&r.selected(n),n}var a={union:function(t,e){return n(t,[0,2,1,0,2,2,0,0,1,0,1,0,0,0,0,0],e)},intersect:function(t,e){return n(t,[0,0,0,0,0,2,0,2,0,0,1,1,0,2,1,0],e)},difference:function(t,e){return n(t,[0,0,0,0,2,0,2,0,1,1,0,0,0,1,2,0],e)},differenceRev:function(t,e){return n(t,[0,2,1,0,0,0,1,1,0,2,0,2,0,0,0,0],e)},xor:function(t,e){return n(t,[0,2,1,0,2,0,0,1,1,0,0,2,0,1,2,0],e)}};e.exports=a},{}],483:[function(t,e,r){\"use strict\";var n=new Float64Array(4),a=new Float64Array(4),i=new Float64Array(4);e.exports=function(t,e,r,o,s){n.length<o.length&&(n=new Float64Array(o.length),a=new Float64Array(o.length),i=new Float64Array(o.length));for(var l=0;l<o.length;++l)n[l]=t[l]-o[l],a[l]=e[l]-t[l],i[l]=r[l]-t[l];var c=0,u=0,h=0,f=0,p=0,d=0;for(l=0;l<o.length;++l){var g=a[l],v=i[l],m=n[l];c+=g*g,u+=g*v,h+=v*v,f+=m*g,p+=m*v,d+=m*m}var y,x,b,_,w,k=Math.abs(c*h-u*u),T=u*p-h*f,M=u*f-c*p;if(T+M<=k)if(T<0)M<0&&f<0?(M=0,-f>=c?(T=1,y=c+2*f+d):y=f*(T=-f/c)+d):(T=0,p>=0?(M=0,y=d):-p>=h?(M=1,y=h+2*p+d):y=p*(M=-p/h)+d);else if(M<0)M=0,f>=0?(T=0,y=d):-f>=c?(T=1,y=c+2*f+d):y=f*(T=-f/c)+d;else{var A=1/k;y=(T*=A)*(c*T+u*(M*=A)+2*f)+M*(u*T+h*M+2*p)+d}else T<0?(b=h+p)>(x=u+f)?(_=b-x)>=(w=c-2*u+h)?(T=1,M=0,y=c+2*f+d):y=(T=_/w)*(c*T+u*(M=1-T)+2*f)+M*(u*T+h*M+2*p)+d:(T=0,b<=0?(M=1,y=h+2*p+d):p>=0?(M=0,y=d):y=p*(M=-p/h)+d):M<0?(b=c+f)>(x=u+p)?(_=b-x)>=(w=c-2*u+h)?(M=1,T=0,y=h+2*p+d):y=(T=1-(M=_/w))*(c*T+u*M+2*f)+M*(u*T+h*M+2*p)+d:(M=0,b<=0?(T=1,y=c+2*f+d):f>=0?(T=0,y=d):y=f*(T=-f/c)+d):(_=h+p-u-f)<=0?(T=0,M=1,y=h+2*p+d):_>=(w=c-2*u+h)?(T=1,M=0,y=c+2*f+d):y=(T=_/w)*(c*T+u*(M=1-T)+2*f)+M*(u*T+h*M+2*p)+d;var S=1-T-M;for(l=0;l<o.length;++l)s[l]=S*t[l]+T*e[l]+M*r[l];return y<0?0:y}},{}],484:[function(t,e,r){var n,a,i=e.exports={};function o(){throw new Error(\"setTimeout has not been defined\")}function s(){throw new Error(\"clearTimeout has not been defined\")}function l(t){if(n===setTimeout)return setTimeout(t,0);if((n===o||!n)&&setTimeout)return n=setTimeout,setTimeout(t,0);try{return n(t,0)}catch(e){try{return n.call(null,t,0)}catch(e){return n.call(this,t,0)}}}!function(){try{n=\"function\"==typeof setTimeout?setTimeout:o}catch(t){n=o}try{a=\"function\"==typeof clearTimeout?clearTimeout:s}catch(t){a=s}}();var c,u=[],h=!1,f=-1;function p(){h&&c&&(h=!1,c.length?u=c.concat(u):f=-1,u.length&&d())}function d(){if(!h){var t=l(p);h=!0;for(var e=u.length;e;){for(c=u,u=[];++f<e;)c&&c[f].run();f=-1,e=u.length}c=null,h=!1,function(t){if(a===clearTimeout)return clearTimeout(t);if((a===s||!a)&&clearTimeout)return a=clearTimeout,clearTimeout(t);try{a(t)}catch(e){try{return a.call(null,t)}catch(e){return a.call(this,t)}}}(t)}}function g(t,e){this.fun=t,this.array=e}function v(){}i.nextTick=function(t){var e=new Array(arguments.length-1);if(arguments.length>1)for(var r=1;r<arguments.length;r++)e[r-1]=arguments[r];u.push(new g(t,e)),1!==u.length||h||l(d)},g.prototype.run=function(){this.fun.apply(null,this.array)},i.title=\"browser\",i.browser=!0,i.env={},i.argv=[],i.version=\"\",i.versions={},i.on=v,i.addListener=v,i.once=v,i.off=v,i.removeListener=v,i.removeAllListeners=v,i.emit=v,i.prependListener=v,i.prependOnceListener=v,i.listeners=function(t){return[]},i.binding=function(t){throw new Error(\"process.binding is not supported\")},i.cwd=function(){return\"/\"},i.chdir=function(t){throw new Error(\"process.chdir is not supported\")},i.umask=function(){return 0}},{}],485:[function(t,e,r){e.exports=t(\"gl-quat/slerp\")},{\"gl-quat/slerp\":296}],486:[function(t,e,r){(function(r){for(var n=t(\"performance-now\"),a=\"undefined\"==typeof window?r:window,i=[\"moz\",\"webkit\"],o=\"AnimationFrame\",s=a[\"request\"+o],l=a[\"cancel\"+o]||a[\"cancelRequest\"+o],c=0;!s&&c<i.length;c++)s=a[i[c]+\"Request\"+o],l=a[i[c]+\"Cancel\"+o]||a[i[c]+\"CancelRequest\"+o];if(!s||!l){var u=0,h=0,f=[];s=function(t){if(0===f.length){var e=n(),r=Math.max(0,1e3/60-(e-u));u=r+e,setTimeout(function(){var t=f.slice(0);f.length=0;for(var e=0;e<t.length;e++)if(!t[e].cancelled)try{t[e].callback(u)}catch(t){setTimeout(function(){throw t},0)}},Math.round(r))}return f.push({handle:++h,callback:t,cancelled:!1}),h},l=function(t){for(var e=0;e<f.length;e++)f[e].handle===t&&(f[e].cancelled=!0)}}e.exports=function(t){return s.call(a,t)},e.exports.cancel=function(){l.apply(a,arguments)},e.exports.polyfill=function(t){t||(t=a),t.requestAnimationFrame=s,t.cancelAnimationFrame=l}}).call(this,\"undefined\"!=typeof global?global:\"undefined\"!=typeof self?self:\"undefined\"!=typeof window?window:{})},{\"performance-now\":464}],487:[function(t,e,r){\"use strict\";var n=t(\"big-rat/add\");e.exports=function(t,e){for(var r=t.length,a=new Array(r),i=0;i<r;++i)a[i]=n(t[i],e[i]);return a}},{\"big-rat/add\":77}],488:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=new Array(t.length),r=0;r<t.length;++r)e[r]=n(t[r]);return e};var n=t(\"big-rat\")},{\"big-rat\":80}],489:[function(t,e,r){\"use strict\";var n=t(\"big-rat\"),a=t(\"big-rat/mul\");e.exports=function(t,e){for(var r=n(e),i=t.length,o=new Array(i),s=0;s<i;++s)o[s]=a(t[s],r);return o}},{\"big-rat\":80,\"big-rat/mul\":89}],490:[function(t,e,r){\"use strict\";var n=t(\"big-rat/sub\");e.exports=function(t,e){for(var r=t.length,a=new Array(r),i=0;i<r;++i)a[i]=n(t[i],e[i]);return a}},{\"big-rat/sub\":91}],491:[function(t,e,r){\"use strict\";var n=t(\"compare-cell\"),a=t(\"compare-oriented-cell\"),i=t(\"cell-orientation\");e.exports=function(t){t.sort(a);for(var e=t.length,r=0,o=0;o<e;++o){var s=t[o],l=i(s);if(0!==l){if(r>0){var c=t[r-1];if(0===n(s,c)&&i(c)!==l){r-=1;continue}}t[r++]=s}}return t.length=r,t}},{\"cell-orientation\":114,\"compare-cell\":130,\"compare-oriented-cell\":131}],492:[function(t,e,r){\"use strict\";var n=t(\"array-bounds\"),a=t(\"color-normalize\"),i=t(\"update-diff\"),o=t(\"pick-by-alias\"),s=t(\"object-assign\"),l=t(\"flatten-vertex-data\"),c=t(\"to-float32\"),u=c.float32,h=c.fract32;e.exports=function(t,e){\"function\"==typeof t?(e||(e={}),e.regl=t):e=t;e.length&&(e.positions=e);if(!(t=e.regl).hasExtension(\"ANGLE_instanced_arrays\"))throw Error(\"regl-error2d: `ANGLE_instanced_arrays` extension should be enabled\");var r,c,p,d,g,v,m=t._gl,y={color:\"black\",capSize:5,lineWidth:1,opacity:1,viewport:null,range:null,offset:0,count:0,bounds:null,positions:[],errors:[]},x=[];return d=t.buffer({usage:\"dynamic\",type:\"uint8\",data:new Uint8Array(0)}),c=t.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array(0)}),p=t.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array(0)}),g=t.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array(0)}),v=t.buffer({usage:\"static\",type:\"float\",data:f}),k(e),r=t({vert:\"\\n\\t\\tprecision highp float;\\n\\n\\t\\tattribute vec2 position, positionFract;\\n\\t\\tattribute vec4 error;\\n\\t\\tattribute vec4 color;\\n\\n\\t\\tattribute vec2 direction, lineOffset, capOffset;\\n\\n\\t\\tuniform vec4 viewport;\\n\\t\\tuniform float lineWidth, capSize;\\n\\t\\tuniform vec2 scale, scaleFract, translate, translateFract;\\n\\n\\t\\tvarying vec4 fragColor;\\n\\n\\t\\tvoid main() {\\n\\t\\t\\tfragColor = color / 255.;\\n\\n\\t\\t\\tvec2 pixelOffset = lineWidth * lineOffset + (capSize + lineWidth) * capOffset;\\n\\n\\t\\t\\tvec2 dxy = -step(.5, direction.xy) * error.xz + step(direction.xy, vec2(-.5)) * error.yw;\\n\\n\\t\\t\\tvec2 position = position + dxy;\\n\\n\\t\\t\\tvec2 pos = (position + translate) * scale\\n\\t\\t\\t\\t+ (positionFract + translateFract) * scale\\n\\t\\t\\t\\t+ (position + translate) * scaleFract\\n\\t\\t\\t\\t+ (positionFract + translateFract) * scaleFract;\\n\\n\\t\\t\\tpos += pixelOffset / viewport.zw;\\n\\n\\t\\t\\tgl_Position = vec4(pos * 2. - 1., 0, 1);\\n\\t\\t}\\n\\t\\t\",frag:\"\\n\\t\\tprecision highp float;\\n\\n\\t\\tvarying vec4 fragColor;\\n\\n\\t\\tuniform float opacity;\\n\\n\\t\\tvoid main() {\\n\\t\\t\\tgl_FragColor = fragColor;\\n\\t\\t\\tgl_FragColor.a *= opacity;\\n\\t\\t}\\n\\t\\t\",uniforms:{range:t.prop(\"range\"),lineWidth:t.prop(\"lineWidth\"),capSize:t.prop(\"capSize\"),opacity:t.prop(\"opacity\"),scale:t.prop(\"scale\"),translate:t.prop(\"translate\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]}},attributes:{color:{buffer:d,offset:function(t,e){return 4*e.offset},divisor:1},position:{buffer:c,offset:function(t,e){return 8*e.offset},divisor:1},positionFract:{buffer:p,offset:function(t,e){return 8*e.offset},divisor:1},error:{buffer:g,offset:function(t,e){return 16*e.offset},divisor:1},direction:{buffer:v,stride:24,offset:0},lineOffset:{buffer:v,stride:24,offset:8},capOffset:{buffer:v,stride:24,offset:16}},primitive:\"triangles\",blend:{enable:!0,color:[0,0,0,0],equation:{rgb:\"add\",alpha:\"add\"},func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},depth:{enable:!1},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\"),stencil:!1,instances:t.prop(\"count\"),count:f.length}),s(b,{update:k,draw:_,destroy:T,regl:t,gl:m,canvas:m.canvas,groups:x}),b;function b(t){t?k(t):null===t&&T(),_()}function _(e){if(\"number\"==typeof e)return w(e);e&&!Array.isArray(e)&&(e=[e]),t._refresh(),x.forEach(function(t,r){t&&(e&&(e[r]?t.draw=!0:t.draw=!1),t.draw?w(r):t.draw=!0)})}function w(t){\"number\"==typeof t&&(t=x[t]),null!=t&&t&&t.count&&t.color&&t.opacity&&t.positions&&t.positions.length>1&&(t.scaleRatio=[t.scale[0]*t.viewport.width,t.scale[1]*t.viewport.height],r(t),t.after&&t.after(t))}function k(t){if(t){null!=t.length?\"number\"==typeof t[0]&&(t=[{positions:t}]):Array.isArray(t)||(t=[t]);var e=0,r=0;if(b.groups=x=t.map(function(t,c){var u=x[c];return t?(\"function\"==typeof t?t={after:t}:\"number\"==typeof t[0]&&(t={positions:t}),t=o(t,{color:\"color colors fill\",capSize:\"capSize cap capsize cap-size\",lineWidth:\"lineWidth line-width width line thickness\",opacity:\"opacity alpha\",range:\"range dataBox\",viewport:\"viewport viewBox\",errors:\"errors error\",positions:\"positions position data points\"}),u||(x[c]=u={id:c,scale:null,translate:null,scaleFract:null,translateFract:null,draw:!0},t=s({},y,t)),i(u,t,[{lineWidth:function(t){return.5*+t},capSize:function(t){return.5*+t},opacity:parseFloat,errors:function(t){return t=l(t),r+=t.length,t},positions:function(t,r){return t=l(t,\"float64\"),r.count=Math.floor(t.length/2),r.bounds=n(t,2),r.offset=e,e+=r.count,t}},{color:function(t,e){var r=e.count;if(t||(t=\"transparent\"),!Array.isArray(t)||\"number\"==typeof t[0]){var n=t;t=Array(r);for(var i=0;i<r;i++)t[i]=n}if(t.length<r)throw Error(\"Not enough colors\");for(var o=new Uint8Array(4*r),s=0;s<r;s++){var l=a(t[s],\"uint8\");o.set(l,4*s)}return o},range:function(t,e,r){var n=e.bounds;return t||(t=n),e.scale=[1/(t[2]-t[0]),1/(t[3]-t[1])],e.translate=[-t[0],-t[1]],e.scaleFract=h(e.scale),e.translateFract=h(e.translate),t},viewport:function(t){var e;return Array.isArray(t)?e={x:t[0],y:t[1],width:t[2]-t[0],height:t[3]-t[1]}:t?(e={x:t.x||t.left||0,y:t.y||t.top||0},t.right?e.width=t.right-e.x:e.width=t.w||t.width||0,t.bottom?e.height=t.bottom-e.y:e.height=t.h||t.height||0):e={x:0,y:0,width:m.drawingBufferWidth,height:m.drawingBufferHeight},e}}]),u):u}),e||r){var f=x.reduce(function(t,e,r){return t+(e?e.count:0)},0),v=new Float64Array(2*f),_=new Uint8Array(4*f),w=new Float32Array(4*f);x.forEach(function(t,e){if(t){var r=t.positions,n=t.count,a=t.offset,i=t.color,o=t.errors;n&&(_.set(i,4*a),w.set(o,4*a),v.set(r,2*a))}}),c(u(v)),p(h(v)),d(_),g(w)}}}function T(){c.destroy(),p.destroy(),d.destroy(),g.destroy(),v.destroy()}};var f=[[1,0,0,1,0,0],[1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,1,0,0],[1,0,0,1,0,0],[1,0,-1,0,0,1],[1,0,-1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,1],[1,0,-1,0,0,1],[-1,0,-1,0,0,1],[-1,0,-1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,1],[-1,0,-1,0,0,1],[0,1,1,0,0,0],[0,1,-1,0,0,0],[0,-1,-1,0,0,0],[0,-1,-1,0,0,0],[0,1,1,0,0,0],[0,-1,1,0,0,0],[0,1,0,-1,1,0],[0,1,0,-1,-1,0],[0,1,0,1,-1,0],[0,1,0,1,1,0],[0,1,0,-1,1,0],[0,1,0,1,-1,0],[0,-1,0,-1,1,0],[0,-1,0,-1,-1,0],[0,-1,0,1,-1,0],[0,-1,0,1,1,0],[0,-1,0,-1,1,0],[0,-1,0,1,-1,0]]},{\"array-bounds\":68,\"color-normalize\":122,\"flatten-vertex-data\":230,\"object-assign\":456,\"pick-by-alias\":467,\"to-float32\":537,\"update-diff\":548}],493:[function(t,e,r){\"use strict\";var n=t(\"color-normalize\"),a=t(\"array-bounds\"),i=t(\"object-assign\"),o=t(\"glslify\"),s=t(\"pick-by-alias\"),l=t(\"flatten-vertex-data\"),c=t(\"earcut\"),u=t(\"array-normalize\"),h=t(\"to-float32\"),f=h.float32,p=h.fract32,d=t(\"es6-weak-map\"),g=t(\"parse-rect\");function v(t,e){if(!(this instanceof v))return new v(t,e);if(\"function\"==typeof t?(e||(e={}),e.regl=t):e=t,e.length&&(e.positions=e),!(t=e.regl).hasExtension(\"ANGLE_instanced_arrays\"))throw Error(\"regl-error2d: `ANGLE_instanced_arrays` extension should be enabled\");this.gl=t._gl,this.regl=t,this.passes=[],this.shaders=v.shaders.has(t)?v.shaders.get(t):v.shaders.set(t,v.createShaders(t)).get(t),this.update(e)}e.exports=v,v.dashMult=2,v.maxPatternLength=256,v.precisionThreshold=3e6,v.maxPoints=1e4,v.maxLines=2048,v.shaders=new d,v.createShaders=function(t){var e,r=t.buffer({usage:\"static\",type:\"float\",data:[0,1,0,0,1,1,1,0]}),n={primitive:\"triangle strip\",instances:t.prop(\"count\"),count:4,offset:0,uniforms:{miterMode:function(t,e){return\"round\"===e.join?2:1},miterLimit:t.prop(\"miterLimit\"),scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),thickness:t.prop(\"thickness\"),dashPattern:t.prop(\"dashTexture\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),dashSize:t.prop(\"dashLength\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]},depth:t.prop(\"depth\")},blend:{enable:!0,color:[0,0,0,0],equation:{rgb:\"add\",alpha:\"add\"},func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},depth:{enable:function(t,e){return!e.overlay}},stencil:{enable:!1},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\")},a=t(i({vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, aCoordFract, bCoordFract;\\nattribute vec4 color;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvec2 project(vec2 position, vec2 positionFract, vec2 scale, vec2 scaleFract, vec2 translate, vec2 translateFract) {\\n\\t// the order is important\\n\\treturn position * scale + translate\\n       + positionFract * scale + translateFract\\n       + position * scaleFract\\n       + positionFract * scaleFract;\\n}\\n\\nvoid main() {\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineOffset = lineTop * 2. - 1.;\\n\\n\\tvec2 diff = (bCoord + bCoordFract - aCoord - aCoordFract);\\n\\ttangent = normalize(diff * scale * viewport.zw);\\n\\tvec2 normal = vec2(-tangent.y, tangent.x);\\n\\n\\tvec2 position = project(aCoord, aCoordFract, scale, scaleFract, translate, translateFract) * lineStart\\n\\t\\t+ project(bCoord, bCoordFract, scale, scaleFract, translate, translateFract) * lineEnd\\n\\n\\t\\t+ thickness * normal * .5 * lineOffset / viewport.zw;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D dashPattern;\\n\\nuniform float dashSize, pixelRatio, thickness, opacity, id;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvoid main() {\\n\\tfloat alpha = 1.;\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashSize) * .5 + .25;\\n\\tfloat dash = texture2D(dashPattern, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},aCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8,divisor:1},bCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:16,divisor:1},color:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1}}},n));try{e=t(i({cull:{enable:!0,face:\"back\"},vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, nextCoord, prevCoord;\\nattribute vec4 aColor, bColor;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, translate;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\nuniform float miterLimit, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 tangent;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nconst float REVERSE_THRESHOLD = -.875;\\nconst float MIN_DIFF = 1e-6;\\n\\n// TODO: possible optimizations: avoid overcalculating all for vertices and calc just one instead\\n// TODO: precalculate dot products, normalize things beforehead etc.\\n// TODO: refactor to rectangular algorithm\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nbool isNaN( float val ){\\n  return ( val < 0.0 || 0.0 < val || val == 0.0 ) ? false : true;\\n}\\n\\nvoid main() {\\n\\tvec2 aCoord = aCoord, bCoord = bCoord, prevCoord = prevCoord, nextCoord = nextCoord;\\n\\n  vec2 adjustedScale;\\n  adjustedScale.x = (abs(scale.x) < MIN_DIFF) ? MIN_DIFF : scale.x;\\n  adjustedScale.y = (abs(scale.y) < MIN_DIFF) ? MIN_DIFF : scale.y;\\n\\n  vec2 scaleRatio = adjustedScale * viewport.zw;\\n\\tvec2 normalWidth = thickness / scaleRatio;\\n\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineBot = 1. - lineTop;\\n\\n\\tfragColor = (lineStart * aColor + lineEnd * bColor) / 255.;\\n\\n\\tif (isNaN(aCoord.x) || isNaN(aCoord.y) || isNaN(bCoord.x) || isNaN(bCoord.y)) return;\\n\\n\\tif (aCoord == prevCoord) prevCoord = aCoord + normalize(bCoord - aCoord);\\n\\tif (bCoord == nextCoord) nextCoord = bCoord - normalize(bCoord - aCoord);\\n\\n\\tvec2 prevDiff = aCoord - prevCoord;\\n\\tvec2 currDiff = bCoord - aCoord;\\n\\tvec2 nextDiff = nextCoord - bCoord;\\n\\n\\tvec2 prevTangent = normalize(prevDiff * scaleRatio);\\n\\tvec2 currTangent = normalize(currDiff * scaleRatio);\\n\\tvec2 nextTangent = normalize(nextDiff * scaleRatio);\\n\\n\\tvec2 prevNormal = vec2(-prevTangent.y, prevTangent.x);\\n\\tvec2 currNormal = vec2(-currTangent.y, currTangent.x);\\n\\tvec2 nextNormal = vec2(-nextTangent.y, nextTangent.x);\\n\\n\\tvec2 startJoinDirection = normalize(prevTangent - currTangent);\\n\\tvec2 endJoinDirection = normalize(currTangent - nextTangent);\\n\\n\\t// collapsed/unidirectional segment cases\\n\\t// FIXME: there should be more elegant solution\\n\\tvec2 prevTanDiff = abs(prevTangent - currTangent);\\n\\tvec2 nextTanDiff = abs(nextTangent - currTangent);\\n\\tif (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) {\\n\\t\\tstartJoinDirection = currNormal;\\n\\t}\\n\\tif (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) {\\n\\t\\tendJoinDirection = currNormal;\\n\\t}\\n\\tif (aCoord == bCoord) {\\n\\t\\tendJoinDirection = startJoinDirection;\\n\\t\\tcurrNormal = prevNormal;\\n\\t\\tcurrTangent = prevTangent;\\n\\t}\\n\\n\\ttangent = currTangent;\\n\\n\\t//calculate join shifts relative to normals\\n\\tfloat startJoinShift = dot(currNormal, startJoinDirection);\\n\\tfloat endJoinShift = dot(currNormal, endJoinDirection);\\n\\n\\tfloat startMiterRatio = abs(1. / startJoinShift);\\n\\tfloat endMiterRatio = abs(1. / endJoinShift);\\n\\n\\tvec2 startJoin = startJoinDirection * startMiterRatio;\\n\\tvec2 endJoin = endJoinDirection * endMiterRatio;\\n\\n\\tvec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin;\\n\\tstartTopJoin = sign(startJoinShift) * startJoin * .5;\\n\\tstartBotJoin = -startTopJoin;\\n\\n\\tendTopJoin = sign(endJoinShift) * endJoin * .5;\\n\\tendBotJoin = -endTopJoin;\\n\\n\\tvec2 aTopCoord = aCoord + normalWidth * startTopJoin;\\n\\tvec2 bTopCoord = bCoord + normalWidth * endTopJoin;\\n\\tvec2 aBotCoord = aCoord + normalWidth * startBotJoin;\\n\\tvec2 bBotCoord = bCoord + normalWidth * endBotJoin;\\n\\n\\t//miter anti-clipping\\n\\tfloat baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x)));\\n\\tfloat abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x)));\\n\\n\\t//prevent close to reverse direction switch\\n\\tbool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\tbool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\n\\tif (prevReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.);\\n\\t\\taBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\taTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\tbTopCoord -= normalWidth * endTopJoin;\\n\\t\\tbTopCoord += normalize(endTopJoin * normalWidth) * baClipping;\\n\\t}\\n\\n\\tif (nextReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.);\\n\\t\\tbBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\taBotCoord -= normalWidth * startBotJoin;\\n\\t\\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\\n\\t}\\n\\n\\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\\n\\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\\n\\n\\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\\n\\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\\n\\n\\t//position is normalized 0..1 coord on the screen\\n\\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd;\\n\\n\\tstartCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\tendCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\n\\tgl_Position = vec4(position  * 2.0 - 1.0, depth, 1);\\n\\n\\tenableStartMiter = step(dot(currTangent, prevTangent), .5);\\n\\tenableEndMiter = step(dot(currTangent, nextTangent), .5);\\n\\n\\t//bevel miter cutoffs\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n\\n\\t//round miter cutoffs\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D dashPattern;\\nuniform float dashSize, pixelRatio, thickness, opacity, id, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nvoid main() {\\n\\tfloat alpha = 1., distToStart, distToEnd;\\n\\tfloat cutoff = thickness * .5;\\n\\n\\t//bevel miter\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToStart + 1., 0.), 1.);\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToEnd + 1., 0.), 1.);\\n\\t\\t}\\n\\t}\\n\\n\\t// round miter\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - startCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - endCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashSize) * .5 + .25;\\n\\tfloat dash = texture2D(dashPattern, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1},bColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:4,divisor:1},prevCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:0,divisor:1},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},nextCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:24,divisor:1}}},n))}catch(t){e=a}return{fill:t({primitive:\"triangle\",elements:function(t,e){return e.triangles},offset:0,vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position, positionFract;\\n\\nuniform vec4 color;\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float pixelRatio, id;\\nuniform vec4 viewport;\\nuniform float opacity;\\n\\nvarying vec4 fragColor;\\n\\nconst float MAX_LINES = 256.;\\n\\nvoid main() {\\n\\tfloat depth = (MAX_LINES - 4. - id) / (MAX_LINES);\\n\\n\\tvec2 position = position * scale + translate\\n       + positionFract * scale + translateFract\\n       + position * scaleFract\\n       + positionFract * scaleFract;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n\\tfragColor.a *= opacity;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n\\tgl_FragColor = fragColor;\\n}\\n\"]),uniforms:{scale:t.prop(\"scale\"),color:t.prop(\"fill\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]}},attributes:{position:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8},positionFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8}},blend:n.blend,depth:{enable:!1},scissor:n.scissor,stencil:n.stencil,viewport:n.viewport}),rect:a,miter:e}},v.defaults={dashes:null,join:\"miter\",miterLimit:1,thickness:10,cap:\"square\",color:\"black\",opacity:1,overlay:!1,viewport:null,range:null,close:!1,fill:null},v.prototype.render=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];e.length&&(t=this).update.apply(t,e),this.draw()},v.prototype.draw=function(){for(var t=this,e=[],r=arguments.length;r--;)e[r]=arguments[r];return(e.length?e:this.passes).forEach(function(e,r){var n;if(e&&Array.isArray(e))return(n=t).draw.apply(n,e);\"number\"==typeof e&&(e=t.passes[e]),e&&e.count>1&&e.opacity&&(t.regl._refresh(),e.fill&&e.triangles&&e.triangles.length>2&&t.shaders.fill(e),e.thickness&&(e.scale[0]*e.viewport.width>v.precisionThreshold||e.scale[1]*e.viewport.height>v.precisionThreshold?t.shaders.rect(e):\"rect\"===e.join||!e.join&&(e.thickness<=2||e.count>=v.maxPoints)?t.shaders.rect(e):t.shaders.miter(e)))}),this},v.prototype.update=function(t){var e=this;if(t){null!=t.length?\"number\"==typeof t[0]&&(t=[{positions:t}]):Array.isArray(t)||(t=[t]);var r=this.regl,o=this.gl;if(t.forEach(function(t,h){var d=e.passes[h];if(void 0!==t)if(null!==t){if(\"number\"==typeof t[0]&&(t={positions:t}),t=s(t,{positions:\"positions points data coords\",thickness:\"thickness lineWidth lineWidths line-width linewidth width stroke-width strokewidth strokeWidth\",join:\"lineJoin linejoin join type mode\",miterLimit:\"miterlimit miterLimit\",dashes:\"dash dashes dasharray dash-array dashArray\",color:\"color colour stroke colors colours stroke-color strokeColor\",fill:\"fill fill-color fillColor\",opacity:\"alpha opacity\",overlay:\"overlay crease overlap intersect\",close:\"closed close closed-path closePath\",range:\"range dataBox\",viewport:\"viewport viewBox\",hole:\"holes hole hollow\"}),d||(e.passes[h]=d={id:h,scale:null,scaleFract:null,translate:null,translateFract:null,count:0,hole:[],depth:0,dashLength:1,dashTexture:r.texture({channels:1,data:new Uint8Array([255]),width:1,height:1,mag:\"linear\",min:\"linear\"}),colorBuffer:r.buffer({usage:\"dynamic\",type:\"uint8\",data:new Uint8Array}),positionBuffer:r.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array}),positionFractBuffer:r.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array})},t=i({},v.defaults,t)),null!=t.thickness&&(d.thickness=parseFloat(t.thickness)),null!=t.opacity&&(d.opacity=parseFloat(t.opacity)),null!=t.miterLimit&&(d.miterLimit=parseFloat(t.miterLimit)),null!=t.overlay&&(d.overlay=!!t.overlay,h<v.maxLines&&(d.depth=2*(v.maxLines-1-h%v.maxLines)/v.maxLines-1)),null!=t.join&&(d.join=t.join),null!=t.hole&&(d.hole=t.hole),null!=t.fill&&(d.fill=t.fill?n(t.fill,\"uint8\"):null),null!=t.viewport&&(d.viewport=g(t.viewport)),d.viewport||(d.viewport=g([o.drawingBufferWidth,o.drawingBufferHeight])),null!=t.close&&(d.close=t.close),null===t.positions&&(t.positions=[]),t.positions){var m,y;if(t.positions.x&&t.positions.y){var x=t.positions.x,b=t.positions.y;y=d.count=Math.max(x.length,b.length),m=new Float64Array(2*y);for(var _=0;_<y;_++)m[2*_]=x[_],m[2*_+1]=b[_]}else m=l(t.positions,\"float64\"),y=d.count=Math.floor(m.length/2);var w=d.bounds=a(m,2);if(d.fill){for(var k=[],T={},M=0,A=0,S=0,E=d.count;A<E;A++){var L=m[2*A],C=m[2*A+1];isNaN(L)||isNaN(C)||null==L||null==C?(L=m[2*M],C=m[2*M+1],T[A]=M):M=A,k[S++]=L,k[S++]=C}for(var P=c(k,d.hole||[]),O=0,z=P.length;O<z;O++)null!=T[P[O]]&&(P[O]=T[P[O]]);d.triangles=P}var I=new Float64Array(m);u(I,2,w);var D=new Float64Array(2*y+6);d.close?m[0]===m[2*y-2]&&m[1]===m[2*y-1]?(D[0]=I[2*y-4],D[1]=I[2*y-3]):(D[0]=I[2*y-2],D[1]=I[2*y-1]):(D[0]=I[0],D[1]=I[1]),D.set(I,2),d.close?m[0]===m[2*y-2]&&m[1]===m[2*y-1]?(D[2*y+2]=I[2],D[2*y+3]=I[3],d.count-=1):(D[2*y+2]=I[0],D[2*y+3]=I[1],D[2*y+4]=I[2],D[2*y+5]=I[3]):(D[2*y+2]=I[2*y-2],D[2*y+3]=I[2*y-1],D[2*y+4]=I[2*y-2],D[2*y+5]=I[2*y-1]),d.positionBuffer(f(D)),d.positionFractBuffer(p(D))}if(t.range?d.range=t.range:d.range||(d.range=d.bounds),(t.range||t.positions)&&d.count){var R=d.bounds,F=R[2]-R[0],B=R[3]-R[1],N=d.range[2]-d.range[0],j=d.range[3]-d.range[1];d.scale=[F/N,B/j],d.translate=[-d.range[0]/N+R[0]/N||0,-d.range[1]/j+R[1]/j||0],d.scaleFract=p(d.scale),d.translateFract=p(d.translate)}if(t.dashes){var V,U=0;if(!t.dashes||t.dashes.length<2)U=1,V=new Uint8Array([255,255,255,255,255,255,255,255]);else{U=0;for(var q=0;q<t.dashes.length;++q)U+=t.dashes[q];V=new Uint8Array(U*v.dashMult);for(var H=0,G=255,Y=0;Y<2;Y++)for(var W=0;W<t.dashes.length;++W){for(var X=0,Z=t.dashes[W]*v.dashMult*.5;X<Z;++X)V[H++]=G;G^=255}}d.dashLength=U,d.dashTexture({channels:1,data:V,width:V.length,height:1,mag:\"linear\",min:\"linear\"},0,0)}if(t.color){var J=d.count,K=t.color;K||(K=\"transparent\");var Q=new Uint8Array(4*J+4);if(Array.isArray(K)&&\"number\"!=typeof K[0]){for(var $=0;$<J;$++){var tt=n(K[$],\"uint8\");Q.set(tt,4*$)}Q.set(n(K[0],\"uint8\"),4*J)}else for(var et=n(K,\"uint8\"),rt=0;rt<J+1;rt++)Q.set(et,4*rt);d.colorBuffer({usage:\"dynamic\",type:\"uint8\",data:Q})}}else e.passes[h]=null}),t.length<this.passes.length){for(var h=t.length;h<this.passes.length;h++){var d=e.passes[h];d&&(d.colorBuffer.destroy(),d.positionBuffer.destroy(),d.dashTexture.destroy())}this.passes.length=t.length}for(var m=[],y=0;y<this.passes.length;y++)null!==e.passes[y]&&m.push(e.passes[y]);return this.passes=m,this}},v.prototype.destroy=function(){return this.passes.forEach(function(t){t.colorBuffer.destroy(),t.positionBuffer.destroy(),t.dashTexture.destroy()}),this.passes.length=0,this}},{\"array-bounds\":68,\"array-normalize\":494,\"color-normalize\":122,earcut:173,\"es6-weak-map\":495,\"flatten-vertex-data\":230,glslify:411,\"object-assign\":456,\"parse-rect\":461,\"pick-by-alias\":467,\"to-float32\":537}],494:[function(t,e,r){\"use strict\";var n=t(\"array-bounds\");e.exports=function(t,e,r){if(!t||null==t.length)throw Error(\"Argument should be an array\");null==e&&(e=1);null==r&&(r=n(t,e));for(var a=0;a<e;a++){var i=r[e+a],o=r[a],s=a,l=t.length;if(i===1/0&&o===-1/0)for(s=a;s<l;s+=e)t[s]=t[s]===i?1:t[s]===o?0:.5;else if(i===1/0)for(s=a;s<l;s+=e)t[s]=t[s]===i?1:0;else if(o===-1/0)for(s=a;s<l;s+=e)t[s]=t[s]===o?0:1;else{var c=i-o;for(s=a;s<l;s+=e)isNaN(t[s])||(t[s]=0===c?.5:(t[s]-o)/c)}}return t}},{\"array-bounds\":68}],495:[function(t,e,r){arguments[4][320][0].apply(r,arguments)},{\"./is-implemented\":496,\"./polyfill\":498,dup:320}],496:[function(t,e,r){arguments[4][321][0].apply(r,arguments)},{dup:321}],497:[function(t,e,r){arguments[4][322][0].apply(r,arguments)},{dup:322}],498:[function(t,e,r){arguments[4][323][0].apply(r,arguments)},{\"./is-native-implemented\":497,d:153,dup:323,\"es5-ext/object/is-value\":197,\"es5-ext/object/set-prototype-of\":203,\"es5-ext/object/valid-object\":207,\"es5-ext/object/valid-value\":208,\"es5-ext/string/random-uniq\":213,\"es6-iterator/for-of\":215,\"es6-iterator/get\":216,\"es6-symbol\":222}],499:[function(t,e,r){\"use strict\";function n(t,e){return function(t){if(Array.isArray(t))return t}(t)||function(t,e){var r=[],n=!0,a=!1,i=void 0;try{for(var o,s=t[Symbol.iterator]();!(n=(o=s.next()).done)&&(r.push(o.value),!e||r.length!==e);n=!0);}catch(t){a=!0,i=t}finally{try{n||null==s.return||s.return()}finally{if(a)throw i}}return r}(t,e)||function(){throw new TypeError(\"Invalid attempt to destructure non-iterable instance\")}()}function a(t){return function(t){if(Array.isArray(t)){for(var e=0,r=new Array(t.length);e<t.length;e++)r[e]=t[e];return r}}(t)||function(t){if(Symbol.iterator in Object(t)||\"[object Arguments]\"===Object.prototype.toString.call(t))return Array.from(t)}(t)||function(){throw new TypeError(\"Invalid attempt to spread non-iterable instance\")}()}var i=t(\"color-normalize\"),o=t(\"array-bounds\"),s=t(\"color-id\"),l=t(\"point-cluster\"),c=t(\"object-assign\"),u=t(\"glslify\"),h=t(\"pick-by-alias\"),f=t(\"update-diff\"),p=t(\"flatten-vertex-data\"),d=t(\"is-iexplorer\"),g=t(\"to-float32\"),v=t(\"parse-rect\"),m=y;function y(t,e){var r=this;if(!(this instanceof y))return new y(t,e);\"function\"==typeof t?(e||(e={}),e.regl=t):(e=t,t=null),e&&e.length&&(e.positions=e);var n,a=(t=e.regl)._gl,i=[];this.tooManyColors=d,n=t.texture({data:new Uint8Array(1020),width:255,height:1,type:\"uint8\",format:\"rgba\",wrapS:\"clamp\",wrapT:\"clamp\",mag:\"nearest\",min:\"nearest\"}),c(this,{regl:t,gl:a,groups:[],markerCache:[null],markerTextures:[null],palette:i,paletteIds:{},paletteTexture:n,maxColors:255,maxSize:100,canvas:a.canvas}),this.update(e);var o={uniforms:{pixelRatio:t.context(\"pixelRatio\"),palette:n,paletteSize:function(t,e){return[r.tooManyColors?0:255,n.height]},scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translate:t.prop(\"translate\"),translateFract:t.prop(\"translateFract\"),opacity:t.prop(\"opacity\"),marker:t.prop(\"markerTexture\")},attributes:{x:function(t,e){return e.xAttr||{buffer:e.positionBuffer,stride:8,offset:0}},y:function(t,e){return e.yAttr||{buffer:e.positionBuffer,stride:8,offset:4}},xFract:function(t,e){return e.xAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:0}},yFract:function(t,e){return e.yAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:4}},size:function(t,e){return e.size.length?{buffer:e.sizeBuffer,stride:2,offset:0}:{constant:[Math.round(255*e.size/r.maxSize)]}},borderSize:function(t,e){return e.borderSize.length?{buffer:e.sizeBuffer,stride:2,offset:1}:{constant:[Math.round(255*e.borderSize/r.maxSize)]}},colorId:function(t,e){return e.color.length?{buffer:e.colorBuffer,stride:r.tooManyColors?8:4,offset:0}:{constant:r.tooManyColors?i.slice(4*e.color,4*e.color+4):[e.color]}},borderColorId:function(t,e){return e.borderColor.length?{buffer:e.colorBuffer,stride:r.tooManyColors?8:4,offset:r.tooManyColors?4:2}:{constant:r.tooManyColors?i.slice(4*e.borderColor,4*e.borderColor+4):[e.borderColor]}},isActive:function(t,e){return!0===e.activation?{constant:[1]}:e.activation?e.activation:{constant:[0]}}},blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\"),stencil:{enable:!1},depth:{enable:!1},elements:t.prop(\"elements\"),count:t.prop(\"count\"),offset:t.prop(\"offset\"),primitive:\"points\"},s=c({},o);s.frag=u([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragWidth, fragBorderColorLevel, fragColorLevel;\\n\\nuniform sampler2D marker;\\nuniform float pixelRatio, opacity;\\n\\nfloat smoothStep(float x, float y) {\\n  return 1.0 / (1.0 + exp(50.0*(x - y)));\\n}\\n\\nvoid main() {\\n  float dist = texture2D(marker, gl_PointCoord).r, delta = fragWidth;\\n\\n  // max-distance alpha\\n  if (dist < 0.003) discard;\\n\\n  // null-border case\\n  if (fragBorderColorLevel == fragColorLevel || fragBorderColor.a == 0.) {\\n    float colorAmt = smoothstep(.5 - delta, .5 + delta, dist);\\n    gl_FragColor = vec4(fragColor.rgb, colorAmt * fragColor.a * opacity);\\n  }\\n  else {\\n    float borderColorAmt = smoothstep(fragBorderColorLevel - delta, fragBorderColorLevel + delta, dist);\\n    float colorAmt = smoothstep(fragColorLevel - delta, fragColorLevel + delta, dist);\\n\\n    vec4 color = fragBorderColor;\\n    color.a *= borderColorAmt;\\n    color = mix(color, fragColor, colorAmt);\\n    color.a *= opacity;\\n\\n    gl_FragColor = color;\\n  }\\n\\n}\\n\"]),s.vert=u([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract, paletteSize;\\nuniform float pixelRatio;\\nuniform sampler2D palette;\\n\\nconst float maxSize = 100.;\\nconst float borderLevel = .5;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragPointSize, fragBorderRadius, fragWidth, fragBorderColorLevel, fragColorLevel;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n  return isDirect ? id / 255. : texture2D(palette,\\n    vec2(\\n      (id.x + .5) / paletteSize.x,\\n      (id.y + .5) / paletteSize.y\\n    )\\n  );\\n}\\n\\nvoid main() {\\n  if (isActive == 0.) return;\\n\\n  vec2 position = vec2(x, y);\\n  vec2 positionFract = vec2(xFract, yFract);\\n\\n  vec4 color = getColor(colorId);\\n  vec4 borderColor = getColor(borderColorId);\\n\\n  float size = size * maxSize / 255.;\\n  float borderSize = borderSize * maxSize / 255.;\\n\\n  gl_PointSize = 2. * size * pixelRatio;\\n  fragPointSize = size * pixelRatio;\\n\\n  vec2 pos = (position + translate) * scale\\n      + (positionFract + translateFract) * scale\\n      + (position + translate) * scaleFract\\n      + (positionFract + translateFract) * scaleFract;\\n\\n  gl_Position = vec4(pos * 2. - 1., 0, 1);\\n\\n  fragColor = color;\\n  fragBorderColor = borderColor;\\n  fragWidth = 1. / gl_PointSize;\\n\\n  fragBorderColorLevel = clamp(borderLevel - borderLevel * borderSize / size, 0., 1.);\\n  fragColorLevel = clamp(borderLevel + (1. - borderLevel) * borderSize / size, 0., 1.);\\n}\"]),this.drawMarker=t(s);var l=c({},o);l.frag=u([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor, fragBorderColor;\\n\\nuniform float opacity;\\nvarying float fragBorderRadius, fragWidth;\\n\\nfloat smoothStep(float edge0, float edge1, float x) {\\n\\tfloat t;\\n\\tt = clamp((x - edge0) / (edge1 - edge0), 0.0, 1.0);\\n\\treturn t * t * (3.0 - 2.0 * t);\\n}\\n\\nvoid main() {\\n\\tfloat radius, alpha = 1.0, delta = fragWidth;\\n\\n\\tradius = length(2.0 * gl_PointCoord.xy - 1.0);\\n\\n\\tif (radius > 1.0 + delta) {\\n\\t\\tdiscard;\\n\\t}\\n\\n\\talpha -= smoothstep(1.0 - delta, 1.0 + delta, radius);\\n\\n\\tfloat borderRadius = fragBorderRadius;\\n\\tfloat ratio = smoothstep(borderRadius - delta, borderRadius + delta, radius);\\n\\tvec4 color = mix(fragColor, fragBorderColor, ratio);\\n\\tcolor.a *= alpha * opacity;\\n\\tgl_FragColor = color;\\n}\\n\"]),l.vert=u([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float pixelRatio;\\nuniform sampler2D palette;\\nuniform vec2 paletteSize;\\n\\nconst float maxSize = 100.;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragBorderRadius, fragWidth;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n  return isDirect ? id / 255. : texture2D(palette,\\n    vec2(\\n      (id.x + .5) / paletteSize.x,\\n      (id.y + .5) / paletteSize.y\\n    )\\n  );\\n}\\n\\nvoid main() {\\n  // ignore inactive points\\n  if (isActive == 0.) return;\\n\\n  vec2 position = vec2(x, y);\\n  vec2 positionFract = vec2(xFract, yFract);\\n\\n  vec4 color = getColor(colorId);\\n  vec4 borderColor = getColor(borderColorId);\\n\\n  float size = size * maxSize / 255.;\\n  float borderSize = borderSize * maxSize / 255.;\\n\\n  gl_PointSize = (size + borderSize) * pixelRatio;\\n\\n  vec2 pos = (position + translate) * scale\\n      + (positionFract + translateFract) * scale\\n      + (position + translate) * scaleFract\\n      + (positionFract + translateFract) * scaleFract;\\n\\n  gl_Position = vec4(pos * 2. - 1., 0, 1);\\n\\n  fragBorderRadius = 1. - 2. * borderSize / (size + borderSize);\\n  fragColor = color;\\n  fragBorderColor = borderColor.a == 0. || borderSize == 0. ? vec4(color.rgb, 0.) : borderColor;\\n  fragWidth = 1. / gl_PointSize;\\n}\\n\"]),d&&(l.frag=l.frag.replace(\"smoothstep\",\"smoothStep\"),s.frag=s.frag.replace(\"smoothstep\",\"smoothStep\")),this.drawCircle=t(l)}y.defaults={color:\"black\",borderColor:\"transparent\",borderSize:0,size:12,opacity:1,marker:void 0,viewport:null,range:null,pixelSize:null,count:0,offset:0,bounds:null,positions:[],snap:1e4},y.prototype.render=function(){return arguments.length&&this.update.apply(this,arguments),this.draw(),this},y.prototype.draw=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];var a=this.groups;if(1===r.length&&Array.isArray(r[0])&&(null===r[0][0]||Array.isArray(r[0][0]))&&(r=r[0]),this.regl._refresh(),r.length)for(var i=0;i<r.length;i++)this.drawItem(i,r[i]);else a.forEach(function(e,r){t.drawItem(r)});return this},y.prototype.drawItem=function(t,e){var r=this.groups,n=r[t];if(\"number\"==typeof e&&(t=e,n=r[e],e=null),n&&n.count&&n.opacity){n.activation[0]&&this.drawCircle(this.getMarkerDrawOptions(0,n,e));for(var i=[],o=1;o<n.activation.length;o++)n.activation[o]&&(!0===n.activation[o]||n.activation[o].data.length)&&i.push.apply(i,a(this.getMarkerDrawOptions(o,n,e)));i.length&&this.drawMarker(i)}},y.prototype.getMarkerDrawOptions=function(t,e,r){var a=e.range,i=e.tree,o=e.viewport,s=e.activation,l=e.selectionBuffer,u=e.count;this.regl;if(!i)return r?[c({},e,{markerTexture:this.markerTextures[t],activation:s[t],count:r.length,elements:r,offset:0})]:[c({},e,{markerTexture:this.markerTextures[t],activation:s[t],offset:0})];var h=[],f=i.range(a,{lod:!0,px:[(a[2]-a[0])/o.width,(a[3]-a[1])/o.height]});if(r){for(var p=s[t].data,d=new Uint8Array(u),g=0;g<r.length;g++){var v=r[g];d[v]=p?p[v]:1}l.subdata(d)}for(var m=f.length;m--;){var y=n(f[m],2),x=y[0],b=y[1];h.push(c({},e,{markerTexture:this.markerTextures[t],activation:r?l:s[t],offset:x,count:b-x}))}return h},y.prototype.update=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];if(r.length){1===r.length&&Array.isArray(r[0])&&(r=r[0]);var a=this.groups,i=this.gl,s=this.regl,u=this.maxSize,d=this.maxColors,m=this.palette;this.groups=a=r.map(function(e,r){var n=a[r];if(void 0===e)return n;null===e?e={positions:null}:\"function\"==typeof e?e={ondraw:e}:\"number\"==typeof e[0]&&(e={positions:e}),null===(e=h(e,{positions:\"positions data points\",snap:\"snap cluster lod tree\",size:\"sizes size radius\",borderSize:\"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline\",color:\"colors color fill fill-color fillColor\",borderColor:\"borderColors borderColor stroke stroke-color strokeColor\",marker:\"markers marker shape\",range:\"range dataBox databox\",viewport:\"viewport viewPort viewBox viewbox\",opacity:\"opacity alpha transparency\",bounds:\"bound bounds boundaries limits\",tooManyColors:\"tooManyColors palette paletteMode optimizePalette enablePalette\"})).positions&&(e.positions=[]),null!=e.tooManyColors&&(t.tooManyColors=e.tooManyColors),n||(a[r]=n={id:r,scale:null,translate:null,scaleFract:null,translateFract:null,activation:[],selectionBuffer:s.buffer({data:new Uint8Array(0),usage:\"stream\",type:\"uint8\"}),sizeBuffer:s.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),colorBuffer:s.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),positionBuffer:s.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"float\"}),positionFractBuffer:s.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"float\"})},e=c({},y.defaults,e)),!e.positions||\"marker\"in e||(e.marker=n.marker,delete n.marker),!e.marker||\"positions\"in e||(e.positions=n.positions,delete n.positions);var x=0,b=0;if(f(n,e,[{snap:!0,size:function(t,e){return null==t&&(t=y.defaults.size),x+=t&&t.length?1:0,t},borderSize:function(t,e){return null==t&&(t=y.defaults.borderSize),x+=t&&t.length?1:0,t},opacity:parseFloat,color:function(e,r){return null==e&&(e=y.defaults.color),e=t.updateColor(e),b++,e},borderColor:function(e,r){return null==e&&(e=y.defaults.borderColor),e=t.updateColor(e),b++,e},bounds:function(t,e,r){return\"range\"in r||(r.range=null),t},positions:function(t,e,r){var n=e.snap,a=e.positionBuffer,i=e.positionFractBuffer,c=e.selectionBuffer;if(t.x||t.y)return t.x.length?e.xAttr={buffer:s.buffer(t.x),offset:0,stride:4,count:t.x.length}:e.xAttr={buffer:t.x.buffer,offset:4*t.x.offset||0,stride:4*(t.x.stride||1),count:t.x.count},t.y.length?e.yAttr={buffer:s.buffer(t.y),offset:0,stride:4,count:t.y.length}:e.yAttr={buffer:t.y.buffer,offset:4*t.y.offset||0,stride:4*(t.y.stride||1),count:t.y.count},e.count=Math.max(e.xAttr.count,e.yAttr.count),t;t=p(t,\"float64\");var u=e.count=Math.floor(t.length/2),h=e.bounds=u?o(t,2):null;if(r.range||e.range||(delete e.range,r.range=h),r.marker||e.marker||(delete e.marker,r.marker=null),n&&(!0===n||u>n)?e.tree=l(t,{bounds:h}):n&&n.length&&(e.tree=n),e.tree){var f={primitive:\"points\",usage:\"static\",data:e.tree,type:\"uint32\"};e.elements?e.elements(f):e.elements=s.elements(f)}return a({data:g.float(t),usage:\"dynamic\"}),i({data:g.fract(t),usage:\"dynamic\"}),c({data:new Uint8Array(u),type:\"uint8\",usage:\"stream\"}),t}},{marker:function(e,r,n){var a=r.activation;if(a.forEach(function(t){return t&&t.destroy&&t.destroy()}),a.length=0,e&&\"number\"!=typeof e[0]){for(var i=[],o=0,l=Math.min(e.length,r.count);o<l;o++){var c=t.addMarker(e[o]);i[c]||(i[c]=new Uint8Array(r.count)),i[c][o]=1}for(var u=0;u<i.length;u++)if(i[u]){var h={data:i[u],type:\"uint8\",usage:\"static\"};a[u]?a[u](h):a[u]=s.buffer(h),a[u].data=i[u]}}else{a[t.addMarker(e)]=!0}return e},range:function(t,e,r){var n=e.bounds;if(n)return t||(t=n),e.scale=[1/(t[2]-t[0]),1/(t[3]-t[1])],e.translate=[-t[0],-t[1]],e.scaleFract=g.fract(e.scale),e.translateFract=g.fract(e.translate),t},viewport:function(t){return v(t||[i.drawingBufferWidth,i.drawingBufferHeight])}}]),x){var _=n,w=_.count,k=_.size,T=_.borderSize,M=_.sizeBuffer,A=new Uint8Array(2*w);if(k.length||T.length)for(var S=0;S<w;S++)A[2*S]=Math.round(255*(null==k[S]?k:k[S])/u),A[2*S+1]=Math.round(255*(null==T[S]?T:T[S])/u);M({data:A,usage:\"dynamic\"})}if(b){var E,L=n,C=L.count,P=L.color,O=L.borderColor,z=L.colorBuffer;if(t.tooManyColors){if(P.length||O.length){E=new Uint8Array(8*C);for(var I=0;I<C;I++){var D=P[I];E[8*I]=m[4*D],E[8*I+1]=m[4*D+1],E[8*I+2]=m[4*D+2],E[8*I+3]=m[4*D+3];var R=O[I];E[8*I+4]=m[4*R],E[8*I+5]=m[4*R+1],E[8*I+6]=m[4*R+2],E[8*I+7]=m[4*R+3]}}}else if(P.length||O.length){E=new Uint8Array(4*C+2);for(var F=0;F<C;F++)null!=P[F]&&(E[4*F]=P[F]%d,E[4*F+1]=Math.floor(P[F]/d)),null!=O[F]&&(E[4*F+2]=O[F]%d,E[4*F+3]=Math.floor(O[F]/d))}z({data:E||new Uint8Array(0),type:\"uint8\",usage:\"dynamic\"})}return n})}},y.prototype.addMarker=function(t){var e,r=this.markerTextures,n=this.regl,a=this.markerCache,i=null==t?0:a.indexOf(t);if(i>=0)return i;if(t instanceof Uint8Array||t instanceof Uint8ClampedArray)e=t;else{e=new Uint8Array(t.length);for(var o=0,s=t.length;o<s;o++)e[o]=255*t[o]}var l=Math.floor(Math.sqrt(e.length));return i=r.length,a.push(t),r.push(n.texture({channels:1,data:e,radius:l,mag:\"linear\",min:\"linear\"})),i},y.prototype.updateColor=function(t){var e=this.paletteIds,r=this.palette,n=this.maxColors;Array.isArray(t)||(t=[t]);var a=[];if(\"number\"==typeof t[0]){var o=[];if(Array.isArray(t))for(var l=0;l<t.length;l+=4)o.push(t.slice(l,l+4));else for(var c=0;c<t.length;c+=4)o.push(t.subarray(c,c+4));t=o}for(var u=0;u<t.length;u++){var h=t[u];h=i(h,\"uint8\");var f=s(h,!1);if(null==e[f]){var p=r.length;e[f]=Math.floor(p/4),r[p]=h[0],r[p+1]=h[1],r[p+2]=h[2],r[p+3]=h[3]}a[u]=e[f]}return!this.tooManyColors&&r.length>4*n&&(this.tooManyColors=!0),this.updatePalette(r),1===a.length?a[0]:a},y.prototype.updatePalette=function(t){if(!this.tooManyColors){var e=this.maxColors,r=this.paletteTexture,n=Math.ceil(.25*t.length/e);if(n>1)for(var a=.25*(t=t.slice()).length%e;a<n*e;a++)t.push(0,0,0,0);r.height<n&&r.resize(e,n),r.subimage({width:Math.min(.25*t.length,e),height:n,data:t},0,0)}},y.prototype.destroy=function(){return this.groups.forEach(function(t){t.sizeBuffer.destroy(),t.positionBuffer.destroy(),t.positionFractBuffer.destroy(),t.colorBuffer.destroy(),t.activation.forEach(function(t){return t&&t.destroy&&t.destroy()}),t.selectionBuffer.destroy(),t.elements&&t.elements.destroy()}),this.groups.length=0,this.paletteTexture.destroy(),this.markerTextures.forEach(function(t){return t&&t.destroy&&t.destroy()}),this};var x=t(\"object-assign\");e.exports=function(t,e){var r=new m(t,e),n=r.render.bind(r);return x(n,{render:n,update:r.update.bind(r),draw:r.draw.bind(r),destroy:r.destroy.bind(r),regl:r.regl,gl:r.gl,canvas:r.gl.canvas,groups:r.groups,markers:r.markerCache,palette:r.palette}),n}},{\"array-bounds\":68,\"color-id\":120,\"color-normalize\":122,\"flatten-vertex-data\":230,glslify:411,\"is-iexplorer\":421,\"object-assign\":456,\"parse-rect\":461,\"pick-by-alias\":467,\"point-cluster\":471,\"to-float32\":537,\"update-diff\":548}],500:[function(t,e,r){\"use strict\";var n=t(\"regl-scatter2d\"),a=t(\"pick-by-alias\"),i=t(\"array-bounds\"),o=t(\"raf\"),s=t(\"array-range\"),l=t(\"parse-rect\"),c=t(\"flatten-vertex-data\");function u(t,e){if(!(this instanceof u))return new u(t,e);this.traces=[],this.passes={},this.regl=t,this.scatter=n(t),this.canvas=this.scatter.canvas}function h(t,e,r){return(null!=t.id?t.id:t)<<16|(255&e)<<8|255&r}function f(t,e,r){var n,a,i,o,s=t[e],l=t[r];return s.length>2?(s[0],s[2],n=s[1],a=s[3]):s.length?(n=s[0],a=s[1]):(s.x,n=s.y,s.x+s.width,a=s.y+s.height),l.length>2?(i=l[0],o=l[2],l[1],l[3]):l.length?(i=l[0],o=l[1]):(i=l.x,l.y,o=l.x+l.width,l.y+l.height),[i,n,o,a]}function p(t){if(\"number\"==typeof t)return[t,t,t,t];if(2===t.length)return[t[0],t[1],t[0],t[1]];var e=l(t);return[e.x,e.y,e.x+e.width,e.y+e.height]}e.exports=u,u.prototype.render=function(){for(var t,e=this,r=[],n=arguments.length;n--;)r[n]=arguments[n];return r.length&&(t=this).update.apply(t,r),this.regl.attributes.preserveDrawingBuffer?this.draw():(this.dirty?null==this.planned&&(this.planned=o(function(){e.draw(),e.dirty=!0,e.planned=null})):(this.draw(),this.dirty=!0,o(function(){e.dirty=!1})),this)},u.prototype.update=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=0;n<e.length;n++)this.updateItem(n,e[n]);this.traces=this.traces.filter(Boolean);for(var a=[],i=0,o=0;o<this.traces.length;o++){for(var s=this.traces[o],l=this.traces[o].passes,c=0;c<l.length;c++)a.push(this.passes[l[c]]);s.passOffset=i,i+=s.passes.length}return(t=this.scatter).update.apply(t,a),this}},u.prototype.updateItem=function(t,e){var r=this.regl;if(null===e)return this.traces[t]=null,this;if(!e)return this;var n,o=a(e,{data:\"data items columns rows values dimensions samples x\",snap:\"snap cluster\",size:\"sizes size radius\",color:\"colors color fill fill-color fillColor\",opacity:\"opacity alpha transparency opaque\",borderSize:\"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline\",borderColor:\"borderColors borderColor bordercolor stroke stroke-color strokeColor\",marker:\"markers marker shape\",range:\"range ranges databox dataBox\",viewport:\"viewport viewBox viewbox\",domain:\"domain domains area areas\",padding:\"pad padding paddings pads margin margins\",transpose:\"transpose transposed\",diagonal:\"diagonal diag showDiagonal\",upper:\"upper up top upperhalf upperHalf showupperhalf showUpper showUpperHalf\",lower:\"lower low bottom lowerhalf lowerHalf showlowerhalf showLowerHalf showLower\"}),s=this.traces[t]||(this.traces[t]={id:t,buffer:r.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array}),color:\"black\",marker:null,size:12,borderColor:\"transparent\",borderSize:1,viewport:l([r._gl.drawingBufferWidth,r._gl.drawingBufferHeight]),padding:[0,0,0,0],opacity:1,diagonal:!0,upper:!0,lower:!0});if(null!=o.color&&(s.color=o.color),null!=o.size&&(s.size=o.size),null!=o.marker&&(s.marker=o.marker),null!=o.borderColor&&(s.borderColor=o.borderColor),null!=o.borderSize&&(s.borderSize=o.borderSize),null!=o.opacity&&(s.opacity=o.opacity),o.viewport&&(s.viewport=l(o.viewport)),null!=o.diagonal&&(s.diagonal=o.diagonal),null!=o.upper&&(s.upper=o.upper),null!=o.lower&&(s.lower=o.lower),o.data){s.buffer(c(o.data)),s.columns=o.data.length,s.count=o.data[0].length,s.bounds=[];for(var u=0;u<s.columns;u++)s.bounds[u]=i(o.data[u],1)}o.range&&(s.range=o.range,n=s.range&&\"number\"!=typeof s.range[0]),o.domain&&(s.domain=o.domain);var d=!1;null!=o.padding&&(Array.isArray(o.padding)&&o.padding.length===s.columns&&\"number\"==typeof o.padding[o.padding.length-1]?(s.padding=o.padding.map(p),d=!0):s.padding=p(o.padding));var g=s.columns,v=s.count,m=s.viewport.width,y=s.viewport.height,x=s.viewport.x,b=s.viewport.y,_=m/g,w=y/g;s.passes=[];for(var k=0;k<g;k++)for(var T=0;T<g;T++)if((s.diagonal||T!==k)&&(s.upper||!(k>T))&&(s.lower||!(k<T))){var M=h(s.id,k,T),A=this.passes[M]||(this.passes[M]={});if(o.data&&(o.transpose?A.positions={x:{buffer:s.buffer,offset:T,count:v,stride:g},y:{buffer:s.buffer,offset:k,count:v,stride:g}}:A.positions={x:{buffer:s.buffer,offset:T*v,count:v},y:{buffer:s.buffer,offset:k*v,count:v}},A.bounds=f(s.bounds,k,T)),o.domain||o.viewport||o.data){var S=d?f(s.padding,k,T):s.padding;if(s.domain){var E=f(s.domain,k,T),L=E[0],C=E[1],P=E[2],O=E[3];A.viewport=[x+L*m+S[0],b+C*y+S[1],x+P*m-S[2],b+O*y-S[3]]}else A.viewport=[x+T*_+_*S[0],b+k*w+w*S[1],x+(T+1)*_-_*S[2],b+(k+1)*w-w*S[3]]}o.color&&(A.color=s.color),o.size&&(A.size=s.size),o.marker&&(A.marker=s.marker),o.borderSize&&(A.borderSize=s.borderSize),o.borderColor&&(A.borderColor=s.borderColor),o.opacity&&(A.opacity=s.opacity),o.range&&(A.range=n?f(s.range,k,T):s.range||A.bounds),s.passes.push(M)}return this},u.prototype.draw=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=[],a=0;a<e.length;a++)if(\"number\"==typeof e[a]){var i=this.traces[e[a]],o=i.passes,l=i.passOffset;n.push.apply(n,s(l,l+o.length))}else if(e[a].length){var c=e[a],u=this.traces[a],h=u.passes,f=u.passOffset;h=h.map(function(t,e){n[f+e]=c})}(t=this.scatter).draw.apply(t,n)}else this.scatter.draw();return this},u.prototype.destroy=function(){return this.traces.forEach(function(t){t.buffer&&t.buffer.destroy&&t.buffer.destroy()}),this.traces=null,this.passes=null,this.scatter.destroy(),this}},{\"array-bounds\":68,\"array-range\":69,\"flatten-vertex-data\":230,\"parse-rect\":461,\"pick-by-alias\":467,raf:486,\"regl-scatter2d\":499}],501:[function(t,e,r){var n,a;n=this,a=function(){function t(t,e){this.id=V++,this.type=t,this.data=e}function e(t){return\"[\"+function t(e){if(0===e.length)return[];var r=e.charAt(0),n=e.charAt(e.length-1);if(1<e.length&&r===n&&('\"'===r||\"'\"===r))return['\"'+e.substr(1,e.length-2).replace(/\\\\/g,\"\\\\\\\\\").replace(/\"/g,'\\\\\"')+'\"'];if(r=/\\[(false|true|null|\\d+|'[^']*'|\"[^\"]*\")\\]/.exec(e))return t(e.substr(0,r.index)).concat(t(r[1])).concat(t(e.substr(r.index+r[0].length)));if(1===(r=e.split(\".\")).length)return['\"'+e.replace(/\\\\/g,\"\\\\\\\\\").replace(/\"/g,'\\\\\"')+'\"'];for(e=[],n=0;n<r.length;++n)e=e.concat(t(r[n]));return e}(t).join(\"][\")+\"]\"}function r(t){return\"string\"==typeof t?t.split():t}function n(t){return\"string\"==typeof t?document.querySelector(t):t}function a(t){var e,a,i,o,s=t||{};t={};var l=[],c=[],u=\"undefined\"==typeof window?1:window.devicePixelRatio,h=!1,f=function(t){},p=function(){};if(\"string\"==typeof s?e=document.querySelector(s):\"object\"==typeof s&&(\"string\"==typeof s.nodeName&&\"function\"==typeof s.appendChild&&\"function\"==typeof s.getBoundingClientRect?e=s:\"function\"==typeof s.drawArrays||\"function\"==typeof s.drawElements?i=(o=s).canvas:(\"gl\"in s?o=s.gl:\"canvas\"in s?i=n(s.canvas):\"container\"in s&&(a=n(s.container)),\"attributes\"in s&&(t=s.attributes),\"extensions\"in s&&(l=r(s.extensions)),\"optionalExtensions\"in s&&(c=r(s.optionalExtensions)),\"onDone\"in s&&(f=s.onDone),\"profile\"in s&&(h=!!s.profile),\"pixelRatio\"in s&&(u=+s.pixelRatio))),e&&(\"canvas\"===e.nodeName.toLowerCase()?i=e:a=e),!o){if(!i){if(!(e=function(t,e,r){function n(){var e=window.innerWidth,n=window.innerHeight;t!==document.body&&(e=(n=t.getBoundingClientRect()).right-n.left,n=n.bottom-n.top),a.width=r*e,a.height=r*n,j(a.style,{width:e+\"px\",height:n+\"px\"})}var a=document.createElement(\"canvas\");return j(a.style,{border:0,margin:0,padding:0,top:0,left:0}),t.appendChild(a),t===document.body&&(a.style.position=\"absolute\",j(t.style,{margin:0,padding:0})),window.addEventListener(\"resize\",n,!1),n(),{canvas:a,onDestroy:function(){window.removeEventListener(\"resize\",n),t.removeChild(a)}}}(a||document.body,0,u)))return null;i=e.canvas,p=e.onDestroy}o=function(t,e){function r(r){try{return t.getContext(r,e)}catch(t){return null}}return r(\"webgl\")||r(\"experimental-webgl\")||r(\"webgl-experimental\")}(i,t)}return o?{gl:o,canvas:i,container:a,extensions:l,optionalExtensions:c,pixelRatio:u,profile:h,onDone:f,onDestroy:p}:(p(),f(\"webgl not supported, try upgrading your browser or graphics drivers http://get.webgl.org\"),null)}function i(t,e){for(var r=Array(t),n=0;n<t;++n)r[n]=e(n);return r}function o(t){var e,r;return e=(65535<t)<<4,e|=r=(255<(t>>>=e))<<3,(e|=r=(15<(t>>>=r))<<2)|(r=(3<(t>>>=r))<<1)|t>>>r>>1}function s(){function t(t){t:{for(var e=16;268435456>=e;e*=16)if(t<=e){t=e;break t}t=0}return 0<(e=r[o(t)>>2]).length?e.pop():new ArrayBuffer(t)}function e(t){r[o(t.byteLength)>>2].push(t)}var r=i(8,function(){return[]});return{alloc:t,free:e,allocType:function(e,r){var n=null;switch(e){case 5120:n=new Int8Array(t(r),0,r);break;case 5121:n=new Uint8Array(t(r),0,r);break;case 5122:n=new Int16Array(t(2*r),0,r);break;case 5123:n=new Uint16Array(t(2*r),0,r);break;case 5124:n=new Int32Array(t(4*r),0,r);break;case 5125:n=new Uint32Array(t(4*r),0,r);break;case 5126:n=new Float32Array(t(4*r),0,r);break;default:return null}return n.length!==r?n.subarray(0,r):n},freeType:function(t){e(t.buffer)}}}function l(t){return!!t&&\"object\"==typeof t&&Array.isArray(t.shape)&&Array.isArray(t.stride)&&\"number\"==typeof t.offset&&t.shape.length===t.stride.length&&(Array.isArray(t.data)||W(t.data))}function c(t,e,r,n,a,i){for(var o=0;o<e;++o)for(var s=t[o],l=0;l<r;++l)for(var c=s[l],u=0;u<n;++u)a[i++]=c[u]}function u(t){return 0|J[Object.prototype.toString.call(t)]}function h(t,e){for(var r=0;r<e.length;++r)t[r]=e[r]}function f(t,e,r,n,a,i,o){for(var s=0,l=0;l<r;++l)for(var c=0;c<n;++c)t[s++]=e[a*l+i*c+o]}function p(t,e,r,n){function a(e){this.id=c++,this.buffer=t.createBuffer(),this.type=e,this.usage=35044,this.byteLength=0,this.dimension=1,this.dtype=5121,this.persistentData=null,r.profile&&(this.stats={size:0})}function i(e,r,n){e.byteLength=r.byteLength,t.bufferData(e.type,r,n)}function o(t,e,r,n,a,o){if(t.usage=r,Array.isArray(e)){if(t.dtype=n||5126,0<e.length)if(Array.isArray(e[0])){a=tt(e);for(var s=n=1;s<a.length;++s)n*=a[s];t.dimension=n,i(t,e=$(e,a,t.dtype),r),o?t.persistentData=e:G.freeType(e)}else\"number\"==typeof e[0]?(t.dimension=a,h(a=G.allocType(t.dtype,e.length),e),i(t,a,r),o?t.persistentData=a:G.freeType(a)):W(e[0])&&(t.dimension=e[0].length,t.dtype=n||u(e[0])||5126,i(t,e=$(e,[e.length,e[0].length],t.dtype),r),o?t.persistentData=e:G.freeType(e))}else if(W(e))t.dtype=n||u(e),t.dimension=a,i(t,e,r),o&&(t.persistentData=new Uint8Array(new Uint8Array(e.buffer)));else if(l(e)){a=e.shape;var c=e.stride,p=(s=e.offset,0),d=0,g=0,v=0;1===a.length?(p=a[0],d=1,g=c[0],v=0):2===a.length&&(p=a[0],d=a[1],g=c[0],v=c[1]),t.dtype=n||u(e.data)||5126,t.dimension=d,f(a=G.allocType(t.dtype,p*d),e.data,p,d,g,v,s),i(t,a,r),o?t.persistentData=a:G.freeType(a)}}function s(r){e.bufferCount--;for(var a=0;a<n.state.length;++a){var i=n.state[a];i.buffer===r&&(t.disableVertexAttribArray(a),i.buffer=null)}t.deleteBuffer(r.buffer),r.buffer=null,delete p[r.id]}var c=0,p={};a.prototype.bind=function(){t.bindBuffer(this.type,this.buffer)},a.prototype.destroy=function(){s(this)};var d=[];return r.profile&&(e.getTotalBufferSize=function(){var t=0;return Object.keys(p).forEach(function(e){t+=p[e].stats.size}),t}),{create:function(n,i,c,d){function g(e){var n=35044,a=null,i=0,s=0,c=1;return Array.isArray(e)||W(e)||l(e)?a=e:\"number\"==typeof e?i=0|e:e&&(\"data\"in e&&(a=e.data),\"usage\"in e&&(n=Q[e.usage]),\"type\"in e&&(s=K[e.type]),\"dimension\"in e&&(c=0|e.dimension),\"length\"in e&&(i=0|e.length)),v.bind(),a?o(v,a,n,s,c,d):(i&&t.bufferData(v.type,i,n),v.dtype=s||5121,v.usage=n,v.dimension=c,v.byteLength=i),r.profile&&(v.stats.size=v.byteLength*et[v.dtype]),g}e.bufferCount++;var v=new a(i);return p[v.id]=v,c||g(n),g._reglType=\"buffer\",g._buffer=v,g.subdata=function(e,r){var n,a=0|(r||0);if(v.bind(),W(e))t.bufferSubData(v.type,a,e);else if(Array.isArray(e)){if(0<e.length)if(\"number\"==typeof e[0]){var i=G.allocType(v.dtype,e.length);h(i,e),t.bufferSubData(v.type,a,i),G.freeType(i)}else(Array.isArray(e[0])||W(e[0]))&&(n=tt(e),i=$(e,n,v.dtype),t.bufferSubData(v.type,a,i),G.freeType(i))}else if(l(e)){n=e.shape;var o=e.stride,s=i=0,c=0,p=0;1===n.length?(i=n[0],s=1,c=o[0],p=0):2===n.length&&(i=n[0],s=n[1],c=o[0],p=o[1]),n=Array.isArray(e.data)?v.dtype:u(e.data),f(n=G.allocType(n,i*s),e.data,i,s,c,p,e.offset),t.bufferSubData(v.type,a,n),G.freeType(n)}return g},r.profile&&(g.stats=v.stats),g.destroy=function(){s(v)},g},createStream:function(t,e){var r=d.pop();return r||(r=new a(t)),r.bind(),o(r,e,35040,0,1,!1),r},destroyStream:function(t){d.push(t)},clear:function(){X(p).forEach(s),d.forEach(s)},getBuffer:function(t){return t&&t._buffer instanceof a?t._buffer:null},restore:function(){X(p).forEach(function(e){e.buffer=t.createBuffer(),t.bindBuffer(e.type,e.buffer),t.bufferData(e.type,e.persistentData||e.byteLength,e.usage)})},_initBuffer:o}}function d(t,e,r,n){function a(t){this.id=c++,s[this.id]=this,this.buffer=t,this.primType=4,this.type=this.vertCount=0}function i(n,a,i,o,s,c,u){if(n.buffer.bind(),a){var h=u;u||W(a)&&(!l(a)||W(a.data))||(h=e.oes_element_index_uint?5125:5123),r._initBuffer(n.buffer,a,i,h,3)}else t.bufferData(34963,c,i),n.buffer.dtype=h||5121,n.buffer.usage=i,n.buffer.dimension=3,n.buffer.byteLength=c;if(h=u,!u){switch(n.buffer.dtype){case 5121:case 5120:h=5121;break;case 5123:case 5122:h=5123;break;case 5125:case 5124:h=5125}n.buffer.dtype=h}n.type=h,0>(a=s)&&(a=n.buffer.byteLength,5123===h?a>>=1:5125===h&&(a>>=2)),n.vertCount=a,a=o,0>o&&(a=4,1===(o=n.buffer.dimension)&&(a=0),2===o&&(a=1),3===o&&(a=4)),n.primType=a}function o(t){n.elementsCount--,delete s[t.id],t.buffer.destroy(),t.buffer=null}var s={},c=0,u={uint8:5121,uint16:5123};e.oes_element_index_uint&&(u.uint32=5125),a.prototype.bind=function(){this.buffer.bind()};var h=[];return{create:function(t,e){function s(t){if(t)if(\"number\"==typeof t)c(t),h.primType=4,h.vertCount=0|t,h.type=5121;else{var e=null,r=35044,n=-1,a=-1,o=0,f=0;Array.isArray(t)||W(t)||l(t)?e=t:(\"data\"in t&&(e=t.data),\"usage\"in t&&(r=Q[t.usage]),\"primitive\"in t&&(n=rt[t.primitive]),\"count\"in t&&(a=0|t.count),\"type\"in t&&(f=u[t.type]),\"length\"in t?o=0|t.length:(o=a,5123===f||5122===f?o*=2:5125!==f&&5124!==f||(o*=4))),i(h,e,r,n,a,o,f)}else c(),h.primType=4,h.vertCount=0,h.type=5121;return s}var c=r.create(null,34963,!0),h=new a(c._buffer);return n.elementsCount++,s(t),s._reglType=\"elements\",s._elements=h,s.subdata=function(t,e){return c.subdata(t,e),s},s.destroy=function(){o(h)},s},createStream:function(t){var e=h.pop();return e||(e=new a(r.create(null,34963,!0,!1)._buffer)),i(e,t,35040,-1,-1,0,0),e},destroyStream:function(t){h.push(t)},getElements:function(t){return\"function\"==typeof t&&t._elements instanceof a?t._elements:null},clear:function(){X(s).forEach(o)}}}function g(t){for(var e=G.allocType(5123,t.length),r=0;r<t.length;++r)if(isNaN(t[r]))e[r]=65535;else if(1/0===t[r])e[r]=31744;else if(-1/0===t[r])e[r]=64512;else{nt[0]=t[r];var n=(i=at[0])>>>31<<15,a=(i<<1>>>24)-127,i=i>>13&1023;e[r]=-24>a?n:-14>a?n+(i+1024>>-14-a):15<a?n+31744:n+(a+15<<10)+i}return e}function v(t){return Array.isArray(t)||W(t)}function m(t){return\"[object \"+t+\"]\"}function y(t){return Array.isArray(t)&&(0===t.length||\"number\"==typeof t[0])}function x(t){return!(!Array.isArray(t)||0===t.length||!v(t[0]))}function b(t){return Object.prototype.toString.call(t)}function _(t){if(!t)return!1;var e=b(t);return 0<=pt.indexOf(e)||(y(t)||x(t)||l(t))}function w(t,e){36193===t.type?(t.data=g(e),G.freeType(e)):t.data=e}function k(t,e,r,n,a,i){if(t=\"undefined\"!=typeof gt[t]?gt[t]:st[t]*dt[e],i&&(t*=6),a){for(n=0;1<=r;)n+=t*r*r,r/=2;return n}return t*r*n}function T(t,e,r,n,a,i,o){function s(){this.format=this.internalformat=6408,this.type=5121,this.flipY=this.premultiplyAlpha=this.compressed=!1,this.unpackAlignment=1,this.colorSpace=37444,this.channels=this.height=this.width=0}function c(t,e){t.internalformat=e.internalformat,t.format=e.format,t.type=e.type,t.compressed=e.compressed,t.premultiplyAlpha=e.premultiplyAlpha,t.flipY=e.flipY,t.unpackAlignment=e.unpackAlignment,t.colorSpace=e.colorSpace,t.width=e.width,t.height=e.height,t.channels=e.channels}function u(t,e){if(\"object\"==typeof e&&e){\"premultiplyAlpha\"in e&&(t.premultiplyAlpha=e.premultiplyAlpha),\"flipY\"in e&&(t.flipY=e.flipY),\"alignment\"in e&&(t.unpackAlignment=e.alignment),\"colorSpace\"in e&&(t.colorSpace=q[e.colorSpace]),\"type\"in e&&(t.type=H[e.type]);var r=t.width,n=t.height,a=t.channels,i=!1;\"shape\"in e?(r=e.shape[0],n=e.shape[1],3===e.shape.length&&(a=e.shape[2],i=!0)):(\"radius\"in e&&(r=n=e.radius),\"width\"in e&&(r=e.width),\"height\"in e&&(n=e.height),\"channels\"in e&&(a=e.channels,i=!0)),t.width=0|r,t.height=0|n,t.channels=0|a,r=!1,\"format\"in e&&(r=e.format,n=t.internalformat=Y[r],t.format=pt[n],r in H&&!(\"type\"in e)&&(t.type=H[r]),r in K&&(t.compressed=!0),r=!0),!i&&r?t.channels=st[t.format]:i&&!r&&t.channels!==ot[t.format]&&(t.format=t.internalformat=ot[t.channels])}}function h(e){t.pixelStorei(37440,e.flipY),t.pixelStorei(37441,e.premultiplyAlpha),t.pixelStorei(37443,e.colorSpace),t.pixelStorei(3317,e.unpackAlignment)}function f(){s.call(this),this.yOffset=this.xOffset=0,this.data=null,this.needsFree=!1,this.element=null,this.needsCopy=!1}function p(t,e){var r=null;if(_(e)?r=e:e&&(u(t,e),\"x\"in e&&(t.xOffset=0|e.x),\"y\"in e&&(t.yOffset=0|e.y),_(e.data)&&(r=e.data)),e.copy){var n=a.viewportWidth,i=a.viewportHeight;t.width=t.width||n-t.xOffset,t.height=t.height||i-t.yOffset,t.needsCopy=!0}else if(r){if(W(r))t.channels=t.channels||4,t.data=r,\"type\"in e||5121!==t.type||(t.type=0|J[Object.prototype.toString.call(r)]);else if(y(r)){switch(t.channels=t.channels||4,i=(n=r).length,t.type){case 5121:case 5123:case 5125:case 5126:(i=G.allocType(t.type,i)).set(n),t.data=i;break;case 36193:t.data=g(n)}t.alignment=1,t.needsFree=!0}else if(l(r)){n=r.data,Array.isArray(n)||5121!==t.type||(t.type=0|J[Object.prototype.toString.call(n)]);i=r.shape;var o,s,c,h,f=r.stride;3===i.length?(c=i[2],h=f[2]):h=c=1,o=i[0],s=i[1],i=f[0],f=f[1],t.alignment=1,t.width=o,t.height=s,t.channels=c,t.format=t.internalformat=ot[c],t.needsFree=!0,o=h,r=r.offset,c=t.width,h=t.height,s=t.channels;for(var p=G.allocType(36193===t.type?5126:t.type,c*h*s),d=0,m=0;m<h;++m)for(var k=0;k<c;++k)for(var T=0;T<s;++T)p[d++]=n[i*k+f*m+o*T+r];w(t,p)}else if(b(r)===lt||b(r)===ct)b(r)===lt?t.element=r:t.element=r.canvas,t.width=t.element.width,t.height=t.element.height,t.channels=4;else if(b(r)===ut)t.element=r,t.width=r.width,t.height=r.height,t.channels=4;else if(b(r)===ht)t.element=r,t.width=r.naturalWidth,t.height=r.naturalHeight,t.channels=4;else if(b(r)===ft)t.element=r,t.width=r.videoWidth,t.height=r.videoHeight,t.channels=4;else if(x(r)){for(n=t.width||r[0].length,i=t.height||r.length,f=t.channels,f=v(r[0][0])?f||r[0][0].length:f||1,o=Z.shape(r),c=1,h=0;h<o.length;++h)c*=o[h];c=G.allocType(36193===t.type?5126:t.type,c),Z.flatten(r,o,\"\",c),w(t,c),t.alignment=1,t.width=n,t.height=i,t.channels=f,t.format=t.internalformat=ot[f],t.needsFree=!0}}else t.width=t.width||1,t.height=t.height||1,t.channels=t.channels||4}function d(e,r,a,i,o){var s=e.element,l=e.data,c=e.internalformat,u=e.format,f=e.type,p=e.width,d=e.height;h(e),s?t.texSubImage2D(r,o,a,i,u,f,s):e.compressed?t.compressedTexSubImage2D(r,o,a,i,c,p,d,l):e.needsCopy?(n(),t.copyTexSubImage2D(r,o,a,i,e.xOffset,e.yOffset,p,d)):t.texSubImage2D(r,o,a,i,p,d,u,f,l)}function m(){return dt.pop()||new f}function T(t){t.needsFree&&G.freeType(t.data),f.call(t),dt.push(t)}function M(){s.call(this),this.genMipmaps=!1,this.mipmapHint=4352,this.mipmask=0,this.images=Array(16)}function A(t,e,r){var n=t.images[0]=m();t.mipmask=1,n.width=t.width=e,n.height=t.height=r,n.channels=t.channels=4}function S(t,e){var r=null;if(_(e))c(r=t.images[0]=m(),t),p(r,e),t.mipmask=1;else if(u(t,e),Array.isArray(e.mipmap))for(var n=e.mipmap,a=0;a<n.length;++a)c(r=t.images[a]=m(),t),r.width>>=a,r.height>>=a,p(r,n[a]),t.mipmask|=1<<a;else c(r=t.images[0]=m(),t),p(r,e),t.mipmask=1;c(t,t.images[0])}function E(e,r){for(var a=e.images,i=0;i<a.length&&a[i];++i){var o=a[i],s=r,l=i,c=o.element,u=o.data,f=o.internalformat,p=o.format,d=o.type,g=o.width,v=o.height,m=o.channels;h(o),c?t.texImage2D(s,l,p,p,d,c):o.compressed?t.compressedTexImage2D(s,l,f,g,v,0,u):o.needsCopy?(n(),t.copyTexImage2D(s,l,p,o.xOffset,o.yOffset,g,v,0)):((o=!u)&&(u=G.zero.allocType(d,g*v*m)),t.texImage2D(s,l,p,g,v,0,p,d,u),o&&u&&G.zero.freeType(u))}}function L(){var t=gt.pop()||new M;s.call(t);for(var e=t.mipmask=0;16>e;++e)t.images[e]=null;return t}function C(t){for(var e=t.images,r=0;r<e.length;++r)e[r]&&T(e[r]),e[r]=null;gt.push(t)}function P(){this.magFilter=this.minFilter=9728,this.wrapT=this.wrapS=33071,this.anisotropic=1,this.genMipmaps=!1,this.mipmapHint=4352}function O(t,e){\"min\"in e&&(t.minFilter=U[e.min],0<=it.indexOf(t.minFilter)&&!(\"faces\"in e)&&(t.genMipmaps=!0)),\"mag\"in e&&(t.magFilter=V[e.mag]);var r=t.wrapS,n=t.wrapT;if(\"wrap\"in e){var a=e.wrap;\"string\"==typeof a?r=n=N[a]:Array.isArray(a)&&(r=N[a[0]],n=N[a[1]])}else\"wrapS\"in e&&(r=N[e.wrapS]),\"wrapT\"in e&&(n=N[e.wrapT]);if(t.wrapS=r,t.wrapT=n,\"anisotropic\"in e&&(t.anisotropic=e.anisotropic),\"mipmap\"in e){switch(r=!1,typeof e.mipmap){case\"string\":t.mipmapHint=B[e.mipmap],r=t.genMipmaps=!0;break;case\"boolean\":r=t.genMipmaps=e.mipmap;break;case\"object\":t.genMipmaps=!1,r=!0}!r||\"min\"in e||(t.minFilter=9984)}}function z(r,n){t.texParameteri(n,10241,r.minFilter),t.texParameteri(n,10240,r.magFilter),t.texParameteri(n,10242,r.wrapS),t.texParameteri(n,10243,r.wrapT),e.ext_texture_filter_anisotropic&&t.texParameteri(n,34046,r.anisotropic),r.genMipmaps&&(t.hint(33170,r.mipmapHint),t.generateMipmap(n))}function I(e){s.call(this),this.mipmask=0,this.internalformat=6408,this.id=vt++,this.refCount=1,this.target=e,this.texture=t.createTexture(),this.unit=-1,this.bindCount=0,this.texInfo=new P,o.profile&&(this.stats={size:0})}function D(e){t.activeTexture(33984),t.bindTexture(e.target,e.texture)}function R(){var e=xt[0];e?t.bindTexture(e.target,e.texture):t.bindTexture(3553,null)}function F(e){var r=e.texture,n=e.unit,a=e.target;0<=n&&(t.activeTexture(33984+n),t.bindTexture(a,null),xt[n]=null),t.deleteTexture(r),e.texture=null,e.params=null,e.pixels=null,e.refCount=0,delete mt[e.id],i.textureCount--}var B={\"don't care\":4352,\"dont care\":4352,nice:4354,fast:4353},N={repeat:10497,clamp:33071,mirror:33648},V={nearest:9728,linear:9729},U=j({mipmap:9987,\"nearest mipmap nearest\":9984,\"linear mipmap nearest\":9985,\"nearest mipmap linear\":9986,\"linear mipmap linear\":9987},V),q={none:0,browser:37444},H={uint8:5121,rgba4:32819,rgb565:33635,\"rgb5 a1\":32820},Y={alpha:6406,luminance:6409,\"luminance alpha\":6410,rgb:6407,rgba:6408,rgba4:32854,\"rgb5 a1\":32855,rgb565:36194},K={};e.ext_srgb&&(Y.srgb=35904,Y.srgba=35906),e.oes_texture_float&&(H.float32=H.float=5126),e.oes_texture_half_float&&(H.float16=H[\"half float\"]=36193),e.webgl_depth_texture&&(j(Y,{depth:6402,\"depth stencil\":34041}),j(H,{uint16:5123,uint32:5125,\"depth stencil\":34042})),e.webgl_compressed_texture_s3tc&&j(K,{\"rgb s3tc dxt1\":33776,\"rgba s3tc dxt1\":33777,\"rgba s3tc dxt3\":33778,\"rgba s3tc dxt5\":33779}),e.webgl_compressed_texture_atc&&j(K,{\"rgb atc\":35986,\"rgba atc explicit alpha\":35987,\"rgba atc interpolated alpha\":34798}),e.webgl_compressed_texture_pvrtc&&j(K,{\"rgb pvrtc 4bppv1\":35840,\"rgb pvrtc 2bppv1\":35841,\"rgba pvrtc 4bppv1\":35842,\"rgba pvrtc 2bppv1\":35843}),e.webgl_compressed_texture_etc1&&(K[\"rgb etc1\"]=36196);var Q=Array.prototype.slice.call(t.getParameter(34467));Object.keys(K).forEach(function(t){var e=K[t];0<=Q.indexOf(e)&&(Y[t]=e)});var $=Object.keys(Y);r.textureFormats=$;var tt=[];Object.keys(Y).forEach(function(t){tt[Y[t]]=t});var et=[];Object.keys(H).forEach(function(t){et[H[t]]=t});var rt=[];Object.keys(V).forEach(function(t){rt[V[t]]=t});var nt=[];Object.keys(U).forEach(function(t){nt[U[t]]=t});var at=[];Object.keys(N).forEach(function(t){at[N[t]]=t});var pt=$.reduce(function(t,e){var r=Y[e];return 6409===r||6406===r||6409===r||6410===r||6402===r||34041===r?t[r]=r:32855===r||0<=e.indexOf(\"rgba\")?t[r]=6408:t[r]=6407,t},{}),dt=[],gt=[],vt=0,mt={},yt=r.maxTextureUnits,xt=Array(yt).map(function(){return null});return j(I.prototype,{bind:function(){this.bindCount+=1;var e=this.unit;if(0>e){for(var r=0;r<yt;++r){var n=xt[r];if(n){if(0<n.bindCount)continue;n.unit=-1}xt[r]=this,e=r;break}o.profile&&i.maxTextureUnits<e+1&&(i.maxTextureUnits=e+1),this.unit=e,t.activeTexture(33984+e),t.bindTexture(this.target,this.texture)}return e},unbind:function(){--this.bindCount},decRef:function(){0>=--this.refCount&&F(this)}}),o.profile&&(i.getTotalTextureSize=function(){var t=0;return Object.keys(mt).forEach(function(e){t+=mt[e].stats.size}),t}),{create2D:function(e,r){function n(t,e){var r=a.texInfo;P.call(r);var i=L();return\"number\"==typeof t?A(i,0|t,\"number\"==typeof e?0|e:0|t):t?(O(r,t),S(i,t)):A(i,1,1),r.genMipmaps&&(i.mipmask=(i.width<<1)-1),a.mipmask=i.mipmask,c(a,i),a.internalformat=i.internalformat,n.width=i.width,n.height=i.height,D(a),E(i,3553),z(r,3553),R(),C(i),o.profile&&(a.stats.size=k(a.internalformat,a.type,i.width,i.height,r.genMipmaps,!1)),n.format=tt[a.internalformat],n.type=et[a.type],n.mag=rt[r.magFilter],n.min=nt[r.minFilter],n.wrapS=at[r.wrapS],n.wrapT=at[r.wrapT],n}var a=new I(3553);return mt[a.id]=a,i.textureCount++,n(e,r),n.subimage=function(t,e,r,i){e|=0,r|=0,i|=0;var o=m();return c(o,a),o.width=0,o.height=0,p(o,t),o.width=o.width||(a.width>>i)-e,o.height=o.height||(a.height>>i)-r,D(a),d(o,3553,e,r,i),R(),T(o),n},n.resize=function(e,r){var i=0|e,s=0|r||i;if(i===a.width&&s===a.height)return n;n.width=a.width=i,n.height=a.height=s,D(a);for(var l,c=a.channels,u=a.type,h=0;a.mipmask>>h;++h){var f=i>>h,p=s>>h;if(!f||!p)break;l=G.zero.allocType(u,f*p*c),t.texImage2D(3553,h,a.format,f,p,0,a.format,a.type,l),l&&G.zero.freeType(l)}return R(),o.profile&&(a.stats.size=k(a.internalformat,a.type,i,s,!1,!1)),n},n._reglType=\"texture2d\",n._texture=a,o.profile&&(n.stats=a.stats),n.destroy=function(){a.decRef()},n},createCube:function(e,r,n,a,s,l){function h(t,e,r,n,a,i){var s,l=f.texInfo;for(P.call(l),s=0;6>s;++s)g[s]=L();if(\"number\"!=typeof t&&t){if(\"object\"==typeof t)if(e)S(g[0],t),S(g[1],e),S(g[2],r),S(g[3],n),S(g[4],a),S(g[5],i);else if(O(l,t),u(f,t),\"faces\"in t)for(t=t.faces,s=0;6>s;++s)c(g[s],f),S(g[s],t[s]);else for(s=0;6>s;++s)S(g[s],t)}else for(t=0|t||1,s=0;6>s;++s)A(g[s],t,t);for(c(f,g[0]),f.mipmask=l.genMipmaps?(g[0].width<<1)-1:g[0].mipmask,f.internalformat=g[0].internalformat,h.width=g[0].width,h.height=g[0].height,D(f),s=0;6>s;++s)E(g[s],34069+s);for(z(l,34067),R(),o.profile&&(f.stats.size=k(f.internalformat,f.type,h.width,h.height,l.genMipmaps,!0)),h.format=tt[f.internalformat],h.type=et[f.type],h.mag=rt[l.magFilter],h.min=nt[l.minFilter],h.wrapS=at[l.wrapS],h.wrapT=at[l.wrapT],s=0;6>s;++s)C(g[s]);return h}var f=new I(34067);mt[f.id]=f,i.cubeCount++;var g=Array(6);return h(e,r,n,a,s,l),h.subimage=function(t,e,r,n,a){r|=0,n|=0,a|=0;var i=m();return c(i,f),i.width=0,i.height=0,p(i,e),i.width=i.width||(f.width>>a)-r,i.height=i.height||(f.height>>a)-n,D(f),d(i,34069+t,r,n,a),R(),T(i),h},h.resize=function(e){if((e|=0)!==f.width){h.width=f.width=e,h.height=f.height=e,D(f);for(var r=0;6>r;++r)for(var n=0;f.mipmask>>n;++n)t.texImage2D(34069+r,n,f.format,e>>n,e>>n,0,f.format,f.type,null);return R(),o.profile&&(f.stats.size=k(f.internalformat,f.type,h.width,h.height,!1,!0)),h}},h._reglType=\"textureCube\",h._texture=f,o.profile&&(h.stats=f.stats),h.destroy=function(){f.decRef()},h},clear:function(){for(var e=0;e<yt;++e)t.activeTexture(33984+e),t.bindTexture(3553,null),xt[e]=null;X(mt).forEach(F),i.cubeCount=0,i.textureCount=0},getTexture:function(t){return null},restore:function(){for(var e=0;e<yt;++e){var r=xt[e];r&&(r.bindCount=0,r.unit=-1,xt[e]=null)}X(mt).forEach(function(e){e.texture=t.createTexture(),t.bindTexture(e.target,e.texture);for(var r=0;32>r;++r)if(0!=(e.mipmask&1<<r))if(3553===e.target)t.texImage2D(3553,r,e.internalformat,e.width>>r,e.height>>r,0,e.internalformat,e.type,null);else for(var n=0;6>n;++n)t.texImage2D(34069+n,r,e.internalformat,e.width>>r,e.height>>r,0,e.internalformat,e.type,null);z(e.texInfo,e.target)})}}}function M(t,e,r,n,a,i){function o(t,e,r){this.target=t,this.texture=e,this.renderbuffer=r;var n=t=0;e?(t=e.width,n=e.height):r&&(t=r.width,n=r.height),this.width=t,this.height=n}function s(t){t&&(t.texture&&t.texture._texture.decRef(),t.renderbuffer&&t.renderbuffer._renderbuffer.decRef())}function l(t,e,r){t&&(t.texture?t.texture._texture.refCount+=1:t.renderbuffer._renderbuffer.refCount+=1)}function c(e,r){r&&(r.texture?t.framebufferTexture2D(36160,e,r.target,r.texture._texture.texture,0):t.framebufferRenderbuffer(36160,e,36161,r.renderbuffer._renderbuffer.renderbuffer))}function u(t){var e=3553,r=null,n=null,a=t;return\"object\"==typeof t&&(a=t.data,\"target\"in t&&(e=0|t.target)),\"texture2d\"===(t=a._reglType)?r=a:\"textureCube\"===t?r=a:\"renderbuffer\"===t&&(n=a,e=36161),new o(e,r,n)}function h(t,e,r,i,s){return r?((t=n.create2D({width:t,height:e,format:i,type:s}))._texture.refCount=0,new o(3553,t,null)):((t=a.create({width:t,height:e,format:i}))._renderbuffer.refCount=0,new o(36161,null,t))}function f(t){return t&&(t.texture||t.renderbuffer)}function p(t,e,r){t&&(t.texture?t.texture.resize(e,r):t.renderbuffer&&t.renderbuffer.resize(e,r),t.width=e,t.height=r)}function d(){this.id=k++,T[this.id]=this,this.framebuffer=t.createFramebuffer(),this.height=this.width=0,this.colorAttachments=[],this.depthStencilAttachment=this.stencilAttachment=this.depthAttachment=null}function g(t){t.colorAttachments.forEach(s),s(t.depthAttachment),s(t.stencilAttachment),s(t.depthStencilAttachment)}function v(e){t.deleteFramebuffer(e.framebuffer),e.framebuffer=null,i.framebufferCount--,delete T[e.id]}function m(e){var n;t.bindFramebuffer(36160,e.framebuffer);var a=e.colorAttachments;for(n=0;n<a.length;++n)c(36064+n,a[n]);for(n=a.length;n<r.maxColorAttachments;++n)t.framebufferTexture2D(36160,36064+n,3553,null,0);t.framebufferTexture2D(36160,33306,3553,null,0),t.framebufferTexture2D(36160,36096,3553,null,0),t.framebufferTexture2D(36160,36128,3553,null,0),c(36096,e.depthAttachment),c(36128,e.stencilAttachment),c(33306,e.depthStencilAttachment),t.checkFramebufferStatus(36160),t.isContextLost(),t.bindFramebuffer(36160,x.next?x.next.framebuffer:null),x.cur=x.next,t.getError()}function y(t,e){function r(t,e){var a,i=0,o=0,s=!0,c=!0;a=null;var p=!0,d=\"rgba\",v=\"uint8\",y=1,x=null,w=null,k=null,T=!1;\"number\"==typeof t?(i=0|t,o=0|e||i):t?(\"shape\"in t?(i=(o=t.shape)[0],o=o[1]):(\"radius\"in t&&(i=o=t.radius),\"width\"in t&&(i=t.width),\"height\"in t&&(o=t.height)),(\"color\"in t||\"colors\"in t)&&(a=t.color||t.colors,Array.isArray(a)),a||(\"colorCount\"in t&&(y=0|t.colorCount),\"colorTexture\"in t&&(p=!!t.colorTexture,d=\"rgba4\"),\"colorType\"in t&&(v=t.colorType,!p)&&(\"half float\"===v||\"float16\"===v?d=\"rgba16f\":\"float\"!==v&&\"float32\"!==v||(d=\"rgba32f\")),\"colorFormat\"in t&&(d=t.colorFormat,0<=b.indexOf(d)?p=!0:0<=_.indexOf(d)&&(p=!1))),(\"depthTexture\"in t||\"depthStencilTexture\"in t)&&(T=!(!t.depthTexture&&!t.depthStencilTexture)),\"depth\"in t&&(\"boolean\"==typeof t.depth?s=t.depth:(x=t.depth,c=!1)),\"stencil\"in t&&(\"boolean\"==typeof t.stencil?c=t.stencil:(w=t.stencil,s=!1)),\"depthStencil\"in t&&(\"boolean\"==typeof t.depthStencil?s=c=t.depthStencil:(k=t.depthStencil,c=s=!1))):i=o=1;var M=null,A=null,S=null,E=null;if(Array.isArray(a))M=a.map(u);else if(a)M=[u(a)];else for(M=Array(y),a=0;a<y;++a)M[a]=h(i,o,p,d,v);for(i=i||M[0].width,o=o||M[0].height,x?A=u(x):s&&!c&&(A=h(i,o,T,\"depth\",\"uint32\")),w?S=u(w):c&&!s&&(S=h(i,o,!1,\"stencil\",\"uint8\")),k?E=u(k):!x&&!w&&c&&s&&(E=h(i,o,T,\"depth stencil\",\"depth stencil\")),s=null,a=0;a<M.length;++a)l(M[a]),M[a]&&M[a].texture&&(c=yt[M[a].texture._texture.format]*xt[M[a].texture._texture.type],null===s&&(s=c));return l(A),l(S),l(E),g(n),n.width=i,n.height=o,n.colorAttachments=M,n.depthAttachment=A,n.stencilAttachment=S,n.depthStencilAttachment=E,r.color=M.map(f),r.depth=f(A),r.stencil=f(S),r.depthStencil=f(E),r.width=n.width,r.height=n.height,m(n),r}var n=new d;return i.framebufferCount++,r(t,e),j(r,{resize:function(t,e){var a=Math.max(0|t,1),i=Math.max(0|e||a,1);if(a===n.width&&i===n.height)return r;for(var o=n.colorAttachments,s=0;s<o.length;++s)p(o[s],a,i);return p(n.depthAttachment,a,i),p(n.stencilAttachment,a,i),p(n.depthStencilAttachment,a,i),n.width=r.width=a,n.height=r.height=i,m(n),r},_reglType:\"framebuffer\",_framebuffer:n,destroy:function(){v(n),g(n)},use:function(t){x.setFBO({framebuffer:r},t)}})}var x={cur:null,next:null,dirty:!1,setFBO:null},b=[\"rgba\"],_=[\"rgba4\",\"rgb565\",\"rgb5 a1\"];e.ext_srgb&&_.push(\"srgba\"),e.ext_color_buffer_half_float&&_.push(\"rgba16f\",\"rgb16f\"),e.webgl_color_buffer_float&&_.push(\"rgba32f\");var w=[\"uint8\"];e.oes_texture_half_float&&w.push(\"half float\",\"float16\"),e.oes_texture_float&&w.push(\"float\",\"float32\");var k=0,T={};return j(x,{getFramebuffer:function(t){return\"function\"==typeof t&&\"framebuffer\"===t._reglType&&(t=t._framebuffer)instanceof d?t:null},create:y,createCube:function(t){function e(t){var a,i={color:null},o=0,s=null;a=\"rgba\";var l=\"uint8\",c=1;if(\"number\"==typeof t?o=0|t:t?(\"shape\"in t?o=t.shape[0]:(\"radius\"in t&&(o=0|t.radius),\"width\"in t?o=0|t.width:\"height\"in t&&(o=0|t.height)),(\"color\"in t||\"colors\"in t)&&(s=t.color||t.colors,Array.isArray(s)),s||(\"colorCount\"in t&&(c=0|t.colorCount),\"colorType\"in t&&(l=t.colorType),\"colorFormat\"in t&&(a=t.colorFormat)),\"depth\"in t&&(i.depth=t.depth),\"stencil\"in t&&(i.stencil=t.stencil),\"depthStencil\"in t&&(i.depthStencil=t.depthStencil)):o=1,s)if(Array.isArray(s))for(t=[],a=0;a<s.length;++a)t[a]=s[a];else t=[s];else for(t=Array(c),s={radius:o,format:a,type:l},a=0;a<c;++a)t[a]=n.createCube(s);for(i.color=Array(t.length),a=0;a<t.length;++a)c=t[a],o=o||c.width,i.color[a]={target:34069,data:t[a]};for(a=0;6>a;++a){for(c=0;c<t.length;++c)i.color[c].target=34069+a;0<a&&(i.depth=r[0].depth,i.stencil=r[0].stencil,i.depthStencil=r[0].depthStencil),r[a]?r[a](i):r[a]=y(i)}return j(e,{width:o,height:o,color:t})}var r=Array(6);return e(t),j(e,{faces:r,resize:function(t){var n=0|t;if(n===e.width)return e;var a=e.color;for(t=0;t<a.length;++t)a[t].resize(n);for(t=0;6>t;++t)r[t].resize(n);return e.width=e.height=n,e},_reglType:\"framebufferCube\",destroy:function(){r.forEach(function(t){t.destroy()})}})},clear:function(){X(T).forEach(v)},restore:function(){x.cur=null,x.next=null,x.dirty=!0,X(T).forEach(function(e){e.framebuffer=t.createFramebuffer(),m(e)})}})}function A(){this.w=this.z=this.y=this.x=this.state=0,this.buffer=null,this.size=0,this.normalized=!1,this.type=5126,this.divisor=this.stride=this.offset=0}function S(t,e,r,n){function a(t,e,r,n){this.name=t,this.id=e,this.location=r,this.info=n}function i(t,e){for(var r=0;r<t.length;++r)if(t[r].id===e.id)return void(t[r].location=e.location);t.push(e)}function o(r,n,a){if(!(o=(a=35632===r?c:u)[n])){var i=e.str(n),o=t.createShader(r);t.shaderSource(o,i),t.compileShader(o),a[n]=o}return o}function s(t,e){this.id=p++,this.fragId=t,this.vertId=e,this.program=null,this.uniforms=[],this.attributes=[],n.profile&&(this.stats={uniformsCount:0,attributesCount:0})}function l(r,s){var l,c;l=o(35632,r.fragId),c=o(35633,r.vertId);var u=r.program=t.createProgram();t.attachShader(u,l),t.attachShader(u,c),t.linkProgram(u);var h=t.getProgramParameter(u,35718);n.profile&&(r.stats.uniformsCount=h);var f=r.uniforms;for(l=0;l<h;++l)if(c=t.getActiveUniform(u,l))if(1<c.size)for(var p=0;p<c.size;++p){var d=c.name.replace(\"[0]\",\"[\"+p+\"]\");i(f,new a(d,e.id(d),t.getUniformLocation(u,d),c))}else i(f,new a(c.name,e.id(c.name),t.getUniformLocation(u,c.name),c));for(h=t.getProgramParameter(u,35721),n.profile&&(r.stats.attributesCount=h),f=r.attributes,l=0;l<h;++l)(c=t.getActiveAttrib(u,l))&&i(f,new a(c.name,e.id(c.name),t.getAttribLocation(u,c.name),c))}var c={},u={},h={},f=[],p=0;return n.profile&&(r.getMaxUniformsCount=function(){var t=0;return f.forEach(function(e){e.stats.uniformsCount>t&&(t=e.stats.uniformsCount)}),t},r.getMaxAttributesCount=function(){var t=0;return f.forEach(function(e){e.stats.attributesCount>t&&(t=e.stats.attributesCount)}),t}),{clear:function(){var e=t.deleteShader.bind(t);X(c).forEach(e),c={},X(u).forEach(e),u={},f.forEach(function(e){t.deleteProgram(e.program)}),f.length=0,h={},r.shaderCount=0},program:function(t,e,n){var a=h[e];a||(a=h[e]={});var i=a[t];return i||(i=new s(e,t),r.shaderCount++,l(i),a[t]=i,f.push(i)),i},restore:function(){c={},u={};for(var t=0;t<f.length;++t)l(f[t])},shader:o,frag:-1,vert:-1}}function E(t,e,r,n,a,i,o){function s(a){var i;i=null===e.next?5121:e.next.colorAttachments[0].texture._texture.type;var o=0,s=0,l=n.framebufferWidth,c=n.framebufferHeight,u=null;return W(a)?u=a:a&&(o=0|a.x,s=0|a.y,l=0|(a.width||n.framebufferWidth-o),c=0|(a.height||n.framebufferHeight-s),u=a.data||null),r(),a=l*c*4,u||(5121===i?u=new Uint8Array(a):5126===i&&(u=u||new Float32Array(a))),t.pixelStorei(3333,4),t.readPixels(o,s,l,c,6408,i,u),u}return function(t){return t&&\"framebuffer\"in t?function(t){var r;return e.setFBO({framebuffer:t.framebuffer},function(){r=s(t)}),r}(t):s(t)}}function L(t){return Array.prototype.slice.call(t)}function C(t){return L(t).join(\"\")}function P(){function t(){var t=[],e=[];return j(function(){t.push.apply(t,L(arguments))},{def:function(){var n=\"v\"+r++;return e.push(n),0<arguments.length&&(t.push(n,\"=\"),t.push.apply(t,L(arguments)),t.push(\";\")),n},toString:function(){return C([0<e.length?\"var \"+e+\";\":\"\",C(t)])}})}function e(){function e(t,e){n(t,e,\"=\",r.def(t,e),\";\")}var r=t(),n=t(),a=r.toString,i=n.toString;return j(function(){r.apply(r,L(arguments))},{def:r.def,entry:r,exit:n,save:e,set:function(t,n,a){e(t,n),r(t,n,\"=\",a,\";\")},toString:function(){return a()+i()}})}var r=0,n=[],a=[],i=t(),o={};return{global:i,link:function(t){for(var e=0;e<a.length;++e)if(a[e]===t)return n[e];return e=\"g\"+r++,n.push(e),a.push(t),e},block:t,proc:function(t,r){function n(){var t=\"a\"+a.length;return a.push(t),t}var a=[];r=r||0;for(var i=0;i<r;++i)n();var s=(i=e()).toString;return o[t]=j(i,{arg:n,toString:function(){return C([\"function(\",a.join(),\"){\",s(),\"}\"])}})},scope:e,cond:function(){var t=C(arguments),r=e(),n=e(),a=r.toString,i=n.toString;return j(r,{then:function(){return r.apply(r,L(arguments)),this},else:function(){return n.apply(n,L(arguments)),this},toString:function(){var e=i();return e&&(e=\"else{\"+e+\"}\"),C([\"if(\",t,\"){\",a(),\"}\",e])}})},compile:function(){var t=['\"use strict\";',i,\"return {\"];Object.keys(o).forEach(function(e){t.push('\"',e,'\":',o[e].toString(),\",\")}),t.push(\"}\");var e=C(t).replace(/;/g,\";\\n\").replace(/}/g,\"}\\n\").replace(/{/g,\"{\\n\");return Function.apply(null,n.concat(e)).apply(null,a)}}}function O(t){return Array.isArray(t)||W(t)||l(t)}function z(t){return t.sort(function(t,e){return\"viewport\"===t?-1:\"viewport\"===e?1:t<e?-1:1})}function I(t,e,r,n){this.thisDep=t,this.contextDep=e,this.propDep=r,this.append=n}function D(t){return t&&!(t.thisDep||t.contextDep||t.propDep)}function R(t){return new I(!1,!1,!1,t)}function F(t,e){var r=t.type;return 0===r?new I(!0,1<=(r=t.data.length),2<=r,e):4===r?new I((r=t.data).thisDep,r.contextDep,r.propDep,e):new I(3===r,2===r,1===r,e)}function B(t,e,r,n,a,o,s,l,c,u,h,f,p,d,g){function m(t){return t.replace(\".\",\"_\")}function y(t,e,r){var n=m(t);nt.push(t),et[n]=tt[n]=!!r,at[n]=e}function x(t,e,r){var n=m(t);nt.push(t),Array.isArray(r)?(tt[n]=r.slice(),et[n]=r.slice()):tt[n]=et[n]=r,it[n]=e}function b(){var t=P(),r=t.link,n=t.global;t.id=lt++,t.batchId=\"0\";var a=r(ot),i=t.shared={props:\"a0\"};Object.keys(ot).forEach(function(t){i[t]=n.def(a,\".\",t)});var o=t.next={},s=t.current={};Object.keys(it).forEach(function(t){Array.isArray(tt[t])&&(o[t]=n.def(i.next,\".\",t),s[t]=n.def(i.current,\".\",t))});var l=t.constants={};Object.keys(st).forEach(function(t){l[t]=n.def(JSON.stringify(st[t]))}),t.invoke=function(e,n){switch(n.type){case 0:var a=[\"this\",i.context,i.props,t.batchId];return e.def(r(n.data),\".call(\",a.slice(0,Math.max(n.data.length+1,4)),\")\");case 1:return e.def(i.props,n.data);case 2:return e.def(i.context,n.data);case 3:return e.def(\"this\",n.data);case 4:return n.data.append(t,e),n.data.ref}},t.attribCache={};var c={};return t.scopeAttrib=function(t){if((t=e.id(t))in c)return c[t];var n=u.scope[t];return n||(n=u.scope[t]=new Z),c[t]=r(n)},t}function _(t,e){var r=t.static,n=t.dynamic;if(\"framebuffer\"in r){var a=r.framebuffer;return a?(a=l.getFramebuffer(a),R(function(t,e){var r=t.link(a),n=t.shared;return e.set(n.framebuffer,\".next\",r),n=n.context,e.set(n,\".framebufferWidth\",r+\".width\"),e.set(n,\".framebufferHeight\",r+\".height\"),r})):R(function(t,e){var r=t.shared;return e.set(r.framebuffer,\".next\",\"null\"),r=r.context,e.set(r,\".framebufferWidth\",r+\".drawingBufferWidth\"),e.set(r,\".framebufferHeight\",r+\".drawingBufferHeight\"),\"null\"})}if(\"framebuffer\"in n){var i=n.framebuffer;return F(i,function(t,e){var r=t.invoke(e,i),n=t.shared,a=n.framebuffer;r=e.def(a,\".getFramebuffer(\",r,\")\");return e.set(a,\".next\",r),n=n.context,e.set(n,\".framebufferWidth\",r+\"?\"+r+\".width:\"+n+\".drawingBufferWidth\"),e.set(n,\".framebufferHeight\",r+\"?\"+r+\".height:\"+n+\".drawingBufferHeight\"),r})}return null}function w(t){function r(t){if(t in n){var r=e.id(n[t]);return(t=R(function(){return r})).id=r,t}if(t in a){var i=a[t];return F(i,function(t,e){var r=t.invoke(e,i);return e.def(t.shared.strings,\".id(\",r,\")\")})}return null}var n=t.static,a=t.dynamic,i=r(\"frag\"),o=r(\"vert\"),s=null;return D(i)&&D(o)?(s=h.program(o.id,i.id),t=R(function(t,e){return t.link(s)})):t=new I(i&&i.thisDep||o&&o.thisDep,i&&i.contextDep||o&&o.contextDep,i&&i.propDep||o&&o.propDep,function(t,e){var r,n,a=t.shared.shader;return r=i?i.append(t,e):e.def(a,\".\",\"frag\"),n=o?o.append(t,e):e.def(a,\".\",\"vert\"),e.def(a+\".program(\"+n+\",\"+r+\")\")}),{frag:i,vert:o,progVar:t,program:s}}function k(t,e){function r(t,e){if(t in n){var r=0|n[t];return R(function(t,n){return e&&(t.OFFSET=r),r})}if(t in a){var o=a[t];return F(o,function(t,r){var n=t.invoke(r,o);return e&&(t.OFFSET=n),n})}return e&&i?R(function(t,e){return t.OFFSET=\"0\",0}):null}var n=t.static,a=t.dynamic,i=function(){if(\"elements\"in n){var t=n.elements;O(t)?t=o.getElements(o.create(t,!0)):t&&(t=o.getElements(t));var e=R(function(e,r){if(t){var n=e.link(t);return e.ELEMENTS=n}return e.ELEMENTS=null});return e.value=t,e}if(\"elements\"in a){var r=a.elements;return F(r,function(t,e){var n=(a=t.shared).isBufferArgs,a=a.elements,i=t.invoke(e,r),o=e.def(\"null\");n=e.def(n,\"(\",i,\")\"),i=t.cond(n).then(o,\"=\",a,\".createStream(\",i,\");\").else(o,\"=\",a,\".getElements(\",i,\");\");return e.entry(i),e.exit(t.cond(n).then(a,\".destroyStream(\",o,\");\")),t.ELEMENTS=o})}return null}(),s=r(\"offset\",!0);return{elements:i,primitive:function(){if(\"primitive\"in n){var t=n.primitive;return R(function(e,r){return rt[t]})}if(\"primitive\"in a){var e=a.primitive;return F(e,function(t,r){var n=t.constants.primTypes,a=t.invoke(r,e);return r.def(n,\"[\",a,\"]\")})}return i?D(i)?i.value?R(function(t,e){return e.def(t.ELEMENTS,\".primType\")}):R(function(){return 4}):new I(i.thisDep,i.contextDep,i.propDep,function(t,e){var r=t.ELEMENTS;return e.def(r,\"?\",r,\".primType:\",4)}):null}(),count:function(){if(\"count\"in n){var t=0|n.count;return R(function(){return t})}if(\"count\"in a){var e=a.count;return F(e,function(t,r){return t.invoke(r,e)})}return i?D(i)?i?s?new I(s.thisDep,s.contextDep,s.propDep,function(t,e){return e.def(t.ELEMENTS,\".vertCount-\",t.OFFSET)}):R(function(t,e){return e.def(t.ELEMENTS,\".vertCount\")}):R(function(){return-1}):new I(i.thisDep||s.thisDep,i.contextDep||s.contextDep,i.propDep||s.propDep,function(t,e){var r=t.ELEMENTS;return t.OFFSET?e.def(r,\"?\",r,\".vertCount-\",t.OFFSET,\":-1\"):e.def(r,\"?\",r,\".vertCount:-1\")}):null}(),instances:r(\"instances\",!1),offset:s}}function T(t,r){var n=t.static,i=t.dynamic,o={};return Object.keys(n).forEach(function(t){var r=n[t],i=e.id(t),s=new Z;if(O(r))s.state=1,s.buffer=a.getBuffer(a.create(r,34962,!1,!0)),s.type=0;else if(c=a.getBuffer(r))s.state=1,s.buffer=c,s.type=0;else if(\"constant\"in r){var l=r.constant;s.buffer=\"null\",s.state=2,\"number\"==typeof l?s.x=l:bt.forEach(function(t,e){e<l.length&&(s[t]=l[e])})}else{var c=O(r.buffer)?a.getBuffer(a.create(r.buffer,34962,!1,!0)):a.getBuffer(r.buffer),u=0|r.offset,h=0|r.stride,f=0|r.size,p=!!r.normalized,d=0;\"type\"in r&&(d=K[r.type]),r=0|r.divisor,s.buffer=c,s.state=1,s.size=f,s.normalized=p,s.type=d||c.dtype,s.offset=u,s.stride=h,s.divisor=r}o[t]=R(function(t,e){var r=t.attribCache;if(i in r)return r[i];var n={isStream:!1};return Object.keys(s).forEach(function(t){n[t]=s[t]}),s.buffer&&(n.buffer=t.link(s.buffer),n.type=n.type||n.buffer+\".dtype\"),r[i]=n})}),Object.keys(i).forEach(function(t){var e=i[t];o[t]=F(e,function(t,r){function n(t){r(l[t],\"=\",a,\".\",t,\"|0;\")}var a=t.invoke(r,e),i=t.shared,o=i.isBufferArgs,s=i.buffer,l={isStream:r.def(!1)},c=new Z;c.state=1,Object.keys(c).forEach(function(t){l[t]=r.def(\"\"+c[t])});var u=l.buffer,h=l.type;return r(\"if(\",o,\"(\",a,\")){\",l.isStream,\"=true;\",u,\"=\",s,\".createStream(\",34962,\",\",a,\");\",h,\"=\",u,\".dtype;\",\"}else{\",u,\"=\",s,\".getBuffer(\",a,\");\",\"if(\",u,\"){\",h,\"=\",u,\".dtype;\",'}else if(\"constant\" in ',a,\"){\",l.state,\"=\",2,\";\",\"if(typeof \"+a+'.constant === \"number\"){',l[bt[0]],\"=\",a,\".constant;\",bt.slice(1).map(function(t){return l[t]}).join(\"=\"),\"=0;\",\"}else{\",bt.map(function(t,e){return l[t]+\"=\"+a+\".constant.length>\"+e+\"?\"+a+\".constant[\"+e+\"]:0;\"}).join(\"\"),\"}}else{\",\"if(\",o,\"(\",a,\".buffer)){\",u,\"=\",s,\".createStream(\",34962,\",\",a,\".buffer);\",\"}else{\",u,\"=\",s,\".getBuffer(\",a,\".buffer);\",\"}\",h,'=\"type\" in ',a,\"?\",i.glTypes,\"[\",a,\".type]:\",u,\".dtype;\",l.normalized,\"=!!\",a,\".normalized;\"),n(\"size\"),n(\"offset\"),n(\"stride\"),n(\"divisor\"),r(\"}}\"),r.exit(\"if(\",l.isStream,\"){\",s,\".destroyStream(\",u,\");\",\"}\"),l})}),o}function M(t,e,r,n,a){var o=_(t),s=function(t,e,r){function n(t){if(t in a){var r=a[t];t=!0;var n,o,s=0|r.x,l=0|r.y;return\"width\"in r?n=0|r.width:t=!1,\"height\"in r?o=0|r.height:t=!1,new I(!t&&e&&e.thisDep,!t&&e&&e.contextDep,!t&&e&&e.propDep,function(t,e){var a=t.shared.context,i=n;\"width\"in r||(i=e.def(a,\".\",\"framebufferWidth\",\"-\",s));var c=o;return\"height\"in r||(c=e.def(a,\".\",\"framebufferHeight\",\"-\",l)),[s,l,i,c]})}if(t in i){var c=i[t];return t=F(c,function(t,e){var r=t.invoke(e,c),n=t.shared.context,a=e.def(r,\".x|0\"),i=e.def(r,\".y|0\");return[a,i,e.def('\"width\" in ',r,\"?\",r,\".width|0:\",\"(\",n,\".\",\"framebufferWidth\",\"-\",a,\")\"),r=e.def('\"height\" in ',r,\"?\",r,\".height|0:\",\"(\",n,\".\",\"framebufferHeight\",\"-\",i,\")\")]}),e&&(t.thisDep=t.thisDep||e.thisDep,t.contextDep=t.contextDep||e.contextDep,t.propDep=t.propDep||e.propDep),t}return e?new I(e.thisDep,e.contextDep,e.propDep,function(t,e){var r=t.shared.context;return[0,0,e.def(r,\".\",\"framebufferWidth\"),e.def(r,\".\",\"framebufferHeight\")]}):null}var a=t.static,i=t.dynamic;if(t=n(\"viewport\")){var o=t;t=new I(t.thisDep,t.contextDep,t.propDep,function(t,e){var r=o.append(t,e),n=t.shared.context;return e.set(n,\".viewportWidth\",r[2]),e.set(n,\".viewportHeight\",r[3]),r})}return{viewport:t,scissor_box:n(\"scissor.box\")}}(t,o),l=k(t),c=function(t,e){var r=t.static,n=t.dynamic,a={};return nt.forEach(function(t){function e(e,i){if(t in r){var s=e(r[t]);a[o]=R(function(){return s})}else if(t in n){var l=n[t];a[o]=F(l,function(t,e){return i(t,e,t.invoke(e,l))})}}var o=m(t);switch(t){case\"cull.enable\":case\"blend.enable\":case\"dither\":case\"stencil.enable\":case\"depth.enable\":case\"scissor.enable\":case\"polygonOffset.enable\":case\"sample.alpha\":case\"sample.enable\":case\"depth.mask\":return e(function(t){return t},function(t,e,r){return r});case\"depth.func\":return e(function(t){return kt[t]},function(t,e,r){return e.def(t.constants.compareFuncs,\"[\",r,\"]\")});case\"depth.range\":return e(function(t){return t},function(t,e,r){return[e.def(\"+\",r,\"[0]\"),e=e.def(\"+\",r,\"[1]\")]});case\"blend.func\":return e(function(t){return[wt[\"srcRGB\"in t?t.srcRGB:t.src],wt[\"dstRGB\"in t?t.dstRGB:t.dst],wt[\"srcAlpha\"in t?t.srcAlpha:t.src],wt[\"dstAlpha\"in t?t.dstAlpha:t.dst]]},function(t,e,r){function n(t,n){return e.def('\"',t,n,'\" in ',r,\"?\",r,\".\",t,n,\":\",r,\".\",t)}t=t.constants.blendFuncs;var a=n(\"src\",\"RGB\"),i=n(\"dst\",\"RGB\"),o=(a=e.def(t,\"[\",a,\"]\"),e.def(t,\"[\",n(\"src\",\"Alpha\"),\"]\"));return[a,i=e.def(t,\"[\",i,\"]\"),o,t=e.def(t,\"[\",n(\"dst\",\"Alpha\"),\"]\")]});case\"blend.equation\":return e(function(t){return\"string\"==typeof t?[J[t],J[t]]:\"object\"==typeof t?[J[t.rgb],J[t.alpha]]:void 0},function(t,e,r){var n=t.constants.blendEquations,a=e.def(),i=e.def();return(t=t.cond(\"typeof \",r,'===\"string\"')).then(a,\"=\",i,\"=\",n,\"[\",r,\"];\"),t.else(a,\"=\",n,\"[\",r,\".rgb];\",i,\"=\",n,\"[\",r,\".alpha];\"),e(t),[a,i]});case\"blend.color\":return e(function(t){return i(4,function(e){return+t[e]})},function(t,e,r){return i(4,function(t){return e.def(\"+\",r,\"[\",t,\"]\")})});case\"stencil.mask\":return e(function(t){return 0|t},function(t,e,r){return e.def(r,\"|0\")});case\"stencil.func\":return e(function(t){return[kt[t.cmp||\"keep\"],t.ref||0,\"mask\"in t?t.mask:-1]},function(t,e,r){return[t=e.def('\"cmp\" in ',r,\"?\",t.constants.compareFuncs,\"[\",r,\".cmp]\",\":\",7680),e.def(r,\".ref|0\"),e=e.def('\"mask\" in ',r,\"?\",r,\".mask|0:-1\")]});case\"stencil.opFront\":case\"stencil.opBack\":return e(function(e){return[\"stencil.opBack\"===t?1029:1028,Tt[e.fail||\"keep\"],Tt[e.zfail||\"keep\"],Tt[e.zpass||\"keep\"]]},function(e,r,n){function a(t){return r.def('\"',t,'\" in ',n,\"?\",i,\"[\",n,\".\",t,\"]:\",7680)}var i=e.constants.stencilOps;return[\"stencil.opBack\"===t?1029:1028,a(\"fail\"),a(\"zfail\"),a(\"zpass\")]});case\"polygonOffset.offset\":return e(function(t){return[0|t.factor,0|t.units]},function(t,e,r){return[e.def(r,\".factor|0\"),e=e.def(r,\".units|0\")]});case\"cull.face\":return e(function(t){var e=0;return\"front\"===t?e=1028:\"back\"===t&&(e=1029),e},function(t,e,r){return e.def(r,'===\"front\"?',1028,\":\",1029)});case\"lineWidth\":return e(function(t){return t},function(t,e,r){return r});case\"frontFace\":return e(function(t){return Mt[t]},function(t,e,r){return e.def(r+'===\"cw\"?2304:2305')});case\"colorMask\":return e(function(t){return t.map(function(t){return!!t})},function(t,e,r){return i(4,function(t){return\"!!\"+r+\"[\"+t+\"]\"})});case\"sample.coverage\":return e(function(t){return[\"value\"in t?t.value:1,!!t.invert]},function(t,e,r){return[e.def('\"value\" in ',r,\"?+\",r,\".value:1\"),e=e.def(\"!!\",r,\".invert\")]})}}),a}(t),u=w(t),h=s.viewport;return h&&(c.viewport=h),(s=s[h=m(\"scissor.box\")])&&(c[h]=s),(o={framebuffer:o,draw:l,shader:u,state:c,dirty:s=0<Object.keys(c).length}).profile=function(t){var e,r=t.static;if(t=t.dynamic,\"profile\"in r){var n=!!r.profile;(e=R(function(t,e){return n})).enable=n}else if(\"profile\"in t){var a=t.profile;e=F(a,function(t,e){return t.invoke(e,a)})}return e}(t),o.uniforms=function(t,e){var r=t.static,n=t.dynamic,a={};return Object.keys(r).forEach(function(t){var e,n=r[t];if(\"number\"==typeof n||\"boolean\"==typeof n)e=R(function(){return n});else if(\"function\"==typeof n){var o=n._reglType;\"texture2d\"===o||\"textureCube\"===o?e=R(function(t){return t.link(n)}):\"framebuffer\"!==o&&\"framebufferCube\"!==o||(e=R(function(t){return t.link(n.color[0])}))}else v(n)&&(e=R(function(t){return t.global.def(\"[\",i(n.length,function(t){return n[t]}),\"]\")}));e.value=n,a[t]=e}),Object.keys(n).forEach(function(t){var e=n[t];a[t]=F(e,function(t,r){return t.invoke(r,e)})}),a}(r),o.attributes=T(e),o.context=function(t){var e=t.static,r=t.dynamic,n={};return Object.keys(e).forEach(function(t){var r=e[t];n[t]=R(function(t,e){return\"number\"==typeof r||\"boolean\"==typeof r?\"\"+r:t.link(r)})}),Object.keys(r).forEach(function(t){var e=r[t];n[t]=F(e,function(t,r){return t.invoke(r,e)})}),n}(n),o}function A(t,e,r){var n=t.shared.context,a=t.scope();Object.keys(r).forEach(function(i){e.save(n,\".\"+i),a(n,\".\",i,\"=\",r[i].append(t,e),\";\")}),e(a)}function S(t,e,r,n){var a,i=(s=t.shared).gl,o=s.framebuffer;$&&(a=e.def(s.extensions,\".webgl_draw_buffers\"));var s=(l=t.constants).drawBuffer,l=l.backBuffer;t=r?r.append(t,e):e.def(o,\".next\"),n||e(\"if(\",t,\"!==\",o,\".cur){\"),e(\"if(\",t,\"){\",i,\".bindFramebuffer(\",36160,\",\",t,\".framebuffer);\"),$&&e(a,\".drawBuffersWEBGL(\",s,\"[\",t,\".colorAttachments.length]);\"),e(\"}else{\",i,\".bindFramebuffer(\",36160,\",null);\"),$&&e(a,\".drawBuffersWEBGL(\",l,\");\"),e(\"}\",o,\".cur=\",t,\";\"),n||e(\"}\")}function E(t,e,r){var n=t.shared,a=n.gl,o=t.current,s=t.next,l=n.current,c=n.next,u=t.cond(l,\".dirty\");nt.forEach(function(e){var n,h;if(!((e=m(e))in r.state))if(e in s){n=s[e],h=o[e];var f=i(tt[e].length,function(t){return u.def(n,\"[\",t,\"]\")});u(t.cond(f.map(function(t,e){return t+\"!==\"+h+\"[\"+e+\"]\"}).join(\"||\")).then(a,\".\",it[e],\"(\",f,\");\",f.map(function(t,e){return h+\"[\"+e+\"]=\"+t}).join(\";\"),\";\"))}else n=u.def(c,\".\",e),f=t.cond(n,\"!==\",l,\".\",e),u(f),e in at?f(t.cond(n).then(a,\".enable(\",at[e],\");\").else(a,\".disable(\",at[e],\");\"),l,\".\",e,\"=\",n,\";\"):f(a,\".\",it[e],\"(\",n,\");\",l,\".\",e,\"=\",n,\";\")}),0===Object.keys(r.state).length&&u(l,\".dirty=false;\"),e(u)}function L(t,e,r,n){var a=t.shared,i=t.current,o=a.current,s=a.gl;z(Object.keys(r)).forEach(function(a){var l=r[a];if(!n||n(l)){var c=l.append(t,e);if(at[a]){var u=at[a];D(l)?e(s,c?\".enable(\":\".disable(\",u,\");\"):e(t.cond(c).then(s,\".enable(\",u,\");\").else(s,\".disable(\",u,\");\")),e(o,\".\",a,\"=\",c,\";\")}else if(v(c)){var h=i[a];e(s,\".\",it[a],\"(\",c,\");\",c.map(function(t,e){return h+\"[\"+e+\"]=\"+t}).join(\";\"),\";\")}else e(s,\".\",it[a],\"(\",c,\");\",o,\".\",a,\"=\",c,\";\")}})}function C(t,e){Q&&(t.instancing=e.def(t.shared.extensions,\".angle_instanced_arrays\"))}function B(t,e,r,n,a){function i(){return\"undefined\"==typeof performance?\"Date.now()\":\"performance.now()\"}function o(t){t(c=e.def(),\"=\",i(),\";\"),\"string\"==typeof a?t(f,\".count+=\",a,\";\"):t(f,\".count++;\"),d&&(n?t(u=e.def(),\"=\",g,\".getNumPendingQueries();\"):t(g,\".beginQuery(\",f,\");\"))}function s(t){t(f,\".cpuTime+=\",i(),\"-\",c,\";\"),d&&(n?t(g,\".pushScopeStats(\",u,\",\",g,\".getNumPendingQueries(),\",f,\");\"):t(g,\".endQuery();\"))}function l(t){var r=e.def(p,\".profile\");e(p,\".profile=\",t,\";\"),e.exit(p,\".profile=\",r,\";\")}var c,u,h=t.shared,f=t.stats,p=h.current,g=h.timer;if(r=r.profile){if(D(r))return void(r.enable?(o(e),s(e.exit),l(\"true\")):l(\"false\"));l(r=r.append(t,e))}else r=e.def(p,\".profile\");o(h=t.block()),e(\"if(\",r,\"){\",h,\"}\"),s(t=t.block()),e.exit(\"if(\",r,\"){\",t,\"}\")}function N(t,e,r,n,a){function i(r,n,a){function i(){e(\"if(!\",u,\".buffer){\",l,\".enableVertexAttribArray(\",c,\");}\");var r,i=a.type;r=a.size?e.def(a.size,\"||\",n):n,e(\"if(\",u,\".type!==\",i,\"||\",u,\".size!==\",r,\"||\",p.map(function(t){return u+\".\"+t+\"!==\"+a[t]}).join(\"||\"),\"){\",l,\".bindBuffer(\",34962,\",\",h,\".buffer);\",l,\".vertexAttribPointer(\",[c,r,i,a.normalized,a.stride,a.offset],\");\",u,\".type=\",i,\";\",u,\".size=\",r,\";\",p.map(function(t){return u+\".\"+t+\"=\"+a[t]+\";\"}).join(\"\"),\"}\"),Q&&(i=a.divisor,e(\"if(\",u,\".divisor!==\",i,\"){\",t.instancing,\".vertexAttribDivisorANGLE(\",[c,i],\");\",u,\".divisor=\",i,\";}\"))}function s(){e(\"if(\",u,\".buffer){\",l,\".disableVertexAttribArray(\",c,\");\",\"}if(\",bt.map(function(t,e){return u+\".\"+t+\"!==\"+f[e]}).join(\"||\"),\"){\",l,\".vertexAttrib4f(\",c,\",\",f,\");\",bt.map(function(t,e){return u+\".\"+t+\"=\"+f[e]+\";\"}).join(\"\"),\"}\")}var l=o.gl,c=e.def(r,\".location\"),u=e.def(o.attributes,\"[\",c,\"]\");r=a.state;var h=a.buffer,f=[a.x,a.y,a.z,a.w],p=[\"buffer\",\"normalized\",\"offset\",\"stride\"];1===r?i():2===r?s():(e(\"if(\",r,\"===\",1,\"){\"),i(),e(\"}else{\"),s(),e(\"}\"))}var o=t.shared;n.forEach(function(n){var o,s=n.name,l=r.attributes[s];if(l){if(!a(l))return;o=l.append(t,e)}else{if(!a(At))return;var c=t.scopeAttrib(s);o={},Object.keys(new Z).forEach(function(t){o[t]=e.def(c,\".\",t)})}i(t.link(n),function(t){switch(t){case 35664:case 35667:case 35671:return 2;case 35665:case 35668:case 35672:return 3;case 35666:case 35669:case 35673:return 4;default:return 1}}(n.info.type),o)})}function j(t,r,n,a,o){for(var s,l=t.shared,c=l.gl,u=0;u<a.length;++u){var h,f=(g=a[u]).name,p=g.info.type,d=n.uniforms[f],g=t.link(g)+\".location\";if(d){if(!o(d))continue;if(D(d)){if(f=d.value,35678===p||35680===p)r(c,\".uniform1i(\",g,\",\",(p=t.link(f._texture||f.color[0]._texture))+\".bind());\"),r.exit(p,\".unbind();\");else if(35674===p||35675===p||35676===p)d=2,35675===p?d=3:35676===p&&(d=4),r(c,\".uniformMatrix\",d,\"fv(\",g,\",false,\",f=t.global.def(\"new Float32Array([\"+Array.prototype.slice.call(f)+\"])\"),\");\");else{switch(p){case 5126:s=\"1f\";break;case 35664:s=\"2f\";break;case 35665:s=\"3f\";break;case 35666:s=\"4f\";break;case 35670:case 5124:s=\"1i\";break;case 35671:case 35667:s=\"2i\";break;case 35672:case 35668:s=\"3i\";break;case 35673:s=\"4i\";break;case 35669:s=\"4i\"}r(c,\".uniform\",s,\"(\",g,\",\",v(f)?Array.prototype.slice.call(f):f,\");\")}continue}h=d.append(t,r)}else{if(!o(At))continue;h=r.def(l.uniforms,\"[\",e.id(f),\"]\")}switch(35678===p?r(\"if(\",h,\"&&\",h,'._reglType===\"framebuffer\"){',h,\"=\",h,\".color[0];\",\"}\"):35680===p&&r(\"if(\",h,\"&&\",h,'._reglType===\"framebufferCube\"){',h,\"=\",h,\".color[0];\",\"}\"),f=1,p){case 35678:case 35680:p=r.def(h,\"._texture\"),r(c,\".uniform1i(\",g,\",\",p,\".bind());\"),r.exit(p,\".unbind();\");continue;case 5124:case 35670:s=\"1i\";break;case 35667:case 35671:s=\"2i\",f=2;break;case 35668:case 35672:s=\"3i\",f=3;break;case 35669:case 35673:s=\"4i\",f=4;break;case 5126:s=\"1f\";break;case 35664:s=\"2f\",f=2;break;case 35665:s=\"3f\",f=3;break;case 35666:s=\"4f\",f=4;break;case 35674:s=\"Matrix2fv\";break;case 35675:s=\"Matrix3fv\";break;case 35676:s=\"Matrix4fv\"}if(r(c,\".uniform\",s,\"(\",g,\",\"),\"M\"===s.charAt(0)){g=Math.pow(p-35674+2,2);var m=t.global.def(\"new Float32Array(\",g,\")\");r(\"false,(Array.isArray(\",h,\")||\",h,\" instanceof Float32Array)?\",h,\":(\",i(g,function(t){return m+\"[\"+t+\"]=\"+h+\"[\"+t+\"]\"}),\",\",m,\")\")}else r(1<f?i(f,function(t){return h+\"[\"+t+\"]\"}):h);r(\");\")}}function V(t,e,r,n){function a(a){var i=f[a];return i?i.contextDep&&n.contextDynamic||i.propDep?i.append(t,r):i.append(t,e):e.def(h,\".\",a)}function i(){function t(){r(l,\".drawElementsInstancedANGLE(\",[d,v,m,g+\"<<((\"+m+\"-5121)>>1)\",s],\");\")}function e(){r(l,\".drawArraysInstancedANGLE(\",[d,g,v,s],\");\")}p?y?t():(r(\"if(\",p,\"){\"),t(),r(\"}else{\"),e(),r(\"}\")):e()}function o(){function t(){r(u+\".drawElements(\"+[d,v,m,g+\"<<((\"+m+\"-5121)>>1)\"]+\");\")}function e(){r(u+\".drawArrays(\"+[d,g,v]+\");\")}p?y?t():(r(\"if(\",p,\"){\"),t(),r(\"}else{\"),e(),r(\"}\")):e()}var s,l,c=t.shared,u=c.gl,h=c.draw,f=n.draw,p=function(){var a=f.elements,i=e;return a?((a.contextDep&&n.contextDynamic||a.propDep)&&(i=r),a=a.append(t,i)):a=i.def(h,\".\",\"elements\"),a&&i(\"if(\"+a+\")\"+u+\".bindBuffer(34963,\"+a+\".buffer.buffer);\"),a}(),d=a(\"primitive\"),g=a(\"offset\"),v=function(){var a=f.count,i=e;return a?((a.contextDep&&n.contextDynamic||a.propDep)&&(i=r),a=a.append(t,i)):a=i.def(h,\".\",\"count\"),a}();if(\"number\"==typeof v){if(0===v)return}else r(\"if(\",v,\"){\"),r.exit(\"}\");Q&&(s=a(\"instances\"),l=t.instancing);var m=p+\".type\",y=f.elements&&D(f.elements);Q&&(\"number\"!=typeof s||0<=s)?\"string\"==typeof s?(r(\"if(\",s,\">0){\"),i(),r(\"}else if(\",s,\"<0){\"),o(),r(\"}\")):i():o()}function q(t,e,r,n,a){return a=(e=b()).proc(\"body\",a),Q&&(e.instancing=a.def(e.shared.extensions,\".angle_instanced_arrays\")),t(e,a,r,n),e.compile().body}function H(t,e,r,n){C(t,e),N(t,e,r,n.attributes,function(){return!0}),j(t,e,r,n.uniforms,function(){return!0}),V(t,e,e,r)}function G(t,e,r,n){function a(){return!0}t.batchId=\"a1\",C(t,e),N(t,e,r,n.attributes,a),j(t,e,r,n.uniforms,a),V(t,e,e,r)}function Y(t,e,r,n){function a(t){return t.contextDep&&o||t.propDep}function i(t){return!a(t)}C(t,e);var o=r.contextDep,s=e.def(),l=e.def();t.shared.props=l,t.batchId=s;var c=t.scope(),u=t.scope();e(c.entry,\"for(\",s,\"=0;\",s,\"<\",\"a1\",\";++\",s,\"){\",l,\"=\",\"a0\",\"[\",s,\"];\",u,\"}\",c.exit),r.needsContext&&A(t,u,r.context),r.needsFramebuffer&&S(t,u,r.framebuffer),L(t,u,r.state,a),r.profile&&a(r.profile)&&B(t,u,r,!1,!0),n?(N(t,c,r,n.attributes,i),N(t,u,r,n.attributes,a),j(t,c,r,n.uniforms,i),j(t,u,r,n.uniforms,a),V(t,c,u,r)):(e=t.global.def(\"{}\"),n=r.shader.progVar.append(t,u),l=u.def(n,\".id\"),c=u.def(e,\"[\",l,\"]\"),u(t.shared.gl,\".useProgram(\",n,\".program);\",\"if(!\",c,\"){\",c,\"=\",e,\"[\",l,\"]=\",t.link(function(e){return q(G,t,r,e,2)}),\"(\",n,\");}\",c,\".call(this,a0[\",s,\"],\",s,\");\"))}function W(t,r){function n(e){var n=r.shader[e];n&&a.set(i.shader,\".\"+e,n.append(t,a))}var a=t.proc(\"scope\",3);t.batchId=\"a2\";var i=t.shared,o=i.current;A(t,a,r.context),r.framebuffer&&r.framebuffer.append(t,a),z(Object.keys(r.state)).forEach(function(e){var n=r.state[e].append(t,a);v(n)?n.forEach(function(r,n){a.set(t.next[e],\"[\"+n+\"]\",r)}):a.set(i.next,\".\"+e,n)}),B(t,a,r,!0,!0),[\"elements\",\"offset\",\"count\",\"instances\",\"primitive\"].forEach(function(e){var n=r.draw[e];n&&a.set(i.draw,\".\"+e,\"\"+n.append(t,a))}),Object.keys(r.uniforms).forEach(function(n){a.set(i.uniforms,\"[\"+e.id(n)+\"]\",r.uniforms[n].append(t,a))}),Object.keys(r.attributes).forEach(function(e){var n=r.attributes[e].append(t,a),i=t.scopeAttrib(e);Object.keys(new Z).forEach(function(t){a.set(i,\".\"+t,n[t])})}),n(\"vert\"),n(\"frag\"),0<Object.keys(r.state).length&&(a(o,\".dirty=true;\"),a.exit(o,\".dirty=true;\")),a(\"a1(\",t.shared.context,\",a0,\",t.batchId,\");\")}function X(t,e,r){var n=e.static[r];if(n&&function(t){if(\"object\"==typeof t&&!v(t)){for(var e=Object.keys(t),r=0;r<e.length;++r)if(U.isDynamic(t[e[r]]))return!0;return!1}}(n)){var a=t.global,i=Object.keys(n),o=!1,s=!1,l=!1,c=t.global.def(\"{}\");i.forEach(function(e){var r=n[e];if(U.isDynamic(r))\"function\"==typeof r&&(r=n[e]=U.unbox(r)),e=F(r,null),o=o||e.thisDep,l=l||e.propDep,s=s||e.contextDep;else{switch(a(c,\".\",e,\"=\"),typeof r){case\"number\":a(r);break;case\"string\":a('\"',r,'\"');break;case\"object\":Array.isArray(r)&&a(\"[\",r.join(),\"]\");break;default:a(t.link(r))}a(\";\")}}),e.dynamic[r]=new U.DynamicVariable(4,{thisDep:o,contextDep:s,propDep:l,ref:c,append:function(t,e){i.forEach(function(r){var a=n[r];U.isDynamic(a)&&(a=t.invoke(e,a),e(c,\".\",r,\"=\",a,\";\"))})}}),delete e.static[r]}}var Z=u.Record,J={add:32774,subtract:32778,\"reverse subtract\":32779};r.ext_blend_minmax&&(J.min=32775,J.max=32776);var Q=r.angle_instanced_arrays,$=r.webgl_draw_buffers,tt={dirty:!0,profile:g.profile},et={},nt=[],at={},it={};y(\"dither\",3024),y(\"blend.enable\",3042),x(\"blend.color\",\"blendColor\",[0,0,0,0]),x(\"blend.equation\",\"blendEquationSeparate\",[32774,32774]),x(\"blend.func\",\"blendFuncSeparate\",[1,0,1,0]),y(\"depth.enable\",2929,!0),x(\"depth.func\",\"depthFunc\",513),x(\"depth.range\",\"depthRange\",[0,1]),x(\"depth.mask\",\"depthMask\",!0),x(\"colorMask\",\"colorMask\",[!0,!0,!0,!0]),y(\"cull.enable\",2884),x(\"cull.face\",\"cullFace\",1029),x(\"frontFace\",\"frontFace\",2305),x(\"lineWidth\",\"lineWidth\",1),y(\"polygonOffset.enable\",32823),x(\"polygonOffset.offset\",\"polygonOffset\",[0,0]),y(\"sample.alpha\",32926),y(\"sample.enable\",32928),x(\"sample.coverage\",\"sampleCoverage\",[1,!1]),y(\"stencil.enable\",2960),x(\"stencil.mask\",\"stencilMask\",-1),x(\"stencil.func\",\"stencilFunc\",[519,0,-1]),x(\"stencil.opFront\",\"stencilOpSeparate\",[1028,7680,7680,7680]),x(\"stencil.opBack\",\"stencilOpSeparate\",[1029,7680,7680,7680]),y(\"scissor.enable\",3089),x(\"scissor.box\",\"scissor\",[0,0,t.drawingBufferWidth,t.drawingBufferHeight]),x(\"viewport\",\"viewport\",[0,0,t.drawingBufferWidth,t.drawingBufferHeight]);var ot={gl:t,context:p,strings:e,next:et,current:tt,draw:f,elements:o,buffer:a,shader:h,attributes:u.state,uniforms:c,framebuffer:l,extensions:r,timer:d,isBufferArgs:O},st={primTypes:rt,compareFuncs:kt,blendFuncs:wt,blendEquations:J,stencilOps:Tt,glTypes:K,orientationType:Mt};$&&(st.backBuffer=[1029],st.drawBuffer=i(n.maxDrawbuffers,function(t){return 0===t?[0]:i(t,function(t){return 36064+t})}));var lt=0;return{next:et,current:tt,procs:function(){var t=b(),e=t.proc(\"poll\"),r=t.proc(\"refresh\"),a=t.block();e(a),r(a);var o,s=t.shared,l=s.gl,c=s.next,u=s.current;a(u,\".dirty=false;\"),S(t,e),S(t,r,null,!0),Q&&(o=t.link(Q));for(var h=0;h<n.maxAttributes;++h){var f=r.def(s.attributes,\"[\",h,\"]\"),p=t.cond(f,\".buffer\");p.then(l,\".enableVertexAttribArray(\",h,\");\",l,\".bindBuffer(\",34962,\",\",f,\".buffer.buffer);\",l,\".vertexAttribPointer(\",h,\",\",f,\".size,\",f,\".type,\",f,\".normalized,\",f,\".stride,\",f,\".offset);\").else(l,\".disableVertexAttribArray(\",h,\");\",l,\".vertexAttrib4f(\",h,\",\",f,\".x,\",f,\".y,\",f,\".z,\",f,\".w);\",f,\".buffer=null;\"),r(p),Q&&r(o,\".vertexAttribDivisorANGLE(\",h,\",\",f,\".divisor);\")}return Object.keys(at).forEach(function(n){var i=at[n],o=a.def(c,\".\",n),s=t.block();s(\"if(\",o,\"){\",l,\".enable(\",i,\")}else{\",l,\".disable(\",i,\")}\",u,\".\",n,\"=\",o,\";\"),r(s),e(\"if(\",o,\"!==\",u,\".\",n,\"){\",s,\"}\")}),Object.keys(it).forEach(function(n){var o,s,h=it[n],f=tt[n],p=t.block();p(l,\".\",h,\"(\"),v(f)?(h=f.length,o=t.global.def(c,\".\",n),s=t.global.def(u,\".\",n),p(i(h,function(t){return o+\"[\"+t+\"]\"}),\");\",i(h,function(t){return s+\"[\"+t+\"]=\"+o+\"[\"+t+\"];\"}).join(\"\")),e(\"if(\",i(h,function(t){return o+\"[\"+t+\"]!==\"+s+\"[\"+t+\"]\"}).join(\"||\"),\"){\",p,\"}\")):(o=a.def(c,\".\",n),s=a.def(u,\".\",n),p(o,\");\",u,\".\",n,\"=\",o,\";\"),e(\"if(\",o,\"!==\",s,\"){\",p,\"}\")),r(p)}),t.compile()}(),compile:function(t,e,r,n,a){var i=b();return i.stats=i.link(a),Object.keys(e.static).forEach(function(t){X(i,e,t)}),_t.forEach(function(e){X(i,t,e)}),r=M(t,e,r,n),function(t,e){var r=t.proc(\"draw\",1);C(t,r),A(t,r,e.context),S(t,r,e.framebuffer),E(t,r,e),L(t,r,e.state),B(t,r,e,!1,!0);var n=e.shader.progVar.append(t,r);if(r(t.shared.gl,\".useProgram(\",n,\".program);\"),e.shader.program)H(t,r,e,e.shader.program);else{var a=t.global.def(\"{}\"),i=r.def(n,\".id\"),o=r.def(a,\"[\",i,\"]\");r(t.cond(o).then(o,\".call(this,a0);\").else(o,\"=\",a,\"[\",i,\"]=\",t.link(function(r){return q(H,t,e,r,1)}),\"(\",n,\");\",o,\".call(this,a0);\"))}0<Object.keys(e.state).length&&r(t.shared.current,\".dirty=true;\")}(i,r),W(i,r),function(t,e){function r(t){return t.contextDep&&a||t.propDep}var n=t.proc(\"batch\",2);t.batchId=\"0\",C(t,n);var a=!1,i=!0;Object.keys(e.context).forEach(function(t){a=a||e.context[t].propDep}),a||(A(t,n,e.context),i=!1);var o=!1;if((s=e.framebuffer)?(s.propDep?a=o=!0:s.contextDep&&a&&(o=!0),o||S(t,n,s)):S(t,n,null),e.state.viewport&&e.state.viewport.propDep&&(a=!0),E(t,n,e),L(t,n,e.state,function(t){return!r(t)}),e.profile&&r(e.profile)||B(t,n,e,!1,\"a1\"),e.contextDep=a,e.needsContext=i,e.needsFramebuffer=o,(i=e.shader.progVar).contextDep&&a||i.propDep)Y(t,n,e,null);else if(i=i.append(t,n),n(t.shared.gl,\".useProgram(\",i,\".program);\"),e.shader.program)Y(t,n,e,e.shader.program);else{var s=t.global.def(\"{}\"),l=(o=n.def(i,\".id\"),n.def(s,\"[\",o,\"]\"));n(t.cond(l).then(l,\".call(this,a0,a1);\").else(l,\"=\",s,\"[\",o,\"]=\",t.link(function(r){return q(Y,t,e,r,2)}),\"(\",i,\");\",l,\".call(this,a0,a1);\"))}0<Object.keys(e.state).length&&n(t.shared.current,\".dirty=true;\")}(i,r),i.compile()}}}function N(t,e){for(var r=0;r<t.length;++r)if(t[r]===e)return r;return-1}var j=function(t,e){for(var r=Object.keys(e),n=0;n<r.length;++n)t[r[n]]=e[r[n]];return t},V=0,U={DynamicVariable:t,define:function(r,n){return new t(r,e(n+\"\"))},isDynamic:function(e){return\"function\"==typeof e&&!e._reglType||e instanceof t},unbox:function(e,r){return\"function\"==typeof e?new t(0,e):e},accessor:e},q={next:\"function\"==typeof requestAnimationFrame?function(t){return requestAnimationFrame(t)}:function(t){return setTimeout(t,16)},cancel:\"function\"==typeof cancelAnimationFrame?function(t){return cancelAnimationFrame(t)}:clearTimeout},H=\"undefined\"!=typeof performance&&performance.now?function(){return performance.now()}:function(){return+new Date},G=s();G.zero=s();var Y=function(t,e){var r=1;e.ext_texture_filter_anisotropic&&(r=t.getParameter(34047));var n=1,a=1;e.webgl_draw_buffers&&(n=t.getParameter(34852),a=t.getParameter(36063));var i=!!e.oes_texture_float;if(i){i=t.createTexture(),t.bindTexture(3553,i),t.texImage2D(3553,0,6408,1,1,0,6408,5126,null);var o=t.createFramebuffer();if(t.bindFramebuffer(36160,o),t.framebufferTexture2D(36160,36064,3553,i,0),t.bindTexture(3553,null),36053!==t.checkFramebufferStatus(36160))i=!1;else{t.viewport(0,0,1,1),t.clearColor(1,0,0,1),t.clear(16384);var s=G.allocType(5126,4);t.readPixels(0,0,1,1,6408,5126,s),t.getError()?i=!1:(t.deleteFramebuffer(o),t.deleteTexture(i),i=1===s[0]),G.freeType(s)}}return s=!0,\"undefined\"!=typeof navigator&&(/MSIE/.test(navigator.userAgent)||/Trident\\//.test(navigator.appVersion)||/Edge/.test(navigator.userAgent))||(s=t.createTexture(),o=G.allocType(5121,36),t.activeTexture(33984),t.bindTexture(34067,s),t.texImage2D(34069,0,6408,3,3,0,6408,5121,o),G.freeType(o),t.bindTexture(34067,null),t.deleteTexture(s),s=!t.getError()),{colorBits:[t.getParameter(3410),t.getParameter(3411),t.getParameter(3412),t.getParameter(3413)],depthBits:t.getParameter(3414),stencilBits:t.getParameter(3415),subpixelBits:t.getParameter(3408),extensions:Object.keys(e).filter(function(t){return!!e[t]}),maxAnisotropic:r,maxDrawbuffers:n,maxColorAttachments:a,pointSizeDims:t.getParameter(33901),lineWidthDims:t.getParameter(33902),maxViewportDims:t.getParameter(3386),maxCombinedTextureUnits:t.getParameter(35661),maxCubeMapSize:t.getParameter(34076),maxRenderbufferSize:t.getParameter(34024),maxTextureUnits:t.getParameter(34930),maxTextureSize:t.getParameter(3379),maxAttributes:t.getParameter(34921),maxVertexUniforms:t.getParameter(36347),maxVertexTextureUnits:t.getParameter(35660),maxVaryingVectors:t.getParameter(36348),maxFragmentUniforms:t.getParameter(36349),glsl:t.getParameter(35724),renderer:t.getParameter(7937),vendor:t.getParameter(7936),version:t.getParameter(7938),readFloat:i,npotTextureCube:s}},W=function(t){return t instanceof Uint8Array||t instanceof Uint16Array||t instanceof Uint32Array||t instanceof Int8Array||t instanceof Int16Array||t instanceof Int32Array||t instanceof Float32Array||t instanceof Float64Array||t instanceof Uint8ClampedArray},X=function(t){return Object.keys(t).map(function(e){return t[e]})},Z={shape:function(t){for(var e=[];t.length;t=t[0])e.push(t.length);return e},flatten:function(t,e,r,n){var a=1;if(e.length)for(var i=0;i<e.length;++i)a*=e[i];else a=0;switch(r=n||G.allocType(r,a),e.length){case 0:break;case 1:for(n=e[0],e=0;e<n;++e)r[e]=t[e];break;case 2:for(n=e[0],e=e[1],i=a=0;i<n;++i)for(var o=t[i],s=0;s<e;++s)r[a++]=o[s];break;case 3:c(t,e[0],e[1],e[2],r,0);break;default:!function t(e,r,n,a,i){for(var o=1,s=n+1;s<r.length;++s)o*=r[s];var l=r[n];if(4==r.length-n){var u=r[n+1],h=r[n+2];for(r=r[n+3],s=0;s<l;++s)c(e[s],u,h,r,a,i),i+=o}else for(s=0;s<l;++s)t(e[s],r,n+1,a,i),i+=o}(t,e,0,r,0)}return r}},J={\"[object Int8Array]\":5120,\"[object Int16Array]\":5122,\"[object Int32Array]\":5124,\"[object Uint8Array]\":5121,\"[object Uint8ClampedArray]\":5121,\"[object Uint16Array]\":5123,\"[object Uint32Array]\":5125,\"[object Float32Array]\":5126,\"[object Float64Array]\":5121,\"[object ArrayBuffer]\":5121},K={int8:5120,int16:5122,int32:5124,uint8:5121,uint16:5123,uint32:5125,float:5126,float32:5126},Q={dynamic:35048,stream:35040,static:35044},$=Z.flatten,tt=Z.shape,et=[];et[5120]=1,et[5122]=2,et[5124]=4,et[5121]=1,et[5123]=2,et[5125]=4,et[5126]=4;var rt={points:0,point:0,lines:1,line:1,triangles:4,triangle:4,\"line loop\":2,\"line strip\":3,\"triangle strip\":5,\"triangle fan\":6},nt=new Float32Array(1),at=new Uint32Array(nt.buffer),it=[9984,9986,9985,9987],ot=[0,6409,6410,6407,6408],st={};st[6409]=st[6406]=st[6402]=1,st[34041]=st[6410]=2,st[6407]=st[35904]=3,st[6408]=st[35906]=4;var lt=m(\"HTMLCanvasElement\"),ct=m(\"CanvasRenderingContext2D\"),ut=m(\"ImageBitmap\"),ht=m(\"HTMLImageElement\"),ft=m(\"HTMLVideoElement\"),pt=Object.keys(J).concat([lt,ct,ut,ht,ft]),dt=[];dt[5121]=1,dt[5126]=4,dt[36193]=2,dt[5123]=2,dt[5125]=4;var gt=[];gt[32854]=2,gt[32855]=2,gt[36194]=2,gt[34041]=4,gt[33776]=.5,gt[33777]=.5,gt[33778]=1,gt[33779]=1,gt[35986]=.5,gt[35987]=1,gt[34798]=1,gt[35840]=.5,gt[35841]=.25,gt[35842]=.5,gt[35843]=.25,gt[36196]=.5;var vt=[];vt[32854]=2,vt[32855]=2,vt[36194]=2,vt[33189]=2,vt[36168]=1,vt[34041]=4,vt[35907]=4,vt[34836]=16,vt[34842]=8,vt[34843]=6;var mt=function(t,e,r,n,a){function i(t){this.id=c++,this.refCount=1,this.renderbuffer=t,this.format=32854,this.height=this.width=0,a.profile&&(this.stats={size:0})}function o(e){var r=e.renderbuffer;t.bindRenderbuffer(36161,null),t.deleteRenderbuffer(r),e.renderbuffer=null,e.refCount=0,delete u[e.id],n.renderbufferCount--}var s={rgba4:32854,rgb565:36194,\"rgb5 a1\":32855,depth:33189,stencil:36168,\"depth stencil\":34041};e.ext_srgb&&(s.srgba=35907),e.ext_color_buffer_half_float&&(s.rgba16f=34842,s.rgb16f=34843),e.webgl_color_buffer_float&&(s.rgba32f=34836);var l=[];Object.keys(s).forEach(function(t){l[s[t]]=t});var c=0,u={};return i.prototype.decRef=function(){0>=--this.refCount&&o(this)},a.profile&&(n.getTotalRenderbufferSize=function(){var t=0;return Object.keys(u).forEach(function(e){t+=u[e].stats.size}),t}),{create:function(e,r){function o(e,r){var n=0,i=0,u=32854;if(\"object\"==typeof e&&e?(\"shape\"in e?(n=0|(i=e.shape)[0],i=0|i[1]):(\"radius\"in e&&(n=i=0|e.radius),\"width\"in e&&(n=0|e.width),\"height\"in e&&(i=0|e.height)),\"format\"in e&&(u=s[e.format])):\"number\"==typeof e?(n=0|e,i=\"number\"==typeof r?0|r:n):e||(n=i=1),n!==c.width||i!==c.height||u!==c.format)return o.width=c.width=n,o.height=c.height=i,c.format=u,t.bindRenderbuffer(36161,c.renderbuffer),t.renderbufferStorage(36161,u,n,i),a.profile&&(c.stats.size=vt[c.format]*c.width*c.height),o.format=l[c.format],o}var c=new i(t.createRenderbuffer());return u[c.id]=c,n.renderbufferCount++,o(e,r),o.resize=function(e,r){var n=0|e,i=0|r||n;return n===c.width&&i===c.height?o:(o.width=c.width=n,o.height=c.height=i,t.bindRenderbuffer(36161,c.renderbuffer),t.renderbufferStorage(36161,c.format,n,i),a.profile&&(c.stats.size=vt[c.format]*c.width*c.height),o)},o._reglType=\"renderbuffer\",o._renderbuffer=c,a.profile&&(o.stats=c.stats),o.destroy=function(){c.decRef()},o},clear:function(){X(u).forEach(o)},restore:function(){X(u).forEach(function(e){e.renderbuffer=t.createRenderbuffer(),t.bindRenderbuffer(36161,e.renderbuffer),t.renderbufferStorage(36161,e.format,e.width,e.height)}),t.bindRenderbuffer(36161,null)}}},yt=[];yt[6408]=4,yt[6407]=3;var xt=[];xt[5121]=1,xt[5126]=4,xt[36193]=2;var bt=[\"x\",\"y\",\"z\",\"w\"],_t=\"blend.func blend.equation stencil.func stencil.opFront stencil.opBack sample.coverage viewport scissor.box polygonOffset.offset\".split(\" \"),wt={0:0,1:1,zero:0,one:1,\"src color\":768,\"one minus src color\":769,\"src alpha\":770,\"one minus src alpha\":771,\"dst color\":774,\"one minus dst color\":775,\"dst alpha\":772,\"one minus dst alpha\":773,\"constant color\":32769,\"one minus constant color\":32770,\"constant alpha\":32771,\"one minus constant alpha\":32772,\"src alpha saturate\":776},kt={never:512,less:513,\"<\":513,equal:514,\"=\":514,\"==\":514,\"===\":514,lequal:515,\"<=\":515,greater:516,\">\":516,notequal:517,\"!=\":517,\"!==\":517,gequal:518,\">=\":518,always:519},Tt={0:0,zero:0,keep:7680,replace:7681,increment:7682,decrement:7683,\"increment wrap\":34055,\"decrement wrap\":34056,invert:5386},Mt={cw:2304,ccw:2305},At=new I(!1,!1,!1,function(){});return function(t){function e(){if(0===Z.length)w&&w.update(),$=null;else{$=q.next(e),h();for(var t=Z.length-1;0<=t;--t){var r=Z[t];r&&r(P,null,0)}v.flush(),w&&w.update()}}function r(){!$&&0<Z.length&&($=q.next(e))}function n(){$&&(q.cancel(e),$=null)}function i(t){t.preventDefault(),n(),J.forEach(function(t){t()})}function o(t){v.getError(),y.restore(),D.restore(),z.restore(),R.restore(),F.restore(),V.restore(),w&&w.restore(),G.procs.refresh(),r(),K.forEach(function(t){t()})}function s(t){function e(t){var e={},r={};return Object.keys(t).forEach(function(n){var a=t[n];U.isDynamic(a)?r[n]=U.unbox(a,n):e[n]=a}),{dynamic:r,static:e}}var r=e(t.context||{}),n=e(t.uniforms||{}),a=e(t.attributes||{}),i=e(function(t){function e(t){if(t in r){var e=r[t];delete r[t],Object.keys(e).forEach(function(n){r[t+\".\"+n]=e[n]})}}var r=j({},t);return delete r.uniforms,delete r.attributes,delete r.context,\"stencil\"in r&&r.stencil.op&&(r.stencil.opBack=r.stencil.opFront=r.stencil.op,delete r.stencil.op),e(\"blend\"),e(\"depth\"),e(\"cull\"),e(\"stencil\"),e(\"polygonOffset\"),e(\"scissor\"),e(\"sample\"),r}(t));t={gpuTime:0,cpuTime:0,count:0};var o=(r=G.compile(i,a,n,r,t)).draw,s=r.batch,l=r.scope,c=[];return j(function(t,e){var r;if(\"function\"==typeof t)return l.call(this,null,t,0);if(\"function\"==typeof e)if(\"number\"==typeof t)for(r=0;r<t;++r)l.call(this,null,e,r);else{if(!Array.isArray(t))return l.call(this,t,e,0);for(r=0;r<t.length;++r)l.call(this,t[r],e,r)}else if(\"number\"==typeof t){if(0<t)return s.call(this,function(t){for(;c.length<t;)c.push(null);return c}(0|t),0|t)}else{if(!Array.isArray(t))return o.call(this,t);if(t.length)return s.call(this,t,t.length)}},{stats:t})}function l(t,e){var r=0;G.procs.poll();var n=e.color;n&&(v.clearColor(+n[0]||0,+n[1]||0,+n[2]||0,+n[3]||0),r|=16384),\"depth\"in e&&(v.clearDepth(+e.depth),r|=256),\"stencil\"in e&&(v.clearStencil(0|e.stencil),r|=1024),v.clear(r)}function c(t){return Z.push(t),r(),{cancel:function(){var e=N(Z,t);Z[e]=function t(){var e=N(Z,t);Z[e]=Z[Z.length-1],--Z.length,0>=Z.length&&n()}}}}function u(){var t=W.viewport,e=W.scissor_box;t[0]=t[1]=e[0]=e[1]=0,P.viewportWidth=P.framebufferWidth=P.drawingBufferWidth=t[2]=e[2]=v.drawingBufferWidth,P.viewportHeight=P.framebufferHeight=P.drawingBufferHeight=t[3]=e[3]=v.drawingBufferHeight}function h(){P.tick+=1,P.time=g(),u(),G.procs.poll()}function f(){u(),G.procs.refresh(),w&&w.update()}function g(){return(H()-k)/1e3}if(!(t=a(t)))return null;var v=t.gl,m=v.getContextAttributes();v.isContextLost();var y=function(t,e){function r(e){var r;e=e.toLowerCase();try{r=n[e]=t.getExtension(e)}catch(t){}return!!r}for(var n={},a=0;a<e.extensions.length;++a){var i=e.extensions[a];if(!r(i))return e.onDestroy(),e.onDone('\"'+i+'\" extension is not supported by the current WebGL context, try upgrading your system or a different browser'),null}return e.optionalExtensions.forEach(r),{extensions:n,restore:function(){Object.keys(n).forEach(function(t){if(n[t]&&!r(t))throw Error(\"(regl): error restoring extension \"+t)})}}}(v,t);if(!y)return null;var x=function(){var t={\"\":0},e=[\"\"];return{id:function(r){var n=t[r];return n||(n=t[r]=e.length,e.push(r),n)},str:function(t){return e[t]}}}(),b={bufferCount:0,elementsCount:0,framebufferCount:0,shaderCount:0,textureCount:0,cubeCount:0,renderbufferCount:0,maxTextureUnits:0},_=y.extensions,w=function(t,e){function r(){this.endQueryIndex=this.startQueryIndex=-1,this.sum=0,this.stats=null}function n(t,e,n){var a=o.pop()||new r;a.startQueryIndex=t,a.endQueryIndex=e,a.sum=0,a.stats=n,s.push(a)}if(!e.ext_disjoint_timer_query)return null;var a=[],i=[],o=[],s=[],l=[],c=[];return{beginQuery:function(t){var r=a.pop()||e.ext_disjoint_timer_query.createQueryEXT();e.ext_disjoint_timer_query.beginQueryEXT(35007,r),i.push(r),n(i.length-1,i.length,t)},endQuery:function(){e.ext_disjoint_timer_query.endQueryEXT(35007)},pushScopeStats:n,update:function(){var t,r;if(0!==(t=i.length)){c.length=Math.max(c.length,t+1),l.length=Math.max(l.length,t+1),l[0]=0;var n=c[0]=0;for(r=t=0;r<i.length;++r){var u=i[r];e.ext_disjoint_timer_query.getQueryObjectEXT(u,34919)?(n+=e.ext_disjoint_timer_query.getQueryObjectEXT(u,34918),a.push(u)):i[t++]=u,l[r+1]=n,c[r+1]=t}for(i.length=t,r=t=0;r<s.length;++r){var h=(n=s[r]).startQueryIndex;u=n.endQueryIndex,n.sum+=l[u]-l[h],h=c[h],(u=c[u])===h?(n.stats.gpuTime+=n.sum/1e6,o.push(n)):(n.startQueryIndex=h,n.endQueryIndex=u,s[t++]=n)}s.length=t}},getNumPendingQueries:function(){return i.length},clear:function(){a.push.apply(a,i);for(var t=0;t<a.length;t++)e.ext_disjoint_timer_query.deleteQueryEXT(a[t]);i.length=0,a.length=0},restore:function(){i.length=0,a.length=0}}}(0,_),k=H(),L=v.drawingBufferWidth,C=v.drawingBufferHeight,P={tick:0,time:0,viewportWidth:L,viewportHeight:C,framebufferWidth:L,framebufferHeight:C,drawingBufferWidth:L,drawingBufferHeight:C,pixelRatio:t.pixelRatio},O=Y(v,_),z=(L=function(t,e,r,n){for(t=r.maxAttributes,e=Array(t),r=0;r<t;++r)e[r]=new A;return{Record:A,scope:{},state:e}}(v,_,O),p(v,b,t,L)),I=d(v,_,z,b),D=S(v,x,b,t),R=T(v,_,O,function(){G.procs.poll()},P,b,t),F=mt(v,_,0,b,t),V=M(v,_,O,R,F,b),G=B(v,x,_,O,z,I,0,V,{},L,D,{elements:null,primitive:4,count:-1,offset:0,instances:-1},P,w,t),W=(x=E(v,V,G.procs.poll,P),G.next),X=v.canvas,Z=[],J=[],K=[],Q=[t.onDestroy],$=null;X&&(X.addEventListener(\"webglcontextlost\",i,!1),X.addEventListener(\"webglcontextrestored\",o,!1));var tt=V.setFBO=s({framebuffer:U.define.call(null,1,\"framebuffer\")});return f(),m=j(s,{clear:function(t){if(\"framebuffer\"in t)if(t.framebuffer&&\"framebufferCube\"===t.framebuffer_reglType)for(var e=0;6>e;++e)tt(j({framebuffer:t.framebuffer.faces[e]},t),l);else tt(t,l);else l(0,t)},prop:U.define.bind(null,1),context:U.define.bind(null,2),this:U.define.bind(null,3),draw:s({}),buffer:function(t){return z.create(t,34962,!1,!1)},elements:function(t){return I.create(t,!1)},texture:R.create2D,cube:R.createCube,renderbuffer:F.create,framebuffer:V.create,framebufferCube:V.createCube,attributes:m,frame:c,on:function(t,e){var r;switch(t){case\"frame\":return c(e);case\"lost\":r=J;break;case\"restore\":r=K;break;case\"destroy\":r=Q}return r.push(e),{cancel:function(){for(var t=0;t<r.length;++t)if(r[t]===e){r[t]=r[r.length-1],r.pop();break}}}},limits:O,hasExtension:function(t){return 0<=O.extensions.indexOf(t.toLowerCase())},read:x,destroy:function(){Z.length=0,n(),X&&(X.removeEventListener(\"webglcontextlost\",i),X.removeEventListener(\"webglcontextrestored\",o)),D.clear(),V.clear(),F.clear(),R.clear(),I.clear(),z.clear(),w&&w.clear(),Q.forEach(function(t){t()})},_gl:v,_refresh:f,poll:function(){h(),w&&w.update()},now:g,stats:b}),t.onDone(null,m),m}},\"object\"==typeof r&&\"undefined\"!=typeof e?e.exports=a():n.createREGL=a()},{}],502:[function(t,e,r){\"use strict\";var n,a=\"\";e.exports=function(t,e){if(\"string\"!=typeof t)throw new TypeError(\"expected a string\");if(1===e)return t;if(2===e)return t+t;var r=t.length*e;if(n!==t||\"undefined\"==typeof n)n=t,a=\"\";else if(a.length>=r)return a.substr(0,r);for(;r>a.length&&e>1;)1&e&&(a+=t),e>>=1,t+=t;return a=(a+=t).substr(0,r)}},{}],503:[function(t,e,r){(function(t){e.exports=t.performance&&t.performance.now?function(){return performance.now()}:Date.now||function(){return+new Date}}).call(this,\"undefined\"!=typeof global?global:\"undefined\"!=typeof self?self:\"undefined\"!=typeof window?window:{})},{}],504:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=t.length,r=t[t.length-1],n=e,a=e-2;a>=0;--a){var i=r,o=t[a],s=(r=i+o)-i,l=o-s;l&&(t[--n]=r,r=l)}for(var c=0,a=n;a<e;++a){var i=t[a],o=r,s=(r=i+o)-i,l=o-s;l&&(t[c++]=l)}return t[c++]=r,t.length=c,t}},{}],505:[function(t,e,r){\"use strict\";var n=t(\"two-product\"),a=t(\"robust-sum\"),i=t(\"robust-scale\"),o=t(\"robust-compress\"),s=6;function l(t,e){for(var r=new Array(t.length-1),n=1;n<t.length;++n)for(var a=r[n-1]=new Array(t.length-1),i=0,o=0;i<t.length;++i)i!==e&&(a[o++]=t[n][i]);return r}function c(t){for(var e=new Array(t),r=0;r<t;++r){e[r]=new Array(t);for(var n=0;n<t;++n)e[r][n]=[\"m[\",r,\"][\",n,\"]\"].join(\"\")}return e}function u(t){if(2===t.length)return[\"sum(prod(\",t[0][0],\",\",t[1][1],\"),prod(-\",t[0][1],\",\",t[1][0],\"))\"].join(\"\");for(var e=[],r=0;r<t.length;++r)e.push([\"scale(\",u(l(t,r)),\",\",(n=r,1&n?\"-\":\"\"),t[0][r],\")\"].join(\"\"));return function t(e){if(1===e.length)return e[0];if(2===e.length)return[\"sum(\",e[0],\",\",e[1],\")\"].join(\"\");var r=e.length>>1;return[\"sum(\",t(e.slice(0,r)),\",\",t(e.slice(r)),\")\"].join(\"\")}(e);var n}function h(t){return new Function(\"sum\",\"scale\",\"prod\",\"compress\",[\"function robustDeterminant\",t,\"(m){return compress(\",u(c(t)),\")};return robustDeterminant\",t].join(\"\"))(a,i,n,o)}var f=[function(){return[0]},function(t){return[t[0][0]]}];!function(){for(;f.length<s;)f.push(h(f.length));for(var t=[],r=[\"function robustDeterminant(m){switch(m.length){\"],n=0;n<s;++n)t.push(\"det\"+n),r.push(\"case \",n,\":return det\",n,\"(m);\");r.push(\"}var det=CACHE[m.length];if(!det)det=CACHE[m.length]=gen(m.length);return det(m);}return robustDeterminant\"),t.push(\"CACHE\",\"gen\",r.join(\"\"));var a=Function.apply(void 0,t);for(e.exports=a.apply(void 0,f.concat([f,h])),n=0;n<f.length;++n)e.exports[n]=f[n]}()},{\"robust-compress\":504,\"robust-scale\":511,\"robust-sum\":514,\"two-product\":542}],506:[function(t,e,r){\"use strict\";var n=t(\"two-product\"),a=t(\"robust-sum\");e.exports=function(t,e){for(var r=n(t[0],e[0]),i=1;i<t.length;++i)r=a(r,n(t[i],e[i]));return r}},{\"robust-sum\":514,\"two-product\":542}],507:[function(t,e,r){\"use strict\";var n=t(\"two-product\"),a=t(\"robust-sum\"),i=t(\"robust-subtract\"),o=t(\"robust-scale\"),s=6;function l(t,e){for(var r=new Array(t.length-1),n=1;n<t.length;++n)for(var a=r[n-1]=new Array(t.length-1),i=0,o=0;i<t.length;++i)i!==e&&(a[o++]=t[n][i]);return r}function c(t){if(1===t.length)return t[0];if(2===t.length)return[\"sum(\",t[0],\",\",t[1],\")\"].join(\"\");var e=t.length>>1;return[\"sum(\",c(t.slice(0,e)),\",\",c(t.slice(e)),\")\"].join(\"\")}function u(t,e){if(\"m\"===t.charAt(0)){if(\"w\"===e.charAt(0)){var r=t.split(\"[\");return[\"w\",e.substr(1),\"m\",r[0].substr(1)].join(\"\")}return[\"prod(\",t,\",\",e,\")\"].join(\"\")}return u(e,t)}function h(t){if(2===t.length)return[[\"diff(\",u(t[0][0],t[1][1]),\",\",u(t[1][0],t[0][1]),\")\"].join(\"\")];for(var e=[],r=0;r<t.length;++r)e.push([\"scale(\",c(h(l(t,r))),\",\",(n=r,!0&n?\"-\":\"\"),t[0][r],\")\"].join(\"\"));return e;var n}function f(t,e){for(var r=[],n=0;n<e-2;++n)r.push([\"prod(m\",t,\"[\",n,\"],m\",t,\"[\",n,\"])\"].join(\"\"));return c(r)}function p(t){for(var e=[],r=[],s=function(t){for(var e=new Array(t),r=0;r<t;++r){e[r]=new Array(t);for(var n=0;n<t;++n)e[r][n]=[\"m\",n,\"[\",t-r-2,\"]\"].join(\"\")}return e}(t),u=0;u<t;++u)s[0][u]=\"1\",s[t-1][u]=\"w\"+u;for(u=0;u<t;++u)0==(1&u)?e.push.apply(e,h(l(s,u))):r.push.apply(r,h(l(s,u)));var p=c(e),d=c(r),g=\"exactInSphere\"+t,v=[];for(u=0;u<t;++u)v.push(\"m\"+u);var m=[\"function \",g,\"(\",v.join(),\"){\"];for(u=0;u<t;++u){m.push(\"var w\",u,\"=\",f(u,t),\";\");for(var y=0;y<t;++y)y!==u&&m.push(\"var w\",u,\"m\",y,\"=scale(w\",u,\",m\",y,\"[0]);\")}return m.push(\"var p=\",p,\",n=\",d,\",d=diff(p,n);return d[d.length-1];}return \",g),new Function(\"sum\",\"diff\",\"prod\",\"scale\",m.join(\"\"))(a,i,n,o)}var d=[function(){return 0},function(){return 0},function(){return 0}];function g(t){var e=d[t.length];return e||(e=d[t.length]=p(t.length)),e.apply(void 0,t)}!function(){for(;d.length<=s;)d.push(p(d.length));for(var t=[],r=[\"slow\"],n=0;n<=s;++n)t.push(\"a\"+n),r.push(\"o\"+n);var a=[\"function testInSphere(\",t.join(),\"){switch(arguments.length){case 0:case 1:return 0;\"];for(n=2;n<=s;++n)a.push(\"case \",n,\":return o\",n,\"(\",t.slice(0,n).join(),\");\");a.push(\"}var s=new Array(arguments.length);for(var i=0;i<arguments.length;++i){s[i]=arguments[i]};return slow(s);}return testInSphere\"),r.push(a.join(\"\"));var i=Function.apply(void 0,r);for(e.exports=i.apply(void 0,[g].concat(d)),n=0;n<=s;++n)e.exports[n]=d[n]}()},{\"robust-scale\":511,\"robust-subtract\":513,\"robust-sum\":514,\"two-product\":542}],508:[function(t,e,r){\"use strict\";var n=t(\"robust-determinant\"),a=6;function i(t){for(var e=\"robustLinearSolve\"+t+\"d\",r=[\"function \",e,\"(A,b){return [\"],a=0;a<t;++a){r.push(\"det([\");for(var i=0;i<t;++i){i>0&&r.push(\",\"),r.push(\"[\");for(var o=0;o<t;++o)o>0&&r.push(\",\"),o===a?r.push(\"+b[\",i,\"]\"):r.push(\"+A[\",i,\"][\",o,\"]\");r.push(\"]\")}r.push(\"]),\")}r.push(\"det(A)]}return \",e);var s=new Function(\"det\",r.join(\"\"));return s(t<6?n[t]:n)}var o=[function(){return[0]},function(t,e){return[[e[0]],[t[0][0]]]}];!function(){for(;o.length<a;)o.push(i(o.length));for(var t=[],r=[\"function dispatchLinearSolve(A,b){switch(A.length){\"],n=0;n<a;++n)t.push(\"s\"+n),r.push(\"case \",n,\":return s\",n,\"(A,b);\");r.push(\"}var s=CACHE[A.length];if(!s)s=CACHE[A.length]=g(A.length);return s(A,b)}return dispatchLinearSolve\"),t.push(\"CACHE\",\"g\",r.join(\"\"));var s=Function.apply(void 0,t);for(e.exports=s.apply(void 0,o.concat([o,i])),n=0;n<a;++n)e.exports[n]=o[n]}()},{\"robust-determinant\":505}],509:[function(t,e,r){\"use strict\";var n=t(\"two-product\"),a=t(\"robust-sum\"),i=t(\"robust-scale\"),o=t(\"robust-subtract\"),s=5;function l(t,e){for(var r=new Array(t.length-1),n=1;n<t.length;++n)for(var a=r[n-1]=new Array(t.length-1),i=0,o=0;i<t.length;++i)i!==e&&(a[o++]=t[n][i]);return r}function c(t){if(1===t.length)return t[0];if(2===t.length)return[\"sum(\",t[0],\",\",t[1],\")\"].join(\"\");var e=t.length>>1;return[\"sum(\",c(t.slice(0,e)),\",\",c(t.slice(e)),\")\"].join(\"\")}function u(t){if(2===t.length)return[[\"sum(prod(\",t[0][0],\",\",t[1][1],\"),prod(-\",t[0][1],\",\",t[1][0],\"))\"].join(\"\")];for(var e=[],r=0;r<t.length;++r)e.push([\"scale(\",c(u(l(t,r))),\",\",(n=r,1&n?\"-\":\"\"),t[0][r],\")\"].join(\"\"));return e;var n}function h(t){for(var e=[],r=[],s=function(t){for(var e=new Array(t),r=0;r<t;++r){e[r]=new Array(t);for(var n=0;n<t;++n)e[r][n]=[\"m\",n,\"[\",t-r-1,\"]\"].join(\"\")}return e}(t),h=[],f=0;f<t;++f)0==(1&f)?e.push.apply(e,u(l(s,f))):r.push.apply(r,u(l(s,f))),h.push(\"m\"+f);var p=c(e),d=c(r),g=\"orientation\"+t+\"Exact\",v=[\"function \",g,\"(\",h.join(),\"){var p=\",p,\",n=\",d,\",d=sub(p,n);return d[d.length-1];};return \",g].join(\"\");return new Function(\"sum\",\"prod\",\"scale\",\"sub\",v)(a,n,i,o)}var f=h(3),p=h(4),d=[function(){return 0},function(){return 0},function(t,e){return e[0]-t[0]},function(t,e,r){var n,a=(t[1]-r[1])*(e[0]-r[0]),i=(t[0]-r[0])*(e[1]-r[1]),o=a-i;if(a>0){if(i<=0)return o;n=a+i}else{if(!(a<0))return o;if(i>=0)return o;n=-(a+i)}var s=3.3306690738754716e-16*n;return o>=s||o<=-s?o:f(t,e,r)},function(t,e,r,n){var a=t[0]-n[0],i=e[0]-n[0],o=r[0]-n[0],s=t[1]-n[1],l=e[1]-n[1],c=r[1]-n[1],u=t[2]-n[2],h=e[2]-n[2],f=r[2]-n[2],d=i*c,g=o*l,v=o*s,m=a*c,y=a*l,x=i*s,b=u*(d-g)+h*(v-m)+f*(y-x),_=7.771561172376103e-16*((Math.abs(d)+Math.abs(g))*Math.abs(u)+(Math.abs(v)+Math.abs(m))*Math.abs(h)+(Math.abs(y)+Math.abs(x))*Math.abs(f));return b>_||-b>_?b:p(t,e,r,n)}];function g(t){var e=d[t.length];return e||(e=d[t.length]=h(t.length)),e.apply(void 0,t)}!function(){for(;d.length<=s;)d.push(h(d.length));for(var t=[],r=[\"slow\"],n=0;n<=s;++n)t.push(\"a\"+n),r.push(\"o\"+n);var a=[\"function getOrientation(\",t.join(),\"){switch(arguments.length){case 0:case 1:return 0;\"];for(n=2;n<=s;++n)a.push(\"case \",n,\":return o\",n,\"(\",t.slice(0,n).join(),\");\");a.push(\"}var s=new Array(arguments.length);for(var i=0;i<arguments.length;++i){s[i]=arguments[i]};return slow(s);}return getOrientation\"),r.push(a.join(\"\"));var i=Function.apply(void 0,r);for(e.exports=i.apply(void 0,[g].concat(d)),n=0;n<=s;++n)e.exports[n]=d[n]}()},{\"robust-scale\":511,\"robust-subtract\":513,\"robust-sum\":514,\"two-product\":542}],510:[function(t,e,r){\"use strict\";var n=t(\"robust-sum\"),a=t(\"robust-scale\");e.exports=function(t,e){if(1===t.length)return a(e,t[0]);if(1===e.length)return a(t,e[0]);if(0===t.length||0===e.length)return[0];var r=[0];if(t.length<e.length)for(var i=0;i<t.length;++i)r=n(r,a(e,t[i]));else for(var i=0;i<e.length;++i)r=n(r,a(t,e[i]));return r}},{\"robust-scale\":511,\"robust-sum\":514}],511:[function(t,e,r){\"use strict\";var n=t(\"two-product\"),a=t(\"two-sum\");e.exports=function(t,e){var r=t.length;if(1===r){var i=n(t[0],e);return i[0]?i:[i[1]]}var o=new Array(2*r),s=[.1,.1],l=[.1,.1],c=0;n(t[0],e,s),s[0]&&(o[c++]=s[0]);for(var u=1;u<r;++u){n(t[u],e,l);var h=s[1];a(h,l[0],s),s[0]&&(o[c++]=s[0]);var f=l[1],p=s[1],d=f+p,g=d-f,v=p-g;s[1]=d,v&&(o[c++]=v)}s[1]&&(o[c++]=s[1]);0===c&&(o[c++]=0);return o.length=c,o}},{\"two-product\":542,\"two-sum\":543}],512:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,a){var i=n(t,r,a),o=n(e,r,a);if(i>0&&o>0||i<0&&o<0)return!1;var s=n(r,t,e),l=n(a,t,e);if(s>0&&l>0||s<0&&l<0)return!1;if(0===i&&0===o&&0===s&&0===l)return function(t,e,r,n){for(var a=0;a<2;++a){var i=t[a],o=e[a],s=Math.min(i,o),l=Math.max(i,o),c=r[a],u=n[a],h=Math.min(c,u),f=Math.max(c,u);if(f<s||l<h)return!1}return!0}(t,e,r,a);return!0};var n=t(\"robust-orientation\")[3]},{\"robust-orientation\":509}],513:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=0|t.length,n=0|e.length;if(1===r&&1===n)return function(t,e){var r=t+e,n=r-t,a=t-(r-n)+(e-n);if(a)return[a,r];return[r]}(t[0],-e[0]);var a,i,o=new Array(r+n),s=0,l=0,c=0,u=Math.abs,h=t[l],f=u(h),p=-e[c],d=u(p);f<d?(i=h,(l+=1)<r&&(h=t[l],f=u(h))):(i=p,(c+=1)<n&&(p=-e[c],d=u(p)));l<r&&f<d||c>=n?(a=h,(l+=1)<r&&(h=t[l],f=u(h))):(a=p,(c+=1)<n&&(p=-e[c],d=u(p)));var g,v,m=a+i,y=m-a,x=i-y,b=x,_=m;for(;l<r&&c<n;)f<d?(a=h,(l+=1)<r&&(h=t[l],f=u(h))):(a=p,(c+=1)<n&&(p=-e[c],d=u(p))),(x=(i=b)-(y=(m=a+i)-a))&&(o[s++]=x),b=_-((g=_+m)-(v=g-_))+(m-v),_=g;for(;l<r;)(x=(i=b)-(y=(m=(a=h)+i)-a))&&(o[s++]=x),b=_-((g=_+m)-(v=g-_))+(m-v),_=g,(l+=1)<r&&(h=t[l]);for(;c<n;)(x=(i=b)-(y=(m=(a=p)+i)-a))&&(o[s++]=x),b=_-((g=_+m)-(v=g-_))+(m-v),_=g,(c+=1)<n&&(p=-e[c]);b&&(o[s++]=b);_&&(o[s++]=_);s||(o[s++]=0);return o.length=s,o}},{}],514:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=0|t.length,n=0|e.length;if(1===r&&1===n)return function(t,e){var r=t+e,n=r-t,a=t-(r-n)+(e-n);if(a)return[a,r];return[r]}(t[0],e[0]);var a,i,o=new Array(r+n),s=0,l=0,c=0,u=Math.abs,h=t[l],f=u(h),p=e[c],d=u(p);f<d?(i=h,(l+=1)<r&&(h=t[l],f=u(h))):(i=p,(c+=1)<n&&(p=e[c],d=u(p)));l<r&&f<d||c>=n?(a=h,(l+=1)<r&&(h=t[l],f=u(h))):(a=p,(c+=1)<n&&(p=e[c],d=u(p)));var g,v,m=a+i,y=m-a,x=i-y,b=x,_=m;for(;l<r&&c<n;)f<d?(a=h,(l+=1)<r&&(h=t[l],f=u(h))):(a=p,(c+=1)<n&&(p=e[c],d=u(p))),(x=(i=b)-(y=(m=a+i)-a))&&(o[s++]=x),b=_-((g=_+m)-(v=g-_))+(m-v),_=g;for(;l<r;)(x=(i=b)-(y=(m=(a=h)+i)-a))&&(o[s++]=x),b=_-((g=_+m)-(v=g-_))+(m-v),_=g,(l+=1)<r&&(h=t[l]);for(;c<n;)(x=(i=b)-(y=(m=(a=p)+i)-a))&&(o[s++]=x),b=_-((g=_+m)-(v=g-_))+(m-v),_=g,(c+=1)<n&&(p=e[c]);b&&(o[s++]=b);_&&(o[s++]=_);s||(o[s++]=0);return o.length=s,o}},{}],515:[function(t,e,r){\"use strict\";e.exports=function(t){return t<0?-1:t>0?1:0}},{}],516:[function(t,e,r){\"use strict\";e.exports=function(t){return a(n(t))};var n=t(\"boundary-cells\"),a=t(\"reduce-simplicial-complex\")},{\"boundary-cells\":97,\"reduce-simplicial-complex\":491}],517:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,s){r=r||0,\"undefined\"==typeof s&&(s=function(t){for(var e=t.length,r=0,n=0;n<e;++n)r=0|Math.max(r,t[n].length);return r-1}(t));if(0===t.length||s<1)return{cells:[],vertexIds:[],vertexWeights:[]};var l=function(t,e){for(var r=t.length,n=a.mallocUint8(r),i=0;i<r;++i)n[i]=t[i]<e|0;return n}(e,+r),c=function(t,e){for(var r=t.length,o=e*(e+1)/2*r|0,s=a.mallocUint32(2*o),l=0,c=0;c<r;++c)for(var u=t[c],e=u.length,h=0;h<e;++h)for(var f=0;f<h;++f){var p=u[f],d=u[h];s[l++]=0|Math.min(p,d),s[l++]=0|Math.max(p,d)}i(n(s,[l/2|0,2]));for(var g=2,c=2;c<l;c+=2)s[c-2]===s[c]&&s[c-1]===s[c+1]||(s[g++]=s[c],s[g++]=s[c+1]);return n(s,[g/2|0,2])}(t,s),u=function(t,e,r,i){for(var o=t.data,s=t.shape[0],l=a.mallocDouble(s),c=0,u=0;u<s;++u){var h=o[2*u],f=o[2*u+1];if(r[h]!==r[f]){var p=e[h],d=e[f];o[2*c]=h,o[2*c+1]=f,l[c++]=(d-i)/(d-p)}}return t.shape[0]=c,n(l,[c])}(c,e,l,+r),h=function(t,e){var r=a.mallocInt32(2*e),n=t.shape[0],i=t.data;r[0]=0;for(var o=0,s=0;s<n;++s){var l=i[2*s];if(l!==o){for(r[2*o+1]=s;++o<l;)r[2*o]=s,r[2*o+1]=s;r[2*o]=s}}r[2*o+1]=n;for(;++o<e;)r[2*o]=r[2*o+1]=n;return r}(c,0|e.length),f=o(s)(t,c.data,h,l),p=function(t){for(var e=0|t.shape[0],r=t.data,n=new Array(e),a=0;a<e;++a)n[a]=[r[2*a],r[2*a+1]];return n}(c),d=[].slice.call(u.data,0,u.shape[0]);return a.free(l),a.free(c.data),a.free(u.data),a.free(h),{cells:f,vertexIds:p,vertexWeights:d}};var n=t(\"ndarray\"),a=t(\"typedarray-pool\"),i=t(\"ndarray-sort\"),o=t(\"./lib/codegen\")},{\"./lib/codegen\":518,ndarray:452,\"ndarray-sort\":450,\"typedarray-pool\":544}],518:[function(t,e,r){\"use strict\";e.exports=function(t){var e=i[t];e||(e=i[t]=function(t){var e=0,r=new Array(t+1);r[0]=[[]];for(var i=1;i<=t;++i)for(var o=r[i]=a(i),s=0;s<o.length;++s)e=Math.max(e,o[i].length);var l=[\"function B(C,E,i,j){\",\"var a=Math.min(i,j)|0,b=Math.max(i,j)|0,l=C[2*a],h=C[2*a+1];\",\"while(l<h){\",\"var m=(l+h)>>1,v=E[2*m+1];\",\"if(v===b){return m}\",\"if(b<v){h=m}else{l=m+1}\",\"}\",\"return l;\",\"};\",\"function getContour\",t,\"d(F,E,C,S){\",\"var n=F.length,R=[];\",\"for(var i=0;i<n;++i){var c=F[i],l=c.length;\"];function c(t){if(!(t.length<=0)){l.push(\"R.push(\");for(var e=0;e<t.length;++e){var r=t[e];e>0&&l.push(\",\"),l.push(\"[\");for(var n=0;n<r.length;++n){var a=r[n];n>0&&l.push(\",\"),l.push(\"B(C,E,c[\",a[0],\"],c[\",a[1],\"])\")}l.push(\"]\")}l.push(\");\")}}for(var i=t+1;i>1;--i){i<t+1&&l.push(\"else \"),l.push(\"if(l===\",i,\"){\");for(var u=[],s=0;s<i;++s)u.push(\"(S[c[\"+s+\"]]<<\"+s+\")\");l.push(\"var M=\",u.join(\"+\"),\";if(M===0||M===\",(1<<i)-1,\"){continue}switch(M){\");for(var o=r[i-1],s=0;s<o.length;++s)l.push(\"case \",s,\":\"),c(o[s]),l.push(\"break;\");l.push(\"}}\")}return l.push(\"}return R;};return getContour\",t,\"d\"),new Function(\"pool\",l.join(\"\"))(n)}(t));return e};var n=t(\"typedarray-pool\"),a=t(\"marching-simplex-table\"),i={}},{\"marching-simplex-table\":429,\"typedarray-pool\":544}],519:[function(t,e,r){\"use strict\";var n=t(\"bit-twiddle\"),a=t(\"union-find\");function i(t,e){var r=t.length,n=t.length-e.length,a=Math.min;if(n)return n;switch(r){case 0:return 0;case 1:return t[0]-e[0];case 2:return(s=t[0]+t[1]-e[0]-e[1])||a(t[0],t[1])-a(e[0],e[1]);case 3:var i=t[0]+t[1],o=e[0]+e[1];if(s=i+t[2]-(o+e[2]))return s;var s,l=a(t[0],t[1]),c=a(e[0],e[1]);return(s=a(l,t[2])-a(c,e[2]))||a(l+t[2],i)-a(c+e[2],o);default:var u=t.slice(0);u.sort();var h=e.slice(0);h.sort();for(var f=0;f<r;++f)if(n=u[f]-h[f])return n;return 0}}function o(t,e){return i(t[0],e[0])}function s(t,e){if(e){for(var r=t.length,n=new Array(r),a=0;a<r;++a)n[a]=[t[a],e[a]];n.sort(o);for(a=0;a<r;++a)t[a]=n[a][0],e[a]=n[a][1];return t}return t.sort(i),t}function l(t){if(0===t.length)return[];for(var e=1,r=t.length,n=1;n<r;++n){var a=t[n];if(i(a,t[n-1])){if(n===e){e++;continue}t[e++]=a}}return t.length=e,t}function c(t,e){for(var r=0,n=t.length-1,a=-1;r<=n;){var o=r+n>>1,s=i(t[o],e);s<=0?(0===s&&(a=o),r=o+1):s>0&&(n=o-1)}return a}function u(t,e){for(var r=new Array(t.length),a=0,o=r.length;a<o;++a)r[a]=[];for(var s=[],l=(a=0,e.length);a<l;++a)for(var u=e[a],h=u.length,f=1,p=1<<h;f<p;++f){s.length=n.popCount(f);for(var d=0,g=0;g<h;++g)f&1<<g&&(s[d++]=u[g]);var v=c(t,s);if(!(v<0))for(;r[v++].push(a),!(v>=t.length||0!==i(t[v],s)););}return r}function h(t,e){if(e<0)return[];for(var r=[],a=(1<<e+1)-1,i=0;i<t.length;++i)for(var o=t[i],l=a;l<1<<o.length;l=n.nextCombination(l)){for(var c=new Array(e+1),u=0,h=0;h<o.length;++h)l&1<<h&&(c[u++]=o[h]);r.push(c)}return s(r)}r.dimension=function(t){for(var e=0,r=Math.max,n=0,a=t.length;n<a;++n)e=r(e,t[n].length);return e-1},r.countVertices=function(t){for(var e=-1,r=Math.max,n=0,a=t.length;n<a;++n)for(var i=t[n],o=0,s=i.length;o<s;++o)e=r(e,i[o]);return e+1},r.cloneCells=function(t){for(var e=new Array(t.length),r=0,n=t.length;r<n;++r)e[r]=t[r].slice(0);return e},r.compareCells=i,r.normalize=s,r.unique=l,r.findCell=c,r.incidence=u,r.dual=function(t,e){if(!e)return u(l(h(t,0)),t);for(var r=new Array(e),n=0;n<e;++n)r[n]=[];n=0;for(var a=t.length;n<a;++n)for(var i=t[n],o=0,s=i.length;o<s;++o)r[i[o]].push(n);return r},r.explode=function(t){for(var e=[],r=0,n=t.length;r<n;++r)for(var a=t[r],i=0|a.length,o=1,l=1<<i;o<l;++o){for(var c=[],u=0;u<i;++u)o>>>u&1&&c.push(a[u]);e.push(c)}return s(e)},r.skeleton=h,r.boundary=function(t){for(var e=[],r=0,n=t.length;r<n;++r)for(var a=t[r],i=0,o=a.length;i<o;++i){for(var l=new Array(a.length-1),c=0,u=0;c<o;++c)c!==i&&(l[u++]=a[c]);e.push(l)}return s(e)},r.connectedComponents=function(t,e){return e?function(t,e){for(var r=new a(e),n=0;n<t.length;++n)for(var i=t[n],o=0;o<i.length;++o)for(var s=o+1;s<i.length;++s)r.link(i[o],i[s]);var l=[],c=r.ranks;for(n=0;n<c.length;++n)c[n]=-1;for(n=0;n<t.length;++n){var u=r.find(t[n][0]);c[u]<0?(c[u]=l.length,l.push([t[n].slice(0)])):l[c[u]].push(t[n].slice(0))}return l}(t,e):function(t){for(var e=l(s(h(t,0))),r=new a(e.length),n=0;n<t.length;++n)for(var i=t[n],o=0;o<i.length;++o)for(var u=c(e,[i[o]]),f=o+1;f<i.length;++f)r.link(u,c(e,[i[f]]));var p=[],d=r.ranks;for(n=0;n<d.length;++n)d[n]=-1;for(n=0;n<t.length;++n){var g=r.find(c(e,[t[n][0]]));d[g]<0?(d[g]=p.length,p.push([t[n].slice(0)])):p[d[g]].push(t[n].slice(0))}return p}(t)}},{\"bit-twiddle\":94,\"union-find\":545}],520:[function(t,e,r){arguments[4][94][0].apply(r,arguments)},{dup:94}],521:[function(t,e,r){arguments[4][519][0].apply(r,arguments)},{\"bit-twiddle\":520,dup:519,\"union-find\":522}],522:[function(t,e,r){\"use strict\";function n(t){this.roots=new Array(t),this.ranks=new Array(t);for(var e=0;e<t;++e)this.roots[e]=e,this.ranks[e]=0}e.exports=n,n.prototype.length=function(){return this.roots.length},n.prototype.makeSet=function(){var t=this.roots.length;return this.roots.push(t),this.ranks.push(0),t},n.prototype.find=function(t){for(var e=this.roots;e[t]!==t;){var r=e[t];e[t]=e[r],t=r}return t},n.prototype.link=function(t,e){var r=this.find(t),n=this.find(e);if(r!==n){var a=this.ranks,i=this.roots,o=a[r],s=a[n];o<s?i[r]=n:s<o?i[n]=r:(i[n]=r,++a[r])}}},{}],523:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){for(var i=e.length,o=t.length,s=new Array(i),l=new Array(i),c=new Array(i),u=new Array(i),h=0;h<i;++h)s[h]=l[h]=-1,c[h]=1/0,u[h]=!1;for(var h=0;h<o;++h){var f=t[h];if(2!==f.length)throw new Error(\"Input must be a graph\");var p=f[1],d=f[0];-1!==l[d]?l[d]=-2:l[d]=p,-1!==s[p]?s[p]=-2:s[p]=d}function g(t){if(u[t])return 1/0;var r,a,i,o,c,h=s[t],f=l[t];return h<0||f<0?1/0:(r=e[t],a=e[h],i=e[f],o=Math.abs(n(r,a,i)),c=Math.sqrt(Math.pow(a[0]-i[0],2)+Math.pow(a[1]-i[1],2)),o/c)}function v(t,e){var r=T[t],n=T[e];T[t]=n,T[e]=r,M[r]=e,M[n]=t}function m(t){return c[T[t]]}function y(t){return 1&t?t-1>>1:(t>>1)-1}function x(t){for(var e=m(t);;){var r=e,n=2*t+1,a=2*(t+1),i=t;if(n<S){var o=m(n);o<r&&(i=n,r=o)}if(a<S){var s=m(a);s<r&&(i=a)}if(i===t)return t;v(t,i),t=i}}function b(t){for(var e=m(t);t>0;){var r=y(t);if(r>=0){var n=m(r);if(e<n){v(t,r),t=r;continue}}return t}}function _(){if(S>0){var t=T[0];return v(0,S-1),S-=1,x(0),t}return-1}function w(t,e){var r=T[t];return c[r]===e?t:(c[r]=-1/0,b(t),_(),c[r]=e,b((S+=1)-1))}function k(t){if(!u[t]){u[t]=!0;var e=s[t],r=l[t];s[r]>=0&&(s[r]=e),l[e]>=0&&(l[e]=r),M[e]>=0&&w(M[e],g(e)),M[r]>=0&&w(M[r],g(r))}}for(var T=[],M=new Array(i),h=0;h<i;++h){var A=c[h]=g(h);A<1/0?(M[h]=T.length,T.push(h)):M[h]=-1}for(var S=T.length,h=S>>1;h>=0;--h)x(h);for(;;){var E=_();if(E<0||c[E]>r)break;k(E)}for(var L=[],h=0;h<i;++h)u[h]||(M[h]=L.length,L.push(e[h].slice()));L.length;function C(t,e){if(t[e]<0)return e;var r=e,n=e;do{var a=t[n];if(!u[n]||a<0||a===n)break;if(a=t[n=a],!u[n]||a<0||a===n)break;n=a,r=t[r]}while(r!==n);for(var i=e;i!==n;i=t[i])t[i]=n;return n}var P=[];return t.forEach(function(t){var e=C(s,t[0]),r=C(l,t[1]);if(e>=0&&r>=0&&e!==r){var n=M[e],a=M[r];n!==a&&P.push([n,a])}}),a.unique(a.normalize(P)),{positions:L,edges:P}};var n=t(\"robust-orientation\"),a=t(\"simplicial-complex\")},{\"robust-orientation\":509,\"simplicial-complex\":521}],524:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r,i,o,s;if(e[0][0]<e[1][0])r=e[0],i=e[1];else{if(!(e[0][0]>e[1][0]))return a(e,t);r=e[1],i=e[0]}if(t[0][0]<t[1][0])o=t[0],s=t[1];else{if(!(t[0][0]>t[1][0]))return-a(t,e);o=t[1],s=t[0]}var l=n(r,i,s),c=n(r,i,o);if(l<0){if(c<=0)return l}else if(l>0){if(c>=0)return l}else if(c)return c;if(l=n(s,o,i),c=n(s,o,r),l<0){if(c<=0)return l}else if(l>0){if(c>=0)return l}else if(c)return c;return i[0]-s[0]};var n=t(\"robust-orientation\");function a(t,e){var r,a,i,o;if(e[0][0]<e[1][0])r=e[0],a=e[1];else{if(!(e[0][0]>e[1][0])){var s=Math.min(t[0][1],t[1][1]),l=Math.max(t[0][1],t[1][1]),c=Math.min(e[0][1],e[1][1]),u=Math.max(e[0][1],e[1][1]);return l<c?l-c:s>u?s-u:l-u}r=e[1],a=e[0]}t[0][1]<t[1][1]?(i=t[0],o=t[1]):(i=t[1],o=t[0]);var h=n(a,r,i);return h||((h=n(a,r,o))||o-a)}},{\"robust-orientation\":509}],525:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=t.length,r=2*e,n=new Array(r),i=0;i<e;++i){var l=t[i],c=l[0][0]<l[1][0];n[2*i]=new h(l[0][0],l,c,i),n[2*i+1]=new h(l[1][0],l,!c,i)}n.sort(function(t,e){var r=t.x-e.x;return r||((r=t.create-e.create)||Math.min(t.segment[0][1],t.segment[1][1])-Math.min(e.segment[0][1],e.segment[1][1]))});for(var f=a(o),p=[],d=[],g=[],i=0;i<r;){for(var v=n[i].x,m=[];i<r;){var y=n[i];if(y.x!==v)break;i+=1,y.segment[0][0]===y.x&&y.segment[1][0]===y.x?y.create&&(y.segment[0][1]<y.segment[1][1]?(m.push(new u(y.segment[0][1],y.index,!0,!0)),m.push(new u(y.segment[1][1],y.index,!1,!1))):(m.push(new u(y.segment[1][1],y.index,!0,!1)),m.push(new u(y.segment[0][1],y.index,!1,!0)))):f=y.create?f.insert(y.segment,y.index):f.remove(y.segment)}p.push(f.root),d.push(v),g.push(m)}return new s(p,d,g)};var n=t(\"binary-search-bounds\"),a=t(\"functional-red-black-tree\"),i=t(\"robust-orientation\"),o=t(\"./lib/order-segments\");function s(t,e,r){this.slabs=t,this.coordinates=e,this.horizontal=r}function l(t,e){return t.y-e}function c(t,e){for(var r=null;t;){var n,a,o=t.key;o[0][0]<o[1][0]?(n=o[0],a=o[1]):(n=o[1],a=o[0]);var s=i(n,a,e);if(s<0)t=t.left;else if(s>0)if(e[0]!==o[1][0])r=t,t=t.right;else{if(l=c(t.right,e))return l;t=t.left}else{if(e[0]!==o[1][0])return t;var l;if(l=c(t.right,e))return l;t=t.left}}return r}function u(t,e,r,n){this.y=t,this.index=e,this.start=r,this.closed=n}function h(t,e,r,n){this.x=t,this.segment=e,this.create=r,this.index=n}s.prototype.castUp=function(t){var e=n.le(this.coordinates,t[0]);if(e<0)return-1;this.slabs[e];var r=c(this.slabs[e],t),a=-1;if(r&&(a=r.value),this.coordinates[e]===t[0]){var s=null;if(r&&(s=r.key),e>0){var u=c(this.slabs[e-1],t);u&&(s?o(u.key,s)>0&&(s=u.key,a=u.value):(a=u.value,s=u.key))}var h=this.horizontal[e];if(h.length>0){var f=n.ge(h,t[1],l);if(f<h.length){var p=h[f];if(t[1]===p.y){if(p.closed)return p.index;for(;f<h.length-1&&h[f+1].y===t[1];)if((p=h[f+=1]).closed)return p.index;if(p.y===t[1]&&!p.start){if((f+=1)>=h.length)return a;p=h[f]}}if(p.start)if(s){var d=i(s[0],s[1],[t[0],p.y]);s[0][0]>s[1][0]&&(d=-d),d>0&&(a=p.index)}else a=p.index;else p.y!==t[1]&&(a=p.index)}}}return a}},{\"./lib/order-segments\":524,\"binary-search-bounds\":93,\"functional-red-black-tree\":233,\"robust-orientation\":509}],526:[function(t,e,r){\"use strict\";var n=t(\"robust-dot-product\"),a=t(\"robust-sum\");function i(t,e){var r=a(n(t,e),[e[e.length-1]]);return r[r.length-1]}function o(t,e,r,n){var a=-e/(n-e);a<0?a=0:a>1&&(a=1);for(var i=1-a,o=t.length,s=new Array(o),l=0;l<o;++l)s[l]=a*t[l]+i*r[l];return s}e.exports=function(t,e){for(var r=[],n=[],a=i(t[t.length-1],e),s=t[t.length-1],l=t[0],c=0;c<t.length;++c,s=l){var u=i(l=t[c],e);if(a<0&&u>0||a>0&&u<0){var h=o(s,u,l,a);r.push(h),n.push(h.slice())}u<0?n.push(l.slice()):u>0?r.push(l.slice()):(r.push(l.slice()),n.push(l.slice())),a=u}return{positive:r,negative:n}},e.exports.positive=function(t,e){for(var r=[],n=i(t[t.length-1],e),a=t[t.length-1],s=t[0],l=0;l<t.length;++l,a=s){var c=i(s=t[l],e);(n<0&&c>0||n>0&&c<0)&&r.push(o(a,c,s,n)),c>=0&&r.push(s.slice()),n=c}return r},e.exports.negative=function(t,e){for(var r=[],n=i(t[t.length-1],e),a=t[t.length-1],s=t[0],l=0;l<t.length;++l,a=s){var c=i(s=t[l],e);(n<0&&c>0||n>0&&c<0)&&r.push(o(a,c,s,n)),c<=0&&r.push(s.slice()),n=c}return r}},{\"robust-dot-product\":506,\"robust-sum\":514}],527:[function(t,e,r){!function(){\"use strict\";var t={not_string:/[^s]/,not_bool:/[^t]/,not_type:/[^T]/,not_primitive:/[^v]/,number:/[diefg]/,numeric_arg:/[bcdiefguxX]/,json:/[j]/,not_json:/[^j]/,text:/^[^\\x25]+/,modulo:/^\\x25{2}/,placeholder:/^\\x25(?:([1-9]\\d*)\\$|\\(([^)]+)\\))?(\\+)?(0|'[^$])?(-)?(\\d+)?(?:\\.(\\d+))?([b-gijostTuvxX])/,key:/^([a-z_][a-z_\\d]*)/i,key_access:/^\\.([a-z_][a-z_\\d]*)/i,index_access:/^\\[(\\d+)\\]/,sign:/^[+-]/};function e(r){return function(r,n){var a,i,o,s,l,c,u,h,f,p=1,d=r.length,g=\"\";for(i=0;i<d;i++)if(\"string\"==typeof r[i])g+=r[i];else if(\"object\"==typeof r[i]){if((s=r[i]).keys)for(a=n[p],o=0;o<s.keys.length;o++){if(null==a)throw new Error(e('[sprintf] Cannot access property \"%s\" of undefined value \"%s\"',s.keys[o],s.keys[o-1]));a=a[s.keys[o]]}else a=s.param_no?n[s.param_no]:n[p++];if(t.not_type.test(s.type)&&t.not_primitive.test(s.type)&&a instanceof Function&&(a=a()),t.numeric_arg.test(s.type)&&\"number\"!=typeof a&&isNaN(a))throw new TypeError(e(\"[sprintf] expecting number but found %T\",a));switch(t.number.test(s.type)&&(h=a>=0),s.type){case\"b\":a=parseInt(a,10).toString(2);break;case\"c\":a=String.fromCharCode(parseInt(a,10));break;case\"d\":case\"i\":a=parseInt(a,10);break;case\"j\":a=JSON.stringify(a,null,s.width?parseInt(s.width):0);break;case\"e\":a=s.precision?parseFloat(a).toExponential(s.precision):parseFloat(a).toExponential();break;case\"f\":a=s.precision?parseFloat(a).toFixed(s.precision):parseFloat(a);break;case\"g\":a=s.precision?String(Number(a.toPrecision(s.precision))):parseFloat(a);break;case\"o\":a=(parseInt(a,10)>>>0).toString(8);break;case\"s\":a=String(a),a=s.precision?a.substring(0,s.precision):a;break;case\"t\":a=String(!!a),a=s.precision?a.substring(0,s.precision):a;break;case\"T\":a=Object.prototype.toString.call(a).slice(8,-1).toLowerCase(),a=s.precision?a.substring(0,s.precision):a;break;case\"u\":a=parseInt(a,10)>>>0;break;case\"v\":a=a.valueOf(),a=s.precision?a.substring(0,s.precision):a;break;case\"x\":a=(parseInt(a,10)>>>0).toString(16);break;case\"X\":a=(parseInt(a,10)>>>0).toString(16).toUpperCase()}t.json.test(s.type)?g+=a:(!t.number.test(s.type)||h&&!s.sign?f=\"\":(f=h?\"+\":\"-\",a=a.toString().replace(t.sign,\"\")),c=s.pad_char?\"0\"===s.pad_char?\"0\":s.pad_char.charAt(1):\" \",u=s.width-(f+a).length,l=s.width&&u>0?c.repeat(u):\"\",g+=s.align?f+a+l:\"0\"===c?f+l+a:l+f+a)}return g}(function(e){if(a[e])return a[e];var r,n=e,i=[],o=0;for(;n;){if(null!==(r=t.text.exec(n)))i.push(r[0]);else if(null!==(r=t.modulo.exec(n)))i.push(\"%\");else{if(null===(r=t.placeholder.exec(n)))throw new SyntaxError(\"[sprintf] unexpected placeholder\");if(r[2]){o|=1;var s=[],l=r[2],c=[];if(null===(c=t.key.exec(l)))throw new SyntaxError(\"[sprintf] failed to parse named argument key\");for(s.push(c[1]);\"\"!==(l=l.substring(c[0].length));)if(null!==(c=t.key_access.exec(l)))s.push(c[1]);else{if(null===(c=t.index_access.exec(l)))throw new SyntaxError(\"[sprintf] failed to parse named argument key\");s.push(c[1])}r[2]=s}else o|=2;if(3===o)throw new Error(\"[sprintf] mixing positional and named placeholders is not (yet) supported\");i.push({placeholder:r[0],param_no:r[1],keys:r[2],sign:r[3],pad_char:r[4],align:r[5],width:r[6],precision:r[7],type:r[8]})}n=n.substring(r[0].length)}return a[e]=i}(r),arguments)}function n(t,r){return e.apply(null,[t].concat(r||[]))}var a=Object.create(null);\"undefined\"!=typeof r&&(r.sprintf=e,r.vsprintf=n),\"undefined\"!=typeof window&&(window.sprintf=e,window.vsprintf=n)}()},{}],528:[function(t,e,r){\"use strict\";var n=t(\"parenthesis\");e.exports=function(t,e,r){if(null==t)throw Error(\"First argument should be a string\");if(null==e)throw Error(\"Separator should be a string or a RegExp\");r?(\"string\"==typeof r||Array.isArray(r))&&(r={ignore:r}):r={},null==r.escape&&(r.escape=!0),null==r.ignore?r.ignore=[\"[]\",\"()\",\"{}\",\"<>\",'\"\"',\"''\",\"``\",\"\\u201c\\u201d\",\"\\xab\\xbb\"]:(\"string\"==typeof r.ignore&&(r.ignore=[r.ignore]),r.ignore=r.ignore.map(function(t){return 1===t.length&&(t+=t),t}));var a=n.parse(t,{flat:!0,brackets:r.ignore}),i=a[0].split(e);if(r.escape){for(var o=[],s=0;s<i.length;s++){var l=i[s],c=i[s+1];\"\\\\\"===l[l.length-1]&&\"\\\\\"!==l[l.length-2]?(o.push(l+e+c),s++):o.push(l)}i=o}for(s=0;s<i.length;s++)a[0]=i[s],i[s]=n.stringify(a,{flat:!0});return i}},{parenthesis:460}],529:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=t.length,r=new Array(e),n=new Array(e),a=new Array(e),i=new Array(e),o=new Array(e),s=new Array(e),l=0;l<e;++l)r[l]=-1,n[l]=0,a[l]=!1,i[l]=0,o[l]=-1,s[l]=[];var c,u=0,h=[],f=[];function p(e){var l=[e],c=[e];for(r[e]=n[e]=u,a[e]=!0,u+=1;c.length>0;){e=c[c.length-1];var p=t[e];if(i[e]<p.length){for(var d=i[e];d<p.length;++d){var g=p[d];if(r[g]<0){r[g]=n[g]=u,a[g]=!0,u+=1,l.push(g),c.push(g);break}a[g]&&(n[e]=0|Math.min(n[e],n[g])),o[g]>=0&&s[e].push(o[g])}i[e]=d}else{if(n[e]===r[e]){for(var v=[],m=[],y=0,d=l.length-1;d>=0;--d){var x=l[d];if(a[x]=!1,v.push(x),m.push(s[x]),y+=s[x].length,o[x]=h.length,x===e){l.length=d;break}}h.push(v);for(var b=new Array(y),d=0;d<m.length;d++)for(var _=0;_<m[d].length;_++)b[--y]=m[d][_];f.push(b)}c.pop()}}}for(var l=0;l<e;++l)r[l]<0&&p(l);for(var l=0;l<f.length;l++){var d=f[l];if(0!==d.length){d.sort(function(t,e){return t-e}),c=[d[0]];for(var g=1;g<d.length;g++)d[g]!==d[g-1]&&c.push(d[g]);f[l]=c}}return{components:h,adjacencyList:f}}},{}],530:[function(t,e,r){\"use strict\";e.exports=function(t,e){if(t.dimension<=0)return{positions:[],cells:[]};if(1===t.dimension)return function(t,e){for(var r=i(t,e),n=r.length,a=new Array(n),o=new Array(n),s=0;s<n;++s)a[s]=[r[s]],o[s]=[s];return{positions:a,cells:o}}(t,e);var r=t.order.join()+\"-\"+t.dtype,s=o[r],e=+e||0;s||(s=o[r]=function(t,e){var r=t.length,i=[\"'use strict';\"],o=\"surfaceNets\"+t.join(\"_\")+\"d\"+e;i.push(\"var contour=genContour({\",\"order:[\",t.join(),\"],\",\"scalarArguments: 3,\",\"phase:function phaseFunc(p,a,b,c) { return (p > c)|0 },\"),\"generic\"===e&&i.push(\"getters:[0],\");for(var s=[],l=[],c=0;c<r;++c)s.push(\"d\"+c),l.push(\"d\"+c);for(var c=0;c<1<<r;++c)s.push(\"v\"+c),l.push(\"v\"+c);for(var c=0;c<1<<r;++c)s.push(\"p\"+c),l.push(\"p\"+c);s.push(\"a\",\"b\",\"c\"),l.push(\"a\",\"c\"),i.push(\"vertex:function vertexFunc(\",s.join(),\"){\");for(var u=[],c=0;c<1<<r;++c)u.push(\"(p\"+c+\"<<\"+c+\")\");i.push(\"var m=(\",u.join(\"+\"),\")|0;if(m===0||m===\",(1<<(1<<r))-1,\"){return}\");var h=[],f=[];1<<(1<<r)<=128?(i.push(\"switch(m){\"),f=i):i.push(\"switch(m>>>7){\");for(var c=0;c<1<<(1<<r);++c){if(1<<(1<<r)>128&&c%128==0){h.length>0&&f.push(\"}}\");var p=\"vExtra\"+h.length;i.push(\"case \",c>>>7,\":\",p,\"(m&0x7f,\",l.join(),\");break;\"),f=[\"function \",p,\"(m,\",l.join(),\"){switch(m){\"],h.push(f)}f.push(\"case \",127&c,\":\");for(var d=new Array(r),g=new Array(r),v=new Array(r),m=new Array(r),y=0,x=0;x<r;++x)d[x]=[],g[x]=[],v[x]=0,m[x]=0;for(var x=0;x<1<<r;++x)for(var b=0;b<r;++b){var _=x^1<<b;if(!(_>x)&&!(c&1<<_)!=!(c&1<<x)){var w=1;c&1<<_?g[b].push(\"v\"+_+\"-v\"+x):(g[b].push(\"v\"+x+\"-v\"+_),w=-w),w<0?(d[b].push(\"-v\"+x+\"-v\"+_),v[b]+=2):(d[b].push(\"v\"+x+\"+v\"+_),v[b]-=2),y+=1;for(var k=0;k<r;++k)k!==b&&(_&1<<k?m[k]+=1:m[k]-=1)}}for(var T=[],b=0;b<r;++b)if(0===d[b].length)T.push(\"d\"+b+\"-0.5\");else{var M=\"\";v[b]<0?M=v[b]+\"*c\":v[b]>0&&(M=\"+\"+v[b]+\"*c\");var A=d[b].length/y*.5,S=.5+m[b]/y*.5;T.push(\"d\"+b+\"-\"+S+\"-\"+A+\"*(\"+d[b].join(\"+\")+M+\")/(\"+g[b].join(\"+\")+\")\")}f.push(\"a.push([\",T.join(),\"]);\",\"break;\")}i.push(\"}},\"),h.length>0&&f.push(\"}}\");for(var E=[],c=0;c<1<<r-1;++c)E.push(\"v\"+c);E.push(\"c0\",\"c1\",\"p0\",\"p1\",\"a\",\"b\",\"c\"),i.push(\"cell:function cellFunc(\",E.join(),\"){\");var L=a(r-1);i.push(\"if(p0){b.push(\",L.map(function(t){return\"[\"+t.map(function(t){return\"v\"+t})+\"]\"}).join(),\")}else{b.push(\",L.map(function(t){var e=t.slice();return e.reverse(),\"[\"+e.map(function(t){return\"v\"+t})+\"]\"}).join(),\")}}});function \",o,\"(array,level){var verts=[],cells=[];contour(array,verts,cells,level);return {positions:verts,cells:cells};} return \",o,\";\");for(var c=0;c<h.length;++c)i.push(h[c].join(\"\"));return new Function(\"genContour\",i.join(\"\"))(n)}(t.order,t.dtype));return s(t,e)};var n=t(\"ndarray-extract-contour\"),a=t(\"triangulate-hypercube\"),i=t(\"zero-crossings\");var o={}},{\"ndarray-extract-contour\":441,\"triangulate-hypercube\":540,\"zero-crossings\":573}],531:[function(t,e,r){\"use strict\";Object.defineProperty(r,\"__esModule\",{value:!0});var n=function(){return function(t,e){if(Array.isArray(t))return t;if(Symbol.iterator in Object(t))return function(t,e){var r=[],n=!0,a=!1,i=void 0;try{for(var o,s=t[Symbol.iterator]();!(n=(o=s.next()).done)&&(r.push(o.value),!e||r.length!==e);n=!0);}catch(t){a=!0,i=t}finally{try{!n&&s.return&&s.return()}finally{if(a)throw i}}return r}(t,e);throw new TypeError(\"Invalid attempt to destructure non-iterable instance\")}}(),a=2*Math.PI,i=function(t,e,r,n,a,i,o){var s=t.x,l=t.y;return{x:n*(s*=e)-a*(l*=r)+i,y:a*s+n*l+o}},o=function(t,e){var r=.551915024494*(e<0?-1:1),n=Math.cos(t),a=Math.sin(t),i=Math.cos(t+e),o=Math.sin(t+e);return[{x:n-a*r,y:a+n*r},{x:i+o*r,y:o-i*r},{x:i,y:o}]},s=function(t,e,r,n){var a=t*n-e*r<0?-1:1,i=(t*r+e*n)/(Math.sqrt(t*t+e*e)*Math.sqrt(t*t+e*e));return i>1&&(i=1),i<-1&&(i=-1),a*Math.acos(i)};r.default=function(t){var e=t.px,r=t.py,l=t.cx,c=t.cy,u=t.rx,h=t.ry,f=t.xAxisRotation,p=void 0===f?0:f,d=t.largeArcFlag,g=void 0===d?0:d,v=t.sweepFlag,m=void 0===v?0:v,y=[];if(0===u||0===h)return[];var x=Math.sin(p*a/360),b=Math.cos(p*a/360),_=b*(e-l)/2+x*(r-c)/2,w=-x*(e-l)/2+b*(r-c)/2;if(0===_&&0===w)return[];u=Math.abs(u),h=Math.abs(h);var k=Math.pow(_,2)/Math.pow(u,2)+Math.pow(w,2)/Math.pow(h,2);k>1&&(u*=Math.sqrt(k),h*=Math.sqrt(k));var T=function(t,e,r,n,i,o,l,c,u,h,f,p){var d=Math.pow(i,2),g=Math.pow(o,2),v=Math.pow(f,2),m=Math.pow(p,2),y=d*g-d*m-g*v;y<0&&(y=0),y/=d*m+g*v;var x=(y=Math.sqrt(y)*(l===c?-1:1))*i/o*p,b=y*-o/i*f,_=h*x-u*b+(t+r)/2,w=u*x+h*b+(e+n)/2,k=(f-x)/i,T=(p-b)/o,M=(-f-x)/i,A=(-p-b)/o,S=s(1,0,k,T),E=s(k,T,M,A);return 0===c&&E>0&&(E-=a),1===c&&E<0&&(E+=a),[_,w,S,E]}(e,r,l,c,u,h,g,m,x,b,_,w),M=n(T,4),A=M[0],S=M[1],E=M[2],L=M[3],C=Math.abs(L)/(a/4);Math.abs(1-C)<1e-7&&(C=1);var P=Math.max(Math.ceil(C),1);L/=P;for(var O=0;O<P;O++)y.push(o(E,L)),E+=L;return y.map(function(t){var e=i(t[0],u,h,b,x,A,S),r=e.x,n=e.y,a=i(t[1],u,h,b,x,A,S),o=a.x,s=a.y,l=i(t[2],u,h,b,x,A,S);return{x1:r,y1:n,x2:o,y2:s,x:l.x,y:l.y}})},e.exports=r.default},{}],532:[function(t,e,r){\"use strict\";var n=t(\"parse-svg-path\"),a=t(\"abs-svg-path\"),i=t(\"normalize-svg-path\"),o=t(\"is-svg-path\"),s=t(\"assert\");e.exports=function(t){Array.isArray(t)&&1===t.length&&\"string\"==typeof t[0]&&(t=t[0]);\"string\"==typeof t&&(s(o(t),\"String is not an SVG path.\"),t=n(t));if(s(Array.isArray(t),\"Argument should be a string or an array of path segments.\"),t=a(t),!(t=i(t)).length)return[0,0,0,0];for(var e=[1/0,1/0,-1/0,-1/0],r=0,l=t.length;r<l;r++)for(var c=t[r].slice(1),u=0;u<c.length;u+=2)c[u+0]<e[0]&&(e[0]=c[u+0]),c[u+1]<e[1]&&(e[1]=c[u+1]),c[u+0]>e[2]&&(e[2]=c[u+0]),c[u+1]>e[3]&&(e[3]=c[u+1]);return e}},{\"abs-svg-path\":63,assert:70,\"is-svg-path\":426,\"normalize-svg-path\":533,\"parse-svg-path\":462}],533:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e,r=[],o=0,s=0,l=0,c=0,u=null,h=null,f=0,p=0,d=0,g=t.length;d<g;d++){var v=t[d],m=v[0];switch(m){case\"M\":l=v[1],c=v[2];break;case\"A\":var y=n({px:f,py:p,cx:v[6],cy:v[7],rx:v[1],ry:v[2],xAxisRotation:v[3],largeArcFlag:v[4],sweepFlag:v[5]});if(!y.length)continue;for(var x,b=0;b<y.length;b++)x=y[b],v=[\"C\",x.x1,x.y1,x.x2,x.y2,x.x,x.y],b<y.length-1&&r.push(v);break;case\"S\":var _=f,w=p;\"C\"!=e&&\"S\"!=e||(_+=_-o,w+=w-s),v=[\"C\",_,w,v[1],v[2],v[3],v[4]];break;case\"T\":\"Q\"==e||\"T\"==e?(u=2*f-u,h=2*p-h):(u=f,h=p),v=i(f,p,u,h,v[1],v[2]);break;case\"Q\":u=v[1],h=v[2],v=i(f,p,v[1],v[2],v[3],v[4]);break;case\"L\":v=a(f,p,v[1],v[2]);break;case\"H\":v=a(f,p,v[1],p);break;case\"V\":v=a(f,p,f,v[1]);break;case\"Z\":v=a(f,p,l,c)}e=m,f=v[v.length-2],p=v[v.length-1],v.length>4?(o=v[v.length-4],s=v[v.length-3]):(o=f,s=p),r.push(v)}return r};var n=t(\"svg-arc-to-cubic-bezier\");function a(t,e,r,n){return[\"C\",t,e,r,n,r,n]}function i(t,e,r,n,a,i){return[\"C\",t/3+2/3*r,e/3+2/3*n,a/3+2/3*r,i/3+2/3*n,a,i]}},{\"svg-arc-to-cubic-bezier\":531}],534:[function(t,e,r){\"use strict\";var n,a=t(\"svg-path-bounds\"),i=t(\"parse-svg-path\"),o=t(\"draw-svg-path\"),s=t(\"is-svg-path\"),l=t(\"bitmap-sdf\"),c=document.createElement(\"canvas\"),u=c.getContext(\"2d\");e.exports=function(t,e){if(!s(t))throw Error(\"Argument should be valid svg path string\");e||(e={});var r,h;e.shape?(r=e.shape[0],h=e.shape[1]):(r=c.width=e.w||e.width||200,h=c.height=e.h||e.height||200);var f=Math.min(r,h),p=e.stroke||0,d=e.viewbox||e.viewBox||a(t),g=[r/(d[2]-d[0]),h/(d[3]-d[1])],v=Math.min(g[0]||0,g[1]||0)/2;u.fillStyle=\"black\",u.fillRect(0,0,r,h),u.fillStyle=\"white\",p&&(\"number\"!=typeof p&&(p=1),u.strokeStyle=p>0?\"white\":\"black\",u.lineWidth=Math.abs(p));if(u.translate(.5*r,.5*h),u.scale(v,v),function(){if(null!=n)return n;var t=document.createElement(\"canvas\").getContext(\"2d\");if(t.canvas.width=t.canvas.height=1,!window.Path2D)return n=!1;var e=new Path2D(\"M0,0h1v1h-1v-1Z\");t.fillStyle=\"black\",t.fill(e);var r=t.getImageData(0,0,1,1);return n=r&&r.data&&255===r.data[3]}()){var m=new Path2D(t);u.fill(m),p&&u.stroke(m)}else{var y=i(t);o(u,y),u.fill(),p&&u.stroke()}return u.setTransform(1,0,0,1,0,0),l(u,{cutoff:null!=e.cutoff?e.cutoff:.5,radius:null!=e.radius?e.radius:.5*f})}},{\"bitmap-sdf\":95,\"draw-svg-path\":170,\"is-svg-path\":426,\"parse-svg-path\":462,\"svg-path-bounds\":532}],535:[function(t,e,r){(function(r){\"use strict\";e.exports=function t(e,r,a){var a=a||{};var o=i[e];o||(o=i[e]={\" \":{data:new Float32Array(0),shape:.2}});var s=o[r];if(!s)if(r.length<=1||!/\\d/.test(r))s=o[r]=function(t){for(var e=t.cells,r=t.positions,n=new Float32Array(6*e.length),a=0,i=0,o=0;o<e.length;++o)for(var s=e[o],l=0;l<3;++l){var c=r[s[l]];n[a++]=c[0],n[a++]=c[1]+1.4,i=Math.max(c[0],i)}return{data:n,shape:i}}(n(r,{triangles:!0,font:e,textAlign:a.textAlign||\"left\",textBaseline:\"alphabetic\",styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0}}));else{for(var l=r.split(/(\\d|\\s)/),c=new Array(l.length),u=0,h=0,f=0;f<l.length;++f)c[f]=t(e,l[f]),u+=c[f].data.length,h+=c[f].shape,f>0&&(h+=.02);for(var p=new Float32Array(u),d=0,g=-.5*h,f=0;f<c.length;++f){for(var v=c[f].data,m=0;m<v.length;m+=2)p[d++]=v[m]+g,p[d++]=v[m+1];g+=c[f].shape+.02}s=o[r]={data:p,shape:h}}return s};var n=t(\"vectorize-text\"),a=window||r.global||{},i=a.__TEXT_CACHE||{};a.__TEXT_CACHE={}}).call(this,t(\"_process\"))},{_process:484,\"vectorize-text\":549}],536:[function(t,e,r){!function(t){var r=/^\\s+/,n=/\\s+$/,a=0,i=t.round,o=t.min,s=t.max,l=t.random;function c(e,l){if(l=l||{},(e=e||\"\")instanceof c)return e;if(!(this instanceof c))return new c(e,l);var u=function(e){var a={r:0,g:0,b:0},i=1,l=null,c=null,u=null,h=!1,f=!1;\"string\"==typeof e&&(e=function(t){t=t.replace(r,\"\").replace(n,\"\").toLowerCase();var e,a=!1;if(S[t])t=S[t],a=!0;else if(\"transparent\"==t)return{r:0,g:0,b:0,a:0,format:\"name\"};if(e=j.rgb.exec(t))return{r:e[1],g:e[2],b:e[3]};if(e=j.rgba.exec(t))return{r:e[1],g:e[2],b:e[3],a:e[4]};if(e=j.hsl.exec(t))return{h:e[1],s:e[2],l:e[3]};if(e=j.hsla.exec(t))return{h:e[1],s:e[2],l:e[3],a:e[4]};if(e=j.hsv.exec(t))return{h:e[1],s:e[2],v:e[3]};if(e=j.hsva.exec(t))return{h:e[1],s:e[2],v:e[3],a:e[4]};if(e=j.hex8.exec(t))return{r:O(e[1]),g:O(e[2]),b:O(e[3]),a:R(e[4]),format:a?\"name\":\"hex8\"};if(e=j.hex6.exec(t))return{r:O(e[1]),g:O(e[2]),b:O(e[3]),format:a?\"name\":\"hex\"};if(e=j.hex4.exec(t))return{r:O(e[1]+\"\"+e[1]),g:O(e[2]+\"\"+e[2]),b:O(e[3]+\"\"+e[3]),a:R(e[4]+\"\"+e[4]),format:a?\"name\":\"hex8\"};if(e=j.hex3.exec(t))return{r:O(e[1]+\"\"+e[1]),g:O(e[2]+\"\"+e[2]),b:O(e[3]+\"\"+e[3]),format:a?\"name\":\"hex\"};return!1}(e));\"object\"==typeof e&&(V(e.r)&&V(e.g)&&V(e.b)?(p=e.r,d=e.g,g=e.b,a={r:255*C(p,255),g:255*C(d,255),b:255*C(g,255)},h=!0,f=\"%\"===String(e.r).substr(-1)?\"prgb\":\"rgb\"):V(e.h)&&V(e.s)&&V(e.v)?(l=I(e.s),c=I(e.v),a=function(e,r,n){e=6*C(e,360),r=C(r,100),n=C(n,100);var a=t.floor(e),i=e-a,o=n*(1-r),s=n*(1-i*r),l=n*(1-(1-i)*r),c=a%6;return{r:255*[n,s,o,o,l,n][c],g:255*[l,n,n,s,o,o][c],b:255*[o,o,l,n,n,s][c]}}(e.h,l,c),h=!0,f=\"hsv\"):V(e.h)&&V(e.s)&&V(e.l)&&(l=I(e.s),u=I(e.l),a=function(t,e,r){var n,a,i;function o(t,e,r){return r<0&&(r+=1),r>1&&(r-=1),r<1/6?t+6*(e-t)*r:r<.5?e:r<2/3?t+(e-t)*(2/3-r)*6:t}if(t=C(t,360),e=C(e,100),r=C(r,100),0===e)n=a=i=r;else{var s=r<.5?r*(1+e):r+e-r*e,l=2*r-s;n=o(l,s,t+1/3),a=o(l,s,t),i=o(l,s,t-1/3)}return{r:255*n,g:255*a,b:255*i}}(e.h,l,u),h=!0,f=\"hsl\"),e.hasOwnProperty(\"a\")&&(i=e.a));var p,d,g;return i=L(i),{ok:h,format:e.format||f,r:o(255,s(a.r,0)),g:o(255,s(a.g,0)),b:o(255,s(a.b,0)),a:i}}(e);this._originalInput=e,this._r=u.r,this._g=u.g,this._b=u.b,this._a=u.a,this._roundA=i(100*this._a)/100,this._format=l.format||u.format,this._gradientType=l.gradientType,this._r<1&&(this._r=i(this._r)),this._g<1&&(this._g=i(this._g)),this._b<1&&(this._b=i(this._b)),this._ok=u.ok,this._tc_id=a++}function u(t,e,r){t=C(t,255),e=C(e,255),r=C(r,255);var n,a,i=s(t,e,r),l=o(t,e,r),c=(i+l)/2;if(i==l)n=a=0;else{var u=i-l;switch(a=c>.5?u/(2-i-l):u/(i+l),i){case t:n=(e-r)/u+(e<r?6:0);break;case e:n=(r-t)/u+2;break;case r:n=(t-e)/u+4}n/=6}return{h:n,s:a,l:c}}function h(t,e,r){t=C(t,255),e=C(e,255),r=C(r,255);var n,a,i=s(t,e,r),l=o(t,e,r),c=i,u=i-l;if(a=0===i?0:u/i,i==l)n=0;else{switch(i){case t:n=(e-r)/u+(e<r?6:0);break;case e:n=(r-t)/u+2;break;case r:n=(t-e)/u+4}n/=6}return{h:n,s:a,v:c}}function f(t,e,r,n){var a=[z(i(t).toString(16)),z(i(e).toString(16)),z(i(r).toString(16))];return n&&a[0].charAt(0)==a[0].charAt(1)&&a[1].charAt(0)==a[1].charAt(1)&&a[2].charAt(0)==a[2].charAt(1)?a[0].charAt(0)+a[1].charAt(0)+a[2].charAt(0):a.join(\"\")}function p(t,e,r,n){return[z(D(n)),z(i(t).toString(16)),z(i(e).toString(16)),z(i(r).toString(16))].join(\"\")}function d(t,e){e=0===e?0:e||10;var r=c(t).toHsl();return r.s-=e/100,r.s=P(r.s),c(r)}function g(t,e){e=0===e?0:e||10;var r=c(t).toHsl();return r.s+=e/100,r.s=P(r.s),c(r)}function v(t){return c(t).desaturate(100)}function m(t,e){e=0===e?0:e||10;var r=c(t).toHsl();return r.l+=e/100,r.l=P(r.l),c(r)}function y(t,e){e=0===e?0:e||10;var r=c(t).toRgb();return r.r=s(0,o(255,r.r-i(-e/100*255))),r.g=s(0,o(255,r.g-i(-e/100*255))),r.b=s(0,o(255,r.b-i(-e/100*255))),c(r)}function x(t,e){e=0===e?0:e||10;var r=c(t).toHsl();return r.l-=e/100,r.l=P(r.l),c(r)}function b(t,e){var r=c(t).toHsl(),n=(r.h+e)%360;return r.h=n<0?360+n:n,c(r)}function _(t){var e=c(t).toHsl();return e.h=(e.h+180)%360,c(e)}function w(t){var e=c(t).toHsl(),r=e.h;return[c(t),c({h:(r+120)%360,s:e.s,l:e.l}),c({h:(r+240)%360,s:e.s,l:e.l})]}function k(t){var e=c(t).toHsl(),r=e.h;return[c(t),c({h:(r+90)%360,s:e.s,l:e.l}),c({h:(r+180)%360,s:e.s,l:e.l}),c({h:(r+270)%360,s:e.s,l:e.l})]}function T(t){var e=c(t).toHsl(),r=e.h;return[c(t),c({h:(r+72)%360,s:e.s,l:e.l}),c({h:(r+216)%360,s:e.s,l:e.l})]}function M(t,e,r){e=e||6,r=r||30;var n=c(t).toHsl(),a=360/r,i=[c(t)];for(n.h=(n.h-(a*e>>1)+720)%360;--e;)n.h=(n.h+a)%360,i.push(c(n));return i}function A(t,e){e=e||6;for(var r=c(t).toHsv(),n=r.h,a=r.s,i=r.v,o=[],s=1/e;e--;)o.push(c({h:n,s:a,v:i})),i=(i+s)%1;return o}c.prototype={isDark:function(){return this.getBrightness()<128},isLight:function(){return!this.isDark()},isValid:function(){return this._ok},getOriginalInput:function(){return this._originalInput},getFormat:function(){return this._format},getAlpha:function(){return this._a},getBrightness:function(){var t=this.toRgb();return(299*t.r+587*t.g+114*t.b)/1e3},getLuminance:function(){var e,r,n,a=this.toRgb();return e=a.r/255,r=a.g/255,n=a.b/255,.2126*(e<=.03928?e/12.92:t.pow((e+.055)/1.055,2.4))+.7152*(r<=.03928?r/12.92:t.pow((r+.055)/1.055,2.4))+.0722*(n<=.03928?n/12.92:t.pow((n+.055)/1.055,2.4))},setAlpha:function(t){return this._a=L(t),this._roundA=i(100*this._a)/100,this},toHsv:function(){var t=h(this._r,this._g,this._b);return{h:360*t.h,s:t.s,v:t.v,a:this._a}},toHsvString:function(){var t=h(this._r,this._g,this._b),e=i(360*t.h),r=i(100*t.s),n=i(100*t.v);return 1==this._a?\"hsv(\"+e+\", \"+r+\"%, \"+n+\"%)\":\"hsva(\"+e+\", \"+r+\"%, \"+n+\"%, \"+this._roundA+\")\"},toHsl:function(){var t=u(this._r,this._g,this._b);return{h:360*t.h,s:t.s,l:t.l,a:this._a}},toHslString:function(){var t=u(this._r,this._g,this._b),e=i(360*t.h),r=i(100*t.s),n=i(100*t.l);return 1==this._a?\"hsl(\"+e+\", \"+r+\"%, \"+n+\"%)\":\"hsla(\"+e+\", \"+r+\"%, \"+n+\"%, \"+this._roundA+\")\"},toHex:function(t){return f(this._r,this._g,this._b,t)},toHexString:function(t){return\"#\"+this.toHex(t)},toHex8:function(t){return function(t,e,r,n,a){var o=[z(i(t).toString(16)),z(i(e).toString(16)),z(i(r).toString(16)),z(D(n))];if(a&&o[0].charAt(0)==o[0].charAt(1)&&o[1].charAt(0)==o[1].charAt(1)&&o[2].charAt(0)==o[2].charAt(1)&&o[3].charAt(0)==o[3].charAt(1))return o[0].charAt(0)+o[1].charAt(0)+o[2].charAt(0)+o[3].charAt(0);return o.join(\"\")}(this._r,this._g,this._b,this._a,t)},toHex8String:function(t){return\"#\"+this.toHex8(t)},toRgb:function(){return{r:i(this._r),g:i(this._g),b:i(this._b),a:this._a}},toRgbString:function(){return 1==this._a?\"rgb(\"+i(this._r)+\", \"+i(this._g)+\", \"+i(this._b)+\")\":\"rgba(\"+i(this._r)+\", \"+i(this._g)+\", \"+i(this._b)+\", \"+this._roundA+\")\"},toPercentageRgb:function(){return{r:i(100*C(this._r,255))+\"%\",g:i(100*C(this._g,255))+\"%\",b:i(100*C(this._b,255))+\"%\",a:this._a}},toPercentageRgbString:function(){return 1==this._a?\"rgb(\"+i(100*C(this._r,255))+\"%, \"+i(100*C(this._g,255))+\"%, \"+i(100*C(this._b,255))+\"%)\":\"rgba(\"+i(100*C(this._r,255))+\"%, \"+i(100*C(this._g,255))+\"%, \"+i(100*C(this._b,255))+\"%, \"+this._roundA+\")\"},toName:function(){return 0===this._a?\"transparent\":!(this._a<1)&&(E[f(this._r,this._g,this._b,!0)]||!1)},toFilter:function(t){var e=\"#\"+p(this._r,this._g,this._b,this._a),r=e,n=this._gradientType?\"GradientType = 1, \":\"\";if(t){var a=c(t);r=\"#\"+p(a._r,a._g,a._b,a._a)}return\"progid:DXImageTransform.Microsoft.gradient(\"+n+\"startColorstr=\"+e+\",endColorstr=\"+r+\")\"},toString:function(t){var e=!!t;t=t||this._format;var r=!1,n=this._a<1&&this._a>=0;return e||!n||\"hex\"!==t&&\"hex6\"!==t&&\"hex3\"!==t&&\"hex4\"!==t&&\"hex8\"!==t&&\"name\"!==t?(\"rgb\"===t&&(r=this.toRgbString()),\"prgb\"===t&&(r=this.toPercentageRgbString()),\"hex\"!==t&&\"hex6\"!==t||(r=this.toHexString()),\"hex3\"===t&&(r=this.toHexString(!0)),\"hex4\"===t&&(r=this.toHex8String(!0)),\"hex8\"===t&&(r=this.toHex8String()),\"name\"===t&&(r=this.toName()),\"hsl\"===t&&(r=this.toHslString()),\"hsv\"===t&&(r=this.toHsvString()),r||this.toHexString()):\"name\"===t&&0===this._a?this.toName():this.toRgbString()},clone:function(){return c(this.toString())},_applyModification:function(t,e){var r=t.apply(null,[this].concat([].slice.call(e)));return this._r=r._r,this._g=r._g,this._b=r._b,this.setAlpha(r._a),this},lighten:function(){return this._applyModification(m,arguments)},brighten:function(){return this._applyModification(y,arguments)},darken:function(){return this._applyModification(x,arguments)},desaturate:function(){return this._applyModification(d,arguments)},saturate:function(){return this._applyModification(g,arguments)},greyscale:function(){return this._applyModification(v,arguments)},spin:function(){return this._applyModification(b,arguments)},_applyCombination:function(t,e){return t.apply(null,[this].concat([].slice.call(e)))},analogous:function(){return this._applyCombination(M,arguments)},complement:function(){return this._applyCombination(_,arguments)},monochromatic:function(){return this._applyCombination(A,arguments)},splitcomplement:function(){return this._applyCombination(T,arguments)},triad:function(){return this._applyCombination(w,arguments)},tetrad:function(){return this._applyCombination(k,arguments)}},c.fromRatio=function(t,e){if(\"object\"==typeof t){var r={};for(var n in t)t.hasOwnProperty(n)&&(r[n]=\"a\"===n?t[n]:I(t[n]));t=r}return c(t,e)},c.equals=function(t,e){return!(!t||!e)&&c(t).toRgbString()==c(e).toRgbString()},c.random=function(){return c.fromRatio({r:l(),g:l(),b:l()})},c.mix=function(t,e,r){r=0===r?0:r||50;var n=c(t).toRgb(),a=c(e).toRgb(),i=r/100;return c({r:(a.r-n.r)*i+n.r,g:(a.g-n.g)*i+n.g,b:(a.b-n.b)*i+n.b,a:(a.a-n.a)*i+n.a})},c.readability=function(e,r){var n=c(e),a=c(r);return(t.max(n.getLuminance(),a.getLuminance())+.05)/(t.min(n.getLuminance(),a.getLuminance())+.05)},c.isReadable=function(t,e,r){var n,a,i=c.readability(t,e);switch(a=!1,(n=function(t){var e,r;e=((t=t||{level:\"AA\",size:\"small\"}).level||\"AA\").toUpperCase(),r=(t.size||\"small\").toLowerCase(),\"AA\"!==e&&\"AAA\"!==e&&(e=\"AA\");\"small\"!==r&&\"large\"!==r&&(r=\"small\");return{level:e,size:r}}(r)).level+n.size){case\"AAsmall\":case\"AAAlarge\":a=i>=4.5;break;case\"AAlarge\":a=i>=3;break;case\"AAAsmall\":a=i>=7}return a},c.mostReadable=function(t,e,r){var n,a,i,o,s=null,l=0;a=(r=r||{}).includeFallbackColors,i=r.level,o=r.size;for(var u=0;u<e.length;u++)(n=c.readability(t,e[u]))>l&&(l=n,s=c(e[u]));return c.isReadable(t,s,{level:i,size:o})||!a?s:(r.includeFallbackColors=!1,c.mostReadable(t,[\"#fff\",\"#000\"],r))};var S=c.names={aliceblue:\"f0f8ff\",antiquewhite:\"faebd7\",aqua:\"0ff\",aquamarine:\"7fffd4\",azure:\"f0ffff\",beige:\"f5f5dc\",bisque:\"ffe4c4\",black:\"000\",blanchedalmond:\"ffebcd\",blue:\"00f\",blueviolet:\"8a2be2\",brown:\"a52a2a\",burlywood:\"deb887\",burntsienna:\"ea7e5d\",cadetblue:\"5f9ea0\",chartreuse:\"7fff00\",chocolate:\"d2691e\",coral:\"ff7f50\",cornflowerblue:\"6495ed\",cornsilk:\"fff8dc\",crimson:\"dc143c\",cyan:\"0ff\",darkblue:\"00008b\",darkcyan:\"008b8b\",darkgoldenrod:\"b8860b\",darkgray:\"a9a9a9\",darkgreen:\"006400\",darkgrey:\"a9a9a9\",darkkhaki:\"bdb76b\",darkmagenta:\"8b008b\",darkolivegreen:\"556b2f\",darkorange:\"ff8c00\",darkorchid:\"9932cc\",darkred:\"8b0000\",darksalmon:\"e9967a\",darkseagreen:\"8fbc8f\",darkslateblue:\"483d8b\",darkslategray:\"2f4f4f\",darkslategrey:\"2f4f4f\",darkturquoise:\"00ced1\",darkviolet:\"9400d3\",deeppink:\"ff1493\",deepskyblue:\"00bfff\",dimgray:\"696969\",dimgrey:\"696969\",dodgerblue:\"1e90ff\",firebrick:\"b22222\",floralwhite:\"fffaf0\",forestgreen:\"228b22\",fuchsia:\"f0f\",gainsboro:\"dcdcdc\",ghostwhite:\"f8f8ff\",gold:\"ffd700\",goldenrod:\"daa520\",gray:\"808080\",green:\"008000\",greenyellow:\"adff2f\",grey:\"808080\",honeydew:\"f0fff0\",hotpink:\"ff69b4\",indianred:\"cd5c5c\",indigo:\"4b0082\",ivory:\"fffff0\",khaki:\"f0e68c\",lavender:\"e6e6fa\",lavenderblush:\"fff0f5\",lawngreen:\"7cfc00\",lemonchiffon:\"fffacd\",lightblue:\"add8e6\",lightcoral:\"f08080\",lightcyan:\"e0ffff\",lightgoldenrodyellow:\"fafad2\",lightgray:\"d3d3d3\",lightgreen:\"90ee90\",lightgrey:\"d3d3d3\",lightpink:\"ffb6c1\",lightsalmon:\"ffa07a\",lightseagreen:\"20b2aa\",lightskyblue:\"87cefa\",lightslategray:\"789\",lightslategrey:\"789\",lightsteelblue:\"b0c4de\",lightyellow:\"ffffe0\",lime:\"0f0\",limegreen:\"32cd32\",linen:\"faf0e6\",magenta:\"f0f\",maroon:\"800000\",mediumaquamarine:\"66cdaa\",mediumblue:\"0000cd\",mediumorchid:\"ba55d3\",mediumpurple:\"9370db\",mediumseagreen:\"3cb371\",mediumslateblue:\"7b68ee\",mediumspringgreen:\"00fa9a\",mediumturquoise:\"48d1cc\",mediumvioletred:\"c71585\",midnightblue:\"191970\",mintcream:\"f5fffa\",mistyrose:\"ffe4e1\",moccasin:\"ffe4b5\",navajowhite:\"ffdead\",navy:\"000080\",oldlace:\"fdf5e6\",olive:\"808000\",olivedrab:\"6b8e23\",orange:\"ffa500\",orangered:\"ff4500\",orchid:\"da70d6\",palegoldenrod:\"eee8aa\",palegreen:\"98fb98\",paleturquoise:\"afeeee\",palevioletred:\"db7093\",papayawhip:\"ffefd5\",peachpuff:\"ffdab9\",peru:\"cd853f\",pink:\"ffc0cb\",plum:\"dda0dd\",powderblue:\"b0e0e6\",purple:\"800080\",rebeccapurple:\"663399\",red:\"f00\",rosybrown:\"bc8f8f\",royalblue:\"4169e1\",saddlebrown:\"8b4513\",salmon:\"fa8072\",sandybrown:\"f4a460\",seagreen:\"2e8b57\",seashell:\"fff5ee\",sienna:\"a0522d\",silver:\"c0c0c0\",skyblue:\"87ceeb\",slateblue:\"6a5acd\",slategray:\"708090\",slategrey:\"708090\",snow:\"fffafa\",springgreen:\"00ff7f\",steelblue:\"4682b4\",tan:\"d2b48c\",teal:\"008080\",thistle:\"d8bfd8\",tomato:\"ff6347\",turquoise:\"40e0d0\",violet:\"ee82ee\",wheat:\"f5deb3\",white:\"fff\",whitesmoke:\"f5f5f5\",yellow:\"ff0\",yellowgreen:\"9acd32\"},E=c.hexNames=function(t){var e={};for(var r in t)t.hasOwnProperty(r)&&(e[t[r]]=r);return e}(S);function L(t){return t=parseFloat(t),(isNaN(t)||t<0||t>1)&&(t=1),t}function C(e,r){(function(t){return\"string\"==typeof t&&-1!=t.indexOf(\".\")&&1===parseFloat(t)})(e)&&(e=\"100%\");var n=function(t){return\"string\"==typeof t&&-1!=t.indexOf(\"%\")}(e);return e=o(r,s(0,parseFloat(e))),n&&(e=parseInt(e*r,10)/100),t.abs(e-r)<1e-6?1:e%r/parseFloat(r)}function P(t){return o(1,s(0,t))}function O(t){return parseInt(t,16)}function z(t){return 1==t.length?\"0\"+t:\"\"+t}function I(t){return t<=1&&(t=100*t+\"%\"),t}function D(e){return t.round(255*parseFloat(e)).toString(16)}function R(t){return O(t)/255}var F,B,N,j=(B=\"[\\\\s|\\\\(]+(\"+(F=\"(?:[-\\\\+]?\\\\d*\\\\.\\\\d+%?)|(?:[-\\\\+]?\\\\d+%?)\")+\")[,|\\\\s]+(\"+F+\")[,|\\\\s]+(\"+F+\")\\\\s*\\\\)?\",N=\"[\\\\s|\\\\(]+(\"+F+\")[,|\\\\s]+(\"+F+\")[,|\\\\s]+(\"+F+\")[,|\\\\s]+(\"+F+\")\\\\s*\\\\)?\",{CSS_UNIT:new RegExp(F),rgb:new RegExp(\"rgb\"+B),rgba:new RegExp(\"rgba\"+N),hsl:new RegExp(\"hsl\"+B),hsla:new RegExp(\"hsla\"+N),hsv:new RegExp(\"hsv\"+B),hsva:new RegExp(\"hsva\"+N),hex3:/^#?([0-9a-fA-F]{1})([0-9a-fA-F]{1})([0-9a-fA-F]{1})$/,hex6:/^#?([0-9a-fA-F]{2})([0-9a-fA-F]{2})([0-9a-fA-F]{2})$/,hex4:/^#?([0-9a-fA-F]{1})([0-9a-fA-F]{1})([0-9a-fA-F]{1})([0-9a-fA-F]{1})$/,hex8:/^#?([0-9a-fA-F]{2})([0-9a-fA-F]{2})([0-9a-fA-F]{2})([0-9a-fA-F]{2})$/});function V(t){return!!j.CSS_UNIT.exec(t)}\"undefined\"!=typeof e&&e.exports?e.exports=c:window.tinycolor=c}(Math)},{}],537:[function(t,e,r){\"use strict\";e.exports=a,e.exports.float32=e.exports.float=a,e.exports.fract32=e.exports.fract=function(t){if(t.length){for(var e=a(t),r=0,n=e.length;r<n;r++)e[r]=t[r]-e[r];return e}return a(t-a(t))};var n=new Float32Array(1);function a(t){if(t.length){if(t instanceof Float32Array)return t;var e=new Float32Array(t);return e.set(t),e}return n[0]=t,n[0]}},{}],538:[function(t,e,r){\"use strict\";var n=t(\"parse-unit\");e.exports=o;var a=96;function i(t,e){var r=n(getComputedStyle(t).getPropertyValue(e));return r[0]*o(r[1],t)}function o(t,e){switch(e=e||document.body,t=(t||\"px\").trim().toLowerCase(),e!==window&&e!==document||(e=document.body),t){case\"%\":return e.clientHeight/100;case\"ch\":case\"ex\":return function(t,e){var r=document.createElement(\"div\");r.style[\"font-size\"]=\"128\"+t,e.appendChild(r);var n=i(r,\"font-size\")/128;return e.removeChild(r),n}(t,e);case\"em\":return i(e,\"font-size\");case\"rem\":return i(document.body,\"font-size\");case\"vw\":return window.innerWidth/100;case\"vh\":return window.innerHeight/100;case\"vmin\":return Math.min(window.innerWidth,window.innerHeight)/100;case\"vmax\":return Math.max(window.innerWidth,window.innerHeight)/100;case\"in\":return a;case\"cm\":return a/2.54;case\"mm\":return a/25.4;case\"pt\":return a/72;case\"pc\":return a/6}return 1}},{\"parse-unit\":463}],539:[function(t,e,r){var n;n=this,function(t){\"use strict\";var e=function(t){return t},r=function(t){if(null==(r=t.transform))return e;var r,n,a,i=r.scale[0],o=r.scale[1],s=r.translate[0],l=r.translate[1];return function(t,e){return e||(n=a=0),t[0]=(n+=t[0])*i+s,t[1]=(a+=t[1])*o+l,t}},n=function(t){var e=t.bbox;function n(t){l[0]=t[0],l[1]=t[1],s(l),l[0]<c&&(c=l[0]),l[0]>h&&(h=l[0]),l[1]<u&&(u=l[1]),l[1]>f&&(f=l[1])}function a(t){switch(t.type){case\"GeometryCollection\":t.geometries.forEach(a);break;case\"Point\":n(t.coordinates);break;case\"MultiPoint\":t.coordinates.forEach(n)}}if(!e){var i,o,s=r(t),l=new Array(2),c=1/0,u=c,h=-c,f=-c;for(o in t.arcs.forEach(function(t){for(var e=-1,r=t.length;++e<r;)i=t[e],l[0]=i[0],l[1]=i[1],s(l,e),l[0]<c&&(c=l[0]),l[0]>h&&(h=l[0]),l[1]<u&&(u=l[1]),l[1]>f&&(f=l[1])}),t.objects)a(t.objects[o]);e=t.bbox=[c,u,h,f]}return e},a=function(t,e){for(var r,n=t.length,a=n-e;a<--n;)r=t[a],t[a++]=t[n],t[n]=r};function i(t,e){var r=e.id,n=e.bbox,a=null==e.properties?{}:e.properties,i=o(t,e);return null==r&&null==n?{type:\"Feature\",properties:a,geometry:i}:null==n?{type:\"Feature\",id:r,properties:a,geometry:i}:{type:\"Feature\",id:r,bbox:n,properties:a,geometry:i}}function o(t,e){var n=r(t),i=t.arcs;function o(t,e){e.length&&e.pop();for(var r=i[t<0?~t:t],o=0,s=r.length;o<s;++o)e.push(n(r[o].slice(),o));t<0&&a(e,s)}function s(t){return n(t.slice())}function l(t){for(var e=[],r=0,n=t.length;r<n;++r)o(t[r],e);return e.length<2&&e.push(e[0].slice()),e}function c(t){for(var e=l(t);e.length<4;)e.push(e[0].slice());return e}function u(t){return t.map(c)}return function t(e){var r,n=e.type;switch(n){case\"GeometryCollection\":return{type:n,geometries:e.geometries.map(t)};case\"Point\":r=s(e.coordinates);break;case\"MultiPoint\":r=e.coordinates.map(s);break;case\"LineString\":r=l(e.arcs);break;case\"MultiLineString\":r=e.arcs.map(l);break;case\"Polygon\":r=u(e.arcs);break;case\"MultiPolygon\":r=e.arcs.map(u);break;default:return null}return{type:n,coordinates:r}}(e)}var s=function(t,e){var r={},n={},a={},i=[],o=-1;function s(t,e){for(var n in t){var a=t[n];delete e[a.start],delete a.start,delete a.end,a.forEach(function(t){r[t<0?~t:t]=1}),i.push(a)}}return e.forEach(function(r,n){var a,i=t.arcs[r<0?~r:r];i.length<3&&!i[1][0]&&!i[1][1]&&(a=e[++o],e[o]=r,e[n]=a)}),e.forEach(function(e){var r,i,o=function(e){var r,n=t.arcs[e<0?~e:e],a=n[0];t.transform?(r=[0,0],n.forEach(function(t){r[0]+=t[0],r[1]+=t[1]})):r=n[n.length-1];return e<0?[r,a]:[a,r]}(e),s=o[0],l=o[1];if(r=a[s])if(delete a[r.end],r.push(e),r.end=l,i=n[l]){delete n[i.start];var c=i===r?r:r.concat(i);n[c.start=r.start]=a[c.end=i.end]=c}else n[r.start]=a[r.end]=r;else if(r=n[l])if(delete n[r.start],r.unshift(e),r.start=s,i=a[s]){delete a[i.end];var u=i===r?r:i.concat(r);n[u.start=i.start]=a[u.end=r.end]=u}else n[r.start]=a[r.end]=r;else n[(r=[e]).start=s]=a[r.end=l]=r}),s(a,n),s(n,a),e.forEach(function(t){r[t<0?~t:t]||i.push([t])}),i};function l(t,e,r){var n,a,i;if(arguments.length>1)n=function(t,e,r){var n,a=[],i=[];function o(t){var e=t<0?~t:t;(i[e]||(i[e]=[])).push({i:t,g:n})}function s(t){t.forEach(o)}function l(t){t.forEach(s)}return function t(e){switch(n=e,e.type){case\"GeometryCollection\":e.geometries.forEach(t);break;case\"LineString\":s(e.arcs);break;case\"MultiLineString\":case\"Polygon\":l(e.arcs);break;case\"MultiPolygon\":e.arcs.forEach(l)}}(e),i.forEach(null==r?function(t){a.push(t[0].i)}:function(t){r(t[0].g,t[t.length-1].g)&&a.push(t[0].i)}),a}(0,e,r);else for(a=0,n=new Array(i=t.arcs.length);a<i;++a)n[a]=a;return{type:\"MultiLineString\",arcs:s(t,n)}}function c(t,e){var r={},n=[],a=[];function i(t){t.forEach(function(e){e.forEach(function(e){(r[e=e<0?~e:e]||(r[e]=[])).push(t)})}),n.push(t)}function l(e){return function(t){for(var e,r=-1,n=t.length,a=t[n-1],i=0;++r<n;)e=a,a=t[r],i+=e[0]*a[1]-e[1]*a[0];return Math.abs(i)}(o(t,{type:\"Polygon\",arcs:[e]}).coordinates[0])}return e.forEach(function t(e){switch(e.type){case\"GeometryCollection\":e.geometries.forEach(t);break;case\"Polygon\":i(e.arcs);break;case\"MultiPolygon\":e.arcs.forEach(i)}}),n.forEach(function(t){if(!t._){var e=[],n=[t];for(t._=1,a.push(e);t=n.pop();)e.push(t),t.forEach(function(t){t.forEach(function(t){r[t<0?~t:t].forEach(function(t){t._||(t._=1,n.push(t))})})})}}),n.forEach(function(t){delete t._}),{type:\"MultiPolygon\",arcs:a.map(function(e){var n,a=[];if(e.forEach(function(t){t.forEach(function(t){t.forEach(function(t){r[t<0?~t:t].length<2&&a.push(t)})})}),(n=(a=s(t,a)).length)>1)for(var i,o,c=1,u=l(a[0]);c<n;++c)(i=l(a[c]))>u&&(o=a[0],a[0]=a[c],a[c]=o,u=i);return a})}}var u=function(t,e){for(var r=0,n=t.length;r<n;){var a=r+n>>>1;t[a]<e?r=a+1:n=a}return r};t.bbox=n,t.feature=function(t,e){return\"GeometryCollection\"===e.type?{type:\"FeatureCollection\",features:e.geometries.map(function(e){return i(t,e)})}:i(t,e)},t.mesh=function(t){return o(t,l.apply(this,arguments))},t.meshArcs=l,t.merge=function(t){return o(t,c.apply(this,arguments))},t.mergeArcs=c,t.neighbors=function(t){var e={},r=t.map(function(){return[]});function n(t,r){t.forEach(function(t){t<0&&(t=~t);var n=e[t];n?n.push(r):e[t]=[r]})}function a(t,e){t.forEach(function(t){n(t,e)})}var i={LineString:n,MultiLineString:a,Polygon:a,MultiPolygon:function(t,e){t.forEach(function(t){a(t,e)})}};for(var o in t.forEach(function t(e,r){\"GeometryCollection\"===e.type?e.geometries.forEach(function(e){t(e,r)}):e.type in i&&i[e.type](e.arcs,r)}),e)for(var s=e[o],l=s.length,c=0;c<l;++c)for(var h=c+1;h<l;++h){var f,p=s[c],d=s[h];(f=r[p])[o=u(f,d)]!==d&&f.splice(o,0,d),(f=r[d])[o=u(f,p)]!==p&&f.splice(o,0,p)}return r},t.quantize=function(t,e){if(!((e=Math.floor(e))>=2))throw new Error(\"n must be \\u22652\");if(t.transform)throw new Error(\"already quantized\");var r,a=n(t),i=a[0],o=(a[2]-i)/(e-1)||1,s=a[1],l=(a[3]-s)/(e-1)||1;function c(t){t[0]=Math.round((t[0]-i)/o),t[1]=Math.round((t[1]-s)/l)}function u(t){switch(t.type){case\"GeometryCollection\":t.geometries.forEach(u);break;case\"Point\":c(t.coordinates);break;case\"MultiPoint\":t.coordinates.forEach(c)}}for(r in t.arcs.forEach(function(t){for(var e,r,n,a=1,c=1,u=t.length,h=t[0],f=h[0]=Math.round((h[0]-i)/o),p=h[1]=Math.round((h[1]-s)/l);a<u;++a)h=t[a],r=Math.round((h[0]-i)/o),n=Math.round((h[1]-s)/l),r===f&&n===p||((e=t[c++])[0]=r-f,f=r,e[1]=n-p,p=n);c<2&&((e=t[c++])[0]=0,e[1]=0),t.length=c}),t.objects)u(t.objects[r]);return t.transform={scale:[o,l],translate:[i,s]},t},t.transform=r,t.untransform=function(t){if(null==(r=t.transform))return e;var r,n,a,i=r.scale[0],o=r.scale[1],s=r.translate[0],l=r.translate[1];return function(t,e){e||(n=a=0);var r=Math.round((t[0]-s)/i),c=Math.round((t[1]-l)/o);return t[0]=r-n,n=r,t[1]=c-a,a=c,t}},Object.defineProperty(t,\"__esModule\",{value:!0})}(\"object\"==typeof r&&\"undefined\"!=typeof e?r:n.topojson=n.topojson||{})},{}],540:[function(t,e,r){\"use strict\";e.exports=function(t){if(t<0)return[];if(0===t)return[[0]];for(var e=0|Math.round(i(t+1)),r=[],o=0;o<e;++o){for(var s=n.unrank(t,o),l=[0],c=0,u=0;u<s.length;++u)c+=1<<s[u],l.push(c);a(s)<1&&(l[0]=c,l[t]=0),r.push(l)}return r};var n=t(\"permutation-rank\"),a=t(\"permutation-parity\"),i=t(\"gamma\")},{gamma:234,\"permutation-parity\":465,\"permutation-rank\":466}],541:[function(t,e,r){\"use strict\";e.exports=function(t){var e=(t=t||{}).center||[0,0,0],r=t.up||[0,1,0],n=t.right||h(r),a=t.radius||1,i=t.theta||0,u=t.phi||0;if(e=[].slice.call(e,0,3),r=[].slice.call(r,0,3),s(r,r),n=[].slice.call(n,0,3),s(n,n),\"eye\"in t){var p=t.eye,d=[p[0]-e[0],p[1]-e[1],p[2]-e[2]];o(n,d,r),c(n[0],n[1],n[2])<1e-6?n=h(r):s(n,n),a=c(d[0],d[1],d[2]);var g=l(r,d)/a,v=l(n,d)/a;u=Math.acos(g),i=Math.acos(v)}return a=Math.log(a),new f(t.zoomMin,t.zoomMax,e,r,n,a,i,u)};var n=t(\"filtered-vector\"),a=t(\"gl-mat4/invert\"),i=t(\"gl-mat4/rotate\"),o=t(\"gl-vec3/cross\"),s=t(\"gl-vec3/normalize\"),l=t(\"gl-vec3/dot\");function c(t,e,r){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2))}function u(t){return Math.min(1,Math.max(-1,t))}function h(t){var e=Math.abs(t[0]),r=Math.abs(t[1]),n=Math.abs(t[2]),a=[0,0,0];e>Math.max(r,n)?a[2]=1:r>Math.max(e,n)?a[0]=1:a[1]=1;for(var i=0,o=0,l=0;l<3;++l)i+=t[l]*t[l],o+=a[l]*t[l];for(l=0;l<3;++l)a[l]-=o/i*t[l];return s(a,a),a}function f(t,e,r,a,i,o,s,l){this.center=n(r),this.up=n(a),this.right=n(i),this.radius=n([o]),this.angle=n([s,l]),this.angle.bounds=[[-1/0,-Math.PI/2],[1/0,Math.PI/2]],this.setDistanceLimits(t,e),this.computedCenter=this.center.curve(0),this.computedUp=this.up.curve(0),this.computedRight=this.right.curve(0),this.computedRadius=this.radius.curve(0),this.computedAngle=this.angle.curve(0),this.computedToward=[0,0,0],this.computedEye=[0,0,0],this.computedMatrix=new Array(16);for(var c=0;c<16;++c)this.computedMatrix[c]=.5;this.recalcMatrix(0)}var p=f.prototype;p.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-1/0,e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},p.getDistanceLimits=function(t){var e=this.radius.bounds[0];return t?(t[0]=Math.exp(e[0][0]),t[1]=Math.exp(e[1][0]),t):[Math.exp(e[0][0]),Math.exp(e[1][0])]},p.recalcMatrix=function(t){this.center.curve(t),this.up.curve(t),this.right.curve(t),this.radius.curve(t),this.angle.curve(t);for(var e=this.computedUp,r=this.computedRight,n=0,a=0,i=0;i<3;++i)a+=e[i]*r[i],n+=e[i]*e[i];var l=Math.sqrt(n),u=0;for(i=0;i<3;++i)r[i]-=e[i]*a/n,u+=r[i]*r[i],e[i]/=l;var h=Math.sqrt(u);for(i=0;i<3;++i)r[i]/=h;var f=this.computedToward;o(f,e,r),s(f,f);var p=Math.exp(this.computedRadius[0]),d=this.computedAngle[0],g=this.computedAngle[1],v=Math.cos(d),m=Math.sin(d),y=Math.cos(g),x=Math.sin(g),b=this.computedCenter,_=v*y,w=m*y,k=x,T=-v*x,M=-m*x,A=y,S=this.computedEye,E=this.computedMatrix;for(i=0;i<3;++i){var L=_*r[i]+w*f[i]+k*e[i];E[4*i+1]=T*r[i]+M*f[i]+A*e[i],E[4*i+2]=L,E[4*i+3]=0}var C=E[1],P=E[5],O=E[9],z=E[2],I=E[6],D=E[10],R=P*D-O*I,F=O*z-C*D,B=C*I-P*z,N=c(R,F,B);R/=N,F/=N,B/=N,E[0]=R,E[4]=F,E[8]=B;for(i=0;i<3;++i)S[i]=b[i]+E[2+4*i]*p;for(i=0;i<3;++i){u=0;for(var j=0;j<3;++j)u+=E[i+4*j]*S[j];E[12+i]=-u}E[15]=1},p.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;n<16;++n)e[n]=r[n];return e}return r};var d=[0,0,0];p.rotate=function(t,e,r,n){if(this.angle.move(t,e,r),n){this.recalcMatrix(t);var a=this.computedMatrix;d[0]=a[2],d[1]=a[6],d[2]=a[10];for(var o=this.computedUp,s=this.computedRight,l=this.computedToward,c=0;c<3;++c)a[4*c]=o[c],a[4*c+1]=s[c],a[4*c+2]=l[c];i(a,a,n,d);for(c=0;c<3;++c)o[c]=a[4*c],s[c]=a[4*c+1];this.up.set(t,o[0],o[1],o[2]),this.right.set(t,s[0],s[1],s[2])}},p.pan=function(t,e,r,n){e=e||0,r=r||0,n=n||0,this.recalcMatrix(t);var a=this.computedMatrix,i=(Math.exp(this.computedRadius[0]),a[1]),o=a[5],s=a[9],l=c(i,o,s);i/=l,o/=l,s/=l;var u=a[0],h=a[4],f=a[8],p=u*i+h*o+f*s,d=c(u-=i*p,h-=o*p,f-=s*p),g=(u/=d)*e+i*r,v=(h/=d)*e+o*r,m=(f/=d)*e+s*r;this.center.move(t,g,v,m);var y=Math.exp(this.computedRadius[0]);y=Math.max(1e-4,y+n),this.radius.set(t,Math.log(y))},p.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},p.setMatrix=function(t,e,r,n){var i=1;\"number\"==typeof r&&(i=0|r),(i<0||i>3)&&(i=1);var o=(i+2)%3;e||(this.recalcMatrix(t),e=this.computedMatrix);var s=e[i],l=e[i+4],h=e[i+8];if(n){var f=Math.abs(s),p=Math.abs(l),d=Math.abs(h),g=Math.max(f,p,d);f===g?(s=s<0?-1:1,l=h=0):d===g?(h=h<0?-1:1,s=l=0):(l=l<0?-1:1,s=h=0)}else{var v=c(s,l,h);s/=v,l/=v,h/=v}var m,y,x=e[o],b=e[o+4],_=e[o+8],w=x*s+b*l+_*h,k=c(x-=s*w,b-=l*w,_-=h*w),T=l*(_/=k)-h*(b/=k),M=h*(x/=k)-s*_,A=s*b-l*x,S=c(T,M,A);if(T/=S,M/=S,A/=S,this.center.jump(t,H,G,Y),this.radius.idle(t),this.up.jump(t,s,l,h),this.right.jump(t,x,b,_),2===i){var E=e[1],L=e[5],C=e[9],P=E*x+L*b+C*_,O=E*T+L*M+C*A;m=R<0?-Math.PI/2:Math.PI/2,y=Math.atan2(O,P)}else{var z=e[2],I=e[6],D=e[10],R=z*s+I*l+D*h,F=z*x+I*b+D*_,B=z*T+I*M+D*A;m=Math.asin(u(R)),y=Math.atan2(B,F)}this.angle.jump(t,y,m),this.recalcMatrix(t);var N=e[2],j=e[6],V=e[10],U=this.computedMatrix;a(U,e);var q=U[15],H=U[12]/q,G=U[13]/q,Y=U[14]/q,W=Math.exp(this.computedRadius[0]);this.center.jump(t,H-N*W,G-j*W,Y-V*W)},p.lastT=function(){return Math.max(this.center.lastT(),this.up.lastT(),this.right.lastT(),this.radius.lastT(),this.angle.lastT())},p.idle=function(t){this.center.idle(t),this.up.idle(t),this.right.idle(t),this.radius.idle(t),this.angle.idle(t)},p.flush=function(t){this.center.flush(t),this.up.flush(t),this.right.flush(t),this.radius.flush(t),this.angle.flush(t)},p.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},p.lookAt=function(t,e,r,n){this.recalcMatrix(t),e=e||this.computedEye,r=r||this.computedCenter;var a=(n=n||this.computedUp)[0],i=n[1],o=n[2],s=c(a,i,o);if(!(s<1e-6)){a/=s,i/=s,o/=s;var l=e[0]-r[0],h=e[1]-r[1],f=e[2]-r[2],p=c(l,h,f);if(!(p<1e-6)){l/=p,h/=p,f/=p;var d=this.computedRight,g=d[0],v=d[1],m=d[2],y=a*g+i*v+o*m,x=c(g-=y*a,v-=y*i,m-=y*o);if(!(x<.01&&(x=c(g=i*f-o*h,v=o*l-a*f,m=a*h-i*l))<1e-6)){g/=x,v/=x,m/=x,this.up.set(t,a,i,o),this.right.set(t,g,v,m),this.center.set(t,r[0],r[1],r[2]),this.radius.set(t,Math.log(p));var b=i*m-o*v,_=o*g-a*m,w=a*v-i*g,k=c(b,_,w),T=a*l+i*h+o*f,M=g*l+v*h+m*f,A=(b/=k)*l+(_/=k)*h+(w/=k)*f,S=Math.asin(u(T)),E=Math.atan2(A,M),L=this.angle._state,C=L[L.length-1],P=L[L.length-2];C%=2*Math.PI;var O=Math.abs(C+2*Math.PI-E),z=Math.abs(C-E),I=Math.abs(C-2*Math.PI-E);O<z&&(C+=2*Math.PI),I<z&&(C-=2*Math.PI),this.angle.jump(this.angle.lastT(),C,P),this.angle.set(t,E,S)}}}}},{\"filtered-vector\":229,\"gl-mat4/invert\":268,\"gl-mat4/rotate\":273,\"gl-vec3/cross\":336,\"gl-vec3/dot\":341,\"gl-vec3/normalize\":358}],542:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){var a=t*e,i=n*t,o=i-(i-t),s=t-o,l=n*e,c=l-(l-e),u=e-c,h=s*u-(a-o*c-s*c-o*u);if(r)return r[0]=h,r[1]=a,r;return[h,a]};var n=+(Math.pow(2,27)+1)},{}],543:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){var n=t+e,a=n-t,i=e-a,o=t-(n-a);if(r)return r[0]=o+i,r[1]=n,r;return[o+i,n]}},{}],544:[function(t,e,r){(function(e,n){\"use strict\";var a=t(\"bit-twiddle\"),i=t(\"dup\");e.__TYPEDARRAY_POOL||(e.__TYPEDARRAY_POOL={UINT8:i([32,0]),UINT16:i([32,0]),UINT32:i([32,0]),INT8:i([32,0]),INT16:i([32,0]),INT32:i([32,0]),FLOAT:i([32,0]),DOUBLE:i([32,0]),DATA:i([32,0]),UINT8C:i([32,0]),BUFFER:i([32,0])});var o=\"undefined\"!=typeof Uint8ClampedArray,s=e.__TYPEDARRAY_POOL;s.UINT8C||(s.UINT8C=i([32,0])),s.BUFFER||(s.BUFFER=i([32,0]));var l=s.DATA,c=s.BUFFER;function u(t){if(t){var e=t.length||t.byteLength,r=a.log2(e);l[r].push(t)}}function h(t){t=a.nextPow2(t);var e=a.log2(t),r=l[e];return r.length>0?r.pop():new ArrayBuffer(t)}function f(t){return new Uint8Array(h(t),0,t)}function p(t){return new Uint16Array(h(2*t),0,t)}function d(t){return new Uint32Array(h(4*t),0,t)}function g(t){return new Int8Array(h(t),0,t)}function v(t){return new Int16Array(h(2*t),0,t)}function m(t){return new Int32Array(h(4*t),0,t)}function y(t){return new Float32Array(h(4*t),0,t)}function x(t){return new Float64Array(h(8*t),0,t)}function b(t){return o?new Uint8ClampedArray(h(t),0,t):f(t)}function _(t){return new DataView(h(t),0,t)}function w(t){t=a.nextPow2(t);var e=a.log2(t),r=c[e];return r.length>0?r.pop():new n(t)}r.free=function(t){if(n.isBuffer(t))c[a.log2(t.length)].push(t);else{if(\"[object ArrayBuffer]\"!==Object.prototype.toString.call(t)&&(t=t.buffer),!t)return;var e=t.length||t.byteLength,r=0|a.log2(e);l[r].push(t)}},r.freeUint8=r.freeUint16=r.freeUint32=r.freeInt8=r.freeInt16=r.freeInt32=r.freeFloat32=r.freeFloat=r.freeFloat64=r.freeDouble=r.freeUint8Clamped=r.freeDataView=function(t){u(t.buffer)},r.freeArrayBuffer=u,r.freeBuffer=function(t){c[a.log2(t.length)].push(t)},r.malloc=function(t,e){if(void 0===e||\"arraybuffer\"===e)return h(t);switch(e){case\"uint8\":return f(t);case\"uint16\":return p(t);case\"uint32\":return d(t);case\"int8\":return g(t);case\"int16\":return v(t);case\"int32\":return m(t);case\"float\":case\"float32\":return y(t);case\"double\":case\"float64\":return x(t);case\"uint8_clamped\":return b(t);case\"buffer\":return w(t);case\"data\":case\"dataview\":return _(t);default:return null}return null},r.mallocArrayBuffer=h,r.mallocUint8=f,r.mallocUint16=p,r.mallocUint32=d,r.mallocInt8=g,r.mallocInt16=v,r.mallocInt32=m,r.mallocFloat32=r.mallocFloat=y,r.mallocFloat64=r.mallocDouble=x,r.mallocUint8Clamped=b,r.mallocDataView=_,r.mallocBuffer=w,r.clearCache=function(){for(var t=0;t<32;++t)s.UINT8[t].length=0,s.UINT16[t].length=0,s.UINT32[t].length=0,s.INT8[t].length=0,s.INT16[t].length=0,s.INT32[t].length=0,s.FLOAT[t].length=0,s.DOUBLE[t].length=0,s.UINT8C[t].length=0,l[t].length=0,c[t].length=0}}).call(this,\"undefined\"!=typeof global?global:\"undefined\"!=typeof self?self:\"undefined\"!=typeof window?window:{},t(\"buffer\").Buffer)},{\"bit-twiddle\":94,buffer:107,dup:172}],545:[function(t,e,r){\"use strict\";function n(t){this.roots=new Array(t),this.ranks=new Array(t);for(var e=0;e<t;++e)this.roots[e]=e,this.ranks[e]=0}e.exports=n;var a=n.prototype;Object.defineProperty(a,\"length\",{get:function(){return this.roots.length}}),a.makeSet=function(){var t=this.roots.length;return this.roots.push(t),this.ranks.push(0),t},a.find=function(t){for(var e=t,r=this.roots;r[t]!==t;)t=r[t];for(;r[e]!==t;){var n=r[e];r[e]=t,e=n}return t},a.link=function(t,e){var r=this.find(t),n=this.find(e);if(r!==n){var a=this.ranks,i=this.roots,o=a[r],s=a[n];o<s?i[r]=n:s<o?i[n]=r:(i[n]=r,++a[r])}}},{}],546:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){return 0===t.length?t:e?(r||t.sort(e),function(t,e){for(var r=1,n=t.length,a=t[0],i=t[0],o=1;o<n;++o)if(i=a,e(a=t[o],i)){if(o===r){r++;continue}t[r++]=a}return t.length=r,t}(t,e)):(r||t.sort(),function(t){for(var e=1,r=t.length,n=t[0],a=t[0],i=1;i<r;++i,a=n)if(a=n,(n=t[i])!==a){if(i===e){e++;continue}t[e++]=n}return t.length=e,t}(t))}},{}],547:[function(t,e,r){var n=/[\\'\\\"]/;e.exports=function(t){return t?(n.test(t.charAt(0))&&(t=t.substr(1)),n.test(t.charAt(t.length-1))&&(t=t.substr(0,t.length-1)),t):\"\"}},{}],548:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){Array.isArray(r)||(r=[].slice.call(arguments,2));for(var n=0,a=r.length;n<a;n++){var i=r[n];for(var o in i)if((void 0===e[o]||Array.isArray(e[o])||t[o]!==e[o])&&o in e){var s;if(!0===i[o])s=e[o];else{if(!1===i[o])continue;if(\"function\"==typeof i[o]&&void 0===(s=i[o](e[o],t,e)))continue}t[o]=s}}return t}},{}],549:[function(t,e,r){\"use strict\";e.exports=function(t,e){\"object\"==typeof e&&null!==e||(e={});return n(t,e.canvas||a,e.context||i,e)};var n=t(\"./lib/vtext\"),a=null,i=null;\"undefined\"!=typeof document&&((a=document.createElement(\"canvas\")).width=8192,a.height=1024,i=a.getContext(\"2d\"))},{\"./lib/vtext\":550}],550:[function(t,e,r){e.exports=function(t,e,r,n){var i=64,o=1.25,s={breaklines:!1,bolds:!1,italics:!1,subscripts:!1,superscripts:!1};n&&(n.size&&n.size>0&&(i=n.size),n.lineSpacing&&n.lineSpacing>0&&(o=n.lineSpacing),n.styletags&&n.styletags.breaklines&&(s.breaklines=!!n.styletags.breaklines),n.styletags&&n.styletags.bolds&&(s.bolds=!!n.styletags.bolds),n.styletags&&n.styletags.italics&&(s.italics=!!n.styletags.italics),n.styletags&&n.styletags.subscripts&&(s.subscripts=!!n.styletags.subscripts),n.styletags&&n.styletags.superscripts&&(s.superscripts=!!n.styletags.superscripts));return r.font=[n.fontStyle,n.fontVariant,n.fontWeight,i+\"px\",n.font].filter(function(t){return t}).join(\" \"),r.textAlign=\"start\",r.textBaseline=\"alphabetic\",r.direction=\"ltr\",w(function(t,e,r,n,i,o){r=r.replace(/\\n/g,\"\"),r=!0===o.breaklines?r.replace(/\\<br\\>/g,\"\\n\"):r.replace(/\\<br\\>/g,\" \");var s=\"\",l=[];for(k=0;k<r.length;++k)l[k]=s;!0===o.bolds&&(l=x(c,u,r,l)),!0===o.italics&&(l=x(h,f,r,l)),!0===o.superscripts&&(l=x(p,g,r,l)),!0===o.subscripts&&(l=x(v,y,r,l));var b=[],_=\"\";for(k=0;k<r.length;++k)null!==l[k]&&(_+=r[k],b.push(l[k]));var w,k,T,M,A,S=_.split(\"\\n\"),E=S.length,L=Math.round(i*n),C=n,P=2*n,O=0,z=E*L+P;t.height<z&&(t.height=z),e.fillStyle=\"#000\",e.fillRect(0,0,t.width,t.height),e.fillStyle=\"#fff\";var I=0,D=\"\";function R(){if(\"\"!==D){var t=e.measureText(D).width;e.fillText(D,C+T,P+M),T+=t}}function F(){return Math.round(A)+\"px \"}function B(t,r){var n=\"\"+e.font;if(!0===o.subscripts){var a=t.indexOf(m),i=r.indexOf(m),s=a>-1?parseInt(t[1+a]):0,l=i>-1?parseInt(r[1+i]):0;s!==l&&(n=n.replace(F(),\"?px \"),A*=Math.pow(.75,l-s),n=n.replace(\"?px \",F())),M+=.25*L*(l-s)}if(!0===o.superscripts){var c=t.indexOf(d),h=r.indexOf(d),p=c>-1?parseInt(t[1+c]):0,g=h>-1?parseInt(r[1+h]):0;p!==g&&(n=n.replace(F(),\"?px \"),A*=Math.pow(.75,g-p),n=n.replace(\"?px \",F())),M-=.25*L*(g-p)}if(!0===o.bolds){var v=t.indexOf(u)>-1,y=r.indexOf(u)>-1;!v&&y&&(n=x?n.replace(\"italic \",\"italic bold \"):\"bold \"+n),v&&!y&&(n=n.replace(\"bold \",\"\"))}if(!0===o.italics){var x=t.indexOf(f)>-1,b=r.indexOf(f)>-1;!x&&b&&(n=\"italic \"+n),x&&!b&&(n=n.replace(\"italic \",\"\"))}e.font=n}for(w=0;w<E;++w){var N=S[w]+\"\\n\";for(T=0,M=w*L,A=n,D=\"\",k=0;k<N.length;++k){var j=k+I<b.length?b[k+I]:b[b.length-1];s===j?D+=N[k]:(R(),D=N[k],void 0!==j&&(B(s,j),s=j))}R(),I+=N.length;var V=0|Math.round(T+2*C);O<V&&(O=V)}var U=O,q=P+L*E;return a(e.getImageData(0,0,U,q).data,[q,U,4]).pick(-1,-1,0).transpose(1,0)}(e,r,t,i,o,s),n,i)},e.exports.processPixels=w;var n=t(\"surface-nets\"),a=t(\"ndarray\"),i=t(\"simplify-planar-graph\"),o=t(\"clean-pslg\"),s=t(\"cdt2d\"),l=t(\"planar-graph-to-polyline\"),c=\"b\",u=\"b|\",h=\"i\",f=\"i|\",p=\"sup\",d=\"+\",g=\"+1\",v=\"sub\",m=\"-\",y=\"-1\";function x(t,e,r,n){for(var a=\"<\"+t+\">\",i=\"</\"+t+\">\",o=a.length,s=i.length,l=e[0]===d||e[0]===m,c=0,u=-s;c>-1&&-1!==(c=r.indexOf(a,c))&&-1!==(u=r.indexOf(i,c+o))&&!(u<=c);){for(var h=c;h<u+s;++h)if(h<c+o||h>=u)n[h]=null,r=r.substr(0,h)+\" \"+r.substr(h+1);else if(null!==n[h]){var f=n[h].indexOf(e[0]);-1===f?n[h]+=e:l&&(n[h]=n[h].substr(0,f+1)+(1+parseInt(n[h][f+1]))+n[h].substr(f+2))}var p=c+o,g=r.substr(p,u-p).indexOf(a);c=-1!==g?g:u+s}return n}function b(t,e){var r=n(t,128);return e?i(r.cells,r.positions,.25):{edges:r.cells,positions:r.positions}}function _(t,e,r,n){var a=b(t,n),i=function(t,e,r){for(var n=e.textAlign||\"start\",a=e.textBaseline||\"alphabetic\",i=[1<<30,1<<30],o=[0,0],s=t.length,l=0;l<s;++l)for(var c=t[l],u=0;u<2;++u)i[u]=0|Math.min(i[u],c[u]),o[u]=0|Math.max(o[u],c[u]);var h=0;switch(n){case\"center\":h=-.5*(i[0]+o[0]);break;case\"right\":case\"end\":h=-o[0];break;case\"left\":case\"start\":h=-i[0];break;default:throw new Error(\"vectorize-text: Unrecognized textAlign: '\"+n+\"'\")}var f=0;switch(a){case\"hanging\":case\"top\":f=-i[1];break;case\"middle\":f=-.5*(i[1]+o[1]);break;case\"alphabetic\":case\"ideographic\":f=-3*r;break;case\"bottom\":f=-o[1];break;default:throw new Error(\"vectorize-text: Unrecoginized textBaseline: '\"+a+\"'\")}var p=1/r;return\"lineHeight\"in e?p*=+e.lineHeight:\"width\"in e?p=e.width/(o[0]-i[0]):\"height\"in e&&(p=e.height/(o[1]-i[1])),t.map(function(t){return[p*(t[0]+h),p*(t[1]+f)]})}(a.positions,e,r),c=a.edges,u=\"ccw\"===e.orientation;if(o(i,c),e.polygons||e.polygon||e.polyline){for(var h=l(c,i),f=new Array(h.length),p=0;p<h.length;++p){for(var d=h[p],g=new Array(d.length),v=0;v<d.length;++v){for(var m=d[v],y=new Array(m.length),x=0;x<m.length;++x)y[x]=i[m[x]].slice();u&&y.reverse(),g[v]=y}f[p]=g}return f}return e.triangles||e.triangulate||e.triangle?{cells:s(i,c,{delaunay:!1,exterior:!1,interior:!0}),positions:i}:{edges:c,positions:i}}function w(t,e,r){try{return _(t,e,r,!0)}catch(t){}try{return _(t,e,r,!1)}catch(t){}return e.polygons||e.polyline||e.polygon?[]:e.triangles||e.triangulate||e.triangle?{cells:[],positions:[]}:{edges:[],positions:[]}}},{cdt2d:108,\"clean-pslg\":118,ndarray:452,\"planar-graph-to-polyline\":470,\"simplify-planar-graph\":523,\"surface-nets\":530}],551:[function(t,e,r){!function(){\"use strict\";if(\"undefined\"==typeof ses||!ses.ok||ses.ok()){\"undefined\"!=typeof ses&&(ses.weakMapPermitHostObjects=v);var t=!1;if(\"function\"==typeof WeakMap){var r=WeakMap;if(\"undefined\"!=typeof navigator&&/Firefox/.test(navigator.userAgent));else{var n=new r,a=Object.freeze({});if(n.set(a,1),1===n.get(a))return void(e.exports=WeakMap);t=!0}}Object.prototype.hasOwnProperty;var i=Object.getOwnPropertyNames,o=Object.defineProperty,s=Object.isExtensible,l=\"weakmap:\",c=l+\"ident:\"+Math.random()+\"___\";if(\"undefined\"!=typeof crypto&&\"function\"==typeof crypto.getRandomValues&&\"function\"==typeof ArrayBuffer&&\"function\"==typeof Uint8Array){var u=new ArrayBuffer(25),h=new Uint8Array(u);crypto.getRandomValues(h),c=l+\"rand:\"+Array.prototype.map.call(h,function(t){return(t%36).toString(36)}).join(\"\")+\"___\"}if(o(Object,\"getOwnPropertyNames\",{value:function(t){return i(t).filter(m)}}),\"getPropertyNames\"in Object){var f=Object.getPropertyNames;o(Object,\"getPropertyNames\",{value:function(t){return f(t).filter(m)}})}!function(){var t=Object.freeze;o(Object,\"freeze\",{value:function(e){return y(e),t(e)}});var e=Object.seal;o(Object,\"seal\",{value:function(t){return y(t),e(t)}});var r=Object.preventExtensions;o(Object,\"preventExtensions\",{value:function(t){return y(t),r(t)}})}();var p=!1,d=0,g=function(){this instanceof g||b();var t=[],e=[],r=d++;return Object.create(g.prototype,{get___:{value:x(function(n,a){var i,o=y(n);return o?r in o?o[r]:a:(i=t.indexOf(n))>=0?e[i]:a})},has___:{value:x(function(e){var n=y(e);return n?r in n:t.indexOf(e)>=0})},set___:{value:x(function(n,a){var i,o=y(n);return o?o[r]=a:(i=t.indexOf(n))>=0?e[i]=a:(i=t.length,e[i]=a,t[i]=n),this})},delete___:{value:x(function(n){var a,i,o=y(n);return o?r in o&&delete o[r]:!((a=t.indexOf(n))<0||(i=t.length-1,t[a]=void 0,e[a]=e[i],t[a]=t[i],t.length=i,e.length=i,0))})}})};g.prototype=Object.create(Object.prototype,{get:{value:function(t,e){return this.get___(t,e)},writable:!0,configurable:!0},has:{value:function(t){return this.has___(t)},writable:!0,configurable:!0},set:{value:function(t,e){return this.set___(t,e)},writable:!0,configurable:!0},delete:{value:function(t){return this.delete___(t)},writable:!0,configurable:!0}}),\"function\"==typeof r?function(){function n(){this instanceof g||b();var e,n=new r,a=void 0,i=!1;return e=t?function(t,e){return n.set(t,e),n.has(t)||(a||(a=new g),a.set(t,e)),this}:function(t,e){if(i)try{n.set(t,e)}catch(r){a||(a=new g),a.set___(t,e)}else n.set(t,e);return this},Object.create(g.prototype,{get___:{value:x(function(t,e){return a?n.has(t)?n.get(t):a.get___(t,e):n.get(t,e)})},has___:{value:x(function(t){return n.has(t)||!!a&&a.has___(t)})},set___:{value:x(e)},delete___:{value:x(function(t){var e=!!n.delete(t);return a&&a.delete___(t)||e})},permitHostObjects___:{value:x(function(t){if(t!==v)throw new Error(\"bogus call to permitHostObjects___\");i=!0})}})}t&&\"undefined\"!=typeof Proxy&&(Proxy=void 0),n.prototype=g.prototype,e.exports=n,Object.defineProperty(WeakMap.prototype,\"constructor\",{value:WeakMap,enumerable:!1,configurable:!0,writable:!0})}():(\"undefined\"!=typeof Proxy&&(Proxy=void 0),e.exports=g)}function v(t){t.permitHostObjects___&&t.permitHostObjects___(v)}function m(t){return!(t.substr(0,l.length)==l&&\"___\"===t.substr(t.length-3))}function y(t){if(t!==Object(t))throw new TypeError(\"Not an object: \"+t);var e=t[c];if(e&&e.key===t)return e;if(s(t)){e={key:t};try{return o(t,c,{value:e,writable:!1,enumerable:!1,configurable:!1}),e}catch(t){return}}}function x(t){return t.prototype=null,Object.freeze(t)}function b(){p||\"undefined\"==typeof console||(p=!0,console.warn(\"WeakMap should be invoked as new WeakMap(), not WeakMap(). This will be an error in the future.\"))}}()},{}],552:[function(t,e,r){var n=t(\"./hidden-store.js\");e.exports=function(){var t={};return function(e){if((\"object\"!=typeof e||null===e)&&\"function\"!=typeof e)throw new Error(\"Weakmap-shim: Key must be object\");var r=e.valueOf(t);return r&&r.identity===t?r:n(e,t)}}},{\"./hidden-store.js\":553}],553:[function(t,e,r){e.exports=function(t,e){var r={identity:e},n=t.valueOf;return Object.defineProperty(t,\"valueOf\",{value:function(t){return t!==e?n.apply(this,arguments):r},writable:!0}),r}},{}],554:[function(t,e,r){var n=t(\"./create-store.js\");e.exports=function(){var t=n();return{get:function(e,r){var n=t(e);return n.hasOwnProperty(\"value\")?n.value:r},set:function(e,r){return t(e).value=r,this},has:function(e){return\"value\"in t(e)},delete:function(e){return delete t(e).value}}}},{\"./create-store.js\":552}],555:[function(t,e,r){var n=t(\"get-canvas-context\");e.exports=function(t){return n(\"webgl\",t)}},{\"get-canvas-context\":235}],556:[function(t,e,r){var n=t(\"../main\"),a=t(\"object-assign\"),i=n.instance();function o(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}o.prototype=new n.baseCalendar,a(o.prototype,{name:\"Chinese\",jdEpoch:1721425.5,hasYearZero:!1,minMonth:0,firstMonth:0,minDay:1,regionalOptions:{\"\":{name:\"Chinese\",epochs:[\"BEC\",\"EC\"],monthNumbers:function(t,e){if(\"string\"==typeof t){var r=t.match(l);return r?r[0]:\"\"}var n=this._validateYear(t),a=t.month(),i=\"\"+this.toChineseMonth(n,a);return e&&i.length<2&&(i=\"0\"+i),this.isIntercalaryMonth(n,a)&&(i+=\"i\"),i},monthNames:function(t){if(\"string\"==typeof t){var e=t.match(c);return e?e[0]:\"\"}var r=this._validateYear(t),n=t.month(),a=[\"\\u4e00\\u6708\",\"\\u4e8c\\u6708\",\"\\u4e09\\u6708\",\"\\u56db\\u6708\",\"\\u4e94\\u6708\",\"\\u516d\\u6708\",\"\\u4e03\\u6708\",\"\\u516b\\u6708\",\"\\u4e5d\\u6708\",\"\\u5341\\u6708\",\"\\u5341\\u4e00\\u6708\",\"\\u5341\\u4e8c\\u6708\"][this.toChineseMonth(r,n)-1];return this.isIntercalaryMonth(r,n)&&(a=\"\\u95f0\"+a),a},monthNamesShort:function(t){if(\"string\"==typeof t){var e=t.match(u);return e?e[0]:\"\"}var r=this._validateYear(t),n=t.month(),a=[\"\\u4e00\",\"\\u4e8c\",\"\\u4e09\",\"\\u56db\",\"\\u4e94\",\"\\u516d\",\"\\u4e03\",\"\\u516b\",\"\\u4e5d\",\"\\u5341\",\"\\u5341\\u4e00\",\"\\u5341\\u4e8c\"][this.toChineseMonth(r,n)-1];return this.isIntercalaryMonth(r,n)&&(a=\"\\u95f0\"+a),a},parseMonth:function(t,e){t=this._validateYear(t);var r,n=parseInt(e);if(isNaN(n))\"\\u95f0\"===e[0]&&(r=!0,e=e.substring(1)),\"\\u6708\"===e[e.length-1]&&(e=e.substring(0,e.length-1)),n=1+[\"\\u4e00\",\"\\u4e8c\",\"\\u4e09\",\"\\u56db\",\"\\u4e94\",\"\\u516d\",\"\\u4e03\",\"\\u516b\",\"\\u4e5d\",\"\\u5341\",\"\\u5341\\u4e00\",\"\\u5341\\u4e8c\"].indexOf(e);else{var a=e[e.length-1];r=\"i\"===a||\"I\"===a}return this.toMonthIndex(t,n,r)},dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:1,isRTL:!1}},_validateYear:function(t,e){if(t.year&&(t=t.year()),\"number\"!=typeof t||t<1888||t>2111)throw e.replace(/\\{0\\}/,this.local.name);return t},toMonthIndex:function(t,e,r){var a=this.intercalaryMonth(t);if(r&&e!==a||e<1||e>12)throw n.local.invalidMonth.replace(/\\{0\\}/,this.local.name);return a?!r&&e<=a?e-1:e:e-1},toChineseMonth:function(t,e){t.year&&(e=(t=t.year()).month());var r=this.intercalaryMonth(t);if(e<0||e>(r?12:11))throw n.local.invalidMonth.replace(/\\{0\\}/,this.local.name);return r?e<r?e+1:e:e+1},intercalaryMonth:function(t){return t=this._validateYear(t),h[t-h[0]]>>13},isIntercalaryMonth:function(t,e){t.year&&(e=(t=t.year()).month());var r=this.intercalaryMonth(t);return!!r&&r===e},leapYear:function(t){return 0!==this.intercalaryMonth(t)},weekOfYear:function(t,e,r){var a,o=this._validateYear(t,n.local.invalidyear),s=f[o-f[0]],l=s>>9&4095,c=s>>5&15,u=31&s;(a=i.newDate(l,c,u)).add(4-(a.dayOfWeek()||7),\"d\");var h=this.toJD(t,e,r)-a.toJD();return 1+Math.floor(h/7)},monthsInYear:function(t){return this.leapYear(t)?13:12},daysInMonth:function(t,e){t.year&&(e=t.month(),t=t.year()),t=this._validateYear(t);var r=h[t-h[0]];if(e>(r>>13?12:11))throw n.local.invalidMonth.replace(/\\{0\\}/,this.local.name);return r&1<<12-e?30:29},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var a=this._validate(t,s,r,n.local.invalidDate);t=this._validateYear(a.year()),e=a.month(),r=a.day();var o=this.isIntercalaryMonth(t,e),s=this.toChineseMonth(t,e),l=function(t,e,r,n,a){var i,o,s;if(\"object\"==typeof t)o=t,i=e||{};else{var l=\"number\"==typeof t&&t>=1888&&t<=2111;if(!l)throw new Error(\"Lunar year outside range 1888-2111\");var c=\"number\"==typeof e&&e>=1&&e<=12;if(!c)throw new Error(\"Lunar month outside range 1 - 12\");var u,p=\"number\"==typeof r&&r>=1&&r<=30;if(!p)throw new Error(\"Lunar day outside range 1 - 30\");\"object\"==typeof n?(u=!1,i=n):(u=!!n,i=a||{}),o={year:t,month:e,day:r,isIntercalary:u}}s=o.day-1;var d,g=h[o.year-h[0]],v=g>>13;d=v?o.month>v?o.month:o.isIntercalary?o.month:o.month-1:o.month-1;for(var m=0;m<d;m++){var y=g&1<<12-m?30:29;s+=y}var x=f[o.year-f[0]],b=new Date(x>>9&4095,(x>>5&15)-1,(31&x)+s);return i.year=b.getFullYear(),i.month=1+b.getMonth(),i.day=b.getDate(),i}(t,s,r,o);return i.toJD(l.year,l.month,l.day)},fromJD:function(t){var e=i.fromJD(t),r=function(t,e,r,n){var a,i;if(\"object\"==typeof t)a=t,i=e||{};else{var o=\"number\"==typeof t&&t>=1888&&t<=2111;if(!o)throw new Error(\"Solar year outside range 1888-2111\");var s=\"number\"==typeof e&&e>=1&&e<=12;if(!s)throw new Error(\"Solar month outside range 1 - 12\");var l=\"number\"==typeof r&&r>=1&&r<=31;if(!l)throw new Error(\"Solar day outside range 1 - 31\");a={year:t,month:e,day:r},i=n||{}}var c=f[a.year-f[0]],u=a.year<<9|a.month<<5|a.day;i.year=u>=c?a.year:a.year-1,c=f[i.year-f[0]];var p,d=new Date(c>>9&4095,(c>>5&15)-1,31&c),g=new Date(a.year,a.month-1,a.day);p=Math.round((g-d)/864e5);var v,m=h[i.year-h[0]];for(v=0;v<13;v++){var y=m&1<<12-v?30:29;if(p<y)break;p-=y}var x=m>>13;!x||v<x?(i.isIntercalary=!1,i.month=1+v):v===x?(i.isIntercalary=!0,i.month=v):(i.isIntercalary=!1,i.month=v);return i.day=1+p,i}(e.year(),e.month(),e.day()),n=this.toMonthIndex(r.year,r.month,r.isIntercalary);return this.newDate(r.year,n,r.day)},fromString:function(t){var e=t.match(s),r=this._validateYear(+e[1]),n=+e[2],a=!!e[3],i=this.toMonthIndex(r,n,a),o=+e[4];return this.newDate(r,i,o)},add:function(t,e,r){var n=t.year(),a=t.month(),i=this.isIntercalaryMonth(n,a),s=this.toChineseMonth(n,a),l=Object.getPrototypeOf(o.prototype).add.call(this,t,e,r);if(\"y\"===r){var c=l.year(),u=l.month(),h=this.isIntercalaryMonth(c,s),f=i&&h?this.toMonthIndex(c,s,!0):this.toMonthIndex(c,s,!1);f!==u&&l.month(f)}return l}});var s=/^\\s*(-?\\d\\d\\d\\d|\\d\\d)[-/](\\d?\\d)([iI]?)[-/](\\d?\\d)/m,l=/^\\d?\\d[iI]?/m,c=/^\\u95f0?\\u5341?[\\u4e00\\u4e8c\\u4e09\\u56db\\u4e94\\u516d\\u4e03\\u516b\\u4e5d]?\\u6708/m,u=/^\\u95f0?\\u5341?[\\u4e00\\u4e8c\\u4e09\\u56db\\u4e94\\u516d\\u4e03\\u516b\\u4e5d]?/m;n.calendars.chinese=o;var h=[1887,5780,5802,19157,2742,50359,1198,2646,46378,7466,3412,30122,5482,67949,2396,5294,43597,6732,6954,36181,2772,4954,18781,2396,54427,5274,6730,47781,5800,6868,21210,4790,59703,2350,5270,46667,3402,3496,38325,1388,4782,18735,2350,52374,6804,7498,44457,2906,1388,29294,4700,63789,6442,6804,56138,5802,2772,38235,1210,4698,22827,5418,63125,3476,5802,43701,2484,5302,27223,2646,70954,7466,3412,54698,5482,2412,38062,5294,2636,32038,6954,60245,2772,4826,43357,2394,5274,39501,6730,72357,5800,5844,53978,4790,2358,38039,5270,87627,3402,3496,54708,5484,4782,43311,2350,3222,27978,7498,68965,2904,5484,45677,4700,6444,39573,6804,6986,19285,2772,62811,1210,4698,47403,5418,5780,38570,5546,76469,2420,5302,51799,2646,5414,36501,3412,5546,18869,2412,54446,5276,6732,48422,6822,2900,28010,4826,92509,2394,5274,55883,6730,6820,47956,5812,2778,18779,2358,62615,5270,5450,46757,3492,5556,27318,4718,67887,2350,3222,52554,7498,3428,38252,5468,4700,31022,6444,64149,6804,6986,43861,2772,5338,35421,2650,70955,5418,5780,54954,5546,2740,38074,5302,2646,29991,3366,61011,3412,5546,43445,2412,5294,35406,6732,72998,6820,6996,52586,2778,2396,38045,5274,6698,23333,6820,64338,5812,2746,43355,2358,5270,39499,5450,79525,3492,5548],f=[1887,966732,967231,967733,968265,968766,969297,969798,970298,970829,971330,971830,972362,972863,973395,973896,974397,974928,975428,975929,976461,976962,977462,977994,978494,979026,979526,980026,980558,981059,981559,982091,982593,983124,983624,984124,984656,985157,985656,986189,986690,987191,987722,988222,988753,989254,989754,990286,990788,991288,991819,992319,992851,993352,993851,994383,994885,995385,995917,996418,996918,997450,997949,998481,998982,999483,1000014,1000515,1001016,1001548,1002047,1002578,1003080,1003580,1004111,1004613,1005113,1005645,1006146,1006645,1007177,1007678,1008209,1008710,1009211,1009743,1010243,1010743,1011275,1011775,1012306,1012807,1013308,1013840,1014341,1014841,1015373,1015874,1016404,1016905,1017405,1017937,1018438,1018939,1019471,1019972,1020471,1021002,1021503,1022035,1022535,1023036,1023568,1024069,1024568,1025100,1025601,1026102,1026633,1027133,1027666,1028167,1028666,1029198,1029699,1030199,1030730,1031231,1031763,1032264,1032764,1033296,1033797,1034297,1034828,1035329,1035830,1036362,1036861,1037393,1037894,1038394,1038925,1039427,1039927,1040459,1040959,1041491,1041992,1042492,1043023,1043524,1044024,1044556,1045057,1045558,1046090,1046590,1047121,1047622,1048122,1048654,1049154,1049655,1050187,1050689,1051219,1051720,1052220,1052751,1053252,1053752,1054284,1054786,1055285,1055817,1056317,1056849,1057349,1057850,1058382,1058883,1059383,1059915,1060415,1060947,1061447,1061947,1062479,1062981,1063480,1064012,1064514,1065014,1065545,1066045,1066577,1067078,1067578,1068110,1068611,1069112,1069642,1070142,1070674,1071175,1071675,1072207,1072709,1073209,1073740,1074241,1074741,1075273,1075773,1076305,1076807,1077308,1077839,1078340,1078840,1079372,1079871,1080403,1080904]},{\"../main\":570,\"object-assign\":456}],557:[function(t,e,r){var n=t(\"../main\"),a=t(\"object-assign\");function i(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}i.prototype=new n.baseCalendar,a(i.prototype,{name:\"Coptic\",jdEpoch:1825029.5,daysPerMonth:[30,30,30,30,30,30,30,30,30,30,30,30,5],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Coptic\",epochs:[\"BAM\",\"AM\"],monthNames:[\"Thout\",\"Paopi\",\"Hathor\",\"Koiak\",\"Tobi\",\"Meshir\",\"Paremhat\",\"Paremoude\",\"Pashons\",\"Paoni\",\"Epip\",\"Mesori\",\"Pi Kogi Enavot\"],monthNamesShort:[\"Tho\",\"Pao\",\"Hath\",\"Koi\",\"Tob\",\"Mesh\",\"Pat\",\"Pad\",\"Pash\",\"Pao\",\"Epi\",\"Meso\",\"PiK\"],dayNames:[\"Tkyriaka\",\"Pesnau\",\"Pshoment\",\"Peftoou\",\"Ptiou\",\"Psoou\",\"Psabbaton\"],dayNamesShort:[\"Tky\",\"Pes\",\"Psh\",\"Pef\",\"Pti\",\"Pso\",\"Psa\"],dayNamesMin:[\"Tk\",\"Pes\",\"Psh\",\"Pef\",\"Pt\",\"Pso\",\"Psa\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()+(e.year()<0?1:0))%4==3||t%4==-1},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear),13},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(13===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);return(t=a.year())<0&&t++,a.day()+30*(a.month()-1)+365*(t-1)+Math.floor(t/4)+this.jdEpoch-1},fromJD:function(t){var e=Math.floor(t)+.5-this.jdEpoch,r=Math.floor((e-Math.floor((e+366)/1461))/365)+1;r<=0&&r--,e=Math.floor(t)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(e/30)+1,a=e-30*(n-1)+1;return this.newDate(r,n,a)}}),n.calendars.coptic=i},{\"../main\":570,\"object-assign\":456}],558:[function(t,e,r){var n=t(\"../main\"),a=t(\"object-assign\");function i(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}i.prototype=new n.baseCalendar,a(i.prototype,{name:\"Discworld\",jdEpoch:1721425.5,daysPerMonth:[16,32,32,32,32,32,32,32,32,32,32,32,32],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Discworld\",epochs:[\"BUC\",\"UC\"],monthNames:[\"Ick\",\"Offle\",\"February\",\"March\",\"April\",\"May\",\"June\",\"Grune\",\"August\",\"Spune\",\"Sektober\",\"Ember\",\"December\"],monthNamesShort:[\"Ick\",\"Off\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Gru\",\"Aug\",\"Spu\",\"Sek\",\"Emb\",\"Dec\"],dayNames:[\"Sunday\",\"Octeday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Oct\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Oc\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:2,isRTL:!1}},leapYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),13},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),400},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/8)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]},daysInWeek:function(){return 8},dayOfWeek:function(t,e,r){return(this._validate(t,e,r,n.local.invalidDate).day()+1)%8},weekDay:function(t,e,r){var n=this.dayOfWeek(t,e,r);return n>=2&&n<=6},extraInfo:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);return{century:o[Math.floor((a.year()-1)/100)+1]||\"\"}},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);return t=a.year()+(a.year()<0?1:0),e=a.month(),(r=a.day())+(e>1?16:0)+(e>2?32*(e-2):0)+400*(t-1)+this.jdEpoch-1},fromJD:function(t){t=Math.floor(t+.5)-Math.floor(this.jdEpoch)-1;var e=Math.floor(t/400)+1;t-=400*(e-1),t+=t>15?16:0;var r=Math.floor(t/32)+1,n=t-32*(r-1)+1;return this.newDate(e<=0?e-1:e,r,n)}});var o={20:\"Fruitbat\",21:\"Anchovy\"};n.calendars.discworld=i},{\"../main\":570,\"object-assign\":456}],559:[function(t,e,r){var n=t(\"../main\"),a=t(\"object-assign\");function i(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}i.prototype=new n.baseCalendar,a(i.prototype,{name:\"Ethiopian\",jdEpoch:1724220.5,daysPerMonth:[30,30,30,30,30,30,30,30,30,30,30,30,5],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Ethiopian\",epochs:[\"BEE\",\"EE\"],monthNames:[\"Meskerem\",\"Tikemet\",\"Hidar\",\"Tahesas\",\"Tir\",\"Yekatit\",\"Megabit\",\"Miazia\",\"Genbot\",\"Sene\",\"Hamle\",\"Nehase\",\"Pagume\"],monthNamesShort:[\"Mes\",\"Tik\",\"Hid\",\"Tah\",\"Tir\",\"Yek\",\"Meg\",\"Mia\",\"Gen\",\"Sen\",\"Ham\",\"Neh\",\"Pag\"],dayNames:[\"Ehud\",\"Segno\",\"Maksegno\",\"Irob\",\"Hamus\",\"Arb\",\"Kidame\"],dayNamesShort:[\"Ehu\",\"Seg\",\"Mak\",\"Iro\",\"Ham\",\"Arb\",\"Kid\"],dayNamesMin:[\"Eh\",\"Se\",\"Ma\",\"Ir\",\"Ha\",\"Ar\",\"Ki\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()+(e.year()<0?1:0))%4==3||t%4==-1},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear),13},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(13===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);return(t=a.year())<0&&t++,a.day()+30*(a.month()-1)+365*(t-1)+Math.floor(t/4)+this.jdEpoch-1},fromJD:function(t){var e=Math.floor(t)+.5-this.jdEpoch,r=Math.floor((e-Math.floor((e+366)/1461))/365)+1;r<=0&&r--,e=Math.floor(t)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(e/30)+1,a=e-30*(n-1)+1;return this.newDate(r,n,a)}}),n.calendars.ethiopian=i},{\"../main\":570,\"object-assign\":456}],560:[function(t,e,r){var n=t(\"../main\"),a=t(\"object-assign\");function i(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function o(t,e){return t-e*Math.floor(t/e)}i.prototype=new n.baseCalendar,a(i.prototype,{name:\"Hebrew\",jdEpoch:347995.5,daysPerMonth:[30,29,30,29,30,29,30,29,30,29,30,29,29],hasYearZero:!1,minMonth:1,firstMonth:7,minDay:1,regionalOptions:{\"\":{name:\"Hebrew\",epochs:[\"BAM\",\"AM\"],monthNames:[\"Nisan\",\"Iyar\",\"Sivan\",\"Tammuz\",\"Av\",\"Elul\",\"Tishrei\",\"Cheshvan\",\"Kislev\",\"Tevet\",\"Shevat\",\"Adar\",\"Adar II\"],monthNamesShort:[\"Nis\",\"Iya\",\"Siv\",\"Tam\",\"Av\",\"Elu\",\"Tis\",\"Che\",\"Kis\",\"Tev\",\"She\",\"Ada\",\"Ad2\"],dayNames:[\"Yom Rishon\",\"Yom Sheni\",\"Yom Shlishi\",\"Yom Revi'i\",\"Yom Chamishi\",\"Yom Shishi\",\"Yom Shabbat\"],dayNamesShort:[\"Ris\",\"She\",\"Shl\",\"Rev\",\"Cha\",\"Shi\",\"Sha\"],dayNamesMin:[\"Ri\",\"She\",\"Shl\",\"Re\",\"Ch\",\"Shi\",\"Sha\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return this._leapYear(e.year())},_leapYear:function(t){return o(7*(t=t<0?t+1:t)+1,19)<7},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),this._leapYear(t.year?t.year():t)?13:12},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){return t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year(),this.toJD(-1===t?1:t+1,7,1)-this.toJD(t,7,1)},daysInMonth:function(t,e){return t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,n.local.invalidMonth),12===e&&this.leapYear(t)?30:8===e&&5===o(this.daysInYear(t),10)?30:9===e&&3===o(this.daysInYear(t),10)?29:this.daysPerMonth[e-1]},weekDay:function(t,e,r){return 6!==this.dayOfWeek(t,e,r)},extraInfo:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);return{yearType:(this.leapYear(a)?\"embolismic\":\"common\")+\" \"+[\"deficient\",\"regular\",\"complete\"][this.daysInYear(a)%10-3]}},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);t=a.year(),e=a.month(),r=a.day();var i=t<=0?t+1:t,o=this.jdEpoch+this._delay1(i)+this._delay2(i)+r+1;if(e<7){for(var s=7;s<=this.monthsInYear(t);s++)o+=this.daysInMonth(t,s);for(s=1;s<e;s++)o+=this.daysInMonth(t,s)}else for(s=7;s<e;s++)o+=this.daysInMonth(t,s);return o},_delay1:function(t){var e=Math.floor((235*t-234)/19),r=12084+13753*e,n=29*e+Math.floor(r/25920);return o(3*(n+1),7)<3&&n++,n},_delay2:function(t){var e=this._delay1(t-1),r=this._delay1(t);return this._delay1(t+1)-r==356?2:r-e==382?1:0},fromJD:function(t){t=Math.floor(t)+.5;for(var e=Math.floor(98496*(t-this.jdEpoch)/35975351)-1;t>=this.toJD(-1===e?1:e+1,7,1);)e++;for(var r=t<this.toJD(e,1,1)?7:1;t>this.toJD(e,r,this.daysInMonth(e,r));)r++;var n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.hebrew=i},{\"../main\":570,\"object-assign\":456}],561:[function(t,e,r){var n=t(\"../main\"),a=t(\"object-assign\");function i(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}i.prototype=new n.baseCalendar,a(i.prototype,{name:\"Islamic\",jdEpoch:1948439.5,daysPerMonth:[30,29,30,29,30,29,30,29,30,29,30,29],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Islamic\",epochs:[\"BH\",\"AH\"],monthNames:[\"Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' al-thani\",\"Jumada al-awwal\",\"Jumada al-thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-ahad\",\"Yawm al-ithnayn\",\"Yawm ath-thulaathaa'\",\"Yawm al-arbi'aa'\",\"Yawm al-kham\\u012bs\",\"Yawm al-jum'a\",\"Yawm as-sabt\"],dayNamesShort:[\"Aha\",\"Ith\",\"Thu\",\"Arb\",\"Kha\",\"Jum\",\"Sab\"],dayNamesMin:[\"Ah\",\"It\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!1}},leapYear:function(t){return(11*this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year()+14)%30<11},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){return this.leapYear(t)?355:354},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);return t=a.year(),e=a.month(),t=t<=0?t+1:t,(r=a.day())+Math.ceil(29.5*(e-1))+354*(t-1)+Math.floor((3+11*t)/30)+this.jdEpoch-1},fromJD:function(t){t=Math.floor(t)+.5;var e=Math.floor((30*(t-this.jdEpoch)+10646)/10631);e=e<=0?e-1:e;var r=Math.min(12,Math.ceil((t-29-this.toJD(e,1,1))/29.5)+1),n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.islamic=i},{\"../main\":570,\"object-assign\":456}],562:[function(t,e,r){var n=t(\"../main\"),a=t(\"object-assign\");function i(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}i.prototype=new n.baseCalendar,a(i.prototype,{name:\"Julian\",jdEpoch:1721423.5,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Julian\",epochs:[\"BC\",\"AD\"],monthNames:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],monthNamesShort:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"mm/dd/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()<0?e.year()+1:e.year())%4==0},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(4-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);return t=a.year(),e=a.month(),r=a.day(),t<0&&t++,e<=2&&(t--,e+=12),Math.floor(365.25*(t+4716))+Math.floor(30.6001*(e+1))+r-1524.5},fromJD:function(t){var e=Math.floor(t+.5)+1524,r=Math.floor((e-122.1)/365.25),n=Math.floor(365.25*r),a=Math.floor((e-n)/30.6001),i=a-Math.floor(a<14?1:13),o=r-Math.floor(i>2?4716:4715),s=e-n-Math.floor(30.6001*a);return o<=0&&o--,this.newDate(o,i,s)}}),n.calendars.julian=i},{\"../main\":570,\"object-assign\":456}],563:[function(t,e,r){var n=t(\"../main\"),a=t(\"object-assign\");function i(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function o(t,e){return t-e*Math.floor(t/e)}function s(t,e){return o(t-1,e)+1}i.prototype=new n.baseCalendar,a(i.prototype,{name:\"Mayan\",jdEpoch:584282.5,hasYearZero:!0,minMonth:0,firstMonth:0,minDay:0,regionalOptions:{\"\":{name:\"Mayan\",epochs:[\"\",\"\"],monthNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],monthNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],dayNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesMin:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],digits:null,dateFormat:\"YYYY.m.d\",firstDay:0,isRTL:!1,haabMonths:[\"Pop\",\"Uo\",\"Zip\",\"Zotz\",\"Tzec\",\"Xul\",\"Yaxkin\",\"Mol\",\"Chen\",\"Yax\",\"Zac\",\"Ceh\",\"Mac\",\"Kankin\",\"Muan\",\"Pax\",\"Kayab\",\"Cumku\",\"Uayeb\"],tzolkinMonths:[\"Imix\",\"Ik\",\"Akbal\",\"Kan\",\"Chicchan\",\"Cimi\",\"Manik\",\"Lamat\",\"Muluc\",\"Oc\",\"Chuen\",\"Eb\",\"Ben\",\"Ix\",\"Men\",\"Cib\",\"Caban\",\"Etznab\",\"Cauac\",\"Ahau\"]}},leapYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},formatYear:function(t){t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year();var e=Math.floor(t/400);return t%=400,t+=t<0?400:0,e+\".\"+Math.floor(t/20)+\".\"+t%20},forYear:function(t){if((t=t.split(\".\")).length<3)throw\"Invalid Mayan year\";for(var e=0,r=0;r<t.length;r++){var n=parseInt(t[r],10);if(Math.abs(n)>19||r>0&&n<0)throw\"Invalid Mayan year\";e=20*e+n}return e},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),18},weekOfYear:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),0},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),360},daysInMonth:function(t,e){return this._validate(t,e,this.minDay,n.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate).day()},weekDay:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),!0},extraInfo:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate).toJD(),i=this._toHaab(a),o=this._toTzolkin(a);return{haabMonthName:this.local.haabMonths[i[0]-1],haabMonth:i[0],haabDay:i[1],tzolkinDayName:this.local.tzolkinMonths[o[0]-1],tzolkinDay:o[0],tzolkinTrecena:o[1]}},_toHaab:function(t){var e=o((t-=this.jdEpoch)+8+340,365);return[Math.floor(e/20)+1,o(e,20)]},_toTzolkin:function(t){return[s((t-=this.jdEpoch)+20,20),s(t+4,13)]},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);return a.day()+20*a.month()+360*a.year()+this.jdEpoch},fromJD:function(t){t=Math.floor(t)+.5-this.jdEpoch;var e=Math.floor(t/360);t%=360,t+=t<0?360:0;var r=Math.floor(t/20),n=t%20;return this.newDate(e,r,n)}}),n.calendars.mayan=i},{\"../main\":570,\"object-assign\":456}],564:[function(t,e,r){var n=t(\"../main\"),a=t(\"object-assign\");function i(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}i.prototype=new n.baseCalendar;var o=n.instance(\"gregorian\");a(i.prototype,{name:\"Nanakshahi\",jdEpoch:2257673.5,daysPerMonth:[31,31,31,31,31,30,30,30,30,30,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Nanakshahi\",epochs:[\"BN\",\"AN\"],monthNames:[\"Chet\",\"Vaisakh\",\"Jeth\",\"Harh\",\"Sawan\",\"Bhadon\",\"Assu\",\"Katak\",\"Maghar\",\"Poh\",\"Magh\",\"Phagun\"],monthNamesShort:[\"Che\",\"Vai\",\"Jet\",\"Har\",\"Saw\",\"Bha\",\"Ass\",\"Kat\",\"Mgr\",\"Poh\",\"Mgh\",\"Pha\"],dayNames:[\"Somvaar\",\"Mangalvar\",\"Budhvaar\",\"Veervaar\",\"Shukarvaar\",\"Sanicharvaar\",\"Etvaar\"],dayNamesShort:[\"Som\",\"Mangal\",\"Budh\",\"Veer\",\"Shukar\",\"Sanichar\",\"Et\"],dayNamesMin:[\"So\",\"Ma\",\"Bu\",\"Ve\",\"Sh\",\"Sa\",\"Et\"],digits:null,dateFormat:\"dd-mm-yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear);return o.leapYear(e.year()+(e.year()<1?1:0)+1469)},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(1-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidMonth);(t=a.year())<0&&t++;for(var i=a.day(),s=1;s<a.month();s++)i+=this.daysPerMonth[s-1];return i+o.toJD(t+1468,3,13)},fromJD:function(t){t=Math.floor(t+.5);for(var e=Math.floor((t-(this.jdEpoch-1))/366);t>=this.toJD(e+1,1,1);)e++;for(var r=t-Math.floor(this.toJD(e,1,1)+.5)+1,n=1;r>this.daysInMonth(e,n);)r-=this.daysInMonth(e,n),n++;return this.newDate(e,n,r)}}),n.calendars.nanakshahi=i},{\"../main\":570,\"object-assign\":456}],565:[function(t,e,r){var n=t(\"../main\"),a=t(\"object-assign\");function i(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}i.prototype=new n.baseCalendar,a(i.prototype,{name:\"Nepali\",jdEpoch:1700709.5,daysPerMonth:[31,31,32,32,31,30,30,29,30,29,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,daysPerYear:365,regionalOptions:{\"\":{name:\"Nepali\",epochs:[\"BBS\",\"ABS\"],monthNames:[\"Baisakh\",\"Jestha\",\"Ashadh\",\"Shrawan\",\"Bhadra\",\"Ashwin\",\"Kartik\",\"Mangsir\",\"Paush\",\"Mangh\",\"Falgun\",\"Chaitra\"],monthNamesShort:[\"Bai\",\"Je\",\"As\",\"Shra\",\"Bha\",\"Ash\",\"Kar\",\"Mang\",\"Pau\",\"Ma\",\"Fal\",\"Chai\"],dayNames:[\"Aaitabaar\",\"Sombaar\",\"Manglbaar\",\"Budhabaar\",\"Bihibaar\",\"Shukrabaar\",\"Shanibaar\"],dayNamesShort:[\"Aaita\",\"Som\",\"Mangl\",\"Budha\",\"Bihi\",\"Shukra\",\"Shani\"],dayNamesMin:[\"Aai\",\"So\",\"Man\",\"Bu\",\"Bi\",\"Shu\",\"Sha\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:1,isRTL:!1}},leapYear:function(t){return this.daysInYear(t)!==this.daysPerYear},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){if(t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year(),\"undefined\"==typeof this.NEPALI_CALENDAR_DATA[t])return this.daysPerYear;for(var e=0,r=this.minMonth;r<=12;r++)e+=this.NEPALI_CALENDAR_DATA[t][r];return e},daysInMonth:function(t,e){return t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,n.local.invalidMonth),\"undefined\"==typeof this.NEPALI_CALENDAR_DATA[t]?this.daysPerMonth[e-1]:this.NEPALI_CALENDAR_DATA[t][e]},weekDay:function(t,e,r){return 6!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);t=a.year(),e=a.month(),r=a.day();var i=n.instance(),o=0,s=e,l=t;this._createMissingCalendarData(t);var c=t-(s>9||9===s&&r>=this.NEPALI_CALENDAR_DATA[l][0]?56:57);for(9!==e&&(o=r,s--);9!==s;)s<=0&&(s=12,l--),o+=this.NEPALI_CALENDAR_DATA[l][s],s--;return 9===e?(o+=r-this.NEPALI_CALENDAR_DATA[l][0])<0&&(o+=i.daysInYear(c)):o+=this.NEPALI_CALENDAR_DATA[l][9]-this.NEPALI_CALENDAR_DATA[l][0],i.newDate(c,1,1).add(o,\"d\").toJD()},fromJD:function(t){var e=n.instance().fromJD(t),r=e.year(),a=e.dayOfYear(),i=r+56;this._createMissingCalendarData(i);for(var o=9,s=this.NEPALI_CALENDAR_DATA[i][0],l=this.NEPALI_CALENDAR_DATA[i][o]-s+1;a>l;)++o>12&&(o=1,i++),l+=this.NEPALI_CALENDAR_DATA[i][o];var c=this.NEPALI_CALENDAR_DATA[i][o]-(l-a);return this.newDate(i,o,c)},_createMissingCalendarData:function(t){var e=this.daysPerMonth.slice(0);e.unshift(17);for(var r=t-1;r<t+2;r++)\"undefined\"==typeof this.NEPALI_CALENDAR_DATA[r]&&(this.NEPALI_CALENDAR_DATA[r]=e)},NEPALI_CALENDAR_DATA:{1970:[18,31,31,32,31,31,31,30,29,30,29,30,30],1971:[18,31,31,32,31,32,30,30,29,30,29,30,30],1972:[17,31,32,31,32,31,30,30,30,29,29,30,30],1973:[19,30,32,31,32,31,30,30,30,29,30,29,31],1974:[19,31,31,32,30,31,31,30,29,30,29,30,30],1975:[18,31,31,32,32,30,31,30,29,30,29,30,30],1976:[17,31,32,31,32,31,30,30,30,29,29,30,31],1977:[18,31,32,31,32,31,31,29,30,29,30,29,31],1978:[18,31,31,32,31,31,31,30,29,30,29,30,30],1979:[18,31,31,32,32,31,30,30,29,30,29,30,30],1980:[17,31,32,31,32,31,30,30,30,29,29,30,31],1981:[18,31,31,31,32,31,31,29,30,30,29,30,30],1982:[18,31,31,32,31,31,31,30,29,30,29,30,30],1983:[18,31,31,32,32,31,30,30,29,30,29,30,30],1984:[17,31,32,31,32,31,30,30,30,29,29,30,31],1985:[18,31,31,31,32,31,31,29,30,30,29,30,30],1986:[18,31,31,32,31,31,31,30,29,30,29,30,30],1987:[18,31,32,31,32,31,30,30,29,30,29,30,30],1988:[17,31,32,31,32,31,30,30,30,29,29,30,31],1989:[18,31,31,31,32,31,31,30,29,30,29,30,30],1990:[18,31,31,32,31,31,31,30,29,30,29,30,30],1991:[18,31,32,31,32,31,30,30,29,30,29,30,30],1992:[17,31,32,31,32,31,30,30,30,29,30,29,31],1993:[18,31,31,31,32,31,31,30,29,30,29,30,30],1994:[18,31,31,32,31,31,31,30,29,30,29,30,30],1995:[17,31,32,31,32,31,30,30,30,29,29,30,30],1996:[17,31,32,31,32,31,30,30,30,29,30,29,31],1997:[18,31,31,32,31,31,31,30,29,30,29,30,30],1998:[18,31,31,32,31,31,31,30,29,30,29,30,30],1999:[17,31,32,31,32,31,30,30,30,29,29,30,31],2000:[17,30,32,31,32,31,30,30,30,29,30,29,31],2001:[18,31,31,32,31,31,31,30,29,30,29,30,30],2002:[18,31,31,32,32,31,30,30,29,30,29,30,30],2003:[17,31,32,31,32,31,30,30,30,29,29,30,31],2004:[17,30,32,31,32,31,30,30,30,29,30,29,31],2005:[18,31,31,32,31,31,31,30,29,30,29,30,30],2006:[18,31,31,32,32,31,30,30,29,30,29,30,30],2007:[17,31,32,31,32,31,30,30,30,29,29,30,31],2008:[17,31,31,31,32,31,31,29,30,30,29,29,31],2009:[18,31,31,32,31,31,31,30,29,30,29,30,30],2010:[18,31,31,32,32,31,30,30,29,30,29,30,30],2011:[17,31,32,31,32,31,30,30,30,29,29,30,31],2012:[17,31,31,31,32,31,31,29,30,30,29,30,30],2013:[18,31,31,32,31,31,31,30,29,30,29,30,30],2014:[18,31,31,32,32,31,30,30,29,30,29,30,30],2015:[17,31,32,31,32,31,30,30,30,29,29,30,31],2016:[17,31,31,31,32,31,31,29,30,30,29,30,30],2017:[18,31,31,32,31,31,31,30,29,30,29,30,30],2018:[18,31,32,31,32,31,30,30,29,30,29,30,30],2019:[17,31,32,31,32,31,30,30,30,29,30,29,31],2020:[17,31,31,31,32,31,31,30,29,30,29,30,30],2021:[18,31,31,32,31,31,31,30,29,30,29,30,30],2022:[17,31,32,31,32,31,30,30,30,29,29,30,30],2023:[17,31,32,31,32,31,30,30,30,29,30,29,31],2024:[17,31,31,31,32,31,31,30,29,30,29,30,30],2025:[18,31,31,32,31,31,31,30,29,30,29,30,30],2026:[17,31,32,31,32,31,30,30,30,29,29,30,31],2027:[17,30,32,31,32,31,30,30,30,29,30,29,31],2028:[17,31,31,32,31,31,31,30,29,30,29,30,30],2029:[18,31,31,32,31,32,30,30,29,30,29,30,30],2030:[17,31,32,31,32,31,30,30,30,30,30,30,31],2031:[17,31,32,31,32,31,31,31,31,31,31,31,31],2032:[17,32,32,32,32,32,32,32,32,32,32,32,32],2033:[18,31,31,32,32,31,30,30,29,30,29,30,30],2034:[17,31,32,31,32,31,30,30,30,29,29,30,31],2035:[17,30,32,31,32,31,31,29,30,30,29,29,31],2036:[17,31,31,32,31,31,31,30,29,30,29,30,30],2037:[18,31,31,32,32,31,30,30,29,30,29,30,30],2038:[17,31,32,31,32,31,30,30,30,29,29,30,31],2039:[17,31,31,31,32,31,31,29,30,30,29,30,30],2040:[17,31,31,32,31,31,31,30,29,30,29,30,30],2041:[18,31,31,32,32,31,30,30,29,30,29,30,30],2042:[17,31,32,31,32,31,30,30,30,29,29,30,31],2043:[17,31,31,31,32,31,31,29,30,30,29,30,30],2044:[17,31,31,32,31,31,31,30,29,30,29,30,30],2045:[18,31,32,31,32,31,30,30,29,30,29,30,30],2046:[17,31,32,31,32,31,30,30,30,29,29,30,31],2047:[17,31,31,31,32,31,31,30,29,30,29,30,30],2048:[17,31,31,32,31,31,31,30,29,30,29,30,30],2049:[17,31,32,31,32,31,30,30,30,29,29,30,30],2050:[17,31,32,31,32,31,30,30,30,29,30,29,31],2051:[17,31,31,31,32,31,31,30,29,30,29,30,30],2052:[17,31,31,32,31,31,31,30,29,30,29,30,30],2053:[17,31,32,31,32,31,30,30,30,29,29,30,30],2054:[17,31,32,31,32,31,30,30,30,29,30,29,31],2055:[17,31,31,32,31,31,31,30,29,30,30,29,30],2056:[17,31,31,32,31,32,30,30,29,30,29,30,30],2057:[17,31,32,31,32,31,30,30,30,29,29,30,31],2058:[17,30,32,31,32,31,30,30,30,29,30,29,31],2059:[17,31,31,32,31,31,31,30,29,30,29,30,30],2060:[17,31,31,32,32,31,30,30,29,30,29,30,30],2061:[17,31,32,31,32,31,30,30,30,29,29,30,31],2062:[17,30,32,31,32,31,31,29,30,29,30,29,31],2063:[17,31,31,32,31,31,31,30,29,30,29,30,30],2064:[17,31,31,32,32,31,30,30,29,30,29,30,30],2065:[17,31,32,31,32,31,30,30,30,29,29,30,31],2066:[17,31,31,31,32,31,31,29,30,30,29,29,31],2067:[17,31,31,32,31,31,31,30,29,30,29,30,30],2068:[17,31,31,32,32,31,30,30,29,30,29,30,30],2069:[17,31,32,31,32,31,30,30,30,29,29,30,31],2070:[17,31,31,31,32,31,31,29,30,30,29,30,30],2071:[17,31,31,32,31,31,31,30,29,30,29,30,30],2072:[17,31,32,31,32,31,30,30,29,30,29,30,30],2073:[17,31,32,31,32,31,30,30,30,29,29,30,31],2074:[17,31,31,31,32,31,31,30,29,30,29,30,30],2075:[17,31,31,32,31,31,31,30,29,30,29,30,30],2076:[16,31,32,31,32,31,30,30,30,29,29,30,30],2077:[17,31,32,31,32,31,30,30,30,29,30,29,31],2078:[17,31,31,31,32,31,31,30,29,30,29,30,30],2079:[17,31,31,32,31,31,31,30,29,30,29,30,30],2080:[16,31,32,31,32,31,30,30,30,29,29,30,30],2081:[17,31,31,32,32,31,30,30,30,29,30,30,30],2082:[17,31,32,31,32,31,30,30,30,29,30,30,30],2083:[17,31,31,32,31,31,30,30,30,29,30,30,30],2084:[17,31,31,32,31,31,30,30,30,29,30,30,30],2085:[17,31,32,31,32,31,31,30,30,29,30,30,30],2086:[17,31,32,31,32,31,30,30,30,29,30,30,30],2087:[16,31,31,32,31,31,31,30,30,29,30,30,30],2088:[16,30,31,32,32,30,31,30,30,29,30,30,30],2089:[17,31,32,31,32,31,30,30,30,29,30,30,30],2090:[17,31,32,31,32,31,30,30,30,29,30,30,30],2091:[16,31,31,32,31,31,31,30,30,29,30,30,30],2092:[16,31,31,32,32,31,30,30,30,29,30,30,30],2093:[17,31,32,31,32,31,30,30,30,29,30,30,30],2094:[17,31,31,32,31,31,30,30,30,29,30,30,30],2095:[17,31,31,32,31,31,31,30,29,30,30,30,30],2096:[17,30,31,32,32,31,30,30,29,30,29,30,30],2097:[17,31,32,31,32,31,30,30,30,29,30,30,30],2098:[17,31,31,32,31,31,31,29,30,29,30,30,31],2099:[17,31,31,32,31,31,31,30,29,29,30,30,30],2100:[17,31,32,31,32,30,31,30,29,30,29,30,30]}}),n.calendars.nepali=i},{\"../main\":570,\"object-assign\":456}],566:[function(t,e,r){var n=t(\"../main\"),a=t(\"object-assign\");function i(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function o(t,e){return t-e*Math.floor(t/e)}i.prototype=new n.baseCalendar,a(i.prototype,{name:\"Persian\",jdEpoch:1948320.5,daysPerMonth:[31,31,31,31,31,31,30,30,30,30,30,29],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Persian\",epochs:[\"BP\",\"AP\"],monthNames:[\"Farvardin\",\"Ordibehesht\",\"Khordad\",\"Tir\",\"Mordad\",\"Shahrivar\",\"Mehr\",\"Aban\",\"Azar\",\"Day\",\"Bahman\",\"Esfand\"],monthNamesShort:[\"Far\",\"Ord\",\"Kho\",\"Tir\",\"Mor\",\"Sha\",\"Meh\",\"Aba\",\"Aza\",\"Day\",\"Bah\",\"Esf\"],dayNames:[\"Yekshambe\",\"Doshambe\",\"Seshambe\",\"Ch\\xe6harshambe\",\"Panjshambe\",\"Jom'e\",\"Shambe\"],dayNamesShort:[\"Yek\",\"Do\",\"Se\",\"Ch\\xe6\",\"Panj\",\"Jom\",\"Sha\"],dayNamesMin:[\"Ye\",\"Do\",\"Se\",\"Ch\",\"Pa\",\"Jo\",\"Sh\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 682*((e.year()-(e.year()>0?474:473))%2820+474+38)%2816<682},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-(n.dayOfWeek()+1)%7,\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);t=a.year(),e=a.month(),r=a.day();var i=t-(t>=0?474:473),s=474+o(i,2820);return r+(e<=7?31*(e-1):30*(e-1)+6)+Math.floor((682*s-110)/2816)+365*(s-1)+1029983*Math.floor(i/2820)+this.jdEpoch-1},fromJD:function(t){var e=(t=Math.floor(t)+.5)-this.toJD(475,1,1),r=Math.floor(e/1029983),n=o(e,1029983),a=2820;if(1029982!==n){var i=Math.floor(n/366),s=o(n,366);a=Math.floor((2134*i+2816*s+2815)/1028522)+i+1}var l=a+2820*r+474;l=l<=0?l-1:l;var c=t-this.toJD(l,1,1)+1,u=c<=186?Math.ceil(c/31):Math.ceil((c-6)/30),h=t-this.toJD(l,u,1)+1;return this.newDate(l,u,h)}}),n.calendars.persian=i,n.calendars.jalali=i},{\"../main\":570,\"object-assign\":456}],567:[function(t,e,r){var n=t(\"../main\"),a=t(\"object-assign\"),i=n.instance();function o(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}o.prototype=new n.baseCalendar,a(o.prototype,{name:\"Taiwan\",jdEpoch:2419402.5,yearsOffset:1911,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Taiwan\",epochs:[\"BROC\",\"ROC\"],monthNames:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],monthNamesShort:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:1,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(e.year());return i.leapYear(t)},weekOfYear:function(t,e,r){var a=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(a.year());return i.weekOfYear(t,a.month(),a.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);t=this._t2gYear(a.year());return i.toJD(t,a.month(),a.day())},fromJD:function(t){var e=i.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)},_g2tYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)}}),n.calendars.taiwan=o},{\"../main\":570,\"object-assign\":456}],568:[function(t,e,r){var n=t(\"../main\"),a=t(\"object-assign\"),i=n.instance();function o(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}o.prototype=new n.baseCalendar,a(o.prototype,{name:\"Thai\",jdEpoch:1523098.5,yearsOffset:543,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Thai\",epochs:[\"BBE\",\"BE\"],monthNames:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],monthNamesShort:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(e.year());return i.leapYear(t)},weekOfYear:function(t,e,r){var a=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(a.year());return i.weekOfYear(t,a.month(),a.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);t=this._t2gYear(a.year());return i.toJD(t,a.month(),a.day())},fromJD:function(t){var e=i.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)},_g2tYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)}}),n.calendars.thai=o},{\"../main\":570,\"object-assign\":456}],569:[function(t,e,r){var n=t(\"../main\"),a=t(\"object-assign\");function i(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}i.prototype=new n.baseCalendar,a(i.prototype,{name:\"UmmAlQura\",hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Umm al-Qura\",epochs:[\"BH\",\"AH\"],monthNames:[\"Al-Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' Al-Thani\",\"Jumada Al-Awwal\",\"Jumada Al-Thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-Ahad\",\"Yawm al-Ithnain\",\"Yawm al-Thal\\u0101th\\u0101\\u2019\",\"Yawm al-Arba\\u2018\\u0101\\u2019\",\"Yawm al-Kham\\u012bs\",\"Yawm al-Jum\\u2018a\",\"Yawm al-Sabt\"],dayNamesMin:[\"Ah\",\"Ith\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!0}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 355===this.daysInYear(e.year())},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){for(var e=0,r=1;r<=12;r++)e+=this.daysInMonth(t,r);return e},daysInMonth:function(t,e){for(var r=this._validate(t,e,this.minDay,n.local.invalidMonth).toJD()-24e5+.5,a=0,i=0;i<o.length;i++){if(o[i]>r)return o[a]-o[a-1];a++}return 30},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate),i=12*(a.year()-1)+a.month()-15292;return a.day()+o[i-1]-1+24e5-.5},fromJD:function(t){for(var e=t-24e5+.5,r=0,n=0;n<o.length&&!(o[n]>e);n++)r++;var a=r+15292,i=Math.floor((a-1)/12),s=i+1,l=a-12*i,c=e-o[r-1]+1;return this.newDate(s,l,c)},isValid:function(t,e,r){var a=n.baseCalendar.prototype.isValid.apply(this,arguments);return a&&(a=(t=null!=t.year?t.year:t)>=1276&&t<=1500),a},_validate:function(t,e,r,a){var i=n.baseCalendar.prototype._validate.apply(this,arguments);if(i.year<1276||i.year>1500)throw a.replace(/\\{0\\}/,this.local.name);return i}}),n.calendars.ummalqura=i;var o=[20,50,79,109,138,168,197,227,256,286,315,345,374,404,433,463,492,522,551,581,611,641,670,700,729,759,788,818,847,877,906,936,965,995,1024,1054,1083,1113,1142,1172,1201,1231,1260,1290,1320,1350,1379,1409,1438,1468,1497,1527,1556,1586,1615,1645,1674,1704,1733,1763,1792,1822,1851,1881,1910,1940,1969,1999,2028,2058,2087,2117,2146,2176,2205,2235,2264,2294,2323,2353,2383,2413,2442,2472,2501,2531,2560,2590,2619,2649,2678,2708,2737,2767,2796,2826,2855,2885,2914,2944,2973,3003,3032,3062,3091,3121,3150,3180,3209,3239,3268,3298,3327,3357,3386,3416,3446,3476,3505,3535,3564,3594,3623,3653,3682,3712,3741,3771,3800,3830,3859,3889,3918,3948,3977,4007,4036,4066,4095,4125,4155,4185,4214,4244,4273,4303,4332,4362,4391,4421,4450,4480,4509,4539,4568,4598,4627,4657,4686,4716,4745,4775,4804,4834,4863,4893,4922,4952,4981,5011,5040,5070,5099,5129,5158,5188,5218,5248,5277,5307,5336,5366,5395,5425,5454,5484,5513,5543,5572,5602,5631,5661,5690,5720,5749,5779,5808,5838,5867,5897,5926,5956,5985,6015,6044,6074,6103,6133,6162,6192,6221,6251,6281,6311,6340,6370,6399,6429,6458,6488,6517,6547,6576,6606,6635,6665,6694,6724,6753,6783,6812,6842,6871,6901,6930,6960,6989,7019,7048,7078,7107,7137,7166,7196,7225,7255,7284,7314,7344,7374,7403,7433,7462,7492,7521,7551,7580,7610,7639,7669,7698,7728,7757,7787,7816,7846,7875,7905,7934,7964,7993,8023,8053,8083,8112,8142,8171,8201,8230,8260,8289,8319,8348,8378,8407,8437,8466,8496,8525,8555,8584,8614,8643,8673,8702,8732,8761,8791,8821,8850,8880,8909,8938,8968,8997,9027,9056,9086,9115,9145,9175,9205,9234,9264,9293,9322,9352,9381,9410,9440,9470,9499,9529,9559,9589,9618,9648,9677,9706,9736,9765,9794,9824,9853,9883,9913,9943,9972,10002,10032,10061,10090,10120,10149,10178,10208,10237,10267,10297,10326,10356,10386,10415,10445,10474,10504,10533,10562,10592,10621,10651,10680,10710,10740,10770,10799,10829,10858,10888,10917,10947,10976,11005,11035,11064,11094,11124,11153,11183,11213,11242,11272,11301,11331,11360,11389,11419,11448,11478,11507,11537,11567,11596,11626,11655,11685,11715,11744,11774,11803,11832,11862,11891,11921,11950,11980,12010,12039,12069,12099,12128,12158,12187,12216,12246,12275,12304,12334,12364,12393,12423,12453,12483,12512,12542,12571,12600,12630,12659,12688,12718,12747,12777,12807,12837,12866,12896,12926,12955,12984,13014,13043,13072,13102,13131,13161,13191,13220,13250,13280,13310,13339,13368,13398,13427,13456,13486,13515,13545,13574,13604,13634,13664,13693,13723,13752,13782,13811,13840,13870,13899,13929,13958,13988,14018,14047,14077,14107,14136,14166,14195,14224,14254,14283,14313,14342,14372,14401,14431,14461,14490,14520,14550,14579,14609,14638,14667,14697,14726,14756,14785,14815,14844,14874,14904,14933,14963,14993,15021,15051,15081,15110,15140,15169,15199,15228,15258,15287,15317,15347,15377,15406,15436,15465,15494,15524,15553,15582,15612,15641,15671,15701,15731,15760,15790,15820,15849,15878,15908,15937,15966,15996,16025,16055,16085,16114,16144,16174,16204,16233,16262,16292,16321,16350,16380,16409,16439,16468,16498,16528,16558,16587,16617,16646,16676,16705,16734,16764,16793,16823,16852,16882,16912,16941,16971,17001,17030,17060,17089,17118,17148,17177,17207,17236,17266,17295,17325,17355,17384,17414,17444,17473,17502,17532,17561,17591,17620,17650,17679,17709,17738,17768,17798,17827,17857,17886,17916,17945,17975,18004,18034,18063,18093,18122,18152,18181,18211,18241,18270,18300,18330,18359,18388,18418,18447,18476,18506,18535,18565,18595,18625,18654,18684,18714,18743,18772,18802,18831,18860,18890,18919,18949,18979,19008,19038,19068,19098,19127,19156,19186,19215,19244,19274,19303,19333,19362,19392,19422,19452,19481,19511,19540,19570,19599,19628,19658,19687,19717,19746,19776,19806,19836,19865,19895,19924,19954,19983,20012,20042,20071,20101,20130,20160,20190,20219,20249,20279,20308,20338,20367,20396,20426,20455,20485,20514,20544,20573,20603,20633,20662,20692,20721,20751,20780,20810,20839,20869,20898,20928,20957,20987,21016,21046,21076,21105,21135,21164,21194,21223,21253,21282,21312,21341,21371,21400,21430,21459,21489,21519,21548,21578,21607,21637,21666,21696,21725,21754,21784,21813,21843,21873,21902,21932,21962,21991,22021,22050,22080,22109,22138,22168,22197,22227,22256,22286,22316,22346,22375,22405,22434,22464,22493,22522,22552,22581,22611,22640,22670,22700,22730,22759,22789,22818,22848,22877,22906,22936,22965,22994,23024,23054,23083,23113,23143,23173,23202,23232,23261,23290,23320,23349,23379,23408,23438,23467,23497,23527,23556,23586,23616,23645,23674,23704,23733,23763,23792,23822,23851,23881,23910,23940,23970,23999,24029,24058,24088,24117,24147,24176,24206,24235,24265,24294,24324,24353,24383,24413,24442,24472,24501,24531,24560,24590,24619,24648,24678,24707,24737,24767,24796,24826,24856,24885,24915,24944,24974,25003,25032,25062,25091,25121,25150,25180,25210,25240,25269,25299,25328,25358,25387,25416,25446,25475,25505,25534,25564,25594,25624,25653,25683,25712,25742,25771,25800,25830,25859,25888,25918,25948,25977,26007,26037,26067,26096,26126,26155,26184,26214,26243,26272,26302,26332,26361,26391,26421,26451,26480,26510,26539,26568,26598,26627,26656,26686,26715,26745,26775,26805,26834,26864,26893,26923,26952,26982,27011,27041,27070,27099,27129,27159,27188,27218,27248,27277,27307,27336,27366,27395,27425,27454,27484,27513,27542,27572,27602,27631,27661,27691,27720,27750,27779,27809,27838,27868,27897,27926,27956,27985,28015,28045,28074,28104,28134,28163,28193,28222,28252,28281,28310,28340,28369,28399,28428,28458,28488,28517,28547,28577,28607,28636,28665,28695,28724,28754,28783,28813,28843,28872,28901,28931,28960,28990,29019,29049,29078,29108,29137,29167,29196,29226,29255,29285,29315,29345,29375,29404,29434,29463,29492,29522,29551,29580,29610,29640,29669,29699,29729,29759,29788,29818,29847,29876,29906,29935,29964,29994,30023,30053,30082,30112,30141,30171,30200,30230,30259,30289,30318,30348,30378,30408,30437,30467,30496,30526,30555,30585,30614,30644,30673,30703,30732,30762,30791,30821,30850,30880,30909,30939,30968,30998,31027,31057,31086,31116,31145,31175,31204,31234,31263,31293,31322,31352,31381,31411,31441,31471,31500,31530,31559,31589,31618,31648,31676,31706,31736,31766,31795,31825,31854,31884,31913,31943,31972,32002,32031,32061,32090,32120,32150,32180,32209,32239,32268,32298,32327,32357,32386,32416,32445,32475,32504,32534,32563,32593,32622,32652,32681,32711,32740,32770,32799,32829,32858,32888,32917,32947,32976,33006,33035,33065,33094,33124,33153,33183,33213,33243,33272,33302,33331,33361,33390,33420,33450,33479,33509,33539,33568,33598,33627,33657,33686,33716,33745,33775,33804,33834,33863,33893,33922,33952,33981,34011,34040,34069,34099,34128,34158,34187,34217,34247,34277,34306,34336,34365,34395,34424,34454,34483,34512,34542,34571,34601,34631,34660,34690,34719,34749,34778,34808,34837,34867,34896,34926,34955,34985,35015,35044,35074,35103,35133,35162,35192,35222,35251,35280,35310,35340,35370,35399,35429,35458,35488,35517,35547,35576,35605,35635,35665,35694,35723,35753,35782,35811,35841,35871,35901,35930,35960,35989,36019,36048,36078,36107,36136,36166,36195,36225,36254,36284,36314,36343,36373,36403,36433,36462,36492,36521,36551,36580,36610,36639,36669,36698,36728,36757,36786,36816,36845,36875,36904,36934,36963,36993,37022,37052,37081,37111,37141,37170,37200,37229,37259,37288,37318,37347,37377,37406,37436,37465,37495,37524,37554,37584,37613,37643,37672,37701,37731,37760,37790,37819,37849,37878,37908,37938,37967,37997,38027,38056,38085,38115,38144,38174,38203,38233,38262,38292,38322,38351,38381,38410,38440,38469,38499,38528,38558,38587,38617,38646,38676,38705,38735,38764,38794,38823,38853,38882,38912,38941,38971,39001,39030,39059,39089,39118,39148,39178,39208,39237,39267,39297,39326,39355,39385,39414,39444,39473,39503,39532,39562,39592,39621,39650,39680,39709,39739,39768,39798,39827,39857,39886,39916,39946,39975,40005,40035,40064,40094,40123,40153,40182,40212,40241,40271,40300,40330,40359,40389,40418,40448,40477,40507,40536,40566,40595,40625,40655,40685,40714,40744,40773,40803,40832,40862,40892,40921,40951,40980,41009,41039,41068,41098,41127,41157,41186,41216,41245,41275,41304,41334,41364,41393,41422,41452,41481,41511,41540,41570,41599,41629,41658,41688,41718,41748,41777,41807,41836,41865,41894,41924,41953,41983,42012,42042,42072,42102,42131,42161,42190,42220,42249,42279,42308,42337,42367,42397,42426,42456,42485,42515,42545,42574,42604,42633,42662,42692,42721,42751,42780,42810,42839,42869,42899,42929,42958,42988,43017,43046,43076,43105,43135,43164,43194,43223,43253,43283,43312,43342,43371,43401,43430,43460,43489,43519,43548,43578,43607,43637,43666,43696,43726,43755,43785,43814,43844,43873,43903,43932,43962,43991,44021,44050,44080,44109,44139,44169,44198,44228,44258,44287,44317,44346,44375,44405,44434,44464,44493,44523,44553,44582,44612,44641,44671,44700,44730,44759,44788,44818,44847,44877,44906,44936,44966,44996,45025,45055,45084,45114,45143,45172,45202,45231,45261,45290,45320,45350,45380,45409,45439,45468,45498,45527,45556,45586,45615,45644,45674,45704,45733,45763,45793,45823,45852,45882,45911,45940,45970,45999,46028,46058,46088,46117,46147,46177,46206,46236,46265,46295,46324,46354,46383,46413,46442,46472,46501,46531,46560,46590,46620,46649,46679,46708,46738,46767,46797,46826,46856,46885,46915,46944,46974,47003,47033,47063,47092,47122,47151,47181,47210,47240,47269,47298,47328,47357,47387,47417,47446,47476,47506,47535,47565,47594,47624,47653,47682,47712,47741,47771,47800,47830,47860,47890,47919,47949,47978,48008,48037,48066,48096,48125,48155,48184,48214,48244,48273,48303,48333,48362,48392,48421,48450,48480,48509,48538,48568,48598,48627,48657,48687,48717,48746,48776,48805,48834,48864,48893,48922,48952,48982,49011,49041,49071,49100,49130,49160,49189,49218,49248,49277,49306,49336,49365,49395,49425,49455,49484,49514,49543,49573,49602,49632,49661,49690,49720,49749,49779,49809,49838,49868,49898,49927,49957,49986,50016,50045,50075,50104,50133,50163,50192,50222,50252,50281,50311,50340,50370,50400,50429,50459,50488,50518,50547,50576,50606,50635,50665,50694,50724,50754,50784,50813,50843,50872,50902,50931,50960,50990,51019,51049,51078,51108,51138,51167,51197,51227,51256,51286,51315,51345,51374,51403,51433,51462,51492,51522,51552,51582,51611,51641,51670,51699,51729,51758,51787,51816,51846,51876,51906,51936,51965,51995,52025,52054,52083,52113,52142,52171,52200,52230,52260,52290,52319,52349,52379,52408,52438,52467,52497,52526,52555,52585,52614,52644,52673,52703,52733,52762,52792,52822,52851,52881,52910,52939,52969,52998,53028,53057,53087,53116,53146,53176,53205,53235,53264,53294,53324,53353,53383,53412,53441,53471,53500,53530,53559,53589,53619,53648,53678,53708,53737,53767,53796,53825,53855,53884,53913,53943,53973,54003,54032,54062,54092,54121,54151,54180,54209,54239,54268,54297,54327,54357,54387,54416,54446,54476,54505,54535,54564,54593,54623,54652,54681,54711,54741,54770,54800,54830,54859,54889,54919,54948,54977,55007,55036,55066,55095,55125,55154,55184,55213,55243,55273,55302,55332,55361,55391,55420,55450,55479,55508,55538,55567,55597,55627,55657,55686,55716,55745,55775,55804,55834,55863,55892,55922,55951,55981,56011,56040,56070,56100,56129,56159,56188,56218,56247,56276,56306,56335,56365,56394,56424,56454,56483,56513,56543,56572,56601,56631,56660,56690,56719,56749,56778,56808,56837,56867,56897,56926,56956,56985,57015,57044,57074,57103,57133,57162,57192,57221,57251,57280,57310,57340,57369,57399,57429,57458,57487,57517,57546,57576,57605,57634,57664,57694,57723,57753,57783,57813,57842,57871,57901,57930,57959,57989,58018,58048,58077,58107,58137,58167,58196,58226,58255,58285,58314,58343,58373,58402,58432,58461,58491,58521,58551,58580,58610,58639,58669,58698,58727,58757,58786,58816,58845,58875,58905,58934,58964,58994,59023,59053,59082,59111,59141,59170,59200,59229,59259,59288,59318,59348,59377,59407,59436,59466,59495,59525,59554,59584,59613,59643,59672,59702,59731,59761,59791,59820,59850,59879,59909,59939,59968,59997,60027,60056,60086,60115,60145,60174,60204,60234,60264,60293,60323,60352,60381,60411,60440,60469,60499,60528,60558,60588,60618,60648,60677,60707,60736,60765,60795,60824,60853,60883,60912,60942,60972,61002,61031,61061,61090,61120,61149,61179,61208,61237,61267,61296,61326,61356,61385,61415,61445,61474,61504,61533,61563,61592,61621,61651,61680,61710,61739,61769,61799,61828,61858,61888,61917,61947,61976,62006,62035,62064,62094,62123,62153,62182,62212,62242,62271,62301,62331,62360,62390,62419,62448,62478,62507,62537,62566,62596,62625,62655,62685,62715,62744,62774,62803,62832,62862,62891,62921,62950,62980,63009,63039,63069,63099,63128,63157,63187,63216,63246,63275,63305,63334,63363,63393,63423,63453,63482,63512,63541,63571,63600,63630,63659,63689,63718,63747,63777,63807,63836,63866,63895,63925,63955,63984,64014,64043,64073,64102,64131,64161,64190,64220,64249,64279,64309,64339,64368,64398,64427,64457,64486,64515,64545,64574,64603,64633,64663,64692,64722,64752,64782,64811,64841,64870,64899,64929,64958,64987,65017,65047,65076,65106,65136,65166,65195,65225,65254,65283,65313,65342,65371,65401,65431,65460,65490,65520,65549,65579,65608,65638,65667,65697,65726,65755,65785,65815,65844,65874,65903,65933,65963,65992,66022,66051,66081,66110,66140,66169,66199,66228,66258,66287,66317,66346,66376,66405,66435,66465,66494,66524,66553,66583,66612,66641,66671,66700,66730,66760,66789,66819,66849,66878,66908,66937,66967,66996,67025,67055,67084,67114,67143,67173,67203,67233,67262,67292,67321,67351,67380,67409,67439,67468,67497,67527,67557,67587,67617,67646,67676,67705,67735,67764,67793,67823,67852,67882,67911,67941,67971,68e3,68030,68060,68089,68119,68148,68177,68207,68236,68266,68295,68325,68354,68384,68414,68443,68473,68502,68532,68561,68591,68620,68650,68679,68708,68738,68768,68797,68827,68857,68886,68916,68946,68975,69004,69034,69063,69092,69122,69152,69181,69211,69240,69270,69300,69330,69359,69388,69418,69447,69476,69506,69535,69565,69595,69624,69654,69684,69713,69743,69772,69802,69831,69861,69890,69919,69949,69978,70008,70038,70067,70097,70126,70156,70186,70215,70245,70274,70303,70333,70362,70392,70421,70451,70481,70510,70540,70570,70599,70629,70658,70687,70717,70746,70776,70805,70835,70864,70894,70924,70954,70983,71013,71042,71071,71101,71130,71159,71189,71218,71248,71278,71308,71337,71367,71397,71426,71455,71485,71514,71543,71573,71602,71632,71662,71691,71721,71751,71781,71810,71839,71869,71898,71927,71957,71986,72016,72046,72075,72105,72135,72164,72194,72223,72253,72282,72311,72341,72370,72400,72429,72459,72489,72518,72548,72577,72607,72637,72666,72695,72725,72754,72784,72813,72843,72872,72902,72931,72961,72991,73020,73050,73080,73109,73139,73168,73197,73227,73256,73286,73315,73345,73375,73404,73434,73464,73493,73523,73552,73581,73611,73640,73669,73699,73729,73758,73788,73818,73848,73877,73907,73936,73965,73995,74024,74053,74083,74113,74142,74172,74202,74231,74261,74291,74320,74349,74379,74408,74437,74467,74497,74526,74556,74586,74615,74645,74675,74704,74733,74763,74792,74822,74851,74881,74910,74940,74969,74999,75029,75058,75088,75117,75147,75176,75206,75235,75264,75294,75323,75353,75383,75412,75442,75472,75501,75531,75560,75590,75619,75648,75678,75707,75737,75766,75796,75826,75856,75885,75915,75944,75974,76003,76032,76062,76091,76121,76150,76180,76210,76239,76269,76299,76328,76358,76387,76416,76446,76475,76505,76534,76564,76593,76623,76653,76682,76712,76741,76771,76801,76830,76859,76889,76918,76948,76977,77007,77036,77066,77096,77125,77155,77185,77214,77243,77273,77302,77332,77361,77390,77420,77450,77479,77509,77539,77569,77598,77627,77657,77686,77715,77745,77774,77804,77833,77863,77893,77923,77952,77982,78011,78041,78070,78099,78129,78158,78188,78217,78247,78277,78307,78336,78366,78395,78425,78454,78483,78513,78542,78572,78601,78631,78661,78690,78720,78750,78779,78808,78838,78867,78897,78926,78956,78985,79015,79044,79074,79104,79133,79163,79192,79222,79251,79281,79310,79340,79369,79399,79428,79458,79487,79517,79546,79576,79606,79635,79665,79695,79724,79753,79783,79812,79841,79871,79900,79930,79960,79990]},{\"../main\":570,\"object-assign\":456}],570:[function(t,e,r){var n=t(\"object-assign\");function a(){this.regionalOptions=[],this.regionalOptions[\"\"]={invalidCalendar:\"Calendar {0} not found\",invalidDate:\"Invalid {0} date\",invalidMonth:\"Invalid {0} month\",invalidYear:\"Invalid {0} year\",differentCalendars:\"Cannot mix {0} and {1} dates\"},this.local=this.regionalOptions[\"\"],this.calendars={},this._localCals={}}function i(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function o(t,e){return\"000000\".substring(0,e-(t=\"\"+t).length)+t}function s(){this.shortYearCutoff=\"+10\"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[\"\"]}n(a.prototype,{instance:function(t,e){t=(t||\"gregorian\").toLowerCase(),e=e||\"\";var r=this._localCals[t+\"-\"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+\"-\"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[\"\"].invalidCalendar).replace(/\\{0\\}/,t);return r},newDate:function(t,e,r,n,a){return(n=(null!=t&&t.year?t.calendar():\"string\"==typeof n?this.instance(n,a):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+\"\").replace(/[0-9]/g,function(e){return t[e]})}},substituteChineseDigits:function(t,e){return function(r){for(var n=\"\",a=0;r>0;){var i=r%10;n=(0===i?\"\":t[i]+e[a])+n,a++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(i.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,\"y\")},month:function(t){return 0===arguments.length?this._month:this.set(t,\"m\")},day:function(t){return 0===arguments.length?this._day:this.set(t,\"d\")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(c.local.differentCalendars||c.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this._calendar.local.name).replace(/\\{1\\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?\"-\":\"\")+o(Math.abs(this.year()),4)+\"-\"+o(this.month(),2)+\"-\"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),r=t.day(),e=t.month(),t=t.year()),new i(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return(e.year()<0?\"-\":\"\")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var r=(e+this.firstMonth-2*this.minMonth)%this.monthsInYear(t)+this.minMonth;return this._validate(t,r,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth),r},daysInYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return this.leapYear(e)?366:365},dayOfYear:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return n.toJD()-this.newDate(n.year(),this.fromMonthOfYear(n.year(),this.minMonth),this.minDay).toJD()+1},daysInWeek:function(){return 7},dayOfWeek:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),this._correctAdd(t,this._add(t,e,r),e,r)},_add:function(t,e,r){if(this._validateLevel++,\"d\"===r||\"w\"===r){var n=t.toJD()+e*(\"w\"===r?this.daysInWeek():1),a=t.calendar().fromJD(n);return this._validateLevel--,[a.year(),a.month(),a.day()]}try{var i=t.year()+(\"y\"===r?e:0),o=t.monthOfYear()+(\"m\"===r?e:0);a=t.day();\"y\"===r?(t.month()!==this.fromMonthOfYear(i,o)&&(o=this.newDate(i,t.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(i)),a=Math.min(a,this.daysInMonth(i,this.fromMonthOfYear(i,o)))):\"m\"===r&&(!function(t){for(;o<t.minMonth;)i--,o+=t.monthsInYear(i);for(var e=t.monthsInYear(i);o>e-1+t.minMonth;)i++,o-=e,e=t.monthsInYear(i)}(this),a=Math.min(a,this.daysInMonth(i,this.fromMonthOfYear(i,o))));var s=[i,this.fromMonthOfYear(i,o),a];return this._validateLevel--,s}catch(t){throw this._validateLevel--,t}},_correctAdd:function(t,e,r,n){if(!(this.hasYearZero||\"y\"!==n&&\"m\"!==n||0!==e[0]&&t.year()>0==e[0]>0)){var a={y:[1,1,\"y\"],m:[1,this.monthsInYear(-1),\"m\"],w:[this.daysInWeek(),this.daysInYear(-1),\"d\"],d:[1,this.daysInYear(-1),\"d\"]}[n],i=r<0?-1:1;e=this._add(t,r*a[0]+i*a[1],a[2])}return t.date(e[0],e[1],e[2])},set:function(t,e,r){this._validate(t,this.minMonth,this.minDay,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);var n=\"y\"===r?e:t.year(),a=\"m\"===r?e:t.month(),i=\"d\"===r?e:t.day();return\"y\"!==r&&\"m\"!==r||(i=Math.min(i,this.daysInMonth(n,a))),t.date(n,a,i)},isValid:function(t,e,r){this._validateLevel++;var n=this.hasYearZero||0!==t;if(n){var a=this.newDate(t,e,this.minDay);n=e>=this.minMonth&&e-this.minMonth<this.monthsInYear(a)&&r>=this.minDay&&r-this.minDay<this.daysInMonth(a)}return this._validateLevel--,n},toJSDate:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return c.instance().fromJD(this.toJD(n)).toJSDate()},fromJSDate:function(t){return this.fromJD(c.instance().fromJSDate(t).toJD())},_validate:function(t,e,r,n){if(t.year){if(0===this._validateLevel&&this.name!==t.calendar().name)throw(c.local.differentCalendars||c.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this.local.name).replace(/\\{1\\}/,t.calendar().local.name);return t}try{if(this._validateLevel++,1===this._validateLevel&&!this.isValid(t,e,r))throw n.replace(/\\{0\\}/,this.local.name);var a=this.newDate(t,e,r);return this._validateLevel--,a}catch(t){throw this._validateLevel--,t}}}),l.prototype=new s,n(l.prototype,{name:\"Gregorian\",jdEpoch:1721425.5,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Gregorian\",epochs:[\"BCE\",\"CE\"],monthNames:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],monthNamesShort:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"mm/dd/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return(t=e.year()+(e.year()<0?1:0))%4==0&&(t%100!=0||t%400==0)},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(4-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);t=n.year(),e=n.month(),r=n.day(),t<0&&t++,e<3&&(e+=12,t--);var a=Math.floor(t/100),i=2-a+Math.floor(a/4);return Math.floor(365.25*(t+4716))+Math.floor(30.6001*(e+1))+r+i-1524.5},fromJD:function(t){var e=Math.floor(t+.5),r=Math.floor((e-1867216.25)/36524.25),n=(r=e+1+r-Math.floor(r/4))+1524,a=Math.floor((n-122.1)/365.25),i=Math.floor(365.25*a),o=Math.floor((n-i)/30.6001),s=n-i-Math.floor(30.6001*o),l=o-(o>13.5?13:1),c=a-(l>2.5?4716:4715);return c<=0&&c--,this.newDate(c,l,s)},toJSDate:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),a=new Date(n.year(),n.month()-1,n.day());return a.setHours(0),a.setMinutes(0),a.setSeconds(0),a.setMilliseconds(0),a.setHours(a.getHours()>12?a.getHours()+2:0),a},fromJSDate:function(t){return this.newDate(t.getFullYear(),t.getMonth()+1,t.getDate())}});var c=e.exports=new a;c.cdate=i,c.baseCalendar=s,c.calendars.gregorian=l},{\"object-assign\":456}],571:[function(t,e,r){var n=t(\"object-assign\"),a=t(\"./main\");n(a.regionalOptions[\"\"],{invalidArguments:\"Invalid arguments\",invalidFormat:\"Cannot format a date from another calendar\",missingNumberAt:\"Missing number at position {0}\",unknownNameAt:\"Unknown name at position {0}\",unexpectedLiteralAt:\"Unexpected literal at position {0}\",unexpectedText:\"Additional text found at end\"}),a.local=a.regionalOptions[\"\"],n(a.cdate.prototype,{formatDate:function(t,e){return\"string\"!=typeof t&&(e=t,t=\"\"),this._calendar.formatDate(t||\"\",this,e)}}),n(a.baseCalendar.prototype,{UNIX_EPOCH:a.instance().newDate(1970,1,1).toJD(),SECS_PER_DAY:86400,TICKS_EPOCH:a.instance().jdEpoch,TICKS_PER_DAY:864e9,ATOM:\"yyyy-mm-dd\",COOKIE:\"D, dd M yyyy\",FULL:\"DD, MM d, yyyy\",ISO_8601:\"yyyy-mm-dd\",JULIAN:\"J\",RFC_822:\"D, d M yy\",RFC_850:\"DD, dd-M-yy\",RFC_1036:\"D, d M yy\",RFC_1123:\"D, d M yyyy\",RFC_2822:\"D, d M yyyy\",RSS:\"D, d M yy\",TICKS:\"!\",TIMESTAMP:\"@\",W3C:\"yyyy-mm-dd\",formatDate:function(t,e,r){if(\"string\"!=typeof t&&(r=e,e=t,t=\"\"),!e)return\"\";if(e.calendar()!==this)throw a.local.invalidFormat||a.regionalOptions[\"\"].invalidFormat;t=t||this.local.dateFormat;for(var n,i,o,s,l=(r=r||{}).dayNamesShort||this.local.dayNamesShort,c=r.dayNames||this.local.dayNames,u=r.monthNumbers||this.local.monthNumbers,h=r.monthNamesShort||this.local.monthNamesShort,f=r.monthNames||this.local.monthNames,p=(r.calculateWeek||this.local.calculateWeek,function(e,r){for(var n=1;w+n<t.length&&t.charAt(w+n)===e;)n++;return w+=n-1,Math.floor(n/(r||1))>1}),d=function(t,e,r,n){var a=\"\"+e;if(p(t,n))for(;a.length<r;)a=\"0\"+a;return a},g=this,v=function(t){return\"function\"==typeof u?u.call(g,t,p(\"m\")):x(d(\"m\",t.month(),2))},m=function(t,e){return e?\"function\"==typeof f?f.call(g,t):f[t.month()-g.minMonth]:\"function\"==typeof h?h.call(g,t):h[t.month()-g.minMonth]},y=this.local.digits,x=function(t){return r.localNumbers&&y?y(t):t},b=\"\",_=!1,w=0;w<t.length;w++)if(_)\"'\"!==t.charAt(w)||p(\"'\")?b+=t.charAt(w):_=!1;else switch(t.charAt(w)){case\"d\":b+=x(d(\"d\",e.day(),2));break;case\"D\":b+=(n=\"D\",i=e.dayOfWeek(),o=l,s=c,p(n)?s[i]:o[i]);break;case\"o\":b+=d(\"o\",e.dayOfYear(),3);break;case\"w\":b+=d(\"w\",e.weekOfYear(),2);break;case\"m\":b+=v(e);break;case\"M\":b+=m(e,p(\"M\"));break;case\"y\":b+=p(\"y\",2)?e.year():(e.year()%100<10?\"0\":\"\")+e.year()%100;break;case\"Y\":p(\"Y\",2),b+=e.formatYear();break;case\"J\":b+=e.toJD();break;case\"@\":b+=(e.toJD()-this.UNIX_EPOCH)*this.SECS_PER_DAY;break;case\"!\":b+=(e.toJD()-this.TICKS_EPOCH)*this.TICKS_PER_DAY;break;case\"'\":p(\"'\")?b+=\"'\":_=!0;break;default:b+=t.charAt(w)}return b},parseDate:function(t,e,r){if(null==e)throw a.local.invalidArguments||a.regionalOptions[\"\"].invalidArguments;if(\"\"===(e=\"object\"==typeof e?e.toString():e+\"\"))return null;t=t||this.local.dateFormat;var n=(r=r||{}).shortYearCutoff||this.shortYearCutoff;n=\"string\"!=typeof n?n:this.today().year()%100+parseInt(n,10);for(var i=r.dayNamesShort||this.local.dayNamesShort,o=r.dayNames||this.local.dayNames,s=r.parseMonth||this.local.parseMonth,l=r.monthNumbers||this.local.monthNumbers,c=r.monthNamesShort||this.local.monthNamesShort,u=r.monthNames||this.local.monthNames,h=-1,f=-1,p=-1,d=-1,g=-1,v=!1,m=!1,y=function(e,r){for(var n=1;A+n<t.length&&t.charAt(A+n)===e;)n++;return A+=n-1,Math.floor(n/(r||1))>1},x=function(t,r){var n=y(t,r),i=[2,3,n?4:2,n?4:2,10,11,20][\"oyYJ@!\".indexOf(t)+1],o=new RegExp(\"^-?\\\\d{1,\"+i+\"}\"),s=e.substring(M).match(o);if(!s)throw(a.local.missingNumberAt||a.regionalOptions[\"\"].missingNumberAt).replace(/\\{0\\}/,M);return M+=s[0].length,parseInt(s[0],10)},b=this,_=function(){if(\"function\"==typeof l){y(\"m\");var t=l.call(b,e.substring(M));return M+=t.length,t}return x(\"m\")},w=function(t,r,n,i){for(var o=y(t,i)?n:r,s=0;s<o.length;s++)if(e.substr(M,o[s].length).toLowerCase()===o[s].toLowerCase())return M+=o[s].length,s+b.minMonth;throw(a.local.unknownNameAt||a.regionalOptions[\"\"].unknownNameAt).replace(/\\{0\\}/,M)},k=function(){if(\"function\"==typeof u){var t=y(\"M\")?u.call(b,e.substring(M)):c.call(b,e.substring(M));return M+=t.length,t}return w(\"M\",c,u)},T=function(){if(e.charAt(M)!==t.charAt(A))throw(a.local.unexpectedLiteralAt||a.regionalOptions[\"\"].unexpectedLiteralAt).replace(/\\{0\\}/,M);M++},M=0,A=0;A<t.length;A++)if(m)\"'\"!==t.charAt(A)||y(\"'\")?T():m=!1;else switch(t.charAt(A)){case\"d\":d=x(\"d\");break;case\"D\":w(\"D\",i,o);break;case\"o\":g=x(\"o\");break;case\"w\":x(\"w\");break;case\"m\":p=_();break;case\"M\":p=k();break;case\"y\":var S=A;v=!y(\"y\",2),A=S,f=x(\"y\",2);break;case\"Y\":f=x(\"Y\",2);break;case\"J\":h=x(\"J\")+.5,\".\"===e.charAt(M)&&(M++,x(\"J\"));break;case\"@\":h=x(\"@\")/this.SECS_PER_DAY+this.UNIX_EPOCH;break;case\"!\":h=x(\"!\")/this.TICKS_PER_DAY+this.TICKS_EPOCH;break;case\"*\":M=e.length;break;case\"'\":y(\"'\")?T():m=!0;break;default:T()}if(M<e.length)throw a.local.unexpectedText||a.regionalOptions[\"\"].unexpectedText;if(-1===f?f=this.today().year():f<100&&v&&(f+=-1===n?1900:this.today().year()-this.today().year()%100-(f<=n?0:100)),\"string\"==typeof p&&(p=s.call(this,f,p)),g>-1){p=1,d=g;for(var E=this.daysInMonth(f,p);d>E;E=this.daysInMonth(f,p))p++,d-=E}return h>-1?this.fromJD(h):this.newDate(f,p,d)},determineDate:function(t,e,r,n,a){r&&\"object\"!=typeof r&&(a=n,n=r,r=null),\"string\"!=typeof n&&(a=n,n=\"\");var i=this;return e=e?e.newDate():null,t=null==t?e:\"string\"==typeof t?function(t){try{return i.parseDate(n,t,a)}catch(t){}for(var e=((t=t.toLowerCase()).match(/^c/)&&r?r.newDate():null)||i.today(),o=/([+-]?[0-9]+)\\s*(d|w|m|y)?/g,s=o.exec(t);s;)e.add(parseInt(s[1],10),s[2]||\"d\"),s=o.exec(t);return e}(t):\"number\"==typeof t?isNaN(t)||t===1/0||t===-1/0?e:i.today().add(t,\"d\"):i.newDate(t)}})},{\"./main\":570,\"object-assign\":456}],572:[function(t,e,r){e.exports=t(\"cwise-compiler\")({args:[\"array\",{offset:[1],array:0},\"scalar\",\"scalar\",\"index\"],pre:{body:\"{}\",args:[],thisVars:[],localVars:[]},post:{body:\"{}\",args:[],thisVars:[],localVars:[]},body:{body:\"{\\n        var _inline_1_da = _inline_1_arg0_ - _inline_1_arg3_\\n        var _inline_1_db = _inline_1_arg1_ - _inline_1_arg3_\\n        if((_inline_1_da >= 0) !== (_inline_1_db >= 0)) {\\n          _inline_1_arg2_.push(_inline_1_arg4_[0] + 0.5 + 0.5 * (_inline_1_da + _inline_1_db) / (_inline_1_da - _inline_1_db))\\n        }\\n      }\",args:[{name:\"_inline_1_arg0_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_1_arg1_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_1_arg2_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_1_arg3_\",lvalue:!1,rvalue:!0,count:2},{name:\"_inline_1_arg4_\",lvalue:!1,rvalue:!0,count:1}],thisVars:[],localVars:[\"_inline_1_da\",\"_inline_1_db\"]},funcName:\"zeroCrossings\"})},{\"cwise-compiler\":148}],573:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=[];return e=+e||0,n(t.hi(t.shape[0]-1),r,e),r};var n=t(\"./lib/zc-core\")},{\"./lib/zc-core\":572}],574:[function(t,e,r){\"use strict\";e.exports=[{path:\"\",backoff:0},{path:\"M-2.4,-3V3L0.6,0Z\",backoff:.6},{path:\"M-3.7,-2.5V2.5L1.3,0Z\",backoff:1.3},{path:\"M-4.45,-3L-1.65,-0.2V0.2L-4.45,3L1.55,0Z\",backoff:1.55},{path:\"M-2.2,-2.2L-0.2,-0.2V0.2L-2.2,2.2L-1.4,3L1.6,0L-1.4,-3Z\",backoff:1.6},{path:\"M-4.4,-2.1L-0.6,-0.2V0.2L-4.4,2.1L-4,3L2,0L-4,-3Z\",backoff:2},{path:\"M2,0A2,2 0 1,1 0,-2A2,2 0 0,1 2,0Z\",backoff:0,noRotate:!0},{path:\"M2,2V-2H-2V2Z\",backoff:0,noRotate:!0}]},{}],575:[function(t,e,r){\"use strict\";var n=t(\"./arrow_paths\"),a=t(\"../../plots/font_attributes\"),i=t(\"../../plots/cartesian/constants\"),o=t(\"../../plot_api/plot_template\").templatedArray;e.exports=o(\"annotation\",{visible:{valType:\"boolean\",dflt:!0,editType:\"calc+arraydraw\"},text:{valType:\"string\",editType:\"calc+arraydraw\"},textangle:{valType:\"angle\",dflt:0,editType:\"calc+arraydraw\"},font:a({editType:\"calc+arraydraw\",colorEditType:\"arraydraw\"}),width:{valType:\"number\",min:1,dflt:null,editType:\"calc+arraydraw\"},height:{valType:\"number\",min:1,dflt:null,editType:\"calc+arraydraw\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,editType:\"arraydraw\"},align:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"center\",editType:\"arraydraw\"},valign:{valType:\"enumerated\",values:[\"top\",\"middle\",\"bottom\"],dflt:\"middle\",editType:\"arraydraw\"},bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"arraydraw\"},bordercolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"arraydraw\"},borderpad:{valType:\"number\",min:0,dflt:1,editType:\"calc+arraydraw\"},borderwidth:{valType:\"number\",min:0,dflt:1,editType:\"calc+arraydraw\"},showarrow:{valType:\"boolean\",dflt:!0,editType:\"calc+arraydraw\"},arrowcolor:{valType:\"color\",editType:\"arraydraw\"},arrowhead:{valType:\"integer\",min:0,max:n.length,dflt:1,editType:\"arraydraw\"},startarrowhead:{valType:\"integer\",min:0,max:n.length,dflt:1,editType:\"arraydraw\"},arrowside:{valType:\"flaglist\",flags:[\"end\",\"start\"],extras:[\"none\"],dflt:\"end\",editType:\"arraydraw\"},arrowsize:{valType:\"number\",min:.3,dflt:1,editType:\"calc+arraydraw\"},startarrowsize:{valType:\"number\",min:.3,dflt:1,editType:\"calc+arraydraw\"},arrowwidth:{valType:\"number\",min:.1,editType:\"calc+arraydraw\"},standoff:{valType:\"number\",min:0,dflt:0,editType:\"calc+arraydraw\"},startstandoff:{valType:\"number\",min:0,dflt:0,editType:\"calc+arraydraw\"},ax:{valType:\"any\",editType:\"calc+arraydraw\"},ay:{valType:\"any\",editType:\"calc+arraydraw\"},axref:{valType:\"enumerated\",dflt:\"pixel\",values:[\"pixel\",i.idRegex.x.toString()],editType:\"calc\"},ayref:{valType:\"enumerated\",dflt:\"pixel\",values:[\"pixel\",i.idRegex.y.toString()],editType:\"calc\"},xref:{valType:\"enumerated\",values:[\"paper\",i.idRegex.x.toString()],editType:\"calc\"},x:{valType:\"any\",editType:\"calc+arraydraw\"},xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"auto\",editType:\"calc+arraydraw\"},xshift:{valType:\"number\",dflt:0,editType:\"calc+arraydraw\"},yref:{valType:\"enumerated\",values:[\"paper\",i.idRegex.y.toString()],editType:\"calc\"},y:{valType:\"any\",editType:\"calc+arraydraw\"},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"auto\",editType:\"calc+arraydraw\"},yshift:{valType:\"number\",dflt:0,editType:\"calc+arraydraw\"},clicktoshow:{valType:\"enumerated\",values:[!1,\"onoff\",\"onout\"],dflt:!1,editType:\"arraydraw\"},xclick:{valType:\"any\",editType:\"arraydraw\"},yclick:{valType:\"any\",editType:\"arraydraw\"},hovertext:{valType:\"string\",editType:\"arraydraw\"},hoverlabel:{bgcolor:{valType:\"color\",editType:\"arraydraw\"},bordercolor:{valType:\"color\",editType:\"arraydraw\"},font:a({editType:\"arraydraw\"}),editType:\"arraydraw\"},captureevents:{valType:\"boolean\",editType:\"arraydraw\"},editType:\"calc\",_deprecated:{ref:{valType:\"string\",editType:\"calc\"}}})},{\"../../plot_api/plot_template\":755,\"../../plots/cartesian/constants\":771,\"../../plots/font_attributes\":791,\"./arrow_paths\":574}],576:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/cartesian/axes\"),i=t(\"./draw\").draw;function o(t){var e=t._fullLayout;n.filterVisible(e.annotations).forEach(function(e){var r=a.getFromId(t,e.xref),n=a.getFromId(t,e.yref);e._extremes={},r&&s(e,r),n&&s(e,n)})}function s(t,e){var r,n=e._id,i=n.charAt(0),o=t[i],s=t[\"a\"+i],l=t[i+\"ref\"],c=t[\"a\"+i+\"ref\"],u=t[\"_\"+i+\"padplus\"],h=t[\"_\"+i+\"padminus\"],f={x:1,y:-1}[i]*t[i+\"shift\"],p=3*t.arrowsize*t.arrowwidth||0,d=p+f,g=p-f,v=3*t.startarrowsize*t.arrowwidth||0,m=v+f,y=v-f;if(c===l){var x=a.findExtremes(e,[e.r2c(o)],{ppadplus:d,ppadminus:g}),b=a.findExtremes(e,[e.r2c(s)],{ppadplus:Math.max(u,m),ppadminus:Math.max(h,y)});r={min:[x.min[0],b.min[0]],max:[x.max[0],b.max[0]]}}else m=s?m+s:m,y=s?y-s:y,r=a.findExtremes(e,[e.r2c(o)],{ppadplus:Math.max(u,d,m),ppadminus:Math.max(h,g,y)});t._extremes[n]=r}e.exports=function(t){var e=t._fullLayout;if(n.filterVisible(e.annotations).length&&t._fullData.length)return n.syncOrAsync([i,o],t)}},{\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"./draw\":581}],577:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../registry\"),i=t(\"../../plot_api/plot_template\").arrayEditor;function o(t,e){var r,n,a,i,o,l,c,u=t._fullLayout.annotations,h=[],f=[],p=[],d=(e||[]).length;for(r=0;r<u.length;r++)if(i=(a=u[r]).clicktoshow){for(n=0;n<d;n++)if(l=(o=e[n]).xaxis,c=o.yaxis,l._id===a.xref&&c._id===a.yref&&l.d2r(o.x)===s(a._xclick,l)&&c.d2r(o.y)===s(a._yclick,c)){(a.visible?\"onout\"===i?f:p:h).push(r);break}n===d&&a.visible&&\"onout\"===i&&f.push(r)}return{on:h,off:f,explicitOff:p}}function s(t,e){return\"log\"===e.type?e.l2r(t):e.d2r(t)}e.exports={hasClickToShow:function(t,e){var r=o(t,e);return r.on.length>0||r.explicitOff.length>0},onClick:function(t,e){var r,s,l=o(t,e),c=l.on,u=l.off.concat(l.explicitOff),h={},f=t._fullLayout.annotations;if(!c.length&&!u.length)return;for(r=0;r<c.length;r++)(s=i(t.layout,\"annotations\",f[c[r]])).modifyItem(\"visible\",!0),n.extendFlat(h,s.getUpdateObj());for(r=0;r<u.length;r++)(s=i(t.layout,\"annotations\",f[u[r]])).modifyItem(\"visible\",!1),n.extendFlat(h,s.getUpdateObj());return a.call(\"update\",t,{},h)}}},{\"../../lib\":717,\"../../plot_api/plot_template\":755,\"../../registry\":846}],578:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../color\");e.exports=function(t,e,r,i){i(\"opacity\");var o=i(\"bgcolor\"),s=i(\"bordercolor\"),l=a.opacity(s);i(\"borderpad\");var c=i(\"borderwidth\"),u=i(\"showarrow\");if(i(\"text\",u?\" \":r._dfltTitle.annotation),i(\"textangle\"),n.coerceFont(i,\"font\",r.font),i(\"width\"),i(\"align\"),i(\"height\")&&i(\"valign\"),u){var h,f,p=i(\"arrowside\");-1!==p.indexOf(\"end\")&&(h=i(\"arrowhead\"),f=i(\"arrowsize\")),-1!==p.indexOf(\"start\")&&(i(\"startarrowhead\",h),i(\"startarrowsize\",f)),i(\"arrowcolor\",l?e.bordercolor:a.defaultLine),i(\"arrowwidth\",2*(l&&c||1)),i(\"standoff\"),i(\"startstandoff\")}var d=i(\"hovertext\"),g=r.hoverlabel||{};if(d){var v=i(\"hoverlabel.bgcolor\",g.bgcolor||(a.opacity(o)?a.rgb(o):a.defaultLine)),m=i(\"hoverlabel.bordercolor\",g.bordercolor||a.contrast(v));n.coerceFont(i,\"hoverlabel.font\",{family:g.font.family,size:g.font.size,color:g.font.color||m})}i(\"captureevents\",!!d)}},{\"../../lib\":717,\"../color\":592}],579:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib/to_log_range\");e.exports=function(t,e,r,i){e=e||{};var o=\"log\"===r&&\"linear\"===e.type,s=\"linear\"===r&&\"log\"===e.type;if(o||s)for(var l,c,u=t._fullLayout.annotations,h=e._id.charAt(0),f=0;f<u.length;f++)l=u[f],c=\"annotations[\"+f+\"].\",l[h+\"ref\"]===e._id&&p(h),l[\"a\"+h+\"ref\"]===e._id&&p(\"a\"+h);function p(t){var r=l[t],s=null;s=o?a(r,e.range):Math.pow(10,r),n(s)||(s=null),i(c+t,s)}}},{\"../../lib/to_log_range\":743,\"fast-isnumeric\":228}],580:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/cartesian/axes\"),i=t(\"../../plots/array_container_defaults\"),o=t(\"./common_defaults\"),s=t(\"./attributes\");function l(t,e,r){function i(r,a){return n.coerce(t,e,s,r,a)}var l=i(\"visible\"),c=i(\"clicktoshow\");if(l||c){o(t,e,r,i);for(var u=e.showarrow,h=[\"x\",\"y\"],f=[-10,-30],p={_fullLayout:r},d=0;d<2;d++){var g=h[d],v=a.coerceRef(t,e,p,g,\"\",\"paper\");if(\"paper\"!==v)a.getFromId(p,v)._annIndices.push(e._index);if(a.coercePosition(e,p,i,v,g,.5),u){var m=\"a\"+g,y=a.coerceRef(t,e,p,m,\"pixel\");\"pixel\"!==y&&y!==v&&(y=e[m]=\"pixel\");var x=\"pixel\"===y?f[d]:.4;a.coercePosition(e,p,i,y,m,x)}i(g+\"anchor\"),i(g+\"shift\")}if(n.noneOrAll(t,e,[\"x\",\"y\"]),u&&n.noneOrAll(t,e,[\"ax\",\"ay\"]),c){var b=i(\"xclick\"),_=i(\"yclick\");e._xclick=void 0===b?e.x:a.cleanPosition(b,p,e.xref),e._yclick=void 0===_?e.y:a.cleanPosition(_,p,e.yref)}}}e.exports=function(t,e){i(t,e,{name:\"annotations\",handleItemDefaults:l})}},{\"../../lib\":717,\"../../plots/array_container_defaults\":761,\"../../plots/cartesian/axes\":765,\"./attributes\":575,\"./common_defaults\":578}],581:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../registry\"),i=t(\"../../plots/plots\"),o=t(\"../../lib\"),s=t(\"../../plots/cartesian/axes\"),l=t(\"../color\"),c=t(\"../drawing\"),u=t(\"../fx\"),h=t(\"../../lib/svg_text_utils\"),f=t(\"../../lib/setcursor\"),p=t(\"../dragelement\"),d=t(\"../../plot_api/plot_template\").arrayEditor,g=t(\"./draw_arrow_head\");function v(t,e){var r=t._fullLayout.annotations[e]||{},n=s.getFromId(t,r.xref),a=s.getFromId(t,r.yref);n&&n.setScale(),a&&a.setScale(),m(t,r,e,!1,n,a)}function m(t,e,r,i,s,v){var m,y,x=t._fullLayout,b=t._fullLayout._size,_=t._context.edits;i?(m=\"annotation-\"+i,y=i+\".annotations\"):(m=\"annotation\",y=\"annotations\");var w=d(t.layout,y,e),k=w.modifyBase,T=w.modifyItem,M=w.getUpdateObj;x._infolayer.selectAll(\".\"+m+'[data-index=\"'+r+'\"]').remove();var A=\"clip\"+x._uid+\"_ann\"+r;if(e._input&&!1!==e.visible){var S={x:{},y:{}},E=+e.textangle||0,L=x._infolayer.append(\"g\").classed(m,!0).attr(\"data-index\",String(r)).style(\"opacity\",e.opacity),C=L.append(\"g\").classed(\"annotation-text-g\",!0),P=_[e.showarrow?\"annotationTail\":\"annotationPosition\"],O=e.captureevents||_.annotationText||P,z=C.append(\"g\").style(\"pointer-events\",O?\"all\":null).call(f,\"pointer\").on(\"click\",function(){t._dragging=!1,t.emit(\"plotly_clickannotation\",q(n.event))});e.hovertext&&z.on(\"mouseover\",function(){var r=e.hoverlabel,n=r.font,a=this.getBoundingClientRect(),i=t.getBoundingClientRect();u.loneHover({x0:a.left-i.left,x1:a.right-i.left,y:(a.top+a.bottom)/2-i.top,text:e.hovertext,color:r.bgcolor,borderColor:r.bordercolor,fontFamily:n.family,fontSize:n.size,fontColor:n.color},{container:x._hoverlayer.node(),outerContainer:x._paper.node(),gd:t})}).on(\"mouseout\",function(){u.loneUnhover(x._hoverlayer.node())});var I=e.borderwidth,D=e.borderpad,R=I+D,F=z.append(\"rect\").attr(\"class\",\"bg\").style(\"stroke-width\",I+\"px\").call(l.stroke,e.bordercolor).call(l.fill,e.bgcolor),B=e.width||e.height,N=x._topclips.selectAll(\"#\"+A).data(B?[0]:[]);N.enter().append(\"clipPath\").classed(\"annclip\",!0).attr(\"id\",A).append(\"rect\"),N.exit().remove();var j=e.font,V=x._meta?o.templateString(e.text,x._meta):e.text,U=z.append(\"text\").classed(\"annotation-text\",!0).text(V);_.annotationText?U.call(h.makeEditable,{delegate:z,gd:t}).call(H).on(\"edit\",function(r){e.text=r,this.call(H),T(\"text\",r),s&&s.autorange&&k(s._name+\".autorange\",!0),v&&v.autorange&&k(v._name+\".autorange\",!0),a.call(\"_guiRelayout\",t,M())}):U.call(H)}else n.selectAll(\"#\"+A).remove();function q(t){var n={index:r,annotation:e._input,fullAnnotation:e,event:t};return i&&(n.subplotId=i),n}function H(r){return r.call(c.font,j).attr({\"text-anchor\":{left:\"start\",right:\"end\"}[e.align]||\"middle\"}),h.convertToTspans(r,t,G),r}function G(){var r=U.selectAll(\"a\");1===r.size()&&r.text()===U.text()&&z.insert(\"a\",\":first-child\").attr({\"xlink:xlink:href\":r.attr(\"xlink:href\"),\"xlink:xlink:show\":r.attr(\"xlink:show\")}).style({cursor:\"pointer\"}).node().appendChild(F.node());var n=z.select(\".annotation-text-math-group\"),u=!n.empty(),d=c.bBox((u?n:U).node()),m=d.width,y=d.height,w=e.width||m,O=e.height||y,D=Math.round(w+2*R),j=Math.round(O+2*R);function V(t,e){return\"auto\"===e&&(e=t<1/3?\"left\":t>2/3?\"right\":\"center\"),{center:0,middle:0,left:.5,bottom:-.5,right:-.5,top:.5}[e]}for(var H=!1,G=[\"x\",\"y\"],Y=0;Y<G.length;Y++){var W,X,Z,J,K,Q=G[Y],$=e[Q+\"ref\"]||Q,tt=e[\"a\"+Q+\"ref\"],et={x:s,y:v}[Q],rt=(E+(\"x\"===Q?0:-90))*Math.PI/180,nt=D*Math.cos(rt),at=j*Math.sin(rt),it=Math.abs(nt)+Math.abs(at),ot=e[Q+\"anchor\"],st=e[Q+\"shift\"]*(\"x\"===Q?1:-1),lt=S[Q];if(et){var ct=et.r2fraction(e[Q]);(ct<0||ct>1)&&(tt===$?((ct=et.r2fraction(e[\"a\"+Q]))<0||ct>1)&&(H=!0):H=!0),W=et._offset+et.r2p(e[Q]),J=.5}else\"x\"===Q?(Z=e[Q],W=b.l+b.w*Z):(Z=1-e[Q],W=b.t+b.h*Z),J=e.showarrow?.5:Z;if(e.showarrow){lt.head=W;var ut=e[\"a\"+Q];K=nt*V(.5,e.xanchor)-at*V(.5,e.yanchor),tt===$?(lt.tail=et._offset+et.r2p(ut),X=K):(lt.tail=W+ut,X=K+ut),lt.text=lt.tail+K;var ht=x[\"x\"===Q?\"width\":\"height\"];if(\"paper\"===$&&(lt.head=o.constrain(lt.head,1,ht-1)),\"pixel\"===tt){var ft=-Math.max(lt.tail-3,lt.text),pt=Math.min(lt.tail+3,lt.text)-ht;ft>0?(lt.tail+=ft,lt.text+=ft):pt>0&&(lt.tail-=pt,lt.text-=pt)}lt.tail+=st,lt.head+=st}else X=K=it*V(J,ot),lt.text=W+K;lt.text+=st,K+=st,X+=st,e[\"_\"+Q+\"padplus\"]=it/2+X,e[\"_\"+Q+\"padminus\"]=it/2-X,e[\"_\"+Q+\"size\"]=it,e[\"_\"+Q+\"shift\"]=K}if(H)z.remove();else{var dt=0,gt=0;if(\"left\"!==e.align&&(dt=(w-m)*(\"center\"===e.align?.5:1)),\"top\"!==e.valign&&(gt=(O-y)*(\"middle\"===e.valign?.5:1)),u)n.select(\"svg\").attr({x:R+dt-1,y:R+gt}).call(c.setClipUrl,B?A:null,t);else{var vt=R+gt-d.top,mt=R+dt-d.left;U.call(h.positionText,mt,vt).call(c.setClipUrl,B?A:null,t)}N.select(\"rect\").call(c.setRect,R,R,w,O),F.call(c.setRect,I/2,I/2,D-I,j-I),z.call(c.setTranslate,Math.round(S.x.text-D/2),Math.round(S.y.text-j/2)),C.attr({transform:\"rotate(\"+E+\",\"+S.x.text+\",\"+S.y.text+\")\"});var yt,xt=function(r,n){L.selectAll(\".annotation-arrow-g\").remove();var u=S.x.head,h=S.y.head,f=S.x.tail+r,d=S.y.tail+n,m=S.x.text+r,y=S.y.text+n,x=o.rotationXYMatrix(E,m,y),w=o.apply2DTransform(x),A=o.apply2DTransform2(x),P=+F.attr(\"width\"),O=+F.attr(\"height\"),I=m-.5*P,D=I+P,R=y-.5*O,B=R+O,N=[[I,R,I,B],[I,B,D,B],[D,B,D,R],[D,R,I,R]].map(A);if(!N.reduce(function(t,e){return t^!!o.segmentsIntersect(u,h,u+1e6,h+1e6,e[0],e[1],e[2],e[3])},!1)){N.forEach(function(t){var e=o.segmentsIntersect(f,d,u,h,t[0],t[1],t[2],t[3]);e&&(f=e.x,d=e.y)});var j=e.arrowwidth,V=e.arrowcolor,U=e.arrowside,q=L.append(\"g\").style({opacity:l.opacity(V)}).classed(\"annotation-arrow-g\",!0),H=q.append(\"path\").attr(\"d\",\"M\"+f+\",\"+d+\"L\"+u+\",\"+h).style(\"stroke-width\",j+\"px\").call(l.stroke,l.rgb(V));if(g(H,U,e),_.annotationPosition&&H.node().parentNode&&!i){var G=u,Y=h;if(e.standoff){var W=Math.sqrt(Math.pow(u-f,2)+Math.pow(h-d,2));G+=e.standoff*(f-u)/W,Y+=e.standoff*(d-h)/W}var X,Z,J=q.append(\"path\").classed(\"annotation-arrow\",!0).classed(\"anndrag\",!0).classed(\"cursor-move\",!0).attr({d:\"M3,3H-3V-3H3ZM0,0L\"+(f-G)+\",\"+(d-Y),transform:\"translate(\"+G+\",\"+Y+\")\"}).style(\"stroke-width\",j+6+\"px\").call(l.stroke,\"rgba(0,0,0,0)\").call(l.fill,\"rgba(0,0,0,0)\");p.init({element:J.node(),gd:t,prepFn:function(){var t=c.getTranslate(z);X=t.x,Z=t.y,s&&s.autorange&&k(s._name+\".autorange\",!0),v&&v.autorange&&k(v._name+\".autorange\",!0)},moveFn:function(t,r){var n=w(X,Z),a=n[0]+t,i=n[1]+r;z.call(c.setTranslate,a,i),T(\"x\",s?s.p2r(s.r2p(e.x)+t):e.x+t/b.w),T(\"y\",v?v.p2r(v.r2p(e.y)+r):e.y-r/b.h),e.axref===e.xref&&T(\"ax\",s.p2r(s.r2p(e.ax)+t)),e.ayref===e.yref&&T(\"ay\",v.p2r(v.r2p(e.ay)+r)),q.attr(\"transform\",\"translate(\"+t+\",\"+r+\")\"),C.attr({transform:\"rotate(\"+E+\",\"+a+\",\"+i+\")\"})},doneFn:function(){a.call(\"_guiRelayout\",t,M());var e=document.querySelector(\".js-notes-box-panel\");e&&e.redraw(e.selectedObj)}})}}};if(e.showarrow&&xt(0,0),P)p.init({element:z.node(),gd:t,prepFn:function(){yt=C.attr(\"transform\")},moveFn:function(t,r){var n=\"pointer\";if(e.showarrow)e.axref===e.xref?T(\"ax\",s.p2r(s.r2p(e.ax)+t)):T(\"ax\",e.ax+t),e.ayref===e.yref?T(\"ay\",v.p2r(v.r2p(e.ay)+r)):T(\"ay\",e.ay+r),xt(t,r);else{if(i)return;var a,o;if(s)a=s.p2r(s.r2p(e.x)+t);else{var l=e._xsize/b.w,c=e.x+(e._xshift-e.xshift)/b.w-l/2;a=p.align(c+t/b.w,l,0,1,e.xanchor)}if(v)o=v.p2r(v.r2p(e.y)+r);else{var u=e._ysize/b.h,h=e.y-(e._yshift+e.yshift)/b.h-u/2;o=p.align(h-r/b.h,u,0,1,e.yanchor)}T(\"x\",a),T(\"y\",o),s&&v||(n=p.getCursor(s?.5:a,v?.5:o,e.xanchor,e.yanchor))}C.attr({transform:\"translate(\"+t+\",\"+r+\")\"+yt}),f(z,n)},clickFn:function(r,n){e.captureevents&&t.emit(\"plotly_clickannotation\",q(n))},doneFn:function(){f(z),a.call(\"_guiRelayout\",t,M());var e=document.querySelector(\".js-notes-box-panel\");e&&e.redraw(e.selectedObj)}})}}}e.exports={draw:function(t){var e=t._fullLayout;e._infolayer.selectAll(\".annotation\").remove();for(var r=0;r<e.annotations.length;r++)e.annotations[r].visible&&v(t,r);return i.previousPromises(t)},drawOne:v,drawRaw:m}},{\"../../lib\":717,\"../../lib/setcursor\":737,\"../../lib/svg_text_utils\":741,\"../../plot_api/plot_template\":755,\"../../plots/cartesian/axes\":765,\"../../plots/plots\":826,\"../../registry\":846,\"../color\":592,\"../dragelement\":610,\"../drawing\":613,\"../fx\":630,\"./draw_arrow_head\":582,d3:165}],582:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../color\"),i=t(\"./arrow_paths\");e.exports=function(t,e,r){var o,s,l,c,u=t.node(),h=i[r.arrowhead||0],f=i[r.startarrowhead||0],p=(r.arrowwidth||1)*(r.arrowsize||1),d=(r.arrowwidth||1)*(r.startarrowsize||1),g=e.indexOf(\"start\")>=0,v=e.indexOf(\"end\")>=0,m=h.backoff*p+r.standoff,y=f.backoff*d+r.startstandoff;if(\"line\"===u.nodeName){o={x:+t.attr(\"x1\"),y:+t.attr(\"y1\")},s={x:+t.attr(\"x2\"),y:+t.attr(\"y2\")};var x=o.x-s.x,b=o.y-s.y;if(c=(l=Math.atan2(b,x))+Math.PI,m&&y&&m+y>Math.sqrt(x*x+b*b))return void P();if(m){if(m*m>x*x+b*b)return void P();var _=m*Math.cos(l),w=m*Math.sin(l);s.x+=_,s.y+=w,t.attr({x2:s.x,y2:s.y})}if(y){if(y*y>x*x+b*b)return void P();var k=y*Math.cos(l),T=y*Math.sin(l);o.x-=k,o.y-=T,t.attr({x1:o.x,y1:o.y})}}else if(\"path\"===u.nodeName){var M=u.getTotalLength(),A=\"\";if(M<m+y)return void P();var S=u.getPointAtLength(0),E=u.getPointAtLength(.1);l=Math.atan2(S.y-E.y,S.x-E.x),o=u.getPointAtLength(Math.min(y,M)),A=\"0px,\"+y+\"px,\";var L=u.getPointAtLength(M),C=u.getPointAtLength(M-.1);c=Math.atan2(L.y-C.y,L.x-C.x),s=u.getPointAtLength(Math.max(0,M-m)),A+=M-(A?y+m:m)+\"px,\"+M+\"px\",t.style(\"stroke-dasharray\",A)}function P(){t.style(\"stroke-dasharray\",\"0px,100px\")}function O(e,i,o,s){e.path&&(e.noRotate&&(o=0),n.select(u.parentNode).append(\"path\").attr({class:t.attr(\"class\"),d:e.path,transform:\"translate(\"+i.x+\",\"+i.y+\")\"+(o?\"rotate(\"+180*o/Math.PI+\")\":\"\")+\"scale(\"+s+\")\"}).style({fill:a.rgb(r.arrowcolor),\"stroke-width\":0}))}g&&O(f,o,l,d),v&&O(h,s,c,p)}},{\"../color\":592,\"./arrow_paths\":574,d3:165}],583:[function(t,e,r){\"use strict\";var n=t(\"./draw\"),a=t(\"./click\");e.exports={moduleType:\"component\",name:\"annotations\",layoutAttributes:t(\"./attributes\"),supplyLayoutDefaults:t(\"./defaults\"),includeBasePlot:t(\"../../plots/cartesian/include_components\")(\"annotations\"),calcAutorange:t(\"./calc_autorange\"),draw:n.draw,drawOne:n.drawOne,drawRaw:n.drawRaw,hasClickToShow:a.hasClickToShow,onClick:a.onClick,convertCoords:t(\"./convert_coords\")}},{\"../../plots/cartesian/include_components\":775,\"./attributes\":575,\"./calc_autorange\":576,\"./click\":577,\"./convert_coords\":579,\"./defaults\":580,\"./draw\":581}],584:[function(t,e,r){\"use strict\";var n=t(\"../annotations/attributes\"),a=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"../../plot_api/plot_template\").templatedArray;e.exports=a(i(\"annotation\",{visible:n.visible,x:{valType:\"any\"},y:{valType:\"any\"},z:{valType:\"any\"},ax:{valType:\"number\"},ay:{valType:\"number\"},xanchor:n.xanchor,xshift:n.xshift,yanchor:n.yanchor,yshift:n.yshift,text:n.text,textangle:n.textangle,font:n.font,width:n.width,height:n.height,opacity:n.opacity,align:n.align,valign:n.valign,bgcolor:n.bgcolor,bordercolor:n.bordercolor,borderpad:n.borderpad,borderwidth:n.borderwidth,showarrow:n.showarrow,arrowcolor:n.arrowcolor,arrowhead:n.arrowhead,startarrowhead:n.startarrowhead,arrowside:n.arrowside,arrowsize:n.arrowsize,startarrowsize:n.startarrowsize,arrowwidth:n.arrowwidth,standoff:n.standoff,startstandoff:n.startstandoff,hovertext:n.hovertext,hoverlabel:n.hoverlabel,captureevents:n.captureevents}),\"calc\",\"from-root\")},{\"../../plot_api/edit_types\":748,\"../../plot_api/plot_template\":755,\"../annotations/attributes\":575}],585:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/cartesian/axes\");function i(t,e){var r=e.fullSceneLayout.domain,i=e.fullLayout._size,o={pdata:null,type:\"linear\",autorange:!1,range:[-1/0,1/0]};t._xa={},n.extendFlat(t._xa,o),a.setConvert(t._xa),t._xa._offset=i.l+r.x[0]*i.w,t._xa.l2p=function(){return.5*(1+t._pdata[0]/t._pdata[3])*i.w*(r.x[1]-r.x[0])},t._ya={},n.extendFlat(t._ya,o),a.setConvert(t._ya),t._ya._offset=i.t+(1-r.y[1])*i.h,t._ya.l2p=function(){return.5*(1-t._pdata[1]/t._pdata[3])*i.h*(r.y[1]-r.y[0])}}e.exports=function(t){for(var e=t.fullSceneLayout.annotations,r=0;r<e.length;r++)i(e[r],t);t.fullLayout._infolayer.selectAll(\".annotation-\"+t.id).remove()}},{\"../../lib\":717,\"../../plots/cartesian/axes\":765}],586:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/cartesian/axes\"),i=t(\"../../plots/array_container_defaults\"),o=t(\"../annotations/common_defaults\"),s=t(\"./attributes\");function l(t,e,r,i){function l(r,a){return n.coerce(t,e,s,r,a)}function c(t){var n=t+\"axis\",i={_fullLayout:{}};return i._fullLayout[n]=r[n],a.coercePosition(e,i,l,t,t,.5)}l(\"visible\")&&(o(t,e,i.fullLayout,l),c(\"x\"),c(\"y\"),c(\"z\"),n.noneOrAll(t,e,[\"x\",\"y\",\"z\"]),e.xref=\"x\",e.yref=\"y\",e.zref=\"z\",l(\"xanchor\"),l(\"yanchor\"),l(\"xshift\"),l(\"yshift\"),e.showarrow&&(e.axref=\"pixel\",e.ayref=\"pixel\",l(\"ax\",-10),l(\"ay\",-30),n.noneOrAll(t,e,[\"ax\",\"ay\"])))}e.exports=function(t,e,r){i(t,e,{name:\"annotations\",handleItemDefaults:l,fullLayout:r.fullLayout})}},{\"../../lib\":717,\"../../plots/array_container_defaults\":761,\"../../plots/cartesian/axes\":765,\"../annotations/common_defaults\":578,\"./attributes\":584}],587:[function(t,e,r){\"use strict\";var n=t(\"../annotations/draw\").drawRaw,a=t(\"../../plots/gl3d/project\"),i=[\"x\",\"y\",\"z\"];e.exports=function(t){for(var e=t.fullSceneLayout,r=t.dataScale,o=e.annotations,s=0;s<o.length;s++){for(var l=o[s],c=!1,u=0;u<3;u++){var h=i[u],f=l[h],p=e[h+\"axis\"].r2fraction(f);if(p<0||p>1){c=!0;break}}c?t.fullLayout._infolayer.select(\".annotation-\"+t.id+'[data-index=\"'+s+'\"]').remove():(l._pdata=a(t.glplot.cameraParams,[e.xaxis.r2l(l.x)*r[0],e.yaxis.r2l(l.y)*r[1],e.zaxis.r2l(l.z)*r[2]]),n(t.graphDiv,l,s,t.id,l._xa,l._ya))}}},{\"../../plots/gl3d/project\":814,\"../annotations/draw\":581}],588:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../lib\");e.exports={moduleType:\"component\",name:\"annotations3d\",schema:{subplots:{scene:{annotations:t(\"./attributes\")}}},layoutAttributes:t(\"./attributes\"),handleDefaults:t(\"./defaults\"),includeBasePlot:function(t,e){var r=n.subplotsRegistry.gl3d;if(!r)return;for(var i=r.attrRegex,o=Object.keys(t),s=0;s<o.length;s++){var l=o[s];i.test(l)&&(t[l].annotations||[]).length&&(a.pushUnique(e._basePlotModules,r),a.pushUnique(e._subplots.gl3d,l))}},convert:t(\"./convert\"),draw:t(\"./draw\")}},{\"../../lib\":717,\"../../registry\":846,\"./attributes\":584,\"./convert\":585,\"./defaults\":586,\"./draw\":587}],589:[function(t,e,r){\"use strict\";e.exports=t(\"world-calendars/dist/main\"),t(\"world-calendars/dist/plus\"),t(\"world-calendars/dist/calendars/chinese\"),t(\"world-calendars/dist/calendars/coptic\"),t(\"world-calendars/dist/calendars/discworld\"),t(\"world-calendars/dist/calendars/ethiopian\"),t(\"world-calendars/dist/calendars/hebrew\"),t(\"world-calendars/dist/calendars/islamic\"),t(\"world-calendars/dist/calendars/julian\"),t(\"world-calendars/dist/calendars/mayan\"),t(\"world-calendars/dist/calendars/nanakshahi\"),t(\"world-calendars/dist/calendars/nepali\"),t(\"world-calendars/dist/calendars/persian\"),t(\"world-calendars/dist/calendars/taiwan\"),t(\"world-calendars/dist/calendars/thai\"),t(\"world-calendars/dist/calendars/ummalqura\")},{\"world-calendars/dist/calendars/chinese\":556,\"world-calendars/dist/calendars/coptic\":557,\"world-calendars/dist/calendars/discworld\":558,\"world-calendars/dist/calendars/ethiopian\":559,\"world-calendars/dist/calendars/hebrew\":560,\"world-calendars/dist/calendars/islamic\":561,\"world-calendars/dist/calendars/julian\":562,\"world-calendars/dist/calendars/mayan\":563,\"world-calendars/dist/calendars/nanakshahi\":564,\"world-calendars/dist/calendars/nepali\":565,\"world-calendars/dist/calendars/persian\":566,\"world-calendars/dist/calendars/taiwan\":567,\"world-calendars/dist/calendars/thai\":568,\"world-calendars/dist/calendars/ummalqura\":569,\"world-calendars/dist/main\":570,\"world-calendars/dist/plus\":571}],590:[function(t,e,r){\"use strict\";var n=t(\"./calendars\"),a=t(\"../../lib\"),i=t(\"../../constants/numerical\"),o=i.EPOCHJD,s=i.ONEDAY,l={valType:\"enumerated\",values:Object.keys(n.calendars),editType:\"calc\",dflt:\"gregorian\"},c=function(t,e,r,n){var i={};return i[r]=l,a.coerce(t,e,i,r,n)},u=\"##\",h={d:{0:\"dd\",\"-\":\"d\"},e:{0:\"d\",\"-\":\"d\"},a:{0:\"D\",\"-\":\"D\"},A:{0:\"DD\",\"-\":\"DD\"},j:{0:\"oo\",\"-\":\"o\"},W:{0:\"ww\",\"-\":\"w\"},m:{0:\"mm\",\"-\":\"m\"},b:{0:\"M\",\"-\":\"M\"},B:{0:\"MM\",\"-\":\"MM\"},y:{0:\"yy\",\"-\":\"yy\"},Y:{0:\"yyyy\",\"-\":\"yyyy\"},U:u,w:u,c:{0:\"D M d %X yyyy\",\"-\":\"D M d %X yyyy\"},x:{0:\"mm/dd/yyyy\",\"-\":\"mm/dd/yyyy\"}};var f={};function p(t){var e=f[t];return e||(e=f[t]=n.instance(t))}function d(t){return a.extendFlat({},l,{description:t})}function g(t){return\"Sets the calendar system to use with `\"+t+\"` date data.\"}var v={xcalendar:d(g(\"x\"))},m=a.extendFlat({},v,{ycalendar:d(g(\"y\"))}),y=a.extendFlat({},m,{zcalendar:d(g(\"z\"))}),x=d([\"Sets the calendar system to use for `range` and `tick0`\",\"if this is a date axis. This does not set the calendar for\",\"interpreting data on this axis, that's specified in the trace\",\"or via the global `layout.calendar`\"].join(\" \"));e.exports={moduleType:\"component\",name:\"calendars\",schema:{traces:{scatter:m,bar:m,box:m,heatmap:m,contour:m,histogram:m,histogram2d:m,histogram2dcontour:m,scatter3d:y,surface:y,mesh3d:y,scattergl:m,ohlc:v,candlestick:v},layout:{calendar:d([\"Sets the default calendar system to use for interpreting and\",\"displaying dates throughout the plot.\"].join(\" \"))},subplots:{xaxis:{calendar:x},yaxis:{calendar:x},scene:{xaxis:{calendar:x},yaxis:{calendar:x},zaxis:{calendar:x}},polar:{radialaxis:{calendar:x}}},transforms:{filter:{valuecalendar:d([\"Sets the calendar system to use for `value`, if it is a date.\"].join(\" \")),targetcalendar:d([\"Sets the calendar system to use for `target`, if it is an\",\"array of dates. If `target` is a string (eg *x*) we use the\",\"corresponding trace attribute (eg `xcalendar`) if it exists,\",\"even if `targetcalendar` is provided.\"].join(\" \"))}}},layoutAttributes:l,handleDefaults:c,handleTraceDefaults:function(t,e,r,n){for(var a=0;a<r.length;a++)c(t,e,r[a]+\"calendar\",n.calendar)},CANONICAL_SUNDAY:{chinese:\"2000-01-02\",coptic:\"2000-01-03\",discworld:\"2000-01-03\",ethiopian:\"2000-01-05\",hebrew:\"5000-01-01\",islamic:\"1000-01-02\",julian:\"2000-01-03\",mayan:\"5000-01-01\",nanakshahi:\"1000-01-05\",nepali:\"2000-01-05\",persian:\"1000-01-01\",jalali:\"1000-01-01\",taiwan:\"1000-01-04\",thai:\"2000-01-04\",ummalqura:\"1400-01-06\"},CANONICAL_TICK:{chinese:\"2000-01-01\",coptic:\"2000-01-01\",discworld:\"2000-01-01\",ethiopian:\"2000-01-01\",hebrew:\"5000-01-01\",islamic:\"1000-01-01\",julian:\"2000-01-01\",mayan:\"5000-01-01\",nanakshahi:\"1000-01-01\",nepali:\"2000-01-01\",persian:\"1000-01-01\",jalali:\"1000-01-01\",taiwan:\"1000-01-01\",thai:\"2000-01-01\",ummalqura:\"1400-01-01\"},DFLTRANGE:{chinese:[\"2000-01-01\",\"2001-01-01\"],coptic:[\"1700-01-01\",\"1701-01-01\"],discworld:[\"1800-01-01\",\"1801-01-01\"],ethiopian:[\"2000-01-01\",\"2001-01-01\"],hebrew:[\"5700-01-01\",\"5701-01-01\"],islamic:[\"1400-01-01\",\"1401-01-01\"],julian:[\"2000-01-01\",\"2001-01-01\"],mayan:[\"5200-01-01\",\"5201-01-01\"],nanakshahi:[\"0500-01-01\",\"0501-01-01\"],nepali:[\"2000-01-01\",\"2001-01-01\"],persian:[\"1400-01-01\",\"1401-01-01\"],jalali:[\"1400-01-01\",\"1401-01-01\"],taiwan:[\"0100-01-01\",\"0101-01-01\"],thai:[\"2500-01-01\",\"2501-01-01\"],ummalqura:[\"1400-01-01\",\"1401-01-01\"]},getCal:p,worldCalFmt:function(t,e,r){for(var n,a,i,l,c,f=Math.floor((e+.05)/s)+o,d=p(r).fromJD(f),g=0;-1!==(g=t.indexOf(\"%\",g));)\"0\"===(n=t.charAt(g+1))||\"-\"===n||\"_\"===n?(i=3,a=t.charAt(g+2),\"_\"===n&&(n=\"-\")):(a=n,n=\"0\",i=2),(l=h[a])?(c=l===u?u:d.formatDate(l[n]),t=t.substr(0,g)+c+t.substr(g+i),g+=c.length):g+=i;return t}}},{\"../../constants/numerical\":693,\"../../lib\":717,\"./calendars\":589}],591:[function(t,e,r){\"use strict\";r.defaults=[\"#1f77b4\",\"#ff7f0e\",\"#2ca02c\",\"#d62728\",\"#9467bd\",\"#8c564b\",\"#e377c2\",\"#7f7f7f\",\"#bcbd22\",\"#17becf\"],r.defaultLine=\"#444\",r.lightLine=\"#eee\",r.background=\"#fff\",r.borderLine=\"#BEC8D9\",r.lightFraction=1e3/11},{}],592:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\"),a=t(\"fast-isnumeric\"),i=e.exports={},o=t(\"./attributes\");i.defaults=o.defaults;var s=i.defaultLine=o.defaultLine;i.lightLine=o.lightLine;var l=i.background=o.background;function c(t){if(a(t)||\"string\"!=typeof t)return t;var e=t.trim();if(\"rgb\"!==e.substr(0,3))return t;var r=e.match(/^rgba?\\s*\\(([^()]*)\\)$/);if(!r)return t;var n=r[1].trim().split(/\\s*[\\s,]\\s*/),i=\"a\"===e.charAt(3)&&4===n.length;if(!i&&3!==n.length)return t;for(var o=0;o<n.length;o++){if(!n[o].length)return t;if(n[o]=Number(n[o]),!(n[o]>=0))return t;if(3===o)n[o]>1&&(n[o]=1);else if(n[o]>=1)return t}var s=Math.round(255*n[0])+\", \"+Math.round(255*n[1])+\", \"+Math.round(255*n[2]);return i?\"rgba(\"+s+\", \"+n[3]+\")\":\"rgb(\"+s+\")\"}i.tinyRGB=function(t){var e=t.toRgb();return\"rgb(\"+Math.round(e.r)+\", \"+Math.round(e.g)+\", \"+Math.round(e.b)+\")\"},i.rgb=function(t){return i.tinyRGB(n(t))},i.opacity=function(t){return t?n(t).getAlpha():0},i.addOpacity=function(t,e){var r=n(t).toRgb();return\"rgba(\"+Math.round(r.r)+\", \"+Math.round(r.g)+\", \"+Math.round(r.b)+\", \"+e+\")\"},i.combine=function(t,e){var r=n(t).toRgb();if(1===r.a)return n(t).toRgbString();var a=n(e||l).toRgb(),i=1===a.a?a:{r:255*(1-a.a)+a.r*a.a,g:255*(1-a.a)+a.g*a.a,b:255*(1-a.a)+a.b*a.a},o={r:i.r*(1-r.a)+r.r*r.a,g:i.g*(1-r.a)+r.g*r.a,b:i.b*(1-r.a)+r.b*r.a};return n(o).toRgbString()},i.contrast=function(t,e,r){var a=n(t);return 1!==a.getAlpha()&&(a=n(i.combine(t,l))),(a.isDark()?e?a.lighten(e):l:r?a.darken(r):s).toString()},i.stroke=function(t,e){var r=n(e);t.style({stroke:i.tinyRGB(r),\"stroke-opacity\":r.getAlpha()})},i.fill=function(t,e){var r=n(e);t.style({fill:i.tinyRGB(r),\"fill-opacity\":r.getAlpha()})},i.clean=function(t){if(t&&\"object\"==typeof t){var e,r,n,a,o=Object.keys(t);for(e=0;e<o.length;e++)if(a=t[n=o[e]],\"color\"===n.substr(n.length-5))if(Array.isArray(a))for(r=0;r<a.length;r++)a[r]=c(a[r]);else t[n]=c(a);else if(\"colorscale\"===n.substr(n.length-10)&&Array.isArray(a))for(r=0;r<a.length;r++)Array.isArray(a[r])&&(a[r][1]=c(a[r][1]));else if(Array.isArray(a)){var s=a[0];if(!Array.isArray(s)&&s&&\"object\"==typeof s)for(r=0;r<a.length;r++)i.clean(a[r])}else a&&\"object\"==typeof a&&i.clean(a)}}},{\"./attributes\":591,\"fast-isnumeric\":228,tinycolor2:536}],593:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/layout_attributes\"),a=t(\"../../plots/font_attributes\"),i=t(\"../../lib/extend\").extendFlat,o=t(\"../../plot_api/edit_types\").overrideAll;e.exports=o({thicknessmode:{valType:\"enumerated\",values:[\"fraction\",\"pixels\"],dflt:\"pixels\"},thickness:{valType:\"number\",min:0,dflt:30},lenmode:{valType:\"enumerated\",values:[\"fraction\",\"pixels\"],dflt:\"fraction\"},len:{valType:\"number\",min:0,dflt:1},x:{valType:\"number\",dflt:1.02,min:-2,max:3},xanchor:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"left\"},xpad:{valType:\"number\",min:0,dflt:10},y:{valType:\"number\",dflt:.5,min:-2,max:3},yanchor:{valType:\"enumerated\",values:[\"top\",\"middle\",\"bottom\"],dflt:\"middle\"},ypad:{valType:\"number\",min:0,dflt:10},outlinecolor:n.linecolor,outlinewidth:n.linewidth,bordercolor:n.linecolor,borderwidth:{valType:\"number\",min:0,dflt:0},bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\"},tickmode:n.tickmode,nticks:n.nticks,tick0:n.tick0,dtick:n.dtick,tickvals:n.tickvals,ticktext:n.ticktext,ticks:i({},n.ticks,{dflt:\"\"}),ticklen:n.ticklen,tickwidth:n.tickwidth,tickcolor:n.tickcolor,showticklabels:n.showticklabels,tickfont:a({}),tickangle:n.tickangle,tickformat:n.tickformat,tickformatstops:n.tickformatstops,tickprefix:n.tickprefix,showtickprefix:n.showtickprefix,ticksuffix:n.ticksuffix,showticksuffix:n.showticksuffix,separatethousands:n.separatethousands,exponentformat:n.exponentformat,showexponent:n.showexponent,title:{text:{valType:\"string\"},font:a({}),side:{valType:\"enumerated\",values:[\"right\",\"top\",\"bottom\"],dflt:\"top\"}},_deprecated:{title:{valType:\"string\"},titlefont:a({}),titleside:{valType:\"enumerated\",values:[\"right\",\"top\",\"bottom\"],dflt:\"top\"}}},\"colorbars\",\"from-root\")},{\"../../lib/extend\":708,\"../../plot_api/edit_types\":748,\"../../plots/cartesian/layout_attributes\":777,\"../../plots/font_attributes\":791}],594:[function(t,e,r){\"use strict\";e.exports={cn:{colorbar:\"colorbar\",cbbg:\"cbbg\",cbfill:\"cbfill\",cbfills:\"cbfills\",cbline:\"cbline\",cblines:\"cblines\",cbaxis:\"cbaxis\",cbtitleunshift:\"cbtitleunshift\",cbtitle:\"cbtitle\",cboutline:\"cboutline\",crisp:\"crisp\",jsPlaceholder:\"js-placeholder\"}}},{}],595:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plot_api/plot_template\"),i=t(\"../../plots/cartesian/tick_value_defaults\"),o=t(\"../../plots/cartesian/tick_mark_defaults\"),s=t(\"../../plots/cartesian/tick_label_defaults\"),l=t(\"./attributes\");e.exports=function(t,e,r){var c=a.newContainer(e,\"colorbar\"),u=t.colorbar||{};function h(t,e){return n.coerce(u,c,l,t,e)}var f=h(\"thicknessmode\");h(\"thickness\",\"fraction\"===f?30/(r.width-r.margin.l-r.margin.r):30);var p=h(\"lenmode\");h(\"len\",\"fraction\"===p?1:r.height-r.margin.t-r.margin.b),h(\"x\"),h(\"xanchor\"),h(\"xpad\"),h(\"y\"),h(\"yanchor\"),h(\"ypad\"),n.noneOrAll(u,c,[\"x\",\"y\"]),h(\"outlinecolor\"),h(\"outlinewidth\"),h(\"bordercolor\"),h(\"borderwidth\"),h(\"bgcolor\"),i(u,c,h,\"linear\");var d={outerTicks:!1,font:r.font};s(u,c,h,\"linear\",d),o(u,c,h,\"linear\",d),h(\"title.text\",r._dfltTitle.colorbar),n.coerceFont(h,\"title.font\",r.font),h(\"title.side\")}},{\"../../lib\":717,\"../../plot_api/plot_template\":755,\"../../plots/cartesian/tick_label_defaults\":784,\"../../plots/cartesian/tick_mark_defaults\":785,\"../../plots/cartesian/tick_value_defaults\":786,\"./attributes\":593}],596:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"tinycolor2\"),i=t(\"../../plots/plots\"),o=t(\"../../registry\"),s=t(\"../../plots/cartesian/axes\"),l=t(\"../dragelement\"),c=t(\"../../lib\"),u=t(\"../../lib/extend\").extendFlat,h=t(\"../../lib/setcursor\"),f=t(\"../drawing\"),p=t(\"../color\"),d=t(\"../titles\"),g=t(\"../../lib/svg_text_utils\"),v=t(\"../colorscale/helpers\").flipScale,m=t(\"../../plots/cartesian/axis_defaults\"),y=t(\"../../plots/cartesian/position_defaults\"),x=t(\"../../plots/cartesian/layout_attributes\"),b=t(\"../../constants/alignment\"),_=b.LINE_SPACING,w=b.FROM_TL,k=b.FROM_BR,T=t(\"./constants\").cn;e.exports={draw:function(t){var e=t._fullLayout._infolayer.selectAll(\"g.\"+T.colorbar).data(function(t){var e,r,n,a,i=t._fullLayout,o=t.calcdata,s=[];function l(t){return u(t,{_fillcolor:null,_line:{color:null,width:null,dash:null},_levels:{start:null,end:null,size:null},_filllevels:null,_fillgradient:null,_zrange:null})}function c(){\"function\"==typeof a.calc?a.calc(t,n,e):(e._fillgradient=r.reversescale?v(r.colorscale):r.colorscale,e._zrange=[r[a.min],r[a.max]])}for(var h=0;h<o.length;h++){var f=o[h],p=(n=f[0].trace)._module.colorbar;if(!0===n.visible&&p)for(var d=Array.isArray(p),g=d?p:[p],m=0;m<g.length;m++){var y=(a=g[m]).container;(r=y?n[y]:n)&&r.showscale&&((e=l(r.colorbar))._id=\"cb\"+n.uid+(d&&y?\"-\"+y:\"\"),e._traceIndex=n.index,e._propPrefix=(y?y+\".\":\"\")+\"colorbar.\",e._meta=n._meta,c(),s.push(e))}}for(var x in i._colorAxes)if((r=i[x]).showscale){var b=i._colorAxes[x];(e=l(r.colorbar))._id=\"cb\"+x,e._propPrefix=x+\".colorbar.\",e._meta=i._meta,a={min:\"cmin\",max:\"cmax\"},\"heatmap\"!==b[0]&&(n=b[1],a.calc=n._module.colorbar.calc),c(),s.push(e)}return s}(t),function(t){return t._id});e.enter().append(\"g\").attr(\"class\",function(t){return t._id}).classed(T.colorbar,!0),e.each(function(e){var r=n.select(this);c.ensureSingle(r,\"rect\",T.cbbg),c.ensureSingle(r,\"g\",T.cbfills),c.ensureSingle(r,\"g\",T.cblines),c.ensureSingle(r,\"g\",T.cbaxis,function(t){t.classed(T.crisp,!0)}),c.ensureSingle(r,\"g\",T.cbtitleunshift,function(t){t.append(\"g\").classed(T.cbtitle,!0)}),c.ensureSingle(r,\"rect\",T.cboutline);var v=function(t,e,r){var o=r._fullLayout,l=o._size,h=e._fillcolor,v=e._line,b=e.title,M=b.side,A=e._zrange||n.extent((\"function\"==typeof h?h:v.color).domain()),S=\"function\"==typeof v.color?v.color:function(){return v.color},E=\"function\"==typeof h?h:function(){return h},L=e._levels,C=function(t,e,r){var n,a,i=e._levels,o=[],s=[],l=i.end+i.size/100,c=i.size,u=1.001*r[0]-.001*r[1],h=1.001*r[1]-.001*r[0];for(a=0;a<1e5&&(n=i.start+a*c,!(c>0?n>=l:n<=l));a++)n>u&&n<h&&o.push(n);if(e._fillgradient)s=[0];else if(\"function\"==typeof e._fillcolor){var f=e._filllevels;if(f)for(l=f.end+f.size/100,c=f.size,a=0;a<1e5&&(n=f.start+a*c,!(c>0?n>=l:n<=l));a++)n>r[0]&&n<r[1]&&s.push(n);else(s=o.map(function(t){return t-i.size/2})).push(s[s.length-1]+i.size)}else e._fillcolor&&\"string\"==typeof e._fillcolor&&(s=[0]);return i.size<0&&(o.reverse(),s.reverse()),{line:o,fill:s}}(0,e,A),P=C.fill,O=C.line,z=Math.round(e.thickness*(\"fraction\"===e.thicknessmode?l.w:1)),I=z/l.w,D=Math.round(e.len*(\"fraction\"===e.lenmode?l.h:1)),R=D/l.h,F=e.xpad/l.w,B=(e.borderwidth+e.outlinewidth)/2,N=e.ypad/l.h,j=Math.round(e.x*l.w+e.xpad),V=e.x-I*({middle:.5,right:1}[e.xanchor]||0),U=e.y+R*(({top:-.5,bottom:.5}[e.yanchor]||0)-.5),q=Math.round(l.h*(1-U)),H=q-D;e._lenFrac=R,e._thickFrac=I,e._xLeftFrac=V,e._yBottomFrac=U;var G=e._axis=function(t,e,r){var n=t._fullLayout,a={type:\"linear\",range:r,tickmode:e.tickmode,nticks:e.nticks,tick0:e.tick0,dtick:e.dtick,tickvals:e.tickvals,ticktext:e.ticktext,ticks:e.ticks,ticklen:e.ticklen,tickwidth:e.tickwidth,tickcolor:e.tickcolor,showticklabels:e.showticklabels,tickfont:e.tickfont,tickangle:e.tickangle,tickformat:e.tickformat,exponentformat:e.exponentformat,separatethousands:e.separatethousands,showexponent:e.showexponent,showtickprefix:e.showtickprefix,tickprefix:e.tickprefix,showticksuffix:e.showticksuffix,ticksuffix:e.ticksuffix,title:e.title,showline:!0,anchor:\"free\",side:\"right\",position:1},i={type:\"linear\",_id:\"y\"+e._id},o={letter:\"y\",font:n.font,noHover:!0,noTickson:!0,calendar:n.calendar};function s(t,e){return c.coerce(a,i,x,t,e)}return m(a,i,s,o,n),y(a,i,s,o),i}(r,e,A);if(G.position=e.x+F+I,-1!==[\"top\",\"bottom\"].indexOf(M)&&(G.title.side=M,G.titlex=e.x+F,G.titley=U+(\"top\"===b.side?R-N:N)),v.color&&\"auto\"===e.tickmode){G.tickmode=\"linear\",G.tick0=L.start;var Y=L.size,W=c.constrain((q-H)/50,4,15)+1,X=(A[1]-A[0])/((e.nticks||W)*Y);if(X>1){var Z=Math.pow(10,Math.floor(Math.log(X)/Math.LN10));Y*=Z*c.roundUp(X/Z,[2,5,10]),(Math.abs(L.start)/L.size+1e-6)%1<2e-6&&(G.tick0=0)}G.dtick=Y}G.domain=[U+N,U+R-N],G.setScale(),t.attr(\"transform\",\"translate(\"+Math.round(l.l)+\",\"+Math.round(l.t)+\")\");var J,K=t.select(\".\"+T.cbtitleunshift).attr(\"transform\",\"translate(-\"+Math.round(l.l)+\",-\"+Math.round(l.t)+\")\"),Q=t.select(\".\"+T.cbaxis),$=0;function tt(n,a){var i={propContainer:G,propName:e._propPrefix+\"title\",traceIndex:e._traceIndex,_meta:e._meta,placeholder:o._dfltTitle.colorbar,containerGroup:t.select(\".\"+T.cbtitle)},s=\"h\"===n.charAt(0)?n.substr(1):\"h\"+n;t.selectAll(\".\"+s+\",.\"+s+\"-math-group\").remove(),d.draw(r,n,u(i,a||{}))}return c.syncOrAsync([i.previousPromises,function(){if(-1!==[\"top\",\"bottom\"].indexOf(M)){var t,r=l.l+(e.x+F)*l.w,n=G.title.font.size;t=\"top\"===M?(1-(U+R-N))*l.h+l.t+3+.75*n:(1-(U+N))*l.h+l.t-3-.25*n,tt(G._id+\"title\",{attributes:{x:r,y:t,\"text-anchor\":\"start\"}})}},function(){if(-1!==[\"top\",\"bottom\"].indexOf(M)){var i=t.select(\".\"+T.cbtitle),o=i.select(\"text\"),u=[-e.outlinewidth/2,e.outlinewidth/2],h=i.select(\".h\"+G._id+\"title-math-group\").node(),p=15.6;if(o.node()&&(p=parseInt(o.node().style.fontSize,10)*_),h?($=f.bBox(h).height)>p&&(u[1]-=($-p)/2):o.node()&&!o.classed(T.jsPlaceholder)&&($=f.bBox(o.node()).height),$){if($+=5,\"top\"===M)G.domain[1]-=$/l.h,u[1]*=-1;else{G.domain[0]+=$/l.h;var d=g.lineCount(o);u[1]+=(1-d)*p}i.attr(\"transform\",\"translate(\"+u+\")\"),G.setScale()}}t.selectAll(\".\"+T.cbfills+\",.\"+T.cblines).attr(\"transform\",\"translate(0,\"+Math.round(l.h*(1-G.domain[1]))+\")\"),Q.attr(\"transform\",\"translate(0,\"+Math.round(-l.t)+\")\");var m=t.select(\".\"+T.cbfills).selectAll(\"rect.\"+T.cbfill).data(P);m.enter().append(\"rect\").classed(T.cbfill,!0).style(\"stroke\",\"none\"),m.exit().remove();var y=A.map(G.c2p).map(Math.round).sort(function(t,e){return t-e});m.each(function(t,i){var o=[0===i?A[0]:(P[i]+P[i-1])/2,i===P.length-1?A[1]:(P[i]+P[i+1])/2].map(G.c2p).map(Math.round);o[1]=c.constrain(o[1]+(o[1]>o[0])?1:-1,y[0],y[1]);var s=n.select(this).attr({x:j,width:Math.max(z,2),y:n.min(o),height:Math.max(n.max(o)-n.min(o),2)});if(e._fillgradient)f.gradient(s,r,e._id,\"vertical\",e._fillgradient,\"fill\");else{var l=E(t).replace(\"e-\",\"\");s.attr(\"fill\",a(l).toHexString())}});var x=t.select(\".\"+T.cblines).selectAll(\"path.\"+T.cbline).data(v.color&&v.width?O:[]);x.enter().append(\"path\").classed(T.cbline,!0),x.exit().remove(),x.each(function(t){n.select(this).attr(\"d\",\"M\"+j+\",\"+(Math.round(G.c2p(t))+v.width/2%1)+\"h\"+z).call(f.lineGroupStyle,v.width,S(t),v.dash)}),Q.selectAll(\"g.\"+G._id+\"tick,path\").remove();var b=j+z+(e.outlinewidth||0)/2-(\"outside\"===e.ticks?1:0),w=s.calcTicks(G),k=s.makeTransFn(G),L=s.getTickSigns(G)[2];return s.drawTicks(r,G,{vals:\"inside\"===G.ticks?s.clipEnds(G,w):w,layer:Q,path:s.makeTickPath(G,b,L),transFn:k}),s.drawLabels(r,G,{vals:w,layer:Q,transFn:k,labelFns:s.makeLabelFns(G,b)})},function(){if(-1===[\"top\",\"bottom\"].indexOf(M)){var t=G.title.font.size,e=G._offset+G._length/2,a=l.l+(G.position||0)*l.w+(\"right\"===G.side?10+t*(G.showticklabels?1:.5):-10-t*(G.showticklabels?.5:0));tt(\"h\"+G._id+\"title\",{avoid:{selection:n.select(r).selectAll(\"g.\"+G._id+\"tick\"),side:M,offsetLeft:l.l,offsetTop:0,maxShift:o.width},attributes:{x:a,y:e,\"text-anchor\":\"middle\"},transform:{rotate:\"-90\",offset:0}})}},i.previousPromises,function(){var n=z+e.outlinewidth/2+f.bBox(Q.node()).width;if((J=K.select(\"text\")).node()&&!J.classed(T.jsPlaceholder)){var a,o=K.select(\".h\"+G._id+\"title-math-group\").node();a=o&&-1!==[\"top\",\"bottom\"].indexOf(M)?f.bBox(o).width:f.bBox(K.node()).right-j-l.l,n=Math.max(n,a)}var s=2*e.xpad+n+e.borderwidth+e.outlinewidth/2,c=q-H;t.select(\".\"+T.cbbg).attr({x:j-e.xpad-(e.borderwidth+e.outlinewidth)/2,y:H-B,width:Math.max(s,2),height:Math.max(c+2*B,2)}).call(p.fill,e.bgcolor).call(p.stroke,e.bordercolor).style(\"stroke-width\",e.borderwidth),t.selectAll(\".\"+T.cboutline).attr({x:j,y:H+e.ypad+(\"top\"===M?$:0),width:Math.max(z,2),height:Math.max(c-2*e.ypad-$,2)}).call(p.stroke,e.outlinecolor).style({fill:\"none\",\"stroke-width\":e.outlinewidth});var u=({center:.5,right:1}[e.xanchor]||0)*s;t.attr(\"transform\",\"translate(\"+(l.l-u)+\",\"+l.t+\")\");var h={},d=w[e.yanchor],g=k[e.yanchor];\"pixels\"===e.lenmode?(h.y=e.y,h.t=c*d,h.b=c*g):(h.t=h.b=0,h.yt=e.y+e.len*d,h.yb=e.y-e.len*g);var v=w[e.xanchor],m=k[e.xanchor];if(\"pixels\"===e.thicknessmode)h.x=e.x,h.l=s*v,h.r=s*m;else{var y=s-z;h.l=y*v,h.r=y*m,h.xl=e.x-e.thickness*v,h.xr=e.x+e.thickness*m}i.autoMargin(r,e._id,h)}],r)}(r,e,t);v&&v.then&&(t._promises||[]).push(v),t._context.edits.colorbarPosition&&function(t,e,r){var n,a,i,s=r._fullLayout._size;l.init({element:t.node(),gd:r,prepFn:function(){n=t.attr(\"transform\"),h(t)},moveFn:function(r,o){t.attr(\"transform\",n+\" translate(\"+r+\",\"+o+\")\"),a=l.align(e._xLeftFrac+r/s.w,e._thickFrac,0,1,e.xanchor),i=l.align(e._yBottomFrac-o/s.h,e._lenFrac,0,1,e.yanchor);var c=l.getCursor(a,i,e.xanchor,e.yanchor);h(t,c)},doneFn:function(){if(h(t),void 0!==a&&void 0!==i){var n={};n[e._propPrefix+\"x\"]=a,n[e._propPrefix+\"y\"]=i,void 0!==e._traceIndex?o.call(\"_guiRestyle\",r,n,e._traceIndex):o.call(\"_guiRelayout\",r,n)}}})}(r,e,t)}),e.exit().each(function(e){i.autoMargin(t,e._id)}).remove(),e.order()}}},{\"../../constants/alignment\":686,\"../../lib\":717,\"../../lib/extend\":708,\"../../lib/setcursor\":737,\"../../lib/svg_text_utils\":741,\"../../plots/cartesian/axes\":765,\"../../plots/cartesian/axis_defaults\":767,\"../../plots/cartesian/layout_attributes\":777,\"../../plots/cartesian/position_defaults\":780,\"../../plots/plots\":826,\"../../registry\":846,\"../color\":592,\"../colorscale/helpers\":603,\"../dragelement\":610,\"../drawing\":613,\"../titles\":679,\"./constants\":594,d3:165,tinycolor2:536}],597:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t){return n.isPlainObject(t.colorbar)}},{\"../../lib\":717}],598:[function(t,e,r){\"use strict\";e.exports={moduleType:\"component\",name:\"colorbar\",attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),draw:t(\"./draw\").draw,hasColorbar:t(\"./has_colorbar\")}},{\"./attributes\":593,\"./defaults\":595,\"./draw\":596,\"./has_colorbar\":597}],599:[function(t,e,r){\"use strict\";var n=t(\"../colorbar/attributes\"),a=t(\"../../lib/regex\").counter,i=t(\"./scales.js\").scales;Object.keys(i);function o(t){return\"`\"+t+\"`\"}e.exports=function(t,e){t=t||\"\";var r,s=(e=e||{}).cLetter||\"c\",l=(\"onlyIfNumerical\"in e?e.onlyIfNumerical:Boolean(t),\"noScale\"in e?e.noScale:\"marker.line\"===t),c=\"showScaleDflt\"in e?e.showScaleDflt:\"z\"===s,u=\"string\"==typeof e.colorscaleDflt?i[e.colorscaleDflt]:null,h=e.editTypeOverride||\"\",f=t?t+\".\":\"\";\"colorAttr\"in e?(r=e.colorAttr,e.colorAttr):o(f+(r={z:\"z\",c:\"color\"}[s]));var p=s+\"auto\",d=s+\"min\",g=s+\"max\",v=s+\"mid\",m=(o(f+p),o(f+d),o(f+g),{});m[d]=m[g]=void 0;var y={};y[p]=!1;var x={};return\"color\"===r&&(x.color={valType:\"color\",arrayOk:!0,editType:h||\"style\"},e.anim&&(x.color.anim=!0)),x[p]={valType:\"boolean\",dflt:!0,editType:\"calc\",impliedEdits:m},x[d]={valType:\"number\",dflt:null,editType:h||\"plot\",impliedEdits:y},x[g]={valType:\"number\",dflt:null,editType:h||\"plot\",impliedEdits:y},x[v]={valType:\"number\",dflt:null,editType:\"calc\",impliedEdits:m},x.colorscale={valType:\"colorscale\",editType:\"calc\",dflt:u,impliedEdits:{autocolorscale:!1}},x.autocolorscale={valType:\"boolean\",dflt:!1!==e.autoColorDflt,editType:\"calc\",impliedEdits:{colorscale:void 0}},x.reversescale={valType:\"boolean\",dflt:!1,editType:\"plot\"},l||(x.showscale={valType:\"boolean\",dflt:c,editType:\"calc\"},x.colorbar=n),e.noColorAxis||(x.coloraxis={valType:\"subplotid\",regex:a(\"coloraxis\"),dflt:null,editType:\"calc\"}),x}},{\"../../lib/regex\":733,\"../colorbar/attributes\":593,\"./scales.js\":607}],600:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib\"),i=t(\"./helpers\").extractOpts;e.exports=function(t,e,r){var o,s=t._fullLayout,l=r.vals,c=r.containerStr,u=c?a.nestedProperty(e,c).get():e,h=i(u),f=!1!==h.auto,p=h.min,d=h.max,g=h.mid,v=function(){return a.aggNums(Math.min,null,l)},m=function(){return a.aggNums(Math.max,null,l)};(void 0===p?p=v():f&&(p=u._colorAx&&n(p)?Math.min(p,v()):v()),void 0===d?d=m():f&&(d=u._colorAx&&n(d)?Math.max(d,m()):m()),f&&void 0!==g&&(d-g>g-p?p=g-(d-g):d-g<g-p&&(d=g+(g-p))),p===d&&(p-=.5,d+=.5),h._sync(\"min\",p),h._sync(\"max\",d),h.autocolorscale)&&(o=p*d<0?s.colorscale.diverging:p>=0?s.colorscale.sequential:s.colorscale.sequentialminus,h._sync(\"colorscale\",o))}},{\"../../lib\":717,\"./helpers\":603,\"fast-isnumeric\":228}],601:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./helpers\").hasColorscale,i=t(\"./helpers\").extractOpts;e.exports=function(t,e){function r(t,e){var r=t[\"_\"+e];void 0!==r&&(t[e]=r)}function o(t,a){var o=a.container?n.nestedProperty(t,a.container).get():t;if(o)if(o.coloraxis)o._colorAx=e[o.coloraxis];else{var s=i(o),l=s.auto;(l||void 0===s.min)&&r(o,a.min),(l||void 0===s.max)&&r(o,a.max),s.autocolorscale&&r(o,\"colorscale\")}}for(var s=0;s<t.length;s++){var l=t[s],c=l._module.colorbar;if(c)if(Array.isArray(c))for(var u=0;u<c.length;u++)o(l,c[u]);else o(l,c);a(l,\"marker.line\")&&o(l,{container:\"marker.line\",min:\"cmin\",max:\"cmax\"})}for(var h in e._colorAxes)o(e[h],{min:\"cmin\",max:\"cmax\"})}},{\"../../lib\":717,\"./helpers\":603}],602:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib\"),i=t(\"../colorbar/has_colorbar\"),o=t(\"../colorbar/defaults\"),s=t(\"./scales\").isValid,l=t(\"../../registry\").traceIs;function c(t,e){var r=e.slice(0,e.length-1);return e?a.nestedProperty(t,r).get()||{}:t}e.exports=function t(e,r,u,h,f){var p=f.prefix,d=f.cLetter,g=\"_module\"in r,v=c(e,p),m=c(r,p),y=c(r._template||{},p)||{},x=function(){return delete e.coloraxis,delete r.coloraxis,t(e,r,u,h,f)};if(g){var b=u._colorAxes||{},_=h(p+\"coloraxis\");if(_){var w=l(r,\"contour\")&&a.nestedProperty(r,\"contours.coloring\").get()||\"heatmap\",k=b[_];return void(k?(k[2].push(x),k[0]!==w&&(k[0]=!1,a.warn([\"Ignoring coloraxis:\",_,\"setting\",\"as it is linked to incompatible colorscales.\"].join(\" \")))):b[_]=[w,r,[x]])}}var T=v[d+\"min\"],M=v[d+\"max\"],A=n(T)&&n(M)&&T<M;h(p+d+\"auto\",!A)?h(p+d+\"mid\"):(h(p+d+\"min\"),h(p+d+\"max\"));var S,E,L=v.colorscale,C=y.colorscale;(void 0!==L&&(S=!s(L)),void 0!==C&&(S=!s(C)),h(p+\"autocolorscale\",S),h(p+\"colorscale\"),h(p+\"reversescale\"),\"marker.line.\"!==p)&&(p&&g&&(E=i(v)),h(p+\"showscale\",E)&&(p&&y&&(m._template=y),o(v,m,u)))}},{\"../../lib\":717,\"../../registry\":846,\"../colorbar/defaults\":595,\"../colorbar/has_colorbar\":597,\"./scales\":607,\"fast-isnumeric\":228}],603:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"tinycolor2\"),i=t(\"fast-isnumeric\"),o=t(\"../../lib\"),s=t(\"../color\"),l=t(\"./scales\").isValid;var c=[\"showscale\",\"autocolorscale\",\"colorscale\",\"reversescale\",\"colorbar\"],u=[\"min\",\"max\",\"mid\",\"auto\"];function h(t){var e,r,n,a=t._colorAx,i=a||t,o={};for(r=0;r<c.length;r++)o[n=c[r]]=i[n];if(a)for(e=\"c\",r=0;r<u.length;r++)o[n=u[r]]=i[\"c\"+n];else{var s;for(r=0;r<u.length;r++)(s=\"c\"+(n=u[r]))in i?o[n]=i[s]:(s=\"z\"+n)in i&&(o[n]=i[s]);e=s.charAt(0)}return o._sync=function(t,r){var n=-1!==u.indexOf(t)?e+t:t;i[n]=i[\"_\"+n]=r},o}function f(t){for(var e=h(t),r=e.min,n=e.max,a=e.reversescale?p(e.colorscale):e.colorscale,i=a.length,o=new Array(i),s=new Array(i),l=0;l<i;l++){var c=a[l];o[l]=r+c[0]*(n-r),s[l]=c[1]}return{domain:o,range:s}}function p(t){for(var e=t.length,r=new Array(e),n=e-1,a=0;n>=0;n--,a++){var i=t[n];r[a]=[1-i[0],i[1]]}return r}function d(t,e){e=e||{};for(var r=t.domain,o=t.range,l=o.length,c=new Array(l),u=0;u<l;u++){var h=a(o[u]).toRgb();c[u]=[h.r,h.g,h.b,h.a]}var f,p=n.scale.linear().domain(r).range(c).clamp(!0),d=e.noNumericCheck,v=e.returnArray;return(f=d&&v?p:d?function(t){return g(p(t))}:v?function(t){return i(t)?p(t):a(t).isValid()?t:s.defaultLine}:function(t){return i(t)?g(p(t)):a(t).isValid()?t:s.defaultLine}).domain=p.domain,f.range=function(){return o},f}function g(t){var e={r:t[0],g:t[1],b:t[2],a:t[3]};return a(e).toRgbString()}e.exports={hasColorscale:function(t,e,r){var n=e?o.nestedProperty(t,e).get()||{}:t,a=n[r||\"color\"],s=!1;if(o.isArrayOrTypedArray(a))for(var c=0;c<a.length;c++)if(i(a[c])){s=!0;break}return o.isPlainObject(n)&&(s||!0===n.showscale||i(n.cmin)&&i(n.cmax)||l(n.colorscale)||o.isPlainObject(n.colorbar))},extractOpts:h,extractScale:f,flipScale:p,makeColorScaleFunc:d,makeColorScaleFuncFromTrace:function(t,e){return d(f(t),e)}}},{\"../../lib\":717,\"../color\":592,\"./scales\":607,d3:165,\"fast-isnumeric\":228,tinycolor2:536}],604:[function(t,e,r){\"use strict\";var n=t(\"./scales\"),a=t(\"./helpers\");e.exports={moduleType:\"component\",name:\"colorscale\",attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyLayoutDefaults:t(\"./layout_defaults\"),handleDefaults:t(\"./defaults\"),crossTraceDefaults:t(\"./cross_trace_defaults\"),calc:t(\"./calc\"),scales:n.scales,defaultScale:n.defaultScale,getScale:n.get,isValidScale:n.isValid,hasColorscale:a.hasColorscale,extractOpts:a.extractOpts,extractScale:a.extractScale,flipScale:a.flipScale,makeColorScaleFunc:a.makeColorScaleFunc,makeColorScaleFuncFromTrace:a.makeColorScaleFuncFromTrace}},{\"./attributes\":599,\"./calc\":600,\"./cross_trace_defaults\":601,\"./defaults\":602,\"./helpers\":603,\"./layout_attributes\":605,\"./layout_defaults\":606,\"./scales\":607}],605:[function(t,e,r){\"use strict\";var n=t(\"../../lib/extend\").extendFlat,a=t(\"./attributes\"),i=t(\"./scales\").scales;e.exports={editType:\"calc\",colorscale:{editType:\"calc\",sequential:{valType:\"colorscale\",dflt:i.Reds,editType:\"calc\"},sequentialminus:{valType:\"colorscale\",dflt:i.Blues,editType:\"calc\"},diverging:{valType:\"colorscale\",dflt:i.RdBu,editType:\"calc\"}},coloraxis:n({_isSubplotObj:!0,editType:\"calc\"},a(\"\",{colorAttr:\"corresponding trace color array(s)\",noColorAxis:!0,showScaleDflt:!0}))}},{\"../../lib/extend\":708,\"./attributes\":599,\"./scales\":607}],606:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plot_api/plot_template\"),i=t(\"./layout_attributes\"),o=t(\"./defaults\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"colorscale.sequential\"),r(\"colorscale.sequentialminus\"),r(\"colorscale.diverging\");var s,l,c=e._colorAxes;function u(t,e){return n.coerce(s,l,i.coloraxis,t,e)}for(var h in c){var f=c[h];if(f[0])s=t[h]||{},(l=a.newContainer(e,h,\"coloraxis\"))._name=h,o(s,l,e,u,{prefix:\"\",cLetter:\"c\"});else{for(var p=0;p<f[2].length;p++)f[2][p]();delete e._colorAxes[h]}}}},{\"../../lib\":717,\"../../plot_api/plot_template\":755,\"./defaults\":602,\"./layout_attributes\":605}],607:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\"),a={Greys:[[0,\"rgb(0,0,0)\"],[1,\"rgb(255,255,255)\"]],YlGnBu:[[0,\"rgb(8,29,88)\"],[.125,\"rgb(37,52,148)\"],[.25,\"rgb(34,94,168)\"],[.375,\"rgb(29,145,192)\"],[.5,\"rgb(65,182,196)\"],[.625,\"rgb(127,205,187)\"],[.75,\"rgb(199,233,180)\"],[.875,\"rgb(237,248,217)\"],[1,\"rgb(255,255,217)\"]],Greens:[[0,\"rgb(0,68,27)\"],[.125,\"rgb(0,109,44)\"],[.25,\"rgb(35,139,69)\"],[.375,\"rgb(65,171,93)\"],[.5,\"rgb(116,196,118)\"],[.625,\"rgb(161,217,155)\"],[.75,\"rgb(199,233,192)\"],[.875,\"rgb(229,245,224)\"],[1,\"rgb(247,252,245)\"]],YlOrRd:[[0,\"rgb(128,0,38)\"],[.125,\"rgb(189,0,38)\"],[.25,\"rgb(227,26,28)\"],[.375,\"rgb(252,78,42)\"],[.5,\"rgb(253,141,60)\"],[.625,\"rgb(254,178,76)\"],[.75,\"rgb(254,217,118)\"],[.875,\"rgb(255,237,160)\"],[1,\"rgb(255,255,204)\"]],Bluered:[[0,\"rgb(0,0,255)\"],[1,\"rgb(255,0,0)\"]],RdBu:[[0,\"rgb(5,10,172)\"],[.35,\"rgb(106,137,247)\"],[.5,\"rgb(190,190,190)\"],[.6,\"rgb(220,170,132)\"],[.7,\"rgb(230,145,90)\"],[1,\"rgb(178,10,28)\"]],Reds:[[0,\"rgb(220,220,220)\"],[.2,\"rgb(245,195,157)\"],[.4,\"rgb(245,160,105)\"],[1,\"rgb(178,10,28)\"]],Blues:[[0,\"rgb(5,10,172)\"],[.35,\"rgb(40,60,190)\"],[.5,\"rgb(70,100,245)\"],[.6,\"rgb(90,120,245)\"],[.7,\"rgb(106,137,247)\"],[1,\"rgb(220,220,220)\"]],Picnic:[[0,\"rgb(0,0,255)\"],[.1,\"rgb(51,153,255)\"],[.2,\"rgb(102,204,255)\"],[.3,\"rgb(153,204,255)\"],[.4,\"rgb(204,204,255)\"],[.5,\"rgb(255,255,255)\"],[.6,\"rgb(255,204,255)\"],[.7,\"rgb(255,153,255)\"],[.8,\"rgb(255,102,204)\"],[.9,\"rgb(255,102,102)\"],[1,\"rgb(255,0,0)\"]],Rainbow:[[0,\"rgb(150,0,90)\"],[.125,\"rgb(0,0,200)\"],[.25,\"rgb(0,25,255)\"],[.375,\"rgb(0,152,255)\"],[.5,\"rgb(44,255,150)\"],[.625,\"rgb(151,255,0)\"],[.75,\"rgb(255,234,0)\"],[.875,\"rgb(255,111,0)\"],[1,\"rgb(255,0,0)\"]],Portland:[[0,\"rgb(12,51,131)\"],[.25,\"rgb(10,136,186)\"],[.5,\"rgb(242,211,56)\"],[.75,\"rgb(242,143,56)\"],[1,\"rgb(217,30,30)\"]],Jet:[[0,\"rgb(0,0,131)\"],[.125,\"rgb(0,60,170)\"],[.375,\"rgb(5,255,255)\"],[.625,\"rgb(255,255,0)\"],[.875,\"rgb(250,0,0)\"],[1,\"rgb(128,0,0)\"]],Hot:[[0,\"rgb(0,0,0)\"],[.3,\"rgb(230,0,0)\"],[.6,\"rgb(255,210,0)\"],[1,\"rgb(255,255,255)\"]],Blackbody:[[0,\"rgb(0,0,0)\"],[.2,\"rgb(230,0,0)\"],[.4,\"rgb(230,210,0)\"],[.7,\"rgb(255,255,255)\"],[1,\"rgb(160,200,255)\"]],Earth:[[0,\"rgb(0,0,130)\"],[.1,\"rgb(0,180,180)\"],[.2,\"rgb(40,210,40)\"],[.4,\"rgb(230,230,50)\"],[.6,\"rgb(120,70,20)\"],[1,\"rgb(255,255,255)\"]],Electric:[[0,\"rgb(0,0,0)\"],[.15,\"rgb(30,0,100)\"],[.4,\"rgb(120,0,100)\"],[.6,\"rgb(160,90,0)\"],[.8,\"rgb(230,200,0)\"],[1,\"rgb(255,250,220)\"]],Viridis:[[0,\"#440154\"],[.06274509803921569,\"#48186a\"],[.12549019607843137,\"#472d7b\"],[.18823529411764706,\"#424086\"],[.25098039215686274,\"#3b528b\"],[.3137254901960784,\"#33638d\"],[.3764705882352941,\"#2c728e\"],[.4392156862745098,\"#26828e\"],[.5019607843137255,\"#21918c\"],[.5647058823529412,\"#1fa088\"],[.6274509803921569,\"#28ae80\"],[.6901960784313725,\"#3fbc73\"],[.7529411764705882,\"#5ec962\"],[.8156862745098039,\"#84d44b\"],[.8784313725490196,\"#addc30\"],[.9411764705882353,\"#d8e219\"],[1,\"#fde725\"]],Cividis:[[0,\"rgb(0,32,76)\"],[.058824,\"rgb(0,42,102)\"],[.117647,\"rgb(0,52,110)\"],[.176471,\"rgb(39,63,108)\"],[.235294,\"rgb(60,74,107)\"],[.294118,\"rgb(76,85,107)\"],[.352941,\"rgb(91,95,109)\"],[.411765,\"rgb(104,106,112)\"],[.470588,\"rgb(117,117,117)\"],[.529412,\"rgb(131,129,120)\"],[.588235,\"rgb(146,140,120)\"],[.647059,\"rgb(161,152,118)\"],[.705882,\"rgb(176,165,114)\"],[.764706,\"rgb(192,177,109)\"],[.823529,\"rgb(209,191,102)\"],[.882353,\"rgb(225,204,92)\"],[.941176,\"rgb(243,219,79)\"],[1,\"rgb(255,233,69)\"]]},i=a.RdBu;function o(t){var e=0;if(!Array.isArray(t)||t.length<2)return!1;if(!t[0]||!t[t.length-1])return!1;if(0!=+t[0][0]||1!=+t[t.length-1][0])return!1;for(var r=0;r<t.length;r++){var a=t[r];if(2!==a.length||+a[0]<e||!n(a[1]).isValid())return!1;e=+a[0]}return!0}e.exports={scales:a,defaultScale:i,get:function(t,e){if(e||(e=i),!t)return e;function r(){try{t=a[t]||JSON.parse(t)}catch(r){t=e}}return\"string\"==typeof t&&(r(),\"string\"==typeof t&&r()),o(t)?t:e},isValid:function(t){return void 0!==a[t]||o(t)}}},{tinycolor2:536}],608:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,a){var i=(t-r)/(n-r),o=i+e/(n-r),s=(i+o)/2;return\"left\"===a||\"bottom\"===a?i:\"center\"===a||\"middle\"===a?s:\"right\"===a||\"top\"===a?o:i<2/3-s?i:o>4/3-s?o:s}},{}],609:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=[[\"sw-resize\",\"s-resize\",\"se-resize\"],[\"w-resize\",\"move\",\"e-resize\"],[\"nw-resize\",\"n-resize\",\"ne-resize\"]];e.exports=function(t,e,r,i){return t=\"left\"===r?0:\"center\"===r?1:\"right\"===r?2:n.constrain(Math.floor(3*t),0,2),e=\"bottom\"===i?0:\"middle\"===i?1:\"top\"===i?2:n.constrain(Math.floor(3*e),0,2),a[e][t]}},{\"../../lib\":717}],610:[function(t,e,r){\"use strict\";var n=t(\"mouse-event-offset\"),a=t(\"has-hover\"),i=t(\"has-passive-events\"),o=t(\"../../lib\").removeElement,s=t(\"../../plots/cartesian/constants\"),l=e.exports={};l.align=t(\"./align\"),l.getCursor=t(\"./cursor\");var c=t(\"./unhover\");function u(){var t=document.createElement(\"div\");t.className=\"dragcover\";var e=t.style;return e.position=\"fixed\",e.left=0,e.right=0,e.top=0,e.bottom=0,e.zIndex=999999999,e.background=\"none\",document.body.appendChild(t),t}function h(t){return n(t.changedTouches?t.changedTouches[0]:t,document.body)}l.unhover=c.wrapped,l.unhoverRaw=c.raw,l.init=function(t){var e,r,n,c,f,p,d,g,v=t.gd,m=1,y=v._context.doubleClickDelay,x=t.element;v._mouseDownTime||(v._mouseDownTime=0),x.style.pointerEvents=\"all\",x.onmousedown=_,i?(x._ontouchstart&&x.removeEventListener(\"touchstart\",x._ontouchstart),x._ontouchstart=_,x.addEventListener(\"touchstart\",_,{passive:!1})):x.ontouchstart=_;var b=t.clampFn||function(t,e,r){return Math.abs(t)<r&&(t=0),Math.abs(e)<r&&(e=0),[t,e]};function _(i){v._dragged=!1,v._dragging=!0;var o=h(i);e=o[0],r=o[1],d=i.target,p=i,g=2===i.buttons||i.ctrlKey,\"undefined\"==typeof i.clientX&&\"undefined\"==typeof i.clientY&&(i.clientX=e,i.clientY=r),(n=(new Date).getTime())-v._mouseDownTime<y?m+=1:(m=1,v._mouseDownTime=n),t.prepFn&&t.prepFn(i,e,r),a&&!g?(f=u()).style.cursor=window.getComputedStyle(x).cursor:a||(f=document,c=window.getComputedStyle(document.documentElement).cursor,document.documentElement.style.cursor=window.getComputedStyle(x).cursor),document.addEventListener(\"mouseup\",k),document.addEventListener(\"touchend\",k),!1!==t.dragmode&&(i.preventDefault(),document.addEventListener(\"mousemove\",w),document.addEventListener(\"touchmove\",w,{passive:!1}))}function w(n){n.preventDefault();var a=h(n),i=t.minDrag||s.MINDRAG,o=b(a[0]-e,a[1]-r,i),c=o[0],u=o[1];(c||u)&&(v._dragged=!0,l.unhover(v)),v._dragged&&t.moveFn&&!g&&(v._dragdata={element:x,dx:c,dy:u},t.moveFn(c,u))}function k(e){if(delete v._dragdata,!1!==t.dragmode&&(e.preventDefault(),document.removeEventListener(\"mousemove\",w),document.removeEventListener(\"touchmove\",w)),document.removeEventListener(\"mouseup\",k),document.removeEventListener(\"touchend\",k),a?o(f):c&&(f.documentElement.style.cursor=c,c=null),v._dragging){if(v._dragging=!1,(new Date).getTime()-v._mouseDownTime>y&&(m=Math.max(m-1,1)),v._dragged)t.doneFn&&t.doneFn();else if(t.clickFn&&t.clickFn(m,p),!g){var r;try{r=new MouseEvent(\"click\",e)}catch(t){var n=h(e);(r=document.createEvent(\"MouseEvents\")).initMouseEvent(\"click\",e.bubbles,e.cancelable,e.view,e.detail,e.screenX,e.screenY,n[0],n[1],e.ctrlKey,e.altKey,e.shiftKey,e.metaKey,e.button,e.relatedTarget)}d.dispatchEvent(r)}v._dragging=!1,v._dragged=!1}else v._dragged=!1}},l.coverSlip=u},{\"../../lib\":717,\"../../plots/cartesian/constants\":771,\"./align\":608,\"./cursor\":609,\"./unhover\":611,\"has-hover\":412,\"has-passive-events\":413,\"mouse-event-offset\":438}],611:[function(t,e,r){\"use strict\";var n=t(\"../../lib/events\"),a=t(\"../../lib/throttle\"),i=t(\"../../lib/dom\").getGraphDiv,o=t(\"../fx/constants\"),s=e.exports={};s.wrapped=function(t,e,r){(t=i(t))._fullLayout&&a.clear(t._fullLayout._uid+o.HOVERID),s.raw(t,e,r)},s.raw=function(t,e){var r=t._fullLayout,a=t._hoverdata;e||(e={}),e.target&&!1===n.triggerHandler(t,\"plotly_beforehover\",e)||(r._hoverlayer.selectAll(\"g\").remove(),r._hoverlayer.selectAll(\"line\").remove(),r._hoverlayer.selectAll(\"circle\").remove(),t._hoverdata=void 0,e.target&&a&&t.emit(\"plotly_unhover\",{event:e,points:a}))}},{\"../../lib/dom\":706,\"../../lib/events\":707,\"../../lib/throttle\":742,\"../fx/constants\":625}],612:[function(t,e,r){\"use strict\";r.dash={valType:\"string\",values:[\"solid\",\"dot\",\"dash\",\"longdash\",\"dashdot\",\"longdashdot\"],dflt:\"solid\",editType:\"style\"}},{}],613:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"fast-isnumeric\"),i=t(\"tinycolor2\"),o=t(\"../../registry\"),s=t(\"../color\"),l=t(\"../colorscale\"),c=t(\"../../lib\"),u=t(\"../../lib/svg_text_utils\"),h=t(\"../../constants/xmlns_namespaces\"),f=t(\"../../constants/alignment\").LINE_SPACING,p=t(\"../../constants/interactions\").DESELECTDIM,d=t(\"../../traces/scatter/subtypes\"),g=t(\"../../traces/scatter/make_bubble_size_func\"),v=t(\"../../components/fx/helpers\").appendArrayPointValue,m=e.exports={};m.font=function(t,e,r,n){c.isPlainObject(e)&&(n=e.color,r=e.size,e=e.family),e&&t.style(\"font-family\",e),r+1&&t.style(\"font-size\",r+\"px\"),n&&t.call(s.fill,n)},m.setPosition=function(t,e,r){t.attr(\"x\",e).attr(\"y\",r)},m.setSize=function(t,e,r){t.attr(\"width\",e).attr(\"height\",r)},m.setRect=function(t,e,r,n,a){t.call(m.setPosition,e,r).call(m.setSize,n,a)},m.translatePoint=function(t,e,r,n){var i=r.c2p(t.x),o=n.c2p(t.y);return!!(a(i)&&a(o)&&e.node())&&(\"text\"===e.node().nodeName?e.attr(\"x\",i).attr(\"y\",o):e.attr(\"transform\",\"translate(\"+i+\",\"+o+\")\"),!0)},m.translatePoints=function(t,e,r){t.each(function(t){var a=n.select(this);m.translatePoint(t,a,e,r)})},m.hideOutsideRangePoint=function(t,e,r,n,a,i){e.attr(\"display\",r.isPtWithinRange(t,a)&&n.isPtWithinRange(t,i)?null:\"none\")},m.hideOutsideRangePoints=function(t,e){if(e._hasClipOnAxisFalse){var r=e.xaxis,a=e.yaxis;t.each(function(e){var i=e[0].trace,s=i.xcalendar,l=i.ycalendar,c=o.traceIs(i,\"bar-like\")?\".bartext\":\".point,.textpoint\";t.selectAll(c).each(function(t){m.hideOutsideRangePoint(t,n.select(this),r,a,s,l)})})}},m.crispRound=function(t,e,r){return e&&a(e)?t._context.staticPlot?e:e<1?1:Math.round(e):r||0},m.singleLineStyle=function(t,e,r,n,a){e.style(\"fill\",\"none\");var i=(((t||[])[0]||{}).trace||{}).line||{},o=r||i.width||0,l=a||i.dash||\"\";s.stroke(e,n||i.color),m.dashLine(e,l,o)},m.lineGroupStyle=function(t,e,r,a){t.style(\"fill\",\"none\").each(function(t){var i=(((t||[])[0]||{}).trace||{}).line||{},o=e||i.width||0,l=a||i.dash||\"\";n.select(this).call(s.stroke,r||i.color).call(m.dashLine,l,o)})},m.dashLine=function(t,e,r){r=+r||0,e=m.dashStyle(e,r),t.style({\"stroke-dasharray\":e,\"stroke-width\":r+\"px\"})},m.dashStyle=function(t,e){e=+e||1;var r=Math.max(e,3);return\"solid\"===t?t=\"\":\"dot\"===t?t=r+\"px,\"+r+\"px\":\"dash\"===t?t=3*r+\"px,\"+3*r+\"px\":\"longdash\"===t?t=5*r+\"px,\"+5*r+\"px\":\"dashdot\"===t?t=3*r+\"px,\"+r+\"px,\"+r+\"px,\"+r+\"px\":\"longdashdot\"===t&&(t=5*r+\"px,\"+2*r+\"px,\"+r+\"px,\"+2*r+\"px\"),t},m.singleFillStyle=function(t){var e=(((n.select(t.node()).data()[0]||[])[0]||{}).trace||{}).fillcolor;e&&t.call(s.fill,e)},m.fillGroupStyle=function(t){t.style(\"stroke-width\",0).each(function(t){var e=n.select(this);t[0].trace&&e.call(s.fill,t[0].trace.fillcolor)})};var y=t(\"./symbol_defs\");m.symbolNames=[],m.symbolFuncs=[],m.symbolNeedLines={},m.symbolNoDot={},m.symbolNoFill={},m.symbolList=[],Object.keys(y).forEach(function(t){var e=y[t],r=e.n;m.symbolList.push(r,t,r+100,t+\"-open\"),m.symbolNames[r]=t,m.symbolFuncs[r]=e.f,e.needLine&&(m.symbolNeedLines[r]=!0),e.noDot?m.symbolNoDot[r]=!0:m.symbolList.push(r+200,t+\"-dot\",r+300,t+\"-open-dot\"),e.noFill&&(m.symbolNoFill[r]=!0)});var x=m.symbolNames.length,b=\"M0,0.5L0.5,0L0,-0.5L-0.5,0Z\";function _(t,e){var r=t%100;return m.symbolFuncs[r](e)+(t>=200?b:\"\")}m.symbolNumber=function(t){if(\"string\"==typeof t){var e=0;t.indexOf(\"-open\")>0&&(e=100,t=t.replace(\"-open\",\"\")),t.indexOf(\"-dot\")>0&&(e+=200,t=t.replace(\"-dot\",\"\")),(t=m.symbolNames.indexOf(t))>=0&&(t+=e)}return t%100>=x||t>=400?0:Math.floor(Math.max(t,0))};var w={x1:1,x2:0,y1:0,y2:0},k={x1:0,x2:0,y1:1,y2:0},T=n.format(\"~.1f\"),M={radial:{node:\"radialGradient\"},radialreversed:{node:\"radialGradient\",reversed:!0},horizontal:{node:\"linearGradient\",attrs:w},horizontalreversed:{node:\"linearGradient\",attrs:w,reversed:!0},vertical:{node:\"linearGradient\",attrs:k},verticalreversed:{node:\"linearGradient\",attrs:k,reversed:!0}};m.gradient=function(t,e,r,a,o,l){for(var u=o.length,h=M[a],f=new Array(u),p=0;p<u;p++)h.reversed?f[u-1-p]=[T(100*(1-o[p][0])),o[p][1]]:f[p]=[T(100*o[p][0]),o[p][1]];var d=e._fullLayout,g=\"g\"+d._uid+\"-\"+r,v=d._defs.select(\".gradients\").selectAll(\"#\"+g).data([a+f.join(\";\")],c.identity);v.exit().remove(),v.enter().append(h.node).each(function(){var t=n.select(this);h.attrs&&t.attr(h.attrs),t.attr(\"id\",g);var e=t.selectAll(\"stop\").data(f);e.exit().remove(),e.enter().append(\"stop\"),e.each(function(t){var e=i(t[1]);n.select(this).attr({offset:t[0]+\"%\",\"stop-color\":s.tinyRGB(e),\"stop-opacity\":e.getAlpha()})})}),t.style(l,D(g,e)).style(l+\"-opacity\",null);var m=function(t){return\".\"+t.attr(\"class\").replace(/\\s/g,\".\")},y=m(n.select(t.node().parentNode))+\">\"+m(t);d._gradientUrlQueryParts[y]=1},m.initGradients=function(t){var e=t._fullLayout;c.ensureSingle(e._defs,\"g\",\"gradients\").selectAll(\"linearGradient,radialGradient\").remove(),e._gradientUrlQueryParts={}},m.pointStyle=function(t,e,r){if(t.size()){var a=m.makePointStyleFns(e);t.each(function(t){m.singlePointStyle(t,n.select(this),e,a,r)})}},m.singlePointStyle=function(t,e,r,n,a){var i=r.marker,o=i.line;if(e.style(\"opacity\",n.selectedOpacityFn?n.selectedOpacityFn(t):void 0===t.mo?i.opacity:t.mo),n.ms2mrc){var l;l=\"various\"===t.ms||\"various\"===i.size?3:n.ms2mrc(t.ms),t.mrc=l,n.selectedSizeFn&&(l=t.mrc=n.selectedSizeFn(t));var u=m.symbolNumber(t.mx||i.symbol)||0;t.om=u%200>=100,e.attr(\"d\",_(u,l))}var h,f,p,d=!1;if(t.so)p=o.outlierwidth,f=o.outliercolor,h=i.outliercolor;else{var g=(o||{}).width;p=(t.mlw+1||g+1||(t.trace?(t.trace.marker.line||{}).width:0)+1)-1||0,f=\"mlc\"in t?t.mlcc=n.lineScale(t.mlc):c.isArrayOrTypedArray(o.color)?s.defaultLine:o.color,c.isArrayOrTypedArray(i.color)&&(h=s.defaultLine,d=!0),h=\"mc\"in t?t.mcc=n.markerScale(t.mc):i.color||\"rgba(0,0,0,0)\",n.selectedColorFn&&(h=n.selectedColorFn(t))}if(t.om)e.call(s.stroke,h).style({\"stroke-width\":(p||1)+\"px\",fill:\"none\"});else{e.style(\"stroke-width\",(t.isBlank?0:p)+\"px\");var v=i.gradient,y=t.mgt;if(y?d=!0:y=v&&v.type,Array.isArray(y)&&(y=y[0],M[y]||(y=0)),y&&\"none\"!==y){var x=t.mgc;x?d=!0:x=v.color;var b=r.uid;d&&(b+=\"-\"+t.i),m.gradient(e,a,b,y,[[0,x],[1,h]],\"fill\")}else s.fill(e,h);p&&s.stroke(e,f)}},m.makePointStyleFns=function(t){var e={},r=t.marker;return e.markerScale=m.tryColorscale(r,\"\"),e.lineScale=m.tryColorscale(r,\"line\"),o.traceIs(t,\"symbols\")&&(e.ms2mrc=d.isBubble(t)?g(t):function(){return(r.size||6)/2}),t.selectedpoints&&c.extendFlat(e,m.makeSelectedPointStyleFns(t)),e},m.makeSelectedPointStyleFns=function(t){var e={},r=t.selected||{},n=t.unselected||{},a=t.marker||{},i=r.marker||{},s=n.marker||{},l=a.opacity,u=i.opacity,h=s.opacity,f=void 0!==u,d=void 0!==h;(c.isArrayOrTypedArray(l)||f||d)&&(e.selectedOpacityFn=function(t){var e=void 0===t.mo?a.opacity:t.mo;return t.selected?f?u:e:d?h:p*e});var g=a.color,v=i.color,m=s.color;(v||m)&&(e.selectedColorFn=function(t){var e=t.mcc||g;return t.selected?v||e:m||e});var y=a.size,x=i.size,b=s.size,_=void 0!==x,w=void 0!==b;return o.traceIs(t,\"symbols\")&&(_||w)&&(e.selectedSizeFn=function(t){var e=t.mrc||y/2;return t.selected?_?x/2:e:w?b/2:e}),e},m.makeSelectedTextStyleFns=function(t){var e={},r=t.selected||{},n=t.unselected||{},a=t.textfont||{},i=r.textfont||{},o=n.textfont||{},l=a.color,c=i.color,u=o.color;return e.selectedTextColorFn=function(t){var e=t.tc||l;return t.selected?c||e:u||(c?e:s.addOpacity(e,p))},e},m.selectedPointStyle=function(t,e){if(t.size()&&e.selectedpoints){var r=m.makeSelectedPointStyleFns(e),a=e.marker||{},i=[];r.selectedOpacityFn&&i.push(function(t,e){t.style(\"opacity\",r.selectedOpacityFn(e))}),r.selectedColorFn&&i.push(function(t,e){s.fill(t,r.selectedColorFn(e))}),r.selectedSizeFn&&i.push(function(t,e){var n=e.mx||a.symbol||0,i=r.selectedSizeFn(e);t.attr(\"d\",_(m.symbolNumber(n),i)),e.mrc2=i}),i.length&&t.each(function(t){for(var e=n.select(this),r=0;r<i.length;r++)i[r](e,t)})}},m.tryColorscale=function(t,e){var r=e?c.nestedProperty(t,e).get():t;if(r){var n=r.color;if((r.colorscale||r._colorAx)&&c.isArrayOrTypedArray(n))return l.makeColorScaleFuncFromTrace(r)}return c.identity};var A={start:1,end:-1,middle:0,bottom:1,top:-1};function S(t,e,r,a){var i=n.select(t.node().parentNode),o=-1!==e.indexOf(\"top\")?\"top\":-1!==e.indexOf(\"bottom\")?\"bottom\":\"middle\",s=-1!==e.indexOf(\"left\")?\"end\":-1!==e.indexOf(\"right\")?\"start\":\"middle\",l=a?a/.8+1:0,c=(u.lineCount(t)-1)*f+1,h=A[s]*l,p=.75*r+A[o]*l+(A[o]-1)*c*r/2;t.attr(\"text-anchor\",s),i.attr(\"transform\",\"translate(\"+h+\",\"+p+\")\")}function E(t,e){var r=t.ts||e.textfont.size;return a(r)&&r>0?r:0}m.textPointStyle=function(t,e,r){if(t.size()){var a;if(e.selectedpoints){var i=m.makeSelectedTextStyleFns(e);a=i.selectedTextColorFn}var o=e.texttemplate,s=r._fullLayout;t.each(function(t){var i=n.select(this),l=o?c.extractOption(t,e,\"txt\",\"texttemplate\"):c.extractOption(t,e,\"tx\",\"text\");if(l||0===l){if(o){var h=e._module.formatLabels?e._module.formatLabels(t,e,s):{},f={};v(f,e,t.i);var p=e._meta||{};l=c.texttemplateString(l,h,s._d3locale,f,t,p)}var d=t.tp||e.textposition,g=E(t,e),y=a?a(t):t.tc||e.textfont.color;i.call(m.font,t.tf||e.textfont.family,g,y).text(l).call(u.convertToTspans,r).call(S,d,g,t.mrc)}else i.remove()})}},m.selectedTextStyle=function(t,e){if(t.size()&&e.selectedpoints){var r=m.makeSelectedTextStyleFns(e);t.each(function(t){var a=n.select(this),i=r.selectedTextColorFn(t),o=t.tp||e.textposition,l=E(t,e);s.fill(a,i),S(a,o,l,t.mrc2||t.mrc)})}};var L=.5;function C(t,e,r,a){var i=t[0]-e[0],o=t[1]-e[1],s=r[0]-e[0],l=r[1]-e[1],c=Math.pow(i*i+o*o,L/2),u=Math.pow(s*s+l*l,L/2),h=(u*u*i-c*c*s)*a,f=(u*u*o-c*c*l)*a,p=3*u*(c+u),d=3*c*(c+u);return[[n.round(e[0]+(p&&h/p),2),n.round(e[1]+(p&&f/p),2)],[n.round(e[0]-(d&&h/d),2),n.round(e[1]-(d&&f/d),2)]]}m.smoothopen=function(t,e){if(t.length<3)return\"M\"+t.join(\"L\");var r,n=\"M\"+t[0],a=[];for(r=1;r<t.length-1;r++)a.push(C(t[r-1],t[r],t[r+1],e));for(n+=\"Q\"+a[0][0]+\" \"+t[1],r=2;r<t.length-1;r++)n+=\"C\"+a[r-2][1]+\" \"+a[r-1][0]+\" \"+t[r];return n+=\"Q\"+a[t.length-3][1]+\" \"+t[t.length-1]},m.smoothclosed=function(t,e){if(t.length<3)return\"M\"+t.join(\"L\")+\"Z\";var r,n=\"M\"+t[0],a=t.length-1,i=[C(t[a],t[0],t[1],e)];for(r=1;r<a;r++)i.push(C(t[r-1],t[r],t[r+1],e));for(i.push(C(t[a-1],t[a],t[0],e)),r=1;r<=a;r++)n+=\"C\"+i[r-1][1]+\" \"+i[r][0]+\" \"+t[r];return n+=\"C\"+i[a][1]+\" \"+i[0][0]+\" \"+t[0]+\"Z\"};var P={hv:function(t,e){return\"H\"+n.round(e[0],2)+\"V\"+n.round(e[1],2)},vh:function(t,e){return\"V\"+n.round(e[1],2)+\"H\"+n.round(e[0],2)},hvh:function(t,e){return\"H\"+n.round((t[0]+e[0])/2,2)+\"V\"+n.round(e[1],2)+\"H\"+n.round(e[0],2)},vhv:function(t,e){return\"V\"+n.round((t[1]+e[1])/2,2)+\"H\"+n.round(e[0],2)+\"V\"+n.round(e[1],2)}},O=function(t,e){return\"L\"+n.round(e[0],2)+\",\"+n.round(e[1],2)};m.steps=function(t){var e=P[t]||O;return function(t){for(var r=\"M\"+n.round(t[0][0],2)+\",\"+n.round(t[0][1],2),a=1;a<t.length;a++)r+=e(t[a-1],t[a]);return r}},m.makeTester=function(){var t=c.ensureSingleById(n.select(\"body\"),\"svg\",\"js-plotly-tester\",function(t){t.attr(h.svgAttrs).style({position:\"absolute\",left:\"-10000px\",top:\"-10000px\",width:\"9000px\",height:\"9000px\",\"z-index\":\"1\"})}),e=c.ensureSingle(t,\"path\",\"js-reference-point\",function(t){t.attr(\"d\",\"M0,0H1V1H0Z\").style({\"stroke-width\":0,fill:\"black\"})});m.tester=t,m.testref=e},m.savedBBoxes={};var z=0;function I(t){var e=t.getAttribute(\"data-unformatted\");if(null!==e)return e+t.getAttribute(\"data-math\")+t.getAttribute(\"text-anchor\")+t.getAttribute(\"style\")}function D(t,e){if(!t)return null;var r=e._context;return\"url('\"+(r._exportedPlot?\"\":r._baseUrl||\"\")+\"#\"+t+\"')\"}m.bBox=function(t,e,r){var a,i,o;if(r||(r=I(t)),r){if(a=m.savedBBoxes[r])return c.extendFlat({},a)}else if(1===t.childNodes.length){var s=t.childNodes[0];if(r=I(s)){var l=+s.getAttribute(\"x\")||0,h=+s.getAttribute(\"y\")||0,f=s.getAttribute(\"transform\");if(!f){var p=m.bBox(s,!1,r);return l&&(p.left+=l,p.right+=l),h&&(p.top+=h,p.bottom+=h),p}if(r+=\"~\"+l+\"~\"+h+\"~\"+f,a=m.savedBBoxes[r])return c.extendFlat({},a)}}e?i=t:(o=m.tester.node(),i=t.cloneNode(!0),o.appendChild(i)),n.select(i).attr(\"transform\",null).call(u.positionText,0,0);var d=i.getBoundingClientRect(),g=m.testref.node().getBoundingClientRect();e||o.removeChild(i);var v={height:d.height,width:d.width,left:d.left-g.left,top:d.top-g.top,right:d.right-g.left,bottom:d.bottom-g.top};return z>=1e4&&(m.savedBBoxes={},z=0),r&&(m.savedBBoxes[r]=v),z++,c.extendFlat({},v)},m.setClipUrl=function(t,e,r){t.attr(\"clip-path\",D(e,r))},m.getTranslate=function(t){var e=(t[t.attr?\"attr\":\"getAttribute\"](\"transform\")||\"\").replace(/.*\\btranslate\\((-?\\d*\\.?\\d*)[^-\\d]*(-?\\d*\\.?\\d*)[^\\d].*/,function(t,e,r){return[e,r].join(\" \")}).split(\" \");return{x:+e[0]||0,y:+e[1]||0}},m.setTranslate=function(t,e,r){var n=t.attr?\"attr\":\"getAttribute\",a=t.attr?\"attr\":\"setAttribute\",i=t[n](\"transform\")||\"\";return e=e||0,r=r||0,i=i.replace(/(\\btranslate\\(.*?\\);?)/,\"\").trim(),i=(i+=\" translate(\"+e+\", \"+r+\")\").trim(),t[a](\"transform\",i),i},m.getScale=function(t){var e=(t[t.attr?\"attr\":\"getAttribute\"](\"transform\")||\"\").replace(/.*\\bscale\\((\\d*\\.?\\d*)[^\\d]*(\\d*\\.?\\d*)[^\\d].*/,function(t,e,r){return[e,r].join(\" \")}).split(\" \");return{x:+e[0]||1,y:+e[1]||1}},m.setScale=function(t,e,r){var n=t.attr?\"attr\":\"getAttribute\",a=t.attr?\"attr\":\"setAttribute\",i=t[n](\"transform\")||\"\";return e=e||1,r=r||1,i=i.replace(/(\\bscale\\(.*?\\);?)/,\"\").trim(),i=(i+=\" scale(\"+e+\", \"+r+\")\").trim(),t[a](\"transform\",i),i};var R=/\\s*sc.*/;m.setPointGroupScale=function(t,e,r){if(e=e||1,r=r||1,t){var n=1===e&&1===r?\"\":\" scale(\"+e+\",\"+r+\")\";t.each(function(){var t=(this.getAttribute(\"transform\")||\"\").replace(R,\"\");t=(t+=n).trim(),this.setAttribute(\"transform\",t)})}};var F=/translate\\([^)]*\\)\\s*$/;m.setTextPointsScale=function(t,e,r){t&&t.each(function(){var t,a=n.select(this),i=a.select(\"text\");if(i.node()){var o=parseFloat(i.attr(\"x\")||0),s=parseFloat(i.attr(\"y\")||0),l=(a.attr(\"transform\")||\"\").match(F);t=1===e&&1===r?[]:[\"translate(\"+o+\",\"+s+\")\",\"scale(\"+e+\",\"+r+\")\",\"translate(\"+-o+\",\"+-s+\")\"],l&&t.push(l),a.attr(\"transform\",t.join(\" \"))}})}},{\"../../components/fx/helpers\":627,\"../../constants/alignment\":686,\"../../constants/interactions\":692,\"../../constants/xmlns_namespaces\":694,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"../../registry\":846,\"../../traces/scatter/make_bubble_size_func\":1137,\"../../traces/scatter/subtypes\":1144,\"../color\":592,\"../colorscale\":604,\"./symbol_defs\":614,d3:165,\"fast-isnumeric\":228,tinycolor2:536}],614:[function(t,e,r){\"use strict\";var n=t(\"d3\");e.exports={circle:{n:0,f:function(t){var e=n.round(t,2);return\"M\"+e+\",0A\"+e+\",\"+e+\" 0 1,1 0,-\"+e+\"A\"+e+\",\"+e+\" 0 0,1 \"+e+\",0Z\"}},square:{n:1,f:function(t){var e=n.round(t,2);return\"M\"+e+\",\"+e+\"H-\"+e+\"V-\"+e+\"H\"+e+\"Z\"}},diamond:{n:2,f:function(t){var e=n.round(1.3*t,2);return\"M\"+e+\",0L0,\"+e+\"L-\"+e+\",0L0,-\"+e+\"Z\"}},cross:{n:3,f:function(t){var e=n.round(.4*t,2),r=n.round(1.2*t,2);return\"M\"+r+\",\"+e+\"H\"+e+\"V\"+r+\"H-\"+e+\"V\"+e+\"H-\"+r+\"V-\"+e+\"H-\"+e+\"V-\"+r+\"H\"+e+\"V-\"+e+\"H\"+r+\"Z\"}},x:{n:4,f:function(t){var e=n.round(.8*t/Math.sqrt(2),2),r=\"l\"+e+\",\"+e,a=\"l\"+e+\",-\"+e,i=\"l-\"+e+\",-\"+e,o=\"l-\"+e+\",\"+e;return\"M0,\"+e+r+a+i+a+i+o+i+o+r+o+r+\"Z\"}},\"triangle-up\":{n:5,f:function(t){var e=n.round(2*t/Math.sqrt(3),2);return\"M-\"+e+\",\"+n.round(t/2,2)+\"H\"+e+\"L0,-\"+n.round(t,2)+\"Z\"}},\"triangle-down\":{n:6,f:function(t){var e=n.round(2*t/Math.sqrt(3),2);return\"M-\"+e+\",-\"+n.round(t/2,2)+\"H\"+e+\"L0,\"+n.round(t,2)+\"Z\"}},\"triangle-left\":{n:7,f:function(t){var e=n.round(2*t/Math.sqrt(3),2);return\"M\"+n.round(t/2,2)+\",-\"+e+\"V\"+e+\"L-\"+n.round(t,2)+\",0Z\"}},\"triangle-right\":{n:8,f:function(t){var e=n.round(2*t/Math.sqrt(3),2);return\"M-\"+n.round(t/2,2)+\",-\"+e+\"V\"+e+\"L\"+n.round(t,2)+\",0Z\"}},\"triangle-ne\":{n:9,f:function(t){var e=n.round(.6*t,2),r=n.round(1.2*t,2);return\"M-\"+r+\",-\"+e+\"H\"+e+\"V\"+r+\"Z\"}},\"triangle-se\":{n:10,f:function(t){var e=n.round(.6*t,2),r=n.round(1.2*t,2);return\"M\"+e+\",-\"+r+\"V\"+e+\"H-\"+r+\"Z\"}},\"triangle-sw\":{n:11,f:function(t){var e=n.round(.6*t,2),r=n.round(1.2*t,2);return\"M\"+r+\",\"+e+\"H-\"+e+\"V-\"+r+\"Z\"}},\"triangle-nw\":{n:12,f:function(t){var e=n.round(.6*t,2),r=n.round(1.2*t,2);return\"M-\"+e+\",\"+r+\"V-\"+e+\"H\"+r+\"Z\"}},pentagon:{n:13,f:function(t){var e=n.round(.951*t,2),r=n.round(.588*t,2),a=n.round(-t,2),i=n.round(-.309*t,2);return\"M\"+e+\",\"+i+\"L\"+r+\",\"+n.round(.809*t,2)+\"H-\"+r+\"L-\"+e+\",\"+i+\"L0,\"+a+\"Z\"}},hexagon:{n:14,f:function(t){var e=n.round(t,2),r=n.round(t/2,2),a=n.round(t*Math.sqrt(3)/2,2);return\"M\"+a+\",-\"+r+\"V\"+r+\"L0,\"+e+\"L-\"+a+\",\"+r+\"V-\"+r+\"L0,-\"+e+\"Z\"}},hexagon2:{n:15,f:function(t){var e=n.round(t,2),r=n.round(t/2,2),a=n.round(t*Math.sqrt(3)/2,2);return\"M-\"+r+\",\"+a+\"H\"+r+\"L\"+e+\",0L\"+r+\",-\"+a+\"H-\"+r+\"L-\"+e+\",0Z\"}},octagon:{n:16,f:function(t){var e=n.round(.924*t,2),r=n.round(.383*t,2);return\"M-\"+r+\",-\"+e+\"H\"+r+\"L\"+e+\",-\"+r+\"V\"+r+\"L\"+r+\",\"+e+\"H-\"+r+\"L-\"+e+\",\"+r+\"V-\"+r+\"Z\"}},star:{n:17,f:function(t){var e=1.4*t,r=n.round(.225*e,2),a=n.round(.951*e,2),i=n.round(.363*e,2),o=n.round(.588*e,2),s=n.round(-e,2),l=n.round(-.309*e,2),c=n.round(.118*e,2),u=n.round(.809*e,2);return\"M\"+r+\",\"+l+\"H\"+a+\"L\"+i+\",\"+c+\"L\"+o+\",\"+u+\"L0,\"+n.round(.382*e,2)+\"L-\"+o+\",\"+u+\"L-\"+i+\",\"+c+\"L-\"+a+\",\"+l+\"H-\"+r+\"L0,\"+s+\"Z\"}},hexagram:{n:18,f:function(t){var e=n.round(.66*t,2),r=n.round(.38*t,2),a=n.round(.76*t,2);return\"M-\"+a+\",0l-\"+r+\",-\"+e+\"h\"+a+\"l\"+r+\",-\"+e+\"l\"+r+\",\"+e+\"h\"+a+\"l-\"+r+\",\"+e+\"l\"+r+\",\"+e+\"h-\"+a+\"l-\"+r+\",\"+e+\"l-\"+r+\",-\"+e+\"h-\"+a+\"Z\"}},\"star-triangle-up\":{n:19,f:function(t){var e=n.round(t*Math.sqrt(3)*.8,2),r=n.round(.8*t,2),a=n.round(1.6*t,2),i=n.round(4*t,2),o=\"A \"+i+\",\"+i+\" 0 0 1 \";return\"M-\"+e+\",\"+r+o+e+\",\"+r+o+\"0,-\"+a+o+\"-\"+e+\",\"+r+\"Z\"}},\"star-triangle-down\":{n:20,f:function(t){var e=n.round(t*Math.sqrt(3)*.8,2),r=n.round(.8*t,2),a=n.round(1.6*t,2),i=n.round(4*t,2),o=\"A \"+i+\",\"+i+\" 0 0 1 \";return\"M\"+e+\",-\"+r+o+\"-\"+e+\",-\"+r+o+\"0,\"+a+o+e+\",-\"+r+\"Z\"}},\"star-square\":{n:21,f:function(t){var e=n.round(1.1*t,2),r=n.round(2*t,2),a=\"A \"+r+\",\"+r+\" 0 0 1 \";return\"M-\"+e+\",-\"+e+a+\"-\"+e+\",\"+e+a+e+\",\"+e+a+e+\",-\"+e+a+\"-\"+e+\",-\"+e+\"Z\"}},\"star-diamond\":{n:22,f:function(t){var e=n.round(1.4*t,2),r=n.round(1.9*t,2),a=\"A \"+r+\",\"+r+\" 0 0 1 \";return\"M-\"+e+\",0\"+a+\"0,\"+e+a+e+\",0\"+a+\"0,-\"+e+a+\"-\"+e+\",0Z\"}},\"diamond-tall\":{n:23,f:function(t){var e=n.round(.7*t,2),r=n.round(1.4*t,2);return\"M0,\"+r+\"L\"+e+\",0L0,-\"+r+\"L-\"+e+\",0Z\"}},\"diamond-wide\":{n:24,f:function(t){var e=n.round(1.4*t,2),r=n.round(.7*t,2);return\"M0,\"+r+\"L\"+e+\",0L0,-\"+r+\"L-\"+e+\",0Z\"}},hourglass:{n:25,f:function(t){var e=n.round(t,2);return\"M\"+e+\",\"+e+\"H-\"+e+\"L\"+e+\",-\"+e+\"H-\"+e+\"Z\"},noDot:!0},bowtie:{n:26,f:function(t){var e=n.round(t,2);return\"M\"+e+\",\"+e+\"V-\"+e+\"L-\"+e+\",\"+e+\"V-\"+e+\"Z\"},noDot:!0},\"circle-cross\":{n:27,f:function(t){var e=n.round(t,2);return\"M0,\"+e+\"V-\"+e+\"M\"+e+\",0H-\"+e+\"M\"+e+\",0A\"+e+\",\"+e+\" 0 1,1 0,-\"+e+\"A\"+e+\",\"+e+\" 0 0,1 \"+e+\",0Z\"},needLine:!0,noDot:!0},\"circle-x\":{n:28,f:function(t){var e=n.round(t,2),r=n.round(t/Math.sqrt(2),2);return\"M\"+r+\",\"+r+\"L-\"+r+\",-\"+r+\"M\"+r+\",-\"+r+\"L-\"+r+\",\"+r+\"M\"+e+\",0A\"+e+\",\"+e+\" 0 1,1 0,-\"+e+\"A\"+e+\",\"+e+\" 0 0,1 \"+e+\",0Z\"},needLine:!0,noDot:!0},\"square-cross\":{n:29,f:function(t){var e=n.round(t,2);return\"M0,\"+e+\"V-\"+e+\"M\"+e+\",0H-\"+e+\"M\"+e+\",\"+e+\"H-\"+e+\"V-\"+e+\"H\"+e+\"Z\"},needLine:!0,noDot:!0},\"square-x\":{n:30,f:function(t){var e=n.round(t,2);return\"M\"+e+\",\"+e+\"L-\"+e+\",-\"+e+\"M\"+e+\",-\"+e+\"L-\"+e+\",\"+e+\"M\"+e+\",\"+e+\"H-\"+e+\"V-\"+e+\"H\"+e+\"Z\"},needLine:!0,noDot:!0},\"diamond-cross\":{n:31,f:function(t){var e=n.round(1.3*t,2);return\"M\"+e+\",0L0,\"+e+\"L-\"+e+\",0L0,-\"+e+\"ZM0,-\"+e+\"V\"+e+\"M-\"+e+\",0H\"+e},needLine:!0,noDot:!0},\"diamond-x\":{n:32,f:function(t){var e=n.round(1.3*t,2),r=n.round(.65*t,2);return\"M\"+e+\",0L0,\"+e+\"L-\"+e+\",0L0,-\"+e+\"ZM-\"+r+\",-\"+r+\"L\"+r+\",\"+r+\"M-\"+r+\",\"+r+\"L\"+r+\",-\"+r},needLine:!0,noDot:!0},\"cross-thin\":{n:33,f:function(t){var e=n.round(1.4*t,2);return\"M0,\"+e+\"V-\"+e+\"M\"+e+\",0H-\"+e},needLine:!0,noDot:!0,noFill:!0},\"x-thin\":{n:34,f:function(t){var e=n.round(t,2);return\"M\"+e+\",\"+e+\"L-\"+e+\",-\"+e+\"M\"+e+\",-\"+e+\"L-\"+e+\",\"+e},needLine:!0,noDot:!0,noFill:!0},asterisk:{n:35,f:function(t){var e=n.round(1.2*t,2),r=n.round(.85*t,2);return\"M0,\"+e+\"V-\"+e+\"M\"+e+\",0H-\"+e+\"M\"+r+\",\"+r+\"L-\"+r+\",-\"+r+\"M\"+r+\",-\"+r+\"L-\"+r+\",\"+r},needLine:!0,noDot:!0,noFill:!0},hash:{n:36,f:function(t){var e=n.round(t/2,2),r=n.round(t,2);return\"M\"+e+\",\"+r+\"V-\"+r+\"m-\"+r+\",0V\"+r+\"M\"+r+\",\"+e+\"H-\"+r+\"m0,-\"+r+\"H\"+r},needLine:!0,noFill:!0},\"y-up\":{n:37,f:function(t){var e=n.round(1.2*t,2),r=n.round(1.6*t,2),a=n.round(.8*t,2);return\"M-\"+e+\",\"+a+\"L0,0M\"+e+\",\"+a+\"L0,0M0,-\"+r+\"L0,0\"},needLine:!0,noDot:!0,noFill:!0},\"y-down\":{n:38,f:function(t){var e=n.round(1.2*t,2),r=n.round(1.6*t,2),a=n.round(.8*t,2);return\"M-\"+e+\",-\"+a+\"L0,0M\"+e+\",-\"+a+\"L0,0M0,\"+r+\"L0,0\"},needLine:!0,noDot:!0,noFill:!0},\"y-left\":{n:39,f:function(t){var e=n.round(1.2*t,2),r=n.round(1.6*t,2),a=n.round(.8*t,2);return\"M\"+a+\",\"+e+\"L0,0M\"+a+\",-\"+e+\"L0,0M-\"+r+\",0L0,0\"},needLine:!0,noDot:!0,noFill:!0},\"y-right\":{n:40,f:function(t){var e=n.round(1.2*t,2),r=n.round(1.6*t,2),a=n.round(.8*t,2);return\"M-\"+a+\",\"+e+\"L0,0M-\"+a+\",-\"+e+\"L0,0M\"+r+\",0L0,0\"},needLine:!0,noDot:!0,noFill:!0},\"line-ew\":{n:41,f:function(t){var e=n.round(1.4*t,2);return\"M\"+e+\",0H-\"+e},needLine:!0,noDot:!0,noFill:!0},\"line-ns\":{n:42,f:function(t){var e=n.round(1.4*t,2);return\"M0,\"+e+\"V-\"+e},needLine:!0,noDot:!0,noFill:!0},\"line-ne\":{n:43,f:function(t){var e=n.round(t,2);return\"M\"+e+\",-\"+e+\"L-\"+e+\",\"+e},needLine:!0,noDot:!0,noFill:!0},\"line-nw\":{n:44,f:function(t){var e=n.round(t,2);return\"M\"+e+\",\"+e+\"L-\"+e+\",-\"+e},needLine:!0,noDot:!0,noFill:!0}}},{d3:165}],615:[function(t,e,r){\"use strict\";e.exports={visible:{valType:\"boolean\",editType:\"calc\"},type:{valType:\"enumerated\",values:[\"percent\",\"constant\",\"sqrt\",\"data\"],editType:\"calc\"},symmetric:{valType:\"boolean\",editType:\"calc\"},array:{valType:\"data_array\",editType:\"calc\"},arrayminus:{valType:\"data_array\",editType:\"calc\"},value:{valType:\"number\",min:0,dflt:10,editType:\"calc\"},valueminus:{valType:\"number\",min:0,dflt:10,editType:\"calc\"},traceref:{valType:\"integer\",min:0,dflt:0,editType:\"style\"},tracerefminus:{valType:\"integer\",min:0,dflt:0,editType:\"style\"},copy_ystyle:{valType:\"boolean\",editType:\"plot\"},copy_zstyle:{valType:\"boolean\",editType:\"style\"},color:{valType:\"color\",editType:\"style\"},thickness:{valType:\"number\",min:0,dflt:2,editType:\"style\"},width:{valType:\"number\",min:0,editType:\"plot\"},editType:\"calc\",_deprecated:{opacity:{valType:\"number\",editType:\"style\"}}}},{}],616:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../registry\"),i=t(\"../../plots/cartesian/axes\"),o=t(\"../../lib\"),s=t(\"./compute_error\");function l(t,e,r,a){var l=e[\"error_\"+a]||{},c=[];if(l.visible&&-1!==[\"linear\",\"log\"].indexOf(r.type)){for(var u=s(l),h=0;h<t.length;h++){var f=t[h],p=f.i;if(void 0===p)p=h;else if(null===p)continue;var d=f[a];if(n(r.c2l(d))){var g=u(d,p);if(n(g[0])&&n(g[1])){var v=f[a+\"s\"]=d-g[0],m=f[a+\"h\"]=d+g[1];c.push(v,m)}}}var y=r._id,x=e._extremes[y],b=i.findExtremes(r,c,o.extendFlat({tozero:x.opts.tozero},{padded:!0}));x.min=x.min.concat(b.min),x.max=x.max.concat(b.max)}}e.exports=function(t){for(var e=t.calcdata,r=0;r<e.length;r++){var n=e[r],o=n[0].trace;if(!0===o.visible&&a.traceIs(o,\"errorBarsOK\")){var s=i.getFromId(t,o.xaxis),c=i.getFromId(t,o.yaxis);l(n,o,s,\"x\"),l(n,o,c,\"y\")}}}},{\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"../../registry\":846,\"./compute_error\":617,\"fast-isnumeric\":228}],617:[function(t,e,r){\"use strict\";function n(t,e){return\"percent\"===t?function(t){return Math.abs(t*e/100)}:\"constant\"===t?function(){return Math.abs(e)}:\"sqrt\"===t?function(t){return Math.sqrt(Math.abs(t))}:void 0}e.exports=function(t){var e=t.type,r=t.symmetric;if(\"data\"===e){var a=t.array||[];if(r)return function(t,e){var r=+a[e];return[r,r]};var i=t.arrayminus||[];return function(t,e){var r=+a[e],n=+i[e];return isNaN(r)&&isNaN(n)?[NaN,NaN]:[n||0,r||0]}}var o=n(e,t.value),s=n(e,t.valueminus);return r||void 0===t.valueminus?function(t){var e=o(t);return[e,e]}:function(t){return[s(t),o(t)]}}},{}],618:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../registry\"),i=t(\"../../lib\"),o=t(\"../../plot_api/plot_template\"),s=t(\"./attributes\");e.exports=function(t,e,r,l){var c=\"error_\"+l.axis,u=o.newContainer(e,c),h=t[c]||{};function f(t,e){return i.coerce(h,u,s,t,e)}if(!1!==f(\"visible\",void 0!==h.array||void 0!==h.value||\"sqrt\"===h.type)){var p=f(\"type\",\"array\"in h?\"data\":\"percent\"),d=!0;\"sqrt\"!==p&&(d=f(\"symmetric\",!((\"data\"===p?\"arrayminus\":\"valueminus\")in h))),\"data\"===p?(f(\"array\"),f(\"traceref\"),d||(f(\"arrayminus\"),f(\"tracerefminus\"))):\"percent\"!==p&&\"constant\"!==p||(f(\"value\"),d||f(\"valueminus\"));var g=\"copy_\"+l.inherit+\"style\";if(l.inherit)(e[\"error_\"+l.inherit]||{}).visible&&f(g,!(h.color||n(h.thickness)||n(h.width)));l.inherit&&u[g]||(f(\"color\",r),f(\"thickness\"),f(\"width\",a.traceIs(e,\"gl3d\")?0:4))}}},{\"../../lib\":717,\"../../plot_api/plot_template\":755,\"../../registry\":846,\"./attributes\":615,\"fast-isnumeric\":228}],619:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"./attributes\"),o={error_x:n.extendFlat({},i),error_y:n.extendFlat({},i)};delete o.error_x.copy_zstyle,delete o.error_y.copy_zstyle,delete o.error_y.copy_ystyle;var s={error_x:n.extendFlat({},i),error_y:n.extendFlat({},i),error_z:n.extendFlat({},i)};delete s.error_x.copy_ystyle,delete s.error_y.copy_ystyle,delete s.error_z.copy_ystyle,delete s.error_z.copy_zstyle,e.exports={moduleType:\"component\",name:\"errorbars\",schema:{traces:{scatter:o,bar:o,histogram:o,scatter3d:a(s,\"calc\",\"nested\"),scattergl:a(o,\"calc\",\"nested\")}},supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),makeComputeError:t(\"./compute_error\"),plot:t(\"./plot\"),style:t(\"./style\"),hoverInfo:function(t,e,r){(e.error_y||{}).visible&&(r.yerr=t.yh-t.y,e.error_y.symmetric||(r.yerrneg=t.y-t.ys));(e.error_x||{}).visible&&(r.xerr=t.xh-t.x,e.error_x.symmetric||(r.xerrneg=t.x-t.xs))}}},{\"../../lib\":717,\"../../plot_api/edit_types\":748,\"./attributes\":615,\"./calc\":616,\"./compute_error\":617,\"./defaults\":618,\"./plot\":620,\"./style\":621}],620:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"fast-isnumeric\"),i=t(\"../drawing\"),o=t(\"../../traces/scatter/subtypes\");e.exports=function(t,e,r,s){var l=r.xaxis,c=r.yaxis,u=s&&s.duration>0;e.each(function(e){var h,f=e[0].trace,p=f.error_x||{},d=f.error_y||{};f.ids&&(h=function(t){return t.id});var g=o.hasMarkers(f)&&f.marker.maxdisplayed>0;d.visible||p.visible||(e=[]);var v=n.select(this).selectAll(\"g.errorbar\").data(e,h);if(v.exit().remove(),e.length){p.visible||v.selectAll(\"path.xerror\").remove(),d.visible||v.selectAll(\"path.yerror\").remove(),v.style(\"opacity\",1);var m=v.enter().append(\"g\").classed(\"errorbar\",!0);u&&m.style(\"opacity\",0).transition().duration(s.duration).style(\"opacity\",1),i.setClipUrl(v,r.layerClipId,t),v.each(function(t){var e=n.select(this),r=function(t,e,r){var n={x:e.c2p(t.x),y:r.c2p(t.y)};void 0!==t.yh&&(n.yh=r.c2p(t.yh),n.ys=r.c2p(t.ys),a(n.ys)||(n.noYS=!0,n.ys=r.c2p(t.ys,!0)));void 0!==t.xh&&(n.xh=e.c2p(t.xh),n.xs=e.c2p(t.xs),a(n.xs)||(n.noXS=!0,n.xs=e.c2p(t.xs,!0)));return n}(t,l,c);if(!g||t.vis){var i,o=e.select(\"path.yerror\");if(d.visible&&a(r.x)&&a(r.yh)&&a(r.ys)){var h=d.width;i=\"M\"+(r.x-h)+\",\"+r.yh+\"h\"+2*h+\"m-\"+h+\",0V\"+r.ys,r.noYS||(i+=\"m-\"+h+\",0h\"+2*h),!o.size()?o=e.append(\"path\").style(\"vector-effect\",\"non-scaling-stroke\").classed(\"yerror\",!0):u&&(o=o.transition().duration(s.duration).ease(s.easing)),o.attr(\"d\",i)}else o.remove();var f=e.select(\"path.xerror\");if(p.visible&&a(r.y)&&a(r.xh)&&a(r.xs)){var v=(p.copy_ystyle?d:p).width;i=\"M\"+r.xh+\",\"+(r.y-v)+\"v\"+2*v+\"m0,-\"+v+\"H\"+r.xs,r.noXS||(i+=\"m0,-\"+v+\"v\"+2*v),!f.size()?f=e.append(\"path\").style(\"vector-effect\",\"non-scaling-stroke\").classed(\"xerror\",!0):u&&(f=f.transition().duration(s.duration).ease(s.easing)),f.attr(\"d\",i)}else f.remove()}})}})}},{\"../../traces/scatter/subtypes\":1144,\"../drawing\":613,d3:165,\"fast-isnumeric\":228}],621:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../color\");e.exports=function(t){t.each(function(t){var e=t[0].trace,r=e.error_y||{},i=e.error_x||{},o=n.select(this);o.selectAll(\"path.yerror\").style(\"stroke-width\",r.thickness+\"px\").call(a.stroke,r.color),i.copy_ystyle&&(i=r),o.selectAll(\"path.xerror\").style(\"stroke-width\",i.thickness+\"px\").call(a.stroke,i.color)})}},{\"../color\":592,d3:165}],622:[function(t,e,r){\"use strict\";var n=t(\"../../plots/font_attributes\"),a=t(\"./layout_attributes\").hoverlabel,i=t(\"../../lib/extend\").extendFlat;e.exports={hoverlabel:{bgcolor:i({},a.bgcolor,{arrayOk:!0}),bordercolor:i({},a.bordercolor,{arrayOk:!0}),font:n({arrayOk:!0,editType:\"none\"}),align:i({},a.align,{arrayOk:!0}),namelength:i({},a.namelength,{arrayOk:!0}),editType:\"none\"}}},{\"../../lib/extend\":708,\"../../plots/font_attributes\":791,\"./layout_attributes\":631}],623:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../registry\");function i(t,e,r,a){a=a||n.identity,Array.isArray(t)&&(e[0][r]=a(t))}e.exports=function(t){var e=t.calcdata,r=t._fullLayout;function o(t){return function(e){return n.coerceHoverinfo({hoverinfo:e},{_module:t._module},r)}}for(var s=0;s<e.length;s++){var l=e[s],c=l[0].trace;if(!a.traceIs(c,\"pie-like\")){var u=a.traceIs(c,\"2dMap\")?i:n.fillArray;u(c.hoverinfo,l,\"hi\",o(c)),c.hovertemplate&&u(c.hovertemplate,l,\"ht\"),c.hoverlabel&&(u(c.hoverlabel.bgcolor,l,\"hbg\"),u(c.hoverlabel.bordercolor,l,\"hbc\"),u(c.hoverlabel.font.size,l,\"hts\"),u(c.hoverlabel.font.color,l,\"htc\"),u(c.hoverlabel.font.family,l,\"htf\"),u(c.hoverlabel.namelength,l,\"hnl\"),u(c.hoverlabel.align,l,\"hta\"))}}}},{\"../../lib\":717,\"../../registry\":846}],624:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"./hover\").hover;e.exports=function(t,e,r){var i=n.getComponentMethod(\"annotations\",\"onClick\")(t,t._hoverdata);function o(){t.emit(\"plotly_click\",{points:t._hoverdata,event:e})}void 0!==r&&a(t,e,r,!0),t._hoverdata&&e&&e.target&&(i&&i.then?i.then(o):o(),e.stopImmediatePropagation&&e.stopImmediatePropagation())}},{\"../../registry\":846,\"./hover\":628}],625:[function(t,e,r){\"use strict\";e.exports={YANGLE:60,HOVERARROWSIZE:6,HOVERTEXTPAD:3,HOVERFONTSIZE:13,HOVERFONT:\"Arial, sans-serif\",HOVERMINTIME:50,HOVERID:\"-hover\"}},{}],626:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./attributes\"),i=t(\"./hoverlabel_defaults\");e.exports=function(t,e,r,o){var s=n.extendFlat({},o.hoverlabel);e.hovertemplate&&(s.namelength=-1),i(t,e,function(r,i){return n.coerce(t,e,a,r,i)},s)}},{\"../../lib\":717,\"./attributes\":622,\"./hoverlabel_defaults\":629}],627:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");r.getSubplot=function(t){return t.subplot||t.xaxis+t.yaxis||t.geo},r.isTraceInSubplots=function(t,e){if(\"splom\"===t.type){for(var n=t.xaxes||[],a=t.yaxes||[],i=0;i<n.length;i++)for(var o=0;o<a.length;o++)if(-1!==e.indexOf(n[i]+a[o]))return!0;return!1}return-1!==e.indexOf(r.getSubplot(t))},r.flat=function(t,e){for(var r=new Array(t.length),n=0;n<t.length;n++)r[n]=e;return r},r.p2c=function(t,e){for(var r=new Array(t.length),n=0;n<t.length;n++)r[n]=t[n].p2c(e);return r},r.getDistanceFunction=function(t,e,n,a){return\"closest\"===t?a||r.quadrature(e,n):\"x\"===t?e:n},r.getClosest=function(t,e,r){if(!1!==r.index)r.index>=0&&r.index<t.length?r.distance=0:r.index=!1;else for(var n=0;n<t.length;n++){var a=e(t[n]);a<=r.distance&&(r.index=n,r.distance=a)}return r},r.inbox=function(t,e,r){return t*e<0||0===t?r:1/0},r.quadrature=function(t,e){return function(r){var n=t(r),a=e(r);return Math.sqrt(n*n+a*a)}},r.makeEventData=function(t,e,n){var a=\"index\"in t?t.index:t.pointNumber,i={data:e._input,fullData:e,curveNumber:e.index,pointNumber:a};if(e._indexToPoints){var o=e._indexToPoints[a];1===o.length?i.pointIndex=o[0]:i.pointIndices=o}else i.pointIndex=a;return e._module.eventData?i=e._module.eventData(i,t,e,n,a):(\"xVal\"in t?i.x=t.xVal:\"x\"in t&&(i.x=t.x),\"yVal\"in t?i.y=t.yVal:\"y\"in t&&(i.y=t.y),t.xa&&(i.xaxis=t.xa),t.ya&&(i.yaxis=t.ya),void 0!==t.zLabelVal&&(i.z=t.zLabelVal)),r.appendArrayPointValue(i,e,a),i},r.appendArrayPointValue=function(t,e,r){var a=e._arrayAttrs;if(a)for(var s=0;s<a.length;s++){var l=a[s],c=i(l);if(void 0===t[c]){var u=o(n.nestedProperty(e,l).get(),r);void 0!==u&&(t[c]=u)}}},r.appendArrayMultiPointValues=function(t,e,r){var a=e._arrayAttrs;if(a)for(var s=0;s<a.length;s++){var l=a[s],c=i(l);if(void 0===t[c]){for(var u=n.nestedProperty(e,l).get(),h=new Array(r.length),f=0;f<r.length;f++)h[f]=o(u,r[f]);t[c]=h}}};var a={ids:\"id\",locations:\"location\",labels:\"label\",values:\"value\",\"marker.colors\":\"color\",parents:\"parent\"};function i(t){return a[t]||t}function o(t,e){return Array.isArray(e)?Array.isArray(t)&&Array.isArray(t[e[0]])?t[e[0]][e[1]]:void 0:t[e]}},{\"../../lib\":717}],628:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"fast-isnumeric\"),i=t(\"tinycolor2\"),o=t(\"../../lib\"),s=t(\"../../lib/events\"),l=t(\"../../lib/svg_text_utils\"),c=t(\"../../lib/override_cursor\"),u=t(\"../drawing\"),h=t(\"../color\"),f=t(\"../dragelement\"),p=t(\"../../plots/cartesian/axes\"),d=t(\"../../registry\"),g=t(\"./helpers\"),v=t(\"./constants\"),m=v.YANGLE,y=Math.PI*m/180,x=1/Math.sin(y),b=Math.cos(y),_=Math.sin(y),w=v.HOVERARROWSIZE,k=v.HOVERTEXTPAD;r.hover=function(t,e,r,i){t=o.getGraphDiv(t),o.throttle(t._fullLayout._uid+v.HOVERID,v.HOVERMINTIME,function(){!function(t,e,r,i){r||(r=\"xy\");var l=Array.isArray(r)?r:[r],u=t._fullLayout,p=u._plots||[],v=p[r],m=u._has(\"cartesian\");if(v){var y=v.overlays.map(function(t){return t.id});l=l.concat(y)}for(var b=l.length,_=new Array(b),w=new Array(b),k=!1,T=0;T<b;T++){var C=l[T];if(p[C])k=!0,_[T]=p[C].xaxis,w[T]=p[C].yaxis;else{if(!u[C]||!u[C]._subplot)return void o.warn(\"Unrecognized subplot: \"+C);var P=u[C]._subplot;_[T]=P.xaxis,w[T]=P.yaxis}}var O=e.hovermode||u.hovermode;O&&!k&&(O=\"closest\");if(-1===[\"x\",\"y\",\"closest\"].indexOf(O)||!t.calcdata||t.querySelector(\".zoombox\")||t._dragging)return f.unhoverRaw(t,e);var z,I,D,R,F,B,N,j,V,U,q,H,G,Y=-1===u.hoverdistance?1/0:u.hoverdistance,W=-1===u.spikedistance?1/0:u.spikedistance,X=[],Z=[],J={hLinePoint:null,vLinePoint:null},K=!1;if(Array.isArray(e))for(O=\"array\",D=0;D<e.length;D++)(F=t.calcdata[e[D].curveNumber||0])&&(B=F[0].trace,\"skip\"!==F[0].trace.hoverinfo&&(Z.push(F),\"h\"===B.orientation&&(K=!0)));else{for(R=0;R<t.calcdata.length;R++)F=t.calcdata[R],\"skip\"!==(B=F[0].trace).hoverinfo&&g.isTraceInSubplots(B,l)&&(Z.push(F),\"h\"===B.orientation&&(K=!0));var Q,$,tt=!e.target;if(tt)Q=\"xpx\"in e?e.xpx:_[0]._length/2,$=\"ypx\"in e?e.ypx:w[0]._length/2;else{if(!1===s.triggerHandler(t,\"plotly_beforehover\",e))return;var et=e.target.getBoundingClientRect();if(Q=e.clientX-et.left,$=e.clientY-et.top,Q<0||Q>_[0]._length||$<0||$>w[0]._length)return f.unhoverRaw(t,e)}if(e.pointerX=Q+_[0]._offset,e.pointerY=$+w[0]._offset,z=\"xval\"in e?g.flat(l,e.xval):g.p2c(_,Q),I=\"yval\"in e?g.flat(l,e.yval):g.p2c(w,$),!a(z[0])||!a(I[0]))return o.warn(\"Fx.hover failed\",e,t),f.unhoverRaw(t,e)}var rt=1/0;for(R=0;R<Z.length;R++)if((F=Z[R])&&F[0]&&F[0].trace&&!0===(B=F[0].trace).visible&&0!==B._length&&-1===[\"carpet\",\"contourcarpet\"].indexOf(B._module.name)){if(\"splom\"===B.type?N=l[j=0]:(N=g.getSubplot(B),j=l.indexOf(N)),V=O,H={cd:F,trace:B,xa:_[j],ya:w[j],maxHoverDistance:Y,maxSpikeDistance:W,index:!1,distance:Math.min(rt,Y),spikeDistance:1/0,xSpike:void 0,ySpike:void 0,color:h.defaultLine,name:B.name,x0:void 0,x1:void 0,y0:void 0,y1:void 0,xLabelVal:void 0,yLabelVal:void 0,zLabelVal:void 0,text:void 0},u[N]&&(H.subplot=u[N]._subplot),u._splomScenes&&u._splomScenes[B.uid]&&(H.scene=u._splomScenes[B.uid]),G=X.length,\"array\"===V){var nt=e[R];\"pointNumber\"in nt?(H.index=nt.pointNumber,V=\"closest\"):(V=\"\",\"xval\"in nt&&(U=nt.xval,V=\"x\"),\"yval\"in nt&&(q=nt.yval,V=V?\"closest\":\"y\"))}else U=z[j],q=I[j];if(0!==Y)if(B._module&&B._module.hoverPoints){var at=B._module.hoverPoints(H,U,q,V,u._hoverlayer);if(at)for(var it,ot=0;ot<at.length;ot++)it=at[ot],a(it.x0)&&a(it.y0)&&X.push(S(it,O))}else o.log(\"Unrecognized trace type in hover:\",B);if(\"closest\"===O&&X.length>G&&(X.splice(0,G),rt=X[0].distance),m&&0!==W&&0===X.length){H.distance=W,H.index=!1;var st=B._module.hoverPoints(H,U,q,\"closest\",u._hoverlayer);if(st&&(st=st.filter(function(t){return t.spikeDistance<=W})),st&&st.length){var lt,ct=st.filter(function(t){return t.xa.showspikes});if(ct.length){var ut=ct[0];a(ut.x0)&&a(ut.y0)&&(lt=dt(ut),(!J.vLinePoint||J.vLinePoint.spikeDistance>lt.spikeDistance)&&(J.vLinePoint=lt))}var ht=st.filter(function(t){return t.ya.showspikes});if(ht.length){var ft=ht[0];a(ft.x0)&&a(ft.y0)&&(lt=dt(ft),(!J.hLinePoint||J.hLinePoint.spikeDistance>lt.spikeDistance)&&(J.hLinePoint=lt))}}}}function pt(t,e){for(var r,n=null,a=1/0,i=0;i<t.length;i++)(r=t[i].spikeDistance)<a&&r<=e&&(n=t[i],a=r);return n}function dt(t){return t?{xa:t.xa,ya:t.ya,x:void 0!==t.xSpike?t.xSpike:(t.x0+t.x1)/2,y:void 0!==t.ySpike?t.ySpike:(t.y0+t.y1)/2,distance:t.distance,spikeDistance:t.spikeDistance,curveNumber:t.trace.index,color:t.color,pointNumber:t.index}:null}var gt={fullLayout:u,container:u._hoverlayer,outerContainer:u._paperdiv,event:e},vt=t._spikepoints,mt={vLinePoint:J.vLinePoint,hLinePoint:J.hLinePoint};if(t._spikepoints=mt,m&&0!==W&&0!==X.length){var yt=X.filter(function(t){return t.ya.showspikes}),xt=pt(yt,W);J.hLinePoint=dt(xt);var bt=X.filter(function(t){return t.xa.showspikes}),_t=pt(bt,W);J.vLinePoint=dt(_t)}if(0===X.length){var wt=f.unhoverRaw(t,e);return!m||null===J.hLinePoint&&null===J.vLinePoint||L(vt)&&E(t,J,gt),wt}m&&L(vt)&&E(t,J,gt);X.sort(function(t,e){return t.distance-e.distance});var kt=t._hoverdata,Tt=[];for(D=0;D<X.length;D++){var Mt=X[D],At=g.makeEventData(Mt,Mt.trace,Mt.cd);if(!1!==Mt.hovertemplate){var St=!1;Mt.cd[Mt.index]&&Mt.cd[Mt.index].ht&&(St=Mt.cd[Mt.index].ht),Mt.hovertemplate=St||Mt.trace.hovertemplate||!1}Mt.eventData=[At],Tt.push(At)}t._hoverdata=Tt;var Et=\"y\"===O&&(Z.length>1||X.length>1)||\"closest\"===O&&K&&X.length>1,Lt=h.combine(u.plot_bgcolor||h.background,u.paper_bgcolor),Ct={hovermode:O,rotateLabels:Et,bgColor:Lt,container:u._hoverlayer,outerContainer:u._paperdiv,commonLabelOpts:u.hoverlabel,hoverdistance:u.hoverdistance},Pt=M(X,Ct,t);if(function(t,e,r){var n,a,i,o,s,l,c,u=0,h=1,f=t.size(),p=new Array(f),d=0;function g(t){var e=t[0],r=t[t.length-1];if(a=e.pmin-e.pos-e.dp+e.size,i=r.pos+r.dp+r.size-e.pmax,a>.01){for(s=t.length-1;s>=0;s--)t[s].dp+=a;n=!1}if(!(i<.01)){if(a<-.01){for(s=t.length-1;s>=0;s--)t[s].dp-=i;n=!1}if(n){var c=0;for(o=0;o<t.length;o++)(l=t[o]).pos+l.dp+l.size>e.pmax&&c++;for(o=t.length-1;o>=0&&!(c<=0);o--)(l=t[o]).pos>e.pmax-1&&(l.del=!0,c--);for(o=0;o<t.length&&!(c<=0);o++)if((l=t[o]).pos<e.pmin+1)for(l.del=!0,c--,i=2*l.size,s=t.length-1;s>=0;s--)t[s].dp-=i;for(o=t.length-1;o>=0&&!(c<=0);o--)(l=t[o]).pos+l.dp+l.size>e.pmax&&(l.del=!0,c--)}}}for(t.each(function(t){var n=t[e],a=\"x\"===n._id.charAt(0),i=n.range;0===d&&i&&i[0]>i[1]!==a&&(h=-1),p[d++]=[{datum:t,traceIndex:t.trace.index,dp:0,pos:t.pos,posref:t.posref,size:t.by*(a?x:1)/2,pmin:0,pmax:a?r.width:r.height}]}),p.sort(function(t,e){return t[0].posref-e[0].posref||h*(e[0].traceIndex-t[0].traceIndex)});!n&&u<=f;){for(u++,n=!0,o=0;o<p.length-1;){var v=p[o],m=p[o+1],y=v[v.length-1],b=m[0];if((a=y.pos+y.dp+y.size-b.pos-b.dp+b.size)>.01&&y.pmin===b.pmin&&y.pmax===b.pmax){for(s=m.length-1;s>=0;s--)m[s].dp+=a;for(v.push.apply(v,m),p.splice(o+1,1),c=0,s=v.length-1;s>=0;s--)c+=v[s].dp;for(i=c/v.length,s=v.length-1;s>=0;s--)v[s].dp-=i;n=!1}else o++}p.forEach(g)}for(o=p.length-1;o>=0;o--){var _=p[o];for(s=_.length-1;s>=0;s--){var w=_[s],k=w.datum;k.offset=w.dp,k.del=w.del}}}(Pt,Et?\"xa\":\"ya\",u),A(Pt,Et),e.target&&e.target.tagName){var Ot=d.getComponentMethod(\"annotations\",\"hasClickToShow\")(t,Tt);c(n.select(e.target),Ot?\"pointer\":\"\")}if(!e.target||i||!function(t,e,r){if(!r||r.length!==t._hoverdata.length)return!0;for(var n=r.length-1;n>=0;n--){var a=r[n],i=t._hoverdata[n];if(a.curveNumber!==i.curveNumber||String(a.pointNumber)!==String(i.pointNumber)||String(a.pointNumbers)!==String(i.pointNumbers))return!0}return!1}(t,0,kt))return;kt&&t.emit(\"plotly_unhover\",{event:e,points:kt});t.emit(\"plotly_hover\",{event:e,points:t._hoverdata,xaxes:_,yaxes:w,xvals:z,yvals:I})}(t,e,r,i)})},r.loneHover=function(t,e){var r=!0;Array.isArray(t)||(r=!1,t=[t]);var a=t.map(function(t){return{color:t.color||h.defaultLine,x0:t.x0||t.x||0,x1:t.x1||t.x||0,y0:t.y0||t.y||0,y1:t.y1||t.y||0,xLabel:t.xLabel,yLabel:t.yLabel,zLabel:t.zLabel,text:t.text,name:t.name,idealAlign:t.idealAlign,borderColor:t.borderColor,fontFamily:t.fontFamily,fontSize:t.fontSize,fontColor:t.fontColor,nameLength:t.nameLength,textAlign:t.textAlign,trace:t.trace||{index:0,hoverinfo:\"\"},xa:{_offset:0},ya:{_offset:0},index:0,hovertemplate:t.hovertemplate||!1,eventData:t.eventData||!1,hovertemplateLabels:t.hovertemplateLabels||!1}}),i=n.select(e.container),o=e.outerContainer?n.select(e.outerContainer):i,s={hovermode:\"closest\",rotateLabels:!1,bgColor:e.bgColor||h.background,container:i,outerContainer:o},l=M(a,s,e.gd),c=0,u=0;return l.sort(function(t,e){return t.y0-e.y0}).each(function(t,r){var n=t.y0-t.by/2;t.offset=n-5<c?c-n+5:0,c=n+t.by+t.offset,r===e.anchorIndex&&(u=t.offset)}).each(function(t){t.offset-=u}),A(l,s.rotateLabels),r?l:l.node()};var T=/<extra>([\\s\\S]*)<\\/extra>/;function M(t,e,r){var a=r._fullLayout,i=e.hovermode,s=e.rotateLabels,c=e.bgColor,f=e.container,p=e.outerContainer,d=e.commonLabelOpts||{},g=e.fontFamily||v.HOVERFONT,y=e.fontSize||v.HOVERFONTSIZE,x=t[0],b=x.xa,_=x.ya,M=\"y\"===i?\"yLabel\":\"xLabel\",A=x[M],S=(String(A)||\"\").split(\" \")[0],E=p.node().getBoundingClientRect(),L=E.top,P=E.width,O=E.height,z=void 0!==A&&x.distance<=e.hoverdistance&&(\"x\"===i||\"y\"===i);if(z){var I,D,R=!0;for(I=0;I<t.length;I++)if(R&&void 0===t[I].zLabel&&(R=!1),D=t[I].hoverinfo||t[I].trace.hoverinfo){var F=Array.isArray(D)?D:D.split(\"+\");if(-1===F.indexOf(\"all\")&&-1===F.indexOf(i)){z=!1;break}}R&&(z=!1)}var B=f.selectAll(\"g.axistext\").data(z?[0]:[]);B.enter().append(\"g\").classed(\"axistext\",!0),B.exit().remove(),B.each(function(){var e=n.select(this),s=o.ensureSingle(e,\"path\",\"\",function(t){t.style({\"stroke-width\":\"1px\"})}),c=o.ensureSingle(e,\"text\",\"\",function(t){t.attr(\"data-notex\",1)}),f=d.bgcolor||h.defaultLine,p=d.bordercolor||h.contrast(f),v=h.contrast(f),m={family:d.font.family||g,size:d.font.size||y,color:d.font.color||v};s.style({fill:f,stroke:p}),c.text(A).call(u.font,m).call(l.positionText,0,0).call(l.convertToTspans,r),e.attr(\"transform\",\"\");var T,E,C=c.node().getBoundingClientRect();if(\"x\"===i){var P=\"top\"===b.side?\"-\":\"\";c.attr(\"text-anchor\",\"middle\").call(l.positionText,0,\"top\"===b.side?L-C.bottom-w-k:L-C.top+w+k),T=b._offset+(x.x0+x.x1)/2,E=_._offset+(\"top\"===b.side?0:_._length);var O=C.width/2+k;T<O?(T=O,s.attr(\"d\",\"M-\"+(O-w)+\",0L-\"+(O-2*w)+\",\"+P+w+\"H\"+(k+C.width/2)+\"v\"+P+(2*k+C.height)+\"H-\"+O+\"V\"+P+w+\"Z\")):T>a.width-O?(T=a.width-O,s.attr(\"d\",\"M\"+(O-w)+\",0L\"+O+\",\"+P+w+\"v\"+P+(2*k+C.height)+\"H-\"+O+\"V\"+P+w+\"H\"+(O-2*w)+\"Z\")):s.attr(\"d\",\"M0,0L\"+w+\",\"+P+w+\"H\"+(k+C.width/2)+\"v\"+P+(2*k+C.height)+\"H-\"+(k+C.width/2)+\"V\"+P+w+\"H-\"+w+\"Z\")}else{var z,I,D;\"right\"===_.side?(z=\"start\",I=1,D=\"\",T=b._offset+b._length):(z=\"end\",I=-1,D=\"-\",T=b._offset),E=_._offset+(x.y0+x.y1)/2,c.attr(\"text-anchor\",z),s.attr(\"d\",\"M0,0L\"+D+w+\",\"+w+\"V\"+(k+C.height/2)+\"h\"+D+(2*k+C.width)+\"V-\"+(k+C.height/2)+\"H\"+D+w+\"V-\"+w+\"Z\");var R,F=C.height/2,B=L-C.top-F,N=\"clip\"+a._uid+\"commonlabel\"+_._id;if(T<C.width+2*k+w){R=\"M-\"+(w+k)+\"-\"+F+\"h-\"+(C.width-k)+\"V\"+F+\"h\"+(C.width-k)+\"Z\";var j=C.width-T+k;l.positionText(c,j,B),\"end\"===z&&c.selectAll(\"tspan\").each(function(){var t=n.select(this),e=u.tester.append(\"text\").text(t.text()).call(u.font,m),r=e.node().getBoundingClientRect();Math.round(r.width)<Math.round(C.width)&&t.attr(\"x\",j-r.width),e.remove()})}else l.positionText(c,I*(k+w),B),R=null;var V=a._topclips.selectAll(\"#\"+N).data(R?[0]:[]);V.enter().append(\"clipPath\").attr(\"id\",N).append(\"path\"),V.exit().remove(),V.select(\"path\").attr(\"d\",R),u.setClipUrl(c,R?N:null,r)}e.attr(\"transform\",\"translate(\"+T+\",\"+E+\")\"),t=t.filter(function(t){return void 0!==t.zLabelVal||(t[M]||\"\").split(\" \")[0]===S})});var N=f.selectAll(\"g.hovertext\").data(t,function(t){return[t.trace.index,t.index,t.x0,t.y0,t.name,t.attr,t.xa,t.ya||\"\"].join(\",\")});return N.enter().append(\"g\").classed(\"hovertext\",!0).each(function(){var t=n.select(this);t.append(\"rect\").call(h.fill,h.addOpacity(c,.8)),t.append(\"text\").classed(\"name\",!0),t.append(\"path\").style(\"stroke-width\",\"1px\"),t.append(\"text\").classed(\"nums\",!0).call(u.font,g,y)}),N.exit().remove(),N.each(function(t){var e=n.select(this).attr(\"transform\",\"\"),f=\"\",p=\"\",d=t.bgcolor||t.color,v=h.combine(h.opacity(d)?d:h.defaultLine,c),x=h.combine(h.opacity(t.color)?t.color:h.defaultLine,c),b=t.borderColor||h.contrast(v);void 0!==t.nameOverride&&(t.name=t.nameOverride),t.name&&(t.trace._meta&&(t.name=o.templateString(t.name,t.trace._meta)),f=C(t.name,t.nameLength)),void 0!==t.zLabel?(void 0!==t.xLabel&&(p+=\"x: \"+t.xLabel+\"<br>\"),void 0!==t.yLabel&&(p+=\"y: \"+t.yLabel+\"<br>\"),\"choropleth\"!==t.trace.type&&\"choroplethmapbox\"!==t.trace.type&&(p+=(p?\"z: \":\"\")+t.zLabel)):z&&t[i+\"Label\"]===A?p=t[(\"x\"===i?\"y\":\"x\")+\"Label\"]||\"\":void 0===t.xLabel?void 0!==t.yLabel&&\"scattercarpet\"!==t.trace.type&&(p=t.yLabel):p=void 0===t.yLabel?t.xLabel:\"(\"+t.xLabel+\", \"+t.yLabel+\")\",!t.text&&0!==t.text||Array.isArray(t.text)||(p+=(p?\"<br>\":\"\")+t.text),void 0!==t.extraText&&(p+=(p?\"<br>\":\"\")+t.extraText),\"\"!==p||t.hovertemplate||(\"\"===f&&e.remove(),p=f);var _=a._d3locale,M=t.hovertemplate||!1,S=t.hovertemplateLabels||t,E=t.eventData[0]||{};M&&(p=(p=o.hovertemplateString(M,S,_,E,t.trace._meta)).replace(T,function(e,r){return f=C(r,t.nameLength),\"\"}));var I=e.select(\"text.nums\").call(u.font,t.fontFamily||g,t.fontSize||y,t.fontColor||b).text(p).attr(\"data-notex\",1).call(l.positionText,0,0).call(l.convertToTspans,r),D=e.select(\"text.name\"),R=0,F=0;if(f&&f!==p){D.call(u.font,t.fontFamily||g,t.fontSize||y,x).text(f).attr(\"data-notex\",1).call(l.positionText,0,0).call(l.convertToTspans,r);var B=D.node().getBoundingClientRect();R=B.width+2*k,F=B.height+2*k}else D.remove(),e.select(\"rect\").remove();e.select(\"path\").style({fill:v,stroke:b});var N,j,V=I.node().getBoundingClientRect(),U=t.xa._offset+(t.x0+t.x1)/2,q=t.ya._offset+(t.y0+t.y1)/2,H=Math.abs(t.x1-t.x0),G=Math.abs(t.y1-t.y0),Y=V.width+w+k+R;if(t.ty0=L-V.top,t.bx=V.width+2*k,t.by=Math.max(V.height+2*k,F),t.anchor=\"start\",t.txwidth=V.width,t.tx2width=R,t.offset=0,s)t.pos=U,N=q+G/2+Y<=O,j=q-G/2-Y>=0,\"top\"!==t.idealAlign&&N||!j?N?(q+=G/2,t.anchor=\"start\"):t.anchor=\"middle\":(q-=G/2,t.anchor=\"end\");else if(t.pos=q,N=U+H/2+Y<=P,j=U-H/2-Y>=0,\"left\"!==t.idealAlign&&N||!j)if(N)U+=H/2,t.anchor=\"start\";else{t.anchor=\"middle\";var W=Y/2,X=U+W-P,Z=U-W;X>0&&(U-=X),Z<0&&(U+=-Z)}else U-=H/2,t.anchor=\"end\";I.attr(\"text-anchor\",t.anchor),R&&D.attr(\"text-anchor\",t.anchor),e.attr(\"transform\",\"translate(\"+U+\",\"+q+\")\"+(s?\"rotate(\"+m+\")\":\"\"))}),N}function A(t,e){t.each(function(t){var r=n.select(this);if(t.del)return r.remove();var a=r.select(\"text.nums\"),i=t.anchor,o=\"end\"===i?-1:1,s={start:1,end:-1,middle:0}[i],c=s*(w+k),h=c+s*(t.txwidth+k),f=0,p=t.offset;\"middle\"===i&&(c-=t.tx2width/2,h+=t.txwidth/2+k),e&&(p*=-_,f=t.offset*b),r.select(\"path\").attr(\"d\",\"middle\"===i?\"M-\"+(t.bx/2+t.tx2width/2)+\",\"+(p-t.by/2)+\"h\"+t.bx+\"v\"+t.by+\"h-\"+t.bx+\"Z\":\"M0,0L\"+(o*w+f)+\",\"+(w+p)+\"v\"+(t.by/2-w)+\"h\"+o*t.bx+\"v-\"+t.by+\"H\"+(o*w+f)+\"V\"+(p-w)+\"Z\");var d=c+f,g=p+t.ty0-t.by/2+k,v=t.textAlign||\"auto\";\"auto\"!==v&&(\"left\"===v&&\"start\"!==i?(a.attr(\"text-anchor\",\"start\"),d=\"middle\"===i?-t.bx/2-t.tx2width/2+k:-t.bx-k):\"right\"===v&&\"end\"!==i&&(a.attr(\"text-anchor\",\"end\"),d=\"middle\"===i?t.bx/2-t.tx2width/2-k:t.bx+k)),a.call(l.positionText,d,g),t.tx2width&&(r.select(\"text.name\").call(l.positionText,h+s*k+f,p+t.ty0-t.by/2+k),r.select(\"rect\").call(u.setRect,h+(s-1)*t.tx2width/2+f,p-t.by/2-1,t.tx2width,t.by+2))})}function S(t,e){var r=t.index,n=t.trace||{},i=t.cd[0],s=t.cd[r]||{};function l(t){return t||a(t)&&0===t}var c=Array.isArray(r)?function(t,e){var a=o.castOption(i,r,t);return l(a)?a:o.extractOption({},n,\"\",e)}:function(t,e){return o.extractOption(s,n,t,e)};function u(e,r,n){var a=c(r,n);l(a)&&(t[e]=a)}if(u(\"hoverinfo\",\"hi\",\"hoverinfo\"),u(\"bgcolor\",\"hbg\",\"hoverlabel.bgcolor\"),u(\"borderColor\",\"hbc\",\"hoverlabel.bordercolor\"),u(\"fontFamily\",\"htf\",\"hoverlabel.font.family\"),u(\"fontSize\",\"hts\",\"hoverlabel.font.size\"),u(\"fontColor\",\"htc\",\"hoverlabel.font.color\"),u(\"nameLength\",\"hnl\",\"hoverlabel.namelength\"),u(\"textAlign\",\"hta\",\"hoverlabel.align\"),t.posref=\"y\"===e||\"closest\"===e&&\"h\"===n.orientation?t.xa._offset+(t.x0+t.x1)/2:t.ya._offset+(t.y0+t.y1)/2,t.x0=o.constrain(t.x0,0,t.xa._length),t.x1=o.constrain(t.x1,0,t.xa._length),t.y0=o.constrain(t.y0,0,t.ya._length),t.y1=o.constrain(t.y1,0,t.ya._length),void 0!==t.xLabelVal&&(t.xLabel=\"xLabel\"in t?t.xLabel:p.hoverLabelText(t.xa,t.xLabelVal),t.xVal=t.xa.c2d(t.xLabelVal)),void 0!==t.yLabelVal&&(t.yLabel=\"yLabel\"in t?t.yLabel:p.hoverLabelText(t.ya,t.yLabelVal),t.yVal=t.ya.c2d(t.yLabelVal)),void 0!==t.zLabelVal&&void 0===t.zLabel&&(t.zLabel=String(t.zLabelVal)),!(isNaN(t.xerr)||\"log\"===t.xa.type&&t.xerr<=0)){var h=p.tickText(t.xa,t.xa.c2l(t.xerr),\"hover\").text;void 0!==t.xerrneg?t.xLabel+=\" +\"+h+\" / -\"+p.tickText(t.xa,t.xa.c2l(t.xerrneg),\"hover\").text:t.xLabel+=\" \\xb1 \"+h,\"x\"===e&&(t.distance+=1)}if(!(isNaN(t.yerr)||\"log\"===t.ya.type&&t.yerr<=0)){var f=p.tickText(t.ya,t.ya.c2l(t.yerr),\"hover\").text;void 0!==t.yerrneg?t.yLabel+=\" +\"+f+\" / -\"+p.tickText(t.ya,t.ya.c2l(t.yerrneg),\"hover\").text:t.yLabel+=\" \\xb1 \"+f,\"y\"===e&&(t.distance+=1)}var d=t.hoverinfo||t.trace.hoverinfo;return d&&\"all\"!==d&&(-1===(d=Array.isArray(d)?d:d.split(\"+\")).indexOf(\"x\")&&(t.xLabel=void 0),-1===d.indexOf(\"y\")&&(t.yLabel=void 0),-1===d.indexOf(\"z\")&&(t.zLabel=void 0),-1===d.indexOf(\"text\")&&(t.text=void 0),-1===d.indexOf(\"name\")&&(t.name=void 0)),t}function E(t,e,r){var n,a,o=r.container,s=r.fullLayout,l=s._size,c=r.event,f=!!e.hLinePoint,d=!!e.vLinePoint;if(o.selectAll(\".spikeline\").remove(),d||f){var g=h.combine(s.plot_bgcolor,s.paper_bgcolor);if(f){var v,m,y=e.hLinePoint;n=y&&y.xa,\"cursor\"===(a=y&&y.ya).spikesnap?(v=c.pointerX,m=c.pointerY):(v=n._offset+y.x,m=a._offset+y.y);var x,b,_=i.readability(y.color,g)<1.5?h.contrast(g):y.color,w=a.spikemode,k=a.spikethickness,T=a.spikecolor||_,M=p.getPxPosition(t,a);if(-1!==w.indexOf(\"toaxis\")||-1!==w.indexOf(\"across\")){if(-1!==w.indexOf(\"toaxis\")&&(x=M,b=v),-1!==w.indexOf(\"across\")){var A=a._counterDomainMin,S=a._counterDomainMax;\"free\"===a.anchor&&(A=Math.min(A,a.position),S=Math.max(S,a.position)),x=l.l+A*l.w,b=l.l+S*l.w}o.insert(\"line\",\":first-child\").attr({x1:x,x2:b,y1:m,y2:m,\"stroke-width\":k,stroke:T,\"stroke-dasharray\":u.dashStyle(a.spikedash,k)}).classed(\"spikeline\",!0).classed(\"crisp\",!0),o.insert(\"line\",\":first-child\").attr({x1:x,x2:b,y1:m,y2:m,\"stroke-width\":k+2,stroke:g}).classed(\"spikeline\",!0).classed(\"crisp\",!0)}-1!==w.indexOf(\"marker\")&&o.insert(\"circle\",\":first-child\").attr({cx:M+(\"right\"!==a.side?k:-k),cy:m,r:k,fill:T}).classed(\"spikeline\",!0)}if(d){var E,L,C=e.vLinePoint;n=C&&C.xa,a=C&&C.ya,\"cursor\"===n.spikesnap?(E=c.pointerX,L=c.pointerY):(E=n._offset+C.x,L=a._offset+C.y);var P,O,z=i.readability(C.color,g)<1.5?h.contrast(g):C.color,I=n.spikemode,D=n.spikethickness,R=n.spikecolor||z,F=p.getPxPosition(t,n);if(-1!==I.indexOf(\"toaxis\")||-1!==I.indexOf(\"across\")){if(-1!==I.indexOf(\"toaxis\")&&(P=F,O=L),-1!==I.indexOf(\"across\")){var B=n._counterDomainMin,N=n._counterDomainMax;\"free\"===n.anchor&&(B=Math.min(B,n.position),N=Math.max(N,n.position)),P=l.t+(1-N)*l.h,O=l.t+(1-B)*l.h}o.insert(\"line\",\":first-child\").attr({x1:E,x2:E,y1:P,y2:O,\"stroke-width\":D,stroke:R,\"stroke-dasharray\":u.dashStyle(n.spikedash,D)}).classed(\"spikeline\",!0).classed(\"crisp\",!0),o.insert(\"line\",\":first-child\").attr({x1:E,x2:E,y1:P,y2:O,\"stroke-width\":D+2,stroke:g}).classed(\"spikeline\",!0).classed(\"crisp\",!0)}-1!==I.indexOf(\"marker\")&&o.insert(\"circle\",\":first-child\").attr({cx:E,cy:F-(\"top\"!==n.side?D:-D),r:D,fill:R}).classed(\"spikeline\",!0)}}}function L(t,e){return!e||(e.vLinePoint!==t._spikepoints.vLinePoint||e.hLinePoint!==t._spikepoints.hLinePoint)}function C(t,e){return l.plainText(t||\"\",{len:e,allowedTags:[\"br\",\"sub\",\"sup\",\"b\",\"i\",\"em\"]})}},{\"../../lib\":717,\"../../lib/events\":707,\"../../lib/override_cursor\":728,\"../../lib/svg_text_utils\":741,\"../../plots/cartesian/axes\":765,\"../../registry\":846,\"../color\":592,\"../dragelement\":610,\"../drawing\":613,\"./constants\":625,\"./helpers\":627,d3:165,\"fast-isnumeric\":228,tinycolor2:536}],629:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e,r,a){r(\"hoverlabel.bgcolor\",(a=a||{}).bgcolor),r(\"hoverlabel.bordercolor\",a.bordercolor),r(\"hoverlabel.namelength\",a.namelength),n.coerceFont(r,\"hoverlabel.font\",a.font),r(\"hoverlabel.align\",a.align)}},{\"../../lib\":717}],630:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\"),i=t(\"../dragelement\"),o=t(\"./helpers\"),s=t(\"./layout_attributes\"),l=t(\"./hover\");e.exports={moduleType:\"component\",name:\"fx\",constants:t(\"./constants\"),schema:{layout:s},attributes:t(\"./attributes\"),layoutAttributes:s,supplyLayoutGlobalDefaults:t(\"./layout_global_defaults\"),supplyDefaults:t(\"./defaults\"),supplyLayoutDefaults:t(\"./layout_defaults\"),calc:t(\"./calc\"),getDistanceFunction:o.getDistanceFunction,getClosest:o.getClosest,inbox:o.inbox,quadrature:o.quadrature,appendArrayPointValue:o.appendArrayPointValue,castHoverOption:function(t,e,r){return a.castOption(t,e,\"hoverlabel.\"+r)},castHoverinfo:function(t,e,r){return a.castOption(t,r,\"hoverinfo\",function(r){return a.coerceHoverinfo({hoverinfo:r},{_module:t._module},e)})},hover:l.hover,unhover:i.unhover,loneHover:l.loneHover,loneUnhover:function(t){var e=a.isD3Selection(t)?t:n.select(t);e.selectAll(\"g.hovertext\").remove(),e.selectAll(\".spikeline\").remove()},click:t(\"./click\")}},{\"../../lib\":717,\"../dragelement\":610,\"./attributes\":622,\"./calc\":623,\"./click\":624,\"./constants\":625,\"./defaults\":626,\"./helpers\":627,\"./hover\":628,\"./layout_attributes\":631,\"./layout_defaults\":632,\"./layout_global_defaults\":633,d3:165}],631:[function(t,e,r){\"use strict\";var n=t(\"./constants\"),a=t(\"../../plots/font_attributes\")({editType:\"none\"});a.family.dflt=n.HOVERFONT,a.size.dflt=n.HOVERFONTSIZE,e.exports={clickmode:{valType:\"flaglist\",flags:[\"event\",\"select\"],dflt:\"event\",editType:\"plot\",extras:[\"none\"]},dragmode:{valType:\"enumerated\",values:[\"zoom\",\"pan\",\"select\",\"lasso\",\"orbit\",\"turntable\",!1],dflt:\"zoom\",editType:\"modebar\"},hovermode:{valType:\"enumerated\",values:[\"x\",\"y\",\"closest\",!1],editType:\"modebar\"},hoverdistance:{valType:\"integer\",min:-1,dflt:20,editType:\"none\"},spikedistance:{valType:\"integer\",min:-1,dflt:20,editType:\"none\"},hoverlabel:{bgcolor:{valType:\"color\",editType:\"none\"},bordercolor:{valType:\"color\",editType:\"none\"},font:a,align:{valType:\"enumerated\",values:[\"left\",\"right\",\"auto\"],dflt:\"auto\",editType:\"none\"},namelength:{valType:\"integer\",min:-1,dflt:15,editType:\"none\"},editType:\"none\"},selectdirection:{valType:\"enumerated\",values:[\"h\",\"v\",\"d\",\"any\"],dflt:\"any\",editType:\"none\"}}},{\"../../plots/font_attributes\":791,\"./constants\":625}],632:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./layout_attributes\");e.exports=function(t,e,r){function i(r,i){return n.coerce(t,e,a,r,i)}var o,s=i(\"clickmode\");\"select\"===i(\"dragmode\")&&i(\"selectdirection\"),e._has(\"cartesian\")?s.indexOf(\"select\")>-1?o=\"closest\":(e._isHoriz=function(t,e){for(var r=e._scatterStackOpts||{},n=0;n<t.length;n++){var a=t[n],i=a.xaxis+a.yaxis,o=r[i]||{},s=o[a.stackgroup]||{};if(\"h\"!==a.orientation&&\"h\"!==s.orientation)return!1}return!0}(r,e),o=e._isHoriz?\"y\":\"x\"):o=\"closest\",i(\"hovermode\",o)&&(i(\"hoverdistance\"),i(\"spikedistance\"));var l=e._has(\"mapbox\"),c=e._has(\"geo\"),u=e._basePlotModules.length;\"zoom\"===e.dragmode&&((l||c)&&1===u||l&&c&&2===u)&&(e.dragmode=\"pan\")}},{\"../../lib\":717,\"./layout_attributes\":631}],633:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./hoverlabel_defaults\"),i=t(\"./layout_attributes\");e.exports=function(t,e){a(t,e,function(r,a){return n.coerce(t,e,i,r,a)})}},{\"../../lib\":717,\"./hoverlabel_defaults\":629,\"./layout_attributes\":631}],634:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../lib/regex\").counter,i=t(\"../../plots/domain\").attributes,o=t(\"../../plots/cartesian/constants\").idRegex,s=t(\"../../plot_api/plot_template\"),l={rows:{valType:\"integer\",min:1,editType:\"plot\"},roworder:{valType:\"enumerated\",values:[\"top to bottom\",\"bottom to top\"],dflt:\"top to bottom\",editType:\"plot\"},columns:{valType:\"integer\",min:1,editType:\"plot\"},subplots:{valType:\"info_array\",freeLength:!0,dimensions:2,items:{valType:\"enumerated\",values:[a(\"xy\").toString(),\"\"],editType:\"plot\"},editType:\"plot\"},xaxes:{valType:\"info_array\",freeLength:!0,items:{valType:\"enumerated\",values:[o.x.toString(),\"\"],editType:\"plot\"},editType:\"plot\"},yaxes:{valType:\"info_array\",freeLength:!0,items:{valType:\"enumerated\",values:[o.y.toString(),\"\"],editType:\"plot\"},editType:\"plot\"},pattern:{valType:\"enumerated\",values:[\"independent\",\"coupled\"],dflt:\"coupled\",editType:\"plot\"},xgap:{valType:\"number\",min:0,max:1,editType:\"plot\"},ygap:{valType:\"number\",min:0,max:1,editType:\"plot\"},domain:i({name:\"grid\",editType:\"plot\",noGridCell:!0},{}),xside:{valType:\"enumerated\",values:[\"bottom\",\"bottom plot\",\"top plot\",\"top\"],dflt:\"bottom plot\",editType:\"plot\"},yside:{valType:\"enumerated\",values:[\"left\",\"left plot\",\"right plot\",\"right\"],dflt:\"left plot\",editType:\"plot\"},editType:\"plot\"};function c(t,e,r){var n=e[r+\"axes\"],a=Object.keys((t._splomAxes||{})[r]||{});return Array.isArray(n)?n:a.length?a:void 0}function u(t,e,r,n,a,i){var o=e(t+\"gap\",r),s=e(\"domain.\"+t);e(t+\"side\",n);for(var l=new Array(a),c=s[0],u=(s[1]-c)/(a-o),h=u*(1-o),f=0;f<a;f++){var p=c+u*f;l[i?a-1-f:f]=[p,p+h]}return l}function h(t,e,r,n,a){var i,o=new Array(r);function s(t,r){-1!==e.indexOf(r)&&void 0===n[r]?(o[t]=r,n[r]=t):o[t]=\"\"}if(Array.isArray(t))for(i=0;i<r;i++)s(i,t[i]);else for(s(0,a),i=1;i<r;i++)s(i,a+(i+1));return o}e.exports={moduleType:\"component\",name:\"grid\",schema:{layout:{grid:l}},layoutAttributes:l,sizeDefaults:function(t,e){var r=t.grid||{},a=c(e,r,\"x\"),i=c(e,r,\"y\");if(t.grid||a||i){var o,h,f=Array.isArray(r.subplots)&&Array.isArray(r.subplots[0]),p=Array.isArray(a),d=Array.isArray(i),g=p&&a!==r.xaxes&&d&&i!==r.yaxes;f?(o=r.subplots.length,h=r.subplots[0].length):(d&&(o=i.length),p&&(h=a.length));var v=s.newContainer(e,\"grid\"),m=T(\"rows\",o),y=T(\"columns\",h);if(m*y>1){f||p||d||\"independent\"===T(\"pattern\")&&(f=!0),v._hasSubplotGrid=f;var x,b,_=\"top to bottom\"===T(\"roworder\"),w=f?.2:.1,k=f?.3:.1;g&&e._splomGridDflt&&(x=e._splomGridDflt.xside,b=e._splomGridDflt.yside),v._domains={x:u(\"x\",T,w,x,y),y:u(\"y\",T,k,b,m,_)}}else delete e.grid}function T(t,e){return n.coerce(r,v,l,t,e)}},contentDefaults:function(t,e){var r=e.grid;if(r&&r._domains){var n,a,i,o,s,l,u,f=t.grid||{},p=e._subplots,d=r._hasSubplotGrid,g=r.rows,v=r.columns,m=\"independent\"===r.pattern,y=r._axisMap={};if(d){var x=f.subplots||[];l=r.subplots=new Array(g);var b=1;for(n=0;n<g;n++){var _=l[n]=new Array(v),w=x[n]||[];for(a=0;a<v;a++)if(m?(s=1===b?\"xy\":\"x\"+b+\"y\"+b,b++):s=w[a],_[a]=\"\",-1!==p.cartesian.indexOf(s)){if(u=s.indexOf(\"y\"),i=s.slice(0,u),o=s.slice(u),void 0!==y[i]&&y[i]!==a||void 0!==y[o]&&y[o]!==n)continue;_[a]=s,y[i]=a,y[o]=n}}}else{var k=c(e,f,\"x\"),T=c(e,f,\"y\");r.xaxes=h(k,p.xaxis,v,y,\"x\"),r.yaxes=h(T,p.yaxis,g,y,\"y\")}var M=r._anchors={},A=\"top to bottom\"===r.roworder;for(var S in y){var E,L,C,P=S.charAt(0),O=r[P+\"side\"];if(O.length<8)M[S]=\"free\";else if(\"x\"===P){if(\"t\"===O.charAt(0)===A?(E=0,L=1,C=g):(E=g-1,L=-1,C=-1),d){var z=y[S];for(n=E;n!==C;n+=L)if((s=l[n][z])&&(u=s.indexOf(\"y\"),s.slice(0,u)===S)){M[S]=s.slice(u);break}}else for(n=E;n!==C;n+=L)if(o=r.yaxes[n],-1!==p.cartesian.indexOf(S+o)){M[S]=o;break}}else if(\"l\"===O.charAt(0)?(E=0,L=1,C=v):(E=v-1,L=-1,C=-1),d){var I=y[S];for(n=E;n!==C;n+=L)if((s=l[I][n])&&(u=s.indexOf(\"y\"),s.slice(u)===S)){M[S]=s.slice(0,u);break}}else for(n=E;n!==C;n+=L)if(i=r.xaxes[n],-1!==p.cartesian.indexOf(i+S)){M[S]=i;break}}}}}},{\"../../lib\":717,\"../../lib/regex\":733,\"../../plot_api/plot_template\":755,\"../../plots/cartesian/constants\":771,\"../../plots/domain\":790}],635:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/constants\"),a=t(\"../../plot_api/plot_template\").templatedArray;e.exports=a(\"image\",{visible:{valType:\"boolean\",dflt:!0,editType:\"arraydraw\"},source:{valType:\"string\",editType:\"arraydraw\"},layer:{valType:\"enumerated\",values:[\"below\",\"above\"],dflt:\"above\",editType:\"arraydraw\"},sizex:{valType:\"number\",dflt:0,editType:\"arraydraw\"},sizey:{valType:\"number\",dflt:0,editType:\"arraydraw\"},sizing:{valType:\"enumerated\",values:[\"fill\",\"contain\",\"stretch\"],dflt:\"contain\",editType:\"arraydraw\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,editType:\"arraydraw\"},x:{valType:\"any\",dflt:0,editType:\"arraydraw\"},y:{valType:\"any\",dflt:0,editType:\"arraydraw\"},xanchor:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"left\",editType:\"arraydraw\"},yanchor:{valType:\"enumerated\",values:[\"top\",\"middle\",\"bottom\"],dflt:\"top\",editType:\"arraydraw\"},xref:{valType:\"enumerated\",values:[\"paper\",n.idRegex.x.toString()],dflt:\"paper\",editType:\"arraydraw\"},yref:{valType:\"enumerated\",values:[\"paper\",n.idRegex.y.toString()],dflt:\"paper\",editType:\"arraydraw\"},editType:\"arraydraw\"})},{\"../../plot_api/plot_template\":755,\"../../plots/cartesian/constants\":771}],636:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib/to_log_range\");e.exports=function(t,e,r,i){e=e||{};var o=\"log\"===r&&\"linear\"===e.type,s=\"linear\"===r&&\"log\"===e.type;if(o||s)for(var l,c,u=t._fullLayout.images,h=e._id.charAt(0),f=0;f<u.length;f++)if(c=\"images[\"+f+\"].\",(l=u[f])[h+\"ref\"]===e._id){var p=l[h],d=l[\"size\"+h],g=null,v=null;if(o){g=a(p,e.range);var m=d/Math.pow(10,g)/2;v=2*Math.log(m+Math.sqrt(1+m*m))/Math.LN10}else v=(g=Math.pow(10,p))*(Math.pow(10,d/2)-Math.pow(10,-d/2));n(g)?n(v)||(v=null):(g=null,v=null),i(c+h,g),i(c+\"size\"+h,v)}}},{\"../../lib/to_log_range\":743,\"fast-isnumeric\":228}],637:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/cartesian/axes\"),i=t(\"../../plots/array_container_defaults\"),o=t(\"./attributes\");function s(t,e,r){function i(r,a){return n.coerce(t,e,o,r,a)}var s=i(\"source\");if(!i(\"visible\",!!s))return e;i(\"layer\"),i(\"xanchor\"),i(\"yanchor\"),i(\"sizex\"),i(\"sizey\"),i(\"sizing\"),i(\"opacity\");for(var l={_fullLayout:r},c=[\"x\",\"y\"],u=0;u<2;u++){var h=c[u],f=a.coerceRef(t,e,l,h,\"paper\");if(\"paper\"!==f)a.getFromId(l,f)._imgIndices.push(e._index);a.coercePosition(e,l,i,f,h,0)}return e}e.exports=function(t,e){i(t,e,{name:\"images\",handleItemDefaults:s})}},{\"../../lib\":717,\"../../plots/array_container_defaults\":761,\"../../plots/cartesian/axes\":765,\"./attributes\":635}],638:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../drawing\"),i=t(\"../../plots/cartesian/axes\"),o=t(\"../../constants/xmlns_namespaces\");e.exports=function(t){var e,r,s=t._fullLayout,l=[],c={},u=[];for(r=0;r<s.images.length;r++){var h=s.images[r];if(h.visible)if(\"below\"===h.layer&&\"paper\"!==h.xref&&\"paper\"!==h.yref){e=h.xref+h.yref;var f=s._plots[e];if(!f){u.push(h);continue}f.mainplot&&(e=f.mainplot.id),c[e]||(c[e]=[]),c[e].push(h)}else\"above\"===h.layer?l.push(h):u.push(h)}var p={x:{left:{sizing:\"xMin\",offset:0},center:{sizing:\"xMid\",offset:-.5},right:{sizing:\"xMax\",offset:-1}},y:{top:{sizing:\"YMin\",offset:0},middle:{sizing:\"YMid\",offset:-.5},bottom:{sizing:\"YMax\",offset:-1}}};function d(e){var r=n.select(this);if(this._imgSrc!==e.source)if(r.attr(\"xmlns\",o.svg),e.source&&\"data:\"===e.source.slice(0,5))r.attr(\"xlink:href\",e.source),this._imgSrc=e.source;else{var a=new Promise(function(t){var n=new Image;function a(){r.remove(),t()}this.img=n,n.setAttribute(\"crossOrigin\",\"anonymous\"),n.onerror=a,n.onload=function(){var e=document.createElement(\"canvas\");e.width=this.width,e.height=this.height,e.getContext(\"2d\").drawImage(this,0,0);var n=e.toDataURL(\"image/png\");r.attr(\"xlink:href\",n),t()},r.on(\"error\",a),n.src=e.source,this._imgSrc=e.source}.bind(this));t._promises.push(a)}}function g(e){var r=n.select(this),o=i.getFromId(t,e.xref),l=i.getFromId(t,e.yref),c=s._size,u=o?Math.abs(o.l2p(e.sizex)-o.l2p(0)):e.sizex*c.w,h=l?Math.abs(l.l2p(e.sizey)-l.l2p(0)):e.sizey*c.h,f=u*p.x[e.xanchor].offset,d=h*p.y[e.yanchor].offset,g=p.x[e.xanchor].sizing+p.y[e.yanchor].sizing,v=(o?o.r2p(e.x)+o._offset:e.x*c.w+c.l)+f,m=(l?l.r2p(e.y)+l._offset:c.h-e.y*c.h+c.t)+d;switch(e.sizing){case\"fill\":g+=\" slice\";break;case\"stretch\":g=\"none\"}r.attr({x:v,y:m,width:u,height:h,preserveAspectRatio:g,opacity:e.opacity});var y=(o?o._id:\"\")+(l?l._id:\"\");a.setClipUrl(r,y?\"clip\"+s._uid+y:null,t)}var v=s._imageLowerLayer.selectAll(\"image\").data(u),m=s._imageUpperLayer.selectAll(\"image\").data(l);v.enter().append(\"image\"),m.enter().append(\"image\"),v.exit().remove(),m.exit().remove(),v.each(function(t){d.bind(this)(t),g.bind(this)(t)}),m.each(function(t){d.bind(this)(t),g.bind(this)(t)});var y=Object.keys(s._plots);for(r=0;r<y.length;r++){e=y[r];var x=s._plots[e];if(x.imagelayer){var b=x.imagelayer.selectAll(\"image\").data(c[e]||[]);b.enter().append(\"image\"),b.exit().remove(),b.each(function(t){d.bind(this)(t),g.bind(this)(t)})}}}},{\"../../constants/xmlns_namespaces\":694,\"../../plots/cartesian/axes\":765,\"../drawing\":613,d3:165}],639:[function(t,e,r){\"use strict\";e.exports={moduleType:\"component\",name:\"images\",layoutAttributes:t(\"./attributes\"),supplyLayoutDefaults:t(\"./defaults\"),includeBasePlot:t(\"../../plots/cartesian/include_components\")(\"images\"),draw:t(\"./draw\"),convertCoords:t(\"./convert_coords\")}},{\"../../plots/cartesian/include_components\":775,\"./attributes\":635,\"./convert_coords\":636,\"./defaults\":637,\"./draw\":638}],640:[function(t,e,r){\"use strict\";var n=t(\"../../plots/font_attributes\"),a=t(\"../color/attributes\");e.exports={bgcolor:{valType:\"color\",editType:\"legend\"},bordercolor:{valType:\"color\",dflt:a.defaultLine,editType:\"legend\"},borderwidth:{valType:\"number\",min:0,dflt:0,editType:\"legend\"},font:n({editType:\"legend\"}),orientation:{valType:\"enumerated\",values:[\"v\",\"h\"],dflt:\"v\",editType:\"legend\"},traceorder:{valType:\"flaglist\",flags:[\"reversed\",\"grouped\"],extras:[\"normal\"],editType:\"legend\"},tracegroupgap:{valType:\"number\",min:0,dflt:10,editType:\"legend\"},itemsizing:{valType:\"enumerated\",values:[\"trace\",\"constant\"],dflt:\"trace\",editType:\"legend\"},itemclick:{valType:\"enumerated\",values:[\"toggle\",\"toggleothers\",!1],dflt:\"toggle\",editType:\"legend\"},itemdoubleclick:{valType:\"enumerated\",values:[\"toggle\",\"toggleothers\",!1],dflt:\"toggleothers\",editType:\"legend\"},x:{valType:\"number\",min:-2,max:3,editType:\"legend\"},xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\",editType:\"legend\"},y:{valType:\"number\",min:-2,max:3,editType:\"legend\"},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],editType:\"legend\"},uirevision:{valType:\"any\",editType:\"none\"},valign:{valType:\"enumerated\",values:[\"top\",\"middle\",\"bottom\"],dflt:\"middle\",editType:\"legend\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"legend\"},font:n({editType:\"legend\"}),side:{valType:\"enumerated\",values:[\"top\",\"left\",\"top left\"],editType:\"legend\"},editType:\"legend\"},editType:\"legend\"}},{\"../../plots/font_attributes\":791,\"../color/attributes\":591}],641:[function(t,e,r){\"use strict\";e.exports={scrollBarWidth:6,scrollBarMinHeight:20,scrollBarColor:\"#808BA4\",scrollBarMargin:4,scrollBarEnterAttrs:{rx:20,ry:3,width:0,height:0},titlePad:2,textGap:40,itemGap:5}},{}],642:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../lib\"),i=t(\"../../plot_api/plot_template\"),o=t(\"./attributes\"),s=t(\"../../plots/layout_attributes\"),l=t(\"./helpers\");e.exports=function(t,e,r){for(var c=t.legend||{},u=0,h=!1,f=\"normal\",p=0;p<r.length;p++){var d=r[p];d.visible&&((d.showlegend||d._dfltShowLegend&&!(d._module&&d._module.attributes&&d._module.attributes.showlegend&&!1===d._module.attributes.showlegend.dflt))&&(u++,d.showlegend&&(h=!0,(n.traceIs(d,\"pie-like\")||!0===d._input.showlegend)&&u++)),(n.traceIs(d,\"bar\")&&\"stack\"===e.barmode||-1!==[\"tonextx\",\"tonexty\"].indexOf(d.fill))&&(f=l.isGrouped({traceorder:f})?\"grouped+reversed\":\"reversed\"),void 0!==d.legendgroup&&\"\"!==d.legendgroup&&(f=l.isReversed({traceorder:f})?\"reversed+grouped\":\"grouped\"))}var g=a.coerce(t,e,s,\"showlegend\",h&&u>1);if(!1!==g||c.uirevision){var v=i.newContainer(e,\"legend\");if(_(\"uirevision\",e.uirevision),!1!==g){_(\"bgcolor\",e.paper_bgcolor),_(\"bordercolor\"),_(\"borderwidth\"),a.coerceFont(_,\"font\",e.font);var m,y,x,b=_(\"orientation\");\"h\"===b?(m=0,n.getComponentMethod(\"rangeslider\",\"isVisible\")(t.xaxis)?(y=1.1,x=\"bottom\"):(y=-.1,x=\"top\")):(m=1.02,y=1,x=\"auto\"),_(\"traceorder\",f),l.isGrouped(e.legend)&&_(\"tracegroupgap\"),_(\"itemsizing\"),_(\"itemclick\"),_(\"itemdoubleclick\"),_(\"x\",m),_(\"xanchor\"),_(\"y\",y),_(\"yanchor\",x),_(\"valign\"),a.noneOrAll(c,v,[\"x\",\"y\"]),_(\"title.text\")&&(_(\"title.side\",\"h\"===b?\"left\":\"top\"),a.coerceFont(_,\"title.font\",e.font))}}function _(t,e){return a.coerce(c,v,o,t,e)}}},{\"../../lib\":717,\"../../plot_api/plot_template\":755,\"../../plots/layout_attributes\":817,\"../../registry\":846,\"./attributes\":640,\"./helpers\":646}],643:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\"),i=t(\"../../plots/plots\"),o=t(\"../../registry\"),s=t(\"../../lib/events\"),l=t(\"../dragelement\"),c=t(\"../drawing\"),u=t(\"../color\"),h=t(\"../../lib/svg_text_utils\"),f=t(\"./handle_click\"),p=t(\"./constants\"),d=t(\"../../constants/alignment\"),g=d.LINE_SPACING,v=d.FROM_TL,m=d.FROM_BR,y=t(\"./get_legend_data\"),x=t(\"./style\"),b=t(\"./helpers\");function _(t,e,r,n,a){var i=r.data()[0][0].trace,l={event:a,node:r.node(),curveNumber:i.index,expandedIndex:i._expandedIndex,data:t.data,layout:t.layout,frames:t._transitionData._frames,config:t._context,fullData:t._fullData,fullLayout:t._fullLayout};if(i._group&&(l.group=i._group),o.traceIs(i,\"pie-like\")&&(l.label=r.datum()[0].label),!1!==s.triggerHandler(t,\"plotly_legendclick\",l))if(1===n)e._clickTimeout=setTimeout(function(){f(r,t,n)},t._context.doubleClickDelay);else if(2===n){e._clickTimeout&&clearTimeout(e._clickTimeout),t._legendMouseDownTime=0,!1!==s.triggerHandler(t,\"plotly_legenddoubleclick\",l)&&f(r,t,n)}}function w(t,e){var r=t.data()[0][0],n=e._fullLayout.legend,i=r.trace,s=o.traceIs(i,\"pie-like\"),l=i.index,u=e._context.edits.legendText&&!s,f=n._maxNameLength,d=s?r.label:i.name;i._meta&&(d=a.templateString(d,i._meta));var g=a.ensureSingle(t,\"text\",\"legendtext\");g.attr(\"text-anchor\",\"start\").classed(\"user-select-none\",!0).call(c.font,n.font).text(u?k(d,f):d),h.positionText(g,p.textGap,0),u?g.call(h.makeEditable,{gd:e,text:d}).call(M,t,e).on(\"edit\",function(n){this.text(k(n,f)).call(M,t,e);var i=r.trace._fullInput||{},s={};if(o.hasTransform(i,\"groupby\")){var c=o.getTransformIndices(i,\"groupby\"),u=c[c.length-1],h=a.keyedContainer(i,\"transforms[\"+u+\"].styles\",\"target\",\"value.name\");h.set(r.trace._group,n),s=h.constructUpdate()}else s.name=n;return o.call(\"_guiRestyle\",e,s,l)}):M(g,t,e)}function k(t,e){var r=Math.max(4,e);if(t&&t.trim().length>=r/2)return t;for(var n=r-(t=t||\"\").length;n>0;n--)t+=\" \";return t}function T(t,e){var r,i=e._context.doubleClickDelay,o=1,s=a.ensureSingle(t,\"rect\",\"legendtoggle\",function(t){t.style(\"cursor\",\"pointer\").attr(\"pointer-events\",\"all\").call(u.fill,\"rgba(0,0,0,0)\")});s.on(\"mousedown\",function(){(r=(new Date).getTime())-e._legendMouseDownTime<i?o+=1:(o=1,e._legendMouseDownTime=r)}),s.on(\"mouseup\",function(){if(!e._dragged&&!e._editing){var r=e._fullLayout.legend;(new Date).getTime()-e._legendMouseDownTime>i&&(o=Math.max(o-1,1)),_(e,r,t,o,n.event)}})}function M(t,e,r){h.convertToTspans(t,r,function(){!function(t,e){var r=t.data()[0][0];if(r&&!r.trace.showlegend)return void t.remove();var n,a,i=t.select(\"g[class*=math-group]\"),o=i.node(),s=e._fullLayout.legend.borderwidth,l=e._fullLayout.legend,u=(r?l:l.title).font.size*g;if(o){var f=c.bBox(o);n=f.height,a=f.width,r?c.setTranslate(i,0,.25*n):c.setTranslate(i,s,.75*n+s)}else{var d=t.select(r?\".legendtext\":\".legendtitletext\"),v=h.lineCount(d),m=d.node();n=u*v,a=m?c.bBox(m).width:0;var y=u*((v-1)/2-.3);r?h.positionText(d,p.textGap,-y):h.positionText(d,p.titlePad+s,u+s)}r?(r.lineHeight=u,r.height=Math.max(n,16)+3,r.width=a):(l._titleWidth=a,l._titleHeight=n)}(e,r)})}function A(t){return a.isRightAnchor(t)?\"right\":a.isCenterAnchor(t)?\"center\":\"left\"}function S(t){return a.isBottomAnchor(t)?\"bottom\":a.isMiddleAnchor(t)?\"middle\":\"top\"}e.exports=function(t){var e=t._fullLayout,r=\"legend\"+e._uid;if(e._infolayer&&t.calcdata){t._legendMouseDownTime||(t._legendMouseDownTime=0);var s=e.legend,h=e.showlegend&&y(t.calcdata,s),f=e.hiddenlabels||[];if(!e.showlegend||!h.length)return e._infolayer.selectAll(\".legend\").remove(),e._topdefs.select(\"#\"+r).remove(),i.autoMargin(t,\"legend\");var d=a.ensureSingle(e._infolayer,\"g\",\"legend\",function(t){t.attr(\"pointer-events\",\"all\")}),g=a.ensureSingleById(e._topdefs,\"clipPath\",r,function(t){t.append(\"rect\")}),k=a.ensureSingle(d,\"rect\",\"bg\",function(t){t.attr(\"shape-rendering\",\"crispEdges\")});k.call(u.stroke,s.bordercolor).call(u.fill,s.bgcolor).style(\"stroke-width\",s.borderwidth+\"px\");var E=a.ensureSingle(d,\"g\",\"scrollbox\"),L=s.title;if(s._titleWidth=0,s._titleHeight=0,L.text){var C=a.ensureSingle(E,\"text\",\"legendtitletext\");C.attr(\"text-anchor\",\"start\").classed(\"user-select-none\",!0).call(c.font,L.font).text(L.text),M(C,E,t)}var P=a.ensureSingle(d,\"rect\",\"scrollbar\",function(t){t.attr(p.scrollBarEnterAttrs).call(u.fill,p.scrollBarColor)}),O=E.selectAll(\"g.groups\").data(h);O.enter().append(\"g\").attr(\"class\",\"groups\"),O.exit().remove();var z=O.selectAll(\"g.traces\").data(a.identity);z.enter().append(\"g\").attr(\"class\",\"traces\"),z.exit().remove(),z.style(\"opacity\",function(t){var e=t[0].trace;return o.traceIs(e,\"pie-like\")?-1!==f.indexOf(t[0].label)?.5:1:\"legendonly\"===e.visible?.5:1}).each(function(){n.select(this).call(w,t)}).call(x,t).each(function(){n.select(this).call(T,t)}),a.syncOrAsync([i.previousPromises,function(){return function(t,e,r){var a=t._fullLayout,i=a.legend,o=a._size,s=b.isVertical(i),l=b.isGrouped(i),u=i.borderwidth,h=2*u,f=p.textGap,d=p.itemGap,g=2*(u+d),v=S(i),m=i.y<0||0===i.y&&\"top\"===v,y=i.y>1||1===i.y&&\"bottom\"===v;i._maxHeight=Math.max(m||y?a.height/2:o.h,30);var x=0;i._width=0,i._height=0;var _=function(t){var e=0,r=0,n=t.title.side;n&&(-1!==n.indexOf(\"left\")&&(e=t._titleWidth),-1!==n.indexOf(\"top\")&&(r=t._titleHeight));return[e,r]}(i);if(s)r.each(function(t){var e=t[0].height;c.setTranslate(this,u+_[0],u+_[1]+i._height+e/2+d),i._height+=e,i._width=Math.max(i._width,t[0].width)}),x=f+i._width,i._width+=d+f+h,i._height+=g,l&&(e.each(function(t,e){c.setTranslate(this,0,e*i.tracegroupgap)}),i._height+=(i._lgroupsLength-1)*i.tracegroupgap);else{var w=A(i),k=i.x<0||0===i.x&&\"right\"===w,T=i.x>1||1===i.x&&\"left\"===w,M=y||m,E=a.width/2;i._maxWidth=Math.max(k?M&&\"left\"===w?o.l+o.w:E:T?M&&\"right\"===w?o.r+o.w:E:o.w,2*f);var L=0,C=0;r.each(function(t){var e=t[0].width+f;L=Math.max(L,e),C+=e}),x=null;var P=0;if(l){var O=0,z=0,I=0;e.each(function(){var t=0,e=0;n.select(this).selectAll(\"g.traces\").each(function(r){var n=r[0].height;c.setTranslate(this,_[0],_[1]+u+d+n/2+e),e+=n,t=Math.max(t,f+r[0].width)}),O=Math.max(O,e);var r=t+d;r+u+z>i._maxWidth&&(P=Math.max(P,z),z=0,I+=O+i.tracegroupgap,O=e),c.setTranslate(this,z,I),z+=r}),i._width=Math.max(P,z)+u,i._height=I+O+g}else{var D=r.size(),R=C+h+(D-1)*d<i._maxWidth,F=0,B=0,N=0,j=0;r.each(function(t){var e=t[0].height,r=f+t[0].width,n=(R?r:L)+d;n+u+B>i._maxWidth&&(P=Math.max(P,j),B=0,N+=F,i._height+=F,F=0),c.setTranslate(this,_[0]+u+B,_[1]+u+N+e/2+d),j=B+r+d,B+=n,F=Math.max(F,e)}),R?(i._width=B+h,i._height=F+g):(i._width=Math.max(P,j)+h,i._height+=F+g)}}i._width=Math.ceil(Math.max(i._width+_[0],i._titleWidth+2*(u+p.titlePad))),i._height=Math.ceil(Math.max(i._height+_[1],i._titleHeight+2*(u+p.itemGap))),i._effHeight=Math.min(i._height,i._maxHeight);var V=t._context.edits,U=V.legendText||V.legendPosition;r.each(function(t){var e=n.select(this).select(\".legendtoggle\"),r=t[0].height,a=U?f:x||f+t[0].width;s||(a+=d/2),c.setRect(e,0,-r/2,a,r)})}(t,O,z)},function(){if(!function(t){var e=t._fullLayout.legend,r=A(e),n=S(e);return i.autoMargin(t,\"legend\",{x:e.x,y:e.y,l:e._width*v[r],r:e._width*m[r],b:e._effHeight*m[n],t:e._effHeight*v[n]})}(t)){var u,h,f,y,x=e._size,b=s.borderwidth,w=x.l+x.w*s.x-v[A(s)]*s._width,T=x.t+x.h*(1-s.y)-v[S(s)]*s._effHeight;if(e.margin.autoexpand){var M=w,L=T;w=a.constrain(w,0,e.width-s._width),T=a.constrain(T,0,e.height-s._effHeight),w!==M&&a.log(\"Constrain legend.x to make legend fit inside graph\"),T!==L&&a.log(\"Constrain legend.y to make legend fit inside graph\")}if(c.setTranslate(d,w,T),P.on(\".drag\",null),d.on(\"wheel\",null),s._height<=s._maxHeight||t._context.staticPlot)k.attr({width:s._width-b,height:s._effHeight-b,x:b/2,y:b/2}),c.setTranslate(E,0,0),g.select(\"rect\").attr({width:s._width-2*b,height:s._effHeight-2*b,x:b,y:b}),c.setClipUrl(E,r,t),c.setRect(P,0,0,0,0),delete s._scrollY;else{var C,O,z,I=Math.max(p.scrollBarMinHeight,s._effHeight*s._effHeight/s._height),D=s._effHeight-I-2*p.scrollBarMargin,R=s._height-s._effHeight,F=D/R,B=Math.min(s._scrollY||0,R);k.attr({width:s._width-2*b+p.scrollBarWidth+p.scrollBarMargin,height:s._effHeight-b,x:b/2,y:b/2}),g.select(\"rect\").attr({width:s._width-2*b+p.scrollBarWidth+p.scrollBarMargin,height:s._effHeight-2*b,x:b,y:b+B}),c.setClipUrl(E,r,t),V(B,I,F),d.on(\"wheel\",function(){V(B=a.constrain(s._scrollY+n.event.deltaY/D*R,0,R),I,F),0!==B&&B!==R&&n.event.preventDefault()});var N=n.behavior.drag().on(\"dragstart\",function(){var t=n.event.sourceEvent;C=\"touchstart\"===t.type?t.changedTouches[0].clientY:t.clientY,z=B}).on(\"drag\",function(){var t=n.event.sourceEvent;2===t.buttons||t.ctrlKey||(O=\"touchmove\"===t.type?t.changedTouches[0].clientY:t.clientY,V(B=function(t,e,r){var n=(r-e)/F+t;return a.constrain(n,0,R)}(z,C,O),I,F))});P.call(N);var j=n.behavior.drag().on(\"dragstart\",function(){var t=n.event.sourceEvent;\"touchstart\"===t.type&&(C=t.changedTouches[0].clientY,z=B)}).on(\"drag\",function(){var t=n.event.sourceEvent;\"touchmove\"===t.type&&(O=t.changedTouches[0].clientY,V(B=function(t,e,r){var n=(e-r)/F+t;return a.constrain(n,0,R)}(z,C,O),I,F))});E.call(j)}if(t._context.edits.legendPosition)d.classed(\"cursor-move\",!0),l.init({element:d.node(),gd:t,prepFn:function(){var t=c.getTranslate(d);f=t.x,y=t.y},moveFn:function(t,e){var r=f+t,n=y+e;c.setTranslate(d,r,n),u=l.align(r,0,x.l,x.l+x.w,s.xanchor),h=l.align(n,0,x.t+x.h,x.t,s.yanchor)},doneFn:function(){void 0!==u&&void 0!==h&&o.call(\"_guiRelayout\",t,{\"legend.x\":u,\"legend.y\":h})},clickFn:function(r,n){var a=e._infolayer.selectAll(\"g.traces\").filter(function(){var t=this.getBoundingClientRect();return n.clientX>=t.left&&n.clientX<=t.right&&n.clientY>=t.top&&n.clientY<=t.bottom});a.size()>0&&_(t,d,a,r,n)}})}function V(e,r,n){s._scrollY=t._fullLayout.legend._scrollY=e,c.setTranslate(E,0,-e),c.setRect(P,s._width,p.scrollBarMargin+e*n,p.scrollBarWidth,r),g.select(\"rect\").attr(\"y\",b+e)}}],t)}}},{\"../../constants/alignment\":686,\"../../lib\":717,\"../../lib/events\":707,\"../../lib/svg_text_utils\":741,\"../../plots/plots\":826,\"../../registry\":846,\"../color\":592,\"../dragelement\":610,\"../drawing\":613,\"./constants\":641,\"./get_legend_data\":644,\"./handle_click\":645,\"./helpers\":646,\"./style\":648,d3:165}],644:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"./helpers\");e.exports=function(t,e){var r,i,o={},s=[],l=!1,c={},u=0,h=0;function f(t,r){if(\"\"!==t&&a.isGrouped(e))-1===s.indexOf(t)?(s.push(t),l=!0,o[t]=[[r]]):o[t].push([r]);else{var n=\"~~i\"+u;s.push(n),o[n]=[[r]],u++}}for(r=0;r<t.length;r++){var p=t[r],d=p[0],g=d.trace,v=g.legendgroup;if(g.visible&&g.showlegend)if(n.traceIs(g,\"pie-like\"))for(c[v]||(c[v]={}),i=0;i<p.length;i++){var m=p[i].label;c[v][m]||(f(v,{label:m,color:p[i].color,i:p[i].i,trace:g,pts:p[i].pts}),c[v][m]=!0,h=Math.max(h,(m||\"\").length))}else f(v,d),h=Math.max(h,(g.name||\"\").length)}if(!s.length)return[];var y,x,b=s.length;if(l&&a.isGrouped(e))for(x=new Array(b),r=0;r<b;r++)y=o[s[r]],x[r]=a.isReversed(e)?y.reverse():y;else{for(x=[new Array(b)],r=0;r<b;r++)y=o[s[r]][0],x[0][a.isReversed(e)?b-r-1:r]=y;b=1}return e._lgroupsLength=b,e._maxNameLength=h,x}},{\"../../registry\":846,\"./helpers\":646}],645:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../registry\"),i=!0;e.exports=function(t,e,r){var o=e._fullLayout;if(!e._dragged&&!e._editing){var s,l=o.legend.itemclick,c=o.legend.itemdoubleclick;if(1===r&&\"toggle\"===l&&\"toggleothers\"===c&&i&&e.data&&e._context.showTips?(n.notifier(n._(e,\"Double-click on legend to isolate one trace\"),\"long\"),i=!1):i=!1,1===r?s=l:2===r&&(s=c),s){var u,h,f,p,d,g=o.hiddenlabels?o.hiddenlabels.slice():[],v=t.data()[0][0],m=e._fullData,y=v.trace,x=y.legendgroup,b={},_=[],w=[],k=[];if(a.traceIs(y,\"pie-like\")){var T=v.label,M=g.indexOf(T);\"toggle\"===s?-1===M?g.push(T):g.splice(M,1):\"toggleothers\"===s&&(g=[],e.calcdata[0].forEach(function(t){T!==t.label&&g.push(t.label)}),e._fullLayout.hiddenlabels&&e._fullLayout.hiddenlabels.length===g.length&&-1===M&&(g=[])),a.call(\"_guiRelayout\",e,\"hiddenlabels\",g)}else{var A,S=x&&x.length,E=[];if(S)for(u=0;u<m.length;u++)(A=m[u]).visible&&A.legendgroup===x&&E.push(u);if(\"toggle\"===s){var L;switch(y.visible){case!0:L=\"legendonly\";break;case!1:L=!1;break;case\"legendonly\":L=!0}if(S)for(u=0;u<m.length;u++)!1!==m[u].visible&&m[u].legendgroup===x&&B(m[u],L);else B(y,L)}else if(\"toggleothers\"===s){var C,P,O,z,I=!0;for(u=0;u<m.length;u++)if(C=m[u]===y,O=!0!==m[u].showlegend,!(C||O||(P=S&&m[u].legendgroup===x)||!0!==m[u].visible||a.traceIs(m[u],\"notLegendIsolatable\"))){I=!1;break}for(u=0;u<m.length;u++)if(!1!==m[u].visible&&!a.traceIs(m[u],\"notLegendIsolatable\"))switch(y.visible){case\"legendonly\":B(m[u],!0);break;case!0:z=!!I||\"legendonly\",C=m[u]===y,O=!0!==m[u].showlegend&&!m[u].legendgroup,P=C||S&&m[u].legendgroup===x,B(m[u],!(!P&&!O)||z)}}for(u=0;u<w.length;u++)if(f=w[u]){var D=f.constructUpdate(),R=Object.keys(D);for(h=0;h<R.length;h++)p=R[h],(b[p]=b[p]||[])[k[u]]=D[p]}for(d=Object.keys(b),u=0;u<d.length;u++)for(p=d[u],h=0;h<_.length;h++)b[p].hasOwnProperty(h)||(b[p][h]=void 0);a.call(\"_guiRestyle\",e,b,_)}}}function F(t,e,r){var n=_.indexOf(t),a=b[e];return a||(a=b[e]=[]),-1===_.indexOf(t)&&(_.push(t),n=_.length-1),a[n]=r,n}function B(t,e){var r=t._fullInput;if(a.hasTransform(r,\"groupby\")){var i=w[r.index];if(!i){var o=a.getTransformIndices(r,\"groupby\"),s=o[o.length-1];i=n.keyedContainer(r,\"transforms[\"+s+\"].styles\",\"target\",\"value.visible\"),w[r.index]=i}var l=i.get(t._group);void 0===l&&(l=!0),!1!==l&&i.set(t._group,e),k[r.index]=F(r.index,\"visible\",!1!==r.visible)}else{var c=!1!==r.visible&&e;F(r.index,\"visible\",c)}}}},{\"../../lib\":717,\"../../registry\":846}],646:[function(t,e,r){\"use strict\";r.isGrouped=function(t){return-1!==(t.traceorder||\"\").indexOf(\"grouped\")},r.isVertical=function(t){return\"h\"!==t.orientation},r.isReversed=function(t){return-1!==(t.traceorder||\"\").indexOf(\"reversed\")}},{}],647:[function(t,e,r){\"use strict\";e.exports={moduleType:\"component\",name:\"legend\",layoutAttributes:t(\"./attributes\"),supplyLayoutDefaults:t(\"./defaults\"),draw:t(\"./draw\"),style:t(\"./style\")}},{\"./attributes\":640,\"./defaults\":642,\"./draw\":643,\"./style\":648}],648:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../registry\"),i=t(\"../../lib\"),o=t(\"../drawing\"),s=t(\"../color\"),l=t(\"../colorscale/helpers\").extractOpts,c=t(\"../../traces/scatter/subtypes\"),u=t(\"../../traces/pie/style_one\"),h=t(\"../../traces/pie/helpers\").castOption,f=12,p=5,d=2,g=10,v=5;function m(t,e){return(e?\"radial\":\"horizontal\")+(t?\"\":\"reversed\")}e.exports=function(t,e){var r=e._fullLayout.legend,y=\"constant\"===r.itemsizing,x=function(t,e,r,n){var a;if(t+1)a=t;else{if(!(e&&e.width>0))return 0;a=e.width}return y?n:Math.min(a,r)};function b(t,e,r){var i=t[0].trace,o=i.marker||{},l=o.line||{},c=r?i.visible&&i.type===r:a.traceIs(i,\"bar\"),u=n.select(e).select(\"g.legendpoints\").selectAll(\"path.legend\"+r).data(c?[t]:[]);u.enter().append(\"path\").classed(\"legend\"+r,!0).attr(\"d\",\"M6,6H-6V-6H6Z\").attr(\"transform\",\"translate(20,0)\"),u.exit().remove(),u.each(function(t){var e=n.select(this),r=t[0],a=x(r.mlw,o.line,v,d);e.style(\"stroke-width\",a+\"px\").call(s.fill,r.mc||o.color),a&&s.stroke(e,r.mlc||l.color)})}function _(t,e,r){var o=t[0],s=o.trace,l=r?s.visible&&s.type===r:a.traceIs(s,r),c=n.select(e).select(\"g.legendpoints\").selectAll(\"path.legend\"+r).data(l?[t]:[]);if(c.enter().append(\"path\").classed(\"legend\"+r,!0).attr(\"d\",\"M6,6H-6V-6H6Z\").attr(\"transform\",\"translate(20,0)\"),c.exit().remove(),c.size()){var f=(s.marker||{}).line,p=x(h(f.width,o.pts),f,v,d),g=i.minExtend(s,{marker:{line:{width:p}}});g.marker.line.color=f.color;var m=i.minExtend(o,{trace:g});u(c,m,g)}}t.each(function(t){var e=n.select(this),a=i.ensureSingle(e,\"g\",\"layers\");a.style(\"opacity\",t[0].trace.opacity);var o=r.valign,s=t[0].lineHeight,l=t[0].height;if(\"middle\"!==o&&s&&l){var c={top:1,bottom:-1}[o]*(.5*(s-l+3));a.attr(\"transform\",\"translate(0,\"+c+\")\")}else a.attr(\"transform\",null);a.selectAll(\"g.legendfill\").data([t]).enter().append(\"g\").classed(\"legendfill\",!0),a.selectAll(\"g.legendlines\").data([t]).enter().append(\"g\").classed(\"legendlines\",!0);var u=a.selectAll(\"g.legendsymbols\").data([t]);u.enter().append(\"g\").classed(\"legendsymbols\",!0),u.selectAll(\"g.legendpoints\").data([t]).enter().append(\"g\").classed(\"legendpoints\",!0)}).each(function(t){var r,a=t[0].trace,c=[];if(a.visible)switch(a.type){case\"histogram2d\":case\"heatmap\":c=[[\"M-15,-2V4H15V-2Z\"]],r=!0;break;case\"choropleth\":case\"choroplethmapbox\":c=[[\"M-6,-6V6H6V-6Z\"]],r=!0;break;case\"densitymapbox\":c=[[\"M-6,0 a6,6 0 1,0 12,0 a 6,6 0 1,0 -12,0\"]],r=\"radial\";break;case\"cone\":c=[[\"M-6,2 A2,2 0 0,0 -6,6 V6L6,4Z\"],[\"M-6,-6 A2,2 0 0,0 -6,-2 L6,-4Z\"],[\"M-6,-2 A2,2 0 0,0 -6,2 L6,0Z\"]],r=!1;break;case\"streamtube\":c=[[\"M-6,2 A2,2 0 0,0 -6,6 H6 A2,2 0 0,1 6,2 Z\"],[\"M-6,-6 A2,2 0 0,0 -6,-2 H6 A2,2 0 0,1 6,-6 Z\"],[\"M-6,-2 A2,2 0 0,0 -6,2 H6 A2,2 0 0,1 6,-2 Z\"]],r=!1;break;case\"surface\":c=[[\"M-6,-6 A2,3 0 0,0 -6,0 H6 A2,3 0 0,1 6,-6 Z\"],[\"M-6,1 A2,3 0 0,1 -6,6 H6 A2,3 0 0,0 6,0 Z\"]],r=!0;break;case\"mesh3d\":c=[[\"M-6,6H0L-6,-6Z\"],[\"M6,6H0L6,-6Z\"],[\"M-6,-6H6L0,6Z\"]],r=!1;break;case\"volume\":c=[[\"M-6,6H0L-6,-6Z\"],[\"M6,6H0L6,-6Z\"],[\"M-6,-6H6L0,6Z\"]],r=!0;break;case\"isosurface\":c=[[\"M-6,6H0L-6,-6Z\"],[\"M6,6H0L6,-6Z\"],[\"M-6,-6 A12,24 0 0,0 6,-6 L0,6Z\"]],r=!1}var u=n.select(this).select(\"g.legendpoints\").selectAll(\"path.legend3dandfriends\").data(c);u.enter().append(\"path\").classed(\"legend3dandfriends\",!0).attr(\"transform\",\"translate(20,0)\").style(\"stroke-miterlimit\",1),u.exit().remove(),u.each(function(t,c){var u,h=n.select(this),f=l(a),p=f.colorscale,d=f.reversescale;if(p){if(!r){var g=p.length;u=0===c?p[d?g-1:0][1]:1===c?p[d?0:g-1][1]:p[Math.floor((g-1)/2)][1]}}else{var v=a.vertexcolor||a.facecolor||a.color;u=i.isArrayOrTypedArray(v)?v[c]||v[0]:v}h.attr(\"d\",t[0]),u?h.call(s.fill,u):h.call(function(t){if(t.size()){var n=\"legendfill-\"+a.uid;o.gradient(t,e,n,m(d,\"radial\"===r),p,\"fill\")}})})}).each(function(t){var e=t[0].trace,r=[];e.visible&&\"waterfall\"===e.type&&(r=t[0].hasTotals?[[\"increasing\",\"M-6,-6V6H0Z\"],[\"totals\",\"M6,6H0L-6,-6H-0Z\"],[\"decreasing\",\"M6,6V-6H0Z\"]]:[[\"increasing\",\"M-6,-6V6H6Z\"],[\"decreasing\",\"M6,6V-6H-6Z\"]]);var a=n.select(this).select(\"g.legendpoints\").selectAll(\"path.legendwaterfall\").data(r);a.enter().append(\"path\").classed(\"legendwaterfall\",!0).attr(\"transform\",\"translate(20,0)\").style(\"stroke-miterlimit\",1),a.exit().remove(),a.each(function(t){var r=n.select(this),a=e[t[0]].marker,i=x(void 0,a.line,v,d);r.attr(\"d\",t[1]).style(\"stroke-width\",i+\"px\").call(s.fill,a.color),i&&r.call(s.stroke,a.line.color)})}).each(function(t){b(t,this,\"funnel\")}).each(function(t){b(t,this)}).each(function(t){var r=t[0].trace,l=n.select(this).select(\"g.legendpoints\").selectAll(\"path.legendbox\").data(r.visible&&a.traceIs(r,\"box-violin\")?[t]:[]);l.enter().append(\"path\").classed(\"legendbox\",!0).attr(\"d\",\"M6,6H-6V-6H6Z\").attr(\"transform\",\"translate(20,0)\"),l.exit().remove(),l.each(function(){var t=n.select(this);if(\"all\"!==r.boxpoints&&\"all\"!==r.points||0!==s.opacity(r.fillcolor)||0!==s.opacity((r.line||{}).color)){var a=x(void 0,r.line,v,d);t.style(\"stroke-width\",a+\"px\").call(s.fill,r.fillcolor),a&&s.stroke(t,r.line.color)}else{var c=i.minExtend(r,{marker:{size:y?f:i.constrain(r.marker.size,2,16),sizeref:1,sizemin:1,sizemode:\"diameter\"}});l.call(o.pointStyle,c,e)}})}).each(function(t){_(t,this,\"funnelarea\")}).each(function(t){_(t,this,\"pie\")}).each(function(t){var r,a,s=t[0],u=s.trace,h=u.visible&&u.fill&&\"none\"!==u.fill,f=c.hasLines(u),d=u.contours,v=!1,y=!1,b=l(u),_=b.colorscale,w=b.reversescale;if(d){var k=d.coloring;\"lines\"===k?v=!0:f=\"none\"===k||\"heatmap\"===k||d.showlines,\"constraint\"===d.type?h=\"=\"!==d._operation:\"fill\"!==k&&\"heatmap\"!==k||(y=!0)}var T=c.hasMarkers(u)||c.hasText(u),M=h||y,A=f||v,S=T||!M?\"M5,0\":A?\"M5,-2\":\"M5,-3\",E=n.select(this),L=E.select(\".legendfill\").selectAll(\"path\").data(h||y?[t]:[]);if(L.enter().append(\"path\").classed(\"js-fill\",!0),L.exit().remove(),L.attr(\"d\",S+\"h30v6h-30z\").call(h?o.fillGroupStyle:function(t){if(t.size()){var r=\"legendfill-\"+u.uid;o.gradient(t,e,r,m(w),_,\"fill\")}}),f||v){var C=x(void 0,u.line,g,p);a=i.minExtend(u,{line:{width:C}}),r=[i.minExtend(s,{trace:a})]}var P=E.select(\".legendlines\").selectAll(\"path\").data(f||v?[r]:[]);P.enter().append(\"path\").classed(\"js-line\",!0),P.exit().remove(),P.attr(\"d\",S+(v?\"l30,0.0001\":\"h30\")).call(f?o.lineGroupStyle:function(t){if(t.size()){var r=\"legendline-\"+u.uid;o.lineGroupStyle(t),o.gradient(t,e,r,m(w),_,\"stroke\")}})}).each(function(t){var r,a,s=t[0],l=s.trace,u=c.hasMarkers(l),h=c.hasText(l),g=c.hasLines(l);function v(t,e,r,n){var a=i.nestedProperty(l,t).get(),o=i.isArrayOrTypedArray(a)&&e?e(a):a;if(y&&o&&void 0!==n&&(o=n),r){if(o<r[0])return r[0];if(o>r[1])return r[1]}return o}function m(t){return t[0]}if(u||h||g){var x={},b={};if(u){x.mc=v(\"marker.color\",m),x.mx=v(\"marker.symbol\",m),x.mo=v(\"marker.opacity\",i.mean,[.2,1]),x.mlc=v(\"marker.line.color\",m),x.mlw=v(\"marker.line.width\",i.mean,[0,5],d),b.marker={sizeref:1,sizemin:1,sizemode:\"diameter\"};var _=v(\"marker.size\",i.mean,[2,16],f);x.ms=_,b.marker.size=_}g&&(b.line={width:v(\"line.width\",m,[0,10],p)}),h&&(x.tx=\"Aa\",x.tp=v(\"textposition\",m),x.ts=10,x.tc=v(\"textfont.color\",m),x.tf=v(\"textfont.family\",m)),r=[i.minExtend(s,x)],(a=i.minExtend(l,b)).selectedpoints=null,a.texttemplate=null}var w=n.select(this).select(\"g.legendpoints\"),k=w.selectAll(\"path.scatterpts\").data(u?r:[]);k.enter().insert(\"path\",\":first-child\").classed(\"scatterpts\",!0).attr(\"transform\",\"translate(20,0)\"),k.exit().remove(),k.call(o.pointStyle,a,e),u&&(r[0].mrc=3);var T=w.selectAll(\"g.pointtext\").data(h?r:[]);T.enter().append(\"g\").classed(\"pointtext\",!0).append(\"text\").attr(\"transform\",\"translate(20,0)\"),T.exit().remove(),T.selectAll(\"text\").call(o.textPointStyle,a,e)}).each(function(t){var e=t[0].trace,r=n.select(this).select(\"g.legendpoints\").selectAll(\"path.legendcandle\").data(e.visible&&\"candlestick\"===e.type?[t,t]:[]);r.enter().append(\"path\").classed(\"legendcandle\",!0).attr(\"d\",function(t,e){return e?\"M-15,0H-8M-8,6V-6H8Z\":\"M15,0H8M8,-6V6H-8Z\"}).attr(\"transform\",\"translate(20,0)\").style(\"stroke-miterlimit\",1),r.exit().remove(),r.each(function(t,r){var a=n.select(this),i=e[r?\"increasing\":\"decreasing\"],o=x(void 0,i.line,v,d);a.style(\"stroke-width\",o+\"px\").call(s.fill,i.fillcolor),o&&s.stroke(a,i.line.color)})}).each(function(t){var e=t[0].trace,r=n.select(this).select(\"g.legendpoints\").selectAll(\"path.legendohlc\").data(e.visible&&\"ohlc\"===e.type?[t,t]:[]);r.enter().append(\"path\").classed(\"legendohlc\",!0).attr(\"d\",function(t,e){return e?\"M-15,0H0M-8,-6V0\":\"M15,0H0M8,6V0\"}).attr(\"transform\",\"translate(20,0)\").style(\"stroke-miterlimit\",1),r.exit().remove(),r.each(function(t,r){var a=n.select(this),i=e[r?\"increasing\":\"decreasing\"],l=x(void 0,i.line,v,d);a.style(\"fill\",\"none\").call(o.dashLine,i.line.dash,l),l&&s.stroke(a,i.line.color)})})}},{\"../../lib\":717,\"../../registry\":846,\"../../traces/pie/helpers\":1099,\"../../traces/pie/style_one\":1105,\"../../traces/scatter/subtypes\":1144,\"../color\":592,\"../colorscale/helpers\":603,\"../drawing\":613,d3:165}],649:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../plots/plots\"),i=t(\"../../plots/cartesian/axis_ids\"),o=t(\"../../lib\"),s=t(\"../../fonts/ploticon\"),l=o._,c=e.exports={};function u(t,e){var r,a,o=e.currentTarget,s=o.getAttribute(\"data-attr\"),l=o.getAttribute(\"data-val\")||!0,c=t._fullLayout,u={},h=i.list(t,null,!0),f=c._cartesianSpikesEnabled;if(\"zoom\"===s){var p,d=\"in\"===l?.5:2,g=(1+d)/2,v=(1-d)/2;for(a=0;a<h.length;a++)if(!(r=h[a]).fixedrange)if(p=r._name,\"auto\"===l)u[p+\".autorange\"]=!0;else if(\"reset\"===l){if(void 0===r._rangeInitial)u[p+\".autorange\"]=!0;else{var m=r._rangeInitial.slice();u[p+\".range[0]\"]=m[0],u[p+\".range[1]\"]=m[1]}void 0!==r._showSpikeInitial&&(u[p+\".showspikes\"]=r._showSpikeInitial,\"on\"!==f||r._showSpikeInitial||(f=\"off\"))}else{var y=[r.r2l(r.range[0]),r.r2l(r.range[1])],x=[g*y[0]+v*y[1],g*y[1]+v*y[0]];u[p+\".range[0]\"]=r.l2r(x[0]),u[p+\".range[1]\"]=r.l2r(x[1])}}else\"hovermode\"!==s||\"x\"!==l&&\"y\"!==l||(l=c._isHoriz?\"y\":\"x\",o.setAttribute(\"data-val\",l)),u[s]=l;c._cartesianSpikesEnabled=f,n.call(\"_guiRelayout\",t,u)}function h(t,e){for(var r=e.currentTarget,a=r.getAttribute(\"data-attr\"),i=r.getAttribute(\"data-val\")||!0,o=t._fullLayout._subplots.gl3d||[],s={},l=a.split(\".\"),c=0;c<o.length;c++)s[o[c]+\".\"+l[1]]=i;var u=\"pan\"===i?i:\"zoom\";s.dragmode=u,n.call(\"_guiRelayout\",t,s)}function f(t,e){for(var r=e.currentTarget.getAttribute(\"data-attr\"),a=t._fullLayout,i=a._subplots.gl3d||[],o={},s=0;s<i.length;s++){var l,c=i[s],u=c+\".camera\",h=c+\".aspectratio\",f=a[c]._scene;\"resetLastSave\"===r?(o[u+\".up\"]=f.viewInitial.up,o[u+\".eye\"]=f.viewInitial.eye,o[u+\".center\"]=f.viewInitial.center,l=!0):\"resetDefault\"===r&&(o[u+\".up\"]=null,o[u+\".eye\"]=null,o[u+\".center\"]=null,l=!0),l&&(o[h+\".x\"]=f.viewInitial.aspectratio.x,o[h+\".y\"]=f.viewInitial.aspectratio.y,o[h+\".z\"]=f.viewInitial.aspectratio.z)}n.call(\"_guiRelayout\",t,o)}function p(t,e){var r=e.currentTarget,n=r._previousVal,a=t._fullLayout,i=a._subplots.gl3d||[],o=[\"xaxis\",\"yaxis\",\"zaxis\"],s={},l={};if(n)l=n,r._previousVal=null;else{for(var c=0;c<i.length;c++){var u=i[c],h=a[u],f=u+\".hovermode\";s[f]=h.hovermode,l[f]=!1;for(var p=0;p<3;p++){var d=o[p],g=u+\".\"+d+\".showspikes\";l[g]=!1,s[g]=h[d].showspikes}}r._previousVal=s}return l}function d(t,e){for(var r=e.currentTarget,a=r.getAttribute(\"data-attr\"),i=r.getAttribute(\"data-val\")||!0,o=t._fullLayout,s=o._subplots.geo||[],l=0;l<s.length;l++){var c=s[l],u=o[c];if(\"zoom\"===a){var h=u.projection.scale,f=\"in\"===i?2*h:.5*h;n.call(\"_guiRelayout\",t,c+\".projection.scale\",f)}}\"reset\"===a&&y(t,\"geo\")}function g(t){var e=t._fullLayout;return!e.hovermode&&(e._has(\"cartesian\")?e._isHoriz?\"y\":\"x\":\"closest\")}function v(t){var e=g(t);n.call(\"_guiRelayout\",t,\"hovermode\",e)}function m(t,e){for(var r=e.currentTarget.getAttribute(\"data-val\"),a=t._fullLayout,i=a._subplots.mapbox||[],o={},s=0;s<i.length;s++){var l=i[s],c=a[l].zoom,u=\"in\"===r?1.05*c:c/1.05;o[l+\".zoom\"]=u}n.call(\"_guiRelayout\",t,o)}function y(t,e){for(var r=t._fullLayout,a=r._subplots[e]||[],i={},o=0;o<a.length;o++)for(var s=a[o],l=r[s]._subplot.viewInitial,c=Object.keys(l),u=0;u<c.length;u++){var h=c[u];i[s+\".\"+h]=l[h]}n.call(\"_guiRelayout\",t,i)}c.toImage={name:\"toImage\",title:function(t){var e=(t._context.toImageButtonOptions||{}).format||\"png\";return l(t,\"png\"===e?\"Download plot as a png\":\"Download plot\")},icon:s.camera,click:function(t){var e=t._context.toImageButtonOptions,r={format:e.format||\"png\"};o.notifier(l(t,\"Taking snapshot - this may take a few seconds\"),\"long\"),\"svg\"!==r.format&&o.isIE()&&(o.notifier(l(t,\"IE only supports svg.  Changing format to svg.\"),\"long\"),r.format=\"svg\"),[\"filename\",\"width\",\"height\",\"scale\"].forEach(function(t){t in e&&(r[t]=e[t])}),n.call(\"downloadImage\",t,r).then(function(e){o.notifier(l(t,\"Snapshot succeeded\")+\" - \"+e,\"long\")}).catch(function(){o.notifier(l(t,\"Sorry, there was a problem downloading your snapshot!\"),\"long\")})}},c.sendDataToCloud={name:\"sendDataToCloud\",title:function(t){return l(t,\"Edit in Chart Studio\")},icon:s.disk,click:function(t){a.sendDataToCloud(t)}},c.editInChartStudio={name:\"editInChartStudio\",title:function(t){return l(t,\"Edit in Chart Studio\")},icon:s.pencil,click:function(t){a.sendDataToCloud(t)}},c.zoom2d={name:\"zoom2d\",title:function(t){return l(t,\"Zoom\")},attr:\"dragmode\",val:\"zoom\",icon:s.zoombox,click:u},c.pan2d={name:\"pan2d\",title:function(t){return l(t,\"Pan\")},attr:\"dragmode\",val:\"pan\",icon:s.pan,click:u},c.select2d={name:\"select2d\",title:function(t){return l(t,\"Box Select\")},attr:\"dragmode\",val:\"select\",icon:s.selectbox,click:u},c.lasso2d={name:\"lasso2d\",title:function(t){return l(t,\"Lasso Select\")},attr:\"dragmode\",val:\"lasso\",icon:s.lasso,click:u},c.zoomIn2d={name:\"zoomIn2d\",title:function(t){return l(t,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:s.zoom_plus,click:u},c.zoomOut2d={name:\"zoomOut2d\",title:function(t){return l(t,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:s.zoom_minus,click:u},c.autoScale2d={name:\"autoScale2d\",title:function(t){return l(t,\"Autoscale\")},attr:\"zoom\",val:\"auto\",icon:s.autoscale,click:u},c.resetScale2d={name:\"resetScale2d\",title:function(t){return l(t,\"Reset axes\")},attr:\"zoom\",val:\"reset\",icon:s.home,click:u},c.hoverClosestCartesian={name:\"hoverClosestCartesian\",title:function(t){return l(t,\"Show closest data on hover\")},attr:\"hovermode\",val:\"closest\",icon:s.tooltip_basic,gravity:\"ne\",click:u},c.hoverCompareCartesian={name:\"hoverCompareCartesian\",title:function(t){return l(t,\"Compare data on hover\")},attr:\"hovermode\",val:function(t){return t._fullLayout._isHoriz?\"y\":\"x\"},icon:s.tooltip_compare,gravity:\"ne\",click:u},c.zoom3d={name:\"zoom3d\",title:function(t){return l(t,\"Zoom\")},attr:\"scene.dragmode\",val:\"zoom\",icon:s.zoombox,click:h},c.pan3d={name:\"pan3d\",title:function(t){return l(t,\"Pan\")},attr:\"scene.dragmode\",val:\"pan\",icon:s.pan,click:h},c.orbitRotation={name:\"orbitRotation\",title:function(t){return l(t,\"Orbital rotation\")},attr:\"scene.dragmode\",val:\"orbit\",icon:s[\"3d_rotate\"],click:h},c.tableRotation={name:\"tableRotation\",title:function(t){return l(t,\"Turntable rotation\")},attr:\"scene.dragmode\",val:\"turntable\",icon:s[\"z-axis\"],click:h},c.resetCameraDefault3d={name:\"resetCameraDefault3d\",title:function(t){return l(t,\"Reset camera to default\")},attr:\"resetDefault\",icon:s.home,click:f},c.resetCameraLastSave3d={name:\"resetCameraLastSave3d\",title:function(t){return l(t,\"Reset camera to last save\")},attr:\"resetLastSave\",icon:s.movie,click:f},c.hoverClosest3d={name:\"hoverClosest3d\",title:function(t){return l(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:s.tooltip_basic,gravity:\"ne\",click:function(t,e){var r=p(t,e);n.call(\"_guiRelayout\",t,r)}},c.zoomInGeo={name:\"zoomInGeo\",title:function(t){return l(t,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:s.zoom_plus,click:d},c.zoomOutGeo={name:\"zoomOutGeo\",title:function(t){return l(t,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:s.zoom_minus,click:d},c.resetGeo={name:\"resetGeo\",title:function(t){return l(t,\"Reset\")},attr:\"reset\",val:null,icon:s.autoscale,click:d},c.hoverClosestGeo={name:\"hoverClosestGeo\",title:function(t){return l(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:s.tooltip_basic,gravity:\"ne\",click:v},c.hoverClosestGl2d={name:\"hoverClosestGl2d\",title:function(t){return l(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:s.tooltip_basic,gravity:\"ne\",click:v},c.hoverClosestPie={name:\"hoverClosestPie\",title:function(t){return l(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:\"closest\",icon:s.tooltip_basic,gravity:\"ne\",click:v},c.resetViewSankey={name:\"resetSankeyGroup\",title:function(t){return l(t,\"Reset view\")},icon:s.home,click:function(t){for(var e={\"node.groups\":[],\"node.x\":[],\"node.y\":[]},r=0;r<t._fullData.length;r++){var a=t._fullData[r]._viewInitial;e[\"node.groups\"].push(a.node.groups.slice()),e[\"node.x\"].push(a.node.x.slice()),e[\"node.y\"].push(a.node.y.slice())}n.call(\"restyle\",t,e)}},c.toggleHover={name:\"toggleHover\",title:function(t){return l(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:s.tooltip_basic,gravity:\"ne\",click:function(t,e){var r=p(t,e);r.hovermode=g(t),n.call(\"_guiRelayout\",t,r)}},c.resetViews={name:\"resetViews\",title:function(t){return l(t,\"Reset views\")},icon:s.home,click:function(t,e){var r=e.currentTarget;r.setAttribute(\"data-attr\",\"zoom\"),r.setAttribute(\"data-val\",\"reset\"),u(t,e),r.setAttribute(\"data-attr\",\"resetLastSave\"),f(t,e),y(t,\"geo\"),y(t,\"mapbox\")}},c.toggleSpikelines={name:\"toggleSpikelines\",title:function(t){return l(t,\"Toggle Spike Lines\")},icon:s.spikeline,attr:\"_cartesianSpikesEnabled\",val:\"on\",click:function(t){var e=t._fullLayout,r=e._cartesianSpikesEnabled;e._cartesianSpikesEnabled=\"on\"===r?\"off\":\"on\",n.call(\"_guiRelayout\",t,function(t){for(var e=\"on\"===t._fullLayout._cartesianSpikesEnabled,r=i.list(t,null,!0),n={},a=0;a<r.length;a++){var o=r[a];n[o._name+\".showspikes\"]=!!e||o._showSpikeInitial}return n}(t))}},c.resetViewMapbox={name:\"resetViewMapbox\",title:function(t){return l(t,\"Reset view\")},attr:\"reset\",icon:s.home,click:function(t){y(t,\"mapbox\")}},c.zoomInMapbox={name:\"zoomInMapbox\",title:function(t){return l(t,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:s.zoom_plus,click:m},c.zoomOutMapbox={name:\"zoomOutMapbox\",title:function(t){return l(t,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:s.zoom_minus,click:m}},{\"../../fonts/ploticon\":697,\"../../lib\":717,\"../../plots/cartesian/axis_ids\":768,\"../../plots/plots\":826,\"../../registry\":846}],650:[function(t,e,r){\"use strict\";r.manage=t(\"./manage\")},{\"./manage\":651}],651:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axis_ids\"),a=t(\"../../traces/scatter/subtypes\"),i=t(\"../../registry\"),o=t(\"./modebar\"),s=t(\"./buttons\");e.exports=function(t){var e=t._fullLayout,r=t._context,l=e._modeBar;if(r.displayModeBar||r.watermark){if(!Array.isArray(r.modeBarButtonsToRemove))throw new Error([\"*modeBarButtonsToRemove* configuration options\",\"must be an array.\"].join(\" \"));if(!Array.isArray(r.modeBarButtonsToAdd))throw new Error([\"*modeBarButtonsToAdd* configuration options\",\"must be an array.\"].join(\" \"));var c,u=r.modeBarButtons;c=Array.isArray(u)&&u.length?function(t){for(var e=0;e<t.length;e++)for(var r=t[e],n=0;n<r.length;n++){var a=r[n];if(\"string\"==typeof a){if(void 0===s[a])throw new Error([\"*modeBarButtons* configuration options\",\"invalid button name\"].join(\" \"));t[e][n]=s[a]}}return t}(u):!r.displayModeBar&&r.watermark?[]:function(t){var e=t._fullLayout,r=t._fullData,o=t._context,l=o.modeBarButtonsToRemove,c=o.modeBarButtonsToAdd,u=e._has(\"cartesian\"),h=e._has(\"gl3d\"),f=e._has(\"geo\"),p=e._has(\"pie\"),d=e._has(\"funnelarea\"),g=e._has(\"gl2d\"),v=e._has(\"ternary\"),m=e._has(\"mapbox\"),y=e._has(\"polar\"),x=e._has(\"sankey\"),b=function(t){for(var e=n.list({_fullLayout:t},null,!0),r=0;r<e.length;r++)if(!e[r].fixedrange)return!1;return!0}(e),_=[];function w(t){if(t.length){for(var e=[],r=0;r<t.length;r++){var n=t[r];-1===l.indexOf(n)&&e.push(s[n])}_.push(e)}}var k=[\"toImage\"];o.showEditInChartStudio?k.push(\"editInChartStudio\"):o.showSendToCloud&&k.push(\"sendDataToCloud\");w(k);var T=[],M=[],A=[],S=[];(u||g||p||d||v)+f+h+m+y>1?(M=[\"toggleHover\"],A=[\"resetViews\"]):f?(T=[\"zoomInGeo\",\"zoomOutGeo\"],M=[\"hoverClosestGeo\"],A=[\"resetGeo\"]):h?(M=[\"hoverClosest3d\"],A=[\"resetCameraDefault3d\",\"resetCameraLastSave3d\"]):m?(T=[\"zoomInMapbox\",\"zoomOutMapbox\"],M=[\"toggleHover\"],A=[\"resetViewMapbox\"]):g?M=[\"hoverClosestGl2d\"]:p?M=[\"hoverClosestPie\"]:x?(M=[\"hoverClosestCartesian\",\"hoverCompareCartesian\"],A=[\"resetViewSankey\"]):M=[\"toggleHover\"];u&&(M=[\"toggleSpikelines\",\"hoverClosestCartesian\",\"hoverCompareCartesian\"]);(function(t){for(var e=0;e<t.length;e++)if(!i.traceIs(t[e],\"noHover\"))return!1;return!0})(r)&&(M=[]);!u&&!g||b||(T=[\"zoomIn2d\",\"zoomOut2d\",\"autoScale2d\"],\"resetViews\"!==A[0]&&(A=[\"resetScale2d\"]));h?S=[\"zoom3d\",\"pan3d\",\"orbitRotation\",\"tableRotation\"]:(u||g)&&!b||v?S=[\"zoom2d\",\"pan2d\"]:m||f?S=[\"pan2d\"]:y&&(S=[\"zoom2d\"]);(function(t){for(var e=!1,r=0;r<t.length&&!e;r++){var n=t[r];n._module&&n._module.selectPoints&&(i.traceIs(n,\"scatter-like\")?(a.hasMarkers(n)||a.hasText(n))&&(e=!0):i.traceIs(n,\"box-violin\")&&\"all\"!==n.boxpoints&&\"all\"!==n.points||(e=!0))}return e})(r)&&S.push(\"select2d\",\"lasso2d\");return w(S),w(T.concat(A)),w(M),function(t,e){if(e.length)if(Array.isArray(e[0]))for(var r=0;r<e.length;r++)t.push(e[r]);else t.push(e);return t}(_,c)}(t),l?l.update(t,c):e._modeBar=o(t,c)}else l&&(l.destroy(),delete e._modeBar)}},{\"../../plots/cartesian/axis_ids\":768,\"../../registry\":846,\"../../traces/scatter/subtypes\":1144,\"./buttons\":649,\"./modebar\":652}],652:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"fast-isnumeric\"),i=t(\"../../lib\"),o=t(\"../../fonts/ploticon\"),s=new DOMParser;function l(t){this.container=t.container,this.element=document.createElement(\"div\"),this.update(t.graphInfo,t.buttons),this.container.appendChild(this.element)}var c=l.prototype;c.update=function(t,e){this.graphInfo=t;var r=this.graphInfo._context,n=this.graphInfo._fullLayout,a=\"modebar-\"+n._uid;this.element.setAttribute(\"id\",a),this._uid=a,this.element.className=\"modebar\",\"hover\"===r.displayModeBar&&(this.element.className+=\" modebar--hover ease-bg\"),\"v\"===n.modebar.orientation&&(this.element.className+=\" vertical\",e=e.reverse());var o=n.modebar,s=\"hover\"===r.displayModeBar?\".js-plotly-plot .plotly:hover \":\"\";i.deleteRelatedStyleRule(a),i.addRelatedStyleRule(a,s+\"#\"+a+\" .modebar-group\",\"background-color: \"+o.bgcolor),i.addRelatedStyleRule(a,\"#\"+a+\" .modebar-btn .icon path\",\"fill: \"+o.color),i.addRelatedStyleRule(a,\"#\"+a+\" .modebar-btn:hover .icon path\",\"fill: \"+o.activecolor),i.addRelatedStyleRule(a,\"#\"+a+\" .modebar-btn.active .icon path\",\"fill: \"+o.activecolor);var l=!this.hasButtons(e),c=this.hasLogo!==r.displaylogo,u=this.locale!==r.locale;if(this.locale=r.locale,(l||c||u)&&(this.removeAllButtons(),this.updateButtons(e),r.watermark||r.displaylogo)){var h=this.getLogo();r.watermark&&(h.className=h.className+\" watermark\"),\"v\"===n.modebar.orientation?this.element.insertBefore(h,this.element.childNodes[0]):this.element.appendChild(h),this.hasLogo=!0}this.updateActiveButton()},c.updateButtons=function(t){var e=this;this.buttons=t,this.buttonElements=[],this.buttonsNames=[],this.buttons.forEach(function(t){var r=e.createGroup();t.forEach(function(t){var n=t.name;if(!n)throw new Error(\"must provide button 'name' in button config\");if(-1!==e.buttonsNames.indexOf(n))throw new Error(\"button name '\"+n+\"' is taken\");e.buttonsNames.push(n);var a=e.createButton(t);e.buttonElements.push(a),r.appendChild(a)}),e.element.appendChild(r)})},c.createGroup=function(){var t=document.createElement(\"div\");return t.className=\"modebar-group\",t},c.createButton=function(t){var e=this,r=document.createElement(\"a\");r.setAttribute(\"rel\",\"tooltip\"),r.className=\"modebar-btn\";var a=t.title;void 0===a?a=t.name:\"function\"==typeof a&&(a=a(this.graphInfo)),(a||0===a)&&r.setAttribute(\"data-title\",a),void 0!==t.attr&&r.setAttribute(\"data-attr\",t.attr);var i=t.val;if(void 0!==i&&(\"function\"==typeof i&&(i=i(this.graphInfo)),r.setAttribute(\"data-val\",i)),\"function\"!=typeof t.click)throw new Error(\"must provide button 'click' function in button config\");r.addEventListener(\"click\",function(r){t.click(e.graphInfo,r),e.updateActiveButton(r.currentTarget)}),r.setAttribute(\"data-toggle\",t.toggle||!1),t.toggle&&n.select(r).classed(\"active\",!0);var s=t.icon;return\"function\"==typeof s?r.appendChild(s()):r.appendChild(this.createIcon(s||o.question)),r.setAttribute(\"data-gravity\",t.gravity||\"n\"),r},c.createIcon=function(t){var e,r=a(t.height)?Number(t.height):t.ascent-t.descent,n=\"http://www.w3.org/2000/svg\";if(t.path){(e=document.createElementNS(n,\"svg\")).setAttribute(\"viewBox\",[0,0,t.width,r].join(\" \")),e.setAttribute(\"class\",\"icon\");var i=document.createElementNS(n,\"path\");i.setAttribute(\"d\",t.path),t.transform?i.setAttribute(\"transform\",t.transform):void 0!==t.ascent&&i.setAttribute(\"transform\",\"matrix(1 0 0 -1 0 \"+t.ascent+\")\"),e.appendChild(i)}t.svg&&(e=s.parseFromString(t.svg,\"application/xml\").childNodes[0]);return e.setAttribute(\"height\",\"1em\"),e.setAttribute(\"width\",\"1em\"),e},c.updateActiveButton=function(t){var e=this.graphInfo._fullLayout,r=void 0!==t?t.getAttribute(\"data-attr\"):null;this.buttonElements.forEach(function(t){var a=t.getAttribute(\"data-val\")||!0,o=t.getAttribute(\"data-attr\"),s=\"true\"===t.getAttribute(\"data-toggle\"),l=n.select(t);if(s)o===r&&l.classed(\"active\",!l.classed(\"active\"));else{var c=null===o?o:i.nestedProperty(e,o).get();l.classed(\"active\",c===a)}})},c.hasButtons=function(t){var e=this.buttons;if(!e)return!1;if(t.length!==e.length)return!1;for(var r=0;r<t.length;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;n<t[r].length;n++)if(t[r][n].name!==e[r][n].name)return!1}return!0},c.getLogo=function(){var t=this.createGroup(),e=document.createElement(\"a\");return e.href=\"https://plot.ly/\",e.target=\"_blank\",e.setAttribute(\"data-title\",i._(this.graphInfo,\"Produced with Plotly\")),e.className=\"modebar-btn plotlyjsicon modebar-btn--logo\",e.appendChild(this.createIcon(o.newplotlylogo)),t.appendChild(e),t},c.removeAllButtons=function(){for(;this.element.firstChild;)this.element.removeChild(this.element.firstChild);this.hasLogo=!1},c.destroy=function(){i.removeElement(this.container.querySelector(\".modebar\")),i.deleteRelatedStyleRule(this._uid)},e.exports=function(t,e){var r=t._fullLayout,a=new l({graphInfo:t,container:r._modebardiv.node(),buttons:e});return r._privateplot&&n.select(a.element).append(\"span\").classed(\"badge-private float--left\",!0).text(\"PRIVATE\"),a}},{\"../../fonts/ploticon\":697,\"../../lib\":717,d3:165,\"fast-isnumeric\":228}],653:[function(t,e,r){\"use strict\";var n=t(\"../../plots/font_attributes\"),a=t(\"../color/attributes\"),i=(0,t(\"../../plot_api/plot_template\").templatedArray)(\"button\",{visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},step:{valType:\"enumerated\",values:[\"month\",\"year\",\"day\",\"hour\",\"minute\",\"second\",\"all\"],dflt:\"month\",editType:\"plot\"},stepmode:{valType:\"enumerated\",values:[\"backward\",\"todate\"],dflt:\"backward\",editType:\"plot\"},count:{valType:\"number\",min:0,dflt:1,editType:\"plot\"},label:{valType:\"string\",editType:\"plot\"},editType:\"plot\"});e.exports={visible:{valType:\"boolean\",editType:\"plot\"},buttons:i,x:{valType:\"number\",min:-2,max:3,editType:\"plot\"},xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\",editType:\"plot\"},y:{valType:\"number\",min:-2,max:3,editType:\"plot\"},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"bottom\",editType:\"plot\"},font:n({editType:\"plot\"}),bgcolor:{valType:\"color\",dflt:a.lightLine,editType:\"plot\"},activecolor:{valType:\"color\",editType:\"plot\"},bordercolor:{valType:\"color\",dflt:a.defaultLine,editType:\"plot\"},borderwidth:{valType:\"number\",min:0,dflt:0,editType:\"plot\"},editType:\"plot\"}},{\"../../plot_api/plot_template\":755,\"../../plots/font_attributes\":791,\"../color/attributes\":591}],654:[function(t,e,r){\"use strict\";e.exports={yPad:.02,minButtonWidth:30,rx:3,ry:3,lightAmount:25,darkAmount:10}},{}],655:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../color\"),i=t(\"../../plot_api/plot_template\"),o=t(\"../../plots/array_container_defaults\"),s=t(\"./attributes\"),l=t(\"./constants\");function c(t,e,r,a){var i=a.calendar;function o(r,a){return n.coerce(t,e,s.buttons,r,a)}if(o(\"visible\")){var l=o(\"step\");\"all\"!==l&&(!i||\"gregorian\"===i||\"month\"!==l&&\"year\"!==l?o(\"stepmode\"):e.stepmode=\"backward\",o(\"count\")),o(\"label\")}}e.exports=function(t,e,r,u,h){var f=t.rangeselector||{},p=i.newContainer(e,\"rangeselector\");function d(t,e){return n.coerce(f,p,s,t,e)}if(d(\"visible\",o(f,p,{name:\"buttons\",handleItemDefaults:c,calendar:h}).length>0)){var g=function(t,e,r){for(var n=r.filter(function(r){return e[r].anchor===t._id}),a=0,i=0;i<n.length;i++){var o=e[n[i]].domain;o&&(a=Math.max(o[1],a))}return[t.domain[0],a+l.yPad]}(e,r,u);d(\"x\",g[0]),d(\"y\",g[1]),n.noneOrAll(t,e,[\"x\",\"y\"]),d(\"xanchor\"),d(\"yanchor\"),n.coerceFont(d,\"font\",r.font);var v=d(\"bgcolor\");d(\"activecolor\",a.contrast(v,l.lightAmount,l.darkAmount)),d(\"bordercolor\"),d(\"borderwidth\")}}},{\"../../lib\":717,\"../../plot_api/plot_template\":755,\"../../plots/array_container_defaults\":761,\"../color\":592,\"./attributes\":653,\"./constants\":654}],656:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../registry\"),i=t(\"../../plots/plots\"),o=t(\"../color\"),s=t(\"../drawing\"),l=t(\"../../lib\"),c=t(\"../../lib/svg_text_utils\"),u=t(\"../../plots/cartesian/axis_ids\"),h=t(\"../../constants/alignment\"),f=h.LINE_SPACING,p=h.FROM_TL,d=h.FROM_BR,g=t(\"./constants\"),v=t(\"./get_update_object\");function m(t){return t._id}function y(t,e,r){var n=l.ensureSingle(t,\"rect\",\"selector-rect\",function(t){t.attr(\"shape-rendering\",\"crispEdges\")});n.attr({rx:g.rx,ry:g.ry}),n.call(o.stroke,e.bordercolor).call(o.fill,function(t,e){return e._isActive||e._isHovered?t.activecolor:t.bgcolor}(e,r)).style(\"stroke-width\",e.borderwidth+\"px\")}function x(t,e,r,n){l.ensureSingle(t,\"text\",\"selector-text\",function(t){t.classed(\"user-select-none\",!0).attr(\"text-anchor\",\"middle\")}).call(s.font,e.font).text(function(t,e){if(t.label)return e?l.templateString(t.label,e):t.label;return\"all\"===t.step?\"all\":t.count+t.step.charAt(0)}(r,n._fullLayout._meta)).call(function(t){c.convertToTspans(t,n)})}e.exports=function(t){var e=t._fullLayout._infolayer.selectAll(\".rangeselector\").data(function(t){for(var e=u.list(t,\"x\",!0),r=[],n=0;n<e.length;n++){var a=e[n];a.rangeselector&&a.rangeselector.visible&&r.push(a)}return r}(t),m);e.enter().append(\"g\").classed(\"rangeselector\",!0),e.exit().remove(),e.style({cursor:\"pointer\",\"pointer-events\":\"all\"}),e.each(function(e){var r=n.select(this),o=e,u=o.rangeselector,h=r.selectAll(\"g.button\").data(l.filterVisible(u.buttons));h.enter().append(\"g\").classed(\"button\",!0),h.exit().remove(),h.each(function(e){var r=n.select(this),i=v(o,e);e._isActive=function(t,e,r){if(\"all\"===e.step)return!0===t.autorange;var n=Object.keys(r);return t.range[0]===r[n[0]]&&t.range[1]===r[n[1]]}(o,e,i),r.call(y,u,e),r.call(x,u,e,t),r.on(\"click\",function(){t._dragged||a.call(\"_guiRelayout\",t,i)}),r.on(\"mouseover\",function(){e._isHovered=!0,r.call(y,u,e)}),r.on(\"mouseout\",function(){e._isHovered=!1,r.call(y,u,e)})}),function(t,e,r,a,o){var u=0,h=0,v=r.borderwidth;e.each(function(){var t=n.select(this),e=t.select(\".selector-text\"),a=r.font.size*f,i=Math.max(a*c.lineCount(e),16)+3;h=Math.max(h,i)}),e.each(function(){var t=n.select(this),e=t.select(\".selector-rect\"),a=t.select(\".selector-text\"),i=a.node()&&s.bBox(a.node()).width,o=r.font.size*f,l=c.lineCount(a),p=Math.max(i+10,g.minButtonWidth);t.attr(\"transform\",\"translate(\"+(v+u)+\",\"+v+\")\"),e.attr({x:0,y:0,width:p,height:h}),c.positionText(a,p/2,h/2-(l-1)*o/2+3),u+=p+5});var m=t._fullLayout._size,y=m.l+m.w*r.x,x=m.t+m.h*(1-r.y),b=\"left\";l.isRightAnchor(r)&&(y-=u,b=\"right\");l.isCenterAnchor(r)&&(y-=u/2,b=\"center\");var _=\"top\";l.isBottomAnchor(r)&&(x-=h,_=\"bottom\");l.isMiddleAnchor(r)&&(x-=h/2,_=\"middle\");u=Math.ceil(u),h=Math.ceil(h),y=Math.round(y),x=Math.round(x),i.autoMargin(t,a+\"-range-selector\",{x:r.x,y:r.y,l:u*p[b],r:u*d[b],b:h*d[_],t:h*p[_]}),o.attr(\"transform\",\"translate(\"+y+\",\"+x+\")\")}(t,h,u,o._name,r)})}},{\"../../constants/alignment\":686,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"../../plots/cartesian/axis_ids\":768,\"../../plots/plots\":826,\"../../registry\":846,\"../color\":592,\"../drawing\":613,\"./constants\":654,\"./get_update_object\":657,d3:165}],657:[function(t,e,r){\"use strict\";var n=t(\"d3\");e.exports=function(t,e){var r=t._name,a={};if(\"all\"===e.step)a[r+\".autorange\"]=!0;else{var i=function(t,e){var r,a=t.range,i=new Date(t.r2l(a[1])),o=e.step,s=e.count;switch(e.stepmode){case\"backward\":r=t.l2r(+n.time[o].utc.offset(i,-s));break;case\"todate\":var l=n.time[o].utc.offset(i,-s);r=t.l2r(+n.time[o].utc.ceil(l))}var c=a[1];return[r,c]}(t,e);a[r+\".range[0]\"]=i[0],a[r+\".range[1]\"]=i[1]}return a}},{d3:165}],658:[function(t,e,r){\"use strict\";e.exports={moduleType:\"component\",name:\"rangeselector\",schema:{subplots:{xaxis:{rangeselector:t(\"./attributes\")}}},layoutAttributes:t(\"./attributes\"),handleDefaults:t(\"./defaults\"),draw:t(\"./draw\")}},{\"./attributes\":653,\"./defaults\":655,\"./draw\":656}],659:[function(t,e,r){\"use strict\";var n=t(\"../color/attributes\");e.exports={bgcolor:{valType:\"color\",dflt:n.background,editType:\"plot\"},bordercolor:{valType:\"color\",dflt:n.defaultLine,editType:\"plot\"},borderwidth:{valType:\"integer\",dflt:0,min:0,editType:\"plot\"},autorange:{valType:\"boolean\",dflt:!0,editType:\"calc\",impliedEdits:{\"range[0]\":void 0,\"range[1]\":void 0}},range:{valType:\"info_array\",items:[{valType:\"any\",editType:\"calc\",impliedEdits:{\"^autorange\":!1}},{valType:\"any\",editType:\"calc\",impliedEdits:{\"^autorange\":!1}}],editType:\"calc\",impliedEdits:{autorange:!1}},thickness:{valType:\"number\",dflt:.15,min:0,max:1,editType:\"plot\"},visible:{valType:\"boolean\",dflt:!0,editType:\"calc\"},editType:\"calc\"}},{\"../color/attributes\":591}],660:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axis_ids\").list,a=t(\"../../plots/cartesian/autorange\").getAutoRange,i=t(\"./constants\");e.exports=function(t){for(var e=n(t,\"x\",!0),r=0;r<e.length;r++){var o=e[r],s=o[i.name];s&&s.visible&&s.autorange&&(s._input.autorange=!0,s._input.range=s.range=a(t,o))}}},{\"../../plots/cartesian/autorange\":764,\"../../plots/cartesian/axis_ids\":768,\"./constants\":661}],661:[function(t,e,r){\"use strict\";e.exports={name:\"rangeslider\",containerClassName:\"rangeslider-container\",bgClassName:\"rangeslider-bg\",rangePlotClassName:\"rangeslider-rangeplot\",maskMinClassName:\"rangeslider-mask-min\",maskMaxClassName:\"rangeslider-mask-max\",slideBoxClassName:\"rangeslider-slidebox\",grabberMinClassName:\"rangeslider-grabber-min\",grabAreaMinClassName:\"rangeslider-grabarea-min\",handleMinClassName:\"rangeslider-handle-min\",grabberMaxClassName:\"rangeslider-grabber-max\",grabAreaMaxClassName:\"rangeslider-grabarea-max\",handleMaxClassName:\"rangeslider-handle-max\",maskMinOppAxisClassName:\"rangeslider-mask-min-opp-axis\",maskMaxOppAxisClassName:\"rangeslider-mask-max-opp-axis\",maskColor:\"rgba(0,0,0,0.4)\",maskOppAxisColor:\"rgba(0,0,0,0.2)\",slideBoxFill:\"transparent\",slideBoxCursor:\"ew-resize\",grabAreaFill:\"transparent\",grabAreaCursor:\"col-resize\",grabAreaWidth:10,handleWidth:4,handleRadius:1,handleStrokeWidth:1,extraPad:15}},{}],662:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plot_api/plot_template\"),i=t(\"../../plots/cartesian/axis_ids\"),o=t(\"./attributes\"),s=t(\"./oppaxis_attributes\");e.exports=function(t,e,r){var l=t[r],c=e[r];if(l.rangeslider||e._requestRangeslider[c._id]){n.isPlainObject(l.rangeslider)||(l.rangeslider={});var u,h,f=l.rangeslider,p=a.newContainer(c,\"rangeslider\");if(_(\"visible\")){_(\"bgcolor\",e.plot_bgcolor),_(\"bordercolor\"),_(\"borderwidth\"),_(\"thickness\"),_(\"autorange\",!c.isValidRange(f.range)),_(\"range\");var d=e._subplots;if(d)for(var g=d.cartesian.filter(function(t){return t.substr(0,t.indexOf(\"y\"))===i.name2id(r)}).map(function(t){return t.substr(t.indexOf(\"y\"),t.length)}),v=n.simpleMap(g,i.id2name),m=0;m<v.length;m++){var y=v[m];u=f[y]||{},h=a.newContainer(p,y,\"yaxis\");var x,b=e[y];u.range&&b.isValidRange(u.range)&&(x=\"fixed\"),\"match\"!==w(\"rangemode\",x)&&w(\"range\",b.range.slice())}p._input=f}}function _(t,e){return n.coerce(f,p,o,t,e)}function w(t,e){return n.coerce(u,h,s,t,e)}}},{\"../../lib\":717,\"../../plot_api/plot_template\":755,\"../../plots/cartesian/axis_ids\":768,\"./attributes\":659,\"./oppaxis_attributes\":666}],663:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../registry\"),i=t(\"../../plots/plots\"),o=t(\"../../lib\"),s=t(\"../drawing\"),l=t(\"../color\"),c=t(\"../titles\"),u=t(\"../../plots/cartesian\"),h=t(\"../../plots/cartesian/axis_ids\"),f=t(\"../dragelement\"),p=t(\"../../lib/setcursor\"),d=t(\"./constants\");function g(t,e,r,n){var a=o.ensureSingle(t,\"rect\",d.bgClassName,function(t){t.attr({x:0,y:0,\"shape-rendering\":\"crispEdges\"})}),i=n.borderwidth%2==0?n.borderwidth:n.borderwidth-1,l=-n._offsetShift,c=s.crispRound(e,n.borderwidth);a.attr({width:n._width+i,height:n._height+i,transform:\"translate(\"+l+\",\"+l+\")\",fill:n.bgcolor,stroke:n.bordercolor,\"stroke-width\":c})}function v(t,e,r,n){var a=e._fullLayout;o.ensureSingleById(a._topdefs,\"clipPath\",n._clipId,function(t){t.append(\"rect\").attr({x:0,y:0})}).select(\"rect\").attr({width:n._width,height:n._height})}function m(t,e,r,a){var l,c=e.calcdata,f=t.selectAll(\"g.\"+d.rangePlotClassName).data(r._subplotsWith,o.identity);f.enter().append(\"g\").attr(\"class\",function(t){return d.rangePlotClassName+\" \"+t}).call(s.setClipUrl,a._clipId,e),f.order(),f.exit().remove(),f.each(function(t,o){var s=n.select(this),f=0===o,p=h.getFromId(e,t,\"y\"),d=p._name,g=a[d],v={data:[],layout:{xaxis:{type:r.type,domain:[0,1],range:a.range.slice(),calendar:r.calendar},width:a._width,height:a._height,margin:{t:0,b:0,l:0,r:0}},_context:e._context};v.layout[d]={type:p.type,domain:[0,1],range:\"match\"!==g.rangemode?g.range.slice():p.range.slice(),calendar:p.calendar},i.supplyDefaults(v);var m=v._fullLayout.xaxis,y=v._fullLayout[d];m.clearCalc(),m.setScale(),y.clearCalc(),y.setScale();var x={id:t,plotgroup:s,xaxis:m,yaxis:y,isRangePlot:!0};f?l=x:(x.mainplot=\"xy\",x.mainplotinfo=l),u.rangePlot(e,x,function(t,e){for(var r=[],n=0;n<t.length;n++){var a=t[n],i=a[0].trace;i.xaxis+i.yaxis===e&&r.push(a)}return r}(c,t))})}function y(t,e,r,n,a){(o.ensureSingle(t,\"rect\",d.maskMinClassName,function(t){t.attr({x:0,y:0,\"shape-rendering\":\"crispEdges\"})}).attr(\"height\",n._height).call(l.fill,d.maskColor),o.ensureSingle(t,\"rect\",d.maskMaxClassName,function(t){t.attr({y:0,\"shape-rendering\":\"crispEdges\"})}).attr(\"height\",n._height).call(l.fill,d.maskColor),\"match\"!==a.rangemode)&&(o.ensureSingle(t,\"rect\",d.maskMinOppAxisClassName,function(t){t.attr({y:0,\"shape-rendering\":\"crispEdges\"})}).attr(\"width\",n._width).call(l.fill,d.maskOppAxisColor),o.ensureSingle(t,\"rect\",d.maskMaxOppAxisClassName,function(t){t.attr({y:0,\"shape-rendering\":\"crispEdges\"})}).attr(\"width\",n._width).style(\"border-top\",d.maskOppBorder).call(l.fill,d.maskOppAxisColor))}function x(t,e,r,n){e._context.staticPlot||o.ensureSingle(t,\"rect\",d.slideBoxClassName,function(t){t.attr({y:0,cursor:d.slideBoxCursor,\"shape-rendering\":\"crispEdges\"})}).attr({height:n._height,fill:d.slideBoxFill})}function b(t,e,r,n){var a=o.ensureSingle(t,\"g\",d.grabberMinClassName),i=o.ensureSingle(t,\"g\",d.grabberMaxClassName),s={x:0,width:d.handleWidth,rx:d.handleRadius,fill:l.background,stroke:l.defaultLine,\"stroke-width\":d.handleStrokeWidth,\"shape-rendering\":\"crispEdges\"},c={y:Math.round(n._height/4),height:Math.round(n._height/2)};if(o.ensureSingle(a,\"rect\",d.handleMinClassName,function(t){t.attr(s)}).attr(c),o.ensureSingle(i,\"rect\",d.handleMaxClassName,function(t){t.attr(s)}).attr(c),!e._context.staticPlot){var u={width:d.grabAreaWidth,x:0,y:0,fill:d.grabAreaFill,cursor:d.grabAreaCursor};o.ensureSingle(a,\"rect\",d.grabAreaMinClassName,function(t){t.attr(u)}).attr(\"height\",n._height),o.ensureSingle(i,\"rect\",d.grabAreaMaxClassName,function(t){t.attr(u)}).attr(\"height\",n._height)}}e.exports=function(t){for(var e=t._fullLayout,r=e._rangeSliderData,i=0;i<r.length;i++){var s=r[i][d.name];s._clipId=s._id+\"-\"+e._uid}var l=e._infolayer.selectAll(\"g.\"+d.containerClassName).data(r,function(t){return t._name});l.exit().each(function(t){var r=t[d.name];e._topdefs.select(\"#\"+r._clipId).remove()}).remove(),0!==r.length&&(l.enter().append(\"g\").classed(d.containerClassName,!0).attr(\"pointer-events\",\"all\"),l.each(function(r){var i=n.select(this),s=r[d.name],l=e[h.id2name(r.anchor)],u=s[h.id2name(r.anchor)];if(s.range){var _,w=o.simpleMap(s.range,r.r2l),k=o.simpleMap(r.range,r.r2l);_=k[0]<k[1]?[Math.min(w[0],k[0]),Math.max(w[1],k[1])]:[Math.max(w[0],k[0]),Math.min(w[1],k[1])],s.range=s._input.range=o.simpleMap(_,r.l2r)}r.cleanRange(\"rangeslider.range\");var T=e._size,M=r.domain;s._width=T.w*(M[1]-M[0]);var A=Math.round(T.l+T.w*M[0]),S=Math.round(T.t+T.h*(1-r._counterDomainMin)+(\"bottom\"===r.side?r._depth:0)+s._offsetShift+d.extraPad);i.attr(\"transform\",\"translate(\"+A+\",\"+S+\")\");var E=r.r2l(s.range[0]),L=r.r2l(s.range[1]),C=L-E;if(s.p2d=function(t){return t/s._width*C+E},s.d2p=function(t){return(t-E)/C*s._width},s._rl=[E,L],\"match\"!==u.rangemode){var P=l.r2l(u.range[0]),O=l.r2l(u.range[1])-P;s.d2pOppAxis=function(t){return(t-P)/O*s._height}}i.call(g,t,r,s).call(v,t,r,s).call(m,t,r,s).call(y,t,r,s,u).call(x,t,r,s).call(b,t,r,s),function(t,e,r,i){var s=t.select(\"rect.\"+d.slideBoxClassName).node(),l=t.select(\"rect.\"+d.grabAreaMinClassName).node(),c=t.select(\"rect.\"+d.grabAreaMaxClassName).node();t.on(\"mousedown\",function(){var u=n.event,h=u.target,d=u.clientX,g=d-t.node().getBoundingClientRect().left,v=i.d2p(r._rl[0]),m=i.d2p(r._rl[1]),y=f.coverSlip();function x(t){var u,f,x,b=+t.clientX-d;switch(h){case s:x=\"ew-resize\",u=v+b,f=m+b;break;case l:x=\"col-resize\",u=v+b,f=m;break;case c:x=\"col-resize\",u=v,f=m+b;break;default:x=\"ew-resize\",u=g,f=g+b}if(f<u){var _=f;f=u,u=_}i._pixelMin=u,i._pixelMax=f,p(n.select(y),x),function(t,e,r,n){function i(t){return r.l2r(o.constrain(t,n._rl[0],n._rl[1]))}var s=i(n.p2d(n._pixelMin)),l=i(n.p2d(n._pixelMax));window.requestAnimationFrame(function(){a.call(\"_guiRelayout\",e,r._name+\".range\",[s,l])})}(0,e,r,i)}y.addEventListener(\"mousemove\",x),y.addEventListener(\"mouseup\",function t(){y.removeEventListener(\"mousemove\",x);y.removeEventListener(\"mouseup\",t);o.removeElement(y)})})}(i,t,r,s),function(t,e,r,n,a,i){var s=d.handleWidth/2;function l(t){return o.constrain(t,0,n._width)}function c(t){return o.constrain(t,0,n._height)}function u(t){return o.constrain(t,-s,n._width+s)}var h=l(n.d2p(r._rl[0])),f=l(n.d2p(r._rl[1]));if(t.select(\"rect.\"+d.slideBoxClassName).attr(\"x\",h).attr(\"width\",f-h),t.select(\"rect.\"+d.maskMinClassName).attr(\"width\",h),t.select(\"rect.\"+d.maskMaxClassName).attr(\"x\",f).attr(\"width\",n._width-f),\"match\"!==i.rangemode){var p=n._height-c(n.d2pOppAxis(a._rl[1])),g=n._height-c(n.d2pOppAxis(a._rl[0]));t.select(\"rect.\"+d.maskMinOppAxisClassName).attr(\"x\",h).attr(\"height\",p).attr(\"width\",f-h),t.select(\"rect.\"+d.maskMaxOppAxisClassName).attr(\"x\",h).attr(\"y\",g).attr(\"height\",n._height-g).attr(\"width\",f-h),t.select(\"rect.\"+d.slideBoxClassName).attr(\"y\",p).attr(\"height\",g-p)}var v=Math.round(u(h-s))-.5,m=Math.round(u(f-s))+.5;t.select(\"g.\"+d.grabberMinClassName).attr(\"transform\",\"translate(\"+v+\",0.5)\"),t.select(\"g.\"+d.grabberMaxClassName).attr(\"transform\",\"translate(\"+m+\",0.5)\")}(i,0,r,s,l,u),\"bottom\"===r.side&&c.draw(t,r._id+\"title\",{propContainer:r,propName:r._name+\".title\",placeholder:e._dfltTitle.x,attributes:{x:r._offset+r._length/2,y:S+s._height+s._offsetShift+10+1.5*r.title.font.size,\"text-anchor\":\"middle\"}})}))}},{\"../../lib\":717,\"../../lib/setcursor\":737,\"../../plots/cartesian\":776,\"../../plots/cartesian/axis_ids\":768,\"../../plots/plots\":826,\"../../registry\":846,\"../color\":592,\"../dragelement\":610,\"../drawing\":613,\"../titles\":679,\"./constants\":661,d3:165}],664:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axis_ids\"),a=t(\"../../lib/svg_text_utils\"),i=t(\"./constants\"),o=t(\"../../constants/alignment\").LINE_SPACING,s=i.name;function l(t){var e=t&&t[s];return e&&e.visible}r.isVisible=l,r.makeData=function(t){var e=n.list({_fullLayout:t},\"x\",!0),r=t.margin,a=[];if(!t._has(\"gl2d\"))for(var i=0;i<e.length;i++){var o=e[i];if(l(o)){a.push(o);var c=o[s];c._id=s+o._id,c._height=(t.height-r.b-r.t)*c.thickness,c._offsetShift=Math.floor(c.borderwidth/2)}}t._rangeSliderData=a},r.autoMarginOpts=function(t,e){var r=t._fullLayout,n=e[s],l=e._id.charAt(0),c=0,u=0;\"bottom\"===e.side&&(c=e._depth,e.title.text!==r._dfltTitle[l]&&(u=1.5*e.title.font.size+10+n._offsetShift,u+=(e.title.text.match(a.BR_TAG_ALL)||[]).length*e.title.font.size*o));return{x:0,y:e._counterDomainMin,l:0,r:0,t:0,b:n._height+c+Math.max(r.margin.b,u),pad:i.extraPad+2*n._offsetShift}}},{\"../../constants/alignment\":686,\"../../lib/svg_text_utils\":741,\"../../plots/cartesian/axis_ids\":768,\"./constants\":661}],665:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./attributes\"),i=t(\"./oppaxis_attributes\"),o=t(\"./helpers\");e.exports={moduleType:\"component\",name:\"rangeslider\",schema:{subplots:{xaxis:{rangeslider:n.extendFlat({},a,{yaxis:i})}}},layoutAttributes:t(\"./attributes\"),handleDefaults:t(\"./defaults\"),calcAutorange:t(\"./calc_autorange\"),draw:t(\"./draw\"),isVisible:o.isVisible,makeData:o.makeData,autoMarginOpts:o.autoMarginOpts}},{\"../../lib\":717,\"./attributes\":659,\"./calc_autorange\":660,\"./defaults\":662,\"./draw\":663,\"./helpers\":664,\"./oppaxis_attributes\":666}],666:[function(t,e,r){\"use strict\";e.exports={_isSubplotObj:!0,rangemode:{valType:\"enumerated\",values:[\"auto\",\"fixed\",\"match\"],dflt:\"match\",editType:\"calc\"},range:{valType:\"info_array\",items:[{valType:\"any\",editType:\"plot\"},{valType:\"any\",editType:\"plot\"}],editType:\"plot\"},editType:\"calc\"}},{}],667:[function(t,e,r){\"use strict\";var n=t(\"../annotations/attributes\"),a=t(\"../../traces/scatter/attributes\").line,i=t(\"../drawing/attributes\").dash,o=t(\"../../lib/extend\").extendFlat,s=t(\"../../plot_api/plot_template\").templatedArray;e.exports=s(\"shape\",{visible:{valType:\"boolean\",dflt:!0,editType:\"calc+arraydraw\"},type:{valType:\"enumerated\",values:[\"circle\",\"rect\",\"path\",\"line\"],editType:\"calc+arraydraw\"},layer:{valType:\"enumerated\",values:[\"below\",\"above\"],dflt:\"above\",editType:\"arraydraw\"},xref:o({},n.xref,{}),xsizemode:{valType:\"enumerated\",values:[\"scaled\",\"pixel\"],dflt:\"scaled\",editType:\"calc+arraydraw\"},xanchor:{valType:\"any\",editType:\"calc+arraydraw\"},x0:{valType:\"any\",editType:\"calc+arraydraw\"},x1:{valType:\"any\",editType:\"calc+arraydraw\"},yref:o({},n.yref,{}),ysizemode:{valType:\"enumerated\",values:[\"scaled\",\"pixel\"],dflt:\"scaled\",editType:\"calc+arraydraw\"},yanchor:{valType:\"any\",editType:\"calc+arraydraw\"},y0:{valType:\"any\",editType:\"calc+arraydraw\"},y1:{valType:\"any\",editType:\"calc+arraydraw\"},path:{valType:\"string\",editType:\"calc+arraydraw\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,editType:\"arraydraw\"},line:{color:o({},a.color,{editType:\"arraydraw\"}),width:o({},a.width,{editType:\"calc+arraydraw\"}),dash:o({},i,{editType:\"arraydraw\"}),editType:\"calc+arraydraw\"},fillcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"arraydraw\"},editType:\"arraydraw\"})},{\"../../lib/extend\":708,\"../../plot_api/plot_template\":755,\"../../traces/scatter/attributes\":1120,\"../annotations/attributes\":575,\"../drawing/attributes\":612}],668:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/cartesian/axes\"),i=t(\"./constants\"),o=t(\"./helpers\");function s(t){return c(t.line.width,t.xsizemode,t.x0,t.x1,t.path,!1)}function l(t){return c(t.line.width,t.ysizemode,t.y0,t.y1,t.path,!0)}function c(t,e,r,a,s,l){var c=t/2,u=l;if(\"pixel\"===e){var h=s?o.extractPathCoords(s,l?i.paramIsY:i.paramIsX):[r,a],f=n.aggNums(Math.max,null,h),p=n.aggNums(Math.min,null,h),d=p<0?Math.abs(p)+c:c,g=f>0?f+c:c;return{ppad:c,ppadplus:u?d:g,ppadminus:u?g:d}}return{ppad:c}}function u(t,e,r,n,a){var s=\"category\"===t.type||\"multicategory\"===t.type?t.r2c:t.d2c;if(void 0!==e)return[s(e),s(r)];if(n){var l,c,u,h,f=1/0,p=-1/0,d=n.match(i.segmentRE);for(\"date\"===t.type&&(s=o.decodeDate(s)),l=0;l<d.length;l++)void 0!==(c=a[d[l].charAt(0)].drawn)&&(!(u=d[l].substr(1).match(i.paramRE))||u.length<c||((h=s(u[c]))<f&&(f=h),h>p&&(p=h)));return p>=f?[f,p]:void 0}}e.exports=function(t){var e=t._fullLayout,r=n.filterVisible(e.shapes);if(r.length&&t._fullData.length)for(var o=0;o<r.length;o++){var c,h,f=r[o];if(f._extremes={},\"paper\"!==f.xref){var p=\"pixel\"===f.xsizemode?f.xanchor:f.x0,d=\"pixel\"===f.xsizemode?f.xanchor:f.x1;(h=u(c=a.getFromId(t,f.xref),p,d,f.path,i.paramIsX))&&(f._extremes[c._id]=a.findExtremes(c,h,s(f)))}if(\"paper\"!==f.yref){var g=\"pixel\"===f.ysizemode?f.yanchor:f.y0,v=\"pixel\"===f.ysizemode?f.yanchor:f.y1;(h=u(c=a.getFromId(t,f.yref),g,v,f.path,i.paramIsY))&&(f._extremes[c._id]=a.findExtremes(c,h,l(f)))}}}},{\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"./constants\":669,\"./helpers\":672}],669:[function(t,e,r){\"use strict\";e.exports={segmentRE:/[MLHVQCTSZ][^MLHVQCTSZ]*/g,paramRE:/[^\\s,]+/g,paramIsX:{M:{0:!0,drawn:0},L:{0:!0,drawn:0},H:{0:!0,drawn:0},V:{},Q:{0:!0,2:!0,drawn:2},C:{0:!0,2:!0,4:!0,drawn:4},T:{0:!0,drawn:0},S:{0:!0,2:!0,drawn:2},Z:{}},paramIsY:{M:{1:!0,drawn:1},L:{1:!0,drawn:1},H:{},V:{0:!0,drawn:0},Q:{1:!0,3:!0,drawn:3},C:{1:!0,3:!0,5:!0,drawn:5},T:{1:!0,drawn:1},S:{1:!0,3:!0,drawn:5},Z:{}},numParams:{M:2,L:2,H:1,V:1,Q:4,C:6,T:2,S:4,Z:0}}},{}],670:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/cartesian/axes\"),i=t(\"../../plots/array_container_defaults\"),o=t(\"./attributes\"),s=t(\"./helpers\");function l(t,e,r){function i(r,a){return n.coerce(t,e,o,r,a)}if(i(\"visible\")){i(\"layer\"),i(\"opacity\"),i(\"fillcolor\"),i(\"line.color\"),i(\"line.width\"),i(\"line.dash\");for(var l=i(\"type\",t.path?\"path\":\"rect\"),c=i(\"xsizemode\"),u=i(\"ysizemode\"),h=[\"x\",\"y\"],f=0;f<2;f++){var p,d,g,v=h[f],m=v+\"anchor\",y=\"x\"===v?c:u,x={_fullLayout:r},b=a.coerceRef(t,e,x,v,\"\",\"paper\");if(\"paper\"!==b?((p=a.getFromId(x,b))._shapeIndices.push(e._index),g=s.rangeToShapePosition(p),d=s.shapePositionToRange(p)):d=g=n.identity,\"path\"!==l){var _=v+\"0\",w=v+\"1\",k=t[_],T=t[w];t[_]=d(t[_],!0),t[w]=d(t[w],!0),\"pixel\"===y?(i(_,0),i(w,10)):(a.coercePosition(e,x,i,b,_,.25),a.coercePosition(e,x,i,b,w,.75)),e[_]=g(e[_]),e[w]=g(e[w]),t[_]=k,t[w]=T}if(\"pixel\"===y){var M=t[m];t[m]=d(t[m],!0),a.coercePosition(e,x,i,b,m,.25),e[m]=g(e[m]),t[m]=M}}\"path\"===l?i(\"path\"):n.noneOrAll(t,e,[\"x0\",\"x1\",\"y0\",\"y1\"])}}e.exports=function(t,e){i(t,e,{name:\"shapes\",handleItemDefaults:l})}},{\"../../lib\":717,\"../../plots/array_container_defaults\":761,\"../../plots/cartesian/axes\":765,\"./attributes\":667,\"./helpers\":672}],671:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../lib\"),i=t(\"../../plots/cartesian/axes\"),o=t(\"../color\"),s=t(\"../drawing\"),l=t(\"../../plot_api/plot_template\").arrayEditor,c=t(\"../dragelement\"),u=t(\"../../lib/setcursor\"),h=t(\"./constants\"),f=t(\"./helpers\");function p(t,e){t._fullLayout._paperdiv.selectAll('.shapelayer [data-index=\"'+e+'\"]').remove();var r=t._fullLayout.shapes[e]||{};if(r._input&&!1!==r.visible)if(\"below\"!==r.layer)m(t._fullLayout._shapeUpperLayer);else if(\"paper\"===r.xref||\"paper\"===r.yref)m(t._fullLayout._shapeLowerLayer);else{var p=t._fullLayout._plots[r.xref+r.yref];if(p)m((p.mainplotinfo||p).shapelayer);else m(t._fullLayout._shapeLowerLayer)}function m(p){var m={\"data-index\":e,\"fill-rule\":\"evenodd\",d:g(t,r)},y=r.line.width?r.line.color:\"rgba(0,0,0,0)\",x=p.append(\"path\").attr(m).style(\"opacity\",r.opacity).call(o.stroke,y).call(o.fill,r.fillcolor).call(s.dashLine,r.line.dash,r.line.width);d(x,t,r),t._context.edits.shapePosition&&function(t,e,r,o,p){var m,y,x,b,_,w,k,T,M,A,S,E,L,C,P,O,z=10,I=10,D=\"pixel\"===r.xsizemode,R=\"pixel\"===r.ysizemode,F=\"line\"===r.type,B=\"path\"===r.type,N=l(t.layout,\"shapes\",r),j=N.modifyItem,V=i.getFromId(t,r.xref),U=i.getFromId(t,r.yref),q=f.getDataToPixel(t,V),H=f.getDataToPixel(t,U,!0),G=f.getPixelToData(t,V),Y=f.getPixelToData(t,U,!0),W=F?function(){var t=Math.max(r.line.width,10),n=p.append(\"g\").attr(\"data-index\",o);n.append(\"path\").attr(\"d\",e.attr(\"d\")).style({cursor:\"move\",\"stroke-width\":t,\"stroke-opacity\":\"0\"});var a={\"fill-opacity\":\"0\"},i=t/2>10?t/2:10;return n.append(\"circle\").attr({\"data-line-point\":\"start-point\",cx:D?q(r.xanchor)+r.x0:q(r.x0),cy:R?H(r.yanchor)-r.y0:H(r.y0),r:i}).style(a).classed(\"cursor-grab\",!0),n.append(\"circle\").attr({\"data-line-point\":\"end-point\",cx:D?q(r.xanchor)+r.x1:q(r.x1),cy:R?H(r.yanchor)-r.y1:H(r.y1),r:i}).style(a).classed(\"cursor-grab\",!0),n}():e,X={element:W.node(),gd:t,prepFn:function(n){D&&(_=q(r.xanchor));R&&(w=H(r.yanchor));\"path\"===r.type?P=r.path:(m=D?r.x0:q(r.x0),y=R?r.y0:H(r.y0),x=D?r.x1:q(r.x1),b=R?r.y1:H(r.y1));m<x?(M=m,L=\"x0\",A=x,C=\"x1\"):(M=x,L=\"x1\",A=m,C=\"x0\");!R&&y<b||R&&y>b?(k=y,S=\"y0\",T=b,E=\"y1\"):(k=b,S=\"y1\",T=y,E=\"y0\");Z(n),Q(p,r),function(t,e,r){var n=e.xref,a=e.yref,o=i.getFromId(r,n),l=i.getFromId(r,a),c=\"\";\"paper\"===n||o.autorange||(c+=n);\"paper\"===a||l.autorange||(c+=a);s.setClipUrl(t,c?\"clip\"+r._fullLayout._uid+c:null,r)}(e,r,t),X.moveFn=\"move\"===O?J:K},doneFn:function(){u(e),$(p),d(e,t,r),n.call(\"_guiRelayout\",t,N.getUpdateObj())},clickFn:function(){$(p)}};function Z(t){if(F)O=\"path\"===t.target.tagName?\"move\":\"start-point\"===t.target.attributes[\"data-line-point\"].value?\"resize-over-start-point\":\"resize-over-end-point\";else{var r=X.element.getBoundingClientRect(),n=r.right-r.left,a=r.bottom-r.top,i=t.clientX-r.left,o=t.clientY-r.top,s=!B&&n>z&&a>I&&!t.shiftKey?c.getCursor(i/n,1-o/a):\"move\";u(e,s),O=s.split(\"-\")[0]}}function J(n,a){if(\"path\"===r.type){var i=function(t){return t},o=i,s=i;D?j(\"xanchor\",r.xanchor=G(_+n)):(o=function(t){return G(q(t)+n)},V&&\"date\"===V.type&&(o=f.encodeDate(o))),R?j(\"yanchor\",r.yanchor=Y(w+a)):(s=function(t){return Y(H(t)+a)},U&&\"date\"===U.type&&(s=f.encodeDate(s))),j(\"path\",r.path=v(P,o,s))}else D?j(\"xanchor\",r.xanchor=G(_+n)):(j(\"x0\",r.x0=G(m+n)),j(\"x1\",r.x1=G(x+n))),R?j(\"yanchor\",r.yanchor=Y(w+a)):(j(\"y0\",r.y0=Y(y+a)),j(\"y1\",r.y1=Y(b+a)));e.attr(\"d\",g(t,r)),Q(p,r)}function K(n,a){if(B){var i=function(t){return t},o=i,s=i;D?j(\"xanchor\",r.xanchor=G(_+n)):(o=function(t){return G(q(t)+n)},V&&\"date\"===V.type&&(o=f.encodeDate(o))),R?j(\"yanchor\",r.yanchor=Y(w+a)):(s=function(t){return Y(H(t)+a)},U&&\"date\"===U.type&&(s=f.encodeDate(s))),j(\"path\",r.path=v(P,o,s))}else if(F){if(\"resize-over-start-point\"===O){var l=m+n,c=R?y-a:y+a;j(\"x0\",r.x0=D?l:G(l)),j(\"y0\",r.y0=R?c:Y(c))}else if(\"resize-over-end-point\"===O){var u=x+n,h=R?b-a:b+a;j(\"x1\",r.x1=D?u:G(u)),j(\"y1\",r.y1=R?h:Y(h))}}else{var d=~O.indexOf(\"n\")?k+a:k,N=~O.indexOf(\"s\")?T+a:T,W=~O.indexOf(\"w\")?M+n:M,X=~O.indexOf(\"e\")?A+n:A;~O.indexOf(\"n\")&&R&&(d=k-a),~O.indexOf(\"s\")&&R&&(N=T-a),(!R&&N-d>I||R&&d-N>I)&&(j(S,r[S]=R?d:Y(d)),j(E,r[E]=R?N:Y(N))),X-W>z&&(j(L,r[L]=D?W:G(W)),j(C,r[C]=D?X:G(X)))}e.attr(\"d\",g(t,r)),Q(p,r)}function Q(t,e){(D||R)&&function(){var r=\"path\"!==e.type,n=t.selectAll(\".visual-cue\").data([0]);n.enter().append(\"path\").attr({fill:\"#fff\",\"fill-rule\":\"evenodd\",stroke:\"#000\",\"stroke-width\":1}).classed(\"visual-cue\",!0);var i=q(D?e.xanchor:a.midRange(r?[e.x0,e.x1]:f.extractPathCoords(e.path,h.paramIsX))),o=H(R?e.yanchor:a.midRange(r?[e.y0,e.y1]:f.extractPathCoords(e.path,h.paramIsY)));if(i=f.roundPositionForSharpStrokeRendering(i,1),o=f.roundPositionForSharpStrokeRendering(o,1),D&&R){var s=\"M\"+(i-1-1)+\",\"+(o-1-1)+\"h-8v2h8 v8h2v-8 h8v-2h-8 v-8h-2 Z\";n.attr(\"d\",s)}else if(D){var l=\"M\"+(i-1-1)+\",\"+(o-9-1)+\"v18 h2 v-18 Z\";n.attr(\"d\",l)}else{var c=\"M\"+(i-9-1)+\",\"+(o-1-1)+\"h18 v2 h-18 Z\";n.attr(\"d\",c)}}()}function $(t){t.selectAll(\".visual-cue\").remove()}c.init(X),W.node().onmousemove=Z}(t,x,r,e,p)}}function d(t,e,r){var n=(r.xref+r.yref).replace(/paper/g,\"\");s.setClipUrl(t,n?\"clip\"+e._fullLayout._uid+n:null,e)}function g(t,e){var r,n,o,s,l,c,u,p,d=e.type,g=i.getFromId(t,e.xref),v=i.getFromId(t,e.yref),m=t._fullLayout._size;if(g?(r=f.shapePositionToRange(g),n=function(t){return g._offset+g.r2p(r(t,!0))}):n=function(t){return m.l+m.w*t},v?(o=f.shapePositionToRange(v),s=function(t){return v._offset+v.r2p(o(t,!0))}):s=function(t){return m.t+m.h*(1-t)},\"path\"===d)return g&&\"date\"===g.type&&(n=f.decodeDate(n)),v&&\"date\"===v.type&&(s=f.decodeDate(s)),function(t,e,r){var n=t.path,i=t.xsizemode,o=t.ysizemode,s=t.xanchor,l=t.yanchor;return n.replace(h.segmentRE,function(t){var n=0,c=t.charAt(0),u=h.paramIsX[c],f=h.paramIsY[c],p=h.numParams[c],d=t.substr(1).replace(h.paramRE,function(t){return u[n]?t=\"pixel\"===i?e(s)+Number(t):e(t):f[n]&&(t=\"pixel\"===o?r(l)-Number(t):r(t)),++n>p&&(t=\"X\"),t});return n>p&&(d=d.replace(/[\\s,]*X.*/,\"\"),a.log(\"Ignoring extra params in segment \"+t)),c+d})}(e,n,s);if(\"pixel\"===e.xsizemode){var y=n(e.xanchor);l=y+e.x0,c=y+e.x1}else l=n(e.x0),c=n(e.x1);if(\"pixel\"===e.ysizemode){var x=s(e.yanchor);u=x-e.y0,p=x-e.y1}else u=s(e.y0),p=s(e.y1);if(\"line\"===d)return\"M\"+l+\",\"+u+\"L\"+c+\",\"+p;if(\"rect\"===d)return\"M\"+l+\",\"+u+\"H\"+c+\"V\"+p+\"H\"+l+\"Z\";var b=(l+c)/2,_=(u+p)/2,w=Math.abs(b-l),k=Math.abs(_-u),T=\"A\"+w+\",\"+k,M=b+w+\",\"+_;return\"M\"+M+T+\" 0 1,1 \"+(b+\",\"+(_-k))+T+\" 0 0,1 \"+M+\"Z\"}function v(t,e,r){return t.replace(h.segmentRE,function(t){var n=0,a=t.charAt(0),i=h.paramIsX[a],o=h.paramIsY[a],s=h.numParams[a];return a+t.substr(1).replace(h.paramRE,function(t){return n>=s?t:(i[n]?t=e(t):o[n]&&(t=r(t)),n++,t)})})}e.exports={draw:function(t){var e=t._fullLayout;for(var r in e._shapeUpperLayer.selectAll(\"path\").remove(),e._shapeLowerLayer.selectAll(\"path\").remove(),e._plots){var n=e._plots[r].shapelayer;n&&n.selectAll(\"path\").remove()}for(var a=0;a<e.shapes.length;a++)e.shapes[a].visible&&p(t,a)},drawOne:p}},{\"../../lib\":717,\"../../lib/setcursor\":737,\"../../plot_api/plot_template\":755,\"../../plots/cartesian/axes\":765,\"../../registry\":846,\"../color\":592,\"../dragelement\":610,\"../drawing\":613,\"./constants\":669,\"./helpers\":672}],672:[function(t,e,r){\"use strict\";var n=t(\"./constants\"),a=t(\"../../lib\");r.rangeToShapePosition=function(t){return\"log\"===t.type?t.r2d:function(t){return t}},r.shapePositionToRange=function(t){return\"log\"===t.type?t.d2r:function(t){return t}},r.decodeDate=function(t){return function(e){return e.replace&&(e=e.replace(\"_\",\" \")),t(e)}},r.encodeDate=function(t){return function(e){return t(e).replace(\" \",\"_\")}},r.extractPathCoords=function(t,e){var r=[];return t.match(n.segmentRE).forEach(function(t){var i=e[t.charAt(0)].drawn;if(void 0!==i){var o=t.substr(1).match(n.paramRE);!o||o.length<i||r.push(a.cleanNumber(o[i]))}}),r},r.getDataToPixel=function(t,e,n){var a,i=t._fullLayout._size;if(e){var o=r.shapePositionToRange(e);a=function(t){return e._offset+e.r2p(o(t,!0))},\"date\"===e.type&&(a=r.decodeDate(a))}else a=n?function(t){return i.t+i.h*(1-t)}:function(t){return i.l+i.w*t};return a},r.getPixelToData=function(t,e,n){var a,i=t._fullLayout._size;if(e){var o=r.rangeToShapePosition(e);a=function(t){return o(e.p2r(t-e._offset))}}else a=n?function(t){return 1-(t-i.t)/i.h}:function(t){return(t-i.l)/i.w};return a},r.roundPositionForSharpStrokeRendering=function(t,e){var r=1===Math.round(e%2),n=Math.round(t);return r?n+.5:n}},{\"../../lib\":717,\"./constants\":669}],673:[function(t,e,r){\"use strict\";var n=t(\"./draw\");e.exports={moduleType:\"component\",name:\"shapes\",layoutAttributes:t(\"./attributes\"),supplyLayoutDefaults:t(\"./defaults\"),includeBasePlot:t(\"../../plots/cartesian/include_components\")(\"shapes\"),calcAutorange:t(\"./calc_autorange\"),draw:n.draw,drawOne:n.drawOne}},{\"../../plots/cartesian/include_components\":775,\"./attributes\":667,\"./calc_autorange\":668,\"./defaults\":670,\"./draw\":671}],674:[function(t,e,r){\"use strict\";var n=t(\"../../plots/font_attributes\"),a=t(\"../../plots/pad_attributes\"),i=t(\"../../lib/extend\").extendDeepAll,o=t(\"../../plot_api/edit_types\").overrideAll,s=t(\"../../plots/animation_attributes\"),l=t(\"../../plot_api/plot_template\").templatedArray,c=t(\"./constants\"),u=l(\"step\",{visible:{valType:\"boolean\",dflt:!0},method:{valType:\"enumerated\",values:[\"restyle\",\"relayout\",\"animate\",\"update\",\"skip\"],dflt:\"restyle\"},args:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},label:{valType:\"string\"},value:{valType:\"string\"},execute:{valType:\"boolean\",dflt:!0}});e.exports=o(l(\"slider\",{visible:{valType:\"boolean\",dflt:!0},active:{valType:\"number\",min:0,dflt:0},steps:u,lenmode:{valType:\"enumerated\",values:[\"fraction\",\"pixels\"],dflt:\"fraction\"},len:{valType:\"number\",min:0,dflt:1},x:{valType:\"number\",min:-2,max:3,dflt:0},pad:i(a({editType:\"arraydraw\"}),{},{t:{dflt:20}}),xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\"},y:{valType:\"number\",min:-2,max:3,dflt:0},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"top\"},transition:{duration:{valType:\"number\",min:0,dflt:150},easing:{valType:\"enumerated\",values:s.transition.easing.values,dflt:\"cubic-in-out\"}},currentvalue:{visible:{valType:\"boolean\",dflt:!0},xanchor:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"left\"},offset:{valType:\"number\",dflt:10},prefix:{valType:\"string\"},suffix:{valType:\"string\"},font:n({})},font:n({}),activebgcolor:{valType:\"color\",dflt:c.gripBgActiveColor},bgcolor:{valType:\"color\",dflt:c.railBgColor},bordercolor:{valType:\"color\",dflt:c.railBorderColor},borderwidth:{valType:\"number\",min:0,dflt:c.railBorderWidth},ticklen:{valType:\"number\",min:0,dflt:c.tickLength},tickcolor:{valType:\"color\",dflt:c.tickColor},tickwidth:{valType:\"number\",min:0,dflt:1},minorticklen:{valType:\"number\",min:0,dflt:c.minorTickLength}}),\"arraydraw\",\"from-root\")},{\"../../lib/extend\":708,\"../../plot_api/edit_types\":748,\"../../plot_api/plot_template\":755,\"../../plots/animation_attributes\":760,\"../../plots/font_attributes\":791,\"../../plots/pad_attributes\":825,\"./constants\":675}],675:[function(t,e,r){\"use strict\";e.exports={name:\"sliders\",containerClassName:\"slider-container\",groupClassName:\"slider-group\",inputAreaClass:\"slider-input-area\",railRectClass:\"slider-rail-rect\",railTouchRectClass:\"slider-rail-touch-rect\",gripRectClass:\"slider-grip-rect\",tickRectClass:\"slider-tick-rect\",inputProxyClass:\"slider-input-proxy\",labelsClass:\"slider-labels\",labelGroupClass:\"slider-label-group\",labelClass:\"slider-label\",currentValueClass:\"slider-current-value\",railHeight:5,menuIndexAttrName:\"slider-active-index\",autoMarginIdRoot:\"slider-\",minWidth:30,minHeight:30,textPadX:40,arrowOffsetX:4,railRadius:2,railWidth:5,railBorder:4,railBorderWidth:1,railBorderColor:\"#bec8d9\",railBgColor:\"#f8fafc\",railInset:8,stepInset:10,gripRadius:10,gripWidth:20,gripHeight:20,gripBorder:20,gripBorderWidth:1,gripBorderColor:\"#bec8d9\",gripBgColor:\"#f6f8fa\",gripBgActiveColor:\"#dbdde0\",labelPadding:8,labelOffset:0,tickWidth:1,tickColor:\"#333\",tickOffset:25,tickLength:7,minorTickOffset:25,minorTickColor:\"#333\",minorTickLength:4,currentValuePadding:8,currentValueInset:0}},{}],676:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/array_container_defaults\"),i=t(\"./attributes\"),o=t(\"./constants\").name,s=i.steps;function l(t,e,r){function o(r,a){return n.coerce(t,e,i,r,a)}for(var s=a(t,e,{name:\"steps\",handleItemDefaults:c}),l=0,u=0;u<s.length;u++)s[u].visible&&l++;if(l<2?e.visible=!1:o(\"visible\")){e._stepCount=l;var h=e._visibleSteps=n.filterVisible(s);(s[o(\"active\")]||{}).visible||(e.active=h[0]._index),o(\"x\"),o(\"y\"),n.noneOrAll(t,e,[\"x\",\"y\"]),o(\"xanchor\"),o(\"yanchor\"),o(\"len\"),o(\"lenmode\"),o(\"pad.t\"),o(\"pad.r\"),o(\"pad.b\"),o(\"pad.l\"),n.coerceFont(o,\"font\",r.font),o(\"currentvalue.visible\")&&(o(\"currentvalue.xanchor\"),o(\"currentvalue.prefix\"),o(\"currentvalue.suffix\"),o(\"currentvalue.offset\"),n.coerceFont(o,\"currentvalue.font\",e.font)),o(\"transition.duration\"),o(\"transition.easing\"),o(\"bgcolor\"),o(\"activebgcolor\"),o(\"bordercolor\"),o(\"borderwidth\"),o(\"ticklen\"),o(\"tickwidth\"),o(\"tickcolor\"),o(\"minorticklen\")}}function c(t,e){function r(r,a){return n.coerce(t,e,s,r,a)}if(\"skip\"===t.method||Array.isArray(t.args)?r(\"visible\"):e.visible=!1){r(\"method\"),r(\"args\");var a=r(\"label\",\"step-\"+e._index);r(\"value\",a),r(\"execute\")}}e.exports=function(t,e){a(t,e,{name:o,handleItemDefaults:l})}},{\"../../lib\":717,\"../../plots/array_container_defaults\":761,\"./attributes\":674,\"./constants\":675}],677:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../plots/plots\"),i=t(\"../color\"),o=t(\"../drawing\"),s=t(\"../../lib\"),l=t(\"../../lib/svg_text_utils\"),c=t(\"../../plot_api/plot_template\").arrayEditor,u=t(\"./constants\"),h=t(\"../../constants/alignment\"),f=h.LINE_SPACING,p=h.FROM_TL,d=h.FROM_BR;function g(t){return u.autoMarginIdRoot+t._index}function v(t){return t._index}function m(t,e){var r=o.tester.selectAll(\"g.\"+u.labelGroupClass).data(e._visibleSteps);r.enter().append(\"g\").classed(u.labelGroupClass,!0);var i=0,c=0;r.each(function(t){var r=b(n.select(this),{step:t},e).node();if(r){var a=o.bBox(r);c=Math.max(c,a.height),i=Math.max(i,a.width)}}),r.remove();var h=e._dims={};h.inputAreaWidth=Math.max(u.railWidth,u.gripHeight);var f=t._fullLayout._size;h.lx=f.l+f.w*e.x,h.ly=f.t+f.h*(1-e.y),\"fraction\"===e.lenmode?h.outerLength=Math.round(f.w*e.len):h.outerLength=e.len,h.inputAreaStart=0,h.inputAreaLength=Math.round(h.outerLength-e.pad.l-e.pad.r);var v=(h.inputAreaLength-2*u.stepInset)/(e._stepCount-1),m=i+u.labelPadding;if(h.labelStride=Math.max(1,Math.ceil(m/v)),h.labelHeight=c,h.currentValueMaxWidth=0,h.currentValueHeight=0,h.currentValueTotalHeight=0,h.currentValueMaxLines=1,e.currentvalue.visible){var x=o.tester.append(\"g\");r.each(function(t){var r=y(x,e,t.label),n=r.node()&&o.bBox(r.node())||{width:0,height:0},a=l.lineCount(r);h.currentValueMaxWidth=Math.max(h.currentValueMaxWidth,Math.ceil(n.width)),h.currentValueHeight=Math.max(h.currentValueHeight,Math.ceil(n.height)),h.currentValueMaxLines=Math.max(h.currentValueMaxLines,a)}),h.currentValueTotalHeight=h.currentValueHeight+e.currentvalue.offset,x.remove()}h.height=h.currentValueTotalHeight+u.tickOffset+e.ticklen+u.labelOffset+h.labelHeight+e.pad.t+e.pad.b;var _=\"left\";s.isRightAnchor(e)&&(h.lx-=h.outerLength,_=\"right\"),s.isCenterAnchor(e)&&(h.lx-=h.outerLength/2,_=\"center\");var w=\"top\";s.isBottomAnchor(e)&&(h.ly-=h.height,w=\"bottom\"),s.isMiddleAnchor(e)&&(h.ly-=h.height/2,w=\"middle\"),h.outerLength=Math.ceil(h.outerLength),h.height=Math.ceil(h.height),h.lx=Math.round(h.lx),h.ly=Math.round(h.ly);var k={y:e.y,b:h.height*d[w],t:h.height*p[w]};\"fraction\"===e.lenmode?(k.l=0,k.xl=e.x-e.len*p[_],k.r=0,k.xr=e.x+e.len*d[_]):(k.x=e.x,k.l=h.outerLength*p[_],k.r=h.outerLength*d[_]),a.autoMargin(t,g(e),k)}function y(t,e,r){if(e.currentvalue.visible){var n,a,i=e._dims;switch(e.currentvalue.xanchor){case\"right\":n=i.inputAreaLength-u.currentValueInset-i.currentValueMaxWidth,a=\"left\";break;case\"center\":n=.5*i.inputAreaLength,a=\"middle\";break;default:n=u.currentValueInset,a=\"left\"}var c=s.ensureSingle(t,\"text\",u.labelClass,function(t){t.classed(\"user-select-none\",!0).attr({\"text-anchor\":a,\"data-notex\":1})}),h=e.currentvalue.prefix?e.currentvalue.prefix:\"\";if(\"string\"==typeof r)h+=r;else{var p=e.steps[e.active].label,d=e._gd._fullLayout._meta;d&&(p=s.templateString(p,d)),h+=p}e.currentvalue.suffix&&(h+=e.currentvalue.suffix),c.call(o.font,e.currentvalue.font).text(h).call(l.convertToTspans,e._gd);var g=l.lineCount(c),v=(i.currentValueMaxLines+1-g)*e.currentvalue.font.size*f;return l.positionText(c,n,v),c}}function x(t,e,r){s.ensureSingle(t,\"rect\",u.gripRectClass,function(n){n.call(T,e,t,r).style(\"pointer-events\",\"all\")}).attr({width:u.gripWidth,height:u.gripHeight,rx:u.gripRadius,ry:u.gripRadius}).call(i.stroke,r.bordercolor).call(i.fill,r.bgcolor).style(\"stroke-width\",r.borderwidth+\"px\")}function b(t,e,r){var n=s.ensureSingle(t,\"text\",u.labelClass,function(t){t.classed(\"user-select-none\",!0).attr({\"text-anchor\":\"middle\",\"data-notex\":1})}),a=e.step.label,i=r._gd._fullLayout._meta;return i&&(a=s.templateString(a,i)),n.call(o.font,r.font).text(a).call(l.convertToTspans,r._gd),n}function _(t,e){var r=s.ensureSingle(t,\"g\",u.labelsClass),a=e._dims,i=r.selectAll(\"g.\"+u.labelGroupClass).data(a.labelSteps);i.enter().append(\"g\").classed(u.labelGroupClass,!0),i.exit().remove(),i.each(function(t){var r=n.select(this);r.call(b,t,e),o.setTranslate(r,S(e,t.fraction),u.tickOffset+e.ticklen+e.font.size*f+u.labelOffset+a.currentValueTotalHeight)})}function w(t,e,r,n,a){var i=Math.round(n*(r._stepCount-1)),o=r._visibleSteps[i]._index;o!==r.active&&k(t,e,r,o,!0,a)}function k(t,e,r,n,i,o){var s=r.active;r.active=n,c(t.layout,u.name,r).applyUpdate(\"active\",n);var l=r.steps[r.active];e.call(A,r,o),e.call(y,r),t.emit(\"plotly_sliderchange\",{slider:r,step:r.steps[r.active],interaction:i,previousActive:s}),l&&l.method&&i&&(e._nextMethod?(e._nextMethod.step=l,e._nextMethod.doCallback=i,e._nextMethod.doTransition=o):(e._nextMethod={step:l,doCallback:i,doTransition:o},e._nextMethodRaf=window.requestAnimationFrame(function(){var r=e._nextMethod.step;r.method&&(r.execute&&a.executeAPICommand(t,r.method,r.args),e._nextMethod=null,e._nextMethodRaf=null)})))}function T(t,e,r){var a=r.node(),o=n.select(e);function s(){return r.data()[0]}t.on(\"mousedown\",function(){var t=s();e.emit(\"plotly_sliderstart\",{slider:t});var l=r.select(\".\"+u.gripRectClass);n.event.stopPropagation(),n.event.preventDefault(),l.call(i.fill,t.activebgcolor);var c=E(t,n.mouse(a)[0]);w(e,r,t,c,!0),t._dragging=!0,o.on(\"mousemove\",function(){var t=s(),i=E(t,n.mouse(a)[0]);w(e,r,t,i,!1)}),o.on(\"mouseup\",function(){var t=s();t._dragging=!1,l.call(i.fill,t.bgcolor),o.on(\"mouseup\",null),o.on(\"mousemove\",null),e.emit(\"plotly_sliderend\",{slider:t,step:t.steps[t.active]})})})}function M(t,e){var r=t.selectAll(\"rect.\"+u.tickRectClass).data(e._visibleSteps),a=e._dims;r.enter().append(\"rect\").classed(u.tickRectClass,!0),r.exit().remove(),r.attr({width:e.tickwidth+\"px\",\"shape-rendering\":\"crispEdges\"}),r.each(function(t,r){var s=r%a.labelStride==0,l=n.select(this);l.attr({height:s?e.ticklen:e.minorticklen}).call(i.fill,e.tickcolor),o.setTranslate(l,S(e,r/(e._stepCount-1))-.5*e.tickwidth,(s?u.tickOffset:u.minorTickOffset)+a.currentValueTotalHeight)})}function A(t,e,r){for(var n=t.select(\"rect.\"+u.gripRectClass),a=0,i=0;i<e._stepCount;i++)if(e._visibleSteps[i]._index===e.active){a=i;break}var o=S(e,a/(e._stepCount-1));if(!e._invokingCommand){var s=n;r&&e.transition.duration>0&&(s=s.transition().duration(e.transition.duration).ease(e.transition.easing)),s.attr(\"transform\",\"translate(\"+(o-.5*u.gripWidth)+\",\"+e._dims.currentValueTotalHeight+\")\")}}function S(t,e){var r=t._dims;return r.inputAreaStart+u.stepInset+(r.inputAreaLength-2*u.stepInset)*Math.min(1,Math.max(0,e))}function E(t,e){var r=t._dims;return Math.min(1,Math.max(0,(e-u.stepInset-r.inputAreaStart)/(r.inputAreaLength-2*u.stepInset-2*r.inputAreaStart)))}function L(t,e,r){var n=r._dims,a=s.ensureSingle(t,\"rect\",u.railTouchRectClass,function(n){n.call(T,e,t,r).style(\"pointer-events\",\"all\")});a.attr({width:n.inputAreaLength,height:Math.max(n.inputAreaWidth,u.tickOffset+r.ticklen+n.labelHeight)}).call(i.fill,r.bgcolor).attr(\"opacity\",0),o.setTranslate(a,0,n.currentValueTotalHeight)}function C(t,e){var r=e._dims,n=r.inputAreaLength-2*u.railInset,a=s.ensureSingle(t,\"rect\",u.railRectClass);a.attr({width:n,height:u.railWidth,rx:u.railRadius,ry:u.railRadius,\"shape-rendering\":\"crispEdges\"}).call(i.stroke,e.bordercolor).call(i.fill,e.bgcolor).style(\"stroke-width\",e.borderwidth+\"px\"),o.setTranslate(a,u.railInset,.5*(r.inputAreaWidth-u.railWidth)+r.currentValueTotalHeight)}e.exports=function(t){var e=t._fullLayout,r=function(t,e){for(var r=t[u.name],n=[],a=0;a<r.length;a++){var i=r[a];i.visible&&(i._gd=e,n.push(i))}return n}(e,t),i=e._infolayer.selectAll(\"g.\"+u.containerClassName).data(r.length>0?[0]:[]);function s(e){e._commandObserver&&(e._commandObserver.remove(),delete e._commandObserver),a.autoMargin(t,g(e))}if(i.enter().append(\"g\").classed(u.containerClassName,!0).style(\"cursor\",\"ew-resize\"),i.exit().each(function(){n.select(this).selectAll(\"g.\"+u.groupClassName).each(s)}).remove(),0!==r.length){var l=i.selectAll(\"g.\"+u.groupClassName).data(r,v);l.enter().append(\"g\").classed(u.groupClassName,!0),l.exit().each(s).remove();for(var c=0;c<r.length;c++){var h=r[c];m(t,h)}l.each(function(e){var r=n.select(this);!function(t){var e=t._dims;e.labelSteps=[];for(var r=t._stepCount,n=0;n<r;n+=e.labelStride)e.labelSteps.push({fraction:n/(r-1),step:t._visibleSteps[n]})}(e),a.manageCommandObserver(t,e,e._visibleSteps,function(e){var n=r.data()[0];n.active!==e.index&&(n._dragging||k(t,r,n,e.index,!1,!0))}),function(t,e,r){(r.steps[r.active]||{}).visible||(r.active=r._visibleSteps[0]._index);e.call(y,r).call(C,r).call(_,r).call(M,r).call(L,t,r).call(x,t,r);var n=r._dims;o.setTranslate(e,n.lx+r.pad.l,n.ly+r.pad.t),e.call(A,r,!1),e.call(y,r)}(t,n.select(this),e)})}}},{\"../../constants/alignment\":686,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"../../plot_api/plot_template\":755,\"../../plots/plots\":826,\"../color\":592,\"../drawing\":613,\"./constants\":675,d3:165}],678:[function(t,e,r){\"use strict\";var n=t(\"./constants\");e.exports={moduleType:\"component\",name:n.name,layoutAttributes:t(\"./attributes\"),supplyLayoutDefaults:t(\"./defaults\"),draw:t(\"./draw\")}},{\"./attributes\":674,\"./constants\":675,\"./defaults\":676,\"./draw\":677}],679:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"fast-isnumeric\"),i=t(\"../../plots/plots\"),o=t(\"../../registry\"),s=t(\"../../lib\"),l=t(\"../drawing\"),c=t(\"../color\"),u=t(\"../../lib/svg_text_utils\"),h=t(\"../../constants/interactions\"),f=t(\"../../constants/alignment\").OPPOSITE_SIDE,p=/ [XY][0-9]* /;e.exports={draw:function(t,e,r){var d,g=r.propContainer,v=r.propName,m=r.placeholder,y=r.traceIndex,x=r.avoid||{},b=r.attributes,_=r.transform,w=r.containerGroup,k=t._fullLayout,T=1,M=!1,A=g.title,S=(A&&A.text?A.text:\"\").trim(),E=A&&A.font?A.font:{},L=E.family,C=E.size,P=E.color;\"title.text\"===v?d=\"titleText\":-1!==v.indexOf(\"axis\")?d=\"axisTitleText\":v.indexOf(!0)&&(d=\"colorbarTitleText\");var O=t._context.edits[d];\"\"===S?T=0:S.replace(p,\" % \")===m.replace(p,\" % \")&&(T=.2,M=!0,O||(S=\"\")),r._meta?S=s.templateString(S,r._meta):k._meta&&(S=s.templateString(S,k._meta));var z=S||O;w||(w=s.ensureSingle(k._infolayer,\"g\",\"g-\"+e));var I=w.selectAll(\"text\").data(z?[0]:[]);if(I.enter().append(\"text\"),I.text(S).attr(\"class\",e),I.exit().remove(),!z)return w;function D(t){s.syncOrAsync([R,F],t)}function R(e){var r;return _?(r=\"\",_.rotate&&(r+=\"rotate(\"+[_.rotate,b.x,b.y]+\")\"),_.offset&&(r+=\"translate(0, \"+_.offset+\")\")):r=null,e.attr(\"transform\",r),e.style({\"font-family\":L,\"font-size\":n.round(C,2)+\"px\",fill:c.rgb(P),opacity:T*c.opacity(P),\"font-weight\":i.fontWeight}).attr(b).call(u.convertToTspans,t),i.previousPromises(t)}function F(t){var e=n.select(t.node().parentNode);if(x&&x.selection&&x.side&&S){e.attr(\"transform\",null);var r=f[x.side],i=\"left\"===x.side||\"top\"===x.side?-1:1,o=a(x.pad)?x.pad:2,c=l.bBox(e.node()),u={left:0,top:0,right:k.width,bottom:k.height},h=x.maxShift||i*(u[x.side]-c[x.side]),p=0;if(h<0)p=h;else{var d=x.offsetLeft||0,g=x.offsetTop||0;c.left-=d,c.right-=d,c.top-=g,c.bottom-=g,x.selection.each(function(){var t=l.bBox(this);s.bBoxIntersect(c,t,o)&&(p=Math.max(p,i*(t[x.side]-c[r])+o))}),p=Math.min(h,p)}if(p>0||h<0){var v={left:[-p,0],right:[p,0],top:[0,-p],bottom:[0,p]}[x.side];e.attr(\"transform\",\"translate(\"+v+\")\")}}}return I.call(D),O&&(S?I.on(\".opacity\",null):(T=0,M=!0,I.text(m).on(\"mouseover.opacity\",function(){n.select(this).transition().duration(h.SHOW_PLACEHOLDER).style(\"opacity\",1)}).on(\"mouseout.opacity\",function(){n.select(this).transition().duration(h.HIDE_PLACEHOLDER).style(\"opacity\",0)})),I.call(u.makeEditable,{gd:t}).on(\"edit\",function(e){void 0!==y?o.call(\"_guiRestyle\",t,v,e,y):o.call(\"_guiRelayout\",t,v,e)}).on(\"cancel\",function(){this.text(this.attr(\"data-unformatted\")).call(D)}).on(\"input\",function(t){this.text(t||\" \").call(u.positionText,b.x,b.y)})),I.classed(\"js-placeholder\",M),w}}},{\"../../constants/alignment\":686,\"../../constants/interactions\":692,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"../../plots/plots\":826,\"../../registry\":846,\"../color\":592,\"../drawing\":613,d3:165,\"fast-isnumeric\":228}],680:[function(t,e,r){\"use strict\";var n=t(\"../../plots/font_attributes\"),a=t(\"../color/attributes\"),i=t(\"../../lib/extend\").extendFlat,o=t(\"../../plot_api/edit_types\").overrideAll,s=t(\"../../plots/pad_attributes\"),l=t(\"../../plot_api/plot_template\").templatedArray,c=l(\"button\",{visible:{valType:\"boolean\"},method:{valType:\"enumerated\",values:[\"restyle\",\"relayout\",\"animate\",\"update\",\"skip\"],dflt:\"restyle\"},args:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},args2:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},label:{valType:\"string\",dflt:\"\"},execute:{valType:\"boolean\",dflt:!0}});e.exports=o(l(\"updatemenu\",{_arrayAttrRegexps:[/^updatemenus\\[(0|[1-9][0-9]+)\\]\\.buttons/],visible:{valType:\"boolean\"},type:{valType:\"enumerated\",values:[\"dropdown\",\"buttons\"],dflt:\"dropdown\"},direction:{valType:\"enumerated\",values:[\"left\",\"right\",\"up\",\"down\"],dflt:\"down\"},active:{valType:\"integer\",min:-1,dflt:0},showactive:{valType:\"boolean\",dflt:!0},buttons:c,x:{valType:\"number\",min:-2,max:3,dflt:-.05},xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"right\"},y:{valType:\"number\",min:-2,max:3,dflt:1},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"top\"},pad:i(s({editType:\"arraydraw\"}),{}),font:n({}),bgcolor:{valType:\"color\"},bordercolor:{valType:\"color\",dflt:a.borderLine},borderwidth:{valType:\"number\",min:0,dflt:1,editType:\"arraydraw\"}}),\"arraydraw\",\"from-root\")},{\"../../lib/extend\":708,\"../../plot_api/edit_types\":748,\"../../plot_api/plot_template\":755,\"../../plots/font_attributes\":791,\"../../plots/pad_attributes\":825,\"../color/attributes\":591}],681:[function(t,e,r){\"use strict\";e.exports={name:\"updatemenus\",containerClassName:\"updatemenu-container\",headerGroupClassName:\"updatemenu-header-group\",headerClassName:\"updatemenu-header\",headerArrowClassName:\"updatemenu-header-arrow\",dropdownButtonGroupClassName:\"updatemenu-dropdown-button-group\",dropdownButtonClassName:\"updatemenu-dropdown-button\",buttonClassName:\"updatemenu-button\",itemRectClassName:\"updatemenu-item-rect\",itemTextClassName:\"updatemenu-item-text\",menuIndexAttrName:\"updatemenu-active-index\",autoMarginIdRoot:\"updatemenu-\",blankHeaderOpts:{label:\"  \"},minWidth:30,minHeight:30,textPadX:24,arrowPadX:16,rx:2,ry:2,textOffsetX:12,textOffsetY:3,arrowOffsetX:4,gapButtonHeader:5,gapButton:2,activeColor:\"#F4FAFF\",hoverColor:\"#F4FAFF\",arrowSymbol:{left:\"\\u25c4\",right:\"\\u25ba\",up:\"\\u25b2\",down:\"\\u25bc\"}}},{}],682:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/array_container_defaults\"),i=t(\"./attributes\"),o=t(\"./constants\").name,s=i.buttons;function l(t,e,r){function o(r,a){return n.coerce(t,e,i,r,a)}o(\"visible\",a(t,e,{name:\"buttons\",handleItemDefaults:c}).length>0)&&(o(\"active\"),o(\"direction\"),o(\"type\"),o(\"showactive\"),o(\"x\"),o(\"y\"),n.noneOrAll(t,e,[\"x\",\"y\"]),o(\"xanchor\"),o(\"yanchor\"),o(\"pad.t\"),o(\"pad.r\"),o(\"pad.b\"),o(\"pad.l\"),n.coerceFont(o,\"font\",r.font),o(\"bgcolor\",r.paper_bgcolor),o(\"bordercolor\"),o(\"borderwidth\"))}function c(t,e){function r(r,a){return n.coerce(t,e,s,r,a)}r(\"visible\",\"skip\"===t.method||Array.isArray(t.args))&&(r(\"method\"),r(\"args\"),r(\"args2\"),r(\"label\"),r(\"execute\"))}e.exports=function(t,e){a(t,e,{name:o,handleItemDefaults:l})}},{\"../../lib\":717,\"../../plots/array_container_defaults\":761,\"./attributes\":680,\"./constants\":681}],683:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../plots/plots\"),i=t(\"../color\"),o=t(\"../drawing\"),s=t(\"../../lib\"),l=t(\"../../lib/svg_text_utils\"),c=t(\"../../plot_api/plot_template\").arrayEditor,u=t(\"../../constants/alignment\").LINE_SPACING,h=t(\"./constants\"),f=t(\"./scrollbox\");function p(t){return t._index}function d(t,e){return+t.attr(h.menuIndexAttrName)===e._index}function g(t,e,r,n,a,i,o,s){e.active=o,c(t.layout,h.name,e).applyUpdate(\"active\",o),\"buttons\"===e.type?m(t,n,null,null,e):\"dropdown\"===e.type&&(a.attr(h.menuIndexAttrName,\"-1\"),v(t,n,a,i,e),s||m(t,n,a,i,e))}function v(t,e,r,n,a){var i=s.ensureSingle(e,\"g\",h.headerClassName,function(t){t.style(\"pointer-events\",\"all\")}),l=a._dims,c=a.active,u=a.buttons[c]||h.blankHeaderOpts,f={y:a.pad.t,yPad:0,x:a.pad.l,xPad:0,index:0},p={width:l.headerWidth,height:l.headerHeight};i.call(y,a,u,t).call(A,a,f,p),s.ensureSingle(e,\"text\",h.headerArrowClassName,function(t){t.classed(\"user-select-none\",!0).attr(\"text-anchor\",\"end\").call(o.font,a.font).text(h.arrowSymbol[a.direction])}).attr({x:l.headerWidth-h.arrowOffsetX+a.pad.l,y:l.headerHeight/2+h.textOffsetY+a.pad.t}),i.on(\"click\",function(){r.call(S,String(d(r,a)?-1:a._index)),m(t,e,r,n,a)}),i.on(\"mouseover\",function(){i.call(w)}),i.on(\"mouseout\",function(){i.call(k,a)}),o.setTranslate(e,l.lx,l.ly)}function m(t,e,r,i,o){r||(r=e).attr(\"pointer-events\",\"all\");var l=function(t){return-1==+t.attr(h.menuIndexAttrName)}(r)&&\"buttons\"!==o.type?[]:o.buttons,c=\"dropdown\"===o.type?h.dropdownButtonClassName:h.buttonClassName,u=r.selectAll(\"g.\"+c).data(s.filterVisible(l)),f=u.enter().append(\"g\").classed(c,!0),p=u.exit();\"dropdown\"===o.type?(f.attr(\"opacity\",\"0\").transition().attr(\"opacity\",\"1\"),p.transition().attr(\"opacity\",\"0\").remove()):p.remove();var d=0,v=0,m=o._dims,x=-1!==[\"up\",\"down\"].indexOf(o.direction);\"dropdown\"===o.type&&(x?v=m.headerHeight+h.gapButtonHeader:d=m.headerWidth+h.gapButtonHeader),\"dropdown\"===o.type&&\"up\"===o.direction&&(v=-h.gapButtonHeader+h.gapButton-m.openHeight),\"dropdown\"===o.type&&\"left\"===o.direction&&(d=-h.gapButtonHeader+h.gapButton-m.openWidth);var b={x:m.lx+d+o.pad.l,y:m.ly+v+o.pad.t,yPad:h.gapButton,xPad:h.gapButton,index:0},T={l:b.x+o.borderwidth,t:b.y+o.borderwidth};u.each(function(s,l){var c=n.select(this);c.call(y,o,s,t).call(A,o,b),c.on(\"click\",function(){n.event.defaultPrevented||(s.execute&&(s.args2&&o.active===l?(g(t,o,0,e,r,i,-1),a.executeAPICommand(t,s.method,s.args2)):(g(t,o,0,e,r,i,l),a.executeAPICommand(t,s.method,s.args))),t.emit(\"plotly_buttonclicked\",{menu:o,button:s,active:o.active}))}),c.on(\"mouseover\",function(){c.call(w)}),c.on(\"mouseout\",function(){c.call(k,o),u.call(_,o)})}),u.call(_,o),x?(T.w=Math.max(m.openWidth,m.headerWidth),T.h=b.y-T.t):(T.w=b.x-T.l,T.h=Math.max(m.openHeight,m.headerHeight)),T.direction=o.direction,i&&(u.size()?function(t,e,r,n,a,i){var o,s,l,c=a.direction,u=\"up\"===c||\"down\"===c,f=a._dims,p=a.active;if(u)for(s=0,l=0;l<p;l++)s+=f.heights[l]+h.gapButton;else for(o=0,l=0;l<p;l++)o+=f.widths[l]+h.gapButton;n.enable(i,o,s),n.hbar&&n.hbar.attr(\"opacity\",\"0\").transition().attr(\"opacity\",\"1\");n.vbar&&n.vbar.attr(\"opacity\",\"0\").transition().attr(\"opacity\",\"1\")}(0,0,0,i,o,T):function(t){var e=!!t.hbar,r=!!t.vbar;e&&t.hbar.transition().attr(\"opacity\",\"0\").each(\"end\",function(){e=!1,r||t.disable()});r&&t.vbar.transition().attr(\"opacity\",\"0\").each(\"end\",function(){r=!1,e||t.disable()})}(i))}function y(t,e,r,n){t.call(x,e).call(b,e,r,n)}function x(t,e){s.ensureSingle(t,\"rect\",h.itemRectClassName,function(t){t.attr({rx:h.rx,ry:h.ry,\"shape-rendering\":\"crispEdges\"})}).call(i.stroke,e.bordercolor).call(i.fill,e.bgcolor).style(\"stroke-width\",e.borderwidth+\"px\")}function b(t,e,r,n){var a=s.ensureSingle(t,\"text\",h.itemTextClassName,function(t){t.classed(\"user-select-none\",!0).attr({\"text-anchor\":\"start\",\"data-notex\":1})}),i=r.label,c=n._fullLayout._meta;c&&(i=s.templateString(i,c)),a.call(o.font,e.font).text(i).call(l.convertToTspans,n)}function _(t,e){var r=e.active;t.each(function(t,a){var o=n.select(this);a===r&&e.showactive&&o.select(\"rect.\"+h.itemRectClassName).call(i.fill,h.activeColor)})}function w(t){t.select(\"rect.\"+h.itemRectClassName).call(i.fill,h.hoverColor)}function k(t,e){t.select(\"rect.\"+h.itemRectClassName).call(i.fill,e.bgcolor)}function T(t,e){var r=e._dims={width1:0,height1:0,heights:[],widths:[],totalWidth:0,totalHeight:0,openWidth:0,openHeight:0,lx:0,ly:0},i=o.tester.selectAll(\"g.\"+h.dropdownButtonClassName).data(s.filterVisible(e.buttons));i.enter().append(\"g\").classed(h.dropdownButtonClassName,!0);var c=-1!==[\"up\",\"down\"].indexOf(e.direction);i.each(function(a,i){var s=n.select(this);s.call(y,e,a,t);var f=s.select(\".\"+h.itemTextClassName),p=f.node()&&o.bBox(f.node()).width,d=Math.max(p+h.textPadX,h.minWidth),g=e.font.size*u,v=l.lineCount(f),m=Math.max(g*v,h.minHeight)+h.textOffsetY;m=Math.ceil(m),d=Math.ceil(d),r.widths[i]=d,r.heights[i]=m,r.height1=Math.max(r.height1,m),r.width1=Math.max(r.width1,d),c?(r.totalWidth=Math.max(r.totalWidth,d),r.openWidth=r.totalWidth,r.totalHeight+=m+h.gapButton,r.openHeight+=m+h.gapButton):(r.totalWidth+=d+h.gapButton,r.openWidth+=d+h.gapButton,r.totalHeight=Math.max(r.totalHeight,m),r.openHeight=r.totalHeight)}),c?r.totalHeight-=h.gapButton:r.totalWidth-=h.gapButton,r.headerWidth=r.width1+h.arrowPadX,r.headerHeight=r.height1,\"dropdown\"===e.type&&(c?(r.width1+=h.arrowPadX,r.totalHeight=r.height1):r.totalWidth=r.width1,r.totalWidth+=h.arrowPadX),i.remove();var f=r.totalWidth+e.pad.l+e.pad.r,p=r.totalHeight+e.pad.t+e.pad.b,d=t._fullLayout._size;r.lx=d.l+d.w*e.x,r.ly=d.t+d.h*(1-e.y);var g=\"left\";s.isRightAnchor(e)&&(r.lx-=f,g=\"right\"),s.isCenterAnchor(e)&&(r.lx-=f/2,g=\"center\");var v=\"top\";s.isBottomAnchor(e)&&(r.ly-=p,v=\"bottom\"),s.isMiddleAnchor(e)&&(r.ly-=p/2,v=\"middle\"),r.totalWidth=Math.ceil(r.totalWidth),r.totalHeight=Math.ceil(r.totalHeight),r.lx=Math.round(r.lx),r.ly=Math.round(r.ly),a.autoMargin(t,M(e),{x:e.x,y:e.y,l:f*({right:1,center:.5}[g]||0),r:f*({left:1,center:.5}[g]||0),b:p*({top:1,middle:.5}[v]||0),t:p*({bottom:1,middle:.5}[v]||0)})}function M(t){return h.autoMarginIdRoot+t._index}function A(t,e,r,n){n=n||{};var a=t.select(\".\"+h.itemRectClassName),i=t.select(\".\"+h.itemTextClassName),s=e.borderwidth,c=r.index,f=e._dims;o.setTranslate(t,s+r.x,s+r.y);var p=-1!==[\"up\",\"down\"].indexOf(e.direction),d=n.height||(p?f.heights[c]:f.height1);a.attr({x:0,y:0,width:n.width||(p?f.width1:f.widths[c]),height:d});var g=e.font.size*u,v=(l.lineCount(i)-1)*g/2;l.positionText(i,h.textOffsetX,d/2-v+h.textOffsetY),p?r.y+=f.heights[c]+r.yPad:r.x+=f.widths[c]+r.xPad,r.index++}function S(t,e){t.attr(h.menuIndexAttrName,e||\"-1\").selectAll(\"g.\"+h.dropdownButtonClassName).remove()}e.exports=function(t){var e=t._fullLayout,r=s.filterVisible(e[h.name]);function i(e){a.autoMargin(t,M(e))}var o=e._menulayer.selectAll(\"g.\"+h.containerClassName).data(r.length>0?[0]:[]);if(o.enter().append(\"g\").classed(h.containerClassName,!0).style(\"cursor\",\"pointer\"),o.exit().each(function(){n.select(this).selectAll(\"g.\"+h.headerGroupClassName).each(i)}).remove(),0!==r.length){var l=o.selectAll(\"g.\"+h.headerGroupClassName).data(r,p);l.enter().append(\"g\").classed(h.headerGroupClassName,!0);for(var c=s.ensureSingle(o,\"g\",h.dropdownButtonGroupClassName,function(t){t.style(\"pointer-events\",\"all\")}),u=0;u<r.length;u++){var y=r[u];T(t,y)}var x=\"updatemenus\"+e._uid,b=new f(t,c,x);l.enter().size()&&(c.node().parentNode.appendChild(c.node()),c.call(S)),l.exit().each(function(t){c.call(S),i(t)}).remove(),l.each(function(e){var r=n.select(this),i=\"dropdown\"===e.type?c:null;a.manageCommandObserver(t,e,e.buttons,function(n){g(t,e,e.buttons[n.index],r,i,b,n.index,!0)}),\"dropdown\"===e.type?(v(t,r,c,b,e),d(c,e)&&m(t,r,c,b,e)):m(t,r,null,null,e)})}}},{\"../../constants/alignment\":686,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"../../plot_api/plot_template\":755,\"../../plots/plots\":826,\"../color\":592,\"../drawing\":613,\"./constants\":681,\"./scrollbox\":685,d3:165}],684:[function(t,e,r){arguments[4][678][0].apply(r,arguments)},{\"./attributes\":680,\"./constants\":681,\"./defaults\":682,\"./draw\":683,dup:678}],685:[function(t,e,r){\"use strict\";e.exports=s;var n=t(\"d3\"),a=t(\"../color\"),i=t(\"../drawing\"),o=t(\"../../lib\");function s(t,e,r){this.gd=t,this.container=e,this.id=r,this.position=null,this.translateX=null,this.translateY=null,this.hbar=null,this.vbar=null,this.bg=this.container.selectAll(\"rect.scrollbox-bg\").data([0]),this.bg.exit().on(\".drag\",null).on(\"wheel\",null).remove(),this.bg.enter().append(\"rect\").classed(\"scrollbox-bg\",!0).style(\"pointer-events\",\"all\").attr({opacity:0,x:0,y:0,width:0,height:0})}s.barWidth=2,s.barLength=20,s.barRadius=2,s.barPad=1,s.barColor=\"#808BA4\",s.prototype.enable=function(t,e,r){var o=this.gd._fullLayout,l=o.width,c=o.height;this.position=t;var u,h,f,p,d=this.position.l,g=this.position.w,v=this.position.t,m=this.position.h,y=this.position.direction,x=\"down\"===y,b=\"left\"===y,_=\"up\"===y,w=g,k=m;x||b||\"right\"===y||_||(this.position.direction=\"down\",x=!0),x||_?(h=(u=d)+w,x?(f=v,k=(p=Math.min(f+k,c))-f):k=(p=v+k)-(f=Math.max(p-k,0))):(p=(f=v)+k,b?w=(h=d+w)-(u=Math.max(h-w,0)):(u=d,w=(h=Math.min(u+w,l))-u)),this._box={l:u,t:f,w:w,h:k};var T=g>w,M=s.barLength+2*s.barPad,A=s.barWidth+2*s.barPad,S=d,E=v+m;E+A>c&&(E=c-A);var L=this.container.selectAll(\"rect.scrollbar-horizontal\").data(T?[0]:[]);L.exit().on(\".drag\",null).remove(),L.enter().append(\"rect\").classed(\"scrollbar-horizontal\",!0).call(a.fill,s.barColor),T?(this.hbar=L.attr({rx:s.barRadius,ry:s.barRadius,x:S,y:E,width:M,height:A}),this._hbarXMin=S+M/2,this._hbarTranslateMax=w-M):(delete this.hbar,delete this._hbarXMin,delete this._hbarTranslateMax);var C=m>k,P=s.barWidth+2*s.barPad,O=s.barLength+2*s.barPad,z=d+g,I=v;z+P>l&&(z=l-P);var D=this.container.selectAll(\"rect.scrollbar-vertical\").data(C?[0]:[]);D.exit().on(\".drag\",null).remove(),D.enter().append(\"rect\").classed(\"scrollbar-vertical\",!0).call(a.fill,s.barColor),C?(this.vbar=D.attr({rx:s.barRadius,ry:s.barRadius,x:z,y:I,width:P,height:O}),this._vbarYMin=I+O/2,this._vbarTranslateMax=k-O):(delete this.vbar,delete this._vbarYMin,delete this._vbarTranslateMax);var R=this.id,F=u-.5,B=C?h+P+.5:h+.5,N=f-.5,j=T?p+A+.5:p+.5,V=o._topdefs.selectAll(\"#\"+R).data(T||C?[0]:[]);if(V.exit().remove(),V.enter().append(\"clipPath\").attr(\"id\",R).append(\"rect\"),T||C?(this._clipRect=V.select(\"rect\").attr({x:Math.floor(F),y:Math.floor(N),width:Math.ceil(B)-Math.floor(F),height:Math.ceil(j)-Math.floor(N)}),this.container.call(i.setClipUrl,R,this.gd),this.bg.attr({x:d,y:v,width:g,height:m})):(this.bg.attr({width:0,height:0}),this.container.on(\"wheel\",null).on(\".drag\",null).call(i.setClipUrl,null),delete this._clipRect),T||C){var U=n.behavior.drag().on(\"dragstart\",function(){n.event.sourceEvent.preventDefault()}).on(\"drag\",this._onBoxDrag.bind(this));this.container.on(\"wheel\",null).on(\"wheel\",this._onBoxWheel.bind(this)).on(\".drag\",null).call(U);var q=n.behavior.drag().on(\"dragstart\",function(){n.event.sourceEvent.preventDefault(),n.event.sourceEvent.stopPropagation()}).on(\"drag\",this._onBarDrag.bind(this));T&&this.hbar.on(\".drag\",null).call(q),C&&this.vbar.on(\".drag\",null).call(q)}this.setTranslate(e,r)},s.prototype.disable=function(){(this.hbar||this.vbar)&&(this.bg.attr({width:0,height:0}),this.container.on(\"wheel\",null).on(\".drag\",null).call(i.setClipUrl,null),delete this._clipRect),this.hbar&&(this.hbar.on(\".drag\",null),this.hbar.remove(),delete this.hbar,delete this._hbarXMin,delete this._hbarTranslateMax),this.vbar&&(this.vbar.on(\".drag\",null),this.vbar.remove(),delete this.vbar,delete this._vbarYMin,delete this._vbarTranslateMax)},s.prototype._onBoxDrag=function(){var t=this.translateX,e=this.translateY;this.hbar&&(t-=n.event.dx),this.vbar&&(e-=n.event.dy),this.setTranslate(t,e)},s.prototype._onBoxWheel=function(){var t=this.translateX,e=this.translateY;this.hbar&&(t+=n.event.deltaY),this.vbar&&(e+=n.event.deltaY),this.setTranslate(t,e)},s.prototype._onBarDrag=function(){var t=this.translateX,e=this.translateY;if(this.hbar){var r=t+this._hbarXMin,a=r+this._hbarTranslateMax;t=(o.constrain(n.event.x,r,a)-r)/(a-r)*(this.position.w-this._box.w)}if(this.vbar){var i=e+this._vbarYMin,s=i+this._vbarTranslateMax;e=(o.constrain(n.event.y,i,s)-i)/(s-i)*(this.position.h-this._box.h)}this.setTranslate(t,e)},s.prototype.setTranslate=function(t,e){var r=this.position.w-this._box.w,n=this.position.h-this._box.h;if(t=o.constrain(t||0,0,r),e=o.constrain(e||0,0,n),this.translateX=t,this.translateY=e,this.container.call(i.setTranslate,this._box.l-this.position.l-t,this._box.t-this.position.t-e),this._clipRect&&this._clipRect.attr({x:Math.floor(this.position.l+t-.5),y:Math.floor(this.position.t+e-.5)}),this.hbar){var a=t/r;this.hbar.call(i.setTranslate,t+a*this._hbarTranslateMax,e)}if(this.vbar){var s=e/n;this.vbar.call(i.setTranslate,t,e+s*this._vbarTranslateMax)}}},{\"../../lib\":717,\"../color\":592,\"../drawing\":613,d3:165}],686:[function(t,e,r){\"use strict\";e.exports={FROM_BL:{left:0,center:.5,right:1,bottom:0,middle:.5,top:1},FROM_TL:{left:0,center:.5,right:1,bottom:1,middle:.5,top:0},FROM_BR:{left:1,center:.5,right:0,bottom:0,middle:.5,top:1},LINE_SPACING:1.3,CAP_SHIFT:.7,MID_SHIFT:.35,OPPOSITE_SIDE:{left:\"right\",right:\"left\",top:\"bottom\",bottom:\"top\"}}},{}],687:[function(t,e,r){\"use strict\";e.exports={INCREASING:{COLOR:\"#3D9970\",SYMBOL:\"\\u25b2\"},DECREASING:{COLOR:\"#FF4136\",SYMBOL:\"\\u25bc\"}}},{}],688:[function(t,e,r){\"use strict\";e.exports={FORMAT_LINK:\"https://github.com/d3/d3-3.x-api-reference/blob/master/Formatting.md#d3_format\",DATE_FORMAT_LINK:\"https://github.com/d3/d3-3.x-api-reference/blob/master/Time-Formatting.md#format\"}},{}],689:[function(t,e,r){\"use strict\";e.exports={COMPARISON_OPS:[\"=\",\"!=\",\"<\",\">=\",\">\",\"<=\"],COMPARISON_OPS2:[\"=\",\"<\",\">=\",\">\",\"<=\"],INTERVAL_OPS:[\"[]\",\"()\",\"[)\",\"(]\",\"][\",\")(\",\"](\",\")[\"],SET_OPS:[\"{}\",\"}{\"],CONSTRAINT_REDUCTION:{\"=\":\"=\",\"<\":\"<\",\"<=\":\"<\",\">\":\">\",\">=\":\">\",\"[]\":\"[]\",\"()\":\"[]\",\"[)\":\"[]\",\"(]\":\"[]\",\"][\":\"][\",\")(\":\"][\",\"](\":\"][\",\")[\":\"][\"}}},{}],690:[function(t,e,r){\"use strict\";e.exports={solid:[[],0],dot:[[.5,1],200],dash:[[.5,1],50],longdash:[[.5,1],10],dashdot:[[.5,.625,.875,1],50],longdashdot:[[.5,.7,.8,1],10]}},{}],691:[function(t,e,r){\"use strict\";e.exports={circle:\"\\u25cf\",\"circle-open\":\"\\u25cb\",square:\"\\u25a0\",\"square-open\":\"\\u25a1\",diamond:\"\\u25c6\",\"diamond-open\":\"\\u25c7\",cross:\"+\",x:\"\\u274c\"}},{}],692:[function(t,e,r){\"use strict\";e.exports={SHOW_PLACEHOLDER:100,HIDE_PLACEHOLDER:1e3,DESELECTDIM:.2}},{}],693:[function(t,e,r){\"use strict\";e.exports={BADNUM:void 0,FP_SAFE:Number.MAX_VALUE/1e4,ONEAVGYEAR:315576e5,ONEAVGMONTH:26298e5,ONEDAY:864e5,ONEHOUR:36e5,ONEMIN:6e4,ONESEC:1e3,EPOCHJD:2440587.5,ALMOST_EQUAL:1-1e-6,LOG_CLIP:10,MINUS_SIGN:\"\\u2212\"}},{}],694:[function(t,e,r){\"use strict\";r.xmlns=\"http://www.w3.org/2000/xmlns/\",r.svg=\"http://www.w3.org/2000/svg\",r.xlink=\"http://www.w3.org/1999/xlink\",r.svgAttrs={xmlns:r.svg,\"xmlns:xlink\":r.xlink}},{}],695:[function(t,e,r){\"use strict\";r.version=\"1.52.2\",t(\"es6-promise\").polyfill(),t(\"../build/plotcss\"),t(\"./fonts/mathjax_config\")();for(var n=t(\"./registry\"),a=r.register=n.register,i=t(\"./plot_api\"),o=Object.keys(i),s=0;s<o.length;s++){var l=o[s];\"_\"!==l.charAt(0)&&(r[l]=i[l]),a({moduleType:\"apiMethod\",name:l,fn:i[l]})}a(t(\"./traces/scatter\")),a([t(\"./components/fx\"),t(\"./components/legend\"),t(\"./components/annotations\"),t(\"./components/annotations3d\"),t(\"./components/shapes\"),t(\"./components/images\"),t(\"./components/updatemenus\"),t(\"./components/sliders\"),t(\"./components/rangeslider\"),t(\"./components/rangeselector\"),t(\"./components/grid\"),t(\"./components/errorbars\"),t(\"./components/colorscale\"),t(\"./components/colorbar\")]),a([t(\"./locale-en\"),t(\"./locale-en-us\")]),window.PlotlyLocales&&Array.isArray(window.PlotlyLocales)&&(a(window.PlotlyLocales),delete window.PlotlyLocales),r.Icons=t(\"./fonts/ploticon\"),r.Plots=t(\"./plots/plots\"),r.Fx=t(\"./components/fx\"),r.Snapshot=t(\"./snapshot\"),r.PlotSchema=t(\"./plot_api/plot_schema\"),r.Queue=t(\"./lib/queue\"),r.d3=t(\"d3\")},{\"../build/plotcss\":1,\"./components/annotations\":583,\"./components/annotations3d\":588,\"./components/colorbar\":598,\"./components/colorscale\":604,\"./components/errorbars\":619,\"./components/fx\":630,\"./components/grid\":634,\"./components/images\":639,\"./components/legend\":647,\"./components/rangeselector\":658,\"./components/rangeslider\":665,\"./components/shapes\":673,\"./components/sliders\":678,\"./components/updatemenus\":684,\"./fonts/mathjax_config\":696,\"./fonts/ploticon\":697,\"./lib/queue\":732,\"./locale-en\":746,\"./locale-en-us\":745,\"./plot_api\":750,\"./plot_api/plot_schema\":754,\"./plots/plots\":826,\"./registry\":846,\"./snapshot\":851,\"./traces/scatter\":1132,d3:165,\"es6-promise\":221}],696:[function(t,e,r){\"use strict\";e.exports=function(){\"undefined\"!=typeof MathJax&&(\"local\"!==(window.PlotlyConfig||{}).MathJaxConfig&&(MathJax.Hub.Config({messageStyle:\"none\",skipStartupTypeset:!0,displayAlign:\"left\",tex2jax:{inlineMath:[[\"$\",\"$\"],[\"\\\\(\",\"\\\\)\"]]}}),MathJax.Hub.Configured()))}},{}],697:[function(t,e,r){\"use strict\";e.exports={undo:{width:857.1,height:1e3,path:\"m857 350q0-87-34-166t-91-137-137-92-166-34q-96 0-183 41t-147 114q-4 6-4 13t5 11l76 77q6 5 14 5 9-1 13-7 41-53 100-82t126-29q58 0 110 23t92 61 61 91 22 111-22 111-61 91-92 61-110 23q-55 0-105-20t-90-57l77-77q17-16 8-38-10-23-33-23h-250q-15 0-25 11t-11 25v250q0 24 22 33 22 10 39-8l72-72q60 57 137 88t159 31q87 0 166-34t137-92 91-137 34-166z\",transform:\"matrix(1 0 0 -1 0 850)\"},home:{width:928.6,height:1e3,path:\"m786 296v-267q0-15-11-26t-25-10h-214v214h-143v-214h-214q-15 0-25 10t-11 26v267q0 1 0 2t0 2l321 264 321-264q1-1 1-4z m124 39l-34-41q-5-5-12-6h-2q-7 0-12 3l-386 322-386-322q-7-4-13-4-7 2-12 7l-35 41q-4 5-3 13t6 12l401 334q18 15 42 15t43-15l136-114v109q0 8 5 13t13 5h107q8 0 13-5t5-13v-227l122-102q5-5 6-12t-4-13z\",transform:\"matrix(1 0 0 -1 0 850)\"},\"camera-retro\":{width:1e3,height:1e3,path:\"m518 386q0 8-5 13t-13 5q-37 0-63-27t-26-63q0-8 5-13t13-5 12 5 5 13q0 23 16 38t38 16q8 0 13 5t5 13z m125-73q0-59-42-101t-101-42-101 42-42 101 42 101 101 42 101-42 42-101z m-572-320h858v71h-858v-71z m643 320q0 89-62 152t-152 62-151-62-63-152 63-151 151-63 152 63 62 151z m-571 358h214v72h-214v-72z m-72-107h858v143h-462l-36-71h-360v-72z m929 143v-714q0-30-21-51t-50-21h-858q-29 0-50 21t-21 51v714q0 30 21 51t50 21h858q29 0 50-21t21-51z\",transform:\"matrix(1 0 0 -1 0 850)\"},zoombox:{width:1e3,height:1e3,path:\"m1000-25l-250 251c40 63 63 138 63 218 0 224-182 406-407 406-224 0-406-182-406-406s183-406 407-406c80 0 155 22 218 62l250-250 125 125z m-812 250l0 438 437 0 0-438-437 0z m62 375l313 0 0-312-313 0 0 312z\",transform:\"matrix(1 0 0 -1 0 850)\"},pan:{width:1e3,height:1e3,path:\"m1000 350l-187 188 0-125-250 0 0 250 125 0-188 187-187-187 125 0 0-250-250 0 0 125-188-188 186-187 0 125 252 0 0-250-125 0 187-188 188 188-125 0 0 250 250 0 0-126 187 188z\",transform:\"matrix(1 0 0 -1 0 850)\"},zoom_plus:{width:875,height:1e3,path:\"m1 787l0-875 875 0 0 875-875 0z m687-500l-187 0 0-187-125 0 0 187-188 0 0 125 188 0 0 187 125 0 0-187 187 0 0-125z\",transform:\"matrix(1 0 0 -1 0 850)\"},zoom_minus:{width:875,height:1e3,path:\"m0 788l0-876 875 0 0 876-875 0z m688-500l-500 0 0 125 500 0 0-125z\",transform:\"matrix(1 0 0 -1 0 850)\"},autoscale:{width:1e3,height:1e3,path:\"m250 850l-187 0-63 0 0-62 0-188 63 0 0 188 187 0 0 62z m688 0l-188 0 0-62 188 0 0-188 62 0 0 188 0 62-62 0z m-875-938l0 188-63 0 0-188 0-62 63 0 187 0 0 62-187 0z m875 188l0-188-188 0 0-62 188 0 62 0 0 62 0 188-62 0z m-125 188l-1 0-93-94-156 156 156 156 92-93 2 0 0 250-250 0 0-2 93-92-156-156-156 156 94 92 0 2-250 0 0-250 0 0 93 93 157-156-157-156-93 94 0 0 0-250 250 0 0 0-94 93 156 157 156-157-93-93 0 0 250 0 0 250z\",transform:\"matrix(1 0 0 -1 0 850)\"},tooltip_basic:{width:1500,height:1e3,path:\"m375 725l0 0-375-375 375-374 0-1 1125 0 0 750-1125 0z\",transform:\"matrix(1 0 0 -1 0 850)\"},tooltip_compare:{width:1125,height:1e3,path:\"m187 786l0 2-187-188 188-187 0 0 937 0 0 373-938 0z m0-499l0 1-187-188 188-188 0 0 937 0 0 376-938-1z\",transform:\"matrix(1 0 0 -1 0 850)\"},plotlylogo:{width:1542,height:1e3,path:\"m0-10h182v-140h-182v140z m228 146h183v-286h-183v286z m225 714h182v-1000h-182v1000z m225-285h182v-715h-182v715z m225 142h183v-857h-183v857z m231-428h182v-429h-182v429z m225-291h183v-138h-183v138z\",transform:\"matrix(1 0 0 -1 0 850)\"},\"z-axis\":{width:1e3,height:1e3,path:\"m833 5l-17 108v41l-130-65 130-66c0 0 0 38 0 39 0-1 36-14 39-25 4-15-6-22-16-30-15-12-39-16-56-20-90-22-187-23-279-23-261 0-341 34-353 59 3 60 228 110 228 110-140-8-351-35-351-116 0-120 293-142 474-142 155 0 477 22 477 142 0 50-74 79-163 96z m-374 94c-58-5-99-21-99-40 0-24 65-43 144-43 79 0 143 19 143 43 0 19-42 34-98 40v216h87l-132 135-133-135h88v-216z m167 515h-136v1c16 16 31 34 46 52l84 109v54h-230v-71h124v-1c-16-17-28-32-44-51l-89-114v-51h245v72z\",transform:\"matrix(1 0 0 -1 0 850)\"},\"3d_rotate\":{width:1e3,height:1e3,path:\"m922 660c-5 4-9 7-14 11-359 263-580-31-580-31l-102 28 58-400c0 1 1 1 2 2 118 108 351 249 351 249s-62 27-100 42c88 83 222 183 347 122 16-8 30-17 44-27-2 1-4 2-6 4z m36-329c0 0 64 229-88 296-62 27-124 14-175-11 157-78 225-208 249-266 8-19 11-31 11-31 2 5 6 15 11 32-5-13-8-20-8-20z m-775-239c70-31 117-50 198-32-121 80-199 346-199 346l-96-15-58-12c0 0 55-226 155-287z m603 133l-317-139c0 0 4-4 19-14 7-5 24-15 24-15s-177-147-389 4c235-287 536-112 536-112l31-22 100 299-4-1z m-298-153c6-4 14-9 24-15 0 0-17 10-24 15z\",transform:\"matrix(1 0 0 -1 0 850)\"},camera:{width:1e3,height:1e3,path:\"m500 450c-83 0-150-67-150-150 0-83 67-150 150-150 83 0 150 67 150 150 0 83-67 150-150 150z m400 150h-120c-16 0-34 13-39 29l-31 93c-6 15-23 28-40 28h-340c-16 0-34-13-39-28l-31-94c-6-15-23-28-40-28h-120c-55 0-100-45-100-100v-450c0-55 45-100 100-100h800c55 0 100 45 100 100v450c0 55-45 100-100 100z m-400-550c-138 0-250 112-250 250 0 138 112 250 250 250 138 0 250-112 250-250 0-138-112-250-250-250z m365 380c-19 0-35 16-35 35 0 19 16 35 35 35 19 0 35-16 35-35 0-19-16-35-35-35z\",transform:\"matrix(1 0 0 -1 0 850)\"},movie:{width:1e3,height:1e3,path:\"m938 413l-188-125c0 37-17 71-44 94 64 38 107 107 107 187 0 121-98 219-219 219-121 0-219-98-219-219 0-61 25-117 66-156h-115c30 33 49 76 49 125 0 103-84 187-187 187s-188-84-188-187c0-57 26-107 65-141-38-22-65-62-65-109v-250c0-70 56-126 125-126h500c69 0 125 56 125 126l188-126c34 0 62 28 62 63v375c0 35-28 63-62 63z m-750 0c-69 0-125 56-125 125s56 125 125 125 125-56 125-125-56-125-125-125z m406-1c-87 0-157 70-157 157 0 86 70 156 157 156s156-70 156-156-70-157-156-157z\",transform:\"matrix(1 0 0 -1 0 850)\"},question:{width:857.1,height:1e3,path:\"m500 82v107q0 8-5 13t-13 5h-107q-8 0-13-5t-5-13v-107q0-8 5-13t13-5h107q8 0 13 5t5 13z m143 375q0 49-31 91t-77 65-95 23q-136 0-207-119-9-14 4-24l74-55q4-4 10-4 9 0 14 7 30 38 48 51 19 14 48 14 27 0 48-15t21-33q0-21-11-34t-38-25q-35-16-65-48t-29-70v-20q0-8 5-13t13-5h107q8 0 13 5t5 13q0 10 12 27t30 28q18 10 28 16t25 19 25 27 16 34 7 45z m214-107q0-117-57-215t-156-156-215-58-216 58-155 156-58 215 58 215 155 156 216 58 215-58 156-156 57-215z\",transform:\"matrix(1 0 0 -1 0 850)\"},disk:{width:857.1,height:1e3,path:\"m214-7h429v214h-429v-214z m500 0h72v500q0 8-6 21t-11 20l-157 156q-5 6-19 12t-22 5v-232q0-22-15-38t-38-16h-322q-22 0-37 16t-16 38v232h-72v-714h72v232q0 22 16 38t37 16h465q22 0 38-16t15-38v-232z m-214 518v178q0 8-5 13t-13 5h-107q-7 0-13-5t-5-13v-178q0-8 5-13t13-5h107q7 0 13 5t5 13z m357-18v-518q0-22-15-38t-38-16h-750q-23 0-38 16t-16 38v750q0 22 16 38t38 16h517q23 0 50-12t42-26l156-157q16-15 27-42t11-49z\",transform:\"matrix(1 0 0 -1 0 850)\"},lasso:{width:1031,height:1e3,path:\"m1018 538c-36 207-290 336-568 286-277-48-473-256-436-463 10-57 36-108 76-151-13-66 11-137 68-183 34-28 75-41 114-42l-55-70 0 0c-2-1-3-2-4-3-10-14-8-34 5-45 14-11 34-8 45 4 1 1 2 3 2 5l0 0 113 140c16 11 31 24 45 40 4 3 6 7 8 11 48-3 100 0 151 9 278 48 473 255 436 462z m-624-379c-80 14-149 48-197 96 42 42 109 47 156 9 33-26 47-66 41-105z m-187-74c-19 16-33 37-39 60 50-32 109-55 174-68-42-25-95-24-135 8z m360 75c-34-7-69-9-102-8 8 62-16 128-68 170-73 59-175 54-244-5-9 20-16 40-20 61-28 159 121 317 333 354s407-60 434-217c28-159-121-318-333-355z\",transform:\"matrix(1 0 0 -1 0 850)\"},selectbox:{width:1e3,height:1e3,path:\"m0 850l0-143 143 0 0 143-143 0z m286 0l0-143 143 0 0 143-143 0z m285 0l0-143 143 0 0 143-143 0z m286 0l0-143 143 0 0 143-143 0z m-857-286l0-143 143 0 0 143-143 0z m857 0l0-143 143 0 0 143-143 0z m-857-285l0-143 143 0 0 143-143 0z m857 0l0-143 143 0 0 143-143 0z m-857-286l0-143 143 0 0 143-143 0z m286 0l0-143 143 0 0 143-143 0z m285 0l0-143 143 0 0 143-143 0z m286 0l0-143 143 0 0 143-143 0z\",transform:\"matrix(1 0 0 -1 0 850)\"},spikeline:{width:1e3,height:1e3,path:\"M512 409c0-57-46-104-103-104-57 0-104 47-104 104 0 57 47 103 104 103 57 0 103-46 103-103z m-327-39l92 0 0 92-92 0z m-185 0l92 0 0 92-92 0z m370-186l92 0 0 93-92 0z m0-184l92 0 0 92-92 0z\",transform:\"matrix(1.5 0 0 -1.5 0 850)\"},pencil:{width:1792,height:1792,path:\"M491 1536l91-91-235-235-91 91v107h128v128h107zm523-928q0-22-22-22-10 0-17 7l-542 542q-7 7-7 17 0 22 22 22 10 0 17-7l542-542q7-7 7-17zm-54-192l416 416-832 832h-416v-416zm683 96q0 53-37 90l-166 166-416-416 166-165q36-38 90-38 53 0 91 38l235 234q37 39 37 91z\",transform:\"matrix(1 0 0 1 0 1)\"},newplotlylogo:{name:\"newplotlylogo\",svg:\"<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 132 132'><defs><style>.cls-1 {fill: #119dff;} .cls-2 {fill: #25fefd;} .cls-3 {fill: #fff;}</style></defs><title>plotly-logomark</title><g id='symbol'><rect class='cls-1' width='132' height='132' rx='6' ry='6'/><circle class='cls-2' cx='78' cy='54' r='6'/><circle class='cls-2' cx='102' cy='30' r='6'/><circle class='cls-2' cx='78' cy='30' r='6'/><circle class='cls-2' cx='54' cy='30' r='6'/><circle class='cls-2' cx='30' cy='30' r='6'/><circle class='cls-2' cx='30' cy='54' r='6'/><path class='cls-3' d='M30,72a6,6,0,0,0-6,6v24a6,6,0,0,0,12,0V78A6,6,0,0,0,30,72Z'/><path class='cls-3' d='M78,72a6,6,0,0,0-6,6v24a6,6,0,0,0,12,0V78A6,6,0,0,0,78,72Z'/><path class='cls-3' d='M54,48a6,6,0,0,0-6,6v48a6,6,0,0,0,12,0V54A6,6,0,0,0,54,48Z'/><path class='cls-3' d='M102,48a6,6,0,0,0-6,6v48a6,6,0,0,0,12,0V54A6,6,0,0,0,102,48Z'/></g></svg>\"}}},{}],698:[function(t,e,r){\"use strict\";r.isLeftAnchor=function(t){return\"left\"===t.xanchor||\"auto\"===t.xanchor&&t.x<=1/3},r.isCenterAnchor=function(t){return\"center\"===t.xanchor||\"auto\"===t.xanchor&&t.x>1/3&&t.x<2/3},r.isRightAnchor=function(t){return\"right\"===t.xanchor||\"auto\"===t.xanchor&&t.x>=2/3},r.isTopAnchor=function(t){return\"top\"===t.yanchor||\"auto\"===t.yanchor&&t.y>=2/3},r.isMiddleAnchor=function(t){return\"middle\"===t.yanchor||\"auto\"===t.yanchor&&t.y>1/3&&t.y<2/3},r.isBottomAnchor=function(t){return\"bottom\"===t.yanchor||\"auto\"===t.yanchor&&t.y<=1/3}},{}],699:[function(t,e,r){\"use strict\";var n=t(\"./mod\"),a=n.mod,i=n.modHalf,o=Math.PI,s=2*o;function l(t){return Math.abs(t[1]-t[0])>s-1e-14}function c(t,e){return i(e-t,s)}function u(t,e){if(l(e))return!0;var r,n;e[0]<e[1]?(r=e[0],n=e[1]):(r=e[1],n=e[0]),(r=a(r,s))>(n=a(n,s))&&(n+=s);var i=a(t,s),o=i+s;return i>=r&&i<=n||o>=r&&o<=n}function h(t,e,r,n,a,i,c){a=a||0,i=i||0;var u,h,f,p,d,g=l([r,n]);function v(t,e){return[t*Math.cos(e)+a,i-t*Math.sin(e)]}g?(u=0,h=o,f=s):r<n?(u=r,f=n):(u=n,f=r),t<e?(p=t,d=e):(p=e,d=t);var m,y=Math.abs(f-u)<=o?0:1;function x(t,e,r){return\"A\"+[t,t]+\" \"+[0,y,r]+\" \"+v(t,e)}return g?m=null===p?\"M\"+v(d,u)+x(d,h,0)+x(d,f,0)+\"Z\":\"M\"+v(p,u)+x(p,h,0)+x(p,f,0)+\"ZM\"+v(d,u)+x(d,h,1)+x(d,f,1)+\"Z\":null===p?(m=\"M\"+v(d,u)+x(d,f,0),c&&(m+=\"L0,0Z\")):m=\"M\"+v(p,u)+\"L\"+v(d,u)+x(d,f,0)+\"L\"+v(p,f)+x(p,u,1)+\"Z\",m}e.exports={deg2rad:function(t){return t/180*o},rad2deg:function(t){return t/o*180},angleDelta:c,angleDist:function(t,e){return Math.abs(c(t,e))},isFullCircle:l,isAngleInsideSector:u,isPtInsideSector:function(t,e,r,n){return!!u(e,n)&&(r[0]<r[1]?(a=r[0],i=r[1]):(a=r[1],i=r[0]),t>=a&&t<=i);var a,i},pathArc:function(t,e,r,n,a){return h(null,t,e,r,n,a,0)},pathSector:function(t,e,r,n,a){return h(null,t,e,r,n,a,1)},pathAnnulus:function(t,e,r,n,a,i){return h(t,e,r,n,a,i,1)}}},{\"./mod\":724}],700:[function(t,e,r){\"use strict\";var n=Array.isArray,a=\"undefined\"!=typeof ArrayBuffer&&ArrayBuffer.isView?ArrayBuffer:{isView:function(){return!1}},i=\"undefined\"==typeof DataView?function(){}:DataView;function o(t){return a.isView(t)&&!(t instanceof i)}function s(t){return n(t)||o(t)}function l(t,e,r){if(s(t)){if(s(t[0])){for(var n=r,a=0;a<t.length;a++)n=e(n,t[a].length);return n}return t.length}return 0}r.isTypedArray=o,r.isArrayOrTypedArray=s,r.isArray1D=function(t){return!s(t[0])},r.ensureArray=function(t,e){return n(t)||(t=[]),t.length=e,t},r.concat=function(){var t,e,r,a,i,o,s,l,c=[],u=!0,h=0;for(r=0;r<arguments.length;r++)(o=(a=arguments[r]).length)&&(e?c.push(a):(e=a,i=o),n(a)?t=!1:(u=!1,h?t!==a.constructor&&(t=!1):t=a.constructor),h+=o);if(!h)return[];if(!c.length)return e;if(u)return e.concat.apply(e,c);if(t){for((s=new t(h)).set(e),r=0;r<c.length;r++)a=c[r],s.set(a,i),i+=a.length;return s}for(s=new Array(h),l=0;l<e.length;l++)s[l]=e[l];for(r=0;r<c.length;r++){for(a=c[r],l=0;l<a.length;l++)s[i+l]=a[l];i+=l}return s},r.maxRowLength=function(t){return l(t,Math.max,0)},r.minRowLength=function(t){return l(t,Math.min,1/0)}},{}],701:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../constants/numerical\").BADNUM,i=/^['\"%,$#\\s']+|[, ]|['\"%,$#\\s']+$/g;e.exports=function(t){return\"string\"==typeof t&&(t=t.replace(i,\"\")),n(t)?Number(t):a}},{\"../constants/numerical\":693,\"fast-isnumeric\":228}],702:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t._fullLayout;e._glcanvas&&e._glcanvas.size()&&e._glcanvas.each(function(t){t.regl&&t.regl.clear({color:!0,depth:!0})})}},{}],703:[function(t,e,r){\"use strict\";e.exports=function(t){t._responsiveChartHandler&&(window.removeEventListener(\"resize\",t._responsiveChartHandler),delete t._responsiveChartHandler)}},{}],704:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"tinycolor2\"),i=t(\"../plots/attributes\"),o=t(\"../components/colorscale/scales\"),s=t(\"../constants/interactions\").DESELECTDIM,l=t(\"./nested_property\"),c=t(\"./regex\").counter,u=t(\"./mod\").modHalf,h=t(\"./array\").isArrayOrTypedArray;function f(t,e){var n=r.valObjectMeta[e.valType];if(e.arrayOk&&h(t))return!0;if(n.validateFunction)return n.validateFunction(t,e);var a={},i=a,o={set:function(t){i=t}};return n.coerceFunction(t,o,a,e),i!==a}r.valObjectMeta={data_array:{coerceFunction:function(t,e,r){h(t)?e.set(t):void 0!==r&&e.set(r)}},enumerated:{coerceFunction:function(t,e,r,n){n.coerceNumber&&(t=+t),-1===n.values.indexOf(t)?e.set(r):e.set(t)},validateFunction:function(t,e){e.coerceNumber&&(t=+t);for(var r=e.values,n=0;n<r.length;n++){var a=String(r[n]);if(\"/\"===a.charAt(0)&&\"/\"===a.charAt(a.length-1)){if(new RegExp(a.substr(1,a.length-2)).test(t))return!0}else if(t===r[n])return!0}return!1}},boolean:{coerceFunction:function(t,e,r){!0===t||!1===t?e.set(t):e.set(r)}},number:{coerceFunction:function(t,e,r,a){!n(t)||void 0!==a.min&&t<a.min||void 0!==a.max&&t>a.max?e.set(r):e.set(+t)}},integer:{coerceFunction:function(t,e,r,a){t%1||!n(t)||void 0!==a.min&&t<a.min||void 0!==a.max&&t>a.max?e.set(r):e.set(+t)}},string:{coerceFunction:function(t,e,r,n){if(\"string\"!=typeof t){var a=\"number\"==typeof t;!0!==n.strict&&a?e.set(String(t)):e.set(r)}else n.noBlank&&!t?e.set(r):e.set(t)}},color:{coerceFunction:function(t,e,r){a(t).isValid()?e.set(t):e.set(r)}},colorlist:{coerceFunction:function(t,e,r){Array.isArray(t)&&t.length&&t.every(function(t){return a(t).isValid()})?e.set(t):e.set(r)}},colorscale:{coerceFunction:function(t,e,r){e.set(o.get(t,r))}},angle:{coerceFunction:function(t,e,r){\"auto\"===t?e.set(\"auto\"):n(t)?e.set(u(+t,360)):e.set(r)}},subplotid:{coerceFunction:function(t,e,r,n){var a=n.regex||c(r);\"string\"==typeof t&&a.test(t)?e.set(t):e.set(r)},validateFunction:function(t,e){var r=e.dflt;return t===r||\"string\"==typeof t&&!!c(r).test(t)}},flaglist:{coerceFunction:function(t,e,r,n){if(\"string\"==typeof t)if(-1===(n.extras||[]).indexOf(t)){for(var a=t.split(\"+\"),i=0;i<a.length;){var o=a[i];-1===n.flags.indexOf(o)||a.indexOf(o)<i?a.splice(i,1):i++}a.length?e.set(a.join(\"+\")):e.set(r)}else e.set(t);else e.set(r)}},any:{coerceFunction:function(t,e,r){void 0===t?e.set(r):e.set(t)}},info_array:{coerceFunction:function(t,e,n,a){function i(t,e,n){var a,i={set:function(t){a=t}};return void 0===n&&(n=e.dflt),r.valObjectMeta[e.valType].coerceFunction(t,i,n,e),a}var o=2===a.dimensions||\"1-2\"===a.dimensions&&Array.isArray(t)&&Array.isArray(t[0]);if(Array.isArray(t)){var s,l,c,u,h,f,p=a.items,d=[],g=Array.isArray(p),v=g&&o&&Array.isArray(p[0]),m=o&&g&&!v,y=g&&!m?p.length:t.length;if(n=Array.isArray(n)?n:[],o)for(s=0;s<y;s++)for(d[s]=[],c=Array.isArray(t[s])?t[s]:[],h=m?p.length:g?p[s].length:c.length,l=0;l<h;l++)u=m?p[l]:g?p[s][l]:p,void 0!==(f=i(c[l],u,(n[s]||[])[l]))&&(d[s][l]=f);else for(s=0;s<y;s++)void 0!==(f=i(t[s],g?p[s]:p,n[s]))&&(d[s]=f);e.set(d)}else e.set(n)},validateFunction:function(t,e){if(!Array.isArray(t))return!1;var r=e.items,n=Array.isArray(r),a=2===e.dimensions;if(!e.freeLength&&t.length!==r.length)return!1;for(var i=0;i<t.length;i++)if(a){if(!Array.isArray(t[i])||!e.freeLength&&t[i].length!==r[i].length)return!1;for(var o=0;o<t[i].length;o++)if(!f(t[i][o],n?r[i][o]:r))return!1}else if(!f(t[i],n?r[i]:r))return!1;return!0}}},r.coerce=function(t,e,n,a,i){var o=l(n,a).get(),s=l(t,a),c=l(e,a),u=s.get(),p=e._template;if(void 0===u&&p&&(u=l(p,a).get(),p=0),void 0===i&&(i=o.dflt),o.arrayOk&&h(u))return c.set(u),u;var d=r.valObjectMeta[o.valType].coerceFunction;d(u,c,i,o);var g=c.get();return p&&g===i&&!f(u,o)&&(d(u=l(p,a).get(),c,i,o),g=c.get()),g},r.coerce2=function(t,e,n,a,i){var o=l(t,a),s=r.coerce(t,e,n,a,i),c=o.get();return null!=c&&s},r.coerceFont=function(t,e,r){var n={};return r=r||{},n.family=t(e+\".family\",r.family),n.size=t(e+\".size\",r.size),n.color=t(e+\".color\",r.color),n},r.coerceHoverinfo=function(t,e,n){var a,o=e._module.attributes,s=o.hoverinfo?o:i,l=s.hoverinfo;if(1===n._dataLength){var c=\"all\"===l.dflt?l.flags.slice():l.dflt.split(\"+\");c.splice(c.indexOf(\"name\"),1),a=c.join(\"+\")}return r.coerce(t,e,s,\"hoverinfo\",a)},r.coerceSelectionMarkerOpacity=function(t,e){if(t.marker){var r,n,a=t.marker.opacity;if(void 0!==a)h(a)||t.selected||t.unselected||(r=a,n=s*a),e(\"selected.marker.opacity\",r),e(\"unselected.marker.opacity\",n)}},r.validate=f},{\"../components/colorscale/scales\":607,\"../constants/interactions\":692,\"../plots/attributes\":762,\"./array\":700,\"./mod\":724,\"./nested_property\":725,\"./regex\":733,\"fast-isnumeric\":228,tinycolor2:536}],705:[function(t,e,r){\"use strict\";var n,a,i=t(\"d3\"),o=t(\"fast-isnumeric\"),s=t(\"./loggers\"),l=t(\"./mod\").mod,c=t(\"../constants/numerical\"),u=c.BADNUM,h=c.ONEDAY,f=c.ONEHOUR,p=c.ONEMIN,d=c.ONESEC,g=c.EPOCHJD,v=t(\"../registry\"),m=i.time.format.utc,y=/^\\s*(-?\\d\\d\\d\\d|\\d\\d)(-(\\d?\\d)(-(\\d?\\d)([ Tt]([01]?\\d|2[0-3])(:([0-5]\\d)(:([0-5]\\d(\\.\\d+)?))?(Z|z|[+\\-]\\d\\d:?\\d\\d)?)?)?)?)?\\s*$/m,x=/^\\s*(-?\\d\\d\\d\\d|\\d\\d)(-(\\d?\\di?)(-(\\d?\\d)([ Tt]([01]?\\d|2[0-3])(:([0-5]\\d)(:([0-5]\\d(\\.\\d+)?))?(Z|z|[+\\-]\\d\\d:?\\d\\d)?)?)?)?)?\\s*$/m,b=(new Date).getFullYear()-70;function _(t){return t&&v.componentsRegistry.calendars&&\"string\"==typeof t&&\"gregorian\"!==t}function w(t,e){return String(t+Math.pow(10,e)).substr(1)}r.dateTick0=function(t,e){return _(t)?e?v.getComponentMethod(\"calendars\",\"CANONICAL_SUNDAY\")[t]:v.getComponentMethod(\"calendars\",\"CANONICAL_TICK\")[t]:e?\"2000-01-02\":\"2000-01-01\"},r.dfltRange=function(t){return _(t)?v.getComponentMethod(\"calendars\",\"DFLTRANGE\")[t]:[\"2000-01-01\",\"2001-01-01\"]},r.isJSDate=function(t){return\"object\"==typeof t&&null!==t&&\"function\"==typeof t.getTime},r.dateTime2ms=function(t,e){if(r.isJSDate(t)){var i=t.getTimezoneOffset()*p,o=(t.getUTCMinutes()-t.getMinutes())*p+(t.getUTCSeconds()-t.getSeconds())*d+(t.getUTCMilliseconds()-t.getMilliseconds());if(o){var s=3*p;i=i-s/2+l(o-i+s/2,s)}return(t=Number(t)-i)>=n&&t<=a?t:u}if(\"string\"!=typeof t&&\"number\"!=typeof t)return u;t=String(t);var c=_(e),m=t.charAt(0);!c||\"G\"!==m&&\"g\"!==m||(t=t.substr(1),e=\"\");var w=c&&\"chinese\"===e.substr(0,7),k=t.match(w?x:y);if(!k)return u;var T=k[1],M=k[3]||\"1\",A=Number(k[5]||1),S=Number(k[7]||0),E=Number(k[9]||0),L=Number(k[11]||0);if(c){if(2===T.length)return u;var C;T=Number(T);try{var P=v.getComponentMethod(\"calendars\",\"getCal\")(e);if(w){var O=\"i\"===M.charAt(M.length-1);M=parseInt(M,10),C=P.newDate(T,P.toMonthIndex(T,M,O),A)}else C=P.newDate(T,Number(M),A)}catch(t){return u}return C?(C.toJD()-g)*h+S*f+E*p+L*d:u}T=2===T.length?(Number(T)+2e3-b)%100+b:Number(T),M-=1;var z=new Date(Date.UTC(2e3,M,A,S,E));return z.setUTCFullYear(T),z.getUTCMonth()!==M?u:z.getUTCDate()!==A?u:z.getTime()+L*d},n=r.MIN_MS=r.dateTime2ms(\"-9999\"),a=r.MAX_MS=r.dateTime2ms(\"9999-12-31 23:59:59.9999\"),r.isDateTime=function(t,e){return r.dateTime2ms(t,e)!==u};var k=90*h,T=3*f,M=5*p;function A(t,e,r,n,a){if((e||r||n||a)&&(t+=\" \"+w(e,2)+\":\"+w(r,2),(n||a)&&(t+=\":\"+w(n,2),a))){for(var i=4;a%10==0;)i-=1,a/=10;t+=\".\"+w(a,i)}return t}r.ms2DateTime=function(t,e,r){if(\"number\"!=typeof t||!(t>=n&&t<=a))return u;e||(e=0);var i,o,s,c,y,x,b=Math.floor(10*l(t+.05,1)),w=Math.round(t-b/10);if(_(r)){var S=Math.floor(w/h)+g,E=Math.floor(l(t,h));try{i=v.getComponentMethod(\"calendars\",\"getCal\")(r).fromJD(S).formatDate(\"yyyy-mm-dd\")}catch(t){i=m(\"G%Y-%m-%d\")(new Date(w))}if(\"-\"===i.charAt(0))for(;i.length<11;)i=\"-0\"+i.substr(1);else for(;i.length<10;)i=\"0\"+i;o=e<k?Math.floor(E/f):0,s=e<k?Math.floor(E%f/p):0,c=e<T?Math.floor(E%p/d):0,y=e<M?E%d*10+b:0}else x=new Date(w),i=m(\"%Y-%m-%d\")(x),o=e<k?x.getUTCHours():0,s=e<k?x.getUTCMinutes():0,c=e<T?x.getUTCSeconds():0,y=e<M?10*x.getUTCMilliseconds()+b:0;return A(i,o,s,c,y)},r.ms2DateTimeLocal=function(t){if(!(t>=n+h&&t<=a-h))return u;var e=Math.floor(10*l(t+.05,1)),r=new Date(Math.round(t-e/10));return A(i.time.format(\"%Y-%m-%d\")(r),r.getHours(),r.getMinutes(),r.getSeconds(),10*r.getUTCMilliseconds()+e)},r.cleanDate=function(t,e,n){if(t===u)return e;if(r.isJSDate(t)||\"number\"==typeof t&&isFinite(t)){if(_(n))return s.error(\"JS Dates and milliseconds are incompatible with world calendars\",t),e;if(!(t=r.ms2DateTimeLocal(+t))&&void 0!==e)return e}else if(!r.isDateTime(t,n))return s.error(\"unrecognized date\",t),e;return t};var S=/%\\d?f/g;function E(t,e,r,n){t=t.replace(S,function(t){var r=Math.min(+t.charAt(1)||6,6);return(e/1e3%1+2).toFixed(r).substr(2).replace(/0+$/,\"\")||\"0\"});var a=new Date(Math.floor(e+.05));if(_(n))try{t=v.getComponentMethod(\"calendars\",\"worldCalFmt\")(t,e,n)}catch(t){return\"Invalid\"}return r(t)(a)}var L=[59,59.9,59.99,59.999,59.9999];r.formatDate=function(t,e,r,n,a,i){if(a=_(a)&&a,!e)if(\"y\"===r)e=i.year;else if(\"m\"===r)e=i.month;else{if(\"d\"!==r)return function(t,e){var r=l(t+.05,h),n=w(Math.floor(r/f),2)+\":\"+w(l(Math.floor(r/p),60),2);if(\"M\"!==e){o(e)||(e=0);var a=(100+Math.min(l(t/d,60),L[e])).toFixed(e).substr(1);e>0&&(a=a.replace(/0+$/,\"\").replace(/[\\.]$/,\"\")),n+=\":\"+a}return n}(t,r)+\"\\n\"+E(i.dayMonthYear,t,n,a);e=i.dayMonth+\"\\n\"+i.year}return E(e,t,n,a)};var C=3*h;r.incrementMonth=function(t,e,r){r=_(r)&&r;var n=l(t,h);if(t=Math.round(t-n),r)try{var a=Math.round(t/h)+g,i=v.getComponentMethod(\"calendars\",\"getCal\")(r),o=i.fromJD(a);return e%12?i.add(o,e,\"m\"):i.add(o,e/12,\"y\"),(o.toJD()-g)*h+n}catch(e){s.error(\"invalid ms \"+t+\" in calendar \"+r)}var c=new Date(t+C);return c.setUTCMonth(c.getUTCMonth()+e)+n-C},r.findExactDates=function(t,e){for(var r,n,a=0,i=0,s=0,l=0,c=_(e)&&v.getComponentMethod(\"calendars\",\"getCal\")(e),u=0;u<t.length;u++)if(n=t[u],o(n)){if(!(n%h))if(c)try{1===(r=c.fromJD(n/h+g)).day()?1===r.month()?a++:i++:s++}catch(t){}else 1===(r=new Date(n)).getUTCDate()?0===r.getUTCMonth()?a++:i++:s++}else l++;s+=i+=a;var f=t.length-l;return{exactYears:a/f,exactMonths:i/f,exactDays:s/f}}},{\"../constants/numerical\":693,\"../registry\":846,\"./loggers\":721,\"./mod\":724,d3:165,\"fast-isnumeric\":228}],706:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"./loggers\");function i(t){var e=t&&t.parentNode;e&&e.removeChild(t)}function o(t,e,r){var n=\"plotly.js-style-\"+t,i=document.getElementById(n);i||((i=document.createElement(\"style\")).setAttribute(\"id\",n),i.appendChild(document.createTextNode(\"\")),document.head.appendChild(i));var o=i.sheet;o.insertRule?o.insertRule(e+\"{\"+r+\"}\",0):o.addRule?o.addRule(e,r,0):a.warn(\"addStyleRule failed\")}e.exports={getGraphDiv:function(t){var e;if(\"string\"==typeof t){if(null===(e=document.getElementById(t)))throw new Error(\"No DOM element with id '\"+t+\"' exists on the page.\");return e}if(null==t)throw new Error(\"DOM element provided is null or undefined\");return t},isPlotDiv:function(t){var e=n.select(t);return e.node()instanceof HTMLElement&&e.size()&&e.classed(\"js-plotly-plot\")},removeElement:i,addStyleRule:function(t,e){o(\"global\",t,e)},addRelatedStyleRule:o,deleteRelatedStyleRule:function(t){var e=\"plotly.js-style-\"+t,r=document.getElementById(e);r&&i(r)}}},{\"./loggers\":721,d3:165}],707:[function(t,e,r){\"use strict\";var n=t(\"events\").EventEmitter,a={init:function(t){if(t._ev instanceof n)return t;var e=new n,r=new n;return t._ev=e,t._internalEv=r,t.on=e.on.bind(e),t.once=e.once.bind(e),t.removeListener=e.removeListener.bind(e),t.removeAllListeners=e.removeAllListeners.bind(e),t._internalOn=r.on.bind(r),t._internalOnce=r.once.bind(r),t._removeInternalListener=r.removeListener.bind(r),t._removeAllInternalListeners=r.removeAllListeners.bind(r),t.emit=function(n,a){\"undefined\"!=typeof jQuery&&jQuery(t).trigger(n,a),e.emit(n,a),r.emit(n,a)},t},triggerHandler:function(t,e,r){var n,a;\"undefined\"!=typeof jQuery&&(n=jQuery(t).triggerHandler(e,r));var i=t._ev;if(!i)return n;var o,s=i._events[e];if(!s)return n;function l(t){return t.listener?(i.removeListener(e,t.listener),t.fired?void 0:(t.fired=!0,t.listener.apply(i,[r]))):t.apply(i,[r])}for(s=Array.isArray(s)?s:[s],o=0;o<s.length-1;o++)l(s[o]);return a=l(s[o]),void 0!==n?n:a},purge:function(t){return delete t._ev,delete t.on,delete t.once,delete t.removeListener,delete t.removeAllListeners,delete t.emit,delete t._ev,delete t._internalEv,delete t._internalOn,delete t._internalOnce,delete t._removeInternalListener,delete t._removeAllInternalListeners,t}};e.exports=a},{events:106}],708:[function(t,e,r){\"use strict\";var n=t(\"./is_plain_object.js\"),a=Array.isArray;function i(t,e,r,o){var s,l,c,u,h,f,p=t[0],d=t.length;if(2===d&&a(p)&&a(t[1])&&0===p.length){if(function(t,e){var r,n;for(r=0;r<t.length;r++){if(null!==(n=t[r])&&\"object\"==typeof n)return!1;void 0!==n&&(e[r]=n)}return!0}(t[1],p))return p;p.splice(0,p.length)}for(var g=1;g<d;g++)for(l in s=t[g])c=p[l],u=s[l],o&&a(u)?p[l]=u:e&&u&&(n(u)||(h=a(u)))?(h?(h=!1,f=c&&a(c)?c:[]):f=c&&n(c)?c:{},p[l]=i([f,u],e,r,o)):(\"undefined\"!=typeof u||r)&&(p[l]=u);return p}r.extendFlat=function(){return i(arguments,!1,!1,!1)},r.extendDeep=function(){return i(arguments,!0,!1,!1)},r.extendDeepAll=function(){return i(arguments,!0,!0,!1)},r.extendDeepNoArrays=function(){return i(arguments,!0,!1,!0)}},{\"./is_plain_object.js\":718}],709:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e={},r=[],n=0,a=0;a<t.length;a++){var i=t[a];1!==e[i]&&(e[i]=1,r[n++]=i)}return r}},{}],710:[function(t,e,r){\"use strict\";function n(t){return!0===t.visible}function a(t){var e=t[0].trace;return!0===e.visible&&0!==e._length}e.exports=function(t){for(var e,r=(e=t,Array.isArray(e)&&Array.isArray(e[0])&&e[0][0]&&e[0][0].trace?a:n),i=[],o=0;o<t.length;o++){var s=t[o];r(s)&&i.push(s)}return i}},{}],711:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"country-regex\"),i=t(\"@turf/area\"),o=t(\"@turf/centroid\"),s=t(\"@turf/bbox\"),l=t(\"./identity\"),c=t(\"./loggers\"),u=t(\"./is_plain_object\"),h=t(\"./nested_property\"),f=t(\"./polygon\"),p=Object.keys(a),d={\"ISO-3\":l,\"USA-states\":l,\"country names\":function(t){for(var e=0;e<p.length;e++){var r=p[e],n=new RegExp(a[r]);if(n.test(t.trim().toLowerCase()))return r}return c.log(\"Unrecognized country name: \"+t+\".\"),!1}};function g(t){var e=t.geojson,r=window.PlotlyGeoAssets||{},n=\"string\"==typeof e?r[e]:e;return u(n)?n:(c.error(\"Oops ... something went wrong when fetching \"+e),!1)}e.exports={locationToFeature:function(t,e,r){if(!e||\"string\"!=typeof e)return!1;var n,a,i,o=d[t](e);if(o){if(\"USA-states\"===t)for(n=[],i=0;i<r.length;i++)(a=r[i]).properties&&a.properties.gu&&\"USA\"===a.properties.gu&&n.push(a);else n=r;for(i=0;i<n.length;i++)if((a=n[i]).id===o)return a;c.log([\"Location with id\",o,\"does not have a matching topojson feature at this resolution.\"].join(\" \"))}return!1},feature2polygons:function(t){var e,r,n,a,i=t.geometry,o=i.coordinates,s=t.id,l=[];function c(t){for(var e=0;e<t.length-1;e++)if(t[e][0]>0&&t[e+1][0]<0)return e;return null}switch(e=\"RUS\"===s||\"FJI\"===s?function(t){var e;if(null===c(t))e=t;else for(e=new Array(t.length),a=0;a<t.length;a++)e[a]=[t[a][0]<0?t[a][0]+360:t[a][0],t[a][1]];l.push(f.tester(e))}:\"ATA\"===s?function(t){var e=c(t);if(null===e)return l.push(f.tester(t));var r=new Array(t.length+1),n=0;for(a=0;a<t.length;a++)a>e?r[n++]=[t[a][0]+360,t[a][1]]:a===e?(r[n++]=t[a],r[n++]=[t[a][0],-90]):r[n++]=t[a];var i=f.tester(r);i.pts.pop(),l.push(i)}:function(t){l.push(f.tester(t))},i.type){case\"MultiPolygon\":for(r=0;r<o.length;r++)for(n=0;n<o[r].length;n++)e(o[r][n]);break;case\"Polygon\":for(r=0;r<o.length;r++)e(o[r])}return l},getTraceGeojson:g,extractTraceFeature:function(t){var e=t[0].trace,r=g(e);if(!r)return!1;var n,a={},s=[];for(n=0;n<e._length;n++){var l=t[n];(l.loc||0===l.loc)&&(a[l.loc]=l)}function u(t){var r=h(t,e.featureidkey||\"id\").get(),n=a[r];if(n){var l=t.geometry;if(\"Polygon\"===l.type||\"MultiPolygon\"===l.type){var u={type:\"Feature\",id:r,geometry:l,properties:{}};u.properties.ct=function(t){var e,r=t.geometry;if(\"MultiPolygon\"===r.type)for(var n=r.coordinates,a=0,s=0;s<n.length;s++){var l={type:\"Polygon\",coordinates:n[s]},c=i.default(l);c>a&&(a=c,e=l)}else e=r;return o.default(e).geometry.coordinates}(u),n.fIn=t,n.fOut=u,s.push(u)}else c.log([\"Location\",n.loc,\"does not have a valid GeoJSON geometry.\",\"Traces with locationmode *geojson-id* only support\",\"*Polygon* and *MultiPolygon* geometries.\"].join(\" \"))}delete a[r]}switch(r.type){case\"FeatureCollection\":var f=r.features;for(n=0;n<f.length;n++)u(f[n]);break;case\"Feature\":u(r);break;default:return c.warn([\"Invalid GeoJSON type\",(r.type||\"none\")+\".\",\"Traces with locationmode *geojson-id* only support\",\"*FeatureCollection* and *Feature* types.\"].join(\" \")),!1}for(var p in a)c.log([\"Location *\"+p+\"*\",\"does not have a matching feature with id-key\",\"*\"+e.featureidkey+\"*.\"].join(\" \"));return s},fetchTraceGeoData:function(t){var e=window.PlotlyGeoAssets||{},r=[];function a(t){return new Promise(function(r,a){n.json(t,function(n,i){if(n){delete e[t];var o=404===n.status?'GeoJSON at URL \"'+t+'\" does not exist.':\"Unexpected error while fetching from \"+t;return a(new Error(o))}return e[t]=i,r(i)})})}function i(t){return new Promise(function(r,n){var a=0,i=setInterval(function(){return e[t]&&\"pending\"!==e[t]?(clearInterval(i),r(e[t])):a>100?(clearInterval(i),n(\"Unexpected error while fetching from \"+t)):void a++},50)})}for(var o=0;o<t.length;o++){var s=t[o][0].trace.geojson;\"string\"==typeof s&&(e[s]?\"pending\"===e[s]&&r.push(i(s)):(e[s]=\"pending\",r.push(a(s))))}return r},computeBbox:function(t){return s.default(t)}}},{\"./identity\":716,\"./is_plain_object\":718,\"./loggers\":721,\"./nested_property\":725,\"./polygon\":729,\"@turf/area\":57,\"@turf/bbox\":58,\"@turf/centroid\":59,\"country-regex\":136,d3:165}],712:[function(t,e,r){\"use strict\";var n=t(\"../constants/numerical\").BADNUM;r.calcTraceToLineCoords=function(t){for(var e=t[0].trace.connectgaps,r=[],a=[],i=0;i<t.length;i++){var o=t[i].lonlat;o[0]!==n?a.push(o):!e&&a.length>0&&(r.push(a),a=[])}return a.length>0&&r.push(a),r},r.makeLine=function(t){return 1===t.length?{type:\"LineString\",coordinates:t[0]}:{type:\"MultiLineString\",coordinates:t}},r.makePolygon=function(t){if(1===t.length)return{type:\"Polygon\",coordinates:t};for(var e=new Array(t.length),r=0;r<t.length;r++)e[r]=[t[r]];return{type:\"MultiPolygon\",coordinates:e}},r.makeBlank=function(){return{type:\"Point\",coordinates:[]}}},{\"../constants/numerical\":693}],713:[function(t,e,r){\"use strict\";var n,a,i,o=t(\"./mod\").mod;function s(t,e,r,n,a,i,o,s){var l=r-t,c=a-t,u=o-a,h=n-e,f=i-e,p=s-i,d=l*p-u*h;if(0===d)return null;var g=(c*p-u*f)/d,v=(c*h-l*f)/d;return v<0||v>1||g<0||g>1?null:{x:t+l*g,y:e+h*g}}function l(t,e,r,n,a){var i=n*t+a*e;if(i<0)return n*n+a*a;if(i>r){var o=n-t,s=a-e;return o*o+s*s}var l=n*e-a*t;return l*l/r}r.segmentsIntersect=s,r.segmentDistance=function(t,e,r,n,a,i,o,c){if(s(t,e,r,n,a,i,o,c))return 0;var u=r-t,h=n-e,f=o-a,p=c-i,d=u*u+h*h,g=f*f+p*p,v=Math.min(l(u,h,d,a-t,i-e),l(u,h,d,o-t,c-e),l(f,p,g,t-a,e-i),l(f,p,g,r-a,n-i));return Math.sqrt(v)},r.getTextLocation=function(t,e,r,s){if(t===a&&s===i||(n={},a=t,i=s),n[r])return n[r];var l=t.getPointAtLength(o(r-s/2,e)),c=t.getPointAtLength(o(r+s/2,e)),u=Math.atan((c.y-l.y)/(c.x-l.x)),h=t.getPointAtLength(o(r,e)),f={x:(4*h.x+l.x+c.x)/6,y:(4*h.y+l.y+c.y)/6,theta:u};return n[r]=f,f},r.clearLocationCache=function(){a=null},r.getVisibleSegment=function(t,e,r){var n,a,i=e.left,o=e.right,s=e.top,l=e.bottom,c=0,u=t.getTotalLength(),h=u;function f(e){var r=t.getPointAtLength(e);0===e?n=r:e===u&&(a=r);var c=r.x<i?i-r.x:r.x>o?r.x-o:0,h=r.y<s?s-r.y:r.y>l?r.y-l:0;return Math.sqrt(c*c+h*h)}for(var p=f(c);p;){if((c+=p+r)>h)return;p=f(c)}for(p=f(h);p;){if(c>(h-=p+r))return;p=f(h)}return{min:c,max:h,len:h-c,total:u,isClosed:0===c&&h===u&&Math.abs(n.x-a.x)<.1&&Math.abs(n.y-a.y)<.1}},r.findPointOnPath=function(t,e,r,n){for(var a,i,o,s=(n=n||{}).pathLength||t.getTotalLength(),l=n.tolerance||.001,c=n.iterationLimit||30,u=t.getPointAtLength(0)[r]>t.getPointAtLength(s)[r]?-1:1,h=0,f=0,p=s;h<c;){if(a=(f+p)/2,o=(i=t.getPointAtLength(a))[r]-e,Math.abs(o)<l)return i;u*o>0?p=a:f=a,h++}return i}},{\"./mod\":724}],714:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"tinycolor2\"),i=t(\"color-normalize\"),o=t(\"../components/colorscale\"),s=t(\"../components/color/attributes\").defaultLine,l=t(\"./array\").isArrayOrTypedArray,c=i(s),u=1;function h(t,e){var r=t;return r[3]*=e,r}function f(t){if(n(t))return c;var e=i(t);return e.length?e:c}function p(t){return n(t)?t:u}e.exports={formatColor:function(t,e,r){var n,a,s,d,g,v=t.color,m=l(v),y=l(e),x=o.extractOpts(t),b=[];if(n=void 0!==x.colorscale?o.makeColorScaleFuncFromTrace(t):f,a=m?function(t,e){return void 0===t[e]?c:i(n(t[e]))}:f,s=y?function(t,e){return void 0===t[e]?u:p(t[e])}:p,m||y)for(var _=0;_<r;_++)d=a(v,_),g=s(e,_),b[_]=h(d,g);else b=h(i(v),e);return b},parseColorScale:function(t,e){void 0===e&&(e=1);var r=o.extractOpts(t);return(r.reversescale?o.flipScale(r.colorscale):r.colorscale).map(function(t){var r=t[0],n=a(t[1]).toRgb();return{index:r,rgb:[n.r,n.g,n.b,e]}})}}},{\"../components/color/attributes\":591,\"../components/colorscale\":604,\"./array\":700,\"color-normalize\":122,\"fast-isnumeric\":228,tinycolor2:536}],715:[function(t,e,r){\"use strict\";var n=t(\"./identity\");function a(t){return[t]}e.exports={keyFun:function(t){return t.key},repeat:a,descend:n,wrap:a,unwrap:function(t){return t[0]}}},{\"./identity\":716}],716:[function(t,e,r){\"use strict\";e.exports=function(t){return t}},{}],717:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"fast-isnumeric\"),i=t(\"../constants/numerical\"),o=i.FP_SAFE,s=i.BADNUM,l=e.exports={};l.nestedProperty=t(\"./nested_property\"),l.keyedContainer=t(\"./keyed_container\"),l.relativeAttr=t(\"./relative_attr\"),l.isPlainObject=t(\"./is_plain_object\"),l.toLogRange=t(\"./to_log_range\"),l.relinkPrivateKeys=t(\"./relink_private\");var c=t(\"./array\");l.isTypedArray=c.isTypedArray,l.isArrayOrTypedArray=c.isArrayOrTypedArray,l.isArray1D=c.isArray1D,l.ensureArray=c.ensureArray,l.concat=c.concat,l.maxRowLength=c.maxRowLength,l.minRowLength=c.minRowLength;var u=t(\"./mod\");l.mod=u.mod,l.modHalf=u.modHalf;var h=t(\"./coerce\");l.valObjectMeta=h.valObjectMeta,l.coerce=h.coerce,l.coerce2=h.coerce2,l.coerceFont=h.coerceFont,l.coerceHoverinfo=h.coerceHoverinfo,l.coerceSelectionMarkerOpacity=h.coerceSelectionMarkerOpacity,l.validate=h.validate;var f=t(\"./dates\");l.dateTime2ms=f.dateTime2ms,l.isDateTime=f.isDateTime,l.ms2DateTime=f.ms2DateTime,l.ms2DateTimeLocal=f.ms2DateTimeLocal,l.cleanDate=f.cleanDate,l.isJSDate=f.isJSDate,l.formatDate=f.formatDate,l.incrementMonth=f.incrementMonth,l.dateTick0=f.dateTick0,l.dfltRange=f.dfltRange,l.findExactDates=f.findExactDates,l.MIN_MS=f.MIN_MS,l.MAX_MS=f.MAX_MS;var p=t(\"./search\");l.findBin=p.findBin,l.sorterAsc=p.sorterAsc,l.sorterDes=p.sorterDes,l.distinctVals=p.distinctVals,l.roundUp=p.roundUp,l.sort=p.sort,l.findIndexOfMin=p.findIndexOfMin;var d=t(\"./stats\");l.aggNums=d.aggNums,l.len=d.len,l.mean=d.mean,l.median=d.median,l.midRange=d.midRange,l.variance=d.variance,l.stdev=d.stdev,l.interp=d.interp;var g=t(\"./matrix\");l.init2dArray=g.init2dArray,l.transposeRagged=g.transposeRagged,l.dot=g.dot,l.translationMatrix=g.translationMatrix,l.rotationMatrix=g.rotationMatrix,l.rotationXYMatrix=g.rotationXYMatrix,l.apply2DTransform=g.apply2DTransform,l.apply2DTransform2=g.apply2DTransform2;var v=t(\"./angles\");l.deg2rad=v.deg2rad,l.rad2deg=v.rad2deg,l.angleDelta=v.angleDelta,l.angleDist=v.angleDist,l.isFullCircle=v.isFullCircle,l.isAngleInsideSector=v.isAngleInsideSector,l.isPtInsideSector=v.isPtInsideSector,l.pathArc=v.pathArc,l.pathSector=v.pathSector,l.pathAnnulus=v.pathAnnulus;var m=t(\"./anchor_utils\");l.isLeftAnchor=m.isLeftAnchor,l.isCenterAnchor=m.isCenterAnchor,l.isRightAnchor=m.isRightAnchor,l.isTopAnchor=m.isTopAnchor,l.isMiddleAnchor=m.isMiddleAnchor,l.isBottomAnchor=m.isBottomAnchor;var y=t(\"./geometry2d\");l.segmentsIntersect=y.segmentsIntersect,l.segmentDistance=y.segmentDistance,l.getTextLocation=y.getTextLocation,l.clearLocationCache=y.clearLocationCache,l.getVisibleSegment=y.getVisibleSegment,l.findPointOnPath=y.findPointOnPath;var x=t(\"./extend\");l.extendFlat=x.extendFlat,l.extendDeep=x.extendDeep,l.extendDeepAll=x.extendDeepAll,l.extendDeepNoArrays=x.extendDeepNoArrays;var b=t(\"./loggers\");l.log=b.log,l.warn=b.warn,l.error=b.error;var _=t(\"./regex\");l.counterRegex=_.counter;var w=t(\"./throttle\");l.throttle=w.throttle,l.throttleDone=w.done,l.clearThrottle=w.clear;var k=t(\"./dom\");function T(t){var e={};for(var r in t)for(var n=t[r],a=0;a<n.length;a++)e[n[a]]=+r;return e}l.getGraphDiv=k.getGraphDiv,l.isPlotDiv=k.isPlotDiv,l.removeElement=k.removeElement,l.addStyleRule=k.addStyleRule,l.addRelatedStyleRule=k.addRelatedStyleRule,l.deleteRelatedStyleRule=k.deleteRelatedStyleRule,l.clearResponsive=t(\"./clear_responsive\"),l.makeTraceGroups=t(\"./make_trace_groups\"),l._=t(\"./localize\"),l.notifier=t(\"./notifier\"),l.filterUnique=t(\"./filter_unique\"),l.filterVisible=t(\"./filter_visible\"),l.pushUnique=t(\"./push_unique\"),l.cleanNumber=t(\"./clean_number\"),l.ensureNumber=function(t){return a(t)?(t=Number(t))<-o||t>o?s:a(t)?Number(t):s:s},l.isIndex=function(t,e){return!(void 0!==e&&t>=e)&&(a(t)&&t>=0&&t%1==0)},l.noop=t(\"./noop\"),l.identity=t(\"./identity\"),l.repeat=function(t,e){for(var r=new Array(e),n=0;n<e;n++)r[n]=t;return r},l.swapAttrs=function(t,e,r,n){r||(r=\"x\"),n||(n=\"y\");for(var a=0;a<e.length;a++){var i=e[a],o=l.nestedProperty(t,i.replace(\"?\",r)),s=l.nestedProperty(t,i.replace(\"?\",n)),c=o.get();o.set(s.get()),s.set(c)}},l.raiseToTop=function(t){t.parentNode.appendChild(t)},l.cancelTransition=function(t){return t.transition().duration(0)},l.constrain=function(t,e,r){return e>r?Math.max(r,Math.min(e,t)):Math.max(e,Math.min(r,t))},l.bBoxIntersect=function(t,e,r){return r=r||0,t.left<=e.right+r&&e.left<=t.right+r&&t.top<=e.bottom+r&&e.top<=t.bottom+r},l.simpleMap=function(t,e,r,n){for(var a=t.length,i=new Array(a),o=0;o<a;o++)i[o]=e(t[o],r,n);return i},l.randstr=function t(e,r,n,a){if(n||(n=16),void 0===r&&(r=24),r<=0)return\"0\";var i,o,s=Math.log(Math.pow(2,r))/Math.log(n),c=\"\";for(i=2;s===1/0;i*=2)s=Math.log(Math.pow(2,r/i))/Math.log(n)*i;var u=s-Math.floor(s);for(i=0;i<Math.floor(s);i++)c=Math.floor(Math.random()*n).toString(n)+c;u&&(o=Math.pow(n,u),c=Math.floor(Math.random()*o).toString(n)+c);var h=parseInt(c,n);return e&&e[c]||h!==1/0&&h>=Math.pow(2,r)?a>10?(l.warn(\"randstr failed uniqueness\"),c):t(e,r,n,(a||0)+1):c},l.OptionControl=function(t,e){t||(t={}),e||(e=\"opt\");var r={optionList:[],_newoption:function(n){n[e]=t,r[n.name]=n,r.optionList.push(n)}};return r[\"_\"+e]=t,r},l.smooth=function(t,e){if((e=Math.round(e)||0)<2)return t;var r,n,a,i,o=t.length,s=2*o,l=2*e-1,c=new Array(l),u=new Array(o);for(r=0;r<l;r++)c[r]=(1-Math.cos(Math.PI*(r+1)/e))/(2*e);for(r=0;r<o;r++){for(i=0,n=0;n<l;n++)(a=r+n+1-e)<-o?a-=s*Math.round(a/s):a>=s&&(a-=s*Math.floor(a/s)),a<0?a=-1-a:a>=o&&(a=s-1-a),i+=t[a]*c[n];u[r]=i}return u},l.syncOrAsync=function(t,e,r){var n;function a(){return l.syncOrAsync(t,e,r)}for(;t.length;)if((n=(0,t.splice(0,1)[0])(e))&&n.then)return n.then(a).then(void 0,l.promiseError);return r&&r(e)},l.stripTrailingSlash=function(t){return\"/\"===t.substr(-1)?t.substr(0,t.length-1):t},l.noneOrAll=function(t,e,r){if(t){var n,a=!1,i=!0;for(n=0;n<r.length;n++)null!=t[r[n]]?a=!0:i=!1;if(a&&!i)for(n=0;n<r.length;n++)t[r[n]]=e[r[n]]}},l.mergeArray=function(t,e,r,n){var a=\"function\"==typeof n;if(l.isArrayOrTypedArray(t))for(var i=Math.min(t.length,e.length),o=0;o<i;o++){var s=t[o];e[o][r]=a?n(s):s}},l.mergeArrayCastPositive=function(t,e,r){return l.mergeArray(t,e,r,function(t){var e=+t;return isFinite(e)&&e>0?e:0})},l.fillArray=function(t,e,r,n){if(n=n||l.identity,l.isArrayOrTypedArray(t))for(var a=0;a<e.length;a++)e[a][r]=n(t[a])},l.castOption=function(t,e,r,n){n=n||l.identity;var a=l.nestedProperty(t,r).get();return l.isArrayOrTypedArray(a)?Array.isArray(e)&&l.isArrayOrTypedArray(a[e[0]])?n(a[e[0]][e[1]]):n(a[e]):a},l.extractOption=function(t,e,r,n){if(r in t)return t[r];var a=l.nestedProperty(e,n).get();return Array.isArray(a)?void 0:a},l.tagSelected=function(t,e,r){var n,a,i=e.selectedpoints,o=e._indexToPoints;o&&(n=T(o));for(var s=0;s<i.length;s++){var c=i[s];if(l.isIndex(c)||l.isArrayOrTypedArray(c)&&l.isIndex(c[0])&&l.isIndex(c[1])){var u=n?n[c]:c,h=r?r[u]:u;void 0!==(a=h)&&a<t.length&&(t[h].selected=1)}}},l.selIndices2selPoints=function(t){var e=t.selectedpoints,r=t._indexToPoints;if(r){for(var n=T(r),a=[],i=0;i<e.length;i++){var o=e[i];if(l.isIndex(o)){var s=n[o];l.isIndex(s)&&a.push(s)}}return a}return e},l.getTargetArray=function(t,e){var r=e.target;if(\"string\"==typeof r&&r){var n=l.nestedProperty(t,r).get();return!!Array.isArray(n)&&n}return!!Array.isArray(r)&&r},l.minExtend=function(t,e){var r={};\"object\"!=typeof e&&(e={});var n,a,i,o=Object.keys(t);for(n=0;n<o.length;n++)i=t[a=o[n]],\"_\"!==a.charAt(0)&&\"function\"!=typeof i&&(\"module\"===a?r[a]=i:Array.isArray(i)?r[a]=\"colorscale\"===a?i.slice():i.slice(0,3):l.isTypedArray(i)?r[a]=i.subarray(0,3):r[a]=i&&\"object\"==typeof i?l.minExtend(t[a],e[a]):i);for(o=Object.keys(e),n=0;n<o.length;n++)\"object\"==typeof(i=e[a=o[n]])&&a in r&&\"object\"==typeof r[a]||(r[a]=i);return r},l.titleCase=function(t){return t.charAt(0).toUpperCase()+t.substr(1)},l.containsAny=function(t,e){for(var r=0;r<e.length;r++)if(-1!==t.indexOf(e[r]))return!0;return!1},l.isIE=function(){return\"undefined\"!=typeof window.navigator.msSaveBlob};var M=/MSIE [1-9]\\./;l.isIE9orBelow=function(){return l.isIE()&&M.test(window.navigator.userAgent)};var A=/Version\\/[\\d\\.]+.*Safari/;l.isSafari=function(){return A.test(window.navigator.userAgent)},l.isD3Selection=function(t){return t&&\"function\"==typeof t.classed},l.ensureSingle=function(t,e,r,n){var a=t.select(e+(r?\".\"+r:\"\"));if(a.size())return a;var i=t.append(e);return r&&i.classed(r,!0),n&&i.call(n),i},l.ensureSingleById=function(t,e,r,n){var a=t.select(e+\"#\"+r);if(a.size())return a;var i=t.append(e).attr(\"id\",r);return n&&i.call(n),i},l.objectFromPath=function(t,e){for(var r,n=t.split(\".\"),a=r={},i=0;i<n.length;i++){var o=n[i],s=null,l=n[i].match(/(.*)\\[([0-9]+)\\]/);l?(o=l[1],s=l[2],r=r[o]=[],i===n.length-1?r[s]=e:r[s]={},r=r[s]):(i===n.length-1?r[o]=e:r[o]={},r=r[o])}return a};var S=/^([^\\[\\.]+)\\.(.+)?/,E=/^([^\\.]+)\\[([0-9]+)\\](\\.)?(.+)?/;l.expandObjectPaths=function(t){var e,r,n,a,i,o,s;if(\"object\"==typeof t&&!Array.isArray(t))for(r in t)t.hasOwnProperty(r)&&((e=r.match(S))?(a=t[r],n=e[1],delete t[r],t[n]=l.extendDeepNoArrays(t[n]||{},l.objectFromPath(r,l.expandObjectPaths(a))[n])):(e=r.match(E))?(a=t[r],n=e[1],i=parseInt(e[2]),delete t[r],t[n]=t[n]||[],\".\"===e[3]?(s=e[4],o=t[n][i]=t[n][i]||{},l.extendDeepNoArrays(o,l.objectFromPath(s,l.expandObjectPaths(a)))):t[n][i]=l.expandObjectPaths(a)):t[r]=l.expandObjectPaths(t[r]));return t},l.numSeparate=function(t,e,r){if(r||(r=!1),\"string\"!=typeof e||0===e.length)throw new Error(\"Separator string required for formatting!\");\"number\"==typeof t&&(t=String(t));var n=/(\\d+)(\\d{3})/,a=e.charAt(0),i=e.charAt(1),o=t.split(\".\"),s=o[0],l=o.length>1?a+o[1]:\"\";if(i&&(o.length>1||s.length>4||r))for(;n.test(s);)s=s.replace(n,\"$1\"+i+\"$2\");return s+l},l.TEMPLATE_STRING_REGEX=/%{([^\\s%{}:]*)([:|\\|][^}]*)?}/g;var L=/^\\w*$/;l.templateString=function(t,e){var r={};return t.replace(l.TEMPLATE_STRING_REGEX,function(t,n){var a;return L.test(n)?a=e[n]:(r[n]=r[n]||l.nestedProperty(e,n).get,a=r[n]()),l.isValidTextValue(a)?a:\"\"})};var C={max:10,count:0,name:\"hovertemplate\"};l.hovertemplateString=function(){return z.apply(C,arguments)};var P={max:10,count:0,name:\"texttemplate\"};l.texttemplateString=function(){return z.apply(P,arguments)};var O=/^[:|\\|]/;function z(t,e,r){var a=this,i=arguments;e||(e={});var o={};return t.replace(l.TEMPLATE_STRING_REGEX,function(t,s,c){var u,h,f,p;for(f=3;f<i.length;f++)if(u=i[f]){if(u.hasOwnProperty(s)){h=u[s];break}if(L.test(s)||(h=o[s]||l.nestedProperty(u,s).get())&&(o[s]=h),void 0!==h)break}if(void 0===h&&a)return a.count<a.max&&(l.warn(\"Variable '\"+s+\"' in \"+a.name+\" could not be found!\"),h=t),a.count===a.max&&l.warn(\"Too many \"+a.name+\" warnings - additional warnings will be suppressed\"),a.count++,t;if(c){if(\":\"===c[0]&&(h=(p=r?r.numberFormat:n.format)(c.replace(O,\"\"))(h)),\"|\"===c[0]){p=r?r.timeFormat.utc:n.time.format.utc;var d=l.dateTime2ms(h);h=l.formatDate(d,c.replace(O,\"\"),!1,p)}}else e.hasOwnProperty(s+\"Label\")&&(h=e[s+\"Label\"]);return h})}l.subplotSort=function(t,e){for(var r=Math.min(t.length,e.length)+1,n=0,a=0,i=0;i<r;i++){var o=t.charCodeAt(i)||0,s=e.charCodeAt(i)||0,l=o>=48&&o<=57,c=s>=48&&s<=57;if(l&&(n=10*n+o-48),c&&(a=10*a+s-48),!l||!c){if(n!==a)return n-a;if(o!==s)return o-s}}return a-n};var I=2e9;l.seedPseudoRandom=function(){I=2e9},l.pseudoRandom=function(){var t=I;return I=(69069*I+1)%4294967296,Math.abs(I-t)<429496729?l.pseudoRandom():I/4294967296},l.fillText=function(t,e,r){var n=Array.isArray(r)?function(t){r.push(t)}:function(t){r.text=t},a=l.extractOption(t,e,\"htx\",\"hovertext\");if(l.isValidTextValue(a))return n(a);var i=l.extractOption(t,e,\"tx\",\"text\");return l.isValidTextValue(i)?n(i):void 0},l.isValidTextValue=function(t){return t||0===t},l.formatPercent=function(t,e){e=e||0;for(var r=(Math.round(100*t*Math.pow(10,e))*Math.pow(.1,e)).toFixed(e)+\"%\",n=0;n<e;n++)-1!==r.indexOf(\".\")&&(r=(r=r.replace(\"0%\",\"%\")).replace(\".%\",\"%\"));return r},l.isHidden=function(t){var e=window.getComputedStyle(t).display;return!e||\"none\"===e},l.getTextTransform=function(t){var e=t.noCenter,r=t.textX,n=t.textY,a=t.targetX,i=t.targetY,o=t.anchorX||0,s=t.anchorY||0,l=t.rotate,c=t.scale;return c?c>1&&(c=1):c=0,\"translate(\"+(a-c*(r+o))+\",\"+(i-c*(n+s))+\")\"+(c<1?\"scale(\"+c+\")\":\"\")+(l?\"rotate(\"+l+(e?\"\":\" \"+r+\" \"+n)+\")\":\"\")},l.ensureUniformFontSize=function(t,e){var r=l.extendFlat({},e);return r.size=Math.max(e.size,t._fullLayout.uniformtext.minsize||0),r}},{\"../constants/numerical\":693,\"./anchor_utils\":698,\"./angles\":699,\"./array\":700,\"./clean_number\":701,\"./clear_responsive\":703,\"./coerce\":704,\"./dates\":705,\"./dom\":706,\"./extend\":708,\"./filter_unique\":709,\"./filter_visible\":710,\"./geometry2d\":713,\"./identity\":716,\"./is_plain_object\":718,\"./keyed_container\":719,\"./localize\":720,\"./loggers\":721,\"./make_trace_groups\":722,\"./matrix\":723,\"./mod\":724,\"./nested_property\":725,\"./noop\":726,\"./notifier\":727,\"./push_unique\":731,\"./regex\":733,\"./relative_attr\":734,\"./relink_private\":735,\"./search\":736,\"./stats\":739,\"./throttle\":742,\"./to_log_range\":743,d3:165,\"fast-isnumeric\":228}],718:[function(t,e,r){\"use strict\";e.exports=function(t){return window&&window.process&&window.process.versions?\"[object Object]\"===Object.prototype.toString.call(t):\"[object Object]\"===Object.prototype.toString.call(t)&&Object.getPrototypeOf(t)===Object.prototype}},{}],719:[function(t,e,r){\"use strict\";var n=t(\"./nested_property\"),a=/^\\w*$/;e.exports=function(t,e,r,i){var o,s,l;r=r||\"name\",i=i||\"value\";var c={};e&&e.length?(l=n(t,e),s=l.get()):s=t,e=e||\"\";var u={};if(s)for(o=0;o<s.length;o++)u[s[o][r]]=o;var h=a.test(i),f={set:function(t,e){var a=null===e?4:0;if(!s){if(!l||4===a)return;s=[],l.set(s)}var o=u[t];if(void 0===o){if(4===a)return;a|=3,o=s.length,u[t]=o}else e!==(h?s[o][i]:n(s[o],i).get())&&(a|=2);var p=s[o]=s[o]||{};return p[r]=t,h?p[i]=e:n(p,i).set(e),null!==e&&(a&=-5),c[o]=c[o]|a,f},get:function(t){if(s){var e=u[t];return void 0===e?void 0:h?s[e][i]:n(s[e],i).get()}},rename:function(t,e){var n=u[t];return void 0===n?f:(c[n]=1|c[n],u[e]=n,delete u[t],s[n][r]=e,f)},remove:function(t){var e=u[t];if(void 0===e)return f;var a=s[e];if(Object.keys(a).length>2)return c[e]=2|c[e],f.set(t,null);if(h){for(o=e;o<s.length;o++)c[o]=3|c[o];for(o=e;o<s.length;o++)u[s[o][r]]--;s.splice(e,1),delete u[t]}else n(a,i).set(null),c[e]=6|c[e];return f},constructUpdate:function(){for(var t,a,o={},l=Object.keys(c),u=0;u<l.length;u++)a=l[u],t=e+\"[\"+a+\"]\",s[a]?(1&c[a]&&(o[t+\".\"+r]=s[a][r]),2&c[a]&&(o[t+\".\"+i]=h?4&c[a]?null:s[a][i]:4&c[a]?null:n(s[a],i).get())):o[t]=null;return o}};return f}},{\"./nested_property\":725}],720:[function(t,e,r){\"use strict\";var n=t(\"../registry\");e.exports=function(t,e){for(var r=t._context.locale,a=0;a<2;a++){for(var i=t._context.locales,o=0;o<2;o++){var s=(i[r]||{}).dictionary;if(s){var l=s[e];if(l)return l}i=n.localeRegistry}var c=r.split(\"-\")[0];if(c===r)break;r=c}return e}},{\"../registry\":846}],721:[function(t,e,r){\"use strict\";var n=t(\"../plot_api/plot_config\").dfltConfig,a=t(\"./notifier\"),i=e.exports={};function o(t,e){if(t&&t.apply)try{return void t.apply(console,e)}catch(t){}for(var r=0;r<e.length;r++)try{t(e[r])}catch(t){console.log(e[r])}}i.log=function(){var t;if(n.logging>1){var e=[\"LOG:\"];for(t=0;t<arguments.length;t++)e.push(arguments[t]);o(console.trace||console.log,e)}if(n.notifyOnLogging>1){var r=[];for(t=0;t<arguments.length;t++)r.push(arguments[t]);a(r.join(\"<br>\"),\"long\")}},i.warn=function(){var t;if(n.logging>0){var e=[\"WARN:\"];for(t=0;t<arguments.length;t++)e.push(arguments[t]);o(console.trace||console.log,e)}if(n.notifyOnLogging>0){var r=[];for(t=0;t<arguments.length;t++)r.push(arguments[t]);a(r.join(\"<br>\"),\"stick\")}},i.error=function(){var t;if(n.logging>0){var e=[\"ERROR:\"];for(t=0;t<arguments.length;t++)e.push(arguments[t]);o(console.error,e)}if(n.notifyOnLogging>0){var r=[];for(t=0;t<arguments.length;t++)r.push(arguments[t]);a(r.join(\"<br>\"),\"stick\")}}},{\"../plot_api/plot_config\":753,\"./notifier\":727}],722:[function(t,e,r){\"use strict\";var n=t(\"d3\");e.exports=function(t,e,r){var a=t.selectAll(\"g.\"+r.replace(/\\s/g,\".\")).data(e,function(t){return t[0].trace.uid});a.exit().remove(),a.enter().append(\"g\").attr(\"class\",r),a.order();var i=t.classed(\"rangeplot\")?\"nodeRangePlot3\":\"node3\";return a.each(function(t){t[0][i]=n.select(this)}),a}},{d3:165}],723:[function(t,e,r){\"use strict\";r.init2dArray=function(t,e){for(var r=new Array(t),n=0;n<t;n++)r[n]=new Array(e);return r},r.transposeRagged=function(t){var e,r,n=0,a=t.length;for(e=0;e<a;e++)n=Math.max(n,t[e].length);var i=new Array(n);for(e=0;e<n;e++)for(i[e]=new Array(a),r=0;r<a;r++)i[e][r]=t[r][e];return i},r.dot=function(t,e){if(!t.length||!e.length||t.length!==e.length)return null;var n,a,i=t.length;if(t[0].length)for(n=new Array(i),a=0;a<i;a++)n[a]=r.dot(t[a],e);else if(e[0].length){var o=r.transposeRagged(e);for(n=new Array(o.length),a=0;a<o.length;a++)n[a]=r.dot(t,o[a])}else for(n=0,a=0;a<i;a++)n+=t[a]*e[a];return n},r.translationMatrix=function(t,e){return[[1,0,t],[0,1,e],[0,0,1]]},r.rotationMatrix=function(t){var e=t*Math.PI/180;return[[Math.cos(e),-Math.sin(e),0],[Math.sin(e),Math.cos(e),0],[0,0,1]]},r.rotationXYMatrix=function(t,e,n){return r.dot(r.dot(r.translationMatrix(e,n),r.rotationMatrix(t)),r.translationMatrix(-e,-n))},r.apply2DTransform=function(t){return function(){var e=arguments;3===e.length&&(e=e[0]);var n=1===arguments.length?e[0]:[e[0],e[1]];return r.dot(t,[n[0],n[1],1]).slice(0,2)}},r.apply2DTransform2=function(t){var e=r.apply2DTransform(t);return function(t){return e(t.slice(0,2)).concat(e(t.slice(2,4)))}}},{}],724:[function(t,e,r){\"use strict\";e.exports={mod:function(t,e){var r=t%e;return r<0?r+e:r},modHalf:function(t,e){return Math.abs(t)>e/2?t-Math.round(t/e)*e:t}}},{}],725:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"./array\").isArrayOrTypedArray;function i(t,e){return function(){var r,n,o,s,l,c=t;for(s=0;s<e.length-1;s++){if(-1===(r=e[s])){for(n=!0,o=[],l=0;l<c.length;l++)o[l]=i(c[l],e.slice(s+1))(),o[l]!==o[0]&&(n=!1);return n?o[0]:o}if(\"number\"==typeof r&&!a(c))return;if(\"object\"!=typeof(c=c[r])||null===c)return}if(\"object\"==typeof c&&null!==c&&null!==(o=c[e[s]]))return o}}e.exports=function(t,e){if(n(e))e=String(e);else if(\"string\"!=typeof e||\"[-1]\"===e.substr(e.length-4))throw\"bad property string\";for(var r,a,o,s=0,c=e.split(\".\");s<c.length;){if(r=String(c[s]).match(/^([^\\[\\]]*)((\\[\\-?[0-9]*\\])+)$/)){if(r[1])c[s]=r[1];else{if(0!==s)throw\"bad property string\";c.splice(0,1)}for(a=r[2].substr(1,r[2].length-2).split(\"][\"),o=0;o<a.length;o++)s++,c.splice(s,0,Number(a[o]))}s++}return\"object\"!=typeof t?function(t,e,r){return{set:function(){throw\"bad container\"},get:function(){},astr:e,parts:r,obj:t}}(t,e,c):{set:l(t,c,e),get:i(t,c),astr:e,parts:c,obj:t}};var o=/(^|\\.)args\\[/;function s(t,e){return void 0===t||null===t&&!e.match(o)}function l(t,e,r){return function(n){var i,o,l=t,f=\"\",p=[[t,f]],d=s(n,r);for(o=0;o<e.length-1;o++){if(\"number\"==typeof(i=e[o])&&!a(l))throw\"array index but container is not an array\";if(-1===i){if(d=!u(l,e.slice(o+1),n,r))break;return}if(!h(l,i,e[o+1],d))break;if(\"object\"!=typeof(l=l[i])||null===l)throw\"container is not an object\";f=c(f,i),p.push([l,f])}if(d){if(o===e.length-1&&(delete l[e[o]],Array.isArray(l)&&+e[o]==l.length-1))for(;l.length&&void 0===l[l.length-1];)l.pop()}else l[e[o]]=n}}function c(t,e){var r=e;return n(e)?r=\"[\"+e+\"]\":t&&(r=\".\"+e),t+r}function u(t,e,r,n){var i,o=a(r),c=!0,u=r,f=n.replace(\"-1\",0),p=!o&&s(r,f),d=e[0];for(i=0;i<t.length;i++)f=n.replace(\"-1\",i),o&&(p=s(u=r[i%r.length],f)),p&&(c=!1),h(t,i,d,p)&&l(t[i],e,n.replace(\"-1\",i))(u);return c}function h(t,e,r,n){if(void 0===t[e]){if(n)return!1;t[e]=\"number\"==typeof r?[]:{}}return!0}},{\"./array\":700,\"fast-isnumeric\":228}],726:[function(t,e,r){\"use strict\";e.exports=function(){}},{}],727:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"fast-isnumeric\"),i=[];e.exports=function(t,e){if(-1===i.indexOf(t)){i.push(t);var r=1e3;a(e)?r=e:\"long\"===e&&(r=3e3);var o=n.select(\"body\").selectAll(\".plotly-notifier\").data([0]);o.enter().append(\"div\").classed(\"plotly-notifier\",!0),o.selectAll(\".notifier-note\").data(i).enter().append(\"div\").classed(\"notifier-note\",!0).style(\"opacity\",0).each(function(t){var a=n.select(this);a.append(\"button\").classed(\"notifier-close\",!0).html(\"&times;\").on(\"click\",function(){a.transition().call(s)});for(var i=a.append(\"p\"),o=t.split(/<br\\s*\\/?>/g),l=0;l<o.length;l++)l&&i.append(\"br\"),i.append(\"span\").text(o[l]);\"stick\"===e?a.transition().duration(350).style(\"opacity\",1):a.transition().duration(700).style(\"opacity\",1).transition().delay(r).call(s)})}function s(t){t.duration(700).style(\"opacity\",0).each(\"end\",function(t){var e=i.indexOf(t);-1!==e&&i.splice(e,1),n.select(this).remove()})}}},{d3:165,\"fast-isnumeric\":228}],728:[function(t,e,r){\"use strict\";var n=t(\"./setcursor\"),a=\"data-savedcursor\";e.exports=function(t,e){var r=t.attr(a);if(e){if(!r){for(var i=(t.attr(\"class\")||\"\").split(\" \"),o=0;o<i.length;o++){var s=i[o];0===s.indexOf(\"cursor-\")&&t.attr(a,s.substr(7)).classed(s,!1)}t.attr(a)||t.attr(a,\"!!\")}n(t,e)}else r&&(t.attr(a,null),\"!!\"===r?n(t):n(t,r))}},{\"./setcursor\":737}],729:[function(t,e,r){\"use strict\";var n=t(\"./matrix\").dot,a=t(\"../constants/numerical\").BADNUM,i=e.exports={};i.tester=function(t){var e,r=t.slice(),n=r[0][0],i=n,o=r[0][1],s=o;for(r.push(r[0]),e=1;e<r.length;e++)n=Math.min(n,r[e][0]),i=Math.max(i,r[e][0]),o=Math.min(o,r[e][1]),s=Math.max(s,r[e][1]);var l,c=!1;5===r.length&&(r[0][0]===r[1][0]?r[2][0]===r[3][0]&&r[0][1]===r[3][1]&&r[1][1]===r[2][1]&&(c=!0,l=function(t){return t[0]===r[0][0]}):r[0][1]===r[1][1]&&r[2][1]===r[3][1]&&r[0][0]===r[3][0]&&r[1][0]===r[2][0]&&(c=!0,l=function(t){return t[1]===r[0][1]}));var u=!0,h=r[0];for(e=1;e<r.length;e++)if(h[0]!==r[e][0]||h[1]!==r[e][1]){u=!1;break}return{xmin:n,xmax:i,ymin:o,ymax:s,pts:r,contains:c?function(t,e){var r=t[0],c=t[1];return!(r===a||r<n||r>i||c===a||c<o||c>s||e&&l(t))}:function(t,e){var l=t[0],c=t[1];if(l===a||l<n||l>i||c===a||c<o||c>s)return!1;var u,h,f,p,d,g=r.length,v=r[0][0],m=r[0][1],y=0;for(u=1;u<g;u++)if(h=v,f=m,v=r[u][0],m=r[u][1],!(l<(p=Math.min(h,v))||l>Math.max(h,v)||c>Math.max(f,m)))if(c<Math.min(f,m))l!==p&&y++;else{if(c===(d=v===h?c:f+(l-h)*(m-f)/(v-h)))return 1!==u||!e;c<=d&&l!==p&&y++}return y%2==1},isRect:c,degenerate:u}},i.isSegmentBent=function(t,e,r,a){var i,o,s,l=t[e],c=[t[r][0]-l[0],t[r][1]-l[1]],u=n(c,c),h=Math.sqrt(u),f=[-c[1]/h,c[0]/h];for(i=e+1;i<r;i++)if(o=[t[i][0]-l[0],t[i][1]-l[1]],(s=n(o,c))<0||s>u||Math.abs(n(o,f))>a)return!0;return!1},i.filter=function(t,e){var r=[t[0]],n=0,a=0;function o(o){t.push(o);var s=r.length,l=n;r.splice(a+1);for(var c=l+1;c<t.length;c++)(c===t.length-1||i.isSegmentBent(t,l,c+1,e))&&(r.push(t[c]),r.length<s-2&&(n=c,a=r.length-1),l=c)}t.length>1&&o(t.pop());return{addPt:o,raw:t,filtered:r}}},{\"../constants/numerical\":693,\"./matrix\":723}],730:[function(t,e,r){(function(r){\"use strict\";var n=t(\"./show_no_webgl_msg\"),a=t(\"regl\");e.exports=function(t,e){var i=t._fullLayout,o=!0;return i._glcanvas.each(function(n){if(!n.regl&&(!n.pick||i._has(\"parcoords\"))){try{n.regl=a({canvas:this,attributes:{antialias:!n.pick,preserveDrawingBuffer:!0},pixelRatio:t._context.plotGlPixelRatio||r.devicePixelRatio,extensions:e||[]})}catch(t){o=!1}o&&this.addEventListener(\"webglcontextlost\",function(e){t&&t.emit&&t.emit(\"plotly_webglcontextlost\",{event:e,layer:n.key})},!1)}}),o||n({container:i._glcontainer.node()}),o}}).call(this,\"undefined\"!=typeof global?global:\"undefined\"!=typeof self?self:\"undefined\"!=typeof window?window:{})},{\"./show_no_webgl_msg\":738,regl:501}],731:[function(t,e,r){\"use strict\";e.exports=function(t,e){if(e instanceof RegExp){for(var r=e.toString(),n=0;n<t.length;n++)if(t[n]instanceof RegExp&&t[n].toString()===r)return t;t.push(e)}else!e&&0!==e||-1!==t.indexOf(e)||t.push(e);return t}},{}],732:[function(t,e,r){\"use strict\";var n=t(\"../lib\"),a=t(\"../plot_api/plot_config\").dfltConfig;var i={add:function(t,e,r,n,i){var o,s;t.undoQueue=t.undoQueue||{index:0,queue:[],sequence:!1},s=t.undoQueue.index,t.autoplay?t.undoQueue.inSequence||(t.autoplay=!1):(!t.undoQueue.sequence||t.undoQueue.beginSequence?(o={undo:{calls:[],args:[]},redo:{calls:[],args:[]}},t.undoQueue.queue.splice(s,t.undoQueue.queue.length-s,o),t.undoQueue.index+=1):o=t.undoQueue.queue[s-1],t.undoQueue.beginSequence=!1,o&&(o.undo.calls.unshift(e),o.undo.args.unshift(r),o.redo.calls.push(n),o.redo.args.push(i)),t.undoQueue.queue.length>a.queueLength&&(t.undoQueue.queue.shift(),t.undoQueue.index--))},startSequence:function(t){t.undoQueue=t.undoQueue||{index:0,queue:[],sequence:!1},t.undoQueue.sequence=!0,t.undoQueue.beginSequence=!0},stopSequence:function(t){t.undoQueue=t.undoQueue||{index:0,queue:[],sequence:!1},t.undoQueue.sequence=!1,t.undoQueue.beginSequence=!1},undo:function(t){var e,r;if(t.framework&&t.framework.isPolar)t.framework.undo();else if(!(void 0===t.undoQueue||isNaN(t.undoQueue.index)||t.undoQueue.index<=0)){for(t.undoQueue.index--,e=t.undoQueue.queue[t.undoQueue.index],t.undoQueue.inSequence=!0,r=0;r<e.undo.calls.length;r++)i.plotDo(t,e.undo.calls[r],e.undo.args[r]);t.undoQueue.inSequence=!1,t.autoplay=!1}},redo:function(t){var e,r;if(t.framework&&t.framework.isPolar)t.framework.redo();else if(!(void 0===t.undoQueue||isNaN(t.undoQueue.index)||t.undoQueue.index>=t.undoQueue.queue.length)){for(e=t.undoQueue.queue[t.undoQueue.index],t.undoQueue.inSequence=!0,r=0;r<e.redo.calls.length;r++)i.plotDo(t,e.redo.calls[r],e.redo.args[r]);t.undoQueue.inSequence=!1,t.autoplay=!1,t.undoQueue.index++}}};i.plotDo=function(t,e,r){t.autoplay=!0,r=function(t,e){for(var r,a=[],i=0;i<e.length;i++)r=e[i],a[i]=r===t?r:\"object\"==typeof r?Array.isArray(r)?n.extendDeep([],r):n.extendDeepAll({},r):r;return a}(t,r),e.apply(null,r)},e.exports=i},{\"../lib\":717,\"../plot_api/plot_config\":753}],733:[function(t,e,r){\"use strict\";r.counter=function(t,e,r,n){var a=(e||\"\")+(r?\"\":\"$\"),i=!1===n?\"\":\"^\";return\"xy\"===t?new RegExp(i+\"x([2-9]|[1-9][0-9]+)?y([2-9]|[1-9][0-9]+)?\"+a):new RegExp(i+t+\"([2-9]|[1-9][0-9]+)?\"+a)}},{}],734:[function(t,e,r){\"use strict\";var n=/^(.*)(\\.[^\\.\\[\\]]+|\\[\\d\\])$/,a=/^[^\\.\\[\\]]+$/;e.exports=function(t,e){for(;e;){var r=t.match(n);if(r)t=r[1];else{if(!t.match(a))throw new Error(\"bad relativeAttr call:\"+[t,e]);t=\"\"}if(\"^\"!==e.charAt(0))break;e=e.slice(1)}return t&&\"[\"!==e.charAt(0)?t+\".\"+e:t+e}},{}],735:[function(t,e,r){\"use strict\";var n=t(\"./array\").isArrayOrTypedArray,a=t(\"./is_plain_object\");e.exports=function t(e,r){for(var i in r){var o=r[i],s=e[i];if(s!==o)if(\"_\"===i.charAt(0)||\"function\"==typeof o){if(i in e)continue;e[i]=o}else if(n(o)&&n(s)&&a(o[0])){if(\"customdata\"===i||\"ids\"===i)continue;for(var l=Math.min(o.length,s.length),c=0;c<l;c++)s[c]!==o[c]&&a(o[c])&&a(s[c])&&t(s[c],o[c])}else a(o)&&a(s)&&(t(s,o),Object.keys(s).length||delete e[i])}}},{\"./array\":700,\"./is_plain_object\":718}],736:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"./loggers\"),i=t(\"./identity\");function o(t,e){return t<e}function s(t,e){return t<=e}function l(t,e){return t>e}function c(t,e){return t>=e}r.findBin=function(t,e,r){if(n(e.start))return r?Math.ceil((t-e.start)/e.size-1e-9)-1:Math.floor((t-e.start)/e.size+1e-9);var i,u,h=0,f=e.length,p=0,d=f>1?(e[f-1]-e[0])/(f-1):1;for(u=d>=0?r?o:s:r?c:l,t+=1e-9*d*(r?-1:1)*(d>=0?1:-1);h<f&&p++<100;)u(e[i=Math.floor((h+f)/2)],t)?h=i+1:f=i;return p>90&&a.log(\"Long binary search...\"),h-1},r.sorterAsc=function(t,e){return t-e},r.sorterDes=function(t,e){return e-t},r.distinctVals=function(t){var e=t.slice();e.sort(r.sorterAsc);for(var n=e.length-1,a=e[n]-e[0]||1,i=a/(n||1)/1e4,o=[e[0]],s=0;s<n;s++)e[s+1]>e[s]+i&&(a=Math.min(a,e[s+1]-e[s]),o.push(e[s+1]));return{vals:o,minDiff:a}},r.roundUp=function(t,e,r){for(var n,a=0,i=e.length-1,o=0,s=r?0:1,l=r?1:0,c=r?Math.ceil:Math.floor;a<i&&o++<100;)e[n=c((a+i)/2)]<=t?a=n+s:i=n-l;return e[a]},r.sort=function(t,e){for(var r=0,n=0,a=1;a<t.length;a++){var i=e(t[a],t[a-1]);if(i<0?r=1:i>0&&(n=1),r&&n)return t.sort(e)}return n?t:t.reverse()},r.findIndexOfMin=function(t,e){e=e||i;for(var r,n=1/0,a=0;a<t.length;a++){var o=e(t[a]);o<n&&(n=o,r=a)}return r}},{\"./identity\":716,\"./loggers\":721,\"fast-isnumeric\":228}],737:[function(t,e,r){\"use strict\";e.exports=function(t,e){(t.attr(\"class\")||\"\").split(\" \").forEach(function(e){0===e.indexOf(\"cursor-\")&&t.classed(e,!1)}),e&&t.classed(\"cursor-\"+e,!0)}},{}],738:[function(t,e,r){\"use strict\";var n=t(\"../components/color\"),a=function(){};e.exports=function(t){for(var e in t)\"function\"==typeof t[e]&&(t[e]=a);t.destroy=function(){t.container.parentNode.removeChild(t.container)};var r=document.createElement(\"div\");r.className=\"no-webgl\",r.style.cursor=\"pointer\",r.style.fontSize=\"24px\",r.style.color=n.defaults[0],r.style.position=\"absolute\",r.style.left=r.style.top=\"0px\",r.style.width=r.style.height=\"100%\",r.style[\"background-color\"]=n.lightLine,r.style[\"z-index\"]=30;var i=document.createElement(\"p\");return i.textContent=\"WebGL is not supported by your browser - visit https://get.webgl.org for more info\",i.style.position=\"relative\",i.style.top=\"50%\",i.style.left=\"50%\",i.style.height=\"30%\",i.style.width=\"50%\",i.style.margin=\"-15% 0 0 -25%\",r.appendChild(i),t.container.appendChild(r),t.container.style.background=\"#FFFFFF\",t.container.onclick=function(){window.open(\"https://get.webgl.org\")},!1}},{\"../components/color\":592}],739:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"./array\").isArrayOrTypedArray;r.aggNums=function(t,e,i,o){var s,l;if((!o||o>i.length)&&(o=i.length),n(e)||(e=!1),a(i[0])){for(l=new Array(o),s=0;s<o;s++)l[s]=r.aggNums(t,e,i[s]);i=l}for(s=0;s<o;s++)n(e)?n(i[s])&&(e=t(+e,+i[s])):e=i[s];return e},r.len=function(t){return r.aggNums(function(t){return t+1},0,t)},r.mean=function(t,e){return e||(e=r.len(t)),r.aggNums(function(t,e){return t+e},0,t)/e},r.midRange=function(t){if(void 0!==t&&0!==t.length)return(r.aggNums(Math.max,null,t)+r.aggNums(Math.min,null,t))/2},r.variance=function(t,e,a){return e||(e=r.len(t)),n(a)||(a=r.mean(t,e)),r.aggNums(function(t,e){return t+Math.pow(e-a,2)},0,t)/e},r.stdev=function(t,e,n){return Math.sqrt(r.variance(t,e,n))},r.median=function(t){var e=t.slice().sort();return r.interp(e,.5)},r.interp=function(t,e){if(!n(e))throw\"n should be a finite number\";if((e=e*t.length-.5)<0)return t[0];if(e>t.length-1)return t[t.length-1];var r=e%1;return r*t[Math.ceil(e)]+(1-r)*t[Math.floor(e)]}},{\"./array\":700,\"fast-isnumeric\":228}],740:[function(t,e,r){\"use strict\";var n=t(\"color-normalize\");e.exports=function(t){return t?n(t):[0,0,0,1]}},{\"color-normalize\":122}],741:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../lib\"),i=t(\"../constants/xmlns_namespaces\"),o=t(\"../constants/alignment\").LINE_SPACING;function s(t,e){return t.node().getBoundingClientRect()[e]}var l=/([^$]*)([$]+[^$]*[$]+)([^$]*)/;r.convertToTspans=function(t,e,A){var S=t.text(),L=!t.attr(\"data-notex\")&&\"undefined\"!=typeof MathJax&&S.match(l),C=n.select(t.node().parentNode);if(!C.empty()){var P=t.attr(\"class\")?t.attr(\"class\").split(\" \")[0]:\"text\";return P+=\"-math\",C.selectAll(\"svg.\"+P).remove(),C.selectAll(\"g.\"+P+\"-group\").remove(),t.style(\"display\",null).attr({\"data-unformatted\":S,\"data-math\":\"N\"}),L?(e&&e._promises||[]).push(new Promise(function(e){t.style(\"display\",\"none\");var r=parseInt(t.node().style.fontSize,10),i={fontSize:r};!function(t,e,r){var i,o,s,l;MathJax.Hub.Queue(function(){return o=a.extendDeepAll({},MathJax.Hub.config),s=MathJax.Hub.processSectionDelay,void 0!==MathJax.Hub.processSectionDelay&&(MathJax.Hub.processSectionDelay=0),MathJax.Hub.Config({messageStyle:\"none\",tex2jax:{inlineMath:[[\"$\",\"$\"],[\"\\\\(\",\"\\\\)\"]]},displayAlign:\"left\"})},function(){if(\"SVG\"!==(i=MathJax.Hub.config.menuSettings.renderer))return MathJax.Hub.setRenderer(\"SVG\")},function(){var r=\"math-output-\"+a.randstr({},64);return l=n.select(\"body\").append(\"div\").attr({id:r}).style({visibility:\"hidden\",position:\"absolute\"}).style({\"font-size\":e.fontSize+\"px\"}).text(t.replace(c,\"\\\\lt \").replace(u,\"\\\\gt \")),MathJax.Hub.Typeset(l.node())},function(){var e=n.select(\"body\").select(\"#MathJax_SVG_glyphs\");if(l.select(\".MathJax_SVG\").empty()||!l.select(\"svg\").node())a.log(\"There was an error in the tex syntax.\",t),r();else{var o=l.select(\"svg\").node().getBoundingClientRect();r(l.select(\".MathJax_SVG\"),e,o)}if(l.remove(),\"SVG\"!==i)return MathJax.Hub.setRenderer(i)},function(){return void 0!==s&&(MathJax.Hub.processSectionDelay=s),MathJax.Hub.Config(o)})}(L[2],i,function(n,a,i){C.selectAll(\"svg.\"+P).remove(),C.selectAll(\"g.\"+P+\"-group\").remove();var o=n&&n.select(\"svg\");if(!o||!o.node())return O(),void e();var l=C.append(\"g\").classed(P+\"-group\",!0).attr({\"pointer-events\":\"none\",\"data-unformatted\":S,\"data-math\":\"Y\"});l.node().appendChild(o.node()),a&&a.node()&&o.node().insertBefore(a.node().cloneNode(!0),o.node().firstChild),o.attr({class:P,height:i.height,preserveAspectRatio:\"xMinYMin meet\"}).style({overflow:\"visible\",\"pointer-events\":\"none\"});var c=t.node().style.fill||\"black\",u=o.select(\"g\");u.attr({fill:c,stroke:c});var h=s(u,\"width\"),f=s(u,\"height\"),p=+t.attr(\"x\")-h*{start:0,middle:.5,end:1}[t.attr(\"text-anchor\")||\"start\"],d=-(r||s(t,\"height\"))/4;\"y\"===P[0]?(l.attr({transform:\"rotate(\"+[-90,+t.attr(\"x\"),+t.attr(\"y\")]+\") translate(\"+[-h/2,d-f/2]+\")\"}),o.attr({x:+t.attr(\"x\"),y:+t.attr(\"y\")})):\"l\"===P[0]?o.attr({x:t.attr(\"x\"),y:d-f/2}):\"a\"===P[0]&&0!==P.indexOf(\"atitle\")?o.attr({x:0,y:d}):o.attr({x:p,y:+t.attr(\"y\")+d-f/2}),A&&A.call(t,l),e(l)})})):O(),t}function O(){C.empty()||(P=t.attr(\"class\")+\"-math\",C.select(\"svg.\"+P).remove()),t.text(\"\").style(\"white-space\",\"pre\"),function(t,e){e=e.replace(v,\" \");var r,s=!1,l=[],c=-1;function u(){c++;var e=document.createElementNS(i.svg,\"tspan\");n.select(e).attr({class:\"line\",dy:c*o+\"em\"}),t.appendChild(e),r=e;var a=l;if(l=[{node:e}],a.length>1)for(var s=1;s<a.length;s++)A(a[s])}function A(t){var e,a=t.type,o={};if(\"a\"===a){e=\"a\";var s=t.target,c=t.href,u=t.popup;c&&(o={\"xlink:xlink:show\":\"_blank\"===s||\"_\"!==s.charAt(0)?\"new\":\"replace\",target:s,\"xlink:xlink:href\":c},u&&(o.onclick='window.open(this.href.baseVal,this.target.baseVal,\"'+u+'\");return false;'))}else e=\"tspan\";t.style&&(o.style=t.style);var h=document.createElementNS(i.svg,e);if(\"sup\"===a||\"sub\"===a){S(r,d),r.appendChild(h);var g=document.createElementNS(i.svg,\"tspan\");S(g,d),n.select(g).attr(\"dy\",p[a]),o.dy=f[a],r.appendChild(h),r.appendChild(g)}else r.appendChild(h);n.select(h).attr(o),r=t.node=h,l.push(t)}function S(t,e){t.appendChild(document.createTextNode(e))}function L(t){if(1!==l.length){var n=l.pop();t!==n.type&&a.log(\"Start tag <\"+n.type+\"> doesnt match end tag <\"+t+\">. Pretending it did match.\",e),r=l[l.length-1].node}else a.log(\"Ignoring unexpected end tag </\"+t+\">.\",e)}x.test(e)?u():(r=t,l=[{node:t}]);for(var C=e.split(m),P=0;P<C.length;P++){var O=C[P],z=O.match(y),I=z&&z[2].toLowerCase(),D=h[I];if(\"br\"===I)u();else if(void 0===D)S(r,E(O));else if(z[1])L(I);else{var R=z[4],F={type:I},B=T(R,b);if(B?(B=B.replace(M,\"$1 fill:\"),D&&(B+=\";\"+D)):D&&(B=D),B&&(F.style=B),\"a\"===I){s=!0;var N=T(R,_);if(N){var j=document.createElement(\"a\");j.href=N,-1!==g.indexOf(j.protocol)&&(F.href=encodeURI(decodeURI(N)),F.target=T(R,w)||\"_blank\",F.popup=T(R,k))}}A(F)}}return s}(t.node(),S)&&t.style(\"pointer-events\",\"all\"),r.positionText(t),A&&A.call(t)}};var c=/(<|&lt;|&#60;)/g,u=/(>|&gt;|&#62;)/g;var h={sup:\"font-size:70%\",sub:\"font-size:70%\",b:\"font-weight:bold\",i:\"font-style:italic\",a:\"cursor:pointer\",span:\"\",em:\"font-style:italic;font-weight:bold\"},f={sub:\"0.3em\",sup:\"-0.6em\"},p={sub:\"-0.21em\",sup:\"0.42em\"},d=\"\\u200b\",g=[\"http:\",\"https:\",\"mailto:\",\"\",void 0,\":\"],v=r.NEWLINES=/(\\r\\n?|\\n)/g,m=/(<[^<>]*>)/,y=/<(\\/?)([^ >]*)(\\s+(.*))?>/i,x=/<br(\\s+.*)?>/i;r.BR_TAG_ALL=/<br(\\s+.*)?>/gi;var b=/(^|[\\s\"'])style\\s*=\\s*(\"([^\"]*);?\"|'([^']*);?')/i,_=/(^|[\\s\"'])href\\s*=\\s*(\"([^\"]*)\"|'([^']*)')/i,w=/(^|[\\s\"'])target\\s*=\\s*(\"([^\"\\s]*)\"|'([^'\\s]*)')/i,k=/(^|[\\s\"'])popup\\s*=\\s*(\"([\\w=,]*)\"|'([\\w=,]*)')/i;function T(t,e){if(!t)return null;var r=t.match(e),n=r&&(r[3]||r[4]);return n&&E(n)}var M=/(^|;)\\s*color:/;r.plainText=function(t,e){for(var r=void 0!==(e=e||{}).len&&-1!==e.len?e.len:1/0,n=void 0!==e.allowedTags?e.allowedTags:[\"br\"],a=\"...\".length,i=t.split(m),o=[],s=\"\",l=0,c=0;c<i.length;c++){var u=i[c],h=u.match(y),f=h&&h[2].toLowerCase();if(f)-1!==n.indexOf(f)&&(o.push(u),s=f);else{var p=u.length;if(l+p<r)o.push(u),l+=p;else if(l<r){var d=r-l;s&&(\"br\"!==s||d<=a||p<=a)&&o.pop(),r>a?o.push(u.substr(0,d-a)+\"...\"):o.push(u.substr(0,d));break}s=\"\"}}return o.join(\"\")};var A={mu:\"\\u03bc\",amp:\"&\",lt:\"<\",gt:\">\",nbsp:\"\\xa0\",times:\"\\xd7\",plusmn:\"\\xb1\",deg:\"\\xb0\"},S=/&(#\\d+|#x[\\da-fA-F]+|[a-z]+);/g;function E(t){return t.replace(S,function(t,e){return(\"#\"===e.charAt(0)?function(t){if(t>1114111)return;var e=String.fromCodePoint;if(e)return e(t);var r=String.fromCharCode;return t<=65535?r(t):r(55232+(t>>10),t%1024+56320)}(\"x\"===e.charAt(1)?parseInt(e.substr(2),16):parseInt(e.substr(1),10)):A[e])||t})}function L(t,e,r){var n,a,i,o=r.horizontalAlign,s=r.verticalAlign||\"top\",l=t.node().getBoundingClientRect(),c=e.node().getBoundingClientRect();return a=\"bottom\"===s?function(){return l.bottom-n.height}:\"middle\"===s?function(){return l.top+(l.height-n.height)/2}:function(){return l.top},i=\"right\"===o?function(){return l.right-n.width}:\"center\"===o?function(){return l.left+(l.width-n.width)/2}:function(){return l.left},function(){return n=this.node().getBoundingClientRect(),this.style({top:a()-c.top+\"px\",left:i()-c.left+\"px\",\"z-index\":1e3}),this}}r.convertEntities=E,r.lineCount=function(t){return t.selectAll(\"tspan.line\").size()||1},r.positionText=function(t,e,r){return t.each(function(){var t=n.select(this);function a(e,r){return void 0===r?null===(r=t.attr(e))&&(t.attr(e,0),r=0):t.attr(e,r),r}var i=a(\"x\",e),o=a(\"y\",r);\"text\"===this.nodeName&&t.selectAll(\"tspan.line\").attr({x:i,y:o})})},r.makeEditable=function(t,e){var r=e.gd,a=e.delegate,i=n.dispatch(\"edit\",\"input\",\"cancel\"),o=a||t;if(t.style({\"pointer-events\":a?\"none\":\"all\"}),1!==t.size())throw new Error(\"boo\");function s(){!function(){var a=n.select(r).select(\".svg-container\"),o=a.append(\"div\"),s=t.node().style,c=parseFloat(s.fontSize||12),u=e.text;void 0===u&&(u=t.attr(\"data-unformatted\"));o.classed(\"plugin-editable editable\",!0).style({position:\"absolute\",\"font-family\":s.fontFamily||\"Arial\",\"font-size\":c,color:e.fill||s.fill||\"black\",opacity:1,\"background-color\":e.background||\"transparent\",outline:\"#ffffff33 1px solid\",margin:[-c/8+1,0,0,-1].join(\"px \")+\"px\",padding:\"0\",\"box-sizing\":\"border-box\"}).attr({contenteditable:!0}).text(u).call(L(t,a,e)).on(\"blur\",function(){r._editing=!1,t.text(this.textContent).style({opacity:1});var e,a=n.select(this).attr(\"class\");(e=a?\".\"+a.split(\" \")[0]+\"-math-group\":\"[class*=-math-group]\")&&n.select(t.node().parentNode).select(e).style({opacity:0});var o=this.textContent;n.select(this).transition().duration(0).remove(),n.select(document).on(\"mouseup\",null),i.edit.call(t,o)}).on(\"focus\",function(){var t=this;r._editing=!0,n.select(document).on(\"mouseup\",function(){if(n.event.target===t)return!1;document.activeElement===o.node()&&o.node().blur()})}).on(\"keyup\",function(){27===n.event.which?(r._editing=!1,t.style({opacity:1}),n.select(this).style({opacity:0}).on(\"blur\",function(){return!1}).transition().remove(),i.cancel.call(t,this.textContent)):(i.input.call(t,this.textContent),n.select(this).call(L(t,a,e)))}).on(\"keydown\",function(){13===n.event.which&&this.blur()}).call(l)}(),t.style({opacity:0});var a,s=o.attr(\"class\");(a=s?\".\"+s.split(\" \")[0]+\"-math-group\":\"[class*=-math-group]\")&&n.select(t.node().parentNode).select(a).style({opacity:0})}function l(t){var e=t.node(),r=document.createRange();r.selectNodeContents(e);var n=window.getSelection();n.removeAllRanges(),n.addRange(r),e.focus()}return e.immediate?s():o.on(\"click\",s),n.rebind(t,i,\"on\")}},{\"../constants/alignment\":686,\"../constants/xmlns_namespaces\":694,\"../lib\":717,d3:165}],742:[function(t,e,r){\"use strict\";var n={};function a(t){t&&null!==t.timer&&(clearTimeout(t.timer),t.timer=null)}r.throttle=function(t,e,r){var i=n[t],o=Date.now();if(!i){for(var s in n)n[s].ts<o-6e4&&delete n[s];i=n[t]={ts:0,timer:null}}function l(){r(),i.ts=Date.now(),i.onDone&&(i.onDone(),i.onDone=null)}a(i),o>i.ts+e?l():i.timer=setTimeout(function(){l(),i.timer=null},e)},r.done=function(t){var e=n[t];return e&&e.timer?new Promise(function(t){var r=e.onDone;e.onDone=function(){r&&r(),t(),e.onDone=null}}):Promise.resolve()},r.clear=function(t){if(t)a(n[t]),delete n[t];else for(var e in n)r.clear(e)}},{}],743:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\");e.exports=function(t,e){if(t>0)return Math.log(t)/Math.LN10;var r=Math.log(Math.min(e[0],e[1]))/Math.LN10;return n(r)||(r=Math.log(Math.max(e[0],e[1]))/Math.LN10-6),r}},{\"fast-isnumeric\":228}],744:[function(t,e,r){\"use strict\";var n=e.exports={},a=t(\"../plots/geo/constants\").locationmodeToLayer,i=t(\"topojson-client\").feature;n.getTopojsonName=function(t){return[t.scope.replace(/ /g,\"-\"),\"_\",t.resolution.toString(),\"m\"].join(\"\")},n.getTopojsonPath=function(t,e){return t+e+\".json\"},n.getTopojsonFeatures=function(t,e){var r=a[t.locationmode],n=e.objects[r];return i(e,n).features}},{\"../plots/geo/constants\":793,\"topojson-client\":539}],745:[function(t,e,r){\"use strict\";e.exports={moduleType:\"locale\",name:\"en-US\",dictionary:{\"Click to enter Colorscale title\":\"Click to enter Colorscale title\"},format:{date:\"%m/%d/%Y\"}}},{}],746:[function(t,e,r){\"use strict\";e.exports={moduleType:\"locale\",name:\"en\",dictionary:{\"Click to enter Colorscale title\":\"Click to enter Colourscale title\"},format:{days:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],shortDays:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],months:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],shortMonths:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],periods:[\"AM\",\"PM\"],dateTime:\"%a %b %e %X %Y\",date:\"%d/%m/%Y\",time:\"%H:%M:%S\",decimal:\".\",thousands:\",\",grouping:[3],currency:[\"$\",\"\"],year:\"%Y\",month:\"%b %Y\",dayMonth:\"%b %-d\",dayMonthYear:\"%b %-d, %Y\"}}},{}],747:[function(t,e,r){\"use strict\";var n=t(\"../registry\");e.exports=function(t){for(var e,r,a=n.layoutArrayContainers,i=n.layoutArrayRegexes,o=t.split(\"[\")[0],s=0;s<i.length;s++)if((r=t.match(i[s]))&&0===r.index){e=r[0];break}if(e||(e=a[a.indexOf(o)]),!e)return!1;var l=t.substr(e.length);return l?!!(r=l.match(/^\\[(0|[1-9][0-9]*)\\](\\.(.+))?$/))&&{array:e,index:Number(r[1]),property:r[3]||\"\"}:{array:e,index:\"\",property:\"\"}}},{\"../registry\":846}],748:[function(t,e,r){\"use strict\";var n=t(\"../lib\"),a=n.extendFlat,i=n.isPlainObject,o={valType:\"flaglist\",extras:[\"none\"],flags:[\"calc\",\"clearAxisTypes\",\"plot\",\"style\",\"markerSize\",\"colorbars\"]},s={valType:\"flaglist\",extras:[\"none\"],flags:[\"calc\",\"plot\",\"legend\",\"ticks\",\"axrange\",\"layoutstyle\",\"modebar\",\"camera\",\"arraydraw\",\"colorbars\"]},l=o.flags.slice().concat([\"fullReplot\"]),c=s.flags.slice().concat(\"layoutReplot\");function u(t){for(var e={},r=0;r<t.length;r++)e[t[r]]=!1;return e}function h(t,e,r){var n=a({},t);for(var o in n){var s=n[o];i(s)&&(n[o]=f(s,e,r,o))}return\"from-root\"===r&&(n.editType=e),n}function f(t,e,r,n){if(t.valType){var i=a({},t);if(i.editType=e,Array.isArray(t.items)){i.items=new Array(t.items.length);for(var o=0;o<t.items.length;o++)i.items[o]=f(t.items[o],e,\"from-root\")}return i}return h(t,e,\"_\"===n.charAt(0)?\"nested\":\"from-root\")}e.exports={traces:o,layout:s,traceFlags:function(){return u(l)},layoutFlags:function(){return u(c)},update:function(t,e){var r=e.editType;if(r&&\"none\"!==r)for(var n=r.split(\"+\"),a=0;a<n.length;a++)t[n[a]]=!0},overrideAll:h}},{\"../lib\":717}],749:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"gl-mat4/fromQuat\"),i=t(\"../registry\"),o=t(\"../lib\"),s=t(\"../plots/plots\"),l=t(\"../plots/cartesian/axis_ids\"),c=t(\"../components/color\"),u=l.cleanId,h=l.getFromTrace,f=i.traceIs;function p(t,e){var r=t[e],n=e.charAt(0);r&&\"paper\"!==r&&(t[e]=u(r,n))}function d(t){function e(e,r){var n=t[e],a=t.title&&t.title[r];n&&!a&&(t.title||(t.title={}),t.title[r]=t[e],delete t[e])}t&&(\"string\"!=typeof t.title&&\"number\"!=typeof t.title||(t.title={text:t.title}),e(\"titlefont\",\"font\"),e(\"titleposition\",\"position\"),e(\"titleside\",\"side\"),e(\"titleoffset\",\"offset\"))}function g(t){if(!o.isPlainObject(t))return!1;var e=t.name;return delete t.name,delete t.showlegend,(\"string\"==typeof e||\"number\"==typeof e)&&String(e)}function v(t,e,r,n){if(r&&!n)return t;if(n&&!r)return e;if(!t.trim())return e;if(!e.trim())return t;var a,i=Math.min(t.length,e.length);for(a=0;a<i&&t.charAt(a)===e.charAt(a);a++);return t.substr(0,a).trim()}function m(t){var e=\"middle\",r=\"center\";return\"string\"==typeof t&&(-1!==t.indexOf(\"top\")?e=\"top\":-1!==t.indexOf(\"bottom\")&&(e=\"bottom\"),-1!==t.indexOf(\"left\")?r=\"left\":-1!==t.indexOf(\"right\")&&(r=\"right\")),e+\" \"+r}function y(t,e){return e in t&&\"object\"==typeof t[e]&&0===Object.keys(t[e]).length}r.clearPromiseQueue=function(t){Array.isArray(t._promises)&&t._promises.length>0&&o.log(\"Clearing previous rejected promises from queue.\"),t._promises=[]},r.cleanLayout=function(t){var e,n;t||(t={}),t.xaxis1&&(t.xaxis||(t.xaxis=t.xaxis1),delete t.xaxis1),t.yaxis1&&(t.yaxis||(t.yaxis=t.yaxis1),delete t.yaxis1),t.scene1&&(t.scene||(t.scene=t.scene1),delete t.scene1);var i=(s.subplotsRegistry.cartesian||{}).attrRegex,l=(s.subplotsRegistry.polar||{}).attrRegex,h=(s.subplotsRegistry.ternary||{}).attrRegex,f=(s.subplotsRegistry.gl3d||{}).attrRegex,g=Object.keys(t);for(e=0;e<g.length;e++){var v=g[e];if(i&&i.test(v)){var m=t[v];m.anchor&&\"free\"!==m.anchor&&(m.anchor=u(m.anchor)),m.overlaying&&(m.overlaying=u(m.overlaying)),m.type||(m.isdate?m.type=\"date\":m.islog?m.type=\"log\":!1===m.isdate&&!1===m.islog&&(m.type=\"linear\")),\"withzero\"!==m.autorange&&\"tozero\"!==m.autorange||(m.autorange=!0,m.rangemode=\"tozero\"),delete m.islog,delete m.isdate,delete m.categories,y(m,\"domain\")&&delete m.domain,void 0!==m.autotick&&(void 0===m.tickmode&&(m.tickmode=m.autotick?\"auto\":\"linear\"),delete m.autotick),d(m)}else if(l&&l.test(v)){d(t[v].radialaxis)}else if(h&&h.test(v)){var x=t[v];d(x.aaxis),d(x.baxis),d(x.caxis)}else if(f&&f.test(v)){var b=t[v],_=b.cameraposition;if(Array.isArray(_)&&4===_[0].length){var w=_[0],k=_[1],T=_[2],M=a([],w),A=[];for(n=0;n<3;++n)A[n]=k[n]+T*M[2+4*n];b.camera={eye:{x:A[0],y:A[1],z:A[2]},center:{x:k[0],y:k[1],z:k[2]},up:{x:0,y:0,z:1}},delete b.cameraposition}d(b.xaxis),d(b.yaxis),d(b.zaxis)}}var S=Array.isArray(t.annotations)?t.annotations.length:0;for(e=0;e<S;e++){var E=t.annotations[e];o.isPlainObject(E)&&(E.ref&&(\"paper\"===E.ref?(E.xref=\"paper\",E.yref=\"paper\"):\"data\"===E.ref&&(E.xref=\"x\",E.yref=\"y\"),delete E.ref),p(E,\"xref\"),p(E,\"yref\"))}var L=Array.isArray(t.shapes)?t.shapes.length:0;for(e=0;e<L;e++){var C=t.shapes[e];o.isPlainObject(C)&&(p(C,\"xref\"),p(C,\"yref\"))}var P=t.legend;return P&&(P.x>3?(P.x=1.02,P.xanchor=\"left\"):P.x<-2&&(P.x=-.02,P.xanchor=\"right\"),P.y>3?(P.y=1.02,P.yanchor=\"bottom\"):P.y<-2&&(P.y=-.02,P.yanchor=\"top\")),d(t),\"rotate\"===t.dragmode&&(t.dragmode=\"orbit\"),c.clean(t),t.template&&t.template.layout&&r.cleanLayout(t.template.layout),t},r.cleanData=function(t){for(var e=0;e<t.length;e++){var n,a=t[e];if(\"histogramy\"===a.type&&\"xbins\"in a&&!(\"ybins\"in a)&&(a.ybins=a.xbins,delete a.xbins),a.error_y&&\"opacity\"in a.error_y){var l=c.defaults,h=a.error_y.color||(f(a,\"bar\")?c.defaultLine:l[e%l.length]);a.error_y.color=c.addOpacity(c.rgb(h),c.opacity(h)*a.error_y.opacity),delete a.error_y.opacity}if(\"bardir\"in a&&(\"h\"!==a.bardir||!f(a,\"bar\")&&\"histogram\"!==a.type.substr(0,9)||(a.orientation=\"h\",r.swapXYData(a)),delete a.bardir),\"histogramy\"===a.type&&r.swapXYData(a),\"histogramx\"!==a.type&&\"histogramy\"!==a.type||(a.type=\"histogram\"),\"scl\"in a&&!(\"colorscale\"in a)&&(a.colorscale=a.scl,delete a.scl),\"reversescl\"in a&&!(\"reversescale\"in a)&&(a.reversescale=a.reversescl,delete a.reversescl),a.xaxis&&(a.xaxis=u(a.xaxis,\"x\")),a.yaxis&&(a.yaxis=u(a.yaxis,\"y\")),f(a,\"gl3d\")&&a.scene&&(a.scene=s.subplotsRegistry.gl3d.cleanId(a.scene)),!f(a,\"pie-like\")&&!f(a,\"bar-like\"))if(Array.isArray(a.textposition))for(n=0;n<a.textposition.length;n++)a.textposition[n]=m(a.textposition[n]);else a.textposition&&(a.textposition=m(a.textposition));var p=i.getModule(a);if(p&&p.colorbar){var x=p.colorbar.container,b=x?a[x]:a;b&&b.colorscale&&(\"YIGnBu\"===b.colorscale&&(b.colorscale=\"YlGnBu\"),\"YIOrRd\"===b.colorscale&&(b.colorscale=\"YlOrRd\"))}if(\"surface\"===a.type&&o.isPlainObject(a.contours)){var _=[\"x\",\"y\",\"z\"];for(n=0;n<_.length;n++){var w=a.contours[_[n]];o.isPlainObject(w)&&(w.highlightColor&&(w.highlightcolor=w.highlightColor,delete w.highlightColor),w.highlightWidth&&(w.highlightwidth=w.highlightWidth,delete w.highlightWidth))}}if(\"candlestick\"===a.type||\"ohlc\"===a.type){var k=!1!==(a.increasing||{}).showlegend,T=!1!==(a.decreasing||{}).showlegend,M=g(a.increasing),A=g(a.decreasing);if(!1!==M&&!1!==A){var S=v(M,A,k,T);S&&(a.name=S)}else!M&&!A||a.name||(a.name=M||A)}if(Array.isArray(a.transforms)){var E=a.transforms;for(n=0;n<E.length;n++){var L=E[n];if(o.isPlainObject(L))switch(L.type){case\"filter\":L.filtersrc&&(L.target=L.filtersrc,delete L.filtersrc),L.calendar&&(L.valuecalendar||(L.valuecalendar=L.calendar),delete L.calendar);break;case\"groupby\":if(L.styles=L.styles||L.style,L.styles&&!Array.isArray(L.styles)){var C=L.styles,P=Object.keys(C);L.styles=[];for(var O=0;O<P.length;O++)L.styles.push({target:P[O],value:C[P[O]]})}}}}y(a,\"line\")&&delete a.line,\"marker\"in a&&(y(a.marker,\"line\")&&delete a.marker.line,y(a,\"marker\")&&delete a.marker),c.clean(a),a.autobinx&&(delete a.autobinx,delete a.xbins),a.autobiny&&(delete a.autobiny,delete a.ybins),d(a),a.colorbar&&d(a.colorbar),a.marker&&a.marker.colorbar&&d(a.marker.colorbar),a.line&&a.line.colorbar&&d(a.line.colorbar),a.aaxis&&d(a.aaxis),a.baxis&&d(a.baxis)}},r.swapXYData=function(t){var e;if(o.swapAttrs(t,[\"?\",\"?0\",\"d?\",\"?bins\",\"nbins?\",\"autobin?\",\"?src\",\"error_?\"]),Array.isArray(t.z)&&Array.isArray(t.z[0])&&(t.transpose?delete t.transpose:t.transpose=!0),t.error_x&&t.error_y){var r=t.error_y,n=\"copy_ystyle\"in r?r.copy_ystyle:!(r.color||r.thickness||r.width);o.swapAttrs(t,[\"error_?.copy_ystyle\"]),n&&o.swapAttrs(t,[\"error_?.color\",\"error_?.thickness\",\"error_?.width\"])}if(\"string\"==typeof t.hoverinfo){var a=t.hoverinfo.split(\"+\");for(e=0;e<a.length;e++)\"x\"===a[e]?a[e]=\"y\":\"y\"===a[e]&&(a[e]=\"x\");t.hoverinfo=a.join(\"+\")}},r.coerceTraceIndices=function(t,e){if(n(e))return[e];if(!Array.isArray(e)||!e.length)return t.data.map(function(t,e){return e});if(Array.isArray(e)){for(var r=[],a=0;a<e.length;a++)o.isIndex(e[a],t.data.length)?r.push(e[a]):o.warn(\"trace index (\",e[a],\") is not a number or is out of bounds\");return r}return e},r.manageArrayContainers=function(t,e,r){var a=t.obj,i=t.parts,s=i.length,l=i[s-1],c=n(l);if(c&&null===e){var u=i.slice(0,s-1).join(\".\");o.nestedProperty(a,u).get().splice(l,1)}else c&&void 0===t.get()?(void 0===t.get()&&(r[t.astr]=null),t.set(e)):t.set(e)};var x=/(\\.[^\\[\\]\\.]+|\\[[^\\[\\]\\.]+\\])$/;function b(t){var e=t.search(x);if(e>0)return t.substr(0,e)}r.hasParent=function(t,e){for(var r=b(e);r;){if(r in t)return!0;r=b(r)}return!1};var _=[\"x\",\"y\",\"z\"];r.clearAxisTypes=function(t,e,r){for(var n=0;n<e.length;n++)for(var a=t._fullData[n],i=0;i<3;i++){var s=h(t,a,_[i]);if(s&&\"log\"!==s.type){var l=s._name,c=s._id.substr(1);if(\"scene\"===c.substr(0,5)){if(void 0!==r[c])continue;l=c+\".\"+l}var u=l+\".type\";void 0===r[l]&&void 0===r[u]&&o.nestedProperty(t.layout,u).set(null)}}}},{\"../components/color\":592,\"../lib\":717,\"../plots/cartesian/axis_ids\":768,\"../plots/plots\":826,\"../registry\":846,\"fast-isnumeric\":228,\"gl-mat4/fromQuat\":265}],750:[function(t,e,r){\"use strict\";var n=t(\"./plot_api\");r.plot=n.plot,r.newPlot=n.newPlot,r.restyle=n.restyle,r.relayout=n.relayout,r.redraw=n.redraw,r.update=n.update,r._guiRestyle=n._guiRestyle,r._guiRelayout=n._guiRelayout,r._guiUpdate=n._guiUpdate,r._storeDirectGUIEdit=n._storeDirectGUIEdit,r.react=n.react,r.extendTraces=n.extendTraces,r.prependTraces=n.prependTraces,r.addTraces=n.addTraces,r.deleteTraces=n.deleteTraces,r.moveTraces=n.moveTraces,r.purge=n.purge,r.addFrames=n.addFrames,r.deleteFrames=n.deleteFrames,r.animate=n.animate,r.setPlotConfig=n.setPlotConfig,r.toImage=t(\"./to_image\"),r.validate=t(\"./validate\"),r.downloadImage=t(\"../snapshot/download\");var a=t(\"./template_api\");r.makeTemplate=a.makeTemplate,r.validateTemplate=a.validateTemplate},{\"../snapshot/download\":848,\"./plot_api\":752,\"./template_api\":757,\"./to_image\":758,\"./validate\":759}],751:[function(t,e,r){\"use strict\";var n=t(\"../lib/is_plain_object\"),a=t(\"../lib/noop\"),i=t(\"../lib/loggers\"),o=t(\"../lib/search\").sorterAsc,s=t(\"../registry\");r.containerArrayMatch=t(\"./container_array_match\");var l=r.isAddVal=function(t){return\"add\"===t||n(t)},c=r.isRemoveVal=function(t){return null===t||\"remove\"===t};r.applyContainerArrayChanges=function(t,e,r,n,u){var h=e.astr,f=s.getComponentMethod(h,\"supplyLayoutDefaults\"),p=s.getComponentMethod(h,\"draw\"),d=s.getComponentMethod(h,\"drawOne\"),g=n.replot||n.recalc||f===a||p===a,v=t.layout,m=t._fullLayout;if(r[\"\"]){Object.keys(r).length>1&&i.warn(\"Full array edits are incompatible with other edits\",h);var y=r[\"\"][\"\"];if(c(y))e.set(null);else{if(!Array.isArray(y))return i.warn(\"Unrecognized full array edit value\",h,y),!0;e.set(y)}return!g&&(f(v,m),p(t),!0)}var x,b,_,w,k,T,M,A,S=Object.keys(r).map(Number).sort(o),E=e.get(),L=E||[],C=u(m,h).get(),P=[],O=-1,z=L.length;for(x=0;x<S.length;x++)if(w=r[_=S[x]],k=Object.keys(w),T=w[\"\"],M=l(T),_<0||_>L.length-(M?0:1))i.warn(\"index out of range\",h,_);else if(void 0!==T)k.length>1&&i.warn(\"Insertion & removal are incompatible with edits to the same index.\",h,_),c(T)?P.push(_):M?(\"add\"===T&&(T={}),L.splice(_,0,T),C&&C.splice(_,0,{})):i.warn(\"Unrecognized full object edit value\",h,_,T),-1===O&&(O=_);else for(b=0;b<k.length;b++)A=h+\"[\"+_+\"].\",u(L[_],k[b],A).set(w[k[b]]);for(x=P.length-1;x>=0;x--)L.splice(P[x],1),C&&C.splice(P[x],1);if(L.length?E||e.set(L):e.set(null),g)return!1;if(f(v,m),d!==a){var I;if(-1===O)I=S;else{for(z=Math.max(L.length,z),I=[],x=0;x<S.length&&!((_=S[x])>=O);x++)I.push(_);for(x=O;x<z;x++)I.push(x)}for(x=0;x<I.length;x++)d(t,I[x])}else p(t);return!0}},{\"../lib/is_plain_object\":718,\"../lib/loggers\":721,\"../lib/noop\":726,\"../lib/search\":736,\"../registry\":846,\"./container_array_match\":747}],752:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"fast-isnumeric\"),i=t(\"has-hover\"),o=t(\"../lib\"),s=o.nestedProperty,l=t(\"../lib/events\"),c=t(\"../lib/queue\"),u=t(\"../registry\"),h=t(\"./plot_schema\"),f=t(\"../plots/plots\"),p=t(\"../plots/polar/legacy\"),d=t(\"../plots/cartesian/axes\"),g=t(\"../components/drawing\"),v=t(\"../components/color\"),m=t(\"../plots/cartesian/graph_interact\").initInteractions,y=t(\"../constants/xmlns_namespaces\"),x=t(\"../lib/svg_text_utils\"),b=t(\"../plots/cartesian/select\").clearSelect,_=t(\"./plot_config\").dfltConfig,w=t(\"./manage_arrays\"),k=t(\"./helpers\"),T=t(\"./subroutines\"),M=t(\"./edit_types\"),A=t(\"../plots/cartesian/constants\").AX_NAME_PATTERN,S=0,E=5;function L(t){var e=t._fullLayout;e._redrawFromAutoMarginCount?e._redrawFromAutoMarginCount--:t.emit(\"plotly_afterplot\")}function C(t,e){try{t._fullLayout._paper.style(\"background\",e)}catch(t){o.error(t)}}function P(t,e){C(t,v.combine(e,\"white\"))}function O(t,e){if(!t._context){t._context=o.extendDeep({},_);var r=n.select(\"base\");t._context._baseUrl=r.size()&&r.attr(\"href\")?window.location.href.split(\"#\")[0]:\"\"}var a,s,l,c=t._context;if(e){for(s=Object.keys(e),a=0;a<s.length;a++)\"editable\"!==(l=s[a])&&\"edits\"!==l&&l in c&&(\"setBackground\"===l&&\"opaque\"===e[l]?c[l]=P:c[l]=e[l]);e.plot3dPixelRatio&&!c.plotGlPixelRatio&&(c.plotGlPixelRatio=c.plot3dPixelRatio);var u=e.editable;if(void 0!==u)for(c.editable=u,s=Object.keys(c.edits),a=0;a<s.length;a++)c.edits[s[a]]=u;if(e.edits)for(s=Object.keys(e.edits),a=0;a<s.length;a++)(l=s[a])in c.edits&&(c.edits[l]=e.edits[l]);c._exportedPlot=e._exportedPlot}c.staticPlot&&(c.editable=!1,c.edits={},c.autosizable=!1,c.scrollZoom=!1,c.doubleClick=!1,c.showTips=!1,c.showLink=!1,c.displayModeBar=!1),\"hover\"!==c.displayModeBar||i||(c.displayModeBar=!0),\"transparent\"!==c.setBackground&&\"function\"==typeof c.setBackground||(c.setBackground=C),c._hasZeroHeight=c._hasZeroHeight||0===t.clientHeight,c._hasZeroWidth=c._hasZeroWidth||0===t.clientWidth;var h=c.scrollZoom,f=c._scrollZoom={};if(!0===h)f.cartesian=1,f.gl3d=1,f.geo=1,f.mapbox=1;else if(\"string\"==typeof h){var p=h.split(\"+\");for(a=0;a<p.length;a++)f[p[a]]=1}else!1!==h&&(f.gl3d=1,f.geo=1,f.mapbox=1)}function z(t,e){var r,n,a=e+1,i=[];for(r=0;r<t.length;r++)(n=t[r])<0?i.push(a+n):i.push(n);return i}function I(t,e,r){var n,a;for(n=0;n<e.length;n++){if((a=e[n])!==parseInt(a,10))throw new Error(\"all values in \"+r+\" must be integers\");if(a>=t.data.length||a<-t.data.length)throw new Error(r+\" must be valid indices for gd.data.\");if(e.indexOf(a,n+1)>-1||a>=0&&e.indexOf(-t.data.length+a)>-1||a<0&&e.indexOf(t.data.length+a)>-1)throw new Error(\"each index in \"+r+\" must be unique.\")}}function D(t,e,r){if(!Array.isArray(t.data))throw new Error(\"gd.data must be an array.\");if(\"undefined\"==typeof e)throw new Error(\"currentIndices is a required argument.\");if(Array.isArray(e)||(e=[e]),I(t,e,\"currentIndices\"),\"undefined\"==typeof r||Array.isArray(r)||(r=[r]),\"undefined\"!=typeof r&&I(t,r,\"newIndices\"),\"undefined\"!=typeof r&&e.length!==r.length)throw new Error(\"current and new indices must be of equal length.\")}function R(t,e,r,n,i){!function(t,e,r,n){var a=o.isPlainObject(n);if(!Array.isArray(t.data))throw new Error(\"gd.data must be an array\");if(!o.isPlainObject(e))throw new Error(\"update must be a key:value object\");if(\"undefined\"==typeof r)throw new Error(\"indices must be an integer or array of integers\");for(var i in I(t,r,\"indices\"),e){if(!Array.isArray(e[i])||e[i].length!==r.length)throw new Error(\"attribute \"+i+\" must be an array of length equal to indices array length\");if(a&&(!(i in n)||!Array.isArray(n[i])||n[i].length!==e[i].length))throw new Error(\"when maxPoints is set as a key:value object it must contain a 1:1 corrispondence with the keys and number of traces in the update object\")}}(t,e,r,n);for(var l=function(t,e,r,n){var i,l,c,u,h,f=o.isPlainObject(n),p=[];for(var d in Array.isArray(r)||(r=[r]),r=z(r,t.data.length-1),e)for(var g=0;g<r.length;g++){if(i=t.data[r[g]],l=(c=s(i,d)).get(),u=e[d][g],!o.isArrayOrTypedArray(u))throw new Error(\"attribute: \"+d+\" index: \"+g+\" must be an array\");if(!o.isArrayOrTypedArray(l))throw new Error(\"cannot extend missing or non-array attribute: \"+d);if(l.constructor!==u.constructor)throw new Error(\"cannot extend array with an array of a different type: \"+d);h=f?n[d][g]:n,a(h)||(h=-1),p.push({prop:c,target:l,insert:u,maxp:Math.floor(h)})}return p}(t,e,r,n),c={},u={},h=0;h<l.length;h++){var f=l[h].prop,p=l[h].maxp,d=i(l[h].target,l[h].insert,p);f.set(d[0]),Array.isArray(c[f.astr])||(c[f.astr]=[]),c[f.astr].push(d[1]),Array.isArray(u[f.astr])||(u[f.astr]=[]),u[f.astr].push(l[h].target.length)}return{update:c,maxPoints:u}}function F(t,e){var r=new t.constructor(t.length+e.length);return r.set(t),r.set(e,t.length),r}function B(t,e,n,a){t=o.getGraphDiv(t),k.clearPromiseQueue(t);var i={};if(\"string\"==typeof e)i[e]=n;else{if(!o.isPlainObject(e))return o.warn(\"Restyle fail.\",e,n,a),Promise.reject();i=o.extendFlat({},e),void 0===a&&(a=n)}Object.keys(i).length&&(t.changed=!0);var s=k.coerceTraceIndices(t,a),l=U(t,i,s),u=l.flags;u.calc&&(t.calcdata=void 0),u.clearAxisTypes&&k.clearAxisTypes(t,s,{});var h=[];u.fullReplot?h.push(r.plot):(h.push(f.previousPromises),f.supplyDefaults(t),u.markerSize&&(f.doCalcdata(t),Y(h)),u.style&&h.push(T.doTraceStyle),u.colorbars&&h.push(T.doColorBars),h.push(L)),h.push(f.rehover,f.redrag),c.add(t,B,[t,l.undoit,l.traces],B,[t,l.redoit,l.traces]);var p=o.syncOrAsync(h,t);return p&&p.then||(p=Promise.resolve()),p.then(function(){return t.emit(\"plotly_restyle\",l.eventData),t})}function N(t){return void 0===t?null:t}function j(t,e){return e?function(e,r,n){var a=s(e,r),i=a.set;return a.set=function(e){V((n||\"\")+r,a.get(),e,t),i(e)},a}:s}function V(t,e,r,n){if(Array.isArray(e)||Array.isArray(r))for(var a=Array.isArray(e)?e:[],i=Array.isArray(r)?r:[],s=Math.max(a.length,i.length),l=0;l<s;l++)V(t+\"[\"+l+\"]\",a[l],i[l],n);else if(o.isPlainObject(e)||o.isPlainObject(r)){var c=o.isPlainObject(e)?e:{},u=o.isPlainObject(r)?r:{},h=o.extendFlat({},c,u);for(var f in h)V(t+\".\"+f,c[f],u[f],n)}else void 0===n[t]&&(n[t]=N(e))}function U(t,e,r){var n,a=t._fullLayout,i=t._fullData,l=t.data,c=a._guiEditing,p=j(a._preGUI,c),g=o.extendDeepAll({},e);q(e);var v,m=M.traceFlags(),y={},x={};function b(){return r.map(function(){})}function _(t){var e=d.id2name(t);-1===v.indexOf(e)&&v.push(e)}function w(t){return\"LAYOUT\"+t+\".autorange\"}function T(t){return\"LAYOUT\"+t+\".range\"}function A(t){for(var e=t;e<i.length;e++)if(i[e]._input===l[t])return i[e]}function S(n,i,o){if(Array.isArray(n))n.forEach(function(t){S(t,i,o)});else if(!(n in e||k.hasParent(e,n))){var s;if(\"LAYOUT\"===n.substr(0,6))s=p(t.layout,n.replace(\"LAYOUT\",\"\"));else{var u=r[o];s=j(a._tracePreGUI[A(u)._fullInput.uid],c)(l[u],n)}n in x||(x[n]=b()),void 0===x[n][o]&&(x[n][o]=N(s.get())),void 0!==i&&s.set(i)}}function E(t){return function(e){return i[e][t]}}function L(t){return function(e,n){return!1===e?i[r[n]][t]:null}}for(var C in e){if(k.hasParent(e,C))throw new Error(\"cannot set \"+C+\" and a parent attribute simultaneously\");var P,O,z,I,D,R,F=e[C];if(\"autobinx\"!==C&&\"autobiny\"!==C||(C=C.charAt(C.length-1)+\"bins\",F=Array.isArray(F)?F.map(L(C)):!1===F?r.map(E(C)):null),y[C]=F,\"LAYOUT\"!==C.substr(0,6)){for(x[C]=b(),n=0;n<r.length;n++){if(P=l[r[n]],O=A(r[n]),I=(z=j(a._tracePreGUI[O._fullInput.uid],c)(P,C)).get(),void 0!==(D=Array.isArray(F)?F[n%F.length]:F)){var B=z.parts[z.parts.length-1],V=C.substr(0,C.length-B.length-1),U=V?V+\".\":\"\",H=V?s(O,V).get():O;if((R=h.getTraceValObject(O,z.parts))&&R.impliedEdits&&null!==D)for(var G in R.impliedEdits)S(o.relativeAttr(C,G),R.impliedEdits[G],n);else if(\"thicknessmode\"!==B&&\"lenmode\"!==B||I===D||\"fraction\"!==D&&\"pixels\"!==D||!H){if(\"type\"===C&&(\"pie\"===D!=(\"pie\"===I)||\"funnelarea\"===D!=(\"funnelarea\"===I))){var Y=\"x\",W=\"y\";\"bar\"!==D&&\"bar\"!==I||\"h\"!==P.orientation||(Y=\"y\",W=\"x\"),o.swapAttrs(P,[\"?\",\"?src\"],\"labels\",Y),o.swapAttrs(P,[\"d?\",\"?0\"],\"label\",Y),o.swapAttrs(P,[\"?\",\"?src\"],\"values\",W),\"pie\"===I||\"funnelarea\"===I?(s(P,\"marker.color\").set(s(P,\"marker.colors\").get()),a._pielayer.selectAll(\"g.trace\").remove()):u.traceIs(P,\"cartesian\")&&s(P,\"marker.colors\").set(s(P,\"marker.color\").get())}}else{var X=a._size,Z=H.orient,J=\"top\"===Z||\"bottom\"===Z;if(\"thicknessmode\"===B){var K=J?X.h:X.w;S(U+\"thickness\",H.thickness*(\"fraction\"===D?1/K:K),n)}else{var Q=J?X.w:X.h;S(U+\"len\",H.len*(\"fraction\"===D?1/Q:Q),n)}}x[C][n]=N(I);if(-1!==[\"swapxy\",\"swapxyaxes\",\"orientation\",\"orientationaxes\"].indexOf(C)){if(\"orientation\"===C){z.set(D);var $=P.x&&!P.y?\"h\":\"v\";if((z.get()||$)===O.orientation)continue}else\"orientationaxes\"===C&&(P.orientation={v:\"h\",h:\"v\"}[O.orientation]);k.swapXYData(P),m.calc=m.clearAxisTypes=!0}else-1!==f.dataArrayContainers.indexOf(z.parts[0])?(k.manageArrayContainers(z,D,x),m.calc=!0):(R?R.arrayOk&&!u.traceIs(O,\"regl\")&&(o.isArrayOrTypedArray(D)||o.isArrayOrTypedArray(I))?m.calc=!0:M.update(m,R):m.calc=!0,z.set(D))}}if(-1!==[\"swapxyaxes\",\"orientationaxes\"].indexOf(C)&&d.swap(t,r),\"orientationaxes\"===C){var tt=s(t.layout,\"hovermode\");\"x\"===tt.get()?tt.set(\"y\"):\"y\"===tt.get()&&tt.set(\"x\")}if(-1!==[\"orientation\",\"type\"].indexOf(C)){for(v=[],n=0;n<r.length;n++){var et=l[r[n]];u.traceIs(et,\"cartesian\")&&(_(et.xaxis||\"x\"),_(et.yaxis||\"y\"))}S(v.map(w),!0,0),S(v.map(T),[0,1],0)}}else z=p(t.layout,C.replace(\"LAYOUT\",\"\")),x[C]=[N(z.get())],z.set(Array.isArray(F)?F[0]:F),m.calc=!0}return(m.calc||m.plot)&&(m.fullReplot=!0),{flags:m,undoit:x,redoit:y,traces:r,eventData:o.extendDeepNoArrays([],[g,r])}}function q(t){var e,r,n,a=o.counterRegex(\"axis\",\".title\",!1,!1),i=/colorbar\\.title$/,s=Object.keys(t);for(e=0;e<s.length;e++)r=s[e],n=t[r],\"title\"!==r&&!a.test(r)&&!i.test(r)||\"string\"!=typeof n&&\"number\"!=typeof n?r.indexOf(\"titlefont\")>-1?l(r,r.replace(\"titlefont\",\"title.font\")):r.indexOf(\"titleposition\")>-1?l(r,r.replace(\"titleposition\",\"title.position\")):r.indexOf(\"titleside\")>-1?l(r,r.replace(\"titleside\",\"title.side\")):r.indexOf(\"titleoffset\")>-1&&l(r,r.replace(\"titleoffset\",\"title.offset\")):l(r,r.replace(\"title\",\"title.text\"));function l(e,r){t[r]=t[e],delete t[e]}}function H(t,e,r){if(t=o.getGraphDiv(t),k.clearPromiseQueue(t),t.framework&&t.framework.isPolar)return Promise.resolve(t);var n={};if(\"string\"==typeof e)n[e]=r;else{if(!o.isPlainObject(e))return o.warn(\"Relayout fail.\",e,r),Promise.reject();n=o.extendFlat({},e)}Object.keys(n).length&&(t.changed=!0);var a=J(t,n),i=a.flags;i.calc&&(t.calcdata=void 0);var s=[f.previousPromises];i.layoutReplot?s.push(T.layoutReplot):Object.keys(n).length&&(G(t,i,a)||f.supplyDefaults(t),i.legend&&s.push(T.doLegend),i.layoutstyle&&s.push(T.layoutStyles),i.axrange&&Y(s,a.rangesAltered),i.ticks&&s.push(T.doTicksRelayout),i.modebar&&s.push(T.doModeBar),i.camera&&s.push(T.doCamera),i.colorbars&&s.push(T.doColorBars),s.push(L)),s.push(f.rehover,f.redrag),c.add(t,H,[t,a.undoit],H,[t,a.redoit]);var l=o.syncOrAsync(s,t);return l&&l.then||(l=Promise.resolve(t)),l.then(function(){return t.emit(\"plotly_relayout\",a.eventData),t})}function G(t,e,r){var n=t._fullLayout;if(!e.axrange)return!1;for(var a in e)if(\"axrange\"!==a&&e[a])return!1;for(var i in r.rangesAltered){var o=d.id2name(i),s=t.layout[o],l=n[o];if(l.autorange=s.autorange,l.range=s.range.slice(),l.cleanRange(),l._matchGroup)for(var c in l._matchGroup)if(c!==i){var u=n[d.id2name(c)];u.autorange=l.autorange,u.range=l.range.slice(),u._input.range=l.range.slice()}}return!0}function Y(t,e){var r=e?function(t){var r=[],n=!0;for(var a in e){var i=d.getFromId(t,a);if(r.push(a),i._matchGroup)for(var o in i._matchGroup)e[o]||r.push(o);i.automargin&&(n=!1)}return d.draw(t,r,{skipTitle:n})}:function(t){return d.draw(t,\"redraw\")};t.push(b,T.doAutoRangeAndConstraints,r,T.drawData,T.finalDraw)}var W=/^[xyz]axis[0-9]*\\.range(\\[[0|1]\\])?$/,X=/^[xyz]axis[0-9]*\\.autorange$/,Z=/^[xyz]axis[0-9]*\\.domain(\\[[0|1]\\])?$/;function J(t,e){var r,n,a,i=t.layout,l=t._fullLayout,c=l._guiEditing,f=j(l._preGUI,c),p=Object.keys(e),g=d.list(t),v=o.extendDeepAll({},e),m={};for(q(e),p=Object.keys(e),n=0;n<p.length;n++)if(0===p[n].indexOf(\"allaxes\")){for(a=0;a<g.length;a++){var y=g[a]._id.substr(1),x=-1!==y.indexOf(\"scene\")?y+\".\":\"\",b=p[n].replace(\"allaxes\",x+g[a]._name);e[b]||(e[b]=e[p[n]])}delete e[p[n]]}var _=M.layoutFlags(),T={},S={};function E(t,r){if(Array.isArray(t))t.forEach(function(t){E(t,r)});else if(!(t in e||k.hasParent(e,t))){var n=f(i,t);t in S||(S[t]=N(n.get())),void 0!==r&&n.set(r)}}var L,C={};function P(t){var e=d.name2id(t.split(\".\")[0]);return C[e]=1,e}for(var O in e){if(k.hasParent(e,O))throw new Error(\"cannot set \"+O+\" and a parent attribute simultaneously\");for(var z=f(i,O),I=e[O],D=z.parts.length-1;D>0&&\"string\"!=typeof z.parts[D];)D--;var R=z.parts[D],F=z.parts[D-1]+\".\"+R,B=z.parts.slice(0,D).join(\".\"),V=s(t.layout,B).get(),U=s(l,B).get(),H=z.get();if(void 0!==I){T[O]=I,S[O]=\"reverse\"===R?I:N(H);var G=h.getLayoutValObject(l,z.parts);if(G&&G.impliedEdits&&null!==I)for(var Y in G.impliedEdits)E(o.relativeAttr(O,Y),G.impliedEdits[Y]);if(-1!==[\"width\",\"height\"].indexOf(O))if(I){E(\"autosize\",null);var J=\"height\"===O?\"width\":\"height\";E(J,l[J])}else l[O]=t._initialAutoSize[O];else if(\"autosize\"===O)E(\"width\",I?null:l.width),E(\"height\",I?null:l.height);else if(F.match(W))P(F),s(l,B+\"._inputRange\").set(null);else if(F.match(X)){P(F),s(l,B+\"._inputRange\").set(null);var Q=s(l,B).get();Q._inputDomain&&(Q._input.domain=Q._inputDomain.slice())}else F.match(Z)&&s(l,B+\"._inputDomain\").set(null);if(\"type\"===R){var $=V,tt=\"linear\"===U.type&&\"log\"===I,et=\"log\"===U.type&&\"linear\"===I;if(tt||et){if($&&$.range)if(U.autorange)tt&&($.range=$.range[1]>$.range[0]?[1,2]:[2,1]);else{var rt=$.range[0],nt=$.range[1];tt?(rt<=0&&nt<=0&&E(B+\".autorange\",!0),rt<=0?rt=nt/1e6:nt<=0&&(nt=rt/1e6),E(B+\".range[0]\",Math.log(rt)/Math.LN10),E(B+\".range[1]\",Math.log(nt)/Math.LN10)):(E(B+\".range[0]\",Math.pow(10,rt)),E(B+\".range[1]\",Math.pow(10,nt)))}else E(B+\".autorange\",!0);Array.isArray(l._subplots.polar)&&l._subplots.polar.length&&l[z.parts[0]]&&\"radialaxis\"===z.parts[1]&&delete l[z.parts[0]]._subplot.viewInitial[\"radialaxis.range\"],u.getComponentMethod(\"annotations\",\"convertCoords\")(t,U,I,E),u.getComponentMethod(\"images\",\"convertCoords\")(t,U,I,E)}else E(B+\".autorange\",!0),E(B+\".range\",null);s(l,B+\"._inputRange\").set(null)}else if(R.match(A)){var at=s(l,O).get(),it=(I||{}).type;it&&\"-\"!==it||(it=\"linear\"),u.getComponentMethod(\"annotations\",\"convertCoords\")(t,at,it,E),u.getComponentMethod(\"images\",\"convertCoords\")(t,at,it,E)}var ot=w.containerArrayMatch(O);if(ot){r=ot.array,n=ot.index;var st=ot.property,lt=G||{editType:\"calc\"};\"\"!==n&&\"\"===st&&(w.isAddVal(I)?S[O]=null:w.isRemoveVal(I)?S[O]=(s(i,r).get()||[])[n]:o.warn(\"unrecognized full object value\",e)),M.update(_,lt),m[r]||(m[r]={});var ct=m[r][n];ct||(ct=m[r][n]={}),ct[st]=I,delete e[O]}else\"reverse\"===R?(V.range?V.range.reverse():(E(B+\".autorange\",!0),V.range=[1,0]),U.autorange?_.calc=!0:_.plot=!0):(l._has(\"scatter-like\")&&l._has(\"regl\")&&\"dragmode\"===O&&(\"lasso\"===I||\"select\"===I)&&\"lasso\"!==H&&\"select\"!==H?_.plot=!0:l._has(\"gl2d\")?_.plot=!0:G?M.update(_,G):_.calc=!0,z.set(I))}}for(r in m){w.applyContainerArrayChanges(t,f(i,r),m[r],_,f)||(_.plot=!0)}var ut=l._axisConstraintGroups||[];for(L in C)for(n=0;n<ut.length;n++){var ht=ut[n];if(ht[L])for(var ft in _.calc=!0,ht)C[ft]||(d.getFromId(t,ft)._constraintShrinkable=!0)}return(K(t)||e.height||e.width)&&(_.plot=!0),(_.plot||_.calc)&&(_.layoutReplot=!0),{flags:_,rangesAltered:C,undoit:S,redoit:T,eventData:v}}function K(t){var e=t._fullLayout,r=e.width,n=e.height;return t.layout.autosize&&f.plotAutoSize(t,t.layout,e),e.width!==r||e.height!==n}function Q(t,e,n,a){if(t=o.getGraphDiv(t),k.clearPromiseQueue(t),t.framework&&t.framework.isPolar)return Promise.resolve(t);o.isPlainObject(e)||(e={}),o.isPlainObject(n)||(n={}),Object.keys(e).length&&(t.changed=!0),Object.keys(n).length&&(t.changed=!0);var i=k.coerceTraceIndices(t,a),s=U(t,o.extendFlat({},e),i),l=s.flags,u=J(t,o.extendFlat({},n)),h=u.flags;(l.calc||h.calc)&&(t.calcdata=void 0),l.clearAxisTypes&&k.clearAxisTypes(t,i,n);var p=[];h.layoutReplot?p.push(T.layoutReplot):l.fullReplot?p.push(r.plot):(p.push(f.previousPromises),G(t,h,u)||f.supplyDefaults(t),l.style&&p.push(T.doTraceStyle),(l.colorbars||h.colorbars)&&p.push(T.doColorBars),h.legend&&p.push(T.doLegend),h.layoutstyle&&p.push(T.layoutStyles),h.axrange&&Y(p,u.rangesAltered),h.ticks&&p.push(T.doTicksRelayout),h.modebar&&p.push(T.doModeBar),h.camera&&p.push(T.doCamera),p.push(L)),p.push(f.rehover,f.redrag),c.add(t,Q,[t,s.undoit,u.undoit,s.traces],Q,[t,s.redoit,u.redoit,s.traces]);var d=o.syncOrAsync(p,t);return d&&d.then||(d=Promise.resolve(t)),d.then(function(){return t.emit(\"plotly_update\",{data:s.eventData,layout:u.eventData}),t})}function $(t){return function(e){e._fullLayout._guiEditing=!0;var r=t.apply(null,arguments);return e._fullLayout._guiEditing=!1,r}}var tt=[{pattern:/^hiddenlabels/,attr:\"legend.uirevision\"},{pattern:/^((x|y)axis\\d*)\\.((auto)?range|title\\.text)/},{pattern:/axis\\d*\\.showspikes$/,attr:\"modebar.uirevision\"},{pattern:/(hover|drag)mode$/,attr:\"modebar.uirevision\"},{pattern:/^(scene\\d*)\\.camera/},{pattern:/^(geo\\d*)\\.(projection|center|fitbounds)/},{pattern:/^(ternary\\d*\\.[abc]axis)\\.(min|title\\.text)$/},{pattern:/^(polar\\d*\\.radialaxis)\\.((auto)?range|angle|title\\.text)/},{pattern:/^(polar\\d*\\.angularaxis)\\.rotation/},{pattern:/^(mapbox\\d*)\\.(center|zoom|bearing|pitch)/},{pattern:/^legend\\.(x|y)$/,attr:\"editrevision\"},{pattern:/^(shapes|annotations)/,attr:\"editrevision\"},{pattern:/^title\\.text$/,attr:\"editrevision\"}],et=[{pattern:/^selectedpoints$/,attr:\"selectionrevision\"},{pattern:/(^|value\\.)visible$/,attr:\"legend.uirevision\"},{pattern:/^dimensions\\[\\d+\\]\\.constraintrange/},{pattern:/^node\\.(x|y|groups)/},{pattern:/^level$/},{pattern:/(^|value\\.)name$/},{pattern:/colorbar\\.title\\.text$/},{pattern:/colorbar\\.(x|y)$/,attr:\"editrevision\"}];function rt(t,e){for(var r=0;r<e.length;r++){var n=e[r],a=t.match(n.pattern);if(a)return{head:a[1],attr:n.attr}}}function nt(t,e){var r=s(e,t).get();if(void 0!==r)return r;var n=t.split(\".\");for(n.pop();n.length>1;)if(n.pop(),void 0!==(r=s(e,n.join(\".\")+\".uirevision\").get()))return r;return e.uirevision}function at(t,e){for(var r=0;r<e.length;r++)if(e[r]._fullInput.uid===t)return r;return-1}function it(t,e,r){for(var n=0;n<e.length;n++)if(e[n].uid===t)return n;return!e[r]||e[r].uid?-1:r}function ot(t,e){var r=o.isPlainObject(t),n=Array.isArray(t);return r||n?(r&&o.isPlainObject(e)||n&&Array.isArray(e))&&JSON.stringify(t)===JSON.stringify(e):t===e}function st(t,e,r,n){var a,i,l,c=n.getValObject,u=n.flags,h=n.immutable,f=n.inArray,p=n.arrayIndex;function d(){var t=a.editType;f&&-1!==t.indexOf(\"arraydraw\")?o.pushUnique(u.arrays[f],p):(M.update(u,a),\"none\"!==t&&u.nChanges++,n.transition&&a.anim&&u.nChangesAnim++,(W.test(l)||X.test(l))&&(u.rangesAltered[r[0]]=1),Z.test(l)&&s(e,\"_inputDomain\").set(null),\"datarevision\"===i&&(u.newDataRevision=1))}function g(t){return\"data_array\"===t.valType||t.arrayOk}for(i in t){if(u.calc&&!n.transition)return;var v=t[i],m=e[i],y=r.concat(i);if(l=y.join(\".\"),\"_\"!==i.charAt(0)&&\"function\"!=typeof v&&v!==m){if((\"tick0\"===i||\"dtick\"===i)&&\"geo\"!==r[0]){var x=e.tickmode;if(\"auto\"===x||\"array\"===x||!x)continue}if((\"range\"!==i||!e.autorange)&&(\"zmin\"!==i&&\"zmax\"!==i||\"contourcarpet\"!==e.type)&&(a=c(y))&&(!a._compareAsJSON||JSON.stringify(v)!==JSON.stringify(m))){var b,_=a.valType,w=g(a),k=Array.isArray(v),T=Array.isArray(m);if(k&&T){var A=\"_input_\"+i,S=t[A],E=e[A];if(Array.isArray(S)&&S===E)continue}if(void 0===m)w&&k?u.calc=!0:d();else if(a._isLinkedToArray){var L=[],C=!1;f||(u.arrays[i]=L);var P=Math.min(v.length,m.length),O=Math.max(v.length,m.length);if(P!==O){if(\"arraydraw\"!==a.editType){d();continue}C=!0}for(b=0;b<P;b++)st(v[b],m[b],y.concat(b),o.extendFlat({inArray:i,arrayIndex:b},n));if(C)for(b=P;b<O;b++)L.push(b)}else!_&&o.isPlainObject(v)?st(v,m,y,n):w?k&&T?(h&&(u.calc=!0),(h||n.newDataRevision)&&d()):k!==T?u.calc=!0:d():k&&T&&v.length===m.length&&String(v)===String(m)||d()}}}for(i in e)if(!(i in t||\"_\"===i.charAt(0)||\"function\"==typeof e[i])){if(g(a=c(r.concat(i)))&&Array.isArray(e[i]))return void(u.calc=!0);d()}}function lt(t){var e=n.select(t),r=t._fullLayout;if(r._container=e.selectAll(\".plot-container\").data([0]),r._container.enter().insert(\"div\",\":first-child\").classed(\"plot-container\",!0).classed(\"plotly\",!0),r._paperdiv=r._container.selectAll(\".svg-container\").data([0]),r._paperdiv.enter().append(\"div\").classed(\"svg-container\",!0).style(\"position\",\"relative\"),r._glcontainer=r._paperdiv.selectAll(\".gl-container\").data([{}]),r._glcontainer.enter().append(\"div\").classed(\"gl-container\",!0),r._paperdiv.selectAll(\".main-svg\").remove(),r._paperdiv.select(\".modebar-container\").remove(),r._paper=r._paperdiv.insert(\"svg\",\":first-child\").classed(\"main-svg\",!0),r._toppaper=r._paperdiv.append(\"svg\").classed(\"main-svg\",!0),r._modebardiv=r._paperdiv.append(\"div\"),r._hoverpaper=r._paperdiv.append(\"svg\").classed(\"main-svg\",!0),!r._uid){var a={};n.selectAll(\"defs\").each(function(){this.id&&(a[this.id.split(\"-\")[1]]=1)}),r._uid=o.randstr(a)}r._paperdiv.selectAll(\".main-svg\").attr(y.svgAttrs),r._defs=r._paper.append(\"defs\").attr(\"id\",\"defs-\"+r._uid),r._clips=r._defs.append(\"g\").classed(\"clips\",!0),r._topdefs=r._toppaper.append(\"defs\").attr(\"id\",\"topdefs-\"+r._uid),r._topclips=r._topdefs.append(\"g\").classed(\"clips\",!0),r._bgLayer=r._paper.append(\"g\").classed(\"bglayer\",!0),r._draggers=r._paper.append(\"g\").classed(\"draglayer\",!0);var i=r._paper.append(\"g\").classed(\"layer-below\",!0);r._imageLowerLayer=i.append(\"g\").classed(\"imagelayer\",!0),r._shapeLowerLayer=i.append(\"g\").classed(\"shapelayer\",!0),r._cartesianlayer=r._paper.append(\"g\").classed(\"cartesianlayer\",!0),r._polarlayer=r._paper.append(\"g\").classed(\"polarlayer\",!0),r._ternarylayer=r._paper.append(\"g\").classed(\"ternarylayer\",!0),r._geolayer=r._paper.append(\"g\").classed(\"geolayer\",!0),r._funnelarealayer=r._paper.append(\"g\").classed(\"funnelarealayer\",!0),r._pielayer=r._paper.append(\"g\").classed(\"pielayer\",!0),r._treemaplayer=r._paper.append(\"g\").classed(\"treemaplayer\",!0),r._sunburstlayer=r._paper.append(\"g\").classed(\"sunburstlayer\",!0),r._indicatorlayer=r._toppaper.append(\"g\").classed(\"indicatorlayer\",!0),r._glimages=r._paper.append(\"g\").classed(\"glimages\",!0);var s=r._toppaper.append(\"g\").classed(\"layer-above\",!0);r._imageUpperLayer=s.append(\"g\").classed(\"imagelayer\",!0),r._shapeUpperLayer=s.append(\"g\").classed(\"shapelayer\",!0),r._infolayer=r._toppaper.append(\"g\").classed(\"infolayer\",!0),r._menulayer=r._toppaper.append(\"g\").classed(\"menulayer\",!0),r._zoomlayer=r._toppaper.append(\"g\").classed(\"zoomlayer\",!0),r._hoverlayer=r._hoverpaper.append(\"g\").classed(\"hoverlayer\",!0),r._modebardiv.classed(\"modebar-container\",!0).style(\"position\",\"absolute\").style(\"top\",\"0px\").style(\"right\",\"0px\"),t.emit(\"plotly_framework\")}r.animate=function(t,e,r){if(t=o.getGraphDiv(t),!o.isPlotDiv(t))throw new Error(\"This element is not a Plotly plot: \"+t+\". It's likely that you've failed to create a plot before animating it. For more details, see https://plot.ly/javascript/animations/\");var n=t._transitionData;n._frameQueue||(n._frameQueue=[]);var a=(r=f.supplyAnimationDefaults(r)).transition,i=r.frame;function s(t){return Array.isArray(a)?t>=a.length?a[0]:a[t]:a}function l(t){return Array.isArray(i)?t>=i.length?i[0]:i[t]:i}function c(t,e){var r=0;return function(){if(t&&++r===e)return t()}}return void 0===n._frameWaitingCnt&&(n._frameWaitingCnt=0),new Promise(function(i,u){function h(){n._currentFrame&&n._currentFrame.onComplete&&n._currentFrame.onComplete();var e=n._currentFrame=n._frameQueue.shift();if(e){var r=e.name?e.name.toString():null;t._fullLayout._currentFrame=r,n._lastFrameAt=Date.now(),n._timeToNext=e.frameOpts.duration,f.transition(t,e.frame.data,e.frame.layout,k.coerceTraceIndices(t,e.frame.traces),e.frameOpts,e.transitionOpts).then(function(){e.onComplete&&e.onComplete()}),t.emit(\"plotly_animatingframe\",{name:r,frame:e.frame,animation:{frame:e.frameOpts,transition:e.transitionOpts}})}else t.emit(\"plotly_animated\"),window.cancelAnimationFrame(n._animationRaf),n._animationRaf=null}function p(){t.emit(\"plotly_animating\"),n._lastFrameAt=-1/0,n._timeToNext=0,n._runningTransitions=0,n._currentFrame=null;var e=function(){n._animationRaf=window.requestAnimationFrame(e),Date.now()-n._lastFrameAt>n._timeToNext&&h()};e()}var d,g,v=0;function m(t){return Array.isArray(a)?v>=a.length?t.transitionOpts=a[v]:t.transitionOpts=a[0]:t.transitionOpts=a,v++,t}var y=[],x=null==e,b=Array.isArray(e);if(x||b||!o.isPlainObject(e)){if(x||-1!==[\"string\",\"number\"].indexOf(typeof e))for(d=0;d<n._frames.length;d++)(g=n._frames[d])&&(x||String(g.group)===String(e))&&y.push({type:\"byname\",name:String(g.name),data:m({name:g.name})});else if(b)for(d=0;d<e.length;d++){var _=e[d];-1!==[\"number\",\"string\"].indexOf(typeof _)?(_=String(_),y.push({type:\"byname\",name:_,data:m({name:_})})):o.isPlainObject(_)&&y.push({type:\"object\",data:m(o.extendFlat({},_))})}}else y.push({type:\"object\",data:m(o.extendFlat({},e))});for(d=0;d<y.length;d++)if(\"byname\"===(g=y[d]).type&&!n._frameHash[g.data.name])return o.warn('animate failure: frame not found: \"'+g.data.name+'\"'),void u();-1!==[\"next\",\"immediate\"].indexOf(r.mode)&&function(){if(0!==n._frameQueue.length){for(;n._frameQueue.length;){var e=n._frameQueue.pop();e.onInterrupt&&e.onInterrupt()}t.emit(\"plotly_animationinterrupted\",[])}}(),\"reverse\"===r.direction&&y.reverse();var w=t._fullLayout._currentFrame;if(w&&r.fromcurrent){var T=-1;for(d=0;d<y.length;d++)if(\"byname\"===(g=y[d]).type&&g.name===w){T=d;break}if(T>0&&T<y.length-1){var M=[];for(d=0;d<y.length;d++)g=y[d],(\"byname\"!==y[d].type||d>T)&&M.push(g);y=M}}y.length>0?function(e){if(0!==e.length){for(var a=0;a<e.length;a++){var o;o=\"byname\"===e[a].type?f.computeFrame(t,e[a].name):e[a].data;var h=l(a),d=s(a);d.duration=Math.min(d.duration,h.duration);var g={frame:o,name:e[a].name,frameOpts:h,transitionOpts:d};a===e.length-1&&(g.onComplete=c(i,2),g.onInterrupt=u),n._frameQueue.push(g)}\"immediate\"===r.mode&&(n._lastFrameAt=-1/0),n._animationRaf||p()}}(y):(t.emit(\"plotly_animated\"),i())})},r.addFrames=function(t,e,r){if(t=o.getGraphDiv(t),null==e)return Promise.resolve();if(!o.isPlotDiv(t))throw new Error(\"This element is not a Plotly plot: \"+t+\". It's likely that you've failed to create a plot before adding frames. For more details, see https://plot.ly/javascript/animations/\");var n,a,i,s,l=t._transitionData._frames,u=t._transitionData._frameHash;if(!Array.isArray(e))throw new Error(\"addFrames failure: frameList must be an Array of frame definitions\"+e);var h=l.length+2*e.length,p=[],d={};for(n=e.length-1;n>=0;n--)if(o.isPlainObject(e[n])){var g=e[n].name,v=(u[g]||d[g]||{}).name,m=e[n].name,y=u[v]||d[v];v&&m&&\"number\"==typeof m&&y&&S<E&&(S++,o.warn('addFrames: overwriting frame \"'+(u[v]||d[v]).name+'\" with a frame whose name of type \"number\" also equates to \"'+v+'\". This is valid but may potentially lead to unexpected behavior since all plotly.js frame names are stored internally as strings.'),S===E&&o.warn(\"addFrames: This API call has yielded too many of these warnings. For the rest of this call, further warnings about numeric frame names will be suppressed.\")),d[g]={name:g},p.push({frame:f.supplyFrameDefaults(e[n]),index:r&&void 0!==r[n]&&null!==r[n]?r[n]:h+n})}p.sort(function(t,e){return t.index>e.index?-1:t.index<e.index?1:0});var x=[],b=[],_=l.length;for(n=p.length-1;n>=0;n--){if(\"number\"==typeof(a=p[n].frame).name&&o.warn(\"Warning: addFrames accepts frames with numeric names, but the numbers areimplicitly cast to strings\"),!a.name)for(;u[a.name=\"frame \"+t._transitionData._counter++];);if(u[a.name]){for(i=0;i<l.length&&(l[i]||{}).name!==a.name;i++);x.push({type:\"replace\",index:i,value:a}),b.unshift({type:\"replace\",index:i,value:l[i]})}else s=Math.max(0,Math.min(p[n].index,_)),x.push({type:\"insert\",index:s,value:a}),b.unshift({type:\"delete\",index:s}),_++}var w=f.modifyFrames,k=f.modifyFrames,T=[t,b],M=[t,x];return c&&c.add(t,w,T,k,M),f.modifyFrames(t,x)},r.deleteFrames=function(t,e){if(t=o.getGraphDiv(t),!o.isPlotDiv(t))throw new Error(\"This element is not a Plotly plot: \"+t);var r,n,a=t._transitionData._frames,i=[],s=[];if(!e)for(e=[],r=0;r<a.length;r++)e.push(r);for((e=e.slice()).sort(),r=e.length-1;r>=0;r--)n=e[r],i.push({type:\"delete\",index:n}),s.unshift({type:\"insert\",index:n,value:a[n]});var l=f.modifyFrames,u=f.modifyFrames,h=[t,s],p=[t,i];return c&&c.add(t,l,h,u,p),f.modifyFrames(t,i)},r.addTraces=function t(e,n,a){e=o.getGraphDiv(e);var i,s,l=[],u=r.deleteTraces,h=t,f=[e,l],p=[e,n];for(function(t,e,r){var n,a;if(!Array.isArray(t.data))throw new Error(\"gd.data must be an array.\");if(\"undefined\"==typeof e)throw new Error(\"traces must be defined.\");for(Array.isArray(e)||(e=[e]),n=0;n<e.length;n++)if(\"object\"!=typeof(a=e[n])||Array.isArray(a)||null===a)throw new Error(\"all values in traces array must be non-array objects\");if(\"undefined\"==typeof r||Array.isArray(r)||(r=[r]),\"undefined\"!=typeof r&&r.length!==e.length)throw new Error(\"if indices is specified, traces.length must equal indices.length\")}(e,n,a),Array.isArray(n)||(n=[n]),n=n.map(function(t){return o.extendFlat({},t)}),k.cleanData(n),i=0;i<n.length;i++)e.data.push(n[i]);for(i=0;i<n.length;i++)l.push(-n.length+i);if(\"undefined\"==typeof a)return s=r.redraw(e),c.add(e,u,f,h,p),s;Array.isArray(a)||(a=[a]);try{D(e,l,a)}catch(t){throw e.data.splice(e.data.length-n.length,n.length),t}return c.startSequence(e),c.add(e,u,f,h,p),s=r.moveTraces(e,l,a),c.stopSequence(e),s},r.deleteTraces=function t(e,n){e=o.getGraphDiv(e);var a,i,s=[],l=r.addTraces,u=t,h=[e,s,n],f=[e,n];if(\"undefined\"==typeof n)throw new Error(\"indices must be an integer or array of integers.\");for(Array.isArray(n)||(n=[n]),I(e,n,\"indices\"),(n=z(n,e.data.length-1)).sort(o.sorterDes),a=0;a<n.length;a+=1)i=e.data.splice(n[a],1)[0],s.push(i);var p=r.redraw(e);return c.add(e,l,h,u,f),p},r.extendTraces=function t(e,n,a,i){var s=R(e=o.getGraphDiv(e),n,a,i,function(t,e,r){var n,a;if(o.isTypedArray(t))if(r<0){var i=new t.constructor(0),s=F(t,e);r<0?(n=s,a=i):(n=i,a=s)}else if(n=new t.constructor(r),a=new t.constructor(t.length+e.length-r),r===e.length)n.set(e),a.set(t);else if(r<e.length){var l=e.length-r;n.set(e.subarray(l)),a.set(t),a.set(e.subarray(0,l),t.length)}else{var c=r-e.length,u=t.length-c;n.set(t.subarray(u)),n.set(e,c),a.set(t.subarray(0,u))}else n=t.concat(e),a=r>=0&&r<n.length?n.splice(0,n.length-r):[];return[n,a]}),l=r.redraw(e),u=[e,s.update,a,s.maxPoints];return c.add(e,r.prependTraces,u,t,arguments),l},r.moveTraces=function t(e,n,a){var i,s=[],l=[],u=t,h=t,f=[e=o.getGraphDiv(e),a,n],p=[e,n,a];if(D(e,n,a),n=Array.isArray(n)?n:[n],\"undefined\"==typeof a)for(a=[],i=0;i<n.length;i++)a.push(-n.length+i);for(a=Array.isArray(a)?a:[a],n=z(n,e.data.length-1),a=z(a,e.data.length-1),i=0;i<e.data.length;i++)-1===n.indexOf(i)&&s.push(e.data[i]);for(i=0;i<n.length;i++)l.push({newIndex:a[i],trace:e.data[n[i]]});for(l.sort(function(t,e){return t.newIndex-e.newIndex}),i=0;i<l.length;i+=1)s.splice(l[i].newIndex,0,l[i].trace);e.data=s;var d=r.redraw(e);return c.add(e,u,f,h,p),d},r.prependTraces=function t(e,n,a,i){var s=R(e=o.getGraphDiv(e),n,a,i,function(t,e,r){var n,a;if(o.isTypedArray(t))if(r<=0){var i=new t.constructor(0),s=F(e,t);r<0?(n=s,a=i):(n=i,a=s)}else if(n=new t.constructor(r),a=new t.constructor(t.length+e.length-r),r===e.length)n.set(e),a.set(t);else if(r<e.length){var l=e.length-r;n.set(e.subarray(0,l)),a.set(e.subarray(l)),a.set(t,l)}else{var c=r-e.length;n.set(e),n.set(t.subarray(0,c),e.length),a.set(t.subarray(c))}else n=e.concat(t),a=r>=0&&r<n.length?n.splice(r,n.length):[];return[n,a]}),l=r.redraw(e),u=[e,s.update,a,s.maxPoints];return c.add(e,r.extendTraces,u,t,arguments),l},r.newPlot=function(t,e,n,a){return t=o.getGraphDiv(t),f.cleanPlot([],{},t._fullData||[],t._fullLayout||{}),f.purge(t),r.plot(t,e,n,a)},r.plot=function(t,e,a,i){var s;if(t=o.getGraphDiv(t),l.init(t),o.isPlainObject(e)){var c=e;e=c.data,a=c.layout,i=c.config,s=c.frames}if(!1===l.triggerHandler(t,\"plotly_beforeplot\",[e,a,i]))return Promise.reject();e||a||o.isPlotDiv(t)||o.warn(\"Calling Plotly.plot as if redrawing but this container doesn't yet have a plot.\",t),O(t,i),a||(a={}),n.select(t).classed(\"js-plotly-plot\",!0),g.makeTester(),Array.isArray(t._promises)||(t._promises=[]);var h=0===(t.data||[]).length&&Array.isArray(e);Array.isArray(e)&&(k.cleanData(e),h?t.data=e:t.data.push.apply(t.data,e),t.empty=!1),t.layout&&!h||(t.layout=k.cleanLayout(a)),f.supplyDefaults(t);var v=t._fullLayout,y=v._has(\"cartesian\");if(!v._has(\"polar\")&&e&&e[0]&&e[0].r)return o.log(\"Legacy polar charts are deprecated!\"),function(t,e,r){var a=n.select(t).selectAll(\".plot-container\").data([0]);a.enter().insert(\"div\",\":first-child\").classed(\"plot-container plotly\",!0);var i=a.selectAll(\".svg-container\").data([0]);i.enter().append(\"div\").classed(\"svg-container\",!0).style(\"position\",\"relative\"),i.html(\"\"),e&&(t.data=e),r&&(t.layout=r),p.manager.fillLayout(t),i.style({width:t._fullLayout.width+\"px\",height:t._fullLayout.height+\"px\"}),t.framework=p.manager.framework(t),t.framework({data:t.data,layout:t.layout},i.node()),t.framework.setUndoPoint();var s=t.framework.svg(),l=1,c=t._fullLayout.title?t._fullLayout.title.text:\"\";\"\"!==c&&c||(l=0);var u=function(){this.call(x.convertToTspans,t)},h=s.select(\".title-group text\").call(u);if(t._context.edits.titleText){var d=o._(t,\"Click to enter Plot title\");c&&c!==d||(l=.2,h.attr({\"data-unformatted\":d}).text(d).style({opacity:l}).on(\"mouseover.opacity\",function(){n.select(this).transition().duration(100).style(\"opacity\",1)}).on(\"mouseout.opacity\",function(){n.select(this).transition().duration(1e3).style(\"opacity\",0)}));var g=function(){this.call(x.makeEditable,{gd:t}).on(\"edit\",function(e){t.framework({layout:{title:{text:e}}}),this.text(e).call(u),this.call(g)}).on(\"cancel\",function(){var t=this.attr(\"data-unformatted\");this.text(t).call(u)})};h.call(g)}return t._context.setBackground(t,t._fullLayout.paper_bgcolor),f.addLinks(t),Promise.resolve()}(t,e,a);v._replotting=!0,h&&lt(t),t.framework!==lt&&(t.framework=lt,lt(t)),g.initGradients(t),h&&d.saveShowSpikeInitial(t);var b=!t.calcdata||t.calcdata.length!==(t._fullData||[]).length;b&&f.doCalcdata(t);for(var _=0;_<t.calcdata.length;_++)t.calcdata[_][0].trace=t._fullData[_];t._context.responsive?t._responsiveChartHandler||(t._responsiveChartHandler=function(){o.isHidden(t)||f.resize(t)},window.addEventListener(\"resize\",t._responsiveChartHandler)):o.clearResponsive(t);var w=o.extendFlat({},v._size),M=0;function A(){if(f.clearAutoMarginIds(t),T.drawMarginPushers(t),d.allowAutoMargin(t),v._has(\"pie\"))for(var e=t._fullData,r=0;r<e.length;r++){var n=e[r];\"pie\"===n.type&&n.automargin&&f.allowAutoMargin(t,\"pie.\"+n.uid+\".automargin\")}return f.doAutoMargin(t),f.previousPromises(t)}function S(){t._transitioning||(T.doAutoRangeAndConstraints(t),h&&d.saveRangeInitial(t),u.getComponentMethod(\"rangeslider\",\"calcAutorange\")(t))}var E=[f.previousPromises,function(){if(s)return r.addFrames(t,s)},function e(){for(var r=v._basePlotModules,n=0;n<r.length;n++)r[n].drawFramework&&r[n].drawFramework(t);if(!v._glcanvas&&v._has(\"gl\")&&(v._glcanvas=v._glcontainer.selectAll(\".gl-canvas\").data([{key:\"contextLayer\",context:!0,pick:!1},{key:\"focusLayer\",context:!1,pick:!1},{key:\"pickLayer\",context:!1,pick:!0}],function(t){return t.key}),v._glcanvas.enter().append(\"canvas\").attr(\"class\",function(t){return\"gl-canvas gl-canvas-\"+t.key.replace(\"Layer\",\"\")}).style({position:\"absolute\",top:0,left:0,overflow:\"visible\",\"pointer-events\":\"none\"})),v._glcanvas){v._glcanvas.attr(\"width\",v.width).attr(\"height\",v.height);var a=v._glcanvas.data()[0].regl;if(a&&(Math.floor(v.width)!==a._gl.drawingBufferWidth||Math.floor(v.height)!==a._gl.drawingBufferHeight)){var i=\"WebGL context buffer and canvas dimensions do not match due to browser/WebGL bug.\";if(!M)return o.log(i+\" Clearing graph and plotting again.\"),f.cleanPlot([],{},t._fullData,v),f.supplyDefaults(t),v=t._fullLayout,f.doCalcdata(t),M++,e();o.error(i)}}return\"h\"===v.modebar.orientation?v._modebardiv.style(\"height\",null).style(\"width\",\"100%\"):v._modebardiv.style(\"width\",null).style(\"height\",v.height+\"px\"),f.previousPromises(t)},A,function(){if(f.didMarginChange(w,v._size))return o.syncOrAsync([A,T.layoutStyles],t)}];y&&E.push(function(){if(b)return o.syncOrAsync([u.getComponentMethod(\"shapes\",\"calcAutorange\"),u.getComponentMethod(\"annotations\",\"calcAutorange\"),S],t);S()}),E.push(T.layoutStyles),y&&E.push(function(){return d.draw(t,h?\"\":\"redraw\")}),E.push(T.drawData,T.finalDraw,m,f.addLinks,f.rehover,f.redrag,f.doAutoMargin,f.previousPromises);var C=o.syncOrAsync(E,t);return C&&C.then||(C=Promise.resolve()),C.then(function(){return L(t),t})},r.purge=function(t){var e=(t=o.getGraphDiv(t))._fullLayout||{},r=t._fullData||[];return f.cleanPlot([],{},r,e),f.purge(t),l.purge(t),e._container&&e._container.remove(),delete t._context,t},r.react=function(t,e,n,a){var i,l;t=o.getGraphDiv(t),k.clearPromiseQueue(t);var c=t._fullData,p=t._fullLayout;if(o.isPlotDiv(t)&&c&&p){if(o.isPlainObject(e)){var d=e;e=d.data,n=d.layout,a=d.config,i=d.frames}var g=!1;if(a){var v=o.extendDeep({},t._context);t._context=void 0,O(t,a),g=function t(e,r){var n;for(n in e)if(\"_\"!==n.charAt(0)){var a=e[n],i=r[n];if(a!==i)if(o.isPlainObject(a)&&o.isPlainObject(i)){if(t(a,i))return!0}else{if(!Array.isArray(a)||!Array.isArray(i))return!0;if(a.length!==i.length)return!0;for(var s=0;s<a.length;s++)if(a[s]!==i[s]){if(!o.isPlainObject(a[s])||!o.isPlainObject(i[s]))return!0;if(t(a[s],i[s]))return!0}}}}(v,t._context)}t.data=e||[],k.cleanData(t.data),t.layout=n||{},k.cleanLayout(t.layout),function(t,e,r,n){var a,i,l,c,u,h,f,p,d=n._preGUI,g=[],v={};for(a in d){if(u=rt(a,tt)){if(i=u.attr||u.head+\".uirevision\",(c=(l=s(n,i).get())&&nt(i,e))&&c===l&&(null===(h=d[a])&&(h=void 0),ot(p=(f=s(e,a)).get(),h))){void 0===p&&\"autorange\"===a.substr(a.length-9)&&g.push(a.substr(0,a.length-10)),f.set(N(s(n,a).get()));continue}}else o.warn(\"unrecognized GUI edit: \"+a);delete d[a],\"range[\"===a.substr(a.length-8,6)&&(v[a.substr(0,a.length-9)]=1)}for(var m=0;m<g.length;m++){var y=g[m];if(v[y]){var x=s(e,y).get();x&&delete x.autorange}}var b=n._tracePreGUI;for(var _ in b){var w,k=b[_],T=null;for(a in k){if(!T){var M=at(_,r);if(M<0){delete b[_];break}var A=it(_,t,(w=r[M]._fullInput).index);if(A<0){delete b[_];break}T=t[A]}if(u=rt(a,et)){if(u.attr?c=(l=s(n,u.attr).get())&&nt(u.attr,e):(l=w.uirevision,void 0===(c=T.uirevision)&&(c=e.uirevision)),c&&c===l&&(null===(h=k[a])&&(h=void 0),ot(p=(f=s(T,a)).get(),h))){f.set(N(s(w,a).get()));continue}}else o.warn(\"unrecognized GUI edit: \"+a+\" in trace uid \"+_);delete k[a]}}}(t.data,t.layout,c,p),f.supplyDefaults(t,{skipUpdateCalc:!0});var m=t._fullData,y=t._fullLayout,x=void 0===y.datarevision,b=y.transition,_=function(t,e,r,n,a){var i=M.layoutFlags();return i.arrays={},i.rangesAltered={},i.nChanges=0,i.nChangesAnim=0,st(e,r,[],{getValObject:function(t){return h.getLayoutValObject(r,t)},flags:i,immutable:n,transition:a,gd:t}),(i.plot||i.calc)&&(i.layoutReplot=!0),a&&i.nChanges&&i.nChangesAnim&&(i.anim=i.nChanges===i.nChangesAnim?\"all\":\"some\"),i}(t,p,y,x,b),w=_.newDataRevision,A=function(t,e,r,n,a,i){var o=e.length===r.length;if(!a&&!o)return{fullReplot:!0,calc:!0};var s,l,c=M.traceFlags();c.arrays={},c.nChanges=0,c.nChangesAnim=0;var u={getValObject:function(t){var e=h.getTraceValObject(l,t);return!l._module.animatable&&e.anim&&(e.anim=!1),e},flags:c,immutable:n,transition:a,newDataRevision:i,gd:t},p={};for(s=0;s<e.length;s++)if(r[s]){if(l=r[s]._fullInput,f.hasMakesDataTransform(l)&&(l=r[s]),p[l.uid])continue;p[l.uid]=1,st(e[s]._fullInput,l,[],u)}return(c.calc||c.plot)&&(c.fullReplot=!0),a&&c.nChanges&&c.nChangesAnim&&(c.anim=c.nChanges===c.nChangesAnim&&o?\"all\":\"some\"),c}(t,c,m,x,b,w);K(t)&&(_.layoutReplot=!0),A.calc||_.calc?t.calcdata=void 0:f.supplyDefaultsUpdateCalc(t.calcdata,m);var S=[];if(i&&(t._transitionData={},f.createTransitionData(t),S.push(function(){return r.addFrames(t,i)})),y.transition&&!g&&(A.anim||_.anim))f.doCalcdata(t),T.doAutoRangeAndConstraints(t),S.push(function(){return f.transitionFromReact(t,A,_,p)});else if(A.fullReplot||_.layoutReplot||g)t._fullLayout._skipDefaults=!0,S.push(r.plot);else{for(var E in _.arrays){var C=_.arrays[E];if(C.length){var P=u.getComponentMethod(E,\"drawOne\");if(P!==o.noop)for(var z=0;z<C.length;z++)P(t,C[z]);else{var I=u.getComponentMethod(E,\"draw\");if(I===o.noop)throw new Error(\"cannot draw components: \"+E);I(t)}}}S.push(f.previousPromises),A.style&&S.push(T.doTraceStyle),(A.colorbars||_.colorbars)&&S.push(T.doColorBars),_.legend&&S.push(T.doLegend),_.layoutstyle&&S.push(T.layoutStyles),_.axrange&&Y(S),_.ticks&&S.push(T.doTicksRelayout),_.modebar&&S.push(T.doModeBar),_.camera&&S.push(T.doCamera),S.push(L)}S.push(f.rehover,f.redrag),(l=o.syncOrAsync(S,t))&&l.then||(l=Promise.resolve(t))}else l=r.newPlot(t,e,n,a);return l.then(function(){return t.emit(\"plotly_react\",{data:e,layout:n}),t})},r.redraw=function(t){if(t=o.getGraphDiv(t),!o.isPlotDiv(t))throw new Error(\"This element is not a Plotly plot: \"+t);return k.cleanData(t.data),k.cleanLayout(t.layout),t.calcdata=void 0,r.plot(t).then(function(){return t.emit(\"plotly_redraw\"),t})},r.relayout=H,r.restyle=B,r.setPlotConfig=function(t){return o.extendFlat(_,t)},r.update=Q,r._guiRelayout=$(H),r._guiRestyle=$(B),r._guiUpdate=$(Q),r._storeDirectGUIEdit=function(t,e,r){for(var n in r)V(n,s(t,n).get(),r[n],e)}},{\"../components/color\":592,\"../components/drawing\":613,\"../constants/xmlns_namespaces\":694,\"../lib\":717,\"../lib/events\":707,\"../lib/queue\":732,\"../lib/svg_text_utils\":741,\"../plots/cartesian/axes\":765,\"../plots/cartesian/constants\":771,\"../plots/cartesian/graph_interact\":774,\"../plots/cartesian/select\":782,\"../plots/plots\":826,\"../plots/polar/legacy\":834,\"../registry\":846,\"./edit_types\":748,\"./helpers\":749,\"./manage_arrays\":751,\"./plot_config\":753,\"./plot_schema\":754,\"./subroutines\":756,d3:165,\"fast-isnumeric\":228,\"has-hover\":412}],753:[function(t,e,r){\"use strict\";var n={staticPlot:{valType:\"boolean\",dflt:!1},plotlyServerURL:{valType:\"string\",dflt:\"https://plot.ly\"},editable:{valType:\"boolean\",dflt:!1},edits:{annotationPosition:{valType:\"boolean\",dflt:!1},annotationTail:{valType:\"boolean\",dflt:!1},annotationText:{valType:\"boolean\",dflt:!1},axisTitleText:{valType:\"boolean\",dflt:!1},colorbarPosition:{valType:\"boolean\",dflt:!1},colorbarTitleText:{valType:\"boolean\",dflt:!1},legendPosition:{valType:\"boolean\",dflt:!1},legendText:{valType:\"boolean\",dflt:!1},shapePosition:{valType:\"boolean\",dflt:!1},titleText:{valType:\"boolean\",dflt:!1}},autosizable:{valType:\"boolean\",dflt:!1},responsive:{valType:\"boolean\",dflt:!1},fillFrame:{valType:\"boolean\",dflt:!1},frameMargins:{valType:\"number\",dflt:0,min:0,max:.5},scrollZoom:{valType:\"flaglist\",flags:[\"cartesian\",\"gl3d\",\"geo\",\"mapbox\"],extras:[!0,!1],dflt:\"gl3d+geo+mapbox\"},doubleClick:{valType:\"enumerated\",values:[!1,\"reset\",\"autosize\",\"reset+autosize\"],dflt:\"reset+autosize\"},doubleClickDelay:{valType:\"number\",dflt:300,min:0},showAxisDragHandles:{valType:\"boolean\",dflt:!0},showAxisRangeEntryBoxes:{valType:\"boolean\",dflt:!0},showTips:{valType:\"boolean\",dflt:!0},showLink:{valType:\"boolean\",dflt:!1},linkText:{valType:\"string\",dflt:\"Edit chart\",noBlank:!0},sendData:{valType:\"boolean\",dflt:!0},showSources:{valType:\"any\",dflt:!1},displayModeBar:{valType:\"enumerated\",values:[\"hover\",!0,!1],dflt:\"hover\"},showSendToCloud:{valType:\"boolean\",dflt:!1},showEditInChartStudio:{valType:\"boolean\",dflt:!1},modeBarButtonsToRemove:{valType:\"any\",dflt:[]},modeBarButtonsToAdd:{valType:\"any\",dflt:[]},modeBarButtons:{valType:\"any\",dflt:!1},toImageButtonOptions:{valType:\"any\",dflt:{}},displaylogo:{valType:\"boolean\",dflt:!0},watermark:{valType:\"boolean\",dflt:!1},plotGlPixelRatio:{valType:\"number\",dflt:2,min:1,max:4},setBackground:{valType:\"any\",dflt:\"transparent\"},topojsonURL:{valType:\"string\",noBlank:!0,dflt:\"https://cdn.plot.ly/\"},mapboxAccessToken:{valType:\"string\",dflt:null},logging:{valType:\"integer\",min:0,max:2,dflt:1},notifyOnLogging:{valType:\"integer\",min:0,max:2,dflt:0},queueLength:{valType:\"integer\",min:0,dflt:0},globalTransforms:{valType:\"any\",dflt:[]},locale:{valType:\"string\",dflt:\"en-US\"},locales:{valType:\"any\",dflt:{}}},a={};!function t(e,r){for(var n in e){var a=e[n];a.valType?r[n]=a.dflt:(r[n]||(r[n]={}),t(a,r[n]))}}(n,a),e.exports={configAttributes:n,dfltConfig:a}},{}],754:[function(t,e,r){\"use strict\";var n=t(\"../registry\"),a=t(\"../lib\"),i=t(\"../plots/attributes\"),o=t(\"../plots/layout_attributes\"),s=t(\"../plots/frame_attributes\"),l=t(\"../plots/animation_attributes\"),c=t(\"./plot_config\").configAttributes,u=t(\"../plots/polar/legacy/area_attributes\"),h=t(\"../plots/polar/legacy/axis_attributes\"),f=t(\"./edit_types\"),p=a.extendFlat,d=a.extendDeepAll,g=a.isPlainObject,v=a.isArrayOrTypedArray,m=a.nestedProperty,y=a.valObjectMeta,x=\"_isSubplotObj\",b=\"_isLinkedToArray\",_=[x,b,\"_arrayAttrRegexps\",\"_deprecated\"];function w(t,e,r){if(!t)return!1;if(t._isLinkedToArray)if(k(e[r]))r++;else if(r<e.length)return!1;for(;r<e.length;r++){var n=t[e[r]];if(!g(n))break;if(t=n,r===e.length-1)break;if(t._isLinkedToArray){if(!k(e[++r]))return!1}else if(\"info_array\"===t.valType){var a=e[++r];if(!k(a))return!1;var i=t.items;if(Array.isArray(i)){if(a>=i.length)return!1;if(2===t.dimensions){if(r++,e.length===r)return t;var o=e[r];if(!k(o))return!1;t=i[a][o]}else t=i[a]}else t=i}}return t}function k(t){return t===Math.round(t)&&t>=0}function T(){var t,e,r={};for(t in d(r,o),n.subplotsRegistry){if((e=n.subplotsRegistry[t]).layoutAttributes)if(Array.isArray(e.attr))for(var a=0;a<e.attr.length;a++)S(r,e,e.attr[a]);else S(r,e,\"subplot\"===e.attr?e.name:e.attr)}for(t in r=function(t){return p(t,{radialaxis:h.radialaxis,angularaxis:h.angularaxis}),p(t,h.layout),t}(r),n.componentsRegistry){var i=(e=n.componentsRegistry[t]).schema;if(i&&(i.subplots||i.layout)){var s=i.subplots;if(s&&s.xaxis&&!s.yaxis)for(var l in s.xaxis)delete r.yaxis[l]}else\"colorscale\"===e.name?d(r,e.layoutAttributes):e.layoutAttributes&&E(r,e.layoutAttributes,e.name)}return{layoutAttributes:A(r)}}function M(){var t={frames:d({},s)};return A(t),t.frames}function A(t){return function(t){r.crawl(t,function(t,e,n){r.isValObject(t)?\"data_array\"===t.valType?(t.role=\"data\",n[e+\"src\"]={valType:\"string\",editType:\"none\"}):!0===t.arrayOk&&(n[e+\"src\"]={valType:\"string\",editType:\"none\"}):g(t)&&(t.role=\"object\")})}(t),function(t){r.crawl(t,function(t,e,r){if(!t)return;var n=t[b];if(!n)return;delete t[b],r[e]={items:{}},r[e].items[n]=t,r[e].role=\"object\"})}(t),function(t){!function t(e){for(var r in e)if(g(e[r]))t(e[r]);else if(Array.isArray(e[r]))for(var n=0;n<e[r].length;n++)t(e[r][n]);else e[r]instanceof RegExp&&(e[r]=e[r].toString())}(t)}(t),t}function S(t,e,r){var n=m(t,r),a=d({},e.layoutAttributes);a[x]=!0,n.set(a)}function E(t,e,r){var n=m(t,r);n.set(d(n.get()||{},e))}r.IS_SUBPLOT_OBJ=x,r.IS_LINKED_TO_ARRAY=b,r.DEPRECATED=\"_deprecated\",r.UNDERSCORE_ATTRS=_,r.get=function(){var t={};n.allTypes.concat(\"area\").forEach(function(e){t[e]=function(t){var e,a;\"area\"===t?(e={attributes:u},a={}):(e=n.modules[t]._module,a=e.basePlotModule);var o={type:null},s=d({},i),l=d({},e.attributes);r.crawl(l,function(t,e,r,n,a){m(s,a).set(void 0),void 0===t&&m(l,a).set(void 0)}),d(o,s),n.traceIs(t,\"noOpacity\")&&delete o.opacity;n.traceIs(t,\"showLegend\")||(delete o.showlegend,delete o.legendgroup);n.traceIs(t,\"noHover\")&&(delete o.hoverinfo,delete o.hoverlabel);e.selectPoints||delete o.selectedpoints;d(o,l),a.attributes&&d(o,a.attributes);o.type=t;var c={meta:e.meta||{},categories:e.categories||{},animatable:Boolean(e.animatable),type:t,attributes:A(o)};if(e.layoutAttributes){var h={};d(h,e.layoutAttributes),c.layoutAttributes=A(h)}e.animatable||r.crawl(c,function(t){r.isValObject(t)&&\"anim\"in t&&delete t.anim});return c}(e)});var e={};return Object.keys(n.transformsRegistry).forEach(function(t){e[t]=function(t){var e=n.transformsRegistry[t],r=d({},e.attributes);return Object.keys(n.componentsRegistry).forEach(function(e){var a=n.componentsRegistry[e];a.schema&&a.schema.transforms&&a.schema.transforms[t]&&Object.keys(a.schema.transforms[t]).forEach(function(e){E(r,a.schema.transforms[t][e],e)})}),{attributes:A(r)}}(t)}),{defs:{valObjects:y,metaKeys:_.concat([\"description\",\"role\",\"editType\",\"impliedEdits\"]),editType:{traces:f.traces,layout:f.layout},impliedEdits:{}},traces:t,layout:T(),transforms:e,frames:M(),animation:A(l),config:A(c)}},r.crawl=function(t,e,n,a){var i=n||0;a=a||\"\",Object.keys(t).forEach(function(n){var o=t[n];if(-1===_.indexOf(n)){var s=(a?a+\".\":\"\")+n;e(o,n,t,i,s),r.isValObject(o)||g(o)&&\"impliedEdits\"!==n&&r.crawl(o,e,i+1,s)}})},r.isValObject=function(t){return t&&void 0!==t.valType},r.findArrayAttributes=function(t){var e,n,a=[],o=[],s=[];function l(t,r,i,l){o=o.slice(0,l).concat([r]),s=s.slice(0,l).concat([t&&t._isLinkedToArray]),t&&(\"data_array\"===t.valType||!0===t.arrayOk)&&!(\"colorbar\"===o[l-1]&&(\"ticktext\"===r||\"tickvals\"===r))&&function t(e,r,i){var l=e[o[r]];var c=i+o[r];if(r===o.length-1)v(l)&&a.push(n+c);else if(s[r]){if(Array.isArray(l))for(var u=0;u<l.length;u++)g(l[u])&&t(l[u],r+1,c+\"[\"+u+\"].\")}else g(l)&&t(l,r+1,c+\".\")}(e,0,\"\")}e=t,n=\"\",r.crawl(i,l),t._module&&t._module.attributes&&r.crawl(t._module.attributes,l);var c=t.transforms;if(c)for(var u=0;u<c.length;u++){var h=c[u],f=h._module;f&&(n=\"transforms[\"+u+\"].\",e=h,r.crawl(f.attributes,l))}return a},r.getTraceValObject=function(t,e){var r,a,o=e[0],s=1;if(\"transforms\"===o){if(1===e.length)return i.transforms;var l=t.transforms;if(!Array.isArray(l)||!l.length)return!1;var c=e[1];if(!k(c)||c>=l.length)return!1;a=(r=(n.transformsRegistry[l[c].type]||{}).attributes)&&r[e[2]],s=3}else if(\"area\"===t.type)a=u[o];else{var h=t._module;if(h||(h=(n.modules[t.type||i.type.dflt]||{})._module),!h)return!1;if(!(a=(r=h.attributes)&&r[o])){var f=h.basePlotModule;f&&f.attributes&&(a=f.attributes[o])}a||(a=i[o])}return w(a,e,s)},r.getLayoutValObject=function(t,e){return w(function(t,e){var r,a,i,s,l=t._basePlotModules;if(l){var c;for(r=0;r<l.length;r++){if((i=l[r]).attrRegex&&i.attrRegex.test(e)){if(i.layoutAttrOverrides)return i.layoutAttrOverrides;!c&&i.layoutAttributes&&(c=i.layoutAttributes)}var u=i.baseLayoutAttrOverrides;if(u&&e in u)return u[e]}if(c)return c}var f=t._modules;if(f)for(r=0;r<f.length;r++)if((s=f[r].layoutAttributes)&&e in s)return s[e];for(a in n.componentsRegistry){if(\"colorscale\"===(i=n.componentsRegistry[a]).name&&0===e.indexOf(\"coloraxis\"))return i.layoutAttributes[e];if(!i.schema&&e===i.name)return i.layoutAttributes}if(e in o)return o[e];if(\"radialaxis\"===e||\"angularaxis\"===e)return h[e];return h.layout[e]||!1}(t,e[0]),e,1)}},{\"../lib\":717,\"../plots/animation_attributes\":760,\"../plots/attributes\":762,\"../plots/frame_attributes\":792,\"../plots/layout_attributes\":817,\"../plots/polar/legacy/area_attributes\":832,\"../plots/polar/legacy/axis_attributes\":833,\"../registry\":846,\"./edit_types\":748,\"./plot_config\":753}],755:[function(t,e,r){\"use strict\";var n=t(\"../lib\"),a=t(\"../plots/attributes\"),i=\"templateitemname\",o={name:{valType:\"string\",editType:\"none\"}};function s(t){return t&&\"string\"==typeof t}function l(t){var e=t.length-1;return\"s\"!==t.charAt(e)&&n.warn(\"bad argument to arrayDefaultKey: \"+t),t.substr(0,t.length-1)+\"defaults\"}o[i]={valType:\"string\",editType:\"calc\"},r.templatedArray=function(t,e){return e._isLinkedToArray=t,e.name=o.name,e[i]=o[i],e},r.traceTemplater=function(t){var e,r,i={};for(e in t)r=t[e],Array.isArray(r)&&r.length&&(i[e]=0);return{newTrace:function(o){var s={type:e=n.coerce(o,{},a,\"type\"),_template:null};if(e in i){r=t[e];var l=i[e]%r.length;i[e]++,s._template=r[l]}return s}}},r.newContainer=function(t,e,r){var a=t._template,i=a&&(a[e]||r&&a[r]);return n.isPlainObject(i)||(i=null),t[e]={_template:i}},r.arrayTemplater=function(t,e,r){var n=t._template,a=n&&n[l(e)],o=n&&n[e];Array.isArray(o)&&o.length||(o=[]);var c={};return{newItem:function(t){var e={name:t.name,_input:t},n=e[i]=t[i];if(!s(n))return e._template=a,e;for(var l=0;l<o.length;l++){var u=o[l];if(u.name===n)return c[n]=1,e._template=u,e}return e[r]=t[r]||!1,e._template=!1,e},defaultItems:function(){for(var t=[],e=0;e<o.length;e++){var r=o[e],n=r.name;if(s(n)&&!c[n]){var a={_template:r,name:n,_input:{_templateitemname:n}};a[i]=r[i],t.push(a),c[n]=1}}return t}}},r.arrayDefaultKey=l,r.arrayEditor=function(t,e,r){var a=(n.nestedProperty(t,e).get()||[]).length,o=r._index,s=o>=a&&(r._input||{})._templateitemname;s&&(o=a);var l,c=e+\"[\"+o+\"]\";function u(){l={},s&&(l[c]={},l[c][i]=s)}function h(t,e){s?n.nestedProperty(l[c],t).set(e):l[c+\".\"+t]=e}function f(){var t=l;return u(),t}return u(),{modifyBase:function(t,e){l[t]=e},modifyItem:h,getUpdateObj:f,applyUpdate:function(e,r){e&&h(e,r);var a=f();for(var i in a)n.nestedProperty(t,i).set(a[i])}}}},{\"../lib\":717,\"../plots/attributes\":762}],756:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../registry\"),i=t(\"../plots/plots\"),o=t(\"../lib\"),s=t(\"../lib/clear_gl_canvases\"),l=t(\"../components/color\"),c=t(\"../components/drawing\"),u=t(\"../components/titles\"),h=t(\"../components/modebar\"),f=t(\"../plots/cartesian/axes\"),p=t(\"../constants/alignment\"),d=t(\"../plots/cartesian/constraints\"),g=d.enforce,v=d.clean,m=t(\"../plots/cartesian/autorange\").doAutoRange,y=\"start\",x=\"middle\",b=\"end\";function _(t,e,r){for(var n=0;n<r.length;n++){var a=r[n][0],i=r[n][1];if(!(a[0]>=t[1]||a[1]<=t[0])&&(i[0]<e[1]&&i[1]>e[0]))return!0}return!1}function w(t){var e,a,s,u,d,g,v=t._fullLayout,m=v._size,y=m.p,x=f.list(t,\"\",!0);if(v._paperdiv.style({width:t._context.responsive&&v.autosize&&!t._context._hasZeroWidth&&!t.layout.width?\"100%\":v.width+\"px\",height:t._context.responsive&&v.autosize&&!t._context._hasZeroHeight&&!t.layout.height?\"100%\":v.height+\"px\"}).selectAll(\".main-svg\").call(c.setSize,v.width,v.height),t._context.setBackground(t,v.paper_bgcolor),r.drawMainTitle(t),h.manage(t),!v._has(\"cartesian\"))return i.previousPromises(t);function b(t,e,r){var n=t._lw/2;return\"x\"===t._id.charAt(0)?e?\"top\"===r?e._offset-y-n:e._offset+e._length+y+n:m.t+m.h*(1-(t.position||0))+n%1:e?\"right\"===r?e._offset+e._length+y+n:e._offset-y-n:m.l+m.w*(t.position||0)+n%1}for(e=0;e<x.length;e++){var w=(u=x[e])._anchorAxis;u._linepositions={},u._lw=c.crispRound(t,u.linewidth,1),u._mainLinePosition=b(u,w,u.side),u._mainMirrorPosition=u.mirror&&w?b(u,w,p.OPPOSITE_SIDE[u.side]):null}var T=[],A=[],S=[],E=1===l.opacity(v.paper_bgcolor)&&1===l.opacity(v.plot_bgcolor)&&v.paper_bgcolor===v.plot_bgcolor;for(a in v._plots)if((s=v._plots[a]).mainplot)s.bg&&s.bg.remove(),s.bg=void 0;else{var L=s.xaxis.domain,C=s.yaxis.domain,P=s.plotgroup;if(_(L,C,S)){var O=P.node(),z=s.bg=o.ensureSingle(P,\"rect\",\"bg\");O.insertBefore(z.node(),O.childNodes[0]),A.push(a)}else P.select(\"rect.bg\").remove(),S.push([L,C]),E||(T.push(a),A.push(a))}var I,D,R,F,B,N,j,V,U,q,H,G,Y,W=v._bgLayer.selectAll(\".bg\").data(T);for(W.enter().append(\"rect\").classed(\"bg\",!0),W.exit().remove(),W.each(function(t){v._plots[t].bg=n.select(this)}),e=0;e<A.length;e++)s=v._plots[A[e]],d=s.xaxis,g=s.yaxis,s.bg&&s.bg.call(c.setRect,d._offset-y,g._offset-y,d._length+2*y,g._length+2*y).call(l.fill,v.plot_bgcolor).style(\"stroke-width\",0);if(!v._hasOnlyLargeSploms)for(a in v._plots){s=v._plots[a],d=s.xaxis,g=s.yaxis;var X,Z,J=s.clipId=\"clip\"+v._uid+a+\"plot\",K=o.ensureSingleById(v._clips,\"clipPath\",J,function(t){t.classed(\"plotclip\",!0).append(\"rect\")});s.clipRect=K.select(\"rect\").attr({width:d._length,height:g._length}),c.setTranslate(s.plot,d._offset,g._offset),s._hasClipOnAxisFalse?(X=null,Z=J):(X=J,Z=null),c.setClipUrl(s.plot,X,t),s.layerClipId=Z}function Q(t){return\"M\"+I+\",\"+t+\"H\"+D}function $(t){return\"M\"+d._offset+\",\"+t+\"h\"+d._length}function tt(t){return\"M\"+t+\",\"+V+\"V\"+j}function et(t){return\"M\"+t+\",\"+g._offset+\"v\"+g._length}function rt(t,e,r){if(!t.showline||a!==t._mainSubplot)return\"\";if(!t._anchorAxis)return r(t._mainLinePosition);var n=e(t._mainLinePosition);return t.mirror&&(n+=e(t._mainMirrorPosition)),n}for(a in v._plots){s=v._plots[a],d=s.xaxis,g=s.yaxis;var nt=\"M0,0\";k(d,a)&&(B=M(d,\"left\",g,x),I=d._offset-(B?y+B:0),N=M(d,\"right\",g,x),D=d._offset+d._length+(N?y+N:0),R=b(d,g,\"bottom\"),F=b(d,g,\"top\"),!(Y=!d._anchorAxis||a!==d._mainSubplot)||\"allticks\"!==d.mirror&&\"all\"!==d.mirror||(d._linepositions[a]=[R,F]),nt=rt(d,Q,$),Y&&d.showline&&(\"all\"===d.mirror||\"allticks\"===d.mirror)&&(nt+=Q(R)+Q(F)),s.xlines.style(\"stroke-width\",d._lw+\"px\").call(l.stroke,d.showline?d.linecolor:\"rgba(0,0,0,0)\")),s.xlines.attr(\"d\",nt);var at=\"M0,0\";k(g,a)&&(H=M(g,\"bottom\",d,x),j=g._offset+g._length+(H?y:0),G=M(g,\"top\",d,x),V=g._offset-(G?y:0),U=b(g,d,\"left\"),q=b(g,d,\"right\"),!(Y=!g._anchorAxis||a!==g._mainSubplot)||\"allticks\"!==g.mirror&&\"all\"!==g.mirror||(g._linepositions[a]=[U,q]),at=rt(g,tt,et),Y&&g.showline&&(\"all\"===g.mirror||\"allticks\"===g.mirror)&&(at+=tt(U)+tt(q)),s.ylines.style(\"stroke-width\",g._lw+\"px\").call(l.stroke,g.showline?g.linecolor:\"rgba(0,0,0,0)\")),s.ylines.attr(\"d\",at)}return f.makeClipPaths(t),i.previousPromises(t)}function k(t,e){return(t.ticks||t.showline)&&(e===t._mainSubplot||\"all\"===t.mirror||\"allticks\"===t.mirror)}function T(t,e,r){if(!r.showline||!r._lw)return!1;if(\"all\"===r.mirror||\"allticks\"===r.mirror)return!0;var n=r._anchorAxis;if(!n)return!1;var a=p.FROM_BL[e];return r.side===e?n.domain[a]===t.domain[a]:r.mirror&&n.domain[1-a]===t.domain[1-a]}function M(t,e,r,n){if(T(t,e,r))return r._lw;for(var a=0;a<n.length;a++){var i=n[a];if(i._mainAxis===r._mainAxis&&T(t,e,i))return i._lw}return 0}function A(t,e){var r=t.title,n=t._size,a=0;switch(e===y?a=r.pad.l:e===b&&(a=-r.pad.r),r.xref){case\"paper\":return n.l+n.w*r.x+a;case\"container\":default:return t.width*r.x+a}}function S(t,e){var r=t.title,n=t._size,a=0;if(\"0em\"!==e&&e?e===p.CAP_SHIFT+\"em\"&&(a=r.pad.t):a=-r.pad.b,\"auto\"===r.y)return n.t/2;switch(r.yref){case\"paper\":return n.t+n.h-n.h*r.y+a;case\"container\":default:return t.height-t.height*r.y+a}}r.layoutStyles=function(t){return o.syncOrAsync([i.doAutoMargin,w],t)},r.drawMainTitle=function(t){var e=t._fullLayout,r=function(t){var e=t.title,r=x;o.isRightAnchor(e)?r=b:o.isLeftAnchor(e)&&(r=y);return r}(e),n=function(t){var e=t.title,r=\"0em\";o.isTopAnchor(e)?r=p.CAP_SHIFT+\"em\":o.isMiddleAnchor(e)&&(r=p.MID_SHIFT+\"em\");return r}(e);u.draw(t,\"gtitle\",{propContainer:e,propName:\"title.text\",placeholder:e._dfltTitle.plot,attributes:{x:A(e,r),y:S(e,n),\"text-anchor\":r,dy:n}})},r.doTraceStyle=function(t){var e,n=t.calcdata,o=[];for(e=0;e<n.length;e++){var l=n[e],c=l[0]||{},u=c.trace||{},h=u._module||{},f=h.arraysToCalcdata;f&&f(l,u);var p=h.editStyle;p&&o.push({fn:p,cd0:c})}if(o.length){for(e=0;e<o.length;e++){var d=o[e];d.fn(t,d.cd0)}s(t),r.redrawReglTraces(t)}return i.style(t),a.getComponentMethod(\"legend\",\"draw\")(t),i.previousPromises(t)},r.doColorBars=function(t){return a.getComponentMethod(\"colorbar\",\"draw\")(t),i.previousPromises(t)},r.layoutReplot=function(t){var e=t.layout;return t.layout=void 0,a.call(\"plot\",t,\"\",e)},r.doLegend=function(t){return a.getComponentMethod(\"legend\",\"draw\")(t),i.previousPromises(t)},r.doTicksRelayout=function(t){return f.draw(t,\"redraw\"),t._fullLayout._hasOnlyLargeSploms&&(a.subplotsRegistry.splom.updateGrid(t),s(t),r.redrawReglTraces(t)),r.drawMainTitle(t),i.previousPromises(t)},r.doModeBar=function(t){var e=t._fullLayout;h.manage(t);for(var r=0;r<e._basePlotModules.length;r++){var n=e._basePlotModules[r].updateFx;n&&n(t)}return i.previousPromises(t)},r.doCamera=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=0;n<r.length;n++){var a=e[r[n]];a._scene.setViewport(a)}},r.drawData=function(t){var e=t._fullLayout;s(t);for(var n=e._basePlotModules,o=0;o<n.length;o++)n[o].plot(t);return r.redrawReglTraces(t),i.style(t),a.getComponentMethod(\"shapes\",\"draw\")(t),a.getComponentMethod(\"annotations\",\"draw\")(t),a.getComponentMethod(\"images\",\"draw\")(t),e._replotting=!1,i.previousPromises(t)},r.redrawReglTraces=function(t){var e=t._fullLayout;if(e._has(\"regl\")){var r,n,a=t._fullData,i=[],s=[];for(e._hasOnlyLargeSploms&&e._splomGrid.draw(),r=0;r<a.length;r++){var l=a[r];!0===l.visible&&0!==l._length&&(\"splom\"===l.type?e._splomScenes[l.uid].draw():\"scattergl\"===l.type?o.pushUnique(i,l.xaxis+l.yaxis):\"scatterpolargl\"===l.type&&o.pushUnique(s,l.subplot))}for(r=0;r<i.length;r++)(n=e._plots[i[r]])._scene&&n._scene.draw();for(r=0;r<s.length;r++)(n=e[s[r]]._subplot)._scene&&n._scene.draw()}},r.doAutoRangeAndConstraints=function(t){for(var e,r,n=t._fullLayout,a=f.list(t,\"\",!0),i=n._axisMatchGroups||[],s={},l=0;l<a.length;l++)e=a[l],v(t,e),m(t,e),s[e._id]=1;g(t);t:for(var c=0;c<i.length;c++){var u,h=i[c],p=null;for(u in h)if(s[(e=f.getFromId(t,u))._id]){if(!1===e.autorange)continue t;r=o.simpleMap(e.range,e.r2l),p?p[0]<p[1]?(p[0]=Math.min(p[0],r[0]),p[1]=Math.max(p[1],r[1])):(p[0]=Math.max(p[0],r[0]),p[1]=Math.min(p[1],r[1])):p=r}for(u in h)(e=f.getFromId(t,u)).range=o.simpleMap(p,e.l2r),e._input.range=e.range.slice(),e.setScale()}},r.finalDraw=function(t){a.getComponentMethod(\"rangeslider\",\"draw\")(t),a.getComponentMethod(\"rangeselector\",\"draw\")(t)},r.drawMarginPushers=function(t){a.getComponentMethod(\"legend\",\"draw\")(t),a.getComponentMethod(\"rangeselector\",\"draw\")(t),a.getComponentMethod(\"sliders\",\"draw\")(t),a.getComponentMethod(\"updatemenus\",\"draw\")(t),a.getComponentMethod(\"colorbar\",\"draw\")(t)}},{\"../components/color\":592,\"../components/drawing\":613,\"../components/modebar\":650,\"../components/titles\":679,\"../constants/alignment\":686,\"../lib\":717,\"../lib/clear_gl_canvases\":702,\"../plots/cartesian/autorange\":764,\"../plots/cartesian/axes\":765,\"../plots/cartesian/constraints\":772,\"../plots/plots\":826,\"../registry\":846,d3:165}],757:[function(t,e,r){\"use strict\";var n=t(\"../lib\"),a=n.isPlainObject,i=t(\"./plot_schema\"),o=t(\"../plots/plots\"),s=t(\"../plots/attributes\"),l=t(\"./plot_template\"),c=t(\"./plot_config\").dfltConfig;function u(t,e){t=n.extendDeep({},t);var r,i,o=Object.keys(t).sort();function s(e,r,n){if(a(r)&&a(e))u(e,r);else if(Array.isArray(r)&&Array.isArray(e)){var o=l.arrayTemplater({_template:t},n);for(i=0;i<r.length;i++){var s=r[i],c=o.newItem(s)._template;c&&u(c,s)}var h=o.defaultItems();for(i=0;i<h.length;i++)r.push(h[i]._template);for(i=0;i<r.length;i++)delete r[i].templateitemname}}for(r=0;r<o.length;r++){var c=o[r],f=t[c];if(c in e?s(f,e[c],c):e[c]=f,h(c)===c)for(var p in e){var d=h(p);p===d||d!==c||p in t||s(f,e[p],c)}}}function h(t){return t.replace(/[0-9]+$/,\"\")}function f(t,e,r,i,o){var s=o&&r(o);for(var c in t){var u=t[c],d=p(t,c,i),g=p(t,c,o),v=r(g);if(!v){var m=h(c);m!==c&&(v=r(g=p(t,m,o)))}if((!s||s!==v)&&!(!v||v._noTemplating||\"data_array\"===v.valType||v.arrayOk&&Array.isArray(u)))if(!v.valType&&a(u))f(u,e,r,d,g);else if(v._isLinkedToArray&&Array.isArray(u))for(var y=!1,x=0,b={},_=0;_<u.length;_++){var w=u[_];if(a(w)){var k=w.name;if(k)b[k]||(f(w,e,r,p(u,x,d),p(u,x,g)),x++,b[k]=1);else if(!y){var T=p(t,l.arrayDefaultKey(c),i),M=p(u,x,d);f(w,e,r,M,p(u,x,g));var A=n.nestedProperty(e,M);n.nestedProperty(e,T).set(A.get()),A.set(null),y=!0}}}else{n.nestedProperty(e,d).set(u)}}}function p(t,e,r){return r?Array.isArray(t)?r+\"[\"+e+\"]\":r+\".\"+e:e}function d(t){for(var e=0;e<t.length;e++)if(a(t[e]))return!0}function g(t){var e;switch(t.code){case\"data\":e=\"The template has no key data.\";break;case\"layout\":e=\"The template has no key layout.\";break;case\"missing\":e=t.path?\"There are no templates for item \"+t.path+\" with name \"+t.templateitemname:\"There are no templates for trace \"+t.index+\", of type \"+t.traceType+\".\";break;case\"unused\":e=t.path?\"The template item at \"+t.path+\" was not used in constructing the plot.\":t.dataCount?\"Some of the templates of type \"+t.traceType+\" were not used. The template has \"+t.templateCount+\" traces, the data only has \"+t.dataCount+\" of this type.\":\"The template has \"+t.templateCount+\" traces of type \"+t.traceType+\" but there are none in the data.\";break;case\"reused\":e=\"Some of the templates of type \"+t.traceType+\" were used more than once. The template has \"+t.templateCount+\" traces, the data has \"+t.dataCount+\" of this type.\"}return t.msg=e,t}r.makeTemplate=function(t){t=n.isPlainObject(t)?t:n.getGraphDiv(t),t=n.extendDeep({_context:c},{data:t.data,layout:t.layout}),o.supplyDefaults(t);var e=t.data||[],r=t.layout||{};r._basePlotModules=t._fullLayout._basePlotModules,r._modules=t._fullLayout._modules;var l={data:{},layout:{}};e.forEach(function(t){var e={};f(t,e,function(t,e){return i.getTraceValObject(t,n.nestedProperty({},e).parts)}.bind(null,t));var r=n.coerce(t,{},s,\"type\"),a=l.data[r];a||(a=l.data[r]=[]),a.push(e)}),f(r,l.layout,function(t,e){return i.getLayoutValObject(t,n.nestedProperty({},e).parts)}.bind(null,r)),delete l.layout.template;var h=r.template;if(a(h)){var p,d,g,v,m,y,x=h.layout;a(x)&&u(x,l.layout);var b=h.data;if(a(b)){for(d in l.data)if(g=b[d],Array.isArray(g)){for(y=(m=l.data[d]).length,v=g.length,p=0;p<y;p++)u(g[p%v],m[p]);for(p=y;p<v;p++)m.push(n.extendDeep({},g[p]))}for(d in b)d in l.data||(l.data[d]=n.extendDeep([],b[d]))}}return l},r.validateTemplate=function(t,e){var r=n.extendDeep({},{_context:c,data:t.data,layout:t.layout}),i=r.layout||{};a(e)||(e=i.template||{});var s=e.layout,l=e.data,u=[];r.layout=i,r.layout.template=e,o.supplyDefaults(r);var f=r._fullLayout,v=r._fullData,m={};if(a(s)?(!function t(e,r){for(var n in e)if(\"_\"!==n.charAt(0)&&a(e[n])){var i,o=h(n),s=[];for(i=0;i<r.length;i++)s.push(p(e,n,r[i])),o!==n&&s.push(p(e,o,r[i]));for(i=0;i<s.length;i++)m[s[i]]=1;t(e[n],s)}}(f,[\"layout\"]),function t(e,r){for(var n in e)if(-1===n.indexOf(\"defaults\")&&a(e[n])){var i=p(e,n,r);m[i]?t(e[n],i):u.push({code:\"unused\",path:i})}}(s,\"layout\")):u.push({code:\"layout\"}),a(l)){for(var y,x={},b=0;b<v.length;b++){var _=v[b];x[y=_.type]=(x[y]||0)+1,_._fullInput._template||u.push({code:\"missing\",index:_._fullInput.index,traceType:y})}for(y in l){var w=l[y].length,k=x[y]||0;w>k?u.push({code:\"unused\",traceType:y,templateCount:w,dataCount:k}):k>w&&u.push({code:\"reused\",traceType:y,templateCount:w,dataCount:k})}}else u.push({code:\"data\"});if(function t(e,r){for(var n in e)if(\"_\"!==n.charAt(0)){var i=e[n],o=p(e,n,r);a(i)?(Array.isArray(e)&&!1===i._template&&i.templateitemname&&u.push({code:\"missing\",path:o,templateitemname:i.templateitemname}),t(i,o)):Array.isArray(i)&&d(i)&&t(i,o)}}({data:v,layout:f},\"\"),u.length)return u.map(g)}},{\"../lib\":717,\"../plots/attributes\":762,\"../plots/plots\":826,\"./plot_config\":753,\"./plot_schema\":754,\"./plot_template\":755}],758:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"./plot_api\"),i=t(\"../lib\"),o=t(\"../snapshot/helpers\"),s=t(\"../snapshot/tosvg\"),l=t(\"../snapshot/svgtoimg\"),c={format:{valType:\"enumerated\",values:[\"png\",\"jpeg\",\"webp\",\"svg\"],dflt:\"png\"},width:{valType:\"number\",min:1},height:{valType:\"number\",min:1},scale:{valType:\"number\",min:0,dflt:1},setBackground:{valType:\"any\",dflt:!1},imageDataOnly:{valType:\"boolean\",dflt:!1}};e.exports=function(t,e){var r,u,h,f;function p(t){return!(t in e)||i.validate(e[t],c[t])}if(e=e||{},i.isPlainObject(t)?(r=t.data||[],u=t.layout||{},h=t.config||{},f={}):(t=i.getGraphDiv(t),r=i.extendDeep([],t.data),u=i.extendDeep({},t.layout),h=t._context,f=t._fullLayout||{}),!p(\"width\")&&null!==e.width||!p(\"height\")&&null!==e.height)throw new Error(\"Height and width should be pixel values.\");if(!p(\"format\"))throw new Error(\"Image format is not jpeg, png, svg or webp.\");var d={};function g(t,r){return i.coerce(e,d,c,t,r)}var v=g(\"format\"),m=g(\"width\"),y=g(\"height\"),x=g(\"scale\"),b=g(\"setBackground\"),_=g(\"imageDataOnly\"),w=document.createElement(\"div\");w.style.position=\"absolute\",w.style.left=\"-5000px\",document.body.appendChild(w);var k=i.extendFlat({},u);m?k.width=m:null===e.width&&n(f.width)&&(k.width=f.width),y?k.height=y:null===e.height&&n(f.height)&&(k.height=f.height);var T=i.extendFlat({},h,{_exportedPlot:!0,staticPlot:!0,setBackground:b}),M=o.getRedrawFunc(w);function A(){return new Promise(function(t){setTimeout(t,o.getDelay(w._fullLayout))})}function S(){return new Promise(function(t,e){var r=s(w,v,x),n=w._fullLayout.width,c=w._fullLayout.height;if(a.purge(w),document.body.removeChild(w),\"svg\"===v)return t(_?r:o.encodeSVG(r));var u=document.createElement(\"canvas\");u.id=i.randstr(),l({format:v,width:n,height:c,scale:x,canvas:u,svg:r,promise:!0}).then(t).catch(e)})}return new Promise(function(t,e){a.plot(w,r,k,T).then(M).then(A).then(S).then(function(e){t(function(t){return _?t.replace(o.IMAGE_URL_PREFIX,\"\"):t}(e))}).catch(function(t){e(t)})})}},{\"../lib\":717,\"../snapshot/helpers\":850,\"../snapshot/svgtoimg\":852,\"../snapshot/tosvg\":854,\"./plot_api\":752,\"fast-isnumeric\":228}],759:[function(t,e,r){\"use strict\";var n=t(\"../lib\"),a=t(\"../plots/plots\"),i=t(\"./plot_schema\"),o=t(\"./plot_config\").dfltConfig,s=n.isPlainObject,l=Array.isArray,c=n.isArrayOrTypedArray;function u(t,e,r,a,i,o){o=o||[];for(var h=Object.keys(t),f=0;f<h.length;f++){var v=h[f];if(\"transforms\"!==v){var m=o.slice();m.push(v);var y=t[v],x=e[v],b=g(r,v),_=(b||{}).valType,w=\"info_array\"===_,k=\"colorscale\"===_,T=(b||{}).items;if(d(r,v))if(s(y)&&s(x)&&\"any\"!==_)u(y,x,b,a,i,m);else if(w&&l(y)){y.length>x.length&&a.push(p(\"unused\",i,m.concat(x.length)));var M,A,S,E,L,C=x.length,P=Array.isArray(T);if(P&&(C=Math.min(C,T.length)),2===b.dimensions)for(A=0;A<C;A++)if(l(y[A])){y[A].length>x[A].length&&a.push(p(\"unused\",i,m.concat(A,x[A].length)));var O=x[A].length;for(M=0;M<(P?Math.min(O,T[A].length):O);M++)S=P?T[A][M]:T,E=y[A][M],L=x[A][M],n.validate(E,S)?L!==E&&L!==+E&&a.push(p(\"dynamic\",i,m.concat(A,M),E,L)):a.push(p(\"value\",i,m.concat(A,M),E))}else a.push(p(\"array\",i,m.concat(A),y[A]));else for(A=0;A<C;A++)S=P?T[A]:T,E=y[A],L=x[A],n.validate(E,S)?L!==E&&L!==+E&&a.push(p(\"dynamic\",i,m.concat(A),E,L)):a.push(p(\"value\",i,m.concat(A),E))}else if(b.items&&!w&&l(y)){var z,I,D=T[Object.keys(T)[0]],R=[];for(z=0;z<x.length;z++){var F=x[z]._index||z;if((I=m.slice()).push(F),s(y[F])&&s(x[z])){R.push(F);var B=y[F],N=x[z];s(B)&&!1!==B.visible&&!1===N.visible?a.push(p(\"invisible\",i,I)):u(B,N,D,a,i,I)}}for(z=0;z<y.length;z++)(I=m.slice()).push(z),s(y[z])?-1===R.indexOf(z)&&a.push(p(\"unused\",i,I)):a.push(p(\"object\",i,I,y[z]))}else!s(y)&&s(x)?a.push(p(\"object\",i,m,y)):c(y)||!c(x)||w||k?v in e?n.validate(y,b)?\"enumerated\"===b.valType&&(b.coerceNumber&&y!==+x||y!==x)&&a.push(p(\"dynamic\",i,m,y,x)):a.push(p(\"value\",i,m,y)):a.push(p(\"unused\",i,m,y)):a.push(p(\"array\",i,m,y));else a.push(p(\"schema\",i,m))}}return a}e.exports=function(t,e){var r,c,h=i.get(),f=[],d={_context:n.extendFlat({},o)};l(t)?(d.data=n.extendDeep([],t),r=t):(d.data=[],r=[],f.push(p(\"array\",\"data\"))),s(e)?(d.layout=n.extendDeep({},e),c=e):(d.layout={},c={},arguments.length>1&&f.push(p(\"object\",\"layout\"))),a.supplyDefaults(d);for(var g=d._fullData,v=r.length,m=0;m<v;m++){var y=r[m],x=[\"data\",m];if(s(y)){var b=g[m],_=b.type,w=h.traces[_].attributes;w.type={valType:\"enumerated\",values:[_]},!1===b.visible&&!1!==y.visible&&f.push(p(\"invisible\",x)),u(y,b,w,f,x);var k=y.transforms,T=b.transforms;if(k){l(k)||f.push(p(\"array\",x,[\"transforms\"])),x.push(\"transforms\");for(var M=0;M<k.length;M++){var A=[\"transforms\",M],S=k[M].type;if(s(k[M])){var E=h.transforms[S]?h.transforms[S].attributes:{};E.type={valType:\"enumerated\",values:Object.keys(h.transforms)},u(k[M],T[M],E,f,x,A)}else f.push(p(\"object\",x,A))}}}else f.push(p(\"object\",x))}return u(c,d._fullLayout,function(t,e){for(var r=t.layout.layoutAttributes,a=0;a<e.length;a++){var i=e[a],o=t.traces[i.type],s=o.layoutAttributes;s&&(i.subplot?n.extendFlat(r[o.attributes.subplot.dflt],s):n.extendFlat(r,s))}return r}(h,g),f,\"layout\"),0===f.length?void 0:f};var h={object:function(t,e){return(\"layout\"===t&&\"\"===e?\"The layout argument\":\"data\"===t[0]&&\"\"===e?\"Trace \"+t[1]+\" in the data argument\":f(t)+\"key \"+e)+\" must be linked to an object container\"},array:function(t,e){return(\"data\"===t?\"The data argument\":f(t)+\"key \"+e)+\" must be linked to an array container\"},schema:function(t,e){return f(t)+\"key \"+e+\" is not part of the schema\"},unused:function(t,e,r){var n=s(r)?\"container\":\"key\";return f(t)+n+\" \"+e+\" did not get coerced\"},dynamic:function(t,e,r,n){return[f(t)+\"key\",e,\"(set to '\"+r+\"')\",\"got reset to\",\"'\"+n+\"'\",\"during defaults.\"].join(\" \")},invisible:function(t,e){return(e?f(t)+\"item \"+e:\"Trace \"+t[1])+\" got defaulted to be not visible\"},value:function(t,e,r){return[f(t)+\"key \"+e,\"is set to an invalid value (\"+r+\")\"].join(\" \")}};function f(t){return l(t)?\"In data trace \"+t[1]+\", \":\"In \"+t+\", \"}function p(t,e,r,a,i){var o,s;r=r||\"\",l(e)?(o=e[0],s=e[1]):(o=e,s=null);var c=function(t){if(!l(t))return String(t);for(var e=\"\",r=0;r<t.length;r++){var n=t[r];\"number\"==typeof n?e=e.substr(0,e.length-1)+\"[\"+n+\"]\":e+=n,r<t.length-1&&(e+=\".\")}return e}(r),u=h[t](e,c,a,i);return n.log(u),{code:t,container:o,trace:s,path:r,astr:c,msg:u}}function d(t,e){var r=m(e),n=r.keyMinusId,a=r.id;return!!(n in t&&t[n]._isSubplotObj&&a)||e in t}function g(t,e){return e in t?t[e]:t[m(e).keyMinusId]}var v=n.counterRegex(\"([a-z]+)\");function m(t){var e=t.match(v);return{keyMinusId:e&&e[1],id:e&&e[2]}}},{\"../lib\":717,\"../plots/plots\":826,\"./plot_config\":753,\"./plot_schema\":754}],760:[function(t,e,r){\"use strict\";e.exports={mode:{valType:\"enumerated\",dflt:\"afterall\",values:[\"immediate\",\"next\",\"afterall\"]},direction:{valType:\"enumerated\",values:[\"forward\",\"reverse\"],dflt:\"forward\"},fromcurrent:{valType:\"boolean\",dflt:!1},frame:{duration:{valType:\"number\",min:0,dflt:500},redraw:{valType:\"boolean\",dflt:!0}},transition:{duration:{valType:\"number\",min:0,dflt:500,editType:\"none\"},easing:{valType:\"enumerated\",dflt:\"cubic-in-out\",values:[\"linear\",\"quad\",\"cubic\",\"sin\",\"exp\",\"circle\",\"elastic\",\"back\",\"bounce\",\"linear-in\",\"quad-in\",\"cubic-in\",\"sin-in\",\"exp-in\",\"circle-in\",\"elastic-in\",\"back-in\",\"bounce-in\",\"linear-out\",\"quad-out\",\"cubic-out\",\"sin-out\",\"exp-out\",\"circle-out\",\"elastic-out\",\"back-out\",\"bounce-out\",\"linear-in-out\",\"quad-in-out\",\"cubic-in-out\",\"sin-in-out\",\"exp-in-out\",\"circle-in-out\",\"elastic-in-out\",\"back-in-out\",\"bounce-in-out\"],editType:\"none\"},ordering:{valType:\"enumerated\",values:[\"layout first\",\"traces first\"],dflt:\"layout first\",editType:\"none\"}}}},{}],761:[function(t,e,r){\"use strict\";var n=t(\"../lib\"),a=t(\"../plot_api/plot_template\");e.exports=function(t,e,r){var i,o,s=r.name,l=r.inclusionAttr||\"visible\",c=e[s],u=n.isArrayOrTypedArray(t[s])?t[s]:[],h=e[s]=[],f=a.arrayTemplater(e,s,l);for(i=0;i<u.length;i++){var p=u[i];n.isPlainObject(p)?o=f.newItem(p):(o=f.newItem({}))[l]=!1,o._index=i,!1!==o[l]&&r.handleItemDefaults(p,o,e,r),h.push(o)}var d=f.defaultItems();for(i=0;i<d.length;i++)(o=d[i])._index=h.length,r.handleItemDefaults({},o,e,r,{}),h.push(o);if(n.isArrayOrTypedArray(c)){var g=Math.min(c.length,h.length);for(i=0;i<g;i++)n.relinkPrivateKeys(h[i],c[i])}return h}},{\"../lib\":717,\"../plot_api/plot_template\":755}],762:[function(t,e,r){\"use strict\";var n=t(\"../components/fx/attributes\");e.exports={type:{valType:\"enumerated\",values:[],dflt:\"scatter\",editType:\"calc+clearAxisTypes\",_noTemplating:!0},visible:{valType:\"enumerated\",values:[!0,!1,\"legendonly\"],dflt:!0,editType:\"calc\"},showlegend:{valType:\"boolean\",dflt:!0,editType:\"style\"},legendgroup:{valType:\"string\",dflt:\"\",editType:\"style\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,editType:\"style\"},name:{valType:\"string\",editType:\"style\"},uid:{valType:\"string\",editType:\"plot\",anim:!0},ids:{valType:\"data_array\",editType:\"calc\",anim:!0},customdata:{valType:\"data_array\",editType:\"calc\"},meta:{valType:\"any\",arrayOk:!0,editType:\"plot\"},selectedpoints:{valType:\"any\",editType:\"calc\"},hoverinfo:{valType:\"flaglist\",flags:[\"x\",\"y\",\"z\",\"text\",\"name\"],extras:[\"all\",\"none\",\"skip\"],arrayOk:!0,dflt:\"all\",editType:\"none\"},hoverlabel:n.hoverlabel,stream:{token:{valType:\"string\",noBlank:!0,strict:!0,editType:\"calc\"},maxpoints:{valType:\"number\",min:0,max:1e4,dflt:500,editType:\"calc\"},editType:\"calc\"},transforms:{_isLinkedToArray:\"transform\",editType:\"calc\"},uirevision:{valType:\"any\",editType:\"none\"}}},{\"../components/fx/attributes\":622}],763:[function(t,e,r){\"use strict\";e.exports={xaxis:{valType:\"subplotid\",dflt:\"x\",editType:\"calc+clearAxisTypes\"},yaxis:{valType:\"subplotid\",dflt:\"y\",editType:\"calc+clearAxisTypes\"}}},{}],764:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib\"),i=t(\"../../constants/numerical\").FP_SAFE,o=t(\"../../registry\");function s(t,e){var r,n,i=[],o=l(e),s=c(t,e),u=s.min,h=s.max;if(0===u.length||0===h.length)return a.simpleMap(e.range,e.r2l);var f=u[0].val,p=h[0].val;for(r=1;r<u.length&&f===p;r++)f=Math.min(f,u[r].val);for(r=1;r<h.length&&f===p;r++)p=Math.max(p,h[r].val);var d=!1;if(e.range){var g=a.simpleMap(e.range,e.r2l);d=g[1]<g[0]}\"reversed\"===e.autorange&&(d=!0,e.autorange=!0);var v,m,y,x,b,_,w=e.rangemode,k=\"tozero\"===w,T=\"nonnegative\"===w,M=e._length,A=M/10,S=0;for(r=0;r<u.length;r++)for(v=u[r],n=0;n<h.length;n++)(_=(m=h[n]).val-v.val)>0&&((b=M-o(v)-o(m))>A?_/b>S&&(y=v,x=m,S=_/b):_/M>S&&(y={val:v.val,pad:0},x={val:m.val,pad:0},S=_/M));if(f===p){var E=f-1,L=f+1;if(k)if(0===f)i=[0,1];else{var C=(f>0?h:u).reduce(function(t,e){return Math.max(t,o(e))},0),P=f/(1-Math.min(.5,C/M));i=f>0?[0,P]:[P,0]}else i=T?[Math.max(0,E),Math.max(1,L)]:[E,L]}else k?(y.val>=0&&(y={val:0,pad:0}),x.val<=0&&(x={val:0,pad:0})):T&&(y.val-S*o(y)<0&&(y={val:0,pad:0}),x.val<=0&&(x={val:1,pad:0})),S=(x.val-y.val)/(M-o(y)-o(x)),i=[y.val-S*o(y),x.val+S*o(x)];return d&&i.reverse(),a.simpleMap(i,e.l2r||Number)}function l(t){var e=t._length/20;return\"domain\"===t.constrain&&t._inputDomain&&(e*=(t._inputDomain[1]-t._inputDomain[0])/(t.domain[1]-t.domain[0])),function(t){return t.pad+(t.extrapad?e:0)}}function c(t,e){var r,n,a,i=e._id,o=t._fullData,s=t._fullLayout,l=[],c=[];function f(t,e){for(r=0;r<e.length;r++){var o=t[e[r]],s=(o._extremes||{})[i];if(!0===o.visible&&s){for(n=0;n<s.min.length;n++)a=s.min[n],u(l,a.val,a.pad,{extrapad:a.extrapad});for(n=0;n<s.max.length;n++)a=s.max[n],h(c,a.val,a.pad,{extrapad:a.extrapad})}}}return f(o,e._traceIndices),f(s.annotations||[],e._annIndices||[]),f(s.shapes||[],e._shapeIndices||[]),{min:l,max:c}}function u(t,e,r,n){f(t,e,r,n,d)}function h(t,e,r,n){f(t,e,r,n,g)}function f(t,e,r,n,a){for(var i=n.tozero,o=n.extrapad,s=!0,l=0;l<t.length&&s;l++){var c=t[l];if(a(c.val,e)&&c.pad>=r&&(c.extrapad||!o)){s=!1;break}a(e,c.val)&&c.pad<=r&&(o||!c.extrapad)&&(t.splice(l,1),l--)}if(s){var u=i&&0===e;t.push({val:e,pad:u?0:r,extrapad:!u&&o})}}function p(t){return n(t)&&Math.abs(t)<i}function d(t,e){return t<=e}function g(t,e){return t>=e}e.exports={getAutoRange:s,makePadFn:l,doAutoRange:function(t,e){if(e.setScale(),e.autorange){e.range=s(t,e),e._r=e.range.slice(),e._rl=a.simpleMap(e._r,e.r2l);var r=e._input,n={};n[e._attr+\".range\"]=e.range,n[e._attr+\".autorange\"]=e.autorange,o.call(\"_storeDirectGUIEdit\",t.layout,t._fullLayout._preGUI,n),r.range=e.range.slice(),r.autorange=e.autorange}var i=e._anchorAxis;if(i&&i.rangeslider){var l=i.rangeslider[e._name];l&&\"auto\"===l.rangemode&&(l.range=s(t,e)),i._input.rangeslider[e._name]=a.extendFlat({},l)}},findExtremes:function(t,e,r){r||(r={});t._m||t.setScale();var a,o,s,l,c,f,d,g,v,m=[],y=[],x=e.length,b=r.padded||!1,_=r.tozero&&(\"linear\"===t.type||\"-\"===t.type),w=\"log\"===t.type,k=!1,T=r.vpadLinearized||!1;function M(t){if(Array.isArray(t))return k=!0,function(e){return Math.max(Number(t[e]||0),0)};var e=Math.max(Number(t||0),0);return function(){return e}}var A=M((t._m>0?r.ppadplus:r.ppadminus)||r.ppad||0),S=M((t._m>0?r.ppadminus:r.ppadplus)||r.ppad||0),E=M(r.vpadplus||r.vpad),L=M(r.vpadminus||r.vpad);if(!k){if(g=1/0,v=-1/0,w)for(a=0;a<x;a++)(o=e[a])<g&&o>0&&(g=o),o>v&&o<i&&(v=o);else for(a=0;a<x;a++)(o=e[a])<g&&o>-i&&(g=o),o>v&&o<i&&(v=o);e=[g,v],x=2}var C={tozero:_,extrapad:b};function P(r){s=e[r],n(s)&&(f=A(r),d=S(r),T?(l=t.c2l(s)-L(r),c=t.c2l(s)+E(r)):(g=s-L(r),v=s+E(r),w&&g<v/10&&(g=v/10),l=t.c2l(g),c=t.c2l(v)),_&&(l=Math.min(0,l),c=Math.max(0,c)),p(l)&&u(m,l,d,C),p(c)&&h(y,c,f,C))}var O=Math.min(6,x);for(a=0;a<O;a++)P(a);for(a=x-1;a>=O;a--)P(a);return{min:m,max:y,opts:r}},concatExtremes:c}},{\"../../constants/numerical\":693,\"../../lib\":717,\"../../registry\":846,\"fast-isnumeric\":228}],765:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"fast-isnumeric\"),i=t(\"../../plots/plots\"),o=t(\"../../registry\"),s=t(\"../../lib\"),l=t(\"../../lib/svg_text_utils\"),c=t(\"../../components/titles\"),u=t(\"../../components/color\"),h=t(\"../../components/drawing\"),f=t(\"./layout_attributes\"),p=t(\"./clean_ticks\"),d=t(\"../../constants/numerical\"),g=d.ONEAVGYEAR,v=d.ONEAVGMONTH,m=d.ONEDAY,y=d.ONEHOUR,x=d.ONEMIN,b=d.ONESEC,_=d.MINUS_SIGN,w=d.BADNUM,k=t(\"../../constants/alignment\"),T=k.MID_SHIFT,M=k.CAP_SHIFT,A=k.LINE_SPACING,S=k.OPPOSITE_SIDE,E=e.exports={};E.setConvert=t(\"./set_convert\");var L=t(\"./axis_autotype\"),C=t(\"./axis_ids\");E.id2name=C.id2name,E.name2id=C.name2id,E.cleanId=C.cleanId,E.list=C.list,E.listIds=C.listIds,E.getFromId=C.getFromId,E.getFromTrace=C.getFromTrace;var P=t(\"./autorange\");E.getAutoRange=P.getAutoRange,E.findExtremes=P.findExtremes,E.coerceRef=function(t,e,r,n,a,i){var o=n.charAt(n.length-1),l=r._fullLayout._subplots[o+\"axis\"],c=n+\"ref\",u={};return a||(a=l[0]||i),i||(i=a),u[c]={valType:\"enumerated\",values:l.concat(i?[i]:[]),dflt:a},s.coerce(t,e,u,c)},E.coercePosition=function(t,e,r,n,a,i){var o,l;if(\"paper\"===n||\"pixel\"===n)o=s.ensureNumber,l=r(a,i);else{var c=E.getFromId(e,n);l=r(a,i=c.fraction2r(i)),o=c.cleanPos}t[a]=o(l)},E.cleanPosition=function(t,e,r){return(\"paper\"===r||\"pixel\"===r?s.ensureNumber:E.getFromId(e,r).cleanPos)(t)},E.redrawComponents=function(t,e){e=e||E.listIds(t);var r=t._fullLayout;function n(n,a,i,s){for(var l=o.getComponentMethod(n,a),c={},u=0;u<e.length;u++)for(var h=r[E.id2name(e[u])][i],f=0;f<h.length;f++){var p=h[f];if(!c[p]&&(l(t,p),c[p]=1,s))return}}n(\"annotations\",\"drawOne\",\"_annIndices\"),n(\"shapes\",\"drawOne\",\"_shapeIndices\"),n(\"images\",\"draw\",\"_imgIndices\",!0)};var O=E.getDataConversions=function(t,e,r,n){var a,i=\"x\"===r||\"y\"===r||\"z\"===r?r:n;if(Array.isArray(i)){if(a={type:L(n),_categories:[]},E.setConvert(a),\"category\"===a.type)for(var o=0;o<n.length;o++)a.d2c(n[o])}else a=E.getFromTrace(t,e,i);return a?{d2c:a.d2c,c2d:a.c2d}:\"ids\"===i?{d2c:I,c2d:I}:{d2c:z,c2d:z}};function z(t){return+t}function I(t){return String(t)}E.getDataToCoordFunc=function(t,e,r,n){return O(t,e,r,n).d2c},E.counterLetter=function(t){var e=t.charAt(0);return\"x\"===e?\"y\":\"y\"===e?\"x\":void 0},E.minDtick=function(t,e,r,n){-1===[\"log\",\"category\",\"multicategory\"].indexOf(t.type)&&n?void 0===t._minDtick?(t._minDtick=e,t._forceTick0=r):t._minDtick&&((t._minDtick/e+1e-6)%1<2e-6&&((r-t._forceTick0)/e%1+1.000001)%1<2e-6?(t._minDtick=e,t._forceTick0=r):((e/t._minDtick+1e-6)%1>2e-6||((r-t._forceTick0)/t._minDtick%1+1.000001)%1>2e-6)&&(t._minDtick=0)):t._minDtick=0},E.saveRangeInitial=function(t,e){for(var r=E.list(t,\"\",!0),n=!1,a=0;a<r.length;a++){var i=r[a],o=void 0===i._rangeInitial,s=o||!(i.range[0]===i._rangeInitial[0]&&i.range[1]===i._rangeInitial[1]);(o&&!1===i.autorange||e&&s)&&(i._rangeInitial=i.range.slice(),n=!0)}return n},E.saveShowSpikeInitial=function(t,e){for(var r=E.list(t,\"\",!0),n=!1,a=\"on\",i=0;i<r.length;i++){var o=r[i],s=void 0===o._showSpikeInitial,l=s||!(o.showspikes===o._showspikes);(s||e&&l)&&(o._showSpikeInitial=o.showspikes,n=!0),\"on\"!==a||o.showspikes||(a=\"off\")}return t._fullLayout._cartesianSpikesEnabled=a,n},E.autoBin=function(t,e,r,n,i,o){var l,c=s.aggNums(Math.min,null,t),u=s.aggNums(Math.max,null,t);if(\"category\"===e.type||\"multicategory\"===e.type)return{start:c-.5,end:u+.5,size:Math.max(1,Math.round(o)||1),_dataSpan:u-c};if(i||(i=e.calendar),l=\"log\"===e.type?{type:\"linear\",range:[c,u]}:{type:e.type,range:s.simpleMap([c,u],e.c2r,0,i),calendar:i},E.setConvert(l),o=o&&p.dtick(o,l.type))l.dtick=o,l.tick0=p.tick0(void 0,l.type,i);else{var h;if(r)h=(u-c)/r;else{var f=s.distinctVals(t),d=Math.pow(10,Math.floor(Math.log(f.minDiff)/Math.LN10)),g=d*s.roundUp(f.minDiff/d,[.9,1.9,4.9,9.9],!0);h=Math.max(g,2*s.stdev(t)/Math.pow(t.length,n?.25:.4)),a(h)||(h=1)}E.autoTicks(l,h)}var v,y=l.dtick,x=E.tickIncrement(E.tickFirst(l),y,\"reverse\",i);if(\"number\"==typeof y)v=(x=function(t,e,r,n,i){var o=0,s=0,l=0,c=0;function u(e){return(1+100*(e-t)/r.dtick)%100<2}for(var h=0;h<e.length;h++)e[h]%1==0?l++:a(e[h])||c++,u(e[h])&&o++,u(e[h]+r.dtick/2)&&s++;var f=e.length-c;if(l===f&&\"date\"!==r.type)r.dtick<1?t=n-.5*r.dtick:(t-=.5)+r.dtick<n&&(t+=r.dtick);else if(s<.1*f&&(o>.3*f||u(n)||u(i))){var p=r.dtick/2;t+=t+p<n?p:-p}return t}(x,t,l,c,u))+(1+Math.floor((u-x)/y))*y;else for(\"M\"===l.dtick.charAt(0)&&(x=function(t,e,r,n,a){var i=s.findExactDates(e,a);if(i.exactDays>.8){var o=Number(r.substr(1));i.exactYears>.8&&o%12==0?t=E.tickIncrement(t,\"M6\",\"reverse\")+1.5*m:i.exactMonths>.8?t=E.tickIncrement(t,\"M1\",\"reverse\")+15.5*m:t-=m/2;var l=E.tickIncrement(t,r);if(l<=n)return l}return t}(x,t,y,c,i)),v=x,0;v<=u;)v=E.tickIncrement(v,y,!1,i),0;return{start:e.c2r(x,0,i),end:e.c2r(v,0,i),size:y,_dataSpan:u-c}},E.prepTicks=function(t){var e=s.simpleMap(t.range,t.r2l);if(\"auto\"===t.tickmode||!t.dtick){var r,n=t.nticks;n||(\"category\"===t.type||\"multicategory\"===t.type?(r=t.tickfont?1.2*(t.tickfont.size||12):15,n=t._length/r):(r=\"y\"===t._id.charAt(0)?40:80,n=s.constrain(t._length/r,4,9)+1),\"radialaxis\"===t._name&&(n*=2)),\"array\"===t.tickmode&&(n*=100),E.autoTicks(t,Math.abs(e[1]-e[0])/n),t._minDtick>0&&t.dtick<2*t._minDtick&&(t.dtick=t._minDtick,t.tick0=t.l2r(t._forceTick0))}t.tick0||(t.tick0=\"date\"===t.type?\"2000-01-01\":0),\"date\"===t.type&&t.dtick<.1&&(t.dtick=.1),q(t)},E.calcTicks=function(t){E.prepTicks(t);var e=s.simpleMap(t.range,t.r2l);if(\"array\"===t.tickmode)return function(t){var e=t.tickvals,r=t.ticktext,n=new Array(e.length),a=s.simpleMap(t.range,t.r2l),i=1.0001*a[0]-1e-4*a[1],o=1.0001*a[1]-1e-4*a[0],l=Math.min(i,o),c=Math.max(i,o),u=0;Array.isArray(r)||(r=[]);var h=\"category\"===t.type?t.d2l_noadd:t.d2l;\"log\"===t.type&&\"L\"!==String(t.dtick).charAt(0)&&(t.dtick=\"L\"+Math.pow(10,Math.floor(Math.min(t.range[0],t.range[1]))-1));for(var f=0;f<e.length;f++){var p=h(e[f]);p>l&&p<c&&(void 0===r[f]?n[u]=E.tickText(t,p):n[u]=H(t,p,String(r[f])),u++)}u<e.length&&n.splice(u,e.length-u);return n}(t);t._tmin=E.tickFirst(t);var r=1.0001*e[0]-1e-4*e[1],n=1.0001*e[1]-1e-4*e[0],i=e[1]<e[0];if(t._tmin<r!==i)return[];var o=[];\"category\"!==t.type&&\"multicategory\"!==t.type||(n=i?Math.max(-.5,n):Math.min(t._categories.length-.5,n));for(var l=\"log\"===t.type&&!(a(t.dtick)||\"L\"===t.dtick.charAt(0)),c=null,u=Math.max(1e3,t._length||0),h=t._tmin;(i?h>=n:h<=n)&&!(o.length>u||h===c);h=E.tickIncrement(h,t.dtick,i,t.calendar)){c=h;var f=!1;l&&h!==(0|h)&&(f=!0),o.push({minor:f,value:h})}ot(t)&&360===Math.abs(e[1]-e[0])&&o.pop(),t._tmax=(o[o.length-1]||{}).value,t._prevDateHead=\"\",t._inCalcTicks=!0;for(var p=new Array(o.length),d=0;d<o.length;d++)p[d]=E.tickText(t,o[d].value,!1,o[d].minor);return t._inCalcTicks=!1,p};var D=[2,5,10],R=[1,2,3,6,12],F=[1,2,5,10,15,30],B=[1,2,3,7,14],N=[-.046,0,.301,.477,.602,.699,.778,.845,.903,.954,1],j=[-.301,0,.301,.699,1],V=[15,30,45,90,180];function U(t,e,r){return e*s.roundUp(t/e,r)}function q(t){var e=t.dtick;if(t._tickexponent=0,a(e)||\"string\"==typeof e||(e=1),\"category\"!==t.type&&\"multicategory\"!==t.type||(t._tickround=null),\"date\"===t.type){var r=t.r2l(t.tick0),n=t.l2r(r).replace(/(^-|i)/g,\"\"),i=n.length;if(\"M\"===String(e).charAt(0))i>10||\"01-01\"!==n.substr(5)?t._tickround=\"d\":t._tickround=+e.substr(1)%12==0?\"y\":\"m\";else if(e>=m&&i<=10||e>=15*m)t._tickround=\"d\";else if(e>=x&&i<=16||e>=y)t._tickround=\"M\";else if(e>=b&&i<=19||e>=x)t._tickround=\"S\";else{var o=t.l2r(r+e).replace(/^-/,\"\").length;t._tickround=Math.max(i,o)-20,t._tickround<0&&(t._tickround=4)}}else if(a(e)||\"L\"===e.charAt(0)){var s=t.range.map(t.r2d||Number);a(e)||(e=Number(e.substr(1))),t._tickround=2-Math.floor(Math.log(e)/Math.LN10+.01);var l=Math.max(Math.abs(s[0]),Math.abs(s[1])),c=Math.floor(Math.log(l)/Math.LN10+.01);Math.abs(c)>3&&(Y(t.exponentformat)&&!W(c)?t._tickexponent=3*Math.round((c-1)/3):t._tickexponent=c)}else t._tickround=null}function H(t,e,r){var n=t.tickfont||{};return{x:e,dx:0,dy:0,text:r||\"\",fontSize:n.size,font:n.family,fontColor:n.color}}E.autoTicks=function(t,e){var r;function n(t){return Math.pow(t,Math.floor(Math.log(e)/Math.LN10))}if(\"date\"===t.type){t.tick0=s.dateTick0(t.calendar);var i=2*e;i>g?(e/=g,r=n(10),t.dtick=\"M\"+12*U(e,r,D)):i>v?(e/=v,t.dtick=\"M\"+U(e,1,R)):i>m?(t.dtick=U(e,m,B),t.tick0=s.dateTick0(t.calendar,!0)):i>y?t.dtick=U(e,y,R):i>x?t.dtick=U(e,x,F):i>b?t.dtick=U(e,b,F):(r=n(10),t.dtick=U(e,r,D))}else if(\"log\"===t.type){t.tick0=0;var o=s.simpleMap(t.range,t.r2l);if(e>.7)t.dtick=Math.ceil(e);else if(Math.abs(o[1]-o[0])<1){var l=1.5*Math.abs((o[1]-o[0])/e);e=Math.abs(Math.pow(10,o[1])-Math.pow(10,o[0]))/l,r=n(10),t.dtick=\"L\"+U(e,r,D)}else t.dtick=e>.3?\"D2\":\"D1\"}else\"category\"===t.type||\"multicategory\"===t.type?(t.tick0=0,t.dtick=Math.ceil(Math.max(e,1))):ot(t)?(t.tick0=0,r=1,t.dtick=U(e,r,V)):(t.tick0=0,r=n(10),t.dtick=U(e,r,D));if(0===t.dtick&&(t.dtick=1),!a(t.dtick)&&\"string\"!=typeof t.dtick){var c=t.dtick;throw t.dtick=1,\"ax.dtick error: \"+String(c)}},E.tickIncrement=function(t,e,r,i){var o=r?-1:1;if(a(e))return t+o*e;var l=e.charAt(0),c=o*Number(e.substr(1));if(\"M\"===l)return s.incrementMonth(t,c,i);if(\"L\"===l)return Math.log(Math.pow(10,t)+c)/Math.LN10;if(\"D\"===l){var u=\"D2\"===e?j:N,h=t+.01*o,f=s.roundUp(s.mod(h,1),u,r);return Math.floor(h)+Math.log(n.round(Math.pow(10,f),1))/Math.LN10}throw\"unrecognized dtick \"+String(e)},E.tickFirst=function(t){var e=t.r2l||Number,r=s.simpleMap(t.range,e),i=r[1]<r[0],o=i?Math.floor:Math.ceil,l=1.0001*r[0]-1e-4*r[1],c=t.dtick,u=e(t.tick0);if(a(c)){var h=o((l-u)/c)*c+u;return\"category\"!==t.type&&\"multicategory\"!==t.type||(h=s.constrain(h,0,t._categories.length-1)),h}var f=c.charAt(0),p=Number(c.substr(1));if(\"M\"===f){for(var d,g,v,m=0,y=u;m<10;){if(((d=E.tickIncrement(y,c,i,t.calendar))-l)*(y-l)<=0)return i?Math.min(y,d):Math.max(y,d);g=(l-(y+d)/2)/(d-y),v=f+(Math.abs(Math.round(g))||1)*p,y=E.tickIncrement(y,v,g<0?!i:i,t.calendar),m++}return s.error(\"tickFirst did not converge\",t),y}if(\"L\"===f)return Math.log(o((Math.pow(10,l)-u)/p)*p+u)/Math.LN10;if(\"D\"===f){var x=\"D2\"===c?j:N,b=s.roundUp(s.mod(l,1),x,i);return Math.floor(l)+Math.log(n.round(Math.pow(10,b),1))/Math.LN10}throw\"unrecognized dtick \"+String(c)},E.tickText=function(t,e,r,n){var i,o=H(t,e),l=\"array\"===t.tickmode,c=r||l,u=t.type,h=\"category\"===u?t.d2l_noadd:t.d2l;if(l&&Array.isArray(t.ticktext)){var f=s.simpleMap(t.range,t.r2l),p=Math.abs(f[1]-f[0])/1e4;for(i=0;i<t.ticktext.length&&!(Math.abs(e-h(t.tickvals[i]))<p);i++);if(i<t.ticktext.length)return o.text=String(t.ticktext[i]),o}function d(n){if(void 0===n)return!0;if(r)return\"none\"===n;var a={first:t._tmin,last:t._tmax}[n];return\"all\"!==n&&e!==a}var g=r?\"never\":\"none\"!==t.exponentformat&&d(t.showexponent)?\"hide\":\"\";if(\"date\"===u?function(t,e,r,n){var i=t._tickround,o=r&&t.hoverformat||E.getTickFormat(t);n&&(i=a(i)?4:{y:\"m\",m:\"d\",d:\"M\",M:\"S\",S:4}[i]);var l,c=s.formatDate(e.x,o,i,t._dateFormat,t.calendar,t._extraFormat),u=c.indexOf(\"\\n\");-1!==u&&(l=c.substr(u+1),c=c.substr(0,u));n&&(\"00:00:00\"===c||\"00:00\"===c?(c=l,l=\"\"):8===c.length&&(c=c.replace(/:00$/,\"\")));l&&(r?\"d\"===i?c+=\", \"+l:c=l+(c?\", \"+c:\"\"):t._inCalcTicks&&l===t._prevDateHead||(c+=\"<br>\"+l,t._prevDateHead=l));e.text=c}(t,o,r,c):\"log\"===u?function(t,e,r,n,i){var o=t.dtick,l=e.x,c=t.tickformat,u=\"string\"==typeof o&&o.charAt(0);\"never\"===i&&(i=\"\");n&&\"L\"!==u&&(o=\"L3\",u=\"L\");if(c||\"L\"===u)e.text=X(Math.pow(10,l),t,i,n);else if(a(o)||\"D\"===u&&s.mod(l+.01,1)<.1){var h=Math.round(l),f=Math.abs(h),p=t.exponentformat;\"power\"===p||Y(p)&&W(h)?(e.text=0===h?1:1===h?\"10\":\"10<sup>\"+(h>1?\"\":_)+f+\"</sup>\",e.fontSize*=1.25):(\"e\"===p||\"E\"===p)&&f>2?e.text=\"1\"+p+(h>0?\"+\":_)+f:(e.text=X(Math.pow(10,l),t,\"\",\"fakehover\"),\"D1\"===o&&\"y\"===t._id.charAt(0)&&(e.dy-=e.fontSize/6))}else{if(\"D\"!==u)throw\"unrecognized dtick \"+String(o);e.text=String(Math.round(Math.pow(10,s.mod(l,1)))),e.fontSize*=.75}if(\"D1\"===t.dtick){var d=String(e.text).charAt(0);\"0\"!==d&&\"1\"!==d||(\"y\"===t._id.charAt(0)?e.dx-=e.fontSize/4:(e.dy+=e.fontSize/2,e.dx+=(t.range[1]>t.range[0]?1:-1)*e.fontSize*(l<0?.5:.25)))}}(t,o,0,c,g):\"category\"===u?function(t,e){var r=t._categories[Math.round(e.x)];void 0===r&&(r=\"\");e.text=String(r)}(t,o):\"multicategory\"===u?function(t,e,r){var n=Math.round(e.x),a=t._categories[n]||[],i=void 0===a[1]?\"\":String(a[1]),o=void 0===a[0]?\"\":String(a[0]);r?e.text=o+\" - \"+i:(e.text=i,e.text2=o)}(t,o,r):ot(t)?function(t,e,r,n,a){if(\"radians\"!==t.thetaunit||r)e.text=X(e.x,t,a,n);else{var i=e.x/180;if(0===i)e.text=\"0\";else{var o=function(t){function e(t,e){return Math.abs(t-e)<=1e-6}var r=function(t){var r=1;for(;!e(Math.round(t*r)/r,t);)r*=10;return r}(t),n=t*r,a=Math.abs(function t(r,n){return e(n,0)?r:t(n,r%n)}(n,r));return[Math.round(n/a),Math.round(r/a)]}(i);if(o[1]>=100)e.text=X(s.deg2rad(e.x),t,a,n);else{var l=e.x<0;1===o[1]?1===o[0]?e.text=\"\\u03c0\":e.text=o[0]+\"\\u03c0\":e.text=[\"<sup>\",o[0],\"</sup>\",\"\\u2044\",\"<sub>\",o[1],\"</sub>\",\"\\u03c0\"].join(\"\"),l&&(e.text=_+e.text)}}}}(t,o,r,c,g):function(t,e,r,n,a){\"never\"===a?a=\"\":\"all\"===t.showexponent&&Math.abs(e.x/t.dtick)<1e-6&&(a=\"hide\");e.text=X(e.x,t,a,n)}(t,o,0,c,g),n||(t.tickprefix&&!d(t.showtickprefix)&&(o.text=t.tickprefix+o.text),t.ticksuffix&&!d(t.showticksuffix)&&(o.text+=t.ticksuffix)),\"boundaries\"===t.tickson||t.showdividers){var v=function(e){var r=t.l2p(e);return r>=0&&r<=t._length?e:null};o.xbnd=[v(o.x-.5),v(o.x+t.dtick-.5)]}return o},E.hoverLabelText=function(t,e,r){if(r!==w&&r!==e)return E.hoverLabelText(t,e)+\" - \"+E.hoverLabelText(t,r);var n=\"log\"===t.type&&e<=0,a=E.tickText(t,t.c2l(n?-e:e),\"hover\").text;return n?0===e?\"0\":_+a:a};var G=[\"f\",\"p\",\"n\",\"\\u03bc\",\"m\",\"\",\"k\",\"M\",\"G\",\"T\"];function Y(t){return\"SI\"===t||\"B\"===t}function W(t){return t>14||t<-15}function X(t,e,r,n){var i=t<0,o=e._tickround,l=r||e.exponentformat||\"B\",c=e._tickexponent,u=E.getTickFormat(e),h=e.separatethousands;if(n){var f={exponentformat:l,dtick:\"none\"===e.showexponent?e.dtick:a(t)&&Math.abs(t)||1,range:\"none\"===e.showexponent?e.range.map(e.r2d):[0,t||1]};q(f),o=(Number(f._tickround)||0)+4,c=f._tickexponent,e.hoverformat&&(u=e.hoverformat)}if(u)return e._numFormat(u)(t).replace(/-/g,_);var p,d=Math.pow(10,-o)/2;if(\"none\"===l&&(c=0),(t=Math.abs(t))<d)t=\"0\",i=!1;else{if(t+=d,c&&(t*=Math.pow(10,-c),o+=c),0===o)t=String(Math.floor(t));else if(o<0){t=(t=String(Math.round(t))).substr(0,t.length+o);for(var g=o;g<0;g++)t+=\"0\"}else{var v=(t=String(t)).indexOf(\".\")+1;v&&(t=t.substr(0,v+o).replace(/\\.?0+$/,\"\"))}t=s.numSeparate(t,e._separators,h)}c&&\"hide\"!==l&&(Y(l)&&W(c)&&(l=\"power\"),p=c<0?_+-c:\"power\"!==l?\"+\"+c:String(c),\"e\"===l||\"E\"===l?t+=l+p:\"power\"===l?t+=\"\\xd710<sup>\"+p+\"</sup>\":\"B\"===l&&9===c?t+=\"B\":Y(l)&&(t+=G[c/3+5]));return i?_+t:t}function Z(t,e){for(var r=[],n={},a=0;a<e.length;a++){var i=e[a];n[i.text2]?n[i.text2].push(i.x):n[i.text2]=[i.x]}for(var o in n)r.push(H(t,s.interp(n[o],.5),o));return r}function J(t){return[t.text,t.x,t.axInfo,t.font,t.fontSize,t.fontColor].join(\"_\")}function K(t){var e=t.title.font.size,r=(t.title.text.match(l.BR_TAG_ALL)||[]).length;return t.title.hasOwnProperty(\"standoff\")?r?e*(M+r*A):e*M:r?e*(r+1)*A:e}function Q(t,e){var r=t.l2p(e);return r>1&&r<t._length-1}function $(t){var e=n.select(t),r=e.select(\".text-math-group\");return r.empty()?e.select(\"text\"):r}function tt(t){return t._id+\".automargin\"}function et(t){return tt(t)+\".mirror\"}function rt(t){return t._id+\".rangeslider\"}function nt(t,e){for(var r=0;r<e.length;r++)-1===t.indexOf(e[r])&&t.push(e[r])}function at(t,e,r){var n,a,i=[],o=[],l=t.layout;for(n=0;n<e.length;n++)i.push(E.getFromId(t,e[n]));for(n=0;n<r.length;n++)o.push(E.getFromId(t,r[n]));var c=Object.keys(f),u=[\"anchor\",\"domain\",\"overlaying\",\"position\",\"side\",\"tickangle\",\"editType\"],h=[\"linear\",\"log\"];for(n=0;n<c.length;n++){var p=c[n],d=i[0][p],g=o[0][p],v=!0,m=!1,y=!1;if(\"_\"!==p.charAt(0)&&\"function\"!=typeof d&&-1===u.indexOf(p)){for(a=1;a<i.length&&v;a++){var x=i[a][p];\"type\"===p&&-1!==h.indexOf(d)&&-1!==h.indexOf(x)&&d!==x?m=!0:x!==d&&(v=!1)}for(a=1;a<o.length&&v;a++){var b=o[a][p];\"type\"===p&&-1!==h.indexOf(g)&&-1!==h.indexOf(b)&&g!==b?y=!0:o[a][p]!==g&&(v=!1)}v&&(m&&(l[i[0]._name].type=\"linear\"),y&&(l[o[0]._name].type=\"linear\"),it(l,p,i,o,t._fullLayout._dfltTitle))}}for(n=0;n<t._fullLayout.annotations.length;n++){var _=t._fullLayout.annotations[n];-1!==e.indexOf(_.xref)&&-1!==r.indexOf(_.yref)&&s.swapAttrs(l.annotations[n],[\"?\"])}}function it(t,e,r,n,a){var i,o=s.nestedProperty,l=o(t[r[0]._name],e).get(),c=o(t[n[0]._name],e).get();for(\"title\"===e&&(l&&l.text===a.x&&(l.text=a.y),c&&c.text===a.y&&(c.text=a.x)),i=0;i<r.length;i++)o(t,r[i]._name+\".\"+e).set(c);for(i=0;i<n.length;i++)o(t,n[i]._name+\".\"+e).set(l)}function ot(t){return\"angularaxis\"===t._id}E.getTickFormat=function(t){var e,r,n,a,i,o,s,l;function c(t){return\"string\"!=typeof t?t:Number(t.replace(\"M\",\"\"))*v}function u(t,e){var r=[\"L\",\"D\"];if(typeof t==typeof e){if(\"number\"==typeof t)return t-e;var n=r.indexOf(t.charAt(0)),a=r.indexOf(e.charAt(0));return n===a?Number(t.replace(/(L|D)/g,\"\"))-Number(e.replace(/(L|D)/g,\"\")):n-a}return\"number\"==typeof t?1:-1}function h(t,e){var r=null===e[0],n=null===e[1],a=u(t,e[0])>=0,i=u(t,e[1])<=0;return(r||a)&&(n||i)}if(t.tickformatstops&&t.tickformatstops.length>0)switch(t.type){case\"date\":case\"linear\":for(e=0;e<t.tickformatstops.length;e++)if((n=t.tickformatstops[e]).enabled&&(a=t.dtick,i=n.dtickrange,o=void 0,s=void 0,l=void 0,o=c||function(t){return t},s=i[0],l=i[1],(!s&&\"number\"!=typeof s||o(s)<=o(a))&&(!l&&\"number\"!=typeof l||o(l)>=o(a)))){r=n;break}break;case\"log\":for(e=0;e<t.tickformatstops.length;e++)if((n=t.tickformatstops[e]).enabled&&h(t.dtick,n.dtickrange)){r=n;break}}return r?r.value:t.tickformat},E.getSubplots=function(t,e){var r=t._fullLayout._subplots,n=r.cartesian.concat(r.gl2d||[]),a=e?E.findSubplotsWithAxis(n,e):n;return a.sort(function(t,e){var r=t.substr(1).split(\"y\"),n=e.substr(1).split(\"y\");return r[0]===n[0]?+r[1]-+n[1]:+r[0]-+n[0]}),a},E.findSubplotsWithAxis=function(t,e){for(var r=new RegExp(\"x\"===e._id.charAt(0)?\"^\"+e._id+\"y\":e._id+\"$\"),n=[],a=0;a<t.length;a++){var i=t[a];r.test(i)&&n.push(i)}return n},E.makeClipPaths=function(t){var e=t._fullLayout;if(!e._hasOnlyLargeSploms){var r,a,i={_offset:0,_length:e.width,_id:\"\"},o={_offset:0,_length:e.height,_id:\"\"},s=E.list(t,\"x\",!0),l=E.list(t,\"y\",!0),c=[];for(r=0;r<s.length;r++)for(c.push({x:s[r],y:o}),a=0;a<l.length;a++)0===r&&c.push({x:i,y:l[a]}),c.push({x:s[r],y:l[a]});var u=e._clips.selectAll(\".axesclip\").data(c,function(t){return t.x._id+t.y._id});u.enter().append(\"clipPath\").classed(\"axesclip\",!0).attr(\"id\",function(t){return\"clip\"+e._uid+t.x._id+t.y._id}).append(\"rect\"),u.exit().remove(),u.each(function(t){n.select(this).select(\"rect\").attr({x:t.x._offset||0,y:t.y._offset||0,width:t.x._length||1,height:t.y._length||1})})}},E.draw=function(t,e,r){var n=t._fullLayout;\"redraw\"===e&&n._paper.selectAll(\"g.subplot\").each(function(t){var e=t[0],r=n._plots[e],a=r.xaxis,i=r.yaxis;r.xaxislayer.selectAll(\".\"+a._id+\"tick\").remove(),r.yaxislayer.selectAll(\".\"+i._id+\"tick\").remove(),r.xaxislayer.selectAll(\".\"+a._id+\"tick2\").remove(),r.yaxislayer.selectAll(\".\"+i._id+\"tick2\").remove(),r.xaxislayer.selectAll(\".\"+a._id+\"divider\").remove(),r.yaxislayer.selectAll(\".\"+i._id+\"divider\").remove(),r.gridlayer&&r.gridlayer.selectAll(\"path\").remove(),r.zerolinelayer&&r.zerolinelayer.selectAll(\"path\").remove(),n._infolayer.select(\".g-\"+a._id+\"title\").remove(),n._infolayer.select(\".g-\"+i._id+\"title\").remove()});var a=e&&\"redraw\"!==e?e:E.listIds(t);return s.syncOrAsync(a.map(function(e){return function(){if(e){var n=E.getFromId(t,e),a=E.drawOne(t,n,r);return n._r=n.range.slice(),n._rl=s.simpleMap(n._r,n.r2l),a}}}))},E.drawOne=function(t,e,r){var n,a,l;r=r||{},e.setScale();var f=t._fullLayout,p=e._id,d=p.charAt(0),g=E.counterLetter(p),v=f._plots[e._mainSubplot];if(v){var m=v[d+\"axislayer\"],y=e._mainLinePosition,x=e._mainMirrorPosition,b=e._vals=E.calcTicks(e),_=[e.mirror,y,x].join(\"_\");for(n=0;n<b.length;n++)b[n].axInfo=_;e._selections={},e._tickAngles&&(e._prevTickAngles=e._tickAngles),e._tickAngles={},e._depth=null;var w={};if(e.visible){var k,T,M=E.makeTransFn(e);if(\"boundaries\"===e.tickson){var L=function(t,e){var r,n=[],a=function(t,e){var r=t.xbnd[e];null!==r&&n.push(s.extendFlat({},t,{x:r}))};if(e.length){for(r=0;r<e.length;r++)a(e[r],0);a(e[r-1],1)}return n}(0,b);T=E.clipEnds(e,L),k=\"inside\"===e.ticks?T:L}else T=E.clipEnds(e,b),k=\"inside\"===e.ticks?T:b;var C=e._gridVals=T,P=function(t,e){var r,n,a=[],i=function(t,e){var r=t.xbnd[e];null!==r&&a.push(s.extendFlat({},t,{x:r}))};if(t.showdividers&&e.length){for(r=0;r<e.length;r++){var o=e[r];o.text2!==n&&i(o,0),n=o.text2}i(e[r-1],1)}return a}(e,b);if(!f._hasOnlyLargeSploms){var O=e._subplotsWith,z={};for(n=0;n<O.length;n++){a=O[n];var I=(l=f._plots[a])[g+\"axis\"],D=I._mainAxis._id;if(!z[D]){z[D]=1;var R=\"x\"===d?\"M0,\"+I._offset+\"v\"+I._length:\"M\"+I._offset+\",0h\"+I._length;E.drawGrid(t,e,{vals:C,counterAxis:I,layer:l.gridlayer.select(\".\"+p),path:R,transFn:M}),E.drawZeroLine(t,e,{counterAxis:I,layer:l.zerolinelayer,path:R,transFn:M})}}}var F=E.getTickSigns(e),B=[];if(e.ticks){var N,j,V,U=E.makeTickPath(e,y,F[2]);if(e._anchorAxis&&e.mirror&&!0!==e.mirror?(N=E.makeTickPath(e,x,F[3]),j=U+N):(N=\"\",j=U),e.showdividers&&\"outside\"===e.ticks&&\"boundaries\"===e.tickson){var q={};for(n=0;n<P.length;n++)q[P[n].x]=1;V=function(t){return q[t.x]?N:j}}else V=j;E.drawTicks(t,e,{vals:k,layer:m,path:V,transFn:M}),\"allticks\"===e.mirror&&(B=Object.keys(e._linepositions||{}))}for(n=0;n<B.length;n++){a=B[n],l=f._plots[a];var H=e._linepositions[a]||[],G=E.makeTickPath(e,H[0],F[0])+E.makeTickPath(e,H[1],F[1]);E.drawTicks(t,e,{vals:k,layer:l[d+\"axislayer\"],path:G,transFn:M})}var Y=[];if(Y.push(function(){return E.drawLabels(t,e,{vals:b,layer:m,transFn:M,labelFns:E.makeLabelFns(e,y)})}),\"multicategory\"===e.type){var W={x:2,y:10}[d];Y.push(function(){var r={x:\"height\",y:\"width\"}[d],n=Q()[r]+W+(e._tickAngles[p+\"tick\"]?e.tickfont.size*A:0);return E.drawLabels(t,e,{vals:Z(e,b),layer:m,cls:p+\"tick2\",repositionOnUpdate:!0,secondary:!0,transFn:M,labelFns:E.makeLabelFns(e,y+n*F[4])})}),Y.push(function(){return e._depth=F[4]*(Q(\"tick2\")[e.side]-y),function(t,e,r){var n=e._id+\"divider\",a=r.vals,i=r.layer.selectAll(\"path.\"+n).data(a,J);i.exit().remove(),i.enter().insert(\"path\",\":first-child\").classed(n,1).classed(\"crisp\",1).call(u.stroke,e.dividercolor).style(\"stroke-width\",h.crispRound(t,e.dividerwidth,1)+\"px\"),i.attr(\"transform\",r.transFn).attr(\"d\",r.path)}(t,e,{vals:P,layer:m,path:E.makeTickPath(e,y,F[4],e._depth),transFn:M})})}else e.title.hasOwnProperty(\"standoff\")&&Y.push(function(){e._depth=F[4]*(Q()[e.side]-y)});var X=o.getComponentMethod(\"rangeslider\",\"isVisible\")(e);return Y.push(function(){var r,n,a,s,l=e.side.charAt(0),c=S[e.side].charAt(0),u=E.getPxPosition(t,e),h=\"outside\"===e.ticks?e.ticklen:0;if((e.automargin||X)&&(\"multicategory\"===e.type?r=Q(\"tick2\"):(r=Q(),\"x\"===d&&\"b\"===l&&(e._depth=Math.max(r.width>0?r.bottom-u:0,h)))),e.automargin){n={x:0,y:0,r:0,l:0,t:0,b:0};var p=[0,1];if(\"x\"===d){if(\"b\"===l?n[l]=e._depth:(n[l]=e._depth=Math.max(r.width>0?u-r.top:0,h),p.reverse()),r.width>0){var v=r.right-(e._offset+e._length);v>0&&(n.xr=1,n.r=v);var m=e._offset-r.left;m>0&&(n.xl=0,n.l=m)}}else if(\"l\"===l?n[l]=e._depth=Math.max(r.height>0?u-r.left:0,h):(n[l]=e._depth=Math.max(r.height>0?r.right-u:0,h),p.reverse()),r.height>0){var y=r.bottom-(e._offset+e._length);y>0&&(n.yb=0,n.b=y);var x=e._offset-r.top;x>0&&(n.yt=1,n.t=x)}n[g]=\"free\"===e.anchor?e.position:e._anchorAxis.domain[p[0]],e.title.text!==f._dfltTitle[d]&&(n[l]+=K(e)+(e.title.standoff||0)),e.mirror&&\"free\"!==e.anchor&&((a={x:0,y:0,r:0,l:0,t:0,b:0})[c]=e.linewidth,e.mirror&&!0!==e.mirror&&(a[c]+=h),!0===e.mirror||\"ticks\"===e.mirror?a[g]=e._anchorAxis.domain[p[1]]:\"all\"!==e.mirror&&\"allticks\"!==e.mirror||(a[g]=[e._counterDomainMin,e._counterDomainMax][p[1]]))}X&&(s=o.getComponentMethod(\"rangeslider\",\"autoMarginOpts\")(t,e)),i.autoMargin(t,tt(e),n),i.autoMargin(t,et(e),a),i.autoMargin(t,rt(e),s)}),r.skipTitle||X&&\"bottom\"===e.side||Y.push(function(){return function(t,e){var r,n=t._fullLayout,a=e._id,i=a.charAt(0),o=e.title.font.size;if(e.title.hasOwnProperty(\"standoff\"))r=e._depth+e.title.standoff+K(e);else{if(\"multicategory\"===e.type)r=e._depth;else{r=10+1.5*o+(e.linewidth?e.linewidth-1:0)}r+=\"x\"===i?\"top\"===e.side?o*(e.showticklabels?1:0):o*(e.showticklabels?1.5:.5):\"right\"===e.side?o*(e.showticklabels?1:.5):o*(e.showticklabels?.5:0)}var s,l,u,f,p=E.getPxPosition(t,e);\"x\"===i?(l=e._offset+e._length/2,u=\"top\"===e.side?p-r:p+r):(u=e._offset+e._length/2,l=\"right\"===e.side?p+r:p-r,s={rotate:\"-90\",offset:0});if(\"multicategory\"!==e.type){var d=e._selections[e._id+\"tick\"];if(f={selection:d,side:e.side},d&&d.node()&&d.node().parentNode){var g=h.getTranslate(d.node().parentNode);f.offsetLeft=g.x,f.offsetTop=g.y}e.title.hasOwnProperty(\"standoff\")&&(f.pad=0)}return c.draw(t,a+\"title\",{propContainer:e,propName:e._name+\".title.text\",placeholder:n._dfltTitle[i],avoid:f,transform:s,attributes:{x:l,y:u,\"text-anchor\":\"middle\"}})}(t,e)}),s.syncOrAsync(Y)}}function Q(t){var r=p+(t||\"tick\");return w[r]||(w[r]=function(t,e){var r,n,a,i;t._selections[e].size()?(r=1/0,n=-1/0,a=1/0,i=-1/0,t._selections[e].each(function(){var t=$(this),e=h.bBox(t.node().parentNode);r=Math.min(r,e.top),n=Math.max(n,e.bottom),a=Math.min(a,e.left),i=Math.max(i,e.right)})):(r=0,n=0,a=0,i=0);return{top:r,bottom:n,left:a,right:i,height:n-r,width:i-a}}(e,r)),w[r]}},E.getTickSigns=function(t){var e=t._id.charAt(0),r={x:\"top\",y:\"right\"}[e],n=t.side===r?1:-1,a=[-1,1,n,-n];return\"inside\"!==t.ticks==(\"x\"===e)&&(a=a.map(function(t){return-t})),t.side&&a.push({l:-1,t:-1,r:1,b:1}[t.side.charAt(0)]),a},E.makeTransFn=function(t){var e=t._id.charAt(0),r=t._offset;return\"x\"===e?function(e){return\"translate(\"+(r+t.l2p(e.x))+\",0)\"}:function(e){return\"translate(0,\"+(r+t.l2p(e.x))+\")\"}},E.makeTickPath=function(t,e,r,n){n=void 0!==n?n:t.ticklen;var a=t._id.charAt(0),i=(t.linewidth||1)/2;return\"x\"===a?\"M0,\"+(e+i*r)+\"v\"+n*r:\"M\"+(e+i*r)+\",0h\"+n*r},E.makeLabelFns=function(t,e,r){var n=t._id.charAt(0),i=\"boundaries\"!==t.tickson&&\"outside\"===t.ticks,o=0,l=0;if(i&&(o+=t.ticklen),r&&\"outside\"===t.ticks){var c=s.deg2rad(r);o=t.ticklen*Math.cos(c)+1,l=t.ticklen*Math.sin(c)}t.showticklabels&&(i||t.showline)&&(o+=.2*t.tickfont.size);var u,h,f,p,d={labelStandoff:o+=(t.linewidth||1)/2,labelShift:l};return\"x\"===n?(p=\"bottom\"===t.side?1:-1,u=l*p,h=e+o*p,f=\"bottom\"===t.side?1:-.2,d.xFn=function(t){return t.dx+u},d.yFn=function(t){return t.dy+h+t.fontSize*f},d.anchorFn=function(t,e){return a(e)&&0!==e&&180!==e?e*p<0?\"end\":\"start\":\"middle\"},d.heightFn=function(e,r,n){return r<-60||r>60?-.5*n:\"top\"===t.side?-n:0}):\"y\"===n&&(p=\"right\"===t.side?1:-1,u=o,h=-l*p,f=90===Math.abs(t.tickangle)?.5:0,d.xFn=function(t){return t.dx+e+(u+t.fontSize*f)*p},d.yFn=function(t){return t.dy+h+t.fontSize*T},d.anchorFn=function(e,r){return a(r)&&90===Math.abs(r)?\"middle\":\"right\"===t.side?\"start\":\"end\"},d.heightFn=function(e,r,n){return(r*=\"left\"===t.side?1:-1)<-30?-n:r<30?-.5*n:0}),d},E.drawTicks=function(t,e,r){r=r||{};var n=e._id+\"tick\",a=r.layer.selectAll(\"path.\"+n).data(e.ticks?r.vals:[],J);a.exit().remove(),a.enter().append(\"path\").classed(n,1).classed(\"ticks\",1).classed(\"crisp\",!1!==r.crisp).call(u.stroke,e.tickcolor).style(\"stroke-width\",h.crispRound(t,e.tickwidth,1)+\"px\").attr(\"d\",r.path),a.attr(\"transform\",r.transFn)},E.drawGrid=function(t,e,r){r=r||{};var n=e._id+\"grid\",a=r.vals,i=r.counterAxis;if(!1===e.showgrid)a=[];else if(i&&E.shouldShowZeroLine(t,e,i))for(var o=\"array\"===e.tickmode,s=0;s<a.length;s++){var l=a[s].x;if(o?!l:Math.abs(l)<e.dtick/100){if(a=a.slice(0,s).concat(a.slice(s+1)),!o)break;s--}}var c=r.layer.selectAll(\"path.\"+n).data(a,J);c.exit().remove(),c.enter().append(\"path\").classed(n,1).classed(\"crisp\",!1!==r.crisp),e._gw=h.crispRound(t,e.gridwidth,1),c.attr(\"transform\",r.transFn).attr(\"d\",r.path).call(u.stroke,e.gridcolor||\"#ddd\").style(\"stroke-width\",e._gw+\"px\"),\"function\"==typeof r.path&&c.attr(\"d\",r.path)},E.drawZeroLine=function(t,e,r){r=r||r;var n=e._id+\"zl\",a=E.shouldShowZeroLine(t,e,r.counterAxis),i=r.layer.selectAll(\"path.\"+n).data(a?[{x:0,id:e._id}]:[]);i.exit().remove(),i.enter().append(\"path\").classed(n,1).classed(\"zl\",1).classed(\"crisp\",!1!==r.crisp).each(function(){r.layer.selectAll(\"path\").sort(function(t,e){return C.idSort(t.id,e.id)})}),i.attr(\"transform\",r.transFn).attr(\"d\",r.path).call(u.stroke,e.zerolinecolor||u.defaultLine).style(\"stroke-width\",h.crispRound(t,e.zerolinewidth,e._gw||1)+\"px\")},E.drawLabels=function(t,e,r){r=r||{};var i=t._fullLayout,o=e._id,c=o.charAt(0),u=r.cls||o+\"tick\",f=r.vals,p=r.labelFns,d=r.secondary?0:e.tickangle,g=(e._prevTickAngles||{})[u],v=r.layer.selectAll(\"g.\"+u).data(e.showticklabels?f:[],J),m=[];function y(t,e){t.each(function(t){var i=n.select(this),o=i.select(\".text-math-group\"),s=p.anchorFn(t,e),c=r.transFn.call(i.node(),t)+(a(e)&&0!=+e?\" rotate(\"+e+\",\"+p.xFn(t)+\",\"+(p.yFn(t)-t.fontSize/2)+\")\":\"\"),u=l.lineCount(i),f=A*t.fontSize,d=p.heightFn(t,a(e)?+e:0,(u-1)*f);if(d&&(c+=\" translate(0, \"+d+\")\"),o.empty())i.select(\"text\").attr({transform:c,\"text-anchor\":s});else{var g=h.bBox(o.node()).width*{end:-.5,start:.5}[s];o.attr(\"transform\",c+(g?\"translate(\"+g+\",0)\":\"\"))}})}v.enter().append(\"g\").classed(u,1).append(\"text\").attr(\"text-anchor\",\"middle\").each(function(e){var r=n.select(this),a=t._promises.length;r.call(l.positionText,p.xFn(e),p.yFn(e)).call(h.font,e.font,e.fontSize,e.fontColor).text(e.text).call(l.convertToTspans,t),t._promises[a]?m.push(t._promises.pop().then(function(){y(r,d)})):y(r,d)}),v.exit().remove(),r.repositionOnUpdate&&v.each(function(t){n.select(this).select(\"text\").call(l.positionText,p.xFn(t),p.yFn(t))}),y(v,g+1?g:d);var x=null;e._selections&&(e._selections[u]=v);var b=[function(){return m.length&&Promise.all(m)}];e.automargin&&i._redrawFromAutoMarginCount&&90===g?(x=90,b.push(function(){y(v,g)})):b.push(function(){if(y(v,d),f.length&&\"x\"===c&&!a(d)&&(\"log\"!==e.type||\"D\"!==String(e.dtick).charAt(0))){x=0;var t,n=0,i=[];if(v.each(function(t){n=Math.max(n,t.fontSize);var r=e.l2p(t.x),a=$(this),o=h.bBox(a.node());i.push({top:0,bottom:10,height:10,left:r-o.width/2,right:r+o.width/2+2,width:o.width+2})}),\"boundaries\"!==e.tickson&&!e.showdividers||r.secondary){var o=f.length,l=Math.abs((f[o-1].x-f[0].x)*e._m)/(o-1)<2.5*n||\"multicategory\"===e.type;for(t=0;t<i.length-1;t++)if(s.bBoxIntersect(i[t],i[t+1])){x=l?90:30;break}}else{var u=2;for(e.ticks&&(u+=e.tickwidth/2),t=0;t<i.length;t++){var p=f[t].xbnd,g=i[t];if(null!==p[0]&&g.left-e.l2p(p[0])<u||null!==p[1]&&e.l2p(p[1])-g.right<u){x=90;break}}}x&&y(v,x)}}),e._tickAngles&&b.push(function(){e._tickAngles[u]=null===x?a(d)?d:0:x});var _=s.syncOrAsync(b);return _&&_.then&&t._promises.push(_),_},E.getPxPosition=function(t,e){var r,n=t._fullLayout._size,a=e._id.charAt(0),i=e.side;return\"free\"!==e.anchor?r=e._anchorAxis:\"x\"===a?r={_offset:n.t+(1-(e.position||0))*n.h,_length:0}:\"y\"===a&&(r={_offset:n.l+(e.position||0)*n.w,_length:0}),\"top\"===i||\"left\"===i?r._offset:\"bottom\"===i||\"right\"===i?r._offset+r._length:void 0},E.shouldShowZeroLine=function(t,e,r){var n=s.simpleMap(e.range,e.r2l);return n[0]*n[1]<=0&&e.zeroline&&(\"linear\"===e.type||\"-\"===e.type)&&(Q(e,0)||!function(t,e,r,n){var a=r._mainAxis;if(!a)return;var i=t._fullLayout,o=e._id.charAt(0),s=E.counterLetter(e._id),l=e._offset+(Math.abs(n[0])<Math.abs(n[1])==(\"x\"===o)?0:e._length);function c(t){if(!t.showline||!t.linewidth)return!1;var r=Math.max((t.linewidth+e.zerolinewidth)/2,1);function n(t){return\"number\"==typeof t&&Math.abs(t-l)<r}if(n(t._mainLinePosition)||n(t._mainMirrorPosition))return!0;var a=t._linepositions||{};for(var i in a)if(n(a[i][0])||n(a[i][1]))return!0}var u=i._plots[r._mainSubplot];if(!(u.mainplotinfo||u).overlays.length)return c(r);for(var h=E.list(t,s),f=0;f<h.length;f++){var p=h[f];if(p._mainAxis===a&&c(p))return!0}}(t,e,r,n)||function(t,e){for(var r=t._fullData,n=e._mainSubplot,a=e._id.charAt(0),i=0;i<r.length;i++){var s=r[i];if(!0===s.visible&&s.xaxis+s.yaxis===n){if(o.traceIs(s,\"bar-like\")&&s.orientation==={x:\"h\",y:\"v\"}[a])return!0;if(s.fill&&s.fill.charAt(s.fill.length-1)===a)return!0}}return!1}(t,e))},E.clipEnds=function(t,e){return e.filter(function(e){return Q(t,e.x)})},E.allowAutoMargin=function(t){for(var e=E.list(t,\"\",!0),r=0;r<e.length;r++){var n=e[r];n.automargin&&(i.allowAutoMargin(t,tt(n)),n.mirror&&i.allowAutoMargin(t,et(n))),o.getComponentMethod(\"rangeslider\",\"isVisible\")(n)&&i.allowAutoMargin(t,rt(n))}},E.swap=function(t,e){for(var r=function(t,e){var r,n,a=[];for(r=0;r<e.length;r++){var i=[],o=t._fullData[e[r]].xaxis,s=t._fullData[e[r]].yaxis;if(o&&s){for(n=0;n<a.length;n++)-1===a[n].x.indexOf(o)&&-1===a[n].y.indexOf(s)||i.push(n);if(i.length){var l,c=a[i[0]];if(i.length>1)for(n=1;n<i.length;n++)l=a[i[n]],nt(c.x,l.x),nt(c.y,l.y);nt(c.x,[o]),nt(c.y,[s])}else a.push({x:[o],y:[s]})}}return a}(t,e),n=0;n<r.length;n++)at(t,r[n].x,r[n].y)}},{\"../../components/color\":592,\"../../components/drawing\":613,\"../../components/titles\":679,\"../../constants/alignment\":686,\"../../constants/numerical\":693,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"../../plots/plots\":826,\"../../registry\":846,\"./autorange\":764,\"./axis_autotype\":766,\"./axis_ids\":768,\"./clean_ticks\":770,\"./layout_attributes\":777,\"./set_convert\":783,d3:165,\"fast-isnumeric\":228}],766:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib\"),i=t(\"../../constants/numerical\").BADNUM;e.exports=function(t,e,r){return!(r=r||{}).noMultiCategory&&(o=t,a.isArrayOrTypedArray(o[0])&&a.isArrayOrTypedArray(o[1]))?\"multicategory\":function(t,e){for(var r=Math.max(1,(t.length-1)/1e3),i=0,o=0,s={},l=0;l<t.length;l+=r){var c=t[Math.round(l)],u=String(c);s[u]||(s[u]=1,a.isDateTime(c,e)&&(i+=1),n(c)&&(o+=1))}return i>2*o}(t,e)?\"date\":function(t){for(var e=Math.max(1,(t.length-1)/1e3),r=0,n=0,o={},s=0;s<t.length;s+=e){var l=t[Math.round(s)],c=String(l);o[c]||(o[c]=1,\"boolean\"==typeof l?n++:a.cleanNumber(l)!==i?r++:\"string\"==typeof l&&n++)}return n>2*r}(t)?\"category\":function(t){if(!t)return!1;for(var e=0;e<t.length;e++)if(n(t[e]))return!0;return!1}(t)?\"linear\":\"-\";var o}},{\"../../constants/numerical\":693,\"../../lib\":717,\"fast-isnumeric\":228}],767:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../lib\"),i=t(\"./layout_attributes\"),o=t(\"./tick_value_defaults\"),s=t(\"./tick_mark_defaults\"),l=t(\"./tick_label_defaults\"),c=t(\"./category_order_defaults\"),u=t(\"./line_grid_defaults\"),h=t(\"./set_convert\");e.exports=function(t,e,r,f,p){var d=f.letter,g=f.font||{},v=f.splomStash||{},m=r(\"visible\",!f.visibleDflt),y=e.type;\"date\"===y&&n.getComponentMethod(\"calendars\",\"handleDefaults\")(t,e,\"calendar\",f.calendar);h(e,p);var x=!e.isValidRange(t.range);x&&f.reverseDflt&&(x=\"reversed\"),!r(\"autorange\",x)||\"linear\"!==y&&\"-\"!==y||r(\"rangemode\"),r(\"range\"),e.cleanRange(),c(t,e,r,f),\"category\"===y||f.noHover||r(\"hoverformat\");var b=r(\"color\"),_=b!==i.color.dflt?b:g.color,w=v.label||p._dfltTitle[d];if(l(t,e,r,y,f,{pass:1}),!m)return e;r(\"title.text\",w),a.coerceFont(r,\"title.font\",{family:g.family,size:Math.round(1.2*g.size),color:_}),o(t,e,r,y),l(t,e,r,y,f,{pass:2}),s(t,e,r,f),u(t,e,r,{dfltColor:b,bgColor:f.bgColor,showGrid:f.showGrid,attributes:i}),(e.showline||e.ticks)&&r(\"mirror\"),f.automargin&&r(\"automargin\");var k,T=\"multicategory\"===e.type;f.noTickson||\"category\"!==e.type&&!T||!e.ticks&&!e.showgrid||(T&&(k=\"boundaries\"),r(\"tickson\",k));T&&(r(\"showdividers\")&&(r(\"dividercolor\"),r(\"dividerwidth\")));return e}},{\"../../lib\":717,\"../../registry\":846,\"./category_order_defaults\":769,\"./layout_attributes\":777,\"./line_grid_defaults\":779,\"./set_convert\":783,\"./tick_label_defaults\":784,\"./tick_mark_defaults\":785,\"./tick_value_defaults\":786}],768:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"./constants\");r.id2name=function(t){if(\"string\"==typeof t&&t.match(a.AX_ID_PATTERN)){var e=t.substr(1);return\"1\"===e&&(e=\"\"),t.charAt(0)+\"axis\"+e}},r.name2id=function(t){if(t.match(a.AX_NAME_PATTERN)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),t.charAt(0)+e}},r.cleanId=function(t,e){if(t.match(a.AX_ID_PATTERN)&&(!e||t.charAt(0)===e)){var r=t.substr(1).replace(/^0+/,\"\");return\"1\"===r&&(r=\"\"),t.charAt(0)+r}},r.list=function(t,e,n){var a=t._fullLayout;if(!a)return[];var i,o=r.listIds(t,e),s=new Array(o.length);for(i=0;i<o.length;i++){var l=o[i];s[i]=a[l.charAt(0)+\"axis\"+l.substr(1)]}if(!n){var c=a._subplots.gl3d||[];for(i=0;i<c.length;i++){var u=a[c[i]];e?s.push(u[e+\"axis\"]):s.push(u.xaxis,u.yaxis,u.zaxis)}}return s},r.listIds=function(t,e){var r=t._fullLayout;if(!r)return[];var n=r._subplots;return e?n[e+\"axis\"]:n.xaxis.concat(n.yaxis)},r.getFromId=function(t,e,n){var a=t._fullLayout;return\"x\"===n?e=e.replace(/y[0-9]*/,\"\"):\"y\"===n&&(e=e.replace(/x[0-9]*/,\"\")),a[r.id2name(e)]},r.getFromTrace=function(t,e,a){var i=t._fullLayout,o=null;if(n.traceIs(e,\"gl3d\")){var s=e.scene;\"scene\"===s.substr(0,5)&&(o=i[s][a+\"axis\"])}else o=r.getFromId(t,e[a+\"axis\"]||a);return o},r.idSort=function(t,e){var r=t.charAt(0),n=e.charAt(0);return r!==n?r>n?1:-1:+(t.substr(1)||1)-+(e.substr(1)||1)},r.getAxisGroup=function(t,e){for(var r=t._axisMatchGroups,n=0;n<r.length;n++){if(r[n][e])return\"g\"+n}return e}},{\"../../registry\":846,\"./constants\":771}],769:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n){if(\"category\"===e.type){var a,i=t.categoryarray,o=Array.isArray(i)&&i.length>0;o&&(a=\"array\");var s,l=r(\"categoryorder\",a);\"array\"===l&&(s=r(\"categoryarray\")),o||\"array\"!==l||(l=e.categoryorder=\"trace\"),\"trace\"===l?e._initialCategories=[]:\"array\"===l?e._initialCategories=s.slice():(s=function(t,e){var r,n,a,i=e.dataAttr||t._id.charAt(0),o={};if(e.axData)r=e.axData;else for(r=[],n=0;n<e.data.length;n++){var s=e.data[n];s[i+\"axis\"]===t._id&&r.push(s)}for(n=0;n<r.length;n++){var l=r[n][i];for(a=0;a<l.length;a++){var c=l[a];null!=c&&(o[c]=1)}}return Object.keys(o)}(e,n).sort(),\"category ascending\"===l?e._initialCategories=s:\"category descending\"===l&&(e._initialCategories=s.reverse()))}}},{}],770:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib\"),i=t(\"../../constants/numerical\").ONEDAY;r.dtick=function(t,e){var r=\"log\"===e,a=\"date\"===e,o=\"category\"===e,s=a?i:1;if(!t)return s;if(n(t))return(t=Number(t))<=0?s:o?Math.max(1,Math.round(t)):a?Math.max(.1,t):t;if(\"string\"!=typeof t||!a&&!r)return s;var l=t.charAt(0),c=t.substr(1);return(c=n(c)?Number(c):0)<=0||!(a&&\"M\"===l&&c===Math.round(c)||r&&\"L\"===l||r&&\"D\"===l&&(1===c||2===c))?s:t},r.tick0=function(t,e,r,i){return\"date\"===e?a.cleanDate(t,a.dateTick0(r)):\"D1\"!==i&&\"D2\"!==i?n(t)?Number(t):0:void 0}},{\"../../constants/numerical\":693,\"../../lib\":717,\"fast-isnumeric\":228}],771:[function(t,e,r){\"use strict\";var n=t(\"../../lib/regex\").counter;e.exports={idRegex:{x:n(\"x\"),y:n(\"y\")},attrRegex:n(\"[xy]axis\"),xAxisMatch:n(\"xaxis\"),yAxisMatch:n(\"yaxis\"),AX_ID_PATTERN:/^[xyz][0-9]*$/,AX_NAME_PATTERN:/^[xyz]axis[0-9]*$/,SUBPLOT_PATTERN:/^x([0-9]*)y([0-9]*)$/,MINDRAG:8,MINSELECT:12,MINZOOM:20,DRAGGERSIZE:20,BENDPX:1.5,REDRAWDELAY:50,SELECTDELAY:100,SELECTID:\"-select\",DFLTRANGEX:[-1,6],DFLTRANGEY:[-1,4],traceLayerClasses:[\"imagelayer\",\"heatmaplayer\",\"contourcarpetlayer\",\"contourlayer\",\"funnellayer\",\"waterfalllayer\",\"barlayer\",\"carpetlayer\",\"violinlayer\",\"boxlayer\",\"ohlclayer\",\"scattercarpetlayer\",\"scatterlayer\"],clipOnAxisFalseQuery:[\".scatterlayer\",\".barlayer\",\".funnellayer\",\".waterfalllayer\"],layerValue2layerClass:{\"above traces\":\"above\",\"below traces\":\"below\"}}},{\"../../lib/regex\":733}],772:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./axis_ids\").id2name,i=t(\"./scale_zoom\"),o=t(\"./autorange\").makePadFn,s=t(\"./autorange\").concatExtremes,l=t(\"../../constants/numerical\").ALMOST_EQUAL,c=t(\"../../constants/alignment\").FROM_BL;function u(t,e,r,n,i){var o,s,l,c,u=\"range\"!==i,h=n[a(e)].type,f=[];for(s=0;s<r.length;s++)if((l=r[s])!==e&&(c=n[a(l)]).type===h)if(c.fixedrange){if(u&&c.anchor){n[a(c.anchor)].fixedrange&&f.push(l)}}else f.push(l);for(o=0;o<t.length;o++)if(t[o][e]){var p=t[o],d=[];for(s=0;s<f.length;s++)p[l=f[s]]||d.push(l);return{linkableAxes:d,thisGroup:p}}return{linkableAxes:f,thisGroup:null}}function h(t,e,r,n,a){var i,o,s,l,c;null===e?((e={})[r]=1,c=t.length,t.push(e)):c=t.indexOf(e);var u=Object.keys(e);for(i=0;i<t.length;i++)if(s=t[i],i!==c&&s[n]){var h=s[n];for(o=0;o<u.length;o++)s[l=u[o]]=h*a*e[l];return void t.splice(c,1)}if(1!==a)for(o=0;o<u.length;o++)e[u[o]]*=a;e[n]=1}function f(t,e){var r=t._inputDomain,n=c[t.constraintoward],a=r[0]+(r[1]-r[0])*n;t.domain=t._input.domain=[a+(r[0]-a)/e,a+(r[1]-a)/e],t.setScale()}r.handleConstraintDefaults=function(t,e,r,a){var i,o,s,l,c=a.allAxisIds,f=a.layoutOut,p=a.scaleanchorDflt,d=a.constrainDflt,g=f._axisConstraintGroups,v=f._axisMatchGroups,m=e._id,y=m.charAt(0),x=((f._splomAxes||{})[y]||{})[m]||{},b=e._id,_=b.charAt(0),w=r(\"constrain\",d);if(n.coerce(t,e,{constraintoward:{valType:\"enumerated\",values:\"x\"===_?[\"left\",\"center\",\"right\"]:[\"bottom\",\"middle\",\"top\"],dflt:\"x\"===_?\"center\":\"middle\"}},\"constraintoward\"),!t.matches&&!x.matches||e.fixedrange||(o=u(v,b,c,f),i=n.coerce(t,e,{matches:{valType:\"enumerated\",values:o.linkableAxes||[],dflt:x.matches}},\"matches\")),i||e.fixedrange&&\"domain\"!==w||!t.scaleanchor&&!p||(l=u(g,b,c,f,w),s=n.coerce(t,e,{scaleanchor:{valType:\"enumerated\",values:l.linkableAxes||[]}},\"scaleanchor\",p)),i?(delete e.constrain,h(v,o.thisGroup,b,i,1)):-1!==c.indexOf(t.matches)&&n.warn(\"ignored \"+e._name+'.matches: \"'+t.matches+'\" to avoid either an infinite loop or because the target axis has fixed range.'),s){var k=r(\"scaleratio\");k||(k=e.scaleratio=1),h(g,l.thisGroup,b,s,k)}else-1!==c.indexOf(t.scaleanchor)&&n.warn(\"ignored \"+e._name+'.scaleanchor: \"'+t.scaleanchor+'\" to avoid either an infinite loop and possibly inconsistent scaleratios, or because the target axis has fixed range or this axis declares a *matches* constraint.')},r.enforce=function(t){var e,r,n,c,u,h,p,d=t._fullLayout,g=d._axisConstraintGroups||[];for(e=0;e<g.length;e++){var v=g[e],m=Object.keys(v),y=1/0,x=0,b=1/0,_={},w={},k=!1;for(r=0;r<m.length;r++)w[n=m[r]]=c=d[a(n)],c._inputDomain?c.domain=c._inputDomain.slice():c._inputDomain=c.domain.slice(),c._inputRange||(c._inputRange=c.range.slice()),c.setScale(),_[n]=u=Math.abs(c._m)/v[n],y=Math.min(y,u),\"domain\"!==c.constrain&&c._constraintShrinkable||(b=Math.min(b,u)),delete c._constraintShrinkable,x=Math.max(x,u),\"domain\"===c.constrain&&(k=!0);if(!(y>l*x)||k)for(r=0;r<m.length;r++)if(u=_[n=m[r]],h=(c=w[n]).constrain,u!==b||\"domain\"===h)if(p=u/b,\"range\"===h)i(c,p);else{var T=c._inputDomain,M=(c.domain[1]-c.domain[0])/(T[1]-T[0]),A=(c.r2l(c.range[1])-c.r2l(c.range[0]))/(c.r2l(c._inputRange[1])-c.r2l(c._inputRange[0]));if((p/=M)*A<1){c.domain=c._input.domain=T.slice(),i(c,p);continue}if(A<1&&(c.range=c._input.range=c._inputRange.slice(),p*=A),c.autorange){var S=c.r2l(c.range[0]),E=c.r2l(c.range[1]),L=(S+E)/2,C=L,P=L,O=Math.abs(E-L),z=L-O*p*1.0001,I=L+O*p*1.0001,D=o(c);f(c,p);var R,F,B=Math.abs(c._m),N=s(t,c),j=N.min,V=N.max;for(F=0;F<j.length;F++)(R=j[F].val-D(j[F])/B)>z&&R<C&&(C=R);for(F=0;F<V.length;F++)(R=V[F].val+D(V[F])/B)<I&&R>P&&(P=R);p/=(P-C)/(2*O),C=c.l2r(C),P=c.l2r(P),c.range=c._input.range=S<E?[C,P]:[P,C]}f(c,p)}}},r.clean=function(t,e){if(e._inputDomain){for(var r=!1,n=e._id,a=t._fullLayout._axisConstraintGroups,i=0;i<a.length;i++)if(a[i][n]){r=!0;break}r&&\"domain\"===e.constrain||(e._input.domain=e.domain=e._inputDomain,delete e._inputDomain)}}},{\"../../constants/alignment\":686,\"../../constants/numerical\":693,\"../../lib\":717,\"./autorange\":764,\"./axis_ids\":768,\"./scale_zoom\":781}],773:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"tinycolor2\"),i=t(\"has-passive-events\"),o=t(\"../../registry\"),s=t(\"../../lib\"),l=t(\"../../lib/svg_text_utils\"),c=t(\"../../components/color\"),u=t(\"../../components/drawing\"),h=t(\"../../components/fx\"),f=t(\"./axes\"),p=t(\"../../lib/setcursor\"),d=t(\"../../components/dragelement\"),g=t(\"../../constants/alignment\").FROM_TL,v=t(\"../../lib/clear_gl_canvases\"),m=t(\"../../plot_api/subroutines\").redrawReglTraces,y=t(\"../plots\"),x=t(\"./axis_ids\").getFromId,b=t(\"./select\").prepSelect,_=t(\"./select\").clearSelect,w=t(\"./select\").selectOnClick,k=t(\"./scale_zoom\"),T=t(\"./constants\"),M=T.MINDRAG,A=T.MINZOOM,S=!0;function E(t,e,r,n){var a=s.ensureSingle(t.draglayer,e,r,function(e){e.classed(\"drag\",!0).style({fill:\"transparent\",\"stroke-width\":0}).attr(\"data-subplot\",t.id)});return a.call(p,n),a.node()}function L(t,e,r,a,i,o,s){var l=E(t,\"rect\",e,r);return n.select(l).call(u.setRect,a,i,o,s),l}function C(t,e){for(var r=0;r<t.length;r++)if(!t[r].fixedrange)return e;return\"\"}function P(t,e,r,n,a){for(var i=0;i<t.length;i++){var o=t[i];if(!o.fixedrange){var s=o._rl[0],l=o._rl[1]-s;n[o._name+\".range[0]\"]=o.l2r(s+l*e),n[o._name+\".range[1]\"]=o.l2r(s+l*r)}}if(a&&a.length){var c=(e+(1-r))/2;P(a,c,1-c,n,[])}}function O(t,e){for(var r=0;r<t.length;r++){var n=t[r];n.fixedrange||(n.range=[n.l2r(n._rl[0]-e/n._m),n.l2r(n._rl[1]-e/n._m)])}}function z(t){return 1-(t>=0?Math.min(t,.9):1/(1/Math.max(t,-.3)+3.222))}function I(t,e,r,n,a){return t.append(\"path\").attr(\"class\",\"zoombox\").style({fill:e>.2?\"rgba(0,0,0,0)\":\"rgba(255,255,255,0)\",\"stroke-width\":0}).attr(\"transform\",\"translate(\"+r+\", \"+n+\")\").attr(\"d\",a+\"Z\")}function D(t,e,r){return t.append(\"path\").attr(\"class\",\"zoombox-corners\").style({fill:c.background,stroke:c.defaultLine,\"stroke-width\":1,opacity:0}).attr(\"transform\",\"translate(\"+e+\", \"+r+\")\").attr(\"d\",\"M0,0Z\")}function R(t,e,r,n,a,i){t.attr(\"d\",n+\"M\"+r.l+\",\"+r.t+\"v\"+r.h+\"h\"+r.w+\"v-\"+r.h+\"h-\"+r.w+\"Z\"),F(t,e,a,i)}function F(t,e,r,n){r||(t.transition().style(\"fill\",n>.2?\"rgba(0,0,0,0.4)\":\"rgba(255,255,255,0.3)\").duration(200),e.transition().style(\"opacity\",1).duration(200))}function B(t){n.select(t).selectAll(\".zoombox,.js-zoombox-backdrop,.js-zoombox-menu,.zoombox-corners\").remove()}function N(t){S&&t.data&&t._context.showTips&&(s.notifier(s._(t,\"Double-click to zoom back out\"),\"long\"),S=!1)}function j(t){return\"lasso\"===t||\"select\"===t}function V(t){var e=Math.floor(Math.min(t.b-t.t,t.r-t.l,A)/2);return\"M\"+(t.l-3.5)+\",\"+(t.t-.5+e)+\"h3v\"+-e+\"h\"+e+\"v-3h-\"+(e+3)+\"ZM\"+(t.r+3.5)+\",\"+(t.t-.5+e)+\"h-3v\"+-e+\"h\"+-e+\"v-3h\"+(e+3)+\"ZM\"+(t.r+3.5)+\",\"+(t.b+.5-e)+\"h-3v\"+e+\"h\"+-e+\"v3h\"+(e+3)+\"ZM\"+(t.l-3.5)+\",\"+(t.b+.5-e)+\"h3v\"+e+\"h\"+e+\"v3h-\"+(e+3)+\"Z\"}function U(t,e,r,n){for(var a,i,o,l,c=!1,u={},h={},f=0;f<e.length;f++){var p=e[f];for(a in r)if(p[a]){for(o in p)(\"x\"===o.charAt(0)?r:n)[o]||(u[o]=a);for(i in n)p[i]&&(c=!0)}for(i in n)if(p[i])for(l in p)(\"x\"===l.charAt(0)?r:n)[l]||(h[l]=i)}c&&(s.extendFlat(u,h),h={});var d={},g=[];for(o in u){var v=x(t,o);g.push(v),d[v._id]=v}var m={},y=[];for(l in h){var b=x(t,l);y.push(b),m[b._id]=b}return{xaHash:d,yaHash:m,xaxes:g,yaxes:y,xLinks:u,yLinks:h,isSubplotConstrained:c}}function q(t,e){if(i){var r=void 0!==t.onwheel?\"wheel\":\"mousewheel\";t._onwheel&&t.removeEventListener(r,t._onwheel),t._onwheel=e,t.addEventListener(r,e,{passive:!1})}else void 0!==t.onwheel?t.onwheel=e:void 0!==t.onmousewheel&&(t.onmousewheel=e)}function H(t){var e=[];for(var r in t)e.push(t[r]);return e}e.exports={makeDragBox:function(t,e,r,i,c,p,S,E){var F,G,Y,W,X,Z,J,K,Q,$,tt,et,rt,nt,at,it,ot,st,lt,ct,ut,ht=t._fullLayout._zoomlayer,ft=S+E===\"nsew\",pt=1===(S+E).length;function dt(){if(F=e.xaxis,G=e.yaxis,Q=F._length,$=G._length,J=F._offset,K=G._offset,(Y={})[F._id]=F,(W={})[G._id]=G,S&&E)for(var r=e.overlays,n=0;n<r.length;n++){var a=r[n].xaxis;Y[a._id]=a;var i=r[n].yaxis;W[i._id]=i}X=H(Y),Z=H(W),rt=C(X,E),nt=C(Z,S),at=!nt&&!rt,tt=U(t,t._fullLayout._axisConstraintGroups,Y,W),et=U(t,t._fullLayout._axisMatchGroups,Y,W),it=E||tt.isSubplotConstrained||et.isSubplotConstrained,ot=S||tt.isSubplotConstrained||et.isSubplotConstrained;var o=t._fullLayout;st=o._has(\"scattergl\"),lt=o._has(\"splom\"),ct=o._has(\"svg\")}dt();var gt=function(t,e,r){return t?\"nsew\"===t?r?\"\":\"pan\"===e?\"move\":\"crosshair\":t.toLowerCase()+\"-resize\":\"pointer\"}(nt+rt,t._fullLayout.dragmode,ft),vt=L(e,S+E+\"drag\",gt,r,i,c,p);if(at&&!ft)return vt.onmousedown=null,vt.style.pointerEvents=\"none\",vt;var mt,yt,xt,bt,_t,wt,kt,Tt,Mt,At,St={element:vt,gd:t,plotinfo:e};function Et(){St.plotinfo.selection=!1,_(t)}function Lt(r,a){var i=t._fullLayout.clickmode;if(B(t),2!==r||pt||function(){if(!t._transitioningWithDuration){var e=t._context.doubleClick,r=[];rt&&(r=r.concat(X)),nt&&(r=r.concat(Z)),et.xaxes&&(r=r.concat(et.xaxes)),et.yaxes&&(r=r.concat(et.yaxes));var n,a,i,s={};if(\"reset+autosize\"===e)for(e=\"autosize\",a=0;a<r.length;a++)if((n=r[a])._rangeInitial&&(n.range[0]!==n._rangeInitial[0]||n.range[1]!==n._rangeInitial[1])||!n._rangeInitial&&!n.autorange){e=\"reset\";break}if(\"autosize\"===e)for(a=0;a<r.length;a++)(n=r[a]).fixedrange||(s[n._name+\".autorange\"]=!0);else if(\"reset\"===e)for((rt||tt.isSubplotConstrained)&&(r=r.concat(tt.xaxes)),nt&&!tt.isSubplotConstrained&&(r=r.concat(tt.yaxes)),tt.isSubplotConstrained&&(rt?nt||(r=r.concat(Z)):r=r.concat(X)),a=0;a<r.length;a++)(n=r[a]).fixedrange||(n._rangeInitial?(i=n._rangeInitial,s[n._name+\".range[0]\"]=i[0],s[n._name+\".range[1]\"]=i[1]):s[n._name+\".autorange\"]=!0);t.emit(\"plotly_doubleclick\",null),o.call(\"_guiRelayout\",t,s)}}(),ft)i.indexOf(\"select\")>-1&&w(a,t,X,Z,e.id,St),i.indexOf(\"event\")>-1&&h.click(t,a,e.id);else if(1===r&&pt){var s=S?G:F,c=\"s\"===S||\"w\"===E?0:1,u=s._name+\".range[\"+c+\"]\",f=function(t,e){var r,a=t.range[e],i=Math.abs(a-t.range[1-e]);return\"date\"===t.type?a:\"log\"===t.type?(r=Math.ceil(Math.max(0,-Math.log(i)/Math.LN10))+3,n.format(\".\"+r+\"g\")(Math.pow(10,a))):(r=Math.floor(Math.log(Math.abs(a))/Math.LN10)-Math.floor(Math.log(i)/Math.LN10)+4,n.format(\".\"+String(r)+\"g\")(a))}(s,c),p=\"left\",d=\"middle\";if(s.fixedrange)return;S?(d=\"n\"===S?\"top\":\"bottom\",\"right\"===s.side&&(p=\"right\")):\"e\"===E&&(p=\"right\"),t._context.showAxisRangeEntryBoxes&&n.select(vt).call(l.makeEditable,{gd:t,immediate:!0,background:t._fullLayout.paper_bgcolor,text:String(f),fill:s.tickfont?s.tickfont.color:\"#444\",horizontalAlign:p,verticalAlign:d}).on(\"edit\",function(e){var r=s.d2r(e);void 0!==r&&o.call(\"_guiRelayout\",t,u,r)})}}function Ct(e,r){if(t._transitioningWithDuration)return!1;var n=Math.max(0,Math.min(Q,e+mt)),a=Math.max(0,Math.min($,r+yt)),i=Math.abs(n-mt),o=Math.abs(a-yt);function s(){kt=\"\",xt.r=xt.l,xt.t=xt.b,Mt.attr(\"d\",\"M0,0Z\")}if(xt.l=Math.min(mt,n),xt.r=Math.max(mt,n),xt.t=Math.min(yt,a),xt.b=Math.max(yt,a),tt.isSubplotConstrained)i>A||o>A?(kt=\"xy\",i/Q>o/$?(o=i*$/Q,yt>a?xt.t=yt-o:xt.b=yt+o):(i=o*Q/$,mt>n?xt.l=mt-i:xt.r=mt+i),Mt.attr(\"d\",V(xt))):s();else if(et.isSubplotConstrained)if(i>A||o>A){kt=\"xy\";var l=Math.min(xt.l/Q,($-xt.b)/$),c=Math.max(xt.r/Q,($-xt.t)/$);xt.l=l*Q,xt.r=c*Q,xt.b=(1-l)*$,xt.t=(1-c)*$,Mt.attr(\"d\",V(xt))}else s();else!nt||o<Math.min(Math.max(.6*i,M),A)?i<M||!rt?s():(xt.t=0,xt.b=$,kt=\"x\",Mt.attr(\"d\",function(t,e){return\"M\"+(t.l-.5)+\",\"+(e-A-.5)+\"h-3v\"+(2*A+1)+\"h3ZM\"+(t.r+.5)+\",\"+(e-A-.5)+\"h3v\"+(2*A+1)+\"h-3Z\"}(xt,yt))):!rt||i<Math.min(.6*o,A)?(xt.l=0,xt.r=Q,kt=\"y\",Mt.attr(\"d\",function(t,e){return\"M\"+(e-A-.5)+\",\"+(t.t-.5)+\"v-3h\"+(2*A+1)+\"v3ZM\"+(e-A-.5)+\",\"+(t.b+.5)+\"v3h\"+(2*A+1)+\"v-3Z\"}(xt,mt))):(kt=\"xy\",Mt.attr(\"d\",V(xt)));xt.w=xt.r-xt.l,xt.h=xt.b-xt.t,kt&&(At=!0),t._dragged=At,R(Tt,Mt,xt,_t,wt,bt),Pt(),t.emit(\"plotly_relayouting\",ut),wt=!0}function Pt(){ut={},\"xy\"!==kt&&\"x\"!==kt||(P(X,xt.l/Q,xt.r/Q,ut,tt.xaxes),Bt(\"x\",ut)),\"xy\"!==kt&&\"y\"!==kt||(P(Z,($-xt.b)/$,($-xt.t)/$,ut,tt.yaxes),Bt(\"y\",ut))}function Ot(){Pt(),B(t),jt(),N(t)}St.prepFn=function(e,r,n){var i=St.dragmode,o=t._fullLayout.dragmode;o!==i&&(St.dragmode=o),dt(),at||(ft?e.shiftKey?\"pan\"===o?o=\"zoom\":j(o)||(o=\"pan\"):e.ctrlKey&&(o=\"pan\"):o=\"pan\"),St.minDrag=\"lasso\"===o?1:void 0,j(o)?(St.xaxes=X,St.yaxes=Z,b(e,r,n,St,o)):(St.clickFn=Lt,j(i)&&Et(),at||(\"zoom\"===o?(St.moveFn=Ct,St.doneFn=Ot,St.minDrag=1,function(e,r,n){var i=vt.getBoundingClientRect();mt=r-i.left,yt=n-i.top,xt={l:mt,r:mt,w:0,t:yt,b:yt,h:0},bt=t._hmpixcount?t._hmlumcount/t._hmpixcount:a(t._fullLayout.plot_bgcolor).getLuminance(),wt=!1,kt=\"xy\",At=!1,Tt=I(ht,bt,J,K,_t=\"M0,0H\"+Q+\"V\"+$+\"H0V0\"),Mt=D(ht,J,K)}(0,r,n)):\"pan\"===o&&(St.moveFn=Ft,St.doneFn=jt))),t._fullLayout._redrag=function(){var e=t._dragdata;e&&e.element===vt&&(j(t._fullLayout.dragmode)||(dt(),Vt([0,0,Q,$]),St.moveFn(e.dx,e.dy)))}},d.init(St);var zt=[0,0,Q,$],It=null,Dt=T.REDRAWDELAY,Rt=e.mainplot?t._fullLayout._plots[e.mainplot]:e;function Ft(e,r){if(!t._transitioningWithDuration){if(t._fullLayout._replotting=!0,\"ew\"===rt||\"ns\"===nt)return rt&&(O(X,e),Bt(\"x\")),nt&&(O(Z,r),Bt(\"y\")),Vt([rt?-e:0,nt?-r:0,Q,$]),Nt(),void t.emit(\"plotly_relayouting\",ut);if(tt.isSubplotConstrained&&rt&&nt){var n=\"w\"===rt==(\"n\"===nt)?1:-1,a=(e/Q+n*r/$)/2;e=a*Q,r=n*a*$}\"w\"===rt?e=l(X,0,e):\"e\"===rt?e=l(X,1,-e):rt||(e=0),\"n\"===nt?r=l(Z,1,r):\"s\"===nt?r=l(Z,0,-r):nt||(r=0);var i=\"w\"===rt?e:0,o=\"n\"===nt?r:0;if(tt.isSubplotConstrained){var s;if(!rt&&1===nt.length){for(s=0;s<X.length;s++)X[s].range=X[s]._r.slice(),k(X[s],1-r/$);i=(e=r*Q/$)/2}if(!nt&&1===rt.length){for(s=0;s<Z.length;s++)Z[s].range=Z[s]._r.slice(),k(Z[s],1-e/Q);o=(r=e*$/Q)/2}}Bt(\"x\"),Bt(\"y\"),Vt([i,o,Q-e,$-r]),Nt(),t.emit(\"plotly_relayouting\",ut)}function l(t,e,r){for(var n,a,i=1-e,o=0;o<t.length;o++){var s=t[o];if(!s.fixedrange){n=s,a=s._rl[i]+(s._rl[e]-s._rl[i])/z(r/s._length);var l=s.l2r(a);!1!==l&&void 0!==l&&(s.range[e]=l)}}return n._length*(n._rl[e]-a)/(n._rl[e]-n._rl[i])}}function Bt(t,e){for(var r=et.isSubplotConstrained?{x:Z,y:X}[t]:et[t+\"axes\"],n=et.isSubplotConstrained?{x:X,y:Z}[t]:[],a=0;a<r.length;a++){var i=r[a],o=i._id,s=et.xLinks[o]||et.yLinks[o],l=n[0]||Y[s]||W[s];l&&(e?(e[i._name+\".range[0]\"]=e[l._name+\".range[0]\"],e[i._name+\".range[1]\"]=e[l._name+\".range[1]\"]):i.range=l.range.slice())}}function Nt(){var e,r=[];function n(t){for(e=0;e<t.length;e++)t[e].fixedrange||r.push(t[e]._id)}for(it&&(n(X),n(tt.xaxes),n(et.xaxes)),ot&&(n(Z),n(tt.yaxes),n(et.yaxes)),ut={},e=0;e<r.length;e++){var a=r[e],i=x(t,a);f.drawOne(t,i,{skipTitle:!0}),ut[i._name+\".range[0]\"]=i.range[0],ut[i._name+\".range[1]\"]=i.range[1]}f.redrawComponents(t,r)}function jt(){Vt([0,0,Q,$]),s.syncOrAsync([y.previousPromises,function(){t._fullLayout._replotting=!1,o.call(\"_guiRelayout\",t,ut)}],t)}function Vt(e){var r,n,a,i,l=t._fullLayout,c=l._plots,h=l._subplots.cartesian;if(lt&&o.subplotsRegistry.splom.drag(t),st)for(r=0;r<h.length;r++)if(a=(n=c[h[r]]).xaxis,i=n.yaxis,n._scene){var f=s.simpleMap(a.range,a.r2l),p=s.simpleMap(i.range,i.r2l);n._scene.update({range:[f[0],p[0],f[1],p[1]]})}if((lt||st)&&(v(t),m(t)),ct){var d=e[2]/F._length,g=e[3]/G._length;for(r=0;r<h.length;r++){a=(n=c[h[r]]).xaxis,i=n.yaxis;var y,x,b,_,w=it&&!a.fixedrange&&Y[a._id],k=ot&&!i.fixedrange&&W[i._id];if(w?(y=d,b=E?e[0]:Ht(a,y)):et.xaHash[a._id]?(y=d,b=e[0]*a._length/F._length):et.yaHash[a._id]?(y=g,b=\"ns\"===nt?-e[1]*a._length/G._length:Ht(a,y,{n:\"top\",s:\"bottom\"}[nt])):b=qt(a,y=Ut(a,d,g)),k?(x=g,_=S?e[1]:Ht(i,x)):et.yaHash[i._id]?(x=g,_=e[1]*i._length/G._length):et.xaHash[i._id]?(x=d,_=\"ew\"===rt?-e[0]*i._length/F._length:Ht(i,x,{e:\"right\",w:\"left\"}[rt])):_=qt(i,x=Ut(i,d,g)),y||x){y||(y=1),x||(x=1);var T=a._offset-b/y,M=i._offset-_/x;n.clipRect.call(u.setTranslate,b,_).call(u.setScale,y,x),n.plot.call(u.setTranslate,T,M).call(u.setScale,1/y,1/x),y===n.xScaleFactor&&x===n.yScaleFactor||(u.setPointGroupScale(n.zoomScalePts,y,x),u.setTextPointsScale(n.zoomScaleTxt,y,x)),u.hideOutsideRangePoints(n.clipOnAxisFalseTraces,n),n.xScaleFactor=y,n.yScaleFactor=x}}}}function Ut(t,e,r){return t.fixedrange?0:it&&tt.xaHash[t._id]?e:ot&&(tt.isSubplotConstrained?tt.xaHash:tt.yaHash)[t._id]?r:0}function qt(t,e){return e?(t.range=t._r.slice(),k(t,e),Ht(t,e)):0}function Ht(t,e,r){return t._length*(1-e)*g[r||t.constraintoward||\"middle\"]}return S.length*E.length!=1&&q(vt,function(e){if(t._context._scrollZoom.cartesian||t._fullLayout._enablescrollzoom){if(Et(),t._transitioningWithDuration)return e.preventDefault(),void e.stopPropagation();dt(),clearTimeout(It);var r=-e.deltaY;if(isFinite(r)||(r=e.wheelDelta/10),isFinite(r)){var n,a=Math.exp(-Math.min(Math.max(r,-20),20)/200),i=Rt.draglayer.select(\".nsewdrag\").node().getBoundingClientRect(),o=(e.clientX-i.left)/i.width,l=(i.bottom-e.clientY)/i.height;if(it){for(E||(o=.5),n=0;n<X.length;n++)c(X[n],o,a);Bt(\"x\"),zt[2]*=a,zt[0]+=zt[2]*o*(1/a-1)}if(ot){for(S||(l=.5),n=0;n<Z.length;n++)c(Z[n],l,a);Bt(\"y\"),zt[3]*=a,zt[1]+=zt[3]*(1-l)*(1/a-1)}Vt(zt),Nt(),t.emit(\"plotly_relayouting\",ut),It=setTimeout(function(){zt=[0,0,Q,$],jt()},Dt),e.preventDefault()}else s.log(\"Did not find wheel motion attributes: \",e)}function c(t,e,r){if(!t.fixedrange){var n=s.simpleMap(t.range,t.r2l),a=n[0]+(n[1]-n[0])*e;t.range=n.map(function(e){return t.l2r(a+(e-a)*r)})}}}),vt},makeDragger:E,makeRectDragger:L,makeZoombox:I,makeCorners:D,updateZoombox:R,xyCorners:V,transitionZoombox:F,removeZoombox:B,showDoubleClickNotifier:N,attachWheelEventHandler:q}},{\"../../components/color\":592,\"../../components/dragelement\":610,\"../../components/drawing\":613,\"../../components/fx\":630,\"../../constants/alignment\":686,\"../../lib\":717,\"../../lib/clear_gl_canvases\":702,\"../../lib/setcursor\":737,\"../../lib/svg_text_utils\":741,\"../../plot_api/subroutines\":756,\"../../registry\":846,\"../plots\":826,\"./axes\":765,\"./axis_ids\":768,\"./constants\":771,\"./scale_zoom\":781,\"./select\":782,d3:165,\"has-passive-events\":413,tinycolor2:536}],774:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../components/fx\"),i=t(\"../../components/dragelement\"),o=t(\"../../lib/setcursor\"),s=t(\"./dragbox\").makeDragBox,l=t(\"./constants\").DRAGGERSIZE;r.initInteractions=function(t){var e=t._fullLayout;if(t._context.staticPlot)n.select(t).selectAll(\".drag\").remove();else if(e._has(\"cartesian\")||e._has(\"splom\")){Object.keys(e._plots||{}).sort(function(t,r){if((e._plots[t].mainplot&&!0)===(e._plots[r].mainplot&&!0)){var n=t.split(\"y\"),a=r.split(\"y\");return n[0]===a[0]?Number(n[1]||1)-Number(a[1]||1):Number(n[0]||1)-Number(a[0]||1)}return e._plots[t].mainplot?1:-1}).forEach(function(r){var n=e._plots[r],o=n.xaxis,c=n.yaxis;if(!n.mainplot){var u=s(t,n,o._offset,c._offset,o._length,c._length,\"ns\",\"ew\");u.onmousemove=function(e){t._fullLayout._rehover=function(){t._fullLayout._hoversubplot===r&&t._fullLayout._plots[r]&&a.hover(t,e,r)},a.hover(t,e,r),t._fullLayout._lasthover=u,t._fullLayout._hoversubplot=r},u.onmouseout=function(e){t._dragging||(t._fullLayout._hoversubplot=null,i.unhover(t,e))},t._context.showAxisDragHandles&&(s(t,n,o._offset-l,c._offset-l,l,l,\"n\",\"w\"),s(t,n,o._offset+o._length,c._offset-l,l,l,\"n\",\"e\"),s(t,n,o._offset-l,c._offset+c._length,l,l,\"s\",\"w\"),s(t,n,o._offset+o._length,c._offset+c._length,l,l,\"s\",\"e\"))}if(t._context.showAxisDragHandles){if(r===o._mainSubplot){var h=o._mainLinePosition;\"top\"===o.side&&(h-=l),s(t,n,o._offset+.1*o._length,h,.8*o._length,l,\"\",\"ew\"),s(t,n,o._offset,h,.1*o._length,l,\"\",\"w\"),s(t,n,o._offset+.9*o._length,h,.1*o._length,l,\"\",\"e\")}if(r===c._mainSubplot){var f=c._mainLinePosition;\"right\"!==c.side&&(f-=l),s(t,n,f,c._offset+.1*c._length,l,.8*c._length,\"ns\",\"\"),s(t,n,f,c._offset+.9*c._length,l,.1*c._length,\"s\",\"\"),s(t,n,f,c._offset,l,.1*c._length,\"n\",\"\")}}});var o=e._hoverlayer.node();o.onmousemove=function(r){r.target=t._fullLayout._lasthover,a.hover(t,r,e._hoversubplot)},o.onclick=function(e){e.target=t._fullLayout._lasthover,a.click(t,e)},o.onmousedown=function(e){t._fullLayout._lasthover.onmousedown(e)},r.updateFx(t)}},r.updateFx=function(t){var e=t._fullLayout,r=\"pan\"===e.dragmode?\"move\":\"crosshair\";o(e._draggers,r)}},{\"../../components/dragelement\":610,\"../../components/fx\":630,\"../../lib/setcursor\":737,\"./constants\":771,\"./dragbox\":773,d3:165}],775:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../lib\");e.exports=function(t){return function(e,r){var i=e[t];if(Array.isArray(i))for(var o=n.subplotsRegistry.cartesian,s=o.idRegex,l=r._subplots,c=l.xaxis,u=l.yaxis,h=l.cartesian,f=r._has(\"cartesian\")||r._has(\"gl2d\"),p=0;p<i.length;p++){var d=i[p];if(a.isPlainObject(d)){var g=d.xref,v=d.yref,m=s.x.test(g),y=s.y.test(v);if(m||y){f||a.pushUnique(r._basePlotModules,o);var x=!1;m&&-1===c.indexOf(g)&&(c.push(g),x=!0),y&&-1===u.indexOf(v)&&(u.push(v),x=!0),x&&m&&y&&h.push(g+v)}}}}}},{\"../../lib\":717,\"../../registry\":846}],776:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../registry\"),i=t(\"../../lib\"),o=t(\"../plots\"),s=t(\"../../components/drawing\"),l=t(\"../get_data\").getModuleCalcData,c=t(\"./axis_ids\"),u=t(\"./constants\"),h=t(\"../../constants/xmlns_namespaces\"),f=i.ensureSingle;function p(t,e,r){return i.ensureSingle(t,e,r,function(t){t.datum(r)})}function d(t,e,r,i,o){for(var c,h,f,p=u.traceLayerClasses,d=t._fullLayout,g=d._modules,v=[],m=[],y=0;y<g.length;y++){var x=(c=g[y]).name,b=a.modules[x].categories;if(b.svg){var _=c.layerName||x+\"layer\",w=c.plot;f=(h=l(r,w))[0],r=h[1],f.length&&v.push({i:p.indexOf(_),className:_,plotMethod:w,cdModule:f}),b.zoomScale&&m.push(\".\"+_)}}v.sort(function(t,e){return t.i-e.i});var k=e.plot.selectAll(\"g.mlayer\").data(v,function(t){return t.className});if(k.enter().append(\"g\").attr(\"class\",function(t){return t.className}).classed(\"mlayer\",!0).classed(\"rangeplot\",e.isRangePlot),k.exit().remove(),k.order(),k.each(function(r){var a=n.select(this),l=r.className;r.plotMethod(t,e,r.cdModule,a,i,o),-1===u.clipOnAxisFalseQuery.indexOf(\".\"+l)&&s.setClipUrl(a,e.layerClipId,t)}),d._has(\"scattergl\")&&(c=a.getModule(\"scattergl\"),f=l(r,c)[0],c.plot(t,e,f)),!t._context.staticPlot&&(e._hasClipOnAxisFalse&&(e.clipOnAxisFalseTraces=e.plot.selectAll(u.clipOnAxisFalseQuery.join(\",\")).selectAll(\".trace\")),m.length)){var T=e.plot.selectAll(m.join(\",\")).selectAll(\".trace\");e.zoomScalePts=T.selectAll(\"path.point\"),e.zoomScaleTxt=T.selectAll(\".textpoint\")}}function g(t,e){var r=e.plotgroup,n=e.id,a=u.layerValue2layerClass[e.xaxis.layer],i=u.layerValue2layerClass[e.yaxis.layer],o=t._fullLayout._hasOnlyLargeSploms;if(e.mainplot){var s=e.mainplotinfo,l=s.plotgroup,h=n+\"-x\",d=n+\"-y\";e.gridlayer=s.gridlayer,e.zerolinelayer=s.zerolinelayer,f(s.overlinesBelow,\"path\",h),f(s.overlinesBelow,\"path\",d),f(s.overaxesBelow,\"g\",h),f(s.overaxesBelow,\"g\",d),e.plot=f(s.overplot,\"g\",n),f(s.overlinesAbove,\"path\",h),f(s.overlinesAbove,\"path\",d),f(s.overaxesAbove,\"g\",h),f(s.overaxesAbove,\"g\",d),e.xlines=l.select(\".overlines-\"+a).select(\".\"+h),e.ylines=l.select(\".overlines-\"+i).select(\".\"+d),e.xaxislayer=l.select(\".overaxes-\"+a).select(\".\"+h),e.yaxislayer=l.select(\".overaxes-\"+i).select(\".\"+d)}else if(o)e.xlines=f(r,\"path\",\"xlines-above\"),e.ylines=f(r,\"path\",\"ylines-above\"),e.xaxislayer=f(r,\"g\",\"xaxislayer-above\"),e.yaxislayer=f(r,\"g\",\"yaxislayer-above\");else{var g=f(r,\"g\",\"layer-subplot\");e.shapelayer=f(g,\"g\",\"shapelayer\"),e.imagelayer=f(g,\"g\",\"imagelayer\"),e.gridlayer=f(r,\"g\",\"gridlayer\"),e.zerolinelayer=f(r,\"g\",\"zerolinelayer\"),f(r,\"path\",\"xlines-below\"),f(r,\"path\",\"ylines-below\"),e.overlinesBelow=f(r,\"g\",\"overlines-below\"),f(r,\"g\",\"xaxislayer-below\"),f(r,\"g\",\"yaxislayer-below\"),e.overaxesBelow=f(r,\"g\",\"overaxes-below\"),e.plot=f(r,\"g\",\"plot\"),e.overplot=f(r,\"g\",\"overplot\"),e.xlines=f(r,\"path\",\"xlines-above\"),e.ylines=f(r,\"path\",\"ylines-above\"),e.overlinesAbove=f(r,\"g\",\"overlines-above\"),f(r,\"g\",\"xaxislayer-above\"),f(r,\"g\",\"yaxislayer-above\"),e.overaxesAbove=f(r,\"g\",\"overaxes-above\"),e.xlines=r.select(\".xlines-\"+a),e.ylines=r.select(\".ylines-\"+i),e.xaxislayer=r.select(\".xaxislayer-\"+a),e.yaxislayer=r.select(\".yaxislayer-\"+i)}o||(p(e.gridlayer,\"g\",e.xaxis._id),p(e.gridlayer,\"g\",e.yaxis._id),e.gridlayer.selectAll(\"g\").map(function(t){return t[0]}).sort(c.idSort)),e.xlines.style(\"fill\",\"none\").classed(\"crisp\",!0),e.ylines.style(\"fill\",\"none\").classed(\"crisp\",!0)}function v(t,e){if(t){var r={};for(var a in t.each(function(t){var a=t[0];n.select(this).remove(),m(a,e),r[a]=!0}),e._plots)for(var i=e._plots[a].overlays||[],o=0;o<i.length;o++){var s=i[o];r[s.id]&&s.plot.selectAll(\".trace\").remove()}}}function m(t,e){e._draggers.selectAll(\"g.\"+t).remove(),e._defs.select(\"#clip\"+e._uid+t+\"plot\").remove()}r.name=\"cartesian\",r.attr=[\"xaxis\",\"yaxis\"],r.idRoot=[\"x\",\"y\"],r.idRegex=u.idRegex,r.attrRegex=u.attrRegex,r.attributes=t(\"./attributes\"),r.layoutAttributes=t(\"./layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout_defaults\"),r.transitionAxes=t(\"./transition_axes\"),r.finalizeSubplots=function(t,e){var r,n,a,o=e._subplots,s=o.xaxis,l=o.yaxis,h=o.cartesian,f=h.concat(o.gl2d||[]),p={},d={};for(r=0;r<f.length;r++){var g=f[r].split(\"y\");p[g[0]]=1,d[\"y\"+g[1]]=1}for(r=0;r<s.length;r++)p[n=s[r]]||(a=(t[c.id2name(n)]||{}).anchor,u.idRegex.y.test(a)||(a=\"y\"),h.push(n+a),f.push(n+a),d[a]||(d[a]=1,i.pushUnique(l,a)));for(r=0;r<l.length;r++)d[a=l[r]]||(n=(t[c.id2name(a)]||{}).anchor,u.idRegex.x.test(n)||(n=\"x\"),h.push(n+a),f.push(n+a),p[n]||(p[n]=1,i.pushUnique(s,n)));if(!f.length){for(var v in n=\"\",a=\"\",t){if(u.attrRegex.test(v))\"x\"===v.charAt(0)?(!n||+v.substr(5)<+n.substr(5))&&(n=v):(!a||+v.substr(5)<+a.substr(5))&&(a=v)}n=n?c.name2id(n):\"x\",a=a?c.name2id(a):\"y\",s.push(n),l.push(a),h.push(n+a)}},r.plot=function(t,e,r,n){var a,i=t._fullLayout,o=i._subplots.cartesian,s=t.calcdata;if(!Array.isArray(e))for(e=[],a=0;a<s.length;a++)e.push(a);for(a=0;a<o.length;a++){for(var l,c=o[a],u=i._plots[c],h=[],f=0;f<s.length;f++){var p=s[f],g=p[0].trace;g.xaxis+g.yaxis===c&&((-1!==e.indexOf(g.index)||g.carpet)&&(l&&l[0].trace.xaxis+l[0].trace.yaxis===c&&-1!==[\"tonextx\",\"tonexty\",\"tonext\"].indexOf(g.fill)&&-1===h.indexOf(l)&&h.push(l),h.push(p)),l=p)}d(t,u,h,r,n)}},r.clean=function(t,e,r,n){var a,i,o,s=n._plots||{},l=e._plots||{},u=n._subplots||{};if(n._hasOnlyLargeSploms&&!e._hasOnlyLargeSploms)for(o in s)(a=s[o]).plotgroup&&a.plotgroup.remove();var h=n._has&&n._has(\"gl\"),f=e._has&&e._has(\"gl\");if(h&&!f)for(o in s)(a=s[o])._scene&&a._scene.destroy();if(u.xaxis&&u.yaxis){var p=c.listIds({_fullLayout:n});for(i=0;i<p.length;i++){var d=p[i];e[c.id2name(d)]||n._infolayer.selectAll(\".g-\"+d+\"title\").remove()}}var g=n._has&&n._has(\"cartesian\"),y=e._has&&e._has(\"cartesian\");if(g&&!y)v(n._cartesianlayer.selectAll(\".subplot\"),n),n._defs.selectAll(\".axesclip\").remove(),delete n._axisConstraintGroups;else if(u.cartesian)for(i=0;i<u.cartesian.length;i++){var x=u.cartesian[i];if(!l[x]){var b=\".\"+x+\",.\"+x+\"-x,.\"+x+\"-y\";n._cartesianlayer.selectAll(b).remove(),m(x,n)}}},r.drawFramework=function(t){var e=t._fullLayout,r=function(t){var e,r,n,a,i,o,s=t._fullLayout,l=s._subplots.cartesian,c=l.length,u=[],h=[];for(e=0;e<c;e++){n=l[e],a=s._plots[n],i=a.xaxis,o=a.yaxis;var f=i._mainAxis,p=o._mainAxis,d=f._id+p._id,g=s._plots[d];a.overlays=[],d!==n&&g?(a.mainplot=d,a.mainplotinfo=g,h.push(n)):(a.mainplot=void 0,a.mainPlotinfo=void 0,u.push(n))}for(e=0;e<h.length;e++)n=h[e],(a=s._plots[n]).mainplotinfo.overlays.push(a);var v=u.concat(h),m=new Array(c);for(e=0;e<c;e++){n=v[e],a=s._plots[n],i=a.xaxis,o=a.yaxis;var y=[n,i.layer,o.layer,i.overlaying||\"\",o.overlaying||\"\"];for(r=0;r<a.overlays.length;r++)y.push(a.overlays[r].id);m[e]=y}return m}(t),a=e._cartesianlayer.selectAll(\".subplot\").data(r,String);a.enter().append(\"g\").attr(\"class\",function(t){return\"subplot \"+t[0]}),a.order(),a.exit().call(v,e),a.each(function(r){var a=r[0],i=e._plots[a];i.plotgroup=n.select(this),g(t,i),i.draglayer=f(e._draggers,\"g\",a)})},r.rangePlot=function(t,e,r){g(t,e),d(t,e,r),o.style(t)},r.toSVG=function(t){var e=t._fullLayout._glimages,r=n.select(t).selectAll(\".svg-container\");r.filter(function(t,e){return e===r.size()-1}).selectAll(\".gl-canvas-context, .gl-canvas-focus\").each(function(){var t=this.toDataURL(\"image/png\");e.append(\"svg:image\").attr({xmlns:h.svg,\"xlink:href\":t,preserveAspectRatio:\"none\",x:0,y:0,width:this.width,height:this.height})})},r.updateFx=t(\"./graph_interact\").updateFx},{\"../../components/drawing\":613,\"../../constants/xmlns_namespaces\":694,\"../../lib\":717,\"../../registry\":846,\"../get_data\":800,\"../plots\":826,\"./attributes\":763,\"./axis_ids\":768,\"./constants\":771,\"./graph_interact\":774,\"./layout_attributes\":777,\"./layout_defaults\":778,\"./transition_axes\":787,d3:165}],777:[function(t,e,r){\"use strict\";var n=t(\"../font_attributes\"),a=t(\"../../components/color/attributes\"),i=t(\"../../components/drawing/attributes\").dash,o=t(\"../../lib/extend\").extendFlat,s=t(\"../../plot_api/plot_template\").templatedArray,l=(t(\"../../constants/docs\").FORMAT_LINK,t(\"../../constants/docs\").DATE_FORMAT_LINK,t(\"./constants\"));e.exports={visible:{valType:\"boolean\",editType:\"plot\"},color:{valType:\"color\",dflt:a.defaultLine,editType:\"ticks\"},title:{text:{valType:\"string\",editType:\"ticks\"},font:n({editType:\"ticks\"}),standoff:{valType:\"number\",min:0,editType:\"ticks\"},editType:\"ticks\"},type:{valType:\"enumerated\",values:[\"-\",\"linear\",\"log\",\"date\",\"category\",\"multicategory\"],dflt:\"-\",editType:\"calc\",_noTemplating:!0},autorange:{valType:\"enumerated\",values:[!0,!1,\"reversed\"],dflt:!0,editType:\"axrange\",impliedEdits:{\"range[0]\":void 0,\"range[1]\":void 0}},rangemode:{valType:\"enumerated\",values:[\"normal\",\"tozero\",\"nonnegative\"],dflt:\"normal\",editType:\"plot\"},range:{valType:\"info_array\",items:[{valType:\"any\",editType:\"axrange\",impliedEdits:{\"^autorange\":!1},anim:!0},{valType:\"any\",editType:\"axrange\",impliedEdits:{\"^autorange\":!1},anim:!0}],editType:\"axrange\",impliedEdits:{autorange:!1},anim:!0},fixedrange:{valType:\"boolean\",dflt:!1,editType:\"calc\"},scaleanchor:{valType:\"enumerated\",values:[l.idRegex.x.toString(),l.idRegex.y.toString()],editType:\"plot\"},scaleratio:{valType:\"number\",min:0,dflt:1,editType:\"plot\"},constrain:{valType:\"enumerated\",values:[\"range\",\"domain\"],dflt:\"range\",editType:\"plot\"},constraintoward:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\",\"top\",\"middle\",\"bottom\"],editType:\"plot\"},matches:{valType:\"enumerated\",values:[l.idRegex.x.toString(),l.idRegex.y.toString()],editType:\"calc\"},tickmode:{valType:\"enumerated\",values:[\"auto\",\"linear\",\"array\"],editType:\"ticks\",impliedEdits:{tick0:void 0,dtick:void 0}},nticks:{valType:\"integer\",min:0,dflt:0,editType:\"ticks\"},tick0:{valType:\"any\",editType:\"ticks\",impliedEdits:{tickmode:\"linear\"}},dtick:{valType:\"any\",editType:\"ticks\",impliedEdits:{tickmode:\"linear\"}},tickvals:{valType:\"data_array\",editType:\"ticks\"},ticktext:{valType:\"data_array\",editType:\"ticks\"},ticks:{valType:\"enumerated\",values:[\"outside\",\"inside\",\"\"],editType:\"ticks\"},tickson:{valType:\"enumerated\",values:[\"labels\",\"boundaries\"],dflt:\"labels\",editType:\"ticks\"},mirror:{valType:\"enumerated\",values:[!0,\"ticks\",!1,\"all\",\"allticks\"],dflt:!1,editType:\"ticks+layoutstyle\"},ticklen:{valType:\"number\",min:0,dflt:5,editType:\"ticks\"},tickwidth:{valType:\"number\",min:0,dflt:1,editType:\"ticks\"},tickcolor:{valType:\"color\",dflt:a.defaultLine,editType:\"ticks\"},showticklabels:{valType:\"boolean\",dflt:!0,editType:\"ticks\"},automargin:{valType:\"boolean\",dflt:!1,editType:\"ticks\"},showspikes:{valType:\"boolean\",dflt:!1,editType:\"modebar\"},spikecolor:{valType:\"color\",dflt:null,editType:\"none\"},spikethickness:{valType:\"number\",dflt:3,editType:\"none\"},spikedash:o({},i,{dflt:\"dash\",editType:\"none\"}),spikemode:{valType:\"flaglist\",flags:[\"toaxis\",\"across\",\"marker\"],dflt:\"toaxis\",editType:\"none\"},spikesnap:{valType:\"enumerated\",values:[\"data\",\"cursor\"],dflt:\"data\",editType:\"none\"},tickfont:n({editType:\"ticks\"}),tickangle:{valType:\"angle\",dflt:\"auto\",editType:\"ticks\"},tickprefix:{valType:\"string\",dflt:\"\",editType:\"ticks\"},showtickprefix:{valType:\"enumerated\",values:[\"all\",\"first\",\"last\",\"none\"],dflt:\"all\",editType:\"ticks\"},ticksuffix:{valType:\"string\",dflt:\"\",editType:\"ticks\"},showticksuffix:{valType:\"enumerated\",values:[\"all\",\"first\",\"last\",\"none\"],dflt:\"all\",editType:\"ticks\"},showexponent:{valType:\"enumerated\",values:[\"all\",\"first\",\"last\",\"none\"],dflt:\"all\",editType:\"ticks\"},exponentformat:{valType:\"enumerated\",values:[\"none\",\"e\",\"E\",\"power\",\"SI\",\"B\"],dflt:\"B\",editType:\"ticks\"},separatethousands:{valType:\"boolean\",dflt:!1,editType:\"ticks\"},tickformat:{valType:\"string\",dflt:\"\",editType:\"ticks\"},tickformatstops:s(\"tickformatstop\",{enabled:{valType:\"boolean\",dflt:!0,editType:\"ticks\"},dtickrange:{valType:\"info_array\",items:[{valType:\"any\",editType:\"ticks\"},{valType:\"any\",editType:\"ticks\"}],editType:\"ticks\"},value:{valType:\"string\",dflt:\"\",editType:\"ticks\"},editType:\"ticks\"}),hoverformat:{valType:\"string\",dflt:\"\",editType:\"none\"},showline:{valType:\"boolean\",dflt:!1,editType:\"ticks+layoutstyle\"},linecolor:{valType:\"color\",dflt:a.defaultLine,editType:\"layoutstyle\"},linewidth:{valType:\"number\",min:0,dflt:1,editType:\"ticks+layoutstyle\"},showgrid:{valType:\"boolean\",editType:\"ticks\"},gridcolor:{valType:\"color\",dflt:a.lightLine,editType:\"ticks\"},gridwidth:{valType:\"number\",min:0,dflt:1,editType:\"ticks\"},zeroline:{valType:\"boolean\",editType:\"ticks\"},zerolinecolor:{valType:\"color\",dflt:a.defaultLine,editType:\"ticks\"},zerolinewidth:{valType:\"number\",dflt:1,editType:\"ticks\"},showdividers:{valType:\"boolean\",dflt:!0,editType:\"ticks\"},dividercolor:{valType:\"color\",dflt:a.defaultLine,editType:\"ticks\"},dividerwidth:{valType:\"number\",dflt:1,editType:\"ticks\"},anchor:{valType:\"enumerated\",values:[\"free\",l.idRegex.x.toString(),l.idRegex.y.toString()],editType:\"plot\"},side:{valType:\"enumerated\",values:[\"top\",\"bottom\",\"left\",\"right\"],editType:\"plot\"},overlaying:{valType:\"enumerated\",values:[\"free\",l.idRegex.x.toString(),l.idRegex.y.toString()],editType:\"plot\"},layer:{valType:\"enumerated\",values:[\"above traces\",\"below traces\"],dflt:\"above traces\",editType:\"plot\"},domain:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1,editType:\"plot\"},{valType:\"number\",min:0,max:1,editType:\"plot\"}],dflt:[0,1],editType:\"plot\"},position:{valType:\"number\",min:0,max:1,dflt:0,editType:\"plot\"},categoryorder:{valType:\"enumerated\",values:[\"trace\",\"category ascending\",\"category descending\",\"array\",\"total ascending\",\"total descending\",\"min ascending\",\"min descending\",\"max ascending\",\"max descending\",\"sum ascending\",\"sum descending\",\"mean ascending\",\"mean descending\",\"median ascending\",\"median descending\"],dflt:\"trace\",editType:\"calc\"},categoryarray:{valType:\"data_array\",editType:\"calc\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"calc\",_deprecated:{autotick:{valType:\"boolean\",editType:\"ticks\"},title:{valType:\"string\",editType:\"ticks\"},titlefont:n({editType:\"ticks\"})}}},{\"../../components/color/attributes\":591,\"../../components/drawing/attributes\":612,\"../../constants/docs\":688,\"../../lib/extend\":708,\"../../plot_api/plot_template\":755,\"../font_attributes\":791,\"./constants\":771}],778:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/color\"),i=t(\"../../plot_api/plot_template\"),o=t(\"../layout_attributes\"),s=t(\"./layout_attributes\"),l=t(\"./type_defaults\"),c=t(\"./axis_defaults\"),u=t(\"./constraints\").handleConstraintDefaults,h=t(\"./position_defaults\"),f=t(\"./axis_ids\"),p=f.id2name,d=f.name2id,g=t(\"./constants\").AX_ID_PATTERN,v=t(\"../../registry\"),m=v.traceIs,y=v.getComponentMethod;function x(t,e,r){Array.isArray(t[e])?t[e].push(r):t[e]=[r]}e.exports=function(t,e,r){var f,v,b={},_={},w={},k={},T={},M={},A={},S={},E={},L={};for(f=0;f<r.length;f++){var C=r[f];if(m(C,\"cartesian\")||m(C,\"gl2d\")){var P,O;if(C.xaxis)P=p(C.xaxis),x(b,P,C);else if(C.xaxes)for(v=0;v<C.xaxes.length;v++)x(b,p(C.xaxes[v]),C);if(C.yaxis)O=p(C.yaxis),x(b,O,C);else if(C.yaxes)for(v=0;v<C.yaxes.length;v++)x(b,p(C.yaxes[v]),C);if(\"funnel\"===C.type?\"h\"===C.orientation?(P&&(_[P]=!0),O&&(A[O]=!0)):O&&(w[O]=!0):\"image\"===C.type?(O&&(S[O]=!0),P&&(S[P]=!0)):(O&&(T[O]=!0,M[O]=!0),m(C,\"carpet\")&&(\"carpet\"!==C.type||C._cheater)||P&&(k[P]=!0)),\"carpet\"===C.type&&C._cheater&&P&&(_[P]=!0),m(C,\"2dMap\")&&(E[P]=!0,E[O]=!0),m(C,\"oriented\"))L[\"h\"===C.orientation?O:P]=!0}}var z=e._subplots,I=z.xaxis,D=z.yaxis,R=n.simpleMap(I,p),F=n.simpleMap(D,p),B=R.concat(F),N=a.background;I.length&&D.length&&(N=n.coerce(t,e,o,\"plot_bgcolor\"));var j,V,U,q,H,G=a.combine(N,e.paper_bgcolor);function Y(){var t=b[j]||[];H._traceIndices=t.map(function(t){return t._expandedIndex}),H._annIndices=[],H._shapeIndices=[],H._imgIndices=[],H._subplotsWith=[],H._counterAxes=[],H._name=H._attr=j,H._id=V}function W(t,e){return n.coerce(q,H,s,t,e)}function X(t,e){return n.coerce2(q,H,s,t,e)}function Z(t){return\"x\"===t?D:I}function J(e,r){for(var n=\"x\"===e?R:F,a=[],i=0;i<n.length;i++){var o=n[i];o===r||(t[o]||{}).overlaying||a.push(d(o))}return a}var K={x:Z(\"x\"),y:Z(\"y\")},Q=K.x.concat(K.y),$={},tt=[];function et(){var t=q.matches;g.test(t)&&-1===Q.indexOf(t)&&($[t]=q.type,tt=Object.keys($))}for(f=0;f<B.length;f++){j=B[f],V=d(j),U=j.charAt(0),n.isPlainObject(t[j])||(t[j]={}),q=t[j],H=i.newContainer(e,j,U+\"axis\"),Y();var rt=\"x\"===U&&!k[j]&&_[j]||\"y\"===U&&!T[j]&&w[j],nt=\"y\"===U&&(!M[j]&&A[j]||S[j]),at={letter:U,font:e.font,outerTicks:E[j],showGrid:!L[j],data:b[j]||[],bgColor:G,calendar:e.calendar,automargin:!0,visibleDflt:rt,reverseDflt:nt,splomStash:((e._splomAxes||{})[U]||{})[V]};W(\"uirevision\",e.uirevision),l(q,H,W,at),c(q,H,W,at,e);var it=X(\"spikecolor\"),ot=X(\"spikethickness\"),st=X(\"spikedash\"),lt=X(\"spikemode\"),ct=X(\"spikesnap\");W(\"showspikes\",!!(it||ot||st||lt||ct))||(delete H.spikecolor,delete H.spikethickness,delete H.spikedash,delete H.spikemode,delete H.spikesnap),h(q,H,W,{letter:U,counterAxes:K[U],overlayableAxes:J(U,j),grid:e.grid}),W(\"title.standoff\"),et(),H._input=q}for(f=0;f<tt.length;){V=tt[f++],U=(j=p(V)).charAt(0),n.isPlainObject(t[j])||(t[j]={}),q=t[j],H=i.newContainer(e,j,U+\"axis\"),Y();var ut={letter:U,font:e.font,outerTicks:E[j],showGrid:!L[j],data:[],bgColor:G,calendar:e.calendar,automargin:!0,visibleDflt:!1,reverseDflt:!1,splomStash:((e._splomAxes||{})[U]||{})[V]};W(\"uirevision\",e.uirevision),H.type=$[V]||\"linear\",c(q,H,W,ut,e),h(q,H,W,{letter:U,counterAxes:K[U],overlayableAxes:J(U,j),grid:e.grid}),W(\"fixedrange\"),et(),H._input=q}var ht=y(\"rangeslider\",\"handleDefaults\"),ft=y(\"rangeselector\",\"handleDefaults\");for(f=0;f<R.length;f++)j=R[f],q=t[j],H=e[j],ht(t,e,j),\"date\"===H.type&&ft(q,H,e,F,H.calendar),W(\"fixedrange\");for(f=0;f<F.length;f++){j=F[f],q=t[j],H=e[j];var pt=e[p(H.anchor)];W(\"fixedrange\",y(\"rangeslider\",\"isVisible\")(pt))}var dt=e._axisConstraintGroups=[],gt=e._axisMatchGroups=[],vt=Q.concat(tt),mt=B.concat(n.simpleMap(tt,p));for(f=0;f<mt.length;f++){var yt,xt;U=(j=mt[f]).charAt(0),q=t[j],H=e[j],yt=\"y\"===U&&!q.hasOwnProperty(\"scaleanchor\")&&S[j]?H.anchor:void 0,xt=!q.hasOwnProperty(\"constrain\")&&S[j]?\"domain\":void 0,u(q,H,W,{allAxisIds:vt,layoutOut:e,scaleanchorDflt:yt,constrainDflt:xt})}for(f=0;f<gt.length;f++){var bt=gt[f],_t=null,wt=null;for(V in bt)(H=e[p(V)]).matches||(_t=H.range,wt=H.autorange);if(null===_t||null===wt)for(V in bt){_t=(H=e[p(V)]).range,wt=H.autorange;break}for(V in bt)(H=e[p(V)]).matches&&(H.range=_t.slice(),H.autorange=wt),H._matchGroup=bt;if(dt.length)for(V in bt)for(v=0;v<dt.length;v++){var kt=dt[v];for(var Tt in kt)V===Tt&&(n.warn(\"Axis \"+Tt+\" is set with both a *scaleanchor* and *matches* constraint; ignoring the scale constraint.\"),delete kt[Tt],Object.keys(kt).length<2&&dt.splice(v,1))}}}},{\"../../components/color\":592,\"../../lib\":717,\"../../plot_api/plot_template\":755,\"../../registry\":846,\"../layout_attributes\":817,\"./axis_defaults\":767,\"./axis_ids\":768,\"./constants\":771,\"./constraints\":772,\"./layout_attributes\":777,\"./position_defaults\":780,\"./type_defaults\":788}],779:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,a=t(\"../../components/color/attributes\").lightFraction,i=t(\"../../lib\");e.exports=function(t,e,r,o){var s=(o=o||{}).dfltColor;function l(r,n){return i.coerce2(t,e,o.attributes,r,n)}var c=l(\"linecolor\",s),u=l(\"linewidth\");r(\"showline\",o.showLine||!!c||!!u)||(delete e.linecolor,delete e.linewidth);var h=l(\"gridcolor\",n(s,o.bgColor,o.blend||a).toRgbString()),f=l(\"gridwidth\");if(r(\"showgrid\",o.showGrid||!!h||!!f)||(delete e.gridcolor,delete e.gridwidth),!o.noZeroLine){var p=l(\"zerolinecolor\",s),d=l(\"zerolinewidth\");r(\"zeroline\",o.showGrid||!!p||!!d)||(delete e.zerolinecolor,delete e.zerolinewidth)}}},{\"../../components/color/attributes\":591,\"../../lib\":717,tinycolor2:536}],780:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib\");e.exports=function(t,e,r,i){var o,s,l,c,u=i.counterAxes||[],h=i.overlayableAxes||[],f=i.letter,p=i.grid;p&&(s=p._domains[f][p._axisMap[e._id]],o=p._anchors[e._id],s&&(l=p[f+\"side\"].split(\" \")[0],c=p.domain[f][\"right\"===l||\"top\"===l?1:0])),s=s||[0,1],o=o||(n(t.position)?\"free\":u[0]||\"free\"),l=l||(\"x\"===f?\"bottom\":\"left\"),c=c||0,\"free\"===a.coerce(t,e,{anchor:{valType:\"enumerated\",values:[\"free\"].concat(u),dflt:o}},\"anchor\")&&r(\"position\",c),a.coerce(t,e,{side:{valType:\"enumerated\",values:\"x\"===f?[\"bottom\",\"top\"]:[\"left\",\"right\"],dflt:l}},\"side\");var d=!1;if(h.length&&(d=a.coerce(t,e,{overlaying:{valType:\"enumerated\",values:[!1].concat(h),dflt:!1}},\"overlaying\")),!d){var g=r(\"domain\",s);g[0]>g[1]-1/4096&&(e.domain=s),a.noneOrAll(t.domain,e.domain,s)}return r(\"layer\"),e}},{\"../../lib\":717,\"fast-isnumeric\":228}],781:[function(t,e,r){\"use strict\";var n=t(\"../../constants/alignment\").FROM_BL;e.exports=function(t,e,r){void 0===r&&(r=n[t.constraintoward||\"center\"]);var a=[t.r2l(t.range[0]),t.r2l(t.range[1])],i=a[0]+(a[1]-a[0])*r;t.range=t._input.range=[t.l2r(i+(a[0]-i)*e),t.l2r(i+(a[1]-i)*e)]}},{\"../../constants/alignment\":686}],782:[function(t,e,r){\"use strict\";var n=t(\"polybooljs\"),a=t(\"../../registry\"),i=t(\"../../components/color\"),o=t(\"../../components/fx\"),s=t(\"../../lib\"),l=t(\"../../lib/polygon\"),c=t(\"../../lib/throttle\"),u=t(\"../../components/fx/helpers\").makeEventData,h=t(\"./axis_ids\").getFromId,f=t(\"../../lib/clear_gl_canvases\"),p=t(\"../../plot_api/subroutines\").redrawReglTraces,d=t(\"./constants\"),g=d.MINSELECT,v=l.filter,m=l.tester;function y(t){return t._id}function x(t,e,r,n,a,i,o){var s,l,c,u,h,f,p,d,g,v=e._hoverdata,m=e._fullLayout.clickmode.indexOf(\"event\")>-1,y=[];if(function(t){return t&&Array.isArray(t)&&!0!==t[0].hoverOnBox}(v)){k(t,e,i);var x=function(t,e){var r,n,a=t[0],i=-1,o=[];for(n=0;n<e.length;n++)if(r=e[n],a.fullData._expandedIndex===r.cd[0].trace._expandedIndex){if(!0===a.hoverOnBox)break;void 0!==a.pointNumber?i=a.pointNumber:void 0!==a.binNumber&&(i=a.binNumber,o=a.pointNumbers);break}return{pointNumber:i,pointNumbers:o,searchInfo:r}}(v,s=M(e,r,n,a));if(x.pointNumbers.length>0?function(t,e){var r,n,a,i=[];for(a=0;a<t.length;a++)(r=t[a]).cd[0].trace.selectedpoints&&r.cd[0].trace.selectedpoints.length>0&&i.push(r);if(1===i.length&&i[0]===e.searchInfo&&(n=e.searchInfo.cd[0].trace).selectedpoints.length===e.pointNumbers.length){for(a=0;a<e.pointNumbers.length;a++)if(n.selectedpoints.indexOf(e.pointNumbers[a])<0)return!1;return!0}return!1}(s,x):function(t){var e,r,n,a=0;for(n=0;n<t.length;n++)if(e=t[n],(r=e.cd[0].trace).selectedpoints){if(r.selectedpoints.length>1)return!1;if((a+=r.selectedpoints.length)>1)return!1}return 1===a}(s)&&(f=S(x))){for(o&&o.remove(),g=0;g<s.length;g++)(l=s[g])._module.selectPoints(l,!1);E(e,s),T(i),m&&e.emit(\"plotly_deselect\",null)}else{for(p=t.shiftKey&&(void 0!==f?f:S(x)),c=function(t,e,r){return{pointNumber:t,searchInfo:e,subtract:r}}(x.pointNumber,x.searchInfo,p),u=w(i.selectionDefs.concat([c])),g=0;g<s.length;g++)if(h=L(s[g]._module.selectPoints(s[g],u),s[g]),y.length)for(var b=0;b<h.length;b++)y.push(h[b]);else y=h;E(e,s,d={points:y}),c&&i&&i.selectionDefs.push(c),o&&A(i.mergedPolygons,o),m&&e.emit(\"plotly_selected\",d)}}}function b(t){return\"pointNumber\"in t&&\"searchInfo\"in t}function _(t){return{xmin:0,xmax:0,ymin:0,ymax:0,pts:[],contains:function(e,r,n,a){var i=t.searchInfo.cd[0].trace._expandedIndex;return a.cd[0].trace._expandedIndex===i&&n===t.pointNumber},isRect:!1,degenerate:!1,subtract:t.subtract}}function w(t){for(var e=[],r=b(t[0])?0:t[0][0][0],n=r,a=b(t[0])?0:t[0][0][1],i=a,o=0;o<t.length;o++)if(b(t[o]))e.push(_(t[o]));else{var s=l.tester(t[o]);s.subtract=t[o].subtract,e.push(s),r=Math.min(r,s.xmin),n=Math.max(n,s.xmax),a=Math.min(a,s.ymin),i=Math.max(i,s.ymax)}return{xmin:r,xmax:n,ymin:a,ymax:i,pts:[],contains:function(t,r,n,a){for(var i=!1,o=0;o<e.length;o++)e[o].contains(t,r,n,a)&&(i=!1===e[o].subtract);return i},isRect:!1,degenerate:!1}}function k(t,e,r){var n=e._fullLayout,a=r.plotinfo,i=n._lastSelectedSubplot&&n._lastSelectedSubplot===a.id,o=t.shiftKey||t.altKey;i&&o&&a.selection&&a.selection.selectionDefs&&!r.selectionDefs?(r.selectionDefs=a.selection.selectionDefs,r.mergedPolygons=a.selection.mergedPolygons):o&&a.selection||T(r),i||(C(e),n._lastSelectedSubplot=a.id)}function T(t){var e=t.plotinfo;e.selection={},e.selection.selectionDefs=t.selectionDefs=[],e.selection.mergedPolygons=t.mergedPolygons=[]}function M(t,e,r,n){var a,i,o,s=[],l=e.map(y),c=r.map(y);for(o=0;o<t.calcdata.length;o++)if(!0===(i=(a=t.calcdata[o])[0].trace).visible&&i._module&&i._module.selectPoints)if(!n||i.subplot!==n&&i.geo!==n)if(\"splom\"===i.type&&i._xaxes[l[0]]&&i._yaxes[c[0]]){var u=p(i._module,a,e[0],r[0]);u.scene=t._fullLayout._splomScenes[i.uid],s.push(u)}else if(\"sankey\"===i.type){var f=p(i._module,a,e[0],r[0]);s.push(f)}else{if(-1===l.indexOf(i.xaxis))continue;if(-1===c.indexOf(i.yaxis))continue;s.push(p(i._module,a,h(t,i.xaxis),h(t,i.yaxis)))}else s.push(p(i._module,a,e[0],r[0]));return s;function p(t,e,r,n){return{_module:t,cd:e,xaxis:r,yaxis:n}}}function A(t,e){var r,n,a=[];for(r=0;r<t.length;r++){var i=t[r];a.push(i.join(\"L\")+\"L\"+i[0])}n=t.length>0?\"M\"+a.join(\"M\")+\"Z\":\"M0,0Z\",e.attr(\"d\",n)}function S(t){var e=t.searchInfo.cd[0].trace,r=t.pointNumber,n=t.pointNumbers,a=n.length>0?n[0]:r;return!!e.selectedpoints&&e.selectedpoints.indexOf(a)>-1}function E(t,e,r){var n,i,o,s;for(n=0;n<e.length;n++){var l=e[n].cd[0].trace._fullInput,c=t._fullLayout._tracePreGUI[l.uid]||{};void 0===c.selectedpoints&&(c.selectedpoints=l._input.selectedpoints||null)}if(r){var u=r.points||[];for(n=0;n<e.length;n++)(s=e[n].cd[0].trace)._input.selectedpoints=s._fullInput.selectedpoints=[],s._fullInput!==s&&(s.selectedpoints=[]);for(n=0;n<u.length;n++){var h=u[n],d=h.data,g=h.fullData;h.pointIndices?([].push.apply(d.selectedpoints,h.pointIndices),s._fullInput!==s&&[].push.apply(g.selectedpoints,h.pointIndices)):(d.selectedpoints.push(h.pointIndex),s._fullInput!==s&&g.selectedpoints.push(h.pointIndex))}}else for(n=0;n<e.length;n++)delete(s=e[n].cd[0].trace).selectedpoints,delete s._input.selectedpoints,s._fullInput!==s&&delete s._fullInput.selectedpoints;var v=!1;for(n=0;n<e.length;n++){s=(o=(i=e[n]).cd)[0].trace,a.traceIs(s,\"regl\")&&(v=!0);var m=i._module,y=m.styleOnSelect||m.style;y&&(y(t,o,o[0].node3),o[0].nodeRangePlot3&&y(t,o,o[0].nodeRangePlot3))}v&&(f(t),p(t))}function L(t,e){if(Array.isArray(t))for(var r=e.cd,n=e.cd[0].trace,a=0;a<t.length;a++)t[a]=u(t[a],n,r);return t}function C(t){var e=(t._fullLayout||{})._zoomlayer;e&&e.selectAll(\".select-outline\").remove()}e.exports={prepSelect:function(t,e,r,a,l){var u,h,f,p,y,b,_,S=a.gd,C=S._fullLayout,P=C._zoomlayer,O=a.element.getBoundingClientRect(),z=a.plotinfo,I=z.xaxis._offset,D=z.yaxis._offset,R=e-O.left,F=r-O.top,B=R,N=F,j=\"M\"+R+\",\"+F,V=a.xaxes[0]._length,U=a.yaxes[0]._length,q=a.xaxes.concat(a.yaxes),H=t.altKey;k(t,S,a),\"lasso\"===l&&(u=v([[R,F]],d.BENDPX));var G=P.selectAll(\"path.select-outline-\"+z.id).data([1,2]);G.enter().append(\"path\").attr(\"class\",function(t){return\"select-outline select-outline-\"+t+\" select-outline-\"+z.id}).attr(\"transform\",\"translate(\"+I+\", \"+D+\")\").attr(\"d\",j+\"Z\");var Y,W=P.append(\"path\").attr(\"class\",\"zoombox-corners\").style({fill:i.background,stroke:i.defaultLine,\"stroke-width\":1}).attr(\"transform\",\"translate(\"+I+\", \"+D+\")\").attr(\"d\",\"M0,0Z\"),X=C._uid+d.SELECTID,Z=[],J=M(S,a.xaxes,a.yaxes,a.subplot);function K(t,e){return\"log\"===t.type?t.p2d(e):t.p2r(e)}function Q(t){var e=\"y\"===t._id.charAt(0)?1:0;return function(r){return K(t,r[e])}}function $(t,e){return t-e}Y=z.fillRangeItems?z.fillRangeItems:\"select\"===l?function(t,e){var r=t.range={};for(y=0;y<q.length;y++){var n=q[y],a=n._id.charAt(0);r[n._id]=[K(n,e[a+\"min\"]),K(n,e[a+\"max\"])].sort($)}}:function(t,e,r){var n=t.lassoPoints={};for(y=0;y<q.length;y++){var a=q[y];n[a._id]=r.filtered.map(Q(a))}},a.moveFn=function(t,e){B=Math.max(0,Math.min(V,t+R)),N=Math.max(0,Math.min(U,e+F));var r=Math.abs(B-R),i=Math.abs(N-F);if(\"select\"===l){var o=C.selectdirection;\"h\"===(o=\"any\"===C.selectdirection?i<Math.min(.6*r,g)?\"h\":r<Math.min(.6*i,g)?\"v\":\"d\":C.selectdirection)?((p=[[R,0],[R,U],[B,U],[B,0]]).xmin=Math.min(R,B),p.xmax=Math.max(R,B),p.ymin=Math.min(0,U),p.ymax=Math.max(0,U),W.attr(\"d\",\"M\"+p.xmin+\",\"+(F-g)+\"h-4v\"+2*g+\"h4ZM\"+(p.xmax-1)+\",\"+(F-g)+\"h4v\"+2*g+\"h-4Z\")):\"v\"===o?((p=[[0,F],[0,N],[V,N],[V,F]]).xmin=Math.min(0,V),p.xmax=Math.max(0,V),p.ymin=Math.min(F,N),p.ymax=Math.max(F,N),W.attr(\"d\",\"M\"+(R-g)+\",\"+p.ymin+\"v-4h\"+2*g+\"v4ZM\"+(R-g)+\",\"+(p.ymax-1)+\"v4h\"+2*g+\"v-4Z\")):\"d\"===o&&((p=[[R,F],[R,N],[B,N],[B,F]]).xmin=Math.min(R,B),p.xmax=Math.max(R,B),p.ymin=Math.min(F,N),p.ymax=Math.max(F,N),W.attr(\"d\",\"M0,0Z\"))}else\"lasso\"===l&&(u.addPt([B,N]),p=u.filtered);a.selectionDefs&&a.selectionDefs.length?(f=function(t,e,r){return r?n.difference({regions:t,inverted:!1},{regions:[e],inverted:!1}).regions:n.union({regions:t,inverted:!1},{regions:[e],inverted:!1}).regions}(a.mergedPolygons,p,H),p.subtract=H,h=w(a.selectionDefs.concat([p]))):(f=[p],h=m(p)),A(f,G),c.throttle(X,d.SELECTDELAY,function(){var t;Z=[];var e,r=[];for(y=0;y<J.length;y++)if(e=(b=J[y])._module.selectPoints(b,h),r.push(e),t=L(e,b),Z.length)for(var n=0;n<t.length;n++)Z.push(t[n]);else Z=t;E(S,J,_={points:Z}),Y(_,p,u),a.gd.emit(\"plotly_selecting\",_)})},a.clickFn=function(t,e){var r=C.clickmode;W.remove(),c.done(X).then(function(){if(c.clear(X),2===t){for(G.remove(),y=0;y<J.length;y++)(b=J[y])._module.selectPoints(b,!1);E(S,J),T(a),S.emit(\"plotly_deselect\",null)}else r.indexOf(\"select\")>-1&&x(e,S,a.xaxes,a.yaxes,a.subplot,a,G),\"event\"===r&&S.emit(\"plotly_selected\",void 0);o.click(S,e)}).catch(s.error)},a.doneFn=function(){W.remove(),c.done(X).then(function(){c.clear(X),a.gd.emit(\"plotly_selected\",_),p&&a.selectionDefs&&(p.subtract=H,a.selectionDefs.push(p),a.mergedPolygons.length=0,[].push.apply(a.mergedPolygons,f)),a.doneFnCompleted&&a.doneFnCompleted(Z)}).catch(s.error)}},clearSelect:C,selectOnClick:x}},{\"../../components/color\":592,\"../../components/fx\":630,\"../../components/fx/helpers\":627,\"../../lib\":717,\"../../lib/clear_gl_canvases\":702,\"../../lib/polygon\":729,\"../../lib/throttle\":742,\"../../plot_api/subroutines\":756,\"../../registry\":846,\"./axis_ids\":768,\"./constants\":771,polybooljs:475}],783:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"fast-isnumeric\"),i=t(\"../../lib\"),o=i.cleanNumber,s=i.ms2DateTime,l=i.dateTime2ms,c=i.ensureNumber,u=i.isArrayOrTypedArray,h=t(\"../../constants/numerical\"),f=h.FP_SAFE,p=h.BADNUM,d=h.LOG_CLIP,g=t(\"./constants\"),v=t(\"./axis_ids\");function m(t){return Math.pow(10,t)}function y(t){return null!=t}e.exports=function(t,e){e=e||{};var r=t._id||\"x\",h=r.charAt(0);function x(e,r){if(e>0)return Math.log(e)/Math.LN10;if(e<=0&&r&&t.range&&2===t.range.length){var n=t.range[0],a=t.range[1];return.5*(n+a-2*d*Math.abs(n-a))}return p}function b(e,r,n){var o=l(e,n||t.calendar);if(o===p){if(!a(e))return p;e=+e;var s=Math.floor(10*i.mod(e+.05,1)),c=Math.round(e-s/10);o=l(new Date(c))+s/10}return o}function _(e,r,n){return s(e,r,n||t.calendar)}function w(e){return t._categories[Math.round(e)]}function k(e){if(y(e)){if(void 0===t._categoriesMap&&(t._categoriesMap={}),void 0!==t._categoriesMap[e])return t._categoriesMap[e];t._categories.push(\"number\"==typeof e?String(e):e);var r=t._categories.length-1;return t._categoriesMap[e]=r,r}return p}function T(e){if(t._categoriesMap)return t._categoriesMap[e]}function M(t){var e=T(t);return void 0!==e?e:a(t)?+t:void 0}function A(e){return a(e)?n.round(t._b+t._m*e,2):p}function S(e){return(e-t._b)/t._m}t.c2l=\"log\"===t.type?x:c,t.l2c=\"log\"===t.type?m:c,t.l2p=A,t.p2l=S,t.c2p=\"log\"===t.type?function(t,e){return A(x(t,e))}:A,t.p2c=\"log\"===t.type?function(t){return m(S(t))}:S,-1!==[\"linear\",\"-\"].indexOf(t.type)?(t.d2r=t.r2d=t.d2c=t.r2c=t.d2l=t.r2l=o,t.c2d=t.c2r=t.l2d=t.l2r=c,t.d2p=t.r2p=function(e){return t.l2p(o(e))},t.p2d=t.p2r=S,t.cleanPos=c):\"log\"===t.type?(t.d2r=t.d2l=function(t,e){return x(o(t),e)},t.r2d=t.r2c=function(t){return m(o(t))},t.d2c=t.r2l=o,t.c2d=t.l2r=c,t.c2r=x,t.l2d=m,t.d2p=function(e,r){return t.l2p(t.d2r(e,r))},t.p2d=function(t){return m(S(t))},t.r2p=function(e){return t.l2p(o(e))},t.p2r=S,t.cleanPos=c):\"date\"===t.type?(t.d2r=t.r2d=i.identity,t.d2c=t.r2c=t.d2l=t.r2l=b,t.c2d=t.c2r=t.l2d=t.l2r=_,t.d2p=t.r2p=function(e,r,n){return t.l2p(b(e,0,n))},t.p2d=t.p2r=function(t,e,r){return _(S(t),e,r)},t.cleanPos=function(e){return i.cleanDate(e,p,t.calendar)}):\"category\"===t.type?(t.d2c=t.d2l=k,t.r2d=t.c2d=t.l2d=w,t.d2r=t.d2l_noadd=M,t.r2c=function(e){var r=M(e);return void 0!==r?r:t.fraction2r(.5)},t.l2r=t.c2r=c,t.r2l=M,t.d2p=function(e){return t.l2p(t.r2c(e))},t.p2d=function(t){return w(S(t))},t.r2p=t.d2p,t.p2r=S,t.cleanPos=function(t){return\"string\"==typeof t&&\"\"!==t?t:c(t)}):\"multicategory\"===t.type&&(t.r2d=t.c2d=t.l2d=w,t.d2r=t.d2l_noadd=M,t.r2c=function(e){var r=M(e);return void 0!==r?r:t.fraction2r(.5)},t.r2c_just_indices=T,t.l2r=t.c2r=c,t.r2l=M,t.d2p=function(e){return t.l2p(t.r2c(e))},t.p2d=function(t){return w(S(t))},t.r2p=t.d2p,t.p2r=S,t.cleanPos=function(t){return Array.isArray(t)||\"string\"==typeof t&&\"\"!==t?t:c(t)},t.setupMultiCategory=function(n){var a,o,s=t._traceIndices,l=e._axisMatchGroups;if(l&&l.length&&0===t._categories.length)for(a=0;a<l.length;a++){var c=l[a];if(c[r])for(var f in c)if(f!==r){var p=e[v.id2name(f)];s=s.concat(p._traceIndices)}}var d=[[0,{}],[0,{}]],g=[];for(a=0;a<s.length;a++){var m=n[s[a]];if(h in m){var x=m[h],b=m._length||i.minRowLength(x);if(u(x[0])&&u(x[1]))for(o=0;o<b;o++){var _=x[0][o],w=x[1][o];y(_)&&y(w)&&(g.push([_,w]),_ in d[0][1]||(d[0][1][_]=d[0][0]++),w in d[1][1]||(d[1][1][w]=d[1][0]++))}}}for(g.sort(function(t,e){var r=d[0][1],n=r[t[0]]-r[e[0]];if(n)return n;var a=d[1][1];return a[t[1]]-a[e[1]]}),a=0;a<g.length;a++)k(g[a])}),t.fraction2r=function(e){var r=t.r2l(t.range[0]),n=t.r2l(t.range[1]);return t.l2r(r+e*(n-r))},t.r2fraction=function(e){var r=t.r2l(t.range[0]),n=t.r2l(t.range[1]);return(t.r2l(e)-r)/(n-r)},t.cleanRange=function(e,r){r||(r={}),e||(e=\"range\");var n,o,s=i.nestedProperty(t,e).get();if(o=(o=\"date\"===t.type?i.dfltRange(t.calendar):\"y\"===h?g.DFLTRANGEY:r.dfltRange||g.DFLTRANGEX).slice(),\"tozero\"!==t.rangemode&&\"nonnegative\"!==t.rangemode||(o[0]=0),s&&2===s.length)for(\"date\"!==t.type||t.autorange||(s[0]=i.cleanDate(s[0],p,t.calendar),s[1]=i.cleanDate(s[1],p,t.calendar)),n=0;n<2;n++)if(\"date\"===t.type){if(!i.isDateTime(s[n],t.calendar)){t[e]=o;break}if(t.r2l(s[0])===t.r2l(s[1])){var l=i.constrain(t.r2l(s[0]),i.MIN_MS+1e3,i.MAX_MS-1e3);s[0]=t.l2r(l-1e3),s[1]=t.l2r(l+1e3);break}}else{if(!a(s[n])){if(!a(s[1-n])){t[e]=o;break}s[n]=s[1-n]*(n?10:.1)}if(s[n]<-f?s[n]=-f:s[n]>f&&(s[n]=f),s[0]===s[1]){var c=Math.max(1,Math.abs(1e-6*s[0]));s[0]-=c,s[1]+=c}}else i.nestedProperty(t,e).set(o)},t.setScale=function(r){var n=e._size;if(t.overlaying){var a=v.getFromId({_fullLayout:e},t.overlaying);t.domain=a.domain}var i=r&&t._r?\"_r\":\"range\",o=t.calendar;t.cleanRange(i);var s=t.r2l(t[i][0],o),l=t.r2l(t[i][1],o);if(\"y\"===h?(t._offset=n.t+(1-t.domain[1])*n.h,t._length=n.h*(t.domain[1]-t.domain[0]),t._m=t._length/(s-l),t._b=-t._m*l):(t._offset=n.l+t.domain[0]*n.w,t._length=n.w*(t.domain[1]-t.domain[0]),t._m=t._length/(l-s),t._b=-t._m*s),!isFinite(t._m)||!isFinite(t._b)||t._length<0)throw e._replotting=!1,new Error(\"Something went wrong with axis scaling\")},t.makeCalcdata=function(e,r){var n,a,o,s,l=t.type,c=\"date\"===l&&e[r+\"calendar\"];if(r in e){if(n=e[r],s=e._length||i.minRowLength(n),i.isTypedArray(n)&&(\"linear\"===l||\"log\"===l)){if(s===n.length)return n;if(n.subarray)return n.subarray(0,s)}if(\"multicategory\"===l)return function(t,e){for(var r=new Array(e),n=0;n<e;n++){var a=(t[0]||[])[n],i=(t[1]||[])[n];r[n]=T([a,i])}return r}(n,s);for(a=new Array(s),o=0;o<s;o++)a[o]=t.d2c(n[o],0,c)}else{var u=r+\"0\"in e?t.d2c(e[r+\"0\"],0,c):0,h=e[\"d\"+r]?Number(e[\"d\"+r]):1;for(n=e[{x:\"y\",y:\"x\"}[r]],s=e._length||n.length,a=new Array(s),o=0;o<s;o++)a[o]=u+o*h}return a},t.isValidRange=function(e){return Array.isArray(e)&&2===e.length&&a(t.r2l(e[0]))&&a(t.r2l(e[1]))},t.isPtWithinRange=function(e,r){var n=t.c2l(e[h],null,r),a=t.r2l(t.range[0]),i=t.r2l(t.range[1]);return a<i?a<=n&&n<=i:i<=n&&n<=a},t.clearCalc=function(){var n=function(){t._categories=[],t._categoriesMap={}},a=e._axisMatchGroups;if(a&&a.length){for(var i=!1,o=0;o<a.length;o++){var s=a[o];if(s[r]){i=!0;var l=null,c=null;for(var u in s){var h=e[v.id2name(u)];if(h._categories){l=h._categories,c=h._categoriesMap;break}}l&&c?(t._categories=l,t._categoriesMap=c):n();break}}i||n()}else n();if(t._initialCategories)for(var f=0;f<t._initialCategories.length;f++)k(t._initialCategories[f])},t.sortByInitialCategories=function(){var n=[];if(t._categories=[],t._categoriesMap={},t._initialCategories)for(var a=0;a<t._initialCategories.length;a++)k(t._initialCategories[a]);n=n.concat(t._traceIndices);var i=t._matchGroup;for(var o in i)if(r!==o){var s=e[v.id2name(o)];s._categories=t._categories,s._categoriesMap=t._categoriesMap,n=n.concat(s._traceIndices)}return n};var E=e._d3locale;\"date\"===t.type&&(t._dateFormat=E?E.timeFormat.utc:n.time.format.utc,t._extraFormat=e._extraFormat),t._separators=e.separators,t._numFormat=E?E.numberFormat:n.format,delete t._minDtick,delete t._forceTick0}},{\"../../constants/numerical\":693,\"../../lib\":717,\"./axis_ids\":768,\"./constants\":771,d3:165,\"fast-isnumeric\":228}],784:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./layout_attributes\"),i=t(\"../array_container_defaults\");function o(t){var e=[\"showexponent\",\"showtickprefix\",\"showticksuffix\"].filter(function(e){return void 0!==t[e]});if(e.every(function(r){return t[r]===t[e[0]]})||1===e.length)return t[e[0]]}function s(t,e){function r(r,i){return n.coerce(t,e,a.tickformatstops,r,i)}r(\"enabled\")&&(r(\"dtickrange\"),r(\"value\"))}e.exports=function(t,e,r,l,c,u){u&&1!==u.pass||function(t,e,r,n,a){var i=o(t);r(\"tickprefix\")&&r(\"showtickprefix\",i);r(\"ticksuffix\",a.tickSuffixDflt)&&r(\"showticksuffix\",i)}(t,0,r,0,c),u&&2!==u.pass||function(t,e,r,l,c){var u=o(t);r(\"tickprefix\")&&r(\"showtickprefix\",u);r(\"ticksuffix\",c.tickSuffixDflt)&&r(\"showticksuffix\",u);if(r(\"showticklabels\")){var h=c.font||{},f=e.color,p=f&&f!==a.color.dflt?f:h.color;if(n.coerceFont(r,\"tickfont\",{family:h.family,size:h.size,color:p}),r(\"tickangle\"),\"category\"!==l){var d=r(\"tickformat\"),g=t.tickformatstops;Array.isArray(g)&&g.length&&i(t,e,{name:\"tickformatstops\",inclusionAttr:\"enabled\",handleItemDefaults:s}),d||\"date\"===l||(r(\"showexponent\",u),r(\"exponentformat\"),r(\"separatethousands\"))}}}(t,e,r,l,c)}},{\"../../lib\":717,\"../array_container_defaults\":761,\"./layout_attributes\":777}],785:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./layout_attributes\");e.exports=function(t,e,r,i){var o=n.coerce2(t,e,a,\"ticklen\"),s=n.coerce2(t,e,a,\"tickwidth\"),l=n.coerce2(t,e,a,\"tickcolor\",e.color);r(\"ticks\",i.outerTicks||o||s||l?\"outside\":\"\")||(delete e.ticklen,delete e.tickwidth,delete e.tickcolor)}},{\"../../lib\":717,\"./layout_attributes\":777}],786:[function(t,e,r){\"use strict\";var n=t(\"./clean_ticks\");e.exports=function(t,e,r,a){var i;\"array\"!==t.tickmode||\"log\"!==a&&\"date\"!==a?i=r(\"tickmode\",Array.isArray(t.tickvals)?\"array\":t.dtick?\"linear\":\"auto\"):i=e.tickmode=\"auto\";if(\"auto\"===i)r(\"nticks\");else if(\"linear\"===i){var o=e.dtick=n.dtick(t.dtick,a);e.tick0=n.tick0(t.tick0,a,e.calendar,o)}else if(\"multicategory\"!==a){void 0===r(\"tickvals\")?e.tickmode=\"auto\":r(\"ticktext\")}}},{\"./clean_ticks\":770}],787:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../registry\"),i=t(\"../../lib\"),o=t(\"../../components/drawing\"),s=t(\"./axes\");e.exports=function(t,e,r,l){var c=t._fullLayout;if(0!==e.length){var u,h,f,p;l&&(u=l());var d=n.ease(r.easing);return t._transitionData._interruptCallbacks.push(function(){return window.cancelAnimationFrame(p),p=null,function(){for(var r={},n=0;n<e.length;n++){var i=e[n],o=i.plotinfo.xaxis,s=i.plotinfo.yaxis;i.xr0&&(r[o._name+\".range\"]=i.xr0.slice()),i.yr0&&(r[s._name+\".range\"]=i.yr0.slice())}return a.call(\"relayout\",t,r).then(function(){for(var t=0;t<e.length;t++)g(e[t].plotinfo)})}()}),h=Date.now(),p=window.requestAnimationFrame(function n(){f=Date.now();for(var i=Math.min(1,(f-h)/r.duration),o=d(i),s=0;s<e.length;s++)v(e[s],o);f-h>r.duration?(function(){for(var r={},n=0;n<e.length;n++){var i=e[n],o=i.plotinfo.xaxis,s=i.plotinfo.yaxis;i.xr1&&(r[o._name+\".range\"]=i.xr1.slice()),i.yr1&&(r[s._name+\".range\"]=i.yr1.slice())}u&&u(),a.call(\"relayout\",t,r).then(function(){for(var t=0;t<e.length;t++)g(e[t].plotinfo)})}(),p=window.cancelAnimationFrame(n)):p=window.requestAnimationFrame(n)}),Promise.resolve()}function g(t){var e=t.xaxis,r=t.yaxis;c._defs.select(\"#\"+t.clipId+\"> rect\").call(o.setTranslate,0,0).call(o.setScale,1,1),t.plot.call(o.setTranslate,e._offset,r._offset).call(o.setScale,1,1);var n=t.plot.selectAll(\".scatterlayer .trace\");n.selectAll(\".point\").call(o.setPointGroupScale,1,1),n.selectAll(\".textpoint\").call(o.setTextPointsScale,1,1),n.call(o.hideOutsideRangePoints,t)}function v(e,r){var n=e.plotinfo,a=n.xaxis,l=n.yaxis,c=a._length,u=l._length,h=!!e.xr1,f=!!e.yr1,p=[];if(h){var d=i.simpleMap(e.xr0,a.r2l),g=i.simpleMap(e.xr1,a.r2l),v=d[1]-d[0],m=g[1]-g[0];p[0]=(d[0]*(1-r)+r*g[0]-d[0])/(d[1]-d[0])*c,p[2]=c*(1-r+r*m/v),a.range[0]=a.l2r(d[0]*(1-r)+r*g[0]),a.range[1]=a.l2r(d[1]*(1-r)+r*g[1])}else p[0]=0,p[2]=c;if(f){var y=i.simpleMap(e.yr0,l.r2l),x=i.simpleMap(e.yr1,l.r2l),b=y[1]-y[0],_=x[1]-x[0];p[1]=(y[1]*(1-r)+r*x[1]-y[1])/(y[0]-y[1])*u,p[3]=u*(1-r+r*_/b),l.range[0]=a.l2r(y[0]*(1-r)+r*x[0]),l.range[1]=l.l2r(y[1]*(1-r)+r*x[1])}else p[1]=0,p[3]=u;s.drawOne(t,a,{skipTitle:!0}),s.drawOne(t,l,{skipTitle:!0}),s.redrawComponents(t,[a._id,l._id]);var w=h?c/p[2]:1,k=f?u/p[3]:1,T=h?p[0]:0,M=f?p[1]:0,A=h?p[0]/p[2]*c:0,S=f?p[1]/p[3]*u:0,E=a._offset-A,L=l._offset-S;n.clipRect.call(o.setTranslate,T,M).call(o.setScale,1/w,1/k),n.plot.call(o.setTranslate,E,L).call(o.setScale,w,k),o.setPointGroupScale(n.zoomScalePts,1/w,1/k),o.setTextPointsScale(n.zoomScaleTxt,1/w,1/k)}s.redrawComponents(t)}},{\"../../components/drawing\":613,\"../../lib\":717,\"../../registry\":846,\"./axes\":765,d3:165}],788:[function(t,e,r){\"use strict\";var n=t(\"../../registry\").traceIs,a=t(\"./axis_autotype\");function i(t){return{v:\"x\",h:\"y\"}[t.orientation||\"v\"]}function o(t,e){var r=i(t),a=n(t,\"box-violin\"),o=n(t._fullInput||{},\"candlestick\");return a&&!o&&e===r&&void 0===t[r]&&void 0===t[r+\"0\"]}e.exports=function(t,e,r,s){\"-\"===r(\"type\",(s.splomStash||{}).type)&&(!function(t,e){if(\"-\"!==t.type)return;var r,s=t._id,l=s.charAt(0);-1!==s.indexOf(\"scene\")&&(s=l);var c=function(t,e,r){for(var n=0;n<t.length;n++){var a=t[n];if(\"splom\"===a.type&&a._length>0&&(a[\"_\"+r+\"axes\"]||{})[e])return a;if((a[r+\"axis\"]||r)===e){if(o(a,r))return a;if((a[r]||[]).length||a[r+\"0\"])return a}}}(e,s,l);if(!c)return;if(\"histogram\"===c.type&&l==={v:\"y\",h:\"x\"}[c.orientation||\"v\"])return void(t.type=\"linear\");var u=l+\"calendar\",h=c[u],f={noMultiCategory:!n(c,\"cartesian\")||n(c,\"noMultiCategory\")};\"box\"===c.type&&c._hasPreCompStats&&l==={h:\"x\",v:\"y\"}[c.orientation||\"v\"]&&(f.noMultiCategory=!0);if(o(c,l)){var p=i(c),d=[];for(r=0;r<e.length;r++){var g=e[r];n(g,\"box-violin\")&&(g[l+\"axis\"]||l)===s&&(void 0!==g[p]?d.push(g[p][0]):void 0!==g.name?d.push(g.name):d.push(\"text\"),g[u]!==h&&(h=void 0))}t.type=a(d,h,f)}else if(\"splom\"===c.type){var v=c.dimensions,m=v[c._axesDim[s]];m.visible&&(t.type=a(m.values,h,f))}else t.type=a(c[l]||[c[l+\"0\"]],h,f)}(e,s.data),\"-\"===e.type?e.type=\"linear\":t.type=e.type)}},{\"../../registry\":846,\"./axis_autotype\":766}],789:[function(t,e,r){\"use strict\";var n=t(\"../registry\"),a=t(\"../lib\");function i(t,e,r){var n,i,o,s=!1;if(\"data\"===e.type)n=t._fullData[null!==e.traces?e.traces[0]:0];else{if(\"layout\"!==e.type)return!1;n=t._fullLayout}return i=a.nestedProperty(n,e.prop).get(),(o=r[e.type]=r[e.type]||{}).hasOwnProperty(e.prop)&&o[e.prop]!==i&&(s=!0),o[e.prop]=i,{changed:s,value:i}}function o(t,e){var r=[],n=e[0],i={};if(\"string\"==typeof n)i[n]=e[1];else{if(!a.isPlainObject(n))return r;i=n}return l(i,function(t,e,n){r.push({type:\"layout\",prop:t,value:n})},\"\",0),r}function s(t,e){var r,n,i,o,s=[];if(n=e[0],i=e[1],r=e[2],o={},\"string\"==typeof n)o[n]=i;else{if(!a.isPlainObject(n))return s;o=n,void 0===r&&(r=i)}return void 0===r&&(r=null),l(o,function(e,n,a){var i,o;if(Array.isArray(a)){o=a.slice();var l=Math.min(o.length,t.data.length);r&&(l=Math.min(l,r.length)),i=[];for(var c=0;c<l;c++)i[c]=r?r[c]:c}else o=a,i=r?r.slice():null;if(null===i)Array.isArray(o)&&(o=o[0]);else if(Array.isArray(i)){if(!Array.isArray(o)){var u=o;o=[];for(var h=0;h<i.length;h++)o[h]=u}o.length=Math.min(i.length,o.length)}s.push({type:\"data\",prop:e,traces:i,value:o})},\"\",0),s}function l(t,e,r,n){Object.keys(t).forEach(function(i){var o=t[i];if(\"_\"!==i[0]){var s=r+(n>0?\".\":\"\")+i;a.isPlainObject(o)?l(o,e,s,n+1):e(s,i,o)}})}r.manageCommandObserver=function(t,e,n,o){var s={},l=!0;e&&e._commandObserver&&(s=e._commandObserver),s.cache||(s.cache={}),s.lookupTable={};var c=r.hasSimpleAPICommandBindings(t,n,s.lookupTable);if(e&&e._commandObserver){if(c)return s;if(e._commandObserver.remove)return e._commandObserver.remove(),e._commandObserver=null,s}if(c){i(t,c,s.cache),s.check=function(){if(l){var e=i(t,c,s.cache);return e.changed&&o&&void 0!==s.lookupTable[e.value]&&(s.disable(),Promise.resolve(o({value:e.value,type:c.type,prop:c.prop,traces:c.traces,index:s.lookupTable[e.value]})).then(s.enable,s.enable)),e.changed}};for(var u=[\"plotly_relayout\",\"plotly_redraw\",\"plotly_restyle\",\"plotly_update\",\"plotly_animatingframe\",\"plotly_afterplot\"],h=0;h<u.length;h++)t._internalOn(u[h],s.check);s.remove=function(){for(var e=0;e<u.length;e++)t._removeInternalListener(u[e],s.check)}}else a.log(\"Unable to automatically bind plot updates to API command\"),s.lookupTable={},s.remove=function(){};return s.disable=function(){l=!1},s.enable=function(){l=!0},e&&(e._commandObserver=s),s},r.hasSimpleAPICommandBindings=function(t,e,n){var a,i,o=e.length;for(a=0;a<o;a++){var s,l=e[a],c=l.method,u=l.args;if(Array.isArray(u)||(u=[]),!c)return!1;var h=r.computeAPICommandBindings(t,c,u);if(1!==h.length)return!1;if(i){if((s=h[0]).type!==i.type)return!1;if(s.prop!==i.prop)return!1;if(Array.isArray(i.traces)){if(!Array.isArray(s.traces))return!1;s.traces.sort();for(var f=0;f<i.traces.length;f++)if(i.traces[f]!==s.traces[f])return!1}else if(s.prop!==i.prop)return!1}else i=h[0],Array.isArray(i.traces)&&i.traces.sort();var p=(s=h[0]).value;if(Array.isArray(p)){if(1!==p.length)return!1;p=p[0]}n&&(n[p]=a)}return i},r.executeAPICommand=function(t,e,r){if(\"skip\"===e)return Promise.resolve();var i=n.apiMethodRegistry[e],o=[t];Array.isArray(r)||(r=[]);for(var s=0;s<r.length;s++)o.push(r[s]);return i.apply(null,o).catch(function(t){return a.warn(\"API call to Plotly.\"+e+\" rejected.\",t),Promise.reject(t)})},r.computeAPICommandBindings=function(t,e,r){var n;switch(Array.isArray(r)||(r=[]),e){case\"restyle\":n=s(t,r);break;case\"relayout\":n=o(t,r);break;case\"update\":n=s(t,[r[0],r[2]]).concat(o(t,[r[1]]));break;case\"animate\":n=function(t,e){return Array.isArray(e[0])&&1===e[0].length&&-1!==[\"string\",\"number\"].indexOf(typeof e[0][0])?[{type:\"layout\",prop:\"_currentFrame\",value:e[0][0].toString()}]:[]}(0,r);break;default:n=[]}return n}},{\"../lib\":717,\"../registry\":846}],790:[function(t,e,r){\"use strict\";var n=t(\"../lib/extend\").extendFlat;r.attributes=function(t,e){e=e||{};var r={valType:\"info_array\",editType:(t=t||{}).editType,items:[{valType:\"number\",min:0,max:1,editType:t.editType},{valType:\"number\",min:0,max:1,editType:t.editType}],dflt:[0,1]},a=(t.name&&t.name,t.trace,e.description&&e.description,{x:n({},r,{}),y:n({},r,{}),editType:t.editType});return t.noGridCell||(a.row={valType:\"integer\",min:0,dflt:0,editType:t.editType},a.column={valType:\"integer\",min:0,dflt:0,editType:t.editType}),a},r.defaults=function(t,e,r,n){var a=n&&n.x||[0,1],i=n&&n.y||[0,1],o=e.grid;if(o){var s=r(\"domain.column\");void 0!==s&&(s<o.columns?a=o._domains.x[s]:delete t.domain.column);var l=r(\"domain.row\");void 0!==l&&(l<o.rows?i=o._domains.y[l]:delete t.domain.row)}var c=r(\"domain.x\",a),u=r(\"domain.y\",i);c[0]<c[1]||(t.domain.x=a.slice()),u[0]<u[1]||(t.domain.y=i.slice())}},{\"../lib/extend\":708}],791:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.editType,r=t.colorEditType;void 0===r&&(r=e);var n={family:{valType:\"string\",noBlank:!0,strict:!0,editType:e},size:{valType:\"number\",min:1,editType:e},color:{valType:\"color\",editType:r},editType:e};return t.arrayOk&&(n.family.arrayOk=!0,n.size.arrayOk=!0,n.color.arrayOk=!0),n}},{}],792:[function(t,e,r){\"use strict\";e.exports={_isLinkedToArray:\"frames_entry\",group:{valType:\"string\"},name:{valType:\"string\"},traces:{valType:\"any\"},baseframe:{valType:\"string\"},data:{valType:\"any\"},layout:{valType:\"any\"}}},{}],793:[function(t,e,r){\"use strict\";r.projNames={equirectangular:\"equirectangular\",mercator:\"mercator\",orthographic:\"orthographic\",\"natural earth\":\"naturalEarth\",kavrayskiy7:\"kavrayskiy7\",miller:\"miller\",robinson:\"robinson\",eckert4:\"eckert4\",\"azimuthal equal area\":\"azimuthalEqualArea\",\"azimuthal equidistant\":\"azimuthalEquidistant\",\"conic equal area\":\"conicEqualArea\",\"conic conformal\":\"conicConformal\",\"conic equidistant\":\"conicEquidistant\",gnomonic:\"gnomonic\",stereographic:\"stereographic\",mollweide:\"mollweide\",hammer:\"hammer\",\"transverse mercator\":\"transverseMercator\",\"albers usa\":\"albersUsa\",\"winkel tripel\":\"winkel3\",aitoff:\"aitoff\",sinusoidal:\"sinusoidal\"},r.axesNames=[\"lonaxis\",\"lataxis\"],r.lonaxisSpan={orthographic:180,\"azimuthal equal area\":360,\"azimuthal equidistant\":360,\"conic conformal\":180,gnomonic:160,stereographic:180,\"transverse mercator\":180,\"*\":360},r.lataxisSpan={\"conic conformal\":150,stereographic:179.5,\"*\":180},r.scopeDefaults={world:{lonaxisRange:[-180,180],lataxisRange:[-90,90],projType:\"equirectangular\",projRotate:[0,0,0]},usa:{lonaxisRange:[-180,-50],lataxisRange:[15,80],projType:\"albers usa\"},europe:{lonaxisRange:[-30,60],lataxisRange:[30,85],projType:\"conic conformal\",projRotate:[15,0,0],projParallels:[0,60]},asia:{lonaxisRange:[22,160],lataxisRange:[-15,55],projType:\"mercator\",projRotate:[0,0,0]},africa:{lonaxisRange:[-30,60],lataxisRange:[-40,40],projType:\"mercator\",projRotate:[0,0,0]},\"north america\":{lonaxisRange:[-180,-45],lataxisRange:[5,85],projType:\"conic conformal\",projRotate:[-100,0,0],projParallels:[29.5,45.5]},\"south america\":{lonaxisRange:[-100,-30],lataxisRange:[-60,15],projType:\"mercator\",projRotate:[0,0,0]}},r.clipPad=.001,r.precision=.1,r.landColor=\"#F0DC82\",r.waterColor=\"#3399FF\",r.locationmodeToLayer={\"ISO-3\":\"countries\",\"USA-states\":\"subunits\",\"country names\":\"countries\"},r.sphereSVG={type:\"Sphere\"},r.fillLayers={ocean:1,land:1,lakes:1},r.lineLayers={subunits:1,countries:1,coastlines:1,rivers:1,frame:1},r.layers=[\"bg\",\"ocean\",\"land\",\"lakes\",\"subunits\",\"countries\",\"coastlines\",\"rivers\",\"lataxis\",\"lonaxis\",\"frame\",\"backplot\",\"frontplot\"],r.layersForChoropleth=[\"bg\",\"ocean\",\"land\",\"subunits\",\"countries\",\"coastlines\",\"lataxis\",\"lonaxis\",\"frame\",\"backplot\",\"rivers\",\"lakes\",\"frontplot\"],r.layerNameToAdjective={ocean:\"ocean\",land:\"land\",lakes:\"lake\",subunits:\"subunit\",countries:\"country\",coastlines:\"coastline\",rivers:\"river\",frame:\"frame\"}},{}],794:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../registry\"),i=t(\"../../lib\"),o=t(\"../../components/color\"),s=t(\"../../components/drawing\"),l=t(\"../../components/fx\"),c=t(\"../plots\"),u=t(\"../cartesian/axes\"),h=t(\"../cartesian/autorange\").getAutoRange,f=t(\"../../components/dragelement\"),p=t(\"../cartesian/select\").prepSelect,d=t(\"../cartesian/select\").selectOnClick,g=t(\"./zoom\"),v=t(\"./constants\"),m=t(\"../../lib/geo_location_utils\"),y=t(\"../../lib/topojson_utils\"),x=t(\"topojson-client\").feature;function b(t){this.id=t.id,this.graphDiv=t.graphDiv,this.container=t.container,this.topojsonURL=t.topojsonURL,this.isStatic=t.staticPlot,this.topojsonName=null,this.topojson=null,this.projection=null,this.scope=null,this.viewInitial=null,this.fitScale=null,this.bounds=null,this.midPt=null,this.hasChoropleth=!1,this.traceHash={},this.layers={},this.basePaths={},this.dataPaths={},this.dataPoints={},this.clipDef=null,this.clipRect=null,this.bgRect=null,this.makeFramework()}t(\"./projections\")(n);var _=b.prototype;function w(t,e){var r=v.clipPad,n=t[0]+r,a=t[1]-r,i=e[0]+r,o=e[1]-r;n>0&&a<0&&(a+=360);var s=(a-n)/4;return{type:\"Polygon\",coordinates:[[[n,i],[n,o],[n+s,o],[n+2*s,o],[n+3*s,o],[a,o],[a,i],[a-s,i],[a-2*s,i],[a-3*s,i],[n,i]]]}}e.exports=function(t){return new b(t)},_.plot=function(t,e,r){var n=this,a=e[this.id],i=[],o=!1;for(var s in v.layerNameToAdjective)if(\"frame\"!==s&&a[\"show\"+s]){o=!0;break}for(var l=0;l<t.length;l++)if(t[0][0].trace.locationmode){o=!0;break}if(o){var c=y.getTopojsonName(a);null!==n.topojson&&c===n.topojsonName||(n.topojsonName=c,void 0===PlotlyGeoAssets.topojson[n.topojsonName]&&i.push(n.fetchTopojson()))}i=i.concat(m.fetchTraceGeoData(t)),r.push(new Promise(function(r,a){Promise.all(i).then(function(){n.topojson=PlotlyGeoAssets.topojson[n.topojsonName],n.update(t,e),r()}).catch(a)}))},_.fetchTopojson=function(){var t=this,e=y.getTopojsonPath(t.topojsonURL,t.topojsonName);return new Promise(function(r,a){n.json(e,function(n,i){if(n)return 404===n.status?a(new Error([\"plotly.js could not find topojson file at\",e,\".\",\"Make sure the *topojsonURL* plot config option\",\"is set properly.\"].join(\" \"))):a(new Error([\"unexpected error while fetching topojson file at\",e].join(\" \")));PlotlyGeoAssets.topojson[t.topojsonName]=i,r()})})},_.update=function(t,e){var r=e[this.id];this.hasChoropleth=!1;for(var n=0;n<t.length;n++){var a=t[n],i=a[0].trace;\"choropleth\"===i.type&&(this.hasChoropleth=!0),!0===i.visible&&i._length>0&&i._module.calcGeoJSON(a,e)}if(!this.updateProjection(t,e)){this.viewInitial&&this.scope===r.scope||this.saveViewInitial(r),this.scope=r.scope,this.updateBaseLayers(e,r),this.updateDims(e,r),this.updateFx(e,r),c.generalUpdatePerTraceModule(this.graphDiv,this,t,r);var o=this.layers.frontplot.select(\".scatterlayer\");this.dataPoints.point=o.selectAll(\".point\"),this.dataPoints.text=o.selectAll(\"text\"),this.dataPaths.line=o.selectAll(\".js-line\");var s=this.layers.backplot.select(\".choroplethlayer\");this.dataPaths.choropleth=s.selectAll(\"path\"),this.render()}},_.updateProjection=function(t,e){var r=this.graphDiv,o=e[this.id],s=e._size,l=o.domain,c=o.projection,u=o.lonaxis,f=o.lataxis,p=u._ax,d=f._ax,g=this.projection=function(t){for(var e=t.projection.type,r=n.geo[v.projNames[e]](),a=t._isClipped?v.lonaxisSpan[e]/2:null,i=[\"center\",\"rotate\",\"parallels\",\"clipExtent\"],o=function(t){return t?r:[]},s=0;s<i.length;s++){var l=i[s];\"function\"!=typeof r[l]&&(r[l]=o)}r.isLonLatOverEdges=function(t){if(null===r(t))return!0;if(a){var e=r.rotate();return n.geo.distance(t,[-e[0],-e[1]])>a*Math.PI/180}return!1},r.getPath=function(){return n.geo.path().projection(r)},r.getBounds=function(t){return r.getPath().bounds(t)},r.fitExtent=function(t,e){var n=t[1][0]-t[0][0],a=t[1][1]-t[0][1],i=r.clipExtent&&r.clipExtent();r.scale(150).translate([0,0]),i&&r.clipExtent(null);var o=r.getBounds(e),s=Math.min(n/(o[1][0]-o[0][0]),a/(o[1][1]-o[0][1])),l=+t[0][0]+(n-s*(o[1][0]+o[0][0]))/2,c=+t[0][1]+(a-s*(o[1][1]+o[0][1]))/2;return i&&r.clipExtent(i),r.scale(150*s).translate([l,c])},r.precision(v.precision),a&&r.clipAngle(a-v.clipPad);return r}(o),m=[[s.l+s.w*l.x[0],s.t+s.h*(1-l.y[1])],[s.l+s.w*l.x[1],s.t+s.h*(1-l.y[0])]],y=o.center||{},x=c.rotation||{},b=u.range||[],_=f.range||[];if(o.fitbounds){p._length=m[1][0]-m[0][0],d._length=m[1][1]-m[0][1],p.range=h(r,p),d.range=h(r,d);var k=(p.range[0]+p.range[1])/2,T=(d.range[0]+d.range[1])/2;if(o._isScoped)y={lon:k,lat:T};else if(o._isClipped){y={lon:k,lat:T},x={lon:k,lat:T,roll:x.roll};var M=c.type,A=v.lonaxisSpan[M]/2||180,S=v.lataxisSpan[M]/2||180;b=[k-A,k+A],_=[T-S,T+S]}else y={lon:k,lat:T},x={lon:k,lat:x.lat,roll:x.roll}}g.center([y.lon-x.lon,y.lat-x.lat]).rotate([-x.lon,-x.lat,x.roll]).parallels(c.parallels);var E=w(b,_);g.fitExtent(m,E);var L=this.bounds=g.getBounds(E),C=this.fitScale=g.scale(),P=g.translate();if(!isFinite(L[0][0])||!isFinite(L[0][1])||!isFinite(L[1][0])||!isFinite(L[1][1])||isNaN(P[0])||isNaN(P[0])){for(var O=[\"fitbounds\",\"projection.rotation\",\"center\",\"lonaxis.range\",\"lataxis.range\"],z=\"Invalid geo settings, relayout'ing to default view.\",I={},D=0;D<O.length;D++)I[this.id+\".\"+O[D]]=null;return this.viewInitial=null,i.warn(z),r._promises.push(a.call(\"relayout\",r,I)),z}if(o.fitbounds){var R=g.getBounds(w(p.range,d.range)),F=Math.min((L[1][0]-L[0][0])/(R[1][0]-R[0][0]),(L[1][1]-L[0][1])/(R[1][1]-R[0][1]));isFinite(F)?g.scale(F*C):i.warn(\"Something went wrong during\"+this.id+\"fitbounds computations.\")}else g.scale(c.scale*C);var B=this.midPt=[(L[0][0]+L[1][0])/2,(L[0][1]+L[1][1])/2];if(g.translate([P[0]+(B[0]-P[0]),P[1]+(B[1]-P[1])]).clipExtent(L),o._isAlbersUsa){var N=g([y.lon,y.lat]),j=g.translate();g.translate([j[0]-(N[0]-j[0]),j[1]-(N[1]-j[1])])}},_.updateBaseLayers=function(t,e){var r=this,a=r.topojson,i=r.layers,l=r.basePaths;function c(t){return\"lonaxis\"===t||\"lataxis\"===t}function h(t){return Boolean(v.lineLayers[t])}function f(t){return Boolean(v.fillLayers[t])}var p=(this.hasChoropleth?v.layersForChoropleth:v.layers).filter(function(t){return h(t)||f(t)?e[\"show\"+t]:!c(t)||e[t].showgrid}),d=r.framework.selectAll(\".layer\").data(p,String);d.exit().each(function(t){delete i[t],delete l[t],n.select(this).remove()}),d.enter().append(\"g\").attr(\"class\",function(t){return\"layer \"+t}).each(function(t){var e=i[t]=n.select(this);\"bg\"===t?r.bgRect=e.append(\"rect\").style(\"pointer-events\",\"all\"):c(t)?l[t]=e.append(\"path\").style(\"fill\",\"none\"):\"backplot\"===t?e.append(\"g\").classed(\"choroplethlayer\",!0):\"frontplot\"===t?e.append(\"g\").classed(\"scatterlayer\",!0):h(t)?l[t]=e.append(\"path\").style(\"fill\",\"none\").style(\"stroke-miterlimit\",2):f(t)&&(l[t]=e.append(\"path\").style(\"stroke\",\"none\"))}),d.order(),d.each(function(r){var n=l[r],i=v.layerNameToAdjective[r];\"frame\"===r?n.datum(v.sphereSVG):h(r)||f(r)?n.datum(x(a,a.objects[r])):c(r)&&n.datum(function(t,e,r){var n,a,i,o=e[t],s=v.scopeDefaults[e.scope];\"lonaxis\"===t?(n=s.lonaxisRange,a=s.lataxisRange,i=function(t,e){return[t,e]}):\"lataxis\"===t&&(n=s.lataxisRange,a=s.lonaxisRange,i=function(t,e){return[e,t]});var l={type:\"linear\",range:[n[0],n[1]-1e-6],tick0:o.tick0,dtick:o.dtick};u.setConvert(l,r);var c=u.calcTicks(l);e.isScoped||\"lonaxis\"!==t||c.pop();for(var h=c.length,f=new Array(h),p=0;p<h;p++)for(var d=c[p].x,g=f[p]=[],m=a[0];m<a[1]+2.5;m+=2.5)g.push(i(d,m));return{type:\"MultiLineString\",coordinates:f}}(r,e,t)).call(o.stroke,e[r].gridcolor).call(s.dashLine,\"\",e[r].gridwidth),h(r)?n.call(o.stroke,e[i+\"color\"]).call(s.dashLine,\"\",e[i+\"width\"]):f(r)&&n.call(o.fill,e[i+\"color\"])})},_.updateDims=function(t,e){var r=this.bounds,n=(e.framewidth||0)/2,a=r[0][0]-n,i=r[0][1]-n,l=r[1][0]-a+n,c=r[1][1]-i+n;s.setRect(this.clipRect,a,i,l,c),this.bgRect.call(s.setRect,a,i,l,c).call(o.fill,e.bgcolor),this.xaxis._offset=a,this.xaxis._length=l,this.yaxis._offset=i,this.yaxis._length=c},_.updateFx=function(t,e){var r=this,i=r.graphDiv,o=r.bgRect,s=t.dragmode,c=t.clickmode;if(!r.isStatic){var u;\"select\"===s?u=function(t,e){(t.range={})[r.id]=[v([e.xmin,e.ymin]),v([e.xmax,e.ymax])]}:\"lasso\"===s&&(u=function(t,e,n){(t.lassoPoints={})[r.id]=n.filtered.map(v)});var h={element:r.bgRect.node(),gd:i,plotinfo:{id:r.id,xaxis:r.xaxis,yaxis:r.yaxis,fillRangeItems:u},xaxes:[r.xaxis],yaxes:[r.yaxis],subplot:r.id,clickFn:function(e){2===e&&t._zoomlayer.selectAll(\".select-outline\").remove()}};\"pan\"===s?(o.node().onmousedown=null,o.call(g(r,e)),o.on(\"dblclick.zoom\",function(){var t=r.viewInitial,e={};for(var n in t)e[r.id+\".\"+n]=t[n];a.call(\"_guiRelayout\",i,e),i.emit(\"plotly_doubleclick\",null)}),i._context._scrollZoom.geo||o.on(\"wheel.zoom\",null)):\"select\"!==s&&\"lasso\"!==s||(o.on(\".zoom\",null),h.prepFn=function(t,e,r){p(t,e,r,h,s)},f.init(h)),o.on(\"mousemove\",function(){var t=r.projection.invert(n.mouse(this));if(!t||isNaN(t[0])||isNaN(t[1]))return f.unhover(i,n.event);r.xaxis.p2c=function(){return t[0]},r.yaxis.p2c=function(){return t[1]},l.hover(i,n.event,r.id)}),o.on(\"mouseout\",function(){i._dragging||f.unhover(i,n.event)}),o.on(\"click\",function(){\"select\"!==s&&\"lasso\"!==s&&(c.indexOf(\"select\")>-1&&d(n.event,i,[r.xaxis],[r.yaxis],r.id,h),c.indexOf(\"event\")>-1&&l.click(i,n.event))})}function v(t){return r.projection.invert([t[0]+r.xaxis._offset,t[1]+r.yaxis._offset])}},_.makeFramework=function(){var t=this,e=t.graphDiv,r=e._fullLayout,a=\"clip\"+r._uid+t.id;t.clipDef=r._clips.append(\"clipPath\").attr(\"id\",a),t.clipRect=t.clipDef.append(\"rect\"),t.framework=n.select(t.container).append(\"g\").attr(\"class\",\"geo \"+t.id).call(s.setClipUrl,a,e),t.project=function(e){var r=t.projection(e);return r?[r[0]-t.xaxis._offset,r[1]-t.yaxis._offset]:[null,null]},t.xaxis={_id:\"x\",c2p:function(e){return t.project(e)[0]}},t.yaxis={_id:\"y\",c2p:function(e){return t.project(e)[1]}},t.mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},u.setConvert(t.mockAxis,r)},_.saveViewInitial=function(t){var e,r=t.center||{},n=t.projection,a=n.rotation||{};this.viewInitial={fitbounds:t.fitbounds,\"projection.scale\":n.scale},e=t._isScoped?{\"center.lon\":r.lon,\"center.lat\":r.lat}:t._isClipped?{\"projection.rotation.lon\":a.lon,\"projection.rotation.lat\":a.lat}:{\"center.lon\":r.lon,\"center.lat\":r.lat,\"projection.rotation.lon\":a.lon},i.extendFlat(this.viewInitial,e)},_.render=function(){var t,e=this.projection,r=e.getPath();function n(t){var r=e(t.lonlat);return r?\"translate(\"+r[0]+\",\"+r[1]+\")\":null}function a(t){return e.isLonLatOverEdges(t.lonlat)?\"none\":null}for(t in this.basePaths)this.basePaths[t].attr(\"d\",r);for(t in this.dataPaths)this.dataPaths[t].attr(\"d\",function(t){return r(t.geojson)});for(t in this.dataPoints)this.dataPoints[t].attr(\"display\",a).attr(\"transform\",n)}},{\"../../components/color\":592,\"../../components/dragelement\":610,\"../../components/drawing\":613,\"../../components/fx\":630,\"../../lib\":717,\"../../lib/geo_location_utils\":711,\"../../lib/topojson_utils\":744,\"../../registry\":846,\"../cartesian/autorange\":764,\"../cartesian/axes\":765,\"../cartesian/select\":782,\"../plots\":826,\"./constants\":793,\"./projections\":798,\"./zoom\":799,d3:165,\"topojson-client\":539}],795:[function(t,e,r){\"use strict\";var n=t(\"../../plots/get_data\").getSubplotCalcData,a=t(\"../../lib\").counterRegex,i=t(\"./geo\"),o=\"geo\",s=a(o),l={};l[o]={valType:\"subplotid\",dflt:o,editType:\"calc\"},e.exports={attr:o,name:o,idRoot:o,idRegex:s,attrRegex:s,attributes:l,layoutAttributes:t(\"./layout_attributes\"),supplyLayoutDefaults:t(\"./layout_defaults\"),plot:function(t){for(var e=t._fullLayout,r=t.calcdata,a=e._subplots[o],s=0;s<a.length;s++){var l=a[s],c=n(r,o,l),u=e[l]._subplot;u||(u=i({id:l,graphDiv:t,container:e._geolayer.node(),topojsonURL:t._context.topojsonURL,staticPlot:t._context.staticPlot}),e[l]._subplot=u),u.plot(c,e,t._promises)}},updateFx:function(t){for(var e=t._fullLayout,r=e._subplots[o],n=0;n<r.length;n++){var a=e[r[n]];a._subplot.updateFx(e,a)}},clean:function(t,e,r,n){for(var a=n._subplots[o]||[],i=0;i<a.length;i++){var s=a[i],l=n[s]._subplot;!e[s]&&l&&(l.framework.remove(),l.clipDef.remove())}}}},{\"../../lib\":717,\"../../plots/get_data\":800,\"./geo\":794,\"./layout_attributes\":796,\"./layout_defaults\":797}],796:[function(t,e,r){\"use strict\";var n=t(\"../../components/color/attributes\"),a=t(\"../domain\").attributes,i=t(\"./constants\"),o=t(\"../../plot_api/edit_types\").overrideAll,s={range:{valType:\"info_array\",items:[{valType:\"number\"},{valType:\"number\"}]},showgrid:{valType:\"boolean\",dflt:!1},tick0:{valType:\"number\",dflt:0},dtick:{valType:\"number\"},gridcolor:{valType:\"color\",dflt:n.lightLine},gridwidth:{valType:\"number\",min:0,dflt:1}};(e.exports=o({domain:a({name:\"geo\"},{}),fitbounds:{valType:\"enumerated\",values:[!1,\"locations\",\"geojson\"],dflt:!1,editType:\"plot\"},resolution:{valType:\"enumerated\",values:[110,50],dflt:110,coerceNumber:!0},scope:{valType:\"enumerated\",values:Object.keys(i.scopeDefaults),dflt:\"world\"},projection:{type:{valType:\"enumerated\",values:Object.keys(i.projNames)},rotation:{lon:{valType:\"number\"},lat:{valType:\"number\"},roll:{valType:\"number\"}},parallels:{valType:\"info_array\",items:[{valType:\"number\"},{valType:\"number\"}]},scale:{valType:\"number\",min:0,dflt:1}},center:{lon:{valType:\"number\"},lat:{valType:\"number\"}},visible:{valType:\"boolean\",dflt:!0},showcoastlines:{valType:\"boolean\"},coastlinecolor:{valType:\"color\",dflt:n.defaultLine},coastlinewidth:{valType:\"number\",min:0,dflt:1},showland:{valType:\"boolean\",dflt:!1},landcolor:{valType:\"color\",dflt:i.landColor},showocean:{valType:\"boolean\",dflt:!1},oceancolor:{valType:\"color\",dflt:i.waterColor},showlakes:{valType:\"boolean\",dflt:!1},lakecolor:{valType:\"color\",dflt:i.waterColor},showrivers:{valType:\"boolean\",dflt:!1},rivercolor:{valType:\"color\",dflt:i.waterColor},riverwidth:{valType:\"number\",min:0,dflt:1},showcountries:{valType:\"boolean\"},countrycolor:{valType:\"color\",dflt:n.defaultLine},countrywidth:{valType:\"number\",min:0,dflt:1},showsubunits:{valType:\"boolean\"},subunitcolor:{valType:\"color\",dflt:n.defaultLine},subunitwidth:{valType:\"number\",min:0,dflt:1},showframe:{valType:\"boolean\"},framecolor:{valType:\"color\",dflt:n.defaultLine},framewidth:{valType:\"number\",min:0,dflt:1},bgcolor:{valType:\"color\",dflt:n.background},lonaxis:s,lataxis:s},\"plot\",\"from-root\")).uirevision={valType:\"any\",editType:\"none\"}},{\"../../components/color/attributes\":591,\"../../plot_api/edit_types\":748,\"../domain\":790,\"./constants\":793}],797:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../subplot_defaults\"),i=t(\"../get_data\").getSubplotData,o=t(\"./constants\"),s=t(\"./layout_attributes\"),l=o.axesNames;function c(t,e,r,a){var s=i(a.fullData,\"geo\",a.id).map(function(t){return t._expandedIndex}),c=r(\"resolution\"),u=r(\"scope\"),h=o.scopeDefaults[u],f=r(\"projection.type\",h.projType),p=e._isAlbersUsa=\"albers usa\"===f;p&&(u=e.scope=\"usa\");var d=e._isScoped=\"world\"!==u,g=e._isConic=-1!==f.indexOf(\"conic\"),v=e._isClipped=!!o.lonaxisSpan[f];if(!1===t.visible){var m=n.extendDeep({},e._template);m.showcoastlines=!1,m.showcountries=!1,m.showframe=!1,m.showlakes=!1,m.showland=!1,m.showocean=!1,m.showrivers=!1,m.showsubunits=!1,m.lonaxis&&(m.lonaxis.showgrid=!1),m.lataxis&&(m.lataxis.showgrid=!1),e._template=m}for(var y=r(\"visible\"),x=0;x<l.length;x++){var b,_=l[x],w=[30,10][x];if(d)b=h[_+\"Range\"];else{var k=o[_+\"Span\"],T=(k[f]||k[\"*\"])/2,M=r(\"projection.rotation.\"+_.substr(0,3),h.projRotate[x]);b=[M-T,M+T]}var A=r(_+\".range\",b);r(_+\".tick0\"),r(_+\".dtick\",w),r(_+\".showgrid\",!!y&&void 0)&&(r(_+\".gridcolor\"),r(_+\".gridwidth\")),e[_]._ax={type:\"linear\",_id:_.slice(0,3),_traceIndices:s,setScale:n.identity,c2l:n.identity,r2l:n.identity,autorange:!0,range:A.slice(),_m:1,_input:{}}}var S=e.lonaxis.range,E=e.lataxis.range,L=S[0],C=S[1];L>0&&C<0&&(C+=360);var P,O,z,I=(L+C)/2;if(!p){var D=d?h.projRotate:[I,0,0];P=r(\"projection.rotation.lon\",D[0]),r(\"projection.rotation.lat\",D[1]),r(\"projection.rotation.roll\",D[2]),r(\"showcoastlines\",!d&&y)&&(r(\"coastlinecolor\"),r(\"coastlinewidth\")),r(\"showocean\",!!y&&void 0)&&r(\"oceancolor\")}(p?(O=-96.6,z=38.7):(O=d?I:P,z=(E[0]+E[1])/2),r(\"center.lon\",O),r(\"center.lat\",z),g)&&r(\"projection.parallels\",h.projParallels||[0,60]);r(\"projection.scale\"),r(\"showland\",!!y&&void 0)&&r(\"landcolor\"),r(\"showlakes\",!!y&&void 0)&&r(\"lakecolor\"),r(\"showrivers\",!!y&&void 0)&&(r(\"rivercolor\"),r(\"riverwidth\")),r(\"showcountries\",d&&\"usa\"!==u&&y)&&(r(\"countrycolor\"),r(\"countrywidth\")),(\"usa\"===u||\"north america\"===u&&50===c)&&(r(\"showsubunits\",y),r(\"subunitcolor\"),r(\"subunitwidth\")),d||r(\"showframe\",y)&&(r(\"framecolor\"),r(\"framewidth\")),r(\"bgcolor\"),r(\"fitbounds\")&&(delete e.projection.scale,d?(delete e.center.lon,delete e.center.lat):v?(delete e.center.lon,delete e.center.lat,delete e.projection.rotation.lon,delete e.projection.rotation.lat,delete e.lonaxis.range,delete e.lataxis.range):(delete e.center.lon,delete e.center.lat,delete e.projection.rotation.lon))}e.exports=function(t,e,r){a(t,e,r,{type:\"geo\",attributes:s,handleDefaults:c,fullData:r,partition:\"y\"})}},{\"../../lib\":717,\"../get_data\":800,\"../subplot_defaults\":840,\"./constants\":793,\"./layout_attributes\":796}],798:[function(t,e,r){\"use strict\";e.exports=function(t){function e(t,e){return{type:\"Feature\",id:t.id,properties:t.properties,geometry:r(t.geometry,e)}}function r(e,n){if(!e)return null;if(\"GeometryCollection\"===e.type)return{type:\"GeometryCollection\",geometries:object.geometries.map(function(t){return r(t,n)})};if(!c.hasOwnProperty(e.type))return null;var a=c[e.type];return t.geo.stream(e,n(a)),a.result()}t.geo.project=function(t,e){var a=e.stream;if(!a)throw new Error(\"not yet supported\");return(t&&n.hasOwnProperty(t.type)?n[t.type]:r)(t,a)};var n={Feature:e,FeatureCollection:function(t,r){return{type:\"FeatureCollection\",features:t.features.map(function(t){return e(t,r)})}}},a=[],i=[],o={point:function(t,e){a.push([t,e])},result:function(){var t=a.length?a.length<2?{type:\"Point\",coordinates:a[0]}:{type:\"MultiPoint\",coordinates:a}:null;return a=[],t}},s={lineStart:u,point:function(t,e){a.push([t,e])},lineEnd:function(){a.length&&(i.push(a),a=[])},result:function(){var t=i.length?i.length<2?{type:\"LineString\",coordinates:i[0]}:{type:\"MultiLineString\",coordinates:i}:null;return i=[],t}},l={polygonStart:u,lineStart:u,point:function(t,e){a.push([t,e])},lineEnd:function(){var t=a.length;if(t){do{a.push(a[0].slice())}while(++t<4);i.push(a),a=[]}},polygonEnd:u,result:function(){if(!i.length)return null;var t=[],e=[];return i.forEach(function(r){!function(t){if((e=t.length)<4)return!1;for(var e,r=0,n=t[e-1][1]*t[0][0]-t[e-1][0]*t[0][1];++r<e;)n+=t[r-1][1]*t[r][0]-t[r-1][0]*t[r][1];return n<=0}(r)?e.push(r):t.push([r])}),e.forEach(function(e){var r=e[0];t.some(function(t){if(function(t,e){for(var r=e[0],n=e[1],a=!1,i=0,o=t.length,s=o-1;i<o;s=i++){var l=t[i],c=l[0],u=l[1],h=t[s],f=h[0],p=h[1];u>n^p>n&&r<(f-c)*(n-u)/(p-u)+c&&(a=!a)}return a}(t[0],r))return t.push(e),!0})||t.push([e])}),i=[],t.length?t.length>1?{type:\"MultiPolygon\",coordinates:t}:{type:\"Polygon\",coordinates:t[0]}:null}},c={Point:o,MultiPoint:o,LineString:s,MultiLineString:s,Polygon:l,MultiPolygon:l,Sphere:l};function u(){}var h=1e-6,f=h*h,p=Math.PI,d=p/2,g=(Math.sqrt(p),p/180),v=180/p;function m(t){return t>1?d:t<-1?-d:Math.asin(t)}function y(t){return t>1?0:t<-1?p:Math.acos(t)}var x=t.geo.projection,b=t.geo.projectionMutator;function _(t,e){var r=(2+d)*Math.sin(e);e/=2;for(var n=0,a=1/0;n<10&&Math.abs(a)>h;n++){var i=Math.cos(e);e-=a=(e+Math.sin(e)*(i+2)-r)/(2*i*(1+i))}return[2/Math.sqrt(p*(4+p))*t*(1+Math.cos(e)),2*Math.sqrt(p/(4+p))*Math.sin(e)]}t.geo.interrupt=function(e){var r,n=[[[[-p,0],[0,d],[p,0]]],[[[-p,0],[0,-d],[p,0]]]];function a(t,r){for(var a=r<0?-1:1,i=n[+(r<0)],o=0,s=i.length-1;o<s&&t>i[o][2][0];++o);var l=e(t-i[o][1][0],r);return l[0]+=e(i[o][1][0],a*r>a*i[o][0][1]?i[o][0][1]:r)[0],l}e.invert&&(a.invert=function(t,i){for(var o=r[+(i<0)],s=n[+(i<0)],c=0,u=o.length;c<u;++c){var h=o[c];if(h[0][0]<=t&&t<h[1][0]&&h[0][1]<=i&&i<h[1][1]){var f=e.invert(t-e(s[c][1][0],0)[0],i);return f[0]+=s[c][1][0],l(a(f[0],f[1]),[t,i])?f:null}}});var i=t.geo.projection(a),o=i.stream;function s(t,e){for(var r,n,a,i=-1,o=t.length,s=t[0],l=[];++i<o;){n=((r=t[i])[0]-s[0])/e,a=(r[1]-s[1])/e;for(var c=0;c<e;++c)l.push([s[0]+c*n,s[1]+c*a]);s=r}return l.push(r),l}function l(t,e){return Math.abs(t[0]-e[0])<h&&Math.abs(t[1]-e[1])<h}return i.stream=function(e){var r=i.rotate(),a=o(e),l=(i.rotate([0,0]),o(e));return i.rotate(r),a.sphere=function(){t.geo.stream(function(){for(var e=1e-6,r=[],a=0,i=n[0].length;a<i;++a){var o=n[0][a],l=180*o[0][0]/p,c=180*o[0][1]/p,u=180*o[1][1]/p,h=180*o[2][0]/p,f=180*o[2][1]/p;r.push(s([[l+e,c+e],[l+e,u-e],[h-e,u-e],[h-e,f+e]],30))}for(var a=n[1].length-1;a>=0;--a){var o=n[1][a],l=180*o[0][0]/p,c=180*o[0][1]/p,u=180*o[1][1]/p,h=180*o[2][0]/p,f=180*o[2][1]/p;r.push(s([[h-e,f-e],[h-e,u+e],[l+e,u+e],[l+e,c-e]],30))}return{type:\"Polygon\",coordinates:[t.merge(r)]}}(),l)},a},i.lobes=function(t){return arguments.length?(n=t.map(function(t){return t.map(function(t){return[[t[0][0]*p/180,t[0][1]*p/180],[t[1][0]*p/180,t[1][1]*p/180],[t[2][0]*p/180,t[2][1]*p/180]]})}),r=n.map(function(t){return t.map(function(t){var r,n=e(t[0][0],t[0][1])[0],a=e(t[2][0],t[2][1])[0],i=e(t[1][0],t[0][1])[1],o=e(t[1][0],t[1][1])[1];return i>o&&(r=i,i=o,o=r),[[n,i],[a,o]]})}),i):n.map(function(t){return t.map(function(t){return[[180*t[0][0]/p,180*t[0][1]/p],[180*t[1][0]/p,180*t[1][1]/p],[180*t[2][0]/p,180*t[2][1]/p]]})})},i},_.invert=function(t,e){var r=.5*e*Math.sqrt((4+p)/p),n=m(r),a=Math.cos(n);return[t/(2/Math.sqrt(p*(4+p))*(1+a)),m((n+r*(a+2))/(2+d))]},(t.geo.eckert4=function(){return x(_)}).raw=_;var w=t.geo.azimuthalEqualArea.raw;function k(t,e){if(arguments.length<2&&(e=t),1===e)return w;if(e===1/0)return T;function r(r,n){var a=w(r/e,n);return a[0]*=t,a}return r.invert=function(r,n){var a=w.invert(r/t,n);return a[0]*=e,a},r}function T(t,e){return[t*Math.cos(e)/Math.cos(e/=2),2*Math.sin(e)]}function M(t,e){return[3*t/(2*p)*Math.sqrt(p*p/3-e*e),e]}function A(t,e){return[t,1.25*Math.log(Math.tan(p/4+.4*e))]}function S(t){return function(e){var r,n=t*Math.sin(e),a=30;do{e-=r=(e+Math.sin(e)-n)/(1+Math.cos(e))}while(Math.abs(r)>h&&--a>0);return e/2}}T.invert=function(t,e){var r=2*m(e/2);return[t*Math.cos(r/2)/Math.cos(r),r]},(t.geo.hammer=function(){var t=2,e=b(k),r=e(t);return r.coefficient=function(r){return arguments.length?e(t=+r):t},r}).raw=k,M.invert=function(t,e){return[2/3*p*t/Math.sqrt(p*p/3-e*e),e]},(t.geo.kavrayskiy7=function(){return x(M)}).raw=M,A.invert=function(t,e){return[t,2.5*Math.atan(Math.exp(.8*e))-.625*p]},(t.geo.miller=function(){return x(A)}).raw=A,S(p);var E=function(t,e,r){var n=S(r);function a(r,a){return[t*r*Math.cos(a=n(a)),e*Math.sin(a)]}return a.invert=function(n,a){var i=m(a/e);return[n/(t*Math.cos(i)),m((2*i+Math.sin(2*i))/r)]},a}(Math.SQRT2/d,Math.SQRT2,p);function L(t,e){var r=e*e,n=r*r;return[t*(.8707-.131979*r+n*(n*(.003971*r-.001529*n)-.013791)),e*(1.007226+r*(.015085+n*(.028874*r-.044475-.005916*n)))]}(t.geo.mollweide=function(){return x(E)}).raw=E,L.invert=function(t,e){var r,n=e,a=25;do{var i=n*n,o=i*i;n-=r=(n*(1.007226+i*(.015085+o*(.028874*i-.044475-.005916*o)))-e)/(1.007226+i*(.045255+o*(.259866*i-.311325-.005916*11*o)))}while(Math.abs(r)>h&&--a>0);return[t/(.8707+(i=n*n)*(i*(i*i*i*(.003971-.001529*i)-.013791)-.131979)),n]},(t.geo.naturalEarth=function(){return x(L)}).raw=L;var C=[[.9986,-.062],[1,0],[.9986,.062],[.9954,.124],[.99,.186],[.9822,.248],[.973,.31],[.96,.372],[.9427,.434],[.9216,.4958],[.8962,.5571],[.8679,.6176],[.835,.6769],[.7986,.7346],[.7597,.7903],[.7186,.8435],[.6732,.8936],[.6213,.9394],[.5722,.9761],[.5322,1]];function P(t,e){var r,n=Math.min(18,36*Math.abs(e)/p),a=Math.floor(n),i=n-a,o=(r=C[a])[0],s=r[1],l=(r=C[++a])[0],c=r[1],u=(r=C[Math.min(19,++a)])[0],h=r[1];return[t*(l+i*(u-o)/2+i*i*(u-2*l+o)/2),(e>0?d:-d)*(c+i*(h-s)/2+i*i*(h-2*c+s)/2)]}function O(t,e){return[t*Math.cos(e),e]}function z(t,e){var r,n=Math.cos(e),a=(r=y(n*Math.cos(t/=2)))?r/Math.sin(r):1;return[2*n*Math.sin(t)*a,Math.sin(e)*a]}function I(t,e){var r=z(t,e);return[(r[0]+t/d)/2,(r[1]+e)/2]}C.forEach(function(t){t[1]*=1.0144}),P.invert=function(t,e){var r=e/d,n=90*r,a=Math.min(18,Math.abs(n/5)),i=Math.max(0,Math.floor(a));do{var o=C[i][1],s=C[i+1][1],l=C[Math.min(19,i+2)][1],c=l-o,u=l-2*s+o,h=2*(Math.abs(r)-s)/c,p=u/c,m=h*(1-p*h*(1-2*p*h));if(m>=0||1===i){n=(e>=0?5:-5)*(m+a);var y,x=50;do{m=(a=Math.min(18,Math.abs(n)/5))-(i=Math.floor(a)),o=C[i][1],s=C[i+1][1],l=C[Math.min(19,i+2)][1],n-=(y=(e>=0?d:-d)*(s+m*(l-o)/2+m*m*(l-2*s+o)/2)-e)*v}while(Math.abs(y)>f&&--x>0);break}}while(--i>=0);var b=C[i][0],_=C[i+1][0],w=C[Math.min(19,i+2)][0];return[t/(_+m*(w-b)/2+m*m*(w-2*_+b)/2),n*g]},(t.geo.robinson=function(){return x(P)}).raw=P,O.invert=function(t,e){return[t/Math.cos(e),e]},(t.geo.sinusoidal=function(){return x(O)}).raw=O,z.invert=function(t,e){if(!(t*t+4*e*e>p*p+h)){var r=t,n=e,a=25;do{var i,o=Math.sin(r),s=Math.sin(r/2),l=Math.cos(r/2),c=Math.sin(n),u=Math.cos(n),f=Math.sin(2*n),d=c*c,g=u*u,v=s*s,m=1-g*l*l,x=m?y(u*l)*Math.sqrt(i=1/m):i=0,b=2*x*u*s-t,_=x*c-e,w=i*(g*v+x*u*l*d),k=i*(.5*o*f-2*x*c*s),T=.25*i*(f*s-x*c*g*o),M=i*(d*l+x*v*u),A=k*T-M*w;if(!A)break;var S=(_*k-b*M)/A,E=(b*T-_*w)/A;r-=S,n-=E}while((Math.abs(S)>h||Math.abs(E)>h)&&--a>0);return[r,n]}},(t.geo.aitoff=function(){return x(z)}).raw=z,I.invert=function(t,e){var r=t,n=e,a=25;do{var i,o=Math.cos(n),s=Math.sin(n),l=Math.sin(2*n),c=s*s,u=o*o,f=Math.sin(r),p=Math.cos(r/2),g=Math.sin(r/2),v=g*g,m=1-u*p*p,x=m?y(o*p)*Math.sqrt(i=1/m):i=0,b=.5*(2*x*o*g+r/d)-t,_=.5*(x*s+n)-e,w=.5*i*(u*v+x*o*p*c)+.5/d,k=i*(f*l/4-x*s*g),T=.125*i*(l*g-x*s*u*f),M=.5*i*(c*p+x*v*o)+.5,A=k*T-M*w,S=(_*k-b*M)/A,E=(b*T-_*w)/A;r-=S,n-=E}while((Math.abs(S)>h||Math.abs(E)>h)&&--a>0);return[r,n]},(t.geo.winkel3=function(){return x(I)}).raw=I}},{}],799:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\"),i=t(\"../../registry\"),o=Math.PI/180,s=180/Math.PI,l={cursor:\"pointer\"},c={cursor:\"auto\"};function u(t,e){return n.behavior.zoom().translate(e.translate()).scale(e.scale())}function h(t,e,r){var n=t.id,o=t.graphDiv,s=o.layout,l=s[n],c=o._fullLayout,u=c[n],h={},f={};function p(t,e){h[n+\".\"+t]=a.nestedProperty(l,t).get(),i.call(\"_storeDirectGUIEdit\",s,c._preGUI,h);var r=a.nestedProperty(u,t);r.get()!==e&&(r.set(e),a.nestedProperty(l,t).set(e),f[n+\".\"+t]=e)}r(p),p(\"projection.scale\",e.scale()/t.fitScale),p(\"fitbounds\",!1),o.emit(\"plotly_relayout\",f)}function f(t,e){var r=u(0,e);function a(r){var n=e.invert(t.midPt);r(\"center.lon\",n[0]),r(\"center.lat\",n[1])}return r.on(\"zoomstart\",function(){n.select(this).style(l)}).on(\"zoom\",function(){e.scale(n.event.scale).translate(n.event.translate),t.render();var r=e.invert(t.midPt);t.graphDiv.emit(\"plotly_relayouting\",{\"geo.projection.scale\":e.scale()/t.fitScale,\"geo.center.lon\":r[0],\"geo.center.lat\":r[1]})}).on(\"zoomend\",function(){n.select(this).style(c),h(t,e,a)}),r}function p(t,e){var r,a,i,o,s,f,p,d,g,v=u(0,e),m=2;function y(t){return e.invert(t)}function x(r){var n=e.rotate(),a=e.invert(t.midPt);r(\"projection.rotation.lon\",-n[0]),r(\"center.lon\",a[0]),r(\"center.lat\",a[1])}return v.on(\"zoomstart\",function(){n.select(this).style(l),r=n.mouse(this),a=e.rotate(),i=e.translate(),o=a,s=y(r)}).on(\"zoom\",function(){if(f=n.mouse(this),function(t){var r=y(t);if(!r)return!0;var n=e(r);return Math.abs(n[0]-t[0])>m||Math.abs(n[1]-t[1])>m}(r))return v.scale(e.scale()),void v.translate(e.translate());e.scale(n.event.scale),e.translate([i[0],n.event.translate[1]]),s?y(f)&&(d=y(f),p=[o[0]+(d[0]-s[0]),a[1],a[2]],e.rotate(p),o=p):s=y(r=f),g=!0,t.render();var l=e.rotate(),c=e.invert(t.midPt);t.graphDiv.emit(\"plotly_relayouting\",{\"geo.projection.scale\":e.scale()/t.fitScale,\"geo.center.lon\":c[0],\"geo.center.lat\":c[1],\"geo.projection.rotation.lon\":-l[0]})}).on(\"zoomend\",function(){n.select(this).style(c),g&&h(t,e,x)}),v}function d(t,e){var r,a={r:e.rotate(),k:e.scale()},i=u(0,e),f=function(t){var e=0,r=arguments.length,a=[];for(;++e<r;)a.push(arguments[e]);var i=n.dispatch.apply(null,a);return i.of=function(e,r){return function(a){var o;try{o=a.sourceEvent=n.event,a.target=t,n.event=a,i[a.type].apply(e,r)}finally{n.event=o}}},i}(i,\"zoomstart\",\"zoom\",\"zoomend\"),p=0,d=i.on;function m(t){var r=e.rotate();t(\"projection.rotation.lon\",-r[0]),t(\"projection.rotation.lat\",-r[1])}return i.on(\"zoomstart\",function(){n.select(this).style(l);var t,c,u,h,m,b,_,w,k,T,M,A=n.mouse(this),S=e.rotate(),E=S,L=e.translate(),C=(c=.5*(t=S)[0]*o,u=.5*t[1]*o,h=.5*t[2]*o,m=Math.sin(c),b=Math.cos(c),_=Math.sin(u),w=Math.cos(u),k=Math.sin(h),T=Math.cos(h),[b*w*T+m*_*k,m*w*T-b*_*k,b*_*T+m*w*k,b*w*k-m*_*T]);r=g(e,A),d.call(i,\"zoom\",function(){var t,i,o,l,c,u,h,p,d,m,b=n.mouse(this);if(e.scale(a.k=n.event.scale),r){if(g(e,b)){e.rotate(S).translate(L);var _=g(e,b),w=function(t,e){if(!t||!e)return;var r=function(t,e){return[t[1]*e[2]-t[2]*e[1],t[2]*e[0]-t[0]*e[2],t[0]*e[1]-t[1]*e[0]]}(t,e),n=Math.sqrt(x(r,r)),a=.5*Math.acos(Math.max(-1,Math.min(1,x(t,e)))),i=Math.sin(a)/n;return n&&[Math.cos(a),r[2]*i,-r[1]*i,r[0]*i]}(r,_),k=function(t){return[Math.atan2(2*(t[0]*t[1]+t[2]*t[3]),1-2*(t[1]*t[1]+t[2]*t[2]))*s,Math.asin(Math.max(-1,Math.min(1,2*(t[0]*t[2]-t[3]*t[1]))))*s,Math.atan2(2*(t[0]*t[3]+t[1]*t[2]),1-2*(t[2]*t[2]+t[3]*t[3]))*s]}((i=w,o=(t=C)[0],l=t[1],c=t[2],u=t[3],h=i[0],p=i[1],d=i[2],m=i[3],[o*h-l*p-c*d-u*m,o*p+l*h+c*m-u*d,o*d-l*m+c*h+u*p,o*m+l*d-c*p+u*h])),T=a.r=function(t,e,r){var n=y(e,2,t[0]);n=y(n,1,t[1]),n=y(n,0,t[2]-r[2]);var a,i,o=e[0],l=e[1],c=e[2],u=n[0],h=n[1],f=n[2],p=Math.atan2(l,o)*s,d=Math.sqrt(o*o+l*l);Math.abs(h)>d?(i=(h>0?90:-90)-p,a=0):(i=Math.asin(h/d)*s-p,a=Math.sqrt(d*d-h*h));var g=180-i-2*p,m=(Math.atan2(f,u)-Math.atan2(c,a))*s,x=(Math.atan2(f,u)-Math.atan2(c,-a))*s,b=v(r[0],r[1],i,m),_=v(r[0],r[1],g,x);return b<=_?[i,m,r[2]]:[g,x,r[2]]}(k,r,E);isFinite(T[0])&&isFinite(T[1])&&isFinite(T[2])||(T=E),e.rotate(T),E=T}}else r=g(e,A=b);f.of(this,arguments)({type:\"zoom\"})}),M=f.of(this,arguments),p++||M({type:\"zoomstart\"})}).on(\"zoomend\",function(){var r;n.select(this).style(c),d.call(i,\"zoom\",null),r=f.of(this,arguments),--p||r({type:\"zoomend\"}),h(t,e,m)}).on(\"zoom.redraw\",function(){t.render();var r=e.rotate();t.graphDiv.emit(\"plotly_relayouting\",{\"geo.projection.scale\":e.scale()/t.fitScale,\"geo.projection.rotation.lon\":-r[0],\"geo.projection.rotation.lat\":-r[1]})}),n.rebind(i,f,\"on\")}function g(t,e){var r=t.invert(e);return r&&isFinite(r[0])&&isFinite(r[1])&&function(t){var e=t[0]*o,r=t[1]*o,n=Math.cos(r);return[n*Math.cos(e),n*Math.sin(e),Math.sin(r)]}(r)}function v(t,e,r,n){var a=m(r-t),i=m(n-e);return Math.sqrt(a*a+i*i)}function m(t){return(t%360+540)%360-180}function y(t,e,r){var n=r*o,a=t.slice(),i=0===e?1:0,s=2===e?1:2,l=Math.cos(n),c=Math.sin(n);return a[i]=t[i]*l-t[s]*c,a[s]=t[s]*l+t[i]*c,a}function x(t,e){for(var r=0,n=0,a=t.length;n<a;++n)r+=t[n]*e[n];return r}e.exports=function(t,e){var r=t.projection;return(e._isScoped?f:e._isClipped?d:p)(t,r)}},{\"../../lib\":717,\"../../registry\":846,d3:165}],800:[function(t,e,r){\"use strict\";var n=t(\"../registry\"),a=t(\"./cartesian/constants\").SUBPLOT_PATTERN;r.getSubplotCalcData=function(t,e,r){var a=n.subplotsRegistry[e];if(!a)return[];for(var i=a.attr,o=[],s=0;s<t.length;s++){var l=t[s];l[0].trace[i]===r&&o.push(l)}return o},r.getModuleCalcData=function(t,e){var r,a=[],i=[];if(!(r=\"string\"==typeof e?n.getModule(e).plot:\"function\"==typeof e?e:e.plot))return[a,t];for(var o=0;o<t.length;o++){var s=t[o],l=s[0].trace;!0===l.visible&&0!==l._length&&(l._module.plot===r?a.push(s):i.push(s))}return[a,i]},r.getSubplotData=function(t,e,r){if(!n.subplotsRegistry[e])return[];var i,o,s,l=n.subplotsRegistry[e].attr,c=[];if(\"gl2d\"===e){var u=r.match(a);o=\"x\"+u[1],s=\"y\"+u[2]}for(var h=0;h<t.length;h++)i=t[h],\"gl2d\"===e&&n.traceIs(i,\"gl2d\")?i[l[0]]===o&&i[l[1]]===s&&c.push(i):i[l]===r&&c.push(i);return c}},{\"../registry\":846,\"./cartesian/constants\":771}],801:[function(t,e,r){\"use strict\";var n=t(\"mouse-change\"),a=t(\"mouse-wheel\"),i=t(\"mouse-event-offset\"),o=t(\"../cartesian/constants\"),s=t(\"has-passive-events\");function l(t,e){this.element=t,this.plot=e,this.mouseListener=null,this.wheelListener=null,this.lastInputTime=Date.now(),this.lastPos=[0,0],this.boxEnabled=!1,this.boxInited=!1,this.boxStart=[0,0],this.boxEnd=[0,0],this.dragStart=[0,0]}e.exports=function(t){var e=t.mouseContainer,r=t.glplot,c=new l(e,r);function u(){t.xaxis.autorange=!1,t.yaxis.autorange=!1}function h(e,n,a){var i,s,l=t.calcDataBox(),h=r.viewBox,f=c.lastPos[0],p=c.lastPos[1],d=o.MINDRAG*r.pixelRatio,g=o.MINZOOM*r.pixelRatio;function v(e,r,n){var a=Math.min(r,n),i=Math.max(r,n);a!==i?(l[e]=a,l[e+2]=i,c.dataBox=l,t.setRanges(l)):(t.selectBox.selectBox=[0,0,1,1],t.glplot.setDirty())}switch(n*=r.pixelRatio,a*=r.pixelRatio,a=h[3]-h[1]-a,t.fullLayout.dragmode){case\"zoom\":if(e){var m=n/(h[2]-h[0])*(l[2]-l[0])+l[0],y=a/(h[3]-h[1])*(l[3]-l[1])+l[1];c.boxInited||(c.boxStart[0]=m,c.boxStart[1]=y,c.dragStart[0]=n,c.dragStart[1]=a),c.boxEnd[0]=m,c.boxEnd[1]=y,c.boxInited=!0,c.boxEnabled||c.boxStart[0]===c.boxEnd[0]&&c.boxStart[1]===c.boxEnd[1]||(c.boxEnabled=!0);var x=Math.abs(c.dragStart[0]-n)<g,b=Math.abs(c.dragStart[1]-a)<g;if(!function(){for(var e=t.graphDiv._fullLayout._axisConstraintGroups,r=t.xaxis._id,n=t.yaxis._id,a=0;a<e.length;a++)if(-1!==e[a][r]){if(-1!==e[a][n])return!0;break}return!1}()||x&&b)x&&(c.boxEnd[0]=c.boxStart[0]),b&&(c.boxEnd[1]=c.boxStart[1]);else{i=c.boxEnd[0]-c.boxStart[0],s=c.boxEnd[1]-c.boxStart[1];var _=(l[3]-l[1])/(l[2]-l[0]);Math.abs(i*_)>Math.abs(s)?(c.boxEnd[1]=c.boxStart[1]+Math.abs(i)*_*(s>=0?1:-1),c.boxEnd[1]<l[1]?(c.boxEnd[1]=l[1],c.boxEnd[0]=c.boxStart[0]+(l[1]-c.boxStart[1])/Math.abs(_)):c.boxEnd[1]>l[3]&&(c.boxEnd[1]=l[3],c.boxEnd[0]=c.boxStart[0]+(l[3]-c.boxStart[1])/Math.abs(_))):(c.boxEnd[0]=c.boxStart[0]+Math.abs(s)/_*(i>=0?1:-1),c.boxEnd[0]<l[0]?(c.boxEnd[0]=l[0],c.boxEnd[1]=c.boxStart[1]+(l[0]-c.boxStart[0])*Math.abs(_)):c.boxEnd[0]>l[2]&&(c.boxEnd[0]=l[2],c.boxEnd[1]=c.boxStart[1]+(l[2]-c.boxStart[0])*Math.abs(_)))}}else c.boxEnabled?(i=c.boxStart[0]!==c.boxEnd[0],s=c.boxStart[1]!==c.boxEnd[1],i||s?(i&&(v(0,c.boxStart[0],c.boxEnd[0]),t.xaxis.autorange=!1),s&&(v(1,c.boxStart[1],c.boxEnd[1]),t.yaxis.autorange=!1),t.relayoutCallback()):t.glplot.setDirty(),c.boxEnabled=!1,c.boxInited=!1):c.boxInited&&(c.boxInited=!1);break;case\"pan\":c.boxEnabled=!1,c.boxInited=!1,e?(c.panning||(c.dragStart[0]=n,c.dragStart[1]=a),Math.abs(c.dragStart[0]-n)<d&&(n=c.dragStart[0]),Math.abs(c.dragStart[1]-a)<d&&(a=c.dragStart[1]),i=(f-n)*(l[2]-l[0])/(r.viewBox[2]-r.viewBox[0]),s=(p-a)*(l[3]-l[1])/(r.viewBox[3]-r.viewBox[1]),l[0]+=i,l[2]+=i,l[1]+=s,l[3]+=s,t.setRanges(l),c.panning=!0,c.lastInputTime=Date.now(),u(),t.cameraChanged(),t.handleAnnotations()):c.panning&&(c.panning=!1,t.relayoutCallback())}c.lastPos[0]=n,c.lastPos[1]=a}return c.mouseListener=n(e,h),e.addEventListener(\"touchstart\",function(t){var r=i(t.changedTouches[0],e);h(0,r[0],r[1]),h(1,r[0],r[1]),t.preventDefault()},!!s&&{passive:!1}),e.addEventListener(\"touchmove\",function(t){t.preventDefault();var r=i(t.changedTouches[0],e);h(1,r[0],r[1]),t.preventDefault()},!!s&&{passive:!1}),e.addEventListener(\"touchend\",function(t){h(0,c.lastPos[0],c.lastPos[1]),t.preventDefault()},!!s&&{passive:!1}),c.wheelListener=a(e,function(e,n){if(!t.scrollZoom)return!1;var a=t.calcDataBox(),i=r.viewBox,o=c.lastPos[0],s=c.lastPos[1],l=Math.exp(5*n/(i[3]-i[1])),h=o/(i[2]-i[0])*(a[2]-a[0])+a[0],f=s/(i[3]-i[1])*(a[3]-a[1])+a[1];return a[0]=(a[0]-h)*l+h,a[2]=(a[2]-h)*l+h,a[1]=(a[1]-f)*l+f,a[3]=(a[3]-f)*l+f,t.setRanges(a),c.lastInputTime=Date.now(),u(),t.cameraChanged(),t.handleAnnotations(),t.relayoutCallback(),!0},!0),c}},{\"../cartesian/constants\":771,\"has-passive-events\":413,\"mouse-change\":437,\"mouse-event-offset\":438,\"mouse-wheel\":440}],802:[function(t,e,r){\"use strict\";var n=t(\"../cartesian/axes\"),a=t(\"../../lib/str2rgbarray\");function i(t){this.scene=t,this.gl=t.gl,this.pixelRatio=t.pixelRatio,this.screenBox=[0,0,1,1],this.viewBox=[0,0,1,1],this.dataBox=[-1,-1,1,1],this.borderLineEnable=[!1,!1,!1,!1],this.borderLineWidth=[1,1,1,1],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.ticks=[[],[]],this.tickEnable=[!0,!0,!1,!1],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labels=[\"x\",\"y\"],this.labelEnable=[!0,!0,!1,!1],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelPad=[15,15,15,15],this.labelSize=[12,12],this.labelFont=[\"sans-serif\",\"sans-serif\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.title=\"\",this.titleEnable=!0,this.titleCenter=[0,0,0,0],this.titleAngle=0,this.titleColor=[0,0,0,1],this.titleFont=\"sans-serif\",this.titleSize=18,this.gridLineEnable=[!0,!0],this.gridLineColor=[[0,0,0,.5],[0,0,0,.5]],this.gridLineWidth=[1,1],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[1,1],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.static=this.scene.staticPlot}var o=i.prototype,s=[\"xaxis\",\"yaxis\"];o.merge=function(t){var e,r,n,i,o,l,c,u,h,f,p;for(this.titleEnable=!1,this.backgroundColor=a(t.plot_bgcolor),f=0;f<2;++f){var d=(e=s[f]).charAt(0);for(n=(r=t[this.scene[e]._name]).title.text===this.scene.fullLayout._dfltTitle[d]?\"\":r.title.text,p=0;p<=2;p+=2)this.labelEnable[f+p]=!1,this.labels[f+p]=n,this.labelColor[f+p]=a(r.title.font.color),this.labelFont[f+p]=r.title.font.family,this.labelSize[f+p]=r.title.font.size,this.labelPad[f+p]=this.getLabelPad(e,r),this.tickEnable[f+p]=!1,this.tickColor[f+p]=a((r.tickfont||{}).color),this.tickAngle[f+p]=\"auto\"===r.tickangle?0:Math.PI*-r.tickangle/180,this.tickPad[f+p]=this.getTickPad(r),this.tickMarkLength[f+p]=0,this.tickMarkWidth[f+p]=r.tickwidth||0,this.tickMarkColor[f+p]=a(r.tickcolor),this.borderLineEnable[f+p]=!1,this.borderLineColor[f+p]=a(r.linecolor),this.borderLineWidth[f+p]=r.linewidth||0;c=this.hasSharedAxis(r),o=this.hasAxisInDfltPos(e,r)&&!c,l=this.hasAxisInAltrPos(e,r)&&!c,i=r.mirror||!1,u=c?-1!==String(i).indexOf(\"all\"):!!i,h=c?\"allticks\"===i:-1!==String(i).indexOf(\"ticks\"),o?this.labelEnable[f]=!0:l&&(this.labelEnable[f+2]=!0),o?this.tickEnable[f]=r.showticklabels:l&&(this.tickEnable[f+2]=r.showticklabels),(o||u)&&(this.borderLineEnable[f]=r.showline),(l||u)&&(this.borderLineEnable[f+2]=r.showline),(o||h)&&(this.tickMarkLength[f]=this.getTickMarkLength(r)),(l||h)&&(this.tickMarkLength[f+2]=this.getTickMarkLength(r)),this.gridLineEnable[f]=r.showgrid,this.gridLineColor[f]=a(r.gridcolor),this.gridLineWidth[f]=r.gridwidth,this.zeroLineEnable[f]=r.zeroline,this.zeroLineColor[f]=a(r.zerolinecolor),this.zeroLineWidth[f]=r.zerolinewidth}},o.hasSharedAxis=function(t){var e=this.scene,r=e.fullLayout._subplots.gl2d;return 0!==n.findSubplotsWithAxis(r,t).indexOf(e.id)},o.hasAxisInDfltPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"bottom\"===r:\"yaxis\"===t?\"left\"===r:void 0},o.hasAxisInAltrPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"top\"===r:\"yaxis\"===t?\"right\"===r:void 0},o.getLabelPad=function(t,e){var r=e.title.font.size,n=e.showticklabels;return\"xaxis\"===t?\"top\"===e.side?r*(1.5+(n?1:0))-10:r*(1.5+(n?.5:0))-10:\"yaxis\"===t?\"right\"===e.side?10+r*(1.5+(n?1:.5)):10+r*(1.5+(n?.5:0)):void 0},o.getTickPad=function(t){return\"outside\"===t.ticks?10+t.ticklen:15},o.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return\"inside\"===t.ticks?-e:e},e.exports=function(t){return new i(t)}},{\"../../lib/str2rgbarray\":740,\"../cartesian/axes\":765}],803:[function(t,e,r){\"use strict\";var n=t(\"../../plot_api/edit_types\").overrideAll,a=t(\"./scene2d\"),i=t(\"../layout_attributes\"),o=t(\"../../constants/xmlns_namespaces\"),s=t(\"../cartesian/constants\"),l=t(\"../cartesian\"),c=t(\"../../components/fx/layout_attributes\"),u=t(\"../get_data\").getSubplotData;r.name=\"gl2d\",r.attr=[\"xaxis\",\"yaxis\"],r.idRoot=[\"x\",\"y\"],r.idRegex=s.idRegex,r.attrRegex=s.attrRegex,r.attributes=t(\"../cartesian/attributes\"),r.supplyLayoutDefaults=function(t,e,r){e._has(\"cartesian\")||l.supplyLayoutDefaults(t,e,r)},r.layoutAttrOverrides=n(l.layoutAttributes,\"plot\",\"from-root\"),r.baseLayoutAttrOverrides=n({plot_bgcolor:i.plot_bgcolor,hoverlabel:c.hoverlabel},\"plot\",\"nested\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl2d,i=0;i<n.length;i++){var o=n[i],s=e._plots[o],l=u(r,\"gl2d\",o),c=s._scene2d;void 0===c&&(c=new a({id:o,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),s._scene2d=c),c.plot(l,t.calcdata,e,t.layout)}},r.clean=function(t,e,r,n){for(var a=n._subplots.gl2d||[],i=0;i<a.length;i++){var o=a[i],s=n._plots[o];if(s._scene2d)0===u(t,\"gl2d\",o).length&&(s._scene2d.destroy(),delete n._plots[o])}l.clean.apply(this,arguments)},r.drawFramework=function(t){t._context.staticPlot||l.drawFramework(t)},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){var a=e._plots[r[n]]._scene2d,i=a.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":i,x:0,y:0,width:\"100%\",height:\"100%\",preserveAspectRatio:\"none\"}),a.destroy()}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){e._plots[r[n]]._scene2d.updateFx(e.dragmode)}}},{\"../../components/fx/layout_attributes\":631,\"../../constants/xmlns_namespaces\":694,\"../../plot_api/edit_types\":748,\"../cartesian\":776,\"../cartesian/attributes\":763,\"../cartesian/constants\":771,\"../get_data\":800,\"../layout_attributes\":817,\"./scene2d\":804}],804:[function(t,e,r){\"use strict\";var n,a,i=t(\"../../registry\"),o=t(\"../../plots/cartesian/axes\"),s=t(\"../../components/fx\"),l=t(\"gl-plot2d\"),c=t(\"gl-spikes2d\"),u=t(\"gl-select-box\"),h=t(\"webgl-context\"),f=t(\"./convert\"),p=t(\"./camera\"),d=t(\"../../lib/show_no_webgl_msg\"),g=t(\"../cartesian/constraints\"),v=g.enforce,m=g.clean,y=t(\"../cartesian/autorange\").doAutoRange,x=[\"xaxis\",\"yaxis\"],b=t(\"../cartesian/constants\").SUBPLOT_PATTERN;function _(t,e){this.container=t.container,this.graphDiv=t.graphDiv,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.scrollZoom=this.graphDiv._context._scrollZoom.cartesian,this.fullData=null,this.updateRefs(e),this.makeFramework(),this.stopped||(this.glplotOptions=f(this),this.glplotOptions.merge(e),this.glplot=l(this.glplotOptions),this.camera=p(this),this.traces={},this.spikes=c(this.glplot),this.selectBox=u(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.isMouseOver=!0,this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw())}e.exports=_;var w=_.prototype;w.makeFramework=function(){if(this.staticPlot){if(!(a||(n=document.createElement(\"canvas\"),a=h({canvas:n,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"Error creating static canvas/context for image server\");this.canvas=n,this.gl=a}else{var t=this.container.querySelector(\".gl-canvas-focus\"),e=h({canvas:t,preserveDrawingBuffer:!0,premultipliedAlpha:!0});if(!e)return d(this),void(this.stopped=!0);this.canvas=t,this.gl=e}var r=this.canvas;r.style.width=\"100%\",r.style.height=\"100%\",r.style.position=\"absolute\",r.style.top=\"0px\",r.style.left=\"0px\",r.style[\"pointer-events\"]=\"none\",this.updateSize(r),r.className+=\" user-select-none\";var i=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");i.style.position=\"absolute\",i.style.top=i.style.left=\"0px\",i.style.width=i.style.height=\"100%\",i.style[\"z-index\"]=20,i.style[\"pointer-events\"]=\"none\";var o=this.mouseContainer=document.createElement(\"div\");o.style.position=\"absolute\",o.style[\"pointer-events\"]=\"auto\",this.pickCanvas=this.container.querySelector(\".gl-canvas-pick\");var s=this.container;s.appendChild(i),s.appendChild(o);var l=this;o.addEventListener(\"mouseout\",function(){l.isMouseOver=!1,l.unhover()}),o.addEventListener(\"mouseover\",function(){l.isMouseOver=!0})},w.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(n),this.updateSize(this.canvas);var e=this.glplot.gl,r=e.drawingBufferWidth,a=e.drawingBufferHeight;e.clearColor(1,1,1,0),e.clear(e.COLOR_BUFFER_BIT|e.DEPTH_BUFFER_BIT),this.glplot.setDirty(),this.glplot.draw(),e.bindFramebuffer(e.FRAMEBUFFER,null);var i=new Uint8Array(r*a*4);e.readPixels(0,0,r,a,e.RGBA,e.UNSIGNED_BYTE,i);for(var o=0,s=a-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var c=0;c<4;++c){var u=i[4*(r*o+l)+c];i[4*(r*o+l)+c]=i[4*(r*s+l)+c],i[4*(r*s+l)+c]=u}var h=document.createElement(\"canvas\");h.width=r,h.height=a;var f,p=h.getContext(\"2d\"),d=p.createImageData(r,a);switch(d.data.set(i),p.putImageData(d,0,0),t){case\"jpeg\":f=h.toDataURL(\"image/jpeg\");break;case\"webp\":f=h.toDataURL(\"image/webp\");break;default:f=h.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(n),f},w.updateSize=function(t){t||(t=this.canvas);var e=this.pixelRatio,r=this.fullLayout,n=r.width,a=r.height,i=0|Math.ceil(e*n),o=0|Math.ceil(e*a);return t.width===i&&t.height===o||(t.width=i,t.height=o),t},w.computeTickMarks=function(){this.xaxis.setScale(),this.yaxis.setScale();for(var t=[o.calcTicks(this.xaxis),o.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=t[e][r].text+\"\";return t},w.updateRefs=function(t){this.fullLayout=t;var e=this.id.match(b),r=\"xaxis\"+e[1],n=\"yaxis\"+e[2];this.xaxis=this.fullLayout[r],this.yaxis=this.fullLayout[n]},w.relayoutCallback=function(){var t=this.graphDiv,e=this.xaxis,r=this.yaxis,n=t.layout,a={},o=a[e._name+\".range\"]=e.range.slice(),s=a[r._name+\".range\"]=r.range.slice();a[e._name+\".autorange\"]=e.autorange,a[r._name+\".autorange\"]=r.autorange,i.call(\"_storeDirectGUIEdit\",t.layout,t._fullLayout._preGUI,a);var l=n[e._name];l.range=o,l.autorange=e.autorange;var c=n[r._name];c.range=s,c.autorange=r.autorange,a.lastInputTime=this.camera.lastInputTime,t.emit(\"plotly_relayout\",a)},w.cameraChanged=function(){var t=this.camera;this.glplot.setDataBox(this.calcDataBox());var e=this.computeTickMarks();(function(t,e){for(var r=0;r<2;++r){var n=t[r],a=e[r];if(n.length!==a.length)return!0;for(var i=0;i<n.length;++i)if(n[i].x!==a[i].x)return!0}return!1})(e,this.glplotOptions.ticks)&&(this.glplotOptions.ticks=e,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),this.handleAnnotations())},w.handleAnnotations=function(){for(var t=this.graphDiv,e=this.fullLayout.annotations,r=0;r<e.length;r++){var n=e[r];n.xref===this.xaxis._id&&n.yref===this.yaxis._id&&i.getComponentMethod(\"annotations\",\"drawOne\")(t,r)}},w.destroy=function(){if(this.glplot){var t=this.traces;t&&Object.keys(t).map(function(e){t[e].dispose(),delete t[e]}),this.glplot.dispose(),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this.glplot=null,this.stopped=!0,this.camera.mouseListener.enabled=!1,this.mouseContainer.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null}},w.plot=function(t,e,r){var n=this.glplot;this.updateRefs(r),this.xaxis.clearCalc(),this.yaxis.clearCalc(),this.updateTraces(t,e),this.updateFx(r.dragmode);var a=r.width,i=r.height;this.updateSize(this.canvas);var o=this.glplotOptions;o.merge(r),o.screenBox=[0,0,a,i];var s={_fullLayout:{_axisConstraintGroups:this.graphDiv._fullLayout._axisConstraintGroups,xaxis:this.xaxis,yaxis:this.yaxis}};m(s,this.xaxis),m(s,this.yaxis);var l,c,u=r._size,h=this.xaxis.domain,f=this.yaxis.domain;for(o.viewBox=[u.l+h[0]*u.w,u.b+f[0]*u.h,a-u.r-(1-h[1])*u.w,i-u.t-(1-f[1])*u.h],this.mouseContainer.style.width=u.w*(h[1]-h[0])+\"px\",this.mouseContainer.style.height=u.h*(f[1]-f[0])+\"px\",this.mouseContainer.height=u.h*(f[1]-f[0]),this.mouseContainer.style.left=u.l+h[0]*u.w+\"px\",this.mouseContainer.style.top=u.t+(1-f[1])*u.h+\"px\",c=0;c<2;++c)(l=this[x[c]])._length=o.viewBox[c+2]-o.viewBox[c],y(this.graphDiv,l),l.setScale();v(s),o.ticks=this.computeTickMarks(),o.dataBox=this.calcDataBox(),o.merge(r),n.update(o),this.glplot.draw()},w.calcDataBox=function(){var t=this.xaxis,e=this.yaxis,r=t.range,n=e.range,a=t.r2l,i=e.r2l;return[a(r[0]),i(n[0]),a(r[1]),i(n[1])]},w.setRanges=function(t){var e=this.xaxis,r=this.yaxis,n=e.l2r,a=r.l2r;e.range=[n(t[0]),n(t[2])],r.range=[a(t[1]),a(t[3])]},w.updateTraces=function(t,e){var r,n,a,i=Object.keys(this.traces);this.fullData=t;t:for(r=0;r<i.length;r++){var o=i[r],s=this.traces[o];for(n=0;n<t.length;n++)if((a=t[n]).uid===o&&a.type===s.type)continue t;s.dispose(),delete this.traces[o]}for(r=0;r<t.length;r++){a=t[r];var l=e[r],c=this.traces[a.uid];c?c.update(a,l):(c=a._module.plot(this,a,l),this.traces[a.uid]=c)}this.glplot.objects.sort(function(t,e){return t._trace.index-e._trace.index})},w.updateFx=function(t){\"lasso\"===t||\"select\"===t?(this.pickCanvas.style[\"pointer-events\"]=\"none\",this.mouseContainer.style[\"pointer-events\"]=\"none\"):(this.pickCanvas.style[\"pointer-events\"]=\"auto\",this.mouseContainer.style[\"pointer-events\"]=\"auto\"),this.mouseContainer.style.cursor=\"pan\"===t?\"move\":\"zoom\"===t?\"crosshair\":null},w.emitPointAction=function(t,e){for(var r,n=t.trace.uid,a=t.pointIndex,i=0;i<this.fullData.length;i++)this.fullData[i].uid===n&&(r=this.fullData[i]);var o={x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r.index,pointNumber:a,data:r._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis};s.appendArrayPointValue(o,r,a),this.graphDiv.emit(e,{points:[o]})},w.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=1===this.lastButtonState&&0===r.buttons,a=this.fullLayout;this.lastButtonState=r.buttons,this.cameraChanged();var i,o=r.x*t.pixelRatio,l=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===a.dragmode){this.selectBox.enabled=!0;for(var c=this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],u=0;u<2;u++)e.boxStart[u]===e.boxEnd[u]&&(c[u]=t.dataBox[u],c[u+2]=t.dataBox[u+2]);t.setDirty()}else if(!e.panning&&this.isMouseOver){this.selectBox.enabled=!1;var h=a._size,f=this.xaxis.domain,p=this.yaxis.domain,d=(i=t.pick(o/t.pixelRatio+h.l+f[0]*h.w,l/t.pixelRatio-(h.t+(1-p[1])*h.h)))&&i.object._trace.handlePick(i);if(d&&n&&this.emitPointAction(d,\"plotly_click\"),i&&\"skip\"!==i.object._trace.hoverinfo&&a.hovermode&&d&&(!this.lastPickResult||this.lastPickResult.traceUid!==d.trace.uid||this.lastPickResult.dataCoord[0]!==d.dataCoord[0]||this.lastPickResult.dataCoord[1]!==d.dataCoord[1])){var g=d;this.lastPickResult={traceUid:d.trace?d.trace.uid:null,dataCoord:d.dataCoord.slice()},this.spikes.update({center:i.dataCoord}),g.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(i.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(i.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio],this.emitPointAction(d,\"plotly_hover\");var v=this.fullData[g.trace.index]||{},m=g.pointIndex,y=s.castHoverinfo(v,a,m);if(y&&\"all\"!==y){var x=y.split(\"+\");-1===x.indexOf(\"x\")&&(g.traceCoord[0]=void 0),-1===x.indexOf(\"y\")&&(g.traceCoord[1]=void 0),-1===x.indexOf(\"z\")&&(g.traceCoord[2]=void 0),-1===x.indexOf(\"text\")&&(g.textLabel=void 0),-1===x.indexOf(\"name\")&&(g.name=void 0)}s.loneHover({x:g.screenCoord[0],y:g.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",g.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",g.traceCoord[1]),zLabel:g.traceCoord[2],text:g.textLabel,name:g.name,color:s.castHoverOption(v,m,\"bgcolor\")||g.color,borderColor:s.castHoverOption(v,m,\"bordercolor\"),fontFamily:s.castHoverOption(v,m,\"font.family\"),fontSize:s.castHoverOption(v,m,\"font.size\"),fontColor:s.castHoverOption(v,m,\"font.color\"),nameLength:s.castHoverOption(v,m,\"namelength\"),textAlign:s.castHoverOption(v,m,\"align\")},{container:this.svgContainer,gd:this.graphDiv})}}i||this.unhover(),t.draw()}},w.unhover=function(){this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit(\"plotly_unhover\"),s.loneUnhover(this.svgContainer))},w.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return o.tickText(r,r.c2l(e),\"hover\").text}}},{\"../../components/fx\":630,\"../../lib/show_no_webgl_msg\":738,\"../../plots/cartesian/axes\":765,\"../../registry\":846,\"../cartesian/autorange\":764,\"../cartesian/constants\":771,\"../cartesian/constraints\":772,\"./camera\":801,\"./convert\":802,\"gl-plot2d\":290,\"gl-select-box\":302,\"gl-spikes2d\":311,\"webgl-context\":555}],805:[function(t,e,r){\"use strict\";var n=t(\"../../plot_api/edit_types\").overrideAll,a=t(\"../../components/fx/layout_attributes\"),i=t(\"./scene\"),o=t(\"../get_data\").getSubplotData,s=t(\"../../lib\"),l=t(\"../../constants/xmlns_namespaces\");r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=r.attrRegex=s.counterRegex(\"scene\"),r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.baseLayoutAttrOverrides=n({hoverlabel:a.hoverlabel},\"plot\",\"nested\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl3d,a=0;a<n.length;a++){var s=n[a],l=o(r,\"gl3d\",s),c=e[s],u=c.camera,h=c._scene;h||(h=new i({id:s,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio,camera:u},e),c._scene=h),h.viewInitial||(h.viewInitial={up:{x:u.up.x,y:u.up.y,z:u.up.z},eye:{x:u.eye.x,y:u.eye.y,z:u.eye.z},center:{x:u.center.x,y:u.center.y,z:u.center.z}}),h.plot(l,e,t.layout)}},r.clean=function(t,e,r,n){for(var a=n._subplots.gl3d||[],i=0;i<a.length;i++){var o=a[i];!e[o]&&n[o]._scene&&(n[o]._scene.destroy(),n._infolayer&&n._infolayer.selectAll(\".annotation-\"+o).remove())}},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=e._size,a=0;a<r.length;a++){var i=e[r[a]],o=i.domain,s=i._scene,c=s.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:l.svg,\"xlink:href\":c,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:\"none\"}),s.destroy()}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=0;n<r.length;n++){e[r[n]]._scene.updateFx(e.dragmode,e.hovermode)}}},{\"../../components/fx/layout_attributes\":631,\"../../constants/xmlns_namespaces\":694,\"../../lib\":717,\"../../plot_api/edit_types\":748,\"../get_data\":800,\"./layout/attributes\":806,\"./layout/defaults\":810,\"./layout/layout_attributes\":811,\"./scene\":815}],806:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"subplotid\",dflt:\"scene\",editType:\"calc+clearAxisTypes\"}}},{}],807:[function(t,e,r){\"use strict\";var n=t(\"../../../components/color\"),a=t(\"../../cartesian/layout_attributes\"),i=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../plot_api/edit_types\").overrideAll;e.exports=o({visible:a.visible,showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:n.defaultLine},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},color:a.color,categoryorder:a.categoryorder,categoryarray:a.categoryarray,title:{text:a.title.text,font:a.title.font},type:i({},a.type,{values:[\"-\",\"linear\",\"log\",\"date\",\"category\"]}),autorange:a.autorange,rangemode:a.rangemode,range:i({},a.range,{items:[{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}},{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}}],anim:!1}),tickmode:a.tickmode,nticks:a.nticks,tick0:a.tick0,dtick:a.dtick,tickvals:a.tickvals,ticktext:a.ticktext,ticks:a.ticks,mirror:a.mirror,ticklen:a.ticklen,tickwidth:a.tickwidth,tickcolor:a.tickcolor,showticklabels:a.showticklabels,tickfont:a.tickfont,tickangle:a.tickangle,tickprefix:a.tickprefix,showtickprefix:a.showtickprefix,ticksuffix:a.ticksuffix,showticksuffix:a.showticksuffix,showexponent:a.showexponent,exponentformat:a.exponentformat,separatethousands:a.separatethousands,tickformat:a.tickformat,tickformatstops:a.tickformatstops,hoverformat:a.hoverformat,showline:a.showline,linecolor:a.linecolor,linewidth:a.linewidth,showgrid:a.showgrid,gridcolor:i({},a.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:a.gridwidth,zeroline:a.zeroline,zerolinecolor:a.zerolinecolor,zerolinewidth:a.zerolinewidth,_deprecated:{title:a._deprecated.title,titlefont:a._deprecated.titlefont}},\"plot\",\"from-root\")},{\"../../../components/color\":592,\"../../../lib/extend\":708,\"../../../plot_api/edit_types\":748,\"../../cartesian/layout_attributes\":777}],808:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,a=t(\"../../../lib\"),i=t(\"../../../plot_api/plot_template\"),o=t(\"./axis_attributes\"),s=t(\"../../cartesian/type_defaults\"),l=t(\"../../cartesian/axis_defaults\"),c=[\"xaxis\",\"yaxis\",\"zaxis\"];e.exports=function(t,e,r){var u,h;function f(t,e){return a.coerce(u,h,o,t,e)}for(var p=0;p<c.length;p++){var d=c[p];u=t[d]||{},(h=i.newContainer(e,d))._id=d[0]+r.scene,h._name=d,s(u,h,f,r),l(u,h,f,{font:r.font,letter:d[0],data:r.data,showGrid:!0,noTickson:!0,bgColor:r.bgColor,calendar:r.calendar},r.fullLayout),f(\"gridcolor\",n(h.color,r.bgColor,13600/187).toRgbString()),f(\"title.text\",d[0]),h.setScale=a.noop,f(\"showspikes\")&&(f(\"spikesides\"),f(\"spikethickness\"),f(\"spikecolor\",h.color)),f(\"showaxeslabels\"),f(\"showbackground\")&&f(\"backgroundcolor\")}}},{\"../../../lib\":717,\"../../../plot_api/plot_template\":755,\"../../cartesian/axis_defaults\":767,\"../../cartesian/type_defaults\":788,\"./axis_attributes\":807,tinycolor2:536}],809:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),a=t(\"../../../lib\"),i=[\"xaxis\",\"yaxis\",\"zaxis\"];function o(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=this.tickPad.slice(),this._defaultLabelPad=this.labelPad.slice(),this._defaultLineTickLength=this.lineTickLength.slice()}o.prototype.merge=function(t,e){for(var r=0;r<3;++r){var o=e[i[r]];o.visible?(this.labels[r]=t._meta?a.templateString(o.title.text,t._meta):o.title.text,\"font\"in o.title&&(o.title.font.color&&(this.labelColor[r]=n(o.title.font.color)),o.title.font.family&&(this.labelFont[r]=o.title.font.family),o.title.font.size&&(this.labelSize[r]=o.title.font.size)),\"showline\"in o&&(this.lineEnable[r]=o.showline),\"linecolor\"in o&&(this.lineColor[r]=n(o.linecolor)),\"linewidth\"in o&&(this.lineWidth[r]=o.linewidth),\"showgrid\"in o&&(this.gridEnable[r]=o.showgrid),\"gridcolor\"in o&&(this.gridColor[r]=n(o.gridcolor)),\"gridwidth\"in o&&(this.gridWidth[r]=o.gridwidth),\"log\"===o.type?this.zeroEnable[r]=!1:\"zeroline\"in o&&(this.zeroEnable[r]=o.zeroline),\"zerolinecolor\"in o&&(this.zeroLineColor[r]=n(o.zerolinecolor)),\"zerolinewidth\"in o&&(this.zeroLineWidth[r]=o.zerolinewidth),\"ticks\"in o&&o.ticks?this.lineTickEnable[r]=!0:this.lineTickEnable[r]=!1,\"ticklen\"in o&&(this.lineTickLength[r]=this._defaultLineTickLength[r]=o.ticklen),\"tickcolor\"in o&&(this.lineTickColor[r]=n(o.tickcolor)),\"tickwidth\"in o&&(this.lineTickWidth[r]=o.tickwidth),\"tickangle\"in o&&(this.tickAngle[r]=\"auto\"===o.tickangle?-3600:Math.PI*-o.tickangle/180),\"showticklabels\"in o&&(this.tickEnable[r]=o.showticklabels),\"tickfont\"in o&&(o.tickfont.color&&(this.tickColor[r]=n(o.tickfont.color)),o.tickfont.family&&(this.tickFont[r]=o.tickfont.family),o.tickfont.size&&(this.tickSize[r]=o.tickfont.size)),\"mirror\"in o?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(o.mirror)?(this.lineTickMirror[r]=!0,this.lineMirror[r]=!0):!0===o.mirror?(this.lineTickMirror[r]=!1,this.lineMirror[r]=!0):(this.lineTickMirror[r]=!1,this.lineMirror[r]=!1):this.lineMirror[r]=!1,\"showbackground\"in o&&!1!==o.showbackground?(this.backgroundEnable[r]=!0,this.backgroundColor[r]=n(o.backgroundcolor)):this.backgroundEnable[r]=!1):(this.tickEnable[r]=!1,this.labelEnable[r]=!1,this.lineEnable[r]=!1,this.lineTickEnable[r]=!1,this.gridEnable[r]=!1,this.zeroEnable[r]=!1,this.backgroundEnable[r]=!1)}},e.exports=function(t,e){var r=new o;return r.merge(t,e),r}},{\"../../../lib\":717,\"../../../lib/str2rgbarray\":740}],810:[function(t,e,r){\"use strict\";var n=t(\"../../../lib\"),a=t(\"../../../components/color\"),i=t(\"../../../registry\"),o=t(\"../../subplot_defaults\"),s=t(\"./axis_defaults\"),l=t(\"./layout_attributes\"),c=t(\"../../get_data\").getSubplotData,u=\"gl3d\";function h(t,e,r,n){for(var o=r(\"bgcolor\"),l=a.combine(o,n.paper_bgcolor),h=[\"up\",\"center\",\"eye\"],f=0;f<h.length;f++)r(\"camera.\"+h[f]+\".x\"),r(\"camera.\"+h[f]+\".y\"),r(\"camera.\"+h[f]+\".z\");r(\"camera.projection.type\");var p=!!r(\"aspectratio.x\")&&!!r(\"aspectratio.y\")&&!!r(\"aspectratio.z\"),d=r(\"aspectmode\",p?\"manual\":\"auto\");p||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},\"manual\"===d&&(e.aspectmode=\"auto\"),t.aspectmode=e.aspectmode);var g=c(n.fullData,u,n.id);s(t,e,{font:n.font,scene:n.id,data:g,bgColor:l,calendar:n.calendar,fullLayout:n.fullLayout}),i.getComponentMethod(\"annotations3d\",\"handleDefaults\")(t,e,n);var v=n.getDfltFromLayout(\"dragmode\");if(!1!==v&&!v)if(v=\"orbit\",t.camera&&t.camera.up){var m=t.camera.up.x,y=t.camera.up.y,x=t.camera.up.z;0!==x&&(m&&y&&x?x/Math.sqrt(m*m+y*y+x*x)>.999&&(v=\"turntable\"):v=\"turntable\")}else v=\"turntable\";r(\"dragmode\",v),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}e.exports=function(t,e,r){var a=e._basePlotModules.length>1;o(t,e,r,{type:u,attributes:l,handleDefaults:h,fullLayout:e,font:e.font,fullData:r,getDfltFromLayout:function(e){if(!a)return n.validate(t[e],l[e])?t[e]:void 0},paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},{\"../../../components/color\":592,\"../../../lib\":717,\"../../../registry\":846,\"../../get_data\":800,\"../../subplot_defaults\":840,\"./axis_defaults\":808,\"./layout_attributes\":811}],811:[function(t,e,r){\"use strict\";var n=t(\"./axis_attributes\"),a=t(\"../../domain\").attributes,i=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../lib\").counterRegex;function s(t,e,r){return{x:{valType:\"number\",dflt:t,editType:\"camera\"},y:{valType:\"number\",dflt:e,editType:\"camera\"},z:{valType:\"number\",dflt:r,editType:\"camera\"},editType:\"camera\"}}e.exports={_arrayAttrRegexps:[o(\"scene\",\".annotations\",!0)],bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"plot\"},camera:{up:i(s(0,0,1),{}),center:i(s(0,0,0),{}),eye:i(s(1.25,1.25,1.25),{}),projection:{type:{valType:\"enumerated\",values:[\"perspective\",\"orthographic\"],dflt:\"perspective\",editType:\"calc\"},editType:\"calc\"},editType:\"camera\"},domain:a({name:\"scene\",editType:\"plot\"}),aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\",editType:\"plot\",impliedEdits:{\"aspectratio.x\":void 0,\"aspectratio.y\":void 0,\"aspectratio.z\":void 0}},aspectratio:{x:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},y:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},z:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},editType:\"plot\",impliedEdits:{aspectmode:\"manual\"}},xaxis:n,yaxis:n,zaxis:n,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\",!1],editType:\"plot\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\",editType:\"modebar\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"plot\",_deprecated:{cameraposition:{valType:\"info_array\",editType:\"camera\"}}}},{\"../../../lib\":717,\"../../../lib/extend\":708,\"../../domain\":790,\"./axis_attributes\":807}],812:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"];function i(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}i.prototype.merge=function(t){for(var e=0;e<3;++e){var r=t[a[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},e.exports=function(t){var e=new i;return e.merge(t),e}},{\"../../../lib/str2rgbarray\":740}],813:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],c=0;c<3;++c){var u=s[i[c]];if(u._length=(r[c].hi-r[c].lo)*r[c].pixelsPerDataUnit/t.dataScale[c],Math.abs(u._length)===1/0||isNaN(u._length))l[c]=[];else{u._input_range=u.range.slice(),u.range[0]=r[c].lo/t.dataScale[c],u.range[1]=r[c].hi/t.dataScale[c],u._m=1/(t.dataScale[c]*r[c].pixelsPerDataUnit),u.range[0]===u.range[1]&&(u.range[0]-=1,u.range[1]+=1);var h=u.tickmode;if(\"auto\"===u.tickmode){u.tickmode=\"linear\";var f=u.nticks||a.constrain(u._length/40,4,9);n.autoTicks(u,Math.abs(u.range[1]-u.range[0])/f)}for(var p=n.calcTicks(u),d=0;d<p.length;++d)p[d].x=p[d].x*t.dataScale[c],\"date\"===u.type&&(p[d].text=p[d].text.replace(/\\<br\\>/g,\" \"));l[c]=p,u.tickmode=h}}e.ticks=l;for(var c=0;c<3;++c){o[c]=.5*(t.glplot.bounds[0][c]+t.glplot.bounds[1][c]);for(var d=0;d<2;++d)e.bounds[d][c]=t.glplot.bounds[d][c]}t.contourLevels=function(t){for(var e=new Array(3),r=0;r<3;++r){for(var n=t[r],a=new Array(n.length),i=0;i<n.length;++i)a[i]=n[i].x;e[r]=a}return e}(l)};var n=t(\"../../cartesian/axes\"),a=t(\"../../../lib\"),i=[\"xaxis\",\"yaxis\",\"zaxis\"],o=[0,0,0]},{\"../../../lib\":717,\"../../cartesian/axes\":765}],814:[function(t,e,r){\"use strict\";function n(t,e){var r,n,a=[0,0,0,0];for(r=0;r<4;++r)for(n=0;n<4;++n)a[n]+=t[4*r+n]*e[r];return a}e.exports=function(t,e){return n(t.projection,n(t.view,n(t.model,[e[0],e[1],e[2],1])))}},{}],815:[function(t,e,r){\"use strict\";var n,a,i=t(\"gl-plot3d\"),o=i.createCamera,s=i.createScene,l=t(\"webgl-context\"),c=t(\"has-passive-events\"),u=t(\"../../registry\"),h=t(\"../../lib\"),f=t(\"../../plots/cartesian/axes\"),p=t(\"../../components/fx\"),d=t(\"../../lib/str2rgbarray\"),g=t(\"../../lib/show_no_webgl_msg\"),v=t(\"./project\"),m=t(\"./layout/convert\"),y=t(\"./layout/spikes\"),x=t(\"./layout/tick_marks\"),b=t(\"is-mobile\"),_=function(){if(!navigator)return!1;var t;t||\"undefined\"==typeof navigator||(t=navigator.userAgent);t&&t.headers&&\"string\"==typeof t.headers[\"user-agent\"]&&(t=t.headers[\"user-agent\"]);if(\"string\"!=typeof t)return!1;var e=b({ua:t,tablet:!0});!1===e&&-1!==t.indexOf(\"Macintosh\")&&-1!==t.indexOf(\"Safari\")&&navigator.maxTouchPoints>1&&(e=!0);return e}();function w(t,e){var r=document.createElement(\"div\"),n=t.container;this.graphDiv=t.graphDiv;var a=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");a.style.position=\"absolute\",a.style.top=a.style.left=\"0px\",a.style.width=a.style.height=\"100%\",a.style[\"z-index\"]=20,a.style[\"pointer-events\"]=\"none\",r.appendChild(a),this.svgContainer=a,r.id=t.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=e,this.id=t.id||\"scene\",this.fullSceneLayout=e[this.id],this.plotArgs=[[],{},{}],this.axesOptions=m(e,e[this.id]),this.spikeOptions=y(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=this.pixelRatio||t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],this.convertAnnotations=u.getComponentMethod(\"annotations3d\",\"convert\"),this.drawAnnotations=u.getComponentMethod(\"annotations3d\",\"draw\"),this.initializeGLPlot()}var k=w.prototype;k.tryCreatePlot=function(){var t={canvas:this.canvas,gl:this.gl,glOptions:{preserveDrawingBuffer:_,premultipliedAlpha:!0,antialias:!0},container:this.container,axes:this.axesOptions,spikes:this.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1,cameraObject:this.camera,pixelRatio:this.pixelRatio};if(this.staticMode){if(!(a||(n=document.createElement(\"canvas\"),a=l({canvas:n,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"error creating static canvas/context for image server\");t.gl=a,t.canvas=n}var e=0;try{this.glplot=s(t)}catch(r){e++;try{this.glplot=s(t)}catch(t){e++}}return e<2},k.initializeGLCamera=function(){var t=this.fullSceneLayout.camera,e=\"orthographic\"===t.projection.type;this.camera=o(this.container,{center:[t.center.x,t.center.y,t.center.z],eye:[t.eye.x,t.eye.y,t.eye.z],up:[t.up.x,t.up.y,t.up.z],_ortho:e,zoomMin:.01,zoomMax:100,mode:\"orbit\"})},k.initializeGLPlot=function(){var t=this;if(t.initializeGLCamera(),!t.tryCreatePlot())return g(t);t.traces={},t.make4thDimension();var e=t.graphDiv,r=e.layout,n=function(){var e={};return t.isCameraChanged(r)&&(e[t.id+\".camera\"]=t.getCamera()),t.isAspectChanged(r)&&(e[t.id+\".aspectratio\"]=t.glplot.getAspectratio()),e},a=function(t){if(!1!==t.fullSceneLayout.dragmode){var e=n();t.saveLayout(r),t.graphDiv.emit(\"plotly_relayout\",e)}};return t.glplot.canvas.addEventListener(\"mouseup\",function(){a(t)}),t.glplot.canvas.addEventListener(\"wheel\",function(r){if(e._context._scrollZoom.gl3d){if(t.camera._ortho){var n=r.deltaX>r.deltaY?1.1:1/1.1,i=t.glplot.getAspectratio();t.glplot.setAspectratio({x:n*i.x,y:n*i.y,z:n*i.z})}a(t)}},!!c&&{passive:!1}),t.glplot.canvas.addEventListener(\"mousemove\",function(){if(!1!==t.fullSceneLayout.dragmode&&0!==t.camera.mouseListener.buttons){var e=n();t.graphDiv.emit(\"plotly_relayouting\",e)}}),t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",function(r){e&&e.emit&&e.emit(\"plotly_webglcontextlost\",{event:r,layer:t.id})},!1),t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=function(){t.render()},!0},k.render=function(){var t,e=this,r=e.graphDiv,n=e.svgContainer,a=e.container.getBoundingClientRect(),i=a.width,o=a.height;n.setAttributeNS(null,\"viewBox\",\"0 0 \"+i+\" \"+o),n.setAttributeNS(null,\"width\",i),n.setAttributeNS(null,\"height\",o),x(e),e.glplot.axes.update(e.axesOptions);for(var s,l=Object.keys(e.traces),c=null,u=e.glplot.selection,d=0;d<l.length;++d)\"skip\"!==(t=e.traces[l[d]]).data.hoverinfo&&t.handlePick(u)&&(c=t),t.setContourLevels&&t.setContourLevels();function g(t,r){var n=e.fullSceneLayout[t];return f.tickText(n,n.d2l(r),\"hover\").text}if(null!==c){var m=v(e.glplot.cameraParams,u.dataCoordinate);t=c.data;var y,b=r._fullData[t.index],_=u.index,w={xLabel:g(\"xaxis\",u.traceCoordinate[0]),yLabel:g(\"yaxis\",u.traceCoordinate[1]),zLabel:g(\"zaxis\",u.traceCoordinate[2])},k=p.castHoverinfo(b,e.fullLayout,_),T=(k||\"\").split(\"+\"),M=k&&\"all\"===k;b.hovertemplate||M||(-1===T.indexOf(\"x\")&&(w.xLabel=void 0),-1===T.indexOf(\"y\")&&(w.yLabel=void 0),-1===T.indexOf(\"z\")&&(w.zLabel=void 0),-1===T.indexOf(\"text\")&&(u.textLabel=void 0),-1===T.indexOf(\"name\")&&(c.name=void 0));var A=[];\"cone\"===t.type||\"streamtube\"===t.type?(w.uLabel=g(\"xaxis\",u.traceCoordinate[3]),(M||-1!==T.indexOf(\"u\"))&&A.push(\"u: \"+w.uLabel),w.vLabel=g(\"yaxis\",u.traceCoordinate[4]),(M||-1!==T.indexOf(\"v\"))&&A.push(\"v: \"+w.vLabel),w.wLabel=g(\"zaxis\",u.traceCoordinate[5]),(M||-1!==T.indexOf(\"w\"))&&A.push(\"w: \"+w.wLabel),w.normLabel=u.traceCoordinate[6].toPrecision(3),(M||-1!==T.indexOf(\"norm\"))&&A.push(\"norm: \"+w.normLabel),\"streamtube\"===t.type&&(w.divergenceLabel=u.traceCoordinate[7].toPrecision(3),(M||-1!==T.indexOf(\"divergence\"))&&A.push(\"divergence: \"+w.divergenceLabel)),u.textLabel&&A.push(u.textLabel),y=A.join(\"<br>\")):\"isosurface\"===t.type||\"volume\"===t.type?(w.valueLabel=f.tickText(e._mockAxis,e._mockAxis.d2l(u.traceCoordinate[3]),\"hover\").text,A.push(\"value: \"+w.valueLabel),u.textLabel&&A.push(u.textLabel),y=A.join(\"<br>\")):y=u.textLabel;var S={x:u.traceCoordinate[0],y:u.traceCoordinate[1],z:u.traceCoordinate[2],data:b._input,fullData:b,curveNumber:b.index,pointNumber:_};p.appendArrayPointValue(S,b,_),t._module.eventData&&(S=b._module.eventData(S,u,b,{},_));var E={points:[S]};e.fullSceneLayout.hovermode&&p.loneHover({trace:b,x:(.5+.5*m[0]/m[3])*i,y:(.5-.5*m[1]/m[3])*o,xLabel:w.xLabel,yLabel:w.yLabel,zLabel:w.zLabel,text:y,name:c.name,color:p.castHoverOption(b,_,\"bgcolor\")||c.color,borderColor:p.castHoverOption(b,_,\"bordercolor\"),fontFamily:p.castHoverOption(b,_,\"font.family\"),fontSize:p.castHoverOption(b,_,\"font.size\"),fontColor:p.castHoverOption(b,_,\"font.color\"),nameLength:p.castHoverOption(b,_,\"namelength\"),textAlign:p.castHoverOption(b,_,\"align\"),hovertemplate:h.castOption(b,_,\"hovertemplate\"),hovertemplateLabels:h.extendFlat({},S,w),eventData:[S]},{container:n,gd:r}),u.buttons&&u.distance<5?r.emit(\"plotly_click\",E):r.emit(\"plotly_hover\",E),s=E}else p.loneUnhover(n),r.emit(\"plotly_unhover\",s);e.drawAnnotations(e)},k.recoverContext=function(){var t=this;t.glplot.dispose();var e=function(){t.glplot.gl.isContextLost()?requestAnimationFrame(e):t.initializeGLPlot()?t.plot.apply(t,t.plotArgs):h.error(\"Catastrophic and unrecoverable WebGL error. Context lost.\")};requestAnimationFrame(e)};var T=[\"xaxis\",\"yaxis\",\"zaxis\"];function M(t,e,r){for(var n=t.fullSceneLayout,a=0;a<3;a++){var i=T[a],o=i.charAt(0),s=n[i],l=e[o],c=e[o+\"calendar\"],u=e[\"_\"+o+\"length\"];if(h.isArrayOrTypedArray(l))for(var f,p=0;p<(u||l.length);p++)if(h.isArrayOrTypedArray(l[p]))for(var d=0;d<l[p].length;++d)f=s.d2l(l[p][d],0,c),!isNaN(f)&&isFinite(f)&&(r[0][a]=Math.min(r[0][a],f),r[1][a]=Math.max(r[1][a],f));else f=s.d2l(l[p],0,c),!isNaN(f)&&isFinite(f)&&(r[0][a]=Math.min(r[0][a],f),r[1][a]=Math.max(r[1][a],f));else r[0][a]=Math.min(r[0][a],0),r[1][a]=Math.max(r[1][a],u-1)}}k.plot=function(t,e,r){if(this.plotArgs=[t,e,r],!this.glplot.contextLost){var n,a,i,o,s,l,c=e[this.id],u=r[this.id];this.fullLayout=e,this.fullSceneLayout=c,this.axesOptions.merge(e,c),this.spikeOptions.merge(c),this.setViewport(c),this.updateFx(c.dragmode,c.hovermode),this.camera.enableWheel=this.graphDiv._context._scrollZoom.gl3d,this.glplot.setClearColor(d(c.bgcolor)),this.setConvert(s),t?Array.isArray(t)||(t=[t]):t=[];var h=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(i=0;i<t.length;++i)!0===(n=t[i]).visible&&0!==n._length&&M(this,n,h);!function(t,e){for(var r=t.fullSceneLayout,n=r.annotations||[],a=0;a<3;a++)for(var i=T[a],o=i.charAt(0),s=r[i],l=0;l<n.length;l++){var c=n[l];if(c.visible){var u=s.r2l(c[o]);!isNaN(u)&&isFinite(u)&&(e[0][a]=Math.min(e[0][a],u),e[1][a]=Math.max(e[1][a],u))}}}(this,h);var f=[1,1,1];for(o=0;o<3;++o)h[1][o]===h[0][o]?f[o]=1:f[o]=1/(h[1][o]-h[0][o]);for(this.dataScale=f,this.convertAnnotations(this),i=0;i<t.length;++i)!0===(n=t[i]).visible&&0!==n._length&&((a=this.traces[n.uid])?a.data.type===n.type?a.update(n):(a.dispose(),a=n._module.plot(this,n),this.traces[n.uid]=a):(a=n._module.plot(this,n),this.traces[n.uid]=a),a.name=n.name);var p=Object.keys(this.traces);t:for(i=0;i<p.length;++i){for(o=0;o<t.length;++o)if(t[o].uid===p[i]&&!0===t[o].visible&&0!==t[o]._length)continue t;(a=this.traces[p[i]]).dispose(),delete this.traces[p[i]]}this.glplot.objects.sort(function(t,e){return t._trace.data.index-e._trace.data.index});var g=[[0,0,0],[0,0,0]],v=[],m={};for(i=0;i<3;++i){if((l=(s=c[T[i]]).type)in m?(m[l].acc*=f[i],m[l].count+=1):m[l]={acc:f[i],count:1},s.autorange){g[0][i]=1/0,g[1][i]=-1/0;var y=this.glplot.objects,x=this.fullSceneLayout.annotations||[],b=s._name.charAt(0);for(o=0;o<y.length;o++){var _=y[o],w=_.bounds,k=_._trace.data._pad||0;\"ErrorBars\"===_.constructor.name&&s._lowerLogErrorBound?g[0][i]=Math.min(g[0][i],s._lowerLogErrorBound):g[0][i]=Math.min(g[0][i],w[0][i]/f[i]-k),g[1][i]=Math.max(g[1][i],w[1][i]/f[i]+k)}for(o=0;o<x.length;o++){var A=x[o];if(A.visible){var S=s.r2l(A[b]);g[0][i]=Math.min(g[0][i],S),g[1][i]=Math.max(g[1][i],S)}}if(\"rangemode\"in s&&\"tozero\"===s.rangemode&&(g[0][i]=Math.min(g[0][i],0),g[1][i]=Math.max(g[1][i],0)),g[0][i]>g[1][i])g[0][i]=-1,g[1][i]=1;else{var E=g[1][i]-g[0][i];g[0][i]-=E/32,g[1][i]+=E/32}if(\"reversed\"===s.autorange){var L=g[0][i];g[0][i]=g[1][i],g[1][i]=L}}else{var C=s.range;g[0][i]=s.r2l(C[0]),g[1][i]=s.r2l(C[1])}g[0][i]===g[1][i]&&(g[0][i]-=1,g[1][i]+=1),v[i]=g[1][i]-g[0][i],this.glplot.setBounds(i,{min:g[0][i]*f[i],max:g[1][i]*f[i]})}var P=[1,1,1];for(i=0;i<3;++i){var O=m[l=(s=c[T[i]]).type];P[i]=Math.pow(O.acc,1/O.count)/f[i]}var z;if(\"auto\"===c.aspectmode)z=Math.max.apply(null,P)/Math.min.apply(null,P)<=4?P:[1,1,1];else if(\"cube\"===c.aspectmode)z=[1,1,1];else if(\"data\"===c.aspectmode)z=P;else{if(\"manual\"!==c.aspectmode)throw new Error(\"scene.js aspectRatio was not one of the enumerated types\");var I=c.aspectratio;z=[I.x,I.y,I.z]}c.aspectratio.x=u.aspectratio.x=z[0],c.aspectratio.y=u.aspectratio.y=z[1],c.aspectratio.z=u.aspectratio.z=z[2],this.glplot.setAspectratio(c.aspectratio),this.viewInitial.aspectratio||(this.viewInitial.aspectratio={x:c.aspectratio.x,y:c.aspectratio.y,z:c.aspectratio.z});var D=c.domain||null,R=e._size||null;if(D&&R){var F=this.container.style;F.position=\"absolute\",F.left=R.l+D.x[0]*R.w+\"px\",F.top=R.t+(1-D.y[1])*R.h+\"px\",F.width=R.w*(D.x[1]-D.x[0])+\"px\",F.height=R.h*(D.y[1]-D.y[0])+\"px\"}this.glplot.redraw()}},k.destroy=function(){this.glplot&&(this.camera.mouseListener.enabled=!1,this.container.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null,this.glplot.dispose(),this.container.parentNode.removeChild(this.container),this.glplot=null)},k.getCamera=function(){var t;return this.camera.view.recalcMatrix(this.camera.view.lastT()),{up:{x:(t=this.camera).up[0],y:t.up[1],z:t.up[2]},center:{x:t.center[0],y:t.center[1],z:t.center[2]},eye:{x:t.eye[0],y:t.eye[1],z:t.eye[2]},projection:{type:!0===t._ortho?\"orthographic\":\"perspective\"}}},k.setViewport=function(t){var e,r=t.camera;this.camera.lookAt.apply(this,[[(e=r).eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]),this.glplot.setAspectratio(t.aspectratio),\"orthographic\"===r.projection.type!==this.camera._ortho&&(this.glplot.redraw(),this.glplot.clearRGBA(),this.glplot.dispose(),this.initializeGLPlot())},k.isCameraChanged=function(t){var e=this.getCamera(),r=h.nestedProperty(t,this.id+\".camera\").get();function n(t,e,r,n){var a=[\"up\",\"center\",\"eye\"],i=[\"x\",\"y\",\"z\"];return e[a[r]]&&t[a[r]][i[n]]===e[a[r]][i[n]]}var a=!1;if(void 0===r)a=!0;else{for(var i=0;i<3;i++)for(var o=0;o<3;o++)if(!n(e,r,i,o)){a=!0;break}(!r.projection||e.projection&&e.projection.type!==r.projection.type)&&(a=!0)}return a},k.isAspectChanged=function(t){var e=this.glplot.getAspectratio(),r=h.nestedProperty(t,this.id+\".aspectratio\").get();return void 0===r||r.x!==e.x||r.y!==e.y||r.z!==e.z},k.saveLayout=function(t){var e,r,n,a,i,o,s=this.fullLayout,l=this.isCameraChanged(t),c=this.isAspectChanged(t),f=l||c;if(f){var p={};if(l&&(e=this.getCamera(),n=(r=h.nestedProperty(t,this.id+\".camera\")).get(),p[this.id+\".camera\"]=n),c&&(a=this.glplot.getAspectratio(),o=(i=h.nestedProperty(t,this.id+\".aspectratio\")).get(),p[this.id+\".aspectratio\"]=o),u.call(\"_storeDirectGUIEdit\",t,s._preGUI,p),l)r.set(e),h.nestedProperty(s,this.id+\".camera\").set(e);if(c)i.set(a),h.nestedProperty(s,this.id+\".aspectratio\").set(a),this.glplot.redraw()}return f},k.updateFx=function(t,e){var r=this.camera;if(r)if(\"orbit\"===t)r.mode=\"orbit\",r.keyBindingMode=\"rotate\";else if(\"turntable\"===t){r.up=[0,0,1],r.mode=\"turntable\",r.keyBindingMode=\"rotate\";var n=this.graphDiv,a=n._fullLayout,i=this.fullSceneLayout.camera,o=i.up.x,s=i.up.y,l=i.up.z;if(l/Math.sqrt(o*o+s*s+l*l)<.999){var c=this.id+\".camera.up\",f={x:0,y:0,z:1},p={};p[c]=f;var d=n.layout;u.call(\"_storeDirectGUIEdit\",d,a._preGUI,p),i.up=f,h.nestedProperty(d,c).set(f)}}else r.keyBindingMode=t;this.fullSceneLayout.hovermode=e},k.toImage=function(t){t||(t=\"png\"),this.staticMode&&this.container.appendChild(n),this.glplot.redraw();var e=this.glplot.gl,r=e.drawingBufferWidth,a=e.drawingBufferHeight;e.bindFramebuffer(e.FRAMEBUFFER,null);var i=new Uint8Array(r*a*4);e.readPixels(0,0,r,a,e.RGBA,e.UNSIGNED_BYTE,i);for(var o=0,s=a-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var c=0;c<4;++c){var u=i[4*(r*o+l)+c];i[4*(r*o+l)+c]=i[4*(r*s+l)+c],i[4*(r*s+l)+c]=u}var h=document.createElement(\"canvas\");h.width=r,h.height=a;var f,p=h.getContext(\"2d\"),d=p.createImageData(r,a);switch(d.data.set(i),p.putImageData(d,0,0),t){case\"jpeg\":f=h.toDataURL(\"image/jpeg\");break;case\"webp\":f=h.toDataURL(\"image/webp\");break;default:f=h.toDataURL(\"image/png\")}return this.staticMode&&this.container.removeChild(n),f},k.setConvert=function(){for(var t=0;t<3;t++){var e=this.fullSceneLayout[T[t]];f.setConvert(e,this.fullLayout),e.setScale=h.noop}},k.make4thDimension=function(){var t=this.graphDiv._fullLayout;this._mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},f.setConvert(this._mockAxis,t)},e.exports=w},{\"../../components/fx\":630,\"../../lib\":717,\"../../lib/show_no_webgl_msg\":738,\"../../lib/str2rgbarray\":740,\"../../plots/cartesian/axes\":765,\"../../registry\":846,\"./layout/convert\":809,\"./layout/spikes\":812,\"./layout/tick_marks\":813,\"./project\":814,\"gl-plot3d\":293,\"has-passive-events\":413,\"is-mobile\":422,\"webgl-context\":555}],816:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n){n=n||t.length;for(var a=new Array(n),i=0;i<n;i++)a[i]=[t[i],e[i],r[i]];return a}},{}],817:[function(t,e,r){\"use strict\";var n=t(\"./font_attributes\"),a=t(\"./animation_attributes\"),i=t(\"../components/color/attributes\"),o=t(\"./pad_attributes\"),s=t(\"../lib/extend\").extendFlat,l=n({editType:\"calc\"});l.family.dflt='\"Open Sans\", verdana, arial, sans-serif',l.size.dflt=12,l.color.dflt=i.defaultLine,e.exports={font:l,title:{text:{valType:\"string\",editType:\"layoutstyle\"},font:n({editType:\"layoutstyle\"}),xref:{valType:\"enumerated\",dflt:\"container\",values:[\"container\",\"paper\"],editType:\"layoutstyle\"},yref:{valType:\"enumerated\",dflt:\"container\",values:[\"container\",\"paper\"],editType:\"layoutstyle\"},x:{valType:\"number\",min:0,max:1,dflt:.5,editType:\"layoutstyle\"},y:{valType:\"number\",min:0,max:1,dflt:\"auto\",editType:\"layoutstyle\"},xanchor:{valType:\"enumerated\",dflt:\"auto\",values:[\"auto\",\"left\",\"center\",\"right\"],editType:\"layoutstyle\"},yanchor:{valType:\"enumerated\",dflt:\"auto\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],editType:\"layoutstyle\"},pad:s(o({editType:\"layoutstyle\"}),{}),editType:\"layoutstyle\"},uniformtext:{mode:{valType:\"enumerated\",values:[!1,\"hide\",\"show\"],dflt:!1,editType:\"plot\"},minsize:{valType:\"number\",min:0,dflt:0,editType:\"plot\"},editType:\"plot\"},autosize:{valType:\"boolean\",dflt:!1,editType:\"none\"},width:{valType:\"number\",min:10,dflt:700,editType:\"plot\"},height:{valType:\"number\",min:10,dflt:450,editType:\"plot\"},margin:{l:{valType:\"number\",min:0,dflt:80,editType:\"plot\"},r:{valType:\"number\",min:0,dflt:80,editType:\"plot\"},t:{valType:\"number\",min:0,dflt:100,editType:\"plot\"},b:{valType:\"number\",min:0,dflt:80,editType:\"plot\"},pad:{valType:\"number\",min:0,dflt:0,editType:\"plot\"},autoexpand:{valType:\"boolean\",dflt:!0,editType:\"plot\"},editType:\"plot\"},paper_bgcolor:{valType:\"color\",dflt:i.background,editType:\"plot\"},plot_bgcolor:{valType:\"color\",dflt:i.background,editType:\"layoutstyle\"},separators:{valType:\"string\",editType:\"plot\"},hidesources:{valType:\"boolean\",dflt:!1,editType:\"plot\"},showlegend:{valType:\"boolean\",editType:\"legend\"},colorway:{valType:\"colorlist\",dflt:i.defaults,editType:\"calc\"},datarevision:{valType:\"any\",editType:\"calc\"},uirevision:{valType:\"any\",editType:\"none\"},editrevision:{valType:\"any\",editType:\"none\"},selectionrevision:{valType:\"any\",editType:\"none\"},template:{valType:\"any\",editType:\"calc\"},modebar:{orientation:{valType:\"enumerated\",values:[\"v\",\"h\"],dflt:\"h\",editType:\"modebar\"},bgcolor:{valType:\"color\",editType:\"modebar\"},color:{valType:\"color\",editType:\"modebar\"},activecolor:{valType:\"color\",editType:\"modebar\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"modebar\"},meta:{valType:\"any\",arrayOk:!0,editType:\"plot\"},transition:s({},a.transition,{editType:\"none\"}),_deprecated:{title:{valType:\"string\",editType:\"layoutstyle\"},titlefont:n({editType:\"layoutstyle\"})}}},{\"../components/color/attributes\":591,\"../lib/extend\":708,\"./animation_attributes\":760,\"./font_attributes\":791,\"./pad_attributes\":825}],818:[function(t,e,r){\"use strict\";var n={\"open-street-map\":{id:\"osm\",version:8,sources:{\"plotly-osm-tiles\":{type:\"raster\",attribution:'<a href=\"http://www.openstreetmap.org/about/\" target=\"_blank\">\\xa9 OpenStreetMap</a>',tiles:[\"https://a.tile.openstreetmap.org/{z}/{x}/{y}.png\",\"https://b.tile.openstreetmap.org/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-osm-tiles\",type:\"raster\",source:\"plotly-osm-tiles\",minzoom:0,maxzoom:22}]},\"white-bg\":{id:\"white-bg\",version:8,sources:{},layers:[{id:\"white-bg\",type:\"background\",paint:{\"background-color\":\"#FFFFFF\"},minzoom:0,maxzoom:22}]},\"carto-positron\":{id:\"carto-positron\",version:8,sources:{\"plotly-carto-positron\":{type:\"raster\",attribution:'<a href=\"https://carto.com/\" target=\"_blank\">\\xa9 CARTO</a>',tiles:[\"https://cartodb-basemaps-c.global.ssl.fastly.net/light_all/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-carto-positron\",type:\"raster\",source:\"plotly-carto-positron\",minzoom:0,maxzoom:22}]},\"carto-darkmatter\":{id:\"carto-darkmatter\",version:8,sources:{\"plotly-carto-darkmatter\":{type:\"raster\",attribution:'<a href=\"https://carto.com/\" target=\"_blank\">\\xa9 CARTO</a>',tiles:[\"https://cartodb-basemaps-c.global.ssl.fastly.net/dark_all/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-carto-darkmatter\",type:\"raster\",source:\"plotly-carto-darkmatter\",minzoom:0,maxzoom:22}]},\"stamen-terrain\":{id:\"stamen-terrain\",version:8,sources:{\"plotly-stamen-terrain\":{type:\"raster\",attribution:'Map tiles by <a href=\"http://stamen.com\">Stamen Design</a>, under <a href=\"http://creativecommons.org/licenses/by/3.0\">CC BY 3.0</a> | Data by <a href=\"http://openstreetmap.org\">OpenStreetMap</a>, under <a href=\"http://www.openstreetmap.org/copyright\">ODbL</a>.',tiles:[\"https://stamen-tiles.a.ssl.fastly.net/terrain/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-stamen-terrain\",type:\"raster\",source:\"plotly-stamen-terrain\",minzoom:0,maxzoom:22}]},\"stamen-toner\":{id:\"stamen-toner\",version:8,sources:{\"plotly-stamen-toner\":{type:\"raster\",attribution:'Map tiles by <a href=\"http://stamen.com\">Stamen Design</a>, under <a href=\"http://creativecommons.org/licenses/by/3.0\">CC BY 3.0</a> | Data by <a href=\"http://openstreetmap.org\">OpenStreetMap</a>, under <a href=\"http://www.openstreetmap.org/copyright\">ODbL</a>.',tiles:[\"https://stamen-tiles.a.ssl.fastly.net/toner/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-stamen-toner\",type:\"raster\",source:\"plotly-stamen-toner\",minzoom:0,maxzoom:22}]},\"stamen-watercolor\":{id:\"stamen-watercolor\",version:8,sources:{\"plotly-stamen-watercolor\":{type:\"raster\",attribution:'Map tiles by <a href=\"http://stamen.com\">Stamen Design</a>, under <a href=\"http://creativecommons.org/licenses/by/3.0\">CC BY 3.0</a> | Data by <a href=\"http://openstreetmap.org\">OpenStreetMap</a>, under <a href=\"http://creativecommons.org/licenses/by-sa/3.0\">CC BY SA</a>.',tiles:[\"https://stamen-tiles.a.ssl.fastly.net/watercolor/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-stamen-watercolor\",type:\"raster\",source:\"plotly-stamen-watercolor\",minzoom:0,maxzoom:22}]}},a=Object.keys(n);e.exports={requiredVersion:\"1.3.2\",styleUrlPrefix:\"mapbox://styles/mapbox/\",styleUrlSuffix:\"v9\",styleValuesMapbox:[\"basic\",\"streets\",\"outdoors\",\"light\",\"dark\",\"satellite\",\"satellite-streets\"],styleValueDflt:\"basic\",stylesNonMapbox:n,styleValuesNonMapbox:a,traceLayerPrefix:\"plotly-trace-layer-\",layoutLayerPrefix:\"plotly-layout-layer-\",wrongVersionErrorMsg:[\"Your custom plotly.js bundle is not using the correct mapbox-gl version\",\"Please install mapbox-gl@1.3.2.\"].join(\"\\n\"),noAccessTokenErrorMsg:[\"Missing Mapbox access token.\",\"Mapbox trace type require a Mapbox access token to be registered.\",\"For example:\",\"  Plotly.plot(gd, data, layout, { mapboxAccessToken: 'my-access-token' });\",\"More info here: https://www.mapbox.com/help/define-access-token/\"].join(\"\\n\"),missingStyleErrorMsg:[\"No valid mapbox style found, please set `mapbox.style` to one of:\",a.join(\", \"),\"or register a Mapbox access token to use a Mapbox-served style.\"].join(\"\\n\"),multipleTokensErrorMsg:[\"Set multiple mapbox access token across different mapbox subplot,\",\"using first token found as mapbox-gl does not allow multipleaccess tokens on the same page.\"].join(\"\\n\"),mapOnErrorMsg:\"Mapbox error.\",mapboxLogo:{path0:\"m 10.5,1.24 c -5.11,0 -9.25,4.15 -9.25,9.25 0,5.1 4.15,9.25 9.25,9.25 5.1,0 9.25,-4.15 9.25,-9.25 0,-5.11 -4.14,-9.25 -9.25,-9.25 z m 4.39,11.53 c -1.93,1.93 -4.78,2.31 -6.7,2.31 -0.7,0 -1.41,-0.05 -2.1,-0.16 0,0 -1.02,-5.64 2.14,-8.81 0.83,-0.83 1.95,-1.28 3.13,-1.28 1.27,0 2.49,0.51 3.39,1.42 1.84,1.84 1.89,4.75 0.14,6.52 z\",path1:\"M 10.5,-0.01 C 4.7,-0.01 0,4.7 0,10.49 c 0,5.79 4.7,10.5 10.5,10.5 5.8,0 10.5,-4.7 10.5,-10.5 C 20.99,4.7 16.3,-0.01 10.5,-0.01 Z m 0,19.75 c -5.11,0 -9.25,-4.15 -9.25,-9.25 0,-5.1 4.14,-9.26 9.25,-9.26 5.11,0 9.25,4.15 9.25,9.25 0,5.13 -4.14,9.26 -9.25,9.26 z\",path2:\"M 14.74,6.25 C 12.9,4.41 9.98,4.35 8.23,6.1 5.07,9.27 6.09,14.91 6.09,14.91 c 0,0 5.64,1.02 8.81,-2.14 C 16.64,11 16.59,8.09 14.74,6.25 Z m -2.27,4.09 -0.91,1.87 -0.9,-1.87 -1.86,-0.91 1.86,-0.9 0.9,-1.87 0.91,1.87 1.86,0.9 z\",polygon:\"11.56,12.21 10.66,10.34 8.8,9.43 10.66,8.53 11.56,6.66 12.47,8.53 14.33,9.43 12.47,10.34\"},styleRules:{map:\"overflow:hidden;position:relative;\",\"missing-css\":\"display:none;\",canary:\"background-color:salmon;\",\"ctrl-bottom-left\":\"position: absolute; pointer-events: none; z-index: 2; bottom: 0; left: 0;\",\"ctrl-bottom-right\":\"position: absolute; pointer-events: none; z-index: 2; right: 0; bottom: 0;\",ctrl:\"clear: both; pointer-events: auto; transform: translate(0, 0);\",\"ctrl-attrib.mapboxgl-compact .mapboxgl-ctrl-attrib-inner\":\"display: none;\",\"ctrl-attrib.mapboxgl-compact:hover .mapboxgl-ctrl-attrib-inner\":\"display: block; margin-top:2px\",\"ctrl-attrib.mapboxgl-compact:hover\":\"padding: 2px 24px 2px 4px; visibility: visible; margin-top: 6px;\",\"ctrl-attrib.mapboxgl-compact::after\":'content: \"\"; cursor: pointer; position: absolute; background-image: url(\\'data:image/svg+xml;charset=utf-8,%3Csvg viewBox=\"0 0 20 20\" xmlns=\"http://www.w3.org/2000/svg\"%3E %3Cpath fill=\"%23333333\" fill-rule=\"evenodd\" d=\"M4,10a6,6 0 1,0 12,0a6,6 0 1,0 -12,0 M9,7a1,1 0 1,0 2,0a1,1 0 1,0 -2,0 M9,10a1,1 0 1,1 2,0l0,3a1,1 0 1,1 -2,0\"/%3E %3C/svg%3E\\'); background-color: rgba(255, 255, 255, 0.5); width: 24px; height: 24px; box-sizing: border-box; border-radius: 12px;',\"ctrl-attrib.mapboxgl-compact\":\"min-height: 20px; padding: 0; margin: 10px; position: relative; background-color: #fff; border-radius: 3px 12px 12px 3px;\",\"ctrl-bottom-right > .mapboxgl-ctrl-attrib.mapboxgl-compact::after\":\"bottom: 0; right: 0\",\"ctrl-bottom-left > .mapboxgl-ctrl-attrib.mapboxgl-compact::after\":\"bottom: 0; left: 0\",\"ctrl-bottom-left .mapboxgl-ctrl\":\"margin: 0 0 10px 10px; float: left;\",\"ctrl-bottom-right .mapboxgl-ctrl\":\"margin: 0 10px 10px 0; float: right;\",\"ctrl-attrib\":\"color: rgba(0, 0, 0, 0.75); text-decoration: none; font-size: 12px\",\"ctrl-attrib a\":\"color: rgba(0, 0, 0, 0.75); text-decoration: none; font-size: 12px\",\"ctrl-attrib a:hover\":\"color: inherit; text-decoration: underline;\",\"ctrl-attrib .mapbox-improve-map\":\"font-weight: bold; margin-left: 2px;\",\"attrib-empty\":\"display: none;\",\"ctrl-logo\":'display:block; width: 21px; height: 21px; background-image: url(\\'data:image/svg+xml;charset=utf-8,%3C?xml version=\"1.0\" encoding=\"utf-8\"?%3E %3Csvg version=\"1.1\" id=\"Layer_1\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" x=\"0px\" y=\"0px\" viewBox=\"0 0 21 21\" style=\"enable-background:new 0 0 21 21;\" xml:space=\"preserve\"%3E%3Cg transform=\"translate(0,0.01)\"%3E%3Cpath d=\"m 10.5,1.24 c -5.11,0 -9.25,4.15 -9.25,9.25 0,5.1 4.15,9.25 9.25,9.25 5.1,0 9.25,-4.15 9.25,-9.25 0,-5.11 -4.14,-9.25 -9.25,-9.25 z m 4.39,11.53 c -1.93,1.93 -4.78,2.31 -6.7,2.31 -0.7,0 -1.41,-0.05 -2.1,-0.16 0,0 -1.02,-5.64 2.14,-8.81 0.83,-0.83 1.95,-1.28 3.13,-1.28 1.27,0 2.49,0.51 3.39,1.42 1.84,1.84 1.89,4.75 0.14,6.52 z\" style=\"opacity:0.9;fill:%23ffffff;enable-background:new\" class=\"st0\"/%3E%3Cpath d=\"M 10.5,-0.01 C 4.7,-0.01 0,4.7 0,10.49 c 0,5.79 4.7,10.5 10.5,10.5 5.8,0 10.5,-4.7 10.5,-10.5 C 20.99,4.7 16.3,-0.01 10.5,-0.01 Z m 0,19.75 c -5.11,0 -9.25,-4.15 -9.25,-9.25 0,-5.1 4.14,-9.26 9.25,-9.26 5.11,0 9.25,4.15 9.25,9.25 0,5.13 -4.14,9.26 -9.25,9.26 z\" style=\"opacity:0.35;enable-background:new\" class=\"st1\"/%3E%3Cpath d=\"M 14.74,6.25 C 12.9,4.41 9.98,4.35 8.23,6.1 5.07,9.27 6.09,14.91 6.09,14.91 c 0,0 5.64,1.02 8.81,-2.14 C 16.64,11 16.59,8.09 14.74,6.25 Z m -2.27,4.09 -0.91,1.87 -0.9,-1.87 -1.86,-0.91 1.86,-0.9 0.9,-1.87 0.91,1.87 1.86,0.9 z\" style=\"opacity:0.35;enable-background:new\" class=\"st1\"/%3E%3Cpolygon points=\"11.56,12.21 10.66,10.34 8.8,9.43 10.66,8.53 11.56,6.66 12.47,8.53 14.33,9.43 12.47,10.34 \" style=\"opacity:0.9;fill:%23ffffff;enable-background:new\" class=\"st0\"/%3E%3C/g%3E%3C/svg%3E\\')'}}},{}],819:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){var r=t.split(\" \"),a=r[0],i=r[1],o=n.isArrayOrTypedArray(e)?n.mean(e):e,s=.5+o/100,l=1.5+o/100,c=[\"\",\"\"],u=[0,0];switch(a){case\"top\":c[0]=\"top\",u[1]=-l;break;case\"bottom\":c[0]=\"bottom\",u[1]=l}switch(i){case\"left\":c[1]=\"right\",u[0]=-s;break;case\"right\":c[1]=\"left\",u[0]=s}return{anchor:c[0]&&c[1]?c.join(\"-\"):c[0]?c[0]:c[1]?c[1]:\"center\",offset:u}}},{\"../../lib\":717}],820:[function(t,e,r){\"use strict\";var n=t(\"mapbox-gl\"),a=t(\"../../lib\"),i=t(\"../../plots/get_data\").getSubplotCalcData,o=t(\"../../constants/xmlns_namespaces\"),s=t(\"d3\"),l=t(\"../../components/drawing\"),c=t(\"../../lib/svg_text_utils\"),u=t(\"./mapbox\"),h=r.constants=t(\"./constants\");function f(t){return\"string\"==typeof t&&(-1!==h.styleValuesMapbox.indexOf(t)||0===t.indexOf(\"mapbox://\"))}r.name=\"mapbox\",r.attr=\"subplot\",r.idRoot=\"mapbox\",r.idRegex=r.attrRegex=a.counterRegex(\"mapbox\"),r.attributes={subplot:{valType:\"subplotid\",dflt:\"mapbox\",editType:\"calc\"}},r.layoutAttributes=t(\"./layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout_defaults\"),r.plot=function(t){var e=t._fullLayout,r=t.calcdata,o=e._subplots.mapbox;if(n.version!==h.requiredVersion)throw new Error(h.wrongVersionErrorMsg);var s=function(t,e){var r=t._fullLayout;if(\"\"===t._context.mapboxAccessToken)return\"\";for(var n=[],i=[],o=!1,s=!1,l=0;l<e.length;l++){var c=r[e[l]],u=c.accesstoken;f(c.style)&&(u?a.pushUnique(n,u):(f(c._input.style)&&(a.error(\"Uses Mapbox map style, but did not set an access token.\"),o=!0),s=!0)),u&&a.pushUnique(i,u)}if(s){var p=o?h.noAccessTokenErrorMsg:h.missingStyleErrorMsg;throw a.error(p),new Error(p)}return n.length?(n.length>1&&a.warn(h.multipleTokensErrorMsg),n[0]):(i.length&&a.log([\"Listed mapbox access token(s)\",i.join(\",\"),\"but did not use a Mapbox map style, ignoring token(s).\"].join(\" \")),\"\")}(t,o);n.accessToken=s;for(var l=0;l<o.length;l++){var c=o[l],p=i(r,\"mapbox\",c),d=e[c],g=d._subplot;g||(g=new u(t,c),e[c]._subplot=g),g.viewInitial||(g.viewInitial={center:a.extendFlat({},d.center),zoom:d.zoom,bearing:d.bearing,pitch:d.pitch}),g.plot(p,e,t._promises)}},r.clean=function(t,e,r,n){for(var a=n._subplots.mapbox||[],i=0;i<a.length;i++){var o=a[i];!e[o]&&n[o]._subplot&&n[o]._subplot.destroy()}},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.mapbox,n=e._size,a=0;a<r.length;a++){var i=e[r[a]],u=i.domain,f=i._subplot.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":f,x:n.l+n.w*u.x[0],y:n.t+n.h*(1-u.y[1]),width:n.w*(u.x[1]-u.x[0]),height:n.h*(u.y[1]-u.y[0]),preserveAspectRatio:\"none\"});var p=s.select(i._subplot.div);if(!(null===p.select(\".mapboxgl-ctrl-logo\").node().offsetParent)){var d=e._glimages.append(\"g\");d.attr(\"transform\",\"translate(\"+(n.l+n.w*u.x[0]+10)+\", \"+(n.t+n.h*(1-u.y[0])-31)+\")\"),d.append(\"path\").attr(\"d\",h.mapboxLogo.path0).style({opacity:.9,fill:\"#ffffff\",\"enable-background\":\"new\"}),d.append(\"path\").attr(\"d\",h.mapboxLogo.path1).style(\"opacity\",.35).style(\"enable-background\",\"new\"),d.append(\"path\").attr(\"d\",h.mapboxLogo.path2).style(\"opacity\",.35).style(\"enable-background\",\"new\"),d.append(\"polygon\").attr(\"points\",h.mapboxLogo.polygon).style({opacity:.9,fill:\"#ffffff\",\"enable-background\":\"new\"})}var g=p.select(\".mapboxgl-ctrl-attrib\").text().replace(\"Improve this map\",\"\"),v=e._glimages.append(\"g\"),m=v.append(\"text\");m.text(g).classed(\"static-attribution\",!0).attr({\"font-size\":12,\"font-family\":\"Arial\",color:\"rgba(0, 0, 0, 0.75)\",\"text-anchor\":\"end\",\"data-unformatted\":g});var y=l.bBox(m.node()),x=n.w*(u.x[1]-u.x[0]);if(y.width>x/2){var b=g.split(\"|\").join(\"<br>\");m.text(b).attr(\"data-unformatted\",b).call(c.convertToTspans,t),y=l.bBox(m.node())}m.attr(\"transform\",\"translate(-3, \"+(8-y.height)+\")\"),v.insert(\"rect\",\".static-attribution\").attr({x:-y.width-6,y:-y.height-3,width:y.width+6,height:y.height+3,fill:\"rgba(255, 255, 255, 0.75)\"});var _=1;y.width+6>x&&(_=x/(y.width+6));var w=[n.l+n.w*u.x[1],n.t+n.h*(1-u.y[0])];v.attr(\"transform\",\"translate(\"+w[0]+\",\"+w[1]+\") scale(\"+_+\")\")}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.mapbox,n=0;n<r.length;n++){e[r[n]]._subplot.updateFx(e)}}},{\"../../components/drawing\":613,\"../../constants/xmlns_namespaces\":694,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"../../plots/get_data\":800,\"./constants\":818,\"./layout_attributes\":822,\"./layout_defaults\":823,\"./mapbox\":824,d3:165,\"mapbox-gl\":428}],821:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./convert_text_opts\"),i=t(\"./constants\");function o(t,e){this.subplot=t,this.uid=t.uid+\"-\"+e,this.index=e,this.idSource=\"source-\"+this.uid,this.idLayer=i.layoutLayerPrefix+this.uid,this.sourceType=null,this.source=null,this.layerType=null,this.below=null,this.visible=!1}var s=o.prototype;function l(t){if(!t.visible)return!1;var e=t.source;if(Array.isArray(e)&&e.length>0){for(var r=0;r<e.length;r++)if(\"string\"!=typeof e[r]||0===e[r].length)return!1;return!0}return n.isPlainObject(e)||\"string\"==typeof e&&e.length>0}function c(t){var e={},r={};switch(t.type){case\"circle\":n.extendFlat(r,{\"circle-radius\":t.circle.radius,\"circle-color\":t.color,\"circle-opacity\":t.opacity});break;case\"line\":n.extendFlat(r,{\"line-width\":t.line.width,\"line-color\":t.color,\"line-opacity\":t.opacity,\"line-dasharray\":t.line.dash});break;case\"fill\":n.extendFlat(r,{\"fill-color\":t.color,\"fill-outline-color\":t.fill.outlinecolor,\"fill-opacity\":t.opacity});break;case\"symbol\":var i=t.symbol,o=a(i.textposition,i.iconsize);n.extendFlat(e,{\"icon-image\":i.icon+\"-15\",\"icon-size\":i.iconsize/10,\"text-field\":i.text,\"text-size\":i.textfont.size,\"text-anchor\":o.anchor,\"text-offset\":o.offset,\"symbol-placement\":i.placement}),n.extendFlat(r,{\"icon-color\":t.color,\"text-color\":i.textfont.color,\"text-opacity\":t.opacity});break;case\"raster\":n.extendFlat(r,{\"raster-fade-duration\":0,\"raster-opacity\":t.opacity})}return{layout:e,paint:r}}s.update=function(t){this.visible?this.needsNewImage(t)?this.updateImage(t):this.needsNewSource(t)?(this.removeLayer(),this.updateSource(t),this.updateLayer(t)):this.needsNewLayer(t)?this.updateLayer(t):this.updateStyle(t):(this.updateSource(t),this.updateLayer(t)),this.visible=l(t)},s.needsNewImage=function(t){return this.subplot.map.getSource(this.idSource)&&\"image\"===this.sourceType&&\"image\"===t.sourcetype&&(this.source!==t.source||JSON.stringify(this.coordinates)!==JSON.stringify(t.coordinates))},s.needsNewSource=function(t){return this.sourceType!==t.sourcetype||this.source!==t.source||this.layerType!==t.type},s.needsNewLayer=function(t){return this.layerType!==t.type||this.below!==this.subplot.belowLookup[\"layout-\"+this.index]},s.updateImage=function(t){this.subplot.map.getSource(this.idSource).updateImage({url:t.source,coordinates:t.coordinates})},s.updateSource=function(t){var e=this.subplot.map;if(e.getSource(this.idSource)&&e.removeSource(this.idSource),this.sourceType=t.sourcetype,this.source=t.source,l(t)){var r=function(t){var e,r=t.sourcetype,n=t.source,a={type:r};\"geojson\"===r?e=\"data\":\"vector\"===r?e=\"string\"==typeof n?\"url\":\"tiles\":\"raster\"===r?(e=\"tiles\",a.tileSize=256):\"image\"===r&&(e=\"url\",a.coordinates=t.coordinates);a[e]=n,t.sourceattribution&&(a.attribution=t.sourceattribution);return a}(t);e.addSource(this.idSource,r)}},s.updateLayer=function(t){var e,r=this.subplot,n=c(t),a=this.subplot.belowLookup[\"layout-\"+this.index];if(\"traces\"===a)for(var o=r.getMapLayers(),s=0;s<o.length;s++){var u=o[s].id;if(\"string\"==typeof u&&0===u.indexOf(i.traceLayerPrefix)){e=u;break}}else e=a;this.removeLayer(),l(t)&&r.addLayer({id:this.idLayer,source:this.idSource,\"source-layer\":t.sourcelayer||\"\",type:t.type,minzoom:t.minzoom,maxzoom:t.maxzoom,layout:n.layout,paint:n.paint},e),this.layerType=t.type,this.below=a},s.updateStyle=function(t){if(l(t)){var e=c(t);this.subplot.setOptions(this.idLayer,\"setLayoutProperty\",e.layout),this.subplot.setOptions(this.idLayer,\"setPaintProperty\",e.paint)}},s.removeLayer=function(){var t=this.subplot.map;t.getLayer(this.idLayer)&&t.removeLayer(this.idLayer)},s.dispose=function(){var t=this.subplot.map;t.getLayer(this.idLayer)&&t.removeLayer(this.idLayer),t.getSource(this.idSource)&&t.removeSource(this.idSource)},e.exports=function(t,e,r){var n=new o(t,e);return n.update(r),n}},{\"../../lib\":717,\"./constants\":818,\"./convert_text_opts\":819}],822:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/color\").defaultLine,i=t(\"../domain\").attributes,o=t(\"../font_attributes\"),s=t(\"../../traces/scatter/attributes\").textposition,l=t(\"../../plot_api/edit_types\").overrideAll,c=t(\"../../plot_api/plot_template\").templatedArray,u=t(\"./constants\"),h=o({});h.family.dflt=\"Open Sans Regular, Arial Unicode MS Regular\",(e.exports=l({_arrayAttrRegexps:[n.counterRegex(\"mapbox\",\".layers\",!0)],domain:i({name:\"mapbox\"}),accesstoken:{valType:\"string\",noBlank:!0,strict:!0},style:{valType:\"any\",values:u.styleValuesMapbox.concat(u.styleValuesNonMapbox),dflt:u.styleValueDflt},center:{lon:{valType:\"number\",dflt:0},lat:{valType:\"number\",dflt:0}},zoom:{valType:\"number\",dflt:1},bearing:{valType:\"number\",dflt:0},pitch:{valType:\"number\",dflt:0},layers:c(\"layer\",{visible:{valType:\"boolean\",dflt:!0},sourcetype:{valType:\"enumerated\",values:[\"geojson\",\"vector\",\"raster\",\"image\"],dflt:\"geojson\"},source:{valType:\"any\"},sourcelayer:{valType:\"string\",dflt:\"\"},sourceattribution:{valType:\"string\"},type:{valType:\"enumerated\",values:[\"circle\",\"line\",\"fill\",\"symbol\",\"raster\"],dflt:\"circle\"},coordinates:{valType:\"any\"},below:{valType:\"string\"},color:{valType:\"color\",dflt:a},opacity:{valType:\"number\",min:0,max:1,dflt:1},minzoom:{valType:\"number\",min:0,max:24,dflt:0},maxzoom:{valType:\"number\",min:0,max:24,dflt:24},circle:{radius:{valType:\"number\",dflt:15}},line:{width:{valType:\"number\",dflt:2},dash:{valType:\"data_array\"}},fill:{outlinecolor:{valType:\"color\",dflt:a}},symbol:{icon:{valType:\"string\",dflt:\"marker\"},iconsize:{valType:\"number\",dflt:10},text:{valType:\"string\",dflt:\"\"},placement:{valType:\"enumerated\",values:[\"point\",\"line\",\"line-center\"],dflt:\"point\"},textfont:h,textposition:n.extendFlat({},s,{arrayOk:!1})}})},\"plot\",\"from-root\")).uirevision={valType:\"any\",editType:\"none\"}},{\"../../components/color\":592,\"../../lib\":717,\"../../plot_api/edit_types\":748,\"../../plot_api/plot_template\":755,\"../../traces/scatter/attributes\":1120,\"../domain\":790,\"../font_attributes\":791,\"./constants\":818}],823:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../subplot_defaults\"),i=t(\"../array_container_defaults\"),o=t(\"./layout_attributes\");function s(t,e,r,n){r(\"accesstoken\",n.accessToken),r(\"style\"),r(\"center.lon\"),r(\"center.lat\"),r(\"zoom\"),r(\"bearing\"),r(\"pitch\"),i(t,e,{name:\"layers\",handleItemDefaults:l}),e._input=t}function l(t,e){function r(r,a){return n.coerce(t,e,o.layers,r,a)}if(r(\"visible\")){var a,i=r(\"sourcetype\"),s=\"raster\"===i||\"image\"===i;r(\"source\"),r(\"sourceattribution\"),\"vector\"===i&&r(\"sourcelayer\"),\"image\"===i&&r(\"coordinates\"),s&&(a=\"raster\");var l=r(\"type\",a);s&&\"raster\"!==l&&(l=e.type=\"raster\",n.log(\"Source types *raster* and *image* must drawn *raster* layer type.\")),r(\"below\"),r(\"color\"),r(\"opacity\"),r(\"minzoom\"),r(\"maxzoom\"),\"circle\"===l&&r(\"circle.radius\"),\"line\"===l&&(r(\"line.width\"),r(\"line.dash\")),\"fill\"===l&&r(\"fill.outlinecolor\"),\"symbol\"===l&&(r(\"symbol.icon\"),r(\"symbol.iconsize\"),r(\"symbol.text\"),n.coerceFont(r,\"symbol.textfont\"),r(\"symbol.textposition\"),r(\"symbol.placement\"))}}e.exports=function(t,e,r){a(t,e,r,{type:\"mapbox\",attributes:o,handleDefaults:s,partition:\"y\",accessToken:e._mapboxAccessToken})}},{\"../../lib\":717,\"../array_container_defaults\":761,\"../subplot_defaults\":840,\"./layout_attributes\":822}],824:[function(t,e,r){\"use strict\";var n=t(\"mapbox-gl\"),a=t(\"../../components/fx\"),i=t(\"../../lib\"),o=t(\"../../lib/geo_location_utils\"),s=t(\"../../registry\"),l=t(\"../cartesian/axes\"),c=t(\"../../components/dragelement\"),u=t(\"../cartesian/select\").prepSelect,h=t(\"../cartesian/select\").selectOnClick,f=t(\"./constants\"),p=t(\"./layers\");function d(t,e){this.id=e,this.gd=t;var r=t._fullLayout,n=t._context;this.container=r._glcontainer.node(),this.isStatic=n.staticPlot,this.uid=r._uid+\"-\"+this.id,this.div=null,this.xaxis=null,this.yaxis=null,this.createFramework(r),this.map=null,this.accessToken=null,this.styleObj=null,this.traceHash={},this.layerList=[],this.belowLookup={},this.dragging=!1,this.wheeling=!1}var g=d.prototype;g.plot=function(t,e,r){var n,a=this,i=e[a.id];a.map&&i.accesstoken!==a.accessToken&&(a.map.remove(),a.map=null,a.styleObj=null,a.traceHash=[],a.layerList={}),n=a.map?new Promise(function(r,n){a.updateMap(t,e,r,n)}):new Promise(function(r,n){a.createMap(t,e,r,n)}),r.push(n)},g.createMap=function(t,e,r,a){var i=this,s=e[i.id],l=i.styleObj=m(s.style);i.accessToken=s.accesstoken;var c=i.map=new n.Map({container:i.div,style:l.style,center:x(s.center),zoom:s.zoom,bearing:s.bearing,pitch:s.pitch,interactive:!i.isStatic,preserveDrawingBuffer:i.isStatic,doubleClickZoom:!1,boxZoom:!1,attributionControl:!1}).addControl(new n.AttributionControl({compact:!0}));c._canvas.style.left=\"0px\",c._canvas.style.top=\"0px\",i.rejectOnError(a),i.isStatic||i.initFx(t,e);var u=[];u.push(new Promise(function(t){c.once(\"load\",t)})),u=u.concat(o.fetchTraceGeoData(t)),Promise.all(u).then(function(){i.fillBelowLookup(t,e),i.updateData(t),i.updateLayout(e),i.resolveOnRender(r)}).catch(a)},g.updateMap=function(t,e,r,n){var a=this,i=a.map,s=e[this.id];a.rejectOnError(n);var l=[],c=m(s.style);a.styleObj.id!==c.id&&(a.styleObj=c,i.setStyle(c.style),a.traceHash={},l.push(new Promise(function(t){i.once(\"styledata\",t)}))),l=l.concat(o.fetchTraceGeoData(t)),Promise.all(l).then(function(){a.fillBelowLookup(t,e),a.updateData(t),a.updateLayout(e),a.resolveOnRender(r)}).catch(n)},g.fillBelowLookup=function(t,e){var r,n,a=e[this.id].layers,i=this.belowLookup={},o=!1;for(r=0;r<t.length;r++){var s=t[r][0].trace,l=s._module;\"string\"==typeof s.below?n=s.below:l.getBelow&&(n=l.getBelow(s,this)),\"\"===n&&(o=!0),i[\"trace-\"+s.uid]=n||\"\"}for(r=0;r<a.length;r++){var c=a[r];n=\"string\"==typeof c.below?c.below:o?\"traces\":\"\",i[\"layout-\"+r]=n}var u,h,f={};for(u in i)f[n=i[u]]?f[n].push(u):f[n]=[u];for(n in f){var p=f[n];if(p.length>1)for(r=0;r<p.length;r++)0===(u=p[r]).indexOf(\"trace-\")?(h=u.split(\"trace-\")[1],this.traceHash[h]&&(this.traceHash[h].below=null)):0===u.indexOf(\"layout-\")&&(h=u.split(\"layout-\")[1],this.layerList[h]&&(this.layerList[h].below=null))}};var v={choroplethmapbox:0,densitymapbox:1,scattermapbox:2};function m(t){var e={};return i.isPlainObject(t)?(e.id=t.id,e.style=t):\"string\"==typeof t?(e.id=t,-1!==f.styleValuesMapbox.indexOf(t)?e.style=y(t):f.stylesNonMapbox[t]?e.style=f.stylesNonMapbox[t]:e.style=t):(e.id=f.styleValueDflt,e.style=y(f.styleValueDflt)),e.transition={duration:0,delay:0},e}function y(t){return f.styleUrlPrefix+t+\"-\"+f.styleUrlSuffix}function x(t){return[t.lon,t.lat]}g.updateData=function(t){var e,r,n,a,i=this.traceHash,o=t.slice().sort(function(t,e){return v[t[0].trace.type]-v[e[0].trace.type]});for(n=0;n<o.length;n++){var s=o[n],l=!1;(e=i[(r=s[0].trace).uid])&&(e.type===r.type?(e.update(s),l=!0):e.dispose()),!l&&r._module&&(i[r.uid]=r._module.plot(this,s))}var c=Object.keys(i);t:for(n=0;n<c.length;n++){var u=c[n];for(a=0;a<t.length;a++)if(u===(r=t[a][0].trace).uid)continue t;(e=i[u]).dispose(),delete i[u]}},g.updateLayout=function(t){var e=this.map,r=t[this.id];this.dragging||this.wheeling||(e.setCenter(x(r.center)),e.setZoom(r.zoom),e.setBearing(r.bearing),e.setPitch(r.pitch)),this.updateLayers(t),this.updateFramework(t),this.updateFx(t),this.map.resize(),this.gd._context._scrollZoom.mapbox?e.scrollZoom.enable():e.scrollZoom.disable()},g.resolveOnRender=function(t){var e=this.map;e.on(\"render\",function r(){e.loaded()&&(e.off(\"render\",r),setTimeout(t,10))})},g.rejectOnError=function(t){var e=this.map;function r(){t(new Error(f.mapOnErrorMsg))}e.once(\"error\",r),e.once(\"style.error\",r),e.once(\"source.error\",r),e.once(\"tile.error\",r),e.once(\"layer.error\",r)},g.createFramework=function(t){var e=this,r=e.div=document.createElement(\"div\");r.id=e.uid,r.style.position=\"absolute\",e.container.appendChild(r),e.xaxis={_id:\"x\",c2p:function(t){return e.project(t).x}},e.yaxis={_id:\"y\",c2p:function(t){return e.project(t).y}},e.updateFramework(t),e.mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},l.setConvert(e.mockAxis,t)},g.initFx=function(t,e){var r=this,n=r.gd,i=r.map;function o(){a.loneUnhover(e._hoverlayer)}function l(){var t=r.getView();n.emit(\"plotly_relayouting\",r.getViewEditsWithDerived(t))}i.on(\"moveend\",function(t){if(r.map){var e=n._fullLayout;if(t.originalEvent||r.wheeling){var a=e[r.id];s.call(\"_storeDirectGUIEdit\",n.layout,e._preGUI,r.getViewEdits(a));var i=r.getView();a._input.center=a.center=i.center,a._input.zoom=a.zoom=i.zoom,a._input.bearing=a.bearing=i.bearing,a._input.pitch=a.pitch=i.pitch,n.emit(\"plotly_relayout\",r.getViewEditsWithDerived(i))}t.originalEvent&&\"mouseup\"===t.originalEvent.type?r.dragging=!1:r.wheeling&&(r.wheeling=!1),e._rehover&&e._rehover()}}),i.on(\"wheel\",function(){r.wheeling=!0}),i.on(\"mousemove\",function(t){var e=r.div.getBoundingClientRect();t.clientX=t.point.x+e.left,t.clientY=t.point.y+e.top,t.target.getBoundingClientRect=function(){return e},r.xaxis.p2c=function(){return t.lngLat.lng},r.yaxis.p2c=function(){return t.lngLat.lat},n._fullLayout._rehover=function(){n._fullLayout._hoversubplot===r.id&&n._fullLayout[r.id]&&a.hover(n,t,r.id)},a.hover(n,t,r.id),n._fullLayout._hoversubplot=r.id}),i.on(\"dragstart\",function(){r.dragging=!0,o()}),i.on(\"zoomstart\",o),i.on(\"mouseout\",function(){n._fullLayout._hoversubplot=null}),i.on(\"drag\",l),i.on(\"zoom\",l),i.on(\"dblclick\",function(){var t=n._fullLayout[r.id];s.call(\"_storeDirectGUIEdit\",n.layout,n._fullLayout._preGUI,r.getViewEdits(t));var e=r.viewInitial;i.setCenter(x(e.center)),i.setZoom(e.zoom),i.setBearing(e.bearing),i.setPitch(e.pitch);var a=r.getView();t._input.center=t.center=a.center,t._input.zoom=t.zoom=a.zoom,t._input.bearing=t.bearing=a.bearing,t._input.pitch=t.pitch=a.pitch,n.emit(\"plotly_doubleclick\",null),n.emit(\"plotly_relayout\",r.getViewEditsWithDerived(a))}),r.clearSelect=function(){n._fullLayout._zoomlayer.selectAll(\".select-outline\").remove()},r.onClickInPanFn=function(t){return function(e){var i=n._fullLayout.clickmode;i.indexOf(\"select\")>-1&&h(e.originalEvent,n,[r.xaxis],[r.yaxis],r.id,t),i.indexOf(\"event\")>-1&&a.click(n,e.originalEvent)}}},g.updateFx=function(t){var e=this,r=e.map,n=e.gd;if(!e.isStatic){var a,o=t.dragmode;a=\"select\"===o?function(t,r){(t.range={})[e.id]=[l([r.xmin,r.ymin]),l([r.xmax,r.ymax])]}:function(t,r,n){(t.lassoPoints={})[e.id]=n.filtered.map(l)};var s=e.dragOptions;e.dragOptions=i.extendDeep(s||{},{element:e.div,gd:n,plotinfo:{id:e.id,xaxis:e.xaxis,yaxis:e.yaxis,fillRangeItems:a},xaxes:[e.xaxis],yaxes:[e.yaxis],subplot:e.id}),r.off(\"click\",e.onClickInPanHandler),\"select\"===o||\"lasso\"===o?(r.dragPan.disable(),r.on(\"zoomstart\",e.clearSelect),e.dragOptions.prepFn=function(t,r,n){u(t,r,n,e.dragOptions,o)},c.init(e.dragOptions)):(r.dragPan.enable(),r.off(\"zoomstart\",e.clearSelect),e.div.onmousedown=null,e.onClickInPanHandler=e.onClickInPanFn(e.dragOptions),r.on(\"click\",e.onClickInPanHandler))}function l(t){var r=e.map.unproject(t);return[r.lng,r.lat]}},g.updateFramework=function(t){var e=t[this.id].domain,r=t._size,n=this.div.style;n.width=r.w*(e.x[1]-e.x[0])+\"px\",n.height=r.h*(e.y[1]-e.y[0])+\"px\",n.left=r.l+e.x[0]*r.w+\"px\",n.top=r.t+(1-e.y[1])*r.h+\"px\",this.xaxis._offset=r.l+e.x[0]*r.w,this.xaxis._length=r.w*(e.x[1]-e.x[0]),this.yaxis._offset=r.t+(1-e.y[1])*r.h,this.yaxis._length=r.h*(e.y[1]-e.y[0])},g.updateLayers=function(t){var e,r=t[this.id].layers,n=this.layerList;if(r.length!==n.length){for(e=0;e<n.length;e++)n[e].dispose();for(n=this.layerList=[],e=0;e<r.length;e++)n.push(p(this,e,r[e]))}else for(e=0;e<r.length;e++)n[e].update(r[e])},g.destroy=function(){this.map&&(this.map.remove(),this.map=null,this.container.removeChild(this.div))},g.toImage=function(){return this.map.stop(),this.map.getCanvas().toDataURL()},g.setOptions=function(t,e,r){for(var n in r)this.map[e](t,n,r[n])},g.getMapLayers=function(){return this.map.getStyle().layers},g.addLayer=function(t,e){var r=this.map;if(\"string\"==typeof e){if(\"\"===e)return void r.addLayer(t,e);for(var n=this.getMapLayers(),a=0;a<n.length;a++)if(e===n[a].id)return void r.addLayer(t,e);i.warn([\"Trying to add layer with *below* value\",e,\"referencing a layer that does not exist\",\"or that does not yet exist.\"].join(\" \"))}r.addLayer(t)},g.project=function(t){return this.map.project(new n.LngLat(t[0],t[1]))},g.getView=function(){var t=this.map,e=t.getCenter(),r={lon:e.lng,lat:e.lat},n=t.getCanvas(),a=n.width,i=n.height;return{center:r,zoom:t.getZoom(),bearing:t.getBearing(),pitch:t.getPitch(),_derived:{coordinates:[t.unproject([0,0]).toArray(),t.unproject([a,0]).toArray(),t.unproject([a,i]).toArray(),t.unproject([0,i]).toArray()]}}},g.getViewEdits=function(t){for(var e=this.id,r=[\"center\",\"zoom\",\"bearing\",\"pitch\"],n={},a=0;a<r.length;a++){var i=r[a];n[e+\".\"+i]=t[i]}return n},g.getViewEditsWithDerived=function(t){var e=this.id,r=this.getViewEdits(t);return r[e+\"._derived\"]=t._derived,r},e.exports=d},{\"../../components/dragelement\":610,\"../../components/fx\":630,\"../../lib\":717,\"../../lib/geo_location_utils\":711,\"../../registry\":846,\"../cartesian/axes\":765,\"../cartesian/select\":782,\"./constants\":818,\"./layers\":821,\"mapbox-gl\":428}],825:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.editType;return{t:{valType:\"number\",dflt:0,editType:e},r:{valType:\"number\",dflt:0,editType:e},b:{valType:\"number\",dflt:0,editType:e},l:{valType:\"number\",dflt:0,editType:e},editType:e}}},{}],826:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"fast-isnumeric\"),i=t(\"../registry\"),o=t(\"../plot_api/plot_schema\"),s=t(\"../plot_api/plot_template\"),l=t(\"../lib\"),c=t(\"../components/color\"),u=t(\"../constants/numerical\").BADNUM,h=t(\"./cartesian/axis_ids\"),f=t(\"./animation_attributes\"),p=t(\"./frame_attributes\"),d=t(\"../plots/get_data\").getModuleCalcData,g=l.relinkPrivateKeys,v=l._,m=e.exports={};l.extendFlat(m,i),m.attributes=t(\"./attributes\"),m.attributes.type.values=m.allTypes,m.fontAttrs=t(\"./font_attributes\"),m.layoutAttributes=t(\"./layout_attributes\"),m.fontWeight=\"normal\";var y=m.transformsRegistry,x=t(\"./command\");m.executeAPICommand=x.executeAPICommand,m.computeAPICommandBindings=x.computeAPICommandBindings,m.manageCommandObserver=x.manageCommandObserver,m.hasSimpleAPICommandBindings=x.hasSimpleAPICommandBindings,m.redrawText=function(t){var e=(t=l.getGraphDiv(t))._fullLayout||{};if(!(!(e._has&&e._has(\"polar\"))&&t.data&&t.data[0]&&t.data[0].r))return new Promise(function(e){setTimeout(function(){i.getComponentMethod(\"annotations\",\"draw\")(t),i.getComponentMethod(\"legend\",\"draw\")(t),i.getComponentMethod(\"colorbar\",\"draw\")(t),e(m.previousPromises(t))},300)})},m.resize=function(t){var e;t=l.getGraphDiv(t);var r=new Promise(function(r,n){t&&!l.isHidden(t)||n(new Error(\"Resize must be passed a displayed plot div element.\")),t._redrawTimer&&clearTimeout(t._redrawTimer),t._resolveResize&&(e=t._resolveResize),t._resolveResize=r,t._redrawTimer=setTimeout(function(){if(!t.layout||t.layout.width&&t.layout.height||l.isHidden(t))r(t);else{delete t.layout.width,delete t.layout.height;var e=t.changed;t.autoplay=!0,i.call(\"relayout\",t,{autosize:!0}).then(function(){t.changed=e,t._resolveResize===r&&(delete t._resolveResize,r(t))})}},100)});return e&&e(r),r},m.previousPromises=function(t){if((t._promises||[]).length)return Promise.all(t._promises).then(function(){t._promises=[]})},m.addLinks=function(t){if(t._context.showLink||t._context.showSources){var e=t._fullLayout,r=l.ensureSingle(e._paper,\"text\",\"js-plot-link-container\",function(t){t.style({\"font-family\":'\"Open Sans\", Arial, sans-serif',\"font-size\":\"12px\",fill:c.defaultLine,\"pointer-events\":\"all\"}).each(function(){var t=n.select(this);t.append(\"tspan\").classed(\"js-link-to-tool\",!0),t.append(\"tspan\").classed(\"js-link-spacer\",!0),t.append(\"tspan\").classed(\"js-sourcelinks\",!0)})}),a=r.node(),i={y:e._paper.attr(\"height\")-9};document.body.contains(a)&&a.getComputedTextLength()>=e.width-20?(i[\"text-anchor\"]=\"start\",i.x=5):(i[\"text-anchor\"]=\"end\",i.x=e._paper.attr(\"width\")-7),r.attr(i);var o=r.select(\".js-link-to-tool\"),s=r.select(\".js-link-spacer\"),u=r.select(\".js-sourcelinks\");t._context.showSources&&t._context.showSources(t),t._context.showLink&&function(t,e){e.text(\"\");var r=e.append(\"a\").attr({\"xlink:xlink:href\":\"#\",class:\"link--impt link--embedview\",\"font-weight\":\"bold\"}).text(t._context.linkText+\" \"+String.fromCharCode(187));if(t._context.sendData)r.on(\"click\",function(){m.sendDataToCloud(t)});else{var n=window.location.pathname.split(\"/\"),a=window.location.search;r.attr({\"xlink:xlink:show\":\"new\",\"xlink:xlink:href\":\"/\"+n[2].split(\".\")[0]+\"/\"+n[1]+a})}}(t,o),s.text(o.text()&&u.text()?\" - \":\"\")}},m.sendDataToCloud=function(t){t.emit(\"plotly_beforeexport\");var e=(window.PLOTLYENV||{}).BASE_URL||t._context.plotlyServerURL,r=n.select(t).append(\"div\").attr(\"id\",\"hiddenform\").style(\"display\",\"none\"),a=r.append(\"form\").attr({action:e+\"/external\",method:\"post\",target:\"_blank\"});return a.append(\"input\").attr({type:\"text\",name:\"data\"}).node().value=m.graphJson(t,!1,\"keepdata\"),a.node().submit(),r.remove(),t.emit(\"plotly_afterexport\"),!1};var b=[\"days\",\"shortDays\",\"months\",\"shortMonths\",\"periods\",\"dateTime\",\"date\",\"time\",\"decimal\",\"thousands\",\"grouping\",\"currency\"],_=[\"year\",\"month\",\"dayMonth\",\"dayMonthYear\"];function w(t,e){var r=t._context.locale,n=!1,a={};function o(t){for(var r=!0,i=0;i<e.length;i++){var o=e[i];a[o]||(t[o]?a[o]=t[o]:r=!1)}r&&(n=!0)}for(var s=0;s<2;s++){for(var l=t._context.locales,c=0;c<2;c++){var u=(l[r]||{}).format;if(u&&(o(u),n))break;l=i.localeRegistry}var h=r.split(\"-\")[0];if(n||h===r)break;r=h}return n||o(i.localeRegistry.en.format),a}function k(t,e){var r={_fullLayout:e},n=\"x\"===t._id.charAt(0),a=t._mainAxis._anchorAxis,i=\"\",o=\"\",s=\"\";if(a&&(s=a._mainAxis._id,i=n?t._id+s:s+t._id),!i||!e._plots[i]){i=\"\";for(var l=t._counterAxes,c=0;c<l.length;c++){var u=l[c],f=n?t._id+u:u+t._id;o||(o=f);var p=h.getFromId(r,u);if(s&&p.overlaying===s){i=f;break}}}return i||o}function T(t){var e=t.transforms;if(Array.isArray(e)&&e.length)for(var r=0;r<e.length;r++){var n=e[r],a=n._module||y[n.type];if(a&&a.makesData)return!0}return!1}function M(t,e,r,n){for(var a=t.transforms,i=[t],o=0;o<a.length;o++){var s=a[o],l=y[s.type];l&&l.transform&&(i=l.transform(i,{transform:s,fullTrace:t,fullData:e,layout:r,fullLayout:n,transformIndex:o}))}return i}function A(t){var e=t.margin;if(!t._size){var r=t._size={l:Math.round(e.l),r:Math.round(e.r),t:Math.round(e.t),b:Math.round(e.b),p:Math.round(e.pad)};r.w=Math.round(t.width)-r.l-r.r,r.h=Math.round(t.height)-r.t-r.b}t._pushmargin||(t._pushmargin={}),t._pushmarginIds||(t._pushmarginIds={})}m.supplyDefaults=function(t,e){var r=e&&e.skipUpdateCalc,a=t._fullLayout||{};if(a._skipDefaults)delete a._skipDefaults;else{var o,s=t._fullLayout={},c=t.layout||{},u=t._fullData||[],h=t._fullData=[],f=t.data||[],p=t.calcdata||[],d=t._context||{};t._transitionData||m.createTransitionData(t),s._dfltTitle={plot:v(t,\"Click to enter Plot title\"),x:v(t,\"Click to enter X axis title\"),y:v(t,\"Click to enter Y axis title\"),colorbar:v(t,\"Click to enter Colorscale title\"),annotation:v(t,\"new text\")},s._traceWord=v(t,\"trace\");var y=w(t,b);if(s._mapboxAccessToken=d.mapboxAccessToken,a._initialAutoSizeIsDone){var x=a.width,k=a.height;m.supplyLayoutGlobalDefaults(c,s,y),c.width||(s.width=x),c.height||(s.height=k),m.sanitizeMargins(s)}else{m.supplyLayoutGlobalDefaults(c,s,y);var T=!c.width||!c.height,M=s.autosize,S=d.autosizable;T&&(M||S)?m.plotAutoSize(t,c,s):T&&m.sanitizeMargins(s),!M&&T&&(c.width=s.width,c.height=s.height)}s._d3locale=function(t,e){return t.decimal=e.charAt(0),t.thousands=e.charAt(1),n.locale(t)}(y,s.separators),s._extraFormat=w(t,_),s._initialAutoSizeIsDone=!0,s._dataLength=f.length,s._modules=[],s._visibleModules=[],s._basePlotModules=[];var E=s._subplots=function(){var t,e,r=i.collectableSubplotTypes,n={};if(!r){r=[];var a=i.subplotsRegistry;for(var o in a){var s=a[o],c=s.attr;if(c&&(r.push(o),Array.isArray(c)))for(e=0;e<c.length;e++)l.pushUnique(r,c[e])}}for(t=0;t<r.length;t++)n[r[t]]=[];return n}(),L=s._splomAxes={x:{},y:{}},C=s._splomSubplots={};s._splomGridDflt={},s._scatterStackOpts={},s._firstScatter={},s._alignmentOpts={},s._colorAxes={},s._requestRangeslider={},s._traceUids=function(t,e){var r,n,a=e.length,i=[];for(r=0;r<t.length;r++){var o=t[r]._fullInput;o!==n&&i.push(o),n=o}var s=i.length,c=new Array(a),u={};function h(t,e){c[e]=t,u[t]=1}function f(t,e){if(t&&\"string\"==typeof t&&!u[t])return h(t,e),!0}for(r=0;r<a;r++){var p=e[r].uid;\"number\"==typeof p&&(p=String(p)),f(p,r)||(r<s&&f(i[r].uid,r)||h(l.randstr(u),r))}return c}(u,f),s._globalTransforms=(t._context||{}).globalTransforms,m.supplyDataDefaults(f,h,c,s);var P=Object.keys(L.x),O=Object.keys(L.y);if(P.length>1&&O.length>1){for(i.getComponentMethod(\"grid\",\"sizeDefaults\")(c,s),o=0;o<P.length;o++)l.pushUnique(E.xaxis,P[o]);for(o=0;o<O.length;o++)l.pushUnique(E.yaxis,O[o]);for(var z in C)l.pushUnique(E.cartesian,z)}if(s._has=m._hasPlotType.bind(s),u.length===h.length)for(o=0;o<h.length;o++)g(h[o],u[o]);m.supplyLayoutModuleDefaults(c,s,h,t._transitionData);var I=s._visibleModules,D=[];for(o=0;o<I.length;o++){var R=I[o].crossTraceDefaults;R&&l.pushUnique(D,R)}for(o=0;o<D.length;o++)D[o](h,s);s._hasOnlyLargeSploms=1===s._basePlotModules.length&&\"splom\"===s._basePlotModules[0].name&&P.length>15&&O.length>15&&0===s.shapes.length&&0===s.images.length,s._hasCartesian=s._has(\"cartesian\"),s._hasGeo=s._has(\"geo\"),s._hasGL3D=s._has(\"gl3d\"),s._hasGL2D=s._has(\"gl2d\"),s._hasTernary=s._has(\"ternary\"),s._hasPie=s._has(\"pie\"),m.linkSubplots(h,s,u,a),m.cleanPlot(h,s,u,a),a._zoomlayer&&!t._dragging&&a._zoomlayer.selectAll(\".select-outline\").remove(),function(t,e){var r,n=[];e.meta&&(r=e._meta={meta:e.meta,layout:{meta:e.meta}});for(var a=0;a<t.length;a++){var i=t[a];i.meta?n[i.index]=i._meta={meta:i.meta}:e.meta&&(i._meta={meta:e.meta}),e.meta&&(i._meta.layout={meta:e.meta})}n.length&&(r||(r=e._meta={}),r.data=n)}(h,s),g(s,a),i.getComponentMethod(\"colorscale\",\"crossTraceDefaults\")(h,s),s._preGUI||(s._preGUI={}),s._tracePreGUI||(s._tracePreGUI={});var F,B=s._tracePreGUI,N={};for(F in B)N[F]=\"old\";for(o=0;o<h.length;o++)N[F=h[o]._fullInput.uid]||(B[F]={}),N[F]=\"new\";for(F in N)\"old\"===N[F]&&delete B[F];A(s),i.getComponentMethod(\"rangeslider\",\"makeData\")(s),r||p.length!==h.length||m.supplyDefaultsUpdateCalc(p,h)}},m.supplyDefaultsUpdateCalc=function(t,e){for(var r=0;r<e.length;r++){var n=e[r],a=(t[r]||[])[0];if(a&&a.trace){var i=a.trace;if(i._hasCalcTransform){var o,s,c,u=i._arrayAttrs;for(o=0;o<u.length;o++)s=u[o],c=l.nestedProperty(i,s).get().slice(),l.nestedProperty(n,s).set(c)}a.trace=n}}},m.createTransitionData=function(t){t._transitionData||(t._transitionData={}),t._transitionData._frames||(t._transitionData._frames=[]),t._transitionData._frameHash||(t._transitionData._frameHash={}),t._transitionData._counter||(t._transitionData._counter=0),t._transitionData._interruptCallbacks||(t._transitionData._interruptCallbacks=[])},m._hasPlotType=function(t){var e,r=this._basePlotModules||[];for(e=0;e<r.length;e++)if(r[e].name===t)return!0;var n=this._modules||[];for(e=0;e<n.length;e++){var a=n[e].name;if(a===t)return!0;var o=i.modules[a];if(o&&o.categories[t])return!0}return!1},m.cleanPlot=function(t,e,r,n){var a,i,o=n._basePlotModules||[];for(a=0;a<o.length;a++){var s=o[a];s.clean&&s.clean(t,e,r,n)}var l=n._has&&n._has(\"gl\"),c=e._has&&e._has(\"gl\");l&&!c&&void 0!==n._glcontainer&&(n._glcontainer.selectAll(\".gl-canvas\").remove(),n._glcontainer.selectAll(\".no-webgl\").remove(),n._glcanvas=null);var u=!!n._infolayer;t:for(a=0;a<r.length;a++){var h=r[a].uid;for(i=0;i<t.length;i++){if(h===t[i].uid)continue t}u&&n._infolayer.select(\".cb\"+h).remove()}},m.linkSubplots=function(t,e,r,n){var a,o,s=n._plots||{},c=e._plots={},u=e._subplots,f={_fullData:t,_fullLayout:e},p=u.cartesian.concat(u.gl2d||[]);for(a=0;a<p.length;a++){var d,g=p[a],v=s[g],m=h.getFromId(f,g,\"x\"),y=h.getFromId(f,g,\"y\");for(v?d=c[g]=v:(d=c[g]={}).id=g,m._counterAxes.push(y._id),y._counterAxes.push(m._id),m._subplotsWith.push(g),y._subplotsWith.push(g),d.xaxis=m,d.yaxis=y,d._hasClipOnAxisFalse=!1,o=0;o<t.length;o++){var x=t[o];if(x.xaxis===d.xaxis._id&&x.yaxis===d.yaxis._id&&!1===x.cliponaxis){d._hasClipOnAxisFalse=!0;break}}}var b,_=h.list(f,null,!0);for(a=0;a<_.length;a++){var w=null;(b=_[a]).overlaying&&(w=h.getFromId(f,b.overlaying))&&w.overlaying&&(b.overlaying=!1,w=null),b._mainAxis=w||b,w&&(b.domain=w.domain.slice()),b._anchorAxis=\"free\"===b.anchor?null:h.getFromId(f,b.anchor)}for(a=0;a<_.length;a++)if((b=_[a])._counterAxes.sort(h.idSort),b._subplotsWith.sort(l.subplotSort),b._mainSubplot=k(b,e),b._counterAxes.length&&(b.spikemode&&-1!==b.spikemode.indexOf(\"across\")||b.automargin&&b.mirror&&\"free\"!==b.anchor||i.getComponentMethod(\"rangeslider\",\"isVisible\")(b))){var T=1,M=0;for(o=0;o<b._counterAxes.length;o++){var A=h.getFromId(f,b._counterAxes[o]);T=Math.min(T,A.domain[0]),M=Math.max(M,A.domain[1])}T<M&&(b._counterDomainMin=T,b._counterDomainMax=M)}},m.clearExpandedTraceDefaultColors=function(t){var e,r,n;for(r=[],(e=t._module._colorAttrs)||(t._module._colorAttrs=e=[],o.crawl(t._module.attributes,function(t,n,a,i){r[i]=n,r.length=i+1,\"color\"===t.valType&&void 0===t.dflt&&e.push(r.join(\".\"))})),n=0;n<e.length;n++){l.nestedProperty(t,\"_input.\"+e[n]).get()||l.nestedProperty(t,e[n]).set(null)}},m.supplyDataDefaults=function(t,e,r,n){var a,o,c,u=n._modules,h=n._visibleModules,f=n._basePlotModules,p=0,d=0;function v(t){e.push(t);var r=t._module;r&&(l.pushUnique(u,r),!0===t.visible&&l.pushUnique(h,r),l.pushUnique(f,t._module.basePlotModule),p++,!1!==t._input.visible&&d++)}n._transformModules=[];var y={},x=[],b=(r.template||{}).data||{},_=s.traceTemplater(b);for(a=0;a<t.length;a++){if(c=t[a],(o=_.newTrace(c)).uid=n._traceUids[a],m.supplyTraceDefaults(c,o,d,n,a),o.index=a,o._input=c,o._expandedIndex=p,o.transforms&&o.transforms.length)for(var w=!1!==c.visible&&!1===o.visible,k=M(o,e,r,n),T=0;T<k.length;T++){var A=k[T],S={_template:o._template,type:o.type,uid:o.uid+T};w&&!1===A.visible&&delete A.visible,m.supplyTraceDefaults(A,S,p,n,a),g(S,A),S.index=a,S._input=c,S._fullInput=o,S._expandedIndex=p,S._expandedInput=A,v(S)}else o._fullInput=o,o._expandedInput=o,v(o);i.traceIs(o,\"carpetAxis\")&&(y[o.carpet]=o),i.traceIs(o,\"carpetDependent\")&&x.push(a)}for(a=0;a<x.length;a++)if((o=e[x[a]]).visible){var E=y[o.carpet];o._carpet=E,E&&E.visible?(o.xaxis=E.xaxis,o.yaxis=E.yaxis):o.visible=!1}},m.supplyAnimationDefaults=function(t){var e;t=t||{};var r={};function n(e,n){return l.coerce(t||{},r,f,e,n)}if(n(\"mode\"),n(\"direction\"),n(\"fromcurrent\"),Array.isArray(t.frame))for(r.frame=[],e=0;e<t.frame.length;e++)r.frame[e]=m.supplyAnimationFrameDefaults(t.frame[e]||{});else r.frame=m.supplyAnimationFrameDefaults(t.frame||{});if(Array.isArray(t.transition))for(r.transition=[],e=0;e<t.transition.length;e++)r.transition[e]=m.supplyAnimationTransitionDefaults(t.transition[e]||{});else r.transition=m.supplyAnimationTransitionDefaults(t.transition||{});return r},m.supplyAnimationFrameDefaults=function(t){var e={};function r(r,n){return l.coerce(t||{},e,f.frame,r,n)}return r(\"duration\"),r(\"redraw\"),e},m.supplyAnimationTransitionDefaults=function(t){var e={};function r(r,n){return l.coerce(t||{},e,f.transition,r,n)}return r(\"duration\"),r(\"easing\"),e},m.supplyFrameDefaults=function(t){var e={};function r(r,n){return l.coerce(t,e,p,r,n)}return r(\"group\"),r(\"name\"),r(\"traces\"),r(\"baseframe\"),r(\"data\"),r(\"layout\"),e},m.supplyTraceDefaults=function(t,e,r,n,a){var o,s=n.colorway||c.defaults,u=s[r%s.length];function h(r,n){return l.coerce(t,e,m.attributes,r,n)}var f=h(\"visible\");h(\"type\"),h(\"name\",n._traceWord+\" \"+a),h(\"uirevision\",n.uirevision);var p=m.getModule(e);if(e._module=p,p){var d=p.basePlotModule,g=d.attr,v=d.attributes;if(g&&v){var y=n._subplots,x=\"\";if(f||\"gl2d\"!==d.name){if(Array.isArray(g))for(o=0;o<g.length;o++){var b=g[o],_=l.coerce(t,e,v,b);y[b]&&l.pushUnique(y[b],_),x+=_}else x=l.coerce(t,e,v,g);y[d.name]&&l.pushUnique(y[d.name],x)}}}return f&&(h(\"customdata\"),h(\"ids\"),h(\"meta\"),i.traceIs(e,\"showLegend\")?(l.coerce(t,e,p.attributes.showlegend?p.attributes:m.attributes,\"showlegend\"),h(\"legendgroup\"),e._dfltShowLegend=!0):e._dfltShowLegend=!1,p&&p.supplyDefaults(t,e,u,n),i.traceIs(e,\"noOpacity\")||h(\"opacity\"),i.traceIs(e,\"notLegendIsolatable\")&&(e.visible=!!e.visible),i.traceIs(e,\"noHover\")||(e.hovertemplate||l.coerceHoverinfo(t,e,n),\"parcats\"!==e.type&&i.getComponentMethod(\"fx\",\"supplyDefaults\")(t,e,u,n)),p&&p.selectPoints&&h(\"selectedpoints\"),m.supplyTransformDefaults(t,e,n)),e},m.hasMakesDataTransform=T,m.supplyTransformDefaults=function(t,e,r){if(e._length||T(t)){var n=r._globalTransforms||[],a=r._transformModules||[];if(Array.isArray(t.transforms)||0!==n.length)for(var i=t.transforms||[],o=n.concat(i),s=e.transforms=[],c=0;c<o.length;c++){var u,h=o[c],f=h.type,p=y[f],d=!(h._module&&h._module===p),g=p&&\"function\"==typeof p.transform;p||l.warn(\"Unrecognized transform type \"+f+\".\"),p&&p.supplyDefaults&&(d||g)?((u=p.supplyDefaults(h,e,r,t)).type=f,u._module=p,l.pushUnique(a,p)):u=l.extendFlat({},h),s.push(u)}}},m.supplyLayoutGlobalDefaults=function(t,e,r){function n(r,n){return l.coerce(t,e,m.layoutAttributes,r,n)}var a=t.template;l.isPlainObject(a)&&(e.template=a,e._template=a.layout,e._dataTemplate=a.data);var o=l.coerceFont(n,\"font\");n(\"title.text\",e._dfltTitle.plot),l.coerceFont(n,\"title.font\",{family:o.family,size:Math.round(1.4*o.size),color:o.color}),n(\"title.xref\"),n(\"title.yref\"),n(\"title.x\"),n(\"title.y\"),n(\"title.xanchor\"),n(\"title.yanchor\"),n(\"title.pad.t\"),n(\"title.pad.r\"),n(\"title.pad.b\"),n(\"title.pad.l\"),n(\"uniformtext.mode\")&&n(\"uniformtext.minsize\"),n(\"autosize\",!(t.width&&t.height)),n(\"width\"),n(\"height\"),n(\"margin.l\"),n(\"margin.r\"),n(\"margin.t\"),n(\"margin.b\"),n(\"margin.pad\"),n(\"margin.autoexpand\"),t.width&&t.height&&m.sanitizeMargins(e),i.getComponentMethod(\"grid\",\"sizeDefaults\")(t,e),n(\"paper_bgcolor\"),n(\"separators\",r.decimal+r.thousands),n(\"hidesources\"),n(\"colorway\"),n(\"datarevision\");var s=n(\"uirevision\");n(\"editrevision\",s),n(\"selectionrevision\",s),n(\"modebar.orientation\"),n(\"modebar.bgcolor\",c.addOpacity(e.paper_bgcolor,.5));var u=c.contrast(c.rgb(e.modebar.bgcolor));n(\"modebar.color\",c.addOpacity(u,.3)),n(\"modebar.activecolor\",c.addOpacity(u,.7)),n(\"modebar.uirevision\",s),n(\"meta\"),l.isPlainObject(t.transition)&&(n(\"transition.duration\"),n(\"transition.easing\"),n(\"transition.ordering\")),i.getComponentMethod(\"calendars\",\"handleDefaults\")(t,e,\"calendar\"),i.getComponentMethod(\"fx\",\"supplyLayoutGlobalDefaults\")(t,e,n)},m.plotAutoSize=function(t,e,r){var n,i,o=t._context||{},s=o.frameMargins,c=l.isPlotDiv(t);if(c&&t.emit(\"plotly_autosize\"),o.fillFrame)n=window.innerWidth,i=window.innerHeight,document.body.style.overflow=\"hidden\";else{var u=c?window.getComputedStyle(t):{};if(n=parseFloat(u.width)||parseFloat(u.maxWidth)||r.width,i=parseFloat(u.height)||parseFloat(u.maxHeight)||r.height,a(s)&&s>0){var h=1-2*s;n=Math.round(h*n),i=Math.round(h*i)}}var f=m.layoutAttributes.width.min,p=m.layoutAttributes.height.min;n<f&&(n=f),i<p&&(i=p);var d=!e.width&&Math.abs(r.width-n)>1,g=!e.height&&Math.abs(r.height-i)>1;(g||d)&&(d&&(r.width=n),g&&(r.height=i)),t._initialAutoSize||(t._initialAutoSize={width:n,height:i}),m.sanitizeMargins(r)},m.supplyLayoutModuleDefaults=function(t,e,r,n){var a,o,s,c=i.componentsRegistry,u=e._basePlotModules,h=i.subplotsRegistry.cartesian;for(a in c)(s=c[a]).includeBasePlot&&s.includeBasePlot(t,e);for(var f in u.length||u.push(h),e._has(\"cartesian\")&&(i.getComponentMethod(\"grid\",\"contentDefaults\")(t,e),h.finalizeSubplots(t,e)),e._subplots)e._subplots[f].sort(l.subplotSort);for(o=0;o<u.length;o++)(s=u[o]).supplyLayoutDefaults&&s.supplyLayoutDefaults(t,e,r);var p=e._modules;for(o=0;o<p.length;o++)(s=p[o]).supplyLayoutDefaults&&s.supplyLayoutDefaults(t,e,r);var d=e._transformModules;for(o=0;o<d.length;o++)(s=d[o]).supplyLayoutDefaults&&s.supplyLayoutDefaults(t,e,r,n);for(a in c)(s=c[a]).supplyLayoutDefaults&&s.supplyLayoutDefaults(t,e,r)},m.purge=function(t){var e=t._fullLayout||{};void 0!==e._glcontainer&&(e._glcontainer.selectAll(\".gl-canvas\").remove(),e._glcontainer.remove(),e._glcanvas=null),e._modeBar&&e._modeBar.destroy(),t._transitionData&&(t._transitionData._interruptCallbacks&&(t._transitionData._interruptCallbacks.length=0),t._transitionData._animationRaf&&window.cancelAnimationFrame(t._transitionData._animationRaf)),l.clearThrottle(),l.clearResponsive(t),delete t.data,delete t.layout,delete t._fullData,delete t._fullLayout,delete t.calcdata,delete t.framework,delete t.empty,delete t.fid,delete t.undoqueue,delete t.undonum,delete t.autoplay,delete t.changed,delete t._promises,delete t._redrawTimer,delete t._hmlumcount,delete t._hmpixcount,delete t._transitionData,delete t._transitioning,delete t._initialAutoSize,delete t._transitioningWithDuration,delete t._dragging,delete t._dragged,delete t._dragdata,delete t._hoverdata,delete t._snapshotInProgress,delete t._editing,delete t._mouseDownTime,delete t._legendMouseDownTime,t.removeAllListeners&&t.removeAllListeners()},m.style=function(t){var e,r=t._fullLayout._visibleModules,n=[];for(e=0;e<r.length;e++){var a=r[e];a.style&&l.pushUnique(n,a.style)}for(e=0;e<n.length;e++)n[e](t)},m.sanitizeMargins=function(t){if(t&&t.margin){var e,r=t.width,n=t.height,a=t.margin,i=r-(a.l+a.r),o=n-(a.t+a.b);i<0&&(e=(r-1)/(a.l+a.r),a.l=Math.floor(e*a.l),a.r=Math.floor(e*a.r)),o<0&&(e=(n-1)/(a.t+a.b),a.t=Math.floor(e*a.t),a.b=Math.floor(e*a.b))}},m.clearAutoMarginIds=function(t){t._fullLayout._pushmarginIds={}},m.allowAutoMargin=function(t,e){t._fullLayout._pushmarginIds[e]=1},m.autoMargin=function(t,e,r){var n=t._fullLayout,a=n._pushmargin,i=n._pushmarginIds;if(!1!==n.margin.autoexpand){if(r){var o=r.pad;if(void 0===o){var s=n.margin;o=Math.min(12,s.l,s.r,s.t,s.b)}r.l+r.r>.5*n.width&&(l.log(\"Margin push\",e,\"is too big in x, dropping\"),r.l=r.r=0),r.b+r.t>.5*n.height&&(l.log(\"Margin push\",e,\"is too big in y, dropping\"),r.b=r.t=0);var c=void 0!==r.xl?r.xl:r.x,u=void 0!==r.xr?r.xr:r.x,h=void 0!==r.yt?r.yt:r.y,f=void 0!==r.yb?r.yb:r.y;a[e]={l:{val:c,size:r.l+o},r:{val:u,size:r.r+o},b:{val:f,size:r.b+o},t:{val:h,size:r.t+o}},i[e]=1}else delete a[e],delete i[e];if(!n._replotting)return m.doAutoMargin(t)}},m.doAutoMargin=function(t){var e=t._fullLayout;e._size||(e._size={}),A(e);var r=e._size,n=e.margin,o=l.extendFlat({},r),s=n.l,c=n.r,u=n.t,h=n.b,f=e.width,p=e.height,d=e._pushmargin,g=e._pushmarginIds;if(!1!==e.margin.autoexpand){for(var v in d)g[v]||delete d[v];for(var y in d.base={l:{val:0,size:s},r:{val:1,size:c},t:{val:1,size:u},b:{val:0,size:h}},d){var x=d[y].l||{},b=d[y].b||{},_=x.val,w=x.size,k=b.val,T=b.size;for(var M in d){if(a(w)&&d[M].r){var S=d[M].r.val,E=d[M].r.size;if(S>_){var L=(w*S+(E-f)*_)/(S-_),C=(E*(1-_)+(w-f)*(1-S))/(S-_);L>=0&&C>=0&&f-(L+C)>0&&L+C>s+c&&(s=L,c=C)}}if(a(T)&&d[M].t){var P=d[M].t.val,O=d[M].t.size;if(P>k){var z=(T*P+(O-p)*k)/(P-k),I=(O*(1-k)+(T-p)*(1-P))/(P-k);z>=0&&I>=0&&p-(I+z)>0&&z+I>h+u&&(h=z,u=I)}}}}}if(r.l=Math.round(s),r.r=Math.round(c),r.t=Math.round(u),r.b=Math.round(h),r.p=Math.round(n.pad),r.w=Math.round(f)-r.l-r.r,r.h=Math.round(p)-r.t-r.b,!e._replotting&&m.didMarginChange(o,r)){\"_redrawFromAutoMarginCount\"in e?e._redrawFromAutoMarginCount++:e._redrawFromAutoMarginCount=1;var D=3*(1+Object.keys(g).length);if(e._redrawFromAutoMarginCount<D)return i.call(\"plot\",t);l.warn(\"Too many auto-margin redraws.\")}};var S=[\"l\",\"r\",\"t\",\"b\",\"p\",\"w\",\"h\"];function E(t,e,r){var n=!1;var a=[m.previousPromises,function(){if(t._transitionData)return t._transitioning=!1,function(t){var e=Promise.resolve();if(!t)return e;for(;t.length;)e=e.then(t.shift());return e}(t._transitionData._interruptCallbacks)},r.prepareFn,m.rehover,function(){return t.emit(\"plotly_transitioning\",[]),new Promise(function(a){t._transitioning=!0,e.duration>0&&(t._transitioningWithDuration=!0),t._transitionData._interruptCallbacks.push(function(){n=!0}),r.redraw&&t._transitionData._interruptCallbacks.push(function(){return i.call(\"redraw\",t)}),t._transitionData._interruptCallbacks.push(function(){t.emit(\"plotly_transitioninterrupted\",[])});var o=0,s=0;function l(){return o++,function(){var e;s++,n||s!==o||(e=a,t._transitionData&&(function(t){if(t)for(;t.length;)t.shift()}(t._transitionData._interruptCallbacks),Promise.resolve().then(function(){if(r.redraw)return i.call(\"redraw\",t)}).then(function(){t._transitioning=!1,t._transitioningWithDuration=!1,t.emit(\"plotly_transitioned\",[])}).then(e)))}}r.runFn(l),setTimeout(l())})}],o=l.syncOrAsync(a,t);return o&&o.then||(o=Promise.resolve()),o.then(function(){return t})}m.didMarginChange=function(t,e){for(var r=0;r<S.length;r++){var n=S[r],i=t[n],o=e[n];if(!a(i)||Math.abs(o-i)>1)return!0}return!1},m.graphJson=function(t,e,r,n,a){(a&&e&&!t._fullData||a&&!e&&!t._fullLayout)&&m.supplyDefaults(t);var i=a?t._fullData:t.data,o=a?t._fullLayout:t.layout,s=(t._transitionData||{})._frames;function c(t){if(\"function\"==typeof t)return null;if(l.isPlainObject(t)){var e,n,a={};for(e in t)if(\"function\"!=typeof t[e]&&-1===[\"_\",\"[\"].indexOf(e.charAt(0))){if(\"keepdata\"===r){if(\"src\"===e.substr(e.length-3))continue}else if(\"keepstream\"===r){if(\"string\"==typeof(n=t[e+\"src\"])&&n.indexOf(\":\")>0&&!l.isPlainObject(t.stream))continue}else if(\"keepall\"!==r&&\"string\"==typeof(n=t[e+\"src\"])&&n.indexOf(\":\")>0)continue;a[e]=c(t[e])}return a}return Array.isArray(t)?t.map(c):l.isTypedArray(t)?l.simpleMap(t,l.identity):l.isJSDate(t)?l.ms2DateTimeLocal(+t):t}var u={data:(i||[]).map(function(t){var r=c(t);return e&&delete r.fit,r})};return e||(u.layout=c(o)),t.framework&&t.framework.isPolar&&(u=t.framework.getConfig()),s&&(u.frames=c(s)),\"object\"===n?u:JSON.stringify(u)},m.modifyFrames=function(t,e){var r,n,a,i=t._transitionData._frames,o=t._transitionData._frameHash;for(r=0;r<e.length;r++)switch((n=e[r]).type){case\"replace\":a=n.value;var s=(i[n.index]||{}).name,l=a.name;i[n.index]=o[l]=a,l!==s&&(delete o[s],o[l]=a);break;case\"insert\":o[(a=n.value).name]=a,i.splice(n.index,0,a);break;case\"delete\":delete o[(a=i[n.index]).name],i.splice(n.index,1)}return Promise.resolve()},m.computeFrame=function(t,e){var r,n,a,i,o=t._transitionData._frameHash;if(!e)throw new Error(\"computeFrame must be given a string frame name\");var s=o[e.toString()];if(!s)return!1;for(var l=[s],c=[s.name];s.baseframe&&(s=o[s.baseframe.toString()])&&-1===c.indexOf(s.name);)l.push(s),c.push(s.name);for(var u={};s=l.pop();)if(s.layout&&(u.layout=m.extendLayout(u.layout,s.layout)),s.data){if(u.data||(u.data=[]),!(n=s.traces))for(n=[],r=0;r<s.data.length;r++)n[r]=r;for(u.traces||(u.traces=[]),r=0;r<s.data.length;r++)null!=(a=n[r])&&(-1===(i=u.traces.indexOf(a))&&(i=u.data.length,u.traces[i]=a),u.data[i]=m.extendTrace(u.data[i],s.data[r]))}return u},m.recomputeFrameHash=function(t){for(var e=t._transitionData._frameHash={},r=t._transitionData._frames,n=0;n<r.length;n++){var a=r[n];a&&a.name&&(e[a.name]=a)}},m.extendObjectWithContainers=function(t,e,r){var n,a,i,o,s,c,u,h=l.extendDeepNoArrays({},e||{}),f=l.expandObjectPaths(h),p={};if(r&&r.length)for(i=0;i<r.length;i++)void 0===(a=(n=l.nestedProperty(f,r[i])).get())?l.nestedProperty(p,r[i]).set(null):(n.set(null),l.nestedProperty(p,r[i]).set(a));if(t=l.extendDeepNoArrays(t||{},f),r&&r.length)for(i=0;i<r.length;i++)if(c=l.nestedProperty(p,r[i]).get()){for(u=(s=l.nestedProperty(t,r[i])).get(),Array.isArray(u)||(u=[],s.set(u)),o=0;o<c.length;o++){var d=c[o];u[o]=null===d?null:m.extendObjectWithContainers(u[o],d)}s.set(u)}return t},m.dataArrayContainers=[\"transforms\",\"dimensions\"],m.layoutArrayContainers=i.layoutArrayContainers,m.extendTrace=function(t,e){return m.extendObjectWithContainers(t,e,m.dataArrayContainers)},m.extendLayout=function(t,e){return m.extendObjectWithContainers(t,e,m.layoutArrayContainers)},m.transition=function(t,e,r,n,a,i){var o={redraw:a.redraw},s={},c=[];return o.prepareFn=function(){for(var a=Array.isArray(e)?e.length:0,i=n.slice(0,a),o=0;o<i.length;o++){var u=i[o],h=t._fullData[u]._module;if(h){if(h.animatable){var f=h.basePlotModule.name;s[f]||(s[f]=[]),s[f].push(u)}t.data[i[o]]=m.extendTrace(t.data[i[o]],e[o])}}var p=l.expandObjectPaths(l.extendDeepNoArrays({},r)),d=/^[xy]axis[0-9]*$/;for(var g in p)d.test(g)&&delete p[g].range;m.extendLayout(t.layout,p),delete t.calcdata,m.supplyDefaults(t),m.doCalcdata(t);var v=l.expandObjectPaths(r);if(v){var y=t._fullLayout._plots;for(var x in y){var b=y[x],_=b.xaxis,w=b.yaxis,k=_.range.slice(),T=w.range.slice(),M=null,A=null,S=null,E=null;Array.isArray(v[_._name+\".range\"])?M=v[_._name+\".range\"].slice():Array.isArray((v[_._name]||{}).range)&&(M=v[_._name].range.slice()),Array.isArray(v[w._name+\".range\"])?A=v[w._name+\".range\"].slice():Array.isArray((v[w._name]||{}).range)&&(A=v[w._name].range.slice()),k&&M&&(_.r2l(k[0])!==_.r2l(M[0])||_.r2l(k[1])!==_.r2l(M[1]))&&(S={xr0:k,xr1:M}),T&&A&&(w.r2l(T[0])!==w.r2l(A[0])||w.r2l(T[1])!==w.r2l(A[1]))&&(E={yr0:T,yr1:A}),(S||E)&&c.push(l.extendFlat({plotinfo:b},S,E))}}return Promise.resolve()},o.runFn=function(e){var n,a,o=t._fullLayout._basePlotModules,u=c.length;if(r)for(a=0;a<o.length;a++)o[a].transitionAxes&&o[a].transitionAxes(t,c,i,e);for(var h in u?((n=l.extendFlat({},i)).duration=0,delete s.cartesian):n=i,s){var f=s[h];t._fullData[f[0]]._module.basePlotModule.plot(t,f,n,e)}},E(t,i,o)},m.transitionFromReact=function(t,e,r,n){var a=t._fullLayout,i=a.transition,o={},s=[];return o.prepareFn=function(){var t=a._plots;for(var i in o.redraw=!1,\"some\"===e.anim&&(o.redraw=!0),\"some\"===r.anim&&(o.redraw=!0),t){var c=t[i],u=c.xaxis,h=c.yaxis,f=n[u._name].range.slice(),p=n[h._name].range.slice(),d=u.range.slice(),g=h.range.slice();u.setScale(),h.setScale();var v=null,m=null;u.r2l(f[0])===u.r2l(d[0])&&u.r2l(f[1])===u.r2l(d[1])||(v={xr0:f,xr1:d}),h.r2l(p[0])===h.r2l(g[0])&&h.r2l(p[1])===h.r2l(g[1])||(m={yr0:p,yr1:g}),(v||m)&&s.push(l.extendFlat({plotinfo:c},v,m))}return Promise.resolve()},o.runFn=function(r){for(var n,a,o,c=t._fullData,u=t._fullLayout._basePlotModules,h=[],f=0;f<c.length;f++)h.push(f);function p(){for(var e=0;e<u.length;e++)u[e].transitionAxes&&u[e].transitionAxes(t,s,n,r)}function d(){for(var e=0;e<u.length;e++)u[e].plot(t,o,a,r)}s.length&&e.anim?\"traces first\"===i.ordering?(n=l.extendFlat({},i,{duration:0}),o=h,a=i,setTimeout(p,i.duration),d()):(n=i,o=null,a=l.extendFlat({},i,{duration:0}),setTimeout(d,n.duration),p()):s.length?(n=i,p()):e.anim&&(o=h,a=i,d())},E(t,i,o)},m.doCalcdata=function(t,e){var r,n,a,s,c=h.list(t),f=t._fullData,p=t._fullLayout,d=new Array(f.length),g=(t.calcdata||[]).slice();for(t.calcdata=d,p._numBoxes=0,p._numViolins=0,p._violinScaleGroupStats={},t._hmpixcount=0,t._hmlumcount=0,p._piecolormap={},p._sunburstcolormap={},p._treemapcolormap={},p._funnelareacolormap={},a=0;a<f.length;a++)Array.isArray(e)&&-1===e.indexOf(a)&&(d[a]=g[a]);for(a=0;a<f.length;a++)(r=f[a])._arrayAttrs=o.findArrayAttributes(r),r._extremes={};var v=p._subplots.polar||[];for(a=0;a<v.length;a++)c.push(p[v[a]].radialaxis,p[v[a]].angularaxis);for(var m in p._colorAxes){var x=p[m];!1!==x.cauto&&(delete x.cmin,delete x.cmax)}var b=!1;function _(e){if(r=f[e],n=r._module,!0===r.visible&&r.transforms){if(n&&n.calc){var a=n.calc(t,r);a[0]&&a[0].t&&a[0].t._scene&&delete a[0].t._scene.dirty}for(s=0;s<r.transforms.length;s++){var i=r.transforms[s];(n=y[i.type])&&n.calcTransform&&(r._hasCalcTransform=!0,b=!0,n.calcTransform(t,r,i))}}}function w(e,a){if(r=f[e],!!(n=r._module).isContainer===a){var i=[];if(!0===r.visible&&0!==r._length){delete r._indexToPoints;var o=r.transforms||[];for(s=o.length-1;s>=0;s--)if(o[s].enabled){r._indexToPoints=o[s]._indexToPoints;break}n&&n.calc&&(i=n.calc(t,r))}Array.isArray(i)&&i[0]||(i=[{x:u,y:u}]),i[0].t||(i[0].t={}),i[0].trace=r,d[e]=i}}for(C(c,f,p),a=0;a<f.length;a++)w(a,!0);for(a=0;a<f.length;a++)_(a);for(b&&C(c,f,p),a=0;a<f.length;a++)w(a,!0);for(a=0;a<f.length;a++)w(a,!1);P(t);var k=function(t,e){var r,n,a,o,s,c=[];function u(t,r,n){var a=r._id.charAt(0);if(\"histogram2dcontour\"===t){var i=r._counterAxes[0],o=h.getFromId(e,i),s=\"x\"===a||\"x\"===i&&\"category\"===o.type,l=\"y\"===a||\"y\"===i&&\"category\"===o.type;return function(t,e){return 0===t||0===e?-1:s&&t===n[e].length-1?-1:l&&e===n.length-1?-1:(\"y\"===a?e:t)-1}}return function(t,e){return\"y\"===a?e:t}}var f={min:function(t){return l.aggNums(Math.min,null,t)},max:function(t){return l.aggNums(Math.max,null,t)},sum:function(t){return l.aggNums(function(t,e){return t+e},null,t)},total:function(t){return l.aggNums(function(t,e){return t+e},null,t)},mean:function(t){return l.mean(t)},median:function(t){return l.median(t)}};for(r=0;r<t.length;r++){var p=t[r];if(\"category\"===p.type){var d=p.categoryorder.match(L);if(d){var g=d[1],v=d[2],m=[];for(n=0;n<p._categories.length;n++)m.push([p._categories[n],[]]);for(n=0;n<p._traceIndices.length;n++){var y=p._traceIndices[n],x=e._fullData[y],b=p._id.charAt(0);if(!0===x.visible){var _=x.type;i.traceIs(x,\"histogram\")&&(delete x._xautoBinFinished,delete x._yautoBinFinished);var w=e.calcdata[y];for(a=0;a<w.length;a++){var k,T,M,A=w[a];if(\"splom\"===_){var S=x._axesDim[p._id];if(\"y\"===b){var E=x._diag[S][0];E&&(p=e._fullLayout[h.id2name(E)])}var C=A.trace.dimensions[S].values;for(o=0;o<C.length;o++)for(k=C[o],T=p._categoriesMap[k],s=0;s<A.trace.dimensions.length;s++)if(s!==S){var P=A.trace.dimensions[s];m[T][1].push(P.values[o])}}else if(\"scattergl\"===_){for(o=0;o<A.t.x.length;o++)\"x\"===b&&(k=A.t.x[o],T=k,M=A.t.y[o]),\"y\"===b&&(k=A.t.y[o],T=k,M=A.t.x[o]),m[T][1].push(M);A.t&&A.t._scene&&delete A.t._scene.dirty}else if(A.hasOwnProperty(\"z\")){M=A.z;var O=u(x.type,p,M);for(o=0;o<M.length;o++)for(s=0;s<M[o].length;s++)(T=O(s,o))+1&&m[T][1].push(M[o][s])}else for(\"x\"===b?(k=A.p+1?A.p:A.x,M=A.s||A.v||A.y):\"y\"===b&&(k=A.p+1?A.p:A.y,M=A.s||A.v||A.x),Array.isArray(M)||(M=[M]),o=0;o<M.length;o++)m[k][1].push(M[o])}}}p._categoriesValue=m;var z=[];for(n=0;n<m.length;n++)z.push([m[n][0],f[g](m[n][1])]);z.sort(function(t,e){return t[1]-e[1]}),p._categoriesAggregatedValue=z,p._initialCategories=z.map(function(t){return t[0]}),\"descending\"===v&&p._initialCategories.reverse(),c=c.concat(p.sortByInitialCategories())}}}return c}(c,t);if(k.length){for(p._numBoxes=0,p._numViolins=0,a=0;a<k.length;a++)w(k[a],!0);for(a=0;a<k.length;a++)w(k[a],!1);P(t)}i.getComponentMethod(\"fx\",\"calc\")(t),i.getComponentMethod(\"errorbars\",\"calc\")(t)};var L=/(total|sum|min|max|mean|median) (ascending|descending)/;function C(t,e,r){var n,a,i,o={};for(n=0;n<t.length;n++)i=(a=t[n])._id,a.clearCalc(),\"multicategory\"===a.type&&a.setupMultiCategory(e),o[a._id]=1;var s=r._axisMatchGroups||[];for(n=0;n<s.length;n++)for(i in s[n])o[i]||(a=r[h.id2name(i)]).clearCalc()}function P(t){var e,r,n,a=t._fullLayout,i=a._visibleModules,o={};for(r=0;r<i.length;r++){var s=i[r],c=s.crossTraceCalc;if(c){var u=s.basePlotModule.name;o[u]?l.pushUnique(o[u],c):o[u]=[c]}}for(n in o){var h=o[n],f=a._subplots[n];if(Array.isArray(f))for(e=0;e<f.length;e++){var p=f[e],d=\"cartesian\"===n?a._plots[p]:a[p];for(r=0;r<h.length;r++)h[r](t,d,p)}else for(r=0;r<h.length;r++)h[r](t)}}m.rehover=function(t){t._fullLayout._rehover&&t._fullLayout._rehover()},m.redrag=function(t){t._fullLayout._redrag&&t._fullLayout._redrag()},m.generalUpdatePerTraceModule=function(t,e,r,n){var a,i=e.traceHash,o={};for(a=0;a<r.length;a++){var s=r[a],c=s[0].trace;c.visible&&(o[c.type]=o[c.type]||[],o[c.type].push(s))}for(var u in i)if(!o[u]){var h=i[u][0];h[0].trace.visible=!1,o[u]=[h]}for(var f in o){var p=o[f];p[0][0].trace._module.plot(t,e,l.filterVisible(p),n)}e.traceHash=o},m.plotBasePlot=function(t,e,r,n,a){var o=i.getModule(t),s=d(e.calcdata,o)[0];o.plot(e,s,n,a)},m.cleanBasePlot=function(t,e,r,n,a){var i=a._has&&a._has(t),o=r._has&&r._has(t);i&&!o&&a[\"_\"+t+\"layer\"].selectAll(\"g.trace\").remove()}},{\"../components/color\":592,\"../constants/numerical\":693,\"../lib\":717,\"../plot_api/plot_schema\":754,\"../plot_api/plot_template\":755,\"../plots/get_data\":800,\"../registry\":846,\"./animation_attributes\":760,\"./attributes\":762,\"./cartesian/axis_ids\":768,\"./command\":789,\"./font_attributes\":791,\"./frame_attributes\":792,\"./layout_attributes\":817,d3:165,\"fast-isnumeric\":228}],827:[function(t,e,r){\"use strict\";e.exports={attr:\"subplot\",name:\"polar\",axisNames:[\"angularaxis\",\"radialaxis\"],axisName2dataArray:{angularaxis:\"theta\",radialaxis:\"r\"},layerNames:[\"draglayer\",\"plotbg\",\"backplot\",\"angular-grid\",\"radial-grid\",\"frontplot\",\"angular-line\",\"radial-line\",\"angular-axis\",\"radial-axis\"],radialDragBoxSize:50,angularDragBoxSize:30,cornerLen:25,cornerHalfWidth:2,MINDRAG:8,MINZOOM:20,OFFEDGE:20}},{}],828:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../lib/polygon\").tester,i=n.findIndexOfMin,o=n.isAngleInsideSector,s=n.angleDelta,l=n.angleDist;function c(t,e,r,n){var a,i,o=n[0],s=n[1],l=h(Math.sin(e)-Math.sin(t)),c=h(Math.cos(e)-Math.cos(t)),u=Math.tan(r),f=h(1/u),p=l/c,d=s-p*o;return f?l&&c?i=u*(a=d/(u-p)):c?(a=s*f,i=s):(a=o,i=o*u):l&&c?(a=0,i=d):c?(a=0,i=s):a=i=NaN,[a,i]}function u(t,e,r,a){return n.isFullCircle([e,r])?function(t,e){var r,n=e.length,a=new Array(n+1);for(r=0;r<n;r++){var i=e[r];a[r]=[t*Math.cos(i),t*Math.sin(i)]}return a[r]=a[0].slice(),a}(t,a):function(t,e,r,a){var s,u,h=a.length,f=[];function p(e){return[t*Math.cos(e),t*Math.sin(e)]}function d(t,e,r){return c(t,e,r,p(t))}function g(t){return n.mod(t,h)}function v(t){return o(t,[e,r])}var m=i(a,function(t){return v(t)?l(t,e):1/0}),y=d(a[m],a[g(m-1)],e);for(f.push(y),s=m,u=0;u<h;s++,u++){var x=a[g(s)];if(!v(x))break;f.push(p(x))}var b=i(a,function(t){return v(t)?l(t,r):1/0}),_=d(a[b],a[g(b+1)],r);return f.push(_),f.push([0,0]),f.push(f[0].slice()),f}(t,e,r,a)}function h(t){return Math.abs(t)>1e-10?t:0}function f(t,e,r){e=e||0,r=r||0;for(var n=t.length,a=new Array(n),i=0;i<n;i++){var o=t[i];a[i]=[e+o[0],r-o[1]]}return a}e.exports={isPtInsidePolygon:function(t,e,r,n,i){if(!o(e,n))return!1;var s,l;r[0]<r[1]?(s=r[0],l=r[1]):(s=r[1],l=r[0]);var c=a(u(s,n[0],n[1],i)),h=a(u(l,n[0],n[1],i)),f=[t*Math.cos(e),t*Math.sin(e)];return h.contains(f)&&!c.contains(f)},findPolygonOffset:function(t,e,r,n){for(var a=1/0,i=1/0,o=u(t,e,r,n),s=0;s<o.length;s++){var l=o[s];a=Math.min(a,l[0]),i=Math.min(i,-l[1])}return[a,i]},findEnclosingVertexAngles:function(t,e){var r=i(e,function(e){var r=s(e,t);return r>0?r:1/0}),a=n.mod(r+1,e.length);return[e[r],e[a]]},findIntersectionXY:c,findXYatLength:function(t,e,r,n){var a=-e*r,i=e*e+1,o=2*(e*a-r),s=a*a+r*r-t*t,l=Math.sqrt(o*o-4*i*s),c=(-o+l)/(2*i),u=(-o-l)/(2*i);return[[c,e*c+a+n],[u,e*u+a+n]]},clampTiny:h,pathPolygon:function(t,e,r,n,a,i){return\"M\"+f(u(t,e,r,n),a,i).join(\"L\")},pathPolygonAnnulus:function(t,e,r,n,a,i,o){var s,l;t<e?(s=t,l=e):(s=e,l=t);var c=f(u(s,r,n,a),i,o);return\"M\"+f(u(l,r,n,a),i,o).reverse().join(\"L\")+\"M\"+c.join(\"L\")}}},{\"../../lib\":717,\"../../lib/polygon\":729}],829:[function(t,e,r){\"use strict\";var n=t(\"../get_data\").getSubplotCalcData,a=t(\"../../lib\").counterRegex,i=t(\"./polar\"),o=t(\"./constants\"),s=o.attr,l=o.name,c=a(l),u={};u[s]={valType:\"subplotid\",dflt:l,editType:\"calc\"},e.exports={attr:s,name:l,idRoot:l,idRegex:c,attrRegex:c,attributes:u,layoutAttributes:t(\"./layout_attributes\"),supplyLayoutDefaults:t(\"./layout_defaults\"),plot:function(t){for(var e=t._fullLayout,r=t.calcdata,a=e._subplots[l],o=0;o<a.length;o++){var s=a[o],c=n(r,l,s),u=e[s]._subplot;u||(u=i(t,s),e[s]._subplot=u),u.plot(c,e,t._promises)}},clean:function(t,e,r,n){for(var a=n._subplots[l]||[],i=n._has&&n._has(\"gl\"),o=e._has&&e._has(\"gl\"),s=i&&!o,c=0;c<a.length;c++){var u=a[c],h=n[u]._subplot;if(!e[u]&&h)for(var f in h.framework.remove(),h.layers[\"radial-axis-title\"].remove(),h.clipPaths)h.clipPaths[f].remove();s&&h._scene&&(h._scene.destroy(),h._scene=null)}},toSVG:t(\"../cartesian\").toSVG}},{\"../../lib\":717,\"../cartesian\":776,\"../get_data\":800,\"./constants\":827,\"./layout_attributes\":830,\"./layout_defaults\":831,\"./polar\":838}],830:[function(t,e,r){\"use strict\";var n=t(\"../../components/color/attributes\"),a=t(\"../cartesian/layout_attributes\"),i=t(\"../domain\").attributes,o=t(\"../../lib\").extendFlat,s=t(\"../../plot_api/edit_types\").overrideAll,l=s({color:a.color,showline:o({},a.showline,{dflt:!0}),linecolor:a.linecolor,linewidth:a.linewidth,showgrid:o({},a.showgrid,{dflt:!0}),gridcolor:a.gridcolor,gridwidth:a.gridwidth},\"plot\",\"from-root\"),c=s({tickmode:a.tickmode,nticks:a.nticks,tick0:a.tick0,dtick:a.dtick,tickvals:a.tickvals,ticktext:a.ticktext,ticks:a.ticks,ticklen:a.ticklen,tickwidth:a.tickwidth,tickcolor:a.tickcolor,showticklabels:a.showticklabels,showtickprefix:a.showtickprefix,tickprefix:a.tickprefix,showticksuffix:a.showticksuffix,ticksuffix:a.ticksuffix,showexponent:a.showexponent,exponentformat:a.exponentformat,separatethousands:a.separatethousands,tickfont:a.tickfont,tickangle:a.tickangle,tickformat:a.tickformat,tickformatstops:a.tickformatstops,layer:a.layer},\"plot\",\"from-root\"),u={visible:o({},a.visible,{dflt:!0}),type:o({},a.type,{values:[\"-\",\"linear\",\"log\",\"date\",\"category\"]}),autorange:o({},a.autorange,{editType:\"plot\"}),rangemode:{valType:\"enumerated\",values:[\"tozero\",\"nonnegative\",\"normal\"],dflt:\"tozero\",editType:\"calc\"},range:o({},a.range,{items:[{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}},{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}}],editType:\"plot\"}),categoryorder:a.categoryorder,categoryarray:a.categoryarray,angle:{valType:\"angle\",editType:\"plot\"},side:{valType:\"enumerated\",values:[\"clockwise\",\"counterclockwise\"],dflt:\"clockwise\",editType:\"plot\"},title:{text:o({},a.title.text,{editType:\"plot\",dflt:\"\"}),font:o({},a.title.font,{editType:\"plot\"}),editType:\"plot\"},hoverformat:a.hoverformat,uirevision:{valType:\"any\",editType:\"none\"},editType:\"calc\",_deprecated:{title:a._deprecated.title,titlefont:a._deprecated.titlefont}};o(u,l,c);var h={visible:o({},a.visible,{dflt:!0}),type:{valType:\"enumerated\",values:[\"-\",\"linear\",\"category\"],dflt:\"-\",editType:\"calc\",_noTemplating:!0},categoryorder:a.categoryorder,categoryarray:a.categoryarray,thetaunit:{valType:\"enumerated\",values:[\"radians\",\"degrees\"],dflt:\"degrees\",editType:\"calc\"},period:{valType:\"number\",editType:\"calc\",min:0},direction:{valType:\"enumerated\",values:[\"counterclockwise\",\"clockwise\"],dflt:\"counterclockwise\",editType:\"calc\"},rotation:{valType:\"angle\",editType:\"calc\"},hoverformat:a.hoverformat,uirevision:{valType:\"any\",editType:\"none\"},editType:\"calc\"};o(h,l,c),e.exports={domain:i({name:\"polar\",editType:\"plot\"}),sector:{valType:\"info_array\",items:[{valType:\"number\",editType:\"plot\"},{valType:\"number\",editType:\"plot\"}],dflt:[0,360],editType:\"plot\"},hole:{valType:\"number\",min:0,max:1,dflt:0,editType:\"plot\"},bgcolor:{valType:\"color\",editType:\"plot\",dflt:n.background},radialaxis:u,angularaxis:h,gridshape:{valType:\"enumerated\",values:[\"circular\",\"linear\"],dflt:\"circular\",editType:\"plot\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"calc\"}},{\"../../components/color/attributes\":591,\"../../lib\":717,\"../../plot_api/edit_types\":748,\"../cartesian/layout_attributes\":777,\"../domain\":790}],831:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/color\"),i=t(\"../../plot_api/plot_template\"),o=t(\"../subplot_defaults\"),s=t(\"../get_data\").getSubplotData,l=t(\"../cartesian/tick_value_defaults\"),c=t(\"../cartesian/tick_mark_defaults\"),u=t(\"../cartesian/tick_label_defaults\"),h=t(\"../cartesian/category_order_defaults\"),f=t(\"../cartesian/line_grid_defaults\"),p=t(\"../cartesian/axis_autotype\"),d=t(\"./layout_attributes\"),g=t(\"./set_convert\"),v=t(\"./constants\"),m=v.axisNames;function y(t,e,r,o){var p=r(\"bgcolor\");o.bgColor=a.combine(p,o.paper_bgcolor);var y=r(\"sector\");r(\"hole\");var b,_=s(o.fullData,v.name,o.id),w=o.layoutOut;function k(t,e){return r(b+\".\"+t,e)}for(var T=0;T<m.length;T++){b=m[T],n.isPlainObject(t[b])||(t[b]={});var M=t[b],A=i.newContainer(e,b);A._id=A._name=b,A._attr=o.id+\".\"+b,A._traceIndices=_.map(function(t){return t._expandedIndex});var S=v.axisName2dataArray[b],E=x(M,A,k,_,S);h(M,A,k,{axData:_,dataAttr:S});var L,C,P=k(\"visible\");switch(g(A,e,w),k(\"uirevision\",e.uirevision),P&&(C=(L=k(\"color\"))===M.color?L:o.font.color),A._m=1,b){case\"radialaxis\":var O=k(\"autorange\",!A.isValidRange(M.range));M.autorange=O,!O||\"linear\"!==E&&\"-\"!==E||k(\"rangemode\"),\"reversed\"===O&&(A._m=-1),k(\"range\"),A.cleanRange(\"range\",{dfltRange:[0,1]}),P&&(k(\"side\"),k(\"angle\",y[0]),k(\"title.text\"),n.coerceFont(k,\"title.font\",{family:o.font.family,size:Math.round(1.2*o.font.size),color:C}));break;case\"angularaxis\":if(\"date\"===E){n.log(\"Polar plots do not support date angular axes yet.\");for(var z=0;z<_.length;z++)_[z].visible=!1;E=M.type=A.type=\"linear\"}k(\"linear\"===E?\"thetaunit\":\"period\");var I=k(\"direction\");k(\"rotation\",{counterclockwise:0,clockwise:90}[I])}if(P)l(M,A,k,A.type),u(M,A,k,A.type,{tickSuffixDflt:\"degrees\"===A.thetaunit?\"\\xb0\":void 0}),c(M,A,k,{outerTicks:!0}),k(\"showticklabels\")&&(n.coerceFont(k,\"tickfont\",{family:o.font.family,size:o.font.size,color:C}),k(\"tickangle\"),k(\"tickformat\")),f(M,A,k,{dfltColor:L,bgColor:o.bgColor,blend:60,showLine:!0,showGrid:!0,noZeroLine:!0,attributes:d[b]}),k(\"layer\");\"category\"!==E&&k(\"hoverformat\"),A._input=M}\"category\"===e.angularaxis.type&&r(\"gridshape\")}function x(t,e,r,n,a){if(\"-\"===r(\"type\")){for(var i,o=0;o<n.length;o++)if(n[o].visible){i=n[o];break}i&&i[a]&&(e.type=p(i[a],\"gregorian\")),\"-\"===e.type?e.type=\"linear\":t.type=e.type}return e.type}e.exports=function(t,e,r){o(t,e,r,{type:v.name,attributes:d,handleDefaults:y,font:e.font,paper_bgcolor:e.paper_bgcolor,fullData:r,layoutOut:e})}},{\"../../components/color\":592,\"../../lib\":717,\"../../plot_api/plot_template\":755,\"../cartesian/axis_autotype\":766,\"../cartesian/category_order_defaults\":769,\"../cartesian/line_grid_defaults\":779,\"../cartesian/tick_label_defaults\":784,\"../cartesian/tick_mark_defaults\":785,\"../cartesian/tick_value_defaults\":786,\"../get_data\":800,\"../subplot_defaults\":840,\"./constants\":827,\"./layout_attributes\":830,\"./set_convert\":839}],832:[function(t,e,r){\"use strict\";var n=t(\"../../../traces/scatter/attributes\"),a=n.marker,i=t(\"../../../lib/extend\").extendFlat;[\"Area traces are deprecated!\",\"Please switch to the *barpolar* trace type.\"].join(\" \");e.exports={r:i({},n.r,{}),t:i({},n.t,{}),marker:{color:i({},a.color,{}),size:i({},a.size,{}),symbol:i({},a.symbol,{}),opacity:i({},a.opacity,{}),editType:\"calc\"}}},{\"../../../lib/extend\":708,\"../../../traces/scatter/attributes\":1120}],833:[function(t,e,r){\"use strict\";var n=t(\"../../cartesian/layout_attributes\"),a=t(\"../../../lib/extend\").extendFlat,i=t(\"../../../plot_api/edit_types\").overrideAll,o=[\"Legacy polar charts are deprecated!\",\"Please switch to *polar* subplots.\"].join(\" \"),s=a({},n.domain,{});function l(t,e){return a({},e,{showline:{valType:\"boolean\"},showticklabels:{valType:\"boolean\"},tickorientation:{valType:\"enumerated\",values:[\"horizontal\",\"vertical\"]},ticklen:{valType:\"number\",min:0},tickcolor:{valType:\"color\"},ticksuffix:{valType:\"string\"},endpadding:{valType:\"number\",description:o},visible:{valType:\"boolean\"}})}e.exports=i({radialaxis:l(0,{range:{valType:\"info_array\",items:[{valType:\"number\"},{valType:\"number\"}]},domain:s,orientation:{valType:\"number\"}}),angularaxis:l(0,{range:{valType:\"info_array\",items:[{valType:\"number\",dflt:0},{valType:\"number\",dflt:360}]},domain:s}),layout:{direction:{valType:\"enumerated\",values:[\"clockwise\",\"counterclockwise\"]},orientation:{valType:\"angle\"}}},\"plot\",\"nested\")},{\"../../../lib/extend\":708,\"../../../plot_api/edit_types\":748,\"../../cartesian/layout_attributes\":777}],834:[function(t,e,r){\"use strict\";(e.exports=t(\"./micropolar\")).manager=t(\"./micropolar_manager\")},{\"./micropolar\":835,\"./micropolar_manager\":836}],835:[function(t,e,r){var n=t(\"d3\"),a=t(\"../../../lib\").extendDeepAll,i=t(\"../../../constants/alignment\").MID_SHIFT,o=e.exports={version:\"0.2.2\"};o.Axis=function(){var t,e,r,s,l={data:[],layout:{}},c={},u={},h=n.dispatch(\"hover\"),f={};return f.render=function(c){return function(c){e=c||e;var h=l.data,f=l.layout;(\"string\"==typeof e||e.nodeName)&&(e=n.select(e)),e.datum(h).each(function(e,l){var c=e.slice();u={data:o.util.cloneJson(c),layout:o.util.cloneJson(f)};var h=0;c.forEach(function(t,e){t.color||(t.color=f.defaultColorRange[h],h=(h+1)%f.defaultColorRange.length),t.strokeColor||(t.strokeColor=\"LinePlot\"===t.geometry?t.color:n.rgb(t.color).darker().toString()),u.data[e].color=t.color,u.data[e].strokeColor=t.strokeColor,u.data[e].strokeDash=t.strokeDash,u.data[e].strokeSize=t.strokeSize});var p=c.filter(function(t,e){var r=t.visible;return\"undefined\"==typeof r||!0===r}),d=!1,g=p.map(function(t,e){return d=d||\"undefined\"!=typeof t.groupId,t});if(d){var v=n.nest().key(function(t,e){return\"undefined\"!=typeof t.groupId?t.groupId:\"unstacked\"}).entries(g),m=[],y=v.map(function(t,e){if(\"unstacked\"===t.key)return t.values;var r=t.values[0].r.map(function(t,e){return 0});return t.values.forEach(function(t,e,n){t.yStack=[r],m.push(r),r=o.util.sumArrays(t.r,r)}),t.values});p=n.merge(y)}p.forEach(function(t,e){t.t=Array.isArray(t.t[0])?t.t:[t.t],t.r=Array.isArray(t.r[0])?t.r:[t.r]});var x=Math.min(f.width-f.margin.left-f.margin.right,f.height-f.margin.top-f.margin.bottom)/2;x=Math.max(10,x);var b,_=[f.margin.left+x,f.margin.top+x];b=d?[0,n.max(o.util.sumArrays(o.util.arrayLast(p).r[0],o.util.arrayLast(m)))]:n.extent(o.util.flattenArray(p.map(function(t,e){return t.r}))),f.radialAxis.domain!=o.DATAEXTENT&&(b[0]=0),r=n.scale.linear().domain(f.radialAxis.domain!=o.DATAEXTENT&&f.radialAxis.domain?f.radialAxis.domain:b).range([0,x]),u.layout.radialAxis.domain=r.domain();var w,k=o.util.flattenArray(p.map(function(t,e){return t.t})),T=\"string\"==typeof k[0];T&&(k=o.util.deduplicate(k),w=k.slice(),k=n.range(k.length),p=p.map(function(t,e){var r=t;return t.t=[k],d&&(r.yStack=t.yStack),r}));var M=p.filter(function(t,e){return\"LinePlot\"===t.geometry||\"DotPlot\"===t.geometry}).length===p.length,A=null===f.needsEndSpacing?T||!M:f.needsEndSpacing,S=f.angularAxis.domain&&f.angularAxis.domain!=o.DATAEXTENT&&!T&&f.angularAxis.domain[0]>=0?f.angularAxis.domain:n.extent(k),E=Math.abs(k[1]-k[0]);M&&!T&&(E=0);var L=S.slice();A&&T&&(L[1]+=E);var C=f.angularAxis.ticksCount||4;C>8&&(C=C/(C/8)+C%8),f.angularAxis.ticksStep&&(C=(L[1]-L[0])/C);var P=f.angularAxis.ticksStep||(L[1]-L[0])/(C*(f.minorTicks+1));w&&(P=Math.max(Math.round(P),1)),L[2]||(L[2]=P);var O=n.range.apply(this,L);if(O=O.map(function(t,e){return parseFloat(t.toPrecision(12))}),s=n.scale.linear().domain(L.slice(0,2)).range(\"clockwise\"===f.direction?[0,360]:[360,0]),u.layout.angularAxis.domain=s.domain(),u.layout.angularAxis.endPadding=A?E:0,\"undefined\"==typeof(t=n.select(this).select(\"svg.chart-root\"))||t.empty()){var z=(new DOMParser).parseFromString(\"<svg xmlns='http://www.w3.org/2000/svg' class='chart-root'>' + '<g class='outer-group'>' + '<g class='chart-group'>' + '<circle class='background-circle'></circle>' + '<g class='geometry-group'></g>' + '<g class='radial axis-group'>' + '<circle class='outside-circle'></circle>' + '</g>' + '<g class='angular axis-group'></g>' + '<g class='guides-group'><line></line><circle r='0'></circle></g>' + '</g>' + '<g class='legend-group'></g>' + '<g class='tooltips-group'></g>' + '<g class='title-group'><text></text></g>' + '</g>' + '</svg>\",\"application/xml\"),I=this.appendChild(this.ownerDocument.importNode(z.documentElement,!0));t=n.select(I)}t.select(\".guides-group\").style({\"pointer-events\":\"none\"}),t.select(\".angular.axis-group\").style({\"pointer-events\":\"none\"}),t.select(\".radial.axis-group\").style({\"pointer-events\":\"none\"});var D,R=t.select(\".chart-group\"),F={fill:\"none\",stroke:f.tickColor},B={\"font-size\":f.font.size,\"font-family\":f.font.family,fill:f.font.color,\"text-shadow\":[\"-1px 0px\",\"1px -1px\",\"-1px 1px\",\"1px 1px\"].map(function(t,e){return\" \"+t+\" 0 \"+f.font.outlineColor}).join(\",\")};if(f.showLegend){D=t.select(\".legend-group\").attr({transform:\"translate(\"+[x,f.margin.top]+\")\"}).style({display:\"block\"});var N=p.map(function(t,e){var r=o.util.cloneJson(t);return r.symbol=\"DotPlot\"===t.geometry?t.dotType||\"circle\":\"LinePlot\"!=t.geometry?\"square\":\"line\",r.visibleInLegend=\"undefined\"==typeof t.visibleInLegend||t.visibleInLegend,r.color=\"LinePlot\"===t.geometry?t.strokeColor:t.color,r});o.Legend().config({data:p.map(function(t,e){return t.name||\"Element\"+e}),legendConfig:a({},o.Legend.defaultConfig().legendConfig,{container:D,elements:N,reverseOrder:f.legend.reverseOrder})})();var j=D.node().getBBox();x=Math.min(f.width-j.width-f.margin.left-f.margin.right,f.height-f.margin.top-f.margin.bottom)/2,x=Math.max(10,x),_=[f.margin.left+x,f.margin.top+x],r.range([0,x]),u.layout.radialAxis.domain=r.domain(),D.attr(\"transform\",\"translate(\"+[_[0]+x,_[1]-x]+\")\")}else D=t.select(\".legend-group\").style({display:\"none\"});t.attr({width:f.width,height:f.height}).style({opacity:f.opacity}),R.attr(\"transform\",\"translate(\"+_+\")\").style({cursor:\"crosshair\"});var V=[(f.width-(f.margin.left+f.margin.right+2*x+(j?j.width:0)))/2,(f.height-(f.margin.top+f.margin.bottom+2*x))/2];if(V[0]=Math.max(0,V[0]),V[1]=Math.max(0,V[1]),t.select(\".outer-group\").attr(\"transform\",\"translate(\"+V+\")\"),f.title&&f.title.text){var U=t.select(\"g.title-group text\").style(B).text(f.title.text),q=U.node().getBBox();U.attr({x:_[0]-q.width/2,y:_[1]-x-20})}var H=t.select(\".radial.axis-group\");if(f.radialAxis.gridLinesVisible){var G=H.selectAll(\"circle.grid-circle\").data(r.ticks(5));G.enter().append(\"circle\").attr({class:\"grid-circle\"}).style(F),G.attr(\"r\",r),G.exit().remove()}H.select(\"circle.outside-circle\").attr({r:x}).style(F);var Y=t.select(\"circle.background-circle\").attr({r:x}).style({fill:f.backgroundColor,stroke:f.stroke});function W(t,e){return s(t)%360+f.orientation}if(f.radialAxis.visible){var X=n.svg.axis().scale(r).ticks(5).tickSize(5);H.call(X).attr({transform:\"rotate(\"+f.radialAxis.orientation+\")\"}),H.selectAll(\".domain\").style(F),H.selectAll(\"g>text\").text(function(t,e){return this.textContent+f.radialAxis.ticksSuffix}).style(B).style({\"text-anchor\":\"start\"}).attr({x:0,y:0,dx:0,dy:0,transform:function(t,e){return\"horizontal\"===f.radialAxis.tickOrientation?\"rotate(\"+-f.radialAxis.orientation+\") translate(\"+[0,B[\"font-size\"]]+\")\":\"translate(\"+[0,B[\"font-size\"]]+\")\"}}),H.selectAll(\"g>line\").style({stroke:\"black\"})}var Z=t.select(\".angular.axis-group\").selectAll(\"g.angular-tick\").data(O),J=Z.enter().append(\"g\").classed(\"angular-tick\",!0);Z.attr({transform:function(t,e){return\"rotate(\"+W(t)+\")\"}}).style({display:f.angularAxis.visible?\"block\":\"none\"}),Z.exit().remove(),J.append(\"line\").classed(\"grid-line\",!0).classed(\"major\",function(t,e){return e%(f.minorTicks+1)==0}).classed(\"minor\",function(t,e){return!(e%(f.minorTicks+1)==0)}).style(F),J.selectAll(\".minor\").style({stroke:f.minorTickColor}),Z.select(\"line.grid-line\").attr({x1:f.tickLength?x-f.tickLength:0,x2:x}).style({display:f.angularAxis.gridLinesVisible?\"block\":\"none\"}),J.append(\"text\").classed(\"axis-text\",!0).style(B);var K=Z.select(\"text.axis-text\").attr({x:x+f.labelOffset,dy:i+\"em\",transform:function(t,e){var r=W(t),n=x+f.labelOffset,a=f.angularAxis.tickOrientation;return\"horizontal\"==a?\"rotate(\"+-r+\" \"+n+\" 0)\":\"radial\"==a?r<270&&r>90?\"rotate(180 \"+n+\" 0)\":null:\"rotate(\"+(r<=180&&r>0?-90:90)+\" \"+n+\" 0)\"}}).style({\"text-anchor\":\"middle\",display:f.angularAxis.labelsVisible?\"block\":\"none\"}).text(function(t,e){return e%(f.minorTicks+1)!=0?\"\":w?w[t]+f.angularAxis.ticksSuffix:t+f.angularAxis.ticksSuffix}).style(B);f.angularAxis.rewriteTicks&&K.text(function(t,e){return e%(f.minorTicks+1)!=0?\"\":f.angularAxis.rewriteTicks(this.textContent,e)});var Q=n.max(R.selectAll(\".angular-tick text\")[0].map(function(t,e){return t.getCTM().e+t.getBBox().width}));D.attr({transform:\"translate(\"+[x+Q,f.margin.top]+\")\"});var $=t.select(\"g.geometry-group\").selectAll(\"g\").size()>0,tt=t.select(\"g.geometry-group\").selectAll(\"g.geometry\").data(p);if(tt.enter().append(\"g\").attr({class:function(t,e){return\"geometry geometry\"+e}}),tt.exit().remove(),p[0]||$){var et=[];p.forEach(function(t,e){var n={};n.radialScale=r,n.angularScale=s,n.container=tt.filter(function(t,r){return r==e}),n.geometry=t.geometry,n.orientation=f.orientation,n.direction=f.direction,n.index=e,et.push({data:t,geometryConfig:n})});var rt=n.nest().key(function(t,e){return\"undefined\"!=typeof t.data.groupId||\"unstacked\"}).entries(et),nt=[];rt.forEach(function(t,e){\"unstacked\"===t.key?nt=nt.concat(t.values.map(function(t,e){return[t]})):nt.push(t.values)}),nt.forEach(function(t,e){var r;r=Array.isArray(t)?t[0].geometryConfig.geometry:t.geometryConfig.geometry;var n=t.map(function(t,e){return a(o[r].defaultConfig(),t)});o[r]().config(n)()})}var at,it,ot=t.select(\".guides-group\"),st=t.select(\".tooltips-group\"),lt=o.tooltipPanel().config({container:st,fontSize:8})(),ct=o.tooltipPanel().config({container:st,fontSize:8})(),ut=o.tooltipPanel().config({container:st,hasTick:!0})();if(!T){var ht=ot.select(\"line\").attr({x1:0,y1:0,y2:0}).style({stroke:\"grey\",\"pointer-events\":\"none\"});R.on(\"mousemove.angular-guide\",function(t,e){var r=o.util.getMousePos(Y).angle;ht.attr({x2:-x,transform:\"rotate(\"+r+\")\"}).style({opacity:.5});var n=(r+180+360-f.orientation)%360;at=s.invert(n);var a=o.util.convertToCartesian(x+12,r+180);lt.text(o.util.round(at)).move([a[0]+_[0],a[1]+_[1]])}).on(\"mouseout.angular-guide\",function(t,e){ot.select(\"line\").style({opacity:0})})}var ft=ot.select(\"circle\").style({stroke:\"grey\",fill:\"none\"});R.on(\"mousemove.radial-guide\",function(t,e){var n=o.util.getMousePos(Y).radius;ft.attr({r:n}).style({opacity:.5}),it=r.invert(o.util.getMousePos(Y).radius);var a=o.util.convertToCartesian(n,f.radialAxis.orientation);ct.text(o.util.round(it)).move([a[0]+_[0],a[1]+_[1]])}).on(\"mouseout.radial-guide\",function(t,e){ft.style({opacity:0}),ut.hide(),lt.hide(),ct.hide()}),t.selectAll(\".geometry-group .mark\").on(\"mouseover.tooltip\",function(e,r){var a=n.select(this),i=this.style.fill,s=\"black\",l=this.style.opacity||1;if(a.attr({\"data-opacity\":l}),i&&\"none\"!==i){a.attr({\"data-fill\":i}),s=n.hsl(i).darker().toString(),a.style({fill:s,opacity:1});var c={t:o.util.round(e[0]),r:o.util.round(e[1])};T&&(c.t=w[e[0]]);var u=\"t: \"+c.t+\", r: \"+c.r,h=this.getBoundingClientRect(),f=t.node().getBoundingClientRect(),p=[h.left+h.width/2-V[0]-f.left,h.top+h.height/2-V[1]-f.top];ut.config({color:s}).text(u),ut.move(p)}else i=this.style.stroke||\"black\",a.attr({\"data-stroke\":i}),s=n.hsl(i).darker().toString(),a.style({stroke:s,opacity:1})}).on(\"mousemove.tooltip\",function(t,e){if(0!=n.event.which)return!1;n.select(this).attr(\"data-fill\")&&ut.show()}).on(\"mouseout.tooltip\",function(t,e){ut.hide();var r=n.select(this),a=r.attr(\"data-fill\");a?r.style({fill:a,opacity:r.attr(\"data-opacity\")}):r.style({stroke:r.attr(\"data-stroke\"),opacity:r.attr(\"data-opacity\")})})})}(c),this},f.config=function(t){if(!arguments.length)return l;var e=o.util.cloneJson(t);return e.data.forEach(function(t,e){l.data[e]||(l.data[e]={}),a(l.data[e],o.Axis.defaultConfig().data[0]),a(l.data[e],t)}),a(l.layout,o.Axis.defaultConfig().layout),a(l.layout,e.layout),this},f.getLiveConfig=function(){return u},f.getinputConfig=function(){return c},f.radialScale=function(t){return r},f.angularScale=function(t){return s},f.svg=function(){return t},n.rebind(f,h,\"on\"),f},o.Axis.defaultConfig=function(t,e){return{data:[{t:[1,2,3,4],r:[10,11,12,13],name:\"Line1\",geometry:\"LinePlot\",color:null,strokeDash:\"solid\",strokeColor:null,strokeSize:\"1\",visibleInLegend:!0,opacity:1}],layout:{defaultColorRange:n.scale.category10().range(),title:null,height:450,width:500,margin:{top:40,right:40,bottom:40,left:40},font:{size:12,color:\"gray\",outlineColor:\"white\",family:\"Tahoma, sans-serif\"},direction:\"clockwise\",orientation:0,labelOffset:10,radialAxis:{domain:null,orientation:-45,ticksSuffix:\"\",visible:!0,gridLinesVisible:!0,tickOrientation:\"horizontal\",rewriteTicks:null},angularAxis:{domain:[0,360],ticksSuffix:\"\",visible:!0,gridLinesVisible:!0,labelsVisible:!0,tickOrientation:\"horizontal\",rewriteTicks:null,ticksCount:null,ticksStep:null},minorTicks:0,tickLength:null,tickColor:\"silver\",minorTickColor:\"#eee\",backgroundColor:\"none\",needsEndSpacing:null,showLegend:!0,legend:{reverseOrder:!1},opacity:1}}},o.util={},o.DATAEXTENT=\"dataExtent\",o.AREA=\"AreaChart\",o.LINE=\"LinePlot\",o.DOT=\"DotPlot\",o.BAR=\"BarChart\",o.util._override=function(t,e){for(var r in t)r in e&&(e[r]=t[r])},o.util._extend=function(t,e){for(var r in t)e[r]=t[r]},o.util._rndSnd=function(){return 2*Math.random()-1+(2*Math.random()-1)+(2*Math.random()-1)},o.util.dataFromEquation2=function(t,e){var r=e||6;return n.range(0,360+r,r).map(function(e,r){var n=e*Math.PI/180;return[e,t(n)]})},o.util.dataFromEquation=function(t,e,r){var a=e||6,i=[],o=[];n.range(0,360+a,a).forEach(function(e,r){var n=e*Math.PI/180,a=t(n);i.push(e),o.push(a)});var s={t:i,r:o};return r&&(s.name=r),s},o.util.ensureArray=function(t,e){if(\"undefined\"==typeof t)return null;var r=[].concat(t);return n.range(e).map(function(t,e){return r[e]||r[0]})},o.util.fillArrays=function(t,e,r){return e.forEach(function(e,n){t[e]=o.util.ensureArray(t[e],r)}),t},o.util.cloneJson=function(t){return JSON.parse(JSON.stringify(t))},o.util.validateKeys=function(t,e){\"string\"==typeof e&&(e=e.split(\".\"));var r=e.shift();return t[r]&&(!e.length||objHasKeys(t[r],e))},o.util.sumArrays=function(t,e){return n.zip(t,e).map(function(t,e){return n.sum(t)})},o.util.arrayLast=function(t){return t[t.length-1]},o.util.arrayEqual=function(t,e){for(var r=Math.max(t.length,e.length,1);r-- >=0&&t[r]===e[r];);return-2===r},o.util.flattenArray=function(t){for(var e=[];!o.util.arrayEqual(e,t);)e=t,t=[].concat.apply([],t);return t},o.util.deduplicate=function(t){return t.filter(function(t,e,r){return r.indexOf(t)==e})},o.util.convertToCartesian=function(t,e){var r=e*Math.PI/180;return[t*Math.cos(r),t*Math.sin(r)]},o.util.round=function(t,e){var r=e||2,n=Math.pow(10,r);return Math.round(t*n)/n},o.util.getMousePos=function(t){var e=n.mouse(t.node()),r=e[0],a=e[1],i={};return i.x=r,i.y=a,i.pos=e,i.angle=180*(Math.atan2(a,r)+Math.PI)/Math.PI,i.radius=Math.sqrt(r*r+a*a),i},o.util.duplicatesCount=function(t){for(var e,r={},n={},a=0,i=t.length;a<i;a++)(e=t[a])in r?(r[e]++,n[e]=r[e]):r[e]=1;return n},o.util.duplicates=function(t){return Object.keys(o.util.duplicatesCount(t))},o.util.translator=function(t,e,r,n){if(n){var a=r.slice();r=e,e=a}var i=e.reduce(function(t,e){if(\"undefined\"!=typeof t)return t[e]},t);\"undefined\"!=typeof i&&(e.reduce(function(t,r,n){if(\"undefined\"!=typeof t)return n===e.length-1&&delete t[r],t[r]},t),r.reduce(function(t,e,n){return\"undefined\"==typeof t[e]&&(t[e]={}),n===r.length-1&&(t[e]=i),t[e]},t))},o.PolyChart=function(){var t=[o.PolyChart.defaultConfig()],e=n.dispatch(\"hover\"),r={solid:\"none\",dash:[5,2],dot:[2,5]};function i(){var e=t[0].geometryConfig,a=e.container;\"string\"==typeof a&&(a=n.select(a)),a.datum(t).each(function(t,a){var i=!!t[0].data.yStack,o=t.map(function(t,e){return i?n.zip(t.data.t[0],t.data.r[0],t.data.yStack[0]):n.zip(t.data.t[0],t.data.r[0])}),s=e.angularScale,l=e.radialScale.domain()[0],c={bar:function(r,a,i){var o=t[i].data,l=e.radialScale(r[1])-e.radialScale(0),c=e.radialScale(r[2]||0),u=o.barWidth;n.select(this).attr({class:\"mark bar\",d:\"M\"+[[l+c,-u/2],[l+c,u/2],[c,u/2],[c,-u/2]].join(\"L\")+\"Z\",transform:function(t,r){return\"rotate(\"+(e.orientation+s(t[0]))+\")\"}})}};c.dot=function(r,a,i){var o=r[2]?[r[0],r[1]+r[2]]:r,s=n.svg.symbol().size(t[i].data.dotSize).type(t[i].data.dotType)(r,a);n.select(this).attr({class:\"mark dot\",d:s,transform:function(t,r){var n,a,i,s=(n=function(t,r){var n=e.radialScale(t[1]),a=(e.angularScale(t[0])+e.orientation)*Math.PI/180;return{r:n,t:a}}(o),a=n.r*Math.cos(n.t),i=n.r*Math.sin(n.t),{x:a,y:i});return\"translate(\"+[s.x,s.y]+\")\"}})};var u=n.svg.line.radial().interpolate(t[0].data.lineInterpolation).radius(function(t){return e.radialScale(t[1])}).angle(function(t){return e.angularScale(t[0])*Math.PI/180});c.line=function(r,a,i){var s=r[2]?o[i].map(function(t,e){return[t[0],t[1]+t[2]]}):o[i];if(n.select(this).each(c.dot).style({opacity:function(e,r){return+t[i].data.dotVisible},fill:d.stroke(r,a,i)}).attr({class:\"mark dot\"}),!(a>0)){var l=n.select(this.parentNode).selectAll(\"path.line\").data([0]);l.enter().insert(\"path\"),l.attr({class:\"line\",d:u(s),transform:function(t,r){return\"rotate(\"+(e.orientation+90)+\")\"},\"pointer-events\":\"none\"}).style({fill:function(t,e){return d.fill(r,a,i)},\"fill-opacity\":0,stroke:function(t,e){return d.stroke(r,a,i)},\"stroke-width\":function(t,e){return d[\"stroke-width\"](r,a,i)},\"stroke-dasharray\":function(t,e){return d[\"stroke-dasharray\"](r,a,i)},opacity:function(t,e){return d.opacity(r,a,i)},display:function(t,e){return d.display(r,a,i)}})}};var h=e.angularScale.range(),f=Math.abs(h[1]-h[0])/o[0].length*Math.PI/180,p=n.svg.arc().startAngle(function(t){return-f/2}).endAngle(function(t){return f/2}).innerRadius(function(t){return e.radialScale(l+(t[2]||0))}).outerRadius(function(t){return e.radialScale(l+(t[2]||0))+e.radialScale(t[1])});c.arc=function(t,r,a){n.select(this).attr({class:\"mark arc\",d:p,transform:function(t,r){return\"rotate(\"+(e.orientation+s(t[0])+90)+\")\"}})};var d={fill:function(e,r,n){return t[n].data.color},stroke:function(e,r,n){return t[n].data.strokeColor},\"stroke-width\":function(e,r,n){return t[n].data.strokeSize+\"px\"},\"stroke-dasharray\":function(e,n,a){return r[t[a].data.strokeDash]},opacity:function(e,r,n){return t[n].data.opacity},display:function(e,r,n){return\"undefined\"==typeof t[n].data.visible||t[n].data.visible?\"block\":\"none\"}},g=n.select(this).selectAll(\"g.layer\").data(o);g.enter().append(\"g\").attr({class:\"layer\"});var v=g.selectAll(\"path.mark\").data(function(t,e){return t});v.enter().append(\"path\").attr({class:\"mark\"}),v.style(d).each(c[e.geometryType]),v.exit().remove(),g.exit().remove()})}return i.config=function(e){return arguments.length?(e.forEach(function(e,r){t[r]||(t[r]={}),a(t[r],o.PolyChart.defaultConfig()),a(t[r],e)}),this):t},i.getColorScale=function(){},n.rebind(i,e,\"on\"),i},o.PolyChart.defaultConfig=function(){return{data:{name:\"geom1\",t:[[1,2,3,4]],r:[[1,2,3,4]],dotType:\"circle\",dotSize:64,dotVisible:!1,barWidth:20,color:\"#ffa500\",strokeSize:1,strokeColor:\"silver\",strokeDash:\"solid\",opacity:1,index:0,visible:!0,visibleInLegend:!0},geometryConfig:{geometry:\"LinePlot\",geometryType:\"arc\",direction:\"clockwise\",orientation:0,container:\"body\",radialScale:null,angularScale:null,colorScale:n.scale.category20()}}},o.BarChart=function(){return o.PolyChart()},o.BarChart.defaultConfig=function(){return{geometryConfig:{geometryType:\"bar\"}}},o.AreaChart=function(){return o.PolyChart()},o.AreaChart.defaultConfig=function(){return{geometryConfig:{geometryType:\"arc\"}}},o.DotPlot=function(){return o.PolyChart()},o.DotPlot.defaultConfig=function(){return{geometryConfig:{geometryType:\"dot\",dotType:\"circle\"}}},o.LinePlot=function(){return o.PolyChart()},o.LinePlot.defaultConfig=function(){return{geometryConfig:{geometryType:\"line\"}}},o.Legend=function(){var t=o.Legend.defaultConfig(),e=n.dispatch(\"hover\");function r(){var e=t.legendConfig,i=t.data.map(function(t,r){return[].concat(t).map(function(t,n){var i=a({},e.elements[r]);return i.name=t,i.color=[].concat(e.elements[r].color)[n],i})}),o=n.merge(i);o=o.filter(function(t,r){return e.elements[r]&&(e.elements[r].visibleInLegend||\"undefined\"==typeof e.elements[r].visibleInLegend)}),e.reverseOrder&&(o=o.reverse());var s=e.container;(\"string\"==typeof s||s.nodeName)&&(s=n.select(s));var l=o.map(function(t,e){return t.color}),c=e.fontSize,u=null==e.isContinuous?\"number\"==typeof o[0]:e.isContinuous,h=u?e.height:c*o.length,f=s.classed(\"legend-group\",!0).selectAll(\"svg\").data([0]),p=f.enter().append(\"svg\").attr({width:300,height:h+c,xmlns:\"http://www.w3.org/2000/svg\",\"xmlns:xlink\":\"http://www.w3.org/1999/xlink\",version:\"1.1\"});p.append(\"g\").classed(\"legend-axis\",!0),p.append(\"g\").classed(\"legend-marks\",!0);var d=n.range(o.length),g=n.scale[u?\"linear\":\"ordinal\"]().domain(d).range(l),v=n.scale[u?\"linear\":\"ordinal\"]().domain(d)[u?\"range\":\"rangePoints\"]([0,h]);if(u){var m=f.select(\".legend-marks\").append(\"defs\").append(\"linearGradient\").attr({id:\"grad1\",x1:\"0%\",y1:\"0%\",x2:\"0%\",y2:\"100%\"}).selectAll(\"stop\").data(l);m.enter().append(\"stop\"),m.attr({offset:function(t,e){return e/(l.length-1)*100+\"%\"}}).style({\"stop-color\":function(t,e){return t}}),f.append(\"rect\").classed(\"legend-mark\",!0).attr({height:e.height,width:e.colorBandWidth,fill:\"url(#grad1)\"})}else{var y=f.select(\".legend-marks\").selectAll(\"path.legend-mark\").data(o);y.enter().append(\"path\").classed(\"legend-mark\",!0),y.attr({transform:function(t,e){return\"translate(\"+[c/2,v(e)+c/2]+\")\"},d:function(t,e){var r,a,i,o=t.symbol;return i=3*(a=c),\"line\"===(r=o)?\"M\"+[[-a/2,-a/12],[a/2,-a/12],[a/2,a/12],[-a/2,a/12]]+\"Z\":-1!=n.svg.symbolTypes.indexOf(r)?n.svg.symbol().type(r).size(i)():n.svg.symbol().type(\"square\").size(i)()},fill:function(t,e){return g(e)}}),y.exit().remove()}var x=n.svg.axis().scale(v).orient(\"right\"),b=f.select(\"g.legend-axis\").attr({transform:\"translate(\"+[u?e.colorBandWidth:c,c/2]+\")\"}).call(x);return b.selectAll(\".domain\").style({fill:\"none\",stroke:\"none\"}),b.selectAll(\"line\").style({fill:\"none\",stroke:u?e.textColor:\"none\"}),b.selectAll(\"text\").style({fill:e.textColor,\"font-size\":e.fontSize}).text(function(t,e){return o[e].name}),r}return r.config=function(e){return arguments.length?(a(t,e),this):t},n.rebind(r,e,\"on\"),r},o.Legend.defaultConfig=function(t,e){return{data:[\"a\",\"b\",\"c\"],legendConfig:{elements:[{symbol:\"line\",color:\"red\"},{symbol:\"square\",color:\"yellow\"},{symbol:\"diamond\",color:\"limegreen\"}],height:150,colorBandWidth:30,fontSize:12,container:\"body\",isContinuous:null,textColor:\"grey\",reverseOrder:!1}}},o.tooltipPanel=function(){var t,e,r,i={container:null,hasTick:!1,fontSize:12,color:\"white\",padding:5},s=\"tooltip-\"+o.tooltipPanel.uid++,l=10,c=function(){var n=(t=i.container.selectAll(\"g.\"+s).data([0])).enter().append(\"g\").classed(s,!0).style({\"pointer-events\":\"none\",display:\"none\"});return r=n.append(\"path\").style({fill:\"white\",\"fill-opacity\":.9}).attr({d:\"M0 0\"}),e=n.append(\"text\").attr({dx:i.padding+l,dy:.3*+i.fontSize}),c};return c.text=function(a){var o=n.hsl(i.color).l,s=o>=.5?\"#aaa\":\"white\",u=o>=.5?\"black\":\"white\",h=a||\"\";e.style({fill:u,\"font-size\":i.fontSize+\"px\"}).text(h);var f=i.padding,p=e.node().getBBox(),d={fill:i.color,stroke:s,\"stroke-width\":\"2px\"},g=p.width+2*f+l,v=p.height+2*f;return r.attr({d:\"M\"+[[l,-v/2],[l,-v/4],[i.hasTick?0:l,0],[l,v/4],[l,v/2],[g,v/2],[g,-v/2]].join(\"L\")+\"Z\"}).style(d),t.attr({transform:\"translate(\"+[l,-v/2+2*f]+\")\"}),t.style({display:\"block\"}),c},c.move=function(e){if(t)return t.attr({transform:\"translate(\"+[e[0],e[1]]+\")\"}).style({display:\"block\"}),c},c.hide=function(){if(t)return t.style({display:\"none\"}),c},c.show=function(){if(t)return t.style({display:\"block\"}),c},c.config=function(t){return a(i,t),c},c},o.tooltipPanel.uid=1,o.adapter={},o.adapter.plotly=function(){var t={convert:function(t,e){var r={};if(t.data&&(r.data=t.data.map(function(t,r){var n=a({},t);return[[n,[\"marker\",\"color\"],[\"color\"]],[n,[\"marker\",\"opacity\"],[\"opacity\"]],[n,[\"marker\",\"line\",\"color\"],[\"strokeColor\"]],[n,[\"marker\",\"line\",\"dash\"],[\"strokeDash\"]],[n,[\"marker\",\"line\",\"width\"],[\"strokeSize\"]],[n,[\"marker\",\"symbol\"],[\"dotType\"]],[n,[\"marker\",\"size\"],[\"dotSize\"]],[n,[\"marker\",\"barWidth\"],[\"barWidth\"]],[n,[\"line\",\"interpolation\"],[\"lineInterpolation\"]],[n,[\"showlegend\"],[\"visibleInLegend\"]]].forEach(function(t,r){o.util.translator.apply(null,t.concat(e))}),e||delete n.marker,e&&delete n.groupId,e?(\"LinePlot\"===n.geometry?(n.type=\"scatter\",!0===n.dotVisible?(delete n.dotVisible,n.mode=\"lines+markers\"):n.mode=\"lines\"):\"DotPlot\"===n.geometry?(n.type=\"scatter\",n.mode=\"markers\"):\"AreaChart\"===n.geometry?n.type=\"area\":\"BarChart\"===n.geometry&&(n.type=\"bar\"),delete n.geometry):(\"scatter\"===n.type?\"lines\"===n.mode?n.geometry=\"LinePlot\":\"markers\"===n.mode?n.geometry=\"DotPlot\":\"lines+markers\"===n.mode&&(n.geometry=\"LinePlot\",n.dotVisible=!0):\"area\"===n.type?n.geometry=\"AreaChart\":\"bar\"===n.type&&(n.geometry=\"BarChart\"),delete n.mode,delete n.type),n}),!e&&t.layout&&\"stack\"===t.layout.barmode)){var i=o.util.duplicates(r.data.map(function(t,e){return t.geometry}));r.data.forEach(function(t,e){var n=i.indexOf(t.geometry);-1!=n&&(r.data[e].groupId=n)})}if(t.layout){var s=a({},t.layout);if([[s,[\"plot_bgcolor\"],[\"backgroundColor\"]],[s,[\"showlegend\"],[\"showLegend\"]],[s,[\"radialaxis\"],[\"radialAxis\"]],[s,[\"angularaxis\"],[\"angularAxis\"]],[s.angularaxis,[\"showline\"],[\"gridLinesVisible\"]],[s.angularaxis,[\"showticklabels\"],[\"labelsVisible\"]],[s.angularaxis,[\"nticks\"],[\"ticksCount\"]],[s.angularaxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.angularaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.angularaxis,[\"range\"],[\"domain\"]],[s.angularaxis,[\"endpadding\"],[\"endPadding\"]],[s.radialaxis,[\"showline\"],[\"gridLinesVisible\"]],[s.radialaxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.radialaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.radialaxis,[\"range\"],[\"domain\"]],[s.angularAxis,[\"showline\"],[\"gridLinesVisible\"]],[s.angularAxis,[\"showticklabels\"],[\"labelsVisible\"]],[s.angularAxis,[\"nticks\"],[\"ticksCount\"]],[s.angularAxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.angularAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.angularAxis,[\"range\"],[\"domain\"]],[s.angularAxis,[\"endpadding\"],[\"endPadding\"]],[s.radialAxis,[\"showline\"],[\"gridLinesVisible\"]],[s.radialAxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.radialAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.radialAxis,[\"range\"],[\"domain\"]],[s.font,[\"outlinecolor\"],[\"outlineColor\"]],[s.legend,[\"traceorder\"],[\"reverseOrder\"]],[s,[\"labeloffset\"],[\"labelOffset\"]],[s,[\"defaultcolorrange\"],[\"defaultColorRange\"]]].forEach(function(t,r){o.util.translator.apply(null,t.concat(e))}),e?(\"undefined\"!=typeof s.tickLength&&(s.angularaxis.ticklen=s.tickLength,delete s.tickLength),s.tickColor&&(s.angularaxis.tickcolor=s.tickColor,delete s.tickColor)):(s.angularAxis&&\"undefined\"!=typeof s.angularAxis.ticklen&&(s.tickLength=s.angularAxis.ticklen),s.angularAxis&&\"undefined\"!=typeof s.angularAxis.tickcolor&&(s.tickColor=s.angularAxis.tickcolor)),s.legend&&\"boolean\"!=typeof s.legend.reverseOrder&&(s.legend.reverseOrder=\"normal\"!=s.legend.reverseOrder),s.legend&&\"boolean\"==typeof s.legend.traceorder&&(s.legend.traceorder=s.legend.traceorder?\"reversed\":\"normal\",delete s.legend.reverseOrder),s.margin&&\"undefined\"!=typeof s.margin.t){var l=[\"t\",\"r\",\"b\",\"l\",\"pad\"],c=[\"top\",\"right\",\"bottom\",\"left\",\"pad\"],u={};n.entries(s.margin).forEach(function(t,e){u[c[l.indexOf(t.key)]]=t.value}),s.margin=u}e&&(delete s.needsEndSpacing,delete s.minorTickColor,delete s.minorTicks,delete s.angularaxis.ticksCount,delete s.angularaxis.ticksCount,delete s.angularaxis.ticksStep,delete s.angularaxis.rewriteTicks,delete s.angularaxis.nticks,delete s.radialaxis.ticksCount,delete s.radialaxis.ticksCount,delete s.radialaxis.ticksStep,delete s.radialaxis.rewriteTicks,delete s.radialaxis.nticks),r.layout=s}return r}};return t}},{\"../../../constants/alignment\":686,\"../../../lib\":717,d3:165}],836:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../../lib\"),i=t(\"../../../components/color\"),o=t(\"./micropolar\"),s=t(\"./undo_manager\"),l=a.extendDeepAll,c=e.exports={};c.framework=function(t){var e,r,a,i,u,h=new s;function f(r,s){return s&&(u=s),n.select(n.select(u).node().parentNode).selectAll(\".svg-container>*:not(.chart-root)\").remove(),e=e?l(e,r):r,a||(a=o.Axis()),i=o.adapter.plotly().convert(e),a.config(i).render(u),t.data=e.data,t.layout=e.layout,c.fillLayout(t),e}return f.isPolar=!0,f.svg=function(){return a.svg()},f.getConfig=function(){return e},f.getLiveConfig=function(){return o.adapter.plotly().convert(a.getLiveConfig(),!0)},f.getLiveScales=function(){return{t:a.angularScale(),r:a.radialScale()}},f.setUndoPoint=function(){var t,n,a=this,i=o.util.cloneJson(e);t=i,n=r,h.add({undo:function(){n&&a(n)},redo:function(){a(t)}}),r=o.util.cloneJson(i)},f.undo=function(){h.undo()},f.redo=function(){h.redo()},f},c.fillLayout=function(t){var e=n.select(t).selectAll(\".plot-container\"),r=e.selectAll(\".svg-container\"),a=t.framework&&t.framework.svg&&t.framework.svg(),o={width:800,height:600,paper_bgcolor:i.background,_container:e,_paperdiv:r,_paper:a};t._fullLayout=l(o,t.layout)}},{\"../../../components/color\":592,\"../../../lib\":717,\"./micropolar\":835,\"./undo_manager\":837,d3:165}],837:[function(t,e,r){\"use strict\";e.exports=function(){var t,e=[],r=-1,n=!1;function a(t,e){return t?(n=!0,t[e](),n=!1,this):this}return{add:function(t){return n?this:(e.splice(r+1,e.length-r),e.push(t),r=e.length-1,this)},setCallback:function(e){t=e},undo:function(){var n=e[r];return n?(a(n,\"undo\"),r-=1,t&&t(n.undo),this):this},redo:function(){var n=e[r+1];return n?(a(n,\"redo\"),r+=1,t&&t(n.redo),this):this},clear:function(){e=[],r=-1},hasUndo:function(){return-1!==r},hasRedo:function(){return r<e.length-1},getCommands:function(){return e},getPreviousCommand:function(){return e[r-1]},getIndex:function(){return r}}}},{}],838:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"tinycolor2\"),i=t(\"../../registry\"),o=t(\"../../lib\"),s=t(\"../../components/color\"),l=t(\"../../components/drawing\"),c=t(\"../plots\"),u=t(\"../../plots/cartesian/axes\"),h=t(\"../cartesian/set_convert\"),f=t(\"./set_convert\"),p=t(\"../cartesian/autorange\").doAutoRange,d=t(\"../cartesian/dragbox\"),g=t(\"../../components/dragelement\"),v=t(\"../../components/fx\"),m=t(\"../../components/titles\"),y=t(\"../cartesian/select\").prepSelect,x=t(\"../cartesian/select\").selectOnClick,b=t(\"../cartesian/select\").clearSelect,_=t(\"../../lib/setcursor\"),w=t(\"../../lib/clear_gl_canvases\"),k=t(\"../../plot_api/subroutines\").redrawReglTraces,T=t(\"../../constants/alignment\").MID_SHIFT,M=t(\"./constants\"),A=t(\"./helpers\"),S=o._,E=o.mod,L=o.deg2rad,C=o.rad2deg;function P(t,e){this.id=e,this.gd=t,this._hasClipOnAxisFalse=null,this.vangles=null,this.radialAxisAngle=null,this.traceHash={},this.layers={},this.clipPaths={},this.clipIds={},this.viewInitial={};var r=t._fullLayout,n=\"clip\"+r._uid+e;this.clipIds.forTraces=n+\"-for-traces\",this.clipPaths.forTraces=r._clips.append(\"clipPath\").attr(\"id\",this.clipIds.forTraces),this.clipPaths.forTraces.append(\"path\"),this.framework=r._polarlayer.append(\"g\").attr(\"class\",e),this.radialTickLayout=null,this.angularTickLayout=null}var O=P.prototype;function z(t){var e=t.ticks+String(t.ticklen)+String(t.showticklabels);return\"side\"in t&&(e+=t.side),e}function I(t,e){return e[o.findIndexOfMin(e,function(e){return o.angleDist(t,e)})]}function D(t,e,r){return e?(t.attr(\"display\",null),t.attr(r)):t&&t.attr(\"display\",\"none\"),t}function R(t,e){return\"translate(\"+t+\",\"+e+\")\"}function F(t){return\"rotate(\"+t+\")\"}e.exports=function(t,e){return new P(t,e)},O.plot=function(t,e){var r=e[this.id];this._hasClipOnAxisFalse=!1;for(var n=0;n<t.length;n++){if(!1===t[n][0].trace.cliponaxis){this._hasClipOnAxisFalse=!0;break}}this.updateLayers(e,r),this.updateLayout(e,r),c.generalUpdatePerTraceModule(this.gd,this,t,r),this.updateFx(e,r)},O.updateLayers=function(t,e){var r=this.layers,a=e.radialaxis,i=e.angularaxis,o=M.layerNames,s=o.indexOf(\"frontplot\"),l=o.slice(0,s),c=\"below traces\"===i.layer,u=\"below traces\"===a.layer;c&&l.push(\"angular-line\"),u&&l.push(\"radial-line\"),c&&l.push(\"angular-axis\"),u&&l.push(\"radial-axis\"),l.push(\"frontplot\"),c||l.push(\"angular-line\"),u||l.push(\"radial-line\"),c||l.push(\"angular-axis\"),u||l.push(\"radial-axis\");var h=this.framework.selectAll(\".polarsublayer\").data(l,String);h.enter().append(\"g\").attr(\"class\",function(t){return\"polarsublayer \"+t}).each(function(t){var e=r[t]=n.select(this);switch(t){case\"frontplot\":e.append(\"g\").classed(\"barlayer\",!0),e.append(\"g\").classed(\"scatterlayer\",!0);break;case\"backplot\":e.append(\"g\").classed(\"maplayer\",!0);break;case\"plotbg\":r.bg=e.append(\"path\");break;case\"radial-grid\":case\"angular-grid\":e.style(\"fill\",\"none\");break;case\"radial-line\":e.append(\"line\").style(\"fill\",\"none\");break;case\"angular-line\":e.append(\"path\").style(\"fill\",\"none\")}}),h.order()},O.updateLayout=function(t,e){var r=this.layers,n=t._size,a=e.radialaxis,i=e.angularaxis,o=e.domain.x,c=e.domain.y;this.xOffset=n.l+n.w*o[0],this.yOffset=n.t+n.h*(1-c[1]);var u=this.xLength=n.w*(o[1]-o[0]),h=this.yLength=n.h*(c[1]-c[0]),f=e.sector;this.sectorInRad=f.map(L);var p,d,g,v,m,y=this.sectorBBox=function(t){var e,r,n,a,i=t[0],o=t[1]-i,s=E(i,360),l=s+o,c=Math.cos(L(s)),u=Math.sin(L(s)),h=Math.cos(L(l)),f=Math.sin(L(l));a=s<=90&&l>=90||s>90&&l>=450?1:u<=0&&f<=0?0:Math.max(u,f);e=s<=180&&l>=180||s>180&&l>=540?-1:c>=0&&h>=0?0:Math.min(c,h);r=s<=270&&l>=270||s>270&&l>=630?-1:u>=0&&f>=0?0:Math.min(u,f);n=l>=360?1:c<=0&&h<=0?0:Math.max(c,h);return[e,r,n,a]}(f),x=y[2]-y[0],b=y[3]-y[1],_=h/u,w=Math.abs(b/x);_>w?(p=u,m=(h-(d=u*w))/n.h/2,g=[o[0],o[1]],v=[c[0]+m,c[1]-m]):(d=h,m=(u-(p=h/w))/n.w/2,g=[o[0]+m,o[1]-m],v=[c[0],c[1]]),this.xLength2=p,this.yLength2=d,this.xDomain2=g,this.yDomain2=v;var k=this.xOffset2=n.l+n.w*g[0],T=this.yOffset2=n.t+n.h*(1-v[1]),M=this.radius=p/x,A=this.innerRadius=e.hole*M,S=this.cx=k-M*y[0],C=this.cy=T+M*y[3],P=this.cxx=S-k,O=this.cyy=C-T;this.radialAxis=this.mockAxis(t,e,a,{_id:\"x\",side:{counterclockwise:\"top\",clockwise:\"bottom\"}[a.side],domain:[A/n.w,M/n.w]}),this.angularAxis=this.mockAxis(t,e,i,{side:\"right\",domain:[0,Math.PI],autorange:!1}),this.doAutoRange(t,e),this.updateAngularAxis(t,e),this.updateRadialAxis(t,e),this.updateRadialAxisTitle(t,e),this.xaxis=this.mockCartesianAxis(t,e,{_id:\"x\",domain:g}),this.yaxis=this.mockCartesianAxis(t,e,{_id:\"y\",domain:v});var z=this.pathSubplot();this.clipPaths.forTraces.select(\"path\").attr(\"d\",z).attr(\"transform\",R(P,O)),r.frontplot.attr(\"transform\",R(k,T)).call(l.setClipUrl,this._hasClipOnAxisFalse?null:this.clipIds.forTraces,this.gd),r.bg.attr(\"d\",z).attr(\"transform\",R(S,C)).call(s.fill,e.bgcolor)},O.mockAxis=function(t,e,r,n){var a=o.extendFlat({},r,n);return f(a,e,t),a},O.mockCartesianAxis=function(t,e,r){var n=this,a=r._id,i=o.extendFlat({type:\"linear\"},r);h(i,t);var s={x:[0,2],y:[1,3]};return i.setRange=function(){var t=n.sectorBBox,r=s[a],o=n.radialAxis._rl,l=(o[1]-o[0])/(1-e.hole);i.range=[t[r[0]]*l,t[r[1]]*l]},i.isPtWithinRange=\"x\"===a?function(t){return n.isPtInside(t)}:function(){return!0},i.setRange(),i.setScale(),i},O.doAutoRange=function(t,e){var r=this.gd,n=this.radialAxis,a=e.radialaxis;n.setScale(),p(r,n);var i=n.range;a.range=i.slice(),a._input.range=i.slice(),n._rl=[n.r2l(i[0],null,\"gregorian\"),n.r2l(i[1],null,\"gregorian\")]},O.updateRadialAxis=function(t,e){var r=this,n=r.gd,a=r.layers,i=r.radius,l=r.innerRadius,c=r.cx,h=r.cy,f=e.radialaxis,p=E(e.sector[0],360),d=r.radialAxis,g=l<i;r.fillViewInitialKey(\"radialaxis.angle\",f.angle),r.fillViewInitialKey(\"radialaxis.range\",d.range.slice()),d.setGeometry(),\"auto\"===d.tickangle&&p>90&&p<=270&&(d.tickangle=180);var v=function(t){return\"translate(\"+(d.l2p(t.x)+l)+\",0)\"},m=z(f);if(r.radialTickLayout!==m&&(a[\"radial-axis\"].selectAll(\".xtick\").remove(),r.radialTickLayout=m),g){d.setScale();var y=u.calcTicks(d),x=u.clipEnds(d,y),b=u.getTickSigns(d)[2];u.drawTicks(n,d,{vals:y,layer:a[\"radial-axis\"],path:u.makeTickPath(d,0,b),transFn:v,crisp:!1}),u.drawGrid(n,d,{vals:x,layer:a[\"radial-grid\"],path:function(t){return r.pathArc(d.r2p(t.x)+l)},transFn:o.noop,crisp:!1}),u.drawLabels(n,d,{vals:y,layer:a[\"radial-axis\"],transFn:v,labelFns:u.makeLabelFns(d,0)})}var _=r.radialAxisAngle=r.vangles?C(I(L(f.angle),r.vangles)):f.angle,w=R(c,h),k=w+F(-_);D(a[\"radial-axis\"],g&&(f.showticklabels||f.ticks),{transform:k}),D(a[\"radial-grid\"],g&&f.showgrid,{transform:w}),D(a[\"radial-line\"].select(\"line\"),g&&f.showline,{x1:l,y1:0,x2:i,y2:0,transform:k}).attr(\"stroke-width\",f.linewidth).call(s.stroke,f.linecolor)},O.updateRadialAxisTitle=function(t,e,r){var n=this.gd,a=this.radius,i=this.cx,o=this.cy,s=e.radialaxis,c=this.id+\"title\",u=void 0!==r?r:this.radialAxisAngle,h=L(u),f=Math.cos(h),p=Math.sin(h),d=0;if(s.title){var g=l.bBox(this.layers[\"radial-axis\"].node()).height,v=s.title.font.size;d=\"counterclockwise\"===s.side?-g-.4*v:g+.8*v}this.layers[\"radial-axis-title\"]=m.draw(n,c,{propContainer:s,propName:this.id+\".radialaxis.title\",placeholder:S(n,\"Click to enter radial axis title\"),attributes:{x:i+a/2*f+d*p,y:o-a/2*p+d*f,\"text-anchor\":\"middle\"},transform:{rotate:-u}})},O.updateAngularAxis=function(t,e){var r=this,n=r.gd,a=r.layers,i=r.radius,l=r.innerRadius,c=r.cx,h=r.cy,f=e.angularaxis,p=r.angularAxis;r.fillViewInitialKey(\"angularaxis.rotation\",f.rotation),p.setGeometry(),p.setScale();var d=function(t){return p.t2g(t.x)};\"linear\"===p.type&&\"radians\"===p.thetaunit&&(p.tick0=C(p.tick0),p.dtick=C(p.dtick));var g=function(t){return R(c+i*Math.cos(t),h-i*Math.sin(t))},v=u.makeLabelFns(p,0).labelStandoff,m={xFn:function(t){var e=d(t);return Math.cos(e)*v},yFn:function(t){var e=d(t),r=Math.sin(e)>0?.2:1;return-Math.sin(e)*(v+t.fontSize*r)+Math.abs(Math.cos(e))*(t.fontSize*T)},anchorFn:function(t){var e=d(t),r=Math.cos(e);return Math.abs(r)<.1?\"middle\":r>0?\"start\":\"end\"},heightFn:function(t,e,r){var n=d(t);return-.5*(1+Math.sin(n))*r}},y=z(f);r.angularTickLayout!==y&&(a[\"angular-axis\"].selectAll(\".\"+p._id+\"tick\").remove(),r.angularTickLayout=y);var x,b=u.calcTicks(p);if(\"linear\"===e.gridshape?(x=b.map(d),o.angleDelta(x[0],x[1])<0&&(x=x.slice().reverse())):x=null,r.vangles=x,\"category\"===p.type&&(b=b.filter(function(t){return o.isAngleInsideSector(d(t),r.sectorInRad)})),p.visible){var _=\"inside\"===p.ticks?-1:1,w=(p.linewidth||1)/2;u.drawTicks(n,p,{vals:b,layer:a[\"angular-axis\"],path:\"M\"+_*w+\",0h\"+_*p.ticklen,transFn:function(t){var e=d(t);return g(e)+F(-C(e))},crisp:!1}),u.drawGrid(n,p,{vals:b,layer:a[\"angular-grid\"],path:function(t){var e=d(t),r=Math.cos(e),n=Math.sin(e);return\"M\"+[c+l*r,h-l*n]+\"L\"+[c+i*r,h-i*n]},transFn:o.noop,crisp:!1}),u.drawLabels(n,p,{vals:b,layer:a[\"angular-axis\"],repositionOnUpdate:!0,transFn:function(t){return g(d(t))},labelFns:m})}D(a[\"angular-line\"].select(\"path\"),f.showline,{d:r.pathSubplot(),transform:R(c,h)}).attr(\"stroke-width\",f.linewidth).call(s.stroke,f.linecolor)},O.updateFx=function(t,e){this.gd._context.staticPlot||(this.updateAngularDrag(t),this.updateRadialDrag(t,e,0),this.updateRadialDrag(t,e,1),this.updateMainDrag(t))},O.updateMainDrag=function(t){var e=this,r=e.gd,o=e.layers,s=t._zoomlayer,l=M.MINZOOM,c=M.OFFEDGE,u=e.radius,h=e.innerRadius,f=e.cx,p=e.cy,m=e.cxx,_=e.cyy,w=e.sectorInRad,k=e.vangles,T=e.radialAxis,S=A.clampTiny,E=A.findXYatLength,L=A.findEnclosingVertexAngles,C=M.cornerHalfWidth,P=M.cornerLen/2,O=d.makeDragger(o,\"path\",\"maindrag\",\"crosshair\");n.select(O).attr(\"d\",e.pathSubplot()).attr(\"transform\",R(f,p));var z,I,D,F,B,N,j,V,U,q={element:O,gd:r,subplot:e.id,plotinfo:{id:e.id,xaxis:e.xaxis,yaxis:e.yaxis},xaxes:[e.xaxis],yaxes:[e.yaxis]};function H(t,e){return Math.sqrt(t*t+e*e)}function G(t,e){return H(t-m,e-_)}function Y(t,e){return Math.atan2(_-e,t-m)}function W(t,e){return[t*Math.cos(e),t*Math.sin(-e)]}function X(t,r){if(0===t)return e.pathSector(2*C);var n=P/t,a=r-n,i=r+n,o=Math.max(0,Math.min(t,u)),s=o-C,l=o+C;return\"M\"+W(s,a)+\"A\"+[s,s]+\" 0,0,0 \"+W(s,i)+\"L\"+W(l,i)+\"A\"+[l,l]+\" 0,0,1 \"+W(l,a)+\"Z\"}function Z(t,r,n){if(0===t)return e.pathSector(2*C);var a,i,o=W(t,r),s=W(t,n),l=S((o[0]+s[0])/2),c=S((o[1]+s[1])/2);if(l&&c){var u=c/l,h=-1/u,f=E(C,u,l,c);a=E(P,h,f[0][0],f[0][1]),i=E(P,h,f[1][0],f[1][1])}else{var p,d;c?(p=P,d=C):(p=C,d=P),a=[[l-p,c-d],[l+p,c-d]],i=[[l-p,c+d],[l+p,c+d]]}return\"M\"+a.join(\"L\")+\"L\"+i.reverse().join(\"L\")+\"Z\"}function J(t,e){return e=Math.max(Math.min(e,u),h),t<c?t=0:u-t<c?t=u:e<c?e=0:u-e<c&&(e=u),Math.abs(e-t)>l?(t<e?(D=t,F=e):(D=e,F=t),!0):(D=null,F=null,!1)}function K(t,e){t=t||B,e=e||\"M0,0Z\",V.attr(\"d\",t),U.attr(\"d\",e),d.transitionZoombox(V,U,N,j),N=!0;var n={};rt(n),r.emit(\"plotly_relayouting\",n)}function Q(t,r){var n,a,i=z+t,o=I+r,s=G(z,I),l=Math.min(G(i,o),u),c=Y(z,I);J(s,l)&&(n=B+e.pathSector(F),D&&(n+=e.pathSector(D)),a=X(D,c)+X(F,c)),K(n,a)}function $(t,e,r,n){var a=A.findIntersectionXY(r,n,r,[t-m,_-e]);return H(a[0],a[1])}function tt(t,r){var n,a,i=z+t,o=I+r,s=Y(z,I),l=Y(i,o),c=L(s,k),h=L(l,k);J($(z,I,c[0],c[1]),Math.min($(i,o,h[0],h[1]),u))&&(n=B+e.pathSector(F),D&&(n+=e.pathSector(D)),a=[Z(D,c[0],c[1]),Z(F,c[0],c[1])].join(\" \")),K(n,a)}function et(){if(d.removeZoombox(r),null!==D&&null!==F){var t={};rt(t),d.showDoubleClickNotifier(r),i.call(\"_guiRelayout\",r,t)}}function rt(t){var r=T._rl,n=(r[1]-r[0])/(1-h/u)/u,a=[r[0]+(D-h)*n,r[0]+(F-h)*n];t[e.id+\".radialaxis.range\"]=a}function nt(t,n){var a=r._fullLayout.clickmode;if(d.removeZoombox(r),2===t){var o={};for(var s in e.viewInitial)o[e.id+\".\"+s]=e.viewInitial[s];r.emit(\"plotly_doubleclick\",null),i.call(\"_guiRelayout\",r,o)}a.indexOf(\"select\")>-1&&1===t&&x(n,r,[e.xaxis],[e.yaxis],e.id,q),a.indexOf(\"event\")>-1&&v.click(r,n,e.id)}q.prepFn=function(t,n,i){var o=r._fullLayout.dragmode,l=O.getBoundingClientRect();if(z=n-l.left,I=i-l.top,k){var c=A.findPolygonOffset(u,w[0],w[1],k);z+=m+c[0],I+=_+c[1]}switch(o){case\"zoom\":q.moveFn=k?tt:Q,q.clickFn=nt,q.doneFn=et,function(){D=null,F=null,B=e.pathSubplot(),N=!1;var t=r._fullLayout[e.id];j=a(t.bgcolor).getLuminance(),(V=d.makeZoombox(s,j,f,p,B)).attr(\"fill-rule\",\"evenodd\"),U=d.makeCorners(s,f,p),b(r)}();break;case\"select\":case\"lasso\":y(t,n,i,q,o)}},O.onmousemove=function(t){v.hover(r,t,e.id),r._fullLayout._lasthover=O,r._fullLayout._hoversubplot=e.id},O.onmouseout=function(t){r._dragging||g.unhover(r,t)},g.init(q)},O.updateRadialDrag=function(t,e,r){var a=this,s=a.gd,l=a.layers,c=a.radius,u=a.innerRadius,h=a.cx,f=a.cy,p=a.radialAxis,v=M.radialDragBoxSize,m=v/2;if(p.visible){var y,x,_,T=L(a.radialAxisAngle),A=p._rl,S=A[0],E=A[1],P=A[r],O=.75*(A[1]-A[0])/(1-e.hole)/c;r?(y=h+(c+m)*Math.cos(T),x=f-(c+m)*Math.sin(T),_=\"radialdrag\"):(y=h+(u-m)*Math.cos(T),x=f-(u-m)*Math.sin(T),_=\"radialdrag-inner\");var z,B,N,j=d.makeRectDragger(l,_,\"crosshair\",-m,-m,v,v),V={element:j,gd:s};D(n.select(j),p.visible&&u<c,{transform:R(y,x)}),V.prepFn=function(){z=null,B=null,N=null,V.moveFn=U,V.doneFn=q,b(s)},V.clampFn=function(t,e){return Math.sqrt(t*t+e*e)<M.MINDRAG&&(t=0,e=0),[t,e]},g.init(V)}function U(t,e){if(z)z(t,e);else{var n=[t,-e],i=[Math.cos(T),Math.sin(T)],l=Math.abs(o.dot(n,i)/Math.sqrt(o.dot(n,n)));isNaN(l)||(z=l<.5?H:G)}var c={};!function(t){null!==B?t[a.id+\".radialaxis.angle\"]=B:null!==N&&(t[a.id+\".radialaxis.range[\"+r+\"]\"]=N)}(c),s.emit(\"plotly_relayouting\",c)}function q(){null!==B?i.call(\"_guiRelayout\",s,a.id+\".radialaxis.angle\",B):null!==N&&i.call(\"_guiRelayout\",s,a.id+\".radialaxis.range[\"+r+\"]\",N)}function H(t,e){if(0!==r){var n=y+t,i=x+e;B=Math.atan2(f-i,n-h),a.vangles&&(B=I(B,a.vangles)),B=C(B);var o=R(h,f)+F(-B);l[\"radial-axis\"].attr(\"transform\",o),l[\"radial-line\"].select(\"line\").attr(\"transform\",o);var s=a.gd._fullLayout,c=s[a.id];a.updateRadialAxisTitle(s,c,B)}}function G(t,e){var n=o.dot([t,-e],[Math.cos(T),Math.sin(T)]);if(N=P-O*n,O>0==(r?N>S:N<E)){var l=s._fullLayout,c=l[a.id];p.range[r]=N,p._rl[r]=N,a.updateRadialAxis(l,c),a.xaxis.setRange(),a.xaxis.setScale(),a.yaxis.setRange(),a.yaxis.setScale();var u=!1;for(var h in a.traceHash){var f=a.traceHash[h],d=o.filterVisible(f);f[0][0].trace._module.plot(s,a,d,c),i.traceIs(h,\"gl\")&&d.length&&(u=!0)}u&&(w(s),k(s))}else N=null}},O.updateAngularDrag=function(t){var e=this,r=e.gd,a=e.layers,s=e.radius,c=e.angularAxis,u=e.cx,h=e.cy,f=e.cxx,p=e.cyy,v=M.angularDragBoxSize,m=d.makeDragger(a,\"path\",\"angulardrag\",\"move\"),y={element:m,gd:r};function x(t,e){return Math.atan2(p+v-e,t-f-v)}n.select(m).attr(\"d\",e.pathAnnulus(s,s+v)).attr(\"transform\",R(u,h)).call(_,\"move\");var T,A,S,E,L,P,O=a.frontplot.select(\".scatterlayer\").selectAll(\".trace\"),z=O.selectAll(\".point\"),I=O.selectAll(\".textpoint\");function D(t,s){var d=e.gd._fullLayout,g=d[e.id],v=x(T+t,A+s),m=C(v-P);if(E=S+m,a.frontplot.attr(\"transform\",R(e.xOffset2,e.yOffset2)+F([-m,f,p])),e.vangles){L=e.radialAxisAngle+m;var y=R(u,h)+F(-m),b=R(u,h)+F(-L);a.bg.attr(\"transform\",y),a[\"radial-grid\"].attr(\"transform\",y),a[\"radial-axis\"].attr(\"transform\",b),a[\"radial-line\"].select(\"line\").attr(\"transform\",b),e.updateRadialAxisTitle(d,g,L)}else e.clipPaths.forTraces.select(\"path\").attr(\"transform\",R(f,p)+F(m));z.each(function(){var t=n.select(this),e=l.getTranslate(t);t.attr(\"transform\",R(e.x,e.y)+F([m]))}),I.each(function(){var t=n.select(this),e=t.select(\"text\"),r=l.getTranslate(t);t.attr(\"transform\",F([m,e.attr(\"x\"),e.attr(\"y\")])+R(r.x,r.y))}),c.rotation=o.modHalf(E,360),e.updateAngularAxis(d,g),e._hasClipOnAxisFalse&&!o.isFullCircle(e.sectorInRad)&&O.call(l.hideOutsideRangePoints,e);var _=!1;for(var M in e.traceHash)if(i.traceIs(M,\"gl\")){var D=e.traceHash[M],N=o.filterVisible(D);D[0][0].trace._module.plot(r,e,N,g),N.length&&(_=!0)}_&&(w(r),k(r));var j={};B(j),r.emit(\"plotly_relayouting\",j)}function B(t){t[e.id+\".angularaxis.rotation\"]=E,e.vangles&&(t[e.id+\".radialaxis.angle\"]=L)}function N(){I.select(\"text\").attr(\"transform\",null);var t={};B(t),i.call(\"_guiRelayout\",r,t)}y.prepFn=function(n,a,i){var o=t[e.id];S=o.angularaxis.rotation;var s=m.getBoundingClientRect();T=a-s.left,A=i-s.top,P=x(T,A),y.moveFn=D,y.doneFn=N,b(r)},e.vangles&&!o.isFullCircle(e.sectorInRad)&&(y.prepFn=o.noop,_(n.select(m),null)),g.init(y)},O.isPtInside=function(t){var e=this.sectorInRad,r=this.vangles,n=this.angularAxis.c2g(t.theta),a=this.radialAxis,i=a.c2l(t.r),s=a._rl;return(r?A.isPtInsidePolygon:o.isPtInsideSector)(i,n,s,e,r)},O.pathArc=function(t){var e=this.sectorInRad,r=this.vangles;return(r?A.pathPolygon:o.pathArc)(t,e[0],e[1],r)},O.pathSector=function(t){var e=this.sectorInRad,r=this.vangles;return(r?A.pathPolygon:o.pathSector)(t,e[0],e[1],r)},O.pathAnnulus=function(t,e){var r=this.sectorInRad,n=this.vangles;return(n?A.pathPolygonAnnulus:o.pathAnnulus)(t,e,r[0],r[1],n)},O.pathSubplot=function(){var t=this.innerRadius,e=this.radius;return t?this.pathAnnulus(t,e):this.pathSector(e)},O.fillViewInitialKey=function(t,e){t in this.viewInitial||(this.viewInitial[t]=e)}},{\"../../components/color\":592,\"../../components/dragelement\":610,\"../../components/drawing\":613,\"../../components/fx\":630,\"../../components/titles\":679,\"../../constants/alignment\":686,\"../../lib\":717,\"../../lib/clear_gl_canvases\":702,\"../../lib/setcursor\":737,\"../../plot_api/subroutines\":756,\"../../plots/cartesian/axes\":765,\"../../registry\":846,\"../cartesian/autorange\":764,\"../cartesian/dragbox\":773,\"../cartesian/select\":782,\"../cartesian/set_convert\":783,\"../plots\":826,\"./constants\":827,\"./helpers\":828,\"./set_convert\":839,d3:165,tinycolor2:536}],839:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../cartesian/set_convert\"),i=n.deg2rad,o=n.rad2deg;e.exports=function(t,e,r){switch(a(t,r),t._id){case\"x\":case\"radialaxis\":!function(t,e){var r=e._subplot;t.setGeometry=function(){var e=t._rl[0],n=t._rl[1],a=r.innerRadius,i=(r.radius-a)/(n-e),o=a/i,s=e>n?function(t){return t<=0}:function(t){return t>=0};t.c2g=function(r){var n=t.c2l(r)-e;return(s(n)?n:0)+o},t.g2c=function(r){return t.l2c(r+e-o)},t.g2p=function(t){return t*i},t.c2p=function(e){return t.g2p(t.c2g(e))}}}(t,e);break;case\"angularaxis\":!function(t,e){var r=t.type;if(\"linear\"===r){var a=t.d2c,s=t.c2d;t.d2c=function(t,e){return function(t,e){return\"degrees\"===e?i(t):t}(a(t),e)},t.c2d=function(t,e){return s(function(t,e){return\"degrees\"===e?o(t):t}(t,e))}}t.makeCalcdata=function(e,a){var i,o,s=e[a],l=e._length,c=function(r){return t.d2c(r,e.thetaunit)};if(s){if(n.isTypedArray(s)&&\"linear\"===r){if(l===s.length)return s;if(s.subarray)return s.subarray(0,l)}for(i=new Array(l),o=0;o<l;o++)i[o]=c(s[o])}else{var u=a+\"0\",h=\"d\"+a,f=u in e?c(e[u]):0,p=e[h]?c(e[h]):(t.period||2*Math.PI)/l;for(i=new Array(l),o=0;o<l;o++)i[o]=f+o*p}return i},t.setGeometry=function(){var a,s,l,c,u=e.sector,h=u.map(i),f={clockwise:-1,counterclockwise:1}[t.direction],p=i(t.rotation),d=function(t){return f*t+p},g=function(t){return(t-p)/f};switch(r){case\"linear\":s=a=n.identity,c=i,l=o,t.range=n.isFullCircle(h)?[u[0],u[0]+360]:h.map(g).map(o);break;case\"category\":var v=t._categories.length,m=t.period?Math.max(t.period,v):v;0===m&&(m=1),s=c=function(t){return 2*t*Math.PI/m},a=l=function(t){return t*m/Math.PI/2},t.range=[0,m]}t.c2g=function(t){return d(s(t))},t.g2c=function(t){return a(g(t))},t.t2g=function(t){return d(c(t))},t.g2t=function(t){return l(g(t))}}}(t,e)}}},{\"../../lib\":717,\"../cartesian/set_convert\":783}],840:[function(t,e,r){\"use strict\";var n=t(\"../lib\"),a=t(\"../plot_api/plot_template\"),i=t(\"./domain\").defaults;e.exports=function(t,e,r,o){var s,l,c=o.type,u=o.attributes,h=o.handleDefaults,f=o.partition||\"x\",p=e._subplots[c],d=p.length,g=d&&p[0].replace(/\\d+$/,\"\");function v(t,e){return n.coerce(s,l,u,t,e)}for(var m=0;m<d;m++){var y=p[m];s=t[y]?t[y]:t[y]={},l=a.newContainer(e,y,g),v(\"uirevision\",e.uirevision);var x={};x[f]=[m/d,(m+1)/d],i(l,e,v,x),o.id=y,h(s,l,v,o)}}},{\"../lib\":717,\"../plot_api/plot_template\":755,\"./domain\":790}],841:[function(t,e,r){\"use strict\";['Variables are inserted using %{variable}, for example \"y: %{y}\".','Numbers are formatted using d3-format\\'s syntax %{variable:d3-format}, for example \"Price: %{y:$.2f}\".',t(\"../constants/docs\").FORMAT_LINK,\"for details on the formatting syntax.\",'Dates are formatted using d3-time-format\\'s syntax %{variable|d3-time-format}, for example \"Day: %{2019-01-01|%A}\".',t(\"../constants/docs\").DATE_FORMAT_LINK,\"for details on the date formatting syntax.\"].join(\" \");function n(t){var e=t.description?\" \"+t.description:\"\",r=t.keys||[];if(r.length>0){for(var n=[],a=0;a<r.length;a++)n[a]=\"`\"+r[a]+\"`\";e+=\"Finally, the template string has access to \",e=1===r.length?\"variable \"+n[0]:\"variables \"+n.slice(0,-1).join(\", \")+\" and \"+n.slice(-1)+\".\"}return e}r.hovertemplateAttrs=function(t,e){t=t||{};n(e=e||{});var r={valType:\"string\",dflt:\"\",editType:t.editType||\"none\"};return!1!==t.arrayOk&&(r.arrayOk=!0),r},r.texttemplateAttrs=function(t,e){t=t||{};n(e=e||{});var r={valType:\"string\",dflt:\"\",editType:t.editType||\"calc\"};return!1!==t.arrayOk&&(r.arrayOk=!0),r}},{\"../constants/docs\":688}],842:[function(t,e,r){\"use strict\";var n=t(\"./ternary\"),a=t(\"../../plots/get_data\").getSubplotCalcData,i=t(\"../../lib\").counterRegex;r.name=\"ternary\";var o=r.attr=\"subplot\";r.idRoot=\"ternary\",r.idRegex=r.attrRegex=i(\"ternary\"),(r.attributes={})[o]={valType:\"subplotid\",dflt:\"ternary\",editType:\"calc\"},r.layoutAttributes=t(\"./layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout_defaults\"),r.plot=function(t){for(var e=t._fullLayout,r=t.calcdata,i=e._subplots.ternary,o=0;o<i.length;o++){var s=i[o],l=a(r,\"ternary\",s),c=e[s]._subplot;c||(c=new n({id:s,graphDiv:t,container:e._ternarylayer.node()},e),e[s]._subplot=c),c.plot(l,e,t._promises)}},r.clean=function(t,e,r,n){for(var a=n._subplots.ternary||[],i=0;i<a.length;i++){var o=a[i],s=n[o]._subplot;!e[o]&&s&&(s.plotContainer.remove(),s.clipDef.remove(),s.clipDefRelative.remove(),s.layers[\"a-title\"].remove(),s.layers[\"b-title\"].remove(),s.layers[\"c-title\"].remove())}}},{\"../../lib\":717,\"../../plots/get_data\":800,\"./layout_attributes\":843,\"./layout_defaults\":844,\"./ternary\":845}],843:[function(t,e,r){\"use strict\";var n=t(\"../../components/color/attributes\"),a=t(\"../domain\").attributes,i=t(\"../cartesian/layout_attributes\"),o=t(\"../../plot_api/edit_types\").overrideAll,s=t(\"../../lib/extend\").extendFlat,l={title:{text:i.title.text,font:i.title.font},color:i.color,tickmode:i.tickmode,nticks:s({},i.nticks,{dflt:6,min:1}),tick0:i.tick0,dtick:i.dtick,tickvals:i.tickvals,ticktext:i.ticktext,ticks:i.ticks,ticklen:i.ticklen,tickwidth:i.tickwidth,tickcolor:i.tickcolor,showticklabels:i.showticklabels,showtickprefix:i.showtickprefix,tickprefix:i.tickprefix,showticksuffix:i.showticksuffix,ticksuffix:i.ticksuffix,showexponent:i.showexponent,exponentformat:i.exponentformat,separatethousands:i.separatethousands,tickfont:i.tickfont,tickangle:i.tickangle,tickformat:i.tickformat,tickformatstops:i.tickformatstops,hoverformat:i.hoverformat,showline:s({},i.showline,{dflt:!0}),linecolor:i.linecolor,linewidth:i.linewidth,showgrid:s({},i.showgrid,{dflt:!0}),gridcolor:i.gridcolor,gridwidth:i.gridwidth,layer:i.layer,min:{valType:\"number\",dflt:0,min:0},_deprecated:{title:i._deprecated.title,titlefont:i._deprecated.titlefont}},c=e.exports=o({domain:a({name:\"ternary\"}),bgcolor:{valType:\"color\",dflt:n.background},sum:{valType:\"number\",dflt:1,min:0},aaxis:l,baxis:l,caxis:l},\"plot\",\"from-root\");c.uirevision={valType:\"any\",editType:\"none\"},c.aaxis.uirevision=c.baxis.uirevision=c.caxis.uirevision={valType:\"any\",editType:\"none\"}},{\"../../components/color/attributes\":591,\"../../lib/extend\":708,\"../../plot_api/edit_types\":748,\"../cartesian/layout_attributes\":777,\"../domain\":790}],844:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),a=t(\"../../plot_api/plot_template\"),i=t(\"../../lib\"),o=t(\"../subplot_defaults\"),s=t(\"../cartesian/tick_label_defaults\"),l=t(\"../cartesian/tick_mark_defaults\"),c=t(\"../cartesian/tick_value_defaults\"),u=t(\"../cartesian/line_grid_defaults\"),h=t(\"./layout_attributes\"),f=[\"aaxis\",\"baxis\",\"caxis\"];function p(t,e,r,i){var o,s,l,c=r(\"bgcolor\"),u=r(\"sum\");i.bgColor=n.combine(c,i.paper_bgcolor);for(var h=0;h<f.length;h++)s=t[o=f[h]]||{},(l=a.newContainer(e,o))._name=o,d(s,l,i,e);var p=e.aaxis,g=e.baxis,v=e.caxis;p.min+g.min+v.min>=u&&(p.min=0,g.min=0,v.min=0,t.aaxis&&delete t.aaxis.min,t.baxis&&delete t.baxis.min,t.caxis&&delete t.caxis.min)}function d(t,e,r,n){var a=h[e._name];function o(r,n){return i.coerce(t,e,a,r,n)}o(\"uirevision\",n.uirevision),e.type=\"linear\";var f=o(\"color\"),p=f!==a.color.dflt?f:r.font.color,d=e._name.charAt(0).toUpperCase(),g=\"Component \"+d,v=o(\"title.text\",g);e._hovertitle=v===g?v:d,i.coerceFont(o,\"title.font\",{family:r.font.family,size:Math.round(1.2*r.font.size),color:p}),o(\"min\"),c(t,e,o,\"linear\"),s(t,e,o,\"linear\",{}),l(t,e,o,{outerTicks:!0}),o(\"showticklabels\")&&(i.coerceFont(o,\"tickfont\",{family:r.font.family,size:r.font.size,color:p}),o(\"tickangle\"),o(\"tickformat\")),u(t,e,o,{dfltColor:f,bgColor:r.bgColor,blend:60,showLine:!0,showGrid:!0,noZeroLine:!0,attributes:a}),o(\"hoverformat\"),o(\"layer\")}e.exports=function(t,e,r){o(t,e,r,{type:\"ternary\",attributes:h,handleDefaults:p,font:e.font,paper_bgcolor:e.paper_bgcolor})}},{\"../../components/color\":592,\"../../lib\":717,\"../../plot_api/plot_template\":755,\"../cartesian/line_grid_defaults\":779,\"../cartesian/tick_label_defaults\":784,\"../cartesian/tick_mark_defaults\":785,\"../cartesian/tick_value_defaults\":786,\"../subplot_defaults\":840,\"./layout_attributes\":843}],845:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"tinycolor2\"),i=t(\"../../registry\"),o=t(\"../../lib\"),s=o._,l=t(\"../../components/color\"),c=t(\"../../components/drawing\"),u=t(\"../cartesian/set_convert\"),h=t(\"../../lib/extend\").extendFlat,f=t(\"../plots\"),p=t(\"../cartesian/axes\"),d=t(\"../../components/dragelement\"),g=t(\"../../components/fx\"),v=t(\"../../components/titles\"),m=t(\"../cartesian/select\").prepSelect,y=t(\"../cartesian/select\").selectOnClick,x=t(\"../cartesian/select\").clearSelect,b=t(\"../cartesian/constants\");function _(t,e){this.id=t.id,this.graphDiv=t.graphDiv,this.init(e),this.makeFramework(e),this.aTickLayout=null,this.bTickLayout=null,this.cTickLayout=null}e.exports=_;var w=_.prototype;w.init=function(t){this.container=t._ternarylayer,this.defs=t._defs,this.layoutId=t._uid,this.traceHash={},this.layers={}},w.plot=function(t,e){var r=e[this.id],n=e._size;this._hasClipOnAxisFalse=!1;for(var a=0;a<t.length;a++){if(!1===t[a][0].trace.cliponaxis){this._hasClipOnAxisFalse=!0;break}}this.updateLayers(r),this.adjustLayout(r,n),f.generalUpdatePerTraceModule(this.graphDiv,this,t,r),this.layers.plotbg.select(\"path\").call(l.fill,r.bgcolor)},w.makeFramework=function(t){var e=this.graphDiv,r=t[this.id],n=this.clipId=\"clip\"+this.layoutId+this.id,a=this.clipIdRelative=\"clip-relative\"+this.layoutId+this.id;this.clipDef=o.ensureSingleById(t._clips,\"clipPath\",n,function(t){t.append(\"path\").attr(\"d\",\"M0,0Z\")}),this.clipDefRelative=o.ensureSingleById(t._clips,\"clipPath\",a,function(t){t.append(\"path\").attr(\"d\",\"M0,0Z\")}),this.plotContainer=o.ensureSingle(this.container,\"g\",this.id),this.updateLayers(r),c.setClipUrl(this.layers.backplot,n,e),c.setClipUrl(this.layers.grids,n,e)},w.updateLayers=function(t){var e=this.layers,r=[\"draglayer\",\"plotbg\",\"backplot\",\"grids\"];\"below traces\"===t.aaxis.layer&&r.push(\"aaxis\",\"aline\"),\"below traces\"===t.baxis.layer&&r.push(\"baxis\",\"bline\"),\"below traces\"===t.caxis.layer&&r.push(\"caxis\",\"cline\"),r.push(\"frontplot\"),\"above traces\"===t.aaxis.layer&&r.push(\"aaxis\",\"aline\"),\"above traces\"===t.baxis.layer&&r.push(\"baxis\",\"bline\"),\"above traces\"===t.caxis.layer&&r.push(\"caxis\",\"cline\");var a=this.plotContainer.selectAll(\"g.toplevel\").data(r,String),i=[\"agrid\",\"bgrid\",\"cgrid\"];a.enter().append(\"g\").attr(\"class\",function(t){return\"toplevel \"+t}).each(function(t){var r=n.select(this);e[t]=r,\"frontplot\"===t?r.append(\"g\").classed(\"scatterlayer\",!0):\"backplot\"===t?r.append(\"g\").classed(\"maplayer\",!0):\"plotbg\"===t?r.append(\"path\").attr(\"d\",\"M0,0Z\"):\"aline\"===t||\"bline\"===t||\"cline\"===t?r.append(\"path\"):\"grids\"===t&&i.forEach(function(t){e[t]=r.append(\"g\").classed(\"grid \"+t,!0)})}),a.order()};var k=Math.sqrt(4/3);w.adjustLayout=function(t,e){var r,n,a,i,o,s,f=this,p=t.domain,d=(p.x[0]+p.x[1])/2,g=(p.y[0]+p.y[1])/2,v=p.x[1]-p.x[0],m=p.y[1]-p.y[0],y=v*e.w,x=m*e.h,b=t.sum,_=t.aaxis.min,w=t.baxis.min,T=t.caxis.min;y>k*x?a=(i=x)*k:i=(a=y)/k,o=v*a/y,s=m*i/x,r=e.l+e.w*d-a/2,n=e.t+e.h*(1-g)-i/2,f.x0=r,f.y0=n,f.w=a,f.h=i,f.sum=b,f.xaxis={type:\"linear\",range:[_+2*T-b,b-_-2*w],domain:[d-o/2,d+o/2],_id:\"x\"},u(f.xaxis,f.graphDiv._fullLayout),f.xaxis.setScale(),f.xaxis.isPtWithinRange=function(t){return t.a>=f.aaxis.range[0]&&t.a<=f.aaxis.range[1]&&t.b>=f.baxis.range[1]&&t.b<=f.baxis.range[0]&&t.c>=f.caxis.range[1]&&t.c<=f.caxis.range[0]},f.yaxis={type:\"linear\",range:[_,b-w-T],domain:[g-s/2,g+s/2],_id:\"y\"},u(f.yaxis,f.graphDiv._fullLayout),f.yaxis.setScale(),f.yaxis.isPtWithinRange=function(){return!0};var M=f.yaxis.domain[0],A=f.aaxis=h({},t.aaxis,{range:[_,b-w-T],side:\"left\",tickangle:(+t.aaxis.tickangle||0)-30,domain:[M,M+s*k],anchor:\"free\",position:0,_id:\"y\",_length:a});u(A,f.graphDiv._fullLayout),A.setScale();var S=f.baxis=h({},t.baxis,{range:[b-_-T,w],side:\"bottom\",domain:f.xaxis.domain,anchor:\"free\",position:0,_id:\"x\",_length:a});u(S,f.graphDiv._fullLayout),S.setScale();var E=f.caxis=h({},t.caxis,{range:[b-_-w,T],side:\"right\",tickangle:(+t.caxis.tickangle||0)+30,domain:[M,M+s*k],anchor:\"free\",position:0,_id:\"y\",_length:a});u(E,f.graphDiv._fullLayout),E.setScale();var L=\"M\"+r+\",\"+(n+i)+\"h\"+a+\"l-\"+a/2+\",-\"+i+\"Z\";f.clipDef.select(\"path\").attr(\"d\",L),f.layers.plotbg.select(\"path\").attr(\"d\",L);var C=\"M0,\"+i+\"h\"+a+\"l-\"+a/2+\",-\"+i+\"Z\";f.clipDefRelative.select(\"path\").attr(\"d\",C);var P=\"translate(\"+r+\",\"+n+\")\";f.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",P),f.clipDefRelative.select(\"path\").attr(\"transform\",null);var O=\"translate(\"+(r-S._offset)+\",\"+(n+i)+\")\";f.layers.baxis.attr(\"transform\",O),f.layers.bgrid.attr(\"transform\",O);var z=\"translate(\"+(r+a/2)+\",\"+n+\")rotate(30)translate(0,\"+-A._offset+\")\";f.layers.aaxis.attr(\"transform\",z),f.layers.agrid.attr(\"transform\",z);var I=\"translate(\"+(r+a/2)+\",\"+n+\")rotate(-30)translate(0,\"+-E._offset+\")\";f.layers.caxis.attr(\"transform\",I),f.layers.cgrid.attr(\"transform\",I),f.drawAxes(!0),f.layers.aline.select(\"path\").attr(\"d\",A.showline?\"M\"+r+\",\"+(n+i)+\"l\"+a/2+\",-\"+i:\"M0,0\").call(l.stroke,A.linecolor||\"#000\").style(\"stroke-width\",(A.linewidth||0)+\"px\"),f.layers.bline.select(\"path\").attr(\"d\",S.showline?\"M\"+r+\",\"+(n+i)+\"h\"+a:\"M0,0\").call(l.stroke,S.linecolor||\"#000\").style(\"stroke-width\",(S.linewidth||0)+\"px\"),f.layers.cline.select(\"path\").attr(\"d\",E.showline?\"M\"+(r+a/2)+\",\"+n+\"l\"+a/2+\",\"+i:\"M0,0\").call(l.stroke,E.linecolor||\"#000\").style(\"stroke-width\",(E.linewidth||0)+\"px\"),f.graphDiv._context.staticPlot||f.initInteractions(),c.setClipUrl(f.layers.frontplot,f._hasClipOnAxisFalse?null:f.clipId,f.graphDiv)},w.drawAxes=function(t){var e=this.graphDiv,r=this.id.substr(7)+\"title\",n=this.layers,a=this.aaxis,i=this.baxis,o=this.caxis;if(this.drawAx(a),this.drawAx(i),this.drawAx(o),t){var l=Math.max(a.showticklabels?a.tickfont.size/2:0,(o.showticklabels?.75*o.tickfont.size:0)+(\"outside\"===o.ticks?.87*o.ticklen:0)),c=(i.showticklabels?i.tickfont.size:0)+(\"outside\"===i.ticks?i.ticklen:0)+3;n[\"a-title\"]=v.draw(e,\"a\"+r,{propContainer:a,propName:this.id+\".aaxis.title\",placeholder:s(e,\"Click to enter Component A title\"),attributes:{x:this.x0+this.w/2,y:this.y0-a.title.font.size/3-l,\"text-anchor\":\"middle\"}}),n[\"b-title\"]=v.draw(e,\"b\"+r,{propContainer:i,propName:this.id+\".baxis.title\",placeholder:s(e,\"Click to enter Component B title\"),attributes:{x:this.x0-c,y:this.y0+this.h+.83*i.title.font.size+c,\"text-anchor\":\"middle\"}}),n[\"c-title\"]=v.draw(e,\"c\"+r,{propContainer:o,propName:this.id+\".caxis.title\",placeholder:s(e,\"Click to enter Component C title\"),attributes:{x:this.x0+this.w+c,y:this.y0+this.h+.83*o.title.font.size+c,\"text-anchor\":\"middle\"}})}},w.drawAx=function(t){var e,r=this.graphDiv,n=t._name,a=n.charAt(0),i=t._id,s=this.layers[n],l=a+\"tickLayout\",c=(e=t).ticks+String(e.ticklen)+String(e.showticklabels);this[l]!==c&&(s.selectAll(\".\"+i+\"tick\").remove(),this[l]=c),t.setScale();var u=p.calcTicks(t),h=p.clipEnds(t,u),f=p.makeTransFn(t),d=p.getTickSigns(t)[2],g=o.deg2rad(30),v=d*(t.linewidth||1)/2,m=d*t.ticklen,y=this.w,x=this.h,b=\"b\"===a?\"M0,\"+v+\"l\"+Math.sin(g)*m+\",\"+Math.cos(g)*m:\"M\"+v+\",0l\"+Math.cos(g)*m+\",\"+-Math.sin(g)*m,_={a:\"M0,0l\"+x+\",-\"+y/2,b:\"M0,0l-\"+y/2+\",-\"+x,c:\"M0,0l-\"+x+\",\"+y/2}[a];p.drawTicks(r,t,{vals:\"inside\"===t.ticks?h:u,layer:s,path:b,transFn:f,crisp:!1}),p.drawGrid(r,t,{vals:h,layer:this.layers[a+\"grid\"],path:_,transFn:f,crisp:!1}),p.drawLabels(r,t,{vals:u,layer:s,transFn:f,labelFns:p.makeLabelFns(t,0,30)})};var T=b.MINZOOM/2+.87,M=\"m-0.87,.5h\"+T+\"v3h-\"+(T+5.2)+\"l\"+(T/2+2.6)+\",-\"+(.87*T+4.5)+\"l2.6,1.5l-\"+T/2+\",\"+.87*T+\"Z\",A=\"m0.87,.5h-\"+T+\"v3h\"+(T+5.2)+\"l-\"+(T/2+2.6)+\",-\"+(.87*T+4.5)+\"l-2.6,1.5l\"+T/2+\",\"+.87*T+\"Z\",S=\"m0,1l\"+T/2+\",\"+.87*T+\"l2.6,-1.5l-\"+(T/2+2.6)+\",-\"+(.87*T+4.5)+\"l-\"+(T/2+2.6)+\",\"+(.87*T+4.5)+\"l2.6,1.5l\"+T/2+\",-\"+.87*T+\"Z\",E=\"m0.5,0.5h5v-2h-5v-5h-2v5h-5v2h5v5h2Z\",L=!0;function C(t){n.select(t).selectAll(\".zoombox,.js-zoombox-backdrop,.js-zoombox-menu,.zoombox-corners\").remove()}w.initInteractions=function(){var t,e,r,n,u,h,f,p,v,_,w=this,T=w.layers.plotbg.select(\"path\").node(),P=w.graphDiv,O=P._fullLayout._zoomlayer,z={element:T,gd:P,plotinfo:{id:w.id,xaxis:w.xaxis,yaxis:w.yaxis},subplot:w.id,prepFn:function(i,o,s){z.xaxes=[w.xaxis],z.yaxes=[w.yaxis];var c=P._fullLayout.dragmode;z.minDrag=\"lasso\"===c?1:void 0,\"zoom\"===c?(z.moveFn=N,z.clickFn=D,z.doneFn=j,function(i,o,s){var c=T.getBoundingClientRect();t=o-c.left,e=s-c.top,r={a:w.aaxis.range[0],b:w.baxis.range[1],c:w.caxis.range[1]},u=r,n=w.aaxis.range[1]-r.a,h=a(w.graphDiv._fullLayout[w.id].bgcolor).getLuminance(),f=\"M0,\"+w.h+\"L\"+w.w/2+\", 0L\"+w.w+\",\"+w.h+\"Z\",p=!1,v=O.append(\"path\").attr(\"class\",\"zoombox\").attr(\"transform\",\"translate(\"+w.x0+\", \"+w.y0+\")\").style({fill:h>.2?\"rgba(0,0,0,0)\":\"rgba(255,255,255,0)\",\"stroke-width\":0}).attr(\"d\",f),_=O.append(\"path\").attr(\"class\",\"zoombox-corners\").attr(\"transform\",\"translate(\"+w.x0+\", \"+w.y0+\")\").style({fill:l.background,stroke:l.defaultLine,\"stroke-width\":1,opacity:0}).attr(\"d\",\"M0,0Z\"),x(P)}(0,o,s)):\"pan\"===c?(z.moveFn=V,z.clickFn=D,z.doneFn=U,r={a:w.aaxis.range[0],b:w.baxis.range[1],c:w.caxis.range[1]},u=r,x(P)):\"select\"!==c&&\"lasso\"!==c||m(i,o,s,z,c)}};function I(t){var e={};return e[w.id+\".aaxis.min\"]=t.a,e[w.id+\".baxis.min\"]=t.b,e[w.id+\".caxis.min\"]=t.c,e}function D(t,e){var r=P._fullLayout.clickmode;C(P),2===t&&(P.emit(\"plotly_doubleclick\",null),i.call(\"_guiRelayout\",P,I({a:0,b:0,c:0}))),r.indexOf(\"select\")>-1&&1===t&&y(e,P,[w.xaxis],[w.yaxis],w.id,z),r.indexOf(\"event\")>-1&&g.click(P,e,w.id)}function R(t,e){return 1-e/w.h}function F(t,e){return 1-(t+(w.h-e)/Math.sqrt(3))/w.w}function B(t,e){return(t-(w.h-e)/Math.sqrt(3))/w.w}function N(a,i){var o=t+a,s=e+i,l=Math.max(0,Math.min(1,R(0,e),R(0,s))),c=Math.max(0,Math.min(1,F(t,e),F(o,s))),d=Math.max(0,Math.min(1,B(t,e),B(o,s))),g=(l/2+d)*w.w,m=(1-l/2-c)*w.w,y=(g+m)/2,x=m-g,T=(1-l)*w.h,L=T-x/k;x<b.MINZOOM?(u=r,v.attr(\"d\",f),_.attr(\"d\",\"M0,0Z\")):(u={a:r.a+l*n,b:r.b+c*n,c:r.c+d*n},v.attr(\"d\",f+\"M\"+g+\",\"+T+\"H\"+m+\"L\"+y+\",\"+L+\"L\"+g+\",\"+T+\"Z\"),_.attr(\"d\",\"M\"+t+\",\"+e+E+\"M\"+g+\",\"+T+M+\"M\"+m+\",\"+T+A+\"M\"+y+\",\"+L+S)),p||(v.transition().style(\"fill\",h>.2?\"rgba(0,0,0,0.4)\":\"rgba(255,255,255,0.3)\").duration(200),_.transition().style(\"opacity\",1).duration(200),p=!0),P.emit(\"plotly_relayouting\",I(u))}function j(){C(P),u!==r&&(i.call(\"_guiRelayout\",P,I(u)),L&&P.data&&P._context.showTips&&(o.notifier(s(P,\"Double-click to zoom back out\"),\"long\"),L=!1))}function V(t,e){var n=t/w.xaxis._m,a=e/w.yaxis._m,i=[(u={a:r.a-a,b:r.b+(n+a)/2,c:r.c-(n-a)/2}).a,u.b,u.c].sort(),o=i.indexOf(u.a),s=i.indexOf(u.b),l=i.indexOf(u.c);i[0]<0&&(i[1]+i[0]/2<0?(i[2]+=i[0]+i[1],i[0]=i[1]=0):(i[2]+=i[0]/2,i[1]+=i[0]/2,i[0]=0),u={a:i[o],b:i[s],c:i[l]},e=(r.a-u.a)*w.yaxis._m,t=(r.c-u.c-r.b+u.b)*w.xaxis._m);var h=\"translate(\"+(w.x0+t)+\",\"+(w.y0+e)+\")\";w.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",h);var f=\"translate(\"+-t+\",\"+-e+\")\";w.clipDefRelative.select(\"path\").attr(\"transform\",f),w.aaxis.range=[u.a,w.sum-u.b-u.c],w.baxis.range=[w.sum-u.a-u.c,u.b],w.caxis.range=[w.sum-u.a-u.b,u.c],w.drawAxes(!1),w._hasClipOnAxisFalse&&w.plotContainer.select(\".scatterlayer\").selectAll(\".trace\").call(c.hideOutsideRangePoints,w),P.emit(\"plotly_relayouting\",I(u))}function U(){i.call(\"_guiRelayout\",P,I(u))}T.onmousemove=function(t){g.hover(P,t,w.id),P._fullLayout._lasthover=T,P._fullLayout._hoversubplot=w.id},T.onmouseout=function(t){P._dragging||d.unhover(P,t)},d.init(z)}},{\"../../components/color\":592,\"../../components/dragelement\":610,\"../../components/drawing\":613,\"../../components/fx\":630,\"../../components/titles\":679,\"../../lib\":717,\"../../lib/extend\":708,\"../../registry\":846,\"../cartesian/axes\":765,\"../cartesian/constants\":771,\"../cartesian/select\":782,\"../cartesian/set_convert\":783,\"../plots\":826,d3:165,tinycolor2:536}],846:[function(t,e,r){\"use strict\";var n=t(\"./lib/loggers\"),a=t(\"./lib/noop\"),i=t(\"./lib/push_unique\"),o=t(\"./lib/is_plain_object\"),s=t(\"./lib/dom\").addStyleRule,l=t(\"./lib/extend\"),c=t(\"./plots/attributes\"),u=t(\"./plots/layout_attributes\"),h=l.extendFlat,f=l.extendDeepAll;function p(t){var e=t.name,a=t.categories,i=t.meta;if(r.modules[e])n.log(\"Type \"+e+\" already registered\");else{r.subplotsRegistry[t.basePlotModule.name]||function(t){var e=t.name;if(r.subplotsRegistry[e])return void n.log(\"Plot type \"+e+\" already registered.\");for(var a in m(t),r.subplotsRegistry[e]=t,r.componentsRegistry)b(a,t.name)}(t.basePlotModule);for(var o={},l=0;l<a.length;l++)o[a[l]]=!0,r.allCategories[a[l]]=!0;for(var c in r.modules[e]={_module:t,categories:o},i&&Object.keys(i).length&&(r.modules[e].meta=i),r.allTypes.push(e),r.componentsRegistry)y(c,e);t.layoutAttributes&&h(r.traceLayoutAttributes,t.layoutAttributes);var u=t.basePlotModule,f=u.name;if(\"mapbox\"===f){var p=u.constants.styleRules;for(var d in p)s(\".js-plotly-plot .plotly .mapboxgl-\"+d,p[d])}\"geo\"!==f&&\"mapbox\"!==f||void 0===typeof window||void 0!==window.PlotlyGeoAssets||(window.PlotlyGeoAssets={topojson:{}})}}function d(t){if(\"string\"!=typeof t.name)throw new Error(\"Component module *name* must be a string.\");var e=t.name;for(var n in r.componentsRegistry[e]=t,t.layoutAttributes&&(t.layoutAttributes._isLinkedToArray&&i(r.layoutArrayContainers,e),m(t)),r.modules)y(e,n);for(var a in r.subplotsRegistry)b(e,a);for(var o in r.transformsRegistry)x(e,o);t.schema&&t.schema.layout&&f(u,t.schema.layout)}function g(t){if(\"string\"!=typeof t.name)throw new Error(\"Transform module *name* must be a string.\");var e=\"Transform module \"+t.name,a=\"function\"==typeof t.transform,i=\"function\"==typeof t.calcTransform;if(!a&&!i)throw new Error(e+\" is missing a *transform* or *calcTransform* method.\");for(var s in a&&i&&n.log([e+\" has both a *transform* and *calcTransform* methods.\",\"Please note that all *transform* methods are executed\",\"before all *calcTransform* methods.\"].join(\" \")),o(t.attributes)||n.log(e+\" registered without an *attributes* object.\"),\"function\"!=typeof t.supplyDefaults&&n.log(e+\" registered without a *supplyDefaults* method.\"),r.transformsRegistry[t.name]=t,r.componentsRegistry)x(s,t.name)}function v(t){var e=t.name,n=e.split(\"-\")[0],a=t.dictionary,i=t.format,o=a&&Object.keys(a).length,s=i&&Object.keys(i).length,l=r.localeRegistry,c=l[e];if(c||(l[e]=c={}),n!==e){var u=l[n];u||(l[n]=u={}),o&&u.dictionary===c.dictionary&&(u.dictionary=a),s&&u.format===c.format&&(u.format=i)}o&&(c.dictionary=a),s&&(c.format=i)}function m(t){if(t.layoutAttributes){var e=t.layoutAttributes._arrayAttrRegexps;if(e)for(var n=0;n<e.length;n++)i(r.layoutArrayRegexes,e[n])}}function y(t,e){var n=r.componentsRegistry[t].schema;if(n&&n.traces){var a=n.traces[e];a&&f(r.modules[e]._module.attributes,a)}}function x(t,e){var n=r.componentsRegistry[t].schema;if(n&&n.transforms){var a=n.transforms[e];a&&f(r.transformsRegistry[e].attributes,a)}}function b(t,e){var n=r.componentsRegistry[t].schema;if(n&&n.subplots){var a=r.subplotsRegistry[e],i=a.layoutAttributes,o=\"subplot\"===a.attr?a.name:a.attr;Array.isArray(o)&&(o=o[0]);var s=n.subplots[o];i&&s&&f(i,s)}}function _(t){return\"object\"==typeof t&&(t=t.type),t}r.modules={},r.allCategories={},r.allTypes=[],r.subplotsRegistry={},r.transformsRegistry={},r.componentsRegistry={},r.layoutArrayContainers=[],r.layoutArrayRegexes=[],r.traceLayoutAttributes={},r.localeRegistry={},r.apiMethodRegistry={},r.collectableSubplotTypes=null,r.register=function(t){if(r.collectableSubplotTypes=null,!t)throw new Error(\"No argument passed to Plotly.register.\");t&&!Array.isArray(t)&&(t=[t]);for(var e=0;e<t.length;e++){var n=t[e];if(!n)throw new Error(\"Invalid module was attempted to be registered!\");switch(n.moduleType){case\"trace\":p(n);break;case\"transform\":g(n);break;case\"component\":d(n);break;case\"locale\":v(n);break;case\"apiMethod\":var a=n.name;r.apiMethodRegistry[a]=n.fn;break;default:throw new Error(\"Invalid module was attempted to be registered!\")}}},r.getModule=function(t){var e=r.modules[_(t)];return!!e&&e._module},r.traceIs=function(t,e){if(\"various\"===(t=_(t)))return!1;var a=r.modules[t];return a||(t&&\"area\"!==t&&n.log(\"Unrecognized trace type \"+t+\".\"),a=r.modules[c.type.dflt]),!!a.categories[e]},r.getTransformIndices=function(t,e){for(var r=[],n=t.transforms||[],a=0;a<n.length;a++)n[a].type===e&&r.push(a);return r},r.hasTransform=function(t,e){for(var r=t.transforms||[],n=0;n<r.length;n++)if(r[n].type===e)return!0;return!1},r.getComponentMethod=function(t,e){var n=r.componentsRegistry[t];return n&&n[e]||a},r.call=function(){var t=arguments[0],e=[].slice.call(arguments,1);return r.apiMethodRegistry[t].apply(null,e)}},{\"./lib/dom\":706,\"./lib/extend\":708,\"./lib/is_plain_object\":718,\"./lib/loggers\":721,\"./lib/noop\":726,\"./lib/push_unique\":731,\"./plots/attributes\":762,\"./plots/layout_attributes\":817}],847:[function(t,e,r){\"use strict\";var n=t(\"../registry\"),a=t(\"../lib\"),i=a.extendFlat,o=a.extendDeep;function s(t){var e;switch(t){case\"themes__thumb\":e={autosize:!0,width:150,height:150,title:{text:\"\"},showlegend:!1,margin:{l:5,r:5,t:5,b:5,pad:0},annotations:[]};break;case\"thumbnail\":e={title:{text:\"\"},hidesources:!0,showlegend:!1,borderwidth:0,bordercolor:\"\",margin:{l:1,r:1,t:1,b:1,pad:0},annotations:[]};break;default:e={}}return e}e.exports=function(t,e){var r;t.framework&&t.framework.isPolar&&(t=t.framework.getConfig());var a,l=t.data,c=t.layout,u=o([],l),h=o({},c,s(e.tileClass)),f=t._context||{};if(e.width&&(h.width=e.width),e.height&&(h.height=e.height),\"thumbnail\"===e.tileClass||\"themes__thumb\"===e.tileClass){h.annotations=[];var p=Object.keys(h);for(r=0;r<p.length;r++)a=p[r],[\"xaxis\",\"yaxis\",\"zaxis\"].indexOf(a.slice(0,5))>-1&&(h[p[r]].title={text:\"\"});for(r=0;r<u.length;r++){var d=u[r];d.showscale=!1,d.marker&&(d.marker.showscale=!1),n.traceIs(d,\"pie-like\")&&(d.textposition=\"none\")}}if(Array.isArray(e.annotations))for(r=0;r<e.annotations.length;r++)h.annotations.push(e.annotations[r]);var g=Object.keys(h).filter(function(t){return t.match(/^scene\\d*$/)});if(g.length){var v={};for(\"thumbnail\"===e.tileClass&&(v={title:{text:\"\"},showaxeslabels:!1,showticklabels:!1,linetickenable:!1}),r=0;r<g.length;r++){var m=h[g[r]];m.xaxis||(m.xaxis={}),m.yaxis||(m.yaxis={}),m.zaxis||(m.zaxis={}),i(m.xaxis,v),i(m.yaxis,v),i(m.zaxis,v),m._scene=null}}var y=document.createElement(\"div\");e.tileClass&&(y.className=e.tileClass);var x={gd:y,td:y,layout:h,data:u,config:{staticPlot:void 0===e.staticPlot||e.staticPlot,plotGlPixelRatio:void 0===e.plotGlPixelRatio?2:e.plotGlPixelRatio,displaylogo:e.displaylogo||!1,showLink:e.showLink||!1,showTips:e.showTips||!1,mapboxAccessToken:f.mapboxAccessToken}};return\"transparent\"!==e.setBackground&&(x.config.setBackground=e.setBackground||\"opaque\"),x.gd.defaultLayout=s(e.tileClass),x}},{\"../lib\":717,\"../registry\":846}],848:[function(t,e,r){\"use strict\";var n=t(\"../lib\"),a=t(\"../plot_api/to_image\"),i=t(\"./filesaver\"),o=t(\"./helpers\");e.exports=function(t,e){var r;return n.isPlainObject(t)||(r=n.getGraphDiv(t)),(e=e||{}).format=e.format||\"png\",e.imageDataOnly=!0,new Promise(function(s,l){r&&r._snapshotInProgress&&l(new Error(\"Snapshotting already in progress.\")),n.isIE()&&\"svg\"!==e.format&&l(new Error(o.MSG_IE_BAD_FORMAT)),r&&(r._snapshotInProgress=!0);var c=a(t,e),u=e.filename||t.fn||\"newplot\";u+=\".\"+e.format,c.then(function(t){return r&&(r._snapshotInProgress=!1),i(t,u,e.format)}).then(function(t){s(t)}).catch(function(t){r&&(r._snapshotInProgress=!1),l(t)})})}},{\"../lib\":717,\"../plot_api/to_image\":758,\"./filesaver\":849,\"./helpers\":850}],849:[function(t,e,r){\"use strict\";var n=t(\"../lib\"),a=t(\"./helpers\");e.exports=function(t,e,r){var i=document.createElement(\"a\"),o=\"download\"in i;return new Promise(function(s,l){var c,u;if(n.isIE9orBelow()&&l(new Error(\"IE < 10 unsupported\")),n.isSafari()){var h=\"svg\"===r?\",\":\";base64,\";return a.octetStream(h+encodeURIComponent(t)),s(e)}return n.isIE()?(c=a.createBlob(t,\"svg\"),window.navigator.msSaveBlob(c,e),c=null,s(e)):o?(c=a.createBlob(t,r),u=a.createObjectURL(c),i.href=u,i.download=e,document.body.appendChild(i),i.click(),document.body.removeChild(i),a.revokeObjectURL(u),c=null,s(e)):void l(new Error(\"download error\"))})}},{\"../lib\":717,\"./helpers\":850}],850:[function(t,e,r){\"use strict\";var n=t(\"../registry\");r.getDelay=function(t){return t._has&&(t._has(\"gl3d\")||t._has(\"gl2d\")||t._has(\"mapbox\"))?500:0},r.getRedrawFunc=function(t){return function(){var e=t._fullLayout||{};!(e._has&&e._has(\"polar\"))&&t.data&&t.data[0]&&t.data[0].r||n.getComponentMethod(\"colorbar\",\"draw\")(t)}},r.encodeSVG=function(t){return\"data:image/svg+xml,\"+encodeURIComponent(t)};var a=window.URL||window.webkitURL;r.createObjectURL=function(t){return a.createObjectURL(t)},r.revokeObjectURL=function(t){return a.revokeObjectURL(t)},r.createBlob=function(t,e){if(\"svg\"===e)return new window.Blob([t],{type:\"image/svg+xml;charset=utf-8\"});var r=function(t){for(var e=t.length,r=new ArrayBuffer(e),n=new Uint8Array(r),a=0;a<e;a++)n[a]=t.charCodeAt(a);return r}(window.atob(t));return new window.Blob([r],{type:\"image/\"+e})},r.octetStream=function(t){document.location.href=\"data:application/octet-stream\"+t},r.IMAGE_URL_PREFIX=/^data:image\\/\\w+;base64,/,r.MSG_IE_BAD_FORMAT=\"Sorry IE does not support downloading from canvas. Try {format:'svg'} instead.\"},{\"../registry\":846}],851:[function(t,e,r){\"use strict\";var n=t(\"./helpers\"),a={getDelay:n.getDelay,getRedrawFunc:n.getRedrawFunc,clone:t(\"./cloneplot\"),toSVG:t(\"./tosvg\"),svgToImg:t(\"./svgtoimg\"),toImage:t(\"./toimage\"),downloadImage:t(\"./download\")};e.exports=a},{\"./cloneplot\":847,\"./download\":848,\"./helpers\":850,\"./svgtoimg\":852,\"./toimage\":853,\"./tosvg\":854}],852:[function(t,e,r){\"use strict\";var n=t(\"../lib\"),a=t(\"events\").EventEmitter,i=t(\"./helpers\");e.exports=function(t){var e=t.emitter||new a,r=new Promise(function(a,o){var s=window.Image,l=t.svg,c=t.format||\"png\";if(n.isIE()&&\"svg\"!==c){var u=new Error(i.MSG_IE_BAD_FORMAT);return o(u),t.promise?r:e.emit(\"error\",u)}var h,f,p=t.canvas,d=t.scale||1,g=t.width||300,v=t.height||150,m=d*g,y=d*v,x=p.getContext(\"2d\"),b=new s;\"svg\"===c||n.isIE9orBelow()||n.isSafari()?f=i.encodeSVG(l):(h=i.createBlob(l,\"svg\"),f=i.createObjectURL(h)),p.width=m,p.height=y,b.onload=function(){var r;switch(h=null,i.revokeObjectURL(f),\"svg\"!==c&&x.drawImage(b,0,0,m,y),c){case\"jpeg\":r=p.toDataURL(\"image/jpeg\");break;case\"png\":r=p.toDataURL(\"image/png\");break;case\"webp\":r=p.toDataURL(\"image/webp\");break;case\"svg\":r=f;break;default:var n=\"Image format is not jpeg, png, svg or webp.\";if(o(new Error(n)),!t.promise)return e.emit(\"error\",n)}a(r),t.promise||e.emit(\"success\",r)},b.onerror=function(r){if(h=null,i.revokeObjectURL(f),o(r),!t.promise)return e.emit(\"error\",r)},b.src=f});return t.promise?r:e}},{\"../lib\":717,\"./helpers\":850,events:106}],853:[function(t,e,r){\"use strict\";var n=t(\"events\").EventEmitter,a=t(\"../registry\"),i=t(\"../lib\"),o=t(\"./helpers\"),s=t(\"./cloneplot\"),l=t(\"./tosvg\"),c=t(\"./svgtoimg\");e.exports=function(t,e){var r=new n,u=s(t,{format:\"png\"}),h=u.gd;h.style.position=\"absolute\",h.style.left=\"-5000px\",document.body.appendChild(h);var f=o.getRedrawFunc(h);return a.call(\"plot\",h,u.data,u.layout,u.config).then(f).then(function(){var t=o.getDelay(h._fullLayout);setTimeout(function(){var t=l(h),n=document.createElement(\"canvas\");n.id=i.randstr(),(r=c({format:e.format,width:h._fullLayout.width,height:h._fullLayout.height,canvas:n,emitter:r,svg:t})).clean=function(){h&&document.body.removeChild(h)}},t)}).catch(function(t){r.emit(\"error\",t)}),r}},{\"../lib\":717,\"../registry\":846,\"./cloneplot\":847,\"./helpers\":850,\"./svgtoimg\":852,\"./tosvg\":854,events:106}],854:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../lib\"),i=t(\"../components/drawing\"),o=t(\"../components/color\"),s=t(\"../constants/xmlns_namespaces\"),l=/\"/g,c=new RegExp('(\"TOBESTRIPPED)|(TOBESTRIPPED\")',\"g\");e.exports=function(t,e,r){var u,h=t._fullLayout,f=h._paper,p=h._toppaper,d=h.width,g=h.height;f.insert(\"rect\",\":first-child\").call(i.setRect,0,0,d,g).call(o.fill,h.paper_bgcolor);var v=h._basePlotModules||[];for(u=0;u<v.length;u++){var m=v[u];m.toSVG&&m.toSVG(t)}if(p){var y=p.node().childNodes,x=Array.prototype.slice.call(y);for(u=0;u<x.length;u++){var b=x[u];b.childNodes.length&&f.node().appendChild(b)}}if(h._draggers&&h._draggers.remove(),f.node().style.background=\"\",f.selectAll(\"text\").attr({\"data-unformatted\":null,\"data-math\":null}).each(function(){var t=n.select(this);if(\"hidden\"!==this.style.visibility&&\"none\"!==this.style.display){t.style({visibility:null,display:null});var e=this.style.fontFamily;e&&-1!==e.indexOf('\"')&&t.style(\"font-family\",e.replace(l,\"TOBESTRIPPED\"))}else t.remove()}),h._gradientUrlQueryParts){var _=[];for(var w in h._gradientUrlQueryParts)_.push(w);_.length&&f.selectAll(_.join(\",\")).each(function(){var t=n.select(this),e=this.style.fill;e&&-1!==e.indexOf(\"url(\")&&t.style(\"fill\",e.replace(l,\"TOBESTRIPPED\"));var r=this.style.stroke;r&&-1!==r.indexOf(\"url(\")&&t.style(\"stroke\",r.replace(l,\"TOBESTRIPPED\"))})}\"pdf\"!==e&&\"eps\"!==e||f.selectAll(\"#MathJax_SVG_glyphs path\").attr(\"stroke-width\",0),f.node().setAttributeNS(s.xmlns,\"xmlns\",s.svg),f.node().setAttributeNS(s.xmlns,\"xmlns:xlink\",s.xlink),\"svg\"===e&&r&&(f.attr(\"width\",r*d),f.attr(\"height\",r*g),f.attr(\"viewBox\",\"0 0 \"+d+\" \"+g));var k=(new window.XMLSerializer).serializeToString(f.node());return k=function(t){var e=n.select(\"body\").append(\"div\").style({display:\"none\"}).html(\"\"),r=t.replace(/(&[^;]*;)/gi,function(t){return\"&lt;\"===t?\"&#60;\":\"&rt;\"===t?\"&#62;\":-1!==t.indexOf(\"<\")||-1!==t.indexOf(\">\")?\"\":e.html(t).text()});return e.remove(),r}(k),k=(k=k.replace(/&(?!\\w+;|\\#[0-9]+;| \\#x[0-9A-F]+;)/g,\"&amp;\")).replace(c,\"'\"),a.isIE()&&(k=(k=(k=k.replace(/\"/gi,\"'\")).replace(/(\\('#)([^']*)('\\))/gi,'(\"#$2\")')).replace(/(\\\\')/gi,'\"')),k}},{\"../components/color\":592,\"../components/drawing\":613,\"../constants/xmlns_namespaces\":694,\"../lib\":717,d3:165}],855:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){for(var r=0;r<t.length;r++)t[r].i=r;n.mergeArray(e.text,t,\"tx\"),n.mergeArray(e.hovertext,t,\"htx\");var a=e.marker;if(a){n.mergeArray(a.opacity,t,\"mo\",!0),n.mergeArray(a.color,t,\"mc\");var i=a.line;i&&(n.mergeArray(i.color,t,\"mlc\"),n.mergeArrayCastPositive(i.width,t,\"mlw\"))}}},{\"../../lib\":717}],856:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),a=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,o=t(\"../../components/colorscale/attributes\"),s=t(\"../../plots/font_attributes\"),l=t(\"./constants\"),c=t(\"../../lib/extend\").extendFlat,u=s({editType:\"calc\",arrayOk:!0,colorEditType:\"style\"}),h=c({},n.marker.line.width,{dflt:0}),f=c({width:h,editType:\"calc\"},o(\"marker.line\")),p=c({line:f,editType:\"calc\"},o(\"marker\"),{opacity:{valType:\"number\",arrayOk:!0,dflt:1,min:0,max:1,editType:\"style\"}});e.exports={x:n.x,x0:n.x0,dx:n.dx,y:n.y,y0:n.y0,dy:n.dy,text:n.text,texttemplate:i({editType:\"plot\"},{keys:l.eventDataKeys}),hovertext:n.hovertext,hovertemplate:a({},{keys:l.eventDataKeys}),textposition:{valType:\"enumerated\",values:[\"inside\",\"outside\",\"auto\",\"none\"],dflt:\"none\",arrayOk:!0,editType:\"calc\"},insidetextanchor:{valType:\"enumerated\",values:[\"end\",\"middle\",\"start\"],dflt:\"end\",editType:\"plot\"},textangle:{valType:\"angle\",dflt:\"auto\",editType:\"plot\"},textfont:c({},u,{}),insidetextfont:c({},u,{}),outsidetextfont:c({},u,{}),constraintext:{valType:\"enumerated\",values:[\"inside\",\"outside\",\"both\",\"none\"],dflt:\"both\",editType:\"calc\"},cliponaxis:c({},n.cliponaxis,{}),orientation:{valType:\"enumerated\",values:[\"v\",\"h\"],editType:\"calc+clearAxisTypes\"},base:{valType:\"any\",dflt:null,arrayOk:!0,editType:\"calc\"},offset:{valType:\"number\",dflt:null,arrayOk:!0,editType:\"calc\"},width:{valType:\"number\",dflt:null,min:0,arrayOk:!0,editType:\"calc\"},marker:p,offsetgroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},alignmentgroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},selected:{marker:{opacity:n.selected.marker.opacity,color:n.selected.marker.color,editType:\"style\"},textfont:n.selected.textfont,editType:\"style\"},unselected:{marker:{opacity:n.unselected.marker.opacity,color:n.unselected.marker.color,editType:\"style\"},textfont:n.unselected.textfont,editType:\"style\"},r:n.r,t:n.t,_deprecated:{bardir:{valType:\"enumerated\",editType:\"calc\",values:[\"v\",\"h\"]}}}},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plots/font_attributes\":791,\"../../plots/template_attributes\":841,\"../scatter/attributes\":1120,\"./constants\":858}],857:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\"),a=t(\"../../components/colorscale/helpers\").hasColorscale,i=t(\"../../components/colorscale/calc\"),o=t(\"./arrays_to_calcdata\"),s=t(\"../scatter/calc_selection\");e.exports=function(t,e){var r,l,c=n.getFromId(t,e.xaxis||\"x\"),u=n.getFromId(t,e.yaxis||\"y\");\"h\"===e.orientation?(r=c.makeCalcdata(e,\"x\"),l=u.makeCalcdata(e,\"y\")):(r=u.makeCalcdata(e,\"y\"),l=c.makeCalcdata(e,\"x\"));for(var h=Math.min(l.length,r.length),f=new Array(h),p=0;p<h;p++)f[p]={p:l[p],s:r[p]},e.ids&&(f[p].id=String(e.ids[p]));return a(e,\"marker\")&&i(t,e,{vals:e.marker.color,containerStr:\"marker\",cLetter:\"c\"}),a(e,\"marker.line\")&&i(t,e,{vals:e.marker.line.color,containerStr:\"marker.line\",cLetter:\"c\"}),o(f,e),s(f,e),f}},{\"../../components/colorscale/calc\":600,\"../../components/colorscale/helpers\":603,\"../../plots/cartesian/axes\":765,\"../scatter/calc_selection\":1122,\"./arrays_to_calcdata\":855}],858:[function(t,e,r){\"use strict\";e.exports={TEXTPAD:3,eventDataKeys:[\"value\",\"label\"]}},{}],859:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib\").isArrayOrTypedArray,i=t(\"../../constants/numerical\").BADNUM,o=t(\"../../registry\"),s=t(\"../../plots/cartesian/axes\"),l=t(\"../../plots/cartesian/axis_ids\").getAxisGroup,c=t(\"./sieve.js\");function u(t,e,r,o,u){if(o.length){var b,_,w,k;switch(function(t,e){var r,i;for(r=0;r<e.length;r++){var o,s=e[r],l=s[0].trace,c=\"funnel\"===l.type?l._base:l.base,u=\"h\"===l.orientation?l.xcalendar:l.ycalendar,h=\"category\"===t.type||\"multicategory\"===t.type?function(){return null}:t.d2c;if(a(c)){for(i=0;i<Math.min(c.length,s.length);i++)o=h(c[i],0,u),n(o)?(s[i].b=+o,s[i].hasB=1):s[i].b=0;for(;i<s.length;i++)s[i].b=0}else{o=h(c,0,u);var f=n(o);for(o=f?o:0,i=0;i<s.length;i++)s[i].b=o,f&&(s[i].hasB=1)}}}(r,o),u.mode){case\"overlay\":h(e,r,o,u);break;case\"group\":for(b=[],_=[],w=0;w<o.length;w++)void 0===(k=o[w])[0].trace.offset?_.push(k):b.push(k);_.length&&function(t,e,r,n,a){var o=new c(n,{sepNegVal:!1,overlapNoMerge:!a.norm});(function(t,e,r,n){for(var a=t._fullLayout,i=r.positions,o=r.distinctPositions,s=r.minDiff,c=r.traces,u=c.length,h=i.length!==o.length,f=s*(1-n.gap),v=l(a,e._id)+c[0][0].trace.orientation,m=a._alignmentOpts[v]||{},y=0;y<u;y++){var x,b,_=c[y],w=_[0].trace,k=m[w.alignmentgroup]||{},T=Object.keys(k.offsetGroups||{}).length,M=(x=T?f/T:h?f/u:f)*(1-(n.groupgap||0));b=T?((2*w._offsetIndex+1-T)*x-M)/2:h?((2*y+1-u)*x-M)/2:-M/2;var A=_[0].t;A.barwidth=M,A.poffset=b,A.bargroupwidth=f,A.bardelta=s}r.binWidth=c[0][0].t.barwidth/100,p(r),d(e,r),g(e,r,h)})(t,e,o,a),function(t){for(var e=t.traces,r=0;r<e.length;r++){var n=e[r],a=n[0].trace;if(void 0===a.base)for(var o=new c([n],{sepNegVal:!0,overlapNoMerge:!0}),s=0;s<n.length;s++){var l=n[s];if(l.p!==i){var u=o.put(l.p,l.b+l.s);u&&(l.b=u)}}}}(o),a.norm?(m(o),y(r,o,a)):v(r,o)}(t,e,r,_,u),b.length&&h(e,r,b,u);break;case\"stack\":case\"relative\":for(b=[],_=[],w=0;w<o.length;w++)void 0===(k=o[w])[0].trace.base?_.push(k):b.push(k);_.length&&function(t,e,r,n,a){var o=new c(n,{sepNegVal:\"relative\"===a.mode,overlapNoMerge:!(a.norm||\"stack\"===a.mode||\"relative\"===a.mode)});f(e,o,a),function(t,e,r){var n,a,o,l,c,u,h=x(t),f=e.traces;for(l=0;l<f.length;l++)if(n=f[l],\"funnel\"===(a=n[0].trace).type)for(c=0;c<n.length;c++)(u=n[c]).s!==i&&e.put(u.p,-.5*u.s);for(l=0;l<f.length;l++){n=f[l],a=n[0].trace,o=\"funnel\"===a.type;var p=[];for(c=0;c<n.length;c++)if((u=n[c]).s!==i){var d;d=o?u.s:u.s+u.b;var g=e.put(u.p,d),v=g+d;u.b=g,u[h]=v,r.norm||(p.push(v),u.hasB&&p.push(g))}r.norm||(a._extremes[t._id]=s.findExtremes(t,p,{tozero:!0,padded:!0}))}}(r,o,a);for(var l=0;l<n.length;l++)for(var u=n[l],h=0;h<u.length;h++){var p=u[h];if(p.s!==i){var d=p.b+p.s===o.get(p.p,p.s);d&&(p._outmost=!0)}}a.norm&&y(r,o,a)}(0,e,r,_,u),b.length&&h(e,r,b,u)}!function(t,e){var r,a,i,o=x(e),s={},l=1/0,c=-1/0;for(r=0;r<t.length;r++)for(i=t[r],a=0;a<i.length;a++){var u=i[a].p;n(u)&&(l=Math.min(l,u),c=Math.max(c,u))}var h=1e4/(c-l),f=s.round=function(t){return String(Math.round(h*(t-l)))};for(r=0;r<t.length;r++){(i=t[r])[0].t.extents=s;var p=i[0].t.poffset,d=Array.isArray(p);for(a=0;a<i.length;a++){var g=i[a],v=g[o]-g.w/2;if(n(v)){var m=g[o]+g.w/2,y=f(g.p);s[y]?s[y]=[Math.min(v,s[y][0]),Math.max(m,s[y][1])]:s[y]=[v,m]}g.p0=g.p+(d?p[a]:p),g.p1=g.p0+g.w,g.s0=g.b,g.s1=g.s0+g.s}}}(o,e)}}function h(t,e,r,n){for(var a=0;a<r.length;a++){var i=r[a],o=new c([i],{sepNegVal:!1,overlapNoMerge:!n.norm});f(t,o,n),n.norm?(m(o),y(e,o,n)):v(e,o)}}function f(t,e,r){for(var n=e.minDiff,a=e.traces,i=n*(1-r.gap),o=i*(1-(r.groupgap||0)),s=-o/2,l=0;l<a.length;l++){var c=a[l][0].t;c.barwidth=o,c.poffset=s,c.bargroupwidth=i,c.bardelta=n}e.binWidth=a[0][0].t.barwidth/100,p(e),d(t,e),g(t,e)}function p(t){var e,r,i=t.traces;for(e=0;e<i.length;e++){var o,s=i[e],l=s[0],c=l.trace,u=l.t,h=c._offset||c.offset,f=u.poffset;if(a(h)){for(o=Array.prototype.slice.call(h,0,s.length),r=0;r<o.length;r++)n(o[r])||(o[r]=f);for(r=o.length;r<s.length;r++)o.push(f);u.poffset=o}else void 0!==h&&(u.poffset=h);var p=c._width||c.width,d=u.barwidth;if(a(p)){var g=Array.prototype.slice.call(p,0,s.length);for(r=0;r<g.length;r++)n(g[r])||(g[r]=d);for(r=g.length;r<s.length;r++)g.push(d);if(u.barwidth=g,void 0===h){for(o=[],r=0;r<s.length;r++)o.push(f+(d-g[r])/2);u.poffset=o}}else void 0!==p&&(u.barwidth=p,void 0===h&&(u.poffset=f+(d-p)/2))}}function d(t,e){for(var r=e.traces,n=x(t),a=0;a<r.length;a++)for(var i=r[a],o=i[0].t,s=o.poffset,l=Array.isArray(s),c=o.barwidth,u=Array.isArray(c),h=0;h<i.length;h++){var f=i[h],p=f.w=u?c[h]:c;f[n]=f.p+(l?s[h]:s)+p/2}}function g(t,e,r){var n=e.traces,a=e.minDiff/2;s.minDtick(t,e.minDiff,e.distinctPositions[0],r);for(var i=0;i<n.length;i++){var o,l,c,u,h=n[i],f=h[0],p=f.trace,d=[];for(u=0;u<h.length;u++)l=(o=h[u]).p-a,c=o.p+a,d.push(l,c);if(p.width||p.offset){var g=f.t,v=g.poffset,m=g.barwidth,y=Array.isArray(v),x=Array.isArray(m);for(u=0;u<h.length;u++){o=h[u];var b=y?v[u]:v,_=x?m[u]:m;c=(l=o.p+b)+_,d.push(l,c)}}p._extremes[t._id]=s.findExtremes(t,d,{padded:!1})}}function v(t,e){for(var r=e.traces,n=x(t),a=0;a<r.length;a++){for(var i=r[a],o=i[0].trace,l=[],c=!0,u=0;u<i.length;u++){var h=i[u],f=h.b,p=f+h.s;h[n]=p,l.push(p),h.hasB&&l.push(f),h.hasB&&h.b>0&&h.s>0||(c=!1)}o._extremes[t._id]=s.findExtremes(t,l,{tozero:!c,padded:!0})}}function m(t){for(var e=t.traces,r=0;r<e.length;r++)for(var n=e[r],a=0;a<n.length;a++){var o=n[a];o.s!==i&&t.put(o.p,o.b+o.s)}}function y(t,e,r){var a=e.traces,o=x(t),l=\"fraction\"===r.norm?1:100,c=l/1e9,u=t.l2c(t.c2l(0)),h=\"stack\"===r.mode?l:u;function f(e){return n(t.c2l(e))&&(e<u-c||e>h+c||!n(u))}for(var p=0;p<a.length;p++){for(var d=a[p],g=d[0].trace,v=[],m=!0,y=!1,b=0;b<d.length;b++){var _=d[b];if(_.s!==i){var w=Math.abs(l/e.get(_.p,_.s));_.b*=w,_.s*=w;var k=_.b,T=k+_.s;_[o]=T,v.push(T),y=y||f(T),_.hasB&&(v.push(k),y=y||f(k)),_.hasB&&_.b>0&&_.s>0||(m=!1)}}g._extremes[t._id]=s.findExtremes(t,v,{tozero:!m,padded:y})}}function x(t){return t._id.charAt(0)}e.exports={crossTraceCalc:function(t,e){for(var r=e.xaxis,n=e.yaxis,a=t._fullLayout,i=t._fullData,s=t.calcdata,l=[],c=[],h=0;h<i.length;h++){var f=i[h];!0===f.visible&&o.traceIs(f,\"bar\")&&f.xaxis===r._id&&f.yaxis===n._id&&(\"h\"===f.orientation?l.push(s[h]):c.push(s[h]))}var p={mode:a.barmode,norm:a.barnorm,gap:a.bargap,groupgap:a.bargroupgap};u(t,r,n,c,p),u(t,n,r,l,p)},setGroupPositions:u}},{\"../../constants/numerical\":693,\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"../../plots/cartesian/axis_ids\":768,\"../../registry\":846,\"./sieve.js\":869,\"fast-isnumeric\":228}],860:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/color\"),i=t(\"../../registry\"),o=t(\"../scatter/xy_defaults\"),s=t(\"./style_defaults\"),l=t(\"../../plots/cartesian/axis_ids\").getAxisGroup,c=t(\"./attributes\"),u=n.coerceFont;function h(t,e,r,n){var a=e.orientation,i=e[{v:\"x\",h:\"y\"}[a]+\"axis\"],o=l(r,i)+a,s=r._alignmentOpts||{},c=n(\"alignmentgroup\"),u=s[o];u||(u=s[o]={});var h=u[c];h?h.traces.push(e):h=u[c]={traces:[e],alignmentIndex:Object.keys(u).length,offsetGroups:{}};var f=n(\"offsetgroup\"),p=h.offsetGroups,d=p[f];f&&(d||(d=p[f]={offsetIndex:Object.keys(p).length}),e._offsetIndex=d.offsetIndex)}function f(t,e,r,a,i,o){var s=!(!1===(o=o||{}).moduleHasSelected),l=!(!1===o.moduleHasUnselected),c=!(!1===o.moduleHasConstrain),h=!(!1===o.moduleHasCliponaxis),f=!(!1===o.moduleHasTextangle),p=!(!1===o.moduleHasInsideanchor),d=!!o.hasPathbar,g=Array.isArray(i)||\"auto\"===i,v=g||\"inside\"===i,m=g||\"outside\"===i;if(v||m){var y=u(a,\"textfont\",r.font),x=n.extendFlat({},y),b=!(t.textfont&&t.textfont.color);if(b&&delete x.color,u(a,\"insidetextfont\",x),d){var _=n.extendFlat({},y);b&&delete _.color,u(a,\"pathbar.textfont\",_)}m&&u(a,\"outsidetextfont\",y),s&&a(\"selected.textfont.color\"),l&&a(\"unselected.textfont.color\"),c&&a(\"constraintext\"),h&&a(\"cliponaxis\"),f&&a(\"textangle\"),a(\"texttemplate\")}v&&p&&a(\"insidetextanchor\")}e.exports={supplyDefaults:function(t,e,r,l){function u(r,a){return n.coerce(t,e,c,r,a)}if(o(t,e,l,u)){u(\"orientation\",e.x&&!e.y?\"h\":\"v\"),u(\"base\"),u(\"offset\"),u(\"width\"),u(\"text\"),u(\"hovertext\"),u(\"hovertemplate\");var h=u(\"textposition\");f(t,0,l,u,h,{moduleHasSelected:!0,moduleHasUnselected:!0,moduleHasConstrain:!0,moduleHasCliponaxis:!0,moduleHasTextangle:!0,moduleHasInsideanchor:!0}),s(t,e,u,r,l);var p=(e.marker.line||{}).color,d=i.getComponentMethod(\"errorbars\",\"supplyDefaults\");d(t,e,p||a.defaultLine,{axis:\"y\"}),d(t,e,p||a.defaultLine,{axis:\"x\",inherit:\"y\"}),n.coerceSelectionMarkerOpacity(e,u)}else e.visible=!1},crossTraceDefaults:function(t,e){var r;function a(t){return n.coerce(r._input,r,c,t)}if(\"group\"===e.barmode)for(var i=0;i<t.length;i++)\"bar\"===(r=t[i]).type&&(r._input,h(0,r,e,a))},handleGroupingDefaults:h,handleText:f}},{\"../../components/color\":592,\"../../lib\":717,\"../../plots/cartesian/axis_ids\":768,\"../../registry\":846,\"../scatter/xy_defaults\":1146,\"./attributes\":856,\"./style_defaults\":871}],861:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){return t.x=\"xVal\"in e?e.xVal:e.x,t.y=\"yVal\"in e?e.yVal:e.y,e.xa&&(t.xaxis=e.xa),e.ya&&(t.yaxis=e.ya),\"h\"===r.orientation?(t.label=t.y,t.value=t.x):(t.label=t.x,t.value=t.y),t}},{}],862:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"tinycolor2\"),i=t(\"../../lib\").isArrayOrTypedArray;r.coerceString=function(t,e,r){if(\"string\"==typeof e){if(e||!t.noBlank)return e}else if((\"number\"==typeof e||!0===e)&&!t.strict)return String(e);return void 0!==r?r:t.dflt},r.coerceNumber=function(t,e,r){if(n(e)){e=+e;var a=t.min,i=t.max;if(!(void 0!==a&&e<a||void 0!==i&&e>i))return e}return void 0!==r?r:t.dflt},r.coerceColor=function(t,e,r){return a(e).isValid()?e:void 0!==r?r:t.dflt},r.coerceEnumerated=function(t,e,r){return t.coerceNumber&&(e=+e),-1!==t.values.indexOf(e)?e:void 0!==r?r:t.dflt},r.getValue=function(t,e){var r;return Array.isArray(t)?e<t.length&&(r=t[e]):r=t,r},r.getLineWidth=function(t,e){return 0<e.mlw?e.mlw:i(t.marker.line.width)?0:t.marker.line.width}},{\"../../lib\":717,\"fast-isnumeric\":228,tinycolor2:536}],863:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx\"),a=t(\"../../registry\"),i=t(\"../../components/color\"),o=t(\"../../lib\").fillText,s=t(\"./helpers\").getLineWidth,l=t(\"../../plots/cartesian/axes\").hoverLabelText;function c(t,e,r,a){var i,s,c,u,h,f,p,d=t.cd,g=d[0].trace,v=d[0].t,m=\"closest\"===a,y=\"waterfall\"===g.type,x=t.maxHoverDistance,b=t.maxSpikeDistance;function _(t){return t[c]-t.w/2}function w(t){return t[c]+t.w/2}var k=m?_:function(t){return Math.min(_(t),t.p-v.bardelta/2)},T=m?w:function(t){return Math.max(w(t),t.p+v.bardelta/2)};function M(t,e){return n.inbox(t-i,e-i,x+Math.min(1,Math.abs(e-t)/p)-1)}function A(t){return M(k(t),T(t))}function S(t){var e=s,r=t.b,a=t[u];if(y){var i=Math.abs(t.rawS)||0;e>0?a+=i:e<0&&(a-=i)}return n.inbox(r-e,a-e,x+(a-e)/(a-r)-1)}\"h\"===g.orientation?(i=r,s=e,c=\"y\",u=\"x\",h=S,f=A):(i=e,s=r,c=\"x\",u=\"y\",f=S,h=A);var E=t[c+\"a\"],L=t[u+\"a\"];p=Math.abs(E.r2c(E.range[1])-E.r2c(E.range[0]));var C=n.getDistanceFunction(a,h,f,function(t){return(h(t)+f(t))/2});if(n.getClosest(d,C,t),!1!==t.index){m||(k=function(t){return Math.min(_(t),t.p-v.bargroupwidth/2)},T=function(t){return Math.max(w(t),t.p+v.bargroupwidth/2)});var P=d[t.index],O=g.base?P.b+P.s:P.s;t[u+\"0\"]=t[u+\"1\"]=L.c2p(P[u],!0),t[u+\"LabelVal\"]=O;var z=v.extents[v.extents.round(P.p)];return t[c+\"0\"]=E.c2p(m?k(P):z[0],!0),t[c+\"1\"]=E.c2p(m?T(P):z[1],!0),t[c+\"LabelVal\"]=P.p,t.labelLabel=l(E,t[c+\"LabelVal\"]),t.valueLabel=l(L,t[u+\"LabelVal\"]),t.spikeDistance=(S(P)+function(t){return M(_(t),w(t))}(P))/2+b-x,t[c+\"Spike\"]=E.c2p(P.p,!0),o(P,g,t),t.hovertemplate=g.hovertemplate,t}}function u(t,e){var r=e.mcc||t.marker.color,n=e.mlcc||t.marker.line.color,a=s(t,e);return i.opacity(r)?r:i.opacity(n)&&a?n:void 0}e.exports={hoverPoints:function(t,e,r,n){var i=c(t,e,r,n);if(i){var o=i.cd,s=o[0].trace,l=o[i.index];return i.color=u(s,l),a.getComponentMethod(\"errorbars\",\"hoverInfo\")(l,s,i),[i]}},hoverOnBars:c,getTraceColor:u}},{\"../../components/color\":592,\"../../components/fx\":630,\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"../../registry\":846,\"./helpers\":862}],864:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,crossTraceDefaults:t(\"./defaults\").crossTraceDefaults,supplyLayoutDefaults:t(\"./layout_defaults\"),calc:t(\"./calc\"),crossTraceCalc:t(\"./cross_trace_calc\").crossTraceCalc,colorbar:t(\"../scatter/marker_colorbar\"),arraysToCalcdata:t(\"./arrays_to_calcdata\"),plot:t(\"./plot\").plot,style:t(\"./style\").style,styleOnSelect:t(\"./style\").styleOnSelect,hoverPoints:t(\"./hover\").hoverPoints,eventData:t(\"./event_data\"),selectPoints:t(\"./select\"),moduleType:\"trace\",name:\"bar\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"bar-like\",\"cartesian\",\"svg\",\"bar\",\"oriented\",\"errorBarsOK\",\"showLegend\",\"zoomScale\"],animatable:!0,meta:{}}},{\"../../plots/cartesian\":776,\"../scatter/marker_colorbar\":1138,\"./arrays_to_calcdata\":855,\"./attributes\":856,\"./calc\":857,\"./cross_trace_calc\":859,\"./defaults\":860,\"./event_data\":861,\"./hover\":863,\"./layout_attributes\":865,\"./layout_defaults\":866,\"./plot\":867,\"./select\":868,\"./style\":870}],865:[function(t,e,r){\"use strict\";e.exports={barmode:{valType:\"enumerated\",values:[\"stack\",\"group\",\"overlay\",\"relative\"],dflt:\"group\",editType:\"calc\"},barnorm:{valType:\"enumerated\",values:[\"\",\"fraction\",\"percent\"],dflt:\"\",editType:\"calc\"},bargap:{valType:\"number\",min:0,max:1,editType:\"calc\"},bargroupgap:{valType:\"number\",min:0,max:1,dflt:0,editType:\"calc\"}}},{}],866:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../plots/cartesian/axes\"),i=t(\"../../lib\"),o=t(\"./layout_attributes\");e.exports=function(t,e,r){function s(r,n){return i.coerce(t,e,o,r,n)}for(var l=!1,c=!1,u=!1,h={},f=s(\"barmode\"),p=0;p<r.length;p++){var d=r[p];if(n.traceIs(d,\"bar\")&&d.visible){if(l=!0,\"group\"===f){var g=d.xaxis+d.yaxis;h[g]&&(u=!0),h[g]=!0}if(d.visible&&\"histogram\"===d.type)\"category\"!==a.getFromId({_fullLayout:e},d[\"v\"===d.orientation?\"xaxis\":\"yaxis\"]).type&&(c=!0)}}l?(\"overlay\"!==f&&s(\"barnorm\"),s(\"bargap\",c&&!u?0:.2),s(\"bargroupgap\")):delete e.barmode}},{\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"../../registry\":846,\"./layout_attributes\":865}],867:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"fast-isnumeric\"),i=t(\"../../lib\"),o=t(\"../../lib/svg_text_utils\"),s=t(\"../../components/color\"),l=t(\"../../components/drawing\"),c=t(\"../../registry\"),u=t(\"../../plots/cartesian/axes\").tickText,h=t(\"./uniform_text\"),f=h.recordMinTextSize,p=h.clearMinTextSize,d=t(\"./style\"),g=t(\"./helpers\"),v=t(\"./constants\"),m=t(\"./attributes\"),y=m.text,x=m.textposition,b=t(\"../../components/fx/helpers\").appendArrayPointValue,_=v.TEXTPAD;function w(t){return t.id}function k(t){if(t.ids)return w}function T(t,e){return t<e?1:-1}function M(t,e,r,n){var a;return!e.uniformtext.mode&&A(r)?(n&&(a=n()),t.transition().duration(r.duration).ease(r.easing).each(\"end\",function(){a&&a()}).each(\"interrupt\",function(){a&&a()})):t}function A(t){return t&&t.duration>0}function S(t){return\"auto\"===t?0:t}function E(t,e){var r=Math.PI/180*e,n=Math.abs(Math.sin(r)),a=Math.abs(Math.cos(r));return{x:t.width*a+t.height*n,y:t.width*n+t.height*a}}function L(t,e,r,n,a,i){var o=!!i.isHorizontal,s=!!i.constrained,l=i.angle||0,c=i.anchor||\"end\",u=\"end\"===c,h=\"start\"===c,f=((i.leftToRight||0)+1)/2,p=1-f,d=a.width,g=a.height,v=Math.abs(e-t),m=Math.abs(n-r),y=v>2*_&&m>2*_?_:0;v-=2*y,m-=2*y;var x=S(l);\"auto\"!==l||d<=v&&g<=m||!(d>v||g>m)||(d>m||g>v)&&d<g==v<m||(x+=90);var b=E(a,x),w=1;s&&(w=Math.min(1,v/b.x,m/b.y));var k=a.left*p+a.right*f,M=(a.top+a.bottom)/2,A=(t+_)*p+(e-_)*f,L=(r+n)/2,C=0,P=0;if(h||u){var O=(o?b.x:b.y)/2,z=o?T(t,e):T(r,n);o?h?(A=t+z*y,C=-z*O):(A=e-z*y,C=z*O):h?(L=r+z*y,P=-z*O):(L=n-z*y,P=z*O)}return{textX:k,textY:M,targetX:A,targetY:L,anchorX:C,anchorY:P,scale:w,rotate:x}}e.exports={plot:function(t,e,r,h,v,m){var w=e.xaxis,C=e.yaxis,P=t._fullLayout;v||(v={mode:P.barmode,norm:P.barmode,gap:P.bargap,groupgap:P.bargroupgap},p(\"bar\",P));var O=i.makeTraceGroups(h,r,\"trace bars\").each(function(r){var c=n.select(this),h=r[0].trace,p=\"waterfall\"===h.type,O=\"funnel\"===h.type,z=\"bar\"===h.type||O,I=0;p&&h.connector.visible&&\"between\"===h.connector.mode&&(I=h.connector.line.width/2);var D=\"h\"===h.orientation,R=i.ensureSingle(c,\"g\",\"points\"),F=k(h),B=R.selectAll(\"g.point\").data(i.identity,F);B.enter().append(\"g\").classed(\"point\",!0),B.exit().remove(),B.each(function(c,p){var k=n.select(this),O=function(t,e,r,n){var a=[],i=[],o=n?e:r,s=n?r:e;return a[0]=o.c2p(t.s0,!0),i[0]=s.c2p(t.p0,!0),a[1]=o.c2p(t.s1,!0),i[1]=s.c2p(t.p1,!0),n?[a,i]:[i,a]}(c,w,C,D),R=O[0][0],F=O[0][1],B=O[1][0],N=O[1][1],j=!(R!==F&&B!==N&&a(R)&&a(F)&&a(B)&&a(N));j&&z&&g.getLineWidth(h,c)&&(D?F-R==0:N-B==0)&&(j=!1),c.isBlank=j,j&&D&&(F=R),j&&!D&&(N=B);var V,U,q=D&&R!==F,H=!D&&B!==N;if(I&&!j&&(D?(R-=T(R,F)*I,F+=T(R,F)*I):(B-=T(B,N)*I,N+=T(B,N)*I)),\"waterfall\"===h.type){if(!j){var G=h[c.dir].marker;V=G.line.width,U=G.color}}else V=g.getLineWidth(h,c),U=c.mc||h.marker.color;var Y=n.round(V/2%1,2);function W(t){return 0===v.gap&&0===v.groupgap?n.round(Math.round(t)-Y,2):t}if(!t._context.staticPlot){var X=s.opacity(U)<1||V>.01?W:function(t,e){return Math.abs(t-e)>=2?W(t):t>e?Math.ceil(t):Math.floor(t)};q&&(R=X(R,F),F=X(F,R)),H&&(B=X(B,N),N=X(N,B))}var Z=M(i.ensureSingle(k,\"path\"),P,v,m);if(Z.style(\"vector-effect\",\"non-scaling-stroke\").attr(\"d\",\"M\"+R+\",\"+B+\"V\"+N+\"H\"+F+\"V\"+B+\"Z\").call(l.setClipUrl,e.layerClipId,t),!P.uniformtext.mode&&A(v)){var J=l.makePointStyleFns(h);l.singlePointStyle(c,Z,h,J,t)}!function(t,e,r,n,a,s,c,h,p,v,m){var w,k=e.xaxis,A=e.yaxis,C=t._fullLayout;function P(e,r,n){var a=i.ensureSingle(e,\"text\").text(r).attr({class:\"bartext bartext-\"+w,\"text-anchor\":\"middle\",\"data-notex\":1}).call(l.font,n).call(o.convertToTspans,t);return a}var O=n[0].trace,z=\"h\"===O.orientation,I=function(t,e,r,n,a){var o,s=e[0].trace;return o=s.texttemplate?function(t,e,r,n,a){var o=e[0].trace,s=i.castOption(o,r,\"texttemplate\");if(!s)return\"\";var l,c,h,f,p=\"waterfall\"===o.type,d=\"funnel\"===o.type;function g(t){return u(f,+t,!0).text}\"h\"===o.orientation?(l=\"y\",c=a,h=\"x\",f=n):(l=\"x\",c=n,h=\"y\",f=a);var v,m=e[r],y={};y.label=m.p,y.labelLabel=y[l+\"Label\"]=(v=m.p,u(c,v,!0).text);var x=i.castOption(o,m.i,\"text\");(0===x||x)&&(y.text=x),y.value=m.s,y.valueLabel=y[h+\"Label\"]=g(m.s);var _={};b(_,o,m.i),p&&(y.delta=+m.rawS||m.s,y.deltaLabel=g(y.delta),y.final=m.v,y.finalLabel=g(y.final),y.initial=y.final-y.delta,y.initialLabel=g(y.initial)),d&&(y.value=m.s,y.valueLabel=g(y.value),y.percentInitial=m.begR,y.percentInitialLabel=i.formatPercent(m.begR),y.percentPrevious=m.difR,y.percentPreviousLabel=i.formatPercent(m.difR),y.percentTotal=m.sumR,y.percenTotalLabel=i.formatPercent(m.sumR));var w=i.castOption(o,m.i,\"customdata\");return w&&(y.customdata=w),i.texttemplateString(s,y,t._d3locale,_,y,o._meta||{})}(t,e,r,n,a):s.textinfo?function(t,e,r,n){var a=t[0].trace,o=\"h\"===a.orientation,s=\"waterfall\"===a.type,l=\"funnel\"===a.type;function c(t){var e=o?r:n;return u(e,+t,!0).text}var h,f,p=a.textinfo,d=t[e],g=p.split(\"+\"),v=[],m=function(t){return-1!==g.indexOf(t)};if(m(\"label\")&&v.push((f=t[e].p,u(o?n:r,f,!0).text)),m(\"text\")&&(0===(h=i.castOption(a,d.i,\"text\"))||h)&&v.push(h),s){var y=+d.rawS||d.s,x=d.v,b=x-y;m(\"initial\")&&v.push(c(b)),m(\"delta\")&&v.push(c(y)),m(\"final\")&&v.push(c(x))}if(l){m(\"value\")&&v.push(c(d.s));var _=0;m(\"percent initial\")&&_++,m(\"percent previous\")&&_++,m(\"percent total\")&&_++;var w=_>1;m(\"percent initial\")&&(h=i.formatPercent(d.begR),w&&(h+=\" of initial\"),v.push(h)),m(\"percent previous\")&&(h=i.formatPercent(d.difR),w&&(h+=\" of previous\"),v.push(h)),m(\"percent total\")&&(h=i.formatPercent(d.sumR),w&&(h+=\" of total\"),v.push(h))}return v.join(\"<br>\")}(e,r,n,a):g.getValue(s.text,r),g.coerceString(y,o)}(C,n,a,k,A);w=function(t,e){var r=g.getValue(t.textposition,e);return g.coerceEnumerated(x,r)}(O,a);var D=\"stack\"===v.mode||\"relative\"===v.mode,R=n[a],F=!D||R._outmost;if(I&&\"none\"!==w&&(!R.isBlank&&s!==c&&h!==p||\"auto\"!==w&&\"inside\"!==w)){var B=C.font,N=d.getBarColor(n[a],O),j=d.getInsideTextFont(O,a,B,N),V=d.getOutsideTextFont(O,a,B),U=r.datum();z?\"log\"===k.type&&U.s0<=0&&(s=k.range[0]<k.range[1]?0:k._length):\"log\"===A.type&&U.s0<=0&&(h=A.range[0]<A.range[1]?A._length:0);var q,H,G,Y,W,X=Math.abs(c-s)-2*_,Z=Math.abs(p-h)-2*_;if(\"outside\"===w&&(F||R.hasB||(w=\"inside\")),\"auto\"===w)if(F){w=\"inside\",W=i.ensureUniformFontSize(t,j),q=P(r,I,W),H=l.bBox(q.node()),G=H.width,Y=H.height;var J=G>0&&Y>0,K=G<=X&&Y<=Z,Q=G<=Z&&Y<=X,$=z?X>=G*(Z/Y):Z>=Y*(X/G);J&&(K||Q||$)?w=\"inside\":(w=\"outside\",q.remove(),q=null)}else w=\"inside\";if(!q){W=i.ensureUniformFontSize(t,\"outside\"===w?V:j);var tt=(q=P(r,I,W)).attr(\"transform\");if(q.attr(\"transform\",\"\"),H=l.bBox(q.node()),G=H.width,Y=H.height,q.attr(\"transform\",tt),G<=0||Y<=0)return void q.remove()}var et,rt,nt=O.textangle;\"outside\"===w?(rt=\"both\"===O.constraintext||\"outside\"===O.constraintext,et=function(t,e,r,n,a,i){var o,s=!!i.isHorizontal,l=!!i.constrained,c=i.angle||0,u=a.width,h=a.height,f=Math.abs(e-t),p=Math.abs(n-r);o=s?p>2*_?_:0:f>2*_?_:0;var d=1;l&&(d=s?Math.min(1,p/h):Math.min(1,f/u));var g=S(c),v=E(a,g),m=(s?v.x:v.y)/2,y=(a.left+a.right)/2,x=(a.top+a.bottom)/2,b=(t+e)/2,w=(r+n)/2,k=0,M=0,A=s?T(e,t):T(r,n);return s?(b=e-A*o,k=A*m):(w=n+A*o,M=-A*m),{textX:y,textY:x,targetX:b,targetY:w,anchorX:k,anchorY:M,scale:d,rotate:g}}(s,c,h,p,H,{isHorizontal:z,constrained:rt,angle:nt})):(rt=\"both\"===O.constraintext||\"inside\"===O.constraintext,et=L(s,c,h,p,H,{isHorizontal:z,constrained:rt,angle:nt,anchor:O.insidetextanchor})),et.fontSize=W.size,f(O.type,et,C),R.transform=et,M(q,C,v,m).attr(\"transform\",i.getTextTransform(et))}else r.select(\"text\").remove()}(t,e,k,r,p,R,F,B,N,v,m),e.layerClipId&&l.hideOutsideRangePoint(c,k.select(\"text\"),w,C,h.xcalendar,h.ycalendar)});var N=!1===h.cliponaxis;l.setClipUrl(c,N?null:e.layerClipId,t)});c.getComponentMethod(\"errorbars\",\"plot\")(t,O,e,v)},toMoveInsideBar:L}},{\"../../components/color\":592,\"../../components/drawing\":613,\"../../components/fx/helpers\":627,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"../../plots/cartesian/axes\":765,\"../../registry\":846,\"./attributes\":856,\"./constants\":858,\"./helpers\":862,\"./style\":870,\"./uniform_text\":872,d3:165,\"fast-isnumeric\":228}],868:[function(t,e,r){\"use strict\";function n(t,e,r,n,a){var i=e.c2p(n?t.s0:t.p0,!0),o=e.c2p(n?t.s1:t.p1,!0),s=r.c2p(n?t.p0:t.s0,!0),l=r.c2p(n?t.p1:t.s1,!0);return a?[(i+o)/2,(s+l)/2]:n?[o,(s+l)/2]:[(i+o)/2,l]}e.exports=function(t,e){var r,a=t.cd,i=t.xaxis,o=t.yaxis,s=a[0].trace,l=\"funnel\"===s.type,c=\"h\"===s.orientation,u=[];if(!1===e)for(r=0;r<a.length;r++)a[r].selected=0;else for(r=0;r<a.length;r++){var h=a[r],f=\"ct\"in h?h.ct:n(h,i,o,c,l);e.contains(f,!1,r,t)?(u.push({pointNumber:r,x:i.c2d(h.x),y:o.c2d(h.y)}),h.selected=1):h.selected=0}return u}},{}],869:[function(t,e,r){\"use strict\";e.exports=i;var n=t(\"../../lib\").distinctVals,a=t(\"../../constants/numerical\").BADNUM;function i(t,e){this.traces=t,this.sepNegVal=e.sepNegVal,this.overlapNoMerge=e.overlapNoMerge;for(var r=1/0,i=[],o=0;o<t.length;o++){for(var s=t[o],l=0;l<s.length;l++){var c=s[l];c.p!==a&&i.push(c.p)}s[0]&&s[0].width1&&(r=Math.min(s[0].width1,r))}this.positions=i;var u=n(i);this.distinctPositions=u.vals,1===u.vals.length&&r!==1/0?this.minDiff=r:this.minDiff=Math.min(u.minDiff,r),this.binWidth=this.minDiff,this.bins={}}i.prototype.put=function(t,e){var r=this.getLabel(t,e),n=this.bins[r]||0;return this.bins[r]=n+e,n},i.prototype.get=function(t,e){var r=this.getLabel(t,e);return this.bins[r]||0},i.prototype.getLabel=function(t,e){return(e<0&&this.sepNegVal?\"v\":\"^\")+(this.overlapNoMerge?t:Math.round(t/this.binWidth))}},{\"../../constants/numerical\":693,\"../../lib\":717}],870:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../components/color\"),i=t(\"../../components/drawing\"),o=t(\"../../lib\"),s=t(\"../../registry\"),l=t(\"./uniform_text\").resizeText,c=t(\"./attributes\"),u=c.textfont,h=c.insidetextfont,f=c.outsidetextfont,p=t(\"./helpers\");function d(t,e,r){i.pointStyle(t.selectAll(\"path\"),e,r),g(t,e,r)}function g(t,e,r){t.selectAll(\"text\").each(function(t){var a=n.select(this),s=o.ensureUniformFontSize(r,v(a,t,e,r));i.font(a,s)})}function v(t,e,r,n){var a=n._fullLayout.font,i=r.textfont;if(t.classed(\"bartext-inside\")){var o=_(e,r);i=y(r,e.i,a,o)}else t.classed(\"bartext-outside\")&&(i=x(r,e.i,a));return i}function m(t,e,r){return b(u,t.textfont,e,r)}function y(t,e,r,n){var i=m(t,e,r);return(void 0===t._input.textfont||void 0===t._input.textfont.color||Array.isArray(t.textfont.color)&&void 0===t.textfont.color[e])&&(i={color:a.contrast(n),family:i.family,size:i.size}),b(h,t.insidetextfont,e,i)}function x(t,e,r){var n=m(t,e,r);return b(f,t.outsidetextfont,e,n)}function b(t,e,r,n){e=e||{};var a=p.getValue(e.family,r),i=p.getValue(e.size,r),o=p.getValue(e.color,r);return{family:p.coerceString(t.family,a,n.family),size:p.coerceNumber(t.size,i,n.size),color:p.coerceColor(t.color,o,n.color)}}function _(t,e){return\"waterfall\"===e.type?e[t.dir].marker.color:t.mc||e.marker.color}e.exports={style:function(t){var e=n.select(t).selectAll(\"g.barlayer\").selectAll(\"g.trace\");l(t,e,\"bar\");var r=e.size(),a=t._fullLayout;e.style(\"opacity\",function(t){return t[0].trace.opacity}).each(function(t){(\"stack\"===a.barmode&&r>1||0===a.bargap&&0===a.bargroupgap&&!t[0].trace.marker.line.width)&&n.select(this).attr(\"shape-rendering\",\"crispEdges\")}),e.selectAll(\"g.points\").each(function(e){d(n.select(this),e[0].trace,t)}),s.getComponentMethod(\"errorbars\",\"style\")(e)},styleTextPoints:g,styleOnSelect:function(t,e,r){var a=e[0].trace;a.selectedpoints?function(t,e,r){i.selectedPointStyle(t.selectAll(\"path\"),e),function(t,e,r){t.each(function(t){var a,s=n.select(this);if(t.selected){a=o.ensureUniformFontSize(r,v(s,t,e,r));var l=e.selected.textfont&&e.selected.textfont.color;l&&(a.color=l),i.font(s,a)}else i.selectedTextStyle(s,e)})}(t.selectAll(\"text\"),e,r)}(r,a,t):(d(r,a,t),s.getComponentMethod(\"errorbars\",\"style\")(r))},getInsideTextFont:y,getOutsideTextFont:x,getBarColor:_,resizeText:l}},{\"../../components/color\":592,\"../../components/drawing\":613,\"../../lib\":717,\"../../registry\":846,\"./attributes\":856,\"./helpers\":862,\"./uniform_text\":872,d3:165}],871:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),a=t(\"../../components/colorscale/helpers\").hasColorscale,i=t(\"../../components/colorscale/defaults\");e.exports=function(t,e,r,o,s){r(\"marker.color\",o),a(t,\"marker\")&&i(t,e,s,r,{prefix:\"marker.\",cLetter:\"c\"}),r(\"marker.line.color\",n.defaultLine),a(t,\"marker.line\")&&i(t,e,s,r,{prefix:\"marker.line.\",cLetter:\"c\"}),r(\"marker.line.width\"),r(\"marker.opacity\"),r(\"selected.marker.color\"),r(\"unselected.marker.color\")}},{\"../../components/color\":592,\"../../components/colorscale/defaults\":602,\"../../components/colorscale/helpers\":603}],872:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\");function i(t){return\"_\"+t+\"Text_minsize\"}e.exports={recordMinTextSize:function(t,e,r){if(r.uniformtext.mode){var n=i(t),a=r.uniformtext.minsize,o=e.scale*e.fontSize;e.hide=o<a,r[n]=r[n]||1/0,e.hide||(r[n]=Math.min(r[n],Math.max(o,a)))}},clearMinTextSize:function(t,e){e[i(t)]=void 0},resizeText:function(t,e,r){var i=t._fullLayout,o=i[\"_\"+r+\"Text_minsize\"];if(o){var s,l=\"hide\"===i.uniformtext.mode;switch(r){case\"funnelarea\":case\"pie\":case\"sunburst\":s=\"g.slice\";break;case\"treemap\":s=\"g.slice, g.pathbar\";break;default:s=\"g.points > g.point\"}e.selectAll(s).each(function(t){var e=t.transform;e&&(e.scale=l&&e.hide?0:o/e.fontSize,n.select(this).select(\"text\").attr(\"transform\",a.getTextTransform(e)))})}}}},{\"../../lib\":717,d3:165}],873:[function(t,e,r){\"use strict\";var n=t(\"../../plots/template_attributes\").hovertemplateAttrs,a=t(\"../../lib/extend\").extendFlat,i=t(\"../scatterpolar/attributes\"),o=t(\"../bar/attributes\");e.exports={r:i.r,theta:i.theta,r0:i.r0,dr:i.dr,theta0:i.theta0,dtheta:i.dtheta,thetaunit:i.thetaunit,base:a({},o.base,{}),offset:a({},o.offset,{}),width:a({},o.width,{}),text:a({},o.text,{}),hovertext:a({},o.hovertext,{}),marker:o.marker,hoverinfo:i.hoverinfo,hovertemplate:n(),selected:o.selected,unselected:o.unselected}},{\"../../lib/extend\":708,\"../../plots/template_attributes\":841,\"../bar/attributes\":856,\"../scatterpolar/attributes\":1193}],874:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/helpers\").hasColorscale,a=t(\"../../components/colorscale/calc\"),i=t(\"../bar/arrays_to_calcdata\"),o=t(\"../bar/cross_trace_calc\").setGroupPositions,s=t(\"../scatter/calc_selection\"),l=t(\"../../registry\").traceIs,c=t(\"../../lib\").extendFlat;e.exports={calc:function(t,e){for(var r=t._fullLayout,o=e.subplot,l=r[o].radialaxis,c=r[o].angularaxis,u=l.makeCalcdata(e,\"r\"),h=c.makeCalcdata(e,\"theta\"),f=e._length,p=new Array(f),d=u,g=h,v=0;v<f;v++)p[v]={p:g[v],s:d[v]};function m(t){var r=e[t];void 0!==r&&(e[\"_\"+t]=Array.isArray(r)?c.makeCalcdata(e,t):c.d2c(r,e.thetaunit))}return\"linear\"===c.type&&(m(\"width\"),m(\"offset\")),n(e,\"marker\")&&a(t,e,{vals:e.marker.color,containerStr:\"marker\",cLetter:\"c\"}),n(e,\"marker.line\")&&a(t,e,{vals:e.marker.line.color,containerStr:\"marker.line\",cLetter:\"c\"}),i(p,e),s(p,e),p},crossTraceCalc:function(t,e,r){for(var n=t.calcdata,a=[],i=0;i<n.length;i++){var s=n[i],u=s[0].trace;!0===u.visible&&l(u,\"bar\")&&u.subplot===r&&a.push(s)}var h=c({},e.radialaxis,{_id:\"x\"}),f=e.angularaxis;o(t,f,h,a,{mode:e.barmode,norm:e.barnorm,gap:e.bargap,groupgap:e.bargroupgap})}}},{\"../../components/colorscale/calc\":600,\"../../components/colorscale/helpers\":603,\"../../lib\":717,\"../../registry\":846,\"../bar/arrays_to_calcdata\":855,\"../bar/cross_trace_calc\":859,\"../scatter/calc_selection\":1122}],875:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../scatterpolar/defaults\").handleRThetaDefaults,i=t(\"../bar/style_defaults\"),o=t(\"./attributes\");e.exports=function(t,e,r,s){function l(r,a){return n.coerce(t,e,o,r,a)}a(t,e,s,l)?(l(\"thetaunit\"),l(\"base\"),l(\"offset\"),l(\"width\"),l(\"text\"),l(\"hovertext\"),l(\"hovertemplate\"),i(t,e,l,r,s),n.coerceSelectionMarkerOpacity(e,l)):e.visible=!1}},{\"../../lib\":717,\"../bar/style_defaults\":871,\"../scatterpolar/defaults\":1195,\"./attributes\":873}],876:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx\"),a=t(\"../../lib\"),i=t(\"../bar/hover\").getTraceColor,o=a.fillText,s=t(\"../scatterpolar/hover\").makeHoverPointText,l=t(\"../../plots/polar/helpers\").isPtInsidePolygon;e.exports=function(t,e,r){var c=t.cd,u=c[0].trace,h=t.subplot,f=h.radialAxis,p=h.angularAxis,d=h.vangles,g=d?l:a.isPtInsideSector,v=t.maxHoverDistance,m=p._period||2*Math.PI,y=Math.abs(f.g2p(Math.sqrt(e*e+r*r))),x=Math.atan2(r,e);f.range[0]>f.range[1]&&(x+=Math.PI);if(n.getClosest(c,function(t){return g(y,x,[t.rp0,t.rp1],[t.thetag0,t.thetag1],d)?v+Math.min(1,Math.abs(t.thetag1-t.thetag0)/m)-1+(t.rp1-y)/(t.rp1-t.rp0)-1:1/0},t),!1!==t.index){var b=c[t.index];t.x0=t.x1=b.ct[0],t.y0=t.y1=b.ct[1];var _=a.extendFlat({},b,{r:b.s,theta:b.p});return o(b,u,t),s(_,u,h,t),t.hovertemplate=u.hovertemplate,t.color=i(u,b),t.xLabelVal=t.yLabelVal=void 0,b.s<0&&(t.idealAlign=\"left\"),[t]}}},{\"../../components/fx\":630,\"../../lib\":717,\"../../plots/polar/helpers\":828,\"../bar/hover\":863,\"../scatterpolar/hover\":1197}],877:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"barpolar\",basePlotModule:t(\"../../plots/polar\"),categories:[\"polar\",\"bar\",\"showLegend\"],attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyDefaults:t(\"./defaults\"),supplyLayoutDefaults:t(\"./layout_defaults\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\"),colorbar:t(\"../scatter/marker_colorbar\"),formatLabels:t(\"../scatterpolar/format_labels\"),style:t(\"../bar/style\").style,styleOnSelect:t(\"../bar/style\").styleOnSelect,hoverPoints:t(\"./hover\"),selectPoints:t(\"../bar/select\"),meta:{}}},{\"../../plots/polar\":829,\"../bar/select\":868,\"../bar/style\":870,\"../scatter/marker_colorbar\":1138,\"../scatterpolar/format_labels\":1196,\"./attributes\":873,\"./calc\":874,\"./defaults\":875,\"./hover\":876,\"./layout_attributes\":878,\"./layout_defaults\":879,\"./plot\":880}],878:[function(t,e,r){\"use strict\";e.exports={barmode:{valType:\"enumerated\",values:[\"stack\",\"overlay\"],dflt:\"stack\",editType:\"calc\"},bargap:{valType:\"number\",dflt:.1,min:0,max:1,editType:\"calc\"}}},{}],879:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./layout_attributes\");e.exports=function(t,e,r){var i,o={};function s(r,o){return n.coerce(t[i]||{},e[i],a,r,o)}for(var l=0;l<r.length;l++){var c=r[l];\"barpolar\"===c.type&&!0===c.visible&&(o[i=c.subplot]||(s(\"barmode\"),s(\"bargap\"),o[i]=1))}}},{\"../../lib\":717,\"./layout_attributes\":878}],880:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"fast-isnumeric\"),i=t(\"../../lib\"),o=t(\"../../components/drawing\"),s=t(\"../../plots/polar/helpers\");e.exports=function(t,e,r){var l=e.xaxis,c=e.yaxis,u=e.radialAxis,h=e.angularAxis,f=function(t){var e=t.cxx,r=t.cyy;if(t.vangles)return function(n,a,o,l){var c,u;i.angleDelta(o,l)>0?(c=o,u=l):(c=l,u=o);var h=s.findEnclosingVertexAngles(c,t.vangles)[0],f=s.findEnclosingVertexAngles(u,t.vangles)[1],p=[h,(c+u)/2,f];return s.pathPolygonAnnulus(n,a,c,u,p,e,r)};return function(t,n,a,o){return i.pathAnnulus(t,n,a,o,e,r)}}(e),p=e.layers.frontplot.select(\"g.barlayer\");i.makeTraceGroups(p,r,\"trace bars\").each(function(){var r=n.select(this),s=i.ensureSingle(r,\"g\",\"points\").selectAll(\"g.point\").data(i.identity);s.enter().append(\"g\").style(\"vector-effect\",\"non-scaling-stroke\").style(\"stroke-miterlimit\",2).classed(\"point\",!0),s.exit().remove(),s.each(function(t){var e,r=n.select(this),o=t.rp0=u.c2p(t.s0),s=t.rp1=u.c2p(t.s1),p=t.thetag0=h.c2g(t.p0),d=t.thetag1=h.c2g(t.p1);if(a(o)&&a(s)&&a(p)&&a(d)&&o!==s&&p!==d){var g=u.c2g(t.s1),v=(p+d)/2;t.ct=[l.c2p(g*Math.cos(v)),c.c2p(g*Math.sin(v))],e=f(o,s,p,d)}else e=\"M0,0Z\";i.ensureSingle(r,\"path\").attr(\"d\",e)}),o.setClipUrl(r,e._hasClipOnAxisFalse?e.clipIds.forTraces:null,t)})}},{\"../../components/drawing\":613,\"../../lib\":717,\"../../plots/polar/helpers\":828,d3:165,\"fast-isnumeric\":228}],881:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),a=t(\"../bar/attributes\"),i=t(\"../../components/color/attributes\"),o=t(\"../../plots/template_attributes\").hovertemplateAttrs,s=t(\"../../lib/extend\").extendFlat,l=n.marker,c=l.line;e.exports={y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},x0:{valType:\"any\",editType:\"calc+clearAxisTypes\"},y0:{valType:\"any\",editType:\"calc+clearAxisTypes\"},dx:{valType:\"number\",editType:\"calc\"},dy:{valType:\"number\",editType:\"calc\"},name:{valType:\"string\",editType:\"calc+clearAxisTypes\"},q1:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},median:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},q3:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},lowerfence:{valType:\"data_array\",editType:\"calc\"},upperfence:{valType:\"data_array\",editType:\"calc\"},notched:{valType:\"boolean\",editType:\"calc\"},notchwidth:{valType:\"number\",min:0,max:.5,dflt:.25,editType:\"calc\"},notchspan:{valType:\"data_array\",editType:\"calc\"},boxpoints:{valType:\"enumerated\",values:[\"all\",\"outliers\",\"suspectedoutliers\",!1],editType:\"calc\"},jitter:{valType:\"number\",min:0,max:1,editType:\"calc\"},pointpos:{valType:\"number\",min:-2,max:2,editType:\"calc\"},boxmean:{valType:\"enumerated\",values:[!0,\"sd\",!1],editType:\"calc\"},mean:{valType:\"data_array\",editType:\"calc\"},sd:{valType:\"data_array\",editType:\"calc\"},orientation:{valType:\"enumerated\",values:[\"v\",\"h\"],editType:\"calc+clearAxisTypes\"},quartilemethod:{valType:\"enumerated\",values:[\"linear\",\"exclusive\",\"inclusive\"],dflt:\"linear\",editType:\"calc\"},width:{valType:\"number\",min:0,dflt:0,editType:\"calc\"},marker:{outliercolor:{valType:\"color\",dflt:\"rgba(0, 0, 0, 0)\",editType:\"style\"},symbol:s({},l.symbol,{arrayOk:!1,editType:\"plot\"}),opacity:s({},l.opacity,{arrayOk:!1,dflt:1,editType:\"style\"}),size:s({},l.size,{arrayOk:!1,editType:\"calc\"}),color:s({},l.color,{arrayOk:!1,editType:\"style\"}),line:{color:s({},c.color,{arrayOk:!1,dflt:i.defaultLine,editType:\"style\"}),width:s({},c.width,{arrayOk:!1,dflt:0,editType:\"style\"}),outliercolor:{valType:\"color\",editType:\"style\"},outlierwidth:{valType:\"number\",min:0,dflt:1,editType:\"style\"},editType:\"style\"},editType:\"plot\"},line:{color:{valType:\"color\",editType:\"style\"},width:{valType:\"number\",min:0,dflt:2,editType:\"style\"},editType:\"plot\"},fillcolor:n.fillcolor,whiskerwidth:{valType:\"number\",min:0,max:1,dflt:.5,editType:\"calc\"},offsetgroup:a.offsetgroup,alignmentgroup:a.alignmentgroup,selected:{marker:n.selected.marker,editType:\"style\"},unselected:{marker:n.unselected.marker,editType:\"style\"},text:s({},n.text,{}),hovertext:s({},n.hovertext,{}),hovertemplate:o({}),hoveron:{valType:\"flaglist\",flags:[\"boxes\",\"points\"],dflt:\"boxes+points\",editType:\"style\"}}},{\"../../components/color/attributes\":591,\"../../lib/extend\":708,\"../../plots/template_attributes\":841,\"../bar/attributes\":856,\"../scatter/attributes\":1120}],882:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../plots/cartesian/axes\"),i=t(\"../../lib\"),o=t(\"../../constants/numerical\").BADNUM,s=i._;e.exports=function(t,e){var r,l,m,y,x,b,_=t._fullLayout,w=a.getFromId(t,e.xaxis||\"x\"),k=a.getFromId(t,e.yaxis||\"y\"),T=[],M=\"violin\"===e.type?\"_numViolins\":\"_numBoxes\";\"h\"===e.orientation?(m=w,y=\"x\",x=k,b=\"y\"):(m=k,y=\"y\",x=w,b=\"x\");var A,S,E,L,C,P,O=function(t,e,r,a){var o,s=e+\"0\"in t,l=\"d\"+e in t;if(e in t||s&&l)return r.makeCalcdata(t,e);o=s?t[e+\"0\"]:\"name\"in t&&(\"category\"===r.type||n(t.name)&&-1!==[\"linear\",\"log\"].indexOf(r.type)||i.isDateTime(t.name)&&\"date\"===r.type)?t.name:a;for(var c=\"multicategory\"===r.type?r.r2c_just_indices(o):r.d2c(o,0,t[e+\"calendar\"]),u=t._length,h=new Array(u),f=0;f<u;f++)h[f]=c;return h}(e,b,x,_[M]),z=i.distinctVals(O),I=z.vals,D=z.minDiff/2,R=\"all\"===(e.boxpoints||e.points)?i.identity:function(t){return t.v<A.lf||t.v>A.uf};if(e._hasPreCompStats){var F=e[y],B=function(t){return m.d2c((e[t]||[])[r])},N=1/0,j=-1/0;for(r=0;r<e._length;r++){var V=O[r];if(n(V)){if((A={}).pos=A[b]=V,A.q1=B(\"q1\"),A.med=B(\"median\"),A.q3=B(\"q3\"),S=[],F&&i.isArrayOrTypedArray(F[r]))for(l=0;l<F[r].length;l++)(P=m.d2c(F[r][l]))!==o&&(c(C={v:P,i:[r,l]},e,[r,l]),S.push(C));if(A.pts=S.sort(u),L=(E=A[y]=S.map(h)).length,A.med!==o&&A.q1!==o&&A.q3!==o&&A.med>=A.q1&&A.q3>=A.med){var U=B(\"lowerfence\");A.lf=U!==o&&U<=A.q1?U:f(A,E,L);var q=B(\"upperfence\");A.uf=q!==o&&q>=A.q3?q:p(A,E,L);var H=B(\"mean\");A.mean=H!==o?H:L?i.mean(E,L):(A.q1+A.q3)/2;var G=B(\"sd\");A.sd=H!==o&&G>=0?G:L?i.stdev(E,L,A.mean):A.q3-A.q1,A.lo=d(A),A.uo=g(A);var Y=B(\"notchspan\");Y=Y!==o&&Y>0?Y:v(A,L),A.ln=A.med-Y,A.un=A.med+Y;var W=A.lf,X=A.uf;e.boxpoints&&E.length&&(W=Math.min(W,E[0]),X=Math.max(X,E[L-1])),e.notched&&(W=Math.min(W,A.ln),X=Math.max(X,A.un)),A.min=W,A.max=X}else{var Z;i.warn([\"Invalid input - make sure that q1 <= median <= q3\",\"q1 = \"+A.q1,\"median = \"+A.med,\"q3 = \"+A.q3].join(\"\\n\")),Z=A.med!==o?A.med:A.q1!==o?A.q3!==o?(A.q1+A.q3)/2:A.q1:A.q3!==o?A.q3:0,A.med=Z,A.q1=A.q3=Z,A.lf=A.uf=Z,A.mean=A.sd=Z,A.ln=A.un=Z,A.min=A.max=Z}N=Math.min(N,A.min),j=Math.max(j,A.max),A.pts2=S.filter(R),T.push(A)}}e._extremes[m._id]=a.findExtremes(m,[N,j],{padded:!0})}else{var J=m.makeCalcdata(e,y),K=function(t,e){for(var r=t.length,n=new Array(r+1),a=0;a<r;a++)n[a]=t[a]-e;return n[r]=t[r-1]+e,n}(I,D),Q=I.length,$=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=[];return e}(Q);for(r=0;r<e._length;r++)if(P=J[r],n(P)){var tt=i.findBin(O[r],K);tt>=0&&tt<Q&&(c(C={v:P,i:r},e,r),$[tt].push(C))}var et=1/0,rt=-1/0,nt=e.quartilemethod,at=\"exclusive\"===nt,it=\"inclusive\"===nt;for(r=0;r<Q;r++)if($[r].length>0){var ot,st;if((A={}).pos=A[b]=I[r],S=A.pts=$[r].sort(u),L=(E=A[y]=S.map(h)).length,A.min=E[0],A.max=E[L-1],A.mean=i.mean(E,L),A.sd=i.stdev(E,L,A.mean),A.med=i.interp(E,.5),L%2&&(at||it))at?(ot=E.slice(0,L/2),st=E.slice(L/2+1)):it&&(ot=E.slice(0,L/2+1),st=E.slice(L/2)),A.q1=i.interp(ot,.5),A.q3=i.interp(st,.5);else A.q1=i.interp(E,.25),A.q3=i.interp(E,.75);A.lf=f(A,E,L),A.uf=p(A,E,L),A.lo=d(A),A.uo=g(A);var lt=v(A,L);A.ln=A.med-lt,A.un=A.med+lt,et=Math.min(et,A.ln),rt=Math.max(rt,A.un),A.pts2=S.filter(R),T.push(A)}e._extremes[m._id]=a.findExtremes(m,e.notched?J.concat([et,rt]):J,{padded:!0})}return function(t,e){if(i.isArrayOrTypedArray(e.selectedpoints))for(var r=0;r<t.length;r++){for(var n=t[r].pts||[],a={},o=0;o<n.length;o++)a[n[o].i]=o;i.tagSelected(n,e,a)}}(T,e),T.length>0?(T[0].t={num:_[M],dPos:D,posLetter:b,valLetter:y,labels:{med:s(t,\"median:\"),min:s(t,\"min:\"),q1:s(t,\"q1:\"),q3:s(t,\"q3:\"),max:s(t,\"max:\"),mean:\"sd\"===e.boxmean?s(t,\"mean \\xb1 \\u03c3:\"):s(t,\"mean:\"),lf:s(t,\"lower fence:\"),uf:s(t,\"upper fence:\")}},_[M]++,T):[{t:{empty:!0}}]};var l={text:\"tx\",hovertext:\"htx\"};function c(t,e,r){for(var n in l)i.isArrayOrTypedArray(e[n])&&(Array.isArray(r)?i.isArrayOrTypedArray(e[n][r[0]])&&(t[l[n]]=e[n][r[0]][r[1]]):t[l[n]]=e[n][r])}function u(t,e){return t.v-e.v}function h(t){return t.v}function f(t,e,r){return 0===r?t.q1:Math.min(t.q1,e[Math.min(i.findBin(2.5*t.q1-1.5*t.q3,e,!0)+1,r-1)])}function p(t,e,r){return 0===r?t.q3:Math.max(t.q3,e[Math.max(i.findBin(2.5*t.q3-1.5*t.q1,e),0)])}function d(t){return 4*t.q1-3*t.q3}function g(t){return 4*t.q3-3*t.q1}function v(t,e){return 0===e?0:1.57*(t.q3-t.q1)/Math.sqrt(e)}},{\"../../constants/numerical\":693,\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"fast-isnumeric\":228}],883:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\"),a=t(\"../../lib\"),i=t(\"../../plots/cartesian/axis_ids\").getAxisGroup,o=[\"v\",\"h\"];function s(t,e,r,o){var s,l,c,u=e.calcdata,h=e._fullLayout,f=o._id,p=f.charAt(0),d=[],g=0;for(s=0;s<r.length;s++)for(c=u[r[s]],l=0;l<c.length;l++)d.push(o.c2l(c[l].pos,!0)),g+=(c[l].pts2||[]).length;if(d.length){var v=a.distinctVals(d),m=v.minDiff/2;n.minDtick(o,v.minDiff,v.vals[0],!0);var y=h[\"violin\"===t?\"_numViolins\":\"_numBoxes\"],x=\"group\"===h[t+\"mode\"]&&y>1,b=1-h[t+\"gap\"],_=1-h[t+\"groupgap\"];for(s=0;s<r.length;s++){var w,k,T,M,A,S,E=(c=u[r[s]])[0].trace,L=c[0].t,C=E.width,P=E.side;if(C)w=k=M=C/2,T=0;else if(w=m,x){var O=i(h,o._id)+E.orientation,z=(h._alignmentOpts[O]||{})[E.alignmentgroup]||{},I=Object.keys(z.offsetGroups||{}).length,D=I||y;k=w*b*_/D,T=2*w*(((I?E._offsetIndex:L.num)+.5)/D-.5)*b,M=w*b/D}else k=w*b*_,T=0,M=w;L.dPos=w,L.bPos=T,L.bdPos=k,L.wHover=M;var R,F,B,N,j,V,U=T+k,q=Boolean(C);if(\"positive\"===P?(A=w*(C?1:.5),R=U,S=R=T):\"negative\"===P?(A=R=T,S=w*(C?1:.5),F=U):(A=S=w,R=F=U),(E.boxpoints||E.points)&&g>0){var H=E.pointpos,G=E.jitter,Y=E.marker.size/2,W=0;H+G>=0&&((W=U*(H+G))>A?(q=!0,j=Y,B=W):W>R&&(j=Y,B=A)),W<=A&&(B=A);var X=0;H-G<=0&&((X=-U*(H-G))>S?(q=!0,V=Y,N=X):X>F&&(V=Y,N=S)),X<=S&&(N=S)}else B=A,N=S;var Z=new Array(c.length);for(l=0;l<c.length;l++)Z[l]=c[l].pos;E._extremes[f]=n.findExtremes(o,Z,{padded:q,vpadminus:N,vpadplus:B,vpadLinearized:!0,ppadminus:{x:V,y:j}[p],ppadplus:{x:j,y:V}[p]})}}}e.exports={crossTraceCalc:function(t,e){for(var r=t.calcdata,n=e.xaxis,a=e.yaxis,i=0;i<o.length;i++){for(var l=o[i],c=\"h\"===l?a:n,u=[],h=0;h<r.length;h++){var f=r[h],p=f[0].t,d=f[0].trace;!0!==d.visible||\"box\"!==d.type&&\"candlestick\"!==d.type||p.empty||(d.orientation||\"v\")!==l||d.xaxis!==n._id||d.yaxis!==a._id||u.push(h)}s(\"box\",t,u,c)}},setPositionOffset:s}},{\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"../../plots/cartesian/axis_ids\":768}],884:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../registry\"),i=t(\"../../components/color\"),o=t(\"../bar/defaults\").handleGroupingDefaults,s=t(\"../../plots/cartesian/axis_autotype\"),l=t(\"./attributes\");function c(t,e,r,i){function o(t){var e=0;return t&&t.length&&(e+=1,n.isArrayOrTypedArray(t[0])&&t[0].length&&(e+=1)),e}function c(e){return n.validate(t[e],l[e])}var u,h=r(\"y\"),f=r(\"x\");if(\"box\"===e.type){var p=r(\"q1\"),d=r(\"median\"),g=r(\"q3\");e._hasPreCompStats=p&&p.length&&d&&d.length&&g&&g.length,u=Math.min(n.minRowLength(p),n.minRowLength(d),n.minRowLength(g))}var v,m,y=o(h),x=o(f),b=y&&n.minRowLength(h),_=x&&n.minRowLength(f);if(e._hasPreCompStats)switch(String(x)+String(y)){case\"00\":var w=c(\"x0\")||c(\"dx\");v=(c(\"y0\")||c(\"dy\"))&&!w?\"h\":\"v\",m=u;break;case\"10\":v=\"v\",m=Math.min(u,_);break;case\"20\":v=\"h\",m=Math.min(u,f.length);break;case\"01\":v=\"h\",m=Math.min(u,b);break;case\"02\":v=\"v\",m=Math.min(u,h.length);break;case\"12\":v=\"v\",m=Math.min(u,_,h.length);break;case\"21\":v=\"h\",m=Math.min(u,f.length,b);break;case\"11\":m=0;break;case\"22\":var k,T=!1;for(k=0;k<f.length;k++)if(\"category\"===s(f[k])){T=!0;break}if(T)v=\"v\",m=Math.min(u,_,h.length);else{for(k=0;k<h.length;k++)if(\"category\"===s(h[k])){T=!0;break}T?(v=\"h\",m=Math.min(u,f.length,b)):(v=\"v\",m=Math.min(u,_,h.length))}}else y>0?(v=\"v\",m=x>0?Math.min(_,b):Math.min(b)):x>0?(v=\"h\",m=Math.min(_)):m=0;if(m){e._length=m;var M=r(\"orientation\",v);e._hasPreCompStats?\"v\"===M&&0===x?(r(\"x0\",0),r(\"dx\",1)):\"h\"===M&&0===y&&(r(\"y0\",0),r(\"dy\",1)):\"v\"===M&&0===x?r(\"x0\"):\"h\"===M&&0===y&&r(\"y0\"),a.getComponentMethod(\"calendars\",\"handleTraceDefaults\")(t,e,[\"x\",\"y\"],i)}else e.visible=!1}function u(t,e,r,a){var i=a.prefix,o=n.coerce2(t,e,l,\"marker.outliercolor\"),s=r(\"marker.line.outliercolor\"),c=\"outliers\";e._hasPreCompStats?c=\"all\":(o||s)&&(c=\"suspectedoutliers\");var u=r(i+\"points\",c);u?(r(\"jitter\",\"all\"===u?.3:0),r(\"pointpos\",\"all\"===u?-1.5:0),r(\"marker.symbol\"),r(\"marker.opacity\"),r(\"marker.size\"),r(\"marker.color\",e.line.color),r(\"marker.line.color\"),r(\"marker.line.width\"),\"suspectedoutliers\"===u&&(r(\"marker.line.outliercolor\",e.marker.color),r(\"marker.line.outlierwidth\")),r(\"selected.marker.color\"),r(\"unselected.marker.color\"),r(\"selected.marker.size\"),r(\"unselected.marker.size\"),r(\"text\"),r(\"hovertext\")):delete e.marker;var h=r(\"hoveron\");\"all\"!==h&&-1===h.indexOf(\"points\")||r(\"hovertemplate\"),n.coerceSelectionMarkerOpacity(e,r)}e.exports={supplyDefaults:function(t,e,r,a){function o(r,a){return n.coerce(t,e,l,r,a)}if(c(t,e,o,a),!1!==e.visible){var s=e._hasPreCompStats;s&&(o(\"lowerfence\"),o(\"upperfence\")),o(\"line.color\",(t.marker||{}).color||r),o(\"line.width\"),o(\"fillcolor\",i.addOpacity(e.line.color,.5));var h=!1;if(s){var f=o(\"mean\"),p=o(\"sd\");f&&f.length&&(h=!0,p&&p.length&&(h=\"sd\"))}o(\"boxmean\",h),o(\"whiskerwidth\"),o(\"width\"),o(\"quartilemethod\");var d=!1;if(s){var g=o(\"notchspan\");g&&g.length&&(d=!0)}else n.validate(t.notchwidth,l.notchwidth)&&(d=!0);o(\"notched\",d)&&o(\"notchwidth\"),u(t,e,o,{prefix:\"box\"})}},crossTraceDefaults:function(t,e){var r,a;function i(t){return n.coerce(a._input,a,l,t)}for(var s=0;s<t.length;s++){var c=(a=t[s]).type;\"box\"!==c&&\"violin\"!==c||(r=a._input,\"group\"===e[c+\"mode\"]&&o(r,a,e,i))}},handleSampleDefaults:c,handlePointsDefaults:u}},{\"../../components/color\":592,\"../../lib\":717,\"../../plots/cartesian/axis_autotype\":766,\"../../registry\":846,\"../bar/defaults\":860,\"./attributes\":881}],885:[function(t,e,r){\"use strict\";e.exports=function(t,e){return e.hoverOnBox&&(t.hoverOnBox=e.hoverOnBox),\"xVal\"in e&&(t.x=e.xVal),\"yVal\"in e&&(t.y=e.yVal),e.xa&&(t.xaxis=e.xa),e.ya&&(t.yaxis=e.ya),t}},{}],886:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\"),a=t(\"../../lib\"),i=t(\"../../components/fx\"),o=t(\"../../components/color\"),s=a.fillText;function l(t,e,r,s){var l,c,u,h,f,p,d,g,v,m,y,x,b,_,w=t.cd,k=t.xa,T=t.ya,M=w[0].trace,A=w[0].t,S=\"violin\"===M.type,E=[],L=A.bdPos,C=A.wHover,P=function(t){return u.c2l(t.pos)+A.bPos-u.c2l(p)};S&&\"both\"!==M.side?(\"positive\"===M.side&&(v=function(t){var e=P(t);return i.inbox(e,e+C,m)},x=L,b=0),\"negative\"===M.side&&(v=function(t){var e=P(t);return i.inbox(e-C,e,m)},x=0,b=L)):(v=function(t){var e=P(t);return i.inbox(e-C,e+C,m)},x=b=L),_=S?function(t){return i.inbox(t.span[0]-f,t.span[1]-f,m)}:function(t){return i.inbox(t.min-f,t.max-f,m)},\"h\"===M.orientation?(f=e,p=r,d=_,g=v,l=\"y\",u=T,c=\"x\",h=k):(f=r,p=e,d=v,g=_,l=\"x\",u=k,c=\"y\",h=T);var O=Math.min(1,L/Math.abs(u.r2c(u.range[1])-u.r2c(u.range[0])));function z(t){return(d(t)+g(t))/2}m=t.maxHoverDistance-O,y=t.maxSpikeDistance-O;var I=i.getDistanceFunction(s,d,g,z);if(i.getClosest(w,I,t),!1===t.index)return[];var D=w[t.index],R=M.line.color,F=(M.marker||{}).color;o.opacity(R)&&M.line.width?t.color=R:o.opacity(F)&&M.boxpoints?t.color=F:t.color=M.fillcolor,t[l+\"0\"]=u.c2p(D.pos+A.bPos-b,!0),t[l+\"1\"]=u.c2p(D.pos+A.bPos+x,!0),t[l+\"LabelVal\"]=D.pos;var B=l+\"Spike\";t.spikeDistance=z(D)*y/m,t[B]=u.c2p(D.pos,!0);var N={},j=[\"med\",\"q1\",\"q3\",\"min\",\"max\"];(M.boxmean||(M.meanline||{}).visible)&&j.push(\"mean\"),(M.boxpoints||M.points)&&j.push(\"lf\",\"uf\");for(var V=0;V<j.length;V++){var U=j[V];if(U in D&&!(D[U]in N)){N[D[U]]=!0;var q=D[U],H=h.c2p(q,!0),G=a.extendFlat({},t);G.attr=U,G[c+\"0\"]=G[c+\"1\"]=H,G[c+\"LabelVal\"]=q,G[c+\"Label\"]=(A.labels?A.labels[U]+\" \":\"\")+n.hoverLabelText(h,q),G.hoverOnBox=!0,\"mean\"===U&&\"sd\"in D&&\"sd\"===M.boxmean&&(G[c+\"err\"]=D.sd),t.name=\"\",t.spikeDistance=void 0,t[B]=void 0,G.hovertemplate=!1,E.push(G)}}return E}function c(t,e,r){for(var n,o,l,c=t.cd,u=t.xa,h=t.ya,f=c[0].trace,p=u.c2p(e),d=h.c2p(r),g=i.quadrature(function(t){var e=Math.max(3,t.mrc||0);return Math.max(Math.abs(u.c2p(t.x)-p)-e,1-3/e)},function(t){var e=Math.max(3,t.mrc||0);return Math.max(Math.abs(h.c2p(t.y)-d)-e,1-3/e)}),v=!1,m=0;m<c.length;m++){o=c[m];for(var y=0;y<(o.pts||[]).length;y++){var x=g(l=o.pts[y]);x<=t.distance&&(t.distance=x,v=[m,y])}}if(!v)return!1;l=(o=c[v[0]]).pts[v[1]];var b,_=u.c2p(l.x,!0),w=h.c2p(l.y,!0),k=l.mrc||1;return n=a.extendFlat({},t,{index:l.i,color:(f.marker||{}).color,name:f.name,x0:_-k,x1:_+k,y0:w-k,y1:w+k,spikeDistance:t.distance,hovertemplate:f.hovertemplate}),\"h\"===f.orientation?(b=h,n.xLabelVal=l.x,n.yLabelVal=o.pos):(b=u,n.xLabelVal=o.pos,n.yLabelVal=l.y),n[b._id.charAt(0)+\"Spike\"]=b.c2p(o.pos,!0),s(l,f,n),n}e.exports={hoverPoints:function(t,e,r,n){var a,i=t.cd[0].trace.hoveron,o=[];return-1!==i.indexOf(\"boxes\")&&(o=o.concat(l(t,e,r,n))),-1!==i.indexOf(\"points\")&&(a=c(t,e,r)),\"closest\"===n?a?[a]:o:a?(o.push(a),o):o},hoverOnBoxes:l,hoverOnPoints:c}},{\"../../components/color\":592,\"../../components/fx\":630,\"../../lib\":717,\"../../plots/cartesian/axes\":765}],887:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,crossTraceDefaults:t(\"./defaults\").crossTraceDefaults,supplyLayoutDefaults:t(\"./layout_defaults\").supplyLayoutDefaults,calc:t(\"./calc\"),crossTraceCalc:t(\"./cross_trace_calc\").crossTraceCalc,plot:t(\"./plot\").plot,style:t(\"./style\").style,styleOnSelect:t(\"./style\").styleOnSelect,hoverPoints:t(\"./hover\").hoverPoints,eventData:t(\"./event_data\"),selectPoints:t(\"./select\"),moduleType:\"trace\",name:\"box\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"cartesian\",\"svg\",\"symbols\",\"oriented\",\"box-violin\",\"showLegend\",\"boxLayout\",\"zoomScale\"],meta:{}}},{\"../../plots/cartesian\":776,\"./attributes\":881,\"./calc\":882,\"./cross_trace_calc\":883,\"./defaults\":884,\"./event_data\":885,\"./hover\":886,\"./layout_attributes\":888,\"./layout_defaults\":889,\"./plot\":890,\"./select\":891,\"./style\":892}],888:[function(t,e,r){\"use strict\";e.exports={boxmode:{valType:\"enumerated\",values:[\"group\",\"overlay\"],dflt:\"overlay\",editType:\"calc\"},boxgap:{valType:\"number\",min:0,max:1,dflt:.3,editType:\"calc\"},boxgroupgap:{valType:\"number\",min:0,max:1,dflt:.3,editType:\"calc\"}}},{}],889:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../lib\"),i=t(\"./layout_attributes\");function o(t,e,r,a,i){for(var o=i+\"Layout\",s=!1,l=0;l<r.length;l++){var c=r[l];if(n.traceIs(c,o)){s=!0;break}}s&&(a(i+\"mode\"),a(i+\"gap\"),a(i+\"groupgap\"))}e.exports={supplyLayoutDefaults:function(t,e,r){o(0,0,r,function(r,n){return a.coerce(t,e,i,r,n)},\"box\")},_supply:o}},{\"../../lib\":717,\"../../registry\":846,\"./layout_attributes\":888}],890:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\"),i=t(\"../../components/drawing\"),o=5,s=.01;function l(t,e,r,i){var o,s,l=e.pos,c=e.val,u=i.bPos,h=i.wdPos||0,f=i.bPosPxOffset||0,p=r.whiskerwidth||0,d=r.notched||!1,g=d?1-2*r.notchwidth:1;Array.isArray(i.bdPos)?(o=i.bdPos[0],s=i.bdPos[1]):(o=i.bdPos,s=i.bdPos);var v=t.selectAll(\"path.box\").data(\"violin\"!==r.type||r.box.visible?a.identity:[]);v.enter().append(\"path\").style(\"vector-effect\",\"non-scaling-stroke\").attr(\"class\",\"box\"),v.exit().remove(),v.each(function(t){if(t.empty)return\"M0,0Z\";var e=l.c2l(t.pos+u,!0),i=l.l2p(e)+f,v=l.l2p(e-o)+f,m=l.l2p(e+s)+f,y=l.l2p(e-h)+f,x=l.l2p(e+h)+f,b=l.l2p(e-o*g)+f,_=l.l2p(e+s*g)+f,w=c.c2p(t.q1,!0),k=c.c2p(t.q3,!0),T=a.constrain(c.c2p(t.med,!0),Math.min(w,k)+1,Math.max(w,k)-1),M=void 0===t.lf||!1===r.boxpoints,A=c.c2p(M?t.min:t.lf,!0),S=c.c2p(M?t.max:t.uf,!0),E=c.c2p(t.ln,!0),L=c.c2p(t.un,!0);\"h\"===r.orientation?n.select(this).attr(\"d\",\"M\"+T+\",\"+b+\"V\"+_+\"M\"+w+\",\"+v+\"V\"+m+(d?\"H\"+E+\"L\"+T+\",\"+_+\"L\"+L+\",\"+m:\"\")+\"H\"+k+\"V\"+v+(d?\"H\"+L+\"L\"+T+\",\"+b+\"L\"+E+\",\"+v:\"\")+\"ZM\"+w+\",\"+i+\"H\"+A+\"M\"+k+\",\"+i+\"H\"+S+(0===p?\"\":\"M\"+A+\",\"+y+\"V\"+x+\"M\"+S+\",\"+y+\"V\"+x)):n.select(this).attr(\"d\",\"M\"+b+\",\"+T+\"H\"+_+\"M\"+v+\",\"+w+\"H\"+m+(d?\"V\"+E+\"L\"+_+\",\"+T+\"L\"+m+\",\"+L:\"\")+\"V\"+k+\"H\"+v+(d?\"V\"+L+\"L\"+b+\",\"+T+\"L\"+v+\",\"+E:\"\")+\"ZM\"+i+\",\"+w+\"V\"+A+\"M\"+i+\",\"+k+\"V\"+S+(0===p?\"\":\"M\"+y+\",\"+A+\"H\"+x+\"M\"+y+\",\"+S+\"H\"+x))})}function c(t,e,r,n){var l=e.x,c=e.y,u=n.bdPos,h=n.bPos,f=r.boxpoints||r.points;a.seedPseudoRandom();var p=t.selectAll(\"g.points\").data(f?function(t){return t.forEach(function(t){t.t=n,t.trace=r}),t}:[]);p.enter().append(\"g\").attr(\"class\",\"points\"),p.exit().remove();var d=p.selectAll(\"path\").data(function(t){var e,n,i=t.pts2,l=Math.max((t.max-t.min)/10,t.q3-t.q1),c=1e-9*l,p=l*s,d=[],g=0;if(r.jitter){if(0===l)for(g=1,d=new Array(i.length),e=0;e<i.length;e++)d[e]=1;else for(e=0;e<i.length;e++){var v=Math.max(0,e-o),m=i[v].v,y=Math.min(i.length-1,e+o),x=i[y].v;\"all\"!==f&&(i[e].v<t.lf?x=Math.min(x,t.lf):m=Math.max(m,t.uf));var b=Math.sqrt(p*(y-v)/(x-m+c))||0;b=a.constrain(Math.abs(b),0,1),d.push(b),g=Math.max(b,g)}n=2*r.jitter/(g||1)}for(e=0;e<i.length;e++){var _=i[e],w=_.v,k=r.jitter?n*d[e]*(a.pseudoRandom()-.5):0,T=t.pos+h+u*(r.pointpos+k);\"h\"===r.orientation?(_.y=T,_.x=w):(_.x=T,_.y=w),\"suspectedoutliers\"===f&&w<t.uo&&w>t.lo&&(_.so=!0)}return i});d.enter().append(\"path\").classed(\"point\",!0),d.exit().remove(),d.call(i.translatePoints,l,c)}function u(t,e,r,i){var o,s,l=e.pos,c=e.val,u=i.bPos,h=i.bPosPxOffset||0,f=r.boxmean||(r.meanline||{}).visible;Array.isArray(i.bdPos)?(o=i.bdPos[0],s=i.bdPos[1]):(o=i.bdPos,s=i.bdPos);var p=t.selectAll(\"path.mean\").data(\"box\"===r.type&&r.boxmean||\"violin\"===r.type&&r.box.visible&&r.meanline.visible?a.identity:[]);p.enter().append(\"path\").attr(\"class\",\"mean\").style({fill:\"none\",\"vector-effect\":\"non-scaling-stroke\"}),p.exit().remove(),p.each(function(t){var e=l.c2l(t.pos+u,!0),a=l.l2p(e)+h,i=l.l2p(e-o)+h,p=l.l2p(e+s)+h,d=c.c2p(t.mean,!0),g=c.c2p(t.mean-t.sd,!0),v=c.c2p(t.mean+t.sd,!0);\"h\"===r.orientation?n.select(this).attr(\"d\",\"M\"+d+\",\"+i+\"V\"+p+(\"sd\"===f?\"m0,0L\"+g+\",\"+a+\"L\"+d+\",\"+i+\"L\"+v+\",\"+a+\"Z\":\"\")):n.select(this).attr(\"d\",\"M\"+i+\",\"+d+\"H\"+p+(\"sd\"===f?\"m0,0L\"+a+\",\"+g+\"L\"+i+\",\"+d+\"L\"+a+\",\"+v+\"Z\":\"\"))})}e.exports={plot:function(t,e,r,i){var o=e.xaxis,s=e.yaxis;a.makeTraceGroups(i,r,\"trace boxes\").each(function(t){var e,r,a=n.select(this),i=t[0],h=i.t,f=i.trace;h.wdPos=h.bdPos*f.whiskerwidth,!0!==f.visible||h.empty?a.remove():(\"h\"===f.orientation?(e=s,r=o):(e=o,r=s),l(a,{pos:e,val:r},f,h),c(a,{x:o,y:s},f,h),u(a,{pos:e,val:r},f,h))})},plotBoxAndWhiskers:l,plotPoints:c,plotBoxMean:u}},{\"../../components/drawing\":613,\"../../lib\":717,d3:165}],891:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r,n,a=t.cd,i=t.xaxis,o=t.yaxis,s=[];if(!1===e)for(r=0;r<a.length;r++)for(n=0;n<(a[r].pts||[]).length;n++)a[r].pts[n].selected=0;else for(r=0;r<a.length;r++)for(n=0;n<(a[r].pts||[]).length;n++){var l=a[r].pts[n],c=i.c2p(l.x),u=o.c2p(l.y);e.contains([c,u],null,l.i,t)?(s.push({pointNumber:l.i,x:i.c2d(l.x),y:o.c2d(l.y)}),l.selected=1):l.selected=0}return s}},{}],892:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../components/color\"),i=t(\"../../components/drawing\");e.exports={style:function(t,e,r){var o=r||n.select(t).selectAll(\"g.trace.boxes\");o.style(\"opacity\",function(t){return t[0].trace.opacity}),o.each(function(e){var r=n.select(this),o=e[0].trace,s=o.line.width;function l(t,e,r,n){t.style(\"stroke-width\",e+\"px\").call(a.stroke,r).call(a.fill,n)}var c=r.selectAll(\"path.box\");if(\"candlestick\"===o.type)c.each(function(t){if(!t.empty){var e=n.select(this),r=o[t.dir];l(e,r.line.width,r.line.color,r.fillcolor),e.style(\"opacity\",o.selectedpoints&&!t.selected?.3:1)}});else{l(c,s,o.line.color,o.fillcolor),r.selectAll(\"path.mean\").style({\"stroke-width\":s,\"stroke-dasharray\":2*s+\"px,\"+s+\"px\"}).call(a.stroke,o.line.color);var u=r.selectAll(\"path.point\");i.pointStyle(u,o,t)}})},styleOnSelect:function(t,e,r){var n=e[0].trace,a=r.selectAll(\"path.point\");n.selectedpoints?i.selectedPointStyle(a,n):i.pointStyle(a,n,t)}}},{\"../../components/color\":592,\"../../components/drawing\":613,d3:165}],893:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").extendFlat,a=t(\"../ohlc/attributes\"),i=t(\"../box/attributes\");function o(t){return{line:{color:n({},i.line.color,{dflt:t}),width:i.line.width,editType:\"style\"},fillcolor:i.fillcolor,editType:\"style\"}}e.exports={x:a.x,open:a.open,high:a.high,low:a.low,close:a.close,line:{width:n({},i.line.width,{}),editType:\"style\"},increasing:o(a.increasing.line.color.dflt),decreasing:o(a.decreasing.line.color.dflt),text:a.text,hovertext:a.hovertext,whiskerwidth:n({},i.whiskerwidth,{dflt:0}),hoverlabel:a.hoverlabel}},{\"../../lib\":717,\"../box/attributes\":881,\"../ohlc/attributes\":1066}],894:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/cartesian/axes\"),i=t(\"../ohlc/calc\").calcCommon;function o(t,e,r,n){return{min:r,q1:Math.min(t,n),med:n,q3:Math.max(t,n),max:e}}e.exports=function(t,e){var r=t._fullLayout,s=a.getFromId(t,e.xaxis),l=a.getFromId(t,e.yaxis),c=s.makeCalcdata(e,\"x\"),u=i(t,e,c,l,o);return u.length?(n.extendFlat(u[0].t,{num:r._numBoxes,dPos:n.distinctVals(c).minDiff/2,posLetter:\"x\",valLetter:\"y\"}),r._numBoxes++,u):[{t:{empty:!0}}]}},{\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"../ohlc/calc\":1067}],895:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/color\"),i=t(\"../ohlc/ohlc_defaults\"),o=t(\"./attributes\");function s(t,e,r,n){var i=r(n+\".line.color\");r(n+\".line.width\",e.line.width),r(n+\".fillcolor\",a.addOpacity(i,.5))}e.exports=function(t,e,r,a){function l(r,a){return n.coerce(t,e,o,r,a)}i(t,e,l,a)?(l(\"line.width\"),s(t,e,l,\"increasing\"),s(t,e,l,\"decreasing\"),l(\"text\"),l(\"hovertext\"),l(\"whiskerwidth\"),a._requestRangeslider[e.xaxis]=!0):e.visible=!1}},{\"../../components/color\":592,\"../../lib\":717,\"../ohlc/ohlc_defaults\":1071,\"./attributes\":893}],896:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"candlestick\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"cartesian\",\"svg\",\"showLegend\",\"candlestick\",\"boxLayout\"],meta:{},attributes:t(\"./attributes\"),layoutAttributes:t(\"../box/layout_attributes\"),supplyLayoutDefaults:t(\"../box/layout_defaults\").supplyLayoutDefaults,crossTraceCalc:t(\"../box/cross_trace_calc\").crossTraceCalc,supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"../box/plot\").plot,layerName:\"boxlayer\",style:t(\"../box/style\").style,hoverPoints:t(\"../ohlc/hover\").hoverPoints,selectPoints:t(\"../ohlc/select\")}},{\"../../plots/cartesian\":776,\"../box/cross_trace_calc\":883,\"../box/layout_attributes\":888,\"../box/layout_defaults\":889,\"../box/plot\":890,\"../box/style\":892,\"../ohlc/hover\":1069,\"../ohlc/select\":1073,\"./attributes\":893,\"./calc\":894,\"./defaults\":895}],897:[function(t,e,r){\"use strict\";var n=t(\"./axis_defaults\"),a=t(\"../../plot_api/plot_template\");e.exports=function(t,e,r,i,o){i(\"a\")||(i(\"da\"),i(\"a0\")),i(\"b\")||(i(\"db\"),i(\"b0\")),function(t,e,r,i){[\"aaxis\",\"baxis\"].forEach(function(o){var s=o.charAt(0),l=t[o]||{},c=a.newContainer(e,o),u={tickfont:\"x\",id:s+\"axis\",letter:s,font:e.font,name:o,data:t[s],calendar:e.calendar,dfltColor:i,bgColor:r.paper_bgcolor,fullLayout:r};n(l,c,u),c._categories=c._categories||[],t[o]||\"-\"===l.type||(t[o]={type:l.type})})}(t,e,r,o)}},{\"../../plot_api/plot_template\":755,\"./axis_defaults\":902}],898:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").isArrayOrTypedArray;e.exports=function(t){return function t(e,r){if(!n(e)||r>=10)return null;var a=1/0;var i=-1/0;var o=e.length;for(var s=0;s<o;s++){var l=e[s];if(n(l)){var c=t(l,r+1);c&&(a=Math.min(c[0],a),i=Math.max(c[1],i))}else a=Math.min(l,a),i=Math.max(l,i)}return[a,i]}(t,0)}},{\"../../lib\":717}],899:[function(t,e,r){\"use strict\";var n=t(\"../../plots/font_attributes\"),a=t(\"./axis_attributes\"),i=t(\"../../components/color/attributes\"),o=n({editType:\"calc\"});o.family.dflt='\"Open Sans\", verdana, arial, sans-serif',o.size.dflt=12,o.color.dflt=i.defaultLine,e.exports={carpet:{valType:\"string\",editType:\"calc\"},x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},a:{valType:\"data_array\",editType:\"calc\"},a0:{valType:\"number\",dflt:0,editType:\"calc\"},da:{valType:\"number\",dflt:1,editType:\"calc\"},b:{valType:\"data_array\",editType:\"calc\"},b0:{valType:\"number\",dflt:0,editType:\"calc\"},db:{valType:\"number\",dflt:1,editType:\"calc\"},cheaterslope:{valType:\"number\",dflt:1,editType:\"calc\"},aaxis:a,baxis:a,font:o,color:{valType:\"color\",dflt:i.defaultLine,editType:\"plot\"},transforms:void 0}},{\"../../components/color/attributes\":591,\"../../plots/font_attributes\":791,\"./axis_attributes\":901}],900:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").isArrayOrTypedArray;e.exports=function(t,e,r,a){var i,o,s,l,c,u,h,f,p,d,g,v,m,y=n(r)?\"a\":\"b\",x=(\"a\"===y?t.aaxis:t.baxis).smoothing,b=\"a\"===y?t.a2i:t.b2j,_=\"a\"===y?r:a,w=\"a\"===y?a:r,k=\"a\"===y?e.a.length:e.b.length,T=\"a\"===y?e.b.length:e.a.length,M=Math.floor(\"a\"===y?t.b2j(w):t.a2i(w)),A=\"a\"===y?function(e){return t.evalxy([],e,M)}:function(e){return t.evalxy([],M,e)};x&&(s=Math.max(0,Math.min(T-2,M)),l=M-s,o=\"a\"===y?function(e,r){return t.dxydi([],e,s,r,l)}:function(e,r){return t.dxydj([],s,e,l,r)});var S=b(_[0]),E=b(_[1]),L=S<E?1:-1,C=1e-8*(E-S),P=L>0?Math.floor:Math.ceil,O=L>0?Math.ceil:Math.floor,z=L>0?Math.min:Math.max,I=L>0?Math.max:Math.min,D=P(S+C),R=O(E-C),F=[[h=A(S)]];for(i=D;i*L<R*L;i+=L)c=[],g=I(S,i),m=(v=z(E,i+L))-g,u=Math.max(0,Math.min(k-2,Math.floor(.5*(g+v)))),f=A(v),x&&(p=o(u,g-u),d=o(u,v-u),c.push([h[0]+p[0]/3*m,h[1]+p[1]/3*m]),c.push([f[0]-d[0]/3*m,f[1]-d[1]/3*m])),c.push(f),F.push(c),h=f;return F}},{\"../../lib\":717}],901:[function(t,e,r){\"use strict\";var n=t(\"../../plots/font_attributes\"),a=t(\"../../components/color/attributes\"),i=t(\"../../plots/cartesian/layout_attributes\"),o=t(\"../../plot_api/edit_types\").overrideAll;t(\"../../constants/docs\").FORMAT_LINK,t(\"../../constants/docs\").TIME_FORMAT_LINK;e.exports={color:{valType:\"color\",editType:\"calc\"},smoothing:{valType:\"number\",dflt:1,min:0,max:1.3,editType:\"calc\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"calc\"},font:n({editType:\"calc\"}),offset:{valType:\"number\",dflt:10,editType:\"calc\"},editType:\"calc\"},type:{valType:\"enumerated\",values:[\"-\",\"linear\",\"date\",\"category\"],dflt:\"-\",editType:\"calc\"},autorange:{valType:\"enumerated\",values:[!0,!1,\"reversed\"],dflt:!0,editType:\"calc\"},rangemode:{valType:\"enumerated\",values:[\"normal\",\"tozero\",\"nonnegative\"],dflt:\"normal\",editType:\"calc\"},range:{valType:\"info_array\",editType:\"calc\",items:[{valType:\"any\",editType:\"calc\"},{valType:\"any\",editType:\"calc\"}]},fixedrange:{valType:\"boolean\",dflt:!1,editType:\"calc\"},cheatertype:{valType:\"enumerated\",values:[\"index\",\"value\"],dflt:\"value\",editType:\"calc\"},tickmode:{valType:\"enumerated\",values:[\"linear\",\"array\"],dflt:\"array\",editType:\"calc\"},nticks:{valType:\"integer\",min:0,dflt:0,editType:\"calc\"},tickvals:{valType:\"data_array\",editType:\"calc\"},ticktext:{valType:\"data_array\",editType:\"calc\"},showticklabels:{valType:\"enumerated\",values:[\"start\",\"end\",\"both\",\"none\"],dflt:\"start\",editType:\"calc\"},tickfont:n({editType:\"calc\"}),tickangle:{valType:\"angle\",dflt:\"auto\",editType:\"calc\"},tickprefix:{valType:\"string\",dflt:\"\",editType:\"calc\"},showtickprefix:{valType:\"enumerated\",values:[\"all\",\"first\",\"last\",\"none\"],dflt:\"all\",editType:\"calc\"},ticksuffix:{valType:\"string\",dflt:\"\",editType:\"calc\"},showticksuffix:{valType:\"enumerated\",values:[\"all\",\"first\",\"last\",\"none\"],dflt:\"all\",editType:\"calc\"},showexponent:{valType:\"enumerated\",values:[\"all\",\"first\",\"last\",\"none\"],dflt:\"all\",editType:\"calc\"},exponentformat:{valType:\"enumerated\",values:[\"none\",\"e\",\"E\",\"power\",\"SI\",\"B\"],dflt:\"B\",editType:\"calc\"},separatethousands:{valType:\"boolean\",dflt:!1,editType:\"calc\"},tickformat:{valType:\"string\",dflt:\"\",editType:\"calc\"},tickformatstops:o(i.tickformatstops,\"calc\",\"from-root\"),categoryorder:{valType:\"enumerated\",values:[\"trace\",\"category ascending\",\"category descending\",\"array\"],dflt:\"trace\",editType:\"calc\"},categoryarray:{valType:\"data_array\",editType:\"calc\"},labelpadding:{valType:\"integer\",dflt:10,editType:\"calc\"},labelprefix:{valType:\"string\",editType:\"calc\"},labelsuffix:{valType:\"string\",dflt:\"\",editType:\"calc\"},showline:{valType:\"boolean\",dflt:!1,editType:\"calc\"},linecolor:{valType:\"color\",dflt:a.defaultLine,editType:\"calc\"},linewidth:{valType:\"number\",min:0,dflt:1,editType:\"calc\"},gridcolor:{valType:\"color\",editType:\"calc\"},gridwidth:{valType:\"number\",min:0,dflt:1,editType:\"calc\"},showgrid:{valType:\"boolean\",dflt:!0,editType:\"calc\"},minorgridcount:{valType:\"integer\",min:0,dflt:0,editType:\"calc\"},minorgridwidth:{valType:\"number\",min:0,dflt:1,editType:\"calc\"},minorgridcolor:{valType:\"color\",dflt:a.lightLine,editType:\"calc\"},startline:{valType:\"boolean\",editType:\"calc\"},startlinecolor:{valType:\"color\",editType:\"calc\"},startlinewidth:{valType:\"number\",dflt:1,editType:\"calc\"},endline:{valType:\"boolean\",editType:\"calc\"},endlinewidth:{valType:\"number\",dflt:1,editType:\"calc\"},endlinecolor:{valType:\"color\",editType:\"calc\"},tick0:{valType:\"number\",min:0,dflt:0,editType:\"calc\"},dtick:{valType:\"number\",min:0,dflt:1,editType:\"calc\"},arraytick0:{valType:\"integer\",min:0,dflt:0,editType:\"calc\"},arraydtick:{valType:\"integer\",min:1,dflt:1,editType:\"calc\"},_deprecated:{title:{valType:\"string\",editType:\"calc\"},titlefont:n({editType:\"calc\"}),titleoffset:{valType:\"number\",dflt:10,editType:\"calc\"}},editType:\"calc\"}},{\"../../components/color/attributes\":591,\"../../constants/docs\":688,\"../../plot_api/edit_types\":748,\"../../plots/cartesian/layout_attributes\":777,\"../../plots/font_attributes\":791}],902:[function(t,e,r){\"use strict\";var n=t(\"./attributes\"),a=t(\"../../components/color\").addOpacity,i=t(\"../../registry\"),o=t(\"../../lib\"),s=t(\"../../plots/cartesian/tick_value_defaults\"),l=t(\"../../plots/cartesian/tick_label_defaults\"),c=t(\"../../plots/cartesian/category_order_defaults\"),u=t(\"../../plots/cartesian/set_convert\"),h=t(\"../../plots/cartesian/axis_autotype\");e.exports=function(t,e,r){var f=r.letter,p=r.font||{},d=n[f+\"axis\"];function g(r,n){return o.coerce(t,e,d,r,n)}function v(r,n){return o.coerce2(t,e,d,r,n)}r.name&&(e._name=r.name,e._id=r.name);var m=g(\"type\");(\"-\"===m&&(r.data&&function(t,e){if(\"-\"!==t.type)return;var r=t._id.charAt(0),n=t[r+\"calendar\"];t.type=h(e,n)}(e,r.data),\"-\"===e.type?e.type=\"linear\":m=t.type=e.type),g(\"smoothing\"),g(\"cheatertype\"),g(\"showticklabels\"),g(\"labelprefix\",f+\" = \"),g(\"labelsuffix\"),g(\"showtickprefix\"),g(\"showticksuffix\"),g(\"separatethousands\"),g(\"tickformat\"),g(\"exponentformat\"),g(\"showexponent\"),g(\"categoryorder\"),g(\"tickmode\"),g(\"tickvals\"),g(\"ticktext\"),g(\"tick0\"),g(\"dtick\"),\"array\"===e.tickmode&&(g(\"arraytick0\"),g(\"arraydtick\")),g(\"labelpadding\"),e._hovertitle=f,\"date\"===m)&&i.getComponentMethod(\"calendars\",\"handleDefaults\")(t,e,\"calendar\",r.calendar);u(e,r.fullLayout),e.c2p=o.identity;var y=g(\"color\",r.dfltColor),x=y===t.color?y:p.color;g(\"title.text\")&&(o.coerceFont(g,\"title.font\",{family:p.family,size:Math.round(1.2*p.size),color:x}),g(\"title.offset\")),g(\"tickangle\"),g(\"autorange\",!e.isValidRange(t.range))&&g(\"rangemode\"),g(\"range\"),e.cleanRange(),g(\"fixedrange\"),s(t,e,g,m),l(t,e,g,m,r),c(t,e,g,{data:r.data,dataAttr:f});var b=v(\"gridcolor\",a(y,.3)),_=v(\"gridwidth\"),w=g(\"showgrid\");w||(delete e.gridcolor,delete e.gridwidth);var k=v(\"startlinecolor\",y),T=v(\"startlinewidth\",_);g(\"startline\",e.showgrid||!!k||!!T)||(delete e.startlinecolor,delete e.startlinewidth);var M=v(\"endlinecolor\",y),A=v(\"endlinewidth\",_);return g(\"endline\",e.showgrid||!!M||!!A)||(delete e.endlinecolor,delete e.endlinewidth),w?(g(\"minorgridcount\"),g(\"minorgridwidth\",_),g(\"minorgridcolor\",a(b,.06)),e.minorgridcount||(delete e.minorgridwidth,delete e.minorgridcolor)):(delete e.gridcolor,delete e.gridWidth),\"none\"===e.showticklabels&&(delete e.tickfont,delete e.tickangle,delete e.showexponent,delete e.exponentformat,delete e.tickformat,delete e.showticksuffix,delete e.showtickprefix),e.showticksuffix||delete e.ticksuffix,e.showtickprefix||delete e.tickprefix,g(\"tickmode\"),e}},{\"../../components/color\":592,\"../../lib\":717,\"../../plots/cartesian/axis_autotype\":766,\"../../plots/cartesian/category_order_defaults\":769,\"../../plots/cartesian/set_convert\":783,\"../../plots/cartesian/tick_label_defaults\":784,\"../../plots/cartesian/tick_value_defaults\":786,\"../../registry\":846,\"./attributes\":899}],903:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\"),a=t(\"../../lib\").isArray1D,i=t(\"./cheater_basis\"),o=t(\"./array_minmax\"),s=t(\"./calc_gridlines\"),l=t(\"./calc_labels\"),c=t(\"./calc_clippath\"),u=t(\"../heatmap/clean_2d_array\"),h=t(\"./smooth_fill_2d_array\"),f=t(\"../heatmap/convert_column_xyz\"),p=t(\"./set_convert\");e.exports=function(t,e){var r=n.getFromId(t,e.xaxis),d=n.getFromId(t,e.yaxis),g=e.aaxis,v=e.baxis,m=e.x,y=e.y,x=[];m&&a(m)&&x.push(\"x\"),y&&a(y)&&x.push(\"y\"),x.length&&f(e,g,v,\"a\",\"b\",x);var b=e._a=e._a||e.a,_=e._b=e._b||e.b;m=e._x||e.x,y=e._y||e.y;var w={};if(e._cheater){var k=\"index\"===g.cheatertype?b.length:b,T=\"index\"===v.cheatertype?_.length:_;m=i(k,T,e.cheaterslope)}e._x=m=u(m),e._y=y=u(y),h(m,b,_),h(y,b,_),p(e),e.setScale();var M=o(m),A=o(y),S=.5*(M[1]-M[0]),E=.5*(M[1]+M[0]),L=.5*(A[1]-A[0]),C=.5*(A[1]+A[0]);return M=[E-1.3*S,E+1.3*S],A=[C-1.3*L,C+1.3*L],e._extremes[r._id]=n.findExtremes(r,M,{padded:!0}),e._extremes[d._id]=n.findExtremes(d,A,{padded:!0}),s(e,\"a\",\"b\"),s(e,\"b\",\"a\"),l(e,g),l(e,v),w.clipsegments=c(e._xctrl,e._yctrl,g,v),w.x=m,w.y=y,w.a=b,w.b=_,[w]}},{\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"../heatmap/clean_2d_array\":1002,\"../heatmap/convert_column_xyz\":1004,\"./array_minmax\":898,\"./calc_clippath\":904,\"./calc_gridlines\":905,\"./calc_labels\":906,\"./cheater_basis\":908,\"./set_convert\":921,\"./smooth_fill_2d_array\":922}],904:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n){var a,i,o,s=[],l=!!r.smoothing,c=!!n.smoothing,u=t[0].length-1,h=t.length-1;for(a=0,i=[],o=[];a<=u;a++)i[a]=t[0][a],o[a]=e[0][a];for(s.push({x:i,y:o,bicubic:l}),a=0,i=[],o=[];a<=h;a++)i[a]=t[a][u],o[a]=e[a][u];for(s.push({x:i,y:o,bicubic:c}),a=u,i=[],o=[];a>=0;a--)i[u-a]=t[h][a],o[u-a]=e[h][a];for(s.push({x:i,y:o,bicubic:l}),a=h,i=[],o=[];a>=0;a--)i[h-a]=t[a][0],o[h-a]=e[a][0];return s.push({x:i,y:o,bicubic:c}),s}},{}],905:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\"),a=t(\"../../lib/extend\").extendFlat;e.exports=function(t,e,r){var i,o,s,l,c,u,h,f,p,d,g,v,m,y,x=t[\"_\"+e],b=t[e+\"axis\"],_=b._gridlines=[],w=b._minorgridlines=[],k=b._boundarylines=[],T=t[\"_\"+r],M=t[r+\"axis\"];\"array\"===b.tickmode&&(b.tickvals=x.slice());var A=t._xctrl,S=t._yctrl,E=A[0].length,L=A.length,C=t._a.length,P=t._b.length;n.prepTicks(b),\"array\"===b.tickmode&&delete b.tickvals;var O=b.smoothing?3:1;function z(n){var a,i,o,s,l,c,u,h,p,d,g,v,m=[],y=[],x={};if(\"b\"===e)for(i=t.b2j(n),o=Math.floor(Math.max(0,Math.min(P-2,i))),s=i-o,x.length=P,x.crossLength=C,x.xy=function(e){return t.evalxy([],e,i)},x.dxy=function(e,r){return t.dxydi([],e,o,r,s)},a=0;a<C;a++)c=Math.min(C-2,a),u=a-c,h=t.evalxy([],a,i),M.smoothing&&a>0&&(p=t.dxydi([],a-1,o,0,s),m.push(l[0]+p[0]/3),y.push(l[1]+p[1]/3),d=t.dxydi([],a-1,o,1,s),m.push(h[0]-d[0]/3),y.push(h[1]-d[1]/3)),m.push(h[0]),y.push(h[1]),l=h;else for(a=t.a2i(n),c=Math.floor(Math.max(0,Math.min(C-2,a))),u=a-c,x.length=C,x.crossLength=P,x.xy=function(e){return t.evalxy([],a,e)},x.dxy=function(e,r){return t.dxydj([],c,e,u,r)},i=0;i<P;i++)o=Math.min(P-2,i),s=i-o,h=t.evalxy([],a,i),M.smoothing&&i>0&&(g=t.dxydj([],c,i-1,u,0),m.push(l[0]+g[0]/3),y.push(l[1]+g[1]/3),v=t.dxydj([],c,i-1,u,1),m.push(h[0]-v[0]/3),y.push(h[1]-v[1]/3)),m.push(h[0]),y.push(h[1]),l=h;return x.axisLetter=e,x.axis=b,x.crossAxis=M,x.value=n,x.constvar=r,x.index=f,x.x=m,x.y=y,x.smoothing=M.smoothing,x}function I(n){var a,i,o,s,l,c=[],u=[],h={};if(h.length=x.length,h.crossLength=T.length,\"b\"===e)for(o=Math.max(0,Math.min(P-2,n)),l=Math.min(1,Math.max(0,n-o)),h.xy=function(e){return t.evalxy([],e,n)},h.dxy=function(e,r){return t.dxydi([],e,o,r,l)},a=0;a<E;a++)c[a]=A[n*O][a],u[a]=S[n*O][a];else for(i=Math.max(0,Math.min(C-2,n)),s=Math.min(1,Math.max(0,n-i)),h.xy=function(e){return t.evalxy([],n,e)},h.dxy=function(e,r){return t.dxydj([],i,e,s,r)},a=0;a<L;a++)c[a]=A[a][n*O],u[a]=S[a][n*O];return h.axisLetter=e,h.axis=b,h.crossAxis=M,h.value=x[n],h.constvar=r,h.index=n,h.x=c,h.y=u,h.smoothing=M.smoothing,h}if(\"array\"===b.tickmode){for(l=5e-15,u=(c=[Math.floor((x.length-1-b.arraytick0)/b.arraydtick*(1+l)),Math.ceil(-b.arraytick0/b.arraydtick/(1+l))].sort(function(t,e){return t-e}))[0]-1,h=c[1]+1,f=u;f<h;f++)(o=b.arraytick0+b.arraydtick*f)<0||o>x.length-1||_.push(a(I(o),{color:b.gridcolor,width:b.gridwidth}));for(f=u;f<h;f++)if(s=b.arraytick0+b.arraydtick*f,g=Math.min(s+b.arraydtick,x.length-1),!(s<0||s>x.length-1||g<0||g>x.length-1))for(v=x[s],m=x[g],i=0;i<b.minorgridcount;i++)(y=g-s)<=0||(d=v+(m-v)*(i+1)/(b.minorgridcount+1)*(b.arraydtick/y))<x[0]||d>x[x.length-1]||w.push(a(z(d),{color:b.minorgridcolor,width:b.minorgridwidth}));b.startline&&k.push(a(I(0),{color:b.startlinecolor,width:b.startlinewidth})),b.endline&&k.push(a(I(x.length-1),{color:b.endlinecolor,width:b.endlinewidth}))}else{for(l=5e-15,u=(c=[Math.floor((x[x.length-1]-b.tick0)/b.dtick*(1+l)),Math.ceil((x[0]-b.tick0)/b.dtick/(1+l))].sort(function(t,e){return t-e}))[0],h=c[1],f=u;f<=h;f++)p=b.tick0+b.dtick*f,_.push(a(z(p),{color:b.gridcolor,width:b.gridwidth}));for(f=u-1;f<h+1;f++)for(p=b.tick0+b.dtick*f,i=0;i<b.minorgridcount;i++)(d=p+b.dtick*(i+1)/(b.minorgridcount+1))<x[0]||d>x[x.length-1]||w.push(a(z(d),{color:b.minorgridcolor,width:b.minorgridwidth}));b.startline&&k.push(a(z(x[0]),{color:b.startlinecolor,width:b.startlinewidth})),b.endline&&k.push(a(z(x[x.length-1]),{color:b.endlinecolor,width:b.endlinewidth}))}}},{\"../../lib/extend\":708,\"../../plots/cartesian/axes\":765}],906:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\"),a=t(\"../../lib/extend\").extendFlat;e.exports=function(t,e){var r,i,o,s=e._labels=[],l=e._gridlines;for(r=0;r<l.length;r++)o=l[r],-1!==[\"start\",\"both\"].indexOf(e.showticklabels)&&(i=n.tickText(e,o.value),a(i,{prefix:void 0,suffix:void 0,endAnchor:!0,xy:o.xy(0),dxy:o.dxy(0,0),axis:o.axis,length:o.crossAxis.length,font:o.axis.tickfont,isFirst:0===r,isLast:r===l.length-1}),s.push(i)),-1!==[\"end\",\"both\"].indexOf(e.showticklabels)&&(i=n.tickText(e,o.value),a(i,{endAnchor:!1,xy:o.xy(o.crossLength-1),dxy:o.dxy(o.crossLength-2,1),axis:o.axis,length:o.crossAxis.length,font:o.axis.tickfont,isFirst:0===r,isLast:r===l.length-1}),s.push(i))}},{\"../../lib/extend\":708,\"../../plots/cartesian/axes\":765}],907:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n){var a=t[0]-e[0],i=t[1]-e[1],o=r[0]-e[0],s=r[1]-e[1],l=Math.pow(a*a+i*i,.25),c=Math.pow(o*o+s*s,.25),u=(c*c*a-l*l*o)*n,h=(c*c*i-l*l*s)*n,f=c*(l+c)*3,p=l*(l+c)*3;return[[e[0]+(f&&u/f),e[1]+(f&&h/f)],[e[0]-(p&&u/p),e[1]-(p&&h/p)]]}},{}],908:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").isArrayOrTypedArray;e.exports=function(t,e,r){var a,i,o,s,l,c,u=[],h=n(t)?t.length:t,f=n(e)?e.length:e,p=n(t)?t:null,d=n(e)?e:null;p&&(o=(p.length-1)/(p[p.length-1]-p[0])/(h-1)),d&&(s=(d.length-1)/(d[d.length-1]-d[0])/(f-1));var g=1/0,v=-1/0;for(i=0;i<f;i++)for(u[i]=[],l=d?(d[i]-d[0])*s:i/(f-1),a=0;a<h;a++)c=(p?(p[a]-p[0])*o:a/(h-1))-l*r,g=Math.min(c,g),v=Math.max(c,v),u[i][a]=c;var m=1/(v-g),y=-g*m;for(i=0;i<f;i++)for(a=0;a<h;a++)u[i][a]=m*u[i][a]+y;return u}},{\"../../lib\":717}],909:[function(t,e,r){\"use strict\";var n=t(\"./catmull_rom\"),a=t(\"../../lib\").ensureArray;function i(t,e,r){var n=-.5*r[0]+1.5*e[0],a=-.5*r[1]+1.5*e[1];return[(2*n+t[0])/3,(2*a+t[1])/3]}e.exports=function(t,e,r,o,s,l){var c,u,h,f,p,d,g,v,m,y,x=r[0].length,b=r.length,_=s?3*x-2:x,w=l?3*b-2:b;for(t=a(t,w),e=a(e,w),h=0;h<w;h++)t[h]=a(t[h],_),e[h]=a(e[h],_);for(u=0,f=0;u<b;u++,f+=l?3:1)for(p=t[f],d=e[f],g=r[u],v=o[u],c=0,h=0;c<x;c++,h+=s?3:1)p[h]=g[c],d[h]=v[c];if(s)for(u=0,f=0;u<b;u++,f+=l?3:1){for(c=1,h=3;c<x-1;c++,h+=3)m=n([r[u][c-1],o[u][c-1]],[r[u][c],o[u][c]],[r[u][c+1],o[u][c+1]],s),t[f][h-1]=m[0][0],e[f][h-1]=m[0][1],t[f][h+1]=m[1][0],e[f][h+1]=m[1][1];y=i([t[f][0],e[f][0]],[t[f][2],e[f][2]],[t[f][3],e[f][3]]),t[f][1]=y[0],e[f][1]=y[1],y=i([t[f][_-1],e[f][_-1]],[t[f][_-3],e[f][_-3]],[t[f][_-4],e[f][_-4]]),t[f][_-2]=y[0],e[f][_-2]=y[1]}if(l)for(h=0;h<_;h++){for(f=3;f<w-3;f+=3)m=n([t[f-3][h],e[f-3][h]],[t[f][h],e[f][h]],[t[f+3][h],e[f+3][h]],l),t[f-1][h]=m[0][0],e[f-1][h]=m[0][1],t[f+1][h]=m[1][0],e[f+1][h]=m[1][1];y=i([t[0][h],e[0][h]],[t[2][h],e[2][h]],[t[3][h],e[3][h]]),t[1][h]=y[0],e[1][h]=y[1],y=i([t[w-1][h],e[w-1][h]],[t[w-3][h],e[w-3][h]],[t[w-4][h],e[w-4][h]]),t[w-2][h]=y[0],e[w-2][h]=y[1]}if(s&&l)for(f=1;f<w;f+=(f+1)%3==0?2:1){for(h=3;h<_-3;h+=3)m=n([t[f][h-3],e[f][h-3]],[t[f][h],e[f][h]],[t[f][h+3],e[f][h+3]],s),t[f][h-1]=.5*(t[f][h-1]+m[0][0]),e[f][h-1]=.5*(e[f][h-1]+m[0][1]),t[f][h+1]=.5*(t[f][h+1]+m[1][0]),e[f][h+1]=.5*(e[f][h+1]+m[1][1]);y=i([t[f][0],e[f][0]],[t[f][2],e[f][2]],[t[f][3],e[f][3]]),t[f][1]=.5*(t[f][1]+y[0]),e[f][1]=.5*(e[f][1]+y[1]),y=i([t[f][_-1],e[f][_-1]],[t[f][_-3],e[f][_-3]],[t[f][_-4],e[f][_-4]]),t[f][_-2]=.5*(t[f][_-2]+y[0]),e[f][_-2]=.5*(e[f][_-2]+y[1])}return[t,e]}},{\"../../lib\":717,\"./catmull_rom\":907}],910:[function(t,e,r){\"use strict\";e.exports={RELATIVE_CULL_TOLERANCE:1e-6}},{}],911:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){return e&&r?function(e,r,n,a,i){var o,s,l,c,u,h;e||(e=[]),r*=3,n*=3;var f=a*a,p=1-a,d=p*p,g=p*a*2,v=-3*d,m=3*(d-g),y=3*(g-f),x=3*f,b=i*i,_=b*i,w=1-i,k=w*w,T=k*w;for(h=0;h<t.length;h++)o=v*(u=t[h])[n][r]+m*u[n][r+1]+y*u[n][r+2]+x*u[n][r+3],s=v*u[n+1][r]+m*u[n+1][r+1]+y*u[n+1][r+2]+x*u[n+1][r+3],l=v*u[n+2][r]+m*u[n+2][r+1]+y*u[n+2][r+2]+x*u[n+2][r+3],c=v*u[n+3][r]+m*u[n+3][r+1]+y*u[n+3][r+2]+x*u[n+3][r+3],e[h]=T*o+3*(k*i*s+w*b*l)+_*c;return e}:e?function(e,r,n,a,i){var o,s,l,c;e||(e=[]),r*=3;var u=a*a,h=1-a,f=h*h,p=h*a*2,d=-3*f,g=3*(f-p),v=3*(p-u),m=3*u,y=1-i;for(l=0;l<t.length;l++)o=d*(c=t[l])[n][r]+g*c[n][r+1]+v*c[n][r+2]+m*c[n][r+3],s=d*c[n+1][r]+g*c[n+1][r+1]+v*c[n+1][r+2]+m*c[n+1][r+3],e[l]=y*o+i*s;return e}:r?function(e,r,n,a,i){var o,s,l,c,u,h;e||(e=[]),n*=3;var f=i*i,p=f*i,d=1-i,g=d*d,v=g*d;for(u=0;u<t.length;u++)o=(h=t[u])[n][r+1]-h[n][r],s=h[n+1][r+1]-h[n+1][r],l=h[n+2][r+1]-h[n+2][r],c=h[n+3][r+1]-h[n+3][r],e[u]=v*o+3*(g*i*s+d*f*l)+p*c;return e}:function(e,r,n,a,i){var o,s,l,c;e||(e=[]);var u=1-i;for(l=0;l<t.length;l++)o=(c=t[l])[n][r+1]-c[n][r],s=c[n+1][r+1]-c[n+1][r],e[l]=u*o+i*s;return e}}},{}],912:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){return e&&r?function(e,r,n,a,i){var o,s,l,c,u,h;e||(e=[]),r*=3,n*=3;var f=a*a,p=f*a,d=1-a,g=d*d,v=g*d,m=i*i,y=1-i,x=y*y,b=y*i*2,_=-3*x,w=3*(x-b),k=3*(b-m),T=3*m;for(h=0;h<t.length;h++)o=_*(u=t[h])[n][r]+w*u[n+1][r]+k*u[n+2][r]+T*u[n+3][r],s=_*u[n][r+1]+w*u[n+1][r+1]+k*u[n+2][r+1]+T*u[n+3][r+1],l=_*u[n][r+2]+w*u[n+1][r+2]+k*u[n+2][r+2]+T*u[n+3][r+2],c=_*u[n][r+3]+w*u[n+1][r+3]+k*u[n+2][r+3]+T*u[n+3][r+3],e[h]=v*o+3*(g*a*s+d*f*l)+p*c;return e}:e?function(e,r,n,a,i){var o,s,l,c,u,h;e||(e=[]),r*=3;var f=i*i,p=f*i,d=1-i,g=d*d,v=g*d;for(u=0;u<t.length;u++)o=(h=t[u])[n+1][r]-h[n][r],s=h[n+1][r+1]-h[n][r+1],l=h[n+1][r+2]-h[n][r+2],c=h[n+1][r+3]-h[n][r+3],e[u]=v*o+3*(g*i*s+d*f*l)+p*c;return e}:r?function(e,r,n,a,i){var o,s,l,c;e||(e=[]),n*=3;var u=1-a,h=i*i,f=1-i,p=f*f,d=f*i*2,g=-3*p,v=3*(p-d),m=3*(d-h),y=3*h;for(l=0;l<t.length;l++)o=g*(c=t[l])[n][r]+v*c[n+1][r]+m*c[n+2][r]+y*c[n+3][r],s=g*c[n][r+1]+v*c[n+1][r+1]+m*c[n+2][r+1]+y*c[n+3][r+1],e[l]=u*o+a*s;return e}:function(e,r,n,a,i){var o,s,l,c;e||(e=[]);var u=1-a;for(l=0;l<t.length;l++)o=(c=t[l])[n+1][r]-c[n][r],s=c[n+1][r+1]-c[n][r+1],e[l]=u*o+a*s;return e}}},{}],913:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,a){var i=e-2,o=r-2;return n&&a?function(e,r,n){var a,s,l,c,u,h;e||(e=[]);var f=Math.max(0,Math.min(Math.floor(r),i)),p=Math.max(0,Math.min(Math.floor(n),o)),d=Math.max(0,Math.min(1,r-f)),g=Math.max(0,Math.min(1,n-p));f*=3,p*=3;var v=d*d,m=v*d,y=1-d,x=y*y,b=x*y,_=g*g,w=_*g,k=1-g,T=k*k,M=T*k;for(h=0;h<t.length;h++)a=b*(u=t[h])[p][f]+3*(x*d*u[p][f+1]+y*v*u[p][f+2])+m*u[p][f+3],s=b*u[p+1][f]+3*(x*d*u[p+1][f+1]+y*v*u[p+1][f+2])+m*u[p+1][f+3],l=b*u[p+2][f]+3*(x*d*u[p+2][f+1]+y*v*u[p+2][f+2])+m*u[p+2][f+3],c=b*u[p+3][f]+3*(x*d*u[p+3][f+1]+y*v*u[p+3][f+2])+m*u[p+3][f+3],e[h]=M*a+3*(T*g*s+k*_*l)+w*c;return e}:n?function(e,r,n){e||(e=[]);var a,s,l,c,u,h,f=Math.max(0,Math.min(Math.floor(r),i)),p=Math.max(0,Math.min(Math.floor(n),o)),d=Math.max(0,Math.min(1,r-f)),g=Math.max(0,Math.min(1,n-p));f*=3;var v=d*d,m=v*d,y=1-d,x=y*y,b=x*y,_=1-g;for(u=0;u<t.length;u++)a=_*(h=t[u])[p][f]+g*h[p+1][f],s=_*h[p][f+1]+g*h[p+1][f+1],l=_*h[p][f+2]+g*h[p+1][f+1],c=_*h[p][f+3]+g*h[p+1][f+1],e[u]=b*a+3*(x*d*s+y*v*l)+m*c;return e}:a?function(e,r,n){e||(e=[]);var a,s,l,c,u,h,f=Math.max(0,Math.min(Math.floor(r),i)),p=Math.max(0,Math.min(Math.floor(n),o)),d=Math.max(0,Math.min(1,r-f)),g=Math.max(0,Math.min(1,n-p));p*=3;var v=g*g,m=v*g,y=1-g,x=y*y,b=x*y,_=1-d;for(u=0;u<t.length;u++)a=_*(h=t[u])[p][f]+d*h[p][f+1],s=_*h[p+1][f]+d*h[p+1][f+1],l=_*h[p+2][f]+d*h[p+2][f+1],c=_*h[p+3][f]+d*h[p+3][f+1],e[u]=b*a+3*(x*g*s+y*v*l)+m*c;return e}:function(e,r,n){e||(e=[]);var a,s,l,c,u=Math.max(0,Math.min(Math.floor(r),i)),h=Math.max(0,Math.min(Math.floor(n),o)),f=Math.max(0,Math.min(1,r-u)),p=Math.max(0,Math.min(1,n-h)),d=1-p,g=1-f;for(l=0;l<t.length;l++)a=g*(c=t[l])[h][u]+f*c[h][u+1],s=g*c[h+1][u]+f*c[h+1][u+1],e[l]=d*a+p*s;return e}}},{}],914:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./xy_defaults\"),i=t(\"./ab_defaults\"),o=t(\"./attributes\"),s=t(\"../../components/color/attributes\");e.exports=function(t,e,r,l){function c(r,a){return n.coerce(t,e,o,r,a)}e._clipPathId=\"clip\"+e.uid+\"carpet\";var u=c(\"color\",s.defaultLine);(n.coerceFont(c,\"font\"),c(\"carpet\"),i(t,e,l,c,u),e.a&&e.b)?(e.a.length<3&&(e.aaxis.smoothing=0),e.b.length<3&&(e.baxis.smoothing=0),a(t,e,c)||(e.visible=!1),e._cheater&&c(\"cheaterslope\")):e.visible=!1}},{\"../../components/color/attributes\":591,\"../../lib\":717,\"./ab_defaults\":897,\"./attributes\":899,\"./xy_defaults\":923}],915:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),plot:t(\"./plot\"),calc:t(\"./calc\"),animatable:!0,isContainer:!0,moduleType:\"trace\",name:\"carpet\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"cartesian\",\"svg\",\"carpet\",\"carpetAxis\",\"notLegendIsolatable\",\"noMultiCategory\",\"noHover\",\"noSortingByValue\"],meta:{}}},{\"../../plots/cartesian\":776,\"./attributes\":899,\"./calc\":903,\"./defaults\":914,\"./plot\":920}],916:[function(t,e,r){\"use strict\";e.exports=function(t,e){for(var r,n=t._fullData.length,a=0;a<n;a++){var i=t._fullData[a];if(i.index!==e.index&&(\"carpet\"===i.type&&(r||(r=i),i.carpet===e.carpet)))return i}return r}},{}],917:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){if(0===t.length)return\"\";var n,a=[],i=r?3:1;for(n=0;n<t.length;n+=i)a.push(t[n]+\",\"+e[n]),r&&n<t.length-i&&(a.push(\"C\"),a.push([t[n+1]+\",\"+e[n+1],t[n+2]+\",\"+e[n+2]+\" \"].join(\" \")));return a.join(r?\"\":\"L\")}},{}],918:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").isArrayOrTypedArray;e.exports=function(t,e,r){var a;for(n(t)?t.length>e.length&&(t=t.slice(0,e.length)):t=[],a=0;a<e.length;a++)t[a]=r(e[a]);return t}},{\"../../lib\":717}],919:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,a,i){var o=a[0]*t.dpdx(e),s=a[1]*t.dpdy(r),l=1,c=1;if(i){var u=Math.sqrt(a[0]*a[0]+a[1]*a[1]),h=Math.sqrt(i[0]*i[0]+i[1]*i[1]),f=(a[0]*i[0]+a[1]*i[1])/u/h;c=Math.max(0,f)}var p=180*Math.atan2(s,o)/Math.PI;return p<-90?(p+=180,l=-l):p>90&&(p-=180,l=-l),{angle:p,flip:l,p:t.c2p(n,e,r),offsetMultplier:c}}},{}],920:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../components/drawing\"),i=t(\"./map_1d_array\"),o=t(\"./makepath\"),s=t(\"./orient_text\"),l=t(\"../../lib/svg_text_utils\"),c=t(\"../../lib\"),u=t(\"../../constants/alignment\");function h(t,e,r,a,s,l){var c=\"const-\"+s+\"-lines\",u=r.selectAll(\".\"+c).data(l);u.enter().append(\"path\").classed(c,!0).style(\"vector-effect\",\"non-scaling-stroke\"),u.each(function(r){var a=r,s=a.x,l=a.y,c=i([],s,t.c2p),u=i([],l,e.c2p),h=\"M\"+o(c,u,a.smoothing);n.select(this).attr(\"d\",h).style(\"stroke-width\",a.width).style(\"stroke\",a.color).style(\"fill\",\"none\")}),u.exit().remove()}function f(t,e,r,i,o,c,u,h){var f=c.selectAll(\"text.\"+h).data(u);f.enter().append(\"text\").classed(h,!0);var p=0,d={};return f.each(function(o,c){var u;if(\"auto\"===o.axis.tickangle)u=s(i,e,r,o.xy,o.dxy);else{var h=(o.axis.tickangle+180)*Math.PI/180;u=s(i,e,r,o.xy,[Math.cos(h),Math.sin(h)])}c||(d={angle:u.angle,flip:u.flip});var f=(o.endAnchor?-1:1)*u.flip,g=n.select(this).attr({\"text-anchor\":f>0?\"start\":\"end\",\"data-notex\":1}).call(a.font,o.font).text(o.text).call(l.convertToTspans,t),v=a.bBox(this);g.attr(\"transform\",\"translate(\"+u.p[0]+\",\"+u.p[1]+\") rotate(\"+u.angle+\")translate(\"+o.axis.labelpadding*f+\",\"+.3*v.height+\")\"),p=Math.max(p,v.width+o.axis.labelpadding)}),f.exit().remove(),d.maxExtent=p,d}e.exports=function(t,e,r,a){var l=e.xaxis,u=e.yaxis,p=t._fullLayout._clips;c.makeTraceGroups(a,r,\"trace\").each(function(e){var r=n.select(this),a=e[0],d=a.trace,v=d.aaxis,m=d.baxis,y=c.ensureSingle(r,\"g\",\"minorlayer\"),x=c.ensureSingle(r,\"g\",\"majorlayer\"),b=c.ensureSingle(r,\"g\",\"boundarylayer\"),_=c.ensureSingle(r,\"g\",\"labellayer\");r.style(\"opacity\",d.opacity),h(l,u,x,v,\"a\",v._gridlines),h(l,u,x,m,\"b\",m._gridlines),h(l,u,y,v,\"a\",v._minorgridlines),h(l,u,y,m,\"b\",m._minorgridlines),h(l,u,b,v,\"a-boundary\",v._boundarylines),h(l,u,b,m,\"b-boundary\",m._boundarylines);var w=f(t,l,u,d,a,_,v._labels,\"a-label\"),k=f(t,l,u,d,a,_,m._labels,\"b-label\");!function(t,e,r,n,a,i,o,l){var u,h,f,p,d=c.aggNums(Math.min,null,r.a),v=c.aggNums(Math.max,null,r.a),m=c.aggNums(Math.min,null,r.b),y=c.aggNums(Math.max,null,r.b);u=.5*(d+v),h=m,f=r.ab2xy(u,h,!0),p=r.dxyda_rough(u,h),void 0===o.angle&&c.extendFlat(o,s(r,a,i,f,r.dxydb_rough(u,h)));g(t,e,r,n,f,p,r.aaxis,a,i,o,\"a-title\"),u=d,h=.5*(m+y),f=r.ab2xy(u,h,!0),p=r.dxydb_rough(u,h),void 0===l.angle&&c.extendFlat(l,s(r,a,i,f,r.dxyda_rough(u,h)));g(t,e,r,n,f,p,r.baxis,a,i,l,\"b-title\")}(t,_,d,a,l,u,w,k),function(t,e,r,n,a){var s,l,u,h,f=r.select(\"#\"+t._clipPathId);f.size()||(f=r.append(\"clipPath\").classed(\"carpetclip\",!0));var p=c.ensureSingle(f,\"path\",\"carpetboundary\"),d=e.clipsegments,g=[];for(h=0;h<d.length;h++)s=d[h],l=i([],s.x,n.c2p),u=i([],s.y,a.c2p),g.push(o(l,u,s.bicubic));var v=\"M\"+g.join(\"L\")+\"Z\";f.attr(\"id\",t._clipPathId),p.attr(\"d\",v)}(d,a,p,l,u)})};var p=u.LINE_SPACING,d=(1-u.MID_SHIFT)/p+1;function g(t,e,r,i,o,c,u,h,f,g,v){var m=[];u.title.text&&m.push(u.title.text);var y=e.selectAll(\"text.\"+v).data(m),x=g.maxExtent;y.enter().append(\"text\").classed(v,!0),y.each(function(){var e=s(r,h,f,o,c);-1===[\"start\",\"both\"].indexOf(u.showticklabels)&&(x=0);var i=u.title.font.size;x+=i+u.title.offset;var v=(g.angle+(g.flip<0?180:0)-e.angle+450)%360,m=v>90&&v<270,y=n.select(this);y.text(u.title.text).call(l.convertToTspans,t),m&&(x=(-l.lineCount(y)+d)*p*i-x),y.attr(\"transform\",\"translate(\"+e.p[0]+\",\"+e.p[1]+\") rotate(\"+e.angle+\") translate(0,\"+x+\")\").classed(\"user-select-none\",!0).attr(\"text-anchor\",\"middle\").call(a.font,u.title.font)}),y.exit().remove()}},{\"../../components/drawing\":613,\"../../constants/alignment\":686,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"./makepath\":917,\"./map_1d_array\":918,\"./orient_text\":919,d3:165}],921:[function(t,e,r){\"use strict\";var n=t(\"./constants\"),a=t(\"../../lib/search\").findBin,i=t(\"./compute_control_points\"),o=t(\"./create_spline_evaluator\"),s=t(\"./create_i_derivative_evaluator\"),l=t(\"./create_j_derivative_evaluator\");e.exports=function(t){var e=t._a,r=t._b,c=e.length,u=r.length,h=t.aaxis,f=t.baxis,p=e[0],d=e[c-1],g=r[0],v=r[u-1],m=e[e.length-1]-e[0],y=r[r.length-1]-r[0],x=m*n.RELATIVE_CULL_TOLERANCE,b=y*n.RELATIVE_CULL_TOLERANCE;p-=x,d+=x,g-=b,v+=b,t.isVisible=function(t,e){return t>p&&t<d&&e>g&&e<v},t.isOccluded=function(t,e){return t<p||t>d||e<g||e>v},t.setScale=function(){var e=t._x,r=t._y,n=i(t._xctrl,t._yctrl,e,r,h.smoothing,f.smoothing);t._xctrl=n[0],t._yctrl=n[1],t.evalxy=o([t._xctrl,t._yctrl],c,u,h.smoothing,f.smoothing),t.dxydi=s([t._xctrl,t._yctrl],h.smoothing,f.smoothing),t.dxydj=l([t._xctrl,t._yctrl],h.smoothing,f.smoothing)},t.i2a=function(t){var r=Math.max(0,Math.floor(t[0]),c-2),n=t[0]-r;return(1-n)*e[r]+n*e[r+1]},t.j2b=function(t){var e=Math.max(0,Math.floor(t[1]),c-2),n=t[1]-e;return(1-n)*r[e]+n*r[e+1]},t.ij2ab=function(e){return[t.i2a(e[0]),t.j2b(e[1])]},t.a2i=function(t){var r=Math.max(0,Math.min(a(t,e),c-2)),n=e[r],i=e[r+1];return Math.max(0,Math.min(c-1,r+(t-n)/(i-n)))},t.b2j=function(t){var e=Math.max(0,Math.min(a(t,r),u-2)),n=r[e],i=r[e+1];return Math.max(0,Math.min(u-1,e+(t-n)/(i-n)))},t.ab2ij=function(e){return[t.a2i(e[0]),t.b2j(e[1])]},t.i2c=function(e,r){return t.evalxy([],e,r)},t.ab2xy=function(n,a,i){if(!i&&(n<e[0]||n>e[c-1]|a<r[0]||a>r[u-1]))return[!1,!1];var o=t.a2i(n),s=t.b2j(a),l=t.evalxy([],o,s);if(i){var h,f,p,d,g=0,v=0,m=[];n<e[0]?(h=0,f=0,g=(n-e[0])/(e[1]-e[0])):n>e[c-1]?(h=c-2,f=1,g=(n-e[c-1])/(e[c-1]-e[c-2])):f=o-(h=Math.max(0,Math.min(c-2,Math.floor(o)))),a<r[0]?(p=0,d=0,v=(a-r[0])/(r[1]-r[0])):a>r[u-1]?(p=u-2,d=1,v=(a-r[u-1])/(r[u-1]-r[u-2])):d=s-(p=Math.max(0,Math.min(u-2,Math.floor(s)))),g&&(t.dxydi(m,h,p,f,d),l[0]+=m[0]*g,l[1]+=m[1]*g),v&&(t.dxydj(m,h,p,f,d),l[0]+=m[0]*v,l[1]+=m[1]*v)}return l},t.c2p=function(t,e,r){return[e.c2p(t[0]),r.c2p(t[1])]},t.p2x=function(t,e,r){return[e.p2c(t[0]),r.p2c(t[1])]},t.dadi=function(t){var r=Math.max(0,Math.min(e.length-2,t));return e[r+1]-e[r]},t.dbdj=function(t){var e=Math.max(0,Math.min(r.length-2,t));return r[e+1]-r[e]},t.dxyda=function(e,r,n,a){var i=t.dxydi(null,e,r,n,a),o=t.dadi(e,n);return[i[0]/o,i[1]/o]},t.dxydb=function(e,r,n,a){var i=t.dxydj(null,e,r,n,a),o=t.dbdj(r,a);return[i[0]/o,i[1]/o]},t.dxyda_rough=function(e,r,n){var a=m*(n||.1),i=t.ab2xy(e+a,r,!0),o=t.ab2xy(e-a,r,!0);return[.5*(i[0]-o[0])/a,.5*(i[1]-o[1])/a]},t.dxydb_rough=function(e,r,n){var a=y*(n||.1),i=t.ab2xy(e,r+a,!0),o=t.ab2xy(e,r-a,!0);return[.5*(i[0]-o[0])/a,.5*(i[1]-o[1])/a]},t.dpdx=function(t){return t._m},t.dpdy=function(t){return t._m}}},{\"../../lib/search\":736,\"./compute_control_points\":909,\"./constants\":910,\"./create_i_derivative_evaluator\":911,\"./create_j_derivative_evaluator\":912,\"./create_spline_evaluator\":913}],922:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e,r){var a,i,o,s=[],l=[],c=t[0].length,u=t.length;function h(e,r){var n,a=0,i=0;return e>0&&void 0!==(n=t[r][e-1])&&(i++,a+=n),e<c-1&&void 0!==(n=t[r][e+1])&&(i++,a+=n),r>0&&void 0!==(n=t[r-1][e])&&(i++,a+=n),r<u-1&&void 0!==(n=t[r+1][e])&&(i++,a+=n),a/Math.max(1,i)}var f,p,d,g,v,m,y,x,b,_,w,k=0;for(a=0;a<c;a++)for(i=0;i<u;i++)void 0===t[i][a]&&(s.push(a),l.push(i),t[i][a]=h(a,i)),k=Math.max(k,Math.abs(t[i][a]));if(!s.length)return t;var T=0,M=0,A=s.length;do{for(T=0,o=0;o<A;o++){a=s[o],i=l[o];var S,E,L,C,P,O,z=0,I=0;0===a?(L=e[P=Math.min(c-1,2)],C=e[1],S=t[i][P],I+=(E=t[i][1])+(E-S)*(e[0]-C)/(C-L),z++):a===c-1&&(L=e[P=Math.max(0,c-3)],C=e[c-2],S=t[i][P],I+=(E=t[i][c-2])+(E-S)*(e[c-1]-C)/(C-L),z++),(0===a||a===c-1)&&i>0&&i<u-1&&(f=r[i+1]-r[i],I+=((p=r[i]-r[i-1])*t[i+1][a]+f*t[i-1][a])/(p+f),z++),0===i?(L=r[O=Math.min(u-1,2)],C=r[1],S=t[O][a],I+=(E=t[1][a])+(E-S)*(r[0]-C)/(C-L),z++):i===u-1&&(L=r[O=Math.max(0,u-3)],C=r[u-2],S=t[O][a],I+=(E=t[u-2][a])+(E-S)*(r[u-1]-C)/(C-L),z++),(0===i||i===u-1)&&a>0&&a<c-1&&(f=e[a+1]-e[a],I+=((p=e[a]-e[a-1])*t[i][a+1]+f*t[i][a-1])/(p+f),z++),z?I/=z:(d=e[a+1]-e[a],g=e[a]-e[a-1],x=(v=r[i+1]-r[i])*(m=r[i]-r[i-1])*(v+m),I=((y=d*g*(d+g))*(m*t[i+1][a]+v*t[i-1][a])+x*(g*t[i][a+1]+d*t[i][a-1]))/(x*(g+d)+y*(m+v))),T+=(_=(b=I-t[i][a])/k)*_,w=z?0:.85,t[i][a]+=b*(1+w)}T=Math.sqrt(T)}while(M++<100&&T>1e-5);return n.log(\"Smoother converged to\",T,\"after\",M,\"iterations\"),t}},{\"../../lib\":717}],923:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").isArray1D;e.exports=function(t,e,r){var a=r(\"x\"),i=a&&a.length,o=r(\"y\"),s=o&&o.length;if(!i&&!s)return!1;if(e._cheater=!a,i&&!n(a)||s&&!n(o))e._length=null;else{var l=i?a.length:1/0;s&&(l=Math.min(l,o.length)),e.a&&e.a.length&&(l=Math.min(l,e.a.length)),e.b&&e.b.length&&(l=Math.min(l,e.b.length)),e._length=l}return!0}},{\"../../lib\":717}],924:[function(t,e,r){\"use strict\";var n=t(\"../../plots/template_attributes\").hovertemplateAttrs,a=t(\"../scattergeo/attributes\"),i=t(\"../../components/colorscale/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../components/color/attributes\").defaultLine,l=t(\"../../lib/extend\").extendFlat,c=a.marker.line;e.exports=l({locations:{valType:\"data_array\",editType:\"calc\"},locationmode:a.locationmode,z:{valType:\"data_array\",editType:\"calc\"},geojson:l({},a.geojson,{}),featureidkey:a.featureidkey,text:l({},a.text,{}),hovertext:l({},a.hovertext,{}),marker:{line:{color:l({},c.color,{dflt:s}),width:l({},c.width,{dflt:1}),editType:\"calc\"},opacity:{valType:\"number\",arrayOk:!0,min:0,max:1,dflt:1,editType:\"style\"},editType:\"calc\"},selected:{marker:{opacity:a.selected.marker.opacity,editType:\"plot\"},editType:\"plot\"},unselected:{marker:{opacity:a.unselected.marker.opacity,editType:\"plot\"},editType:\"plot\"},hoverinfo:l({},o.hoverinfo,{editType:\"calc\",flags:[\"location\",\"z\",\"text\",\"name\"]}),hovertemplate:n(),showlegend:l({},o.showlegend,{dflt:!1})},i(\"\",{cLetter:\"z\",editTypeOverride:\"calc\"}))},{\"../../components/color/attributes\":591,\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"../scattergeo/attributes\":1161}],925:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../constants/numerical\").BADNUM,i=t(\"../../components/colorscale/calc\"),o=t(\"../scatter/arrays_to_calcdata\"),s=t(\"../scatter/calc_selection\");function l(t){return t&&\"string\"==typeof t}e.exports=function(t,e){var r,c=e._length,u=new Array(c);r=e.geojson?function(t){return l(t)||n(t)}:l;for(var h=0;h<c;h++){var f=u[h]={},p=e.locations[h],d=e.z[h];r(p)&&n(d)?(f.loc=p,f.z=d):(f.loc=null,f.z=a),f.index=h}return o(u,e),i(t,e,{vals:e.z,containerStr:\"\",cLetter:\"z\"}),s(u,e),u}},{\"../../components/colorscale/calc\":600,\"../../constants/numerical\":693,\"../scatter/arrays_to_calcdata\":1119,\"../scatter/calc_selection\":1122,\"fast-isnumeric\":228}],926:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/colorscale/defaults\"),i=t(\"./attributes\");e.exports=function(t,e,r,o){function s(r,a){return n.coerce(t,e,i,r,a)}var l=s(\"locations\"),c=s(\"z\");if(l&&l.length&&n.isArrayOrTypedArray(c)&&c.length){e._length=Math.min(l.length,c.length);var u,h=s(\"geojson\");(\"string\"==typeof h&&\"\"!==h||n.isPlainObject(h))&&(u=\"geojson-id\"),\"geojson-id\"===s(\"locationmode\",u)&&s(\"featureidkey\"),s(\"text\"),s(\"hovertext\"),s(\"hovertemplate\"),s(\"marker.line.width\")&&s(\"marker.line.color\"),s(\"marker.opacity\"),a(t,e,o,s,{prefix:\"\",cLetter:\"z\"}),n.coerceSelectionMarkerOpacity(e,s)}else e.visible=!1}},{\"../../components/colorscale/defaults\":602,\"../../lib\":717,\"./attributes\":924}],927:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,a){t.location=e.location,t.z=e.z;var i=n[a];return i.fIn&&i.fIn.properties&&(t.properties=i.fIn.properties),t.ct=i.ct,t}},{}],928:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\"),a=t(\"./attributes\"),i=t(\"../../lib\").fillText;e.exports=function(t,e,r){var o,s,l,c,u=t.cd,h=u[0].trace,f=t.subplot;for(s=0;s<u.length;s++)if(c=!1,(o=u[s])._polygons){for(l=0;l<o._polygons.length;l++)o._polygons[l].contains([e,r])&&(c=!c),o._polygons[l].contains([e+360,r])&&(c=!c);if(c)break}if(c&&o)return t.x0=t.x1=t.xa.c2p(o.ct),t.y0=t.y1=t.ya.c2p(o.ct),t.index=o.index,t.location=o.loc,t.z=o.z,t.zLabel=n.tickText(f.mockAxis,f.mockAxis.c2l(o.z),\"hover\").text,t.hovertemplate=o.hovertemplate,function(t,e,r){if(e.hovertemplate)return;var n=r.hi||e.hoverinfo,o=String(r.loc),s=\"all\"===n?a.hoverinfo.flags:n.split(\"+\"),l=-1!==s.indexOf(\"name\"),c=-1!==s.indexOf(\"location\"),u=-1!==s.indexOf(\"z\"),h=-1!==s.indexOf(\"text\"),f=[];!l&&c?t.nameOverride=o:(l&&(t.nameOverride=e.name),c&&f.push(o));u&&f.push(t.zLabel);h&&i(r,e,f);t.extraText=f.join(\"<br>\")}(t,h,o,f.mockAxis),[t]}},{\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"./attributes\":924}],929:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),colorbar:t(\"../heatmap/colorbar\"),calc:t(\"./calc\"),calcGeoJSON:t(\"./plot\").calcGeoJSON,plot:t(\"./plot\").plot,style:t(\"./style\").style,styleOnSelect:t(\"./style\").styleOnSelect,hoverPoints:t(\"./hover\"),eventData:t(\"./event_data\"),selectPoints:t(\"./select\"),moduleType:\"trace\",name:\"choropleth\",basePlotModule:t(\"../../plots/geo\"),categories:[\"geo\",\"noOpacity\",\"showLegend\"],meta:{}}},{\"../../plots/geo\":795,\"../heatmap/colorbar\":1003,\"./attributes\":924,\"./calc\":925,\"./defaults\":926,\"./event_data\":927,\"./hover\":928,\"./plot\":930,\"./select\":931,\"./style\":932}],930:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\"),i=t(\"../../lib/geo_location_utils\"),o=t(\"../../lib/topojson_utils\").getTopojsonFeatures,s=t(\"../../plots/cartesian/autorange\").findExtremes,l=t(\"./style\").style;e.exports={calcGeoJSON:function(t,e){for(var r=t[0].trace,n=e[r.geo],a=n._subplot,l=r.locationmode,c=r._length,u=\"geojson-id\"===l?i.extractTraceFeature(t):o(r,a.topojson),h=[],f=[],p=0;p<c;p++){var d=t[p],g=\"geojson-id\"===l?d.fOut:i.locationToFeature(l,d.loc,u);if(g){d.geojson=g,d.ct=g.properties.ct,d._polygons=i.feature2polygons(g);var v=i.computeBbox(g);h.push(v[0],v[2]),f.push(v[1],v[3])}else d.geojson=null}if(\"geojson\"===n.fitbounds&&\"geojson-id\"===l){var m=i.computeBbox(i.getTraceGeojson(r));h=[m[0],m[2]],f=[m[1],m[3]]}var y={padded:!0};r._extremes.lon=s(n.lonaxis._ax,h,y),r._extremes.lat=s(n.lataxis._ax,f,y)},plot:function(t,e,r){var i=e.layers.backplot.select(\".choroplethlayer\");a.makeTraceGroups(i,r,\"trace choropleth\").each(function(e){var r=n.select(this).selectAll(\"path.choroplethlocation\").data(a.identity);r.enter().append(\"path\").classed(\"choroplethlocation\",!0),r.exit().remove(),l(t,e)})}}},{\"../../lib\":717,\"../../lib/geo_location_utils\":711,\"../../lib/topojson_utils\":744,\"../../plots/cartesian/autorange\":764,\"./style\":932,d3:165}],931:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r,n,a,i,o,s=t.cd,l=t.xaxis,c=t.yaxis,u=[];if(!1===e)for(r=0;r<s.length;r++)s[r].selected=0;else for(r=0;r<s.length;r++)(a=(n=s[r]).ct)&&(i=l.c2p(a),o=c.c2p(a),e.contains([i,o],null,r,t)?(u.push({pointNumber:r,lon:a[0],lat:a[1]}),n.selected=1):n.selected=0);return u}},{}],932:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../components/color\"),i=t(\"../../components/drawing\"),o=t(\"../../components/colorscale\");function s(t,e){var r=e[0].trace,s=e[0].node3.selectAll(\".choroplethlocation\"),l=r.marker||{},c=l.line||{},u=o.makeColorScaleFuncFromTrace(r);s.each(function(t){n.select(this).attr(\"fill\",u(t.z)).call(a.stroke,t.mlc||c.color).call(i.dashLine,\"\",t.mlw||c.width||0).style(\"opacity\",l.opacity)}),i.selectedPointStyle(s,r,t)}e.exports={style:function(t,e){e&&s(t,e)},styleOnSelect:function(t,e){var r=e[0].node3,n=e[0].trace;n.selectedpoints?i.selectedPointStyle(r.selectAll(\".choroplethlocation\"),n,t):s(t,e)}}},{\"../../components/color\":592,\"../../components/colorscale\":604,\"../../components/drawing\":613,d3:165}],933:[function(t,e,r){\"use strict\";var n=t(\"../choropleth/attributes\"),a=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../../plots/attributes\"),s=t(\"../../lib/extend\").extendFlat;e.exports=s({locations:{valType:\"data_array\",editType:\"calc\"},z:{valType:\"data_array\",editType:\"calc\"},geojson:{valType:\"any\",editType:\"calc\"},featureidkey:s({},n.featureidkey,{}),below:{valType:\"string\",editType:\"plot\"},text:n.text,hovertext:n.hovertext,marker:{line:{color:s({},n.marker.line.color,{editType:\"plot\"}),width:s({},n.marker.line.width,{editType:\"plot\"}),editType:\"calc\"},opacity:s({},n.marker.opacity,{editType:\"plot\"}),editType:\"calc\"},selected:{marker:{opacity:s({},n.selected.marker.opacity,{editType:\"plot\"}),editType:\"plot\"},editType:\"plot\"},unselected:{marker:{opacity:s({},n.unselected.marker.opacity,{editType:\"plot\"}),editType:\"plot\"},editType:\"plot\"},hoverinfo:n.hoverinfo,hovertemplate:i({},{keys:[\"properties\"]}),showlegend:s({},o.showlegend,{dflt:!1})},a(\"\",{cLetter:\"z\",editTypeOverride:\"calc\"}))},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"../choropleth/attributes\":924}],934:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib\"),i=t(\"../../components/colorscale\"),o=t(\"../../components/drawing\"),s=t(\"../../lib/geojson_utils\").makeBlank,l=t(\"../../lib/geo_location_utils\");function c(t){var e,r=t[0].trace,n=r._opts;if(r.selectedpoints){for(var i=o.makeSelectedPointStyleFns(r),s=0;s<t.length;s++){var l=t[s];l.fOut&&(l.fOut.properties.mo2=i.selectedOpacityFn(l))}e={type:\"identity\",property:\"mo2\"}}else e=a.isArrayOrTypedArray(r.marker.opacity)?{type:\"identity\",property:\"mo\"}:r.marker.opacity;return a.extendFlat(n.fill.paint,{\"fill-opacity\":e}),a.extendFlat(n.line.paint,{\"line-opacity\":e}),n}e.exports={convert:function(t){var e=t[0].trace,r=!0===e.visible&&0!==e._length,o={layout:{visibility:\"none\"},paint:{}},u={layout:{visibility:\"none\"},paint:{}},h=e._opts={fill:o,line:u,geojson:s()};if(!r)return h;var f=l.extractTraceFeature(t);if(!f)return h;var p,d,g,v=i.makeColorScaleFuncFromTrace(e),m=e.marker,y=m.line||{};a.isArrayOrTypedArray(m.opacity)&&(p=function(t){var e=t.mo;return n(e)?+a.constrain(e,0,1):0}),a.isArrayOrTypedArray(y.color)&&(d=function(t){return t.mlc}),a.isArrayOrTypedArray(y.width)&&(g=function(t){return t.mlw});for(var x=0;x<t.length;x++){var b=t[x],_=b.fOut;if(_){var w=_.properties;w.fc=v(b.z),p&&(w.mo=p(b)),d&&(w.mlc=d(b)),g&&(w.mlw=g(b)),b.ct=w.ct,b._polygons=l.feature2polygons(_)}}var k=p?{type:\"identity\",property:\"mo\"}:m.opacity;return a.extendFlat(o.paint,{\"fill-color\":{type:\"identity\",property:\"fc\"},\"fill-opacity\":k}),a.extendFlat(u.paint,{\"line-color\":d?{type:\"identity\",property:\"mlc\"}:y.color,\"line-width\":g?{type:\"identity\",property:\"mlw\"}:y.width,\"line-opacity\":k}),o.layout.visibility=\"visible\",u.layout.visibility=\"visible\",h.geojson={type:\"FeatureCollection\",features:f},c(t),h},convertOnSelect:c}},{\"../../components/colorscale\":604,\"../../components/drawing\":613,\"../../lib\":717,\"../../lib/geo_location_utils\":711,\"../../lib/geojson_utils\":712,\"fast-isnumeric\":228}],935:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/colorscale/defaults\"),i=t(\"./attributes\");e.exports=function(t,e,r,o){function s(r,a){return n.coerce(t,e,i,r,a)}var l=s(\"locations\"),c=s(\"z\"),u=s(\"geojson\");n.isArrayOrTypedArray(l)&&l.length&&n.isArrayOrTypedArray(c)&&c.length&&(\"string\"==typeof u&&\"\"!==u||n.isPlainObject(u))?(s(\"featureidkey\"),e._length=Math.min(l.length,c.length),s(\"below\"),s(\"text\"),s(\"hovertext\"),s(\"hovertemplate\"),s(\"marker.line.width\")&&s(\"marker.line.color\"),s(\"marker.opacity\"),a(t,e,o,s,{prefix:\"\",cLetter:\"z\"}),n.coerceSelectionMarkerOpacity(e,s)):e.visible=!1}},{\"../../components/colorscale/defaults\":602,\"../../lib\":717,\"./attributes\":933}],936:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),colorbar:t(\"../heatmap/colorbar\"),calc:t(\"../choropleth/calc\"),plot:t(\"./plot\"),hoverPoints:t(\"../choropleth/hover\"),eventData:t(\"../choropleth/event_data\"),selectPoints:t(\"../choropleth/select\"),styleOnSelect:function(t,e){e&&e[0].trace._glTrace.updateOnSelect(e)},getBelow:function(t,e){for(var r=e.getMapLayers(),n=r.length-2;n>=0;n--){var a=r[n].id;if(\"string\"==typeof a&&0===a.indexOf(\"water\"))for(var i=n+1;i<r.length;i++)if(\"string\"==typeof(a=r[i].id)&&-1===a.indexOf(\"plotly-\"))return a}},moduleType:\"trace\",name:\"choroplethmapbox\",basePlotModule:t(\"../../plots/mapbox\"),categories:[\"mapbox\",\"gl\",\"noOpacity\",\"showLegend\"],meta:{hr_name:\"choropleth_mapbox\"}}},{\"../../plots/mapbox\":820,\"../choropleth/calc\":925,\"../choropleth/event_data\":927,\"../choropleth/hover\":928,\"../choropleth/select\":931,\"../heatmap/colorbar\":1003,\"./attributes\":933,\"./defaults\":935,\"./plot\":937}],937:[function(t,e,r){\"use strict\";var n=t(\"./convert\").convert,a=t(\"./convert\").convertOnSelect,i=t(\"../../plots/mapbox/constants\").traceLayerPrefix;function o(t,e){this.type=\"choroplethmapbox\",this.subplot=t,this.uid=e,this.sourceId=\"source-\"+e,this.layerList=[[\"fill\",i+e+\"-fill\"],[\"line\",i+e+\"-line\"]],this.below=null}var s=o.prototype;s.update=function(t){this._update(n(t))},s.updateOnSelect=function(t){this._update(a(t))},s._update=function(t){var e=this.subplot,r=this.layerList,n=e.belowLookup[\"trace-\"+this.uid];e.map.getSource(this.sourceId).setData(t.geojson),n!==this.below&&(this._removeLayers(),this._addLayers(t,n),this.below=n);for(var a=0;a<r.length;a++){var i=r[a],o=i[0],s=i[1],l=t[o];e.setOptions(s,\"setLayoutProperty\",l.layout),\"visible\"===l.layout.visibility&&e.setOptions(s,\"setPaintProperty\",l.paint)}},s._addLayers=function(t,e){for(var r=this.subplot,n=this.layerList,a=this.sourceId,i=0;i<n.length;i++){var o=n[i],s=o[0],l=t[s];r.addLayer({type:s,id:o[1],source:a,layout:l.layout,paint:l.paint},e)}},s._removeLayers=function(){for(var t=this.subplot.map,e=this.layerList,r=e.length-1;r>=0;r--)t.removeLayer(e[r][1])},s.dispose=function(){var t=this.subplot.map;this._removeLayers(),t.removeSource(this.sourceId)},e.exports=function(t,e){var r=e[0].trace,a=new o(t,r.uid),i=a.sourceId,s=n(e),l=a.below=t.belowLookup[\"trace-\"+r.uid];return t.map.addSource(i,{type:\"geojson\",data:s.geojson}),a._addLayers(s,l),e[0].trace._glTrace=a,a}},{\"../../plots/mapbox/constants\":818,\"./convert\":934}],938:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/attributes\"),a=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../mesh3d/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../lib/extend\").extendFlat,l={x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},u:{valType:\"data_array\",editType:\"calc\"},v:{valType:\"data_array\",editType:\"calc\"},w:{valType:\"data_array\",editType:\"calc\"},sizemode:{valType:\"enumerated\",values:[\"scaled\",\"absolute\"],editType:\"calc\",dflt:\"scaled\"},sizeref:{valType:\"number\",editType:\"calc\",min:0},anchor:{valType:\"enumerated\",editType:\"calc\",values:[\"tip\",\"tail\",\"cm\",\"center\"],dflt:\"cm\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertemplate:a({editType:\"calc\"},{keys:[\"norm\"]}),showlegend:s({},o.showlegend,{dflt:!1})};s(l,n(\"\",{colorAttr:\"u/v/w norm\",showScaleDflt:!0,editTypeOverride:\"calc\"}));[\"opacity\",\"lightposition\",\"lighting\"].forEach(function(t){l[t]=i[t]}),l.hoverinfo=s({},o.hoverinfo,{editType:\"calc\",flags:[\"x\",\"y\",\"z\",\"u\",\"v\",\"w\",\"norm\",\"text\",\"name\"],dflt:\"x+y+z+norm+text+name\"}),l.transforms=void 0,e.exports=l},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"../mesh3d/attributes\":1061}],939:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/calc\");e.exports=function(t,e){for(var r=e.u,a=e.v,i=e.w,o=Math.min(e.x.length,e.y.length,e.z.length,r.length,a.length,i.length),s=-1/0,l=1/0,c=0;c<o;c++){var u=r[c],h=a[c],f=i[c],p=Math.sqrt(u*u+h*h+f*f);s=Math.max(s,p),l=Math.min(l,p)}e._len=o,e._normMax=s,n(t,e,{vals:[l,s],containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":600}],940:[function(t,e,r){\"use strict\";var n=t(\"gl-cone3d\"),a=t(\"gl-cone3d\").createConeMesh,i=t(\"../../lib\").simpleMap,o=t(\"../../lib/gl_format_color\").parseColorScale,s=t(\"../../components/colorscale\").extractOpts,l=t(\"../../plots/gl3d/zip3\");function c(t,e){this.scene=t,this.uid=e,this.mesh=null,this.data=null}var u=c.prototype;u.handlePick=function(t){if(t.object===this.mesh){var e=t.index=t.data.index,r=this.data.x[e],n=this.data.y[e],a=this.data.z[e],i=this.data.u[e],o=this.data.v[e],s=this.data.w[e];t.traceCoordinate=[r,n,a,i,o,s,Math.sqrt(i*i+o*o+s*s)];var l=this.data.hovertext||this.data.text;return Array.isArray(l)&&void 0!==l[e]?t.textLabel=l[e]:l&&(t.textLabel=l),!0}};var h={xaxis:0,yaxis:1,zaxis:2},f={tip:1,tail:0,cm:.25,center:.5},p={tip:1,tail:1,cm:.75,center:.5};function d(t,e){var r=t.fullSceneLayout,a=t.dataScale,c={};function u(t,e){var n=r[e],o=a[h[e]];return i(t,function(t){return n.d2l(t)*o})}c.vectors=l(u(e.u,\"xaxis\"),u(e.v,\"yaxis\"),u(e.w,\"zaxis\"),e._len),c.positions=l(u(e.x,\"xaxis\"),u(e.y,\"yaxis\"),u(e.z,\"zaxis\"),e._len);var d=s(e);c.colormap=o(e),c.vertexIntensityBounds=[d.min/e._normMax,d.max/e._normMax],c.coneOffset=f[e.anchor],\"scaled\"===e.sizemode?c.coneSize=e.sizeref||.5:c.coneSize=e.sizeref&&e._normMax?e.sizeref/e._normMax:.5;var g=n(c),v=e.lightposition;return g.lightPosition=[v.x,v.y,v.z],g.ambient=e.lighting.ambient,g.diffuse=e.lighting.diffuse,g.specular=e.lighting.specular,g.roughness=e.lighting.roughness,g.fresnel=e.lighting.fresnel,g.opacity=e.opacity,e._pad=p[e.anchor]*g.vectorScale*g.coneScale*e._normMax,g}u.update=function(t){this.data=t;var e=d(this.scene,t);this.mesh.update(e)},u.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()},e.exports=function(t,e){var r=t.glplot.gl,n=d(t,e),i=a(r,n),o=new c(t,e.uid);return o.mesh=i,o.data=e,i._trace=o,t.glplot.add(i),o}},{\"../../components/colorscale\":604,\"../../lib\":717,\"../../lib/gl_format_color\":714,\"../../plots/gl3d/zip3\":816,\"gl-cone3d\":245}],941:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/colorscale/defaults\"),i=t(\"./attributes\");e.exports=function(t,e,r,o){function s(r,a){return n.coerce(t,e,i,r,a)}var l=s(\"u\"),c=s(\"v\"),u=s(\"w\"),h=s(\"x\"),f=s(\"y\"),p=s(\"z\");l&&l.length&&c&&c.length&&u&&u.length&&h&&h.length&&f&&f.length&&p&&p.length?(s(\"sizeref\"),s(\"sizemode\"),s(\"anchor\"),s(\"lighting.ambient\"),s(\"lighting.diffuse\"),s(\"lighting.specular\"),s(\"lighting.roughness\"),s(\"lighting.fresnel\"),s(\"lightposition.x\"),s(\"lightposition.y\"),s(\"lightposition.z\"),a(t,e,o,s,{prefix:\"\",cLetter:\"c\"}),s(\"text\"),s(\"hovertext\"),s(\"hovertemplate\"),e._length=null):e.visible=!1}},{\"../../components/colorscale/defaults\":602,\"../../lib\":717,\"./attributes\":938}],942:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"cone\",basePlotModule:t(\"../../plots/gl3d\"),categories:[\"gl3d\",\"showLegend\"],attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),colorbar:{min:\"cmin\",max:\"cmax\"},calc:t(\"./calc\"),plot:t(\"./convert\"),eventData:function(t,e){return t.norm=e.traceCoordinate[6],t},meta:{}}},{\"../../plots/gl3d\":805,\"./attributes\":938,\"./calc\":939,\"./convert\":940,\"./defaults\":941}],943:[function(t,e,r){\"use strict\";var n=t(\"../heatmap/attributes\"),a=t(\"../scatter/attributes\"),i=t(\"../../components/colorscale/attributes\"),o=t(\"../../components/drawing/attributes\").dash,s=t(\"../../plots/font_attributes\"),l=t(\"../../lib/extend\").extendFlat,c=t(\"../../constants/filter_ops\"),u=c.COMPARISON_OPS2,h=c.INTERVAL_OPS,f=(t(\"../../constants/docs\").FORMAT_LINK,a.line);e.exports=l({z:n.z,x:n.x,x0:n.x0,dx:n.dx,y:n.y,y0:n.y0,dy:n.dy,text:n.text,hovertext:n.hovertext,transpose:n.transpose,xtype:n.xtype,ytype:n.ytype,zhoverformat:n.zhoverformat,hovertemplate:n.hovertemplate,hoverongaps:n.hoverongaps,connectgaps:l({},n.connectgaps,{}),fillcolor:{valType:\"color\",editType:\"calc\"},autocontour:{valType:\"boolean\",dflt:!0,editType:\"calc\",impliedEdits:{\"contours.start\":void 0,\"contours.end\":void 0,\"contours.size\":void 0}},ncontours:{valType:\"integer\",dflt:15,min:1,editType:\"calc\"},contours:{type:{valType:\"enumerated\",values:[\"levels\",\"constraint\"],dflt:\"levels\",editType:\"calc\"},start:{valType:\"number\",dflt:null,editType:\"plot\",impliedEdits:{\"^autocontour\":!1}},end:{valType:\"number\",dflt:null,editType:\"plot\",impliedEdits:{\"^autocontour\":!1}},size:{valType:\"number\",dflt:null,min:0,editType:\"plot\",impliedEdits:{\"^autocontour\":!1}},coloring:{valType:\"enumerated\",values:[\"fill\",\"heatmap\",\"lines\",\"none\"],dflt:\"fill\",editType:\"calc\"},showlines:{valType:\"boolean\",dflt:!0,editType:\"plot\"},showlabels:{valType:\"boolean\",dflt:!1,editType:\"plot\"},labelfont:s({editType:\"plot\",colorEditType:\"style\"}),labelformat:{valType:\"string\",dflt:\"\",editType:\"plot\"},operation:{valType:\"enumerated\",values:[].concat(u).concat(h),dflt:\"=\",editType:\"calc\"},value:{valType:\"any\",dflt:0,editType:\"calc\"},editType:\"calc\",impliedEdits:{autocontour:!1}},line:{color:l({},f.color,{editType:\"style+colorbars\"}),width:{valType:\"number\",min:0,editType:\"style+colorbars\"},dash:o,smoothing:l({},f.smoothing,{}),editType:\"plot\"}},i(\"\",{cLetter:\"z\",autoColorDflt:!1,editTypeOverride:\"calc\"}))},{\"../../components/colorscale/attributes\":599,\"../../components/drawing/attributes\":612,\"../../constants/docs\":688,\"../../constants/filter_ops\":689,\"../../lib/extend\":708,\"../../plots/font_attributes\":791,\"../heatmap/attributes\":1e3,\"../scatter/attributes\":1120}],944:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale\"),a=t(\"../heatmap/calc\"),i=t(\"./set_contours\"),o=t(\"./end_plus\");e.exports=function(t,e){var r=a(t,e),s=r[0].z;i(e,s);var l,c=e.contours,u=n.extractOpts(e);if(\"heatmap\"===c.coloring&&u.auto&&!1===e.autocontour){var h=c.start,f=o(c),p=c.size||1,d=Math.floor((f-h)/p)+1;isFinite(p)||(p=1,d=1);var g=h-p/2;l=[g,g+d*p]}else l=s;return n.calc(t,e,{vals:l,cLetter:\"z\"}),r}},{\"../../components/colorscale\":604,\"../heatmap/calc\":1001,\"./end_plus\":954,\"./set_contours\":962}],945:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r,n=t[0],a=n.z;switch(e.type){case\"levels\":var i=Math.min(a[0][0],a[0][1]);for(r=0;r<t.length;r++){var o=t[r];o.prefixBoundary=!o.edgepaths.length&&(i>o.level||o.starts.length&&i===o.level)}break;case\"constraint\":if(n.prefixBoundary=!1,n.edgepaths.length)return;var s=n.x.length,l=n.y.length,c=-1/0,u=1/0;for(r=0;r<l;r++)u=Math.min(u,a[r][0]),u=Math.min(u,a[r][s-1]),c=Math.max(c,a[r][0]),c=Math.max(c,a[r][s-1]);for(r=1;r<s-1;r++)u=Math.min(u,a[0][r]),u=Math.min(u,a[l-1][r]),c=Math.max(c,a[0][r]),c=Math.max(c,a[l-1][r]);var h,f,p=e.value;switch(e._operation){case\">\":p>c&&(n.prefixBoundary=!0);break;case\"<\":(p<u||n.starts.length&&p===u)&&(n.prefixBoundary=!0);break;case\"[]\":h=Math.min(p[0],p[1]),((f=Math.max(p[0],p[1]))<u||h>c||n.starts.length&&f===u)&&(n.prefixBoundary=!0);break;case\"][\":h=Math.min(p[0],p[1]),f=Math.max(p[0],p[1]),h<u&&f>c&&(n.prefixBoundary=!0)}}}},{}],946:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale\"),a=t(\"./make_color_map\"),i=t(\"./end_plus\");e.exports={min:\"zmin\",max:\"zmax\",calc:function(t,e,r){var o=e.contours,s=e.line,l=o.size||1,c=o.coloring,u=a(e,{isColorbar:!0});if(\"heatmap\"===c){var h=n.extractOpts(e);r._fillgradient=h.reversescale?n.flipScale(h.colorscale):h.colorscale,r._zrange=[h.min,h.max]}else\"fill\"===c&&(r._fillcolor=u);r._line={color:\"lines\"===c?u:s.color,width:!1!==o.showlines?s.width:0,dash:s.dash},r._levels={start:o.start,end:i(o),size:l}}}},{\"../../components/colorscale\":604,\"./end_plus\":954,\"./make_color_map\":959}],947:[function(t,e,r){\"use strict\";e.exports={BOTTOMSTART:[1,9,13,104,713],TOPSTART:[4,6,7,104,713],LEFTSTART:[8,12,14,208,1114],RIGHTSTART:[2,3,11,208,1114],NEWDELTA:[null,[-1,0],[0,-1],[-1,0],[1,0],null,[0,-1],[-1,0],[0,1],[0,1],null,[0,1],[1,0],[1,0],[0,-1]],CHOOSESADDLE:{104:[4,1],208:[2,8],713:[7,13],1114:[11,14]},SADDLEREMAINDER:{1:4,2:8,4:1,7:13,8:2,11:14,13:7,14:11},LABELDISTANCE:2,LABELINCREASE:10,LABELMIN:3,LABELMAX:10,LABELOPTIMIZER:{EDGECOST:1,ANGLECOST:1,NEIGHBORCOST:5,SAMELEVELFACTOR:10,SAMELEVELDISTANCE:5,MAXCOST:100,INITIALSEARCHPOINTS:10,ITERATIONS:5}}},{}],948:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"./label_defaults\"),i=t(\"../../components/color\"),o=i.addOpacity,s=i.opacity,l=t(\"../../constants/filter_ops\"),c=l.CONSTRAINT_REDUCTION,u=l.COMPARISON_OPS2;e.exports=function(t,e,r,i,l,h){var f,p,d,g=e.contours,v=r(\"contours.operation\");(g._operation=c[v],function(t,e){var r;-1===u.indexOf(e.operation)?(t(\"contours.value\",[0,1]),Array.isArray(e.value)?e.value.length>2?e.value=e.value.slice(2):0===e.length?e.value=[0,1]:e.length<2?(r=parseFloat(e.value[0]),e.value=[r,r+1]):e.value=[parseFloat(e.value[0]),parseFloat(e.value[1])]:n(e.value)&&(r=parseFloat(e.value),e.value=[r,r+1])):(t(\"contours.value\",0),n(e.value)||(Array.isArray(e.value)?e.value=parseFloat(e.value[0]):e.value=0))}(r,g),\"=\"===v?f=g.showlines=!0:(f=r(\"contours.showlines\"),d=r(\"fillcolor\",o((t.line||{}).color||l,.5))),f)&&(p=r(\"line.color\",d&&s(d)?o(e.fillcolor,1):l),r(\"line.width\",2),r(\"line.dash\"));r(\"line.smoothing\"),a(r,i,p,h)}},{\"../../components/color\":592,\"../../constants/filter_ops\":689,\"./label_defaults\":958,\"fast-isnumeric\":228}],949:[function(t,e,r){\"use strict\";var n=t(\"../../constants/filter_ops\"),a=t(\"fast-isnumeric\");function i(t,e){var r,i=Array.isArray(e);function o(t){return a(t)?+t:null}return-1!==n.COMPARISON_OPS2.indexOf(t)?r=o(i?e[0]:e):-1!==n.INTERVAL_OPS.indexOf(t)?r=i?[o(e[0]),o(e[1])]:[o(e),o(e)]:-1!==n.SET_OPS.indexOf(t)&&(r=i?e.map(o):[o(e)]),r}function o(t){return function(e){e=i(t,e);var r=Math.min(e[0],e[1]),n=Math.max(e[0],e[1]);return{start:r,end:n,size:n-r}}}function s(t){return function(e){return{start:e=i(t,e),end:1/0,size:1/0}}}e.exports={\"[]\":o(\"[]\"),\"][\":o(\"][\"),\">\":s(\">\"),\"<\":s(\"<\"),\"=\":s(\"=\")}},{\"../../constants/filter_ops\":689,\"fast-isnumeric\":228}],950:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n){var a=n(\"contours.start\"),i=n(\"contours.end\"),o=!1===a||!1===i,s=r(\"contours.size\");!(o?e.autocontour=!0:r(\"autocontour\",!1))&&s||r(\"ncontours\")}},{}],951:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");function a(t){return n.extendFlat({},t,{edgepaths:n.extendDeep([],t.edgepaths),paths:n.extendDeep([],t.paths),starts:n.extendDeep([],t.starts)})}e.exports=function(t,e){var r,i,o,s=function(t){return t.reverse()},l=function(t){return t};switch(e){case\"=\":case\"<\":return t;case\">\":for(1!==t.length&&n.warn(\"Contour data invalid for the specified inequality operation.\"),i=t[0],r=0;r<i.edgepaths.length;r++)i.edgepaths[r]=s(i.edgepaths[r]);for(r=0;r<i.paths.length;r++)i.paths[r]=s(i.paths[r]);for(r=0;r<i.starts.length;r++)i.starts[r]=s(i.starts[r]);return t;case\"][\":var c=s;s=l,l=c;case\"[]\":for(2!==t.length&&n.warn(\"Contour data invalid for the specified inequality range operation.\"),i=a(t[0]),o=a(t[1]),r=0;r<i.edgepaths.length;r++)i.edgepaths[r]=s(i.edgepaths[r]);for(r=0;r<i.paths.length;r++)i.paths[r]=s(i.paths[r]);for(r=0;r<i.starts.length;r++)i.starts[r]=s(i.starts[r]);for(;o.edgepaths.length;)i.edgepaths.push(l(o.edgepaths.shift()));for(;o.paths.length;)i.paths.push(l(o.paths.shift()));for(;o.starts.length;)i.starts.push(l(o.starts.shift()));return[i]}}},{\"../../lib\":717}],952:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../heatmap/xyz_defaults\"),i=t(\"./constraint_defaults\"),o=t(\"./contours_defaults\"),s=t(\"./style_defaults\"),l=t(\"./attributes\");e.exports=function(t,e,r,c){function u(r,a){return n.coerce(t,e,l,r,a)}if(a(t,e,u,c)){u(\"text\"),u(\"hovertext\"),u(\"hovertemplate\"),u(\"hoverongaps\");var h=\"constraint\"===u(\"contours.type\");u(\"connectgaps\",n.isArray1D(e.z)),h?i(t,e,u,c,r):(o(t,e,u,function(r){return n.coerce2(t,e,l,r)}),s(t,e,u,c))}else e.visible=!1}},{\"../../lib\":717,\"../heatmap/xyz_defaults\":1014,\"./attributes\":943,\"./constraint_defaults\":948,\"./contours_defaults\":950,\"./style_defaults\":964}],953:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./constraint_mapping\"),i=t(\"./end_plus\");e.exports=function(t,e,r){for(var o=\"constraint\"===t.type?a[t._operation](t.value):t,s=o.size,l=[],c=i(o),u=r.trace._carpetTrace,h=u?{xaxis:u.aaxis,yaxis:u.baxis,x:r.a,y:r.b}:{xaxis:e.xaxis,yaxis:e.yaxis,x:r.x,y:r.y},f=o.start;f<c;f+=s)if(l.push(n.extendFlat({level:f,crossings:{},starts:[],edgepaths:[],paths:[],z:r.z,smoothing:r.trace.line.smoothing},h)),l.length>1e3){n.warn(\"Too many contours, clipping at 1000\",t);break}return l}},{\"../../lib\":717,\"./constraint_mapping\":949,\"./end_plus\":954}],954:[function(t,e,r){\"use strict\";e.exports=function(t){return t.end+t.size/1e6}},{}],955:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./constants\");function i(t,e,r,n){return Math.abs(t[0]-e[0])<r&&Math.abs(t[1]-e[1])<n}function o(t,e,r,o,l){var c,u=e.join(\",\"),h=t.crossings[u],f=function(t,e,r){var n=0,i=0;t>20&&e?208===t||1114===t?n=0===r[0]?1:-1:i=0===r[1]?1:-1:-1!==a.BOTTOMSTART.indexOf(t)?i=1:-1!==a.LEFTSTART.indexOf(t)?n=1:-1!==a.TOPSTART.indexOf(t)?i=-1:n=-1;return[n,i]}(h,r,e),p=[s(t,e,[-f[0],-f[1]])],d=t.z.length,g=t.z[0].length,v=e.slice(),m=f.slice();for(c=0;c<1e4;c++){if(h>20?(h=a.CHOOSESADDLE[h][(f[0]||f[1])<0?0:1],t.crossings[u]=a.SADDLEREMAINDER[h]):delete t.crossings[u],!(f=a.NEWDELTA[h])){n.log(\"Found bad marching index:\",h,e,t.level);break}p.push(s(t,e,f)),e[0]+=f[0],e[1]+=f[1],u=e.join(\",\"),i(p[p.length-1],p[p.length-2],o,l)&&p.pop();var y=f[0]&&(e[0]<0||e[0]>g-2)||f[1]&&(e[1]<0||e[1]>d-2);if(e[0]===v[0]&&e[1]===v[1]&&f[0]===m[0]&&f[1]===m[1]||r&&y)break;h=t.crossings[u]}1e4===c&&n.log(\"Infinite loop in contour?\");var x,b,_,w,k,T,M,A,S,E,L,C,P,O,z,I=i(p[0],p[p.length-1],o,l),D=0,R=.2*t.smoothing,F=[],B=0;for(c=1;c<p.length;c++)C=p[c],P=p[c-1],O=void 0,z=void 0,O=C[2]-P[2],z=C[3]-P[3],D+=M=Math.sqrt(O*O+z*z),F.push(M);var N=D/F.length*R;function j(t){return p[t%p.length]}for(c=p.length-2;c>=B;c--)if((x=F[c])<N){for(_=0,b=c-1;b>=B&&x+F[b]<N;b--)x+=F[b];if(I&&c===p.length-2)for(_=0;_<b&&x+F[_]<N;_++)x+=F[_];k=c-b+_+1,T=Math.floor((c+b+_+2)/2),w=I||c!==p.length-2?I||-1!==b?k%2?j(T):[(j(T)[0]+j(T+1)[0])/2,(j(T)[1]+j(T+1)[1])/2]:p[0]:p[p.length-1],p.splice(b+1,c-b+1,w),c=b+1,_&&(B=_),I&&(c===p.length-2?p[_]=p[p.length-1]:0===c&&(p[p.length-1]=p[0]))}for(p.splice(0,B),c=0;c<p.length;c++)p[c].length=2;if(!(p.length<2))if(I)p.pop(),t.paths.push(p);else{r||n.log(\"Unclosed interior contour?\",t.level,v.join(\",\"),p.join(\"L\"));var V=!1;for(A=0;A<t.edgepaths.length;A++)if(E=t.edgepaths[A],!V&&i(E[0],p[p.length-1],o,l)){p.pop(),V=!0;var U=!1;for(S=0;S<t.edgepaths.length;S++)if(i((L=t.edgepaths[S])[L.length-1],p[0],o,l)){U=!0,p.shift(),t.edgepaths.splice(A,1),S===A?t.paths.push(p.concat(L)):(S>A&&S--,t.edgepaths[S]=L.concat(p,E));break}U||(t.edgepaths[A]=p.concat(E))}for(A=0;A<t.edgepaths.length&&!V;A++)i((E=t.edgepaths[A])[E.length-1],p[0],o,l)&&(p.shift(),t.edgepaths[A]=E.concat(p),V=!0);V||t.edgepaths.push(p)}}function s(t,e,r){var n=e[0]+Math.max(r[0],0),a=e[1]+Math.max(r[1],0),i=t.z[a][n],o=t.xaxis,s=t.yaxis;if(r[1]){var l=(t.level-i)/(t.z[a][n+1]-i);return[o.c2p((1-l)*t.x[n]+l*t.x[n+1],!0),s.c2p(t.y[a],!0),n+l,a]}var c=(t.level-i)/(t.z[a+1][n]-i);return[o.c2p(t.x[n],!0),s.c2p((1-c)*t.y[a]+c*t.y[a+1],!0),n,a+c]}e.exports=function(t,e,r){var a,i,s,l;for(e=e||.01,r=r||.01,i=0;i<t.length;i++){for(s=t[i],l=0;l<s.starts.length;l++)o(s,s.starts[l],\"edge\",e,r);for(a=0;Object.keys(s.crossings).length&&a<1e4;)a++,o(s,Object.keys(s.crossings)[0].split(\",\").map(Number),void 0,e,r);1e4===a&&n.log(\"Infinite loop in contour?\")}}},{\"../../lib\":717,\"./constants\":947}],956:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),a=t(\"../heatmap/hover\");e.exports=function(t,e,r,i,o){var s=a(t,e,r,i,o,!0);return s&&s.forEach(function(t){var e=t.trace;\"constraint\"===e.contours.type&&(e.fillcolor&&n.opacity(e.fillcolor)?t.color=n.addOpacity(e.fillcolor,1):e.contours.showlines&&n.opacity(e.line.color)&&(t.color=n.addOpacity(e.line.color,1)))}),s}},{\"../../components/color\":592,\"../heatmap/hover\":1007}],957:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"./plot\").plot,style:t(\"./style\"),colorbar:t(\"./colorbar\"),hoverPoints:t(\"./hover\"),moduleType:\"trace\",name:\"contour\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"cartesian\",\"svg\",\"2dMap\",\"contour\",\"showLegend\"],meta:{}}},{\"../../plots/cartesian\":776,\"./attributes\":943,\"./calc\":944,\"./colorbar\":946,\"./defaults\":952,\"./hover\":956,\"./plot\":961,\"./style\":963}],958:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e,r,a){if(a||(a={}),t(\"contours.showlabels\")){var i=e.font;n.coerceFont(t,\"contours.labelfont\",{family:i.family,size:i.size,color:r}),t(\"contours.labelformat\")}!1!==a.hasHover&&t(\"zhoverformat\")}},{\"../../lib\":717}],959:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../components/colorscale\"),i=t(\"./end_plus\");e.exports=function(t){var e=t.contours,r=e.start,o=i(e),s=e.size||1,l=Math.floor((o-r)/s)+1,c=\"lines\"===e.coloring?0:1,u=a.extractOpts(t);isFinite(s)||(s=1,l=1);var h,f,p=u.reversescale?a.flipScale(u.colorscale):u.colorscale,d=p.length,g=new Array(d),v=new Array(d);if(\"heatmap\"===e.coloring){var m=u.min,y=u.max;for(f=0;f<d;f++)h=p[f],g[f]=h[0]*(y-m)+m,v[f]=h[1];var x=n.extent([m,y,e.start,e.start+s*(l-1)]),b=x[m<y?0:1],_=x[m<y?1:0];b!==m&&(g.splice(0,0,b),v.splice(0,0,v[0])),_!==y&&(g.push(_),v.push(v[v.length-1]))}else for(f=0;f<d;f++)h=p[f],g[f]=(h[0]*(l+c-1)-c/2)*s+r,v[f]=h[1];return a.makeColorScaleFunc({domain:g,range:v},{noNumericCheck:!0})}},{\"../../components/colorscale\":604,\"./end_plus\":954,d3:165}],960:[function(t,e,r){\"use strict\";var n=t(\"./constants\");function a(t,e){var r=(e[0][0]>t?0:1)+(e[0][1]>t?0:2)+(e[1][1]>t?0:4)+(e[1][0]>t?0:8);return 5===r||10===r?t>(e[0][0]+e[0][1]+e[1][0]+e[1][1])/4?5===r?713:1114:5===r?104:208:15===r?0:r}e.exports=function(t){var e,r,i,o,s,l,c,u,h,f=t[0].z,p=f.length,d=f[0].length,g=2===p||2===d;for(r=0;r<p-1;r++)for(o=[],0===r&&(o=o.concat(n.BOTTOMSTART)),r===p-2&&(o=o.concat(n.TOPSTART)),e=0;e<d-1;e++)for(i=o.slice(),0===e&&(i=i.concat(n.LEFTSTART)),e===d-2&&(i=i.concat(n.RIGHTSTART)),s=e+\",\"+r,l=[[f[r][e],f[r][e+1]],[f[r+1][e],f[r+1][e+1]]],h=0;h<t.length;h++)(c=a((u=t[h]).level,l))&&(u.crossings[s]=c,-1!==i.indexOf(c)&&(u.starts.push([e,r]),g&&-1!==i.indexOf(c,i.indexOf(c)+1)&&u.starts.push([e,r])))}},{\"./constants\":947}],961:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\"),i=t(\"../../components/drawing\"),o=t(\"../../components/colorscale\"),s=t(\"../../lib/svg_text_utils\"),l=t(\"../../plots/cartesian/axes\"),c=t(\"../../plots/cartesian/set_convert\"),u=t(\"../heatmap/plot\"),h=t(\"./make_crossings\"),f=t(\"./find_all_paths\"),p=t(\"./empty_pathinfo\"),d=t(\"./convert_to_constraints\"),g=t(\"./close_boundaries\"),v=t(\"./constants\"),m=v.LABELOPTIMIZER;function y(t,e){var r,n,o,s,l,c,u,h=\"\",f=0,p=t.edgepaths.map(function(t,e){return e}),d=!0;function g(t){return Math.abs(t[1]-e[2][1])<.01}function v(t){return Math.abs(t[0]-e[0][0])<.01}function m(t){return Math.abs(t[0]-e[2][0])<.01}for(;p.length;){for(c=i.smoothopen(t.edgepaths[f],t.smoothing),h+=d?c:c.replace(/^M/,\"L\"),p.splice(p.indexOf(f),1),r=t.edgepaths[f][t.edgepaths[f].length-1],s=-1,o=0;o<4;o++){if(!r){a.log(\"Missing end?\",f,t);break}for(u=r,Math.abs(u[1]-e[0][1])<.01&&!m(r)?n=e[1]:v(r)?n=e[0]:g(r)?n=e[3]:m(r)&&(n=e[2]),l=0;l<t.edgepaths.length;l++){var y=t.edgepaths[l][0];Math.abs(r[0]-n[0])<.01?Math.abs(r[0]-y[0])<.01&&(y[1]-r[1])*(n[1]-y[1])>=0&&(n=y,s=l):Math.abs(r[1]-n[1])<.01?Math.abs(r[1]-y[1])<.01&&(y[0]-r[0])*(n[0]-y[0])>=0&&(n=y,s=l):a.log(\"endpt to newendpt is not vert. or horz.\",r,n,y)}if(r=n,s>=0)break;h+=\"L\"+n}if(s===t.edgepaths.length){a.log(\"unclosed perimeter path\");break}f=s,(d=-1===p.indexOf(f))&&(f=p[0],h+=\"Z\")}for(f=0;f<t.paths.length;f++)h+=i.smoothclosed(t.paths[f],t.smoothing);return h}function x(t,e,r,n){var i=e.width/2,o=e.height/2,s=t.x,l=t.y,c=t.theta,u=Math.cos(c)*i,h=Math.sin(c)*i,f=(s>n.center?n.right-s:s-n.left)/(u+Math.abs(Math.sin(c)*o)),p=(l>n.middle?n.bottom-l:l-n.top)/(Math.abs(h)+Math.cos(c)*o);if(f<1||p<1)return 1/0;var d=m.EDGECOST*(1/(f-1)+1/(p-1));d+=m.ANGLECOST*c*c;for(var g=s-u,v=l-h,y=s+u,x=l+h,b=0;b<r.length;b++){var _=r[b],w=Math.cos(_.theta)*_.width/2,k=Math.sin(_.theta)*_.width/2,T=2*a.segmentDistance(g,v,y,x,_.x-w,_.y-k,_.x+w,_.y+k)/(e.height+_.height),M=_.level===e.level,A=M?m.SAMELEVELDISTANCE:1;if(T<=A)return 1/0;d+=m.NEIGHBORCOST*(M?m.SAMELEVELFACTOR:1)/(T-A)}return d}function b(t){var e,r,n=t.trace._emptypoints,a=[],i=t.z.length,o=t.z[0].length,s=[];for(e=0;e<o;e++)s.push(1);for(e=0;e<i;e++)a.push(s.slice());for(e=0;e<n.length;e++)a[(r=n[e])[0]][r[1]]=0;return t.zmask=a,a}r.plot=function(t,e,o,s){var l=e.xaxis,c=e.yaxis;a.makeTraceGroups(s,o,\"contour\").each(function(o){var s=n.select(this),m=o[0],x=m.trace,_=m.x,w=m.y,k=x.contours,T=p(k,e,m),M=a.ensureSingle(s,\"g\",\"heatmapcoloring\"),A=[];\"heatmap\"===k.coloring&&(A=[o]),u(t,e,A,M),h(T),f(T);var S=l.c2p(_[0],!0),E=l.c2p(_[_.length-1],!0),L=c.c2p(w[0],!0),C=c.c2p(w[w.length-1],!0),P=[[S,C],[E,C],[E,L],[S,L]],O=T;\"constraint\"===k.type&&(O=d(T,k._operation)),function(t,e,r){var n=a.ensureSingle(t,\"g\",\"contourbg\").selectAll(\"path\").data(\"fill\"===r.coloring?[0]:[]);n.enter().append(\"path\"),n.exit().remove(),n.attr(\"d\",\"M\"+e.join(\"L\")+\"Z\").style(\"stroke\",\"none\")}(s,P,k),function(t,e,r,i){var o=\"fill\"===i.coloring||\"constraint\"===i.type&&\"=\"!==i._operation,s=\"M\"+r.join(\"L\")+\"Z\";o&&g(e,i);var l=a.ensureSingle(t,\"g\",\"contourfill\").selectAll(\"path\").data(o?e:[]);l.enter().append(\"path\"),l.exit().remove(),l.each(function(t){var e=(t.prefixBoundary?s:\"\")+y(t,r);e?n.select(this).attr(\"d\",e).style(\"stroke\",\"none\"):n.select(this).remove()})}(s,O,P,k),function(t,e,o,s,l){var c=a.ensureSingle(t,\"g\",\"contourlines\"),u=!1!==l.showlines,h=l.showlabels,f=u&&h,p=r.createLines(c,u||h,e),d=r.createLineClip(c,f,o,s.trace.uid),g=t.selectAll(\"g.contourlabels\").data(h?[0]:[]);if(g.exit().remove(),g.enter().append(\"g\").classed(\"contourlabels\",!0),h){var m=[],y=[];a.clearLocationCache();var x=r.labelFormatter(o,s),b=i.tester.append(\"text\").attr(\"data-notex\",1).call(i.font,l.labelfont),_=e[0].xaxis,w=e[0].yaxis,k=_._length,T=w._length,M=_.range,A=w.range,S=a.aggNums(Math.min,null,s.x),E=a.aggNums(Math.max,null,s.x),L=a.aggNums(Math.min,null,s.y),C=a.aggNums(Math.max,null,s.y),P=Math.max(_.c2p(S,!0),0),O=Math.min(_.c2p(E,!0),k),z=Math.max(w.c2p(C,!0),0),I=Math.min(w.c2p(L,!0),T),D={};M[0]<M[1]?(D.left=P,D.right=O):(D.left=O,D.right=P),A[0]<A[1]?(D.top=z,D.bottom=I):(D.top=I,D.bottom=z),D.middle=(D.top+D.bottom)/2,D.center=(D.left+D.right)/2,m.push([[D.left,D.top],[D.right,D.top],[D.right,D.bottom],[D.left,D.bottom]]);var R=Math.sqrt(k*k+T*T),F=v.LABELDISTANCE*R/Math.max(1,e.length/v.LABELINCREASE);p.each(function(t){var e=r.calcTextOpts(t.level,x,b,o);n.select(this).selectAll(\"path\").each(function(){var t=a.getVisibleSegment(this,D,e.height/2);if(t&&!(t.len<(e.width+e.height)*v.LABELMIN))for(var n=Math.min(Math.ceil(t.len/F),v.LABELMAX),i=0;i<n;i++){var o=r.findBestTextLocation(this,t,e,y,D);if(!o)break;r.addLabelData(o,e,y,m)}})}),b.remove(),r.drawLabels(g,y,o,d,f?m:null)}h&&!u&&p.remove()}(s,T,t,m,k),function(t,e,r,n,o){var s=n.trace,l=r._fullLayout._clips,c=\"clip\"+s.uid,u=l.selectAll(\"#\"+c).data(s.connectgaps?[]:[0]);if(u.enter().append(\"clipPath\").classed(\"contourclip\",!0).attr(\"id\",c),u.exit().remove(),!1===s.connectgaps){var p={level:.9,crossings:{},starts:[],edgepaths:[],paths:[],xaxis:e.xaxis,yaxis:e.yaxis,x:n.x,y:n.y,z:b(n),smoothing:0};h([p]),f([p]),g([p],{type:\"levels\"});var d=a.ensureSingle(u,\"path\",\"\");d.attr(\"d\",(p.prefixBoundary?\"M\"+o.join(\"L\")+\"Z\":\"\")+y(p,o))}else c=null;i.setClipUrl(t,c,r)}(s,e,t,m,P)})},r.createLines=function(t,e,r){var n=r[0].smoothing,a=t.selectAll(\"g.contourlevel\").data(e?r:[]);if(a.exit().remove(),a.enter().append(\"g\").classed(\"contourlevel\",!0),e){var o=a.selectAll(\"path.openline\").data(function(t){return t.pedgepaths||t.edgepaths});o.exit().remove(),o.enter().append(\"path\").classed(\"openline\",!0),o.attr(\"d\",function(t){return i.smoothopen(t,n)}).style(\"stroke-miterlimit\",1).style(\"vector-effect\",\"non-scaling-stroke\");var s=a.selectAll(\"path.closedline\").data(function(t){return t.ppaths||t.paths});s.exit().remove(),s.enter().append(\"path\").classed(\"closedline\",!0),s.attr(\"d\",function(t){return i.smoothclosed(t,n)}).style(\"stroke-miterlimit\",1).style(\"vector-effect\",\"non-scaling-stroke\")}return a},r.createLineClip=function(t,e,r,n){var a=e?\"clipline\"+n:null,o=r._fullLayout._clips.selectAll(\"#\"+a).data(e?[0]:[]);return o.exit().remove(),o.enter().append(\"clipPath\").classed(\"contourlineclip\",!0).attr(\"id\",a),i.setClipUrl(t,a,r),o},r.labelFormatter=function(t,e){var r=t._fullLayout,n=e.trace,a=n.contours;if(a.labelformat)return r._d3locale.numberFormat(a.labelformat);var i,s=o.extractOpts(n);if(s&&s.colorbar&&s.colorbar._axis)i=s.colorbar._axis;else{if(i={type:\"linear\",_id:\"ycontour\",showexponent:\"all\",exponentformat:\"B\"},\"constraint\"===a.type){var u=a.value;Array.isArray(u)?i.range=[u[0],u[u.length-1]]:i.range=[u,u]}else i.range=[a.start,a.end],i.nticks=(a.end-a.start)/a.size;i.range[0]===i.range[1]&&(i.range[1]+=i.range[0]||1),i.nticks||(i.nticks=1e3),c(i,r),l.prepTicks(i),i._tmin=null,i._tmax=null}return function(t){return l.tickText(i,t).text}},r.calcTextOpts=function(t,e,r,n){var a=e(t);r.text(a).call(s.convertToTspans,n);var o=i.bBox(r.node(),!0);return{text:a,width:o.width,height:o.height,level:t,dy:(o.top+o.bottom)/2}},r.findBestTextLocation=function(t,e,r,n,i){var o,s,l,c,u,h=r.width;e.isClosed?(s=e.len/m.INITIALSEARCHPOINTS,o=e.min+s/2,l=e.max):(s=(e.len-h)/(m.INITIALSEARCHPOINTS+1),o=e.min+s+h/2,l=e.max-(s+h)/2);for(var f=1/0,p=0;p<m.ITERATIONS;p++){for(var d=o;d<l;d+=s){var g=a.getTextLocation(t,e.total,d,h),v=x(g,r,n,i);v<f&&(f=v,u=g,c=d)}if(f>2*m.MAXCOST)break;p&&(s/=2),l=(o=c-s/2)+1.5*s}if(f<=m.MAXCOST)return u},r.addLabelData=function(t,e,r,n){var a=e.width/2,i=e.height/2,o=t.x,s=t.y,l=t.theta,c=Math.sin(l),u=Math.cos(l),h=a*u,f=i*c,p=a*c,d=-i*u,g=[[o-h-f,s-p-d],[o+h-f,s+p-d],[o+h+f,s+p+d],[o-h+f,s-p+d]];r.push({text:e.text,x:o,y:s,dy:e.dy,theta:l,level:e.level,width:e.width,height:e.height}),n.push(g)},r.drawLabels=function(t,e,r,i,o){var l=t.selectAll(\"text\").data(e,function(t){return t.text+\",\"+t.x+\",\"+t.y+\",\"+t.theta});if(l.exit().remove(),l.enter().append(\"text\").attr({\"data-notex\":1,\"text-anchor\":\"middle\"}).each(function(t){var e=t.x+Math.sin(t.theta)*t.dy,a=t.y-Math.cos(t.theta)*t.dy;n.select(this).text(t.text).attr({x:e,y:a,transform:\"rotate(\"+180*t.theta/Math.PI+\" \"+e+\" \"+a+\")\"}).call(s.convertToTspans,r)}),o){for(var c=\"\",u=0;u<o.length;u++)c+=\"M\"+o[u].join(\"L\")+\"Z\";a.ensureSingle(i,\"path\",\"\").attr(\"d\",c)}}},{\"../../components/colorscale\":604,\"../../components/drawing\":613,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"../../plots/cartesian/axes\":765,\"../../plots/cartesian/set_convert\":783,\"../heatmap/plot\":1011,\"./close_boundaries\":945,\"./constants\":947,\"./convert_to_constraints\":951,\"./empty_pathinfo\":953,\"./find_all_paths\":955,\"./make_crossings\":960,d3:165}],962:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\"),a=t(\"../../lib\");function i(t,e,r){var a={type:\"linear\",range:[t,e]};return n.autoTicks(a,(e-t)/(r||15)),a}e.exports=function(t,e){var r=t.contours;if(t.autocontour){var o=t.zmin,s=t.zmax;(t.zauto||void 0===o)&&(o=a.aggNums(Math.min,null,e)),(t.zauto||void 0===s)&&(s=a.aggNums(Math.max,null,e));var l=i(o,s,t.ncontours);r.size=l.dtick,r.start=n.tickFirst(l),l.range.reverse(),r.end=n.tickFirst(l),r.start===o&&(r.start+=r.size),r.end===s&&(r.end-=r.size),r.start>r.end&&(r.start=r.end=(r.start+r.end)/2),t._input.contours||(t._input.contours={}),a.extendFlat(t._input.contours,{start:r.start,end:r.end,size:r.size}),t._input.autocontour=!0}else if(\"constraint\"!==r.type){var c,u=r.start,h=r.end,f=t._input.contours;if(u>h&&(r.start=f.start=h,h=r.end=f.end=u,u=r.start),!(r.size>0))c=u===h?1:i(u,h,t.ncontours).dtick,f.size=r.size=c}}},{\"../../lib\":717,\"../../plots/cartesian/axes\":765}],963:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../components/drawing\"),i=t(\"../heatmap/style\"),o=t(\"./make_color_map\");e.exports=function(t){var e=n.select(t).selectAll(\"g.contour\");e.style(\"opacity\",function(t){return t[0].trace.opacity}),e.each(function(t){var e=n.select(this),r=t[0].trace,i=r.contours,s=r.line,l=i.size||1,c=i.start,u=\"constraint\"===i.type,h=!u&&\"lines\"===i.coloring,f=!u&&\"fill\"===i.coloring,p=h||f?o(r):null;e.selectAll(\"g.contourlevel\").each(function(t){n.select(this).selectAll(\"path\").call(a.lineGroupStyle,s.width,h?p(t.level):s.color,s.dash)});var d=i.labelfont;if(e.selectAll(\"g.contourlabels text\").each(function(t){a.font(n.select(this),{family:d.family,size:d.size,color:d.color||(h?p(t.level):s.color)})}),u)e.selectAll(\"g.contourfill path\").style(\"fill\",r.fillcolor);else if(f){var g;e.selectAll(\"g.contourfill path\").style(\"fill\",function(t){return void 0===g&&(g=t.level),p(t.level+.5*l)}),void 0===g&&(g=c),e.selectAll(\"g.contourbg path\").style(\"fill\",p(g-.5*l))}}),i(t)}},{\"../../components/drawing\":613,\"../heatmap/style\":1012,\"./make_color_map\":959,d3:165}],964:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/defaults\"),a=t(\"./label_defaults\");e.exports=function(t,e,r,i,o){var s,l=r(\"contours.coloring\"),c=\"\";\"fill\"===l&&(s=r(\"contours.showlines\")),!1!==s&&(\"lines\"!==l&&(c=r(\"line.color\",\"#000\")),r(\"line.width\",.5),r(\"line.dash\")),\"none\"!==l&&(!0!==t.showlegend&&(e.showlegend=!1),e._dfltShowLegend=!1,n(t,e,i,r,{prefix:\"\",cLetter:\"z\"})),r(\"line.smoothing\"),a(r,i,c,o)}},{\"../../components/colorscale/defaults\":602,\"./label_defaults\":958}],965:[function(t,e,r){\"use strict\";var n=t(\"../heatmap/attributes\"),a=t(\"../contour/attributes\"),i=t(\"../../components/colorscale/attributes\"),o=t(\"../../lib/extend\").extendFlat,s=a.contours;e.exports=o({carpet:{valType:\"string\",editType:\"calc\"},z:n.z,a:n.x,a0:n.x0,da:n.dx,b:n.y,b0:n.y0,db:n.dy,text:n.text,hovertext:n.hovertext,transpose:n.transpose,atype:n.xtype,btype:n.ytype,fillcolor:a.fillcolor,autocontour:a.autocontour,ncontours:a.ncontours,contours:{type:s.type,start:s.start,end:s.end,size:s.size,coloring:{valType:\"enumerated\",values:[\"fill\",\"lines\",\"none\"],dflt:\"fill\",editType:\"calc\"},showlines:s.showlines,showlabels:s.showlabels,labelfont:s.labelfont,labelformat:s.labelformat,operation:s.operation,value:s.value,editType:\"calc\",impliedEdits:{autocontour:!1}},line:{color:a.line.color,width:a.line.width,dash:a.line.dash,smoothing:a.line.smoothing,editType:\"plot\"},transforms:void 0},i(\"\",{cLetter:\"z\",autoColorDflt:!1}))},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../contour/attributes\":943,\"../heatmap/attributes\":1e3}],966:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/calc\"),a=t(\"../../lib\"),i=t(\"../heatmap/convert_column_xyz\"),o=t(\"../heatmap/clean_2d_array\"),s=t(\"../heatmap/interp2d\"),l=t(\"../heatmap/find_empties\"),c=t(\"../heatmap/make_bound_array\"),u=t(\"./defaults\"),h=t(\"../carpet/lookup_carpetid\"),f=t(\"../contour/set_contours\");e.exports=function(t,e){var r=e._carpetTrace=h(t,e);if(r&&r.visible&&\"legendonly\"!==r.visible){if(!e.a||!e.b){var p=t.data[r.index],d=t.data[e.index];d.a||(d.a=p.a),d.b||(d.b=p.b),u(d,e,e._defaultColor,t._fullLayout)}var g=function(t,e){var r,u,h,f,p,d,g,v=e._carpetTrace,m=v.aaxis,y=v.baxis;m._minDtick=0,y._minDtick=0,a.isArray1D(e.z)&&i(e,m,y,\"a\",\"b\",[\"z\"]);r=e._a=e._a||e.a,f=e._b=e._b||e.b,r=r?m.makeCalcdata(e,\"_a\"):[],f=f?y.makeCalcdata(e,\"_b\"):[],u=e.a0||0,h=e.da||1,p=e.b0||0,d=e.db||1,g=e._z=o(e._z||e.z,e.transpose),e._emptypoints=l(g),s(g,e._emptypoints);var x=a.maxRowLength(g),b=\"scaled\"===e.xtype?\"\":r,_=c(e,b,u,h,x,m),w=\"scaled\"===e.ytype?\"\":f,k=c(e,w,p,d,g.length,y),T={a:_,b:k,z:g};\"levels\"===e.contours.type&&\"none\"!==e.contours.coloring&&n(t,e,{vals:g,containerStr:\"\",cLetter:\"z\"});return[T]}(t,e);return f(e,e._z),g}}},{\"../../components/colorscale/calc\":600,\"../../lib\":717,\"../carpet/lookup_carpetid\":916,\"../contour/set_contours\":962,\"../heatmap/clean_2d_array\":1002,\"../heatmap/convert_column_xyz\":1004,\"../heatmap/find_empties\":1006,\"../heatmap/interp2d\":1009,\"../heatmap/make_bound_array\":1010,\"./defaults\":967}],967:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../heatmap/xyz_defaults\"),i=t(\"./attributes\"),o=t(\"../contour/constraint_defaults\"),s=t(\"../contour/contours_defaults\"),l=t(\"../contour/style_defaults\");e.exports=function(t,e,r,c){function u(r,a){return n.coerce(t,e,i,r,a)}if(u(\"carpet\"),t.a&&t.b){if(!a(t,e,u,c,\"a\",\"b\"))return void(e.visible=!1);u(\"text\"),\"constraint\"===u(\"contours.type\")?o(t,e,u,c,r,{hasHover:!1}):(s(t,e,u,function(r){return n.coerce2(t,e,i,r)}),l(t,e,u,c,{hasHover:!1}))}else e._defaultColor=r,e._length=null}},{\"../../lib\":717,\"../contour/constraint_defaults\":948,\"../contour/contours_defaults\":950,\"../contour/style_defaults\":964,\"../heatmap/xyz_defaults\":1014,\"./attributes\":965}],968:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),colorbar:t(\"../contour/colorbar\"),calc:t(\"./calc\"),plot:t(\"./plot\"),style:t(\"../contour/style\"),moduleType:\"trace\",name:\"contourcarpet\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"cartesian\",\"svg\",\"carpet\",\"contour\",\"symbols\",\"showLegend\",\"hasLines\",\"carpetDependent\",\"noHover\",\"noSortingByValue\"],meta:{}}},{\"../../plots/cartesian\":776,\"../contour/colorbar\":946,\"../contour/style\":963,\"./attributes\":965,\"./calc\":966,\"./defaults\":967,\"./plot\":969}],969:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../carpet/map_1d_array\"),i=t(\"../carpet/makepath\"),o=t(\"../../components/drawing\"),s=t(\"../../lib\"),l=t(\"../contour/make_crossings\"),c=t(\"../contour/find_all_paths\"),u=t(\"../contour/plot\"),h=t(\"../contour/constants\"),f=t(\"../contour/convert_to_constraints\"),p=t(\"../contour/empty_pathinfo\"),d=t(\"../contour/close_boundaries\"),g=t(\"../carpet/lookup_carpetid\"),v=t(\"../carpet/axis_aligned_line\");function m(t,e,r){var n=t.getPointAtLength(e),a=t.getPointAtLength(r),i=a.x-n.x,o=a.y-n.y,s=Math.sqrt(i*i+o*o);return[i/s,o/s]}function y(t){var e=Math.sqrt(t[0]*t[0]+t[1]*t[1]);return[t[0]/e,t[1]/e]}function x(t,e){var r=Math.abs(t[0]*e[0]+t[1]*e[1]);return Math.sqrt(1-r*r)/r}e.exports=function(t,e,r,b){var _=e.xaxis,w=e.yaxis;s.makeTraceGroups(b,r,\"contour\").each(function(r){var b=n.select(this),k=r[0],T=k.trace,M=T._carpetTrace=g(t,T),A=t.calcdata[M.index][0];if(M.visible&&\"legendonly\"!==M.visible){var S=k.a,E=k.b,L=T.contours,C=p(L,e,k),P=\"constraint\"===L.type,O=L._operation,z=P?\"=\"===O?\"lines\":\"fill\":L.coloring,I=[[S[0],E[E.length-1]],[S[S.length-1],E[E.length-1]],[S[S.length-1],E[0]],[S[0],E[0]]];l(C);var D=1e-8*(S[S.length-1]-S[0]),R=1e-8*(E[E.length-1]-E[0]);c(C,D,R);var F,B,N,j,V=C;\"constraint\"===L.type&&(V=f(C,O)),function(t,e){var r,n,a,i,o,s,l,c,u;for(r=0;r<t.length;r++){for(i=t[r],o=i.pedgepaths=[],s=i.ppaths=[],n=0;n<i.edgepaths.length;n++){for(u=i.edgepaths[n],l=[],a=0;a<u.length;a++)l[a]=e(u[a]);o.push(l)}for(n=0;n<i.paths.length;n++){for(u=i.paths[n],c=[],a=0;a<u.length;a++)c[a]=e(u[a]);s.push(c)}}}(C,H);var U=[];for(j=A.clipsegments.length-1;j>=0;j--)F=A.clipsegments[j],B=a([],F.x,_.c2p),N=a([],F.y,w.c2p),B.reverse(),N.reverse(),U.push(i(B,N,F.bicubic));var q=\"M\"+U.join(\"L\")+\"Z\";!function(t,e,r,n,o,l){var c,u,h,f,p=s.ensureSingle(t,\"g\",\"contourbg\").selectAll(\"path\").data(\"fill\"!==l||o?[]:[0]);p.enter().append(\"path\"),p.exit().remove();var d=[];for(f=0;f<e.length;f++)c=e[f],u=a([],c.x,r.c2p),h=a([],c.y,n.c2p),d.push(i(u,h,c.bicubic));p.attr(\"d\",\"M\"+d.join(\"L\")+\"Z\").style(\"stroke\",\"none\")}(b,A.clipsegments,_,w,P,z),function(t,e,r,a,i,l,c,u,h,f,p){var g=\"fill\"===f;g&&d(i,t.contours);var m=s.ensureSingle(e,\"g\",\"contourfill\").selectAll(\"path\").data(g?i:[]);m.enter().append(\"path\"),m.exit().remove(),m.each(function(t){var e=(t.prefixBoundary?p:\"\")+function(t,e,r,n,a,i,l,c){var u,h,f,p,d,g,m,y=\"\",x=e.edgepaths.map(function(t,e){return e}),b=!0,_=1e-4*Math.abs(r[0][0]-r[2][0]),w=1e-4*Math.abs(r[0][1]-r[2][1]);function k(t){return Math.abs(t[1]-r[0][1])<w}function T(t){return Math.abs(t[1]-r[2][1])<w}function M(t){return Math.abs(t[0]-r[0][0])<_}function A(t){return Math.abs(t[0]-r[2][0])<_}function S(t,e){var r,n,o,s,u=\"\";for(k(t)&&!A(t)||T(t)&&!M(t)?(s=a.aaxis,o=v(a,i,[t[0],e[0]],.5*(t[1]+e[1]))):(s=a.baxis,o=v(a,i,.5*(t[0]+e[0]),[t[1],e[1]])),r=1;r<o.length;r++)for(u+=s.smoothing?\"C\":\"L\",n=0;n<o[r].length;n++){var h=o[r][n];u+=[l.c2p(h[0]),c.c2p(h[1])]+\" \"}return u}u=0,h=null;for(;x.length;){var E=e.edgepaths[u][0];for(h&&(y+=S(h,E)),m=o.smoothopen(e.edgepaths[u].map(n),e.smoothing),y+=b?m:m.replace(/^M/,\"L\"),x.splice(x.indexOf(u),1),h=e.edgepaths[u][e.edgepaths[u].length-1],d=-1,p=0;p<4;p++){if(!h){s.log(\"Missing end?\",u,e);break}for(k(h)&&!A(h)?f=r[1]:M(h)?f=r[0]:T(h)?f=r[3]:A(h)&&(f=r[2]),g=0;g<e.edgepaths.length;g++){var L=e.edgepaths[g][0];Math.abs(h[0]-f[0])<_?Math.abs(h[0]-L[0])<_&&(L[1]-h[1])*(f[1]-L[1])>=0&&(f=L,d=g):Math.abs(h[1]-f[1])<w?Math.abs(h[1]-L[1])<w&&(L[0]-h[0])*(f[0]-L[0])>=0&&(f=L,d=g):s.log(\"endpt to newendpt is not vert. or horz.\",h,f,L)}if(d>=0)break;y+=S(h,f),h=f}if(d===e.edgepaths.length){s.log(\"unclosed perimeter path\");break}u=d,(b=-1===x.indexOf(u))&&(u=x[0],y+=S(h,f)+\"Z\",h=null)}for(u=0;u<e.paths.length;u++)y+=o.smoothclosed(e.paths[u].map(n),e.smoothing);return y}(0,t,l,c,u,h,r,a);e?n.select(this).attr(\"d\",e).style(\"stroke\",\"none\"):n.select(this).remove()})}(T,b,_,w,V,I,H,M,A,z,q),function(t,e,r,a,i,l,c){var f=s.ensureSingle(t,\"g\",\"contourlines\"),p=!1!==i.showlines,d=i.showlabels,g=p&&d,v=u.createLines(f,p||d,e),b=u.createLineClip(f,g,r,a.trace.uid),_=t.selectAll(\"g.contourlabels\").data(d?[0]:[]);if(_.exit().remove(),_.enter().append(\"g\").classed(\"contourlabels\",!0),d){var w=l.xaxis,k=l.yaxis,T=w._length,M=k._length,A=[[[0,0],[T,0],[T,M],[0,M]]],S=[];s.clearLocationCache();var E=u.labelFormatter(r,a),L=o.tester.append(\"text\").attr(\"data-notex\",1).call(o.font,i.labelfont),C={left:0,right:T,center:T/2,top:0,bottom:M,middle:M/2},P=Math.sqrt(T*T+M*M),O=h.LABELDISTANCE*P/Math.max(1,e.length/h.LABELINCREASE);v.each(function(t){var e=u.calcTextOpts(t.level,E,L,r);n.select(this).selectAll(\"path\").each(function(r){var n=s.getVisibleSegment(this,C,e.height/2);if(n&&(function(t,e,r,n,a,i){for(var o,s=0;s<r.pedgepaths.length;s++)e===r.pedgepaths[s]&&(o=r.edgepaths[s]);if(!o)return;var l=a.a[0],c=a.a[a.a.length-1],u=a.b[0],h=a.b[a.b.length-1];function f(t,e){var r,n=0;return(Math.abs(t[0]-l)<.1||Math.abs(t[0]-c)<.1)&&(r=y(a.dxydb_rough(t[0],t[1],.1)),n=Math.max(n,i*x(e,r)/2)),(Math.abs(t[1]-u)<.1||Math.abs(t[1]-h)<.1)&&(r=y(a.dxyda_rough(t[0],t[1],.1)),n=Math.max(n,i*x(e,r)/2)),n}var p=m(t,0,1),d=m(t,n.total,n.total-1),g=f(o[0],p),v=n.total-f(o[o.length-1],d);n.min<g&&(n.min=g);n.max>v&&(n.max=v);n.len=n.max-n.min}(this,r,t,n,c,e.height),!(n.len<(e.width+e.height)*h.LABELMIN)))for(var a=Math.min(Math.ceil(n.len/O),h.LABELMAX),i=0;i<a;i++){var o=u.findBestTextLocation(this,n,e,S,C);if(!o)break;u.addLabelData(o,e,S,A)}})}),L.remove(),u.drawLabels(_,S,r,b,g?A:null)}d&&!p&&v.remove()}(b,C,t,k,L,e,M),o.setClipUrl(b,M._clipPathId,t)}function H(t){var e=M.ab2xy(t[0],t[1],!0);return[_.c2p(e[0]),w.c2p(e[1])]}})}},{\"../../components/drawing\":613,\"../../lib\":717,\"../carpet/axis_aligned_line\":900,\"../carpet/lookup_carpetid\":916,\"../carpet/makepath\":917,\"../carpet/map_1d_array\":918,\"../contour/close_boundaries\":945,\"../contour/constants\":947,\"../contour/convert_to_constraints\":951,\"../contour/empty_pathinfo\":953,\"../contour/find_all_paths\":955,\"../contour/make_crossings\":960,\"../contour/plot\":961,d3:165}],970:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/attributes\"),a=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/attributes\"),o=t(\"../scattermapbox/attributes\"),s=t(\"../../lib/extend\").extendFlat;e.exports=s({lon:o.lon,lat:o.lat,z:{valType:\"data_array\",editType:\"calc\"},radius:{valType:\"number\",editType:\"plot\",arrayOk:!0,min:1,dflt:30},below:{valType:\"string\",editType:\"plot\"},text:o.text,hovertext:o.hovertext,hoverinfo:s({},i.hoverinfo,{flags:[\"lon\",\"lat\",\"z\",\"text\",\"name\"]}),hovertemplate:a(),showlegend:s({},i.showlegend,{dflt:!1})},n(\"\",{cLetter:\"z\",editTypeOverride:\"calc\"}))},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"../scattermapbox/attributes\":1184}],971:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib\").isArrayOrTypedArray,i=t(\"../../constants/numerical\").BADNUM,o=t(\"../../components/colorscale/calc\"),s=t(\"../../lib\")._;e.exports=function(t,e){for(var r=e._length,l=new Array(r),c=e.z,u=a(c)&&c.length,h=0;h<r;h++){var f=l[h]={},p=e.lon[h],d=e.lat[h];if(f.lonlat=n(p)&&n(d)?[+p,+d]:[i,i],u){var g=c[h];f.z=n(g)?g:i}}return o(t,e,{vals:u?c:[0,1],containerStr:\"\",cLetter:\"z\"}),r&&(l[0].t={labels:{lat:s(t,\"lat:\")+\" \",lon:s(t,\"lon:\")+\" \"}}),l}},{\"../../components/colorscale/calc\":600,\"../../constants/numerical\":693,\"../../lib\":717,\"fast-isnumeric\":228}],972:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib\"),i=t(\"../../components/color\"),o=t(\"../../components/colorscale\"),s=t(\"../../constants/numerical\").BADNUM,l=t(\"../../lib/geojson_utils\").makeBlank;e.exports=function(t){var e=t[0].trace,r=!0===e.visible&&0!==e._length,c=e._opts={heatmap:{layout:{visibility:\"none\"},paint:{}},geojson:l()};if(!r)return c;var u,h=[],f=e.z,p=e.radius,d=a.isArrayOrTypedArray(f)&&f.length,g=a.isArrayOrTypedArray(p);for(u=0;u<t.length;u++){var v=t[u],m=v.lonlat;if(m[0]!==s){var y={};if(d){var x=v.z;y.z=x!==s?x:0}g&&(y.r=n(p[u])&&p[u]>0?+p[u]:0),h.push({type:\"Feature\",geometry:{type:\"Point\",coordinates:m},properties:y})}}var b=o.extractOpts(e),_=b.reversescale?o.flipScale(b.colorscale):b.colorscale,w=_[0][1],k=[\"interpolate\",[\"linear\"],[\"heatmap-density\"],0,i.opacity(w)<1?w:i.addOpacity(w,0)];for(u=1;u<_.length;u++)k.push(_[u][0],_[u][1]);var T=[\"interpolate\",[\"linear\"],[\"get\",\"z\"],b.min,0,b.max,1];return a.extendFlat(c.heatmap.paint,{\"heatmap-weight\":d?T:1/(b.max-b.min),\"heatmap-color\":k,\"heatmap-radius\":g?{type:\"identity\",property:\"r\"}:e.radius,\"heatmap-opacity\":e.opacity}),c.geojson={type:\"FeatureCollection\",features:h},c.heatmap.layout.visibility=\"visible\",c}},{\"../../components/color\":592,\"../../components/colorscale\":604,\"../../constants/numerical\":693,\"../../lib\":717,\"../../lib/geojson_utils\":712,\"fast-isnumeric\":228}],973:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/colorscale/defaults\"),i=t(\"./attributes\");e.exports=function(t,e,r,o){function s(r,a){return n.coerce(t,e,i,r,a)}var l=s(\"lon\")||[],c=s(\"lat\")||[],u=Math.min(l.length,c.length);u?(e._length=u,s(\"z\"),s(\"radius\"),s(\"below\"),s(\"text\"),s(\"hovertext\"),s(\"hovertemplate\"),a(t,e,o,s,{prefix:\"\",cLetter:\"z\"})):e.visible=!1}},{\"../../components/colorscale/defaults\":602,\"../../lib\":717,\"./attributes\":970}],974:[function(t,e,r){\"use strict\";e.exports=function(t,e){return t.lon=e.lon,t.lat=e.lat,t.z=e.z,t}},{}],975:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/cartesian/axes\"),i=t(\"../scattermapbox/hover\");e.exports=function(t,e,r){var o=i(t,e,r);if(o){var s=o[0],l=s.cd,c=l[0].trace,u=l[s.index];if(delete s.color,\"z\"in u){var h=s.subplot.mockAxis;s.z=u.z,s.zLabel=a.tickText(h,h.c2l(u.z),\"hover\").text}return s.extraText=function(t,e,r){if(t.hovertemplate)return;var a=(e.hi||t.hoverinfo).split(\"+\"),i=-1!==a.indexOf(\"all\"),o=-1!==a.indexOf(\"lon\"),s=-1!==a.indexOf(\"lat\"),l=e.lonlat,c=[];function u(t){return t+\"\\xb0\"}i||o&&s?c.push(\"(\"+u(l[0])+\", \"+u(l[1])+\")\"):o?c.push(r.lon+u(l[0])):s&&c.push(r.lat+u(l[1]));(i||-1!==a.indexOf(\"text\"))&&n.fillText(e,t,c);return c.join(\"<br>\")}(c,u,l[0].t.labels),[s]}}},{\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"../scattermapbox/hover\":1189}],976:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),colorbar:t(\"../heatmap/colorbar\"),formatLabels:t(\"../scattermapbox/format_labels\"),calc:t(\"./calc\"),plot:t(\"./plot\"),hoverPoints:t(\"./hover\"),eventData:t(\"./event_data\"),getBelow:function(t,e){for(var r=e.getMapLayers(),n=0;n<r.length;n++){var a=r[n],i=a.id;if(\"symbol\"===a.type&&\"string\"==typeof i&&-1===i.indexOf(\"plotly-\"))return i}},moduleType:\"trace\",name:\"densitymapbox\",basePlotModule:t(\"../../plots/mapbox\"),categories:[\"mapbox\",\"gl\",\"showLegend\"],meta:{hr_name:\"density_mapbox\"}}},{\"../../plots/mapbox\":820,\"../heatmap/colorbar\":1003,\"../scattermapbox/format_labels\":1188,\"./attributes\":970,\"./calc\":971,\"./defaults\":973,\"./event_data\":974,\"./hover\":975,\"./plot\":977}],977:[function(t,e,r){\"use strict\";var n=t(\"./convert\"),a=t(\"../../plots/mapbox/constants\").traceLayerPrefix;function i(t,e){this.type=\"densitymapbox\",this.subplot=t,this.uid=e,this.sourceId=\"source-\"+e,this.layerList=[[\"heatmap\",a+e+\"-heatmap\"]],this.below=null}var o=i.prototype;o.update=function(t){var e=this.subplot,r=this.layerList,a=n(t),i=e.belowLookup[\"trace-\"+this.uid];e.map.getSource(this.sourceId).setData(a.geojson),i!==this.below&&(this._removeLayers(),this._addLayers(a,i),this.below=i);for(var o=0;o<r.length;o++){var s=r[o],l=s[0],c=s[1],u=a[l];e.setOptions(c,\"setLayoutProperty\",u.layout),\"visible\"===u.layout.visibility&&e.setOptions(c,\"setPaintProperty\",u.paint)}},o._addLayers=function(t,e){for(var r=this.subplot,n=this.layerList,a=this.sourceId,i=0;i<n.length;i++){var o=n[i],s=o[0],l=t[s];r.addLayer({type:s,id:o[1],source:a,layout:l.layout,paint:l.paint},e)}},o._removeLayers=function(){for(var t=this.subplot.map,e=this.layerList,r=e.length-1;r>=0;r--)t.removeLayer(e[r][1])},o.dispose=function(){var t=this.subplot.map;this._removeLayers(),t.removeSource(this.sourceId)},e.exports=function(t,e){var r=e[0].trace,a=new i(t,r.uid),o=a.sourceId,s=n(e),l=a.below=t.belowLookup[\"trace-\"+r.uid];return t.map.addSource(o,{type:\"geojson\",data:s.geojson}),a._addLayers(s,l),a}},{\"../../plots/mapbox/constants\":818,\"./convert\":972}],978:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){for(var r=0;r<t.length;r++)t[r].i=r;n.mergeArray(e.text,t,\"tx\"),n.mergeArray(e.hovertext,t,\"htx\");var a=e.marker;if(a){n.mergeArray(a.opacity,t,\"mo\"),n.mergeArray(a.color,t,\"mc\");var i=a.line;i&&(n.mergeArray(i.color,t,\"mlc\"),n.mergeArrayCastPositive(i.width,t,\"mlw\"))}}},{\"../../lib\":717}],979:[function(t,e,r){\"use strict\";var n=t(\"../bar/attributes\"),a=t(\"../scatter/attributes\").line,i=t(\"../../plots/attributes\"),o=t(\"../../plots/template_attributes\").hovertemplateAttrs,s=t(\"../../plots/template_attributes\").texttemplateAttrs,l=t(\"./constants\"),c=t(\"../../lib/extend\").extendFlat,u=t(\"../../components/color\");e.exports={x:n.x,x0:n.x0,dx:n.dx,y:n.y,y0:n.y0,dy:n.dy,hovertext:n.hovertext,hovertemplate:o({},{keys:l.eventDataKeys}),hoverinfo:c({},i.hoverinfo,{flags:[\"name\",\"x\",\"y\",\"text\",\"percent initial\",\"percent previous\",\"percent total\"]}),textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"percent initial\",\"percent previous\",\"percent total\",\"value\"],extras:[\"none\"],editType:\"plot\",arrayOk:!1},texttemplate:s({editType:\"plot\"},{keys:l.eventDataKeys.concat([\"label\",\"value\"])}),text:n.text,textposition:c({},n.textposition,{dflt:\"auto\"}),insidetextanchor:c({},n.insidetextanchor,{dflt:\"middle\"}),textangle:c({},n.textangle,{dflt:0}),textfont:n.textfont,insidetextfont:n.insidetextfont,outsidetextfont:n.outsidetextfont,constraintext:n.constraintext,cliponaxis:n.cliponaxis,orientation:c({},n.orientation,{}),offset:c({},n.offset,{arrayOk:!1}),width:c({},n.width,{arrayOk:!1}),marker:n.marker,connector:{fillcolor:{valType:\"color\",editType:\"style\"},line:{color:c({},a.color,{dflt:u.defaultLine}),width:c({},a.width,{dflt:0,editType:\"plot\"}),dash:a.dash,editType:\"style\"},visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},editType:\"plot\"},offsetgroup:n.offsetgroup,alignmentgroup:n.alignmentgroup}},{\"../../components/color\":592,\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"../bar/attributes\":856,\"../scatter/attributes\":1120,\"./constants\":981}],980:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\"),a=t(\"./arrays_to_calcdata\"),i=t(\"../scatter/calc_selection\"),o=t(\"../../constants/numerical\").BADNUM;function s(t){return t===o?0:t}e.exports=function(t,e){var r,l,c,u,h=n.getFromId(t,e.xaxis||\"x\"),f=n.getFromId(t,e.yaxis||\"y\");\"h\"===e.orientation?(r=h.makeCalcdata(e,\"x\"),l=f.makeCalcdata(e,\"y\")):(r=f.makeCalcdata(e,\"y\"),l=h.makeCalcdata(e,\"x\"));var p,d=Math.min(l.length,r.length),g=new Array(d);for(e._base=[],c=0;c<d;c++){r[c]<0&&(r[c]=o);var v=!1;r[c]!==o&&c+1<d&&r[c+1]!==o&&(v=!0),u=g[c]={p:l[c],s:r[c],cNext:v},e._base[c]=-.5*u.s,e.ids&&(u.id=String(e.ids[c])),0===c&&(g[0].vTotal=0),g[0].vTotal+=s(u.s),u.begR=s(u.s)/s(g[0].s)}for(c=0;c<d;c++)(u=g[c]).s!==o&&(u.sumR=u.s/g[0].vTotal,u.difR=void 0!==p?u.s/p:1,p=u.s);return a(g,e),i(g,e),g}},{\"../../constants/numerical\":693,\"../../plots/cartesian/axes\":765,\"../scatter/calc_selection\":1122,\"./arrays_to_calcdata\":978}],981:[function(t,e,r){\"use strict\";e.exports={eventDataKeys:[\"percentInitial\",\"percentPrevious\",\"percentTotal\"]}},{}],982:[function(t,e,r){\"use strict\";var n=t(\"../bar/cross_trace_calc\").setGroupPositions;e.exports=function(t,e){var r,a,i=t._fullLayout,o=t._fullData,s=t.calcdata,l=e.xaxis,c=e.yaxis,u=[],h=[],f=[];for(a=0;a<o.length;a++){var p=o[a],d=\"h\"===p.orientation;!0===p.visible&&p.xaxis===l._id&&p.yaxis===c._id&&\"funnel\"===p.type&&(r=s[a],d?f.push(r):h.push(r),u.push(r))}var g={mode:i.funnelmode,norm:i.funnelnorm,gap:i.funnelgap,groupgap:i.funnelgroupgap};for(n(t,l,c,h,g),n(t,c,l,f,g),a=0;a<u.length;a++){r=u[a];for(var v=0;v<r.length;v++)v+1<r.length&&(r[v].nextP0=r[v+1].p0,r[v].nextS0=r[v+1].s0,r[v].nextP1=r[v+1].p1,r[v].nextS1=r[v+1].s1)}}},{\"../bar/cross_trace_calc\":859}],983:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../bar/defaults\").handleGroupingDefaults,i=t(\"../bar/defaults\").handleText,o=t(\"../scatter/xy_defaults\"),s=t(\"./attributes\"),l=t(\"../../components/color\");e.exports={supplyDefaults:function(t,e,r,a){function c(r,a){return n.coerce(t,e,s,r,a)}if(o(t,e,a,c)){c(\"orientation\",e.y&&!e.x?\"v\":\"h\"),c(\"offset\"),c(\"width\");var u=c(\"text\");c(\"hovertext\"),c(\"hovertemplate\");var h=c(\"textposition\");i(t,e,a,c,h,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!0,moduleHasCliponaxis:!0,moduleHasTextangle:!0,moduleHasInsideanchor:!0}),\"none\"===e.textposition||e.texttemplate||c(\"textinfo\",Array.isArray(u)?\"text+value\":\"value\");var f=c(\"marker.color\",r);c(\"marker.line.color\",l.defaultLine),c(\"marker.line.width\"),c(\"connector.visible\")&&(c(\"connector.fillcolor\",function(t){var e=n.isArrayOrTypedArray(t)?\"#000\":t;return l.addOpacity(e,.5*l.opacity(e))}(f)),c(\"connector.line.width\")&&(c(\"connector.line.color\"),c(\"connector.line.dash\")))}else e.visible=!1},crossTraceDefaults:function(t,e){var r,i;function o(t){return n.coerce(i._input,i,s,t)}if(\"group\"===e.funnelmode)for(var l=0;l<t.length;l++)r=(i=t[l])._input,a(r,i,e,o)}}},{\"../../components/color\":592,\"../../lib\":717,\"../bar/defaults\":860,\"../scatter/xy_defaults\":1146,\"./attributes\":979}],984:[function(t,e,r){\"use strict\";e.exports=function(t,e){return t.x=\"xVal\"in e?e.xVal:e.x,t.y=\"yVal\"in e?e.yVal:e.y,\"percentInitial\"in e&&(t.percentInitial=e.percentInitial),\"percentPrevious\"in e&&(t.percentPrevious=e.percentPrevious),\"percentTotal\"in e&&(t.percentTotal=e.percentTotal),e.xa&&(t.xaxis=e.xa),e.ya&&(t.yaxis=e.ya),t}},{}],985:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\").opacity,a=t(\"../bar/hover\").hoverOnBars,i=t(\"../../lib\").formatPercent;e.exports=function(t,e,r,o){var s=a(t,e,r,o);if(s){var l=s.cd,c=l[0].trace,u=\"h\"===c.orientation,h=l[s.index];s[(u?\"x\":\"y\")+\"LabelVal\"]=h.s,s.percentInitial=h.begR,s.percentInitialLabel=i(h.begR,1),s.percentPrevious=h.difR,s.percentPreviousLabel=i(h.difR,1),s.percentTotal=h.sumR,s.percentTotalLabel=i(h.sumR,1);var f=h.hi||c.hoverinfo,p=[];if(f&&\"none\"!==f&&\"skip\"!==f){var d=\"all\"===f,g=f.split(\"+\"),v=function(t){return d||-1!==g.indexOf(t)};v(\"percent initial\")&&p.push(s.percentInitialLabel+\" of initial\"),v(\"percent previous\")&&p.push(s.percentPreviousLabel+\" of previous\"),v(\"percent total\")&&p.push(s.percentTotalLabel+\" of total\")}return s.extraText=p.join(\"<br>\"),s.color=function(t,e){var r=t.marker,a=e.mc||r.color,i=e.mlc||r.line.color,o=e.mlw||r.line.width;if(n(a))return a;if(n(i)&&o)return i}(c,h),[s]}}},{\"../../components/color\":592,\"../../lib\":717,\"../bar/hover\":863}],986:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,crossTraceDefaults:t(\"./defaults\").crossTraceDefaults,supplyLayoutDefaults:t(\"./layout_defaults\"),calc:t(\"./calc\"),crossTraceCalc:t(\"./cross_trace_calc\"),plot:t(\"./plot\"),style:t(\"./style\").style,hoverPoints:t(\"./hover\"),eventData:t(\"./event_data\"),selectPoints:t(\"../bar/select\"),moduleType:\"trace\",name:\"funnel\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"bar-like\",\"cartesian\",\"svg\",\"oriented\",\"showLegend\",\"zoomScale\"],meta:{}}},{\"../../plots/cartesian\":776,\"../bar/select\":868,\"./attributes\":979,\"./calc\":980,\"./cross_trace_calc\":982,\"./defaults\":983,\"./event_data\":984,\"./hover\":985,\"./layout_attributes\":987,\"./layout_defaults\":988,\"./plot\":989,\"./style\":990}],987:[function(t,e,r){\"use strict\";e.exports={funnelmode:{valType:\"enumerated\",values:[\"stack\",\"group\",\"overlay\"],dflt:\"stack\",editType:\"calc\"},funnelgap:{valType:\"number\",min:0,max:1,editType:\"calc\"},funnelgroupgap:{valType:\"number\",min:0,max:1,dflt:0,editType:\"calc\"}}},{}],988:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./layout_attributes\");e.exports=function(t,e,r){var i=!1;function o(r,i){return n.coerce(t,e,a,r,i)}for(var s=0;s<r.length;s++){var l=r[s];if(l.visible&&\"funnel\"===l.type){i=!0;break}}i&&(o(\"funnelmode\"),o(\"funnelgap\",.2),o(\"funnelgroupgap\"))}},{\"../../lib\":717,\"./layout_attributes\":987}],989:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\"),i=t(\"../../components/drawing\"),o=t(\"../bar/plot\"),s=t(\"../bar/uniform_text\").clearMinTextSize;function l(t,e,r,n){var a=[],i=[],o=n?e:r,s=n?r:e;return a[0]=o.c2p(t.s0,!0),i[0]=s.c2p(t.p0,!0),a[1]=o.c2p(t.s1,!0),i[1]=s.c2p(t.p1,!0),a[2]=o.c2p(t.nextS0,!0),i[2]=s.c2p(t.nextP0,!0),a[3]=o.c2p(t.nextS1,!0),i[3]=s.c2p(t.nextP1,!0),n?[a,i]:[i,a]}e.exports=function(t,e,r,c){var u=t._fullLayout;s(\"funnel\",u),function(t,e,r,o){var s=e.xaxis,c=e.yaxis;a.makeTraceGroups(o,r,\"trace bars\").each(function(r){var o=n.select(this),u=r[0].trace,h=a.ensureSingle(o,\"g\",\"regions\");if(u.connector&&u.connector.visible){var f=\"h\"===u.orientation,p=h.selectAll(\"g.region\").data(a.identity);p.enter().append(\"g\").classed(\"region\",!0),p.exit().remove();var d=p.size();p.each(function(r,o){if(o===d-1||r.cNext){var u=l(r,s,c,f),h=u[0],p=u[1],g=\"\";void 0!==h[3]&&void 0!==p[3]&&(g+=f?\"M\"+h[0]+\",\"+p[1]+\"L\"+h[2]+\",\"+p[2]+\"H\"+h[3]+\"L\"+h[1]+\",\"+p[1]+\"Z\":\"M\"+h[1]+\",\"+p[1]+\"L\"+h[2]+\",\"+p[3]+\"V\"+p[2]+\"L\"+h[1]+\",\"+p[0]+\"Z\"),a.ensureSingle(n.select(this),\"path\").attr(\"d\",g).call(i.setClipUrl,e.layerClipId,t)}})}else h.remove()})}(t,e,r,c),function(t,e,r,o){var s=e.xaxis,c=e.yaxis;a.makeTraceGroups(o,r,\"trace bars\").each(function(r){var o=n.select(this),u=r[0].trace,h=a.ensureSingle(o,\"g\",\"lines\");if(u.connector&&u.connector.visible&&u.connector.line.width){var f=\"h\"===u.orientation,p=h.selectAll(\"g.line\").data(a.identity);p.enter().append(\"g\").classed(\"line\",!0),p.exit().remove();var d=p.size();p.each(function(r,o){if(o===d-1||r.cNext){var u=l(r,s,c,f),h=u[0],p=u[1],g=\"\";void 0!==h[3]&&void 0!==p[3]&&(f?(g+=\"M\"+h[0]+\",\"+p[1]+\"L\"+h[2]+\",\"+p[2],g+=\"M\"+h[1]+\",\"+p[1]+\"L\"+h[3]+\",\"+p[2]):(g+=\"M\"+h[1]+\",\"+p[1]+\"L\"+h[2]+\",\"+p[3],g+=\"M\"+h[1]+\",\"+p[0]+\"L\"+h[2]+\",\"+p[2])),\"\"===g&&(g=\"M0,0Z\"),a.ensureSingle(n.select(this),\"path\").attr(\"d\",g).call(i.setClipUrl,e.layerClipId,t)}})}else h.remove()})}(t,e,r,c),o.plot(t,e,r,c,{mode:u.funnelmode,norm:u.funnelmode,gap:u.funnelgap,groupgap:u.funnelgroupgap})}},{\"../../components/drawing\":613,\"../../lib\":717,\"../bar/plot\":867,\"../bar/uniform_text\":872,d3:165}],990:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../components/drawing\"),i=t(\"../../components/color\"),o=t(\"../../constants/interactions\").DESELECTDIM,s=t(\"../bar/style\"),l=t(\"../bar/uniform_text\").resizeText,c=s.styleTextPoints;e.exports={style:function(t,e,r){var s=r||n.select(t).selectAll(\"g.funnellayer\").selectAll(\"g.trace\");l(t,s,\"funnel\"),s.style(\"opacity\",function(t){return t[0].trace.opacity}),s.each(function(e){var r=n.select(this),s=e[0].trace;r.selectAll(\".point > path\").each(function(t){if(!t.isBlank){var e=s.marker;n.select(this).call(i.fill,t.mc||e.color).call(i.stroke,t.mlc||e.line.color).call(a.dashLine,e.line.dash,t.mlw||e.line.width).style(\"opacity\",s.selectedpoints&&!t.selected?o:1)}}),c(r,s,t),r.selectAll(\".regions\").each(function(){n.select(this).selectAll(\"path\").style(\"stroke-width\",0).call(i.fill,s.connector.fillcolor)}),r.selectAll(\".lines\").each(function(){var t=s.connector.line;a.lineGroupStyle(n.select(this).selectAll(\"path\"),t.width,t.color,t.dash)})})}}},{\"../../components/color\":592,\"../../components/drawing\":613,\"../../constants/interactions\":692,\"../bar/style\":870,\"../bar/uniform_text\":872,d3:165}],991:[function(t,e,r){\"use strict\";var n=t(\"../pie/attributes\"),a=t(\"../../plots/attributes\"),i=t(\"../../plots/domain\").attributes,o=t(\"../../plots/template_attributes\").hovertemplateAttrs,s=t(\"../../plots/template_attributes\").texttemplateAttrs,l=t(\"../../lib/extend\").extendFlat;e.exports={labels:n.labels,label0:n.label0,dlabel:n.dlabel,values:n.values,marker:{colors:n.marker.colors,line:{color:l({},n.marker.line.color,{dflt:null}),width:l({},n.marker.line.width,{dflt:1}),editType:\"calc\"},editType:\"calc\"},text:n.text,hovertext:n.hovertext,scalegroup:l({},n.scalegroup,{}),textinfo:l({},n.textinfo,{flags:[\"label\",\"text\",\"value\",\"percent\"]}),texttemplate:s({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"text\",\"percent\"]}),hoverinfo:l({},a.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:o({},{keys:[\"label\",\"color\",\"value\",\"text\",\"percent\"]}),textposition:l({},n.textposition,{values:[\"inside\",\"none\"],dflt:\"inside\"}),textfont:n.textfont,insidetextfont:n.insidetextfont,title:{text:n.title.text,font:n.title.font,position:l({},n.title.position,{values:[\"top left\",\"top center\",\"top right\"],dflt:\"top center\"}),editType:\"plot\"},domain:i({name:\"funnelarea\",trace:!0,editType:\"calc\"}),aspectratio:{valType:\"number\",min:0,dflt:1,editType:\"plot\"},baseratio:{valType:\"number\",min:0,max:1,dflt:.333,editType:\"plot\"}}},{\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/domain\":790,\"../../plots/template_attributes\":841,\"../pie/attributes\":1094}],992:[function(t,e,r){\"use strict\";var n=t(\"../../plots/plots\");r.name=\"funnelarea\",r.plot=function(t,e,a,i){n.plotBasePlot(r.name,t,e,a,i)},r.clean=function(t,e,a,i){n.cleanBasePlot(r.name,t,e,a,i)}},{\"../../plots/plots\":826}],993:[function(t,e,r){\"use strict\";var n=t(\"../pie/calc\");e.exports={calc:function(t,e){return n.calc(t,e)},crossTraceCalc:function(t){n.crossTraceCalc(t,{type:\"funnelarea\"})}}},{\"../pie/calc\":1096}],994:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./attributes\"),i=t(\"../../plots/domain\").defaults,o=t(\"../bar/defaults\").handleText,s=t(\"../pie/defaults\").handleLabelsAndValues;e.exports=function(t,e,r,l){function c(r,i){return n.coerce(t,e,a,r,i)}var u=c(\"labels\"),h=c(\"values\"),f=s(u,h),p=f.len;if(e._hasLabels=f.hasLabels,e._hasValues=f.hasValues,!e._hasLabels&&e._hasValues&&(c(\"label0\"),c(\"dlabel\")),p){e._length=p,c(\"marker.line.width\")&&c(\"marker.line.color\",l.paper_bgcolor),c(\"marker.colors\"),c(\"scalegroup\");var d,g=c(\"text\"),v=c(\"texttemplate\");if(v||(d=c(\"textinfo\",Array.isArray(g)?\"text+percent\":\"percent\")),c(\"hovertext\"),c(\"hovertemplate\"),v||d&&\"none\"!==d){var m=c(\"textposition\");o(t,e,l,c,m,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1})}i(e,l,c),c(\"title.text\")&&(c(\"title.position\"),n.coerceFont(c,\"title.font\",l.font)),c(\"aspectratio\"),c(\"baseratio\")}else e.visible=!1}},{\"../../lib\":717,\"../../plots/domain\":790,\"../bar/defaults\":860,\"../pie/defaults\":1097,\"./attributes\":991}],995:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"funnelarea\",basePlotModule:t(\"./base_plot\"),categories:[\"pie-like\",\"funnelarea\",\"showLegend\"],attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyDefaults:t(\"./defaults\"),supplyLayoutDefaults:t(\"./layout_defaults\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\"),style:t(\"./style\"),styleOne:t(\"../pie/style_one\"),meta:{}}},{\"../pie/style_one\":1105,\"./attributes\":991,\"./base_plot\":992,\"./calc\":993,\"./defaults\":994,\"./layout_attributes\":996,\"./layout_defaults\":997,\"./plot\":998,\"./style\":999}],996:[function(t,e,r){\"use strict\";var n=t(\"../pie/layout_attributes\").hiddenlabels;e.exports={hiddenlabels:n,funnelareacolorway:{valType:\"colorlist\",editType:\"calc\"},extendfunnelareacolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{\"../pie/layout_attributes\":1101}],997:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,i){return n.coerce(t,e,a,r,i)}r(\"hiddenlabels\"),r(\"funnelareacolorway\",e.colorway),r(\"extendfunnelareacolors\")}},{\"../../lib\":717,\"./layout_attributes\":996}],998:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../components/drawing\"),i=t(\"../../lib\"),o=t(\"../../lib/svg_text_utils\"),s=t(\"../bar/plot\").toMoveInsideBar,l=t(\"../bar/uniform_text\"),c=l.recordMinTextSize,u=l.clearMinTextSize,h=t(\"../pie/helpers\"),f=t(\"../pie/plot\"),p=f.attachFxHandlers,d=f.determineInsideTextFont,g=f.layoutAreas,v=f.prerenderTitles,m=f.positionTitleOutside,y=f.formatSliceLabel;function x(t,e){return\"l\"+(e[0]-t[0])+\",\"+(e[1]-t[1])}e.exports=function(t,e){var r=t._fullLayout;u(\"funnelarea\",r),v(e,t),g(e,r._size),i.makeTraceGroups(r._funnelarealayer,e,\"trace\").each(function(e){var l=n.select(this),u=e[0],f=u.trace;!function(t){if(!t.length)return;var e=t[0],r=e.trace,n=r.aspectratio,a=r.baseratio;a>.999&&(a=.999);var i,o=Math.pow(a,2),s=e.vTotal,l=s,c=s*o/(1-o)/s;function u(){var t,e={x:t=Math.sqrt(c),y:-t};return[e.x,e.y]}var h,f,p=[];for(p.push(u()),h=t.length-1;h>-1;h--)if(!(f=t[h]).hidden){var d=f.v/l;c+=d,p.push(u())}var g=1/0,v=-1/0;for(h=0;h<p.length;h++)i=p[h],g=Math.min(g,i[1]),v=Math.max(v,i[1]);for(h=0;h<p.length;h++)p[h][1]-=(v+g)/2;var m=p[p.length-1][0],y=e.r,x=(v-g)/2,b=y/m,_=y/x*n;for(e.r=_*x,h=0;h<p.length;h++)p[h][0]*=b,p[h][1]*=_;var w=[-(i=p[0])[0],i[1]],k=[i[0],i[1]],T=0;for(h=t.length-1;h>-1;h--)if(!(f=t[h]).hidden){var M=p[T+=1][0],A=p[T][1];f.TL=[-M,A],f.TR=[M,A],f.BL=w,f.BR=k,f.pxmid=(S=f.TR,E=f.BR,[.5*(S[0]+E[0]),.5*(S[1]+E[1])]),w=f.TL,k=f.TR}var S,E}(e),l.each(function(){var l=n.select(this).selectAll(\"g.slice\").data(e);l.enter().append(\"g\").classed(\"slice\",!0),l.exit().remove(),l.each(function(l,g){if(l.hidden)n.select(this).selectAll(\"path,g\").remove();else{l.pointNumber=l.i,l.curveNumber=f.index;var v=u.cx,m=u.cy,b=n.select(this),_=b.selectAll(\"path.surface\").data([l]);_.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),b.call(p,t,e);var w=\"M\"+(v+l.TR[0])+\",\"+(m+l.TR[1])+x(l.TR,l.BR)+x(l.BR,l.BL)+x(l.BL,l.TL)+\"Z\";_.attr(\"d\",w),y(t,l,u);var k=h.castOption(f.textposition,l.pts),T=b.selectAll(\"g.slicetext\").data(l.text&&\"none\"!==k?[0]:[]);T.enter().append(\"g\").classed(\"slicetext\",!0),T.exit().remove(),T.each(function(){var u=i.ensureSingle(n.select(this),\"text\",\"\",function(t){t.attr(\"data-notex\",1)}),h=i.ensureUniformFontSize(t,d(f,l,r.font));u.text(l.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(a.font,h).call(o.convertToTspans,t);var p,y,x,b=a.bBox(u.node()),_=Math.min(l.BL[1],l.BR[1])+m,w=Math.max(l.TL[1],l.TR[1])+m;y=Math.max(l.TL[0],l.BL[0])+v,x=Math.min(l.TR[0],l.BR[0])+v,(p=s(y,x,_,w,b,{isHorizontal:!0,constrained:!0,angle:0,anchor:\"middle\"})).fontSize=h.size,c(f.type,p,r),e[g].transform=p,u.attr(\"transform\",i.getTextTransform(p))})}});var g=n.select(this).selectAll(\"g.titletext\").data(f.title.text?[0]:[]);g.enter().append(\"g\").classed(\"titletext\",!0),g.exit().remove(),g.each(function(){var e=i.ensureSingle(n.select(this),\"text\",\"\",function(t){t.attr(\"data-notex\",1)}),s=f.title.text;f._meta&&(s=i.templateString(s,f._meta)),e.text(s).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(a.font,f.title.font).call(o.convertToTspans,t);var l=m(u,r._size);e.attr(\"transform\",\"translate(\"+l.x+\",\"+l.y+\")\"+(l.scale<1?\"scale(\"+l.scale+\")\":\"\")+\"translate(\"+l.tx+\",\"+l.ty+\")\")})})})}},{\"../../components/drawing\":613,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"../bar/plot\":867,\"../bar/uniform_text\":872,\"../pie/helpers\":1099,\"../pie/plot\":1103,d3:165}],999:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../pie/style_one\"),i=t(\"../bar/uniform_text\").resizeText;e.exports=function(t){var e=t._fullLayout._funnelarealayer.selectAll(\".trace\");i(t,e,\"funnelarea\"),e.each(function(t){var e=t[0].trace,r=n.select(this);r.style({opacity:e.opacity}),r.selectAll(\"path.surface\").each(function(t){n.select(this).call(a,t,e)})})}},{\"../bar/uniform_text\":872,\"../pie/style_one\":1105,d3:165}],1000:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),a=t(\"../../plots/attributes\"),i=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../../components/colorscale/attributes\"),s=(t(\"../../constants/docs\").FORMAT_LINK,t(\"../../lib/extend\").extendFlat);e.exports=s({z:{valType:\"data_array\",editType:\"calc\"},x:s({},n.x,{impliedEdits:{xtype:\"array\"}}),x0:s({},n.x0,{impliedEdits:{xtype:\"scaled\"}}),dx:s({},n.dx,{impliedEdits:{xtype:\"scaled\"}}),y:s({},n.y,{impliedEdits:{ytype:\"array\"}}),y0:s({},n.y0,{impliedEdits:{ytype:\"scaled\"}}),dy:s({},n.dy,{impliedEdits:{ytype:\"scaled\"}}),text:{valType:\"data_array\",editType:\"calc\"},hovertext:{valType:\"data_array\",editType:\"calc\"},transpose:{valType:\"boolean\",dflt:!1,editType:\"calc\"},xtype:{valType:\"enumerated\",values:[\"array\",\"scaled\"],editType:\"calc+clearAxisTypes\"},ytype:{valType:\"enumerated\",values:[\"array\",\"scaled\"],editType:\"calc+clearAxisTypes\"},zsmooth:{valType:\"enumerated\",values:[\"fast\",\"best\",!1],dflt:!1,editType:\"calc\"},hoverongaps:{valType:\"boolean\",dflt:!0,editType:\"none\"},connectgaps:{valType:\"boolean\",editType:\"calc\"},xgap:{valType:\"number\",dflt:0,min:0,editType:\"plot\"},ygap:{valType:\"number\",dflt:0,min:0,editType:\"plot\"},zhoverformat:{valType:\"string\",dflt:\"\",editType:\"none\"},hovertemplate:i(),showlegend:s({},a.showlegend,{dflt:!1})},{transforms:void 0},o(\"\",{cLetter:\"z\",autoColorDflt:!1}))},{\"../../components/colorscale/attributes\":599,\"../../constants/docs\":688,\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"../scatter/attributes\":1120}],1001:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../lib\"),i=t(\"../../plots/cartesian/axes\"),o=t(\"../histogram2d/calc\"),s=t(\"../../components/colorscale/calc\"),l=t(\"./convert_column_xyz\"),c=t(\"./clean_2d_array\"),u=t(\"./interp2d\"),h=t(\"./find_empties\"),f=t(\"./make_bound_array\");e.exports=function(t,e){var r,p,d,g,v,m,y,x,b,_=i.getFromId(t,e.xaxis||\"x\"),w=i.getFromId(t,e.yaxis||\"y\"),k=n.traceIs(e,\"contour\"),T=n.traceIs(e,\"histogram\"),M=n.traceIs(e,\"gl2d\"),A=k?\"best\":e.zsmooth;if(_._minDtick=0,w._minDtick=0,T)r=(b=o(t,e)).x,p=b.x0,d=b.dx,g=b.y,v=b.y0,m=b.dy,y=b.z;else{var S=e.z;a.isArray1D(S)?(l(e,_,w,\"x\",\"y\",[\"z\"]),r=e._x,g=e._y,S=e._z):(r=e._x=e.x?_.makeCalcdata(e,\"x\"):[],g=e._y=e.y?w.makeCalcdata(e,\"y\"):[]),p=e.x0,d=e.dx,v=e.y0,m=e.dy,y=c(S,e,_,w),(k||e.connectgaps)&&(e._emptypoints=h(y),u(y,e._emptypoints))}function E(t){A=e._input.zsmooth=e.zsmooth=!1,a.warn('cannot use zsmooth: \"fast\": '+t)}if(\"fast\"===A)if(\"log\"===_.type||\"log\"===w.type)E(\"log axis found\");else if(!T){if(r.length){var L=(r[r.length-1]-r[0])/(r.length-1),C=Math.abs(L/100);for(x=0;x<r.length-1;x++)if(Math.abs(r[x+1]-r[x]-L)>C){E(\"x scale is not linear\");break}}if(g.length&&\"fast\"===A){var P=(g[g.length-1]-g[0])/(g.length-1),O=Math.abs(P/100);for(x=0;x<g.length-1;x++)if(Math.abs(g[x+1]-g[x]-P)>O){E(\"y scale is not linear\");break}}}var z=a.maxRowLength(y),I=\"scaled\"===e.xtype?\"\":r,D=f(e,I,p,d,z,_),R=\"scaled\"===e.ytype?\"\":g,F=f(e,R,v,m,y.length,w);M||(e._extremes[_._id]=i.findExtremes(_,D),e._extremes[w._id]=i.findExtremes(w,F));var B={x:D,y:F,z:y,text:e._text||e.text,hovertext:e._hovertext||e.hovertext};if(I&&I.length===D.length-1&&(B.xCenter=I),R&&R.length===F.length-1&&(B.yCenter=R),T&&(B.xRanges=b.xRanges,B.yRanges=b.yRanges,B.pts=b.pts),k||s(t,e,{vals:y,cLetter:\"z\"}),k&&e.contours&&\"heatmap\"===e.contours.coloring){var N={type:\"contour\"===e.type?\"heatmap\":\"histogram2d\",xcalendar:e.xcalendar,ycalendar:e.ycalendar};B.xfill=f(N,I,p,d,z,_),B.yfill=f(N,R,v,m,y.length,w)}return[B]}},{\"../../components/colorscale/calc\":600,\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"../../registry\":846,\"../histogram2d/calc\":1032,\"./clean_2d_array\":1002,\"./convert_column_xyz\":1004,\"./find_empties\":1006,\"./interp2d\":1009,\"./make_bound_array\":1010}],1002:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib\"),i=t(\"../../constants/numerical\").BADNUM;e.exports=function(t,e,r,o){var s,l,c,u,h,f;function p(t){if(n(t))return+t}if(e&&e.transpose){for(s=0,h=0;h<t.length;h++)s=Math.max(s,t[h].length);if(0===s)return!1;c=function(t){return t.length},u=function(t,e,r){return(t[r]||[])[e]}}else s=t.length,c=function(t,e){return t[e].length},u=function(t,e,r){return(t[e]||[])[r]};var d=function(t,e,r){return e===i||r===i?i:u(t,e,r)};function g(t){if(e&&\"carpet\"!==e.type&&\"contourcarpet\"!==e.type&&t&&\"category\"===t.type&&e[\"_\"+t._id.charAt(0)].length){var r=t._id.charAt(0),n={},o=e[\"_\"+r+\"CategoryMap\"]||e[r];for(h=0;h<o.length;h++)n[o[h]]=h;return function(e){var r=n[t._categories[e]];return r+1?r:i}}return a.identity}var v=g(r),m=g(o);o&&\"category\"===o.type&&(s=o._categories.length);var y=new Array(s);for(h=0;h<s;h++)for(l=r&&\"category\"===r.type?r._categories.length:c(t,h),y[h]=new Array(l),f=0;f<l;f++)y[h][f]=p(d(t,m(h),v(f)));return y}},{\"../../constants/numerical\":693,\"../../lib\":717,\"fast-isnumeric\":228}],1003:[function(t,e,r){\"use strict\";e.exports={min:\"zmin\",max:\"zmax\"}},{}],1004:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../constants/numerical\").BADNUM;e.exports=function(t,e,r,i,o,s){var l,c,u,h,f=t._length,p=e.makeCalcdata(t,i),d=r.makeCalcdata(t,o),g=t.text,v=void 0!==g&&n.isArray1D(g),m=t.hovertext,y=void 0!==m&&n.isArray1D(m),x=n.distinctVals(p),b=x.vals,_=n.distinctVals(d),w=_.vals,k=[];for(l=0;l<s.length;l++)k[l]=n.init2dArray(w.length,b.length);v&&(u=n.init2dArray(w.length,b.length)),y&&(h=n.init2dArray(w.length,b.length));var T=n.init2dArray(w.length,b.length);for(l=0;l<f;l++)if(p[l]!==a&&d[l]!==a){var M=n.findBin(p[l]+x.minDiff/2,b),A=n.findBin(d[l]+_.minDiff/2,w);for(c=0;c<s.length;c++){var S=t[s[c]];k[c][A][M]=S[l],T[A][M]=l}v&&(u[A][M]=g[l]),y&&(h[A][M]=m[l])}for(t[\"_\"+i]=b,t[\"_\"+o]=w,c=0;c<s.length;c++)t[\"_\"+s[c]]=k[c];v&&(t._text=u),y&&(t._hovertext=h),e&&\"category\"===e.type&&(t[\"_\"+i+\"CategoryMap\"]=b.map(function(t){return e._categories[t]})),r&&\"category\"===r.type&&(t[\"_\"+o+\"CategoryMap\"]=w.map(function(t){return r._categories[t]})),t._after2before=T}},{\"../../constants/numerical\":693,\"../../lib\":717}],1005:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./xyz_defaults\"),i=t(\"./style_defaults\"),o=t(\"../../components/colorscale/defaults\"),s=t(\"./attributes\");e.exports=function(t,e,r,l){function c(r,a){return n.coerce(t,e,s,r,a)}a(t,e,c,l)?(c(\"text\"),c(\"hovertext\"),c(\"hovertemplate\"),i(t,e,c,l),c(\"hoverongaps\"),c(\"connectgaps\",n.isArray1D(e.z)&&!1!==e.zsmooth),o(t,e,l,c,{prefix:\"\",cLetter:\"z\"})):e.visible=!1}},{\"../../components/colorscale/defaults\":602,\"../../lib\":717,\"./attributes\":1e3,\"./style_defaults\":1013,\"./xyz_defaults\":1014}],1006:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").maxRowLength;e.exports=function(t){var e,r,a,i,o,s,l,c,u=[],h={},f=[],p=t[0],d=[],g=[0,0,0],v=n(t);for(r=0;r<t.length;r++)for(e=d,d=p,p=t[r+1]||[],a=0;a<v;a++)void 0===d[a]&&((s=(void 0!==d[a-1]?1:0)+(void 0!==d[a+1]?1:0)+(void 0!==e[a]?1:0)+(void 0!==p[a]?1:0))?(0===r&&s++,0===a&&s++,r===t.length-1&&s++,a===d.length-1&&s++,s<4&&(h[[r,a]]=[r,a,s]),u.push([r,a,s])):f.push([r,a]));for(;f.length;){for(l={},c=!1,o=f.length-1;o>=0;o--)(s=((h[[(r=(i=f[o])[0])-1,a=i[1]]]||g)[2]+(h[[r+1,a]]||g)[2]+(h[[r,a-1]]||g)[2]+(h[[r,a+1]]||g)[2])/20)&&(l[i]=[r,a,s],f.splice(o,1),c=!0);if(!c)throw\"findEmpties iterated with no new neighbors\";for(i in l)h[i]=l[i],u.push(l[i])}return u.sort(function(t,e){return e[2]-t[2]})}},{\"../../lib\":717}],1007:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx\"),a=t(\"../../lib\"),i=t(\"../../plots/cartesian/axes\"),o=t(\"../../components/colorscale\").extractOpts;e.exports=function(t,e,r,s,l,c){var u,h,f,p,d=t.cd[0],g=d.trace,v=t.xa,m=t.ya,y=d.x,x=d.y,b=d.z,_=d.xCenter,w=d.yCenter,k=d.zmask,T=g.zhoverformat,M=y,A=x;if(!1!==t.index){try{f=Math.round(t.index[1]),p=Math.round(t.index[0])}catch(e){return void a.error(\"Error hovering on heatmap, pointNumber must be [row,col], found:\",t.index)}if(f<0||f>=b[0].length||p<0||p>b.length)return}else{if(n.inbox(e-y[0],e-y[y.length-1],0)>0||n.inbox(r-x[0],r-x[x.length-1],0)>0)return;if(c){var S;for(M=[2*y[0]-y[1]],S=1;S<y.length;S++)M.push((y[S]+y[S-1])/2);for(M.push([2*y[y.length-1]-y[y.length-2]]),A=[2*x[0]-x[1]],S=1;S<x.length;S++)A.push((x[S]+x[S-1])/2);A.push([2*x[x.length-1]-x[x.length-2]])}f=Math.max(0,Math.min(M.length-2,a.findBin(e,M))),p=Math.max(0,Math.min(A.length-2,a.findBin(r,A)))}var E=v.c2p(y[f]),L=v.c2p(y[f+1]),C=m.c2p(x[p]),P=m.c2p(x[p+1]);c?(L=E,u=y[f],P=C,h=x[p]):(u=_?_[f]:(y[f]+y[f+1])/2,h=w?w[p]:(x[p]+x[p+1])/2,v&&\"category\"===v.type&&(u=y[f]),m&&\"category\"===m.type&&(h=x[p]),g.zsmooth&&(E=L=v.c2p(u),C=P=m.c2p(h)));var O=b[p][f];if(k&&!k[p][f]&&(O=void 0),void 0!==O||g.hoverongaps){var z;Array.isArray(d.hovertext)&&Array.isArray(d.hovertext[p])?z=d.hovertext[p][f]:Array.isArray(d.text)&&Array.isArray(d.text[p])&&(z=d.text[p][f]);var I=o(g),D={type:\"linear\",range:[I.min,I.max],hoverformat:T,_separators:v._separators,_numFormat:v._numFormat},R=i.tickText(D,O,\"hover\").text;return[a.extendFlat(t,{index:g._after2before?g._after2before[p][f]:[p,f],distance:t.maxHoverDistance,spikeDistance:t.maxSpikeDistance,x0:E,x1:L,y0:C,y1:P,xLabelVal:u,yLabelVal:h,zLabelVal:O,zLabel:R,text:z})]}}},{\"../../components/colorscale\":604,\"../../components/fx\":630,\"../../lib\":717,\"../../plots/cartesian/axes\":765}],1008:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"./plot\"),colorbar:t(\"./colorbar\"),style:t(\"./style\"),hoverPoints:t(\"./hover\"),moduleType:\"trace\",name:\"heatmap\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"cartesian\",\"svg\",\"2dMap\",\"showLegend\"],meta:{}}},{\"../../plots/cartesian\":776,\"./attributes\":1e3,\"./calc\":1001,\"./colorbar\":1003,\"./defaults\":1005,\"./hover\":1007,\"./plot\":1011,\"./style\":1012}],1009:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=[[-1,0],[1,0],[0,-1],[0,1]];function i(t){return.5-.25*Math.min(1,.5*t)}function o(t,e,r){var n,i,o,s,l,c,u,h,f,p,d,g,v,m=0;for(s=0;s<e.length;s++){for(i=(n=e[s])[0],o=n[1],d=t[i][o],p=0,f=0,l=0;l<4;l++)(u=t[i+(c=a[l])[0]])&&void 0!==(h=u[o+c[1]])&&(0===p?g=v=h:(g=Math.min(g,h),v=Math.max(v,h)),f++,p+=h);if(0===f)throw\"iterateInterp2d order is wrong: no defined neighbors\";t[i][o]=p/f,void 0===d?f<4&&(m=1):(t[i][o]=(1+r)*t[i][o]-r*d,v>g&&(m=Math.max(m,Math.abs(t[i][o]-d)/(v-g))))}return m}e.exports=function(t,e){var r,a=1;for(o(t,e),r=0;r<e.length&&!(e[r][2]<4);r++);for(e=e.slice(r),r=0;r<100&&a>.01;r++)a=o(t,e,i(a));return a>.01&&n.log(\"interp2d didn't converge quickly\",a),t}},{\"../../lib\":717}],1010:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../lib\").isArrayOrTypedArray;e.exports=function(t,e,r,i,o,s){var l,c,u,h=[],f=n.traceIs(t,\"contour\"),p=n.traceIs(t,\"histogram\"),d=n.traceIs(t,\"gl2d\");if(a(e)&&e.length>1&&!p&&\"category\"!==s.type){var g=e.length;if(!(g<=o))return f?e.slice(0,o):e.slice(0,o+1);if(f||d)h=e.slice(0,o);else if(1===o)h=[e[0]-.5,e[0]+.5];else{for(h=[1.5*e[0]-.5*e[1]],u=1;u<g;u++)h.push(.5*(e[u-1]+e[u]));h.push(1.5*e[g-1]-.5*e[g-2])}if(g<o){var v=h[h.length-1],m=v-h[h.length-2];for(u=g;u<o;u++)v+=m,h.push(v)}}else{var y=t[s._id.charAt(0)+\"calendar\"];if(p)l=s.r2c(r,0,y);else if(a(e)&&1===e.length)l=e[0];else if(void 0===r)l=0;else{l=(\"log\"===s.type?s.d2c:s.r2c)(r,0,y)}for(c=i||1,u=f||d?0:-.5;u<o;u++)h.push(l+c*u)}return h}},{\"../../lib\":717,\"../../registry\":846}],1011:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"tinycolor2\"),i=t(\"../../registry\"),o=t(\"../../lib\"),s=t(\"../../components/colorscale\").makeColorScaleFuncFromTrace,l=t(\"../../constants/xmlns_namespaces\");function c(t,e){var r=e.length-2,n=o.constrain(o.findBin(t,e),0,r),a=e[n],i=e[n+1],s=o.constrain(n+(t-a)/(i-a)-.5,0,r),l=Math.round(s),c=Math.abs(s-l);return s&&s!==r&&c?{bin0:l,frac:c,bin1:Math.round(l+c/(s-l))}:{bin0:l,bin1:l,frac:0}}function u(t,e){var r=e.length-1,n=o.constrain(o.findBin(t,e),0,r),a=e[n],i=(t-a)/(e[n+1]-a)||0;return i<=0?{bin0:n,bin1:n,frac:0}:i<.5?{bin0:n,bin1:n+1,frac:i}:{bin0:n+1,bin1:n,frac:1-i}}function h(t,e,r){t[e]=r[0],t[e+1]=r[1],t[e+2]=r[2],t[e+3]=Math.round(255*r[3])}e.exports=function(t,e,r,f){var p=e.xaxis,d=e.yaxis;o.makeTraceGroups(f,r,\"hm\").each(function(e){var r,f,g,v,m,y,x=n.select(this),b=e[0],_=b.trace,w=b.z,k=b.x,T=b.y,M=b.xCenter,A=b.yCenter,S=i.traceIs(_,\"contour\"),E=S?\"best\":_.zsmooth,L=w.length,C=o.maxRowLength(w),P=!1,O=!1;for(y=0;void 0===r&&y<k.length-1;)r=p.c2p(k[y]),y++;for(y=k.length-1;void 0===f&&y>0;)f=p.c2p(k[y]),y--;for(f<r&&(g=f,f=r,r=g,P=!0),y=0;void 0===v&&y<T.length-1;)v=d.c2p(T[y]),y++;for(y=T.length-1;void 0===m&&y>0;)m=d.c2p(T[y]),y--;if(m<v&&(g=v,v=m,m=g,O=!0),S&&(M=k,A=T,k=b.xfill,T=b.yfill),\"fast\"!==E){var z=\"best\"===E?0:.5;r=Math.max(-z*p._length,r),f=Math.min((1+z)*p._length,f),v=Math.max(-z*d._length,v),m=Math.min((1+z)*d._length,m)}var I=Math.round(f-r),D=Math.round(m-v);if(I<=0||D<=0){x.selectAll(\"image\").data([]).exit().remove()}else{var R,F;\"fast\"===E?(R=C,F=L):(R=I,F=D);var B=document.createElement(\"canvas\");B.width=R,B.height=F;var N,j,V=B.getContext(\"2d\"),U=s(_,{noNumericCheck:!0,returnArray:!0});\"fast\"===E?(N=P?function(t){return C-1-t}:o.identity,j=O?function(t){return L-1-t}:o.identity):(N=function(t){return o.constrain(Math.round(p.c2p(k[t])-r),0,I)},j=function(t){return o.constrain(Math.round(d.c2p(T[t])-v),0,D)});var q,H,G,Y,W,X=j(0),Z=[X,X],J=P?0:1,K=O?0:1,Q=0,$=0,tt=0,et=0;if(E){var rt,nt=0;try{rt=new Uint8Array(I*D*4)}catch(t){rt=new Array(I*D*4)}if(\"best\"===E){var at,it,ot,st=M||k,lt=A||T,ct=new Array(st.length),ut=new Array(lt.length),ht=new Array(I),ft=M?u:c,pt=A?u:c;for(y=0;y<st.length;y++)ct[y]=Math.round(p.c2p(st[y])-r);for(y=0;y<lt.length;y++)ut[y]=Math.round(d.c2p(lt[y])-v);for(y=0;y<I;y++)ht[y]=ft(y,ct);for(H=0;H<D;H++)for(it=w[(at=pt(H,ut)).bin0],ot=w[at.bin1],y=0;y<I;y++,nt+=4)h(rt,nt,W=Tt(it,ot,ht[y],at))}else for(H=0;H<L;H++)for(Y=w[H],Z=j(H),y=0;y<I;y++)W=kt(Y[y],1),h(rt,nt=4*(Z*I+N(y)),W);var dt=V.createImageData(I,D);try{dt.data.set(rt)}catch(t){var gt=dt.data,vt=gt.length;for(H=0;H<vt;H++)gt[H]=rt[H]}V.putImageData(dt,0,0)}else{var mt=_.xgap,yt=_.ygap,xt=Math.floor(mt/2),bt=Math.floor(yt/2);for(H=0;H<L;H++)if(Y=w[H],Z.reverse(),Z[K]=j(H+1),Z[0]!==Z[1]&&void 0!==Z[0]&&void 0!==Z[1])for(q=[G=N(0),G],y=0;y<C;y++)q.reverse(),q[J]=N(y+1),q[0]!==q[1]&&void 0!==q[0]&&void 0!==q[1]&&(W=kt(Y[y],(q[1]-q[0])*(Z[1]-Z[0])),V.fillStyle=\"rgba(\"+W.join(\",\")+\")\",V.fillRect(q[0]+xt,Z[0]+bt,q[1]-q[0]-mt,Z[1]-Z[0]-yt))}$=Math.round($/Q),tt=Math.round(tt/Q),et=Math.round(et/Q);var _t=a(\"rgb(\"+$+\",\"+tt+\",\"+et+\")\");t._hmpixcount=(t._hmpixcount||0)+Q,t._hmlumcount=(t._hmlumcount||0)+Q*_t.getLuminance();var wt=x.selectAll(\"image\").data(e);wt.enter().append(\"svg:image\").attr({xmlns:l.svg,preserveAspectRatio:\"none\"}),wt.attr({height:D,width:I,x:r,y:v,\"xlink:href\":B.toDataURL(\"image/png\")})}function kt(t,e){if(void 0!==t){var r=U(t);return r[0]=Math.round(r[0]),r[1]=Math.round(r[1]),r[2]=Math.round(r[2]),Q+=e,$+=r[0]*e,tt+=r[1]*e,et+=r[2]*e,r}return[0,0,0,0]}function Tt(t,e,r,n){var a=t[r.bin0];if(void 0===a)return kt(void 0,1);var i,o=t[r.bin1],s=e[r.bin0],l=e[r.bin1],c=o-a||0,u=s-a||0;return i=void 0===o?void 0===l?0:void 0===s?2*(l-a):2*(2*l-s-a)/3:void 0===l?void 0===s?0:2*(2*a-o-s)/3:void 0===s?2*(2*l-o-a)/3:l+a-o-s,kt(a+r.frac*c+n.frac*(u+r.frac*i))}})}},{\"../../components/colorscale\":604,\"../../constants/xmlns_namespaces\":694,\"../../lib\":717,\"../../registry\":846,d3:165,tinycolor2:536}],1012:[function(t,e,r){\"use strict\";var n=t(\"d3\");e.exports=function(t){n.select(t).selectAll(\".hm image\").style(\"opacity\",function(t){return t.trace.opacity})}},{d3:165}],1013:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){!1===r(\"zsmooth\")&&(r(\"xgap\"),r(\"ygap\")),r(\"zhoverformat\")}},{}],1014:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib\"),i=t(\"../../registry\");function o(t,e){var r=e(t);return\"scaled\"===(r?e(t+\"type\",\"array\"):\"scaled\")&&(e(t+\"0\"),e(\"d\"+t)),r}e.exports=function(t,e,r,s,l,c){var u,h,f=r(\"z\");if(l=l||\"x\",c=c||\"y\",void 0===f||!f.length)return 0;if(a.isArray1D(t.z)){u=r(l),h=r(c);var p=a.minRowLength(u),d=a.minRowLength(h);if(0===p||0===d)return 0;e._length=Math.min(p,d,f.length)}else{if(u=o(l,r),h=o(c,r),!function(t){for(var e,r=!0,i=!1,o=!1,s=0;s<t.length;s++){if(e=t[s],!a.isArrayOrTypedArray(e)){r=!1;break}e.length>0&&(i=!0);for(var l=0;l<e.length;l++)if(n(e[l])){o=!0;break}}return r&&i&&o}(f))return 0;r(\"transpose\"),e._length=null}return i.getComponentMethod(\"calendars\",\"handleTraceDefaults\")(t,e,[l,c],s),!0}},{\"../../lib\":717,\"../../registry\":846,\"fast-isnumeric\":228}],1015:[function(t,e,r){\"use strict\";for(var n=t(\"../heatmap/attributes\"),a=t(\"../../components/colorscale/attributes\"),i=t(\"../../lib/extend\").extendFlat,o=t(\"../../plot_api/edit_types\").overrideAll,s=[\"z\",\"x\",\"x0\",\"dx\",\"y\",\"y0\",\"dy\",\"text\",\"transpose\",\"xtype\",\"ytype\"],l={},c=0;c<s.length;c++){var u=s[c];l[u]=n[u]}i(l,a(\"\",{cLetter:\"z\",autoColorDflt:!1})),e.exports=o(l,\"calc\",\"nested\")},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plot_api/edit_types\":748,\"../heatmap/attributes\":1e3}],1016:[function(t,e,r){\"use strict\";var n=t(\"gl-heatmap2d\"),a=t(\"../../plots/cartesian/axes\"),i=t(\"../../lib/str2rgbarray\");function o(t,e){this.scene=t,this.uid=e,this.type=\"heatmapgl\",this.name=\"\",this.hoverinfo=\"all\",this.xData=[],this.yData=[],this.zData=[],this.textLabels=[],this.idToIndex=[],this.bounds=[0,0,0,0],this.options={z:[],x:[],y:[],shape:[0,0],colorLevels:[0],colorValues:[0,0,0,1]},this.heatmap=n(t.glplot,this.options),this.heatmap._trace=this}var s=o.prototype;s.handlePick=function(t){var e=this.options,r=e.shape,n=t.pointId,a=n%r[0],i=Math.floor(n/r[0]),o=n;return{trace:this,dataCoord:t.dataCoord,traceCoord:[e.x[a],e.y[i],e.z[o]],textLabel:this.textLabels[n],name:this.name,pointIndex:[i,a],hoverinfo:this.hoverinfo}},s.update=function(t,e){var r=e[0];this.index=t.index,this.name=t.name,this.hoverinfo=t.hoverinfo;var n=r.z;this.options.z=[].concat.apply([],n);var o=n[0].length,s=n.length;this.options.shape=[o,s],this.options.x=r.x,this.options.y=r.y;var l=function(t){for(var e=t.colorscale,r=t.zmin,n=t.zmax,a=e.length,o=new Array(a),s=new Array(4*a),l=0;l<a;l++){var c=e[l],u=i(c[1]);o[l]=r+c[0]*(n-r);for(var h=0;h<4;h++)s[4*l+h]=u[h]}return{colorLevels:o,colorValues:s}}(t);this.options.colorLevels=l.colorLevels,this.options.colorValues=l.colorValues,this.textLabels=[].concat.apply([],t.text),this.heatmap.update(this.options);var c=this.scene.xaxis,u=this.scene.yaxis;t._extremes[c._id]=a.findExtremes(c,r.x),t._extremes[u._id]=a.findExtremes(u,r.y)},s.dispose=function(){this.heatmap.dispose()},e.exports=function(t,e,r){var n=new o(t,e.uid);return n.update(e,r),n}},{\"../../lib/str2rgbarray\":740,\"../../plots/cartesian/axes\":765,\"gl-heatmap2d\":254}],1017:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"../heatmap/defaults\"),colorbar:t(\"../heatmap/colorbar\"),calc:t(\"../heatmap/calc\"),plot:t(\"./convert\"),moduleType:\"trace\",name:\"heatmapgl\",basePlotModule:t(\"../../plots/gl2d\"),categories:[\"gl\",\"gl2d\",\"2dMap\"],meta:{}}},{\"../../plots/gl2d\":803,\"../heatmap/calc\":1001,\"../heatmap/colorbar\":1003,\"../heatmap/defaults\":1005,\"./attributes\":1015,\"./convert\":1016}],1018:[function(t,e,r){\"use strict\";var n=t(\"../bar/attributes\"),a=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"./bin_attributes\"),o=t(\"./constants\"),s=t(\"../../lib/extend\").extendFlat;e.exports={x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},text:s({},n.text,{}),hovertext:s({},n.hovertext,{}),orientation:n.orientation,histfunc:{valType:\"enumerated\",values:[\"count\",\"sum\",\"avg\",\"min\",\"max\"],dflt:\"count\",editType:\"calc\"},histnorm:{valType:\"enumerated\",values:[\"\",\"percent\",\"probability\",\"density\",\"probability density\"],dflt:\"\",editType:\"calc\"},cumulative:{enabled:{valType:\"boolean\",dflt:!1,editType:\"calc\"},direction:{valType:\"enumerated\",values:[\"increasing\",\"decreasing\"],dflt:\"increasing\",editType:\"calc\"},currentbin:{valType:\"enumerated\",values:[\"include\",\"exclude\",\"half\"],dflt:\"include\",editType:\"calc\"},editType:\"calc\"},nbinsx:{valType:\"integer\",min:0,dflt:0,editType:\"calc\"},xbins:i(\"x\",!0),nbinsy:{valType:\"integer\",min:0,dflt:0,editType:\"calc\"},ybins:i(\"y\",!0),autobinx:{valType:\"boolean\",dflt:null,editType:\"calc\"},autobiny:{valType:\"boolean\",dflt:null,editType:\"calc\"},bingroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},hovertemplate:a({},{keys:o.eventDataKeys}),marker:n.marker,offsetgroup:n.offsetgroup,alignmentgroup:n.alignmentgroup,selected:n.selected,unselected:n.unselected,_deprecated:{bardir:n._deprecated.bardir}}},{\"../../lib/extend\":708,\"../../plots/template_attributes\":841,\"../bar/attributes\":856,\"./bin_attributes\":1020,\"./constants\":1024}],1019:[function(t,e,r){\"use strict\";e.exports=function(t,e){for(var r=t.length,n=0,a=0;a<r;a++)e[a]?(t[a]/=e[a],n+=t[a]):t[a]=null;return n}},{}],1020:[function(t,e,r){\"use strict\";e.exports=function(t,e){return{start:{valType:\"any\",editType:\"calc\"},end:{valType:\"any\",editType:\"calc\"},size:{valType:\"any\",editType:\"calc\"},editType:\"calc\"}}},{}],1021:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\");e.exports={count:function(t,e,r){return r[t]++,1},sum:function(t,e,r,a){var i=a[e];return n(i)?(i=Number(i),r[t]+=i,i):0},avg:function(t,e,r,a,i){var o=a[e];return n(o)&&(o=Number(o),r[t]+=o,i[t]++),0},min:function(t,e,r,a){var i=a[e];if(n(i)){if(i=Number(i),!n(r[t]))return r[t]=i,i;if(r[t]>i){var o=i-r[t];return r[t]=i,o}}return 0},max:function(t,e,r,a){var i=a[e];if(n(i)){if(i=Number(i),!n(r[t]))return r[t]=i,i;if(r[t]<i){var o=i-r[t];return r[t]=i,o}}return 0}}},{\"fast-isnumeric\":228}],1022:[function(t,e,r){\"use strict\";var n=t(\"../../constants/numerical\"),a=n.ONEAVGYEAR,i=n.ONEAVGMONTH,o=n.ONEDAY,s=n.ONEHOUR,l=n.ONEMIN,c=n.ONESEC,u=t(\"../../plots/cartesian/axes\").tickIncrement;function h(t,e,r,n){if(t*e<=0)return 1/0;for(var a=Math.abs(e-t),i=\"date\"===r.type,o=f(a,i),s=0;s<10;s++){var l=f(80*o,i);if(o===l)break;if(!p(l,t,e,i,r,n))break;o=l}return o}function f(t,e){return e&&t>c?t>o?t>1.1*a?a:t>1.1*i?i:o:t>s?s:t>l?l:c:Math.pow(10,Math.floor(Math.log(t)/Math.LN10))}function p(t,e,r,n,i,s){if(n&&t>o){var l=d(e,i,s),c=d(r,i,s),u=t===a?0:1;return l[u]!==c[u]}return Math.floor(r/t)-Math.floor(e/t)>.1}function d(t,e,r){var n=e.c2d(t,a,r).split(\"-\");return\"\"===n[0]&&(n.unshift(),n[0]=\"-\"+n[0]),n}e.exports=function(t,e,r,n,i){var s,l,c=-1.1*e,f=-.1*e,p=t-f,d=r[0],g=r[1],v=Math.min(h(d+f,d+p,n,i),h(g+f,g+p,n,i)),m=Math.min(h(d+c,d+f,n,i),h(g+c,g+f,n,i));if(v>m&&m<Math.abs(g-d)/4e3?(s=v,l=!1):(s=Math.min(v,m),l=!0),\"date\"===n.type&&s>o){var y=s===a?1:6,x=s===a?\"M12\":\"M1\";return function(e,r){var o=n.c2d(e,a,i),s=o.indexOf(\"-\",y);s>0&&(o=o.substr(0,s));var c=n.d2c(o,0,i);if(c<e){var h=u(c,x,!1,i);(c+h)/2<e+t&&(c=h)}return r&&l?u(c,x,!0,i):c}}return function(e,r){var n=s*Math.round(e/s);return n+s/10<e&&n+.9*s<e+t&&(n+=s),r&&l&&(n-=s),n}}},{\"../../constants/numerical\":693,\"../../plots/cartesian/axes\":765}],1023:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib\"),i=t(\"../../registry\"),o=t(\"../../plots/cartesian/axes\"),s=t(\"../bar/arrays_to_calcdata\"),l=t(\"./bin_functions\"),c=t(\"./norm_functions\"),u=t(\"./average\"),h=t(\"./bin_label_vals\");function f(t,e,r,s,l){var c,u,h,p,d,g,v,m=s+\"bins\",y=t._fullLayout,x=e[\"_\"+s+\"bingroup\"],b=y._histogramBinOpts[x],_=\"overlay\"===y.barmode,w=function(t){return r.r2c(t,0,p)},k=function(t){return r.c2r(t,0,p)},T=\"date\"===r.type?function(t){return t||0===t?a.cleanDate(t,null,p):null}:function(t){return n(t)?Number(t):null};function M(t,e,r){e[t+\"Found\"]?(e[t]=T(e[t]),null===e[t]&&(e[t]=r[t])):(g[t]=e[t]=r[t],a.nestedProperty(u[0],m+\".\"+t).set(r[t]))}if(e[\"_\"+s+\"autoBinFinished\"])delete e[\"_\"+s+\"autoBinFinished\"];else{u=b.traces;var A=[],S=!0,E=!1,L=!1;for(c=0;c<u.length;c++)if((h=u[c]).visible){var C=b.dirs[c];d=h[\"_\"+C+\"pos0\"]=r.makeCalcdata(h,C),A=a.concat(A,d),delete h[\"_\"+s+\"autoBinFinished\"],!0===e.visible&&(S?S=!1:(delete h._autoBin,h[\"_\"+s+\"autoBinFinished\"]=1),i.traceIs(h,\"2dMap\")&&(E=!0),\"histogram2dcontour\"===h.type&&(L=!0))}p=u[0][s+\"calendar\"];var P=o.autoBin(A,r,b.nbins,E,p,b.sizeFound&&b.size),O=u[0]._autoBin={};if(g=O[b.dirs[0]]={},L&&(b.size||(P.start=k(o.tickIncrement(w(P.start),P.size,!0,p))),void 0===b.end&&(P.end=k(o.tickIncrement(w(P.end),P.size,!1,p)))),_&&!i.traceIs(e,\"2dMap\")&&0===P._dataSpan&&\"category\"!==r.type&&\"multicategory\"!==r.type){if(l)return[P,d,!0];P=function(t,e,r,n,i){var o,s,l,c=t._fullLayout,u=function(t,e){for(var r=e.xaxis,n=e.yaxis,a=e.orientation,i=[],o=t._fullData,s=0;s<o.length;s++){var l=o[s];\"histogram\"===l.type&&!0===l.visible&&l.orientation===a&&l.xaxis===r&&l.yaxis===n&&i.push(l)}return i}(t,e),h=!1,p=1/0,d=[e];for(o=0;o<u.length;o++)if((s=u[o])===e)h=!0;else if(h){var g=f(t,s,r,n,!0),v=g[0],m=g[2];s[\"_\"+n+\"autoBinFinished\"]=1,s[\"_\"+n+\"pos0\"]=g[1],m?d.push(s):p=Math.min(p,v.size)}else l=c._histogramBinOpts[s[\"_\"+n+\"bingroup\"]],p=Math.min(p,l.size||s[i].size);var y=new Array(d.length);for(o=0;o<d.length;o++)for(var x=d[o][\"_\"+n+\"pos0\"],b=0;b<x.length;b++)if(void 0!==x[b]){y[o]=x[b];break}isFinite(p)||(p=a.distinctVals(y).minDiff);for(o=0;o<d.length;o++){var _=(s=d[o])[n+\"calendar\"],w={start:r.c2r(y[o]-p/2,0,_),end:r.c2r(y[o]+p/2,0,_),size:p};s._input[i]=s[i]=w,(l=c._histogramBinOpts[s[\"_\"+n+\"bingroup\"]])&&a.extendFlat(l,w)}return e[i]}(t,e,r,s,m)}(v=h.cumulative||{}).enabled&&\"include\"!==v.currentbin&&(\"decreasing\"===v.direction?P.start=k(o.tickIncrement(w(P.start),P.size,!0,p)):P.end=k(o.tickIncrement(w(P.end),P.size,!1,p))),b.size=P.size,b.sizeFound||(g.size=P.size,a.nestedProperty(u[0],m+\".size\").set(P.size)),M(\"start\",b,P),M(\"end\",b,P)}d=e[\"_\"+s+\"pos0\"],delete e[\"_\"+s+\"pos0\"];var z=e._input[m]||{},I=a.extendFlat({},b),D=b.start,R=r.r2l(z.start),F=void 0!==R;if((b.startFound||F)&&R!==r.r2l(D)){var B=F?R:a.aggNums(Math.min,null,d),N={type:\"category\"===r.type||\"multicategory\"===r.type?\"linear\":r.type,r2l:r.r2l,dtick:b.size,tick0:D,calendar:p,range:[B,o.tickIncrement(B,b.size,!1,p)].map(r.l2r)},j=o.tickFirst(N);j>r.r2l(B)&&(j=o.tickIncrement(j,b.size,!0,p)),I.start=r.l2r(j),F||a.nestedProperty(e,m+\".start\").set(I.start)}var V=b.end,U=r.r2l(z.end),q=void 0!==U;if((b.endFound||q)&&U!==r.r2l(V)){var H=q?U:a.aggNums(Math.max,null,d);I.end=r.l2r(H),q||a.nestedProperty(e,m+\".start\").set(I.end)}var G=\"autobin\"+s;return!1===e._input[G]&&(e._input[m]=a.extendFlat({},e[m]||{}),delete e._input[G],delete e[G]),[I,d]}e.exports={calc:function(t,e){var r,i,p,d,g=[],v=[],m=o.getFromId(t,\"h\"===e.orientation?e.yaxis:e.xaxis),y=\"h\"===e.orientation?\"y\":\"x\",x={x:\"y\",y:\"x\"}[y],b=e[y+\"calendar\"],_=e.cumulative,w=f(t,e,m,y),k=w[0],T=w[1],M=\"string\"==typeof k.size,A=[],S=M?A:k,E=[],L=[],C=[],P=0,O=e.histnorm,z=e.histfunc,I=-1!==O.indexOf(\"density\");_.enabled&&I&&(O=O.replace(/ ?density$/,\"\"),I=!1);var D,R=\"max\"===z||\"min\"===z?null:0,F=l.count,B=c[O],N=!1,j=function(t){return m.r2c(t,0,b)};for(a.isArrayOrTypedArray(e[x])&&\"count\"!==z&&(D=e[x],N=\"avg\"===z,F=l[z]),r=j(k.start),p=j(k.end)+(r-o.tickIncrement(r,k.size,!1,b))/1e6;r<p&&g.length<1e6&&(i=o.tickIncrement(r,k.size,!1,b),g.push((r+i)/2),v.push(R),C.push([]),A.push(r),I&&E.push(1/(i-r)),N&&L.push(0),!(i<=r));)r=i;A.push(r),M||\"date\"!==m.type||(S={start:j(S.start),end:j(S.end),size:S.size});var V,U=v.length,q=!0,H=1/0,G=1/0,Y={};for(r=0;r<T.length;r++){var W=T[r];(d=a.findBin(W,S))>=0&&d<U&&(P+=F(d,r,v,D,L),q&&C[d].length&&W!==T[C[d][0]]&&(q=!1),C[d].push(r),Y[r]=d,H=Math.min(H,W-A[d]),G=Math.min(G,A[d+1]-W))}q||(V=h(H,G,A,m,b)),N&&(P=u(v,L)),B&&B(v,P,E),_.enabled&&function(t,e,r){var n,a,i;function o(e){i=t[e],t[e]/=2}function s(e){a=t[e],t[e]=i+a/2,i+=a}if(\"half\"===r)if(\"increasing\"===e)for(o(0),n=1;n<t.length;n++)s(n);else for(o(t.length-1),n=t.length-2;n>=0;n--)s(n);else if(\"increasing\"===e){for(n=1;n<t.length;n++)t[n]+=t[n-1];\"exclude\"===r&&(t.unshift(0),t.pop())}else{for(n=t.length-2;n>=0;n--)t[n]+=t[n+1];\"exclude\"===r&&(t.push(0),t.shift())}}(v,_.direction,_.currentbin);var X=Math.min(g.length,v.length),Z=[],J=0,K=X-1;for(r=0;r<X;r++)if(v[r]){J=r;break}for(r=X-1;r>=J;r--)if(v[r]){K=r;break}for(r=J;r<=K;r++)if(n(g[r])&&n(v[r])){var Q={p:g[r],s:v[r],b:0};_.enabled||(Q.pts=C[r],q?Q.ph0=Q.ph1=C[r].length?T[C[r][0]]:g[r]:(Q.ph0=V(A[r]),Q.ph1=V(A[r+1],!0))),Z.push(Q)}return 1===Z.length&&(Z[0].width1=o.tickIncrement(Z[0].p,k.size,!1,b)-Z[0].p),s(Z,e),a.isArrayOrTypedArray(e.selectedpoints)&&a.tagSelected(Z,e,Y),Z},calcAllAutoBins:f}},{\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"../../registry\":846,\"../bar/arrays_to_calcdata\":855,\"./average\":1019,\"./bin_functions\":1021,\"./bin_label_vals\":1022,\"./norm_functions\":1030,\"fast-isnumeric\":228}],1024:[function(t,e,r){\"use strict\";e.exports={eventDataKeys:[\"binNumber\"]}},{}],1025:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/cartesian/axis_ids\"),i=t(\"../../registry\").traceIs,o=t(\"../bar/defaults\").handleGroupingDefaults,s=n.nestedProperty,l=a.getAxisGroup,c=[{aStr:{x:\"xbins.start\",y:\"ybins.start\"},name:\"start\"},{aStr:{x:\"xbins.end\",y:\"ybins.end\"},name:\"end\"},{aStr:{x:\"xbins.size\",y:\"ybins.size\"},name:\"size\"},{aStr:{x:\"nbinsx\",y:\"nbinsy\"},name:\"nbins\"}],u=[\"x\",\"y\"];e.exports=function(t,e){var r,h,f,p,d,g,v,m=e._histogramBinOpts={},y=[],x={},b=[];function _(t,e){return n.coerce(r._input,r,r._module.attributes,t,e)}function w(t){return\"v\"===t.orientation?\"x\":\"y\"}function k(t,r,i){var o=t.uid+\"__\"+i;r||(r=o);var s=function(t,r){return a.getFromTrace({_fullLayout:e},t,r).type}(t,i),l=t[i+\"calendar\"]||\"\",c=m[r],u=!0;c&&(s===c.axType&&l===c.calendar?(u=!1,c.traces.push(t),c.dirs.push(i)):(r=o,s!==c.axType&&n.warn([\"Attempted to group the bins of trace\",t.index,\"set on a\",\"type:\"+s,\"axis\",\"with bins on\",\"type:\"+c.axType,\"axis.\"].join(\" \")),l!==c.calendar&&n.warn([\"Attempted to group the bins of trace\",t.index,\"set with a\",l,\"calendar\",\"with bins\",c.calendar?\"on a \"+c.calendar+\" calendar\":\"w/o a set calendar\"].join(\" \")))),u&&(m[r]={traces:[t],dirs:[i],axType:s,calendar:t[i+\"calendar\"]||\"\"}),t[\"_\"+i+\"bingroup\"]=r}for(d=0;d<t.length;d++)r=t[d],i(r,\"histogram\")&&(y.push(r),delete r._xautoBinFinished,delete r._yautoBinFinished,i(r,\"2dMap\")||o(r._input,r,e,_));var T=e._alignmentOpts||{};for(d=0;d<y.length;d++){if(r=y[d],f=\"\",!i(r,\"2dMap\")){if(p=w(r),\"group\"===e.barmode&&r.alignmentgroup){var M=r[p+\"axis\"],A=l(e,M)+r.orientation;(T[A]||{})[r.alignmentgroup]&&(f=A)}f||\"overlay\"===e.barmode||(f=l(e,r.xaxis)+l(e,r.yaxis)+w(r))}f?(x[f]||(x[f]=[]),x[f].push(r)):b.push(r)}for(f in x)if(1!==(h=x[f]).length){var S=!1;for(d=0;d<h.length;d++){r=h[d],S=_(\"bingroup\");break}for(f=S||f,d=0;d<h.length;d++){var E=(r=h[d])._input.bingroup;E&&E!==f&&n.warn([\"Trace\",r.index,\"must match\",\"within bingroup\",f+\".\",\"Ignoring its bingroup:\",E,\"setting.\"].join(\" \")),r.bingroup=f,k(r,f,w(r))}}else b.push(h[0]);for(d=0;d<b.length;d++){r=b[d];var L=_(\"bingroup\");if(i(r,\"2dMap\"))for(v=0;v<2;v++){var C=_((p=u[v])+\"bingroup\",L?L+\"__\"+p:null);k(r,C,p)}else k(r,L,w(r))}for(f in m){var P=m[f];for(h=P.traces,g=0;g<c.length;g++){var O,z,I=c[g],D=I.name;if(\"nbins\"!==D||!P.sizeFound){for(d=0;d<h.length;d++){if(r=h[d],p=P.dirs[d],O=I.aStr[p],void 0!==s(r._input,O).get()){P[D]=_(O),P[D+\"Found\"]=!0;break}(z=(r._autoBin||{})[p]||{})[D]&&s(r,O).set(z[D])}if(\"start\"===D||\"end\"===D)for(;d<h.length;d++)(r=h[d])[\"_\"+p+\"bingroup\"]&&_(O,(z=(r._autoBin||{})[p]||{})[D]);\"nbins\"!==D||P.sizeFound||P.nbinsFound||(r=h[0],P[D]=_(O))}}}}},{\"../../lib\":717,\"../../plots/cartesian/axis_ids\":768,\"../../registry\":846,\"../bar/defaults\":860}],1026:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../lib\"),i=t(\"../../components/color\"),o=t(\"../bar/style_defaults\"),s=t(\"./attributes\");e.exports=function(t,e,r,l){function c(r,n){return a.coerce(t,e,s,r,n)}var u=c(\"x\"),h=c(\"y\");c(\"cumulative.enabled\")&&(c(\"cumulative.direction\"),c(\"cumulative.currentbin\")),c(\"text\"),c(\"hovertext\"),c(\"hovertemplate\");var f=c(\"orientation\",h&&!u?\"h\":\"v\"),p=\"v\"===f?\"x\":\"y\",d=\"v\"===f?\"y\":\"x\",g=u&&h?Math.min(a.minRowLength(u)&&a.minRowLength(h)):a.minRowLength(e[p]||[]);if(g){e._length=g,n.getComponentMethod(\"calendars\",\"handleTraceDefaults\")(t,e,[\"x\",\"y\"],l),e[d]&&c(\"histfunc\"),c(\"histnorm\"),c(\"autobin\"+p),o(t,e,c,r,l),a.coerceSelectionMarkerOpacity(e,c);var v=(e.marker.line||{}).color,m=n.getComponentMethod(\"errorbars\",\"supplyDefaults\");m(t,e,v||i.defaultLine,{axis:\"y\"}),m(t,e,v||i.defaultLine,{axis:\"x\",inherit:\"y\"})}else e.visible=!1}},{\"../../components/color\":592,\"../../lib\":717,\"../../registry\":846,\"../bar/style_defaults\":871,\"./attributes\":1018}],1027:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,a){if(t.x=\"xVal\"in e?e.xVal:e.x,t.y=\"yVal\"in e?e.yVal:e.y,\"zLabelVal\"in e&&(t.z=e.zLabelVal),e.xa&&(t.xaxis=e.xa),e.ya&&(t.yaxis=e.ya),!(r.cumulative||{}).enabled){var i,o=Array.isArray(a)?n[0].pts[a[0]][a[1]]:n[a].pts;if(t.pointNumbers=o,t.binNumber=t.pointNumber,delete t.pointNumber,delete t.pointIndex,r._indexToPoints){i=[];for(var s=0;s<o.length;s++)i=i.concat(r._indexToPoints[o[s]])}else i=o;t.pointIndices=i}return t}},{}],1028:[function(t,e,r){\"use strict\";var n=t(\"../bar/hover\").hoverPoints,a=t(\"../../plots/cartesian/axes\").hoverLabelText;e.exports=function(t,e,r,i){var o=n(t,e,r,i);if(o){var s=(t=o[0]).cd[t.index],l=t.cd[0].trace;if(!l.cumulative.enabled){var c=\"h\"===l.orientation?\"y\":\"x\";t[c+\"Label\"]=a(t[c+\"a\"],s.ph0,s.ph1)}return l.hovermplate&&(t.hovertemplate=l.hovertemplate),o}}},{\"../../plots/cartesian/axes\":765,\"../bar/hover\":863}],1029:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),layoutAttributes:t(\"../bar/layout_attributes\"),supplyDefaults:t(\"./defaults\"),crossTraceDefaults:t(\"./cross_trace_defaults\"),supplyLayoutDefaults:t(\"../bar/layout_defaults\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"../bar/cross_trace_calc\").crossTraceCalc,plot:t(\"../bar/plot\").plot,layerName:\"barlayer\",style:t(\"../bar/style\").style,styleOnSelect:t(\"../bar/style\").styleOnSelect,colorbar:t(\"../scatter/marker_colorbar\"),hoverPoints:t(\"./hover\"),selectPoints:t(\"../bar/select\"),eventData:t(\"./event_data\"),moduleType:\"trace\",name:\"histogram\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"bar-like\",\"cartesian\",\"svg\",\"bar\",\"histogram\",\"oriented\",\"errorBarsOK\",\"showLegend\"],meta:{}}},{\"../../plots/cartesian\":776,\"../bar/cross_trace_calc\":859,\"../bar/layout_attributes\":865,\"../bar/layout_defaults\":866,\"../bar/plot\":867,\"../bar/select\":868,\"../bar/style\":870,\"../scatter/marker_colorbar\":1138,\"./attributes\":1018,\"./calc\":1023,\"./cross_trace_defaults\":1025,\"./defaults\":1026,\"./event_data\":1027,\"./hover\":1028}],1030:[function(t,e,r){\"use strict\";e.exports={percent:function(t,e){for(var r=t.length,n=100/e,a=0;a<r;a++)t[a]*=n},probability:function(t,e){for(var r=t.length,n=0;n<r;n++)t[n]/=e},density:function(t,e,r,n){var a=t.length;n=n||1;for(var i=0;i<a;i++)t[i]*=r[i]*n},\"probability density\":function(t,e,r,n){var a=t.length;n&&(e/=n);for(var i=0;i<a;i++)t[i]*=r[i]/e}}},{}],1031:[function(t,e,r){\"use strict\";var n=t(\"../histogram/attributes\"),a=t(\"../histogram/bin_attributes\"),i=t(\"../heatmap/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../plots/template_attributes\").hovertemplateAttrs,l=t(\"../../components/colorscale/attributes\"),c=t(\"../../lib/extend\").extendFlat;e.exports=c({x:n.x,y:n.y,z:{valType:\"data_array\",editType:\"calc\"},marker:{color:{valType:\"data_array\",editType:\"calc\"},editType:\"calc\"},histnorm:n.histnorm,histfunc:n.histfunc,nbinsx:n.nbinsx,xbins:a(\"x\"),nbinsy:n.nbinsy,ybins:a(\"y\"),autobinx:n.autobinx,autobiny:n.autobiny,bingroup:c({},n.bingroup,{}),xbingroup:c({},n.bingroup,{}),ybingroup:c({},n.bingroup,{}),xgap:i.xgap,ygap:i.ygap,zsmooth:i.zsmooth,zhoverformat:i.zhoverformat,hovertemplate:s({},{keys:\"z\"}),showlegend:c({},o.showlegend,{dflt:!1})},l(\"\",{cLetter:\"z\",autoColorDflt:!1}))},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"../heatmap/attributes\":1e3,\"../histogram/attributes\":1018,\"../histogram/bin_attributes\":1020}],1032:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/cartesian/axes\"),i=t(\"../histogram/bin_functions\"),o=t(\"../histogram/norm_functions\"),s=t(\"../histogram/average\"),l=t(\"../histogram/bin_label_vals\"),c=t(\"../histogram/calc\").calcAllAutoBins;function u(t,e,r,n){var a,i=new Array(t);if(n)for(a=0;a<t;a++)i[a]=1/(e[a+1]-e[a]);else{var o=1/r;for(a=0;a<t;a++)i[a]=o}return i}function h(t,e){return{start:t(e.start),end:t(e.end),size:e.size}}function f(t,e,r,n,a,i){var o,s=t.length-1,c=new Array(s),u=l(r,n,t,a,i);for(o=0;o<s;o++){var h=(e||[])[o];c[o]=void 0===h?[u(t[o]),u(t[o+1],!0)]:[h,h]}return c}e.exports=function(t,e){var r,l,p,d,g=a.getFromId(t,e.xaxis),v=a.getFromId(t,e.yaxis),m=e.xcalendar,y=e.ycalendar,x=function(t){return g.r2c(t,0,m)},b=function(t){return v.r2c(t,0,y)},_=c(t,e,g,\"x\"),w=_[0],k=_[1],T=c(t,e,v,\"y\"),M=T[0],A=T[1],S=e._length;k.length>S&&k.splice(S,k.length-S),A.length>S&&A.splice(S,A.length-S);var E=[],L=[],C=[],P=\"string\"==typeof w.size,O=\"string\"==typeof M.size,z=[],I=[],D=P?z:w,R=O?I:M,F=0,B=[],N=[],j=e.histnorm,V=e.histfunc,U=-1!==j.indexOf(\"density\"),q=\"max\"===V||\"min\"===V?null:0,H=i.count,G=o[j],Y=!1,W=[],X=[],Z=\"z\"in e?e.z:\"marker\"in e&&Array.isArray(e.marker.color)?e.marker.color:\"\";Z&&\"count\"!==V&&(Y=\"avg\"===V,H=i[V]);var J=w.size,K=x(w.start),Q=x(w.end)+(K-a.tickIncrement(K,J,!1,m))/1e6;for(r=K;r<Q;r=a.tickIncrement(r,J,!1,m))L.push(q),z.push(r),Y&&C.push(0);z.push(r);var $,tt=L.length,et=(r-K)/tt,rt=($=K+et/2,g.c2r($,0,m)),nt=M.size,at=b(M.start),it=b(M.end)+(at-a.tickIncrement(at,nt,!1,y))/1e6;for(r=at;r<it;r=a.tickIncrement(r,nt,!1,y)){E.push(L.slice()),I.push(r);var ot=new Array(tt);for(l=0;l<tt;l++)ot[l]=[];N.push(ot),Y&&B.push(C.slice())}I.push(r);var st=E.length,lt=(r-at)/st,ct=function(t){return v.c2r(t,0,y)}(at+lt/2);U&&(W=u(L.length,D,et,P),X=u(E.length,R,lt,O)),P||\"date\"!==g.type||(D=h(x,D)),O||\"date\"!==v.type||(R=h(b,R));var ut=!0,ht=!0,ft=new Array(tt),pt=new Array(st),dt=1/0,gt=1/0,vt=1/0,mt=1/0;for(r=0;r<S;r++){var yt=k[r],xt=A[r];p=n.findBin(yt,D),d=n.findBin(xt,R),p>=0&&p<tt&&d>=0&&d<st&&(F+=H(p,r,E[d],Z,B[d]),N[d][p].push(r),ut&&(void 0===ft[p]?ft[p]=yt:ft[p]!==yt&&(ut=!1)),ht&&(void 0===pt[d]?pt[d]=xt:pt[d]!==xt&&(ht=!1)),dt=Math.min(dt,yt-z[p]),gt=Math.min(gt,z[p+1]-yt),vt=Math.min(vt,xt-I[d]),mt=Math.min(mt,I[d+1]-xt))}if(Y)for(d=0;d<st;d++)F+=s(E[d],B[d]);if(G)for(d=0;d<st;d++)G(E[d],F,W,X[d]);return{x:k,xRanges:f(z,ut&&ft,dt,gt,g,m),x0:rt,dx:et,y:A,yRanges:f(I,ht&&pt,vt,mt,v,y),y0:ct,dy:lt,z:E,pts:N}}},{\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"../histogram/average\":1019,\"../histogram/bin_functions\":1021,\"../histogram/bin_label_vals\":1022,\"../histogram/calc\":1023,\"../histogram/norm_functions\":1030}],1033:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./sample_defaults\"),i=t(\"../heatmap/style_defaults\"),o=t(\"../../components/colorscale/defaults\"),s=t(\"./attributes\");e.exports=function(t,e,r,l){function c(r,a){return n.coerce(t,e,s,r,a)}a(t,e,c,l),!1!==e.visible&&(i(t,e,c,l),o(t,e,l,c,{prefix:\"\",cLetter:\"z\"}),c(\"hovertemplate\"))}},{\"../../components/colorscale/defaults\":602,\"../../lib\":717,\"../heatmap/style_defaults\":1013,\"./attributes\":1031,\"./sample_defaults\":1036}],1034:[function(t,e,r){\"use strict\";var n=t(\"../heatmap/hover\"),a=t(\"../../plots/cartesian/axes\").hoverLabelText;e.exports=function(t,e,r,i,o,s){var l=n(t,e,r,i,o,s);if(l){var c=(t=l[0]).index,u=c[0],h=c[1],f=t.cd[0],p=f.xRanges[h],d=f.yRanges[u];return t.xLabel=a(t.xa,p[0],p[1]),t.yLabel=a(t.ya,d[0],d[1]),l}}},{\"../../plots/cartesian/axes\":765,\"../heatmap/hover\":1007}],1035:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),crossTraceDefaults:t(\"../histogram/cross_trace_defaults\"),calc:t(\"../heatmap/calc\"),plot:t(\"../heatmap/plot\"),layerName:\"heatmaplayer\",colorbar:t(\"../heatmap/colorbar\"),style:t(\"../heatmap/style\"),hoverPoints:t(\"./hover\"),eventData:t(\"../histogram/event_data\"),moduleType:\"trace\",name:\"histogram2d\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"cartesian\",\"svg\",\"2dMap\",\"histogram\",\"showLegend\"],meta:{}}},{\"../../plots/cartesian\":776,\"../heatmap/calc\":1001,\"../heatmap/colorbar\":1003,\"../heatmap/plot\":1011,\"../heatmap/style\":1012,\"../histogram/cross_trace_defaults\":1025,\"../histogram/event_data\":1027,\"./attributes\":1031,\"./defaults\":1033,\"./hover\":1034}],1036:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../lib\");e.exports=function(t,e,r,i){var o=r(\"x\"),s=r(\"y\"),l=a.minRowLength(o),c=a.minRowLength(s);l&&c?(e._length=Math.min(l,c),n.getComponentMethod(\"calendars\",\"handleTraceDefaults\")(t,e,[\"x\",\"y\"],i),(r(\"z\")||r(\"marker.color\"))&&r(\"histfunc\"),r(\"histnorm\"),r(\"autobinx\"),r(\"autobiny\")):e.visible=!1}},{\"../../lib\":717,\"../../registry\":846}],1037:[function(t,e,r){\"use strict\";var n=t(\"../histogram2d/attributes\"),a=t(\"../contour/attributes\"),i=t(\"../../components/colorscale/attributes\"),o=t(\"../../lib/extend\").extendFlat;e.exports=o({x:n.x,y:n.y,z:n.z,marker:n.marker,histnorm:n.histnorm,histfunc:n.histfunc,nbinsx:n.nbinsx,xbins:n.xbins,nbinsy:n.nbinsy,ybins:n.ybins,autobinx:n.autobinx,autobiny:n.autobiny,bingroup:n.bingroup,xbingroup:n.xbingroup,ybingroup:n.ybingroup,autocontour:a.autocontour,ncontours:a.ncontours,contours:a.contours,line:{color:a.line.color,width:o({},a.line.width,{dflt:.5}),dash:a.line.dash,smoothing:a.line.smoothing,editType:\"plot\"},zhoverformat:n.zhoverformat,hovertemplate:n.hovertemplate},i(\"\",{cLetter:\"z\",editTypeOverride:\"calc\"}))},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../contour/attributes\":943,\"../histogram2d/attributes\":1031}],1038:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../histogram2d/sample_defaults\"),i=t(\"../contour/contours_defaults\"),o=t(\"../contour/style_defaults\"),s=t(\"./attributes\");e.exports=function(t,e,r,l){function c(r,a){return n.coerce(t,e,s,r,a)}a(t,e,c,l),!1!==e.visible&&(i(t,e,c,function(r){return n.coerce2(t,e,s,r)}),o(t,e,c,l),c(\"hovertemplate\"))}},{\"../../lib\":717,\"../contour/contours_defaults\":950,\"../contour/style_defaults\":964,\"../histogram2d/sample_defaults\":1036,\"./attributes\":1037}],1039:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),crossTraceDefaults:t(\"../histogram/cross_trace_defaults\"),calc:t(\"../contour/calc\"),plot:t(\"../contour/plot\").plot,layerName:\"contourlayer\",style:t(\"../contour/style\"),colorbar:t(\"../contour/colorbar\"),hoverPoints:t(\"../contour/hover\"),moduleType:\"trace\",name:\"histogram2dcontour\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"cartesian\",\"svg\",\"2dMap\",\"contour\",\"histogram\",\"showLegend\"],meta:{}}},{\"../../plots/cartesian\":776,\"../contour/calc\":944,\"../contour/colorbar\":946,\"../contour/hover\":956,\"../contour/plot\":961,\"../contour/style\":963,\"../histogram/cross_trace_defaults\":1025,\"./attributes\":1037,\"./defaults\":1038}],1040:[function(t,e,r){\"use strict\";for(var n=t(\"../../plots/attributes\"),a=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../lib/extend\").extendFlat,o=t(\"./constants\").colormodel,s=[\"rgb\",\"rgba\",\"hsl\",\"hsla\"],l=[],c=[],u=0;u<s.length;u++)l.push(\"For the `\"+s[u]+\"` colormodel, it is [\"+o[s[u]].min.join(\", \")+\"].\"),c.push(\"For the `\"+s[u]+\"` colormodel, it is [\"+o[s[u]].max.join(\", \")+\"].\");e.exports=i({z:{valType:\"data_array\",editType:\"calc\"},colormodel:{valType:\"enumerated\",values:s,dflt:\"rgb\",editType:\"calc\"},zmin:{valType:\"info_array\",items:[{valType:\"number\",editType:\"calc\"},{valType:\"number\",editType:\"calc\"},{valType:\"number\",editType:\"calc\"},{valType:\"number\",editType:\"calc\"}],editType:\"calc\"},zmax:{valType:\"info_array\",items:[{valType:\"number\",editType:\"calc\"},{valType:\"number\",editType:\"calc\"},{valType:\"number\",editType:\"calc\"},{valType:\"number\",editType:\"calc\"}],editType:\"calc\"},x0:{valType:\"any\",dflt:0,editType:\"calc+clearAxisTypes\"},y0:{valType:\"any\",dflt:0,editType:\"calc+clearAxisTypes\"},dx:{valType:\"number\",dflt:1,editType:\"calc\"},dy:{valType:\"number\",dflt:1,editType:\"calc\"},text:{valType:\"data_array\",editType:\"plot\"},hovertext:{valType:\"data_array\",editType:\"plot\"},hoverinfo:i({},n.hoverinfo,{flags:[\"x\",\"y\",\"z\",\"color\",\"name\",\"text\"],dflt:\"x+y+z+text+name\"}),hovertemplate:a({},{keys:[\"z\",\"color\",\"colormodel\"]}),transforms:void 0})},{\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"./constants\":1042}],1041:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./constants\"),i=t(\"fast-isnumeric\"),o=t(\"../../plots/cartesian/axes\"),s=t(\"../../lib\").maxRowLength;function l(t,e,r,a){return function(i){return n.constrain((i-t)*e,r,a)}}function c(t,e){return function(r){return n.constrain(r,t,e)}}e.exports=function(t,e){var r,n=o.getFromId(t,e.xaxis||\"x\"),u=o.getFromId(t,e.yaxis||\"y\"),h=n.d2c(e.x0)-e.dx/2,f=u.d2c(e.y0)-e.dy/2,p=e.z.length,d=s(e.z),g=[h,h+d*e.dx],v=[f,f+p*e.dy];if(n&&\"log\"===n.type)for(r=0;r<d;r++)g.push(h+r*e.dx);if(u&&\"log\"===u.type)for(r=0;r<p;r++)v.push(f+r*e.dy);return e._extremes[n._id]=o.findExtremes(n,g),e._extremes[u._id]=o.findExtremes(u,v),e._scaler=function(t){var e=t.colormodel,r=e.length,n=a.colormodel[e];t._sArray=[];for(var o=0;o<r;o++)n.min[o]!==t.zmin[o]||n.max[o]!==t.zmax[o]?t._sArray.push(l(t.zmin[o],(n.max[o]-n.min[o])/(t.zmax[o]-t.zmin[o]),n.min[o],n.max[o])):t._sArray.push(c(n.min[o],n.max[o]));return function(e){for(var n=e.slice(0,r),a=0;a<r;a++){var o=n[a];if(!i(o))return!1;n[a]=t._sArray[a](o)}return n}}(e),[{x0:h,y0:f,z:e.z,w:d,h:p}]}},{\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"./constants\":1042,\"fast-isnumeric\":228}],1042:[function(t,e,r){\"use strict\";e.exports={colormodel:{rgb:{min:[0,0,0],max:[255,255,255],fmt:function(t){return t.slice(0,3)},suffix:[\"\",\"\",\"\"]},rgba:{min:[0,0,0,0],max:[255,255,255,1],fmt:function(t){return t.slice(0,4)},suffix:[\"\",\"\",\"\",\"\"]},hsl:{min:[0,0,0],max:[360,100,100],fmt:function(t){var e=t.slice(0,3);return e[1]=e[1]+\"%\",e[2]=e[2]+\"%\",e},suffix:[\"\\xb0\",\"%\",\"%\"]},hsla:{min:[0,0,0,0],max:[360,100,100,1],fmt:function(t){var e=t.slice(0,4);return e[1]=e[1]+\"%\",e[2]=e[2]+\"%\",e},suffix:[\"\\xb0\",\"%\",\"%\",\"\"]}}}},{}],1043:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./attributes\"),i=t(\"./constants\");e.exports=function(t,e){function r(r,i){return n.coerce(t,e,a,r,i)}var o=r(\"z\");if(void 0!==o&&o.length&&o[0]&&o[0].length){r(\"x0\"),r(\"y0\"),r(\"dx\"),r(\"dy\");var s=r(\"colormodel\");r(\"zmin\",i.colormodel[s].min),r(\"zmax\",i.colormodel[s].max),r(\"text\"),r(\"hovertext\"),r(\"hovertemplate\"),e._length=null}else e.visible=!1}},{\"../../lib\":717,\"./attributes\":1040,\"./constants\":1042}],1044:[function(t,e,r){\"use strict\";e.exports=function(t,e){return\"xVal\"in e&&(t.x=e.xVal),\"yVal\"in e&&(t.y=e.yVal),e.xa&&(t.xaxis=e.xa),e.ya&&(t.yaxis=e.ya),t.color=e.color,t.colormodel=e.trace.colormodel,t}},{}],1045:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx\"),a=t(\"../../lib\"),i=t(\"./constants\");e.exports=function(t,e,r){var o=t.cd[0],s=o.trace,l=t.xa,c=t.ya;if(!(n.inbox(e-o.x0,e-(o.x0+o.w*s.dx),0)>0||n.inbox(r-o.y0,r-(o.y0+o.h*s.dy),0)>0)){var u=Math.floor((e-o.x0)/s.dx),h=Math.floor(Math.abs(r-o.y0)/s.dy);if(o.z[h][u]){var f,p=o.hi||s.hoverinfo;if(p){var d=p.split(\"+\");-1!==d.indexOf(\"all\")&&(d=[\"color\"]),-1!==d.indexOf(\"color\")&&(f=!0)}var g,v=s.colormodel,m=v.length,y=s._scaler(o.z[h][u]),x=i.colormodel[v].suffix,b=[];(s.hovertemplate||f)&&(b.push(\"[\"+[y[0]+x[0],y[1]+x[1],y[2]+x[2]].join(\", \")),4===m&&b.push(\", \"+y[3]+x[3]),b.push(\"]\"),b=b.join(\"\"),t.extraText=v.toUpperCase()+\": \"+b),Array.isArray(s.hovertext)&&Array.isArray(s.hovertext[h])?g=s.hovertext[h][u]:Array.isArray(s.text)&&Array.isArray(s.text[h])&&(g=s.text[h][u]);var _=c.c2p(o.y0+(h+.5)*s.dy),w=o.x0+(u+.5)*s.dx,k=o.y0+(h+.5)*s.dy,T=\"[\"+o.z[h][u].slice(0,s.colormodel.length).join(\", \")+\"]\";return[a.extendFlat(t,{index:[h,u],x0:l.c2p(o.x0+u*s.dx),x1:l.c2p(o.x0+(u+1)*s.dx),y0:_,y1:_,color:y,xVal:w,xLabelVal:w,yVal:k,yLabelVal:k,zLabelVal:T,text:g,hovertemplateLabels:{zLabel:T,colorLabel:b,\"color[0]Label\":y[0]+x[0],\"color[1]Label\":y[1]+x[1],\"color[2]Label\":y[2]+x[2],\"color[3]Label\":y[3]+x[3]}})]}}}},{\"../../components/fx\":630,\"../../lib\":717,\"./constants\":1042}],1046:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"./plot\"),style:t(\"./style\"),hoverPoints:t(\"./hover\"),eventData:t(\"./event_data\"),moduleType:\"trace\",name:\"image\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"cartesian\",\"svg\",\"2dMap\",\"noSortingByValue\"],animatable:!1,meta:{}}},{\"../../plots/cartesian\":776,\"./attributes\":1040,\"./calc\":1041,\"./defaults\":1043,\"./event_data\":1044,\"./hover\":1045,\"./plot\":1047,\"./style\":1048}],1047:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\"),i=t(\"../../constants/xmlns_namespaces\"),o=t(\"./constants\");e.exports=function(t,e,r,s){var l=e.xaxis,c=e.yaxis;a.makeTraceGroups(s,r,\"im\").each(function(t){var e,r,s,u,h,f,p=n.select(this),d=t[0],g=d.trace,v=d.z,m=d.x0,y=d.y0,x=d.w,b=d.h,_=g.dx,w=g.dy;for(f=0;void 0===e&&f<x;)e=l.c2p(m+f*_),f++;for(f=x;void 0===r&&f>0;)r=l.c2p(m+f*_),f--;for(f=0;void 0===u&&f<b;)u=c.c2p(y+f*w),f++;for(f=b;void 0===h&&f>0;)h=c.c2p(y+f*w),f--;r<e&&(s=r,r=e,e=s),h<u&&(s=u,u=h,h=s);e=Math.max(-.5*l._length,e),r=Math.min(1.5*l._length,r),u=Math.max(-.5*c._length,u),h=Math.min(1.5*c._length,h);var k=Math.round(r-e),T=Math.round(h-u);if(k<=0||T<=0){p.selectAll(\"image\").data([]).exit().remove()}else{var M=document.createElement(\"canvas\");M.width=k,M.height=T;var A,S=M.getContext(\"2d\"),E=function(t){return a.constrain(Math.round(l.c2p(m+t*_)-e),0,k)},L=function(t){return a.constrain(Math.round(c.c2p(y+t*w)-u),0,T)},C=o.colormodel[g.colormodel].fmt;for(f=0;f<d.w;f++){var P=E(f),O=E(f+1);if(O!==P&&!isNaN(O)&&!isNaN(P))for(var z=0;z<d.h;z++){var I=L(z),D=L(z+1);D===I||isNaN(D)||isNaN(I)||!v[z][f]||(A=g._scaler(v[z][f]),S.fillStyle=A?g.colormodel+\"(\"+C(A).join(\",\")+\")\":\"rgba(0,0,0,0)\",S.fillRect(P,I,O-P,D-I))}}var R=p.selectAll(\"image\").data(t);R.enter().append(\"svg:image\").attr({xmlns:i.svg,preserveAspectRatio:\"none\"}),R.attr({height:T,width:k,x:e,y:u,\"xlink:href\":M.toDataURL(\"image/png\")})}})}},{\"../../constants/xmlns_namespaces\":694,\"../../lib\":717,\"./constants\":1042,d3:165}],1048:[function(t,e,r){\"use strict\";var n=t(\"d3\");e.exports=function(t){n.select(t).selectAll(\".im image\").style(\"opacity\",function(t){return t.trace.opacity})}},{d3:165}],1049:[function(t,e,r){\"use strict\";var n=t(\"../../lib/extend\").extendFlat,a=t(\"../../lib/extend\").extendDeep,i=t(\"../../plot_api/edit_types\").overrideAll,o=t(\"../../plots/font_attributes\"),s=t(\"../../components/color/attributes\"),l=t(\"../../plots/domain\").attributes,c=t(\"../../plots/cartesian/layout_attributes\"),u=t(\"../../plot_api/plot_template\").templatedArray,h=t(\"../../constants/delta.js\"),f=(t(\"../../constants/docs\").FORMAT_LINK,o({editType:\"plot\",colorEditType:\"plot\"})),p={color:{valType:\"color\",editType:\"plot\"},line:{color:{valType:\"color\",dflt:s.defaultLine,editType:\"plot\"},width:{valType:\"number\",min:0,dflt:0,editType:\"plot\"},editType:\"calc\"},thickness:{valType:\"number\",min:0,max:1,dflt:1,editType:\"plot\"},editType:\"calc\"},d={valType:\"info_array\",items:[{valType:\"number\",editType:\"plot\"},{valType:\"number\",editType:\"plot\"}],editType:\"plot\"},g=u(\"step\",a({},p,{range:d}));e.exports={mode:{valType:\"flaglist\",editType:\"calc\",flags:[\"number\",\"delta\",\"gauge\"],dflt:\"number\"},value:{valType:\"number\",editType:\"calc\",anim:!0},align:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],editType:\"plot\"},domain:l({name:\"indicator\",trace:!0,editType:\"calc\"}),title:{text:{valType:\"string\",editType:\"plot\"},align:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],editType:\"plot\"},font:n({},f,{}),editType:\"plot\"},number:{valueformat:{valType:\"string\",dflt:\"\",editType:\"plot\"},font:n({},f,{}),prefix:{valType:\"string\",dflt:\"\",editType:\"plot\"},suffix:{valType:\"string\",dflt:\"\",editType:\"plot\"},editType:\"plot\"},delta:{reference:{valType:\"number\",editType:\"calc\"},position:{valType:\"enumerated\",values:[\"top\",\"bottom\",\"left\",\"right\"],dflt:\"bottom\",editType:\"plot\"},relative:{valType:\"boolean\",editType:\"plot\",dflt:!1},valueformat:{valType:\"string\",editType:\"plot\"},increasing:{symbol:{valType:\"string\",dflt:h.INCREASING.SYMBOL,editType:\"plot\"},color:{valType:\"color\",dflt:h.INCREASING.COLOR,editType:\"plot\"},editType:\"plot\"},decreasing:{symbol:{valType:\"string\",dflt:h.DECREASING.SYMBOL,editType:\"plot\"},color:{valType:\"color\",dflt:h.DECREASING.COLOR,editType:\"plot\"},editType:\"plot\"},font:n({},f,{}),editType:\"calc\"},gauge:{shape:{valType:\"enumerated\",editType:\"plot\",dflt:\"angular\",values:[\"angular\",\"bullet\"]},bar:a({},p,{color:{dflt:\"green\"}}),bgcolor:{valType:\"color\",editType:\"plot\"},bordercolor:{valType:\"color\",dflt:s.defaultLine,editType:\"plot\"},borderwidth:{valType:\"number\",min:0,dflt:1,editType:\"plot\"},axis:i({range:d,visible:n({},c.visible,{dflt:!0}),tickmode:c.tickmode,nticks:c.nticks,tick0:c.tick0,dtick:c.dtick,tickvals:c.tickvals,ticktext:c.ticktext,ticks:n({},c.ticks,{dflt:\"outside\"}),ticklen:c.ticklen,tickwidth:c.tickwidth,tickcolor:c.tickcolor,showticklabels:c.showticklabels,tickfont:o({}),tickangle:c.tickangle,tickformat:c.tickformat,tickformatstops:c.tickformatstops,tickprefix:c.tickprefix,showtickprefix:c.showtickprefix,ticksuffix:c.ticksuffix,showticksuffix:c.showticksuffix,separatethousands:c.separatethousands,exponentformat:c.exponentformat,showexponent:c.showexponent,editType:\"plot\"},\"plot\"),steps:g,threshold:{line:{color:n({},p.line.color,{}),width:n({},p.line.width,{dflt:1}),editType:\"plot\"},thickness:n({},p.thickness,{dflt:.85}),value:{valType:\"number\",editType:\"calc\",dflt:!1},editType:\"plot\"},editType:\"plot\"}}},{\"../../components/color/attributes\":591,\"../../constants/delta.js\":687,\"../../constants/docs\":688,\"../../lib/extend\":708,\"../../plot_api/edit_types\":748,\"../../plot_api/plot_template\":755,\"../../plots/cartesian/layout_attributes\":777,\"../../plots/domain\":790,\"../../plots/font_attributes\":791}],1050:[function(t,e,r){\"use strict\";var n=t(\"../../plots/plots\");r.name=\"indicator\",r.plot=function(t,e,a,i){n.plotBasePlot(r.name,t,e,a,i)},r.clean=function(t,e,a,i){n.cleanBasePlot(r.name,t,e,a,i)}},{\"../../plots/plots\":826}],1051:[function(t,e,r){\"use strict\";e.exports={calc:function(t,e){var r=[],n=e.value;\"number\"!=typeof e._lastValue&&(e._lastValue=e.value);var a=e._lastValue,i=a;return e._hasDelta&&\"number\"==typeof e.delta.reference&&(i=e.delta.reference),r[0]={y:n,lastY:a,delta:n-i,relativeDelta:(n-i)/i},r}}},{}],1052:[function(t,e,r){\"use strict\";e.exports={defaultNumberFontSize:80,bulletNumberDomainSize:.25,bulletPadding:.025,innerRadius:.75,valueThickness:.5,titlePadding:5,horizontalPadding:10}},{}],1053:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./attributes\"),i=t(\"../../plots/domain\").defaults,o=t(\"../../plot_api/plot_template\"),s=t(\"../../plots/array_container_defaults\"),l=t(\"./constants.js\"),c=t(\"../../plots/cartesian/tick_value_defaults\"),u=t(\"../../plots/cartesian/tick_mark_defaults\"),h=t(\"../../plots/cartesian/tick_label_defaults\");function f(t,e){function r(r,i){return n.coerce(t,e,a.gauge.steps,r,i)}r(\"color\"),r(\"line.color\"),r(\"line.width\"),r(\"range\"),r(\"thickness\")}e.exports={supplyDefaults:function(t,e,r,p){function d(r,i){return n.coerce(t,e,a,r,i)}i(e,p,d),d(\"mode\"),e._hasNumber=-1!==e.mode.indexOf(\"number\"),e._hasDelta=-1!==e.mode.indexOf(\"delta\"),e._hasGauge=-1!==e.mode.indexOf(\"gauge\");var g=d(\"value\");e._range=[0,\"number\"==typeof g?1.5*g:1];var v,m,y,x,b,_,w=new Array(2);function k(t,e){return n.coerce(y,x,a.gauge,t,e)}function T(t,e){return n.coerce(b,_,a.gauge.axis,t,e)}if(e._hasNumber&&(d(\"number.valueformat\"),d(\"number.font.color\",p.font.color),d(\"number.font.family\",p.font.family),d(\"number.font.size\"),void 0===e.number.font.size&&(e.number.font.size=l.defaultNumberFontSize,w[0]=!0),d(\"number.prefix\"),d(\"number.suffix\"),v=e.number.font.size),e._hasDelta&&(d(\"delta.font.color\",p.font.color),d(\"delta.font.family\",p.font.family),d(\"delta.font.size\"),void 0===e.delta.font.size&&(e.delta.font.size=(e._hasNumber?.5:1)*(v||l.defaultNumberFontSize),w[1]=!0),d(\"delta.reference\",e.value),d(\"delta.relative\"),d(\"delta.valueformat\",e.delta.relative?\"2%\":\"\"),d(\"delta.increasing.symbol\"),d(\"delta.increasing.color\"),d(\"delta.decreasing.symbol\"),d(\"delta.decreasing.color\"),d(\"delta.position\"),m=e.delta.font.size),e._scaleNumbers=(!e._hasNumber||w[0])&&(!e._hasDelta||w[1])||!1,d(\"title.font.color\",p.font.color),d(\"title.font.family\",p.font.family),d(\"title.font.size\",.25*(v||m||l.defaultNumberFontSize)),d(\"title.text\"),e._hasGauge){(y=t.gauge)||(y={}),x=o.newContainer(e,\"gauge\"),k(\"shape\"),(e._isBullet=\"bullet\"===e.gauge.shape)||d(\"title.align\",\"center\"),(e._isAngular=\"angular\"===e.gauge.shape)||d(\"align\",\"center\"),k(\"bgcolor\",p.paper_bgcolor),k(\"borderwidth\"),k(\"bordercolor\"),k(\"bar.color\"),k(\"bar.line.color\"),k(\"bar.line.width\"),k(\"bar.thickness\",l.valueThickness*(\"bullet\"===e.gauge.shape?.5:1)),s(y,x,{name:\"steps\",handleItemDefaults:f}),k(\"threshold.value\"),k(\"threshold.thickness\"),k(\"threshold.line.width\"),k(\"threshold.line.color\"),b={},y&&(b=y.axis||{}),_=o.newContainer(x,\"axis\"),T(\"visible\"),e._range=T(\"range\",e._range);var M={outerTicks:!0};c(b,_,T,\"linear\"),h(b,_,T,\"linear\",M),u(b,_,T,M)}else d(\"title.align\",\"center\"),d(\"align\",\"center\"),e._isAngular=e._isBullet=!1;e._length=null}}},{\"../../lib\":717,\"../../plot_api/plot_template\":755,\"../../plots/array_container_defaults\":761,\"../../plots/cartesian/tick_label_defaults\":784,\"../../plots/cartesian/tick_mark_defaults\":785,\"../../plots/cartesian/tick_value_defaults\":786,\"../../plots/domain\":790,\"./attributes\":1049,\"./constants.js\":1052}],1054:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"indicator\",basePlotModule:t(\"./base_plot\"),categories:[\"svg\",\"noOpacity\",\"noHover\"],animatable:!0,attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,calc:t(\"./calc\").calc,plot:t(\"./plot\"),meta:{}}},{\"./attributes\":1049,\"./base_plot\":1050,\"./calc\":1051,\"./defaults\":1053,\"./plot\":1055}],1055:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\"),i=a.rad2deg,o=t(\"../../constants/alignment\").MID_SHIFT,s=t(\"../../components/drawing\"),l=t(\"./constants\"),c=t(\"../../lib/svg_text_utils\"),u=t(\"../../plots/cartesian/axes\"),h=t(\"../../plots/cartesian/axis_defaults\"),f=t(\"../../plots/cartesian/position_defaults\"),p=t(\"../../plots/cartesian/layout_attributes\"),d=t(\"../../components/color\"),g={left:\"start\",center:\"middle\",right:\"end\"},v={left:0,center:.5,right:1},m=/[yzafpn\\xb5mkMGTPEZY]/;function y(t){return t&&t.duration>0}function x(t){t.each(function(t){d.stroke(n.select(this),t.line.color)}).each(function(t){d.fill(n.select(this),t.color)}).style(\"stroke-width\",function(t){return t.line.width})}function b(t,e,r){var n=t._fullLayout,i=a.extendFlat({type:\"linear\",ticks:\"outside\",range:r,showline:!0},e),o={type:\"linear\",_id:\"x\"+e._id},s={letter:\"x\",font:n.font,noHover:!0,noTickson:!0};function l(t,e){return a.coerce(i,o,p,t,e)}return h(i,o,l,s,n),f(i,o,l,s),o}function _(t,e){return\"translate(\"+t+\",\"+e+\")\"}function w(t,e,r){return[Math.min(e/t.width,r/t.height),t,e+\"x\"+r]}function k(t,e,r,a){var i=document.createElementNS(\"http://www.w3.org/2000/svg\",\"text\"),o=n.select(i);return o.text(t).attr(\"x\",0).attr(\"y\",0).attr(\"text-anchor\",r).attr(\"data-unformatted\",t).call(c.convertToTspans,a).call(s.font,e),s.bBox(o.node())}function T(t,e,r,n,i,o){var s=\"_cache\"+e;t[s]&&t[s].key===i||(t[s]={key:i,value:r});var l=a.aggNums(o,null,[t[s].value,n],2);return t[s].value=l,l}e.exports=function(t,e,r,h){var f,p=t._fullLayout;y(r)&&h&&(f=h()),a.makeTraceGroups(p._indicatorlayer,e,\"trace\").each(function(e){var h,M,A,S,E,L=e[0].trace,C=n.select(this),P=L._hasGauge,O=L._isAngular,z=L._isBullet,I=L.domain,D={w:p._size.w*(I.x[1]-I.x[0]),h:p._size.h*(I.y[1]-I.y[0]),l:p._size.l+p._size.w*I.x[0],r:p._size.r+p._size.w*(1-I.x[1]),t:p._size.t+p._size.h*(1-I.y[1]),b:p._size.b+p._size.h*I.y[0]},R=D.l+D.w/2,F=D.t+D.h/2,B=Math.min(D.w/2,D.h),N=l.innerRadius*B,j=L.align||\"center\";if(M=F,P){if(O&&(h=R,M=F+B/2,A=function(t){return e=t,r=.9*N,n=Math.sqrt(e.width/2*(e.width/2)+e.height*e.height),[r/n,e,r];var e,r,n}),z){var V=l.bulletPadding,U=1-l.bulletNumberDomainSize+V;h=D.l+(U+(1-U)*v[j])*D.w,A=function(t){return w(t,(l.bulletNumberDomainSize-V)*D.w,D.h)}}}else h=D.l+v[j]*D.w,A=function(t){return w(t,D.w,D.h)};!function(t,e,r,i){var o,l,h,f=r[0].trace,p=i.numbersX,x=i.numbersY,w=f.align||\"center\",M=g[w],A=i.transitionOpts,S=i.onComplete,E=a.ensureSingle(e,\"g\",\"numbers\"),L=[];f._hasNumber&&L.push(\"number\");f._hasDelta&&(L.push(\"delta\"),\"left\"===f.delta.position&&L.reverse());var C=E.selectAll(\"text\").data(L);function P(e,r,n,a){if(!e.match(\"s\")||n>=0==a>=0||r(n).slice(-1).match(m)||r(a).slice(-1).match(m))return r;var i=e.slice().replace(\"s\",\"f\").replace(/\\d+/,function(t){return parseInt(t)-1}),o=b(t,{tickformat:i});return function(t){return Math.abs(t)<1?u.tickText(o,t).text:r(t)}}C.enter().append(\"text\"),C.attr(\"text-anchor\",function(){return M}).attr(\"class\",function(t){return t}).attr(\"x\",null).attr(\"y\",null).attr(\"dx\",null).attr(\"dy\",null),C.exit().remove();var O,z=f.mode+f.align;f._hasDelta&&(O=function(){var e=b(t,{tickformat:f.delta.valueformat},f._range);e.setScale(),u.prepTicks(e);var a=function(t){return u.tickText(e,t).text},i=function(t){var e=f.delta.relative?t.relativeDelta:t.delta;return e},o=function(t,e){return 0===t||\"number\"!=typeof t||isNaN(t)?\"-\":(t>0?f.delta.increasing.symbol:f.delta.decreasing.symbol)+e(t)},h=function(t){return t.delta>=0?f.delta.increasing.color:f.delta.decreasing.color};void 0===f._deltaLastValue&&(f._deltaLastValue=i(r[0]));var p=E.select(\"text.delta\");function g(){p.text(o(i(r[0]),a)).call(d.fill,h(r[0])).call(c.convertToTspans,t)}p.call(s.font,f.delta.font).call(d.fill,h({delta:f._deltaLastValue})),y(A)?p.transition().duration(A.duration).ease(A.easing).tween(\"text\",function(){var t=n.select(this),e=i(r[0]),s=f._deltaLastValue,l=P(f.delta.valueformat,a,s,e),c=n.interpolateNumber(s,e);return f._deltaLastValue=e,function(e){t.text(o(c(e),l)),t.call(d.fill,h({delta:c(e)}))}}).each(\"end\",function(){g(),S&&S()}).each(\"interrupt\",function(){g(),S&&S()}):g();return l=k(o(i(r[0]),a),f.delta.font,M,t),p}(),z+=f.delta.position+f.delta.font.size+f.delta.font.family+f.delta.valueformat,z+=f.delta.increasing.symbol+f.delta.decreasing.symbol,h=l);f._hasNumber&&(!function(){var e=b(t,{tickformat:f.number.valueformat},f._range);e.setScale(),u.prepTicks(e);var a=function(t){return u.tickText(e,t).text},i=f.number.suffix,l=f.number.prefix,h=E.select(\"text.number\");function p(){var e=\"number\"==typeof r[0].y?l+a(r[0].y)+i:\"-\";h.text(e).call(s.font,f.number.font).call(c.convertToTspans,t)}y(A)?h.transition().duration(A.duration).ease(A.easing).each(\"end\",function(){p(),S&&S()}).each(\"interrupt\",function(){p(),S&&S()}).attrTween(\"text\",function(){var t=n.select(this),e=n.interpolateNumber(r[0].lastY,r[0].y);f._lastValue=r[0].y;var o=P(f.number.valueformat,a,r[0].lastY,r[0].y);return function(r){t.text(l+o(e(r))+i)}}):p();o=k(l+a(r[0].y)+i,f.number.font,M,t)}(),z+=f.number.font.size+f.number.font.family+f.number.valueformat+f.number.suffix+f.number.prefix,h=o);if(f._hasDelta&&f._hasNumber){var I,D,R=[(o.left+o.right)/2,(o.top+o.bottom)/2],F=[(l.left+l.right)/2,(l.top+l.bottom)/2],B=.75*f.delta.font.size;\"left\"===f.delta.position&&(I=T(f,\"deltaPos\",0,-1*(o.width*v[f.align]+l.width*(1-v[f.align])+B),z,Math.min),D=R[1]-F[1],h={width:o.width+l.width+B,height:Math.max(o.height,l.height),left:l.left+I,right:o.right,top:Math.min(o.top,l.top+D),bottom:Math.max(o.bottom,l.bottom+D)}),\"right\"===f.delta.position&&(I=T(f,\"deltaPos\",0,o.width*(1-v[f.align])+l.width*v[f.align]+B,z,Math.max),D=R[1]-F[1],h={width:o.width+l.width+B,height:Math.max(o.height,l.height),left:o.left,right:l.right+I,top:Math.min(o.top,l.top+D),bottom:Math.max(o.bottom,l.bottom+D)}),\"bottom\"===f.delta.position&&(I=null,D=l.height,h={width:Math.max(o.width,l.width),height:o.height+l.height,left:Math.min(o.left,l.left),right:Math.max(o.right,l.right),top:o.bottom-o.height,bottom:o.bottom+l.height}),\"top\"===f.delta.position&&(I=null,D=o.top,h={width:Math.max(o.width,l.width),height:o.height+l.height,left:Math.min(o.left,l.left),right:Math.max(o.right,l.right),top:o.bottom-o.height-l.height,bottom:o.bottom}),O.attr({dx:I,dy:D})}(f._hasNumber||f._hasDelta)&&E.attr(\"transform\",function(){var t=i.numbersScaler(h);z+=t[2];var e,r=T(f,\"numbersScale\",1,t[0],z,Math.min);f._scaleNumbers||(r=1),e=f._isAngular?x-r*h.bottom:x-r*(h.top+h.bottom)/2,f._numbersTop=r*h.top+e;var n=h[w];\"center\"===w&&(n=(h.left+h.right)/2);var a=p-r*n;return _(a=T(f,\"numbersTranslate\",0,a,z,Math.max),e)+\" scale(\"+r+\")\"})}(t,C,e,{numbersX:h,numbersY:M,numbersScaler:A,transitionOpts:r,onComplete:f}),P&&(S={range:L.gauge.axis.range,color:L.gauge.bgcolor,line:{color:L.gauge.bordercolor,width:0},thickness:1},E={range:L.gauge.axis.range,color:\"rgba(0, 0, 0, 0)\",line:{color:L.gauge.bordercolor,width:L.gauge.borderwidth},thickness:1});var q=C.selectAll(\"g.angular\").data(O?e:[]);q.exit().remove();var H=C.selectAll(\"g.angularaxis\").data(O?e:[]);H.exit().remove(),O&&function(t,e,r,a){var s,l,c,h,f=r[0].trace,p=a.size,d=a.radius,g=a.innerRadius,v=a.gaugeBg,m=a.gaugeOutline,w=[p.l+p.w/2,p.t+p.h/2+d/2],k=a.gauge,T=a.layer,M=a.transitionOpts,A=a.onComplete,S=Math.PI/2;function E(t){var e=f.gauge.axis.range[0],r=f.gauge.axis.range[1],n=(t-e)/(r-e)*Math.PI-S;return n<-S?-S:n>S?S:n}function L(t){return n.svg.arc().innerRadius((g+d)/2-t/2*(d-g)).outerRadius((g+d)/2+t/2*(d-g)).startAngle(-S)}function C(t){t.attr(\"d\",function(t){return L(t.thickness).startAngle(E(t.range[0])).endAngle(E(t.range[1]))()})}k.enter().append(\"g\").classed(\"angular\",!0),k.attr(\"transform\",_(w[0],w[1])),T.enter().append(\"g\").classed(\"angularaxis\",!0).classed(\"crisp\",!0),T.selectAll(\"g.xangularaxistick,path,text\").remove(),(s=b(t,f.gauge.axis)).type=\"linear\",s.range=f.gauge.axis.range,s._id=\"xangularaxis\",s.setScale();var P=function(t){return(s.range[0]-t.x)/(s.range[1]-s.range[0])*Math.PI+Math.PI},O={},z=u.makeLabelFns(s,0).labelStandoff;O.xFn=function(t){var e=P(t);return Math.cos(e)*z},O.yFn=function(t){var e=P(t),r=Math.sin(e)>0?.2:1;return-Math.sin(e)*(z+t.fontSize*r)+Math.abs(Math.cos(e))*(t.fontSize*o)},O.anchorFn=function(t){var e=P(t),r=Math.cos(e);return Math.abs(r)<.1?\"middle\":r>0?\"start\":\"end\"},O.heightFn=function(t,e,r){var n=P(t);return-.5*(1+Math.sin(n))*r};var I=function(t){return _(w[0]+d*Math.cos(t),w[1]-d*Math.sin(t))};c=function(t){return I(P(t))};if(l=u.calcTicks(s),h=u.getTickSigns(s)[2],s.visible){h=\"inside\"===s.ticks?-1:1;var D=(s.linewidth||1)/2;u.drawTicks(t,s,{vals:l,layer:T,path:\"M\"+h*D+\",0h\"+h*s.ticklen,transFn:function(t){var e=P(t);return I(e)+\"rotate(\"+-i(e)+\")\"}}),u.drawLabels(t,s,{vals:l,layer:T,transFn:c,labelFns:O})}var R=[v].concat(f.gauge.steps),F=k.selectAll(\"g.bg-arc\").data(R);F.enter().append(\"g\").classed(\"bg-arc\",!0).append(\"path\"),F.select(\"path\").call(C).call(x),F.exit().remove();var B=L(f.gauge.bar.thickness),N=k.selectAll(\"g.value-arc\").data([f.gauge.bar]);N.enter().append(\"g\").classed(\"value-arc\",!0).append(\"path\");var j=N.select(\"path\");y(M)?(j.transition().duration(M.duration).ease(M.easing).each(\"end\",function(){A&&A()}).each(\"interrupt\",function(){A&&A()}).attrTween(\"d\",(V=B,U=E(r[0].lastY),q=E(r[0].y),function(){var t=n.interpolate(U,q);return function(e){return V.endAngle(t(e))()}})),f._lastValue=r[0].y):j.attr(\"d\",\"number\"==typeof r[0].y?B.endAngle(E(r[0].y)):\"M0,0Z\");var V,U,q;j.call(x),N.exit().remove(),R=[];var H=f.gauge.threshold.value;H&&R.push({range:[H,H],color:f.gauge.threshold.color,line:{color:f.gauge.threshold.line.color,width:f.gauge.threshold.line.width},thickness:f.gauge.threshold.thickness});var G=k.selectAll(\"g.threshold-arc\").data(R);G.enter().append(\"g\").classed(\"threshold-arc\",!0).append(\"path\"),G.select(\"path\").call(C).call(x),G.exit().remove();var Y=k.selectAll(\"g.gauge-outline\").data([m]);Y.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"path\"),Y.select(\"path\").call(C).call(x),Y.exit().remove()}(t,0,e,{radius:B,innerRadius:N,gauge:q,layer:H,size:D,gaugeBg:S,gaugeOutline:E,transitionOpts:r,onComplete:f});var G=C.selectAll(\"g.bullet\").data(z?e:[]);G.exit().remove();var Y=C.selectAll(\"g.bulletaxis\").data(z?e:[]);Y.exit().remove(),z&&function(t,e,r,n){var a,i,o,s,c,h=r[0].trace,f=n.gauge,p=n.layer,g=n.gaugeBg,v=n.gaugeOutline,m=n.size,_=h.domain,w=n.transitionOpts,k=n.onComplete;f.enter().append(\"g\").classed(\"bullet\",!0),f.attr(\"transform\",\"translate(\"+m.l+\", \"+m.t+\")\"),p.enter().append(\"g\").classed(\"bulletaxis\",!0).classed(\"crisp\",!0),p.selectAll(\"g.xbulletaxistick,path,text\").remove();var T=m.h,M=h.gauge.bar.thickness*T,A=_.x[0],S=_.x[0]+(_.x[1]-_.x[0])*(h._hasNumber||h._hasDelta?1-l.bulletNumberDomainSize:1);(a=b(t,h.gauge.axis))._id=\"xbulletaxis\",a.domain=[A,S],a.setScale(),i=u.calcTicks(a),o=u.makeTransFn(a),s=u.getTickSigns(a)[2],c=m.t+m.h,a.visible&&(u.drawTicks(t,a,{vals:\"inside\"===a.ticks?u.clipEnds(a,i):i,layer:p,path:u.makeTickPath(a,c,s),transFn:o}),u.drawLabels(t,a,{vals:i,layer:p,transFn:o,labelFns:u.makeLabelFns(a,c)}));function E(t){t.attr(\"width\",function(t){return Math.max(0,a.c2p(t.range[1])-a.c2p(t.range[0]))}).attr(\"x\",function(t){return a.c2p(t.range[0])}).attr(\"y\",function(t){return.5*(1-t.thickness)*T}).attr(\"height\",function(t){return t.thickness*T})}var L=[g].concat(h.gauge.steps),C=f.selectAll(\"g.bg-bullet\").data(L);C.enter().append(\"g\").classed(\"bg-bullet\",!0).append(\"rect\"),C.select(\"rect\").call(E).call(x),C.exit().remove();var P=f.selectAll(\"g.value-bullet\").data([h.gauge.bar]);P.enter().append(\"g\").classed(\"value-bullet\",!0).append(\"rect\"),P.select(\"rect\").attr(\"height\",M).attr(\"y\",(T-M)/2).call(x),y(w)?P.select(\"rect\").transition().duration(w.duration).ease(w.easing).each(\"end\",function(){k&&k()}).each(\"interrupt\",function(){k&&k()}).attr(\"width\",Math.max(0,a.c2p(Math.min(h.gauge.axis.range[1],r[0].y)))):P.select(\"rect\").attr(\"width\",\"number\"==typeof r[0].y?Math.max(0,a.c2p(Math.min(h.gauge.axis.range[1],r[0].y))):0);P.exit().remove();var O=r.filter(function(){return h.gauge.threshold.value}),z=f.selectAll(\"g.threshold-bullet\").data(O);z.enter().append(\"g\").classed(\"threshold-bullet\",!0).append(\"line\"),z.select(\"line\").attr(\"x1\",a.c2p(h.gauge.threshold.value)).attr(\"x2\",a.c2p(h.gauge.threshold.value)).attr(\"y1\",(1-h.gauge.threshold.thickness)/2*T).attr(\"y2\",(1-(1-h.gauge.threshold.thickness)/2)*T).call(d.stroke,h.gauge.threshold.line.color).style(\"stroke-width\",h.gauge.threshold.line.width),z.exit().remove();var I=f.selectAll(\"g.gauge-outline\").data([v]);I.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"rect\"),I.select(\"rect\").call(E).call(x),I.exit().remove()}(t,0,e,{gauge:G,layer:Y,size:D,gaugeBg:S,gaugeOutline:E,transitionOpts:r,onComplete:f});var W=C.selectAll(\"text.title\").data(e);W.exit().remove(),W.enter().append(\"text\").classed(\"title\",!0),W.attr(\"text-anchor\",function(){return z?g.right:g[L.title.align]}).text(L.title.text).call(s.font,L.title.font).call(c.convertToTspans,t),W.attr(\"transform\",function(){var t,e=D.l+D.w*v[L.title.align],r=l.titlePadding,n=s.bBox(W.node());if(P){if(O)if(L.gauge.axis.visible)t=s.bBox(H.node()).top-r-n.bottom;else t=D.t+D.h/2-B/2-n.bottom-r;z&&(t=M-(n.top+n.bottom)/2,e=D.l-l.bulletPadding*D.w)}else t=L._numbersTop-r-n.bottom;return _(e,t)})})}},{\"../../components/color\":592,\"../../components/drawing\":613,\"../../constants/alignment\":686,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"../../plots/cartesian/axes\":765,\"../../plots/cartesian/axis_defaults\":767,\"../../plots/cartesian/layout_attributes\":777,\"../../plots/cartesian/position_defaults\":780,\"./constants\":1052,d3:165}],1056:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/attributes\"),a=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../mesh3d/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../lib/extend\").extendFlat,l=t(\"../../plot_api/edit_types\").overrideAll;var c=e.exports=l(s({x:{valType:\"data_array\"},y:{valType:\"data_array\"},z:{valType:\"data_array\"},value:{valType:\"data_array\"},isomin:{valType:\"number\"},isomax:{valType:\"number\"},surface:{show:{valType:\"boolean\",dflt:!0},count:{valType:\"integer\",dflt:2,min:1},fill:{valType:\"number\",min:0,max:1,dflt:1},pattern:{valType:\"flaglist\",flags:[\"A\",\"B\",\"C\",\"D\",\"E\"],extras:[\"all\",\"odd\",\"even\"],dflt:\"all\"}},spaceframe:{show:{valType:\"boolean\",dflt:!1},fill:{valType:\"number\",min:0,max:1,dflt:.15}},slices:{x:{show:{valType:\"boolean\",dflt:!1},locations:{valType:\"data_array\",dflt:[]},fill:{valType:\"number\",min:0,max:1,dflt:1}},y:{show:{valType:\"boolean\",dflt:!1},locations:{valType:\"data_array\",dflt:[]},fill:{valType:\"number\",min:0,max:1,dflt:1}},z:{show:{valType:\"boolean\",dflt:!1},locations:{valType:\"data_array\",dflt:[]},fill:{valType:\"number\",min:0,max:1,dflt:1}}},caps:{x:{show:{valType:\"boolean\",dflt:!0},fill:{valType:\"number\",min:0,max:1,dflt:1}},y:{show:{valType:\"boolean\",dflt:!0},fill:{valType:\"number\",min:0,max:1,dflt:1}},z:{show:{valType:\"boolean\",dflt:!0},fill:{valType:\"number\",min:0,max:1,dflt:1}}},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:a(),showlegend:s({},o.showlegend,{dflt:!1})},n(\"\",{colorAttr:\"`value`\",showScaleDflt:!0,editTypeOverride:\"calc\"}),{opacity:i.opacity,lightposition:i.lightposition,lighting:i.lighting,flatshading:i.flatshading,contour:i.contour,hoverinfo:s({},o.hoverinfo)}),\"calc\",\"nested\");c.flatshading.dflt=!0,c.lighting.facenormalsepsilon.dflt=0,c.x.editType=c.y.editType=c.z.editType=c.value.editType=\"calc+clearAxisTypes\",c.transforms=void 0},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plot_api/edit_types\":748,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"../mesh3d/attributes\":1061}],1057:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/calc\"),a=t(\"../streamtube/calc\").processGrid,i=t(\"../streamtube/calc\").filter;e.exports=function(t,e){e._len=Math.min(e.x.length,e.y.length,e.z.length,e.value.length),e._x=i(e.x,e._len),e._y=i(e.y,e._len),e._z=i(e.z,e._len),e._value=i(e.value,e._len);var r=a(e);e._gridFill=r.fill,e._Xs=r.Xs,e._Ys=r.Ys,e._Zs=r.Zs,e._len=r.len;for(var o=1/0,s=-1/0,l=0;l<e._len;l++){var c=e._value[l];o=Math.min(o,c),s=Math.max(s,c)}e._minValues=o,e._maxValues=s,e._vMin=void 0===e.isomin||null===e.isomin?o:e.isomin,e._vMax=void 0===e.isomax||null===e.isomin?s:e.isomax,n(t,e,{vals:[e._vMin,e._vMax],containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":600,\"../streamtube/calc\":1227}],1058:[function(t,e,r){\"use strict\";var n=t(\"gl-mesh3d\"),a=t(\"../../lib/gl_format_color\").parseColorScale,i=t(\"../../lib/str2rgbarray\"),o=t(\"../../components/colorscale\").extractOpts,s=t(\"../../plots/gl3d/zip3\"),l=function(t,e){for(var r=e.length-1;r>0;r--){var n=Math.min(e[r],e[r-1]),a=Math.max(e[r],e[r-1]);if(a>n&&n<t&&t<=a)return{id:r,distRatio:(a-t)/(a-n)}}return{id:0,distRatio:0}};function c(t,e,r){this.scene=t,this.uid=r,this.mesh=e,this.name=\"\",this.data=null,this.showContour=!1}var u=c.prototype;u.handlePick=function(t){if(t.object===this.mesh){var e=t.data.index,r=this.data._meshX[e],n=this.data._meshY[e],a=this.data._meshZ[e],i=this.data._Ys.length,o=this.data._Zs.length,s=l(r,this.data._Xs).id,c=l(n,this.data._Ys).id,u=l(a,this.data._Zs).id,h=t.index=u+o*c+o*i*s;t.traceCoordinate=[this.data._meshX[h],this.data._meshY[h],this.data._meshZ[h],this.data._value[h]];var f=this.data.hovertext||this.data.text;return Array.isArray(f)&&void 0!==f[h]?t.textLabel=f[h]:f&&(t.textLabel=f),!0}},u.update=function(t){var e=this.scene,r=e.fullSceneLayout;function n(t,e,r,n){return e.map(function(e){return t.d2l(e,0,n)*r})}this.data=f(t);var l={positions:s(n(r.xaxis,t._meshX,e.dataScale[0],t.xcalendar),n(r.yaxis,t._meshY,e.dataScale[1],t.ycalendar),n(r.zaxis,t._meshZ,e.dataScale[2],t.zcalendar)),cells:s(t._meshI,t._meshJ,t._meshK),lightPosition:[t.lightposition.x,t.lightposition.y,t.lightposition.z],ambient:t.lighting.ambient,diffuse:t.lighting.diffuse,specular:t.lighting.specular,roughness:t.lighting.roughness,fresnel:t.lighting.fresnel,vertexNormalsEpsilon:t.lighting.vertexnormalsepsilon,faceNormalsEpsilon:t.lighting.facenormalsepsilon,opacity:t.opacity,contourEnable:t.contour.show,contourColor:i(t.contour.color).slice(0,3),contourWidth:t.contour.width,useFacetNormals:t.flatshading},c=o(t);l.vertexIntensity=t._meshIntensity,l.vertexIntensityBounds=[c.min,c.max],l.colormap=a(t),this.mesh.update(l)},u.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()};var h=[\"xyz\",\"xzy\",\"yxz\",\"yzx\",\"zxy\",\"zyx\"];function f(t){t._meshI=[],t._meshJ=[],t._meshK=[];var e,r,n,a,i,o,s,c=t.surface.show,u=t.spaceframe.show,f=t.surface.fill,p=t.spaceframe.fill,d=!1,g=!1,v=0,m=t._Xs,y=t._Ys,x=t._Zs,b=m.length,_=y.length,w=x.length,k=h.indexOf(t._gridFill.replace(/-/g,\"\").replace(/\\+/g,\"\")),T=function(t,e,r){switch(k){case 5:return r+w*e+w*_*t;case 4:return r+w*t+w*b*e;case 3:return e+_*r+_*w*t;case 2:return e+_*t+_*b*r;case 1:return t+b*r+b*w*e;default:return t+b*e+b*_*r}},M=t._minValues,A=t._maxValues,S=t._vMin,E=t._vMax;function L(t,e,s){for(var l=o.length,c=r;c<l;c++)if(t===n[c]&&e===a[c]&&s===i[c])return c;return-1}function C(){r=e}function P(){n=[],a=[],i=[],o=[],e=0,C()}function O(t,r,s,l){return n.push(t),a.push(r),i.push(s),o.push(l),++e-1}function z(t,e,r){for(var n=[],a=0;a<t.length;a++)n[a]=t[a]*(1-r)+r*e[a];return n}function I(t){s=t}function D(t,e){return\"all\"===t||null===t||t.indexOf(e)>-1}function R(t,e){return null===t?e:t}function F(e,r,n){C();var a,i,o,l=[r],c=[n];if(s>=1)l=[r],c=[n];else if(s>0){var u=function(t,e){var r=t[0],n=t[1],a=t[2],i=function(t,e,r){for(var n=[],a=0;a<t.length;a++)n[a]=(t[a]+e[a]+r[a])/3;return n}(r,n,a),o=Math.sqrt(1-s),l=z(i,r,o),c=z(i,n,o),u=z(i,a,o),h=e[0],f=e[1],p=e[2];return{xyzv:[[r,n,c],[c,l,r],[n,a,u],[u,c,n],[a,r,l],[l,u,a]],abc:[[h,f,-1],[-1,-1,h],[f,p,-1],[-1,-1,f],[p,h,-1],[-1,-1,p]]}}(r,n);l=u.xyzv,c=u.abc}for(var h=0;h<l.length;h++){r=l[h],n=c[h];for(var f=[],p=0;p<3;p++){var d=r[p][0],g=r[p][1],m=r[p][2],y=r[p][3],x=n[p]>-1?n[p]:L(d,g,m);f[p]=x>-1?x:O(d,g,m,R(e,y))}a=f[0],i=f[1],o=f[2],t._meshI.push(a),t._meshJ.push(i),t._meshK.push(o),++v}}function B(t,e,r,n){var a=t[3];a<r&&(a=r),a>n&&(a=n);for(var i=(t[3]-a)/(t[3]-e[3]+1e-9),o=[],s=0;s<4;s++)o[s]=(1-i)*t[s]+i*e[s];return o}function N(t,e,r){return t>=e&&t<=r}function j(t){var e=.001*(E-S);return t>=S-e&&t<=E+e}function V(e){for(var r=[],n=0;n<4;n++){var a=e[n];r.push([t._x[a],t._y[a],t._z[a],t._value[a]])}return r}var U=3;function q(t,e,r,n,a,i){i||(i=1),r=[-1,-1,-1];var o=!1,s=[N(e[0][3],n,a),N(e[1][3],n,a),N(e[2][3],n,a)];if(!s[0]&&!s[1]&&!s[2])return!1;var l=function(t,e,r){return j(e[0][3])&&j(e[1][3])&&j(e[2][3])?(F(t,e,r),!0):i<U&&q(t,e,r,S,E,++i)};if(s[0]&&s[1]&&s[2])return l(t,e,r)||o;var c=!1;return[[0,1,2],[2,0,1],[1,2,0]].forEach(function(i){if(s[i[0]]&&s[i[1]]&&!s[i[2]]){var u=e[i[0]],h=e[i[1]],f=e[i[2]],p=B(f,u,n,a),d=B(f,h,n,a);o=l(t,[d,p,u],[-1,-1,r[i[0]]])||o,o=l(t,[u,h,d],[r[i[0]],r[i[1]],-1])||o,c=!0}}),c?o:([[0,1,2],[1,2,0],[2,0,1]].forEach(function(i){if(s[i[0]]&&!s[i[1]]&&!s[i[2]]){var u=e[i[0]],h=e[i[1]],f=e[i[2]],p=B(h,u,n,a),d=B(f,u,n,a);o=l(t,[d,p,u],[-1,-1,r[i[0]]])||o,c=!0}}),o)}function H(t,e,r,n){var a=!1,i=V(e),o=[N(i[0][3],r,n),N(i[1][3],r,n),N(i[2][3],r,n),N(i[3][3],r,n)];if(!(o[0]||o[1]||o[2]||o[3]))return a;if(o[0]&&o[1]&&o[2]&&o[3])return g&&(a=function(t,e,r){var n=function(n,a,i){F(t,[e[n],e[a],e[i]],[r[n],r[a],r[i]])};n(0,1,2),n(3,0,1),n(2,3,0),n(1,2,3)}(t,i,e)||a),a;var s=!1;return[[0,1,2,3],[3,0,1,2],[2,3,0,1],[1,2,3,0]].forEach(function(l){if(o[l[0]]&&o[l[1]]&&o[l[2]]&&!o[l[3]]){var c=i[l[0]],u=i[l[1]],h=i[l[2]],f=i[l[3]];if(g)a=F(t,[c,u,h],[e[l[0]],e[l[1]],e[l[2]]])||a;else{var p=B(f,c,r,n),d=B(f,u,r,n),v=B(f,h,r,n);a=F(null,[p,d,v],[-1,-1,-1])||a}s=!0}}),s?a:([[0,1,2,3],[1,2,3,0],[2,3,0,1],[3,0,1,2],[0,2,3,1],[1,3,2,0]].forEach(function(l){if(o[l[0]]&&o[l[1]]&&!o[l[2]]&&!o[l[3]]){var c=i[l[0]],u=i[l[1]],h=i[l[2]],f=i[l[3]],p=B(h,c,r,n),d=B(h,u,r,n),v=B(f,u,r,n),m=B(f,c,r,n);g?(a=F(t,[c,m,p],[e[l[0]],-1,-1])||a,a=F(t,[u,d,v],[e[l[1]],-1,-1])||a):a=function(t,e,r){var n=function(n,a,i){F(t,[e[n],e[a],e[i]],[r[n],r[a],r[i]])};n(0,1,2),n(2,3,0)}(null,[p,d,v,m],[-1,-1,-1,-1])||a,s=!0}}),s?a:([[0,1,2,3],[1,2,3,0],[2,3,0,1],[3,0,1,2]].forEach(function(l){if(o[l[0]]&&!o[l[1]]&&!o[l[2]]&&!o[l[3]]){var c=i[l[0]],u=i[l[1]],h=i[l[2]],f=i[l[3]],p=B(u,c,r,n),d=B(h,c,r,n),v=B(f,c,r,n);g?(a=F(t,[c,p,d],[e[l[0]],-1,-1])||a,a=F(t,[c,d,v],[e[l[0]],-1,-1])||a,a=F(t,[c,v,p],[e[l[0]],-1,-1])||a):a=F(null,[p,d,v],[-1,-1,-1])||a,s=!0}}),a))}function G(t,e,r,n,a,i,o,s,l,c,u){var h=!1;return d&&(D(t,\"A\")&&(h=H(null,[e,r,n,i],c,u)||h),D(t,\"B\")&&(h=H(null,[r,n,a,l],c,u)||h),D(t,\"C\")&&(h=H(null,[r,i,o,l],c,u)||h),D(t,\"D\")&&(h=H(null,[n,i,s,l],c,u)||h),D(t,\"E\")&&(h=H(null,[r,n,i,l],c,u)||h)),g&&(h=H(t,[r,n,i,l],c,u)||h),h}function Y(t,e,r,n,a,i,o,s){return[!0===s[0]||q(t,V([e,r,n]),[e,r,n],i,o),!0===s[1]||q(t,V([n,a,e]),[n,a,e],i,o)]}function W(t,e,r,n,a,i,o,s,l){return s?Y(t,e,r,a,n,i,o,l):Y(t,r,a,n,e,i,o,l)}function X(t,e,r,n,a,i,o){var s,l,c,u,h=!1,f=function(){h=q(t,[s,l,c],[-1,-1,-1],a,i)||h,h=q(t,[c,u,s],[-1,-1,-1],a,i)||h},p=o[0],d=o[1],g=o[2];return p&&(s=z(V([T(e,r-0,n-0)])[0],V([T(e-1,r-0,n-0)])[0],p),l=z(V([T(e,r-0,n-1)])[0],V([T(e-1,r-0,n-1)])[0],p),c=z(V([T(e,r-1,n-1)])[0],V([T(e-1,r-1,n-1)])[0],p),u=z(V([T(e,r-1,n-0)])[0],V([T(e-1,r-1,n-0)])[0],p),f()),d&&(s=z(V([T(e-0,r,n-0)])[0],V([T(e-0,r-1,n-0)])[0],d),l=z(V([T(e-0,r,n-1)])[0],V([T(e-0,r-1,n-1)])[0],d),c=z(V([T(e-1,r,n-1)])[0],V([T(e-1,r-1,n-1)])[0],d),u=z(V([T(e-1,r,n-0)])[0],V([T(e-1,r-1,n-0)])[0],d),f()),g&&(s=z(V([T(e-0,r-0,n)])[0],V([T(e-0,r-0,n-1)])[0],g),l=z(V([T(e-0,r-1,n)])[0],V([T(e-0,r-1,n-1)])[0],g),c=z(V([T(e-1,r-1,n)])[0],V([T(e-1,r-1,n-1)])[0],g),u=z(V([T(e-1,r-0,n)])[0],V([T(e-1,r-0,n-1)])[0],g),f()),h}function Z(t,e,r,n,a,i,o,s,l,c,u,h){var f=t;return h?(d&&\"even\"===t&&(f=null),G(f,e,r,n,a,i,o,s,l,c,u)):(d&&\"odd\"===t&&(f=null),G(f,l,s,o,i,a,n,r,e,c,u))}function J(t,e,r,n,a){for(var i=[],o=0,s=0;s<e.length;s++)for(var l=e[s],c=1;c<w;c++)for(var u=1;u<_;u++)i.push(W(t,T(l,u-1,c-1),T(l,u-1,c),T(l,u,c-1),T(l,u,c),r,n,(l+u+c)%2,a&&a[o]?a[o]:[])),o++;return i}function K(t,e,r,n,a){for(var i=[],o=0,s=0;s<e.length;s++)for(var l=e[s],c=1;c<b;c++)for(var u=1;u<w;u++)i.push(W(t,T(c-1,l,u-1),T(c,l,u-1),T(c-1,l,u),T(c,l,u),r,n,(c+l+u)%2,a&&a[o]?a[o]:[])),o++;return i}function Q(t,e,r,n,a){for(var i=[],o=0,s=0;s<e.length;s++)for(var l=e[s],c=1;c<_;c++)for(var u=1;u<b;u++)i.push(W(t,T(u-1,c-1,l),T(u-1,c,l),T(u,c-1,l),T(u,c,l),r,n,(u+c+l)%2,a&&a[o]?a[o]:[])),o++;return i}function $(t,e,r){for(var n=1;n<w;n++)for(var a=1;a<_;a++)for(var i=1;i<b;i++)Z(t,T(i-1,a-1,n-1),T(i-1,a-1,n),T(i-1,a,n-1),T(i-1,a,n),T(i,a-1,n-1),T(i,a-1,n),T(i,a,n-1),T(i,a,n),e,r,(i+a+n)%2)}function tt(t,e,r){d=!0,$(t,e,r),d=!1}function et(t,e,r,n,a,i){for(var o=[],s=0,l=0;l<e.length;l++)for(var c=e[l],u=1;u<w;u++)for(var h=1;h<_;h++)o.push(X(t,c,h,u,r,n,a[l],i&&i[s]&&i[s])),s++;return o}function rt(t,e,r,n,a,i){for(var o=[],s=0,l=0;l<e.length;l++)for(var c=e[l],u=1;u<b;u++)for(var h=1;h<w;h++)o.push(X(t,u,c,h,r,n,a[l],i&&i[s]&&i[s])),s++;return o}function nt(t,e,r,n,a,i){for(var o=[],s=0,l=0;l<e.length;l++)for(var c=e[l],u=1;u<_;u++)for(var h=1;h<b;h++)o.push(X(t,h,u,c,r,n,a[l],i&&i[s]&&i[s])),s++;return o}function at(t,e){for(var r=[],n=t;n<e;n++)r.push(n);return r}return function(){if(P(),function(){for(var e=0;e<b;e++)for(var r=0;r<_;r++)for(var n=0;n<w;n++){var a=T(e,r,n);O(t._x[a],t._y[a],t._z[a],t._value[a])}}(),u&&p&&(I(p),g=!0,$(null,S,E),g=!1),c&&f){I(f);for(var e=t.surface.pattern,r=t.surface.count,s=0;s<r;s++){var h=1===r?.5:s/(r-1),d=(1-h)*S+h*E,k=Math.abs(d-M)>Math.abs(d-A)?[M,d]:[d,A];tt(e,k[0],k[1])}}var L=[[Math.min(S,A),Math.max(S,A)],[Math.min(M,E),Math.max(M,E)]];[\"x\",\"y\",\"z\"].forEach(function(e){for(var r=[],n=0;n<L.length;n++){var a=0,i=L[n][0],o=L[n][1],s=t.slices[e];if(s.show&&s.fill){I(s.fill);var c=[],u=[],h=[];if(s.locations.length)for(var f=0;f<s.locations.length;f++){var p=l(s.locations[f],\"x\"===e?m:\"y\"===e?y:x);0===p.distRatio?c.push(p.id):p.id>0&&(u.push(p.id),\"x\"===e?h.push([p.distRatio,0,0]):\"y\"===e?h.push([0,p.distRatio,0]):h.push([0,0,p.distRatio]))}else c=at(1,\"x\"===e?b-1:\"y\"===e?_-1:w-1);u.length>0&&(r[a]=\"x\"===e?et(null,u,i,o,h,r[a]):\"y\"===e?rt(null,u,i,o,h,r[a]):nt(null,u,i,o,h,r[a]),a++),c.length>0&&(r[a]=\"x\"===e?J(null,c,i,o,r[a]):\"y\"===e?K(null,c,i,o,r[a]):Q(null,c,i,o,r[a]),a++)}var d=t.caps[e];d.show&&d.fill&&(I(d.fill),r[a]=\"x\"===e?J(null,[0,b-1],i,o,r[a]):\"y\"===e?K(null,[0,_-1],i,o,r[a]):Q(null,[0,w-1],i,o,r[a]),a++)}}),0===v&&P(),t._meshX=n,t._meshY=a,t._meshZ=i,t._meshIntensity=o,t._Xs=m,t._Ys=y,t._Zs=x}(),t}e.exports={findNearestOnAxis:l,generateIsoMeshes:f,createIsosurfaceTrace:function(t,e){var r=t.glplot.gl,a=n({gl:r}),i=new c(t,a,e.uid);return a._trace=i,i.update(e),t.glplot.add(a),i}}},{\"../../components/colorscale\":604,\"../../lib/gl_format_color\":714,\"../../lib/str2rgbarray\":740,\"../../plots/gl3d/zip3\":816,\"gl-mesh3d\":283}],1059:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../registry\"),i=t(\"./attributes\"),o=t(\"../../components/colorscale/defaults\");function s(t,e,r,n,i){var s=i(\"isomin\"),l=i(\"isomax\");null!=l&&null!=s&&s>l&&(e.isomin=null,e.isomax=null);var c=i(\"x\"),u=i(\"y\"),h=i(\"z\"),f=i(\"value\");c&&c.length&&u&&u.length&&h&&h.length&&f&&f.length?(a.getComponentMethod(\"calendars\",\"handleTraceDefaults\")(t,e,[\"x\",\"y\",\"z\"],n),[\"x\",\"y\",\"z\"].forEach(function(t){var e=\"caps.\"+t;i(e+\".show\")&&i(e+\".fill\");var r=\"slices.\"+t;i(r+\".show\")&&(i(r+\".fill\"),i(r+\".locations\"))}),i(\"spaceframe.show\")&&i(\"spaceframe.fill\"),i(\"surface.show\")&&(i(\"surface.count\"),i(\"surface.fill\"),i(\"surface.pattern\")),i(\"contour.show\")&&(i(\"contour.color\"),i(\"contour.width\")),[\"text\",\"hovertext\",\"hovertemplate\",\"lighting.ambient\",\"lighting.diffuse\",\"lighting.specular\",\"lighting.roughness\",\"lighting.fresnel\",\"lighting.vertexnormalsepsilon\",\"lighting.facenormalsepsilon\",\"lightposition.x\",\"lightposition.y\",\"lightposition.z\",\"flatshading\",\"opacity\"].forEach(function(t){i(t)}),o(t,e,n,i,{prefix:\"\",cLetter:\"c\"}),e._length=null):e.visible=!1}e.exports={supplyDefaults:function(t,e,r,a){s(t,e,0,a,function(r,a){return n.coerce(t,e,i,r,a)})},supplyIsoDefaults:s}},{\"../../components/colorscale/defaults\":602,\"../../lib\":717,\"../../registry\":846,\"./attributes\":1056}],1060:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,calc:t(\"./calc\"),colorbar:{min:\"cmin\",max:\"cmax\"},plot:t(\"./convert\").createIsosurfaceTrace,moduleType:\"trace\",name:\"isosurface\",basePlotModule:t(\"../../plots/gl3d\"),categories:[\"gl3d\",\"showLegend\"],meta:{}}},{\"../../plots/gl3d\":805,\"./attributes\":1056,\"./calc\":1057,\"./convert\":1058,\"./defaults\":1059}],1061:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/attributes\"),a=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../surface/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../lib/extend\").extendFlat;e.exports=s({x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},i:{valType:\"data_array\",editType:\"calc\"},j:{valType:\"data_array\",editType:\"calc\"},k:{valType:\"data_array\",editType:\"calc\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertemplate:a({editType:\"calc\"}),delaunayaxis:{valType:\"enumerated\",values:[\"x\",\"y\",\"z\"],dflt:\"z\",editType:\"calc\"},alphahull:{valType:\"number\",dflt:-1,editType:\"calc\"},intensity:{valType:\"data_array\",editType:\"calc\"},intensitymode:{valType:\"enumerated\",values:[\"vertex\",\"cell\"],dflt:\"vertex\",editType:\"calc\"},color:{valType:\"color\",editType:\"calc\"},vertexcolor:{valType:\"data_array\",editType:\"calc\"},facecolor:{valType:\"data_array\",editType:\"calc\"},transforms:void 0},n(\"\",{colorAttr:\"`intensity`\",showScaleDflt:!0,editTypeOverride:\"calc\"}),{opacity:i.opacity,flatshading:{valType:\"boolean\",dflt:!1,editType:\"calc\"},contour:{show:s({},i.contours.x.show,{}),color:i.contours.x.color,width:i.contours.x.width,editType:\"calc\"},lightposition:{x:s({},i.lightposition.x,{dflt:1e5}),y:s({},i.lightposition.y,{dflt:1e5}),z:s({},i.lightposition.z,{dflt:0}),editType:\"calc\"},lighting:s({vertexnormalsepsilon:{valType:\"number\",min:0,max:1,dflt:1e-12,editType:\"calc\"},facenormalsepsilon:{valType:\"number\",min:0,max:1,dflt:1e-6,editType:\"calc\"},editType:\"calc\"},i.lighting),hoverinfo:s({},o.hoverinfo,{editType:\"calc\"}),showlegend:s({},o.showlegend,{dflt:!1})})},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"../surface/attributes\":1243}],1062:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/calc\");e.exports=function(t,e){e.intensity&&n(t,e,{vals:e.intensity,containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":600}],1063:[function(t,e,r){\"use strict\";var n=t(\"gl-mesh3d\"),a=t(\"delaunay-triangulate\"),i=t(\"alpha-shape\"),o=t(\"convex-hull\"),s=t(\"../../lib/gl_format_color\").parseColorScale,l=t(\"../../lib/str2rgbarray\"),c=t(\"../../components/colorscale\").extractOpts,u=t(\"../../plots/gl3d/zip3\");function h(t,e,r){this.scene=t,this.uid=r,this.mesh=e,this.name=\"\",this.color=\"#fff\",this.data=null,this.showContour=!1}var f=h.prototype;function p(t){for(var e=[],r=t.length,n=0;n<r;n++)e[n]=l(t[n]);return e}function d(t,e,r,n){for(var a=[],i=e.length,o=0;o<i;o++)a[o]=t.d2l(e[o],0,n)*r;return a}function g(t){for(var e=[],r=t.length,n=0;n<r;n++)e[n]=Math.round(t[n]);return e}function v(t,e){for(var r=t.length,n=0;n<r;n++)if(t[n]<=-.5||t[n]>=e-.5)return!1;return!0}f.handlePick=function(t){if(t.object===this.mesh){var e=t.index=t.data.index;t.data._cellCenter?t.traceCoordinate=t.data.dataCoordinate:t.traceCoordinate=[this.data.x[e],this.data.y[e],this.data.z[e]];var r=this.data.hovertext||this.data.text;return Array.isArray(r)&&void 0!==r[e]?t.textLabel=r[e]:r&&(t.textLabel=r),!0}},f.update=function(t){var e=this.scene,r=e.fullSceneLayout;this.data=t;var n,h=t.x.length,f=u(d(r.xaxis,t.x,e.dataScale[0],t.xcalendar),d(r.yaxis,t.y,e.dataScale[1],t.ycalendar),d(r.zaxis,t.z,e.dataScale[2],t.zcalendar));if(t.i&&t.j&&t.k){if(t.i.length!==t.j.length||t.j.length!==t.k.length||!v(t.i,h)||!v(t.j,h)||!v(t.k,h))return;n=u(g(t.i),g(t.j),g(t.k))}else n=0===t.alphahull?o(f):t.alphahull>0?i(t.alphahull,f):function(t,e){for(var r=[\"x\",\"y\",\"z\"].indexOf(t),n=[],i=e.length,o=0;o<i;o++)n[o]=[e[o][(r+1)%3],e[o][(r+2)%3]];return a(n)}(t.delaunayaxis,f);var m={positions:f,cells:n,lightPosition:[t.lightposition.x,t.lightposition.y,t.lightposition.z],ambient:t.lighting.ambient,diffuse:t.lighting.diffuse,specular:t.lighting.specular,roughness:t.lighting.roughness,fresnel:t.lighting.fresnel,vertexNormalsEpsilon:t.lighting.vertexnormalsepsilon,faceNormalsEpsilon:t.lighting.facenormalsepsilon,opacity:t.opacity,contourEnable:t.contour.show,contourColor:l(t.contour.color).slice(0,3),contourWidth:t.contour.width,useFacetNormals:t.flatshading};if(t.intensity){var y=c(t);this.color=\"#fff\";var x=t.intensitymode;m[x+\"Intensity\"]=t.intensity,m[x+\"IntensityBounds\"]=[y.min,y.max],m.colormap=s(t)}else t.vertexcolor?(this.color=t.vertexcolor[0],m.vertexColors=p(t.vertexcolor)):t.facecolor?(this.color=t.facecolor[0],m.cellColors=p(t.facecolor)):(this.color=t.color,m.meshColor=l(t.color));this.mesh.update(m)},f.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()},e.exports=function(t,e){var r=t.glplot.gl,a=n({gl:r}),i=new h(t,a,e.uid);return a._trace=i,i.update(e),t.glplot.add(a),i}},{\"../../components/colorscale\":604,\"../../lib/gl_format_color\":714,\"../../lib/str2rgbarray\":740,\"../../plots/gl3d/zip3\":816,\"alpha-shape\":67,\"convex-hull\":132,\"delaunay-triangulate\":167,\"gl-mesh3d\":283}],1064:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../lib\"),i=t(\"../../components/colorscale/defaults\"),o=t(\"./attributes\");e.exports=function(t,e,r,s){function l(r,n){return a.coerce(t,e,o,r,n)}function c(t){var e=t.map(function(t){var e=l(t);return e&&a.isArrayOrTypedArray(e)?e:null});return e.every(function(t){return t&&t.length===e[0].length})&&e}c([\"x\",\"y\",\"z\"])?(c([\"i\",\"j\",\"k\"]),(!e.i||e.j&&e.k)&&(!e.j||e.k&&e.i)&&(!e.k||e.i&&e.j)?(n.getComponentMethod(\"calendars\",\"handleTraceDefaults\")(t,e,[\"x\",\"y\",\"z\"],s),[\"lighting.ambient\",\"lighting.diffuse\",\"lighting.specular\",\"lighting.roughness\",\"lighting.fresnel\",\"lighting.vertexnormalsepsilon\",\"lighting.facenormalsepsilon\",\"lightposition.x\",\"lightposition.y\",\"lightposition.z\",\"flatshading\",\"alphahull\",\"delaunayaxis\",\"opacity\"].forEach(function(t){l(t)}),l(\"contour.show\")&&(l(\"contour.color\"),l(\"contour.width\")),\"intensity\"in t?(l(\"intensity\"),l(\"intensitymode\"),i(t,e,s,l,{prefix:\"\",cLetter:\"c\"})):(e.showscale=!1,\"facecolor\"in t?l(\"facecolor\"):\"vertexcolor\"in t?l(\"vertexcolor\"):l(\"color\",r)),l(\"text\"),l(\"hovertext\"),l(\"hovertemplate\"),e._length=null):e.visible=!1):e.visible=!1}},{\"../../components/colorscale/defaults\":602,\"../../lib\":717,\"../../registry\":846,\"./attributes\":1061}],1065:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),colorbar:{min:\"cmin\",max:\"cmax\"},plot:t(\"./convert\"),moduleType:\"trace\",name:\"mesh3d\",basePlotModule:t(\"../../plots/gl3d\"),categories:[\"gl3d\",\"showLegend\"],meta:{}}},{\"../../plots/gl3d\":805,\"./attributes\":1061,\"./calc\":1062,\"./convert\":1063,\"./defaults\":1064}],1066:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").extendFlat,a=t(\"../scatter/attributes\"),i=t(\"../../components/drawing/attributes\").dash,o=t(\"../../components/fx/attributes\"),s=t(\"../../constants/delta.js\"),l=s.INCREASING.COLOR,c=s.DECREASING.COLOR,u=a.line;function h(t){return{line:{color:n({},u.color,{dflt:t}),width:u.width,dash:i,editType:\"style\"},editType:\"style\"}}e.exports={x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},open:{valType:\"data_array\",editType:\"calc\"},high:{valType:\"data_array\",editType:\"calc\"},low:{valType:\"data_array\",editType:\"calc\"},close:{valType:\"data_array\",editType:\"calc\"},line:{width:n({},u.width,{}),dash:n({},i,{}),editType:\"style\"},increasing:h(l),decreasing:h(c),text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},tickwidth:{valType:\"number\",min:0,max:.5,dflt:.3,editType:\"calc\"},hoverlabel:n({},o.hoverlabel,{split:{valType:\"boolean\",dflt:!1,editType:\"style\"}})}},{\"../../components/drawing/attributes\":612,\"../../components/fx/attributes\":622,\"../../constants/delta.js\":687,\"../../lib\":717,\"../scatter/attributes\":1120}],1067:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=n._,i=t(\"../../plots/cartesian/axes\"),o=t(\"../../constants/numerical\").BADNUM;function s(t,e,r,n){return{o:t,h:e,l:r,c:n}}function l(t,e,r,s,l){for(var c=s.makeCalcdata(e,\"open\"),u=s.makeCalcdata(e,\"high\"),h=s.makeCalcdata(e,\"low\"),f=s.makeCalcdata(e,\"close\"),p=Array.isArray(e.text),d=Array.isArray(e.hovertext),g=!0,v=null,m=[],y=0;y<r.length;y++){var x=r[y],b=c[y],_=u[y],w=h[y],k=f[y];if(x!==o&&b!==o&&_!==o&&w!==o&&k!==o){k===b?null!==v&&k!==v&&(g=k>v):g=k>b,v=k;var T=l(b,_,w,k);T.pos=x,T.yc=(b+k)/2,T.i=y,T.dir=g?\"increasing\":\"decreasing\",T.x=T.pos,T.y=[w,_],p&&(T.tx=e.text[y]),d&&(T.htx=e.hovertext[y]),m.push(T)}else m.push({pos:x,empty:!0})}return e._extremes[s._id]=i.findExtremes(s,n.concat(h,u),{padded:!0}),m.length&&(m[0].t={labels:{open:a(t,\"open:\")+\" \",high:a(t,\"high:\")+\" \",low:a(t,\"low:\")+\" \",close:a(t,\"close:\")+\" \"}}),m}e.exports={calc:function(t,e){var r=i.getFromId(t,e.xaxis),a=i.getFromId(t,e.yaxis),o=function(t,e,r){var a=r._minDiff;if(!a){var i,o=t._fullData,s=[];for(a=1/0,i=0;i<o.length;i++){var l=o[i];if(\"ohlc\"===l.type&&!0===l.visible&&l.xaxis===e._id){s.push(l);var c=e.makeCalcdata(l,\"x\");l._xcalc=c;var u=n.distinctVals(c).minDiff;u&&isFinite(u)&&(a=Math.min(a,u))}}for(a===1/0&&(a=1),i=0;i<s.length;i++)s[i]._minDiff=a}return a*r.tickwidth}(t,r,e),c=e._minDiff;e._minDiff=null;var u=e._xcalc;e._xcalc=null;var h=l(t,e,u,a,s);return e._extremes[r._id]=i.findExtremes(r,u,{vpad:c/2}),h.length?(n.extendFlat(h[0].t,{wHover:c/2,tickLen:o}),h):[{t:{empty:!0}}]},calcCommon:l}},{\"../../constants/numerical\":693,\"../../lib\":717,\"../../plots/cartesian/axes\":765}],1068:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./ohlc_defaults\"),i=t(\"./attributes\");function o(t,e,r,n){r(n+\".line.color\"),r(n+\".line.width\",e.line.width),r(n+\".line.dash\",e.line.dash)}e.exports=function(t,e,r,s){function l(r,a){return n.coerce(t,e,i,r,a)}a(t,e,l,s)?(l(\"line.width\"),l(\"line.dash\"),o(t,e,l,\"increasing\"),o(t,e,l,\"decreasing\"),l(\"text\"),l(\"hovertext\"),l(\"tickwidth\"),s._requestRangeslider[e.xaxis]=!0):e.visible=!1}},{\"../../lib\":717,\"./attributes\":1066,\"./ohlc_defaults\":1071}],1069:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\"),a=t(\"../../lib\"),i=t(\"../../components/fx\"),o=t(\"../../components/color\"),s=t(\"../../lib\").fillText,l=t(\"../../constants/delta.js\"),c={increasing:l.INCREASING.SYMBOL,decreasing:l.DECREASING.SYMBOL};function u(t,e,r,n){var a,s,l=t.cd,c=t.xa,u=l[0].trace,h=l[0].t,f=u.type,p=\"ohlc\"===f?\"l\":\"min\",d=\"ohlc\"===f?\"h\":\"max\",g=h.bPos||0,v=function(t){return t.pos+g-e},m=h.bdPos||h.tickLen,y=h.wHover,x=Math.min(1,m/Math.abs(c.r2c(c.range[1])-c.r2c(c.range[0])));function b(t){var e=v(t);return i.inbox(e-y,e+y,a)}function _(t){var e=t[p],n=t[d];return e===n||i.inbox(e-r,n-r,a)}function w(t){return(b(t)+_(t))/2}a=t.maxHoverDistance-x,s=t.maxSpikeDistance-x;var k=i.getDistanceFunction(n,b,_,w);if(i.getClosest(l,k,t),!1===t.index)return null;var T=l[t.index];if(T.empty)return null;var M=u[T.dir],A=M.line.color;return o.opacity(A)&&M.line.width?t.color=A:t.color=M.fillcolor,t.x0=c.c2p(T.pos+g-m,!0),t.x1=c.c2p(T.pos+g+m,!0),t.xLabelVal=T.pos,t.spikeDistance=w(T)*s/a,t.xSpike=c.c2p(T.pos,!0),t}function h(t,e,r,i){var o=t.cd,s=t.ya,l=o[0].trace,c=o[0].t,h=[],f=u(t,e,r,i);if(!f)return[];var p=o[f.index].hi||l.hoverinfo,d=p.split(\"+\");if(!(\"all\"===p||-1!==d.indexOf(\"y\")))return[];for(var g=[\"high\",\"open\",\"close\",\"low\"],v={},m=0;m<g.length;m++){var y,x=g[m],b=l[x][f.index],_=s.c2p(b,!0);b in v?(y=v[b]).yLabel+=\"<br>\"+c.labels[x]+n.hoverLabelText(s,b):((y=a.extendFlat({},f)).y0=y.y1=_,y.yLabelVal=b,y.yLabel=c.labels[x]+n.hoverLabelText(s,b),y.name=\"\",h.push(y),v[b]=y)}return h}function f(t,e,r,a){var i=t.cd,o=t.ya,l=i[0].trace,h=i[0].t,f=u(t,e,r,a);if(!f)return[];var p=i[f.index],d=f.index=p.i,g=p.dir;function v(t){return h.labels[t]+n.hoverLabelText(o,l[t][d])}var m=p.hi||l.hoverinfo,y=m.split(\"+\"),x=\"all\"===m,b=x||-1!==y.indexOf(\"y\"),_=x||-1!==y.indexOf(\"text\"),w=b?[v(\"open\"),v(\"high\"),v(\"low\"),v(\"close\")+\"  \"+c[g]]:[];return _&&s(p,l,w),f.extraText=w.join(\"<br>\"),f.y0=f.y1=o.c2p(p.yc,!0),[f]}e.exports={hoverPoints:function(t,e,r,n){return t.cd[0].trace.hoverlabel.split?h(t,e,r,n):f(t,e,r,n)},hoverSplit:h,hoverOnPoints:f}},{\"../../components/color\":592,\"../../components/fx\":630,\"../../constants/delta.js\":687,\"../../lib\":717,\"../../plots/cartesian/axes\":765}],1070:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"ohlc\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"cartesian\",\"svg\",\"showLegend\"],meta:{},attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\").calc,plot:t(\"./plot\"),style:t(\"./style\"),hoverPoints:t(\"./hover\").hoverPoints,selectPoints:t(\"./select\")}},{\"../../plots/cartesian\":776,\"./attributes\":1066,\"./calc\":1067,\"./defaults\":1068,\"./hover\":1069,\"./plot\":1072,\"./select\":1073,\"./style\":1074}],1071:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../lib\");e.exports=function(t,e,r,i){var o=r(\"x\"),s=r(\"open\"),l=r(\"high\"),c=r(\"low\"),u=r(\"close\");if(r(\"hoverlabel.split\"),n.getComponentMethod(\"calendars\",\"handleTraceDefaults\")(t,e,[\"x\"],i),s&&l&&c&&u){var h=Math.min(s.length,l.length,c.length,u.length);return o&&(h=Math.min(h,a.minRowLength(o))),e._length=h,h}}},{\"../../lib\":717,\"../../registry\":846}],1072:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\");e.exports=function(t,e,r,i){var o=e.xaxis,s=e.yaxis;a.makeTraceGroups(i,r,\"trace ohlc\").each(function(t){var e=n.select(this),r=t[0],i=r.t;if(!0!==r.trace.visible||i.empty)e.remove();else{var l=i.tickLen,c=e.selectAll(\"path\").data(a.identity);c.enter().append(\"path\"),c.exit().remove(),c.attr(\"d\",function(t){if(t.empty)return\"M0,0Z\";var e=o.c2p(t.pos,!0),r=o.c2p(t.pos-l,!0),n=o.c2p(t.pos+l,!0);return\"M\"+r+\",\"+s.c2p(t.o,!0)+\"H\"+e+\"M\"+e+\",\"+s.c2p(t.h,!0)+\"V\"+s.c2p(t.l,!0)+\"M\"+n+\",\"+s.c2p(t.c,!0)+\"H\"+e})}})}},{\"../../lib\":717,d3:165}],1073:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r,n=t.cd,a=t.xaxis,i=t.yaxis,o=[],s=n[0].t.bPos||0;if(!1===e)for(r=0;r<n.length;r++)n[r].selected=0;else for(r=0;r<n.length;r++){var l=n[r];e.contains([a.c2p(l.pos+s),i.c2p(l.yc)],null,l.i,t)?(o.push({pointNumber:l.i,x:a.c2d(l.pos),y:i.c2d(l.yc)}),l.selected=1):l.selected=0}return o}},{}],1074:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../components/drawing\"),i=t(\"../../components/color\");e.exports=function(t,e,r){var o=r||n.select(t).selectAll(\"g.ohlclayer\").selectAll(\"g.trace\");o.style(\"opacity\",function(t){return t[0].trace.opacity}),o.each(function(t){var e=t[0].trace;n.select(this).selectAll(\"path\").each(function(t){if(!t.empty){var r=e[t.dir].line;n.select(this).style(\"fill\",\"none\").call(i.stroke,r.color).call(a.dashLine,r.dash,r.width).style(\"opacity\",e.selectedpoints&&!t.selected?.3:1)}})})}},{\"../../components/color\":592,\"../../components/drawing\":613,d3:165}],1075:[function(t,e,r){\"use strict\";var n=t(\"../../lib/extend\").extendFlat,a=t(\"../../plots/attributes\"),i=t(\"../../plots/font_attributes\"),o=t(\"../../components/colorscale/attributes\"),s=t(\"../../plots/template_attributes\").hovertemplateAttrs,l=t(\"../../plots/domain\").attributes,c=n({editType:\"calc\"},o(\"line\",{editTypeOverride:\"calc\"}),{shape:{valType:\"enumerated\",values:[\"linear\",\"hspline\"],dflt:\"linear\",editType:\"plot\"},hovertemplate:s({editType:\"plot\",arrayOk:!1},{keys:[\"count\",\"probability\"]})});e.exports={domain:l({name:\"parcats\",trace:!0,editType:\"calc\"}),hoverinfo:n({},a.hoverinfo,{flags:[\"count\",\"probability\"],editType:\"plot\",arrayOk:!1}),hoveron:{valType:\"enumerated\",values:[\"category\",\"color\",\"dimension\"],dflt:\"category\",editType:\"plot\"},hovertemplate:s({editType:\"plot\",arrayOk:!1},{keys:[\"count\",\"probability\",\"category\",\"categorycount\",\"colorcount\",\"bandcolorcount\"]}),arrangement:{valType:\"enumerated\",values:[\"perpendicular\",\"freeform\",\"fixed\"],dflt:\"perpendicular\",editType:\"plot\"},bundlecolors:{valType:\"boolean\",dflt:!0,editType:\"plot\"},sortpaths:{valType:\"enumerated\",values:[\"forward\",\"backward\"],dflt:\"forward\",editType:\"plot\"},labelfont:i({editType:\"calc\"}),tickfont:i({editType:\"calc\"}),dimensions:{_isLinkedToArray:\"dimension\",label:{valType:\"string\",editType:\"calc\"},categoryorder:{valType:\"enumerated\",values:[\"trace\",\"category ascending\",\"category descending\",\"array\"],dflt:\"trace\",editType:\"calc\"},categoryarray:{valType:\"data_array\",editType:\"calc\"},ticktext:{valType:\"data_array\",editType:\"calc\"},values:{valType:\"data_array\",dflt:[],editType:\"calc\"},displayindex:{valType:\"integer\",editType:\"calc\"},editType:\"calc\",visible:{valType:\"boolean\",dflt:!0,editType:\"calc\"}},line:c,counts:{valType:\"number\",min:0,dflt:1,arrayOk:!0,editType:\"calc\"},customdata:void 0,hoverlabel:void 0,ids:void 0,legendgroup:void 0,opacity:void 0,selectedpoints:void 0,showlegend:void 0}},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/domain\":790,\"../../plots/font_attributes\":791,\"../../plots/template_attributes\":841}],1076:[function(t,e,r){\"use strict\";var n=t(\"../../plots/get_data\").getModuleCalcData,a=t(\"./plot\");r.name=\"parcats\",r.plot=function(t,e,r,i){var o=n(t.calcdata,\"parcats\");if(o.length){var s=o[0];a(t,s,r,i)}},r.clean=function(t,e,r,n){var a=n._has&&n._has(\"parcats\"),i=e._has&&e._has(\"parcats\");a&&!i&&n._paperdiv.selectAll(\".parcats\").remove()}},{\"../../plots/get_data\":800,\"./plot\":1081}],1077:[function(t,e,r){\"use strict\";var n=t(\"../../lib/gup\").wrap,a=t(\"../../components/colorscale/helpers\").hasColorscale,i=t(\"../../components/colorscale/calc\"),o=t(\"../../lib/filter_unique.js\"),s=t(\"../../components/drawing\"),l=t(\"../../lib\");function c(t,e,r){t.valueInds.push(e),t.count+=r}function u(t,e,r){return{categoryInds:t,color:e,rawColor:r,valueInds:[],count:0}}function h(t,e,r){t.valueInds.push(e),t.count+=r}e.exports=function(t,e){var r=l.filterVisible(e.dimensions);if(0===r.length)return[];var f,p,d,g=r.map(function(t){var e;return\"trace\"===t.categoryorder?e=null:\"array\"===t.categoryorder?e=t.categoryarray:(e=o(t.values).sort(),\"category descending\"===t.categoryorder&&(e=e.reverse())),function(t,e){e=null==e?[]:e.map(function(t){return t});var r={},n={},a=[];e.forEach(function(t,e){r[t]=0,n[t]=e});for(var i=0;i<t.length;i++){var o,s=t[i];void 0===r[s]?(r[s]=1,o=e.push(s)-1,n[s]=o):(r[s]++,o=n[s]),a.push(o)}var l=e.map(function(t){return r[t]});return{uniqueValues:e,uniqueCounts:l,inds:a}}(t.values,e)});f=l.isArrayOrTypedArray(e.counts)?e.counts:[e.counts],function(t){var e;if(function(t){for(var e=new Array(t.length),r=0;r<t.length;r++){if(t[r]<0||t[r]>=t.length)return!1;if(void 0!==e[t[r]])return!1;e[t[r]]=!0}return!0}(t.map(function(t){return t.displayindex})))for(e=0;e<t.length;e++)t[e]._displayindex=t[e].displayindex;else for(e=0;e<t.length;e++)t[e]._displayindex=e}(r),r.forEach(function(t,e){!function(t,e){t._categoryarray=e.uniqueValues,null===t.ticktext||void 0===t.ticktext?t._ticktext=[]:t._ticktext=t.ticktext.slice();for(var r=t._ticktext.length;r<e.uniqueValues.length;r++)t._ticktext.push(e.uniqueValues[r])}(t,g[e])});var v,m=e.line;m?(a(e,\"line\")&&i(t,e,{vals:e.line.color,containerStr:\"line\",cLetter:\"c\"}),v=s.tryColorscale(m)):v=l.identity;var y,x,b,_,w,k=r[0].values.length,T={},M=g.map(function(t){return t.inds});for(d=0,y=0;y<k;y++){var A=[];for(x=0;x<M.length;x++)A.push(M[x][y]);p=f[y%f.length],d+=p;var S=(b=y,_=void 0,w=void 0,l.isArrayOrTypedArray(m.color)?w=_=m.color[b%m.color.length]:_=m.color,{color:v(_),rawColor:w}),E=A+\"-\"+S.rawColor;void 0===T[E]&&(T[E]=u(A,S.color,S.rawColor)),h(T[E],y,p)}var L,C=r.map(function(t,e){return r=e,n=t._index,a=t._displayindex,i=t.label,{dimensionInd:r,containerInd:n,displayInd:a,dimensionLabel:i,count:d,categories:[],dragX:null};var r,n,a,i});for(y=0;y<k;y++)for(p=f[y%f.length],x=0;x<C.length;x++){var P=C[x].containerInd,O=g[x].inds[y],z=C[x].categories;if(void 0===z[O]){var I=e.dimensions[P]._categoryarray[O],D=e.dimensions[P]._ticktext[O];z[O]={dimensionInd:x,categoryInd:L=O,categoryValue:I,displayInd:L,categoryLabel:D,valueInds:[],count:0,dragY:null}}c(z[O],y,p)}return n(function(t,e,r){var n=t.map(function(t){return t.categories.length}).reduce(function(t,e){return Math.max(t,e)});return{dimensions:t,paths:e,trace:void 0,maxCats:n,count:r}}(C,T,d))}},{\"../../components/colorscale/calc\":600,\"../../components/colorscale/helpers\":603,\"../../components/drawing\":613,\"../../lib\":717,\"../../lib/filter_unique.js\":709,\"../../lib/gup\":715}],1078:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/colorscale/helpers\").hasColorscale,i=t(\"../../components/colorscale/defaults\"),o=t(\"../../plots/domain\").defaults,s=t(\"../../plots/array_container_defaults\"),l=t(\"./attributes\"),c=t(\"../parcoords/merge_length\");function u(t,e){function r(r,a){return n.coerce(t,e,l.dimensions,r,a)}var a=r(\"values\"),i=r(\"visible\");if(a&&a.length||(i=e.visible=!1),i){r(\"label\"),r(\"displayindex\",e._index);var o,s=t.categoryarray,c=Array.isArray(s)&&s.length>0;c&&(o=\"array\");var u=r(\"categoryorder\",o);\"array\"===u?(r(\"categoryarray\"),r(\"ticktext\")):(delete t.categoryarray,delete t.ticktext),c||\"array\"!==u||(e.categoryorder=\"trace\")}}e.exports=function(t,e,r,h){function f(r,a){return n.coerce(t,e,l,r,a)}var p=s(t,e,{name:\"dimensions\",handleItemDefaults:u}),d=function(t,e,r,o,s){s(\"line.shape\"),s(\"line.hovertemplate\");var l=s(\"line.color\",o.colorway[0]);if(a(t,\"line\")&&n.isArrayOrTypedArray(l)){if(l.length)return s(\"line.colorscale\"),i(t,e,o,s,{prefix:\"line.\",cLetter:\"c\"}),l.length;e.line.color=r}return 1/0}(t,e,r,h,f);o(e,h,f),Array.isArray(p)&&p.length||(e.visible=!1),c(e,p,\"values\",d),f(\"hoveron\"),f(\"hovertemplate\"),f(\"arrangement\"),f(\"bundlecolors\"),f(\"sortpaths\"),f(\"counts\");var g={family:h.font.family,size:Math.round(h.font.size),color:h.font.color};n.coerceFont(f,\"labelfont\",g);var v={family:h.font.family,size:Math.round(h.font.size/1.2),color:h.font.color};n.coerceFont(f,\"tickfont\",v)}},{\"../../components/colorscale/defaults\":602,\"../../components/colorscale/helpers\":603,\"../../lib\":717,\"../../plots/array_container_defaults\":761,\"../../plots/domain\":790,\"../parcoords/merge_length\":1091,\"./attributes\":1075}],1079:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"./plot\"),colorbar:{container:\"line\",min:\"cmin\",max:\"cmax\"},moduleType:\"trace\",name:\"parcats\",basePlotModule:t(\"./base_plot\"),categories:[\"noOpacity\"],meta:{}}},{\"./attributes\":1075,\"./base_plot\":1076,\"./calc\":1077,\"./defaults\":1078,\"./plot\":1081}],1080:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../plot_api/plot_api\"),i=t(\"../../components/fx\"),o=t(\"../../lib\"),s=t(\"../../components/drawing\"),l=t(\"tinycolor2\"),c=t(\"../../lib/svg_text_utils\");function u(t,e,r,a){var i=t.map(function(t,e,r){var n,a=r[0],i=e.margin||{l:80,r:80,t:100,b:80},o=a.trace,s=o.domain,l=e.width,c=e.height,u=Math.floor(l*(s.x[1]-s.x[0])),h=Math.floor(c*(s.y[1]-s.y[0])),f=s.x[0]*l+i.l,p=e.height-s.y[1]*e.height+i.t,d=o.line.shape;n=\"all\"===o.hoverinfo?[\"count\",\"probability\"]:(o.hoverinfo||\"\").split(\"+\");var g={trace:o,key:o.uid,model:a,x:f,y:p,width:u,height:h,hoveron:o.hoveron,hoverinfoItems:n,arrangement:o.arrangement,bundlecolors:o.bundlecolors,sortpaths:o.sortpaths,labelfont:o.labelfont,categorylabelfont:o.tickfont,pathShape:d,dragDimension:null,margin:i,paths:[],dimensions:[],graphDiv:t,traceSelection:null,pathSelection:null,dimensionSelection:null};a.dimensions&&(F(g),R(g));return g}.bind(0,e,r)),l=a.selectAll(\"g.parcatslayer\").data([null]);l.enter().append(\"g\").attr(\"class\",\"parcatslayer\").style(\"pointer-events\",\"all\");var u=l.selectAll(\"g.trace.parcats\").data(i,h),v=u.enter().append(\"g\").attr(\"class\",\"trace parcats\");u.attr(\"transform\",function(t){return\"translate(\"+t.x+\", \"+t.y+\")\"}),v.append(\"g\").attr(\"class\",\"paths\");var m=u.select(\"g.paths\").selectAll(\"path.path\").data(function(t){return t.paths},h);m.attr(\"fill\",function(t){return t.model.color});var b=m.enter().append(\"path\").attr(\"class\",\"path\").attr(\"stroke-opacity\",0).attr(\"fill\",function(t){return t.model.color}).attr(\"fill-opacity\",0);x(b),m.attr(\"d\",function(t){return t.svgD}),b.empty()||m.sort(p),m.exit().remove(),m.on(\"mouseover\",d).on(\"mouseout\",g).on(\"click\",y),v.append(\"g\").attr(\"class\",\"dimensions\");var k=u.select(\"g.dimensions\").selectAll(\"g.dimension\").data(function(t){return t.dimensions},h);k.enter().append(\"g\").attr(\"class\",\"dimension\"),k.attr(\"transform\",function(t){return\"translate(\"+t.x+\", 0)\"}),k.exit().remove();var T=k.selectAll(\"g.category\").data(function(t){return t.categories},h),M=T.enter().append(\"g\").attr(\"class\",\"category\");T.attr(\"transform\",function(t){return\"translate(0, \"+t.y+\")\"}),M.append(\"rect\").attr(\"class\",\"catrect\").attr(\"pointer-events\",\"none\"),T.select(\"rect.catrect\").attr(\"fill\",\"none\").attr(\"width\",function(t){return t.width}).attr(\"height\",function(t){return t.height}),_(M);var A=T.selectAll(\"rect.bandrect\").data(function(t){return t.bands},h);A.each(function(){o.raiseToTop(this)}),A.attr(\"fill\",function(t){return t.color});var O=A.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"stroke-opacity\",0).attr(\"fill\",function(t){return t.color}).attr(\"fill-opacity\",0);A.attr(\"fill\",function(t){return t.color}).attr(\"width\",function(t){return t.width}).attr(\"height\",function(t){return t.height}).attr(\"y\",function(t){return t.y}).attr(\"cursor\",function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"perpendicular\"===t.parcatsViewModel.arrangement?\"ns-resize\":\"move\"}),w(O),A.exit().remove(),M.append(\"text\").attr(\"class\",\"catlabel\").attr(\"pointer-events\",\"none\");var z=e._fullLayout.paper_bgcolor;T.select(\"text.catlabel\").attr(\"text-anchor\",function(t){return f(t)?\"start\":\"end\"}).attr(\"alignment-baseline\",\"middle\").style(\"text-shadow\",z+\" -1px  1px 2px, \"+z+\" 1px  1px 2px, \"+z+\"  1px -1px 2px, \"+z+\" -1px -1px 2px\").style(\"fill\",\"rgb(0, 0, 0)\").attr(\"x\",function(t){return f(t)?t.width+5:-5}).attr(\"y\",function(t){return t.height/2}).text(function(t){return t.model.categoryLabel}).each(function(t){s.font(n.select(this),t.parcatsViewModel.categorylabelfont),c.convertToTspans(n.select(this),e)}),M.append(\"text\").attr(\"class\",\"dimlabel\"),T.select(\"text.dimlabel\").attr(\"text-anchor\",\"middle\").attr(\"alignment-baseline\",\"baseline\").attr(\"cursor\",function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"ew-resize\"}).attr(\"x\",function(t){return t.width/2}).attr(\"y\",-5).text(function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null}).each(function(t){s.font(n.select(this),t.parcatsViewModel.labelfont)}),T.selectAll(\"rect.bandrect\").on(\"mouseover\",S).on(\"mouseout\",E),T.exit().remove(),k.call(n.behavior.drag().origin(function(t){return{x:t.x,y:0}}).on(\"dragstart\",L).on(\"drag\",C).on(\"dragend\",P)),u.each(function(t){t.traceSelection=n.select(this),t.pathSelection=n.select(this).selectAll(\"g.paths\").selectAll(\"path.path\"),t.dimensionSelection=n.select(this).selectAll(\"g.dimensions\").selectAll(\"g.dimension\")}),u.exit().remove()}function h(t){return t.key}function f(t){var e=t.parcatsViewModel.dimensions.length,r=t.parcatsViewModel.dimensions[e-1].model.dimensionInd;return t.model.dimensionInd===r}function p(t,e){return t.model.rawColor>e.model.rawColor?1:t.model.rawColor<e.model.rawColor?-1:0}function d(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){o.raiseToTop(this),b(n.select(this));var e=v(t),r=m(t);if(t.parcatsViewModel.graphDiv.emit(\"plotly_hover\",{points:e,event:n.event,constraints:r}),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\")){var a,s,c,u=n.mouse(this)[0],h=t.parcatsViewModel.graphDiv,f=t.parcatsViewModel.trace,p=h._fullLayout,d=p._paperdiv.node().getBoundingClientRect(),g=t.parcatsViewModel.graphDiv.getBoundingClientRect();for(c=0;c<t.leftXs.length-1;c++)if(t.leftXs[c]+t.dimWidths[c]-2<=u&&u<=t.leftXs[c+1]+2){var y=t.parcatsViewModel.dimensions[c],x=t.parcatsViewModel.dimensions[c+1];a=(y.x+y.width+x.x)/2,s=(t.topYs[c]+t.topYs[c+1]+t.height)/2;break}var _=t.parcatsViewModel.x+a,w=t.parcatsViewModel.y+s,k=l.mostReadable(t.model.color,[\"black\",\"white\"]),T=t.model.count,M=T/t.parcatsViewModel.model.count,A={countLabel:T,probabilityLabel:M.toFixed(3)},S=[];-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&S.push([\"Count:\",A.countLabel].join(\" \")),-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&S.push([\"P:\",A.probabilityLabel].join(\" \"));var E=S.join(\"<br>\"),L=n.mouse(h)[0];i.loneHover({trace:f,x:_-d.left+g.left,y:w-d.top+g.top,text:E,color:t.model.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:10,fontColor:k,idealAlign:L<_?\"right\":\"left\",hovertemplate:(f.line||{}).hovertemplate,hovertemplateLabels:A,eventData:[{data:f._input,fullData:f,count:T,probability:M}]},{container:p._hoverlayer.node(),outerContainer:p._paper.node(),gd:h})}}}function g(t){if(!t.parcatsViewModel.dragDimension&&(x(n.select(this)),i.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()),t.parcatsViewModel.pathSelection.sort(p),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\"))){var e=v(t),r=m(t);t.parcatsViewModel.graphDiv.emit(\"plotly_unhover\",{points:e,event:n.event,constraints:r})}}function v(t){for(var e=[],r=O(t.parcatsViewModel),n=0;n<t.model.valueInds.length;n++){var a=t.model.valueInds[n];e.push({curveNumber:r,pointNumber:a})}return e}function m(t){for(var e={},r=t.parcatsViewModel.model.dimensions,n=0;n<r.length;n++){var a=r[n],i=a.categories[t.model.categoryInds[n]];e[a.containerInd]=i.categoryValue}return void 0!==t.model.rawColor&&(e.color=t.model.rawColor),e}function y(t){if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){var e=v(t),r=m(t);t.parcatsViewModel.graphDiv.emit(\"plotly_click\",{points:e,event:n.event,constraints:r})}}function x(t){t.attr(\"fill\",function(t){return t.model.color}).attr(\"fill-opacity\",.6).attr(\"stroke\",\"lightgray\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1)}function b(t){t.attr(\"fill-opacity\",.8).attr(\"stroke\",function(t){return l.mostReadable(t.model.color,[\"black\",\"white\"])}).attr(\"stroke-width\",.3)}function _(t){t.select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",1).attr(\"stroke-opacity\",1)}function w(t){t.attr(\"stroke\",\"black\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1).attr(\"fill-opacity\",1)}function k(t){var e=t.parcatsViewModel.pathSelection,r=t.categoryViewModel.model.dimensionInd,n=t.categoryViewModel.model.categoryInd;return e.filter(function(e){return e.model.categoryInds[r]===n&&e.model.color===t.color})}function T(t,e,r){var a=n.select(t).datum(),i=a.categoryViewModel.model,o=a.parcatsViewModel.graphDiv,s=n.select(t.parentNode).selectAll(\"rect.bandrect\"),l=[];s.each(function(t){k(t).each(function(t){Array.prototype.push.apply(l,v(t))})});var c={};c[i.dimensionInd]=i.categoryValue,o.emit(e,{points:l,event:r,constraints:c})}function M(t,e,r){var a=n.select(t).datum(),i=a.categoryViewModel.model,o=a.parcatsViewModel.graphDiv,s=k(a),l=[];s.each(function(t){Array.prototype.push.apply(l,v(t))});var c={};c[i.dimensionInd]=i.categoryValue,void 0!==a.rawColor&&(c.color=a.rawColor),o.emit(e,{points:l,event:r,constraints:c})}function A(t,e){var r,a,i=n.select(e.parentNode).select(\"rect.catrect\"),o=i.node().getBoundingClientRect(),s=i.datum(),l=s.parcatsViewModel,c=l.model.dimensions[s.model.dimensionInd],u=l.trace,h=o.top+o.height/2;l.dimensions.length>1&&c.displayInd===l.dimensions.length-1?(r=o.left,a=\"left\"):(r=o.left+o.width,a=\"right\");var f=s.model.count,p=s.model.categoryLabel,d=f/s.parcatsViewModel.model.count,g={countLabel:f,categoryLabel:p,probabilityLabel:d.toFixed(3)},v=[];-1!==s.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&v.push([\"Count:\",g.countLabel].join(\" \")),-1!==s.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&v.push([\"P(\"+g.categoryLabel+\"):\",g.probabilityLabel].join(\" \"));var m=v.join(\"<br>\");return{trace:u,x:r-t.left,y:h-t.top,text:m,color:\"lightgray\",borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:12,fontColor:\"black\",idealAlign:a,hovertemplate:u.hovertemplate,hovertemplateLabels:g,eventData:[{data:u._input,fullData:u,count:f,category:p,probability:d}]}}function S(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){if(n.mouse(this)[1]<-1)return;var e,r=t.parcatsViewModel.graphDiv,a=r._fullLayout,s=a._paperdiv.node().getBoundingClientRect(),c=t.parcatsViewModel.hoveron;if(\"color\"===c?(!function(t){var e=n.select(t).datum(),r=k(e);b(r),r.each(function(){o.raiseToTop(this)}),n.select(t.parentNode).selectAll(\"rect.bandrect\").filter(function(t){return t.color===e.color}).each(function(){o.raiseToTop(this),n.select(this).attr(\"stroke\",\"black\").attr(\"stroke-width\",1.5)})}(this),M(this,\"plotly_hover\",n.event)):(!function(t){n.select(t.parentNode).selectAll(\"rect.bandrect\").each(function(t){var e=k(t);b(e),e.each(function(){o.raiseToTop(this)})}),n.select(t.parentNode).select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",2.5)}(this),T(this,\"plotly_hover\",n.event)),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\"))\"category\"===c?e=A(s,this):\"color\"===c?e=function(t,e){var r,a,i=e.getBoundingClientRect(),o=n.select(e).datum(),s=o.categoryViewModel,c=s.parcatsViewModel,u=c.model.dimensions[s.model.dimensionInd],h=c.trace,f=i.y+i.height/2;c.dimensions.length>1&&u.displayInd===c.dimensions.length-1?(r=i.left,a=\"left\"):(r=i.left+i.width,a=\"right\");var p=s.model.categoryLabel,d=o.parcatsViewModel.model.count,g=0;o.categoryViewModel.bands.forEach(function(t){t.color===o.color&&(g+=t.count)});var v=s.model.count,m=0;c.pathSelection.each(function(t){t.model.color===o.color&&(m+=t.model.count)});var y=g/d,x=g/m,b=g/v,_={countLabel:d,categoryLabel:p,probabilityLabel:y.toFixed(3)},w=[];-1!==s.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&w.push([\"Count:\",_.countLabel].join(\" \")),-1!==s.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&(w.push(\"P(color \\u2229 \"+p+\"): \"+_.probabilityLabel),w.push(\"P(\"+p+\" | color): \"+x.toFixed(3)),w.push(\"P(color | \"+p+\"): \"+b.toFixed(3)));var k=w.join(\"<br>\"),T=l.mostReadable(o.color,[\"black\",\"white\"]);return{trace:h,x:r-t.left,y:f-t.top,text:k,color:o.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontColor:T,fontSize:10,idealAlign:a,hovertemplate:h.hovertemplate,hovertemplateLabels:_,eventData:[{data:h._input,fullData:h,category:p,count:d,probability:y,categorycount:v,colorcount:m,bandcolorcount:g}]}}(s,this):\"dimension\"===c&&(e=function(t,e){var r=[];return n.select(e.parentNode.parentNode).selectAll(\"g.category\").select(\"rect.catrect\").each(function(){r.push(A(t,this))}),r}(s,this)),e&&i.loneHover(e,{container:a._hoverlayer.node(),outerContainer:a._paper.node(),gd:r})}}function E(t){var e=t.parcatsViewModel;if(!e.dragDimension&&(x(e.pathSelection),_(e.dimensionSelection.selectAll(\"g.category\")),w(e.dimensionSelection.selectAll(\"g.category\").selectAll(\"rect.bandrect\")),i.loneUnhover(e.graphDiv._fullLayout._hoverlayer.node()),e.pathSelection.sort(p),-1===e.hoverinfoItems.indexOf(\"skip\"))){\"color\"===t.parcatsViewModel.hoveron?M(this,\"plotly_unhover\",n.event):T(this,\"plotly_unhover\",n.event)}}function L(t){\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragDimensionDisplayInd=t.model.displayInd,t.initialDragDimensionDisplayInds=t.parcatsViewModel.model.dimensions.map(function(t){return t.displayInd}),t.dragHasMoved=!1,t.dragCategoryDisplayInd=null,n.select(this).selectAll(\"g.category\").select(\"rect.catrect\").each(function(e){var r=n.mouse(this)[0],a=n.mouse(this)[1];-2<=r&&r<=e.width+2&&-2<=a&&a<=e.height+2&&(t.dragCategoryDisplayInd=e.model.displayInd,t.initialDragCategoryDisplayInds=t.model.categories.map(function(t){return t.displayInd}),e.model.dragY=e.y,o.raiseToTop(this.parentNode),n.select(this.parentNode).selectAll(\"rect.bandrect\").each(function(e){e.y<a&&a<=e.y+e.height&&(t.potentialClickBand=this)}))}),t.parcatsViewModel.dragDimension=t,i.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()))}function C(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragHasMoved=!0,null!==t.dragDimensionDisplayInd)){var e=t.dragDimensionDisplayInd,r=e-1,a=e+1,i=t.parcatsViewModel.dimensions[e];if(null!==t.dragCategoryDisplayInd){var o=i.categories[t.dragCategoryDisplayInd];o.model.dragY+=n.event.dy;var s=o.model.dragY,l=o.model.displayInd,c=i.categories,u=c[l-1],h=c[l+1];void 0!==u&&s<u.y+u.height/2&&(o.model.displayInd=u.model.displayInd,u.model.displayInd=l),void 0!==h&&s+o.height>h.y+h.height/2&&(o.model.displayInd=h.model.displayInd,h.model.displayInd=l),t.dragCategoryDisplayInd=o.model.displayInd}if(null===t.dragCategoryDisplayInd||\"freeform\"===t.parcatsViewModel.arrangement){i.model.dragX=n.event.x;var f=t.parcatsViewModel.dimensions[r],p=t.parcatsViewModel.dimensions[a];void 0!==f&&i.model.dragX<f.x+f.width&&(i.model.displayInd=f.model.displayInd,f.model.displayInd=e),void 0!==p&&i.model.dragX+i.width>p.x&&(i.model.displayInd=p.model.displayInd,p.model.displayInd=t.dragDimensionDisplayInd),t.dragDimensionDisplayInd=i.model.displayInd}F(t.parcatsViewModel),R(t.parcatsViewModel),I(t.parcatsViewModel),z(t.parcatsViewModel)}}function P(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&null!==t.dragDimensionDisplayInd){n.select(this).selectAll(\"text\").attr(\"font-weight\",\"normal\");var e={},r=O(t.parcatsViewModel),i=t.parcatsViewModel.model.dimensions.map(function(t){return t.displayInd}),o=t.initialDragDimensionDisplayInds.some(function(t,e){return t!==i[e]});o&&i.forEach(function(r,n){var a=t.parcatsViewModel.model.dimensions[n].containerInd;e[\"dimensions[\"+a+\"].displayindex\"]=r});var s=!1;if(null!==t.dragCategoryDisplayInd){var l=t.model.categories.map(function(t){return t.displayInd});if(s=t.initialDragCategoryDisplayInds.some(function(t,e){return t!==l[e]})){var c=t.model.categories.slice().sort(function(t,e){return t.displayInd-e.displayInd}),u=c.map(function(t){return t.categoryValue}),h=c.map(function(t){return t.categoryLabel});e[\"dimensions[\"+t.model.containerInd+\"].categoryarray\"]=[u],e[\"dimensions[\"+t.model.containerInd+\"].ticktext\"]=[h],e[\"dimensions[\"+t.model.containerInd+\"].categoryorder\"]=\"array\"}}if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")&&!t.dragHasMoved&&t.potentialClickBand&&(\"color\"===t.parcatsViewModel.hoveron?M(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent):T(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent)),t.model.dragX=null,null!==t.dragCategoryDisplayInd)t.parcatsViewModel.dimensions[t.dragDimensionDisplayInd].categories[t.dragCategoryDisplayInd].model.dragY=null,t.dragCategoryDisplayInd=null;t.dragDimensionDisplayInd=null,t.parcatsViewModel.dragDimension=null,t.dragHasMoved=null,t.potentialClickBand=null,F(t.parcatsViewModel),R(t.parcatsViewModel),n.transition().duration(300).ease(\"cubic-in-out\").each(function(){I(t.parcatsViewModel,!0),z(t.parcatsViewModel,!0)}).each(\"end\",function(){(o||s)&&a.restyle(t.parcatsViewModel.graphDiv,e,[r])})}}function O(t){for(var e,r=t.graphDiv._fullData,n=0;n<r.length;n++)if(t.key===r[n].uid){e=n;break}return e}function z(t,e){var r;void 0===e&&(e=!1),t.pathSelection.data(function(t){return t.paths},h),(r=t.pathSelection,e?r.transition():r).attr(\"d\",function(t){return t.svgD})}function I(t,e){function r(t){return e?t.transition():t}void 0===e&&(e=!1),t.dimensionSelection.data(function(t){return t.dimensions},h);var a=t.dimensionSelection.selectAll(\"g.category\").data(function(t){return t.categories},h);r(t.dimensionSelection).attr(\"transform\",function(t){return\"translate(\"+t.x+\", 0)\"}),r(a).attr(\"transform\",function(t){return\"translate(0, \"+t.y+\")\"}),a.select(\".dimlabel\").text(function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null}),a.select(\".catlabel\").attr(\"text-anchor\",function(t){return f(t)?\"start\":\"end\"}).attr(\"x\",function(t){return f(t)?t.width+5:-5}).each(function(t){var e,r;f(t)?(e=t.width+5,r=\"start\"):(e=-5,r=\"end\"),n.select(this).selectAll(\"tspan\").attr(\"x\",e).attr(\"text-anchor\",r)});var i=a.selectAll(\"rect.bandrect\").data(function(t){return t.bands},h),s=i.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"cursor\",\"move\").attr(\"stroke-opacity\",0).attr(\"fill\",function(t){return t.color}).attr(\"fill-opacity\",0);i.attr(\"fill\",function(t){return t.color}).attr(\"width\",function(t){return t.width}).attr(\"height\",function(t){return t.height}).attr(\"y\",function(t){return t.y}),w(s),i.each(function(){o.raiseToTop(this)}),i.exit().remove()}function D(t,e,r,a,i){var o,s,l=[],c=[];for(s=0;s<r.length-1;s++)o=n.interpolateNumber(r[s]+t[s],t[s+1]),l.push(o(i)),c.push(o(1-i));var u=\"M \"+t[0]+\",\"+e[0];for(u+=\"l\"+r[0]+\",0 \",s=1;s<r.length;s++)u+=\"C\"+l[s-1]+\",\"+e[s-1]+\" \"+c[s-1]+\",\"+e[s]+\" \"+t[s]+\",\"+e[s],u+=\"l\"+r[s]+\",0 \";for(u+=\"l0,\"+a+\" \",u+=\"l -\"+r[r.length-1]+\",0 \",s=r.length-2;s>=0;s--)u+=\"C\"+c[s]+\",\"+(e[s+1]+a)+\" \"+l[s]+\",\"+(e[s]+a)+\" \"+(t[s]+r[s])+\",\"+(e[s]+a),u+=\"l-\"+r[s]+\",0 \";return u+=\"Z\"}function R(t){var e=t.dimensions,r=t.model,n=e.map(function(t){return t.categories.map(function(t){return t.y})}),a=t.model.dimensions.map(function(t){return t.categories.map(function(t){return t.displayInd})}),i=t.model.dimensions.map(function(t){return t.displayInd}),o=t.dimensions.map(function(t){return t.model.dimensionInd}),s=e.map(function(t){return t.x}),l=e.map(function(t){return t.width}),c=[];for(var u in r.paths)r.paths.hasOwnProperty(u)&&c.push(r.paths[u]);function h(t){var e=t.categoryInds.map(function(t,e){return a[e][t]});return o.map(function(t){return e[t]})}c.sort(function(e,r){var n=h(e),a=h(r);return\"backward\"===t.sortpaths&&(n.reverse(),a.reverse()),n.push(e.valueInds[0]),a.push(r.valueInds[0]),t.bundlecolors&&(n.unshift(e.rawColor),a.unshift(r.rawColor)),n<a?-1:n>a?1:0});for(var f=new Array(c.length),p=e[0].model.count,d=e[0].categories.map(function(t){return t.height}).reduce(function(t,e){return t+e}),g=0;g<c.length;g++){var v,m=c[g];v=p>0?d*(m.count/p):0;for(var y,x=new Array(n.length),b=0;b<m.categoryInds.length;b++){var _=m.categoryInds[b],w=a[b][_],k=i[b];x[k]=n[k][w],n[k][w]+=v;var T=t.dimensions[k].categories[w],M=T.bands.length,A=T.bands[M-1];if(void 0===A||m.rawColor!==A.rawColor){var S=void 0===A?0:A.y+A.height;T.bands.push({key:S,color:m.color,rawColor:m.rawColor,height:v,width:T.width,count:m.count,y:S,categoryViewModel:T,parcatsViewModel:t})}else{var E=T.bands[M-1];E.height+=v,E.count+=m.count}}y=\"hspline\"===t.pathShape?D(s,x,l,v,.5):D(s,x,l,v,0),f[g]={key:m.valueInds[0],model:m,height:v,leftXs:s,topYs:x,dimWidths:l,svgD:y,parcatsViewModel:t}}t.paths=f}function F(t){var e=t.model.dimensions.map(function(t){return{displayInd:t.displayInd,dimensionInd:t.dimensionInd}});e.sort(function(t,e){return t.displayInd-e.displayInd});var r=[];for(var n in e){var a=e[n].dimensionInd,i=t.model.dimensions[a];r.push(B(t,i))}t.dimensions=r}function B(t,e){var r,n=t.model.dimensions.length,a=e.displayInd;r=40+(n>1?(t.width-80-16)/(n-1):0)*a;var i,o,s,l,c,u=[],h=t.model.maxCats,f=e.categories.length,p=e.count,d=t.height-8*(h-1),g=8*(h-f)/2,v=e.categories.map(function(t){return{displayInd:t.displayInd,categoryInd:t.categoryInd}});for(v.sort(function(t,e){return t.displayInd-e.displayInd}),c=0;c<f;c++)l=v[c].categoryInd,o=e.categories[l],i=p>0?o.count/p*d:0,s={key:o.valueInds[0],model:o,width:16,height:i,y:null!==o.dragY?o.dragY:g,bands:[],parcatsViewModel:t},g=g+i+8,u.push(s);return{key:e.dimensionInd,x:null!==e.dragX?e.dragX:r,y:0,width:16,model:e,categories:u,parcatsViewModel:t,dragCategoryDisplayInd:null,dragDimensionDisplayInd:null,initialDragDimensionDisplayInds:null,initialDragCategoryDisplayInds:null,dragHasMoved:null,potentialClickBand:null}}e.exports=function(t,e,r,n){u(r,t,n,e)}},{\"../../components/drawing\":613,\"../../components/fx\":630,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"../../plot_api/plot_api\":752,d3:165,tinycolor2:536}],1081:[function(t,e,r){\"use strict\";var n=t(\"./parcats\");e.exports=function(t,e,r,a){var i=t._fullLayout,o=i._paper,s=i._size;n(t,o,e,{width:s.w,height:s.h,margin:{t:s.t,r:s.r,b:s.b,l:s.l}},r,a)}},{\"./parcats\":1080}],1082:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/attributes\"),a=t(\"../../plots/cartesian/layout_attributes\"),i=t(\"../../plots/font_attributes\"),o=t(\"../../plots/domain\").attributes,s=t(\"../../lib/extend\").extendFlat,l=t(\"../../plot_api/plot_template\").templatedArray;e.exports={domain:o({name:\"parcoords\",trace:!0,editType:\"plot\"}),labelangle:{valType:\"angle\",dflt:0,editType:\"plot\"},labelside:{valType:\"enumerated\",values:[\"top\",\"bottom\"],dflt:\"top\",editType:\"plot\"},labelfont:i({editType:\"plot\"}),tickfont:i({editType:\"plot\"}),rangefont:i({editType:\"plot\"}),dimensions:l(\"dimension\",{label:{valType:\"string\",editType:\"plot\"},tickvals:s({},a.tickvals,{editType:\"plot\"}),ticktext:s({},a.ticktext,{editType:\"plot\"}),tickformat:s({},a.tickformat,{editType:\"plot\"}),visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},range:{valType:\"info_array\",items:[{valType:\"number\",editType:\"plot\"},{valType:\"number\",editType:\"plot\"}],editType:\"plot\"},constraintrange:{valType:\"info_array\",freeLength:!0,dimensions:\"1-2\",items:[{valType:\"number\",editType:\"plot\"},{valType:\"number\",editType:\"plot\"}],editType:\"plot\"},multiselect:{valType:\"boolean\",dflt:!0,editType:\"plot\"},values:{valType:\"data_array\",editType:\"calc\"},editType:\"calc\"}),line:s({editType:\"calc\"},n(\"line\",{colorscaleDflt:\"Viridis\",autoColorDflt:!1,editTypeOverride:\"calc\"}))}},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plot_api/plot_template\":755,\"../../plots/cartesian/layout_attributes\":777,\"../../plots/domain\":790,\"../../plots/font_attributes\":791}],1083:[function(t,e,r){\"use strict\";var n=t(\"./constants\"),a=t(\"d3\"),i=t(\"../../lib/gup\").keyFun,o=t(\"../../lib/gup\").repeat,s=t(\"../../lib\").sorterAsc,l=n.bar.snapRatio;function c(t,e){return t*(1-l)+e*l}var u=n.bar.snapClose;function h(t,e){return t*(1-u)+e*u}function f(t,e,r,n){if(function(t,e){for(var r=0;r<e.length;r++)if(t>=e[r][0]&&t<=e[r][1])return!0;return!1}(r,n))return r;var a=t?-1:1,i=0,o=e.length-1;if(a<0){var s=i;i=o,o=s}for(var l=e[i],u=l,f=i;a*f<a*o;f+=a){var p=f+a,d=e[p];if(a*r<a*h(l,d))return c(l,u);if(a*r<a*d||p===o)return c(d,l);u=l,l=d}}function p(t){t.attr(\"x\",-n.bar.captureWidth/2).attr(\"width\",n.bar.captureWidth)}function d(t){t.attr(\"visibility\",\"visible\").style(\"visibility\",\"visible\").attr(\"fill\",\"yellow\").attr(\"opacity\",0)}function g(t){if(!t.brush.filterSpecified)return\"0,\"+t.height;for(var e,r,n,a=v(t.brush.filter.getConsolidated(),t.height),i=[0],o=a.length?a[0][0]:null,s=0;s<a.length;s++)r=(e=a[s])[1]-e[0],i.push(o),i.push(r),(n=s+1)<a.length&&(o=a[n][0]-e[1]);return i.push(t.height),i}function v(t,e){return t.map(function(t){return t.map(function(t){return Math.max(0,t*e)}).sort(s)})}function m(){a.select(document.body).style(\"cursor\",null)}function y(t){t.attr(\"stroke-dasharray\",g)}function x(t,e){var r=a.select(t).selectAll(\".highlight, .highlight-shadow\");y(e?r.transition().duration(n.bar.snapDuration).each(\"end\",e):r)}function b(t,e){var r,a=t.brush,i=NaN,o={};if(a.filterSpecified){var s=t.height,l=a.filter.getConsolidated(),c=v(l,s),u=NaN,h=NaN,f=NaN;for(r=0;r<=c.length;r++){var p=c[r];if(p&&p[0]<=e&&e<=p[1]){u=r;break}if(h=r?r-1:NaN,p&&p[0]>e){f=r;break}}if(i=u,isNaN(i)&&(i=isNaN(h)||isNaN(f)?isNaN(h)?f:h:e-c[h][1]<c[f][0]-e?h:f),!isNaN(i)){var d=c[i],g=function(t,e){var r=n.bar.handleHeight;if(!(e>t[1]+r||e<t[0]-r))return e>=.9*t[1]+.1*t[0]?\"n\":e<=.9*t[0]+.1*t[1]?\"s\":\"ns\"}(d,e);g&&(o.interval=l[i],o.intervalPix=d,o.region=g)}}if(t.ordinal&&!o.region){var m=t.unitTickvals,y=t.unitToPaddedPx.invert(e);for(r=0;r<m.length;r++){var x=[.25*m[Math.max(r-1,0)]+.75*m[r],.25*m[Math.min(r+1,m.length-1)]+.75*m[r]];if(y>=x[0]&&y<=x[1]){o.clickableOrdinalRange=x;break}}}return o}function _(t,e){a.event.sourceEvent.stopPropagation();var r=e.height-a.mouse(t)[1]-2*n.verticalPadding,i=e.brush.svgBrush;i.wasDragged=!0,i._dragging=!0,i.grabbingBar?i.newExtent=[r-i.grabPoint,r+i.barLength-i.grabPoint].map(e.unitToPaddedPx.invert):i.newExtent=[i.startExtent,e.unitToPaddedPx.invert(r)].sort(s),e.brush.filterSpecified=!0,i.extent=i.stayingIntervals.concat([i.newExtent]),i.brushCallback(e),x(t.parentNode)}function w(t,e){var r=b(e,e.height-a.mouse(t)[1]-2*n.verticalPadding),i=\"crosshair\";r.clickableOrdinalRange?i=\"pointer\":r.region&&(i=r.region+\"-resize\"),a.select(document.body).style(\"cursor\",i)}function k(t){t.on(\"mousemove\",function(t){a.event.preventDefault(),t.parent.inBrushDrag||w(this,t)}).on(\"mouseleave\",function(t){t.parent.inBrushDrag||m()}).call(a.behavior.drag().on(\"dragstart\",function(t){!function(t,e){a.event.sourceEvent.stopPropagation();var r=e.height-a.mouse(t)[1]-2*n.verticalPadding,i=e.unitToPaddedPx.invert(r),o=e.brush,s=b(e,r),l=s.interval,c=o.svgBrush;if(c.wasDragged=!1,c.grabbingBar=\"ns\"===s.region,c.grabbingBar){var u=l.map(e.unitToPaddedPx);c.grabPoint=r-u[0]-n.verticalPadding,c.barLength=u[1]-u[0]}c.clickableOrdinalRange=s.clickableOrdinalRange,c.stayingIntervals=e.multiselect&&o.filterSpecified?o.filter.getConsolidated():[],l&&(c.stayingIntervals=c.stayingIntervals.filter(function(t){return t[0]!==l[0]&&t[1]!==l[1]})),c.startExtent=s.region?l[\"s\"===s.region?1:0]:i,e.parent.inBrushDrag=!0,c.brushStartCallback()}(this,t)}).on(\"drag\",function(t){_(this,t)}).on(\"dragend\",function(t){!function(t,e){var r=e.brush,n=r.filter,i=r.svgBrush;i._dragging||(w(t,e),_(t,e),e.brush.svgBrush.wasDragged=!1),i._dragging=!1,a.event.sourceEvent.stopPropagation();var o=i.grabbingBar;if(i.grabbingBar=!1,i.grabLocation=void 0,e.parent.inBrushDrag=!1,m(),!i.wasDragged)return i.wasDragged=void 0,i.clickableOrdinalRange?r.filterSpecified&&e.multiselect?i.extent.push(i.clickableOrdinalRange):(i.extent=[i.clickableOrdinalRange],r.filterSpecified=!0):o?(i.extent=i.stayingIntervals,0===i.extent.length&&M(r)):M(r),i.brushCallback(e),x(t.parentNode),void i.brushEndCallback(r.filterSpecified?n.getConsolidated():[]);var s=function(){n.set(n.getConsolidated())};if(e.ordinal){var l=e.unitTickvals;l[l.length-1]<l[0]&&l.reverse(),i.newExtent=[f(0,l,i.newExtent[0],i.stayingIntervals),f(1,l,i.newExtent[1],i.stayingIntervals)];var c=i.newExtent[1]>i.newExtent[0];i.extent=i.stayingIntervals.concat(c?[i.newExtent]:[]),i.extent.length||M(r),i.brushCallback(e),c?x(t.parentNode,s):(s(),x(t.parentNode))}else s();i.brushEndCallback(r.filterSpecified?n.getConsolidated():[])}(this,t)}))}function T(t,e){return t[0]-e[0]}function M(t){t.filterSpecified=!1,t.svgBrush.extent=[[-1/0,1/0]]}function A(t){for(var e,r=t.slice(),n=[],a=r.shift();a;){for(e=a.slice();(a=r.shift())&&a[0]<=e[1];)e[1]=Math.max(e[1],a[1]);n.push(e)}return n}e.exports={makeBrush:function(t,e,r,n,a,i){var o,l=function(){var t,e,r=[];return{set:function(n){1===(r=n.map(function(t){return t.slice().sort(s)}).sort(T)).length&&r[0][0]===-1/0&&r[0][1]===1/0&&(r=[[0,-1]]),t=A(r),e=r.reduce(function(t,e){return[Math.min(t[0],e[0]),Math.max(t[1],e[1])]},[1/0,-1/0])},get:function(){return r.slice()},getConsolidated:function(){return t},getBounds:function(){return e}}}();return l.set(r),{filter:l,filterSpecified:e,svgBrush:{extent:[],brushStartCallback:n,brushCallback:(o=a,function(t){var e=t.brush,r=function(t){return t.svgBrush.extent.map(function(t){return t.slice()})}(e).slice();e.filter.set(r),o()}),brushEndCallback:i}}},ensureAxisBrush:function(t){var e=t.selectAll(\".\"+n.cn.axisBrush).data(o,i);e.enter().append(\"g\").classed(n.cn.axisBrush,!0),function(t){var e=t.selectAll(\".background\").data(o);e.enter().append(\"rect\").classed(\"background\",!0).call(p).call(d).style(\"pointer-events\",\"auto\").attr(\"transform\",\"translate(0 \"+n.verticalPadding+\")\"),e.call(k).attr(\"height\",function(t){return t.height-n.verticalPadding});var r=t.selectAll(\".highlight-shadow\").data(o);r.enter().append(\"line\").classed(\"highlight-shadow\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width+n.bar.strokeWidth).attr(\"stroke\",n.bar.strokeColor).attr(\"opacity\",n.bar.strokeOpacity).attr(\"stroke-linecap\",\"butt\"),r.attr(\"y1\",function(t){return t.height}).call(y);var a=t.selectAll(\".highlight\").data(o);a.enter().append(\"line\").classed(\"highlight\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width-n.bar.strokeWidth).attr(\"stroke\",n.bar.fillColor).attr(\"opacity\",n.bar.fillOpacity).attr(\"stroke-linecap\",\"butt\"),a.attr(\"y1\",function(t){return t.height}).call(y)}(e)},cleanRanges:function(t,e){if(Array.isArray(t[0])?(t=t.map(function(t){return t.sort(s)}),t=e.multiselect?A(t.sort(T)):[t[0]]):t=[t.sort(s)],e.tickvals){var r=e.tickvals.slice().sort(s);if(!(t=t.map(function(t){var e=[f(0,r,t[0],[]),f(1,r,t[1],[])];if(e[1]>e[0])return e}).filter(function(t){return t})).length)return}return t.length>1?t:t[0]}}},{\"../../lib\":717,\"../../lib/gup\":715,\"./constants\":1086,d3:165}],1084:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../plots/get_data\").getModuleCalcData,i=t(\"./plot\"),o=t(\"../../constants/xmlns_namespaces\");r.name=\"parcoords\",r.plot=function(t){var e=a(t.calcdata,\"parcoords\")[0];e.length&&i(t,e)},r.clean=function(t,e,r,n){var a=n._has&&n._has(\"parcoords\"),i=e._has&&e._has(\"parcoords\");a&&!i&&(n._paperdiv.selectAll(\".parcoords\").remove(),n._glimages.selectAll(\"*\").remove())},r.toSVG=function(t){var e=t._fullLayout._glimages,r=n.select(t).selectAll(\".svg-container\");r.filter(function(t,e){return e===r.size()-1}).selectAll(\".gl-canvas-context, .gl-canvas-focus\").each(function(){var t=this.toDataURL(\"image/png\");e.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":t,preserveAspectRatio:\"none\",x:0,y:0,width:this.width,height:this.height})}),window.setTimeout(function(){n.selectAll(\"#filterBarPattern\").attr(\"id\",\"filterBarPattern\")},60)}},{\"../../constants/xmlns_namespaces\":694,\"../../plots/get_data\":800,\"./plot\":1093,d3:165}],1085:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").isArrayOrTypedArray,a=t(\"../../components/colorscale\"),i=t(\"../../lib/gup\").wrap;e.exports=function(t,e){var r,o;return a.hasColorscale(e,\"line\")&&n(e.line.color)?(r=e.line.color,o=a.extractOpts(e.line).colorscale,a.calc(t,e,{vals:r,containerStr:\"line\",cLetter:\"c\"})):(r=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=.5;return e}(e._length),o=[[0,e.line.color],[1,e.line.color]]),i({lineColor:r,cscale:o})}},{\"../../components/colorscale\":604,\"../../lib\":717,\"../../lib/gup\":715}],1086:[function(t,e,r){\"use strict\";e.exports={maxDimensionCount:60,overdrag:45,verticalPadding:2,tickDistance:50,canvasPixelRatio:1,blockLineCount:5e3,layers:[\"contextLineLayer\",\"focusLineLayer\",\"pickLineLayer\"],axisTitleOffset:28,axisExtentOffset:10,deselectedLineColor:\"#777\",bar:{width:4,captureWidth:10,fillColor:\"magenta\",fillOpacity:1,snapDuration:150,snapRatio:.25,snapClose:.01,strokeColor:\"white\",strokeOpacity:1,strokeWidth:1,handleHeight:8,handleOpacity:1,handleOverlap:0},cn:{axisExtentText:\"axis-extent-text\",parcoordsLineLayers:\"parcoords-line-layers\",parcoordsLineLayer:\"parcoords-lines\",parcoords:\"parcoords\",parcoordsControlView:\"parcoords-control-view\",yAxis:\"y-axis\",axisOverlays:\"axis-overlays\",axis:\"axis\",axisHeading:\"axis-heading\",axisTitle:\"axis-title\",axisExtent:\"axis-extent\",axisExtentTop:\"axis-extent-top\",axisExtentTopText:\"axis-extent-top-text\",axisExtentBottom:\"axis-extent-bottom\",axisExtentBottomText:\"axis-extent-bottom-text\",axisBrush:\"axis-brush\"},id:{filterBarPattern:\"filter-bar-pattern\"}}},{}],1087:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/colorscale/helpers\").hasColorscale,i=t(\"../../components/colorscale/defaults\"),o=t(\"../../plots/domain\").defaults,s=t(\"../../plots/array_container_defaults\"),l=t(\"../../plots/cartesian/axes\"),c=t(\"./attributes\"),u=t(\"./axisbrush\"),h=t(\"./constants\").maxDimensionCount,f=t(\"./merge_length\");function p(t,e,r,a){function i(r,a){return n.coerce(t,e,c.dimensions,r,a)}var o=i(\"values\"),s=i(\"visible\");if(o&&o.length||(s=e.visible=!1),s){i(\"label\"),i(\"tickvals\"),i(\"ticktext\"),i(\"tickformat\");var h=i(\"range\");e._ax={_id:\"y\",type:\"linear\",showexponent:\"all\",exponentformat:\"B\",range:h},l.setConvert(e._ax,a.layout),i(\"multiselect\");var f=i(\"constraintrange\");f&&(e.constraintrange=u.cleanRanges(f,e))}}e.exports=function(t,e,r,l){function u(r,a){return n.coerce(t,e,c,r,a)}var d=t.dimensions;Array.isArray(d)&&d.length>h&&(n.log(\"parcoords traces support up to \"+h+\" dimensions at the moment\"),d.splice(h));var g=s(t,e,{name:\"dimensions\",layout:l,handleItemDefaults:p}),v=function(t,e,r,o,s){var l=s(\"line.color\",r);if(a(t,\"line\")&&n.isArrayOrTypedArray(l)){if(l.length)return s(\"line.colorscale\"),i(t,e,o,s,{prefix:\"line.\",cLetter:\"c\"}),l.length;e.line.color=r}return 1/0}(t,e,r,l,u);o(e,l,u),Array.isArray(g)&&g.length||(e.visible=!1),f(e,g,\"values\",v);var m={family:l.font.family,size:Math.round(l.font.size/1.2),color:l.font.color};n.coerceFont(u,\"labelfont\",m),n.coerceFont(u,\"tickfont\",m),n.coerceFont(u,\"rangefont\",m),u(\"labelangle\"),u(\"labelside\")}},{\"../../components/colorscale/defaults\":602,\"../../components/colorscale/helpers\":603,\"../../lib\":717,\"../../plots/array_container_defaults\":761,\"../../plots/cartesian/axes\":765,\"../../plots/domain\":790,\"./attributes\":1082,\"./axisbrush\":1083,\"./constants\":1086,\"./merge_length\":1091}],1088:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").isTypedArray;r.convertTypedArray=function(t){return n(t)?Array.prototype.slice.call(t):t},r.isOrdinal=function(t){return!!t.tickvals},r.isVisible=function(t){return t.visible||!(\"visible\"in t)}},{\"../../lib\":717}],1089:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"./plot\"),colorbar:{container:\"line\",min:\"cmin\",max:\"cmax\"},moduleType:\"trace\",name:\"parcoords\",basePlotModule:t(\"./base_plot\"),categories:[\"gl\",\"regl\",\"noOpacity\",\"noHover\"],meta:{}}},{\"./attributes\":1082,\"./base_plot\":1084,\"./calc\":1085,\"./defaults\":1087,\"./plot\":1093}],1090:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nattribute vec4 p01_04, p05_08, p09_12, p13_16,\\n               p17_20, p21_24, p25_28, p29_32,\\n               p33_36, p37_40, p41_44, p45_48,\\n               p49_52, p53_56, p57_60, colors;\\n\\nuniform mat4 dim0A, dim1A, dim0B, dim1B, dim0C, dim1C, dim0D, dim1D,\\n             loA, hiA, loB, hiB, loC, hiC, loD, hiD;\\n\\nuniform vec2 resolution, viewBoxPos, viewBoxSize;\\nuniform sampler2D mask, palette;\\nuniform float maskHeight;\\nuniform float drwLayer; // 0: context, 1: focus, 2: pick\\nuniform vec4 contextColor;\\n\\nbool isPick    = (drwLayer > 1.5);\\nbool isContext = (drwLayer < 0.5);\\n\\nconst vec4 ZEROS = vec4(0.0, 0.0, 0.0, 0.0);\\nconst vec4 UNITS = vec4(1.0, 1.0, 1.0, 1.0);\\n\\nfloat val(mat4 p, mat4 v) {\\n    return dot(matrixCompMult(p, v) * UNITS, UNITS);\\n}\\n\\nfloat axisY(float ratio, mat4 A, mat4 B, mat4 C, mat4 D) {\\n    float y1 = val(A, dim0A) + val(B, dim0B) + val(C, dim0C) + val(D, dim0D);\\n    float y2 = val(A, dim1A) + val(B, dim1B) + val(C, dim1C) + val(D, dim1D);\\n    return y1 * (1.0 - ratio) + y2 * ratio;\\n}\\n\\nint iMod(int a, int b) {\\n    return a - b * (a / b);\\n}\\n\\nbool fOutside(float p, float lo, float hi) {\\n    return (lo < hi) && (lo > p || p > hi);\\n}\\n\\nbool vOutside(vec4 p, vec4 lo, vec4 hi) {\\n    return (\\n        fOutside(p[0], lo[0], hi[0]) ||\\n        fOutside(p[1], lo[1], hi[1]) ||\\n        fOutside(p[2], lo[2], hi[2]) ||\\n        fOutside(p[3], lo[3], hi[3])\\n    );\\n}\\n\\nbool mOutside(mat4 p, mat4 lo, mat4 hi) {\\n    return (\\n        vOutside(p[0], lo[0], hi[0]) ||\\n        vOutside(p[1], lo[1], hi[1]) ||\\n        vOutside(p[2], lo[2], hi[2]) ||\\n        vOutside(p[3], lo[3], hi[3])\\n    );\\n}\\n\\nbool outsideBoundingBox(mat4 A, mat4 B, mat4 C, mat4 D) {\\n    return mOutside(A, loA, hiA) ||\\n           mOutside(B, loB, hiB) ||\\n           mOutside(C, loC, hiC) ||\\n           mOutside(D, loD, hiD);\\n}\\n\\nbool outsideRasterMask(mat4 A, mat4 B, mat4 C, mat4 D) {\\n    mat4 pnts[4];\\n    pnts[0] = A;\\n    pnts[1] = B;\\n    pnts[2] = C;\\n    pnts[3] = D;\\n\\n    for(int i = 0; i < 4; ++i) {\\n        for(int j = 0; j < 4; ++j) {\\n            for(int k = 0; k < 4; ++k) {\\n                if(0 == iMod(\\n                    int(255.0 * texture2D(mask,\\n                        vec2(\\n                            (float(i * 2 + j / 2) + 0.5) / 8.0,\\n                            (pnts[i][j][k] * (maskHeight - 1.0) + 1.0) / maskHeight\\n                        ))[3]\\n                    ) / int(pow(2.0, float(iMod(j * 4 + k, 8)))),\\n                    2\\n                )) return true;\\n            }\\n        }\\n    }\\n    return false;\\n}\\n\\nvec4 position(bool isContext, float v, mat4 A, mat4 B, mat4 C, mat4 D) {\\n    float x = 0.5 * sign(v) + 0.5;\\n    float y = axisY(x, A, B, C, D);\\n    float z = 1.0 - abs(v);\\n\\n    z += isContext ? 0.0 : 2.0 * float(\\n        outsideBoundingBox(A, B, C, D) ||\\n        outsideRasterMask(A, B, C, D)\\n    );\\n\\n    return vec4(\\n        2.0 * (vec2(x, y) * viewBoxSize + viewBoxPos) / resolution - 1.0,\\n        z,\\n        1.0\\n    );\\n}\\n\\nvoid main() {\\n    mat4 A = mat4(p01_04, p05_08, p09_12, p13_16);\\n    mat4 B = mat4(p17_20, p21_24, p25_28, p29_32);\\n    mat4 C = mat4(p33_36, p37_40, p41_44, p45_48);\\n    mat4 D = mat4(p49_52, p53_56, p57_60, ZEROS);\\n\\n    float v = colors[3];\\n\\n    gl_Position = position(isContext, v, A, B, C, D);\\n\\n    fragColor =\\n        isContext ? vec4(contextColor) :\\n        isPick ? vec4(colors.rgb, 1.0) : texture2D(palette, vec2(abs(v), 0.5));\\n}\\n\"]),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n    gl_FragColor = fragColor;\\n}\\n\"]),o=t(\"./constants\").maxDimensionCount,s=t(\"../../lib\"),l=1e-6,c=2048,u=new Uint8Array(4),h=new Uint8Array(4),f={shape:[256,1],format:\"rgba\",type:\"uint8\",mag:\"nearest\",min:\"nearest\"};function p(t,e,r,n,a){var i=t._gl;i.enable(i.SCISSOR_TEST),i.scissor(e,r,n,a),t.clear({color:[0,0,0,0],depth:1})}function d(t,e,r,n,a,i){var o=i.key;r.drawCompleted||(!function(t){t.read({x:0,y:0,width:1,height:1,data:u})}(t),r.drawCompleted=!0),function s(l){var c=Math.min(n,a-l*n);0===l&&(window.cancelAnimationFrame(r.currentRafs[o]),delete r.currentRafs[o],p(t,i.scissorX,i.scissorY,i.scissorWidth,i.viewBoxSize[1])),r.clearOnly||(i.count=2*c,i.offset=2*l*n,e(i),l*n+c<a&&(r.currentRafs[o]=window.requestAnimationFrame(function(){s(l+1)})),r.drawCompleted=!1)}(0)}function g(t,e){for(var r=new Array(256),n=0;n<256;n++)r[n]=t(n/255).concat(e);return r}function v(t,e){return(t>>>8*e)%256/255}function m(t,e,r){for(var n=new Array(8*e),a=0,i=0;i<e;i++)for(var o=0;o<2;o++)for(var s=0;s<4;s++){var l=4*t+s,c=r[64*i+l];63===l&&0===o&&(c*=-1),n[a++]=c}return n}function y(t){var e=\"0\"+t;return e.substr(e.length-2)}function x(t){return t<o?\"p\"+y(t+1)+\"_\"+y(t+4):\"colors\"}function b(t,e,r,n,a,i,o,l,c,u,h,f,p){for(var d=[[],[]],g=0;g<64;g++)d[0][g]=g===a?1:0,d[1][g]=g===i?1:0;var v=t.lines.canvasOverdrag,m=t.domain,y=t.canvasWidth,x=t.canvasHeight,b=t.deselectedLines.color;return s.extendFlat({key:h,resolution:[y,x],viewBoxPos:[o+v,l],viewBoxSize:[c,u],i0:a,i1:i,dim0A:d[0].slice(0,16),dim0B:d[0].slice(16,32),dim0C:d[0].slice(32,48),dim0D:d[0].slice(48,64),dim1A:d[1].slice(0,16),dim1B:d[1].slice(16,32),dim1C:d[1].slice(32,48),dim1D:d[1].slice(48,64),drwLayer:f,contextColor:[b[0]/255,b[1]/255,b[2]/255,b[3]<1?b[3]:Math.max(1/255,Math.pow(1/t.lines.color.length,1/3))],scissorX:(n===e?0:o+v)+(t.pad.l-v)+t.layoutWidth*m.x[0],scissorWidth:(n===r?y-o+v:c+.5)+(n===e?o+v:0),scissorY:l+t.pad.b+t.layoutHeight*m.y[0],scissorHeight:u,viewportX:t.pad.l-v+t.layoutWidth*m.x[0],viewportY:t.pad.b+t.layoutHeight*m.y[0],viewportWidth:y,viewportHeight:x},p)}function _(t){var e=c-1,r=Math.max(0,Math.floor(t[0]*e),0),n=Math.min(e,Math.ceil(t[1]*e),e);return[Math.min(r,n),Math.max(r,n)]}e.exports=function(t,e){var r,n,u,y,w,k=e.context,T=e.pick,M=e.regl,A={currentRafs:{},drawCompleted:!0,clearOnly:!1},S=function(t){for(var e={},r=0;r<=o;r+=4)e[x(r)]=t.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array(0)});return e}(M),E=M.texture(f),L=[];P(e);var C=M({profile:!1,blend:{enable:k,func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:1,dstAlpha:1},equation:{rgb:\"add\",alpha:\"add\"},color:[0,0,0,0]},depth:{enable:!k,mask:!0,func:\"less\",range:[0,1]},cull:{enable:!0,face:\"back\"},scissor:{enable:!0,box:{x:M.prop(\"scissorX\"),y:M.prop(\"scissorY\"),width:M.prop(\"scissorWidth\"),height:M.prop(\"scissorHeight\")}},viewport:{x:M.prop(\"viewportX\"),y:M.prop(\"viewportY\"),width:M.prop(\"viewportWidth\"),height:M.prop(\"viewportHeight\")},dither:!1,vert:a,frag:i,primitive:\"lines\",lineWidth:1,attributes:S,uniforms:{resolution:M.prop(\"resolution\"),viewBoxPos:M.prop(\"viewBoxPos\"),viewBoxSize:M.prop(\"viewBoxSize\"),dim0A:M.prop(\"dim0A\"),dim1A:M.prop(\"dim1A\"),dim0B:M.prop(\"dim0B\"),dim1B:M.prop(\"dim1B\"),dim0C:M.prop(\"dim0C\"),dim1C:M.prop(\"dim1C\"),dim0D:M.prop(\"dim0D\"),dim1D:M.prop(\"dim1D\"),loA:M.prop(\"loA\"),hiA:M.prop(\"hiA\"),loB:M.prop(\"loB\"),hiB:M.prop(\"hiB\"),loC:M.prop(\"loC\"),hiC:M.prop(\"hiC\"),loD:M.prop(\"loD\"),hiD:M.prop(\"hiD\"),palette:E,contextColor:M.prop(\"contextColor\"),mask:M.prop(\"maskTexture\"),drwLayer:M.prop(\"drwLayer\"),maskHeight:M.prop(\"maskHeight\")},offset:M.prop(\"offset\"),count:M.prop(\"count\")});function P(t){r=t.model,n=t.viewModel,u=n.dimensions.slice(),y=u[0]?u[0].values.length:0;var e=r.lines,a=T?e.color.map(function(t,r){return r/e.color.length}):e.color,i=function(t,e,r){for(var n,a=new Array(t*(o+4)),i=0,s=0;s<t;s++){for(var c=0;c<o;c++)a[i++]=c<e.length?e[c].paddedUnitValues[s]:.5;a[i++]=v(s,2),a[i++]=v(s,1),a[i++]=v(s,0),a[i++]=(n=r[s],Math.max(l,Math.min(1-l,n)))}return a}(y,u,a);!function(t,e,r){for(var n=0;n<=o;n+=4)t[x(n)](m(n/4,e,r))}(S,y,i),k||T||(E=M.texture(s.extendFlat({data:g(r.unitToColor,255)},f)))}return{render:function(t,e,n){var a,i,o,s=t.length,l=1/0,h=-1/0;for(a=0;a<s;a++)t[a].dim0.canvasX<l&&(l=t[a].dim0.canvasX,i=a),t[a].dim1.canvasX>h&&(h=t[a].dim1.canvasX,o=a);0===s&&p(M,0,0,r.canvasWidth,r.canvasHeight);var f=function(t){var e,r,n,a=[[],[]];for(n=0;n<64;n++){var i=!t&&n<u.length?u[n].brush.filter.getBounds():[-1/0,1/0];a[0][n]=i[0],a[1][n]=i[1]}var o=8*c,s=new Array(o);for(e=0;e<o;e++)s[e]=255;if(!t)for(e=0;e<u.length;e++){var l=e%8,h=(e-l)/8,f=Math.pow(2,l),p=u[e].brush.filter.get();if(!(p.length<2)){var d=_(p[0])[1];for(r=1;r<p.length;r++){var g=_(p[r]);for(n=d+1;n<g[0];n++)s[8*n+h]&=~f;d=Math.max(d,g[1])}}}var v={shape:[8,c],format:\"alpha\",type:\"uint8\",mag:\"nearest\",min:\"nearest\",data:s};return w?w(v):w=M.texture(v),{maskTexture:w,maskHeight:c,loA:a[0].slice(0,16),loB:a[0].slice(16,32),loC:a[0].slice(32,48),loD:a[0].slice(48,64),hiA:a[1].slice(0,16),hiB:a[1].slice(16,32),hiC:a[1].slice(32,48),hiD:a[1].slice(48,64)}}(k);for(a=0;a<s;a++){var g=t[a],v=g.dim0.crossfilterDimensionIndex,m=g.dim1.crossfilterDimensionIndex,x=g.canvasX,S=g.canvasY,E=x+g.panelSizeX;if(e||!L[v]||L[v][0]!==x||L[v][1]!==E){L[v]=[x,E];var P=b(r,i,o,a,v,m,x,S,g.panelSizeX,g.panelSizeY,g.dim0.crossfilterDimensionIndex,k?0:T?2:1,f);A.clearOnly=n;var O=e?r.lines.blockLineCount:y;d(M,C,A,O,y,P)}}},readPixel:function(t,e){return M.read({x:t,y:e,width:1,height:1,data:h}),h},readPixels:function(t,e,r,n){var a=new Uint8Array(4*r*n);return M.read({x:t,y:e,width:r,height:n,data:a}),a},destroy:function(){for(var e in t.style[\"pointer-events\"]=\"none\",E.destroy(),w&&w.destroy(),S)S[e].destroy()},update:P}}},{\"../../lib\":717,\"./constants\":1086,glslify:411}],1091:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n){var a,i;for(n||(n=1/0),a=0;a<e.length;a++)(i=e[a]).visible&&(n=Math.min(n,i[r].length));for(n===1/0&&(n=0),t._length=n,a=0;a<e.length;a++)(i=e[a]).visible&&(i._length=n);return n}},{}],1092:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"color-rgba\"),i=t(\"../../plots/cartesian/axes\"),o=t(\"../../lib\"),s=t(\"../../lib/svg_text_utils\"),l=t(\"../../components/drawing\"),c=t(\"../../components/colorscale\"),u=t(\"../../lib/gup\"),h=u.keyFun,f=u.repeat,p=u.unwrap,d=t(\"./helpers\"),g=t(\"./constants\"),v=t(\"./axisbrush\"),m=t(\"./lines\");function y(t,e,r){return o.aggNums(t,null,e,r)}function x(t,e){return _(y(Math.min,t,e),y(Math.max,t,e))}function b(t){var e=t.range;return e?_(e[0],e[1]):x(t.values,t._length)}function _(t,e){return!isNaN(t)&&isFinite(t)||(t=0),!isNaN(e)&&isFinite(e)||(e=0),t===e&&(0===t?(t-=1,e+=1):(t*=.9,e*=1.1)),[t,e]}function w(t,e,r,a,i){var o,s,l=b(r);return a?n.scale.ordinal().domain(a.map((o=n.format(r.tickformat),s=i,s?function(t,e){var r=s[e];return null==r?o(t):r}:o))).range(a.map(function(r){var n=(r-l[0])/(l[1]-l[0]);return t-e+n*(2*e-t)})):n.scale.linear().domain(l).range([t-e,e])}function k(t){if(t.tickvals){var e=b(t);return n.scale.ordinal().domain(t.tickvals).range(t.tickvals.map(function(t){return(t-e[0])/(e[1]-e[0])}))}}function T(t){var e=t.map(function(t){return t[0]}),r=t.map(function(t){var e=a(t[1]);return n.rgb(\"rgb(\"+e[0]+\",\"+e[1]+\",\"+e[2]+\")\")}),i=\"rgb\".split(\"\").map(function(t){return n.scale.linear().clamp(!0).domain(e).range(r.map((a=t,function(t){return t[a]})));var a});return function(t){return i.map(function(e){return e(t)})}}function M(t){return t.dimensions.some(function(t){return t.brush.filterSpecified})}function A(t,e,r){var a=r.width,i=r.height,s=r.dimensions,l=r.canvasPixelRatio,c=function(t){return a*t/Math.max(1,r.colCount-1)},u=g.verticalPadding/i,h=function(t,e){return n.scale.linear().range([e,t-e])}(i,g.verticalPadding),f={key:r.key,xScale:c,model:r,inBrushDrag:!1},p={};return f.dimensions=s.filter(d.isVisible).map(function(a,s){var m=function(t,e){return n.scale.linear().domain(b(t)).range([e,1-e])}(a,u),y=p[a.label];p[a.label]=(y||0)+1;var x=a.label+(y?\"__\"+y:\"\"),_=a.constraintrange,T=_&&_.length;T&&!Array.isArray(_[0])&&(_=[_]);var A=T?_.map(function(t){return t.map(m)}):[[-1/0,1/0]],S=a.values;S.length>a._length&&(S=S.slice(0,a._length));var E,L=a.tickvals;function C(t,e){return{val:t,text:E[e]}}function P(t,e){return t.val-e.val}if(Array.isArray(L)&&L.length){E=a.ticktext,Array.isArray(E)&&E.length?E.length>L.length?E=E.slice(0,L.length):L.length>E.length&&(L=L.slice(0,E.length)):E=L.map(n.format(a.tickformat));for(var O=1;O<L.length;O++)if(L[O]<L[O-1]){for(var z=L.map(C).sort(P),I=0;I<L.length;I++)L[I]=z[I].val,E[I]=z[I].text;break}}else L=void 0;return S=d.convertTypedArray(S),{key:x,label:a.label,tickFormat:a.tickformat,tickvals:L,ticktext:E,ordinal:d.isOrdinal(a),multiselect:a.multiselect,xIndex:s,crossfilterDimensionIndex:s,visibleIndex:a._index,height:i,values:S,paddedUnitValues:S.map(m),unitTickvals:L&&L.map(m),xScale:c,x:c(s),canvasX:c(s)*l,unitToPaddedPx:h,domainScale:w(i,g.verticalPadding,a,L,E),ordinalScale:k(a),parent:f,model:r,brush:v.makeBrush(t,T,A,function(){t.linePickActive(!1)},function(){var e=f;e.focusLayer&&e.focusLayer.render(e.panels,!0);var r=M(e);!t.contextShown()&&r?(e.contextLayer&&e.contextLayer.render(e.panels,!0),t.contextShown(!0)):t.contextShown()&&!r&&(e.contextLayer&&e.contextLayer.render(e.panels,!0,!0),t.contextShown(!1))},function(r){if(f.focusLayer.render(f.panels,!0),f.pickLayer&&f.pickLayer.render(f.panels,!0),t.linePickActive(!0),e&&e.filterChanged){var n=m.invert,i=r.map(function(t){return t.map(n).sort(o.sorterAsc)}).sort(function(t,e){return t[0]-e[0]});e.filterChanged(f.key,a._index,i)}})}}),f}function S(t){t.classed(g.cn.axisExtentText,!0).attr(\"text-anchor\",\"middle\").style(\"cursor\",\"default\").style(\"user-select\",\"none\")}function E(t,e){var r=\"top\"===e?1:-1,n=t*Math.PI/180;return{dir:r,dx:Math.sin(n),dy:Math.cos(n),degrees:t}}function L(t,e){for(var r=e.panels||(e.panels=[]),n=t.data(),a=0;a<n.length-1;a++){var i=r[a]||(r[a]={}),o=n[a],s=n[a+1];i.dim0=o,i.dim1=s,i.canvasX=o.canvasX,i.panelSizeX=s.canvasX-o.canvasX,i.panelSizeY=e.model.canvasHeight,i.y=0,i.canvasY=0}}function C(t,e){return i.tickText(t._ax,e,!1).text}function P(t,e){if(t.ordinal)return\"\";var r=t.domainScale.domain(),n=r[e?r.length-1:0];return C(t.model.dimensions[t.visibleIndex],n)}e.exports=function(t,e,r,u){var y=t._fullLayout,w=y._toppaper,k=y._glcontainer;!function(t){for(var e=0;e<t.length;e++)for(var r=0;r<t[e].length;r++)for(var n=t[e][r].trace,a=n.dimensions,o=0;o<a.length;o++){var s=a[o].values,l=a[o]._ax;l&&(l.range?l.range=_(l.range[0],l.range[1]):l.range=x(s,n._length),l.dtick||(l.dtick=.01*(Math.abs(l.range[1]-l.range[0])||1)),l.tickformat=a[o].tickformat,i.calcTicks(l),l.cleanRange())}}(e);var O,z,I=(O=!0,z=!1,{linePickActive:function(t){return arguments.length?O=!!t:O},contextShown:function(t){return arguments.length?z=!!t:z}}),D=e.filter(function(t){return p(t).trace.visible}).map(function(t,e,r){var i=p(e),s=i.trace,l=d.convertTypedArray(i.lineColor),u=s.line,h={color:a(g.deselectedLineColor)},f=c.extractOpts(u),v=f.reversescale?c.flipScale(i.cscale):i.cscale,m=s.domain,y=s.dimensions,x=t.width,_=s.labelangle,w=s.labelside,k=s.labelfont,M=s.tickfont,A=s.rangefont,S=o.extendDeepNoArrays({},u,{color:l.map(n.scale.linear().domain(b({values:l,range:[f.min,f.max],_length:s._length}))),blockLineCount:g.blockLineCount,canvasOverdrag:g.overdrag*g.canvasPixelRatio}),E=Math.floor(x*(m.x[1]-m.x[0])),L=Math.floor(t.height*(m.y[1]-m.y[0])),C=t.margin||{l:80,r:80,t:100,b:80},P=E,O=L;return{key:r,colCount:y.filter(d.isVisible).length,dimensions:y,tickDistance:g.tickDistance,unitToColor:T(v),lines:S,deselectedLines:h,labelAngle:_,labelSide:w,labelFont:k,tickFont:M,rangeFont:A,layoutWidth:x,layoutHeight:t.height,domain:m,translateX:m.x[0]*x,translateY:t.height-m.y[1]*t.height,pad:C,canvasWidth:P*g.canvasPixelRatio+2*S.canvasOverdrag,canvasHeight:O*g.canvasPixelRatio,width:P,height:O,canvasPixelRatio:g.canvasPixelRatio}}.bind(0,r)).map(A.bind(0,I,u));k.each(function(t,e){return o.extendFlat(t,D[e])});var R=k.selectAll(\".gl-canvas\").each(function(t){t.viewModel=D[0],t.model=t.viewModel?t.viewModel.model:null}),F=null;R.filter(function(t){return t.pick}).style(\"pointer-events\",\"auto\").on(\"mousemove\",function(t){if(I.linePickActive()&&t.lineLayer&&u&&u.hover){var e=n.event,r=this.width,a=this.height,i=n.mouse(this),o=i[0],s=i[1];if(o<0||s<0||o>=r||s>=a)return;var l=t.lineLayer.readPixel(o,a-1-s),c=0!==l[3],h=c?l[2]+256*(l[1]+256*l[0]):null,f={x:o,y:s,clientX:e.clientX,clientY:e.clientY,dataIndex:t.model.key,curveNumber:h};h!==F&&(c?u.hover(f):u.unhover&&u.unhover(f),F=h)}}),R.style(\"opacity\",function(t){return t.pick?0:1}),w.style(\"background\",\"rgba(255, 255, 255, 0)\");var B=w.selectAll(\".\"+g.cn.parcoords).data(D,h);B.exit().remove(),B.enter().append(\"g\").classed(g.cn.parcoords,!0).style(\"shape-rendering\",\"crispEdges\").style(\"pointer-events\",\"none\"),B.attr(\"transform\",function(t){return\"translate(\"+t.model.translateX+\",\"+t.model.translateY+\")\"});var N=B.selectAll(\".\"+g.cn.parcoordsControlView).data(f,h);N.enter().append(\"g\").classed(g.cn.parcoordsControlView,!0),N.attr(\"transform\",function(t){return\"translate(\"+t.model.pad.l+\",\"+t.model.pad.t+\")\"});var j=N.selectAll(\".\"+g.cn.yAxis).data(function(t){return t.dimensions},h);j.enter().append(\"g\").classed(g.cn.yAxis,!0),N.each(function(t){L(j,t)}),R.each(function(t){if(t.viewModel){!t.lineLayer||u?t.lineLayer=m(this,t):t.lineLayer.update(t),(t.key||0===t.key)&&(t.viewModel[t.key]=t.lineLayer);var e=!t.context||u;t.lineLayer.render(t.viewModel.panels,e)}}),j.attr(\"transform\",function(t){return\"translate(\"+t.xScale(t.xIndex)+\", 0)\"}),j.call(n.behavior.drag().origin(function(t){return t}).on(\"drag\",function(t){var e=t.parent;I.linePickActive(!1),t.x=Math.max(-g.overdrag,Math.min(t.model.width+g.overdrag,n.event.x)),t.canvasX=t.x*t.model.canvasPixelRatio,j.sort(function(t,e){return t.x-e.x}).each(function(e,r){e.xIndex=r,e.x=t===e?e.x:e.xScale(e.xIndex),e.canvasX=e.x*e.model.canvasPixelRatio}),L(j,e),j.filter(function(e){return 0!==Math.abs(t.xIndex-e.xIndex)}).attr(\"transform\",function(t){return\"translate(\"+t.xScale(t.xIndex)+\", 0)\"}),n.select(this).attr(\"transform\",\"translate(\"+t.x+\", 0)\"),j.each(function(r,n,a){a===t.parent.key&&(e.dimensions[n]=r)}),e.contextLayer&&e.contextLayer.render(e.panels,!1,!M(e)),e.focusLayer.render&&e.focusLayer.render(e.panels)}).on(\"dragend\",function(t){var e=t.parent;t.x=t.xScale(t.xIndex),t.canvasX=t.x*t.model.canvasPixelRatio,L(j,e),n.select(this).attr(\"transform\",function(t){return\"translate(\"+t.x+\", 0)\"}),e.contextLayer&&e.contextLayer.render(e.panels,!1,!M(e)),e.focusLayer&&e.focusLayer.render(e.panels),e.pickLayer&&e.pickLayer.render(e.panels,!0),I.linePickActive(!0),u&&u.axesMoved&&u.axesMoved(e.key,e.dimensions.map(function(t){return t.crossfilterDimensionIndex}))})),j.exit().remove();var V=j.selectAll(\".\"+g.cn.axisOverlays).data(f,h);V.enter().append(\"g\").classed(g.cn.axisOverlays,!0),V.selectAll(\".\"+g.cn.axis).remove();var U=V.selectAll(\".\"+g.cn.axis).data(f,h);U.enter().append(\"g\").classed(g.cn.axis,!0),U.each(function(t){var e=t.model.height/t.model.tickDistance,r=t.domainScale,a=r.domain();n.select(this).call(n.svg.axis().orient(\"left\").tickSize(4).outerTickSize(2).ticks(e,t.tickFormat).tickValues(t.ordinal?a:null).tickFormat(function(e){return d.isOrdinal(t)?e:C(t.model.dimensions[t.visibleIndex],e)}).scale(r)),l.font(U.selectAll(\"text\"),t.model.tickFont)}),U.selectAll(\".domain, .tick>line\").attr(\"fill\",\"none\").attr(\"stroke\",\"black\").attr(\"stroke-opacity\",.25).attr(\"stroke-width\",\"1px\"),U.selectAll(\"text\").style(\"text-shadow\",\"1px 1px 1px #fff, -1px -1px 1px #fff, 1px -1px 1px #fff, -1px 1px 1px #fff\").style(\"cursor\",\"default\").style(\"user-select\",\"none\");var q=V.selectAll(\".\"+g.cn.axisHeading).data(f,h);q.enter().append(\"g\").classed(g.cn.axisHeading,!0);var H=q.selectAll(\".\"+g.cn.axisTitle).data(f,h);H.enter().append(\"text\").classed(g.cn.axisTitle,!0).attr(\"text-anchor\",\"middle\").style(\"cursor\",\"ew-resize\").style(\"user-select\",\"none\").style(\"pointer-events\",\"auto\"),H.text(function(t){return t.label}).each(function(e){var r=n.select(this);l.font(r,e.model.labelFont),s.convertToTspans(r,t)}).attr(\"transform\",function(t){var e=E(t.model.labelAngle,t.model.labelSide),r=g.axisTitleOffset;return(e.dir>0?\"\":\"translate(0,\"+(2*r+t.model.height)+\")\")+\"rotate(\"+e.degrees+\")translate(\"+-r*e.dx+\",\"+-r*e.dy+\")\"}).attr(\"text-anchor\",function(t){var e=E(t.model.labelAngle,t.model.labelSide);return 2*Math.abs(e.dx)>Math.abs(e.dy)?e.dir*e.dx<0?\"start\":\"end\":\"middle\"});var G=V.selectAll(\".\"+g.cn.axisExtent).data(f,h);G.enter().append(\"g\").classed(g.cn.axisExtent,!0);var Y=G.selectAll(\".\"+g.cn.axisExtentTop).data(f,h);Y.enter().append(\"g\").classed(g.cn.axisExtentTop,!0),Y.attr(\"transform\",\"translate(0,\"+-g.axisExtentOffset+\")\");var W=Y.selectAll(\".\"+g.cn.axisExtentTopText).data(f,h);W.enter().append(\"text\").classed(g.cn.axisExtentTopText,!0).call(S),W.text(function(t){return P(t,!0)}).each(function(t){l.font(n.select(this),t.model.rangeFont)});var X=G.selectAll(\".\"+g.cn.axisExtentBottom).data(f,h);X.enter().append(\"g\").classed(g.cn.axisExtentBottom,!0),X.attr(\"transform\",function(t){return\"translate(0,\"+(t.model.height+g.axisExtentOffset)+\")\"});var Z=X.selectAll(\".\"+g.cn.axisExtentBottomText).data(f,h);Z.enter().append(\"text\").classed(g.cn.axisExtentBottomText,!0).attr(\"dy\",\"0.75em\").call(S),Z.text(function(t){return P(t,!1)}).each(function(t){l.font(n.select(this),t.model.rangeFont)}),v.ensureAxisBrush(V)}},{\"../../components/colorscale\":604,\"../../components/drawing\":613,\"../../lib\":717,\"../../lib/gup\":715,\"../../lib/svg_text_utils\":741,\"../../plots/cartesian/axes\":765,\"./axisbrush\":1083,\"./constants\":1086,\"./helpers\":1088,\"./lines\":1090,\"color-rgba\":124,d3:165}],1093:[function(t,e,r){\"use strict\";var n=t(\"./parcoords\"),a=t(\"../../lib/prepare_regl\"),i=t(\"./helpers\").isVisible;function o(t,e,r){var n=e.indexOf(r),a=t.indexOf(n);return-1===a&&(a+=e.length),a}e.exports=function(t,e){var r=t._fullLayout;if(a(t)){var s={},l={},c={},u={},h=r._size;e.forEach(function(e,r){var n=e[0].trace;c[r]=n.index;var a=u[r]=n._fullInput.index;s[r]=t.data[a].dimensions,l[r]=t.data[a].dimensions.slice()});n(t,e,{width:h.w,height:h.h,margin:{t:h.t,r:h.r,b:h.b,l:h.l}},{filterChanged:function(e,n,a){var i=l[e][n],o=a.map(function(t){return t.slice()}),s=\"dimensions[\"+n+\"].constraintrange\",h=r._tracePreGUI[t._fullData[c[e]]._fullInput.uid];if(void 0===h[s]){var f=i.constraintrange;h[s]=f||null}var p=t._fullData[c[e]].dimensions[n];o.length?(1===o.length&&(o=o[0]),i.constraintrange=o,p.constraintrange=o.slice(),o=[o]):(delete i.constraintrange,delete p.constraintrange,o=null);var d={};d[s]=o,t.emit(\"plotly_restyle\",[d,[u[e]]])},hover:function(e){t.emit(\"plotly_hover\",e)},unhover:function(e){t.emit(\"plotly_unhover\",e)},axesMoved:function(e,r){var n=function(t,e){return function(r,n){return o(t,e,r)-o(t,e,n)}}(r,l[e].filter(i));s[e].sort(n),l[e].filter(function(t){return!i(t)}).sort(function(t){return l[e].indexOf(t)}).forEach(function(t){s[e].splice(s[e].indexOf(t),1),s[e].splice(l[e].indexOf(t),0,t)}),t.emit(\"plotly_restyle\",[{dimensions:[s[e]]},[u[e]]])}})}}},{\"../../lib/prepare_regl\":730,\"./helpers\":1088,\"./parcoords\":1092}],1094:[function(t,e,r){\"use strict\";var n=t(\"../../plots/attributes\"),a=t(\"../../plots/domain\").attributes,i=t(\"../../plots/font_attributes\"),o=t(\"../../components/color/attributes\"),s=t(\"../../plots/template_attributes\").hovertemplateAttrs,l=t(\"../../plots/template_attributes\").texttemplateAttrs,c=t(\"../../lib/extend\").extendFlat,u=i({editType:\"plot\",arrayOk:!0,colorEditType:\"plot\"});e.exports={labels:{valType:\"data_array\",editType:\"calc\"},label0:{valType:\"number\",dflt:0,editType:\"calc\"},dlabel:{valType:\"number\",dflt:1,editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},marker:{colors:{valType:\"data_array\",editType:\"calc\"},line:{color:{valType:\"color\",dflt:o.defaultLine,arrayOk:!0,editType:\"style\"},width:{valType:\"number\",min:0,dflt:0,arrayOk:!0,editType:\"style\"},editType:\"calc\"},editType:\"calc\"},text:{valType:\"data_array\",editType:\"plot\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"style\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"percent\"],extras:[\"none\"],editType:\"calc\"},hoverinfo:c({},n.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:s({},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),texttemplate:l({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),textposition:{valType:\"enumerated\",values:[\"inside\",\"outside\",\"auto\",\"none\"],dflt:\"auto\",arrayOk:!0,editType:\"plot\"},textfont:c({},u,{}),insidetextorientation:{valType:\"enumerated\",values:[\"horizontal\",\"radial\",\"tangential\",\"auto\"],dflt:\"auto\",editType:\"plot\"},insidetextfont:c({},u,{}),outsidetextfont:c({},u,{}),automargin:{valType:\"boolean\",dflt:!1,editType:\"plot\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"plot\"},font:c({},u,{}),position:{valType:\"enumerated\",values:[\"top left\",\"top center\",\"top right\",\"middle center\",\"bottom left\",\"bottom center\",\"bottom right\"],editType:\"plot\"},editType:\"plot\"},domain:a({name:\"pie\",trace:!0,editType:\"calc\"}),hole:{valType:\"number\",min:0,max:1,dflt:0,editType:\"calc\"},sort:{valType:\"boolean\",dflt:!0,editType:\"calc\"},direction:{valType:\"enumerated\",values:[\"clockwise\",\"counterclockwise\"],dflt:\"counterclockwise\",editType:\"calc\"},rotation:{valType:\"number\",min:-360,max:360,dflt:0,editType:\"calc\"},pull:{valType:\"number\",min:0,max:1,dflt:0,arrayOk:!0,editType:\"calc\"},_deprecated:{title:{valType:\"string\",dflt:\"\",editType:\"calc\"},titlefont:c({},u,{}),titleposition:{valType:\"enumerated\",values:[\"top left\",\"top center\",\"top right\",\"middle center\",\"bottom left\",\"bottom center\",\"bottom right\"],editType:\"calc\"}}}},{\"../../components/color/attributes\":591,\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/domain\":790,\"../../plots/font_attributes\":791,\"../../plots/template_attributes\":841}],1095:[function(t,e,r){\"use strict\";var n=t(\"../../plots/plots\");r.name=\"pie\",r.plot=function(t,e,a,i){n.plotBasePlot(r.name,t,e,a,i)},r.clean=function(t,e,a,i){n.cleanBasePlot(r.name,t,e,a,i)}},{\"../../plots/plots\":826}],1096:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"tinycolor2\"),i=t(\"../../components/color\"),o={};function s(t){return function(e,r){return!!e&&(!!(e=a(e)).isValid()&&(e=i.addOpacity(e,e.getAlpha()),t[r]||(t[r]=e),e))}}function l(t,e){var r,n=JSON.stringify(t),i=e[n];if(!i){for(i=t.slice(),r=0;r<t.length;r++)i.push(a(t[r]).lighten(20).toHexString());for(r=0;r<t.length;r++)i.push(a(t[r]).darken(20).toHexString());e[n]=i}return i}e.exports={calc:function(t,e){var r,a,i=[],o=t._fullLayout,l=o.hiddenlabels||[],c=e.labels,u=e.marker.colors||[],h=e.values,f=e._length,p=e._hasValues&&f;if(e.dlabel)for(c=new Array(f),r=0;r<f;r++)c[r]=String(e.label0+r*e.dlabel);var d={},g=s(o[\"_\"+e.type+\"colormap\"]),v=0,m=!1;for(r=0;r<f;r++){var y,x,b;if(p){if(y=h[r],!n(y))continue;if((y=+y)<0)continue}else y=1;void 0!==(x=c[r])&&\"\"!==x||(x=r);var _=d[x=String(x)];void 0===_?(d[x]=i.length,(b=-1!==l.indexOf(x))||(v+=y),i.push({v:y,label:x,color:g(u[r],x),i:r,pts:[r],hidden:b})):(m=!0,(a=i[_]).v+=y,a.pts.push(r),a.hidden||(v+=y),!1===a.color&&u[r]&&(a.color=g(u[r],x)))}return(\"funnelarea\"===e.type?m:e.sort)&&i.sort(function(t,e){return e.v-t.v}),i[0]&&(i[0].vTotal=v),i},crossTraceCalc:function(t,e){var r=(e||{}).type;r||(r=\"pie\");var n=t._fullLayout,a=t.calcdata,i=n[r+\"colorway\"],s=n[\"_\"+r+\"colormap\"];n[\"extend\"+r+\"colors\"]&&(i=l(i,o));for(var c=0,u=0;u<a.length;u++){var h=a[u];if(h[0].trace.type===r)for(var f=0;f<h.length;f++){var p=h[f];!1===p.color&&(s[p.label]?p.color=s[p.label]:(s[p.label]=p.color=i[c%i.length],c++))}}},makePullColorFn:s,generateExtendedColors:l}},{\"../../components/color\":592,\"fast-isnumeric\":228,tinycolor2:536}],1097:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib\"),i=t(\"./attributes\"),o=t(\"../../plots/domain\").defaults,s=t(\"../bar/defaults\").handleText;function l(t,e){var r=Array.isArray(t),i=a.isArrayOrTypedArray(e),o=Math.min(r?t.length:1/0,i?e.length:1/0);if(isFinite(o)||(o=0),o&&i){for(var s,l=0;l<o;l++){var c=e[l];if(n(c)&&c>0){s=!0;break}}s||(o=0)}return{hasLabels:r,hasValues:i,len:o}}e.exports={handleLabelsAndValues:l,supplyDefaults:function(t,e,r,n){function c(r,n){return a.coerce(t,e,i,r,n)}var u=l(c(\"labels\"),c(\"values\")),h=u.len;if(e._hasLabels=u.hasLabels,e._hasValues=u.hasValues,!e._hasLabels&&e._hasValues&&(c(\"label0\"),c(\"dlabel\")),h){e._length=h,c(\"marker.line.width\")&&c(\"marker.line.color\"),c(\"marker.colors\"),c(\"scalegroup\");var f,p=c(\"text\"),d=c(\"texttemplate\");if(d||(f=c(\"textinfo\",Array.isArray(p)?\"text+percent\":\"percent\")),c(\"hovertext\"),c(\"hovertemplate\"),d||f&&\"none\"!==f){var g=c(\"textposition\");s(t,e,n,c,g,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),(Array.isArray(g)||\"auto\"===g||\"outside\"===g)&&c(\"automargin\"),(\"inside\"===g||\"auto\"===g||Array.isArray(g))&&c(\"insidetextorientation\")}o(e,n,c);var v=c(\"hole\");if(c(\"title.text\")){var m=c(\"title.position\",v?\"middle center\":\"top center\");v||\"middle center\"!==m||(e.title.position=\"top center\"),a.coerceFont(c,\"title.font\",n.font)}c(\"sort\"),c(\"direction\"),c(\"rotation\"),c(\"pull\")}else e.visible=!1}}},{\"../../lib\":717,\"../../plots/domain\":790,\"../bar/defaults\":860,\"./attributes\":1094,\"fast-isnumeric\":228}],1098:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx/helpers\").appendArrayMultiPointValues;e.exports=function(t,e){var r={curveNumber:e.index,pointNumbers:t.pts,data:e._input,fullData:e,label:t.label,color:t.color,value:t.v,percent:t.percent,text:t.text,v:t.v};return 1===t.pts.length&&(r.pointNumber=r.i=t.pts[0]),n(r,e,t.pts),\"funnelarea\"===e.type&&(delete r.v,delete r.i),r}},{\"../../components/fx/helpers\":627}],1099:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");r.formatPiePercent=function(t,e){var r=(100*t).toPrecision(3);return-1!==r.lastIndexOf(\".\")&&(r=r.replace(/[.]?0+$/,\"\")),n.numSeparate(r,e)+\"%\"},r.formatPieValue=function(t,e){var r=t.toPrecision(10);return-1!==r.lastIndexOf(\".\")&&(r=r.replace(/[.]?0+$/,\"\")),n.numSeparate(r,e)},r.getFirstFilled=function(t,e){if(Array.isArray(t))for(var r=0;r<e.length;r++){var n=t[e[r]];if(n||0===n||\"\"===n)return n}},r.castOption=function(t,e){return Array.isArray(t)?r.getFirstFilled(t,e):t||void 0}},{\"../../lib\":717}],1100:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,supplyLayoutDefaults:t(\"./layout_defaults\"),layoutAttributes:t(\"./layout_attributes\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\").plot,style:t(\"./style\"),styleOne:t(\"./style_one\"),moduleType:\"trace\",name:\"pie\",basePlotModule:t(\"./base_plot\"),categories:[\"pie-like\",\"pie\",\"showLegend\"],meta:{}}},{\"./attributes\":1094,\"./base_plot\":1095,\"./calc\":1096,\"./defaults\":1097,\"./layout_attributes\":1101,\"./layout_defaults\":1102,\"./plot\":1103,\"./style\":1104,\"./style_one\":1105}],1101:[function(t,e,r){\"use strict\";e.exports={hiddenlabels:{valType:\"data_array\",editType:\"calc\"},piecolorway:{valType:\"colorlist\",editType:\"calc\"},extendpiecolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{}],1102:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,i){return n.coerce(t,e,a,r,i)}r(\"hiddenlabels\"),r(\"piecolorway\",e.colorway),r(\"extendpiecolors\")}},{\"../../lib\":717,\"./layout_attributes\":1101}],1103:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../plots/plots\"),i=t(\"../../components/fx\"),o=t(\"../../components/color\"),s=t(\"../../components/drawing\"),l=t(\"../../lib\"),c=t(\"../../lib/svg_text_utils\"),u=t(\"../bar/uniform_text\"),h=u.recordMinTextSize,f=u.clearMinTextSize,p=t(\"./helpers\"),d=t(\"./event_data\"),g=t(\"../../lib\").isValidTextValue;function v(t,e,r){var a=r[0],o=a.trace,s=a.cx,c=a.cy;\"_hasHoverLabel\"in o||(o._hasHoverLabel=!1),\"_hasHoverEvent\"in o||(o._hasHoverEvent=!1),t.on(\"mouseover\",function(t){var r=e._fullLayout,u=e._fullData[o.index];if(!e._dragging&&!1!==r.hovermode){var h=u.hoverinfo;if(Array.isArray(h)&&(h=i.castHoverinfo({hoverinfo:[p.castOption(h,t.pts)],_module:o._module},r,0)),\"all\"===h&&(h=\"label+text+value+percent+name\"),u.hovertemplate||\"none\"!==h&&\"skip\"!==h&&h){var f=t.rInscribed||0,g=s+t.pxmid[0]*(1-f),v=c+t.pxmid[1]*(1-f),m=r.separators,y=[];if(h&&-1!==h.indexOf(\"label\")&&y.push(t.label),t.text=p.castOption(u.hovertext||u.text,t.pts),h&&-1!==h.indexOf(\"text\")){var x=t.text;l.isValidTextValue(x)&&y.push(x)}t.value=t.v,t.valueLabel=p.formatPieValue(t.v,m),h&&-1!==h.indexOf(\"value\")&&y.push(t.valueLabel),t.percent=t.v/a.vTotal,t.percentLabel=p.formatPiePercent(t.percent,m),h&&-1!==h.indexOf(\"percent\")&&y.push(t.percentLabel);var b=u.hoverlabel,_=b.font;i.loneHover({trace:o,x0:g-f*a.r,x1:g+f*a.r,y:v,text:y.join(\"<br>\"),name:u.hovertemplate||-1!==h.indexOf(\"name\")?u.name:void 0,idealAlign:t.pxmid[0]<0?\"left\":\"right\",color:p.castOption(b.bgcolor,t.pts)||t.color,borderColor:p.castOption(b.bordercolor,t.pts),fontFamily:p.castOption(_.family,t.pts),fontSize:p.castOption(_.size,t.pts),fontColor:p.castOption(_.color,t.pts),nameLength:p.castOption(b.namelength,t.pts),textAlign:p.castOption(b.align,t.pts),hovertemplate:p.castOption(u.hovertemplate,t.pts),hovertemplateLabels:t,eventData:[d(t,u)]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:e}),o._hasHoverLabel=!0}o._hasHoverEvent=!0,e.emit(\"plotly_hover\",{points:[d(t,u)],event:n.event})}}),t.on(\"mouseout\",function(t){var r=e._fullLayout,a=e._fullData[o.index],s=n.select(this).datum();o._hasHoverEvent&&(t.originalEvent=n.event,e.emit(\"plotly_unhover\",{points:[d(s,a)],event:n.event}),o._hasHoverEvent=!1),o._hasHoverLabel&&(i.loneUnhover(r._hoverlayer.node()),o._hasHoverLabel=!1)}),t.on(\"click\",function(t){var r=e._fullLayout,a=e._fullData[o.index];e._dragging||!1===r.hovermode||(e._hoverdata=[d(t,a)],i.click(e,n.event))})}function m(t,e,r){var n=p.castOption(t.insidetextfont.color,e.pts);!n&&t._input.textfont&&(n=p.castOption(t._input.textfont.color,e.pts));var a=p.castOption(t.insidetextfont.family,e.pts)||p.castOption(t.textfont.family,e.pts)||r.family,i=p.castOption(t.insidetextfont.size,e.pts)||p.castOption(t.textfont.size,e.pts)||r.size;return{color:n||o.contrast(e.color),family:a,size:i}}function y(t,e){for(var r,n,a=0;a<t.length;a++)if((n=(r=t[a][0]).trace).title.text){var i=n.title.text;n._meta&&(i=l.templateString(i,n._meta));var o=s.tester.append(\"text\").attr(\"data-notex\",1).text(i).call(s.font,n.title.font).call(c.convertToTspans,e),u=s.bBox(o.node(),!0);r.titleBox={width:u.width,height:u.height},o.remove()}}function x(t,e,r){var n,a=Math.sqrt(t.width*t.width+t.height*t.height),i=e.halfangle,o=e.midangle,s=e.ring,l=e.rInscribed,c=r.r||e.rpx1,u=r.trace.insidetextorientation,h=\"horizontal\"===u,f=\"tangential\"===u,p=\"radial\"===u,d=\"auto\"===u,g=1===s&&Math.abs(e.startangle-e.stopangle)===2*Math.PI,v=[];if(!d){var m,y=function(r,a){if(function(t,e){var r=t.startangle,n=t.stopangle;return r>e&&e>n||r<e&&e<n}(e,r)){var i=Math.abs(r-e.startangle),o=Math.abs(r-e.stopangle),l=i<o?i:o;(n=\"tan\"===a?_(t,c,s,l,0):b(t,c,s,l,Math.PI/2)).textPosAngle=r,v.push(n)}};if(h||f){for(m=4;m>=-4;m-=2)y(Math.PI*m,\"tan\");for(m=4;m>=-4;m-=2)y(Math.PI*(m+1),\"tan\")}if(h||p){for(m=4;m>=-4;m-=2)y(Math.PI*(m+1.5),\"rad\");for(m=4;m>=-4;m-=2)y(Math.PI*(m+.5),\"rad\")}}if(g||d||h){if((n={scale:l*c*2/a,rCenter:1-l,rotate:0}).textPosAngle=(e.startangle+e.stopangle)/2,n.scale>=1)return n;v.push(n)}(d||p)&&((n=b(t,c,s,i,o)).textPosAngle=(e.startangle+e.stopangle)/2,v.push(n)),(d||f)&&((n=_(t,c,s,i,o)).textPosAngle=(e.startangle+e.stopangle)/2,v.push(n));for(var x=0,w=0,k=0;k<v.length;k++){var T=v[k].scale;if(w<T&&(w=T,x=k),!d&&w>=1)break}return v[x]}function b(t,e,r,n,a){var i=t.width/t.height,o=T(i,n,e,r);return{scale:2*o/t.height,rCenter:w(i,o/e),rotate:k(a)}}function _(t,e,r,n,a){var i=t.height/t.width,o=T(i,n,e,r);return{scale:2*o/t.width,rCenter:w(i,o/e),rotate:k(a+Math.PI/2)}}function w(t,e){return Math.cos(e)-t*e}function k(t){return(180/Math.PI*t+720)%180-90}function T(t,e,r,n){var a=t+1/(2*Math.tan(e));return r*Math.min(1/(Math.sqrt(a*a+.5)+a),n/(Math.sqrt(t*t+n/2)+t))}function M(t,e){return t.v!==e.vTotal||e.trace.hole?Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2):1}function A(t,e){var r=e.pxmid[0],n=e.pxmid[1],a=t.width/2,i=t.height/2;return r<0&&(a*=-1),n<0&&(i*=-1),{scale:1,rCenter:1,rotate:0,x:a+Math.abs(i)*(a>0?1:-1)/2,y:i/(1+r*r/(n*n)),outside:!0}}function S(t,e){var r,n,a,i=t.trace,o={x:t.cx,y:t.cy},s={tx:0,ty:0};s.ty+=i.title.font.size,a=L(i),-1!==i.title.position.indexOf(\"top\")?(o.y-=(1+a)*t.r,s.ty-=t.titleBox.height):-1!==i.title.position.indexOf(\"bottom\")&&(o.y+=(1+a)*t.r);var l,c,u=(l=t.r,c=t.trace.aspectratio,l/(void 0===c?1:c)),h=e.w*(i.domain.x[1]-i.domain.x[0])/2;return-1!==i.title.position.indexOf(\"left\")?(h+=u,o.x-=(1+a)*u,s.tx+=t.titleBox.width/2):-1!==i.title.position.indexOf(\"center\")?h*=2:-1!==i.title.position.indexOf(\"right\")&&(h+=u,o.x+=(1+a)*u,s.tx-=t.titleBox.width/2),r=h/t.titleBox.width,n=E(t,e)/t.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function E(t,e){var r=t.trace,n=e.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(t.titleBox.height,n/2)}function L(t){var e,r=t.pull;if(!r)return 0;if(Array.isArray(r))for(r=0,e=0;e<t.pull.length;e++)t.pull[e]>r&&(r=t.pull[e]);return r}function C(t,e){for(var r=[],n=0;n<t.length;n++){var a=t[n][0],i=a.trace,o=i.domain,s=e.w*(o.x[1]-o.x[0]),l=e.h*(o.y[1]-o.y[0]);i.title.text&&\"middle center\"!==i.title.position&&(l-=E(a,e));var c=s/2,u=l/2;\"funnelarea\"!==i.type||i.scalegroup||(u/=i.aspectratio),a.r=Math.min(c,u)/(1+L(i)),a.cx=e.l+e.w*(i.domain.x[1]+i.domain.x[0])/2,a.cy=e.t+e.h*(1-i.domain.y[0])-l/2,i.title.text&&-1!==i.title.position.indexOf(\"bottom\")&&(a.cy-=E(a,e)),i.scalegroup&&-1===r.indexOf(i.scalegroup)&&r.push(i.scalegroup)}!function(t,e){for(var r,n,a,i=0;i<e.length;i++){var o=1/0,s=e[i];for(n=0;n<t.length;n++)if(r=t[n][0],(a=r.trace).scalegroup===s){var l;if(\"pie\"===a.type)l=r.r*r.r;else if(\"funnelarea\"===a.type){var c,u;a.aspectratio>1?(c=r.r,u=c/a.aspectratio):(u=r.r,c=u*a.aspectratio),c*=(1+a.baseratio)/2,l=c*u}o=Math.min(o,l/r.vTotal)}for(n=0;n<t.length;n++)if(r=t[n][0],(a=r.trace).scalegroup===s){var h=o*r.vTotal;\"funnelarea\"===a.type&&(h/=(1+a.baseratio)/2,h/=a.aspectratio),r.r=Math.sqrt(h)}}}(t,r)}function P(t,e){return[t*Math.sin(e),-t*Math.cos(e)]}function O(t,e,r){var n=t._fullLayout,a=r.trace,i=a.texttemplate,o=a.textinfo;if(!i&&o&&\"none\"!==o){var s,c=o.split(\"+\"),u=function(t){return-1!==c.indexOf(t)},h=u(\"label\"),f=u(\"text\"),d=u(\"value\"),v=u(\"percent\"),m=n.separators;if(s=h?[e.label]:[],f){var y=p.getFirstFilled(a.text,e.pts);g(y)&&s.push(y)}d&&s.push(p.formatPieValue(e.v,m)),v&&s.push(p.formatPiePercent(e.v/r.vTotal,m)),e.text=s.join(\"<br>\")}if(i){var x=l.castOption(a,e.i,\"texttemplate\");if(x){var b=function(t){return{label:t.label,value:t.v,valueLabel:p.formatPieValue(t.v,n.separators),percent:t.v/r.vTotal,percentLabel:p.formatPiePercent(t.v/r.vTotal,n.separators),color:t.color,text:t.text,customdata:l.castOption(a,t.i,\"customdata\")}}(e),_=p.getFirstFilled(a.text,e.pts);(g(_)||\"\"===_)&&(b.text=_),e.text=l.texttemplateString(x,b,t._fullLayout._d3locale,b,a._meta||{})}else e.text=\"\"}}function z(t,e){var r=t.rotate,n=t.scale;n>1&&(n=1);var a=r*Math.PI/180,i=Math.cos(a),o=Math.sin(a),s=(e.left+e.right)/2,l=(e.top+e.bottom)/2;t.textX=s*i-l*o,t.textY=s*o+l*i,t.noCenter=!0}e.exports={plot:function(t,e){var r=t._fullLayout,i=r._size;f(\"pie\",r),y(e,t),C(e,i);var u=l.makeTraceGroups(r._pielayer,e,\"trace\").each(function(e){var u=n.select(this),f=e[0],d=f.trace;!function(t){var e,r,n,a=t[0],i=a.r,o=a.trace,s=o.rotation*Math.PI/180,l=2*Math.PI/a.vTotal,c=\"px0\",u=\"px1\";if(\"counterclockwise\"===o.direction){for(e=0;e<t.length&&t[e].hidden;e++);if(e===t.length)return;s+=l*t[e].v,l*=-1,c=\"px1\",u=\"px0\"}for(n=P(i,s),e=0;e<t.length;e++)(r=t[e]).hidden||(r[c]=n,r.startangle=s,s+=l*r.v/2,r.pxmid=P(i,s),r.midangle=s,s+=l*r.v/2,n=P(i,s),r.stopangle=s,r[u]=n,r.largeArc=r.v>a.vTotal/2?1:0,r.halfangle=Math.PI*Math.min(r.v/a.vTotal,.5),r.ring=1-o.hole,r.rInscribed=M(r,a))}(e),u.attr(\"stroke-linejoin\",\"round\"),u.each(function(){var g=n.select(this).selectAll(\"g.slice\").data(e);g.enter().append(\"g\").classed(\"slice\",!0),g.exit().remove();var y=[[[],[]],[[],[]]],b=!1;g.each(function(a,i){if(a.hidden)n.select(this).selectAll(\"path,g\").remove();else{a.pointNumber=a.i,a.curveNumber=d.index,y[a.pxmid[1]<0?0:1][a.pxmid[0]<0?0:1].push(a);var o=f.cx,u=f.cy,g=n.select(this),_=g.selectAll(\"path.surface\").data([a]);if(_.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),g.call(v,t,e),d.pull){var w=+p.castOption(d.pull,a.pts)||0;w>0&&(o+=w*a.pxmid[0],u+=w*a.pxmid[1])}a.cxFinal=o,a.cyFinal=u;var k=d.hole;if(a.v===f.vTotal){var T=\"M\"+(o+a.px0[0])+\",\"+(u+a.px0[1])+C(a.px0,a.pxmid,!0,1)+C(a.pxmid,a.px0,!0,1)+\"Z\";k?_.attr(\"d\",\"M\"+(o+k*a.px0[0])+\",\"+(u+k*a.px0[1])+C(a.px0,a.pxmid,!1,k)+C(a.pxmid,a.px0,!1,k)+\"Z\"+T):_.attr(\"d\",T)}else{var M=C(a.px0,a.px1,!0,1);if(k){var S=1-k;_.attr(\"d\",\"M\"+(o+k*a.px1[0])+\",\"+(u+k*a.px1[1])+C(a.px1,a.px0,!1,k)+\"l\"+S*a.px0[0]+\",\"+S*a.px0[1]+M+\"Z\")}else _.attr(\"d\",\"M\"+o+\",\"+u+\"l\"+a.px0[0]+\",\"+a.px0[1]+M+\"Z\")}O(t,a,f);var E=p.castOption(d.textposition,a.pts),L=g.selectAll(\"g.slicetext\").data(a.text&&\"none\"!==E?[0]:[]);L.enter().append(\"g\").classed(\"slicetext\",!0),L.exit().remove(),L.each(function(){var g=l.ensureSingle(n.select(this),\"text\",\"\",function(t){t.attr(\"data-notex\",1)}),v=l.ensureUniformFontSize(t,\"outside\"===E?function(t,e,r){var n=p.castOption(t.outsidetextfont.color,e.pts)||p.castOption(t.textfont.color,e.pts)||r.color,a=p.castOption(t.outsidetextfont.family,e.pts)||p.castOption(t.textfont.family,e.pts)||r.family,i=p.castOption(t.outsidetextfont.size,e.pts)||p.castOption(t.textfont.size,e.pts)||r.size;return{color:n,family:a,size:i}}(d,a,r.font):m(d,a,r.font));g.text(a.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,v).call(c.convertToTspans,t);var y,_=s.bBox(g.node());if(\"outside\"===E)y=A(_,a);else if(y=x(_,a,f),\"auto\"===E&&y.scale<1){var w=l.ensureUniformFontSize(t,d.outsidetextfont);g.call(s.font,w),y=A(_=s.bBox(g.node()),a)}var k=y.textPosAngle,T=void 0===k?a.pxmid:P(f.r,k);if(y.targetX=o+T[0]*y.rCenter+(y.x||0),y.targetY=u+T[1]*y.rCenter+(y.y||0),z(y,_),y.outside){var M=y.targetY;a.yLabelMin=M-_.height/2,a.yLabelMid=M,a.yLabelMax=M+_.height/2,a.labelExtraX=0,a.labelExtraY=0,b=!0}y.fontSize=v.size,h(d.type,y,r),e[i].transform=y,g.attr(\"transform\",l.getTextTransform(y))})}function C(t,e,r,n){var i=n*(e[0]-t[0]),o=n*(e[1]-t[1]);return\"a\"+n*f.r+\",\"+n*f.r+\" 0 \"+a.largeArc+(r?\" 1 \":\" 0 \")+i+\",\"+o}});var _=n.select(this).selectAll(\"g.titletext\").data(d.title.text?[0]:[]);if(_.enter().append(\"g\").classed(\"titletext\",!0),_.exit().remove(),_.each(function(){var e,r=l.ensureSingle(n.select(this),\"text\",\"\",function(t){t.attr(\"data-notex\",1)}),a=d.title.text;d._meta&&(a=l.templateString(a,d._meta)),r.text(a).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,d.title.font).call(c.convertToTspans,t),e=\"middle center\"===d.title.position?function(t){var e=Math.sqrt(t.titleBox.width*t.titleBox.width+t.titleBox.height*t.titleBox.height);return{x:t.cx,y:t.cy,scale:t.trace.hole*t.r*2/e,tx:0,ty:-t.titleBox.height/2+t.trace.title.font.size}}(f):S(f,i),r.attr(\"transform\",\"translate(\"+e.x+\",\"+e.y+\")\"+(e.scale<1?\"scale(\"+e.scale+\")\":\"\")+\"translate(\"+e.tx+\",\"+e.ty+\")\")}),b&&function(t,e){var r,n,a,i,o,s,l,c,u,h,f,d,g;function v(t,e){return t.pxmid[1]-e.pxmid[1]}function m(t,e){return e.pxmid[1]-t.pxmid[1]}function y(t,r){r||(r={});var a,c,u,f,d,g,v=r.labelExtraY+(n?r.yLabelMax:r.yLabelMin),m=n?t.yLabelMin:t.yLabelMax,y=n?t.yLabelMax:t.yLabelMin,x=t.cyFinal+o(t.px0[1],t.px1[1]),b=v-m;if(b*l>0&&(t.labelExtraY=b),Array.isArray(e.pull))for(c=0;c<h.length;c++)(u=h[c])===t||(p.castOption(e.pull,t.pts)||0)>=(p.castOption(e.pull,u.pts)||0)||((t.pxmid[1]-u.pxmid[1])*l>0?(f=u.cyFinal+o(u.px0[1],u.px1[1]),(b=f-m-t.labelExtraY)*l>0&&(t.labelExtraY+=b)):(y+t.labelExtraY-x)*l>0&&(a=3*s*Math.abs(c-h.indexOf(t)),d=u.cxFinal+i(u.px0[0],u.px1[0]),(g=d+a-(t.cxFinal+t.pxmid[0])-t.labelExtraX)*s>0&&(t.labelExtraX+=g)))}for(n=0;n<2;n++)for(a=n?v:m,o=n?Math.max:Math.min,l=n?1:-1,r=0;r<2;r++){for(i=r?Math.max:Math.min,s=r?1:-1,(c=t[n][r]).sort(a),u=t[1-n][r],h=u.concat(c),d=[],f=0;f<c.length;f++)void 0!==c[f].yLabelMid&&d.push(c[f]);for(g=!1,f=0;n&&f<u.length;f++)if(void 0!==u[f].yLabelMid){g=u[f];break}for(f=0;f<d.length;f++){var x=f&&d[f-1];g&&!f&&(x=g),y(d[f],x)}}}(y,d),function(t,e){t.each(function(t){var r=n.select(this);if(t.labelExtraX||t.labelExtraY){var a=r.select(\"g.slicetext text\");t.transform.targetX+=t.labelExtraX,t.transform.targetY+=t.labelExtraY,a.attr(\"transform\",l.getTextTransform(t.transform));var i=t.cxFinal+t.pxmid[0],s=t.cyFinal+t.pxmid[1],c=\"M\"+i+\",\"+s,u=(t.yLabelMax-t.yLabelMin)*(t.pxmid[0]<0?-1:1)/4;if(t.labelExtraX){var h=t.labelExtraX*t.pxmid[1]/t.pxmid[0],f=t.yLabelMid+t.labelExtraY-(t.cyFinal+t.pxmid[1]);Math.abs(h)>Math.abs(f)?c+=\"l\"+f*t.pxmid[0]/t.pxmid[1]+\",\"+f+\"H\"+(i+t.labelExtraX+u):c+=\"l\"+t.labelExtraX+\",\"+h+\"v\"+(f-h)+\"h\"+u}else c+=\"V\"+(t.yLabelMid+t.labelExtraY)+\"h\"+u;l.ensureSingle(r,\"path\",\"textline\").call(o.stroke,e.outsidetextfont.color).attr({\"stroke-width\":Math.min(2,e.outsidetextfont.size/8),d:c,fill:\"none\"})}else r.select(\"path.textline\").remove()})}(g,d),b&&d.automargin){var w=s.bBox(u.node()),k=d.domain,T=i.w*(k.x[1]-k.x[0]),M=i.h*(k.y[1]-k.y[0]),E=(.5*T-f.r)/i.w,L=(.5*M-f.r)/i.h;a.autoMargin(t,\"pie.\"+d.uid+\".automargin\",{xl:k.x[0]-E,xr:k.x[1]+E,yb:k.y[0]-L,yt:k.y[1]+L,l:Math.max(f.cx-f.r-w.left,0),r:Math.max(w.right-(f.cx+f.r),0),b:Math.max(w.bottom-(f.cy+f.r),0),t:Math.max(f.cy-f.r-w.top,0),pad:5})}})});setTimeout(function(){u.selectAll(\"tspan\").each(function(){var t=n.select(this);t.attr(\"dy\")&&t.attr(\"dy\",t.attr(\"dy\"))})},0)},formatSliceLabel:O,transformInsideText:x,determineInsideTextFont:m,positionTitleOutside:S,prerenderTitles:y,layoutAreas:C,attachFxHandlers:v,computeTransform:z}},{\"../../components/color\":592,\"../../components/drawing\":613,\"../../components/fx\":630,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"../../plots/plots\":826,\"../bar/uniform_text\":872,\"./event_data\":1098,\"./helpers\":1099,d3:165}],1104:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"./style_one\"),i=t(\"../bar/uniform_text\").resizeText;e.exports=function(t){var e=t._fullLayout._pielayer.selectAll(\".trace\");i(t,e,\"pie\"),e.each(function(t){var e=t[0].trace,r=n.select(this);r.style({opacity:e.opacity}),r.selectAll(\"path.surface\").each(function(t){n.select(this).call(a,t,e)})})}},{\"../bar/uniform_text\":872,\"./style_one\":1105,d3:165}],1105:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),a=t(\"./helpers\").castOption;e.exports=function(t,e,r){var i=r.marker.line,o=a(i.color,e.pts)||n.defaultLine,s=a(i.width,e.pts)||0;t.style(\"stroke-width\",s).call(n.fill,e.color).call(n.stroke,o)}},{\"../../components/color\":592,\"./helpers\":1099}],1106:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\");e.exports={x:n.x,y:n.y,xy:{valType:\"data_array\",editType:\"calc\"},indices:{valType:\"data_array\",editType:\"calc\"},xbounds:{valType:\"data_array\",editType:\"calc\"},ybounds:{valType:\"data_array\",editType:\"calc\"},text:n.text,marker:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,arrayOk:!1,editType:\"calc\"},blend:{valType:\"boolean\",dflt:null,editType:\"calc\"},sizemin:{valType:\"number\",min:.1,max:2,dflt:.5,editType:\"calc\"},sizemax:{valType:\"number\",min:.1,dflt:20,editType:\"calc\"},border:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},arearatio:{valType:\"number\",min:0,max:1,dflt:0,editType:\"calc\"},editType:\"calc\"},editType:\"calc\"},transforms:void 0}},{\"../scatter/attributes\":1120}],1107:[function(t,e,r){\"use strict\";var n=t(\"gl-pointcloud2d\"),a=t(\"../../lib/str2rgbarray\"),i=t(\"../../plots/cartesian/autorange\").findExtremes,o=t(\"../scatter/get_trace_color\");function s(t,e){this.scene=t,this.uid=e,this.type=\"pointcloud\",this.pickXData=[],this.pickYData=[],this.xData=[],this.yData=[],this.textLabels=[],this.color=\"rgb(0, 0, 0)\",this.name=\"\",this.hoverinfo=\"all\",this.idToIndex=new Int32Array(0),this.bounds=[0,0,0,0],this.pointcloudOptions={positions:new Float32Array(0),idToIndex:this.idToIndex,sizemin:.5,sizemax:12,color:[0,0,0,1],areaRatio:1,borderColor:[0,0,0,1]},this.pointcloud=n(t.glplot,this.pointcloudOptions),this.pointcloud._trace=this}var l=s.prototype;l.handlePick=function(t){var e=this.idToIndex[t.pointId];return{trace:this,dataCoord:t.dataCoord,traceCoord:this.pickXYData?[this.pickXYData[2*e],this.pickXYData[2*e+1]]:[this.pickXData[e],this.pickYData[e]],textLabel:Array.isArray(this.textLabels)?this.textLabels[e]:this.textLabels,color:this.color,name:this.name,pointIndex:e,hoverinfo:this.hoverinfo}},l.update=function(t){this.index=t.index,this.textLabels=t.text,this.name=t.name,this.hoverinfo=t.hoverinfo,this.bounds=[1/0,1/0,-1/0,-1/0],this.updateFast(t),this.color=o(t,{})},l.updateFast=function(t){var e,r,n,o,s,l,c=this.xData=this.pickXData=t.x,u=this.yData=this.pickYData=t.y,h=this.pickXYData=t.xy,f=t.xbounds&&t.ybounds,p=t.indices,d=this.bounds;if(h){if(n=h,e=h.length>>>1,f)d[0]=t.xbounds[0],d[2]=t.xbounds[1],d[1]=t.ybounds[0],d[3]=t.ybounds[1];else for(l=0;l<e;l++)o=n[2*l],s=n[2*l+1],o<d[0]&&(d[0]=o),o>d[2]&&(d[2]=o),s<d[1]&&(d[1]=s),s>d[3]&&(d[3]=s);if(p)r=p;else for(r=new Int32Array(e),l=0;l<e;l++)r[l]=l}else for(e=c.length,n=new Float32Array(2*e),r=new Int32Array(e),l=0;l<e;l++)o=c[l],s=u[l],r[l]=l,n[2*l]=o,n[2*l+1]=s,o<d[0]&&(d[0]=o),o>d[2]&&(d[2]=o),s<d[1]&&(d[1]=s),s>d[3]&&(d[3]=s);this.idToIndex=r,this.pointcloudOptions.idToIndex=r,this.pointcloudOptions.positions=n;var g=a(t.marker.color),v=a(t.marker.border.color),m=t.opacity*t.marker.opacity;g[3]*=m,this.pointcloudOptions.color=g;var y=t.marker.blend;if(null===y){y=c.length<100||u.length<100}this.pointcloudOptions.blend=y,v[3]*=m,this.pointcloudOptions.borderColor=v;var x=t.marker.sizemin,b=Math.max(t.marker.sizemax,t.marker.sizemin);this.pointcloudOptions.sizeMin=x,this.pointcloudOptions.sizeMax=b,this.pointcloudOptions.areaRatio=t.marker.border.arearatio,this.pointcloud.update(this.pointcloudOptions);var _=this.scene.xaxis,w=this.scene.yaxis,k=b/2||.5;t._extremes[_._id]=i(_,[d[0],d[2]],{ppad:k}),t._extremes[w._id]=i(w,[d[1],d[3]],{ppad:k})},l.dispose=function(){this.pointcloud.dispose()},e.exports=function(t,e){var r=new s(t,e.uid);return r.update(e),r}},{\"../../lib/str2rgbarray\":740,\"../../plots/cartesian/autorange\":764,\"../scatter/get_trace_color\":1130,\"gl-pointcloud2d\":295}],1108:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./attributes\");e.exports=function(t,e,r){function i(r,i){return n.coerce(t,e,a,r,i)}i(\"x\"),i(\"y\"),i(\"xbounds\"),i(\"ybounds\"),t.xy&&t.xy instanceof Float32Array&&(e.xy=t.xy),t.indices&&t.indices instanceof Int32Array&&(e.indices=t.indices),i(\"text\"),i(\"marker.color\",r),i(\"marker.opacity\"),i(\"marker.blend\"),i(\"marker.sizemin\"),i(\"marker.sizemax\"),i(\"marker.border.color\",r),i(\"marker.border.arearatio\"),e._length=null}},{\"../../lib\":717,\"./attributes\":1106}],1109:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"../scatter3d/calc\"),plot:t(\"./convert\"),moduleType:\"trace\",name:\"pointcloud\",basePlotModule:t(\"../../plots/gl2d\"),categories:[\"gl\",\"gl2d\",\"showLegend\"],meta:{}}},{\"../../plots/gl2d\":803,\"../scatter3d/calc\":1148,\"./attributes\":1106,\"./convert\":1107,\"./defaults\":1108}],1110:[function(t,e,r){\"use strict\";var n=t(\"../../plots/font_attributes\"),a=t(\"../../plots/attributes\"),i=t(\"../../components/color/attributes\"),o=t(\"../../components/fx/attributes\"),s=t(\"../../plots/domain\").attributes,l=t(\"../../plots/template_attributes\").hovertemplateAttrs,c=t(\"../../components/colorscale/attributes\"),u=t(\"../../plot_api/plot_template\").templatedArray,h=t(\"../../lib/extend\").extendFlat,f=t(\"../../plot_api/edit_types\").overrideAll;t(\"../../constants/docs\").FORMAT_LINK;(e.exports=f({hoverinfo:h({},a.hoverinfo,{flags:[],arrayOk:!1}),hoverlabel:o.hoverlabel,domain:s({name:\"sankey\",trace:!0}),orientation:{valType:\"enumerated\",values:[\"v\",\"h\"],dflt:\"h\"},valueformat:{valType:\"string\",dflt:\".3s\"},valuesuffix:{valType:\"string\",dflt:\"\"},arrangement:{valType:\"enumerated\",values:[\"snap\",\"perpendicular\",\"freeform\",\"fixed\"],dflt:\"snap\"},textfont:n({}),node:{label:{valType:\"data_array\",dflt:[]},groups:{valType:\"info_array\",impliedEdits:{x:[],y:[]},dimensions:2,freeLength:!0,dflt:[],items:{valType:\"number\",editType:\"calc\"}},x:{valType:\"data_array\",dflt:[]},y:{valType:\"data_array\",dflt:[]},color:{valType:\"color\",arrayOk:!0},line:{color:{valType:\"color\",dflt:i.defaultLine,arrayOk:!0},width:{valType:\"number\",min:0,dflt:.5,arrayOk:!0}},pad:{valType:\"number\",arrayOk:!1,min:0,dflt:20},thickness:{valType:\"number\",arrayOk:!1,min:1,dflt:20},hoverinfo:{valType:\"enumerated\",values:[\"all\",\"none\",\"skip\"],dflt:\"all\"},hoverlabel:o.hoverlabel,hovertemplate:l({},{keys:[\"value\",\"label\"]})},link:{label:{valType:\"data_array\",dflt:[]},color:{valType:\"color\",arrayOk:!0},line:{color:{valType:\"color\",dflt:i.defaultLine,arrayOk:!0},width:{valType:\"number\",min:0,dflt:0,arrayOk:!0}},source:{valType:\"data_array\",dflt:[]},target:{valType:\"data_array\",dflt:[]},value:{valType:\"data_array\",dflt:[]},hoverinfo:{valType:\"enumerated\",values:[\"all\",\"none\",\"skip\"],dflt:\"all\"},hoverlabel:o.hoverlabel,hovertemplate:l({},{keys:[\"value\",\"label\"]}),colorscales:u(\"concentrationscales\",{editType:\"calc\",label:{valType:\"string\",editType:\"calc\",dflt:\"\"},cmax:{valType:\"number\",editType:\"calc\",dflt:1},cmin:{valType:\"number\",editType:\"calc\",dflt:0},colorscale:h(c().colorscale,{dflt:[[0,\"white\"],[1,\"black\"]]})})}},\"calc\",\"nested\")).transforms=void 0},{\"../../components/color/attributes\":591,\"../../components/colorscale/attributes\":599,\"../../components/fx/attributes\":622,\"../../constants/docs\":688,\"../../lib/extend\":708,\"../../plot_api/edit_types\":748,\"../../plot_api/plot_template\":755,\"../../plots/attributes\":762,\"../../plots/domain\":790,\"../../plots/font_attributes\":791,\"../../plots/template_attributes\":841}],1111:[function(t,e,r){\"use strict\";var n=t(\"../../plot_api/edit_types\").overrideAll,a=t(\"../../plots/get_data\").getModuleCalcData,i=t(\"./plot\"),o=t(\"../../components/fx/layout_attributes\"),s=t(\"../../lib/setcursor\"),l=t(\"../../components/dragelement\"),c=t(\"../../plots/cartesian/select\").prepSelect,u=t(\"../../lib\"),h=t(\"../../registry\");function f(t,e){var r=t._fullData[e],n=t._fullLayout,a=n.dragmode,i=\"pan\"===n.dragmode?\"move\":\"crosshair\",o=r._bgRect;if(\"pan\"!==a&&\"zoom\"!==a){s(o,i);var f={_id:\"x\",c2p:u.identity,_offset:r._sankey.translateX,_length:r._sankey.width},p={_id:\"y\",c2p:u.identity,_offset:r._sankey.translateY,_length:r._sankey.height},d={gd:t,element:o.node(),plotinfo:{id:e,xaxis:f,yaxis:p,fillRangeItems:u.noop},subplot:e,xaxes:[f],yaxes:[p],doneFnCompleted:function(r){var n,a=t._fullData[e],i=a.node.groups.slice(),o=[];function s(t){for(var e=a._sankey.graph.nodes,r=0;r<e.length;r++)if(e[r].pointNumber===t)return e[r]}for(var l=0;l<r.length;l++){var c=s(r[l].pointNumber);if(c)if(c.group){for(var u=0;u<c.childrenNodes.length;u++)o.push(c.childrenNodes[u].pointNumber);i[c.pointNumber-a.node._count]=!1}else o.push(c.pointNumber)}n=i.filter(Boolean).concat([o]),h.call(\"_guiRestyle\",t,{\"node.groups\":[n]},e)},prepFn:function(t,e,r){c(t,e,r,d,a)}};l.init(d)}}r.name=\"sankey\",r.baseLayoutAttrOverrides=n({hoverlabel:o.hoverlabel},\"plot\",\"nested\"),r.plot=function(t){var e=a(t.calcdata,\"sankey\")[0];i(t,e),r.updateFx(t)},r.clean=function(t,e,r,n){var a=n._has&&n._has(\"sankey\"),i=e._has&&e._has(\"sankey\");a&&!i&&(n._paperdiv.selectAll(\".sankey\").remove(),n._paperdiv.selectAll(\".bgsankey\").remove())},r.updateFx=function(t){for(var e=0;e<t._fullData.length;e++)f(t,e)}},{\"../../components/dragelement\":610,\"../../components/fx/layout_attributes\":631,\"../../lib\":717,\"../../lib/setcursor\":737,\"../../plot_api/edit_types\":748,\"../../plots/cartesian/select\":782,\"../../plots/get_data\":800,\"../../registry\":846,\"./plot\":1116}],1112:[function(t,e,r){\"use strict\";var n=t(\"strongly-connected-components\"),a=t(\"../../lib\"),i=t(\"../../lib/gup\").wrap,o=a.isArrayOrTypedArray,s=a.isIndex,l=t(\"../../components/colorscale\");function c(t){var e,r=t.node,i=t.link,c=[],u=o(i.color),h={},f={},p=i.colorscales.length;for(e=0;e<p;e++){var d=i.colorscales[e],g=l.extractScale(d,{cLetter:\"c\"}),v=l.makeColorScaleFunc(g);f[d.label]=v}var m=0;for(e=0;e<i.value.length;e++)i.source[e]>m&&(m=i.source[e]),i.target[e]>m&&(m=i.target[e]);var y,x=m+1;t.node._count=x;var b=t.node.groups,_={};for(e=0;e<b.length;e++){var w=b[e];for(y=0;y<w.length;y++){var k=w[y],T=x+e;_.hasOwnProperty(k)?a.warn(\"Node \"+k+\" is already part of a group.\"):_[k]=T}}var M={source:[],target:[]};for(e=0;e<i.value.length;e++){var A=i.value[e],S=i.source[e],E=i.target[e];if(A>0&&s(S,x)&&s(E,x)&&(!_.hasOwnProperty(S)||!_.hasOwnProperty(E)||_[S]!==_[E])){_.hasOwnProperty(E)&&(E=_[E]),_.hasOwnProperty(S)&&(S=_[S]),E=+E,h[S=+S]=h[E]=!0;var L=\"\";i.label&&i.label[e]&&(L=i.label[e]);var C=null;L&&f.hasOwnProperty(L)&&(C=f[L]),c.push({pointNumber:e,label:L,color:u?i.color[e]:i.color,concentrationscale:C,source:S,target:E,value:+A}),M.source.push(S),M.target.push(E)}}var P=x+b.length,O=o(r.color),z=[];for(e=0;e<P;e++)if(h[e]){var I=r.label[e];z.push({group:e>x-1,childrenNodes:[],pointNumber:e,label:I,color:O?r.color[e]:r.color})}var D=!1;return function(t,e,r){for(var i=a.init2dArray(t,0),o=0;o<Math.min(e.length,r.length);o++)if(a.isIndex(e[o],t)&&a.isIndex(r[o],t)){if(e[o]===r[o])return!0;i[e[o]].push(r[o])}return n(i).components.some(function(t){return t.length>1})}(P,M.source,M.target)&&(D=!0),{circular:D,links:c,nodes:z,groups:b,groupLookup:_}}e.exports=function(t,e){var r=c(e);return i({circular:r.circular,_nodes:r.nodes,_links:r.links,_groups:r.groups,_groupLookup:r.groupLookup})}},{\"../../components/colorscale\":604,\"../../lib\":717,\"../../lib/gup\":715,\"strongly-connected-components\":529}],1113:[function(t,e,r){\"use strict\";e.exports={nodeTextOffsetHorizontal:4,nodeTextOffsetVertical:3,nodePadAcross:10,sankeyIterations:50,forceIterations:5,forceTicksPerFrame:10,duration:500,ease:\"linear\",cn:{sankey:\"sankey\",sankeyLinks:\"sankey-links\",sankeyLink:\"sankey-link\",sankeyNodeSet:\"sankey-node-set\",sankeyNode:\"sankey-node\",nodeRect:\"node-rect\",nodeCapture:\"node-capture\",nodeCentered:\"node-entered\",nodeLabelGuide:\"node-label-guide\",nodeLabel:\"node-label\",nodeLabelTextPath:\"node-label-text-path\"}}},{}],1114:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./attributes\"),i=t(\"../../components/color\"),o=t(\"tinycolor2\"),s=t(\"../../plots/domain\").defaults,l=t(\"../../components/fx/hoverlabel_defaults\"),c=t(\"../../plot_api/plot_template\"),u=t(\"../../plots/array_container_defaults\");function h(t,e){function r(r,i){return n.coerce(t,e,a.link.colorscales,r,i)}r(\"label\"),r(\"cmin\"),r(\"cmax\"),r(\"colorscale\")}e.exports=function(t,e,r,f){function p(r,i){return n.coerce(t,e,a,r,i)}var d=n.extendDeep(f.hoverlabel,t.hoverlabel),g=t.node,v=c.newContainer(e,\"node\");function m(t,e){return n.coerce(g,v,a.node,t,e)}m(\"label\"),m(\"groups\"),m(\"x\"),m(\"y\"),m(\"pad\"),m(\"thickness\"),m(\"line.color\"),m(\"line.width\"),m(\"hoverinfo\",t.hoverinfo),l(g,v,m,d),m(\"hovertemplate\");var y=f.colorway;m(\"color\",v.label.map(function(t,e){return i.addOpacity(function(t){return y[t%y.length]}(e),.8)}));var x=t.link||{},b=c.newContainer(e,\"link\");function _(t,e){return n.coerce(x,b,a.link,t,e)}_(\"label\"),_(\"source\"),_(\"target\"),_(\"value\"),_(\"line.color\"),_(\"line.width\"),_(\"hoverinfo\",t.hoverinfo),l(x,b,_,d),_(\"hovertemplate\");var w,k=o(f.paper_bgcolor).getLuminance()<.333?\"rgba(255, 255, 255, 0.6)\":\"rgba(0, 0, 0, 0.2)\";_(\"color\",n.repeat(k,b.value.length)),u(x,b,{name:\"colorscales\",handleItemDefaults:h}),s(e,f,p),p(\"orientation\"),p(\"valueformat\"),p(\"valuesuffix\"),v.x.length&&v.y.length&&(w=\"freeform\"),p(\"arrangement\",w),n.coerceFont(p,\"textfont\",n.extendFlat({},f.font)),e._length=null}},{\"../../components/color\":592,\"../../components/fx/hoverlabel_defaults\":629,\"../../lib\":717,\"../../plot_api/plot_template\":755,\"../../plots/array_container_defaults\":761,\"../../plots/domain\":790,\"./attributes\":1110,tinycolor2:536}],1115:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"./plot\"),moduleType:\"trace\",name:\"sankey\",basePlotModule:t(\"./base_plot\"),selectPoints:t(\"./select.js\"),categories:[\"noOpacity\"],meta:{}}},{\"./attributes\":1110,\"./base_plot\":1111,\"./calc\":1112,\"./defaults\":1114,\"./plot\":1116,\"./select.js\":1118}],1116:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"./render\"),i=t(\"../../components/fx\"),o=t(\"../../components/color\"),s=t(\"../../lib\"),l=t(\"./constants\").cn,c=s._;function u(t){return\"\"!==t}function h(t,e){return t.filter(function(t){return t.key===e.traceId})}function f(t,e){n.select(t).select(\"path\").style(\"fill-opacity\",e),n.select(t).select(\"rect\").style(\"fill-opacity\",e)}function p(t){n.select(t).select(\"text.name\").style(\"fill\",\"black\")}function d(t){return function(e){return-1!==t.node.sourceLinks.indexOf(e.link)||-1!==t.node.targetLinks.indexOf(e.link)}}function g(t){return function(e){return-1!==e.node.sourceLinks.indexOf(t.link)||-1!==e.node.targetLinks.indexOf(t.link)}}function v(t,e,r){e&&r&&h(r,e).selectAll(\".\"+l.sankeyLink).filter(d(e)).call(y.bind(0,e,r,!1))}function m(t,e,r){e&&r&&h(r,e).selectAll(\".\"+l.sankeyLink).filter(d(e)).call(x.bind(0,e,r,!1))}function y(t,e,r,n){var a=n.datum().link.label;n.style(\"fill-opacity\",function(t){if(!t.link.concentrationscale)return.4}),a&&h(e,t).selectAll(\".\"+l.sankeyLink).filter(function(t){return t.link.label===a}).style(\"fill-opacity\",function(t){if(!t.link.concentrationscale)return.4}),r&&h(e,t).selectAll(\".\"+l.sankeyNode).filter(g(t)).call(v)}function x(t,e,r,n){var a=n.datum().link.label;n.style(\"fill-opacity\",function(t){return t.tinyColorAlpha}),a&&h(e,t).selectAll(\".\"+l.sankeyLink).filter(function(t){return t.link.label===a}).style(\"fill-opacity\",function(t){return t.tinyColorAlpha}),r&&h(e,t).selectAll(l.sankeyNode).filter(g(t)).call(m)}function b(t,e){var r=t.hoverlabel||{},n=s.nestedProperty(r,e).get();return!Array.isArray(n)&&n}e.exports=function(t,e){for(var r=t._fullLayout,s=r._paper,h=r._size,d=0;d<t._fullData.length;d++)if(t._fullData[d].visible&&t._fullData[d].type===l.sankey&&!t._fullData[d]._viewInitial){var g=t._fullData[d].node;t._fullData[d]._viewInitial={node:{groups:g.groups.slice(),x:g.x.slice(),y:g.y.slice()}}}var _=c(t,\"source:\")+\" \",w=c(t,\"target:\")+\" \",k=c(t,\"concentration:\")+\" \",T=c(t,\"incoming flow count:\")+\" \",M=c(t,\"outgoing flow count:\")+\" \";a(t,s,e,{width:h.w,height:h.h,margin:{t:h.t,r:h.r,b:h.b,l:h.l}},{linkEvents:{hover:function(e,r,a){!1!==t._fullLayout.hovermode&&(n.select(e).call(y.bind(0,r,a,!0)),\"skip\"!==r.link.trace.link.hoverinfo&&(r.link.fullData=r.link.trace,t.emit(\"plotly_hover\",{event:n.event,points:[r.link]})))},follow:function(e,a){if(!1!==t._fullLayout.hovermode){var s=a.link.trace.link;if(\"none\"!==s.hoverinfo&&\"skip\"!==s.hoverinfo){for(var l=[],c=0,h=0;h<a.flow.links.length;h++){var d=a.flow.links[h];if(\"closest\"!==t._fullLayout.hovermode||a.link.pointNumber===d.pointNumber){a.link.pointNumber===d.pointNumber&&(c=h),d.fullData=d.trace,s=a.link.trace.link;var g=m(d),v={valueLabel:n.format(a.valueFormat)(d.value)+a.valueSuffix};l.push({x:g[0],y:g[1],name:v.valueLabel,text:[d.label||\"\",_+d.source.label,w+d.target.label,d.concentrationscale?k+n.format(\"%0.2f\")(d.flow.labelConcentration):\"\"].filter(u).join(\"<br>\"),color:b(s,\"bgcolor\")||o.addOpacity(d.color,1),borderColor:b(s,\"bordercolor\"),fontFamily:b(s,\"font.family\"),fontSize:b(s,\"font.size\"),fontColor:b(s,\"font.color\"),nameLength:b(s,\"namelength\"),textAlign:b(s,\"align\"),idealAlign:n.event.x<g[0]?\"right\":\"left\",hovertemplate:s.hovertemplate,hovertemplateLabels:v,eventData:[d]})}}i.loneHover(l,{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:t,anchorIndex:c}).each(function(){a.link.concentrationscale||f(this,.65),p(this)})}}function m(t){var e,r;t.circular?(e=(t.circularPathData.leftInnerExtent+t.circularPathData.rightInnerExtent)/2,r=t.circularPathData.verticalFullExtent):(e=(t.source.x1+t.target.x0)/2,r=(t.y0+t.y1)/2);var n=[e,r];return\"v\"===t.trace.orientation&&n.reverse(),n[0]+=a.parent.translateX,n[1]+=a.parent.translateY,n}},unhover:function(e,a,o){!1!==t._fullLayout.hovermode&&(n.select(e).call(x.bind(0,a,o,!0)),\"skip\"!==a.link.trace.link.hoverinfo&&(a.link.fullData=a.link.trace,t.emit(\"plotly_unhover\",{event:n.event,points:[a.link]})),i.loneUnhover(r._hoverlayer.node()))},select:function(e,r){var a=r.link;a.originalEvent=n.event,t._hoverdata=[a],i.click(t,{target:!0})}},nodeEvents:{hover:function(e,r,a){!1!==t._fullLayout.hovermode&&(n.select(e).call(v,r,a),\"skip\"!==r.node.trace.node.hoverinfo&&(r.node.fullData=r.node.trace,t.emit(\"plotly_hover\",{event:n.event,points:[r.node]})))},follow:function(e,a){if(!1!==t._fullLayout.hovermode){var o=a.node.trace.node;if(\"none\"!==o.hoverinfo&&\"skip\"!==o.hoverinfo){var s=n.select(e).select(\".\"+l.nodeRect),c=t._fullLayout._paperdiv.node().getBoundingClientRect(),h=s.node().getBoundingClientRect(),d=h.left-2-c.left,g=h.right+2-c.left,v=h.top+h.height/4-c.top,m={valueLabel:n.format(a.valueFormat)(a.node.value)+a.valueSuffix};a.node.fullData=a.node.trace;var y=i.loneHover({x0:d,x1:g,y:v,name:n.format(a.valueFormat)(a.node.value)+a.valueSuffix,text:[a.node.label,T+a.node.targetLinks.length,M+a.node.sourceLinks.length].filter(u).join(\"<br>\"),color:b(o,\"bgcolor\")||a.tinyColorHue,borderColor:b(o,\"bordercolor\"),fontFamily:b(o,\"font.family\"),fontSize:b(o,\"font.size\"),fontColor:b(o,\"font.color\"),nameLength:b(o,\"namelength\"),textAlign:b(o,\"align\"),idealAlign:\"left\",hovertemplate:o.hovertemplate,hovertemplateLabels:m,eventData:[a.node]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:t});f(y,.85),p(y)}}},unhover:function(e,a,o){!1!==t._fullLayout.hovermode&&(n.select(e).call(m,a,o),\"skip\"!==a.node.trace.node.hoverinfo&&(a.node.fullData=a.node.trace,t.emit(\"plotly_unhover\",{event:n.event,points:[a.node]})),i.loneUnhover(r._hoverlayer.node()))},select:function(e,r,a){var o=r.node;o.originalEvent=n.event,t._hoverdata=[o],n.select(e).call(m,r,a),i.click(t,{target:!0})}}})}},{\"../../components/color\":592,\"../../components/fx\":630,\"../../lib\":717,\"./constants\":1113,\"./render\":1117,d3:165}],1117:[function(t,e,r){\"use strict\";var n=t(\"./constants\"),a=t(\"d3\"),i=t(\"tinycolor2\"),o=t(\"../../components/color\"),s=t(\"../../components/drawing\"),l=t(\"@plotly/d3-sankey\"),c=t(\"@plotly/d3-sankey-circular\"),u=t(\"d3-force\"),h=t(\"../../lib\"),f=t(\"../../lib/gup\"),p=f.keyFun,d=f.repeat,g=f.unwrap,v=t(\"d3-interpolate\").interpolateNumber,m=t(\"../../registry\");function y(){var t=.5;return function(e){if(e.link.circular)return r=e.link,n=r.width/2,a=r.circularPathData,\"top\"===r.circularLinkType?\"M \"+a.targetX+\" \"+(a.targetY+n)+\" L\"+a.rightInnerExtent+\" \"+(a.targetY+n)+\"A\"+(a.rightLargeArcRadius+n)+\" \"+(a.rightSmallArcRadius+n)+\" 0 0 1 \"+(a.rightFullExtent-n)+\" \"+(a.targetY-a.rightSmallArcRadius)+\"L\"+(a.rightFullExtent-n)+\" \"+a.verticalRightInnerExtent+\"A\"+(a.rightLargeArcRadius+n)+\" \"+(a.rightLargeArcRadius+n)+\" 0 0 1 \"+a.rightInnerExtent+\" \"+(a.verticalFullExtent-n)+\"L\"+a.leftInnerExtent+\" \"+(a.verticalFullExtent-n)+\"A\"+(a.leftLargeArcRadius+n)+\" \"+(a.leftLargeArcRadius+n)+\" 0 0 1 \"+(a.leftFullExtent+n)+\" \"+a.verticalLeftInnerExtent+\"L\"+(a.leftFullExtent+n)+\" \"+(a.sourceY-a.leftSmallArcRadius)+\"A\"+(a.leftLargeArcRadius+n)+\" \"+(a.leftSmallArcRadius+n)+\" 0 0 1 \"+a.leftInnerExtent+\" \"+(a.sourceY+n)+\"L\"+a.sourceX+\" \"+(a.sourceY+n)+\"L\"+a.sourceX+\" \"+(a.sourceY-n)+\"L\"+a.leftInnerExtent+\" \"+(a.sourceY-n)+\"A\"+(a.leftLargeArcRadius-n)+\" \"+(a.leftSmallArcRadius-n)+\" 0 0 0 \"+(a.leftFullExtent-n)+\" \"+(a.sourceY-a.leftSmallArcRadius)+\"L\"+(a.leftFullExtent-n)+\" \"+a.verticalLeftInnerExtent+\"A\"+(a.leftLargeArcRadius-n)+\" \"+(a.leftLargeArcRadius-n)+\" 0 0 0 \"+a.leftInnerExtent+\" \"+(a.verticalFullExtent+n)+\"L\"+a.rightInnerExtent+\" \"+(a.verticalFullExtent+n)+\"A\"+(a.rightLargeArcRadius-n)+\" \"+(a.rightLargeArcRadius-n)+\" 0 0 0 \"+(a.rightFullExtent+n)+\" \"+a.verticalRightInnerExtent+\"L\"+(a.rightFullExtent+n)+\" \"+(a.targetY-a.rightSmallArcRadius)+\"A\"+(a.rightLargeArcRadius-n)+\" \"+(a.rightSmallArcRadius-n)+\" 0 0 0 \"+a.rightInnerExtent+\" \"+(a.targetY-n)+\"L\"+a.targetX+\" \"+(a.targetY-n)+\"Z\":\"M \"+a.targetX+\" \"+(a.targetY-n)+\" L\"+a.rightInnerExtent+\" \"+(a.targetY-n)+\"A\"+(a.rightLargeArcRadius+n)+\" \"+(a.rightSmallArcRadius+n)+\" 0 0 0 \"+(a.rightFullExtent-n)+\" \"+(a.targetY+a.rightSmallArcRadius)+\"L\"+(a.rightFullExtent-n)+\" \"+a.verticalRightInnerExtent+\"A\"+(a.rightLargeArcRadius+n)+\" \"+(a.rightLargeArcRadius+n)+\" 0 0 0 \"+a.rightInnerExtent+\" \"+(a.verticalFullExtent+n)+\"L\"+a.leftInnerExtent+\" \"+(a.verticalFullExtent+n)+\"A\"+(a.leftLargeArcRadius+n)+\" \"+(a.leftLargeArcRadius+n)+\" 0 0 0 \"+(a.leftFullExtent+n)+\" \"+a.verticalLeftInnerExtent+\"L\"+(a.leftFullExtent+n)+\" \"+(a.sourceY+a.leftSmallArcRadius)+\"A\"+(a.leftLargeArcRadius+n)+\" \"+(a.leftSmallArcRadius+n)+\" 0 0 0 \"+a.leftInnerExtent+\" \"+(a.sourceY-n)+\"L\"+a.sourceX+\" \"+(a.sourceY-n)+\"L\"+a.sourceX+\" \"+(a.sourceY+n)+\"L\"+a.leftInnerExtent+\" \"+(a.sourceY+n)+\"A\"+(a.leftLargeArcRadius-n)+\" \"+(a.leftSmallArcRadius-n)+\" 0 0 1 \"+(a.leftFullExtent-n)+\" \"+(a.sourceY+a.leftSmallArcRadius)+\"L\"+(a.leftFullExtent-n)+\" \"+a.verticalLeftInnerExtent+\"A\"+(a.leftLargeArcRadius-n)+\" \"+(a.leftLargeArcRadius-n)+\" 0 0 1 \"+a.leftInnerExtent+\" \"+(a.verticalFullExtent-n)+\"L\"+a.rightInnerExtent+\" \"+(a.verticalFullExtent-n)+\"A\"+(a.rightLargeArcRadius-n)+\" \"+(a.rightLargeArcRadius-n)+\" 0 0 1 \"+(a.rightFullExtent+n)+\" \"+a.verticalRightInnerExtent+\"L\"+(a.rightFullExtent+n)+\" \"+(a.targetY+a.rightSmallArcRadius)+\"A\"+(a.rightLargeArcRadius-n)+\" \"+(a.rightSmallArcRadius-n)+\" 0 0 1 \"+a.rightInnerExtent+\" \"+(a.targetY+n)+\"L\"+a.targetX+\" \"+(a.targetY+n)+\"Z\";var r,n,a,i=e.link.source.x1,o=e.link.target.x0,s=v(i,o),l=s(t),c=s(1-t),u=e.link.y0-e.link.width/2,h=e.link.y0+e.link.width/2,f=e.link.y1-e.link.width/2,p=e.link.y1+e.link.width/2;return\"M\"+i+\",\"+u+\"C\"+l+\",\"+u+\" \"+c+\",\"+f+\" \"+o+\",\"+f+\"L\"+o+\",\"+p+\"C\"+c+\",\"+p+\" \"+l+\",\"+h+\" \"+i+\",\"+h+\"Z\"}}function x(t){t.attr(\"transform\",function(t){return\"translate(\"+t.node.x0.toFixed(3)+\", \"+t.node.y0.toFixed(3)+\")\"})}function b(t){t.call(x)}function _(t,e){t.call(b),e.attr(\"d\",y())}function w(t){t.attr(\"width\",function(t){return t.node.x1-t.node.x0}).attr(\"height\",function(t){return t.visibleHeight})}function k(t){return t.link.width>1||t.linkLineWidth>0}function T(t){return\"translate(\"+t.translateX+\",\"+t.translateY+\")\"+(t.horizontal?\"matrix(1 0 0 1 0 0)\":\"matrix(0 1 1 0 0 0)\")}function M(t){return\"translate(\"+(t.horizontal?0:t.labelY)+\" \"+(t.horizontal?t.labelY:0)+\")\"}function A(t){return a.svg.line()([[t.horizontal?t.left?-t.sizeAcross:t.visibleWidth+n.nodeTextOffsetHorizontal:n.nodeTextOffsetHorizontal,0],[t.horizontal?t.left?-n.nodeTextOffsetHorizontal:t.sizeAcross:t.visibleHeight-n.nodeTextOffsetHorizontal,0]])}function S(t){return t.horizontal?\"matrix(1 0 0 1 0 0)\":\"matrix(0 1 1 0 0 0)\"}function E(t){return t.horizontal?\"scale(1 1)\":\"scale(-1 1)\"}function L(t){return t.darkBackground&&!t.horizontal?\"rgb(255,255,255)\":\"rgb(0,0,0)\"}function C(t){return t.horizontal&&t.left?\"100%\":\"0%\"}function P(t,e,r){t.on(\".basic\",null).on(\"mouseover.basic\",function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.hover(this,t,e),t.interactionState.hovered=[this,t])}).on(\"mousemove.basic\",function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.follow(this,t),t.interactionState.hovered=[this,t])}).on(\"mouseout.basic\",function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.unhover(this,t,e),t.interactionState.hovered=!1)}).on(\"click.basic\",function(t){t.interactionState.hovered&&(r.unhover(this,t,e),t.interactionState.hovered=!1),t.interactionState.dragInProgress||t.partOfGroup||r.select(this,t,e)})}function O(t,e,r,i){var o=a.behavior.drag().origin(function(t){return{x:t.node.x0+t.visibleWidth/2,y:t.node.y0+t.visibleHeight/2}}).on(\"dragstart\",function(a){if(\"fixed\"!==a.arrangement&&(h.ensureSingle(i._fullLayout._infolayer,\"g\",\"dragcover\",function(t){i._fullLayout._dragCover=t}),h.raiseToTop(this),a.interactionState.dragInProgress=a.node,I(a.node),a.interactionState.hovered&&(r.nodeEvents.unhover.apply(0,a.interactionState.hovered),a.interactionState.hovered=!1),\"snap\"===a.arrangement)){var o=a.traceId+\"|\"+a.key;a.forceLayouts[o]?a.forceLayouts[o].alpha(1):function(t,e,r,a){!function(t){for(var e=0;e<t.length;e++)t[e].y=(t[e].y0+t[e].y1)/2,t[e].x=(t[e].x0+t[e].x1)/2}(r.graph.nodes);var i=r.graph.nodes.filter(function(t){return t.originalX===r.node.originalX}).filter(function(t){return!t.partOfGroup});r.forceLayouts[e]=u.forceSimulation(i).alphaDecay(0).force(\"collide\",u.forceCollide().radius(function(t){return t.dy/2+r.nodePad/2}).strength(1).iterations(n.forceIterations)).force(\"constrain\",function(t,e,r,a){return function(){for(var t=0,i=0;i<r.length;i++){var o=r[i];o===a.interactionState.dragInProgress?(o.x=o.lastDraggedX,o.y=o.lastDraggedY):(o.vx=(o.originalX-o.x)/n.forceTicksPerFrame,o.y=Math.min(a.size-o.dy/2,Math.max(o.dy/2,o.y))),t=Math.max(t,Math.abs(o.vx),Math.abs(o.vy))}!a.interactionState.dragInProgress&&t<.1&&a.forceLayouts[e].alpha()>0&&a.forceLayouts[e].alpha(0)}}(0,e,i,r)).stop()}(0,o,a),function(t,e,r,a,i){window.requestAnimationFrame(function o(){var s;for(s=0;s<n.forceTicksPerFrame;s++)r.forceLayouts[a].tick();var l=r.graph.nodes;if(function(t){for(var e=0;e<t.length;e++)t[e].y0=t[e].y-t[e].dy/2,t[e].y1=t[e].y0+t[e].dy,t[e].x0=t[e].x-t[e].dx/2,t[e].x1=t[e].x0+t[e].dx}(l),r.sankey.update(r.graph),_(t.filter(D(r)),e),r.forceLayouts[a].alpha()>0)window.requestAnimationFrame(o);else{var c=r.node.originalX;r.node.x0=c-r.visibleWidth/2,r.node.x1=c+r.visibleWidth/2,z(r,i)}})}(t,e,a,o,i)}}).on(\"drag\",function(r){if(\"fixed\"!==r.arrangement){var n=a.event.x,i=a.event.y;\"snap\"===r.arrangement?(r.node.x0=n-r.visibleWidth/2,r.node.x1=n+r.visibleWidth/2,r.node.y0=i-r.visibleHeight/2,r.node.y1=i+r.visibleHeight/2):(\"freeform\"===r.arrangement&&(r.node.x0=n-r.visibleWidth/2,r.node.x1=n+r.visibleWidth/2),i=Math.max(0,Math.min(r.size-r.visibleHeight/2,i)),r.node.y0=i-r.visibleHeight/2,r.node.y1=i+r.visibleHeight/2),I(r.node),\"snap\"!==r.arrangement&&(r.sankey.update(r.graph),_(t.filter(D(r)),e))}}).on(\"dragend\",function(t){if(\"fixed\"!==t.arrangement){t.interactionState.dragInProgress=!1;for(var e=0;e<t.node.childrenNodes.length;e++)t.node.childrenNodes[e].x=t.node.x,t.node.childrenNodes[e].y=t.node.y;\"snap\"!==t.arrangement&&z(t,i)}});t.on(\".drag\",null).call(o)}function z(t,e){for(var r=[],n=[],a=0;a<t.graph.nodes.length;a++){var i=(t.graph.nodes[a].x0+t.graph.nodes[a].x1)/2,o=(t.graph.nodes[a].y0+t.graph.nodes[a].y1)/2;r.push(i/t.figure.width),n.push(o/t.figure.height)}m.call(\"_guiRestyle\",e,{\"node.x\":[r],\"node.y\":[n]},t.trace.index).then(function(){e._fullLayout._dragCover&&e._fullLayout._dragCover.remove()})}function I(t){t.lastDraggedX=t.x0+t.dx/2,t.lastDraggedY=t.y0+t.dy/2}function D(t){return function(e){return e.node.originalX===t.node.originalX}}e.exports=function(t,e,r,u,f){var v=!1;h.ensureSingle(t._fullLayout._infolayer,\"g\",\"first-render\",function(){v=!0});var m=t._fullLayout._dragCover,b=r.filter(function(t){return g(t).trace.visible}).map(function(t,e,r){var a,o=g(e),s=o.trace,u=s.domain,f=\"h\"===s.orientation,p=s.node.pad,d=s.node.thickness,v=t.width*(u.x[1]-u.x[0]),m=t.height*(u.y[1]-u.y[0]),y=o._nodes,x=o._links,b=o.circular;(a=b?c.sankeyCircular().circularLinkGap(0):l.sankey()).iterations(n.sankeyIterations).size(f?[v,m]:[m,v]).nodeWidth(d).nodePadding(p).nodeId(function(t){return t.pointNumber}).nodes(y).links(x);var _,w,k,T=a();for(var M in a.nodePadding()<p&&h.warn(\"node.pad was reduced to \",a.nodePadding(),\" to fit within the figure.\"),o._groupLookup){var A,S=parseInt(o._groupLookup[M]);for(_=0;_<T.nodes.length;_++)if(T.nodes[_].pointNumber===S){A=T.nodes[_];break}if(A){var E={pointNumber:parseInt(M),x0:A.x0,x1:A.x1,y0:A.y0,y1:A.y1,partOfGroup:!0,sourceLinks:[],targetLinks:[]};T.nodes.unshift(E),A.childrenNodes.unshift(E)}}if(function(){for(_=0;_<T.nodes.length;_++){var t,e,r=T.nodes[_],n={};for(w=0;w<r.targetLinks.length;w++)t=(e=r.targetLinks[w]).source.pointNumber+\":\"+e.target.pointNumber,n.hasOwnProperty(t)||(n[t]=[]),n[t].push(e);var a=Object.keys(n);for(w=0;w<a.length;w++){var o=n[t=a[w]],s=0,l={};for(k=0;k<o.length;k++)l[(e=o[k]).label]||(l[e.label]=0),l[e.label]+=e.value,s+=e.value;for(k=0;k<o.length;k++)(e=o[k]).flow={value:s,labelConcentration:l[e.label]/s,concentration:e.value/s,links:o},e.concentrationscale&&(e.color=i(e.concentrationscale(e.flow.labelConcentration)))}var c=0;for(w=0;w<r.sourceLinks.length;w++)c+=r.sourceLinks[w].value;for(w=0;w<r.sourceLinks.length;w++)(e=r.sourceLinks[w]).concentrationOut=e.value/c;var u=0;for(w=0;w<r.targetLinks.length;w++)u+=r.targetLinks[w].value;for(w=0;w<r.targetLinks.length;w++)(e=r.targetLinks[w]).concenrationIn=e.value/u}}(),s.node.x.length&&s.node.y.length){for(_=0;_<Math.min(s.node.x.length,s.node.y.length,T.nodes.length);_++)if(s.node.x[_]&&s.node.y[_]){var L=[s.node.x[_]*v,s.node.y[_]*m];T.nodes[_].x0=L[0]-d/2,T.nodes[_].x1=L[0]+d/2;var C=T.nodes[_].y1-T.nodes[_].y0;T.nodes[_].y0=L[1]-C/2,T.nodes[_].y1=L[1]+C/2}\"snap\"===s.arrangement&&function(t){t.forEach(function(t){var e,r,n,a=0,i=t.length;for(t.sort(function(t,e){return t.y0-e.y0}),n=0;n<i;++n)(e=t[n]).y0>=a||(r=a-e.y0)>1e-6&&(e.y0+=r,e.y1+=r),a=e.y1+p})}(function(t){var e,r,n=t.map(function(t,e){return{x0:t.x0,index:e}}).sort(function(t,e){return t.x0-e.x0}),a=[],i=-1,o=-1/0;for(_=0;_<n.length;_++){var s=t[n[_].index];s.x0>o+d&&(i+=1,e=s.x0),o=s.x0,a[i]||(a[i]=[]),a[i].push(s),r=e-s.x0,s.x0+=r,s.x1+=r}return a}(y=T.nodes)),a.update(T)}return{circular:b,key:r,trace:s,guid:h.randstr(),horizontal:f,width:v,height:m,nodePad:s.node.pad,nodeLineColor:s.node.line.color,nodeLineWidth:s.node.line.width,linkLineColor:s.link.line.color,linkLineWidth:s.link.line.width,valueFormat:s.valueformat,valueSuffix:s.valuesuffix,textFont:s.textfont,translateX:u.x[0]*t.width+t.margin.l,translateY:t.height-u.y[1]*t.height+t.margin.t,dragParallel:f?m:v,dragPerpendicular:f?v:m,arrangement:s.arrangement,sankey:a,graph:T,forceLayouts:{},interactionState:{dragInProgress:!1,hovered:!1}}}.bind(null,u)),_=e.selectAll(\".\"+n.cn.sankey).data(b,p);_.exit().remove(),_.enter().append(\"g\").classed(n.cn.sankey,!0).style(\"box-sizing\",\"content-box\").style(\"position\",\"absolute\").style(\"left\",0).style(\"shape-rendering\",\"geometricPrecision\").style(\"pointer-events\",\"auto\").attr(\"transform\",T),_.each(function(e,r){t._fullData[r]._sankey=e;var n=\"bgsankey-\"+e.trace.uid+\"-\"+r;h.ensureSingle(t._fullLayout._draggers,\"rect\",n),t._fullData[r]._bgRect=a.select(\".\"+n),t._fullData[r]._bgRect.style(\"pointer-events\",\"all\").attr(\"width\",e.width).attr(\"height\",e.height).attr(\"x\",e.translateX).attr(\"y\",e.translateY).classed(\"bgsankey\",!0).style({fill:\"transparent\",\"stroke-width\":0})}),_.transition().ease(n.ease).duration(n.duration).attr(\"transform\",T);var z=_.selectAll(\".\"+n.cn.sankeyLinks).data(d,p);z.enter().append(\"g\").classed(n.cn.sankeyLinks,!0).style(\"fill\",\"none\");var I=z.selectAll(\".\"+n.cn.sankeyLink).data(function(t){return t.graph.links.filter(function(t){return t.value}).map(function(t,e,r){var n=i(e.color),a=e.source.label+\"|\"+e.target.label+\"__\"+r;return e.trace=t.trace,e.curveNumber=t.trace.index,{circular:t.circular,key:a,traceId:t.key,pointNumber:e.pointNumber,link:e,tinyColorHue:o.tinyRGB(n),tinyColorAlpha:n.getAlpha(),linkPath:y,linkLineColor:t.linkLineColor,linkLineWidth:t.linkLineWidth,valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,parent:t,interactionState:t.interactionState,flow:e.flow}}.bind(null,t))},p);I.enter().append(\"path\").classed(n.cn.sankeyLink,!0).call(P,_,f.linkEvents),I.style(\"stroke\",function(t){return k(t)?o.tinyRGB(i(t.linkLineColor)):t.tinyColorHue}).style(\"stroke-opacity\",function(t){return k(t)?o.opacity(t.linkLineColor):t.tinyColorAlpha}).style(\"fill\",function(t){return t.tinyColorHue}).style(\"fill-opacity\",function(t){return t.tinyColorAlpha}).style(\"stroke-width\",function(t){return k(t)?t.linkLineWidth:1}).attr(\"d\",y()),I.style(\"opacity\",function(){return t._context.staticPlot||v||m?1:0}).transition().ease(n.ease).duration(n.duration).style(\"opacity\",1),I.exit().transition().ease(n.ease).duration(n.duration).style(\"opacity\",0).remove();var D=_.selectAll(\".\"+n.cn.sankeyNodeSet).data(d,p);D.enter().append(\"g\").classed(n.cn.sankeyNodeSet,!0),D.style(\"cursor\",function(t){switch(t.arrangement){case\"fixed\":return\"default\";case\"perpendicular\":return\"ns-resize\";default:return\"move\"}});var R=D.selectAll(\".\"+n.cn.sankeyNode).data(function(t){var e=t.graph.nodes;return function(t){var e,r=[];for(e=0;e<t.length;e++)t[e].originalX=(t[e].x0+t[e].x1)/2,t[e].originalY=(t[e].y0+t[e].y1)/2,-1===r.indexOf(t[e].originalX)&&r.push(t[e].originalX);for(r.sort(function(t,e){return t-e}),e=0;e<t.length;e++)t[e].originalLayerIndex=r.indexOf(t[e].originalX),t[e].originalLayer=t[e].originalLayerIndex/(r.length-1)}(e),e.map(function(t,e){var r=i(e.color),a=n.nodePadAcross,s=t.nodePad/2;e.dx=e.x1-e.x0,e.dy=e.y1-e.y0;var l=e.dx,c=Math.max(.5,e.dy),u=\"node_\"+e.pointNumber;return e.group&&(u=h.randstr()),e.trace=t.trace,e.curveNumber=t.trace.index,{index:e.pointNumber,key:u,partOfGroup:e.partOfGroup||!1,group:e.group,traceId:t.key,trace:t.trace,node:e,nodePad:t.nodePad,nodeLineColor:t.nodeLineColor,nodeLineWidth:t.nodeLineWidth,textFont:t.textFont,size:t.horizontal?t.height:t.width,visibleWidth:Math.ceil(l),visibleHeight:c,zoneX:-a,zoneY:-s,zoneWidth:l+2*a,zoneHeight:c+2*s,labelY:t.horizontal?e.dy/2+1:e.dx/2+1,left:1===e.originalLayer,sizeAcross:t.width,forceLayouts:t.forceLayouts,horizontal:t.horizontal,darkBackground:r.getBrightness()<=128,tinyColorHue:o.tinyRGB(r),tinyColorAlpha:r.getAlpha(),valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,graph:t.graph,arrangement:t.arrangement,uniqueNodeLabelPathId:[t.guid,t.key,u].join(\"_\"),interactionState:t.interactionState,figure:t}}.bind(null,t))},p);R.enter().append(\"g\").classed(n.cn.sankeyNode,!0).call(x).style(\"opacity\",function(e){return!t._context.staticPlot&&!v||e.partOfGroup?0:1}),R.call(P,_,f.nodeEvents).call(O,I,f,t),R.transition().ease(n.ease).duration(n.duration).call(x).style(\"opacity\",function(t){return t.partOfGroup?0:1}),R.exit().transition().ease(n.ease).duration(n.duration).style(\"opacity\",0).remove();var F=R.selectAll(\".\"+n.cn.nodeRect).data(d);F.enter().append(\"rect\").classed(n.cn.nodeRect,!0).call(w),F.style(\"stroke-width\",function(t){return t.nodeLineWidth}).style(\"stroke\",function(t){return o.tinyRGB(i(t.nodeLineColor))}).style(\"stroke-opacity\",function(t){return o.opacity(t.nodeLineColor)}).style(\"fill\",function(t){return t.tinyColorHue}).style(\"fill-opacity\",function(t){return t.tinyColorAlpha}),F.transition().ease(n.ease).duration(n.duration).call(w);var B=R.selectAll(\".\"+n.cn.nodeCapture).data(d);B.enter().append(\"rect\").classed(n.cn.nodeCapture,!0).style(\"fill-opacity\",0),B.attr(\"x\",function(t){return t.zoneX}).attr(\"y\",function(t){return t.zoneY}).attr(\"width\",function(t){return t.zoneWidth}).attr(\"height\",function(t){return t.zoneHeight});var N=R.selectAll(\".\"+n.cn.nodeCentered).data(d);N.enter().append(\"g\").classed(n.cn.nodeCentered,!0).attr(\"transform\",M),N.transition().ease(n.ease).duration(n.duration).attr(\"transform\",M);var j=N.selectAll(\".\"+n.cn.nodeLabelGuide).data(d);j.enter().append(\"path\").classed(n.cn.nodeLabelGuide,!0).attr(\"id\",function(t){return t.uniqueNodeLabelPathId}).attr(\"d\",A).attr(\"transform\",S),j.transition().ease(n.ease).duration(n.duration).attr(\"d\",A).attr(\"transform\",S);var V=N.selectAll(\".\"+n.cn.nodeLabel).data(d);V.enter().append(\"text\").classed(n.cn.nodeLabel,!0).attr(\"transform\",E).style(\"user-select\",\"none\").style(\"cursor\",\"default\").style(\"fill\",\"black\"),V.style(\"text-shadow\",function(t){return t.horizontal?\"-1px 1px 1px #fff, 1px 1px 1px #fff, 1px -1px 1px #fff, -1px -1px 1px #fff\":\"none\"}).each(function(t){s.font(V,t.textFont)}),V.transition().ease(n.ease).duration(n.duration).attr(\"transform\",E);var U=V.selectAll(\".\"+n.cn.nodeLabelTextPath).data(d);U.enter().append(\"textPath\").classed(n.cn.nodeLabelTextPath,!0).attr(\"alignment-baseline\",\"middle\").attr(\"xlink:href\",function(t){return\"#\"+t.uniqueNodeLabelPathId}).attr(\"startOffset\",C).style(\"fill\",L),U.text(function(t){return t.horizontal||t.node.dy>5?t.node.label:\"\"}).attr(\"text-anchor\",function(t){return t.horizontal&&t.left?\"end\":\"start\"}),U.transition().ease(n.ease).duration(n.duration).attr(\"startOffset\",C).style(\"fill\",L)}},{\"../../components/color\":592,\"../../components/drawing\":613,\"../../lib\":717,\"../../lib/gup\":715,\"../../registry\":846,\"./constants\":1113,\"@plotly/d3-sankey\":56,\"@plotly/d3-sankey-circular\":55,d3:165,\"d3-force\":158,\"d3-interpolate\":160,tinycolor2:536}],1118:[function(t,e,r){\"use strict\";e.exports=function(t,e){for(var r=[],n=t.cd[0].trace,a=n._sankey.graph.nodes,i=0;i<a.length;i++){var o=a[i];if(!o.partOfGroup){var s=[(o.x0+o.x1)/2,(o.y0+o.y1)/2];\"v\"===n.orientation&&s.reverse(),e&&e.contains(s,!1,i,t)&&r.push({pointNumber:o.pointNumber})}}return r}},{}],1119:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){for(var r=0;r<t.length;r++)t[r].i=r;n.mergeArray(e.text,t,\"tx\"),n.mergeArray(e.texttemplate,t,\"txt\"),n.mergeArray(e.hovertext,t,\"htx\"),n.mergeArray(e.customdata,t,\"data\"),n.mergeArray(e.textposition,t,\"tp\"),e.textfont&&(n.mergeArrayCastPositive(e.textfont.size,t,\"ts\"),n.mergeArray(e.textfont.color,t,\"tc\"),n.mergeArray(e.textfont.family,t,\"tf\"));var a=e.marker;if(a){n.mergeArrayCastPositive(a.size,t,\"ms\"),n.mergeArrayCastPositive(a.opacity,t,\"mo\"),n.mergeArray(a.symbol,t,\"mx\"),n.mergeArray(a.color,t,\"mc\");var i=a.line;a.line&&(n.mergeArray(i.color,t,\"mlc\"),n.mergeArrayCastPositive(i.width,t,\"mlw\"));var o=a.gradient;o&&\"none\"!==o.type&&(n.mergeArray(o.type,t,\"mgt\"),n.mergeArray(o.color,t,\"mgc\"))}}},{\"../../lib\":717}],1120:[function(t,e,r){\"use strict\";var n=t(\"../../plots/template_attributes\").texttemplateAttrs,a=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../components/colorscale/attributes\"),o=t(\"../../plots/font_attributes\"),s=t(\"../../components/drawing/attributes\").dash,l=t(\"../../components/drawing\"),c=t(\"./constants\"),u=t(\"../../lib/extend\").extendFlat;e.exports={x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\",anim:!0},x0:{valType:\"any\",dflt:0,editType:\"calc+clearAxisTypes\",anim:!0},dx:{valType:\"number\",dflt:1,editType:\"calc\",anim:!0},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\",anim:!0},y0:{valType:\"any\",dflt:0,editType:\"calc+clearAxisTypes\",anim:!0},dy:{valType:\"number\",dflt:1,editType:\"calc\",anim:!0},stackgroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},orientation:{valType:\"enumerated\",values:[\"v\",\"h\"],editType:\"calc\"},groupnorm:{valType:\"enumerated\",values:[\"\",\"fraction\",\"percent\"],dflt:\"\",editType:\"calc\"},stackgaps:{valType:\"enumerated\",values:[\"infer zero\",\"interpolate\"],dflt:\"infer zero\",editType:\"calc\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},texttemplate:n({},{}),hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"style\"},mode:{valType:\"flaglist\",flags:[\"lines\",\"markers\",\"text\"],extras:[\"none\"],editType:\"calc\"},hoveron:{valType:\"flaglist\",flags:[\"points\",\"fills\"],editType:\"style\"},hovertemplate:a({},{keys:c.eventDataKeys}),line:{color:{valType:\"color\",editType:\"style\",anim:!0},width:{valType:\"number\",min:0,dflt:2,editType:\"style\",anim:!0},shape:{valType:\"enumerated\",values:[\"linear\",\"spline\",\"hv\",\"vh\",\"hvh\",\"vhv\"],dflt:\"linear\",editType:\"plot\"},smoothing:{valType:\"number\",min:0,max:1.3,dflt:1,editType:\"plot\"},dash:u({},s,{editType:\"style\"}),simplify:{valType:\"boolean\",dflt:!0,editType:\"plot\"},editType:\"plot\"},connectgaps:{valType:\"boolean\",dflt:!1,editType:\"calc\"},cliponaxis:{valType:\"boolean\",dflt:!0,editType:\"plot\"},fill:{valType:\"enumerated\",values:[\"none\",\"tozeroy\",\"tozerox\",\"tonexty\",\"tonextx\",\"toself\",\"tonext\"],editType:\"calc\"},fillcolor:{valType:\"color\",editType:\"style\",anim:!0},marker:u({symbol:{valType:\"enumerated\",values:l.symbolList,dflt:\"circle\",arrayOk:!0,editType:\"style\"},opacity:{valType:\"number\",min:0,max:1,arrayOk:!0,editType:\"style\",anim:!0},size:{valType:\"number\",min:0,dflt:6,arrayOk:!0,editType:\"calc\",anim:!0},maxdisplayed:{valType:\"number\",min:0,dflt:0,editType:\"plot\"},sizeref:{valType:\"number\",dflt:1,editType:\"calc\"},sizemin:{valType:\"number\",min:0,dflt:0,editType:\"calc\"},sizemode:{valType:\"enumerated\",values:[\"diameter\",\"area\"],dflt:\"diameter\",editType:\"calc\"},line:u({width:{valType:\"number\",min:0,arrayOk:!0,editType:\"style\",anim:!0},editType:\"calc\"},i(\"marker.line\",{anim:!0})),gradient:{type:{valType:\"enumerated\",values:[\"radial\",\"horizontal\",\"vertical\",\"none\"],arrayOk:!0,dflt:\"none\",editType:\"calc\"},color:{valType:\"color\",arrayOk:!0,editType:\"calc\"},editType:\"calc\"},editType:\"calc\"},i(\"marker\",{anim:!0})),selected:{marker:{opacity:{valType:\"number\",min:0,max:1,editType:\"style\"},color:{valType:\"color\",editType:\"style\"},size:{valType:\"number\",min:0,editType:\"style\"},editType:\"style\"},textfont:{color:{valType:\"color\",editType:\"style\"},editType:\"style\"},editType:\"style\"},unselected:{marker:{opacity:{valType:\"number\",min:0,max:1,editType:\"style\"},color:{valType:\"color\",editType:\"style\"},size:{valType:\"number\",min:0,editType:\"style\"},editType:\"style\"},textfont:{color:{valType:\"color\",editType:\"style\"},editType:\"style\"},editType:\"style\"},textposition:{valType:\"enumerated\",values:[\"top left\",\"top center\",\"top right\",\"middle left\",\"middle center\",\"middle right\",\"bottom left\",\"bottom center\",\"bottom right\"],dflt:\"middle center\",arrayOk:!0,editType:\"calc\"},textfont:o({editType:\"calc\",colorEditType:\"style\",arrayOk:!0}),r:{valType:\"data_array\",editType:\"calc\"},t:{valType:\"data_array\",editType:\"calc\"}}},{\"../../components/colorscale/attributes\":599,\"../../components/drawing\":613,\"../../components/drawing/attributes\":612,\"../../lib/extend\":708,\"../../plots/font_attributes\":791,\"../../plots/template_attributes\":841,\"./constants\":1124}],1121:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib\"),i=t(\"../../plots/cartesian/axes\"),o=t(\"../../constants/numerical\").BADNUM,s=t(\"./subtypes\"),l=t(\"./colorscale_calc\"),c=t(\"./arrays_to_calcdata\"),u=t(\"./calc_selection\");function h(t,e,r,n,a,o,l){var c=e._length,u=t._fullLayout,h=r._id,f=n._id,p=u._firstScatter[d(e)]===e.uid,v=(g(e,u,r,n)||{}).orientation,m=e.fill;r._minDtick=0,n._minDtick=0;var y={padded:!0},x={padded:!0};l&&(y.ppad=x.ppad=l);var b=c<2||a[0]!==a[c-1]||o[0]!==o[c-1];b&&(\"tozerox\"===m||\"tonextx\"===m&&(p||\"h\"===v))?y.tozero=!0:(e.error_y||{}).visible||\"tonexty\"!==m&&\"tozeroy\"!==m&&(s.hasMarkers(e)||s.hasText(e))||(y.padded=!1,y.ppad=0),b&&(\"tozeroy\"===m||\"tonexty\"===m&&(p||\"v\"===v))?x.tozero=!0:\"tonextx\"!==m&&\"tozerox\"!==m||(x.padded=!1),h&&(e._extremes[h]=i.findExtremes(r,a,y)),f&&(e._extremes[f]=i.findExtremes(n,o,x))}function f(t,e){if(s.hasMarkers(t)){var r,n=t.marker,o=1.6*(t.marker.sizeref||1);if(r=\"area\"===t.marker.sizemode?function(t){return Math.max(Math.sqrt((t||0)/o),3)}:function(t){return Math.max((t||0)/o,3)},a.isArrayOrTypedArray(n.size)){var l={type:\"linear\"};i.setConvert(l);for(var c=l.makeCalcdata(t.marker,\"size\"),u=new Array(e),h=0;h<e;h++)u[h]=r(c[h]);return u}return r(n.size)}}function p(t,e){var r=d(e),n=t._firstScatter;n[r]||(n[r]=e.uid)}function d(t){var e=t.stackgroup;return t.xaxis+t.yaxis+t.type+(e?\"-\"+e:\"\")}function g(t,e,r,n){var a=t.stackgroup;if(a){var i=e._scatterStackOpts[r._id+n._id][a],o=\"v\"===i.orientation?n:r;return\"linear\"===o.type||\"log\"===o.type?i:void 0}}e.exports={calc:function(t,e){var r,s,d,v,m,y,x=t._fullLayout,b=i.getFromId(t,e.xaxis||\"x\"),_=i.getFromId(t,e.yaxis||\"y\"),w=b.makeCalcdata(e,\"x\"),k=_.makeCalcdata(e,\"y\"),T=e._length,M=new Array(T),A=e.ids,S=g(e,x,b,_),E=!1;p(x,e);var L,C=\"x\",P=\"y\";for(S?(a.pushUnique(S.traceIndices,e._expandedIndex),(r=\"v\"===S.orientation)?(P=\"s\",L=\"x\"):(C=\"s\",L=\"y\"),m=\"interpolate\"===S.stackgaps):h(t,e,b,_,w,k,f(e,T)),s=0;s<T;s++){var O=M[s]={},z=n(w[s]),I=n(k[s]);z&&I?(O[C]=w[s],O[P]=k[s]):S&&(r?z:I)?(O[L]=r?w[s]:k[s],O.gap=!0,m?(O.s=o,E=!0):O.s=0):O[C]=O[P]=o,A&&(O.id=String(A[s]))}if(c(M,e),l(t,e),u(M,e),S){for(s=0;s<M.length;)M[s][L]===o?M.splice(s,1):s++;if(a.sort(M,function(t,e){return t[L]-e[L]||t.i-e.i}),E){for(s=0;s<M.length-1&&M[s].gap;)s++;for((y=M[s].s)||(y=M[s].s=0),d=0;d<s;d++)M[d].s=y;for(v=M.length-1;v>s&&M[v].gap;)v--;for(y=M[v].s,d=M.length-1;d>v;d--)M[d].s=y;for(;s<v;)if(M[++s].gap){for(d=s+1;M[d].gap;)d++;for(var D=M[s-1][L],R=M[s-1].s,F=(M[d].s-R)/(M[d][L]-D);s<d;)M[s].s=R+(M[s][L]-D)*F,s++}}}return M},calcMarkerSize:f,calcAxisExpansion:h,setFirstScatter:p,getStackOpts:g}},{\"../../constants/numerical\":693,\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"./arrays_to_calcdata\":1119,\"./calc_selection\":1122,\"./colorscale_calc\":1123,\"./subtypes\":1144,\"fast-isnumeric\":228}],1122:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){n.isArrayOrTypedArray(e.selectedpoints)&&n.tagSelected(t,e)}},{\"../../lib\":717}],1123:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/helpers\").hasColorscale,a=t(\"../../components/colorscale/calc\"),i=t(\"./subtypes\");e.exports=function(t,e){i.hasLines(e)&&n(e,\"line\")&&a(t,e,{vals:e.line.color,containerStr:\"line\",cLetter:\"c\"}),i.hasMarkers(e)&&(n(e,\"marker\")&&a(t,e,{vals:e.marker.color,containerStr:\"marker\",cLetter:\"c\"}),n(e,\"marker.line\")&&a(t,e,{vals:e.marker.line.color,containerStr:\"marker.line\",cLetter:\"c\"}))}},{\"../../components/colorscale/calc\":600,\"../../components/colorscale/helpers\":603,\"./subtypes\":1144}],1124:[function(t,e,r){\"use strict\";e.exports={PTS_LINESONLY:20,minTolerance:.2,toleranceGrowth:10,maxScreensAway:20,eventDataKeys:[]}},{}],1125:[function(t,e,r){\"use strict\";var n=t(\"./calc\");function a(t,e,r,n,a,i,o){a[n]=!0;var s={i:null,gap:!0,s:0};if(s[o]=r,t.splice(e,0,s),e&&r===t[e-1][o]){var l=t[e-1];s.s=l.s,s.i=l.i,s.gap=l.gap}else i&&(s.s=function(t,e,r,n){var a=t[e-1],i=t[e+1];return i?a?a.s+(i.s-a.s)*(r-a[n])/(i[n]-a[n]):i.s:a.s}(t,e,r,o));e||(t[0].t=t[1].t,t[0].trace=t[1].trace,delete t[1].t,delete t[1].trace)}e.exports=function(t,e){var r=e.xaxis,i=e.yaxis,o=r._id+i._id,s=t._fullLayout._scatterStackOpts[o];if(s){var l,c,u,h,f,p,d,g,v,m,y,x,b,_,w,k=t.calcdata;for(var T in s){var M=(m=s[T]).traceIndices;if(M.length){for(y=\"interpolate\"===m.stackgaps,x=m.groupnorm,\"v\"===m.orientation?(b=\"x\",_=\"y\"):(b=\"y\",_=\"x\"),w=new Array(M.length),l=0;l<w.length;l++)w[l]=!1;p=k[M[0]];var A=new Array(p.length);for(l=0;l<p.length;l++)A[l]=p[l][b];for(l=1;l<M.length;l++){for(f=k[M[l]],c=u=0;c<f.length;c++){for(d=f[c][b];d>A[u]&&u<A.length;u++)a(f,c,A[u],l,w,y,b),c++;if(d!==A[u]){for(h=0;h<l;h++)a(k[M[h]],u,d,h,w,y,b);A.splice(u,0,d)}u++}for(;u<A.length;u++)a(f,c,A[u],l,w,y,b),c++}var S=A.length;for(c=0;c<p.length;c++){for(g=p[c][_]=p[c].s,l=1;l<M.length;l++)(f=k[M[l]])[0].trace._rawLength=f[0].trace._length,f[0].trace._length=S,g+=f[c].s,f[c][_]=g;if(x)for(v=(\"fraction\"===x?g:g/100)||1,l=0;l<M.length;l++){var E=k[M[l]][c];E[_]/=v,E.sNorm=E.s/v}}for(l=0;l<M.length;l++){var L=(f=k[M[l]])[0].trace,C=n.calcMarkerSize(L,L._rawLength),P=Array.isArray(C);if(C&&w[l]||P){var O=C;for(C=new Array(S),c=0;c<S;c++)C[c]=f[c].gap?0:P?O[f[c].i]:O}var z=new Array(S),I=new Array(S);for(c=0;c<S;c++)z[c]=f[c].x,I[c]=f[c].y;n.calcAxisExpansion(t,L,r,i,z,I,C),f[0].t.orientation=m.orientation}}}}}},{\"./calc\":1121}],1126:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=0;e<t.length;e++){var r=t[e];if(\"scatter\"===r.type){var n=r.fill;if(\"none\"!==n&&\"toself\"!==n&&(r.opacity=void 0,\"tonexty\"===n||\"tonextx\"===n))for(var a=e-1;a>=0;a--){var i=t[a];if(\"scatter\"===i.type&&i.xaxis===r.xaxis&&i.yaxis===r.yaxis){i.opacity=void 0;break}}}}}},{}],1127:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../registry\"),i=t(\"./attributes\"),o=t(\"./constants\"),s=t(\"./subtypes\"),l=t(\"./xy_defaults\"),c=t(\"./stack_defaults\"),u=t(\"./marker_defaults\"),h=t(\"./line_defaults\"),f=t(\"./line_shape_defaults\"),p=t(\"./text_defaults\"),d=t(\"./fillcolor_defaults\");e.exports=function(t,e,r,g){function v(r,a){return n.coerce(t,e,i,r,a)}var m=l(t,e,g,v);if(m||(e.visible=!1),e.visible){var y=c(t,e,g,v),x=!y&&m<o.PTS_LINESONLY?\"lines+markers\":\"lines\";v(\"text\"),v(\"hovertext\"),v(\"mode\",x),s.hasLines(e)&&(h(t,e,r,g,v),f(t,e,v),v(\"connectgaps\"),v(\"line.simplify\")),s.hasMarkers(e)&&u(t,e,r,g,v,{gradient:!0}),s.hasText(e)&&(v(\"texttemplate\"),p(t,e,g,v));var b=[];(s.hasMarkers(e)||s.hasText(e))&&(v(\"cliponaxis\"),v(\"marker.maxdisplayed\"),b.push(\"points\")),v(\"fill\",y?y.fillDflt:\"none\"),\"none\"!==e.fill&&(d(t,e,r,v),s.hasLines(e)||f(t,e,v));var _=(e.line||{}).color,w=(e.marker||{}).color;\"tonext\"!==e.fill&&\"toself\"!==e.fill||b.push(\"fills\"),v(\"hoveron\",b.join(\"+\")||\"points\"),\"fills\"!==e.hoveron&&v(\"hovertemplate\");var k=a.getComponentMethod(\"errorbars\",\"supplyDefaults\");k(t,e,_||w||r,{axis:\"y\"}),k(t,e,_||w||r,{axis:\"x\",inherit:\"y\"}),n.coerceSelectionMarkerOpacity(e,v)}}},{\"../../lib\":717,\"../../registry\":846,\"./attributes\":1120,\"./constants\":1124,\"./fillcolor_defaults\":1128,\"./line_defaults\":1133,\"./line_shape_defaults\":1135,\"./marker_defaults\":1139,\"./stack_defaults\":1142,\"./subtypes\":1144,\"./text_defaults\":1145,\"./xy_defaults\":1146}],1128:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),a=t(\"../../lib\").isArrayOrTypedArray;e.exports=function(t,e,r,i){var o=!1;if(e.marker){var s=e.marker.color,l=(e.marker.line||{}).color;s&&!a(s)?o=s:l&&!a(l)&&(o=l)}i(\"fillcolor\",n.addOpacity((e.line||{}).color||o||r,.5))}},{\"../../components/color\":592,\"../../lib\":717}],1129:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\");e.exports=function(t,e,r){var a={},i={_fullLayout:r},o=n.getFromTrace(i,e,\"x\"),s=n.getFromTrace(i,e,\"y\");return a.xLabel=n.tickText(o,t.x,!0).text,a.yLabel=n.tickText(s,t.y,!0).text,a}},{\"../../plots/cartesian/axes\":765}],1130:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),a=t(\"./subtypes\");e.exports=function(t,e){var r,i;if(\"lines\"===t.mode)return(r=t.line.color)&&n.opacity(r)?r:t.fillcolor;if(\"none\"===t.mode)return t.fill?t.fillcolor:\"\";var o=e.mcc||(t.marker||{}).color,s=e.mlcc||((t.marker||{}).line||{}).color;return(i=o&&n.opacity(o)?o:s&&n.opacity(s)&&(e.mlw||((t.marker||{}).line||{}).width)?s:\"\")?n.opacity(i)<.3?n.addOpacity(i,.3):i:(r=(t.line||{}).color)&&n.opacity(r)&&a.hasLines(t)&&t.line.width?r:t.fillcolor}},{\"../../components/color\":592,\"./subtypes\":1144}],1131:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/fx\"),i=t(\"../../registry\"),o=t(\"./get_trace_color\"),s=t(\"../../components/color\"),l=n.fillText;e.exports=function(t,e,r,c){var u=t.cd,h=u[0].trace,f=t.xa,p=t.ya,d=f.c2p(e),g=p.c2p(r),v=[d,g],m=h.hoveron||\"\",y=-1!==h.mode.indexOf(\"markers\")?3:.5;if(-1!==m.indexOf(\"points\")){var x=function(t){var e=Math.max(y,t.mrc||0),r=f.c2p(t.x)-d,n=p.c2p(t.y)-g;return Math.max(Math.sqrt(r*r+n*n)-e,1-y/e)},b=a.getDistanceFunction(c,function(t){var e=Math.max(3,t.mrc||0),r=1-1/e,n=Math.abs(f.c2p(t.x)-d);return n<e?r*n/e:n-e+r},function(t){var e=Math.max(3,t.mrc||0),r=1-1/e,n=Math.abs(p.c2p(t.y)-g);return n<e?r*n/e:n-e+r},x);if(a.getClosest(u,b,t),!1!==t.index){var _=u[t.index],w=f.c2p(_.x,!0),k=p.c2p(_.y,!0),T=_.mrc||1;t.index=_.i;var M=u[0].t.orientation,A=M&&(_.sNorm||_.s),S=\"h\"===M?A:_.x,E=\"v\"===M?A:_.y;return n.extendFlat(t,{color:o(h,_),x0:w-T,x1:w+T,xLabelVal:S,y0:k-T,y1:k+T,yLabelVal:E,spikeDistance:x(_),hovertemplate:h.hovertemplate}),l(_,h,t),i.getComponentMethod(\"errorbars\",\"hoverInfo\")(_,h,t),[t]}}if(-1!==m.indexOf(\"fills\")&&h._polygons){var L,C,P,O,z,I,D,R,F,B=h._polygons,N=[],j=!1,V=1/0,U=-1/0,q=1/0,H=-1/0;for(L=0;L<B.length;L++)(P=B[L]).contains(v)&&(j=!j,N.push(P),q=Math.min(q,P.ymin),H=Math.max(H,P.ymax));if(j){var G=((q=Math.max(q,0))+(H=Math.min(H,p._length)))/2;for(L=0;L<N.length;L++)for(O=N[L].pts,C=1;C<O.length;C++)(R=O[C-1][1])>G!=(F=O[C][1])>=G&&(I=O[C-1][0],D=O[C][0],F-R&&(z=I+(D-I)*(G-R)/(F-R),V=Math.min(V,z),U=Math.max(U,z)));V=Math.max(V,0),U=Math.min(U,f._length);var Y=s.defaultLine;return s.opacity(h.fillcolor)?Y=h.fillcolor:s.opacity((h.line||{}).color)&&(Y=h.line.color),n.extendFlat(t,{distance:t.maxHoverDistance,x0:V,x1:U,y0:G,y1:G,color:Y,hovertemplate:!1}),delete t.index,h.text&&!Array.isArray(h.text)?t.text=String(h.text):t.text=h.name,[t]}}}},{\"../../components/color\":592,\"../../components/fx\":630,\"../../lib\":717,\"../../registry\":846,\"./get_trace_color\":1130}],1132:[function(t,e,r){\"use strict\";var n=t(\"./subtypes\");e.exports={hasLines:n.hasLines,hasMarkers:n.hasMarkers,hasText:n.hasText,isBubble:n.isBubble,attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),crossTraceDefaults:t(\"./cross_trace_defaults\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./cross_trace_calc\"),arraysToCalcdata:t(\"./arrays_to_calcdata\"),plot:t(\"./plot\"),colorbar:t(\"./marker_colorbar\"),formatLabels:t(\"./format_labels\"),style:t(\"./style\").style,styleOnSelect:t(\"./style\").styleOnSelect,hoverPoints:t(\"./hover\"),selectPoints:t(\"./select\"),animatable:!0,moduleType:\"trace\",name:\"scatter\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"cartesian\",\"svg\",\"symbols\",\"errorBarsOK\",\"showLegend\",\"scatter-like\",\"zoomScale\"],meta:{}}},{\"../../plots/cartesian\":776,\"./arrays_to_calcdata\":1119,\"./attributes\":1120,\"./calc\":1121,\"./cross_trace_calc\":1125,\"./cross_trace_defaults\":1126,\"./defaults\":1127,\"./format_labels\":1129,\"./hover\":1131,\"./marker_colorbar\":1138,\"./plot\":1140,\"./select\":1141,\"./style\":1143,\"./subtypes\":1144}],1133:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").isArrayOrTypedArray,a=t(\"../../components/colorscale/helpers\").hasColorscale,i=t(\"../../components/colorscale/defaults\");e.exports=function(t,e,r,o,s,l){var c=(t.marker||{}).color;(s(\"line.color\",r),a(t,\"line\"))?i(t,e,o,s,{prefix:\"line.\",cLetter:\"c\"}):s(\"line.color\",!n(c)&&c||r);s(\"line.width\"),(l||{}).noDash||s(\"line.dash\")}},{\"../../components/colorscale/defaults\":602,\"../../components/colorscale/helpers\":603,\"../../lib\":717}],1134:[function(t,e,r){\"use strict\";var n=t(\"../../constants/numerical\"),a=n.BADNUM,i=n.LOG_CLIP,o=i+.5,s=i-.5,l=t(\"../../lib\"),c=l.segmentsIntersect,u=l.constrain,h=t(\"./constants\");e.exports=function(t,e){var r,n,i,f,p,d,g,v,m,y,x,b,_,w,k,T,M,A,S=e.xaxis,E=e.yaxis,L=\"log\"===S.type,C=\"log\"===E.type,P=S._length,O=E._length,z=e.connectGaps,I=e.baseTolerance,D=e.shape,R=\"linear\"===D,F=e.fill&&\"none\"!==e.fill,B=[],N=h.minTolerance,j=t.length,V=new Array(j),U=0;function q(r){var n=t[r];if(!n)return!1;var i=e.linearized?S.l2p(n.x):S.c2p(n.x),l=e.linearized?E.l2p(n.y):E.c2p(n.y);if(i===a){if(L&&(i=S.c2p(n.x,!0)),i===a)return!1;C&&l===a&&(i*=Math.abs(S._m*O*(S._m>0?o:s)/(E._m*P*(E._m>0?o:s)))),i*=1e3}if(l===a){if(C&&(l=E.c2p(n.y,!0)),l===a)return!1;l*=1e3}return[i,l]}function H(t,e,r,n){var a=r-t,i=n-e,o=.5-t,s=.5-e,l=a*a+i*i,c=a*o+i*s;if(c>0&&c<l){var u=o*i-s*a;if(u*u<l)return!0}}function G(t,e){var r=t[0]/P,n=t[1]/O,a=Math.max(0,-r,r-1,-n,n-1);return a&&void 0!==M&&H(r,n,M,A)&&(a=0),a&&e&&H(r,n,e[0]/P,e[1]/O)&&(a=0),(1+h.toleranceGrowth*a)*I}function Y(t,e){var r=t[0]-e[0],n=t[1]-e[1];return Math.sqrt(r*r+n*n)}var W,X,Z,J,K,Q,$,tt=h.maxScreensAway,et=-P*tt,rt=P*(1+tt),nt=-O*tt,at=O*(1+tt),it=[[et,nt,rt,nt],[rt,nt,rt,at],[rt,at,et,at],[et,at,et,nt]];function ot(t){if(t[0]<et||t[0]>rt||t[1]<nt||t[1]>at)return[u(t[0],et,rt),u(t[1],nt,at)]}function st(t,e){return t[0]===e[0]&&(t[0]===et||t[0]===rt)||(t[1]===e[1]&&(t[1]===nt||t[1]===at)||void 0)}function lt(t,e,r){return function(n,a){var i=ot(n),o=ot(a),s=[];if(i&&o&&st(i,o))return s;i&&s.push(i),o&&s.push(o);var c=2*l.constrain((n[t]+a[t])/2,e,r)-((i||n)[t]+(o||a)[t]);c&&((i&&o?c>0==i[t]>o[t]?i:o:i||o)[t]+=c);return s}}function ct(t){var e=t[0],r=t[1],n=e===V[U-1][0],a=r===V[U-1][1];if(!n||!a)if(U>1){var i=e===V[U-2][0],o=r===V[U-2][1];n&&(e===et||e===rt)&&i?o?U--:V[U-1]=t:a&&(r===nt||r===at)&&o?i?U--:V[U-1]=t:V[U++]=t}else V[U++]=t}function ut(t){V[U-1][0]!==t[0]&&V[U-1][1]!==t[1]&&ct([Z,J]),ct(t),K=null,Z=J=0}function ht(t){if(M=t[0]/P,A=t[1]/O,W=t[0]<et?et:t[0]>rt?rt:0,X=t[1]<nt?nt:t[1]>at?at:0,W||X){if(U)if(K){var e=$(K,t);e.length>1&&(ut(e[0]),V[U++]=e[1])}else Q=$(V[U-1],t)[0],V[U++]=Q;else V[U++]=[W||t[0],X||t[1]];var r=V[U-1];W&&X&&(r[0]!==W||r[1]!==X)?(K&&(Z!==W&&J!==X?ct(Z&&J?(n=K,i=(a=t)[0]-n[0],o=(a[1]-n[1])/i,(n[1]*a[0]-a[1]*n[0])/i>0?[o>0?et:rt,at]:[o>0?rt:et,nt]):[Z||W,J||X]):Z&&J&&ct([Z,J])),ct([W,X])):Z-W&&J-X&&ct([W||Z,X||J]),K=t,Z=W,J=X}else K&&ut($(K,t)[0]),V[U++]=t;var n,a,i,o}for(\"linear\"===D||\"spline\"===D?$=function(t,e){for(var r=[],n=0,a=0;a<4;a++){var i=it[a],o=c(t[0],t[1],e[0],e[1],i[0],i[1],i[2],i[3]);o&&(!n||Math.abs(o.x-r[0][0])>1||Math.abs(o.y-r[0][1])>1)&&(o=[o.x,o.y],n&&Y(o,t)<Y(r[0],t)?r.unshift(o):r.push(o),n++)}return r}:\"hv\"===D||\"vh\"===D?$=function(t,e){var r=[],n=ot(t),a=ot(e);return n&&a&&st(n,a)?r:(n&&r.push(n),a&&r.push(a),r)}:\"hvh\"===D?$=lt(0,et,rt):\"vhv\"===D&&($=lt(1,nt,at)),r=0;r<j;r++)if(n=q(r)){for(U=0,K=null,ht(n),r++;r<j;r++){if(!(f=q(r))){if(z)continue;break}if(R&&e.simplify){var ft=q(r+1);if(y=Y(f,n),F&&(0===U||U===j-1)||!(y<G(f,ft)*N)){for(v=[(f[0]-n[0])/y,(f[1]-n[1])/y],p=n,x=y,b=w=k=0,g=!1,i=f,r++;r<t.length;r++){if(d=ft,ft=q(r+1),!d){if(z)continue;break}if(T=(m=[d[0]-n[0],d[1]-n[1]])[0]*v[1]-m[1]*v[0],w=Math.min(w,T),(k=Math.max(k,T))-w>G(d,ft))break;i=d,(_=m[0]*v[0]+m[1]*v[1])>x?(x=_,f=d,g=!1):_<b&&(b=_,p=d,g=!0)}if(g?(ht(f),i!==p&&ht(p)):(p!==n&&ht(p),i!==f&&ht(f)),ht(i),r>=t.length||!d)break;ht(d),n=d}}else ht(f)}K&&ct([Z||K[0],J||K[1]]),B.push(V.slice(0,U))}return B}},{\"../../constants/numerical\":693,\"../../lib\":717,\"./constants\":1124}],1135:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){\"spline\"===r(\"line.shape\")&&r(\"line.smoothing\")}},{}],1136:[function(t,e,r){\"use strict\";var n={tonextx:1,tonexty:1,tonext:1};e.exports=function(t,e,r){var a,i,o,s,l,c={},u=!1,h=-1,f=0,p=-1;for(i=0;i<r.length;i++)(o=(a=r[i][0].trace).stackgroup||\"\")?o in c?l=c[o]:(l=c[o]=f,f++):a.fill in n&&p>=0?l=p:(l=p=f,f++),l<h&&(u=!0),a._groupIndex=h=l;var d=r.slice();u&&d.sort(function(t,e){var r=t[0].trace,n=e[0].trace;return r._groupIndex-n._groupIndex||r.index-n.index});var g={};for(i=0;i<d.length;i++)o=(a=d[i][0].trace).stackgroup||\"\",!0===a.visible?(a._nexttrace=null,a.fill in n&&(s=g[o],a._prevtrace=s||null,s&&(s._nexttrace=a)),a._ownfill=a.fill&&(\"tozero\"===a.fill.substr(0,6)||\"toself\"===a.fill||\"to\"===a.fill.substr(0,2)&&!a._prevtrace),g[o]=a):a._prevtrace=a._nexttrace=a._ownfill=null;return d}},{}],1137:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\");e.exports=function(t){var e=t.marker,r=e.sizeref||1,a=e.sizemin||0,i=\"area\"===e.sizemode?function(t){return Math.sqrt(t/r)}:function(t){return t/r};return function(t){var e=i(t/2);return n(e)&&e>0?Math.max(e,a):0}}},{\"fast-isnumeric\":228}],1138:[function(t,e,r){\"use strict\";e.exports={container:\"marker\",min:\"cmin\",max:\"cmax\"}},{}],1139:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),a=t(\"../../components/colorscale/helpers\").hasColorscale,i=t(\"../../components/colorscale/defaults\"),o=t(\"./subtypes\");e.exports=function(t,e,r,s,l,c){var u=o.isBubble(t),h=(t.line||{}).color;(c=c||{},h&&(r=h),l(\"marker.symbol\"),l(\"marker.opacity\",u?.7:1),l(\"marker.size\"),l(\"marker.color\",r),a(t,\"marker\")&&i(t,e,s,l,{prefix:\"marker.\",cLetter:\"c\"}),c.noSelect||(l(\"selected.marker.color\"),l(\"unselected.marker.color\"),l(\"selected.marker.size\"),l(\"unselected.marker.size\")),c.noLine||(l(\"marker.line.color\",h&&!Array.isArray(h)&&e.marker.color!==h?h:u?n.background:n.defaultLine),a(t,\"marker.line\")&&i(t,e,s,l,{prefix:\"marker.line.\",cLetter:\"c\"}),l(\"marker.line.width\",u?1:0)),u&&(l(\"marker.sizeref\"),l(\"marker.sizemin\"),l(\"marker.sizemode\")),c.gradient)&&(\"none\"!==l(\"marker.gradient.type\")&&l(\"marker.gradient.color\"))}},{\"../../components/color\":592,\"../../components/colorscale/defaults\":602,\"../../components/colorscale/helpers\":603,\"./subtypes\":1144}],1140:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../registry\"),i=t(\"../../lib\"),o=i.ensureSingle,s=i.identity,l=t(\"../../components/drawing\"),c=t(\"./subtypes\"),u=t(\"./line_points\"),h=t(\"./link_traces\"),f=t(\"../../lib/polygon\").tester;function p(t,e,r,h,p,d,g){var v;!function(t,e,r,a,o){var s=r.xaxis,l=r.yaxis,u=n.extent(i.simpleMap(s.range,s.r2c)),h=n.extent(i.simpleMap(l.range,l.r2c)),f=a[0].trace;if(!c.hasMarkers(f))return;var p=f.marker.maxdisplayed;if(0===p)return;var d=a.filter(function(t){return t.x>=u[0]&&t.x<=u[1]&&t.y>=h[0]&&t.y<=h[1]}),g=Math.ceil(d.length/p),v=0;o.forEach(function(t,r){var n=t[0].trace;c.hasMarkers(n)&&n.marker.maxdisplayed>0&&r<e&&v++});var m=Math.round(v*g/3+Math.floor(v/3)*g/7.1);a.forEach(function(t){delete t.vis}),d.forEach(function(t,e){0===Math.round((e+m)%g)&&(t.vis=!0)})}(0,e,r,h,p);var m=!!g&&g.duration>0;function y(t){return m?t.transition():t}var x=r.xaxis,b=r.yaxis,_=h[0].trace,w=_.line,k=n.select(d),T=o(k,\"g\",\"errorbars\"),M=o(k,\"g\",\"lines\"),A=o(k,\"g\",\"points\"),S=o(k,\"g\",\"text\");if(a.getComponentMethod(\"errorbars\",\"plot\")(t,T,r,g),!0===_.visible){var E,L;y(k).style(\"opacity\",_.opacity);var C=_.fill.charAt(_.fill.length-1);\"x\"!==C&&\"y\"!==C&&(C=\"\"),h[0][r.isRangePlot?\"nodeRangePlot3\":\"node3\"]=k;var P,O,z=\"\",I=[],D=_._prevtrace;D&&(z=D._prevRevpath||\"\",L=D._nextFill,I=D._polygons);var R,F,B,N,j,V,U,q=\"\",H=\"\",G=[],Y=i.noop;if(E=_._ownFill,c.hasLines(_)||\"none\"!==_.fill){for(L&&L.datum(h),-1!==[\"hv\",\"vh\",\"hvh\",\"vhv\"].indexOf(w.shape)?(R=l.steps(w.shape),F=l.steps(w.shape.split(\"\").reverse().join(\"\"))):R=F=\"spline\"===w.shape?function(t){var e=t[t.length-1];return t.length>1&&t[0][0]===e[0]&&t[0][1]===e[1]?l.smoothclosed(t.slice(1),w.smoothing):l.smoothopen(t,w.smoothing)}:function(t){return\"M\"+t.join(\"L\")},B=function(t){return F(t.reverse())},G=u(h,{xaxis:x,yaxis:b,connectGaps:_.connectgaps,baseTolerance:Math.max(w.width||1,3)/4,shape:w.shape,simplify:w.simplify,fill:_.fill}),U=_._polygons=new Array(G.length),v=0;v<G.length;v++)_._polygons[v]=f(G[v]);G.length&&(N=G[0][0],V=(j=G[G.length-1])[j.length-1]),Y=function(t){return function(e){if(P=R(e),O=B(e),q?C?(q+=\"L\"+P.substr(1),H=O+\"L\"+H.substr(1)):(q+=\"Z\"+P,H=O+\"Z\"+H):(q=P,H=O),c.hasLines(_)&&e.length>1){var r=n.select(this);if(r.datum(h),t)y(r.style(\"opacity\",0).attr(\"d\",P).call(l.lineGroupStyle)).style(\"opacity\",1);else{var a=y(r);a.attr(\"d\",P),l.singleLineStyle(h,a)}}}}}var W=M.selectAll(\".js-line\").data(G);y(W.exit()).style(\"opacity\",0).remove(),W.each(Y(!1)),W.enter().append(\"path\").classed(\"js-line\",!0).style(\"vector-effect\",\"non-scaling-stroke\").call(l.lineGroupStyle).each(Y(!0)),l.setClipUrl(W,r.layerClipId,t),G.length?(E?(E.datum(h),N&&V&&(C?(\"y\"===C?N[1]=V[1]=b.c2p(0,!0):\"x\"===C&&(N[0]=V[0]=x.c2p(0,!0)),y(E).attr(\"d\",\"M\"+V+\"L\"+N+\"L\"+q.substr(1)).call(l.singleFillStyle)):y(E).attr(\"d\",q+\"Z\").call(l.singleFillStyle))):L&&(\"tonext\"===_.fill.substr(0,6)&&q&&z?(\"tonext\"===_.fill?y(L).attr(\"d\",q+\"Z\"+z+\"Z\").call(l.singleFillStyle):y(L).attr(\"d\",q+\"L\"+z.substr(1)+\"Z\").call(l.singleFillStyle),_._polygons=_._polygons.concat(I)):(Z(L),_._polygons=null)),_._prevRevpath=H,_._prevPolygons=U):(E?Z(E):L&&Z(L),_._polygons=_._prevRevpath=_._prevPolygons=null),A.datum(h),S.datum(h),function(e,a,i){var o,u=i[0].trace,h=c.hasMarkers(u),f=c.hasText(u),p=tt(u),d=et,g=et;if(h||f){var v=s,_=u.stackgroup,w=_&&\"infer zero\"===t._fullLayout._scatterStackOpts[x._id+b._id][_].stackgaps;u.marker.maxdisplayed||u._needsCull?v=w?K:J:_&&!w&&(v=Q),h&&(d=v),f&&(g=v)}var k,T=(o=e.selectAll(\"path.point\").data(d,p)).enter().append(\"path\").classed(\"point\",!0);m&&T.call(l.pointStyle,u,t).call(l.translatePoints,x,b).style(\"opacity\",0).transition().style(\"opacity\",1),o.order(),h&&(k=l.makePointStyleFns(u)),o.each(function(e){var a=n.select(this),i=y(a);l.translatePoint(e,i,x,b)?(l.singlePointStyle(e,i,u,k,t),r.layerClipId&&l.hideOutsideRangePoint(e,i,x,b,u.xcalendar,u.ycalendar),u.customdata&&a.classed(\"plotly-customdata\",null!==e.data&&void 0!==e.data)):i.remove()}),m?o.exit().transition().style(\"opacity\",0).remove():o.exit().remove(),(o=a.selectAll(\"g\").data(g,p)).enter().append(\"g\").classed(\"textpoint\",!0).append(\"text\"),o.order(),o.each(function(t){var e=n.select(this),a=y(e.select(\"text\"));l.translatePoint(t,a,x,b)?r.layerClipId&&l.hideOutsideRangePoint(t,e,x,b,u.xcalendar,u.ycalendar):e.remove()}),o.selectAll(\"text\").call(l.textPointStyle,u,t).each(function(t){var e=x.c2p(t.x),r=b.c2p(t.y);n.select(this).selectAll(\"tspan.line\").each(function(){y(n.select(this)).attr({x:e,y:r})})}),o.exit().remove()}(A,S,h);var X=!1===_.cliponaxis?null:r.layerClipId;l.setClipUrl(A,X,t),l.setClipUrl(S,X,t)}function Z(t){y(t).attr(\"d\",\"M0,0Z\")}function J(t){return t.filter(function(t){return!t.gap&&t.vis})}function K(t){return t.filter(function(t){return t.vis})}function Q(t){return t.filter(function(t){return!t.gap})}function $(t){return t.id}function tt(t){if(t.ids)return $}function et(){return!1}}e.exports=function(t,e,r,a,i,c){var u,f,d=!i,g=!!i&&i.duration>0,v=h(t,e,r);((u=a.selectAll(\"g.trace\").data(v,function(t){return t[0].trace.uid})).enter().append(\"g\").attr(\"class\",function(t){return\"trace scatter trace\"+t[0].trace.uid}).style(\"stroke-miterlimit\",2),u.order(),function(t,e,r){e.each(function(e){var a=o(n.select(this),\"g\",\"fills\");l.setClipUrl(a,r.layerClipId,t);var i=e[0].trace,c=[];i._ownfill&&c.push(\"_ownFill\"),i._nexttrace&&c.push(\"_nextFill\");var u=a.selectAll(\"g\").data(c,s);u.enter().append(\"g\"),u.exit().each(function(t){i[t]=null}).remove(),u.order().each(function(t){i[t]=o(n.select(this),\"path\",\"js-fill\")})})}(t,u,e),g)?(c&&(f=c()),n.transition().duration(i.duration).ease(i.easing).each(\"end\",function(){f&&f()}).each(\"interrupt\",function(){f&&f()}).each(function(){a.selectAll(\"g.trace\").each(function(r,n){p(t,n,e,r,v,this,i)})})):u.each(function(r,n){p(t,n,e,r,v,this,i)});d&&u.exit().remove(),a.selectAll(\"path:not([d])\").remove()}},{\"../../components/drawing\":613,\"../../lib\":717,\"../../lib/polygon\":729,\"../../registry\":846,\"./line_points\":1134,\"./link_traces\":1136,\"./subtypes\":1144,d3:165}],1141:[function(t,e,r){\"use strict\";var n=t(\"./subtypes\");e.exports=function(t,e){var r,a,i,o,s=t.cd,l=t.xaxis,c=t.yaxis,u=[],h=s[0].trace;if(!n.hasMarkers(h)&&!n.hasText(h))return[];if(!1===e)for(r=0;r<s.length;r++)s[r].selected=0;else for(r=0;r<s.length;r++)a=s[r],i=l.c2p(a.x),o=c.c2p(a.y),null!==a.i&&e.contains([i,o],!1,r,t)?(u.push({pointNumber:a.i,x:l.c2d(a.x),y:c.c2d(a.y)}),a.selected=1):a.selected=0;return u}},{\"./subtypes\":1144}],1142:[function(t,e,r){\"use strict\";var n=[\"orientation\",\"groupnorm\",\"stackgaps\"];e.exports=function(t,e,r,a){var i=r._scatterStackOpts,o=a(\"stackgroup\");if(o){var s=e.xaxis+e.yaxis,l=i[s];l||(l=i[s]={});var c=l[o],u=!1;c?c.traces.push(e):(c=l[o]={traceIndices:[],traces:[e]},u=!0);for(var h={orientation:e.x&&!e.y?\"h\":\"v\"},f=0;f<n.length;f++){var p=n[f],d=p+\"Found\";if(!c[d]){var g=void 0!==t[p],v=\"orientation\"===p;if((g||u)&&(c[p]=a(p,h[p]),v&&(c.fillDflt=\"h\"===c[p]?\"tonextx\":\"tonexty\"),g&&(c[d]=!0,!u&&(delete c.traces[0][p],v))))for(var m=0;m<c.traces.length-1;m++){var y=c.traces[m];y._input.fill!==y.fill&&(y.fill=c.fillDflt)}}}return c}}},{}],1143:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../components/drawing\"),i=t(\"../../registry\");function o(t,e,r){a.pointStyle(t.selectAll(\"path.point\"),e,r)}function s(t,e,r){a.textPointStyle(t.selectAll(\"text\"),e,r)}e.exports={style:function(t){var e=n.select(t).selectAll(\"g.trace.scatter\");e.style(\"opacity\",function(t){return t[0].trace.opacity}),e.selectAll(\"g.points\").each(function(e){o(n.select(this),e.trace||e[0].trace,t)}),e.selectAll(\"g.text\").each(function(e){s(n.select(this),e.trace||e[0].trace,t)}),e.selectAll(\"g.trace path.js-line\").call(a.lineGroupStyle),e.selectAll(\"g.trace path.js-fill\").call(a.fillGroupStyle),i.getComponentMethod(\"errorbars\",\"style\")(e)},stylePoints:o,styleText:s,styleOnSelect:function(t,e,r){var n=e[0].trace;n.selectedpoints?(a.selectedPointStyle(r.selectAll(\"path.point\"),n),a.selectedTextStyle(r.selectAll(\"text\"),n)):(o(r,n,t),s(r,n,t))}}},{\"../../components/drawing\":613,\"../../registry\":846,d3:165}],1144:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports={hasLines:function(t){return t.visible&&t.mode&&-1!==t.mode.indexOf(\"lines\")},hasMarkers:function(t){return t.visible&&(t.mode&&-1!==t.mode.indexOf(\"markers\")||\"splom\"===t.type)},hasText:function(t){return t.visible&&t.mode&&-1!==t.mode.indexOf(\"text\")},isBubble:function(t){return n.isPlainObject(t.marker)&&n.isArrayOrTypedArray(t.marker.size)}}},{\"../../lib\":717}],1145:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e,r,a,i){i=i||{},a(\"textposition\"),n.coerceFont(a,\"textfont\",r.font),i.noSelect||(a(\"selected.textfont.color\"),a(\"unselected.textfont.color\"))}},{\"../../lib\":717}],1146:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../registry\");e.exports=function(t,e,r,i){var o,s=i(\"x\"),l=i(\"y\");if(a.getComponentMethod(\"calendars\",\"handleTraceDefaults\")(t,e,[\"x\",\"y\"],r),s){var c=n.minRowLength(s);l?o=Math.min(c,n.minRowLength(l)):(o=c,i(\"y0\"),i(\"dy\"))}else{if(!l)return 0;o=n.minRowLength(l),i(\"x0\"),i(\"dx\")}return e._length=o,o}},{\"../../lib\":717,\"../../registry\":846}],1147:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),a=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../../plots/template_attributes\").texttemplateAttrs,s=t(\"../../plots/attributes\"),l=t(\"../../constants/gl3d_dashes\"),c=t(\"../../constants/gl3d_markers\"),u=t(\"../../lib/extend\").extendFlat,h=t(\"../../plot_api/edit_types\").overrideAll,f=n.line,p=n.marker,d=p.line,g=u({width:f.width,dash:{valType:\"enumerated\",values:Object.keys(l),dflt:\"solid\"}},a(\"line\"));var v=e.exports=h({x:n.x,y:n.y,z:{valType:\"data_array\"},text:u({},n.text,{}),texttemplate:o({},{}),hovertext:u({},n.hovertext,{}),hovertemplate:i(),mode:u({},n.mode,{dflt:\"lines+markers\"}),surfaceaxis:{valType:\"enumerated\",values:[-1,0,1,2],dflt:-1},surfacecolor:{valType:\"color\"},projection:{x:{show:{valType:\"boolean\",dflt:!1},opacity:{valType:\"number\",min:0,max:1,dflt:1},scale:{valType:\"number\",min:0,max:10,dflt:2/3}},y:{show:{valType:\"boolean\",dflt:!1},opacity:{valType:\"number\",min:0,max:1,dflt:1},scale:{valType:\"number\",min:0,max:10,dflt:2/3}},z:{show:{valType:\"boolean\",dflt:!1},opacity:{valType:\"number\",min:0,max:1,dflt:1},scale:{valType:\"number\",min:0,max:10,dflt:2/3}}},connectgaps:n.connectgaps,line:g,marker:u({symbol:{valType:\"enumerated\",values:Object.keys(c),dflt:\"circle\",arrayOk:!0},size:u({},p.size,{dflt:8}),sizeref:p.sizeref,sizemin:p.sizemin,sizemode:p.sizemode,opacity:u({},p.opacity,{arrayOk:!1}),colorbar:p.colorbar,line:u({width:u({},d.width,{arrayOk:!1})},a(\"marker.line\"))},a(\"marker\")),textposition:u({},n.textposition,{dflt:\"top center\"}),textfont:{color:n.textfont.color,size:n.textfont.size,family:u({},n.textfont.family,{arrayOk:!1})},hoverinfo:u({},s.hoverinfo)},\"calc\",\"nested\");v.x.editType=v.y.editType=v.z.editType=\"calc+clearAxisTypes\"},{\"../../components/colorscale/attributes\":599,\"../../constants/gl3d_dashes\":690,\"../../constants/gl3d_markers\":691,\"../../lib/extend\":708,\"../../plot_api/edit_types\":748,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"../scatter/attributes\":1120}],1148:[function(t,e,r){\"use strict\";var n=t(\"../scatter/arrays_to_calcdata\"),a=t(\"../scatter/colorscale_calc\");e.exports=function(t,e){var r=[{x:!1,y:!1,trace:e,t:{}}];return n(r,e),a(t,e),r}},{\"../scatter/arrays_to_calcdata\":1119,\"../scatter/colorscale_calc\":1123}],1149:[function(t,e,r){\"use strict\";var n=t(\"../../registry\");function a(t,e,r,a){if(!e||!e.visible)return null;for(var i=n.getComponentMethod(\"errorbars\",\"makeComputeError\")(e),o=new Array(t.length),s=0;s<t.length;s++){var l=i(+t[s],s);if(\"log\"===a.type){var c=a.c2l(t[s]),u=t[s]-l[0],h=t[s]+l[1];if(o[s]=[(a.c2l(u,!0)-c)*r,(a.c2l(h,!0)-c)*r],u>0){var f=a.c2l(u);a._lowerLogErrorBound||(a._lowerLogErrorBound=f),a._lowerErrorBound=Math.min(a._lowerLogErrorBound,f)}}else o[s]=[-l[0]*r,l[1]*r]}return o}e.exports=function(t,e,r){var n=[a(t.x,t.error_x,e[0],r.xaxis),a(t.y,t.error_y,e[1],r.yaxis),a(t.z,t.error_z,e[2],r.zaxis)],i=function(t){for(var e=0;e<t.length;e++)if(t[e])return t[e].length;return 0}(n);if(0===i)return null;for(var o=new Array(i),s=0;s<i;s++){for(var l=[[0,0,0],[0,0,0]],c=0;c<3;c++)if(n[c])for(var u=0;u<2;u++)l[u][c]=n[c][s][u];o[s]=l}return o}},{\"../../registry\":846}],1150:[function(t,e,r){\"use strict\";var n=t(\"gl-line3d\"),a=t(\"gl-scatter3d\"),i=t(\"gl-error3d\"),o=t(\"gl-mesh3d\"),s=t(\"delaunay-triangulate\"),l=t(\"../../lib\"),c=t(\"../../lib/str2rgbarray\"),u=t(\"../../lib/gl_format_color\").formatColor,h=t(\"../scatter/make_bubble_size_func\"),f=t(\"../../constants/gl3d_dashes\"),p=t(\"../../constants/gl3d_markers\"),d=t(\"../../plots/cartesian/axes\"),g=t(\"../../components/fx/helpers\").appendArrayPointValue,v=t(\"./calc_errors\");function m(t,e){this.scene=t,this.uid=e,this.linePlot=null,this.scatterPlot=null,this.errorBars=null,this.textMarkers=null,this.delaunayMesh=null,this.color=null,this.mode=\"\",this.dataPoints=[],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.textLabels=null,this.data=null}var y=m.prototype;function x(t){return null==t?0:t.indexOf(\"left\")>-1?-1:t.indexOf(\"right\")>-1?1:0}function b(t){return null==t?0:t.indexOf(\"top\")>-1?-1:t.indexOf(\"bottom\")>-1?1:0}function _(t,e){return e(4*t)}function w(t){return p[t]}function k(t,e,r,n,a){var i=null;if(l.isArrayOrTypedArray(t)){i=[];for(var o=0;o<e;o++)void 0===t[o]?i[o]=n:i[o]=r(t[o],a)}else i=r(t,l.identity);return i}function T(t,e){var r,n,a,i,o,s,f=[],p=t.fullSceneLayout,m=t.dataScale,y=p.xaxis,T=p.yaxis,M=p.zaxis,A=e.marker,S=e.line,E=e.x||[],L=e.y||[],C=e.z||[],P=E.length,O=e.xcalendar,z=e.ycalendar,I=e.zcalendar;for(o=0;o<P;o++)r=y.d2l(E[o],0,O)*m[0],n=T.d2l(L[o],0,z)*m[1],a=M.d2l(C[o],0,I)*m[2],f[o]=[r,n,a];if(Array.isArray(e.text))s=e.text;else if(void 0!==e.text)for(s=new Array(P),o=0;o<P;o++)s[o]=e.text;function D(t,e){var r=p[t];return d.tickText(r,r.d2l(e),!0).text}var R=e.texttemplate;if(R){var F=t.fullLayout._d3locale,B=Array.isArray(R),N=B?Math.min(R.length,P):P,j=B?function(t){return R[t]}:function(){return R};for(s=new Array(N),o=0;o<N;o++){var V={x:E[o],y:L[o],z:C[o]},U={xLabel:D(\"xaxis\",E[o]),yLabel:D(\"yaxis\",L[o]),zLabel:D(\"zaxis\",C[o])},q={};g(q,e,o);var H=e._meta||{};s[o]=l.texttemplateString(j(o),U,F,q,V,H)}}if(i={position:f,mode:e.mode,text:s},\"line\"in e&&(i.lineColor=u(S,1,P),i.lineWidth=S.width,i.lineDashes=S.dash),\"marker\"in e){var G=h(e);i.scatterColor=u(A,1,P),i.scatterSize=k(A.size,P,_,20,G),i.scatterMarker=k(A.symbol,P,w,\"\\u25cf\"),i.scatterLineWidth=A.line.width,i.scatterLineColor=u(A.line,1,P),i.scatterAngle=0}\"textposition\"in e&&(i.textOffset=function(t){var e=[0,0];if(Array.isArray(t))for(var r=0;r<t.length;r++)e[r]=[0,0],t[r]&&(e[r][0]=x(t[r]),e[r][1]=b(t[r]));else e[0]=x(t),e[1]=b(t);return e}(e.textposition),i.textColor=u(e.textfont,1,P),i.textSize=k(e.textfont.size,P,l.identity,12),i.textFont=e.textfont.family,i.textAngle=0);var Y=[\"x\",\"y\",\"z\"];for(i.project=[!1,!1,!1],i.projectScale=[1,1,1],i.projectOpacity=[1,1,1],o=0;o<3;++o){var W=e.projection[Y[o]];(i.project[o]=W.show)&&(i.projectOpacity[o]=W.opacity,i.projectScale[o]=W.scale)}i.errorBounds=v(e,m,p);var X=function(t){for(var e=[0,0,0],r=[[0,0,0],[0,0,0],[0,0,0]],n=[1,1,1],a=0;a<3;a++){var i=t[a];i&&!1!==i.copy_zstyle&&!1!==t[2].visible&&(i=t[2]),i&&i.visible&&(e[a]=i.width/2,r[a]=c(i.color),n[a]=i.thickness)}return{capSize:e,color:r,lineWidth:n}}([e.error_x,e.error_y,e.error_z]);return i.errorColor=X.color,i.errorLineWidth=X.lineWidth,i.errorCapSize=X.capSize,i.delaunayAxis=e.surfaceaxis,i.delaunayColor=c(e.surfacecolor),i}function M(t){if(Array.isArray(t)){var e=t[0];return Array.isArray(e)&&(t=e),\"rgb(\"+t.slice(0,3).map(function(t){return Math.round(255*t)})+\")\"}return null}y.handlePick=function(t){if(t.object&&(t.object===this.linePlot||t.object===this.delaunayMesh||t.object===this.textMarkers||t.object===this.scatterPlot)){var e=t.index=t.data.index;return t.object.highlight&&t.object.highlight(null),this.scatterPlot&&(t.object=this.scatterPlot,this.scatterPlot.highlight(t.data)),t.textLabel=\"\",this.textLabels&&(Array.isArray(this.textLabels)?(this.textLabels[e]||0===this.textLabels[e])&&(t.textLabel=this.textLabels[e]):t.textLabel=this.textLabels),t.traceCoordinate=[this.data.x[e],this.data.y[e],this.data.z[e]],!0}},y.update=function(t){var e,r,l,c,u=this.scene.glplot.gl,h=f.solid;this.data=t;var p=T(this.scene,t);\"mode\"in p&&(this.mode=p.mode),\"lineDashes\"in p&&p.lineDashes in f&&(h=f[p.lineDashes]),this.color=M(p.scatterColor)||M(p.lineColor),this.dataPoints=p.position,e={gl:this.scene.glplot.gl,position:p.position,color:p.lineColor,lineWidth:p.lineWidth||1,dashes:h[0],dashScale:h[1],opacity:t.opacity,connectGaps:t.connectgaps},-1!==this.mode.indexOf(\"lines\")?this.linePlot?this.linePlot.update(e):(this.linePlot=n(e),this.linePlot._trace=this,this.scene.glplot.add(this.linePlot)):this.linePlot&&(this.scene.glplot.remove(this.linePlot),this.linePlot.dispose(),this.linePlot=null);var d=t.opacity;if(t.marker&&t.marker.opacity&&(d*=t.marker.opacity),r={gl:this.scene.glplot.gl,position:p.position,color:p.scatterColor,size:p.scatterSize,glyph:p.scatterMarker,opacity:d,orthographic:!0,lineWidth:p.scatterLineWidth,lineColor:p.scatterLineColor,project:p.project,projectScale:p.projectScale,projectOpacity:p.projectOpacity},-1!==this.mode.indexOf(\"markers\")?this.scatterPlot?this.scatterPlot.update(r):(this.scatterPlot=a(r),this.scatterPlot._trace=this,this.scatterPlot.highlightScale=1,this.scene.glplot.add(this.scatterPlot)):this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose(),this.scatterPlot=null),c={gl:this.scene.glplot.gl,position:p.position,glyph:p.text,color:p.textColor,size:p.textSize,angle:p.textAngle,alignment:p.textOffset,font:p.textFont,orthographic:!0,lineWidth:0,project:!1,opacity:t.opacity},this.textLabels=t.hovertext||t.text,-1!==this.mode.indexOf(\"text\")?this.textMarkers?this.textMarkers.update(c):(this.textMarkers=a(c),this.textMarkers._trace=this,this.textMarkers.highlightScale=1,this.scene.glplot.add(this.textMarkers)):this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose(),this.textMarkers=null),l={gl:this.scene.glplot.gl,position:p.position,color:p.errorColor,error:p.errorBounds,lineWidth:p.errorLineWidth,capSize:p.errorCapSize,opacity:t.opacity},this.errorBars?p.errorBounds?this.errorBars.update(l):(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose(),this.errorBars=null):p.errorBounds&&(this.errorBars=i(l),this.errorBars._trace=this,this.scene.glplot.add(this.errorBars)),p.delaunayAxis>=0){var g=function(t,e,r){var n,a=(r+1)%3,i=(r+2)%3,o=[],l=[];for(n=0;n<t.length;++n){var c=t[n];!isNaN(c[a])&&isFinite(c[a])&&!isNaN(c[i])&&isFinite(c[i])&&(o.push([c[a],c[i]]),l.push(n))}var u=s(o);for(n=0;n<u.length;++n)for(var h=u[n],f=0;f<h.length;++f)h[f]=l[h[f]];return{positions:t,cells:u,meshColor:e}}(p.position,p.delaunayColor,p.delaunayAxis);g.opacity=t.opacity,this.delaunayMesh?this.delaunayMesh.update(g):(g.gl=u,this.delaunayMesh=o(g),this.delaunayMesh._trace=this,this.scene.glplot.add(this.delaunayMesh))}else this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose(),this.delaunayMesh=null)},y.dispose=function(){this.linePlot&&(this.scene.glplot.remove(this.linePlot),this.linePlot.dispose()),this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose()),this.errorBars&&(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose()),this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose()),this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose())},e.exports=function(t,e){var r=new m(t,e.uid);return r.update(e),r}},{\"../../components/fx/helpers\":627,\"../../constants/gl3d_dashes\":690,\"../../constants/gl3d_markers\":691,\"../../lib\":717,\"../../lib/gl_format_color\":714,\"../../lib/str2rgbarray\":740,\"../../plots/cartesian/axes\":765,\"../scatter/make_bubble_size_func\":1137,\"./calc_errors\":1149,\"delaunay-triangulate\":167,\"gl-error3d\":250,\"gl-line3d\":258,\"gl-mesh3d\":283,\"gl-scatter3d\":300}],1151:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../lib\"),i=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,u){function h(r,n){return a.coerce(t,e,c,r,n)}if(function(t,e,r,a){var i=0,o=r(\"x\"),s=r(\"y\"),l=r(\"z\");n.getComponentMethod(\"calendars\",\"handleTraceDefaults\")(t,e,[\"x\",\"y\",\"z\"],a),o&&s&&l&&(i=Math.min(o.length,s.length,l.length),e._length=e._xlength=e._ylength=e._zlength=i);return i}(t,e,h,u)){h(\"text\"),h(\"hovertext\"),h(\"hovertemplate\"),h(\"mode\"),i.hasLines(e)&&(h(\"connectgaps\"),s(t,e,r,u,h)),i.hasMarkers(e)&&o(t,e,r,u,h,{noSelect:!0}),i.hasText(e)&&(h(\"texttemplate\"),l(t,e,u,h,{noSelect:!0}));var f=(e.line||{}).color,p=(e.marker||{}).color;h(\"surfaceaxis\")>=0&&h(\"surfacecolor\",f||p);for(var d=[\"x\",\"y\",\"z\"],g=0;g<3;++g){var v=\"projection.\"+d[g];h(v+\".show\")&&(h(v+\".opacity\"),h(v+\".scale\"))}var m=n.getComponentMethod(\"errorbars\",\"supplyDefaults\");m(t,e,f||p||r,{axis:\"z\"}),m(t,e,f||p||r,{axis:\"y\",inherit:\"z\"}),m(t,e,f||p||r,{axis:\"x\",inherit:\"z\"})}else e.visible=!1}},{\"../../lib\":717,\"../../registry\":846,\"../scatter/line_defaults\":1133,\"../scatter/marker_defaults\":1139,\"../scatter/subtypes\":1144,\"../scatter/text_defaults\":1145,\"./attributes\":1147}],1152:[function(t,e,r){\"use strict\";e.exports={plot:t(\"./convert\"),attributes:t(\"./attributes\"),markerSymbols:t(\"../../constants/gl3d_markers\"),supplyDefaults:t(\"./defaults\"),colorbar:[{container:\"marker\",min:\"cmin\",max:\"cmax\"},{container:\"line\",min:\"cmin\",max:\"cmax\"}],calc:t(\"./calc\"),moduleType:\"trace\",name:\"scatter3d\",basePlotModule:t(\"../../plots/gl3d\"),categories:[\"gl3d\",\"symbols\",\"showLegend\",\"scatter-like\"],meta:{}}},{\"../../constants/gl3d_markers\":691,\"../../plots/gl3d\":805,\"./attributes\":1147,\"./calc\":1148,\"./convert\":1150,\"./defaults\":1151}],1153:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),a=t(\"../../plots/attributes\"),i=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../../plots/template_attributes\").texttemplateAttrs,s=t(\"../../components/colorscale/attributes\"),l=t(\"../../lib/extend\").extendFlat,c=n.marker,u=n.line,h=c.line;e.exports={carpet:{valType:\"string\",editType:\"calc\"},a:{valType:\"data_array\",editType:\"calc\"},b:{valType:\"data_array\",editType:\"calc\"},mode:l({},n.mode,{dflt:\"markers\"}),text:l({},n.text,{}),texttemplate:o({editType:\"plot\"},{keys:[\"a\",\"b\",\"text\"]}),hovertext:l({},n.hovertext,{}),line:{color:u.color,width:u.width,dash:u.dash,shape:l({},u.shape,{values:[\"linear\",\"spline\"]}),smoothing:u.smoothing,editType:\"calc\"},connectgaps:n.connectgaps,fill:l({},n.fill,{values:[\"none\",\"toself\",\"tonext\"],dflt:\"none\"}),fillcolor:n.fillcolor,marker:l({symbol:c.symbol,opacity:c.opacity,maxdisplayed:c.maxdisplayed,size:c.size,sizeref:c.sizeref,sizemin:c.sizemin,sizemode:c.sizemode,line:l({width:h.width,editType:\"calc\"},s(\"marker.line\")),gradient:c.gradient,editType:\"calc\"},s(\"marker\")),textfont:n.textfont,textposition:n.textposition,selected:n.selected,unselected:n.unselected,hoverinfo:l({},a.hoverinfo,{flags:[\"a\",\"b\",\"text\",\"name\"]}),hoveron:n.hoveron,hovertemplate:i()}},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"../scatter/attributes\":1120}],1154:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../scatter/colorscale_calc\"),i=t(\"../scatter/arrays_to_calcdata\"),o=t(\"../scatter/calc_selection\"),s=t(\"../scatter/calc\").calcMarkerSize,l=t(\"../carpet/lookup_carpetid\");e.exports=function(t,e){var r=e._carpetTrace=l(t,e);if(r&&r.visible&&\"legendonly\"!==r.visible){var c;e.xaxis=r.xaxis,e.yaxis=r.yaxis;var u,h,f=e._length,p=new Array(f),d=!1;for(c=0;c<f;c++)if(u=e.a[c],h=e.b[c],n(u)&&n(h)){var g=r.ab2xy(+u,+h,!0),v=r.isVisible(+u,+h);v||(d=!0),p[c]={x:g[0],y:g[1],a:u,b:h,vis:v}}else p[c]={x:!1,y:!1};return e._needsCull=d,p[0].carpet=r,p[0].trace=e,s(e,f),a(t,e),i(p,e),o(p,e),p}}},{\"../carpet/lookup_carpetid\":916,\"../scatter/arrays_to_calcdata\":1119,\"../scatter/calc\":1121,\"../scatter/calc_selection\":1122,\"../scatter/colorscale_calc\":1123,\"fast-isnumeric\":228}],1155:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../scatter/constants\"),i=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/line_shape_defaults\"),c=t(\"../scatter/text_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),h=t(\"./attributes\");e.exports=function(t,e,r,f){function p(r,a){return n.coerce(t,e,h,r,a)}p(\"carpet\"),e.xaxis=\"x\",e.yaxis=\"y\";var d=p(\"a\"),g=p(\"b\"),v=Math.min(d.length,g.length);if(v){e._length=v,p(\"text\"),p(\"texttemplate\"),p(\"hovertext\"),p(\"mode\",v<a.PTS_LINESONLY?\"lines+markers\":\"lines\"),i.hasLines(e)&&(s(t,e,r,f,p),l(t,e,p),p(\"connectgaps\")),i.hasMarkers(e)&&o(t,e,r,f,p,{gradient:!0}),i.hasText(e)&&c(t,e,f,p);var m=[];(i.hasMarkers(e)||i.hasText(e))&&(p(\"marker.maxdisplayed\"),m.push(\"points\")),p(\"fill\"),\"none\"!==e.fill&&(u(t,e,r,p),i.hasLines(e)||l(t,e,p)),\"tonext\"!==e.fill&&\"toself\"!==e.fill||m.push(\"fills\"),\"fills\"!==p(\"hoveron\",m.join(\"+\")||\"points\")&&p(\"hovertemplate\"),n.coerceSelectionMarkerOpacity(e,p)}else e.visible=!1}},{\"../../lib\":717,\"../scatter/constants\":1124,\"../scatter/fillcolor_defaults\":1128,\"../scatter/line_defaults\":1133,\"../scatter/line_shape_defaults\":1135,\"../scatter/marker_defaults\":1139,\"../scatter/subtypes\":1144,\"../scatter/text_defaults\":1145,\"./attributes\":1153}],1156:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,a){var i=n[a];return t.a=i.a,t.b=i.b,t.y=i.y,t}},{}],1157:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r={},n=e._carpet,a=n.ab2ij([t.a,t.b]),i=Math.floor(a[0]),o=a[0]-i,s=Math.floor(a[1]),l=a[1]-s,c=n.evalxy([],i,s,o,l);return r.yLabel=c[1].toFixed(3),r}},{}],1158:[function(t,e,r){\"use strict\";var n=t(\"../scatter/hover\"),a=t(\"../../lib\").fillText;e.exports=function(t,e,r,i){var o=n(t,e,r,i);if(o&&!1!==o[0].index){var s=o[0];if(void 0===s.index){var l=1-s.y0/t.ya._length,c=t.xa._length,u=c*l/2,h=c-u;return s.x0=Math.max(Math.min(s.x0,h),u),s.x1=Math.max(Math.min(s.x1,h),u),o}var f=s.cd[s.index];s.a=f.a,s.b=f.b,s.xLabelVal=void 0,s.yLabelVal=void 0;var p=s.trace,d=p._carpet,g=p._module.formatLabels(f,p);s.yLabel=g.yLabel,delete s.text;var v=[];if(!p.hovertemplate){var m=(f.hi||p.hoverinfo).split(\"+\");-1!==m.indexOf(\"all\")&&(m=[\"a\",\"b\",\"text\"]),-1!==m.indexOf(\"a\")&&y(d.aaxis,f.a),-1!==m.indexOf(\"b\")&&y(d.baxis,f.b),v.push(\"y: \"+s.yLabel),-1!==m.indexOf(\"text\")&&a(f,p,v),s.extraText=v.join(\"<br>\")}return o}function y(t,e){var r;r=t.labelprefix&&t.labelprefix.length>0?t.labelprefix.replace(/ = $/,\"\"):t._hovertitle,v.push(r+\": \"+e.toFixed(3)+t.labelsuffix)}}},{\"../../lib\":717,\"../scatter/hover\":1131}],1159:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),colorbar:t(\"../scatter/marker_colorbar\"),formatLabels:t(\"./format_labels\"),calc:t(\"./calc\"),plot:t(\"./plot\"),style:t(\"../scatter/style\").style,styleOnSelect:t(\"../scatter/style\").styleOnSelect,hoverPoints:t(\"./hover\"),selectPoints:t(\"../scatter/select\"),eventData:t(\"./event_data\"),moduleType:\"trace\",name:\"scattercarpet\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"svg\",\"carpet\",\"symbols\",\"showLegend\",\"carpetDependent\",\"zoomScale\"],meta:{}}},{\"../../plots/cartesian\":776,\"../scatter/marker_colorbar\":1138,\"../scatter/select\":1141,\"../scatter/style\":1143,\"./attributes\":1153,\"./calc\":1154,\"./defaults\":1155,\"./event_data\":1156,\"./format_labels\":1157,\"./hover\":1158,\"./plot\":1160}],1160:[function(t,e,r){\"use strict\";var n=t(\"../scatter/plot\"),a=t(\"../../plots/cartesian/axes\"),i=t(\"../../components/drawing\");e.exports=function(t,e,r,o){var s,l,c,u=r[0][0].carpet,h={xaxis:a.getFromId(t,u.xaxis||\"x\"),yaxis:a.getFromId(t,u.yaxis||\"y\"),plot:e.plot};for(n(t,h,r,o),s=0;s<r.length;s++)l=r[s][0].trace,c=o.selectAll(\"g.trace\"+l.uid+\" .js-line\"),i.setClipUrl(c,r[s][0].carpet._clipPathId,t)}},{\"../../components/drawing\":613,\"../../plots/cartesian/axes\":765,\"../scatter/plot\":1140}],1161:[function(t,e,r){\"use strict\";var n=t(\"../../plots/template_attributes\").hovertemplateAttrs,a=t(\"../../plots/template_attributes\").texttemplateAttrs,i=t(\"../scatter/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../components/colorscale/attributes\"),l=t(\"../../components/drawing/attributes\").dash,c=t(\"../../lib/extend\").extendFlat,u=t(\"../../plot_api/edit_types\").overrideAll,h=i.marker,f=i.line,p=h.line;e.exports=u({lon:{valType:\"data_array\"},lat:{valType:\"data_array\"},locations:{valType:\"data_array\"},locationmode:{valType:\"enumerated\",values:[\"ISO-3\",\"USA-states\",\"country names\",\"geojson-id\"],dflt:\"ISO-3\"},geojson:{valType:\"any\",editType:\"calc\"},featureidkey:{valType:\"string\",editType:\"calc\",dflt:\"id\"},mode:c({},i.mode,{dflt:\"markers\"}),text:c({},i.text,{}),texttemplate:a({editType:\"plot\"},{keys:[\"lat\",\"lon\",\"location\",\"text\"]}),hovertext:c({},i.hovertext,{}),textfont:i.textfont,textposition:i.textposition,line:{color:f.color,width:f.width,dash:l},connectgaps:i.connectgaps,marker:c({symbol:h.symbol,opacity:h.opacity,size:h.size,sizeref:h.sizeref,sizemin:h.sizemin,sizemode:h.sizemode,colorbar:h.colorbar,line:c({width:p.width},s(\"marker.line\")),gradient:h.gradient},s(\"marker\")),fill:{valType:\"enumerated\",values:[\"none\",\"toself\"],dflt:\"none\"},fillcolor:i.fillcolor,selected:i.selected,unselected:i.unselected,hoverinfo:c({},o.hoverinfo,{flags:[\"lon\",\"lat\",\"location\",\"text\",\"name\"]}),hovertemplate:n()},\"calc\",\"nested\")},{\"../../components/colorscale/attributes\":599,\"../../components/drawing/attributes\":612,\"../../lib/extend\":708,\"../../plot_api/edit_types\":748,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"../scatter/attributes\":1120}],1162:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../constants/numerical\").BADNUM,i=t(\"../scatter/colorscale_calc\"),o=t(\"../scatter/arrays_to_calcdata\"),s=t(\"../scatter/calc_selection\"),l=t(\"../../lib\")._;function c(t){return t&&\"string\"==typeof t}e.exports=function(t,e){var r,u=Array.isArray(e.locations),h=u?e.locations.length:e._length,f=new Array(h);r=e.geojson?function(t){return c(t)||n(t)}:c;for(var p=0;p<h;p++){var d=f[p]={};if(u){var g=e.locations[p];d.loc=r(g)?g:null}else{var v=e.lon[p],m=e.lat[p];n(v)&&n(m)?d.lonlat=[+v,+m]:d.lonlat=[a,a]}}return o(f,e),i(t,e),s(f,e),h&&(f[0].t={labels:{lat:l(t,\"lat:\")+\" \",lon:l(t,\"lon:\")+\" \"}}),f}},{\"../../constants/numerical\":693,\"../../lib\":717,\"../scatter/arrays_to_calcdata\":1119,\"../scatter/calc_selection\":1122,\"../scatter/colorscale_calc\":1123,\"fast-isnumeric\":228}],1163:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),i=t(\"../scatter/marker_defaults\"),o=t(\"../scatter/line_defaults\"),s=t(\"../scatter/text_defaults\"),l=t(\"../scatter/fillcolor_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,u){function h(r,a){return n.coerce(t,e,c,r,a)}var f,p=h(\"locations\");if(p&&p.length){var d,g=h(\"geojson\");(\"string\"==typeof g&&\"\"!==g||n.isPlainObject(g))&&(d=\"geojson-id\"),\"geojson-id\"===h(\"locationmode\",d)&&h(\"featureidkey\"),f=p.length}else{var v=h(\"lon\")||[],m=h(\"lat\")||[];f=Math.min(v.length,m.length)}f?(e._length=f,h(\"text\"),h(\"hovertext\"),h(\"hovertemplate\"),h(\"mode\"),a.hasLines(e)&&(o(t,e,r,u,h),h(\"connectgaps\")),a.hasMarkers(e)&&i(t,e,r,u,h,{gradient:!0}),a.hasText(e)&&(h(\"texttemplate\"),s(t,e,u,h)),h(\"fill\"),\"none\"!==e.fill&&l(t,e,r,h),n.coerceSelectionMarkerOpacity(e,h)):e.visible=!1}},{\"../../lib\":717,\"../scatter/fillcolor_defaults\":1128,\"../scatter/line_defaults\":1133,\"../scatter/marker_defaults\":1139,\"../scatter/subtypes\":1144,\"../scatter/text_defaults\":1145,\"./attributes\":1161}],1164:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,a){t.lon=e.lon,t.lat=e.lat,t.location=e.loc?e.loc:null;var i=n[a];return i.fIn&&i.fIn.properties&&(t.properties=i.fIn.properties),t}},{}],1165:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\");e.exports=function(t,e,r){var a={},i=r[e.geo]._subplot.mockAxis,o=t.lonlat;return a.lonLabel=n.tickText(i,i.c2l(o[0]),!0).text,a.latLabel=n.tickText(i,i.c2l(o[1]),!0).text,a}},{\"../../plots/cartesian/axes\":765}],1166:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx\"),a=t(\"../../constants/numerical\").BADNUM,i=t(\"../scatter/get_trace_color\"),o=t(\"../../lib\").fillText,s=t(\"./attributes\");e.exports=function(t,e,r){var l=t.cd,c=l[0].trace,u=t.xa,h=t.ya,f=t.subplot,p=f.projection.isLonLatOverEdges,d=f.project;if(n.getClosest(l,function(t){var n=t.lonlat;if(n[0]===a)return 1/0;if(p(n))return 1/0;var i=d(n),o=d([e,r]),s=Math.abs(i[0]-o[0]),l=Math.abs(i[1]-o[1]),c=Math.max(3,t.mrc||0);return Math.max(Math.sqrt(s*s+l*l)-c,1-3/c)},t),!1!==t.index){var g=l[t.index],v=g.lonlat,m=[u.c2p(v),h.c2p(v)],y=g.mrc||1;t.x0=m[0]-y,t.x1=m[0]+y,t.y0=m[1]-y,t.y1=m[1]+y,t.loc=g.loc,t.lon=v[0],t.lat=v[1];var x={};x[c.geo]={_subplot:f};var b=c._module.formatLabels(g,c,x);return t.lonLabel=b.lonLabel,t.latLabel=b.latLabel,t.color=i(c,g),t.extraText=function(t,e,r,n){if(t.hovertemplate)return;var a=e.hi||t.hoverinfo,i=\"all\"===a?s.hoverinfo.flags:a.split(\"+\"),l=-1!==i.indexOf(\"location\")&&Array.isArray(t.locations),c=-1!==i.indexOf(\"lon\"),u=-1!==i.indexOf(\"lat\"),h=-1!==i.indexOf(\"text\"),f=[];function p(t){return t+\"\\xb0\"}l?f.push(e.loc):c&&u?f.push(\"(\"+p(r.lonLabel)+\", \"+p(r.latLabel)+\")\"):c?f.push(n.lon+p(r.lonLabel)):u&&f.push(n.lat+p(r.latLabel));h&&o(e,t,f);return f.join(\"<br>\")}(c,g,t,l[0].t.labels),t.hovertemplate=c.hovertemplate,[t]}}},{\"../../components/fx\":630,\"../../constants/numerical\":693,\"../../lib\":717,\"../scatter/get_trace_color\":1130,\"./attributes\":1161}],1167:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),colorbar:t(\"../scatter/marker_colorbar\"),formatLabels:t(\"./format_labels\"),calc:t(\"./calc\"),calcGeoJSON:t(\"./plot\").calcGeoJSON,plot:t(\"./plot\").plot,style:t(\"./style\"),styleOnSelect:t(\"../scatter/style\").styleOnSelect,hoverPoints:t(\"./hover\"),eventData:t(\"./event_data\"),selectPoints:t(\"./select\"),moduleType:\"trace\",name:\"scattergeo\",basePlotModule:t(\"../../plots/geo\"),categories:[\"geo\",\"symbols\",\"showLegend\",\"scatter-like\"],meta:{}}},{\"../../plots/geo\":795,\"../scatter/marker_colorbar\":1138,\"../scatter/style\":1143,\"./attributes\":1161,\"./calc\":1162,\"./defaults\":1163,\"./event_data\":1164,\"./format_labels\":1165,\"./hover\":1166,\"./plot\":1168,\"./select\":1169,\"./style\":1170}],1168:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\"),i=t(\"../../lib/topojson_utils\").getTopojsonFeatures,o=t(\"../../lib/geojson_utils\"),s=t(\"../../lib/geo_location_utils\"),l=t(\"../../plots/cartesian/autorange\").findExtremes,c=t(\"../../constants/numerical\").BADNUM,u=t(\"../scatter/calc\").calcMarkerSize,h=t(\"../scatter/subtypes\"),f=t(\"./style\");e.exports={calcGeoJSON:function(t,e){var r,n,a=t[0].trace,o=e[a.geo],h=o._subplot,f=a._length;if(Array.isArray(a.locations)){var p=a.locationmode,d=\"geojson-id\"===p?s.extractTraceFeature(t):i(a,h.topojson);for(r=0;r<f;r++){n=t[r];var g=\"geojson-id\"===p?n.fOut:s.locationToFeature(p,n.loc,d);n.lonlat=g?g.properties.ct:[c,c]}}var v,m,y={padded:!0};if(\"geojson\"===o.fitbounds&&\"geojson-id\"===a.locationmode){var x=s.computeBbox(s.getTraceGeojson(a));v=[x[0],x[2]],m=[x[1],x[3]]}else{for(v=new Array(f),m=new Array(f),r=0;r<f;r++)n=t[r],v[r]=n.lonlat[0],m[r]=n.lonlat[1];y.ppad=u(a,f)}a._extremes.lon=l(o.lonaxis._ax,v,y),a._extremes.lat=l(o.lataxis._ax,m,y)},plot:function(t,e,r){var i=e.layers.frontplot.select(\".scatterlayer\"),s=a.makeTraceGroups(i,r,\"trace scattergeo\");function l(t,e){t.lonlat[0]===c&&n.select(e).remove()}s.selectAll(\"*\").remove(),s.each(function(e){var r=n.select(this),i=e[0].trace;if(h.hasLines(i)||\"none\"!==i.fill){var s=o.calcTraceToLineCoords(e),c=\"none\"!==i.fill?o.makePolygon(s):o.makeLine(s);r.selectAll(\"path.js-line\").data([{geojson:c,trace:i}]).enter().append(\"path\").classed(\"js-line\",!0).style(\"stroke-miterlimit\",2)}h.hasMarkers(i)&&r.selectAll(\"path.point\").data(a.identity).enter().append(\"path\").classed(\"point\",!0).each(function(t){l(t,this)}),h.hasText(i)&&r.selectAll(\"g\").data(a.identity).enter().append(\"g\").append(\"text\").each(function(t){l(t,this)}),f(t,e)})}}},{\"../../constants/numerical\":693,\"../../lib\":717,\"../../lib/geo_location_utils\":711,\"../../lib/geojson_utils\":712,\"../../lib/topojson_utils\":744,\"../../plots/cartesian/autorange\":764,\"../scatter/calc\":1121,\"../scatter/subtypes\":1144,\"./style\":1170,d3:165}],1169:[function(t,e,r){\"use strict\";var n=t(\"../scatter/subtypes\"),a=t(\"../../constants/numerical\").BADNUM;e.exports=function(t,e){var r,i,o,s,l,c=t.cd,u=t.xaxis,h=t.yaxis,f=[],p=c[0].trace;if(!n.hasMarkers(p)&&!n.hasText(p))return[];if(!1===e)for(l=0;l<c.length;l++)c[l].selected=0;else for(l=0;l<c.length;l++)(i=(r=c[l]).lonlat)[0]!==a&&(o=u.c2p(i),s=h.c2p(i),e.contains([o,s],null,l,t)?(f.push({pointNumber:l,lon:i[0],lat:i[1]}),r.selected=1):r.selected=0);return f}},{\"../../constants/numerical\":693,\"../scatter/subtypes\":1144}],1170:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../components/drawing\"),i=t(\"../../components/color\"),o=t(\"../scatter/style\"),s=o.stylePoints,l=o.styleText;e.exports=function(t,e){e&&function(t,e){var r=e[0].trace,o=e[0].node3;o.style(\"opacity\",e[0].trace.opacity),s(o,r,t),l(o,r,t),o.selectAll(\"path.js-line\").style(\"fill\",\"none\").each(function(t){var e=n.select(this),r=t.trace,o=r.line||{};e.call(i.stroke,o.color).call(a.dashLine,o.dash||\"\",o.width||0),\"none\"!==r.fill&&e.call(i.fill,r.fillcolor)})}(t,e)}},{\"../../components/color\":592,\"../../components/drawing\":613,\"../scatter/style\":1143,d3:165}],1171:[function(t,e,r){\"use strict\";var n=t(\"../../plots/attributes\"),a=t(\"../scatter/attributes\"),i=t(\"../../components/colorscale/attributes\"),o=t(\"../../lib/extend\").extendFlat,s=t(\"../../plot_api/edit_types\").overrideAll,l=t(\"./constants\").DASHES,c=a.line,u=a.marker,h=u.line,f=e.exports=s({x:a.x,x0:a.x0,dx:a.dx,y:a.y,y0:a.y0,dy:a.dy,text:a.text,hovertext:a.hovertext,textposition:a.textposition,textfont:a.textfont,mode:{valType:\"flaglist\",flags:[\"lines\",\"markers\",\"text\"],extras:[\"none\"]},line:{color:c.color,width:c.width,shape:{valType:\"enumerated\",values:[\"linear\",\"hv\",\"vh\",\"hvh\",\"vhv\"],dflt:\"linear\",editType:\"plot\"},dash:{valType:\"enumerated\",values:Object.keys(l),dflt:\"solid\"}},marker:o({},i(\"marker\"),{symbol:u.symbol,size:u.size,sizeref:u.sizeref,sizemin:u.sizemin,sizemode:u.sizemode,opacity:u.opacity,colorbar:u.colorbar,line:o({},i(\"marker.line\"),{width:h.width})}),connectgaps:a.connectgaps,fill:o({},a.fill,{dflt:\"none\"}),fillcolor:a.fillcolor,selected:{marker:a.selected.marker,textfont:a.selected.textfont},unselected:{marker:a.unselected.marker,textfont:a.unselected.textfont},opacity:n.opacity},\"calc\",\"nested\");f.x.editType=f.y.editType=f.x0.editType=f.y0.editType=\"calc+clearAxisTypes\",f.hovertemplate=a.hovertemplate,f.texttemplate=a.texttemplate},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plot_api/edit_types\":748,\"../../plots/attributes\":762,\"../scatter/attributes\":1120,\"./constants\":1173}],1172:[function(t,e,r){\"use strict\";var n=t(\"point-cluster\"),a=t(\"../../lib\"),i=t(\"../../plots/cartesian/axis_ids\"),o=t(\"../../plots/cartesian/autorange\").findExtremes,s=t(\"../scatter/calc\"),l=s.calcMarkerSize,c=s.calcAxisExpansion,u=s.setFirstScatter,h=t(\"../scatter/colorscale_calc\"),f=t(\"./convert\"),p=t(\"./scene_update\"),d=t(\"../../constants/numerical\").BADNUM,g=t(\"./constants\").TOO_MANY_POINTS;function v(t,e,r){var n=t._extremes[e._id],a=o(e,r._bnds,{padded:!0});n.min=n.min.concat(a.min),n.max=n.max.concat(a.max)}e.exports=function(t,e){var r,o,s,m=t._fullLayout,y=i.getFromId(t,e.xaxis),x=i.getFromId(t,e.yaxis),b=m._plots[e.xaxis+e.yaxis],_=e._length,w=_>=g,k=2*_,T={},M=e._x=y.makeCalcdata(e,\"x\"),A=e._y=x.makeCalcdata(e,\"y\"),S=new Array(k);for(r=0;r<_;r++)o=M[r],s=A[r],S[2*r]=o===d?NaN:o,S[2*r+1]=s===d?NaN:s;if(\"log\"===y.type)for(r=0;r<k;r+=2)S[r]=y.c2l(S[r]);if(\"log\"===x.type)for(r=1;r<k;r+=2)S[r]=x.c2l(S[r]);if(w&&\"log\"!==y.type&&\"log\"!==x.type)T.tree=n(S);else{var E=T.ids=new Array(_);for(r=0;r<_;r++)E[r]=r}h(t,e);var L,C=function(t,e,r,n,i,o){var s=f.style(t,r);s.marker&&(s.marker.positions=n);s.line&&n.length>1&&a.extendFlat(s.line,f.linePositions(t,r,n));if(s.errorX||s.errorY){var l=f.errorBarPositions(t,r,n,i,o);s.errorX&&a.extendFlat(s.errorX,l.x),s.errorY&&a.extendFlat(s.errorY,l.y)}s.text&&(a.extendFlat(s.text,{positions:n},f.textPosition(t,r,s.text,s.marker)),a.extendFlat(s.textSel,{positions:n},f.textPosition(t,r,s.text,s.markerSel)),a.extendFlat(s.textUnsel,{positions:n},f.textPosition(t,r,s.text,s.markerUnsel)));return s}(t,0,e,S,M,A),P=p(t,b);return u(m,e),w?C.marker&&(L=2*(C.marker.sizeAvg||Math.max(C.marker.size,3))):L=l(e,_),c(t,e,y,x,M,A,L),C.errorX&&v(e,y,C.errorX),C.errorY&&v(e,x,C.errorY),C.fill&&!P.fill2d&&(P.fill2d=!0),C.marker&&!P.scatter2d&&(P.scatter2d=!0),C.line&&!P.line2d&&(P.line2d=!0),!C.errorX&&!C.errorY||P.error2d||(P.error2d=!0),C.text&&!P.glText&&(P.glText=!0),C.marker&&(C.marker.snap=_),P.lineOptions.push(C.line),P.errorXOptions.push(C.errorX),P.errorYOptions.push(C.errorY),P.fillOptions.push(C.fill),P.markerOptions.push(C.marker),P.markerSelectedOptions.push(C.markerSel),P.markerUnselectedOptions.push(C.markerUnsel),P.textOptions.push(C.text),P.textSelectedOptions.push(C.textSel),P.textUnselectedOptions.push(C.textUnsel),P.selectBatch.push([]),P.unselectBatch.push([]),T._scene=P,T.index=P.count,T.x=M,T.y=A,T.positions=S,P.count++,[{x:!1,y:!1,t:T,trace:e}]}},{\"../../constants/numerical\":693,\"../../lib\":717,\"../../plots/cartesian/autorange\":764,\"../../plots/cartesian/axis_ids\":768,\"../scatter/calc\":1121,\"../scatter/colorscale_calc\":1123,\"./constants\":1173,\"./convert\":1174,\"./scene_update\":1182,\"point-cluster\":471}],1173:[function(t,e,r){\"use strict\";e.exports={TOO_MANY_POINTS:1e5,SYMBOL_SDF_SIZE:200,SYMBOL_SIZE:20,SYMBOL_STROKE:1,DOT_RE:/-dot/,OPEN_RE:/-open/,DASHES:{solid:[1],dot:[1,1],dash:[4,1],longdash:[8,1],dashdot:[4,1,1,1],longdashdot:[8,1,1,1]}}},{}],1174:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"svg-path-sdf\"),i=t(\"color-normalize\"),o=t(\"../../registry\"),s=t(\"../../lib\"),l=t(\"../../components/drawing\"),c=t(\"../../plots/cartesian/axis_ids\"),u=t(\"../../lib/gl_format_color\").formatColor,h=t(\"../scatter/subtypes\"),f=t(\"../scatter/make_bubble_size_func\"),p=t(\"./helpers\"),d=t(\"./constants\"),g=t(\"../../constants/interactions\").DESELECTDIM,v={start:1,left:1,end:-1,right:-1,middle:0,center:0,bottom:1,top:-1},m=t(\"../../components/fx/helpers\").appendArrayPointValue;function y(t,e){var r,a=t._fullLayout,i=e._length,o=e.textfont,l=e.textposition,c=Array.isArray(l)?l:[l],u=o.color,h=o.size,f=o.family,p={},d=e.texttemplate;if(d){p.text=[];var g=a._d3locale,v=Array.isArray(d),y=v?Math.min(d.length,i):i,x=v?function(t){return d[t]}:function(){return d};for(r=0;r<y;r++){var b={i:r},_=e._module.formatLabels(b,e,a),w={};m(w,e,r);var k=e._meta||{};p.text.push(s.texttemplateString(x(r),_,g,w,b,k))}}else Array.isArray(e.text)&&e.text.length<i?p.text=e.text.slice():p.text=e.text;if(Array.isArray(p.text))for(r=p.text.length;r<i;r++)p.text[r]=\"\";for(p.opacity=e.opacity,p.font={},p.align=[],p.baseline=[],r=0;r<c.length;r++){var T=c[r].split(/\\s+/);switch(T[1]){case\"left\":p.align.push(\"right\");break;case\"right\":p.align.push(\"left\");break;default:p.align.push(T[1])}switch(T[0]){case\"top\":p.baseline.push(\"bottom\");break;case\"bottom\":p.baseline.push(\"top\");break;default:p.baseline.push(T[0])}}if(Array.isArray(u))for(p.color=new Array(i),r=0;r<i;r++)p.color[r]=u[r];else p.color=u;if(s.isArrayOrTypedArray(h)||Array.isArray(f))for(p.font=new Array(i),r=0;r<i;r++){var M=p.font[r]={};M.size=s.isTypedArray(h)?h[r]:Array.isArray(h)?n(h[r])?h[r]:0:h,M.family=Array.isArray(f)?f[r]:f}else p.font={size:h,family:f};return p}function x(t){var e,r,n=t._length,a=t.marker,o={},l=s.isArrayOrTypedArray(a.symbol),c=s.isArrayOrTypedArray(a.color),h=s.isArrayOrTypedArray(a.line.color),d=s.isArrayOrTypedArray(a.opacity),g=s.isArrayOrTypedArray(a.size),v=s.isArrayOrTypedArray(a.line.width);if(l||(r=p.isOpenSymbol(a.symbol)),l||c||h||d){o.colors=new Array(n),o.borderColors=new Array(n);var m=u(a,a.opacity,n),y=u(a.line,a.opacity,n);if(!Array.isArray(y[0])){var x=y;for(y=Array(n),e=0;e<n;e++)y[e]=x}if(!Array.isArray(m[0])){var b=m;for(m=Array(n),e=0;e<n;e++)m[e]=b}for(o.colors=m,o.borderColors=y,e=0;e<n;e++){if(l){var _=a.symbol[e];r=p.isOpenSymbol(_)}r&&(y[e]=m[e].slice(),m[e]=m[e].slice(),m[e][3]=0)}o.opacity=t.opacity}else r?(o.color=i(a.color,\"uint8\"),o.color[3]=0,o.borderColor=i(a.color,\"uint8\")):(o.color=i(a.color,\"uint8\"),o.borderColor=i(a.line.color,\"uint8\")),o.opacity=t.opacity*a.opacity;if(l)for(o.markers=new Array(n),e=0;e<n;e++)o.markers[e]=E(a.symbol[e]);else o.marker=E(a.symbol);var w,k=f(t);if(g||v){var T,M=o.sizes=new Array(n),A=o.borderSizes=new Array(n),S=0;if(g){for(e=0;e<n;e++)M[e]=k(a.size[e]),S+=M[e];T=S/n}else for(w=k(a.size),e=0;e<n;e++)M[e]=w;if(v)for(e=0;e<n;e++)A[e]=a.line.width[e]/2;else for(w=a.line.width/2,e=0;e<n;e++)A[e]=w;o.sizeAvg=T}else o.size=k(a&&a.size||10),o.borderSizes=k(a.line.width);return o}function b(t,e){var r=t.marker,n={};return e?(e.marker&&e.marker.symbol?n=x(s.extendFlat({},r,e.marker)):e.marker&&(e.marker.size&&(n.size=e.marker.size/2),e.marker.color&&(n.colors=e.marker.color),void 0!==e.marker.opacity&&(n.opacity=e.marker.opacity)),n):n}function _(t,e,r){var n={};if(!r)return n;if(r.textfont){var a={opacity:1,text:e.text,texttemplate:e.texttemplate,textposition:e.textposition,textfont:s.extendFlat({},e.textfont)};r.textfont&&s.extendFlat(a.textfont,r.textfont),n=y(t,a)}return n}function w(t,e){var r={capSize:2*e.width,lineWidth:e.thickness,color:e.color};return e.copy_ystyle&&(r=t.error_y),r}var k=d.SYMBOL_SDF_SIZE,T=d.SYMBOL_SIZE,M=d.SYMBOL_STROKE,A={},S=l.symbolFuncs[0](.05*T);function E(t){if(\"circle\"===t)return null;var e,r,n=l.symbolNumber(t),i=l.symbolFuncs[n%100],o=!!l.symbolNoDot[n%100],s=!!l.symbolNoFill[n%100],c=p.isDotSymbol(t);return A[t]?A[t]:(e=c&&!o?i(1.1*T)+S:i(T),r=a(e,{w:k,h:k,viewBox:[-T,-T,T,T],stroke:s?M:-M}),A[t]=r,r||null)}e.exports={style:function(t,e){var r,n={marker:void 0,markerSel:void 0,markerUnsel:void 0,line:void 0,fill:void 0,errorX:void 0,errorY:void 0,text:void 0,textSel:void 0,textUnsel:void 0};if(!0!==e.visible)return n;if(h.hasText(e)&&(n.text=y(t,e),n.textSel=_(t,e,e.selected),n.textUnsel=_(t,e,e.unselected)),h.hasMarkers(e)&&(n.marker=x(e),n.markerSel=b(e,e.selected),n.markerUnsel=b(e,e.unselected),!e.unselected&&s.isArrayOrTypedArray(e.marker.opacity))){var a=e.marker.opacity;for(n.markerUnsel.opacity=new Array(a.length),r=0;r<a.length;r++)n.markerUnsel.opacity[r]=g*a[r]}if(h.hasLines(e)){n.line={overlay:!0,thickness:e.line.width,color:e.line.color,opacity:e.opacity};var i=(d.DASHES[e.line.dash]||[1]).slice();for(r=0;r<i.length;++r)i[r]*=e.line.width;n.line.dashes=i}return e.error_x&&e.error_x.visible&&(n.errorX=w(e,e.error_x)),e.error_y&&e.error_y.visible&&(n.errorY=w(e,e.error_y)),e.fill&&\"none\"!==e.fill&&(n.fill={closed:!0,fill:e.fillcolor,thickness:0}),n},markerStyle:x,markerSelection:b,linePositions:function(t,e,r){var n,a,i=r.length,o=i/2;if(h.hasLines(e)&&o)if(\"hv\"===e.line.shape){for(n=[],a=0;a<o-1;a++)isNaN(r[2*a])||isNaN(r[2*a+1])?n.push(NaN,NaN,NaN,NaN):(n.push(r[2*a],r[2*a+1]),isNaN(r[2*a+2])||isNaN(r[2*a+3])?n.push(NaN,NaN):n.push(r[2*a+2],r[2*a+1]));n.push(r[i-2],r[i-1])}else if(\"hvh\"===e.line.shape){for(n=[],a=0;a<o-1;a++)if(isNaN(r[2*a])||isNaN(r[2*a+1])||isNaN(r[2*a+2])||isNaN(r[2*a+3]))isNaN(r[2*a])||isNaN(r[2*a+1])?n.push(NaN,NaN):n.push(r[2*a],r[2*a+1]),n.push(NaN,NaN);else{var s=(r[2*a]+r[2*a+2])/2;n.push(r[2*a],r[2*a+1],s,r[2*a+1],s,r[2*a+3])}n.push(r[i-2],r[i-1])}else if(\"vhv\"===e.line.shape){for(n=[],a=0;a<o-1;a++)if(isNaN(r[2*a])||isNaN(r[2*a+1])||isNaN(r[2*a+2])||isNaN(r[2*a+3]))isNaN(r[2*a])||isNaN(r[2*a+1])?n.push(NaN,NaN):n.push(r[2*a],r[2*a+1]),n.push(NaN,NaN);else{var l=(r[2*a+1]+r[2*a+3])/2;n.push(r[2*a],r[2*a+1],r[2*a],l,r[2*a+2],l)}n.push(r[i-2],r[i-1])}else if(\"vh\"===e.line.shape){for(n=[],a=0;a<o-1;a++)isNaN(r[2*a])||isNaN(r[2*a+1])?n.push(NaN,NaN,NaN,NaN):(n.push(r[2*a],r[2*a+1]),isNaN(r[2*a+2])||isNaN(r[2*a+3])?n.push(NaN,NaN):n.push(r[2*a],r[2*a+3]));n.push(r[i-2],r[i-1])}else n=r;var c=!1;for(a=0;a<n.length;a++)if(isNaN(n[a])){c=!0;break}var u=c||n.length>d.TOO_MANY_POINTS?\"rect\":h.hasMarkers(e)?\"rect\":\"round\";if(c&&e.connectgaps){var f=n[0],p=n[1];for(a=0;a<n.length;a+=2)isNaN(n[a])||isNaN(n[a+1])?(n[a]=f,n[a+1]=p):(f=n[a],p=n[a+1])}return{join:u,positions:n}},errorBarPositions:function(t,e,r,a,i){var s=o.getComponentMethod(\"errorbars\",\"makeComputeError\"),l=c.getFromId(t,e.xaxis),u=c.getFromId(t,e.yaxis),h=r.length/2,f={};function p(t,a){var i=a._id.charAt(0),o=e[\"error_\"+i];if(o&&o.visible&&(\"linear\"===a.type||\"log\"===a.type)){for(var l=s(o),c={x:0,y:1}[i],u={x:[0,1,2,3],y:[2,3,0,1]}[i],p=new Float64Array(4*h),d=1/0,g=-1/0,v=0,m=0;v<h;v++,m+=4){var y=t[v];if(n(y)){var x=r[2*v+c],b=l(y,v),_=b[0],w=b[1];if(n(_)&&n(w)){var k=y-_,T=y+w;p[m+u[0]]=x-a.c2l(k),p[m+u[1]]=a.c2l(T)-x,p[m+u[2]]=0,p[m+u[3]]=0,d=Math.min(d,y-_),g=Math.max(g,y+w)}}}f[i]={positions:r,errors:p,_bnds:[d,g]}}}return p(a,l),p(i,u),f},textPosition:function(t,e,r,n){var a,i=e._length,o={};if(h.hasMarkers(e)){var s=r.font,l=r.align,c=r.baseline;for(o.offset=new Array(i),a=0;a<i;a++){var u=n.sizes?n.sizes[a]:n.size,f=Array.isArray(s)?s[a].size:s.size,p=Array.isArray(l)?l.length>1?l[a]:l[0]:l,d=Array.isArray(c)?c.length>1?c[a]:c[0]:c,g=v[p],m=v[d],y=u?u/.8+1:0,x=-m*y-.5*m;o.offset[a]=[g*y/f,x/f]}}return o}}},{\"../../components/drawing\":613,\"../../components/fx/helpers\":627,\"../../constants/interactions\":692,\"../../lib\":717,\"../../lib/gl_format_color\":714,\"../../plots/cartesian/axis_ids\":768,\"../../registry\":846,\"../scatter/make_bubble_size_func\":1137,\"../scatter/subtypes\":1144,\"./constants\":1173,\"./helpers\":1178,\"color-normalize\":122,\"fast-isnumeric\":228,\"svg-path-sdf\":534}],1175:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../registry\"),i=t(\"./helpers\"),o=t(\"./attributes\"),s=t(\"../scatter/constants\"),l=t(\"../scatter/subtypes\"),c=t(\"../scatter/xy_defaults\"),u=t(\"../scatter/marker_defaults\"),h=t(\"../scatter/line_defaults\"),f=t(\"../scatter/fillcolor_defaults\"),p=t(\"../scatter/text_defaults\");e.exports=function(t,e,r,d){function g(r,a){return n.coerce(t,e,o,r,a)}var v=!!t.marker&&i.isOpenSymbol(t.marker.symbol),m=l.isBubble(t),y=c(t,e,d,g);if(y){var x=y<s.PTS_LINESONLY?\"lines+markers\":\"lines\";g(\"text\"),g(\"hovertext\"),g(\"hovertemplate\"),g(\"mode\",x),l.hasLines(e)&&(g(\"connectgaps\"),h(t,e,r,d,g),g(\"line.shape\")),l.hasMarkers(e)&&(u(t,e,r,d,g),g(\"marker.line.width\",v||m?1:0)),l.hasText(e)&&(g(\"texttemplate\"),p(t,e,d,g));var b=(e.line||{}).color,_=(e.marker||{}).color;g(\"fill\"),\"none\"!==e.fill&&f(t,e,r,g);var w=a.getComponentMethod(\"errorbars\",\"supplyDefaults\");w(t,e,b||_||r,{axis:\"y\"}),w(t,e,b||_||r,{axis:\"x\",inherit:\"y\"}),n.coerceSelectionMarkerOpacity(e,g)}else e.visible=!1}},{\"../../lib\":717,\"../../registry\":846,\"../scatter/constants\":1124,\"../scatter/fillcolor_defaults\":1128,\"../scatter/line_defaults\":1133,\"../scatter/marker_defaults\":1139,\"../scatter/subtypes\":1144,\"../scatter/text_defaults\":1145,\"../scatter/xy_defaults\":1146,\"./attributes\":1171,\"./helpers\":1178}],1176:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/color\"),i=t(\"../../constants/interactions\").DESELECTDIM;e.exports={styleTextSelection:function(t){var e,r,o=t[0],s=o.trace,l=o.t,c=l._scene,u=l.index,h=c.selectBatch[u],f=c.unselectBatch[u],p=c.textOptions[u],d=c.textSelectedOptions[u]||{},g=c.textUnselectedOptions[u]||{},v=n.extendFlat({},p);if(h.length||f.length){var m=d.color,y=g.color,x=p.color,b=Array.isArray(x);for(v.color=new Array(s._length),e=0;e<h.length;e++)r=h[e],v.color[r]=m||(b?x[r]:x);for(e=0;e<f.length;e++){r=f[e];var _=b?x[r]:x;v.color[r]=y||(m?_:a.addOpacity(_,i))}}c.glText[u].update(v)}}},{\"../../components/color\":592,\"../../constants/interactions\":692,\"../../lib\":717}],1177:[function(t,e,r){\"use strict\";var n=t(\"../scatter/format_labels\");e.exports=function(t,e,r){var a=t.i;return\"x\"in t||(t.x=e._x[a]),\"y\"in t||(t.y=e._y[a]),n(t,e,r)}},{\"../scatter/format_labels\":1129}],1178:[function(t,e,r){\"use strict\";var n=t(\"./constants\");r.isOpenSymbol=function(t){return\"string\"==typeof t?n.OPEN_RE.test(t):t%200>100},r.isDotSymbol=function(t){return\"string\"==typeof t?n.DOT_RE.test(t):t>200}},{\"./constants\":1173}],1179:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../lib\"),i=t(\"../scatter/get_trace_color\");function o(t,e,r,o){var s=t.xa,l=t.ya,c=t.distance,u=t.dxy,h=t.index,f={pointNumber:h,x:e[h],y:r[h]};f.tx=Array.isArray(o.text)?o.text[h]:o.text,f.htx=Array.isArray(o.hovertext)?o.hovertext[h]:o.hovertext,f.data=Array.isArray(o.customdata)?o.customdata[h]:o.customdata,f.tp=Array.isArray(o.textposition)?o.textposition[h]:o.textposition;var p=o.textfont;p&&(f.ts=a.isArrayOrTypedArray(p.size)?p.size[h]:p.size,f.tc=Array.isArray(p.color)?p.color[h]:p.color,f.tf=Array.isArray(p.family)?p.family[h]:p.family);var d=o.marker;d&&(f.ms=a.isArrayOrTypedArray(d.size)?d.size[h]:d.size,f.mo=a.isArrayOrTypedArray(d.opacity)?d.opacity[h]:d.opacity,f.mx=a.isArrayOrTypedArray(d.symbol)?d.symbol[h]:d.symbol,f.mc=a.isArrayOrTypedArray(d.color)?d.color[h]:d.color);var g=d&&d.line;g&&(f.mlc=Array.isArray(g.color)?g.color[h]:g.color,f.mlw=a.isArrayOrTypedArray(g.width)?g.width[h]:g.width);var v=d&&d.gradient;v&&\"none\"!==v.type&&(f.mgt=Array.isArray(v.type)?v.type[h]:v.type,f.mgc=Array.isArray(v.color)?v.color[h]:v.color);var m=s.c2p(f.x,!0),y=l.c2p(f.y,!0),x=f.mrc||1,b=o.hoverlabel;b&&(f.hbg=Array.isArray(b.bgcolor)?b.bgcolor[h]:b.bgcolor,f.hbc=Array.isArray(b.bordercolor)?b.bordercolor[h]:b.bordercolor,f.hts=a.isArrayOrTypedArray(b.font.size)?b.font.size[h]:b.font.size,f.htc=Array.isArray(b.font.color)?b.font.color[h]:b.font.color,f.htf=Array.isArray(b.font.family)?b.font.family[h]:b.font.family,f.hnl=a.isArrayOrTypedArray(b.namelength)?b.namelength[h]:b.namelength);var _=o.hoverinfo;_&&(f.hi=Array.isArray(_)?_[h]:_);var w=o.hovertemplate;w&&(f.ht=Array.isArray(w)?w[h]:w);var k={};k[t.index]=f;var T=a.extendFlat({},t,{color:i(o,f),x0:m-x,x1:m+x,xLabelVal:f.x,y0:y-x,y1:y+x,yLabelVal:f.y,cd:k,distance:c,spikeDistance:u,hovertemplate:f.ht});return f.htx?T.text=f.htx:f.tx?T.text=f.tx:o.text&&(T.text=o.text),a.fillText(f,o,T),n.getComponentMethod(\"errorbars\",\"hoverInfo\")(f,o,T),T}e.exports={hoverPoints:function(t,e,r,n){var a,i,s,l,c,u,h,f,p,d=t.cd,g=d[0].t,v=d[0].trace,m=t.xa,y=t.ya,x=g.x,b=g.y,_=m.c2p(e),w=y.c2p(r),k=t.distance;if(g.tree){var T=m.p2c(_-k),M=m.p2c(_+k),A=y.p2c(w-k),S=y.p2c(w+k);a=\"x\"===n?g.tree.range(Math.min(T,M),Math.min(y._rl[0],y._rl[1]),Math.max(T,M),Math.max(y._rl[0],y._rl[1])):g.tree.range(Math.min(T,M),Math.min(A,S),Math.max(T,M),Math.max(A,S))}else a=g.ids;var E=k;if(\"x\"===n)for(c=0;c<a.length;c++)s=x[a[c]],(u=Math.abs(m.c2p(s)-_))<E&&(E=u,h=y.c2p(b[a[c]])-w,p=Math.sqrt(u*u+h*h),i=a[c]);else for(c=a.length-1;c>-1;c--)s=x[a[c]],l=b[a[c]],u=m.c2p(s)-_,h=y.c2p(l)-w,(f=Math.sqrt(u*u+h*h))<E&&(E=p=f,i=a[c]);return t.index=i,t.distance=E,t.dxy=p,void 0===i?[t]:[o(t,x,b,v)]},calcHover:o}},{\"../../lib\":717,\"../../registry\":846,\"../scatter/get_trace_color\":1130}],1180:[function(t,e,r){\"use strict\";var n=t(\"./hover\");e.exports={moduleType:\"trace\",name:\"scattergl\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"gl\",\"regl\",\"cartesian\",\"symbols\",\"errorBarsOK\",\"showLegend\",\"scatter-like\"],attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),crossTraceDefaults:t(\"../scatter/cross_trace_defaults\"),colorbar:t(\"../scatter/marker_colorbar\"),formatLabels:t(\"./format_labels\"),calc:t(\"./calc\"),plot:t(\"./plot\"),hoverPoints:n.hoverPoints,selectPoints:t(\"./select\"),meta:{}}},{\"../../plots/cartesian\":776,\"../scatter/cross_trace_defaults\":1126,\"../scatter/marker_colorbar\":1138,\"./attributes\":1171,\"./calc\":1172,\"./defaults\":1175,\"./format_labels\":1177,\"./hover\":1179,\"./plot\":1181,\"./select\":1183}],1181:[function(t,e,r){\"use strict\";var n=t(\"regl-scatter2d\"),a=t(\"regl-line2d\"),i=t(\"regl-error2d\"),o=t(\"gl-text\"),s=t(\"../../lib\"),l=t(\"../../lib/prepare_regl\"),c=t(\"../scatter/subtypes\"),u=t(\"../scatter/link_traces\"),h=t(\"./edit_style\").styleTextSelection;function f(t,e,r){var n=t._size,a=t.width,i=t.height;return[n.l+e.domain[0]*n.w,n.b+r.domain[0]*n.h,a-n.r-(1-e.domain[1])*n.w,i-n.t-(1-r.domain[1])*n.h]}e.exports=function(t,e,r){if(r.length){var p,d,g=t._fullLayout,v=e._scene,m=e.xaxis,y=e.yaxis;if(v)if(l(t,[\"ANGLE_instanced_arrays\",\"OES_element_index_uint\"])){var x=v.count,b=g._glcanvas.data()[0].regl;if(u(t,e,r),v.dirty){if(!0===v.error2d&&(v.error2d=i(b)),!0===v.line2d&&(v.line2d=a(b)),!0===v.scatter2d&&(v.scatter2d=n(b)),!0===v.fill2d&&(v.fill2d=a(b)),!0===v.glText)for(v.glText=new Array(x),p=0;p<x;p++)v.glText[p]=new o(b);if(v.glText){if(x>v.glText.length){var _=x-v.glText.length;for(p=0;p<_;p++)v.glText.push(new o(b))}else if(x<v.glText.length){var w=v.glText.length-x;v.glText.splice(x,w).forEach(function(t){t.destroy()})}for(p=0;p<x;p++)v.glText[p].update(v.textOptions[p])}if(v.line2d&&(v.line2d.update(v.lineOptions),v.lineOptions=v.lineOptions.map(function(t){if(t&&t.positions){for(var e=t.positions,r=0;r<e.length&&(isNaN(e[r])||isNaN(e[r+1]));)r+=2;for(var n=e.length-2;n>r&&(isNaN(e[n])||isNaN(e[n+1]));)n-=2;t.positions=e.slice(r,n+2)}return t}),v.line2d.update(v.lineOptions)),v.error2d){var k=(v.errorXOptions||[]).concat(v.errorYOptions||[]);v.error2d.update(k)}v.scatter2d&&v.scatter2d.update(v.markerOptions),v.fillOrder=s.repeat(null,x),v.fill2d&&(v.fillOptions=v.fillOptions.map(function(t,e){var n=r[e];if(t&&n&&n[0]&&n[0].trace){var a,i,o=n[0],s=o.trace,l=o.t,c=v.lineOptions[e],u=[];s._ownfill&&u.push(e),s._nexttrace&&u.push(e+1),u.length&&(v.fillOrder[e]=u);var h,f,p=[],d=c&&c.positions||l.positions;if(\"tozeroy\"===s.fill){for(h=0;h<d.length&&isNaN(d[h+1]);)h+=2;for(f=d.length-2;f>h&&isNaN(d[f+1]);)f-=2;0!==d[h+1]&&(p=[d[h],0]),p=p.concat(d.slice(h,f+2)),0!==d[f+1]&&(p=p.concat([d[f],0]))}else if(\"tozerox\"===s.fill){for(h=0;h<d.length&&isNaN(d[h]);)h+=2;for(f=d.length-2;f>h&&isNaN(d[f]);)f-=2;0!==d[h]&&(p=[0,d[h+1]]),p=p.concat(d.slice(h,f+2)),0!==d[f]&&(p=p.concat([0,d[f+1]]))}else if(\"toself\"===s.fill||\"tonext\"===s.fill){for(p=[],a=0,i=0;i<d.length;i+=2)(isNaN(d[i])||isNaN(d[i+1]))&&((p=p.concat(d.slice(a,i))).push(d[a],d[a+1]),a=i+2);p=p.concat(d.slice(a)),a&&p.push(d[a],d[a+1])}else{var g=s._nexttrace;if(g){var m=v.lineOptions[e+1];if(m){var y=m.positions;if(\"tonexty\"===s.fill){for(p=d.slice(),e=Math.floor(y.length/2);e--;){var x=y[2*e],b=y[2*e+1];isNaN(x)||isNaN(b)||p.push(x,b)}t.fill=g.fillcolor}}}}if(s._prevtrace&&\"tonext\"===s._prevtrace.fill){var _=v.lineOptions[e-1].positions,w=p.length/2,k=[a=w];for(i=0;i<_.length;i+=2)(isNaN(_[i])||isNaN(_[i+1]))&&(k.push(i/2+w+1),a=i+2);p=p.concat(_),t.hole=k}return t.fillmode=s.fill,t.opacity=s.opacity,t.positions=p,t}}),v.fill2d.update(v.fillOptions))}var T=g.dragmode,M=\"lasso\"===T||\"select\"===T,A=g.clickmode.indexOf(\"select\")>-1;for(p=0;p<x;p++){var S=r[p][0],E=S.trace,L=S.t,C=L.index,P=E._length,O=L.x,z=L.y;if(E.selectedpoints||M||A){if(M||(M=!0),E.selectedpoints){var I=v.selectBatch[C]=s.selIndices2selPoints(E),D={};for(d=0;d<I.length;d++)D[I[d]]=1;var R=[];for(d=0;d<P;d++)D[d]||R.push(d);v.unselectBatch[C]=R}var F=L.xpx=new Array(P),B=L.ypx=new Array(P);for(d=0;d<P;d++)F[d]=m.c2p(O[d]),B[d]=y.c2p(z[d])}else L.xpx=L.ypx=null}if(M){if(v.select2d||(v.select2d=n(g._glcanvas.data()[1].regl)),v.scatter2d){var N=new Array(x);for(p=0;p<x;p++)N[p]=v.selectBatch[p].length||v.unselectBatch[p].length?v.markerUnselectedOptions[p]:{};v.scatter2d.update(N)}v.select2d&&(v.select2d.update(v.markerOptions),v.select2d.update(v.markerSelectedOptions)),v.glText&&r.forEach(function(t){var e=((t||[])[0]||{}).trace||{};c.hasText(e)&&h(t)})}else v.scatter2d&&v.scatter2d.update(v.markerOptions);var j={viewport:f(g,m,y),range:[(m._rl||m.range)[0],(y._rl||y.range)[0],(m._rl||m.range)[1],(y._rl||y.range)[1]]},V=s.repeat(j,v.count);v.fill2d&&v.fill2d.update(V),v.line2d&&v.line2d.update(V),v.error2d&&v.error2d.update(V.concat(V)),v.scatter2d&&v.scatter2d.update(V),v.select2d&&v.select2d.update(V),v.glText&&v.glText.forEach(function(t){t.update(j)})}else v.init()}}},{\"../../lib\":717,\"../../lib/prepare_regl\":730,\"../scatter/link_traces\":1136,\"../scatter/subtypes\":1144,\"./edit_style\":1176,\"gl-text\":319,\"regl-error2d\":492,\"regl-line2d\":493,\"regl-scatter2d\":499}],1182:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){var r=e._scene,a={count:0,dirty:!0,lineOptions:[],fillOptions:[],markerOptions:[],markerSelectedOptions:[],markerUnselectedOptions:[],errorXOptions:[],errorYOptions:[],textOptions:[],textSelectedOptions:[],textUnselectedOptions:[],selectBatch:[],unselectBatch:[]},i={fill2d:!1,scatter2d:!1,error2d:!1,line2d:!1,glText:!1,select2d:!1};return e._scene||((r=e._scene={}).init=function(){n.extendFlat(r,i,a)},r.init(),r.update=function(t){var e=n.repeat(t,r.count);if(r.fill2d&&r.fill2d.update(e),r.scatter2d&&r.scatter2d.update(e),r.line2d&&r.line2d.update(e),r.error2d&&r.error2d.update(e.concat(e)),r.select2d&&r.select2d.update(e),r.glText)for(var a=0;a<r.count;a++)r.glText[a].update(t)},r.draw=function(){for(var t=r.count,e=r.fill2d,a=r.error2d,i=r.line2d,o=r.scatter2d,s=r.glText,l=r.select2d,c=r.selectBatch,u=r.unselectBatch,h=0;h<t;h++){if(e&&r.fillOrder[h]&&e.draw(r.fillOrder[h]),i&&r.lineOptions[h]&&i.draw(h),a&&(r.errorXOptions[h]&&a.draw(h),r.errorYOptions[h]&&a.draw(h+t)),o&&r.markerOptions[h])if(u[h].length){var f=n.repeat([],r.count);f[h]=u[h],o.draw(f)}else c[h].length||o.draw(h);s[h]&&r.textOptions[h]&&s[h].render()}l&&l.draw(c),r.dirty=!1},r.destroy=function(){r.fill2d&&r.fill2d.destroy&&r.fill2d.destroy(),r.scatter2d&&r.scatter2d.destroy&&r.scatter2d.destroy(),r.error2d&&r.error2d.destroy&&r.error2d.destroy(),r.line2d&&r.line2d.destroy&&r.line2d.destroy(),r.select2d&&r.select2d.destroy&&r.select2d.destroy(),r.glText&&r.glText.forEach(function(t){t.destroy&&t.destroy()}),r.lineOptions=null,r.fillOptions=null,r.markerOptions=null,r.markerSelectedOptions=null,r.markerUnselectedOptions=null,r.errorXOptions=null,r.errorYOptions=null,r.textOptions=null,r.textSelectedOptions=null,r.textUnselectedOptions=null,r.selectBatch=null,r.unselectBatch=null,e._scene=null}),r.dirty||n.extendFlat(r,a),r}},{\"../../lib\":717}],1183:[function(t,e,r){\"use strict\";var n=t(\"../scatter/subtypes\"),a=t(\"./edit_style\").styleTextSelection;e.exports=function(t,e){var r=t.cd,i=[],o=r[0].trace,s=r[0].t,l=o._length,c=s.x,u=s.y,h=s._scene,f=s.index;if(!h)return i;var p=n.hasText(o),d=n.hasMarkers(o),g=!d&&!p;if(!0!==o.visible||g)return i;var v=[],m=[];if(!1!==e&&!e.degenerate)for(var y=0;y<l;y++)e.contains([s.xpx[y],s.ypx[y]],!1,y,t)?(v.push(y),i.push({pointNumber:y,x:c[y],y:u[y]})):m.push(y);if(d){var x=h.scatter2d;if(v.length||m.length){if(!h.selectBatch[f].length&&!h.unselectBatch[f].length){var b=new Array(h.count);b[f]=h.markerUnselectedOptions[f],x.update.apply(x,b)}}else{var _=new Array(h.count);_[f]=h.markerOptions[f],x.update.apply(x,_)}}return h.selectBatch[f]=v,h.unselectBatch[f]=m,p&&a(r),i}},{\"../scatter/subtypes\":1144,\"./edit_style\":1176}],1184:[function(t,e,r){\"use strict\";var n=t(\"../../plots/template_attributes\").hovertemplateAttrs,a=t(\"../../plots/template_attributes\").texttemplateAttrs,i=t(\"../scattergeo/attributes\"),o=t(\"../scatter/attributes\"),s=t(\"../../plots/mapbox/layout_attributes\"),l=t(\"../../plots/attributes\"),c=t(\"../../components/colorscale/attributes\"),u=t(\"../../lib/extend\").extendFlat,h=t(\"../../plot_api/edit_types\").overrideAll,f=i.line,p=i.marker;e.exports=h({lon:i.lon,lat:i.lat,mode:u({},o.mode,{dflt:\"markers\"}),text:u({},o.text,{}),texttemplate:a({editType:\"plot\"},{keys:[\"lat\",\"lon\",\"text\"]}),hovertext:u({},o.hovertext,{}),line:{color:f.color,width:f.width},connectgaps:o.connectgaps,marker:u({symbol:{valType:\"string\",dflt:\"circle\",arrayOk:!0},opacity:p.opacity,size:p.size,sizeref:p.sizeref,sizemin:p.sizemin,sizemode:p.sizemode},c(\"marker\")),fill:i.fill,fillcolor:o.fillcolor,textfont:s.layers.symbol.textfont,textposition:s.layers.symbol.textposition,below:{valType:\"string\"},selected:{marker:o.selected.marker},unselected:{marker:o.unselected.marker},hoverinfo:u({},l.hoverinfo,{flags:[\"lon\",\"lat\",\"text\",\"name\"]}),hovertemplate:n()},\"calc\",\"nested\")},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plot_api/edit_types\":748,\"../../plots/attributes\":762,\"../../plots/mapbox/layout_attributes\":822,\"../../plots/template_attributes\":841,\"../scatter/attributes\":1120,\"../scattergeo/attributes\":1161}],1185:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../lib\"),i=t(\"../../constants/numerical\").BADNUM,o=t(\"../../lib/geojson_utils\"),s=t(\"../../components/colorscale\"),l=t(\"../../components/drawing\"),c=t(\"../scatter/make_bubble_size_func\"),u=t(\"../scatter/subtypes\"),h=t(\"../../plots/mapbox/convert_text_opts\"),f=t(\"../../components/fx/helpers\").appendArrayPointValue,p=t(\"../../lib/svg_text_utils\").NEWLINES,d=t(\"../../lib/svg_text_utils\").BR_TAG_ALL;function g(){return{geojson:o.makeBlank(),layout:{visibility:\"none\"},paint:{}}}function v(t){return a.isArrayOrTypedArray(t)?function(t){return t}:t?function(){return t}:m}function m(){return\"\"}function y(t){return t[0]===i}e.exports=function(t,e){var r,i=e[0].trace,x=!0===i.visible&&0!==i._length,b=\"none\"!==i.fill,_=u.hasLines(i),w=u.hasMarkers(i),k=u.hasText(i),T=w&&\"circle\"===i.marker.symbol,M=w&&\"circle\"!==i.marker.symbol,A=g(),S=g(),E=g(),L=g(),C={fill:A,line:S,circle:E,symbol:L};if(!x)return C;if((b||_)&&(r=o.calcTraceToLineCoords(e)),b&&(A.geojson=o.makePolygon(r),A.layout.visibility=\"visible\",a.extendFlat(A.paint,{\"fill-color\":i.fillcolor})),_&&(S.geojson=o.makeLine(r),S.layout.visibility=\"visible\",a.extendFlat(S.paint,{\"line-width\":i.line.width,\"line-color\":i.line.color,\"line-opacity\":i.opacity})),T){var P=function(t){var e,r,i,o,u=t[0].trace,h=u.marker,f=u.selectedpoints,p=a.isArrayOrTypedArray(h.color),d=a.isArrayOrTypedArray(h.size),g=a.isArrayOrTypedArray(h.opacity);function v(t){return u.opacity*t}p&&(r=s.hasColorscale(u,\"marker\")?s.makeColorScaleFuncFromTrace(h):a.identity);d&&(i=c(u));g&&(o=function(t){var e=n(t)?+a.constrain(t,0,1):0;return v(e)});var m,x=[];for(e=0;e<t.length;e++){var b=t[e],_=b.lonlat;if(!y(_)){var w={};r&&(w.mcc=b.mcc=r(b.mc)),i&&(w.mrc=b.mrc=i(b.ms)),o&&(w.mo=o(b.mo)),f&&(w.selected=b.selected||0),x.push({type:\"Feature\",geometry:{type:\"Point\",coordinates:_},properties:w})}}if(f)for(m=l.makeSelectedPointStyleFns(u),e=0;e<x.length;e++){var k=x[e].properties;m.selectedOpacityFn&&(k.mo=v(m.selectedOpacityFn(k))),m.selectedColorFn&&(k.mcc=m.selectedColorFn(k)),m.selectedSizeFn&&(k.mrc=m.selectedSizeFn(k))}return{geojson:{type:\"FeatureCollection\",features:x},mcc:p||m&&m.selectedColorFn?{type:\"identity\",property:\"mcc\"}:h.color,mrc:d||m&&m.selectedSizeFn?{type:\"identity\",property:\"mrc\"}:(T=h.size,T/2),mo:g||m&&m.selectedOpacityFn?{type:\"identity\",property:\"mo\"}:v(h.opacity)};var T}(e);E.geojson=P.geojson,E.layout.visibility=\"visible\",a.extendFlat(E.paint,{\"circle-color\":P.mcc,\"circle-radius\":P.mrc,\"circle-opacity\":P.mo})}if((M||k)&&(L.geojson=function(t,e){for(var r=e._fullLayout,n=t[0].trace,i=(n.marker||{}).symbol,o=\"circle\"!==i?v(i):m,s=u.hasText(n)?v(n.text):m,l=[],c=0;c<t.length;c++){var h=t[c];if(!y(h.lonlat)){var g,x=n.texttemplate;if(x){var b=Array.isArray(x)?x[c]||\"\":x,_=n._module.formatLabels(h,n,r),w={};f(w,n,h.i);var k=n._meta||{};g=a.texttemplateString(b,_,r._d3locale,w,h,k)}else g=s(h.tx);g&&(g=g.replace(p,\"\").replace(d,\"\\n\")),l.push({type:\"Feature\",geometry:{type:\"Point\",coordinates:h.lonlat},properties:{symbol:o(h.mx),text:g}})}}return{type:\"FeatureCollection\",features:l}}(e,t),a.extendFlat(L.layout,{visibility:\"visible\",\"icon-image\":\"{symbol}-15\",\"text-field\":\"{text}\"}),M&&(a.extendFlat(L.layout,{\"icon-size\":i.marker.size/10}),a.extendFlat(L.paint,{\"icon-opacity\":i.opacity*i.marker.opacity,\"icon-color\":i.marker.color})),k)){var O=(i.marker||{}).size,z=h(i.textposition,O);a.extendFlat(L.layout,{\"text-size\":i.textfont.size,\"text-anchor\":z.anchor,\"text-offset\":z.offset}),a.extendFlat(L.paint,{\"text-color\":i.textfont.color,\"text-opacity\":i.opacity})}return C}},{\"../../components/colorscale\":604,\"../../components/drawing\":613,\"../../components/fx/helpers\":627,\"../../constants/numerical\":693,\"../../lib\":717,\"../../lib/geojson_utils\":712,\"../../lib/svg_text_utils\":741,\"../../plots/mapbox/convert_text_opts\":819,\"../scatter/make_bubble_size_func\":1137,\"../scatter/subtypes\":1144,\"fast-isnumeric\":228}],1186:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),i=t(\"../scatter/marker_defaults\"),o=t(\"../scatter/line_defaults\"),s=t(\"../scatter/text_defaults\"),l=t(\"../scatter/fillcolor_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,u){function h(r,a){return n.coerce(t,e,c,r,a)}if(function(t,e,r){var n=r(\"lon\")||[],a=r(\"lat\")||[],i=Math.min(n.length,a.length);return e._length=i,i}(0,e,h)){if(h(\"text\"),h(\"texttemplate\"),h(\"hovertext\"),h(\"hovertemplate\"),h(\"mode\"),h(\"below\"),a.hasLines(e)&&(o(t,e,r,u,h,{noDash:!0}),h(\"connectgaps\")),a.hasMarkers(e)){i(t,e,r,u,h,{noLine:!0});var f=e.marker;\"circle\"!==f.symbol&&(n.isArrayOrTypedArray(f.size)&&(f.size=f.size[0]),n.isArrayOrTypedArray(f.color)&&(f.color=f.color[0]))}a.hasText(e)&&s(t,e,u,h,{noSelect:!0}),h(\"fill\"),\"none\"!==e.fill&&l(t,e,r,h),n.coerceSelectionMarkerOpacity(e,h)}else e.visible=!1}},{\"../../lib\":717,\"../scatter/fillcolor_defaults\":1128,\"../scatter/line_defaults\":1133,\"../scatter/marker_defaults\":1139,\"../scatter/subtypes\":1144,\"../scatter/text_defaults\":1145,\"./attributes\":1184}],1187:[function(t,e,r){\"use strict\";e.exports=function(t,e){return t.lon=e.lon,t.lat=e.lat,t}},{}],1188:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\");e.exports=function(t,e,r){var a={},i=r[e.subplot]._subplot.mockAxis,o=t.lonlat;return a.lonLabel=n.tickText(i,i.c2l(o[0]),!0).text,a.latLabel=n.tickText(i,i.c2l(o[1]),!0).text,a}},{\"../../plots/cartesian/axes\":765}],1189:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx\"),a=t(\"../../lib\"),i=t(\"../scatter/get_trace_color\"),o=a.fillText,s=t(\"../../constants/numerical\").BADNUM;e.exports=function(t,e,r){var l=t.cd,c=l[0].trace,u=t.xa,h=t.ya,f=t.subplot,p=360*(e>=0?Math.floor((e+180)/360):Math.ceil((e-180)/360)),d=e-p;if(n.getClosest(l,function(t){var e=t.lonlat;if(e[0]===s)return 1/0;var n=a.modHalf(e[0],360),i=e[1],o=f.project([n,i]),l=o.x-u.c2p([d,i]),c=o.y-h.c2p([n,r]),p=Math.max(3,t.mrc||0);return Math.max(Math.sqrt(l*l+c*c)-p,1-3/p)},t),!1!==t.index){var g=l[t.index],v=g.lonlat,m=[a.modHalf(v[0],360)+p,v[1]],y=u.c2p(m),x=h.c2p(m),b=g.mrc||1;t.x0=y-b,t.x1=y+b,t.y0=x-b,t.y1=x+b;var _={};_[c.subplot]={_subplot:f};var w=c._module.formatLabels(g,c,_);return t.lonLabel=w.lonLabel,t.latLabel=w.latLabel,t.color=i(c,g),t.extraText=function(t,e,r){if(t.hovertemplate)return;var n=(e.hi||t.hoverinfo).split(\"+\"),a=-1!==n.indexOf(\"all\"),i=-1!==n.indexOf(\"lon\"),s=-1!==n.indexOf(\"lat\"),l=e.lonlat,c=[];function u(t){return t+\"\\xb0\"}a||i&&s?c.push(\"(\"+u(l[0])+\", \"+u(l[1])+\")\"):i?c.push(r.lon+u(l[0])):s&&c.push(r.lat+u(l[1]));(a||-1!==n.indexOf(\"text\"))&&o(e,t,c);return c.join(\"<br>\")}(c,g,l[0].t.labels),t.hovertemplate=c.hovertemplate,[t]}}},{\"../../components/fx\":630,\"../../constants/numerical\":693,\"../../lib\":717,\"../scatter/get_trace_color\":1130}],1190:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),colorbar:t(\"../scatter/marker_colorbar\"),formatLabels:t(\"./format_labels\"),calc:t(\"../scattergeo/calc\"),plot:t(\"./plot\"),hoverPoints:t(\"./hover\"),eventData:t(\"./event_data\"),selectPoints:t(\"./select\"),styleOnSelect:function(t,e){e&&e[0].trace._glTrace.update(e)},moduleType:\"trace\",name:\"scattermapbox\",basePlotModule:t(\"../../plots/mapbox\"),categories:[\"mapbox\",\"gl\",\"symbols\",\"showLegend\",\"scatter-like\"],meta:{}}},{\"../../plots/mapbox\":820,\"../scatter/marker_colorbar\":1138,\"../scattergeo/calc\":1162,\"./attributes\":1184,\"./defaults\":1186,\"./event_data\":1187,\"./format_labels\":1188,\"./hover\":1189,\"./plot\":1191,\"./select\":1192}],1191:[function(t,e,r){\"use strict\";var n=t(\"./convert\"),a=t(\"../../plots/mapbox/constants\").traceLayerPrefix,i=[\"fill\",\"line\",\"circle\",\"symbol\"];function o(t,e){this.type=\"scattermapbox\",this.subplot=t,this.uid=e,this.sourceIds={fill:\"source-\"+e+\"-fill\",line:\"source-\"+e+\"-line\",circle:\"source-\"+e+\"-circle\",symbol:\"source-\"+e+\"-symbol\"},this.layerIds={fill:a+e+\"-fill\",line:a+e+\"-line\",circle:a+e+\"-circle\",symbol:a+e+\"-symbol\"},this.below=null}var s=o.prototype;s.addSource=function(t,e){this.subplot.map.addSource(this.sourceIds[t],{type:\"geojson\",data:e.geojson})},s.setSourceData=function(t,e){this.subplot.map.getSource(this.sourceIds[t]).setData(e.geojson)},s.addLayer=function(t,e,r){this.subplot.addLayer({type:t,id:this.layerIds[t],source:this.sourceIds[t],layout:e.layout,paint:e.paint},r)},s.update=function(t){var e,r,a,o=this.subplot,s=o.map,l=n(o.gd,t),c=o.belowLookup[\"trace-\"+this.uid];if(c!==this.below){for(e=i.length-1;e>=0;e--)r=i[e],s.removeLayer(this.layerIds[r]);for(e=0;e<i.length;e++)a=l[r=i[e]],this.addLayer(r,a,c);this.below=c}for(e=0;e<i.length;e++)a=l[r=i[e]],o.setOptions(this.layerIds[r],\"setLayoutProperty\",a.layout),\"visible\"===a.layout.visibility&&(this.setSourceData(r,a),o.setOptions(this.layerIds[r],\"setPaintProperty\",a.paint));t[0].trace._glTrace=this},s.dispose=function(){for(var t=this.subplot.map,e=i.length-1;e>=0;e--){var r=i[e];t.removeLayer(this.layerIds[r]),t.removeSource(this.sourceIds[r])}},e.exports=function(t,e){for(var r=e[0].trace,a=new o(t,r.uid),s=n(t.gd,e),l=a.below=t.belowLookup[\"trace-\"+r.uid],c=0;c<i.length;c++){var u=i[c],h=s[u];a.addSource(u,h),a.addLayer(u,h,l)}return e[0].trace._glTrace=a,a}},{\"../../plots/mapbox/constants\":818,\"./convert\":1185}],1192:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),i=t(\"../../constants/numerical\").BADNUM;e.exports=function(t,e){var r,o=t.cd,s=t.xaxis,l=t.yaxis,c=[],u=o[0].trace;if(!a.hasMarkers(u))return[];if(!1===e)for(r=0;r<o.length;r++)o[r].selected=0;else for(r=0;r<o.length;r++){var h=o[r],f=h.lonlat;if(f[0]!==i){var p=[n.modHalf(f[0],360),f[1]],d=[s.c2p(p),l.c2p(p)];e.contains(d,null,r,t)?(c.push({pointNumber:r,lon:f[0],lat:f[1]}),h.selected=1):h.selected=0}}return c}},{\"../../constants/numerical\":693,\"../../lib\":717,\"../scatter/subtypes\":1144}],1193:[function(t,e,r){\"use strict\";var n=t(\"../../plots/template_attributes\").hovertemplateAttrs,a=t(\"../../plots/template_attributes\").texttemplateAttrs,i=t(\"../../lib/extend\").extendFlat,o=t(\"../scatter/attributes\"),s=t(\"../../plots/attributes\"),l=o.line;e.exports={mode:o.mode,r:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},theta:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},r0:{valType:\"any\",dflt:0,editType:\"calc+clearAxisTypes\"},dr:{valType:\"number\",dflt:1,editType:\"calc\"},theta0:{valType:\"any\",dflt:0,editType:\"calc+clearAxisTypes\"},dtheta:{valType:\"number\",editType:\"calc\"},thetaunit:{valType:\"enumerated\",values:[\"radians\",\"degrees\",\"gradians\"],dflt:\"degrees\",editType:\"calc+clearAxisTypes\"},text:o.text,texttemplate:a({editType:\"plot\"},{keys:[\"r\",\"theta\",\"text\"]}),hovertext:o.hovertext,line:{color:l.color,width:l.width,dash:l.dash,shape:i({},l.shape,{values:[\"linear\",\"spline\"]}),smoothing:l.smoothing,editType:\"calc\"},connectgaps:o.connectgaps,marker:o.marker,cliponaxis:i({},o.cliponaxis,{dflt:!1}),textposition:o.textposition,textfont:o.textfont,fill:i({},o.fill,{values:[\"none\",\"toself\",\"tonext\"],dflt:\"none\"}),fillcolor:o.fillcolor,hoverinfo:i({},s.hoverinfo,{flags:[\"r\",\"theta\",\"text\",\"name\"]}),hoveron:o.hoveron,hovertemplate:n(),selected:o.selected,unselected:o.unselected}},{\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"../scatter/attributes\":1120}],1194:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../../constants/numerical\").BADNUM,i=t(\"../../plots/cartesian/axes\"),o=t(\"../scatter/colorscale_calc\"),s=t(\"../scatter/arrays_to_calcdata\"),l=t(\"../scatter/calc_selection\"),c=t(\"../scatter/calc\").calcMarkerSize;e.exports=function(t,e){for(var r=t._fullLayout,u=e.subplot,h=r[u].radialaxis,f=r[u].angularaxis,p=h.makeCalcdata(e,\"r\"),d=f.makeCalcdata(e,\"theta\"),g=e._length,v=new Array(g),m=0;m<g;m++){var y=p[m],x=d[m],b=v[m]={};n(y)&&n(x)?(b.r=y,b.theta=x):b.r=a}var _=c(e,g);return e._extremes.x=i.findExtremes(h,p,{ppad:_}),o(t,e),s(v,e),l(v,e),v}},{\"../../constants/numerical\":693,\"../../plots/cartesian/axes\":765,\"../scatter/arrays_to_calcdata\":1119,\"../scatter/calc\":1121,\"../scatter/calc_selection\":1122,\"../scatter/colorscale_calc\":1123,\"fast-isnumeric\":228}],1195:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),i=t(\"../scatter/marker_defaults\"),o=t(\"../scatter/line_defaults\"),s=t(\"../scatter/line_shape_defaults\"),l=t(\"../scatter/text_defaults\"),c=t(\"../scatter/fillcolor_defaults\"),u=t(\"../scatter/constants\").PTS_LINESONLY,h=t(\"./attributes\");function f(t,e,r,n){var a,i=n(\"r\"),o=n(\"theta\");if(i)o?a=Math.min(i.length,o.length):(a=i.length,n(\"theta0\"),n(\"dtheta\"));else{if(!o)return 0;a=e.theta.length,n(\"r0\"),n(\"dr\")}return e._length=a,a}e.exports={handleRThetaDefaults:f,supplyDefaults:function(t,e,r,p){function d(r,a){return n.coerce(t,e,h,r,a)}var g=f(0,e,0,d);if(g){d(\"thetaunit\"),d(\"mode\",g<u?\"lines+markers\":\"lines\"),d(\"text\"),d(\"hovertext\"),\"fills\"!==e.hoveron&&d(\"hovertemplate\"),a.hasLines(e)&&(o(t,e,r,p,d),s(t,e,d),d(\"connectgaps\")),a.hasMarkers(e)&&i(t,e,r,p,d,{gradient:!0}),a.hasText(e)&&(d(\"texttemplate\"),l(t,e,p,d));var v=[];(a.hasMarkers(e)||a.hasText(e))&&(d(\"cliponaxis\"),d(\"marker.maxdisplayed\"),v.push(\"points\")),d(\"fill\"),\"none\"!==e.fill&&(c(t,e,r,d),a.hasLines(e)||s(t,e,d)),\"tonext\"!==e.fill&&\"toself\"!==e.fill||v.push(\"fills\"),d(\"hoveron\",v.join(\"+\")||\"points\"),n.coerceSelectionMarkerOpacity(e,d)}else e.visible=!1}}},{\"../../lib\":717,\"../scatter/constants\":1124,\"../scatter/fillcolor_defaults\":1128,\"../scatter/line_defaults\":1133,\"../scatter/line_shape_defaults\":1135,\"../scatter/marker_defaults\":1139,\"../scatter/subtypes\":1144,\"../scatter/text_defaults\":1145,\"./attributes\":1193}],1196:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/cartesian/axes\");e.exports=function(t,e,r){var i,o,s={},l=r[e.subplot]._subplot;l?(i=l.radialAxis,o=l.angularAxis):(i=(l=r[e.subplot]).radialaxis,o=l.angularaxis);var c=i.c2l(t.r);s.rLabel=a.tickText(i,c,!0).text;var u=\"degrees\"===o.thetaunit?n.rad2deg(t.theta):t.theta;return s.thetaLabel=a.tickText(o,u,!0).text,s}},{\"../../lib\":717,\"../../plots/cartesian/axes\":765}],1197:[function(t,e,r){\"use strict\";var n=t(\"../scatter/hover\");function a(t,e,r,n){var a=r.radialAxis,i=r.angularAxis;a._hovertitle=\"r\",i._hovertitle=\"\\u03b8\";var o={};o[e.subplot]={_subplot:r};var s=e._module.formatLabels(t,e,o);n.rLabel=s.rLabel,n.thetaLabel=s.thetaLabel;var l=t.hi||e.hoverinfo,c=[];function u(t,e){c.push(t._hovertitle+\": \"+e)}if(!e.hovertemplate){var h=l.split(\"+\");-1!==h.indexOf(\"all\")&&(h=[\"r\",\"theta\",\"text\"]),-1!==h.indexOf(\"r\")&&u(a,n.rLabel),-1!==h.indexOf(\"theta\")&&u(i,n.thetaLabel),-1!==h.indexOf(\"text\")&&n.text&&(c.push(n.text),delete n.text),n.extraText=c.join(\"<br>\")}}e.exports={hoverPoints:function(t,e,r,i){var o=n(t,e,r,i);if(o&&!1!==o[0].index){var s=o[0];if(void 0===s.index)return o;var l=t.subplot,c=s.cd[s.index],u=s.trace;if(l.isPtInside(c))return s.xLabelVal=void 0,s.yLabelVal=void 0,a(c,u,l,s),s.hovertemplate=u.hovertemplate,o}},makeHoverPointText:a}},{\"../scatter/hover\":1131}],1198:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"scatterpolar\",basePlotModule:t(\"../../plots/polar\"),categories:[\"polar\",\"symbols\",\"showLegend\",\"scatter-like\"],attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,colorbar:t(\"../scatter/marker_colorbar\"),formatLabels:t(\"./format_labels\"),calc:t(\"./calc\"),plot:t(\"./plot\"),style:t(\"../scatter/style\").style,styleOnSelect:t(\"../scatter/style\").styleOnSelect,hoverPoints:t(\"./hover\").hoverPoints,selectPoints:t(\"../scatter/select\"),meta:{}}},{\"../../plots/polar\":829,\"../scatter/marker_colorbar\":1138,\"../scatter/select\":1141,\"../scatter/style\":1143,\"./attributes\":1193,\"./calc\":1194,\"./defaults\":1195,\"./format_labels\":1196,\"./hover\":1197,\"./plot\":1199}],1199:[function(t,e,r){\"use strict\";var n=t(\"../scatter/plot\"),a=t(\"../../constants/numerical\").BADNUM;e.exports=function(t,e,r){for(var i=e.layers.frontplot.select(\"g.scatterlayer\"),o={xaxis:e.xaxis,yaxis:e.yaxis,plot:e.framework,layerClipId:e._hasClipOnAxisFalse?e.clipIds.forTraces:null},s=e.radialAxis,l=e.angularAxis,c=0;c<r.length;c++)for(var u=r[c],h=0;h<u.length;h++){var f=u[h],p=f.r;if(p===a)f.x=f.y=a;else{var d=s.c2g(p),g=l.c2g(f.theta);f.x=d*Math.cos(g),f.y=d*Math.sin(g)}}n(t,o,r,i)}},{\"../../constants/numerical\":693,\"../scatter/plot\":1140}],1200:[function(t,e,r){\"use strict\";var n=t(\"../scatterpolar/attributes\"),a=t(\"../scattergl/attributes\"),i=t(\"../../plots/template_attributes\").texttemplateAttrs;e.exports={mode:n.mode,r:n.r,theta:n.theta,r0:n.r0,dr:n.dr,theta0:n.theta0,dtheta:n.dtheta,thetaunit:n.thetaunit,text:n.text,texttemplate:i({editType:\"plot\"},{keys:[\"r\",\"theta\",\"text\"]}),hovertext:n.hovertext,hovertemplate:n.hovertemplate,line:a.line,connectgaps:a.connectgaps,marker:a.marker,fill:a.fill,fillcolor:a.fillcolor,textposition:a.textposition,textfont:a.textfont,hoverinfo:n.hoverinfo,selected:n.selected,unselected:n.unselected}},{\"../../plots/template_attributes\":841,\"../scattergl/attributes\":1171,\"../scatterpolar/attributes\":1193}],1201:[function(t,e,r){\"use strict\";var n=t(\"../scatter/colorscale_calc\"),a=t(\"../scatter/calc\").calcMarkerSize,i=t(\"../scattergl/convert\"),o=t(\"../../plots/cartesian/axes\"),s=t(\"../scattergl/constants\").TOO_MANY_POINTS;e.exports=function(t,e){var r=t._fullLayout,l=e.subplot,c=r[l].radialaxis,u=r[l].angularaxis,h=e._r=c.makeCalcdata(e,\"r\"),f=e._theta=u.makeCalcdata(e,\"theta\"),p=e._length,d={};p<h.length&&(h=h.slice(0,p)),p<f.length&&(f=f.slice(0,p)),d.r=h,d.theta=f,n(t,e);var g,v=d.opts=i.style(t,e);return p<s?g=a(e,p):v.marker&&(g=2*(v.marker.sizeAvg||Math.max(v.marker.size,3))),e._extremes.x=o.findExtremes(c,h,{ppad:g}),[{x:!1,y:!1,t:d,trace:e}]}},{\"../../plots/cartesian/axes\":765,\"../scatter/calc\":1121,\"../scatter/colorscale_calc\":1123,\"../scattergl/constants\":1173,\"../scattergl/convert\":1174}],1202:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),i=t(\"../scatterpolar/defaults\").handleRThetaDefaults,o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),c=t(\"../scatter/fillcolor_defaults\"),u=t(\"../scatter/constants\").PTS_LINESONLY,h=t(\"./attributes\");e.exports=function(t,e,r,f){function p(r,a){return n.coerce(t,e,h,r,a)}var d=i(t,e,f,p);d?(p(\"thetaunit\"),p(\"mode\",d<u?\"lines+markers\":\"lines\"),p(\"text\"),p(\"hovertext\"),\"fills\"!==e.hoveron&&p(\"hovertemplate\"),a.hasLines(e)&&(s(t,e,r,f,p),p(\"connectgaps\")),a.hasMarkers(e)&&o(t,e,r,f,p),a.hasText(e)&&(p(\"texttemplate\"),l(t,e,f,p)),p(\"fill\"),\"none\"!==e.fill&&c(t,e,r,p),n.coerceSelectionMarkerOpacity(e,p)):e.visible=!1}},{\"../../lib\":717,\"../scatter/constants\":1124,\"../scatter/fillcolor_defaults\":1128,\"../scatter/line_defaults\":1133,\"../scatter/marker_defaults\":1139,\"../scatter/subtypes\":1144,\"../scatter/text_defaults\":1145,\"../scatterpolar/defaults\":1195,\"./attributes\":1200}],1203:[function(t,e,r){\"use strict\";var n=t(\"../scatterpolar/format_labels\");e.exports=function(t,e,r){var a=t.i;return\"r\"in t||(t.r=e._r[a]),\"theta\"in t||(t.theta=e._theta[a]),n(t,e,r)}},{\"../scatterpolar/format_labels\":1196}],1204:[function(t,e,r){\"use strict\";var n=t(\"../scattergl/hover\"),a=t(\"../scatterpolar/hover\").makeHoverPointText;e.exports={hoverPoints:function(t,e,r,i){var o=t.cd[0].t,s=o.r,l=o.theta,c=n.hoverPoints(t,e,r,i);if(c&&!1!==c[0].index){var u=c[0];if(void 0===u.index)return c;var h=t.subplot,f=u.cd[u.index],p=u.trace;if(f.r=s[u.index],f.theta=l[u.index],h.isPtInside(f))return u.xLabelVal=void 0,u.yLabelVal=void 0,a(f,p,h,u),c}}}},{\"../scattergl/hover\":1179,\"../scatterpolar/hover\":1197}],1205:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"scatterpolargl\",basePlotModule:t(\"../../plots/polar\"),categories:[\"gl\",\"regl\",\"polar\",\"symbols\",\"showLegend\",\"scatter-like\"],attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),colorbar:t(\"../scatter/marker_colorbar\"),formatLabels:t(\"./format_labels\"),calc:t(\"./calc\"),plot:t(\"./plot\"),hoverPoints:t(\"./hover\").hoverPoints,selectPoints:t(\"../scattergl/select\"),meta:{}}},{\"../../plots/polar\":829,\"../scatter/marker_colorbar\":1138,\"../scattergl/select\":1183,\"./attributes\":1200,\"./calc\":1201,\"./defaults\":1202,\"./format_labels\":1203,\"./hover\":1204,\"./plot\":1206}],1206:[function(t,e,r){\"use strict\";var n=t(\"point-cluster\"),a=t(\"fast-isnumeric\"),i=t(\"../scattergl/plot\"),o=t(\"../scattergl/scene_update\"),s=t(\"../scattergl/convert\"),l=t(\"../../lib\"),c=t(\"../scattergl/constants\").TOO_MANY_POINTS;e.exports=function(t,e,r){if(r.length){var u=e.radialAxis,h=e.angularAxis,f=o(t,e);return r.forEach(function(r){if(r&&r[0]&&r[0].trace){var i,o=r[0],p=o.trace,d=o.t,g=p._length,v=d.r,m=d.theta,y=d.opts,x=v.slice(),b=m.slice();for(i=0;i<v.length;i++)e.isPtInside({r:v[i],theta:m[i]})||(x[i]=NaN,b[i]=NaN);var _=new Array(2*g),w=Array(g),k=Array(g);for(i=0;i<g;i++){var T,M,A=x[i];if(a(A)){var S=u.c2g(A),E=h.c2g(b[i],p.thetaunit);T=S*Math.cos(E),M=S*Math.sin(E)}else T=M=NaN;w[i]=_[2*i]=T,k[i]=_[2*i+1]=M}d.tree=n(_),y.marker&&g>=c&&(y.marker.cluster=d.tree),y.marker&&(y.markerSel.positions=y.markerUnsel.positions=y.marker.positions=_),y.line&&_.length>1&&l.extendFlat(y.line,s.linePositions(t,p,_)),y.text&&(l.extendFlat(y.text,{positions:_},s.textPosition(t,p,y.text,y.marker)),l.extendFlat(y.textSel,{positions:_},s.textPosition(t,p,y.text,y.markerSel)),l.extendFlat(y.textUnsel,{positions:_},s.textPosition(t,p,y.text,y.markerUnsel))),y.fill&&!f.fill2d&&(f.fill2d=!0),y.marker&&!f.scatter2d&&(f.scatter2d=!0),y.line&&!f.line2d&&(f.line2d=!0),y.text&&!f.glText&&(f.glText=!0),f.lineOptions.push(y.line),f.fillOptions.push(y.fill),f.markerOptions.push(y.marker),f.markerSelectedOptions.push(y.markerSel),f.markerUnselectedOptions.push(y.markerUnsel),f.textOptions.push(y.text),f.textSelectedOptions.push(y.textSel),f.textUnselectedOptions.push(y.textUnsel),f.selectBatch.push([]),f.unselectBatch.push([]),d.x=w,d.y=k,d.rawx=w,d.rawy=k,d.r=v,d.theta=m,d.positions=_,d._scene=f,d.index=f.count,f.count++}}),i(t,e,r)}}},{\"../../lib\":717,\"../scattergl/constants\":1173,\"../scattergl/convert\":1174,\"../scattergl/plot\":1181,\"../scattergl/scene_update\":1182,\"fast-isnumeric\":228,\"point-cluster\":471}],1207:[function(t,e,r){\"use strict\";var n=t(\"../../plots/template_attributes\").hovertemplateAttrs,a=t(\"../../plots/template_attributes\").texttemplateAttrs,i=t(\"../scatter/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../components/colorscale/attributes\"),l=t(\"../../components/drawing/attributes\").dash,c=t(\"../../lib/extend\").extendFlat,u=i.marker,h=i.line,f=u.line;e.exports={a:{valType:\"data_array\",editType:\"calc\"},b:{valType:\"data_array\",editType:\"calc\"},c:{valType:\"data_array\",editType:\"calc\"},sum:{valType:\"number\",dflt:0,min:0,editType:\"calc\"},mode:c({},i.mode,{dflt:\"markers\"}),text:c({},i.text,{}),texttemplate:a({editType:\"plot\"},{keys:[\"a\",\"b\",\"c\",\"text\"]}),hovertext:c({},i.hovertext,{}),line:{color:h.color,width:h.width,dash:l,shape:c({},h.shape,{values:[\"linear\",\"spline\"]}),smoothing:h.smoothing,editType:\"calc\"},connectgaps:i.connectgaps,cliponaxis:i.cliponaxis,fill:c({},i.fill,{values:[\"none\",\"toself\",\"tonext\"],dflt:\"none\"}),fillcolor:i.fillcolor,marker:c({symbol:u.symbol,opacity:u.opacity,maxdisplayed:u.maxdisplayed,size:u.size,sizeref:u.sizeref,sizemin:u.sizemin,sizemode:u.sizemode,line:c({width:f.width,editType:\"calc\"},s(\"marker.line\")),gradient:u.gradient,editType:\"calc\"},s(\"marker\")),textfont:i.textfont,textposition:i.textposition,selected:i.selected,unselected:i.unselected,hoverinfo:c({},o.hoverinfo,{flags:[\"a\",\"b\",\"c\",\"text\",\"name\"]}),hoveron:i.hoveron,hovertemplate:n()}},{\"../../components/colorscale/attributes\":599,\"../../components/drawing/attributes\":612,\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"../scatter/attributes\":1120}],1208:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),a=t(\"../scatter/colorscale_calc\"),i=t(\"../scatter/arrays_to_calcdata\"),o=t(\"../scatter/calc_selection\"),s=t(\"../scatter/calc\").calcMarkerSize,l=[\"a\",\"b\",\"c\"],c={a:[\"b\",\"c\"],b:[\"a\",\"c\"],c:[\"a\",\"b\"]};e.exports=function(t,e){var r,u,h,f,p,d,g=t._fullLayout[e.subplot].sum,v=e.sum||g,m={a:e.a,b:e.b,c:e.c};for(r=0;r<l.length;r++)if(!m[h=l[r]]){for(p=m[c[h][0]],d=m[c[h][1]],f=new Array(p.length),u=0;u<p.length;u++)f[u]=v-p[u]-d[u];m[h]=f}var y,x,b,_,w,k,T=e._length,M=new Array(T);for(r=0;r<T;r++)y=m.a[r],x=m.b[r],b=m.c[r],n(y)&&n(x)&&n(b)?(1!==(_=g/((y=+y)+(x=+x)+(b=+b)))&&(y*=_,x*=_,b*=_),k=y,w=b-x,M[r]={x:w,y:k,a:y,b:x,c:b}):M[r]={x:!1,y:!1};return s(e,T),a(t,e),i(M,e),o(M,e),M}},{\"../scatter/arrays_to_calcdata\":1119,\"../scatter/calc\":1121,\"../scatter/calc_selection\":1122,\"../scatter/colorscale_calc\":1123,\"fast-isnumeric\":228}],1209:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../scatter/constants\"),i=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/line_shape_defaults\"),c=t(\"../scatter/text_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),h=t(\"./attributes\");e.exports=function(t,e,r,f){function p(r,a){return n.coerce(t,e,h,r,a)}var d,g=p(\"a\"),v=p(\"b\"),m=p(\"c\");if(g?(d=g.length,v?(d=Math.min(d,v.length),m&&(d=Math.min(d,m.length))):d=m?Math.min(d,m.length):0):v&&m&&(d=Math.min(v.length,m.length)),d){e._length=d,p(\"sum\"),p(\"text\"),p(\"hovertext\"),\"fills\"!==e.hoveron&&p(\"hovertemplate\"),p(\"mode\",d<a.PTS_LINESONLY?\"lines+markers\":\"lines\"),i.hasLines(e)&&(s(t,e,r,f,p),l(t,e,p),p(\"connectgaps\")),i.hasMarkers(e)&&o(t,e,r,f,p,{gradient:!0}),i.hasText(e)&&(p(\"texttemplate\"),c(t,e,f,p));var y=[];(i.hasMarkers(e)||i.hasText(e))&&(p(\"cliponaxis\"),p(\"marker.maxdisplayed\"),y.push(\"points\")),p(\"fill\"),\"none\"!==e.fill&&(u(t,e,r,p),i.hasLines(e)||l(t,e,p)),\"tonext\"!==e.fill&&\"toself\"!==e.fill||y.push(\"fills\"),p(\"hoveron\",y.join(\"+\")||\"points\"),n.coerceSelectionMarkerOpacity(e,p)}else e.visible=!1}},{\"../../lib\":717,\"../scatter/constants\":1124,\"../scatter/fillcolor_defaults\":1128,\"../scatter/line_defaults\":1133,\"../scatter/line_shape_defaults\":1135,\"../scatter/marker_defaults\":1139,\"../scatter/subtypes\":1144,\"../scatter/text_defaults\":1145,\"./attributes\":1207}],1210:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,a){if(e.xa&&(t.xaxis=e.xa),e.ya&&(t.yaxis=e.ya),n[a]){var i=n[a];t.a=i.a,t.b=i.b,t.c=i.c}else t.a=e.a,t.b=e.b,t.c=e.c;return t}},{}],1211:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\");e.exports=function(t,e,r){var a={},i=r[e.subplot]._subplot;return a.aLabel=n.tickText(i.aaxis,t.a,!0).text,a.bLabel=n.tickText(i.baxis,t.b,!0).text,a.cLabel=n.tickText(i.caxis,t.c,!0).text,a}},{\"../../plots/cartesian/axes\":765}],1212:[function(t,e,r){\"use strict\";var n=t(\"../scatter/hover\");e.exports=function(t,e,r,a){var i=n(t,e,r,a);if(i&&!1!==i[0].index){var o=i[0];if(void 0===o.index){var s=1-o.y0/t.ya._length,l=t.xa._length,c=l*s/2,u=l-c;return o.x0=Math.max(Math.min(o.x0,u),c),o.x1=Math.max(Math.min(o.x1,u),c),i}var h=o.cd[o.index],f=o.trace,p=o.subplot;o.a=h.a,o.b=h.b,o.c=h.c,o.xLabelVal=void 0,o.yLabelVal=void 0;var d={};d[f.subplot]={_subplot:p};var g=f._module.formatLabels(h,f,d);o.aLabel=g.aLabel,o.bLabel=g.bLabel,o.cLabel=g.cLabel;var v=h.hi||f.hoverinfo,m=[];if(!f.hovertemplate){var y=v.split(\"+\");-1!==y.indexOf(\"all\")&&(y=[\"a\",\"b\",\"c\"]),-1!==y.indexOf(\"a\")&&x(p.aaxis,o.aLabel),-1!==y.indexOf(\"b\")&&x(p.baxis,o.bLabel),-1!==y.indexOf(\"c\")&&x(p.caxis,o.cLabel)}return o.extraText=m.join(\"<br>\"),o.hovertemplate=f.hovertemplate,i}function x(t,e){m.push(t._hovertitle+\": \"+e)}}},{\"../scatter/hover\":1131}],1213:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),colorbar:t(\"../scatter/marker_colorbar\"),formatLabels:t(\"./format_labels\"),calc:t(\"./calc\"),plot:t(\"./plot\"),style:t(\"../scatter/style\").style,styleOnSelect:t(\"../scatter/style\").styleOnSelect,hoverPoints:t(\"./hover\"),selectPoints:t(\"../scatter/select\"),eventData:t(\"./event_data\"),moduleType:\"trace\",name:\"scatterternary\",basePlotModule:t(\"../../plots/ternary\"),categories:[\"ternary\",\"symbols\",\"showLegend\",\"scatter-like\"],meta:{}}},{\"../../plots/ternary\":842,\"../scatter/marker_colorbar\":1138,\"../scatter/select\":1141,\"../scatter/style\":1143,\"./attributes\":1207,\"./calc\":1208,\"./defaults\":1209,\"./event_data\":1210,\"./format_labels\":1211,\"./hover\":1212,\"./plot\":1214}],1214:[function(t,e,r){\"use strict\";var n=t(\"../scatter/plot\");e.exports=function(t,e,r){var a=e.plotContainer;a.select(\".scatterlayer\").selectAll(\"*\").remove();var i={xaxis:e.xaxis,yaxis:e.yaxis,plot:a,layerClipId:e._hasClipOnAxisFalse?e.clipIdRelative:null},o=e.layers.frontplot.select(\"g.scatterlayer\");n(t,i,r,o)}},{\"../scatter/plot\":1140}],1215:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),a=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../scattergl/attributes\"),s=t(\"../../plots/cartesian/constants\").idRegex,l=t(\"../../plot_api/plot_template\").templatedArray,c=t(\"../../lib/extend\").extendFlat,u=n.marker,h=u.line,f=c(a(\"marker.line\",{editTypeOverride:\"calc\"}),{width:c({},h.width,{editType:\"calc\"}),editType:\"calc\"}),p=c(a(\"marker\"),{symbol:u.symbol,size:c({},u.size,{editType:\"markerSize\"}),sizeref:u.sizeref,sizemin:u.sizemin,sizemode:u.sizemode,opacity:u.opacity,colorbar:u.colorbar,line:f,editType:\"calc\"});function d(t){return{valType:\"info_array\",freeLength:!0,editType:\"calc\",items:{valType:\"subplotid\",regex:s[t],editType:\"plot\"}}}p.color.editType=p.cmin.editType=p.cmax.editType=\"style\",e.exports={dimensions:l(\"dimension\",{visible:{valType:\"boolean\",dflt:!0,editType:\"calc\"},label:{valType:\"string\",editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},axis:{type:{valType:\"enumerated\",values:[\"linear\",\"log\",\"date\",\"category\"],editType:\"calc+clearAxisTypes\"},matches:{valType:\"boolean\",dflt:!1,editType:\"calc\"},editType:\"calc+clearAxisTypes\"},editType:\"calc+clearAxisTypes\"}),text:c({},o.text,{}),hovertext:c({},o.hovertext,{}),hovertemplate:i(),marker:p,xaxes:d(\"x\"),yaxes:d(\"y\"),diagonal:{visible:{valType:\"boolean\",dflt:!0,editType:\"calc\"},editType:\"calc\"},showupperhalf:{valType:\"boolean\",dflt:!0,editType:\"calc\"},showlowerhalf:{valType:\"boolean\",dflt:!0,editType:\"calc\"},selected:{marker:o.selected.marker,editType:\"calc\"},unselected:{marker:o.unselected.marker,editType:\"calc\"},opacity:o.opacity}},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plot_api/plot_template\":755,\"../../plots/cartesian/constants\":771,\"../../plots/template_attributes\":841,\"../scatter/attributes\":1120,\"../scattergl/attributes\":1171}],1216:[function(t,e,r){\"use strict\";var n=t(\"regl-line2d\"),a=t(\"../../registry\"),i=t(\"../../lib/prepare_regl\"),o=t(\"../../plots/get_data\").getModuleCalcData,s=t(\"../../plots/cartesian\"),l=t(\"../../plots/cartesian/axis_ids\").getFromId,c=t(\"../../plots/cartesian/axes\").shouldShowZeroLine,u=\"splom\";function h(t,e,r){for(var n=r.matrixOptions.data.length,a=e._visibleDims,i=r.viewOpts.ranges=new Array(n),o=0;o<a.length;o++){var s=a[o],c=i[o]=new Array(4),u=l(t,e._diag[s][0]);u&&(c[0]=u.r2l(u.range[0]),c[2]=u.r2l(u.range[1]));var h=l(t,e._diag[s][1]);h&&(c[1]=h.r2l(h.range[0]),c[3]=h.r2l(h.range[1]))}r.selectBatch.length||r.unselectBatch.length?r.matrix.update({ranges:i},{ranges:i}):r.matrix.update({ranges:i})}function f(t){var e=t._fullLayout,r=e._glcanvas.data()[0].regl,a=e._splomGrid;a||(a=e._splomGrid=n(r)),a.update(function(t){var e,r=t._fullLayout,n=r._size,a=[0,0,r.width,r.height],i={};function o(t,e,r,n,o,s){var l=e[t+\"color\"],c=e[t+\"width\"],u=String(l+c);u in i?i[u].data.push(NaN,NaN,r,n,o,s):i[u]={data:[r,n,o,s],join:\"rect\",thickness:c,color:l,viewport:a,range:a,overlay:!1}}for(e in r._splomSubplots){var s,l,u=r._plots[e],h=u.xaxis,f=u.yaxis,p=h._gridVals,d=f._gridVals,g=n.b+f.domain[0]*n.h,v=-f._m,m=-v*f.r2l(f.range[0],f.calendar);if(h.showgrid)for(e=0;e<p.length;e++)s=h._offset+h.l2p(p[e].x),o(\"grid\",h,s,g,s,g+f._length);if(f.showgrid)for(e=0;e<d.length;e++)l=g+m+v*d[e].x,o(\"grid\",f,h._offset,l,h._offset+h._length,l);c(t,h,f)&&(s=h._offset+h.l2p(0),o(\"zeroline\",h,s,g,s,g+f._length)),c(t,f,h)&&(l=g+m+0,o(\"zeroline\",f,h._offset,l,h._offset+h._length,l))}var y=[];for(e in i)y.push(i[e]);return y}(t))}e.exports={name:u,attr:s.attr,attrRegex:s.attrRegex,layoutAttributes:s.layoutAttributes,supplyLayoutDefaults:s.supplyLayoutDefaults,drawFramework:s.drawFramework,plot:function(t){var e=t._fullLayout,r=a.getModule(u),n=o(t.calcdata,r)[0];i(t,[\"ANGLE_instanced_arrays\",\"OES_element_index_uint\"])&&(e._hasOnlyLargeSploms&&f(t),r.plot(t,{},n))},drag:function(t){var e=t.calcdata,r=t._fullLayout;r._hasOnlyLargeSploms&&f(t);for(var n=0;n<e.length;n++){var a=e[n][0].trace,i=r._splomScenes[a.uid];\"splom\"===a.type&&i&&i.matrix&&h(t,a,i)}},updateGrid:f,clean:function(t,e,r,n){var a,i={};if(n._splomScenes){for(a=0;a<t.length;a++){var o=t[a];\"splom\"===o.type&&(i[o.uid]=1)}for(a=0;a<r.length;a++){var l=r[a];if(!i[l.uid]){var c=n._splomScenes[l.uid];c&&c.destroy&&c.destroy(),n._splomScenes[l.uid]=null,delete n._splomScenes[l.uid]}}}0===Object.keys(n._splomScenes||{}).length&&delete n._splomScenes,n._splomGrid&&!e._hasOnlyLargeSploms&&n._hasOnlyLargeSploms&&(n._splomGrid.destroy(),n._splomGrid=null,delete n._splomGrid),s.clean(t,e,r,n)},updateFx:s.updateFx,toSVG:s.toSVG}},{\"../../lib/prepare_regl\":730,\"../../plots/cartesian\":776,\"../../plots/cartesian/axes\":765,\"../../plots/cartesian/axis_ids\":768,\"../../plots/get_data\":800,\"../../registry\":846,\"regl-line2d\":493}],1217:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/cartesian/axis_ids\"),i=t(\"../scatter/calc\").calcMarkerSize,o=t(\"../scatter/calc\").calcAxisExpansion,s=t(\"../scatter/colorscale_calc\"),l=t(\"../scattergl/convert\").markerSelection,c=t(\"../scattergl/convert\").markerStyle,u=t(\"./scene_update\"),h=t(\"../../constants/numerical\").BADNUM,f=t(\"../scattergl/constants\").TOO_MANY_POINTS;e.exports=function(t,e){var r,p,d,g,v,m,y=e.dimensions,x=e._length,b={},_=b.cdata=[],w=b.data=[],k=e._visibleDims=[];function T(t,r){for(var a=t.makeCalcdata({v:r.values,vcalendar:e.calendar},\"v\"),i=0;i<a.length;i++)a[i]=a[i]===h?NaN:a[i];_.push(a),w.push(\"log\"===t.type?n.simpleMap(a,t.c2l):a)}for(r=0;r<y.length;r++)if((d=y[r]).visible){if(g=a.getFromId(t,e._diag[r][0]),v=a.getFromId(t,e._diag[r][1]),g&&v&&g.type!==v.type){n.log(\"Skipping splom dimension \"+r+\" with conflicting axis types\");continue}g?(T(g,d),v&&\"category\"===v.type&&(v._categories=g._categories.slice())):T(v,d),k.push(r)}for(s(t,e),n.extendFlat(b,c(e)),m=_.length*x>f?2*(b.sizeAvg||Math.max(b.size,3)):i(e,x),p=0;p<k.length;p++)d=y[r=k[p]],g=a.getFromId(t,e._diag[r][0])||{},v=a.getFromId(t,e._diag[r][1])||{},o(t,e,g,v,_[p],_[p],m);var M=u(t,e);return M.matrix||(M.matrix=!0),M.matrixOptions=b,M.selectedOptions=l(e,e.selected),M.unselectedOptions=l(e,e.unselected),[{x:!1,y:!1,t:{},trace:e}]}},{\"../../constants/numerical\":693,\"../../lib\":717,\"../../plots/cartesian/axis_ids\":768,\"../scatter/calc\":1121,\"../scatter/colorscale_calc\":1123,\"../scattergl/constants\":1173,\"../scattergl/convert\":1174,\"./scene_update\":1224}],1218:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/array_container_defaults\"),i=t(\"./attributes\"),o=t(\"../scatter/subtypes\"),s=t(\"../scatter/marker_defaults\"),l=t(\"../parcoords/merge_length\"),c=t(\"../scattergl/helpers\").isOpenSymbol;function u(t,e){function r(r,a){return n.coerce(t,e,i.dimensions,r,a)}r(\"label\");var a=r(\"values\");a&&a.length?r(\"visible\"):e.visible=!1,r(\"axis.type\"),r(\"axis.matches\")}e.exports=function(t,e,r,h){function f(r,a){return n.coerce(t,e,i,r,a)}var p=a(t,e,{name:\"dimensions\",handleItemDefaults:u}),d=f(\"diagonal.visible\"),g=f(\"showupperhalf\"),v=f(\"showlowerhalf\");if(l(e,p,\"values\")&&(d||g||v)){f(\"text\"),f(\"hovertext\"),f(\"hovertemplate\"),s(t,e,r,h,f);var m=c(e.marker.symbol),y=o.isBubble(e);f(\"marker.line.width\",m||y?1:0),function(t,e,r,n){var a,i,o=e.dimensions,s=o.length,l=e.showupperhalf,c=e.showlowerhalf,u=e.diagonal.visible,h=new Array(s),f=new Array(s);for(a=0;a<s;a++){var p=a?a+1:\"\";h[a]=\"x\"+p,f[a]=\"y\"+p}var d=n(\"xaxes\",h),g=n(\"yaxes\",f),v=e._diag=new Array(s);e._xaxes={},e._yaxes={};var m=[],y=[];function x(t,n,a,i){if(t){var o=t.charAt(0),s=r._splomAxes[o];if(e[\"_\"+o+\"axes\"][t]=1,i.push(t),!(t in s)){var l=s[t]={};a&&(l.label=a.label||\"\",a.visible&&a.axis&&(a.axis.type&&(l.type=a.axis.type),a.axis.matches&&(l.matches=n)))}}}var b=!u&&!c,_=!u&&!l;for(e._axesDim={},a=0;a<s;a++){var w=o[a],k=0===a,T=a===s-1,M=k&&b||T&&_?void 0:d[a],A=k&&_||T&&b?void 0:g[a];x(M,A,w,m),x(A,M,w,y),v[a]=[M,A],e._axesDim[M]=a,e._axesDim[A]=a}for(a=0;a<m.length;a++)for(i=0;i<y.length;i++){var S=m[a]+y[i];a>i&&l?r._splomSubplots[S]=1:a<i&&c?r._splomSubplots[S]=1:a!==i||!u&&c&&l||(r._splomSubplots[S]=1)}(!c||!u&&l&&c)&&(r._splomGridDflt.xside=\"bottom\",r._splomGridDflt.yside=\"left\")}(0,e,h,f),n.coerceSelectionMarkerOpacity(e,f)}else e.visible=!1}},{\"../../lib\":717,\"../../plots/array_container_defaults\":761,\"../parcoords/merge_length\":1091,\"../scatter/marker_defaults\":1139,\"../scatter/subtypes\":1144,\"../scattergl/helpers\":1178,\"./attributes\":1215}],1219:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../scatter/colorscale_calc\"),i=t(\"../scattergl/convert\").markerStyle;e.exports=function(t,e){var r=e.trace,o=t._fullLayout._splomScenes[r.uid];if(o){a(t,r),n.extendFlat(o.matrixOptions,i(r));var s=n.extendFlat({},o.matrixOptions,o.viewOpts);o.matrix.update(s,null)}}},{\"../../lib\":717,\"../scatter/colorscale_calc\":1123,\"../scattergl/convert\":1174}],1220:[function(t,e,r){\"use strict\";r.getDimIndex=function(t,e){for(var r=e._id,n={x:0,y:1}[r.charAt(0)],a=t._visibleDims,i=0;i<a.length;i++){var o=a[i];if(t._diag[o][n]===r)return i}return!1}},{}],1221:[function(t,e,r){\"use strict\";var n=t(\"./helpers\"),a=t(\"../scattergl/hover\").calcHover;e.exports={hoverPoints:function(t,e,r){var i=t.cd[0].trace,o=t.scene.matrixOptions.cdata,s=t.xa,l=t.ya,c=s.c2p(e),u=l.c2p(r),h=t.distance,f=n.getDimIndex(i,s),p=n.getDimIndex(i,l);if(!1===f||!1===p)return[t];for(var d,g,v=o[f],m=o[p],y=h,x=0;x<v.length;x++){var b=v[x],_=m[x],w=s.c2p(b)-c,k=l.c2p(_)-u,T=Math.sqrt(w*w+k*k);T<y&&(y=g=T,d=x)}return t.index=d,t.distance=y,t.dxy=g,void 0===d?[t]:[a(t,v,m,i)]}}},{\"../scattergl/hover\":1179,\"./helpers\":1220}],1222:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../components/grid\");e.exports={moduleType:\"trace\",name:\"splom\",basePlotModule:t(\"./base_plot\"),categories:[\"gl\",\"regl\",\"cartesian\",\"symbols\",\"showLegend\",\"scatter-like\"],attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),colorbar:t(\"../scatter/marker_colorbar\"),calc:t(\"./calc\"),plot:t(\"./plot\"),hoverPoints:t(\"./hover\").hoverPoints,selectPoints:t(\"./select\"),editStyle:t(\"./edit_style\"),meta:{}},n.register(a)},{\"../../components/grid\":634,\"../../registry\":846,\"../scatter/marker_colorbar\":1138,\"./attributes\":1215,\"./base_plot\":1216,\"./calc\":1217,\"./defaults\":1218,\"./edit_style\":1219,\"./hover\":1221,\"./plot\":1223,\"./select\":1225}],1223:[function(t,e,r){\"use strict\";var n=t(\"regl-splom\"),a=t(\"../../lib\"),i=t(\"../../plots/cartesian/axis_ids\");function o(t,e){var r,o,s,l,c,u=t._fullLayout,h=u._size,f=e.trace,p=e.t,d=u._splomScenes[f.uid],g=d.matrixOptions,v=g.cdata,m=u._glcanvas.data()[0].regl,y=u.dragmode;if(0!==v.length){g.lower=f.showupperhalf,g.upper=f.showlowerhalf,g.diagonal=f.diagonal.visible;var x=f._visibleDims,b=v.length,_=d.viewOpts={};for(_.ranges=new Array(b),_.domains=new Array(b),c=0;c<x.length;c++){s=x[c];var w=_.ranges[c]=new Array(4),k=_.domains[c]=new Array(4);(r=i.getFromId(t,f._diag[s][0]))&&(w[0]=r._rl[0],w[2]=r._rl[1],k[0]=r.domain[0],k[2]=r.domain[1]),(o=i.getFromId(t,f._diag[s][1]))&&(w[1]=o._rl[0],w[3]=o._rl[1],k[1]=o.domain[0],k[3]=o.domain[1])}_.viewport=[h.l,h.b,h.w+h.l,h.h+h.b],!0===d.matrix&&(d.matrix=n(m));var T=u.clickmode.indexOf(\"select\")>-1,M=!0;if(\"lasso\"===y||\"select\"===y||!!f.selectedpoints||T){var A=f._length;if(f.selectedpoints){d.selectBatch=f.selectedpoints;var S=f.selectedpoints,E={};for(s=0;s<S.length;s++)E[S[s]]=!0;var L=[];for(s=0;s<A;s++)E[s]||L.push(s);d.unselectBatch=L}var C=p.xpx=new Array(b),P=p.ypx=new Array(b);for(c=0;c<x.length;c++){if(s=x[c],r=i.getFromId(t,f._diag[s][0]))for(C[c]=new Array(A),l=0;l<A;l++)C[c][l]=r.c2p(v[c][l]);if(o=i.getFromId(t,f._diag[s][1]))for(P[c]=new Array(A),l=0;l<A;l++)P[c][l]=o.c2p(v[c][l])}if(d.selectBatch.length||d.unselectBatch.length){var O=a.extendFlat({},g,d.unselectedOptions,_),z=a.extendFlat({},g,d.selectedOptions,_);d.matrix.update(O,z),M=!1}}else p.xpx=p.ypx=null;if(M){var I=a.extendFlat({},g,_);d.matrix.update(I,null)}}}e.exports=function(t,e,r){if(r.length)for(var n=0;n<r.length;n++)o(t,r[n][0])}},{\"../../lib\":717,\"../../plots/cartesian/axis_ids\":768,\"regl-splom\":500}],1224:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){var r=t._fullLayout,a=e.uid,i=r._splomScenes;i||(i=r._splomScenes={});var o={dirty:!0},s=i[e.uid];return s||((s=i[a]=n.extendFlat({},o,{matrix:!1,selectBatch:[],unselectBatch:[]})).draw=function(){s.matrix&&s.matrix.draw&&(s.selectBatch.length||s.unselectBatch.length?s.matrix.draw(s.unselectBatch,s.selectBatch):s.matrix.draw()),s.dirty=!1},s.destroy=function(){s.matrix&&s.matrix.destroy&&s.matrix.destroy(),s.matrixOptions=null,s.selectBatch=null,s.unselectBatch=null,s=null}),s.dirty||n.extendFlat(s,o),s}},{\"../../lib\":717}],1225:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),i=t(\"./helpers\");e.exports=function(t,e){var r=t.cd,o=r[0].trace,s=r[0].t,l=t.scene,c=l.matrixOptions.cdata,u=t.xaxis,h=t.yaxis,f=[];if(!l)return f;var p=!a.hasMarkers(o)&&!a.hasText(o);if(!0!==o.visible||p)return f;var d=i.getDimIndex(o,u),g=i.getDimIndex(o,h);if(!1===d||!1===g)return f;var v=s.xpx[d],m=s.ypx[g],y=c[d],x=c[g],b=[],_=[];if(!1!==e&&!e.degenerate)for(var w=0;w<y.length;w++)e.contains([v[w],m[w]],null,w,t)?(b.push(w),f.push({pointNumber:w,x:y[w],y:x[w]})):_.push(w);var k=l.matrixOptions;return b.length||_.length?l.selectBatch.length||l.unselectBatch.length||l.matrix.update(l.unselectedOptions,n.extendFlat({},k,l.selectedOptions,l.viewOpts)):l.matrix.update(k,null),l.selectBatch=b,l.unselectBatch=_,f}},{\"../../lib\":717,\"../scatter/subtypes\":1144,\"./helpers\":1220}],1226:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/attributes\"),a=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../mesh3d/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../lib/extend\").extendFlat,l={x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},u:{valType:\"data_array\",editType:\"calc\"},v:{valType:\"data_array\",editType:\"calc\"},w:{valType:\"data_array\",editType:\"calc\"},starts:{x:{valType:\"data_array\",editType:\"calc\"},y:{valType:\"data_array\",editType:\"calc\"},z:{valType:\"data_array\",editType:\"calc\"},editType:\"calc\"},maxdisplayed:{valType:\"integer\",min:0,dflt:1e3,editType:\"calc\"},sizeref:{valType:\"number\",editType:\"calc\",min:0,dflt:1},text:{valType:\"string\",dflt:\"\",editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",editType:\"calc\"},hovertemplate:a({editType:\"calc\"},{keys:[\"tubex\",\"tubey\",\"tubez\",\"tubeu\",\"tubev\",\"tubew\",\"norm\",\"divergence\"]}),showlegend:s({},o.showlegend,{dflt:!1})};s(l,n(\"\",{colorAttr:\"u/v/w norm\",showScaleDflt:!0,editTypeOverride:\"calc\"}));[\"opacity\",\"lightposition\",\"lighting\"].forEach(function(t){l[t]=i[t]}),l.hoverinfo=s({},o.hoverinfo,{editType:\"calc\",flags:[\"x\",\"y\",\"z\",\"u\",\"v\",\"w\",\"norm\",\"divergence\",\"text\",\"name\"],dflt:\"x+y+z+norm+text+name\"}),l.transforms=void 0,e.exports=l},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"../mesh3d/attributes\":1061}],1227:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/colorscale/calc\");function i(t){var e,r,a,i,s,l,c,u,h,f,p,d,g=t._x,v=t._y,m=t._z,y=t._len,x=-1/0,b=1/0,_=-1/0,w=1/0,k=-1/0,T=1/0,M=\"\";for(y&&(c=g[0],h=v[0],p=m[0]),y>1&&(u=g[y-1],f=v[y-1],d=m[y-1]),e=0;e<y;e++)x=Math.max(x,g[e]),b=Math.min(b,g[e]),_=Math.max(_,v[e]),w=Math.min(w,v[e]),k=Math.max(k,m[e]),T=Math.min(T,m[e]),i||g[e]===c||(i=!0,M+=\"x\"),s||v[e]===h||(s=!0,M+=\"y\"),l||m[e]===p||(l=!0,M+=\"z\");i||(M+=\"x\"),s||(M+=\"y\"),l||(M+=\"z\");var A=o(t._x),S=o(t._y),E=o(t._z);M=(M=(M=M.replace(\"x\",(c>u?\"-\":\"+\")+\"x\")).replace(\"y\",(h>f?\"-\":\"+\")+\"y\")).replace(\"z\",(p>d?\"-\":\"+\")+\"z\");var L=function(){y=0,A=[],S=[],E=[]};(!y||y<A.length*S.length*E.length)&&L();var C=function(t){return\"x\"===t?g:\"y\"===t?v:m},P=function(t){return\"x\"===t?A:\"y\"===t?S:E},O=function(t){return t[y-1]<t[0]?-1:1},z=C(M[1]),I=C(M[3]),D=C(M[5]),R=P(M[1]).length,F=P(M[3]).length,B=P(M[5]).length,N=!1,j=function(t,e,r){return R*(F*t+e)+r},V=O(C(M[1])),U=O(C(M[3])),q=O(C(M[5]));for(e=0;e<B-1;e++){for(r=0;r<F-1;r++){for(a=0;a<R-1;a++){var H=j(e,r,a),G=j(e,r,a+1),Y=j(e,r+1,a),W=j(e+1,r,a);if(z[H]*V<z[G]*V&&I[H]*U<I[Y]*U&&D[H]*q<D[W]*q||(N=!0),N)break}if(N)break}if(N)break}return N&&(n.warn(\"Encountered arbitrary coordinates! Unable to input data grid.\"),L()),{xMin:b,yMin:w,zMin:T,xMax:x,yMax:_,zMax:k,Xs:A,Ys:S,Zs:E,len:y,fill:M}}function o(t){return n.distinctVals(t).vals}function s(t,e){if(void 0===e&&(e=t.length),n.isTypedArray(t))return t.subarray(0,e);for(var r=[],a=0;a<e;a++)r[a]=+t[a];return r}e.exports={calc:function(t,e){e._len=Math.min(e.u.length,e.v.length,e.w.length,e.x.length,e.y.length,e.z.length),e._u=s(e.u,e._len),e._v=s(e.v,e._len),e._w=s(e.w,e._len),e._x=s(e.x,e._len),e._y=s(e.y,e._len),e._z=s(e.z,e._len);var r=i(e);e._gridFill=r.fill,e._Xs=r.Xs,e._Ys=r.Ys,e._Zs=r.Zs,e._len=r.len;var n,o,l,c=0;e.starts&&(n=s(e.starts.x||[]),o=s(e.starts.y||[]),l=s(e.starts.z||[]),c=Math.min(n.length,o.length,l.length)),e._startsX=n||[],e._startsY=o||[],e._startsZ=l||[];var u,h=0,f=1/0;for(u=0;u<e._len;u++){var p=e._u[u],d=e._v[u],g=e._w[u],v=Math.sqrt(p*p+d*d+g*g);h=Math.max(h,v),f=Math.min(f,v)}for(a(t,e,{vals:[f,h],containerStr:\"\",cLetter:\"c\"}),u=0;u<c;u++){var m=n[u];r.xMax=Math.max(r.xMax,m),r.xMin=Math.min(r.xMin,m);var y=o[u];r.yMax=Math.max(r.yMax,y),r.yMin=Math.min(r.yMin,y);var x=l[u];r.zMax=Math.max(r.zMax,x),r.zMin=Math.min(r.zMin,x)}e._slen=c,e._normMax=h,e._xbnds=[r.xMin,r.xMax],e._ybnds=[r.yMin,r.yMax],e._zbnds=[r.zMin,r.zMax]},filter:s,processGrid:i}},{\"../../components/colorscale/calc\":600,\"../../lib\":717}],1228:[function(t,e,r){\"use strict\";var n=t(\"gl-streamtube3d\"),a=n.createTubeMesh,i=t(\"../../lib\"),o=t(\"../../lib/gl_format_color\").parseColorScale,s=t(\"../../components/colorscale\").extractOpts,l=t(\"../../plots/gl3d/zip3\"),c={xaxis:0,yaxis:1,zaxis:2};function u(t,e){this.scene=t,this.uid=e,this.mesh=null,this.data=null}var h=u.prototype;function f(t){var e=t.length;return e>2?t.slice(1,e-1):2===e?[(t[0]+t[1])/2]:t}function p(t){var e=t.length;return 1===e?[.5,.5]:[t[1]-t[0],t[e-1]-t[e-2]]}function d(t,e){var r=t.fullSceneLayout,a=t.dataScale,u=e._len,h={};function d(t,e){var n=r[e],o=a[c[e]];return i.simpleMap(t,function(t){return n.d2l(t)*o})}if(h.vectors=l(d(e._u,\"xaxis\"),d(e._v,\"yaxis\"),d(e._w,\"zaxis\"),u),!u)return{positions:[],cells:[]};var g=d(e._Xs,\"xaxis\"),v=d(e._Ys,\"yaxis\"),m=d(e._Zs,\"zaxis\");if(h.meshgrid=[g,v,m],h.gridFill=e._gridFill,e._slen)h.startingPositions=l(d(e._startsX,\"xaxis\"),d(e._startsY,\"yaxis\"),d(e._startsZ,\"zaxis\"));else{for(var y=v[0],x=f(g),b=f(m),_=new Array(x.length*b.length),w=0,k=0;k<x.length;k++)for(var T=0;T<b.length;T++)_[w++]=[x[k],y,b[T]];h.startingPositions=_}h.colormap=o(e),h.tubeSize=e.sizeref,h.maxLength=e.maxdisplayed;var M=d(e._xbnds,\"xaxis\"),A=d(e._ybnds,\"yaxis\"),S=d(e._zbnds,\"zaxis\"),E=p(g),L=p(v),C=p(m),P=[[M[0]-E[0],A[0]-L[0],S[0]-C[0]],[M[1]+E[1],A[1]+L[1],S[1]+C[1]]],O=n(h,P),z=s(e);O.vertexIntensityBounds=[z.min/e._normMax,z.max/e._normMax];var I=e.lightposition;return O.lightPosition=[I.x,I.y,I.z],O.ambient=e.lighting.ambient,O.diffuse=e.lighting.diffuse,O.specular=e.lighting.specular,O.roughness=e.lighting.roughness,O.fresnel=e.lighting.fresnel,O.opacity=e.opacity,e._pad=O.tubeScale*e.sizeref*2,O}h.handlePick=function(t){var e=this.scene.fullSceneLayout,r=this.scene.dataScale;function n(t,n){var a=e[n],i=r[c[n]];return a.l2c(t)/i}if(t.object===this.mesh){var a=t.data.position,i=t.data.velocity;return t.traceCoordinate=[n(a[0],\"xaxis\"),n(a[1],\"yaxis\"),n(a[2],\"zaxis\"),n(i[0],\"xaxis\"),n(i[1],\"yaxis\"),n(i[2],\"zaxis\"),t.data.intensity*this.data._normMax,t.data.divergence],t.textLabel=this.data.hovertext||this.data.text,!0}},h.update=function(t){this.data=t;var e=d(this.scene,t);this.mesh.update(e)},h.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()},e.exports=function(t,e){var r=t.glplot.gl,n=d(t,e),i=a(r,n),o=new u(t,e.uid);return o.mesh=i,o.data=e,i._trace=o,t.glplot.add(i),o}},{\"../../components/colorscale\":604,\"../../lib\":717,\"../../lib/gl_format_color\":714,\"../../plots/gl3d/zip3\":816,\"gl-streamtube3d\":315}],1229:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/colorscale/defaults\"),i=t(\"./attributes\");e.exports=function(t,e,r,o){function s(r,a){return n.coerce(t,e,i,r,a)}var l=s(\"u\"),c=s(\"v\"),u=s(\"w\"),h=s(\"x\"),f=s(\"y\"),p=s(\"z\");l&&l.length&&c&&c.length&&u&&u.length&&h&&h.length&&f&&f.length&&p&&p.length?(s(\"starts.x\"),s(\"starts.y\"),s(\"starts.z\"),s(\"maxdisplayed\"),s(\"sizeref\"),s(\"lighting.ambient\"),s(\"lighting.diffuse\"),s(\"lighting.specular\"),s(\"lighting.roughness\"),s(\"lighting.fresnel\"),s(\"lightposition.x\"),s(\"lightposition.y\"),s(\"lightposition.z\"),a(t,e,o,s,{prefix:\"\",cLetter:\"c\"}),s(\"text\"),s(\"hovertext\"),s(\"hovertemplate\"),e._length=null):e.visible=!1}},{\"../../components/colorscale/defaults\":602,\"../../lib\":717,\"./attributes\":1226}],1230:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"streamtube\",basePlotModule:t(\"../../plots/gl3d\"),categories:[\"gl3d\",\"showLegend\"],attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),colorbar:{min:\"cmin\",max:\"cmax\"},calc:t(\"./calc\").calc,plot:t(\"./convert\"),eventData:function(t,e){return t.tubex=t.x,t.tubey=t.y,t.tubez=t.z,t.tubeu=e.traceCoordinate[3],t.tubev=e.traceCoordinate[4],t.tubew=e.traceCoordinate[5],t.norm=e.traceCoordinate[6],t.divergence=e.traceCoordinate[7],delete t.x,delete t.y,delete t.z,t},meta:{}}},{\"../../plots/gl3d\":805,\"./attributes\":1226,\"./calc\":1227,\"./convert\":1228,\"./defaults\":1229}],1231:[function(t,e,r){\"use strict\";var n=t(\"../../plots/attributes\"),a=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,o=t(\"../../components/colorscale/attributes\"),s=t(\"../../plots/domain\").attributes,l=t(\"../pie/attributes\"),c=t(\"./constants\"),u=t(\"../../lib/extend\").extendFlat;e.exports={labels:{valType:\"data_array\",editType:\"calc\"},parents:{valType:\"data_array\",editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},branchvalues:{valType:\"enumerated\",values:[\"remainder\",\"total\"],dflt:\"remainder\",editType:\"calc\"},count:{valType:\"flaglist\",flags:[\"branches\",\"leaves\"],dflt:\"leaves\",editType:\"calc\"},level:{valType:\"any\",editType:\"plot\",anim:!0},maxdepth:{valType:\"integer\",editType:\"plot\",dflt:-1},marker:u({colors:{valType:\"data_array\",editType:\"calc\"},line:{color:u({},l.marker.line.color,{dflt:null}),width:u({},l.marker.line.width,{dflt:1}),editType:\"calc\"},editType:\"calc\"},o(\"marker\",{colorAttr:\"colors\",anim:!1})),leaf:{opacity:{valType:\"number\",editType:\"style\",min:0,max:1},editType:\"plot\"},text:l.text,textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"current path\",\"percent root\",\"percent entry\",\"percent parent\"],extras:[\"none\"],editType:\"plot\"},texttemplate:i({editType:\"plot\"},{keys:c.eventDataKeys.concat([\"label\",\"value\"])}),hovertext:l.hovertext,hoverinfo:u({},n.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"name\",\"current path\",\"percent root\",\"percent entry\",\"percent parent\"],dflt:\"label+text+value+name\"}),hovertemplate:a({},{keys:c.eventDataKeys}),textfont:l.textfont,insidetextorientation:l.insidetextorientation,insidetextfont:l.insidetextfont,outsidetextfont:u({},l.outsidetextfont,{}),domain:s({name:\"sunburst\",trace:!0,editType:\"calc\"})}},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/domain\":790,\"../../plots/template_attributes\":841,\"../pie/attributes\":1094,\"./constants\":1234}],1232:[function(t,e,r){\"use strict\";var n=t(\"../../plots/plots\");r.name=\"sunburst\",r.plot=function(t,e,a,i){n.plotBasePlot(r.name,t,e,a,i)},r.clean=function(t,e,a,i){n.cleanBasePlot(r.name,t,e,a,i)}},{\"../../plots/plots\":826}],1233:[function(t,e,r){\"use strict\";var n=t(\"d3-hierarchy\"),a=t(\"fast-isnumeric\"),i=t(\"../../lib\"),o=t(\"../../components/colorscale\").makeColorScaleFuncFromTrace,s=t(\"../pie/calc\").makePullColorFn,l=t(\"../pie/calc\").generateExtendedColors,c=t(\"../../components/colorscale\").calc,u=t(\"../../constants/numerical\").ALMOST_EQUAL,h={},f={};r.calc=function(t,e){var r,l,h,f,p,d,g=t._fullLayout,v=e.ids,m=i.isArrayOrTypedArray(v),y=e.labels,x=e.parents,b=e.values,_=i.isArrayOrTypedArray(b),w=[],k={},T={},M=function(t){return t||\"number\"==typeof t},A=function(t){return!_||a(b[t])&&b[t]>=0};m?(r=Math.min(v.length,x.length),l=function(t){return M(v[t])&&A(t)},h=function(t){return String(v[t])}):(r=Math.min(y.length,x.length),l=function(t){return M(y[t])&&A(t)},h=function(t){return String(y[t])}),_&&(r=Math.min(r,b.length));for(var S=0;S<r;S++)if(l(S)){var E=h(S),L=M(x[S])?String(x[S]):\"\",C={i:S,id:E,pid:L,label:M(y[S])?String(y[S]):\"\"};_&&(C.v=+b[S]),w.push(C),p=E,k[f=L]?k[f].push(p):k[f]=[p],T[p]=1}if(k[\"\"]){if(k[\"\"].length>1){for(var P=i.randstr(),O=0;O<w.length;O++)\"\"===w[O].pid&&(w[O].pid=P);w.unshift({hasMultipleRoots:!0,id:P,pid:\"\",label:\"\"})}}else{var z,I=[];for(z in k)T[z]||I.push(z);if(1!==I.length)return i.warn(\"Multiple implied roots, cannot build \"+e.type+\" hierarchy.\");z=I[0],w.unshift({hasImpliedRoot:!0,id:z,pid:\"\",label:z})}try{d=n.stratify().id(function(t){return t.id}).parentId(function(t){return t.pid})(w)}catch(t){return i.warn(\"Failed to build \"+e.type+\" hierarchy. Error: \"+t.message)}var D=n.hierarchy(d),R=!1;if(_)switch(e.branchvalues){case\"remainder\":D.sum(function(t){return t.data.v});break;case\"total\":D.each(function(t){var e=t.data.data,r=e.v;if(t.children){var n=t.children.reduce(function(t,e){return t+e.data.data.v},0);if((e.hasImpliedRoot||e.hasMultipleRoots)&&(r=n),r<n*u)return R=!0,i.warn([\"Total value for node\",t.data.data.id,\"is smaller than the sum of its children.\",\"\\nparent value =\",r,\"\\nchildren sum =\",n].join(\" \"))}t.value=r})}else!function t(e,r,n){var a=0;var i=e.children;if(i){for(var o=i.length,s=0;s<o;s++)a+=t(i[s],r,n);n.branches&&a++}else n.leaves&&a++;e.value=e.data.data.value=a;r._values||(r._values=[]);r._values[e.data.data.i]=a;return a}(D,e,{branches:-1!==e.count.indexOf(\"branches\"),leaves:-1!==e.count.indexOf(\"leaves\")});if(!R){var F,B;D.sort(function(t,e){return e.value-t.value});var N=e.marker.colors||[],j=!!N.length;return e._hasColorscale?(j||(N=_?e.values:e._values),c(t,e,{vals:N,containerStr:\"marker\",cLetter:\"c\"}),B=o(e.marker)):F=s(g[\"_\"+e.type+\"colormap\"]),D.each(function(t){var r=t.data.data;r.color=e._hasColorscale?B(N[r.i]):F(N[r.i],r.id)}),w[0].hierarchy=D,w}},r._runCrossTraceCalc=function(t,e){var r=e._fullLayout,n=e.calcdata,a=r[t+\"colorway\"],i=r[\"_\"+t+\"colormap\"];r[\"extend\"+t+\"colors\"]&&(a=l(a,\"treemap\"===t?f:h));var o=0;function s(t){var e=t.data.data,r=e.id;!1===e.color&&(i[r]?e.color=i[r]:t.parent?t.parent.parent?e.color=t.parent.data.data.color:(i[r]=e.color=a[o%a.length],o++):e.color=\"rgba(0,0,0,0)\")}for(var c=0;c<n.length;c++){var u=n[c][0];u.trace.type===t&&u.hierarchy&&u.hierarchy.each(s)}},r.crossTraceCalc=function(t){return r._runCrossTraceCalc(\"sunburst\",t)}},{\"../../components/colorscale\":604,\"../../constants/numerical\":693,\"../../lib\":717,\"../pie/calc\":1096,\"d3-hierarchy\":159,\"fast-isnumeric\":228}],1234:[function(t,e,r){\"use strict\";e.exports={CLICK_TRANSITION_TIME:750,CLICK_TRANSITION_EASING:\"linear\",eventDataKeys:[\"currentPath\",\"root\",\"entry\",\"percentRoot\",\"percentEntry\",\"percentParent\"]}},{}],1235:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./attributes\"),i=t(\"../../plots/domain\").defaults,o=t(\"../bar/defaults\").handleText,s=t(\"../../components/colorscale\"),l=s.hasColorscale,c=s.handleDefaults;e.exports=function(t,e,r,s){function u(r,i){return n.coerce(t,e,a,r,i)}var h=u(\"labels\"),f=u(\"parents\");if(h&&h.length&&f&&f.length){var p=u(\"values\");p&&p.length?u(\"branchvalues\"):u(\"count\"),u(\"level\"),u(\"maxdepth\"),u(\"marker.line.width\")&&u(\"marker.line.color\",s.paper_bgcolor),u(\"marker.colors\");var d=e._hasColorscale=l(t,\"marker\",\"colors\")||(t.marker||{}).coloraxis;d&&c(t,e,s,u,{prefix:\"marker.\",cLetter:\"c\"}),u(\"leaf.opacity\",d?1:.7);var g=u(\"text\");u(\"texttemplate\"),e.texttemplate||u(\"textinfo\",Array.isArray(g)?\"text+label\":\"label\"),u(\"hovertext\"),u(\"hovertemplate\");o(t,e,s,u,\"auto\",{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),u(\"insidetextorientation\"),i(e,s,u),e._length=null}else e.visible=!1}},{\"../../components/colorscale\":604,\"../../lib\":717,\"../../plots/domain\":790,\"../bar/defaults\":860,\"./attributes\":1231}],1236:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../registry\"),i=t(\"../../components/fx/helpers\").appendArrayPointValue,o=t(\"../../components/fx\"),s=t(\"../../lib\"),l=t(\"../../lib/events\"),c=t(\"./helpers\"),u=t(\"../pie/helpers\").formatPieValue;function h(t,e,r){for(var n=t.data.data,a={curveNumber:e.index,pointNumber:n.i,data:e._input,fullData:e},o=0;o<r.length;o++){var s=r[o];s in t&&(a[s]=t[s])}return\"parentString\"in t&&!c.isHierarchyRoot(t)&&(a.parent=t.parentString),i(a,e,n.i),a}e.exports=function(t,e,r,i,f){var p=i[0],d=p.trace,g=p.hierarchy,v=\"sunburst\"===d.type,m=\"treemap\"===d.type;\"_hasHoverLabel\"in d||(d._hasHoverLabel=!1),\"_hasHoverEvent\"in d||(d._hasHoverEvent=!1);t.on(\"mouseover\",function(a){var i=r._fullLayout;if(!r._dragging&&!1!==i.hovermode){var l=r._fullData[d.index],y=a.data.data,x=y.i,b=c.isHierarchyRoot(a),_=c.getParent(g,a),w=c.getValue(a),k=function(t){return s.castOption(l,x,t)},T=k(\"hovertemplate\"),M=o.castHoverinfo(l,i,x),A=i.separators;if(T||M&&\"none\"!==M&&\"skip\"!==M){var S,E;v&&(S=p.cx+a.pxmid[0]*(1-a.rInscribed),E=p.cy+a.pxmid[1]*(1-a.rInscribed)),m&&(S=a._hoverX,E=a._hoverY);var L,C={},P=[],O=[],z=function(t){return-1!==P.indexOf(t)};M&&(P=\"all\"===M?l._module.attributes.hoverinfo.flags:M.split(\"+\")),C.label=y.label,z(\"label\")&&C.label&&O.push(C.label),y.hasOwnProperty(\"v\")&&(C.value=y.v,C.valueLabel=u(C.value,A),z(\"value\")&&O.push(C.valueLabel)),C.currentPath=a.currentPath=c.getPath(a.data),z(\"current path\")&&!b&&O.push(C.currentPath);var I=[],D=function(){-1===I.indexOf(L)&&(O.push(L),I.push(L))};C.percentParent=a.percentParent=w/c.getValue(_),C.parent=a.parentString=c.getPtLabel(_),z(\"percent parent\")&&(L=c.formatPercent(C.percentParent,A)+\" of \"+C.parent,D()),C.percentEntry=a.percentEntry=w/c.getValue(e),C.entry=a.entry=c.getPtLabel(e),!z(\"percent entry\")||b||a.onPathbar||(L=c.formatPercent(C.percentEntry,A)+\" of \"+C.entry,D()),C.percentRoot=a.percentRoot=w/c.getValue(g),C.root=a.root=c.getPtLabel(g),z(\"percent root\")&&!b&&(L=c.formatPercent(C.percentRoot,A)+\" of \"+C.root,D()),C.text=k(\"hovertext\")||k(\"text\"),z(\"text\")&&(L=C.text,s.isValidTextValue(L)&&O.push(L));var R={trace:l,y:E,text:O.join(\"<br>\"),name:T||z(\"name\")?l.name:void 0,color:k(\"hoverlabel.bgcolor\")||y.color,borderColor:k(\"hoverlabel.bordercolor\"),fontFamily:k(\"hoverlabel.font.family\"),fontSize:k(\"hoverlabel.font.size\"),fontColor:k(\"hoverlabel.font.color\"),nameLength:k(\"hoverlabel.namelength\"),textAlign:k(\"hoverlabel.align\"),hovertemplate:T,hovertemplateLabels:C,eventData:[h(a,l,f.eventDataKeys)]};v&&(R.x0=S-a.rInscribed*a.rpx1,R.x1=S+a.rInscribed*a.rpx1,R.idealAlign=a.pxmid[0]<0?\"left\":\"right\"),m&&(R.x=S,R.idealAlign=S<0?\"left\":\"right\"),o.loneHover(R,{container:i._hoverlayer.node(),outerContainer:i._paper.node(),gd:r}),d._hasHoverLabel=!0}if(m){var F=t.select(\"path.surface\");f.styleOne(F,a,l,{hovered:!0})}d._hasHoverEvent=!0,r.emit(\"plotly_hover\",{points:[h(a,l,f.eventDataKeys)],event:n.event})}}),t.on(\"mouseout\",function(e){var a=r._fullLayout,i=r._fullData[d.index],s=n.select(this).datum();if(d._hasHoverEvent&&(e.originalEvent=n.event,r.emit(\"plotly_unhover\",{points:[h(s,i,f.eventDataKeys)],event:n.event}),d._hasHoverEvent=!1),d._hasHoverLabel&&(o.loneUnhover(a._hoverlayer.node()),d._hasHoverLabel=!1),m){var l=t.select(\"path.surface\");f.styleOne(l,s,i,{hovered:!1})}}),t.on(\"click\",function(t){var e=r._fullLayout,i=r._fullData[d.index],s=v&&(c.isHierarchyRoot(t)||c.isLeaf(t)),u=c.getPtId(t),p=c.isEntry(t)?c.findEntryWithChild(g,u):c.findEntryWithLevel(g,u),m=c.getPtId(p),y={points:[h(t,i,f.eventDataKeys)],event:n.event};s||(y.nextLevel=m);var x=l.triggerHandler(r,\"plotly_\"+d.type+\"click\",y);if(!1!==x&&e.hovermode&&(r._hoverdata=[h(t,i,f.eventDataKeys)],o.click(r,n.event)),!s&&!1!==x&&!r._dragging&&!r._transitioning){a.call(\"_storeDirectGUIEdit\",i,e._tracePreGUI[i.uid],{level:i.level});var b={data:[{level:m}],traces:[d.index]},_={frame:{redraw:!1,duration:f.transitionTime},transition:{duration:f.transitionTime,easing:f.transitionEasing},mode:\"immediate\",fromcurrent:!0};o.loneUnhover(e._hoverlayer.node()),a.call(\"animate\",r,b,_)}})}},{\"../../components/fx\":630,\"../../components/fx/helpers\":627,\"../../lib\":717,\"../../lib/events\":707,\"../../registry\":846,\"../pie/helpers\":1099,\"./helpers\":1237,d3:165}],1237:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/color\"),i=t(\"../../lib/setcursor\"),o=t(\"../pie/helpers\");function s(t){return t.data.data.pid}r.findEntryWithLevel=function(t,e){var n;return e&&t.eachAfter(function(t){if(r.getPtId(t)===e)return n=t.copy()}),n||t},r.findEntryWithChild=function(t,e){var n;return t.eachAfter(function(t){for(var a=t.children||[],i=0;i<a.length;i++){var o=a[i];if(r.getPtId(o)===e)return n=t.copy()}}),n||t},r.isEntry=function(t){return!t.parent},r.isLeaf=function(t){return!t.children},r.getPtId=function(t){return t.data.data.id},r.getPtLabel=function(t){return t.data.data.label},r.getValue=function(t){return t.value},r.isHierarchyRoot=function(t){return\"\"===s(t)},r.setSliceCursor=function(t,e,n){var a=n.isTransitioning;if(!a){var o=t.datum();a=n.hideOnRoot&&r.isHierarchyRoot(o)||n.hideOnLeaves&&r.isLeaf(o)}i(t,a?null:\"pointer\")},r.getInsideTextFontKey=function(t,e,r,a,i){var o=(i||{}).onPathbar?\"pathbar.textfont\":\"insidetextfont\",s=r.data.data.i;return n.castOption(e,s,o+\".\"+t)||n.castOption(e,s,\"textfont.\"+t)||a.size},r.getOutsideTextFontKey=function(t,e,r,a){var i=r.data.data.i;return n.castOption(e,i,\"outsidetextfont.\"+t)||n.castOption(e,i,\"textfont.\"+t)||a.size},r.isOutsideText=function(t,e){return!t._hasColorscale&&r.isHierarchyRoot(e)},r.determineTextFont=function(t,e,i,o){return r.isOutsideText(t,e)?function(t,e,n){return{color:r.getOutsideTextFontKey(\"color\",t,e,n),family:r.getOutsideTextFontKey(\"family\",t,e,n),size:r.getOutsideTextFontKey(\"size\",t,e,n)}}(t,e,i):function(t,e,i,o){var s=(o||{}).onPathbar,l=e.data.data,c=l.i,u=n.castOption(t,c,(s?\"pathbar.textfont\":\"insidetextfont\")+\".color\");return!u&&t._input.textfont&&(u=n.castOption(t._input,c,\"textfont.color\")),{color:u||a.contrast(l.color),family:r.getInsideTextFontKey(\"family\",t,e,i,o),size:r.getInsideTextFontKey(\"size\",t,e,i,o)}}(t,e,i,o)},r.hasTransition=function(t){return!!(t&&t.duration>0)},r.getMaxDepth=function(t){return t.maxdepth>=0?t.maxdepth:1/0},r.isHeader=function(t,e){return!(r.isLeaf(t)||t.depth===e._maxDepth-1)},r.getParent=function(t,e){return r.findEntryWithLevel(t,s(e))},r.listPath=function(t,e){var n=t.parent;if(!n)return[];var a=e?[n.data[e]]:[n];return r.listPath(n,e).concat(a)},r.getPath=function(t){return r.listPath(t,\"label\").join(\"/\")+\"/\"},r.formatValue=o.formatPieValue,r.formatPercent=function(t,e){var r=n.formatPercent(t,0);return\"0%\"===r&&(r=o.formatPiePercent(t,e)),r}},{\"../../components/color\":592,\"../../lib\":717,\"../../lib/setcursor\":737,\"../pie/helpers\":1099}],1238:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"sunburst\",basePlotModule:t(\"./base_plot\"),categories:[],animatable:!0,attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyDefaults:t(\"./defaults\"),supplyLayoutDefaults:t(\"./layout_defaults\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\").plot,style:t(\"./style\").style,colorbar:t(\"../scatter/marker_colorbar\"),meta:{}}},{\"../scatter/marker_colorbar\":1138,\"./attributes\":1231,\"./base_plot\":1232,\"./calc\":1233,\"./defaults\":1235,\"./layout_attributes\":1239,\"./layout_defaults\":1240,\"./plot\":1241,\"./style\":1242}],1239:[function(t,e,r){\"use strict\";e.exports={sunburstcolorway:{valType:\"colorlist\",editType:\"calc\"},extendsunburstcolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{}],1240:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,i){return n.coerce(t,e,a,r,i)}r(\"sunburstcolorway\",e.colorway),r(\"extendsunburstcolors\")}},{\"../../lib\":717,\"./layout_attributes\":1239}],1241:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"d3-hierarchy\"),i=t(\"../../components/drawing\"),o=t(\"../../lib\"),s=t(\"../../lib/svg_text_utils\"),l=t(\"../bar/uniform_text\"),c=l.recordMinTextSize,u=l.clearMinTextSize,h=t(\"../pie/plot\"),f=h.computeTransform,p=h.transformInsideText,d=t(\"./style\").styleOne,g=t(\"../bar/style\").resizeText,v=t(\"./fx\"),m=t(\"./constants\"),y=t(\"./helpers\");function x(t,e,l,u){var h=t._fullLayout,g=!h.uniformtext.mode&&y.hasTransition(u),x=n.select(l).selectAll(\"g.slice\"),_=e[0],w=_.trace,k=_.hierarchy,T=y.findEntryWithLevel(k,w.level),M=y.getMaxDepth(w),A=h._size,S=w.domain,E=A.w*(S.x[1]-S.x[0]),L=A.h*(S.y[1]-S.y[0]),C=.5*Math.min(E,L),P=_.cx=A.l+A.w*(S.x[1]+S.x[0])/2,O=_.cy=A.t+A.h*(1-S.y[0])-L/2;if(!T)return x.remove();var z=null,I={};g&&x.each(function(t){I[y.getPtId(t)]={rpx0:t.rpx0,rpx1:t.rpx1,x0:t.x0,x1:t.x1,transform:t.transform},!z&&y.isEntry(t)&&(z=t)});var D=function(t){return a.partition().size([2*Math.PI,t.height+1])(t)}(T).descendants(),R=T.height+1,F=0,B=M;_.hasMultipleRoots&&y.isHierarchyRoot(T)&&(D=D.slice(1),R-=1,F=1,B+=1),D=D.filter(function(t){return t.y1<=B});var N=Math.min(R,M),j=function(t){return(t-F)/N*C},V=function(t,e){return[t*Math.cos(e),-t*Math.sin(e)]},U=function(t){return o.pathAnnulus(t.rpx0,t.rpx1,t.x0,t.x1,P,O)},q=function(t){return P+b(t)[0]*(t.transform.rCenter||0)+(t.transform.x||0)},H=function(t){return O+b(t)[1]*(t.transform.rCenter||0)+(t.transform.y||0)};(x=x.data(D,y.getPtId)).enter().append(\"g\").classed(\"slice\",!0),g?x.exit().transition().each(function(){var t=n.select(this);t.select(\"path.surface\").transition().attrTween(\"d\",function(t){var e=function(t){var e,r=y.getPtId(t),a=I[r],i=I[y.getPtId(T)];if(i){var o=t.x1>i.x1?2*Math.PI:0;e=t.rpx1<i.rpx1?{rpx0:0,rpx1:0}:{x0:o,x1:o}}else{var s,l=y.getPtId(t.parent);x.each(function(t){if(y.getPtId(t)===l)return s=t});var c,u=s.children;u.forEach(function(t,e){if(y.getPtId(t)===r)return c=e});var h=u.length,f=n.interpolate(s.x0,s.x1);e={rpx0:C,rpx1:C,x0:f(c/h),x1:f((c+1)/h)}}return n.interpolate(a,e)}(t);return function(t){return U(e(t))}}),t.select(\"g.slicetext\").attr(\"opacity\",0)}).remove():x.exit().remove(),x.order();var G=null;if(g&&z){var Y=y.getPtId(z);x.each(function(t){null===G&&y.getPtId(t)===Y&&(G=t.x1)})}var W=x;function X(t){var e=t.parent,r=I[y.getPtId(e)],a={};if(r){var i=e.children,o=i.indexOf(t),s=i.length,l=n.interpolate(r.x0,r.x1);a.x0=l(o/s),a.x1=l(o/s)}else a.x0=a.x1=0;return a}g&&(W=W.transition().each(\"end\",function(){var e=n.select(this);y.setSliceCursor(e,t,{hideOnRoot:!0,hideOnLeaves:!0,isTransitioning:!1})})),W.each(function(a){var l=n.select(this),u=o.ensureSingle(l,\"path\",\"surface\",function(t){t.style(\"pointer-events\",\"all\")});a.rpx0=j(a.y0),a.rpx1=j(a.y1),a.xmid=(a.x0+a.x1)/2,a.pxmid=V(a.rpx1,a.xmid),a.midangle=-(a.xmid-Math.PI/2),a.startangle=-(a.x0-Math.PI/2),a.stopangle=-(a.x1-Math.PI/2),a.halfangle=.5*Math.min(o.angleDelta(a.x0,a.x1)||Math.PI,Math.PI),a.ring=1-a.rpx0/a.rpx1,a.rInscribed=function(t){return 0===t.rpx0&&o.isFullCircle([t.x0,t.x1])?1:Math.max(0,Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2))}(a),g?u.transition().attrTween(\"d\",function(t){var e=function(t){var e,r=I[y.getPtId(t)],a={x0:t.x0,x1:t.x1,rpx0:t.rpx0,rpx1:t.rpx1};if(r)e=r;else if(z)if(t.parent)if(G){var i=t.x1>G?2*Math.PI:0;e={x0:i,x1:i}}else e={rpx0:C,rpx1:C},o.extendFlat(e,X(t));else e={rpx0:0,rpx1:0};else e={x0:0,x1:0};return n.interpolate(e,a)}(t);return function(t){return U(e(t))}}):u.attr(\"d\",U),l.call(v,T,t,e,{eventDataKeys:m.eventDataKeys,transitionTime:m.CLICK_TRANSITION_TIME,transitionEasing:m.CLICK_TRANSITION_EASING}).call(y.setSliceCursor,t,{hideOnRoot:!0,hideOnLeaves:!0,isTransitioning:t._transitioning}),u.call(d,a,w);var x=o.ensureSingle(l,\"g\",\"slicetext\"),b=o.ensureSingle(x,\"text\",\"\",function(t){t.attr(\"data-notex\",1)}),k=o.ensureUniformFontSize(t,y.determineTextFont(w,a,h.font));b.text(r.formatSliceLabel(a,T,w,e,h)).classed(\"slicetext\",!0).attr(\"text-anchor\",\"middle\").call(i.font,k).call(s.convertToTspans,t);var M=i.bBox(b.node());a.transform=p(M,a,_),a.transform.targetX=q(a),a.transform.targetY=H(a);var A=function(t,e){var r=t.transform;return f(r,e),r.fontSize=k.size,c(w.type,r,h),o.getTextTransform(r)};g?b.transition().attrTween(\"transform\",function(t){var e=function(t){var e,r=I[y.getPtId(t)],a=t.transform;if(r)e=r;else if(e={rpx1:t.rpx1,transform:{textPosAngle:a.textPosAngle,scale:0,rotate:a.rotate,rCenter:a.rCenter,x:a.x,y:a.y}},z)if(t.parent)if(G){var i=t.x1>G?2*Math.PI:0;e.x0=e.x1=i}else o.extendFlat(e,X(t));else e.x0=e.x1=0;else e.x0=e.x1=0;var s=n.interpolate(e.transform.textPosAngle,t.transform.textPosAngle),l=n.interpolate(e.rpx1,t.rpx1),u=n.interpolate(e.x0,t.x0),f=n.interpolate(e.x1,t.x1),p=n.interpolate(e.transform.scale,a.scale),d=n.interpolate(e.transform.rotate,a.rotate),g=0===a.rCenter?3:0===e.transform.rCenter?1/3:1,v=n.interpolate(e.transform.rCenter,a.rCenter);return function(t){var e=l(t),r=u(t),n=f(t),i=function(t){return v(Math.pow(t,g))}(t),o=V(e,(r+n)/2),m=s(t),y={pxmid:o,rpx1:e,transform:{textPosAngle:m,rCenter:i,x:a.x,y:a.y}};return c(w.type,a,h),{transform:{targetX:q(y),targetY:H(y),scale:p(t),rotate:d(t),rCenter:i}}}}(t);return function(t){return A(e(t),M)}}):b.attr(\"transform\",A(a,M))})}function b(t){return e=t.rpx1,r=t.transform.textPosAngle,[e*Math.sin(r),-e*Math.cos(r)];var e,r}r.plot=function(t,e,r,a){var i,o,s=t._fullLayout,l=s._sunburstlayer,c=!r,h=!s.uniformtext.mode&&y.hasTransition(r);(u(\"sunburst\",s),(i=l.selectAll(\"g.trace.sunburst\").data(e,function(t){return t[0].trace.uid})).enter().append(\"g\").classed(\"trace\",!0).classed(\"sunburst\",!0).attr(\"stroke-linejoin\",\"round\"),i.order(),h)?(a&&(o=a()),n.transition().duration(r.duration).ease(r.easing).each(\"end\",function(){o&&o()}).each(\"interrupt\",function(){o&&o()}).each(function(){l.selectAll(\"g.trace\").each(function(e){x(t,e,this,r)})})):(i.each(function(e){x(t,e,this,r)}),s.uniformtext.mode&&g(t,s._sunburstlayer.selectAll(\".trace\"),\"sunburst\"));c&&i.exit().remove()},r.formatSliceLabel=function(t,e,r,n,a){var i=r.texttemplate,s=r.textinfo;if(!(i||s&&\"none\"!==s))return\"\";var l=a.separators,c=n[0],u=t.data.data,h=c.hierarchy,f=y.isHierarchyRoot(t),p=y.getParent(h,t),d=y.getValue(t);if(!i){var g,v=s.split(\"+\"),m=function(t){return-1!==v.indexOf(t)},x=[];if(m(\"label\")&&u.label&&x.push(u.label),u.hasOwnProperty(\"v\")&&m(\"value\")&&x.push(y.formatValue(u.v,l)),!f){m(\"current path\")&&x.push(y.getPath(t.data));var b=0;m(\"percent parent\")&&b++,m(\"percent entry\")&&b++,m(\"percent root\")&&b++;var _=b>1;if(b){var w,k=function(t){g=y.formatPercent(w,l),_&&(g+=\" of \"+t),x.push(g)};m(\"percent parent\")&&!f&&(w=d/y.getValue(p),k(\"parent\")),m(\"percent entry\")&&(w=d/y.getValue(e),k(\"entry\")),m(\"percent root\")&&(w=d/y.getValue(h),k(\"root\"))}}return m(\"text\")&&(g=o.castOption(r,u.i,\"text\"),o.isValidTextValue(g)&&x.push(g)),x.join(\"<br>\")}var T=o.castOption(r,u.i,\"texttemplate\");if(!T)return\"\";var M={};u.label&&(M.label=u.label),u.hasOwnProperty(\"v\")&&(M.value=u.v,M.valueLabel=y.formatValue(u.v,l)),M.currentPath=y.getPath(t.data),f||(M.percentParent=d/y.getValue(p),M.percentParentLabel=y.formatPercent(M.percentParent,l),M.parent=y.getPtLabel(p)),M.percentEntry=d/y.getValue(e),M.percentEntryLabel=y.formatPercent(M.percentEntry,l),M.entry=y.getPtLabel(e),M.percentRoot=d/y.getValue(h),M.percentRootLabel=y.formatPercent(M.percentRoot,l),M.root=y.getPtLabel(h),u.hasOwnProperty(\"color\")&&(M.color=u.color);var A=o.castOption(r,u.i,\"text\");return(o.isValidTextValue(A)||\"\"===A)&&(M.text=A),M.customdata=o.castOption(r,u.i,\"customdata\"),o.texttemplateString(T,M,a._d3locale,M,r._meta||{})}},{\"../../components/drawing\":613,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"../bar/style\":870,\"../bar/uniform_text\":872,\"../pie/plot\":1103,\"./constants\":1234,\"./fx\":1236,\"./helpers\":1237,\"./style\":1242,d3:165,\"d3-hierarchy\":159}],1242:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../components/color\"),i=t(\"../../lib\"),o=t(\"../bar/uniform_text\").resizeText;function s(t,e,r){var n=e.data.data,o=!e.children,s=n.i,l=i.castOption(r,s,\"marker.line.color\")||a.defaultLine,c=i.castOption(r,s,\"marker.line.width\")||0;t.style(\"stroke-width\",c).call(a.fill,n.color).call(a.stroke,l).style(\"opacity\",o?r.leaf.opacity:null)}e.exports={style:function(t){var e=t._fullLayout._sunburstlayer.selectAll(\".trace\");o(t,e,\"sunburst\"),e.each(function(t){var e=n.select(this),r=t[0].trace;e.style(\"opacity\",r.opacity),e.selectAll(\"path.surface\").each(function(t){n.select(this).call(s,t,r)})})},styleOne:s}},{\"../../components/color\":592,\"../../lib\":717,\"../bar/uniform_text\":872,d3:165}],1243:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),a=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../../plots/attributes\"),s=t(\"../../lib/extend\").extendFlat,l=t(\"../../plot_api/edit_types\").overrideAll;function c(t){return{show:{valType:\"boolean\",dflt:!1},start:{valType:\"number\",dflt:null,editType:\"plot\"},end:{valType:\"number\",dflt:null,editType:\"plot\"},size:{valType:\"number\",dflt:null,min:0,editType:\"plot\"},project:{x:{valType:\"boolean\",dflt:!1},y:{valType:\"boolean\",dflt:!1},z:{valType:\"boolean\",dflt:!1}},color:{valType:\"color\",dflt:n.defaultLine},usecolormap:{valType:\"boolean\",dflt:!1},width:{valType:\"number\",min:1,max:16,dflt:2},highlight:{valType:\"boolean\",dflt:!0},highlightcolor:{valType:\"color\",dflt:n.defaultLine},highlightwidth:{valType:\"number\",min:1,max:16,dflt:2}}}var u=e.exports=l(s({z:{valType:\"data_array\"},x:{valType:\"data_array\"},y:{valType:\"data_array\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:i(),connectgaps:{valType:\"boolean\",dflt:!1,editType:\"calc\"},surfacecolor:{valType:\"data_array\"}},a(\"\",{colorAttr:\"z or surfacecolor\",showScaleDflt:!0,autoColorDflt:!1,editTypeOverride:\"calc\"}),{contours:{x:c(),y:c(),z:c()},hidesurface:{valType:\"boolean\",dflt:!1},lightposition:{x:{valType:\"number\",min:-1e5,max:1e5,dflt:10},y:{valType:\"number\",min:-1e5,max:1e5,dflt:1e4},z:{valType:\"number\",min:-1e5,max:1e5,dflt:0}},lighting:{ambient:{valType:\"number\",min:0,max:1,dflt:.8},diffuse:{valType:\"number\",min:0,max:1,dflt:.8},specular:{valType:\"number\",min:0,max:2,dflt:.05},roughness:{valType:\"number\",min:0,max:1,dflt:.5},fresnel:{valType:\"number\",min:0,max:5,dflt:.2}},opacity:{valType:\"number\",min:0,max:1,dflt:1},_deprecated:{zauto:s({},a.zauto,{}),zmin:s({},a.zmin,{}),zmax:s({},a.zmax,{})},hoverinfo:s({},o.hoverinfo),showlegend:s({},o.showlegend,{dflt:!1})}),\"calc\",\"nested\");u.x.editType=u.y.editType=u.z.editType=\"calc+clearAxisTypes\",u.transforms=void 0},{\"../../components/color\":592,\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plot_api/edit_types\":748,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841}],1244:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/calc\");e.exports=function(t,e){e.surfacecolor?n(t,e,{vals:e.surfacecolor,containerStr:\"\",cLetter:\"c\"}):n(t,e,{vals:e.z,containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":600}],1245:[function(t,e,r){\"use strict\";var n=t(\"gl-surface3d\"),a=t(\"ndarray\"),i=t(\"ndarray-homography\"),o=t(\"ndarray-fill\"),s=t(\"../../lib\").isArrayOrTypedArray,l=t(\"../../lib/gl_format_color\").parseColorScale,c=t(\"../../lib/str2rgbarray\"),u=t(\"../../components/colorscale\").extractOpts,h=t(\"../heatmap/interp2d\"),f=t(\"../heatmap/find_empties\");function p(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var d=p.prototype;d.getXat=function(t,e,r,n){var a=s(this.data.x)?s(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?a:n.d2l(a,0,r)},d.getYat=function(t,e,r,n){var a=s(this.data.y)?s(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 0===r?a:n.d2l(a,0,r)},d.getZat=function(t,e,r,n){var a=this.data.z[e][t];return null===a&&this.data.connectgaps&&this.data._interpolatedZ&&(a=this.data._interpolatedZ[e][t]),void 0===r?a:n.d2l(a,0,r)},d.handlePick=function(t){if(t.object===this.surface){var e=(t.data.index[0]-1)/this.dataScaleX-1,r=(t.data.index[1]-1)/this.dataScaleY-1,n=Math.max(Math.min(Math.round(e),this.data.z[0].length-1),0),a=Math.max(Math.min(Math.round(r),this.data._ylength-1),0);t.index=[n,a],t.traceCoordinate=[this.getXat(n,a),this.getYat(n,a),this.getZat(n,a)],t.dataCoordinate=[this.getXat(n,a,this.data.xcalendar,this.scene.fullSceneLayout.xaxis),this.getYat(n,a,this.data.ycalendar,this.scene.fullSceneLayout.yaxis),this.getZat(n,a,this.data.zcalendar,this.scene.fullSceneLayout.zaxis)];for(var i=0;i<3;i++){var o=t.dataCoordinate[i];null!=o&&(t.dataCoordinate[i]*=this.scene.dataScale[i])}var s=this.data.hovertext||this.data.text;return Array.isArray(s)&&s[a]&&void 0!==s[a][n]?t.textLabel=s[a][n]:t.textLabel=s||\"\",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}};var g=[2,3,5,7,11,13,17,19,23,29,31,37,41,43,47,53,59,61,67,71,73,79,83,89,97,101,103,107,109,113,127,131,137,139,149,151,157,163,167,173,179,181,191,193,197,199,211,223,227,229,233,239,241,251,257,263,269,271,277,281,283,293,307,311,313,317,331,337,347,349,353,359,367,373,379,383,389,397,401,409,419,421,431,433,439,443,449,457,461,463,467,479,487,491,499,503,509,521,523,541,547,557,563,569,571,577,587,593,599,601,607,613,617,619,631,641,643,647,653,659,661,673,677,683,691,701,709,719,727,733,739,743,751,757,761,769,773,787,797,809,811,821,823,827,829,839,853,857,859,863,877,881,883,887,907,911,919,929,937,941,947,953,967,971,977,983,991,997,1009,1013,1019,1021,1031,1033,1039,1049,1051,1061,1063,1069,1087,1091,1093,1097,1103,1109,1117,1123,1129,1151,1153,1163,1171,1181,1187,1193,1201,1213,1217,1223,1229,1231,1237,1249,1259,1277,1279,1283,1289,1291,1297,1301,1303,1307,1319,1321,1327,1361,1367,1373,1381,1399,1409,1423,1427,1429,1433,1439,1447,1451,1453,1459,1471,1481,1483,1487,1489,1493,1499,1511,1523,1531,1543,1549,1553,1559,1567,1571,1579,1583,1597,1601,1607,1609,1613,1619,1621,1627,1637,1657,1663,1667,1669,1693,1697,1699,1709,1721,1723,1733,1741,1747,1753,1759,1777,1783,1787,1789,1801,1811,1823,1831,1847,1861,1867,1871,1873,1877,1879,1889,1901,1907,1913,1931,1933,1949,1951,1973,1979,1987,1993,1997,1999,2003,2011,2017,2027,2029,2039,2053,2063,2069,2081,2083,2087,2089,2099,2111,2113,2129,2131,2137,2141,2143,2153,2161,2179,2203,2207,2213,2221,2237,2239,2243,2251,2267,2269,2273,2281,2287,2293,2297,2309,2311,2333,2339,2341,2347,2351,2357,2371,2377,2381,2383,2389,2393,2399,2411,2417,2423,2437,2441,2447,2459,2467,2473,2477,2503,2521,2531,2539,2543,2549,2551,2557,2579,2591,2593,2609,2617,2621,2633,2647,2657,2659,2663,2671,2677,2683,2687,2689,2693,2699,2707,2711,2713,2719,2729,2731,2741,2749,2753,2767,2777,2789,2791,2797,2801,2803,2819,2833,2837,2843,2851,2857,2861,2879,2887,2897,2903,2909,2917,2927,2939,2953,2957,2963,2969,2971,2999];function v(t,e){if(t<e)return 0;for(var r=0;0===Math.floor(t%e);)t/=e,r++;return r}function m(t){for(var e=[],r=0;r<g.length;r++){var n=g[r];e.push(v(t,n))}return e}function y(t){for(var e=m(t),r=t,n=0;n<g.length;n++)if(e[n]>0){r=g[n];break}return r}function x(t,e){if(!(t<1||e<1)){for(var r=m(t),n=m(e),a=1,i=0;i<g.length;i++)a*=Math.pow(g[i],Math.max(r[i],n[i]));return a}}d.calcXnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getXat(e-1,0),a=this.getXat(e,0);r[e-1]=a!==n&&null!=n&&null!=a?Math.abs(a-n):0}var i=0;for(e=1;e<t;e++)i+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(i/r[e-1]);return r},d.calcYnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getYat(0,e-1),a=this.getYat(0,e);r[e-1]=a!==n&&null!=n&&null!=a?Math.abs(a-n):0}var i=0;for(e=1;e<t;e++)i+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(i/r[e-1]);return r};var b=[1,2,4,6,12,24,36,48,60,120,180,240,360,720,840,1260],_=b[9],w=b[13];function k(t,e){for(var r=!1,n=0;n<t.length;n++)if(e===t[n]){r=!0;break}!1===r&&t.push(e)}d.estimateScale=function(t,e){for(var r=1+function(t){if(0!==t.length){for(var e=1,r=0;r<t.length;r++)e=x(e,t[r]);return e}}(0===e?this.calcXnums(t):this.calcYnums(t));r<_;)r*=2;for(;r>w;)r--,r/=y(r),++r<_&&(r=w);var n=Math.round(r/t);return n>1?n:1},d.refineCoords=function(t){for(var e=this.dataScaleX,r=this.dataScaleY,n=t[0].shape[0],o=t[0].shape[1],s=0|Math.floor(t[0].shape[0]*e+1),l=0|Math.floor(t[0].shape[1]*r+1),c=1+n+1,u=1+o+1,h=a(new Float32Array(c*u),[c,u]),f=0;f<t.length;++f){this.surface.padField(h,t[f]);var p=a(new Float32Array(s*l),[s,l]);i(p,h,[e,0,0,0,r,0,0,0,1]),t[f]=p}},d.setContourLevels=function(){var t,e,r,n=[[],[],[]],a=[!1,!1,!1],i=!1;for(t=0;t<3;++t)if(this.showContour[t]&&(i=!0,this.contourSize[t]>0&&null!==this.contourStart[t]&&null!==this.contourEnd[t]&&this.contourEnd[t]>this.contourStart[t]))for(a[t]=!0,e=this.contourStart[t];e<this.contourEnd[t];e+=this.contourSize[t])r=e*this.scene.dataScale[t],k(n[t],r);if(i){var o=[[],[],[]];for(t=0;t<3;++t)this.showContour[t]&&(o[t]=a[t]?n[t]:this.scene.contourLevels[t]);this.surface.update({levels:o})}},d.update=function(t){var e,r,n,i,s=this.scene,p=s.fullSceneLayout,d=this.surface,g=t.opacity,v=l(t,g),m=s.dataScale,y=t.z[0].length,x=t._ylength,b=s.contourLevels;this.data=t;var _=[];for(e=0;e<3;e++)for(_[e]=[],r=0;r<y;r++)_[e][r]=[];for(r=0;r<y;r++)for(n=0;n<x;n++)_[0][r][n]=this.getXat(r,n,t.xcalendar,p.xaxis),_[1][r][n]=this.getYat(r,n,t.ycalendar,p.yaxis),_[2][r][n]=this.getZat(r,n,t.zcalendar,p.zaxis);if(t.connectgaps)for(t._emptypoints=f(_[2]),h(_[2],t._emptypoints),t._interpolatedZ=[],r=0;r<y;r++)for(t._interpolatedZ[r]=[],n=0;n<x;n++)t._interpolatedZ[r][n]=_[2][r][n];for(e=0;e<3;e++)for(r=0;r<y;r++)for(n=0;n<x;n++)null==(i=_[e][r][n])?_[e][r][n]=NaN:i=_[e][r][n]*=m[e];for(e=0;e<3;e++)for(r=0;r<y;r++)for(n=0;n<x;n++)null!=(i=_[e][r][n])&&(this.minValues[e]>i&&(this.minValues[e]=i),this.maxValues[e]<i&&(this.maxValues[e]=i));for(e=0;e<3;e++)this.objectOffset[e]=.5*(this.minValues[e]+this.maxValues[e]);for(e=0;e<3;e++)for(r=0;r<y;r++)for(n=0;n<x;n++)null!=(i=_[e][r][n])&&(_[e][r][n]-=this.objectOffset[e]);var k=[a(new Float32Array(y*x),[y,x]),a(new Float32Array(y*x),[y,x]),a(new Float32Array(y*x),[y,x])];o(k[0],function(t,e){return _[0][t][e]}),o(k[1],function(t,e){return _[1][t][e]}),o(k[2],function(t,e){return _[2][t][e]}),_=[];var T={colormap:v,levels:[[],[],[]],showContour:[!0,!0,!0],showSurface:!t.hidesurface,contourProject:[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],contourWidth:[1,1,1],contourColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],contourTint:[1,1,1],dynamicColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],dynamicWidth:[1,1,1],dynamicTint:[1,1,1],opacity:t.opacity},M=u(t);if(T.intensityBounds=[M.min,M.max],t.surfacecolor){var A=a(new Float32Array(y*x),[y,x]);o(A,function(e,r){return t.surfacecolor[r][e]}),k.push(A)}else T.intensityBounds[0]*=m[2],T.intensityBounds[1]*=m[2];(w<k[0].shape[0]||w<k[0].shape[1])&&(this.refineData=!1),!0===this.refineData&&(this.dataScaleX=this.estimateScale(k[0].shape[0],0),this.dataScaleY=this.estimateScale(k[0].shape[1],1),1===this.dataScaleX&&1===this.dataScaleY||this.refineCoords(k)),t.surfacecolor&&(T.intensity=k.pop());var S=[!0,!0,!0],E=[\"x\",\"y\",\"z\"];for(e=0;e<3;++e){var L=t.contours[E[e]];S[e]=L.highlight,T.showContour[e]=L.show||L.highlight,T.showContour[e]&&(T.contourProject[e]=[L.project.x,L.project.y,L.project.z],L.show?(this.showContour[e]=!0,T.levels[e]=b[e],d.highlightColor[e]=T.contourColor[e]=c(L.color),L.usecolormap?d.highlightTint[e]=T.contourTint[e]=0:d.highlightTint[e]=T.contourTint[e]=1,T.contourWidth[e]=L.width,this.contourStart[e]=L.start,this.contourEnd[e]=L.end,this.contourSize[e]=L.size):(this.showContour[e]=!1,this.contourStart[e]=null,this.contourEnd[e]=null,this.contourSize[e]=0),L.highlight&&(T.dynamicColor[e]=c(L.highlightcolor),T.dynamicWidth[e]=L.highlightwidth))}(function(t){var e=t[0].rgb,r=t[t.length-1].rgb;return e[0]===r[0]&&e[1]===r[1]&&e[2]===r[2]&&e[3]===r[3]})(v)&&(T.vertexColor=!0),T.objectOffset=this.objectOffset,T.coords=k,d.update(T),d.visible=t.visible,d.enableDynamic=S,d.enableHighlight=S,d.snapToData=!0,\"lighting\"in t&&(d.ambientLight=t.lighting.ambient,d.diffuseLight=t.lighting.diffuse,d.specularLight=t.lighting.specular,d.roughness=t.lighting.roughness,d.fresnel=t.lighting.fresnel),\"lightposition\"in t&&(d.lightPosition=[t.lightposition.x,t.lightposition.y,t.lightposition.z]),g&&g<1&&(d.supportsTransparency=!0)},d.dispose=function(){this.scene.glplot.remove(this.surface),this.surface.dispose()},e.exports=function(t,e){var r=t.glplot.gl,a=n({gl:r}),i=new p(t,a,e.uid);return a._trace=i,i.update(e),t.glplot.add(a),i}},{\"../../components/colorscale\":604,\"../../lib\":717,\"../../lib/gl_format_color\":714,\"../../lib/str2rgbarray\":740,\"../heatmap/find_empties\":1006,\"../heatmap/interp2d\":1009,\"gl-surface3d\":318,ndarray:452,\"ndarray-fill\":442,\"ndarray-homography\":444}],1246:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),a=t(\"../../lib\"),i=t(\"../../components/colorscale/defaults\"),o=t(\"./attributes\");function s(t,e,r){e in t&&!(r in t)&&(t[r]=t[e])}e.exports=function(t,e,r,l){var c,u;function h(r,n){return a.coerce(t,e,o,r,n)}var f=h(\"x\"),p=h(\"y\"),d=h(\"z\");if(!d||!d.length||f&&f.length<1||p&&p.length<1)e.visible=!1;else{e._xlength=Array.isArray(f)&&a.isArrayOrTypedArray(f[0])?d.length:d[0].length,e._ylength=d.length,n.getComponentMethod(\"calendars\",\"handleTraceDefaults\")(t,e,[\"x\",\"y\",\"z\"],l),h(\"text\"),h(\"hovertext\"),h(\"hovertemplate\"),[\"lighting.ambient\",\"lighting.diffuse\",\"lighting.specular\",\"lighting.roughness\",\"lighting.fresnel\",\"lightposition.x\",\"lightposition.y\",\"lightposition.z\",\"hidesurface\",\"connectgaps\",\"opacity\"].forEach(function(t){h(t)});var g=h(\"surfacecolor\"),v=[\"x\",\"y\",\"z\"];for(c=0;c<3;++c){var m=\"contours.\"+v[c],y=h(m+\".show\"),x=h(m+\".highlight\");if(y||x)for(u=0;u<3;++u)h(m+\".project.\"+v[u]);y&&(h(m+\".color\"),h(m+\".width\"),h(m+\".usecolormap\")),x&&(h(m+\".highlightcolor\"),h(m+\".highlightwidth\")),h(m+\".start\"),h(m+\".end\"),h(m+\".size\")}g||(s(t,\"zmin\",\"cmin\"),s(t,\"zmax\",\"cmax\"),s(t,\"zauto\",\"cauto\")),i(t,e,l,h,{prefix:\"\",cLetter:\"c\"}),e._length=null}}},{\"../../components/colorscale/defaults\":602,\"../../lib\":717,\"../../registry\":846,\"./attributes\":1243}],1247:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),colorbar:{min:\"cmin\",max:\"cmax\"},calc:t(\"./calc\"),plot:t(\"./convert\"),moduleType:\"trace\",name:\"surface\",basePlotModule:t(\"../../plots/gl3d\"),categories:[\"gl3d\",\"2dMap\",\"showLegend\"],meta:{}}},{\"../../plots/gl3d\":805,\"./attributes\":1243,\"./calc\":1244,\"./convert\":1245,\"./defaults\":1246}],1248:[function(t,e,r){\"use strict\";var n=t(\"../../components/annotations/attributes\"),a=t(\"../../lib/extend\").extendFlat,i=t(\"../../plot_api/edit_types\").overrideAll,o=t(\"../../plots/font_attributes\"),s=t(\"../../plots/domain\").attributes;t(\"../../constants/docs\").FORMAT_LINK;(e.exports=i({domain:s({name:\"table\",trace:!0}),columnwidth:{valType:\"number\",arrayOk:!0,dflt:null},columnorder:{valType:\"data_array\"},header:{values:{valType:\"data_array\",dflt:[]},format:{valType:\"data_array\",dflt:[]},prefix:{valType:\"string\",arrayOk:!0,dflt:null},suffix:{valType:\"string\",arrayOk:!0,dflt:null},height:{valType:\"number\",dflt:28},align:a({},n.align,{arrayOk:!0}),line:{width:{valType:\"number\",arrayOk:!0,dflt:1},color:{valType:\"color\",arrayOk:!0,dflt:\"grey\"}},fill:{color:{valType:\"color\",arrayOk:!0,dflt:\"white\"}},font:a({},o({arrayOk:!0}))},cells:{values:{valType:\"data_array\",dflt:[]},format:{valType:\"data_array\",dflt:[]},prefix:{valType:\"string\",arrayOk:!0,dflt:null},suffix:{valType:\"string\",arrayOk:!0,dflt:null},height:{valType:\"number\",dflt:20},align:a({},n.align,{arrayOk:!0}),line:{width:{valType:\"number\",arrayOk:!0,dflt:1},color:{valType:\"color\",arrayOk:!0,dflt:\"grey\"}},fill:{color:{valType:\"color\",arrayOk:!0,dflt:\"white\"}},font:a({},o({arrayOk:!0}))}},\"calc\",\"from-root\")).transforms=void 0},{\"../../components/annotations/attributes\":575,\"../../constants/docs\":688,\"../../lib/extend\":708,\"../../plot_api/edit_types\":748,\"../../plots/domain\":790,\"../../plots/font_attributes\":791}],1249:[function(t,e,r){\"use strict\";var n=t(\"../../plots/get_data\").getModuleCalcData,a=t(\"./plot\");r.name=\"table\",r.plot=function(t){var e=n(t.calcdata,\"table\")[0];e.length&&a(t,e)},r.clean=function(t,e,r,n){var a=n._has&&n._has(\"table\"),i=e._has&&e._has(\"table\");a&&!i&&n._paperdiv.selectAll(\".table\").remove()}},{\"../../plots/get_data\":800,\"./plot\":1256}],1250:[function(t,e,r){\"use strict\";var n=t(\"../../lib/gup\").wrap;e.exports=function(){return n({})}},{\"../../lib/gup\":715}],1251:[function(t,e,r){\"use strict\";e.exports={cellPad:8,columnExtentOffset:10,columnTitleOffset:28,emptyHeaderHeight:16,latexCheck:/^\\$.*\\$$/,goldenRatio:1.618,lineBreaker:\"<br>\",maxDimensionCount:60,overdrag:45,releaseTransitionDuration:120,releaseTransitionEase:\"cubic-out\",scrollbarCaptureWidth:18,scrollbarHideDelay:1e3,scrollbarHideDuration:1e3,scrollbarOffset:5,scrollbarWidth:8,transitionDuration:100,transitionEase:\"cubic-out\",uplift:5,wrapSpacer:\" \",wrapSplitCharacter:\" \",cn:{table:\"table\",tableControlView:\"table-control-view\",scrollBackground:\"scroll-background\",yColumn:\"y-column\",columnBlock:\"column-block\",scrollAreaClip:\"scroll-area-clip\",scrollAreaClipRect:\"scroll-area-clip-rect\",columnBoundary:\"column-boundary\",columnBoundaryClippath:\"column-boundary-clippath\",columnBoundaryRect:\"column-boundary-rect\",columnCells:\"column-cells\",columnCell:\"column-cell\",cellRect:\"cell-rect\",cellText:\"cell-text\",cellTextHolder:\"cell-text-holder\",scrollbarKit:\"scrollbar-kit\",scrollbar:\"scrollbar\",scrollbarSlider:\"scrollbar-slider\",scrollbarGlyph:\"scrollbar-glyph\",scrollbarCaptureZone:\"scrollbar-capture-zone\"}}},{}],1252:[function(t,e,r){\"use strict\";var n=t(\"./constants\"),a=t(\"../../lib/extend\").extendFlat,i=t(\"fast-isnumeric\");function o(t){if(Array.isArray(t)){for(var e=0,r=0;r<t.length;r++)e=Math.max(e,o(t[r]));return e}return t}function s(t,e){return t+e}function l(t){var e,r=t.slice(),n=1/0,a=0;for(e=0;e<r.length;e++)Array.isArray(r[e])||(r[e]=[r[e]]),n=Math.min(n,r[e].length),a=Math.max(a,r[e].length);if(n!==a)for(e=0;e<r.length;e++){var i=a-r[e].length;i&&(r[e]=r[e].concat(c(i)))}return r}function c(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=\"\";return e}function u(t){return t.calcdata.columns.reduce(function(e,r){return r.xIndex<t.xIndex?e+r.columnWidth:e},0)}function h(t,e){return Object.keys(t).map(function(r){return a({},t[r],{auxiliaryBlocks:e})})}function f(t,e){for(var r,n={},a=0,i=0,o={firstRowIndex:null,lastRowIndex:null,rows:[]},s=0,l=0,c=0;c<t.length;c++)r=t[c],o.rows.push({rowIndex:c,rowHeight:r}),((i+=r)>=e||c===t.length-1)&&(n[a]=o,o.key=l++,o.firstRowIndex=s,o.lastRowIndex=c,o={firstRowIndex:null,lastRowIndex:null,rows:[]},a+=i,s=c+1,i=0);return n}e.exports=function(t,e){var r=l(e.cells.values),p=function(t){return t.slice(e.header.values.length,t.length)},d=l(e.header.values);d.length&&!d[0].length&&(d[0]=[\"\"],d=l(d));var g=d.concat(p(r).map(function(){return c((d[0]||[\"\"]).length)})),v=e.domain,m=Math.floor(t._fullLayout._size.w*(v.x[1]-v.x[0])),y=Math.floor(t._fullLayout._size.h*(v.y[1]-v.y[0])),x=e.header.values.length?g[0].map(function(){return e.header.height}):[n.emptyHeaderHeight],b=r.length?r[0].map(function(){return e.cells.height}):[],_=x.reduce(s,0),w=f(b,y-_+n.uplift),k=h(f(x,_),[]),T=h(w,k),M={},A=e._fullInput.columnorder.concat(p(r.map(function(t,e){return e}))),S=g.map(function(t,r){var n=Array.isArray(e.columnwidth)?e.columnwidth[Math.min(r,e.columnwidth.length-1)]:e.columnwidth;return i(n)?Number(n):1}),E=S.reduce(s,0);S=S.map(function(t){return t/E*m});var L=Math.max(o(e.header.line.width),o(e.cells.line.width)),C={key:e.uid+t._context.staticPlot,translateX:v.x[0]*t._fullLayout._size.w,translateY:t._fullLayout._size.h*(1-v.y[1]),size:t._fullLayout._size,width:m,maxLineWidth:L,height:y,columnOrder:A,groupHeight:y,rowBlocks:T,headerRowBlocks:k,scrollY:0,cells:a({},e.cells,{values:r}),headerCells:a({},e.header,{values:g}),gdColumns:g.map(function(t){return t[0]}),gdColumnsOriginalOrder:g.map(function(t){return t[0]}),prevPages:[0,0],scrollbarState:{scrollbarScrollInProgress:!1},columns:g.map(function(t,e){var r=M[t];return M[t]=(r||0)+1,{key:t+\"__\"+M[t],label:t,specIndex:e,xIndex:A[e],xScale:u,x:void 0,calcdata:void 0,columnWidth:S[e]}})};return C.columns.forEach(function(t){t.calcdata=C,t.x=u(t)}),C}},{\"../../lib/extend\":708,\"./constants\":1251,\"fast-isnumeric\":228}],1253:[function(t,e,r){\"use strict\";var n=t(\"../../lib/extend\").extendFlat;r.splitToPanels=function(t){var e=[0,0],r=n({},t,{key:\"header\",type:\"header\",page:0,prevPages:e,currentRepaint:[null,null],dragHandle:!0,values:t.calcdata.headerCells.values[t.specIndex],rowBlocks:t.calcdata.headerRowBlocks,calcdata:n({},t.calcdata,{cells:t.calcdata.headerCells})});return[n({},t,{key:\"cells1\",type:\"cells\",page:0,prevPages:e,currentRepaint:[null,null],dragHandle:!1,values:t.calcdata.cells.values[t.specIndex],rowBlocks:t.calcdata.rowBlocks}),n({},t,{key:\"cells2\",type:\"cells\",page:1,prevPages:e,currentRepaint:[null,null],dragHandle:!1,values:t.calcdata.cells.values[t.specIndex],rowBlocks:t.calcdata.rowBlocks}),r]},r.splitToCells=function(t){var e=function(t){var e=t.rowBlocks[t.page],r=e?e.rows[0].rowIndex:0,n=e?r+e.rows.length:0;return[r,n]}(t);return(t.values||[]).slice(e[0],e[1]).map(function(r,n){return{keyWithinBlock:n+(\"string\"==typeof r&&r.match(/[<$&> ]/)?\"_keybuster_\"+Math.random():\"\"),key:e[0]+n,column:t,calcdata:t.calcdata,page:t.page,rowBlocks:t.rowBlocks,value:r}})}},{\"../../lib/extend\":708}],1254:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./attributes\"),i=t(\"../../plots/domain\").defaults;e.exports=function(t,e,r,o){function s(r,i){return n.coerce(t,e,a,r,i)}i(e,o,s),s(\"columnwidth\"),s(\"header.values\"),s(\"header.format\"),s(\"header.align\"),s(\"header.prefix\"),s(\"header.suffix\"),s(\"header.height\"),s(\"header.line.width\"),s(\"header.line.color\"),s(\"header.fill.color\"),n.coerceFont(s,\"header.font\",n.extendFlat({},o.font)),function(t,e){for(var r=t.columnorder||[],n=t.header.values.length,a=r.slice(0,n),i=a.slice().sort(function(t,e){return t-e}),o=a.map(function(t){return i.indexOf(t)}),s=o.length;s<n;s++)o.push(s);e(\"columnorder\",o)}(e,s),s(\"cells.values\"),s(\"cells.format\"),s(\"cells.align\"),s(\"cells.prefix\"),s(\"cells.suffix\"),s(\"cells.height\"),s(\"cells.line.width\"),s(\"cells.line.color\"),s(\"cells.fill.color\"),n.coerceFont(s,\"cells.font\",n.extendFlat({},o.font)),e._length=null}},{\"../../lib\":717,\"../../plots/domain\":790,\"./attributes\":1248}],1255:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"./plot\"),moduleType:\"trace\",name:\"table\",basePlotModule:t(\"./base_plot\"),categories:[\"noOpacity\"],meta:{}}},{\"./attributes\":1248,\"./base_plot\":1249,\"./calc\":1250,\"./defaults\":1254,\"./plot\":1256}],1256:[function(t,e,r){\"use strict\";var n=t(\"./constants\"),a=t(\"d3\"),i=t(\"../../lib/gup\"),o=t(\"../../components/drawing\"),s=t(\"../../lib/svg_text_utils\"),l=t(\"../../lib\").raiseToTop,c=t(\"../../lib\").cancelTransition,u=t(\"./data_preparation_helper\"),h=t(\"./data_split_helpers\"),f=t(\"../../components/color\");function p(t){return Math.ceil(t.calcdata.maxLineWidth/2)}function d(t,e){return\"clip\"+t._fullLayout._uid+\"_scrollAreaBottomClip_\"+e.key}function g(t,e){return\"clip\"+t._fullLayout._uid+\"_columnBoundaryClippath_\"+e.calcdata.key+\"_\"+e.specIndex}function v(t){return[].concat.apply([],t.map(function(t){return t})).map(function(t){return t.__data__})}function m(t,e,r){var o=t.selectAll(\".\"+n.cn.scrollbarKit).data(i.repeat,i.keyFun);o.enter().append(\"g\").classed(n.cn.scrollbarKit,!0).style(\"shape-rendering\",\"geometricPrecision\"),o.each(function(t){var e=t.scrollbarState;e.totalHeight=function(t){var e=t.rowBlocks;return z(e,e.length-1)+(e.length?I(e[e.length-1],1/0):1)}(t),e.scrollableAreaHeight=t.groupHeight-M(t),e.currentlyVisibleHeight=Math.min(e.totalHeight,e.scrollableAreaHeight),e.ratio=e.currentlyVisibleHeight/e.totalHeight,e.barLength=Math.max(e.ratio*e.currentlyVisibleHeight,n.goldenRatio*n.scrollbarWidth),e.barWiggleRoom=e.currentlyVisibleHeight-e.barLength,e.wiggleRoom=Math.max(0,e.totalHeight-e.scrollableAreaHeight),e.topY=0===e.barWiggleRoom?0:t.scrollY/e.wiggleRoom*e.barWiggleRoom,e.bottomY=e.topY+e.barLength,e.dragMultiplier=e.wiggleRoom/e.barWiggleRoom}).attr(\"transform\",function(t){return\"translate(\"+(t.width+n.scrollbarWidth/2+n.scrollbarOffset)+\" \"+M(t)+\")\"});var s=o.selectAll(\".\"+n.cn.scrollbar).data(i.repeat,i.keyFun);s.enter().append(\"g\").classed(n.cn.scrollbar,!0);var l=s.selectAll(\".\"+n.cn.scrollbarSlider).data(i.repeat,i.keyFun);l.enter().append(\"g\").classed(n.cn.scrollbarSlider,!0),l.attr(\"transform\",function(t){return\"translate(0 \"+(t.scrollbarState.topY||0)+\")\"});var c=l.selectAll(\".\"+n.cn.scrollbarGlyph).data(i.repeat,i.keyFun);c.enter().append(\"line\").classed(n.cn.scrollbarGlyph,!0).attr(\"stroke\",\"black\").attr(\"stroke-width\",n.scrollbarWidth).attr(\"stroke-linecap\",\"round\").attr(\"y1\",n.scrollbarWidth/2),c.attr(\"y2\",function(t){return t.scrollbarState.barLength-n.scrollbarWidth/2}).attr(\"stroke-opacity\",function(t){return t.columnDragInProgress||!t.scrollbarState.barWiggleRoom||r?0:.4}),c.transition().delay(0).duration(0),c.transition().delay(n.scrollbarHideDelay).duration(n.scrollbarHideDuration).attr(\"stroke-opacity\",0);var u=s.selectAll(\".\"+n.cn.scrollbarCaptureZone).data(i.repeat,i.keyFun);u.enter().append(\"line\").classed(n.cn.scrollbarCaptureZone,!0).attr(\"stroke\",\"white\").attr(\"stroke-opacity\",.01).attr(\"stroke-width\",n.scrollbarCaptureWidth).attr(\"stroke-linecap\",\"butt\").attr(\"y1\",0).on(\"mousedown\",function(r){var n=a.event.y,i=this.getBoundingClientRect(),o=r.scrollbarState,s=n-i.top,l=a.scale.linear().domain([0,o.scrollableAreaHeight]).range([0,o.totalHeight]).clamp(!0);o.topY<=s&&s<=o.bottomY||S(e,t,null,l(s-o.barLength/2))(r)}).call(a.behavior.drag().origin(function(t){return a.event.stopPropagation(),t.scrollbarState.scrollbarScrollInProgress=!0,t}).on(\"drag\",S(e,t)).on(\"dragend\",function(){})),u.attr(\"y2\",function(t){return t.scrollbarState.scrollableAreaHeight}),e._context.staticPlot&&(c.remove(),u.remove())}function y(t,e,r,s){var l=function(t){var e=t.selectAll(\".\"+n.cn.columnCell).data(h.splitToCells,function(t){return t.keyWithinBlock});return e.enter().append(\"g\").classed(n.cn.columnCell,!0),e.exit().remove(),e}(function(t){var e=t.selectAll(\".\"+n.cn.columnCells).data(i.repeat,i.keyFun);return e.enter().append(\"g\").classed(n.cn.columnCells,!0),e.exit().remove(),e}(r));!function(t){t.each(function(t,e){var r=t.calcdata.cells.font,n=t.column.specIndex,a={size:_(r.size,n,e),color:_(r.color,n,e),family:_(r.family,n,e)};t.rowNumber=t.key,t.align=_(t.calcdata.cells.align,n,e),t.cellBorderWidth=_(t.calcdata.cells.line.width,n,e),t.font=a})}(l),function(t){t.attr(\"width\",function(t){return t.column.columnWidth}).attr(\"stroke-width\",function(t){return t.cellBorderWidth}).each(function(t){var e=a.select(this);f.stroke(e,_(t.calcdata.cells.line.color,t.column.specIndex,t.rowNumber)),f.fill(e,_(t.calcdata.cells.fill.color,t.column.specIndex,t.rowNumber))})}(function(t){var e=t.selectAll(\".\"+n.cn.cellRect).data(i.repeat,function(t){return t.keyWithinBlock});return e.enter().append(\"rect\").classed(n.cn.cellRect,!0),e}(l));var c=function(t){var e=t.selectAll(\".\"+n.cn.cellText).data(i.repeat,function(t){return t.keyWithinBlock});return e.enter().append(\"text\").classed(n.cn.cellText,!0).style(\"cursor\",function(){return\"auto\"}).on(\"mousedown\",function(){a.event.stopPropagation()}),e}(function(t){var e=t.selectAll(\".\"+n.cn.cellTextHolder).data(i.repeat,function(t){return t.keyWithinBlock});return e.enter().append(\"g\").classed(n.cn.cellTextHolder,!0).style(\"shape-rendering\",\"geometricPrecision\"),e}(l));!function(t){t.each(function(t){o.font(a.select(this),t.font)})}(c),x(c,e,s,t),O(l)}function x(t,e,r,i){t.text(function(t){var e=t.column.specIndex,r=t.rowNumber,i=t.value,o=\"string\"==typeof i,s=o&&i.match(/<br>/i),l=!o||s;t.mayHaveMarkup=o&&i.match(/[<&>]/);var c,u=\"string\"==typeof(c=i)&&c.match(n.latexCheck);t.latex=u;var h,f,p=u?\"\":_(t.calcdata.cells.prefix,e,r)||\"\",d=u?\"\":_(t.calcdata.cells.suffix,e,r)||\"\",g=u?null:_(t.calcdata.cells.format,e,r)||null,v=p+(g?a.format(g)(t.value):t.value)+d;if(t.wrappingNeeded=!t.wrapped&&!l&&!u&&(h=b(v)),t.cellHeightMayIncrease=s||u||t.mayHaveMarkup||(void 0===h?b(v):h),t.needsConvertToTspans=t.mayHaveMarkup||t.wrappingNeeded||t.latex,t.wrappingNeeded){var m=(\" \"===n.wrapSplitCharacter?v.replace(/<a href=/gi,\"<a_href=\"):v).split(n.wrapSplitCharacter),y=\" \"===n.wrapSplitCharacter?m.map(function(t){return t.replace(/<a_href=/gi,\"<a href=\")}):m;t.fragments=y.map(function(t){return{text:t,width:null}}),t.fragments.push({fragment:n.wrapSpacer,width:null}),f=y.join(n.lineBreaker)+n.lineBreaker+n.wrapSpacer}else delete t.fragments,f=v;return f}).attr(\"dy\",function(t){return t.needsConvertToTspans?0:\"0.75em\"}).each(function(t){var o=a.select(this),l=t.wrappingNeeded?L:C;t.needsConvertToTspans?s.convertToTspans(o,i,l(r,this,e,i,t)):a.select(this.parentNode).attr(\"transform\",function(t){return\"translate(\"+P(t)+\" \"+n.cellPad+\")\"}).attr(\"text-anchor\",function(t){return{left:\"start\",center:\"middle\",right:\"end\"}[t.align]})})}function b(t){return-1!==t.indexOf(n.wrapSplitCharacter)}function _(t,e,r){if(Array.isArray(t)){var n=t[Math.min(e,t.length-1)];return Array.isArray(n)?n[Math.min(r,n.length-1)]:n}return t}function w(t,e,r){t.transition().ease(n.releaseTransitionEase).duration(n.releaseTransitionDuration).attr(\"transform\",\"translate(\"+e.x+\" \"+r+\")\")}function k(t){return\"cells\"===t.type}function T(t){return\"header\"===t.type}function M(t){return(t.rowBlocks.length?t.rowBlocks[0].auxiliaryBlocks:[]).reduce(function(t,e){return t+I(e,1/0)},0)}function A(t,e,r){var n=v(e)[0];if(void 0!==n){var a=n.rowBlocks,i=n.calcdata,o=z(a,a.length),s=n.calcdata.groupHeight-M(n),l=i.scrollY=Math.max(0,Math.min(o-s,i.scrollY)),c=function(t,e,r){for(var n=[],a=0,i=0;i<t.length;i++){for(var o=t[i],s=o.rows,l=0,c=0;c<s.length;c++)l+=s[c].rowHeight;o.allRowsHeight=l,e<a+l&&e+r>a&&n.push(i),a+=l}return n}(a,l,s);1===c.length&&(c[0]===a.length-1?c.unshift(c[0]-1):c.push(c[0]+1)),c[0]%2&&c.reverse(),e.each(function(t,e){t.page=c[e],t.scrollY=l}),e.attr(\"transform\",function(t){return\"translate(0 \"+(z(t.rowBlocks,t.page)-t.scrollY)+\")\"}),t&&(E(t,r,e,c,n.prevPages,n,0),E(t,r,e,c,n.prevPages,n,1),m(r,t))}}function S(t,e,r,i){return function(o){var s=o.calcdata?o.calcdata:o,l=e.filter(function(t){return s.key===t.key}),c=r||s.scrollbarState.dragMultiplier,u=s.scrollY;s.scrollY=void 0===i?s.scrollY+c*a.event.dy:i;var h=l.selectAll(\".\"+n.cn.yColumn).selectAll(\".\"+n.cn.columnBlock).filter(k);return A(t,h,l),s.scrollY===u}}function E(t,e,r,n,a,i,o){n[o]!==a[o]&&(clearTimeout(i.currentRepaint[o]),i.currentRepaint[o]=setTimeout(function(){var i=r.filter(function(t,e){return e===o&&n[e]!==a[e]});y(t,e,i,r),a[o]=n[o]}))}function L(t,e,r,i){return function(){var o=a.select(e.parentNode);o.each(function(t){var e=t.fragments;o.selectAll(\"tspan.line\").each(function(t,r){e[r].width=this.getComputedTextLength()});var r,a,i=e[e.length-1].width,s=e.slice(0,-1),l=[],c=0,u=t.column.columnWidth-2*n.cellPad;for(t.value=\"\";s.length;)c+(a=(r=s.shift()).width+i)>u&&(t.value+=l.join(n.wrapSpacer)+n.lineBreaker,l=[],c=0),l.push(r.text),c+=a;c&&(t.value+=l.join(n.wrapSpacer)),t.wrapped=!0}),o.selectAll(\"tspan.line\").remove(),x(o.select(\".\"+n.cn.cellText),r,t,i),a.select(e.parentNode.parentNode).call(O)}}function C(t,e,r,i,o){return function(){if(!o.settledY){var s=a.select(e.parentNode),l=R(o),c=o.key-l.firstRowIndex,u=l.rows[c].rowHeight,h=o.cellHeightMayIncrease?e.parentNode.getBoundingClientRect().height+2*n.cellPad:u,f=Math.max(h,u);f-l.rows[c].rowHeight&&(l.rows[c].rowHeight=f,t.selectAll(\".\"+n.cn.columnCell).call(O),A(null,t.filter(k),0),m(r,i,!0)),s.attr(\"transform\",function(){var t=this.parentNode.getBoundingClientRect(),e=a.select(this.parentNode).select(\".\"+n.cn.cellRect).node().getBoundingClientRect(),r=this.transform.baseVal.consolidate(),i=e.top-t.top+(r?r.matrix.f:n.cellPad);return\"translate(\"+P(o,a.select(this.parentNode).select(\".\"+n.cn.cellTextHolder).node().getBoundingClientRect().width)+\" \"+i+\")\"}),o.settledY=!0}}}function P(t,e){switch(t.align){case\"left\":return n.cellPad;case\"right\":return t.column.columnWidth-(e||0)-n.cellPad;case\"center\":return(t.column.columnWidth-(e||0))/2;default:return n.cellPad}}function O(t){t.attr(\"transform\",function(t){var e=t.rowBlocks[0].auxiliaryBlocks.reduce(function(t,e){return t+I(e,1/0)},0);return\"translate(0 \"+(I(R(t),t.key)+e)+\")\"}).selectAll(\".\"+n.cn.cellRect).attr(\"height\",function(t){return(e=R(t),r=t.key,e.rows[r-e.firstRowIndex]).rowHeight;var e,r})}function z(t,e){for(var r=0,n=e-1;n>=0;n--)r+=D(t[n]);return r}function I(t,e){for(var r=0,n=0;n<t.rows.length&&t.rows[n].rowIndex<e;n++)r+=t.rows[n].rowHeight;return r}function D(t){var e=t.allRowsHeight;if(void 0!==e)return e;for(var r=0,n=0;n<t.rows.length;n++)r+=t.rows[n].rowHeight;return t.allRowsHeight=r,r}function R(t){return t.rowBlocks[t.page]}e.exports=function(t,e){var r=!t._context.staticPlot,s=t._fullLayout._paper.selectAll(\".\"+n.cn.table).data(e.map(function(e){var r=i.unwrap(e).trace;return u(t,r)}),i.keyFun);s.exit().remove(),s.enter().append(\"g\").classed(n.cn.table,!0).attr(\"overflow\",\"visible\").style(\"box-sizing\",\"content-box\").style(\"position\",\"absolute\").style(\"left\",0).style(\"overflow\",\"visible\").style(\"shape-rendering\",\"crispEdges\").style(\"pointer-events\",\"all\"),s.attr(\"width\",function(t){return t.width+t.size.l+t.size.r}).attr(\"height\",function(t){return t.height+t.size.t+t.size.b}).attr(\"transform\",function(t){return\"translate(\"+t.translateX+\",\"+t.translateY+\")\"});var f=s.selectAll(\".\"+n.cn.tableControlView).data(i.repeat,i.keyFun),x=f.enter().append(\"g\").classed(n.cn.tableControlView,!0).style(\"box-sizing\",\"content-box\");r&&x.on(\"mousemove\",function(e){f.filter(function(t){return e===t}).call(m,t)}).on(\"mousewheel\",function(e){if(!e.scrollbarState.wheeling){e.scrollbarState.wheeling=!0;var r=e.scrollY+a.event.deltaY;S(t,f,null,r)(e)||(a.event.stopPropagation(),a.event.preventDefault()),e.scrollbarState.wheeling=!1}}).call(m,t,!0),f.attr(\"transform\",function(t){return\"translate(\"+t.size.l+\" \"+t.size.t+\")\"});var b=f.selectAll(\".\"+n.cn.scrollBackground).data(i.repeat,i.keyFun);b.enter().append(\"rect\").classed(n.cn.scrollBackground,!0).attr(\"fill\",\"none\"),b.attr(\"width\",function(t){return t.width}).attr(\"height\",function(t){return t.height}),f.each(function(e){o.setClipUrl(a.select(this),d(t,e),t)});var _=f.selectAll(\".\"+n.cn.yColumn).data(function(t){return t.columns},i.keyFun);_.enter().append(\"g\").classed(n.cn.yColumn,!0),_.exit().remove(),_.attr(\"transform\",function(t){return\"translate(\"+t.x+\" 0)\"}),r&&_.call(a.behavior.drag().origin(function(e){return w(a.select(this),e,-n.uplift),l(this),e.calcdata.columnDragInProgress=!0,m(f.filter(function(t){return e.calcdata.key===t.key}),t),e}).on(\"drag\",function(t){var e=a.select(this),r=function(e){return(t===e?a.event.x:e.x)+e.columnWidth/2};t.x=Math.max(-n.overdrag,Math.min(t.calcdata.width+n.overdrag-t.columnWidth,a.event.x)),v(_).filter(function(e){return e.calcdata.key===t.calcdata.key}).sort(function(t,e){return r(t)-r(e)}).forEach(function(e,r){e.xIndex=r,e.x=t===e?e.x:e.xScale(e)}),_.filter(function(e){return t!==e}).transition().ease(n.transitionEase).duration(n.transitionDuration).attr(\"transform\",function(t){return\"translate(\"+t.x+\" 0)\"}),e.call(c).attr(\"transform\",\"translate(\"+t.x+\" -\"+n.uplift+\" )\")}).on(\"dragend\",function(e){var r=a.select(this),n=e.calcdata;e.x=e.xScale(e),e.calcdata.columnDragInProgress=!1,w(r,e,0),function(t,e,r){var n=e.gdColumnsOriginalOrder;e.gdColumns.sort(function(t,e){return r[n.indexOf(t)]-r[n.indexOf(e)]}),e.columnorder=r,t.emit(\"plotly_restyle\")}(t,n,n.columns.map(function(t){return t.xIndex}))})),_.each(function(e){o.setClipUrl(a.select(this),g(t,e),t)});var M=_.selectAll(\".\"+n.cn.columnBlock).data(h.splitToPanels,i.keyFun);M.enter().append(\"g\").classed(n.cn.columnBlock,!0).attr(\"id\",function(t){return t.key}),M.style(\"cursor\",function(t){return t.dragHandle?\"ew-resize\":t.calcdata.scrollbarState.barWiggleRoom?\"ns-resize\":\"default\"});var E=M.filter(T),L=M.filter(k);r&&L.call(a.behavior.drag().origin(function(t){return a.event.stopPropagation(),t}).on(\"drag\",S(t,f,-1)).on(\"dragend\",function(){})),y(t,f,E,M),y(t,f,L,M);var C=f.selectAll(\".\"+n.cn.scrollAreaClip).data(i.repeat,i.keyFun);C.enter().append(\"clipPath\").classed(n.cn.scrollAreaClip,!0).attr(\"id\",function(e){return d(t,e)});var P=C.selectAll(\".\"+n.cn.scrollAreaClipRect).data(i.repeat,i.keyFun);P.enter().append(\"rect\").classed(n.cn.scrollAreaClipRect,!0).attr(\"x\",-n.overdrag).attr(\"y\",-n.uplift).attr(\"fill\",\"none\"),P.attr(\"width\",function(t){return t.width+2*n.overdrag}).attr(\"height\",function(t){return t.height+n.uplift}),_.selectAll(\".\"+n.cn.columnBoundary).data(i.repeat,i.keyFun).enter().append(\"g\").classed(n.cn.columnBoundary,!0);var O=_.selectAll(\".\"+n.cn.columnBoundaryClippath).data(i.repeat,i.keyFun);O.enter().append(\"clipPath\").classed(n.cn.columnBoundaryClippath,!0),O.attr(\"id\",function(e){return g(t,e)});var z=O.selectAll(\".\"+n.cn.columnBoundaryRect).data(i.repeat,i.keyFun);z.enter().append(\"rect\").classed(n.cn.columnBoundaryRect,!0).attr(\"fill\",\"none\"),z.attr(\"width\",function(t){return t.columnWidth+2*p(t)}).attr(\"height\",function(t){return t.calcdata.height+2*p(t)+n.uplift}).attr(\"x\",function(t){return-p(t)}).attr(\"y\",function(t){return-p(t)}),A(null,L,f)}},{\"../../components/color\":592,\"../../components/drawing\":613,\"../../lib\":717,\"../../lib/gup\":715,\"../../lib/svg_text_utils\":741,\"./constants\":1251,\"./data_preparation_helper\":1252,\"./data_split_helpers\":1253,d3:165}],1257:[function(t,e,r){\"use strict\";var n=t(\"../../plots/template_attributes\").hovertemplateAttrs,a=t(\"../../plots/template_attributes\").texttemplateAttrs,i=t(\"../../components/colorscale/attributes\"),o=t(\"../../plots/domain\").attributes,s=t(\"../pie/attributes\"),l=t(\"../sunburst/attributes\"),c=t(\"./constants\"),u=t(\"../../lib/extend\").extendFlat;e.exports={labels:l.labels,parents:l.parents,values:l.values,branchvalues:l.branchvalues,count:l.count,level:l.level,maxdepth:l.maxdepth,tiling:{packing:{valType:\"enumerated\",values:[\"squarify\",\"binary\",\"dice\",\"slice\",\"slice-dice\",\"dice-slice\"],dflt:\"squarify\",editType:\"plot\"},squarifyratio:{valType:\"number\",min:1,dflt:1,editType:\"plot\"},flip:{valType:\"flaglist\",flags:[\"x\",\"y\"],dflt:\"\",editType:\"plot\"},pad:{valType:\"number\",min:0,dflt:3,editType:\"plot\"},editType:\"calc\"},marker:u({pad:{t:{valType:\"number\",min:0,editType:\"plot\"},l:{valType:\"number\",min:0,editType:\"plot\"},r:{valType:\"number\",min:0,editType:\"plot\"},b:{valType:\"number\",min:0,editType:\"plot\"},editType:\"calc\"},colors:l.marker.colors,depthfade:{valType:\"enumerated\",values:[!0,!1,\"reversed\"],editType:\"style\"},line:l.marker.line,editType:\"calc\"},i(\"marker\",{colorAttr:\"colors\",anim:!1})),pathbar:{visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},side:{valType:\"enumerated\",values:[\"top\",\"bottom\"],dflt:\"top\",editType:\"plot\"},edgeshape:{valType:\"enumerated\",values:[\">\",\"<\",\"|\",\"/\",\"\\\\\"],dflt:\">\",editType:\"plot\"},thickness:{valType:\"number\",min:12,editType:\"plot\"},textfont:u({},s.textfont,{}),editType:\"calc\"},text:s.text,textinfo:l.textinfo,texttemplate:a({editType:\"plot\"},{keys:c.eventDataKeys.concat([\"label\",\"value\"])}),hovertext:s.hovertext,hoverinfo:l.hoverinfo,hovertemplate:n({},{keys:c.eventDataKeys}),textfont:s.textfont,insidetextfont:s.insidetextfont,outsidetextfont:u({},s.outsidetextfont,{}),textposition:{valType:\"enumerated\",values:[\"top left\",\"top center\",\"top right\",\"middle left\",\"middle center\",\"middle right\",\"bottom left\",\"bottom center\",\"bottom right\"],dflt:\"top left\",editType:\"plot\"},domain:o({name:\"treemap\",trace:!0,editType:\"calc\"})}},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plots/domain\":790,\"../../plots/template_attributes\":841,\"../pie/attributes\":1094,\"../sunburst/attributes\":1231,\"./constants\":1260}],1258:[function(t,e,r){\"use strict\";var n=t(\"../../plots/plots\");r.name=\"treemap\",r.plot=function(t,e,a,i){n.plotBasePlot(r.name,t,e,a,i)},r.clean=function(t,e,a,i){n.cleanBasePlot(r.name,t,e,a,i)}},{\"../../plots/plots\":826}],1259:[function(t,e,r){\"use strict\";var n=t(\"../sunburst/calc\");r.calc=function(t,e){return n.calc(t,e)},r.crossTraceCalc=function(t){return n._runCrossTraceCalc(\"treemap\",t)}},{\"../sunburst/calc\":1233}],1260:[function(t,e,r){\"use strict\";e.exports={CLICK_TRANSITION_TIME:750,CLICK_TRANSITION_EASING:\"poly\",eventDataKeys:[\"currentPath\",\"root\",\"entry\",\"percentRoot\",\"percentEntry\",\"percentParent\"],gapWithPathbar:1}},{}],1261:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./attributes\"),i=t(\"../../components/color\"),o=t(\"../../plots/domain\").defaults,s=t(\"../bar/defaults\").handleText,l=t(\"../bar/constants\").TEXTPAD,c=t(\"../../components/colorscale\"),u=c.hasColorscale,h=c.handleDefaults;e.exports=function(t,e,r,c){function f(r,i){return n.coerce(t,e,a,r,i)}var p=f(\"labels\"),d=f(\"parents\");if(p&&p.length&&d&&d.length){var g=f(\"values\");g&&g.length?f(\"branchvalues\"):f(\"count\"),f(\"level\"),f(\"maxdepth\"),\"squarify\"===f(\"tiling.packing\")&&f(\"tiling.squarifyratio\"),f(\"tiling.flip\"),f(\"tiling.pad\");var v=f(\"text\");f(\"texttemplate\"),e.texttemplate||f(\"textinfo\",Array.isArray(v)?\"text+label\":\"label\"),f(\"hovertext\"),f(\"hovertemplate\");var m=f(\"pathbar.visible\");s(t,e,c,f,\"auto\",{hasPathbar:m,moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),f(\"textposition\");var y=-1!==e.textposition.indexOf(\"bottom\");f(\"marker.line.width\")&&f(\"marker.line.color\",c.paper_bgcolor);var x=f(\"marker.colors\"),b=e._hasColorscale=u(t,\"marker\",\"colors\")||(t.marker||{}).coloraxis;b?h(t,e,c,f,{prefix:\"marker.\",cLetter:\"c\"}):f(\"marker.depthfade\",!(x||[]).length);var _=2*e.textfont.size;f(\"marker.pad.t\",y?_/4:_),f(\"marker.pad.l\",_/4),f(\"marker.pad.r\",_/4),f(\"marker.pad.b\",y?_:_/4),b&&h(t,e,c,f,{prefix:\"marker.\",cLetter:\"c\"}),e._hovered={marker:{line:{width:2,color:i.contrast(c.paper_bgcolor)}}},m&&(f(\"pathbar.thickness\",e.pathbar.textfont.size+2*l),f(\"pathbar.side\"),f(\"pathbar.edgeshape\")),o(e,c,f),e._length=null}else e.visible=!1}},{\"../../components/color\":592,\"../../components/colorscale\":604,\"../../lib\":717,\"../../plots/domain\":790,\"../bar/constants\":858,\"../bar/defaults\":860,\"./attributes\":1257}],1262:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\"),i=t(\"../../components/drawing\"),o=t(\"../../lib/svg_text_utils\"),s=t(\"./partition\"),l=t(\"./style\").styleOne,c=t(\"./constants\"),u=t(\"../sunburst/helpers\"),h=t(\"../sunburst/fx\");e.exports=function(t,e,r,f,p){var d=p.barDifY,g=p.width,v=p.height,m=p.viewX,y=p.viewY,x=p.pathSlice,b=p.toMoveInsideSlice,_=p.strTransform,w=p.hasTransition,k=p.handleSlicesExit,T=p.makeUpdateSliceInterpolator,M=p.makeUpdateTextInterpolator,A={},S=t._fullLayout,E=e[0],L=E.trace,C=E.hierarchy,P=g/L._entryDepth,O=u.listPath(r.data,\"id\"),z=s(C.copy(),[g,v],{packing:\"dice\",pad:{inner:0,top:0,left:0,right:0,bottom:0}}).descendants();(z=z.filter(function(t){var e=O.indexOf(t.data.id);return-1!==e&&(t.x0=P*e,t.x1=P*(e+1),t.y0=d,t.y1=d+v,t.onPathbar=!0,!0)})).reverse(),(f=f.data(z,u.getPtId)).enter().append(\"g\").classed(\"pathbar\",!0),k(f,!0,A,[g,v],x),f.order();var I=f;w&&(I=I.transition().each(\"end\",function(){var e=n.select(this);u.setSliceCursor(e,t,{hideOnRoot:!1,hideOnLeaves:!1,isTransitioning:!1})})),I.each(function(s){s._hoverX=m(s.x1-Math.min(g,v)/2),s._hoverY=y(s.y1-v/2);var f=n.select(this),p=a.ensureSingle(f,\"path\",\"surface\",function(t){t.style(\"pointer-events\",\"all\")});w?p.transition().attrTween(\"d\",function(t){var e=T(t,!0,A,[g,v]);return function(t){return x(e(t))}}):p.attr(\"d\",x),f.call(h,r,t,e,{styleOne:l,eventDataKeys:c.eventDataKeys,transitionTime:c.CLICK_TRANSITION_TIME,transitionEasing:c.CLICK_TRANSITION_EASING}).call(u.setSliceCursor,t,{hideOnRoot:!1,hideOnLeaves:!1,isTransitioning:t._transitioning}),p.call(l,s,L,{hovered:!1}),s._text=(u.getPtLabel(s)||\"\").split(\"<br>\").join(\" \")||\"\";var d=a.ensureSingle(f,\"g\",\"slicetext\"),k=a.ensureSingle(d,\"text\",\"\",function(t){t.attr(\"data-notex\",1)}),E=a.ensureUniformFontSize(t,u.determineTextFont(L,s,S.font,{onPathbar:!0}));k.text(s._text||\" \").classed(\"slicetext\",!0).attr(\"text-anchor\",\"start\").call(i.font,E).call(o.convertToTspans,t),s.textBB=i.bBox(k.node()),s.transform=b(s,{fontSize:E.size,onPathbar:!0}),s.transform.fontSize=E.size,w?k.transition().attrTween(\"transform\",function(t){var e=M(t,!0,A,[g,v]);return function(t){return _(e(t))}}):k.attr(\"transform\",_(s))})}},{\"../../components/drawing\":613,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"../sunburst/fx\":1236,\"../sunburst/helpers\":1237,\"./constants\":1260,\"./partition\":1267,\"./style\":1269,d3:165}],1263:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\"),i=t(\"../../components/drawing\"),o=t(\"../../lib/svg_text_utils\"),s=t(\"./partition\"),l=t(\"./style\").styleOne,c=t(\"./constants\"),u=t(\"../sunburst/helpers\"),h=t(\"../sunburst/fx\"),f=t(\"../sunburst/plot\").formatSliceLabel;e.exports=function(t,e,r,p,d){var g=d.width,v=d.height,m=d.viewX,y=d.viewY,x=d.pathSlice,b=d.toMoveInsideSlice,_=d.strTransform,w=d.hasTransition,k=d.handleSlicesExit,T=d.makeUpdateSliceInterpolator,M=d.makeUpdateTextInterpolator,A=d.prevEntry,S=t._fullLayout,E=e[0].trace,L=-1!==E.textposition.indexOf(\"left\"),C=-1!==E.textposition.indexOf(\"right\"),P=-1!==E.textposition.indexOf(\"bottom\"),O=!P&&!E.marker.pad.t||P&&!E.marker.pad.b,z=s(r,[g,v],{packing:E.tiling.packing,squarifyratio:E.tiling.squarifyratio,flipX:E.tiling.flip.indexOf(\"x\")>-1,flipY:E.tiling.flip.indexOf(\"y\")>-1,pad:{inner:E.tiling.pad,top:E.marker.pad.t,left:E.marker.pad.l,right:E.marker.pad.r,bottom:E.marker.pad.b}}).descendants(),I=1/0,D=-1/0;z.forEach(function(t){var e=t.depth;e>=E._maxDepth?(t.x0=t.x1=(t.x0+t.x1)/2,t.y0=t.y1=(t.y0+t.y1)/2):(I=Math.min(I,e),D=Math.max(D,e))}),p=p.data(z,u.getPtId),E._maxVisibleLayers=isFinite(D)?D-I+1:0,p.enter().append(\"g\").classed(\"slice\",!0),k(p,!1,{},[g,v],x),p.order();var R=null;if(w&&A){var F=u.getPtId(A);p.each(function(t){null===R&&u.getPtId(t)===F&&(R={x0:t.x0,x1:t.x1,y0:t.y0,y1:t.y1})})}var B=function(){return R||{x0:0,x1:g,y0:0,y1:v}},N=p;return w&&(N=N.transition().each(\"end\",function(){var e=n.select(this);u.setSliceCursor(e,t,{hideOnRoot:!0,hideOnLeaves:!1,isTransitioning:!1})})),N.each(function(s){var p=u.isHeader(s,E);s._hoverX=m(s.x1-E.marker.pad.r),s._hoverY=y(P?s.y1-E.marker.pad.b/2:s.y0+E.marker.pad.t/2);var d=n.select(this),k=a.ensureSingle(d,\"path\",\"surface\",function(t){t.style(\"pointer-events\",\"all\")});w?k.transition().attrTween(\"d\",function(t){var e=T(t,!1,B(),[g,v]);return function(t){return x(e(t))}}):k.attr(\"d\",x),d.call(h,r,t,e,{styleOne:l,eventDataKeys:c.eventDataKeys,transitionTime:c.CLICK_TRANSITION_TIME,transitionEasing:c.CLICK_TRANSITION_EASING}).call(u.setSliceCursor,t,{isTransitioning:t._transitioning}),k.call(l,s,E,{hovered:!1}),s.x0===s.x1||s.y0===s.y1?s._text=\"\":s._text=p?O?\"\":u.getPtLabel(s)||\"\":f(s,r,E,e,S)||\"\";var A=a.ensureSingle(d,\"g\",\"slicetext\"),z=a.ensureSingle(A,\"text\",\"\",function(t){t.attr(\"data-notex\",1)}),I=a.ensureUniformFontSize(t,u.determineTextFont(E,s,S.font));z.text(s._text||\" \").classed(\"slicetext\",!0).attr(\"text-anchor\",C?\"end\":L||p?\"start\":\"middle\").call(i.font,I).call(o.convertToTspans,t),s.textBB=i.bBox(z.node()),s.transform=b(s,{fontSize:I.size,isHeader:p}),s.transform.fontSize=I.size,w?z.transition().attrTween(\"transform\",function(t){var e=M(t,!1,B(),[g,v]);return function(t){return _(e(t))}}):z.attr(\"transform\",_(s))}),R}},{\"../../components/drawing\":613,\"../../lib\":717,\"../../lib/svg_text_utils\":741,\"../sunburst/fx\":1236,\"../sunburst/helpers\":1237,\"../sunburst/plot\":1241,\"./constants\":1260,\"./partition\":1267,\"./style\":1269,d3:165}],1264:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"treemap\",basePlotModule:t(\"./base_plot\"),categories:[],animatable:!0,attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyDefaults:t(\"./defaults\"),supplyLayoutDefaults:t(\"./layout_defaults\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\"),style:t(\"./style\").style,colorbar:t(\"../scatter/marker_colorbar\"),meta:{}}},{\"../scatter/marker_colorbar\":1138,\"./attributes\":1257,\"./base_plot\":1258,\"./calc\":1259,\"./defaults\":1261,\"./layout_attributes\":1265,\"./layout_defaults\":1266,\"./plot\":1268,\"./style\":1269}],1265:[function(t,e,r){\"use strict\";e.exports={treemapcolorway:{valType:\"colorlist\",editType:\"calc\"},extendtreemapcolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{}],1266:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,i){return n.coerce(t,e,a,r,i)}r(\"treemapcolorway\",e.colorway),r(\"extendtreemapcolors\")}},{\"../../lib\":717,\"./layout_attributes\":1265}],1267:[function(t,e,r){\"use strict\";var n=t(\"d3-hierarchy\");e.exports=function(t,e,r){var a,i=r.flipX,o=r.flipY,s=\"dice-slice\"===r.packing,l=r.pad[o?\"bottom\":\"top\"],c=r.pad[i?\"right\":\"left\"],u=r.pad[i?\"left\":\"right\"],h=r.pad[o?\"top\":\"bottom\"];s&&(a=c,c=l,l=a,a=u,u=h,h=a);var f=n.treemap().tile(function(t,e){switch(t){case\"squarify\":return n.treemapSquarify.ratio(e);case\"binary\":return n.treemapBinary;case\"dice\":return n.treemapDice;case\"slice\":return n.treemapSlice;default:return n.treemapSliceDice}}(r.packing,r.squarifyratio)).paddingInner(r.pad.inner).paddingLeft(c).paddingRight(u).paddingTop(l).paddingBottom(h).size(s?[e[1],e[0]]:e)(t);return(s||i||o)&&function t(e,r,n){var a;n.swapXY&&(a=e.x0,e.x0=e.y0,e.y0=a,a=e.x1,e.x1=e.y1,e.y1=a);n.flipX&&(a=e.x0,e.x0=r[0]-e.x1,e.x1=r[0]-a);n.flipY&&(a=e.y0,e.y0=r[1]-e.y1,e.y1=r[1]-a);var i=e.children;if(i)for(var o=0;o<i.length;o++)t(i[o],r,n)}(f,e,{swapXY:s,flipX:i,flipY:o}),f}},{\"d3-hierarchy\":159}],1268:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../sunburst/helpers\"),i=t(\"../../lib\"),o=t(\"../bar/constants\").TEXTPAD,s=t(\"../bar/plot\").toMoveInsideBar,l=t(\"../bar/uniform_text\"),c=l.recordMinTextSize,u=l.clearMinTextSize,h=t(\"../bar/style\").resizeText,f=t(\"./constants\"),p=t(\"./draw_descendants\"),d=t(\"./draw_ancestors\");function g(t){return a.isHierarchyRoot(t)?\"\":a.getPtId(t)}function v(t,e,r,l){var u=t._fullLayout,h=e[0],v=h.trace,m=h.hierarchy,y=a.findEntryWithLevel(m,v.level),x=n.select(r),b=x.selectAll(\"g.pathbar\"),_=x.selectAll(\"g.slice\");if(!y)return b.remove(),void _.remove();var w=a.isHierarchyRoot(y),k=!u.uniformtext.mode&&a.hasTransition(l),T=a.getMaxDepth(v),M=u._size,A=v.domain,S=M.w*(A.x[1]-A.x[0]),E=M.h*(A.y[1]-A.y[0]),L=S,C=v.pathbar.thickness,P=v.marker.line.width+f.gapWithPathbar,O=v.pathbar.visible?v.pathbar.side.indexOf(\"bottom\")>-1?E+P:-(C+P):0,z={x0:L,x1:L,y0:O,y1:O+C},I=function(t,e,r){var n=v.tiling.pad,a=function(t){return t-n<=e.x0},i=function(t){return t+n>=e.x1},o=function(t){return t-n<=e.y0},s=function(t){return t+n>=e.y1};return{x0:a(t.x0-n)?0:i(t.x0-n)?r[0]:t.x0,x1:a(t.x1+n)?0:i(t.x1+n)?r[0]:t.x1,y0:o(t.y0-n)?0:s(t.y0-n)?r[1]:t.y0,y1:o(t.y1+n)?0:s(t.y1+n)?r[1]:t.y1}},D=null,R={},F={},B=null,N=function(t,e){return e?R[g(t)]:F[g(t)]},j=function(t,e,r,n){if(e)return R[g(m)]||z;var a=F[v.level]||r;return function(t){return t.data.depth-y.data.depth<T}(t)?I(t,a,n):{}};h.hasMultipleRoots&&w&&T++,v._maxDepth=T,v._backgroundColor=u.paper_bgcolor,v._entryDepth=y.data.depth,v._atRootLevel=w;var V=-S/2+M.l+M.w*(A.x[1]+A.x[0])/2,U=-E/2+M.t+M.h*(1-(A.y[1]+A.y[0])/2),q=function(t){return V+t},H=function(t){return U+t},G=H(0),Y=q(0),W=function(t){return Y+t},X=function(t){return G+t};function Z(t,e){return t+\",\"+e}var J=W(0),K=function(t){t.x=Math.max(J,t.x)},Q=v.pathbar.edgeshape,$=function(t,e){var r=t.x0,n=t.x1,a=t.y0,i=t.y1,l=t.textBB,h=function(t){return-1!==v.textposition.indexOf(t)},f=h(\"bottom\"),p=h(\"top\")||e.isHeader&&!f?\"start\":f?\"end\":\"middle\",d=h(\"right\"),g=h(\"left\")||e.onPathbar?-1:d?1:0,m=v.marker.pad;if(e.isHeader){if((r+=m.l-o)>=(n-=m.r-o)){var y=(r+n)/2;r=y,n=y}var x;f?a<(x=i-m.b)&&x<i&&(a=x):a<(x=a+m.t)&&x<i&&(i=x)}var b=s(r,n,a,i,l,{isHorizontal:!1,constrained:!0,angle:0,anchor:p,leftToRight:g});return b.fontSize=e.fontSize,b.targetX=q(b.targetX),b.targetY=H(b.targetY),isNaN(b.targetX)||isNaN(b.targetY)?{}:(r!==n&&a!==i&&c(v.type,b,u),{scale:b.scale,rotate:b.rotate,textX:b.textX,textY:b.textY,anchorX:b.anchorX,anchorY:b.anchorY,targetX:b.targetX,targetY:b.targetY})},tt=function(t,e){for(var r,n=0,a=t;!r&&n<T;)n++,(a=a.parent)?r=N(a,e):n=T;return r||{}},et=function(t,e,r,a){var o,s=N(t,e);if(s)o=s;else if(e)o=z;else if(D)if(t.parent){var l=B||r;l&&!e?o=I(t,l,a):(o={},i.extendFlat(o,tt(t,e)))}else o=t;else o={};return n.interpolate(o,{x0:t.x0,x1:t.x1,y0:t.y0,y1:t.y1})},rt=function(t,e,r,o){var s=N(t,e),l={},h=j(t,e,r,o);i.extendFlat(l,{transform:$({x0:h.x0,x1:h.x1,y0:h.y0,y1:h.y1,textBB:t.textBB,_text:t._text},{isHeader:a.isHeader(t,v)})}),s?l=s:t.parent&&i.extendFlat(l,tt(t,e));var f=t.transform;return t.x0!==t.x1&&t.y0!==t.y1&&c(v.type,f,u),n.interpolate(l,{transform:{scale:f.scale,rotate:f.rotate,textX:f.textX,textY:f.textY,anchorX:f.anchorX,anchorY:f.anchorY,targetX:f.targetX,targetY:f.targetY}})},nt=function(t,e,r,a,i){var o=a[0],s=a[1];k?t.exit().transition().each(function(){var t=n.select(this);t.select(\"path.surface\").transition().attrTween(\"d\",function(t){var r=function(t,e,r,a){var i,o=N(t,e);if(e)i=z;else{var s=N(y,e);i=s?I(t,s,a):{}}return n.interpolate(o,i)}(t,e,0,[o,s]);return function(t){return i(r(t))}}),t.select(\"g.slicetext\").attr(\"opacity\",0)}).remove():t.exit().remove()},at=function(t){var e=t.transform;return t.x0!==t.x1&&t.y0!==t.y1&&c(v.type,e,u),i.getTextTransform({textX:e.textX,textY:e.textY,anchorX:e.anchorX,anchorY:e.anchorY,targetX:e.targetX,targetY:e.targetY,scale:e.scale,rotate:e.rotate})};k&&(b.each(function(t){R[g(t)]={x0:t.x0,x1:t.x1,y0:t.y0,y1:t.y1},t.transform&&(R[g(t)].transform={textX:t.transform.textX,textY:t.transform.textY,anchorX:t.transform.anchorX,anchorY:t.transform.anchorY,targetX:t.transform.targetX,targetY:t.transform.targetY,scale:t.transform.scale,rotate:t.transform.rotate})}),_.each(function(t){F[g(t)]={x0:t.x0,x1:t.x1,y0:t.y0,y1:t.y1},t.transform&&(F[g(t)].transform={textX:t.transform.textX,textY:t.transform.textY,anchorX:t.transform.anchorX,anchorY:t.transform.anchorY,targetX:t.transform.targetX,targetY:t.transform.targetY,scale:t.transform.scale,rotate:t.transform.rotate}),!D&&a.isEntry(t)&&(D=t)})),B=p(t,e,y,_,{width:S,height:E,viewX:q,viewY:H,pathSlice:function(t){var e=q(t.x0),r=q(t.x1),n=H(t.y0),a=H(t.y1),i=r-e,o=a-n;if(!i||!o)return\"\";return\"M\"+Z(e,n+0)+\"L\"+Z(r-0,n)+\"L\"+Z(r,a-0)+\"L\"+Z(e+0,a)+\"Z\"},toMoveInsideSlice:$,prevEntry:D,makeUpdateSliceInterpolator:et,makeUpdateTextInterpolator:rt,handleSlicesExit:nt,hasTransition:k,strTransform:at}),v.pathbar.visible?d(t,e,y,b,{barDifY:O,width:L,height:C,viewX:W,viewY:X,pathSlice:function(t){var e=W(Math.max(Math.min(t.x0,t.x0),0)),r=W(Math.min(Math.max(t.x1,t.x1),L)),n=X(t.y0),a=X(t.y1),i=C/2,o={},s={};o.x=e,s.x=r,o.y=s.y=(n+a)/2;var l={x:e,y:n},c={x:r,y:n},u={x:r,y:a},h={x:e,y:a};return\">\"===Q?(l.x-=i,c.x-=i,u.x-=i,h.x-=i):\"/\"===Q?(u.x-=i,h.x-=i,o.x-=i/2,s.x-=i/2):\"\\\\\"===Q?(l.x-=i,c.x-=i,o.x-=i/2,s.x-=i/2):\"<\"===Q&&(o.x-=i,s.x-=i),K(l),K(h),K(o),K(c),K(u),K(s),\"M\"+Z(l.x,l.y)+\"L\"+Z(c.x,c.y)+\"L\"+Z(s.x,s.y)+\"L\"+Z(u.x,u.y)+\"L\"+Z(h.x,h.y)+\"L\"+Z(o.x,o.y)+\"Z\"},toMoveInsideSlice:$,makeUpdateSliceInterpolator:et,makeUpdateTextInterpolator:rt,handleSlicesExit:nt,hasTransition:k,strTransform:at}):b.remove()}e.exports=function(t,e,r,i){var o,s,l=t._fullLayout,c=l._treemaplayer,f=!r;(u(\"treemap\",l),(o=c.selectAll(\"g.trace.treemap\").data(e,function(t){return t[0].trace.uid})).enter().append(\"g\").classed(\"trace\",!0).classed(\"treemap\",!0),o.order(),!l.uniformtext.mode&&a.hasTransition(r))?(i&&(s=i()),n.transition().duration(r.duration).ease(r.easing).each(\"end\",function(){s&&s()}).each(\"interrupt\",function(){s&&s()}).each(function(){c.selectAll(\"g.trace\").each(function(e){v(t,e,this,r)})})):(o.each(function(e){v(t,e,this,r)}),l.uniformtext.mode&&h(t,l._treemaplayer.selectAll(\".trace\"),\"treemap\"));f&&o.exit().remove()}},{\"../../lib\":717,\"../bar/constants\":858,\"../bar/plot\":867,\"../bar/style\":870,\"../bar/uniform_text\":872,\"../sunburst/helpers\":1237,\"./constants\":1260,\"./draw_ancestors\":1262,\"./draw_descendants\":1263,d3:165}],1269:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../components/color\"),i=t(\"../../lib\"),o=t(\"../sunburst/helpers\"),s=t(\"../bar/uniform_text\").resizeText;function l(t,e,r,n){var s,l,c=(n||{}).hovered,u=e.data.data,h=u.i,f=u.color,p=o.isHierarchyRoot(e),d=1;if(c)s=r._hovered.marker.line.color,l=r._hovered.marker.line.width;else if(p&&\"rgba(0,0,0,0)\"===f)d=0,s=\"rgba(0,0,0,0)\",l=0;else if(s=i.castOption(r,h,\"marker.line.color\")||a.defaultLine,l=i.castOption(r,h,\"marker.line.width\")||0,!r._hasColorscale&&!e.onPathbar){var g=r.marker.depthfade;if(g){var v,m=a.combine(a.addOpacity(r._backgroundColor,.75),f);if(!0===g){var y=o.getMaxDepth(r);v=isFinite(y)?o.isLeaf(e)?0:r._maxVisibleLayers-(e.data.depth-r._entryDepth):e.data.height+1}else v=e.data.depth-r._entryDepth,r._atRootLevel||v++;if(v>0)for(var x=0;x<v;x++){var b=.5*x/v;f=a.combine(a.addOpacity(m,b),f)}}}t.style(\"stroke-width\",l).call(a.fill,f).call(a.stroke,s).style(\"opacity\",d)}e.exports={style:function(t){var e=t._fullLayout._treemaplayer.selectAll(\".trace\");s(t,e,\"treemap\"),e.each(function(t){var e=n.select(this),r=t[0].trace;e.style(\"opacity\",r.opacity),e.selectAll(\"path.surface\").each(function(t){n.select(this).call(l,t,r,{hovered:!1})})})},styleOne:l}},{\"../../components/color\":592,\"../../lib\":717,\"../bar/uniform_text\":872,\"../sunburst/helpers\":1237,d3:165}],1270:[function(t,e,r){\"use strict\";var n=t(\"../box/attributes\"),a=t(\"../../lib/extend\").extendFlat;e.exports={y:n.y,x:n.x,x0:n.x0,y0:n.y0,name:a({},n.name,{}),orientation:a({},n.orientation,{}),bandwidth:{valType:\"number\",min:0,editType:\"calc\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},scalemode:{valType:\"enumerated\",values:[\"width\",\"count\"],dflt:\"width\",editType:\"calc\"},spanmode:{valType:\"enumerated\",values:[\"soft\",\"hard\",\"manual\"],dflt:\"soft\",editType:\"calc\"},span:{valType:\"info_array\",items:[{valType:\"any\",editType:\"calc\"},{valType:\"any\",editType:\"calc\"}],editType:\"calc\"},line:{color:{valType:\"color\",editType:\"style\"},width:{valType:\"number\",min:0,dflt:2,editType:\"style\"},editType:\"plot\"},fillcolor:n.fillcolor,points:a({},n.boxpoints,{}),jitter:a({},n.jitter,{}),pointpos:a({},n.pointpos,{}),width:a({},n.width,{}),marker:n.marker,text:n.text,hovertext:n.hovertext,hovertemplate:n.hovertemplate,box:{visible:{valType:\"boolean\",dflt:!1,editType:\"plot\"},width:{valType:\"number\",min:0,max:1,dflt:.25,editType:\"plot\"},fillcolor:{valType:\"color\",editType:\"style\"},line:{color:{valType:\"color\",editType:\"style\"},width:{valType:\"number\",min:0,editType:\"style\"},editType:\"style\"},editType:\"plot\"},meanline:{visible:{valType:\"boolean\",dflt:!1,editType:\"plot\"},color:{valType:\"color\",editType:\"style\"},width:{valType:\"number\",min:0,editType:\"style\"},editType:\"plot\"},side:{valType:\"enumerated\",values:[\"both\",\"positive\",\"negative\"],dflt:\"both\",editType:\"calc\"},offsetgroup:n.offsetgroup,alignmentgroup:n.alignmentgroup,selected:n.selected,unselected:n.unselected,hoveron:{valType:\"flaglist\",flags:[\"violins\",\"points\",\"kde\"],dflt:\"violins+points+kde\",extras:[\"all\"],editType:\"style\"}}},{\"../../lib/extend\":708,\"../box/attributes\":881}],1271:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/cartesian/axes\"),i=t(\"../box/calc\"),o=t(\"./helpers\"),s=t(\"../../constants/numerical\").BADNUM;function l(t,e,r){var a=e.max-e.min;if(!a)return t.bandwidth?t.bandwidth:0;if(t.bandwidth)return Math.max(t.bandwidth,a/1e4);var i=r.length,o=n.stdev(r,i-1,e.mean);return Math.max(function(t,e,r){return 1.059*Math.min(e,r/1.349)*Math.pow(t,-.2)}(i,o,e.q3-e.q1),a/100)}function c(t,e,r,n){var i,o=t.spanmode,l=t.span||[],c=[e.min,e.max],u=[e.min-2*n,e.max+2*n];function h(n){var a=l[n],i=\"multicategory\"===r.type?r.r2c(a):r.d2c(a,0,t[e.valLetter+\"calendar\"]);return i===s?u[n]:i}var f={type:\"linear\",range:i=\"soft\"===o?u:\"hard\"===o?c:[h(0),h(1)]};return a.setConvert(f),f.cleanRange(),i}e.exports=function(t,e){var r=i(t,e);if(r[0].t.empty)return r;for(var s=t._fullLayout,u=a.getFromId(t,e[\"h\"===e.orientation?\"xaxis\":\"yaxis\"]),h=1/0,f=-1/0,p=0,d=0,g=0;g<r.length;g++){var v=r[g],m=v.pts.map(o.extractVal),y=v.bandwidth=l(e,v,m),x=v.span=c(e,v,u,y);if(v.min===v.max&&0===y)x=v.span=[v.min,v.max],v.density=[{v:1,t:x[0]}],v.bandwidth=y,p=Math.max(p,1);else{var b=x[1]-x[0],_=Math.ceil(b/(y/3)),w=b/_;if(!isFinite(w)||!isFinite(_))return n.error(\"Something went wrong with computing the violin span\"),r[0].t.empty=!0,r;var k=o.makeKDE(v,e,m);v.density=new Array(_);for(var T=0,M=x[0];M<x[1]+w/2;T++,M+=w){var A=k(M);v.density[T]={v:A,t:M},p=Math.max(p,A)}}d=Math.max(d,m.length),h=Math.min(h,x[0]),f=Math.max(f,x[1])}var S=a.findExtremes(u,[h,f],{padded:!0});if(e._extremes[u._id]=S,e.width)r[0].t.maxKDE=p;else{var E=s._violinScaleGroupStats,L=e.scalegroup,C=E[L];C?(C.maxKDE=Math.max(C.maxKDE,p),C.maxCount=Math.max(C.maxCount,d)):E[L]={maxKDE:p,maxCount:d}}return r[0].t.labels.kde=n._(t,\"kde:\"),r}},{\"../../constants/numerical\":693,\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"../box/calc\":882,\"./helpers\":1274}],1272:[function(t,e,r){\"use strict\";var n=t(\"../box/cross_trace_calc\").setPositionOffset,a=[\"v\",\"h\"];e.exports=function(t,e){for(var r=t.calcdata,i=e.xaxis,o=e.yaxis,s=0;s<a.length;s++){for(var l=a[s],c=\"h\"===l?o:i,u=[],h=0;h<r.length;h++){var f=r[h],p=f[0].t,d=f[0].trace;!0!==d.visible||\"violin\"!==d.type||p.empty||d.orientation!==l||d.xaxis!==i._id||d.yaxis!==o._id||u.push(h)}n(\"violin\",t,u,c)}}},{\"../box/cross_trace_calc\":883}],1273:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../components/color\"),i=t(\"../box/defaults\"),o=t(\"./attributes\");e.exports=function(t,e,r,s){function l(r,a){return n.coerce(t,e,o,r,a)}function c(r,a){return n.coerce2(t,e,o,r,a)}if(i.handleSampleDefaults(t,e,l,s),!1!==e.visible){l(\"bandwidth\"),l(\"side\"),l(\"width\")||(l(\"scalegroup\",e.name),l(\"scalemode\"));var u,h=l(\"span\");Array.isArray(h)&&(u=\"manual\"),l(\"spanmode\",u);var f=l(\"line.color\",(t.marker||{}).color||r),p=l(\"line.width\"),d=l(\"fillcolor\",a.addOpacity(e.line.color,.5));i.handlePointsDefaults(t,e,l,{prefix:\"\"});var g=c(\"box.width\"),v=c(\"box.fillcolor\",d),m=c(\"box.line.color\",f),y=c(\"box.line.width\",p);l(\"box.visible\",Boolean(g||v||m||y))||(e.box={visible:!1});var x=c(\"meanline.color\",f),b=c(\"meanline.width\",p);l(\"meanline.visible\",Boolean(x||b))||(e.meanline={visible:!1})}}},{\"../../components/color\":592,\"../../lib\":717,\"../box/defaults\":884,\"./attributes\":1270}],1274:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=function(t){return 1/Math.sqrt(2*Math.PI)*Math.exp(-.5*t*t)};r.makeKDE=function(t,e,r){var n=r.length,i=a,o=t.bandwidth,s=1/(n*o);return function(t){for(var e=0,a=0;a<n;a++)e+=i((t-r[a])/o);return s*e}},r.getPositionOnKdePath=function(t,e,r){var a,i;\"h\"===e.orientation?(a=\"y\",i=\"x\"):(a=\"x\",i=\"y\");var o=n.findPointOnPath(t.path,r,i,{pathLength:t.pathLength}),s=t.posCenterPx,l=o[a];return[l,\"both\"===e.side?2*s-l:s]},r.getKdeValue=function(t,e,n){var a=t.pts.map(r.extractVal);return r.makeKDE(t,e,a)(n)/t.posDensityScale},r.extractVal=function(t){return t.v}},{\"../../lib\":717}],1275:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../../plots/cartesian/axes\"),i=t(\"../box/hover\"),o=t(\"./helpers\");e.exports=function(t,e,r,s,l){var c,u,h=t.cd,f=h[0].trace,p=f.hoveron,d=-1!==p.indexOf(\"violins\"),g=-1!==p.indexOf(\"kde\"),v=[];if(d||g){var m=i.hoverOnBoxes(t,e,r,s);if(g&&m.length>0){var y,x,b,_,w,k=t.xa,T=t.ya;\"h\"===f.orientation?(w=e,y=\"y\",b=T,x=\"x\",_=k):(w=r,y=\"x\",b=k,x=\"y\",_=T);var M=h[t.index];if(w>=M.span[0]&&w<=M.span[1]){var A=n.extendFlat({},t),S=_.c2p(w,!0),E=o.getKdeValue(M,f,w),L=o.getPositionOnKdePath(M,f,S),C=b._offset,P=b._length;A[y+\"0\"]=L[0],A[y+\"1\"]=L[1],A[x+\"0\"]=A[x+\"1\"]=S,A[x+\"Label\"]=x+\": \"+a.hoverLabelText(_,w)+\", \"+h[0].t.labels.kde+\" \"+E.toFixed(3),A.spikeDistance=m[0].spikeDistance;var O=y+\"Spike\";A[O]=m[0][O],m[0].spikeDistance=void 0,m[0][O]=void 0,A.hovertemplate=!1,v.push(A),(u={stroke:t.color})[y+\"1\"]=n.constrain(C+L[0],C,C+P),u[y+\"2\"]=n.constrain(C+L[1],C,C+P),u[x+\"1\"]=u[x+\"2\"]=_._offset+S}}d&&(v=v.concat(m))}-1!==p.indexOf(\"points\")&&(c=i.hoverOnPoints(t,e,r));var z=l.selectAll(\".violinline-\"+f.uid).data(u?[0]:[]);return z.enter().append(\"line\").classed(\"violinline-\"+f.uid,!0).attr(\"stroke-width\",1.5),z.exit().remove(),z.attr(u),\"closest\"===s?c?[c]:v:c?(v.push(c),v):v}},{\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"../box/hover\":886,\"./helpers\":1274}],1276:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyDefaults:t(\"./defaults\"),crossTraceDefaults:t(\"../box/defaults\").crossTraceDefaults,supplyLayoutDefaults:t(\"./layout_defaults\"),calc:t(\"./calc\"),crossTraceCalc:t(\"./cross_trace_calc\"),plot:t(\"./plot\"),style:t(\"./style\"),styleOnSelect:t(\"../scatter/style\").styleOnSelect,hoverPoints:t(\"./hover\"),selectPoints:t(\"../box/select\"),moduleType:\"trace\",name:\"violin\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"cartesian\",\"svg\",\"symbols\",\"oriented\",\"box-violin\",\"showLegend\",\"violinLayout\",\"zoomScale\"],meta:{}}},{\"../../plots/cartesian\":776,\"../box/defaults\":884,\"../box/select\":891,\"../scatter/style\":1143,\"./attributes\":1270,\"./calc\":1271,\"./cross_trace_calc\":1272,\"./defaults\":1273,\"./hover\":1275,\"./layout_attributes\":1277,\"./layout_defaults\":1278,\"./plot\":1279,\"./style\":1280}],1277:[function(t,e,r){\"use strict\";var n=t(\"../box/layout_attributes\"),a=t(\"../../lib\").extendFlat;e.exports={violinmode:a({},n.boxmode,{}),violingap:a({},n.boxgap,{}),violingroupgap:a({},n.boxgroupgap,{})}},{\"../../lib\":717,\"../box/layout_attributes\":888}],1278:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./layout_attributes\"),i=t(\"../box/layout_defaults\");e.exports=function(t,e,r){i._supply(t,e,r,function(r,i){return n.coerce(t,e,a,r,i)},\"violin\")}},{\"../../lib\":717,\"../box/layout_defaults\":889,\"./layout_attributes\":1277}],1279:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\"),i=t(\"../../components/drawing\"),o=t(\"../box/plot\"),s=t(\"../scatter/line_points\"),l=t(\"./helpers\");e.exports=function(t,e,r,c){var u=t._fullLayout,h=e.xaxis,f=e.yaxis;function p(t){var e=s(t,{xaxis:h,yaxis:f,connectGaps:!0,baseTolerance:.75,shape:\"spline\",simplify:!0,linearized:!0});return i.smoothopen(e[0],1)}a.makeTraceGroups(c,r,\"trace violins\").each(function(t){var r=n.select(this),i=t[0],s=i.t,c=i.trace;if(!0!==c.visible||s.empty)r.remove();else{var d=s.bPos,g=s.bdPos,v=e[s.valLetter+\"axis\"],m=e[s.posLetter+\"axis\"],y=\"both\"===c.side,x=y||\"positive\"===c.side,b=y||\"negative\"===c.side,_=r.selectAll(\"path.violin\").data(a.identity);_.enter().append(\"path\").style(\"vector-effect\",\"non-scaling-stroke\").attr(\"class\",\"violin\"),_.exit().remove(),_.each(function(t){var e,r,a,i,o,l,h,f,_=n.select(this),w=t.density,k=w.length,T=m.c2l(t.pos+d,!0),M=m.l2p(T);if(c.width)e=s.maxKDE/g;else{var A=u._violinScaleGroupStats[c.scalegroup];e=\"count\"===c.scalemode?A.maxKDE/g*(A.maxCount/t.pts.length):A.maxKDE/g}if(x){for(h=new Array(k),o=0;o<k;o++)(f=h[o]={})[s.posLetter]=T+w[o].v/e,f[s.valLetter]=v.c2l(w[o].t,!0);r=p(h)}if(b){for(h=new Array(k),l=0,o=k-1;l<k;l++,o--)(f=h[l]={})[s.posLetter]=T-w[o].v/e,f[s.valLetter]=v.c2l(w[o].t,!0);a=p(h)}if(y)i=r+\"L\"+a.substr(1)+\"Z\";else{var S=[M,v.c2p(w[0].t)],E=[M,v.c2p(w[k-1].t)];\"h\"===c.orientation&&(S.reverse(),E.reverse()),i=x?\"M\"+S+\"L\"+r.substr(1)+\"L\"+E:\"M\"+E+\"L\"+a.substr(1)+\"L\"+S}_.attr(\"d\",i),t.posCenterPx=M,t.posDensityScale=e*g,t.path=_.node(),t.pathLength=t.path.getTotalLength()/(y?2:1)});var w,k,T,M=c.box,A=M.width,S=(M.line||{}).width;y?(w=g*A,k=0):x?(w=[0,g*A/2],k=S*{x:1,y:-1}[s.posLetter]):(w=[g*A/2,0],k=S*{x:-1,y:1}[s.posLetter]),o.plotBoxAndWhiskers(r,{pos:m,val:v},c,{bPos:d,bdPos:w,bPosPxOffset:k}),o.plotBoxMean(r,{pos:m,val:v},c,{bPos:d,bdPos:w,bPosPxOffset:k}),!c.box.visible&&c.meanline.visible&&(T=a.identity);var E=r.selectAll(\"path.meanline\").data(T||[]);E.enter().append(\"path\").attr(\"class\",\"meanline\").style(\"fill\",\"none\").style(\"vector-effect\",\"non-scaling-stroke\"),E.exit().remove(),E.each(function(t){var e=v.c2p(t.mean,!0),r=l.getPositionOnKdePath(t,c,e);n.select(this).attr(\"d\",\"h\"===c.orientation?\"M\"+e+\",\"+r[0]+\"V\"+r[1]:\"M\"+r[0]+\",\"+e+\"H\"+r[1])}),o.plotPoints(r,{x:h,y:f},c,s)}})}},{\"../../components/drawing\":613,\"../../lib\":717,\"../box/plot\":890,\"../scatter/line_points\":1134,\"./helpers\":1274,d3:165}],1280:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../components/color\"),i=t(\"../scatter/style\").stylePoints;e.exports=function(t){var e=n.select(t).selectAll(\"g.trace.violins\");e.style(\"opacity\",function(t){return t[0].trace.opacity}),e.each(function(e){var r=e[0].trace,o=n.select(this),s=r.box||{},l=s.line||{},c=r.meanline||{},u=c.width;o.selectAll(\"path.violin\").style(\"stroke-width\",r.line.width+\"px\").call(a.stroke,r.line.color).call(a.fill,r.fillcolor),o.selectAll(\"path.box\").style(\"stroke-width\",l.width+\"px\").call(a.stroke,l.color).call(a.fill,s.fillcolor);var h={\"stroke-width\":u+\"px\",\"stroke-dasharray\":2*u+\"px,\"+u+\"px\"};o.selectAll(\"path.mean\").style(h).call(a.stroke,c.color),o.selectAll(\"path.meanline\").style(h).call(a.stroke,c.color),i(o,r,t)})}},{\"../../components/color\":592,\"../scatter/style\":1143,d3:165}],1281:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/attributes\"),a=t(\"../isosurface/attributes\"),i=t(\"../../plots/attributes\"),o=t(\"../../lib/extend\").extendFlat,s=t(\"../../plot_api/edit_types\").overrideAll,l=e.exports=s(o({x:a.x,y:a.y,z:a.z,value:a.value,isomin:a.isomin,isomax:a.isomax,surface:a.surface,spaceframe:{show:{valType:\"boolean\",dflt:!1},fill:{valType:\"number\",min:0,max:1,dflt:1}},slices:a.slices,caps:a.caps,text:a.text,hovertext:a.hovertext,hovertemplate:a.hovertemplate},n(\"\",{colorAttr:\"`value`\",showScaleDflt:!0,editTypeOverride:\"calc\"}),{colorbar:a.colorbar,opacity:a.opacity,opacityscale:{valType:\"any\",editType:\"calc\"},lightposition:a.lightposition,lighting:a.lighting,flatshading:a.flatshading,contour:a.contour,hoverinfo:o({},i.hoverinfo),showlegend:o({},i.showlegend,{dflt:!1})}),\"calc\",\"nested\");l.x.editType=l.y.editType=l.z.editType=l.value.editType=\"calc+clearAxisTypes\",l.transforms=void 0},{\"../../components/colorscale/attributes\":599,\"../../lib/extend\":708,\"../../plot_api/edit_types\":748,\"../../plots/attributes\":762,\"../isosurface/attributes\":1056}],1282:[function(t,e,r){\"use strict\";var n=t(\"gl-mesh3d\"),a=t(\"../../lib/gl_format_color\").parseColorScale,i=t(\"../../lib/str2rgbarray\"),o=t(\"../../components/colorscale\").extractOpts,s=t(\"../../plots/gl3d/zip3\"),l=t(\"../isosurface/convert\").findNearestOnAxis,c=t(\"../isosurface/convert\").generateIsoMeshes;function u(t,e,r){this.scene=t,this.uid=r,this.mesh=e,this.name=\"\",this.data=null,this.showContour=!1}var h=u.prototype;h.handlePick=function(t){if(t.object===this.mesh){var e=t.data.index,r=this.data._meshX[e],n=this.data._meshY[e],a=this.data._meshZ[e],i=this.data._Ys.length,o=this.data._Zs.length,s=l(r,this.data._Xs).id,c=l(n,this.data._Ys).id,u=l(a,this.data._Zs).id,h=t.index=u+o*c+o*i*s;t.traceCoordinate=[this.data._meshX[h],this.data._meshY[h],this.data._meshZ[h],this.data._value[h]];var f=this.data.hovertext||this.data.text;return Array.isArray(f)&&void 0!==f[h]?t.textLabel=f[h]:f&&(t.textLabel=f),!0}},h.update=function(t){var e=this.scene,r=e.fullSceneLayout;function n(t,e,r,n){return e.map(function(e){return t.d2l(e,0,n)*r})}this.data=c(t);var l={positions:s(n(r.xaxis,t._meshX,e.dataScale[0],t.xcalendar),n(r.yaxis,t._meshY,e.dataScale[1],t.ycalendar),n(r.zaxis,t._meshZ,e.dataScale[2],t.zcalendar)),cells:s(t._meshI,t._meshJ,t._meshK),lightPosition:[t.lightposition.x,t.lightposition.y,t.lightposition.z],ambient:t.lighting.ambient,diffuse:t.lighting.diffuse,specular:t.lighting.specular,roughness:t.lighting.roughness,fresnel:t.lighting.fresnel,vertexNormalsEpsilon:t.lighting.vertexnormalsepsilon,faceNormalsEpsilon:t.lighting.facenormalsepsilon,opacity:t.opacity,opacityscale:t.opacityscale,contourEnable:t.contour.show,contourColor:i(t.contour.color).slice(0,3),contourWidth:t.contour.width,useFacetNormals:t.flatshading},u=o(t);l.vertexIntensity=t._meshIntensity,l.vertexIntensityBounds=[u.min,u.max],l.colormap=a(t),this.mesh.update(l)},h.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()},e.exports=function(t,e){var r=t.glplot.gl,a=n({gl:r}),i=new u(t,a,e.uid);return a._trace=i,i.update(e),t.glplot.add(a),i}},{\"../../components/colorscale\":604,\"../../lib/gl_format_color\":714,\"../../lib/str2rgbarray\":740,\"../../plots/gl3d/zip3\":816,\"../isosurface/convert\":1058,\"gl-mesh3d\":283}],1283:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./attributes\"),i=t(\"../isosurface/defaults\").supplyIsoDefaults;e.exports=function(t,e,r,o){function s(r,i){return n.coerce(t,e,a,r,i)}i(t,e,r,o,s);var l=s(\"opacityscale\");\"max\"===l?e.opacityscale=[[0,.1],[1,1]]:\"min\"===l?e.opacityscale=[[0,1],[1,.1]]:\"extremes\"===l?e.opacityscale=function(t,e){for(var r=[],n=0;n<32;n++){var a=n/31,i=e+(1-e)*(1-Math.pow(Math.sin(t*a*Math.PI),2));r.push([a,Math.max(1,Math.min(0,i))])}return r}(1,.1):function(t){var e=0;if(!Array.isArray(t)||t.length<2)return!1;if(!t[0]||!t[t.length-1])return!1;if(0!=+t[0][0]||1!=+t[t.length-1][0])return!1;for(var r=0;r<t.length;r++){var n=t[r];if(2!==n.length||+n[0]<e)return!1;e=+n[0]}return!0}(l)||(e.opacityscale=void 0)}},{\"../../lib\":717,\"../isosurface/defaults\":1059,\"./attributes\":1281}],1284:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"../isosurface/calc\"),colorbar:{min:\"cmin\",max:\"cmax\"},plot:t(\"./convert\"),moduleType:\"trace\",name:\"volume\",basePlotModule:t(\"../../plots/gl3d\"),categories:[\"gl3d\",\"showLegend\"],meta:{}}},{\"../../plots/gl3d\":805,\"../isosurface/calc\":1057,\"./attributes\":1281,\"./convert\":1282,\"./defaults\":1283}],1285:[function(t,e,r){\"use strict\";var n=t(\"../bar/attributes\"),a=t(\"../scatter/attributes\").line,i=t(\"../../plots/attributes\"),o=t(\"../../plots/template_attributes\").hovertemplateAttrs,s=t(\"../../plots/template_attributes\").texttemplateAttrs,l=t(\"./constants\"),c=t(\"../../lib/extend\").extendFlat,u=t(\"../../components/color\");function h(t){return{marker:{color:c({},n.marker.color,{arrayOk:!1,editType:\"style\"}),line:{color:c({},n.marker.line.color,{arrayOk:!1,editType:\"style\"}),width:c({},n.marker.line.width,{arrayOk:!1,editType:\"style\"}),editType:\"style\"},editType:\"style\"},editType:\"style\"}}e.exports={measure:{valType:\"data_array\",dflt:[],editType:\"calc\"},base:{valType:\"number\",dflt:null,arrayOk:!1,editType:\"calc\"},x:n.x,x0:n.x0,dx:n.dx,y:n.y,y0:n.y0,dy:n.dy,hovertext:n.hovertext,hovertemplate:o({},{keys:l.eventDataKeys}),hoverinfo:c({},i.hoverinfo,{flags:[\"name\",\"x\",\"y\",\"text\",\"initial\",\"delta\",\"final\"]}),textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"initial\",\"delta\",\"final\"],extras:[\"none\"],editType:\"plot\",arrayOk:!1},texttemplate:s({editType:\"plot\"},{keys:l.eventDataKeys.concat([\"label\"])}),text:n.text,textposition:n.textposition,insidetextanchor:n.insidetextanchor,textangle:n.textangle,textfont:n.textfont,insidetextfont:n.insidetextfont,outsidetextfont:n.outsidetextfont,constraintext:n.constraintext,cliponaxis:n.cliponaxis,orientation:n.orientation,offset:n.offset,width:n.width,increasing:h(),decreasing:h(),totals:h(),connector:{line:{color:c({},a.color,{dflt:u.defaultLine}),width:c({},a.width,{editType:\"plot\"}),dash:a.dash,editType:\"plot\"},mode:{valType:\"enumerated\",values:[\"spanning\",\"between\"],dflt:\"between\",editType:\"plot\"},visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},editType:\"plot\"},offsetgroup:n.offsetgroup,alignmentgroup:n.alignmentgroup}},{\"../../components/color\":592,\"../../lib/extend\":708,\"../../plots/attributes\":762,\"../../plots/template_attributes\":841,\"../bar/attributes\":856,\"../scatter/attributes\":1120,\"./constants\":1287}],1286:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\"),a=t(\"../../lib\").mergeArray,i=t(\"../scatter/calc_selection\"),o=t(\"../../constants/numerical\").BADNUM;function s(t){return\"a\"===t||\"absolute\"===t}function l(t){return\"t\"===t||\"total\"===t}e.exports=function(t,e){var r,c,u=n.getFromId(t,e.xaxis||\"x\"),h=n.getFromId(t,e.yaxis||\"y\");\"h\"===e.orientation?(r=u.makeCalcdata(e,\"x\"),c=h.makeCalcdata(e,\"y\")):(r=h.makeCalcdata(e,\"y\"),c=u.makeCalcdata(e,\"x\"));for(var f,p=Math.min(c.length,r.length),d=new Array(p),g=0,v=!1,m=0;m<p;m++){var y=r[m]||0,x=!1;(r[m]!==o||l(e.measure[m])||s(e.measure[m]))&&m+1<p&&(r[m+1]!==o||l(e.measure[m+1])||s(e.measure[m+1]))&&(x=!0);var b=d[m]={i:m,p:c[m],s:y,rawS:y,cNext:x};s(e.measure[m])?(g=b.s,b.isSum=!0,b.dir=\"totals\",b.s=g):l(e.measure[m])?(b.isSum=!0,b.dir=\"totals\",b.s=g):(b.isSum=!1,b.dir=b.rawS<0?\"decreasing\":\"increasing\",f=b.s,b.s=g+f,g+=f),\"totals\"===b.dir&&(v=!0),e.ids&&(b.id=String(e.ids[m])),b.v=(e.base||0)+g}return d.length&&(d[0].hasTotals=v),a(e.text,d,\"tx\"),a(e.hovertext,d,\"htx\"),i(d,e),d}},{\"../../constants/numerical\":693,\"../../lib\":717,\"../../plots/cartesian/axes\":765,\"../scatter/calc_selection\":1122}],1287:[function(t,e,r){\"use strict\";e.exports={eventDataKeys:[\"initial\",\"delta\",\"final\"]}},{}],1288:[function(t,e,r){\"use strict\";var n=t(\"../bar/cross_trace_calc\").setGroupPositions;e.exports=function(t,e){var r,a,i=t._fullLayout,o=t._fullData,s=t.calcdata,l=e.xaxis,c=e.yaxis,u=[],h=[],f=[];for(a=0;a<o.length;a++){var p=o[a];!0===p.visible&&p.xaxis===l._id&&p.yaxis===c._id&&\"waterfall\"===p.type&&(r=s[a],\"h\"===p.orientation?f.push(r):h.push(r),u.push(r))}var d={mode:i.waterfallmode,norm:i.waterfallnorm,gap:i.waterfallgap,groupgap:i.waterfallgroupgap};for(n(t,l,c,h,d),n(t,c,l,f,d),a=0;a<u.length;a++){r=u[a];for(var g=0;g<r.length;g++){var v=r[g];!1===v.isSum&&(v.s0+=0===g?0:r[g-1].s),g+1<r.length&&(r[g].nextP0=r[g+1].p0,r[g].nextS0=r[g+1].s0)}}}},{\"../bar/cross_trace_calc\":859}],1289:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"../bar/defaults\").handleGroupingDefaults,i=t(\"../bar/defaults\").handleText,o=t(\"../scatter/xy_defaults\"),s=t(\"./attributes\"),l=t(\"../../components/color\"),c=t(\"../../constants/delta.js\"),u=c.INCREASING.COLOR,h=c.DECREASING.COLOR,f=\"#4499FF\";function p(t,e,r){t(e+\".marker.color\",r),t(e+\".marker.line.color\",l.defaultLine),t(e+\".marker.line.width\")}e.exports={supplyDefaults:function(t,e,r,a){function l(r,a){return n.coerce(t,e,s,r,a)}if(o(t,e,a,l)){l(\"measure\"),l(\"orientation\",e.x&&!e.y?\"h\":\"v\"),l(\"base\"),l(\"offset\"),l(\"width\"),l(\"text\"),l(\"hovertext\"),l(\"hovertemplate\");var c=l(\"textposition\");i(t,e,a,l,c,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!0,moduleHasCliponaxis:!0,moduleHasTextangle:!0,moduleHasInsideanchor:!0}),\"none\"!==e.textposition&&(l(\"texttemplate\"),e.texttemplate||l(\"textinfo\")),p(l,\"increasing\",u),p(l,\"decreasing\",h),p(l,\"totals\",f),l(\"connector.visible\")&&(l(\"connector.mode\"),l(\"connector.line.width\")&&(l(\"connector.line.color\"),l(\"connector.line.dash\")))}else e.visible=!1},crossTraceDefaults:function(t,e){var r,i;function o(t){return n.coerce(i._input,i,s,t)}if(\"group\"===e.waterfallmode)for(var l=0;l<t.length;l++)r=(i=t[l])._input,a(r,i,e,o)}}},{\"../../components/color\":592,\"../../constants/delta.js\":687,\"../../lib\":717,\"../bar/defaults\":860,\"../scatter/xy_defaults\":1146,\"./attributes\":1285}],1290:[function(t,e,r){\"use strict\";e.exports=function(t,e){return t.x=\"xVal\"in e?e.xVal:e.x,t.y=\"yVal\"in e?e.yVal:e.y,\"initial\"in e&&(t.initial=e.initial),\"delta\"in e&&(t.delta=e.delta),\"final\"in e&&(t.final=e.final),e.xa&&(t.xaxis=e.xa),e.ya&&(t.yaxis=e.ya),t}},{}],1291:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\").hoverLabelText,a=t(\"../../components/color\").opacity,i=t(\"../bar/hover\").hoverOnBars,o=t(\"../../constants/delta.js\"),s=o.INCREASING.SYMBOL,l=o.DECREASING.SYMBOL;e.exports=function(t,e,r,o){var c=i(t,e,r,o);if(c){var u=c.cd,h=u[0].trace,f=\"h\"===h.orientation,p=f?t.xa:t.ya,d=u[c.index],g=d.isSum?d.b+d.s:d.rawS;if(!d.isSum){c.initial=d.b+d.s-g,c.delta=g,c.final=c.initial+c.delta;var v=w(Math.abs(c.delta));c.deltaLabel=g<0?\"(\"+v+\")\":v,c.finalLabel=w(c.final),c.initialLabel=w(c.initial)}var m=d.hi||h.hoverinfo,y=[];if(m&&\"none\"!==m&&\"skip\"!==m){var x=\"all\"===m,b=m.split(\"+\"),_=function(t){return x||-1!==b.indexOf(t)};d.isSum||(!_(\"final\")||_(f?\"x\":\"y\")||y.push(c.finalLabel),_(\"delta\")&&(g<0?y.push(c.deltaLabel+\" \"+l):y.push(c.deltaLabel+\" \"+s)),_(\"initial\")&&y.push(\"Initial: \"+c.initialLabel))}return y.length&&(c.extraText=y.join(\"<br>\")),c.color=function(t,e){var r=t[e.dir].marker,n=r.color,i=r.line.color,o=r.line.width;if(a(n))return n;if(a(i)&&o)return i}(h,d),[c]}function w(t){return n(p,t)}}},{\"../../components/color\":592,\"../../constants/delta.js\":687,\"../../plots/cartesian/axes\":765,\"../bar/hover\":863}],1292:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,crossTraceDefaults:t(\"./defaults\").crossTraceDefaults,supplyLayoutDefaults:t(\"./layout_defaults\"),calc:t(\"./calc\"),crossTraceCalc:t(\"./cross_trace_calc\"),plot:t(\"./plot\"),style:t(\"./style\").style,hoverPoints:t(\"./hover\"),eventData:t(\"./event_data\"),selectPoints:t(\"../bar/select\"),moduleType:\"trace\",name:\"waterfall\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"bar-like\",\"cartesian\",\"svg\",\"oriented\",\"showLegend\",\"zoomScale\"],meta:{}}},{\"../../plots/cartesian\":776,\"../bar/select\":868,\"./attributes\":1285,\"./calc\":1286,\"./cross_trace_calc\":1288,\"./defaults\":1289,\"./event_data\":1290,\"./hover\":1291,\"./layout_attributes\":1293,\"./layout_defaults\":1294,\"./plot\":1295,\"./style\":1296}],1293:[function(t,e,r){\"use strict\";e.exports={waterfallmode:{valType:\"enumerated\",values:[\"group\",\"overlay\"],dflt:\"group\",editType:\"calc\"},waterfallgap:{valType:\"number\",min:0,max:1,editType:\"calc\"},waterfallgroupgap:{valType:\"number\",min:0,max:1,dflt:0,editType:\"calc\"}}},{}],1294:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./layout_attributes\");e.exports=function(t,e,r){var i=!1;function o(r,i){return n.coerce(t,e,a,r,i)}for(var s=0;s<r.length;s++){var l=r[s];if(l.visible&&\"waterfall\"===l.type){i=!0;break}}i&&(o(\"waterfallmode\"),o(\"waterfallgap\",.2),o(\"waterfallgroupgap\"))}},{\"../../lib\":717,\"./layout_attributes\":1293}],1295:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\"),i=t(\"../../components/drawing\"),o=t(\"../bar/plot\"),s=t(\"../bar/uniform_text\").clearMinTextSize;e.exports=function(t,e,r,l){var c=t._fullLayout;s(\"waterfall\",c),o.plot(t,e,r,l,{mode:c.waterfallmode,norm:c.waterfallmode,gap:c.waterfallgap,groupgap:c.waterfallgroupgap}),function(t,e,r,o){var s=e.xaxis,l=e.yaxis;a.makeTraceGroups(o,r,\"trace bars\").each(function(r){var o=n.select(this),c=r[0].trace,u=a.ensureSingle(o,\"g\",\"lines\");if(c.connector&&c.connector.visible){var h=\"h\"===c.orientation,f=c.connector.mode,p=u.selectAll(\"g.line\").data(a.identity);p.enter().append(\"g\").classed(\"line\",!0),p.exit().remove();var d=p.size();p.each(function(r,o){if(o===d-1||r.cNext){var c=function(t,e,r,n){var a=[],i=[],o=n?e:r,s=n?r:e;return a[0]=o.c2p(t.s0,!0),i[0]=s.c2p(t.p0,!0),a[1]=o.c2p(t.s1,!0),i[1]=s.c2p(t.p1,!0),a[2]=o.c2p(t.nextS0,!0),i[2]=s.c2p(t.nextP0,!0),n?[a,i]:[i,a]}(r,s,l,h),u=c[0],p=c[1],g=\"\";\"spanning\"===f&&!r.isSum&&o>0&&(g+=h?\"M\"+u[0]+\",\"+p[1]+\"V\"+p[0]:\"M\"+u[1]+\",\"+p[0]+\"H\"+u[0]),\"between\"!==f&&(r.isSum||o<d-1)&&(g+=h?\"M\"+u[1]+\",\"+p[0]+\"V\"+p[1]:\"M\"+u[0]+\",\"+p[1]+\"H\"+u[1]),void 0!==u[2]&&void 0!==p[2]&&(g+=h?\"M\"+u[1]+\",\"+p[1]+\"V\"+p[2]:\"M\"+u[1]+\",\"+p[1]+\"H\"+u[2]),\"\"===g&&(g=\"M0,0Z\"),a.ensureSingle(n.select(this),\"path\").attr(\"d\",g).call(i.setClipUrl,e.layerClipId,t)}})}else u.remove()})}(t,e,r,l)}},{\"../../components/drawing\":613,\"../../lib\":717,\"../bar/plot\":867,\"../bar/uniform_text\":872,d3:165}],1296:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../components/drawing\"),i=t(\"../../components/color\"),o=t(\"../../constants/interactions\").DESELECTDIM,s=t(\"../bar/style\"),l=t(\"../bar/uniform_text\").resizeText,c=s.styleTextPoints;e.exports={style:function(t,e,r){var s=r||n.select(t).selectAll(\"g.waterfalllayer\").selectAll(\"g.trace\");l(t,s,\"waterfall\"),s.style(\"opacity\",function(t){return t[0].trace.opacity}),s.each(function(e){var r=n.select(this),s=e[0].trace;r.selectAll(\".point > path\").each(function(t){if(!t.isBlank){var e=s[t.dir].marker;n.select(this).call(i.fill,e.color).call(i.stroke,e.line.color).call(a.dashLine,e.line.dash,e.line.width).style(\"opacity\",s.selectedpoints&&!t.selected?o:1)}}),c(r,s,t),r.selectAll(\".lines\").each(function(){var t=s.connector.line;a.lineGroupStyle(n.select(this).selectAll(\"path\"),t.width,t.color,t.dash)})})}}},{\"../../components/color\":592,\"../../components/drawing\":613,\"../../constants/interactions\":692,\"../bar/style\":870,\"../bar/uniform_text\":872,d3:165}],1297:[function(t,e,r){\"use strict\";var n=t(\"../plots/cartesian/axes\"),a=t(\"../lib\"),i=t(\"../plot_api/plot_schema\"),o=t(\"./helpers\").pointsAccessorFunction,s=t(\"../constants/numerical\").BADNUM;r.moduleType=\"transform\",r.name=\"aggregate\";var l=r.attributes={enabled:{valType:\"boolean\",dflt:!0,editType:\"calc\"},groups:{valType:\"string\",strict:!0,noBlank:!0,arrayOk:!0,dflt:\"x\",editType:\"calc\"},aggregations:{_isLinkedToArray:\"aggregation\",target:{valType:\"string\",editType:\"calc\"},func:{valType:\"enumerated\",values:[\"count\",\"sum\",\"avg\",\"median\",\"mode\",\"rms\",\"stddev\",\"min\",\"max\",\"first\",\"last\",\"change\",\"range\"],dflt:\"first\",editType:\"calc\"},funcmode:{valType:\"enumerated\",values:[\"sample\",\"population\"],dflt:\"sample\",editType:\"calc\"},enabled:{valType:\"boolean\",dflt:!0,editType:\"calc\"},editType:\"calc\"},editType:\"calc\"},c=l.aggregations;function u(t,e,r,i){if(i.enabled){for(var o=i.target,l=a.nestedProperty(e,o),c=l.get(),u=function(t,e){var r=t.func,n=e.d2c,a=e.c2d;switch(r){case\"count\":return h;case\"first\":return f;case\"last\":return p;case\"sum\":return function(t,e){for(var r=0,i=0;i<e.length;i++){var o=n(t[e[i]]);o!==s&&(r+=o)}return a(r)};case\"avg\":return function(t,e){for(var r=0,i=0,o=0;o<e.length;o++){var l=n(t[e[o]]);l!==s&&(r+=l,i++)}return i?a(r/i):s};case\"min\":return function(t,e){for(var r=1/0,i=0;i<e.length;i++){var o=n(t[e[i]]);o!==s&&(r=Math.min(r,o))}return r===1/0?s:a(r)};case\"max\":return function(t,e){for(var r=-1/0,i=0;i<e.length;i++){var o=n(t[e[i]]);o!==s&&(r=Math.max(r,o))}return r===-1/0?s:a(r)};case\"range\":return function(t,e){for(var r=1/0,i=-1/0,o=0;o<e.length;o++){var l=n(t[e[o]]);l!==s&&(r=Math.min(r,l),i=Math.max(i,l))}return i===-1/0||r===1/0?s:a(i-r)};case\"change\":return function(t,e){var r=n(t[e[0]]),i=n(t[e[e.length-1]]);return r===s||i===s?s:a(i-r)};case\"median\":return function(t,e){for(var r=[],i=0;i<e.length;i++){var o=n(t[e[i]]);o!==s&&r.push(o)}if(!r.length)return s;r.sort();var l=(r.length-1)/2;return a((r[Math.floor(l)]+r[Math.ceil(l)])/2)};case\"mode\":return function(t,e){for(var r={},i=0,o=s,l=0;l<e.length;l++){var c=n(t[e[l]]);if(c!==s){var u=r[c]=(r[c]||0)+1;u>i&&(i=u,o=c)}}return i?a(o):s};case\"rms\":return function(t,e){for(var r=0,i=0,o=0;o<e.length;o++){var l=n(t[e[o]]);l!==s&&(r+=l*l,i++)}return i?a(Math.sqrt(r/i)):s};case\"stddev\":return function(e,r){var a,i=0,o=0,l=1,c=s;for(a=0;a<r.length&&c===s;a++)c=n(e[r[a]]);if(c===s)return s;for(;a<r.length;a++){var u=n(e[r[a]]);if(u!==s){var h=u-c;i+=h,o+=h*h,l++}}var f=\"sample\"===t.funcmode?l-1:l;return f?Math.sqrt((o-i*i/l)/f):0}}}(i,n.getDataConversions(t,e,o,c)),d=new Array(r.length),g=0;g<r.length;g++)d[g]=u(c,r[g]);l.set(d),\"count\"===i.func&&a.pushUnique(e._arrayAttrs,o)}}function h(t,e){return e.length}function f(t,e){return t[e[0]]}function p(t,e){return t[e[e.length-1]]}r.supplyDefaults=function(t,e){var r,n={};function o(e,r){return a.coerce(t,n,l,e,r)}if(!o(\"enabled\"))return n;var s=i.findArrayAttributes(e),u={};for(r=0;r<s.length;r++)u[s[r]]=1;var h=o(\"groups\");if(!Array.isArray(h)){if(!u[h])return n.enabled=!1,n;u[h]=0}var f,p=t.aggregations||[],d=n.aggregations=new Array(p.length);function g(t,e){return a.coerce(p[r],f,c,t,e)}for(r=0;r<p.length;r++){f={_index:r};var v=g(\"target\"),m=g(\"func\");g(\"enabled\")&&v&&(u[v]||\"count\"===m&&void 0===u[v])?(\"stddev\"===m&&g(\"funcmode\"),u[v]=0,d[r]=f):d[r]={enabled:!1,_index:r}}for(r=0;r<s.length;r++)u[s[r]]&&d.push({target:s[r],func:c.func.dflt,enabled:!0,_index:-1});return n},r.calcTransform=function(t,e,r){if(r.enabled){var n=r.groups,i=a.getTargetArray(e,{target:n});if(i){var s,l,c,h,f={},p={},d=[],g=o(e.transforms,r),v=i.length;for(e._length&&(v=Math.min(v,e._length)),s=0;s<v;s++)void 0===(c=f[l=i[s]])?(f[l]=d.length,h=[s],d.push(h),p[f[l]]=g(s)):(d[c].push(s),p[f[l]]=(p[f[l]]||[]).concat(g(s)));r._indexToPoints=p;var m=r.aggregations;for(s=0;s<m.length;s++)u(t,e,d,m[s]);\"string\"==typeof n&&u(t,e,d,{target:n,func:\"first\",enabled:!0}),e._length=d.length}}}},{\"../constants/numerical\":693,\"../lib\":717,\"../plot_api/plot_schema\":754,\"../plots/cartesian/axes\":765,\"./helpers\":1300}],1298:[function(t,e,r){\"use strict\";var n=t(\"../lib\"),a=t(\"../registry\"),i=t(\"../plots/cartesian/axes\"),o=t(\"./helpers\").pointsAccessorFunction,s=t(\"../constants/filter_ops\"),l=s.COMPARISON_OPS,c=s.INTERVAL_OPS,u=s.SET_OPS;r.moduleType=\"transform\",r.name=\"filter\",r.attributes={enabled:{valType:\"boolean\",dflt:!0,editType:\"calc\"},target:{valType:\"string\",strict:!0,noBlank:!0,arrayOk:!0,dflt:\"x\",editType:\"calc\"},operation:{valType:\"enumerated\",values:[].concat(l).concat(c).concat(u),dflt:\"=\",editType:\"calc\"},value:{valType:\"any\",dflt:0,editType:\"calc\"},preservegaps:{valType:\"boolean\",dflt:!1,editType:\"calc\"},editType:\"calc\"},r.supplyDefaults=function(t){var e={};function i(a,i){return n.coerce(t,e,r.attributes,a,i)}if(i(\"enabled\")){var o=i(\"target\");if(n.isArrayOrTypedArray(o)&&0===o.length)return e.enabled=!1,e;i(\"preservegaps\"),i(\"operation\"),i(\"value\");var s=a.getComponentMethod(\"calendars\",\"handleDefaults\");s(t,e,\"valuecalendar\",null),s(t,e,\"targetcalendar\",null)}return e},r.calcTransform=function(t,e,r){if(r.enabled){var a=n.getTargetArray(e,r);if(a){var s=r.target,h=a.length;e._length&&(h=Math.min(h,e._length));var f=r.targetcalendar,p=e._arrayAttrs,d=r.preservegaps;if(\"string\"==typeof s){var g=n.nestedProperty(e,s+\"calendar\").get();g&&(f=g)}var v,m,y=function(t,e,r){var n=t.operation,a=t.value,i=Array.isArray(a);function o(t){return-1!==t.indexOf(n)}var s,h=function(r){return e(r,0,t.valuecalendar)},f=function(t){return e(t,0,r)};o(l)?s=h(i?a[0]:a):o(c)?s=i?[h(a[0]),h(a[1])]:[h(a),h(a)]:o(u)&&(s=i?a.map(h):[h(a)]);switch(n){case\"=\":return function(t){return f(t)===s};case\"!=\":return function(t){return f(t)!==s};case\"<\":return function(t){return f(t)<s};case\"<=\":return function(t){return f(t)<=s};case\">\":return function(t){return f(t)>s};case\">=\":return function(t){return f(t)>=s};case\"[]\":return function(t){var e=f(t);return e>=s[0]&&e<=s[1]};case\"()\":return function(t){var e=f(t);return e>s[0]&&e<s[1]};case\"[)\":return function(t){var e=f(t);return e>=s[0]&&e<s[1]};case\"(]\":return function(t){var e=f(t);return e>s[0]&&e<=s[1]};case\"][\":return function(t){var e=f(t);return e<=s[0]||e>=s[1]};case\")(\":return function(t){var e=f(t);return e<s[0]||e>s[1]};case\"](\":return function(t){var e=f(t);return e<=s[0]||e>s[1]};case\")[\":return function(t){var e=f(t);return e<s[0]||e>=s[1]};case\"{}\":return function(t){return-1!==s.indexOf(f(t))};case\"}{\":return function(t){return-1===s.indexOf(f(t))}}}(r,i.getDataToCoordFunc(t,e,s,a),f),x={},b={},_=0;d?(v=function(t){x[t.astr]=n.extendDeep([],t.get()),t.set(new Array(h))},m=function(t,e){var r=x[t.astr][e];t.get()[e]=r}):(v=function(t){x[t.astr]=n.extendDeep([],t.get()),t.set([])},m=function(t,e){var r=x[t.astr][e];t.get().push(r)}),T(v);for(var w=o(e.transforms,r),k=0;k<h;k++){y(a[k])?(T(m,k),b[_++]=w(k)):d&&_++}r._indexToPoints=b,e._length=_}}function T(t,r){for(var a=0;a<p.length;a++){t(n.nestedProperty(e,p[a]),r)}}}},{\"../constants/filter_ops\":689,\"../lib\":717,\"../plots/cartesian/axes\":765,\"../registry\":846,\"./helpers\":1300}],1299:[function(t,e,r){\"use strict\";var n=t(\"../lib\"),a=t(\"../plot_api/plot_schema\"),i=t(\"../plots/plots\"),o=t(\"./helpers\").pointsAccessorFunction;function s(t,e){var r,s,l,c,u,h,f,p,d,g,v=e.transform,m=e.transformIndex,y=t.transforms[m].groups,x=o(t.transforms,v);if(!n.isArrayOrTypedArray(y)||0===y.length)return[t];var b=n.filterUnique(y),_=new Array(b.length),w=y.length,k=a.findArrayAttributes(t),T=v.styles||[],M={};for(r=0;r<T.length;r++)M[T[r].target]=T[r].value;v.styles&&(g=n.keyedContainer(v,\"styles\",\"target\",\"value.name\"));var A={},S={};for(r=0;r<b.length;r++){A[h=b[r]]=r,S[h]=0,(f=_[r]=n.extendDeepNoArrays({},t))._group=h,f.transforms[m]._indexToPoints={};var E=null;for(g&&(E=g.get(h)),f.name=E||\"\"===E?E:n.templateString(v.nameformat,{trace:t.name,group:h}),p=f.transforms,f.transforms=[],s=0;s<p.length;s++)f.transforms[s]=n.extendDeepNoArrays({},p[s]);for(s=0;s<k.length;s++)n.nestedProperty(f,k[s]).set([])}for(l=0;l<k.length;l++){for(c=k[l],s=0,d=[];s<b.length;s++)d[s]=n.nestedProperty(_[s],c).get();for(u=n.nestedProperty(t,c).get(),s=0;s<w;s++)d[A[y[s]]].push(u[s])}for(s=0;s<w;s++){(f=_[A[y[s]]]).transforms[m]._indexToPoints[S[y[s]]]=x(s),S[y[s]]++}for(r=0;r<b.length;r++)h=b[r],f=_[r],i.clearExpandedTraceDefaultColors(f),f=n.extendDeepNoArrays(f,M[h]||{});return _}r.moduleType=\"transform\",r.name=\"groupby\",r.attributes={enabled:{valType:\"boolean\",dflt:!0,editType:\"calc\"},groups:{valType:\"data_array\",dflt:[],editType:\"calc\"},nameformat:{valType:\"string\",editType:\"calc\"},styles:{_isLinkedToArray:\"style\",target:{valType:\"string\",editType:\"calc\"},value:{valType:\"any\",dflt:{},editType:\"calc\",_compareAsJSON:!0},editType:\"calc\"},editType:\"calc\"},r.supplyDefaults=function(t,e,a){var i,o={};function s(e,a){return n.coerce(t,o,r.attributes,e,a)}if(!s(\"enabled\"))return o;s(\"groups\"),s(\"nameformat\",a._dataLength>1?\"%{group} (%{trace})\":\"%{group}\");var l=t.styles,c=o.styles=[];if(l)for(i=0;i<l.length;i++){var u=c[i]={};n.coerce(l[i],c[i],r.attributes.styles,\"target\");var h=n.coerce(l[i],c[i],r.attributes.styles,\"value\");n.isPlainObject(h)?u.value=n.extendDeep({},h):h&&delete u.value}return o},r.transform=function(t,e){var r,n,a,i=[];for(n=0;n<t.length;n++)for(r=s(t[n],e),a=0;a<r.length;a++)i.push(r[a]);return i}},{\"../lib\":717,\"../plot_api/plot_schema\":754,\"../plots/plots\":826,\"./helpers\":1300}],1300:[function(t,e,r){\"use strict\";r.pointsAccessorFunction=function(t,e){for(var r,n,a=0;a<t.length&&(r=t[a])!==e;a++)r._indexToPoints&&!1!==r.enabled&&(n=r._indexToPoints);return n?function(t){return n[t]}:function(t){return[t]}}},{}],1301:[function(t,e,r){\"use strict\";var n=t(\"../lib\"),a=t(\"../plots/cartesian/axes\"),i=t(\"./helpers\").pointsAccessorFunction;r.moduleType=\"transform\",r.name=\"sort\",r.attributes={enabled:{valType:\"boolean\",dflt:!0,editType:\"calc\"},target:{valType:\"string\",strict:!0,noBlank:!0,arrayOk:!0,dflt:\"x\",editType:\"calc\"},order:{valType:\"enumerated\",values:[\"ascending\",\"descending\"],dflt:\"ascending\",editType:\"calc\"},editType:\"calc\"},r.supplyDefaults=function(t){var e={};function a(a,i){return n.coerce(t,e,r.attributes,a,i)}return a(\"enabled\")&&(a(\"target\"),a(\"order\")),e},r.calcTransform=function(t,e,r){if(r.enabled){var o=n.getTargetArray(e,r);if(o){var s=r.target,l=o.length;e._length&&(l=Math.min(l,e._length));var c,u,h=e._arrayAttrs,f=function(t,e,r,n){var a,i=new Array(n),o=new Array(n);for(a=0;a<n;a++)i[a]={v:e[a],i:a};for(i.sort(function(t,e){switch(t.order){case\"ascending\":return function(t,r){return e(t.v)-e(r.v)};case\"descending\":return function(t,r){return e(r.v)-e(t.v)}}}(t,r)),a=0;a<n;a++)o[a]=i[a].i;return o}(r,o,a.getDataToCoordFunc(t,e,s,o),l),p=i(e.transforms,r),d={};for(c=0;c<h.length;c++){var g=n.nestedProperty(e,h[c]),v=g.get(),m=new Array(l);for(u=0;u<l;u++)m[u]=v[f[u]];g.set(m)}for(u=0;u<l;u++)d[u]=p(f[u]);r._indexToPoints=d,e._length=l}}}},{\"../lib\":717,\"../plots/cartesian/axes\":765,\"./helpers\":1300}]},{},[26])(26)});\n",
+       "        });\n",
+       "        require(['plotly'], function(Plotly) {\n",
+       "            window._Plotly = Plotly;\n",
+       "        });\n",
+       "        }\n",
+       "        </script>\n",
+       "        "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "linkText": "Export to plot.ly",
+        "plotlyServerURL": "https://plot.ly",
+        "showLink": false
+       },
+       "data": [
+        {
+         "colorscale": [
+          [
+           0,
+           "#00083e"
+          ],
+          [
+           0.5,
+           "#ededee"
+          ],
+          [
+           1,
+           "#ffffff"
+          ]
+         ],
+         "hoverinfo": "none",
+         "opacity": 0.75,
+         "showscale": false,
+         "type": "heatmap",
+         "z": [
+          [
+           0,
+           0,
+           0,
+           0
+          ],
+          [
+           0.5,
+           0.5,
+           0.5,
+           0.5
+          ],
+          [
+           1,
+           1,
+           1,
+           1
+          ],
+          [
+           0.5,
+           0.5,
+           0.5,
+           0.5
+          ],
+          [
+           1,
+           1,
+           1,
+           1
+          ],
+          [
+           0.5,
+           0.5,
+           0.5,
+           0.5
+          ],
+          [
+           1,
+           1,
+           1,
+           1
+          ],
+          [
+           0.5,
+           0.5,
+           0.5,
+           0.5
+          ],
+          [
+           1,
+           1,
+           1,
+           1
+          ],
+          [
+           0.5,
+           0.5,
+           0.5,
+           0.5
+          ],
+          [
+           1,
+           1,
+           1,
+           1
+          ],
+          [
+           0.5,
+           0.5,
+           0.5,
+           0.5
+          ],
+          [
+           1,
+           1,
+           1,
+           1
+          ],
+          [
+           0.5,
+           0.5,
+           0.5,
+           0.5
+          ],
+          [
+           1,
+           1,
+           1,
+           1
+          ],
+          [
+           0.5,
+           0.5,
+           0.5,
+           0.5
+          ],
+          [
+           1,
+           1,
+           1,
+           1
+          ],
+          [
+           0.5,
+           0.5,
+           0.5,
+           0.5
+          ],
+          [
+           1,
+           1,
+           1,
+           1
+          ],
+          [
+           0.5,
+           0.5,
+           0.5,
+           0.5
+          ],
+          [
+           1,
+           1,
+           1,
+           1
+          ],
+          [
+           0.5,
+           0.5,
+           0.5,
+           0.5
+          ]
+         ]
+        }
+       ],
+       "layout": {
+        "annotations": [
+         {
+          "align": "left",
+          "font": {
+           "color": "#ffffff"
+          },
+          "showarrow": false,
+          "text": "<b>School</b>",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 0,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#ffffff"
+          },
+          "showarrow": false,
+          "text": "<b>Women</b>",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 0,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#ffffff"
+          },
+          "showarrow": false,
+          "text": "<b>Men</b>",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 0,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#ffffff"
+          },
+          "showarrow": false,
+          "text": "<b>Gap</b>",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 0,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "MIT",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 1,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "94",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 1,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "152",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 1,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "58",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 1,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "Stanford",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 2,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "96",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 2,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "151",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 2,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "55",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 2,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "Harvard",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 3,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "112",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 3,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "165",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 3,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "53",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 3,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "U.Penn",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 4,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "92",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 4,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "141",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 4,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "49",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 4,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "Princeton",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 5,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "90",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 5,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "137",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 5,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "47",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 5,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "Chicago",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 6,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "78",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 6,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "118",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 6,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "40",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 6,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "Georgetown",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 7,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "94",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 7,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "131",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 7,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "37",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 7,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "Tufts",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 8,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "76",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 8,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "112",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 8,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "36",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 8,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "Yale",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 9,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "79",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 9,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "114",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 9,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "35",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 9,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "Columbia",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 10,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "86",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 10,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "119",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 10,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "33",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 10,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "Duke",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 11,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "93",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 11,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "124",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 11,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "31",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 11,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "Dartmouth",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 12,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "84",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 12,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "114",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 12,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "30",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 12,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "NYU",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 13,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "67",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 13,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "94",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 13,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "27",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 13,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "Notre Dame",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 14,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "73",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 14,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "100",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 14,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "27",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 14,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "Cornell",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 15,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "80",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 15,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "107",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 15,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "27",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 15,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "Michigan",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 16,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "62",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 16,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "84",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 16,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "22",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 16,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "Brown",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 17,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "72",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 17,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "92",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 17,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "20",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 17,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "Berkeley",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 18,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "71",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 18,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "88",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 18,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "17",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 18,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "Emory",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 19,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "68",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 19,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "82",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 19,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "14",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 19,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "UCLA",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 20,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "64",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 20,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "78",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 20,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "14",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 20,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "SoCal",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 21,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "72",
+          "x": 0.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 21,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "81",
+          "x": 1.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 21,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
+          },
+          "showarrow": false,
+          "text": "9",
+          "x": 2.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 21,
+          "yref": "y"
+         }
+        ],
+        "height": 710,
+        "margin": {
+         "b": 0,
+         "l": 0,
+         "r": 0,
+         "t": 0
+        },
+        "template": {
+         "data": {
+          "bar": [
+           {
+            "error_x": {
+             "color": "#2a3f5f"
+            },
+            "error_y": {
+             "color": "#2a3f5f"
+            },
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             }
+            },
+            "type": "bar"
+           }
+          ],
+          "barpolar": [
+           {
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             }
+            },
+            "type": "barpolar"
+           }
+          ],
+          "carpet": [
+           {
+            "aaxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "baxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "type": "carpet"
+           }
+          ],
+          "choropleth": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "choropleth"
+           }
+          ],
+          "contour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "contour"
+           }
+          ],
+          "contourcarpet": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "contourcarpet"
+           }
+          ],
+          "heatmap": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmap"
+           }
+          ],
+          "heatmapgl": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmapgl"
+           }
+          ],
+          "histogram": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "histogram"
+           }
+          ],
+          "histogram2d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "histogram2d"
+           }
+          ],
+          "histogram2dcontour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "histogram2dcontour"
+           }
+          ],
+          "mesh3d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "mesh3d"
+           }
+          ],
+          "parcoords": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "parcoords"
+           }
+          ],
+          "pie": [
+           {
+            "automargin": true,
+            "type": "pie"
+           }
+          ],
+          "scatter": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatter"
+           }
+          ],
+          "scatter3d": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatter3d"
+           }
+          ],
+          "scattercarpet": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattercarpet"
+           }
+          ],
+          "scattergeo": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergeo"
+           }
+          ],
+          "scattergl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergl"
+           }
+          ],
+          "scattermapbox": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattermapbox"
+           }
+          ],
+          "scatterpolar": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterpolar"
+           }
+          ],
+          "scatterpolargl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterpolargl"
+           }
+          ],
+          "scatterternary": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterternary"
+           }
+          ],
+          "surface": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "surface"
+           }
+          ],
+          "table": [
+           {
+            "cells": {
+             "fill": {
+              "color": "#EBF0F8"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "header": {
+             "fill": {
+              "color": "#C8D4E3"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "type": "table"
+           }
+          ]
+         },
+         "layout": {
+          "annotationdefaults": {
+           "arrowcolor": "#2a3f5f",
+           "arrowhead": 0,
+           "arrowwidth": 1
+          },
+          "coloraxis": {
+           "colorbar": {
+            "outlinewidth": 0,
+            "ticks": ""
+           }
+          },
+          "colorscale": {
+           "diverging": [
+            [
+             0,
+             "#8e0152"
+            ],
+            [
+             0.1,
+             "#c51b7d"
+            ],
+            [
+             0.2,
+             "#de77ae"
+            ],
+            [
+             0.3,
+             "#f1b6da"
+            ],
+            [
+             0.4,
+             "#fde0ef"
+            ],
+            [
+             0.5,
+             "#f7f7f7"
+            ],
+            [
+             0.6,
+             "#e6f5d0"
+            ],
+            [
+             0.7,
+             "#b8e186"
+            ],
+            [
+             0.8,
+             "#7fbc41"
+            ],
+            [
+             0.9,
+             "#4d9221"
+            ],
+            [
+             1,
+             "#276419"
+            ]
+           ],
+           "sequential": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ],
+           "sequentialminus": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ]
+          },
+          "colorway": [
+           "#636efa",
+           "#EF553B",
+           "#00cc96",
+           "#ab63fa",
+           "#FFA15A",
+           "#19d3f3",
+           "#FF6692",
+           "#B6E880",
+           "#FF97FF",
+           "#FECB52"
+          ],
+          "font": {
+           "color": "#2a3f5f"
+          },
+          "geo": {
+           "bgcolor": "white",
+           "lakecolor": "white",
+           "landcolor": "#E5ECF6",
+           "showlakes": true,
+           "showland": true,
+           "subunitcolor": "white"
+          },
+          "hoverlabel": {
+           "align": "left"
+          },
+          "hovermode": "closest",
+          "mapbox": {
+           "style": "light"
+          },
+          "paper_bgcolor": "white",
+          "plot_bgcolor": "#E5ECF6",
+          "polar": {
+           "angularaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "radialaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "scene": {
+           "xaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "yaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "zaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           }
+          },
+          "shapedefaults": {
+           "line": {
+            "color": "#2a3f5f"
+           }
+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        },
+        "xaxis": {
+         "dtick": 1,
+         "gridwidth": 2,
+         "showticklabels": false,
+         "tick0": -0.5,
+         "ticks": "",
+         "zeroline": false
+        },
+        "yaxis": {
+         "autorange": "reversed",
+         "dtick": 1,
+         "gridwidth": 2,
+         "showticklabels": false,
+         "tick0": 0.5,
+         "ticks": "",
+         "zeroline": false
+        }
+       }
+      },
+      "text/html": [
+       "<div>\n",
+       "        \n",
+       "        \n",
+       "            <div id=\"c5d59d0e-b2d7-4d8d-99c0-679c4e8dc8b8\" class=\"plotly-graph-div\" style=\"height:710px; width:100%;\"></div>\n",
+       "            <script type=\"text/javascript\">\n",
+       "                require([\"plotly\"], function(Plotly) {\n",
+       "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
+       "                    \n",
+       "                if (document.getElementById(\"c5d59d0e-b2d7-4d8d-99c0-679c4e8dc8b8\")) {\n",
+       "                    Plotly.newPlot(\n",
+       "                        'c5d59d0e-b2d7-4d8d-99c0-679c4e8dc8b8',\n",
+       "                        [{\"colorscale\": [[0, \"#00083e\"], [0.5, \"#ededee\"], [1, \"#ffffff\"]], \"hoverinfo\": \"none\", \"opacity\": 0.75, \"showscale\": false, \"type\": \"heatmap\", \"z\": [[0, 0, 0, 0], [0.5, 0.5, 0.5, 0.5], [1, 1, 1, 1], [0.5, 0.5, 0.5, 0.5], [1, 1, 1, 1], [0.5, 0.5, 0.5, 0.5], [1, 1, 1, 1], [0.5, 0.5, 0.5, 0.5], [1, 1, 1, 1], [0.5, 0.5, 0.5, 0.5], [1, 1, 1, 1], [0.5, 0.5, 0.5, 0.5], [1, 1, 1, 1], [0.5, 0.5, 0.5, 0.5], [1, 1, 1, 1], [0.5, 0.5, 0.5, 0.5], [1, 1, 1, 1], [0.5, 0.5, 0.5, 0.5], [1, 1, 1, 1], [0.5, 0.5, 0.5, 0.5], [1, 1, 1, 1], [0.5, 0.5, 0.5, 0.5]]}],\n",
+       "                        {\"annotations\": [{\"align\": \"left\", \"font\": {\"color\": \"#ffffff\"}, \"showarrow\": false, \"text\": \"<b>School</b>\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 0, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#ffffff\"}, \"showarrow\": false, \"text\": \"<b>Women</b>\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 0, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#ffffff\"}, \"showarrow\": false, \"text\": \"<b>Men</b>\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 0, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#ffffff\"}, \"showarrow\": false, \"text\": \"<b>Gap</b>\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 0, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"MIT\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 1, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"94\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 1, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"152\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 1, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"58\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 1, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"Stanford\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 2, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"96\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 2, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"151\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 2, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"55\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 2, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"Harvard\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 3, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"112\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 3, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"165\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 3, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"53\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 3, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"U.Penn\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 4, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"92\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 4, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"141\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 4, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"49\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 4, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"Princeton\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 5, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"90\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 5, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"137\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 5, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"47\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 5, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"Chicago\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 6, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"78\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 6, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"118\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 6, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"40\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 6, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"Georgetown\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 7, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"94\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 7, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"131\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 7, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"37\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 7, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"Tufts\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 8, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"76\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 8, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"112\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 8, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"36\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 8, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"Yale\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 9, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"79\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 9, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"114\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 9, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"35\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 9, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"Columbia\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 10, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"86\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 10, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"119\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 10, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"33\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 10, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"Duke\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 11, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"93\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 11, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"124\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 11, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"31\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 11, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"Dartmouth\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 12, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"84\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 12, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"114\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 12, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"30\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 12, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"NYU\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 13, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"67\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 13, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"94\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 13, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"27\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 13, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"Notre Dame\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 14, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"73\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 14, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"100\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 14, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"27\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 14, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"Cornell\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 15, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"80\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 15, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"107\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 15, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"27\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 15, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"Michigan\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 16, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"62\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 16, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"84\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 16, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"22\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 16, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"Brown\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 17, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"72\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 17, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"92\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 17, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"20\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 17, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"Berkeley\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 18, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"71\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 18, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"88\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 18, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"17\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 18, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"Emory\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 19, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"68\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 19, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"82\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 19, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"14\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 19, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"UCLA\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 20, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"64\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 20, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"78\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 20, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"14\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 20, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"SoCal\", \"x\": -0.45, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 21, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"72\", \"x\": 0.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 21, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"81\", \"x\": 1.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 21, \"yref\": \"y\"}, {\"align\": \"left\", \"font\": {\"color\": \"#000000\"}, \"showarrow\": false, \"text\": \"9\", \"x\": 2.55, \"xanchor\": \"left\", \"xref\": \"x\", \"y\": 21, \"yref\": \"y\"}], \"height\": 710, \"margin\": {\"b\": 0, \"l\": 0, \"r\": 0, \"t\": 0}, \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"xaxis\": {\"dtick\": 1, \"gridwidth\": 2, \"showticklabels\": false, \"tick0\": -0.5, \"ticks\": \"\", \"zeroline\": false}, \"yaxis\": {\"autorange\": \"reversed\", \"dtick\": 1, \"gridwidth\": 2, \"showticklabels\": false, \"tick0\": 0.5, \"ticks\": \"\", \"zeroline\": false}},\n",
+       "                        {\"responsive\": true}\n",
+       "                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('c5d59d0e-b2d7-4d8d-99c0-679c4e8dc8b8');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })\n",
+       "                };\n",
+       "                });\n",
+       "            </script>\n",
+       "        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import chart_studio.plotly as py\n",
+    "import plotly.figure_factory as ff\n",
+    "import pandas as pd\n",
+    "from plotly.offline import iplot\n",
+    "\n",
+    "df = pd.read_csv(\"https://raw.githubusercontent.com/plotly/datasets/master/school_earnings.csv\")\n",
+    "\n",
+    "table = ff.create_table(df)\n",
+    "iplot(table, filename='jupyter-table1')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "linkText": "Export to plot.ly",
+        "plotlyServerURL": "https://plot.ly",
+        "showLink": false
+       },
+       "data": [
+        {
+         "type": "bar",
+         "x": [
+          "MIT",
+          "Stanford",
+          "Harvard",
+          "U.Penn",
+          "Princeton",
+          "Chicago",
+          "Georgetown",
+          "Tufts",
+          "Yale",
+          "Columbia",
+          "Duke",
+          "Dartmouth",
+          "NYU",
+          "Notre Dame",
+          "Cornell",
+          "Michigan",
+          "Brown",
+          "Berkeley",
+          "Emory",
+          "UCLA",
+          "SoCal"
+         ],
+         "y": [
+          58,
+          55,
+          53,
+          49,
+          47,
+          40,
+          37,
+          36,
+          35,
+          33,
+          31,
+          30,
+          27,
+          27,
+          27,
+          22,
+          20,
+          17,
+          14,
+          14,
+          9
+         ]
+        }
+       ],
+       "layout": {
+        "template": {
+         "data": {
+          "bar": [
+           {
+            "error_x": {
+             "color": "#2a3f5f"
+            },
+            "error_y": {
+             "color": "#2a3f5f"
+            },
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             }
+            },
+            "type": "bar"
+           }
+          ],
+          "barpolar": [
+           {
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             }
+            },
+            "type": "barpolar"
+           }
+          ],
+          "carpet": [
+           {
+            "aaxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "baxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "type": "carpet"
+           }
+          ],
+          "choropleth": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "choropleth"
+           }
+          ],
+          "contour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "contour"
+           }
+          ],
+          "contourcarpet": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "contourcarpet"
+           }
+          ],
+          "heatmap": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmap"
+           }
+          ],
+          "heatmapgl": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmapgl"
+           }
+          ],
+          "histogram": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "histogram"
+           }
+          ],
+          "histogram2d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "histogram2d"
+           }
+          ],
+          "histogram2dcontour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "histogram2dcontour"
+           }
+          ],
+          "mesh3d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "mesh3d"
+           }
+          ],
+          "parcoords": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "parcoords"
+           }
+          ],
+          "pie": [
+           {
+            "automargin": true,
+            "type": "pie"
+           }
+          ],
+          "scatter": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatter"
+           }
+          ],
+          "scatter3d": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatter3d"
+           }
+          ],
+          "scattercarpet": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattercarpet"
+           }
+          ],
+          "scattergeo": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergeo"
+           }
+          ],
+          "scattergl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergl"
+           }
+          ],
+          "scattermapbox": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattermapbox"
+           }
+          ],
+          "scatterpolar": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterpolar"
+           }
+          ],
+          "scatterpolargl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterpolargl"
+           }
+          ],
+          "scatterternary": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterternary"
+           }
+          ],
+          "surface": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "surface"
+           }
+          ],
+          "table": [
+           {
+            "cells": {
+             "fill": {
+              "color": "#EBF0F8"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "header": {
+             "fill": {
+              "color": "#C8D4E3"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "type": "table"
+           }
+          ]
+         },
+         "layout": {
+          "annotationdefaults": {
+           "arrowcolor": "#2a3f5f",
+           "arrowhead": 0,
+           "arrowwidth": 1
+          },
+          "coloraxis": {
+           "colorbar": {
+            "outlinewidth": 0,
+            "ticks": ""
+           }
+          },
+          "colorscale": {
+           "diverging": [
+            [
+             0,
+             "#8e0152"
+            ],
+            [
+             0.1,
+             "#c51b7d"
+            ],
+            [
+             0.2,
+             "#de77ae"
+            ],
+            [
+             0.3,
+             "#f1b6da"
+            ],
+            [
+             0.4,
+             "#fde0ef"
+            ],
+            [
+             0.5,
+             "#f7f7f7"
+            ],
+            [
+             0.6,
+             "#e6f5d0"
+            ],
+            [
+             0.7,
+             "#b8e186"
+            ],
+            [
+             0.8,
+             "#7fbc41"
+            ],
+            [
+             0.9,
+             "#4d9221"
+            ],
+            [
+             1,
+             "#276419"
+            ]
+           ],
+           "sequential": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ],
+           "sequentialminus": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ]
+          },
+          "colorway": [
+           "#636efa",
+           "#EF553B",
+           "#00cc96",
+           "#ab63fa",
+           "#FFA15A",
+           "#19d3f3",
+           "#FF6692",
+           "#B6E880",
+           "#FF97FF",
+           "#FECB52"
+          ],
+          "font": {
+           "color": "#2a3f5f"
+          },
+          "geo": {
+           "bgcolor": "white",
+           "lakecolor": "white",
+           "landcolor": "#E5ECF6",
+           "showlakes": true,
+           "showland": true,
+           "subunitcolor": "white"
+          },
+          "hoverlabel": {
+           "align": "left"
+          },
+          "hovermode": "closest",
+          "mapbox": {
+           "style": "light"
+          },
+          "paper_bgcolor": "white",
+          "plot_bgcolor": "#E5ECF6",
+          "polar": {
+           "angularaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "radialaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "scene": {
+           "xaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "yaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "zaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           }
+          },
+          "shapedefaults": {
+           "line": {
+            "color": "#2a3f5f"
+           }
+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        }
+       }
+      },
+      "text/html": [
+       "<div>\n",
+       "        \n",
+       "        \n",
+       "            <div id=\"aa85b484-dcaa-494c-aafc-1fdde70e4cca\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
+       "            <script type=\"text/javascript\">\n",
+       "                require([\"plotly\"], function(Plotly) {\n",
+       "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
+       "                    \n",
+       "                if (document.getElementById(\"aa85b484-dcaa-494c-aafc-1fdde70e4cca\")) {\n",
+       "                    Plotly.newPlot(\n",
+       "                        'aa85b484-dcaa-494c-aafc-1fdde70e4cca',\n",
+       "                        [{\"type\": \"bar\", \"x\": [\"MIT\", \"Stanford\", \"Harvard\", \"U.Penn\", \"Princeton\", \"Chicago\", \"Georgetown\", \"Tufts\", \"Yale\", \"Columbia\", \"Duke\", \"Dartmouth\", \"NYU\", \"Notre Dame\", \"Cornell\", \"Michigan\", \"Brown\", \"Berkeley\", \"Emory\", \"UCLA\", \"SoCal\"], \"y\": [58, 55, 53, 49, 47, 40, 37, 36, 35, 33, 31, 30, 27, 27, 27, 22, 20, 17, 14, 14, 9]}],\n",
+       "                        {\"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}},\n",
+       "                        {\"responsive\": true}\n",
+       "                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('aa85b484-dcaa-494c-aafc-1fdde70e4cca');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })\n",
+       "                };\n",
+       "                });\n",
+       "            </script>\n",
+       "        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import chart_studio.plotly as py\n",
+    "import plotly.graph_objects as go\n",
+    "\n",
+    "data = [go.Bar(x=df.School,\n",
+    "            y=df.Gap)]\n",
+    "\n",
+    "iplot(data, filename='jupyter-basic_bar')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "linkText": "Export to plot.ly",
+        "plotlyServerURL": "https://plot.ly",
+        "showLink": false
+       },
+       "data": [
+        {
+         "type": "surface",
+         "x": [
+          [
+           0,
+           0.056018243791582024,
+           0.11876723188987023,
+           0.18784331648031274,
+           0.26260954764839783,
+           0.34221269273537636,
+           0.4256064272344647,
+           0.5115800902079969,
+           0.5987922505586359,
+           0.6858082029981799,
+           0.7711404074799797,
+           0.8532908058874493,
+           0.9307938969633416,
+           1.0022594262020141,
+           1.0664135523722633,
+           1.1221373864195807,
+           1.168501860909015,
+           1.2047979773947326,
+           1.2305615929452358,
+           1.2455920426975036,
+           1.249964049390397,
+           1.2440325395004885,
+           1.2284301646618387,
+           1.2040575120168417,
+           1.172066173382897,
+           1.1338350259531544,
+           1.0909402520781157,
+           1.0451197880882066,
+           0.9982330380059466,
+           0.9522168136540172,
+           0.9090385648829727,
+           0.8706480397872174,
+           0.8389285628616627,
+           0.8156491377795313,
+           0.802418570276951,
+           0.8006427656875247,
+           0.8114862858946872,
+           0.8358391534936732,
+           0.874289769089086,
+           0.9271046638310337,
+           0.9942156469955521,
+           1.0752147315912117,
+           1.1693570339386614,
+           1.2755716505000183,
+           1.3924803216553023,
+           1.5184235023904424,
+           1.651493278646445,
+           1.78957239985179,
+           1.930378547077465,
+           2.0715128260588864,
+           2.2105113682559003,
+           2.3448988438176572,
+           2.4722426397760056,
+           2.5902064362976542,
+           2.6966019239346175,
+           2.7894374453263917,
+           2.8669624147823414,
+           2.927706466941762,
+           2.9705124089224983,
+           2.9945621960518736,
+           2.9993953158989832,
+           2.984919144902403,
+           2.95141103205167,
+           2.899512060213838,
+           2.8302126330304667,
+           2.744830229048498,
+           2.644979850182069,
+           2.5325378642269136,
+           2.4096000967752813,
+           2.2784351627356747,
+           2.1414341384872597,
+           2.0010577598229524,
+           1.859782386243655,
+           1.720045997549324,
+           1.5841954834581968,
+           1.454436451351645,
+           1.3327867121122297,
+           1.221034511042566,
+           1.1207024523491833,
+           1.0330179245985116,
+           0.9588906744010262,
+           0.8988980003165823,
+           0.8532778529262875,
+           0.8219299347680321,
+           0.8044247001127186,
+           0.8000199641216524,
+           0.8076846484377509,
+           0.8261290201838827,
+           0.8538406278149349,
+           0.8891250040229537,
+           0.93015009614457,
+           0.9749933008966695,
+           1.0216899247474471,
+           1.0682818650929202,
+           1.112865311200247,
+           1.1536362974020187,
+           1.1889330033462424,
+           1.2172737855780649,
+           1.237390039033666,
+           1.248253123234139,
+           1.2490947426088512,
+           1.2394203395337227,
+           1.219015238066734,
+           1.1879434614810382,
+           1.1465393328824192,
+           1.09539215078203,
+           1.0353244059065794,
+           0.9673641674083236,
+           0.8927124119504425,
+           0.8127061942752944,
+           0.7287786597116185,
+           0.6424169751285275,
+           0.5551193032367778,
+           0.4683519647061953,
+           0.38350792287249386,
+           0.30186768714330153,
+           0.2245636646065025,
+           0.15254889651988446,
+           0.0865709997041844,
+           0.02715199535426616,
+           -0.02542544706904995,
+           -0.07112499146024243,
+           -0.1101566601808608,
+           -0.14296990264444673,
+           -0.17023988936249904,
+           -0.19284739082306204,
+           -0.21185276882987894,
+           -0.22846476278230923,
+           -0.24400489088369218,
+           -0.25986840292288904,
+           -0.2774828140979546,
+           -0.298265115957844,
+           -0.3235787992016268,
+           -0.35469183277057104,
+           -0.39273672410032845,
+           -0.438673737008059,
+           -0.49325826763785996,
+           -0.557013277039616,
+           -0.6302075538247861,
+           -0.7128404350298457,
+           -0.8046334514381782,
+           -0.9050291892005368,
+           -1.013197477010279,
+           -1.1280488219037779,
+           -1.2482548316387538,
+           -1.372275182206858,
+           -1.4983905198815513,
+           -1.6247405325609303,
+           -1.7493662889585662,
+           -1.8702558298914445,
+           -1.985391906443385,
+           -2.0928006974624234,
+           -2.190600305328375,
+           -2.277047825136191,
+           -2.350583808578468,
+           -2.409872999329884,
+           -2.4538403003603992,
+           -2.4817010433547493,
+           -2.4929847636638556,
+           -2.487551837741151,
+           -2.4656025100969456,
+           -2.427678019292502,
+           -2.3746537229328624,
+           -2.3077243153383202,
+           -2.2283814238234356,
+           -2.138384055561092,
+           -2.039722542272693,
+           -1.934576790137821,
+           -1.825269783394303,
+           -1.7142174086040605,
+           -1.6038757595409125,
+           -1.4966871477872068,
+           -1.3950260797610032,
+           -1.3011464661105727,
+           -1.217131304030897,
+           -1.1448460176490634,
+           -1.085896557502323,
+           -1.041593249307868,
+           -1.0129212473679412,
+           -1.000518292328518,
+           -1.00466030038609,
+           -1.0252551256044227,
+           -1.0618446432659507,
+           -1.113615104849343,
+           -1.179415519092741,
+           -1.2577836234387658,
+           -1.3469788305833141,
+           -1.4450213702257828,
+           -1.5497367004363096,
+           -1.6588041398433022,
+           -1.769808574076164,
+           -1.8802940199242353,
+           -1.9878177901598,
+           -2.0900039918646045,
+           -2.184595111593696,
+           -2.269500491254376,
+           -2.3428405778832393,
+           -2.4029859365783026,
+           -2.44859014603917,
+           -2.47861584725169,
+           -2.492353384081862,
+           -2.4894316557595793,
+           -2.4698209909662308,
+           -2.4338280468206586,
+           -2.3820829287286567,
+           -2.315518914097043,
+           -2.2353453397379655,
+           -2.1430143750870663,
+           -2.0401825471828503,
+           -1.9286680052212164,
+           -1.8104046094757327,
+           -1.6873939991503402,
+           -1.5616568346742017,
+           -1.435184421144021,
+           -1.3098919008916443,
+           -1.1875741550715309,
+           -1.0698654780185384,
+           -0.9582039859095083,
+           -0.853801595604957,
+           -0.757620263659397,
+           -0.6703550130757956,
+           -0.592424100551756,
+           -0.5239664941319829,
+           -0.46484664494438344,
+           -0.4146663517320113,
+           -0.372783337835124,
+           -0.33833599160518646,
+           -0.3102735671559489,
+           -0.28739100671277595,
+           -0.2683674319788744,
+           -0.25180726271244763,
+           -0.23628285829676418,
+           -0.22037754400412285,
+           -0.20272787870956255,
+           -0.18206404507284082,
+           -0.15724729601519458,
+           -0.12730347129111383,
+           -0.09145170303299512,
+           -0.04912755663626539,
+           -4.89858719658941e-16
+          ],
+          [
+           0,
+           0.05839307618986191,
+           0.1233617925380928,
+           0.1943820511637335,
+           0.2707050756209538,
+           0.35137790784807,
+           0.43526974876700136,
+           0.5211034498675013,
+           0.6074913271161951,
+           0.6929743536339265,
+           0.7760636967226291,
+           0.8552835003279383,
+           0.9292137775668231,
+           0.9965322704969629,
+           1.0560541560935521,
+           1.106768527931227,
+           1.1478706611216773,
+           1.1787891717153385,
+           1.1992073084760109,
+           1.2090777615351576,
+           1.2086305352779076,
+           1.1983736078413698,
+           1.179086282440644,
+           1.1518053217979933,
+           1.1178041415652606,
+           1.0785655171549693,
+           1.0357484263305083,
+           0.991149803004612,
+           0.946662112073751,
+           0.904227767348762,
+           0.8657915018486927,
+           0.8332518596425427,
+           0.8084130094642701,
+           0.7929380816172898,
+           0.7883052010910294,
+           0.7957673319417965,
+           0.8163169621798083,
+           0.850656546686698,
+           0.8991754907434103,
+           0.9619343018388712,
+           1.038656366318649,
+           1.1287276242924813,
+           1.231204225528916,
+           1.3448280554991456,
+           1.468049829045505,
+           1.5990592640613925,
+           1.7358216736428271,
+           1.8761201567053378,
+           2.017602427977797,
+           2.1578312120413066,
+           2.2943370355739248,
+           2.4246721894601997,
+           2.546464599512747,
+           2.657470342090816,
+           2.7556235690016173,
+           2.839082664097144,
+           2.9062715405612276,
+           2.955915100945629,
+           2.987068018836656,
+           2.9991361583071887,
+           2.991890121222418,
+           2.9654705988009393,
+           2.920385398060126,
+           2.8574982111757214,
+           2.7780093915615747,
+           2.683429189867384,
+           2.5755440814978363,
+           2.4563769803430384,
+           2.328142277221598,
+           2.193196762591293,
+           2.0539875884545866,
+           1.912998491784189,
+           1.7726955396117317,
+           1.635473663279969,
+           1.5036052261231385,
+           1.3791918156280571,
+           1.2641203692913279,
+           1.1600246349772438,
+           1.0682528342970046,
+           0.9898422446552699,
+           0.9255012459279349,
+           0.8755991954348747,
+           0.840164304446122,
+           0.8188894955936774,
+           0.8111460280144528,
+           0.8160044905411793,
+           0.832262587348095,
+           0.8584789794366825,
+           0.8930123031273065,
+           0.9340643667464071,
+           0.9797264318501301,
+           1.0280274178605375,
+           1.076982830484107,
+           1.12464320558776,
+           1.169140881438574,
+           1.2087339627405411,
+           1.241846418371089,
+           1.2671033590863767,
+           1.2833606690437627,
+           1.289728312527245,
+           1.285586801012501,
+           1.2705964815323798,
+           1.2446994907693827,
+           1.2081144057955546,
+           1.1613238072234056,
+           1.1050551490953704,
+           1.0402554976619536,
+           0.9680608540947259,
+           0.889760910346337,
+           0.8067601994775061,
+           0.7205366890513463,
+           0.6325989265058547,
+           0.5444428772934938,
+           0.4575095992761028,
+           0.37314487037117905,
+           0.29256183148287823,
+           0.21680762475414275,
+           0.14673490025958624,
+           0.08297893516227652,
+           0.02594096137734948,
+           -0.024221865308999793,
+           -0.06759959577673874,
+           -0.10452563948015624,
+           -0.1355660420009156,
+           -0.16150217240002984,
+           -0.18330727715576306,
+           -0.20211751847447693,
+           -0.21919826003475956,
+           -0.23590648907277387,
+           -0.2536503669271845,
+           -0.2738469780922695,
+           -0.2978793984695675,
+           -0.32705422553893393,
+           -0.3625607059855315,
+           -0.40543256005097483,
+           -0.4565135373876702,
+           -0.5164276480591268,
+           -0.5855548967917936,
+           -0.6640132115084659,
+           -0.751647101967686,
+           -0.8480234148669165,
+           -0.9524343722735776,
+           -1.0639078952199967,
+           -1.181225028376585,
+           -1.302944099573765,
+           -1.427431074164192,
+           -1.5528954031900657,
+           -1.6774305201230104,
+           -1.7990580172432522,
+           -1.915774432682567,
+           -2.0255995053521128,
+           -2.126624709343103,
+           -2.2170608631598383,
+           -2.2952836228263256,
+           -2.359875711262457,
+           -2.409664808378247,
+           -2.4437561253953013,
+           -2.4615588106093584,
+           -2.462805479176601,
+           -2.4475643230157984,
+           -2.4162434345880546,
+           -2.3695871658069274,
+           -2.308664536053045,
+           -2.23484989648924,
+           -2.149796246843658,
+           -2.0554017808931913,
+           -1.9537704035931167,
+           -1.8471671120374757,
+           -1.7379692604969759,
+           -1.628614833482099,
+           -1.5215489275264023,
+           -1.4191696902461675,
+           -1.3237749829815975,
+           -1.2375110204733382,
+           -1.162324197839308,
+           -1.099917242596699,
+           -1.0517107293509165,
+           -1.0188108694519324,
+           -1.001984340424485,
+           -1.0016407538817766,
+           -1.0178231799606976,
+           -1.0502069554566393,
+           -1.0981068064250397,
+           -1.1604921188290593,
+           -1.2360099976419718,
+           -1.3230155703539923,
+           -1.4196088195677123,
+           -1.5236770754511848,
+           -1.6329421659837626,
+           -1.7450111143903977,
+           -1.8574291915308003,
+           -1.9677340782469974,
+           -2.0735098700224395,
+           -2.1724396642761907,
+           -2.2623555089643412,
+           -2.3412845588998135,
+           -2.4074903816249327,
+           -2.459508475395202,
+           -2.4961752048564003,
+           -2.5166495217769955,
+           -2.5204270147349424,
+           -2.507346018597796,
+           -2.4775857073746135,
+           -2.431656287820614,
+           -2.3703816012866845,
+           -2.2948746230716233,
+           -2.2065065175166567,
+           -2.1068700591648164,
+           -1.9977383618033648,
+           -1.881019964943558,
+           -1.7587114086899003,
+           -1.6328484810898363,
+           -1.5054573457165008,
+           -1.37850675093735,
+           -1.2538624863183885,
+           -1.1332451869025082,
+           -1.0181924943864216,
+           -0.9100264678753457,
+           -0.8098269988971484,
+           -0.7184118292191877,
+           -0.6363235996855633,
+           -0.5638241780801986,
+           -0.5008963284583358,
+           -0.4472525981364828,
+           -0.40235111625691283,
+           -0.36541782410700424,
+           -0.33547449651310995,
+           -0.31137176965020535,
+           -0.29182626708915466,
+           -0.27546081590124627,
+           -0.26084667061817757,
+           -0.24654661661294966,
+           -0.23115780713105977,
+           -0.21335320014254341,
+           -0.19192050204854588,
+           -0.1657975939790869,
+           -0.13410351118057787,
+           -0.09616416437742566,
+           -0.05153213097427566,
+           -5.123193964678499e-16
+          ],
+          [
+           0,
+           0.06070772999554664,
+           0.1277789874912215,
+           0.20057348261239466,
+           0.2782368071160924,
+           0.35972423103292983,
+           0.44382996474534153,
+           0.5292211141982028,
+           0.6144754327667938,
+           0.6981218719908907,
+           0.7786828575160483,
+           0.8547171681179845,
+           0.924862275888931,
+           0.9878750150806562,
+           1.0426694855375682,
+           1.0883511631942018,
+           1.1242462831257363,
+           1.1499256778312672,
+           1.165222391889602,
+           1.1702425504097649,
+           1.1653691289033175,
+           1.1512584520770528,
+           1.1288294340764735,
+           1.0992457582587285,
+           1.0638913759724327,
+           1.0243398764996585,
+           0.9823184399096685,
+           0.9396672270400827,
+           0.8982951825336294,
+           0.8601333247023029,
+           0.8270866674391376,
+           0.8009859625767671,
+           0.7835404648275324,
+           0.7762929052884145,
+           0.780577813754404,
+           0.7974842557910837,
+           0.827823949417941,
+           0.8721056007641861,
+           0.9305161512051146,
+           1.002909463831903,
+           1.0888027986625373,
+           1.1873812381276154,
+           1.2975100316657768,
+           1.4177546354720136,
+           1.5464080353024223,
+           1.6815247613901227,
+           1.8209608393875698,
+           1.962418773909324,
+           2.1034965353641475,
+           2.2417394194719202,
+           2.3746935746950637,
+           2.499959947648638,
+           2.615247381550837,
+           2.7184236183595645,
+           2.807563001084302,
+           2.8809897477956636,
+           2.9373157712909337,
+           2.9754721457519073,
+           2.99473347097768,
+           2.994734552277483,
+           2.9754789958059926,
+           2.93733951060457,
+           2.881049905224405,
+           2.807688963772384,
+           2.7186565787492,
+           2.615642701461868,
+           2.500589840632847,
+           2.3756499919721046,
+           2.243137012237899,
+           2.105475557522834,
+           1.9651477846029688,
+           1.8246390642836372,
+           1.6863839755824528,
+           1.552713838864316,
+           1.425807004992722,
+           1.3076430472368181,
+           1.1999619048412489,
+           1.1042289042652618,
+           1.0216064391795414,
+           0.9529329269606629,
+           0.8987094816777189,
+           0.859094555804268,
+           0.8339066097309692,
+           0.8226346743438022,
+           0.8244564822209216,
+           0.8382636620288819,
+           0.8626933228827166,
+           0.8961652048573273,
+           0.9369234421490628,
+           0.9830818797122134,
+           1.032671805061197,
+           1.0836909061997388,
+           1.1341522454707245,
+           1.18213204793761,
+           1.2258151413895069,
+           1.2635369521517166,
+           1.2938210548187707,
+           1.3154113923823705,
+           1.3272984229752611,
+           1.328738607042203,
+           1.319266820192656,
+           1.2987014579624747,
+           1.267142184661474,
+           1.2249604647433479,
+           1.1727831970394704,
+           1.1114699452019554,
+           1.0420844174891193,
+           0.9658609916218401,
+           0.8841672023039022,
+           0.7984632071200084,
+           0.7102593184890628,
+           0.6210727334043924,
+           0.5323846077866977,
+           0.44559860808827956,
+           0.3620020297328011,
+           0.2827305011928985,
+           0.20873719583382644,
+           0.1407673535695533,
+           0.07933877396018724,
+           0.02472878520740443,
+           -0.023031976421486633,
+           -0.06415882056988918,
+           -0.09910531626038212,
+           -0.12854887248440303,
+           -0.15336996974531067,
+           -0.1746255927808832,
+           -0.19351756704788511,
+           -0.2113566359951604,
+           -0.22952322925725382,
+           -0.24942596077819054,
+           -0.27245895824384125,
+           -0.2999591594462602,
+           -0.33316471641647083,
+           -0.37317562416541433,
+           -0.4209176382231223,
+           -0.47711046514236455,
+           -0.5422411047038026,
+           -0.616543094335409,
+           -0.6999822584267406,
+           -0.7922494014632225,
+           -0.8927602083175248,
+           -1.0006624320094062,
+           -1.1148502633710562,
+           -1.2339855930019257,
+           -1.3565256982981706,
+           -1.480756721678254,
+           -1.6048321546150706,
+           -1.726815409572682,
+           -1.8447254518141873,
+           -1.9565843781252816,
+           -2.0604657719935973,
+           -2.154542636225672,
+           -2.2371337051827807,
+           -2.306746969846857,
+           -2.362119309119278,
+           -2.402251208713324,
+           -2.4264356626381227,
+           -2.434280488857933,
+           -2.4257234469414555,
+           -2.401039717592427,
+           -2.360841487676006,
+           -2.306069575228898,
+           -2.2379772222823338,
+           -2.158106374382458,
+           -2.0682569497565906,
+           -1.9704497736030029,
+           -1.8668840097092985,
+           -1.759890058645296,
+           -1.6518790057223391,
+           -1.5452897899184184,
+           -1.442535324825505,
+           -1.345948832859989,
+           -1.2577316536933687,
+           -1.1799037570596016,
+           -1.1142581294789404,
+           -1.0623201154375093,
+           -1.0253126783084408,
+           -1.0041284075692625,
+           -0.999308940014949,
+           -1.0110322875350708,
+           -1.0391083768661418,
+           -1.0829829120921761,
+           -1.1417494732779985,
+           -1.2141695692794054,
+           -1.2987001742309054,
+           -1.393528100047581,
+           -1.4966103957959098,
+           -1.6057198229072696,
+           -1.7184943363640859,
+           -1.8324894090538577,
+           -1.9452319716950024,
+           -2.054274705636112,
+           -2.157249421231899,
+           -2.251918280473279,
+           -2.336221678414714,
+           -2.408321682285404,
+           -2.4666400378830122,
+           -2.509889887175623,
+           -2.5371004956502112,
+           -2.5476344590220923,
+           -2.5411970422391073,
+           -2.517837494762739,
+           -2.4779423801893925,
+           -2.4222211506268154,
+           -2.3516843821522158,
+           -2.2676152626073427,
+           -2.1715350826687474,
+           -2.0651636216903864,
+           -1.9503754378526144,
+           -1.8291531648321295,
+           -1.7035389823294516,
+           -1.575585463839023,
+           -1.4473070112291726,
+           -1.3206330619643238,
+           -1.1973642018398958,
+           -1.0791322353254238,
+           -0.967365159124485,
+           -0.8632578550953759,
+           -0.7677491695341351,
+           -0.6815058807834854,
+           -0.6049138803661119,
+           -0.5380767088012897,
+           -0.48082140057377803,
+           -0.4327114080635958,
+           -0.3930661962348395,
+           -0.36098693296571827,
+           -0.33538754823891,
+           -0.31503030277037725,
+           -0.2985648963218236,
+           -0.2845700606384744,
+           -0.271596523769169,
+           -0.25821020286580987,
+           -0.24303448211190687,
+           -0.22479046114853093,
+           -0.20233411647112876,
+           -0.17468940227017227,
+           -0.14107642591566966,
+           -0.10093396395309594,
+           -0.053935733749470964,
+           -5.344934411386254e-16
+          ],
+          [
+           0,
+           0.06294133585385796,
+           0.13197901028207656,
+           0.20636184032097987,
+           0.28513692575109906,
+           0.36717653800418176,
+           0.4512100493879049,
+           0.5358600574058343,
+           0.6196817476655808,
+           0.7012044519972594,
+           0.7789742981755478,
+           0.8515968156105127,
+           0.917778358394535,
+           0.9763652332839994,
+           1.0263794749396273,
+           1.0670502927138317,
+           1.0978403204362421,
+           1.1184659303522049,
+           1.1289110213856883,
+           1.1294338565095918,
+           1.120566700097089,
+           1.1031081892864054,
+           1.0781085590220174,
+           1.0468480238708495,
+           1.0108087963317438,
+           0.9716413867006607,
+           0.9311259794362596,
+           0.891129811581781,
+           0.8535615868040927,
+           0.8203240412309811,
+           0.7932658323521931,
+           0.7741339483288977,
+           0.7645278313801688,
+           0.7658563754726933,
+           0.7792988960608197,
+           0.8057710795611857,
+           0.8458968047410681,
+           0.8999865900301365,
+           0.968023263277753,
+           1.0496552775048613,
+           1.144197911965315,
+           1.250642406848499,
+           1.3676728869120789,
+           1.4936907389801073,
+           1.6268459252700822,
+           1.765074543442703,
+           1.906141789334673,
+           2.047689343382924,
+           2.187286090137556,
+           2.3224809947813654,
+           2.4508569033782934,
+           2.57008400612164,
+           2.6779717058769372,
+           2.7725176677974983,
+           2.8519528889691204,
+           2.9147817184204983,
+           2.959815875230777,
+           2.9862016530485103,
+           2.993439659709726,
+           2.981396616921748,
+           2.9503089328872454,
+           2.9007779557157605,
+           2.8337570127693255,
+           2.7505305359179846,
+           2.6526857603032985,
+           2.54207766006247,
+           2.4207879442806415,
+           2.2910790763352042,
+           2.155344396383994,
+           2.0160555172109262,
+           1.8757082258013982,
+           1.7367681553931524,
+           1.6016174945848012,
+           1.4725039713804644,
+           1.3514932915503866,
+           1.2404261238684327,
+           1.1408806118150718,
+           1.0541412550147482,
+           0.9811748473838257,
+           0.9226139865596523,
+           0.878748484912204,
+           0.8495248208412304,
+           0.83455357484033,
+           0.8331246027272065,
+           0.8442295131975932,
+           0.8665908429822705,
+           0.8986971646067684,
+           0.9388432229130262,
+           0.9851740804551143,
+           1.0357321614110342,
+           1.0885060209055644,
+           1.1414796330711086,
+           1.1926809875154085,
+           1.2402288101056422,
+           1.2823762793660012,
+           1.3175506928475273,
+           1.344388146408874,
+           1.361762420659989,
+           1.3688074195242186,
+           1.364932672150267,
+           1.3498315870566997,
+           1.3234823319475009,
+           1.2861413994642472,
+           1.238330103558561,
+           1.1808144285677047,
+           1.1145788190307733,
+           1.0407946486625284,
+           0.9607842379731021,
+           0.8759813985418708,
+           0.7878895652500807,
+           0.6980386338138022,
+           0.6079416483875297,
+           0.5190524822002108,
+           0.43272562324580727,
+           0.35017911781710487,
+           0.27246163869204937,
+           0.200424534274998,
+           0.13469958279387878,
+           0.07568302513527415,
+           0.023526284897936504,
+           -0.02186639104129605,
+           -0.06083331927226754,
+           -0.09394392407820651,
+           -0.12198074826524245,
+           -0.14591541072361291,
+           -0.16687914957263358,
+           -0.18612873214581035,
+           -0.2050086355340705,
+           -0.22491050080131575,
+           -0.24723093777424232,
+           -0.2733288035882525,
+           -0.30448309573526283,
+           -0.34185258872149954,
+           -0.3864383028529135,
+           -0.4390498251005103,
+           -0.5002764071407853,
+           -0.5704636468639722,
+           -0.6496964198468195,
+           -0.7377885699809593,
+           -0.8342796975617724,
+           -0.9384392029526666,
+           -1.0492775589638628,
+           -1.1655645999687843,
+           -1.2858544351838317,
+           -1.4085164220128865,
+           -1.5317714772430642,
+           -1.6537328631835393,
+           -1.7724504661475227,
+           -1.8859574890561177,
+           -1.9923184108634946,
+           -2.0896770247822936,
+           -2.176303356039392,
+           -2.2506382784971266,
+           -2.3113346975734266,
+           -2.3572942433917037,
+           -2.387698521184786,
+           -2.402034093199784,
+           -2.400110514630625,
+           -2.3820709118420194,
+           -2.3483947703015384,
+           -2.2998927878235707,
+           -2.2376938413353287,
+           -2.163224307667089,
+           -2.0781801661106143,
+           -1.9844924880610333,
+           -1.8842870825672542,
+           -1.779839212011722,
+           -1.6735244158091174,
+           -1.5677665788698203,
+           -1.464984453139343,
+           -1.3675378829868068,
+           -1.2776749974750687,
+           -1.1974816142434968,
+           -1.128834051262541,
+           -1.0733564652100513,
+           -1.0323837305176629,
+           -1.0069307437569492,
+           -0.9976688871004821,
+           -1.0049102157552168,
+           -1.0285997516180128,
+           -1.0683160733796562,
+           -1.123280196569842,
+           -1.1923725403736574,
+           -1.274157586241408,
+           -1.3669156510216252,
+           -1.468681029001393,
+           -1.5772856069271004,
+           -1.69040692744768,
+           -1.8056195725847712,
+           -1.9204486622953645,
+           -2.0324242157867647,
+           -2.13913510609254,
+           -2.238281351899137,
+           -2.3277235343541904,
+           -2.405528199476066,
+           -2.4700082069928264,
+           -2.5197571114736825,
+           -2.5536768083774923,
+           -2.570997842501962,
+           -2.5712919552070135,
+           -2.5544766353005595,
+           -2.5208116319804055,
+           -2.4708875819727716,
+           -2.4056070922499218,
+           -2.326158799820015,
+           -2.233985096668998,
+           -2.1307443569470585,
+           -2.01826863132196,
+           -1.8985178769904025,
+           -1.7735318686741306,
+           -1.6453809842228806,
+           -1.5161170771052808,
+           -1.387725636730104,
+           -1.2620803965872889,
+           -1.1409014807461297,
+           -1.0257180831175663,
+           -0.9178365535568325,
+           -0.8183146234250843,
+           -0.7279423442361258,
+           -0.6472301405072035,
+           -0.5764041962579053,
+           -0.5154092083255795,
+           -0.46391835346018795,
+           -0.4213501346859294,
+           -0.3868916002032425,
+           -0.359527269444366,
+           -0.33807295973255996,
+           -0.3212135868284162,
+           -0.30754391644322815,
+           -0.2956111739205632,
+           -0.28395837743044666,
+           -0.2711672471778972,
+           -0.25589955956121296,
+           -0.23693586045195625,
+           -0.21321052461171436,
+           -0.18384224682129838,
+           -0.1481591720423227,
+           -0.10571801374427198,
+           -0.05631666779500349,
+           -5.561808166845126e-16
+          ],
+          [
+           0,
+           0.06507370850497066,
+           0.13592393405609174,
+           0.2116948904443797,
+           0.2913432034149159,
+           0.3736676568320369,
+           0.45734351099324283,
+           0.540960482319321,
+           0.6230633761970132,
+           0.7021942930596196,
+           0.7769352837045191,
+           0.8459503145147895,
+           0.9080254171017438,
+           0.9621059396086454,
+           1.007329887478306,
+           1.0430564381521485,
+           1.0688888345401932,
+           1.0846910031855224,
+           1.0905974013232516,
+           1.087015768545751,
+           1.0746226392367066,
+           1.0543516567988782,
+           1.0273749153273992,
+           0.9950777341227992,
+           0.9590274407595046,
+           0.9209368950170852,
+           0.8826236248683252,
+           0.8459655633599942,
+           0.8128544686018716,
+           0.7851481757792377,
+           0.7646228683661805,
+           0.7529265644891475,
+           0.751534993352184,
+           0.7617109862085296,
+           0.7844684277011524,
+           0.8205417083553609,
+           0.8703614901073006,
+           0.9340374471082831,
+           1.011348477293501,
+           1.1017407004137483,
+           1.2043333698012666,
+           1.317932632699927,
+           1.4410528822689577,
+           1.5719452580936701,
+           1.7086326758064827,
+           1.8489506045987132,
+           1.9905926680025792,
+           2.1311600219116724,
+           2.268213367419442,
+           2.3993263871109476,
+           2.522139353693756,
+           2.6344116503349606,
+           2.734071963077009,
+           2.819264956779876,
+           2.8883933259874226,
+           2.9401542190372765,
+           2.973569165059012,
+           2.9880067860663346,
+           2.9831977464541555,
+           2.9592415757368147,
+           2.9166051928541634,
+           2.856113157150842,
+           2.7789298674171112,
+           2.686534121394381,
+           2.58068662925045,
+           2.4633912413165526,
+           2.3368507987994174,
+           2.2034186426356337,
+           2.065546917080954,
+           1.9257328785755075,
+           1.7864644651234383,
+           1.6501663958154362,
+           1.5191480538916249,
+           1.395554360326842,
+           1.2813207694964779,
+           1.1781334159342074,
+           1.087395314071283,
+           1.0101993642983262,
+           0.9473087523835511,
+           0.8991451493156187,
+           0.8657849294432691,
+           0.846963431005374,
+           0.8420870895368328,
+           0.8502530859374368,
+           0.8702759718128991,
+           0.9007205694063857,
+           0.9399402960513363,
+           0.9861199371585578,
+           1.0373217903320087,
+           1.091534028706528,
+           1.146720085765057,
+           1.2008678477581896,
+           1.2520374537137557,
+           1.2984065464437564,
+           1.338311889754456,
+           1.37028636536588,
+           1.3930904853193966,
+           1.4057376987768966,
+           1.407512932461771,
+           1.3979839775098462,
+           1.3770055178182383,
+           1.3447157815228692,
+           1.3015259833269337,
+           1.2481029063899114,
+           1.1853451438539517,
+           1.1143536775652392,
+           1.0363976112315019,
+           0.9528759936848565,
+           0.865276762172196,
+           0.7751339033639277,
+           0.6839839694149593,
+           0.5933230969957795,
+           0.5045656585334494,
+           0.41900562749452025,
+           0.33778166465729,
+           0.261846831901513,
+           0.19194371667188317,
+           0.12858560710386863,
+           0.0720441984892858,
+           0.02234414036004386,
+           -0.020735445660526614,
+           -0.05765252939813153,
+           -0.08908705007930443,
+           -0.11591951653455179,
+           -0.1392039018356397,
+           -0.16013555424070275,
+           -0.1800149775544676,
+           -0.20020844344601207,
+           -0.22210648310995001,
+           -0.2470813637337579,
+           -0.27644468504226827,
+           -0.31140623193910033,
+           -0.3530351908941719,
+           -0.402224780909718,
+           -0.45966126602434837,
+           -0.5257982074581302,
+           -0.6008366823649092,
+           -0.6847120460085877,
+           -0.7770876487681165,
+           -0.8773557428409401,
+           -0.9846456302823062,
+           -1.0978389186900104,
+           -1.2155915680829825,
+           -1.3363622369352612,
+           -1.4584462713506003,
+           -1.5800145331523316,
+           -1.6991561339876597,
+           -1.8139240366938612,
+           -1.9223824048727196,
+           -2.0226545289625886,
+           -2.1129701334947946,
+           -2.191710876360977,
+           -2.2574528867498085,
+           -2.3090052531456733,
+           -2.3454434649080533,
+           -2.3661369282740488,
+           -2.370769817322794,
+           -2.3593546791226254,
+           -2.332238386085171,
+           -2.2901002132266073,
+           -2.2339420090588544,
+           -2.165070621509136,
+           -2.085072929851091,
+           -1.9957840154469921,
+           -1.8992491736540082,
+           -1.7976806223362745,
+           -1.6934098952458212,
+           -1.5888370177789224,
+           -1.4863776455435345,
+           -1.3884094006963255,
+           -1.2972186657261724,
+           -1.2149490886084033,
+           -1.1435530171111574,
+           -1.0847470143288716,
+           -1.0399725138023734,
+           -1.0103625531021099,
+           -0.9967153823782032,
+           -0.9994755825580619,
+           -1.0187231505192669,
+           -1.0541708199850321,
+           -1.1051696916618763,
+           -1.170723049009171,
+           -1.2495080417909794,
+           -1.3399047329350686,
+           -1.440031829749723,
+           -1.5477882624652874,
+           -1.6608996352123306,
+           -1.776968460263566,
+           -1.893526998415549,
+           -2.0080914688866187,
+           -2.118216362478367,
+           -2.221547592677355,
+           -2.3158732507990516,
+           -2.3991707923886625,
+           -2.4696495713583078,
+           -2.525787753532679,
+           -2.566362779539361,
+           -2.5904747048966064,
+           -2.5975619188239905,
+           -2.5874089284530086,
+           -2.560146087193058,
+           -2.5162413402984782,
+           -2.456484252423455,
+           -2.381962766454178,
+           -2.2940333156692096,
+           -2.194285068095037,
+           -2.084499218991441,
+           -1.9666043614122495,
+           -1.8426290530091505,
+           -1.714652757590287,
+           -1.5847563710148729,
+           -1.4549735421315586,
+           -1.327243970724782,
+           -1.2033698066333751,
+           -1.0849761888800304,
+           -0.9734768530095621,
+           -0.8700456017121522,
+           -0.7755942815901401,
+           -0.6907577414663564,
+           -0.6158860691519569,
+           -0.5510442185796912,
+           -0.4960189523063089,
+           -0.45033284027309595,
+           -0.41326487898523956,
+           -0.38387713033368054,
+           -0.3610466302386855,
+           -0.34350168783844026,
+           -0.329861589277527,
+           -0.3186786388916216,
+           -0.30848141671756996,
+           -0.2978181060734591,
+           -0.28529874902128427,
+           -0.2696353206801378,
+           -0.24967857470491736,
+           -0.2244507001818277,
+           -0.19317294244806013,
+           -0.15528747404057366,
+           -0.11047295370249774,
+           -0.058653377259266934,
+           -5.771853649180891e-16
+          ],
+          [
+           0,
+           0.06708554037388642,
+           0.1395780749142009,
+           0.21652443556593787,
+           0.29679959473933626,
+           0.37913900835946684,
+           0.46217502409627703,
+           0.5444763864007187,
+           0.6245897871764559,
+           0.7010823550031628,
+           0.7725839482414321,
+           0.8378281188230363,
+           0.8956906440646518,
+           0.9452245827072316,
+           0.9856908971322665,
+           1.016583794217107,
+           1.0376500698157485,
+           1.048901893083073,
+           1.050622633018538,
+           1.0433655065279026,
+           1.0279450105497883,
+           1.0054212857623797,
+           0.9770777414174796,
+           0.9443924453525968,
+           0.9090039457944794,
+           0.8726723380674233,
+           0.8372365160281151,
+           0.8045686517240468,
+           0.7765270247415532,
+           0.7549083729351986,
+           0.7414009573632243,
+           0.737539525667028,
+           0.7446633199382624,
+           0.7638782081645117,
+           0.7960239242004693,
+           0.8416472821224718,
+           0.9009820896612535,
+           0.9739363255964801,
+           1.060086971432796,
+           1.1586827026309376,
+           1.2686544536781086,
+           1.3886336790452845,
+           1.5169779433323896,
+           1.6518032933058302,
+           1.791022696555296,
+           1.9323896803042917,
+           2.07354617326143,
+           2.2120734465578944,
+           2.3455449694606796,
+           2.4715799437139894,
+           2.5878962583768232,
+           2.6923616154957632,
+           2.7830416157332727,
+           2.858243661273437,
+           2.916555629336238,
+           2.9568783911504526,
+           2.9784513953389955,
+           2.980870697876741,
+           2.964098999136814,
+           2.9284674377196884,
+           2.874669086165545,
+           2.803744290534524,
+           2.717058189414298,
+           2.6162709334718963,
+           2.503301299694908,
+           2.380284550760291,
+           2.2495255257316042,
+           2.1134480602249655,
+           1.9745419195926328,
+           1.8353084854929138,
+           1.6982064630899787,
+           1.5655988724343681,
+           1.4397025534415469,
+           1.3225413501836318,
+           1.21590404853443,
+           1.121308023839686,
+           1.0399694151297,
+           0.972780482912246,
+           0.9202946327110902,
+           0.8827194005526801,
+           0.8599175041196583,
+           0.8514158690062521,
+           0.8564223481850922,
+           0.8738496691039949,
+           0.9023459712545354,
+           0.9403311417648358,
+           0.9860380213301907,
+           1.0375574408683963,
+           1.09288596335143,
+           1.1499751473535766,
+           1.2067811203037877,
+           1.2613132508437752,
+           1.3116807409372946,
+           1.356136018576316,
+           1.393113899497038,
+           1.4212655989887537,
+           1.439486809769713,
+           1.4469392155893446,
+           1.4430649788093104,
+           1.427593919468873,
+           1.4005432887489422,
+           1.362210226666779,
+           1.3131571775849278,
+           1.2541907131176608,
+           1.1863343758834584,
+           1.1107963052119787,
+           1.028932533711219,
+           0.9422069483811845,
+           0.8521489891528806,
+           0.7603102094091837,
+           0.6682208459739624,
+           0.5773475397269712,
+           0.48905331263897417,
+           0.4045608435774171,
+           0.32491999536485816,
+           0.2509804315995412,
+           0.18337002659296844,
+           0.12247961889559164,
+           0.06845449216494215,
+           0.021192790821707125,
+           -0.01964910348149104,
+           -0.05464439047985483,
+           -0.08457719871982987,
+           -0.11041796469006583,
+           -0.13329350283269017,
+           -0.15445256498729135,
+           -0.17522780676615135,
+           -0.1969951738417882,
+           -0.22113179070672068,
+           -0.24897347635193878,
+           -0.2817730244129108,
+           -0.32066036928225744,
+           -0.3666057148525882,
+           -0.4203866300226396,
+           -0.4825600166641859,
+           -0.5534397338497185,
+           -0.6330805198182629,
+           -0.7212686939634465,
+           -0.8175199490479331,
+           -0.9210843631953618,
+           -1.0309585765212785,
+           -1.145904893184096,
+           -1.264476890804315,
+           -1.3850509501317694,
+           -1.505862962816765,
+           -1.625049338099549,
+           -1.7406913136699051,
+           -1.8508614848310634,
+           -1.9536714017928418,
+           -2.047319049115911,
+           -2.130135015024221,
+           -2.2006261817541626,
+           -2.257515820834803,
+           -2.2997790579819792,
+           -2.326672779227514,
+           -2.337759180426899,
+           -2.3329223132363532,
+           -2.3123771483511226,
+           -2.2766708571558154,
+           -2.2266762015359225,
+           -2.1635771138056517,
+           -2.088846739789694,
+           -2.00421840334219,
+           -1.9116501254160159,
+           -1.8132834908791744,
+           -1.7113977976366326,
+           -1.6083605417342115,
+           -1.5065753860168523,
+           -1.4084288262221036,
+           -1.3162368054231541,
+           -1.23219253452188,
+           -1.1583167528021798,
+           -1.096411608906186,
+           -1.0480192602457545,
+           -1.014386179770731,
+           -0.9964340258024902,
+           -0.994737776520483,
+           -1.0095116593893465,
+           -1.0406032214877377,
+           -1.0874956938219547,
+           -1.1493186059643639,
+           -1.2248664115318146,
+           -1.3126246948751754,
+           -1.4108033495116292,
+           -1.5173759536694018,
+           -1.6301244218425168,
+           -1.7466878870262923,
+           -1.8646146693319638,
+           -1.9814161153510692,
+           -2.094621050669748,
+           -2.2018295763115407,
+           -2.3007649588642916,
+           -2.3893224131203215,
+           -2.4656136539918054,
+           -2.5280061993116183,
+           -2.57515653429205,
+           -2.606036398695836,
+           -2.6199516254679,
+           -2.616553140551724,
+           -2.595839923421813,
+           -2.558153921843498,
+           -2.5041671077690935,
+           -2.4348610493633593,
+           -2.3514995523292255,
+           -2.255595087636873,
+           -2.148869868465173,
+           -2.0332125631211007,
+           -1.910631729930273,
+           -1.7832071322272462,
+           -1.6530401349288955,
+           -1.5222043977736646,
+           -1.3926980639179285,
+           -1.2663985967044955,
+           -1.1450213432933156,
+           -1.0300828034032061,
+           -0.9228694572371855,
+           -0.8244128619173685,
+           -0.7354715641058803,
+           -0.6565202020161279,
+           -0.5877459871138988,
+           -0.5290525690594734,
+           -0.48007110152644483,
+           -0.4401781460945873,
+           -0.40851988095126124,
+           -0.3840419248884256,
+           -0.3655239489264853,
+           -0.3516181312481178,
+           -0.34089041885662724,
+           -0.331863493740185,
+           -0.3230603039103858,
+           -0.31304701136541774,
+           -0.30047422994831846,
+           -0.2841154756386058,
+           -0.2629018287216229,
+           -0.23595190952982156,
+           -0.20259639441442517,
+           -0.1623964430867038,
+           -0.11515556877943113,
+           -0.06092465473973806,
+           -5.973166896093736e-16
+          ],
+          [
+           0,
+           0.06895858636370204,
+           0.1429083328598495,
+           0.22080677426153494,
+           0.30145677009953686,
+           0.3835411613094982,
+           0.4656609508989791,
+           0.5463759911112874,
+           0.6242470921108212,
+           0.6978784275336699,
+           0.7659591013710956,
+           0.8273027588910113,
+           0.8808841712293813,
+           0.9258717977525278,
+           0.9616554304609757,
+           0.9878681480852223,
+           1.0044019510361504,
+           1.0114166084297527,
+           1.0093414209983582,
+           0.9988697844984528,
+           0.9809466226851344,
+           0.9567489424021504,
+           0.927659941207506,
+           0.8952372657229117,
+           0.8611761723102878,
+           0.8272684768405497,
+           0.795358293777933,
+           0.7672956536416724,
+           0.7448891498192497,
+           0.7298587990523155,
+           0.7237903037675487,
+           0.72809187858324,
+           0.7439547483307558,
+           0.7723183420576932,
+           0.813841098692475,
+           0.8688776679630367,
+           0.9374631379745864,
+           1.0193047522688392,
+           1.113781398330283,
+           1.2199509608079966,
+           1.3365654408223264,
+           1.4620935523515668,
+           1.594750322544455,
+           1.7325330494351787,
+           1.8732628122474857,
+           2.014630590198213,
+           2.1542469289217845,
+           2.289694002261596,
+           2.4185788535168333,
+           2.5385865659206686,
+           2.6475321080654335,
+           2.7434096263470433,
+           2.824438012692512,
+           2.889101660544943,
+           2.9361854332922697,
+           2.9648030043691525,
+           2.974417883878096,
+           2.964856619001208,
+           2.936313840527746,
+           2.8893490210123294,
+           2.824875006709634,
+           2.744138580722654,
+           2.648693504002833,
+           2.5403666593494676,
+           2.421218087031509,
+           2.293495845123964,
+           2.1595867496058534,
+           2.021964145751074,
+           1.8831339310261996,
+           1.745580088940051,
+           1.6117110021410261,
+           1.483807791345791,
+           1.3639758749724331,
+           1.2541008639416305,
+           1.1558097990021772,
+           1.0704386067856877,
+           0.9990064988390724,
+           0.9421978688683145,
+           0.9003520615121468,
+           0.8734611956191297,
+           0.8611760308959807,
+           0.8628196736831594,
+           0.8774087302175296,
+           0.9036813386340543,
+           0.9401313484500516,
+           0.9850477723098486,
+           1.036558512823299,
+           1.0926772703372527,
+           1.1513524677417506,
+           1.2105169875616866,
+           1.26813750553219,
+           1.3222622237755777,
+           1.3710658550212147,
+           1.4128907857421484,
+           1.4462834486357576,
+           1.470025060918511,
+           1.483156031229347,
+           1.4849935008377182,
+           1.475141660223294,
+           1.4534946655260885,
+           1.4202321662589992,
+           1.3758076413540847,
+           1.3209299204444378,
+           1.2565384367860366,
+           1.1837729131865182,
+           1.103938318890156,
+           1.0184660501973226,
+           0.9288723778496449,
+           0.8367152676869142,
+           0.7435507162507287,
+           0.6508897490574674,
+           0.5601572061053938,
+           0.4726533874664883,
+           0.38951955290817963,
+           0.31170816543966307,
+           0.23995864215778073,
+           0.17477923001646423,
+           0.11643546287965285,
+           0.06494548354619559,
+           0.020082334745991096,
+           -0.018616859036865094,
+           -0.05183507703264444,
+           -0.08045338630390604,
+           -0.1055233179776993,
+           -0.1282343759178826,
+           -0.1498775460472136,
+           -0.17180578018269743,
+           -0.1953925089780281,
+           -0.22198929230736514,
+           -0.2528837407876567,
+           -0.2892588384489662,
+           -0.33215476388160803,
+           -0.382434246303497,
+           -0.4407524053999841,
+           -0.5075319116643321,
+           -0.5829441701026945,
+           -0.6668970779060642,
+           -0.7590297398435623,
+           -0.8587143478793965,
+           -0.965065248310402,
+           -1.076955035169856,
+           -1.1930373273960289,
+           -1.3117757138953898,
+           -1.4314781895275215,
+           -1.5503362602891628,
+           -1.6664677712654203,
+           -1.7779624094406041,
+           -1.88292875783818,
+           -1.9795417296690587,
+           -2.0660891924980365,
+           -2.1410166034556783,
+           -2.2029685170538453,
+           -2.250825896298789,
+           -2.283738253913688,
+           -2.3011497712853206,
+           -2.3028186853211574,
+           -2.288829394280418,
+           -2.2595969089001686,
+           -2.2158634604848815,
+           -2.1586872685147696,
+           -2.089423662057544,
+           -2.0096989371119593,
+           -1.9213775113274751,
+           -1.8265231038916738,
+           -1.7273548176263749,
+           -1.6261991287685318,
+           -1.525438894323336,
+           -1.427460564641419,
+           -1.3346008380167294,
+           -1.2490940133565298,
+           -1.1730212858013553,
+           -1.1082631887803713,
+           -1.056456315328142,
+           -1.0189553532340105,
+           -0.9968013450966603,
+           -0.990696938586294,
+           -1.0009892276980177,
+           -1.027660606496738,
+           -1.0703278671562473,
+           -1.1282495785907334,
+           -1.2003415854183055,
+           -1.2852002741635205,
+           -1.3811330691901964,
+           -1.486195449342054,
+           -1.5982336218277016,
+           -1.7149318562694882,
+           -1.8338633722851487,
+           -1.9525435911385454,
+           -2.0684845078780114,
+           -2.1792489162711592,
+           -2.282503225300172,
+           -2.376067642811287,
+           -2.457962568180238,
+           -2.526450129906877,
+           -2.5800699235526205,
+           -2.6176681474276693,
+           -2.6384194944177337,
+           -2.641841334347785,
+           -2.627799907985004,
+           -2.5965084466010246,
+           -2.548517325218209,
+           -2.4846965485030967,
+           -2.406211051080802,
+           -2.31448946437138,
+           -2.2111871557530423,
+           -2.0981444792151347,
+           -1.9773412864627522,
+           -1.8508488310485514,
+           -1.720780253561698,
+           -1.5892408619246725,
+           -1.458279416890842,
+           -1.3298415990979386,
+           -1.2057267714489266,
+           -1.0875490608095233,
+           -0.9767036683473477,
+           -0.8743391812205313,
+           -0.7813365032208555,
+           -0.6982948523059053,
+           -0.6255250929882553,
+           -0.5630504858055111,
+           -0.5106147492244587,
+           -0.4676971460059496,
+           -0.43353413084532477,
+           -0.4071469333654728,
+           -0.38737430431464537,
+           -0.3729095267268974,
+           -0.3623406909468952,
+           -0.3541931553231521,
+           -0.3469730649050709,
+           -0.3392107798147823,
+           -0.329503073555658,
+           -0.31655299908212203,
+           -0.2992063859797268,
+           -0.27648402387916116,
+           -0.24760870288453257,
+           -0.21202641836862018,
+           -0.16942120148682482,
+           -0.1197232042628399,
+           -0.06310984484180572,
+           -6.163919815048678e-16
+          ],
+          [
+           0,
+           0.07067583798832583,
+           0.14588450691536492,
+           0.22450311583667845,
+           0.3052725817926329,
+           0.3868342965244368,
+           0.46776974677520067,
+           0.546642030382914,
+           0.622038158813995,
+           0.6926110136461597,
+           0.7571198304022406,
+           0.8144681179457225,
+           0.8637379845292436,
+           0.9042199309865815,
+           0.9354372852549463,
+           0.9571645875720233,
+           0.9694393889319411,
+           0.9725670928677337,
+           0.9671186481528204,
+           0.9539210831197057,
+           0.934041056372137,
+           0.908761779076778,
+           0.8795538362049741,
+           0.8480405936951413,
+           0.8159590214691869,
+           0.7851168849181016,
+           0.757347356728372,
+           0.7344621741871993,
+           0.7182045124595856,
+           0.7102027605458519,
+           0.7119263732001487,
+           0.7246449292530113,
+           0.7493914555013481,
+           0.7869309772850777,
+           0.8377351344082828,
+           0.9019635571439693,
+           0.9794525351847576,
+           1.0697113365203479,
+           1.171926347645811,
+           1.284973015792084,
+           1.4074353827181318,
+           1.5376328127307166,
+           1.6736533396245847,
+           1.8133928925746372,
+           1.9545995137541543,
+           2.094921554269775,
+           2.2319587330523705,
+           2.3633148681894394,
+           2.486651043740111,
+           2.5997379585454885,
+           2.7005062174085355,
+           2.7870933689955715,
+           2.8578865678925607,
+           2.911559838703741,
+           2.947105045504086,
+           2.9638558173312988,
+           2.9615038461665906,
+           2.9401071539913906,
+           2.9000901156487027,
+           2.8422352197640444,
+           2.7676667461382265,
+           2.6778267300411986,
+           2.5744437670410805,
+           2.45949538193792,
+           2.335164837904841,
+           2.20379339336259,
+           2.0678291212372155,
+           1.9297734854796669,
+           1.7921269211252375,
+           1.6573346855106603,
+           1.5277342390551365,
+           1.4055053745043407,
+           1.2926242447313796,
+           1.1908223428000773,
+           1.10155136641244,
+           1.025954755087254,
+           0.9648465259942576,
+           0.9186978572950986,
+           0.8876316804688572,
+           0.8714253500233545,
+           0.8695212649437767,
+           0.8810451259533644,
+           0.9048313308022696,
+           0.9394548407900362,
+           0.9832686996699175,
+           1.0344462546595614,
+           1.091027021656929,
+           1.1509650555039623,
+           1.2121786331690176,
+           1.2726000342455261,
+           1.3302242096706913,
+           1.3831551657939924,
+           1.4296489558759948,
+           1.4681522630698258,
+           1.4973356755614484,
+           1.516120892845596,
+           1.5237012585859913,
+           1.5195551862021144,
+           1.5034522239467745,
+           1.4754516922583851,
+           1.4358940129342548,
+           1.385385032513206,
+           1.3247738166223073,
+           1.2551245535992317,
+           1.1776833504434732,
+           1.0938408284992736,
+           1.0050915271702991,
+           0.9129911989430046,
+           0.8191131262379633,
+           0.7250046089994159,
+           0.6321447610816177,
+           0.5419047137384927,
+           0.4555112569377766,
+           0.3740148555668143,
+           0.298262860291286,
+           0.2288785948788829,
+           0.1662468467317362,
+           0.11050611913537939,
+           0.061547826607777766,
+           0.019022433219228273,
+           -0.017647647539671088,
+           -0.049248749239410736,
+           -0.07675077041890808,
+           -0.10127679263759558,
+           -0.12406831359673921,
+           -0.14644702556326164,
+           -0.16977416080711427,
+           -0.19540849107568878,
+           -0.22466410560004527,
+           -0.2587691007826281,
+           -0.29882629430494656,
+           -0.3457770273985062,
+           -0.4003690426456099,
+           -0.46312932281152713,
+           -0.5343426513925315,
+           -0.6140365109127072,
+           -0.7019727741362519,
+           -0.7976464703141362,
+           -0.900291727699557,
+           -1.008894809394331,
+           -1.1222139767671948,
+           -1.2388057378284503,
+           -1.3570568715252218,
+           -1.4752214671574018,
+           -1.5914620848662278,
+           -1.7038940318202422,
+           -1.8106316621808822,
+           -1.9098355494217947,
+           -1.9997593486826222,
+           -2.0787951654277035,
+           -2.145516274888941,
+           -2.1987160939973465,
+           -2.2374423924229885,
+           -2.2610258399297134,
+           -2.269102120847298,
+           -2.2616269998300647,
+           -2.2388838924696346,
+           -2.2014836756162133,
+           -2.1503566609894493,
+           -2.086736847184074,
+           -2.012138754775411,
+           -1.9283273322212056,
+           -1.8372815921081518,
+           -1.7411527937389328,
+           -1.6422181252057206,
+           -1.5428309525237374,
+           -1.4453687922328637,
+           -1.3521802248711698,
+           -1.2655319983168318,
+           -1.1875575713419717,
+           -1.1202083187222796,
+           -1.06520856054543,
+           -1.024015491334955,
+           -0.9977849713273333,
+           -0.9873440054288494,
+           -0.9931705783349788,
+           -1.0153813408187589,
+           -1.053727456491274,
+           -1.1075987249159205,
+           -1.1760359005191532,
+           -1.257750932061255,
+           -1.3511546592473949,
+           -1.4543913259507157,
+           -1.5653791077933574,
+           -1.6818557094211204,
+           -1.801427967171469,
+           -1.921624298874702,
+           -2.0399487765162316,
+           -2.153935561011136,
+           -2.2612024322642257,
+           -2.359502172127584,
+           -2.446770612195136,
+           -2.5211702412290493,
+           -2.5811283763382487,
+           -2.625369035120622,
+           -2.6529377995535306,
+           -2.6632191326900214,
+           -2.6559457920042795,
+           -2.6312001740412705,
+           -2.589407619184488,
+           -2.53132189810949,
+           -2.458003288129246,
+           -2.370789823608662,
+           -2.2712624656493006,
+           -2.1612050784162684,
+           -2.042560219364783,
+           -1.9173818453475104,
+           -1.7877861038947742,
+           -1.6559014172893671,
+           -1.5238190755560082,
+           -1.3935455330410962,
+           -1.2669575525013386,
+           -1.1457612619033193,
+           -1.0314560845034833,
+           -0.9253043749092891,
+           -0.828307445968477,
+           -0.7411885072338389,
+           -0.6643828595394253,
+           -0.598035506327024,
+           -0.5420061553862927,
+           -0.4958813992912398,
+           -0.45899368365389165,
+           -0.4304465038312187,
+           -0.409145117096476,
+           -0.3938319223241053,
+           -0.38312554626728473,
+           -0.37556258730161873,
+           -0.3696409062152368,
+           -0.3638633207145358,
+           -0.3567805565424396,
+           -0.34703233349675533,
+           -0.33338551848297865,
+           -0.31476835861845437,
+           -0.2902999132256654,
+           -0.25931393159044797,
+           -0.2213765703392936,
+           -0.17629750645906134,
+           -0.1241341752139477,
+           -0.06518904210514488,
+           -6.342377667793834e-16
+          ],
+          [
+           0,
+           0.07222168509187751,
+           0.14847958124161675,
+           0.22757994607920434,
+           0.3082124587357634,
+           0.38898857571944784,
+           0.4684822458486646,
+           0.5452718954003763,
+           0.6179825593730971,
+           0.6853270283248826,
+           0.7461449028170299,
+           0.7994384985346207,
+           0.8444046234081827,
+           0.8804613515829938,
+           0.9072690452921067,
+           0.9247450214303905,
+           0.9330714212487614,
+           0.9326960150350831,
+           0.9243258545625064,
+           0.9089138699145837,
+           0.8876386894059215,
+           0.861878137109218,
+           0.8331770275262587,
+           0.8032100270153273,
+           0.773740482890539,
+           0.7465762302822019,
+           0.7235234710806205,
+           0.7063398763856737,
+           0.6966880923312018,
+           0.6960908281389955,
+           0.7058886747077097,
+           0.7272017426191264,
+           0.7608961215307702,
+           0.8075560505902506,
+           0.8674625544604478,
+           0.9405791450641546,
+           1.0265450190106065,
+           1.124675999020593,
+           1.2339732789821447,
+           1.353139841190255,
+           1.480604225566372,
+           1.614551148883774,
+           1.7529583017481,
+           1.8936384965280233,
+           2.034286204449523,
+           2.1725274080333814,
+           2.3059716087845126,
+           2.4322647717192907,
+           2.549141959444132,
+           2.654478409854058,
+           2.7463378431401546,
+           2.823016844972003,
+           2.8830842620205,
+           2.9254146612801586,
+           2.9492150431697555,
+           2.954044156794503,
+           2.9398239402090502,
+           2.906842794798758,
+           2.855750596473725,
+           2.7875455425407663,
+           2.703553127111469,
+           2.6053977249990083,
+           2.49496743969927,
+           2.374373030968774,
+           2.2459018778132127,
+           2.111968049976238,
+           1.9750596524227404,
+           1.837684670632073,
+           1.7023165782307517,
+           1.5713409718024771,
+           1.4470044705623475,
+           1.3313670616638502,
+           1.2262589866425193,
+           1.133243153002507,
+           1.053583919976274,
+           0.9882229523599126,
+           0.9377626648641114,
+           0.9024575958361629,
+           0.882213858005751,
+           0.8765966197711959,
+           0.8848453782226176,
+           0.9058965992910133,
+           0.9384131256462845,
+           0.9808195934918846,
+           1.0313429590838743,
+           1.0880571180236598,
+           1.1489305079602774,
+           1.2118755204824865,
+           1.2747985121914984,
+           1.3356491990094503,
+           1.3924682417452625,
+           1.4434318841174425,
+           1.4868925854109174,
+           1.5214146966252355,
+           1.5458043586257044,
+           1.5591329501450772,
+           1.5607535787283835,
+           1.5503102847081225,
+           1.5277398125994845,
+           1.4932659913021356,
+           1.4473869495161473,
+           1.3908555712142385,
+           1.32465376342422,
+           1.2499612608122816,
+           1.1681198248550628,
+           1.0805938064624105,
+           0.9889281270416942,
+           0.8947047920857163,
+           0.7994990820079628,
+           0.7048365664440218,
+           0.6121520606215526,
+           0.5227515864379243,
+           0.4377783180495746,
+           0.35818338421802853,
+           0.2847022701400943,
+           0.21783741332846965,
+           0.15784742508356314,
+           0.10474319535730076,
+           0.05829095877108148,
+           0.01802221778380205,
+           -0.016749759876264477,
+           -0.04690732386310397,
+           -0.07350031798764685,
+           -0.09771320902753035,
+           -0.12082834988546393,
+           -0.1441863611794256,
+           -0.16914469189498038,
+           -0.19703546909859762,
+           -0.22912376762924164,
+           -0.26656742259816746,
+           -0.31037947060878185,
+           -0.3613942407608223,
+           -0.4202380253314459,
+           -0.48730514479988957,
+           -0.5627400854797827,
+           -0.6464262338580384,
+           -0.7379815636766177,
+           -0.8367614540533782,
+           -0.9418686339903443,
+           -1.0521700650693875,
+           -1.16632039461681,
+           -1.2827914406672465,
+           -1.3999070120040176,
+           -1.5158822254139166,
+           -1.6288663616691461,
+           -1.736988204731899,
+           -1.8384027377779038,
+           -1.9313380267161246,
+           -2.014141108110876,
+           -2.085321714231794,
+           -2.1435927130722634,
+           -2.187906214562504,
+           -2.217484394127615,
+           -2.2318442088073245,
+           -2.2308153263607147,
+           -2.2145507505914077,
+           -2.183529802567021,
+           -2.1385533031443873,
+           -2.080730992682081,
+           -2.011461414329767,
+           -1.9324046731241842,
+           -1.8454486596940798,
+           -1.752669490300129,
+           -1.6562870601581097,
+           -1.5586167308909498,
+           -1.4620182724224524,
+           -1.3688432521544587,
+           -1.2813821080111059,
+           -1.2018121557443384,
+           -1.1321477643659217,
+           -1.0741938870387386,
+           -1.0295040592991171,
+           -0.9993438738789253,
+           -0.9846608141065825,
+           -0.9860611789546609,
+           -1.0037946658660426,
+           -1.0377469965748447,
+           -1.0874407806321607,
+           -1.1520446158786546,
+           -1.2303902294291145,
+           -1.3209972716089462,
+           -1.4221051933604423,
+           -1.5317114693451896,
+           -1.647615278402198,
+           -1.7674656238411095,
+           -1.8888127713928067,
+           -2.0091618050432176,
+           -2.1260270523135696,
+           -2.236986111986451,
+           -2.3397322292395897,
+           -2.4321238053171337,
+           -2.5122299001828226,
+           -2.5783706852870254,
+           -2.629151927199155,
+           -2.6634927283583925,
+           -2.680645914995716,
+           -2.6802106403519463,
+           -2.662136959288083,
+           -2.626722323646659,
+           -2.574600141544996,
+           -2.5067207334251758,
+           -2.4243251985242154,
+           -2.3289128730588593,
+           -2.2222032117731287,
+           -2.106093053936596,
+           -1.9826103402930033,
+           -1.8538654263265848,
+           -1.722001187680776,
+           -1.5891431344797033,
+           -1.4573507422479408,
+           -1.32857116842031,
+           -1.204596456136175,
+           -1.0870252328813357,
+           -0.9772297929960795,
+           -0.8763293131296932,
+           -0.7851697919336862,
+           -0.7043111336268217,
+           -0.6340216138483652,
+           -0.5742797799838752,
+           -0.5247836515568106,
+           -0.4849669039836751,
+           -0.45402154552856516,
+           -0.43092643697210925,
+           -0.4144808603006208,
+           -0.4033422201589938,
+           -0.39606686290755255,
+           -0.39115292529330453,
+           -0.3870840797476127,
+           -0.3823730272126758,
+           -0.3756036015104687,
+           -0.36547039119862407,
+           -0.3508148544846523,
+           -0.3306569982758385,
+           -0.3042218113624574,
+           -0.2709597810169943,
+           -0.23056097838353312,
+           -0.18296236695227283,
+           -0.12834816586787845,
+           -0.06714328129962494,
+           -6.506915612942914e-16
+          ],
+          [
+           0,
+           0.07358206353148818,
+           0.15066997939661228,
+           0.23000934037892476,
+           0.31024972576644144,
+           0.3899844111217896,
+           0.4677918238836619,
+           0.5422776343846568,
+           0.6121163531714686,
+           0.6760913157839148,
+           0.7331319751563795,
+           0.7823474885917702,
+           0.8230556791664128,
+           0.8548065681375789,
+           0.8773998125250047,
+           0.8908955370763034,
+           0.8956182184131085,
+           0.8921534570535695,
+           0.8813376557408242,
+           0.8642408054710917,
+           0.8421427591907198,
+           0.8165035428026078,
+           0.7889284095879043,
+           0.7611284834308043,
+           0.7348779547774019,
+           0.7119688880209061,
+           0.6941647675307793,
+           0.6831539500292559,
+           0.6805042023584981,
+           0.6876194854941983,
+           0.7057000983013811,
+           0.7357072190783541,
+           0.778332781180442,
+           0.8339754934004844,
+           0.9027236693514686,
+           0.9843453664159992,
+           1.0782861579020457,
+           1.1836746762169523,
+           1.2993358747150114,
+           1.4238117660784402,
+           1.555389210349342,
+           1.6921341506180545,
+           1.8319315332399073,
+           1.97253000631003,
+           2.111590368550411,
+           2.2467366438061,
+           2.375608586457605,
+           2.4959143820214575,
+           2.6054822961100452,
+           2.7023100440997627,
+           2.784610702913612,
+           2.8508540641255253,
+           2.899802432296167,
+           2.930540001547511,
+           2.9424950937681547,
+           2.9354547098790493,
+           2.9095710272093687,
+           2.865359666827093,
+           2.8036897500023494,
+           2.7257659581032008,
+           2.6331030003849767,
+           2.527493074706509,
+           2.410967072793588,
+           2.285750430217013,
+           2.154214648146046,
+           2.0188256160941025,
+           1.882089939814316,
+           1.7465005244166636,
+           1.6144826785656965,
+           1.4883419909160196,
+           1.3702151851361488,
+           1.2620250860812046,
+           1.1654407287314938,
+           1.0818435159108704,
+           1.0123001836313503,
+           0.9575431677993642,
+           0.9179587870203115,
+           0.8935834677434477,
+           0.8841080446168763,
+           0.888889975404075,
+           0.9069731208765028,
+           0.9371145603487848,
+           0.9778177473372778,
+           1.0273711612317047,
+           1.0838914834646656,
+           1.1453702235084398,
+           1.2097226435822108,
+           1.274837783011863,
+           1.338628364838199,
+           1.3990793788741371,
+           1.4542941765830684,
+           1.5025369827748634,
+           1.542270825377522,
+           1.5721900049703152,
+           1.5912463672946682,
+           1.5986688010118602,
+           1.5939755555454096,
+           1.5769791555976704,
+           1.547783875313395,
+           1.5067759214216587,
+           1.4546066563763886,
+           1.3921693650162097,
+           1.3205702272967559,
+           1.2410943012782794,
+           1.155167441286316,
+           1.0643151730404028,
+           0.9701196182046272,
+           0.8741756035536781,
+           0.7780471037708584,
+           0.6832251515276315,
+           0.5910883043977088,
+           0.5028666865117817,
+           0.41961052553086625,
+           0.3421639850181757,
+           0.2711449517113362,
+           0.20693128012953993,
+           0.14965382739563352,
+           0.09919643342274435,
+           0.05520282022288102,
+           0.017090203643504196,
+           -0.01593076409653429,
+           -0.044830267683113656,
+           -0.0707285152551351,
+           -0.0948606685741214,
+           -0.11853845872141087,
+           -0.14310951661965937,
+           -0.16991550867292537,
+           -0.20025020086274695,
+           -0.23531857886859128,
+           -0.2761981270676187,
+           -0.3238033162078974,
+           -0.37885426945237277,
+           -0.4418504713515439,
+           -0.5130502567468362,
+           -0.5924566698269812,
+           -0.6798101212369562,
+           -0.774588097349314,
+           -0.8760119949213476,
+           -0.9830609709337184,
+           -1.0944925160630552,
+           -1.2088692855642869,
+           -1.3245915577508303,
+           -1.4399345419143021,
+           -1.5530896281990745,
+           -1.662208564949979,
+           -1.765449467141237,
+           -1.861023504806981,
+           -1.9472410943877911,
+           -2.0225564193305177,
+           -2.0856091391430915,
+           -2.13526220769166,
+           -2.170634810395598,
+           -2.1911295440055882,
+           -2.196453099088847,
+           -2.186629860877856,
+           -2.1620080149666796,
+           -2.1232579262757914,
+           -2.071362748280782,
+           -2.0076014100662434,
+           -1.9335243166177247,
+           -1.8509222782530297,
+           -1.7617893537427385,
+           -1.6682804442849613,
+           -1.5726646082750524,
+           -1.4772751764237297,
+           -1.384457830467419,
+           -1.2965178643578192,
+           -1.2156678729761625,
+           -1.1439771093762396,
+           -1.0833237173474342,
+           -1.0353509824736893,
+           -1.0014286533403318,
+           -0.9826202672890763,
+           -0.9796572749578806,
+           -0.9929205981483684,
+           -1.0224300802030657,
+           -1.067842101300383,
+           -1.128455437422575,
+           -1.203225245928838,
+           -1.2907848674362676,
+           -1.3894749477788118,
+           -1.4973792097049485,
+           -1.6123660459273856,
+           -1.732134966997967,
+           -1.8542668226081795,
+           -1.9762766260986564,
+           -2.095667751351806,
+           -2.209986240300078,
+           -2.3168739587418603,
+           -2.4141193680068356,
+           -2.4997047394969107,
+           -2.5718487267682675,
+           -2.629043323445079,
+           -2.670084372063258,
+           -2.694094945564889,
+           -2.7005410957501064,
+           -2.689239647306468,
+           -2.660357907557291,
+           -2.614405356110478,
+           -2.5522175704039123,
+           -2.4749328280507523,
+           -2.3839620003833972,
+           -2.280952509462778,
+           -2.1677472592363256,
+           -2.046339567155601,
+           -1.918825212633346,
+           -1.7873527810953591,
+           -1.6540735156176705,
+           -1.5210918915091791,
+           -1.3904181027184852,
+           -1.263923593362274,
+           -1.1433006844612743,
+           -1.0300272372781407,
+           -0.9253371632560712,
+           -0.830197439789482,
+           -0.7452921247241389,
+           -0.6710136847667824,
+           -0.6074617683391241,
+           -0.5544493664566283,
+           -0.5115161206140036,
+           -0.4779483590125663,
+           -0.45280527618296407,
+           -0.4349505202598268,
+           -0.4230883205777174,
+           -0.4158031791178295,
+           -0.41160206531232746,
+           -0.4089579968447739,
+           -0.40635386072439816,
+           -0.40232532969610246,
+           -0.3955017588831381,
+           -0.38464400562287054,
+           -0.36867820021889824,
+           -0.3467246045979228,
+           -0.3181208268175848,
+           -0.2824388086711467,
+           -0.2394951674680393,
+           -0.1893546472661827,
+           -0.1323266149658324,
+           -0.06895471817307579,
+           -6.65603414021828e-16
+          ],
+          [
+           0,
+           0.0747445873466161,
+           0.15243578420018497,
+           0.2317692211121555,
+           0.3113658444096506,
+           0.38981263339317096,
+           0.4657044369965594,
+           0.5376858075648971,
+           0.6044917073754935,
+           0.6649859903667943,
+           0.7181966165961248,
+           0.7633466388547097,
+           0.7998801075849786,
+           0.8274821691017755,
+           0.8460927798866794,
+           0.8559136226944847,
+           0.857407984287252,
+           0.8512935354135746,
+           0.8385281366228178,
+           0.8202889740284434,
+           0.7979455026474689,
+           0.7730268370490787,
+           0.7471843756270155,
+           0.722150572131861,
+           0.699694872900051,
+           0.6815779177933037,
+           0.6695051551374394,
+           0.6650810445240815,
+           0.6697650155272632,
+           0.6848303152367022,
+           0.7113268137997598,
+           0.7500487463880635,
+           0.8015082543333942,
+           0.8659154504064771,
+           0.9431655766936979,
+           1.0328336520862007,
+           1.1341768242384154,
+           1.2461444524595084,
+           1.3673957580170437,
+           1.4963246914525543,
+           1.6310914873625946,
+           1.7696602101334677,
+           1.9098414434890223,
+           2.049339146179218,
+           2.185800588974492,
+           2.3168682070392523,
+           2.4402321488007908,
+           2.553682278982141,
+           2.655158400178845,
+           2.7427974941390603,
+           2.814976849922916,
+           2.8703520398193523,
+           2.907888823053322,
+           2.9268881990612234,
+           2.927003993028079,
+           2.908252532571928,
+           2.871014161656231,
+           2.8160265314631285,
+           2.744369803360381,
+           2.657444091487836,
+           2.556939657191304,
+           2.444800540044708,
+           2.3231824663241345,
+           2.194406011728953,
+           2.060906107578255,
+           1.9251790659133088,
+           1.7897283568187812,
+           1.6570103994407628,
+           1.5293816259600026,
+           1.4090480452496843,
+           1.2980184709264864,
+           1.198062488530606,
+           1.1106741208677906,
+           1.0370420119649,
+           0.9780267920389702,
+           0.9341461122402704,
+           0.9055676529621326,
+           0.8921102177465153,
+           0.8932528309468395,
+           0.908151566075933,
+           0.9356636478322207,
+           0.9743781986398625,
+           1.0226528443395264,
+           1.0786552572070986,
+           1.140408601046184,
+           1.205839755411957,
+           1.2728291361542166,
+           1.3392608988018095,
+           1.4030723105112162,
+           1.4623011052924137,
+           1.5151296951931326,
+           1.559925195541565,
+           1.5952743330152253,
+           1.6200124383976993,
+           1.6332458780339592,
+           1.6343674453626083,
+           1.6230644122849167,
+           1.599319125056977,
+           1.5634022162414845,
+           1.5158586883709024,
+           1.4574873017739622,
+           1.3893138641146918,
+           1.3125591685009874,
+           1.2286024568540446,
+           1.1389413924005307,
+           1.0451496070387005,
+           0.9488329439572053,
+           0.8515855419563619,
+           0.7549469048588159,
+           0.6603610673527951,
+           0.5691389084661649,
+           0.4824245772057812,
+           0.4011668839599757,
+           0.3260963789045679,
+           0.25770868826084903,
+           0.19625451466314564,
+           0.1417365332924015,
+           0.09391323525663536,
+           0.05230958852193492,
+           0.01623420911310719,
+           -0.015197434187660846,
+           -0.043034415517693624,
+           -0.0684571225917115,
+           -0.0927402977399718,
+           -0.11721334251673893,
+           -0.14321895137152943,
+           -0.17207118484611555,
+           -0.20501410924392888,
+           -0.24318211727762734,
+           -0.2875630031260594,
+           -0.3389647966362693,
+           -0.39798726679845997,
+           -0.4649988864650783,
+           -0.5401199115376857,
+           -0.623212071986698,
+           -0.7138752030140174,
+           -0.8114509666683829,
+           -0.9150336317603373,
+           -1.0234876975993146,
+           -1.1354719694944593,
+           -1.2494695256170822,
+           -1.3638228599862512,
+           -1.4767733489484123,
+           -1.5865040720868608,
+           -1.6911849260083045,
+           -1.7890189033097879,
+           -1.8782883709740463,
+           -1.9574001735201145,
+           -2.024928406769449,
+           -2.0796537576609477,
+           -2.1205983830218367,
+           -2.147055403737545,
+           -2.1586122178714664,
+           -2.155166983881631,
+           -2.1369377895658044,
+           -2.1044641997115834,
+           -2.0586010612772507,
+           -2.000504634705265,
+           -1.9316113089883564,
+           -1.853609341691695,
+           -1.768404238731263,
+           -1.6780785480035525,
+           -1.5848469819843325,
+           -1.491007903637189,
+           -1.3988923043999233,
+           -1.3108114702579428,
+           -1.2290045702440107,
+           -1.1555874101080428,
+           -1.092503572097896,
+           -1.0414791102455787,
+           -1.0039818904570303,
+           -0.9811865579561055,
+           -0.9739459837900319,
+           -0.982769890314868,
+           -1.0078111865138406,
+           -1.0488603617548202,
+           -1.105348095589297,
+           -1.1763560460758593,
+           -1.2606355846229096,
+           -1.3566340562221644,
+           -1.4625279647916898,
+           -1.5762623185277178,
+           -1.6955952236920748,
+           -1.8181466907012025,
+           -1.941450516763353,
+           -2.0630080370501576,
+           -2.180342493236429,
+           -2.291052755232917,
+           -2.3928651493680295,
+           -2.48368219369843,
+           -2.561627117362102,
+           -2.625083144045013,
+           -2.6727266471684206,
+           -2.7035534331790294,
+           -2.71689757568195,
+           -2.712442403012814,
+           -2.69022343079126,
+           -2.650623224406607,
+           -2.594358369528306,
+           -2.52245891689288,
+           -2.4362408462097402,
+           -2.3372722587071877,
+           -2.2273341546137986,
+           -2.1083767771936146,
+           -1.9824726058149111,
+           -1.851767154529366,
+           -1.7184287780355323,
+           -1.584598702670501,
+           -1.4523424859229472,
+           -1.3236040643356184,
+           -1.2001634777382075,
+           -1.0835992593935064,
+           -0.9752563593704934,
+           -0.8762203253847334,
+           -0.7872983050837241,
+           -0.709007260336145,
+           -0.6415696018599168,
+           -0.5849162660534027,
+           -0.5386970698317773,
+           -0.5022979982503902,
+           -0.4748649082165002,
+           -0.455332973900847,
+           -0.4424610594583098,
+           -0.4348700858002116,
+           -0.43108436334260986,
+           -0.42957479419129657,
+           -0.428802806757729,
+           -0.42726387426982654,
+           -0.4235294862600174,
+           -0.4162864883622549,
+           -0.40437277939480315,
+           -0.38680845382615237,
+           -0.36282159976053857,
+           -0.33186810440794756,
+           -0.2936449769989774,
+           -0.24809686924270735,
+           -0.19541565137998665,
+           -0.13603308313667767,
+           -0.07060679883360586,
+           -6.788373241547723e-16
+          ],
+          [
+           0,
+           0.07569866409975042,
+           0.15376092102971542,
+           0.23284355676771024,
+           0.31155057279012655,
+           0.38847455628529975,
+           0.4622385359793738,
+           0.5315371990207443,
+           0.5951763589669321,
+           0.6521096080376013,
+           0.7014711573720481,
+           0.7426039652992383,
+           0.7750823731850751,
+           0.7987286082682041,
+           0.8136226695216152,
+           0.8201052820455376,
+           0.81877378354273,
+           0.8104709885637038,
+           0.7962672578409712,
+           0.7774361765677898,
+           0.7554244124483532,
+           0.7318164775155295,
+           0.7082952531802623,
+           0.6865992522813168,
+           0.6684776821063186,
+           0.6556444361138337,
+           0.6497321777171399,
+           0.6522476860088872,
+           0.6645296104527176,
+           0.6877097298168321,
+           0.7226787311711959,
+           0.7700574195037883,
+           0.8301741399686541,
+           0.9030490460815009,
+           0.9883856819577032,
+           1.0855701689924742,
+           1.1936781015823952,
+           1.3114890671613737,
+           1.437508517650111,
+           1.56999653705589,
+           1.7070028779349498,
+           1.8464074820227212,
+           1.9859655614754481,
+           2.1233562003276467,
+           2.2562333438940363,
+           2.3822779792627373,
+           2.4992502744002207,
+           2.6050404376692433,
+           2.697717083965026,
+           2.775571947677726,
+           2.837159865036953,
+           2.8813330571344045,
+           2.9072688774497757,
+           2.914490340831369,
+           2.9028789209052315,
+           2.872679285685127,
+           2.824495832292687,
+           2.7592810765264226,
+           2.6783161467994834,
+           2.583183819980882,
+           2.4757347143436497,
+           2.3580474178174446,
+           2.232383474091667,
+           2.101138271302716,
+           1.9667889750923895,
+           1.8318407173852678,
+           1.6987722926162763,
+           1.5699826233748573,
+           1.447739237287193,
+           1.3341299469440338,
+           1.231018846041614,
+           1.1400076295792128,
+           1.0624031165440302,
+           0.999191703194288,
+           0.9510213075164766,
+           0.9181911847918247,
+           0.9006498048861076,
+           0.898000788508981,
+           0.9095167069999426,
+           0.934160362890188,
+           0.9706129911258788,
+           1.0173086577298396,
+           1.0724739877786675,
+           1.1341722313792626,
+           1.200350577800462,
+           1.2688895563968043,
+           1.3376533201270626,
+           1.4045395942843197,
+           1.4675280897479104,
+           1.5247262261331835,
+           1.5744110844212411,
+           1.615066609072955,
+           1.6454152037010528,
+           1.664443008942541,
+           1.67141831259236,
+           1.6659027162695261,
+           1.6477548655227852,
+           1.617126736778369,
+           1.5744526602365927,
+           1.5204314381160182,
+           1.4560020880477293,
+           1.3823138977182616,
+           1.3006916151891295,
+           1.2125967162810922,
+           1.1195857831404137,
+           1.0232670943515778,
+           0.9252565651418017,
+           0.8271341854578398,
+           0.7304020838321205,
+           0.636445296568866,
+           0.5464962461618049,
+           0.46160383197399596,
+           0.38260791266899236,
+           0.31011981684828865,
+           0.24450935947515293,
+           0.18589867099595778,
+           0.13416296794557064,
+           0.0889382127648318,
+           0.04963543115756356,
+           0.015461282118370364,
+           -0.014555686841723451,
+           -0.04153381463832999,
+           -0.06670297652855761,
+           -0.09136606149969533,
+           -0.11685831286268186,
+           -0.14450562442448917,
+           -0.17558291322487374,
+           -0.21127368966244092,
+           -0.25263191688737807,
+           -0.30054719431356464,
+           -0.3557142164190507,
+           -0.4186073497514737,
+           -0.4894610409449275,
+           -0.5682566198510905,
+           -0.6547158983254924,
+           -0.7483017909036422,
+           -0.8482260029406893,
+           -0.9534636493277338,
+           -1.0627744872454212,
+           -1.1747302741150785,
+           -1.2877476013267457,
+           -1.400125409543153,
+           -1.5100862660907113,
+           -1.6158203823641504,
+           -1.7155312719385054,
+           -1.8074819002201654,
+           -1.8900401553164319,
+           -1.9617224779841518,
+           -2.021234525925589,
+           -2.0675078134960208,
+           -2.0997313605258685,
+           -2.1173775012205263,
+           -2.1202211431454696,
+           -2.1083519237460617,
+           -2.0821788838387065,
+           -2.042427459820419,
+           -1.99012878448916,
+           -1.9266014757043994,
+           -1.8534262779629551,
+           -1.7724140997122682,
+           -1.6855681544550782,
+           -1.595041062299674,
+           -1.503087896864064,
+           -1.4120162671315464,
+           -1.3241346023356062,
+           -1.2416998582210077,
+           -1.1668658837747707,
+           -1.1016336781600293,
+           -1.0478047282713259,
+           -1.0069385489543612,
+           -0.9803154521038893,
+           -0.9689054498557502,
+           -0.973344053829464,
+           -0.993915570313202,
+           -1.0305443143361332,
+           -1.0827939780358498,
+           -1.1498751951569104,
+           -1.230661148618244,
+           -1.3237108766062156,
+           -1.427299749249907,
+           -1.539456417083566,
+           -1.658005378360639,
+           -1.780614178609413,
+           -1.9048441458656635,
+           -2.02820348145793,
+           -2.148201471082905,
+           -2.26240255552458,
+           -2.3684790053441342,
+           -2.464260979057912,
+           -2.547782808848916,
+           -2.617324450124764,
+           -2.6714471489673057,
+           -2.7090225218178263,
+           -2.729254401159799,
+           -2.7316929755859616,
+           -2.7162409381869916,
+           -2.6831515491320133,
+           -2.633018711932567,
+           -2.5667593534626936,
+           -2.4855885807015827,
+           -2.3909882579211743,
+           -2.284669802513977,
+           -2.1685321321090654,
+           -2.0446158068186544,
+           -1.9150544957342068,
+           -1.7820249541339805,
+           -1.6476967259499031,
+           -1.5141827842711193,
+           -1.3834922911733911,
+           -1.2574865978302798,
+           -1.137839518266269,
+           -1.026002797507899,
+           -0.9231775601437487,
+           -0.8302923718273568,
+           -0.7479883779141842,
+           -0.6766118044403457,
+           -0.6162139215071603,
+           -0.5665583824539445,
+           -0.5271356686327485,
+           -0.49718419370544975,
+           -0.4757174575268429,
+           -0.4615564919092631,
+           -0.45336671252661637,
+           -0.4496981860504271,
+           -0.449028241881968,
+           -0.4498053054762717,
+           -0.4504928064813204,
+           -0.4496120202568652,
+           -0.44578273557973236,
+           -0.43776070355032803,
+           -0.4244709112525713,
+           -0.4050358362931874,
+           -0.3787979720626415,
+           -0.3453360649982166,
+           -0.3044746704284101,
+           -0.256286808531164,
+           -0.20108968210245415,
+           -0.1394335986352553,
+           -0.072084416068499,
+           -6.902725177417421e-16
+          ],
+          [
+           0,
+           0.07643559224875435,
+           0.15463330275205334,
+           0.23322250089548358,
+           0.3108020432057526,
+           0.3859819375465093,
+           0.4574248573107448,
+           0.5238863885519196,
+           0.5842529240326052,
+           0.6375761771354361,
+           0.6831033740064433,
+           0.7203022920477598,
+           0.7488804441933087,
+           0.7687978579897974,
+           0.7802730626051714,
+           0.7837820713671253,
+           0.7800503278985957,
+           0.7700377658121044,
+           0.7549173106546575,
+           0.7360473238362475,
+           0.7149386472901482,
+           0.693217050558885,
+           0.672582005228435,
+           0.6547628119849401,
+           0.6414731804499484,
+           0.6343654094015837,
+           0.6349853337319138,
+           0.6447291939623011,
+           0.6648035445059431,
+           0.6961892490245868,
+           0.7396105167748662,
+           0.7955098150462856,
+           0.8640293525365961,
+           0.9449996702112623,
+           1.0379357037285564,
+           1.1420404991184077,
+           1.2562165755755377,
+           1.3790847406049047,
+           1.5090099780094766,
+           1.6441338529207037,
+           1.7824127146253121,
+           1.9216608314142785,
+           2.059597465737647,
+           2.1938967957576017,
+           2.322239513537128,
+           2.442364882523431,
+           2.5521220189307163,
+           2.6495191736177626,
+           2.73276983287432,
+           2.800334527224941,
+           2.850957335265351,
+           2.883696192329542,
+           2.8979462584954385,
+           2.893455763580537,
+           2.8703339244071615,
+           2.829050717420441,
+           2.770428483157504,
+           2.6956255333885255,
+           2.606112122247798,
+           2.503639324705085,
+           2.390201534857748,
+           2.267993448630133,
+           2.139362526841162,
+           2.0067580420436446,
+           1.8726778934342694,
+           1.7396144265162055,
+           1.6100005167995612,
+           1.4861571691103703,
+           1.370243846250618,
+           1.2642126737512414,
+           1.1697675729421166,
+           1.088329254855143,
+           1.0210068655217723,
+           0.9685769125094088,
+           0.9314699270036583,
+           0.909765129685623,
+           0.9031931766284885,
+           0.9111468681391636,
+           0.9326995136171353,
+           0.9666304637209252,
+           1.0114571518441147,
+           1.0654728342152602,
+           1.1267890855413765,
+           1.1933819981996678,
+           1.2631409501497615,
+           1.3339187519445632,
+           1.4035819577231112,
+           1.470060129409654,
+           1.5313928773189027,
+           1.585773563045824,
+           1.6315886402608253,
+           1.6674517235332453,
+           1.6922316116562774,
+           1.7050736466989285,
+           1.7054139592714943,
+           1.6929863300156822,
+           1.667821582629416,
+           1.6302396101867394,
+           1.5808343194744434,
+           1.5204519529955975,
+           1.4501634108526442,
+           1.3712313409033123,
+           1.2850728917826546,
+           1.19321912651126,
+           1.0972721719528535,
+           0.9988612294781403,
+           0.8995985936595228,
+           0.8010368182053138,
+           0.7046281319134698,
+           0.6116871431755468,
+           0.5233577811796569,
+           0.4405853077870044,
+           0.3640940990241797,
+           0.29437174269643424,
+           0.2316598326719083,
+           0.17595166513456734,
+           0.12699686200516558,
+           0.08431276635276155,
+           0.04720227853557337,
+           0.014777634478890685,
+           -0.014010526844028695,
+           -0.04033959710724413,
+           -0.06547784095103099,
+           -0.09074464809713967,
+           -0.11746926443816241,
+           -0.14694911183410306,
+           -0.18040881841713605,
+           -0.21896106446584787,
+           -0.26357030376864726,
+           -0.31502034797394757,
+           -0.37388670353178144,
+           -0.4405144299200155,
+           -0.5150021469526296,
+           -0.5971926616279635,
+           -0.6866705151494389,
+           -0.7827665727171753,
+           -0.8845695969350553,
+           -0.9909445647930486,
+           -1.1005573127429813,
+           -1.2119049288317398,
+           -1.323351159392842,
+           -1.4331659642831833,
+           -1.5395682425005657,
+           -1.640770662115495,
+           -1.7350254670811978,
+           -1.820670100273527,
+           -1.8961714779809538,
+           -1.9601677762124101,
+           -2.011506643085451,
+           -2.049278832947396,
+           -2.0728463648283415,
+           -2.0818644377459177,
+           -2.0762964851180743,
+           -2.056421916432453,
+           -2.022836272299119,
+           -1.9764437046981105,
+           -1.918441883043449,
+           -1.850299613952307,
+           -1.7737276436906717,
+           -1.6906432826670692,
+           -1.6031296468200134,
+           -1.5133904474096767,
+           -1.4237013751528684,
+           -1.3363592139484302,
+           -1.2536298813578912,
+           -1.1776966259343986,
+           -1.1106096145446391,
+           -1.0542381158513687,
+           -1.0102264297039514,
+           -0.9799546276336835,
+           -0.9645050589747709,
+           -0.9646354429818382,
+           -0.9807592129218174,
+           -1.012933607214472,
+           -1.0608558194237405,
+           -1.1238673277115474,
+           -1.2009663299053468,
+           -1.2908280173332303,
+           -1.391832233746552,
+           -1.502097889532348,
+           -1.61952334030901,
+           -1.7418317968255368,
+           -1.8666207133120765,
+           -1.9914140069735058,
+           -2.1137158944767838,
+           -2.231065093677009,
+           -2.3410881313627896,
+           -2.4415505206456984,
+           -2.530404624196793,
+           -2.6058331005436006,
+           -2.666286938085407,
+           -2.7105172127207644,
+           -2.7375998567840596,
+           -2.7469528956335005,
+           -2.7383457895873904,
+           -2.7119007085282867,
+           -2.6680857597482395,
+           -2.6077003817719957,
+           -2.531853303281727,
+           -2.44193364233823,
+           -2.339575882572242,
+           -2.226619605993296,
+           -2.1050649830826473,
+           -1.977025116997639,
+           -1.8446764077307758,
+           -1.7102081423248112,
+           -1.575772527843971,
+           -1.4434363645726638,
+           -1.315135508425161,
+           -1.1926331950925109,
+           -1.0774831960036944,
+           -0.9709986503534416,
+           -0.8742272714374346,
+           -0.7879334630187005,
+           -0.7125877065082765,
+           -0.6483633967598614,
+           -0.5951411178225624,
+           -0.5525201647137945,
+           -0.5198369377726847,
+           -0.49618966688515476,
+           -0.480468768022615,
+           -0.4713919979262441,
+           -0.4675434577541233,
+           -0.46741540589915953,
+           -0.469451776176751,
+           -0.4720922616983094,
+           -0.47381581780946785,
+           -0.4731824595738784,
+           -0.46887227979107077,
+           -0.4597206911057975,
+           -0.444748998375872,
+           -0.4231895324701817,
+           -0.39450472086445754,
+           -0.35839963010780657,
+           -0.3148276863815353,
+           -0.26398945861363166,
+           -0.20632456942398011,
+           -0.14249697797282937,
+           -0.07337405103873076,
+           -6.998045711564284e-16
+          ],
+          [
+           0,
+           0.07694863959823885,
+           0.15504493489543733,
+           0.2329024695827375,
+           0.30912675673013795,
+           0.38235683666904685,
+           0.4513060932010428,
+           0.5148011881722188,
+           0.571818061591761,
+           0.6215140187109751,
+           0.6632550249562847,
+           0.6966374518312243,
+           0.721503658797632,
+           0.7379509541464669,
+           0.7463336479961369,
+           0.747258088523378,
+           0.7415707538485068,
+           0.7303396520828177,
+           0.7148294563449131,
+           0.6964709656470504,
+           0.6768256322734156,
+           0.6575460278044556,
+           0.6403332299192114,
+           0.6268921976993368,
+           0.6188862621379267,
+           0.6178918893591063,
+           0.6253548758180217,
+           0.6425491073373022,
+           0.6705389578357942,
+           0.710146320324192,
+           0.7619231541694718,
+           0.826130301390294,
+           0.9027231740339897,
+           0.9913447481897516,
+           1.0913261220006667,
+           1.201694709537917,
+           1.3211899541739864,
+           1.4482862587964076,
+           1.581222650460394,
+           1.7180385283564952,
+           1.8566146904741254,
+           1.994718699911394,
+           2.130053539791149,
+           2.260308419019807,
+           2.3832105318784444,
+           2.4965765442004937,
+           2.5983625784898923,
+           2.6867114998571493,
+           2.7599963634507096,
+           2.816858970768078,
+           2.8562425947872505,
+           2.8774180695675127,
+           2.8800025955601494,
+           2.8639707835819146,
+           2.8296576440746573,
+           2.7777534194426496,
+           2.7092903512755377,
+           2.625621666406207,
+           2.528393251337758,
+           2.419508659078373,
+           2.30108825159181,
+           2.1754234210229457,
+           2.0449269501795238,
+           1.912080664583785,
+           1.7793815925150842,
+           1.6492878842896879,
+           1.5241657467264755,
+           1.4062386232243345,
+           1.2975397947657161,
+           1.1998694938221888,
+           1.1147575136233496,
+           1.0434321622508977,
+           0.9867962577994468,
+           0.9454106911608796,
+           0.9194859009962041,
+           0.9088814156112006,
+           0.9131134233903299,
+           0.9313701418809195,
+           0.9625345702268293,
+           1.0052140349395662,
+           1.0577757792078315,
+           1.1183877049528843,
+           1.185063258037285,
+           1.2557093532772414,
+           1.3281761694209693,
+           1.400307606588627,
+           1.4699911906617418,
+           1.5352062308670724,
+           1.5940690876926085,
+           1.6448744869548557,
+           1.6861319202765719,
+           1.7165962997700217,
+           1.735292182124704,
+           1.7415310408580305,
+           1.734921241098288,
+           1.7153705545379119,
+           1.6830812385481149,
+           1.6385378882435777,
+           1.5824884489378641,
+           1.5159189445093113,
+           1.4400226305492112,
+           1.356164416010945,
+           1.2658415101118337,
+           1.1706413397011772,
+           1.0721978440599023,
+           0.9721472876727394,
+           0.8720847361531552,
+           0.7735223161700985,
+           0.6778503276151282,
+           0.5863021967564662,
+           0.49992415482270713,
+           0.4195504000316367,
+           0.34578435576842603,
+           0.27898647713162367,
+           0.21926888649027426,
+           0.16649694039043345,
+           0.12029764963827218,
+           0.0800746962444913,
+           0.045029619652437375,
+           0.014188584624803626,
+           -0.013566001619128092,
+           -0.039459881278746445,
+           -0.0647883088649791,
+           -0.0908754261177,
+           -0.11903274221277818,
+           -0.15051783670881774,
+           -0.18649439817306873,
+           -0.22799467832064935,
+           -0.2758853806224347,
+           -0.3308379152062189,
+           -0.39330384067702634,
+           -0.4634961810073589,
+           -0.5413771552267916,
+           -0.6266526930577213,
+           -0.7187739350457816,
+           -0.8169457355221945,
+           -0.9201420054605157,
+           -1.0271275545345102,
+           -1.13648592194844,
+           -1.2466525282024603,
+           -1.3559523388786812,
+           -1.4626411103897867,
+           -1.5649491895299807,
+           -1.6611267661449376,
+           -1.7494894331943054,
+           -1.8284628921346575,
+           -1.896625654404696,
+           -1.9527486316208835,
+           -1.995830576939956,
+           -2.0251284362618858,
+           -2.04018178821912,
+           -2.040830693306331,
+           -2.027226431597525,
+           -1.9998347813742772,
+           -1.959431673398312,
+           -1.9070912430053446,
+           -1.8441664900412704,
+           -1.7722629402525794,
+           -1.6932058765209486,
+           -1.6090018699465667,
+           -1.5217954852011992,
+           -1.4338221581727728,
+           -1.3473583435972067,
+           -1.264670103594246,
+           -1.1879613529142197,
+           -1.119322992078495,
+           -1.0606841450005138,
+           -1.0137666733869208,
+           -0.9800440672502284,
+           -0.9607057109353361,
+           -0.9566273995560887,
+           -0.9683488346474333,
+           -0.9960586636901146,
+           -1.03958744993284,
+           -1.098408770946339,
+           -1.1716484511638907,
+           -1.2581017399943333,
+           -1.3562580576533703,
+           -1.4643327502638388,
+           -1.5803051284288423,
+           -1.7019619134642239,
+           -1.8269450864471488,
+           -1.9528030303415829,
+           -2.0770437772539525,
+           -2.1971891232566545,
+           -2.3108283533947502,
+           -2.415670329935917,
+           -2.5095927373672233,
+           -2.5906873470823424,
+           -2.6573002614282433,
+           -2.7080662184119517,
+           -2.741936181919801,
+           -2.7581976042517216,
+           -2.7564869241533514,
+           -2.736794050021002,
+           -2.6994587699973573,
+           -2.645159223578044,
+           -2.5748927584042165,
+           -2.489949676518863,
+           -2.3918805421237703,
+           -2.2824578737217154,
+           -2.1636331738182566,
+           -2.0374903559555735,
+           -1.9061967092114616,
+           -1.7719525925246598,
+           -1.6369410741048773,
+           -1.5032787242791636,
+           -1.3729687336779448,
+           -1.2478574636655018,
+           -1.1295954440651,
+           -1.0196037168716845,
+           -0.9190462867400809,
+           -0.8288092830646683,
+           -0.7494872683484801,
+           -0.6813769475573367,
+           -0.624478347765847,
+           -0.5785033512478844,
+           -0.5428912828735724,
+           -0.5168310787710054,
+           -0.4992894019978877,
+           -0.4890439264242423,
+           -0.48472088570700617,
+           -0.48483588318300047,
+           -0.48783688317398755,
+           -0.49214825639444604,
+           -0.496214732995936,
+           -0.49854412666941184,
+           -0.49774773182931265,
+           -0.49257736217256987,
+           -0.481958091102741,
+           -0.46501587024757407,
+           -0.44109933860414463,
+           -0.4097952882340048,
+           -0.37093741899173466,
+           -0.3246081902684114,
+           -0.27113375771111436,
+           -0.2110721627771056,
+           -0.14519511823931527,
+           -0.07446389894137108,
+           -7.073463703085915e-16
+          ],
+          [
+           0,
+           0.07723310207425255,
+           0.1549919800779892,
+           0.23188615680000726,
+           0.3065394950701595,
+           0.377631371130817,
+           0.4439364442635914,
+           0.5043619492155513,
+           0.5579815007317028,
+           0.6040644883003157,
+           0.6421002518256214,
+           0.6718163625280607,
+           0.6931904845745488,
+           0.7064554579523971,
+           0.7120974177613055,
+           0.7108469450012771,
+           0.7036634245361567,
+           0.6917129626447194,
+           0.6763403849564816,
+           0.6590359913330903,
+           0.6413978834336512,
+           0.6250907997385519,
+           0.6118024886449055,
+           0.6031987204072438,
+           0.6008780813376217,
+           0.6063277076433126,
+           0.6208811011264418,
+           0.6456791249840628,
+           0.6816352061362274,
+           0.7294056725774999,
+           0.789366032553634,
+           0.8615938598671289,
+           0.9458587897954838,
+           1.0416199568858884,
+           1.148031023533764,
+           1.263952761261037,
+           1.3879729596095478,
+           1.5184332551928492,
+           1.653462300238551,
+           1.7910145302193148,
+           1.9289136479053062,
+           2.064899819942325,
+           2.1966794849235582,
+           2.321976601345263,
+           2.4385841216333484,
+           2.54441446571788,
+           2.6375477848097035,
+           2.716276852755825,
+           2.7791474975474824,
+           2.8249935874543026,
+           2.8529657124266805,
+           2.862552848813717,
+           2.8535964605264432,
+           2.8262966685375495,
+           2.7812103087106235,
+           2.7192408908209207,
+           2.6416206645713816,
+           2.549885186721162,
+           2.4458409625381434,
+           2.3315269002932757,
+           2.2091704653948043,
+           2.0811395474060297,
+           1.9498911555111569,
+           1.8179181334950845,
+           1.687695132145524,
+           1.5616250940322585,
+           1.441987492460589,
+           1.3308895233653872,
+           1.2302213770712027,
+           1.141616617959768,
+           1.0664185765874739,
+           1.0056535137112363,
+           0.960011152567712,
+           0.9298329986020277,
+           0.915108678992531,
+           0.9154803423347602,
+           0.930254966418649,
+           0.9584242338505906,
+           0.9986914559184312,
+           1.0495048589313498,
+           1.1090963983158968,
+           1.1755251376127849,
+           1.2467241252769328,
+           1.320549624323457,
+           1.3948315002184664,
+           1.4674235521212111,
+           1.5362525820535267,
+           1.5993650354792324,
+           1.6549701140705295,
+           1.7014783553719788,
+           1.7375347922430802,
+           1.7620459443714225,
+           1.7742000512848344,
+           1.7734801272072624,
+           1.7596695985208557,
+           1.7328504700121934,
+           1.6933941518759668,
+           1.641945261008333,
+           1.579398882943802,
+           1.5068719406007882,
+           1.425669458861894,
+           1.3372466364166122,
+           1.2431677352451638,
+           1.1450628712224302,
+           1.0445838348206689,
+           0.9433600877322788,
+           0.8429560690809156,
+           0.7448309041283895,
+           0.6503015401193317,
+           0.5605102399253459,
+           0.47639724688712765,
+           0.3986792967183368,
+           0.327834498044626,
+           0.2640939360368139,
+           0.20744017790723346,
+           0.15761267923175407,
+           0.11411991069471532,
+           0.07625785047189734,
+           0.04313432248073766,
+           0.013698509310208863,
+           -0.013225165376072346,
+           -0.038899703402029376,
+           -0.0646357556267293,
+           -0.09175047416125934,
+           -0.12152610107072365,
+           -0.1551694090573047,
+           -0.1937730886452449,
+           -0.23828012727716966,
+           -0.28945214971142147,
+           -0.34784258808858015,
+           -0.4137754265499493,
+           -0.4873301224468052,
+           -0.5683331475723875,
+           -0.6563564224749758,
+           -0.7507227390664067,
+           -0.8505180859158412,
+           -0.9546106113838283,
+           -1.0616757866436766,
+           -1.1702271680456906,
+           -1.278652010337344,
+           -1.3852508527307719,
+           -1.488280092024403,
+           -1.585996473714863,
+           -1.6767023754470027,
+           -1.7587907287476765,
+           -1.8307884255744833,
+           -1.8913970858622462,
+           -1.9395301203190203,
+           -1.9743451078507164,
+           -1.9952706171406775,
+           -2.002026734411373,
+           -1.9946387110198154,
+           -1.9734433115728969,
+           -1.9390876215880226,
+           -1.8925202589721344,
+           -1.8349751211705645,
+           -1.7679479850999011,
+           -1.6931664553270813,
+           -1.612553922951811,
+           -1.5281883491245605,
+           -1.4422568192958838,
+           -1.3570069238228533,
+           -1.2746961046849798,
+           -1.1975401646374484,
+           -1.12766216268208,
+           -1.0670429175068343,
+           -1.0174743085069364,
+           -0.9805165028633174,
+           -0.9574601483422762,
+           -0.9492944571039652,
+           -0.9566819686071816,
+           -0.9799406229805228,
+           -1.0190336037853904,
+           -1.0735672251060093,
+           -1.1427969468351473,
+           -1.2256414085298402,
+           -1.3207041810012248,
+           -1.4263027505370114,
+           -1.5405040778278585,
+           -1.6611659164963664,
+           -1.7859829384448274,
+           -1.9125365984047398,
+           -2.0383475808889395,
+           -2.160929611389016,
+           -2.277843381620346,
+           -2.386749336668615,
+           -2.4854581000744327,
+           -2.57197737050697,
+           -2.6445542093043928,
+           -2.7017117496940433,
+           -2.742279493210924,
+           -2.765416513407012,
+           -2.7706270575987824,
+           -2.757768219959338,
+           -2.7270495492600775,
+           -2.679024647362885,
+           -2.6145750054528105,
+           -2.5348865093314683,
+           -2.4414192183785572,
+           -2.33587118082701,
+           -2.2201371869612174,
+           -2.0962634783874825,
+           -1.9663995228489473,
+           -1.8327480279963335,
+           -1.6975144025916307,
+           -1.5628568790394122,
+           -1.4308384868669675,
+           -1.3033820134988143,
+           -1.1822290077971815,
+           -1.068903775449917,
+           -0.964683186088247,
+           -0.8705729632753586,
+           -0.7872909639645671,
+           -0.7152577778080866,
+           -0.6545947932085865,
+           -0.6051296908210434,
+           -0.5664091409634582,
+           -0.5377183036542733,
+           -0.5181065631627084,
+           -0.5064187771550037,
+           -0.5013311874805554,
+           -0.5013910286275888,
+           -0.5050587835923169,
+           -0.5107519774297491,
+           -0.5168893674960078,
+           -0.5219343870508026,
+           -0.5244367254395571,
+           -0.5230709827699797,
+           -0.5166714183861294,
+           -0.5042619184069603,
+           -0.48508043540548124,
+           -0.4585972996851255,
+           -0.4245269628263032,
+           -0.38283290612528326,
+           -0.3337256248622271,
+           -0.2776537794926996,
+           -0.2152887822931825,
+           -0.14750325821435342,
+           -0.07534397739993894,
+           -7.128288962184834e-16
+          ],
+          [
+           0,
+           0.0772863422711282,
+           0.15447478113189028,
+           0.23018248760138485,
+           0.3030631507584379,
+           0.3718473738307926,
+           0.4353810596098612,
+           0.4926607473673676,
+           0.5428649412185005,
+           0.5853805724014352,
+           0.6198238626464956,
+           0.6460549995506145,
+           0.6641861940328354,
+           0.674582860511571,
+           0.6778578381101144,
+           0.6748587514758252,
+           0.6666487881314097,
+           0.6544813411475954,
+           0.6397691269747738,
+           0.6240485344017558,
+           0.6089400880952394,
+           0.5961060157482885,
+           0.5872059888080243,
+           0.5838521609523055,
+           0.5875646544988651,
+           0.599728642017365,
+           0.6215541385567385,
+           0.6540395598022855,
+           0.697940014551776,
+           0.7537411882328241,
+           0.8216395404824975,
+           0.9015293873376453,
+           0.992997271078815,
+           1.095323842353032,
+           1.207493294272897,
+           1.3282102013254735,
+           1.455923431756569,
+           1.5888566252004992,
+           1.7250445621082193,
+           1.8623746021143475,
+           1.9986322386202915,
+           2.1315497098249105,
+           2.2588565249171735,
+           2.378330710243234,
+           2.4878495553813917,
+           2.585438643897794,
+           2.669317988076594,
+           2.737944150352686,
+           2.790047325041375,
+           2.824662470098224,
+           2.8411537172693544,
+           2.839231446766091,
+           2.8189615857012726,
+           2.780766873759328,
+           2.7254200304614686,
+           2.6540289512858837,
+           2.5680142501111574,
+           2.4690796483317747,
+           2.359175882085284,
+           2.2404589541556583,
+           2.11524369248869,
+           1.9859536895676309,
+           1.8550687834082618,
+           1.7250712995312767,
+           1.5983923025278957,
+           1.4773591050421382,
+           1.3641452511758112,
+           1.2607241312404625,
+           1.1688272969111277,
+           1.0899084323357109,
+           1.025113800404011,
+           0.9752598275217809,
+           0.9408183186833615,
+           0.9219096115876985,
+           0.918303788471036,
+           0.9294298718766113,
+           0.9543927404414153,
+           0.9919973175840141,
+           1.0407794141802946,
+           1.0990424500841742,
+           1.1648991424675068,
+           1.2363171347158526,
+           1.31116745076025,
+           1.387274598356721,
+           1.4624671123711634,
+           1.5346273262997658,
+           1.6017391870344981,
+           1.6619329835204508,
+           1.713525942987392,
+           1.7550577567391163,
+           1.7853202282989626,
+           1.8033803867356848,
+           1.808596573460415,
+           1.8006271875486635,
+           1.77943195828678,
+           1.7452657995950653,
+           1.6986654846180593,
+           1.6404295555428117,
+           1.5715920492354938,
+           1.4933907694923552,
+           1.4072309678901647,
+           1.3146454041829025,
+           1.2172518412758626,
+           1.1167090869917708,
+           1.0146727237779674,
+           0.9127516675498443,
+           0.8124666681072354,
+           0.7152118068016101,
+           0.6222199638766126,
+           0.534533120317105,
+           0.4529782298937187,
+           0.3781492496880005,
+           0.31039575548800175,
+           0.2498183961746235,
+           0.19627126294931693,
+           0.14937106950360252,
+           0.1085128625525531,
+           0.07289181301803362,
+           0.041530480830077605,
+           0.013310804792280796,
+           -0.012990053194526134,
+           -0.03866097995043718,
+           -0.0650163439943482,
+           -0.09335468265095227,
+           -0.12491775602921228,
+           -0.16085107180426078,
+           -0.20216694755631837,
+           -0.24971111280433364,
+           -0.3041337624407847,
+           -0.3658658593007959,
+           -0.43510134895149694,
+           -0.5117857978570808,
+           -0.5956118006904385,
+           -0.6860213278950397,
+           -0.7822150050604949,
+           -0.8831681357996944,
+           -0.9876531041563406,
+           -1.0942676255814328,
+           -1.2014681614369933,
+           -1.3076076747385266,
+           -1.4109767879419093,
+           -1.509847310019248,
+           -1.6025170322746274,
+           -1.6873546521074085,
+           -1.7628436723330951,
+           -1.8276241411009235,
+           -1.8805311435588459,
+           -1.9206290301481863,
+           -1.9472404660079314,
+           -1.9599695090281466,
+           -1.958718067619094,
+           -1.9436952497457896,
+           -1.9154192882750547,
+           -1.8747119099191243,
+           -1.8226852015344421,
+           -1.7607212136291657,
+           -1.690444722029159,
+           -1.6136897402452248,
+           -1.5324605328939518,
+           -1.4488880206035024,
+           -1.3651825856663993,
+           -1.2835843822847963,
+           -1.2063123231834336,
+           -1.1355129538887239,
+           -1.0732104360344734,
+           -1.0212588413248733,
+           -0.9812979086672274,
+           -0.9547133396089562,
+           -0.9426026034011069,
+           -0.9457470952439463,
+           -0.9645913426212096,
+           -0.9992297886886589,
+           -1.0494015024696075,
+           -1.1144929774761945,
+           -1.193548987895344,
+           -1.2852912793395856,
+           -1.3881446840478857,
+           -1.5002700728944725,
+           -1.619603392956643,
+           -1.74389989369991,
+           -1.8707825206181898,
+           -1.9977933554511194,
+           -2.1224469093246032,
+           -2.2422840310986856,
+           -2.354925178932299,
+           -2.4581218189293943,
+           -2.549804760322053,
+           -2.6281283108507534,
+           -2.6915092369981175,
+           -2.738659639043366,
+           -2.7686129974588978,
+           -2.7807428113798003,
+           -2.7747734277225584,
+           -2.7507828466626103,
+           -2.7091974810297015,
+           -2.6507790390629684,
+           -2.576603887207261,
+           -2.4880354276710603,
+           -2.386690189979738,
+           -2.2743984827593775,
+           -2.153160577926392,
+           -2.0250995013099122,
+           -1.892411579069098,
+           -1.75731593631386,
+           -1.622004162022394,
+           -1.488591342325455,
+           -1.3590696228811152,
+           -1.2352653915024117,
+           -1.118801076225788,
+           -1.0110624340708971,
+           -0.9131720648784329,
+           -0.8259697263702451,
+           -0.7499998549242729,
+           -0.6855065157887705,
+           -0.6324358210842193,
+           -0.5904456685702153,
+           -0.5589224733904806,
+           -0.5370043933287673,
+           -0.5236103897531219,
+           -0.5174743252956738,
+           -0.5171831788722107,
+           -0.5212183618298241,
+           -0.5279990481658156,
+           -0.5359263885777329,
+           -0.5434274635796649,
+           -0.5489978453323672,
+           -0.5512416807386935,
+           -0.5489082785937228,
+           -0.5409242793105259,
+           -0.5264206044923626,
+           -0.5047535223412329,
+           -0.4755193200363241,
+           -0.43856224183191767,
+           -0.3939755274526463,
+           -0.34209556494379045,
+           -0.2834893509153018,
+           -0.2189356245750225,
+           -0.1494002056917689,
+           -0.07600621652334939,
+           -7.162018293862328e-16
+          ],
+          [
+           0,
+           0.0771078074293601,
+           0.1534978427901408,
+           0.227806509805988,
+           0.29872847760231425,
+           0.36505595543287145,
+           0.42571537032027634,
+           0.47980045418187556,
+           0.5266008390371497,
+           0.5656253741874822,
+           0.5966195149192494,
+           0.6195762848875339,
+           0.634740480041429,
+           0.6426059565706921,
+           0.6439060244764526,
+           0.6395971474664468,
+           0.6308363244134525,
+           0.618952693168413,
+           0.6054140498807022,
+           0.591789112265696,
+           0.5797064700151122,
+           0.5708112568188635,
+           0.5667206438924128,
+           0.5689792927585074,
+           0.579015914281761,
+           0.5981020612780722,
+           0.6273142338207346,
+           0.6675003007578016,
+           0.7192511397445831,
+           0.7828782737281753,
+           0.858398137327974,
+           0.9455234454762308,
+           1.0436619629762012,
+           1.1519227915860903,
+           1.2691301053459583,
+           1.393844079739044,
+           1.5243885805170858,
+           1.6588850080971187,
+           1.7952915375968082,
+           1.9314468567191188,
+           2.0651173872907256,
+           2.194046884244392,
+           2.3160072405591046,
+           2.428849289822678,
+           2.5305523906508984,
+           2.6192715994522384,
+           2.6933812895032303,
+           2.751514153811386,
+           2.792594634912009,
+           2.815865954047519,
+           2.8209100620024254,
+           2.807660000594293,
+           2.7764043434107006,
+           2.7277835724728234,
+           2.6627784395222736,
+           2.5826905518921857,
+           2.48911560877265,
+           2.383909889579597,
+           2.269150757790082,
+           2.1470920870670027,
+           2.020115638256917,
+           1.890679512930264,
+           1.7612648791711585,
+           1.634322206603216,
+           1.5122182591512243,
+           1.397185075507355,
+           1.2912721191518741,
+           1.1963027032528184,
+           1.1138356927128872,
+           1.0451333585693334,
+           0.9911361119948828,
+           0.9524446799150946,
+           0.9293101057909934,
+           0.9216317717765292,
+           0.9289634468230663,
+           0.9505271740425462,
+           0.9852346244173504,
+           1.0317153672888366,
+           1.088351345257722,
+           1.1533166961311971,
+           1.224621940853902,
+           1.300161456933804,
+           1.3777630840887272,
+           1.455238664405055,
+           1.5304343042257198,
+           1.6012791595547005,
+           1.6658315905331185,
+           1.7223216023422814,
+           1.7691885878673737,
+           1.8051135091150945,
+           1.8290447966434122,
+           1.8402174055529408,
+           1.8381646389154633,
+           1.8227225305703898,
+           1.7940267644924506,
+           1.7525022928176766,
+           1.698845994523672,
+           1.634002887242543,
+           1.5591365615330102,
+           1.4755946462933203,
+           1.3848702324436875,
+           1.2885602766593933,
+           1.1883220755062311,
+           1.0858289411868485,
+           0.9827262223129678,
+           0.8805887964557692,
+           0.780881116197675,
+           0.6849208182252255,
+           0.5938468075540342,
+           0.5085926087814144,
+           0.4298656364051287,
+           0.35813288030043194,
+           0.2936133343834282,
+           0.23627732057668885,
+           0.1858526808944561,
+           0.14183763232080937,
+           0.10351990667232334,
+           0.07000163517724242,
+           0.04022928917075168,
+           0.013027857846329321,
+           -0.012861665290009105,
+           -0.038742500983606244,
+           -0.06592108082170145,
+           -0.09566592656859593,
+           -0.12916752029253167,
+           -0.16750024819281523,
+           -0.21158744805957813,
+           -0.2621705108166617,
+           -0.3197828826106748,
+           -0.38472968803489715,
+           -0.4570735504872598,
+           -0.5366270260024563,
+           -0.6229518961976139,
+           -0.7153653885389247,
+           -0.8129532124573208,
+           -0.9145891224609499,
+           -1.0189605488048978,
+           -1.1245996768141202,
+           -1.2299192116706326,
+           -1.333251940052388,
+           -1.4328930966634863,
+           -1.5271444650898862,
+           -1.6143590906018281,
+           -1.6929854588873408,
+           -1.7616099999201469,
+           -1.8189968101994216,
+           -1.8641235486864758,
+           -1.896212550439756,
+           -1.9147563150829379,
+           -1.9195366620838283,
+           -1.9106369980797109,
+           -1.8884473093962186,
+           -1.8536616713369602,
+           -1.8072682503638744,
+           -1.7505319613753312,
+           -1.684970125303289,
+           -1.6123216476408193,
+           -1.534510401904773,
+           -1.4536036493500144,
+           -1.3717664537861167,
+           -1.2912131548904269,
+           -1.2141570423109345,
+           -1.142759424084222,
+           -1.0790793051133334,
+           -1.0250248840267946,
+           -0.9823080397716454,
+           -0.9524029136078515,
+           -0.9365095993053149,
+           -0.935523836505679,
+           -0.9500134622261128,
+           -0.9802022167261913,
+           -1.0259613262739242,
+           -1.086809100946491,
+           -1.1619185949678792,
+           -1.2501331848597164,
+           -1.3499897315482539,
+           -1.4597488111427714,
+           -1.5774313298075504,
+           -1.7008606851253898,
+           -1.8277095033342412,
+           -1.9555498720604703,
+           -2.0819059043548966,
+           -2.204307414009604,
+           -2.320343455657057,
+           -2.427714486674307,
+           -2.5242819413435513,
+           -2.608114070235315,
+           -2.677526987848586,
+           -2.7311199869562595,
+           -2.767804316038046,
+           -2.7868247732598976,
+           -2.7877736428372843,
+           -2.770596683084382,
+           -2.7355910655212576,
+           -2.6833953564470856,
+           -2.6149718217074294,
+           -2.5315815173781666,
+           -2.434752799333808,
+           -2.3262440390347123,
+           -2.2080014676227755,
+           -2.0821131823133627,
+           -1.9507604354337,
+           -1.8161673852392504,
+           -1.6805505174759885,
+           -1.5460689468990627,
+           -1.4147767786888599,
+           -1.2885786517326518,
+           -1.169189500578086,
+           -1.0580994626965103,
+           -0.9565447253148768,
+           -0.8654849548220036,
+           -0.7855877854260347,
+           -0.7172206664961911,
+           -0.6604501842862254,
+           -0.6150487880821915,
+           -0.5805086678538807,
+           -0.5560623547505326,
+           -0.5407094516101648,
+           -0.5332487520940609,
+           -0.5323148777617333,
+           -0.5364184555275378,
+           -0.5439887760830386,
+           -0.55341781899478,
+           -0.5631045035833254,
+           -0.5714980269358427,
+           -0.5771391813585675,
+           -0.578698602376794,
+           -0.5750109834834467,
+           -0.5651044030114674,
+           -0.548224038949975,
+           -0.5238496958998687,
+           -0.49170673088752276,
+           -0.45177013729192167,
+           -0.40426172431145335,
+           -0.3496405086862789,
+           -0.2885866112621415,
+           -0.22197911898388412,
+           -0.15086852879596166,
+           -0.07644452976551316,
+           -7.174339672743204e-16
+          ],
+          [
+           0,
+           0.07669902671666083,
+           0.15206977223130247,
+           0.22477922542186696,
+           0.29357376413097264,
+           0.3573169763079085,
+           0.41502432333174183,
+           0.4658937048006904,
+           0.5093310894808322,
+           0.5449705041054743,
+           0.572687817102102,
+           0.5926079144284467,
+           0.6051050354808171,
+           0.6107962141818376,
+           0.6105279493819572,
+           0.6053564050877688,
+           0.5965216102896085,
+           0.5854162860032888,
+           0.5735500695491458,
+           0.5625100294303889,
+           0.553918465279494,
+           0.5493890636061349,
+           0.5504825295113709,
+           0.5586628358080067,
+           0.5752552234866068,
+           0.6014070512901967,
+           0.6380525281256468,
+           0.685882271661903,
+           0.74531852192185,
+           0.8164967027512654,
+           0.8992538700701974,
+           0.9931244175621738,
+           1.097343232081927,
+           1.2108563069716127,
+           1.3323386362296883,
+           1.4602190306760374,
+           1.5927113234266157,
+           1.727851270468587,
+           1.8635383069547966,
+           1.9975811946604292,
+           2.1277464940238446,
+           2.251808717920383,
+           2.3676009757540424,
+           2.4730648968782876,
+           2.566298632341182,
+           2.645601773331331,
+           2.7095160925934687,
+           2.7568611098960347,
+           2.786763602111689,
+           2.7986803197485326,
+           2.7924133314370976,
+           2.768117592071001,
+           2.7263005147899566,
+           2.6678135172966613,
+           2.593835704479564,
+           2.505850037303433,
+           2.405612517841104,
+           2.295115087759345,
+           2.1765430884474335,
+           2.0522282616003467,
+           1.9245983762445544,
+           1.7961246493012673,
+           1.6692681798349156,
+           1.5464266408355039,
+           1.4298824661521419,
+           1.3217537341844225,
+           1.2239488850300353,
+           1.1381263155697665,
+           1.0656597797018605,
+           1.0076103814853707,
+           0.9647057907274702,
+           0.9373271374204909,
+           0.9255038576309288,
+           0.9289165734524781,
+           0.9469078980934007,
+           0.9785008687431564,
+           1.0224245291403091,
+           1.0771460151345704,
+           1.1409083440889929,
+           1.2117729763891716,
+           1.287666107806603,
+           1.366427567623272,
+           1.4458611412482614,
+           1.5237851088455465,
+           1.5980817938301368,
+           1.6667449468344446,
+           1.7279238510305452,
+           1.7799631219476413,
+           1.821437286916538,
+           1.8511793631670088,
+           1.8683028060278746,
+           1.8722163658109048,
+           1.8626315696206408,
+           1.8395627280940663,
+           1.8033195523667704,
+           1.7544926487884922,
+           1.6939323335598648,
+           1.6227213722215654,
+           1.5421423957898035,
+           1.453640872695513,
+           1.3587846204395655,
+           1.259220920483282,
+           1.1566323524457318,
+           1.0526924879485955,
+           0.9490225799161855,
+           0.847150350003837,
+           0.7484719160077311,
+           0.6542178142097643,
+           0.5654239608888406,
+           0.4829082655336592,
+           0.4072534589920271,
+           0.33879653669377113,
+           0.2776250443351691,
+           0.22358025539566626,
+           0.1762671110821327,
+           0.13507061828548472,
+           0.09917823431310868,
+           0.06760761274154914,
+           0.039238946615380764,
+           0.012851026884655163,
+           -0.012839961590836037,
+           -0.039139954527522364,
+           -0.06733592468351421,
+           -0.09865530717716087,
+           -0.134227027480876,
+           -0.17504518475387645,
+           -0.22193637494883928,
+           -0.27553154454821627,
+           -0.3362431492149838,
+           -0.40424825501928946,
+           -0.4794780666733768,
+           -0.5616142012394484,
+           -0.6500918512603188,
+           -0.7441098026115103,
+           -0.8426470941053832,
+           -0.9444859325085236,
+           -1.0482403125608428,
+           -1.152389640979229,
+           -1.2553165301285178,
+           -1.3553478144576052,
+           -1.4507977538241188,
+           -1.5400123247754862,
+           -1.6214134653793268,
+           -1.693542132276571,
+           -1.7550990505271313,
+           -1.8049820870706486,
+           -1.8423192560636843,
+           -1.8664964671274127,
+           -1.8771792531574958,
+           -1.8743278597453954,
+           -1.8582052398729172,
+           -1.8293776713919498,
+           -1.7887078965978769,
+           -1.7373408684492917,
+           -1.6766823720834796,
+           -1.6083709686497953,
+           -1.5342438766861457,
+           -1.456297560094562,
+           -1.376643927373869,
+           -1.2974631607277736,
+           -1.220954283100409,
+           -1.1492846338143379,
+           -1.084539457671614,
+           -1.0286728171996298,
+           -0.9834610129760426,
+           -0.9504596431755723,
+           -0.930965351887765,
+           -0.9259832082880471,
+           -0.936200527973428,
+           -0.9619677968463867,
+           -1.0032871904931078,
+           -1.0598090021141608,
+           -1.1308361040970565,
+           -1.2153363768452794,
+           -1.3119628481627545,
+           -1.419081101979071,
+           -1.5348033409932444,
+           -1.6570283281686056,
+           -1.783486290830534,
+           -1.9117877518547477,
+           -2.0394751580040094,
+           -2.1640761081858826,
+           -2.283156945910433,
+           -2.394375471465782,
+           -2.4955315505165436,
+           -2.584614446445438,
+           -2.659845782563587,
+           -2.7197171453809075,
+           -2.7630214688839643,
+           -2.78887748906511,
+           -2.796746724132904,
+           -2.786442614848574,
+           -2.7581316469037147,
+           -2.7123264686054496,
+           -2.6498712077007407,
+           -2.5719193763101886,
+           -2.479904928151046,
+           -2.375507193256054,
+           -2.2606105583403906,
+           -2.13725988238411,
+           -2.007612733967402,
+           -1.8738896071110314,
+           -1.7383233141875358,
+           -1.6031087669341666,
+           -1.4703543394943273,
+           -1.3420359612477848,
+           -1.2199550131833805,
+           -1.1057010016272746,
+           -1.0006198598072402,
+           -0.9057885841236082,
+           -0.8219967517180342,
+           -0.7497352929954247,
+           -0.6891927114784632,
+           -0.6402587582720148,
+           -0.6025353840838029,
+           -0.5753546127567399,
+           -0.5578028110424086,
+           -0.5487506740567997,
+           -0.5468881083254574,
+           -0.5507630779118466,
+           -0.5588233866631281,
+           -0.569460303331562,
+           -0.5810528978098255,
+           -0.5920119468308997,
+           -0.60082228638753,
+           -0.6060825352623926,
+           -0.6065411881627699,
+           -0.6011281760854355,
+           -0.5889811131375198,
+           -0.5694655899883081,
+           -0.5421890308255979,
+           -0.5070077991496714,
+           -0.4640274136798349,
+           -0.41359591461223216,
+           -0.3562905979226732,
+           -0.29289850686670865,
+           -0.22439123095888172,
+           -0.15189470944551592,
+           -0.07665486491786654,
+           -7.165134511644309e-16
+          ],
+          [
+           0,
+           0.0760635878985933,
+           0.15020317920228252,
+           0.22112736369370437,
+           0.2876444335722459,
+           0.3486984336877013,
+           0.40340152379669425,
+           0.45106177263982933,
+           0.49120562143975316,
+           0.5235943919571607,
+           0.5482343680410348,
+           0.5653801457868123,
+           0.5755311217725481,
+           0.5794211669695538,
+           0.5780017113120062,
+           0.572418636064643,
+           0.5639835336799802,
+           0.5541400436530631,
+           0.5444261041685285,
+           0.5364330697321196,
+           0.5317627316462942,
+           0.5319833388774737,
+           0.5385857499686149,
+           0.5529408512616011,
+           0.5762593526079365,
+           0.6095550194801126,
+           0.6536123211726864,
+           0.7089593705011709,
+           0.775846903598098,
+           0.8542339021670317,
+           0.9437802984765141,
+           1.0438470294497415,
+           1.1535035247290495,
+           1.271542529062067,
+           1.3965019763496287,
+           1.526693455768227,
+           1.660236643944885,
+           1.7950989253828824,
+           1.9291392900213724,
+           2.0601554853203043,
+           2.1859333134208683,
+           2.3042969039635666,
+           2.4131587616139467,
+           2.510568385113698,
+           2.5947582818835224,
+           2.664186258270139,
+           2.7175729491550555,
+           2.753933659849194,
+           2.7726037253723765,
+           2.7732567441783607,
+           2.755915211460487,
+           2.7209532572846316,
+           2.669091382567794,
+           2.601383276781201,
+           2.519194990553585,
+           2.4241769194639047,
+           2.3182292277703476,
+           2.2034614984088785,
+           2.0821475344550158,
+           1.9566763539790066,
+           1.829500511978605,
+           1.7030829475974598,
+           1.5798435905487365,
+           1.462106966686311,
+           1.3520520188493323,
+           1.2516653060304823,
+           1.162698662880248,
+           1.086632294539396,
+           1.0246441514056777,
+           0.9775862778751758,
+           0.9459686620328553,
+           0.9299509337813049,
+           0.9293420713732038,
+           0.9436080853263293,
+           0.9718874589051462,
+           1.0130139403710083,
+           1.0655461085066928,
+           1.127802973725244,
+           1.1979047362313475,
+           1.273817703612864,
+           1.3534022757586066,
+           1.434462837374603,
+           1.514798359189386,
+           1.5922524990819165,
+           1.6647620139922463,
+           1.7304023420183066,
+           1.787429290283554,
+           1.8343158660227232,
+           1.869783413290181,
+           1.8928263625962818,
+           1.9027300619850491,
+           1.8990813315496191,
+           1.8817715648138074,
+           1.8509923852756216,
+           1.8072240501232266,
+           1.751216971146878,
+           1.6839668907843024,
+           1.6066844049157052,
+           1.5207596596947348,
+           1.42772316404653,
+           1.3292037497048284,
+           1.2268847746247344,
+           1.1224597017837563,
+           1.01758819295498,
+           0.9138538359022143,
+           0.8127245742248286,
+           0.7155168330873061,
+           0.6233642332903555,
+           0.5371916631786258,
+           0.45769533588720346,
+           0.3853293020300016,
+           0.3202987191327707,
+           0.26256000319709594,
+           0.21182780920735025,
+           0.16758861067892122,
+           0.12912047795981746,
+           0.09551849524188194,
+           0.0657251111432731,
+           0.03856459094960283,
+           0.012780633341989549,
+           -0.012923866652428562,
+           -0.03984598163690864,
+           -0.06924194319469941,
+           -0.10228746008180736,
+           -0.14004023351109868,
+           -0.18340568304781416,
+           -0.23310681383473095,
+           -0.2896590490796294,
+           -0.35335072366356957,
+           -0.424229788598564,
+           -0.5020971155675091,
+           -0.5865066199719412,
+           -0.676772244112019,
+           -0.7719816638008136,
+           -0.8710164063872345,
+           -0.9725779002748645,
+           -1.0752188198419739,
+           -1.1773789491673783,
+           -1.2774246667357825,
+           -1.3736910544444854,
+           -1.4645255603140603,
+           -1.5483320972511054,
+           -1.6236144412829403,
+           -1.6890178024420248,
+           -1.7433674797635577,
+           -1.785703577800966,
+           -1.8153108540947698,
+           -1.8317428829289883,
+           -1.834839857653405,
+           -1.8247395084853277,
+           -1.801880781228074,
+           -1.7670001005975269,
+           -1.7211202254230584,
+           -1.6655318873328409,
+           -1.6017685850643215,
+           -1.5315750787609292,
+           -1.4568702882243982,
+           -1.379705442090455,
+           -1.3022184476882102,
+           -1.2265855508278292,
+           -1.1549714284041293,
+           -1.0894789026070126,
+           -1.0320994824757554,
+           -0.9846659260188715,
+           -0.9488079743667052,
+           -0.9259123393733655,
+           -0.9170879293812246,
+           -0.9231371768076329,
+           -0.9445341887154329,
+           -0.9814102810251533,
+           -1.0335472824038057,
+           -1.1003788093625801,
+           -1.1809995242012863,
+           -1.2741821967774656,
+           -1.3784022043027475,
+           -1.491868925038884,
+           -1.612563316237978,
+           -1.7382808179935212,
+           -1.8666785964783865,
+           -1.9953260354809517,
+           -2.121757306772031,
+           -2.243524799563994,
+           -2.358252168392875,
+           -2.463685767678804,
+           -2.557743279785092,
+           -2.6385584106594924,
+           -2.7045206214598143,
+           -2.7543089836344414,
+           -2.786919385836118,
+           -2.801684480351342,
+           -2.7982859305354855,
+           -2.7767587048116407,
+           -2.737487352626636,
+           -2.681194388731712,
+           -2.608921099615601,
+           -2.522001265303231,
+           -2.422028456686796,
+           -2.310817719030726,
+           -2.1903625826518494,
+           -2.062788448883492,
+           -1.9303034807265713,
+           -1.7951481811490053,
+           -1.6595448665802965,
+           -1.5256482382386003,
+           -1.3954982197273884,
+           -1.2709761667741302,
+           -1.153765465676979,
+           -1.0453174232559392,
+           -0.9468232157503274,
+           -0.8591925105692461,
+           -0.7830392069319722,
+           -0.7186745634233046,
+           -0.6661077967682969,
+           -0.6250540512667075,
+           -0.5949494569024242,
+           -0.5749728206444104,
+           -0.5640733341633584,
+           -0.561003536069134,
+           -0.5643566413844512,
+           -0.5726072483670562,
+           -0.5841543554591271,
+           -0.5973655709265229,
+           -0.6106213758198924,
+           -0.6223583077038818,
+           -0.6311099679006854,
+           -0.6355448178094804,
+           -0.6344998185370425,
+           -0.6270090803066665,
+           -0.6123268210156846,
+           -0.5899440834873518,
+           -0.5595988245834576,
+           -0.5212791622516684,
+           -0.47521974439099796,
+           -0.4218913816272526,
+           -0.361984260191125,
+           -0.29638521668618373,
+           -0.22614970944227875,
+           -0.1524692575147679,
+           -0.07663523477399013,
+           -7.134478006290147e-16
+          ],
+          [
+           0,
+           0.07520709369811655,
+           0.1479145368555273,
+           0.21688309825486954,
+           0.2809925746419807,
+           0.33927577050809954,
+           0.390948294895722,
+           0.4354333627482429,
+           0.47238091742563393,
+           0.5016805378310005,
+           0.5234677544260514,
+           0.5381235691920222,
+           0.5462671509973023,
+           0.548741855399251,
+           0.5465948921368569,
+           0.5410511300433045,
+           0.5334816835930443,
+           0.5253680638622211,
+           0.518262795784416,
+           0.5137475001691718,
+           0.5133895105227426,
+           0.5186981393965515,
+           0.5310817255875215,
+           0.5518065815264003,
+           0.5819589198311713,
+           0.6224107701993503,
+           0.6737908041806245,
+           0.7364608681745731,
+           0.8104988870953291,
+           0.8956886459177542,
+           0.9915167875893756,
+           1.097177187725884,
+           1.2115826835141945,
+           1.3333839508677,
+           1.4609951446749914,
+           1.592625746424466,
+           1.726317905836609,
+           1.859988422346635,
+           1.9914743918965303,
+           2.118581447563373,
+           2.2391334515424366,
+           2.351022452754699,
+           2.4522577100125362,
+           2.5410125956959404,
+           2.6156682389816956,
+           2.674852839829367,
+           2.7174756834656333,
+           2.7427550076748686,
+           2.7502390188549546,
+           2.7398195140655948,
+           2.711737741275051,
+           2.666582314450793,
+           2.6052791895517045,
+           2.5290738972480695,
+           2.4395064136896805,
+           2.3383792273311723,
+           2.2277193233870083,
+           2.1097349539248698,
+           1.986768187329617,
+           1.861244332800579,
+           1.7356194111829335,
+           1.6123268909229793,
+           1.4937249261089625,
+           1.382045321963466,
+           1.2793454120681707,
+           1.1874639620271206,
+           1.1079821179077927,
+           1.0421902969928376,
+           0.9910617760797559,
+           0.9552335722557312,
+           0.9349950366646682,
+           0.9302843975297986,
+           0.94069329909277,
+           0.9654791928004658,
+           1.0035852506489928,
+           1.0536672926144293,
+           1.1141270548839797,
+           1.1831509771523296,
+           1.2587535591527792,
+           1.3388242319326544,
+           1.4211766106590005,
+           1.5035989448137494,
+           1.5839045596810009,
+           1.6599810905021402,
+           1.7298373473110336,
+           1.7916467132784784,
+           1.8437860707165115,
+           1.8848693643936376,
+           1.9137750485743386,
+           1.9296668187846238,
+           1.9320071978513296,
+           1.920563724061345,
+           1.8954076729011298,
+           1.8569054282084227,
+           1.8057027991301706,
+           1.7427027515716536,
+           1.6690371825950863,
+           1.586033509555861,
+           1.4951769691427383,
+           1.398069621910442,
+           1.2963871329333017,
+           1.1918344470779556,
+           1.0861014969844391,
+           0.9808200727584118,
+           0.8775229449295959,
+           0.7776062674478569,
+           0.6822961970744529,
+           0.5926205518259952,
+           0.5093861970652196,
+           0.43316269683301944,
+           0.3642726039268758,
+           0.3027885892199802,
+           0.24853743316909294,
+           0.20111072487130657,
+           0.15988194088924082,
+           0.12402941174260017,
+           0.09256453260691859,
+           0.06436444018271055,
+           0.038208263290001515,
+           0.01281596338373959,
+           -0.013111284827699281,
+           -0.04085026148784321,
+           -0.07161551827624354,
+           -0.10652092630128576,
+           -0.14654399279360927,
+           -0.192493912482079,
+           -0.2449842229654781,
+           -0.3044108144057027,
+           -0.37093590546825195,
+           -0.4444784431197518,
+           -0.5247112175601153,
+           -0.6110648094238832,
+           -0.702738308837178,
+           -0.7987165694592181,
+           -0.8977935897435741,
+           -0.9986014526630019,
+           -1.0996441081476866,
+           -1.1993351532391223,
+           -1.2960386567692561,
+           -1.3881119910217605,
+           -1.4739495745106128,
+           -1.5520263992624417,
+           -1.6209402136662776,
+           -1.6794512582000984,
+           -1.7265185055847356,
+           -1.7613314378776137,
+           -1.7833364987555,
+           -1.792257487177537,
+           -1.78810930563777,
+           -1.7712046386972946,
+           -1.7421533114236132,
+           -1.7018542584575311,
+           -1.6514802181866999,
+           -1.5924554483639533,
+           -1.5264269349386206,
+           -1.4552297304904296,
+           -1.3808472083468109,
+           -1.3053671494654198,
+           -1.2309346881687278,
+           -1.159703227059086,
+           -1.093784488759686,
+           -1.035198901020177,
+           -0.9858275113950521,
+           -0.9473665980687384,
+           -0.9212860851072183,
+           -0.9087927848133781,
+           -0.9107993789797811,
+           -0.9278999173221393,
+           -0.9603524584547909,
+           -1.0080693101347764,
+           -1.0706151452441377,
+           -1.1472130824834086,
+           -1.2367586305790683,
+           -1.3378412066020706,
+           -1.4487727573480527,
+           -1.567622842082306,
+           -1.6922593794770924,
+           -1.820394125071402,
+           -1.9496318314067254,
+           -2.077521953935504,
+           -2.2016117040463743,
+           -2.319499217619018,
+           -2.428885604223604,
+           -2.5276246685010735,
+           -2.6137691507609837,
+           -2.685612417059391,
+           -2.741724637939791,
+           -2.7809826269754865,
+           -2.802592662019373,
+           -2.8061057799412343,
+           -2.7914252155148525,
+           -2.7588058426186617,
+           -2.708845666461765,
+           -2.642469604499491,
+           -2.560905976460392,
+           -2.465656296028047,
+           -2.3584591140308557,
+           -2.241248801684519,
+           -2.116110279160909,
+           -1.9852307867234444,
+           -1.8508498606856338,
+           -1.7152087129942681,
+           -1.5805002204934375,
+           -1.4488207077931374,
+           -1.3221246567731415,
+           -1.202183397433133,
+           -1.090548731060768,
+           -0.9885223101596645,
+           -0.89713145344595,
+           -0.8171119121487065,
+           -0.74889792988533,
+           -0.6926197568623994,
+           -0.6481085945873793,
+           -0.6149087642434483,
+           -0.5922967149069343,
+           -0.5793063212421736,
+           -0.5747597682908399,
+           -0.5773031872103587,
+           -0.5854460935754928,
+           -0.5976035918618604,
+           -0.6121402480941002,
+           -0.6274144988168324,
+           -0.6418224592895815,
+           -0.6538400171586004,
+           -0.6620621491461248,
+           -0.66523847615117,
+           -0.6623041745439311,
+           -0.6524054857167896,
+           -0.634919208943481,
+           -0.6094657206461311,
+           -0.5759152322573988,
+           -0.5343871747013496,
+           -0.4852427756481352,
+           -0.42907107161840036,
+           -0.3666687662794978,
+           -0.29901450461503265,
+           -0.22723827606919228,
+           -0.1525867846540029,
+           -0.07638572721680723,
+           -7.082637558517266e-16
+          ],
+          [
+           0,
+           0.07413709835275921,
+           0.14522400484054135,
+           0.2120837114363483,
+           0.27367640813371447,
+           0.3291311132120628,
+           0.3777726649168713,
+           0.41914333635258993,
+           0.45301847459912176,
+           0.4794157198424507,
+           0.4985975267427819,
+           0.5110668841392817,
+           0.5175563061081997,
+           0.5190103428692708,
+           0.5165620296238558,
+           0.5115038508004445,
+           0.5052539423232434,
+           0.4993183817047742,
+           0.4952505217369016,
+           0.49460840558754515,
+           0.49891135707029904,
+           0.5095968682598457,
+           0.5279789066844436,
+           0.5552087359542063,
+           0.5922392875087659,
+           0.6397940385161398,
+           0.6983412438172653,
+           0.7680742407954104,
+           0.8488983983163737,
+           0.9404251180684386,
+           1.0419731227491276,
+           1.1525770849027714,
+           1.271003467290637,
+           1.3957732650230008,
+           1.5251911658029627,
+           1.6573804818700868,
+           1.7903230596667499,
+           1.9219032445923503,
+           2.049954871710578,
+           2.1723101716411204,
+           2.2868494261982826,
+           2.3915501820707035,
+           2.484534833705425,
+           2.5641154185842256,
+           2.6288345285583854,
+           2.677501328435003,
+           2.709221785508325,
+           2.723422348509346,
+           2.719866468258337,
+           2.698663521426532,
+           2.6602698791406643,
+           2.60548204931164,
+           2.535422010976461,
+           2.4515150459895323,
+           2.355460553516243,
+           2.249196501564518,
+           2.1348583231076126,
+           2.0147331984490577,
+           1.8912107770704019,
+           1.7667314785467654,
+           1.6437335710925143,
+           1.5246002564578123,
+           1.4116079904894345,
+           1.3068772396729742,
+           1.2123268160895397,
+           1.1296328478565882,
+           1.0601933313605993,
+           1.0050990781307876,
+           0.9651117163050288,
+           0.9406492380326885,
+           0.9317794039580757,
+           0.9382211285277038,
+           0.9593537798324907,
+           0.9942341396608101,
+           1.0416205879749822,
+           1.1000039055412583,
+           1.167643933076221,
+           1.2426111887792812,
+           1.3228324317919975,
+           1.4061390697017517,
+           1.4903172458155949,
+           1.5731584080280172,
+           1.65250915644923,
+           1.7263191915833964,
+           1.7926862380630346,
+           1.8498968993685587,
+           1.8964625045345105,
+           1.9311491358949318,
+           1.953001174229149,
+           1.9613578605468458,
+           1.9558625481323901,
+           1.9364645000120366,
+           1.903413271205604,
+           1.8572458974128168,
+           1.7987672876575895,
+           1.7290243835345116,
+           1.6492747980106222,
+           1.5609507785494836,
+           1.4656194494285593,
+           1.3649403738472543,
+           1.2606215357167874,
+           1.1543748724918432,
+           1.0478724933524448,
+           0.9427046914897614,
+           0.8403408059203511,
+           0.7420939085709509,
+           0.6490901884171605,
+           0.5622437789046766,
+           0.48223763094730915,
+           0.4095108751522778,
+           0.34425294760388725,
+           0.2864045778358868,
+           0.23566555998911579,
+           0.19150905307492802,
+           0.15320198816689823,
+           0.11983100346322727,
+           0.09033318645339776,
+           0.0635307794525542,
+           0.03816890362909503,
+           0.012955279886313065,
+           -0.013399125506303466,
+           -0.042139625539468,
+           -0.07442859712833381,
+           -0.11130858237807517,
+           -0.15366870265436977,
+           -0.20221529568918456,
+           -0.2574475765415772,
+           -0.31963899315196387,
+           -0.38882479976532486,
+           -0.4647962103824786,
+           -0.5471013237037825,
+           -0.6350528350752588,
+           -0.7277423741885858,
+           -0.8240611342034211,
+           -0.9227262929452135,
+           -1.0223125740786485,
+           -1.1212881595574358,
+           -1.2180540476961996,
+           -1.3109858569021855,
+           -1.3984770058814604,
+           -1.4789821588089898,
+           -1.5510598096653394,
+           -1.6134128941343322,
+           -1.6649263598530502,
+           -1.704700695427678,
+           -1.7320805138125037,
+           -1.7466774040883188,
+           -1.7483864044778772,
+           -1.737395605192262,
+           -1.714188558574577,
+           -1.679539351822095,
+           -1.6345003799183297,
+           -1.580383038762783,
+           -1.518731736308321,
+           -1.4512917883663572,
+           -1.3799719213933226,
+           -1.3068022431210369,
+           -1.23388865984744,
+           -1.1633648135734953,
+           -1.097342680546145,
+           -1.0378630133729099,
+           -0.9868468206215596,
+           -0.9460490603292314,
+           -0.9170156774623456,
+           -0.9010450411484238,
+           -0.8991547371885469,
+           -0.9120545473468297,
+           -0.9401263021809515,
+           -0.9834111322206761,
+           -1.0416044670445583,
+           -1.1140589475066105,
+           -1.1997952275113757,
+           -1.2975204529321471,
+           -1.4056540211227342,
+           -1.5223600494881373,
+           -1.6455858200351947,
+           -1.7731053226751827,
+           -1.902566896829245,
+           -2.0315438716162033,
+           -2.1575870320179926,
+           -2.2782776937129094,
+           -2.391280153843771,
+           -2.494392299233526,
+           -2.585593197134089,
+           -2.663086565438127,
+           -2.725339117647255,
+           -2.771112900375439,
+           -2.799490884784316,
+           -2.809895234592832,
+           -2.8020978482425494,
+           -2.7762229571642707,
+           -2.732741751386328,
+           -2.672459193337184,
+           -2.5964933660092804,
+           -2.5062478781612416,
+           -2.4033780126567983,
+           -2.2897514504124965,
+           -2.167404528216806,
+           -2.038495090865805,
+           -1.90525307419379,
+           -1.7699300038640224,
+           -1.63474861411457,
+           -1.501853780631396,
+           -1.3732659226715673,
+           -1.2508379625240515,
+           -1.1362168371018084,
+           -1.0308104392779658,
+           -0.9357607284657805,
+           -0.8519235943625942,
+           -0.7798558886216221,
+           -0.7198098606979285,
+           -0.6717350506751967,
+           -0.6352875080676879,
+           -0.6098460259564071,
+           -0.594534908794757,
+           -0.5882526340184788,
+           -0.5897056261007987,
+           -0.5974462403658937,
+           -0.6099139556626307,
+           -0.6254787022745194,
+           -0.6424852059299792,
+           -0.6592972115262397,
+           -0.6743404615307168,
+           -0.6861433436010842,
+           -0.6933741886911552,
+           -0.694874293029504,
+           -0.6896858524850256,
+           -0.6770741330111265,
+           -0.6565433526333391,
+           -0.6278459149500609,
+           -0.59098480717549,
+           -0.5462091529826396,
+           -0.49400308731910497,
+           -0.4350682924993019,
+           -0.37030069788062786,
+           -0.3007619951979529,
+           -0.22764675438873438,
+           -0.15224603714898577,
+           -0.07590849469238757,
+           -7.010069300183296e-16
+          ],
+          [
+           0,
+           0.07286302508172521,
+           0.14215521657617017,
+           0.20677120932375972,
+           0.26575969494740403,
+           0.3183524464990932,
+           0.3639882921409837,
+           0.4023313797812862,
+           0.4332832226366229,
+           0.45698817703810274,
+           0.4738321743554531,
+           0.4844347043646352,
+           0.48963422328518963,
+           0.4904673316044388,
+           0.48814223032331816,
+           0.4840071152453989,
+           0.4795143035391009,
+           0.47618100159225973,
+           0.4755477152004554,
+           0.479135370005573,
+           0.48840225007635113,
+           0.504701874517693,
+           0.5292429156297337,
+           0.5630522177408696,
+           0.606941904443863,
+           0.6614814652816072,
+           0.7269755933062529,
+           0.8034484052979299,
+           0.8906345202093873,
+           0.9879773024543846,
+           1.094634399160541,
+           1.2094905188642877,
+           1.3311772178523877,
+           1.4580992839683844,
+           1.588467140609023,
+           1.7203345400202883,
+           1.8516406787248412,
+           1.980255752410682,
+           2.1040288758154775,
+           2.2208372274018924,
+           2.328635240646284,
+           2.4255026545822584,
+           2.5096902561685956,
+           2.5796621956855548,
+           2.6341338325927595,
+           2.6721041713109,
+           2.6928820717835253,
+           2.6961055654195927,
+           2.6817537695905855,
+           2.6501510693165553,
+           2.6019634188582685,
+           2.538186804154723,
+           2.460128094814824,
+           2.3693786971029684,
+           2.2677815925818403,
+           2.1573925065521524,
+           2.0404360922505522,
+           1.9192581374559512,
+           1.7962748967476314,
+           1.6739207227816,
+           1.5545952118769322,
+           1.4406110918937547,
+           1.334144063516694,
+           1.2371857600336504,
+           1.151500916634659,
+           1.0785897399511417,
+           1.019656344455822,
+           0.9755839774735366,
+           0.9469175924465415,
+           0.9338541547080118,
+           0.9362408796211055,
+           0.9535814140324254,
+           0.9850497831694944,
+           1.0295117409770653,
+           1.0855529869127756,
+           1.1515135506552903,
+           1.2255275019306944,
+           1.3055670192184419,
+           1.3894897514247744,
+           1.4750883330892013,
+           1.5601408680528053,
+           1.6424611798122604,
+           1.7199476393438953,
+           1.790629422621395,
+           1.8527091192718155,
+           1.9046007090393036,
+           1.9449620415383906,
+           1.9727210941869762,
+           1.9870954397191716,
+           1.9876045243815201,
+           1.974074536586775,
+           1.9466358289992247,
+           1.9057130402141718,
+           1.8520082408419094,
+           1.7864775985064003,
+           1.7103022128459546,
+           1.6248539112176126,
+           1.5316569150489017,
+           1.432346382754257,
+           1.328624905528018,
+           1.2222180754728054,
+           1.1148302604344995,
+           1.0081017063125342,
+           0.9035680459280021,
+           0.8026232248932821,
+           0.7064867611382764,
+           0.616176138237033,
+           0.532484996435887,
+           0.45596763279013247,
+           0.3869301569509364,
+           0.3254284760922896,
+           0.27127310561178297,
+           0.22404062605086061,
+           0.18309143560854083,
+           0.14759328598186122,
+           0.11654994112864747,
+           0.08883416764207305,
+           0.06322415504293505,
+           0.03844237720679033,
+           0.013195844532607184,
+           -0.013783338131837845,
+           -0.043698199505360524,
+           -0.07764898620436354,
+           -0.11659812495529163,
+           -0.1613390092012615,
+           -0.21246945722149121,
+           -0.2703705676639638,
+           -0.33519155841704334,
+           -0.406841019555844,
+           -0.48498484462040126,
+           -0.5690509309286179,
+           -0.6582405633920089,
+           -0.7515462218525766,
+           -0.847775383720067,
+           -0.9455797359341269,
+           -1.0434890670209112,
+           -1.139948984913957,
+           -1.233361502469151,
+           -1.3221274528958018,
+           -1.4046896437230483,
+           -1.4795756318442632,
+           -1.5454390043647581,
+           -1.6010980804452244,
+           -1.645571007402059,
+           -1.6781063086197252,
+           -1.6982080493145806,
+           -1.7056549162194834,
+           -1.7005126556451833,
+           -1.683139477463692,
+           -1.6541842063211023,
+           -1.6145771415179866,
+           -1.5655137690214476,
+           -1.5084316484633928,
+           -1.4449809702594032,
+           -1.3769894388426955,
+           -1.3064222834132837,
+           -1.2353383238928388,
+           -1.1658431237568243,
+           -1.1000403404382526,
+           -1.039982436026004,
+           -0.9876219346425824,
+           -0.9447644075080496,
+           -0.9130243323212932,
+           -0.893784910976143,
+           -0.8881628402360302,
+           -0.896978915937914,
+           -0.9207352153173652,
+           -0.9595994474201632,
+           -1.0133968920344296,
+           -1.0816101672571632,
+           -1.1633868790875934,
+           -1.2575550178685568,
+           -1.362645780579046,
+           -1.476923319458031,
+           -1.5984207505786912,
+           -1.7249816048805802,
+           -1.8543057725082677,
+           -1.9839988823297277,
+           -2.1116239748928938,
+           -2.234754270881867,
+           -2.3510258097421777,
+           -2.458188735239197,
+           -2.5541560362559954,
+           -2.6370486113652505,
+           -2.705235613162253,
+           -2.7573691408924854,
+           -2.792412484805023,
+           -2.809661279622333,
+           -2.8087570937829183,
+           -2.789693161558024,
+           -2.752812152367983,
+           -2.6987960610660275,
+           -2.6286484900047644,
+           -2.5436697738036878,
+           -2.4454255665200253,
+           -2.335709664297834,
+           -2.2165019708221343,
+           -2.0899226248003058,
+           -1.9581833955500603,
+           -1.8235375125281652,
+           -1.6882291258925617,
+           -1.5544435972599289,
+           -1.4242597927286198,
+           -1.299605494726978,
+           -1.182216966761409,
+           -1.0736035977811542,
+           -0.9750184233599062,
+           -0.8874351724710489,
+           -0.8115323250164651,
+           -0.747684490538643,
+           -0.6959612370473262,
+           -0.6561333151289319,
+           -0.6276860410282343,
+           -0.6098394276798292,
+           -0.6015744890257008,
+           -0.6016649944048628,
+           -0.6087138199775151,
+           -0.6211929362119809,
+           -0.6374859870292738,
+           -0.6559323592631408,
+           -0.6748716119847956,
+           -0.6926871345964687,
+           -0.7078479303409674,
+           -0.7189474772215586,
+           -0.7247386998062257,
+           -0.7241641908810856,
+           -0.7163809487013467,
+           -0.7007790404192353,
+           -0.6769937614547045,
+           -0.6449110300717069,
+           -0.6046659319330618,
+           -0.5566345064894277,
+           -0.5014190412383581,
+           -0.4398273067724619,
+           -0.3728463209148886,
+           -0.30161137020328077,
+           -0.22737113800903772,
+           -0.15144988762618417,
+           -0.07520772324784447,
+           -6.917412759595509e-16
+          ],
+          [
+           0,
+           0.07139606537088652,
+           0.138735032995495,
+           0.20099189165341194,
+           0.25731109178621736,
+           0.30703273363752515,
+           0.34971333868624505,
+           0.3851406314990103,
+           0.4133419146745972,
+           0.43458578602374853,
+           0.4493771203070409,
+           0.45844541335442385,
+           0.46272675976386096,
+           0.4633399022237132,
+           0.46155694658443486,
+           0.4587694781462365,
+           0.456450937622879,
+           0.45611621673647795,
+           0.45927951077872825,
+           0.4674115167267379,
+           0.48189708926594743,
+           0.5039944626752677,
+           0.5347971140026812,
+           0.5751992830404921,
+           0.625866078723277,
+           0.6872089917965954,
+           0.7593675026208382,
+           0.8421973239985444,
+           0.9352656556178051,
+           1.0378536531275344,
+           1.1489661353063163,
+           1.2673483717180898,
+           1.3915096151756345,
+           1.5197528727031602,
+           1.6502102497735973,
+           1.7808830593846285,
+           1.909685763639049,
+           2.0344927140477633,
+           2.153186580365844,
+           2.263707308376965,
+           2.364100425968168,
+           2.4525635246960134,
+           2.527489780733475,
+           2.58750744378856,
+           2.631514313791102,
+           2.65870634068741,
+           2.6685996197926523,
+           2.6610452105209776,
+           2.636236376180602,
+           2.5947080227596637,
+           2.5373283008507856,
+           2.4652825225268336,
+           2.3800497295037055,
+           2.283372425796323,
+           2.177220152960902,
+           2.0637477348797373,
+           1.9452491482318075,
+           1.8241080811311483,
+           1.7027463232892202,
+           1.583571184474772,
+           1.4689231626826904,
+           1.3610250786648441,
+           1.2619338594227618,
+           1.1734960907337153,
+           1.0973083692947418,
+           1.0346833707999545,
+           0.9866224139980543,
+           0.9537951458300422,
+           0.9365268028988138,
+           0.9347933239126469,
+           0.9482244007749753,
+           0.9761143672174268,
+           1.0174406378868193,
+           1.0708892321222567,
+           1.134886749634661,
+           1.2076380139767635,
+           1.287168467725979,
+           1.3713702938752188,
+           1.4580511536600578,
+           1.5449843739456393,
+           1.6299593886841681,
+           1.7108312394627094,
+           1.7855679697029172,
+           1.8522948048477097,
+           1.9093340953792821,
+           1.9552401086081108,
+           1.9888278861016584,
+           2.0091955330999363,
+           2.015739470557831,
+           2.0081623554682437,
+           1.9864735565070197,
+           1.9509822553036258,
+           1.902283424247755,
+           1.8412371052345675,
+           1.7689415758595288,
+           1.686701136319498,
+           1.5959893780714303,
+           1.4984089010345598,
+           1.3956485272419448,
+           1.2894391134165475,
+           1.1815090916945574,
+           1.073540866068853,
+           0.9671291622122322,
+           0.8637423710016255,
+           0.7646878428220026,
+           0.6710819827476951,
+           0.5838258687333809,
+           0.5035869692712018,
+           0.43078737729588895,
+           0.36559880750153845,
+           0.30794442896999974,
+           0.2575074285341473,
+           0.21374602706612045,
+           0.17591450525972602,
+           0.14308964163942042,
+           0.11420182734634117,
+           0.08807000319774787,
+           0.06343946757823278,
+           0.039021531328640655,
+           0.013533949761442784,
+           -0.014258956605639441,
+           -0.045507571590754185,
+           -0.08124068504189548,
+           -0.12233260469744568,
+           -0.16947456723721355,
+           -0.22315122569002346,
+           -0.2836228584717051,
+           -0.3509137967402666,
+           -0.4248074052344869,
+           -0.5048477813971711,
+           -0.5903481626895676,
+           -0.6804058570105411,
+           -0.7739233404812971,
+           -0.8696350048768766,
+           -0.9661388877987371,
+           -1.0619325860913253,
+           -1.1554524403995556,
+           -1.2451149890360886,
+           -1.3293596247991228,
+           -1.4066913507454455,
+           -1.475722521200101,
+           -1.5352124727949041,
+           -1.5841039966870822,
+           -1.6215556762324155,
+           -1.6469692125169595,
+           -1.6600109809015338,
+           -1.6606272021460524,
+           -1.649052268301386,
+           -1.6258099325170634,
+           -1.5917072490296196,
+           -1.5478213304716595,
+           -1.4954791697751382,
+           -1.436230948841304,
+           -1.3718174214418548,
+           -1.3041321093572613,
+           -1.2351791847376243,
+           -1.1670280247043903,
+           -1.1017655134261235,
+           -1.0414472300097446,
+           -0.9880486959041876,
+           -0.9434178621531158,
+           -0.9092299945027446,
+           -0.8869460635305685,
+           -0.8777756687771976,
+           -0.8826454221800071,
+           -0.9021735893997092,
+           -0.9366516409476903,
+           -0.9860332019087471,
+           -1.0499307134672053,
+           -1.1276199356542136,
+           -1.2180522332185368,
+           -1.3198743998589664,
+           -1.4314555948051808,
+           -1.5509207943306647,
+           -1.6761900034238673,
+           -1.805022333391188,
+           -1.9350639330398078,
+           -2.0638986671934627,
+           -2.1891003689411646,
+           -2.3082854528703494,
+           -2.419164666564703,
+           -2.519592777111359,
+           -2.6076150378006338,
+           -2.6815093564415875,
+           -2.7398231889073794,
+           -2.7814043071771026,
+           -2.8054247371951186,
+           -2.8113973247644894,
+           -2.7991845634572514,
+           -2.7689995028771683,
+           -2.72139874405838,
+           -2.6572677167376177,
+           -2.5777986161252673,
+           -2.4844615501773637,
+           -2.3789696080293643,
+           -2.263238702327757,
+           -2.1393431592572645,
+           -2.0094681271993706,
+           -1.8758599458538476,
+           -1.7407756606374585,
+           -1.6064328812607505,
+           -1.4749611683031345,
+           -1.3483560878054082,
+           -1.2284370025294078,
+           -1.1168095714249238,
+           -1.014833808453573,
+           -0.92359841127561,
+           -0.8439019129291322,
+           -0.7762410394482876,
+           -0.7208064776119498,
+           -0.6774860741229317,
+           -0.6458753050194337,
+           -0.6252946765236412,
+           -0.6148135502147107,
+           -0.6132797305118312,
+           -0.6193540147629304,
+           -0.6315487891149388,
+           -0.6482696596328605,
+           -0.6678590400894272,
+           -0.6886405770732484,
+           -0.7089632804873582,
+           -0.7272442433530444,
+           -0.7420088786084494,
+           -0.751927671113756,
+           -0.7558485384958735,
+           -0.7528240123178214,
+           -0.7421325883175438,
+           -0.7232937476242708,
+           -0.6960763160317393,
+           -0.6605000013971782,
+           -0.616830125663581,
+           -0.5655657434121728,
+           -0.5074215088155963,
+           -0.4433038130964239,
+           -0.3742818610662733,
+           -0.3015544843448077,
+           -0.22641359719427978,
+           -0.15020528583678483,
+           -0.07428958152193432,
+           -6.805483731389498e-16
+          ],
+          [
+           0,
+           0.06974906116925877,
+           0.13499326539564016,
+           0.1947958810938991,
+           0.24840346127378168,
+           0.29526899149413566,
+           0.33506930496024045,
+           0.3677162813753501,
+           0.39336150779919754,
+           0.41239424988535156,
+           0.42543275615586507,
+           0.43330909200769785,
+           0.43704786951581637,
+           0.4378393995009265,
+           0.4370079396851253,
+           0.43597584330961076,
+           0.4362245229963491,
+           0.4392532320636225,
+           0.4465367276905626,
+           0.4594829156357126,
+           0.47939158368920254,
+           0.507415310414094,
+           0.5445235874510499,
+           0.5914711188571643,
+           0.6487711614266567,
+           0.7166746481229536,
+           0.7951556956260263,
+           0.8839039400425253,
+           0.9823239759189923,
+           1.0895419970271425,
+           1.2044195573446328,
+           1.3255741917189086,
+           1.4514064623419638,
+           1.580132833718226,
+           1.709823629377254,
+           1.8384451919299782,
+           1.963905257520833,
+           2.084100469101491,
+           2.196964892470912,
+           2.300518366274232,
+           2.3929135130294497,
+           2.4724802629493072,
+           2.5377667953272485,
+           2.5875758823414845,
+           2.6209957254092853,
+           2.6374245021786877,
+           2.6365879897967135,
+           2.6185497936733255,
+           2.583713886599034,
+           2.5328193464980875,
+           2.4669273678370605,
+           2.387400807200531,
+           2.295876703255859,
+           2.1942323808580255,
+           2.0845459042380208,
+           1.9690517812661943,
+           1.8500929363183298,
+           1.7300700604546402,
+           1.6113895122019761,
+           1.4964109786101187,
+           1.3873961135259307,
+           1.2864593479991784,
+           1.1955220169231975,
+           1.1162708676490682,
+           1.0501219122954306,
+           0.9981904583369969,
+           0.9612680048887017,
+           0.9398065284941984,
+           0.9339105061634351,
+           0.9433368391737618,
+           0.967502653239596,
+           1.005500763641294,
+           1.0561224123334203,
+           1.1178867123375298,
+           1.1890760770306463,
+           1.2677767720853519,
+           1.3519236091766627,
+           1.439347705995618,
+           1.5278261688567776,
+           1.6151325138638837,
+           1.6990866311240145,
+           1.7776031140846134,
+           1.848736822203941,
+           1.9107246186471911,
+           1.96202232364982,
+           2.0013360461059806,
+           2.0276471977613357,
+           2.0402306525698592,
+           2.038665684371304,
+           2.022839494819359,
+           1.9929433260072937,
+           1.9494613339821747,
+           1.8931525758241714,
+           1.825026629847848,
+           1.746313521659314,
+           1.6584287645276496,
+           1.562934437493403,
+           1.4614973160568185,
+           1.355845135970633,
+           1.2477221090586041,
+           1.1388448202261354,
+           1.0308596167605852,
+           0.9253025551800343,
+           0.8235628985154353,
+           0.7268510598969485,
+           0.6361717691678618,
+           0.552303101023351,
+           0.4757818493929985,
+           0.4068955673647378,
+           0.3456814190774002,
+           0.2919318140632972,
+           0.245206619944695,
+           0.20485158058173095,
+           0.1700224079858612,
+           0.13971387154681145,
+           0.11279308100959659,
+           0.08803605337107318,
+           0.06416657110477844,
+           0.03989628193692082,
+           0.013964960208414302,
+           -0.014820152589761946,
+           -0.04754698518430763,
+           -0.08516425640318943,
+           -0.1284510039363416,
+           -0.1779908462848409,
+           -0.23415167895062872,
+           -0.29707136457390565,
+           -0.3666498208752361,
+           -0.44254774385130763,
+           -0.5241920309224836,
+           -0.6107877940145232,
+           -0.7013366803063231,
+           -0.79466105296271,
+           -0.8894334298001442,
+           -0.9842104384348194,
+           -1.0774704255957697,
+           -1.1676537590477931,
+           -1.2532047855179853,
+           -1.3326143591097122,
+           -1.404461833219072,
+           -1.467455415555147,
+           -1.520469820417503,
+           -1.5625802141115142,
+           -1.5930915368112184,
+           -1.6115623951903202,
+           -1.6178228520202493,
+           -1.6119855884375913,
+           -1.5944500780220576,
+           -1.5658995851544253,
+           -1.5272909790402,
+           -1.4798375348378339,
+           -1.4249850700318045,
+           -1.3643819331237796,
+           -1.2998435186478539,
+           -1.2333121235032016,
+           -1.1668130810838222,
+           -1.1024082085883415,
+           -1.0421476766868014,
+           -0.9880214574943772,
+           -0.9419115253093324,
+           -0.9055459742653045,
+           -0.8804561780896841,
+           -0.8679380504220401,
+           -0.8690183711888912,
+           -0.8844270275640522,
+           -0.9145758798735258,
+           -0.9595448067653981,
+           -1.0190753138389637,
+           -1.0925719098477455,
+           -1.1791112689437537,
+           -1.2774590107453008,
+           -1.3860937468492167,
+           -1.5032378672524143,
+           -1.6268943772879065,
+           -1.754888949110259,
+           -1.8849162250845568,
+           -2.014589306754461,
+           -2.1414912849434207,
+           -2.263227615905883,
+           -2.377478126550647,
+           -2.4820474391580047,
+           -2.574912642543596,
+           -2.6542671014067194,
+           -2.718559387070317,
+           -2.766526428752008,
+           -2.7972201220781767,
+           -2.8100267874168035,
+           -2.8046790409611737,
+           -2.781259822195759,
+           -2.7401985080152236,
+           -2.6822592318030885,
+           -2.608521710632494,
+           -2.5203550609336296,
+           -2.4193852481791094,
+           -2.3074569653655748,
+           -2.186590864709602,
+           -2.0589371739056723,
+           -1.92672680995124,
+           -1.7922211579912382,
+           -1.6576617086044356,
+           -1.525220743881169,
+           -1.3969542306749956,
+           -1.2747580194089525,
+           -1.1603283603275736,
+           -1.0551276383042438,
+           -0.9603560950304733,
+           -0.8769301569433451,
+           -0.8054678223455918,
+           -0.7462813859434975,
+           -0.6993775978217236,
+           -0.664465171178853,
+           -0.6409693734787206,
+           -0.6280532634600333,
+           -0.6246449759260271,
+           -0.6294703113426046,
+           -0.6410897615470357,
+           -0.6579389993651907,
+           -0.6783717811499222,
+           -0.7007041590629702,
+           -0.7232588755379221,
+           -0.7444088162981283,
+           -0.7626184303692627,
+           -0.7764820848298255,
+           -0.7847584070134751,
+           -0.7863997753076752,
+           -0.780576248793509,
+           -0.7666933724410679,
+           -0.7444034546838659,
+           -0.7136100838797961,
+           -0.6744658251284624,
+           -0.6273632147320144,
+           -0.5729193418223733,
+           -0.5119544709906667,
+           -0.4454653120089383,
+           -0.3745936791018246,
+           -0.3005913992828365,
+           -0.22478242408095253,
+           -0.14852316917588676,
+           -0.0731621502835053,
+           -6.675265429218629e-16
+          ],
+          [
+           0,
+           0.06793637126423578,
+           0.13096237033671515,
+           0.1882366168663395,
+           0.23911314369534634,
+           0.2831613298758887,
+           0.32017983673917577,
+           0.3502041565542405,
+           0.3735075496051876,
+           0.39059531778545814,
+           0.40219253668826566,
+           0.4092255392534018,
+           0.41279760796855813,
+           0.4141594852504767,
+           0.41467544906045317,
+           0.41578581953073107,
+           0.4189668593502342,
+           0.425689103379739,
+           0.43737519954380866,
+           0.45535836223937504,
+           0.48084253075416017,
+           0.5148652886479286,
+           0.558264536559013,
+           0.6116498219781159,
+           0.6753791173415766,
+           0.7495417050846361,
+           0.8339476783284339,
+           0.9281244023576459,
+           1.0313201090304862,
+           1.142514618047084,
+           1.2604370000231004,
+           1.3835898210391393,
+           1.5102794411470326,
+           1.6386516844044288,
+           1.7667320592760143,
+           1.8924695891871728,
+           2.0137832166666514,
+           2.1286096733353683,
+           2.23495166383637,
+           2.330925195838364,
+           2.414804900968755,
+           2.4850662327190953,
+           2.5404234960899754,
+           2.579862758394192,
+           2.6026688089642263,
+           2.608445474671292,
+           2.5971287547980717,
+           2.5689924091186085,
+           2.5246458128859266,
+           2.465024077428393,
+           2.391370620693541,
+           2.3052125538141945,
+           2.2083294231572332,
+           2.102716008099829,
+           1.9905400190158065,
+           1.8740956641012152,
+           1.755754154668155,
+           1.637912293898919,
+           1.522940341914146,
+           1.4131303691777322,
+           1.3106463002480453,
+           1.2174768109148244,
+           1.13539217476829,
+           1.0659060618520306,
+           1.0102431745214977,
+           0.9693134668233929,
+           0.9436935370065717,
+           0.9336156119882992,
+           0.9389643618903661,
+           0.9592815965282648,
+           0.993778708516837,
+           1.0413565440021448,
+           1.100632206405672,
+           1.169972135236545,
+           1.2475306549482077,
+           1.331293061543136,
+           1.4191222102284191,
+           1.5088074883968767,
+           1.5981150064278262,
+           1.6848378154717492,
+           1.7668449670068456,
+           1.8421282633235059,
+           1.9088456102894578,
+           1.9653599721758812,
+           2.010273040742106,
+           2.042452864357014,
+           2.0610548343360464,
+           2.06553559111868,
+           2.0556595882887616,
+           2.0314982333990854,
+           1.9934217066237003,
+           1.9420837369309079,
+           1.8783997863450332,
+           1.8035192517469967,
+           1.7187924366603433,
+           1.6257331690914185,
+           1.5259780427389773,
+           1.4212433353216578,
+           1.3132807075752502,
+           1.2038328084957977,
+           1.0945899061937328,
+           0.9871486295265628,
+           0.8829738444389333,
+           0.7833646022770142,
+           0.6894249875081866,
+           0.602040562090849,
+           0.5218609565291294,
+           0.4492889971597344,
+           0.38447658952491237,
+           0.32732740308127034,
+           0.2775062273904498,
+           0.23445469875044955,
+           0.19741293326766315,
+           0.16544645173824446,
+           0.137477647187304,
+           0.11232093088019852,
+           0.08872059995283044,
+           0.06539040182292619,
+           0.041053728934290504,
+           0.01448336317837946,
+           -0.015460297130997162,
+           -0.049793553945355215,
+           -0.08937722881274578,
+           -0.13488885198795184,
+           -0.1867999743345024,
+           -0.24535922152753314,
+           -0.3105815605659367,
+           -0.38224408689349904,
+           -0.45988847060923,
+           -0.5428300266208759,
+           -0.6301732005652539,
+           -0.7208330942751854,
+           -0.8135624957846967,
+           -0.906983733371674,
+           -0.9996245446503601,
+           -1.089957043531254,
+           -1.1764387827435812,
+           -1.2575548497694395,
+           -1.3318599010415155,
+           -1.3980190340079475,
+           -1.454846419373775,
+           -1.5013406659926447,
+           -1.5367159673193875,
+           -1.5604281791978754,
+           -1.5721951015873503,
+           -1.5720103786078998,
+           -1.5601505885150775,
+           -1.5371752640045415,
+           -1.5039197594119154,
+           -1.4614810605302788,
+           -1.4111968104515098,
+           -1.3546179966100018,
+           -1.293475905765124,
+           -1.229644100945813,
+           -1.1650963036836561,
+           -1.1018611729073458,
+           -1.041975055906996,
+           -0.9874338446387877,
+           -0.9401451008080479,
+           -0.9018816148058539,
+           -0.8742375365474868,
+           -0.858588161147102,
+           -0.8560543704332986,
+           -0.8674726245016118,
+           -0.8933712683672095,
+           -0.9339537704342998,
+           -0.9890893455280767,
+           -1.0583112396213674,
+           -1.1408227704065137,
+           -1.2355110319760778,
+           -1.3409679876256595,
+           -1.455518496685718,
+           -1.5772546536905991,
+           -1.704075665212349,
+           -1.833732355081012,
+           -1.9638752757928395,
+           -2.092105315453398,
+           -2.2160256277996306,
+           -2.3332936792244396,
+           -2.441672202134161,
+           -2.5390778685342132,
+           -2.6236265508813204,
+           -2.6936741176794796,
+           -2.747851817081782,
+           -2.7850954303210234,
+           -2.804667525000021,
+           -2.8061723025201393,
+           -2.7895627102127687,
+           -2.755139672770788,
+           -2.703543484873973,
+           -2.6357375929062536,
+           -2.552985173850132,
+           -2.456819089437657,
+           -2.349005949314831,
+           -2.2315051545688664,
+           -2.106423909154793,
+           -1.9759692787480772,
+           -1.8423984421481814,
+           -1.70796831802116,
+           -1.574885758641668,
+           -1.4452594822290565,
+           -1.3210548670326823,
+           -1.2040526547691,
+           -1.095812510274106,
+           -0.9976422608467941,
+           -0.910573495826009,
+           -0.8353440480215985,
+           -0.7723877076803533,
+           -0.7218313409445046,
+           -0.683499402687444,
+           -0.6569256526873558,
+           -0.6413717087878629,
+           -0.6358519053087963,
+           -0.6391637735680837,
+           -0.6499233276594594,
+           -0.6666042258555119,
+           -0.6875797888991213,
+           -0.7111667931423928,
+           -0.735669920478127,
+           -0.7594257390896872,
+           -0.7808451093250202,
+           -0.7984529568800092,
+           -0.8109244296702216,
+           -0.8171165533377561,
+           -0.8160946207377835,
+           -0.8071526898919119,
+           -0.7898277192356251,
+           -0.7639070346032477,
+           -0.7294289950895377,
+           -0.6866769003357925,
+           -0.6361663554820612,
+           -0.5786264776284863,
+           -0.514975484939146,
+           -0.4462913525472729,
+           -0.3737783445908916,
+           -0.29873033588525666,
+           -0.22249191731641652,
+           -0.14641833400858875,
+           -0.07183533331270764,
+           -6.527898018164609e-16
+          ],
+          [
+           0,
+           0.06597372326274838,
+           0.12667711981423446,
+           0.18137031800976394,
+           0.229519197940385,
+           0.2708119651168428,
+           0.30516951713781093,
+           0.33274930838195904,
+           0.35394258723006,
+           0.3693650532381307,
+           0.3798411536598031,
+           0.3863824053906192,
+           0.3901602855437034,
+           0.39247437746648967,
+           0.3947165854097694,
+           0.3983323370297576,
+           0.40477977571764584,
+           0.4154880022643076,
+           0.43181545606838595,
+           0.4550095291432037,
+           0.4861684814241204,
+           0.5262066738729869,
+           0.5758240578546591,
+           0.6354807571111771,
+           0.7053774548793607,
+           0.7854421563311227,
+           0.87532373907791,
+           0.9743925358709369,
+           1.0817480180343246,
+           1.1962334699597288,
+           1.3164573686141627,
+           1.4408210118776783,
+           1.5675517798988616,
+           1.69474126854668,
+           1.82038740710772,
+           1.9424395668457728,
+           2.058845585599049,
+           2.1675995783405058,
+           2.266789376025309,
+           2.35464243587085,
+           2.429569095531449,
+           2.490202100809135,
+           2.5354314202609194,
+           2.564433468340087,
+           2.576693988952326,
+           2.5720240003779615,
+           2.550568366799657,
+           2.5128067371898624,
+           2.459546774779375,
+           2.3919097852948714,
+           2.311309035097694,
+           2.2194212267999487,
+           2.118151765551897,
+           2.0095945999215847,
+           1.895987553419172,
+           1.7796641730020695,
+           1.6630032066128002,
+           1.54837688082983,
+           1.4380991805844083,
+           1.3343753348356044,
+           1.2392536850305618,
+           1.1545810577477293,
+           1.0819626804623483,
+           1.0227275718826538,
+           0.9779002083923299,
+           0.9481791189586011,
+           0.9339228960563603,
+           0.9351439337289531,
+           0.9515100201511698,
+           0.9823537254523388,
+           1.0266893406374642,
+           1.0832369447080374,
+           1.1504530088725011,
+           1.2265667931288522,
+           1.3096216552162014,
+           1.3975202782328204,
+           1.4880727338369524,
+           1.5790462350149652,
+           1.6682153973992622,
+           1.7534118218378085,
+           1.832571833443875,
+           1.9037812630665931,
+           1.965316234706079,
+           2.0156790248792564,
+           2.053628184742366,
+           2.0782022597681076,
+           2.0887366013667354,
+           2.084872936061849,
+           2.066561536434849,
+           2.034056019615929,
+           1.987900979139251,
+           1.9289128300585636,
+           1.8581544110572392,
+           1.7769040368671143,
+           1.6866198259793748,
+           1.588900239186562,
+           1.4854418512668195,
+           1.3779954390361808,
+           1.2683215026253034,
+           1.1581463424386964,
+           1.0491197917818347,
+           0.9427756552479737,
+           0.8404958269781008,
+           0.7434789628277115,
+           0.6527144588739511,
+           0.5689623486898437,
+           0.49273957696590903,
+           0.4243129413053769,
+           0.36369882155524025,
+           0.3106696412194586,
+           0.26476683274319024,
+           0.2253199121088421,
+           0.19147111243029252,
+           0.16220488498282495,
+           0.1363814529058557,
+           0.11277350074826682,
+           0.09010500464228588,
+           0.0670911551432824,
+           0.042478298964892316,
+           0.015082827597657632,
+           -0.016172029943419004,
+           -0.05222249700211653,
+           -0.0938345272562857,
+           -0.14157887171550043,
+           -0.19581161056430663,
+           -0.25666068316594226,
+           -0.32401879324536953,
+           -0.39754290014899724,
+           -0.47666033534264407,
+           -0.5605814103138942,
+           -0.648318212179294,
+           -0.738709120874256,
+           -0.8304484309542394,
+           -0.9221203256020062,
+           -1.0122363338764422,
+           -1.0992753075413184,
+           -1.1817248834195726,
+           -1.2581233529642677,
+           -1.3271008438018188,
+           -1.3874187288819178,
+           -1.4380062173603538,
+           -1.4779931465508145,
+           -1.5067380846430305,
+           -1.5238509671976206,
+           -1.5292096239134352,
+           -1.5229697025314104,
+           -1.5055676602710062,
+           -1.4777166658353906,
+           -1.4403954324770787,
+           -1.3948301804652354,
+           -1.3424701010968583,
+           -1.2849568597965348,
+           -1.2240888287006941,
+           -1.161780875574545,
+           -1.1000206525121512,
+           -1.0408224216589848,
+           -0.9861795237658391,
+           -0.93801663694963,
+           -0.8981429864803584,
+           -0.868207651310098,
+           -0.849658069689751,
+           -0.8437027755634673,
+           -0.851279301146137,
+           -0.8730280614700117,
+           -0.9092728966067307,
+           -0.9600087901152494,
+           -1.0248971118465071,
+           -1.1032685536973725,
+           -1.1941337426270466,
+           -1.296201330729154,
+           -1.4079031819068826,
+           -1.5274261031414538,
+           -1.6527494096848572,
+           -1.7816874716425772,
+           -1.911936267830084,
+           -2.0411228744843775,
+           -2.1668567438150332,
+           -2.2867815822888495,
+           -2.398626622083307,
+           -2.5002560917441707,
+           -2.589715733454217,
+           -2.6652752834742626,
+           -2.7254659275824373,
+           -2.7691118624024518,
+           -2.7953552334835337,
+           -2.8036738784678215,
+           -2.793891474823011,
+           -2.7661798722617754,
+           -2.72105357571773,
+           -2.6593565310796587,
+           -2.5822415482696495,
+           -2.491142870254284,
+           -2.387742557978007,
+           -2.2739315060937,
+           -2.1517660292352128,
+           -2.023421060423004,
+           -1.8911410795782566,
+           -1.7571899392310462,
+           -1.6238007752054593,
+           -1.4931271819085605,
+           -1.3671967951099921,
+           -1.2478683607457246,
+           -1.1367932779615268,
+           -1.035382490613141,
+           -0.9447794666229363,
+           -0.8658398523271126,
+           -0.7991182230258654,
+           -0.7448621754929218,
+           -0.7030138275586587,
+           -0.6732186085198024,
+           -0.6548410465226883,
+           -0.6469870895886892,
+           -0.6485323397603211,
+           -0.658155438792062,
+           -0.6743757223294182,
+           -0.6955941605585798,
+           -0.7201365292463704,
+           -0.7462977076818211,
+           -0.7723859803654991,
+           -0.7967662277668658,
+           -0.8179009277786611,
+           -0.8343879526419861,
+           -0.8449942344322028,
+           -0.8486844833934795,
+           -0.8446442746334297,
+           -0.8322969665871225,
+           -0.8113140754708794,
+           -0.7816188995929862,
+           -0.7433833615791883,
+           -0.6970182109081722,
+           -0.6431568992411016,
+           -0.582633602589264,
+           -0.5164560133338723,
+           -0.4457736577530843,
+           -0.37184260769917926,
+           -0.29598754557735574,
+           -0.21956220754846545,
+           -0.1439092692776629,
+           -0.07032075061075932,
+           -6.364666640263568e-16
+          ],
+          [
+           0,
+           0.06387805274994085,
+           0.12217425017477022,
+           0.1742554218947384,
+           0.21970261951743478,
+           0.2583242180759695,
+           0.29016265584775447,
+           0.31549461479009755,
+           0.33482461497884275,
+           0.3488721684975212,
+           0.3585528068304303,
+           0.3649534566813023,
+           0.3693027881788047,
+           0.37293729284414,
+           0.37726396307707866,
+           0.38372053733249084,
+           0.39373434322644474,
+           0.4086808127548513,
+           0.42984275850817394,
+           0.4583714867853701,
+           0.4952507831058659,
+           0.5412647387356523,
+           0.5969702950940659,
+           0.6626752685295496,
+           0.7384224837549358,
+           0.8239804935268727,
+           0.9188411986710078,
+           1.0222245103530703,
+           1.1330900198611584,
+           1.25015546450174,
+           1.3719216059368504,
+           1.4967029737192348,
+           1.622663776024959,
+           1.7478581454392261,
+           1.8702737735157706,
+           1.9878778966090536,
+           2.09866452951446,
+           2.200701804466414,
+           2.2921782620940108,
+           2.371446958382286,
+           2.4370662971959467,
+           2.4878365704575276,
+           2.522831285929244,
+           2.5414224833937507,
+           2.543299380957609,
+           2.5284798508054074,
+           2.4973143941871094,
+           2.4504824645778864,
+           2.388981171437971,
+           2.314106580335981,
+           2.2274280038948233,
+           2.130755847694559,
+           2.0261037317564115,
+           1.9156457476898858,
+           1.801669830577518,
+           1.6865283202640782,
+           1.5725868565451884,
+           1.46217279508,
+           1.3575243446216707,
+           1.2607416110056282,
+           1.1737406896043472,
+           1.0982118766944766,
+           1.0355829731080004,
+           0.9869885330063036,
+           0.9532457695520653,
+           0.9348376710886624,
+           0.9319037100186982,
+           0.9442383460741498,
+           0.9712973404835057,
+           1.0122117121717398,
+           1.0658089860849267,
+           1.1306412114115973,
+           1.2050190680594681,
+           1.2870512371010316,
+           1.3746880884722203,
+           1.4657686399431165,
+           1.5580696676556316,
+           1.649355802087488,
+           1.7374294252305658,
+           1.8201791954424502,
+           1.8956260655144719,
+           1.9619657259717243,
+           2.0176064977830275,
+           2.061201814185744,
+           2.0916765673247575,
+           2.108246748472189,
+           2.1104319769254833,
+           2.0980606881484345,
+           2.0712679319779626,
+           2.030485912315167,
+           1.9764275762003336,
+           1.9100637281972743,
+           1.8325943014610107,
+           1.745414555933203,
+           1.6500770934151465,
+           1.5482506759198562,
+           1.44167690538229,
+           1.3321258678155352,
+           1.221351862312478,
+           1.11105032456986,
+           1.0028170162163144,
+           0.8981104862073486,
+           0.7982187206197151,
+           0.7042307846638276,
+           0.6170141285233924,
+           0.5371980801004174,
+           0.4651638866660131,
+           0.4010414978748478,
+           0.3447131088802144,
+           0.29582330877024676,
+           0.2537955106053148,
+           0.2178541792206917,
+           0.18705222568890487,
+           0.16030280660577864,
+           0.13641465544604175,
+           0.11412998489957424,
+           0.0921639355482531,
+           0.06924450905059479,
+           0.04415191407724852,
+           0.015756270807912556,
+           -0.016947335609743208,
+           -0.05480739177555624,
+           -0.09848892752803656,
+           -0.1484516506120303,
+           -0.20493383801035234,
+           -0.26794242722468914,
+           -0.33724958910966973,
+           -0.4123958948034713,
+           -0.4927000171459966,
+           -0.5772747360990597,
+           -0.6650488524203108,
+           -0.7547944583934859,
+           -0.8451588727386199,
+           -0.9347004225303788,
+           -1.0219271512207009,
+           -1.1053374513597145,
+           -1.1834615654219696,
+           -1.2549028697251952,
+           -1.318377855557734,
+           -1.3727537483989465,
+           -1.4170827599213476,
+           -1.4506320470214737,
+           -1.4729085555076777,
+           -1.483678050745809,
+           -1.4829777804582351,
+           -1.4711223724556954,
+           -1.4487027384481121,
+           -1.4165779300449124,
+           -1.3758600702585169,
+           -1.327892658842608,
+           -1.2742227182490868,
+           -1.2165674046490826,
+           -1.1567758513659805,
+           -1.0967871366045863,
+           -1.0385853703686927,
+           -0.9841529743080919,
+           -0.9354232808855465,
+           -0.894233603312116,
+           -0.8622799244522666,
+           -0.8410743213362067,
+           -0.8319061827237163,
+           -0.8358081917147445,
+           -0.8535279357221882,
+           -0.8855058748393055,
+           -0.9318602499145462,
+           -0.9923793471172606,
+           -1.0665213604380366,
+           -1.1534219116896243,
+           -1.2519091035999168,
+           -1.3605258000164508,
+           -1.477558652520878,
+           -1.6010732291668837,
+           -1.7289544526250626,
+           -1.858951425394106,
+           -1.9887256121131132,
+           -2.1159012660434287,
+           -2.2381169305343995,
+           -2.3530768181498605,
+           -2.4586008708238007,
+           -2.552672333944864,
+           -2.6334817349405255,
+           -2.6994662413571726,
+           -2.7493434825681633,
+           -2.782139050440174,
+           -2.797207044360881,
+           -2.7942431913268604,
+           -2.7732902482880317,
+           -2.7347355773475432,
+           -2.679300970261237,
+           -2.608024982447624,
+           -2.522238213940902,
+           -2.423532141091951,
+           -2.3137222543113984,
+           -2.1948063900885106,
+           -2.0689192567020416,
+           -1.9382842397935673,
+           -1.8051636342318844,
+           -1.671808481042364,
+           -1.5404091918793243,
+           -1.4130481185576411,
+           -1.2916551722112644,
+           -1.1779675170770223,
+           -1.073494259730163,
+           -0.9794869284432558,
+           -0.896916392357427,
+           -0.8264567099581891,
+           -0.7684762249178294,
+           -0.7230360489519708,
+           -0.6898958903523152,
+           -0.6685270077678418,
+           -0.6581318960224725,
+           -0.6576701485232714,
+           -0.6658897931030134,
+           -0.6813632685596415,
+           -0.702527100850049,
+           -0.727724253479563,
+           -0.7552480681148639,
+           -0.7833866802027473,
+           -0.8104667910846491,
+           -0.8348957027448907,
+           -0.855200573211586,
+           -0.8700639283576752,
+           -0.8783545674000204,
+           -0.8791531221494838,
+           -0.8717716708846945,
+           -0.8557669630202629,
+           -0.8309469765762096,
+           -0.7973707026319068,
+           -0.7553412251164214,
+           -0.7053923360573651,
+           -0.648269091458071,
+           -0.5849028671504817,
+           -0.5163816134088497,
+           -0.4439161283133607,
+           -0.36880326979159417,
+           -0.2923871024459922,
+           -0.2160190258035719,
+           -0.14101795425385635,
+           -0.06863161510404266,
+           -6.186988061787385e-16
+          ],
+          [
+           0,
+           0.061667331324419525,
+           0.11749209345274958,
+           0.16695200382500683,
+           0.2097455437214804,
+           0.24580150683657256,
+           0.2752820880051335,
+           0.29857941231706314,
+           0.31630557619568367,
+           0.32927644174514464,
+           0.33848958948217395,
+           0.3450969882943389,
+           0.3503730811976873,
+           0.3556791076371843,
+           0.3624245845580267,
+           0.3720269466660644,
+           0.3858703991652502,
+           0.4052650624173892,
+           0.43140748669196805,
+           0.46534358642721396,
+           0.507934987863238,
+           0.5598297028637196,
+           0.6214379371853566,
+           0.6929137159486776,
+           0.7741428657040379,
+           0.8647377348203051,
+           0.9640388658636742,
+           1.0711236593613653,
+           1.184821892204877,
+           1.3037377803416301,
+           1.4262781086801801,
+           1.5506857954791944,
+           1.6750781178239473,
+           1.7974887026722963,
+           1.9159122874773988,
+           2.028351178138757,
+           2.1328622819723684,
+           2.227603570855274,
+           2.3108788353401724,
+           2.3811796243059486,
+           2.437223325866973,
+           2.477986432385669,
+           2.502732143451826,
+           2.5110315929462597,
+           2.502778136603875,
+           2.4781943011885654,
+           2.4378311714841616,
+           2.3825601725230197,
+           2.3135573873893387,
+           2.232280731071501,
+           2.140440473781095,
+           2.039963768660746,
+           1.9329539848981716,
+           1.8216457743530796,
+           1.7083569047518132,
+           1.5954379727169021,
+           1.485221163384046,
+           1.3799692487799036,
+           1.281826013839914,
+           1.1927692669885737,
+           1.1145675323400952,
+           1.048741434243652,
+           0.9965306741819216,
+           0.958867367619135,
+           0.9363563575018609,
+           0.9292629554109568,
+           0.937508384877797,
+           0.9606730184060712,
+           0.998007314733775,
+           1.0484501803279243,
+           1.1106543034637364,
+           1.1830178447652955,
+           1.2637217187641738,
+           1.3507715704795014,
+           1.4420434423876372,
+           1.5353320430413129,
+           1.628400471022147,
+           1.719030218218411,
+           1.805070275278002,
+           1.8844841894587492,
+           1.9553939802486733,
+           2.0161198996405103,
+           2.0652151297549977,
+           2.10149463795984,
+           2.124057555541637,
+           2.132302606724318,
+           2.12593628639918,
+           2.104973663089429,
+           2.0697318640131552,
+           2.02081647718582,
+           1.9591012769348075,
+           1.8857018397768364,
+           1.8019437634041906,
+           1.7093263289830085,
+           1.6094825529936598,
+           1.5041366568855674,
+           1.3950600389233947,
+           1.2840268614637689,
+           1.172770367896896,
+           1.0629410166851283,
+           0.9560674660923448,
+           0.8535213637566375,
+           0.7564867922825819,
+           0.6659350981689441,
+           0.5826056898093374,
+           0.5069932346101464,
+           0.43934151940995947,
+           0.37964406655319727,
+           0.32765142450457657,
+           0.2828848811605548,
+           0.24465618431365377,
+           0.21209270116651047,
+           0.1841673112003239,
+           0.15973220752144104,
+           0.13755568401751378,
+           0.11636091168733659,
+           0.09486565920084226,
+           0.07182189128517184,
+           0.046054184430232514,
+           0.016495932484568807,
+           -0.017777625892623893,
+           -0.05752044176955409,
+           -0.10329152948397505,
+           -0.15543632944551633,
+           -0.21407406699106332,
+           -0.2790914575587643,
+           -0.3501429428258574,
+           -0.42665747194317966,
+           -0.5078516709209605,
+           -0.5927490759185775,
+           -0.6802049469155528,
+           -0.7689360310428858,
+           -0.8575545134832967,
+           -0.944605281661506,
+           -1.0286055383173922,
+           -1.1080857333106382,
+           -1.1816307443594054,
+           -1.247920224428395,
+           -1.3057670485330737,
+           -1.3541528350052194,
+           -1.3922595847749226,
+           -1.419496575310202,
+           -1.4355217612424809,
+           -1.44025706855641,
+           -1.4338971202044044,
+           -1.416911094378205,
+           -1.390037588371953,
+           -1.3542725367274768,
+           -1.3108504077752934,
+           -1.261219073386077,
+           -1.2070089084462092,
+           -1.1499968252017798,
+           -1.0920660794282078,
+           -1.0351627970378539,
+           -0.9812502583893459,
+           -0.9322620409289053,
+           -0.8900551572170702,
+           -0.8563643338805231,
+           -0.8327585572745295,
+           -0.8206009640426736,
+           -0.8210130804028597,
+           -0.8348443146220257,
+           -0.8626474851386013,
+           -0.9046610250875083,
+           -0.9607983460055897,
+           -1.030644673081942,
+           -1.1134614856178588,
+           -1.2081985137362303,
+           -1.313513060296478,
+           -1.4277962398877158,
+           -1.549205559033901,
+           -1.6757031074705402,
+           -1.8050984933383007,
+           -1.9350955387613573,
+           -2.0633416594106198,
+           -2.187478784595288,
+           -2.3051946348488848,
+           -2.4142731628759218,
+           -2.5126429814023488,
+           -2.598422647522151,
+           -2.6699617464538097,
+           -2.7258768164454414,
+           -2.7650812785028616,
+           -2.78680867670065,
+           -2.7906286936196243,
+           -2.7764555770726913,
+           -2.7445487945596807,
+           -2.6955059164438344,
+           -2.630247913179027,
+           -2.549997231555338,
+           -2.4562491855075166,
+           -2.3507373544065415,
+           -2.235393822116754,
+           -2.1123052100577695,
+           -1.9836655541725958,
+           -1.8517271467571537,
+           -1.7187505078679761,
+           -1.586954666482027,
+           -1.458468918419888,
+           -1.3352871866477072,
+           -1.2192260410246494,
+           -1.1118873406058691,
+           -1.0146263446138455,
+           -0.9285260010822975,
+           -0.8543779683755583,
+           -0.7926707581157416,
+           -0.7435852126428618,
+           -0.7069973503285498,
+           -0.682488432301212,
+           -0.6693619288475814,
+           -0.6666668972403644,
+           -0.6732271290857049,
+           -0.687675288241182,
+           -0.7084911432591021,
+           -0.734042903992843,
+           -0.7626306027266383,
+           -0.7925304175851748,
+           -0.8220388210163744,
+           -0.8495154490970712,
+           -0.8734236278697552,
+           -0.8923675597788272,
+           -0.9051252647802507,
+           -0.9106764844826973,
+           -0.908224890823075,
+           -0.8972140898896794,
+           -0.8773370727946914,
+           -0.8485389348795841,
+           -0.8110128577330447,
+           -0.7651895211435664,
+           -0.7117202798525161,
+           -0.6514545986016795,
+           -0.585412384501722,
+           -0.5147519845380504,
+           -0.4407347248573438,
+           -0.3646869546261873,
+           -0.28796061858074506,
+           -0.21189341737723386,
+           -0.1377696226555125,
+           -0.06678259417549719,
+           -5.996396084766768e-16
+          ],
+          [
+           0,
+           0.05936038531830097,
+           0.11267019497508252,
+           0.15952118374138133,
+           0.19973044215790675,
+           0.23334634441410443,
+           0.2606479949017704,
+           0.2821381715899171,
+           0.29852993441522124,
+           0.31072723283719234,
+           0.3198000043529358,
+           0.32695440109321255,
+           0.33349891092667144,
+           0.3408072494799164,
+           0.3502789873178199,
+           0.36329893995558293,
+           0.38119638573713327,
+           0.4052051869123596,
+           0.4364258721561195,
+           0.47579069466024476,
+           0.5240326098403876,
+           0.5816590223308484,
+           0.648931035602879,
+           0.7258488021009609,
+           0.8121434205968936,
+           0.9072756642641664,
+           1.0104416518340125,
+           1.12058539937603,
+           1.2364180161175895,
+           1.3564431386372588,
+           1.4789880379814935,
+           1.6022396877823475,
+           1.724284951995505,
+           1.843153941716399,
+           1.9568655044535705,
+           2.0634737484617984,
+           2.1611144708581485,
+           2.2480503521935207,
+           2.322713802173816,
+           2.3837463908666856,
+           2.4300338758551843,
+           2.4607359366138293,
+           2.475309850476613,
+           2.47352748697593,
+           2.455485155608546,
+           2.4216060123840286,
+           2.3726349086826106,
+           2.3096257476422664,
+           2.2339215940631028,
+           2.147127959230666,
+           2.0510798478128516,
+           1.9478033060029105,
+           1.839472344620735,
+           1.7283622246273576,
+           1.6168001826413239,
+           1.5071147383341175,
+           1.4015847624207254,
+           1.3023894924181196,
+           1.2115606631805933,
+           1.1309378709002993,
+           1.062128213936963,
+           1.0064711533280817,
+           0.9650094125627106,
+           0.9384665931686647,
+           0.927232023339597,
+           0.9313531850885154,
+           0.9505358854352756,
+           0.9841521532954809,
+           1.0312556605083198,
+           1.0906042872755282,
+           1.1606892835108562,
+           1.2397703223143257,
+           1.325915603749834,
+           1.4170460496542863,
+           1.5109825361696554,
+           1.6054950423175682,
+           1.698352551848888,
+           1.7873725327464376,
+           1.870468834392127,
+           1.9456968860849801,
+           2.0112951511809047,
+           2.0657218868263785,
+           2.107686377669787,
+           2.136173950095578,
+           2.150464227996207,
+           2.1501422580393754,
+           2.13510230766736,
+           2.1055443183488505,
+           2.0619631754691117,
+           2.005131130289011,
+           1.9360738743535477,
+           1.8560409185463964,
+           1.7664710639630186,
+           1.6689538666307044,
+           1.5651880900649762,
+           1.4569382065178083,
+           1.34599004797102,
+           1.2341067205512473,
+           1.1229858808711664,
+           1.0142194303070802,
+           0.9092566145566914,
+           0.80937142278279,
+           0.715635065642673,
+           0.6288941774759176,
+           0.5497552382896985,
+           0.4785755497397261,
+           0.41546093014154156,
+           0.3602701209326628,
+           0.3126257252909041,
+           0.2719313331172075,
+           0.2373943294946028,
+           0.20805373997715798,
+           0.18281233924283172,
+           0.16047214293008555,
+           0.13977231852909147,
+           0.11942849209810928,
+           0.09817239478092814,
+           0.07479078740572012,
+           0.048162622960463745,
+           0.017293454891278023,
+           -0.01865382728656648,
+           -0.06033275652255869,
+           -0.10819224428013022,
+           -0.16246130135337639,
+           -0.22313994001250242,
+           -0.28999651260019355,
+           -0.3625715736104507,
+           -0.44018818180429237,
+           -0.5219683903797474,
+           -0.6068555108968342,
+           -0.6936415846878193,
+           -0.78099935772723,
+           -0.8675179349088952,
+           -0.9517411904493686,
+           -1.0322079352592377,
+           -1.1074927915622181,
+           -1.1762467011286015,
+           -1.2372359968883986,
+           -1.2893789983790285,
+           -1.3317791487554724,
+           -1.3637537935719293,
+           -1.3848578072225717,
+           -1.3949013992089843,
+           -1.3939615761659667,
+           -1.382386893264274,
+           -1.3607952963012735,
+           -1.3300650293128822,
+           -1.2913187575623308,
+           -1.2459012279056967,
+           -1.1953509534863556,
+           -1.1413665633243186,
+           -1.0857685957706875,
+           -1.0304576344889114,
+           -0.9773697835597918,
+           -0.9284305519746581,
+           -0.8855082652687227,
+           -0.8503681420857986,
+           -0.824628165467864,
+           -0.8097178427320697,
+           -0.8068408847308962,
+           -0.8169427465581244,
+           -0.8406838594725138,
+           -0.8784192506574579,
+           -0.9301850966343946,
+           -0.9956925913582152,
+           -1.074329335254486,
+           -1.1651682709745736,
+           -1.2669840098575185,
+           -1.378276214449032,
+           -1.4972995313190205,
+           -1.6220994090438063,
+           -1.750552992497574,
+           -1.880414160072376,
+           -2.0093616681916417,
+           -2.135049290030463,
+           -2.2551567846340532,
+           -2.3674405099049323,
+           -2.46978249879834,
+           -2.5602368524095276,
+           -2.6370723656467008,
+           -2.6988103893691537,
+           -2.744257045102149,
+           -2.7725290419976174,
+           -2.783072497350225,
+           -2.7756743280165233,
+           -2.7504659564822664,
+           -2.707919257789121,
+           -2.648834857628254,
+           -2.5743230731582067,
+           -2.485777962103212,
+           -2.3848451082113424,
+           -2.2733839182586295,
+           -2.1534253339163127,
+           -2.0271259678617395,
+           -1.8967197549615284,
+           -1.7644682642470713,
+           -1.632610844449684,
+           -1.5033157744619017,
+           -1.3786335603390019,
+           -1.260453463142141,
+           -1.1504642585187907,
+           -1.0501201215233804,
+           -0.9606124014932917,
+           -0.8828479050236816,
+           -0.817434143878427,
+           -0.7646718330326236,
+           -0.7245547462115914,
+           -0.6967768566633753,
+           -0.6807465139024853,
+           -0.67560723714396,
+           -0.6802645472780909,
+           -0.6934181154022065,
+           -0.7135983806304266,
+           -0.739206686182104,
+           -0.7685579030997601,
+           -0.7999244572603165,
+           -0.8315806488626739,
+           -0.8618461548655177,
+           -0.889127633784813,
+           -0.9119574080266207,
+           -0.9290282800477269,
+           -0.939223642994773,
+           -0.9416421713893774,
+           -0.9356165197101649,
+           -0.9207256127555712,
+           -0.8968002774985988,
+           -0.8639221375752106,
+           -0.8224158642575445,
+           -0.772835047403245,
+           -0.7159421121794394,
+           -0.6526828582606136,
+           -0.5841563339137121,
+           -0.5115808745169641,
+           -0.43625723068849553,
+           -0.3595297829479094,
+           -0.28274688592305475,
+           -0.20722140441620412,
+           -0.13419249570529662,
+           -0.06478965750891787,
+           -5.79452587754639e-16
+          ],
+          [
+           0,
+           0.056976707100053196,
+           0.10774892120798521,
+           0.15202452615257733,
+           0.18973932086384462,
+           0.22105935168650892,
+           0.24637675847872986,
+           0.2662992295819439,
+           0.2816333280470239,
+           0.2933621122860964,
+           0.30261762450089097,
+           0.3106489559944565,
+           0.31878671634068484,
+           0.3284048303498663,
+           0.3408806603360942,
+           0.35755449945729945,
+           0.3796895035887767,
+           0.40843312370054974,
+           0.4447810681144459,
+           0.48954476507605116,
+           0.543323212210405,
+           0.6064799926869937,
+           0.679126110925549,
+           0.7611091565682004,
+           0.852009147799298,
+           0.9511412378316568,
+           1.0575652956655643,
+           1.1701021983785067,
+           1.2873565015704445,
+           1.4077449914525315,
+           1.5295304705293877,
+           1.6508599927098884,
+           1.7698066464364313,
+           1.884413889033769,
+           1.9927413643944725,
+           2.092911091189463,
+           2.1831528912235916,
+           2.2618479378766088,
+           2.327569342617022,
+           2.379118762500895,
+           2.4155581018526133,
+           2.436235494822225,
+           2.440804889497799,
+           2.4292387054830296,
+           2.4018332016592967,
+           2.3592063652246575,
+           2.302288312783163,
+           2.2323043748515463,
+           2.150751212231241,
+           2.0593664819157382,
+           1.9600927274063547,
+           1.8550363096230764,
+           1.7464223165352852,
+           1.6365464891854544,
+           1.527725276468735,
+           1.4222451790012614,
+           1.3223125624522913,
+           1.2300051123055753,
+           1.1472260653265571,
+           1.0756622889098801,
+           1.0167471895043647,
+           0.9716293176323831,
+           0.9411474023913,
+           0.9258123960135294,
+           0.9257969427695892,
+           0.940932510268221,
+           0.9707142393251527,
+           1.014313385460818,
+           1.070597045199368,
+           1.1381546880479043,
+           1.2153308545189343,
+           1.3002632357125243,
+           1.3909252243025254,
+           1.4851719233060237,
+           1.5807885202421927,
+           1.6755398820833722,
+           1.7672202019915728,
+           1.853701532758199,
+           1.9329800739686769,
+           2.0032191393501257,
+           2.0627878160129502,
+           2.110294436218159,
+           2.144614112165027,
+           2.164909731862409,
+           2.1706459757553533,
+           2.1615960854224587,
+           2.137841293094696,
+           2.0997629995955,
+           2.048027964161216,
+           1.983566938150243,
+           1.9075473317581544,
+           1.8213406446863383,
+           1.7264855148115368,
+           1.6246473402928145,
+           1.5175755077951818,
+           1.407059310774162,
+           1.2948836658700467,
+           1.1827857318991188,
+           1.072413504884681,
+           0.9652874049093163,
+           0.8627657878183002,
+           0.7660152091102255,
+           0.6759861414303152,
+           0.5933947041484382,
+           0.5187108071894115,
+           0.45215294554695473,
+           0.39368970994088076,
+           0.34304790717955885,
+           0.2997270152911735,
+           0.2630195376197683,
+           0.23203667087946828,
+           0.2057385683571543,
+           0.182968364393116,
+           0.16248903281832708,
+           0.14302208250689097,
+           0.123287049329668,
+           0.1020407266402155,
+           0.07811508638384188,
+           0.05045287970925016,
+           0.018139968619153617,
+           -0.019566472890051836,
+           -0.06321464080044648,
+           -0.11314029054895909,
+           -0.16945491419253317,
+           -0.23204022890263773,
+           -0.3005491355233003,
+           -0.37441313684316774,
+           -0.45285603626262017,
+           -0.5349135729718655,
+           -0.6194584937764387,
+           -0.7052304182804757,
+           -0.7908697269196627,
+           -0.874954593574375,
+           -0.9560401989518629,
+           -1.0326990998105965,
+           -1.103561694004745,
+           -1.1673557131939716,
+           -1.2229436941588991,
+           -1.2693574255673035,
+           -1.305828438657727,
+           -1.3318137059059312,
+           -1.347015828970655,
+           -1.3513971331870165,
+           -1.345187237221986,
+           -1.32888382946804,
+           -1.3032465532717321,
+           -1.2692840769188285,
+           -1.2282345970810415,
+           -1.1815401918412929,
+           -1.1308155972501375,
+           -1.0778121256495223,
+           -1.0243775710847074,
+           -0.9724130537839528,
+           -0.9238278391926206,
+           -0.8804932252471166,
+           -0.8441966229321829,
+           -0.8165969588127103,
+           -0.79918250398473,
+           -0.7932321822564379,
+           -0.7997813325359379,
+           -0.8195927982057674,
+           -0.853134092149767,
+           -0.9005612430569307,
+           -0.9617097701247853,
+           -1.0360930631752008,
+           -1.1229082676259452,
+           -1.2210495930710223,
+           -1.3291287848353779,
+           -1.445502324184932,
+           -1.568304759156736,
+           -1.6954874182546478,
+           -1.824861627222712,
+           -1.9541454380216312,
+           -2.0810127917438046,
+           -2.203143975680312,
+           -2.3182762006395055,
+           -2.4242531187791196,
+           -2.5190721248292327,
+           -2.6009283341305847,
+           -2.6682542081863123,
+           -2.7197539005641014,
+           -2.7544315205193484,
+           -2.771612655618593,
+           -2.770958654431036,
+           -2.7524733421411685,
+           -2.7165020215395477,
+           -2.6637227949037965,
+           -2.59513042433638,
+           -2.512013124754387,
+           -2.4159228506389705,
+           -2.3086397907987584,
+           -2.192131921072036,
+           -2.0685105798084664,
+           -1.9399831223650843,
+           -1.8088037765348184,
+           -1.6772238592439688,
+           -1.5474425251226587,
+           -1.4215591994757595,
+           -1.3015288022641192,
+           -1.1891207971319122,
+           -1.0858830021239367,
+           -0.9931109789709759,
+           -0.9118236786730406,
+           -0.8427458660409236,
+           -0.7862976787131244,
+           -0.7425915010850581,
+           -0.7114361548946361,
+           -0.6923482303069716,
+           -0.6845702086067558,
+           -0.687094864278103,
+           -0.6986952843249188,
+           -0.7179597098165682,
+           -0.7433302920597105,
+           -0.7731447662139019,
+           -0.8056799807260252,
+           -0.839196183168479,
+           -0.8719809527748238,
+           -0.9023916873360068,
+           -0.9288955966240399,
+           -0.9501062249476194,
+           -0.9648156199729029,
+           -0.9720213811225178,
+           -0.9709479557233993,
+           -0.9610617011749917,
+           -0.9420793929465832,
+           -0.9139700271005193,
+           -0.8769499380151318,
+           -0.8314714227170813,
+           -0.7782052284350139,
+           -0.7180174155098011,
+           -0.6519412497440679,
+           -0.581144903095907,
+           -0.5068958462035664,
+           -0.43052289796710963,
+           -0.35337695428452626,
+           -0.27679144864584915,
+           -0.20204360089349938,
+           -0.13031748700477594,
+           -0.06266991286827321,
+           -5.58309738979578e-16
+          ],
+          [
+           0,
+           0.05453626092757085,
+           0.10276906190569345,
+           0.14452343946316942,
+           0.17985292821744714,
+           0.20903829556106054,
+           0.23257986114071644,
+           0.2511835913159973,
+           0.26574132191871247,
+           0.2773056169120258,
+           0.28705991204617803,
+           0.29628471771978687,
+           0.3063207607870083,
+           0.31853002829608146,
+           0.3342557349570016,
+           0.35478226898071885,
+           0.3812961769261749,
+           0.41484922712549704,
+           0.45632454360249447,
+           0.5064067292947488,
+           0.5655568006155363,
+           0.6339926373261628,
+           0.7116755152480343,
+           0.7983031379090962,
+           0.8933094205555071,
+           0.9958711101197362,
+           1.1049211519616806,
+           1.2191685428133623,
+           1.3371242436582464,
+           1.4571325704288747,
+           1.5774073383401233,
+           1.6960719109843814,
+           1.8112022011686078,
+           1.9208715895370532,
+           2.0231966713911276,
+           2.1163827132594353,
+           2.1987676994943364,
+           2.2688638756018635,
+           2.3253957485878374,
+           2.3673335840889695,
+           2.3939215435736574,
+           2.4046997299643516,
+           2.3995195536348914,
+           2.37855198939095,
+           2.3422884648897107,
+           2.2915342978524724,
+           2.2273947790454867,
+           2.1512541759496333,
+           2.0647481039413194,
+           1.969729873439993,
+           1.868231568861823,
+           1.7624207447193256,
+           1.6545537326216628,
+           1.5469266375725668,
+           1.441825160725205,
+           1.3414744171611404,
+           1.2479899205089346,
+           1.163330881191473,
+           1.089256912367448,
+           1.027289158468361,
+           0.9786767575332332,
+           0.9443694228159676,
+           0.9249967844325379,
+           0.9208549716398174,
+           0.9319007445870652,
+           0.9577533052304538,
+           0.9977037349069177,
+           1.0507318252560098,
+           1.1155298941520333,
+           1.1905330133146736,
+           1.273954923308008,
+           1.363828778372182,
+           1.458051751180042,
+           1.5544324388785766,
+           1.6507399487865821,
+           1.744753506366754,
+           1.8343114203944388,
+           1.9173582607389827,
+           1.9919891522981796,
+           2.0564901631451464,
+           2.1093738639775133,
+           2.1494092570194883,
+           2.1756454125990663,
+           2.187428307224664,
+           2.1844105242608545,
+           2.166553653115288,
+           2.1341234008840817,
+           2.087677607276436,
+           2.0280475250040593,
+           1.956312889475771,
+           1.8737714496298292,
+           1.7819037624601197,
+           1.6823341640766296,
+           1.576788917328031,
+           1.4670525980252642,
+           1.3549238171896176,
+           1.2421713847201596,
+           1.1304920003298675,
+           1.0214705111172915,
+           0.9165437029696715,
+           0.8169684970194717,
+           0.7237953050728094,
+           0.6378471622956037,
+           0.5597051049321959,
+           0.4897000992567097,
+           0.4279116594034153,
+           0.37417312043874756,
+           0.3280833633347487,
+           0.2890246246444448,
+           0.25618586977275254,
+           0.2285910686347849,
+           0.20513158969692669,
+           0.18460182596565414,
+           0.1657370869699411,
+           0.1472527361414946,
+           0.12788352457178787,
+           0.10642207059409921,
+           0.081755460003466,
+           0.052898993311975145,
+           0.019026182905880384,
+           -0.020505797636254958,
+           -0.0661358900260422,
+           -0.11808469439436829,
+           -0.17634616894666624,
+           -0.24068571504116304,
+           -0.31064470967467944,
+           -0.3855513787555157,
+           -0.46453773852564695,
+           -0.5465621732817683,
+           -0.6304370691840748,
+           -0.7148607902099052,
+           -0.7984531666172281,
+           -0.879793571590169,
+           -0.9574605904791135,
+           -1.0300722410677987,
+           -1.0963256838122484,
+           -1.1550353685490677,
+           -1.2051685986326055,
+           -1.245877554024185,
+           -1.2765269000574397,
+           -1.2967162163564148,
+           -1.3062966080324212,
+           -1.305381005672687,
+           -1.2943478181744477,
+           -1.2738377692510243,
+           -1.2447439202818753,
+           -1.2081950548006835,
+           -1.1655327689903785,
+           -1.1182827738361034,
+           -1.068121064017026,
+           -1.0168357424218208,
+           -0.9662854039582955,
+           -0.9183550751683168,
+           -0.8749107746678383,
+           -0.8377538018208425,
+           -0.8085758761828693,
+           -0.7889162376460955,
+           -0.7801217771025913,
+           -0.7833112007163998,
+           -0.7993441391211727,
+           -0.828795998224193,
+           -0.871939213555962,
+           -0.928731418516148,
+           -0.998810872113551,
+           -1.0814993178938719,
+           -1.1758122669423172,
+           -1.2804765185149483,
+           -1.3939545563902083,
+           -1.5144752917503987,
+           -1.6400704684168026,
+           -1.7686159073914893,
+           -1.8978766483323402,
+           -2.02555494875886,
+           -2.1493400298601673,
+           -2.2669584125488247,
+           -2.3762236700193706,
+           -2.475084433989106,
+           -2.561669530789826,
+           -2.6343291896224166,
+           -2.691671356995719,
+           -2.7325922664339166,
+           -2.756300548166918,
+           -2.762334316425675,
+           -2.7505708384347365,
+           -2.721228565181747,
+           -2.6748614852684094,
+           -2.612345945203258,
+           -2.5348602579572863,
+           -2.443857592132888,
+           -2.341032792554452,
+           -2.228283925633817,
+           -2.107669466045359,
+           -1.981362142091862,
+           -1.8516005332307086,
+           -1.7206395627466318,
+           -1.5907010503426313,
+           -1.463925482995906,
+           -1.3423261280044,
+           -1.2277465506328709,
+           -1.1218225117193568,
+           -1.0259491102127967,
+           -0.9412539046387911,
+           -0.8685765991937332,
+           -0.8084557182276805,
+           -0.7611225213024424,
+           -0.7265022340420796,
+           -0.7042224919911735,
+           -0.6936287200409352,
+           -0.6938060029620973,
+           -0.7036068472861581,
+           -0.7216840949937431,
+           -0.7465281285995942,
+           -0.7765074081910837,
+           -0.809911306156849,
+           -0.8449941565044653,
+           -0.8800194139328202,
+           -0.9133028236423285,
+           -0.9432535359955483,
+           -0.9684121596648435,
+           -0.987484831250278,
+           -0.9993724863340258,
+           -1.0031946438110548,
+           -0.9983071588645438,
+           -0.984313556493614,
+           -0.9610697230889349,
+           -0.928681904008539,
+           -0.8874981261380742,
+           -0.8380933317269015,
+           -0.7812486691746788,
+           -0.7179255339095425,
+           -0.6492350843602744,
+           -0.5764040709905933,
+           -0.5007379076220287,
+           -0.42358198155992655,
+           -0.3462822406973771,
+           -0.27014611079277956,
+           -0.19640478415747906,
+           -0.12617788238916325,
+           -0.06044143155310813,
+           -5.363898026253221e-16
+          ],
+          [
+           0,
+           0.05205928536736493,
+           0.09777143066292875,
+           0.13707858084900412,
+           0.17014998068900433,
+           0.19737716208639763,
+           0.21936284190886415,
+           0.23690381290666068,
+           0.25096826793802995,
+           0.26266814422364826,
+           0.2732272060372154,
+           0.2839456977419146,
+           0.29616249149939433,
+           0.311215722934263,
+           0.33040295174606704,
+           0.3549419015689306,
+           0.3859328237957549,
+           0.4243234937940009,
+           0.4708777858000554,
+           0.5261486862962722,
+           0.5904564969700373,
+           0.6638728501100413,
+           0.7462110146887894,
+           0.8370228140058367,
+           0.9356023095437267,
+           1.040996234768132,
+           1.152020991261169,
+           1.2672858521079975,
+           1.3852218580696591,
+           1.5041157447853009,
+           1.622148107777022,
+           1.7374348997173257,
+           1.848071264129292,
+           1.9521766437485166,
+           2.0479400619080774,
+           2.1336644625941394,
+           2.2078090096686624,
+           2.2690282878925063,
+           2.3162074168549673,
+           2.3484921821175266,
+           2.365313403587624,
+           2.3664048965679423,
+           2.351814532799863,
+           2.321908073445139,
+           2.2773656193136493,
+           2.2191707015103357,
+           2.148592213684518,
+           2.0671595608522773,
+           1.9766315650555568,
+           1.8789598208508498,
+           1.7762473300183763,
+           1.6707033615785454,
+           1.5645955773041544,
+           1.4602005320834737,
+           1.3597537009895562,
+           1.265400199665568,
+           1.179147351245148,
+           1.1028202117806916,
+           1.0380210980242763,
+           0.9860940680281434,
+           0.9480951886564077,
+           0.924769287543385,
+           0.9165337336082953,
+           0.9234696236667355,
+           0.9453205770140747,
+           0.981499159365451,
+           1.0311007766097549,
+           1.0929247018690746,
+           1.1655017306503508,
+           1.2471278025282666,
+           1.3359027875986125,
+           1.4297735152827706,
+           1.5265800248584074,
+           1.624103943698545,
+           1.7201178523700724,
+           1.8124344765697828,
+           1.8989545547783582,
+           1.977712267218083,
+           2.046917175254983,
+           2.1049917091789343,
+           2.1506033540976963,
+           2.182690815702557,
+           2.2004835966219387,
+           2.203514576282091,
+           2.191625358628695,
+           2.164964328498558,
+           2.1239775345200855,
+           2.06939268981153,
+           2.0021967471839046,
+           1.923607658993298,
+           1.8350410694825743,
+           1.7380728060601753,
+           1.6343981326184982,
+           1.5257888003808147,
+           1.41404897817481,
+           1.3009711634018424,
+           1.188293166915969,
+           1.0776572298400822,
+           0.9705722689957837,
+           0.8683801617249474,
+           0.7722268726581073,
+           0.6830390972120581,
+           0.6015069525325565,
+           0.5280730898929169,
+           0.4629284371787512,
+           0.40601461020513785,
+           0.35703286150111724,
+           0.31545926913140854,
+           0.2805657102712569,
+           0.25144601855880044,
+           0.2270465943606107,
+           0.20620062623796168,
+           0.1876649928494095,
+           0.17015884947370377,
+           0.15240286388443117,
+           0.1331580534074163,
+           0.11126318892849638,
+           0.08566977200211692,
+           0.05547365698461437,
+           0.019942479585926622,
+           -0.021461835889827828,
+           -0.0690660888885032,
+           -0.12297478806785261,
+           -0.18306540706381252,
+           -0.2489900437662339,
+           -0.3201834488558045,
+           -0.39587722267984804,
+           -0.47511981788260915,
+           -0.556801832663487,
+           -0.6396859399945216,
+           -0.7224406751415717,
+           -0.8036772005425219,
+           -0.8819880861480689,
+           -0.9559870868135916,
+           -1.0243488677189156,
+           -1.0858476249114226,
+           -1.139393571070128,
+           -1.1840663059520178,
+           -1.219144165521558,
+           -1.2441287416600166,
+           -1.2587638831940453,
+           -1.2630486258336413,
+           -1.257243650072165,
+           -1.2418710284068362,
+           -1.2177071923390845,
+           -1.1857692212844086,
+           -1.147294725461424,
+           -1.1037157587748254,
+           -1.0566273515317441,
+           -1.0077513926547517,
+           -0.9588967133363814,
+           -0.9119163257082223,
+           -0.8686628484679966,
+           -0.8309432044892312,
+           -0.8004737018229726,
+           -0.7788366084424759,
+           -0.7674393025125241,
+           -0.7674770245003152,
+           -0.7799001763677736,
+           -0.8053870083165288,
+           -0.8443224076079836,
+           -0.8967833598925453,
+           -0.9625314947497203,
+           -1.0410129576288512,
+           -1.1313656742268543,
+           -1.2324338948545863,
+           -1.3427897299030604,
+           -1.4607612174573321,
+           -1.5844663046036704,
+           -1.7118519789644355,
+           -1.8407376600556549,
+           -1.9688618543357885,
+           -2.0939309959249535,
+           -2.21366933896498,
+           -2.3258687388709784,
+           -2.428437159037491,
+           -2.5194447669606905,
+           -2.597166538589738,
+           -2.6601203707181313,
+           -2.707099806421472,
+           -2.7372006053994653,
+           -2.7498405365136085,
+           -2.744771930298505,
+           -2.72208670086511,
+           -2.6822137252366978,
+           -2.6259086494197117,
+           -2.554236370005265,
+           -2.4685466134603495,
+           -2.3704431982901406,
+           -2.261747713978297,
+           -2.1444584814382877,
+           -2.020705769472467,
+           -1.8927043277936964,
+           -1.7627043574559256,
+           -1.6329420726378088,
+           -1.505591012868738,
+           -1.382715241906709,
+           -1.2662255191868481,
+           -1.157839453345313,
+           -1.0590465467111811,
+           -0.9710789173664713,
+           -0.8948883444467981,
+           -0.831130126291496,
+           -0.7801540737164253,
+           -0.7420027862096632,
+           -0.7164171815423362,
+           -0.7028490735072375,
+           -0.7004804225631835,
+           -0.7082487242367401,
+           -0.7248778541220473,
+           -0.7489135597786435,
+           -0.7787626818712887,
+           -0.8127351021231236,
+           -0.8490873560823484,
+           -0.8860668157221738,
+           -0.9219553412305924,
+           -0.9551113230471151,
+           -0.9840090836351778,
+           -1.0072746823453034,
+           -1.023717264099084,
+           -1.0323552110011558,
+           -1.0324364923402556,
+           -1.023452759305216,
+           -1.0051468922957667,
+           -0.97751387687114,
+           -0.9407950549144866,
+           -0.8954659662094685,
+           -0.8422181580949488,
+           -0.7819354931133794,
+           -0.7156656227909467,
+           -0.6445874164324793,
+           -0.5699752340758676,
+           -0.4931610100415814,
+           -0.415495165925375,
+           -0.33830739813666183,
+           -0.2628683845605351,
+           -0.1903534276709308,
+           -0.12180899817176807,
+           -0.05812306537126562,
+           -5.138764760463587e-16
+          ],
+          [
+           0,
+           0.0495660943227184,
+           0.0927964679716602,
+           0.1297492727456427,
+           0.16070641426653662,
+           0.1861652738116317,
+           0.20682431929389192,
+           0.22356297693420754,
+           0.23741628594286832,
+           0.24954499608842273,
+           0.26120188887659584,
+           0.2736952041045066,
+           0.28835013220678496,
+           0.3064693870425601,
+           0.3292939021704963,
+           0.3579646954564488,
+           0.39348692195649854,
+           0.436697083989976,
+           0.48823429139302643,
+           0.5485163659811353,
+           0.6177214646882592,
+           0.6957757586513981,
+           0.7823475540810156,
+           0.8768480788712552,
+           0.97843899060023,
+           1.0860464910596168,
+           1.198381764007858,
+           1.313967290693601,
+           1.4311684459282592,
+           1.548229639931469,
+           1.6633141513170984,
+           1.774546697483508,
+           1.8800577128628306,
+           1.9780282549390515,
+           2.066734434008311,
+           2.1445902660137337,
+           2.2101878784511184,
+           2.2623340566433976,
+           2.3000822002909826,
+           2.3227588661619745,
+           2.3299841995481585,
+           2.321685701616831,
+           2.2981049385266523,
+           2.2597969672807694,
+           2.20762242863129,
+           2.1427324346330323,
+           2.0665465533219316,
+           1.9807243611672267,
+           1.8871311912759068,
+           1.787798847933085,
+           1.6848821824183051,
+           1.5806125280647267,
+           1.4772490716642934,
+           1.377029291589608,
+           1.282119619057303,
+           1.19456747711909,
+           1.1162558222402423,
+           1.0488612563992596,
+           0.9938166948726895,
+           0.9522794682454528,
+           0.9251056092851275,
+           0.9128309292363632,
+           0.9156593273732909,
+           0.9334586061969619,
+           0.9657638866484258,
+           1.0117885374536666,
+           1.0704423546064297,
+           1.1403565553576869,
+           1.2199149900850432,
+           1.3072908289684144,
+           1.4004878520480795,
+           1.4973853640907544,
+           1.5957856723198136,
+           1.693463007473982,
+           1.7882127382076782,
+           1.8778997262321568,
+           1.9605046948329559,
+           2.034167535815842,
+           2.0972265581949627,
+           2.1482527840749177,
+           2.186078520641735,
+           2.2098195788952406,
+           2.2188906662124617,
+           2.213013647158131,
+           2.192218541022946,
+           2.1568373010844804,
+           2.107490595208738,
+           2.0450679758574344,
+           1.9707019857132388,
+           1.8857368891220365,
+           1.7916928458750345,
+           1.6902264494564578,
+           1.5830886342258113,
+           1.4720810131303013,
+           1.3590117381249116,
+           1.2456519788482705,
+           1.1336940912714628,
+           1.0247124976898594,
+           0.9201282239073915,
+           0.8211779407340208,
+           0.7288882375195397,
+           0.6440557184279077,
+           0.5672333609969563,
+           0.4987234150542302,
+           0.4385769523461642,
+           0.3866000075080001,
+           0.34236608352049525,
+           0.305234633767344,
+           0.27437498225582646,
+           0.2487950072542284,
+           0.22737379493181314,
+           0.20889737151116253,
+           0.1920965473882643,
+           0.17568585649101973,
+           0.15840255005296902,
+           0.13904460653992934,
+           0.11650674857612205,
+           0.08981351259864809,
+           0.05814849620260023,
+           0.020879009689384356,
+           -0.022424520396890323,
+           -0.07197491005599761,
+           -0.12776070222443758,
+           -0.18954497974406806,
+           -0.2568705443476843,
+           -0.3290713325624192,
+           -0.4052897761082934,
+           -0.48449965841123366,
+           -0.565533874222118,
+           -0.6471163697169211,
+           -0.7278974291533613,
+           -0.8064913840226559,
+           -0.881515753977108,
+           -0.9516307873621952,
+           -1.0155783540298395,
+           -1.0722191546918634,
+           -1.1205672491510492,
+           -1.1598209694175363,
+           -1.1893893714315558,
+           -1.2089134887143165,
+           -1.2182817800489636,
+           -1.2176393080583583,
+           -1.2073903426948076,
+           -1.1881942492704736,
+           -1.1609546905976216,
+           -1.1268023428204106,
+           -1.087071490338647,
+           -1.043271022679292,
+           -0.997050501292911,
+           -0.9501620933691278,
+           -0.9044192795970831,
+           -0.8616533305372341,
+           -0.8236686096564475,
+           -0.7921977984471756,
+           -0.7688581493845846,
+           -0.7551098554234207,
+           -0.7522175806287695,
+           -0.7612161263736202,
+           -0.7828811129710136,
+           -0.817705439897884,
+           -0.8658821517227707,
+           -0.9272941847660158,
+           -1.0015113050979667,
+           -1.087794375729572,
+           -1.1851069139954526,
+           -1.2921337235066652,
+           -1.4073062129958231,
+           -1.5288338511226103,
+           -1.6547410558765079,
+           -1.7829086833186631,
+           -1.9111191663597353,
+           -2.0371042629048297,
+           -2.158594306286749,
+           -2.273367811121872,
+           -2.3793002755734096,
+           -2.4744110368338967,
+           -2.5569070800939784,
+           -2.625222771323401,
+           -2.6780545791742996,
+           -2.7143899689366675,
+           -2.733529788885913,
+           -2.7351036232311303,
+           -2.7190777524649254,
+           -2.6857555371833715,
+           -2.6357702211279,
+           -2.5700703289309166,
+           -2.489898009455123,
+           -2.39676084244073,
+           -2.2923977803649587,
+           -2.178740035235112,
+           -2.0578678381447895,
+           -1.9319640949708732,
+           -1.8032660322813758,
+           -1.6740159716759537,
+           -1.5464123873586164,
+           -1.422562390390651,
+           -1.30443674412017,
+           -1.1938284497387512,
+           -1.0923158504329584,
+           -1.0012310894455407,
+           -0.9216346243580781,
+           -0.8542963503563706,
+           -0.7996837228464807,
+           -0.757957098565901,
+           -0.7289723385036845,
+           -0.7122905398338407,
+           -0.7071945920039241,
+           -0.7127120883228975,
+           -0.7276439728637415,
+           -0.7505981669297023,
+           -0.7800273030189243,
+           -0.8142695999675075,
+           -0.8515918430104726,
+           -0.8902333885211917,
+           -0.9284500961729162,
+           -0.9645571015405091,
+           -0.9969693793773288,
+           -1.0242391109444213,
+           -1.04508895617724,
+           -1.0584404408894754,
+           -1.06343679783243,
+           -1.059459744976645,
+           -1.0461398411959217,
+           -1.0233602246491285,
+           -0.9912537084102454,
+           -0.9501933770347137,
+           -0.9007769925241031,
+           -0.8438056744326653,
+           -0.780257462739374,
+           -0.7112564999965393,
+           -0.6380386779759771,
+           -0.5619146808678084,
+           -0.48423141989954327,
+           -0.40633289149465146,
+           -0.3295215018851708,
+           -0.2550208852029298,
+           -0.18394119994047886,
+           -0.11724782139805504,
+           -0.05573425705053005,
+           -4.909565874815416e-16
+          ],
+          [
+           0,
+           0.047076878718929654,
+           0.0878838508380211,
+           0.12259293686679143,
+           0.15159466908517913,
+           0.17548646019065206,
+           0.19505509052845812,
+           0.21125377013022711,
+           0.22517437450413433,
+           0.2380155806472168,
+           0.25104773883572007,
+           0.2655754036034827,
+           0.28289851168473523,
+           0.3042732339091113,
+           0.33087354105745115,
+           0.3637545101393718,
+           0.403818357727748,
+           0.45178412183256395,
+           0.5081618249064496,
+           0.5732318401348362,
+           0.6470300539080532,
+           0.7293392725107672,
+           0.8196871642031655,
+           0.9173508629230528,
+           1.0213681909334575,
+           1.1305552891089339,
+           1.2435302794296887,
+           1.358742428766607,
+           1.4745061401157011,
+           1.5890389706962154,
+           1.7005027689852805,
+           1.807046937570266,
+           1.9068527678584006,
+           1.998177757791605,
+           2.079398815730312,
+           2.149053272884504,
+           2.2058766726992296,
+           2.2488363773951856,
+           2.27716012773076,
+           2.2903588096981666,
+           2.288242818456378,
+           2.270931562026013,
+           2.2388558114210317,
+           2.1927527759615875,
+           2.133653958290347,
+           2.0628660187902206,
+           1.9819450493701858,
+           1.8926648177566372,
+           1.7969796915256706,
+           1.6969830824775685,
+           1.5948623633344952,
+           1.4928512973689685,
+           1.393181085231713,
+           1.2980311703412226,
+           1.209480953772136,
+           1.1294635513578115,
+           1.0597226801085742,
+           1.001773689116943,
+           0.9568696535970181,
+           0.9259733319129331,
+           0.9097356472639407,
+           0.9084812014604983,
+           0.9222011616902565,
+           0.9505536863808249,
+           0.9928718774659493,
+           1.0481790679000071,
+           1.1152110794804182,
+           1.1924449211513863,
+           1.2781332459787633,
+           1.3703437495906858,
+           1.4670025773497382,
+           1.565940714649019,
+           1.6649422667387603,
+           1.7617934930128862,
+           1.8543314466856566,
+           1.940491084562437,
+           2.0183497527697454,
+           2.0861680218006198,
+           2.1424259363505143,
+           2.1858538598625166,
+           2.215457227620474,
+           2.2305346723025767,
+           2.230689148422523,
+           2.215831853028075,
+           2.186178915184827,
+           2.142241001838258,
+           2.084806158322111,
+           2.014916363885627,
+           1.9338384321858368,
+           1.843030020091756,
+           1.7441016221399206,
+           1.6387755198172673,
+           1.5288427223341214,
+           1.4161189771010547,
+           1.3024009427985361,
+           1.18942360545653,
+           1.078819978744841,
+           0.9720840647803641,
+           0.8705379628857758,
+           0.7753039031795864,
+           0.6872818524685784,
+           0.6071331949419145,
+           0.535270833304513,
+           0.4718558911968036,
+           0.416801029179524,
+           0.3697802184529906,
+           0.3302446530470267,
+           0.2974443265526407,
+           0.2704546574346715,
+           0.24820742110764807,
+           0.22952514040565186,
+           0.21315800147222352,
+           0.1978223015250421,
+           0.1822393998925639,
+           0.16517413501352507,
+           0.14547168790945517,
+           0.12209191649232273,
+           0.09414025380688038,
+           0.06089435515793684,
+           0.02182579168377041,
+           -0.023383781565836148,
+           -0.07483240992794178,
+           -0.1323938467471825,
+           -0.19571989241703963,
+           -0.26424900731452666,
+           -0.33722097690393116,
+           -0.4136972486858737,
+           -0.492586411696427,
+           -0.5726741537062248,
+           -0.6526569125838869,
+           -0.7311783395017404,
+           -0.8068676153052786,
+           -0.8783786094093518,
+           -0.9444288443794628,
+           -1.0038372296145952,
+           -1.0555595543129817,
+           -1.0987207825512337,
+           -1.1326432705661673,
+           -1.1568701263027577,
+           -1.1711830515126234,
+           -1.1756141441746448,
+           -1.1704512903434816,
+           -1.1562369359400688,
+           -1.133760196448326,
+           -1.1040424317823185,
+           -1.0683165804916324,
+           -1.0280007077838835,
+           -0.9846663715228178,
+           -0.9400025456248567,
+           -0.8957759576952151,
+           -0.8537887943224065,
+           -0.8158348007058484,
+           -0.7836548493190262,
+           -0.7588930738276072,
+           -0.7430546588615078,
+           -0.7374663435287871,
+           -0.7432406374764666,
+           -0.761244664224382,
+           -0.792074439420735,
+           -0.8360352641645064,
+           -0.893128768693758,
+           -0.9630469830691646,
+           -1.0451736428571623,
+           -1.1385927633590316,
+           -1.2421043399151073,
+           -1.3542468585584304,
+           -1.473326135060513,
+           -1.5974498452986987,
+           -1.7245669697095773,
+           -1.8525112528426604,
+           -1.9790476787135123,
+           -2.101920886273068,
+           -2.2189043987728128,
+           -2.3278495173950806,
+           -2.426732733849633,
+           -2.513700548649559,
+           -2.587110640727853,
+           -2.645568418538278,
+           -2.6879580907695395,
+           -2.713467523683107,
+           -2.7216062987415053,
+           -2.712216545068089,
+           -2.685476292464725,
+           -2.6418952680504035,
+           -2.582303238760947,
+           -2.507831178611833,
+           -2.419885709479249,
+           -2.320117423073001,
+           -2.210383835902429,
+           -2.0927078548801092,
+           -1.9692327357255601,
+           -1.8421745970032941,
+           -1.7137736075245074,
+           -1.5862449926603106,
+           -1.4617310052219359,
+           -1.342254979006103,
+           -1.2296785286053469,
+           -1.1256628790271714,
+           -1.03163520506189,
+           -0.9487607357705645,
+           -0.8779212370266541,
+           -0.8197003282661833,
+           -0.7743759223569359,
+           -0.7419199039125387,
+           -0.7220049857259551,
+           -0.7140185095951934,
+           -0.7170827909138808,
+           -0.7300814500835251,
+           -0.7516910318859968,
+           -0.7804170898831297,
+           -0.8146338096860885,
+           -0.8526261650387909,
+           -0.8926335459828431,
+           -0.9328937701828709,
+           -0.9716863873982838,
+           -1.0073742130244299,
+           -1.0384420788558442,
+           -1.0635318663589226,
+           -1.0814729877766687,
+           -1.0913076007546407,
+           -1.0923099798054818,
+           -1.0839996193257917,
+           -1.0661478042151855,
+           -1.038777551353837,
+           -1.0021569940649848,
+           -0.9567864479822147,
+           -0.9033795562905184,
+           -0.8428390611240817,
+           -0.7762278822673784,
+           -0.7047363008732074,
+           -0.629646141786474,
+           -0.5522929208747949,
+           -0.4740269717272575,
+           -0.3961745880282669,
+           -0.32000021333708645,
+           -0.24667067906534323,
+           -0.17722243496677414,
+           -0.1125326359005409,
+           -0.05329484607055901,
+           -4.678182516238691e-16
+          ],
+          [
+           0,
+           0.044611510877342136,
+           0.08307211292779544,
+           0.11566455145898441,
+           0.1428830144077662,
+           0.16541828923471164,
+           0.18413731595511876,
+           0.2000576722397225,
+           0.21431766004362474,
+           0.22814277973365749,
+           0.24280947420881846,
+           0.2596070995734766,
+           0.2797991286203423,
+           0.3045846174131563,
+           0.33506096297587346,
+           0.3721889515054845,
+           0.4167610423010528,
+           0.46937375405910886,
+           0.5304049192554703,
+           0.5999964515115686,
+           0.6780431331287834,
+           0.7641877787956032,
+           0.8578229706020377,
+           0.9580993929561016,
+           1.0639406279606252,
+           1.174064106493413,
+           1.2870077517985419,
+           1.401161704837048,
+           1.5148043876936959,
+           1.6261420463689429,
+           1.7333508202361363,
+           1.8346203147332127,
+           1.9281976083293055,
+           2.0124306056808745,
+           2.0858096567359685,
+           2.147006396257107,
+           2.194908819042976,
+           2.228651691617524,
+           2.2476415092874222,
+           2.251575335644886,
+           2.240453006710126,
+           2.2145823404377447,
+           2.1745771603866713,
+           2.121348115862233,
+           2.0560864555276814,
+           1.9802410830594872,
+           1.8954893876630936,
+           1.8037024951236547,
+           1.7069057227630118,
+           1.6072351407999423,
+           1.5068912402071108,
+           1.408090780791682,
+           1.313017941048912,
+           1.2237759121326115,
+           1.1423400714984853,
+           1.0705138375275738,
+           1.0098882455225318,
+           0.9618061993393953,
+           0.927332243640629,
+           0.9072285719697161,
+           0.9019378386950353,
+           0.9115731819200131,
+           0.9359156936154879,
+           0.9744193966499848,
+           1.0262236103663724,
+           1.0901724112068991,
+           1.1648407268797316,
+           1.2485664457701995,
+           1.3394877815342576,
+           1.4355850095062694,
+           1.5347255896902237,
+           1.6347116131380373,
+           1.733328456318827,
+           1.8283935028841598,
+           1.9178037946089823,
+           1.9995815031321564,
+           2.0719161706575195,
+           2.1332027495748895,
+           2.1820745759724316,
+           2.2174305376216,
+           2.2384558401067998,
+           2.2446359318024167,
+           2.2357633154922576,
+           2.211937147462356,
+           2.1735556996204646,
+           2.1213019323145095,
+           2.056122590819877,
+           1.9792013929013164,
+           1.8919270146648188,
+           1.7958567037030855,
+           1.692676449362369,
+           1.5841587174006444,
+           1.47211880853315,
+           1.3583709261657004,
+           1.2446850374501404,
+           1.1327455837817892,
+           1.0241130427826604,
+           0.9201892651096375,
+           0.8221874081348801,
+           0.7311071672650525,
+           0.6477158674867913,
+           0.5725358261520951,
+           0.50583823687977,
+           0.4476436578083399,
+           0.39772901948156897,
+           0.3556409025942358,
+           0.32071467780594504,
+           0.292098952794053,
+           0.2687846393304251,
+           0.2496378387243673,
+           0.23343565031433208,
+           0.21890393712654183,
+           0.20475603707934772,
+           0.18973138830203212,
+           0.17263304370716104,
+           0.15236308269428964,
+           0.12795498589995688,
+           0.09860212073898145,
+           0.06368158900239383,
+           0.022772810340655977,
+           -0.024329646057875805,
+           -0.07760931840827386,
+           -0.13682737527175737,
+           -0.20152841793933632,
+           -0.2710524114082013,
+           -0.34455243264101265,
+           -0.4210177722383162,
+           -0.4993017848738665,
+           -0.5781537584239921,
+           -0.6562539648621702,
+           -0.7322509704203558,
+           -0.8048002204362885,
+           -0.8726028773186932,
+           -0.934443879147317,
+           -0.9892282019040639,
+           -1.0360143498637713,
+           -1.074044165260773,
+           -1.1027681383618853,
+           -1.1218655102978239,
+           -1.1312585906772792,
+           -1.131120856907042,
+           -1.1218785586559183,
+           -1.104205715120141,
+           -1.0790125605633631,
+           -1.0474276608066277,
+           -1.0107740857314897,
+           -0.9705401763424876,
+           -0.9283455856376851,
+           -0.8859033968922112,
+           -0.8449792278048837,
+           -0.8073483116061515,
+           -0.7747516045384176,
+           -0.7488520015599904,
+           -0.7311917477945934,
+           -0.7231521119162833,
+           -0.7259163397620172,
+           -0.7404368330987962,
+           -0.7674074013715785,
+           -0.8072413157465061,
+           -0.8600557577016377,
+           -0.9256631021300464,
+           -1.003569311117106,
+           -1.0929795432370735,
+           -1.1928109085794194,
+           -1.301712126048484,
+           -1.4180896710516588,
+           -1.5401398426505972,
+           -1.6658860335219416,
+           -1.7932203572639411,
+           -1.9199486788862432,
+           -2.0438380084371732,
+           -2.1626651568032047,
+           -2.2742655182963123,
+           -2.376580837615321,
+           -2.4677048393438237,
+           -2.545925645870853,
+           -2.609763983364398,
+           -2.658006273427761,
+           -2.689731827963611,
+           -2.7043335036618132,
+           -2.701531327049009,
+           -2.6813787674406724,
+           -2.644261509377999,
+           -2.5908887539777696,
+           -2.522277255750033,
+           -2.4397284735405034,
+           -2.344799377149973,
+           -2.2392676009163566,
+           -2.125091768484364,
+           -2.0043679259141074,
+           -1.879283110466613,
+           -1.7520671476823115,
+           -1.6249438081822472,
+           -1.5000824670641892,
+           -1.3795513926016192,
+           -1.2652737476252072,
+           -1.158987317581015,
+           -1.0622088855621694,
+           -0.9762040589407837,
+           -0.9019632174591362,
+           -0.8401841021133871,
+           -0.7912614016001546,
+           -0.7552835225070624,
+           -0.7320365550132434,
+           -0.72101527191158,
+           -0.7214408295383653,
+           -0.7322846788399313,
+           -0.7522980472341284,
+           -0.7800462207283599,
+           -0.8139467441137118,
+           -0.8523105676552031,
+           -0.8933851036737951,
+           -0.9353981172911061,
+           -0.9766013632623525,
+           -1.0153128954709796,
+           -1.049957016843797,
+           -1.0791009040543615,
+           -1.101487031672562,
+           -1.1160606320624111,
+           -1.121991557474462,
+           -1.118690056116897,
+           -1.105816130840811,
+           -1.0832823134830112,
+           -1.051249855735155,
+           -1.0101185044365266,
+           -0.9605101912323358,
+           -0.903247119546316,
+           -0.8393248719653911,
+           -0.76988128493386,
+           -0.696161942029456,
+           -0.619483219459782,
+           -0.5411938757477026,
+           -0.4626362104469527,
+           -0.38510782336423216,
+           -0.30982498604172753,
+           -0.23788859171717494,
+           -0.1702535798184509,
+           -0.10770263807634543,
+           -0.050824871935045784,
+           -4.446490257965839e-16
+          ],
+          [
+           0,
+           0.04218935357197776,
+           0.07839827907974438,
+           0.10901613722844748,
+           0.13463492064785304,
+           0.15603136793669403,
+           0.1741437964338527,
+           0.19004426371973177,
+           0.2049067911430629,
+           0.21997248729369379,
+           0.23651249262711727,
+           0.25578972625398916,
+           0.2790204506895347,
+           0.30733667919426244,
+           0.3417504329616467,
+           0.3831208122126343,
+           0.4321247772832503,
+           0.4892324447069821,
+           0.5546875913481412,
+           0.6284939296137598,
+           0.710407571896159,
+           0.7999359462907216,
+           0.8963432621964761,
+           0.9986624577348299,
+           1.105713395197051,
+           1.216126910121653,
+           1.3283741681567842,
+           1.440800645407868,
+           1.5516639260182412,
+           1.659174408387549,
+           1.7615379313235058,
+           1.8569992756237303,
+           1.9438854665705911,
+           2.020647799430202,
+           2.0859015334528173,
+           2.138462249586553,
+           2.1773779419953097,
+           2.201956011743643,
+           2.211784450320588,
+           2.206746638138816,
+           2.187029335426893,
+           2.1531236063187307,
+           2.1058185874409356,
+           2.04618818572725,
+           1.9755709622900468,
+           1.8955436257170224,
+           1.8078887150307257,
+           1.714557195874421,
+           1.6176268197213342,
+           1.5192572019121549,
+           1.4216426574663075,
+           1.3269638918033626,
+           1.23733967527893,
+           1.154779634958894,
+           1.0811392741689776,
+           1.0180782805778386,
+           0.9670231080759714,
+           0.9291347183058712,
+           0.9052822467752353,
+           0.8960232189672632,
+           0.9015907871306517,
+           0.9218882922409967,
+           0.9564912820115871,
+           1.0046569390141715,
+           1.0653406972475614,
+           1.1372196551354599,
+           1.218722232084602,
+           1.3080633682965637,
+           1.403284437078189,
+           1.5022969285960037,
+           1.6029288765335286,
+           1.702972936541286,
+           1.8002349892095744,
+           1.8925821313880236,
+           1.9779889381989049,
+           2.054580923546265,
+           2.1206741981536914,
+           2.1748104193825224,
+           2.215786243916487,
+           2.2426766299476535,
+           2.2548514864069515,
+           2.251985329323192,
+           2.2340597755607825,
+           2.2013588777912956,
+           2.154457477333775,
+           2.094202919218004,
+           2.0216906323816874,
+           1.9382342234388226,
+           1.8453308614139692,
+           1.7446228401040884,
+           1.6378562916774086,
+           1.5268380876763827,
+           1.413392000296187,
+           1.299315206841692,
+           1.1863362034670946,
+           1.0760751511822713,
+           0.9700076088282894,
+           0.8694325160642669,
+           0.7754451767280045,
+           0.6889158621102232,
+           0.61047450803888,
+           0.5405018228891558,
+           0.4791269596697657,
+           0.4262317383110879,
+           0.3814612383868204,
+           0.34424042189369153,
+           0.31379629440748985,
+           0.2891849747027387,
+           0.2693229212077823,
+           0.2530214614870838,
+           0.23902369082389263,
+           0.22604274988734757,
+           0.21280046077099626,
+           0.19806529610760726,
+           0.18068867756406676,
+           0.15963864720807278,
+           0.13403002678058434,
+           0.10315027395834805,
+           0.06648035883851464,
+           0.023710115207357014,
+           -0.02525233367836387,
+           -0.0802773197582527,
+           -0.14101662873639922,
+           -0.2069126724004634,
+           -0.2772135929967553,
+           -0.350993902582597,
+           -0.42718011500186615,
+           -0.5045806966564181,
+           -0.5819195479224415,
+           -0.6578721328034732,
+           -0.7311033026342001,
+           -0.8003058121997694,
+           -0.864238504751916,
+           -0.9217631466809195,
+           -0.971878922978409,
+           -1.0137536603811368,
+           -1.0467509248610969,
+           -1.0704522419584086,
+           -1.0846738098184057,
+           -1.0894772126768903,
+           -1.0851737935014485,
+           -1.0723225047714726,
+           -1.0517212219542573,
+           -1.0243916709578298,
+           -0.9915582845245543,
+           -0.9546214590523674,
+           -0.9151258287421613,
+           -0.8747243045897093,
+           -0.8351387382485554,
+           -0.7981181623121516,
+           -0.7653956267410372,
+           -0.7386446942129489,
+           -0.71943667394068,
+           -0.7091996634763055,
+           -0.7091804313579827,
+           -0.7204101109763131,
+           -0.7436745892033015,
+           -0.7794903642081775,
+           -0.8280865181075806,
+           -0.889393304782686,
+           -0.9630376948788176,
+           -1.0483460525490491,
+           -1.1443539460116112,
+           -1.249822920693705,
+           -1.36326389389171,
+           -1.4829666676735451,
+           -1.6070349061859819,
+           -1.7334257883309145,
+           -1.8599934302923058,
+           -1.9845350775252295,
+           -2.1048389949302493,
+           -2.2187329388133956,
+           -2.3241320760271895,
+           -2.419085224895177,
+           -2.5018183289618743,
+           -2.5707741374355737,
+           -2.624647153907231,
+           -2.662413025428582,
+           -2.683351674649936,
+           -2.6870636252914304,
+           -2.673479132172746,
+           -2.642859897447756,
+           -2.5957933304417744,
+           -2.5331794852980822,
+           -2.456210984208939,
+           -2.3663464001157295,
+           -2.265277727377615,
+           -2.154892708274858,
+           -2.0372329039535506,
+           -1.9144484976115461,
+           -1.7887508929800262,
+           -1.6623642206668328,
+           -1.5374768875254479,
+           -1.4161942993857832,
+           -1.3004938553906493,
+           -1.1921832536549013,
+           -1.0928630644789623,
+           -1.003894420991323,
+           -0.9263725505111249,
+           -0.86110672624927,
+           -0.8086070617571917,
+           -0.7690784036650585,
+           -0.7424214058357362,
+           -0.728240694335544,
+           -0.7258598618504414,
+           -0.7343428665385252,
+           -0.7525212578038447,
+           -0.779026513817108,
+           -0.8123266561362765,
+           -0.8507662083782273,
+           -0.8926084909186783,
+           -0.9360791938238804,
+           -0.9794101467889497,
+           -1.0208822082639704,
+           -1.0588662260138106,
+           -1.0918610772439004,
+           -1.118527876655672,
+           -1.137719543294772,
+           -1.1485050391960798,
+           -1.1501877315028415,
+           -1.1423174814294987,
+           -1.1246962243181655,
+           -1.0973769710565802,
+           -1.0606563281091521,
+           -1.0150607971767118,
+           -0.9613272719467305,
+           -0.9003782946177149,
+           -0.8332927652607736,
+           -0.7612729093775882,
+           -0.6856084004459072,
+           -0.6076386025568868,
+           -0.5287139417728733,
+           -0.4501574325236597,
+           -0.3732273768179496,
+           -0.29908221953880215,
+           -0.22874848353353594,
+           -0.16309262514499626,
+           -0.1027975463977683,
+           -0.048344376921093585,
+           -4.2163408567789886e-16
+          ],
+          [
+           0,
+           0.03982907570372447,
+           0.07389751785669922,
+           0.10269627704915683,
+           0.12690848460107879,
+           0.14738871823365926,
+           0.16513735062092785,
+           0.18127065865321976,
+           0.1969874833672892,
+           0.21353332248449053,
+           0.23216280699454603,
+           0.25410155843889176,
+           0.2805084433054509,
+           0.31243923470691903,
+           0.3508126593921575,
+           0.396379750901468,
+           0.4496973487205764,
+           0.5111064806125947,
+           0.5807162434584379,
+           0.6583936599461605,
+           0.7437598377608218,
+           0.836192598305737,
+           0.934835577431212,
+           1.0386136352870974,
+           1.1462542504079662,
+           1.2563144185661022,
+           1.3672124336917792,
+           1.4772637998913731,
+           1.5847204135542607,
+           1.687812065543944,
+           1.7847892478130385,
+           1.873966208184926,
+           1.9537631826053417,
+           2.022746746335054,
+           2.0796672641188874,
+           2.123492483459105,
+           2.1534364032386937,
+           2.168982659978953,
+           2.169901803323918,
+           2.156261977786163,
+           2.128432685822453,
+           2.087081474072388,
+           2.0331635560032817,
+           1.967904556051462,
+           1.8927767284060584,
+           1.8094691637035532,
+           1.7198526451349407,
+           1.6259399481431849,
+           1.5298424917143065,
+           1.4337243414068659,
+           1.3397546324166751,
+           1.2500595234176048,
+           1.1666748075656574,
+           1.09150029546944,
+           1.0262570463508744,
+           0.9724484589434487,
+           0.9313261444403242,
+           0.9038613921540626,
+           0.8907229071770687,
+           0.892261351416355,
+           0.9085010585039079,
+           0.9391391231601284,
+           0.983551890740845,
+           1.0408086971782964,
+           1.1096925376002655,
+           1.1887271777585062,
+           1.276210070006219,
+           1.3702502986347065,
+           1.468810661231444,
+           1.5697528962149683,
+           1.670884994163733,
+           1.770009483725786,
+           1.8649715628821282,
+           1.9537059535895238,
+           2.0342813921303953,
+           2.104941727967574,
+           2.1641426890192212,
+           2.2105834789102348,
+           2.243232499248039,
+           2.2613466341560056,
+           2.2644836916155033,
+           2.252507762739312,
+           2.2255874318258275,
+           2.1841869427066034,
+           2.129050596265544,
+           2.0611808159323495,
+           1.981810468482588,
+           1.8923701629485616,
+           1.7944513675740412,
+           1.6897662807073557,
+           1.5801054640253185,
+           1.467294293804415,
+           1.353149307021368,
+           1.2394355134411001,
+           1.1278257127664835,
+           1.019862798267478,
+           0.9169259465953725,
+           0.8202014898334401,
+           0.7306591428909232,
+           0.6490341202393811,
+           0.575815524240784,
+           0.5112412267539286,
+           0.45529930037008726,
+           0.40773588967069707,
+           0.3680692504766629,
+           0.33560953023139656,
+           0.3094837192905434,
+           0.2886650745493637,
+           0.2720062067099878,
+           0.2582749332994252,
+           0.24619193349026527,
+           0.2344691994606902,
+           0.2218482634467191,
+           0.20713719012808904,
+           0.18924536023502578,
+           0.1672151323046011,
+           0.14024955376832948,
+           0.10773539785060085,
+           0.0692609264064659,
+           0.024627917673098028,
+           -0.02614235158273102,
+           -0.08280932169516461,
+           -0.14491955352514507,
+           -0.21181914784695188,
+           -0.2826718514226139,
+           -0.35648237146558603,
+           -0.4321242833681108,
+           -0.5083717954188971,
+           -0.5839345318556016,
+           -0.6574944145951187,
+           -0.7277436664422156,
+           -0.7934229259821084,
+           -0.8533584575770639,
+           -0.9064974591238172,
+           -0.9519405150453751,
+           -0.9889703113017564,
+           -1.0170758213055062,
+           -1.0359712842405762,
+           -1.0456094276094297,
+           -1.0461885306256413,
+           -1.0381530807120412,
+           -1.0221879379628427,
+           -0.9992060879061756,
+           -0.9703302271048637,
+           -0.9368685849256941,
+           -0.9002855341856113,
+           -0.8621676795686976,
+           -0.8241862322442878,
+           -0.7880565789554058,
+           -0.7554960314250746,
+           -0.7281807952318027,
+           -0.7077032249215481,
+           -0.6955304332748393,
+           -0.6929652972146152,
+           -0.7011108513636026,
+           -0.7208389839290239,
+           -0.7527642502162399,
+           -0.7972234990367003,
+           -0.8542618694818561,
+           -0.9236255633325255,
+           -1.00476163547564,
+           -1.0968248750927574,
+           -1.1986916782271722,
+           -1.3089806418602032,
+           -1.4260794450303542,
+           -1.5481774278731661,
+           -1.673303138568592,
+           -1.799365994547782,
+           -1.9242011010059366,
+           -2.0456161893690266,
+           -2.1614395828886206,
+           -2.269568067399081,
+           -2.3680135432285163,
+           -2.4549473594086373,
+           -2.5287412831101475,
+           -2.588004134418216,
+           -2.631613217309668,
+           -2.6587397995747826,
+           -2.6688680344961844,
+           -2.661806871962452,
+           -2.637694672597357,
+           -2.5969964113979365,
+           -2.5404935330936897,
+           -2.469266695693578,
+           -2.384671807240728,
+           -2.2883099195505485,
+           -2.1819916878100947,
+           -2.0676972328440284,
+           -1.947532350506472,
+           -1.8236820974365398,
+           -1.6983628422795138,
+           -1.5737739049961619,
+           -1.4520499132787463,
+           -1.3352149842467707,
+           -1.2251397920592835,
+           -1.123502509058744,
+           -1.031754511381794,
+           -0.951091622040548,
+           -0.8824315282185494,
+           -0.8263978583075312,
+           -0.7833112417662709,
+           -0.7531875052119485,
+           -0.7357429854296034,
+           -0.7304067684454548,
+           -0.7363394976570771,
+           -0.7524582373088577,
+           -0.7774667341647676,
+           -0.8098902935471423,
+           -0.8481143790441998,
+           -0.8904259607083496,
+           -0.9350565764815414,
+           -0.9802260372945286,
+           -1.0241856985541398,
+           -1.0652602396571784,
+           -1.1018869381913385,
+           -1.1326514953964963,
+           -1.1563195624425302,
+           -1.1718632307426964,
+           -1.178481880965719,
+           -1.1756169313004825,
+           -1.162960182178144,
+           -1.1404556181203258,
+           -1.1082946935512488,
+           -1.0669052941185864,
+           -1.0169347241912106,
+           -0.959227220767297,
+           -0.8947966303063221,
+           -0.8247950046053358,
+           -0.7504779718090792,
+           -0.6731678165080106,
+           -0.5942152567288695,
+           -0.5149609341555502,
+           -0.4366976364675881,
+           -0.36063424723635923,
+           -0.28786237001574616,
+           -0.21932650038156037,
+           -0.15579852459338295,
+           -0.0978572087119729,
+           -0.045873210338163536,
+           -3.989544392183075e-16
+          ],
+          [
+           0,
+           0.03754847644786831,
+           0.06960281559674929,
+           0.09674967418129674,
+           0.11975591346211832,
+           0.13954523444868552,
+           0.15717029789002246,
+           0.17378106791311013,
+           0.19059021832112527,
+           0.20883651928358649,
+           0.22974717743968057,
+           0.2545001328648353,
+           0.2841873211143633,
+           0.3197798874976098,
+           0.3620962943423195,
+           0.41177419141081517,
+           0.46924682656629735,
+           0.5347246605656619,
+           0.608182719291289,
+           0.6893540720849408,
+           0.7777296697279715,
+           0.8725646139081492,
+           0.9728907657815076,
+           1.077535438605598,
+           1.1851457624841655,
+           1.294218161984086,
+           1.4031322534912882,
+           1.5101883520645656,
+           1.6136476802136135,
+           1.7117742959722324,
+           1.8028777068107893,
+           1.8853551106857316,
+           1.9577322065755003,
+           2.0187015442663463,
+           2.0671574363367413,
+           2.102226533012394,
+           2.123293260979493,
+           2.130019447938844,
+           2.122357592736558,
+           2.100557392959705,
+           2.0651653042256504,
+           2.0170170740467555,
+           1.9572233639782681,
+           1.8871487425548914,
+           1.8083844941304552,
+           1.7227158411398116,
+           1.6320843157307976,
+           1.5385461377328573,
+           1.4442275565262528,
+           1.3512781920379633,
+           1.2618234628637663,
+           1.1779172160559992,
+           1.1014956727211662,
+           1.034333776199627,
+           0.9780049758720495,
+           0.9338454008224958,
+           0.9029232755709914,
+           0.8860143073251061,
+           0.8835836336565088,
+           0.8957747645890131,
+           0.9224057875474777,
+           0.9629729314823435,
+           1.0166614119358557,
+           1.0823633060966165,
+           1.1587020401983061,
+           1.244062915008111,
+           1.336628952425258,
+           1.4344212208343836,
+           1.5353426918703401,
+           1.6372245991886805,
+           1.737874212674645,
+           1.8351229106273215,
+           1.9268734285448974,
+           2.0111451862698946,
+           2.086116644825861,
+           2.1501637190374887,
+           2.201893370107251,
+           2.240171621285975,
+           2.264145376676561,
+           2.2732575746671553,
+           2.267255369768391,
+           2.2461912057350437,
+           2.2104168146307264,
+           2.1605703467321264,
+           2.0975570006993323,
+           2.022523678242469,
+           1.9368283288208348,
+           1.84200477428863,
+           1.739723907845045,
+           1.6317522436488276,
+           1.519908851070731,
+           1.4060217394411325,
+           1.2918847646037641,
+           1.1792161075648413,
+           1.069619328640746,
+           0.964547929007925,
+           0.8652742573040383,
+           0.7728634843393404,
+           0.6881532369707754,
+           0.6117393361140963,
+           0.5439679274099058,
+           0.4849341301565182,
+           0.43448716486700595,
+           0.3922417563404167,
+           0.3575954515453581,
+           0.32975134383062804,
+           0.3077455606815753,
+           0.29047875476762297,
+           0.2767507402837169,
+           0.265297340984869,
+           0.25482846469809173,
+           0.24406639271489552,
+           0.23178327193015685,
+           0.21683682285983996,
+           0.1982033270529481,
+           0.1750070315939143,
+           0.14654520445535335,
+           0.11230818994388196,
+           0.07199394543347391,
+           0.025516685638925864,
+           -0.026990584843985015,
+           -0.0851797100408449,
+           -0.148497090060884,
+           -0.21619919671471627,
+           -0.28737348446079786,
+           -0.360964142392152,
+           -0.43580200566891786,
+           -0.5106378348915063,
+           -0.5841780821959128,
+           -0.6551221956316805,
+           -0.7222004703838991,
+           -0.7842114377439393,
+           -0.8400577909029363,
+           -0.8887798804710364,
+           -0.9295858713015817,
+           -0.9618777342844669,
+           -0.9852723502374044,
+           -0.9996171252984164,
+           -1.0049996552613554,
+           -1.0017511266516415,
+           -0.9904433012498972,
+           -0.9718790942533204,
+           -0.9470769202134021,
+           -0.9172491411791455,
+           -0.8837751040659535,
+           -0.8481693953051563,
+           -0.8120460667317582,
+           -0.7770796942335678,
+           -0.7449642171588855,
+           -0.7173705696290673,
+           -0.6959041530693096,
+           -0.6820632114180393,
+           -0.6771991562099287,
+           -0.682479848313919,
+           -0.6988567774606403,
+           -0.7270369913573841,
+           -0.767460515299093,
+           -0.8202838734161714,
+           -0.8853701772037111,
+           -0.9622860892981585,
+           -1.0503058044620253,
+           -1.1484220194745376,
+           -1.255363693289863,
+           -1.3696202326086655,
+           -1.4894715800135143,
+           -1.6130235359502816,
+           -1.738247515710023,
+           -1.863023831411348,
+           -1.985187499574016,
+           -2.1025755094501672,
+           -2.2130744474952118,
+           -2.3146673602421597,
+           -2.4054787517638907,
+           -2.483816652577139,
+           -2.5482107633117526,
+           -2.597445767158202,
+           -2.630589017837624,
+           -2.64701194189297,
+           -2.6464046422818006,
+           -2.6287833509688667,
+           -2.5944905475682853,
+           -2.5441877349567874,
+           -2.4788410369444134,
+           -2.3996999533131405,
+           -2.308269769678491,
+           -2.2062782697541854,
+           -2.0956375320593525,
+           -1.9784017086406607,
+           -1.8567217771912035,
+           -1.7327983277701906,
+           -1.6088334894882077,
+           -1.4869831199756651,
+           -1.369310370807559,
+           -1.2577417055892284,
+           -1.1540263850459755,
+           -1.0597003467691892,
+           -0.976055298411684,
+           -0.9041137147951779,
+           -0.8446102847673876,
+           -0.7979801962939739,
+           -0.7643544820676744,
+           -0.7435624769501556,
+           -0.7351412670286146,
+           -0.7383518421718779,
+           -0.7522015038154353,
+           -0.7754719311985244,
+           -0.8067521760309724,
+           -0.8444757408111686,
+           -0.8869608025145076,
+           -0.932452573357978,
+           -0.9791667454704615,
+           -1.0253329475833137,
+           -1.0692371496759945,
+           -1.1092619855828385,
+           -1.1439240229557126,
+           -1.171907093123626,
+           -1.1920908981483622,
+           -1.2035742360674537,
+           -1.2056923247998723,
+           -1.1980278569374403,
+           -1.1804155778309682,
+           -1.1529403439765664,
+           -1.1159287835863427,
+           -1.069934842261102,
+           -1.0157196498487842,
+           -0.9542262860529479,
+           -0.886550148632566,
+           -0.8139057359765427,
+           -0.7375907427771348,
+           -0.6589484313303529,
+           -0.5793292801061264,
+           -0.5000529247262752,
+           -0.4223713940782932,
+           -0.34743460634232004,
+           -0.27625902722394097,
+           -0.2097003072884646,
+           -0.14843060917915382,
+           -0.09292121138835616,
+           -0.04343083630279886,
+           -3.767851968994985e-16
+          ],
+          [
+           0,
+           0.035364319632219546,
+           0.06554467518333669,
+           0.09121675330084375,
+           0.11322307255899555,
+           0.13254722726772766,
+           0.15028405152878885,
+           0.16760649621945792,
+           0.1857300990230124,
+           0.2058759925791564,
+           0.229233436626766,
+           0.25692287559279653,
+           0.2899605130165426,
+           0.3292253587045771,
+           0.37542964444592447,
+           0.4290934209559866,
+           0.4905240445209801,
+           0.559801139173417,
+           0.6367674822021665,
+           0.7210261108378351,
+           0.8119437898109715,
+           0.9086608171240514,
+           1.0101069828883484,
+           1.1150233375446006,
+           1.2219892752115946,
+           1.3294542990980345,
+           1.435773712392233,
+           1.539247372958538,
+           1.6381605662121697,
+           1.7308259898870453,
+           1.8156258086491612,
+           1.8910527266192696,
+           1.955749042188303,
+           2.0085426917212588,
+           2.0484793558887446,
+           2.0748497928572935,
+           2.087211674243073,
+           2.085405329891507,
+           2.0695629530257307,
+           2.040110974561011,
+           1.9977654805622542,
+           1.9435207158749395,
+           1.8786308857292922,
+           1.8045856314447641,
+           1.7230797121895103,
+           1.6359775682221613,
+           1.5452735686024608,
+           1.4530488548308633,
+           1.3614257785568162,
+           1.272520994205033,
+           1.1883983045185946,
+           1.1110223676432205,
+           1.0422143581649217,
+           0.9836106318086785,
+           0.9366253753047872,
+           0.9024181308548535,
+           0.8818669708911008,
+           0.8755479661641685,
+           0.8837214418250079,
+           0.9063253556826777,
+           0.9429759641172106,
+           0.9929757683040351,
+           1.055328560664893,
+           1.1287612230000312,
+           1.2117517676737473,
+           1.3025629654112358,
+           1.3992807713095825,
+           1.499856647771333,
+           1.6021527919691503,
+           1.7039892083441408,
+           1.803191525139054,
+           1.8976384390534629,
+           1.985307684112076,
+           2.0643194594306618,
+           2.132976314766836,
+           2.1897985809484837,
+           2.233554542288154,
+           2.263284677191814,
+           2.2783194381658034,
+           2.27829019974131,
+           2.263133168599453,
+           2.2330862203188704,
+           2.188678797507831,
+           2.1307151704533256,
+           2.0602515197544236,
+           1.9785674468466528,
+           1.8871326493087448,
+           1.7875696102020808,
+           1.6816132417213916,
+           1.5710684909604007,
+           1.4577669580307149,
+           1.3435235931529244,
+           1.2300945293486505,
+           1.1191370713379087,
+           1.0121728001682735,
+           0.9105546685710076,
+           0.8154388562321648,
+           0.7277620297852354,
+           0.6482245125326976,
+           0.5772797172198496,
+           0.5151300354364013,
+           0.4617292134225343,
+           0.41679108031214435,
+           0.3798043352519503,
+           0.3500529483741936,
+           0.32664159104488477,
+           0.30852538662562673,
+           0.29454316725079194,
+           0.2834533374415476,
+           0.27397138383015635,
+           0.26480803334521297,
+           0.254707050784074,
+           0.24248168100464962,
+           0.22704878059057798,
+           0.20745974773183537,
+           0.18292744555864765,
+           0.15284842104527288,
+           0.11681984612619556,
+           0.07465074666344236,
+           0.026367234830951717,
+           -0.027788382471872205,
+           -0.08736458638950921,
+           -0.15171352803623087,
+           -0.22000946329315266,
+           -0.2912722488275907,
+           -0.364395274910125,
+           -0.4381770937918708,
+           -0.5113559045283383,
+           -0.5826459786947268,
+           -0.6507750583893289,
+           -0.7145217296379648,
+           -0.7727517715407543,
+           -0.8244525043494324,
+           -0.8687642075900148,
+           -0.9050077511812196,
+           -0.9327076764702876,
+           -0.9516100778818292,
+           -0.9616947666184337,
+           -0.9631813422994217,
+           -0.9565289529623526,
+           -0.942429684607487,
+           -0.9217956844019957,
+           -0.8957402826801854,
+           -0.8655535339202265,
+           -0.832672742030334,
+           -0.7986486668614351,
+           -0.765108223533687,
+           -0.7337145809917358,
+           -0.7061256387476786,
+           -0.6839519091424113,
+           -0.6687148553644453,
+           -0.6618067322516099,
+           -0.6644529475554288,
+           -0.6776779065109294,
+           -0.7022752235020729,
+           -0.7387830832254836,
+           -0.7874654124721672,
+           -0.8482993854070076,
+           -0.9209696333947257,
+           -1.00486936870842,
+           -1.0991084638254394,
+           -1.2025283585824385,
+           -1.3137235003979146,
+           -1.4310688621970122,
+           -1.5527529325582927,
+           -1.6768154366643666,
+           -1.801188928253451,
+           -1.9237432948861306,
+           -2.0423321439114916,
+           -2.15483998642743,
+           -2.259229112563004,
+           -2.35358505420677,
+           -2.436159560848249,
+           -2.5054100698178376,
+           -2.560034732589503,
+           -2.5990021620290955,
+           -2.6215751890439445,
+           -2.627328058031599,
+           -2.616156645423468,
+           -2.5882814507151197,
+           -2.544243280659554,
+           -2.484891720610268,
+           -2.411366658123419,
+           -2.3250732887022525,
+           -2.227651187985832,
+           -2.1209381749960636,
+           -2.0069298138552365,
+           -1.8877355036939982,
+           -1.7655321858127144,
+           -1.6425167516262402,
+           -1.5208582632134144,
+           -1.4026510997482502,
+           -1.2898701177098122,
+           -1.184328861208176,
+           -1.0876417823217075,
+           -1.001191331922421,
+           -0.9261006615377723,
+           -0.8632125393253487,
+           -0.8130749316146922,
+           -0.7759335394326558,
+           -0.7517314109603815,
+           -0.7401155801071543,
+           -0.7404505125146904,
+           -0.7518379774558106,
+           -0.7731428112391031,
+           -0.8030238985972692,
+           -0.8399695764967556,
+           -0.882336562807075,
+           -0.9283914327561464,
+           -0.9763536109585451,
+           -1.0244388173161678,
+           -1.0709019018974548,
+           -1.1140780269919917,
+           -1.1524212032509908,
+           -1.1845392598665758,
+           -1.209224424219017,
+           -1.2254788018836553,
+           -1.2325341804001937,
+           -1.229865726410943,
+           -1.217199301982825,
+           -1.1945122882117272,
+           -1.1620279684943158,
+           -1.1202036860293993,
+           -1.0697131461255758,
+           -1.0114233798552952,
+           -0.9463670178764989,
+           -0.8757106385603052,
+           -0.8007200500660007,
+           -0.7227234393431495,
+           -0.6430733704249564,
+           -0.5631086386202236,
+           -0.48411698575922424,
+           -0.40729965459330336,
+           -0.3337387085231369,
+           -0.2643679673949756,
+           -0.1999483131056948,
+           -0.1410480026838889,
+           -0.08802849433158338,
+           -0.04103614698797482,
+           -3.552939157982844e-16
+          ],
+          [
+           0,
+           0.03329217998628205,
+           0.061750842476371824,
+           0.08613330816862369,
+           0.10734910104135258,
+           0.126432058371899,
+           0.1445088256618427,
+           0.16276457530801025,
+           0.1824068620267979,
+           0.20462857886020402,
+           0.230571003753618,
+           0.2612879275059353,
+           0.2977118292980023,
+           0.3406230165914761,
+           0.39062257316802546,
+           0.44810986425503946,
+           0.5132652334160154,
+           0.5860383950210678,
+           0.6661428819263301,
+           0.7530567540910018,
+           0.8460296141078995,
+           0.9440958140315204,
+           1.0460935785242662,
+           1.1506896162256073,
+           1.256408648251066,
+           1.3616671534727436,
+           1.464810518009115,
+           1.5641526840285058,
+           1.6580173229264021,
+           1.7447795119989296,
+           1.8229068731332234,
+           1.890999137371105,
+           1.9478251304313174,
+           1.9923562307090765,
+           2.0237954315923496,
+           2.041601242228088,
+           2.045505782674186,
+           2.0355265677300873,
+           2.0119716252792457,
+           1.975437755994429,
+           1.9268019078034944,
+           1.8672058064948962,
+           1.7980341491205976,
+           1.720886825349386,
+           1.6375457797150672,
+           1.549937261127443,
+           1.4600903217523478,
+           1.3700925225332248,
+           1.2820438748351535,
+           1.1980100951183514,
+           1.1199762709741776,
+           1.0498020317022319,
+           0.9891792849440674,
+           0.9395935234406402,
+           0.9022896241037726,
+           0.8782429572448366,
+           0.8681364994976278,
+           0.8723445027101945,
+           0.8909231162830683,
+           0.9236081958542838,
+           0.9698203608716425,
+           1.0286771915905746,
+           1.0990122865739773,
+           1.1794007389698526,
+           1.2681904376621944,
+           1.3635384615293185,
+           1.4634517148497224,
+           1.5658308522837872,
+           1.6685164652401516,
+           1.7693364496550765,
+           1.8661534495086578,
+           1.9569112713714025,
+           2.039679192862742,
+           2.1126931414018215,
+           2.174392797698664,
+           2.2234537791278735,
+           2.2588141789529033,
+           2.279694875340722,
+           2.2856131758229563,
+           2.276389524585742,
+           2.2521471677323994,
+           2.2133048413446708,
+           2.160562714613448,
+           2.094881981425016,
+           2.017458644643585,
+           1.929692174255218,
+           1.8331498402124935,
+           1.729527620356058,
+           1.6206086608036012,
+           1.5082203188652932,
+           1.3941908456488556,
+           1.280306766473604,
+           1.1682719920853442,
+           1.0596696431630284,
+           0.9559274960703071,
+           0.858287861160713,
+           0.767782588667697,
+           0.6852137642561342,
+           0.6111405100434314,
+           0.5458721510029447,
+           0.4894678450583402,
+           0.44174261191632325,
+           0.4022795348513052,
+           0.37044775526383034,
+           0.3454257357307268,
+           0.32622913703006234,
+           0.311742541485113,
+           0.3007541617221525,
+           0.2919926028673225,
+           0.2841646990489028,
+           0.27599342295159085,
+           0.2662548705877583,
+           0.2538133522643575,
+           0.23765367415306876,
+           0.21690977151801327,
+           0.19088895254057842,
+           0.159091128293623,
+           0.12122253677769695,
+           0.07720361366667185,
+           0.027170815836880163,
+           -0.028527638026407072,
+           -0.08934198645617623,
+           -0.1545368248408063,
+           -0.22321225812546958,
+           -0.2943297414933896,
+           -0.36674192088055646,
+           -0.4392256797213153,
+           -0.5105175131582222,
+           -0.5793502882536354,
+           -0.6444904101234454,
+           -0.7047744003806176,
+           -0.7591439062017332,
+           -0.8066781954469617,
+           -0.8466232546716664,
+           -0.8784166910524129,
+           -0.9017077441232982,
+           -0.9163718361683875,
+           -0.9225192280731653,
+           -0.9204974969506726,
+           -0.9108877091792186,
+           -0.8944943236687718,
+           -0.8723290211588235,
+           -0.8455888120859478,
+           -0.8156289240872279,
+           -0.7839311067667396,
+           -0.7520681124790328,
+           -0.7216652144871136,
+           -0.6943597053009052,
+           -0.6717593761855618,
+           -0.6554010122142798,
+           -0.6467099449086771,
+           -0.6469616861821125,
+           -0.6572466233447335,
+           -0.6784386863496364,
+           -0.7111688068779425,
+           -0.7558038764727643,
+           -0.8124317804556376,
+           -0.8808529389664753,
+           -0.9605786297091071,
+           -1.0508362026978653,
+           -1.1505811295203618,
+           -1.258515662486123,
+           -1.3731137166422087,
+           -1.4926514340180415,
+           -1.615242748416392,
+           -1.7388791440977782,
+           -1.8614726959229646,
+           -1.9809013945670373,
+           -2.0950557004112222,
+           -2.201885235180177,
+           -2.2994445122255875,
+           -2.3859366248163334,
+           -2.459753856482496,
+           -2.519514247332179,
+           -2.564093243653246,
+           -2.5926496727859285,
+           -2.6046454184405228,
+           -2.5998583201155467,
+           -2.5783879804464678,
+           -2.540654332295374,
+           -2.4873889890963157,
+           -2.4196195732253347,
+           -2.3386473838035085,
+           -2.2460189233135197,
+           -2.1434919478742667,
+           -2.0329968354398114,
+           -1.9165941764270502,
+           -1.7964295796601697,
+           -1.6746867509144219,
+           -1.5535399402000694,
+           -1.4351068663298687,
+           -1.3214032129871602,
+           -1.2142997498404215,
+           -1.115483066261499,
+           -1.0264208155457697,
+           -0.9483322564292707,
+           -0.8821647488987288,
+           -0.8285767159989177,
+           -0.7879274261373713,
+           -0.7602737851351561,
+           -0.7453741580319987,
+           -0.7426990715732984,
+           -0.7514484835233326,
+           -0.7705751484874881,
+           -0.7988134655986074,
+           -0.8347130647342079,
+           -0.8766762779953997,
+           -0.9229985546391452,
+           -0.9719108126237416,
+           -1.021622679928522,
+           -1.0703655647466717,
+           -1.116434505784937,
+           -1.158227791847386,
+           -1.194283402605413,
+           -1.22331140832436,
+           -1.244221573119648,
+           -1.2561455313286074,
+           -1.2584530466389985,
+           -1.250762015175257,
+           -1.2329420329940615,
+           -1.2051115113849824,
+           -1.16762848592827,
+           -1.1210754233689166,
+           -1.0662384800804725,
+           -1.0040818034894288,
+           -0.9357175898962845,
+           -0.8623727156430624,
+           -0.7853528409893606,
+           -0.706004945353088,
+           -0.6256792873138582,
+           -0.5456917921502941,
+           -0.4672878535086887,
+           -0.3916084945427494,
+           -0.31965976861438206,
+           -0.25228619209770803,
+           -0.1901488942349816,
+           -0.13370904410762682,
+           -0.08321697579514113,
+           -0.03870728323795446,
+           -3.3463903405064493e-16
+          ],
+          [
+           0,
+           0.03134630276816558,
+           0.05824606303967538,
+           0.08153019925610563,
+           0.10216609902200173,
+           0.1212278688704436,
+           0.13986345813731133,
+           0.1592595339861443,
+           0.18060504507379962,
+           0.205054447801432,
+           0.23369158060747025,
+           0.26749515800875584,
+           0.30730681739837995,
+           0.3538025889080263,
+           0.4074685734880368,
+           0.4685815088660614,
+           0.537194779845397,
+           0.6131302915761906,
+           0.6959764754279686,
+           0.7850925406479913,
+           0.879618925037237,
+           0.9784937384396453,
+           1.080474837940259,
+           1.1841670272174971,
+           1.2880537382032624,
+           1.3905324344843366,
+           1.4899528757591765,
+           1.5846573037169271,
+           1.6730215539775655,
+           1.7534960676959894,
+           1.824645770947745,
+           1.8851878103043311,
+           1.9340261786540411,
+           1.9702823352804488,
+           1.9933210168179476,
+           2.0027705487384853,
+           1.9985370977495227,
+           1.9808124507186102,
+           1.9500750619362306,
+           1.907084273857373,
+           1.8528677829103652,
+           1.788702587429667,
+           1.7160898151737525,
+           1.6367239792629962,
+           1.5524573499634002,
+           1.4652602521061147,
+           1.3771782010194988,
+           1.2902868710790687,
+           1.206645948303883,
+           1.1282529503835181,
+           1.0569981032673474,
+           0.9946213427899195,
+           0.9426724631940024,
+           0.9024753629356174,
+           0.875097243514141,
+           0.8613235015367285,
+           0.8616389205860663,
+           0.8762156209466928,
+           0.9049080654577052,
+           0.947255252577551,
+           1.002490057232025,
+           1.0695555103154983,
+           1.1471276429553279,
+           1.2336443658379863,
+           1.327339710821851,
+           1.426282635203258,
+           1.528419481439567,
+           1.631619099473071,
+           1.7337195771127143,
+           1.8325754876996883,
+           1.9261045543664388,
+           2.012332646810309,
+           2.089436069206812,
+           2.155780165608584,
+           2.2099533602276953,
+           2.2507958621244684,
+           2.2774223942548515,
+           2.289238452344404,
+           2.28594975607883,
+           2.2675647197696396,
+           2.234389937928485,
+           2.1870188489424787,
+           2.1263139031825973,
+           2.0533827164162117,
+           1.9695488315702911,
+           1.8763178382526666,
+           1.775339706930305,
+           1.6683682807028177,
+           1.557218930147543,
+           1.4437254142856102,
+           1.3296970024820676,
+           1.2168768978430808,
+           1.106902962848915,
+           1.001271683634711,
+           0.9013062221778798,
+           0.8081292979100216,
+           0.72264151468618,
+           0.6455056087960763,
+           0.5771369423284687,
+           0.5177004075075337,
+           0.4671137455894555,
+           0.42505712259256523,
+           0.390988647563483,
+           0.3641653711555712,
+           0.3436691666916026,
+           0.3284367759617303,
+           0.3172932007335364,
+           0.30898754081411467,
+           0.302230322462113,
+           0.29573132837569005,
+           0.2882369331401893,
+           0.27856596603277795,
+           0.26564316593965925,
+           0.24852935971103127,
+           0.22644758383189517,
+           0.19880447754477865,
+           0.16520640075230397,
+           0.12546986895868906,
+           0.07962604664241943,
+           0.02791919599577674,
+           -0.029200864029985594,
+           -0.09109207698280185,
+           -0.15693888414910556,
+           -0.2257758718717994,
+           -0.29651569840887754,
+           -0.36798055537163155,
+           -0.4389363254301674,
+           -0.5081285260742984,
+           -0.5743190806096985,
+           -0.6363229335063495,
+           -0.6930435283353653,
+           -0.7435061928335539,
+           -0.7868885264909762,
+           -0.822546960214822,
+           -0.850038753244582,
+           -0.8691388071983797,
+           -0.8798508080544526,
+           -0.8824123507398186,
+           -0.8772938542042908,
+           -0.8651912335562044,
+           -0.8470124560362096,
+           -0.8238582652720103,
+           -0.7969975094112008,
+           -0.7678376495479152,
+           -0.7378911517698028,
+           -0.7087385759238173,
+           -0.6819892640230197,
+           -0.6592405987757912,
+           -0.6420368462476513,
+           -0.6318286149951133,
+           -0.6299339565968131,
+           -0.6375020994464318,
+           -0.6554807497004518,
+           -0.6845878117489612,
+           -0.7252882774458337,
+           -0.7777769110832874,
+           -0.841967218693236,
+           -0.9174870390793954,
+           -1.0036809337298558,
+           -1.0996193873625784,
+           -1.2041146643850746,
+           -1.3157430031082482,
+           -1.4328726731812922,
+           -1.5536972762810672,
+           -1.6762735392046202,
+           -1.7985627354351879,
+           -1.918474778804544,
+           -2.0339139633787418,
+           -2.142825278911292,
+           -2.2432402122916058,
+           -2.333320952888439,
+           -2.4114019534206177,
+           -2.4760278572079484,
+           -2.5259868859647505,
+           -2.5603388877041557,
+           -2.5784373692872036,
+           -2.579944979657462,
+           -2.5648420644229306,
+           -2.5334280764311106,
+           -2.486315796347704,
+           -2.4244184878774435,
+           -2.348930280007838,
+           -2.2613002294325577,
+           -2.163200666210936,
+           -2.0564905610983977,
+           -1.9431747705512405,
+           -1.8253601123150311,
+           -1.7052092984031504,
+           -1.5848938013787366,
+           -1.4665467529949356,
+           -1.352216970887866,
+           -1.2438251792646016,
+           -1.1431234341435546,
+           -1.051658684071516,
+           -0.9707412953379614,
+           -0.9014192490550246,
+           -0.8444585790730192,
+           -0.8003304679658682,
+           -0.7692052569803607,
+           -0.7509534588594652,
+           -0.7451536939173324,
+           -0.7511073037873771,
+           -0.7678592379399146,
+           -0.7942246592563068,
+           -0.828820580270603,
+           -0.8701017244101448,
+           -0.9163997095109856,
+           -0.9659645763753804,
+           -1.0170076349387631,
+           -1.0677445758799733,
+           -1.1164377967671377,
+           -1.1614369189642757,
+           -1.2012165237723826,
+           -1.2344102122650158,
+           -1.2598401910388817,
+           -1.2765417031355821,
+           -1.283781756729619,
+           -1.2810717504503433,
+           -1.2681737497278374,
+           -1.2451003294191703,
+           -1.212108060152286,
+           -1.169684875265806,
+           -1.1185317079479966,
+           -1.0595389303856395,
+           -0.9937582548937363,
+           -0.9223708679373982,
+           -0.8466526589424278,
+           -0.7679374745901345,
+           -0.6875793742332653,
+           -0.6069148820828838,
+           -0.5272262264564671,
+           -0.4497065258385019,
+           -0.37542782661152596,
+           -0.3053128195028567,
+           -0.2401109630698926,
+           -0.18037962544759004,
+           -0.12647072309751484,
+           -0.07852319080564121,
+           -0.036461464351740136,
+           -3.1496841126988764e-16
+          ],
+          [
+           0,
+           0.029539478126739724,
+           0.055051871466536555,
+           0.07743310410104638,
+           0.09769888889980292,
+           0.11695340367531902,
+           0.1363553503817283,
+           0.157082304407978,
+           0.18029430742822758,
+           0.20709767926088896,
+           0.23851002117224313,
+           0.2754273550888772,
+           0.3185942909319974,
+           0.3685780390446793,
+           0.4257469883191181,
+           0.4902544555474123,
+           0.5620280805927678,
+           0.6407651984869864,
+           0.725934367103965,
+           0.8167830714678254,
+           0.912351466993547,
+           1.0114918680290887,
+           1.1128935389086692,
+           1.215112206112485,
+           1.31660358557715,
+           1.4157601118870018,
+           1.5109499687477495,
+           1.6005574550555421,
+           1.6830236797301072,
+           1.7568865623900496,
+           1.8208191263985114,
+           1.8736651056496587,
+           1.9144709459189726,
+           1.9425133642670527,
+           1.9573217338905056,
+           1.9586946844451587,
+           1.946710446245962,
+           1.9217306174964632,
+           1.8843971931263104,
+           1.8356228580020904,
+           1.7765747121826683,
+           1.7086517574462978,
+           1.633456628528451,
+           1.552762195555008,
+           1.4684737924820033,
+           1.3825879367628517,
+           1.297148495195834,
+           1.2142013177013482,
+           1.1357484029441203,
+           1.0637026761574344,
+           0.9998444497830562,
+           0.9457806017932207,
+           0.9029074456306454,
+           0.8723781810295308,
+           0.8550757085897055,
+           0.8515914654280268,
+           0.8622107975584739,
+           0.8869052302862499,
+           0.9253318345865494,
+           0.9768397191424064,
+           1.0404835085295996,
+           1.1150435020750182,
+           1.1990520492160361,
+           1.2908255296130928,
+           1.3885011934051963,
+           1.4900780020774531,
+           1.5934605162207631,
+           1.6965048052882201,
+           1.797065308008031,
+           1.8930415515105903,
+           1.9824236429458078,
+           2.063335479239481,
+           2.134074677857342,
+           2.1931483125854627,
+           2.2393036413841254,
+           2.2715531357825496,
+           2.2891932600359928,
+           2.291816599949401,
+           2.279317102155631,
+           2.2518883507731795,
+           2.210014975687684,
+           2.1544574511099484,
+           2.0862307005464027,
+           2.006577071038607,
+           1.916934371921601,
+           1.8188997882111608,
+           1.7141905732901046,
+           1.6046024975628785,
+           1.4919670774857001,
+           1.378108631759547,
+           1.2648022080266,
+           1.15373339430837,
+           1.0464609754709542,
+           0.9443833176181605,
+           0.8487092644924256,
+           0.7604342122293744,
+           0.680321895150487,
+           0.6088922690647112,
+           0.5464157234628622,
+           0.49291369391973155,
+           0.44816558497471237,
+           0.4117217557643502,
+           0.38292216966715414,
+           0.3609201689468722,
+           0.34471070932413705,
+           0.3331622806846644,
+           0.32505165142205855,
+           0.3191005073862938,
+           0.31401301367726897,
+           0.30851330959978956,
+           0.3013819543717396,
+           0.2914903734083635,
+           0.2778324113238509,
+           0.25955217672470854,
+           0.23596746337943292,
+           0.20658814988274093,
+           0.17112911248679796,
+           0.12951732996812715,
+           0.08189301156903227,
+           0.028604735330061647,
+           -0.029801259452008795,
+           -0.0925973293167364,
+           -0.15889579206927582,
+           -0.22767482581794243,
+           -0.29780820814141556,
+           -0.3680981009377824,
+           -0.43731000588861335,
+           -0.5042089572593715,
+           -0.5675959844457513,
+           -0.6263438671554604,
+           -0.6794312216542497,
+           -0.725973996739963,
+           -0.7652535220534018,
+           -0.7967403374062434,
+           -0.820113137861639,
+           -0.835272292695006,
+           -0.8423475340034666,
+           -0.8416995591727804,
+           -0.8339154469240463,
+           -0.8197979453389221,
+           -0.8003488481058624,
+           -0.7767468282585888,
+           -0.7503202430232929,
+           -0.722515555394366,
+           -0.6948621343632777,
+           -0.6689342933612894,
+           -0.6463115029341807,
+           -0.6285377669608228,
+           -0.6170811804455818,
+           -0.6132946902565796,
+           -0.6183790579777202,
+           -0.6333489767588024,
+           -0.6590032227771412,
+           -0.6958996283577018,
+           -0.7443355501868455,
+           -0.8043343751507023,
+           -0.8756384613220527,
+           -0.9577087560553755,
+           -1.0497311708444748,
+           -1.1506296275420302,
+           -1.259085526803823,
+           -1.3735632312462804,
+           -1.4923410067148837,
+           -1.6135467289517478,
+           -1.7351975432089084,
+           -1.855242563968672,
+           -1.9716076234207083,
+           -2.082241022689681,
+           -2.1851592104068094,
+           -2.2784913098524857,
+           -2.360521438706105,
+           -2.429727813920873,
+           -2.484817707261301,
+           -2.524757412861797,
+           -2.5487965044859644,
+           -2.5564857941833523,
+           -2.5476885525110573,
+           -2.5225847098129957,
+           -2.481667924361866,
+           -2.4257355724262375,
+           -2.3558718834118566,
+           -2.2734246060533065,
+           -2.179975745237689,
+           -2.0773070496900057,
+           -1.9673610550199805,
+           -1.8521985915042019,
+           -1.7339537489115617,
+           -1.6147873496685774,
+           -1.496840015285276,
+           -1.382185918424338,
+           -1.2727882941405375,
+           -1.1704577391314819,
+           -1.0768142584456326,
+           -0.9932539267139788,
+           -0.9209209178935346,
+           -0.860685526525547,
+           -0.8131286578451586,
+           -0.7785331073147091,
+           -0.7568817861397735,
+           -0.7478628820869796,
+           -0.7508817785503913,
+           -0.765079393375067,
+           -0.7893564463804342,
+           -0.8224030245446988,
+           -0.8627326898104588,
+           -0.908720269446486,
+           -0.9586423853729845,
+           -1.0107197188140922,
+           -1.0631599714847497,
+           -1.1142004750342744,
+           -1.1621494168054514,
+           -1.205424691635779,
+           -1.2425894553112626,
+           -1.2723835436701663,
+           -1.2937500299780613,
+           -1.3058563192932662,
+           -1.308109318922653,
+           -1.300164375193997,
+           -1.2819278248455017,
+           -1.2535531703941407,
+           -1.215431048865597,
+           -1.1681733182570964,
+           -1.1125917322028485,
+           -1.0496718068914104,
+           -0.9805426020375315,
+           -0.9064432367318073,
+           -0.828687038847878,
+           -0.7486242814814451,
+           -0.6676044903111129,
+           -0.5869393111043998,
+           -0.5078669067694471,
+           -0.43151880893142197,
+           -0.3588900811667133,
+           -0.29081356151816085,
+           -0.22793884304392842,
+           -0.17071652570818685,
+           -0.11938813410410448,
+           -0.07398194684347424,
+           -0.03431482873161225,
+           -2.9641798927082116e-16
+          ],
+          [
+           0,
+           0.02788293139352952,
+           0.05218641524862888,
+           0.07386232259483275,
+           0.09396485279500823,
+           0.11361793293564773,
+           0.1339805239905285,
+           0.1562107624698389,
+           0.18142989845761726,
+           0.21068699849821673,
+           0.24492536450216879,
+           0.28495157811378014,
+           0.33140801484338733,
+           0.3847495853332195,
+           0.4452253545643997,
+           0.5128655662872892,
+           0.5874744625617752,
+           0.6686291404748594,
+           0.7556845335736174,
+           0.8477844482002754,
+           0.9438784287079589,
+           1.0427440744139536,
+           1.1430142889349173,
+           1.2432088128520624,
+           1.3417692767739124,
+           1.4370969167105831,
+           1.5275920196946529,
+           1.6116941167034378,
+           1.6879219135065051,
+           1.7549119488238625,
+           1.8114549932505697,
+           1.8565292512680767,
+           1.8893295011878357,
+           1.9092914023335965,
+           1.916110312890379,
+           1.9097540928616927,
+           1.8904695112874017,
+           1.8587820317407378,
+           1.815488911342497,
+           1.761645712135637,
+           1.6985464856186014,
+           1.6276980475373264,
+           1.550788906811652,
+           1.4696535460768367,
+           1.3862328684281893,
+           1.3025317226396675,
+           1.220574494932889,
+           1.1423598073827617,
+           1.0698153899242109,
+           1.0047541939518274,
+           0.9488327905961529,
+           0.9035130464695996,
+           0.8700279951790981,
+           0.8493527259751604,
+           0.8421809938742887,
+           0.8489081212762293,
+           0.8696206127485225,
+           0.9040927458646661,
+           0.9517902356140479,
+           1.0118809019709114,
+           1.0832521038003131,
+           1.16453454144046,
+           1.2541318789472382,
+           1.3502554988010684,
+           1.4509635802197283,
+           1.5542035900500926,
+           1.6578571950062333,
+           1.7597865477224888,
+           1.8578808680531835,
+           1.950102236012455,
+           2.0345295338075284,
+           2.1093995210375196,
+           2.1731440981422554,
+           2.2244229068304575,
+           2.2621505301794764,
+           2.285517686570062,
+           2.2940059573637295,
+           2.2873957446656945,
+           2.265767318804282,
+           2.2294949812967437,
+           2.1792345339964325,
+           2.1159044047985316,
+           2.0406609308282055,
+           1.954868437784809,
+           1.8600648757291915,
+           1.7579238741423568,
+           1.6502141600925888,
+           1.5387573409006052,
+           1.4253850854464336,
+           1.311896745491238,
+           1.2000184399974636,
+           1.0913645819605722,
+           0.9874027598733396,
+           0.8894227963770605,
+           0.7985106972059366,
+           0.7155280769824383,
+           0.6410975079708625,
+           0.5755940870804809,
+           0.5191433590143821,
+           0.47162557342657396,
+           0.4326860952760193,
+           0.4017516342071629,
+           0.3780518145564287,
+           0.3606454760612946,
+           0.3484509797865123,
+           0.34027969702919003,
+           0.334871783393203,
+           0.330933287671858,
+           0.3271736169044393,
+           0.3223423756253405,
+           0.31526461892622915,
+           0.3048736048987866,
+           0.29024020110454024,
+           0.2705981901367424,
+           0.24536482877099958,
+           0.2141561408451336,
+           0.17679656265888852,
+           0.13332270781061908,
+           0.08398117222593443,
+           0.029220455776129813,
+           -0.03032276961707756,
+           -0.0938426680326355,
+           -0.16038800871500808,
+           -0.22889005689597833,
+           -0.29819383882900463,
+           -0.3670919447749948,
+           -0.43435996629329526,
+           -0.4987926199597658,
+           -0.5592395896936456,
+           -0.6146401247534512,
+           -0.6640554600617512,
+           -0.706698179118464,
+           -0.7419577160367954,
+           -0.7694212902871912,
+           -0.7888896831397194,
+           -0.8003873956667368,
+           -0.8041668712249461,
+           -0.8007066169878473,
+           -0.7907032155333049,
+           -0.7750573747676179,
+           -0.7548543186204744,
+           -0.7313389680790576,
+           -0.7058864985180918,
+           -0.67996898146142,
+           -0.6551189237646272,
+           -0.632890602049498,
+           -0.6148201528566632,
+           -0.6023854177704593,
+           -0.5969665566590693,
+           -0.5998084307326219,
+           -0.611985720551492,
+           -0.6343716832431933,
+           -0.6676113694425735,
+           -0.7121000158626687,
+           -0.767967206462105,
+           -0.8350672568902754,
+           -0.9129761266425849,
+           -1.0009950048278877,
+           -1.0981605525360099,
+           -1.2032616215088836,
+           -1.3148621091966317,
+           -1.4313294582697684,
+           -1.5508681680312058,
+           -1.6715575594237027,
+           -1.7913929275960396,
+           -1.9083291289732265,
+           -2.0203255856648483,
+           -2.1253916504730412,
+           -2.221631261759245,
+           -2.307285829399202,
+           -2.3807743307645417,
+           -2.4407296582485842,
+           -2.4860303458238,
+           -2.515826909422558,
+           -2.529562161988758,
+           -2.5269850058108796,
+           -2.5081573587831634,
+           -2.4734540338139777,
+           -2.423555557759564,
+           -2.3594340839429244,
+           -2.2823327164423133,
+           -2.1937387209077377,
+           -2.0953512418764686,
+           -1.9890442768772703,
+           -1.8768257698686055,
+           -1.7607937780226333,
+           -1.6430907343267058,
+           -1.525856872274096,
+           -1.4111838970065826,
+           -1.3010699792336666,
+           -1.197377114307879,
+           -1.1017918298368303,
+           -1.0157901426289455,
+           -0.9406075616450738,
+           -0.8772148105320792,
+           -0.8262998042796342,
+           -0.7882562629865074,
+           -0.7631791853693198,
+           -0.7508672394275409,
+           -0.7508319616389402,
+           -0.762313493259408,
+           -0.7843024267129398,
+           -0.8155671904704984,
+           -0.8546862707415047,
+           -0.9000844558862818,
+           -0.9500721974081251,
+           -1.0028871118985752,
+           -1.0567366030269714,
+           -1.1098405626226686,
+           -1.1604731155069101,
+           -1.2070024037685663,
+           -1.2479274617921876,
+           -1.2819113120806456,
+           -1.3078095117410886,
+           -1.3246934978772493,
+           -1.3318682140541747,
+           -1.3288836460948892,
+           -1.315540050059793,
+           -1.2918868144730533,
+           -1.2582150587137255,
+           -1.2150442259942582,
+           -1.1631030786081091,
+           -1.1033056414342275,
+           -1.0367227636120298,
+           -0.9645500747861686,
+           -0.8880731987472213,
+           -0.8086311515505402,
+           -0.7275788917279655,
+           -0.6462500060596086,
+           -0.5659205052092702,
+           -0.48777466963882143,
+           -0.4128738285152517,
+           -0.34212887431706857,
+           -0.27627721559977936,
+           -0.21586475246538073,
+           -0.1612333267111102,
+           -0.11251395478633003,
+           -0.06962600022266856,
+           -0.0322822869690475,
+           -2.7911058610218946e-16
+          ],
+          [
+           0,
+           0.026386230323860796,
+           0.04966431475785938,
+           0.07083263881123551,
+           0.09097384721436517,
+           0.11122127062038671,
+           0.13272379259200984,
+           0.15661009882560287,
+           0.18395326848312893,
+           0.21573666079558043,
+           0.2528220189159993,
+           0.29592065809949775,
+           0.34556852803334315,
+           0.40210584145773104,
+           0.4656618455491471,
+           0.5361451817804772,
+           0.6132401374057223,
+           0.6964089409241794,
+           0.7849000986531082,
+           0.8777626137902966,
+           0.9738657770091828,
+           1.071924072551067,
+           1.1705266096380842,
+           1.2681703692362885,
+           1.3632964538069001,
+           1.4543284453223806,
+           1.5397119166234974,
+           1.6179541047355297,
+           1.6876627430375803,
+           1.7475830625649236,
+           1.7966320109707332,
+           1.8339287999103515,
+           1.8588209763688022,
+           1.8709053186966564,
+           1.8700429813025055,
+           1.8563684500722735,
+           1.830292020268505,
+           1.7924956662340852,
+           1.7439223338081262,
+           1.6857588479724126,
+           1.6194127858907774,
+           1.5464838152766176,
+           1.4687301362072538,
+           1.3880307876583082,
+           1.3063446850816782,
+           1.2256673396618858,
+           1.1479862713297384,
+           1.075236164620437,
+           1.0092548280660896,
+           0.951741003664094,
+           0.904215033350166,
+           0.8679833252414465,
+           0.8441074752192161,
+           0.83337879127836,
+           0.8362988415842928,
+           0.853066505403653,
+           0.8835718524464679,
+           0.9273970144025945,
+           0.983824046504119,
+           1.0518496108336934,
+           1.130206150868606,
+           1.2173890723506022,
+           1.3116893027608663,
+           1.411230473933927,
+           1.5140098627712748,
+           1.6179421362779878,
+           1.7209048813962335,
+           1.8207848589378037,
+           1.915523905311031,
+           2.003163416056901,
+           2.081886381181001,
+           2.150056002990573,
+           2.206250011112105,
+           2.2492898944995963,
+           2.2782643939549905,
+           2.292546737926097,
+           2.2918052557022586,
+           2.2760071618798943,
+           2.2454154702041227,
+           2.2005791595895348,
+           2.1423168762587443,
+           2.071694609581198,
+           1.989997921607688,
+           1.8986994380215572,
+           1.79942241817722,
+           1.693901311425345,
+           1.583940273895184,
+           1.4713706627421346,
+           1.358008542594841,
+           1.2456132311957024,
+           1.1358478782956012,
+           1.030243014634424,
+           0.9301639278089767,
+           0.8367826210555062,
+           0.7510549920209281,
+           0.6737037344755313,
+           0.6052073200102086,
+           0.5457952627280999,
+           0.4954497116422688,
+           0.45391325688338824,
+           0.42070268085900636,
+           0.39512823804369696,
+           0.3763179107771088,
+           0.3632459666780236,
+           0.35476503905070084,
+           0.3496408675245982,
+           0.3465887741820124,
+           0.3443109120844156,
+           0.3415333093068399,
+           0.3370417426137887,
+           0.32971551042032793,
+           0.31855823372528974,
+           0.3027248947377294,
+           0.28154442385088174,
+           0.2545372638606877,
+           0.22142747285731598,
+           0.1821490706610123,
+           0.13684648437966213,
+           0.08586910280692014,
+           0.029760103045033296,
+           -0.03076013797152274,
+           -0.09481559324167035,
+           -0.16140051354532026,
+           -0.22940903578599384,
+           -0.29766767778243963,
+           -0.36496984937570326,
+           -0.4301114559401478,
+           -0.49192664029487515,
+           -0.5493227033858336,
+           -0.6013132631123468,
+           -0.6470487538485341,
+           -0.6858434354941193,
+           -0.7171981686319349,
+           -0.7408183193804976,
+           -0.7566262811313337,
+           -0.7647682374539602,
+           -0.7656149375944258,
+           -0.7597564094868603,
+           -0.7479906911769003,
+           -0.7313068160880082,
+           -0.710862436743276,
+           -0.6879566116100336,
+           -0.6639984071085955,
+           -0.640472078276557,
+           -0.618899684255557,
+           -0.6008020662819484,
+           -0.58765916435404,
+           -0.580870672926104,
+           -0.5817180351567929,
+           -0.5913287493536771,
+           -0.6106439108675685,
+           -0.6403898389736539,
+           -0.6810545429883157,
+           -0.7328696673089221,
+           -0.7957984240114078,
+           -0.8695298772958525,
+           -0.9534797899698058,
+           -1.0467980820886948,
+           -1.1483827897753822,
+           -1.2569002521182133,
+           -1.3708110998605503,
+           -1.488401475167717,
+           -1.6078187806798838,
+           -1.727111141599198,
+           -1.8442696695800906,
+           -1.9572725440826126,
+           -2.0641298774638934,
+           -2.16292830569514,
+           -2.2518742478617018,
+           -2.329334804560207,
+           -2.393875317348309,
+           -2.444292687309156,
+           -2.4796436487569973,
+           -2.4992673117808053,
+           -2.5028014218613666,
+           -2.4901919329493265,
+           -2.461695648564957,
+           -2.4178758498343633,
+           -2.359590995916245,
+           -2.287976746946768,
+           -2.2044217184297956,
+           -2.1105375250600242,
+           -2.0081238076587056,
+           -1.899129055924227,
+           -1.7856081391580072,
+           -1.6696775346054857,
+           -1.5534692966750658,
+           -1.4390848387725679,
+           -1.3285496021387493,
+           -1.2237696628585517,
+           -1.1264912797132989,
+           -1.0382643129782285,
+           -0.9604103494251282,
+           -0.8939962540137233,
+           -0.8398137368724949,
+           -0.7983653784229992,
+           -0.769857399470072,
+           -0.7541993005897948,
+           -0.751010330177323,
+           -0.7596325771017074,
+           -0.7791503260442549,
+           -0.8084151651174254,
+           -0.8460761998817553,
+           -0.8906146086813392,
+           -0.9403816741796911,
+           -0.9936393474954147,
+           -1.0486023462730152,
+           -1.10348075765922,
+           -1.1565221121578655,
+           -1.2060519147472037,
+           -1.2505116648754686,
+           -1.2884934658037466,
+           -1.3187704144582304,
+           -1.3403220731683216,
+           -1.3523544516060995,
+           -1.3543140677011531,
+           -1.345895806749017,
+           -1.32704445458843,
+           -1.297949939672727,
+           -1.2590364761365191,
+           -1.2109459516435368,
+           -1.1545160461257165,
+           -1.0907536969601945,
+           -1.020804639480835,
+           -0.9459198461943887,
+           -0.8674197613553075,
+           -0.7866572778689636,
+           -0.7049804296402048,
+           -0.6236957738695859,
+           -0.5440334144515515,
+           -0.46711457019571023,
+           -0.3939225213255456,
+           -0.3252776764316113,
+           -0.2618173921161016,
+           -0.20398105177699463,
+           -0.15200077155191966,
+           -0.10589795389799374,
+           -0.06548575637427632,
+           -0.03037738879990989,
+           -2.6315483490745805e-16
+          ],
+          [
+           0,
+           0.025057210121703827,
+           0.0474965605200613,
+           0.06835324037973478,
+           0.08872819524129517,
+           0.10975388931152423,
+           0.1325590463145943,
+           0.15823331566365645,
+           0.18779281445873552,
+           0.22214747513935848,
+           0.2620710840406126,
+           0.3081748287234123,
+           0.3608850834527971,
+           0.42042605479460987,
+           0.48680778568162497,
+           0.5598198795670235,
+           0.6390311598717235,
+           0.7237953275261692,
+           0.8132625248465116,
+           0.9063965611694716,
+           1.001997408461972,
+           1.0987284372490964,
+           1.1951477381679323,
+           1.2897427654409284,
+           1.3809674483608314,
+           1.4672808478150137,
+           1.547186388750728,
+           1.619270677525595,
+           1.6822409159290783,
+           1.7349599513127427,
+           1.776478054122441,
+           1.8060605889722345,
+           1.8232108414500718,
+           1.8276873777794775,
+           1.819515445484822,
+           1.7989920671191428,
+           1.7666846323842496,
+           1.723422952834013,
+           1.6702849038872447,
+           1.6085759371199362,
+           1.539802897839494,
+           1.4656427249929158,
+           1.3879067389920587,
+           1.308501334844868,
+           1.229385990260358,
+           1.1525295688226291,
+           1.0798659451148394,
+           1.013250000606924,
+           0.9544150355998943,
+           0.904932613569262,
+           0.8661758005206052,
+           0.8392866847218539,
+           0.8251489632494926,
+           0.8243662635545849,
+           0.837246733571055,
+           0.8637942860118111,
+           0.9037067250137716,
+           0.9563808200253315,
+           1.0209242267488328,
+           1.0961739920729592,
+           1.180721223220917,
+           1.2729413546158581,
+           1.371029312798291,
+           1.4730387633631674,
+           1.5769245271481493,
+           1.6805871781500157,
+           1.7819187846856366,
+           1.878848729377385,
+           1.9693885432466935,
+           2.051674714532924,
+           2.1240084831789887,
+           2.1848917059902218,
+           2.233057973448375,
+           2.267498274682617,
+           2.2874806393220006,
+           2.2925633306304944,
+           2.2826013198821054,
+           2.2577459335575885,
+           2.218437728680153,
+           2.1653928134536087,
+           2.099582986373489,
+           2.0222102133505673,
+           1.934676095561204,
+           1.838547097495008,
+           1.7355164021927025,
+           1.6273633366197309,
+           1.5159113627041647,
+           1.4029856575609454,
+           1.2903713092171658,
+           1.1797731317575508,
+           1.0727780568599987,
+           0.9708209884280844,
+           0.8751549152647912,
+           0.7868259658116443,
+           0.7066539617110134,
+           0.6352188865472005,
+           0.5728535361123973,
+           0.5196424606862263,
+           0.4754271520081777,
+           0.43981727179658253,
+           0.4122075687033777,
+           0.3917999902136782,
+           0.3776303686791908,
+           0.3685989495574438,
+           0.3635039377464813,
+           0.3610771669103169,
+           0.36002094860314104,
+           0.35904513396285154,
+           0.35690342129565233,
+           0.3524279679351036,
+           0.34456141363871357,
+           0.332385494194476,
+           0.31514551599662594,
+           0.2922700727458173,
+           0.26338551130859383,
+           0.2283247919232409,
+           0.18713053484780745,
+           0.14005219747810946,
+           0.08753747906281818,
+           0.030218200526484565,
+           -0.031108949232381354,
+           -0.09550627551780638,
+           -0.1619229033149996,
+           -0.2292258173831803,
+           -0.2962332839923844,
+           -0.36174975842711354,
+           -0.4246013424515927,
+           -0.4836708400071542,
+           -0.5379314679123286,
+           -0.5864783110656949,
+           -0.6285566678053244,
+           -0.6635865092605651,
+           -0.6911823747901961,
+           -0.7111681414763241,
+           -0.7235862362302833,
+           -0.7287010010864323,
+           -0.7269960721410127,
+           -0.7191657865628178,
+           -0.7061007862782791,
+           -0.6888681374224307,
+           -0.668686427641914,
+           -0.6468964352105951,
+           -0.6249280813189897,
+           -0.604264476828028,
+           -0.5864039546700478,
+           -0.5728210368660179,
+           -0.5649273192869646,
+           -0.564033266886294,
+           -0.5713118968459809,
+           -0.587765287212205,
+           -0.614194785057132,
+           -0.6511757024977313,
+           -0.6990371830896658,
+           -0.7578477977595872,
+           -0.8274072915497835,
+           -0.9072447534003611,
+           -0.9966233246462691,
+           -1.0945514017136666,
+           -1.1998001286162885,
+           -1.3109268192319286,
+           -1.4263038018399243,
+           -1.5441520426874604,
+           -1.662578784807415,
+           -1.7796183359470379,
+           -1.8932750578556383,
+           -2.0015675503851837,
+           -2.1025729893854366,
+           -2.1944705681335677,
+           -2.2755830083170685,
+           -2.344415148049212,
+           -2.399688680080703,
+           -2.4403722017244736,
+           -2.4657058469187674,
+           -2.4752198976955238,
+           -2.468746914031648,
+           -2.4464270742075604,
+           -2.408706578663535,
+           -2.356329135020824,
+           -2.290320706415812,
+           -2.2119678655781545,
+           -2.1227902492652797,
+           -2.0245077480399356,
+           -1.9190031915263166,
+           -1.8082813961582456,
+           -1.6944255284402432,
+           -1.5795517997917452,
+           -1.4657635476099369,
+           -1.3551057703418128,
+           -1.2495211717974373,
+           -1.150808731989514,
+           -1.0605857593972778,
+           -0.9802542942695245,
+           -0.910972626507762,
+           -0.8536325674175236,
+           -0.8088429752384722,
+           -0.7769198832844,
+           -0.7578834204470156,
+           -0.7514615506384674,
+           -0.7571004944580872,
+           -0.7739815369564653,
+           -0.8010437737208294,
+           -0.8370122073086903,
+           -0.8804304807126371,
+           -0.9296974270771428,
+           -0.9831065278917457,
+           -1.0388873074281626,
+           -1.0952476507862672,
+           -1.150416017483882,
+           -1.202682532368068,
+           -1.250437970416245,
+           -1.2922097107940558,
+           -1.3266938168112097,
+           -1.3527825000821223,
+           -1.3695863466700227,
+           -1.376450817251193,
+           -1.3729666790000572,
+           -1.3589741803103883,
+           -1.334560936793628,
+           -1.3000536543038907,
+           -1.2560039681119617,
+           -1.203168822975415,
+           -1.1424859531180347,
+           -1.0750451407196202,
+           -1.0020560334802642,
+           -0.9248133836613197,
+           -0.8446606307262184,
+           -0.7629527858724857,
+           -0.6810195885186725,
+           -0.6001298919554194,
+           -0.521458198275054,
+           -0.44605420235266974,
+           -0.37481612263867675,
+           -0.3084684949555845,
+           -0.24754498697502034,
+           -0.19237665861278067,
+           -0.1430859505942766,
+           -0.09958653354585069,
+           -0.06158899696597667,
+           -0.028612205205776117,
+           -2.4864427753583253e-16
+          ],
+          [
+           0,
+           0.023901916889567956,
+           0.045690448558034655,
+           0.06642769579219036,
+           0.08722275572524443,
+           0.1091971292589808,
+           0.13344964501347684,
+           0.16102184308787026,
+           0.19286475165899913,
+           0.22980795521445288,
+           0.27253179585865556,
+           0.3215434700742619,
+           0.37715768454323234,
+           0.439482418607763,
+           0.5084102105927493,
+           0.5836152437947486,
+           0.6645563590257869,
+           0.7504859679356043,
+           0.8404646887744908,
+           0.9333813776554675,
+           1.0279780874909668,
+           1.1228793571897313,
+           1.2166251187019257,
+           1.3077064120323811,
+           1.3946030209077853,
+           1.475822086391384,
+           1.5499367238486816,
+           1.6156236611555972,
+           1.671698933174953,
+           1.717150708961834,
+           1.7511683929397073,
+           1.773167227879551,
+           1.7828077338289605,
+           1.7800094405968456,
+           1.7649585089889785,
+           1.738108984339245,
+           1.7001775813448694,
+           1.6521320579601977,
+           1.5951733942117563,
+           1.530712145353283,
+           1.4603394839733335,
+           1.385793578888745,
+           1.3089220765817515,
+           1.231641550615248,
+           1.1558948633824808,
+           1.0836074407142386,
+           1.0166434918361047,
+           0.9567632140914416,
+           0.9055820034890716,
+           0.8645326488864455,
+           0.8348314204806303,
+           0.8174488738410253,
+           0.8130860811195599,
+           0.8221568739548523,
+           0.8447765410180514,
+           0.880757270559893,
+           0.9296104684144676,
+           0.9905559185819683,
+           1.0625375907239791,
+           1.1442457406240276,
+           1.2341447997482988,
+           1.3305064121389052,
+           1.4314468543443604,
+           1.5349679699226721,
+           1.6390006667766917,
+           1.7414499652224802,
+           1.8402405487117826,
+           1.9333617583947023,
+           2.0189109874652744,
+           2.0951344711040374,
+           2.160464531826088,
+           2.213552426578947,
+           2.25329604887924,
+           2.2788618640003646,
+           2.289700594661244,
+           2.285556325398287,
+           2.266468852135022,
+           2.2327692655212257,
+           2.1850689184344207,
+           2.124242085671472,
+           2.051402773466038,
+           1.9678762744112352,
+           1.8751661863019524,
+           1.7749177183682137,
+           1.6688781928287206,
+           1.5588557116402177,
+           1.4466769963003816,
+           1.334145421720238,
+           1.2230002532710036,
+           1.1148780595040162,
+           1.0112772127240353,
+           0.9135263071328984,
+           0.8227572217637021,
+           0.739883435497913,
+           0.6655840671275732,
+           0.6002939680705723,
+           0.5442000426133327,
+           0.4972438142612533,
+           0.4591301008221407,
+           0.42934150911310864,
+           0.4071583164354299,
+           0.39168317376501544,
+           0.38186994822389436,
+           0.37655592271882576,
+           0.37449649109769156,
+           0.37440142971512547,
+           0.3749717922928475,
+           0.37493646519483814,
+           0.373087434892236,
+           0.368312858034944,
+           0.35962708614318317,
+           0.34619687987557923,
+           0.32736314998018956,
+           0.30265768077173455,
+           0.2718144242690549,
+           0.23477509560176424,
+           0.19168894933178018,
+           0.14290676815007616,
+           0.08896924615119771,
+           0.0305900947371429,
+           -0.03136566353693696,
+           -0.09590762266691516,
+           -0.16194944198645653,
+           -0.2283410236338035,
+           -0.2939025547170488,
+           -0.35745950079327243,
+           -0.4178776113105429,
+           -0.4740969958028432,
+           -0.5251643519398864,
+           -0.5702624724708061,
+           -0.6087362265218988,
+           -0.6401142999053988,
+           -0.6641260868357765,
+           -0.6807132490301886,
+           -0.6900355944866265,
+           -0.6924710738592865,
+           -0.6886098436190151,
+           -0.6792424982839725,
+           -0.665342725066631,
+           -0.6480447794876719,
+           -0.6286163161757659,
+           -0.6084272317576237,
+           -0.5889152833177684,
+           -0.5715493336422817,
+           -0.5577911410921309,
+           -0.5490566557399914,
+           -0.546677803177789,
+           -0.5518657325866313,
+           -0.5656764762950459,
+           -0.5889799147875446,
+           -0.6224328652127051,
+           -0.6664570146950152,
+           -0.7212223045173418,
+           -0.7866362403164328,
+           -0.8623394600241666,
+           -0.9477077389117898,
+           -1.041860453503404,
+           -1.1436753672062567,
+           -1.2518094441889926,
+           -1.3647252481986465,
+           -1.480722343365177,
+           -1.5979729880762454,
+           -1.7145613038622378,
+           -1.8285250116500402,
+           -1.9378987599840873,
+           -2.0407580256019333,
+           -2.1352625472380846,
+           -2.2196982592568006,
+           -2.292516722605174,
+           -2.3523711059343944,
+           -2.398147848260505,
+           -2.4289932343550675,
+           -2.444334232774068,
+           -2.443893081186436,
+           -2.427695251190623,
+           -2.3960705815311627,
+           -2.3496475307400497,
+           -2.2893406637878435,
+           -2.216331648355865,
+           -2.132044190912341,
+           -2.038113487126487,
+           -1.936350891768782,
+           -1.8287046269413043,
+           -1.7172174414916939,
+           -1.6039822065010254,
+           -1.4910964800522408,
+           -1.3806170979136405,
+           -1.2745158447537326,
+           -1.1746372331046073,
+           -1.0826593651971153,
+           -1.0000587772937837,
+           -0.9280800691065834,
+           -0.8677110046960477,
+           -0.8196636387613104,
+           -0.7843618766995376,
+           -0.7619357218065895,
+           -0.7522223023045418,
+           -0.7547736084464137,
+           -0.7688707097320508,
+           -0.7935440681788203,
+           -0.8275994193772399,
+           -0.869648562226589,
+           -0.9181442839554552,
+           -0.9714185520407966,
+           -1.0277230312201364,
+           -1.085270933682639,
+           -1.1422791848858747,
+           -1.1970098868302095,
+           -1.2478100849673255,
+           -1.2931488935423423,
+           -1.3316511057914926,
+           -1.3621265081939224,
+           -1.3835942295426504,
+           -1.3953015831315572,
+           -1.3967370006390158,
+           -1.3876368058018995,
+           -1.36798573097263,
+           -1.3380112362655272,
+           -1.2981718453245417,
+           -1.2491398599453893,
+           -1.1917789541855854,
+           -1.1271172737722273,
+           -1.056316775483222,
+           -0.9806396310599422,
+           -0.9014125889148005,
+           -0.8199902327660992,
+           -0.7377180982791383,
+           -0.6558966063322992,
+           -0.5757467447865652,
+           -0.4983783803522823,
+           -0.4247620096420267,
+           -0.3557046656531924,
+           -0.29183058512585114,
+           -0.23356711630571855,
+           -0.18113620882030465,
+           -0.13455168115565402,
+           -0.09362231031602476,
+           -0.057960636488908014,
+           -0.02699722677031896,
+           -2.35656621128742e-16
+          ],
+          [
+           0,
+           0.0229245699457807,
+           0.044249554173665155,
+           0.06505398941607013,
+           0.08644506813270268,
+           0.10952349876301791,
+           0.13534891528583054,
+           0.16490626771778913,
+           0.19907410127686845,
+           0.23859558468937364,
+           0.28405307870617835,
+           0.3358469460522587,
+           0.39417919601512796,
+           0.45904243339446593,
+           0.5302144456910377,
+           0.6072586176265872,
+           0.6895302120055978,
+           0.7761884043405991,
+           0.8662138093944022,
+           0.9584310946222484,
+           1.051536142054331,
+           1.1441270998366568,
+           1.2347385605147578,
+           1.321878017869446,
+           1.4040636898981544,
+           1.4798627540583555,
+           1.5479290232642253,
+           1.6070390978734335,
+           1.6561260599288765,
+           1.6943098305352349,
+           1.7209233881669914,
+           1.7355341430787607,
+           1.7379598784621875,
+           1.7282787997521094,
+           1.7068333763271448,
+           1.674227811267717,
+           1.6313191310980135,
+           1.5792020446889985,
+           1.5191878748456298,
+           1.4527780137144706,
+           1.3816324903577837,
+           1.3075343622263544,
+           1.2323507487395609,
+           1.1579914120729857,
+           1.0863658553648163,
+           1.0193399502188318,
+           0.9586931225159728,
+           0.90607711766231,
+           0.8629773336284141,
+           0.8306776532160791,
+           0.8102296272605658,
+           0.802426759840599,
+           0.807784527440943,
+           0.8265266292680139,
+           0.8585778188187079,
+           0.903563510914707,
+           0.9608161975262813,
+           1.0293885437345638,
+           1.108072876062771,
+           1.1954266230210673,
+           1.2898031257702423,
+           1.3893871087755552,
+           1.4922339893144014,
+           1.5963121134239244,
+           1.6995469365490827,
+           1.7998661214622391,
+           1.895244505077669,
+           1.9837478900783831,
+           2.063574646689927,
+           2.133094163743362,
+           2.1908812650373894,
+           2.235745805044052,
+           2.2667567747928743,
+           2.2832603814469845,
+           2.284891710397201,
+           2.271579733085884,
+           2.243545583452867,
+           2.201294186967251,
+           2.1455994847389563,
+           2.0774836473282314,
+           1.9981908148890346,
+           1.9091560287464668,
+           1.8119701313119454,
+           1.7083415036899752,
+           1.6000555812164745,
+           1.4889331348145614,
+           1.3767883293595558,
+           1.2653875687131841,
+           1.1564101108332656,
+           1.0514113861158652,
+           0.9517898791989258,
+           0.8587583407246608,
+           0.7733199834077448,
+           0.6962501890233106,
+           0.6280841128283824,
+           0.5691104229771384,
+           0.5193712584106793,
+           0.47866833334054804,
+           0.446574963670366,
+           0.4224536443063475,
+           0.40547866992307063,
+           0.3946631687458061,
+           0.3888898123146391,
+           0.3869443766222247,
+           0.38755126359981446,
+           0.38941004826573367,
+           0.3912320969755122,
+           0.39177630655485646,
+           0.38988304248040073,
+           0.38450540592140675,
+           0.3747370330091954,
+           0.35983572325403923,
+           0.3392423051760756,
+           0.3125942731142082,
+           0.2797338666142737,
+           0.2407104092786209,
+           0.19577687378851952,
+           0.14538079018771402,
+           0.09014976162872292,
+           0.03087199190676283,
+           -0.03152764130857801,
+           -0.09601531786732921,
+           -0.16147906246620772,
+           -0.22676175945926594,
+           -0.2906955082280599,
+           -0.3521363964819684,
+           -0.4099987568364091,
+           -0.4632879839930282,
+           -0.5111310255335327,
+           -0.5528037178520403,
+           -0.587754218628654,
+           -0.6156218864888549,
+           -0.6362510746095599,
+           -0.6496994351062506,
+           -0.6562404717947681,
+           -0.6563602268220532,
+           -0.6507481379735103,
+           -0.6402822543713553,
+           -0.6260091449630447,
+           -0.6091189729465804,
+           -0.5909163365680963,
+           -0.572787589315705,
+           -0.5561654475442235,
+           -0.5424917685549353,
+           -0.5331794351765972,
+           -0.5295743125480483,
+           -0.5329182482700182,
+           -0.5443140681581824,
+           -0.5646934768840789,
+           -0.5947887068285801,
+           -0.6351086710637323,
+           -0.6859202696306885,
+           -0.7472353747883531,
+           -0.8188038836861279,
+           -0.9001130793300378,
+           -0.9903933863948592,
+           -1.0886304511918516,
+           -1.1935833188190523,
+           -1.303808329071384,
+           -1.4176882098316523,
+           -1.5334657159576164,
+           -1.649281046387858,
+           -1.7632121751999672,
+           -1.8733171561115605,
+           -1.9776774063536045,
+           -2.0744409463470244,
+           -2.1618645669669587,
+           -2.23835391656273,
+           -2.302500544879024,
+           -2.353115009551059,
+           -2.38925524130021,
+           -2.4102494741711555,
+           -2.415713174473463,
+           -2.4055595434423926,
+           -2.380003320590362,
+           -2.3395577735928716,
+           -2.285024922478416,
+           -2.217479206930369,
+           -2.1382449617383092,
+           -2.048868213050035,
+           -1.951083443476045,
+           -1.8467760939855884,
+           -1.7379416719858694,
+           -1.6266424155238097,
+           -1.5149625212329827,
+           -1.4049629770686107,
+           -1.298637049224991,
+           -1.1978674557213531,
+           -1.1043862174010315,
+           -1.0197381115493385,
+           -0.9452485656151207,
+           -0.8819967207776177,
+           -0.8307942699820807,
+           -0.7921705356449206,
+           -0.7663641019197982,
+           -0.7533211589013318,
+           -0.7527005552757641,
+           -0.7638853956382521,
+           -0.7860008628949442,
+           -0.8179377986488795,
+           -0.8583814388168814,
+           -0.9058445812272657,
+           -0.9587043595141319,
+           -1.0152417157124298,
+           -1.0736826045184018,
+           -1.1322399266044028,
+           -1.189155177466711,
+           -1.2427388122311893,
+           -1.2914083652221242,
+           -1.3337234248891565,
+           -1.368416648285198,
+           -1.3944201025576326,
+           -1.410886341237268,
+           -1.4172037574493137,
+           -1.4130059011526788,
+           -1.3981745995062966,
+           -1.3728368746665627,
+           -1.337355807869742,
+           -1.2923156487040797,
+           -1.238501610305105,
+           -1.1768749213047045,
+           -1.1085438205198164,
+           -1.0347312777498647,
+           -0.9567403012821312,
+           -0.8759177479085529,
+           -0.7936175831172042,
+           -0.7111645469045554,
+           -0.6298191642322778,
+           -0.5507449990024375,
+           -0.47497898761926044,
+           -0.4034056043818583,
+           -0.3367355082730271,
+           -0.2754892018072047,
+           -0.2199861005122916,
+           -0.17033926970952912,
+           -0.12645593713008366,
+           -0.08804373932592768,
+           -0.05462251061437879,
+           -0.025541279220685522,
+           -2.242531641306249e-16
+          ],
+          [
+           0,
+           0.02212754324871093,
+           0.0431737441291337,
+           0.06422461337735809,
+           0.08637557092911731,
+           0.11069706200088207,
+           0.1382007452356245,
+           0.16980716498122034,
+           0.20631578266914363,
+           0.24837818264230951,
+           0.29647518713544874,
+           0.35089851546178485,
+           0.41173750630882444,
+           0.478871292314401,
+           0.5519666760472178,
+           0.6304818096828916,
+           0.7136756307508387,
+           0.8006228571157997,
+           0.8902341996246423,
+           0.9812813142619553,
+           1.0724258906858606,
+           1.162252163841981,
+           1.2493020427965476,
+           1.3321119783709299,
+           1.409250640484533,
+           1.4793564486622,
+           1.54117399569852,
+           1.5935884251594272,
+           1.6356568678022874,
+           1.666636109077739,
+           1.686005748039711,
+           1.6934862151050856,
+           1.6890511395650325,
+           1.672933694536947,
+           1.6456266938013968,
+           1.6078763680793446,
+           1.5606699039918428,
+           1.5052169833553628,
+           1.442925709772091,
+           1.3753734499647698,
+           1.3042732454791477,
+           1.2314365630301647,
+           1.158733246073926,
+           1.0880496037670506,
+           1.0212456244561263,
+           0.9601123279041629,
+           0.9063302728775198,
+           0.86143021436068,
+           0.8267568580225267,
+           0.8034365897101886,
+           0.7923499663511173,
+           0.7941096438894842,
+           0.8090442904364304,
+           0.8371888917561495,
+           0.8782817049599434,
+           0.9317679585111407,
+           0.9968102361915848,
+           1.0723053234511402,
+           1.156907140434421,
+           1.2490552407105713,
+           1.3470082218643866,
+           1.4488812768804837,
+           1.552687016524852,
+           1.6563786151059432,
+           1.757894276975204,
+           1.8552019902411645,
+           1.9463435281675026,
+           2.0294766777404996,
+           2.102914718448844,
+           2.165162241342448,
+           2.21494648727622,
+           2.2512434917161763,
+           2.2732984489260737,
+           2.2806398476870817,
+           2.273087080517425,
+           2.2507513849868612,
+           2.214030135333276,
+           2.163594661287823,
+           2.1003719249314656,
+           2.025520531792572,
+           1.940401685721229,
+           1.846545815111618,
+           1.7456156979414825,
+           1.6393669924603267,
+           1.529607137298818,
+           1.418153617959365,
+           1.3067926053385357,
+           1.1972389559879613,
+           1.0910985237111586,
+           0.9898336688850311,
+           0.8947327672200096,
+           0.8068844156926407,
+           0.7271569127322092,
+           0.6561834554587792,
+           0.5943533522247084,
+           0.5418093975227566,
+           0.49845140226552925,
+           0.46394571934973733,
+           0.4377404560986923,
+           0.41908592530403793,
+           0.4070597586213745,
+           0.40059599316790717,
+           0.3985173470955036,
+           0.3995698249904841,
+           0.40245874099536416,
+           0.4058852178182511,
+           0.40858221397047484,
+           0.4093491497305119,
+           0.40708424395040715,
+           0.4008137377908494,
+           0.3897172661255515,
+           0.3731487405115587,
+           0.3506522266350394,
+           0.3219724309736254,
+           0.28705955270945677,
+           0.24606840409150585,
+           0.1993518517471655,
+           0.14744877909717527,
+           0.09106691229518432,
+           0.03106098539229493,
+           -0.03159315865492609,
+           -0.09582782901684299,
+           -0.16051532054060128,
+           -0.22450146319196063,
+           -0.2866399856673222,
+           -0.34582676951128755,
+           -0.4010330718494779,
+           -0.45133682030444905,
+           -0.49595113217390757,
+           -0.534249280303304,
+           -0.5657854185167599,
+           -0.5903104877112445,
+           -0.6077828470488503,
+           -0.6183733099981654,
+           -0.6224644088701347,
+           -0.6206438603388978,
+           -0.6136923544766645,
+           -0.6025659372716409,
+           -0.5883733977065836,
+           -0.5723492016731827,
+           -0.5558226329475048,
+           -0.5401839031437302,
+           -0.526848075389588,
+           -0.51721770828687,
+           -0.5126451659159753,
+           -0.5143955551593531,
+           -0.5236112429897872,
+           -0.5412788737332207,
+           -0.56819975040954,
+           -0.6049643663984661,
+           -0.651931775741714,
+           -0.7092143747520517,
+           -0.7766685370762378,
+           -0.8538914021504552,
+           -0.9402239665900302,
+           -1.0347604731776492,
+           -1.1363639365837142,
+           -1.2436874926208825,
+           -1.3552011124844747,
+           -1.4692230886780822,
+           -1.5839555785324855,
+           -1.6975233874200801,
+           -1.8080150895580045,
+           -1.9135255218131975,
+           -2.0121986467717705,
+           -2.1022697665416863,
+           -2.182106078750843,
+           -2.25024460080153,
+           -2.3054265468608013,
+           -2.34662732292975,
+           -2.3730814067152983,
+           -2.3843014984903106,
+           -2.380091463788701,
+           -2.3605527353818987,
+           -2.326083996964819,
+           -2.277374130577055,
+           -2.2153885701152958,
+           -2.141349360451395,
+           -2.05670937182737,
+           -1.963121258693175,
+           -1.862401877583744,
+           -1.756492986940183,
+           -1.6474191403253662,
+           -1.5372437511102792,
+           -1.4280243497927214,
+           -1.3217680736110167,
+           -1.2203884215890786,
+           -1.1256642767661686,
+           -1.0392021419036321,
+           -0.9624024567892299,
+           -0.8964307663010024,
+           -0.8421943910766572,
+           -0.8003251198402569,
+           -0.771168297419818,
+           -0.7547785287982035,
+           -0.7509220609351438,
+           -0.7590857444554233,
+           -0.7784923205129153,
+           -0.8081216280322661,
+           -0.8467371867498056,
+           -0.8929174854134777,
+           -0.9450911952062926,
+           -1.0015754385593432,
+           -1.0606161751672276,
+           -1.120429721825005,
+           -1.1792444017119732,
+           -1.2353413223956669,
+           -1.2870933099531097,
+           -1.333001078435457,
+           -1.3717257880826426,
+           -1.4021172403237907,
+           -1.4232370702721335,
+           -1.4343764252945201,
+           -1.4350677580896916,
+           -1.425090511041295,
+           -1.4044706217136935,
+           -1.3734739334136887,
+           -1.3325937459171073,
+           -1.2825328860039604,
+           -1.224180811780843,
+           -1.1585863855782188,
+           -1.086927054521023,
+           -1.0104752631294465,
+           -0.9305629864391833,
+           -0.8485453135952913,
+           -0.7657640296989836,
+           -0.6835121374928549,
+           -0.6030002304801886,
+           -0.5253255761058279,
+           -0.4514446930723964,
+           -0.38215011265747667,
+           -0.31805190245627873,
+           -0.259564405150737,
+           -0.20689850790758166,
+           -0.16005961331939345,
+           -0.11885133409782787,
+           -0.08288478477801657,
+           -0.05159319827170734,
+           -0.024251456895743807,
+           -2.144783963361557e-16
+          ],
+          [
+           0,
+           0.02151136596317517,
+           0.04245922678000075,
+           0.06392671487821748,
+           0.0869878905945,
+           0.11267390951174294,
+           0.1419402699511169,
+           0.17563602552754193,
+           0.21447579795006336,
+           0.25901535400783,
+           0.3096314197157169,
+           0.36650629618703917,
+           0.4296177186812489,
+           0.49873426554201605,
+           0.5734164807911687,
+           0.6530237265828587,
+           0.7367266332767215,
+           0.8235248693127415,
+           0.9122698140513466,
+           1.0016915878082293,
+           1.090429777745325,
+           1.1770670990282774,
+           1.260165150273529,
+           1.3383013628637774,
+           1.4101062067670258,
+           1.474299702049756,
+           1.5297262957407478,
+           1.5753871978937048,
+           1.6104693278356783,
+           1.6343701003212956,
+           1.6467173797450043,
+           1.647384046304558,
+           1.6364967482317032,
+           1.614438555716358,
+           1.5818453814662425,
+           1.5395961862806011,
+           1.488797141779345,
+           1.430760072705662,
+           1.3669756442770407,
+           1.2990818923332161,
+           1.2288288122155884,
+           1.1580398234484561,
+           1.0885710088304033,
+           1.0222690864159714,
+           0.9609291095357804,
+           0.9062529024992009,
+           0.8598092275740016,
+           0.8229966424722489,
+           0.797009947720858,
+           0.7828110413677561,
+           0.7811048964249501,
+           0.7923212567302006,
+           0.8166025124092109,
+           0.8537980700970572,
+           0.9034653790746152,
+           0.9648776162364776,
+           1.0370378741825659,
+           1.1186995415806071,
+           1.2083924170629732,
+           1.3044539609061208,
+           1.4050649659366445,
+           1.5082888235113314,
+           1.6121134746056518,
+           1.7144950721082186,
+           1.8134023399151762,
+           1.9068605983317988,
+           1.9929944340046553,
+           2.070068025905304,
+           2.136522195942548,
+           2.1910073321907606,
+           2.2324114325359203,
+           2.2598826343098213,
+           2.2728457283195507,
+           2.2710123003304767,
+           2.2543842959869145,
+           2.223250962616722,
+           2.178179279518999,
+           2.1199981433202417,
+           2.0497767230295434,
+           1.9687975369289759,
+           1.87852492706721,
+           1.7805697138947698,
+           1.676650900919916,
+           1.5685553650890733,
+           1.458096511352577,
+           1.3470728885836531,
+           1.237227758288766,
+           1.1302105775970697,
+           1.0275413046583968,
+           0.9305783592025069,
+           0.8404909755468939,
+           0.7582365722087739,
+           0.6845436343327131,
+           0.6199004656028174,
+           0.5645500186615541,
+           0.5184908609930957,
+           0.4814841805357659,
+           0.45306658576075315,
+           0.43256831230061316,
+           0.4191363159595029,
+           0.41176161334944306,
+           0.40931012938711037,
+           0.4105562279484738,
+           0.41421804012738267,
+           0.4189936652620804,
+           0.42359730409656654,
+           0.42679439145924036,
+           0.4274348274000905,
+           0.4244834599721748,
+           0.4170470483486071,
+           0.4043970297775963,
+           0.3859875255593108,
+           0.36146814692343177,
+           0.3306912981918267,
+           0.29371381845553834,
+           0.250792950528107,
+           0.20237677341795318,
+           0.14908937825597243,
+           0.09171120388411434,
+           0.031155073709378443,
+           -0.0315614132158527,
+           -0.09534638942778646,
+           -0.15906630189020607,
+           -0.2215796936322855,
+           -0.281771275806803,
+           -0.33858537354660034,
+           -0.3910578442979371,
+           -0.4383456057776238,
+           -0.47975297137534667,
+           -0.5147540721821837,
+           -0.5430107448278866,
+           -0.5643853804385988,
+           -0.5789483593607467,
+           -0.5869798355779348,
+           -0.5889657804638113,
+           -0.58558834398725,
+           -0.5777107389644909,
+           -0.5663569967039015,
+           -0.5526870767934647,
+           -0.537967936423759,
+           -0.5235412723943831,
+           -0.5107887390616869,
+           -0.5010955156302351,
+           -0.49581314454527287,
+           -0.4962225880264675,
+           -0.5034984512872366,
+           -0.5186752985950597,
+           -0.542616942529573,
+           -0.5759895186558008,
+           -0.6192390689786748,
+           -0.6725742501312354,
+           -0.7359546588894553,
+           -0.8090851313213724,
+           -0.891416226015737,
+           -0.9821509499901067,
+           -1.080257631801458,
+           -1.184488693889545,
+           -1.2934049290586156,
+           -1.405404747907327,
+           -1.5187577383938748,
+           -1.6316417687171465,
+           -1.7421827730684343,
+           -1.8484962888775822,
+           -1.9487297657508988,
+           -2.0411046416323884,
+           -2.1239571814884295,
+           -2.1957770980907356,
+           -2.255243022721466,
+           -2.3012539647255976,
+           -2.3329559911014437,
+           -2.3497634685410005,
+           -2.351374337828123,
+           -2.3377790311917206,
+           -2.3092627936824783,
+           -2.26640132624036,
+           -2.2100498270370488,
+           -2.1413256650430372,
+           -2.061585071748072,
+           -1.9723943798502694,
+           -1.8754964680377186,
+           -1.772773185537412,
+           -1.6662046261051142,
+           -1.5578261962344147,
+           -1.4496844747439728,
+           -1.3437928892835669,
+           -1.242088238996099,
+           -1.1463890715009522,
+           -1.0583568770481646,
+           -0.9794609942497309,
+           -0.9109480319063707,
+           -0.8538165023225225,
+           -0.8087972358145649,
+           -0.776340006947656,
+           -0.7566066537917746,
+           -0.7494708158179554,
+           -0.7545242577653254,
+           -0.7710895897614638,
+           -0.7982390420006267,
+           -0.8348188090744021,
+           -0.8794783480843409,
+           -0.9307038991167585,
+           -0.9868553993129205,
+           -1.0462058849572584,
+           -1.1069824215568649,
+           -1.1674075710682883,
+           -1.2257403989288602,
+           -1.2803160414550667,
+           -1.329582895963761,
+           -1.3721365605485805,
+           -1.4067497361387968,
+           -1.4323974080983006,
+           -1.4482767455419112,
+           -1.4538212907113555,
+           -1.4487091547993112,
+           -1.4328650869354205,
+           -1.4064564359035308,
+           -1.369883175741419,
+           -1.3237623129195946,
+           -1.26890713067524,
+           -1.2063018518851572,
+           -1.1370724125003493,
+           -1.0624541303218142,
+           -0.9837571265112818,
+           -0.9023304079482696,
+           -0.8195255461628275,
+           -0.7366608924681516,
+           -0.6549872490595292,
+           -0.575655872801467,
+           -0.4996896233378568,
+           -0.42795798172618527,
+           -0.36115656221843095,
+           -0.2997916207428452,
+           -0.24416993212157856,
+           -0.1943942674368619,
+           -0.15036455680567737,
+           -0.11178467484690129,
+           -0.07817464007496139,
+           -0.0488878790278881,
+           -0.023133074688005142,
+           -2.0635977570917997e-16
+          ],
+          [
+           0,
+           0.021074742000610363,
+           0.042098639312604415,
+           0.06414229693489497,
+           0.08824919764410959,
+           0.11540270570730425,
+           0.14649463974073212,
+           0.1822962652532775,
+           0.22343249573361354,
+           0.27036000912056696,
+           0.3233498861990384,
+           0.3824752614134854,
+           0.44760434771051805,
+           0.518399058560515,
+           0.5943193057587166,
+           0.6746329046196806,
+           0.7584308724717527,
+           0.8446477656196894,
+           0.9320865677436031,
+           1.0194475224017705,
+           1.105360196971065,
+           1.1884179776889625,
+           1.2672141277140723,
+           1.340378494061668,
+           1.4066139261203292,
+           1.4647314688682025,
+           1.5136834179466718,
+           1.5525933708890896,
+           1.580782477937744,
+           1.597791185357057,
+           1.6033958717973273,
+           1.5976199014555577,
+           1.5807387534989992,
+           1.553279032125248,
+           1.5160113121560006,
+           1.469936927478052,
+           1.416268960177443,
+           1.3564078331215466,
+           1.291912044421181,
+           1.2244647052629793,
+           1.1558366499588395,
+           1.0878469760137242,
+           1.022321940314083,
+           0.9610531834411626,
+           0.905756276420505,
+           0.8580305823146949,
+           0.8193213989309059,
+           0.7908852991246872,
+           0.7737595128972874,
+           0.7687361024217532,
+           0.7763415695229426,
+           0.7968224076679695,
+           0.8301369702792384,
+           0.8759538775630218,
+           0.9336570286875983,
+           1.002357128826447,
+           1.0809094851359775,
+           1.1679376759535245,
+           1.261862557033863,
+           1.360935940919754,
+           1.463278173682078,
+           1.5669187399992748,
+           1.669838955150938,
+           1.7700157527429383,
+           1.8654655510740417,
+           1.9542871796253531,
+           2.034702870233604,
+           2.105096364527048,
+           2.1640472590022797,
+           2.21036079998847,
+           2.243092450454078,
+           2.2615666764720492,
+           2.2653895400913036,
+           2.254454833965974,
+           2.2289436477367395,
+           2.1893174130639137,
+           2.136304629552139,
+           2.070881623797006,
+           1.9942478347768533,
+           1.9077962473865184,
+           1.8130797089525126,
+           1.7117739583559817,
+           1.605638271649626,
+           1.4964746800246627,
+           1.3860867444533334,
+           1.2762388756713294,
+           1.1686171683386586,
+           1.0647926747886993,
+           0.9661879778857962,
+           0.8740478358567038,
+           0.7894145667440766,
+           0.7131087190089892,
+           0.645715440829357,
+           0.5875768171588183,
+           0.5387902942105768,
+           0.499213159435778,
+           0.4684728950451868,
+           0.4459830783972543,
+           0.4309643667263398,
+           0.4224699800639997,
+           0.4194149878544243,
+           0.42060861433550695,
+           0.42478870745073766,
+           0.4306574675681847,
+           0.43691750675755714,
+           0.44230730738463864,
+           0.4456351703052191,
+           0.4458107873703035,
+           0.4418736391112945,
+           0.4330175046360529,
+           0.4186104747137435,
+           0.398209978095442,
+           0.37157246226998447,
+           0.33865750975325126,
+           0.29962631610085616,
+           0.25483460244014583,
+           0.20482017972420197,
+           0.1502855204638834,
+           0.09207582289010888,
+           0.031153169071765754,
+           -0.03143252048103491,
+           -0.09457495031533199,
+           -0.15714448355507218,
+           -0.21802185649570843,
+           -0.27613166729732824,
+           -0.33047473706679414,
+           -0.3801584700556491,
+           -0.42442439059546627,
+           -0.4626721064687938,
+           -0.49447903986028013,
+           -0.5196153755485435,
+           -0.5380537988524297,
+           -0.5499737299398936,
+           -0.5557599030621099,
+           -0.5559952855061894,
+           -0.551448477872106,
+           -0.5430558809583447,
+           -0.5318990514455151,
+           -0.5191777952214055,
+           -0.5061796603704262,
+           -0.4942465886637581,
+           -0.48473956234779925,
+           -0.4790021401202219,
+           -0.47832381090656056,
+           -0.48390410546461726,
+           -0.49681839358954266,
+           -0.5179862590008563,
+           -0.5481432856820442,
+           -0.5878170098985129,
+           -0.6373076932585966,
+           -0.6966744564090666,
+           -0.7657271831022872,
+           -0.8440244636249903,
+           -0.930877698405298,
+           -1.0253613306744005,
+           -1.1263290251133777,
+           -1.232435461234366,
+           -1.3421632695133037,
+           -1.4538545085181955,
+           -1.5657459657068291,
+           -1.6760074661021214,
+           -1.7827822941750253,
+           -1.884228776979392,
+           -1.9785620423655808,
+           -2.0640949558587045,
+           -2.1392772538429528,
+           -2.20273192876603,
+           -2.2532879832959747,
+           -2.2900087532843374,
+           -2.312215102035225,
+           -2.3195029082822303,
+           -2.3117544045395637,
+           -2.2891430678679576,
+           -2.2521319180512878,
+           -2.201465234997286,
+           -2.138153864037247,
+           -2.0634544308826483,
+           -1.9788429335676339,
+           -1.8859833132131958,
+           -1.7866917256082828,
+           -1.6828973384810717,
+           -1.5766005624187343,
+           -1.4698296846577932,
+           -1.3645969129161966,
+           -1.2628548501480883,
+           -1.1664544102436634,
+           -1.0771051495400157,
+           -0.9963389304208196,
+           -0.925477752702081,
+           -0.8656064879047463,
+           -0.8175511333688186,
+           -0.7818630703608863,
+           -0.7588096661185182,
+           -0.7483714076871969,
+           -0.7502455991545124,
+           -0.763856497286364,
+           -0.7883716074385908,
+           -0.822723715682509,
+           -0.8656380978900733,
+           -0.9156642253505068,
+           -0.9712111822623359,
+           -1.0305859256688454,
+           -1.0920334551040507,
+           -1.1537779188816346,
+           -1.2140636675141663,
+           -1.2711952725271547,
+           -1.3235755606673756,
+           -1.3697407683428031,
+           -1.408391997649124,
+           -1.4384222515796685,
+           -1.4589384395434866,
+           -1.4692778722694781,
+           -1.4690189043421453,
+           -1.4579855295149862,
+           -1.436245884916082,
+           -1.4041047715390405,
+           -1.362090446244735,
+           -1.3109360812225628,
+           -1.2515564169969184,
+           -1.1850202514088484,
+           -1.1125195066987963,
+           -1.0353356974292347,
+           -0.9548046815623614,
+           -0.872280614123206,
+           -0.7891000366719132,
+           -0.7065470260044018,
+           -0.6258202924123423,
+           -0.5480030623582854,
+           -0.4740365040148391,
+           -0.4046973587558396,
+           -0.34058032982163927,
+           -0.28208565386967727,
+           -0.2294121451634495,
+           -0.1825558592037694,
+           -0.14131437629332344,
+           -0.10529655955673467,
+           -0.07393750000883326,
+           -0.04651822696415797,
+           -0.022189638806084894,
+           -1.9990768281194183e-16
+          ],
+          [
+           0,
+           0.020814588163810134,
+           0.04208117084905372,
+           0.06484846996642576,
+           0.09012062533697406,
+           0.11882530699371477,
+           0.1517838623459178,
+           0.18968430761250338,
+           0.23305790007180827,
+           0.2822599358042103,
+           0.33745530903552046,
+           0.39860924665870257,
+           0.46548349810920475,
+           0.5376381198614756,
+           0.6144388489599464,
+           0.6950699148591915,
+           0.7785519970990951,
+           0.8637649015754131,
+           0.9494744038075073,
+           1.0343625968204924,
+           1.117060986880111,
+           1.1961855047699679,
+           1.2703725455389934,
+           1.3383151171113519,
+           1.3987981687265176,
+           1.4507321841722092,
+           1.4931841619099937,
+           1.5254051636163093,
+           1.5468536929550842,
+           1.5572142656227095,
+           1.556410647445598,
+           1.5446133667315658,
+           1.522241246998078,
+           1.4899568531734981,
+           1.4486558947591592,
+           1.3994507795240934,
+           1.3436486573537139,
+           1.2827244322531755,
+           1.218289347762239,
+           1.1520558639858154,
+           1.0857996402448569,
+           1.021319513586063,
+           0.9603964181146636,
+           0.9047522219186421,
+           0.8560094663846027,
+           0.815652976699217,
+           0.7849942726126475,
+           0.7651396460229192,
+           0.7569626880976403,
+           0.7610819454838622,
+           0.7778442651487549,
+           0.8073142534417106,
+           0.8492701303176579,
+           0.9032061078241426,
+           0.9683412666242358,
+           1.0436347492865379,
+           1.127806938102335,
+           1.2193661419718271,
+           1.3166401849328124,
+           1.4178121714096585,
+           1.5209596031084545,
+           1.6240959421232595,
+           1.7252136562120537,
+           1.8223277467806227,
+           1.9135187487424592,
+           1.9969742043781096,
+           2.0710276502781615,
+           2.134194216512804,
+           2.1852020188547097,
+           2.2230186261896927,
+           2.2468720037002434,
+           2.256265465101925,
+           2.250986310906053,
+           2.231107980862205,
+           2.196985703708701,
+           2.1492457823473003,
+           2.088768803783056,
+           2.016667206951729,
+           1.9342577744033917,
+           1.8430297325031686,
+           1.744609246482514,
+           1.6407211788837304,
+           1.5331490407260806,
+           1.4236941026534096,
+           1.314134647535635,
+           1.2061863362100584,
+           1.101464624575373,
+           1.001450113987173,
+           0.9074576393041572,
+           0.8206098019787116,
+           0.7418155417270326,
+           0.6717542124180305,
+           0.6108654890932045,
+           0.5593452869387087,
+           0.5171477232176077,
+           0.4839930033604953,
+           0.4593809663232813,
+           0.4426098855681092,
+           0.43279999403270253,
+           0.4289210873750533,
+           0.42982346241127195,
+           0.43427136937902805,
+           0.44097809935116117,
+           0.4486417931599877,
+           0.45598104637857506,
+           0.4617693964664174,
+           0.46486781276494543,
+           0.464254366688815,
+           0.45905033671717904,
+           0.44854209864666605,
+           0.4321982635633473,
+           0.40968165126276007,
+           0.3808558222039804,
+           0.345786033086499,
+           0.3047346261849376,
+           0.25815100699242777,
+           0.20665650485428527,
+           0.1510245435763665,
+           0.09215667012427782,
+           0.031055096430970642,
+           -0.03120750069798976,
+           -0.09352010582136888,
+           -0.1547665516985502,
+           -0.21385887364511472,
+           -0.2697699337332117,
+           -0.32156443562936976,
+           -0.3684274919288019,
+           -0.40968996847911104,
+           -0.44484991281183467,
+           -0.4735894743371051,
+           -0.49578683987215827,
+           -0.5115228364462809,
+           -0.5210819909148084,
+           -0.5249479792494474,
+           -0.5237935438294606,
+           -0.5184651009586141,
+           -0.5099623995307865,
+           -0.49941372174331417,
+           -0.4880472347056589,
+           -0.4771592047030823,
+           -0.4680798711142727,
+           -0.46213784235062977,
+           -0.4606239199799546,
+           -0.4647552782526703,
+           -0.47564092396577823,
+           -0.4942493359629521,
+           -0.521379135146906,
+           -0.5576335658117794,
+           -0.6033994790712275,
+           -0.6588314013466976,
+           -0.7238411479229679,
+           -0.7980933064907804,
+           -0.881006771704725,
+           -0.971762362640577,
+           -1.0693164043309686,
+           -1.1724200060297063,
+           -1.2796436261961461,
+           -1.3894063809568167,
+           -1.5000094323221866,
+           -1.6096726877328993,
+           -1.7165739562194788,
+           -1.8188896407695054,
+           -1.9148360030897906,
+           -2.002710016963694,
+           -2.080928830395228,
+           -2.1480668846719615,
+           -2.2028897897467288,
+           -2.2443841287369484,
+           -2.2717824581267303,
+           -2.2845828821821317,
+           -2.282562707456472,
+           -2.265785822989075,
+           -2.234603600497926,
+           -2.1896492629207205,
+           -2.1318258253200173,
+           -2.0622878656435146,
+           -1.9824175303766949,
+           -1.8937953181410976,
+           -1.7981663094068467,
+           -1.6974026196464882,
+           -1.593462943791274,
+           -1.488350129548682,
+           -1.3840677642979735,
+           -1.282576783748378,
+           -1.1857531097495582,
+           -1.0953472996097668,
+           -1.012947140618531,
+           -0.9399440523820173,
+           -0.8775040678027978,
+           -0.8265440533193525,
+           -0.7877137030629723,
+           -0.7613837029717881,
+           -0.7476403130133157,
+           -0.7462864621210098,
+           -0.7568492949950469,
+           -0.7785939563436957,
+           -0.8105432501888873,
+           -0.8515026731250707,
+           -0.900090194269799,
+           -0.9547700441294259,
+           -1.0138896823864951,
+           -1.0757190429057528,
+           -1.1384911047536,
+           -1.2004428118824968,
+           -1.2598553619215882,
+           -1.3150929062209904,
+           -1.364638748313957,
+           -1.4071281951093284,
+           -1.4413773026831616,
+           -1.466406864279935,
+           -1.4814611093928034,
+           -1.4860207165234671,
+           -1.479809885078123,
+           -1.4627973602711817,
+           -1.435191455187834,
+           -1.3974292625670637,
+           -1.3501603917304688,
+           -1.2942256998673378,
+           -1.2306316082948487,
+           -1.1605207003611147,
+           -1.0851393857544787,
+           -1.0058034839841357,
+           -0.9238626260699219,
+           -0.8406643969333539,
+           -0.7575191411005264,
+           -0.6756663311770603,
+           -0.5962433527843644,
+           -0.5202574924687097,
+           -0.44856182825689034,
+           -0.381835618271733,
+           -0.32056966380717433,
+           -0.2650569925321353,
+           -0.2153890683706155,
+           -0.17145759062416344,
+           -0.13296179971180697,
+           -0.09942106417747586,
+           -0.0701923869658058,
+           -0.04449234184807345,
+           -0.021422836501936444,
+           -1.9511555178739183e-16
+          ],
+          [
+           0,
+           0.020726090331266135,
+           0.042392719809300435,
+           0.06601775114034217,
+           0.09255774611647785,
+           0.12287744338178717,
+           0.1577217096213061,
+           0.19769072619185685,
+           0.24321909003694084,
+           0.2945594070075323,
+           0.35177083998654557,
+           0.41471294640652534,
+           0.4830450030839195,
+           0.5562308742214082,
+           0.6335493345440293,
+           0.7141096174769325,
+           0.7968718216426757,
+           0.8806716812226567,
+           0.9642490901405131,
+           1.0462796695349648,
+           1.12540858517116,
+           1.200285758429562,
+           1.2696015729531391,
+           1.3321221600358266,
+           1.3867233499433624,
+           1.4324224035399056,
+           1.4684066882408404,
+           1.494058533251609,
+           1.508975589577191,
+           1.5129861281972834,
+           1.506158832459746,
+           1.4888067751373102,
+           1.4614854134085071,
+           1.4249845827345036,
+           1.380314619550496,
+           1.328686889175725,
+           1.2714891357250429,
+           1.2102562015754532,
+           1.1466367818317798,
+           1.0823569812870775,
+           1.0191815250118155,
+           0.9588735368075093,
+           0.9031538407049868,
+           0.8536607583985663,
+           0.8119113694805304,
+           0.7792651716552471,
+           0.7568910254330007,
+           0.7457381933614137,
+           0.746512189417014,
+           0.7596560420158279,
+           0.7853374469143349,
+           0.8234421471387453,
+           0.8735737293772559,
+           0.9350598735876385,
+           1.0069649386288029,
+           1.0881086152725972,
+           1.1770902326866008,
+           1.2723181689472702,
+           1.3720436936570328,
+           1.4743984642931138,
+           1.577434810112964,
+           1.679167870428966,
+           1.7776186094830773,
+           1.870856709090761,
+           1.9570423431981605,
+           2.0344658654335417,
+           2.101584490973764,
+           2.157055126358862,
+           2.1997625935026344,
+           2.228842604798349,
+           2.243698972199582,
+           2.2440146713868048,
+           2.229756529232726,
+           2.201173455161542,
+           2.1587882909411444,
+           2.1033835052007346,
+           2.0359811048351792,
+           1.9578172718966917,
+           1.870312358275346,
+           1.775036978441103,
+           1.673675030161117,
+           1.5679845422711933,
+           1.4597572956306,
+           1.3507781872327425,
+           1.2427853075617077,
+           1.1374316777423037,
+           1.0362495464778747,
+           0.940618078420842,
+           0.8517351772251631,
+           0.7705940803290786,
+           0.6979652411862214,
+           0.6343838812475443,
+           0.5801434518315505,
+           0.5352950986511802,
+           0.4996530728582924,
+           0.4728058857167401,
+           0.4541328630562436,
+           0.44282562397319647,
+           0.43791388907444556,
+           0.4382949198305517,
+           0.4427658048499539,
+           0.45005774318524266,
+           0.45887143071365993,
+           0.4679126342290016,
+           0.4759270396068376,
+           0.4817334851456574,
+           0.48425473825497,
+           0.48254504181142505,
+           0.47581374396473336,
+           0.46344442969465166,
+           0.44500909132294514,
+           0.4202770054381992,
+           0.3892181219840653,
+           0.3520009140837381,
+           0.30898478090620185,
+           0.26070723688596276,
+           0.20786625532273814,
+           0.15129825940780733,
+           0.0919523658933608,
+           0.030861583109730337,
+           -0.03088825659098238,
+           -0.09219099160389883,
+           -0.15195317797045055,
+           -0.2091267990901768,
+           -0.2627407575390668,
+           -0.3119302995290987,
+           -0.3559635756272198,
+           -0.3942646149410517,
+           -0.42643208221846607,
+           -0.45225329587326685,
+           -0.4717131071014364,
+           -0.48499737290910083,
+           -0.492490895684897,
+           -0.494769845382666,
+           -0.49258882380712093,
+           -0.4868628702831957,
+           -0.4786448405934861,
+           -0.4690987131178377,
+           -0.4594694844949134,
+           -0.4510504090761385,
+           -0.44514840959433905,
+           -0.44304853892663343,
+           -0.4459784032134372,
+           -0.4550734640728826,
+           -0.47134412196485165,
+           -0.4956454442326905,
+           -0.5286503408770784,
+           -0.5708269101395113,
+           -0.6224205764519067,
+           -0.6834415276704796,
+           -0.753657829590466,
+           -0.8325944567050508,
+           -0.9195383324576812,
+           -1.0135493234466886,
+           -1.1134769838644107,
+           -1.2179827025725518,
+           -1.3255667692162063,
+           -1.4345997510574873,
+           -1.5433574618918218,
+           -1.6500587112705736,
+           -1.7529049486491732,
+           -1.8501208648879968,
+           -1.9399949841068151,
+           -2.0209192730255316,
+           -2.091426812827071,
+           -2.1502266198801223,
+           -2.1962347654093155,
+           -2.2286010288929825,
+           -2.2467304235809604,
+           -2.250299052564187,
+           -2.239263887394195,
+           -2.2138662051071174,
+           -2.1746285701591868,
+           -2.122345401563423,
+           -2.0580673186837326,
+           -1.9830796079569206,
+           -1.8988752936430624,
+           -1.8071234251098145,
+           -1.7096333079742574,
+           -1.6083155038492238,
+           -1.5051405010870975,
+           -1.4020960148834136,
+           -1.3011439080255993,
+           -1.204177732644261,
+           -1.1129818783230025,
+           -1.0291932732165747,
+           -0.9542665233633966,
+           -0.8894432926621884,
+           -0.8357266240379623,
+           -0.7938607836438041,
+           -0.7643170774344866,
+           -0.7472859463443823,
+           -0.7426754961016339,
+           -0.7501164640791621,
+           -0.7689734722675334,
+           -0.7983622661897566,
+           -0.8371724979942938,
+           -0.8840954814975948,
+           -0.9376562307609783,
+           -0.9962489946832257,
+           -1.0581754204500875,
+           -1.121684420403472,
+           -1.185012781345694,
+           -1.2464255432859215,
+           -1.3042551863940024,
+           -1.3569387000923432,
+           -1.4030516658545578,
+           -1.441338563903381,
+           -1.4707386116079904,
+           -1.4904065555061037,
+           -1.4997279666503451,
+           -1.4983287272014016,
+           -1.4860785414107112,
+           -1.463088452736574,
+           -1.4297024971269416,
+           -1.3864837668037577,
+           -1.3341952956289036,
+           -1.2737763029476166,
+           -1.206314444598222,
+           -1.1330148148095163,
+           -1.0551665186647692,
+           -0.9741076898601831,
+           -0.8911898613171398,
+           -0.8077426060700799,
+           -0.7250393525691076,
+           -0.6442652425107326,
+           -0.5664878415117169,
+           -0.49263143488334926,
+           -0.4234555444641627,
+           -0.3595381903999211,
+           -0.30126429678322936,
+           -0.24881950536362313,
+           -0.20218952053413025,
+           -0.1611649650673499,
+           -0.12535158325253826,
+           -0.09418548978738939,
+           -0.06695303249886679,
+           -0.0428147179967464,
+           -0.020832544703980375,
+           -1.919601749629227e-16
+          ],
+          [
+           0,
+           0.0208027769275336,
+           0.04301608356532208,
+           0.06761840789336324,
+           0.09551110024549772,
+           0.127489455834434,
+           0.1642166785505628,
+           0.20620143497030513,
+           0.2537796149564986,
+           0.30710080672801593,
+           0.36611987255734124,
+           0.4305938793969023,
+           0.5000845000690537,
+           0.5739658586867652,
+           0.6514376522950026,
+           0.7315432429260604,
+           0.8131922838420995,
+           0.8951873240104913,
+           0.9762537288739556,
+           1.055072165948974,
+           1.1303128330148544,
+           1.2006705564775815,
+           1.264899859229376,
+           1.3218490917520194,
+           1.3704927375376055,
+           1.4099610437599173,
+           1.4395661895936274,
+           1.4588242861756142,
+           1.4674726019549527,
+           1.4654815226502231,
+           1.453060883391405,
+           1.4306604487079937,
+           1.3989644604246645,
+           1.358880320665348,
+           1.3115216233942668,
+           1.2581858896006364,
+           1.2003274948296598,
+           1.1395263999357077,
+           1.0774534036197572,
+           1.0158327257997855,
+           0.9564028018575783,
+           0.9008762174932579,
+           0.8508997410077518,
+           0.8080154135871951,
+           0.7736236384204185,
+           0.7489491666590644,
+           0.7350108133175834,
+           0.7325956507413705,
+           0.7422383232887741,
+           0.7642060068789019,
+           0.7984894039521299,
+           0.8448000214008937,
+           0.90257382962909,
+           0.9709812487255468,
+           1.0489432564997094,
+           1.1351532665160111,
+           1.2281042858580766,
+           1.326120735537581,
+           1.4273942043366616,
+           1.5300223121809318,
+           1.6320497842004518,
+           1.7315107832840555,
+           1.8264715184758364,
+           1.9150721397485488,
+           1.9955669466860575,
+           2.0663619790014276,
+           2.1260491196219933,
+           2.17343592475261,
+           2.2075704978375064,
+           2.2277608431740656,
+           2.233588267184432,
+           2.2249145377923587,
+           2.201882661505479,
+           2.164911290028095,
+           2.1146829198158077,
+           2.0521261952398326,
+           1.9783927653748783,
+           1.8948292724781812,
+           1.8029451638882172,
+           1.7043771155972653,
+           1.6008509328249267,
+           1.4941418487039664,
+           1.3860341753762033,
+           1.2782812716330574,
+           1.1725667775476698,
+           1.0704680297371347,
+           0.9734225119373058,
+           0.8826981159859537,
+           0.7993678901150189,
+           0.7242898371273441,
+           0.6580921974479338,
+           0.6011645143867146,
+           0.5536546346628569,
+           0.5154716499103504,
+           0.4862946381683433,
+           0.4655869218916999,
+           0.4526154243176601,
+           0.4464745824126221,
+           0.44611416513522484,
+           0.4503702530661396,
+           0.45799856182530785,
+           0.46770923889805616,
+           0.4782022327740121,
+           0.48820232536463637,
+           0.4964929336345071,
+           0.5019478238131396,
+           0.5035599404430955,
+           0.5004666313258221,
+           0.4919706461134177,
+           0.47755639838193237,
+           0.45690110564775716,
+           0.42988055578130624,
+           0.3965693882290118,
+           0.35723592082864797,
+           0.31233169419054796,
+           0.2624760420493209,
+           0.20843612422134017,
+           0.151102975596359,
+           0.0914642270016506,
+           0.030574239222618736,
+           -0.03047754220775051,
+           -0.09059915829689116,
+           -0.14872875719620768,
+           -0.20386638627596423,
+           -0.2551040992963332,
+           -0.301653565776797,
+           -0.3428704340540658,
+           -0.3782747831924382,
+           -0.40756709975857225,
+           -0.4306393309495928,
+           -0.44758069275401974,
+           -0.4586780475164016,
+           -0.4644108060393277,
+           -0.4654404516301576,
+           -0.4625949236818213,
+           -0.4568482329134262,
+           -0.44929580587026796,
+           -0.4411261695006277,
+           -0.43358968469786374,
+           -0.4279651181062352,
+           -0.4255249021621856,
+           -0.427499972695538,
+           -0.43504509039522915,
+           -0.44920554655837563,
+           -0.4708861248680069,
+           -0.5008231401326855,
+           -0.5395603031745048,
+           -0.5874290701005614,
+           -0.6445340262504496,
+           -0.7107437328210164,
+           -0.7856873305359634,
+           -0.8687570530476701,
+           -0.9591166565356535,
+           -1.055715624825256,
+           -1.1573088649475098,
+           -1.2624814699929443,
+           -1.3696779978260072,
+           -1.4772355989346682,
+           -1.583420227289774,
+           -1.6864650870906106,
+           -1.784610407737371,
+           -1.8761436008559462,
+           -1.9594388377233867,
+           -2.0329950934536765,
+           -2.095471735674427,
+           -2.1457207894511074,
+           -2.1828150856313435,
+           -2.2060715947934906,
+           -2.215069361311829,
+           -2.2096615789854694,
+           -2.189981488146626,
+           -2.1564419208054115,
+           -2.109728471636245,
+           -2.0507864247813083,
+           -1.980801715828263,
+           -1.9011763512657995,
+           -1.8134988407392931,
+           -1.7195103172676405,
+           -1.6210671243098012,
+           -1.5201007336468495,
+           -1.418575922389184,
+           -1.3184481794526732,
+           -1.2216213305408639,
+           -1.12990636556426,
+           -1.0449824236442513,
+           -0.9683608390921863,
+           -0.9013530782875557,
+           -0.8450433039996517,
+           -0.8002661926870579,
+           -0.767590504381997,
+           -0.747308766999122,
+           -0.7394332906648986,
+           -0.7436985765141466,
+           -0.7595700320306339,
+           -0.7862587551313251,
+           -0.8227420054561257,
+           -0.8677888472186924,
+           -0.9199903267503946,
+           -0.9777934424591443,
+           -1.0395380778654146,
+           -1.1034960017522648,
+           -1.167910994852231,
+           -1.2310391409247163,
+           -1.2911883220178733,
+           -1.3467559830441829,
+           -1.3962642788380812,
+           -1.4383917863581765,
+           -1.4720010538706623,
+           -1.4961613655471635,
+           -1.5101662212467966,
+           -1.513545164288029,
+           -1.506069731427639,
+           -1.4877534455281873,
+           -1.458845918877176,
+           -1.4198212801628525,
+           -1.3713612771253723,
+           -1.3143335364573108,
+           -1.249765579436608,
+           -1.1788152931719351,
+           -1.1027386407515918,
+           -1.0228554569918635,
+           -0.9405142183619473,
+           -0.8570566950425704,
+           -0.773783389540227,
+           -0.6919206399877476,
+           -0.6125902179420781,
+           -0.5367821814184974,
+           -0.4653316558710341,
+           -0.3989001111064858,
+           -0.33796158338414295,
+           -0.28279416223141174,
+           -0.23347692409461182,
+           -0.18989235333001206,
+           -0.1517341488091592,
+           -0.11852017516241001,
+           -0.08961018493383026,
+           -0.06422781502062783,
+           -0.04148625082181809,
+           -0.02041685729585934,
+           -1.9040217631105167e-16
+          ],
+          [
+           0,
+           0.02103660874656932,
+           0.043931178091114284,
+           0.06961484159809968,
+           0.09892677057971053,
+           0.13258708105913228,
+           0.17117299595701208,
+           0.2150989132629351,
+           0.2646009300341967,
+           0.31972625689008777,
+           0.38032783115114227,
+           0.44606430210696146,
+           0.5164054224886516,
+           0.5906427396005386,
+           0.6679053412926946,
+           0.7471802795380478,
+           0.8273371711795466,
+           0.9071563645709105,
+           0.9853599651797038,
+           1.0606449352074634,
+           1.1317174239229975,
+           1.1973274482265681,
+           1.2563030279605962,
+           1.3075828880990232,
+           1.3502468700586003,
+           1.3835432462940942,
+           1.4069122048311942,
+           1.4200048617044811,
+           1.4226972671775577,
+           1.4150989934836196,
+           1.397556024638389,
+           1.3706478093648435,
+           1.3351784828530777,
+           1.2921624083691563,
+           1.2428043320108395,
+           1.1884745796387535,
+           1.130679850797034,
+           1.0710302771246067,
+           1.011203509511985,
+           0.9529066766320341,
+           0.897837115469732,
+           0.8476428105985813,
+           0.8038834922407647,
+           0.7679933332073599,
+           0.7412461518198717,
+           0.7247239726098766,
+           0.7192897202765567,
+           0.725564726869038,
+           0.7439116197446081,
+           0.7744230312478184,
+           0.816916433325292,
+           0.870935254781071,
+           0.9357562891278115,
+           1.0104032506490397,
+           1.0936661890252866,
+           1.1841263322887343,
+           1.280185797393905,
+           1.3801014905178284,
+           1.4820224182005166,
+           1.5840295480798348,
+           1.6841772962828316,
+           1.7805356790221836,
+           1.87123214958296,
+           1.9544921490760214,
+           2.028677429908383,
+           2.0923212641334716,
+           2.1441597233971246,
+           2.183158311268158,
+           2.208533340037574,
+           2.2197675698699912,
+           2.216619765422726,
+           2.1991279703624684,
+           2.1676064500615295,
+           2.1226364034921192,
+           2.0650506932867354,
+           1.9959129844965637,
+           1.9164918143196907,
+           1.8282302337940044,
+           1.7327117652869441,
+           1.6316235040906362,
+           1.5267172565263256,
+           1.419769649159878,
+           1.3125421630553282,
+           1.2067420430344273,
+           1.1039850048297546,
+           1.0057606135483579,
+           0.9134011362837421,
+           0.8280545818257793,
+           0.7506625334923275,
+           0.6819432598308559,
+           0.6223804553490582,
+           0.5722178228395015,
+           0.5314595637643832,
+           0.4998766971657251,
+           0.4770189842811593,
+           0.4622320990176282,
+           0.45467955704321417,
+           0.4533688016323187,
+           0.4571807453485327,
+           0.4649019855861225,
+           0.4752588508754005,
+           0.4869523951484082,
+           0.4986934397818202,
+           0.5092367685469751,
+           0.5174136083989884,
+           0.522161578562456,
+           0.5225513603140487,
+           0.5178094284070023,
+           0.5073362899521668,
+           0.4907197950826218,
+           0.4677432128642587,
+           0.4383879023921479,
+           0.4028305493711897,
+           0.3614350791666338,
+           0.3147394947685568,
+           0.26343801887311563,
+           0.2083590400431666,
+           0.15043947062716628,
+           0.0906962160746819,
+           0.030195529174269927,
+           -0.029978923303594772,
+           -0.08875842140495746,
+           -0.14512110951288434,
+           -0.19812261167179002,
+           -0.2469245196635585,
+           -0.29081998385692404,
+           -0.32925571173993606,
+           -0.3618497718565804,
+           -0.3884047092583455,
+           -0.40891559981151654,
+           -0.42357280170806644,
+           -0.4327593000002117,
+           -0.4370426804385421,
+           -0.4371619087849948,
+           -0.43400922754901916,
+           -0.4286076103117942,
+           -0.42208433119841804,
+           -0.4156413106384668,
+           -0.4105229856705606,
+           -0.4079825214554244,
+           -0.4092472285890806,
+           -0.4154840769886562,
+           -0.42776620083643346,
+           -0.44704127015339656,
+           -0.47410256343829493,
+           -0.5095635134158977,
+           -0.5538364157861281,
+           -0.6071158909486623,
+           -0.6693675734382091,
+           -0.7403223760745058,
+           -0.8194765387567086,
+           -0.9060975288028696,
+           -0.9992357142961314,
+           -1.0977415876629257,
+           -1.200288177265899,
+           -1.3053981536256958,
+           -1.4114750172740602,
+           -1.5168376501890173,
+           -1.6197574249208662,
+           -1.7184969971137545,
+           -1.8113498599144011,
+           -1.8966797139688003,
+           -1.9729587050201505,
+           -2.0388036026476497,
+           -2.09300903796421,
+           -2.134576984098091,
+           -2.1627417494570653,
+           -2.17698985805292,
+           -2.1770743110386364,
+           -2.163022856181838,
+           -2.1351400340511075,
+           -2.0940029177736275,
+           -2.0404506137275495,
+           -1.9755677397904745,
+           -1.9006622421331965,
+           -1.817238047497224,
+           -1.7269631721015672,
+           -1.6316340177487079,
+           -1.5331366776622128,
+           -1.433406146835358,
+           -1.334384382429538,
+           -1.2379781877868843,
+           -1.146017898222812,
+           -1.060217827825098,
+           -0.9821393944649829,
+           -0.913157776148085,
+           -0.8544328672620072,
+           -0.8068852002791962,
+           -0.7711773795633778,
+           -0.7477014420096293,
+           -0.7365724175428523,
+           -0.7376282144647206,
+           -0.750435803885773,
+           -0.7743035276804391,
+           -0.8082992092048584,
+           -0.8512736089498403,
+           -0.901888641689817,
+           -0.9586496605736142,
+           -1.019941019664406,
+           -1.0840640519289724,
+           -1.1492765463738766,
+           -1.2138327771783093,
+           -1.2760231299752385,
+           -1.3342123860089017,
+           -1.3868757632992899,
+           -1.432631874163163,
+           -1.4702718389310225,
+           -1.4987838944185015,
+           -1.5173729501712603,
+           -1.5254746728338544,
+           -1.5227638160126196,
+           -1.509156656295858,
+           -1.4848075420980953,
+           -1.4500997070883617,
+           -1.4056306405538945,
+           -1.352192439669844,
+           -1.2907476900274886,
+           -1.2224015279396112,
+           -1.1483706283738615,
+           -1.0699499336696234,
+           -0.9884779887560416,
+           -0.905301777214144,
+           -0.8217419585696545,
+           -0.739059390585037,
+           -0.6584237815257318,
+           -0.5808852574456791,
+           -0.5073495500367484,
+           -0.43855741356843736,
+           -0.37506876739535566,
+           -0.31725193629077264,
+           -0.2652782276349754,
+           -0.21912194562892648,
+           -0.17856580173457415,
+           -0.1432115410292157,
+           -0.11249546962770193,
+           -0.08570844216887256,
+           -0.062019753763056545,
+           -0.0405042806439827,
+           -0.020172130583058195,
+           -1.9038664723107595e-16
+          ],
+          [
+           0,
+           0.02141808402658015,
+           0.04511528500747241,
+           0.07196800694582536,
+           0.10274699697208296,
+           0.13809227500464594,
+           0.17849165587652543,
+           0.22426345206981527,
+           0.2755438369817115,
+           0.33227922795894504,
+           0.3942239182332969,
+           0.46094305066014535,
+           0.5318208872524471,
+           0.6060741904325542,
+           0.682770398194637,
+           0.7608501493768477,
+           0.8391536001899618,
+           0.9164498719725179,
+           0.9914688854313384,
+           1.0629347705610022,
+           1.129599995731902,
+           1.1902793353013936,
+           1.2438827932048178,
+           1.2894466204351942,
+           1.3261616066746327,
+           1.353397889600369,
+           1.3707256080317405,
+           1.3779308251016404,
+           1.3750262625786478,
+           1.362256514507703,
+           1.3400975443433043,
+           1.3092504113544954,
+           1.2706293157730113,
+           1.2253441943624928,
+           1.174678235264014,
+           1.1200608096945357,
+           1.0630364351158013,
+           1.0052304869095272,
+           0.9483124608046938,
+           0.8939576541388824,
+           0.843808178807791,
+           0.7994342412925385,
+           0.7622966248279268,
+           0.7337112855246865,
+           0.7148169285893693,
+           0.7065463637552206,
+           0.7096023522335602,
+           0.7244385529952896,
+           0.7512460565131224,
+           0.7899458621318683,
+           0.8401875141882147,
+           0.9013539653027498,
+           0.9725725864891365,
+           1.052732096497666,
+           1.1405050407289348,
+           1.2343753165916074,
+           1.3326701206020166,
+           1.433595585810119,
+           1.5352752889015584,
+           1.6357907367583802,
+           1.7332228940698593,
+           1.8256937879557809,
+           1.9114072231311783,
+           1.9886876619700504,
+           2.056016367412461,
+           2.1120639719442726,
+           2.1557187212699733,
+           2.186109744713277,
+           2.2026248232935792,
+           2.2049222579367327,
+           2.192936581176947,
+           2.1668780025562207,
+           2.127225627148593,
+           2.07471463459395,
+           2.010317749119679,
+           1.9352214657810565,
+           1.8507976212941233,
+           1.7585710063883246,
+           1.6601838079526767,
+           1.5573577411970556,
+           1.4518547828878003,
+           1.3454374452535305,
+           1.2398295357530351,
+           1.136678330477133,
+           1.037519049012295,
+           0.9437424571707184,
+           0.8565663426616638,
+           0.7770115096021143,
+           0.7058828232366812,
+           0.6437557092267095,
+           0.5909683755478143,
+           0.5476198827982296,
+           0.5135740441005152,
+           0.4884689923605233,
+           0.4717321139763232,
+           0.4625999175864806,
+           0.460142287321565,
+           0.46329046519515793,
+           0.47086801929900857,
+           0.481623985484541,
+           0.49426732187542277,
+           0.5075017890012654,
+           0.5200603641633118,
+           0.5307383168722053,
+           0.538424112309449,
+           0.5421273706858866,
+           0.5410031905127283,
+           0.5343722410953929,
+           0.5217361415145335,
+           0.5027877671159101,
+           0.4774162569441739,
+           0.4457066332658504,
+           0.4079340838467573,
+           0.3645530954511408,
+           0.3161817596339913,
+           0.2635816959591752,
+           0.20763415016755277,
+           0.14931292271089194,
+           0.08965486399641848,
+           0.029728734619121667,
+           -0.029396729760058384,
+           -0.08668468943830637,
+           -0.14116115043114932,
+           -0.19194416010326734,
+           -0.23827046150077438,
+           -0.27951888514981066,
+           -0.31522984158930695,
+           -0.3451203788411265,
+           -0.36909438383678805,
+           -0.3872476326138252,
+           -0.3998675276855873,
+           -0.4074274989959754,
+           -0.41057618380130084,
+           -0.4101216371545324,
+           -0.40701095494348316,
+           -0.402305812343298,
+           -0.3971545290052591,
+           -0.39276136554767,
+           -0.39035383154768416,
+           -0.3911488413014131,
+           -0.39631858865730724,
+           -0.40695702529355754,
+           -0.42404781751243986,
+           -0.4484346251310578,
+           -0.4807944930830971,
+           -0.5216150731731781,
+           -0.5711763018155622,
+           -0.629537051778169,
+           -0.696527154586874,
+           -0.7717450583134063,
+           -0.8545612462330785,
+           -0.9441273987454668,
+           -1.0393911375554745,
+           -1.1391160509830631,
+           -1.2419065659034487,
+           -1.346237108551635,
+           -1.4504848863490758,
+           -1.5529655287981319,
+           -1.651970749725483,
+           -1.745807137672209,
+           -1.8328351474621423,
+           -1.9115073548328925,
+           -1.980405047830665,
+           -2.0382722632284995,
+           -2.0840464327440076,
+           -2.1168848809805474,
+           -2.1361865129567477,
+           -2.1416081415191073,
+           -2.133075031137046,
+           -2.1107853715013727,
+           -2.0752085386597896,
+           -2.0270771496142963,
+           -1.9673730647624617,
+           -1.897307637663589,
+           -1.8182966498064386,
+           -1.7319304959666877,
+           -1.639940300239017,
+           -1.5441607411050169,
+           -1.4464904435445365,
+           -1.3488508552596794,
+           -1.2531445611056715,
+           -1.1612140038987655,
+           -1.0748015705468412,
+           -0.9955119701433731,
+           -0.9247777760635167,
+           -0.8638289285331329,
+           -0.8136668994502028,
+           -0.7750441097342556,
+           -0.748449063884542,
+           -0.7340975298066466,
+           -0.7319299476534694,
+           -0.7416151029388278,
+           -0.7625599501392213,
+           -0.7939253270300285,
+           -0.8346471606564405,
+           -0.8834626365000555,
+           -0.9389406862030129,
+           -0.9995160489602755,
+           -1.063526079799047,
+           -1.1292494163900488,
+           -1.1949455762338483,
+           -1.2588945389549249,
+           -1.3194353743749274,
+           -1.3750030058156595,
+           -1.4241622489309749,
+           -1.4656383379719091,
+           -1.4983432419292633,
+           -1.5213971801877817,
+           -1.5341448684749983,
+           -1.5361661579659884,
+           -1.5272808701195344,
+           -1.5075477736970724,
+           -1.4772577948832062,
+           -1.4369216929094533,
+           -1.3872525685869637,
+           -1.3291436983537124,
+           -1.263642298762678,
+           -1.191919923032151,
+           -1.115240269994604,
+           -1.03492524461644,
+           -0.9523201468159842,
+           -0.8687588807136054,
+           -0.7855300693923574,
+           -0.7038449309769693,
+           -0.6248077211556881,
+           -0.5493894765080444,
+           -0.47840570399710225,
+           -0.4124985570246488,
+           -0.3521239202153383,
+           -0.29754369660223917,
+           -0.2488234553946139,
+           -0.20583545945349127,
+           -0.1682669524996882,
+           -0.13563345044748568,
+           -0.10729665251818253,
+           -0.08248646918756397,
+           -0.060326558547434364,
+           -0.039862672968768435,
+           -0.020093046298165784,
+           -1.918439364245441e-16
+          ],
+          [
+           0,
+           0.021936357519357658,
+           0.04654332314564361,
+           0.07463586226451417,
+           0.10691082342380279,
+           0.1439240659696543,
+           0.1860714782900345,
+           0.23357440841790136,
+           0.28646991434365765,
+           0.34460611637049043,
+           0.407642801379933,
+           0.4750572923114369,
+           0.5461554589577328,
+           0.6200876118154125,
+           0.6958688926176503,
+           0.7724036565701387,
+           0.8485132352338538,
+           0.9229663781599352,
+           0.9945115981144439,
+           1.0619105909277642,
+           1.1239718680730935,
+           1.1795837289073725,
+           1.227745710438567,
+           1.2675976853043427,
+           1.2984458325988861,
+           1.319784779976391,
+           1.331315307301805,
+           1.3329571097670152,
+           1.324856239199058,
+           1.3073869732770964,
+           1.281148000306989,
+           1.2469529486560913,
+           1.2058154314107135,
+           1.1589289147604551,
+           1.107641849593018,
+           1.0534286265205235,
+           0.9978570220216025,
+           0.9425528948624893,
+           0.8891629651355699,
+           0.8393165612541362,
+           0.7945872516918145,
+           0.7564552873089975,
+           0.7262717664732277,
+           0.7052253991226457,
+           0.6943126882623167,
+           0.6943122694780148,
+           0.7057640527584746,
+           0.7289536985491627,
+           0.7639028342323325,
+           0.8103652811869198,
+           0.8678294195337275,
+           0.93552667109958,
+           1.0124459346136316,
+           1.0973536642579504,
+           1.188819146926746,
+           1.2852444082267738,
+           1.3848980654456653,
+           1.4859523501666279,
+           1.5865224462622574,
+           1.684707232548234,
+           1.7786304848093768,
+           1.8664815800807646,
+           1.9465547572737247,
+           2.017286022214637,
+           2.0772868410906917,
+           2.1253738428104447,
+           2.16059384602404,
+           2.1822436381861228,
+           2.1898840593608497,
+           2.183348079406522,
+           2.162742700422181,
+           2.1284446633984966,
+           2.0810900853078684,
+           2.02155829680897,
+           1.950950287829599,
+           1.8705622952010128,
+           1.7818551801727753,
+           1.6864203412943564,
+           1.5859429874593765,
+           1.4821636549753614,
+           1.3768388899510386,
+           1.2717020322232164,
+           1.1684250291694973,
+           1.0685821773258475,
+           0.9736166375586998,
+           0.8848104969723107,
+           0.8032590596062638,
+           0.7298499405918214,
+           0.6652474174814857,
+           0.609882360965862,
+           0.563947928421034,
+           0.5274010611364794,
+           0.49996968319295415,
+           0.48116536032583346,
+           0.4703010441676511,
+           0.46651340428581645,
+           0.4687891404347228,
+           0.475994573113539,
+           0.4869077341541611,
+           0.5002521224986597,
+           0.5147312549055499,
+           0.52906312786326,
+           0.542013715752217,
+           0.5524286609936365,
+           0.5592623637167606,
+           0.5616037500041898,
+           0.5586980871846059,
+           0.5499643196364443,
+           0.5350075164626495,
+           0.5136261501942938,
+           0.4858140601353556,
+           0.45175709166646516,
+           0.41182454029927773,
+           0.3665556630437691,
+           0.31664164634371866,
+           0.2629035362587652,
+           0.20626673979400018,
+           0.14773279370427053,
+           0.08834916653426095,
+           0.02917790935536894,
+           -0.0287360006172311,
+           -0.08439577231367881,
+           -0.13688253262105635,
+           -0.1853828776412763,
+           -0.22921350017979134,
+           -0.2678422262221537,
+           -0.30090488631580675,
+           -0.328217555765524,
+           -0.3497838176407169,
+           -0.3657968317432157,
+           -0.3766361276269278,
+           -0.3828591770792812,
+           -0.3851879376892397,
+           -0.3844906907829547,
+           -0.3817596207617144,
+           -0.37808469557872115,
+           -0.3746245068659538,
+           -0.3725748105409063,
+           -0.37313557246584395,
+           -0.3774773672432542,
+           -0.386708000359377,
+           -0.4018402240164996,
+           -0.42376139505823324,
+           -0.4532058798771679,
+           -0.49073094712949145,
+           -0.5366968060112726,
+           -0.5912513477996817,
+           -0.6543200337816366,
+           -0.7256012464030653,
+           -0.8045672855930291,
+           -0.8904710520889421,
+           -0.9823583176907358,
+           -1.0790853422339033,
+           -1.1793414621890497,
+           -1.281676149541337,
+           -1.3845299251427126,
+           -1.4862684109435615,
+           -1.5852187229205077,
+           -1.6797073432261211,
+           -1.768098567722275,
+           -1.848832604736233,
+           -1.9204624031680786,
+           -1.981688312993641,
+           -2.0313897282029125,
+           -2.0686529301984606,
+           -2.092794437040339,
+           -2.1033792685710804,
+           -2.100233656864813,
+           -2.08345186272889,
+           -2.0533968989580065,
+           -2.0106951062945093,
+           -1.9562246750445684,
+           -1.891098350450379,
+           -1.816640699676554,
+           -1.734360449215871,
+           -1.6459185204487885,
+           -1.5530924950883482,
+           -1.4577383287557057,
+           -1.3617501978370854,
+           -1.267019410424742,
+           -1.1753933354165782,
+           -1.0886353041632348,
+           -1.0083864163910092,
+           -0.9361301370405838,
+           -0.8731605042395788,
+           -0.8205546824895665,
+           -0.7791504913944104,
+           -0.7495294214173339,
+           -0.7320055171275087,
+           -0.7266203683787158,
+           -0.7331443042667994,
+           -0.7510837370869062,
+           -0.7796944574509358,
+           -0.8180005407831258,
+           -0.8648183930114343,
+           -0.9187853426250676,
+           -0.9783920802927233,
+           -1.0420181584869028,
+           -1.1079696941653507,
+           -1.1745183691716081,
+           -1.2399407967642788,
+           -1.302557319154964,
+           -1.3607693201536704,
+           -1.413094178454474,
+           -1.4581970496640735,
+           -1.494918747283702,
+           -1.5222990924246833,
+           -1.5395952165676086,
+           -1.5462944282983944,
+           -1.5421213905127849,
+           -1.5270394957018483,
+           -1.5012464701124328,
+           -1.4651643792724134,
+           -1.4194243440807983,
+           -1.3648464050178313,
+           -1.3024150888761383,
+           -1.2332513348894993,
+           -1.1585815227431246,
+           -1.0797044116155534,
+           -0.9979568455308354,
+           -0.9146791048081712,
+           -0.8311807857439157,
+           -0.7487080708605907,
+           -0.6684132106745762,
+           -0.5913269760718108,
+           -0.5183347596517761,
+           -0.45015690688565824,
+           -0.3873337461325983,
+           -0.33021566331884733,
+           -0.2789584355412493,
+           -0.23352390134412046,
+           -0.1936859073924271,
+           -0.15904133521223274,
+           -0.1290258810254097,
+           -0.10293413976322727,
+           -0.07994343417373197,
+           -0.05914073431262015,
+           -0.03955193403012536,
+           -0.020172691312177832,
+           -1.946905840445738e-16
+          ],
+          [
+           0,
+           0.022579372155995456,
+           0.04818814151171346,
+           0.07757384569422059,
+           0.1113547707958225,
+           0.14999942797976892,
+           0.19381017776677414,
+           0.24291145429681793,
+           0.29724292242182976,
+           0.3565577723389032,
+           0.42042622286498865,
+           0.48824416876680626,
+           0.5592467732332443,
+           0.6325266770199633,
+           0.7070563742989024,
+           0.781714194901458,
+           0.8553132362690776,
+           0.9266325084872521,
+           0.9944494943371598,
+           1.0575732849507702,
+           1.1148774314952892,
+           1.1653316549068102,
+           1.2080315790615221,
+           1.2422256973906745,
+           1.2673388477540373,
+           1.2829915538195182,
+           1.2890146912183607,
+           1.2854590509011699,
+           1.272599497596786,
+           1.2509335549715972,
+           1.2211743876872228,
+           1.1842382906157431,
+           1.141226933505698,
+           1.0934047419532893,
+           1.0421719193043226,
+           0.9890337259867595,
+           0.935566729933428,
+           0.8833828217400055,
+           0.8340918489760701,
+           0.7892637640594571,
+           0.7503911982602404,
+           0.7188533702023544,
+           0.6958822107117564,
+           0.6825315376053998,
+           0.6796500451483463,
+           0.6878587850609946,
+           0.7075337112399062,
+           0.7387937412888027,
+           0.7814946574236469,
+           0.8352290304870431,
+           0.899332207061356,
+           0.9728942545117966,
+           1.0547776157649364,
+           1.1436400882314437,
+           1.2379626128775483,
+           1.3360812431838427,
+           1.4362225624543181,
+           1.5365417341398053,
+           1.635162305578562,
+           1.7302168424159374,
+           1.819887450011288,
+           1.9024452398976113,
+           1.9762878237954034,
+           2.0399739642096346,
+           2.092254578129159,
+           2.132099377159787,
+           2.1587185314413877,
+           2.171578863390656,
+           2.170414207781152,
+           2.1552297137405008,
+           2.1263000085218415,
+           2.084161288878227,
+           2.0295975499813226,
+           1.9636213005745846,
+           1.8874492430663397,
+           1.8024735153975315,
+           1.7102291949052515,
+           1.6123588505547422,
+           1.51057499676363,
+           1.4066213480038745,
+           1.302233797365897,
+           1.1991020437732485,
+           1.0988327715668964,
+           1.0029152433097148,
+           0.9126901030064494,
+           0.8293221041137786,
+           0.753777376819647,
+           0.6868057346085236,
+           0.6289283939602256,
+           0.5804313462993662,
+           0.5413644813685597,
+           0.5115464195117686,
+           0.49057487043005105,
+           0.47784220126448634,
+           0.47255577068705007,
+           0.47376247113743614,
+           0.48037682123425773,
+           0.491211867149985,
+           0.5050120873827727,
+           0.5204874514234157,
+           0.5363477603285844,
+           0.5513363966624237,
+           0.564262632599979,
+           0.5740316875940977,
+           0.5796717897596245,
+           0.5803575763902918,
+           0.5754292667015984,
+           0.5644071514864706,
+           0.5470010670359567,
+           0.5231146512981393,
+           0.49284431551433283,
+           0.45647300106093047,
+           0.414458925490425,
+           0.36741965041980024,
+           0.31611192371715896,
+           0.26140785637329794,
+           0.20426808780065786,
+           0.1457126697336178,
+           0.08679045649556073,
+           0.028547826708979953,
+           -0.028002422373793228,
+           -0.08191117224403155,
+           -0.13232126349523066,
+           -0.1784931981672405,
+           -0.2198275703452107,
+           -0.2558836163949882,
+           -0.2863933770161206,
+           -0.31127107722839853,
+           -0.33061745459396197,
+           -0.34471889727062927,
+           -0.35404138856868295,
+           -0.359219390120292,
+           -0.36103992813362407,
+           -0.36042227313207187,
+           -0.3583937198706642,
+           -0.356062077813272,
+           -0.35458557099509275,
+           -0.355140917014483,
+           -0.35889040646262704,
+           -0.36694883495827196,
+           -0.38035114927484115,
+           -0.4000216565346227,
+           -0.4267456113524406,
+           -0.4611439409335525,
+           -0.5036517937839595,
+           -0.5545015056823758,
+           -0.6137104691439572,
+           -0.6810742724184762,
+           -0.7561653440770628,
+           -0.838337202669688,
+           -0.9267342711699553,
+           -1.0203070764411881,
+           -1.1178325182359403,
+           -1.217938763672007,
+           -1.319134204933774,
+           -1.4198398130997656,
+           -1.51842413214282,
+           -1.6132400865441003,
+           -1.7026627254154811,
+           -1.785126996852219,
+           -1.859164639229101,
+           -1.9234392915512937,
+           -1.9767789624658656,
+           -2.0182050562744873,
+           -2.0469572328792083,
+           -2.0625134751665306,
+           -2.0646048495678104,
+           -2.053224570714425,
+           -2.028631116198639,
+           -1.9913452791712132,
+           -1.9421411914020645,
+           -1.8820314939650227,
+           -1.812246973350403,
+           -1.7342111141188277,
+           -1.6495101419222953,
+           -1.5598592398249573,
+           -1.4670657136796252,
+           -1.372989956575476,
+           -1.2795051162406321,
+           -1.1884564014311185,
+           -1.1016209729674316,
+           -1.020669351945166,
+           -0.9471292420572006,
+           -0.882352605783026,
+           -0.8274867568142591,
+           -0.7834501353787497,
+           -0.7509133214302511,
+           -0.7302857157092915,
+           -0.7217081834999401,
+           -0.7250518138015626,
+           -0.7399228010671568,
+           -0.7656733111751837,
+           -0.8014180514400966,
+           -0.84605612967583,
+           -0.8982976628775929,
+           -0.9566944849942376,
+           -1.019674208208949,
+           -1.0855768154159342,
+           -1.1526929050077983,
+           -1.2193026740078157,
+           -1.2837147127983322,
+           -1.3443036944674018,
+           -1.3995460738210699,
+           -1.4480529645428364,
+           -1.4885994364536188,
+           -1.5201495664727982,
+           -1.5418766843975766,
+           -1.5531783753113357,
+           -1.553685931289714,
+           -1.5432680828390968,
+           -1.5220289817560209,
+           -1.4903005483390828,
+           -1.4486294336262193,
+           -1.3977589781743576,
+           -1.338606669627687,
+           -1.272237708976389,
+           -1.1998353873618466,
+           -1.1226690493053824,
+           -1.0420604725445015,
+           -0.9593495279673638,
+           -0.8758599946817288,
+           -0.7928663948223174,
+           -0.7115626806220577,
+           -0.633033553419049,
+           -0.5582291220304291,
+           -0.4879435181664435,
+           -0.42279798158696863,
+           -0.3632288101993208,
+           -0.30948044324961416,
+           -0.26160381239405056,
+           -0.21945995912781513,
+           -0.18272878124309683,
+           -0.1509226391118368,
+           -0.12340442796745758,
+           -0.09940960813101124,
+           -0.07807158416401803,
+           -0.05844973876921575,
+           -0.039559360038299136,
+           -0.020402653045908718,
+           -1.988303888215092e-16
+          ],
+          [
+           0,
+           0.023334001785766577,
+           0.050020830326554806,
+           0.08073537190149734,
+           0.11601352767370447,
+           0.15623416494096523,
+           0.2016054305480524,
+           0.2521558069473828,
+           0.30773016809052944,
+           0.3679909622598291,
+           0.43242451540219,
+           0.5003523148911186,
+           0.5709470033077783,
+           0.6432526881074496,
+           0.7162090590709124,
+           0.7886787041359087,
+           0.859476928151948,
+           0.9274033105121837,
+           0.9912741882631146,
+           1.049955222470062,
+           1.1023931981038855,
+           1.147646221758927,
+           1.1849115168199336,
+           1.2135500714395453,
+           1.2331074695267346,
+           1.2433303270587375,
+           1.244177863156675,
+           1.235828254870272,
+           1.218679553546829,
+           1.1933450758190922,
+           1.1606433202784323,
+           1.1215825983672718,
+           1.0773407014975507,
+           1.0292400525414522,
+           0.9787189054826622,
+           0.9272992592507032,
+           0.8765522380035417,
+           0.8280617581817137,
+           0.7833873507838806,
+           0.7440270342521591,
+           0.7113811383709964,
+           0.6867179624817951,
+           0.671142112449562,
+           0.6655663010786512,
+           0.6706873174706076,
+           0.686966774039565,
+           0.7146171278781109,
+           0.7535933486073348,
+           0.8035904707708382,
+           0.8640471285050394,
+           0.9341550270573618,
+           1.0128741632249456,
+           1.0989534684332491,
+           1.1909564173527603,
+           1.2872910248691642,
+           1.3862435478234651,
+           1.4860151178373395,
+           1.5847604599515155,
+           1.680627800495431,
+           1.7717990378434787,
+           1.8565292422381252,
+           1.9331845658691735,
+           2.00027768153682,
+           2.056499926597448,
+           2.100749407078973,
+           2.132154412955454,
+           2.150091607248816,
+           2.154198576158197,
+           2.1443804617702917,
+           2.120810539803574,
+           2.08392474885352,
+           2.034410321228816,
+           1.9731888052063868,
+           1.901393900990351,
+           1.8203446546228241,
+           1.7315146626098854,
+           1.6364980324737517,
+           1.5369729185999397,
+           1.4346635068450118,
+           1.3313013541305387,
+           1.2285869999223864,
+           1.128152754875022,
+           1.0315275383506852,
+           0.940104581884054,
+           0.8551127413529266,
+           0.7775920685140222,
+           0.7083741849845296,
+           0.6480678813860633,
+           0.5970502342183913,
+           0.5554633963323715,
+           0.5232170770151069,
+           0.49999658814694103,
+           0.4852761970854134,
+           0.4783373982210813,
+           0.47829159669615096,
+           0.48410659247965526,
+           0.49463616341977645,
+           0.5086519742160289,
+           0.5248769861926762,
+           0.5420195115398474,
+           0.5588070460283395,
+           0.5740190262678222,
+           0.5865176909941109,
+           0.5952762797351089,
+           0.5994038751049132,
+           0.5981662850258124,
+           0.5910024660688644,
+           0.5775361061580092,
+           0.5575821111240741,
+           0.5311478718220101,
+           0.4984293233911749,
+           0.4598019423376894,
+           0.4158069570670299,
+           0.36713317002069773,
+           0.31459490158988895,
+           0.25910666467653487,
+           0.20165526167070943,
+           0.143270060635721,
+           0.08499225301259333,
+           0.027843920040290973,
+           -0.027202261276479164,
+           -0.07925185951159158,
+           -0.12751530289312385,
+           -0.17133154997173677,
+           -0.21018817758273123,
+           -0.24373734008992595,
+           -0.27180716127031385,
+           -0.29440823893330775,
+           -0.3117350694602584,
+           -0.324162331679665,
+           -0.33223610351066885,
+           -0.3366602172139006,
+           -0.3382780865241662,
+           -0.3380504581653185,
+           -0.3370296482284682,
+           -0.33633091787446456,
+           -0.3371017203926753,
+           -0.34048961081224505,
+           -0.34760964848038184,
+           -0.3595121412546156,
+           -0.3771515766873135,
+           -0.401357560834496,
+           -0.43280853965937893,
+           -0.47200901251150257,
+           -0.51927086343101,
+           -0.5746993361006677,
+           -0.6381840646011468,
+           -0.7093954475218635,
+           -0.7877865205241322,
+           -0.8726003454314858,
+           -0.9628827957416277,
+           -1.0575004825596868,
+           -1.155163434738404,
+           -1.254452025739194,
+           -1.3538475304453423,
+           -1.451765600620605,
+           -1.5465918703093624,
+           -1.6367188441938543,
+           -1.7205831842670378,
+           -1.7967024941448273,
+           -1.8637107063950904,
+           -1.9203912063230755,
+           -1.9657068751004994,
+           -1.998826304804953,
+           -2.0191455261925406,
+           -2.0263046947436396,
+           -2.0201992991729107,
+           -2.0009855863063675,
+           -1.9690800338491619,
+           -1.9251528447466795,
+           -1.8701155801101947,
+           -1.8051031885365045,
+           -1.7314508246527744,
+           -1.650665975556669,
+           -1.5643965274126015,
+           -1.4743955030186982,
+           -1.382483282254149,
+           -1.290508178956153,
+           -1.2003062884388094,
+           -1.1136615385448203,
+           -1.0322668733445712,
+           -0.957687472445662,
+           -0.8913268609764399,
+           -0.8343966968200317,
+           -0.787890934264142,
+           -0.752564959024433,
+           -0.7289201711331434,
+           -0.7171943623464521,
+           -0.7173580966775309,
+           -0.7291171597703666,
+           -0.7519209985720586,
+           -0.7849769306489822,
+           -0.8272697659803433,
+           -0.8775863564659772,
+           -0.9345444727969046,
+           -0.9966253075521722,
+           -1.0622088198326027,
+           -1.1296110724242272,
+           -1.197122668929126,
+           -1.2630473765252852,
+           -1.3257400204991254,
+           -1.383642759366543,
+           -1.4353188936465138,
+           -1.4794834260323522,
+           -1.5150296741755118,
+           -1.5410513374515857,
+           -1.5568595334073263,
+           -1.561994445236358,
+           -1.556231355471487,
+           -1.5395809797894608,
+           -1.51228415496311,
+           -1.4748010731018124,
+           -1.4277953869875093,
+           -1.3721136352768677,
+           -1.3087605485594873,
+           -1.2388708949951899,
+           -1.1636786051238304,
+           -1.0844839774963846,
+           -1.0026198085362006,
+           -0.9194173105326,
+           -0.8361726804549791,
+           -0.7541151594559385,
+           -0.6743773791469378,
+           -0.5979687271412846,
+           -0.5257523826210846,
+           -0.45842657490132843,
+           -0.39651050663690984,
+           -0.3403352612829293,
+           -0.2900398847734919,
+           -0.24557269741370308,
+           -0.20669775707059482,
+           -0.1730062623067683,
+           -0.14393255746417585,
+           -0.11877428406288998,
+           -0.0967161171892587,
+           -0.07685643446398555,
+           -0.05823619098774814,
+           -0.039869218217457154,
+           -0.020773129414140976,
+           -2.0415559552076093e-16
+          ],
+          [
+           0,
+           0.024186203357072774,
+           0.052011046646416065,
+           0.08407234383327387,
+           0.12082065183865887,
+           0.16254379603289412,
+           0.2093559287046636,
+           0.26119142756260544,
+           0.31780381533806346,
+           0.37876975075117925,
+           0.44349800879364687,
+           0.5112432378259189,
+           0.5811241556961488,
+           0.6521457301474404,
+           0.7232247831668068,
+           0.7932183673398161,
+           0.8609541870558822,
+           0.925262280498821,
+           0.9850071412363993,
+           1.0391194418771104,
+           1.0866265271580835,
+           1.12668086989836,
+           1.158585729898902,
+           1.1818173219798584,
+           1.196042883312145,
+           1.2011341299694,
+           1.197175705743142,
+           1.184468349934995,
+           1.1635266420016865,
+           1.1350713163241033,
+           1.1000162766308954,
+           1.0594505733307789,
+           1.014615734852002,
+           0.9668789628474037,
+           0.9177028078126594,
+           0.8686120335904529,
+           0.8211584540618805,
+           0.776884581144622,
+           0.7372869585790365,
+           0.7037800699454934,
+           0.6776617015042373,
+           0.6600806109069046,
+           0.6520073022572522,
+           0.6542086375793909,
+           0.667226926159159,
+           0.6913640285841294,
+           0.7266708941459263,
+           0.772942821448661,
+           0.8297205957204868,
+           0.8962975157732911,
+           0.9717321822287855,
+           1.0548667799824256,
+           1.1443504553035688,
+           1.238667264719939,
+           1.336168061931348,
+           1.4351055931661845,
+           1.5336719929923208,
+           1.6300378135544331,
+           1.722391681991822,
+           1.8089796643450908,
+           1.8881434200040843,
+           1.9583562585575593,
+           2.0182562601112517,
+           2.066675689555083,
+           2.1026660231972967,
+           2.125518010504912,
+           2.134776311856649,
+           2.130248382348795,
+           2.1120074086510505,
+           2.0803892473529007,
+           2.0359834557280663,
+           1.9796186459083893,
+           1.9123425276944823,
+           1.835397130379484,
+           1.7501898069913868,
+           1.6582607225355552,
+           1.561247608776995,
+           1.4608486299012924,
+           1.3587842445665972,
+           1.256758969447318,
+           1.1564239469459692,
+           1.0593411954264278,
+           0.9669503747520725,
+           0.8805388342687803,
+           0.8012156263208481,
+           0.7298900680424851,
+           0.6672553200408371,
+           0.6137773255254291,
+           0.5696893205538508,
+           0.5349919886516932,
+           0.5094591945276125,
+           0.4926490953640033,
+           0.48392029757747124,
+           0.48245260522099975,
+           0.4872717963243062,
+           0.49727776812282515,
+           0.5112753136247717,
+           0.5280067322020472,
+           0.546185437286562,
+           0.5645297057267062,
+           0.5817957163001589,
+           0.5968090491446241,
+           0.6084938627817602,
+           0.6158990297821967,
+           0.6182205942787405,
+           0.6148200123670425,
+           0.6052377474372854,
+           0.5892019138309327,
+           0.5666317908337491,
+           0.5376361616439497,
+           0.5025065652412655,
+           0.4617056796664691,
+           0.4158511798118606,
+           0.36569552828698115,
+           0.31210226135913255,
+           0.256019420779759,
+           0.19845085427058146,
+           0.14042616075847195,
+           0.08297008978741646,
+           0.02707221707505287,
+           -0.026342290379980347,
+           -0.07644003566376968,
+           -0.12250414535201111,
+           -0.16395574891071424,
+           -0.2003716035502068,
+           -0.23149738443150683,
+           -0.2572562729602156,
+           -0.27775259827451365,
+           -0.2932704158400391,
+           -0.30426703904106966,
+           -0.3113616714584461,
+           -0.3153194158057591,
+           -0.3170310569980526,
+           -0.31748912846072225,
+           -0.31776086970440565,
+           -0.31895876686519076,
+           -0.32220943418904496,
+           -0.32862164161013946,
+           -0.33925432039733944,
+           -0.35508538459339617,
+           -0.37698219044695186,
+           -0.40567441957150274,
+           -0.4417301150168732,
+           -0.48553552417145857,
+           -0.5372793102628989,
+           -0.5969415874527487,
+           -0.6642881157594652,
+           -0.7388698642310069,
+           -0.8200280170939785,
+           -0.9069043613541429,
+           -0.9984568589087303,
+           -1.0934800750361977,
+           -1.1906300114386066,
+           -1.2884527789310425,
+           -1.3854164452502384,
+           -1.479945309811472,
+           -1.5704557917090567,
+           -1.6553930715161065,
+           -1.7332676026927711,
+           -1.8026906053392475,
+           -1.8624076737768296,
+           -1.9113296696132758,
+           -1.9485601326241158,
+           -1.9734185215266689,
+           -1.9854586936325263,
+           -1.984482144104286,
+           -1.9705456494101292,
+           -1.9439630925589564,
+           -1.9053013865727553,
+           -1.8553705540252123,
+           -1.7952081608929675,
+           -1.7260584389936027,
+           -1.6493465595907115,
+           -1.566648638184611,
+           -1.4796581541945208,
+           -1.3901495566245246,
+           -1.2999398957401709,
+           -1.2108493695632787,
+           -1.1246617014108833,
+           -1.0430852700741258,
+           -0.9677158974077193,
+           -0.9000021594777046,
+           -0.8412140279250622,
+           -0.7924155692879632,
+           -0.7544423336028737,
+           -0.7278839520212058,
+           -0.7130723391500836,
+           -0.7100757623741087,
+           -0.718698900789984,
+           -0.7384888739873658,
+           -0.7687470792031068,
+           -0.8085465378083969,
+           -0.8567543220013976,
+           -0.9120585131274508,
+           -0.9729990371268752,
+           -1.0380016327735828,
+           -1.1054141367757262,
+           -1.1735442181714961,
+           -1.2406976639858434,
+           -1.3052163095128135,
+           -1.3655147200105113,
+           -1.420114765657503,
+           -1.4676772874048916,
+           -1.5070301264438755,
+           -1.5371918824984834,
+           -1.5573908737262936,
+           -1.5670788909783475,
+           -1.5659394685455494,
+           -1.553890529088349,
+           -1.5310813988499978,
+           -1.497884327068586,
+           -1.4548807773293149,
+           -1.4028428851420427,
+           -1.3427105921842217,
+           -1.275565070574349,
+           -1.2025991377292056,
+           -1.1250854316990913,
+           -1.0443431667065008,
+           -0.9617043177617332,
+           -0.8784800910375791,
+           -0.7959285230305767,
+           -0.7152240168300121,
+           -0.6374295689934408,
+           -0.5634723670240064,
+           -0.49412334715983325,
+           -0.42998119743322405,
+           -0.37146117440955567,
+           -0.31878897663430483,
+           -0.27199978677955283,
+           -0.23094246110276237,
+           -0.19528871247769297,
+           -0.16454700526684998,
+           -0.13808075989862983,
+           -0.11513035521785674,
+           -0.09483832025242449,
+           -0.07627702639912659,
+           -0.05847812819651228,
+           -0.040462957390321075,
+           -0.021273051987301846,
+           -2.1054818888701384e-16
+          ],
+          [
+           0,
+           0.025121176819867894,
+           0.054127350938447706,
+           0.08753567389017637,
+           0.12570927474070545,
+           0.16884443286488401,
+           0.2169624102273268,
+           0.2699061759006424,
+           0.32734212806353674,
+           0.38876678835530604,
+           0.45351831353095395,
+           0.5207925431599493,
+           0.5896631828477467,
+           0.6591056131672001,
+           0.7280237179535282,
+           0.7952790443103006,
+           0.8597215426837791,
+           0.9202210903449848,
+           0.9756989767547437,
+           1.0251585252537831,
+           1.0677140424728404,
+           1.1026173244253437,
+           1.1292810055383655,
+           1.1472981125109425,
+           1.156457277014858,
+           1.1567531676074894,
+           1.1483918191842601,
+           1.1317906649390794,
+           1.1075732079809075,
+           1.0765584041840937,
+           1.0397449611768368,
+           0.9982908872632362,
+           0.9534887453002064,
+           0.9067371770646957,
+           0.8595093606623125,
+           0.8133191445879193,
+           0.7696856650851093,
+           0.7300972968402639,
+           0.6959758096475258,
+           0.668641604865352,
+           0.6492808851542815,
+           0.6389155695722987,
+           0.6383767045640483,
+           0.648282041167873,
+           0.669018351798953,
+           0.7007289485835986,
+           0.7433067421149265,
+           0.7963930476634228,
+           0.8593822085172811,
+           0.9314319665982852,
+           1.0114793722094397,
+           1.098261891105349,
+           1.190343241311553,
+           1.286143377340753,
+           1.3839719384827542,
+           1.4820643931655635,
+           1.578620045085221,
+           1.6718410205205962,
+           1.7599713311361316,
+           1.8413351032621263,
+           1.914373083226648,
+           1.977676568357321,
+           2.030017973811186,
+           2.0703773249605737,
+           2.097964061730477,
+           2.112233652697617,
+           2.1128986402119185,
+           2.0999338702819443,
+           2.0735757992515516,
+           2.034315910019253,
+           1.9828884102905722,
+           1.9202525207090855,
+           1.8475697883963536,
+           1.7661769783472403,
+           1.6775551984452926,
+           1.5832960010888881,
+           1.4850652734564702,
+           1.3845657776407192,
+           1.2834992300882146,
+           1.183528816351287,
+           1.086243021982989,
+           0.9931216239091482,
+           0.905504629741889,
+           0.8245648767041144,
+           0.7512849090249349,
+           0.6864386451676764,
+           0.630578226747823,
+           0.5840263124616814,
+           0.5468739459675158,
+           0.5189839897670921,
+           0.4999999811090065,
+           0.4893601341293841,
+           0.4863160881018473,
+           0.4899558878364555,
+           0.4992305817285648,
+           0.5129837381593195,
+           0.5299831139396721,
+           0.5489536608729562,
+           0.5686110294050075,
+           0.587694722341118,
+           0.6050000668140397,
+           0.6194082086373283,
+           0.6299133889078401,
+           0.6356468367730965,
+           0.6358967027423154,
+           0.6301235614765706,
+           0.6179711289788958,
+           0.5992719635730305,
+           0.5740480498571883,
+           0.542506296665803,
+           0.5050291106410616,
+           0.46216033301778253,
+           0.4145869454900094,
+           0.363117058584503,
+           0.30865479011679414,
+           0.25217271969143723,
+           0.19468266587049762,
+           0.13720557406141928,
+           0.08074132434124458,
+           0.02623926882312715,
+           -0.02542971220881462,
+           -0.07349888678785015,
+           -0.11732839158260423,
+           -0.15642438473896506,
+           -0.19045411313222124,
+           -0.2192564824468171,
+           -0.24284783566999132,
+           -0.26142277042218676,
+           -0.2753499548870743,
+           -0.2851630326677864,
+           -0.291546835371248,
+           -0.29531924484706795,
+           -0.29740916165107967,
+           -0.2988311395465524,
+           -0.3006573350622689,
+           -0.3039874940102204,
+           -0.30991775154811496,
+           -0.31950905742991054,
+           -0.3337560525887417,
+           -0.353557216723446,
+           -0.3796870792207937,
+           -0.41277123817263245,
+           -0.4532648655811971,
+           -0.5014352927082862,
+           -0.557349169977084,
+           -0.6208645833312944,
+           -0.6916283862764819,
+           -0.769078877014544,
+           -0.852453816361048,
+           -0.9408036478375894,
+           -1.0330096498108001,
+           -1.1278066240974869,
+           -1.2238096092195538,
+           -1.3195440023985696,
+           -1.413478385058641,
+           -1.5040592743269565,
+           -1.589746969635785,
+           -1.6690516304242557,
+           -1.7405687090007222,
+           -1.8030128722212826,
+           -1.855249576599926,
+           -1.8963235130942417,
+           -1.9254832088992566,
+           -1.942201162438666,
+           -1.9461889922336228,
+           -1.9374071979309264,
+           -1.9160692596330453,
+           -1.882639936682678,
+           -1.8378277659235667,
+           -1.782571898795904,
+           -1.718023553020868,
+           -1.6455224847439534,
+           -1.5665690076498502,
+           -1.4827921937699151,
+           -1.3959149838164944,
+           -1.307717010602401,
+           -1.2199959955703505,
+           -1.1345286142668782,
+           -1.0530317408550791,
+           -0.9771249741042578,
+           -0.908295317892822,
+           -0.8478648388168677,
+           -0.7969620532292082,
+           -0.7564977076468846,
+           -0.7271455121067031,
+           -0.7093282682575399,
+           -0.7032097056218305,
+           -0.7086922036621576,
+           -0.7254204373581551,
+           -0.7527908433397514,
+           -0.789966665656511,
+           -0.8358982083426197,
+           -0.8893477992651594,
+           -0.9489188592923506,
+           -1.0130883752588338,
+           -1.0802419968387416,
+           -1.148710918142126,
+           -1.2168096660338144,
+           -1.2828738997387532,
+           -1.345297330621177,
+           -1.4025668969480436,
+           -1.4532953752815883,
+           -1.496250676689495,
+           -1.530381160529909,
+           -1.5548363990375937,
+           -1.568982939794594,
+           -1.572414737576651,
+           -1.5649580589343048,
+           -1.5466707989258235,
+           -1.5178362863027486,
+           -1.478951787779591,
+           -1.4307120504894864,
+           -1.3739883411821283,
+           -1.3098035482345618,
+           -1.2393040054971318,
+           -1.1637287731312194,
+           -1.0843771680800829,
+           -1.0025753742841756,
+           -0.9196429793434096,
+           -0.8368602796984372,
+           -0.7554371707368875,
+           -0.6764843922389039,
+           -0.6009878344745487,
+           -0.5297865277427699,
+           -0.46355484031931316,
+           -0.40278929915779194,
+           -0.34780032707890585,
+           -0.2987090626462248,
+           -0.25544929769014774,
+           -0.21777443581879025,
+           -0.18526924656378427,
+           -0.1573660672903468,
+           -0.13336499173429897,
+           -0.11245748285776981,
+           -0.09375276117609377,
+           -0.07630624996647203,
+           -0.05914930756495513,
+           -0.04131944556513259,
+           -0.021890220922771993,
+           -2.1788127918481135e-16
+          ],
+          [
+           0,
+           0.0261235309587004,
+           0.056337550894920436,
+           0.0910758088407067,
+           0.13061280139603706,
+           0.17505363907960178,
+           0.22432865425573487,
+           0.27819290888244325,
+           0.3362306324946833,
+           0.39786449205449326,
+           0.46236946883320734,
+           0.5288909965525956,
+           0.596466902676506,
+           0.6640525938738223,
+           0.7305488398429305,
+           0.7948314391227592,
+           0.8557819980346678,
+           0.9123190208696236,
+           0.9634284967358316,
+           1.0081931764834842,
+           1.0458197616765244,
+           1.0756632760211395,
+           1.0972479568219176,
+           1.110284088282531,
+           1.1146802977304013,
+           1.1105509476760356,
+           1.0982183782497839,
+           1.0782098829731959,
+           1.0512494328241702,
+           1.0182442958535731,
+           0.9802668288999529,
+           0.9385318409899702,
+           0.8943700417151406,
+           0.8491981893757294,
+           0.8044866404124957,
+           0.7617250713999384,
+           0.7223871958611501,
+           0.6878953290560611,
+           0.6595856638593128,
+           0.6386751095651693,
+           0.6262305131443787,
+           0.6231410298621269,
+           0.6300943384812874,
+           0.6475573072289137,
+           0.6757616124363526,
+           0.7146946947943308,
+           0.7640963113317093,
+           0.8234608076164694,
+           0.8920450975483286,
+           0.968882200814842,
+           1.0528000539769378,
+           1.1424451835223053,
+           1.236310711208168,
+           1.3327680565088516,
+           1.4301016105852116,
+           1.526545583131202,
+           1.6203221695337013,
+           1.709680152343553,
+           1.7929330389359102,
+           1.8684958467520247,
+           1.934919678448354,
+           1.9909232808933053,
+           2.035420853001509,
+           2.067545456158317,
+           2.0866674853076352,
+           2.092407776117594,
+           2.084645051145887,
+           2.0635175424964927,
+           2.0294187668167205,
+           1.982987567261566,
+           1.9250926728762094,
+           1.8568121554166315,
+           1.779408283798117,
+           1.6942983842199362,
+           1.6030224069545622,
+           1.507207976572472,
+           1.4085337591833484,
+           1.3086920167633573,
+           1.209351233958572,
+           1.1121196965797517,
+           1.018510873535208,
+           0.9299114059105085,
+           0.8475524395252735,
+           0.772484952280049,
+           0.7055596270833808,
+           0.6474117076311884,
+           0.5984511506230968,
+           0.558858257214196,
+           0.5285848318548919,
+           0.5073607814939013,
+           0.494705935743323,
+           0.48994674228703916,
+           0.4922373746541084,
+           0.5005846843432367,
+           0.5138763387343972,
+           0.5309114124532434,
+           0.5504326446358596,
+           0.5711595391835889,
+           0.5918214704115894,
+           0.6111899627761556,
+           0.62810934038757,
+           0.641524989034516,
+           0.6505085392230194,
+           0.6542793615624314,
+           0.6522218635860512,
+           0.6438981872787871,
+           0.6290560263974883,
+           0.6076314090741141,
+           0.5797464209914258,
+           0.5457019743395307,
+           0.505965854526122,
+           0.4611563970345936,
+           0.4120222578773124,
+           0.35941883999062857,
+           0.3042820221869798,
+           0.24759990481159766,
+           0.19038333536404528,
+           0.1336360068198974,
+           0.07832493050267063,
+           0.02535207390068734,
+           -0.024472077893848726,
+           -0.07045232960720582,
+           -0.11202931384831717,
+           -0.14879620726324666,
+           -0.18051117209105136,
+           -0.2071051819550826,
+           -0.22868501107830597,
+           -0.24553129224559145,
+           -0.25809167755148904,
+           -0.26696926400343324,
+           -0.272906570147622,
+           -0.2767654668945448,
+           -0.2795035726657111,
+           -0.2821477171354833,
+           -0.28576515679390535,
+           -0.29143328727963175,
+           -0.30020864032862904,
+           -0.3130959761276021,
+           -0.3310182842241199,
+           -0.3547884878171981,
+           -0.3850836076409154,
+           -0.42242208367748657,
+           -0.46714487700030416,
+           -0.5194008820099679,
+           -0.5791370734522143,
+           -0.6460936955119949,
+           -0.7198046748649999,
+           -0.7996033089526936,
+           -0.8846331481829237,
+           -0.9738638595538179,
+           -1.066111732636776,
+           -1.1600643701088735,
+           -1.254308997082685,
+           -1.3473637290671567,
+           -1.4377110599012726,
+           -1.5238327704371837,
+           -1.6042454176753211,
+           -1.6775355435541361,
+           -1.7423937432482484,
+           -1.7976467546838804,
+           -1.842286773568531,
+           -1.8754972605673446,
+           -1.896674587866459,
+           -1.905444969313649,
+           -1.901676229281805,
+           -1.8854840876742174,
+           -1.8572327691109507,
+           -1.8175298801208357,
+           -1.7672156357988933,
+           -1.7073466535087112,
+           -1.639174662479649,
+           -1.564120601350344,
+           -1.4837446878173493,
+           -1.3997131428034337,
+           -1.3137623335443724,
+           -1.227661163681359,
+           -1.1431725822622418,
+           -1.0620151064067576,
+           -0.9858252537008768,
+           -0.9161217601022797,
+           -0.8542724177408878,
+           -0.8014643054807654,
+           -0.758678104960563,
+           -0.7266670979942492,
+           -0.7059413300449144,
+           -0.6967573016866919,
+           -0.6991134185313221,
+           -0.7127512932159447,
+           -0.7371628540583971,
+           -0.771603077266867,
+           -0.8151080264901436,
+           -0.8665177582456257,
+           -0.924503537402184,
+           -0.9875987061919524,
+           -1.0542324656098772,
+           -1.1227657615655695,
+           -1.1915284213654118,
+           -1.2588566601251907,
+           -1.3231300721334576,
+           -1.382807239066276,
+           -1.4364591248303729,
+           -1.482799484704677,
+           -1.5207115928894392,
+           -1.5492706856342884,
+           -1.5677616244727526,
+           -1.5756914030642166,
+           -1.5727962487778546,
+           -1.5590432032819803,
+           -1.5346262017327046,
+           -1.499956804346988,
+           -1.4556498638916857,
+           -1.4025045347339145,
+           -1.3414811405868539,
+           -1.2736745162270264,
+           -1.2002845208687765,
+           -1.122584485569785,
+           -1.0418884024629524,
+           -0.9595176887018064,
+           -0.8767683622135642,
+           -0.7948794496420216,
+           -0.7150034097176671,
+           -0.6381792987097457,
+           -0.5653093300715503,
+           -0.4971393898077714,
+           -0.4342439647906087,
+           -0.3770158258858734,
+           -0.3256606842503832,
+           -0.2801969106537049,
+           -0.24046027740720854,
+           -0.2061135537363218,
+           -0.17666066144887477,
+           -0.1514649816505927,
+           -0.12977129795229705,
+           -0.11073076974177526,
+           -0.09342825295500176,
+           -0.07691122727697319,
+           -0.06021954928674052,
+           -0.04241523170782139,
+           -0.02261145010178457,
+           -2.2602056356953833e-16
+          ],
+          [
+           0,
+           0.027177453315198392,
+           0.05860904872038216,
+           0.09464325280137391,
+           0.13546559823924587,
+           0.18109126335206496,
+           0.23136243111360533,
+           0.2859505119466705,
+           0.34436318756183715,
+           0.4059561070132115,
+           0.4699489441727669,
+           0.5354454110838065,
+           0.601456717062221,
+           0.6669278716388213,
+           0.7307661528245066,
+           0.7918710027008766,
+           0.8491645715320477,
+           0.9016221105313693,
+           0.9483014126771524,
+           0.9883705206224439,
+           1.0211329603413668,
+           1.0460498177532682,
+           1.0627580517421567,
+           1.0710845288756803,
+           1.07105537046083,
+           1.0629003187472126,
+           1.0470519532208395,
+           1.0241397169347841,
+           0.9949788434819709,
+           0.9605544042657689,
+           0.9220008199347327,
+           0.8805772961008826,
+           0.83763974882969,
+           0.7946098772120247,
+           0.7529421162722308,
+           0.7140892615900167,
+           0.6794675958131624,
+           0.6504223656852288,
+           0.6281944557824282,
+           0.613889081837346,
+           0.6084472828325805,
+           0.6126209279880649,
+           0.6269518738364696,
+           0.6517558097208687,
+           0.6871112195943632,
+           0.7328537666292048,
+           0.7885762778040898,
+           0.8536343714853604,
+           0.9271576353276701,
+           1.0080661279123806,
+           1.09509184869916,
+           1.1868047002499647,
+           1.2816423572593425,
+           1.377943361384031,
+           1.4739826815643946,
+           1.5680089184302197,
+           1.658282289999508,
+           1.743112515244868,
+           1.8208957127436813,
+           1.8901494535503531,
+           1.9495451501151837,
+           1.9979370254994295,
+           2.0343869877910437,
+           2.0581848315545663,
+           2.068863298997344,
+           2.0662076556074442,
+           2.0502595653466,
+           2.021315185893073,
+           1.9799175416298394,
+           1.9268433677260508,
+           1.8630847494669858,
+           1.7898260037732066,
+           1.7084163616358348,
+           1.6203391082761276,
+           1.527177919846766,
+           1.4305811994587667,
+           1.332225259715675,
+           1.233777222721488,
+           1.1368585111636407,
+           1.043009785540113,
+           0.953658143403099,
+           0.8700873376399256,
+           0.7934116937961913,
+           0.7245543132009457,
+           0.6642300415099653,
+           0.6129335639089543,
+           0.5709328615534923,
+           0.5382681320047804,
+           0.5147561427081082,
+           0.49999985425295185,
+           0.4934030225059258,
+           0.4941893688546031,
+           0.501425798675541,
+           0.5140490524056924,
+           0.5308950935768083,
+           0.5507304757966828,
+           0.5722848874161591,
+           0.5942840495152869,
+           0.6154821403816828,
+           0.634692937830414,
+           0.6508189090051236,
+           0.6628775346826646,
+           0.6700242300824196,
+           0.6715713148251933,
+           0.6670025886767383,
+           0.6559831844002121,
+           0.6383644915210247,
+           0.6141840719776743,
+           0.5836606172829675,
+           0.5471841237095009,
+           0.5053015839491903,
+           0.45869860761592207,
+           0.4081774860057733,
+           0.35463230612055185,
+           0.29902179285860225,
+           0.24234061464005702,
+           0.1855899251630939,
+           0.12974793156171383,
+           0.07574127653329159,
+           0.02441799911523603,
+           -0.023477203687565378,
+           -0.06732475319821637,
+           -0.10664841997668331,
+           -0.1411295189076755,
+           -0.17061668350715947,
+           -0.195130949882959,
+           -0.21486600317508353,
+           -0.2301835655816058,
+           -0.24160403204247616,
+           -0.24979258408404803,
+           -0.25554113106076326,
+           -0.25974653804788556,
+           -0.2633856981378396,
+           -0.26748809135736784,
+           -0.2731065406885199,
+           -0.28128692598375754,
+           -0.2930376476037356,
+           -0.30929964254793785,
+           -0.3309177463693098,
+           -0.35861416445286187,
+           -0.3929647669916198,
+           -0.43437885439949186,
+           -0.4830829556099799,
+           -0.5391091227943565,
+           -0.6022880749353731,
+           -0.672247422165151,
+           -0.7484150758128099,
+           -0.8300278188695949,
+           -0.9161448813172439,
+           -1.005666237736417,
+           -1.0973552240010391,
+           -1.1898649587029515,
+           -1.2817679560426545,
+           -1.37158823277102,
+           -1.4578351445171898,
+           -1.5390381382178895,
+           -1.6137815786431944,
+           -1.680738798971982,
+           -1.738704538275477,
+           -1.786624962368848,
+           -1.8236245180257893,
+           -1.849028942761441,
+           -1.8623838415528398,
+           -1.8634683458387702,
+           -1.8523034864080592,
+           -1.829155037524747,
+           -1.7945307217886772,
+           -1.7491718005664834,
+           -1.6940392100417176,
+           -1.6302945347131748,
+           -1.559276235285233,
+           -1.4824716632706967,
+           -1.4014854974274404,
+           -1.3180053248423211,
+           -1.2337651598951553,
+           -1.150507745737984,
+           -1.0699465140324942,
+           -0.993728088718607,
+           -0.9233962082739007,
+           -0.8603579085232075,
+           -0.8058527553435669,
+           -0.7609258448528919,
+           -0.7264051996086534,
+           -0.7028840851377494,
+           -0.6907086543025829,
+           -0.689971200422924,
+           -0.7005091667979904,
+           -0.721909923551384,
+           -0.7535211858790447,
+           -0.7944668141446563,
+           -0.8436676090847167,
+           -0.899866597743464,
+           -0.9616582005062219,
+           -1.0275205792826645,
+           -1.0958503936847874,
+           -1.1649991377014313,
+           -1.23331019518123,
+           -1.2991557391918929,
+           -1.3609726083034686,
+           -1.4172963218032688,
+           -1.4667924450318026,
+           -1.5082845841786061,
+           -1.5407783752756248,
+           -1.5634809326347017,
+           -1.5758153350874124,
+           -1.5774298512873008,
+           -1.5682017349780588,
+           -1.5482355543084414,
+           -1.5178561526968235,
+           -1.4775964691279229,
+           -1.4281805698961638,
+           -1.370502358650976,
+           -1.3056005343422106,
+           -1.2346304548083327,
+           -1.1588336351625617,
+           -1.0795056630996087,
+           -0.9979633465164203,
+           -0.9155119216548463,
+           -0.833413142083149,
+           -0.7528550405034449,
+           -0.6749241073778309,
+           -0.6005805639703359,
+           -0.5306373243240912,
+           -0.4657431430645106,
+           -0.40637033623108054,
+           -0.3528073433790568,
+           -0.30515627397189804,
+           -0.26333545276982967,
+           -0.22708685074599566,
+           -0.195988163256454,
+           -0.16946917889105337,
+           -0.14683197360870773,
+           -0.127274368139779,
+           -0.10991600463748245,
+           -0.09382633322611533,
+           -0.07805375205207934,
+           -0.0616551168577999,
+           -0.043724828642099256,
+           -0.023422720809460437,
+           -2.3482584682386724e-16
+          ],
+          [
+           0,
+           0.0282668823288952,
+           0.060909188117895294,
+           0.09818908267346886,
+           0.1402036616505419,
+           0.18688023709166843,
+           0.23797639738896442,
+           0.2930848527527146,
+           0.3516429526540648,
+           0.41294663934107007,
+           0.4761684850161971,
+           0.5403793525724185,
+           0.6045731236577035,
+           0.6676938557287984,
+           0.7286646637691053,
+           0.7864175741832694,
+           0.839923569297596,
+           0.8882220316673397,
+           0.9304488082980028,
+           0.9658621457013673,
+           0.9938657967010891,
+           1.0140286678676629,
+           1.0261004607357904,
+           1.0300228584640816,
+           1.0259359199022853,
+           1.014179462399377,
+           0.9952893401487592,
+           0.969988653297942,
+           0.9391740512417271,
+           0.9038974182614229,
+           0.8653433478382276,
+           0.8248029205837235,
+           0.7836443970527855,
+           0.7432815182922534,
+           0.7051401717514691,
+           0.6706242264704969,
+           0.6410813680561827,
+           0.6177697701286954,
+           0.6018264244504868,
+           0.5942379171252198,
+           0.595814383870539,
+           0.60716730470561,
+           0.6286917091869488,
+           0.6605532597214147,
+           0.7026805649904364,
+           0.7547629509400169,
+           0.8162537861615785,
+           0.8863793249987569,
+           0.9641528986302978,
+           1.0483941549603382,
+           1.1377529255706151,
+           1.2307371852671767,
+           1.3257444696618796,
+           1.4210960312343932,
+           1.5150729465245623,
+           1.6059533381886202,
+           1.6920498468355887,
+           1.7717464795702975,
+           1.8435339752246946,
+           1.9060428600620933,
+           1.9580734214836446,
+           1.9986218996579013,
+           2.0269022862809445,
+           2.042363223690147,
+           2.0446996137723987,
+           2.033858671701821,
+           2.0100402914577886,
+           1.973691725102335,
+           1.9254967126526281,
+           1.8663593307904807,
+           1.7973829534145533,
+           1.7198448321343314,
+           1.6351669074397064,
+           1.5448835489751884,
+           1.4506069939909796,
+           1.3539913049422188,
+           1.2566956991318952,
+           1.1603481145030305,
+           1.0665098659517118,
+           0.9766422161386991,
+           0.8920756345149814,
+           0.8139824494235638,
+           0.7433535124290273,
+           0.6809793936018673,
+           0.6274365138488048,
+           0.5830784983311044,
+           0.5480329065748666,
+           0.5222033632260408,
+           0.5052769817867017,
+           0.49673684532860296,
+           0.4958791862674767,
+           0.5018347947837212,
+           0.5135940851389716,
+           0.5300351634033321,
+           0.5499541710471928,
+           0.572097128118879,
+           0.5951924685206632,
+           0.6179834489191667,
+           0.6392596222857008,
+           0.6578865966530355,
+           0.6728333485920739,
+           0.6831964278704512,
+           0.688220473023516,
+           0.6873145550117266,
+           0.6800639752732328,
+           0.6662372625350038,
+           0.6457882367319268,
+           0.6188531351693529,
+           0.5857429224550859,
+           0.5469310285416309,
+           0.5030368753735439,
+           0.45480565921471305,
+           0.40308495006773865,
+           0.3487987493348435,
+           0.29291971001921396,
+           0.23644026875887963,
+           0.18034346471211538,
+           0.12557422614914512,
+           0.07301189142635867,
+           0.023444697206563506,
+           -0.02245308578351541,
+           -0.06414075915260138,
+           -0.10122702070910179,
+           -0.13348158016257533,
+           -0.16084225103317812,
+           -0.18341732128011728,
+           -0.2014831284446639,
+           -0.21547689040407256,
+           -0.22598496696981502,
+           -0.23372684738454996,
+           -0.23953527123179008,
+           -0.2443329925079182,
+           -0.24910678601076133,
+           -0.2548793694855724,
+           -0.2626799722291805,
+           -0.2735143196037014,
+           -0.288334822133461,
+           -0.3080117570232828,
+           -0.33330620901680824,
+           -0.3648454969883302,
+           -0.4031017535019776,
+           -0.44837424821862304,
+           -0.5007759543579131,
+           -0.560224752692377,
+           -0.6264395523560469,
+           -0.6989414849520971,
+           -0.7770602010996684,
+           -0.8599451698460021,
+           -0.9465817545049113,
+           -1.0358117166451528,
+           -1.1263576862036502,
+           -1.2168510329048579,
+           -1.3058624849287375,
+           -1.3919347673544764,
+           -1.4736164771954299,
+           -1.5494963752773896,
+           -1.6182372587699236,
+           -1.678608582334242,
+           -1.7295170205672366,
+           -1.7700342091560644,
+           -1.7994209658707891,
+           -1.8171473737019934,
+           -1.8229082051491112,
+           -1.816633276549059,
+           -1.798492441739126,
+           -1.7688950623440176,
+           -1.7284839244424817,
+           -1.678123705066834,
+           -1.6188842236453207,
+           -1.5520188398842985,
+           -1.4789384776005046,
+           -1.4011818607506668,
+           -1.3203826407366468,
+           -1.2382341706974602,
+           -1.1564527410385992,
+           -1.0767401294385277,
+           -1.0007463370359178,
+           -0.9300333799640842,
+           -0.8660409819013419,
+           -0.8100549694009027,
+           -0.763179108505134,
+           -0.7263110400645844,
+           -0.7001228742369414,
+           -0.68504689418908,
+           -0.6812666977506444,
+           -0.6887139766200077,
+           -0.7070709988443014,
+           -0.7357787249413439,
+           -0.7740503544941324,
+           -0.820889971573703,
+           -0.8751158370529644,
+           -0.9353877666798367,
+           -1.0002379383252589,
+           -1.0681043924140765,
+           -1.1373664280928621,
+           -1.2063810556539531,
+           -1.273519644107543,
+           -1.337203902059713,
+           -1.3959403501862935,
+           -1.4483524840511126,
+           -1.493209885764443,
+           -1.5294536205035005,
+           -1.5562173472767222,
+           -1.5728436801771168,
+           -1.5788954540785918,
+           -1.5741616743626683,
+           -1.5586580607114557,
+           -1.5326222270444863,
+           -1.4965036700572478,
+           -1.4509488643317934,
+           -1.3967818795554547,
+           -1.3349810421268533,
+           -1.2666522567475524,
+           -1.1929996812299895,
+           -1.1152945078284253,
+           -1.034842645490291,
+           -0.9529521185756463,
+           -0.8709009983449765,
+           -0.7899066639209095,
+           -0.7110971500447547,
+           -0.6354852808218118,
+           -0.5639462132934622,
+           -0.4971989240284487,
+           -0.43579206830674005,
+           -0.38009452751347556,
+           -0.33029083895602745,
+           -0.2863815765342299,
+           -0.24818862370537645,
+           -0.215365155189734,
+           -0.18741002400151605,
+           -0.16368613867289694,
+           -0.14344231476461786,
+           -0.12583799744674076,
+           -0.10997018026662995,
+           -0.09490179098182068,
+           -0.07969077986662726,
+           -0.06341913007313912,
+           -0.045221013814867254,
+           -0.024309342215845638,
+           -2.4415260447965187e-16
+          ],
+          [
+           0,
+           0.029375679816000942,
+           0.0632055972336888,
+           0.10166545055369093,
+           0.1447652601459985,
+           0.19234732860770726,
+           0.24408892697399212,
+           0.29950964774972283,
+           0.3579832433834245,
+           0.41875365115413926,
+           0.48095479527570834,
+           0.5436336571461489,
+           0.6057760176292661,
+           0.6663342032777175,
+           0.7242561133407701,
+           0.778514767671872,
+           0.8281375982272265,
+           0.872234709209001,
+           0.9100253530411879,
+           0.9408619107611793,
+           0.9642507250700967,
+           0.9798692107538824,
+           0.9875787585849414,
+           0.9874330528827249,
+           0.9796815370712119,
+           0.9647678829840962,
+           0.943323445309518,
+           0.9161558092982773,
+           0.884232664511352,
+           0.8486613568279435,
+           0.810664582170958,
+           0.7715527856272903,
+           0.7326939163082586,
+           0.6954812592052703,
+           0.6613001186285251,
+           0.6314941621862373,
+           0.6073322487504201,
+           0.5899765580358174,
+           0.5804528133671785,
+           0.5796233435041293,
+           0.5881636650980231,
+           0.6065431859991487,
+           0.63501053316854,
+           0.6735838997067392,
+           0.7220466861428296,
+           0.7799485845366162,
+           0.8466121232243206,
+           0.9211445583804222,
+           1.0024548692007929,
+           1.0892754896096164,
+           1.1801882939999506,
+           1.2736542504757076,
+           1.3680460649371544,
+           1.4616830653698225,
+           1.552867519692026,
+           1.6399215438834505,
+           1.7212237407775068,
+           1.7952447142775856,
+           1.8605806287686362,
+           1.915984028551732,
+           1.9603911961500597,
+           1.9929454097747001,
+           2.013015557125139,
+           2.020209672681424,
+           2.0143830860501035,
+           1.9956409968272144,
+           1.964335423727975,
+           1.9210566091872334,
+           1.8666190920121737,
+           1.8020427867767141,
+           1.728529526423521,
+           1.6474356311286529,
+           1.5602411593059473,
+           1.4685165734429322,
+           1.3738876124215373,
+           1.2779992016787964,
+           1.1824792520725476,
+           1.0889031971987548,
+           0.9987600972310229,
+           0.9134210956941378,
+           0.8341109550069176,
+           0.7618833186628939,
+           0.6976002545132238,
+           0.6419165271032026,
+           0.5952689300389457,
+           0.5578708848235444,
+           0.5297123835822194,
+           0.5105652227778723,
+           0.49999334661134537,
+           0.4973679954601868,
+           0.5018872394590614,
+           0.5125993729809074,
+           0.5284295548811135,
+           0.5482090041193205,
+           0.5707060025841784,
+           0.5946579179878019,
+           0.6188034404706745,
+           0.641914227474239,
+           0.6628251724057433,
+           0.6804625530482429,
+           0.6938693744847683,
+           0.7022272969811013,
+           0.7048746298607866,
+           0.7013199755955474,
+           0.6912512215012043,
+           0.6745396967063688,
+           0.6512394364097491,
+           0.621581620726562,
+           0.5859643784926376,
+           0.5449382641545151,
+           0.4991878253717543,
+           0.4495097774521721,
+           0.39678838577035896,
+           0.34196872676484047,
+           0.28602855024390056,
+           0.22994949926583313,
+           0.1746884579768208,
+           0.12114979215829517,
+           0.07015922202259983,
+           0.022440022660624094,
+           -0.02140781437650053,
+           -0.0609249030043881,
+           -0.09580580502145643,
+           -0.12590803419651134,
+           -0.15125647663007866,
+           -0.17204310174998694,
+           -0.18862196135924578,
+           -0.20149959738796677,
+           -0.21132109928217588,
+           -0.21885216623490733,
+           -0.22495763482256084,
+           -0.2305770263680615,
+           -0.2366977481176571,
+           -0.2443266460459845,
+           -0.2544606531514575,
+           -0.26805730427123,
+           -0.28600589600530385,
+           -0.3091000580581519,
+           -0.338012470447125,
+           -0.37327241034570746,
+           -0.41524674405597983,
+           -0.46412489541173274,
+           -0.5199082238769639,
+           -0.5824041361505502,
+           -0.6512251369338532,
+           -0.7257929006044279,
+           -0.8053473189567356,
+           -0.8889603540835681,
+           -0.9755544030388451,
+           -1.0639247652174317,
+           -1.1527656973245064,
+           -1.2406994470653436,
+           -1.3263075776452014,
+           -1.4081638328469757,
+           -1.4848677484588226,
+           -1.5550781913107758,
+           -1.6175460028233533,
+           -1.671144939947928,
+           -1.714900142361049,
+           -1.7480134099385747,
+           -1.769884647580007,
+           -1.7801289236328943,
+           -1.7785886913335252,
+           -1.7653408373349615,
+           -1.7406983447501836,
+           -1.705206487189874,
+           -1.6596336018682518,
+           -1.6049566207654853,
+           -1.5423416658613047,
+           -1.4731201344723108,
+           -1.398760810782823,
+           -1.3208386370445568,
+           -1.2410008602300133,
+           -1.160931335121063,
+           -1.0823138112791688,
+           -1.0067950579147833,
+           -0.935948686676783,
+           -0.871240517646787,
+           -0.8139962986852463,
+           -0.765372533573444,
+           -0.7263311014448978,
+           -0.6976182605655771,
+           -0.6797485257732043,
+           -0.672993793341434,
+           -0.6773779625029218,
+           -0.6926771723748939,
+           -0.7184256397552616,
+           -0.7539269504378187,
+           -0.7982705275602309,
+           -0.8503528781854195,
+           -0.908903106793359,
+           -0.9725120843527647,
+           -1.039664576567776,
+           -1.1087735668029977,
+           -1.1782159597123965,
+           -1.2463688219063038,
+           -1.3116453067726426,
+           -1.3725294220069328,
+           -1.427608830176507,
+           -1.475604923925428,
+           -1.5153994869172713,
+           -1.546057337567868,
+           -1.5668444528916334,
+           -1.5772411818777434,
+           -1.576950278944557,
+           -1.5658996151929827,
+           -1.5442395552504216,
+           -1.5123351172597126,
+           -1.4707531598297319,
+           -1.4202449594271167,
+           -1.361724651822733,
+           -1.296244109125247,
+           -1.2249649072586308,
+           -1.1491281054592046,
+           -1.0700226078848822,
+           -0.9889529066043459,
+           -0.9072070144090593,
+           -0.8260253849066647,
+           -0.7465715865523364,
+           -0.6699054474895777,
+           -0.5969593206082411,
+           -0.5285180348281366,
+           -0.46520300141768683,
+           -0.40746083563424584,
+           -0.3555567368802237,
+           -0.3095727478687458,
+           -0.2694108880814807,
+           -0.23480103223297696,
+           -0.2053132836625748,
+           -0.18037447858879913,
+           -0.15928835283836873,
+           -0.14125881061244946,
+           -0.12541565737413551,
+           -0.11084209796222387,
+           -0.09660325806889718,
+           -0.0817749633203003,
+           -0.0654720059457957,
+           -0.04687514449587676,
+           -0.025256116855658435,
+           -2.538535710188768e-16
+          ],
+          [
+           0,
+           0.030487801917073284,
+           0.0654665238935023,
+           0.10502606782160806,
+           0.14909154356190296,
+           0.19742384603916116,
+           0.24962486974923467,
+           0.3051472331548618,
+           0.36330826727863136,
+           0.4233079107825805,
+           0.4842500508057811,
+           0.5451667574381299,
+           0.6050447822740778,
+           0.6628536299985922,
+           0.7175744679942853,
+           0.7682291136691101,
+           0.8139083332657572,
+           0.8537986995185464,
+           0.887207288371947,
+           0.9135835462836653,
+           0.9325377281563886,
+           0.9438553899935619,
+           0.947507517881089,
+           0.9436559834425569,
+           0.9326541328030798,
+           0.9150424384145356,
+           0.8915392677892048,
+           0.8630269471402967,
+           0.8305334180288488,
+           0.7952098983487556,
+           0.7583050624916184,
+           0.7211363467029732,
+           0.685059062155135,
+           0.651434058162803,
+           0.6215947197079023,
+           0.5968141059199937,
+           0.5782730387540311,
+           0.5670299336863117,
+           0.5639931271765622,
+           0.5698963997712413,
+           0.5852783203699832,
+           0.6104659480986405,
+           0.6455633255762124,
+           0.690445083616682,
+           0.7447553553368511,
+           0.807912070225037,
+           0.8791165690777237,
+           0.9573683520075118,
+           1.041484647123811,
+           1.1301243700499162,
+           1.221815937057233,
+           1.3149882999175244,
+           1.4080044909368794,
+           1.4991969040137456,
+           1.5869034935161084,
+           1.6695040484034873,
+           1.745455694950378,
+           1.8133267977843563,
+           1.8718284653588924,
+           1.9198429215710981,
+           1.9564480786707754,
+           1.980937736114034,
+           1.992836933423154,
+           1.991912099913958,
+           1.9781757675532299,
+           1.9518857422116256,
+           1.913538760044976,
+           1.8638587864723057,
+           1.8037802420444853,
+           1.7344265593325328,
+           1.6570845849014322,
+           1.5731754378101508,
+           1.4842225185376854,
+           1.3918174277916853,
+           1.2975846017402703,
+           1.2031454977029066,
+           1.1100831716083124,
+           1.019908075438523,
+           0.9340258697905693,
+           0.8537079944529571,
+           0.780065669834565,
+           0.7140279159553788,
+           0.6563240756607456,
+           0.6074712172405793,
+           0.5677666714862963,
+           0.5372858323731706,
+           0.5158852221206992,
+           0.5032106935224733,
+           0.4987105182929639,
+           0.5016529927963437,
+           0.5111480847728302,
+           0.5261725491876266,
+           0.5455978604136807,
+           0.5682202435734699,
+           0.5927920415441591,
+           0.6180536269607945,
+           0.6427650611419591,
+           0.6657367143278428,
+           0.6858580935839923,
+           0.7021241753234267,
+           0.7136586073112696,
+           0.7197332284877556,
+           0.7197834518412667,
+           0.7134191634165704,
+           0.70043090662003,
+           0.6807912423485133,
+           0.6546512990612012,
+           0.6223326496224828,
+           0.5843147704866511,
+           0.5412184505928441,
+           0.49378561939245175,
+           0.44285615319058774,
+           0.38934229421009475,
+           0.3342013756109229,
+           0.27840758666388277,
+           0.22292353438064091,
+           0.16867236061178642,
+           0.11651115690026721,
+           0.06720638366628699,
+           0.021411946526974257,
+           -0.0203494879008181,
+           -0.057701439704411876,
+           -0.0904244279242537,
+           -0.11846235665221425,
+           -0.14192430001714496,
+           -0.16108163135877065,
+           -0.1763605636311289,
+           -0.18833028820333267,
+           -0.19768701468736116,
+           -0.20523432228477678,
+           -0.21186033066135918,
+           -0.21851228304373368,
+           -0.22616920391930573,
+           -0.23581334661987097,
+           -0.248401180810356,
+           -0.26483468557282774,
+           -0.28593370993615935,
+           -0.3124101394074852,
+           -0.34484456485569387,
+           -0.3836660899984784,
+           -0.42913583722256027,
+           -0.48133462040612,
+           -0.54015515006551,
+           -0.6052990230798453,
+           -0.6762786292702188,
+           -0.7524239832169937,
+           -0.8328943649851809,
+           -0.9166945310172284,
+           -1.0026951394176828,
+           -1.0896569251397947,
+           -1.1762580629348556,
+           -1.2611240718153682,
+           -1.342859546356189,
+           -1.4200809491713415,
+           -1.491449666686277,
+           -1.5557045177406308,
+           -1.6116929119843995,
+           -1.6583998823540935,
+           -1.6949742625252222,
+           -1.7207513450439684,
+           -1.7352714373022833,
+           -1.7382938286794527,
+           -1.7298057907048792,
+           -1.7100263503660482,
+           -1.6794047018118057,
+           -1.638613250628602,
+           -1.58853541444129,
+           -1.5302484306340818,
+           -1.4650015433814048,
+           -1.3941900549371657,
+           -1.3193258274760182,
+           -1.2420049092101935,
+           -1.163873029857068,
+           -1.0865897640345594,
+           -1.0117921954789866,
+           -0.9410589292466025,
+           -0.8758752929012638,
+           -0.8176005412315431,
+           -0.7674378329042946,
+           -0.7264076827537003,
+           -0.6953255116862295,
+           -0.6747838194310825,
+           -0.6651393959294938,
+           -0.6665058676929838,
+           -0.6787517488737403,
+           -0.7015040361581143,
+           -0.734157255093094,
+           -0.7758877362827851,
+           -0.8256727761861142,
+           -0.8823142220118684,
+           -0.9444659162367808,
+           -1.010664346083561,
+           -1.0793617690650674,
+           -1.1489610292122814,
+           -1.2178512412048565,
+           -1.2844435021914125,
+           -1.3472057940097149,
+           -1.404696261682084,
+           -1.45559409685931,
+           -1.4987273162271726,
+           -1.533096803229257,
+           -1.5578960748395123,
+           -1.5725263412121566,
+           -1.5766065422117248,
+           -1.5699781682051415,
+           -1.5527048000320198,
+           -1.5250664316139966,
+           -1.487548765055575,
+           -1.4408277892240213,
+           -1.3857500657075188,
+           -1.323309247981673,
+           -1.2546194480850945,
+           -1.1808861379741427,
+           -1.1033753282455994,
+           -1.0233818037680078,
+           -0.9421972130982785,
+           -0.8610788060165269,
+           -0.7812195912201725,
+           -0.7037206448000032,
+           -0.6295662406728194,
+           -0.559602398209748,
+           -0.4945193518268917,
+           -0.43483834460414567,
+           -0.3809030356771029,
+           -0.3328756920501312,
+           -0.2907382126125986,
+           -0.2542979086008979,
+           -0.22319784364275136,
+           -0.19693142088758653,
+           -0.1748607974653618,
+           -0.1562386103091157,
+           -0.14023241462564193,
+           -0.12595116906440534,
+           -0.11247305158520474,
+           -0.09887385839432818,
+           -0.08425522587682381,
+           -0.06777192248541009,
+           -0.048657483850719226,
+           -0.02624750926438835,
+           -2.637803357123145e-16
+          ],
+          [
+           0,
+           0.03158746667630958,
+           0.06766115957758789,
+           0.10822666584964503,
+           0.15312711297836298,
+           0.20204628197090815,
+           0.2545162304539437,
+           0.309929232995808,
+           0.36755373270540864,
+           0.4265538926116453,
+           0.48601224016994066,
+           0.5449548159034713,
+           0.6023781697714918,
+           0.6572774980975279,
+           0.7086751811003691,
+           0.7556489671142538,
+           0.7973590548522197,
+           0.8330733494661543,
+           0.862190211115521,
+           0.8842580752337016,
+           0.8989914001944501,
+           0.9062824887440817,
+           0.9062088321323639,
+           0.8990357377986501,
+           0.8852141199621647,
+           0.8653734545691342,
+           0.8403100227106178,
+           0.8109706867692217,
+           0.7784325581621946,
+           0.7438790217362313,
+           0.7085726769528834,
+           0.673825837570726,
+           0.640969297500696,
+           0.6113201191870998,
+           0.5861492309778811,
+           0.5666496306815378,
+           0.5539059835319038,
+           0.5488663742514011,
+           0.5523169254594797,
+           0.5648599294268498,
+           0.5868960586823503,
+           0.6186111251977758,
+           0.6599677501241216,
+           0.7107021889485353,
+           0.7703264333390223,
+           0.8381355838638709,
+           0.9132203603265989,
+           0.9944844917713709,
+           1.080666609352334,
+           1.1703661551489228,
+           1.2620727213630774,
+           1.3541981495909297,
+           1.44511065112021,
+           1.5331701581741775,
+           1.6167640839799624,
+           1.6943426572953977,
+           1.7644530049108271,
+           1.8257711834848944,
+           1.8771314092202558,
+           1.9175517992075306,
+           1.9462560201885077,
+           1.9626903370303201,
+           1.9665356620199186,
+           1.957714324540396,
+           1.936391405899088,
+           1.9029706129978639,
+           1.858084794034094,
+           1.802581326348343,
+           1.737502727807686,
+           1.6640629557873416,
+           1.5836199591557139,
+           1.4976451362258636,
+           1.4076904232963903,
+           1.3153537924442413,
+           1.2222439723622218,
+           1.1299452214307926,
+           1.039982977537777,
+           0.9537911845641457,
+           0.8726820515809554,
+           0.7978189387657673,
+           0.7301929854048226,
+           0.6706040020634114,
+           0.6196460434016524,
+           0.5776979628050746,
+           0.5449191278419981,
+           0.5212503495687021,
+           0.5064199519831557,
+           0.4999547835948227,
+           0.5011958541822494,
+           0.5093181692618333,
+           0.5233542352875669,
+           0.5422206225610817,
+           0.5647469023338387,
+           0.589706221319243,
+           0.6158467420614164,
+           0.6419231621275844,
+           0.6667275292203477,
+           0.6891185928746293,
+           0.7080489757592678,
+           0.7225895076270105,
+           0.7319501410933694,
+           0.7354969587212993,
+           0.7327648830428608,
+           0.7234658125680579,
+           0.7074920246962352,
+           0.6849148077826241,
+           0.6559784063670684,
+           0.6210894826838889,
+           0.580802411053623,
+           0.5358008267673409,
+           0.48687594498809933,
+           0.43490224566979757,
+           0.3808111855299788,
+           0.3255636460992343,
+           0.2701218566253067,
+           0.2154215414138688,
+           0.16234503279683712,
+           0.11169606357220647,
+           0.06417690717321325,
+           0.02036847117379912,
+           -0.019286128374404413,
+           -0.054494075858637074,
+           -0.08512111507835189,
+           -0.11119533632363152,
+           -0.1329063865536785,
+           -0.150600117349656,
+           -0.16476880468971433,
+           -0.176037190630583,
+           -0.18514470673125238,
+           -0.19292433972849438,
+           -0.2002786890067951,
+           -0.20815384052345096,
+           -0.21751174112838997,
+           -0.229301799129941,
+           -0.24443246040987351,
+           -0.2637435137544797,
+           -0.2879798641933189,
+           -0.3177674793571383,
+           -0.3535921619906472,
+           -0.3957817330492495,
+           -0.4444921259612564,
+           -0.4996977957211789,
+           -0.5611867388994595,
+           -0.6285603050856173,
+           -0.7012378596065315,
+           -0.7784662345945838,
+           -0.8593337836954947,
+           -0.9427887379583102,
+           -1.027661449702192,
+           -1.1126900101993151,
+           -1.1965486384060648,
+           -1.277878163969134,
+           -1.3553178702239406,
+           -1.4275379233788297,
+           -1.4932715935845797,
+           -1.551346472699198,
+           -1.6007139123619178,
+           -1.6404759440879257,
+           -1.6699089996082679,
+           -1.6884838232704227,
+           -1.6958810572217613,
+           -1.6920020821751447,
+           -1.6769748093281074,
+           -1.6511542397296042,
+           -1.615117733115021,
+           -1.5696550558855509,
+           -1.5157534043631957,
+           -1.4545777216030917,
+           -1.387446740885962,
+           -1.315805293716423,
+           -1.2411935121330067,
+           -1.165213632117821,
+           -1.0894951649677318,
+           -1.0156592451571735,
+           -0.945282985438402,
+           -0.8798646721161595,
+           -0.8207906155204114,
+           -0.7693044330945508,
+           -0.7264794861126442,
+           -0.693195117193984,
+           -0.6701172462806269,
+           -0.6576837797521714,
+           -0.656095173371008,
+           -0.6653103675497685,
+           -0.685048185980863,
+           -0.7147941590648581,
+           -0.7538126049708977,
+           -0.8011636766842368,
+           -0.8557249660667563,
+           -0.9162171486233232,
+           -0.9812330579304327,
+           -1.0492694988344593,
+           -1.1187610454885821,
+           -1.1881150255804007,
+           -1.255746866766347,
+           -1.3201149759574298,
+           -1.3797543367870195,
+           -1.4333080449365498,
+           -1.4795560541182469,
+           -1.5174404760751392,
+           -1.546086864190997,
+           -1.5648210100581907,
+           -1.5731808931519866,
+           -1.5709235428614918,
+           -1.5580266965864984,
+           -1.5346852643561697,
+           -1.5013027363399454,
+           -1.458477791610367,
+           -1.4069864815920894,
+           -1.3477604669790264,
+           -1.2818618799564878,
+           -1.2104554620713337,
+           -1.1347786901595587,
+           -1.0561106468879944,
+           -0.9757404176626189,
+           -0.894935801340877,
+           -0.814913108285289,
+           -0.7368087862229264,
+           -0.6616535630182258,
+           -0.5903497271665432,
+           -0.5236520833322419,
+           -0.4621530237227125,
+           -0.4062720489637135,
+           -0.3562499571357003,
+           -0.31214779965144934,
+           -0.2738505807256712,
+           -0.2410755563747237,
+           -0.21338487222183847,
+           -0.1902021697944053,
+           -0.17083269122634373,
+           -0.15448632481124872,
+           -0.14030296086939745,
+           -0.12737947070540775,
+           -0.1147975824433412,
+           -0.10165190718595295,
+           -0.0870773677383032,
+           -0.07027530006505942,
+           -0.05053753423618014,
+           -0.027267815908764693,
+           -2.737849287116157e-16
+          ],
+          [
+           0,
+           0.0326593164669299,
+           0.06975994873334329,
+           0.11122542857802041,
+           0.1568205456075324,
+           0.20615689335385282,
+           0.2587027612179056,
+           0.313797118058088,
+           0.3706673257519964,
+           0.42845012273273986,
+           0.4862153308228374,
+           0.5429916658715584,
+           0.59779397561108,
+           0.6496511882541603,
+           0.6976342337008493,
+           0.7408831963860274,
+           0.7786329748924997,
+           0.8102367581093446,
+           0.8351866800984586,
+           0.8531310846633349,
+           0.8638879141973994,
+           0.8674538336560094,
+           0.864008807055713,
+           0.8539159581034864,
+           0.8377166655475097,
+           0.8161209646443139,
+           0.7899934457277173,
+           0.7603349562399605,
+           0.7282605208405374,
+           0.6949739926106371,
+           0.6617400344278511,
+           0.6298541011059579,
+           0.6006111480445443,
+           0.5752738294826857,
+           0.5550409680091342,
+           0.5410170762225479,
+           0.534183691312045,
+           0.5353732442739471,
+           0.5452461283988803,
+           0.5642715579069012,
+           0.5927127189455694,
+           0.6306166137380746,
+           0.6778088869370643,
+           0.7338938039258714,
+           0.7982594268262411,
+           0.8700879083552936,
+           0.9483706995051804,
+           1.0319283473475387,
+           1.119434447036952,
+           1.2094432100703334,
+           1.3004200215729431,
+           1.390774285037852,
+           1.478893795391439,
+           1.5631798419299845,
+           1.642082222563597,
+           1.7141333504343814,
+           1.777980653383601,
+           1.8324165054800978,
+           1.8764049869678234,
+           1.9091048431706459,
+           1.9298881023161452,
+           1.9383539147411968,
+           1.9343372890339954,
+           1.9179125216031276,
+           1.8893912420051793,
+           1.849315124048952,
+           1.798443439122435,
+           1.7377357502854631,
+           1.6683301604707999,
+           1.5915176328532223,
+           1.5087129935427583,
+           1.421423304007427,
+           1.3312143511714727,
+           1.2396760455162614,
+           1.1483875407286006,
+           1.0588828919616764,
+           0.972618053547038,
+           0.8909399814564206,
+           0.8150585518672692,
+           0.7460219361934464,
+           0.6846959866773598,
+           0.631748087248107,
+           0.5876358142981584,
+           0.5526006340416998,
+           0.5266667401048534,
+           0.5096450099931696,
+           0.5011419351597765,
+           0.5005732596001181,
+           0.5071819491598755,
+           0.5200600108145695,
+           0.5381735905671905,
+           0.5603907025087324,
+           0.5855108818266039,
+           0.612296012549726,
+           0.6395015575655533,
+           0.665907414445256,
+           0.6903476359019135,
+           0.711738287836873,
+           0.7291027699881963,
+           0.741593992825667,
+           0.7485128877725704,
+           0.7493228239444755,
+           0.7436596109370357,
+           0.7313368810759546,
+           0.7123467630878062,
+           0.686855879374572,
+           0.6551968179559612,
+           0.6178553446992714,
+           0.5754537288182358,
+           0.5287306521064584,
+           0.47851825754645433,
+           0.4257169636831412,
+           0.37126872571728986,
+           0.31612946131516145,
+           0.26124137774239603,
+           0.20750593667451872,
+           0.15575817394954347,
+           0.10674305411972085,
+           0.06109448490010948,
+           0.019317545907660407,
+           -0.018225598757089102,
+           -0.05132573135056156,
+           -0.07993228834322767,
+           -0.10415459202730713,
+           -0.12425856968604776,
+           -0.14065904217702005,
+           -0.15390777979070125,
+           -0.16467763427513318,
+           -0.17374315914526217,
+           -0.18195822319448027,
+           -0.19023120212985742,
+           -0.19949839841600164,
+           -0.21069638806186705,
+           -0.2247340239607524,
+           -0.24246483768274305,
+           -0.2646605749742803,
+           -0.2919865747704077,
+           -0.32497965787358324,
+           -0.36402913065914105,
+           -0.4093614327241543,
+           -0.4610288671916226,
+           -0.5189027506523568,
+           -0.5826712090023088,
+           -0.6518417284736523,
+           -0.7257484508852456,
+           -0.8035640815628122,
+           -0.8843161605258614,
+           -0.9669073353695747,
+           -1.0501391706134644,
+           -1.1327389357651636,
+           -1.2133887353069734,
+           -1.2907562802731525,
+           -1.3635265546845756,
+           -1.430433602058731,
+           -1.4902916482777833,
+           -1.5420247875631254,
+           -1.5846944879781604,
+           -1.6175242210911047,
+           -1.639920586045232,
+           -1.6514903797395095,
+           -1.6520531601573571,
+           -1.6416489567867671,
+           -1.6205408979521059,
+           -1.5892126469001737,
+           -1.5483606636671157,
+           -1.498881435031185,
+           -1.4418539371536314,
+           -1.3785177118189729,
+           -1.3102470446409515,
+           -1.2385218295499796,
+           -1.1648957859482643,
+           -1.0909627610747012,
+           -1.018321898715617,
+           -0.9485424852110528,
+           -0.8831292939812171,
+           -0.8234892402531191,
+           -0.7709001285094744,
+           -0.726482227096851,
+           -0.691173338568956,
+           -0.6657079522911633,
+           -0.6506009695785008,
+           -0.6461363835148685,
+           -0.6523611782308861,
+           -0.6690845886533535,
+           -0.6958827345891199,
+           -0.7321085155615988,
+           -0.7769065281771488,
+           -0.829232648989715,
+           -0.8878778157400835,
+           -0.951495441140934,
+           -1.0186318084497328,
+           -1.0877587289693111,
+           -1.1573076900014838,
+           -1.2257046888836176,
+           -1.2914049353330992,
+           -1.3529266107024522,
+           -1.4088828987158537,
+           -1.4580115471429678,
+           -1.499201282531851,
+           -1.531514478998302,
+           -1.554205575187555,
+           -1.5667348385725304,
+           -1.5687771906279964,
+           -1.560225927294998,
+           -1.5411912935427228,
+           -1.511993995682927,
+           -1.4731538573274516,
+           -1.4253739415053324,
+           -1.36952056962029,
+           -1.3065997649950873,
+           -1.2377307323592435,
+           -1.164117052771987,
+           -1.0870163245014957,
+           -1.0077090131004496,
+           -0.9274672875787333,
+           -0.847524613903783,
+           -0.7690468522646926,
+           -0.6931055612994553,
+           -0.6206541519441986,
+           -0.5525074572858922,
+           -0.489325194740132,
+           -0.4315996953275977,
+           -0.37964816436212506,
+           -0.3336096212821359,
+           -0.293446546595484,
+           -0.2589511439782417,
+           -0.2297560084824211,
+           -0.2053488805005016,
+           -0.18509106239077272,
+           -0.16823898305224239,
+           -0.15396831753325205,
+           -0.14140000590633273,
+           -0.12962746969718036,
+           -0.11774429624527129,
+           -0.10487165217043716,
+           -0.09018469682544374,
+           -0.0729372949553404,
+           -0.05248437401758901,
+           -0.028301334550551917,
+           -2.8372138025815163e-16
+          ],
+          [
+           0,
+           0.03368857354818333,
+           0.07173488021301784,
+           0.113983392544268,
+           0.1601248694125861,
+           0.20970421110768353,
+           0.26213246222973985,
+           0.3167026508239668,
+           0.3726090513084817,
+           0.4289693683025601,
+           0.4848492607815747,
+           0.5392885630522117,
+           0.5913285124727298,
+           0.6400392648433896,
+           0.6845469677259625,
+           0.7240596699221595,
+           0.7578913717841804,
+           0.7854835653168616,
+           0.8064236740811985,
+           0.8204598792215456,
+           0.8275119076260686,
+           0.8276774590655777,
+           0.8212340586296061,
+           0.8086362361591217,
+           0.7905080527778768,
+           0.7676311130829858,
+           0.7409283170961414,
+           0.7114437157929953,
+           0.6803189351518497,
+           0.648766723634673,
+           0.6180422545469029,
+           0.589412875860644,
+           0.5641270442511269,
+           0.5433832061298814,
+           0.5282993956497094,
+           0.5198843077626695,
+           0.5190105736628856,
+           0.5263909170395178,
+           0.5425578036521719,
+           0.5678471153957575,
+           0.6023862852044763,
+           0.6460872231529511,
+           0.6986442495254411,
+           0.7595371302383189,
+           0.8280391867620641,
+           0.9032303296186979,
+           0.9840147446522043,
+           1.0691428475332316,
+           1.1572370171693889,
+           1.2468205254374871,
+           1.3363490012429726,
+           1.4242437033169442,
+           1.50892582996867,
+           1.5888510663825504,
+           1.6625435616896038,
+           1.7286285391895382,
+           1.7858627735066293,
+           1.8331622174148943,
+           1.8696261273942858,
+           1.8945571190818273,
+           1.9074766796746616,
+           1.9081357717017866,
+           1.8965202788021935,
+           1.8728511664058727,
+           1.8375793555392241,
+           1.7913754333211065,
+           1.735114446033284,
+           1.6698561369670895,
+           1.59682109874251,
+           1.5173634058593066,
+           1.4329403755464485,
+           1.3450801715384284,
+           1.255348014624618,
+           1.165311794516429,
+           1.0765078890374293,
+           0.9904079886166806,
+           0.9083876967862796,
+           0.831697631553367,
+           0.7614376892915924,
+           0.6985350537594924,
+           0.6437264399715148,
+           0.597544958226246,
+           0.5603118702207088,
+           0.5321333896490233,
+           0.5129025569452285,
+           0.5023060949027855,
+           0.49983603180591935,
+           0.5048057643826347,
+           0.5163701271298876,
+           0.5335489399443021,
+           0.5552534248126226,
+           0.5803148165328709,
+           0.6075144436232237,
+           0.6356145248799875,
+           0.663388915166985,
+           0.6896530411857067,
+           0.7132922939455466,
+           0.7332881887168582,
+           0.7487416642484876,
+           0.7588929693902325,
+           0.7631376750239124,
+           0.7610384500905213,
+           0.7523323499482663,
+           0.7369334805426192,
+           0.7149310200110284,
+           0.6865826974113842,
+           0.6523039432924461,
+           0.6126530359351883,
+           0.5683126675592729,
+           0.5200684441023472,
+           0.4687849081194844,
+           0.4153797350323209,
+           0.36079679688461647,
+           0.3059788138581717,
+           0.2518403214445738,
+           0.199241670192958,
+           0.14896474566918444,
+           0.10169104943468382,
+           0.057982718692111496,
+           0.01826698436805348,
+           -0.017175523201683144,
+           -0.04821831284371888,
+           -0.07489221611167597,
+           -0.09738413054118668,
+           -0.11603135344552275,
+           -0.13131165249664134,
+           -0.1438293310424409,
+           -0.15429765129024625,
+           -0.1635180744640417,
+           -0.1723568613744674,
+           -0.18171964737360008,
+           -0.1925246605945715,
+           -0.2056752902841371,
+           -0.22203273193644146,
+           -0.24238943729276813,
+           -0.2674440800152265,
+           -0.2977787123704288,
+           -0.33383873542907105,
+           -0.37591623639333777,
+           -0.4241371634060423,
+           -0.47845271263681577,
+           -0.5386351969571612,
+           -0.604278552736688,
+           -0.6748035240341009,
+           -0.749467444653339,
+           -0.8273784211664522,
+           -0.9075136070204839,
+           -0.988741152091425,
+           -1.069845316196719,
+           -1.1495541515590102,
+           -1.2265690901563568,
+           -1.299595719071136,
+           -1.3673749917332754,
+           -1.4287141062815139,
+           -1.4825162846169073,
+           -1.5278087071032398,
+           -1.5637678978134415,
+           -1.589741912802366,
+           -1.6052687577378888,
+           -1.610090549571367,
+           -1.6041630376396865,
+           -1.5876602102185027,
+           -1.5609738303937788,
+           -1.524707867306218,
+           -1.4796679123579193,
+           -1.426845791820577,
+           -1.3673997044536177,
+           -1.3026303223430313,
+           -1.2339533925021555,
+           -1.1628694633780061,
+           -1.0909314321338937,
+           -1.0197106636455546,
+           -0.9507624691768533,
+           -0.8855917507544336,
+           -0.8256196158673937,
+           -0.7721517462816537,
+           -0.7263492649610535,
+           -0.6892027872747798,
+           -0.6615102682319487,
+           -0.6438591682167041,
+           -0.6366133577616708,
+           -0.6399050697670499,
+           -0.65363208796943,
+           -0.6774602362952473,
+           -0.7108311080168571,
+           -0.7529748494207761,
+           -0.8029276930164014,
+           -0.8595538230669276,
+           -0.9215710541359866,
+           -0.987579713888402,
+           -1.0560940467240973,
+           -1.1255753967607114,
+           -1.1944663886040865,
+           -1.2612253032060352,
+           -1.3243598443908133,
+           -1.3824595093428307,
+           -1.434225813020532,
+           -1.4784996711619687,
+           -1.5142853179023708,
+           -1.5407702202526106,
+           -1.5573405506462934,
+           -1.5635918880004493,
+           -1.5593349345491512,
+           -1.5445961572190863,
+           -1.5196133855286462,
+           -1.484826519879132,
+           -1.4408636216787125,
+           -1.3885227671197695,
+           -1.3287501469248233,
+           -1.2626149825419728,
+           -1.1912819029741164,
+           -1.1159814838962119,
+           -1.0379796905859586,
+           -0.9585469875393954,
+           -0.8789278799983699,
+           -0.8003116359888758,
+           -0.7238049023357276,
+           -0.650406875416563,
+           -0.5809876185178271,
+           -0.5162700343286714,
+           -0.4568159054813949,
+           -0.4030163105476883,
+           -0.35508661019753773,
+           -0.31306608116504725,
+           -0.2768221571893116,
+           -0.24605911918395296,
+           -0.22033096446715644,
+           -0.19905807976761994,
+           -0.18154724753578452,
+           -0.16701443220557696,
+           -0.15460972452883806,
+           -0.14344376963854877,
+           -0.13261496937817113,
+           -0.12123673251579521,
+           -0.10846404813796952,
+           -0.09351867771573996,
+           -0.07571229951555324,
+           -0.054466994199385985,
+           -0.029332531204025764,
+           -2.934472363064341e-16
+          ],
+          [
+           0,
+           0.034661187129016176,
+           0.07355975784662186,
+           0.11646481035062632,
+           0.16299798281864222,
+           0.21264347460341795,
+           0.2647619860709491,
+           0.3186082127820865,
+           0.373351436091161,
+           0.4280986702421431,
+           0.4819197577763215,
+           0.5338737522733624,
+           0.583035891489444,
+           0.6285244457689081,
+           0.6695267266800433,
+           0.7053235591927424,
+           0.735311556947237,
+           0.7590225933804543,
+           0.7761399303730606,
+           0.7865105489533405,
+           0.7901533213872549,
+           0.7872627683382184,
+           0.7782082560920864,
+           0.7635286043300035,
+           0.7439221917015733,
+           0.7202327615727775,
+           0.6934312409018746,
+           0.6645939884443413,
+           0.6348779817941149,
+           0.6054935337647643,
+           0.577675195234566,
+           0.5526515521111882,
+           0.531614657199364,
+           0.5156898525932491,
+           0.5059067343318582,
+           0.5031719884831768,
+           0.5082447870567007,
+           0.5217153741343521,
+           0.5439873987350013,
+           0.5752644629633203,
+           0.6155412540675482,
+           0.6645995195716152,
+           0.7220090283245313,
+           0.7871335399687651,
+           0.8591416839191987,
+           0.9370225294470741,
+           1.0196055138195725,
+           1.105584288481403,
+           1.1935439466221056,
+           1.28199101154413,
+           1.3693854961155054,
+           1.4541742909800208,
+           1.5348251044265173,
+           1.6098601607701029,
+           1.6778888671961496,
+           1.7376386812178979,
+           1.7879834516866908,
+           1.8279685647003927,
+           1.8568323003780258,
+           1.87402289550599,
+           1.8792109083584603,
+           1.8722965930951514,
+           1.853412109346253,
+           1.8229185150347902,
+           1.7813976141848917,
+           1.7296388534133098,
+           1.6686215780371945,
+           1.5994930684054598,
+           1.5235428765122179,
+           1.4421740697679803,
+           1.3568720608877611,
+           1.2691717584668716,
+           1.180623810622092,
+           1.0927607331820506,
+           1.0070637138793224,
+           0.9249308648606669,
+           0.847647658091902,
+           0.7763602228468965,
+           0.7120521128241937,
+           0.6555250643151367,
+           0.6073841683920327,
+           0.5680277717310415,
+           0.5376423051090354,
+           0.5162021186654457,
+           0.5034742816512364,
+           0.4990281845780342,
+           0.5022496663679414,
+           0.5123592811081392,
+           0.5284342209673929,
+           0.5494333261159884,
+           0.5742245411787726,
+           0.6016141225542516,
+           0.630376863160528,
+           0.6592865816956506,
+           0.6871461227455888,
+           0.7128161319916333,
+           0.7352419068519567,
+           0.7534776761808079,
+           0.7667077317590564,
+           0.7742639174677036,
+           0.7756390771210805,
+           0.7704961665368889,
+           0.7586728468914362,
+           0.7401814919405502,
+           0.7152046583742335,
+           0.6840861834875706,
+           0.647318184613568,
+           0.6055243376187723,
+           0.5594399046438762,
+           0.5098890618672169,
+           0.4577601443793904,
+           0.40397947564361975,
+           0.3494844822426384,
+           0.2951968098748993,
+           0.24199615350933282,
+           0.19069549334778013,
+           0.142018389344625,
+           0.09657893150374047,
+           0.054864872441471854,
+           0.017224384579897705,
+           -0.016143211037637772,
+           -0.04519250150932208,
+           -0.07003269198096833,
+           -0.09092394999288719,
+           -0.1082694797777524,
+           -0.12260353381249842,
+           -0.13457567546064586,
+           -0.14493170510776077,
+           -0.15449175028400458,
+           -0.16412609563873715,
+           -0.1747293893567061,
+           -0.187193907124814,
+           -0.20238258192095102,
+           -0.22110251698584618,
+           -0.24407969009346347,
+           -0.27193552985428904,
+           -0.30516599992442267,
+           -0.34412376574769243,
+           -0.3890039423373984,
+           -0.43983383249410124,
+           -0.4964669649708044,
+           -0.5585816339258899,
+           -0.6256840272485243,
+           -0.697115914847338,
+           -0.7720667516818672,
+           -0.8495899371091591,
+           -0.9286228648661077,
+           -1.0080102994186049,
+           -1.0865305269792895,
+           -1.1629236554503808,
+           -1.2359213787821524,
+           -1.3042774792702425,
+           -1.3667983172494564,
+           -1.4223725521396327,
+           -1.469999352060653,
+           -1.5088143809942343,
+           -1.5381129020045825,
+           -1.5573694011706578,
+           -1.5662532180480306,
+           -1.5646397627101538,
+           -1.5526170044321244,
+           -1.5304870303175604,
+           -1.498762590865413,
+           -1.4581586707221248,
+           -1.4095792436905565,
+           -1.3540994885002484,
+           -1.2929438529913457,
+           -1.2274604564847613,
+           -1.1590924106783098,
+           -1.0893467161780024,
+           -1.0197614528364625,
+           -0.9518720259001457,
+           -0.887177255459994,
+           -0.8271061031996421,
+           -0.7729858177520007,
+           -0.7260122483882459,
+           -0.6872230270174817,
+           -0.6574742517603693,
+           -0.6374212232821326,
+           -0.6275036896142333,
+           -0.6279359486719263,
+           -0.6387020426722629,
+           -0.6595561579668834,
+           -0.6900282203595062,
+           -0.7294345527801267,
+           -0.7768933422313453,
+           -0.8313445491217806,
+           -0.8915737872209621,
+           -0.956239609053113,
+           -1.0239035518566786,
+           -1.093062235196478,
+           -1.1621807544667873,
+           -1.2297265859840576,
+           -1.2942032098055973,
+           -1.3541826660285219,
+           -1.4083362888532074,
+           -1.4554629094067797,
+           -1.4945138820385204,
+           -1.5246143679286692,
+           -1.5450804024275093,
+           -1.5554313762677083,
+           -1.5553976731051684,
+           -1.5449233239701194,
+           -1.5241636602417836,
+           -1.4934780677209973,
+           -1.4534180622978603,
+           -1.4047110197088306,
+           -1.3482399952147732,
+           -1.285020161192846,
+           -1.216172469386921,
+           -1.1428952080055648,
+           -1.066434170478645,
+           -0.9880521813879062,
+           -0.9089987352246253,
+           -0.8304804950108359,
+           -0.753633370728056,
+           -0.6794968526649534,
+           -0.6089912133978954,
+           -0.5428981157399742,
+           -0.4818450745884844,
+           -0.42629412044072634,
+           -0.37653490397004413,
+           -0.332682367193808,
+           -0.2946789902890368,
+           -0.2623015069460847,
+           -0.23517186820836267,
+           -0.21277212785298114,
+           -0.19446282419285,
+           -0.17950434617173877,
+           -0.16708069794255243,
+           -0.1563250175903783,
+           -0.14634616372765524,
+           -0.13625565937237008,
+           -0.1251942764008796,
+           -0.11235755606639138,
+           -0.09701959125313565,
+           -0.0785544435039352,
+           -0.056454631192610155,
+           -0.030346202889009535,
+           -3.028250144757066e-16
+          ],
+          [
+           0,
+           0.03556397042031615,
+           0.07521044741445719,
+           0.11863747398809663,
+           0.1654030155193898,
+           0.2149369870892549,
+           0.26655694234209765,
+           0.3194870118115124,
+           0.3728795929010815,
+           0.4258392206348752,
+           0.4774479897525418,
+           0.5267918562219984,
+           0.5729871208779557,
+           0.6152063903356156,
+           0.6527033207970557,
+           0.6848354786308737,
+           0.7110846969834344,
+           0.7310743690610774,
+           0.7445831945915458,
+           0.7515549844480166,
+           0.7521042272990566,
+           0.746517228966364,
+           0.7352487472593502,
+           0.7189141596045603,
+           0.6982773149244522,
+           0.6742343320746961,
+           0.6477937119284333,
+           0.6200532262526682,
+           0.5921741314209129,
+           0.5653533265855993,
+           0.5407941323593224,
+           0.5196764058650246,
+           0.5031267301618599,
+           0.492189419923076,
+           0.4877990706755287,
+           0.49075534620600886,
+           0.5017006486473152,
+           0.521101249460026,
+           0.5492323786119927,
+           0.5861676756801705,
+           0.6317733026299921,
+           0.685706906199592,
+           0.7474215008630093,
+           0.8161742241337119,
+           0.8910397974243695,
+           0.9709284107174415,
+           1.0546076407572735,
+           1.1407279130287526,
+           1.227850929901463,
+           1.3144804131726007,
+           1.3990944506830565,
+           1.4801786951750018,
+           1.55625964015513,
+           1.6259371928309911,
+           1.6879157783461909,
+           1.7410332422381354,
+           1.7842868685092284,
+           1.8168558977322946,
+           1.838120011589671,
+           1.8476733451917653,
+           1.8453336941348446,
+           1.8311466969769261,
+           1.8053848928730127,
+           1.7685416756231305,
+           1.7213202863948305,
+           1.6646181049444946,
+           1.599506610421895,
+           1.5272074850979407,
+           1.4490654251254813,
+           1.3665182995288008,
+           1.2810653601566884,
+           1.194234249845969,
+           1.1075475824649466,
+           1.0224898762207493,
+           0.9404756104617288,
+           0.8628191464889684,
+           0.7907072053674776,
+           0.7251745315913815,
+           0.6670832923078989,
+           0.6171066696077477,
+           0.5757170004278963,
+           0.5431787074298106,
+           0.5195461475541331,
+           0.5046663856820487,
+           0.498186781884648,
+           0.499567165030769,
+           0.5080962558819775,
+           0.5229119019060073,
+           0.543024596341274,
+           0.5673436777174548,
+           0.5947055449180357,
+           0.6239031784175855,
+           0.6537162315812103,
+           0.6829409474773765,
+           0.7104191666742291,
+           0.7350657196520665,
+           0.7558935430096463,
+           0.7720359203784898,
+           0.7827653252966726,
+           0.787508432281794,
+           0.7858569617210784,
+           0.7775741314506822,
+           0.7625966003210204,
+           0.7410319038118027,
+           0.7131514959886313,
+           0.6793796229206585,
+           0.640278357335097,
+           0.5965292201577851,
+           0.5489118992930152,
+           0.4982806474275497,
+           0.4455389970367459,
+           0.3916134707383399,
+           0.3374269877093292,
+           0.28387267151943385,
+           0.2317887513576927,
+           0.18193521760662515,
+           0.1349728448642264,
+           0.09144513206329705,
+           0.05176363191741548,
+           0.016197052510547667,
+           -0.015135585279004582,
+           -0.04226755714819117,
+           -0.06538274496934465,
+           -0.08480969254311703,
+           -0.1010115647317747,
+           -0.11457227449924003,
+           -0.12617914295080024,
+           -0.13660254874278627,
+           -0.14667310289700403,
+           -0.15725695107394067,
+           -0.16922985604302543,
+           -0.18345074713268858,
+           -0.20073543996081195,
+           -0.2218312282909933,
+           -0.24739303043728075,
+           -0.2779617357073079,
+           -0.3139453428296009,
+           -0.35560341347274715,
+           -0.4030352815359501,
+           -0.45617236492008345,
+           -0.5147748233168089,
+           -0.5784326957568564,
+           -0.6465715379839605,
+           -0.7184624650178668,
+           -0.7932363914189182,
+           -0.8699021536083947,
+           -0.947368097862023,
+           -1.024466626827763,
+           -1.0999811189293358,
+           -1.1726745708078259,
+           -1.2413192646781388,
+           -1.304726731394215,
+           -1.361777266960669,
+           -1.4114482655862248,
+           -1.4528406560761196,
+           -1.4852027698807433,
+           -1.507951027486849,
+           -1.5206869036658246,
+           -1.5232097196049825,
+           -1.5155249090233514,
+           -1.4978475136032776,
+           -1.4706007778116914,
+           -1.4344098316321197,
+           -1.3900905689749907,
+           -1.3386339466487376,
+           -1.2811860408735993,
+           -1.2190243026380736,
+           -1.1535305471559776,
+           -1.0861612939512442,
+           -1.0184161406584724,
+           -0.9518049038180906,
+           -0.8878142925046052,
+           -0.8278748947247208,
+           -0.7733292517811817,
+           -0.7254017723026587,
+           -0.6851711959336529,
+           -0.6535462577534308,
+           -0.6312451297635167,
+           -0.6187791270525111,
+           -0.616441065662089,
+           -0.6242985491777382,
+           -0.6421923443225253,
+           -0.669739885178306,
+           -0.706343824028963,
+           -0.7512054271713061,
+           -0.8033424992793715,
+           -0.8616114128251813,
+           -0.9247327222530727,
+           -0.9913197584223638,
+           -1.0599095293113903,
+           -1.1289951997910457,
+           -1.1970593877038298,
+           -1.2626074963675258,
+           -1.3242003053512934,
+           -1.3804850618742015,
+           -1.43022435391954,
+           -1.4723221021640032,
+           -1.505846079688204,
+           -1.5300464543755599,
+           -1.5443699467896495,
+           -1.5484693037246975,
+           -1.542207901899345,
+           -1.5256594145949947,
+           -1.4991025935174636,
+           -1.4630113358519317,
+           -1.4180403195036877,
+           -1.3650065951093338,
+           -1.3048676189920867,
+           -1.2386962945001803,
+           -1.1676536580980734,
+           -1.092959899523631,
+           -1.0158644410272404,
+           -0.937615818346889,
+           -0.8594321052719979,
+           -0.7824726044909734,
+           -0.7078114904414681,
+           -0.6364140360673359,
+           -0.5691159861273372,
+           -0.506606556773739,
+           -0.44941544663637356,
+           -0.39790414100393984,
+           -0.3522616805077691,
+           -0.31250495175931775,
+           -0.27848344253469726,
+           -0.24988829121832146,
+           -0.2262653521379911,
+           -0.2070318978453361,
+           -0.19149648882511994,
+           -0.17888146280631614,
+           -0.16834743173772782,
+           -0.15901912616267574,
+           -0.15001189536408593,
+           -0.14045815800878017,
+           -0.12953310240735247,
+           -0.11647895777996319,
+           -0.10062719748529418,
+           -0.08141809100224494,
+           -0.05841709211584639,
+           -0.0313276344424506,
+           -3.117235850326852e-16
+          ],
+          [
+           0,
+           0.03638472628062963,
+           0.07666509756661856,
+           0.12047299490834641,
+           0.16730862706589533,
+           0.21655438902772273,
+           0.26749210033505505,
+           0.3193231686854493,
+           0.37119114694215877,
+           0.42220608788395597,
+           0.47147005242502055,
+           0.518103094867067,
+           0.5612690338537075,
+           0.6002003204835399,
+           0.6342213354623983,
+           0.6627694847515032,
+           0.6854135169796455,
+           0.7018685546073169,
+           0.7120074127554404,
+           0.7158678727032495,
+           0.713655678997326,
+           0.70574313734925,
+           0.6926633023225557,
+           0.6750998564155447,
+           0.6538728927046891,
+           0.6299209189392398,
+           0.6042794992016504,
+           0.5780570374830791,
+           0.5524082835251399,
+           0.5285062031054564,
+           0.5075129010020787,
+           0.490550313956539,
+           0.4786714022836205,
+           0.472832562004378,
+           0.47386795461365727,
+           0.482466409387955,
+           0.4991514944820636,
+           0.5242652793522429,
+           0.5579562240549074,
+           0.6001715328112507,
+           0.6506542022893973,
+           0.7089448819485533,
+           0.774388547284284,
+           0.8461458697703409,
+           0.9232090525891388,
+           1.0044217917070335,
+           1.0885029201865415,
+           1.174073202351363,
+           1.2596846657958094,
+           1.343851795214676,
+           1.4250838642231756,
+           1.5019176509436145,
+           1.57294977093428,
+           1.6368678673587005,
+           1.6924799230183367,
+           1.7387410014249638,
+           1.7747767834589812,
+           1.7999033409218268,
+           1.813642676641117,
+           1.8157336605885612,
+           1.806138100303674,
+           1.7850417991389966,
+           1.7528505746557574,
+           1.7101813290146781,
+           1.6578483805195277,
+           1.5968453777293337,
+           1.5283232220311955,
+           1.4535645187227642,
+           1.373955158208337,
+           1.2909536958914474,
+           1.20605925013388,
+           1.120778671027824,
+           1.0365937479034617,
+           0.954929220124011,
+           0.8771223339143617,
+           0.8043946482898485,
+           0.7378267365977842,
+           0.6783363581680749,
+           0.6266605888799381,
+           0.5833423022117024,
+           0.5487212859526064,
+           0.522930166842735,
+           0.5058951987491838,
+           0.49734185244949936,
+           0.49680502956016936,
+           0.5036436124462244,
+           0.5170589587809404,
+           0.5361168563041264,
+           0.5597723725122421,
+           0.5868969674538295,
+           0.6163071870932305,
+           0.646794221042786,
+           0.6771535926227443,
+           0.7062142515201206,
+           0.7328663596633911,
+           0.7560870987430499,
+           0.7749638820904928,
+           0.7887144229745024,
+           0.7967031940097288,
+           0.79845390619269,
+           0.7936577387115971,
+           0.782177159526581,
+           0.7640452890469505,
+           0.7394608722212314,
+           0.7087790351728173,
+           0.6724981083877868,
+           0.6312428967498009,
+           0.5857448649724483,
+           0.5368197830103976,
+           0.48534343795540325,
+           0.43222606521675666,
+           0.378386181317576,
+           0.3247245127001394,
+           0.2720987092567243,
+           0.22129950806436346,
+           0.17302897262098432,
+           0.12788137680042358,
+           0.08632723220728113,
+           0.048700874424814994,
+           0.01519192993224981,
+           -0.014159116391973032,
+           -0.039461140677332175,
+           -0.06096838411223571,
+           -0.0790723496344194,
+           -0.09428980674366896,
+           -0.10724722190291466,
+           -0.11866202588125513,
+           -0.12932121279646297,
+           -0.1400578364103551,
+           -0.1517260256100226,
+           -0.165175181525397,
+           -0.18122404234148123,
+           -0.20063530793928488,
+           -0.2240915048613891,
+           -0.25217274301002246,
+           -0.2853369696509631,
+           -0.323903264840895,
+           -0.3680386468388508,
+           -0.4177487682805377,
+           -0.4728727860741346,
+           -0.5330825825597354,
+           -0.597886405099255,
+           -0.6666368786953816,
+           -0.7385432343038748,
+           -0.8126874870192504,
+           -0.8880441960153836,
+           -0.9635033445965551,
+           -1.0378957963335091,
+           -1.1100207141233438,
+           -1.1786742748946986,
+           -1.2426789749841751,
+           -1.3009128009329922,
+           -1.352337538159941,
+           -1.396025505776924,
+           -1.4311840393959145,
+           -1.4571770943577993,
+           -1.4735434081973868,
+           -1.4800107417527788,
+           -1.4765058111838727,
+           -1.463159626027935,
+           -1.440308058781535,
+           -1.4084875866583466,
+           -1.368426263307671,
+           -1.3210300945107398,
+           -1.2673651043393577,
+           -1.2086354841897269,
+           -1.1461583138749936,
+           -1.0813354291760215,
+           -1.0156230817935281,
+           -0.9505000937324687,
+           -0.8874352473741706,
+           -0.8278546738590888,
+           -0.7731100053560955,
+           -0.7244480412271613,
+           -0.6829826443584267,
+           -0.6496695328144547,
+           -0.625284564704457,
+           -0.6104060323461469,
+           -0.6054013874513576,
+           -0.6104187144231321,
+           -0.6253831564850569,
+           -0.6499983819891181,
+           -0.6837530587206673,
+           -0.7259321852437682,
+           -0.7756330131948701,
+           -0.8317851857355477,
+           -0.8931746177564022,
+           -0.958470555301471,
+           -1.0262551771906945,
+           -1.0950550427577044,
+           -1.1633736474124967,
+           -1.2297243233917494,
+           -1.2926627171426834,
+           -1.3508180874171236,
+           -1.4029226989938326,
+           -1.4478386352158306,
+           -1.4845814170160332,
+           -1.5123398952035911,
+           -1.5304919745324885,
+           -1.5386158302042487,
+           -1.5364963874466342,
+           -1.524126949950742,
+           -1.5017059804078425,
+           -1.469629153281554,
+           -1.4284769134161959,
+           -1.3789978813444486,
+           -1.322088544601265,
+           -1.2587697615835696,
+           -1.1901606784057093,
+           -1.1174507180115523,
+           -1.0418703431150134,
+           -0.9646613193624739,
+           -0.8870472118886642,
+           -0.8102048370662042,
+           -0.735237362071628,
+           -0.6631496986924109,
+           -0.5948267757855509,
+           -0.5310151985640643,
+           -0.4723087143786569,
+           -0.4191378061244828,
+           -0.37176362832787363,
+           -0.33027639002892756,
+           -0.29459817556172246,
+           -0.2644900820791947,
+           -0.23956344398474816,
+           -0.21929481203222953,
+           -0.2030442612929717,
+           -0.19007651978980752,
+           -0.17958434040642857,
+           -0.17071348440480622,
+           -0.162588646855454,
+           -0.15433963342731905,
+           -0.14512709478602312,
+           -0.13416713935666036,
+           -0.1207541770213858,
+           -0.10428139460873878,
+           -0.08425832754395358,
+           -0.06032506913835481,
+           -0.032262747731427795,
+           -3.2001946256190746e-16
+          ],
+          [
+           0,
+           0.03711236019790447,
+           0.0779043325451262,
+           0.12194703823847808,
+           0.16868924063920637,
+           0.21747284724451968,
+           0.2675514886506549,
+           0.31811168308373244,
+           0.36829602654185695,
+           0.4172277943468657,
+           0.4640363013373008,
+           0.5078823460420887,
+           0.5479830595343458,
+           0.5836354924201134,
+           0.6142383032733171,
+           0.6393109580607736,
+           0.6585099115717379,
+           0.6716413170525924,
+           0.6786698972792428,
+           0.679723707007385,
+           0.6750946207074601,
+           0.6652344881136836,
+           0.6507470106705971,
+           0.6323755016680145,
+           0.6109867989538458,
+           0.5875516989266157,
+           0.5631223715099132,
+           0.5388072956888713,
+           0.5157443219063835,
+           0.49507251946052067,
+           0.47790350266834053,
+           0.46529294802002974,
+           0.458213015321845,
+           0.4575263688363262,
+           0.4639624600352507,
+           0.47809668257978155,
+           0.5003329437425007,
+           0.530890116281833,
+           0.5697927427109913,
+           0.6168662622096479,
+           0.6717369215890014,
+           0.7338364184038519,
+           0.8024112092892496,
+           0.8765363027125608,
+           0.9551332453804866,
+           1.0369919082392454,
+           1.1207955839105193,
+           1.205148824849329,
+           1.288607382546241,
+           1.3697095544475764,
+           1.4470082082818119,
+           1.5191027340989698,
+           1.5846701730618076,
+           1.642494788938348,
+           1.6914953829536974,
+           1.730749704347084,
+           1.7595153764121023,
+           1.7772468393515082,
+           1.7836079049825786,
+           1.77847962191551,
+           1.7619632607829419,
+           1.7343783447289196,
+           1.6962557678604901,
+           1.648326160868311,
+           1.591503775701685,
+           1.526866267299315,
+           1.4556308473518003,
+           1.3791273705515819,
+           1.2987689856991207,
+           1.2160210406417622,
+           1.1323689699610753,
+           1.0492859166413144,
+           0.9682008431244646,
+           0.89046787310913,
+           0.8173375735510594,
+           0.7499308373791292,
+           0.6892159626757238,
+           0.6359894450948573,
+           0.5908609090614632,
+           0.5542425020655201,
+           0.5263429676315046,
+           0.5071664989836742,
+           0.49651635983176917,
+           0.4940031439054123,
+           0.4990574336798452,
+           0.5109465138769608,
+           0.5287946993491877,
+           0.5516067521906223,
+           0.57829379141946,
+           0.6077010420558595,
+           0.6386367302241025,
+           0.6699014079743497,
+           0.7003169863562781,
+           0.7287547679511622,
+           0.7541618002062963,
+           0.775584917708773,
+           0.7921919037665021,
+           0.8032892777342273,
+           0.8083363024918615,
+           0.8069549041215738,
+           0.7989353006720374,
+           0.7842372463033246,
+           0.7629869083256492,
+           0.7354695048921448,
+           0.7021179376225701,
+           0.6634977535625967,
+           0.6202888621284991,
+           0.5732645127827491,
+           0.5232681061488658,
+           0.4711884634526605,
+           0.41793421529411773,
+           0.36440798993659046,
+           0.3114810831010624,
+           0.2599692756633921,
+           0.21061043309882413,
+           0.16404447185364712,
+           0.12079621430601716,
+           0.08126157723594826,
+           0.04569745071947344,
+           0.014215527336728845,
+           -0.013219761993021542,
+           -0.03678915673219619,
+           -0.05681237986909618,
+           -0.0737380224672944,
+           -0.08812976942629576,
+           -0.10064933218246364,
+           -0.11203654066290261,
+           -0.12308712184646672,
+           -0.13462875387222525,
+           -0.14749603119163268,
+           -0.16250500658903813,
+           -0.18042798920661093,
+           -0.2019692736427517,
+           -0.22774245382325817,
+           -0.2582499371831541,
+           -0.2938652206786165,
+           -0.33481842160718756,
+           -0.3811854748519489,
+           -0.43288131600774954,
+           -0.4896572691954447,
+           -0.5511027517411793,
+           -0.6166512979641658,
+           -0.685590793838029,
+           -0.7570777060463946,
+           -0.8301549856715875,
+           -0.9037732310453893,
+           -0.9768146085790614,
+           -1.048118956856699,
+           -1.116511439803596,
+           -1.180831070863976,
+           -1.2399594029895493,
+           -1.2928486695865196,
+           -1.3385486696942916,
+           -1.3762317164337243,
+           -1.4052150105859207,
+           -1.4249798600394232,
+           -1.4351872393679834,
+           -1.4356892702001345,
+           -1.4265363002198201,
+           -1.4079793642265994,
+           -1.3804679221035503,
+           -1.3446428830602088,
+           -1.3013250403235133,
+           -1.251499152715831,
+           -1.1962940165168845,
+           -1.136958970012392,
+           -1.074837361734108,
+           -1.0113375893937597,
+           -0.9479023780128699,
+           -0.8859770112117703,
+           -0.8269772578962687,
+           -0.7722577469415175,
+           -0.7230815346321904,
+           -0.6805915837335262,
+           -0.64578482974137,
+           -0.6194894501202844,
+           -0.6023458776210568,
+           -0.5947920108743107,
+           -0.5970529765115602,
+           -0.6091356894676581,
+           -0.630828344480536,
+           -0.6617048548863663,
+           -0.7011341374525839,
+           -0.7482940270507934,
+           -0.802189495240821,
+           -0.8616747449827983,
+           -0.9254786621894924,
+           -0.9922330258961916,
+           -1.0605028143706623,
+           -1.1288178960674582,
+           -1.1957053631104508,
+           -1.259721751705681,
+           -1.319484398843273,
+           -1.3737012076952355,
+           -1.421198134665916,
+           -1.4609437680846007,
+           -1.4920704406245187,
+           -1.5138914029001995,
+           -1.5259136822237522,
+           -1.5278463558074686,
+           -1.5196040791904664,
+           -1.5013058255988996,
+           -1.473268907500336,
+           -1.4359984649514477,
+           -1.3901727136918003,
+           -1.3366243466612873,
+           -1.2763185732640931,
+           -1.210328359070771,
+           -1.1398074928528037,
+           -1.0659621563453214,
+           -0.9900217037892112,
+           -0.9132093723887105,
+           -0.8367136410459456,
+           -0.761660933254358,
+           -0.6890903214408496,
+           -0.6199308353579336,
+           -0.5549819077550726,
+           -0.494897408277147,
+           -0.4401736234389855,
+           -0.39114143896414433,
+           -0.3479628733144398,
+           -0.3106320005770561,
+           -0.2789801897948513,
+           -0.2526854791037233,
+           -0.23128579939546376,
+           -0.21419566623934325,
+           -0.2007258728586274,
+           -0.19010564320093545,
+           -0.18150664438685032,
+           -0.17406821353839405,
+           -0.16692312625655684,
+           -0.15922322349680232,
+           -0.15016422051227932,
+           -0.13900904568671416,
+           -0.1251090978206324,
+           -0.10792286670708151,
+           -0.08703143218853582,
+           -0.06215043952422646,
+           -0.03313824170823004,
+           -3.275979950864032e-16
+          ],
+          [
+           0,
+           0.03773697950054407,
+           0.07891141489450709,
+           0.12303950906325649,
+           0.16952521014785693,
+           0.21767715873931456,
+           0.26672839181160324,
+           0.3158582808343736,
+           0.36421612209959575,
+           0.4109457527588388,
+           0.45521053754008134,
+           0.49621805933701224,
+           0.5332438521604937,
+           0.5656535372024145,
+           0.5929227614505669,
+           0.6146543924594328,
+           0.6305924911852842,
+           0.640632665536881,
+           0.6448284984622472,
+           0.6433938437093799,
+           0.6367008873778597,
+           0.6252739813862913,
+           0.6097793633037647,
+           0.5910109829054878,
+           0.5698727566419821,
+           0.5473576644081597,
+           0.5245241861994056,
+           0.5024706473275897,
+           0.48230809802001323,
+           0.4651323949618961,
+           0.45199617757273297,
+           0.4438814398422909,
+           0.44167338913379156,
+           0.4461362566643266,
+           0.4578916810005523,
+           0.4774002268818343,
+           0.5049465284150612,
+           0.5406284599438375,
+           0.5843506417616153,
+           0.6358224836575591,
+           0.694560859604164,
+           0.7598973944069595,
+           0.8309902306043836,
+           0.9068400341022604,
+           0.9863098926626238,
+           1.0681486650223972,
+           1.151017252482347,
+           1.233517191417156,
+           1.3142209061447416,
+           1.3917029184375773,
+           1.4645712837533824,
+           1.5314985156849434,
+           1.5912512694243857,
+           1.6427180820127552,
+           1.6849345111737923,
+           1.7171050745646899,
+           1.738621465876,
+           1.7490766115788912,
+           1.748274230137483,
+           1.736233661801051,
+           1.7131898490856274,
+           1.6795884630260138,
+           1.6360762854327697,
+           1.5834870699244237,
+           1.5228232116867415,
+           1.4552336551331206,
+           1.381988557492884,
+           1.3044513026814581,
+           1.224048521759637,
+           1.14223882237225,
+           1.0604809586630997,
+           0.9802021846026726,
+           0.9027675271809195,
+           0.8294506916915192,
+           0.7614072699832175,
+           0.6996508651139246,
+           0.6450326737430014,
+           0.5982249826235398,
+           0.5597089398091913,
+           0.5297668570307593,
+           0.5084791896905747,
+           0.49572622777124653,
+           0.49119441743624925,
+           0.4943871219931526,
+           0.5046395249121964,
+           0.5211372793275753,
+           0.5429384202854598,
+           0.5689979800767253,
+           0.5981946851325373,
+           0.6293590666450126,
+           0.6613022873940344,
+           0.6928449748915327,
+           0.7228453561439141,
+           0.750226011893302,
+           0.7739986075114625,
+           0.7932860127545283,
+           0.807341291922536,
+           0.8155631278341131,
+           0.817507335344282,
+           0.8128942205689125,
+           0.8016116480015765,
+           0.7837137866536267,
+           0.7594156154845886,
+           0.7290833749873336,
+           0.69322125318973,
+           0.652454688005661,
+           0.6075107514857383,
+           0.5591961530098085,
+           0.5083734560650655,
+           0.45593614555163536,
+           0.40278320852447325,
+           0.34979390029989665,
+           0.2978033597368946,
+           0.24757971248797936,
+           0.19980325976621482,
+           0.155048293765831,
+           0.11376801075536831,
+           0.07628291082946292,
+           0.04277298145181902,
+           0.013273862586410123,
+           -0.012322913077441856,
+           -0.034265617898266286,
+           -0.05293408434378159,
+           -0.06882773973191456,
+           -0.08255024043130645,
+           -0.0947911145024389,
+           -0.10630490050737526,
+           -0.11788833650396276,
+           -0.13035620537772374,
+           -0.14451647931590306,
+           -0.16114542644685512,
+           -0.1809633459209846,
+           -0.20461158389045137,
+           -0.23263145227721027,
+           -0.26544562564791624,
+           -0.30334253008874074,
+           -0.3464641632170622,
+           -0.39479769824170347,
+           -0.4481711294411213,
+           -0.5062531139594494,
+           -0.5685570579912482,
+           -0.6344493869188584,
+           -0.7031618315099254,
+           -0.7738074585844211,
+           -0.8454000772392406,
+           -0.9168765632382468,
+           -0.9871215667853892,
+           -1.0549940045736754,
+           -1.1193546873978257,
+           -1.1790944010231938,
+           -1.233161741311823,
+           -1.2805900052930197,
+           -1.320522457972839,
+           -1.352235329814144,
+           -1.375157951170882,
+           -1.3888894963072451,
+           -1.3932118893792875,
+           -1.3880985159721724,
+           -1.3737184842508698,
+           -1.3504362870417275,
+           -1.3188068275895555,
+           -1.2795658845935156,
+           -1.233616203637744,
+           -1.182009509549543,
+           -1.1259248348849995,
+           -1.066643651166216,
+           -1.0055223694061757,
+           -0.9439628428669959,
+           -0.8833815562433417,
+           -0.8251782202548246,
+           -0.7707045080812936,
+           -0.721233669719558,
+           -0.6779317421537382,
+           -0.6418310376248488,
+           -0.6138065400987965,
+           -0.5945557725123642,
+           -0.5845826161489562,
+           -0.5841854705218068,
+           -0.5934500396733517,
+           -0.6122469213213002,
+           -0.6402340614530307,
+           -0.676864021556642,
+           -0.7213958914853472,
+           -0.7729115707583366,
+           -0.8303360375849859,
+           -0.892461130575672,
+           -0.9579722852614784,
+           -1.0254775981955608,
+           -1.0935385372276911,
+           -1.1607015788365918,
+           -1.225530033072427,
+           -1.2866353141800706,
+           -1.342706930379499,
+           -1.3925404991721684,
+           -1.4350631440930752,
+           -1.469355693800542,
+           -1.4946711831773274,
+           -1.5104492467577604,
+           -1.5163260950586277,
+           -1.5121398718061294,
+           -1.4979313019750475,
+           -1.4739396542410153,
+           -1.4405941541051908,
+           -1.398501092826316,
+           -1.348426979729605,
+           -1.291278178960755,
+           -1.2280775540474544,
+           -1.1599387127317453,
+           -1.0880384987861254,
+           -1.0135884156362542,
+           -0.9378056876969882,
+           -0.8618846689227705,
+           -0.7869692941484597,
+           -0.7141272377569476,
+           -0.644326396882554,
+           -0.5784142539740703,
+           -0.517100597698874,
+           -0.46094399380076906,
+           -0.4103423008423943,
+           -0.36552742220837897,
+           -0.3265643779231613,
+           -0.29335467045408936,
+           -0.2656438104653789,
+           -0.2430327641656733,
+           -0.22499298605329074,
+           -0.21088461194286853,
+           -0.19997730936187197,
+           -0.1914732176593493,
+           -0.18453136006636736,
+           -0.17829287571201932,
+           -0.17190640205523092,
+           -0.16455293774523208,
+           -0.15546953254736948,
+           -0.14397118421182367,
+           -0.1294703711500759,
+           -0.11149371325181416,
+           -0.08969532949489989,
+           -0.06386654822261877,
+           -0.03394172186256741,
+           -3.3435443864747144e-16
+          ],
+          [
+           0,
+           0.03824997785313923,
+           0.07967237669488218,
+           0.12373468924870884,
+           0.16980291954690388,
+           0.21715976896550354,
+           0.26502524506325,
+           0.3125791454082412,
+           0.3589848185185595,
+           0.40341356927183303,
+           0.4450690575505747,
+           0.48321103697535783,
+           0.5171777954069513,
+           0.5464066901204335,
+           0.570452217404972,
+           0.5890011176641475,
+           0.6018840913597049,
+           0.609083786505037,
+           0.6107388127406481,
+           0.6071436379507972,
+           0.5987443283775099,
+           0.5861301996175258,
+           0.5700215510713024,
+           0.5512537576988548,
+           0.5307580877654486,
+           0.5095397012279858,
+           0.48865335833407436,
+           0.46917742996565576,
+           0.45218684866274456,
+           0.43872567087542474,
+           0.42977993597010783,
+           0.4262515054283584,
+           0.4289335465168343,
+           0.43848828889348285,
+           0.45542763098181144,
+           0.48009710672073314,
+           0.5126636440762923,
+           0.5531074564039143,
+           0.6012183085751049,
+           0.6565962941551038,
+           0.7186571504273979,
+           0.7866420273978817,
+           0.859631517801287,
+           0.9365636502679845,
+           1.0162554497837082,
+           1.0974275808178322,
+           1.1787315112132926,
+           1.2587785710500312,
+           1.336170231814266,
+           1.4095288985618364,
+           1.4775284921914873,
+           1.538924100861312,
+           1.5925799989772649,
+           1.6374953686160942,
+           1.672827110856817,
+           1.697909202027545,
+           1.7122681307033831,
+           1.7156340434639554,
+           1.7079473287040963,
+           1.6893604757314258,
+           1.6602351583587671,
+           1.621134605486171,
+           1.5728114330122387,
+           1.5161912190974427,
+           1.4523522057048943,
+           1.3825016010138056,
+           1.3079490375115377,
+           1.2300778073760608,
+           1.150314548545339,
+           1.070098090385208,
+           0.9908481862635384,
+           0.9139348611862359,
+           0.8406490859505008,
+           0.7721754554530836,
+           0.7095674987052194,
+           0.6537261829989209,
+           0.6053820961547386,
+           0.565081700800053,
+           0.533177955398337,
+           0.5098254907167314,
+           0.494980420187942,
+           0.4884047508979058,
+           0.4896752514501908,
+           0.49819652642314854,
+           0.5132179471461212,
+           0.5338539975097698,
+           0.5591075137001869,
+           0.5878952300339279,
+           0.6190749910710539,
+           0.6514739541284804,
+           0.6839170870431152,
+           0.7152552639626588,
+           0.7443922770653718,
+           0.7703101139955848,
+           0.7920918986031462,
+           0.8089419550526238,
+           0.8202025309214959,
+           0.8253668016142359,
+           0.8240878740863945,
+           0.8161836100876808,
+           0.8016371953254144,
+           0.7805934884567005,
+           0.7533512899488858,
+           0.7203517729533135,
+           0.6821634138729619,
+           0.6394638468954267,
+           0.5930191422624638,
+           0.5436610705908117,
+           0.49226296360924154,
+           0.4397148140620304,
+           0.38689827347257516,
+           0.3346622055992519,
+           0.28379943580773265,
+           0.23502530270918875,
+           0.18895856915928103,
+           0.14610518635126873,
+           0.10684532889412882,
+           0.07142403238137893,
+           0.03994567023058725,
+           0.012372405917395852,
+           -0.011473347300506842,
+           -0.03190253183291615,
+           -0.049349291873890214,
+           -0.06435733397124362,
+           -0.07756316709222215,
+           -0.08967666913513427,
+           -0.10145949730870842,
+           -0.11370191704372339,
+           -0.12719866665269958,
+           -0.14272450172035087,
+           -0.16101007349424634,
+           -0.1827187890704852,
+           -0.20842527807380284,
+           -0.23859605137469075,
+           -0.27357288313188144,
+           -0.31355937944222473,
+           -0.3586111168142029,
+           -0.40862964355463804,
+           -0.4633605392246847,
+           -0.5223956240348576,
+           -0.5851793040020753,
+           -0.6510189315507773,
+           -0.7190989576785501,
+           -0.7884985534383351,
+           -0.8582122878034387,
+           -0.9271733682797232,
+           -0.9942788819688837,
+           -1.0584164199273904,
+           -1.1184914280274285,
+           -1.1734546041511946,
+           -1.2223286550776418,
+           -1.2642337370707788,
+           -1.2984109317440888,
+           -1.3242431526289358,
+           -1.341272936981239,
+           -1.3492166503045178,
+           -1.3479747160859368,
+           -1.337637578268855,
+           -1.3184872067017481,
+           -1.290994063694307,
+           -1.255809560228896,
+           -1.2137541406028713,
+           -1.165801241596952,
+           -1.1130574740256998,
+           -1.0567394682089584,
+           -0.9981479081828302,
+           -0.9386393502724988,
+           -0.8795964782081754,
+           -0.8223974878576468,
+           -0.7683853188363666,
+           -0.7188374571096899,
+           -0.6749370220172777,
+           -0.6377458231542117,
+           -0.6081800278881606,
+           -0.5869890200394151,
+           -0.5747379558456257,
+           -0.5717944365700337,
+           -0.5783196200892144,
+           -0.594263988865402,
+           -0.6193678814163368,
+           -0.653166781421744,
+           -0.695001245696436,
+           -0.7440312421614494,
+           -0.7992545643337969,
+           -0.8595288922759126,
+           -0.9235969837442694,
+           -0.9901144055450946,
+           -1.0576791556306144,
+           -1.124862482687996,
+           -1.1902401829379616,
+           -1.2524236442114345,
+           -1.3100899153264536,
+           -1.3620101041273913,
+           -1.4070754496323636,
+           -1.4443204715116174,
+           -1.4729426721539933,
+           -1.4923183510881173,
+           -1.5020141864230887,
+           -1.501794340921753,
+           -1.4916229587859116,
+           -1.471662030552903,
+           -1.4422647149475432,
+           -1.4039643153744055,
+           -1.3574592123142466,
+           -1.3035941486806975,
+           -1.2433383508716565,
+           -1.177761041740698,
+           -1.1080049612483471,
+           -1.0352585547107893,
+           -0.9607275163067267,
+           -0.8856063862015738,
+           -0.8110508930950938,
+           -0.7381517104141287,
+           -0.6679102543980998,
+           -0.6012170970073858,
+           -0.5388334973483193,
+           -0.4813764739199427,
+           -0.42930774851126097,
+           -0.3829267933240835,
+           -0.3423681083647491,
+           -0.30760274896239015,
+           -0.2784440161172794,
+           -0.25455711793862945,
+           -0.23547251130202637,
+           -0.220602541509853,
+           -0.20926091644107123,
+           -0.2006844824417059,
+           -0.19405671374063294,
+           -0.18853228683540696,
+           -0.18326208705705926,
+           -0.17741798696294525,
+           -0.1702167454753868,
+           -0.16094240251121483,
+           -0.14896658554771244,
+           -0.13376620106067957,
+           -0.11493805359628011,
+           -0.0922100166122502,
+           -0.06544847006919519,
+           -0.03466181775572384,
+           -3.4019490672375753e-16
+          ],
+          [
+           0,
+           0.03864410426381679,
+           0.08017611821398651,
+           0.12402132384387476,
+           0.16951481403821125,
+           0.2159207053388409,
+           0.26245342967724794,
+           0.30830053795302875,
+           0.35264640773976647,
+           0.39469622235353896,
+           0.43369957967512285,
+           0.468973096717701,
+           0.49992139980639105,
+           0.5260559298030882,
+           0.5470110460932321,
+           0.5625569807019568,
+           0.5726092732395065,
+           0.5772344064075715,
+           0.5766514583004504,
+           0.5712296892875856,
+           0.5614820853162922,
+           0.5480549834073977,
+           0.5317140063123463,
+           0.513326629202137,
+           0.4938417894379461,
+           0.4742670286906363,
+           0.45564372293640165,
+           0.439021008458185,
+           0.42542904956446653,
+           0.41585231530783795,
+           0.4112035374521197,
+           0.41229901011787456,
+           0.41983586316916643,
+           0.4343718971389121,
+           0.4563085083728189,
+           0.48587716052093666,
+           0.5231297742764527,
+           0.5679333134025746,
+           0.6199687438926705,
+           0.6787344370557249,
+           0.7435539790138702,
+           0.8135882412078113,
+           0.8878514616914498,
+           0.965230987850449,
+           1.0445102401576591,
+           1.124394375942438,
+           1.2035380639102942,
+           1.2805747260114761,
+           1.3541465645853672,
+           1.4229346704867354,
+           1.4856885027116076,
+           1.5412540420487912,
+           1.5885999502292165,
+           1.6268411112545564,
+           1.6552589919839495,
+           1.6733183331943002,
+           1.680679768418123,
+           1.677208063821111,
+           1.662975775883842,
+           1.6382622321859721,
+           1.603547851519899,
+           1.5595039301871993,
+           1.506978128964614,
+           1.4469759972489238,
+           1.3806389648207191,
+           1.30921931522282,
+           1.234052725901055,
+           1.1565290172784013,
+           1.0780617944497024,
+           1.0000576901949894,
+           0.9238859259212575,
+           0.8508488977807164,
+           0.7821544688267095,
+           0.7188906053220746,
+           0.6620029372740016,
+           0.6122757513741478,
+           0.5703168405494378,
+           0.5365465403492728,
+           0.5111911807221539,
+           0.49428107486829254,
+           0.48565305741744824,
+           0.48495747485454055,
+           0.49166942457399904,
+           0.5051039377882417,
+           0.5244347082098341,
+           0.5487158852364109,
+           0.5769063793042104,
+           0.6078960698489507,
+           0.6405332642857954,
+           0.673652730578921,
+           0.706103616899964,
+           0.736776579740904,
+           0.7646294664000313,
+           0.7887109383350663,
+           0.808181477416593,
+           0.8223312861894762,
+           0.830594674099711,
+           0.8325606122205244,
+           0.8279792370284913,
+           0.8167641867727398,
+           0.7989907593636467,
+           0.7748899858444139,
+           0.7448388157733892,
+           0.70934670768854,
+           0.6690390068400196,
+           0.6246375713547967,
+           0.5769391749866299,
+           0.5267922679564981,
+           0.475072715798857,
+           0.4226591586699241,
+           0.3704086397173277,
+           0.31913314073953736,
+           0.2695776367766907,
+           0.22240023917684487,
+           0.17815494016685424,
+           0.1372774024796856,
+           0.10007415692918564,
+           0.06671548103745305,
+           0.037232135195706034,
+           0.011516031833517511,
+           -0.010675189750738131,
+           -0.02970981227333365,
+           -0.04607014108246912,
+           -0.06033737728772084,
+           -0.07317366869744626,
+           -0.08530181798950018,
+           -0.09748318939686333,
+           -0.11049440319616921,
+           -0.12510344021542075,
+           -0.1420457955785629,
+           -0.1620013215308868,
+           -0.1855723834044845,
+           -0.21326392096441543,
+           -0.24546596030526455,
+           -0.2824390603103534,
+           -0.3243031039640814,
+           -0.37102976036146623,
+           -0.4224388502002203,
+           -0.4781987482013128,
+           -0.5378308527771265,
+           -0.6007180489445474,
+           -0.6661169875907115,
+           -0.7331739053375539,
+           -0.800943616917727,
+           -0.8684112285104592,
+           -0.9345160480153142,
+           -0.9981771086186553,
+           -1.0583196767678247,
+           -1.1139020859925701,
+           -1.1639422246963471,
+           -1.207543009470216,
+           -1.243916195631098,
+           -1.2724039131091653,
+           -1.292497367655761,
+           -1.3038522133769872,
+           -1.30630018122754,
+           -1.2998566374164608,
+           -1.2847238435037047,
+           -1.2612897939105452,
+           -1.2301226140774313,
+           -1.1919606109360557,
+           -1.1476981740454546,
+           -1.0983678280399023,
+           -1.0451188324172587,
+           -0.9891928107938719,
+           -0.9318969664243137,
+           -0.8745755021665758,
+           -0.8185799096262073,
+           -0.7652388227579142,
+           -0.7158281449549817,
+           -0.6715421552415501,
+           -0.6334662786472961,
+           -0.6025521686571605,
+           -0.5795956966673026,
+           -0.5652183759088852,
+           -0.5598526669461793,
+           -0.5637315205558906,
+           -0.5768824137611268,
+           -0.5991260284525111,
+           -0.6300796119632512,
+           -0.6691649478497523,
+           -0.7156207556665924,
+           -0.7685192333771009,
+           -0.8267863577654446,
+           -0.889225469202747,
+           -0.9545435895307748,
+           -1.021379857544618,
+           -1.0883354171375204,
+           -1.1540040598078287,
+           -1.2170029067192343,
+           -1.2760024162354144,
+           -1.3297550207825404,
+           -1.3771217315689483,
+           -1.4170961002424705,
+           -1.448824991736572,
+           -1.4716257007327596,
+           -1.4849990334190768,
+           -1.488638074353454,
+           -1.4824324628322867,
+           -1.4664681116500735,
+           -1.4410224108547063,
+           -1.4065550673688638,
+           -1.3636948355149807,
+           -1.31322249100939,
+           -1.2560504895084061,
+           -1.1931998281499911,
+           -1.1257746928732424,
+           -1.0549355240728984,
+           -0.9818711671791125,
+           -0.9077707922566318,
+           -0.833796267315105,
+           -0.7610556537554828,
+           -0.6905784597053274,
+           -0.6232932387828755,
+           -0.5600080593229662,
+           -0.5013942938969471,
+           -0.44797409297381235,
+           -0.4001118119751123,
+           -0.3580095601547148,
+           -0.32170693521921206,
+           -0.29108490201428366,
+           -0.2658736695769834,
+           -0.24566432098897445,
+           -0.22992385724708259,
+           -0.2180132321103367,
+           -0.20920788167311435,
+           -0.20272019205824288,
+           -0.1977233026029295,
+           -0.19337561134362924,
+           -0.18884533522366814,
+           -0.18333447957297455,
+           -0.17610158995124284,
+           -0.16648269390120088,
+           -0.15390988962498098,
+           -0.13792710179591117,
+           -0.1182026000282215,
+           -0.09453796102343869,
+           -0.06687324891522245,
+           -0.03528828746502289,
+           -3.450371853507737e-16
+          ],
+          [
+           0,
+           0.03891351600926102,
+           0.08041447324695952,
+           0.12389265666758355,
+           0.16865936357384087,
+           0.2139674276734061,
+           0.25903297216278937,
+           0.30305831135917594,
+           0.3452553892782781,
+           0.3848691280972968,
+           0.42120006005431226,
+           0.45362563302157555,
+           0.4816196123481209,
+           0.5047690487997869,
+           0.5227883433597056,
+           0.5355300127710689,
+           0.5429918431795289,
+           0.5453202109750649,
+           0.5428094476418561,
+           0.5358972266454249,
+           0.525156052572743,
+           0.5112810333180495,
+           0.49507421253560746,
+           0.47742582942044615,
+           0.459292953849646,
+           0.441676014957704,
+           0.42559379853698237,
+           0.4120575317696628,
+           0.40204470158404454,
+           0.3964732646388782,
+           0.3961769022275809,
+           0.40188195232115104,
+           0.41418661400380086,
+           0.43354296756477867,
+           0.46024228773545434,
+           0.49440404958985434,
+           0.5359689383534271,
+           0.5846960779428885,
+           0.6401645908505085,
+           0.7017794964988202,
+           0.7687818490228725,
+           0.8402629112056493,
+           0.915182061574707,
+           0.9923880389347906,
+           1.0706430451650415,
+           1.1486491550286604,
+           1.2250764228294893,
+           1.2985920314845922,
+           1.3678898010871552,
+           1.4317193620462343,
+           1.4889143027402865,
+           1.5384186232281254,
+           1.579310864429835,
+           1.6108253354272575,
+           1.6323699288665092,
+           1.643540094253771,
+           1.6441286292928683,
+           1.6341310481309665,
+           1.61374639006244,
+           1.583373440348032,
+           1.5436024437089275,
+           1.49520249810454,
+           1.4391049189944416,
+           1.376382959923019,
+           1.3082283616241885,
+           1.2359252768239215,
+           1.1608221797002403,
+           1.084302416046902,
+           1.007754081441698,
+           0.932539929394502,
+           0.8599680092017742,
+           0.7912637141354262,
+           0.727543885129807,
+           0.669793564186515,
+           0.618845926556319,
+           0.5753658429920006,
+           0.5398374349127705,
+           0.512555888358189,
+           0.4936236895202522,
+           0.4829513379568901,
+           0.48026248592313164,
+           0.48510334624202084,
+           0.4968561093653606,
+           0.5147560152247678,
+           0.5379116394566159,
+           0.565327878683714,
+           0.5959310575573138,
+           0.6285955326885267,
+           0.6621711365532497,
+           0.6955107886780089,
+           0.7274976022417025,
+           0.7570708315838274,
+           0.7832500395097405,
+           0.8051569118467565,
+           0.8220342091779688,
+           0.8332614204670986,
+           0.83836676848979,
+           0.8370353104524074,
+           0.8291129765557371,
+           0.8146064920541053,
+           0.7936792319962473,
+           0.7666431597240466,
+           0.7339470978089688,
+           0.6961616709962233,
+           0.6539613426484429,
+           0.6081040371077506,
+           0.5594088985800775,
+           0.5087327811630745,
+           0.4569460934209713,
+           0.4049086337715287,
+           0.35344604960751286,
+           0.30332753365025616,
+           0.2552453360515843,
+           0.20979662113843622,
+           0.16746813471396657,
+           0.12862407310617088,
+           0.09349746060012701,
+           0.06218524965785555,
+           0.03464726076746008,
+           0.010708978349457245,
+           -0.00993188156753646,
+           -0.02769521465171131,
+           -0.043105059014153006,
+           -0.05677317643822266,
+           -0.06938012438916201,
+           -0.08165432506636945,
+           -0.09434969075860729,
+           -0.10822240344057318,
+           -0.12400746991611837,
+           -0.14239568126257773,
+           -0.16401159665650686,
+           -0.18939314706387234,
+           -0.21897341435886125,
+           -0.2530650871828424,
+           -0.2918480276181642,
+           -0.33536030420858187,
+           -0.3834929589735023,
+           -0.4359886810392706,
+           -0.4924444597321946,
+           -0.552318187953016,
+           -0.6149390849498487,
+           -0.6795217087914189,
+           -0.7451832354121478,
+           -0.8109635954224942,
+           -0.8758479841300006,
+           -0.938791196331963,
+           -0.9987431870610003,
+           -1.0546752238963915,
+           -1.105605976637109,
+           -1.1506268866153175,
+           -1.188926170855152,
+           -1.2198108453847445,
+           -1.2427261966197705,
+           -1.2572721887972982,
+           -1.2632163675302979,
+           -1.2605029029298611,
+           -1.2492575083737334,
+           -1.2297880706216666,
+           -1.2025809311475884,
+           -1.1682928647145503,
+           -1.127738906745231,
+           -1.0818762833326725,
+           -1.0317847942614735,
+           -0.9786440877749218,
+           -0.9237083438310815,
+           -0.8682789482945644,
+           -0.8136757922639052,
+           -0.7612078672318571,
+           -0.7121438470846336,
+           -0.6676833515309317,
+           -0.628929572287431,
+           -0.5968639135228435,
+           -0.5723232523742227,
+           -0.5559803648830073,
+           -0.5483279889053608,
+           -0.5496669102103335,
+           -0.5600983631546297,
+           -0.5795209353124817,
+           -0.6076320587195828,
+           -0.6439340615544125,
+           -0.6877446457751556,
+           -0.7382115510902093,
+           -0.7943310662232178,
+           -0.8549699571576878,
+           -0.9188903011311357,
+           -0.9847766465598267,
+           -1.0512648644759433,
+           -1.11697201777073,
+           -1.180526551504488,
+           -1.2405981013151928,
+           -1.2959262276664156,
+           -1.3453474110433519,
+           -1.3878196865453396,
+           -1.4224443545563294,
+           -1.4484842758599614,
+           -1.46537834293273,
+           -1.4727518121435723,
+           -1.4704222819232244,
+           -1.4584012071775245,
+           -1.4368909477251113,
+           -1.4062774557089872,
+           -1.3671188111432953,
+           -1.320129913468677,
+           -1.2661637277991724,
+           -1.206189565247032,
+           -1.1412689453586846,
+           -1.0725296436362135,
+           -1.0011385670458104,
+           -0.9282741243933682,
+           -0.8550987659386643,
+           -0.7827323574931977,
+           -0.7122270287836102,
+           -0.6445440947473141,
+           -0.580533592730245,
+           -0.5209169097077786,
+           -0.4662728934015916,
+           -0.4170277515488879,
+           -0.37344894685535673,
+           -0.3356431937605098,
+           -0.30355855960580075,
+           -0.2769905697112665,
+           -0.25559211580806385,
+           -0.23888687273360226,
+           -0.22628584162136497,
+           -0.21710656115640867,
+           -0.2105944637125024,
+           -0.20594580192927225,
+           -0.2023315347781387,
+           -0.19892154128329012,
+           -0.19490852529439742,
+           -0.1895309861324879,
+           -0.18209465722408982,
+           -0.17199185727860125,
+           -0.1587182550471889,
+           -0.14188661777474385,
+           -0.12123719335064137,
+           -0.09664446484037323,
+           -0.06812011128042768,
+           -0.035812107922693376,
+           -3.4881140637551027e-16
+          ],
+          [
+           0,
+           0.03905381506809225,
+           0.08038224079099426,
+           0.12334641525807938,
+           0.16724095983711526,
+           0.21131459815714787,
+           0.2547921518350437,
+           0.29689732498817384,
+           0.3368756678463906,
+           0.3740171036743186,
+           0.40767741290984916,
+           0.43729809368852907,
+           0.46242405813592213,
+           0.48271867797363144,
+           0.49797575974991815,
+           0.5081281077044758,
+           0.513252418963526,
+           0.5135703492619194,
+           0.5094456853549072,
+           0.5013776602493192,
+           0.4899905468335248,
+           0.47601976190774076,
+           0.46029480357252645,
+           0.44371942811754944,
+           0.42724954584915315,
+           0.4118693768313877,
+           0.39856645570891147,
+           0.3883061083797786,
+           0.3820060414017523,
+           0.3805116871423406,
+           0.3845729337129665,
+           0.39482283895536263,
+           0.4117588828616806,
+           0.4357272538750101,
+           0.4669105929520383,
+           0.5053195368097322,
+           0.5507883104330223,
+           0.6029745209255283,
+           0.6613632025452945,
+           0.725275058797904,
+           0.7938787443240953,
+           0.8662069295669524,
+           0.9411757973054911,
+           1.0176075344280773,
+           1.0942553069242702,
+           1.1698301428806428,
+           1.2430290988608435,
+           1.3125640506816594,
+           1.3771904311460363,
+           1.4357352352515869,
+           1.4871236278466806,
+           1.5304035193381982,
+           1.5647675211496597,
+           1.5895717530892692,
+           1.6043510481639798,
+           1.6088301848989057,
+           1.6029308708469348,
+           1.586774301431835,
+           1.5606792231207658,
+           1.5251555366206677,
+           1.4808935817426385,
+           1.428749348201259,
+           1.369725953414527,
+           1.304951816989238,
+           1.2356560398608167,
+           1.1631415621031354,
+           1.0887567256299893,
+           1.0138659051117327,
+           0.9398198915346357,
+           0.8679267174349927,
+           0.7994236008476018,
+           0.7354506567278628,
+           0.677026980746064,
+           0.6250296520002984,
+           0.5801761297931177,
+           0.5430104369279888,
+           0.5138934300397627,
+           0.4929973585390985,
+           0.4803048102520089,
+           0.47561203630936655,
+           0.47853654286983144,
+           0.48852873540798647,
+           0.50488730505111,
+           0.5267779581444039,
+           0.5532550120070431,
+           0.5832853135993606,
+           0.6157738851449044,
+           0.6495906628927489,
+           0.6835976730497965,
+           0.7166759829545685,
+           0.7477517758973858,
+           0.7758209243071298,
+           0.7999714776188268,
+           0.8194035369280211,
+           0.833446057098187,
+           0.8415701965728632,
+           0.8433989237424668,
+           0.8387126840951394,
+           0.8274510321461864,
+           0.8097102337931674,
+           0.7857369457430637,
+           0.7559181764861231,
+           0.7207678255140808,
+           0.6809101818098046,
+           0.6370608369840494,
+           0.5900055309695986,
+           0.5405774973692024,
+           0.48963391019375635,
+           0.43803205298994863,
+           0.38660583479738164,
+           0.3361432649467047,
+           0.28736547076330776,
+           0.24090779951512956,
+           0.1973034895479185,
+           0.15697032693827237,
+           0.12020062492084584,
+           0.08715477582935924,
+           0.05785853155961045,
+           0.03220407099965626,
+           0.009954813954997338,
+           -0.009246156664857097,
+           -0.025864296757972874,
+           -0.04045874750246377,
+           -0.053664826698199546,
+           -0.06617433484764608,
+           -0.07871420335587544,
+           -0.09202405622462197,
+           -0.10683328597119128,
+           -0.12383825846485084,
+           -0.143680259573372,
+           -0.16692477897987804,
+           -0.194042693690576,
+           -0.22539386641867454,
+           -0.2612136133760181,
+           -0.30160242354520084,
+           -0.3465192290538402,
+           -0.39577843589524647,
+           -0.4490508282044559,
+           -0.5058683600193653,
+           -0.5656327484327612,
+           -0.6276276837945847,
+           -0.6910343786368556,
+           -0.754950089645967,
+           -0.8184091685164654,
+           -0.8804061298875543,
+           -0.9399201695208036,
+           -0.9959405248467943,
+           -1.0474920440633604,
+           -1.093660319808923,
+           -1.1336157493680001,
+           -1.1666359052989708,
+           -1.1921256378141625,
+           -1.2096343823092846,
+           -1.2188702108874776,
+           -1.2197102439711562,
+           -1.212207125264096,
+           -1.196591358287862,
+           -1.1732694031435011,
+           -1.1428175355736356,
+           -1.1059715742739207,
+           -1.0636126841620466,
+           -1.0167495604395949,
+           -0.9664973883685972,
+           -0.914054054491424,
+           -0.8606741545348625,
+           -0.807641399716901,
+           -0.7562400651957243,
+           -0.7077261508967904,
+           -0.6632989352371598,
+           -0.6240735960467173,
+           -0.5910555503788175,
+           -0.5651171264261289,
+           -0.5469771273204381,
+           -0.5371837794746498,
+           -0.5361014789364917,
+           -0.5439016598786058,
+           -0.5605580120126195,
+           -0.5858461707466093,
+           -0.6193478978073553,
+           -0.6604596634003334,
+           -0.708405436376042,
+           -0.7622533888561829,
+           -0.8209361287816394,
+           -0.8832739901381064,
+           -0.9480008382303281,
+           -1.0137917880701026,
+           -1.079292189154114,
+           -1.1431472007178087,
+           -1.2040312686599033,
+           -1.2606768190401025,
+           -1.3119015032531183,
+           -1.3566333661659962,
+           -1.3939333597716081,
+           -1.4230146899894172,
+           -1.4432585615288087,
+           -1.4542259733158127,
+           -1.4556653127169765,
+           -1.4475155983229082,
+           -1.4299053258884333,
+           -1.403146977598834,
+           -1.367727358560603,
+           -1.3242940237685454,
+           -1.2736381513589756,
+           -1.216674301472794,
+           -1.1544175725008665,
+           -1.0879587261223218,
+           -1.0184378979485003,
+           -0.9470175406792442,
+           -0.8748552607724869,
+           -0.8030772074274254,
+           -0.7327526542939317,
+           -0.6648703802545185,
+           -0.6003174067749806,
+           -0.5398605869450326,
+           -0.4841314670218468,
+           -0.43361475693135354,
+           -0.3886406539031681,
+           -0.3493811655356901,
+           -0.31585047756289986,
+           -0.28790930995120506,
+           -0.2652731052301602,
+           -0.2475237976390073,
+           -0.23412482312029087,
+           -0.2244389506068459,
+           -0.21774844639563917,
+           -0.21327702737026819,
+           -0.2102130167936435,
+           -0.20773308936107793,
+           -0.20502598082153511,
+           -0.20131554198785329,
+           -0.19588253721317442,
+           -0.18808462286352254,
+           -0.1773739910381213,
+           -0.16331222649471205,
+           -0.14558199881779535,
+           -0.12399529542981233,
+           -0.09849799195903601,
+           -0.06917065243044221,
+           -0.03622555029930318,
+           -3.5146057292891057e-16
+          ],
+          [
+           0,
+           0.039062067841347706,
+           0.08007718308179203,
+           0.12238474592874372,
+           0.1652697486108499,
+           0.2079837743581933,
+           0.2497670221791837,
+           0.2898707677503502,
+           0.3275796582248054,
+           0.3622332417018111,
+           0.3932461504238117,
+           0.420126390031041,
+           0.44249123458321105,
+           0.460080287372539,
+           0.4727653392952648,
+           0.4805567379233736,
+           0.4836060693833833,
+           0.48220504947012366,
+           0.4767806177278257,
+           0.46788632606737285,
+           0.4561902093886708,
+           0.44245941721656656,
+           0.42754197021835233,
+           0.41234608149461416,
+           0.3978175477840865,
+           0.3849157685242845,
+           0.3745889896980717,
+           0.3677493935494929,
+           0.36524866391623595,
+           0.3678546498323652,
+           0.3762297273274683,
+           0.3909114215011548,
+           0.41229579887690726,
+           0.44062407498483075,
+           0.4759728056628697,
+           0.5182479445617053,
+           0.56718295589228,
+           0.6223410728587115,
+           0.6831216908981492,
+           0.7487707833007172,
+           0.8183951275161173,
+           0.8909800359265904,
+           0.965410197424856,
+           1.0404931579559995,
+           1.1149849012156068,
+           1.1876169366213272,
+           1.257124261855364,
+           1.322273542726259,
+           1.3818908444604683,
+           1.4348882560579044,
+           1.4802887728838294,
+           1.5172488416813004,
+           1.5450780257519143,
+           1.5632553148872415,
+           1.5714416831311544,
+           1.569488585718273,
+           1.5574421824283926,
+           1.5355431757945046,
+           1.5042222566443166,
+           1.464091253812147,
+           1.4159301869904692,
+           1.360670519112384,
+           1.299374994996322,
+           1.2332145340436267,
+           1.163442714586533,
+           1.0913684443418845,
+           1.01832745395554,
+           0.9456532777951822,
+           0.8746483973133644,
+           0.8065562171978408,
+           0.7425345232911599,
+           0.6836310344294421,
+           0.6307616088360722,
+           0.5846916007834554,
+           0.5460207865059771,
+           0.5151721916985269,
+           0.4923850584968614,
+           0.4777120899266652,
+           0.47102100687617443,
+           0.47200034921221207,
+           0.48016935124932536,
+           0.49489162487044075,
+           0.5153922935442219,
+           0.5407781394755024,
+           0.5700602561203264,
+           0.6021786409813537,
+           0.6360281203416078,
+           0.6704849694144299,
+           0.7044335789306454,
+           0.7367925227064444,
+           0.7665394000981237,
+           0.7927338619222061,
+           0.8145382774936116,
+           0.8312355626480533,
+           0.8422437623826855,
+           0.8471270652032874,
+           0.8456030173030668,
+           0.8375458010301198,
+           0.8229855413138989,
+           0.8021037033358109,
+           0.7752247422609191,
+           0.7428042588696065,
+           0.7054140011307138,
+           0.6637241290067603,
+           0.6184832261710754,
+           0.5704965962148464,
+           0.5206034210134916,
+           0.46965338423856623,
+           0.41848337294746496,
+           0.3678948645481975,
+           0.31863258540138806,
+           0.27136499145288095,
+           0.22666707152598017,
+           0.18500591152807008,
+           0.14672938444270045,
+           0.11205824846066359,
+           0.0810818460552199,
+           0.0537575025051879,
+           0.02991362571068888,
+           0.009256412582898938,
+           -0.008620026729668603,
+           -0.024220404606192836,
+           -0.03813221144095629,
+           -0.051007323223096306,
+           -0.0635417551098384,
+           -0.07645410375430649,
+           -0.09046325609332043,
+           -0.10626596243527162,
+           -0.12451487649204124,
+           -0.14579765433683314,
+           -0.17061767839620517,
+           -0.1993769321372304,
+           -0.23236149709499657,
+           -0.26973007764950785,
+           -0.31150588216146585,
+           -0.35757210363822356,
+           -0.40767115116893665,
+           -0.461407687252463,
+           -0.5182554282623667,
+           -0.5775675681180061,
+           -0.6385905912132052,
+           -0.700481152173724,
+           -0.7623256193160868,
+           -0.8231618078174922,
+           -0.8820023693909786,
+           -0.9378592592155759,
+           -0.9897686691954639,
+           -1.036815800155783,
+           -1.0781588447888812,
+           -1.1130515681156838,
+           -1.1408639026028247,
+           -1.1611000201719586,
+           -1.1734134020798868,
+           -1.1776184986213738,
+           -1.1736986520879347,
+           -1.1618100464174588,
+           -1.1422815432873092,
+           -1.1156103646717086,
+           -1.0824536836338075,
+           -1.0436162858425955,
+           -1.0000345615035502,
+           -0.9527571786602826,
+           -0.902922871894353,
+           -0.8517358532519093,
+           -0.8004394129382383,
+           -0.750288324418511,
+           -0.7025207008517698,
+           -0.6583299664352257,
+           -0.6188376067998304,
+           -0.5850673470245179,
+           -0.5579213744700494,
+           -0.538159177207899,
+           -0.5263795084396424,
+           -0.52300591441649,
+           -0.5282761797344658,
+           -0.542235951521015,
+           -0.564736705182694,
+           -0.5954381114508066,
+           -0.6338147599444233,
+           -0.6791670909104863,
+           -0.7306362867189885,
+           -0.7872227805236999,
+           -0.8478079535379103,
+           -0.9111785167115883,
+           -0.9760530090714816,
+           -1.0411097951412023,
+           -1.1050159089021379,
+           -1.1664560725308128,
+           -1.2241612151114694,
+           -1.2769358297353282,
+           -1.323683536522815,
+           -1.3634302634162156,
+           -1.395344514989484,
+           -1.4187542705678349,
+           -1.4331601348919587,
+           -1.4382444553847868,
+           -1.4338762175522641,
+           -1.420111631782752,
+           -1.3971904283105112,
+           -1.365527979845842,
+           -1.325703470839099,
+           -1.2784444261138643,
+           -1.2246079973963548,
+           -1.1651594820042332,
+           -1.1011486118104543,
+           -1.0336842010349026,
+           -0.9639077772405718,
+           -0.8929668402864216,
+           -0.8219883984639687,
+           -0.7520534195604401,
+           -0.6841728074838345,
+           -0.6192654730760327,
+           -0.5581390119177758,
+           -0.5014734337222682,
+           -0.4498083090539418,
+           -0.4035336115879819,
+           -0.3628844401469842,
+           -0.3279397066714913,
+           -0.2986247765556176,
+           -0.2747179488976423,
+           -0.25586056864138007,
+           -0.24157047269312706,
+           -0.23125839011966823,
+           -0.22424684449175042,
+           -0.21979104610894296,
+           -0.217101214703865,
+           -0.21536574042163661,
+           -0.21377457318858367,
+           -0.21154222842702725,
+           -0.20792981045514555,
+           -0.20226548345754475,
+           -0.19396286286845338,
+           -0.1825368562602337,
+           -0.16761655092722863,
+           -0.1489548235555517,
+           -0.1264344336775795,
+           -0.1000704548283716,
+           -0.07000899310595028,
+           -0.036522239756476296,
+           -3.529409329030155e-16
+          ],
+          [
+           0,
+           0.03893680812818524,
+           0.07949999039598225,
+           0.12101410022679125,
+           0.16276140015128954,
+           0.20400302958757632,
+           0.24400085237021013,
+           0.28203939818336743,
+           0.3174473084986028,
+           0.34961770919342655,
+           0.37802695845372997,
+           0.40225125918727617,
+           0.4219806789852135,
+           0.43703018631908563,
+           0.44734738750786524,
+           0.45301673313040364,
+           0.4542600528796246,
+           0.45143337208375606,
+           0.4450200588833673,
+           0.4356204459351393,
+           0.42393816211659313,
+           0.4107634957109579,
+           0.39695418877484046,
+           0.38341413084114434,
+           0.3710704770346407,
+           0.3608497596115702,
+           0.3536535917335891,
+           0.3503345771572362,
+           0.35167303904116215,
+           0.35835516520527194,
+           0.37095313626325926,
+           0.3899077578131891,
+           0.41551405938883296,
+           0.4479102525585739,
+           0.4870703601177546,
+           0.5328007397188278,
+           0.584740630693257,
+           0.6423667545651287,
+           0.7050019002602491,
+           0.7718273267337259,
+           0.8418987211066425,
+           0.9141653617662603,
+           0.9874920554489387,
+           1.0606833470971797,
+           1.132509443020433,
+           1.201733243060322,
+           1.267137847203055,
+           1.327553887176209,
+           1.3818860344184047,
+           1.4291380524360302,
+           1.4684357935904173,
+           1.4990475870418956,
+           1.520401524802843,
+           1.5320992251750274,
+           1.5339257355232427,
+           1.5258553273675446,
+           1.5080530339531852,
+           1.48087188142105,
+           1.4448458669973825,
+           1.4006788387610671,
+           1.3492295290675989,
+           1.2914930852365185,
+           1.2285795244148094,
+           1.1616896125844256,
+           1.092088728710499,
+           1.0210793225446764,
+           0.9499726074534196,
+           0.8800601470407358,
+           0.8125859958643629,
+           0.7487200401779426,
+           0.68953315473261,
+           0.6359747469831517,
+           0.5888532016713266,
+           0.5488196681417102,
+           0.5163555516208741,
+           0.4917639800529153,
+           0.4751654221325945,
+           0.4664975322639275,
+           0.46551919674252046,
+           0.47181865499384446,
+           0.48482547264886006,
+           0.5038260519669686,
+           0.5279822818420106,
+           0.5563528563673068,
+           0.587916729457412,
+           0.6215981248011572,
+           0.6562924865965274,
+           0.690892737879937,
+           0.7243152102210462,
+           0.7555246211338821,
+           0.7835575033948569,
+           0.807543532820086,
+           0.8267242568436114,
+           0.8404687940289485,
+           0.8482861527201268,
+           0.8498339034244704,
+           0.8449230320460042,
+           0.8335188974361711,
+           0.8157383144881798,
+           0.791842880734287,
+           0.7622287577036512,
+           0.7274132058453389,
+           0.6880182514480788,
+           0.644751933729132,
+           0.5983876384037554,
+           0.5497420691620833,
+           0.4996524394780524,
+           0.4489534833167282,
+           0.3984548842268281,
+           0.34891970802091843,
+           0.3010443951544301,
+           0.2554408257847028,
+           0.21262091444211523,
+           0.17298412371948793,
+           0.13680820911191258,
+           0.10424342208863839,
+           0.07531030781676401,
+           0.04990113998708022,
+           0.027784940301010187,
+           0.00861593677074422,
+           -0.008054774569674317,
+           -0.022764683376756942,
+           -0.036122828163439084,
+           -0.04879072800063004,
+           -0.06146179509498128,
+           -0.07483978069427416,
+           -0.0896168327128613,
+           -0.10645175457529393,
+           -0.12594905075468685,
+           -0.14863932542256197,
+           -0.17496156699691834,
+           -0.20524780401042927,
+           -0.23971055780293363,
+           -0.2784334465710336,
+           -0.32136521506151317,
+           -0.36831737668919917,
+           -0.4189655622933117,
+           -0.4728545744495846,
+           -0.5294070506305485,
+           -0.5879355449676025,
+           -0.6476577492818224,
+           -0.7077144916742896,
+           -0.7671900773952204,
+           -0.8251344738219788,
+           -0.8805867907829869,
+           -0.9325994704766001,
+           -0.9802625788232,
+           -1.022727582863987,
+           -1.0592300070129983,
+           -1.0891103844263663,
+           -1.1118329579408601,
+           -1.127001637049839,
+           -1.134372781979874,
+           -1.1338644615406843,
+           -1.1255619162023498,
+           -1.1097190497324025,
+           -1.0867558694460366,
+           -1.057251894304466,
+           -1.0219356492924327,
+           -0.9816704612630027,
+           -0.9374368633583086,
+           -0.8903119999154975,
+           -0.8414464993354208,
+           -0.7920393468393399,
+           -0.743311340748282,
+           -0.6964777535841392,
+           -0.652720841948107,
+           -0.6131628561862623,
+           -0.5788401920917599,
+           -0.5506793024957943,
+           -0.5294749471270012,
+           -0.5158713055044554,
+           -0.5103464111553239,
+           -0.513200287713555,
+           -0.5245470803388714,
+           -0.5443113815054558,
+           -0.5722288508376824,
+           -0.6078511267304464,
+           -0.6505549254635536,
+           -0.6995551238861758,
+           -0.7539215269346372,
+           -0.8125989335631865,
+           -0.8744300362483892,
+           -0.9381806219813585,
+           -1.0025664882239973,
+           -1.0662814469971393,
+           -1.1280257650654817,
+           -1.1865343786926321,
+           -1.2406042278795102,
+           -1.2891200772023192,
+           -1.3310782277763504,
+           -1.3656075765626299,
+           -1.3919875439292684,
+           -1.4096624664849409,
+           -1.418252137846957,
+           -1.4175582730873442,
+           -1.407566770834662,
+           -1.3884457479904775,
+           -1.3605394232773107,
+           -1.3243580248961206,
+           -1.2805639920206735,
+           -1.2299548273952698,
+           -1.1734430368073672,
+           -1.1120336587795367,
+           -1.0467999428406607,
+           -0.9788577758814407,
+           -0.9093394824059178,
+           -0.8393676353580614,
+           -0.7700295094125913,
+           -0.7023527883408869,
+           -0.6372831028472413,
+           -0.575663926037297,
+           -0.5182192916933511,
+           -0.46553972736767646,
+           -0.41807171181523983,
+           -0.37611087654912945,
+           -0.3397990765682171,
+           -0.30912535794873,
+           -0.2839307524410079,
+           -0.2639167339007608,
+           -0.24865708068004985,
+           -0.2376128042568882,
+           -0.23014972946755002,
+           -0.22555824756893308,
+           -0.22307471157335357,
+           -0.22190390512677274,
+           -0.2212419925625551,
+           -0.22029934921010702,
+           -0.2183226777458922,
+           -0.21461583813552204,
+           -0.20855885494502238,
+           -0.19962461554987507,
+           -0.187392834757277,
+           -0.17156093398945363,
+           -0.1519515645980401,
+           -0.12851659301647803,
+           -0.10133745806757871,
+           -0.07062190547477662,
+           -0.03669719907463587,
+           -3.5322219796025685e-16
+          ],
+          [
+           0,
+           0.038678023513502545,
+           0.07865421339403486,
+           0.11924507462750672,
+           0.15973682086161817,
+           0.19940650572490226,
+           0.23754349615365727,
+           0.27347071104392623,
+           0.3065650536002017,
+           0.3362764854926618,
+           0.3621452248734253,
+           0.383816597594478,
+           0.4010531304334934,
+           0.41374354527908014,
+           0.4219083922939698,
+           0.42570214607666923,
+           0.4254116796155662,
+           0.4214511240879347,
+           0.41435321594743285,
+           0.4047573239083023,
+           0.39339443506536215,
+           0.3810694592886871,
+           0.36864128216805986,
+           0.357001057338363,
+           0.34704927743794767,
+           0.3396721979834189,
+           0.33571820916437534,
+           0.33597475640449664,
+           0.3411464013055998,
+           0.3518345904694536,
+           0.36851966123078694,
+           0.39154556144540303,
+           0.42110769640759727,
+           0.4572442412752805,
+           0.49983117388131787,
+           0.5485811925506825,
+           0.6030465887427311,
+           0.662626047331614,
+           0.726575250520985,
+           0.794021067157762,
+           0.8639790199011331,
+           0.9353736405377124,
+           1.0070612507605425,
+           1.0778546437741157,
+           1.146549092707221,
+           1.211949076260354,
+           1.272895091196183,
+           1.328289915750307,
+           1.3771236979697274,
+           1.4184972681724675,
+           1.451643114582154,
+           1.4759435147832016,
+           1.4909453816836618,
+           1.4963714595745976,
+           1.4921275917791041,
+           1.4783058742100015,
+           1.4551836066499213,
+           1.4232180533616372,
+           1.3830371243023623,
+           1.3354261853270686,
+           1.2813112979575705,
+           1.2217392743202962,
+           1.1578550086452215,
+           1.0908766114257726,
+           1.022068924390079,
+           0.9527160325630125,
+           0.8840934129821681,
+           0.8174403675088103,
+           0.7539333794640611,
+           0.6946610107195815,
+           0.6406009179561922,
+           0.5925995150108816,
+           0.551354743839256,
+           0.5174023412110554,
+           0.4911059036835061,
+           0.4726509617363231,
+           0.4620431774495568,
+           0.45911068112373227,
+           0.4635104632007218,
+           0.4747386411614683,
+           0.4921443291092192,
+           0.5149467527308461,
+           0.542255176325916,
+           0.5730911434399512,
+           0.6064124799007196,
+           0.6411384689919198,
+           0.6761755840252003,
+           0.7104431542455024,
+           0.7428983460079246,
+           0.7725598622994585,
+           0.7985297993755597,
+           0.8200131486103944,
+           0.8363344933564304,
+           0.8469515231061665,
+           0.8514650687146548,
+           0.849625450826207,
+           0.8413350267356194,
+           0.8266469163749356,
+           0.8057599835690984,
+           0.7790102417712894,
+           0.7468589418595378,
+           0.7098776810604958,
+           0.6687309446508448,
+           0.6241565539845598,
+           0.5769445440886422,
+           0.5279150303523854,
+           0.4778956458347349,
+           0.4276991379188271,
+           0.3781017053117045,
+           0.32982263395396844,
+           0.28350575387066246,
+           0.23970318931521828,
+           0.19886181301571643,
+           0.1613127435059468,
+           0.12726414424787502,
+           0.09679749657246628,
+           0.0698674275865164,
+           0.046305081421680924,
+           0.025824929891565724,
+           0.008034829113341255,
+           -0.007550955790260642,
+           -0.021496113025380906,
+           -0.034424456682817905,
+           -0.0470003898782241,
+           -0.059908183677286606,
+           -0.0738306283635979,
+           -0.0894276306834984,
+           -0.1073153330577153,
+           -0.12804631831443342,
+           -0.15209143657543414,
+           -0.17982375018431787,
+           -0.2115050390202725,
+           -0.24727524353244684,
+           -0.287145147988698,
+           -0.3309925236374878,
+           -0.3785618628146824,
+           -0.429467742719899,
+           -0.4832017639665382,
+           -0.5391429164389243,
+           -0.5965711358095379,
+           -0.6546837305385311,
+           -0.7126142834182876,
+           -0.7694535656680661,
+           -0.8242719469191643,
+           -0.8761427425684476,
+           -0.9241659120091452,
+           -0.9674915079188325,
+           -1.0053422784772148,
+           -1.0370348411085186,
+           -1.0619988777270235,
+           -1.0797938467756063,
+           -1.0901227655030412,
+           -1.0928426855208342,
+           -1.087971564021376,
+           -1.0756913201865665,
+           -1.0563469591319266,
+           -1.0304417419318752,
+           -0.9986284774846748,
+           -0.9616971077972456,
+           -0.9205588503266194,
+           -0.8762272470201518,
+           -0.8297965475095688,
+           -0.7824179215911279,
+           -0.735274051968747,
+           -0.6895527008409106,
+           -0.6464198721909863,
+           -0.6069932048612114,
+           -0.5723162292897307,
+           -0.543334103182859,
+           -0.5208714087763671,
+           -0.5056125474741792,
+           -0.4980852076564349,
+           -0.49864730976126737,
+           -0.5074777510947381,
+           -0.5245711831866495,
+           -0.5497369590598629,
+           -0.5826022888356,
+           -0.622619542062877,
+           -0.6690775364712194,
+           -0.721116557905247,
+           -0.7777467673201811,
+           -0.8378695700639547,
+           -0.9003014522089715,
+           -0.963799730139656,
+           -1.027089614375293,
+           -1.0888919578084566,
+           -1.1479510429123487,
+           -1.203061762388251,
+           -1.2530955631792098,
+           -1.2970245543800238,
+           -1.3339432245674008,
+           -1.3630872723475391,
+           -1.3838491240360653,
+           -1.3957897926233944,
+           -1.398646820567433,
+           -1.3923381433270623,
+           -1.3769618085927973,
+           -1.352791585486602,
+           -1.3202685961646845,
+           -1.2799891968707775,
+           -1.2326894242495319,
+           -1.1792264034842723,
+           -1.1205571856155152,
+           -1.0577155405197498,
+           -0.9917872780659782,
+           -0.9238847018293815,
+           -0.855120816687995,
+           -0.7865839132889196,
+           -0.7193131387536038,
+           -0.654275634482057,
+           -0.592345779265693,
+           -0.5342870202281649,
+           -0.48073670680341163,
+           -0.4321942657353492,
+           -0.3890129698906479,
+           -0.3513954626551265,
+           -0.31939310511502195,
+           -0.2929091174693553,
+           -0.27170539156557677,
+           -0.2554127604492342,
+           -0.24354442562714726,
+           -0.2355121654707706,
+           -0.23064488073808304,
+           -0.22820897722537017,
+           -0.22743004244148532,
+           -0.2275152439696188,
+           -0.22767586253876457,
+           -0.22714937309642766,
+           -0.22522050230890847,
+           -0.2212407204967225,
+           -0.2146456692598803,
+           -0.20497008183854584,
+           -0.1918598201538681,
+           -0.17508072876883587,
+           -0.1545240897537619,
+           -0.13020855150387642,
+           -0.10227849667465584,
+           -0.07099890723616285,
+           -0.036746875846970325,
+           -3.5228760736007046e-16
+          ],
+          [
+           0,
+           0.03828712550982384,
+           0.07754616413760493,
+           0.11709220580844178,
+           0.15622181019314754,
+           0.1942339043322352,
+           0.23045069605110405,
+           0.26423804067438517,
+           0.29502471178776535,
+           0.3223200541578798,
+           0.34572953772397763,
+           0.3649677847989057,
+           0.37986870692773894,
+           0.3903924616359319,
+           0.39662902070085576,
+           0.39879822855286534,
+           0.39724631976375385,
+           0.3924389560328083,
+           0.3849509333239018,
+           0.37545279655816827,
+           0.364694680326833,
+           0.35348776739772003,
+           0.3426838204776433,
+           0.33315329512973035,
+           0.325762581576962,
+           0.3213509493108981,
+           0.32070778026708907,
+           0.3245506734826445,
+           0.33350498663974004,
+           0.3480853481106597,
+           0.3686796278015693,
+           0.39553579732889443,
+           0.4287520412518073,
+           0.46827040290300376,
+           0.513874162720725,
+           0.5651890559907468,
+           0.6216883427984623,
+           0.6827016480913848,
+           0.7474273964093178,
+           0.814948576367738,
+           0.8842514866035255,
+           0.9542470396888365,
+           1.0237941353688955,
+           1.091724561018394,
+           1.1568688367893616,
+           1.2180823965720315,
+           1.2742714842956062,
+           1.3244181485816398,
+           1.3676037372820224,
+           1.403030326569131,
+           1.4300395662200773,
+           1.4481284824315217,
+           1.4569618504830737,
+           1.4563808301238628,
+           1.4464076447390786,
+           1.4272461790225606,
+           1.399278466762381,
+           1.3630571380825458,
+           1.3192939916962365,
+           1.2688449500708776,
+           1.2126917416325362,
+           1.1519207321452891,
+           1.0876993952892298,
+           1.0212509685750175,
+           0.9538278837076327,
+           0.8866845893030996,
+           0.8210503977726392,
+           0.7581029868864045,
+           0.6989431700537898,
+           0.6445715181205955,
+           0.595867370257699,
+           0.5535707134159683,
+           0.5182673402768342,
+           0.4903776163456296,
+           0.47014909976013164,
+           0.45765316465403433,
+           0.4527856827940071,
+           0.4552717210501181,
+           0.46467411643502815,
+           0.48040569829380353,
+           0.5017448409859235,
+           0.5278539521676266,
+           0.5578004334491812,
+           0.5905795934144663,
+           0.62513894910819,
+           0.6604033221582697,
+           0.6953001204001368,
+           0.7287841955371487,
+           0.7598616819678458,
+           0.7876122510288002,
+           0.8112092577764641,
+           0.829937312958503,
+           0.84320687959116,
+           0.8505655698744338,
+           0.8517059021199684,
+           0.8464693668306029,
+           0.8348467438169435,
+           0.8169747059500662,
+           0.7931288374964744,
+           0.7637132836673641,
+           0.7292473308405819,
+           0.6903492918329629,
+           0.6477181357669693,
+           0.6021133558899913,
+           0.5543336098551583,
+           0.5051946944661164,
+           0.45550743007513006,
+           0.40605602841353977,
+           0.35757750170141445,
+           0.3107426408680867,
+           0.26613904740838623,
+           0.22425664792409009,
+           0.18547605418321772,
+           0.15006005626610638,
+           0.11814845397624686,
+           0.08975634427216127,
+           0.06477589224497804,
+           0.042981522413831894,
+           0.02403837813835782,
+           0.007513812008045932,
+           -0.007108408686923662,
+           -0.020411567875480745,
+           -0.03302758509925205,
+           -0.045617214572590034,
+           -0.05884939146391366,
+           -0.07338028064358737,
+           -0.08983259158190286,
+           -0.10877571704593095,
+           -0.13070723287958277,
+           -0.1560362619617526,
+           -0.18506915827621617,
+           -0.21799790807462502,
+           -0.25489157584904637,
+           -0.29569104499283766,
+           -0.3402072185753824,
+           -0.38812275671375646,
+           -0.4389973358343027,
+           -0.492276323981096,
+           -0.5473026775498404,
+           -0.6033317806528905,
+           -0.6595488708900517,
+           -0.7150886265813913,
+           -0.7690564322683207,
+           -0.820550793004603,
+           -0.8686863348399761,
+           -0.9126168098185573,
+           -0.9515575192961525,
+           -0.9848065795854936,
+           -1.0117644786599824,
+           -1.0319514113150634,
+           -1.0450219318834155,
+           -1.0507765270803182,
+           -1.0491697852770738,
+           -1.0403149206630877,
+           -1.0244844993470557,
+           -1.002107307285972,
+           -0.973761394728547,
+           -0.9401634262741598,
+           -0.9021545573412545,
+           -0.8606831445335734,
+           -0.8167846769314069,
+           -0.7715593857329199,
+           -0.7261480491640059,
+           -0.6817065566665133,
+           -0.6393798298695391,
+           -0.6002757168853208,
+           -0.5654394805433599,
+           -0.5358294901452653,
+           -0.51229470042071,
+           -0.4955544611913158,
+           -0.4861811477550655,
+           -0.48458603646868564,
+           -0.4910087740069949,
+           -0.5055107041525188,
+           -0.5279722247662516,
+           -0.5580942520249611,
+           -0.5954037714050417,
+           -0.6392633576225429,
+           -0.6888844511725,
+           -0.7433440895517588,
+           -0.8016047088810746,
+           -0.8625365584712886,
+           -0.9249422086882765,
+           -0.9875825827758551,
+           -1.0492039073041384,
+           -1.1085649544957714,
+           -1.1644639433602373,
+           -1.2157644754841639,
+           -1.261419905256065,
+           -1.3004955826542877,
+           -1.3321884585496866,
+           -1.355843606494709,
+           -1.3709672896141885,
+           -1.3772362846481452,
+           -1.3745032653776195,
+           -1.3627981423819329,
+           -1.3423253530127537,
+           -1.3134571922580422,
+           -1.276723369445844,
+           -1.2327970652074478,
+           -1.1824778456070806,
+           -1.1266718638513586,
+           -1.0663698427412525,
+           -1.0026233815148917,
+           -0.936520167748574,
+           -0.8691586976672767,
+           -0.8016231160513912,
+           -0.7349587797666879,
+           -0.6701491270139246,
+           -0.6080943982812312,
+           -0.5495927056237414,
+           -0.49532388555383394,
+           -0.4458364990582623,
+           -0.40153826187669756,
+           -0.3626901012000216,
+           -0.3294039435558348,
+           -0.3016442451269715,
+           -0.2792331824280755,
+           -0.2618593304669292,
+           -0.24908956949483071,
+           -0.2403838823332151,
+           -0.23511263400491644,
+           -0.2325758657256022,
+           -0.23202408768392774,
+           -0.23268002061396525,
+           -0.23376071576442872,
+           -0.23449947696756265,
+           -0.23416701721434843,
+           -0.23209130519378007,
+           -0.2276755940353346,
+           -0.22041417404520258,
+           -0.20990545226902685,
+           -0.19586203268135846,
+           -0.17811754988162137,
+           -0.1566300943539411,
+           -0.13148215645814393,
+           -0.10287710709960313,
+           -0.0711323231743337,
+           -0.03666915311860967,
+           -3.501338376429911e-16
+          ],
+          [
+           0,
+           0.037766903976489935,
+           0.07618478725972676,
+           0.11457372433036747,
+           0.15224666728850478,
+           0.1885299225303975,
+           0.22278333151908877,
+           0.25441961203528346,
+           0.2829223372276002,
+           0.3078620641639067,
+           0.328910170557987,
+           0.3458500167306357,
+           0.35858511819539973,
+           0.3671440908187636,
+           0.3716822133658438,
+           0.3724795393181052,
+           0.36993557894306633,
+           0.3645606614575376,
+           0.35696417350834325,
+           0.3478399519091777,
+           0.33794918354441167,
+           0.3281012316710504,
+           0.31913286382307104,
+           0.3118864007086156,
+           0.30718733674316556,
+           0.30582200035552576,
+           0.30851582545548717,
+           0.31591279433478336,
+           0.3285565870175694,
+           0.34687393326783716,
+           0.3711606120231523,
+           0.401570480198031,
+           0.43810784011393783,
+           0.48062337404300687,
+           0.5288137874810934,
+           0.5822252119308075,
+           0.6402603254182544,
+           0.7021890569776782,
+           0.7671626521965087,
+           0.8342307928344169,
+           0.9023613866084078,
+           0.9704625753935543,
+           1.0374064530272409,
+           1.1020539390623276,
+           1.1632802233312387,
+           1.2200001788710455,
+           1.271193138083566,
+           1.315926439068985,
+           1.3533771756182393,
+           1.382851624763336,
+           1.4038018791085234,
+           1.415839276122794,
+           1.4187442916017183,
+           1.412472647790834,
+           1.3971574761856436,
+           1.373107468611114,
+           1.340801045560909,
+           1.3008766656220045,
+           1.2541194918133578,
+           1.2014447175857101,
+           1.143877934944157,
+           1.0825329977221558,
+           1.0185878927347172,
+           0.9532591789147569,
+           0.8877755884367465,
+           0.8233514034322597,
+           0.761160226729466,
+           0.7023097549912495,
+           0.6478181379372011,
+           0.5985924686239041,
+           0.5554098979794126,
+           0.5189018032146641,
+           0.48954136592753644,
+           0.46763483348478735,
+           0.45331664862768073,
+           0.44654853936876193,
+           0.44712256640071796,
+           0.45466803074018863,
+           0.4686620524842934,
+           0.48844354460174794,
+           0.5132302257263623,
+           0.5421382449056543,
+           0.5742039308952651,
+           0.6084071303301293,
+           0.6436955640941638,
+           0.6790096102720916,
+           0.7133069156713977,
+           0.7455862461619139,
+           0.774910008745766,
+           0.8004249147367332,
+           0.821380302751896,
+           0.8371437011394474,
+           0.8472132804415561,
+           0.8512269257303939,
+           0.8489677441695536,
+           0.840365912800847,
+           0.8254968630995804,
+           0.8045758899993819,
+           0.7779493615947174,
+           0.7460827893908981,
+           0.7095460957184173,
+           0.6689964828685592,
+           0.6251593659717359,
+           0.578807877225053,
+           0.530741481676794,
+           0.48176426361515456,
+           0.4326634472543011,
+           0.3841887057863767,
+           0.33703278925443886,
+           0.29181396472933957,
+           0.24906071290794785,
+           0.20919906476481656,
+           0.172542891835376,
+           0.13928738587526707,
+           0.10950588000959895,
+           0.08315007618329058,
+           0.060053654964883685,
+           0.039939155791134356,
+           0.022427930796607785,
+           0.007052895601653127,
+           -0.006726272147560673,
+           -0.019505899245116354,
+           -0.031919514071113105,
+           -0.04461798102941773,
+           -0.05824910681344164,
+           -0.07343726723444485,
+           -0.09076360345551313,
+           -0.11074732248364738,
+           -0.1338286090281081,
+           -0.1603536150276919,
+           -0.19056194030500584,
+           -0.22457695424798194,
+           -0.2623992357447372,
+           -0.30390332863554864,
+           -0.34883792470841063,
+           -0.3968294979012189,
+           -0.44738932411377774,
+           -0.4999237331324818,
+           -0.5537473548544217,
+           -0.6080990434041987,
+           -0.6621600918642755,
+           -0.7150742889963446,
+           -0.7659693190893319,
+           -0.8139789682265547,
+           -0.8582655758095111,
+           -0.8980421597647236,
+           -0.9325936477994964,
+           -0.961296665310147,
+           -0.9836373626734556,
+           -0.9992268099116809,
+           -1.0078135440277096,
+           -1.0092929222708715,
+           -1.003713011558402,
+           -0.9912768283571836,
+           -0.9723408324590043,
+           -0.9474096700632995,
+           -0.917127254141858,
+           -0.8822643609082101,
+           -0.8437030080956778,
+           -0.8024179615008341,
+           -0.759455788858996,
+           -0.715911942768056,
+           -0.6729064054912937,
+           -0.6315584667557075,
+           -0.5929612301406751,
+           -0.5581564536818922,
+           -0.5281103256120042,
+           -0.5036907567994116,
+           -0.48564673786800405,
+           -0.47459026197194853,
+           -0.47098125488113085,
+           -0.47511588382863984,
+           -0.4871185371757141,
+           -0.5069376802832368,
+           -0.5343457011446331,
+           -0.5689427645641941,
+           -0.610164598263122,
+           -0.6572940405858638,
+           -0.7094760897452762,
+           -0.765736110973882,
+           -0.8250007825782016,
+           -0.8861212965609893,
+           -0.9478982757753999,
+           -1.0091078288130682,
+           -1.068528136996886,
+           -1.1249659555990197,
+           -1.1772824140288392,
+           -1.2244175171636678,
+           -1.265412781793872,
+           -1.2994314875389237,
+           -1.3257760794451212,
+           -1.3439023283779714,
+           -1.353429933581552,
+           -1.3541493374752769,
+           -1.3460246137966945,
+           -1.3291923843497946,
+           -1.303956814581205,
+           -1.2707808316637745,
+           -1.230273798441002,
+           -1.1831759602954164,
+           -1.1303400577183247,
+           -1.072710563245795,
+           -1.0113010559002045,
+           -0.9471702880351046,
+           -0.8813975275363162,
+           -0.8150577720360604,
+           -0.7491974308568169,
+           -0.6848110548859119,
+           -0.6228196649191591,
+           -0.5640511859788155,
+           -0.5092234398129617,
+           -0.45893008162643506,
+           -0.41362979174933845,
+           -0.37363895031346056,
+           -0.33912793515126866,
+           -0.3101210922532283,
+           -0.2865003364835341,
+           -0.2680122501419955,
+           -0.2542784606079679,
+           -0.24480899784944746,
+           -0.23901826001346965,
+           -0.2362431524189835,
+           -0.23576291359134033,
+           -0.23682010276645882,
+           -0.23864219749652943,
+           -0.2404632382147592,
+           -0.24154495911900262,
+           -0.24119686141066096,
+           -0.23879471531840343,
+           -0.23379702064576688,
+           -0.22575901068475185,
+           -0.21434384981700305,
+           -0.19933074930493522,
+           -0.18061980676531994,
+           -0.15823346055730889,
+           -0.1323145386280695,
+           -0.10312097000242511,
+           -0.07101731383197186,
+           -0.036463343538007405,
+           -3.4677076094501506e-16
+          ],
+          [
+           0,
+           0.03712146651289038,
+           0.07458150309202567,
+           0.11171126999941448,
+           0.14784575241297762,
+           0.18234364068394895,
+           0.2146066202535221,
+           0.2440975507975868,
+           0.27035704223764384,
+           0.29301797600602697,
+           0.31181757236213775,
+           0.32660666730687093,
+           0.3373559341565964,
+           0.34415886331564527,
+           0.3472313972497816,
+           0.3469082040074125,
+           0.34363565967999865,
+           0.33796169573742896,
+           0.3305227490516476,
+           0.3220281285550224,
+           0.3132421809320953,
+           0.30496469676721044,
+           0.29801004665215225,
+           0.2931855726549739,
+           0.2912697833240803,
+           0.2929909094375615,
+           0.29900637273642405,
+           0.30988370098108503,
+           0.32608339027084965,
+           0.347944170431711,
+           0.3756710724937725,
+           0.4093266302239357,
+           0.448825471989252,
+           0.49393247675737084,
+           0.5442645808214411,
+           0.5992962320191595,
+           0.6583683980202663,
+           0.7207009469190507,
+           0.7854081340826704,
+           0.8515168510711085,
+           0.9179872224115753,
+           0.9837350758338508,
+           1.0476557627684686,
+           1.1086487697136098,
+           1.1656425384173437,
+           1.2176189042953707,
+           1.2636365683591673,
+           1.3028530380601087,
+           1.3345445064044794,
+           1.3581231856642488,
+           1.3731516708793934,
+           1.3793539777054196,
+           1.3766229773309306,
+           1.3650240362821815,
+           1.3447947588799662,
+           1.3163408227327906,
+           1.2802279906851104,
+           1.2371704738244353,
+           1.1880159072634315,
+           1.133727281328471,
+           1.0753622435303463,
+           1.0140502494913624,
+           0.9509680923238011,
+           0.8873143785466314,
+           0.824283543550386,
+           0.7630400102691208,
+           0.7046930908375303,
+           0.6502732127003219,
+           0.6007100183531708,
+           0.5568128424247228,
+           0.5192540122746797,
+           0.4885553500958512,
+           0.46507817734000134,
+           0.4490170380286239,
+           0.44039726822263525,
+           0.43907644679252505,
+           0.4447496699030949,
+           0.4569585005665994,
+           0.47510335744290144,
+           0.49845902589456614,
+           0.5261929011073768,
+           0.5573855096320849,
+           0.5910528035183942,
+           0.626169681544471,
+           0.6616941658313669,
+           0.6965916499756339,
+           0.7298586369912631,
+           0.7605454017268046,
+           0.787777042567568,
+           0.8107724303596187,
+           0.8288606174963817,
+           0.8414943355933927,
+           0.8482602844893646,
+           0.8488859965846622,
+           0.8432431467258257,
+           0.8313472668137428,
+           0.8133539138364793,
+           0.7895514278799738,
+           0.7603505006716827,
+           0.7262708532854106,
+           0.6879253918538788,
+           0.6460022707726525,
+           0.6012453424512436,
+           0.5544335099699501,
+           0.5063595231384511,
+           0.4578087688593833,
+           0.40953860315625507,
+           0.3622587548587877,
+           0.3166133002246333,
+           0.2731646645221847,
+           0.2323800519259476,
+           0.19462064038900365,
+           0.16013380511117378,
+           0.12904855467882925,
+           0.10137427993578682,
+           0.07700282928739481,
+           0.05571383763131495,
+           0.037183151639765745,
+           0.02099411382716668,
+           0.0066513937554050755,
+           -0.006403011270018626,
+           -0.018772039906744968,
+           -0.0310845738512783,
+           -0.04397570000626953,
+           -0.05806675907223279,
+           -0.07394571786138007,
+           -0.09214839479516292,
+           -0.11314104660245786,
+           -0.13730478971745505,
+           -0.16492228315017854,
+           -0.19616704184135694,
+           -0.23109568216895282,
+           -0.2696433260406514,
+           -0.3116223087797972,
+           -0.35672425083936166,
+           -0.40452546640906456,
+           -0.4544955954121603,
+           -0.5060092614111282,
+           -0.5583604786842531,
+           -0.6107794592112212,
+           -0.6624514063632293,
+           -0.7125368283675106,
+           -0.7601928624899639,
+           -0.8045950714473724,
+           -0.8449591576010232,
+           -0.8805620384394699,
+           -0.9107617388255932,
+           -0.9350155812076826,
+           -0.9528961938777948,
+           -0.9641049084747384,
+           -0.9684821800384891,
+           -0.9660147345154038,
+           -0.9568392279374007,
+           -0.9412422866050777,
+           -0.9196568863979663,
+           -0.8926551196218012,
+           -0.860937487347682,
+           -0.8253189417797215,
+           -0.7867119846527487,
+           -0.7461072019787212,
+           -0.7045516807707963,
+           -0.663125808037675,
+           -0.6229189949774573,
+           -0.5850048988239236,
+           -0.5504167304444852,
+           -0.520123237134282,
+           -0.4950059370232171,
+           -0.4758381543943897,
+           -0.46326636463263304,
+           -0.45779430444281305,
+           -0.4597702386696609,
+           -0.4693777010628941,
+           -0.486629944451688,
+           -0.5113682480058281,
+           -0.5432641376989877,
+           -0.5818254829794837,
+           -0.6264063402624852,
+           -0.6762203244364621,
+           -0.7303572053059002,
+           -0.787802348827581,
+           -0.8474585550191504,
+           -0.9081697871846924,
+           -0.96874624200865,
+           -1.0279901782152352,
+           -1.0847219036509637,
+           -1.137805317254414,
+           -1.1861724135084082,
+           -1.228846182347981,
+           -1.2649613764968017,
+           -1.2937826698661654,
+           -1.3147197937054185,
+           -1.3273393100944557,
+           -1.331372763330877,
+           -1.3267210368042577,
+           -1.3134548339386458,
+           -1.2918112944980105,
+           -1.262186849724981,
+           -1.2251265091737125,
+           -1.1813098565277573,
+           -1.1315341091129683,
+           -1.0766946643489732,
+           -1.0177636143769881,
+           -0.9557667561655582,
+           -0.8917596574337411,
+           -0.826803357970573,
+           -0.7619402909391267,
+           -0.6981709994534079,
+           -0.6364322003797072,
+           -0.5775767105601475,
+           -0.5223557014339634,
+           -0.47140368759644485,
+           -0.42522658471607483,
+           -0.38419309419279385,
+           -0.3485295879424363,
+           -0.3183185788349405,
+           -0.29350077278909026,
+           -0.27388060956245996,
+           -0.2591351130811268,
+           -0.2488257908649767,
+           -0.24241324772965414,
+           -0.23927411331716678,
+           -0.2387198277339693,
+           -0.24001678600623666,
+           -0.2424073112504352,
+           -0.2451309091358045,
+           -0.2474452527781855,
+           -0.24864635769769702,
+           -0.2480874305937264,
+           -0.24519591279616604,
+           -0.23948828837434907,
+           -0.23058228675760065,
+           -0.21820617880864543,
+           -0.20220494182958415,
+           -0.18254315102076069,
+           -0.15930454037133057,
+           -0.13268826266847555,
+           -0.1030019640728143,
+           -0.07065187134919769,
+           -0.03613016727364492,
+           -3.4222105640597696e-16
+          ],
+          [
+           0,
+           0.03635616368727921,
+           0.07275002485656257,
+           0.10852957259284614,
+           0.14305700869190197,
+           0.1757278694302714,
+           0.20598928228811306,
+           0.2333568642597548,
+           0.25742980298239815,
+           0.2779037083358916,
+           0.2945808792487681,
+           0.30737769675147186,
+           0.3163289281770125,
+           0.3215888069606253,
+           0.32342883572656955,
+           0.32223234517015226,
+           0.3184859255021256,
+           0.31276792878768955,
+           0.3057343173149798,
+           0.2981022032161129,
+           0.2906314861510296,
+           0.28410504737421444,
+           0.27930799861054245,
+           0.27700651182606895,
+           0.2779267704594474,
+           0.282734583575237,
+           0.2920161916461716,
+           0.3062607665432033,
+           0.3258450694202804,
+           0.3510206794559346,
+           0.38190414508370785,
+           0.4184703389033487,
+           0.46054921964000445,
+           0.5078261212226313,
+           0.5598456023393031,
+           0.6160188018394956,
+           0.6756341582717547,
+           0.7378712678319544,
+           0.8018175761438613,
+           0.8664875275680337,
+           0.9308437329331617,
+           0.993819664284653,
+           1.0543433447713295,
+           1.1113614741755862,
+           1.1638634165530308,
+           1.2109044763686003,
+           1.2516279034380358,
+           1.2852850946019894,
+           1.3112535007327208,
+           1.3290518004357084,
+           1.3383519653968812,
+           1.3389879152090194,
+           1.3309605399258186,
+           1.314438954589643,
+           1.2897579394700136,
+           1.2574116105572783,
+           1.218043454767938,
+           1.1724329511430571,
+           1.1214790809410764,
+           1.0661811039493492,
+           1.0076170437480727,
+           0.946920379459096,
+           0.8852554843627418,
+           0.8237923816227649,
+           0.7636814034954662,
+           0.7060283424220105,
+           0.6518706702670911,
+           0.6021553759725325,
+           0.5577189326808671,
+           0.519269853914111,
+           0.4873742359293391,
+           0.46244461144597077,
+           0.44473236031112323,
+           0.43432383728763135,
+           0.43114028810153776,
+           0.43494153434740657,
+           0.44533331802948556,
+           0.4617781096032925,
+           0.48360910148981406,
+           0.5100470341511254,
+           0.5402194357545732,
+           0.5731818008058303,
+           0.6079401892332439,
+           0.6434746963002665,
+           0.6787632261352307,
+           0.7128049979908122,
+           0.7446432246273753,
+           0.7733864261596403,
+           0.7982278796826676,
+           0.8184627540484214,
+           0.8335025390499419,
+           0.8428864474722603,
+           0.8462895452475498,
+           0.8435274473818195,
+           0.8345575033422539,
+           0.8194764830635711,
+           0.7985148614734213,
+           0.7720278832986934,
+           0.7404836688208459,
+           0.7044486932513425,
+           0.6645710357262933,
+           0.6215618470208337,
+           0.5761755266653065,
+           0.5291891292036792,
+           0.48138153518123344,
+           0.4335129247264104,
+           0.3863050802834355,
+           0.34042302048072687,
+           0.29645842993918115,
+           0.25491530100299464,
+           0.2161981441726103,
+           0.18060305595200013,
+           0.14831185762809793,
+           0.11938943809287196,
+           0.09378435024052512,
+           0.07133262584328035,
+           0.051764690272986656,
+           0.034715178106373513,
+           0.01973537556102319,
+           0.006307947755177843,
+           -0.006136450315152621,
+           -0.018201128940106993,
+           -0.030504372030846705,
+           -0.043660010306418646,
+           -0.05825808251956869,
+           -0.07484610597578792,
+           -0.09391146227376117,
+           -0.11586537585856058,
+           -0.1410289223421378,
+           -0.1696214516298503,
+           -0.20175174900278975,
+           -0.2374121870014908,
+           -0.2764760440084222,
+           -0.3186980837748756,
+           -0.3637184058430215,
+           -0.41106949200600174,
+           -0.4601862907730846,
+           -0.5104191023707609,
+           -0.5610489531306314,
+           -0.6113050820662271,
+           -0.6603841057102977,
+           -0.7074703813275353,
+           -0.7517570546234619,
+           -0.7924672569292512,
+           -0.8288749091252482,
+           -0.8603245955086248,
+           -0.8862499903077593,
+           -0.9061903521529279,
+           -0.9198046467570922,
+           -0.9268829142592264,
+           -0.9273545637702251,
+           -0.9212933520225632,
+           -0.9089188838346574,
+           -0.8905945573694352,
+           -0.8668219647890553,
+           -0.838231846715277,
+           -0.805571784719863,
+           -0.7696908977579674,
+           -0.7315218839837531,
+           -0.6920608168635191,
+           -0.6523451622347719,
+           -0.6134305294946318,
+           -0.5763667042559447,
+           -0.5421735307064631,
+           -0.511817218992698,
+           -0.48618764601245124,
+           -0.4660771971707803,
+           -0.45216166240819206,
+           -0.4449836529527549,
+           -0.4449389468973521,
+           -0.4522661032612724,
+           -0.46703960731375477,
+           -0.4891667264776974,
+           -0.518388168119999,
+           -0.554282540110612,
+           -0.5962745243965937,
+           -0.6436465851987886,
+           -0.6955539489586398,
+           -0.7510425149025646,
+           -0.8090692849610941,
+           -0.8685248414922061,
+           -0.928257352284174,
+           -0.9870975458486959,
+           -1.0438840769486146,
+           -1.0974886931981165,
+           -1.1468406186461155,
+           -1.1909495893780855,
+           -1.2289270088768687,
+           -1.2600047363646254,
+           -1.2835510784907758,
+           -1.2990836221329376,
+           -1.3062786220889029,
+           -1.3049767401966728,
+           -1.295185019902372,
+           -1.2770750703647036,
+           -1.2509775246404986,
+           -1.2173729251333911,
+           -1.17687927414853,
+           -1.1302365660231648,
+           -1.078288687989652,
+           -1.0219631379659484,
+           -0.962249057390558,
+           -0.9001741148321722,
+           -0.8367808005214121,
+           -0.773102702612275,
+           -0.7101413326632544,
+           -0.6488440506566956,
+           -0.5900836093148379,
+           -0.5346397943171973,
+           -0.48318358238033876,
+           -0.43626417441310766,
+           -0.3942991877403197,
+           -0.3575682115339434,
+           -0.3262098451013673,
+           -0.3002222516638105,
+           -0.2794671728810471,
+           -0.26367726381168266,
+           -0.2524665263617855,
+           -0.24534354358675872,
+           -0.24172714933746464,
+           -0.2409641093484576,
+           -0.24234834238073935,
+           -0.24514117460549653,
+           -0.2485920978973686,
+           -0.2519594936202285,
+           -0.2545307880231237,
+           -0.2556415233654144,
+           -0.2546928598685454,
+           -0.25116706673310635,
+           -0.24464061464654915,
+           -0.23479454604673172,
+           -0.22142187126669013,
+           -0.2044318167355383,
+           -0.1838508336644611,
+           -0.15982036001812983,
+           -0.1325914129219556,
+           -0.1025161708488235,
+           -0.07003678288586611,
+           -0.035671714131325784,
+           -3.3651968076615246e-16
+          ],
+          [
+           0,
+           0.03547750111680663,
+           0.07070615230775851,
+           0.10505610199489504,
+           0.13792145007855863,
+           0.16873846398930065,
+           0.1970026768800167,
+           0.22228440509087383,
+           0.2442422624857337,
+           0.26263430062570964,
+           0.2773264647197681,
+           0.28829812433757385,
+           0.29564451324522306,
+           0.29957599252824246,
+           0.30041413338299666,
+           0.298584698509083,
+           0.2946076818320845,
+           0.2890846432801639,
+           0.28268364657396405,
+           0.2761221716533785,
+           0.27014842783035065,
+           0.26552153762544306,
+           0.2629910933822472,
+           0.263276608314603,
+           0.267047390097257,
+           0.2749033582583387,
+           0.2873573066017625,
+           0.3048190791390657,
+           0.32758208332175776,
+           0.35581250881535614,
+           0.3895415549966796,
+           0.4286608973786441,
+           0.4729215440645593,
+           0.5219361500562637,
+           0.575184771845092,
+           0.6320239593168634,
+           0.6916989987218586,
+           0.7533590413704574,
+           0.8160747797878845,
+           0.8788582681220777,
+           0.9406844282781331,
+           1.0005137389474679,
+           1.0573155725369978,
+           1.1100916258124796,
+           1.1578988843615554,
+           1.199871568934959,
+           1.2352415331812696,
+           1.2633566167609738,
+           1.2836965044974011,
+           1.2958856999817203,
+           1.2997032895083884,
+           1.2950892477474631,
+           1.282147118331607,
+           1.2611429885632366,
+           1.2325007656390226,
+           1.1967938499972652,
+           1.154733387468264,
+           1.1071533637489286,
+           1.0549928803325561,
+           0.9992760185564846,
+           0.941089756234424,
+           0.8815604480043154,
+           0.8218294149065681,
+           0.7630282099717681,
+           0.7062541342228014,
+           0.6525465712990063,
+           0.6028646890430711,
+           0.5580670233429594,
+           0.5188934141019771,
+           0.4859497065331524,
+           0.45969556442759335,
+           0.44043566725927463,
+           0.4283144817901927,
+           0.42331471321493536,
+           0.42525945292378997,
+           0.43381795181493343,
+           0.44851486189742407,
+           0.46874270679527685,
+           0.49377726568402724,
+           0.522795487008584,
+           0.5548954896917891,
+           0.5891181618567382,
+           0.6244698314907159,
+           0.6599454608134353,
+           0.6945518068959895,
+           0.7273299954967164,
+           0.75737697298647,
+           0.783865332147128,
+           0.8060610507422336,
+           0.8233387359766154,
+           0.8351940319099282,
+           0.841252918957183,
+           0.8412777129900113,
+           0.8351696542860705,
+           0.8229680615976595,
+           0.8048461118092529,
+           0.7811033889127523,
+           0.7521554252873244,
+           0.7185205315702924,
+           0.6808042769419083,
+           0.639682037812464,
+           0.5958800783244055,
+           0.5501556596651328,
+           0.5032766961257771,
+           0.45600148365251686,
+           0.4090590211640974,
+           0.3631304263284732,
+           0.31883191630691676,
+           0.27669978100417975,
+           0.23717772272049226,
+           0.20060687316353074,
+           0.167218728154649,
+           0.13713116385308008,
+           0.11034761786910689,
+           0.08675943628340602,
+           0.06615130542137045,
+           0.048209607327750946,
+           0.03253346226887994,
+           0.01864815216807025,
+           0.006020557408037438,
+           -0.005923812535305347,
+           -0.017782655318332063,
+           -0.030158068806353973,
+           -0.04363760770033023,
+           -0.05877571410236869,
+           -0.07607602298645301,
+           -0.09597502124186015,
+           -0.11882750434112312,
+           -0.14489422862275608,
+           -0.17433210083070463,
+           -0.2071871813370021,
+           -0.2433907050350725,
+           -0.28275824605564565,
+           -0.3249920711900572,
+           -0.3696866442599931,
+           -0.4163371617389547,
+           -0.46435092078399665,
+           -0.5130612464846834,
+           -0.5617436374703055,
+           -0.6096337297617324,
+           -0.655946629428231,
+           -0.6998971264831119,
+           -0.7407202765173582,
+           -0.7776918235163649,
+           -0.8101479374988025,
+           -0.8375037540951198,
+           -0.859270229650624,
+           -0.8750688642733805,
+           -0.8846438955192153,
+           -0.8878716258959182,
+           -0.884766616600021,
+           -0.8754845561745672,
+           -0.860321694218138,
+           -0.8397108148742238,
+           -0.8142138104928331,
+           -0.784511000458818,
+           -0.7513874216209528,
+           -0.7157163930034011,
+           -0.6784407266318386,
+           -0.6405520166269447,
+           -0.603068488689685,
+           -0.5670119304601352,
+           -0.5333842489930797,
+           -0.5031442140871288,
+           -0.47718494508374004,
+           -0.4563126840072338,
+           -0.44122736987182576,
+           -0.4325054882901295,
+           -0.43058561814509644,
+           -0.43575703428895146,
+           -0.44815165352128367,
+           -0.4677395322086293,
+           -0.49432803975272704,
+           -0.5275647447391478,
+           -0.5669439621284719,
+           -0.6118168224443054,
+           -0.6614046396976416,
+           -0.7148152758207087,
+           -0.7710621275935642,
+           -0.8290852991869126,
+           -0.8877744710507035,
+           -0.9459929352300919,
+           -1.0026022392814553,
+           -1.056486866472203,
+           -1.1065783792324475,
+           -1.151878465899342,
+           -1.1914803573345356,
+           -1.2245881193502122,
+           -1.2505333780846672,
+           -1.268789097270007,
+           -1.2789800972188803,
+           -1.2808900835899966,
+           -1.274465037660204,
+           -1.2598129068897854,
+           -1.2371996228919744,
+           -1.2070415613533594,
+           -1.1698946428693844,
+           -1.1264403530057145,
+           -1.0774690322465428,
+           -1.0238608500941828,
+           -0.9665649309075905,
+           -0.9065771408326301,
+           -0.844917074392772,
+           -0.7826047952942953,
+           -0.7206378884009836,
+           -0.6599693686309687,
+           -0.6014869680394208,
+           -0.5459942852183716,
+           -0.4941942323234784,
+           -0.44667515576755207,
+           -0.4038999383982509,
+           -0.3661983155166939,
+           -0.3337625562842726,
+           -0.30664657792428096,
+           -0.28476847474846884,
+           -0.2679163595478318,
+           -0.255757333376301,
+           -0.24784932324117306,
+           -0.24365545758211724,
+           -0.2425605883828717,
+           -0.24388951780991333,
+           -0.24692644764957958,
+           -0.2509351424732136,
+           -0.2551792830444548,
+           -0.2589424853150563,
+           -0.2615474724254311,
+           -0.26237391209194455,
+           -0.26087446896162114,
+           -0.25658866997772745,
+           -0.24915423927761698,
+           -0.23831562613918106,
+           -0.2239295232946118,
+           -0.20596725166231658,
+           -0.1845139692103084,
+           -0.159764744187222,
+           -0.13201761425057926,
+           -0.1016638310296488,
+           -0.0691755624102802,
+           -0.03509139048347972,
+           -3.297132057972448e-16
+          ],
+          [
+           0,
+           0.034493039556088644,
+           0.06846754445904861,
+           0.10132069210514436,
+           0.13248262181418743,
+           0.1614336139993825,
+           0.18771992240548205,
+           0.2109678300000346,
+           0.23089554474668486,
+           0.24732260704935058,
+           0.2601765447308469,
+           0.2694965823829159,
+           0.27543428800531383,
+           0.2782511191180765,
+           0.278312910979551,
+           0.27608142913750555,
+           0.2721031852647347,
+           0.2669957871367009,
+           0.2614321588677788,
+           0.25612302446966795,
+           0.2517980949716101,
+           0.2491864355309825,
+           0.24899651322189337,
+           0.25189643787312177,
+           0.25849490710351497,
+           0.26932335256366696,
+           0.28481975765141726,
+           0.30531457825531066,
+           0.3310191483249956,
+           0.36201689247880087,
+           0.39825759989259474,
+           0.4395549390389277,
+           0.4855873133006923,
+           0.5359020750339332,
+           0.5899230323415547,
+           0.6469611007112457,
+           0.7062278728094815,
+           0.7668518060756411,
+           0.8278966611677437,
+           0.8883817664451493,
+           0.9473036359923442,
+           1.0036584324013154,
+           1.0564647415685944,
+           1.1047861157546284,
+           1.1477528434070676,
+           1.1845824197484622,
+           1.2145982205287216,
+           1.2372459219809573,
+           1.252107261930782,
+           1.2589107989496047,
+           1.2575393969188768,
+           1.2480342396795887,
+           1.2305952627041639,
+           1.2055779739466748,
+           1.1734867221273593,
+           1.1349645555901764,
+           1.0907798964666118,
+           1.0418103311930371,
+           0.9890238875980777,
+           0.9334582291101494,
+           0.8761982466582674,
+           0.818352567328041,
+           0.7610295248480802,
+           0.7053131498835359,
+           0.6522397375879959,
+           0.6027755359256612,
+           0.5577960712645008,
+           0.5180675883192477,
+           0.4842310306561062,
+           0.4567889269035344,
+           0.4360954780395642,
+           0.42235006435191524,
+           0.41559430876891434,
+           0.41571274823719734,
+           0.42243707875092684,
+           0.43535385461516796,
+           0.4539154406229949,
+           0.4774539390327727,
+           0.5051977434115927,
+           0.5362903102519182,
+           0.5698106882446567,
+           0.6047953054253895,
+           0.6402604870420405,
+           0.6752251625590114,
+           0.7087332190315991,
+           0.7398749701462757,
+           0.7678072351909081,
+           0.7917715594412442,
+           0.8111101559717243,
+           0.8252792074887082,
+           0.8338592339657938,
+           0.8365623059474211,
+           0.8332359625257232,
+           0.8238637752120567,
+           0.8085625821734045,
+           0.7875764995179169,
+           0.7612678954570464,
+           0.7301055872886758,
+           0.6946505884101748,
+           0.6555397913310842,
+           0.6134680214758801,
+           0.5691689342625913,
+           0.5233952536074591,
+           0.4768988630357852,
+           0.4304112606877268,
+           0.3846248767316759,
+           0.3401757263953842,
+           0.297627834667442,
+           0.25745982067576556,
+           0.22005397205312432,
+           0.18568807372999455,
+           0.15453018323236356,
+           0.1266364675470087,
+           0.10195213690418625,
+           0.08031543043749655,
+           0.06146452964760993,
+           0.04504719991892378,
+           0.03063288992789939,
+           0.01772695541672195,
+           0.005786619085052577,
+           -0.005761766343455289,
+           -0.017504618367200065,
+           -0.030022676298500993,
+           -0.043872701238907595,
+           -0.05956981771094423,
+           -0.07757097378004542,
+           -0.09825996780035218,
+           -0.121934449679963,
+           -0.14879525379908623,
+           -0.17893836070780972,
+           -0.21234971699224856,
+           -0.24890306893772168,
+           -0.28836088769759777,
+           -0.330378383565476,
+           -0.3745105266723223,
+           -0.4202219130220327,
+           -0.4668992402266922,
+           -0.5138660885009905,
+           -0.5603996411762293,
+           -0.6057489267649708,
+           -0.6491541227894639,
+           -0.6898664312634604,
+           -0.7271680176844347,
+           -0.7603915001417852,
+           -0.7889384828472028,
+           -0.8122966488931377,
+           -0.8300549598708494,
+           -0.8419165543482836,
+           -0.8477089920475388,
+           -0.8473915545355278,
+           -0.8410593847826149,
+           -0.8289443252930272,
+           -0.8114123957599236,
+           -0.7889579343374807,
+           -0.7621945095914852,
+           -0.7318427909268288,
+           -0.6987156417844204,
+           -0.6637007702410818,
+           -0.6277413340721985,
+           -0.5918149502784348,
+           -0.5569116011964602,
+           -0.5240109595359089,
+           -0.49405967222885044,
+           -0.46794914737400234,
+           -0.44649437965917566,
+           -0.43041432763323095,
+           -0.42031432157786885,
+           -0.41667093431643026,
+           -0.4198196901993646,
+           -0.42994592109718566,
+           -0.4470790041154037,
+           -0.47109013571790515,
+           -0.5016937129489817,
+           -0.538452306523178,
+           -0.5807851247992635,
+           -0.6279797841612973,
+           -0.6792071221337469,
+           -0.7335387165930708,
+           -0.7899667094884971,
+           -0.8474254781371929,
+           -0.9048146527677874,
+           -0.9610229466363034,
+           -1.0149522455219941,
+           -1.0655413972038426,
+           -1.111789148773688,
+           -1.1527757001805947,
+           -1.1876823757200599,
+           -1.2158089604653712,
+           -1.2365883047779183,
+           -1.2495978656554054,
+           -1.2545679271762245,
+           -1.2513863218783055,
+           -1.2400995586271546,
+           -1.2209103483368142,
+           -1.194171604716269,
+           -1.1603770809317524,
+           -1.1201488826658628,
+           -1.0742221715845512,
+           -1.0234274389117122,
+           -0.9686707850720387,
+           -0.9109126868442623,
+           -0.8511457670836499,
+           -0.7903721030338109,
+           -0.7295806170747655,
+           -0.6697250882925504,
+           -0.611703304678735,
+           -0.5563378445722876,
+           -0.5043589329472842,
+           -0.4563897644243308,
+           -0.4129346217994866,
+           -0.3743700480284516,
+           -0.34093925275110504,
+           -0.3127498535117305,
+           -0.28977496883973275,
+           -0.2718575973668317,
+           -0.2587181362277158,
+           -0.2499648151239102,
+           -0.2451067515217531,
+           -0.24356926924908168,
+           -0.2447110688001235,
+           -0.2478427942689669,
+           -0.2522465100575994,
+           -0.25719558110162044,
+           -0.2619744437719583,
+           -0.2658977609696315,
+           -0.2683284740348256,
+           -0.2686942954245167,
+           -0.266502228853282,
+           -0.2613507566338714,
+           -0.25293939593571746,
+           -0.24107539501703495,
+           -0.22567741541342873,
+           -0.20677612467956194,
+           -0.18451170458647678,
+           -0.15912835964215094,
+           -0.1309659884038508,
+           -0.10044925332657541,
+           -0.06807435199169803,
+           -0.03439385179009256,
+           -3.218590316701881e-16
+          ],
+          [
+           0,
+           0.033411284279382884,
+           0.06605347424679822,
+           0.0973551431466901,
+           0.1267860399059188,
+           0.153873117338393,
+           0.17821500960062325,
+           0.19949456539331006,
+           0.21748909350622841,
+           0.23207803629082357,
+           0.24324785302830973,
+           0.2510939672645524,
+           0.2558197081850921,
+           0.2577322540829427,
+           0.2572356639551714,
+           0.25482115927622606,
+           0.2510548901081695,
+           0.24656348608752013,
+           0.2420177517838014,
+           0.2381149159486307,
+           0.2355598839805128,
+           0.23504597148795406,
+           0.23723561339090946,
+           0.2427415471062122,
+           0.2521089598758663,
+           0.2657990693923186,
+           0.28417457403756585,
+           0.3074873650680816,
+           0.33586883901023606,
+           0.3693230857003969,
+           0.4077231573510981,
+           0.4508105484740145,
+           0.4981979373072691,
+           0.5493751585389531,
+           0.6037182965967391,
+           0.6605017105876516,
+           0.7189127280714288,
+           0.778068677082575,
+           0.8370358658793924,
+           0.8948500693018351,
+           0.9505380406449664,
+           1.0031395396218488,
+           1.0517293510341417,
+           1.0954387656212077,
+           1.1334760043346264,
+           1.1651450897813953,
+           1.1898627032784042,
+           1.2071726120440096,
+           1.2167573074188547,
+           1.2184465603017134,
+           1.2122226726294691,
+           1.1982222819627624,
+           1.1767346581597797,
+           1.1481965147365176,
+           1.1131834407849013,
+           1.07239814021877,
+           1.0266557416664563,
+           0.9768665126569257,
+           0.9240163741344067,
+           0.8691456642578583,
+           0.81332664260114,
+           0.7576402562349156,
+           0.7031527069982456,
+           0.6508923641192683,
+           0.6018275581007866,
+           0.5568457706488765,
+           0.5167347019074443,
+           0.48216565118824656,
+           0.45367959185653267,
+           0.4316762564045075,
+           0.41640647559797284,
+           0.4079679376783207,
+           0.40630445184482605,
+           0.4112087166258838,
+           0.42232851031106183,
+           0.4391761393905645,
+           0.4611409039103028,
+           0.4875042676693605,
+           0.517457357981248,
+           0.5501203658165098,
+           0.58456337383685,
+           0.6198281081523526,
+           0.6549500903283348,
+           0.6889806596761918,
+           0.7210083423060862,
+           0.7501790626031303,
+           0.7757147242034794,
+           0.7969297303829671,
+           0.8132450669389334,
+           0.8241996328033991,
+           0.8294585732112266,
+           0.8288184455187995,
+           0.8222091268486846,
+           0.8096924536553088,
+           0.791457664056437,
+           0.7678137923545286,
+           0.7391792396386323,
+           0.7060688128757368,
+           0.669078585786751,
+           0.6288689865664674,
+           0.586146558889356,
+           0.5416448726453894,
+           0.49610507875993065,
+           0.45025660785960286,
+           0.40479850535554013,
+           0.36038187594510823,
+           0.31759387911045545,
+           0.27694367474018855,
+           0.23885066561667123,
+           0.20363532254020913,
+           0.17151280986028722,
+           0.14258955588412559,
+           0.11686283589578045,
+           0.09422335729014661,
+           0.07446075858566868,
+           0.057271858792965584,
+           0.04227142268568106,
+           0.029005142734977632,
+           0.016964481464399547,
+           0.0056029701944080145,
+           -0.005646477220114803,
+           -0.017353703059587756,
+           -0.03007337820338363,
+           -0.044327491392024194,
+           -0.06058872750197099,
+           -0.07926518412084459,
+           -0.10068684122766564,
+           -0.12509415361251533,
+           -0.15262908095254582,
+           -0.18332880757730638,
+           -0.21712233449337262,
+           -0.25383005195050806,
+           -0.2931663235964453,
+           -0.33474503503820324,
+           -0.37808798238513674,
+           -0.4226359020507806,
+           -0.4677618736234873,
+           -0.5127867647476253,
+           -0.5569963322923015,
+           -0.5996595490241619,
+           -0.6400476907071349,
+           -0.6774536959192297,
+           -0.7112113005079087,
+           -0.7407134507984674,
+           -0.765429514407218,
+           -0.7849208344622662,
+           -0.7988542115621254,
+           -0.8070129469784244,
+           -0.8093051392377135,
+           -0.8057689928642667,
+           -0.7965749710931724,
+           -0.7820247019703986,
+           -0.762546627525248,
+           -0.7386884666414408,
+           -0.7111066418553583,
+           -0.6805528965918966,
+           -0.6478584004057837,
+           -0.6139157038505967,
+           -0.5796589600397974,
+           -0.5460428753947326,
+           -0.5140208863391106,
+           -0.48452308091730906,
+           -0.45843439390000207,
+           -0.43657360062108047,
+           -0.4196736186087557,
+           -0.40836359739230604,
+           -0.40315323635444705,
+           -0.404419719120676,
+           -0.4123975919630984,
+           -0.4271718445185483,
+           -0.44867437545340344,
+           -0.4766839453866814,
+           -0.5108296363618267,
+           -0.5505977534580468,
+           -0.595342021794933,
+           -0.6442968532193613,
+           -0.6965933833001006,
+           -0.7512779126940378,
+           -0.8073323291164292,
+           -0.8636960384613643,
+           -0.9192888972451329,
+           -0.9730346143753271,
+           -1.023884078874848,
+           -1.0708380718914157,
+           -1.1129688360594006,
+           -1.1494400026914262,
+           -1.1795244166925514,
+           -1.2026194495460945,
+           -1.2182594509835447,
+           -1.2261250585487504,
+           -1.2260491595219924,
+           -1.218019379744919,
+           -1.2021770568276853,
+           -1.1788127390021717,
+           -1.1483583334681602,
+           -1.1113761074530115,
+           -1.068544819441039,
+           -1.0206433253262277,
+           -0.968532062974055,
+           -0.9131328674301867,
+           -0.8554076066188646,
+           -0.7963361529401645,
+           -0.7368942191096387,
+           -0.6780315866039606,
+           -0.6206512422185715,
+           -0.5655899128615672,
+           -0.5136004514636932,
+           -0.4653364787297154,
+           -0.4213396276116709,
+           -0.3820296713059207,
+           -0.34769774292020655,
+           -0.3185027775397366,
+           -0.2944712271720713,
+           -0.2755000179644353,
+           -0.2613626391751907,
+           -0.25171817662134066,
+           -0.24612303161078478,
+           -0.2440450014667499,
+           -0.2448793412541809,
+           -0.24796637960299475,
+           -0.25261022572347624,
+           -0.2580980806827776,
+           -0.2637196543210764,
+           -0.26878619008515686,
+           -0.2726486134845741,
+           -0.2747143454571613,
+           -0.274462358988723,
+           -0.2714561049032637,
+           -0.2653539895999623,
+           -0.25591715220590633,
+           -0.24301435948989436,
+           -0.22662391214018002,
+           -0.20683253373868077,
+           -0.18383129199670142,
+           -0.15790867857376423,
+           -0.12944104714181068,
+           -0.09888067743003756,
+           -0.06674179407333125,
+           -0.0335849216492584,
+           -3.130244867068193e-16
+          ],
+          [
+           0,
+           0.032241565153860195,
+           0.06348456816826081,
+           0.09319280721202114,
+           0.12087861633701416,
+           0.14611764650565728,
+           0.16856191847679558,
+           0.18795079190416936,
+           0.2041195488234885,
+           0.2170053513482178,
+           0.2266504013032714,
+           0.23320220198382002,
+           0.23691089740124902,
+           0.23812374036782138,
+           0.23727681565116493,
+           0.2348842163004054,
+           0.2315249382820544,
+           0.22782781905914418,
+           0.2244548981570313,
+           0.22208362074002808,
+           0.2213883376653243,
+           0.22302157653798171,
+           0.22759556740057024,
+           0.2356645035892278,
+           0.24770800301596807,
+           0.2641162080411471,
+           0.2851769238229236,
+           0.31106514649607614,
+           0.3418352749227271,
+           0.3774162344836543,
+           0.417609670046621,
+           0.4620912896178732,
+           0.5104153621260821,
+           0.5620222942407309,
+           0.6162491340419979,
+           0.6723427756575827,
+           0.7294755705048676,
+           0.786762989240177,
+           0.8432829254682161,
+           0.8980961890446907,
+           0.9502677045138539,
+           0.9988879096924337,
+           1.0430938411851423,
+           1.082089397934981,
+           1.1151642907046215,
+           1.1417112142763648,
+           1.1612408194712338,
+           1.1733941128639438,
+           1.1779519720914724,
+           1.1748415324709696,
+           1.1641392746157633,
+           1.1460707210705292,
+           1.1210067307727878,
+           1.0894564614195548,
+           1.052057149592538,
+           1.0095609348246846,
+           0.9628190248094329,
+           0.9127635629246484,
+           0.8603876146000847,
+           0.8067237344444547,
+           0.7528216103534637,
+           0.6997253032018781,
+           0.6484506106309805,
+           0.5999630806330769,
+           0.5551571851736603,
+           0.5148371363558462,
+           0.4796997882976061,
+           0.45032001792057363,
+           0.42713891846067664,
+           0.41045507215584,
+           0.4004190948897823,
+           0.3970315673717097,
+           0.4001443866177441,
+           0.4094654900413766,
+           0.4245668243414196,
+           0.44489535454601886,
+           0.46978683689663864,
+           0.4984820144738997,
+           0.5301448381439181,
+           0.563882268895151,
+           0.5987651820549994,
+           0.6338498700649318,
+           0.6681996290047922,
+           0.7009059151391513,
+           0.7311085713490099,
+           0.7580146490414543,
+           0.7809153883296822,
+           0.7992009669970316,
+           0.8123726857940511,
+           0.8200523225331793,
+           0.8219884586153087,
+           0.8180596572696719,
+           0.8082744510295192,
+           0.7927681748574462,
+           0.7717967589207925,
+           0.7457276693808891,
+           0.7150282548661063,
+           0.6802518188434129,
+           0.6420217923541658,
+           0.6010144262145006,
+           0.5579404557187158,
+           0.513526213313817,
+           0.4684946751121612,
+           0.423546925255083,
+           0.37934450811821163,
+           0.3364931125472983,
+           0.2955279954139228,
+           0.25690150474176016,
+           0.22097300668681188,
+           0.18800145719094905,
+           0.15814078978489013,
+           0.13143821755665308,
+           0.10783547158755614,
+           0.08717292210711844,
+           0.06919645415353394,
+           0.05356689852870151,
+           0.03987175309761788,
+           0.027638870658859636,
+           0.016351739188057823,
+           0.005465939499315073,
+           -0.00557366469413017,
+           -0.017315467953391173,
+           -0.030283865853831752,
+           -0.04496266424001251,
+           -0.06177960261608979,
+           -0.08109241045809454,
+           -0.10317677562363216,
+           -0.1282165546473958,
+           -0.1562964967948374,
+           -0.18739768876423932,
+           -0.22139585652115845,
+           -0.2580625866983634,
+           -0.29706945417199104,
+           -0.33799496675011714,
+           -0.3803341643010038,
+           -0.4235106399731255,
+           -0.4668906871892066,
+           -0.5097992194625908,
+           -0.5515370622350517,
+           -0.5913991781009573,
+           -0.6286933599445298,
+           -0.6627589113816968,
+           -0.6929848308801622,
+           -0.7188270251427495,
+           -0.7398240985852822,
+           -0.755611298525316,
+           -0.7659322392362624,
+           -0.7706480812566272,
+           -0.7697439039756006,
+           -0.7633320780308852,
+           -0.7516525177642045,
+           -0.7350697710628505,
+           -0.7140669824621575,
+           -0.6892368434434039,
+           -0.66126971949144,
+           -0.6309392147893222,
+           -0.5990855006392382,
+           -0.566596791173372,
+           -0.5343893982062787,
+           -0.5033868349576636,
+           -0.4744984648718908,
+           -0.44859820618835616,
+           -0.426503804882042,
+           -0.40895717801031933,
+           -0.39660630659417484,
+           -0.3899891224575609,
+           -0.3895197877675769,
+           -0.39547771045259006,
+           -0.407999574562208,
+           -0.42707459352203375,
+           -0.4525431178513962,
+           -0.484098649110198,
+           -0.5212932305644016,
+           -0.563546104290158,
+           -0.6101554461454279,
+           -0.6603129161381833,
+           -0.7131206940186153,
+           -0.7676106100759817,
+           -0.8227649305940546,
+           -0.8775383174505573,
+           -0.9308804529155121,
+           -0.981758804508866,
+           -1.0291810012177567,
+           -1.0722163015372392,
+           -1.1100156554634315,
+           -1.1418298962062094,
+           -1.1670256421788285,
+           -1.1850985446701552,
+           -1.19568358017161,
+           -1.1985621570632183,
+           -1.1936658825339195,
+           -1.1810769153618237,
+           -1.1610249115649918,
+           -1.133880650969382,
+           -1.100146511454879,
+           -1.0604440321192519,
+           -1.0154988750360163,
+           -0.9661235560186237,
+           -0.913198366374705,
+           -0.8576509488019263,
+           -0.8004350203606211,
+           -0.7425087531580448,
+           -0.6848133285942072,
+           -0.6282521736560833,
+           -0.5736713680222686,
+           -0.521841679174344,
+           -0.47344264011561854,
+           -0.42904903175410325,
+           -0.3891200708391093,
+           -0.35399153608503775,
+           -0.3238709914778505,
+           -0.29883618857559835,
+           -0.2788366508036341,
+           -0.2636983642632232,
+           -0.25313142336194144,
+           -0.24674040751753518,
+           -0.24403719905852467,
+           -0.24445589386788968,
+           -0.24736940672270713,
+           -0.2521073338777109,
+           -0.2579746071732931,
+           -0.26427045748761635,
+           -0.270307201071796,
+           -0.27542837027510864,
+           -0.2790257301466161,
+           -0.2805547538534877,
+           -0.27954817196171966,
+           -0.2756272622940454,
+           -0.26851060698709867,
+           -0.2580201099859511,
+           -0.24408413984356836,
+           -0.22673773751721488,
+           -0.20611990497745133,
+           -0.18246806594201348,
+           -0.15610986300872598,
+           -0.12745252404673246,
+           -0.09697009318366084,
+           -0.06518887652313977,
+           -0.03267149846217078,
+           -3.03285825180752e-16
+          ],
+          [
+           0,
+           0.030993908897351246,
+           0.06078253407901817,
+           0.08886816203903239,
+           0.1148080768349521,
+           0.13822801615840616,
+           0.15883374911697237,
+           0.17642045937343948,
+           0.19087967408278725,
+           0.20220354260240328,
+           0.21048633762086205,
+           0.2159231234183342,
+           0.21880560961367418,
+           0.2195152821044703,
+           0.2185139741072107,
+           0.21633210744763837,
+           0.21355489582601103,
+           0.21080685611829264,
+           0.2087350194818757,
+           0.2079912699374909,
+           0.209214263266061,
+           0.21301139282676074,
+           0.21994127089162724,
+           0.23049718421845375,
+           0.24509196106018938,
+           0.26404465414058725,
+           0.28756940109722756,
+           0.3157667715498843,
+           0.3486178495750571,
+           0.385981233440411,
+           0.4275930626265727,
+           0.47307010721492093,
+           0.5219158785071288,
+           0.5735296441595255,
+           0.6272181580457071,
+           0.6822098463290193,
+           0.7376711285536912,
+           0.7927244975243072,
+           0.8464679357268041,
+           0.8979952102187962,
+           0.9464165632013667,
+           0.9908793025241857,
+           1.0305877955273812,
+           1.0648223809447637,
+           1.0929567368412674,
+           1.1144732771954697,
+           1.1289761949465158,
+           1.1362018240224894,
+           1.1360260557373385,
+           1.1284686144656995,
+           1.113694071993006,
+           1.092009557581229,
+           1.0638591996973485,
+           1.029815413597654,
+           0.9905672246353828,
+           0.9469058884122548,
+           0.8997081339827669,
+           0.8499174136500808,
+           0.7985235910588766,
+           0.7465415371125391,
+           0.694989129790706,
+           0.644865168565663,
+           0.5971277164511456,
+           0.5526733727043173,
+           0.5123179570830726,
+           0.4767790528742571,
+           0.4466608114756332,
+           0.42244136721916137,
+           0.40446314868616834,
+           0.39292630350994806,
+           0.3878853792784919,
+           0.38924932545384905,
+           0.3967848021093469,
+           0.4101227026789586,
+           0.4287677217275009,
+           0.45211072683770465,
+           0.47944362781524064,
+           0.5099763781303033,
+           0.542855694250327,
+           0.5771850394552918,
+           0.6120453907950334,
+           0.6465162917023215,
+           0.6796966887803203,
+           0.7107250595037382,
+           0.7387983577731867,
+           0.763189335912283,
+           0.7832618439850639,
+           0.7984837591657872,
+           0.8084372580084611,
+           0.8128262113326352,
+           0.8114805533951268,
+           0.8043575522618385,
+           0.7915399849604089,
+           0.7732312971821922,
+           0.7497479011268331,
+           0.7215088347228483,
+           0.6890230691996778,
+           0.6528748082675456,
+           0.6137071696069496,
+           0.5722046768283576,
+           0.5290750166346134,
+           0.48503053097640847,
+           0.4407699171964439,
+           0.3969606004681245,
+           0.3542222225044702,
+           0.3131116590874686,
+           0.27410993726836624,
+           0.23761137219222203,
+           0.20391518471026343,
+           0.1732197957615531,
+           0.14561992358918027,
+           0.12110653697979991,
+           0.09956964372449291,
+           0.08080382026486306,
+           0.06451631786060563,
+           0.05033751437547623,
+           0.037833420597409254,
+           0.026519897401074483,
+           0.0158781963513394,
+           0.005371402632720718,
+           -0.005538663680502056,
+           -0.017374543453270327,
+           -0.030626686610846398,
+           -0.045737895806753956,
+           -0.06308908556670116,
+           -0.08298674271595236,
+           -0.10565242984318,
+           -0.13121462068048853,
+           -0.15970309592362236,
+           -0.19104606170397537,
+           -0.2250700823317558,
+           -0.26150284584324024,
+           -0.2999787071546083,
+           -0.34004688111865833,
+           -0.38118208833793027,
+           -0.42279739197317284,
+           -0.46425890564476213,
+           -0.5049020023417524,
+           -0.5440486133157365,
+           -0.5810251753015694,
+           -0.6151807648743964,
+           -0.6459049508452314,
+           -0.6726448995477937,
+           -0.6949212836131392,
+           -0.7123425720057711,
+           -0.7246173170585959,
+           -0.7315641020762418,
+           -0.7331188696102079,
+           -0.7293394143585008,
+           -0.7204068942345041,
+           -0.7066242867659339,
+           -0.6884117938013905,
+           -0.6662992736373073,
+           -0.6409158542372412,
+           -0.612976952339197,
+           -0.583268989156152,
+           -0.5526321524173284,
+           -0.5219416051864303,
+           -0.4920875829453555,
+           -0.4639548508009402,
+           -0.4384020115734785,
+           -0.41624116245649684,
+           -0.3982183926895596,
+           -0.38499559735253736,
+           -0.37713405336179145,
+           -0.37508016370650005,
+           -0.37915372585999524,
+           -0.3895390213393157,
+           -0.40627895698900646,
+           -0.4292724163408297,
+           -0.45827490310342045,
+           -0.4929024803218639,
+           -0.532638929930265,
+           -0.576845980224476,
+           -0.6247763750930825,
+           -0.6755894904649379,
+           -0.7283691420344964,
+           -0.7821431754158227,
+           -0.8359043867498964,
+           -0.8886322895054095,
+           -0.9393152225645399,
+           -0.9869722861801523,
+           -1.0306745962416515,
+           -1.0695653634016298,
+           -1.1028783316038535,
+           -1.129954149732797,
+           -1.1502542995202338,
+           -1.1633722612895758,
+           -1.1690416651667372,
+           -1.167141247425753,
+           -1.157696507910059,
+           -1.140878043116455,
+           -1.1169966086313263,
+           -1.0864950422417656,
+           -1.0499372533194615,
+           -1.0079945531891015,
+           -0.9614296634705057,
+           -0.9110787933198218,
+           -0.8578322207916881,
+           -0.8026138471416792,
+           -0.7463602149916455,
+           -0.6899994913780982,
+           -0.6344309145807007,
+           -0.5805051893696651,
+           -0.5290062893017781,
+           -0.48063508760780993,
+           -0.43599519099385065,
+           -0.3955812945178791,
+           -0.35977031201144405,
+           -0.3288154668880675,
+           -0.3028434543514938,
+           -0.28185470982489585,
+           -0.26572674175758354,
+           -0.2542204117270796,
+           -0.2469889728002271,
+           -0.24358961022040643,
+           -0.24349716829229084,
+           -0.24611969531403774,
+           -0.25081539582610696,
+           -0.25691054733487906,
+           -0.26371791779393483,
+           -0.27055521097057766,
+           -0.2767630695809661,
+           -0.2817221806376278,
+           -0.28486905341684265,
+           -0.2857100771354194,
+           -0.28383351187446526,
+           -0.2789191213075955,
+           -0.2707452179753877,
+           -0.25919295961269034,
+           -0.24424780665921123,
+           -0.2259981247508819,
+           -0.20463098983576924,
+           -0.1804253257172667,
+           -0.15374257247764261,
+           -0.12501514764537414,
+           -0.09473301854237848,
+           -0.06342875255807041,
+           -0.031661450931017715,
+           -2.927271359114701e-16
+          ],
+          [
+           0,
+           0.029678905092289928,
+           0.057969880446891386,
+           0.08441637810634095,
+           0.1086223780556897,
+           0.1302644603167274,
+           0.14910187632086916,
+           0.16498434341510737,
+           0.17785734537521855,
+           0.18776478647439312,
+           0.19484891534741344,
+           0.19934750586191924,
+           0.20158835366181077,
+           0.20198121717232484,
+           0.20100739887222877,
+           0.19920722484255518,
+           0.19716573640893773,
+           0.19549695568017664,
+           0.19482712571798674,
+           0.19577735494637546,
+           0.19894611346907612,
+           0.20489203572540068,
+           0.21411747917676027,
+           0.2270532725638649,
+           0.24404506008032814,
+           0.2653416102213916,
+           0.29108541099742924,
+           0.32130581780056905,
+           0.3559149578395665,
+           0.394706527250545,
+           0.43735754542589445,
+           0.4834330575545498,
+           0.5323937026615172,
+           0.5836059924085163,
+           0.6363550773688645,
+           0.6898597141340798,
+           0.7432890900376284,
+           0.795781113918774,
+           0.8464617424220465,
+           0.8944648828298598,
+           0.938952396095596,
+           0.9791337180455711,
+           1.0142846228276745,
+           1.0437646704875756,
+           1.0670329096467535,
+           1.083661445957364,
+           1.0933465363713037,
+           1.0959169270991977,
+           1.0913392180529682,
+           1.07972010699011,
+           1.0613054407977345,
+           1.0364760775629955,
+           1.0057406394151782,
+           0.9697253107296464,
+           0.9291609073310239,
+           0.8848675080840557,
+           0.8377369991050216,
+           0.7887139313218027,
+           0.7387751330176823,
+           0.6889085493075726,
+           0.640091799469601,
+           0.5932709502210322,
+           0.5493399982056048,
+           0.5091215382632492,
+           0.47334906588718284,
+           0.44265132332273927,
+           0.417539049976142,
+           0.3983944403692732,
+           0.38546354819948847,
+           0.3788518047190211,
+           0.3785227453523778,
+           0.38429996203327227,
+           0.3958722220274768,
+           0.41280161888180283,
+           0.43453454942895725,
+           0.46041524422417973,
+           0.4897015190049223,
+           0.5215823631936191,
+           0.5551969393470124,
+           0.5896545358002373,
+           0.6240549943088953,
+           0.6575091257293479,
+           0.689158629880618,
+           0.7181950505925347,
+           0.743877323166656,
+           0.7655475083831841,
+           0.7826443538402099,
+           0.7947143786350541,
+           0.8014202398056568,
+           0.8025462069833917,
+           0.7980006436719449,
+           0.7878154676714375,
+           0.7721426375751599,
+           0.7512477851371832,
+           0.7255011828440253,
+           0.6953663005106805,
+           0.6613862625779152,
+           0.6241685675994677,
+           0.5843684719632901,
+           0.5426714702119146,
+           0.4997753236920138,
+           0.45637209722512023,
+           0.4131306598886965,
+           0.3706800909561293,
+           0.3295944059781465,
+           0.2903789815834451,
+           0.2534590117769423,
+           0.21917027449705834,
+           0.1877524263396906,
+           0.15934497721535268,
+           0.13398602695690665,
+           0.1116137743055969,
+           0.09207073708345866,
+           0.0751105525197237,
+           0.06040716039940471,
+           0.04756611061477361,
+           0.03613768236291037,
+           0.025631456011601716,
+           0.015531941712954758,
+           0.005314842106053362,
+           -0.005536489413773909,
+           -0.01751483797575884,
+           -0.0310736003948617,
+           -0.04661236055208921,
+           -0.06446395659404587,
+           -0.08488339079461728,
+           -0.10803888512727076,
+           -0.1340053299740994,
+           -0.1627603113544146,
+           -0.19418283516083948,
+           -0.22805479683721683,
+           -0.26406517349364256,
+           -0.3018168444395397,
+           -0.3408358773268839,
+           -0.3805830522793618,
+           -0.4204673371885419,
+           -0.4598609752947952,
+           -0.4981158025714076,
+           -0.534580378417031,
+           -0.5686174896171888,
+           -0.5996215750816078,
+           -0.6270356178451403,
+           -0.6503670612940865,
+           -0.6692023283173268,
+           -0.6832195545704387,
+           -0.6921991894985736,
+           -0.6960321701568766,
+           -0.694725431936663,
+           -0.6884045855979595,
+           -0.6773136599123295,
+           -0.661811882003472,
+           -0.6423675413305521,
+           -0.6195490563533015,
+           -0.5940134334261793,
+           -0.5664923736289564,
+           -0.5377763433946365,
+           -0.5086969774296033,
+           -0.480108226205561,
+           -0.4528666941246172,
+           -0.4278116374487217,
+           -0.405745102639737,
+           -0.3874126855554356,
+           -0.3734853799582511,
+           -0.36454296027745653,
+           -0.3610593090664775,
+           -0.3633900549319635,
+           -0.37176283294908485,
+           -0.38627041801325335,
+           -0.4068669137013835,
+           -0.4333671066730501,
+           -0.46544902119784476,
+           -0.5026596318882316,
+           -0.5444236170141754,
+           -0.590054961726482,
+           -0.6387711519066412,
+           -0.689709636871955,
+           -0.7419461843268002,
+           -0.7945147051092489,
+           -0.8464280895623579,
+           -0.8966995726395807,
+           -0.9443641317432669,
+           -0.9884994201192995,
+           -1.0282457494228936,
+           -1.0628246575702807,
+           -1.0915556316524013,
+           -1.113870599689665,
+           -1.1293258582790673,
+           -1.1376111644269091,
+           -1.1385557875782137,
+           -1.132131390396103,
+           -1.1184516824418655,
+           -1.0977688677170114,
+           -1.0704669831815459,
+           -1.0370522990054172,
+           -0.9981410206530787,
+           -0.95444459626268,
+           -0.9067529886282649,
+           -0.8559163180787214,
+           -0.8028253195437046,
+           -0.7483910832238285,
+           -0.6935245629279995,
+           -0.6391163389755871,
+           -0.5860171135476714,
+           -0.5350193957628605,
+           -0.48684080208781205,
+           -0.44210935578022265,
+           -0.4013511179632157,
+           -0.36498042392965074,
+           -0.3332929328498432,
+           -0.3064616288394963,
+           -0.28453583808323246,
+           -0.2674432522220487,
+           -0.25499487434519413,
+           -0.24689273250389995,
+           -0.24274013844673817,
+           -0.24205420791656077,
+           -0.24428030485019667,
+           -0.24880802650118125,
+           -0.25498831096107605,
+           -0.2621512236388045,
+           -0.2696239655560033,
+           -0.27674864413479733,
+           -0.28289935651022036,
+           -0.28749815602202516,
+           -0.290029503878592,
+           -0.29005284922107505,
+           -0.2872130308848764,
+           -0.2812482517750794,
+           -0.27199544047280744,
+           -0.25939288285119366,
+           -0.24348007737381577,
+           -0.22439483958052128,
+           -0.20236775221998157,
+           -0.1777141257739018,
+           -0.15082369801283266,
+           -0.12214835911853544,
+           -0.09218823934586202,
+           -0.061476537910192613,
+           -0.03056350372726787,
+           -2.814391753231576e-16
+          ],
+          [
+           0,
+           0.02830756758755581,
+           0.055069630432630065,
+           0.07987288417523243,
+           0.10236913099678915,
+           0.12228592757450202,
+           0.13943513771552013,
+           0.15371915413980192,
+           0.16513461438814261,
+           0.17377350091445756,
+           0.17982158343143193,
+           0.18355423079361313,
+           0.18532968836771674,
+           0.1855799832143638,
+           0.1847996818025717,
+           0.18353278181013039,
+           0.1823580693796244,
+           0.18187331472582752,
+           0.18267871115658926,
+           0.18535998454075428,
+           0.19047161145232813,
+           0.19852058432874703,
+           0.20995115096897998,
+           0.22513093380929652,
+           0.2443388021688433,
+           0.26775482883205964,
+           0.2954526119500923,
+           0.327394185534636,
+           0.3634276782065727,
+           0.4032878119204925,
+           0.4465992617982735,
+           0.4928828267238133,
+           0.5415642897563743,
+           0.591985779473568,
+           0.6434193797565017,
+           0.6950826778748268,
+           0.7461558904699123,
+           0.7958001654416453,
+           0.8431766258777367,
+           0.88746570084455,
+           0.9278862776467165,
+           0.9637142113467196,
+           0.994299739921734,
+           1.019083377147959,
+           1.0376098895918493,
+           1.049540008140455,
+           1.0546595772643739,
+           1.0528859054052229,
+           1.0442711460579515,
+           1.0290026096702816,
+           1.007399979690216,
+           0.9799094801733135,
+           0.9470951155055765,
+           0.9096271732173639,
+           0.86826824683527,
+           0.8238570956263219,
+           0.7772907104629823,
+           0.7295049985925958,
+           0.6814545337604865,
+           0.6340918410827974,
+           0.5883466977265047,
+           0.5451059305389454,
+           0.5051941802702437,
+           0.46935607922542255,
+           0.43824025562169744,
+           0.41238553442682324,
+           0.392209652075907,
+           0.3780007424833369,
+           0.3699117856458723,
+           0.36795813948423056,
+           0.3720182021158762,
+           0.3818371772804826,
+           0.39703384196488484,
+           0.41711014418815184,
+           0.44146339213647784,
+           0.4694007350010561,
+           0.5001555824417836,
+           0.5329055648635935,
+           0.5667916017238945,
+           0.6009376207204581,
+           0.6344704575098555,
+           0.6665394638717868,
+           0.6963353619772533,
+           0.7231079033688599,
+           0.7461819228745286,
+           0.764971419145496,
+           0.7789913437877519,
+           0.7878668388807751,
+           0.791339726602193,
+           0.7892721231084785,
+           0.7816471200584724,
+           0.7685665494414661,
+           0.7502459188960857,
+           0.7270066737142246,
+           0.699266006516088,
+           0.6675244945667486,
+           0.6323518964379565,
+           0.594371482941095,
+           0.5542433109223119,
+           0.5126468718131943,
+           0.4702635592238514,
+           0.427759401076672,
+           0.3857684918146033,
+           0.34487753936232846,
+           0.30561191032842094,
+           0.26842351622464694,
+           0.23368083429467695,
+           0.20166130014802197,
+           0.1725462472239642,
+           0.14641850174432078,
+           0.12326267293556244,
+           0.1029681086527707,
+           0.08533441787954817,
+           0.07007939564148356,
+           0.056849124317489425,
+           0.04522996971269862,
+           0.034762141967077734,
+           0.024954451628213158,
+           0.01529986101157849,
+           0.00529141106279918,
+           -0.005561905179897696,
+           -0.017719749524644758,
+           -0.03159594010470848,
+           -0.04754523803898955,
+           -0.06585177638400601,
+           -0.08671944576979736,
+           -0.11026450029176191,
+           -0.13651058959347792,
+           -0.16538636008087387,
+           -0.19672570145020227,
+           -0.23027064588154106,
+           -0.2656768580897244,
+           -0.30252158668934437,
+           -0.3403138827391931,
+           -0.37850683152636716,
+           -0.4165114901550146,
+           -0.45371217768629496,
+           -0.48948272761046147,
+           -0.523203285274289,
+           -0.5542772162476186,
+           -0.5821476859390946,
+           -0.6063134762363575,
+           -0.6263436214439906,
+           -0.6418904729409081,
+           -0.6527008391273268,
+           -0.6586248934782806,
+           -0.6596225977344851,
+           -0.6557674481094389,
+           -0.6472474183724491,
+           -0.6343630431479086,
+           -0.6175226560277144,
+           -0.5972348683541833,
+           -0.5740984440189401,
+           -0.5487897916029075,
+           -0.5220483560007639,
+           -0.49466024580165896,
+           -0.4674404787706727,
+           -0.44121426462355107,
+           -0.41679777096752124,
+           -0.3949788341003985,
+           -0.37649808089285625,
+           -0.36203092107716073,
+           -0.352170851064579,
+           -0.347414481327284,
+           -0.3481486600926703,
+           -0.35464001754515145,
+           -0.3670271980796488,
+           -0.38531598477054274,
+           -0.4093774516463026,
+           -0.43894920726017456,
+           -0.47363971917729863,
+           -0.5129356351606671,
+           -0.5562119448363043,
+           -0.6027447572131979,
+           -0.6517264063005612,
+           -0.7022825407516864,
+           -0.7534908053513186,
+           -0.8044006834342129,
+           -0.8540540409289812,
+           -0.9015058953637121,
+           -0.9458449272783419,
+           -0.9862132572129645,
+           -1.0218250286465203,
+           -1.0519833655304733,
+           -1.0760953117107883,
+           -1.0936844076174739,
+           -1.1044006159529745,
+           -1.108027371354723,
+           -1.1044855976014831,
+           -1.0938346082056436,
+           -1.076269880423075,
+           -1.0521177670118158,
+           -1.021827282672526,
+           -0.9859591712426833,
+           -0.9451725237145553,
+           -0.9002092744541014,
+           -0.8518769522297072,
+           -0.8010301026317723,
+           -0.7485508282212511,
+           -0.6953289115840545,
+           -0.6422419939549413,
+           -0.5901362780545842,
+           -0.539808208386346,
+           -0.4919875558730124,
+           -0.4473222970563017,
+           -0.4063656320632653,
+           -0.3695654313224097,
+           -0.33725633994708615,
+           -0.30965470231882464,
+           -0.28685639935181795,
+           -0.26883761894087477,
+           -0.2554585079724953,
+           -0.2464695837950934,
+           -0.24152071593809826,
+           -0.24017242679125328,
+           -0.24190920442705263,
+           -0.24615447312696304,
+           -0.25228682861236545,
+           -0.2596571164127724,
+           -0.26760591390470234,
+           -0.2754809697356167,
+           -0.2826541587422564,
+           -0.2885375259357165,
+           -0.2925980192346252,
+           -0.29437054669602764,
+           -0.29346903908668187,
+           -0.28959525159715777,
+           -0.28254509797453425,
+           -0.27221237482292865,
+           -0.2585898016584641,
+           -0.24176737178846724,
+           -0.22192807845723378,
+           -0.19934114821136611,
+           -0.17435297738428174,
+           -0.14737602637162658,
+           -0.11887597848847056,
+           -0.08935751435556571,
+           -0.059349087847462435,
+           -0.029387114770941764,
+           -2.6951813940619065e-16
+          ],
+          [
+           0,
+           0.026891192960926857,
+           0.052105034202096015,
+           0.07527293638492909,
+           0.09609503732886558,
+           0.114349402383028,
+           0.1298990644889767,
+           0.1426967069256061,
+           0.15278685500290057,
+           0.16030550776267408,
+           0.16547720741032645,
+           0.1686096110525191,
+           0.17008569465590684,
+           0.17035378131257908,
+           0.1699156433176526,
+           0.16931297877024074,
+           0.16911260709206222,
+           0.16989076289686558,
+           0.17221689313293395,
+           0.17663737769304377,
+           0.18365959832967343,
+           0.19373677458238872,
+           0.20725396864354087,
+           0.22451563404934194,
+           0.24573504643540914,
+           0.2710259092303341,
+           0.3003963741889853,
+           0.3337456573929742,
+           0.3708633672331053,
+           0.41143159352591474,
+           0.4550297379763623,
+           0.5011419973973519,
+           0.5491673441503335,
+           0.5984317848540153,
+           0.6482026201102276,
+           0.6977043762839583,
+           0.746136036554723,
+           0.7926891636422599,
+           0.8365664816936031,
+           0.877000470450146,
+           0.9132715213818972,
+           0.9447252131013931,
+           0.9707882818982646,
+           0.9909828922439882,
+           1.0049388509220523,
+           1.0124034561157256,
+           1.013248728187237,
+           1.0074758306696556,
+           0.9952165566673631,
+           0.9767318258014648,
+           0.9524072083383657,
+           0.9227455644578028,
+           0.8883569560075433,
+           0.8499460538575512,
+           0.8082973244952117,
+           0.7642583333106555,
+           0.7187215477858634,
+           0.672605060397794,
+           0.626832677572685,
+           0.582313836830464,
+           0.5399238189418452,
+           0.5004847153651748,
+           0.46474759358960827,
+           0.4333762747114869,
+           0.4069330992983834,
+           0.38586701028107967,
+           0.37050422640972425,
+           0.361041718061478,
+           0.35754363039790243,
+           0.3599407286684373,
+           0.36803286855183626,
+           0.38149442257088473,
+           0.39988252355537646,
+           0.4226479195667433,
+           0.4491481732501787,
+           0.47866288373469124,
+           0.5104105622829104,
+           0.5435667550288747,
+           0.577282978238539,
+           0.6107060142428653,
+           0.6429971099247684,
+           0.6733506245143719,
+           0.7010116893140852,
+           0.7252924684176467,
+           0.7455866458276152,
+           0.7613818096940428,
+           0.7722694575534913,
+           0.7779524061121347,
+           0.7782494538011004,
+           0.7730972124278792,
+           0.7625490940648839,
+           0.7467715091268062,
+           0.7260373996679491,
+           0.7007172966017059,
+           0.671268149217466,
+           0.6382202285838038,
+           0.6021624518826576,
+           0.563726511314876,
+           0.5235702180731415,
+           0.4823604883582284,
+           0.4407564041429212,
+           0.3993927762572082,
+           0.3588646215422909,
+           0.31971293972932674,
+           0.28241214002704795,
+           0.2473594230737287,
+           0.21486637206122716,
+           0.18515294879568223,
+           0.15834402769745146,
+           0.13446853485387378,
+           0.11346119189025337,
+           0.0951667973186895,
+           0.07934691285402198,
+           0.06568876059335271,
+           0.05381608049029607,
+           0.04330164763672264,
+           0.03368110674644717,
+           0.024467747972838814,
+           0.015167824617755657,
+           0.005295999990071502,
+           -0.0056094920231493555,
+           -0.017972380139776454,
+           -0.032164971659227035,
+           -0.04849621185704395,
+           -0.06720150974267428,
+           -0.08843460713781359,
+           -0.11226171490153118,
+           -0.13865808119967513,
+           -0.16750709348206677,
+           -0.19860194989320737,
+           -0.23164986887134054,
+           -0.26627873938455293,
+           -0.3020460502938329,
+           -0.3384498773467815,
+           -0.37494165181888406,
+           -0.4109403872223521,
+           -0.44584800101438193,
+           -0.4790653378739998,
+           -0.5100084806684673,
+           -0.5381249252375598,
+           -0.5629091958665549,
+           -0.5839174898071607,
+           -0.6007809611810355,
+           -0.6132172865410003,
+           -0.6210401954976988,
+           -0.6241666991399878,
+           -0.6226218052743867,
+           -0.6165405713942272,
+           -0.6061674122317616,
+           -0.5918526471108656,
+           -0.5740463414044288,
+           -0.5532895644875514,
+           -0.5302032519646931,
+           -0.5054749209987073,
+           -0.4798435427490546,
+           -0.45408292384464854,
+           -0.4289839882599735,
+           -0.4053363809253082,
+           -0.38390983410953905,
+           -0.3654357465462394,
+           -0.3505894231749084,
+           -0.33997341025646854,
+           -0.33410233678441714,
+           -0.33338963910516817,
+           -0.3381365022899944,
+           -0.3485233001059031,
+           -0.36460375666037337,
+           -0.3863019883682403,
+           -0.41341251637296594,
+           -0.44560326861708216,
+           -0.48242151912787645,
+           -0.5233026415141316,
+           -0.5675814858839514,
+           -0.614506125052501,
+           -0.6632536585644,
+           -0.7129477131162629,
+           -0.7626772366572585,
+           -0.8115161517864293,
+           -0.8585434128356451,
+           -0.9028630007523988,
+           -0.9436233908350259,
+           -0.980036040507631,
+           -1.0113924673623407,
+           -1.037079521084357,
+           -1.0565924957998138,
+           -1.069545780802563,
+           -1.0756808062718235,
+           -1.0748711050586015,
+           -1.06712438032415,
+           -1.0525815400845817,
+           -1.0315127318162733,
+           -1.0043104814521375,
+           -0.9714801096184524,
+           -0.9336276621617359,
+           -0.8914456503384729,
+           -0.8456969470769263,
+           -0.7971972282393112,
+           -0.7467963807946488,
+           -0.6953593224734058,
+           -0.6437466892848958,
+           -0.5927958479751171,
+           -0.543302680097117,
+           -0.49600456314277974,
+           -0.4515649426933256,
+           -0.4105598485874721,
+           -0.37346665871406637,
+           -0.34065535744881037,
+           -0.3123824733860444,
+           -0.28878781441956375,
+           -0.26989404905574427,
+           -0.25560911281172954,
+           -0.2457313493930375,
+           -0.23995722976479944,
+           -0.23789142986746717,
+           -0.23905899111139897,
+           -0.24291923829952347,
+           -0.2488810884772699,
+           -0.2563193523883486,
+           -0.2645916084838869,
+           -0.27305521829809765,
+           -0.28108405170859296,
+           -0.2880845011152541,
+           -0.2935103846006911,
+           -0.29687636911818066,
+           -0.2977695848827685,
+           -0.29585915038419236,
+           -0.29090338256168835,
+           -0.2827545272761499,
+           -0.27136090974539456,
+           -0.2567664714386281,
+           -0.2391077273664371,
+           -0.21860824405021348,
+           -0.19557080203706992,
+           -0.1703674660418956,
+           -0.14342783915793547,
+           -0.11522582374071143,
+           -0.08626524937908148,
+           -0.05706475687494458,
+           -0.02814234564754803,
+           -2.570643896164852e-16
+          ],
+          [
+           0,
+           0.02544121773650384,
+           0.049099282869924175,
+           0.07065119592891003,
+           0.08984534513568802,
+           0.106509260112395,
+           0.1205551633434363,
+           0.13198316433414367,
+           0.1408820027562217,
+           0.14742731070873982,
+           0.15187742893173417,
+           0.1545668757468074,
+           0.15589762904252455,
+           0.1563284392077603,
+           0.1563624430773568,
+           0.1565333943602028,
+           0.15739086350716677,
+           0.15948478857974857,
+           0.16334977765631872,
+           0.16948957215860586,
+           0.17836207894742268,
+           0.19036536713436136,
+           0.20582500355630787,
+           0.2249830692867571,
+           0.24798915917757067,
+           0.27489361822457786,
+           0.30564321371556813,
+           0.3400793820034861,
+           0.37793912483956926,
+           0.418858564087365,
+           0.46237909696414325,
+           0.5079560283840258,
+           0.5549694941463266,
+           0.6027374301978408,
+           0.650530290469956,
+           0.6975871701810208,
+           0.7431329541579685,
+           0.7863960816227833,
+           0.8266265007362145,
+           0.86311337847532,
+           0.8952021343677056,
+           0.9223103801750582,
+           0.9439423715103427,
+           0.95970161102975,
+           0.9693012854627225,
+           0.9725722693090795,
+           0.9694684853212707,
+           0.9600694745143146,
+           0.9445800948841171,
+           0.9233273366485159,
+           0.8967543109796425,
+           0.8654115371810007,
+           0.8299457184140758,
+           0.7910862568010383,
+           0.7496298135323369,
+           0.7064232671447747,
+           0.6623454622376215,
+           0.6182881705979915,
+           0.5751367062781333,
+           0.5337506451202406,
+           0.494945097332589,
+           0.4594729690234157,
+           0.4280086253996485,
+           0.40113333519754213,
+           0.379322833635723,
+           0.36293729079628684,
+           0.3522139150728932,
+           0.3472623585708751,
+           0.3480630246318962,
+           0.3544683086092877,
+           0.36620673332107356,
+           0.382889871951675,
+           0.40402188522950894,
+           0.42901143807734216,
+           0.45718570510928197,
+           0.48780612568264115,
+           0.520085528877656,
+           0.5532062177400797,
+           0.5863385811190754,
+           0.6186597909554853,
+           0.6493721431550271,
+           0.6777206111833632,
+           0.7030092029485002,
+           0.7246157428377191,
+           0.7420047411562131,
+           0.7547380616563478,
+           0.762483153136295,
+           0.7650186718453004,
+           0.7622373861481225,
+           0.7541463219672699,
+           0.7408641752777727,
+           0.7226160847013519,
+           0.6997259213889984,
+           0.6726063133160444,
+           0.641746675372441,
+           0.6076995638880169,
+           0.5710657133394155,
+           0.5324781429988436,
+           0.4925857414892935,
+           0.4520367471367409,
+           0.4114625414441064,
+           0.37146216200321447,
+           0.3325879200187966,
+           0.29533247690374465,
+           0.2601176949163406,
+           0.22728552956452844,
+           0.19709117770783915,
+           0.16969863631413704,
+           0.14517876417309616,
+           0.12350987411768448,
+           0.10458081809550065,
+           0.08819646340890247,
+           0.07408539721958911,
+           0.06190963953030781,
+           0.05127609374310573,
+           0.04174941983295109,
+           0.03286597927169818,
+           0.024148473988139792,
+           0.01512088452457364,
+           0.005323305572909448,
+           -0.0056737195878931385,
+           -0.018255750667956126,
+           -0.03275224943242613,
+           -0.049425955017301626,
+           -0.06846412309312143,
+           -0.08997186791087497,
+           -0.11396779153038261,
+           -0.14038202501366992,
+           -0.1690567435724525,
+           -0.19974915318093536,
+           -0.2321368816374314,
+           -0.26582564411785153,
+           -0.30035899350952117,
+           -0.33522991076492764,
+           -0.36989394157495764,
+           -0.40378354408110734,
+           -0.4363232791935419,
+           -0.4669454512140023,
+           -0.4951057925045645,
+           -0.520298782272339,
+           -0.5420721962759784,
+           -0.5600405012610549,
+           -0.573896734798869,
+           -0.5834225472901157,
+           -0.5884961273217069,
+           -0.5890977832422138,
+           -0.5853130114753194,
+           -0.5773329442958851,
+           -0.565452135007267,
+           -0.5500637050605648,
+           -0.5316519439873357,
+           -0.5107825174208401,
+           -0.4880904993451369,
+           -0.46426650050879537,
+           -0.44004121426554166,
+           -0.4161687427103943,
+           -0.39340909880804176,
+           -0.372510303417255,
+           -0.35419050909425015,
+           -0.3391205849546473,
+           -0.3279075885945735,
+           -0.32107953228709496,
+           -0.3190718218110167,
+           -0.32221570801550387,
+           -0.3307290444895362,
+           -0.34470959061437084,
+           -0.36413103913803146,
+           -0.3888418826826198,
+           -0.4185671658529038,
+           -0.4529131005096813,
+           -0.49137445299161053,
+           -0.5333445452966792,
+           -0.5781276491044061,
+           -0.6249534935801973,
+           -0.6729935565760293,
+           -0.7213787653887551,
+           -0.7692181987281653,
+           -0.8156183568331306,
+           -0.8597025523675257,
+           -0.9006299711856248,
+           -0.9376139593731166,
+           -0.9699391109728288,
+           -0.9969767590600397,
+           -1.018198510655862,
+           -1.0331875124398762,
+           -1.0416471882137783,
+           -1.043407249262061,
+           -1.0384268436872375,
+           -1.0267947788844638,
+           -1.0087268209055305,
+           -0.9845601438513849,
+           -0.9547450699378879,
+           -0.91983430486121,
+           -0.8804699319948893,
+           -0.8373684813535023,
+           -0.7913044338931167,
+           -0.7430925575126239,
+           -0.6935694972177172,
+           -0.6435750576948567,
+           -0.5939336216541709,
+           -0.545436141638944,
+           -0.4988231267306123,
+           -0.4547690191288924,
+           -0.41386831963225945,
+           -0.3766237764933592,
+           -0.3434369000956093,
+           -0.31460100769178767,
+           -0.290296939513029,
+           -0.2705915214609998,
+           -0.2554387819758871,
+           -0.24468386320043217,
+           -0.2380695009009736,
+           -0.23524488537680002,
+           -0.2357766583170327,
+           -0.2391617496512922,
+           -0.2448417151272961,
+           -0.25221820068440665,
+           -0.26066913450895085,
+           -0.26956523254930914,
+           -0.2782863985785679,
+           -0.2862376057023767,
+           -0.29286386233978645,
+           -0.2976638917190012,
+           -0.3002021891457699,
+           -0.30011916480907036,
+           -0.2971391305708766,
+           -0.2910759457508981,
+           -0.28183619792531533,
+           -0.2694198586639653,
+           -0.2539184193166999,
+           -0.2355105767805162,
+           -0.2144556020002652,
+           -0.19108458319551141,
+           -0.16578978997462604,
+           -0.13901245223406958,
+           -0.11122928784885082,
+           -0.08293814463513569,
+           -0.054643144121947505,
+           -0.026839726757521276,
+           -2.4418114816993406e-16
+          ],
+          [
+           0,
+           0.02396907605358364,
+           0.046075227430963345,
+           0.06604132020383767,
+           0.0836633302807918,
+           0.09881666314760448,
+           0.11146025760714354,
+           0.12163835737803108,
+           0.12947989517648176,
+           0.1351954961738282,
+           0.13907216991414023,
+           0.1414658203137886,
+           0.1427917607099343,
+           0.14351347361888706,
+           0.144129901564766,
+           0.14516159484996,
+           0.14713607344689086,
+           0.15057278248583086,
+           0.155968033511676,
+           0.1637803264395149,
+           0.17441643985953298,
+           0.18821866018295974,
+           0.20545349348721717,
+           0.22630216845328777,
+           0.2508531953572201,
+           0.2790971957474778,
+           0.3109241614521945,
+           0.34612324130109906,
+           0.38438509091141915,
+           0.42530675664362105,
+           0.468399000983097,
+           0.5130959147435205,
+           0.5587666031660926,
+           0.6047286796714643,
+           0.6502632540516089,
+           0.6946310624566484,
+           0.7370893556412674,
+           0.7769091403819769,
+           0.8133923573252577,
+           0.845888577098697,
+           0.8738108053811994,
+           0.8966500065983033,
+           0.9139879845483738,
+           0.9255082958988793,
+           0.9310049182195879,
+           0.930388446940321,
+           0.9236896540592897,
+           0.9110603041652264,
+           0.8927711888452937,
+           0.8692074072331584,
+           0.8408609866782364,
+           0.8083210016673041,
+           0.772261409631439,
+           0.733426877640226,
+           0.6926169228610445,
+           0.6506687308415869,
+           0.6084390481436005,
+           0.5667855688129672,
+           0.5265482470457119,
+           0.4885309708784335,
+           0.45348402372644897,
+           0.4220877423018188,
+           0.3949377513064483,
+           0.37253211799377955,
+           0.3552607241321026,
+           0.34339710019081093,
+           0.33709290799117525,
+           0.33637519504130864,
+           0.34114647784567564,
+           0.3511876442476061,
+           0.36616359796490544,
+           0.38563150354054915,
+           0.4090514285301885,
+           0.43579912337516313,
+           0.4651806294289636,
+           0.4964483632230796,
+           0.5288182912942145,
+           0.5614877855550239,
+           0.5936537348490797,
+           0.6245304843153803,
+           0.6533671805721338,
+           0.6794641173320107,
+           0.7021877024485891,
+           0.7209837028941597,
+           0.7353884678863657,
+           0.745037881219704,
+           0.7496738505479034,
+           0.7491482024938958,
+           0.7434239165177783,
+           0.732573695863286,
+           0.7167759390139589,
+           0.6963082383156282,
+           0.6715385922069237,
+           0.6429145723774553,
+           0.6109507358024638,
+           0.5762146127993658,
+           0.5393116350190625,
+           0.5008693908381635,
+           0.46152160940313697,
+           0.42189227828361936,
+           0.38258029326136034,
+           0.34414502240728667,
+           0.307093140723672,
+           0.27186705692872554,
+           0.23883521133346944,
+           0.20828447429824004,
+           0.18041481971966464,
+           0.15533638878697492,
+           0.13306899735922398,
+           0.11354407731705615,
+           0.09660897972396462,
+           0.08203350716781876,
+           0.06951848576517539,
+           0.05870613542808479,
+           0.049191951417580246,
+           0.04053777208165607,
+           0.032285677951603996,
+           0.023972346790065404,
+           0.015143478257422415,
+           0.005367900857108764,
+           -0.005749017247938372,
+           -0.018553013319412903,
+           -0.03332996293731673,
+           -0.05029659623260771,
+           -0.06959314901648864,
+           -0.09127814991584197,
+           -0.11532548897891058,
+           -0.14162385378314057,
+           -0.16997855736461165,
+           -0.20011571986022478,
+           -0.23168870419355211,
+           -0.2642866470058407,
+           -0.29744487083820065,
+           -0.3306569137150716,
+           -0.36338786903512366,
+           -0.3950886931517991,
+           -0.42521111113658744,
+           -0.453222733663247,
+           -0.47862199019618396,
+           -0.5009524859313508,
+           -0.5198164021924842,
+           -0.5348865819476464,
+           -0.5459169732552192,
+           -0.5527511430181653,
+           -0.5553286204510934,
+           -0.5536888829887806,
+           -0.5479728556693437,
+           -0.5384218568652016,
+           -0.5253739870736563,
+           -0.5092580217264535,
+           -0.490584932030509,
+           -0.4699372181323645,
+           -0.447956294895097,
+           -0.4253282208790689,
+           -0.4027681044568901,
+           -0.3810035562674589,
+           -0.36075758352150483,
+           -0.34273133832925784,
+           -0.3275871387851747,
+           -0.3159321778195072,
+           -0.30830332087073775,
+           -0.3051533695585098,
+           -0.3068391353014076,
+           -0.31361162501807405,
+           -0.325608591676994,
+           -0.34284964671176443,
+           -0.3652340705461997,
+           -0.3925413931546817,
+           -0.4244347502852182,
+           -0.46046695431440565,
+           -0.5000891533148512,
+           -0.5426618893981044,
+           -0.5874683092823465,
+           -0.6337292277511624,
+           -0.680619699502573,
+           -0.7272867179486746,
+           -0.7728676317269191,
+           -0.8165088517124196,
+           -0.8573844136248288,
+           -0.8947139640991719,
+           -0.9277797512780718,
+           -0.9559422242674349,
+           -0.9786538786170677,
+           -0.9954710265454173,
+           -1.0060632199142199,
+           -1.010220109774954,
+           -1.007855587296022,
+           -0.9990091155526586,
+           -0.9838442284459579,
+           -0.9626442402877402,
+           -0.935805275707703,
+           -0.9038267929013869,
+           -0.8672998323036181,
+           -0.8268932761108141,
+           -0.7833384503969032,
+           -0.7374124397555254,
+           -0.6899205135400632,
+           -0.6416780821705459,
+           -0.593492611180439,
+           -0.5461459194852386,
+           -0.500377276823145,
+           -0.4568676937538334,
+           -0.416225766559249,
+           -0.37897539965666505,
+           -0.3455456807080149,
+           -0.3162631296771997,
+           -0.2913464839931218,
+           -0.27090411918930085,
+           -0.25493413946819155,
+           -0.2433271071858973,
+           -0.23587131588666982,
+           -0.2322604498217973,
+           -0.23210341537987444,
+           -0.23493607794353805,
+           -0.24023459263817817,
+           -0.24742998034444585,
+           -0.2559235721021248,
+           -0.265102926309785,
+           -0.2743578143561668,
+           -0.28309587169017897,
+           -0.29075752277888806,
+           -0.29682980959804783,
+           -0.30085878368629726,
+           -0.302460160582803,
+           -0.3013279816610105,
+           -0.2972410807879203,
+           -0.2900672105446074,
+           -0.2797647434859942,
+           -0.2663819265586693,
+           -0.250053729752731,
+           -0.23099639174964862,
+           -0.209499824189699,
+           -0.18591809073972257,
+           -0.16065822602460184,
+           -0.13416770146845874,
+           -0.10692087912319838,
+           -0.07940481979286747,
+           -0.05210482756476324,
+           -0.02549011884251869,
+           -2.309731784318247e-16
+          ],
+          [
+           0,
+           0.02248605946609083,
+           0.04305510595381898,
+           0.06147557213102018,
+           0.077589809276013,
+           0.09131900474736397,
+           0.10266589469968658,
+           0.11171519336432026,
+           0.11863171977558344,
+           0.12365626295539137,
+           0.12709928574559745,
+           0.12933262419573888,
+           0.13077939223190518,
+           0.13190234890507613,
+           0.13319102663001745,
+           0.13514795242537647,
+           0.1382743193863981,
+           0.1430554818076054,
+           0.1499466540939424,
+           0.1593591906624834,
+           0.17164781149229627,
+           0.1870991161180735,
+           0.2059216982086367,
+           0.22823813417072397,
+           0.25407907342095554,
+           0.2833796062035631,
+           0.3159780283789844,
+           0.35161706286937927,
+           0.3899475359071984,
+           0.43053444442612837,
+           0.47286529040406705,
+           0.5163605002309533,
+           0.5603856936798108,
+           0.6042655191545712,
+           0.6472987307843117,
+           0.6887741496756146,
+           0.7279871270752009,
+           0.7642561119724768,
+           0.7969389201945164,
+           0.8254483064821209,
+           0.8492664553076216,
+           0.8679580299821645,
+           0.8811814523454393,
+           0.8886981262548597,
+           0.8903793662111065,
+           0.8862108466103339,
+           0.8762944459867618,
+           0.86084742277073,
+           0.8401989230208756,
+           0.8147838847331796,
+           0.7851344661146159,
+           0.7518691850966945,
+           0.7156800128847353,
+           0.6773177141282576,
+           0.6375757691311177,
+           0.597273248341313,
+           0.5572370353092009,
+           0.5182838107356894,
+           0.48120221673782476,
+           0.4467356168702353,
+           0.4155658538362507,
+           0.38829838352705703,
+           0.36544913160267584,
+           0.3474333780609275,
+           0.3345569271196582,
+           0.3270097654335908,
+           0.3248623525015192,
+           0.3280646245322214,
+           0.3364477285518619,
+           0.34972843872088744,
+           0.36751614326093635,
+           0.38932222961685864,
+           0.4145716389708468,
+           0.44261631035433596,
+           0.47275019059875456,
+           0.5042254502887176,
+           0.5362695185957554,
+           0.5681025320249754,
+           0.5989547841171126,
+           0.6280837651868365,
+           0.6547903931719771,
+           0.6784340582992184,
+           0.6984461349858143,
+           0.7143416534173445,
+           0.7257288695888112,
+           0.7323165251126402,
+           0.7339186454744534,
+           0.7304567862311973,
+           0.7219596993894712,
+           0.7085604553238679,
+           0.6904911175386588,
+           0.6680751268168763,
+           0.6417176063845831,
+           0.611893849296945,
+           0.5791362921180946,
+           0.5440203140794806,
+           0.507149227416765,
+           0.469138841874339,
+           0.43060199403063204,
+           0.3921334299784326,
+           0.35429541807810416,
+           0.31760444731473014,
+           0.2825193367928496,
+           0.2494310438727949,
+           0.21865441336807226,
+           0.19042205923526948,
+           0.16488051459344416,
+           0.14208872711836942,
+           0.1220189163555513,
+           0.10455974881168316,
+           0.08952172734652496,
+           0.07664463488911344,
+           0.06560682026327411,
+           0.056036067238323155,
+           0.047521747990578934,
+           0.03962792996817553,
+           0.031907081498330644,
+           0.023914006949728082,
+           0.015219637219977003,
+           0.005424305877126726,
+           -0.0058298446789377505,
+           -0.01884765951721399,
+           -0.03387127074492495,
+           -0.05107216175975676,
+           -0.07054521149120412,
+           -0.09230488228352672,
+           -0.11628365918348865,
+           -0.1423327896882465,
+           -0.1702253129711615,
+           -0.1996613077588263,
+           -0.23027522990030766,
+           -0.2616451557264485,
+           -0.293303696941074,
+           -0.32475030830094376,
+           -0.3554646718647004,
+           -0.3849208120854554,
+           -0.41260157525018626,
+           -0.43801309527657306,
+           -0.4606988659766423,
+           -0.4802530476584954,
+           -0.4963326531919783,
+           -0.5086682850023594,
+           -0.5170731292402779,
+           -0.5214499557560055,
+           -0.5217959214389148,
+           -0.5182050287604865,
+           -0.510868149636331,
+           -0.5000705855520097,
+           -0.486187196764228,
+           -0.4696751947495531,
+           -0.45106475139244084,
+           -0.4309476341958259,
+           -0.40996412765802553,
+           -0.3887885456059648,
+           -0.3681136765750266,
+           -0.34863453332844896,
+           -0.33103179756616075,
+           -0.31595536125923035,
+           -0.3040083665725008,
+           -0.2957321369591671,
+           -0.2915923729266343,
+           -0.29196695762321545,
+           -0.29713568045018773,
+           -0.30727214224730576,
+           -0.3224380543080417,
+           -0.34258008679527374,
+           -0.3675293614259621,
+           -0.39700362005288314,
+           -0.43061203653635693,
+           -0.46786257563947,
+           -0.5081717411554467,
+           -0.5508764975941349,
+           -0.5952480969372016,
+           -0.6405074955173697,
+           -0.6858420071296245,
+           -0.7304228080032219,
+           -0.7734228880065178,
+           -0.8140350309512746,
+           -0.8514894053993834,
+           -0.8850703559973827,
+           -0.9141320038701897,
+           -0.9381122925503877,
+           -0.9565451526273369,
+           -0.9690705028805162,
+           -0.9754418570307063,
+           -0.9755313621510293,
+           -0.9693321558427662,
+           -0.9569579930118118,
+           -0.9386401579296201,
+           -0.91472174164989,
+           -0.8856494272136373,
+           -0.8519629838959424,
+           -0.8142827256008944,
+           -0.7732952360933688,
+           -0.7297377039183575,
+           -0.684381241635451,
+           -0.6380135866286822,
+           -0.5914215937069954,
+           -0.5453739326929027,
+           -0.5006043971564622,
+           -0.45779621358496664,
+           -0.417567714022818,
+           -0.38045970023897646,
+           -0.34692478466146215,
+           -0.31731894373203934,
+           -0.29189546421609963,
+           -0.27080140372343653,
+           -0.25407662472537473,
+           -0.24165539822611565,
+           -0.23337051052024446,
+           -0.22895974568937522,
+           -0.22807455915296893,
+           -0.23029070509678004,
+           -0.23512053423936882,
+           -0.24202663928997567,
+           -0.2504364945447228,
+           -0.2597577141015712,
+           -0.26939354066315385,
+           -0.27875817411968934,
+           -0.2872915560978843,
+           -0.29447324321923757,
+           -0.29983502748741125,
+           -0.30297199634831873,
+           -0.3035517666574873,
+           -0.30132167497939927,
+           -0.296113760104872,
+           -0.2878474310475967,
+           -0.27652977361689174,
+           -0.26225350944860065,
+           -0.24519268157695787,
+           -0.22559619873110223,
+           -0.2037794250799495,
+           -0.1801140517589646,
+           -0.15501652994820472,
+           -0.12893538144585195,
+           -0.10233773069203977,
+           -0.07569542134700454,
+           -0.0494710903420475,
+           -0.024104572563324062,
+           -2.1754546616233328e-16
+          ],
+          [
+           0,
+           0.021003180515095428,
+           0.04006028219161341,
+           0.05698445210565296,
+           0.07166268911909286,
+           0.08405940678974078,
+           0.0942178263216305,
+           0.10225915647898015,
+           0.10837957517507571,
+           0.11284508493423409,
+           0.11598437015156313,
+           0.1181798366253871,
+           0.1198570618736942,
+           0.12147292704399408,
+           0.12350273670393797,
+           0.12642666054673182,
+           0.13071585034292577,
+           0.13681859581222464,
+           0.14514688419356103,
+           0.15606372010848052,
+           0.16987154502473759,
+           0.1868020696455619,
+           0.20700779850581355,
+           0.230555484783018,
+           0.2574217058455947,
+           0.287490697536634,
+           0.3205545289319568,
+           0.35631564071475885,
+           0.3943917108360784,
+           0.43432275226601397,
+           0.4755802908584735,
+           0.517578418077151,
+           0.5596864649031044,
+           0.6012430008878984,
+           0.6415708271056012,
+           0.6799926045917869,
+           0.7158467414399469,
+           0.7485031525418414,
+           0.7773785062667858,
+           0.8019505821995008,
+           0.8217713831851929,
+           0.8364786729214572,
+           0.8458056465268547,
+           0.8495884850390498,
+           0.8477715946017881,
+           0.8404103859833097,
+           0.8276715086949685,
+           0.8098305149192481,
+           0.7872669902227936,
+           0.7604572491115413,
+           0.7299647523848621,
+           0.6964284585187279,
+           0.6605493715959515,
+           0.6230755923672133,
+           0.5847862157833397,
+           0.546474446879205,
+           0.5089303265049447,
+           0.47292346860161233,
+           0.43918621124693885,
+           0.4083975745302833,
+           0.38116839966944366,
+           0.3580280161035254,
+           0.3394127472542025,
+           0.32565652211663376,
+           0.31698380987815306,
+           0.31350503958258497,
+           0.31521460780303884,
+           0.32199151579329843,
+           0.3336026151536955,
+           0.3497083791902297,
+           0.3698710573693328,
+           0.3935650140268469,
+           0.4201890011425444,
+           0.44908006978389514,
+           0.4795287868460917,
+           0.5107953938825031,
+           0.5421265238430526,
+           0.572772079911389,
+           0.602001878619545,
+           0.6291216670482728,
+           0.6534881409837802,
+           0.6745226169562417,
+           0.6917230454717208,
+           0.704674094602472,
+           0.7130550813742905,
+           0.7166455818811959,
+           0.715328608438249,
+           0.7090913019309748,
+           0.6980231483546807,
+           0.6823117888580629,
+           0.6622365509277353,
+           0.6381598832413664,
+           0.6105169268327327,
+           0.5798034993291699,
+           0.546562806068994,
+           0.511371220989693,
+           0.4748235006026723,
+           0.43751780565960413,
+           0.40004090701927447,
+           0.36295394472673936,
+           0.3267790926370217,
+           0.2919874555000395,
+           0.25898849193551643,
+           0.2281212160294864,
+           0.19964738341925523,
+           0.17374681589476623,
+           0.15051496304668577,
+           0.12996274173957248,
+           0.11201863564065076,
+           0.09653297916653822,
+           0.0832842944780226,
+           0.07198749795691607,
+           0.06230374524857001,
+           0.053851642634832005,
+           0.04621951824791937,
+           0.03897842030005341,
+           0.031695491740839965,
+           0.023947362002129904,
+           0.015333196959206458,
+           0.005487057906084538,
+           -0.005910761041677345,
+           -0.01912372061927342,
+           -0.034350617801843765,
+           -0.051718987801860086,
+           -0.07128050598658349,
+           -0.09300851682674655,
+           -0.11679776148976034,
+           -0.14246631830343312,
+           -0.16975971249519464,
+           -0.19835709482454297,
+           -0.2278793344152487,
+           -0.2578988206396866,
+           -0.28795072359563667,
+           -0.3175454237028424,
+           -0.3461817892320481,
+           -0.37336095698034966,
+           -0.3986002564374619,
+           -0.421446912043399,
+           -0.4414911616857999,
+           -0.45837844235822756,
+           -0.4718203156011253,
+           -0.4816038354520363,
+           -0.4875990994067279,
+           -0.4897647674100357,
+           -0.4881513840557141,
+           -0.48290239373617044,
+           -0.47425279609065496,
+           -0.46252544832038467,
+           -0.4481250802937007,
+           -0.4315301463697839,
+           -0.41328269307190907,
+           -0.3939764727536111,
+           -0.37424357893749766,
+           -0.3547399179141884,
+           -0.3361298624775478,
+           -0.31907045653867844,
+           -0.3041955532089158,
+           -0.2921002733977736,
+           -0.2833261668936438,
+           -0.27834744337738465,
+           -0.27755861718980224,
+           -0.28126387748767456,
+           -0.2896684554462627,
+           -0.30287221336014297,
+           -0.3208656279900794,
+           -0.3435282835756908,
+           -0.37062992996749994,
+           -0.4018340997904331,
+           -0.4367042169383473,
+           -0.4747120685240377,
+           -0.5152484551469655,
+           -0.5576357813976781,
+           -0.6011423011953679,
+           -0.6449976920189205,
+           -0.6884095993421953,
+           -0.7305807684319006,
+           -0.770726365711262,
+           -0.8080910865103422,
+           -0.8419656503553249,
+           -0.8717022988974287,
+           -0.8967289348150331,
+           -0.9165615719798381,
+           -0.9308148070859832,
+           -0.9392100698310425,
+           -0.9415814614704427,
+           -0.9378790488592375,
+           -0.9281695415535426,
+           -0.9126343416969799,
+           -0.891565018753237,
+           -0.8653563221484112,
+           -0.8344969030740398,
+           -0.7995579706611906,
+           -0.76118015616028,
+           -0.7200589004796208,
+           -0.6769287144426822,
+           -0.6325466866049125,
+           -0.5876756298204675,
+           -0.5430672645871545,
+           -0.49944583437812295,
+           -0.4574925357822651,
+           -0.4178311246478959,
+           -0.3810150291081361,
+           -0.34751626212703707,
+           -0.31771638100091265,
+           -0.29189969020797163,
+           -0.2702488283908025,
+           -0.252842821460211,
+           -0.23965762328073717,
+           -0.23056910463289373,
+           -0.22535839164260457,
+           -0.22371939808750402,
+           -0.22526834332544704,
+           -0.22955500033031911,
+           -0.2360753776149003,
+           -0.24428550565584098,
+           -0.25361597360835475,
+           -0.2634868461956086,
+           -0.27332258404478843,
+           -0.2825665935513751,
+           -0.29069504448339833,
+           -0.29722961465492553,
+           -0.3017488505457491,
+           -0.303897869956614,
+           -0.30339617671072433,
+           -0.3000434069217835,
+           -0.293722880188045,
+           -0.28440288587652046,
+           -0.27213569299575835,
+           -0.2570543305478005,
+           -0.2393672422296463,
+           -0.21935097348894764,
+           -0.19734109886868986,
+           -0.17372164204967822,
+           -0.14891327890475484,
+           -0.12336064426840786,
+           -0.09751908524333079,
+           -0.07184121716380122,
+           -0.04676364248923939,
+           -0.022694187815095433,
+           -2.0400191725891347e-16
+          ],
+          [
+           0,
+           0.019531041661630843,
+           0.03711099861013011,
+           0.05259635673429918,
+           0.06591655909829033,
+           0.07707627685756153,
+           0.08615556684643114,
+           0.09330790615208927,
+           0.09875614948627691,
+           0.1027865095596554,
+           0.10574071257344515,
+           0.10800652904815666,
+           0.11000692328485148,
+           0.11218810170058309,
+           0.11500677014985987,
+           0.11891693236851793,
+           0.12435657528209029,
+           0.1317345917453272,
+           0.14141828718088403,
+           0.15372180364526,
+           0.16889577337288403,
+           0.18711848435368214,
+           0.20848880370644388,
+           0.23302106142509513,
+           0.2606420485647103,
+           0.291190231301433,
+           0.3244172268536475,
+           0.3599915303722205,
+           0.39750442501555067,
+           0.4364779519442142,
+           0.47637476429172715,
+           0.5166096406172714,
+           0.5565623901481188,
+           0.5955918453686069,
+           0.6330506081454683,
+           0.6683001943514958,
+           0.7007262094157096,
+           0.7297531837287713,
+           0.7548587024843498,
+           0.7755864792310021,
+           0.7915580458111998,
+           0.8024827629245324,
+           0.8081658945180447,
+           0.8085145346407645,
+           0.8035412262027539,
+           0.7933651660178723,
+           0.7782109482458751,
+           0.7584048574741673,
+           0.7343687817464072,
+           0.7066118734072492,
+           0.6757201402773766,
+           0.6423442000579864,
+           0.6071854757489101,
+           0.5709811481432048,
+           0.5344882121874107,
+           0.49846700640944464,
+           0.46366459815680827,
+           0.4307984117152144,
+           0.40054048137606246,
+           0.37350269730327246,
+           0.35022338895429206,
+           0.33115555939308194,
+           0.31665704485446133,
+           0.3069828283251733,
+           0.3022796848048192,
+           0.30258328054201145,
+           0.3078177902544424,
+           0.31779803655404004,
+           0.3322340959642201,
+           0.3507382574902318,
+           0.37283416410518194,
+           0.3979679160929277,
+           0.4255208691905604,
+           0.4548238210098365,
+           0.48517224723948504,
+           0.515842225405214,
+           0.5461066690547246,
+           0.5752514894871642,
+           0.6025913056815694,
+           0.62748433578953,
+           0.649346125111866,
+           0.6676617953282986,
+           0.6819965371413846,
+           0.6920041124953532,
+           0.6974331820400869,
+           0.6981313273001826,
+           0.6940466937453095,
+           0.6852272392379186,
+           0.6718176307192469,
+           0.6540538890467699,
+           0.6322559362139037,
+           0.6068182494347889,
+           0.5781988715358397,
+           0.5469070656677208,
+           0.5134899336034345,
+           0.478518340071,
+           0.44257250013515687,
+           0.406227592259519,
+           0.3700397562394205,
+           0.33453282281273894,
+           0.30018610076997476,
+           0.26742351834785955,
+           0.23660437935459672,
+           0.20801595177145277,
+           0.18186805859403105,
+           0.15828978863589843,
+           0.13732839023511736,
+           0.11895035466448226,
+           0.10304463996430907,
+           0.08942793130374216,
+           0.07785178220500605,
+           0.06801143333356693,
+           0.059556063258695564,
+           0.052100189680843886,
+           0.04523591099997367,
+           0.03854565747383225,
+           0.03161510909659664,
+           0.024045934011273144,
+           0.015468006827030817,
+           0.005550780495074841,
+           -0.005986491966028116,
+           -0.019365959192429807,
+           -0.03474403252983749,
+           -0.05220609884739851,
+           -0.07176322913434169,
+           -0.09335097478558466,
+           -0.11683028897243344,
+           -0.14199055497484886,
+           -0.16855464823149163,
+           -0.19618590554243454,
+           -0.22449682469226218,
+           -0.25305927202488004,
+           -0.28141593536199966,
+           -0.30909272614137234,
+           -0.33561180861919954,
+           -0.3605049161073852,
+           -0.3833266049695598,
+           -0.4036670967331547,
+           -0.42116436721843636,
+           -0.43551515884573455,
+           -0.4464846178464415,
+           -0.45391429134989025,
+           -0.45772825943129297,
+           -0.4579372231963475,
+           -0.45464042070737765,
+           -0.44802529676467623,
+           -0.4383649088959498,
+           -0.4260131089713316,
+           -0.41139759622485783,
+           -0.3950109917136823,
+           -0.3774001350210624,
+           -0.35915385002939054,
+           -0.3408894666917811,
+           -0.3232384188961409,
+           -0.30683126389555365,
+           -0.2922824857160654,
+           -0.2801754529984824,
+           -0.2710479006552518,
+           -0.265378294522963,
+           -0.2635734190878004,
+           -0.2659575007984776,
+           -0.272763144112138,
+           -0.2841243150910619,
+           -0.30007155910311256,
+           -0.3205295861465606,
+           -0.3453173008100127,
+           -0.3741502952685944,
+           -0.4066457644402939,
+           -0.44232974393265684,
+           -0.480646515133769,
+           -0.5209699691246311,
+           -0.5626166733079347,
+           -0.6048603429377865,
+           -0.6469473851255535,
+           -0.6881131562447326,
+           -0.7275985556248812,
+           -0.7646665694620884,
+           -0.7986183792106933,
+           -0.8288086583593787,
+           -0.8546597002080085,
+           -0.8756740466009103,
+           -0.8914453228773364,
+           -0.9016670267153203,
+           -0.9061390670410373,
+           -0.9047719025736968,
+           -0.8975881865770479,
+           -0.884721883606326,
+           -0.8664148840332204,
+           -0.8430112014422992,
+           -0.8149488951786413,
+           -0.7827499139995997,
+           -0.7470081056418493,
+           -0.7083756799755947,
+           -0.667548449246368,
+           -0.6252501968397316,
+           -0.5822165453790017,
+           -0.5391787053243369,
+           -0.4968474863490609,
+           -0.45589794561886277,
+           -0.4169550299118144,
+           -0.3805805427339314,
+           -0.3472617338583755,
+           -0.3174017678933243,
+           -0.2913122815830917,
+           -0.26920818773670085,
+           -0.25120482824352675,
+           -0.23731752094937988,
+           -0.22746348665366925,
+           -0.2214660845916063,
+           -0.21906122890915314,
+           -0.21990580619309588,
+           -0.22358786636764555,
+           -0.22963831737650228,
+           -0.23754381905188685,
+           -0.24676054427336708,
+           -0.2567284565899375,
+           -0.2668857433597671,
+           -0.2766830423747781,
+           -0.2855971078780577,
+           -0.2931435786226607,
+           -0.29888853571395235,
+           -0.3024585707700547,
+           -0.3035491245818702,
+           -0.30193090194157335,
+           -0.29745421847888986,
+           -0.2900511889256838,
+           -0.2797357218661796,
+           -0.26660134231862803,
+           -0.2508169190165168,
+           -0.23262042661749072,
+           -0.21231092292618028,
+           -0.19023896632348816,
+           -0.16679573782088639,
+           -0.14240116452440246,
+           -0.11749136599339124,
+           -0.09250576140164335,
+           -0.06787418314933412,
+           -0.044004341449148596,
+           -0.021269974457218586,
+           -1.904440873366374e-16
+          ],
+          [
+           0,
+           0.018079711093681262,
+           0.03422614664471808,
+           0.04833726817973926,
+           0.06038232903736794,
+           0.07040292938550795,
+           0.07851203444071038,
+           0.08489097706534504,
+           0.089784518664339,
+           0.09349409322121786,
+           0.09636940710891113,
+           0.09879861076787191,
+           0.1011972963544062,
+           0.10399660705374547,
+           0.1076307681139514,
+           0.11252436615784613,
+           0.11907971153742725,
+           0.12766461818322564,
+           0.13860092655819828,
+           0.15215407815473447,
+           0.1685240248863761,
+           0.18783772433450063,
+           0.2101434329103862,
+           0.23540696454537835,
+           0.26351003362772085,
+           0.29425074877903,
+           0.3273462700047107,
+           0.36243758711032936,
+           0.39909632341696316,
+           0.4368334170832912,
+           0.47510948405080855,
+           0.5133466229885286,
+           0.5509413847292441,
+           0.58727859752447,
+           0.6217457157981681,
+           0.6537473445639499,
+           0.6827195846995784,
+           0.708143846048194,
+           0.7295597858231415,
+           0.7465770488015359,
+           0.758885512858728,
+           0.7662637778791652,
+           0.7685856771515787,
+           0.7658246370262246,
+           0.7580557617471075,
+           0.7454555747283117,
+           0.7282994037945919,
+           0.7069564546769357,
+           0.68188267295333,
+           0.6536115482820849,
+           0.622743064871263,
+           0.5899310474301942,
+           0.5558691912407762,
+           0.5212760974942167,
+           0.48687965985753634,
+           0.45340116474605374,
+           0.4215394755686425,
+           0.39195567008080695,
+           0.3652584899440727,
+           0.34199094288461096,
+           0.32261837091757184,
+           0.3075182636062978,
+           0.29697205409265176,
+           0.29115908866694096,
+           0.29015290908431923,
+           0.29391993193279553,
+           0.30232055245130096,
+           0.31511264266875383,
+           0.33195735698550227,
+           0.35242710372616587,
+           0.3760154900832489,
+           0.4021490014835722,
+           0.43020013586730493,
+           0.4595016796510041,
+           0.4893617860621136,
+           0.519079498705411,
+           0.5479603540714738,
+           0.5753316964292385,
+           0.6005573471474247,
+           0.6230512877327629,
+           0.6422900413154464,
+           0.6578234703113596,
+           0.6692837477197082,
+           0.6763923049826911,
+           0.6789646094103923,
+           0.6769126776177237,
+           0.6702452869087361,
+           0.6590659027073441,
+           0.6435683955887664,
+           0.6240306748497858,
+           0.600806415559233,
+           0.5743151014304447,
+           0.545030645548916,
+           0.5134688840089328,
+           0.4801742630679428,
+           0.4457060579092335,
+           0.41062447010595754,
+           0.37547695120832564,
+           0.34078509155218695,
+           0.30703239664786675,
+           0.27465324879854425,
+           0.24402331956053275,
+           0.2154516601179814,
+           0.18917465258628405,
+           0.1653519568023465,
+           0.14406453553378193,
+           0.12531478754787503,
+           0.10902876397368444,
+           0.09506039022645851,
+           0.0831975647784022,
+           0.07316995853286665,
+           0.06465829568049061,
+           0.05730485975754547,
+           0.05072493811549254,
+           0.044518894905073096,
+           0.038284547549680845,
+           0.031629514901665004,
+           0.024183207001588974,
+           0.01560813654016974,
+           0.005610250488717596,
+           -0.0060519935564849504,
+           -0.019560048644147864,
+           -0.03502940035180897,
+           -0.05250554775199308,
+           -0.07196195332692948,
+           -0.09330002025845394,
+           -0.11635110254809825,
+           -0.14088050026309712,
+           -0.16659334020669822,
+           -0.1931421927966776,
+           -0.22013623016365405,
+           -0.24715168961649403,
+           -0.27374337170918306,
+           -0.29945687407648053,
+           -0.32384124170759615,
+           -0.3464617019316662,
+           -0.36691214842635816,
+           -0.3848270431504573,
+           -0.39989241814694254,
+           -0.4118556803564299,
+           -0.420533951408524,
+           -0.42582071011462036,
+           -0.4276905471890579,
+           -0.4262018885420539,
+           -0.4214975941556611,
+           -0.4138033928125441,
+           -0.40342416746854814,
+           -0.39073816048150056,
+           -0.37618922086735895,
+           -0.36027726592143994,
+           -0.34354717565410753,
+           -0.3265763793825017,
+           -0.30996142845534613,
+           -0.2943038765827331,
+           -0.28019580888865353,
+           -0.268205372086009,
+           -0.2588626607834145,
+           -0.25264630877639765,
+           -0.24997111937567287,
+           -0.2511770457196551,
+           -0.2565198011511407,
+           -0.26616334184621615,
+           -0.28017441987921005,
+           -0.29851935585603273,
+           -0.3210631273413709,
+           -0.34757081383219246,
+           -0.377711382345826,
+           -0.41106374118260536,
+           -0.4471249344761433,
+           -0.48532029810765376,
+           -0.5250153497141425,
+           -0.5655291430422335,
+           -0.6061487808381036,
+           -0.6461447517116631,
+           -0.6847867356831828,
+           -0.7213595109310466,
+           -0.7551785909185612,
+           -0.7856052266780948,
+           -0.8120604234450889,
+           -0.8340376437196876,
+           -0.8511138996391698,
+           -0.8629589755249858,
+           -0.8693425657033399,
+           -0.8701391621135266,
+           -0.8653305796127558,
+           -0.8550060629614066,
+           -0.8393599768647628,
+           -0.8186871377604973,
+           -0.7933759018822544,
+           -0.7638991771419658,
+           -0.7308035752706673,
+           -0.6946969642545486,
+           -0.6562347183459067,
+           -0.616104992920139,
+           -0.5750133734709348,
+           -0.5336672615641526,
+           -0.49276036529246087,
+           -0.4529576575905248,
+           -0.4148811528056738,
+           -0.3790968305083321,
+           -0.3461030062137418,
+           -0.3163204122083486,
+           -0.29008420894284975,
+           -0.26763809953285667,
+           -0.2491306679872759,
+           -0.23461400714964842,
+           -0.22404464633892193,
+           -0.21728673269438825,
+           -0.21411736564238798,
+           -0.21423393205013372,
+           -0.21726324178415,
+           -0.22277222071528072,
+           -0.23027988174609582,
+           -0.23927026506090374,
+           -0.24920601721669314,
+           -0.25954226541371567,
+           -0.2697404386080612,
+           -0.27928169114237905,
+           -0.28767959714539343,
+           -0.2944918047438011,
+           -0.29933036759574017,
+           -0.3018705066570742,
+           -0.30185759652316996,
+           -0.2991122170935963,
+           -0.29353316150744335,
+           -0.28509834402240813,
+           -0.27386360543030847,
+           -0.25995946735688824,
+           -0.24358593903272863,
+           -0.2250055295333118,
+           -0.20453466383115881,
+           -0.18253374114694432,
+           -0.15939610802717485,
+           -0.1355362454680574,
+           -0.11137748858151073,
+           -0.0873396082874924,
+           -0.06382658705084689,
+           -0.04121491470771608,
+           -0.019842716107259486,
+           -1.7696995801236689e-16
+          ],
+          [
+           0,
+           0.01665860683072475,
+           0.03142305677696039,
+           0.044230477548482534,
+           0.05508691788053341,
+           0.06406727480880174,
+           0.07131327843928047,
+           0.07702958344631655,
+           0.08147806613146878,
+           0.08497047300313788,
+           0.08785961029375206,
+           0.09052930251066621,
+           0.09338338103137882,
+           0.09683399005996658,
+           0.10128951628205013,
+           0.1071424597949672,
+           0.11475756704813028,
+           0.12446054150855353,
+           0.13652763467647253,
+           0.1511763992269897,
+           0.16855785795225187,
+           0.18875030751420932,
+           0.21175493564577896,
+           0.23749338535823522,
+           0.2658073510447278,
+           0.2964602403259642,
+           0.32914088333818387,
+           0.3634692192198008,
+           0.3990038391133786,
+           0.43525121733123445,
+           0.4716764186368077,
+           0.5077150309746027,
+           0.5427860404195962,
+           0.5763053394445805,
+           0.6076995414834944,
+           0.636419764676799,
+           0.6619550458993332,
+           0.6838450527643751,
+           0.7016917761346358,
+           0.7151699084118701,
+           0.7240356429854296,
+           0.7281336669766759,
+           0.7274021619350385,
+           0.7218756743927328,
+           0.7116857690199498,
+           0.6970594303010993,
+           0.6783152328758019,
+           0.655857354627935,
+           0.6301675589389918,
+           0.6017953219624717,
+           0.5713463261072164,
+           0.5394695810220234,
+           0.5068434672607112,
+           0.4741610246369004,
+           0.4421148263838144,
+           0.411381791138258,
+           0.3826082871918222,
+           0.3563958773264304,
+           0.3332880380150992,
+           0.3137581641680394,
+           0.2981991404823996,
+           0.28691472353922987,
+           0.2801129359780048,
+           0.27790162640678084,
+           0.280286297332977,
+           0.2871702495749399,
+           0.2983570366467441,
+           0.313555167834712,
+           0.33238494543531866,
+           0.354387271194083,
+           0.37903421059743486,
+           0.40574106244858643,
+           0.43387964610061397,
+           0.46279249067021205,
+           0.49180759018613807,
+           0.5202533764205436,
+           0.5474735573919155,
+           0.5728414742901281,
+           0.5957736427234391,
+           0.6157421653840304,
+           0.6322857319365497,
+           0.6450189574322804,
+           0.6536398519541856,
+           0.6579352604754142,
+           0.6577841619180994,
+           0.6531587688933267,
+           0.6441234232907052,
+           0.6308313364442814,
+           0.6135192747135253,
+           0.592500340705485,
+           0.5681550458185656,
+           0.5409209102013275,
+           0.5112808606100029,
+           0.47975072418618825,
+           0.4468661362030565,
+           0.4131691918740443,
+           0.3791951761106795,
+           0.3454597005903112,
+           0.31244656479082317,
+           0.2805966371120215,
+           0.25029802437051296,
+           0.22187776354516742,
+           0.1955952295448962,
+           0.17163740799063415,
+           0.15011613368497195,
+           0.1310673448077715,
+           0.11445235120171093,
+           0.10016106369898661,
+           0.08801708158147774,
+           0.07778448821230154,
+           0.06917616180537883,
+           0.06186337028805564,
+           0.05548638720809614,
+           0.04966584043645247,
+           0.04401448764510522,
+           0.03814910263155732,
+           0.031702154756641676,
+           0.024332970094489183,
+           0.015738077192382176,
+           0.005660462232939175,
+           -0.0061025126802244515,
+           -0.019692739168233872,
+           -0.03518671058676203,
+           -0.052592713844916476,
+           -0.07184994226777981,
+           -0.09282955652785642,
+           -0.11533766973684763,
+           -0.13912018242384763,
+           -0.16386934460837274,
+           -0.18923187673979472,
+           -0.2148184400751976,
+           -0.24021421115584018,
+           -0.26499028533658153,
+           -0.2887156115856935,
+           -0.3109691455927066,
+           -0.3313519009982517,
+           -0.34949857949145935,
+           -0.3650884696019268,
+           -0.377855321034226,
+           -0.387595925943318,
+           -0.39417717002928526,
+           -0.3975413539647441,
+           -0.3977096285276325,
+           -0.3947834338325933,
+           -0.3889438830662736,
+           -0.38044908288878954,
+           -0.3696294348721975,
+           -0.3568810137000598,
+           -0.34265716706132887,
+           -0.3274585279990011,
+           -0.31182167176282205,
+           -0.2963066849199495,
+           -0.28148394368867663,
+           -0.26792042042843933,
+           -0.25616585137309245,
+           -0.2467391046554662,
+           -0.24011508526361575,
+           -0.23671250282444278,
+           -0.23688280926656946,
+           -0.2409005869108926,
+           -0.24895563400403953,
+           -0.2611469549521568,
+           -0.2774788174908153,
+           -0.29785898983407477,
+           -0.3220992186797334,
+           -0.34991795508209356,
+           -0.3809452809560095,
+           -0.41472993567605976,
+           -0.4507482911911312,
+           -0.4884150765424928,
+           -0.5270956098235113,
+           -0.5661192585088554,
+           -0.6047938186282013,
+           -0.6424204802197638,
+           -0.6783090314467193,
+           -0.7117929470742227,
+           -0.7422440088603032,
+           -0.769086115775763,
+           -0.7918079605927636,
+           -0.8099742758231752,
+           -0.8232353856081818,
+           -0.8313348401462677,
+           -0.834114954627742,
+           -0.8315201243180113,
+           -0.8235978401916615,
+           -0.8104973840820128,
+           -0.7924662373494603,
+           -0.769844291248349,
+           -0.7430559991699252,
+           -0.712600659495369,
+           -0.6790410617306644,
+           -0.6429907668502722,
+           -0.6051003244258769,
+           -0.5660427533989312,
+           -0.5264986296915669,
+           -0.48714113185591534,
+           -0.44862139545719915,
+           -0.4115545179009028,
+           -0.37650653818646984,
+           -0.34398269103894474,
+           -0.31441720266638606,
+           -0.2881648568202783,
+           -0.2654945158598185,
+           -0.24658473323056468,
+           -0.2315215423599309,
+           -0.22029845371697523,
+           -0.21281863799546083,
+           -0.20889922038125824,
+           -0.20827755995951494,
+           -0.21061934075092206,
+           -0.21552825780171453,
+           -0.22255704423689704,
+           -0.23121955412890946,
+           -0.241003592180929,
+           -0.2513841651413207,
+           -0.26183682192564034,
+           -0.27185074979402424,
+           -0.28094130257723116,
+           -0.288661653620718,
+           -0.29461329038030404,
+           -0.2984550988249377,
+           -0.29991082317915674,
+           -0.29877472911608965,
+           -0.29491534520913776,
+           -0.2882772070843103,
+           -0.2788805800319926,
+           -0.2668191875433907,
+           -0.2522560240325138,
+           -0.23541737861382742,
+           -0.21658524201028095,
+           -0.1960883093350665,
+           -0.17429182660770606,
+           -0.15158655755614114,
+           -0.12837716880915614,
+           -0.10507034546581391,
+           -0.08206295490209801,
+           -0.059730574402800225,
+           -0.03841668785720714,
+           -0.018422838601824913,
+           -1.6367277411403843e-16
+          ],
+          [
+           0,
+           0.015276390442690474,
+           0.02871731077278387,
+           0.0402963453344223,
+           0.05005299590065651,
+           0.05809157982931345,
+           0.06457829546537476,
+           0.06973652905163726,
+           0.07384052353128526,
+           0.07720757271786265,
+           0.0801889432733099,
+           0.08315976077977744,
+           0.08650812405053356,
+           0.0906237329840844,
+           0.09588632917618746,
+           0.1026542548011209,
+           0.11125343378181904,
+           0.1219670700093552,
+           0.1350263405620891,
+           0.1506023379199889,
+           0.1687994846566614,
+           0.18965060777256898,
+           0.21311381860686426,
+           0.23907129915604694,
+           0.267330047758295,
+           0.2976245876673302,
+           0.32962159227509774,
+           0.3629263318953644,
+           0.39709080031723576,
+           0.4316233359544894,
+           0.4659995134491352,
+           0.4996740480238132,
+           0.53209342757313,
+           0.5627089671406529,
+           0.590989967576149,
+           0.6164366551520651,
+           0.6385925818904636,
+           0.657056177265102,
+           0.6714911605544449,
+           0.6816355489951178,
+           0.6873090294059242,
+           0.688418499338422,
+           0.6849616271329202,
+           0.6770283274663544,
+           0.6648000989206144,
+           0.6485472215564231,
+           0.6286238641892128,
+           0.6054612017612666,
+           0.5795586916431691,
+           0.5514737026853391,
+           0.5218097312679667,
+           0.4912034734665497,
+           0.46031105089684904,
+           0.429793709120771,
+           0.400303321150547,
+           0.3724680342375042,
+           0.34687839562431333,
+           0.3240742823265667,
+           0.3045329415401584,
+           0.2886584223873038,
+           0.2767726470399753,
+           0.2691083305857636,
+           0.26580391526525093,
+           0.2669006369740539,
+           0.2723417913466427,
+           0.2819742145525211,
+           0.2955519414072197,
+           0.3127419518078435,
+           0.3331318670992624,
+           0.3562394119621126,
+           0.38152341590339695,
+           0.40839609242973895,
+           0.43623630436132704,
+           0.4644035012136257,
+           0.4922519996717812,
+           0.5191452712595304,
+           0.5444699025146769,
+           0.5676489022811612,
+           0.5881540478699736,
+           0.6055169863912636,
+           0.6193388389012211,
+           0.6292980923562917,
+           0.6351566067949372,
+           0.6367636116208426,
+           0.634057614191491,
+           0.6270661949042521,
+           0.615903714361751,
+           0.6007670087254235,
+           0.5819291977906438,
+           0.5597317754532234,
+           0.5345751929836446,
+           0.5069081808914095,
+           0.47721608429189305,
+           0.4460085088830249,
+           0.4138065893731678,
+           0.38113019913533125,
+           0.34848541885093587,
+           0.3163525730013105,
+           0.2851751265152433,
+           0.25534971012424657,
+           0.2272175126300983,
+           0.20105724213073348,
+           0.1770798172030897,
+           0.15542490414719465,
+           0.13615936879081134,
+           0.11927766223983438,
+           0.10470411057322812,
+           0.09229703006390218,
+           0.08185454327340247,
+           0.07312192847652063,
+           0.06580029639420598,
+           0.05955635510932117,
+           0.05403299713338342,
+           0.048860422550303484,
+           0.04366749947877832,
+           0.03809305807642953,
+           0.03179681707096704,
+           0.02446965226569005,
+           0.015842934353988626,
+           0.005696688228912674,
+           -0.0061336428469810425,
+           -0.019752008134729836,
+           -0.035198273988707354,
+           -0.05244655585917606,
+           -0.07140540421760626,
+           -0.0919198424198062,
+           -0.1137752060688619,
+           -0.13670268623907866,
+           -0.16038643417281345,
+           -0.18447204390233385,
+           -0.20857619272706632,
+           -0.23229718852504422,
+           -0.2552261482889152,
+           -0.27695851468492133,
+           -0.29710560729576135,
+           -0.3153059027962314,
+           -0.3312357437009481,
+           -0.34461918839729205,
+           -0.35523673562163305,
+           -0.362932683854929,
+           -0.3676209196335927,
+           -0.36928896766492486,
+           -0.3680001789389614,
+           -0.3638939796635314,
+           -0.3571841526542232,
+           -0.34815517256681056,
+           -0.3371566658210069,
+           -0.32459611399060584,
+           -0.3109299646209115,
+           -0.2966533547406851,
+           -0.2822886887173943,
+           -0.26837334263666934,
+           -0.2554467912883492,
+           -0.2440374704944029,
+           -0.23464969647922865,
+           -0.22775096501129638,
+           -0.22375994608419764,
+           -0.2230354751004858,
+           -0.22586681921348634,
+           -0.23246546819754796,
+           -0.2429586636568036,
+           -0.2573848394039878,
+           -0.27569110043752826,
+           -0.2977328192216689,
+           -0.3232753771195544,
+           -0.3519980270867526,
+           -0.38349980237051245,
+           -0.41730734623885946,
+           -0.452884490906176,
+           -0.48964337098211397,
+           -0.5269568190058016,
+           -0.5641717588711869,
+           -0.6006232879895755,
+           -0.63564912149381,
+           -0.6686040621052283,
+           -0.6988741577079193,
+           -0.7258902152540163,
+           -0.7491403542086628,
+           -0.7681813049869368,
+           -0.7826481872029395,
+           -0.7922625383339338,
+           -0.7968384047330432,
+           -0.7962863527997354,
+           -0.7906153074235643,
+           -0.7799321763550763,
+           -0.7644392716751887,
+           -0.7444295917539381,
+           -0.7202800777419298,
+           -0.692443006492779,
+           -0.6614357257108385,
+           -0.6278289759920467,
+           -0.5922340773365781,
+           -0.5552892838672159,
+           -0.5176456292599629,
+           -0.4799525963378259,
+           -0.442843947142323,
+           -0.406924044525157,
+           -0.3727549830399522,
+           -0.3408448260018831,
+           -0.3116372175496539,
+           -0.2855026040919354,
+           -0.26273125950770543,
+           -0.24352826389131438,
+           -0.22801053759271506,
+           -0.21620598198897625,
+           -0.20805472707621156,
+           -0.2034124348556523,
+           -0.20205555785966722,
+           -0.203688405239654,
+           -0.20795182576506854,
+           -0.21443327891080763,
+           -0.22267803286473306,
+           -0.23220120254792584,
+           -0.24250032222162402,
+           -0.25306813639059095,
+           -0.2634052897461386,
+           -0.273032601869508,
+           -0.28150262518703584,
+           -0.2884102048881733,
+           -0.29340178665704186,
+           -0.29618325142802887,
+           -0.29652609510234745,
+           -0.29427181427035454,
+           -0.2893344053809443,
+           -0.2817009333121113,
+           -0.2714301747027906,
+           -0.2586493904622975,
+           -0.2435493293482492,
+           -0.22637760920661473,
+           -0.20743066328000184,
+           -0.1870444748931207,
+           -0.16558435392313978,
+           -0.1434340320098639,
+           -0.12098436987428329,
+           -0.0986219789921107,
+           -0.07671806099932199,
+           -0.05561776157230782,
+           -0.035630321304380964,
+           -0.017020284662138358,
+           -1.5063995523025341e-16
+          ],
+          [
+           0,
+           0.01394087157888465,
+           0.026122578148348383,
+           0.03655210147727283,
+           0.045298783162516475,
+           0.05249230105842002,
+           0.05831893572633484,
+           0.0630162229883281,
+           0.06686613105094914,
+           0.07018693954734813,
+           0.07332403223884064,
+           0.07663984414237356,
+           0.08050322676489736,
+           0.08527851133922396,
+           0.09131455904645902,
+           0.09893408893422682,
+           0.10842356853936261,
+           0.12002393922685602,
+           0.13392242827551512,
+           0.1502456732629722,
+           0.16905435198009347,
+           0.1903394737372415,
+           0.21402044643980253,
+           0.23994498924056334,
+           0.26789091403378323,
+           0.2975697517037288,
+           0.32863215206518276,
+           0.3606749410143298,
+           0.39324967568835173,
+           0.4258724994891466,
+           0.4580350646470015,
+           0.48921626145349234,
+           0.5188944711106478,
+           0.5465600439000524,
+           0.5717276964742654,
+           0.5939485217353816,
+           0.6128213120259867,
+           0.6280029110619366,
+           0.6392173318451139,
+           0.6462634061915196,
+           0.6490207658154353,
+           0.6474539942958875,
+           0.6416148327618848,
+           0.6316423687085487,
+           0.6177611858601751,
+           0.600277502241468,
+           0.5795733723971737,
+           0.5560990768148799,
+           0.5303638658964654,
+           0.5029252661988262,
+           0.4743771921267885,
+           0.44533713593269436,
+           0.4164327320209862,
+           0.3882880075948476,
+           0.3615096402115538,
+           0.33667354361381047,
+           0.31431209624522105,
+           0.294902312298773,
+           0.2788552333338564,
+           0.2665067899538577,
+           0.25811034845195835,
+           0.2538311175450124,
+           0.2537425462893658,
+           0.2578247970775942,
+           0.26596532839825954,
+           0.27796157199846266,
+           0.2935256394377943,
+           0.31229094496907056,
+           0.33382058639319645,
+           0.3576172841118707,
+           0.3831346420463167,
+           0.40978946328706706,
+           0.43697482903131946,
+           0.4640736321334207,
+           0.4904722468493429,
+           0.5155740143224378,
+           0.5388122290709556,
+           0.5596623250431186,
+           0.5776529803627356,
+           0.5923758871790618,
+           0.6034939663766686,
+           0.6107478454641202,
+           0.6139604607874437,
+           0.6130396912455778,
+           0.6079789787831029,
+           0.5988559399150724,
+           0.5858290211944785,
+           0.5691322986703611,
+           0.5490685658490468,
+           0.5260008953764276,
+           0.5003428956145239,
+           0.47254791361954157,
+           0.44309746001087125,
+           0.41248914827959865,
+           0.38122445082239337,
+           0.34979657618608384,
+           0.31867876664095485,
+           0.28831330242629377,
+           0.2591014791728158,
+           0.23139479862126328,
+           0.20548758050437457,
+           0.18161116616473785,
+           0.15992984309208602,
+           0.14053857512847936,
+           0.12346257673076896,
+           0.10865872256461445,
+           0.09601873701763951,
+           0.08537406313253361,
+           0.07650226810343905,
+           0.06913480390968861,
+           0.06296590784218367,
+           0.057662399450979035,
+           0.05287410850796837,
+           0.04824465347699905,
+           0.04342228208397345,
+           0.03807048506877527,
+           0.031878101080491876,
+           0.024568644762748316,
+           0.015908611001285714,
+           0.005714535533531239,
+           -0.006141375046192869,
+           -0.019727193248810764,
+           -0.03504890856686547,
+           -0.052049817035603116,
+           -0.07061168043449367,
+           -0.09055762679500697,
+           -0.1116567182906996,
+           -0.13363006885404455,
+           -0.15615835310253515,
+           -0.17889051140169698,
+           -0.20145342408181174,
+           -0.22346230177149132,
+           -0.24453151918366406,
+           -0.26428560699577464,
+           -0.2823701110397807,
+           -0.298462030010218,
+           -0.3122795522750254,
+           -0.3235908289132296,
+           -0.3322215434048216,
+           -0.33806106788958745,
+           -0.3410670308653079,
+           -0.3412681607452505,
+           -0.3387653128570838,
+           -0.333730633164623,
+           -0.3264048590888868,
+           -0.31709280511728494,
+           -0.30615712723286603,
+           -0.294010504404781,
+           -0.2811064163423396,
+           -0.2679287333930002,
+           -0.25498036592837325,
+           -0.24277124600887917,
+           -0.23180593289205292,
+           -0.2225711455612314,
+           -0.21552352958701573,
+           -0.21107796216512184,
+           -0.2095966881611051,
+           -0.21137956168249772,
+           -0.21665564252098654,
+           -0.2255763653614457,
+           -0.2382104626974195,
+           -0.2545407808184658,
+           -0.2744630830541016,
+           -0.2977868867735943,
+           -0.3242383316161104,
+           -0.35346502726278795,
+           -0.38504278096773936,
+           -0.418484059221164,
+           -0.45324799545391997,
+           -0.488751717656619,
+           -0.5243827371182171,
+           -0.5595121129990452,
+           -0.5935080878005147,
+           -0.6257498764706748,
+           -0.6556412872040799,
+           -0.6826238550820902,
+           -0.706189180490829,
+           -0.7258901824952317,
+           -0.7413510026024112,
+           -0.7522753260076295,
+           -0.7584529247156617,
+           -0.7597642689651805,
+           -0.7561830991336498,
+           -0.7477768986534585,
+           -0.734705258251379,
+           -0.7172161718225801,
+           -0.6956403532519244,
+           -0.6703837103084205,
+           -0.6419181552268564,
+           -0.6107709706989305,
+           -0.5775129837779588,
+           -0.5427458278404548,
+           -0.5070885935801073,
+           -0.47116418353757006,
+           -0.43558569057507296,
+           -0.40094311885790623,
+           -0.36779075636467234,
+           -0.3366354909632437,
+           -0.30792633809024816,
+           -0.28204541766073254,
+           -0.259300581770157,
+           -0.2399198539292036,
+           -0.22404779600503735,
+           -0.21174387183230342,
+           -0.20298282776841187,
+           -0.19765706149956985,
+           -0.195580902360118,
+           -0.19649668048622757,
+           -0.20008241940982202,
+           -0.20596094825147337,
+           -0.2137101964259642,
+           -0.22287440653455268,
+           -0.2329759805365632,
+           -0.24352766085628302,
+           -0.2540447420975376,
+           -0.26405701063065773,
+           -0.27312011841908124,
+           -0.2808261138137631,
+           -0.28681287523105176,
+           -0.2907722230429389,
+           -0.2924565198934683,
+           -0.29168360912233715,
+           -0.2883399840252324,
+           -0.2823821262214059,
+           -0.2738359982839026,
+           -0.2627947228368351,
+           -0.2494145263553874,
+           -0.23390906976387207,
+           -0.21654232851752334,
+           -0.19762022116111208,
+           -0.17748121647707615,
+           -0.15648617449455432,
+           -0.1350076952060381,
+           -0.11341926037397923,
+           -0.09208445802681975,
+           -0.07134657604801095,
+           -0.05151884074455732,
+           -0.03287555871959381,
+           -0.01564439621962,
+           -1.3795209405752813e-16
+          ],
+          [
+           0,
+           0.01265892436779199,
+           0.023650478631931173,
+           0.033011687111856716,
+           0.04083790619353218,
+           0.047279993416877844,
+           0.052539899842719937,
+           0.056864800273030584,
+           0.06053991434653666,
+           0.06388020610172085,
+           0.06722117940964749,
+           0.07090901096805394,
+           0.07529028069233142,
+           0.08070157086912465,
+           0.087459210051068,
+           0.095849435237139,
+           0.10611923644986417,
+           0.11846813161183739,
+           0.13304109703403624,
+           0.14992285041250097,
+           0.16913364969055064,
+           0.19062673331312596,
+           0.21428748621948326,
+           0.23993437241750015,
+           0.2673216302446268,
+           0.29614368156752097,
+           0.326041162330272,
+           0.3566084401326376,
+           0.3874024459571766,
+           0.4179526127431834,
+           0.44777168410030543,
+           0.4763671328169981,
+           0.5032529115578667,
+           0.5279612477114696,
+           0.5500541910294069,
+           0.569134626595545,
+           0.5848564767089187,
+           0.5969338332056177,
+           0.6051487861625634,
+           0.6093577452368185,
+           0.609496085368079,
+           0.6055809883499922,
+           0.5977123948904373,
+           0.5860720271799088,
+           0.570920488560171,
+           0.5525924934907147,
+           0.53149032650363,
+           0.5080756720989881,
+           0.4828599974963581,
+           0.45639370583675626,
+           0.4292543079399506,
+           0.4020338853073355,
+           0.37532613510753327,
+           0.3497132989375539,
+           0.3257532809345506,
+           0.30396725721825774,
+           0.28482806774896846,
+           0.26874966374654097,
+           0.2560778592613374,
+           0.24708260490957426,
+           0.24195196592254828,
+           0.24078794638074352,
+           0.2436042577873583,
+           0.2503260840433641,
+           0.2607918475380256,
+           0.2747569336159616,
+           0.2918992842777874,
+           0.3118267277437994,
+           0.3340858695329273,
+           0.35817233397637177,
+           0.38354211348626555,
+           0.4096237571977685,
+           0.4358311114162373,
+           0.46157631208771693,
+           0.48628272455770577,
+           0.509397528298456,
+           0.5304036539968799,
+           0.5488307971521272,
+           0.5642652557108238,
+           0.5763583686829674,
+           0.5848333674001317,
+           0.5894904902377562,
+           0.5902102542555465,
+           0.5869548222610629,
+           0.5797674501606738,
+           0.5687700459884346,
+           0.5541589175543651,
+           0.536198829112832,
+           0.5152155277568856,
+           0.49158693641329365,
+           0.46573324146771183,
+           0.4381061284379635,
+           0.4091774381280506,
+           0.3794275278878055,
+           0.3493336276944563,
+           0.319358478661148,
+           0.28993953234060693,
+           0.2614789730837192,
+           0.2343348031567618,
+           0.20881320190087455,
+           0.18516233666120796,
+           0.16356776537532752,
+           0.14414952955029015,
+           0.12696099291528792,
+           0.1119894364068364,
+           0.09915837544847546,
+           0.08833152184858065,
+           0.07931827115128395,
+           0.07188055797408242,
+           0.06574088770708493,
+           0.06059132378330787,
+           0.05610318628063366,
+           0.051937200463135415,
+           0.047753823432712936,
+           0.04322347359238531,
+           0.038036391195745166,
+           0.031911868771478225,
+           0.02460660739142149,
+           0.01592197815188879,
+           0.005709997261132017,
+           -0.00612214297013735,
+           -0.019609107016758064,
+           -0.03472609171276882,
+           -0.051389180331348414,
+           -0.06945736708491346,
+           -0.08873620024695894,
+           -0.10898294968947897,
+           -0.12991316460407876,
+           -0.15120845054903057,
+           -0.172525262671187,
+           -0.19350448481502144,
+           -0.21378154294588286,
+           -0.2329967864289457,
+           -0.25080586260677784,
+           -0.2668898090239687,
+           -0.2809645935980175,
+           -0.2927898458955538,
+           -0.3021765421320432,
+           -0.30899343209513813,
+           -0.3131720272659394,
+           -0.31471000520889625,
+           -0.31367292493025634,
+           -0.3101941903795152,
+           -0.30447324352767025,
+           -0.2967720133928324,
+           -0.28740969187138127,
+           -0.2767559501535817,
+           -0.26522274977559185,
+           -0.25325493896782403,
+           -0.24131985697486705,
+           -0.22989619562913322,
+           -0.21946238797660372,
+           -0.21048480764615343,
+           -0.2034060695552065,
+           -0.1986337222581915,
+           -0.19652961475288258,
+           -0.19740020602451813,
+           -0.20148806436506025,
+           -0.20896477605853941,
+           -0.21992545003145172,
+           -0.23438496732666306,
+           -0.2522760826864019,
+           -0.27344944113757574,
+           -0.29767552634542255,
+           -0.324648510768923,
+           -0.35399193146021957,
+           -0.3852660708359971,
+           -0.41797688000748184,
+           -0.45158624431746025,
+           -0.48552335753521203,
+           -0.5191969435264813,
+           -0.5520080428327648,
+           -0.5833630669969142,
+           -0.6126868160291425,
+           -0.6394351543123469,
+           -0.663107047511934,
+           -0.6832556775158452,
+           -0.6994983737417185,
+           -0.7115251267984071,
+           -0.7191054838110066,
+           -0.7220936629054434,
+           -0.7204317664744017,
+           -0.7141510178880764,
+           -0.7033709931763683,
+           -0.6882968667545685,
+           -0.6692147373364916,
+           -0.64648514563327,
+           -0.6205349381684779,
+           -0.5918476705137976,
+           -0.560952777519303,
+           -0.5284137668499722,
+           -0.4948157146521131,
+           -0.46075235792047453,
+           -0.42681308674524066,
+           -0.3935701408894706,
+           -0.36156630906400655,
+           -0.33130341599025986,
+           -0.3032318622101665,
+           -0.2777414551230697,
+           -0.2551537375625194,
+           -0.23571598317182912,
+           -0.21959698681413342,
+           -0.20688473427544923,
+           -0.197585989672929,
+           -0.19162779239456063,
+           -0.1888608092162708,
+           -0.18906444260070263,
+           -0.1919535541715406,
+           -0.19718662400362155,
+           -0.20437513260511012,
+           -0.21309392411118702,
+           -0.2228922869409609,
+           -0.23330547252036662,
+           -0.24386636400827008,
+           -0.25411700547151334,
+           -0.2636197076496777,
+           -0.2719674591656409,
+           -0.27879339143365917,
+           -0.2837790710873085,
+           -0.28666142483723756,
+           -0.2872381374797492,
+           -0.2853714034018484,
+           -0.28098995436397456,
+           -0.27408933051716006,
+           -0.264730406414835,
+           -0.25303622808539256,
+           -0.23918725992897333,
+           -0.22341518022218335,
+           -0.20599540035795635,
+           -0.1872385147087859,
+           -0.167480914390585,
+           -0.1470748185681034,
+           -0.12637799077989859,
+           -0.1057434147345816,
+           -0.08550920397669683,
+           -0.06598901275316985,
+           -0.047463201519106636,
+           -0.03017099016583313,
+           -0.014303805757722055,
+           -1.2568205290437762e-16
+          ],
+          [
+           0,
+           0.01143641660225258,
+           0.021310472072603375,
+           0.029685639579628817,
+           0.036679314115255705,
+           0.04245929378051047,
+           0.04723882549677317,
+           0.05127034479741985,
+           0.0548380737461284,
+           0.05824967125265698,
+           0.06182715534342635,
+           0.06589733664547635,
+           0.07078201595119415,
+           0.07678820589345549,
+           0.0841986372842254,
+           0.09326280452882721,
+           0.10418879186522871,
+           0.11713610329923528,
+           0.13220969447552286,
+           0.14945537494934477,
+           0.16885671514303194,
+           0.19033355453545467,
+           0.21374216728251574,
+           0.23887709951090627,
+           0.2654746500163468,
+           0.29321792409798164,
+           0.3217433498284676,
+           0.35064850821368343,
+           0.3795010943934426,
+           0.4078487971454151,
+           0.4352298592406777,
+           0.46118406229567627,
+           0.48526386716329617,
+           0.507045434940894,
+           0.5261392545168034,
+           0.542200110231498,
+           0.5549361375285091,
+           0.5641167350813563,
+           0.5695791283168279,
+           0.5712334108772131,
+           0.5690659266099245,
+           0.563140894266632,
+           0.5536002192702163,
+           0.5406614806353909,
+           0.5246141253362063,
+           0.5058139460153118,
+           0.484675959853217,
+           0.46166584562763335,
+           0.43729013152498875,
+           0.4120853572391335,
+           0.38660645953744477,
+           0.36141465015333174,
+           0.3370650680833823,
+           0.31409449479217805,
+           0.2930094202893157,
+           0.2742747405435877,
+           0.25830335241126284,
+           0.24544689151842697,
+           0.23598783184910682,
+           0.2301331337953822,
+           0.22800959089717443,
+           0.2296609853237148,
+           0.2350471193011254,
+           0.24404474521223846,
+           0.25645037206679755,
+           0.27198488155717954,
+           0.29029984405789544,
+           0.3109853847375922,
+           0.33357941340550185,
+           0.3575779996964047,
+           0.38244664848353654,
+           0.40763220964196395,
+           0.4325751419636236,
+           0.4567218434894039,
+           0.4795367599464315,
+           0.5005139893625674,
+           0.5191881141069065,
+           0.5351440112400374,
+           0.5480254176586845,
+           0.5575420574475239,
+           0.5634751743386938,
+           0.565681351347694,
+           0.5640945415354027,
+           0.5587262774069663,
+           0.5496640706271976,
+           0.5370680574237876,
+           0.5211659871929252,
+           0.5022466913860628,
+           0.4806522057765344,
+           0.4567687508050991,
+           0.4310168011198681,
+           0.40384049602392985,
+           0.37569665683416303,
+           0.347043684805297,
+           0.31833061411750374,
+           0.2899865884662669,
+           0.2624110172010412,
+           0.235964648070017,
+           0.2109617689332761,
+           0.1876637209403486,
+           0.16627387139247984,
+           0.1469341566946681,
+           0.12972326540412088,
+           0.11465648941876501,
+           0.10168722887749361,
+           0.09071009442910558,
+           0.081565510219511,
+           0.07404568325465066,
+           0.06790177066036622,
+           0.06285204662998711,
+           0.05859084626375216,
+           0.05479804466919532,
+           0.051148817070928644,
+           0.04732341957780868,
+           0.043016730817048696,
+           0.037947301842603184,
+           0.03186567536647816,
+           0.02456175509194785,
+           0.01587103123956868,
+           0.005679498602800566,
+           -0.006072862121415517,
+           -0.019390131286423713,
+           -0.03422007706943716,
+           -0.05045537226479346,
+           -0.06793636969898885,
+           -0.08645536406598146,
+           -0.1057622290081152,
+           -0.1255712821158787,
+           -0.14556919810837454,
+           -0.1654237626117869,
+           -0.18479323638681636,
+           -0.20333608314695806,
+           -0.22072080368969552,
+           -0.2366356152062494,
+           -0.250797717451608,
+           -0.262961896886664,
+           -0.272928235723314,
+           -0.28054871462544184,
+           -0.28573252510638736,
+           -0.28844993974125444,
+           -0.2887346243833368,
+           -0.28668431573945985,
+           -0.2824598289413986,
+           -0.2762824021170077,
+           -0.2684294273533647,
+           -0.25922865879049417,
+           -0.2490510278472666,
+           -0.23830223177001505,
+           -0.22741329389286483,
+           -0.21683032138812014,
+           -0.20700370816460614,
+           -0.19837704637680642,
+           -0.1913760193230816,
+           -0.18639755108291206,
+           -0.1837994839837789,
+           -0.18389104398035322,
+           -0.1869243365222064,
+           -0.19308709189322684,
+           -0.20249684989005284,
+           -0.21519673976995163,
+           -0.2311529734633892,
+           -0.2502541290364108,
+           -0.2723122583042287,
+           -0.2970658083947181,
+           -0.3241843030206578,
+           -0.35327468632499376,
+           -0.3838891914703465,
+           -0.4155345586561727,
+           -0.4476823938913002,
+           -0.4797804314522817,
+           -0.5112644402251639,
+           -0.5415704976274519,
+           -0.5701473449535823,
+           -0.5964685350338557,
+           -0.6200440871269198,
+           -0.6404313748921132,
+           -0.6572449908532199,
+           -0.6701653545496792,
+           -0.6789458610024328,
+           -0.683418400488062,
+           -0.6834971190840241,
+           -0.6791803310862463,
+           -0.6705505381967329,
+           -0.6577725552688161,
+           -0.641089787289983,
+           -0.6208187460856411,
+           -0.5973419368772205,
+           -0.5710992833132399,
+           -0.5425782939788031,
+           -0.5123032028444804,
+           -0.4808233399282999,
+           -0.4487010060414385,
+           -0.4164991364492042,
+           -0.384769042346697,
+           -0.3540385161348928,
+           -0.3248005766713241,
+           -0.2975031142118535,
+           -0.27253967207131147,
+           -0.2502415736781453,
+           -0.23087157038704353,
+           -0.21461914796982798,
+           -0.20159758905478595,
+           -0.19184284593167936,
+           -0.1853142341393959,
+           -0.1818969131877247,
+           -0.18140607771545503,
+           -0.18359274140814333,
+           -0.18815095809142912,
+           -0.19472629050282686,
+           -0.2029253081488723,
+           -0.21232587207697484,
+           -0.22248794689591989,
+           -0.232964669377448,
+           -0.2433133987137775,
+           -0.253106476074625,
+           -0.26194143041519224,
+           -0.2694503832793026,
+           -0.2753084272048363,
+           -0.2792407797070934,
+           -0.28102854698925545,
+           -0.280512967689434,
+           -0.2775980462046981,
+           -0.27225152644360334,
+           -0.26450419920953433,
+           -0.25444757874349894,
+           -0.24223002519541695,
+           -0.22805142891512745,
+           -0.2121566084810324,
+           -0.1948276064174109,
+           -0.1763750937946061,
+           -0.1571291166843756,
+           -0.13742943321886214,
+           -0.1176156993903993,
+           -0.09801776450612097,
+           -0.0789463333179961,
+           -0.060684241395066105,
+           -0.04347857356472359,
+           -0.027533832656255405,
+           -0.013006337911899837,
+           -1.1389416848591106e-16
+          ],
+          [
+           0,
+           0.010278152468058733,
+           0.019109776913471967,
+           0.026581021752875876,
+           0.032827254777938054,
+           0.038028979466888206,
+           0.04240646212668423,
+           0.04621321116852675,
+           0.04972848009973195,
+           0.05324899172939796,
+           0.057080101971910935,
+           0.06152663695540974,
+           0.0668836465058267,
+           0.07342732023472073,
+           0.08140630932046276,
+           0.0910336877054134,
+           0.10247977106131444,
+           0.11586599087723312,
+           0.13125999491709386,
+           0.14867211472431552,
+           0.16805330657967377,
+           0.18929463519978174,
+           0.21222833042503564,
+           0.23663040716491307,
+           0.26222479894800915,
+           0.28868891656758794,
+           0.31566050649952265,
+           0.34274564992818374,
+           0.36952771320463457,
+           0.39557703514426484,
+           0.4204611163985958,
+           0.4437550617300289,
+           0.46505201775786276,
+           0.48397334685596455,
+           0.50017828243596,
+           0.5133728217537382,
+           0.5233176293824394,
+           0.5298347472009611,
+           0.5328129346101057,
+           0.5322114950365044,
+           0.5280624808325517,
+           0.5204712075506719,
+           0.509615049312546,
+           0.4957405286104604,
+           0.4791587553471285,
+           0.46023931022214576,
+           0.43940270571461787,
+           0.417111592950681,
+           0.3938609138146913,
+           0.3701672239930677,
+           0.3465574335747493,
+           0.3235572268483278,
+           0.30167943165406563,
+           0.2814126108444701,
+           0.2632101440148385,
+           0.247480056781878,
+           0.23457583777005955,
+           0.2247884605208587,
+           0.21833979932168196,
+           0.21537759514091187,
+           0.2159720912478514,
+           0.22011441857958525,
+           0.22771676945054534,
+           0.23861435579260892,
+           0.2525691057947152,
+           0.269275011610007,
+           0.2883650017166506,
+           0.3094191755050117,
+           0.3319742055924626,
+           0.3555336860148602,
+           0.37957918247140826,
+           0.40358172473624915,
+           0.42701347157919706,
+           0.4493592752889043,
+           0.4701278762335916,
+           0.48886246773486514,
+           0.5051503876175959,
+           0.5186317147286793,
+           0.5290065759427434,
+           0.5360410010168039,
+           0.5395711983299957,
+           0.5395061631670132,
+           0.5358285708224113,
+           0.5285939484174534,
+           0.5179281609092063,
+           0.5040232873131879,
+           0.487132001663896,
+           0.4675606087622152,
+           0.4456609164405859,
+           0.4218211531482641,
+           0.3964561614678819,
+           0.3699971142002359,
+           0.34288100952043077,
+           0.3155402051921654,
+           0.2883922488636033,
+           0.2618302521536218,
+           0.23621404082404876,
+           0.21186229222574515,
+           0.18904584494832066,
+           0.1679823348661549,
+           0.14883227733845392,
+           0.13169667805978577,
+           0.11661621591013842,
+           0.10357200110507288,
+           0.09248787200266624,
+           0.08323415508556964,
+           0.0756327758749733,
+           0.0694635747660705,
+           0.06447165184268097,
+           0.06037553937530883,
+           0.056875980559451554,
+           0.05366507860519839,
+           0.05043557189703586,
+           0.04688998880378947,
+           0.042749439874938365,
+           0.037761815495004326,
+           0.031709173311026954,
+           0.024414121479573215,
+           0.01574503044190739,
+           0.005619936847736878,
+           -0.005990962378337567,
+           -0.019064290872357784,
+           -0.03352397500393661,
+           -0.04924321454517389,
+           -0.06604789004714781,
+           -0.08372131750737029,
+           -0.10201022555806982,
+           -0.12063179822514097,
+           -0.13928159812025767,
+           -0.15764216145293206,
+           -0.17539203808599793,
+           -0.19221503747439903,
+           -0.20780943504551475,
+           -0.22189689356843495,
+           -0.23423086033080234,
+           -0.24460421334830837,
+           -0.2528559480722721,
+           -0.2588767196865634,
+           -0.262613084512005,
+           -0.264070316558314,
+           -0.2633137110707043,
+           -0.2604683251166,
+           -0.2557171448921061,
+           -0.24929770950469957,
+           -0.24149726050172288,
+           -0.2326465243694933,
+           -0.22311227066777645,
+           -0.21328882049259312,
+           -0.2035887077634627,
+           -0.19443271869977521,
+           -0.18623955219683824,
+           -0.17941535518354484,
+           -0.1743433921365223,
+           -0.17137410659160912,
+           -0.1708158247435999,
+           -0.17292633722989034,
+           -0.17790557527888692,
+           -0.1858895720434074,
+           -0.19694586974240677,
+           -0.21107049893204585,
+           -0.2281866186534253,
+           -0.24814486627596616,
+           -0.2707254245493465,
+           -0.2956417717060441,
+           -0.32254603944477106,
+           -0.3510358642821852,
+           -0.38066258105661893,
+           -0.41094057421023356,
+           -0.441357573686572,
+           -0.47138565857399356,
+           -0.5004927135934514,
+           -0.5281540716242271,
+           -0.5538640699863918,
+           -0.5771472492993852,
+           -0.5975689313961513,
+           -0.6147449268151397,
+           -0.6283501424844945,
+           -0.6381258858718472,
+           -0.643885692480407,
+           -0.64551953838692,
+           -0.6429963376954851,
+           -0.6363646653964425,
+           -0.6257516881848426,
+           -0.611360328285928,
+           -0.5934647272226166,
+           -0.5724041167240752,
+           -0.5485752416367924,
+           -0.5224235138458218,
+           -0.4944331060162125,
+           -0.4651162187017556,
+           -0.4350017734435835,
+           -0.4046237974369217,
+           -0.3745097718732716,
+           -0.3451692160177205,
+           -0.3170827724684387,
+           -0.29069204604059945,
+           -0.26639042964868,
+           -0.2445151259069032,
+           -0.22534054354117422,
+           -0.20907321384212638,
+           -0.19584833512561398,
+           -0.18572801342399195,
+           -0.17870122638824446,
+           -0.17468549565163435,
+           -0.17353021171457048,
+           -0.1750215157669398,
+           -0.17888860573718246,
+           -0.18481130015177896,
+           -0.19242866392317973,
+           -0.20134847567055614,
+           -0.21115729720427998,
+           -0.2214308928216051,
+           -0.2317447393681918,
+           -0.24168436776206254,
+           -0.2508552828375719,
+           -0.2588922207723232,
+           -0.2654675216800464,
+           -0.2702984187118441,
+           -0.2731530735971489,
+           -0.27385522124562656,
+           -0.2722873219932957,
+           -0.26839215840142944,
+           -0.26217285323989936,
+           -0.2536913254088663,
+           -0.2430652400677786,
+           -0.23046354715931214,
+           -0.2161007378907302,
+           -0.20022998068427994,
+           -0.18313532583702702,
+           -0.1651231909515668,
+           -0.1465133565489481,
+           -0.12762971272878076,
+           -0.10879100302229429,
+           -0.09030181057084453,
+           -0.0724440244921894,
+           -0.05546901096413167,
+           -0.039590694506412574,
+           -0.02497973066718855,
+           -0.01175892244124831,
+           -1.0264357380419972e-16
+          ],
+          [
+           0,
+           0.00918782940933545,
+           0.017053318002497136,
+           0.02370139619084087,
+           0.029281310725896115,
+           0.03398210027266008,
+           0.03802693085825324,
+           0.04166644073879735,
+           0.045171270410276514,
+           0.04882397519432804,
+           0.05291053450217584,
+           0.05771168309047744,
+           0.06349429508012575,
+           0.07050305106606455,
+           0.0789526123043505,
+           0.08902051387188824,
+           0.1008409711491594,
+           0.11449977140909262,
+           0.1300303952650892,
+           0.14741148191021647,
+           0.16656571823611174,
+           0.18736019589977768,
+           0.20960824311090276,
+           0.23307270027699492,
+           0.2574705716141472,
+           0.2824789493401276,
+           0.30774207400952924,
+           0.33287936476485946,
+           0.3574942275196045,
+           0.3811834280175588,
+           0.4035468008696113,
+           0.4241970554681821,
+           0.44276943539438496,
+           0.45893098969092794,
+           0.4723892221518006,
+           0.48289989840538544,
+           0.49027380972246093,
+           0.4943823167084515,
+           0.49516152475714054,
+           0.49261497565524115,
+           0.48681477524256855,
+           0.4779011146839049,
+           0.4660801817741286,
+           0.45162049782403924,
+           0.4348477540984457,
+           0.4161382585537441,
+           0.3959111378416128,
+           0.3746194703620268,
+           0.3527405527983615,
+           0.330765524387014,
+           0.30918858961851525,
+           0.2884960907227568,
+           0.2691556858854794,
+           0.2516058875529603,
+           0.23624620743486302,
+           0.223428141090636,
+           0.2134472056085975,
+           0.20653621932375046,
+           0.2028599833627786,
+           0.20251149175794994,
+           0.20550976073682353,
+           0.21179932944884305,
+           0.2212514447646071,
+           0.23366690284198985,
+           0.2487804808663235,
+           0.26626685469456285,
+           0.2857478629812277,
+           0.30680094659055784,
+           0.3289685644751272,
+           0.35176836439501497,
+           0.3747038694135958,
+           0.39727542945487987,
+           0.4189911816193887,
+           0.43937776355867103,
+           0.4579905309786081,
+           0.47442304310344147,
+           0.48831559836418653,
+           0.49936262621611244,
+           0.5073187692528315,
+           0.5120035219687292,
+           0.5133043278318075,
+           0.5111780738943384,
+           0.5056509610643256,
+           0.4968167674306467,
+           0.48483356071556055,
+           0.46991895307306153,
+           0.4523440261530288,
+           0.43242608576415026,
+           0.4105204328308583,
+           0.387011359990394,
+           0.36230260057274355,
+           0.3368074684368436,
+           0.31093893293042985,
+           0.28509987297515943,
+           0.2596737479803887,
+           0.2350159111351832,
+           0.21144577294027425,
+           0.1892400000782959,
+           0.16862690746503503,
+           0.1497821702705085,
+           0.13282594863324226,
+           0.11782148157419177,
+           0.10477516916022558,
+           0.09363812421170323,
+           0.08430913774076723,
+           0.0766389667747299,
+           0.07043582014934009,
+           0.06547188807343783,
+           0.06149073550949281,
+           0.058215358321492675,
+           0.055356685232421064,
+           0.0526222982970925,
+           0.04972514008093816,
+           0.04639197714349921,
+           0.04237139671001283,
+           0.037441126381033,
+           0.03141448504138553,
+           0.024145796314613704,
+           0.01553462337395989,
+           0.005528714965054055,
+           -0.005874413671630979,
+           -0.018627305529123107,
+           -0.03263379598239706,
+           -0.047751623259065006,
+           -0.06379634611748505,
+           -0.0805464653653396,
+           -0.0977496142347242,
+           -0.11512965445201191,
+           -0.13239449081995475,
+           -0.1492443978789788,
+           -0.16538063822802748,
+           -0.18051414372387645,
+           -0.19437402826160152,
+           -0.20671570424083396,
+           -0.21732838406670357,
+           -0.22604176289803724,
+           -0.23273169897382046,
+           -0.2373247327249561,
+           -0.23980131489445175,
+           -0.24019764632280893,
+           -0.23860606709711446,
+           -0.23517396953571565,
+           -0.23010124706401766,
+           -0.22363632848738038,
+           -0.21607088354228113,
+           -0.2077333199898723,
+           -0.19898122403763543,
+           -0.1901929237356801,
+           -0.18175837848450033,
+           -0.17406961630860063,
+           -0.16751095361571378,
+           -0.16244923942970146,
+           -0.15922436735549245,
+           -0.15814029375428645,
+           -0.15945678987475195,
+           -0.16338213924725228,
+           -0.17006696989165118,
+           -0.1795993843362357,
+           -0.19200151973706145,
+           -0.20722763626927726,
+           -0.2251637952664695,
+           -0.24562915020802173,
+           -0.26837883453866834,
+           -0.2931083914097502,
+           -0.319459652715462,
+           -0.3470279391898636,
+           -0.3753704207114981,
+           -0.40401544713988047,
+           -0.43247263569788397,
+           -0.4602434817218587,
+           -0.48683224600833275,
+           -0.5117568643363773,
+           -0.5345596232367105,
+           -0.5548173507604266,
+           -0.5721508817678544,
+           -0.5862335738583272,
+           -0.5967986720978723,
+           -0.6036453476438207,
+           -0.6066432665622744,
+           -0.6057355798307037,
+           -0.6009402628720062,
+           -0.5923497720710672,
+           -0.5801290256299392,
+           -0.5645117558531756,
+           -0.5457953185545953,
+           -0.5243340818027465,
+           -0.500531549787231,
+           -0.47483140737735763,
+           -0.44770769623652945,
+           -0.4196543535388142,
+           -0.39117435892261865,
+           -0.36276874396143144,
+           -0.33492572093071676,
+           -0.3081101839511684,
+           -0.2827538257914844,
+           -0.2592460979682135,
+           -0.23792622067816,
+           -0.2190764230661929,
+           -0.20291656401404554,
+           -0.18960024978394982,
+           -0.17921252830055479,
+           -0.17176920150612263,
+           -0.16721775802097033,
+           -0.16543988924595446,
+           -0.1662555140147301,
+           -0.16942820087050328,
+           -0.17467184388397494,
+           -0.18165841845231637,
+           -0.19002661843705518,
+           -0.1993911559151877,
+           -0.20935249021148947,
+           -0.21950674409310553,
+           -0.2294555622375072,
+           -0.23881567037985757,
+           -0.24722790280325643,
+           -0.2543654808053397,
+           -0.259941345065813,
+           -0.26371436992933867,
+           -0.26549431686605585,
+           -0.2651454170351886,
+           -0.26258850812979,
+           -0.2578016876337878,
+           -0.25081948234709256,
+           -0.24173057158394995,
+           -0.23067413788386423,
+           -0.21783495348285742,
+           -0.20343734231750965,
+           -0.18773818519096439,
+           -0.17101915922784716,
+           -0.15357842130331886,
+           -0.13572195829441178,
+           -0.11775483444968718,
+           -0.09997256773028637,
+           -0.08265286261392445,
+           -0.06604791669443616,
+           -0.05037750271981442,
+           -0.03582300689672833,
+           -0.022522578883388388,
+           -0.010567519544515194,
+           -9.197564447401857e-17
+          ],
+          [
+           0,
+           0.008168009553076123,
+           0.015143704161384068,
+           0.02104684411171884,
+           0.026036494111439788,
+           0.030306181903937367,
+           0.03407806586720838,
+           0.037596266045596,
+           0.04111953522951013,
+           0.04491346435680716,
+           0.04924242920994884,
+           0.05436149279716245,
+           0.060508479738544944,
+           0.0678964353722067,
+           0.07670667323330906,
+           0.08708260025980398,
+           0.0991244898944364,
+           0.112885349658047,
+           0.12836800235089874,
+           0.14552346948008982,
+           0.1642507125755562,
+           0.18439775356911148,
+           0.20576416023525224,
+           0.22810484771279735,
+           0.2511351132232979,
+           0.27453678913091445,
+           0.2979653702578094,
+           0.3210579456210124,
+           0.3434417431476462,
+           0.3647430790099759,
+           0.3845964914386631,
+           0.40265383253360537,
+           0.41859309087361257,
+           0.43212672266620744,
+           0.4430092796735833,
+           0.4510441379585249,
+           0.45608915224059865,
+           0.4580610858404734,
+           0.45693869520987757,
+           0.45276438019111537,
+           0.44564434563898964,
+           0.43574725602544434,
+           0.4233014012504363,
+           0.40859042820162694,
+           0.3919477277457919,
+           0.3737495999290213,
+           0.35440735039234256,
+           0.3343584976248738,
+           0.3140572930162888,
+           0.2939647731766485,
+           0.27453857622488614,
+           0.2562227603968783,
+           0.23943786421614652,
+           0.2245714425722293,
+           0.2119693024730087,
+           0.2019276462267667,
+           0.1946863087499223,
+           0.19042325009388306,
+           0.1892504347576211,
+           0.19121119661644267,
+           0.19627915314599337,
+           0.20435869590742897,
+           0.21528704687700864,
+           0.22883783305991517,
+           0.24472609582691499,
+           0.26261461742865233,
+           0.282121416001558,
+           0.3028282328375074,
+           0.32428981241391697,
+           0.3460437572349578,
+           0.3676207263620501,
+           0.3885547389279058,
+           0.4083933421106896,
+           0.42670740702989174,
+           0.44310032570736035,
+           0.45721639737030684,
+           0.4687482125793612,
+           0.4774428684411734,
+           0.4831068768978039,
+           0.48560966006375844,
+           0.48488556101738545,
+           0.4809343344983959,
+           0.4738201187315945,
+           0.46366892618629474,
+           0.45066472659520806,
+           0.4350442291279744,
+           0.41709050142458853,
+           0.3971255904942276,
+           0.3755023336149662,
+           0.35259556577351725,
+           0.32879294342335935,
+           0.3044856121049144,
+           0.2800589475894669,
+           0.2558835966460935,
+           0.23230703439555964,
+           0.20964584075260065,
+           0.1881788790452145,
+           0.16814153603593185,
+           0.14972115486402685,
+           0.1330537615821977,
+           0.11822215275577402,
+           0.10525537686340626,
+           0.0941296068581524,
+           0.08477036610380254,
+           0.0770560358724676,
+           0.07082254052549386,
+           0.06586907719944805,
+           0.061964731010387866,
+           0.05885579511232852,
+           0.05627359793449682,
+           0.05394262799362304,
+           0.0515887401209555,
+           0.048947225912499205,
+           0.045770535719818845,
+           0.04183544942310053,
+           0.036949508307525664,
+           0.030956540208601557,
+           0.023741134192596332,
+           0.01523194877872837,
+           0.005403768383146205,
+           -0.005721744509508009,
+           -0.01807661979732909,
+           -0.031548456590898714,
+           -0.04598355601011848,
+           -0.06119122666451031,
+           -0.07694914879101045,
+           -0.09300965519199464,
+           -0.10910676290417855,
+           -0.12496376955331165,
+           -0.14030121312093313,
+           -0.15484498375938954,
+           -0.16833437160208478,
+           -0.1805298353541044,
+           -0.19122028280139558,
+           -0.20022966609322929,
+           -0.2074227114462813,
+           -0.212709624374747,
+           -0.21604963713713335,
+           -0.2174532941697769,
+           -0.21698340312401598,
+           -0.2147546129419107,
+           -0.2109316153471534,
+           -0.2057260013163721,
+           -0.19939183864651078,
+           -0.19222006977573308,
+           -0.1845318597137171,
+           -0.17667105151447268,
+           -0.16899591047957224,
+           -0.16187035760438503,
+           -0.15565490717641284,
+           -0.1506975325266506,
+           -0.14732468747702232,
+           -0.1458327089119593,
+           -0.14647981816325042,
+           -0.14947892570748422,
+           -0.1549914253436463,
+           -0.16312214098205174,
+           -0.17391556198980457,
+           -0.18735347236155178,
+           -0.20335404556452374,
+           -0.2217724415603885,
+           -0.24240290609930856,
+           -0.26498233580792085,
+           -0.28919523675279346,
+           -0.3146799699379408,
+           -0.34103614543481453,
+           -0.36783299833224664,
+           -0.39461855513977695,
+           -0.4209293792924286,
+           -0.44630066948825065,
+           -0.47027647511826304,
+           -0.4924197892647569,
+           -0.5123222817518133,
+           -0.5296134424929885,
+           -0.5439689187155073,
+           -0.5551178482315092,
+           -0.5628490143288477,
+           -0.5670156755025103,
+           -0.5675389544741254,
+           -0.5644097049944463,
+           -0.5576888109657395,
+           -0.5475059095821637,
+           -0.5340565675632116,
+           -0.5175979762394463,
+           -0.4984432663492119,
+           -0.4769545760668141,
+           -0.45353503521353394,
+           -0.42861985408890235,
+           -0.40266672628383465,
+           -0.3761457706942706,
+           -0.349529248363337,
+           -0.3232812944944063,
+           -0.29784790488958907,
+           -0.2736474092129154,
+           -0.25106165103073813,
+           -0.23042807685699918,
+           -0.21203291386965956,
+           -0.19610558912701795,
+           -0.18281451266300563,
+           -0.1722643135306854,
+           -0.16449458251403554,
+           -0.15948013870924113,
+           -0.15713280038513958,
+           -0.15730460436998053,
+           -0.15979238356308245,
+           -0.16434357988100268,
+           -0.17066314080434564,
+           -0.17842132239995737,
+           -0.18726220086418255,
+           -0.19681267876459968,
+           -0.20669176162520822,
+           -0.21651987554554422,
+           -0.22592799727120644,
+           -0.2345663745044436,
+           -0.2421126260815788,
+           -0.24827902863691656,
+           -0.25281881808062984,
+           -0.2555313600854474,
+           -0.2562660731458721,
+           -0.25492501990065636,
+           -0.25146411648399936,
+           -0.24589294483604557,
+           -0.23827318827636476,
+           -0.22871574533915676,
+           -0.21737661001890438,
+           -0.20445163735331784,
+           -0.1901703409107655,
+           -0.17478889256611643,
+           -0.1585825143530482,
+           -0.14183746669509797,
+           -0.12484284658801091,
+           -0.1078824131104298,
+           -0.09122665589430284,
+           -0.07512531494564205,
+           -0.059800547663610336,
+           -0.04544092138753305,
+           -0.03219638775823641,
+           -0.020174369176559834,
+           -0.009437058341566313,
+           -8.192557533740725e-17
+          ],
+          [
+           0,
+           0.007220105939881797,
+           0.013381235576858335,
+           0.01861402863121543,
+           0.023083398977903836,
+           0.026983497803041354,
+           0.030531832414938627,
+           0.0339626968559471,
+           0.03752008874969823,
+           0.04145030065150279,
+           0.04599438319243461,
+           0.05138068128550972,
+           0.05781764348783439,
+           0.06548709830772571,
+           0.07453817996187127,
+           0.08508207010133065,
+           0.09718770173197368,
+           0.11087854745902183,
+           0.12613058688726203,
+           0.14287151819015179,
+           0.16098124726877536,
+           0.18029365534757877,
+           0.20059961311619748,
+           0.22165117744934462,
+           0.24316687612851334,
+           0.2648379576239213,
+           0.28633545759186807,
+           0.30731791194816366,
+           0.3274395287503733,
+           0.3463586181153907,
+           0.36374607135503756,
+           0.37929367764879324,
+           0.3927220689785875,
+           0.403788091684094,
+           0.4122914156862032,
+           0.41808020987335687,
+           0.42105573393332973,
+           0.4211757225162962,
+           0.4184564664122685,
+           0.4129735267153046,
+           0.40486105096311614,
+           0.39430969417426126,
+           0.3815631817220349,
+           0.3669135842466902,
+           0.35069540649492287,
+           0.3332786213040273,
+           0.31506080619091414,
+           0.29645856251107094,
+           0.2778984153582624,
+           0.2598074058259396,
+           0.24260359560577258,
+           0.2266867069421001,
+           0.2124291186082233,
+           0.20016743086860206,
+           0.1901947995187951,
+           0.18275422135811845,
+           0.17803293127383854,
+           0.17615804503486543,
+           0.17719355253812694,
+           0.18113873433350533,
+           0.18792804054803952,
+           0.19743243665583354,
+           0.20946218573960526,
+           0.2237710028091921,
+           0.2400614842102582,
+           0.2579916849636726,
+           0.27718268975597193,
+           0.29722699991211005,
+           0.3176975395897531,
+           0.33815707010099333,
+           0.35816779203664656,
+           0.3773009109597038,
+           0.3951459439364917,
+           0.4113195510428956,
+           0.42547368804315794,
+           0.43730289338789124,
+           0.4465505440941791,
+           0.4530139404229578,
+           0.45654810793067946,
+           0.45706823673631936,
+           0.4545507109414144,
+           0.44903271525626354,
+           0.4406104401825084,
+           0.4294359407407879,
+           0.41571273588957197,
+           0.39969026567325916,
+           0.3816573500371065,
+           0.36193481650182574,
+           0.34086748294118485,
+           0.31881569609621835,
+           0.29614663585024703,
+           0.27322559946479114,
+           0.2504074788520234,
+           0.22802863758051006,
+           0.20639938285342632,
+           0.18579721146374154,
+           0.16646098813810276,
+           0.14858619025695344,
+           0.1323213253031729,
+           0.11776559724421157,
+           0.10496786615321524,
+           0.09392691252478964,
+           0.0845929847647192,
+           0.0768705760552402,
+           0.07062234602445472,
+           0.06567407414695288,
+           0.06182050628119032,
+           0.05883193384025431,
+           0.05646132733738707,
+           0.05445183288202126,
+           0.052544431946404645,
+           0.05048556157375434,
+           0.0480344942244819,
+           0.04497028359552408,
+           0.04109809480904109,
+           0.03625475403699801,
+           0.030313373478249715,
+           0.023186932100736583,
+           0.01483072007808385,
+           0.005243584686484956,
+           -0.005532053174520528,
+           -0.017411410512562262,
+           -0.03026974839142275,
+           -0.04394590802588485,
+           -0.05824688257141227,
+           -0.07295330319179825,
+           -0.08782569392518465,
+           -0.10261132952174792,
+           -0.11705151431397609,
+           -0.13088908871545546,
+           -0.14387596342232947,
+           -0.15578047998457206,
+           -0.16639440016484006,
+           -0.17553933532399757,
+           -0.18307244074973697,
+           -0.18889121804101,
+           -0.19293729092496187,
+           -0.19519904566066573,
+           -0.19571305583192636,
+           -0.19456424213338772,
+           -0.19188474993852483,
+           -0.18785156019709268,
+           -0.1826828817196904,
+           -0.1766334043493427,
+           -0.16998852210059173,
+           -0.16305766231675284,
+           -0.15616688057058398,
+           -0.1496509008085583,
+           -0.14384479560605126,
+           -0.13907551196096893,
+           -0.13565345352642896,
+           -0.1338643304150805,
+           -0.13396148267467664,
+           -0.13615887334375382,
+           -0.14062493188338154,
+           -0.14747740910443885,
+           -0.15677938094240623,
+           -0.16853651114844548,
+           -0.18269565283026765,
+           -0.19914483652476642,
+           -0.21771465890644356,
+           -0.23818105215555985,
+           -0.2602693802662164,
+           -0.28365977599907327,
+           -0.3079936015807935,
+           -0.3328808883802278,
+           -0.35790858634149303,
+           -0.3826494335349837,
+           -0.4066712403095982,
+           -0.42954637159238385,
+           -0.45086120516417777,
+           -0.4702253433923418,
+           -0.48728036094337657,
+           -0.5017078813158339,
+           -0.5132367903845116,
+           -0.5216494151638877,
+           -0.5267865202005758,
+           -0.5285510018068281,
+           -0.5269101910766257,
+           -0.5218967095373557,
+           -0.5136078555842708,
+           -0.5022035346885414,
+           -0.4879027809155721,
+           -0.47097895069846923,
+           -0.4517537012698015,
+           -0.4305898948987735,
+           -0.4078835954126067,
+           -0.38405534478616893,
+           -0.35954092434733537,
+           -0.33478181696309217,
+           -0.3102155931605987,
+           -0.28626644534364215,
+           -0.2633360900659324,
+           -0.24179524882839482,
+           -0.22197590331756564,
+           -0.20416450175992165,
+           -0.1885962696101179,
+           -0.17545075070044328,
+           -0.16484867492328611,
+           -0.15685021623877574,
+           -0.15145467109023222,
+           -0.14860155299857128,
+           -0.148173065034807,
+           -0.14999787887107735,
+           -0.15385611799116108,
+           -0.15948541415928708,
+           -0.16658788109268385,
+           -0.1748378280667478,
+           -0.18389001941157368,
+           -0.1933882739334498,
+           -0.20297419149293447,
+           -0.2122957924430377,
+           -0.22101585939674726,
+           -0.22881977974145376,
+           -0.2354227012092976,
+           -0.24057583128573884,
+           -0.24407173381920608,
+           -0.24574850230738082,
+           -0.24549271831866912,
+           -0.24324113462894784,
+           -0.2389810551305353,
+           -0.23274941658702628,
+           -0.22463061003720616,
+           -0.21475311127544566,
+           -0.20328501956595713,
+           -0.19042863084411732,
+           -0.1764141954470268,
+           -0.16149303030898943,
+           -0.14593017106557743,
+           -0.1299967602531177,
+           -0.11396237350951,
+           -0.09808748624450275,
+           -0.08261627864973438,
+           -0.06776996728737582,
+           -0.05374083708385453,
+           -0.04068712873452736,
+           -0.028728913779347977,
+           -0.017945063519997927,
+           -0.008371389180695354,
+           -7.251809163146941e-17
+          ],
+          [
+           0,
+           0.006344383630324685,
+           0.011763940722871716,
+           0.01639630119328049,
+           0.020408408655858076,
+           0.02399140557359874,
+           0.027354815908589212,
+           0.030720180071214756,
+           0.03431431157844219,
+           0.03836235511237032,
+           0.043080831355118435,
+           0.048670854915488934,
+           0.05531170782660774,
+           0.06315494257206583,
+           0.07231917559914472,
+           0.08288571512261482,
+           0.09489514613740525,
+           0.10834497146359923,
+           0.1231883809445849,
+           0.13933419227710717,
+           0.15664797708855288,
+           0.17495435554206717,
+           0.19404041270722985,
+           0.2136601609403317,
+           0.2335399453062465,
+           0.2533846643328703,
+           0.27288465674800505,
+           0.2917230868601801,
+           0.3095836473718787,
+           0.32615838901691024,
+           0.3411554817432746,
+           0.35430671235155825,
+           0.3653745285586645,
+           0.3741584492782793,
+           0.3805006752649114,
+           0.3842907528164461,
+           0.3854691655247815,
+           0.3840297545651368,
+           0.3800208961011734,
+           0.37354539436878176,
+           0.3647590801514017,
+           0.3538681359087413,
+           0.3411251999919689,
+           0.3268243324027941,
+           0.31129495268905183,
+           0.2948948861182667,
+           0.27800267659856304,
+           0.2610093433666864,
+           0.244309772771404,
+           0.22829394618636425,
+           0.21333820994147853,
+           0.19979679303675352,
+           0.18799377329024503,
+           0.17821568258778034,
+           0.1707049272815109,
+           0.16565418087639938,
+           0.16320188340315342,
+           0.1634289558520243,
+           0.16635680936436417,
+           0.17194669824341288,
+           0.1801004339963968,
+           0.19066244533066287,
+           0.20342313708234872,
+           0.21812347023380746,
+           0.23446065622516543,
+           0.2520948323896732,
+           0.2706565621824966,
+           0.2897549844901039,
+           0.30898642117142083,
+           0.3279432414576045,
+           0.34622277617624697,
+           0.36343607410092477,
+           0.3792162970682076,
+           0.3932265597392064,
+           0.4051670337791443,
+           0.41478115444003094,
+           0.4218607896067315,
+           0.42625025675963807,
+           0.42784910139148336,
+           0.4266135804998248,
+           0.42255682612092693,
+           0.41574769570570075,
+           0.4063083476840055,
+           0.39441061104836256,
+           0.3802712464679502,
+           0.3641462226204781,
+           0.3463241544680739,
+           0.32711906954721126,
+           0.30686268352782337,
+           0.28589637696260184,
+           0.26456307104599425,
+           0.24319920120391814,
+           0.22212698343145265,
+           0.20164715959996643,
+           0.18203239469889504,
+           0.16352148150499551,
+           0.14631448693123897,
+           0.13056894983925496,
+           0.11639721302282911,
+           0.10386494306840979,
+           0.09299086160126364,
+           0.08374768079032838,
+           0.0760642056778145,
+           0.06982853667811609,
+           0.06489227818294498,
+           0.061075634297300556,
+           0.05817325093171056,
+           0.055960645328854065,
+           0.054201050053556306,
+           0.052652488867093235,
+           0.05107489697079126,
+           0.04923709795351111,
+           0.04692345440598972,
+           0.0439400184454136,
+           0.040120022082587754,
+           0.035328565107664675,
+           0.029466379513134987,
+           0.02247257386902796,
+           0.014326287893093499,
+           0.0050472160354233945,
+           -0.005305011503796529,
+           -0.016632572034605813,
+           -0.02880227024415948,
+           -0.041649358849121965,
+           -0.0549822580106925,
+           -0.0685880479008691,
+           -0.08223858843305162,
+           -0.09569710352654155,
+           -0.10872505478800074,
+           -0.12108912148401008,
+           -0.1325681003555062,
+           -0.14295954027709973,
+           -0.1520859329619998,
+           -0.15980029170686053,
+           -0.1659909652948261,
+           -0.17058555325468372,
+           -0.17355381123456373,
+           -0.1749094607271765,
+           -0.1747108451430475,
+           -0.1730604035732013,
+           -0.170102963776916,
+           -0.16602288621450176,
+           -0.16104012055696335,
+           -0.15540526429663307,
+           -0.14939373914224452,
+           -0.14329922414727417,
+           -0.13742650439894805,
+           -0.13208391007784542,
+           -0.1275755323713424,
+           -0.12419340978184719,
+           -0.12220988062081378,
+           -0.12187029484928726,
+           -0.12338627096398529,
+           -0.1269296715037718,
+           -0.132627454250281,
+           -0.14055753571327012,
+           -0.1507457795206687,
+           -0.16316419545753777,
+           -0.17773040577290092,
+           -0.19430840471146232,
+           -0.2127106057810275,
+           -0.23270113980937993,
+           -0.2540003361518207,
+           -0.27629029024056806,
+           -0.2992213937416606,
+           -0.3224196795719732,
+           -0.34549481352586586,
+           -0.36804854777980184,
+           -0.3896834394980633,
+           -0.41001163045870326,
+           -0.42866348124553527,
+           -0.44529585617760375,
+           -0.4595998627178618,
+           -0.47130786144194586,
+           -0.48019957946279446,
+           -0.4861071810943436,
+           -0.4889191739940467,
+           -0.4885830564581549,
+           -0.4851066412907034,
+           -0.4785580230050178,
+           -0.4690641872839573,
+           -0.45680829384014543,
+           -0.44202569529665037,
+           -0.4249987846865637,
+           -0.40605079191772514,
+           -0.38553867439238465,
+           -0.3638452683077057,
+           -0.34137088447475733,
+           -0.3185245453627125,
+           -0.2957150681918813,
+           -0.2733422020713453,
+           -0.2517880253324794,
+           -0.2314088024000825,
+           -0.21252748794100107,
+           -0.19542704992609825,
+           -0.18034476303560426,
+           -0.16746760003031638,
+           -0.15692882188987256,
+           -0.14880583834544,
+           -0.1431193796254514,
+           -0.1398339885463102,
+           -0.13885981029237626,
+           -0.1400556261193387,
+           -0.14323304754236055,
+           -0.14816176005851994,
+           -0.15457568077075143,
+           -0.16217987302532483,
+           -0.17065804385871333,
+           -0.17968043708616557,
+           -0.18891192655848363,
+           -0.19802011065496358,
+           -0.20668321053829314,
+           -0.21459758101874735,
+           -0.22148465388731647,
+           -0.2270971489915441,
+           -0.23122440774660666,
+           -0.23369672670151928,
+           -0.23438859463458617,
+           -0.23322076477998105,
+           -0.23016112348020804,
+           -0.22522434707147654,
+           -0.2184703693760517,
+           -0.21000171203326254,
+           -0.19995975830399823,
+           -0.18852007722515343,
+           -0.17588692841892697,
+           -0.1622870978970314,
+           -0.14796323134771977,
+           -0.1331668432582068,
+           -0.11815118751875785,
+           -0.10316417770462857,
+           -0.08844154298470457,
+           -0.07420039862809988,
+           -0.060633398557792755,
+           -0.04790362163328141,
+           -0.03614032373825537,
+           -0.02543566480648016,
+           -0.01584249422515606,
+           -0.007373250264308955,
+           -6.37672973502418e-17
+          ],
+          [
+           0,
+           0.005539975578475955,
+           0.010287642171045889,
+           0.014383849607753733,
+           0.017993955368585186,
+           0.02130274345153727,
+           0.024508775513467623,
+           0.027818324898789645,
+           0.031439055360325645,
+           0.0355736133256877,
+           0.04041330528855432,
+           0.04613203023306156,
+           0.05288063096782905,
+           0.06078181800033288,
+           0.06992580537509205,
+           0.08036678008310774,
+           0.09212030566906917,
+           0.10516173704108892,
+           0.11942569781636347,
+           0.13480664445880405,
+           0.15116051366132346,
+           0.1683074215954844,
+           0.1860353564959106,
+           0.20410478025195208,
+           0.22225403089751836,
+           0.24020539672562327,
+           0.25767171474661055,
+           0.27436333182008893,
+           0.28999525639265783,
+           0.30429432264013484,
+           0.31700618711191497,
+           0.32790198076394245,
+           0.3367844464914119,
+           0.343493403768062,
+           0.34791039749445934,
+           0.3499624072816201,
+           0.3496245156863309,
+           0.3469214588286204,
+           0.3419280097517035,
+           0.3347681731707556,
+           0.32561319920442133,
+           0.3146784525795021,
+           0.30221920193200136,
+           0.2885254205012638,
+           0.2739157140675451,
+           0.2587305138072602,
+           0.24332469029075354,
+           0.22805975966083067,
+           0.2132958637337526,
+           0.19938371208576924,
+           0.18665667596277083,
+           0.1754232210249813,
+           0.16595985857252948,
+           0.15850478316250888,
+           0.15325234870256219,
+           0.15034851556955015,
+           0.14988737852540596,
+           0.15190885973656953,
+           0.15639762366560508,
+           0.16328324166207228,
+           0.1724416044375928,
+           0.1836975509879775,
+           0.19682865364367805,
+           0.21157007149117038,
+           0.22762035907947048,
+           0.24464809472335194,
+           0.26229917338696535,
+           0.28020459354689015,
+           0.29798855596909685,
+           0.31527668526559527,
+           0.3317041825917052,
+           0.34692371996014343,
+           0.3606128933263097,
+           0.3724810626717311,
+           0.3822754225031177,
+           0.3897861651162501,
+           0.3948506211786429,
+           0.39735628711492493,
+           0.39724267582017925,
+           0.39450195571427993,
+           0.3891783723852466,
+           0.3813664763352725,
+           0.3712082089233438,
+           0.3588889257953401,
+           0.34463246224362615,
+           0.32869536743252037,
+           0.3113604537193564,
+           0.29292982292899183,
+           0.2737175430296602,
+           0.25404215593766877,
+           0.234219199982369,
+           0.21455392883666569,
+           0.19533440252012219,
+           0.17682511557978003,
+           0.1592613130229513,
+           0.14284412639036517,
+           0.12773664098092574,
+           0.11406098121299793,
+           0.1018964750380457,
+           0.09127893086666908,
+           0.08220103231359616,
+           0.07461382792189397,
+           0.06842926559071505,
+           0.06352369538926078,
+           0.059742240440008414,
+           0.056903914192033896,
+           0.054807344208728535,
+           0.05323694801145053,
+           0.05196939590847753,
+           0.05078018935375417,
+           0.04945018137269178,
+           0.04777186800300593,
+           0.04555528645664206,
+           0.04263336663460662,
+           0.03886659743586773,
+           0.03414688761303456,
+           0.028400522272284207,
+           0.021590139948080293,
+           0.0137156808976801,
+           0.0048142842023091185,
+           -0.00504086125317613,
+           -0.015742679520048937,
+           -0.027153325160805836,
+           -0.03910817181376722,
+           -0.05142056509354435,
+           -0.0638872130991998,
+           -0.07629407097120854,
+           -0.08842256278037894,
+           -0.10005597488325299,
+           -0.11098584997485175,
+           -0.12101821053988437,
+           -0.1299794442664769,
+           -0.13772169215031854,
+           -0.14412759228170577,
+           -0.14911424836963708,
+           -0.1526363115164294,
+           -0.1546880861277247,
+           -0.15530459556691345,
+           -0.15456156962052453,
+           -0.1525743433681467,
+           -0.14949568495514853,
+           -0.14551259734623903,
+           -0.14084216569716987,
+           -0.135726546849087,
+           -0.13042721999491141,
+           -0.12521863721604498,
+           -0.1203814288384187,
+           -0.11619533099100127,
+           -0.11293201104331871,
+           -0.11084797053002843,
+           -0.1101777046269896,
+           -0.11112729222290989,
+           -0.11386858124315409,
+           -0.11853412034642019,
+           -0.12521297075298754,
+           -0.13394751119330056,
+           -0.1447313252914824,
+           -0.1575082346968752,
+           -0.1721725135838361,
+           -0.18857029143496562,
+           -0.20650212201153056,
+           -0.22572666781189085,
+           -0.24596542183054518,
+           -0.26690836273720386,
+           -0.288220416334197,
+           -0.3095485759001582,
+           -0.3305295172935205,
+           -0.35079753189052604,
+           -0.3699925918927773,
+           -0.38776835847778696,
+           -0.40379994379215367,
+           -0.4177912428974436,
+           -0.42948166135793564,
+           -0.43865207798124695,
+           -0.4451298999573866,
+           -0.44879308886256314,
+           -0.44957306018859794,
+           -0.44745638564141266,
+           -0.4424852557779612,
+           -0.4347566899323505,
+           -0.4244205101046143,
+           -0.4116761248269314,
+           -0.3967681972683316,
+           -0.37998129830319,
+           -0.36163366930753627,
+           -0.3420702404765263,
+           -0.32165506796586235,
+           -0.3007633667257171,
+           -0.2797733251903168,
+           -0.2590578927873157,
+           -0.23897673142600562,
+           -0.21986851771258337,
+           -0.20204377373754587,
+           -0.18577839110786468,
+           -0.17130799578251835,
+           -0.1588232806380618,
+           -0.14846640905074832,
+           -0.14032856671588573,
+           -0.13444871107503964,
+           -0.13081353877153576,
+           -0.12935866221457487,
+           -0.12997095732065952,
+           -0.13249201652712136,
+           -0.1367226149186424,
+           -0.14242807341250444,
+           -0.14934438199124395,
+           -0.15718492845820997,
+           -0.16564766454203073,
+           -0.1744225317138147,
+           -0.1831989640254522,
+           -0.19167328473885298,
+           -0.19955581749244525,
+           -0.20657754112928053,
+           -0.21249612986830912,
+           -0.21710123691146063,
+           -0.22021889942392806,
+           -0.22171496559897436,
+           -0.22149746964568467,
+           -0.2195179073850564,
+           -0.21577139303205586,
+           -0.2102957059796764,
+           -0.2031692642792982,
+           -0.1945080883341678,
+           -0.18446184342154803,
+           -0.17320907241064915,
+           -0.16095174988420083,
+           -0.1479093053117607,
+           -0.13431227555890698,
+           -0.1203957555405922,
+           -0.10639282003501357,
+           -0.09252808947075015,
+           -0.07901160789983619,
+           -0.066033192498456,
+           -0.05375740102762081,
+           -0.04231924707237019,
+           -0.031820772986267176,
+           -0.02232856780671428,
+           -0.013872292553702972,
+           -0.006444248912428583,
+           -5.567666179211715e-17
+          ],
+          [
+           0,
+           0.004804912988051165,
+           0.008946050303977734,
+           0.012563885618836803,
+           0.015818828530813435,
+           0.018886281570583946,
+           0.02195125510084452,
+           0.025202683953238436,
+           0.028827597714670666,
+           0.033005300753440665,
+           0.03790171825398277,
+           0.043664060698205935,
+           0.05041595148336544,
+           0.05825315089170057,
+           0.06723999471036353,
+           0.07740664781302763,
+           0.08874725240627906,
+           0.10121902793027528,
+           0.11474235535367525,
+           0.1292018534264521,
+           0.14444842898411367,
+           0.1603022582747608,
+           0.17655663214040998,
+           0.19298257533678498,
+           0.20933412989328026,
+           0.22535417471593552,
+           0.24078063907384034,
+           0.25535295655878243,
+           0.26881859885753484,
+           0.280939525420132,
+           0.2914983859406904,
+           0.3003043174829713,
+           0.30719818697237894,
+           0.3120571424316983,
+           0.31479835245766546,
+           0.3153818326307169,
+           0.31381227935495576,
+           0.3101398555076628,
+           0.30445989765299575,
+           0.2969115408199756,
+           0.2876752833146502,
+           0.2769695400776937,
+           0.2650462580681037,
+           0.25218569043267747,
+           0.23869044723171245,
+           0.22487895871075847,
+           0.21107850208107268,
+           0.19761795412159308,
+           0.1848204393552758,
+           0.17299604689078765,
+           0.16243478816568185,
+           0.15339996279109508,
+           0.14612209059531028,
+           0.14079355500879895,
+           0.1375640864360591,
+           0.13653719461641858,
+           0.13776763666127673,
+           0.14125998300926507,
+           0.14696831755645015,
+           0.15479708132702863,
+           0.16460304190465025,
+           0.17619834410570678,
+           0.18935457169417297,
+           0.20380772593759824,
+           0.21926400506935767,
+           0.2354062497815046,
+           0.25190090418534195,
+           0.2684053296232868,
+           0.28457530058665653,
+           0.3000725079846613,
+           0.31457189521379664,
+           0.3277686568848617,
+           0.3393847385644838,
+           0.34917468826701414,
+           0.35693072638363293,
+           0.36248691986400877,
+           0.3657223683000111,
+           0.36656333356305265,
+           0.36498427022664515,
+           0.3610077405355932,
+           0.3547032245127387,
+           0.3461848622665974,
+           0.3356081910319667,
+           0.3231659633197271,
+           0.30908315419191307,
+           0.2936112845893378,
+           0.2770222033655603,
+           0.259601482846157,
+           0.24164159104810473,
+           0.22343500796826107,
+           0.20526745349032458,
+           0.18741139047657468,
+           0.17011995861638124,
+           0.1536214828092758,
+           0.13811468457119527,
+           0.12376470655936356,
+           0.1107000392810668,
+           0.09901041591587842,
+           0.08874571652215378,
+           0.07991589733600016,
+           0.07249193504464523,
+           0.06640775047152005,
+           0.06156305168193393,
+           0.05782701371365293,
+           0.055042691521974406,
+           0.05303204481410397,
+           0.05160143867437526,
+           0.05054747261227479,
+           0.04966298317314888,
+           0.04874306171555858,
+           0.04759092945876667,
+           0.04602351641668562,
+           0.04387659923803636,
+           0.041009365046175,
+           0.03730828380388668,
+           0.032690190122182494,
+           0.02710449631756374,
+           0.020534481366845995,
+           0.012997624631191416,
+           0.004544978205918872,
+           -0.004740403134418495,
+           -0.014745930822526747,
+           -0.025332783173083406,
+           -0.03633994906106207,
+           -0.04758890635861098,
+           -0.05888881020015245,
+           -0.0700420526597537,
+           -0.08085004548285292,
+           -0.09111907137091141,
+           -0.10066604713170746,
+           -0.10932404383943728,
+           -0.11694741495597484,
+           -0.12341639300589065,
+           -0.12864102863477633,
+           -0.13256436238391267,
+           -0.1351647388726798,
+           -0.1364571948092409,
+           -0.13649387580562664,
+           -0.13536346176433184,
+           -0.13318960600687535,
+           -0.1301284186910415,
+           -0.12636504977277987,
+           -0.1221094501866829,
+           -0.11759141145238469,
+           -0.11305500301598673,
+           -0.10875254281834,
+           -0.10493824943026614,
+           -0.10186173327570565,
+           -0.09976148973522644,
+           -0.09885855813936846,
+           -0.09935050777970943,
+           -0.10140590514319331,
+           -0.10515940577079463,
+           -0.11070759971061492,
+           -0.11810572182440908,
+           -0.1273653176440007,
+           -0.1384529325605567,
+           -0.15128986742515815,
+           -0.1657530177491633,
+           -0.1816767872537912,
+           -0.19885604018149153,
+           -0.2170500311971297,
+           -0.23598722750779585,
+           -0.2553709156161473,
+           -0.2748854654457727,
+           -0.2942031079288869,
+           -0.31299106894363377,
+           -0.33091889306315825,
+           -0.34766578517191155,
+           -0.3629277967581212,
+           -0.3764246866448985,
+           -0.3879062930126216,
+           -0.39715826462698156,
+           -0.40400701395755084,
+           -0.40832377299675554,
+           -0.4100276536318949,
+           -0.4090876378744641,
+           -0.40552344854318717,
+           -0.3994052775159749,
+           -0.3908523757671431,
+           -0.38003053643068796,
+           -0.36714852842091394,
+           -0.35245356305855097,
+           -0.3362258990877196,
+           -0.31877271186885375,
+           -0.30042136989958795,
+           -0.2815122757282459,
+           -0.26239143844642837,
+           -0.24340295103463863,
+           -0.2248815477429706,
+           -0.2071454143754579,
+           -0.19048941787252144,
+           -0.1751789111141455,
+           -0.1614442546575081,
+           -0.14947617952871656,
+           -0.13942209464375457,
+           -0.1313834194449052,
+           -0.12541399747150905,
+           -0.12151962044884798,
+           -0.1196586657173333,
+           -0.11974382309149958,
+           -0.12164486118823438,
+           -0.12519235853197141,
+           -0.13018230193335353,
+           -0.1363814343008926,
+           -0.14353321667412008,
+           -0.15136425527926192,
+           -0.1595910341378847,
+           -0.16792678744622572,
+           -0.176088343730567,
+           -0.18380277571315887,
+           -0.19081369583231556,
+           -0.19688704728707035,
+           -0.20181625406225637,
+           -0.20542661028498607,
+           -0.20757880903800474,
+           -0.20817153290834056,
+           -0.2071430525224474,
+           -0.20447180450887129,
+           -0.2001759461047035,
+           -0.19431190933798448,
+           -0.18697200273278886,
+           -0.17828113217401823,
+           -0.16839273434618102,
+           -0.15748403548501066,
+           -0.14575076457533823,
+           -0.1334014631900311,
+           -0.12065154357411033,
+           -0.10771725210839543,
+           -0.09480969680886173,
+           -0.08212909500264762,
+           -0.06985939084201556,
+           -0.05816338204561195,
+           -0.04717848145913534,
+           -0.03701322206035296,
+           -0.027744594330894597,
+           -0.019416282982296723,
+           -0.012037846415041657,
+           -0.00558485760713593,
+           -4.8239143628233183e-17
+          ],
+          [
+           0,
+           0.004136169694361976,
+           0.007730883615837248,
+           0.010920869463157335,
+           0.013858527655459424,
+           0.016707222135347248,
+           0.019636243655940657,
+           0.022815580316156433,
+           0.026410635401199204,
+           0.03057703428839871,
+           0.03545566024545323,
+           0.0411680534237499,
+           0.04781229836913664,
+           0.055459513158874915,
+           0.06415103813068611,
+           0.07389640447606541,
+           0.08467214316825998,
+           0.09642147328199911,
+           0.10905488627495248,
+           0.12245161980551496,
+           0.13646199173710835,
+           0.15091054270419685,
+           0.1655999145528238,
+           0.180315372652565,
+           0.19482986299846097,
+           0.20890948061686554,
+           0.22231921442828254,
+           0.2348288256979518,
+           0.24621871273312745,
+           0.25628561368847486,
+           0.26484800225015037,
+           0.2717510375249552,
+           0.2768709395124941,
+           0.2801186748471764,
+           0.2814428537432415,
+           0.28083175786607284,
+           0.27831443972913106,
+           0.2739608566672713,
+           0.2678810259132085,
+           0.26022321122700603,
+           0.25117117530890026,
+           0.24094055527600355,
+           0.229774440232717,
+           0.21793824987325983,
+           0.20571403062719804,
+           0.19339430065646093,
+           0.18127558666396673,
+           0.1696518036853201,
+           0.15880763359602573,
+           0.1490120588567012,
+           0.1405122050098594,
+           0.13352763869929682,
+           0.12824525766419576,
+           0.12481489550992246,
+           0.12334574740353427,
+           0.12390370358559268,
+           0.12650965619666868,
+           0.13113882190541867,
+           0.13772109875386845,
+           0.1461424510895195,
+           0.15624729203001753,
+           0.1678418091985947,
+           0.18069815705426812,
+           0.1945594185651825,
+           0.20914522073702604,
+           0.22415787305431714,
+           0.23928888559562078,
+           0.254225714742164,
+           0.26865857922582187,
+           0.28228718788035456,
+           0.2948272228991677,
+           0.30601642860062517,
+           0.3156201655025832,
+           0.32343630266802653,
+           0.3292993374779159,
+           0.33308365081610497,
+           0.33470582665086596,
+           0.3341259876518482,
+           0.331348122234132,
+           0.32641940269003095,
+           0.3194285182604802,
+           0.31050307051997017,
+           0.2998061007283897,
+           0.28753183929766374,
+           0.27390078573354754,
+           0.25915424290330313,
+           0.24354844187613064,
+           0.22734840259008857,
+           0.21082168100595994,
+           0.1942321550935836,
+           0.17783399993022952,
+           0.16186599643711408,
+           0.1465463089936466,
+           0.1320678545911295,
+           0.11859437064097683,
+           0.10625727043265158,
+           0.09515335500175993,
+           0.08534342832908907,
+           0.07685183989535985,
+           0.06966695523776771,
+           0.06374253187736523,
+           0.05899995539151999,
+           0.055331269055370294,
+           0.05260291090039665,
+           0.05066005472157705,
+           0.049331436934311614,
+           0.04843453959758904,
+           0.04778099166307739,
+           0.047182045779476205,
+           0.04645398688739962,
+           0.04542333140080113,
+           0.043931681913319684,
+           0.04184011192900177,
+           0.03903296784808185,
+           0.035420991012060046,
+           0.03094368062928318,
+           0.025570838402757413,
+           0.019303257156635924,
+           0.012172538160767625,
+           0.004240044614902623,
+           -0.004404978702014718,
+           -0.013648067858407558,
+           -0.023352912101766,
+           -0.033365345372828696,
+           -0.04351785005824912,
+           -0.053634452559131365,
+           -0.06353587985997555,
+           -0.07304483924089906,
+           -0.08199127976653779,
+           -0.09021749429988891,
+           -0.09758292452944005,
+           -0.10396853877276567,
+           -0.10928066294984347,
+           -0.11345415884045908,
+           -0.11645486020992876,
+           -0.11828119619416017,
+           -0.11896495200758472,
+           -0.11857113905703043,
+           -0.11719696935777339,
+           -0.11496995218063742,
+           -0.1120451535304559,
+           -0.10860168079383305,
+           -0.10483847514771438,
+           -0.10096951257568153,
+           -0.0972185301310443,
+           -0.09381340701036656,
+           -0.09098033972452634,
+           -0.08893795692264024,
+           -0.08789152206871301,
+           -0.08802737111341187,
+           -0.0895077275577096,
+           -0.09246602897708982,
+           -0.09700288735980768,
+           -0.10318279079034828,
+           -0.11103163643763013,
+           -0.12053516491370055,
+           -0.1316383443383705,
+           -0.14424572941074867,
+           -0.15822279701588693,
+           -0.17339823596913154,
+           -0.18956714501281782,
+           -0.206495070710534,
+           -0.22392279599034867,
+           -0.24157177128932486,
+           -0.2591500640158243,
+           -0.2763586887798113,
+           -0.2928981708783269,
+           -0.3084751891164409,
+           -0.3228091413592925,
+           -0.3356384773226891,
+           -0.3467266479995471,
+           -0.35586752967555196,
+           -0.3628901925080143,
+           -0.3676628988398073,
+           -0.37009623443000417,
+           -0.37014529616957026,
+           -0.36781088212055046,
+           -0.3631396533304848,
+           -0.35622326125673764,
+           -0.34719645919528486,
+           -0.33623424024783966,
+           -0.3235480674926795,
+           -0.30938128358520406,
+           -0.2940038064796789,
+           -0.2777062348603726,
+           -0.2607935007881199,
+           -0.2435782176696732,
+           -0.2263738786859626,
+           -0.20948806410295825,
+           -0.19321581535816695,
+           -0.17783332948365288,
+           -0.16359211940230764,
+           -0.1507137741180735,
+           -0.13938543809820497,
+           -0.12975611158003186,
+           -0.12193385355910095,
+           -0.11598394732133499,
+           -0.11192806510690985,
+           -0.10974444440888273,
+           -0.10936906410519764,
+           -0.11069778469300152,
+           -0.11358939392347475,
+           -0.11786947768326614,
+           -0.12333501655636464,
+           -0.12975959159793019,
+           -0.1368990688665522,
+           -0.14449762152823542,
+           -0.15229394111782377,
+           -0.16002748598833721,
+           -0.16744461517133985,
+           -0.17430445979495426,
+           -0.18038439175110088,
+           -0.18548496027124237,
+           -0.18943418117735275,
+           -0.19209108046177534,
+           -0.19334841308786635,
+           -0.19313449900703125,
+           -0.19141414082615485,
+           -0.1881886107695692,
+           -0.18349471798076725,
+           -0.17740299021682987,
+           -0.1700150260297291,
+           -0.16146009405552592,
+           -0.15189107453600362,
+           -0.14147985422018097,
+           -0.1304122989409932,
+           -0.11888293811341115,
+           -0.10708950191325058,
+           -0.09522745481622735,
+           -0.08348466844009109,
+           -0.07203637226631722,
+           -0.06104051294031235,
+           -0.050633641666779985,
+           -0.04092743501888631,
+           -0.03200593763070176,
+           -0.023923596172821533,
+           -0.016704133207188446,
+           -0.010340287508320221,
+           -0.004794424783589257,
+           -4.1437450183561373e-17
+          ],
+          [
+           0,
+           0.003529719948798484,
+           0.006632013970769995,
+           0.009436768442028334,
+           0.012085655263254322,
+           0.014727742050179488,
+           0.017514876706591298,
+           0.020596970069233417,
+           0.02411730321100717,
+           0.02820798563906209,
+           0.03298568703347613,
+           0.03854775842770814,
+           0.044968849000790456,
+           0.05229811217561558,
+           0.060557079809293576,
+           0.06973826629362619,
+           0.07980454578175421,
+           0.09068932598814623,
+           0.10229752157047454,
+           0.11450730950834252,
+           0.12717262866477355,
+           0.14012636636310366,
+           0.15318415682461833,
+           0.16614870014782845,
+           0.17881449658075432,
+           0.1909728794999545,
+           0.2024172220571184,
+           0.21294818710716285,
+           0.22237888793511007,
+           0.23053982851592664,
+           0.2372834965527525,
+           0.24248849024318173,
+           0.24606307043927467,
+           0.24794804333824413,
+           0.2481188947415347,
+           0.24658711486347956,
+           0.24340067221839326,
+           0.23864361578754748,
+           0.23243480595672172,
+           0.22492579609622104,
+           0.21629790760028145,
+           0.20675856119317956,
+           0.1965369458491339,
+           0.18587912330109269,
+           0.1750426804148499,
+           0.16429105332134727,
+           0.15388765583873168,
+           0.1440899501568618,
+           0.1351435998589155,
+           0.1272768440579906,
+           0.12069522675499902,
+           0.11557680758468687,
+           0.11206796909664395,
+           0.11027992188099918,
+           0.11028599252691838,
+           0.11211976099015045,
+           0.11577409388952836,
+           0.12120109903805291,
+           0.12831300465730872,
+           0.13698394475591985,
+           0.1470526106080309,
+           0.1583257076707702,
+           0.17058213813168974,
+           0.1835778120442763,
+           0.1970509751110365,
+           0.21072792897136733,
+           0.2243290106415894,
+           0.23757469175976179,
+           0.2501916556522725,
+           0.2619187110243391,
+           0.27251240526035814,
+           0.28175220779724636,
+           0.2894451446185526,
+           0.2954297783474858,
+           0.29957944436165407,
+           0.30180467141882483,
+           0.3020547350271747,
+           0.30031831273068177,
+           0.2966232320972082,
+           0.29103532396421206,
+           0.283656414882833,
+           0.2746215131834702,
+           0.2640952621661718,
+           0.25226775113382444,
+           0.23934978991867,
+           0.22556776484349803,
+           0.21115820341411753,
+           0.1963621812386287,
+           0.1814197075690135,
+           0.16656422540089136,
+           0.1520173582703133,
+           0.13798402885689862,
+           0.12464806442508246,
+           0.112168391269174,
+           0.10067590500145518,
+           0.0902710861239208,
+           0.08102241129227782,
+           0.07296559049389413,
+           0.06610363952542488,
+           0.06040777619186659,
+           0.05581910807975223,
+           0.05225106009511092,
+           0.049592471689941194,
+           0.047711277281720706,
+           0.04645866920425413,
+           0.04567363096321466,
+           0.04518771988859879,
+           0.044829972688863275,
+           0.044431805049784424,
+           0.043831777336094016,
+           0.04288010261448377,
+           0.04144278051011253,
+           0.039405250644272166,
+           0.03667547231380752,
+           0.033186352331724886,
+           0.028897460163101473,
+           0.023795988222130266,
+           0.01789693496832477,
+           0.011242508750292436,
+           0.003900770678541058,
+           -0.00403644535120966,
+           -0.012456278518842909,
+           -0.02122817848942897,
+           -0.03020774458065072,
+           -0.03924096374823571,
+           -0.04816873394142846,
+           -0.056831551780767126,
+           -0.06507423901341398,
+           -0.07275058092328876,
+           -0.07972775184946826,
+           -0.08589040815001332,
+           -0.0911443372119659,
+           -0.09541956224647377,
+           -0.09867281634303689,
+           -0.10088931524518822,
+           -0.10208377615098402,
+           -0.10230064908768619,
+           -0.10161354757736768,
+           -0.10012388589125214,
+           -0.097958750666678,
+           -0.09526805451467892,
+           -0.09222103797595663,
+           -0.08900220331352858,
+           -0.08580677872564337,
+           -0.08283582423700835,
+           -0.08029110045398093,
+           -0.07836982829228575,
+           -0.07725947152068947,
+           -0.07713267440677016,
+           -0.078142483879348,
+           -0.08041797949671782,
+           -0.08406042527229043,
+           -0.08914004527911257,
+           -0.09569351022404896,
+           -0.10372220520854178,
+           -0.11319133008973484,
+           -0.12402986368369769,
+           -0.13613140200676913,
+           -0.14935585934980453,
+           -0.16353199975134838,
+           -0.17846074590443672,
+           -0.19391919320662643,
+           -0.20966523902403153,
+           -0.2254427217270316,
+           -0.2409869510556097,
+           -0.2560305012126345,
+           -0.2703091310208786,
+           -0.2835676916954579,
+           -0.29556588237866843,
+           -0.3060837165766424,
+           -0.31492656896138566,
+           -0.3219296815098388,
+           -0.32696202041771877,
+           -0.3299293903510035,
+           -0.33077673001747937,
+           -0.3294895323335274,
+           -0.32609435315963453,
+           -0.32065839417952036,
+           -0.3132881674772656,
+           -0.30412727118978855,
+           -0.29335332674740777,
+           -0.28117414814856434,
+           -0.2678232319608816,
+           -0.2535546728556736,
+           -0.23863762307483743,
+           -0.22335042496784702,
+           -0.2079745533619477,
+           -0.19278850885689075,
+           -0.17806180406335367,
+           -0.16404918231181315,
+           -0.15098520250998237,
+           -0.13907931476794924,
+           -0.1285115393655335,
+           -0.11942884690351635,
+           -0.11194232042236427,
+           -0.10612516130851578,
+           -0.10201158040506712,
+           -0.09959659440127688,
+           -0.09883672581662782,
+           -0.0996515832525015,
+           -0.10192627758644132,
+           -0.10551460994237008,
+           -0.11024294906753644,
+           -0.11591469962470487,
+           -0.12231524925549132,
+           -0.1292172714154798,
+           -0.13638625318193776,
+           -0.1435861126728083,
+           -0.1505847694931764,
+           -0.15715953376177644,
+           -0.16310218470164187,
+           -0.16822361836050004,
+           -0.17235795553530162,
+           -0.1753660151165882,
+           -0.17713807448295982,
+           -0.17759585684888185,
+           -0.176693705140386,
+           -0.17441892254922994,
+           -0.17079128088165774,
+           -0.1658617186494573,
+           -0.15971027102945337,
+           -0.15244329284116356,
+           -0.14419005308933044,
+           -0.13509879495812516,
+           -0.12533236804906006,
+           -0.11506354980866347,
+           -0.10447018024776396,
+           -0.09373023804036022,
+           -0.08301698681469083,
+           -0.0724943179023488,
+           -0.062312410065221466,
+           -0.052603817926916624,
+           -0.04348008922371436,
+           -0.0350289968589009,
+           -0.027312455455553136,
+           -0.020365174072197036,
+           -0.014194077432343266,
+           -0.008778507913724653,
+           -0.004071200156602179,
+           -3.524442801006606e-17
+          ],
+          [
+           0,
+           0.0029806088238126197,
+           0.0056376348955634835,
+           0.008091346134285056,
+           0.0104703447255062,
+           0.012907571064156638,
+           0.015536169869117544,
+           0.01848532942452599,
+           0.021876205813500613,
+           0.02581804204904051,
+           0.03040458722149584,
+           0.035710913290435194,
+           0.041790717137419726,
+           0.048674183215232,
+           0.056366467885989466,
+           0.06484685069252147,
+           0.07406858075244528,
+           0.08395942863147424,
+           0.09442293589074117,
+           0.1053403364703844,
+           0.11657310662389868,
+           0.127966083696475,
+           0.13935107906246208,
+           0.15055089738351474,
+           0.16138366335628435,
+           0.1716673485695977,
+           0.18122438520829479,
+           0.1898862502804343,
+           0.19749790389237146,
+           0.20392196786582478,
+           0.20904253662312466,
+           0.2127685206305331,
+           0.21503643358563967,
+           0.21581254770066546,
+           0.21509435654925843,
+           0.21291130164107072,
+           0.20932473675695973,
+           0.20442712267892948,
+           0.19834046382466203,
+           0.1912140169805413,
+           0.183221320357081,
+           0.1745566081194074,
+           0.16543069095199908,
+           0.156066396717054,
+           0.14669367652176926,
+           0.13754449023827356,
+           0.12884759149959799,
+           0.12082333527183373,
+           0.11367863119368583,
+           0.10760216297052233,
+           0.10275998827492316,
+           0.09929162497599386,
+           0.09730671830056938,
+           0.09688236998995284,
+           0.09806119498242358,
+           0.10085015400008265,
+           0.10522019206445753,
+           0.111106693854299,
+           0.11841074741573178,
+           0.12700118851141032,
+           0.13671737931953365,
+           0.14737265771773653,
+           0.15875837743659235,
+           0.17064844533095302,
+           0.18280425023615973,
+           0.19497986863655037,
+           0.2069274258997271,
+           0.21840248827808262,
+           0.22916936033378005,
+           0.23900616491597634,
+           0.24770958824663108,
+           0.2550991809188179,
+           0.2610211164748717,
+           0.26535132244309995,
+           0.26799791394590766,
+           0.26890287687461095,
+           0.26804296574255765,
+           0.26542980023427676,
+           0.2611091637013966,
+           0.25515952594572044,
+           0.2476898311101825,
+           0.23883660891914996,
+           0.22876048344727612,
+           0.21764216766461622,
+           0.20567804386553545,
+           0.1930754394555835,
+           0.180047714221535,
+           0.16680927899012513,
+           0.1535706664067187,
+           0.1405337724254234,
+           0.12788738205944775,
+           0.11580308512889295,
+           0.10443167736492473,
+           0.09390012954975496,
+           0.08430919271279799,
+           0.0757316911349116,
+           0.0682115374438825,
+           0.06176348585339994,
+           0.05637362106060527,
+           0.05200056193650917,
+           0.04857734137677207,
+           0.046013906968871754,
+           0.04420017188963007,
+           0.04300953205095438,
+           0.0423027542911546,
+           0.041932131638975405,
+           0.04174579557039401,
+           0.041592071880117126,
+           0.04132376637582199,
+           0.0408022690764003,
+           0.039901370886298825,
+           0.038510694686460255,
+           0.036538653221340825,
+           0.03391485880224915,
+           0.030591924366118548,
+           0.02654661145523731,
+           0.02178029780941924,
+           0.016318755052284643,
+           0.01021124495613319,
+           0.0035289605286693577,
+           -0.003637144770630197,
+           -0.01117908043893092,
+           -0.018975021310600654,
+           -0.026892902746219503,
+           -0.03479431216877023,
+           -0.04253857266335228,
+           -0.04998690920890171,
+           -0.05700658576908134,
+           -0.0634749019960621,
+           -0.06928294168443457,
+           -0.07433897127010668,
+           -0.07857139544791593,
+           -0.08193118816285473,
+           -0.08439373053361482,
+           -0.08596000236018358,
+           -0.08665709037068682,
+           -0.08653799386175313,
+           -0.08568072644100257,
+           -0.08418673073480917,
+           -0.08217864072100203,
+           -0.07979744333463012,
+           -0.07719910674474638,
+           -0.07455075681110937,
+           -0.0720264953417735,
+           -0.06980296357511953,
+           -0.06805476154954411,
+           -0.06694983851089414,
+           -0.06664497112037802,
+           -0.06728144491415154,
+           -0.06898105025305604,
+           -0.07184249698243082,
+           -0.07593834236307452,
+           -0.08131251476694619,
+           -0.08797850144722236,
+           -0.09591825273730692,
+           -0.10508183769756306,
+           -0.1153878679373504,
+           -0.12672468754346122,
+           -0.13895230820793358,
+           -0.15190505023413697,
+           -0.16539483256622564,
+           -0.1792150387689137,
+           -0.1931448713859064,
+           -0.20695409468837087,
+           -0.22040805580101966,
+           -0.23327286681584347,
+           -0.24532062596054227,
+           -0.2563345542990502,
+           -0.2661139258516133,
+           -0.2744786734041494,
+           -0.2812735595305604,
+           -0.28637181230597747,
+           -0.2896781376057051,
+           -0.29113103446524613,
+           -0.2907043563691024,
+           -0.2884080791431361,
+           -0.2842882549150794,
+           -0.2784261509238082,
+           -0.27093659133049436,
+           -0.2619655391422862,
+           -0.25168697344016977,
+           -0.24029913386693882,
+           -0.2280202193704832,
+           -0.21508364114599107,
+           -0.2017329402631666,
+           -0.1882164883453485,
+           -0.17478209469559267,
+           -0.1616716453195133,
+           -0.14911589832790506,
+           -0.13732955623971915,
+           -0.12650672884723513,
+           -0.11681689072019238,
+           -0.10840142535109773,
+           -0.10137083367733231,
+           -0.09580266860793055,
+           -0.0917402396297323,
+           -0.08919211299949992,
+           -0.08813241390052468,
+           -0.08850191772221552,
+           -0.09020989877872276,
+           -0.09313668677732938,
+           -0.09713686461735133,
+           -0.1020430260516749,
+           -0.1076699987397971,
+           -0.1138194275762569,
+           -0.12028460514587987,
+           -0.12685543092665483,
+           -0.13332337855215032,
+           -0.13948635110573634,
+           -0.145153308022481,
+           -0.15014855362295276,
+           -0.1543155864275216,
+           -0.15752041996556373,
+           -0.1596542995067732,
+           -0.1606357546545293,
+           -0.1604119446631572,
+           -0.15895927124692427,
+           -0.1562832520903996,
+           -0.15241766678661836,
+           -0.1474230050597849,
+           -0.14138426442215585,
+           -0.13440816044118575,
+           -0.12661982715651052,
+           -0.1181590975326262,
+           -0.10917646385913832,
+           -0.09982882547167889,
+           -0.0902751358831053,
+           -0.08067206327554248,
+           -0.07116977727001546,
+           -0.06190797099527166,
+           -0.05301222082600027,
+           -0.04459077692711651,
+           -0.036731866163733015,
+           -0.029501575313043885,
+           -0.022942367192838167,
+           -0.017072265692244133,
+           -0.011884728176546688,
+           -0.007349205784400901,
+           -0.003412374198040849,
+           -2.962357926880667e-17
+          ],
+          [
+           0,
+           0.0024830343071515363,
+           0.004734450712215819,
+           0.006862478518343762,
+           0.008980717566169425,
+           0.011204598087193702,
+           0.013647775249507848,
+           0.016418555313937915,
+           0.019616449673657655,
+           0.023328949932150556,
+           0.027628611659890785,
+           0.03257052669646757,
+           0.038190254026318766,
+           0.04450226759916073,
+           0.051498966283033666,
+           0.05915027675978994,
+           0.06740386496148235,
+           0.07618595598454607,
+           0.08540274670186938,
+           0.09494237991777754,
+           0.1046774342666276,
+           0.11446787051349716,
+           0.12416436281970904,
+           0.1336119331954414,
+           0.14265379904179507,
+           0.15113533760075906,
+           0.15890806744333683,
+           0.16583354593392158,
+           0.1717870829509212,
+           0.17666117499453937,
+           0.18036857008474105,
+           0.18284488239744545,
+           0.18405068619958626,
+           0.1839730310666169,
+           0.18262633429643604,
+           0.1800526215305224,
+           0.17632110248550212,
+           0.17152708499502306,
+           0.16579024686038962,
+           0.15925230090565964,
+           0.15207410373462024,
+           0.1444322726178856,
+           0.13651538735106813,
+           0.12851986450916167,
+           0.12064560001202752,
+           0.11309148209648114,
+           0.1060508805036935,
+           0.0997072188388355,
+           0.09422973560833076,
+           0.08976953541808039,
+           0.08645602531604833,
+           0.08439382243827444,
+           0.08366020817963002,
+           0.08430319132257222,
+           0.08634022822765398,
+           0.08975763266565225,
+           0.0945106915295893,
+           0.10052448590274193,
+           0.10769540018369315,
+           0.11589328558992701,
+           0.1249642287762912,
+           0.13473386189349293,
+           0.14501113752568073,
+           0.1555924808988659,
+           0.16626622281230116,
+           0.17681721013011445,
+           0.1870314865408913,
+           0.19670093474785247,
+           0.20562777232799384,
+           0.21362879716698727,
+           0.2205392845462907,
+           0.22621644647714975,
+           0.23054237453285858,
+           0.23342639996360612,
+           0.23480681897938888,
+           0.23465194640983902,
+           0.23296047711968432,
+           0.22976115117907614,
+           0.22511173545273241,
+           0.21909735057385663,
+           0.21182818781073437,
+           0.20343667473772867,
+           0.19407416153867543,
+           0.18390721088720585,
+           0.17311358339794106,
+           0.16187801740890176,
+           0.15038790617954337,
+           0.138828977371894,
+           0.12738107888844946,
+           0.11621417179761798,
+           0.10548462527639195,
+           0.09533190039178804,
+           0.0858756993355806,
+           0.07721364468038203,
+           0.06941953964378207,
+           0.06254224557286427,
+           0.056605197264648174,
+           0.05160656070914574,
+           0.047520021780815394,
+           0.04429617871128021,
+           0.04186449624115172,
+           0.04013576554188065,
+           0.039005001661000745,
+           0.03835469967984008,
+           0.038058362240733314,
+           0.03798420480868333,
+           0.0379989411315825,
+           0.03797154994470957,
+           0.037776925058139434,
+           0.03729931453588624,
+           0.03643546062691559,
+           0.03509736028497291,
+           0.03321457630517086,
+           0.03073604104893522,
+           0.027631308119969725,
+           0.02389122185111979,
+           0.01952798969671591,
+           0.014574658210253319,
+           0.009084008827777233,
+           0.0031269047791165844,
+           -0.0032098652705002083,
+           -0.009826188148685104,
+           -0.01661160139201048,
+           -0.02344856269440761,
+           -0.03021592581519282,
+           -0.03679252970975437,
+           -0.043060804573749716,
+           -0.04891029789078374,
+           -0.05424102546088181,
+           -0.05896655671685374,
+           -0.06301675030055195,
+           -0.06634006470481112,
+           -0.06890537956852306,
+           -0.07070327567161092,
+           -0.07174673550080865,
+           -0.07207124109868591,
+           -0.07173426139369296,
+           -0.07081413694794716,
+           -0.06940838565479791,
+           -0.06763146797568041,
+           -0.06561206444402723,
+           -0.0634899310240198,
+           -0.06141240916618286,
+           -0.05953067676222177,
+           -0.05799583342701629,
+           -0.056954918438104664,
+           -0.056546962111902674,
+           -0.05689917132189906,
+           -0.058123347260615514,
+           -0.060312628470836405,
+           -0.06353864474088662,
+           -0.0678491578509416,
+           -0.07326625360446871,
+           -0.07978513636185139,
+           -0.08737356273500672,
+           -0.09597193555937064,
+           -0.10549406311531928,
+           -0.11582857222293885,
+           -0.12684094768614818,
+           -0.1383761550144219,
+           -0.1502617887887953,
+           -0.16231167582582376,
+           -0.17432985075859922,
+           -0.18611481208685843,
+           -0.19746395938966338,
+           -0.2081781074312388,
+           -0.21806597045159645,
+           -0.22694851008495773,
+           -0.2346630430935129,
+           -0.2410670103805422,
+           -0.2460413164320548,
+           -0.24949315824696003,
+           -0.2513582747146896,
+           -0.25160256099922546,
+           -0.25022300746070114,
+           -0.2472479386271491,
+           -0.24273654433146793,
+           -0.2367777119486,
+           -0.2294881852959855,
+           -0.22101009179166886,
+           -0.21150789450857227,
+           -0.20116483945390112,
+           -0.19017898040600104,
+           -0.17875887366507684,
+           -0.16711904287515822,
+           -0.1554753194633312,
+           -0.14404016708813835,
+           -0.13301809872432815,
+           -0.12260129263161372,
+           -0.11296550852080231,
+           -0.10426639786403959,
+           -0.09663629267883853,
+           -0.09018154548503314,
+           -0.08498047977574098,
+           -0.08108199558591002,
+           -0.07850485894704018,
+           -0.07723768757117434,
+           -0.0772396284136349,
+           -0.07844170623019527,
+           -0.08074880627378132,
+           -0.08404223925730932,
+           -0.08818282300774159,
+           -0.09301440318372402,
+           -0.09836772531590902,
+           -0.10406456249768029,
+           -0.10992199749262578,
+           -0.1157567549631541,
+           -0.12138947902958817,
+           -0.12664885344493299,
+           -0.13137546625775082,
+           -0.13542532781284022,
+           -0.13867296012640298,
+           -0.1410139868346088,
+           -0.14236716576901204,
+           -0.14267582043493904,
+           -0.1419086419023875,
+           -0.14005984848146222,
+           -0.1371487066495537,
+           -0.13321843262401853,
+           -0.12833450933587087,
+           -0.12258246797568684,
+           -0.11606519639570886,
+           -0.10889984813845474,
+           -0.10121443543963789,
+           -0.09314419698784676,
+           -0.08482783633516013,
+           -0.07640372952005618,
+           -0.0680062006264158,
+           -0.059761961662724114,
+           -0.05178680836903943,
+           -0.04418265647222137,
+           -0.03703499369633075,
+           -0.03041081173222803,
+           -0.024357069662453764,
+           -0.018899726348770744,
+           -0.014043364376366047,
+           -0.009771412689605491,
+           -0.006046959441789385,
+           -0.002814131211462107,
+           -2.4529696943190875e-17
+          ],
+          [
+           0,
+           0.0020304400161089194,
+           0.003907884071547167,
+           0.005726492958941088,
+           0.007583364410422898,
+           0.00957549801408649,
+           0.011796751189099423,
+           0.014334868169270987,
+           0.017268662189278833,
+           0.02066542725044639,
+           0.024578650058867977,
+           0.029046085122336796,
+           0.03408824675449505,
+           0.0397073610967095,
+           0.045886809497672015,
+           0.05259108198373891,
+           0.05976624642706498,
+           0.06734092570465837,
+           0.07522776197578147,
+           0.08332533452064408,
+           0.09152048570154063,
+           0.09969099883033472,
+           0.10770856232819034,
+           0.11544194678533203,
+           0.12276031557089728,
+           0.1295365856609709,
+           0.1356507534528769,
+           0.14099310057014308,
+           0.14546719703635538,
+           0.1489926236551397,
+           0.1515073418733429,
+           0.15296964767110713,
+           0.15335965591605216,
+           0.15268027289834066,
+           0.15095762715312172,
+           0.1482409418725963,
+           0.14460184588689964,
+           0.14013313401361988,
+           0.1349470011982232,
+           0.12917278795423864,
+           0.12295428683758325,
+           0.11644667074932516,
+           0.10981311347907764,
+           0.1032211808357603,
+           0.09683907676340696,
+           0.0908318328528462,
+           0.0853575315312503,
+           0.08056365288909956,
+           0.07658363259037497,
+           0.07353371366302842,
+           0.0715101682918589,
+           0.07058695719369171,
+           0.07081388395019028,
+           0.07221529005278234,
+           0.0747893236582003,
+           0.07850780147133249,
+           0.08331666909434587,
+           0.08913705094973245,
+           0.0958668668464502,
+           0.1033829787545941,
+           0.11154381871409093,
+           0.12019243733475482,
+           0.12915990232817892,
+           0.13826896819030612,
+           0.14733793172969015,
+           0.15618458376648192,
+           0.16463016511684664,
+           0.17250323497976885,
+           0.17964336205670878,
+           0.18590455310402362,
+           0.1911583400352114,
+           0.19529645499675524,
+           0.1982330328331904,
+           0.19990629178857364,
+           0.20027965588227434,
+           0.19934229583832722,
+           0.19710907941040753,
+           0.1936199360873237,
+           0.18893865514139338,
+           0.183151149453308,
+           0.17636323018423478,
+           0.1686979488620891,
+           0.16029257352586623,
+           0.15129527398674586,
+           0.141861597815881,
+           0.13215082320106017,
+           0.12232227722261005,
+           0.11253170833033284,
+           0.10292779985913177,
+           0.09364890735614,
+           0.08482009641376688,
+           0.07655054976778809,
+           0.06893140282968548,
+           0.062034055820651725,
+           0.05590899853817488,
+           0.05058517081962778,
+           0.04606986829532438,
+           0.04234918938250524,
+           0.03938900600145239,
+           0.037136427530229485,
+           0.035521715376859136,
+           0.03446059453724142,
+           0.033856898895201853,
+           0.033605479043672094,
+           0.033595295257808494,
+           0.03371261408040239,
+           0.03384422488605809,
+           0.03388059282001199,
+           0.033718866653591764,
+           0.03326566430162239,
+           0.03243956489656904,
+           0.03117324425021845,
+           0.029415200052017223,
+           0.027131024010124603,
+           0.02430419005983518,
+           0.020936340440931154,
+           0.017047064558690893,
+           0.012673178759963103,
+           0.007867528140885557,
+           0.002697343927506035,
+           -0.0027577984799030883,
+           -0.008408365326099074,
+           -0.014157529759548752,
+           -0.01990404481233357,
+           -0.025545246931418852,
+           -0.030980109420772898,
+           -0.03611226375287184,
+           -0.04085290741345921,
+           -0.04512351973855144,
+           -0.04885831201842549,
+           -0.05200634485960028,
+           -0.05453325424454461,
+           -0.05642253769817538,
+           -0.05767636320981755,
+           -0.05831587578658631,
+           -0.058380989421371786,
+           -0.05792966552046308,
+           -0.057036692117712964,
+           -0.05579199116835302,
+           -0.05429849353787282,
+           -0.05266963266713598,
+           -0.05102651801491664,
+           -0.049494857994838624,
+           -0.04820170901399608,
+           -0.047272132206839124,
+           -0.04682584240902666,
+           -0.04697393475130555,
+           -0.04781577294523927,
+           -0.049436119906397236,
+           -0.05190258589500721,
+           -0.05526346197866399,
+           -0.05954599751398669,
+           -0.0647551697251733,
+           -0.07087298158638922,
+           -0.07785831138274749,
+           -0.08564732384674134,
+           -0.09415443897560276,
+           -0.10327384087089211,
+           -0.1128814955455433,
+           -0.12283763394803857,
+           -0.13298964477424485,
+           -0.14317531126607297,
+           -0.15322631739223053,
+           -0.1629719417914062,
+           -0.1722428528099956,
+           -0.18087491501459935,
+           -0.18871291678213453,
+           -0.19561412999221114,
+           -0.2014516164381167,
+           -0.20611720125146127,
+           -0.209524041267012,
+           -0.21160872565603137,
+           -0.21233285710230712,
+           -0.21168407402061318,
+           -0.2096764875264316,
+           -0.20635052073781268,
+           -0.20177215218808203,
+           -0.19603157930628196,
+           -0.1892413317355421,
+           -0.18153387737147622,
+           -0.1730587760936995,
+           -0.16397944693901845,
+           -0.15446962366217365,
+           -0.14470958102535492,
+           -0.1348822195710948,
+           -0.1251690999333533,
+           -0.11574651884893944,
+           -0.10678171792004192,
+           -0.0984293128769756,
+           -0.09082802568026745,
+           -0.08409779441659784,
+           -0.07833732676562777,
+           -0.07362215207009006,
+           -0.07000321499345323,
+           -0.0675060406934384,
+           -0.06613048769557868,
+           -0.06585109055510482,
+           -0.06661798029226096,
+           -0.06835835681987404,
+           -0.0709784744880153,
+           -0.07436608976724024,
+           -0.07839330927267175,
+           -0.08291976705744364,
+           -0.08779605259867075,
+           -0.09286730534107854,
+           -0.09797688818334137,
+           -0.10297005096920504,
+           -0.10769749590538565,
+           -0.11201875984297932,
+           -0.11580533344733297,
+           -0.11894344431076749,
+           -0.12133643985314585,
+           -0.12290671618382927,
+           -0.12359715070429526,
+           -0.12337200882173635,
+           -0.12221730840475058,
+           -0.12014063921120154,
+           -0.1171704481163683,
+           -0.11335481422823711,
+           -0.1087597505670498,
+           -0.10346708059625212,
+           -0.09757194823508293,
+           -0.09118002880477682,
+           -0.08440451544472048,
+           -0.0773629607097934,
+           -0.07017405620145999,
+           -0.06295443411996225,
+           -0.055815573533079504,
+           -0.04886089097151808,
+           -0.04218308976762719,
+           -0.0358618354885583,
+           -0.02996181605971619,
+           -0.02453123495404862,
+           -0.019600774398524742,
+           -0.015183053212144885,
+           -0.011272590953689605,
+           -0.007846276850564644,
+           -0.0048643288374865005,
+           -0.002271715288426123,
+           -1.9909610495908785e-17
+          ],
+          [
+           0,
+           0.001615617337400946,
+           0.003142299233609343,
+           0.004658525748938165,
+           0.006243843496931414,
+           0.007976371165696687,
+           0.009930335707277405,
+           0.012173705626256345,
+           0.01476598538415983,
+           0.01775623087445583,
+           0.021181340315537926,
+           0.025064667896594155,
+           0.02941499926971312,
+           0.03422591871812456,
+           0.03947558777819747,
+           0.04512694450492538,
+           0.051128321714115105,
+           0.057414471683470907,
+           0.0639079742236016,
+           0.07052099500644181,
+           0.07715735181711457,
+           0.08371483821063432,
+           0.09008774711622197,
+           0.0961695314177089,
+           0.10185553459152079,
+           0.10704572220809422,
+           0.11164734456069793,
+           0.11557746189671735,
+           0.11876526666594132,
+           0.12115414180049665,
+           0.1227034001924376,
+           0.1233896580893287,
+           0.12320780390187196,
+           0.12217153369636594,
+           0.12031343518868237,
+           0.11768461310607739,
+           0.11435386006593862,
+           0.11040638835749969,
+           0.10594214892515684,
+           0.10107377416921771,
+           0.09592419064477231,
+           0.09062395611552324,
+           0.08530838249686101,
+           0.08011451182291805,
+           0.07517801635356786,
+           0.07063009619684127,
+           0.06659444829971806,
+           0.06318437933930612,
+           0.060500131954791335,
+           0.058626488969719746,
+           0.05763071387747192,
+           0.05756087805273944,
+           0.0584446160963638,
+           0.06028834063883795,
+           0.06307693706336943,
+           0.06677394722639883,
+           0.07132223962859287,
+           0.07664515190551006,
+           0.08264808024651292,
+           0.08922047968750439,
+           0.09623822941764777,
+           0.10356630853146209,
+           0.11106172025788215,
+           0.11857659678733837,
+           0.12596141254055793,
+           0.13306823118247396,
+           0.1397539109428067,
+           0.14588319387882637,
+           0.15133160757847247,
+           0.15598811238248245,
+           0.15975743338958406,
+           0.16256202414702778,
+           0.1643436178321633,
+           0.16506433168104165,
+           0.1647073011732518,
+           0.16327683177517568,
+           0.16079806760035098,
+           0.15731618788340324,
+           0.15289515340160764,
+           0.1476160356418998,
+           0.1415749713419451,
+           0.134880793793441,
+           0.12765239977264414,
+           0.120015916977615,
+           0.1121017412605604,
+           0.10404151564349565,
+           0.09596512403504937,
+           0.08799777170824954,
+           0.08025722198026607,
+           0.07285125422550161,
+           0.06587540246490393,
+           0.05941102645740831,
+           0.05352375865961601,
+           0.04826236083299258,
+           0.04365801370491651,
+           0.03972405219057297,
+           0.036456147529208296,
+           0.0338329265585863,
+           0.03181700752229146,
+           0.03035642154443295,
+           0.029386379469142545,
+           0.028831335380814494,
+           0.02860729100126505,
+           0.02862427947594249,
+           0.028788962950844647,
+           0.029007275903156864,
+           0.02918704547808333,
+           0.029240521114847883,
+           0.029086748485711057,
+           0.02865372714964609,
+           0.027880297222658654,
+           0.026717707637283875,
+           0.025130827018010244,
+           0.023098967621308954,
+           0.020616302938578072,
+           0.017691870179640058,
+           0.014349159673939396,
+           0.010625303971949999,
+           0.006569889828340345,
+           0.0022434260378556784,
+           -0.0022844909731001397,
+           -0.006937264047617234,
+           -0.01163357837414439,
+           -0.016289819301026846,
+           -0.020822559913916933,
+           -0.02515105152878784,
+           -0.029199650098102492,
+           -0.032900113093575704,
+           -0.0361937046773186,
+           -0.039033051822946696,
+           -0.04138370037807124,
+           -0.043225327710684845,
+           -0.04455257736210605,
+           -0.045375490817568906,
+           -0.04571952185829804,
+           -0.045625129715118215,
+           -0.04514695813186551,
+           -0.04435261819203157,
+           -0.04332110309223162,
+           -0.0421408726993272,
+           -0.0409076544589858,
+           -0.03972201480943667,
+           -0.03868676150085468,
+           -0.037904241966974346,
+           -0.03747360601733707,
+           -0.03748810253248369,
+           -0.03803247950949884,
+           -0.039180554724265446,
+           -0.04099302049590225,
+           -0.04351554064698116,
+           -0.04677719087947067,
+           -0.050789285597377304,
+           -0.055544624902351195,
+           -0.06101718529588685,
+           -0.06716226679162525,
+           -0.07391709794045029,
+           -0.08120188897626462,
+           -0.08892131218108051,
+           -0.09696637792006448,
+           -0.10521666487520319,
+           -0.11354285405777813,
+           -0.12180950842869633,
+           -0.12987803359669273,
+           -0.13760975025827013,
+           -0.14486900591268104,
+           -0.15152625201199943,
+           -0.15746101312882216,
+           -0.16256467693669402,
+           -0.1667430377512434,
+           -0.1699185319805061,
+           -0.1720321109477293,
+           -0.17304470500827904,
+           -0.17293824248016249,
+           -0.1717161974128523,
+           -0.1694036513767944,
+           -0.16604686599511034,
+           -0.1617123745788934,
+           -0.15648561268471062,
+           -0.15046911840835306,
+           -0.14378034349445695,
+           -0.136549125627121,
+           -0.12891488034562953,
+           -0.12102357770496552,
+           -0.11302457391037098,
+           -0.10506737157445531,
+           -0.09729838389144296,
+           -0.08985777785650789,
+           -0.08287646968375878,
+           -0.07647334184336824,
+           -0.07075274573881177,
+           -0.06580234711210797,
+           -0.061691362968667625,
+           -0.05846922935754809,
+           -0.056164728959364835,
+           -0.05478559637718733,
+           -0.054318607565995866,
+           -0.05473014825379116,
+           -0.05596724478495677,
+           -0.05795902983239418,
+           -0.0606186051464918,
+           -0.06384525418562165,
+           -0.06752694933015568,
+           -0.071543091616115,
+           -0.075767415697419,
+           -0.08007098918105447,
+           -0.08432523365987644,
+           -0.08840489473257551,
+           -0.09219089004489872,
+           -0.09557296786190826,
+           -0.0984521137966165,
+           -0.10074264994423285,
+           -0.1023739786348821,
+           -0.10329193211969083,
+           -0.1034596995164952,
+           -0.1028583130110136,
+           -0.10148668637032061,
+           -0.09936121000189242,
+           -0.09651491780520996,
+           -0.09299625164038275,
+           -0.08886745911747304,
+           -0.0842026693470824,
+           -0.07908569906725824,
+           -0.07360764798330324,
+           -0.0678643470691802,
+           -0.06195372686348958,
+           -0.0559731743719652,
+           -0.05001694702735396,
+           -0.0441737102653435,
+           -0.038524261704095605,
+           -0.03313949975914093,
+           -0.028078687918687017,
+           -0.02338805801674435,
+           -0.01909978687479286,
+           -0.01523137086566724,
+           -0.011785412535745082,
+           -0.008749822667969998,
+           -0.006098430351491548,
+           -0.0037919830178885744,
+           -0.0017795082776353264,
+           -1.5703032273566892e-17
+          ],
+          [
+           0,
+           0.0012308156873652451,
+           0.00242123825683391,
+           0.003632893682619467,
+           0.004927190472919895,
+           0.006363387322099254,
+           0.007996713970726141,
+           0.009876596020525886,
+           0.012045031828029048,
+           0.01453516573811572,
+           0.01737009691362479,
+           0.020561956995426255,
+           0.024111282940259885,
+           0.02800670380456928,
+           0.03222495216245217,
+           0.03673120246847406,
+           0.041479730212959774,
+           0.04641487738243124,
+           0.05147230174213495,
+           0.05658048000394018,
+           0.06166242822084382,
+           0.06663759693041459,
+           0.07142389380292137,
+           0.075939782958693,
+           0.08010640779730804,
+           0.08384968319078961,
+           0.08710230326315525,
+           0.08980561270457071,
+           0.09191129261120394,
+           0.09338281612993778,
+           0.09419663461740245,
+           0.09434306146364872,
+           0.09382682802503954,
+           0.0926672940798209,
+           0.09089830366737862,
+           0.08856768589008984,
+           0.08573640902942457,
+           0.0824774049381936,
+           0.07887408890475202,
+           0.0750186078375895,
+           0.07100985649903332,
+           0.06695130745244535,
+           0.06294870522896132,
+           0.05910767884489787,
+           0.05553132911661537,
+           0.05231784816519252,
+           0.04955822805170651,
+           0.04733411364261451,
+           0.04571585161526291,
+           0.04476078305080796,
+           0.044511821432085534,
+           0.04499635120238981,
+           0.046225474508405064,
+           0.04819362552899602,
+           0.05087856308064722,
+           0.0542417432017359,
+           0.058229064370234986,
+           0.06277196912324048,
+           0.0677888773384838,
+           0.07318691851520623,
+           0.07886392324770006,
+           0.08471062789374119,
+           0.09061304135306712,
+           0.09645491901200078,
+           0.10212028637328727,
+           0.10749595373676897,
+           0.11247396355447864,
+           0.11695391374621622,
+           0.12084510328754901,
+           0.12406845069687272,
+           0.12655814154564585,
+           0.1282629676612211,
+           0.12914732812432458,
+           0.12919187030110846,
+           0.1283937577935923,
+           0.12676656113086227,
+           0.12433977603823243,
+           0.12115798299275736,
+           0.11727967028489013,
+           0.11277575075073583,
+           0.10772780952451944,
+           0.10222612641281126,
+           0.09636752166020215,
+           0.09025307783690278,
+           0.08398579323847981,
+           0.07766822348520738,
+           0.07140016791551473,
+           0.0652764558913496,
+           0.05938488531361425,
+           0.05380436155691531,
+           0.04860327977966722,
+           0.043838187281540694,
+           0.03955275542409827,
+           0.03577708278207107,
+           0.032527342848801676,
+           0.029805780988377106,
+           0.027601056624042265,
+           0.02588891809405865,
+           0.02463318940458473,
+           0.02378704046740817,
+           0.02329450551705141,
+           0.023092208426449004,
+           0.023111248729353218,
+           0.02327919843029751,
+           0.023522157228977002,
+           0.023766812662936447,
+           0.023942451904751024,
+           0.023982873527760507,
+           0.02382815043451362,
+           0.02342619924851607,
+           0.022734116696133906,
+           0.021719249717185002,
+           0.02035997308089359,
+           0.018646155969031623,
+           0.016579307124727594,
+           0.014172396546985966,
+           0.011449360124901296,
+           0.008444301838711369,
+           0.005200415998820837,
+           0.0017686592502644937,
+           -0.0017937914447663723,
+           -0.00542525308376657,
+           -0.009061376923242348,
+           -0.012637065278205383,
+           -0.016088413286292985,
+           -0.01935462341118728,
+           -0.022379841111559287,
+           -0.025114862078760614,
+           -0.027518664699623045,
+           -0.029559725848511655,
+           -0.031217083643589025,
+           -0.03248111727708241,
+           -0.03335402128531168,
+           -0.033849959478629295,
+           -0.03399489200624534,
+           -0.03382607747790059,
+           -0.033391260490082446,
+           -0.03274756309582393,
+           -0.031960106506473275,
+           -0.031100396424365,
+           -0.030244511695958404,
+           -0.02947114128486348,
+           -0.028859518756716673,
+           -0.028487306434261166,
+           -0.028428483042937172,
+           -0.028751288978950754,
+           -0.029516282281038458,
+           -0.030774555995858276,
+           -0.032566163950537186,
+           -0.03491879707201635,
+           -0.03784674643914441,
+           -0.04135018236484355,
+           -0.045414771150606104,
+           -0.0500116429220029,
+           -0.05509771534458702,
+           -0.0606163692470928,
+           -0.06649846346030554,
+           -0.07266366773162262,
+           -0.07902208460723872,
+           -0.08547612388463821,
+           -0.0919225868099455,
+           -0.09825491178897663,
+           -0.10436552913396925,
+           -0.11014826938800462,
+           -0.11550076813303423,
+           -0.1203268099392334,
+           -0.12453855526294451,
+           -0.12805859662319927,
+           -0.1308217942243388,
+           -0.1327768462536844,
+           -0.13388755524749701,
+           -0.13413375903718147,
+           -0.1335119026888345,
+           -0.13203523634131356,
+           -0.12973363272483165,
+           -0.12665302718778867,
+           -0.1228544920539259,
+           -0.1184129658557702,
+           -0.11341566623105674,
+           -0.1079602228253555,
+           -0.10215257323218074,
+           -0.0961046706582441,
+           -0.08993205648829886,
+           -0.08375135413189347,
+           -0.07767774238522268,
+           -0.07182246699038396,
+           -0.06629044811113861,
+           -0.06117803909288624,
+           -0.05657098819296743,
+           -0.05254265004623261,
+           -0.04915248759092081,
+           -0.04644489816943889,
+           -0.04444838970948949,
+           -0.043175124474370795,
+           -0.042620839053104244,
+           -0.042765140256872766,
+           -0.043572167617900906,
+           -0.04499160446908477,
+           -0.0469600113295923,
+           -0.04940244773376786,
+           -0.052234341901804635,
+           -0.055363561923436944,
+           -0.05869263754783813,
+           -0.062121078352940416,
+           -0.06554773208333255,
+           -0.06887312634246122,
+           -0.07200173761269213,
+           -0.0748441337321695,
+           -0.07731893942296166,
+           -0.07935457915103583,
+           -0.08089075738561646,
+           -0.08187964306686914,
+           -0.08228673261680158,
+           -0.0820913739498996,
+           -0.08128694245411046,
+           -0.07988066860688445,
+           -0.07789312554861141,
+           -0.07535739334190679,
+           -0.07231792459148018,
+           -0.06882914338936263,
+           -0.06495381600443967,
+           -0.06076123719512684,
+           -0.05632528035636087,
+           -0.051722362811995715,
+           -0.047029379357322494,
+           -0.04232165760270791,
+           -0.0376709877609426,
+           -0.033143777284434836,
+           -0.028799377253682115,
+           -0.024688622736988727,
+           -0.020852623604023658,
+           -0.017321835629658007,
+           -0.014115434339348193,
+           -0.011241006111185097,
+           -0.008694562764309414,
+           -0.006460877438924432,
+           -0.004514131223117793,
+           -0.002818851917589367,
+           -0.0013311187552393273,
+           -1.1843493770707101e-17
+          ],
+          [
+           0,
+           0.0008678594917907776,
+           0.001727667107702416,
+           0.002623474976496898,
+           0.0035984330673362193,
+           0.0046934262827384885,
+           0.005945770209608244,
+           0.007388000808831593,
+           0.009046790933597833,
+           0.010942023328478614,
+           0.013086045756747561,
+           0.015483129233204003,
+           0.018129145121468154,
+           0.021011471219844466,
+           0.024109131050529694,
+           0.027393164532368244,
+           0.030827222210059856,
+           0.034368369384757375,
+           0.03796808099012057,
+           0.04157340302389074,
+           0.04512825190620089,
+           0.0485748194057023,
+           0.05185504784915648,
+           0.05491213828541311,
+           0.05769205316473922,
+           0.06014497495007031,
+           0.06222668290459476,
+           0.06389981208255101,
+           0.06513496124569736,
+           0.06591161997221337,
+           0.06621888953208316,
+           0.06605597706835825,
+           0.06543244812552411,
+           0.06436822846929399,
+           0.06289335230102075,
+           0.061047460232358575,
+           0.05887905659670701,
+           0.05644454167913611,
+           0.053807040096490885,
+           0.05103505171323492,
+           0.04820095600732558,
+           0.04537940459021613,
+           0.04264563954017704,
+           0.040073777253180176,
+           0.037735098597567004,
+           0.0356963862482625,
+           0.034018349168452325,
+           0.0327541723210391,
+           0.03194822687256966,
+           0.031634972465486785,
+           0.03183807866874669,
+           0.03256978757958697,
+           0.033830533864713755,
+           0.035608832435186734,
+           0.03788143759383052,
+           0.040613771031686285,
+           0.043760609638213786,
+           0.047267017884946194,
+           0.05106950369543255,
+           0.05509737136824439,
+           0.059274240405080385,
+           0.06351969512764119,
+           0.06775102684186139,
+           0.07188502810247703,
+           0.07583979739854202,
+           0.07953651235128627,
+           0.08290113029499609,
+           0.08586597688007572,
+           0.08837118605155954,
+           0.09036595834946204,
+           0.09180960886128632,
+           0.09267238122434965,
+           0.09293600970218956,
+           0.09259401740750683,
+           0.09165174506598402,
+           0.09012611115645215,
+           0.0880451106660843,
+           0.0854470659085266,
+           0.0823796487170571,
+           0.0788986987016125,
+           0.0750668670176427,
+           0.07095211912144037,
+           0.06662613318424195,
+           0.06216263312995198,
+           0.057635696595187476,
+           0.05311807845552957,
+           0.04867958991291058,
+           0.04438557151495309,
+           0.040295495920846816,
+           0.0364617328059299,
+           0.0329285040957307,
+           0.029731052846076907,
+           0.026895043661647765,
+           0.024436206707031984,
+           0.022360231257895793,
+           0.020662908517536285,
+           0.019330517240659054,
+           0.018340439715160747,
+           0.017661990002336616,
+           0.017257431165803208,
+           0.01708315365678795,
+           0.01709098318013848,
+           0.01722958333512459,
+           0.017445916181039217,
+           0.01768672267067693,
+           0.017899984652386354,
+           0.018036330866799722,
+           0.01805035103656957,
+           0.01790178472185086,
+           0.01755655502370556,
+           0.016987621374105477,
+           0.01617563044820133,
+           0.015109349549535382,
+           0.013785872516585806,
+           0.012210594134700643,
+           0.010396955060540928,
+           0.008365965224027418,
+           0.006145519414660234,
+           0.0037695241397271107,
+           0.001276859725291308,
+           -0.001289794106477647,
+           -0.003885237415831994,
+           -0.006463099495593103,
+           -0.008977222278746151,
+           -0.011383040492268223,
+           -0.013638921404692663,
+           -0.015707428028170108,
+           -0.01755647157831939,
+           -0.01916032181827339,
+           -0.020500447546103615,
+           -0.021566163835908144,
+           -0.02235506760275226,
+           -0.02287324850542333,
+           -0.023135267991358833,
+           -0.02316390527900663,
+           -0.022989675112949647,
+           -0.022650128063594434,
+           -0.02218894982571071,
+           -0.0216548812543887,
+           -0.021100485628604934,
+           -0.02058079373025272,
+           -0.02015186066508775,
+           -0.019869270845303166,
+           -0.01978662913613445,
+           -0.019954076798436846,
+           -0.02041687051678647,
+           -0.02121406149380584,
+           -0.02237730934575912,
+           -0.02392986240511391,
+           -0.025885732098018806,
+           -0.02824908441412273,
+           -0.031013866236471406,
+           -0.03416367857914741,
+           -0.03767190273066521,
+           -0.04150207907120366,
+           -0.045608532075685444,
+           -0.04993722888764122,
+           -0.05442685300299557,
+           -0.05901006918405726,
+           -0.06361495086747446,
+           -0.0681665371575167,
+           -0.0725884831128694,
+           -0.07680476452701943,
+           -0.0807413968336508,
+           -0.08432812718057542,
+           -0.08750005912582665,
+           -0.09019917081027366,
+           -0.09237568982068865,
+           -0.09398929122019856,
+           -0.09501008931169652,
+           -0.09541939851589812,
+           -0.09521024417309301,
+           -0.09438760998486945,
+           -0.09296841505583717,
+           -0.09098121992387663,
+           -0.08846566742422418,
+           -0.0854716705604539,
+           -0.08205836559984611,
+           -0.07829285422427731,
+           -0.07424876361361799,
+           -0.0700046576935102,
+           -0.06564233633702815,
+           -0.06124506198325165,
+           -0.05689575486006435,
+           -0.05267519873151314,
+           -0.04866029881419618,
+           -0.044922432229340246,
+           -0.041525929109043014,
+           -0.038526719311858054,
+           -0.03597117570211256,
+           -0.03389518020721151,
+           -0.03232343350379356,
+           -0.0312690233283061,
+           -0.030733260203575287,
+           -0.03070578297189679,
+           -0.03116493008336881,
+           -0.03207836626271132,
+           -0.033403948122711705,
+           -0.03509080665488595,
+           -0.037080619444654725,
+           -0.039309041052177744,
+           -0.04170725637701704,
+           -0.044203619071573254,
+           -0.0467253352498224,
+           -0.04920015189616484,
+           -0.051558009531955426,
+           -0.053732619837740886,
+           -0.055662931026262075,
+           -0.057294446760256273,
+           -0.058580368233169006,
+           -0.05948253358306619,
+           -0.059972133975492996,
+           -0.060030191340022764,
+           -0.0596477887363716,
+           -0.05882605050964638,
+           -0.05757587561655815,
+           -0.055917433610644815,
+           -0.053879438613353293,
+           -0.05149822202484659,
+           -0.04881662960981715,
+           -0.04588277280947869,
+           -0.04274866757819154,
+           -0.039468796638160934,
+           -0.03609863272607524,
+           -0.03269316113214593,
+           -0.02930543958939923,
+           -0.025985232368143395,
+           -0.022777753300210746,
+           -0.019722549455920484,
+           -0.016852553401534298,
+           -0.014193327473856791,
+           -0.011762518436454383,
+           -0.009569535358028642,
+           -0.007615457718252371,
+           -0.005893174747981725,
+           -0.004387751001246407,
+           -0.0030770072879582745,
+           -0.0019323005173606921,
+           -0.0009194808539423287,
+           -8.25935980239455e-18
+          ],
+          [
+           0,
+           0.0005182704059053997,
+           0.0010442285879333235,
+           0.0016040947485557822,
+           0.0022231041890830496,
+           0.0029247069438672105,
+           0.0037298147045610147,
+           0.0046561154417779525,
+           0.005717474399494026,
+           0.006923437923636263,
+           0.008278853946253169,
+           0.0097836199469659,
+           0.011432565929676947,
+           0.013215476467606633,
+           0.015117252271629312,
+           0.01711820811653087,
+           0.019194500408822146,
+           0.021318674288113095,
+           0.023460317007898353,
+           0.025586801521012458,
+           0.027664101772020652,
+           0.029657659235605625,
+           0.03153327878735282,
+           0.03325803108928797,
+           0.03480113834146408,
+           0.03613482050292361,
+           0.037235079915990586,
+           0.03808240365812159,
+           0.03866236486247615,
+           0.03896610664575121,
+           0.03899069510135992,
+           0.03873933098876508,
+           0.03822141319778903,
+           0.037452450705067496,
+           0.03645382347861976,
+           0.03525239653319032,
+           0.0338799950005918,
+           0.032372751564656174,
+           0.030770340832660233,
+           0.029115118093634523,
+           0.027451182376529003,
+           0.025823385705672,
+           0.024276311906883802,
+           0.02285324920751601,
+           0.02159518117400361,
+           0.020539820232165964,
+           0.019720707124140733,
+           0.01916639819178718,
+           0.01889976037407368,
+           0.018937391313126314,
+           0.019289179040135787,
+           0.019958012428769496,
+           0.020939650039625085,
+           0.022222751221102115,
+           0.023789069471239578,
+           0.025613804195574238,
+           0.02766610321222965,
+           0.029909704749550913,
+           0.032303704341668925,
+           0.03480342903497139,
+           0.037361398746669466,
+           0.03992835252830934,
+           0.0424543159331999,
+           0.0448896847052507,
+           0.04718629962158068,
+           0.049298487541788144,
+           0.0511840445375011,
+           0.05280513837655128,
+           0.0541291095824843,
+           0.055129152734410235,
+           0.05578486255454108,
+           0.05608263258059457,
+           0.056015897758051915,
+           0.05558521602655898,
+           0.05479818782420062,
+           0.05366921629902067,
+           0.052219114804768825,
+           0.050474571875237566,
+           0.048467487230812754,
+           0.046234195390572316,
+           0.04381459607046414,
+           0.04125121268006628,
+           0.03858820183625567,
+           0.035870337853897274,
+           0.033141996627466,
+           0.030446163173917507,
+           0.027823486371434128,
+           0.025311403120806278,
+           0.022943352310127337,
+           0.020748096626373325,
+           0.018749167488525068,
+           0.01696444524591017,
+           0.015405883370969743,
+           0.014079381763065222,
+           0.012984810559356953,
+           0.01211618211278003,
+           0.011461965138463665,
+           0.011005531539210633,
+           0.010725723184103395,
+           0.010597523011659619,
+           0.010592812331452199,
+           0.010681194166721456,
+           0.01083086096447534,
+           0.011009484035168016,
+           0.011185101693699195,
+           0.011326983265225509,
+           0.011406446886598014,
+           0.011397610356226755,
+           0.011278056127064664,
+           0.011029393851487284,
+           0.010637706613641098,
+           0.01009387005462247,
+           0.009393736930391475,
+           0.008538183156859485,
+           0.007533015001932667,
+           0.0063887406890908004,
+           0.005120213190093907,
+           0.0037461543167870586,
+           0.0022885732895011504,
+           0.000772095684724567,
+           -0.000776779021275886,
+           -0.0023304712518117895,
+           -0.003861145082837748,
+           -0.005341539782018477,
+           -0.006745786757133491,
+           -0.008050189903031723,
+           -0.009233948267936271,
+           -0.010279801433816375,
+           -0.011174579984733157,
+           -0.011909645871715717,
+           -0.012481210311526167,
+           -0.012890520008335571,
+           -0.013143905882376943,
+           -0.013252692042387146,
+           -0.013232966359338733,
+           -0.01310521759604475,
+           -0.012893847529589147,
+           -0.012626569782873291,
+           -0.012333710074500638,
+           -0.012047425226449422,
+           -0.011800860469184438,
+           -0.011627266297373918,
+           -0.011559097311663482,
+           -0.011627116101683684,
+           -0.011859525265345349,
+           -0.012281150116684975,
+           -0.012912693520820554,
+           -0.013770082636013046,
+           -0.014863925179119952,
+           -0.016199090214287788,
+           -0.017774425459387882,
+           -0.019582619784113197,
+           -0.021610216019512532,
+           -0.023837775498715758,
+           -0.0262401919942248,
+           -0.028787149001466037,
+           -0.031443710733665434,
+           -0.03417103382877844,
+           -0.0369271837092262,
+           -0.03966803685620841,
+           -0.04234824802979828,
+           -0.044922259740324065,
+           -0.04734533009980445,
+           -0.04957455458506099,
+           -0.05156985724294466,
+           -0.053294927464614165,
+           -0.05471807963695661,
+           -0.05581301471759809,
+           -0.056559465034310405,
+           -0.056943706325982675,
+           -0.05695892415528444,
+           -0.05660542525741691,
+           -0.05589068806167279,
+           -0.05482925044367498,
+           -0.053442436643169784,
+           -0.051757929120650886,
+           -0.04980919483230445,
+           -0.04763477888633872,
+           -0.04527748171966509,
+           -0.042783438724541316,
+           -0.04020112359202344,
+           -0.037580298465782216,
+           -0.03497093527141865,
+           -0.03242213327183259,
+           -0.02998105798175055,
+           -0.027691926052304836,
+           -0.025595059622414585,
+           -0.02372603195504322,
+           -0.0221149239743346,
+           -0.020785708648140704,
+           -0.019755777084964437,
+           -0.019035616810110224,
+           -0.01862864903613437,
+           -0.018531227936698317,
+           -0.01873280106358732,
+           -0.019216226208343887,
+           -0.019958236296178586,
+           -0.020930040400884704,
+           -0.02209804577032078,
+           -0.023424682930068195,
+           -0.024869313556168227,
+           -0.026389198933385195,
+           -0.027940505487772667,
+           -0.029479323132445005,
+           -0.030962672010115523,
+           -0.032349473657203726,
+           -0.033601463639489335,
+           -0.03468402429137629,
+           -0.03556691828912199,
+           -0.036224906349506696,
+           -0.03663823530469419,
+           -0.03679298608706813,
+           -0.03668127468239385,
+           -0.036301302787725566,
+           -0.035657258650423795,
+           -0.034759072273516795,
+           -0.033622032758460735,
+           -0.03226627893042594,
+           -0.030716177470321678,
+           -0.028999605486162056,
+           -0.027147156727752458,
+           -0.02519129242776485,
+           -0.023165458996184066,
+           -0.021103195474406197,
+           -0.019037253754671492,
+           -0.01699875408926609,
+           -0.015016397365781687,
+           -0.013115754037611739,
+           -0.011318647514151613,
+           -0.009642647286621429,
+           -0.008100684157854268,
+           -0.006700796731994019,
+           -0.005446014884593683,
+           -0.0043343823623319296,
+           -0.003359117045033594,
+           -0.002508903832471501,
+           -0.0017683116848651952,
+           -0.001118323135888138,
+           -0.0005369616914575457,
+           -4.87490771407221e-18
+          ],
+          [
+           0,
+           0.00017339323377322909,
+           0.0003534988980570004,
+           0.0005489102183198984,
+           0.0007677470250585584,
+           0.0010173970330554355,
+           0.0013042767821381629,
+           0.0016336187302478664,
+           0.0020092903179201806,
+           0.0024336500012493724,
+           0.0029074442987651133,
+           0.0034297488404040704,
+           0.00399795527058505,
+           0.0046078046709892165,
+           0.00525346696199217,
+           0.005927664545323086,
+           0.006621837294746883,
+           0.007326344915708905,
+           0.00803070170656269,
+           0.008723837888426858,
+           0.009394380950053254,
+           0.010030949896901818,
+           0.010622454914407876,
+           0.011158394764259505,
+           0.011629144234748845,
+           0.01202622416246296,
+           0.0123425469284251,
+           0.012572630898223813,
+           0.012712778009079734,
+           0.012761209589404557,
+           0.012718156506645909,
+           0.012585900852298304,
+           0.012368767561486782,
+           0.01207306559914849,
+           0.011706979594986611,
+           0.011280414044031859,
+           0.010804793378115768,
+           0.010292822326207887,
+           0.009758211990582612,
+           0.009215377945851453,
+           0.008679117396852815,
+           0.008164272990754654,
+           0.00768539125416961,
+           0.007256383807799424,
+           0.006890199494067591,
+           0.006598515337216773,
+           0.00639145384519426,
+           0.006277333567873083,
+           0.006262459060870217,
+           0.006350955486759634,
+           0.006544652037942172,
+           0.006843017213163487,
+           0.007243147750612812,
+           0.007739811744558678,
+           0.008325545180642309,
+           0.008990799848738146,
+           0.009724139362836566,
+           0.010512478864720943,
+           0.011341362940458101,
+           0.012195275361502904,
+           0.013057973497961287,
+           0.013912839658944494,
+           0.014743241208480268,
+           0.015532891095055413,
+           0.01626620042369392,
+           0.016928614891737463,
+           0.017506927298474414,
+           0.017989558914932095,
+           0.01836680324939007,
+           0.018631026648157786,
+           0.018776821207761033,
+           0.01880110661855517,
+           0.01870317878296493,
+           0.018484704324167003,
+           0.018149661392022974,
+           0.01770422845096101,
+           0.017156623968178266,
+           0.016516901079999993,
+           0.015796702371353697,
+           0.015008980832522138,
+           0.014167693836227527,
+           0.013287477588006595,
+           0.01238330992927859,
+           0.011470169605540984,
+           0.010562700146587344,
+           0.009674886341256381,
+           0.008819750930626442,
+           0.008009078600172255,
+           0.00725317363715133,
+           0.006560656752520504,
+           0.005938305568868403,
+           0.005390942172241334,
+           0.004921369943954013,
+           0.004530360658001126,
+           0.004216691581146921,
+           0.003977231077175342,
+           0.0038070700247419056,
+           0.0036996952392450533,
+           0.0036472000707063624,
+           0.003640526456832361,
+           0.003669731965058876,
+           0.0037242747775645684,
+           0.0037933091729302182,
+           0.0038659838467540787,
+           0.00393173539581447,
+           0.003980569466155175,
+           0.004003322429776257,
+           0.003991896997756781,
+           0.003939465885469513,
+           0.0038406384998259575,
+           0.0036915865973269108,
+           0.0034901259401139695,
+           0.0032357521277853116,
+           0.0029296299762444447,
+           0.002574537021045081,
+           0.002174762911044178,
+           0.0017359675986300608,
+           0.0012650022965344505,
+           0.0007696981314061073,
+           0.0002586282566839654,
+           -0.0002591501291428336,
+           -0.0007743668953041086,
+           -0.0012778159205756516,
+           -0.0017606304114509903,
+           -0.0022145491846591757,
+           -0.002632166733184848,
+           -0.003007160310727114,
+           -0.003334487859471304,
+           -0.003610551355281103,
+           -0.003833321034064544,
+           -0.004002416970695334,
+           -0.004119145582059476,
+           -0.004186489790773496,
+           -0.004209052786453401,
+           -0.004192956526748402,
+           -0.0041456973001760735,
+           -0.0040759617971909785,
+           -0.003993408176325795,
+           -0.003908417542167662,
+           -0.003831822047611891,
+           -0.0037746164738397376,
+           -0.0037476606112100967,
+           -0.0037613800504164643,
+           -0.003825473088095809,
+           -0.003948631351618417,
+           -0.004138281455927854,
+           -0.004400354527745118,
+           -0.004739089780563933,
+           -0.005156877513388607,
+           -0.005654145956837417,
+           -0.006229295325298233,
+           -0.006878681279456899,
+           -0.007596648788188489,
+           -0.008375616132555217,
+           -0.009206207548378429,
+           -0.010077431788502641,
+           -0.010976902731709811,
+           -0.011891097101078746,
+           -0.01280564340706705,
+           -0.013705635423531419,
+           -0.014575962858688101,
+           -0.0154016514140998,
+           -0.01616820414526722,
+           -0.016861935954753444,
+           -0.017470293165581578,
+           -0.01798215043661892,
+           -0.018388077785615894,
+           -0.018680571167640696,
+           -0.018854240900571074,
+           -0.01890595321478849,
+           -0.01883492130747415,
+           -0.01864274347620753,
+           -0.01833338716291674,
+           -0.01791311902706873,
+           -0.017390382454948648,
+           -0.01677562516855534,
+           -0.016081080792367315,
+           -0.015320509339833354,
+           -0.01450890256694947,
+           -0.013662160983608933,
+           -0.01279674999393437,
+           -0.011929343137882308,
+           -0.011076460715789948,
+           -0.010254112187659571,
+           -0.009477450647150505,
+           -0.008760447378741303,
+           -0.00811559402247119,
+           -0.0075536392059324135,
+           -0.007083365674037591,
+           -0.006711412973816461,
+           -0.006442149657919311,
+           -0.0062775977833497585,
+           -0.0062174112302309835,
+           -0.006258908079684602,
+           -0.006397156001535683,
+           -0.006625108342944231,
+           -0.006933787408850538,
+           -0.007312510313461863,
+           -0.007749151785837576,
+           -0.008230437456010023,
+           -0.008742260451603482,
+           -0.009270013615212574,
+           -0.00979892932211851,
+           -0.010314418743840304,
+           -0.01080240246826057,
+           -0.011249624649442083,
+           -0.011643943312719583,
+           -0.01197459007149303,
+           -0.012232393305276073,
+           -0.012409959783893124,
+           -0.012501810776742825,
+           -0.012504469832333302,
+           -0.0124165006232041,
+           -0.01223849449473147,
+           -0.011973008602253034,
+           -0.011624456738543018,
+           -0.011198956112786365,
+           -0.01070413441423269,
+           -0.010148902452278643,
+           -0.00954319848633355,
+           -0.008897711023432314,
+           -0.008223587353093371,
+           -0.007532135395649226,
+           -0.006834526555108241,
+           -0.006141507188255126,
+           -0.005463126030733604,
+           -0.004808484465634655,
+           -0.004185515892593661,
+           -0.0036007996718259694,
+           -0.0030594141980323404,
+           -0.002564832627187794,
+           -0.0021188636611782583,
+           -0.0017216386194808888,
+           -0.0013716448234184244,
+           -0.0010658041174433862,
+           -0.0007995941838110914,
+           -0.000567209201406425,
+           -0.0003617553843263256,
+           -0.00017547603671591895,
+           -1.611457989444377e-18
+          ],
+          [
+           0,
+           -0.00017547603671590374,
+           -0.00036175538432630213,
+           -0.0005672092014063924,
+           -0.0007995941838110469,
+           -0.00106580411744332,
+           -0.001371644823418345,
+           -0.0017216386194807934,
+           -0.002118863661178131,
+           -0.002564832627187649,
+           -0.0030594141980321773,
+           -0.0036007996718257604,
+           -0.004185515892593416,
+           -0.004808484465634387,
+           -0.0054631260307333,
+           -0.006141507188254782,
+           -0.00683452655510787,
+           -0.00753213539564883,
+           -0.008223587353092922,
+           -0.008897711023431827,
+           -0.00954319848633304,
+           -0.010148902452278095,
+           -0.010704134414232118,
+           -0.011198956112785775,
+           -0.011624456738542397,
+           -0.0119730086022524,
+           -0.012238494494730835,
+           -0.012416500623203456,
+           -0.012504469832332644,
+           -0.012501810776742183,
+           -0.012409959783892489,
+           -0.012232393305275445,
+           -0.011974590071492403,
+           -0.011643943312718993,
+           -0.011249624649441544,
+           -0.010802402468260001,
+           -0.01031441874383978,
+           -0.009798929322118037,
+           -0.009270013615212114,
+           -0.008742260451603031,
+           -0.008230437456009616,
+           -0.007749151785837207,
+           -0.007312510313461473,
+           -0.006933787408850189,
+           -0.006625108342943896,
+           -0.006397156001535358,
+           -0.006258908079684276,
+           -0.006217411230230658,
+           -0.006277597783349425,
+           -0.006442149657918972,
+           -0.006711412973816104,
+           -0.007083365674037201,
+           -0.007553639205931996,
+           -0.008115594022470723,
+           -0.008760447378740816,
+           -0.009477450647149959,
+           -0.010254112187659,
+           -0.011076460715789355,
+           -0.011929343137881644,
+           -0.012796749993933685,
+           -0.013662160983608179,
+           -0.014508902566948673,
+           -0.015320509339832514,
+           -0.01608108079236644,
+           -0.016775625168554447,
+           -0.017390382454947707,
+           -0.017913119027067756,
+           -0.018333387162915757,
+           -0.01864274347620654,
+           -0.018834921307473156,
+           -0.018905953214787493,
+           -0.018854240900570085,
+           -0.018680571167639718,
+           -0.018388077785614947,
+           -0.01798215043661799,
+           -0.017470293165580665,
+           -0.016861935954752584,
+           -0.016168204145266377,
+           -0.01540165141409899,
+           -0.01457596285868739,
+           -0.013705635423530736,
+           -0.012805643407066412,
+           -0.01189109710107816,
+           -0.010976902731709273,
+           -0.010077431788502126,
+           -0.009206207548377959,
+           -0.008375616132554825,
+           -0.007596648788188102,
+           -0.006878681279456563,
+           -0.006229295325297916,
+           -0.005654145956837137,
+           -0.005156877513388352,
+           -0.004739089780563697,
+           -0.004400354527744902,
+           -0.004138281455927644,
+           -0.00394863135161821,
+           -0.0038254730880956105,
+           -0.003761380050416263,
+           -0.003747660611209896,
+           -0.003774616473839534,
+           -0.003831822047611688,
+           -0.003908417542167451,
+           -0.003993408176325581,
+           -0.004075961797190753,
+           -0.004145697300175841,
+           -0.004192956526748178,
+           -0.004209052786453175,
+           -0.00418648979077328,
+           -0.004119145582059252,
+           -0.004002416970695124,
+           -0.0038333210340643366,
+           -0.0036105513552809098,
+           -0.0033344878594711346,
+           -0.0030071603107269546,
+           -0.0026321667331847204,
+           -0.002214549184659062,
+           -0.0017606304114509022,
+           -0.0012778159205755974,
+           -0.0007743668953040727,
+           -0.0002591501291428336,
+           0.00025862825668393827,
+           0.0007696981314060624,
+           0.0012650022965343718,
+           0.0017359675986299652,
+           0.0021747629110440616,
+           0.0025745370210449358,
+           0.002929629976244292,
+           0.0032357521277851407,
+           0.0034901259401137904,
+           0.003691586597326723,
+           0.0038406384998257567,
+           0.003939465885469314,
+           0.0039918969977565675,
+           0.004003322429776052,
+           0.003980569466154969,
+           0.0039317353958142716,
+           0.003865983846753886,
+           0.0037933091729300283,
+           0.003724274777564385,
+           0.003669731965058685,
+           0.003640526456832173,
+           0.0036472000707061716,
+           0.0036996952392448603,
+           0.0038070700247417022,
+           0.003977231077175129,
+           0.004216691581146685,
+           0.004530360658000874,
+           0.004921369943953742,
+           0.005390942172241034,
+           0.005938305568868073,
+           0.006560656752520149,
+           0.0072531736371509205,
+           0.008009078600171823,
+           0.008819750930625946,
+           0.00967488634125586,
+           0.010562700146586756,
+           0.011470169605540342,
+           0.012383309929277882,
+           0.013287477588005869,
+           0.014167693836226746,
+           0.015008980832521316,
+           0.01579670237135286,
+           0.016516901079999105,
+           0.017156623968177343,
+           0.017704228450960067,
+           0.01814966139202201,
+           0.018484704324166025,
+           0.018703178782963948,
+           0.018801106618554185,
+           0.018776821207760048,
+           0.018631026648156825,
+           0.018366803249389118,
+           0.017989558914931172,
+           0.017506927298473515,
+           0.0169286148917366,
+           0.0162662004236931,
+           0.015532891095054626,
+           0.014743241208479509,
+           0.0139128396589438,
+           0.013057973497960661,
+           0.0121952753615023,
+           0.011341362940457542,
+           0.010512478864720424,
+           0.009724139362836087,
+           0.008990799848737685,
+           0.008325545180641894,
+           0.007739811744558308,
+           0.007243147750612451,
+           0.006843017213163151,
+           0.006544652037941838,
+           0.006350955486759302,
+           0.006262459060869889,
+           0.006277333567872749,
+           0.006391453845193922,
+           0.006598515337216414,
+           0.0068901994940672034,
+           0.007256383807799025,
+           0.007685391254169197,
+           0.008164272990754201,
+           0.008679117396852317,
+           0.009215377945850943,
+           0.009758211990582072,
+           0.010292822326207303,
+           0.010804793378115173,
+           0.011280414044031262,
+           0.011706979594985973,
+           0.012073065599147852,
+           0.012368767561486117,
+           0.012585900852297625,
+           0.012718156506645222,
+           0.012761209589403872,
+           0.012712778009079072,
+           0.012572630898223157,
+           0.012342546928424455,
+           0.01202622416246233,
+           0.011629144234748246,
+           0.011158394764258926,
+           0.010622454914407331,
+           0.010030949896901308,
+           0.009394380950052775,
+           0.008723837888426409,
+           0.00803070170656229,
+           0.007326344915708526,
+           0.006621837294746553,
+           0.005927664545322803,
+           0.005253466961991915,
+           0.004607804670988994,
+           0.003997955270584854,
+           0.0034297488404039095,
+           0.002907444298764966,
+           0.0024336500012492567,
+           0.002009290317920092,
+           0.0016336187302477864,
+           0.0013042767821381026,
+           0.0010173970330553891,
+           0.0007677470250585184,
+           0.0005489102183198725,
+           0.0003534988980569862,
+           0.00017339323377322575,
+           1.6114579894442915e-18
+          ],
+          [
+           0,
+           -0.0005369616914575236,
+           -0.0011183231358881168,
+           -0.0017683116848651755,
+           -0.0025089038324714857,
+           -0.0033591170450335524,
+           -0.0043343823623318775,
+           -0.005446014884593633,
+           -0.006700796731993926,
+           -0.008100684157854185,
+           -0.009642647286621361,
+           -0.01131864751415148,
+           -0.013115754037611624,
+           -0.015016397365781546,
+           -0.01699875408926593,
+           -0.019037253754671312,
+           -0.021103195474406027,
+           -0.023165458996183916,
+           -0.02519129242776464,
+           -0.027147156727752267,
+           -0.028999605486161845,
+           -0.030716177470321442,
+           -0.03226627893042571,
+           -0.03362203275846051,
+           -0.034759072273516545,
+           -0.03565725865042356,
+           -0.03630130278772533,
+           -0.0366812746823936,
+           -0.036792986087067894,
+           -0.036638235304694004,
+           -0.03622490634950653,
+           -0.03556691828912181,
+           -0.03468402429137608,
+           -0.03360146363948909,
+           -0.03234947365720355,
+           -0.03096267201011532,
+           -0.029479323132444873,
+           -0.027940505487772622,
+           -0.026389198933385104,
+           -0.02486931355616809,
+           -0.023424682930068108,
+           -0.022098045770320658,
+           -0.02093004040088456,
+           -0.019958236296178496,
+           -0.019216226208343797,
+           -0.018732801063587226,
+           -0.0185312279366982,
+           -0.01862864903613425,
+           -0.0190356168101101,
+           -0.019755777084964316,
+           -0.02078570864814055,
+           -0.022114923974334403,
+           -0.023726031955042998,
+           -0.02559505962241429,
+           -0.027691926052304576,
+           -0.02998105798175033,
+           -0.03242213327183228,
+           -0.03497093527141839,
+           -0.03758029846578187,
+           -0.040201123592023144,
+           -0.04278343872454093,
+           -0.0452774817196647,
+           -0.04763477888633845,
+           -0.049809194832304046,
+           -0.051757929120650525,
+           -0.05344243664316938,
+           -0.05482925044367463,
+           -0.05589068806167239,
+           -0.056605425257416526,
+           -0.05695892415528407,
+           -0.05694370632598232,
+           -0.056559465034310044,
+           -0.05581301471759775,
+           -0.05471807963695629,
+           -0.053294927464613895,
+           -0.05156985724294435,
+           -0.04957455458506076,
+           -0.04734533009980418,
+           -0.044922259740323774,
+           -0.04234824802979812,
+           -0.03966803685620821,
+           -0.03692718370922607,
+           -0.034171033828778334,
+           -0.03144371073366536,
+           -0.028787149001465895,
+           -0.026240191994224615,
+           -0.023837775498715692,
+           -0.021610216019512386,
+           -0.019582619784113145,
+           -0.017774425459387764,
+           -0.01619909021428773,
+           -0.01486392517911988,
+           -0.013770082636012987,
+           -0.0129126935208205,
+           -0.012281150116684913,
+           -0.011859525265345278,
+           -0.01162711610168361,
+           -0.011559097311663394,
+           -0.011627266297373847,
+           -0.011800860469184344,
+           -0.01204742522644936,
+           -0.012333710074500537,
+           -0.012626569782873203,
+           -0.012893847529589029,
+           -0.013105217596044647,
+           -0.013232966359338665,
+           -0.013252692042387047,
+           -0.013143905882376895,
+           -0.012890520008335463,
+           -0.012481210311526108,
+           -0.011909645871715625,
+           -0.011174579984733087,
+           -0.010279801433816328,
+           -0.009233948267936214,
+           -0.008050189903031711,
+           -0.006745786757133457,
+           -0.00534153978201846,
+           -0.003861145082837763,
+           -0.0023304712518117895,
+           -0.0007767790212759219,
+           0.0007720956847245219,
+           0.0022885732895011218,
+           0.0037461543167869988,
+           0.005120213190093859,
+           0.0063887406890907545,
+           0.007533015001932581,
+           0.008538183156859436,
+           0.009393736930391403,
+           0.010093870054622407,
+           0.010637706613641048,
+           0.0110293938514872,
+           0.011278056127064619,
+           0.011397610356226651,
+           0.011406446886597959,
+           0.01132698326522542,
+           0.011185101693699143,
+           0.011009484035167974,
+           0.010830860964475277,
+           0.010681194166721402,
+           0.010592812331452123,
+           0.010597523011659558,
+           0.01072572318410332,
+           0.011005531539210564,
+           0.011461965138463577,
+           0.012116182112779943,
+           0.012984810559356838,
+           0.014079381763065087,
+           0.015405883370969596,
+           0.01696444524591003,
+           0.018749167488524884,
+           0.0207480966263732,
+           0.0229433523101271,
+           0.02531140312080613,
+           0.02782348637143385,
+           0.030446163173917323,
+           0.03314199662746576,
+           0.03587033785389694,
+           0.03858820183625532,
+           0.04125121268006592,
+           0.043814596070463806,
+           0.04623419539057193,
+           0.04846748723081246,
+           0.050474571875237226,
+           0.05221911480476844,
+           0.05366921629902033,
+           0.05479818782420025,
+           0.055585216026558616,
+           0.05601589775805157,
+           0.0560826325805942,
+           0.055784862554540744,
+           0.05512915273440993,
+           0.05412910958248401,
+           0.05280513837655101,
+           0.051184044537500785,
+           0.049298487541787915,
+           0.0471862996215804,
+           0.04488968470525051,
+           0.0424543159331996,
+           0.0399283525283092,
+           0.03736139874666934,
+           0.03480342903497121,
+           0.03230370434166883,
+           0.029909704749550767,
+           0.027666103212229568,
+           0.0256138041955741,
+           0.0237890694712395,
+           0.02222275122110207,
+           0.020939650039624995,
+           0.019958012428769406,
+           0.019289179040135683,
+           0.018937391313126196,
+           0.018899760374073562,
+           0.01916639819178704,
+           0.019720707124140598,
+           0.020539820232165787,
+           0.02159518117400342,
+           0.022853249207515806,
+           0.02427631190688367,
+           0.025823385705671813,
+           0.027451182376528757,
+           0.02911511809363431,
+           0.03077034083265995,
+           0.032372751564655834,
+           0.03387999500059152,
+           0.0352523965331901,
+           0.036453823478619495,
+           0.03745245070506729,
+           0.03822141319778879,
+           0.03873933098876481,
+           0.03899069510135963,
+           0.03896610664575093,
+           0.03866236486247592,
+           0.03808240365812138,
+           0.03723507991599036,
+           0.0361348205029234,
+           0.034801138341463915,
+           0.03325803108928777,
+           0.03153327878735266,
+           0.02965765923560548,
+           0.02766410177202052,
+           0.02558680152101231,
+           0.023460317007898263,
+           0.021318674288112967,
+           0.019194500408822066,
+           0.01711820811653083,
+           0.015117252271629262,
+           0.013215476467606594,
+           0.011432565929676904,
+           0.009783619946965893,
+           0.008278853946253124,
+           0.006923437923636246,
+           0.005717474399494033,
+           0.004656115441777936,
+           0.0037298147045610104,
+           0.0029247069438672092,
+           0.0022231041890830353,
+           0.0016040947485557791,
+           0.0010442285879333289,
+           0.0005182704059054134,
+           4.874907714072175e-18
+          ],
+          [
+           0,
+           -0.0009194808539422866,
+           -0.0019323005173606468,
+           -0.003077007287958227,
+           -0.0043877510012463455,
+           -0.005893174747981604,
+           -0.007615457718252246,
+           -0.009569535358028514,
+           -0.01176251843645417,
+           -0.014193327473856588,
+           -0.016852553401534104,
+           -0.019722549455920176,
+           -0.022777753300210382,
+           -0.02598523236814305,
+           -0.029305439589398838,
+           -0.03269316113214549,
+           -0.0360986327260748,
+           -0.039468796638160504,
+           -0.042748667578191006,
+           -0.04588277280947813,
+           -0.0488166296098166,
+           -0.051498222024846003,
+           -0.0538794386133527,
+           -0.05591743361064421,
+           -0.057575875616557505,
+           -0.05882605050964574,
+           -0.059647788736371034,
+           -0.06003019134002221,
+           -0.05997213397549235,
+           -0.059482533583065655,
+           -0.058580368233168506,
+           -0.057294446760255746,
+           -0.0556629310262615,
+           -0.053732619837740435,
+           -0.05155800953195513,
+           -0.0492001518961643,
+           -0.046725335249822,
+           -0.04420361907157298,
+           -0.04170725637701672,
+           -0.039309041052177376,
+           -0.03708061944465443,
+           -0.035090806654885745,
+           -0.03340394812271132,
+           -0.03207836626271103,
+           -0.03116493008336851,
+           -0.030705782971896495,
+           -0.030733260203574964,
+           -0.03126902332830573,
+           -0.03232343350379314,
+           -0.03389518020721117,
+           -0.03597117570211215,
+           -0.03852671931185754,
+           -0.04152592910904244,
+           -0.044922432229339525,
+           -0.0486602988141955,
+           -0.05267519873151231,
+           -0.05689575486006356,
+           -0.06124506198325093,
+           -0.06564233633702725,
+           -0.07000465769350939,
+           -0.07424876361361703,
+           -0.07829285422427631,
+           -0.08205836559984507,
+           -0.08547167056045286,
+           -0.08846566742422321,
+           -0.09098121992387558,
+           -0.09296841505583606,
+           -0.09438760998486839,
+           -0.095210244173092,
+           -0.0954193985158971,
+           -0.09501008931169554,
+           -0.09398929122019757,
+           -0.09237568982068772,
+           -0.09019917081027284,
+           -0.08750005912582584,
+           -0.08432812718057457,
+           -0.0807413968336501,
+           -0.07680476452701868,
+           -0.0725884831128687,
+           -0.06816653715751626,
+           -0.06361495086747396,
+           -0.05901006918405682,
+           -0.05442685300299519,
+           -0.04993722888764088,
+           -0.04560853207568503,
+           -0.04150207907120329,
+           -0.037671902730665036,
+           -0.03416367857914711,
+           -0.03101386623647119,
+           -0.028249084414122473,
+           -0.025885732098018602,
+           -0.023929862405113717,
+           -0.022377309345758923,
+           -0.021214061493805655,
+           -0.02041687051678627,
+           -0.019954076798436637,
+           -0.01978662913613423,
+           -0.01986927084530292,
+           -0.020151860665087503,
+           -0.020580793730252466,
+           -0.021100485628604688,
+           -0.021654881254388428,
+           -0.022188949825710458,
+           -0.022650128063594132,
+           -0.02298967511294932,
+           -0.023163905279006372,
+           -0.023135267991358566,
+           -0.022873248505423115,
+           -0.022355067602751983,
+           -0.021566163835907922,
+           -0.020500447546103376,
+           -0.019160321818273172,
+           -0.017556471578319237,
+           -0.015707428028169948,
+           -0.013638921404692578,
+           -0.011383040492268121,
+           -0.00897722227874608,
+           -0.006463099495593101,
+           -0.0038852374158319775,
+           -0.0012897941064777016,
+           0.0012768597252912285,
+           0.00376952413972705,
+           0.006145519414660111,
+           0.00836596522402731,
+           0.010396955060540815,
+           0.012210594134700464,
+           0.01378587251658567,
+           0.015109349549535226,
+           0.016175630448201188,
+           0.016987621374105335,
+           0.017556555023705386,
+           0.01790178472185072,
+           0.018050351036569365,
+           0.01803633086679956,
+           0.017899984652386174,
+           0.01768672267067677,
+           0.01744591618103908,
+           0.017229583335124452,
+           0.017090983180138346,
+           0.017083153656787774,
+           0.017257431165803028,
+           0.017661990002336418,
+           0.01834043971516054,
+           0.019330517240658797,
+           0.02066290851753602,
+           0.02236023125789546,
+           0.02443620670703164,
+           0.026895043661647394,
+           0.029731052846076474,
+           0.032928504095730234,
+           0.03646173280592946,
+           0.04029549592084624,
+           0.04438557151495256,
+           0.0486795899129099,
+           0.05311807845552894,
+           0.0576356965951867,
+           0.06216263312995114,
+           0.066626133184241,
+           0.07095211912143948,
+           0.07506686701764176,
+           0.07889869870161151,
+           0.08237964871705616,
+           0.08544706590852562,
+           0.08804511066608328,
+           0.09012611115645117,
+           0.09165174506598303,
+           0.09259401740750584,
+           0.09293600970218861,
+           0.09267238122434868,
+           0.09180960886128538,
+           0.09036595834946123,
+           0.0883711860515587,
+           0.08586597688007494,
+           0.08290113029499534,
+           0.07953651235128557,
+           0.07583979739854138,
+           0.07188502810247643,
+           0.06775102684186074,
+           0.06351969512764072,
+           0.05927424040508006,
+           0.055097371368243976,
+           0.05106950369543217,
+           0.04726701788494586,
+           0.04376060963821347,
+           0.040613771031685904,
+           0.03788143759383022,
+           0.03560883243518649,
+           0.03383053386471346,
+           0.03256978757958668,
+           0.03183807866874637,
+           0.03163497246548645,
+           0.03194822687256929,
+           0.032754172321038715,
+           0.034018349168451936,
+           0.03569638624826202,
+           0.03773509859756644,
+           0.04007377725317964,
+           0.04264563954017655,
+           0.04537940459021552,
+           0.04820095600732485,
+           0.051035051713234296,
+           0.0538070400964902,
+           0.05644454167913529,
+           0.05887905659670624,
+           0.061047460232357895,
+           0.06289335230101999,
+           0.0643682284692933,
+           0.06543244812552336,
+           0.06605597706835749,
+           0.06621888953208241,
+           0.06591161997221262,
+           0.0651349612456967,
+           0.06389981208255038,
+           0.062226682904594134,
+           0.06014497495006971,
+           0.05769205316473871,
+           0.05491213828541256,
+           0.05185504784915603,
+           0.04857481940570189,
+           0.04512825190620051,
+           0.04157340302389034,
+           0.037968080990120286,
+           0.034368369384757035,
+           0.030827222210059624,
+           0.0273931645323681,
+           0.024109131050529538,
+           0.021011471219844337,
+           0.018129145121468026,
+           0.015483129233203927,
+           0.013086045756747447,
+           0.010942023328478552,
+           0.009046790933597813,
+           0.007388000808831542,
+           0.0059457702096082175,
+           0.004693426282738468,
+           0.003598433067336183,
+           0.0026234749764968827,
+           0.0017276671077024169,
+           0.0008678594917907961,
+           8.259359802394451e-18
+          ],
+          [
+           0,
+           -0.001331118755239276,
+           -0.002818851917589323,
+           -0.004514131223117757,
+           -0.006460877438924418,
+           -0.00869456276430934,
+           -0.011241006111185002,
+           -0.014115434339348119,
+           -0.01732183562965783,
+           -0.020852623604023523,
+           -0.024688622736988648,
+           -0.02879937725368189,
+           -0.03314377728443466,
+           -0.03767098776094239,
+           -0.04232165760270768,
+           -0.04702937935732224,
+           -0.05172236281199549,
+           -0.0563252803563607,
+           -0.06076123719512657,
+           -0.06495381600443946,
+           -0.0688291433893624,
+           -0.07231792459147991,
+           -0.07535739334190654,
+           -0.0778931255486112,
+           -0.0798806686068842,
+           -0.08128694245411021,
+           -0.08209137394989935,
+           -0.08228673261680136,
+           -0.08187964306686892,
+           -0.08089075738561638,
+           -0.0793545791510358,
+           -0.07731893942296157,
+           -0.07484413373216932,
+           -0.07200173761269185,
+           -0.06887312634246114,
+           -0.06554773208333235,
+           -0.06212107835294043,
+           -0.058692637547838246,
+           -0.05536356192343693,
+           -0.05223434190180454,
+           -0.049402447733767854,
+           -0.04696001132959221,
+           -0.04499160446908462,
+           -0.043572167617900844,
+           -0.04276514025687267,
+           -0.04262083905310415,
+           -0.04317512447437068,
+           -0.044448389709489305,
+           -0.04644489816943872,
+           -0.049152487590920696,
+           -0.0525426500462324,
+           -0.0565709881929671,
+           -0.06117803909288586,
+           -0.06629044811113807,
+           -0.07182246699038353,
+           -0.07767774238522238,
+           -0.08375135413189298,
+           -0.0899320564882985,
+           -0.09610467065824359,
+           -0.10215257323218038,
+           -0.10796022282535497,
+           -0.11341566623105621,
+           -0.11841296585576991,
+           -0.1228544920539254,
+           -0.1266530271877883,
+           -0.12973363272483118,
+           -0.1320352363413132,
+           -0.1335119026888341,
+           -0.13413375903718106,
+           -0.1338875552474967,
+           -0.13277684625368413,
+           -0.13082179422433843,
+           -0.128058596623199,
+           -0.12453855526294422,
+           -0.12032680993923325,
+           -0.11550076813303396,
+           -0.11014826938800454,
+           -0.10436552913396908,
+           -0.09825491178897632,
+           -0.09192258680994551,
+           -0.08547612388463811,
+           -0.07902208460723877,
+           -0.07266366773162268,
+           -0.0664984634603056,
+           -0.06061636924709272,
+           -0.05509771534458684,
+           -0.05001164292200296,
+           -0.04541477115060596,
+           -0.04135018236484358,
+           -0.03784674643914429,
+           -0.034918797072016346,
+           -0.03256616395053713,
+           -0.030774555995858228,
+           -0.02951628228103841,
+           -0.028751288978950688,
+           -0.028428483042937096,
+           -0.028487306434261065,
+           -0.02885951875671653,
+           -0.029471141284863403,
+           -0.03024451169595826,
+           -0.031100396424364955,
+           -0.03196010650647312,
+           -0.03274756309582383,
+           -0.033391260490082265,
+           -0.03382607747790045,
+           -0.033994892006245295,
+           -0.03384995947862918,
+           -0.033354021285311675,
+           -0.03248111727708227,
+           -0.031217083643588987,
+           -0.029559725848511548,
+           -0.02751866469962298,
+           -0.0251148620787606,
+           -0.022379841111559235,
+           -0.01935462341118732,
+           -0.016088413286292968,
+           -0.012637065278205383,
+           -0.00906137692324242,
+           -0.00542525308376659,
+           -0.0017937914447664625,
+           0.001768659250264397,
+           0.005200415998820792,
+           0.008444301838711267,
+           0.011449360124901227,
+           0.01417239654698592,
+           0.016579307124727462,
+           0.018646155969031592,
+           0.020359973080893514,
+           0.021719249717184943,
+           0.02273411669613389,
+           0.023426199248515977,
+           0.023828150434513615,
+           0.02398287352776038,
+           0.023942451904750993,
+           0.023766812662936357,
+           0.023522157228976978,
+           0.023279198430297503,
+           0.02311124872935317,
+           0.023092208426448955,
+           0.023294505517051336,
+           0.023787040467408097,
+           0.024633189404584636,
+           0.025888918094058546,
+           0.027601056624042126,
+           0.02980578098837699,
+           0.032527342848801474,
+           0.03577708278207085,
+           0.03955275542409803,
+           0.04383818728154049,
+           0.048603279779666934,
+           0.05380436155691518,
+           0.059384885313613876,
+           0.06527645589134946,
+           0.07140016791551429,
+           0.07766822348520722,
+           0.08398579323847948,
+           0.09025307783690228,
+           0.09636752166020165,
+           0.10222612641281077,
+           0.10772780952451902,
+           0.11277575075073533,
+           0.11727967028488982,
+           0.12115798299275697,
+           0.124339776038232,
+           0.1267665611308619,
+           0.12839375779359194,
+           0.1291918703011081,
+           0.1291473281243243,
+           0.12826296766122072,
+           0.1265581415456456,
+           0.12406845069687253,
+           0.12084510328754884,
+           0.11695391374621612,
+           0.11247396355447838,
+           0.1074959537367689,
+           0.10212028637328709,
+           0.09645491901200076,
+           0.0906130413530668,
+           0.0847106278937412,
+           0.07886392324770009,
+           0.07318691851520612,
+           0.06778887733848384,
+           0.0627719691232404,
+           0.05822906437023502,
+           0.05424174320173581,
+           0.050878563080647206,
+           0.04819362552899604,
+           0.04622547450840501,
+           0.04499635120238971,
+           0.04451182143208542,
+           0.04476078305080786,
+           0.04571585161526278,
+           0.04733411364261429,
+           0.04955822805170634,
+           0.05231784816519222,
+           0.05553132911661507,
+           0.05910767884489754,
+           0.0629487052289612,
+           0.06695130745244511,
+           0.07100985649903295,
+           0.07501860783758925,
+           0.07887408890475162,
+           0.08247740493819308,
+           0.08573640902942423,
+           0.08856768589008962,
+           0.09089830366737832,
+           0.0926672940798207,
+           0.09382682802503932,
+           0.09434306146364842,
+           0.09419663461740216,
+           0.09338281612993748,
+           0.09191129261120372,
+           0.08980561270457055,
+           0.08710230326315505,
+           0.08384968319078945,
+           0.08010640779730797,
+           0.07593978295869284,
+           0.0714238938029213,
+           0.0666375969304145,
+           0.06166242822084376,
+           0.05658048000394007,
+           0.05147230174213495,
+           0.04641487738243112,
+           0.04147973021295975,
+           0.036731202468474104,
+           0.032224952162452185,
+           0.028006703804569308,
+           0.024111282940259885,
+           0.02056195699542632,
+           0.017370096913624757,
+           0.014535165738115738,
+           0.012045031828029105,
+           0.009876596020525883,
+           0.007996713970726158,
+           0.006363387322099273,
+           0.004927190472919882,
+           0.0036328936826194717,
+           0.002421238256833929,
+           0.0012308156873652805,
+           1.1843493770707045e-17
+          ],
+          [
+           0,
+           -0.0017795082776352583,
+           -0.0037919830178885163,
+           -0.006098430351491503,
+           -0.008749822667969984,
+           -0.011785412535744987,
+           -0.015231370865667122,
+           -0.01909978687479277,
+           -0.023388058016744134,
+           -0.028078687918686857,
+           -0.03313949975914084,
+           -0.038524261704095335,
+           -0.0441737102653433,
+           -0.05001694702735373,
+           -0.055973174371964945,
+           -0.061953726863489274,
+           -0.06786434706917994,
+           -0.07360764798330309,
+           -0.07908569906725794,
+           -0.08420266934708216,
+           -0.08886745911747282,
+           -0.09299625164038247,
+           -0.09651491780520972,
+           -0.09936121000189221,
+           -0.10148668637032036,
+           -0.10285831301101336,
+           -0.10345969951649496,
+           -0.1032919321196906,
+           -0.1023739786348819,
+           -0.1007426499442328,
+           -0.09845211379661654,
+           -0.09557296786190822,
+           -0.09219089004489857,
+           -0.08840489473257522,
+           -0.08432523365987639,
+           -0.08007098918105421,
+           -0.07576741569741909,
+           -0.07154309161611519,
+           -0.06752694933015574,
+           -0.06384525418562159,
+           -0.060618605146491804,
+           -0.057959029832394086,
+           -0.05596724478495662,
+           -0.054730148253791085,
+           -0.05431860756599576,
+           -0.054785596377187204,
+           -0.05616472895936471,
+           -0.058469229357547864,
+           -0.06169136296866743,
+           -0.06580234711210786,
+           -0.07075274573881152,
+           -0.07647334184336782,
+           -0.08287646968375832,
+           -0.08985777785650721,
+           -0.09729838389144245,
+           -0.10506737157445498,
+           -0.1130245739103704,
+           -0.12102357770496514,
+           -0.12891488034562892,
+           -0.13654912562712057,
+           -0.14378034349445634,
+           -0.15046911840835248,
+           -0.15648561268471037,
+           -0.16171237457889284,
+           -0.16604686599510998,
+           -0.16940365137679392,
+           -0.17171619741285193,
+           -0.17293824248016204,
+           -0.17304470500827868,
+           -0.17203211094772902,
+           -0.16991853198050585,
+           -0.16674303775124302,
+           -0.16256467693669382,
+           -0.15746101312882194,
+           -0.15152625201199937,
+           -0.14486900591268081,
+           -0.13760975025827016,
+           -0.12987803359669256,
+           -0.12180950842869602,
+           -0.11354285405777823,
+           -0.10521666487520312,
+           -0.09696637792006457,
+           -0.08892131218108065,
+           -0.08120188897626476,
+           -0.07391709794045025,
+           -0.06716226679162506,
+           -0.061017185295886935,
+           -0.05554462490235104,
+           -0.050789285597377366,
+           -0.046777190879470576,
+           -0.043515540646981155,
+           -0.04099302049590221,
+           -0.03918055472426539,
+           -0.03803247950949878,
+           -0.037488102532483594,
+           -0.037473606017336986,
+           -0.03790424196697422,
+           -0.03868676150085451,
+           -0.03972201480943659,
+           -0.040907654458985636,
+           -0.04214087269932716,
+           -0.04332110309223144,
+           -0.044352618192031436,
+           -0.0451469581318653,
+           -0.04562512971511805,
+           -0.045719521858298,
+           -0.045375490817568774,
+           -0.044552577362106056,
+           -0.04322532771068469,
+           -0.04138370037807123,
+           -0.039033051822946585,
+           -0.036193704677318535,
+           -0.03290011309357571,
+           -0.029199650098102447,
+           -0.02515105152878791,
+           -0.020822559913916926,
+           -0.016289819301026857,
+           -0.011633578374144488,
+           -0.006937264047617264,
+           -0.0022844909731002563,
+           0.002243426037855558,
+           0.006569889828340291,
+           0.010625303971949877,
+           0.014349159673939318,
+           0.017691870179640013,
+           0.02061630293857792,
+           0.02309896762130893,
+           0.02513082701801017,
+           0.026717707637283827,
+           0.027880297222658654,
+           0.028653727149645994,
+           0.029086748485711075,
+           0.029240521114847737,
+           0.029187045478083314,
+           0.029007275903156767,
+           0.028788962950844627,
+           0.02862427947594249,
+           0.028607291001265,
+           0.02883133538081445,
+           0.029386379469142465,
+           0.030356421544432854,
+           0.031817007522291364,
+           0.03383292655858617,
+           0.03645614752920811,
+           0.03972405219057283,
+           0.04365801370491627,
+           0.0482623608329923,
+           0.05352375865961572,
+           0.059411026457408075,
+           0.06587540246490357,
+           0.07285125422550148,
+           0.0802572219802656,
+           0.08799777170824939,
+           0.09596512403504885,
+           0.10404151564349545,
+           0.11210174126056002,
+           0.12001591697761442,
+           0.1276523997726436,
+           0.13488079379344048,
+           0.14157497134194466,
+           0.14761603564189923,
+           0.15289515340160734,
+           0.15731618788340282,
+           0.1607980676003505,
+           0.16327683177517535,
+           0.1647073011732514,
+           0.1650643316810413,
+           0.16434361783216306,
+           0.16256202414702733,
+           0.1597574333895839,
+           0.15598811238248234,
+           0.15133160757847242,
+           0.14588319387882634,
+           0.13975391094280648,
+           0.13306823118247396,
+           0.12596141254055776,
+           0.11857659678733846,
+           0.11106172025788184,
+           0.10356630853146219,
+           0.09623822941764788,
+           0.08922047968750431,
+           0.08264808024651302,
+           0.07664515190551,
+           0.07132223962859292,
+           0.06677394722639876,
+           0.06307693706336943,
+           0.060288340638837985,
+           0.05844461609636373,
+           0.05756087805273932,
+           0.05763071387747178,
+           0.058626488969719656,
+           0.060500131954791175,
+           0.06318437933930586,
+           0.06659444829971783,
+           0.0706300961968409,
+           0.0751780163535675,
+           0.08011451182291765,
+           0.08530838249686093,
+           0.09062395611552294,
+           0.09592419064477187,
+           0.10107377416921742,
+           0.10594214892515641,
+           0.1104063883574991,
+           0.11435386006593823,
+           0.11768461310607718,
+           0.12031343518868208,
+           0.12217153369636578,
+           0.12320780390187168,
+           0.12338965808932843,
+           0.12270340019243733,
+           0.12115414180049636,
+           0.11876526666594113,
+           0.11557746189671722,
+           0.11164734456069773,
+           0.10704572220809407,
+           0.10185553459152076,
+           0.09616953141770875,
+           0.09008774711622196,
+           0.08371483821063429,
+           0.07715735181711454,
+           0.07052099500644171,
+           0.06390797422360163,
+           0.05741447168347078,
+           0.05112832171411511,
+           0.04512694450492547,
+           0.03947558777819752,
+           0.034225918718124616,
+           0.029414999269713134,
+           0.025064667896594246,
+           0.02118134031553789,
+           0.017756230874455863,
+           0.014765985384159902,
+           0.012173705626256349,
+           0.009930335707277428,
+           0.007976371165696713,
+           0.006243843496931404,
+           0.004658525748938175,
+           0.003142299233609369,
+           0.0016156173374009919,
+           1.570303227356682e-17
+          ],
+          [
+           0,
+           -0.0022717152884260297,
+           -0.004864328837486415,
+           -0.007846276850564568,
+           -0.011272590953689514,
+           -0.015183053212144663,
+           -0.019600774398524545,
+           -0.024531234954048443,
+           -0.029961816059715842,
+           -0.03586183548855801,
+           -0.04218308976762697,
+           -0.04886089097151762,
+           -0.05581557353307899,
+           -0.06295443411996181,
+           -0.07017405620145947,
+           -0.07736296070979283,
+           -0.08440451544472,
+           -0.09118002880477641,
+           -0.09757194823508232,
+           -0.10346708059625155,
+           -0.10875975056704927,
+           -0.11335481422823648,
+           -0.11717044811636775,
+           -0.12014063921120097,
+           -0.12221730840475001,
+           -0.12337200882173578,
+           -0.12359715070429489,
+           -0.12290671618382897,
+           -0.1213364398531453,
+           -0.1189434443107672,
+           -0.11580533344733276,
+           -0.11201875984297902,
+           -0.10769749590538519,
+           -0.10297005096920485,
+           -0.09797688818334147,
+           -0.092867305341078,
+           -0.08779605259867063,
+           -0.08291976705744364,
+           -0.0783933092726716,
+           -0.07436608976723996,
+           -0.07097847448801511,
+           -0.06835835681987393,
+           -0.06661798029226061,
+           -0.06585109055510456,
+           -0.06613048769557835,
+           -0.06750604069343803,
+           -0.07000321499345286,
+           -0.07362215207008954,
+           -0.07833732676562707,
+           -0.08409779441659751,
+           -0.0908280256802669,
+           -0.09842931287697482,
+           -0.10678171792004106,
+           -0.11574651884893829,
+           -0.12516909993335235,
+           -0.13488221957109353,
+           -0.14470958102535378,
+           -0.15446962366217276,
+           -0.16397944693901728,
+           -0.17305877609369857,
+           -0.18153387737147506,
+           -0.18924133173554092,
+           -0.19603157930628076,
+           -0.20177215218808087,
+           -0.2063505207378117,
+           -0.20967648752643048,
+           -0.21168407402061207,
+           -0.21233285710230615,
+           -0.21160872565603042,
+           -0.20952404126701116,
+           -0.2061172012514605,
+           -0.20145161643811577,
+           -0.19561412999221048,
+           -0.18871291678213406,
+           -0.18087491501459882,
+           -0.17224285280999493,
+           -0.16297194179140584,
+           -0.15322631739222997,
+           -0.14317531126607247,
+           -0.13298964477424488,
+           -0.12283763394803839,
+           -0.11288149554554314,
+           -0.103273840870892,
+           -0.09415443897560269,
+           -0.08564732384674106,
+           -0.07785831138274722,
+           -0.07087298158638927,
+           -0.06475516972517308,
+           -0.05954599751398659,
+           -0.0552634619786638,
+           -0.05190258589500705,
+           -0.04943611990639706,
+           -0.04781577294523906,
+           -0.04697393475130529,
+           -0.04682584240902641,
+           -0.04727213220683889,
+           -0.04820170901399578,
+           -0.04949485799483828,
+           -0.05102651801491629,
+           -0.05266963266713561,
+           -0.05429849353787253,
+           -0.05579199116835265,
+           -0.05703669211771267,
+           -0.05792966552046268,
+           -0.058380989421371335,
+           -0.05831587578658604,
+           -0.05767636320981724,
+           -0.05642253769817518,
+           -0.0545332542445443,
+           -0.052006344859600095,
+           -0.048858312018425235,
+           -0.045123519738551235,
+           -0.04085290741345913,
+           -0.0361122637528717,
+           -0.030980109420772894,
+           -0.025545246931418786,
+           -0.019904044812333533,
+           -0.01415752975954884,
+           -0.008408365326099091,
+           -0.0027577984799032227,
+           0.0026973439275058855,
+           0.00786752814088548,
+           0.01267317875996293,
+           0.017047064558690782,
+           0.020936340440931057,
+           0.024304190059834974,
+           0.027131024010124516,
+           0.029415200052017126,
+           0.031173244250218366,
+           0.03243956489656896,
+           0.03326566430162226,
+           0.0337188666535917,
+           0.033880592820011816,
+           0.03384422488605797,
+           0.03371261408040225,
+           0.033595295257808376,
+           0.033605479043672,
+           0.03385689889520174,
+           0.03446059453724129,
+           0.035521715376858956,
+           0.03713642753022925,
+           0.039389006001452134,
+           0.04234918938250495,
+           0.04606986829532395,
+           0.0505851708196274,
+           0.055908998538174305,
+           0.0620340558206512,
+           0.0689314028296849,
+           0.07655054976778745,
+           0.08482009641376621,
+           0.09364890735613944,
+           0.10292779985913093,
+           0.11253170833033219,
+           0.12232227722260912,
+           0.1321508232010594,
+           0.14186159781588004,
+           0.15129527398674475,
+           0.16029257352586498,
+           0.16869794886208808,
+           0.17636323018423364,
+           0.18315114945330685,
+           0.18893865514139244,
+           0.19361993608732272,
+           0.19710907941040653,
+           0.1993422958383263,
+           0.20027965588227345,
+           0.19990629178857283,
+           0.19823303283318963,
+           0.1952964549967544,
+           0.19115834003521073,
+           0.18590455310402318,
+           0.17964336205670828,
+           0.17250323497976838,
+           0.16463016511684622,
+           0.1561845837664816,
+           0.14733793172968987,
+           0.1382689681903059,
+           0.12915990232817848,
+           0.12019243733475465,
+           0.111543818714091,
+           0.10338297875459396,
+           0.09586686684645007,
+           0.08913705094973232,
+           0.08331666909434574,
+           0.07850780147133218,
+           0.07478932365820007,
+           0.0722152900527821,
+           0.07081388395018998,
+           0.07058695719369135,
+           0.07151016829185851,
+           0.07353371366302802,
+           0.07658363259037447,
+           0.08056365288909899,
+           0.0853575315312498,
+           0.09083183285284549,
+           0.09683907676340603,
+           0.10322118083575954,
+           0.10981311347907702,
+           0.11644667074932442,
+           0.12295428683758218,
+           0.12917278795423787,
+           0.13494700119822228,
+           0.14013313401361877,
+           0.14460184588689873,
+           0.14824094187259554,
+           0.1509576271531209,
+           0.15268027289833996,
+           0.1533596559160514,
+           0.1529696476711064,
+           0.15150734187334217,
+           0.14899262365513902,
+           0.1454671970363548,
+           0.14099310057014258,
+           0.1356507534528763,
+           0.12953658566097045,
+           0.12276031557089703,
+           0.11544194678533161,
+           0.10770856232819012,
+           0.09969099883033448,
+           0.09152048570154044,
+           0.08332533452064382,
+           0.0752277619757814,
+           0.06734092570465812,
+           0.059766246427064906,
+           0.05259108198373899,
+           0.045886809497671995,
+           0.039707361096709505,
+           0.034088246754495025,
+           0.02904608512233683,
+           0.02457865005886791,
+           0.02066542725044639,
+           0.01726866218927888,
+           0.01433486816927096,
+           0.011796751189099421,
+           0.0095754980140865,
+           0.007583364410422866,
+           0.0057264929589410825,
+           0.003907884071547187,
+           0.00203044001610897,
+           1.9909610495908637e-17
+          ],
+          [
+           0,
+           -0.002814131211462,
+           -0.006046959441789297,
+           -0.009771412689605427,
+           -0.014043364376366036,
+           -0.0188997263487706,
+           -0.0243570696624536,
+           -0.030410811732227917,
+           -0.037034993696330454,
+           -0.04418265647222115,
+           -0.05178680836903932,
+           -0.05976196166272376,
+           -0.06800620062641556,
+           -0.07640372952005592,
+           -0.08482783633515979,
+           -0.09314419698784641,
+           -0.10121443543963765,
+           -0.1088998481384546,
+           -0.11606519639570854,
+           -0.12258246797568662,
+           -0.1283345093358707,
+           -0.13321843262401825,
+           -0.1371487066495535,
+           -0.14005984848146208,
+           -0.14190864190238733,
+           -0.14267582043493884,
+           -0.14236716576901182,
+           -0.14101398683460864,
+           -0.13867296012640282,
+           -0.13542532781284036,
+           -0.13137546625775104,
+           -0.12664885344493307,
+           -0.12138947902958805,
+           -0.11575675496315382,
+           -0.10992199749262593,
+           -0.10406456249768002,
+           -0.09836772531590919,
+           -0.09301440318372432,
+           -0.08818282300774172,
+           -0.08404223925730926,
+           -0.08074880627378136,
+           -0.07844170623019517,
+           -0.07723962841363476,
+           -0.07723768757117422,
+           -0.07850485894704001,
+           -0.08108199558590981,
+           -0.08498047977574083,
+           -0.0901815454850328,
+           -0.09663629267883826,
+           -0.1042663978640395,
+           -0.112965508520802,
+           -0.12260129263161314,
+           -0.13301809872432754,
+           -0.1440401670881374,
+           -0.15547531946333054,
+           -0.16711904287515783,
+           -0.1787588736650761,
+           -0.19017898040600056,
+           -0.20116483945390037,
+           -0.21150789450857183,
+           -0.22101009179166814,
+           -0.22948818529598486,
+           -0.23677771194859978,
+           -0.24273654433146744,
+           -0.24724793862714875,
+           -0.2502230074607007,
+           -0.2516025609992252,
+           -0.25135827471468924,
+           -0.24949315824695978,
+           -0.24604131643205465,
+           -0.2410670103805421,
+           -0.2346630430935126,
+           -0.2269485100849577,
+           -0.2180659704515963,
+           -0.20817810743123893,
+           -0.19746395938966327,
+           -0.18611481208685868,
+           -0.1743298507585992,
+           -0.16231167582582345,
+           -0.15026178878879562,
+           -0.13837615501442196,
+           -0.1268409476861484,
+           -0.11582857222293912,
+           -0.10549406311531954,
+           -0.09597193555937067,
+           -0.08737356273500656,
+           -0.07978513636185156,
+           -0.0732662536044686,
+           -0.0678491578509417,
+           -0.06353864474088655,
+           -0.060312628470836384,
+           -0.05812334726061547,
+           -0.056899171321898964,
+           -0.05654696211190256,
+           -0.05695491843810453,
+           -0.057995833427016176,
+           -0.05953067676222159,
+           -0.06141240916618262,
+           -0.06348993102401969,
+           -0.065612064444027,
+           -0.0676314679756804,
+           -0.06940838565479769,
+           -0.07081413694794704,
+           -0.0717342613936927,
+           -0.07207124109868575,
+           -0.07174673550080865,
+           -0.07070327567161079,
+           -0.06890537956852315,
+           -0.06634006470481096,
+           -0.063016750300552,
+           -0.05896655671685364,
+           -0.05424102546088176,
+           -0.048910297890783806,
+           -0.0430608045737497,
+           -0.03679252970975449,
+           -0.030215925815192845,
+           -0.023448562694407645,
+           -0.01661160139201064,
+           -0.009826188148685156,
+           -0.003209865270500376,
+           0.0031269047791164196,
+           0.009084008827777169,
+           0.01457465821025317,
+           0.01952798969671582,
+           0.023891221851119762,
+           0.02763130811996954,
+           0.030736041048935212,
+           0.033214576305170794,
+           0.035097360284972866,
+           0.036435460626915626,
+           0.03729931453588614,
+           0.03777692505813948,
+           0.037971549944709415,
+           0.03799894113158251,
+           0.037984204808683225,
+           0.0380583622407333,
+           0.038354699679840086,
+           0.039005001661000696,
+           0.040135765541880565,
+           0.04186449624115165,
+           0.044296178711280075,
+           0.04752002178081526,
+           0.05160656070914553,
+           0.056605197264647925,
+           0.0625422455728641,
+           0.06941953964378171,
+           0.0772136446803816,
+           0.0858756993355802,
+           0.09533190039178775,
+           0.10548462527639146,
+           0.11621417179761787,
+           0.12738107888844885,
+           0.13882897737189384,
+           0.15038790617954273,
+           0.16187801740890156,
+           0.1731135833979406,
+           0.18390721088720516,
+           0.19407416153867482,
+           0.2034366747377281,
+           0.21182818781073393,
+           0.21909735057385613,
+           0.22511173545273214,
+           0.22976115117907578,
+           0.23296047711968393,
+           0.23465194640983872,
+           0.23480681897938868,
+           0.2334263999636058,
+           0.23054237453285853,
+           0.22621644647714936,
+           0.22053928454629068,
+           0.21362879716698735,
+           0.20562777232799395,
+           0.19670093474785263,
+           0.1870314865408912,
+           0.17681721013011464,
+           0.16626622281230113,
+           0.15559248089886615,
+           0.14501113752568043,
+           0.13473386189349318,
+           0.12496422877629146,
+           0.11589328558992701,
+           0.10769540018369335,
+           0.1005244859027419,
+           0.09451069152958942,
+           0.08975763266565218,
+           0.08634022822765398,
+           0.08430319132257216,
+           0.08366020817962988,
+           0.08439382243827427,
+           0.0864560253160482,
+           0.08976953541808032,
+           0.09422973560833058,
+           0.0997072188388351,
+           0.10605088050369324,
+           0.11309148209648065,
+           0.12064560001202701,
+           0.1285198645091611,
+           0.13651538735106808,
+           0.14443227261788533,
+           0.15207410373461974,
+           0.1592523009056593,
+           0.16579024686038907,
+           0.17152708499502234,
+           0.1763211024855017,
+           0.1800526215305222,
+           0.18262633429643574,
+           0.18397303106661678,
+           0.18405068619958606,
+           0.18284488239744526,
+           0.1803685700847409,
+           0.17666117499453915,
+           0.1717870829509211,
+           0.1658335459339216,
+           0.1589080674433367,
+           0.15113533760075898,
+           0.14265379904179518,
+           0.13361193319544132,
+           0.12416436281970915,
+           0.11446787051349719,
+           0.10467743426662768,
+           0.0949423799177775,
+           0.08540274670186955,
+           0.07618595598454596,
+           0.06740386496148243,
+           0.05915027675979012,
+           0.05149896628303376,
+           0.044502267599160844,
+           0.038190254026318815,
+           0.032570526696467705,
+           0.027628611659890775,
+           0.023328949932150612,
+           0.019616449673657752,
+           0.016418555313937922,
+           0.013647775249507882,
+           0.011204598087193741,
+           0.008980717566169416,
+           0.006862478518343778,
+           0.0047344507122158595,
+           0.002483034307151607,
+           2.452969694319076e-17
+          ],
+          [
+           0,
+           -0.003412374198040712,
+           -0.00734920578440078,
+           -0.011884728176546585,
+           -0.017072265692244012,
+           -0.02294236719283786,
+           -0.029501575313043624,
+           -0.03673186616373281,
+           -0.04459077692711606,
+           -0.053012220825999906,
+           -0.06190797099527141,
+           -0.07116977727001492,
+           -0.08067206327554188,
+           -0.09027513588310479,
+           -0.09982882547167829,
+           -0.1091764638591377,
+           -0.11815909753262568,
+           -0.12661982715651005,
+           -0.13440816044118514,
+           -0.14138426442215526,
+           -0.14742300505978442,
+           -0.15241766678661772,
+           -0.15628325209039914,
+           -0.15895927124692377,
+           -0.1604119446631567,
+           -0.16063575465452878,
+           -0.15965429950677298,
+           -0.15752041996556368,
+           -0.15431558642752113,
+           -0.15014855362295262,
+           -0.145153308022481,
+           -0.13948635110573618,
+           -0.13332337855214993,
+           -0.12685543092665474,
+           -0.12028460514588028,
+           -0.11381942757625639,
+           -0.10766999873979706,
+           -0.10204302605167498,
+           -0.09713686461735124,
+           -0.0931366867773291,
+           -0.09020989877872256,
+           -0.08850191772221536,
+           -0.08813241390052437,
+           -0.08919211299949954,
+           -0.09174023962973184,
+           -0.09580266860793006,
+           -0.10137083367733188,
+           -0.10840142535109705,
+           -0.11681689072019141,
+           -0.1265067288472348,
+           -0.13732955623971846,
+           -0.14911589832790406,
+           -0.16167164531951225,
+           -0.17478209469559117,
+           -0.18821648834534727,
+           -0.20173294026316502,
+           -0.21508364114598982,
+           -0.22802021937048222,
+           -0.24029913386693755,
+           -0.25168697344016877,
+           -0.26196553914228493,
+           -0.2709365913304931,
+           -0.2784261509238069,
+           -0.2842882549150783,
+           -0.288408079143135,
+           -0.29070435636910136,
+           -0.2911310344652452,
+           -0.28967813760570416,
+           -0.28637181230597664,
+           -0.2812735595305597,
+           -0.2744786734041487,
+           -0.26611392585161237,
+           -0.2563345542990497,
+           -0.2453206259605421,
+           -0.23327286681584317,
+           -0.22040805580101908,
+           -0.2069540946883707,
+           -0.19314487138590597,
+           -0.17921503876891332,
+           -0.16539483256622592,
+           -0.151905050234137,
+           -0.13895230820793358,
+           -0.12672468754346128,
+           -0.11538786793735047,
+           -0.10508183769756287,
+           -0.09591825273730674,
+           -0.08797850144722248,
+           -0.08131251476694601,
+           -0.07593834236307444,
+           -0.07184249698243063,
+           -0.06898105025305584,
+           -0.06728144491415132,
+           -0.06664497112037773,
+           -0.06694983851089378,
+           -0.06805476154954378,
+           -0.06980296357511924,
+           -0.0720264953417731,
+           -0.0745507568111089,
+           -0.07719910674474594,
+           -0.07979744333462968,
+           -0.08217864072100167,
+           -0.08418673073480874,
+           -0.08568072644100223,
+           -0.08653799386175264,
+           -0.08665709037068632,
+           -0.08596000236018327,
+           -0.08439373053361451,
+           -0.08193118816285457,
+           -0.07857139544791557,
+           -0.07433897127010651,
+           -0.0692829416844343,
+           -0.0634749019960619,
+           -0.057006585769081304,
+           -0.049986909208901587,
+           -0.04253857266335233,
+           -0.03479431216877019,
+           -0.02689290274621949,
+           -0.018975021310600804,
+           -0.011179080438930959,
+           -0.00363714477063038,
+           0.0035289605286691686,
+           0.010211244956133106,
+           0.01631875505228445,
+           0.021780297809419123,
+           0.026546611455237228,
+           0.03059192436611833,
+           0.03391485880224908,
+           0.03653865322134075,
+           0.038510694686460206,
+           0.03990137088629878,
+           0.04080226907640019,
+           0.04132376637582197,
+           0.04159207188011696,
+           0.04174579557039392,
+           0.04193213163897527,
+           0.042302754291154473,
+           0.0430095320509543,
+           0.044200171889629936,
+           0.04601390696887155,
+           0.04857734137677188,
+           0.05200056193650887,
+           0.05637362106060491,
+           0.06176348585339956,
+           0.0682115374438819,
+           0.07573169113491109,
+           0.08430919271279719,
+           0.09390012954975425,
+           0.104431677364924,
+           0.11580308512889212,
+           0.12788738205944689,
+           0.1405337724254227,
+           0.15357066640671768,
+           0.1668092789901244,
+           0.18004771422153393,
+           0.19307543945558267,
+           0.20567804386553437,
+           0.21764216766461503,
+           0.22876048344727476,
+           0.23883660891914882,
+           0.24768983111018134,
+           0.25515952594571933,
+           0.26110916370139564,
+           0.26542980023427587,
+           0.26804296574255676,
+           0.26890287687461006,
+           0.2679979139459069,
+           0.2653513224430992,
+           0.2610211164748712,
+           0.25509918091881717,
+           0.24770958824663067,
+           0.23900616491597626,
+           0.22916936033377977,
+           0.21840248827808234,
+           0.2069274258997269,
+           0.19497986863655023,
+           0.18280425023615962,
+           0.17064844533095297,
+           0.158758377436592,
+           0.14737265771773655,
+           0.13671737931953393,
+           0.12700118851141026,
+           0.1184107474157317,
+           0.1111066938542989,
+           0.10522019206445737,
+           0.10085015400008235,
+           0.09806119498242334,
+           0.09688236998995252,
+           0.09730671830056896,
+           0.09929162497599331,
+           0.10275998827492262,
+           0.1076021629705219,
+           0.11367863119368514,
+           0.120823335271833,
+           0.1288475914995974,
+           0.13754449023827262,
+           0.14669367652176807,
+           0.15606639671705302,
+           0.16543069095199836,
+           0.17455660811940654,
+           0.18322132035707972,
+           0.1912140169805404,
+           0.198340463824661,
+           0.20442712267892824,
+           0.20932473675695867,
+           0.21291130164107003,
+           0.21509435654925751,
+           0.21581254770066474,
+           0.21503643358563893,
+           0.2127685206305324,
+           0.20904253662312414,
+           0.20392196786582414,
+           0.1974979038923709,
+           0.18988625028043396,
+           0.1812243852082943,
+           0.17166734856959737,
+           0.16138366335628432,
+           0.15055089738351438,
+           0.13935107906246202,
+           0.12796608369647486,
+           0.11657310662389864,
+           0.10534033647038418,
+           0.09442293589074122,
+           0.08395942863147406,
+           0.07406858075244531,
+           0.06484685069252168,
+           0.05636646788598953,
+           0.04867418321523207,
+           0.041790717137419726,
+           0.03571091329043527,
+           0.03040458722149579,
+           0.02581804204904054,
+           0.021876205813500672,
+           0.01848532942452596,
+           0.015536169869117537,
+           0.012907571064156657,
+           0.010470344725506169,
+           0.008091346134285053,
+           0.005637634895563516,
+           0.0029806088238126943,
+           2.962357926880646e-17
+          ],
+          [
+           0,
+           -0.004071200156602024,
+           -0.00877850791372453,
+           -0.014194077432343176,
+           -0.020365174072197022,
+           -0.027312455455552945,
+           -0.035028996858900686,
+           -0.04348008922371422,
+           -0.052603817926916215,
+           -0.062312410065221216,
+           -0.07249431790234866,
+           -0.0830169868146904,
+           -0.09373023804035994,
+           -0.10447018024776367,
+           -0.11506354980866308,
+           -0.12533236804905967,
+           -0.13509879495812488,
+           -0.1441900530893303,
+           -0.15244329284116323,
+           -0.15971027102945312,
+           -0.16586171864945717,
+           -0.17079128088165743,
+           -0.17441892254922986,
+           -0.17669370514038585,
+           -0.17759585684888174,
+           -0.17713807448295965,
+           -0.17536601511658798,
+           -0.17235795553530153,
+           -0.16822361836049993,
+           -0.16310218470164212,
+           -0.15715953376177685,
+           -0.1505847694931766,
+           -0.14358611267280824,
+           -0.13638625318193745,
+           -0.12921727141548006,
+           -0.12231524925549105,
+           -0.11591469962470509,
+           -0.11024294906753682,
+           -0.10551460994237019,
+           -0.10192627758644127,
+           -0.09965158325250147,
+           -0.09883672581662771,
+           -0.09959659440127677,
+           -0.1020115804050669,
+           -0.10612516130851546,
+           -0.11194232042236392,
+           -0.11942884690351611,
+           -0.12851153936553297,
+           -0.13907931476794894,
+           -0.15098520250998235,
+           -0.16404918231181276,
+           -0.17806180406335292,
+           -0.19278850885688995,
+           -0.20797455336194648,
+           -0.22335042496784618,
+           -0.23863762307483696,
+           -0.25355467285567274,
+           -0.26782323196088115,
+           -0.28117414814856356,
+           -0.29335332674740733,
+           -0.3041272711897879,
+           -0.31328816747726496,
+           -0.3206583941795201,
+           -0.32609435315963403,
+           -0.329489532333527,
+           -0.33077673001747904,
+           -0.32992939035100327,
+           -0.3269620204177186,
+           -0.3219296815098387,
+           -0.3149265689613856,
+           -0.3060837165766425,
+           -0.29556588237866804,
+           -0.2835676916954581,
+           -0.27030913102087856,
+           -0.25603050121263476,
+           -0.24098695105560963,
+           -0.22544272172703197,
+           -0.20966523902403153,
+           -0.19391919320662612,
+           -0.17846074590443717,
+           -0.1635319997513485,
+           -0.14935585934980491,
+           -0.1361314020067695,
+           -0.12402986368369803,
+           -0.11319133008973487,
+           -0.10372220520854164,
+           -0.09569351022404915,
+           -0.08914004527911247,
+           -0.0840604252722905,
+           -0.08041797949671778,
+           -0.0781424838793479,
+           -0.07713267440677009,
+           -0.07725947152068931,
+           -0.07836982829228559,
+           -0.08029110045398073,
+           -0.0828358242370082,
+           -0.08580677872564312,
+           -0.08900220331352826,
+           -0.0922210379759565,
+           -0.09526805451467862,
+           -0.09795875066667802,
+           -0.10012388589125186,
+           -0.10161354757736751,
+           -0.10230064908768587,
+           -0.10208377615098382,
+           -0.10088931524518824,
+           -0.09867281634303678,
+           -0.09541956224647391,
+           -0.09114433721196573,
+           -0.0858904081500134,
+           -0.07972775184946818,
+           -0.07275058092328876,
+           -0.06507423901341411,
+           -0.056831551780767146,
+           -0.04816873394142863,
+           -0.03924096374823577,
+           -0.030207744580650765,
+           -0.021228178489429185,
+           -0.01245627851884298,
+           -0.004036445351209873,
+           0.003900770678540856,
+           0.011242508750292361,
+           0.017896934968324604,
+           0.023795988222130162,
+           0.02889746016310146,
+           0.03318635233172468,
+           0.03667547231380754,
+           0.03940525064427212,
+           0.04144278051011249,
+           0.042880102614483835,
+           0.043831777336093926,
+           0.04443180504978449,
+           0.0448299726888631,
+           0.04518771988859879,
+           0.04567363096321456,
+           0.04645866920425409,
+           0.0477112772817207,
+           0.049592471689941124,
+           0.05225106009511078,
+           0.05581910807975217,
+           0.060407776191866366,
+           0.06610363952542468,
+           0.07296559049389384,
+           0.08102241129227741,
+           0.09027108612392055,
+           0.10067590500145467,
+           0.11216839126917344,
+           0.1246480644250819,
+           0.13798402885689823,
+           0.15201735827031268,
+           0.16656422540089122,
+           0.18141970756901277,
+           0.19636218123862853,
+           0.21115820341411676,
+           0.22556776484349783,
+           0.2393497899186696,
+           0.25226775113382366,
+           0.26409526216617113,
+           0.2746215131834696,
+           0.28365641488283244,
+           0.2910353239642115,
+           0.2966232320972079,
+           0.30031831273068144,
+           0.3020547350271744,
+           0.3018046714188246,
+           0.29957944436165396,
+           0.2954297783474855,
+           0.2894451446185527,
+           0.28175220779724597,
+           0.2725124052603583,
+           0.26191871102433933,
+           0.25019165565227286,
+           0.23757469175976215,
+           0.2243290106415894,
+           0.2107279289713677,
+           0.19705097511103653,
+           0.1835778120442767,
+           0.1705821381316894,
+           0.15832570767077053,
+           0.1470526106080312,
+           0.13698394475591985,
+           0.1283130046573089,
+           0.1212010990380529,
+           0.11577409388952846,
+           0.11211976099015035,
+           0.11028599252691827,
+           0.11027992188099897,
+           0.1120679690966437,
+           0.11557680758468653,
+           0.12069522675499882,
+           0.12727684405799056,
+           0.13514359985891528,
+           0.14408995015686124,
+           0.15388765583873135,
+           0.16429105332134658,
+           0.17504268041484908,
+           0.18587912330109221,
+           0.19653694584913387,
+           0.20675856119317926,
+           0.21629790760028084,
+           0.22492579609622065,
+           0.2324348059567211,
+           0.23864361578754664,
+           0.2434006722183928,
+           0.2465871148634794,
+           0.24811889474153445,
+           0.247948043338244,
+           0.24606307043927447,
+           0.2424884902431816,
+           0.23728349655275252,
+           0.23053982851592647,
+           0.22237888793511007,
+           0.21294818710716298,
+           0.2024172220571183,
+           0.1909728794999545,
+           0.17881449658075463,
+           0.16614870014782843,
+           0.15318415682461856,
+           0.1401263663631038,
+           0.12717262866477377,
+           0.11450730950834248,
+           0.10229752157047478,
+           0.09068932598814615,
+           0.07980454578175435,
+           0.06973826629362642,
+           0.06055707980929371,
+           0.052298112175615724,
+           0.04496884900079053,
+           0.038547758427708315,
+           0.032985687033476124,
+           0.028207985639062155,
+           0.024117303211007277,
+           0.020596970069233417,
+           0.017514876706591322,
+           0.014727742050179538,
+           0.012085655263254317,
+           0.009436768442028355,
+           0.006632013970770053,
+           0.003529719948798582,
+           3.5244428010065886e-17
+          ],
+          [
+           0,
+           -0.004794424783589081,
+           -0.010340287508320086,
+           -0.016704133207188363,
+           -0.023923596172821453,
+           -0.032005937630701455,
+           -0.04092743501888608,
+           -0.05063364166677987,
+           -0.061040512940311945,
+           -0.07203637226631697,
+           -0.083484668440091,
+           -0.09522745481622699,
+           -0.10708950191325016,
+           -0.11888293811341089,
+           -0.1304122989409928,
+           -0.14147985422018058,
+           -0.1518910745360034,
+           -0.16146009405552578,
+           -0.17001502602972876,
+           -0.17740299021682968,
+           -0.1834947179807671,
+           -0.1881886107695688,
+           -0.19141414082615477,
+           -0.19313449900703109,
+           -0.1933484130878663,
+           -0.1920910804617752,
+           -0.18943418117735294,
+           -0.18548496027124273,
+           -0.1803843917511004,
+           -0.17430445979495424,
+           -0.16744461517134016,
+           -0.1600274859883373,
+           -0.15229394111782374,
+           -0.1444976215282357,
+           -0.1368990688665527,
+           -0.1297595915979299,
+           -0.12333501655636465,
+           -0.11786947768326626,
+           -0.11358939392347471,
+           -0.11069778469300133,
+           -0.10936906410519759,
+           -0.1097444444088826,
+           -0.11192806510690977,
+           -0.1159839473213348,
+           -0.12193385355910057,
+           -0.12975611158003164,
+           -0.13938543809820494,
+           -0.15071377411807288,
+           -0.16359211940230695,
+           -0.17783332948365285,
+           -0.1932158153581669,
+           -0.2094880641029574,
+           -0.22637387868596212,
+           -0.24357821766967228,
+           -0.2607935007881194,
+           -0.2777062348603717,
+           -0.29400380647967794,
+           -0.30938128358520395,
+           -0.32354806749267867,
+           -0.3362342402478392,
+           -0.34719645919528414,
+           -0.35622326125673726,
+           -0.36313965333048426,
+           -0.36781088212055013,
+           -0.37014529616957,
+           -0.3700962344300039,
+           -0.36766289883980713,
+           -0.3628901925080142,
+           -0.35586752967555174,
+           -0.3467266479995472,
+           -0.3356384773226891,
+           -0.32280914135929206,
+           -0.3084751891164408,
+           -0.292898170878327,
+           -0.2763586887798117,
+           -0.25915006401582386,
+           -0.24157177128932542,
+           -0.22392279599034837,
+           -0.20649507071053408,
+           -0.18956714501281835,
+           -0.1733982359691317,
+           -0.158222797015887,
+           -0.14424572941074906,
+           -0.13163834433837085,
+           -0.12053516491370037,
+           -0.11103163643763016,
+           -0.10318279079034848,
+           -0.0970028873598077,
+           -0.09246602897708983,
+           -0.08950772755770955,
+           -0.08802737111341177,
+           -0.08789152206871292,
+           -0.08893795692264002,
+           -0.09098033972452611,
+           -0.09381340701036629,
+           -0.0972185301310443,
+           -0.10096951257568122,
+           -0.1048384751477142,
+           -0.10860168079383294,
+           -0.11204515353045558,
+           -0.11496995218063724,
+           -0.11719696935777314,
+           -0.11857113905703046,
+           -0.11896495200758439,
+           -0.11828119619415997,
+           -0.11645486020992865,
+           -0.11345415884045898,
+           -0.10928066294984354,
+           -0.10396853877276559,
+           -0.09758292452944017,
+           -0.09021749429988886,
+           -0.08199127976653778,
+           -0.07304483924089925,
+           -0.06353587985997558,
+           -0.053634452559131574,
+           -0.04351785005824917,
+           -0.03336534537282877,
+           -0.023352912101766245,
+           -0.01364806785840763,
+           -0.0044049787020149535,
+           0.004240044614902404,
+           0.012172538160767563,
+           0.019303257156635726,
+           0.025570838402757336,
+           0.030943680629283113,
+           0.035420991012059894,
+           0.03903296784808181,
+           0.04184011192900173,
+           0.043931681913319746,
+           0.04542333140080111,
+           0.04645398688739961,
+           0.04718204577947618,
+           0.04778099166307729,
+           0.048434539597588956,
+           0.049331436934311586,
+           0.050660054721576996,
+           0.05260291090039659,
+           0.05533126905537022,
+           0.058999955391519796,
+           0.06374253187736513,
+           0.0696669552377675,
+           0.07685183989535949,
+           0.08534342832908887,
+           0.09515335500175948,
+           0.10625727043265132,
+           0.11859437064097623,
+           0.13206785459112882,
+           0.14654630899364623,
+           0.16186599643711336,
+           0.17783399993022916,
+           0.19423215509358313,
+           0.21082168100595944,
+           0.22734840259008812,
+           0.24354844187612984,
+           0.25915424290330263,
+           0.2739007857335473,
+           0.28753183929766296,
+           0.2998061007283892,
+           0.31050307051996984,
+           0.31942851826047963,
+           0.32641940269003045,
+           0.3313481222341317,
+           0.33412598765184787,
+           0.33470582665086573,
+           0.33308365081610497,
+           0.3292993374779154,
+           0.3234363026680266,
+           0.3156201655025834,
+           0.306016428600625,
+           0.2948272228991672,
+           0.2822871878803553,
+           0.26865857922582226,
+           0.25422571474216354,
+           0.23928888559562125,
+           0.22415787305431764,
+           0.2091452207370265,
+           0.19455941856518214,
+           0.18069815705426814,
+           0.1678418091985951,
+           0.15624729203001758,
+           0.14614245108951926,
+           0.13772109875386865,
+           0.13113882190541878,
+           0.12650965619666857,
+           0.12390370358559256,
+           0.1233457474035341,
+           0.12481489550992231,
+           0.12824525766419576,
+           0.13352763869929624,
+           0.14051220500985892,
+           0.14901205885670094,
+           0.15880763359602512,
+           0.16965180368531943,
+           0.18127558666396637,
+           0.19339430065646093,
+           0.2057140306271969,
+           0.21793824987325908,
+           0.2297744402327166,
+           0.24094055527600294,
+           0.2511711753088993,
+           0.26022321122700554,
+           0.2678810259132085,
+           0.2739608566672705,
+           0.2783144397291305,
+           0.28083175786607256,
+           0.2814428537432412,
+           0.2801186748471761,
+           0.2768709395124939,
+           0.2717510375249552,
+           0.2648480022501505,
+           0.25628561368847474,
+           0.24621871273312745,
+           0.23482882569795205,
+           0.22231921442828248,
+           0.20890948061686576,
+           0.1948298629984611,
+           0.18031537265256464,
+           0.16559991455282422,
+           0.15091054270419707,
+           0.1364619917371083,
+           0.12245161980551506,
+           0.10905488627495284,
+           0.09642147328199914,
+           0.08467214316825988,
+           0.07389640447606584,
+           0.06415103813068633,
+           0.0554595131588749,
+           0.04781229836913677,
+           0.04116805342375007,
+           0.03545566024545325,
+           0.030577034288398725,
+           0.026410635401199308,
+           0.02281558031615643,
+           0.01963624365594069,
+           0.0167072221353473,
+           0.013858527655459417,
+           0.01092086946315735,
+           0.0077308836158373325,
+           0.004136169694362087,
+           4.1437450183561176e-17
+          ],
+          [
+           0,
+           -0.00558485760713571,
+           -0.012037846415041468,
+           -0.019416282982296577,
+           -0.027744594330894434,
+           -0.03701322206035251,
+           -0.04717848145913499,
+           -0.05816338204561168,
+           -0.06985939084201497,
+           -0.08212909500264717,
+           -0.09480969680886144,
+           -0.10771725210839476,
+           -0.12065154357410963,
+           -0.13340146319003057,
+           -0.1457507645753375,
+           -0.15748403548501,
+           -0.16839273434618052,
+           -0.1782811321740178,
+           -0.18697200273278825,
+           -0.1943119093379841,
+           -0.20017594610470318,
+           -0.20447180450887065,
+           -0.20714305252244708,
+           -0.20817153290834015,
+           -0.2075788090380044,
+           -0.2054266102849856,
+           -0.20181625406225637,
+           -0.19688704728707065,
+           -0.19081369583231517,
+           -0.1838027757131589,
+           -0.17608834373056725,
+           -0.16792678744622572,
+           -0.1595910341378844,
+           -0.15136425527926203,
+           -0.1435332166741207,
+           -0.1363814343008921,
+           -0.13018230193335353,
+           -0.1251923585319715,
+           -0.12164486118823423,
+           -0.11974382309149932,
+           -0.119658665717333,
+           -0.1215196204488476,
+           -0.12541399747150875,
+           -0.13138341944490461,
+           -0.13942209464375388,
+           -0.14947617952871584,
+           -0.16144425465750753,
+           -0.1751789111141445,
+           -0.19048941787251994,
+           -0.20714541437545755,
+           -0.22488154774296976,
+           -0.24340295103463722,
+           -0.26239143844642693,
+           -0.2815122757282439,
+           -0.3004213698995865,
+           -0.31877271186885175,
+           -0.3362258990877181,
+           -0.3524535630585498,
+           -0.3671485284209124,
+           -0.3800305364306869,
+           -0.39085237576714166,
+           -0.3994052775159736,
+           -0.40552344854318595,
+           -0.40908763787446306,
+           -0.410027653631894,
+           -0.4083237729967547,
+           -0.4040070139575502,
+           -0.39715826462698084,
+           -0.3879062930126211,
+           -0.3764246866448981,
+           -0.36292779675812087,
+           -0.3476657851719106,
+           -0.3309188930631581,
+           -0.31299106894363377,
+           -0.29420310792888693,
+           -0.2748854654457723,
+           -0.2553709156161475,
+           -0.2359872275077956,
+           -0.21705003119712946,
+           -0.19885604018149222,
+           -0.1816767872537914,
+           -0.16575301774916346,
+           -0.15128986742515835,
+           -0.13845293256055688,
+           -0.12736531764400055,
+           -0.11810572182440891,
+           -0.11070759971061499,
+           -0.10515940577079444,
+           -0.10140590514319311,
+           -0.0993505077797092,
+           -0.09885855813936811,
+           -0.09976148973522607,
+           -0.1018617332757052,
+           -0.1049382494302655,
+           -0.10875254281833953,
+           -0.11305500301598635,
+           -0.11759141145238414,
+           -0.12210945018668228,
+           -0.12636504977277926,
+           -0.13012841869104091,
+           -0.13318960600687496,
+           -0.13536346176433134,
+           -0.13649387580562627,
+           -0.13645719480924032,
+           -0.13516473887267927,
+           -0.13256436238391234,
+           -0.12864102863477603,
+           -0.12341639300589052,
+           -0.11694741495597451,
+           -0.10932404383943721,
+           -0.10066604713170724,
+           -0.09111907137091124,
+           -0.080850045482853,
+           -0.07004205265975363,
+           -0.05888881020015259,
+           -0.047588906358611,
+           -0.03633994906106209,
+           -0.025332783173083646,
+           -0.014745930822526811,
+           -0.004740403134418741,
+           0.004544978205918636,
+           0.01299762463119133,
+           0.020534481366845773,
+           0.027104496317563634,
+           0.03269019012218243,
+           0.037308283803886455,
+           0.04100936504617497,
+           0.043876599238036336,
+           0.046023516416685624,
+           0.04759092945876667,
+           0.0487430617155585,
+           0.049662983173148864,
+           0.05054747261227462,
+           0.05160143867437515,
+           0.05303204481410384,
+           0.05504269152197423,
+           0.057827013713652765,
+           0.0615630516819337,
+           0.06640775047151963,
+           0.07249193504464496,
+           0.0799158973359997,
+           0.08874571652215325,
+           0.09901041591587784,
+           0.11070003928106584,
+           0.12376470655936281,
+           0.13811468457119408,
+           0.15362148280927482,
+           0.17011995861638027,
+           0.18741139047657357,
+           0.2052674534903235,
+           0.22343500796826027,
+           0.24164159104810354,
+           0.2596014828461561,
+           0.277022203365559,
+           0.2936112845893369,
+           0.30908315419191196,
+           0.32316596331972575,
+           0.3356081910319653,
+           0.3461848622665963,
+           0.35470322451273756,
+           0.36100774053559215,
+           0.36498427022664426,
+           0.3665633335630519,
+           0.3657223683000103,
+           0.3624869198640082,
+           0.35693072638363244,
+           0.34917468826701376,
+           0.33938473856448365,
+           0.32776865688486106,
+           0.31457189521379647,
+           0.3000725079846616,
+           0.2845753005866566,
+           0.26840532962328684,
+           0.25190090418534206,
+           0.23540624978150473,
+           0.2192640050693578,
+           0.20380772593759838,
+           0.18935457169417275,
+           0.1761983441057069,
+           0.1646030419046506,
+           0.15479708132702866,
+           0.14696831755645012,
+           0.14125998300926493,
+           0.13776763666127648,
+           0.13653719461641825,
+           0.13756408643605864,
+           0.14079355500879825,
+           0.14612209059530967,
+           0.1533999627910941,
+           0.16243478816568102,
+           0.17299604689078704,
+           0.18482043935527484,
+           0.19761795412159203,
+           0.2110785020810719,
+           0.2248789587107572,
+           0.23869044723171082,
+           0.2521856904326763,
+           0.2650462580681029,
+           0.2769695400776926,
+           0.28767528331464864,
+           0.2969115408199745,
+           0.3044598976529946,
+           0.31013985550766154,
+           0.3138122793549547,
+           0.3153818326307162,
+           0.3147983524576647,
+           0.31205714243169763,
+           0.30719818697237833,
+           0.3003043174829708,
+           0.29149838594069016,
+           0.28093952542013156,
+           0.26881859885753445,
+           0.2553529565587823,
+           0.24078063907383995,
+           0.22535417471593544,
+           0.20933412989328062,
+           0.19298257533678478,
+           0.17655663214041015,
+           0.16030225827476088,
+           0.14444842898411386,
+           0.12920185342645202,
+           0.11474235535367545,
+           0.10121902793027515,
+           0.08874725240627919,
+           0.07740664781302795,
+           0.06723999471036365,
+           0.05825315089170071,
+           0.05041595148336548,
+           0.043664060698206046,
+           0.03790171825398274,
+           0.033005300753440686,
+           0.02882759771467071,
+           0.025202683953238374,
+           0.021951255100844492,
+           0.01888628157058397,
+           0.015818828530813404,
+           0.0125638856188368,
+           0.008946050303977784,
+           0.004804912988051286,
+           4.8239143628232875e-17
+          ],
+          [
+           0,
+           -0.00644424891242834,
+           -0.013872292553702778,
+           -0.022328567806714144,
+           -0.031820772986267155,
+           -0.04231924707236991,
+           -0.05375740102762051,
+           -0.06603319249845581,
+           -0.07901160789983568,
+           -0.09252808947074984,
+           -0.10639282003501344,
+           -0.12039575554059166,
+           -0.13431227555890662,
+           -0.14790930531176036,
+           -0.1609517498842003,
+           -0.17320907241064876,
+           -0.1844618434215478,
+           -0.19450808833416766,
+           -0.2031692642792979,
+           -0.21029570597967615,
+           -0.2157713930320559,
+           -0.21951790738505608,
+           -0.22149746964568473,
+           -0.2217149655989743,
+           -0.22021889942392808,
+           -0.21710123691146052,
+           -0.2124961298683089,
+           -0.2065775411292805,
+           -0.19955581749244516,
+           -0.19167328473885337,
+           -0.18319896402545277,
+           -0.174422531713815,
+           -0.1656476645420307,
+           -0.15718492845820967,
+           -0.1493443819912442,
+           -0.14242807341250419,
+           -0.13672261491864263,
+           -0.13249201652712161,
+           -0.12997095732065955,
+           -0.12935866221457473,
+           -0.1308135387715356,
+           -0.13444871107503947,
+           -0.14032856671588567,
+           -0.14846640905074787,
+           -0.1588232806380612,
+           -0.17130799578251774,
+           -0.18577839110786434,
+           -0.20204377373754503,
+           -0.21986851771258287,
+           -0.23897673142600562,
+           -0.25905789278731517,
+           -0.2797733251903157,
+           -0.3007633667257159,
+           -0.32165506796586074,
+           -0.3420702404765252,
+           -0.3616336693075357,
+           -0.37998129830318894,
+           -0.39676819726833096,
+           -0.41167612482693045,
+           -0.42442051010461385,
+           -0.4347566899323498,
+           -0.4424852557779606,
+           -0.4474563856414124,
+           -0.44957306018859766,
+           -0.44879308886256286,
+           -0.4451298999573865,
+           -0.4386520779812469,
+           -0.4294816613579358,
+           -0.4177912428974438,
+           -0.40379994379215395,
+           -0.3877683584777873,
+           -0.36999259189277695,
+           -0.35079753189052654,
+           -0.33052951729352054,
+           -0.3095485759001588,
+           -0.28822041633419704,
+           -0.26690836273720453,
+           -0.24596542183054532,
+           -0.22572666781189055,
+           -0.2065021220115312,
+           -0.18857029143496581,
+           -0.1721725135838366,
+           -0.15750823469687564,
+           -0.14473132529148275,
+           -0.13394751119330064,
+           -0.1252129707529874,
+           -0.11853412034642033,
+           -0.11386858124315404,
+           -0.1111272922229098,
+           -0.11017770462698959,
+           -0.11084797053002816,
+           -0.11293201104331861,
+           -0.11619533099100089,
+           -0.12038142883841833,
+           -0.1252186372160446,
+           -0.1304272199949112,
+           -0.13572654684908658,
+           -0.14084216569716937,
+           -0.14551259734623886,
+           -0.14949568495514814,
+           -0.15257434336814674,
+           -0.15456156962052423,
+           -0.1553045955669133,
+           -0.1546880861277243,
+           -0.15263631151642923,
+           -0.1491142483696371,
+           -0.1441275922817057,
+           -0.13772169215031874,
+           -0.12997944426647678,
+           -0.12101821053988457,
+           -0.11098584997485174,
+           -0.100055974883253,
+           -0.08842256278037917,
+           -0.0762940709712086,
+           -0.06388721309920004,
+           -0.05142056509354446,
+           -0.03910817181376729,
+           -0.027153325160806138,
+           -0.015742679520049034,
+           -0.005040861253176401,
+           0.004814284202308872,
+           0.013715680897680016,
+           0.021590139948080102,
+           0.028400522272284092,
+           0.03414688761303457,
+           0.03886659743586749,
+           0.04263336663460668,
+           0.04555528645664201,
+           0.04777186800300591,
+           0.04945018137269186,
+           0.05078018935375407,
+           0.05196939590847759,
+           0.05323694801145036,
+           0.05480734420872849,
+           0.05690391419203381,
+           0.05974224044000831,
+           0.06352369538926068,
+           0.06842926559071494,
+           0.0746138279218937,
+           0.08220103231359611,
+           0.09127893086666868,
+           0.10189647503804541,
+           0.11406098121299743,
+           0.1277366409809251,
+           0.14284412639036484,
+           0.15926131302295057,
+           0.17682511557977923,
+           0.1953344025201214,
+           0.21455392883666521,
+           0.23421919998236823,
+           0.2540421559376686,
+           0.2737175430296593,
+           0.29292982292899167,
+           0.31136045371935545,
+           0.32869536743252015,
+           0.34463246224362565,
+           0.3588889257953393,
+           0.37120820892334316,
+           0.381366476335272,
+           0.3891783723852461,
+           0.3945019557142795,
+           0.39724267582017886,
+           0.3973562871149247,
+           0.3948506211786428,
+           0.38978616511624997,
+           0.38227542250311786,
+           0.37248106267173087,
+           0.3606128933263101,
+           0.34692371996014293,
+           0.3317041825917057,
+           0.3152766852655959,
+           0.29798855596909746,
+           0.2802045935468907,
+           0.2622991733869654,
+           0.2446480947233525,
+           0.22762035907947054,
+           0.21157007149117088,
+           0.19682865364367771,
+           0.18369755098797788,
+           0.17244160443759307,
+           0.16328324166207228,
+           0.15639762366560525,
+           0.1519088597365695,
+           0.14988737852540587,
+           0.15034851556955003,
+           0.15325234870256188,
+           0.1585047831625083,
+           0.16595985857252898,
+           0.17542322102498067,
+           0.18665667596277052,
+           0.19938371208576927,
+           0.21329586373375223,
+           0.22805975966082978,
+           0.24332469029075307,
+           0.2587305138072595,
+           0.27391571406754395,
+           0.2885254205012631,
+           0.30221920193200136,
+           0.31467845257950167,
+           0.32561319920442056,
+           0.3347681731707552,
+           0.3419280097517029,
+           0.34692145882861963,
+           0.34962451568633046,
+           0.34996240728162,
+           0.3479103974944592,
+           0.3434934037680618,
+           0.33678444649141187,
+           0.32790198076394256,
+           0.3170061871119153,
+           0.3042943226401349,
+           0.2899952563926579,
+           0.27436333182008926,
+           0.2576717147466105,
+           0.24020539672562333,
+           0.22225403089751888,
+           0.2041047802519521,
+           0.18603535649591105,
+           0.1683074215954846,
+           0.1511605136613238,
+           0.13480664445880405,
+           0.11942569781636378,
+           0.10516173704108886,
+           0.09212030566906936,
+           0.08036678008310805,
+           0.06992580537509223,
+           0.06078181800033304,
+           0.052880630967829134,
+           0.04613203023306174,
+           0.040413305288554316,
+           0.03557361332568775,
+           0.03143905536032573,
+           0.02781832489878963,
+           0.02450877551346763,
+           0.02130274345153734,
+           0.01799395536858519,
+           0.014383849607753763,
+           0.010287642171045974,
+           0.005539975578476109,
+           5.56766617921169e-17
+          ],
+          [
+           0,
+           -0.00737325026430867,
+           -0.01584249422515582,
+           -0.025435664806479984,
+           -0.0361403237382552,
+           -0.0479036216332809,
+           -0.06063339855779236,
+           -0.0742003986280996,
+           -0.0884415429847039,
+           -0.10316417770462812,
+           -0.11815118751875753,
+           -0.1331668432582061,
+           -0.1479632313477191,
+           -0.1622870978970309,
+           -0.17588692841892628,
+           -0.18852007722515285,
+           -0.19995975830399776,
+           -0.21000171203326215,
+           -0.21847036937605113,
+           -0.2252243470714763,
+           -0.23016112348020784,
+           -0.2332207647799805,
+           -0.234388594634586,
+           -0.23369672670151898,
+           -0.23122440774660646,
+           -0.22709714899154368,
+           -0.22148465388731675,
+           -0.21459758101874785,
+           -0.20668321053829286,
+           -0.19802011065496383,
+           -0.18891192655848404,
+           -0.17968043708616568,
+           -0.17065804385871317,
+           -0.162179873025325,
+           -0.15457568077075207,
+           -0.14816176005851947,
+           -0.14323304754236055,
+           -0.1400556261193387,
+           -0.1388598102923761,
+           -0.13983398854630993,
+           -0.14311937962545096,
+           -0.1488058383454394,
+           -0.15692882188987234,
+           -0.1674676000303156,
+           -0.18034476303560337,
+           -0.1954270499260973,
+           -0.21252748794100038,
+           -0.2314088024000812,
+           -0.25178802533247757,
+           -0.273342202071345,
+           -0.2957150681918804,
+           -0.318524545362711,
+           -0.34137088447475566,
+           -0.36384526830770353,
+           -0.38553867439238304,
+           -0.4060507919177231,
+           -0.42499878468656205,
+           -0.4420256952966492,
+           -0.45680829384014393,
+           -0.4690641872839563,
+           -0.4785580230050166,
+           -0.48510664129070236,
+           -0.48858305645815386,
+           -0.4889191739940459,
+           -0.4861071810943428,
+           -0.48019957946279385,
+           -0.47130786144194564,
+           -0.4595998627178615,
+           -0.44529585617760353,
+           -0.4286634812455352,
+           -0.4100116304587033,
+           -0.38968343949806294,
+           -0.3680485477798019,
+           -0.3454948135258661,
+           -0.32241967957197354,
+           -0.29922139374166035,
+           -0.2762902902405685,
+           -0.2540003361518206,
+           -0.23270113980937981,
+           -0.21271060578102835,
+           -0.19430840471146268,
+           -0.17773040577290117,
+           -0.163164195457538,
+           -0.15074577952066887,
+           -0.14055753571327,
+           -0.13262745425028086,
+           -0.12692967150377174,
+           -0.12338627096398509,
+           -0.12187029484928698,
+           -0.12220988062081352,
+           -0.12419340978184673,
+           -0.1275755323713419,
+           -0.13208391007784484,
+           -0.13742650439894724,
+           -0.14329922414727356,
+           -0.1493937391422441,
+           -0.15540526429663246,
+           -0.16104012055696262,
+           -0.16602288621450112,
+           -0.17010296377691542,
+           -0.17306040357320088,
+           -0.174710845143047,
+           -0.17490946072717614,
+           -0.17355381123456315,
+           -0.1705855532546832,
+           -0.1659909652948258,
+           -0.15980029170686033,
+           -0.15208593296199974,
+           -0.14295954027709945,
+           -0.13256810035550623,
+           -0.12108912148400991,
+           -0.10872505478800064,
+           -0.09569710352654173,
+           -0.08223858843305162,
+           -0.06858804790086931,
+           -0.05498225801069258,
+           -0.04164935884912202,
+           -0.028802270244159777,
+           -0.0166325720346059,
+           -0.005305011503796807,
+           0.005047216035423139,
+           0.014326287893093419,
+           0.022472573869027745,
+           0.029466379513134886,
+           0.03532856510766464,
+           0.040120022082587546,
+           0.043940018445413606,
+           0.046923454405989724,
+           0.049237097953511125,
+           0.051074896970791275,
+           0.05265248886709315,
+           0.0542010500535563,
+           0.05596064532885389,
+           0.05817325093171043,
+           0.06107563429730042,
+           0.06489227818294471,
+           0.06982853667811588,
+           0.07606420567781418,
+           0.0837476807903278,
+           0.09299086160126332,
+           0.1038649430684092,
+           0.11639721302282842,
+           0.1305689498392542,
+           0.14631448693123777,
+           0.16352148150499463,
+           0.1820323946988936,
+           0.2016471595999653,
+           0.22212698343145154,
+           0.2431992012039169,
+           0.2645630710459931,
+           0.28589637696260095,
+           0.30686268352782203,
+           0.3271190695472104,
+           0.3463241544680726,
+           0.36414622262047713,
+           0.380271246467949,
+           0.3944106110483613,
+           0.40630834768400426,
+           0.41574769570569986,
+           0.422556826120926,
+           0.4266135804998239,
+           0.42784910139148263,
+           0.42625025675963757,
+           0.421860789606731,
+           0.4147811544400307,
+           0.40516703377914404,
+           0.3932265597392062,
+           0.37921629706820764,
+           0.3634360741009243,
+           0.3462227761762471,
+           0.3279432414576053,
+           0.3089864211714212,
+           0.28975498449010423,
+           0.2706565621824969,
+           0.2520948323896735,
+           0.23446065622516576,
+           0.2181234702338077,
+           0.20342313708234858,
+           0.19066244533066304,
+           0.1801004339963971,
+           0.17194669824341285,
+           0.1663568093643641,
+           0.1634289558520241,
+           0.16320188340315306,
+           0.16565418087639902,
+           0.1707049272815103,
+           0.17821568258777937,
+           0.18799377329024414,
+           0.19979679303675218,
+           0.2133382099414775,
+           0.2282939461863636,
+           0.24430977277140278,
+           0.26100934336668513,
+           0.2780026765985622,
+           0.2948948861182653,
+           0.31129495268904994,
+           0.3268243324027928,
+           0.341125199991968,
+           0.3538681359087402,
+           0.3647590801514001,
+           0.3735453943687807,
+           0.38002089610117235,
+           0.38402975456513566,
+           0.38546916552478044,
+           0.38429075281644554,
+           0.38050067526491077,
+           0.37415844927827874,
+           0.36537452855866404,
+           0.3543067123515581,
+           0.34115548174327476,
+           0.32615838901690997,
+           0.30958364737187855,
+           0.2917230868601803,
+           0.2728846567480048,
+           0.2533846643328705,
+           0.23353994530624714,
+           0.2136601609403317,
+           0.19404041270723024,
+           0.17495435554206734,
+           0.15664797708855321,
+           0.13933419227710717,
+           0.12318838094458523,
+           0.10834497146359916,
+           0.09489514613740542,
+           0.0828857151226152,
+           0.07231917559914491,
+           0.06315494257206597,
+           0.05531170782660779,
+           0.04867085491548904,
+           0.0430808313551184,
+           0.038362355112370315,
+           0.03431431157844221,
+           0.030720180071214683,
+           0.027354815908589163,
+           0.02399140557359877,
+           0.020408408655858044,
+           0.016396301193280494,
+           0.01176394072287179,
+           0.0063443836303248465,
+           6.376729735024142e-17
+          ],
+          [
+           0,
+           -0.00837138918069503,
+           -0.01794506351999766,
+           -0.028728913779347786,
+           -0.04068712873452716,
+           -0.05374083708385397,
+           -0.0677699672873754,
+           -0.08261627864973409,
+           -0.09808748624450203,
+           -0.11396237350950948,
+           -0.12999676025311735,
+           -0.14593017106557668,
+           -0.1614930303089888,
+           -0.1764141954470263,
+           -0.1904286308441166,
+           -0.20328501956595652,
+           -0.2147531112754452,
+           -0.22463061003720577,
+           -0.2327494165870257,
+           -0.2389810551305351,
+           -0.24324113462894767,
+           -0.2454927183186686,
+           -0.24574850230738066,
+           -0.24407173381920577,
+           -0.24057583128573873,
+           -0.23542270120929729,
+           -0.22881977974145407,
+           -0.2210158593967479,
+           -0.21229579244303745,
+           -0.20297419149293475,
+           -0.1933882739334503,
+           -0.1838900194115738,
+           -0.17483782806674764,
+           -0.16658788109268402,
+           -0.15948541415928766,
+           -0.15385611799116067,
+           -0.14999787887107732,
+           -0.14817306503480687,
+           -0.14860155299857103,
+           -0.15145467109023192,
+           -0.15685021623877518,
+           -0.1648486749232853,
+           -0.17545075070044305,
+           -0.188596269610117,
+           -0.2041645017599206,
+           -0.22197590331756453,
+           -0.24179524882839407,
+           -0.263336090065931,
+           -0.28626644534364015,
+           -0.3102155931605984,
+           -0.3347818169630911,
+           -0.35954092434733376,
+           -0.38405534478616726,
+           -0.40788359541260444,
+           -0.43058989489877186,
+           -0.4517537012697994,
+           -0.4709789506984676,
+           -0.48790278091557104,
+           -0.50220353468854,
+           -0.5136078555842698,
+           -0.5218967095373545,
+           -0.5269101910766246,
+           -0.5285510018068271,
+           -0.5267865202005751,
+           -0.5216494151638869,
+           -0.5132367903845111,
+           -0.5017078813158339,
+           -0.4872803609433763,
+           -0.47022534339234173,
+           -0.4508612051641778,
+           -0.42954637159238407,
+           -0.40667124030959784,
+           -0.3826494335349839,
+           -0.3579085863414934,
+           -0.3328808883802282,
+           -0.30799360158079325,
+           -0.28365977599907377,
+           -0.26026938026621627,
+           -0.2381810521555597,
+           -0.21771465890644442,
+           -0.19914483652476683,
+           -0.1826956528302679,
+           -0.16853651114844567,
+           -0.15677938094240643,
+           -0.14747740910443868,
+           -0.14062493188338138,
+           -0.1361588733437537,
+           -0.13396148267467642,
+           -0.13386433041508017,
+           -0.13565345352642869,
+           -0.13907551196096837,
+           -0.14384479560605073,
+           -0.14965090080855764,
+           -0.156166880570583,
+           -0.16305766231675217,
+           -0.1699885221005913,
+           -0.176633404349342,
+           -0.1826828817196896,
+           -0.18785156019709204,
+           -0.19188474993852425,
+           -0.19456424213338727,
+           -0.19571305583192583,
+           -0.19519904566066532,
+           -0.19293729092496129,
+           -0.18889121804100956,
+           -0.1830724407497367,
+           -0.1755393353239974,
+           -0.16639440016484006,
+           -0.15578047998457178,
+           -0.14387596342232956,
+           -0.13088908871545532,
+           -0.11705151431397605,
+           -0.10261132952174815,
+           -0.08782569392518466,
+           -0.07295330319179849,
+           -0.05824688257141236,
+           -0.04394590802588491,
+           -0.03026974839142307,
+           -0.017411410512562352,
+           -0.005532053174520822,
+           0.005243584686484692,
+           0.014830720078083767,
+           0.02318693210073636,
+           0.03031337347824961,
+           0.03625475403699799,
+           0.04109809480904088,
+           0.04497028359552409,
+           0.0480344942244819,
+           0.05048556157375437,
+           0.05254443194640466,
+           0.05445183288202118,
+           0.05646132733738705,
+           0.05883193384025413,
+           0.06182050628119015,
+           0.06567407414695273,
+           0.07062234602445443,
+           0.07687057605523993,
+           0.08459298476471884,
+           0.09392691252478898,
+           0.1049678661532149,
+           0.11776559724421086,
+           0.1323213253031721,
+           0.14858619025695263,
+           0.16646098813810148,
+           0.18579721146374056,
+           0.2063993828534248,
+           0.22802863758050881,
+           0.25040747885202225,
+           0.27322559946478986,
+           0.29614663585024587,
+           0.3188156960962174,
+           0.34086748294118346,
+           0.3619348165018248,
+           0.38165735003710516,
+           0.39969026567325816,
+           0.4157127358895708,
+           0.42943594074078656,
+           0.4406104401825073,
+           0.44903271525626265,
+           0.45455071094141364,
+           0.4570682367363185,
+           0.4565481079306787,
+           0.45301394042295734,
+           0.4465505440941787,
+           0.4373028933878911,
+           0.42547368804315794,
+           0.4113195510428956,
+           0.39514594393649194,
+           0.3773009109597035,
+           0.35816779203664684,
+           0.3381570701009942,
+           0.3176975395897535,
+           0.29722699991211043,
+           0.2771826897559722,
+           0.257991684963673,
+           0.24006148421025855,
+           0.22377100280919238,
+           0.20946218573960515,
+           0.19743243665583368,
+           0.1879280405480398,
+           0.18113873433350525,
+           0.17719355253812674,
+           0.17615804503486512,
+           0.1780329312738381,
+           0.18275422135811806,
+           0.19019479951879434,
+           0.2001674308686009,
+           0.2124291186082223,
+           0.22668670694209858,
+           0.2426035956057714,
+           0.2598074058259389,
+           0.27789841535826104,
+           0.2964585625110693,
+           0.31506080619091326,
+           0.3332786213040258,
+           0.350695406494921,
+           0.3669135842466888,
+           0.381563181722034,
+           0.39430969417426015,
+           0.4048610509631146,
+           0.4129735267153035,
+           0.4184564664122674,
+           0.42117572251629515,
+           0.4210557339333288,
+           0.41808020987335626,
+           0.41229141568620264,
+           0.40378809168409346,
+           0.39272206897858725,
+           0.3792936776487931,
+           0.36374607135503784,
+           0.34635861811539054,
+           0.3274395287503731,
+           0.3073179119481639,
+           0.28633545759186785,
+           0.2648379576239216,
+           0.24316687612851406,
+           0.22165117744934468,
+           0.20059961311619792,
+           0.180293655347579,
+           0.16098124726877575,
+           0.14287151819015179,
+           0.12613058688726242,
+           0.11087854745902179,
+           0.09718770173197387,
+           0.08508207010133104,
+           0.07453817996187143,
+           0.06548709830772585,
+           0.05781764348783445,
+           0.051380681285509815,
+           0.04599438319243456,
+           0.04145030065150278,
+           0.03752008874969822,
+           0.033962696855947,
+           0.030531832414938564,
+           0.026983497803041386,
+           0.023083398977903805,
+           0.018614028631215435,
+           0.013381235576858419,
+           0.007220105939881982,
+           7.251809163146902e-17
+          ],
+          [
+           0,
+           -0.00943705834156597,
+           -0.020174369176559584,
+           -0.03219638775823626,
+           -0.04544092138753293,
+           -0.059800547663609836,
+           -0.07512531494564173,
+           -0.09122665589430269,
+           -0.10788241311042923,
+           -0.12484284658801055,
+           -0.14183746669509784,
+           -0.15858251435304768,
+           -0.174788892566116,
+           -0.19017034091076526,
+           -0.20445163735331728,
+           -0.21737661001890404,
+           -0.22871574533915656,
+           -0.23827318827636462,
+           -0.24589294483604524,
+           -0.2514641164839994,
+           -0.2549250199006564,
+           -0.2562660731458717,
+           -0.25553136008544747,
+           -0.2528188180806297,
+           -0.2482790286369168,
+           -0.2421126260815788,
+           -0.23456637450444404,
+           -0.22592799727120721,
+           -0.21651987554554378,
+           -0.2066917616252083,
+           -0.1968126787646,
+           -0.18726220086418294,
+           -0.1784213223999574,
+           -0.17066314080434594,
+           -0.16434357988100312,
+           -0.15979238356308223,
+           -0.15730460436998048,
+           -0.15713280038513947,
+           -0.15948013870924097,
+           -0.16449458251403545,
+           -0.17226431353068494,
+           -0.1828145126630051,
+           -0.19610558912701798,
+           -0.21203291386965914,
+           -0.23042807685699823,
+           -0.25106165103073763,
+           -0.2736474092129155,
+           -0.2978479048895879,
+           -0.323281294494405,
+           -0.349529248363337,
+           -0.37614577069427046,
+           -0.4026667262838333,
+           -0.42861985408890163,
+           -0.4535350352135326,
+           -0.47695457606681346,
+           -0.4984432663492109,
+           -0.5175979762394451,
+           -0.5340565675632114,
+           -0.5475059095821629,
+           -0.557688810965739,
+           -0.5644097049944458,
+           -0.5675389544741251,
+           -0.5670156755025101,
+           -0.5628490143288476,
+           -0.5551178482315088,
+           -0.5439689187155077,
+           -0.5296134424929888,
+           -0.5123222817518137,
+           -0.49241978926475694,
+           -0.4702764751182637,
+           -0.4463006694882508,
+           -0.4209293792924287,
+           -0.394618555139777,
+           -0.367832998332247,
+           -0.3410361454348154,
+           -0.3146799699379404,
+           -0.2891952367527943,
+           -0.26498233580792047,
+           -0.24240290609930873,
+           -0.22177244156038914,
+           -0.20335404556452397,
+           -0.1873534723615519,
+           -0.17391556198980498,
+           -0.16312214098205205,
+           -0.15499142534364616,
+           -0.14947892570748417,
+           -0.1464798181632504,
+           -0.14583270891195918,
+           -0.14732468747702224,
+           -0.15069753252665044,
+           -0.15565490717641262,
+           -0.16187035760438487,
+           -0.16899591047957166,
+           -0.17667105151447215,
+           -0.18453185971371652,
+           -0.19222006977573322,
+           -0.19939183864651028,
+           -0.2057260013163718,
+           -0.2109316153471533,
+           -0.21475461294191026,
+           -0.21698340312401573,
+           -0.21745329416977657,
+           -0.2160496371371334,
+           -0.21270962437474666,
+           -0.20742271144628122,
+           -0.20022966609322923,
+           -0.1912202828013956,
+           -0.1805298353541046,
+           -0.16833437160208478,
+           -0.15484498375938982,
+           -0.14030121312093316,
+           -0.12496376955331169,
+           -0.10910676290417892,
+           -0.09300965519199474,
+           -0.0769491487910108,
+           -0.061191226664510434,
+           -0.0459835560101186,
+           -0.03154845659089908,
+           -0.018076619797329184,
+           -0.00572174450950832,
+           0.005403768383145931,
+           0.01523194877872831,
+           0.023741134192596092,
+           0.030956540208601488,
+           0.036949508307525615,
+           0.041835449423100364,
+           0.0457705357198188,
+           0.04894722591249917,
+           0.05158874012095557,
+           0.05394262799362302,
+           0.05627359793449677,
+           0.058855795112328475,
+           0.061964731010387734,
+           0.0658690771994479,
+           0.07082254052549378,
+           0.07705603587246733,
+           0.08477036610380238,
+           0.0941296068581522,
+           0.10525537686340578,
+           0.11822215275577379,
+           0.13305376158219734,
+           0.14972115486402615,
+           0.16814153603593146,
+           0.18817887904521363,
+           0.20964584075260023,
+           0.23230703439555864,
+           0.2558835966460924,
+           0.28005894758946637,
+           0.3044856121049134,
+           0.32879294342335885,
+           0.35259556577351664,
+           0.37550233361496593,
+           0.39712559049422713,
+           0.4170905014245876,
+           0.4350442291279739,
+           0.45066472659520773,
+           0.4636689261862941,
+           0.473820118731594,
+           0.4809343344983955,
+           0.48488556101738517,
+           0.4856096600637582,
+           0.48310687689780374,
+           0.4774428684411729,
+           0.46874821257936145,
+           0.4572163973703073,
+           0.44310032570735985,
+           0.42670740702989235,
+           0.40839334211069034,
+           0.38855473892790593,
+           0.36762072636204957,
+           0.3460437572349592,
+           0.32428981241391774,
+           0.302828232837507,
+           0.2821214160015586,
+           0.26261461742865294,
+           0.24472609582691557,
+           0.22883783305991484,
+           0.21528704687700873,
+           0.20435869590742928,
+           0.1962791531459934,
+           0.19121119661644256,
+           0.189250434757621,
+           0.1904232500938828,
+           0.1946863087499223,
+           0.20192764622676643,
+           0.21196930247300802,
+           0.22457144257222894,
+           0.2394378642161466,
+           0.25622276039687686,
+           0.2745385762248851,
+           0.293964773176648,
+           0.31405729301628804,
+           0.33435849762487235,
+           0.354407350392342,
+           0.37374959992902135,
+           0.3919477277457903,
+           0.40859042820162594,
+           0.4233014012504358,
+           0.43574725602544373,
+           0.44564434563898864,
+           0.45276438019111476,
+           0.45693869520987757,
+           0.4580610858404728,
+           0.45608915224059815,
+           0.4510441379585247,
+           0.4430092796735832,
+           0.43212672266620733,
+           0.41859309087361285,
+           0.4026538325336054,
+           0.3845964914386641,
+           0.3647430790099762,
+           0.3434417431476465,
+           0.32105794562101314,
+           0.29796537025780956,
+           0.27453678913091506,
+           0.25113511322329823,
+           0.22810484771279685,
+           0.20576416023525299,
+           0.18439775356911192,
+           0.16425071257555618,
+           0.14552346948008996,
+           0.12836800235089924,
+           0.11288534965804704,
+           0.09912448989443631,
+           0.08708260025980445,
+           0.0767066732333093,
+           0.0678964353722067,
+           0.06050847973854505,
+           0.0543614927971626,
+           0.04924242920994884,
+           0.04491346435680722,
+           0.04111953522951014,
+           0.037596266045595926,
+           0.03407806586720844,
+           0.03030618190393743,
+           0.026036494111439778,
+           0.02104684411171887,
+           0.015143704161384238,
+           0.008168009553076344,
+           8.19255753374069e-17
+          ],
+          [
+           0,
+           -0.010567519544514792,
+           -0.022522578883388062,
+           -0.03582300689672809,
+           -0.0503775027198142,
+           -0.06604791669443551,
+           -0.08265286261392396,
+           -0.09997256773028604,
+           -0.11775483444968642,
+           -0.13572195829441125,
+           -0.15357842130331853,
+           -0.17101915922784636,
+           -0.18773818519096375,
+           -0.20343734231750918,
+           -0.2178349534828566,
+           -0.23067413788386362,
+           -0.24173057158394953,
+           -0.2508194823470922,
+           -0.25780168763378736,
+           -0.2625885081297899,
+           -0.26514541703518857,
+           -0.2654943168660553,
+           -0.2637143699293386,
+           -0.2599413450658128,
+           -0.25436548080533966,
+           -0.24722790280325616,
+           -0.23881567037985804,
+           -0.22945556223750802,
+           -0.21950674409310533,
+           -0.2093524902114898,
+           -0.19939115591518813,
+           -0.19002661843705532,
+           -0.18165841845231617,
+           -0.17467184388397505,
+           -0.1694282008705037,
+           -0.16625551401472966,
+           -0.1654398892459543,
+           -0.16721775802096997,
+           -0.17176920150612215,
+           -0.1792125283005543,
+           -0.18960024978394902,
+           -0.20291656401404431,
+           -0.21907642306619268,
+           -0.23792622067815875,
+           -0.2592460979682122,
+           -0.282753825791483,
+           -0.3081101839511676,
+           -0.33492572093071515,
+           -0.362768743961429,
+           -0.39117435892261815,
+           -0.419654353538813,
+           -0.4477076962365276,
+           -0.4748314073773557,
+           -0.5005315497872286,
+           -0.5243340818027448,
+           -0.5457953185545931,
+           -0.5645117558531739,
+           -0.580129025629938,
+           -0.5923497720710658,
+           -0.600940262872005,
+           -0.6057355798307026,
+           -0.6066432665622734,
+           -0.6036453476438198,
+           -0.5967986720978716,
+           -0.5862335738583264,
+           -0.5721508817678541,
+           -0.5548173507604268,
+           -0.5345596232367104,
+           -0.5117568643363775,
+           -0.48683224600833297,
+           -0.460243481721859,
+           -0.4324726356978837,
+           -0.40401544713988097,
+           -0.3753704207114986,
+           -0.34702793918986413,
+           -0.3194596527154618,
+           -0.29310839140975076,
+           -0.26837883453866823,
+           -0.2456291502080216,
+           -0.22516379526647035,
+           -0.2072276362692776,
+           -0.19200151973706164,
+           -0.17959938433623587,
+           -0.17006696989165124,
+           -0.16338213924725206,
+           -0.15945678987475173,
+           -0.158140293754286,
+           -0.15922436735549217,
+           -0.1624492394297009,
+           -0.16751095361571341,
+           -0.17406961630859985,
+           -0.18175837848449958,
+           -0.19019292373567923,
+           -0.19898122403763427,
+           -0.20773331998987143,
+           -0.2160708835422806,
+           -0.22363632848737955,
+           -0.23010124706401675,
+           -0.23517396953571493,
+           -0.23860606709711374,
+           -0.24019764632280843,
+           -0.23980131489445128,
+           -0.23732473272495574,
+           -0.23273169897381984,
+           -0.22604176289803685,
+           -0.21732838406670324,
+           -0.20671570424083385,
+           -0.19437402826160152,
+           -0.18051414372387625,
+           -0.16538063822802762,
+           -0.14924439787897872,
+           -0.13239449081995472,
+           -0.11512965445201222,
+           -0.09774961423472428,
+           -0.08054646536533988,
+           -0.06379634611748519,
+           -0.04775162325906509,
+           -0.03263379598239742,
+           -0.01862730552912321,
+           -0.0058744136716312925,
+           0.0055287149650537805,
+           0.015534623373959812,
+           0.024145796314613478,
+           0.031414485041385436,
+           0.03744112638103299,
+           0.042371396710012624,
+           0.04639197714349922,
+           0.04972514008093815,
+           0.05262229829709251,
+           0.05535668523242106,
+           0.05821535832149255,
+           0.06149073550949275,
+           0.0654718880734376,
+           0.07043582014933983,
+           0.07663896677472969,
+           0.08430913774076682,
+           0.09363812421170283,
+           0.10477516916022507,
+           0.11782148157419087,
+           0.13282594863324187,
+           0.1497821702705076,
+           0.168626907465034,
+           0.1892400000782949,
+           0.21144577294027264,
+           0.235015911135182,
+           0.2596737479803869,
+           0.285099872975158,
+           0.3109389329304285,
+           0.3368074684368422,
+           0.3623026005727422,
+           0.38701135999039293,
+           0.4105204328308568,
+           0.4324260857641492,
+           0.4523440261530273,
+           0.46991895307306053,
+           0.48483356071555944,
+           0.49681676743064546,
+           0.5056509610643247,
+           0.5111780738943377,
+           0.5133043278318067,
+           0.5120035219687286,
+           0.5073187692528308,
+           0.49936262621611227,
+           0.48831559836418625,
+           0.4744230431034416,
+           0.45799053097860826,
+           0.43937776355867125,
+           0.4189911816193891,
+           0.3972754294548796,
+           0.37470386941359624,
+           0.3517683643950161,
+           0.3289685644751276,
+           0.30680094659055834,
+           0.2857478629812281,
+           0.2662668546945632,
+           0.24878048086632387,
+           0.23366690284199004,
+           0.22125144476460692,
+           0.21179932944884303,
+           0.20550976073682348,
+           0.20251149175794964,
+           0.20285998336277822,
+           0.2065362193237499,
+           0.21344720560859684,
+           0.22342814109063547,
+           0.23624620743486202,
+           0.2516058875529587,
+           0.2691556858854781,
+           0.2884960907227548,
+           0.3091885896185138,
+           0.3307655243870131,
+           0.3527405527983603,
+           0.3746194703620249,
+           0.3959111378416117,
+           0.4161382585537423,
+           0.4348477540984435,
+           0.45162049782403774,
+           0.4660801817741275,
+           0.47790111468390384,
+           0.48681477524256694,
+           0.49261497565524015,
+           0.49516152475713965,
+           0.49438231670845045,
+           0.4902738097224601,
+           0.4828998984053849,
+           0.4723892221518002,
+           0.4589309896909274,
+           0.4427694353943848,
+           0.4241970554681822,
+           0.40354680086961203,
+           0.38118342801755883,
+           0.3574942275196044,
+           0.3328793647648599,
+           0.30774207400952913,
+           0.282478949340128,
+           0.25747057161414816,
+           0.233072700276995,
+           0.20960824311090334,
+           0.18736019589977798,
+           0.16656571823611221,
+           0.1474114819102165,
+           0.13003039526508955,
+           0.11449977140909257,
+           0.10084097114915958,
+           0.08902051387188857,
+           0.07895261230435066,
+           0.07050305106606462,
+           0.06349429508012576,
+           0.05771168309047751,
+           0.05291053450217578,
+           0.04882397519432798,
+           0.04517127041027645,
+           0.0416664407387972,
+           0.03802693085825313,
+           0.033982100272660125,
+           0.02928131072589608,
+           0.023701396190840877,
+           0.017053318002497243,
+           0.00918782940933569,
+           9.197564447401809e-17
+          ],
+          [
+           0,
+           -0.011758922441247889,
+           -0.024979730667188234,
+           -0.03959069450641239,
+           -0.055469010964131545,
+           -0.07244402449218884,
+           -0.09030181057084419,
+           -0.10879100302229412,
+           -0.12762971272878013,
+           -0.1465133565489477,
+           -0.1651231909515666,
+           -0.18313532583702644,
+           -0.20022998068427952,
+           -0.21610073789072998,
+           -0.23046354715931155,
+           -0.24306524006777833,
+           -0.253691325408866,
+           -0.2621728532398992,
+           -0.2683921584014291,
+           -0.27228732199329586,
+           -0.2738552212456267,
+           -0.2731530735971485,
+           -0.27029841871184423,
+           -0.2654675216800462,
+           -0.25889222077232354,
+           -0.2508552828375719,
+           -0.24168436776206303,
+           -0.23174473936819262,
+           -0.22143089282160466,
+           -0.2111572972042801,
+           -0.20134847567055641,
+           -0.1924286639231801,
+           -0.18481130015177888,
+           -0.17888860573718274,
+           -0.17502151576694006,
+           -0.17353021171457023,
+           -0.17468549565163424,
+           -0.1787012263882442,
+           -0.1857280134239917,
+           -0.19584833512561395,
+           -0.20907321384212568,
+           -0.22534054354117344,
+           -0.2445151259069032,
+           -0.2663904296486795,
+           -0.29069204604059823,
+           -0.31708277246843813,
+           -0.34516921601772066,
+           -0.3745097718732702,
+           -0.40462379743692023,
+           -0.4350017734435835,
+           -0.4651162187017555,
+           -0.494433106016211,
+           -0.522423513845821,
+           -0.5485752416367911,
+           -0.5724041167240745,
+           -0.5934647272226156,
+           -0.6113603282859271,
+           -0.6257516881848424,
+           -0.6363646653964418,
+           -0.6429963376954849,
+           -0.6455195383869197,
+           -0.6438856924804066,
+           -0.638125885871847,
+           -0.6283501424844944,
+           -0.6147449268151393,
+           -0.5975689313961517,
+           -0.577147249299386,
+           -0.5538640699863925,
+           -0.5281540716242272,
+           -0.5004927135934524,
+           -0.4713856585739939,
+           -0.44135757368657236,
+           -0.4109405742102337,
+           -0.38066258105661926,
+           -0.3510358642821862,
+           -0.3225460394447706,
+           -0.295641771706045,
+           -0.2707254245493463,
+           -0.24814486627596635,
+           -0.228186618653426,
+           -0.21107049893204605,
+           -0.1969458697424069,
+           -0.18588957204340764,
+           -0.17790557527888712,
+           -0.1729263372298903,
+           -0.1708158247435998,
+           -0.17137410659160887,
+           -0.17434339213652217,
+           -0.17941535518354468,
+           -0.186239552196838,
+           -0.19443271869977494,
+           -0.20358870776346244,
+           -0.2132888204925924,
+           -0.22311227066777584,
+           -0.23264652436949262,
+           -0.24149726050172304,
+           -0.24929770950469904,
+           -0.2557171448921059,
+           -0.2604683251165999,
+           -0.26331371107070384,
+           -0.26407031655831376,
+           -0.26261308451200477,
+           -0.2588767196865635,
+           -0.25285594807227174,
+           -0.24460421334830834,
+           -0.23423086033080226,
+           -0.2218968935684351,
+           -0.207809435045515,
+           -0.19221503747439905,
+           -0.17539203808599826,
+           -0.1576421614529322,
+           -0.13928159812025778,
+           -0.12063179822514143,
+           -0.10201022555806993,
+           -0.08372131750737068,
+           -0.06604789004714795,
+           -0.04924321454517405,
+           -0.03352397500393702,
+           -0.019064290872357885,
+           -0.005990962378337894,
+           0.005619936847736596,
+           0.01574503044190733,
+           0.024414121479572976,
+           0.03170917331102688,
+           0.03776181549500427,
+           0.04274943987493819,
+           0.046889988803789445,
+           0.050435571897035784,
+           0.05366507860519845,
+           0.05687598055945151,
+           0.060375539375308734,
+           0.0644716518426809,
+           0.06946357476607033,
+           0.07563277587497311,
+           0.08323415508556951,
+           0.09248787200266584,
+           0.1035720011050727,
+           0.11661621591013817,
+           0.13169667805978513,
+           0.14883227733845358,
+           0.16798233486615444,
+           0.1890458449483198,
+           0.2118622922257447,
+           0.23621404082404768,
+           0.2618302521536213,
+           0.2883922488636021,
+           0.31554020519216425,
+           0.3428810095204302,
+           0.3699971142002348,
+           0.39645616146788093,
+           0.4218211531482635,
+           0.44566091644058553,
+           0.4675606087622147,
+           0.4871320016638951,
+           0.5040232873131875,
+           0.5179281609092059,
+           0.5285939484174529,
+           0.5358285708224109,
+           0.5395061631670127,
+           0.5395711983299956,
+           0.536041001016804,
+           0.5290065759427431,
+           0.5186317147286787,
+           0.5051503876175965,
+           0.48886246773486586,
+           0.470127876233591,
+           0.449359275288905,
+           0.4270134715791979,
+           0.40358172473624937,
+           0.37957918247140765,
+           0.35553368601486174,
+           0.33197420559246343,
+           0.3094191755050113,
+           0.2883650017166513,
+           0.26927501161000766,
+           0.2525691057947157,
+           0.23861435579260862,
+           0.22771676945054536,
+           0.2201144185795854,
+           0.2159720912478513,
+           0.21537759514091176,
+           0.21833979932168168,
+           0.22478846052085824,
+           0.23457583777005955,
+           0.24748005678187762,
+           0.26321014401483755,
+           0.2814126108444697,
+           0.30167943165406574,
+           0.3235572268483259,
+           0.34655743357474805,
+           0.37016722399306706,
+           0.39386091381469046,
+           0.4171115929506794,
+           0.4394027057146172,
+           0.4602393102221458,
+           0.47915875534712676,
+           0.49574052861045953,
+           0.5096150493125455,
+           0.5204712075506712,
+           0.5280624808325507,
+           0.532211495036504,
+           0.5328129346101057,
+           0.5298347472009608,
+           0.5233176293824392,
+           0.5133728217537381,
+           0.5001782824359602,
+           0.4839733468559645,
+           0.46505201775786326,
+           0.4437550617300291,
+           0.42046111639859707,
+           0.3955770351442653,
+           0.36952771320463484,
+           0.34274564992818457,
+           0.31566050649952293,
+           0.28868891656758866,
+           0.2622247989480095,
+           0.2366304071649126,
+           0.21222833042503653,
+           0.18929463519978224,
+           0.16805330657967374,
+           0.14867211472431568,
+           0.13125999491709434,
+           0.11586599087723322,
+           0.10247977106131438,
+           0.0910336877054138,
+           0.08140630932046299,
+           0.07342732023472076,
+           0.06688364650582677,
+           0.06152663695540984,
+           0.057080101971910914,
+           0.05324899172939805,
+           0.0497284800997319,
+           0.04621321116852664,
+           0.04240646212668431,
+           0.03802897946688829,
+           0.032827254777938054,
+           0.02658102175287591,
+           0.019109776913472185,
+           0.010278152468059014,
+           1.0264357380419932e-16
+          ],
+          [
+           0,
+           -0.013006337911899372,
+           -0.027533832656255065,
+           -0.04347857356472338,
+           -0.06068424139506597,
+           -0.0789463333179955,
+           -0.0980177645061206,
+           -0.11761569939039913,
+           -0.1374294332188615,
+           -0.1571291166843752,
+           -0.17637509379460592,
+           -0.19482760641741032,
+           -0.21215660848103202,
+           -0.22805142891512725,
+           -0.2422300251954163,
+           -0.2544475787434987,
+           -0.26450419920953416,
+           -0.27225152644360306,
+           -0.2775980462046978,
+           -0.28051296768943423,
+           -0.28102854698925567,
+           -0.279240779707093,
+           -0.2753084272048365,
+           -0.2694503832793025,
+           -0.2619414304151926,
+           -0.253106476074625,
+           -0.24331339871377805,
+           -0.23296466937744886,
+           -0.22248794689591944,
+           -0.21232587207697493,
+           -0.2029253081488726,
+           -0.1947262905028272,
+           -0.18815095809142907,
+           -0.1835927414081435,
+           -0.18140607771545514,
+           -0.18189691318772452,
+           -0.18531423413939577,
+           -0.19184284593167894,
+           -0.20159758905478567,
+           -0.21461914796982792,
+           -0.2308715703870427,
+           -0.25024157367814437,
+           -0.2725396720713115,
+           -0.2975031142118529,
+           -0.32480057667132284,
+           -0.3540385161348922,
+           -0.3847690423466971,
+           -0.4164991364492027,
+           -0.44870100604143687,
+           -0.48082333992829995,
+           -0.5123032028444803,
+           -0.5425782939788016,
+           -0.5710992833132392,
+           -0.5973419368772193,
+           -0.6208187460856405,
+           -0.641089787289982,
+           -0.6577725552688152,
+           -0.6705505381967326,
+           -0.6791803310862456,
+           -0.6834971190840238,
+           -0.6834184004880617,
+           -0.6789458610024326,
+           -0.6701653545496793,
+           -0.6572449908532199,
+           -0.6404313748921128,
+           -0.6200440871269206,
+           -0.5964685350338564,
+           -0.5701473449535831,
+           -0.5415704976274521,
+           -0.5112644402251649,
+           -0.4797804314522821,
+           -0.44768239389130055,
+           -0.41553455865617295,
+           -0.3838891914703468,
+           -0.35327468632499476,
+           -0.32418430302065737,
+           -0.2970658083947191,
+           -0.2723122583042284,
+           -0.250254129036411,
+           -0.23115297346338978,
+           -0.21519673976995182,
+           -0.20249684989005298,
+           -0.193087091893227,
+           -0.18692433652220652,
+           -0.1838910439803532,
+           -0.1837994839837788,
+           -0.18639755108291176,
+           -0.19137601932308135,
+           -0.19837704637680623,
+           -0.20700370816460592,
+           -0.2168303213881198,
+           -0.2274132938928646,
+           -0.23830223177001422,
+           -0.24905102784726593,
+           -0.2592286587904935,
+           -0.2684294273533649,
+           -0.27628240211700705,
+           -0.28245982894139826,
+           -0.28668431573945974,
+           -0.28873462438333636,
+           -0.2884499397412542,
+           -0.2857325251063871,
+           -0.28054871462544195,
+           -0.2729282357233137,
+           -0.26296189688666405,
+           -0.25079771745160806,
+           -0.2366356152062496,
+           -0.22072080368969582,
+           -0.20333608314695806,
+           -0.18479323638681674,
+           -0.1654237626117871,
+           -0.14556919810837465,
+           -0.12557128211587923,
+           -0.10576222900811533,
+           -0.08645536406598188,
+           -0.067936369698989,
+           -0.05045537226479362,
+           -0.03422007706943758,
+           -0.01939013128642381,
+           -0.006072862121415849,
+           0.005679498602800282,
+           0.015871031239568626,
+           0.02456175509194761,
+           0.0318656753664781,
+           0.037947301842603136,
+           0.04301673081704853,
+           0.04732341957780865,
+           0.05114881707092859,
+           0.054798044669195356,
+           0.05859084626375213,
+           0.06285204662998697,
+           0.06790177066036615,
+           0.07404568325465048,
+           0.08156551021951076,
+           0.09071009442910541,
+           0.10168722887749317,
+           0.1146564894187648,
+           0.1297232654041206,
+           0.14693415669466736,
+           0.1662738713924795,
+           0.18766372094034808,
+           0.21096176893327515,
+           0.2359646480700165,
+           0.2624110172010401,
+           0.2899865884662664,
+           0.3183306141175025,
+           0.3470436848052958,
+           0.3756966568341625,
+           0.40384049602392874,
+           0.43101680111986723,
+           0.4567687508050985,
+           0.48065220577653395,
+           0.5022466913860624,
+           0.5211659871929244,
+           0.5370680574237872,
+           0.5496640706271972,
+           0.5587262774069659,
+           0.5640945415354022,
+           0.5656813513476936,
+           0.5634751743386937,
+           0.557542057447524,
+           0.5480254176586844,
+           0.5351440112400369,
+           0.519188114106907,
+           0.5005139893625683,
+           0.4795367599464309,
+           0.45672184348940476,
+           0.4325751419636246,
+           0.40763220964196417,
+           0.382446648483536,
+           0.3575779996964063,
+           0.3335794134055028,
+           0.31098538473759174,
+           0.29029984405789616,
+           0.2719848815571801,
+           0.25645037206679805,
+           0.24404474521223815,
+           0.2350471193011254,
+           0.22966098532371487,
+           0.22800959089717432,
+           0.23013313379538206,
+           0.23598783184910638,
+           0.24544689151842639,
+           0.258303352411263,
+           0.27427474054358725,
+           0.29300942028931465,
+           0.3140944947921775,
+           0.3370650680833825,
+           0.36141465015332974,
+           0.3866064595374438,
+           0.41208535723913287,
+           0.4372901315249879,
+           0.46166584562763163,
+           0.4846759598532164,
+           0.5058139460153118,
+           0.5246141253362047,
+           0.5406614806353898,
+           0.5536002192702157,
+           0.5631408942666314,
+           0.5690659266099236,
+           0.5712334108772128,
+           0.569579128316828,
+           0.5641167350813562,
+           0.554936137528509,
+           0.542200110231498,
+           0.5261392545168038,
+           0.5070454349408942,
+           0.4852638671632967,
+           0.46118406229567643,
+           0.43522985924067925,
+           0.40784879714541566,
+           0.37950109439344293,
+           0.3506485082136843,
+           0.32174334982846775,
+           0.29321792409798236,
+           0.2654746500163473,
+           0.2388770995109058,
+           0.21374216728251666,
+           0.1903335545354552,
+           0.16885671514303188,
+           0.14945537494934494,
+           0.13220969447552333,
+           0.11713610329923535,
+           0.10418879186522868,
+           0.09326280452882756,
+           0.08419863728422561,
+           0.0767882058934555,
+           0.07078201595119422,
+           0.06589733664547644,
+           0.061827155343426324,
+           0.05824967125265709,
+           0.05483807374612832,
+           0.051270344797419695,
+           0.04723882549677325,
+           0.04245929378051056,
+           0.0366793141152557,
+           0.02968563957962886,
+           0.02131047207260362,
+           0.011436416602252895,
+           1.1389416848591065e-16
+          ],
+          [
+           0,
+           -0.01430380575772152,
+           -0.030170990165832707,
+           -0.047463201519106345,
+           -0.06598901275316961,
+           -0.08550920397669608,
+           -0.10574341473458106,
+           -0.12637799077989825,
+           -0.14707481856810253,
+           -0.16748091439058438,
+           -0.18723851470878553,
+           -0.20599540035795555,
+           -0.22341518022218282,
+           -0.23918725992897297,
+           -0.2530362280853917,
+           -0.2647304064148345,
+           -0.2740893305171598,
+           -0.2809899543639742,
+           -0.28537140340184797,
+           -0.28723813747974936,
+           -0.2866614248372377,
+           -0.28377907108730804,
+           -0.2787933914336594,
+           -0.2719674591656408,
+           -0.26361970764967785,
+           -0.2541170054715131,
+           -0.24386636400827041,
+           -0.23330547252036776,
+           -0.22289228694096072,
+           -0.21309392411118738,
+           -0.20437513260511062,
+           -0.19718662400362158,
+           -0.19195355417154034,
+           -0.18906444260070254,
+           -0.1888608092162707,
+           -0.1916277923945603,
+           -0.19758598967292854,
+           -0.2068847342754483,
+           -0.2195969868141326,
+           -0.23571598317182849,
+           -0.25515373756251813,
+           -0.2777414551230678,
+           -0.30323186221016635,
+           -0.33130341599025825,
+           -0.3615663090640048,
+           -0.39357014088946884,
+           -0.4268130867452396,
+           -0.4607523579204725,
+           -0.4948157146521101,
+           -0.5284137668499717,
+           -0.5609527775193017,
+           -0.5918476705137956,
+           -0.620534938168476,
+           -0.6464851456332675,
+           -0.66921473733649,
+           -0.6882968667545664,
+           -0.7033709931763666,
+           -0.7141510178880752,
+           -0.7204317664744004,
+           -0.7220936629054424,
+           -0.7191054838110058,
+           -0.7115251267984064,
+           -0.6994983737417181,
+           -0.683255677515845,
+           -0.6631070475119334,
+           -0.639435154312347,
+           -0.6126868160291437,
+           -0.5833630669969145,
+           -0.5520080428327654,
+           -0.5191969435264819,
+           -0.48552335753521275,
+           -0.45158624431746014,
+           -0.41797688000748257,
+           -0.38526607083599784,
+           -0.3539919314602203,
+           -0.3246485107689229,
+           -0.2976755263454232,
+           -0.2734494411375757,
+           -0.25227608268640184,
+           -0.2343849673266638,
+           -0.21992545003145195,
+           -0.2089647760585394,
+           -0.20148806436506017,
+           -0.19740020602451788,
+           -0.1965296147528823,
+           -0.19863372225819118,
+           -0.20340606955520563,
+           -0.210484807646153,
+           -0.21946238797660292,
+           -0.22989619562913283,
+           -0.241319856974866,
+           -0.253254938967823,
+           -0.2652227497755907,
+           -0.2767559501535801,
+           -0.28740969187138027,
+           -0.29677201339283177,
+           -0.30447324352766936,
+           -0.31019419037951423,
+           -0.3136729249302556,
+           -0.3147100052088956,
+           -0.31317202726593885,
+           -0.3089934320951377,
+           -0.30217654213204276,
+           -0.29278984589555324,
+           -0.28096459359801723,
+           -0.2668898090239685,
+           -0.25080586260677795,
+           -0.23299678642894583,
+           -0.21378154294588275,
+           -0.19350448481502175,
+           -0.17252526267118704,
+           -0.15120845054903065,
+           -0.12991316460407917,
+           -0.10898294968947912,
+           -0.08873620024695929,
+           -0.06945736708491365,
+           -0.051389180331348525,
+           -0.03472609171276923,
+           -0.019609107016758182,
+           -0.006122142970137682,
+           0.005709997261131737,
+           0.01592197815188872,
+           0.024606607391421276,
+           0.031911868771478134,
+           0.03803639119574515,
+           0.0432234735923851,
+           0.04775382343271294,
+           0.05193720046313535,
+           0.056103186280633634,
+           0.06059132378330781,
+           0.0657408877070847,
+           0.07188055797408226,
+           0.07931827115128366,
+           0.08833152184858022,
+           0.09915837544847515,
+           0.11198943640683576,
+           0.1269609929152873,
+           0.1441495295502894,
+           0.16356776537532622,
+           0.18516233666120743,
+           0.20881320190087338,
+           0.23433480315676053,
+           0.261478973083718,
+           0.28993953234060493,
+           0.3193584786611467,
+           0.34933362769445425,
+           0.3794275278878039,
+           0.409177438128049,
+           0.438106128437962,
+           0.46573324146771056,
+           0.49158693641329265,
+           0.5152155277568842,
+           0.5361988291128309,
+           0.5541589175543639,
+           0.5687700459884337,
+           0.5797674501606728,
+           0.5869548222610619,
+           0.590210254255546,
+           0.5894904902377559,
+           0.5848333674001313,
+           0.5763583686829672,
+           0.5642652557108233,
+           0.5488307971521276,
+           0.5304036539968802,
+           0.5093975282984565,
+           0.48628272455770627,
+           0.4615763120877175,
+           0.4358311114162379,
+           0.40962375719776845,
+           0.38354211348626616,
+           0.35817233397637305,
+           0.33408586953292785,
+           0.31182672774379994,
+           0.2918992842777877,
+           0.27475693361596193,
+           0.2607918475380257,
+           0.2503260840433641,
+           0.24360425778735803,
+           0.2407879463807432,
+           0.24195196592254772,
+           0.24708260490957362,
+           0.2560778592613365,
+           0.26874966374654,
+           0.28482806774896724,
+           0.303967257218257,
+           0.32575328093454914,
+           0.34971329893755165,
+           0.3753261351075316,
+           0.4020338853073329,
+           0.42925430793994923,
+           0.4563937058367552,
+           0.4828599974963568,
+           0.5080756720989859,
+           0.5314903265036289,
+           0.5525924934907128,
+           0.5709204885601687,
+           0.5860720271799073,
+           0.5977123948904363,
+           0.6055809883499911,
+           0.6094960853680778,
+           0.6093577452368176,
+           0.6051487861625626,
+           0.5969338332056171,
+           0.584856476708918,
+           0.5691346265955447,
+           0.5500541910294069,
+           0.5279612477114694,
+           0.5032529115578669,
+           0.47636713281699883,
+           0.4477716841003068,
+           0.4179526127431837,
+           0.3874024459571766,
+           0.3566084401326383,
+           0.32604116233027197,
+           0.2961436815675216,
+           0.267321630244628,
+           0.2399343724175004,
+           0.214287486219484,
+           0.19062673331312635,
+           0.16913364969055117,
+           0.14992285041250106,
+           0.1330410970340366,
+           0.11846813161183732,
+           0.10611923644986429,
+           0.09584943523713925,
+           0.08745921005106812,
+           0.08070157086912459,
+           0.07529028069233139,
+           0.07090901096805392,
+           0.06722117940964738,
+           0.06388020610172072,
+           0.060539914346536494,
+           0.05686480027303037,
+           0.05253989984271976,
+           0.047279993416877907,
+           0.04083790619353213,
+           0.03301168711185674,
+           0.02365047863193133,
+           0.012658924367792326,
+           1.2568205290437706e-16
+          ],
+          [
+           0,
+           -0.01564439621961945,
+           -0.03287555871959342,
+           -0.05151884074455709,
+           -0.07134657604801083,
+           -0.09208445802681911,
+           -0.11341926037397883,
+           -0.13500769520603795,
+           -0.15648617449455368,
+           -0.1774812164770758,
+           -0.1976202211611119,
+           -0.21654232851752275,
+           -0.23390906976387182,
+           -0.2494145263553873,
+           -0.26279472283683447,
+           -0.27383599828390254,
+           -0.28238212622140585,
+           -0.28833998402523225,
+           -0.29168360912233693,
+           -0.2924565198934687,
+           -0.29077222304293926,
+           -0.2868128752310514,
+           -0.28082611381376343,
+           -0.2731201184190812,
+           -0.26405701063065823,
+           -0.2540447420975377,
+           -0.24352766085628363,
+           -0.23297598053656413,
+           -0.2228744065345523,
+           -0.21371019642596437,
+           -0.20596094825147362,
+           -0.20008241940982222,
+           -0.19649668048622748,
+           -0.19558090236011805,
+           -0.1976570614995697,
+           -0.20298282776841178,
+           -0.21174387183230325,
+           -0.22404779600503666,
+           -0.23991985392920323,
+           -0.2593005817701571,
+           -0.28204541766073155,
+           -0.307926338090247,
+           -0.3366354909632439,
+           -0.3677907563646717,
+           -0.40094311885790473,
+           -0.43558569057507235,
+           -0.4711641835375704,
+           -0.5070885935801056,
+           -0.5427458278404533,
+           -0.5775129837779589,
+           -0.6107709706989305,
+           -0.6419181552268551,
+           -0.6703837103084199,
+           -0.6956403532519234,
+           -0.7172161718225798,
+           -0.7347052582513783,
+           -0.747776898653458,
+           -0.7561830991336495,
+           -0.7597642689651801,
+           -0.7584529247156616,
+           -0.7522753260076296,
+           -0.7413510026024113,
+           -0.7258901824952323,
+           -0.7061891804908292,
+           -0.6826238550820897,
+           -0.655641287204081,
+           -0.6257498764706753,
+           -0.5935080878005158,
+           -0.5595121129990456,
+           -0.5243827371182186,
+           -0.48875171765661957,
+           -0.4532479954539204,
+           -0.4184840592211644,
+           -0.38504278096773986,
+           -0.3534650272627891,
+           -0.32423833161611,
+           -0.2977868867735952,
+           -0.27446308305410133,
+           -0.25454078081846604,
+           -0.2382104626974201,
+           -0.22557636536144593,
+           -0.21665564252098662,
+           -0.2113795616824978,
+           -0.20959668816110502,
+           -0.21107796216512195,
+           -0.21552352958701557,
+           -0.22257114556123092,
+           -0.2318059328920527,
+           -0.24277124600887898,
+           -0.2549803659283731,
+           -0.26792873339299983,
+           -0.2811064163423394,
+           -0.2940105044047801,
+           -0.3061571272328653,
+           -0.3170928051172843,
+           -0.32640485908888706,
+           -0.3337306331646224,
+           -0.3387653128570836,
+           -0.34126816074525057,
+           -0.34106703086530754,
+           -0.3380610678895874,
+           -0.3322215434048215,
+           -0.3235908289132298,
+           -0.31227955227502524,
+           -0.2984620300102182,
+           -0.2823701110397809,
+           -0.264285606995775,
+           -0.2445315191836645,
+           -0.22346230177149146,
+           -0.20145342408181224,
+           -0.17889051140169726,
+           -0.1561583531025353,
+           -0.1336300688540452,
+           -0.11165671829069981,
+           -0.09055762679500741,
+           -0.07061168043449387,
+           -0.05204981703560329,
+           -0.03504890856686592,
+           -0.01972719324881087,
+           -0.006141375046193208,
+           0.005714535533530956,
+           0.01590861100128566,
+           0.024568644762748077,
+           0.03187810108049183,
+           0.03807048506877522,
+           0.04342228208397327,
+           0.048244653476999015,
+           0.05287410850796829,
+           0.05766239945097905,
+           0.06296590784218363,
+           0.06913480390968843,
+           0.07650226810343898,
+           0.08537406313253339,
+           0.09601873701763924,
+           0.10865872256461426,
+           0.12346257673076841,
+           0.14053857512847912,
+           0.15992984309208572,
+           0.18161116616473702,
+           0.2054875805043742,
+           0.2313947986212627,
+           0.2591014791728147,
+           0.28831330242629327,
+           0.3186787666409537,
+           0.3497965761860833,
+           0.3812244508223921,
+           0.41248914827959743,
+           0.44309746001087114,
+           0.47254791361954046,
+           0.500342895614523,
+           0.526000895376427,
+           0.5490685658490465,
+           0.5691322986703607,
+           0.5858290211944779,
+           0.598855939915072,
+           0.6079789787831026,
+           0.6130396912455776,
+           0.6139604607874435,
+           0.6107478454641196,
+           0.603493966376669,
+           0.5923758871790623,
+           0.5776529803627357,
+           0.5596623250431181,
+           0.5388122290709566,
+           0.5155740143224389,
+           0.4904722468493424,
+           0.46407363213342184,
+           0.4369748290313208,
+           0.40978946328706733,
+           0.38313464204631614,
+           0.35761728411187244,
+           0.3338205863931974,
+           0.3122909449690702,
+           0.29352563943779497,
+           0.27796157199846316,
+           0.26596532839826,
+           0.2578247970775941,
+           0.25374254628936577,
+           0.25383111754501225,
+           0.2581103484519582,
+           0.2665067899538578,
+           0.27885523333385576,
+           0.29490231229877223,
+           0.3143120962452213,
+           0.3366735436138099,
+           0.36150964021155246,
+           0.3882880075948471,
+           0.4164327320209866,
+           0.4453371359326921,
+           0.47437719212678764,
+           0.5029252661988256,
+           0.5303638658964644,
+           0.5560990768148782,
+           0.5795733723971731,
+           0.6002775022414683,
+           0.6177611858601736,
+           0.631642368708548,
+           0.6416148327618845,
+           0.6474539942958871,
+           0.6490207658154349,
+           0.6462634061915195,
+           0.6392173318451139,
+           0.6280029110619371,
+           0.6128213120259869,
+           0.5939485217353819,
+           0.5717276964742661,
+           0.5465600439000526,
+           0.5188944711106487,
+           0.4892162614534926,
+           0.4580350646470035,
+           0.42587249948914746,
+           0.39324967568835223,
+           0.360674941014331,
+           0.32863215206518315,
+           0.2975697517037298,
+           0.2678909140337838,
+           0.23994498924056287,
+           0.21402044643980353,
+           0.19033947373724208,
+           0.16905435198009347,
+           0.15024567326297242,
+           0.1339224282755156,
+           0.12002393922685609,
+           0.10842356853936261,
+           0.09893408893422707,
+           0.09131455904645921,
+           0.085278511339224,
+           0.08050322676489739,
+           0.0766398441423736,
+           0.07332403223884061,
+           0.0701869395473483,
+           0.06686613105094902,
+           0.06301622298832793,
+           0.05831893572633496,
+           0.05249230105842014,
+           0.04529878316251647,
+           0.03655210147727289,
+           0.026122578148348688,
+           0.013940871578885045,
+           1.3795209405752768e-16
+          ],
+          [
+           0,
+           -0.017020284662137737,
+           -0.035630321304380486,
+           -0.05561776157230751,
+           -0.07671806099932178,
+           -0.09862197899210992,
+           -0.12098436987428275,
+           -0.1434340320098636,
+           -0.16558435392313897,
+           -0.18704447489312015,
+           -0.2074306632800015,
+           -0.22637760920661398,
+           -0.24354932934824886,
+           -0.2586493904622973,
+           -0.27143017470278996,
+           -0.281700933312111,
+           -0.2893344053809441,
+           -0.2942718142703542,
+           -0.2965260951023471,
+           -0.29618325142802926,
+           -0.2934017866570423,
+           -0.28841020488817304,
+           -0.28150262518703617,
+           -0.273032601869508,
+           -0.2634052897461388,
+           -0.25306813639059084,
+           -0.2425003222216245,
+           -0.23220120254792703,
+           -0.22267803286473295,
+           -0.21443327891080796,
+           -0.20795182576506882,
+           -0.203688405239654,
+           -0.20205555785966697,
+           -0.20341243485565214,
+           -0.20805472707621103,
+           -0.21620598198897595,
+           -0.2280105375927144,
+           -0.24352826389131305,
+           -0.2627312595077043,
+           -0.2855026040919347,
+           -0.3116372175496524,
+           -0.34084482600188093,
+           -0.3727549830399521,
+           -0.4069240445251552,
+           -0.44284394714232106,
+           -0.47995259633782394,
+           -0.5176456292599618,
+           -0.5552892838672139,
+           -0.5922340773365751,
+           -0.6278289759920465,
+           -0.6614357257108372,
+           -0.692443006492777,
+           -0.720280077741928,
+           -0.7444295917539359,
+           -0.7644392716751872,
+           -0.7799321763550748,
+           -0.7906153074235632,
+           -0.7962863527997344,
+           -0.7968384047330425,
+           -0.7922625383339331,
+           -0.7826481872029392,
+           -0.7681813049869367,
+           -0.749140354208663,
+           -0.7258902152540165,
+           -0.6988741577079192,
+           -0.6686040621052289,
+           -0.6356491214938109,
+           -0.6006232879895764,
+           -0.5641717588711876,
+           -0.5269568190058027,
+           -0.4896433709821149,
+           -0.45288449090617605,
+           -0.4173073462388604,
+           -0.38349980237051334,
+           -0.35199802708675343,
+           -0.3232753771195544,
+           -0.29773281922166955,
+           -0.27569110043752826,
+           -0.2573848394039878,
+           -0.24295866365680407,
+           -0.2324654681975481,
+           -0.22586681921348614,
+           -0.22303547510048558,
+           -0.2237599460841973,
+           -0.227750965011296,
+           -0.2346496964792283,
+           -0.2440374704944017,
+           -0.2554467912883487,
+           -0.26837334263666834,
+           -0.2822886887173938,
+           -0.29665335474068394,
+           -0.3109299646209103,
+           -0.3245961139906046,
+           -0.3371566658210053,
+           -0.3481551725668096,
+           -0.35718415265422265,
+           -0.3638939796635305,
+           -0.3680001789389604,
+           -0.3692889676649242,
+           -0.3676209196335921,
+           -0.36293268385492855,
+           -0.35523673562163277,
+           -0.3446191883972917,
+           -0.3312357437009477,
+           -0.3153059027962314,
+           -0.2971056072957612,
+           -0.2769585146849216,
+           -0.2552261482889155,
+           -0.23229718852504427,
+           -0.20857619272706682,
+           -0.18447204390233404,
+           -0.16038643417281367,
+           -0.13670268623907922,
+           -0.11377520606886214,
+           -0.09191984241980661,
+           -0.07140540421760651,
+           -0.0524465558591762,
+           -0.03519827398870778,
+           -0.01975200813472996,
+           -0.006133642846981377,
+           0.005696688228912398,
+           0.01584293435398856,
+           0.024469652265689847,
+           0.031796817070966966,
+           0.0380930580764295,
+           0.043667499478778106,
+           0.04886042255030347,
+           0.054032997133383304,
+           0.05955635510932111,
+           0.06580029639420586,
+           0.07312192847652031,
+           0.0818545432734022,
+           0.09229703006390182,
+           0.10470411057322757,
+           0.11927766223983406,
+           0.13615936879081061,
+           0.1554249041471939,
+           0.17707981720308885,
+           0.20105724213073195,
+           0.22721751263009773,
+           0.25534971012424523,
+           0.2851751265152419,
+           0.3163525730013091,
+           0.3484854188509338,
+           0.3811301991353299,
+           0.4138065893731657,
+           0.4460085088830233,
+           0.4772160842918917,
+           0.5069081808914081,
+           0.5345751929836434,
+           0.5597317754532223,
+           0.5819291977906426,
+           0.6007670087254227,
+           0.61590371436175,
+           0.6270661949042513,
+           0.6340576141914904,
+           0.6367636116208419,
+           0.6351566067949371,
+           0.6292980923562917,
+           0.6193388389012211,
+           0.6055169863912637,
+           0.5881540478699733,
+           0.5676489022811617,
+           0.5444699025146773,
+           0.5191452712595311,
+           0.4922519996717819,
+           0.4644035012136265,
+           0.43623630436132793,
+           0.40839609242973895,
+           0.3815234159033977,
+           0.356239411962114,
+           0.333131867099263,
+           0.312741951807844,
+           0.29555194140722,
+           0.28197421455252136,
+           0.2723417913466427,
+           0.26690063697405375,
+           0.26580391526525066,
+           0.2691083305857631,
+           0.2767726470399743,
+           0.2886584223873029,
+           0.3045329415401574,
+           0.3240742823265654,
+           0.34687839562431194,
+           0.37246803423750335,
+           0.4003033211505453,
+           0.4297937091207683,
+           0.46031105089684715,
+           0.49120347346654686,
+           0.5218097312679654,
+           0.5514737026853381,
+           0.5795586916431675,
+           0.6054612017612644,
+           0.6286238641892117,
+           0.6485472215564212,
+           0.6648000989206124,
+           0.6770283274663531,
+           0.6849616271329192,
+           0.6884184993384213,
+           0.6873090294059232,
+           0.6816355489951171,
+           0.6714911605544445,
+           0.6570561772651019,
+           0.6385925818904634,
+           0.6164366551520649,
+           0.5909899675761493,
+           0.5627089671406528,
+           0.5320934275731306,
+           0.49967404802381415,
+           0.465999513449137,
+           0.43162333595448993,
+           0.39709080031723604,
+           0.3629263318953654,
+           0.32962159227509785,
+           0.2976245876673309,
+           0.26733004775829644,
+           0.23907129915604727,
+           0.21311381860686504,
+           0.18965060777256934,
+           0.16879948465666195,
+           0.15060233791998898,
+           0.13502634056208943,
+           0.12196707000935518,
+           0.11125343378181912,
+           0.10265425480112099,
+           0.09588632917618753,
+           0.09062373298408423,
+           0.08650812405053347,
+           0.08315976077977738,
+           0.08018894327330979,
+           0.07720757271786248,
+           0.07384052353128505,
+           0.069736529051637,
+           0.06457829546537458,
+           0.05809157982931355,
+           0.05005299590065647,
+           0.04029634533442234,
+           0.02871731077278408,
+           0.015276390442690893,
+           1.5063995523025282e-16
+          ],
+          [
+           0,
+           -0.018422838601824258,
+           -0.03841668785720666,
+           -0.05973057440279993,
+           -0.08206295490209783,
+           -0.10507034546581318,
+           -0.12837716880915562,
+           -0.15158655755614087,
+           -0.17429182660770526,
+           -0.19608830933506594,
+           -0.21658524201028057,
+           -0.23541737861382667,
+           -0.2522560240325134,
+           -0.26681918754339046,
+           -0.2788805800319918,
+           -0.28827720708431004,
+           -0.29491534520913754,
+           -0.29877472911608927,
+           -0.2999108231791563,
+           -0.298455098824938,
+           -0.2946132903803042,
+           -0.2886616536207174,
+           -0.28094130257723127,
+           -0.271850749794024,
+           -0.2618368219256407,
+           -0.2513841651413206,
+           -0.24100359218092945,
+           -0.23121955412891013,
+           -0.22255704423689657,
+           -0.2155282578017145,
+           -0.21061934075092206,
+           -0.20827755995951489,
+           -0.2088992203812579,
+           -0.21281863799546055,
+           -0.2202984537169746,
+           -0.23152154235993064,
+           -0.2465847332305642,
+           -0.2654945158598174,
+           -0.2881648568202776,
+           -0.31441720266638595,
+           -0.34398269103894313,
+           -0.3765065381864682,
+           -0.41155451790090264,
+           -0.448621395457198,
+           -0.4871411318559133,
+           -0.5264986296915659,
+           -0.566042753398931,
+           -0.6051003244258748,
+           -0.64299076685027,
+           -0.6790410617306639,
+           -0.7126006594953684,
+           -0.7430559991699233,
+           -0.769844291248348,
+           -0.7924662373494586,
+           -0.8104973840820118,
+           -0.8235978401916603,
+           -0.8315201243180103,
+           -0.8341149546277409,
+           -0.8313348401462671,
+           -0.8232353856081812,
+           -0.809974275823175,
+           -0.791807960592763,
+           -0.7690861157757632,
+           -0.7422440088603027,
+           -0.7117929470742218,
+           -0.6783090314467201,
+           -0.642420480219764,
+           -0.604793818628202,
+           -0.5661192585088555,
+           -0.5270956098235124,
+           -0.488415076542493,
+           -0.45074829119113125,
+           -0.41472993567605987,
+           -0.38094528095600966,
+           -0.34991795508209445,
+           -0.3220992186797329,
+           -0.2978589898340754,
+           -0.27747881749081493,
+           -0.2611469549521566,
+           -0.2489556340040397,
+           -0.24090058691089253,
+           -0.2368828092665693,
+           -0.23671250282444242,
+           -0.24011508526361527,
+           -0.2467391046554661,
+           -0.25616585137309206,
+           -0.2679204204284384,
+           -0.28148394368867613,
+           -0.296306684919949,
+           -0.31182167176282155,
+           -0.3274585279990005,
+           -0.34265716706132837,
+           -0.3568810137000585,
+           -0.3696294348721964,
+           -0.3804490828887885,
+           -0.38894388306627364,
+           -0.39478343383259246,
+           -0.39770962852763203,
+           -0.3975413539647438,
+           -0.39417717002928476,
+           -0.38759592594331765,
+           -0.3778553210342258,
+           -0.36508846960192676,
+           -0.349498579491459,
+           -0.3313519009982518,
+           -0.31096914559270644,
+           -0.2887156115856938,
+           -0.2649902853365818,
+           -0.24021421115584016,
+           -0.21481844007519799,
+           -0.1892318767397949,
+           -0.1638693446083728,
+           -0.13912018242384822,
+           -0.11533766973684775,
+           -0.09282955652785685,
+           -0.07184994226777996,
+           -0.05259271384491662,
+           -0.035186710586762475,
+           -0.01969273916823396,
+           -0.006102512680224785,
+           0.00566046223293889,
+           0.01573807719238211,
+           0.024332970094488926,
+           0.03170215475664159,
+           0.038149102631557234,
+           0.04401448764510501,
+           0.049665840436452384,
+           0.055486387208095955,
+           0.06186337028805555,
+           0.0691761618053787,
+           0.07778448821230119,
+           0.08801708158147754,
+           0.10016106369898624,
+           0.1144523512017105,
+           0.13106734480777116,
+           0.15011613368497106,
+           0.1716374079906337,
+           0.1955952295448957,
+           0.22187776354516622,
+           0.25029802437051235,
+           0.28059663711202054,
+           0.3124465647908218,
+           0.34545970059031045,
+           0.37919517611067793,
+           0.41316919187404344,
+           0.4468661362030543,
+           0.4797507241861866,
+           0.5112808606100023,
+           0.5409209102013259,
+           0.5681550458185646,
+           0.5925003407054841,
+           0.6135192747135243,
+           0.6308313364442806,
+           0.6441234232907043,
+           0.6531587688933259,
+           0.6577841619180984,
+           0.6579352604754136,
+           0.6536398519541848,
+           0.6450189574322794,
+           0.6322857319365497,
+           0.6157421653840306,
+           0.595773642723439,
+           0.5728414742901272,
+           0.5474735573919162,
+           0.5202533764205445,
+           0.49180759018613707,
+           0.4627924906702129,
+           0.43387964610061497,
+           0.40574106244858643,
+           0.37903421059743403,
+           0.35438727119408436,
+           0.3323849454353192,
+           0.31355516783471143,
+           0.2983570366467444,
+           0.2871702495749401,
+           0.280286297332977,
+           0.27790162640678057,
+           0.2801129359780045,
+           0.2869147235392292,
+           0.2981991404823991,
+           0.31375816416803926,
+           0.33328803801509793,
+           0.35639587732642897,
+           0.3826082871918222,
+           0.4113817911382571,
+           0.44211482638381255,
+           0.4741610246368994,
+           0.5068434672607112,
+           0.5394695810220203,
+           0.5713463261072149,
+           0.6017953219624705,
+           0.6301675589389903,
+           0.6558573546279329,
+           0.6783152328758006,
+           0.697059430301099,
+           0.711685769019948,
+           0.7218756743927317,
+           0.7274021619350376,
+           0.7281336669766753,
+           0.7240356429854288,
+           0.7151699084118697,
+           0.7016917761346354,
+           0.6838450527643752,
+           0.6619550458993331,
+           0.6364197646767988,
+           0.6076995414834949,
+           0.5763053394445803,
+           0.5427860404195969,
+           0.5077150309746027,
+           0.4716764186368097,
+           0.4352512173312352,
+           0.39900383911337883,
+           0.3634692192198018,
+           0.3291408833381841,
+           0.29646024032596496,
+           0.2658073510447282,
+           0.23749338535823455,
+           0.21175493564577977,
+           0.18875030751420976,
+           0.16855785795225178,
+           0.15117639922698978,
+           0.13652763467647286,
+           0.12446054150855344,
+           0.11475756704813021,
+           0.10714245979496723,
+           0.10128951628205021,
+           0.09683399005996655,
+           0.09338338103137869,
+           0.09052930251066611,
+           0.08785961029375192,
+           0.08497047300313802,
+           0.08147806613146855,
+           0.07702958344631629,
+           0.07131327843928055,
+           0.06406727480880185,
+           0.055086917880533375,
+           0.04423047754848258,
+           0.03142305677696072,
+           0.016658606830725214,
+           1.636727741140378e-16
+          ],
+          [
+           0,
+           -0.019842716107258795,
+           -0.041214914707715586,
+           -0.0638265870508466,
+           -0.08733960828749228,
+           -0.11137748858151005,
+           -0.13553624546805698,
+           -0.15939610802717472,
+           -0.18253374114694362,
+           -0.20453466383115837,
+           -0.22500552953331154,
+           -0.243585939032728,
+           -0.2599594673568881,
+           -0.27386360543030835,
+           -0.28509834402240747,
+           -0.29353316150744335,
+           -0.2991122170935963,
+           -0.30185759652316974,
+           -0.30187050665707393,
+           -0.2993303675957406,
+           -0.2944918047438015,
+           -0.2876795971453931,
+           -0.2792816911423794,
+           -0.2697404386080613,
+           -0.2595422654137161,
+           -0.24920601721669322,
+           -0.2392702650609043,
+           -0.2302798817460966,
+           -0.2227722207152803,
+           -0.21726324178415002,
+           -0.21423393205013372,
+           -0.2141173656423879,
+           -0.21728673269438806,
+           -0.22404464633892163,
+           -0.2346140071496477,
+           -0.24913066798727587,
+           -0.26763809953285633,
+           -0.2900842089428487,
+           -0.316320412208348,
+           -0.34610300621374185,
+           -0.37909683050833043,
+           -0.41488115280567217,
+           -0.452957657590525,
+           -0.49276036529246,
+           -0.5336672615641507,
+           -0.5750133734709341,
+           -0.6161049929201392,
+           -0.6562347183459047,
+           -0.6946969642545469,
+           -0.7308035752706671,
+           -0.7638991771419656,
+           -0.793375901882253,
+           -0.8186871377604966,
+           -0.8393599768647617,
+           -0.8550060629614062,
+           -0.8653305796127553,
+           -0.8701391621135262,
+           -0.8693425657033395,
+           -0.8629589755249859,
+           -0.8511138996391698,
+           -0.8340376437196882,
+           -0.812060423445089,
+           -0.7856052266780957,
+           -0.7551785909185615,
+           -0.7213595109310468,
+           -0.6847867356831842,
+           -0.6461447517116635,
+           -0.6061487808381051,
+           -0.5655291430422339,
+           -0.5250153497141441,
+           -0.48532029810765426,
+           -0.4471249344761437,
+           -0.4110637411826057,
+           -0.37771138234582646,
+           -0.34757081383219346,
+           -0.32106312734137055,
+           -0.29851935585603345,
+           -0.2801744198792099,
+           -0.26616334184621626,
+           -0.25651980115114087,
+           -0.25117704571965516,
+           -0.2499711193756727,
+           -0.25264630877639727,
+           -0.2588626607834141,
+           -0.26820537208600914,
+           -0.28019580888865314,
+           -0.29430387658273216,
+           -0.3099614284553457,
+           -0.3265763793825014,
+           -0.3435471756541072,
+           -0.36027726592143944,
+           -0.3761892208673587,
+           -0.3907381604814995,
+           -0.40342416746854737,
+           -0.41380339281254325,
+           -0.42149759415566146,
+           -0.4262018885420533,
+           -0.4276905471890576,
+           -0.4258207101146204,
+           -0.42053395140852384,
+           -0.4118556803564297,
+           -0.3998924181469426,
+           -0.3848270431504574,
+           -0.36691214842635805,
+           -0.3464617019316666,
+           -0.3238412417075963,
+           -0.2994568740764811,
+           -0.27374337170918356,
+           -0.2471516896164942,
+           -0.22013623016365463,
+           -0.19314219279667802,
+           -0.1665933402066984,
+           -0.1408805002630978,
+           -0.11635110254809847,
+           -0.09330002025845444,
+           -0.07196195332692967,
+           -0.052505547751993266,
+           -0.03502940035180944,
+           -0.019560048644147964,
+           -0.006051993556485284,
+           0.005610250488717317,
+           0.015608136540169683,
+           0.024183207001588734,
+           0.03162951490166494,
+           0.03828454754968078,
+           0.04451889490507291,
+           0.050724938115492474,
+           0.05730485975754528,
+           0.0646582956804905,
+           0.07316995853286655,
+           0.08319756477840182,
+           0.09506039022645835,
+           0.10902876397368406,
+           0.12531478754787465,
+           0.14406453553378162,
+           0.16535195680234563,
+           0.1891746525862837,
+           0.21545166011798095,
+           0.24402331956053155,
+           0.2746532487985437,
+           0.30703239664786597,
+           0.3407850915521856,
+           0.375476951208325,
+           0.4106244701059562,
+           0.44570605790923284,
+           0.48017426306794087,
+           0.5134688840089313,
+           0.5450306455489157,
+           0.5743151014304436,
+           0.6008064155592322,
+           0.6240306748497851,
+           0.6435683955887658,
+           0.6590659027073437,
+           0.6702452869087356,
+           0.6769126776177234,
+           0.6789646094103917,
+           0.6763923049826911,
+           0.669283747719708,
+           0.6578234703113588,
+           0.6422900413154469,
+           0.6230512877327634,
+           0.6005573471474248,
+           0.5753316964292378,
+           0.5479603540714749,
+           0.5190794987054124,
+           0.4893617860621129,
+           0.45950167965100525,
+           0.4302001358673061,
+           0.40214900148357247,
+           0.37601549008324836,
+           0.35242710372616737,
+           0.331957356985503,
+           0.31511264266875344,
+           0.3023205524513013,
+           0.2939199319327957,
+           0.29015290908431923,
+           0.29115908866694085,
+           0.29697205409265154,
+           0.3075182636062972,
+           0.32261837091757145,
+           0.341990942884611,
+           0.36525848994407145,
+           0.3919556700808057,
+           0.42153947556864274,
+           0.453401164746053,
+           0.4868796598575347,
+           0.521276097494216,
+           0.5558691912407764,
+           0.5899310474301915,
+           0.6227430648712616,
+           0.6536115482820841,
+           0.6818826729533289,
+           0.7069564546769339,
+           0.7282994037945911,
+           0.7454555747283118,
+           0.7580557617471063,
+           0.7658246370262238,
+           0.7685856771515782,
+           0.766263777879165,
+           0.758885512858728,
+           0.7465770488015357,
+           0.7295597858231415,
+           0.7081438460481948,
+           0.6827195846995788,
+           0.6537473445639503,
+           0.6217457157981691,
+           0.5872785975244703,
+           0.5509413847292454,
+           0.5133466229885288,
+           0.47510948405081116,
+           0.4368334170832922,
+           0.3990963234169636,
+           0.3624375871103307,
+           0.32734627000471106,
+           0.294250748779031,
+           0.2635100336277214,
+           0.23540696454537782,
+           0.2101434329103871,
+           0.1878377243345012,
+           0.1685240248863761,
+           0.15215407815473458,
+           0.13860092655819864,
+           0.1276646181832256,
+           0.11907971153742726,
+           0.11252436615784611,
+           0.1076307681139515,
+           0.10399660705374549,
+           0.10119729635440614,
+           0.09879861076787184,
+           0.09636940710891104,
+           0.09349409322121809,
+           0.08978451866433877,
+           0.08489097706534478,
+           0.07851203444071052,
+           0.07040292938550811,
+           0.06038232903736794,
+           0.048337268179739344,
+           0.03422614664471848,
+           0.018079711093681786,
+           1.7696995801236642e-16
+          ],
+          [
+           0,
+           -0.02126997445721784,
+           -0.04400434144914805,
+           -0.06787418314933377,
+           -0.09250576140164318,
+           -0.11749136599339048,
+           -0.14240116452440194,
+           -0.16679573782088614,
+           -0.19023896632348736,
+           -0.21231092292617976,
+           -0.23262042661749036,
+           -0.25081691901651604,
+           -0.2666013423186278,
+           -0.27973572186617945,
+           -0.290051188925683,
+           -0.2974542184788897,
+           -0.3019309019415731,
+           -0.3035491245818698,
+           -0.30245857077005434,
+           -0.2988885357139527,
+           -0.29314357862266094,
+           -0.28559710787805725,
+           -0.27668304237477853,
+           -0.2668857433597671,
+           -0.2567284565899377,
+           -0.24676054427336702,
+           -0.23754381905188726,
+           -0.22963831737650284,
+           -0.2235878663676451,
+           -0.21990580619309577,
+           -0.2190612289091529,
+           -0.22146608459160602,
+           -0.22746348665366892,
+           -0.23731752094937927,
+           -0.25120482824352564,
+           -0.2692081877367007,
+           -0.2913122815830911,
+           -0.31740176789332286,
+           -0.3472617338583746,
+           -0.3805805427339312,
+           -0.4169550299118125,
+           -0.45589794561886077,
+           -0.49684748634906073,
+           -0.5391787053243355,
+           -0.5822165453789995,
+           -0.6252501968397305,
+           -0.6675484492463677,
+           -0.7083756799755926,
+           -0.747008105641847,
+           -0.7827499139995993,
+           -0.8149488951786407,
+           -0.8430112014422974,
+           -0.8664148840332192,
+           -0.8847218836063245,
+           -0.897588186577047,
+           -0.904771902573696,
+           -0.9061390670410366,
+           -0.9016670267153192,
+           -0.8914453228773359,
+           -0.8756740466009098,
+           -0.8546597002080087,
+           -0.8288086583593783,
+           -0.798618379210694,
+           -0.7646665694620884,
+           -0.7275985556248812,
+           -0.6881131562447337,
+           -0.6469473851255538,
+           -0.6048603429377878,
+           -0.562616673307935,
+           -0.5209699691246324,
+           -0.48064651513376916,
+           -0.44232974393265695,
+           -0.40664576444029404,
+           -0.37415029526859456,
+           -0.3453173008100135,
+           -0.32052958614656,
+           -0.30007155910311306,
+           -0.28412431509106156,
+           -0.2727631441121378,
+           -0.26595750079847746,
+           -0.26357341908780024,
+           -0.26537829452296274,
+           -0.2710479006552512,
+           -0.28017545299848157,
+           -0.2922824857160654,
+           -0.30683126389555315,
+           -0.3232384188961398,
+           -0.34088946669178044,
+           -0.35915385002939004,
+           -0.3774001350210618,
+           -0.3950109917136816,
+           -0.4113975962248573,
+           -0.42601310897133027,
+           -0.4383649088959487,
+           -0.4480252967646752,
+           -0.4546404207073777,
+           -0.4579372231963468,
+           -0.4577282594312924,
+           -0.4539142913498902,
+           -0.44648461784644117,
+           -0.4355151588457341,
+           -0.42116436721843636,
+           -0.40366709673315454,
+           -0.3833266049695596,
+           -0.36050491610738555,
+           -0.3356118086191995,
+           -0.3090927261413728,
+           -0.28141593536200005,
+           -0.25305927202488004,
+           -0.22449682469226262,
+           -0.19618590554243484,
+           -0.16855464823149172,
+           -0.14199055497484953,
+           -0.11683028897243361,
+           -0.09335097478558509,
+           -0.07176322913434183,
+           -0.052206098847398665,
+           -0.03474403252983793,
+           -0.019365959192429897,
+           -0.005986491966028445,
+           0.005550780495074562,
+           0.015468006827030754,
+           0.024045934011272897,
+           0.03161510909659656,
+           0.03854565747383215,
+           0.04523591099997345,
+           0.05210018968084379,
+           0.05955606325869531,
+           0.06801143333356674,
+           0.07785178220500588,
+           0.08942793130374166,
+           0.1030446399643088,
+           0.1189503546644818,
+           0.1373283902351168,
+           0.158289788635898,
+           0.18186805859403002,
+           0.2080159517714523,
+           0.2366043793545961,
+           0.26742351834785816,
+           0.30018610076997404,
+           0.33453282281273794,
+           0.3700397562394189,
+           0.4062275922595182,
+           0.4425725001351551,
+           0.47851834007099975,
+           0.5134899336034323,
+           0.5469070656677193,
+           0.578198871535839,
+           0.6068182494347875,
+           0.6322559362139027,
+           0.6540538890467689,
+           0.6718176307192458,
+           0.6852272392379177,
+           0.6940466937453088,
+           0.6981313273001819,
+           0.6974331820400858,
+           0.692004112495353,
+           0.6819965371413841,
+           0.6676617953282975,
+           0.6493461251118663,
+           0.6274843357895306,
+           0.6025913056815694,
+           0.5752514894871633,
+           0.5461066690547255,
+           0.5158422254052151,
+           0.485172247239484,
+           0.4548238210098374,
+           0.4255208691905615,
+           0.39796791609292775,
+           0.3728341641051812,
+           0.35073825749023296,
+           0.33223409596422054,
+           0.31779803655403954,
+           0.3078177902544424,
+           0.3025832805420113,
+           0.30227968480481887,
+           0.3069828283251731,
+           0.3166570448544609,
+           0.3311555593930809,
+           0.35022338895429145,
+           0.3735026973032724,
+           0.4005404813760609,
+           0.43079841171521266,
+           0.4636645981568083,
+           0.4984670064094436,
+           0.5344882121874085,
+           0.5709811481432038,
+           0.6071854757489099,
+           0.6423442000579832,
+           0.675720140277375,
+           0.7066118734072481,
+           0.7343687817464057,
+           0.7584048574741652,
+           0.7782109482458741,
+           0.7933651660178717,
+           0.8035412262027524,
+           0.8085145346407636,
+           0.8081658945180439,
+           0.8024827629245317,
+           0.7915580458111996,
+           0.7755864792310019,
+           0.7548587024843494,
+           0.729753183728772,
+           0.70072620941571,
+           0.6683001943514958,
+           0.6330506081454691,
+           0.5955918453686069,
+           0.5565623901481199,
+           0.5166096406172714,
+           0.47637476429172954,
+           0.43647795194421496,
+           0.397504425015551,
+           0.35999153037222154,
+           0.32441722685364777,
+           0.2911902313014339,
+           0.2606420485647107,
+           0.23302106142509454,
+           0.20848880370644463,
+           0.18711848435368247,
+           0.16889577337288394,
+           0.15372180364526009,
+           0.14141828718088423,
+           0.1317345917453271,
+           0.12435657528209025,
+           0.11891693236851776,
+           0.1150067701498599,
+           0.11218810170058306,
+           0.11000692328485133,
+           0.10800652904815651,
+           0.10574071257344501,
+           0.10278650955965558,
+           0.09875614948627663,
+           0.09330790615208893,
+           0.08615556684643126,
+           0.0770762768575617,
+           0.0659165590982903,
+           0.05259635673429924,
+           0.03711099861013051,
+           0.019531041661631398,
+           1.9044408733663681e-16
+          ],
+          [
+           0,
+           -0.02269418781509465,
+           -0.04676364248923884,
+           -0.0718412171638009,
+           -0.0975190852433307,
+           -0.12336064426840715,
+           -0.1489132789047544,
+           -0.17372164204967805,
+           -0.19734109886868917,
+           -0.21935097348894722,
+           -0.23936724222964603,
+           -0.2570543305477998,
+           -0.2721356929957583,
+           -0.28440288587652046,
+           -0.2937228801880443,
+           -0.3000434069217836,
+           -0.30339617671072433,
+           -0.3038978699566137,
+           -0.301748850545749,
+           -0.2972296146549261,
+           -0.2906950444833988,
+           -0.2825665935513745,
+           -0.27332258404478904,
+           -0.26348684619560875,
+           -0.2536159736083552,
+           -0.2442855056558411,
+           -0.23607537761490074,
+           -0.2295550003303197,
+           -0.2252683433254467,
+           -0.22371939808750402,
+           -0.22535839164260432,
+           -0.23056910463289337,
+           -0.23965762328073686,
+           -0.2528428214602105,
+           -0.27024882839080133,
+           -0.29189969020797163,
+           -0.31771638100091215,
+           -0.3475162621270357,
+           -0.3810150291081354,
+           -0.41783112464789607,
+           -0.45749253578226323,
+           -0.49944583437812107,
+           -0.5430672645871547,
+           -0.5876756298204664,
+           -0.6325466866049104,
+           -0.6769287144426814,
+           -0.7200589004796211,
+           -0.761180156160278,
+           -0.7995579706611889,
+           -0.8344969030740397,
+           -0.865356322148411,
+           -0.8915650187532359,
+           -0.9126343416969792,
+           -0.9281695415535417,
+           -0.9378790488592371,
+           -0.9415814614704425,
+           -0.9392100698310424,
+           -0.9308148070859825,
+           -0.9165615719798385,
+           -0.8967289348150332,
+           -0.8717022988974296,
+           -0.8419656503553251,
+           -0.8080910865103436,
+           -0.7707263657112624,
+           -0.730580768431901,
+           -0.6884095993421967,
+           -0.6449976920189211,
+           -0.6011423011953695,
+           -0.5576357813976786,
+           -0.515248455146967,
+           -0.47471206852403824,
+           -0.43670421693834777,
+           -0.40183409979043333,
+           -0.3706299299675003,
+           -0.34352828357569165,
+           -0.32086562799007917,
+           -0.30287221336014347,
+           -0.2896684554462625,
+           -0.2812638774876745,
+           -0.27755861718980224,
+           -0.27834744337738454,
+           -0.2833261668936436,
+           -0.292100273397773,
+           -0.3041955532089151,
+           -0.31907045653867866,
+           -0.3361298624775474,
+           -0.35473991791418724,
+           -0.37424357893749716,
+           -0.3939764727536107,
+           -0.4132826930719086,
+           -0.4315301463697833,
+           -0.44812508029370035,
+           -0.4625254483203835,
+           -0.47425279609065407,
+           -0.4829023937361697,
+           -0.4881513840557143,
+           -0.4897647674100353,
+           -0.4875990994067277,
+           -0.48160383545203644,
+           -0.4718203156011252,
+           -0.45837844235822744,
+           -0.44149116168580016,
+           -0.4214469120433991,
+           -0.39860025643746194,
+           -0.37336095698035027,
+           -0.34618178923204823,
+           -0.3175454237028431,
+           -0.2879507235956372,
+           -0.2578988206396868,
+           -0.22787933441524932,
+           -0.19835709482454342,
+           -0.16975971249519486,
+           -0.1424663183034339,
+           -0.11679776148976055,
+           -0.09300851682674705,
+           -0.0712805059865837,
+           -0.05171898780186027,
+           -0.03435061780184423,
+           -0.019123720619273518,
+           -0.005910761041677673,
+           0.005487057906084266,
+           0.0153331969592064,
+           0.023947362002129664,
+           0.03169549174083989,
+           0.03897842030005333,
+           0.046219518247919145,
+           0.053851642634831914,
+           0.06230374524856976,
+           0.07198749795691589,
+           0.08328429447802245,
+           0.09653297916653772,
+           0.11201863564065055,
+           0.12996274173957204,
+           0.15051496304668532,
+           0.17374681589476584,
+           0.19964738341925423,
+           0.22812121602948593,
+           0.25898849193551593,
+           0.29198745550003824,
+           0.3267790926370211,
+           0.3629539447267384,
+           0.40004090701927303,
+           0.43751780565960346,
+           0.47482350060267137,
+           0.5113712209896929,
+           0.5465628060689922,
+           0.5798034993291684,
+           0.6105169268327324,
+           0.6381598832413654,
+           0.6622365509277346,
+           0.6823117888580623,
+           0.6980231483546799,
+           0.7090913019309746,
+           0.7153286084382489,
+           0.7166455818811956,
+           0.7130550813742899,
+           0.7046740946024723,
+           0.6917230454717207,
+           0.674522616956241,
+           0.653488140983781,
+           0.6291216670482737,
+           0.6020018786195453,
+           0.5727720799113883,
+           0.5421265238430538,
+           0.5107953938825044,
+           0.47952878684609096,
+           0.4490800697838963,
+           0.4201890011425456,
+           0.3935650140268471,
+           0.3698710573693323,
+           0.3497083791902309,
+           0.333602615153696,
+           0.3219915157932982,
+           0.3152146078030389,
+           0.3135050395825848,
+           0.3169838098781526,
+           0.32565652211663376,
+           0.3394127472542021,
+           0.35802801610352436,
+           0.3811683996694431,
+           0.40839757453028347,
+           0.43918621124693735,
+           0.47292346860161066,
+           0.508930326504945,
+           0.5464744468792043,
+           0.5847862157833377,
+           0.6230755923672127,
+           0.660549371595952,
+           0.6964284585187249,
+           0.729964752384861,
+           0.7604572491115406,
+           0.7872669902227927,
+           0.8098305149192463,
+           0.8276715086949678,
+           0.8404103859833095,
+           0.8477715946017871,
+           0.8495884850390494,
+           0.8458056465268544,
+           0.8364786729214571,
+           0.8217713831851935,
+           0.8019505821995011,
+           0.7773785062667856,
+           0.7485031525418427,
+           0.7158467414399476,
+           0.6799926045917875,
+           0.6415708271056024,
+           0.6012430008878987,
+           0.5596864649031057,
+           0.5175784180771512,
+           0.47558029085847625,
+           0.43432275226601513,
+           0.39439171083607893,
+           0.35631564071476013,
+           0.3205545289319572,
+           0.287490697536635,
+           0.2574217058455952,
+           0.23055548478301757,
+           0.20700779850581438,
+           0.18680206964556234,
+           0.16987154502473753,
+           0.15606372010848063,
+           0.14514688419356125,
+           0.13681859581222458,
+           0.13071585034292582,
+           0.12642666054673163,
+           0.12350273670393803,
+           0.12147292704399408,
+           0.11985706187369408,
+           0.118179836625387,
+           0.11598437015156302,
+           0.11284508493423435,
+           0.10837957517507549,
+           0.10225915647897985,
+           0.09421782632163068,
+           0.084059406789741,
+           0.07166268911909286,
+           0.05698445210565308,
+           0.04006028219161385,
+           0.02100318051509604,
+           2.0400191725891298e-16
+          ],
+          [
+           0,
+           -0.02410457256332321,
+           -0.049471090342046865,
+           -0.07569542134700412,
+           -0.10233773069203957,
+           -0.12893538144585115,
+           -0.1550165299482042,
+           -0.18011405175896433,
+           -0.20377942507994876,
+           -0.2255961987311017,
+           -0.2451926815769575,
+           -0.2622535094486001,
+           -0.27652977361689174,
+           -0.2878474310475967,
+           -0.2961137601048713,
+           -0.30132167497939927,
+           -0.30355176665748734,
+           -0.30297199634831845,
+           -0.2998350274874112,
+           -0.29447324321923823,
+           -0.28729155609788487,
+           -0.2787581741196892,
+           -0.2693935406631543,
+           -0.2597577141015712,
+           -0.25043649454472305,
+           -0.2420266392899756,
+           -0.23512053423936913,
+           -0.23029070509678062,
+           -0.22807455915296868,
+           -0.2289597456893752,
+           -0.233370510520244,
+           -0.241655398226115,
+           -0.2540766247253742,
+           -0.2708014037234356,
+           -0.2918954642160975,
+           -0.3173189437320391,
+           -0.34692478466146065,
+           -0.3804597002389739,
+           -0.41756771402281606,
+           -0.4577962135849656,
+           -0.5006043971564599,
+           -0.5453739326928995,
+           -0.5914215937069951,
+           -0.6380135866286798,
+           -0.6843812416354484,
+           -0.7297377039183551,
+           -0.7732952360933675,
+           -0.8142827256008921,
+           -0.8519629838959393,
+           -0.8856494272136366,
+           -0.9147217416498885,
+           -0.9386401579296183,
+           -0.9569579930118103,
+           -0.9693321558427649,
+           -0.9755313621510283,
+           -0.9754418570307057,
+           -0.9690705028805157,
+           -0.9565451526273361,
+           -0.9381122925503876,
+           -0.914132003870189,
+           -0.8850703559973832,
+           -0.8514894053993842,
+           -0.8140350309512744,
+           -0.7734228880065188,
+           -0.7304228080032231,
+           -0.6858420071296257,
+           -0.6405074955173711,
+           -0.5952480969372029,
+           -0.550876497594136,
+           -0.5081717411554479,
+           -0.46786257563947115,
+           -0.43061203653635693,
+           -0.397003620052884,
+           -0.3675293614259629,
+           -0.34258008679527424,
+           -0.3224380543080416,
+           -0.307272142247306,
+           -0.29713568045018746,
+           -0.29196695762321523,
+           -0.29159237292663365,
+           -0.2957321369591666,
+           -0.3040083665724999,
+           -0.3159553612592294,
+           -0.3310317975661597,
+           -0.34863453332844824,
+           -0.3681136765750259,
+           -0.38878854560596265,
+           -0.40996412765802476,
+           -0.43094763419582444,
+           -0.4510647513924402,
+           -0.4696751947495514,
+           -0.48618719676422656,
+           -0.5000705855520082,
+           -0.5108681496363291,
+           -0.5182050287604855,
+           -0.5217959214389143,
+           -0.5214499557560048,
+           -0.5170731292402772,
+           -0.5086682850023589,
+           -0.496332653191978,
+           -0.480253047658495,
+           -0.46069886597664234,
+           -0.43801309527657284,
+           -0.4126015752501861,
+           -0.384920812085456,
+           -0.3554646718647003,
+           -0.32475030830094437,
+           -0.2933036969410744,
+           -0.2616451557264487,
+           -0.2302752299003084,
+           -0.19966130775882668,
+           -0.1702253129711619,
+           -0.1423327896882472,
+           -0.11628365918348901,
+           -0.09230488228352715,
+           -0.0705452114912044,
+           -0.051072161759756915,
+           -0.03387127074492539,
+           -0.01884765951721411,
+           -0.00582984467893807,
+           0.005424305877126462,
+           0.015219637219976934,
+           0.023914006949727857,
+           0.03190708149833055,
+           0.03962792996817546,
+           0.047521747990578664,
+           0.056036067238322995,
+           0.06560682026327372,
+           0.07664463488911318,
+           0.08952172734652457,
+           0.1045597488116825,
+           0.12201891635555077,
+           0.14208872711836887,
+           0.16488051459344316,
+           0.19042205923526895,
+           0.218654413368071,
+           0.24943104387279377,
+           0.2825193367928483,
+           0.3176044473147279,
+           0.3542954180781034,
+           0.39213342997843087,
+           0.43060199403063026,
+           0.4691388418743374,
+           0.5071492274167627,
+           0.5440203140794792,
+           0.5791362921180925,
+           0.6118938492969432,
+           0.6417176063845819,
+           0.668075126816875,
+           0.6904911175386579,
+           0.7085604553238669,
+           0.7219596993894704,
+           0.7304567862311965,
+           0.7339186454744528,
+           0.7323165251126394,
+           0.7257288695888113,
+           0.7143416534173442,
+           0.6984461349858153,
+           0.678434058299219,
+           0.6547903931719776,
+           0.6280837651868373,
+           0.5989547841171126,
+           0.5681025320249764,
+           0.5362695185957564,
+           0.5042254502887187,
+           0.4727501905987555,
+           0.44261631035433685,
+           0.4145716389708477,
+           0.3893222296168586,
+           0.3675161432609369,
+           0.3497284387208882,
+           0.336447728551862,
+           0.3280646245322214,
+           0.32486235250151885,
+           0.3270097654335903,
+           0.3345569271196575,
+           0.34743337806092656,
+           0.36544913160267517,
+           0.38829838352705565,
+           0.4155658538362483,
+           0.44673561687023333,
+           0.4812022167378227,
+           0.5182838107356872,
+           0.5572370353091985,
+           0.5972732483413118,
+           0.6375757691311152,
+           0.677317714128254,
+           0.7156800128847328,
+           0.7518691850966911,
+           0.7851344661146141,
+           0.8147838847331783,
+           0.8401989230208742,
+           0.8608474227707279,
+           0.8762944459867607,
+           0.8862108466103323,
+           0.8903793662111051,
+           0.8886981262548588,
+           0.8811814523454385,
+           0.8679580299821641,
+           0.8492664553076217,
+           0.8254483064821205,
+           0.7969389201945166,
+           0.7642561119724778,
+           0.7279871270752014,
+           0.6887741496756147,
+           0.6472987307843127,
+           0.6042655191545713,
+           0.5603856936798121,
+           0.5163605002309548,
+           0.4728652904040696,
+           0.4305344444261293,
+           0.3899475359071987,
+           0.3516170628693803,
+           0.31597802837898453,
+           0.28337960620356395,
+           0.2540790734209568,
+           0.22823813417072425,
+           0.20592169820863732,
+           0.18709911611807378,
+           0.17164781149229652,
+           0.1593591906624834,
+           0.14994665409394245,
+           0.14305548180760524,
+           0.13827431938639784,
+           0.1351479524253761,
+           0.1331910266300174,
+           0.13190234890507557,
+           0.13077939223190496,
+           0.12933262419573863,
+           0.12709928574559723,
+           0.12365626295539106,
+           0.11863171977558312,
+           0.11171519336431988,
+           0.10266589469968634,
+           0.09131900474736415,
+           0.07758980927601294,
+           0.06147557213102027,
+           0.043055105953819325,
+           0.02248605946609148,
+           2.1754546616233264e-16
+          ],
+          [
+           0,
+           -0.025490118842517805,
+           -0.0521048275647626,
+           -0.07940481979286701,
+           -0.1069208791231982,
+           -0.13416770146845794,
+           -0.1606582260246013,
+           -0.1859180907397223,
+           -0.20949982418969823,
+           -0.23099639174964803,
+           -0.25005372975273094,
+           -0.26638192655866855,
+           -0.2797647434859941,
+           -0.29006721054460727,
+           -0.2972410807879201,
+           -0.3013279816610105,
+           -0.3024601605828028,
+           -0.30085878368629776,
+           -0.29682980959804756,
+           -0.2907575227788885,
+           -0.2830958716901789,
+           -0.27435781435616713,
+           -0.26510292630978544,
+           -0.25592357210212474,
+           -0.24742998034444605,
+           -0.24023459263817795,
+           -0.23493607794353824,
+           -0.23210341537987458,
+           -0.23226044982179714,
+           -0.23587131588666954,
+           -0.24332710718589673,
+           -0.25493413946819077,
+           -0.27090411918930024,
+           -0.29134648399312074,
+           -0.3162631296771978,
+           -0.34554568070801334,
+           -0.37897539965666416,
+           -0.4162257665592469,
+           -0.4568676937538322,
+           -0.5003772768231449,
+           -0.5461459194852363,
+           -0.5934926111804366,
+           -0.6416780821705435,
+           -0.6899205135400596,
+           -0.7374124397555227,
+           -0.783338450396902,
+           -0.8268932761108136,
+           -0.8672998323036156,
+           -0.9038267929013847,
+           -0.9358052757077011,
+           -0.9626442402877384,
+           -0.9838442284459564,
+           -0.9990091155526574,
+           -1.0078555872960209,
+           -1.0102201097749528,
+           -1.0060632199142192,
+           -0.995471026545417,
+           -0.9786538786170677,
+           -0.9559422242674349,
+           -0.9277797512780713,
+           -0.8947139640991725,
+           -0.8573844136248285,
+           -0.8165088517124206,
+           -0.7728676317269191,
+           -0.7272867179486759,
+           -0.6806196995025743,
+           -0.6337292277511637,
+           -0.5874683092823478,
+           -0.5426618893981046,
+           -0.5000891533148524,
+           -0.46046695431440593,
+           -0.42443475028521915,
+           -0.3925413931546817,
+           -0.3652340705462004,
+           -0.3428496467117649,
+           -0.3256085916769936,
+           -0.31361162501807416,
+           -0.30683913530140733,
+           -0.30515336955850925,
+           -0.30830332087073686,
+           -0.31593217781950655,
+           -0.3275871387851742,
+           -0.34273133832925673,
+           -0.36075758352150356,
+           -0.38100355626745885,
+           -0.4027681044568885,
+           -0.4253282208790666,
+           -0.44795629489509525,
+           -0.4699372181323638,
+           -0.4905849320305074,
+           -0.5092580217264528,
+           -0.5253739870736549,
+           -0.5384218568651999,
+           -0.547972855669342,
+           -0.5536888829887796,
+           -0.5553286204510933,
+           -0.5527511430181646,
+           -0.5459169732552186,
+           -0.534886581947646,
+           -0.519816402192484,
+           -0.5009524859313503,
+           -0.4786219901961842,
+           -0.45322273366324684,
+           -0.42521111113658744,
+           -0.39508869315179984,
+           -0.3633878690351238,
+           -0.3306569137150722,
+           -0.29744487083820137,
+           -0.26428664700584076,
+           -0.2316887041935529,
+           -0.2001157198602252,
+           -0.16997855736461204,
+           -0.14162385378314127,
+           -0.11532548897891073,
+           -0.09127814991584259,
+           -0.0695931490164888,
+           -0.050296596232607946,
+           -0.03332996293731716,
+           -0.018553013319413024,
+           -0.005749017247938686,
+           0.0053679008571085015,
+           0.015143478257422344,
+           0.023972346790065175,
+           0.03228567795160392,
+           0.040537772081655946,
+           0.04919195141757996,
+           0.058706135428084644,
+           0.06951848576517493,
+           0.08203350716781842,
+           0.0966089797239642,
+           0.11354407731705543,
+           0.13306899735922365,
+           0.15533638878697395,
+           0.18041481971966358,
+           0.20828447429823904,
+           0.2388352113334681,
+           0.27186705692872437,
+           0.30709314072367117,
+           0.3441450224072844,
+           0.3825802932613589,
+           0.4218922782836176,
+           0.461521609403135,
+           0.500869390838162,
+           0.5393116350190607,
+           0.5762146127993651,
+           0.6109507358024614,
+           0.6429145723774538,
+           0.6715385922069228,
+           0.6963082383156268,
+           0.716775939013958,
+           0.7325736958632852,
+           0.7434239165177771,
+           0.7491482024938956,
+           0.749673850547903,
+           0.7450378812197042,
+           0.7353884678863644,
+           0.7209837028941606,
+           0.7021877024485894,
+           0.6794641173320094,
+           0.6533671805721345,
+           0.6245304843153809,
+           0.5936537348490808,
+           0.5614877855550229,
+           0.5288182912942165,
+           0.4964483632230807,
+           0.46518062942896365,
+           0.435799123375164,
+           0.40905142853018933,
+           0.38563150354054976,
+           0.3661635979649048,
+           0.3511876442476071,
+           0.3411464778456757,
+           0.33637519504130825,
+           0.3370929079911747,
+           0.34339710019081,
+           0.3552607241321015,
+           0.37253211799377933,
+           0.39493775130644687,
+           0.42208774230181706,
+           0.4534840237264471,
+           0.48853097087843345,
+           0.5265482470457087,
+           0.5667855688129648,
+           0.6084390481435992,
+           0.6506687308415844,
+           0.6926169228610414,
+           0.7334268776402235,
+           0.7722614096314381,
+           0.8083210016673007,
+           0.8408609866782343,
+           0.8692074072331569,
+           0.8927711888452919,
+           0.911060304165224,
+           0.9236896540592879,
+           0.9303884469403202,
+           0.9310049182195869,
+           0.9255082958988788,
+           0.9139879845483729,
+           0.8966500065983031,
+           0.8738108053811998,
+           0.8458885770986971,
+           0.8133923573252575,
+           0.7769091403819789,
+           0.7370893556412684,
+           0.6946310624566486,
+           0.6502632540516105,
+           0.6047286796714645,
+           0.558766603166094,
+           0.5130959147435207,
+           0.4683990009831001,
+           0.4253067566436228,
+           0.38438509091142026,
+           0.34612324130110056,
+           0.310924161452195,
+           0.27909719574747854,
+           0.25085319535722045,
+           0.22630216845328746,
+           0.20545349348721784,
+           0.1882186601829601,
+           0.17441643985953292,
+           0.16378032643951485,
+           0.15596803351167596,
+           0.1505727824858306,
+           0.14713607344689078,
+           0.1451615948499595,
+           0.1441299015647658,
+           0.14351347361888683,
+           0.1427917607099339,
+           0.14146582031378807,
+           0.13907216991413984,
+           0.13519549617382828,
+           0.1294798951764813,
+           0.12163835737803057,
+           0.11146025760714362,
+           0.09881666314760462,
+           0.08366333028079169,
+           0.06604132020383774,
+           0.0460752274309638,
+           0.023969076053584327,
+           2.309731784318241e-16
+          ],
+          [
+           0,
+           -0.026839726757520364,
+           -0.05464314412194687,
+           -0.08293814463513531,
+           -0.11122928784885072,
+           -0.13901245223406888,
+           -0.16578978997462565,
+           -0.19108458319551125,
+           -0.2144556020002646,
+           -0.2355105767805158,
+           -0.2539184193166995,
+           -0.2694198586639647,
+           -0.28183619792531556,
+           -0.29107594575089824,
+           -0.29713913057087593,
+           -0.30011916480907064,
+           -0.30020218914576996,
+           -0.29766389171900093,
+           -0.2928638623397864,
+           -0.28623760570237733,
+           -0.2782863985785681,
+           -0.2695652325493086,
+           -0.26066913450895146,
+           -0.2522182006844068,
+           -0.24484171512729647,
+           -0.2391617496512922,
+           -0.23577665831703296,
+           -0.2352448853768001,
+           -0.23806950090097337,
+           -0.24468386320043206,
+           -0.25543878197588643,
+           -0.270591521460999,
+           -0.2902969395130285,
+           -0.3146010076917866,
+           -0.3434369000956073,
+           -0.37662377649335926,
+           -0.41386831963225873,
+           -0.45476901912889056,
+           -0.49882312673061135,
+           -0.5454361416389443,
+           -0.5939336216541685,
+           -0.6435750576948546,
+           -0.6935694972177174,
+           -0.7430925575126228,
+           -0.7913044338931146,
+           -0.8373684813535014,
+           -0.8804699319948894,
+           -0.9198343048612083,
+           -0.9547450699378861,
+           -0.9845601438513846,
+           -1.00872682090553,
+           -1.0267947788844631,
+           -1.038426843687237,
+           -1.0434072492620605,
+           -1.041647188213778,
+           -1.0331875124398764,
+           -1.0181985106558626,
+           -0.9969767590600391,
+           -0.9699391109728298,
+           -0.9376139593731169,
+           -0.9006299711856262,
+           -0.8597025523675261,
+           -0.8156183568331309,
+           -0.769218198728166,
+           -0.7213787653887557,
+           -0.6729935565760311,
+           -0.624953493580198,
+           -0.5781276491044077,
+           -0.5333445452966796,
+           -0.49137445299161214,
+           -0.4529131005096818,
+           -0.4185671658529042,
+           -0.38884188268262015,
+           -0.3641310391380317,
+           -0.3447095906143714,
+           -0.33072904448953594,
+           -0.32221570801550403,
+           -0.3190718218110166,
+           -0.32107953228709474,
+           -0.327907588594573,
+           -0.3391205849546471,
+           -0.3541905090942497,
+           -0.37251030341725394,
+           -0.3934090988080407,
+           -0.41616874271039467,
+           -0.44004121426554116,
+           -0.46426650050879403,
+           -0.48809049934513626,
+           -0.5107825174208397,
+           -0.5316519439873352,
+           -0.5500637050605641,
+           -0.5654521350072667,
+           -0.577332944295884,
+           -0.5853130114753189,
+           -0.5890977832422132,
+           -0.5884961273217071,
+           -0.5834225472901153,
+           -0.5738967347988688,
+           -0.5600405012610552,
+           -0.5420721962759786,
+           -0.520298782272339,
+           -0.4951057925045651,
+           -0.4669454512140022,
+           -0.43632327919354236,
+           -0.4037835440811082,
+           -0.36989394157495786,
+           -0.3352299107649286,
+           -0.30035899350952183,
+           -0.2658256441178518,
+           -0.23213688163743204,
+           -0.19974915318093595,
+           -0.16905674357245276,
+           -0.14038202501367072,
+           -0.11396779153038283,
+           -0.08997186791087544,
+           -0.06846412309312164,
+           -0.0494259550173018,
+           -0.03275224943242657,
+           -0.018255750667956223,
+           -0.005673719587893451,
+           0.0053233055729091806,
+           0.015120884524573571,
+           0.024148473988139543,
+           0.0328659792716981,
+           0.041749419832950996,
+           0.05127609374310548,
+           0.06190963953030767,
+           0.07408539721958869,
+           0.08819646340890216,
+           0.10458081809550045,
+           0.12350987411768378,
+           0.14517876417309586,
+           0.16969863631413643,
+           0.1970911777078385,
+           0.22728552956452797,
+           0.2601176949163394,
+           0.29533247690374415,
+           0.332587920018796,
+           0.3714621620032129,
+           0.4114625414441058,
+           0.45203674713673997,
+           0.49258574148929196,
+           0.5324781429988424,
+           0.5710657133394145,
+           0.6076995638880166,
+           0.6417466753724395,
+           0.6726063133160431,
+           0.699725921388998,
+           0.7226160847013512,
+           0.7408641752777726,
+           0.7541463219672695,
+           0.7622373861481218,
+           0.7650186718453001,
+           0.7624831531362953,
+           0.7547380616563478,
+           0.7420047411562123,
+           0.7246157428377198,
+           0.7030092029485002,
+           0.6777206111833624,
+           0.6493721431550283,
+           0.6186597909554865,
+           0.5863385811190759,
+           0.553206217740079,
+           0.5200855288776574,
+           0.4878061256826427,
+           0.45718570510928136,
+           0.42901143807734327,
+           0.40402188522950994,
+           0.3828898719516751,
+           0.3662067333210731,
+           0.3544683086092883,
+           0.3480630246318964,
+           0.34726235857087495,
+           0.3522139150728927,
+           0.3629372907962861,
+           0.37932283363572206,
+           0.4011333351975423,
+           0.4280086253996479,
+           0.45947296902341417,
+           0.49494509733258824,
+           0.533750645120241,
+           0.5751367062781314,
+           0.6182881705979901,
+           0.6623454622376213,
+           0.7064232671447738,
+           0.7496298135323348,
+           0.7910862568010375,
+           0.8299457184140762,
+           0.8654115371809978,
+           0.8967543109796415,
+           0.9233273366485152,
+           0.9445800948841162,
+           0.9600694745143131,
+           0.9694684853212701,
+           0.9725722693090794,
+           0.9693012854627224,
+           0.9597016110297499,
+           0.9439423715103427,
+           0.9223103801750584,
+           0.8952021343677068,
+           0.8631133784753207,
+           0.8266265007362145,
+           0.7863960816227854,
+           0.7431329541579696,
+           0.6975871701810213,
+           0.6505302904699575,
+           0.6027374301978412,
+           0.5549694941463281,
+           0.5079560283840261,
+           0.4623790969641463,
+           0.41885856408736627,
+           0.3779391248395698,
+           0.3400793820034875,
+           0.30564321371556846,
+           0.27489361822457875,
+           0.24798915917757114,
+           0.2249830692867568,
+           0.20582500355630845,
+           0.1903653671343617,
+           0.17836207894742265,
+           0.1694895721586059,
+           0.16334977765631872,
+           0.15948478857974843,
+           0.1573908635071669,
+           0.1565333943602023,
+           0.15636244307735678,
+           0.15632843920776032,
+           0.1558976290425244,
+           0.15456687574680725,
+           0.15187742893173403,
+           0.14742731070874016,
+           0.14088200275622145,
+           0.13198316433414337,
+           0.12055516334343655,
+           0.10650926011239534,
+           0.08984534513568801,
+           0.07065119592891018,
+           0.04909928286992473,
+           0.02544121773650461,
+           2.4418114816993366e-16
+          ],
+          [
+           0,
+           -0.028142345647547067,
+           -0.057064756874943896,
+           -0.08626524937908106,
+           -0.11522582374071129,
+           -0.1434278391579347,
+           -0.1703674660418951,
+           -0.19557080203706967,
+           -0.21860824405021276,
+           -0.23910772736643657,
+           -0.25676647143862763,
+           -0.27136090974539384,
+           -0.28275452727614997,
+           -0.2909033825616883,
+           -0.29585915038419147,
+           -0.29776958488276867,
+           -0.2968763691181806,
+           -0.2935103846006906,
+           -0.2880845011152538,
+           -0.2810840517085934,
+           -0.27305521829809765,
+           -0.2645916084838862,
+           -0.25631935238834896,
+           -0.24888108847726992,
+           -0.24291923829952355,
+           -0.23905899111139878,
+           -0.23789142986746714,
+           -0.23995722976479916,
+           -0.24573134939303712,
+           -0.25560911281172916,
+           -0.26989404905574327,
+           -0.28878781441956264,
+           -0.31238247338604364,
+           -0.340655357448809,
+           -0.3734666587140639,
+           -0.4105598485874719,
+           -0.45156494269332464,
+           -0.4960045631427774,
+           -0.5433026800971157,
+           -0.592795847975117,
+           -0.6437466892848931,
+           -0.6953593224734032,
+           -0.7467963807946485,
+           -0.7971972282393096,
+           -0.8456969470769237,
+           -0.8914456503384717,
+           -0.9336276621617353,
+           -0.9714801096184501,
+           -1.0043104814521355,
+           -1.0315127318162727,
+           -1.0525815400845806,
+           -1.0671243803241486,
+           -1.0748711050586004,
+           -1.0756808062718228,
+           -1.0695457808025624,
+           -1.0565924957998136,
+           -1.037079521084357,
+           -1.0113924673623393,
+           -0.9800360405076317,
+           -0.9436233908350257,
+           -0.9028630007523997,
+           -0.858543412835645,
+           -0.8115161517864292,
+           -0.7626772366572585,
+           -0.7129477131162631,
+           -0.6632536585644014,
+           -0.6145061250525012,
+           -0.5675814858839527,
+           -0.5233026415141319,
+           -0.4824215191278777,
+           -0.44560326861708227,
+           -0.413412516372966,
+           -0.38630198836824026,
+           -0.36460375666037337,
+           -0.3485233001059032,
+           -0.3381365022899941,
+           -0.33338963910516783,
+           -0.3341023367844169,
+           -0.33997341025646804,
+           -0.35058942317490743,
+           -0.3654357465462389,
+           -0.3839098341095384,
+           -0.4053363809253069,
+           -0.4289839882599721,
+           -0.4540829238446486,
+           -0.4798435427490538,
+           -0.5054749209987055,
+           -0.5302032519646921,
+           -0.5532895644875506,
+           -0.5740463414044279,
+           -0.5918526471108646,
+           -0.6061674122317611,
+           -0.6165405713942258,
+           -0.6226218052743857,
+           -0.624166699139987,
+           -0.6210401954976987,
+           -0.6132172865409997,
+           -0.6007809611810351,
+           -0.5839174898071607,
+           -0.5629091958665549,
+           -0.5381249252375595,
+           -0.5100084806684676,
+           -0.4790653378739996,
+           -0.445848001014382,
+           -0.4109403872223528,
+           -0.374941651818884,
+           -0.3384498773467824,
+           -0.3020460502938334,
+           -0.2662787393845531,
+           -0.23164986887134106,
+           -0.19860194989320787,
+           -0.16750709348206694,
+           -0.13865808119967588,
+           -0.11226171490153135,
+           -0.08843460713781401,
+           -0.06720150974267443,
+           -0.048496211857044086,
+           -0.032164971659227444,
+           -0.017972380139776534,
+           -0.005609492023149659,
+           0.005295999990071231,
+           0.015167824617755574,
+           0.024467747972838547,
+           0.03368110674644705,
+           0.04330164763672249,
+           0.05381608049029575,
+           0.06568876059335253,
+           0.07934691285402148,
+           0.09516679731868907,
+           0.11346119189025303,
+           0.1344685348538729,
+           0.158344027697451,
+           0.18515294879568148,
+           0.21486637206122636,
+           0.24735942307372802,
+           0.28241214002704645,
+           0.31971293972932596,
+           0.3588646215422901,
+           0.3993927762572064,
+           0.4407564041429204,
+           0.48236048835822765,
+           0.5235702180731397,
+           0.5637265113148746,
+           0.6021624518826563,
+           0.6382202285838031,
+           0.671268149217464,
+           0.7007172966017045,
+           0.7260373996679483,
+           0.746771509126805,
+           0.7625490940648835,
+           0.7730972124278782,
+           0.7782494538010992,
+           0.7779524061121341,
+           0.7722694575534913,
+           0.7613818096940425,
+           0.7455866458276139,
+           0.725292468417647,
+           0.7010116893140849,
+           0.6733506245143707,
+           0.6429971099247693,
+           0.6107060142428661,
+           0.577282978238539,
+           0.5435667550288737,
+           0.5104105622829114,
+           0.47866288373469235,
+           0.44914817325017775,
+           0.422647919566744,
+           0.3998825235553771,
+           0.3814944225708847,
+           0.3680328685518357,
+           0.35994072866843735,
+           0.35754363039790205,
+           0.3610417180614777,
+           0.3705042264097233,
+           0.38586701028107845,
+           0.40693309929838195,
+           0.4333762747114867,
+           0.4647475935896074,
+           0.5004847153651727,
+           0.539923818941844,
+           0.5823138368304639,
+           0.626832677572682,
+           0.6726050603977921,
+           0.7187215477858627,
+           0.7642583333106542,
+           0.808297324495209,
+           0.8499460538575498,
+           0.888356956007543,
+           0.9227455644577993,
+           0.9524072083383641,
+           0.9767318258014637,
+           0.9952165566673619,
+           1.007475830669654,
+           1.013248728187236,
+           1.012403456115725,
+           1.0049388509220516,
+           0.9909828922439877,
+           0.9707882818982642,
+           0.944725213101393,
+           0.9132715213818982,
+           0.8770004704501462,
+           0.8365664816936023,
+           0.7926891636422618,
+           0.7461360365547239,
+           0.6977043762839585,
+           0.6482026201102289,
+           0.5984317848540154,
+           0.549167344150335,
+           0.501141997397352,
+           0.4550297379763652,
+           0.41143159352591563,
+           0.37086336723310565,
+           0.3337456573929753,
+           0.3003963741889855,
+           0.2710259092303348,
+           0.2457350464354094,
+           0.2245156340493415,
+           0.20725396864354126,
+           0.19373677458238883,
+           0.18365959832967332,
+           0.17663737769304363,
+           0.17221689313293373,
+           0.16989076289686528,
+           0.1691126070920623,
+           0.16931297877024,
+           0.16991564331765244,
+           0.17035378131257903,
+           0.17008569465590656,
+           0.16860961105251882,
+           0.1654772074103262,
+           0.16030550776267433,
+           0.15278685500290023,
+           0.14269670692560565,
+           0.12989906448897687,
+           0.11434940238302829,
+           0.09609503732886553,
+           0.07527293638492923,
+           0.05210503420209656,
+           0.026891192960927655,
+           2.5706438961648465e-16
+          ],
+          [
+           0,
+           -0.029387114770940775,
+           -0.05934908784746175,
+           -0.08935751435556531,
+           -0.11887597848847052,
+           -0.1473760263716259,
+           -0.17435297738428132,
+           -0.199341148211366,
+           -0.22192807845723328,
+           -0.24176737178846688,
+           -0.2585898016584638,
+           -0.27221237482292804,
+           -0.28254509797453453,
+           -0.289595251597158,
+           -0.29346903908668115,
+           -0.2943705466960279,
+           -0.29259801923462525,
+           -0.2885375259357162,
+           -0.28265415874225636,
+           -0.27548096973561736,
+           -0.2676059139047025,
+           -0.25965711641277184,
+           -0.25228682861236595,
+           -0.24615447312696312,
+           -0.24190920442705274,
+           -0.24017242679125317,
+           -0.24152071593809832,
+           -0.24646958379509307,
+           -0.25545850797249514,
+           -0.26883761894087455,
+           -0.28685639935181695,
+           -0.30965470231882347,
+           -0.3372563399470854,
+           -0.3695654313224084,
+           -0.40636563206326287,
+           -0.44732229705630183,
+           -0.4919875558730116,
+           -0.5398082083863439,
+           -0.5901362780545831,
+           -0.6422419939549414,
+           -0.695328911584052,
+           -0.748550828221249,
+           -0.8010301026317724,
+           -0.8518769522297059,
+           -0.9002092744540993,
+           -0.9451725237145545,
+           -0.9859591712426834,
+           -1.0218272826725248,
+           -1.0521177670118145,
+           -1.0762698804230748,
+           -1.0938346082056432,
+           -1.104485597601483,
+           -1.1080273713547228,
+           -1.1044006159529745,
+           -1.0936844076174739,
+           -1.076095311710789,
+           -1.0519833655304742,
+           -1.0218250286465191,
+           -0.9862132572129658,
+           -0.9458449272783424,
+           -0.9015058953637137,
+           -0.8540540409289816,
+           -0.8044006834342134,
+           -0.7534908053513194,
+           -0.7022825407516871,
+           -0.6517264063005631,
+           -0.6027447572131985,
+           -0.556211944836306,
+           -0.5129356351606676,
+           -0.47363971917729997,
+           -0.438949207260175,
+           -0.40937745164630285,
+           -0.3853159847705429,
+           -0.36702719807964895,
+           -0.3546400175451518,
+           -0.34814866009267026,
+           -0.3474144813272837,
+           -0.3521708510645791,
+           -0.36203092107716034,
+           -0.37649808089285536,
+           -0.39497883410039825,
+           -0.41679777096752074,
+           -0.44121426462354973,
+           -0.46744047877067124,
+           -0.49466024580165935,
+           -0.5220483560007634,
+           -0.5487897916029061,
+           -0.5740984440189394,
+           -0.5972348683541828,
+           -0.6175226560277141,
+           -0.6343630431479081,
+           -0.6472474183724489,
+           -0.6557674481094379,
+           -0.6596225977344844,
+           -0.6586248934782801,
+           -0.652700839127327,
+           -0.641890472940908,
+           -0.6263436214439906,
+           -0.6063134762363579,
+           -0.582147685939095,
+           -0.5542772162476188,
+           -0.5232032852742898,
+           -0.48948272761046147,
+           -0.45371217768629546,
+           -0.41651149015501565,
+           -0.37850683152636744,
+           -0.3403138827391942,
+           -0.30252158668934503,
+           -0.2656768580897247,
+           -0.23027064588154175,
+           -0.19672570145020288,
+           -0.16538636008087415,
+           -0.13651058959347875,
+           -0.11026450029176216,
+           -0.08671944576979783,
+           -0.06585177638400622,
+           -0.04754523803898973,
+           -0.03159594010470889,
+           -0.01771974952464485,
+           -0.005561905179898,
+           0.005291411062798911,
+           0.015299861011578408,
+           0.024954451628212894,
+           0.03476214196707763,
+           0.045229969712698506,
+           0.05684912431748912,
+           0.0700793956414834,
+           0.08533441787954764,
+           0.10296810865277028,
+           0.12326267293556216,
+           0.14641850174431995,
+           0.17254624722396383,
+           0.20166130014802125,
+           0.23368083429467618,
+           0.26842351622464644,
+           0.3056119103284195,
+           0.3448775393623279,
+           0.38576849181460265,
+           0.4277594010766703,
+           0.4702635592238507,
+           0.5126468718131938,
+           0.5542433109223105,
+           0.5943714829410939,
+           0.6323518964379555,
+           0.6675244945667482,
+           0.6992660065160868,
+           0.7270066737142237,
+           0.750245918896085,
+           0.7685665494414656,
+           0.7816471200584724,
+           0.7892721231084782,
+           0.7913397266021921,
+           0.7878668388807749,
+           0.7789913437877526,
+           0.7649714191454962,
+           0.7461819228745277,
+           0.7231079033688608,
+           0.6963353619772533,
+           0.666539463871786,
+           0.634470457509857,
+           0.6009376207204595,
+           0.5667916017238949,
+           0.5329055648635929,
+           0.5001555824417849,
+           0.46940073500105745,
+           0.44146339213647723,
+           0.41711014418815273,
+           0.39703384196488556,
+           0.38183717728048266,
+           0.372018202115876,
+           0.36795813948423056,
+           0.36991178564587196,
+           0.3780007424833369,
+           0.39220965207590613,
+           0.41238553442682213,
+           0.4382402556216961,
+           0.46935607922542266,
+           0.5051941802702429,
+           0.5451059305389434,
+           0.5883466977265038,
+           0.6340918410827977,
+           0.6814545337604836,
+           0.7295049985925943,
+           0.7772907104629819,
+           0.8238570956263208,
+           0.8682682468352677,
+           0.9096271732173631,
+           0.9470951155055768,
+           0.9799094801733108,
+           1.0073999796902149,
+           1.029002609670281,
+           1.0442711460579506,
+           1.052885905405222,
+           1.0546595772643732,
+           1.0495400081404547,
+           1.0376098895918497,
+           1.0190833771479595,
+           0.9942997399217341,
+           0.9637142113467201,
+           0.9278862776467185,
+           0.8874657008445509,
+           0.8431766258777362,
+           0.7958001654416479,
+           0.7461558904699136,
+           0.6950826778748275,
+           0.6434193797565035,
+           0.5919857794735686,
+           0.5415642897563762,
+           0.49288282672381356,
+           0.4465992617982766,
+           0.40328781192049373,
+           0.36342767820657323,
+           0.32739418553463717,
+           0.2954526119500926,
+           0.2677548288320605,
+           0.2443388021688437,
+           0.2251309338092963,
+           0.20995115096898032,
+           0.19852058432874725,
+           0.19047161145232813,
+           0.18535998454075425,
+           0.18267871115658907,
+           0.18187331472582727,
+           0.1823580693796246,
+           0.18353278181012966,
+           0.1847996818025716,
+           0.18557998321436386,
+           0.18532968836771654,
+           0.18355423079361297,
+           0.17982158343143176,
+           0.17377350091445798,
+           0.16513461438814242,
+           0.1537191541398016,
+           0.1394351377155204,
+           0.12228592757450243,
+           0.10236913099678917,
+           0.07987288417523265,
+           0.055069630432630676,
+           0.028307567587556676,
+           2.6951813940619026e-16
+          ],
+          [
+           0,
+           -0.030563503727266853,
+           -0.06147653791019192,
+           -0.09218823934586162,
+           -0.12214835911853543,
+           -0.15082369801283205,
+           -0.17771412577390144,
+           -0.2023677522199815,
+           -0.2243948395805208,
+           -0.2434800773738155,
+           -0.25939288285119333,
+           -0.27199544047280694,
+           -0.2812482517750798,
+           -0.2872130308848767,
+           -0.29005284922107444,
+           -0.2900295038785924,
+           -0.28749815602202533,
+           -0.2828993565102201,
+           -0.2767486441347973,
+           -0.26962396555600404,
+           -0.2621512236388048,
+           -0.25498831096107555,
+           -0.24880802650118175,
+           -0.24428030485019678,
+           -0.24205420791656085,
+           -0.2427401384467381,
+           -0.24689273250389995,
+           -0.2549948743451937,
+           -0.26744325222204846,
+           -0.2845358380832322,
+           -0.30646162883949524,
+           -0.33329293284984196,
+           -0.36498042392965,
+           -0.4013511179632143,
+           -0.44210935578022,
+           -0.4868408020878121,
+           -0.5350193957628597,
+           -0.5860171135476692,
+           -0.639116338975586,
+           -0.6935245629279996,
+           -0.7483910832238262,
+           -0.8028253195437025,
+           -0.8559163180787216,
+           -0.9067529886282639,
+           -0.954444596262678,
+           -0.9981410206530783,
+           -1.0370522990054174,
+           -1.0704669831815445,
+           -1.0977688677170103,
+           -1.1184516824418655,
+           -1.1321313903961028,
+           -1.1385557875782137,
+           -1.1376111644269093,
+           -1.1293258582790677,
+           -1.113870599689665,
+           -1.0915556316524024,
+           -1.0628246575702818,
+           -1.0282457494228932,
+           -0.9884994201193011,
+           -0.9443641317432676,
+           -0.8966995726395827,
+           -0.8464280895623586,
+           -0.7945147051092497,
+           -0.7419461843268009,
+           -0.6897096368719557,
+           -0.6387711519066432,
+           -0.5900549617264828,
+           -0.5444236170141771,
+           -0.5026596318882322,
+           -0.4654490211978461,
+           -0.4333671066730506,
+           -0.40686691370138384,
+           -0.38627041801325346,
+           -0.3717628329490849,
+           -0.3633900549319635,
+           -0.36105930906647743,
+           -0.3645429602774561,
+           -0.37348537995825126,
+           -0.38741268555543534,
+           -0.40574510263973607,
+           -0.42781163744872136,
+           -0.4528666941246168,
+           -0.48010822620555965,
+           -0.508696977429602,
+           -0.5377763433946371,
+           -0.5664923736289559,
+           -0.5940134334261779,
+           -0.619549056353301,
+           -0.6423675413305519,
+           -0.6618118820034715,
+           -0.6773136599123292,
+           -0.6884045855979595,
+           -0.6947254319366619,
+           -0.6960321701568762,
+           -0.6921991894985736,
+           -0.683219554570439,
+           -0.6692023283173271,
+           -0.6503670612940865,
+           -0.627035617845141,
+           -0.5996215750816085,
+           -0.568617489617189,
+           -0.5345803784170321,
+           -0.4981158025714076,
+           -0.45986097529479586,
+           -0.42046733718854307,
+           -0.3805830522793622,
+           -0.3408358773268851,
+           -0.3018168444395405,
+           -0.2640651734936429,
+           -0.22805479683721758,
+           -0.19418283516084012,
+           -0.16276031135441488,
+           -0.13400532997410022,
+           -0.108038885127271,
+           -0.08488339079461779,
+           -0.06446395659404608,
+           -0.046612360552089394,
+           -0.031073600394862105,
+           -0.017514837975758937,
+           -0.0055364894137742105,
+           0.005314842106053089,
+           0.015531941712954671,
+           0.025631456011601442,
+           0.036137682362910255,
+           0.04756611061477347,
+           0.06040716039940437,
+           0.07511055251972353,
+           0.09207073708345807,
+           0.11161377430559645,
+           0.1339860269569064,
+           0.15934497721535174,
+           0.18775242633969025,
+           0.21917027449705764,
+           0.2534590117769415,
+           0.29037898158344455,
+           0.32959440597814504,
+           0.3706800909561288,
+           0.41313065988869596,
+           0.45637209722511873,
+           0.49977532369201316,
+           0.5426714702119142,
+           0.5843684719632888,
+           0.6241685675994669,
+           0.6613862625779143,
+           0.6953663005106803,
+           0.7255011828440243,
+           0.7512477851371824,
+           0.7721426375751597,
+           0.7878154676714373,
+           0.7980006436719452,
+           0.8025462069833915,
+           0.8014202398056558,
+           0.7947143786350542,
+           0.7826443538402109,
+           0.7655475083831843,
+           0.7438773231666552,
+           0.7181950505925359,
+           0.6891586298806183,
+           0.6575091257293472,
+           0.6240549943088968,
+           0.5896545358002389,
+           0.555196939347013,
+           0.5215823631936184,
+           0.48970151900492365,
+           0.46041524422418106,
+           0.4345345494289567,
+           0.4128016188818037,
+           0.39587222202747757,
+           0.3842999620332723,
+           0.37852274535237757,
+           0.37885180471902097,
+           0.385463548199488,
+           0.39839444036927324,
+           0.417539049976141,
+           0.44265132332273804,
+           0.47334906588718134,
+           0.5091215382632497,
+           0.549339998205604,
+           0.5932709502210302,
+           0.6400917994696002,
+           0.6889085493075731,
+           0.7387751330176793,
+           0.7887139313218013,
+           0.8377369991050215,
+           0.8848675080840547,
+           0.9291609073310216,
+           0.9697253107296457,
+           1.0057406394151784,
+           1.0364760775629933,
+           1.0613054407977336,
+           1.0797201069901092,
+           1.091339218052968,
+           1.0959169270991973,
+           1.0933465363713035,
+           1.083661445957364,
+           1.0670329096467541,
+           1.0437646704875765,
+           1.0142846228276747,
+           0.979133718045572,
+           0.9389523960955982,
+           0.894464882829861,
+           0.8464617424220463,
+           0.7957811139187769,
+           0.7432890900376301,
+           0.6898597141340806,
+           0.6363550773688665,
+           0.583605992408517,
+           0.5323937026615191,
+           0.4834330575545502,
+           0.43735754542589766,
+           0.3947065272505462,
+           0.35591495783956706,
+           0.3213058178005703,
+           0.2910854109974296,
+           0.2653416102213923,
+           0.2440450600803286,
+           0.22705327256386476,
+           0.21411747917676052,
+           0.20489203572540074,
+           0.19894611346907615,
+           0.1957773549463754,
+           0.19482712571798652,
+           0.19549695568017642,
+           0.19716573640893795,
+           0.1992072248425544,
+           0.20100739887222877,
+           0.20198121717232492,
+           0.20158835366181058,
+           0.19934750586191907,
+           0.19484891534741336,
+           0.18776478647439354,
+           0.17785734537521838,
+           0.16498434341510707,
+           0.1491018763208695,
+           0.13026446031672784,
+           0.10862237805568972,
+           0.0844163781063412,
+           0.05796988044689204,
+           0.02967890509229085,
+           2.8143917532315726e-16
+          ],
+          [
+           0,
+           -0.03166145093101665,
+           -0.06342875255806966,
+           -0.09473301854237806,
+           -0.12501514764537405,
+           -0.15374257247764192,
+           -0.18042532571726624,
+           -0.20463098983576908,
+           -0.22599812475088135,
+           -0.2442478066592108,
+           -0.2591929596126905,
+           -0.27074521797538703,
+           -0.2789191213075958,
+           -0.28383351187446537,
+           -0.2857100771354196,
+           -0.28486905341684293,
+           -0.2817221806376278,
+           -0.2767630695809668,
+           -0.2705552109705774,
+           -0.26371791779393533,
+           -0.25691054733487906,
+           -0.25081539582610723,
+           -0.24611969531403802,
+           -0.24349716829229076,
+           -0.24358961022040632,
+           -0.2469889728002268,
+           -0.2542204117270793,
+           -0.2657267417575827,
+           -0.281854709824895,
+           -0.3028434543514933,
+           -0.32881546688806607,
+           -0.3597703120114425,
+           -0.3955812945178782,
+           -0.4359951909938488,
+           -0.4806350876078069,
+           -0.5290062893017758,
+           -0.5805051893696639,
+           -0.634430914580698,
+           -0.6899994913780968,
+           -0.7463602149916453,
+           -0.8026138471416764,
+           -0.8578322207916855,
+           -0.9110787933198192,
+           -0.9614296634705021,
+           -1.0079945531890988,
+           -1.0499372533194604,
+           -1.086495042241765,
+           -1.1169966086313246,
+           -1.1408780431164531,
+           -1.157696507910058,
+           -1.1671412474257519,
+           -1.1690416651667366,
+           -1.1633722612895752,
+           -1.150254299520234,
+           -1.1299541497327965,
+           -1.1028783316038542,
+           -1.0695653634016307,
+           -1.0306745962416524,
+           -0.9869722861801535,
+           -0.93931522256454,
+           -0.8886322895054111,
+           -0.8359043867498968,
+           -0.7821431754158245,
+           -0.7283691420344968,
+           -0.6755894904649395,
+           -0.6247763750930841,
+           -0.5768459802244776,
+           -0.5326389299302663,
+           -0.49290248032186407,
+           -0.45827490310342145,
+           -0.4292724163408299,
+           -0.4062789569890069,
+           -0.3895390213393156,
+           -0.3791537258599953,
+           -0.3750801637064997,
+           -0.37713405336179123,
+           -0.3849955973525366,
+           -0.3982183926895595,
+           -0.4162411624564955,
+           -0.4384020115734764,
+           -0.4639548508009387,
+           -0.49208758294535465,
+           -0.5219416051864285,
+           -0.5526321524173267,
+           -0.5832689891561521,
+           -0.6129769523391949,
+           -0.6409158542372382,
+           -0.6662992736373052,
+           -0.68841179380139,
+           -0.7066242867659323,
+           -0.7204068942345031,
+           -0.7293394143584995,
+           -0.7331188696102067,
+           -0.7315641020762406,
+           -0.7246173170585954,
+           -0.7123425720057711,
+           -0.6949212836131391,
+           -0.6726448995477936,
+           -0.6459049508452316,
+           -0.6151807648743969,
+           -0.5810251753015694,
+           -0.5440486133157373,
+           -0.5049020023417522,
+           -0.4642589056447626,
+           -0.4227973919731744,
+           -0.38118208833793094,
+           -0.3400468811186594,
+           -0.29997870715460934,
+           -0.26150284584324046,
+           -0.22507008233175682,
+           -0.19104606170397598,
+           -0.15970309592362292,
+           -0.1312146206804893,
+           -0.10565242984318018,
+           -0.08298674271595292,
+           -0.0630890855667013,
+           -0.045737895806754185,
+           -0.030626686610846776,
+           -0.01737454345327044,
+           -0.005538663680502352,
+           0.005371402632720441,
+           0.015878196351339295,
+           0.026519897401074168,
+           0.03783342059740908,
+           0.05033751437547607,
+           0.06451631786060515,
+           0.08080382026486282,
+           0.09956964372449201,
+           0.12110653697979934,
+           0.1456199235891796,
+           0.17321979576155203,
+           0.20391518471026296,
+           0.23761137219222073,
+           0.2741099372683648,
+           0.31311165908746735,
+           0.3542222225044686,
+           0.39696060046812315,
+           0.4407699171964431,
+           0.4850305309764054,
+           0.5290750166346121,
+           0.5722046768283563,
+           0.6137071696069479,
+           0.6528748082675445,
+           0.6890230691996763,
+           0.7215088347228477,
+           0.7497479011268319,
+           0.7732312971821911,
+           0.7915399849604082,
+           0.804357552261838,
+           0.8114805533951268,
+           0.8128262113326352,
+           0.8084372580084598,
+           0.7984837591657876,
+           0.7832618439850643,
+           0.7631893359122838,
+           0.7387983577731856,
+           0.7107250595037403,
+           0.6796966887803214,
+           0.6465162917023203,
+           0.6120453907950345,
+           0.5771850394552929,
+           0.5428556942503283,
+           0.5099763781303024,
+           0.47944362781524247,
+           0.4521107268377056,
+           0.4287677217275009,
+           0.41012270267895906,
+           0.3967848021093473,
+           0.38924932545384905,
+           0.3878853792784916,
+           0.3929263035099472,
+           0.40446314868616745,
+           0.42244136721916076,
+           0.44666081147563175,
+           0.4767790528742544,
+           0.5123179570830706,
+           0.5526733727043173,
+           0.5971277164511433,
+           0.6448651685656606,
+           0.6949891297907042,
+           0.7465415371125391,
+           0.7985235910588724,
+           0.8499174136500779,
+           0.8997081339827655,
+           0.946905888412252,
+           0.9905672246353797,
+           1.0298154135976518,
+           1.0638591996973479,
+           1.092009557581226,
+           1.1136940719930044,
+           1.1284686144656983,
+           1.1360260557373376,
+           1.1362018240224885,
+           1.1289761949465151,
+           1.114473277195469,
+           1.0929567368412683,
+           1.0648223809447643,
+           1.030587795527381,
+           0.9908793025241864,
+           0.9464165632013689,
+           0.8979952102187975,
+           0.8464679357268045,
+           0.792724497524311,
+           0.7376711285536932,
+           0.6822098463290203,
+           0.6272181580457095,
+           0.5735296441595258,
+           0.5219158785071304,
+           0.47307010721492154,
+           0.4275930626265761,
+           0.38598123344041285,
+           0.34861784957505815,
+           0.3157667715498857,
+           0.28756940109722795,
+           0.26404465414058775,
+           0.2450919610601896,
+           0.23049718421845358,
+           0.21994127089162724,
+           0.21301139282676063,
+           0.20921426326606077,
+           0.20799126993749054,
+           0.20873501948187512,
+           0.21080685611829209,
+           0.21355489582601098,
+           0.2163321074476374,
+           0.21851397410721035,
+           0.21951528210447002,
+           0.21880560961367368,
+           0.21592312341833353,
+           0.21048633762086164,
+           0.20220354260240345,
+           0.19087967408278686,
+           0.17642045937343895,
+           0.15883374911697254,
+           0.1382280161584065,
+           0.114808076834952,
+           0.08886816203903258,
+           0.06078253407901881,
+           0.030993908897352197,
+           2.927271359114697e-16
+          ],
+          [
+           0,
+           -0.032671498462169705,
+           -0.06518887652313904,
+           -0.09697009318366043,
+           -0.12745252404673246,
+           -0.1561098630087254,
+           -0.18246806594201315,
+           -0.20611990497745128,
+           -0.2267377375172145,
+           -0.24408413984356803,
+           -0.25802010998595076,
+           -0.26851060698709817,
+           -0.2756272622940459,
+           -0.27954817196171994,
+           -0.28055475385348705,
+           -0.2790257301466166,
+           -0.27542837027510875,
+           -0.27030720107179573,
+           -0.2642704574876163,
+           -0.2579746071732938,
+           -0.2521073338777111,
+           -0.24736940672270663,
+           -0.24445589386789,
+           -0.24403719905852467,
+           -0.2467404075175351,
+           -0.2531314233619413,
+           -0.2636983642632228,
+           -0.2788366508036332,
+           -0.29883618857559835,
+           -0.32387099147785015,
+           -0.35399153608503636,
+           -0.38912007083910777,
+           -0.4290490317541024,
+           -0.4734426401156167,
+           -0.5218416791743409,
+           -0.5736713680222687,
+           -0.6282521736560825,
+           -0.684813328594205,
+           -0.7425087531580435,
+           -0.8004350203606213,
+           -0.8576509488019237,
+           -0.9131983663747028,
+           -0.9661235560186238,
+           -1.0154988750360152,
+           -1.0604440321192499,
+           -1.1001465114548783,
+           -1.1338806509693822,
+           -1.161024911564991,
+           -1.181076915361823,
+           -1.193665882533919,
+           -1.1985621570632177,
+           -1.1956835801716104,
+           -1.1850985446701552,
+           -1.1670256421788294,
+           -1.14182989620621,
+           -1.110015655463433,
+           -1.072216301537241,
+           -1.0291810012177571,
+           -0.9817588045088678,
+           -0.9308804529155128,
+           -0.8775383174505597,
+           -0.8227649305940553,
+           -0.7676106100759825,
+           -0.7131206940186161,
+           -0.6603129161381841,
+           -0.6101554461454299,
+           -0.5635461042901587,
+           -0.5212932305644031,
+           -0.48409864911019856,
+           -0.45254311785139734,
+           -0.42707459352203414,
+           -0.40799957456220826,
+           -0.39547771045259,
+           -0.38951978776757695,
+           -0.38998912245756057,
+           -0.39660630659417495,
+           -0.4089571780103186,
+           -0.4265038048820423,
+           -0.4485982061883556,
+           -0.4744984648718895,
+           -0.5033868349576631,
+           -0.5343893982062782,
+           -0.5665967911733705,
+           -0.5990855006392366,
+           -0.6309392147893228,
+           -0.6612697194914395,
+           -0.6892368434434025,
+           -0.714066982462157,
+           -0.7350697710628503,
+           -0.7516525177642042,
+           -0.7633320780308848,
+           -0.7697439039756006,
+           -0.7706480812566266,
+           -0.7659322392362623,
+           -0.755611298525316,
+           -0.7398240985852824,
+           -0.71882702514275,
+           -0.6929848308801624,
+           -0.6627589113816976,
+           -0.6286933599445308,
+           -0.5913991781009577,
+           -0.5515370622350532,
+           -0.5097992194625909,
+           -0.4668906871892075,
+           -0.4235106399731269,
+           -0.38033416430100425,
+           -0.3379949667501185,
+           -0.2970694541719919,
+           -0.2580625866983638,
+           -0.2213958565211592,
+           -0.18739768876424,
+           -0.1562964967948377,
+           -0.12821655464739662,
+           -0.10317677562363241,
+           -0.081092410458095,
+           -0.06177960261608999,
+           -0.044962664240012676,
+           -0.030283865853832144,
+           -0.017315467953391273,
+           -0.005573664694130469,
+           0.0054659394993147896,
+           0.01635173918805771,
+           0.027638870658859338,
+           0.039871753097617736,
+           0.05356689852870134,
+           0.06919645415353354,
+           0.08717292210711823,
+           0.10783547158755541,
+           0.1314382175566525,
+           0.1581407897848898,
+           0.18800145719094796,
+           0.2209730066868115,
+           0.2569015047417593,
+           0.2955279954139219,
+           0.3364931125472977,
+           0.37934450811821013,
+           0.4235469252550824,
+           0.46849467511216053,
+           0.5135262133138149,
+           0.5579404557187151,
+           0.6010144262145001,
+           0.6420217923541645,
+           0.6802518188434121,
+           0.7150282548661054,
+           0.7457276693808886,
+           0.7717967589207918,
+           0.7927681748574454,
+           0.8082744510295188,
+           0.8180596572696719,
+           0.8219884586153093,
+           0.8200523225331792,
+           0.8123726857940501,
+           0.7992009669970317,
+           0.7809153883296832,
+           0.7580146490414545,
+           0.731108571349009,
+           0.7009059151391528,
+           0.6681996290047926,
+           0.6338498700649311,
+           0.5987651820550008,
+           0.5638822688951524,
+           0.5301448381439187,
+           0.49848201447389917,
+           0.4697868368966399,
+           0.44489535454601997,
+           0.42456682434141924,
+           0.4094654900413771,
+           0.4001443866177445,
+           0.3970315673717096,
+           0.4004190948897821,
+           0.41045507215583915,
+           0.4271389184606758,
+           0.4503200179205738,
+           0.4796997882976046,
+           0.5148371363558445,
+           0.5551571851736584,
+           0.5999630806330771,
+           0.6484506106309796,
+           0.6997253032018759,
+           0.7528216103534628,
+           0.8067237344444552,
+           0.8603876146000815,
+           0.9127635629246468,
+           0.9628190248094327,
+           1.0095609348246837,
+           1.0520571495925357,
+           1.089456461419554,
+           1.1210067307727885,
+           1.1460707210705274,
+           1.1641392746157626,
+           1.1748415324709693,
+           1.177951972091472,
+           1.1733941128639438,
+           1.1612408194712336,
+           1.1417112142763646,
+           1.115164290704623,
+           1.0820893979349824,
+           1.0430938411851427,
+           0.9988879096924349,
+           0.9502677045138567,
+           0.8980961890446918,
+           0.8432829254682159,
+           0.7867629892401803,
+           0.7294755705048693,
+           0.6723427756575836,
+           0.616249134042,
+           0.5620222942407316,
+           0.510415362126084,
+           0.46209128961787355,
+           0.4176096700466239,
+           0.37741623448365547,
+           0.3418352749227277,
+           0.31106514649607725,
+           0.2851769238229238,
+           0.26411620804114766,
+           0.24770800301596838,
+           0.23566450358922783,
+           0.22759556740057013,
+           0.22302157653798171,
+           0.2213883376653243,
+           0.222083620740028,
+           0.2244548981570309,
+           0.22782781905914384,
+           0.23152493828205473,
+           0.23488421630040437,
+           0.23727681565116487,
+           0.2381237403678214,
+           0.23691089740124885,
+           0.23320220198381994,
+           0.2266504013032713,
+           0.2170053513482183,
+           0.20411954882348843,
+           0.1879507919041691,
+           0.16856191847679597,
+           0.1461176465056578,
+           0.12087861633701417,
+           0.09319280721202142,
+           0.06348456816826152,
+           0.032241565153861215,
+           3.032858251807519e-16
+          ],
+          [
+           0,
+           -0.03358492164925728,
+           -0.06674179407333047,
+           -0.09888067743003717,
+           -0.12944104714181062,
+           -0.15790867857376362,
+           -0.18383129199670104,
+           -0.20683253373868066,
+           -0.2266239121401795,
+           -0.24301435948989392,
+           -0.25591715220590655,
+           -0.2653539895999617,
+           -0.2714561049032641,
+           -0.2744623589887232,
+           -0.2747143454571616,
+           -0.2726486134845744,
+           -0.26878619008515686,
+           -0.2637196543210771,
+           -0.25809808068277745,
+           -0.25261022572347674,
+           -0.24796637960299478,
+           -0.244879341254181,
+           -0.24404500146675,
+           -0.2461230316107846,
+           -0.25171817662134033,
+           -0.26136263917519037,
+           -0.2755000179644347,
+           -0.29447122717206997,
+           -0.31850277753973544,
+           -0.347697742920206,
+           -0.3820296713059189,
+           -0.4213396276116688,
+           -0.4653364787297141,
+           -0.5136004514636909,
+           -0.5655899128615637,
+           -0.6206512422185689,
+           -0.6780315866039593,
+           -0.736894219109636,
+           -0.796336152940163,
+           -0.8554076066188644,
+           -0.9131328674301837,
+           -0.9685320629740525,
+           -1.0206433253262253,
+           -1.0685448194410356,
+           -1.1113761074530093,
+           -1.1483583334681593,
+           -1.178812739002171,
+           -1.2021770568276837,
+           -1.218019379744918,
+           -1.226049159521992,
+           -1.2261250585487498,
+           -1.2182594509835445,
+           -1.2026194495460938,
+           -1.1795244166925518,
+           -1.149440002691426,
+           -1.1129688360594017,
+           -1.0708380718914172,
+           -1.0238840788748478,
+           -0.9730346143753287,
+           -0.9192888972451332,
+           -0.8636960384613662,
+           -0.8073323291164295,
+           -0.7512779126940382,
+           -0.696593383300101,
+           -0.6442968532193617,
+           -0.5953420217949348,
+           -0.5505977534580473,
+           -0.5108296363618279,
+           -0.47668394538668163,
+           -0.4486743754534042,
+           -0.4271718445185483,
+           -0.4123975919630983,
+           -0.4044197191206757,
+           -0.40315323635444683,
+           -0.4083635973923054,
+           -0.4196736186087556,
+           -0.43657360062107925,
+           -0.4584343939000021,
+           -0.48452308091730834,
+           -0.5140208863391089,
+           -0.5460428753947317,
+           -0.5796589600397966,
+           -0.6139157038505947,
+           -0.6478584004057818,
+           -0.6805528965918968,
+           -0.7111066418553574,
+           -0.7386884666414391,
+           -0.7625466275252473,
+           -0.782024701970398,
+           -0.7965749710931719,
+           -0.8057689928642657,
+           -0.8093051392377133,
+           -0.8070129469784234,
+           -0.798854211562125,
+           -0.7849208344622661,
+           -0.7654295144072177,
+           -0.7407134507984675,
+           -0.7112113005079086,
+           -0.67745369591923,
+           -0.6400476907071355,
+           -0.599659549024162,
+           -0.5569963322923026,
+           -0.512786764747625,
+           -0.4677618736234879,
+           -0.4226359020507818,
+           -0.37808798238513697,
+           -0.3347450350382044,
+           -0.2931663235964459,
+           -0.25383005195050823,
+           -0.21712233449337326,
+           -0.183328807577307,
+           -0.15262908095254604,
+           -0.12509415361251608,
+           -0.10068684122766582,
+           -0.07926518412084498,
+           -0.06058872750197115,
+           -0.04432749139202433,
+           -0.030073378203383985,
+           -0.017353703059587867,
+           -0.005646477220115099,
+           0.005602970194407717,
+           0.01696448146439941,
+           0.029005142734977268,
+           0.042271422685680876,
+           0.057271858792965376,
+           0.0744607585856682,
+           0.09422335729014632,
+           0.11686283589577959,
+           0.14258955588412492,
+           0.1715128098602864,
+           0.20363532254020789,
+           0.2388506656166707,
+           0.27694367474018755,
+           0.31759387911045384,
+           0.36038187594510745,
+           0.4047985053555384,
+           0.4502566078596015,
+           0.49610507875993043,
+           0.5416448726453869,
+           0.5861465588893552,
+           0.6288689865664662,
+           0.6690785857867494,
+           0.7060688128757358,
+           0.7391792396386311,
+           0.767813792354528,
+           0.7914576640564361,
+           0.8096924536553081,
+           0.822209126848684,
+           0.828818445518799,
+           0.8294585732112271,
+           0.8241996328033988,
+           0.8132450669389318,
+           0.7969297303829669,
+           0.7757147242034804,
+           0.7501790626031304,
+           0.7210083423060852,
+           0.6889806596761942,
+           0.6549500903283347,
+           0.6198281081523515,
+           0.5845633738368512,
+           0.5501203658165109,
+           0.5174573579812483,
+           0.4875042676693597,
+           0.4611409039103044,
+           0.43917613939056527,
+           0.4223285103110618,
+           0.411208716625884,
+           0.40630445184482594,
+           0.40796793767832035,
+           0.4164064755979726,
+           0.4316762564045061,
+           0.45367959185653134,
+           0.4821656511882458,
+           0.5167347019074422,
+           0.5568457706488733,
+           0.601827558100784,
+           0.6508923641192683,
+           0.7031527069982443,
+           0.7576402562349128,
+           0.8133266426011386,
+           0.8691456642578583,
+           0.9240163741344024,
+           0.9768665126569229,
+           1.0266557416664548,
+           1.072398140218768,
+           1.1131834407848988,
+           1.148196514736516,
+           1.1767346581597793,
+           1.19822228196276,
+           1.2122226726294678,
+           1.2184465603017125,
+           1.2167573074188542,
+           1.2071726120440094,
+           1.1898627032784037,
+           1.1651450897813946,
+           1.1334760043346275,
+           1.0954387656212088,
+           1.0517293510341417,
+           1.0031395396218499,
+           0.9505380406449692,
+           0.8948500693018369,
+           0.8370358658793923,
+           0.7780686770825787,
+           0.7189127280714304,
+           0.6605017105876522,
+           0.6037182965967408,
+           0.5493751585389537,
+           0.4981979373072708,
+           0.4508105484740152,
+           0.40772315735110115,
+           0.3693230857003982,
+           0.3358688390102367,
+           0.30748736506808244,
+           0.284174574037566,
+           0.2657990693923189,
+           0.25210895987586646,
+           0.2427415471062121,
+           0.23723561339090904,
+           0.2350459714879539,
+           0.2355598839805127,
+           0.23811491594863024,
+           0.24201775178380078,
+           0.2465634860875197,
+           0.2510548901081697,
+           0.2548211592762249,
+           0.25723566395517095,
+           0.2577322540829424,
+           0.2558197081850918,
+           0.251093967264552,
+           0.24324785302830926,
+           0.23207803629082396,
+           0.2174890935062283,
+           0.19949456539330973,
+           0.1782150096006235,
+           0.15387311733839346,
+           0.12678603990591875,
+           0.09735514314669037,
+           0.06605347424679892,
+           0.03341128427938393,
+           3.13024486706819e-16
+          ],
+          [
+           0,
+           -0.03439385179009143,
+           -0.06807435199169726,
+           -0.10044925332657507,
+           -0.1309659884038508,
+           -0.15912835964215033,
+           -0.1845117045864764,
+           -0.2067761246795618,
+           -0.22567741541342826,
+           -0.24107539501703457,
+           -0.25293939593571774,
+           -0.261350756633871,
+           -0.26650222885328234,
+           -0.26869429542451684,
+           -0.26832847403482585,
+           -0.26589776096963147,
+           -0.2619744437719579,
+           -0.2571955811016213,
+           -0.2522465100575989,
+           -0.2478427942689674,
+           -0.2447110688001236,
+           -0.2435692692490818,
+           -0.24510675152175304,
+           -0.2499648151239101,
+           -0.25871813622771545,
+           -0.27185759736683157,
+           -0.2897749688397322,
+           -0.3127498535117295,
+           -0.3409392527511039,
+           -0.37437004802845103,
+           -0.4129346217994848,
+           -0.45638976442433,
+           -0.5043589329472843,
+           -0.5563378445722866,
+           -0.6117033046787327,
+           -0.6697250882925481,
+           -0.7295806170747657,
+           -0.7903721030338082,
+           -0.8511457670836486,
+           -0.9109126868442625,
+           -0.9686707850720374,
+           -1.0234274389117104,
+           -1.0742221715845504,
+           -1.1201488826658608,
+           -1.1603770809317508,
+           -1.194171604716269,
+           -1.2209103483368142,
+           -1.2400995586271544,
+           -1.251386321878305,
+           -1.2545679271762245,
+           -1.2495978656554059,
+           -1.2365883047779183,
+           -1.2158089604653706,
+           -1.187682375720061,
+           -1.1527757001805943,
+           -1.11178914877369,
+           -1.0655413972038432,
+           -1.014952245521996,
+           -0.9610229466363039,
+           -0.9048146527677867,
+           -0.8474254781371954,
+           -0.7899667094884965,
+           -0.733538716593073,
+           -0.6792071221337462,
+           -0.6279797841612994,
+           -0.580785124799264,
+           -0.5384523065231797,
+           -0.5016937129489821,
+           -0.4710901357179049,
+           -0.4470790041154045,
+           -0.4299459210971855,
+           -0.41981969019936477,
+           -0.4166709343164302,
+           -0.42031432157786836,
+           -0.43041432763323073,
+           -0.4464943796591759,
+           -0.46794914737400195,
+           -0.49405967222885083,
+           -0.5240109595359074,
+           -0.5569116011964587,
+           -0.5918149502784329,
+           -0.6277413340721991,
+           -0.6637007702410801,
+           -0.6987156417844199,
+           -0.7318427909268294,
+           -0.7621945095914833,
+           -0.7889579343374793,
+           -0.8114123957599221,
+           -0.8289443252930279,
+           -0.8410593847826139,
+           -0.8473915545355282,
+           -0.8477089920475382,
+           -0.8419165543482835,
+           -0.8300549598708495,
+           -0.8122966488931381,
+           -0.7889384828472031,
+           -0.7603915001417859,
+           -0.7271680176844347,
+           -0.6898664312634614,
+           -0.6491541227894648,
+           -0.6057489267649716,
+           -0.5603996411762308,
+           -0.5138660885009905,
+           -0.46689924022669266,
+           -0.42022191302203427,
+           -0.3745105266723233,
+           -0.33037838356547683,
+           -0.2883608876975991,
+           -0.24890306893772157,
+           -0.2123497169922497,
+           -0.17893836070781005,
+           -0.1487952537990868,
+           -0.1219344496799638,
+           -0.09825996780035223,
+           -0.077570973780046,
+           -0.05956981771094431,
+           -0.04387270123890781,
+           -0.030022676298501322,
+           -0.017504618367200176,
+           -0.005761766343455591,
+           0.005786619085052269,
+           0.01772695541672183,
+           0.030632889927899035,
+           0.045047199918923544,
+           0.06146452964760984,
+           0.08031543043749594,
+           0.1019521369041862,
+           0.12663646754700786,
+           0.1545301832323629,
+           0.18568807372999416,
+           0.2200539720531231,
+           0.25745982067576556,
+           0.29762783466744064,
+           0.3401757263953832,
+           0.3846248767316748,
+           0.4304112606877253,
+           0.47689886303578466,
+           0.523395253607459,
+           0.5691689342625897,
+           0.6134680214758791,
+           0.6555397913310831,
+           0.6946505884101736,
+           0.7301055872886754,
+           0.7612678954570457,
+           0.7875764995179162,
+           0.808562582173404,
+           0.8238637752120563,
+           0.8332359625257231,
+           0.8365623059474216,
+           0.8338592339657932,
+           0.8252792074887091,
+           0.8111101559717233,
+           0.7917715594412457,
+           0.7678072351909094,
+           0.7398749701462772,
+           0.7087332190315985,
+           0.6752251625590118,
+           0.6402604870420421,
+           0.6047953054253888,
+           0.5698106882446582,
+           0.5362903102519196,
+           0.5051977434115942,
+           0.4774539390327722,
+           0.4539154406229951,
+           0.4353538546151677,
+           0.422437078750927,
+           0.41571274823719756,
+           0.4155943087689143,
+           0.4223500643519148,
+           0.4360954780395642,
+           0.45678892690353334,
+           0.48423103065610634,
+           0.518067588319247,
+           0.5577960712644988,
+           0.6027755359256604,
+           0.6522397375879937,
+           0.7053131498835364,
+           0.7610295248480784,
+           0.8183525673280407,
+           0.8761982466582656,
+           0.9334582291101501,
+           0.9890238875980767,
+           1.041810331193035,
+           1.0907798964666109,
+           1.1349645555901744,
+           1.1734867221273588,
+           1.2055779739466732,
+           1.2305952627041636,
+           1.2480342396795883,
+           1.2575393969188764,
+           1.2589107989496044,
+           1.2521072619307823,
+           1.2372459219809577,
+           1.2145982205287214,
+           1.184582419748462,
+           1.1477528434070687,
+           1.1047861157546304,
+           1.056464741568595,
+           1.0036584324013171,
+           0.9473036359923453,
+           0.888381766445149,
+           0.8278966611677445,
+           0.7668518060756433,
+           0.7062278728094816,
+           0.6469611007112472,
+           0.5899230323415574,
+           0.535902075033934,
+           0.48558731330069216,
+           0.4395549390389285,
+           0.3982575998925963,
+           0.3620168924788012,
+           0.33101914832499657,
+           0.3053145782553117,
+           0.2848197576514176,
+           0.2693233525636671,
+           0.25849490710351525,
+           0.2518964378731218,
+           0.2489965132218934,
+           0.24918643553098221,
+           0.2517980949716099,
+           0.2561230244696675,
+           0.26143215886777904,
+           0.26699578713670025,
+           0.2721031852647348,
+           0.27608142913750555,
+           0.27831291097955074,
+           0.2782511191180763,
+           0.2754342880053134,
+           0.2694965823829163,
+           0.2601765447308466,
+           0.2473226070493509,
+           0.2308955447466853,
+           0.2109678300000347,
+           0.18771992240548238,
+           0.16143361399938308,
+           0.1324826218141874,
+           0.10132069210514467,
+           0.06846754445904935,
+           0.03449303955608977,
+           3.2185903167018804e-16
+          ],
+          [
+           0,
+           -0.03509139048347859,
+           -0.06917556241027943,
+           -0.10166383102964846,
+           -0.1320176142505793,
+           -0.15976474418722147,
+           -0.18451396921030808,
+           -0.20596725166231655,
+           -0.22392952329461152,
+           -0.2383156261391808,
+           -0.24915423927761737,
+           -0.256588669977727,
+           -0.2608744689616217,
+           -0.2623739120919448,
+           -0.2615474724254318,
+           -0.25894248531505676,
+           -0.2551792830444549,
+           -0.25093514247321425,
+           -0.24692644764957947,
+           -0.24388951780991378,
+           -0.2425605883828718,
+           -0.24365545758211732,
+           -0.24784932324117306,
+           -0.2557573333763009,
+           -0.2679163595478312,
+           -0.2847684747484684,
+           -0.3066465779242802,
+           -0.3337625562842708,
+           -0.36619831551669246,
+           -0.40389993839825034,
+           -0.4466751557675501,
+           -0.4941942323234763,
+           -0.5459942852183707,
+           -0.6014869680394187,
+           -0.6599693686309649,
+           -0.720637888400981,
+           -0.7826047952942942,
+           -0.8449170743927693,
+           -0.9065771408326289,
+           -0.9665649309075904,
+           -1.0238608500941804,
+           -1.0774690322465406,
+           -1.1264403530057128,
+           -1.169894642869382,
+           -1.2070415613533578,
+           -1.237199622891974,
+           -1.2598129068897852,
+           -1.2744650376602034,
+           -1.2808900835899961,
+           -1.2789800972188805,
+           -1.2687890972700075,
+           -1.2505333780846681,
+           -1.2245881193502122,
+           -1.191480357334537,
+           -1.1518784658993424,
+           -1.106578379232448,
+           -1.056486866472205,
+           -1.0026022392814562,
+           -0.9459929352300942,
+           -0.8877744710507042,
+           -0.829085299186915,
+           -0.7710621275935647,
+           -0.7148152758207095,
+           -0.6614046396976424,
+           -0.6118168224443059,
+           -0.5669439621284735,
+           -0.5275647447391484,
+           -0.4943280397527282,
+           -0.4677395322086296,
+           -0.4481516535212843,
+           -0.4357570342889514,
+           -0.4305856181450964,
+           -0.4325054882901293,
+           -0.44122736987182554,
+           -0.4563126840072328,
+           -0.47718494508374026,
+           -0.5031442140871275,
+           -0.5333842489930799,
+           -0.5670119304601344,
+           -0.6030684886896832,
+           -0.6405520166269442,
+           -0.6784407266318379,
+           -0.7157163930033992,
+           -0.751387421620951,
+           -0.7845110004588187,
+           -0.8142138104928324,
+           -0.8397108148742223,
+           -0.8603216942181374,
+           -0.8754845561745671,
+           -0.8847666166000208,
+           -0.8878716258959178,
+           -0.8846438955192153,
+           -0.87506886427338,
+           -0.8592702296506244,
+           -0.8375037540951202,
+           -0.8101479374988024,
+           -0.7776918235163656,
+           -0.7407202765173586,
+           -0.6998971264831128,
+           -0.6559466294282323,
+           -0.6096337297617327,
+           -0.5617436374703069,
+           -0.5130612464846833,
+           -0.46435092078399776,
+           -0.4163371617389562,
+           -0.3696866442599936,
+           -0.3249920711900586,
+           -0.2827582460556464,
+           -0.24339070503507285,
+           -0.2071871813370028,
+           -0.1743321008307053,
+           -0.14489422862275636,
+           -0.11882750434112387,
+           -0.09597502124186036,
+           -0.07607602298645341,
+           -0.05877571410236886,
+           -0.043637607700330365,
+           -0.030158068806354323,
+           -0.01778265531833217,
+           -0.005923812535305653,
+           0.006020557408037114,
+           0.018648152168070094,
+           0.03253346226887952,
+           0.04820960732775076,
+           0.06615130542137022,
+           0.0867594362834055,
+           0.11034761786910659,
+           0.13713116385307916,
+           0.1672187281546483,
+           0.2006068731635299,
+           0.2371777227204909,
+           0.27669978100417925,
+           0.3188319163069158,
+           0.36313042632847164,
+           0.40905902116409687,
+           0.4560014836525152,
+           0.5032766961257764,
+           0.5501556596651326,
+           0.5958800783244035,
+           0.6396820378124635,
+           0.6808042769419074,
+           0.7185205315702912,
+           0.7521554252873238,
+           0.7811033889127513,
+           0.8048461118092523,
+           0.8229680615976595,
+           0.8351696542860702,
+           0.8412777129900111,
+           0.8412529189571835,
+           0.8351940319099292,
+           0.8233387359766154,
+           0.8060610507422324,
+           0.7838653321471282,
+           0.7573769729864713,
+           0.7273299954967168,
+           0.6945518068959886,
+           0.659945460813438,
+           0.6244698314907162,
+           0.5891181618567372,
+           0.5548954896917905,
+           0.5227954870085854,
+           0.4937772656840276,
+           0.4687427067952763,
+           0.44851486189742534,
+           0.433817951814934,
+           0.4252594529237899,
+           0.4233147132149352,
+           0.4283144817901924,
+           0.44043566725927435,
+           0.45969556442759335,
+           0.48594970653315034,
+           0.5188934141019756,
+           0.5580670233429584,
+           0.6028646890430689,
+           0.6525465712990024,
+           0.7062541342227987,
+           0.7630282099717683,
+           0.821829414906567,
+           0.8815604480043127,
+           0.9410897562344228,
+           0.999276018556485,
+           1.0549928803325521,
+           1.1071533637489264,
+           1.154733387468263,
+           1.1967938499972637,
+           1.2325007656390206,
+           1.2611429885632357,
+           1.2821471183316073,
+           1.2950892477474618,
+           1.299703289508388,
+           1.2958856999817203,
+           1.2836965044974011,
+           1.2633566167609744,
+           1.2352415331812696,
+           1.1998715689349586,
+           1.1578988843615579,
+           1.1100916258124813,
+           1.0573155725369983,
+           1.0005137389474699,
+           0.9406844282781367,
+           0.8788582681220798,
+           0.8160747797878846,
+           0.7533590413704615,
+           0.6916989987218606,
+           0.6320239593168643,
+           0.575184771845094,
+           0.5219361500562644,
+           0.47292154406456105,
+           0.4286608973786447,
+           0.3895415549966824,
+           0.35581250881535725,
+           0.32758208332175837,
+           0.30481907913906636,
+           0.2873573066017627,
+           0.2749033582583389,
+           0.2670473900972572,
+           0.263276608314603,
+           0.26299109338224647,
+           0.26552153762544284,
+           0.2701484278303506,
+           0.276122171653378,
+           0.2826836465739634,
+           0.28908464328016353,
+           0.29460768183208486,
+           0.2985846985090817,
+           0.30041413338299633,
+           0.2995759925282423,
+           0.29564451324522284,
+           0.2882981243375736,
+           0.27732646471976774,
+           0.26263430062571025,
+           0.2442422624857338,
+           0.22228440509087352,
+           0.19700267688001702,
+           0.16873846398930123,
+           0.13792145007855863,
+           0.10505610199489537,
+           0.07070615230775928,
+           0.03547750111680778,
+           3.297132057972448e-16
+          ],
+          [
+           0,
+           -0.03567171413132461,
+           -0.07003678288586532,
+           -0.10251617084882317,
+           -0.1325914129219556,
+           -0.15982036001812927,
+           -0.18385083366446073,
+           -0.20443181673553823,
+           -0.22142187126668977,
+           -0.23479454604673136,
+           -0.24464061464654951,
+           -0.25116706673310585,
+           -0.25469285986854595,
+           -0.2556415233654149,
+           -0.25453078802312434,
+           -0.25195949362022885,
+           -0.24859209789736866,
+           -0.24514117460549717,
+           -0.24234834238073905,
+           -0.24096410934845788,
+           -0.24172714933746456,
+           -0.2453435435867585,
+           -0.25246652636178524,
+           -0.2636772638116823,
+           -0.2794671728810463,
+           -0.30022225166381,
+           -0.3262098451013662,
+           -0.35756821153394125,
+           -0.3942991877403179,
+           -0.43626417441310683,
+           -0.4831835823803363,
+           -0.5346397943171949,
+           -0.5900836093148365,
+           -0.648844050656693,
+           -0.7101413326632503,
+           -0.7731027026122721,
+           -0.8367808005214106,
+           -0.900174114832169,
+           -0.9622490573905563,
+           -1.0219631379659482,
+           -1.0782886879896492,
+           -1.1302365660231624,
+           -1.176879274148528,
+           -1.2173729251333885,
+           -1.2509775246404966,
+           -1.2770750703647027,
+           -1.2951850199023711,
+           -1.304976740196672,
+           -1.3062786220889024,
+           -1.2990836221329378,
+           -1.2835510784907762,
+           -1.2600047363646258,
+           -1.2289270088768687,
+           -1.1909495893780868,
+           -1.1468406186461155,
+           -1.0974886931981183,
+           -1.0438840769486162,
+           -0.9870975458486978,
+           -0.928257352284176,
+           -0.8685248414922064,
+           -0.809069284961096,
+           -0.751042514902565,
+           -0.6955539489586415,
+           -0.6436465851987891,
+           -0.5962745243965953,
+           -0.5542825401106133,
+           -0.5183881681200001,
+           -0.48916672647769815,
+           -0.4670396073137547,
+           -0.45226610326127265,
+           -0.4449389468973519,
+           -0.4449836529527543,
+           -0.45216166240819144,
+           -0.4660771971707792,
+           -0.4861876460124499,
+           -0.5118172189926982,
+           -0.5421735307064612,
+           -0.5763667042559448,
+           -0.6134305294946296,
+           -0.6523451622347685,
+           -0.6920608168635168,
+           -0.7315218839837521,
+           -0.7696908977579653,
+           -0.805571784719861,
+           -0.8382318467152772,
+           -0.866821964789053,
+           -0.8905945573694323,
+           -0.9089188838346556,
+           -0.9212933520225628,
+           -0.9273545637702238,
+           -0.9268829142592256,
+           -0.9198046467570917,
+           -0.9061903521529272,
+           -0.8862499903077591,
+           -0.8603245955086251,
+           -0.8288749091252481,
+           -0.7924672569292518,
+           -0.7517570546234619,
+           -0.7074703813275363,
+           -0.6603841057102987,
+           -0.6113050820662278,
+           -0.5610489531306327,
+           -0.5104191023707606,
+           -0.4601862907730855,
+           -0.41106949200600373,
+           -0.3637184058430224,
+           -0.3186980837748768,
+           -0.27647604400842335,
+           -0.23741218700149108,
+           -0.20175174900279078,
+           -0.16962145162985087,
+           -0.1410289223421383,
+           -0.11586537585856126,
+           -0.09391146227376133,
+           -0.07484610597578842,
+           -0.058258082519568814,
+           -0.0436600103064188,
+           -0.03050437203084702,
+           -0.018201128940107097,
+           -0.006136450315152936,
+           0.006307947755177493,
+           0.019735375561023005,
+           0.034715178106373035,
+           0.05176469027298633,
+           0.07133262584328005,
+           0.09378435024052431,
+           0.1193894380928716,
+           0.14831185762809657,
+           0.1806030559519993,
+           0.21619814417260938,
+           0.25491530100299314,
+           0.2964584299391805,
+           0.34042302048072526,
+           0.38630508028343385,
+           0.43351292472640895,
+           0.48138153518123167,
+           0.5291891292036784,
+           0.576175526665306,
+           0.6215618470208312,
+           0.6645710357262923,
+           0.7044486932513412,
+           0.7404836688208446,
+           0.7720278832986927,
+           0.7985148614734203,
+           0.8194764830635702,
+           0.8345575033422541,
+           0.8435274473818192,
+           0.8462895452475492,
+           0.8428864474722605,
+           0.8335025390499429,
+           0.8184627540484222,
+           0.7982278796826662,
+           0.7733864261596414,
+           0.7446432246273763,
+           0.7128049979908138,
+           0.6787632261352295,
+           0.643474696300269,
+           0.6079401892332452,
+           0.5731818008058294,
+           0.5402194357545743,
+           0.5100470341511264,
+           0.48360910148981495,
+           0.4617781096032919,
+           0.44533331802948645,
+           0.4349415343474069,
+           0.43114028810153743,
+           0.4343238372876308,
+           0.4447323603111226,
+           0.46244461144596966,
+           0.4873742359293389,
+           0.5192698539141073,
+           0.5577189326808651,
+           0.6021553759725314,
+           0.6518706702670886,
+           0.7060283424220063,
+           0.7636814034954632,
+           0.823792381622764,
+           0.8852554843627395,
+           0.9469203794590922,
+           1.0076170437480705,
+           1.066181103949349,
+           1.1214790809410722,
+           1.1724329511430547,
+           1.2180434547679366,
+           1.2574116105572761,
+           1.289757939470011,
+           1.3144389545896413,
+           1.330960539925818,
+           1.3389879152090178,
+           1.3383519653968805,
+           1.3290518004357077,
+           1.3112535007327208,
+           1.2852850946019898,
+           1.251627903438036,
+           1.2109044763685999,
+           1.1638634165530337,
+           1.1113614741755884,
+           1.0543433447713295,
+           0.9938196642846545,
+           0.9308437329331652,
+           0.8664875275680357,
+           0.8018175761438618,
+           0.7378712678319592,
+           0.675634158271757,
+           0.6160188018394969,
+           0.5598456023393055,
+           0.5078261212226317,
+           0.4605492196400058,
+           0.4184703389033493,
+           0.3819041450837103,
+           0.35102067945593574,
+           0.32584506942028096,
+           0.3062607665432039,
+           0.29201619164617154,
+           0.28273458357523684,
+           0.2779267704594474,
+           0.2770065118260689,
+           0.2793079986105414,
+           0.2841050473742138,
+           0.2906314861510292,
+           0.2981022032161123,
+           0.3057343173149787,
+           0.3127679287876886,
+           0.3184859255021255,
+           0.32223234517015087,
+           0.32342883572656916,
+           0.3215888069606251,
+           0.316328928177012,
+           0.3073776967514714,
+           0.29458087924876764,
+           0.27790370833589184,
+           0.2574298029823981,
+           0.2333568642597544,
+           0.20598928228811336,
+           0.17572786943027202,
+           0.1430570086919019,
+           0.10852957259284647,
+           0.07275002485656333,
+           0.03635616368728039,
+           3.3651968076615236e-16
+          ],
+          [
+           0,
+           -0.036130167273643744,
+           -0.07065187134919688,
+           -0.103001964072814,
+           -0.13268826266847558,
+           -0.15930454037133007,
+           -0.1825431510207604,
+           -0.20220494182958407,
+           -0.21820617880864518,
+           -0.23058228675760037,
+           -0.23948828837434943,
+           -0.24519591279616554,
+           -0.2480874305937267,
+           -0.24864635769769752,
+           -0.24744525277818613,
+           -0.2451309091358048,
+           -0.2424073112504352,
+           -0.24001678600623721,
+           -0.23871982773396905,
+           -0.2392741133171669,
+           -0.24241324772965403,
+           -0.24882579086497641,
+           -0.25913511308112636,
+           -0.2738806095624597,
+           -0.29350077278908926,
+           -0.3183185788349399,
+           -0.3485295879424351,
+           -0.3841930941927914,
+           -0.425226584716073,
+           -0.47140368759644385,
+           -0.5223557014339609,
+           -0.577576710560145,
+           -0.6364322003797056,
+           -0.6981709994534052,
+           -0.7619402909391224,
+           -0.8268033579705701,
+           -0.8917596574337397,
+           -0.9557667561655553,
+           -1.0177636143769864,
+           -1.076694664348973,
+           -1.1315341091129656,
+           -1.181309856527755,
+           -1.2251265091737107,
+           -1.2621868497249784,
+           -1.291811294498009,
+           -1.3134548339386451,
+           -1.3267210368042568,
+           -1.3313727633308763,
+           -1.3273393100944555,
+           -1.314719793705419,
+           -1.2937826698661663,
+           -1.2649613764968026,
+           -1.2288461823479808,
+           -1.1861724135084097,
+           -1.1378053172544143,
+           -1.0847219036509639,
+           -1.0279901782152372,
+           -0.9687462420086503,
+           -0.9081697871846945,
+           -0.8474585550191508,
+           -0.7878023488275832,
+           -0.7303572053059006,
+           -0.6762203244364625,
+           -0.6264063402624857,
+           -0.581825482979484,
+           -0.543264137698989,
+           -0.5113682480058284,
+           -0.4866299444516886,
+           -0.4693777010628941,
+           -0.45977023866966094,
+           -0.45779430444281277,
+           -0.4632663646326326,
+           -0.4758381543943891,
+           -0.4950059370232164,
+           -0.5201232371342804,
+           -0.5504167304444852,
+           -0.5850048988239216,
+           -0.6229189949774576,
+           -0.6631258080376737,
+           -0.7045516807707941,
+           -0.7461072019787202,
+           -0.7867119846527476,
+           -0.8253189417797192,
+           -0.8609374873476799,
+           -0.8926551196218014,
+           -0.9196568863979654,
+           -0.9412422866050759,
+           -0.9568392279373998,
+           -0.9660147345154034,
+           -0.9684821800384886,
+           -0.9641049084747377,
+           -0.9528961938777947,
+           -0.9350155812076819,
+           -0.9107617388255934,
+           -0.8805620384394705,
+           -0.8449591576010229,
+           -0.8045950714473733,
+           -0.7601928624899641,
+           -0.7125368283675112,
+           -0.6624514063632306,
+           -0.6107794592112216,
+           -0.5583604786842545,
+           -0.5060092614111278,
+           -0.45449559541216117,
+           -0.404525466409066,
+           -0.35672425083936204,
+           -0.31162230877979846,
+           -0.26964332604065205,
+           -0.2310956821689531,
+           -0.19616704184135753,
+           -0.16492228315017912,
+           -0.13730478971745524,
+           -0.11314104660245851,
+           -0.09214839479516305,
+           -0.07394571786138042,
+           -0.058066759072232924,
+           -0.043975700006269644,
+           -0.031084573851278614,
+           -0.018772039906745076,
+           -0.00640301127001895,
+           0.00665139375540471,
+           0.020994113827166486,
+           0.03718315163976523,
+           0.0557138376313147,
+           0.0770028292873945,
+           0.10137427993578618,
+           0.12904855467882884,
+           0.16013380511117267,
+           0.19462064038900279,
+           0.23238005192594663,
+           0.27316466452218313,
+           0.3166133002246326,
+           0.3622587548587865,
+           0.4095386031562533,
+           0.4578087688593825,
+           0.5063595231384493,
+           0.5544335099699493,
+           0.6012453424512431,
+           0.6460022707726505,
+           0.6879253918538781,
+           0.7262708532854092,
+           0.7603505006716815,
+           0.7895514278799732,
+           0.8133539138364779,
+           0.8313472668137419,
+           0.8432431467258258,
+           0.848885996584662,
+           0.8482602844893644,
+           0.8414943355933932,
+           0.8288606174963828,
+           0.8107724303596185,
+           0.7877770425675665,
+           0.7605454017268047,
+           0.7298586369912643,
+           0.696591649975634,
+           0.6616941658313659,
+           0.6261696815444735,
+           0.5910528035183943,
+           0.557385509632084,
+           0.5261929011073777,
+           0.4984590258945671,
+           0.4751033574429015,
+           0.45695850056659887,
+           0.4447496699030954,
+           0.4390764467925252,
+           0.44039726822263486,
+           0.4490170380286232,
+           0.46507817734000034,
+           0.48855535009585055,
+           0.5192540122746796,
+           0.5568128424247197,
+           0.6007100183531686,
+           0.6502732127003207,
+           0.7046930908375275,
+           0.7630400102691164,
+           0.8242835435503828,
+           0.8873143785466315,
+           0.9509680923237998,
+           1.0140502494913592,
+           1.075362243530345,
+           1.133727281328471,
+           1.1880159072634273,
+           1.237170473824433,
+           1.2802279906851093,
+           1.3163408227327889,
+           1.3447947588799642,
+           1.3650240362821802,
+           1.3766229773309302,
+           1.3793539777054185,
+           1.3731516708793932,
+           1.3581231856642482,
+           1.3345445064044796,
+           1.3028530380601098,
+           1.2636365683591673,
+           1.2176189042953698,
+           1.1656425384173463,
+           1.1086487697136114,
+           1.0476557627684688,
+           0.9837350758338523,
+           0.917987222411579,
+           0.8515168510711104,
+           0.7854081340826704,
+           0.7207009469190551,
+           0.6583683980202681,
+           0.59929623201916,
+           0.5442645808214429,
+           0.49393247675737123,
+           0.4488254719892533,
+           0.4093266302239361,
+           0.3756710724937748,
+           0.34794417043171166,
+           0.32608339027085,
+           0.3098837009810853,
+           0.299006372736424,
+           0.2929909094375613,
+           0.29126978332408027,
+           0.29318557265497397,
+           0.29801004665215103,
+           0.30496469676721,
+           0.3132421809320951,
+           0.3220281285550217,
+           0.33052274905164675,
+           0.3379616957374284,
+           0.34363565967999893,
+           0.3469082040074111,
+           0.3472313972497812,
+           0.344158863315645,
+           0.33735593415659615,
+           0.32660666730687066,
+           0.3118175723621374,
+           0.2930179760060275,
+           0.27035704223764395,
+           0.24409755079758652,
+           0.21460662025352242,
+           0.18234364068394965,
+           0.1478457524129776,
+           0.11171126999941486,
+           0.07458150309202646,
+           0.0371214665128916,
+           3.4222105640597696e-16
+          ],
+          [
+           0,
+           -0.036463343538006225,
+           -0.07101731383197106,
+           -0.1031209700024248,
+           -0.1323145386280695,
+           -0.1582334605573084,
+           -0.1806198067653196,
+           -0.19933074930493505,
+           -0.21434384981700266,
+           -0.2257590106847514,
+           -0.23379702064576713,
+           -0.23879471531840302,
+           -0.24119686141066132,
+           -0.24154495911900264,
+           -0.24046323821475937,
+           -0.23864219749652932,
+           -0.23682010276645846,
+           -0.23576291359134083,
+           -0.23624315241898297,
+           -0.23901826001346974,
+           -0.24480899784944732,
+           -0.2542784606079675,
+           -0.26801225014199515,
+           -0.28650033648353407,
+           -0.3101210922532276,
+           -0.3391279351512686,
+           -0.37363895031345923,
+           -0.41362979174933656,
+           -0.45893008162643323,
+           -0.5092234398129608,
+           -0.5640511859788131,
+           -0.6228196649191577,
+           -0.6848110548859118,
+           -0.7491974308568157,
+           -0.8150577720360574,
+           -0.8813975275363134,
+           -0.9471702880351046,
+           -1.0113010559002018,
+           -1.0727105632457936,
+           -1.1303400577183242,
+           -1.1831759602954148,
+           -1.230273798441,
+           -1.2707808316637736,
+           -1.3039568145812035,
+           -1.3291923843497935,
+           -1.346024613796694,
+           -1.3541493374752762,
+           -1.3534299335815516,
+           -1.3439023283779719,
+           -1.325776079445121,
+           -1.2994314875389246,
+           -1.2654127817938723,
+           -1.2244175171636666,
+           -1.1772824140288412,
+           -1.1249659555990186,
+           -1.0685281369968882,
+           -1.0091078288130688,
+           -0.9478982757754023,
+           -0.8861212965609898,
+           -0.8250007825782008,
+           -0.7657361109738842,
+           -0.7094760897452754,
+           -0.6572940405858657,
+           -0.6101645982631213,
+           -0.5689427645641957,
+           -0.5343457011446334,
+           -0.5069376802832376,
+           -0.4871185371757142,
+           -0.47511588382863973,
+           -0.4709812548811306,
+           -0.4745902619719486,
+           -0.48564673786800316,
+           -0.5036907567994117,
+           -0.5281103256120028,
+           -0.5581564536818916,
+           -0.5929612301406755,
+           -0.6315584667557067,
+           -0.6729064054912941,
+           -0.7159119427680536,
+           -0.7594557888589938,
+           -0.8024179615008319,
+           -0.8437030080956782,
+           -0.8822643609082083,
+           -0.9171272541418575,
+           -0.9474096700632999,
+           -0.9723408324590024,
+           -0.991276828357182,
+           -1.0037130115584008,
+           -1.0092929222708722,
+           -1.0078135440277087,
+           -0.9992268099116809,
+           -0.9836373626734554,
+           -0.961296665310147,
+           -0.932593647799497,
+           -0.8980421597647245,
+           -0.8582655758095107,
+           -0.8139789682265559,
+           -0.7659693190893316,
+           -0.7150742889963461,
+           -0.6621600918642764,
+           -0.6080990434042,
+           -0.5537473548544234,
+           -0.49992373313248145,
+           -0.4473893241137782,
+           -0.3968294979012206,
+           -0.3488379247084118,
+           -0.3039033286355494,
+           -0.2623992357447385,
+           -0.2245769542479818,
+           -0.19056194030500684,
+           -0.16035361502769213,
+           -0.13382860902810859,
+           -0.110747322483648,
+           -0.09076360345551317,
+           -0.07343726723444528,
+           -0.05824910681344173,
+           -0.04461798102941786,
+           -0.031919514071113424,
+           -0.019505899245116462,
+           -0.006726272147561012,
+           0.007052895601652737,
+           0.022427930796607612,
+           0.03993915579113388,
+           0.0600536549648833,
+           0.08315007618329044,
+           0.10950588000959806,
+           0.13928738587526696,
+           0.17254289183537483,
+           0.20919906476481567,
+           0.24906071290794732,
+           0.29181396472933807,
+           0.33703278925443875,
+           0.3841887057863751,
+           0.4326634472542999,
+           0.4817642636151534,
+           0.5307414816767922,
+           0.5788078772250523,
+           0.6251593659717355,
+           0.6689964828685577,
+           0.7095460957184166,
+           0.7460827893908971,
+           0.7779493615947163,
+           0.8045758899993812,
+           0.8254968630995798,
+           0.8403659128008464,
+           0.8489677441695533,
+           0.8512269257303943,
+           0.8472132804415561,
+           0.8371437011394482,
+           0.821380302751895,
+           0.8004249147367344,
+           0.7749100087457648,
+           0.7455862461619155,
+           0.713306915671399,
+           0.6790096102720934,
+           0.643695564094163,
+           0.6084071303301294,
+           0.5742039308952663,
+           0.5421382449056537,
+           0.5132302257263633,
+           0.48844354460174877,
+           0.4686620524842941,
+           0.4546680307401883,
+           0.4471225664007178,
+           0.4465485393687618,
+           0.4533166486276805,
+           0.46763483348478646,
+           0.48954136592753644,
+           0.5189018032146626,
+           0.5554098979794126,
+           0.598592468623902,
+           0.6478181379372013,
+           0.7023097549912484,
+           0.7611602267294633,
+           0.8233514034322583,
+           0.8877755884367434,
+           0.9532591789147563,
+           1.0185878927347152,
+           1.0825329977221552,
+           1.143877934944155,
+           1.2014447175857104,
+           1.2541194918133567,
+           1.300876665622002,
+           1.340801045560908,
+           1.373107468611112,
+           1.3971574761856431,
+           1.412472647790833,
+           1.418744291601718,
+           1.4158392761227938,
+           1.4038018791085234,
+           1.3828516247633362,
+           1.3533771756182402,
+           1.3159264390689853,
+           1.271193138083565,
+           1.2200001788710453,
+           1.1632802233312398,
+           1.1020539390623303,
+           1.0374064530272418,
+           0.9704625753935564,
+           0.9023613866084087,
+           0.8342307928344163,
+           0.7671626521965097,
+           0.7021890569776804,
+           0.6402603254182545,
+           0.5822252119308088,
+           0.5288137874810958,
+           0.4806233740430074,
+           0.43810784011393755,
+           0.40157048019803143,
+           0.37116061202315337,
+           0.3468739332678374,
+           0.32855658701756973,
+           0.3159127943347836,
+           0.30851582545548706,
+           0.3058220003555259,
+           0.30718733674316556,
+           0.3118864007086158,
+           0.3191328638230707,
+           0.32810123167104965,
+           0.3379491835444113,
+           0.3478399519091771,
+           0.35696417350834353,
+           0.3645606614575367,
+           0.3699355789430664,
+           0.3724795393181051,
+           0.3716822133658434,
+           0.3671440908187634,
+           0.3585851181953993,
+           0.34585001673063626,
+           0.32891017055798677,
+           0.3078620641639071,
+           0.28292233722760074,
+           0.2544196120352835,
+           0.2227833315190892,
+           0.18852992253039827,
+           0.15224666728850478,
+           0.11457372433036789,
+           0.07618478725972758,
+           0.03776690397649118,
+           3.467707609450149e-16
+          ],
+          [
+           0,
+           -0.03666915311860848,
+           -0.07113232317433292,
+           -0.10287710709960284,
+           -0.13148215645814393,
+           -0.15663009435394062,
+           -0.1781175498816211,
+           -0.19586203268135832,
+           -0.20990545226902652,
+           -0.22041417404520225,
+           -0.22767559403533502,
+           -0.23209130519377957,
+           -0.23416701721434866,
+           -0.23449947696756304,
+           -0.23376071576442928,
+           -0.23268002061396542,
+           -0.23202408768392763,
+           -0.2325758657256025,
+           -0.23511263400491605,
+           -0.24038388233321495,
+           -0.24908956949483047,
+           -0.2618593304669286,
+           -0.2792331824280747,
+           -0.30164424512697097,
+           -0.32940394355583336,
+           -0.3626901012000207,
+           -0.4015382618766959,
+           -0.4458364990582592,
+           -0.4953238855538316,
+           -0.5495927056237403,
+           -0.6080943982812282,
+           -0.6701491270139216,
+           -0.7349587797666862,
+           -0.8016231160513884,
+           -0.8691586976672722,
+           -0.936520167748571,
+           -1.0026233815148902,
+           -1.0663698427412494,
+           -1.1266718638513569,
+           -1.18247784560708,
+           -1.232797065207445,
+           -1.276723369445842,
+           -1.3134571922580405,
+           -1.3423253530127515,
+           -1.3627981423819315,
+           -1.3745032653776186,
+           -1.377236284648144,
+           -1.3709672896141878,
+           -1.3558436064947088,
+           -1.3321884585496868,
+           -1.3004955826542883,
+           -1.2614199052560662,
+           -1.2157644754841634,
+           -1.1644639433602386,
+           -1.1085649544957714,
+           -1.0492039073041404,
+           -0.9875825827758571,
+           -0.9249422086882784,
+           -0.8625365584712905,
+           -0.8016047088810748,
+           -0.7433440895517606,
+           -0.6888844511725002,
+           -0.6392633576225443,
+           -0.5954037714050417,
+           -0.558094252024962,
+           -0.5279722247662524,
+           -0.5055107041525193,
+           -0.49100877400699505,
+           -0.48458603646868537,
+           -0.4861811477550647,
+           -0.49555446119131535,
+           -0.5122947004207087,
+           -0.5358294901452644,
+           -0.565439480543358,
+           -0.6002757168853186,
+           -0.6393798298695392,
+           -0.6817065566665105,
+           -0.7261480491640059,
+           -0.771559385732917,
+           -0.8167846769314028,
+           -0.8606831445335711,
+           -0.9021545573412533,
+           -0.9401634262741574,
+           -0.9737613947285448,
+           -1.0021073072859723,
+           -1.0244844993470534,
+           -1.040314920663085,
+           -1.049169785277072,
+           -1.0507765270803178,
+           -1.0450219318834142,
+           -1.0319514113150625,
+           -1.011764478659982,
+           -0.9848065795854931,
+           -0.951557519296153,
+           -0.9126168098185578,
+           -0.8686863348399757,
+           -0.820550793004604,
+           -0.7690564322683207,
+           -0.7150886265813926,
+           -0.659548870890053,
+           -0.6033317806528915,
+           -0.5473026775498419,
+           -0.49227632398109555,
+           -0.4389973358343037,
+           -0.3881227567137585,
+           -0.34020721857538333,
+           -0.2956910449928389,
+           -0.2548915758490475,
+           -0.21799790807462524,
+           -0.1850691582762171,
+           -0.15603626196175305,
+           -0.1307072328795831,
+           -0.10877571704593149,
+           -0.08983259158190297,
+           -0.07338028064358774,
+           -0.05884939146391375,
+           -0.04561721457259012,
+           -0.03302758509925234,
+           -0.02041156787548085,
+           -0.007108408686924013,
+           0.007513812008045499,
+           0.024038378138357578,
+           0.042981522413831276,
+           0.06477589224497761,
+           0.08975634427216089,
+           0.11814845397624583,
+           0.1500600562661059,
+           0.18547605418321605,
+           0.22425664792408906,
+           0.26613904740838507,
+           0.31074264086808495,
+           0.3575775017014137,
+           0.4060560284135379,
+           0.45550743007512856,
+           0.5051946944661151,
+           0.5543336098551565,
+           0.6021133558899904,
+           0.6477181357669686,
+           0.6903492918329608,
+           0.729247330840581,
+           0.7637132836673627,
+           0.7931288374964732,
+           0.8169747059500656,
+           0.8348467438169427,
+           0.8464693668306017,
+           0.8517059021199697,
+           0.8505655698744338,
+           0.8432068795911597,
+           0.8299373129585034,
+           0.8112092577764654,
+           0.7876122510288012,
+           0.7598616819678441,
+           0.7287841955371501,
+           0.6953001204001381,
+           0.6604033221582711,
+           0.6251389491081889,
+           0.5905795934144684,
+           0.5578004334491822,
+           0.5278539521676257,
+           0.5017448409859242,
+           0.480405698293804,
+           0.4646741164350285,
+           0.45527172105011765,
+           0.4527856827940068,
+           0.4576531646540338,
+           0.470149099760131,
+           0.4903776163456282,
+           0.5182673402768326,
+           0.5535707134159663,
+           0.5958673702576986,
+           0.6445715181205902,
+           0.6989431700537868,
+           0.7581029868864029,
+           0.8210503977726359,
+           0.8866845893030945,
+           0.9538278837076292,
+           1.0212509685750164,
+           1.087699395289227,
+           1.151920732145285,
+           1.2126917416325336,
+           1.2688449500708772,
+           1.319293991696232,
+           1.3630571380825431,
+           1.3992784667623794,
+           1.4272461790225581,
+           1.446407644739076,
+           1.4563808301238614,
+           1.4569618504830728,
+           1.448128482431521,
+           1.4300395662200773,
+           1.4030303265691306,
+           1.3676037372820231,
+           1.3244181485816415,
+           1.2742714842956069,
+           1.2180823965720304,
+           1.1568688367893651,
+           1.0917245610183968,
+           1.0237941353688957,
+           0.9542470396888385,
+           0.8842514866035291,
+           0.81494857636774,
+           0.7474273964093183,
+           0.6827016480913894,
+           0.6216883427984645,
+           0.5651890559907478,
+           0.5138741627207268,
+           0.46827040290300403,
+           0.4287520412518084,
+           0.3955357973288947,
+           0.36867962780157076,
+           0.34808534811066,
+           0.33350498663974004,
+           0.32455067348264444,
+           0.3207077802670887,
+           0.32135094931089747,
+           0.32576258157696186,
+           0.3331532951297304,
+           0.34268382047764157,
+           0.3534877673977191,
+           0.3646946803268324,
+           0.3754527965581673,
+           0.3849509333239004,
+           0.39243895603280715,
+           0.3972463197637537,
+           0.3987982285528639,
+           0.39662902070085543,
+           0.3903924616359315,
+           0.37986870692773844,
+           0.36496778479890535,
+           0.3457295377239772,
+           0.32232005415788006,
+           0.2950247117877655,
+           0.26423804067438483,
+           0.2304506960511044,
+           0.19423390433223595,
+           0.15622181019314746,
+           0.11709220580844218,
+           0.07754616413760572,
+           0.03828712550982512,
+           3.501338376429912e-16
+          ],
+          [
+           0,
+           -0.036746875846969146,
+           -0.07099890723616208,
+           -0.10227849667465562,
+           -0.13020855150387645,
+           -0.1545240897537615,
+           -0.17508072876883565,
+           -0.19185982015386807,
+           -0.2049700818385456,
+           -0.21464566925988,
+           -0.22124072049672291,
+           -0.225220502308908,
+           -0.22714937309642796,
+           -0.227675862538765,
+           -0.22751524396961928,
+           -0.22743004244148549,
+           -0.22820897722537004,
+           -0.23064488073808329,
+           -0.23551216547077028,
+           -0.24354442562714712,
+           -0.255412760449234,
+           -0.27170539156557594,
+           -0.29290911746935444,
+           -0.3193931051150214,
+           -0.3513954626551249,
+           -0.38901296989064693,
+           -0.43219426573534747,
+           -0.48073670680340835,
+           -0.5342870202281625,
+           -0.5923457792656919,
+           -0.6542756344820537,
+           -0.7193131387536006,
+           -0.7865839132889177,
+           -0.8551208166879922,
+           -0.923884701829377,
+           -0.9917872780659751,
+           -1.0577155405197483,
+           -1.1205571856155119,
+           -1.1792264034842708,
+           -1.2326894242495312,
+           -1.2799891968707748,
+           -1.3202685961646825,
+           -1.3527915854866004,
+           -1.3769618085927957,
+           -1.392338143327061,
+           -1.3986468205674325,
+           -1.3957897926233933,
+           -1.3838491240360653,
+           -1.3630872723475396,
+           -1.3339432245674014,
+           -1.297024554380025,
+           -1.2530955631792113,
+           -1.2030617623882511,
+           -1.1479510429123503,
+           -1.088891957808457,
+           -1.0270896143752934,
+           -0.963799730139658,
+           -0.9003014522089718,
+           -0.8378695700639569,
+           -0.7777467673201814,
+           -0.7211165579052488,
+           -0.6690775364712196,
+           -0.6226195420628772,
+           -0.5826022888356003,
+           -0.5497369590598631,
+           -0.5245711831866501,
+           -0.507477751094738,
+           -0.4986473097612671,
+           -0.49808520765643444,
+           -0.5056125474741783,
+           -0.5208714087763664,
+           -0.5433341031828582,
+           -0.5723162292897299,
+           -0.6069932048612106,
+           -0.646419872190984,
+           -0.6895527008409107,
+           -0.7352740519687444,
+           -0.782417921591128,
+           -0.8297965475095673,
+           -0.8762272470201493,
+           -0.9205588503266184,
+           -0.9616971077972444,
+           -0.9986284774846723,
+           -1.030441741931873,
+           -1.0563469591319266,
+           -1.0756913201865654,
+           -1.0879715640213745,
+           -1.0928426855208335,
+           -1.0901227655030408,
+           -1.079793846775606,
+           -1.0619988777270228,
+           -1.0370348411085186,
+           -1.0053422784772146,
+           -0.9674915079188331,
+           -0.9241659120091462,
+           -0.8761427425684472,
+           -0.8242719469191656,
+           -0.7694535656680663,
+           -0.7126142834182884,
+           -0.6546837305385328,
+           -0.5965711358095381,
+           -0.539142916438926,
+           -0.4832017639665378,
+           -0.4294677427199,
+           -0.3785618628146838,
+           -0.33099252363748816,
+           -0.28714514798869917,
+           -0.24727524353244748,
+           -0.2115050390202727,
+           -0.17982375018431843,
+           -0.15209143657543459,
+           -0.12804631831443358,
+           -0.10731533305771582,
+           -0.08942763068349852,
+           -0.07383062836359822,
+           -0.059908183677286696,
+           -0.04700038987822418,
+           -0.0344244566828182,
+           -0.021496113025381007,
+           -0.007550955790261015,
+           0.008034829113340806,
+           0.025824929891565467,
+           0.04630508142168025,
+           0.0698674275865161,
+           0.09679749657246589,
+           0.1272641442478742,
+           0.16131274350594632,
+           0.19886181301571504,
+           0.23970318931521722,
+           0.28350575387066135,
+           0.32982263395396677,
+           0.3781017053117038,
+           0.4276991379188257,
+           0.4778956458347336,
+           0.5279150303523844,
+           0.5769445440886404,
+           0.6241565539845589,
+           0.668730944650844,
+           0.709877681060494,
+           0.746858941859537,
+           0.7790102417712882,
+           0.8057599835690974,
+           0.826646916374935,
+           0.8413350267356183,
+           0.8496254508262059,
+           0.8514650687146554,
+           0.8469515231061667,
+           0.8363344933564302,
+           0.8200131486103952,
+           0.798529799375561,
+           0.7725598622994583,
+           0.7428983460079229,
+           0.7104431542455024,
+           0.6761755840252015,
+           0.6411384689919201,
+           0.6064124799007184,
+           0.5730911434399534,
+           0.5422551763259159,
+           0.5149467527308452,
+           0.4921443291092198,
+           0.47473864116146874,
+           0.46351046320072165,
+           0.45911068112373177,
+           0.4620431774495563,
+           0.4726509617363223,
+           0.49110590368350543,
+           0.5174023412110539,
+           0.5513547438392543,
+           0.5925995150108805,
+           0.6406009179561922,
+           0.6946610107195772,
+           0.7539333794640581,
+           0.8174403675088087,
+           0.8840934129821646,
+           0.9527160325630072,
+           1.0220689243900751,
+           1.0908766114257726,
+           1.1578550086452195,
+           1.2217392743202926,
+           1.2813112979575687,
+           1.3354261853270681,
+           1.3830371243023585,
+           1.4232180533616348,
+           1.45518360664992,
+           1.47830587421,
+           1.4921275917791026,
+           1.4963714595745965,
+           1.4909453816836609,
+           1.4759435147832012,
+           1.4516431145821542,
+           1.4184972681724672,
+           1.3771236979697286,
+           1.3282899157503092,
+           1.2728950911961836,
+           1.2119490762603526,
+           1.1465490927072244,
+           1.0778546437741179,
+           1.0070612507605432,
+           0.9353736405377147,
+           0.8639790199011371,
+           0.7940210671577641,
+           0.7265752505209849,
+           0.6626260473316181,
+           0.6030465887427326,
+           0.5485811925506829,
+           0.49983117388131926,
+           0.45724424127528085,
+           0.42110769640759826,
+           0.3915455614454034,
+           0.3685196612307881,
+           0.35183459046945365,
+           0.3411464013055997,
+           0.3359747564044965,
+           0.33571820916437506,
+           0.3396721979834181,
+           0.3470492774379475,
+           0.3570010573383631,
+           0.368641282168058,
+           0.3810694592886864,
+           0.3933944350653618,
+           0.4047573239083014,
+           0.4143532159474318,
+           0.421451124087934,
+           0.4254116796155664,
+           0.42570214607666773,
+           0.42190839229396937,
+           0.41374354527907975,
+           0.4010531304334932,
+           0.3838165975944779,
+           0.3621452248734249,
+           0.3362764854926623,
+           0.30656505360020203,
+           0.273470711043926,
+           0.23754349615365764,
+           0.1994065057249031,
+           0.1597368208616181,
+           0.11924507462750715,
+           0.07865421339403568,
+           0.03867802351350385,
+           3.522876073600707e-16
+          ],
+          [
+           0,
+           -0.036697199074634694,
+           -0.0706219054747758,
+           -0.10133745806757845,
+           -0.128516593016478,
+           -0.15195156459803963,
+           -0.17156093398945327,
+           -0.1873928347572768,
+           -0.1996246155498747,
+           -0.208558854945022,
+           -0.2146158381355225,
+           -0.2183226777458918,
+           -0.22029934921010733,
+           -0.2212419925625551,
+           -0.22190390512677285,
+           -0.2230747115733534,
+           -0.22555824756893278,
+           -0.23014972946755022,
+           -0.23761280425688774,
+           -0.2486570806800496,
+           -0.2639167339007606,
+           -0.283930752441007,
+           -0.3091253579487294,
+           -0.3397990765682171,
+           -0.37611087654912845,
+           -0.41807171181523983,
+           -0.4655397273676747,
+           -0.5182192916933488,
+           -0.5756639260372945,
+           -0.6372831028472401,
+           -0.7023527883408837,
+           -0.7700295094125896,
+           -0.8393676353580609,
+           -0.9093394824059161,
+           -0.9788577758814377,
+           -1.0467999428406578,
+           -1.1120336587795365,
+           -1.1734430368073645,
+           -1.2299548273952683,
+           -1.2805639920206728,
+           -1.3243580248961193,
+           -1.3605394232773094,
+           -1.3884457479904768,
+           -1.4075667708346609,
+           -1.4175582730873435,
+           -1.4182521378469564,
+           -1.40966246648494,
+           -1.3919875439292682,
+           -1.3656075765626308,
+           -1.3310782277763504,
+           -1.2891200772023208,
+           -1.2406042278795104,
+           -1.1865343786926306,
+           -1.1280257650654837,
+           -1.0662814469971382,
+           -1.002566488224,
+           -0.9381806219813592,
+           -0.8744300362483914,
+           -0.8125989335631869,
+           -0.7539215269346363,
+           -0.6995551238861778,
+           -0.6505549254635529,
+           -0.6078511267304478,
+           -0.5722288508376819,
+           -0.5443113815054564,
+           -0.5245470803388714,
+           -0.5132002877135551,
+           -0.5103464111553238,
+           -0.5158713055044554,
+           -0.5294749471270002,
+           -0.5506793024957944,
+           -0.5788401920917581,
+           -0.6131628561862627,
+           -0.6527208419481049,
+           -0.6964777535841382,
+           -0.7433113407482824,
+           -0.792039346839339,
+           -0.8414464993354213,
+           -0.8903119999154944,
+           -0.9374368633583059,
+           -0.9816704612630002,
+           -1.0219356492924334,
+           -1.0572518943044638,
+           -1.0867558694460362,
+           -1.1097190497324025,
+           -1.125561916202348,
+           -1.1338644615406832,
+           -1.1343727819798728,
+           -1.1270016370498395,
+           -1.1118329579408597,
+           -1.089110384426366,
+           -1.0592300070129985,
+           -1.022727582863987,
+           -0.980262578823201,
+           -0.9325994704766013,
+           -0.8805867907829865,
+           -0.8251344738219804,
+           -0.7671900773952199,
+           -0.7077144916742913,
+           -0.6476577492818233,
+           -0.5879355449676037,
+           -0.5294070506305504,
+           -0.4728545744495844,
+           -0.4189655622933122,
+           -0.3683173766892007,
+           -0.3213652150615142,
+           -0.27843344657103425,
+           -0.2397105578029347,
+           -0.20524780401042914,
+           -0.17496156699691917,
+           -0.14863932542256217,
+           -0.12594905075468718,
+           -0.10645175457529442,
+           -0.08961683271286136,
+           -0.07483978069427451,
+           -0.061461795094981383,
+           -0.048790728000630106,
+           -0.03612282816343943,
+           -0.022764683376757057,
+           -0.008054774569674714,
+           0.008615936770743739,
+           0.027784940301009965,
+           0.04990113998707961,
+           0.07531030781676354,
+           0.10424342208863821,
+           0.13680820911191147,
+           0.17298412371948774,
+           0.21262091444211384,
+           0.25544082578470184,
+           0.30104439515442954,
+           0.34891970802091676,
+           0.39845488422682795,
+           0.4489534833167264,
+           0.49965243947805105,
+           0.5497420691620821,
+           0.5983876384037538,
+           0.6447519337291314,
+           0.6880182514480783,
+           0.7274132058453376,
+           0.7622287577036506,
+           0.7918428807342859,
+           0.8157383144881791,
+           0.8335188974361704,
+           0.8449230320460038,
+           0.8498339034244694,
+           0.848286152720127,
+           0.8404687940289488,
+           0.8267242568436112,
+           0.807543532820087,
+           0.783557503394856,
+           0.7555246211338835,
+           0.7243152102210448,
+           0.6908927378799385,
+           0.6562924865965287,
+           0.6215981248011587,
+           0.5879167294574111,
+           0.5563528563673067,
+           0.5279822818420116,
+           0.503826051966968,
+           0.48482547264886067,
+           0.4718186549938448,
+           0.4655191967425207,
+           0.46649753226392726,
+           0.4751654221325941,
+           0.4917639800529153,
+           0.5163555516208734,
+           0.5488196681417085,
+           0.5888532016713268,
+           0.6359747469831494,
+           0.68953315473261,
+           0.7487200401779397,
+           0.8125859958643631,
+           0.8800601470407344,
+           0.9499726074534162,
+           1.0210793225446746,
+           1.0920887287104952,
+           1.161689612584425,
+           1.228579524414807,
+           1.2914930852365178,
+           1.3492295290675966,
+           1.4006788387610671,
+           1.4448458669973814,
+           1.4808718814210482,
+           1.5080530339531844,
+           1.5258553273675433,
+           1.533925735523242,
+           1.532099225175027,
+           1.5204015248028426,
+           1.4990475870418953,
+           1.468435793590418,
+           1.4291380524360304,
+           1.381886034418406,
+           1.3275538871762094,
+           1.2671378472030537,
+           1.2017332430603218,
+           1.1325094430204348,
+           1.060683347097183,
+           0.9874920554489393,
+           0.9141653617662627,
+           0.8418987211066435,
+           0.7718273267337251,
+           0.70500190026025,
+           0.6423667545651308,
+           0.584740630693257,
+           0.532800739718829,
+           0.4870703601177565,
+           0.44791025255857425,
+           0.41551405938883285,
+           0.38990775781318937,
+           0.37095313626325976,
+           0.3583551652052719,
+           0.35167303904116193,
+           0.3503345771572357,
+           0.35365359173358857,
+           0.36084975961157045,
+           0.3710704770346405,
+           0.38341413084114456,
+           0.39695418877484007,
+           0.4107634957109568,
+           0.42393816211659247,
+           0.4356204459351385,
+           0.44502005888336765,
+           0.451433372083755,
+           0.4542600528796246,
+           0.45301673313040364,
+           0.447347387507865,
+           0.4370301863190855,
+           0.4219806789852132,
+           0.40225125918727683,
+           0.37802695845372974,
+           0.34961770919342705,
+           0.3174473084986036,
+           0.2820393981833675,
+           0.2440008523702106,
+           0.2040030295875772,
+           0.16276140015128954,
+           0.12101410022679175,
+           0.07949999039598311,
+           0.03893680812818653,
+           3.532221979602567e-16
+          ],
+          [
+           0,
+           -0.036522239756475144,
+           -0.07000899310594952,
+           -0.10007045482837142,
+           -0.1264344336775796,
+           -0.14895482355555142,
+           -0.1676165509272284,
+           -0.1825368562602337,
+           -0.19396286286845327,
+           -0.20226548345754453,
+           -0.207929810455146,
+           -0.21154222842702688,
+           -0.21377457318858392,
+           -0.21536574042163703,
+           -0.2171012147038653,
+           -0.219791046108943,
+           -0.2242468444917503,
+           -0.2312583901196683,
+           -0.24157047269312668,
+           -0.25586056864137957,
+           -0.274717948897642,
+           -0.2986247765556166,
+           -0.3279397066714902,
+           -0.3628844401469835,
+           -0.40353361158798,
+           -0.4498083090539408,
+           -0.501473433722266,
+           -0.5581390119177722,
+           -0.6192654730760301,
+           -0.6841728074838332,
+           -0.7520534195604368,
+           -0.8219883984639655,
+           -0.8929668402864198,
+           -0.963907777240569,
+           -1.0336842010348983,
+           -1.1011486118104514,
+           -1.165159482004232,
+           -1.2246079973963522,
+           -1.2784444261138628,
+           -1.3257034708390982,
+           -1.3655279798458404,
+           -1.3971904283105099,
+           -1.4201116317827511,
+           -1.4338762175522637,
+           -1.4382444553847864,
+           -1.4331601348919587,
+           -1.418754270567834,
+           -1.3953445149894852,
+           -1.363430263416217,
+           -1.3236835365228166,
+           -1.2769358297353282,
+           -1.2241612151114714,
+           -1.1664560725308133,
+           -1.10501590890214,
+           -1.041109795141203,
+           -0.9760530090714824,
+           -0.9111785167115907,
+           -0.8478079535379108,
+           -0.7872227805237021,
+           -0.730636286718989,
+           -0.679167090910488,
+           -0.6338147599444237,
+           -0.5954381114508068,
+           -0.5647367051826944,
+           -0.5422359515210152,
+           -0.5282761797344658,
+           -0.5230059144164899,
+           -0.5263795084396419,
+           -0.5381591772078986,
+           -0.5579213744700482,
+           -0.5850673470245172,
+           -0.6188376067998296,
+           -0.6583299664352246,
+           -0.7025207008517688,
+           -0.7502883244185085,
+           -0.8004394129382386,
+           -0.8517358532519065,
+           -0.9029228718943533,
+           -0.9527571786602813,
+           -1.0000345615035477,
+           -1.0436162858425946,
+           -1.0824536836338068,
+           -1.1156103646717066,
+           -1.1422815432873077,
+           -1.1618100464174592,
+           -1.173698652087934,
+           -1.177618498621373,
+           -1.1734134020798863,
+           -1.1611000201719586,
+           -1.1408639026028244,
+           -1.1130515681156836,
+           -1.0781588447888817,
+           -1.0368158001557835,
+           -0.989768669195465,
+           -0.9378592592155773,
+           -0.8820023693909783,
+           -0.823161807817494,
+           -0.7623256193160873,
+           -0.7004811521737249,
+           -0.6385905912132069,
+           -0.5775675681180067,
+           -0.5182554282623687,
+           -0.4614076872524628,
+           -0.40767115116893793,
+           -0.35757210363822506,
+           -0.31150588216146624,
+           -0.269730077649509,
+           -0.2323614970949972,
+           -0.19937693213723062,
+           -0.1706176783962057,
+           -0.14579765433683356,
+           -0.12451487649204138,
+           -0.10626596243527209,
+           -0.09046325609332055,
+           -0.07645410375430677,
+           -0.06354175510983849,
+           -0.051007323223096375,
+           -0.03813221144095659,
+           -0.02422040460619295,
+           -0.008620026729669028,
+           0.009256412582898417,
+           0.029913625710688573,
+           0.053757502505187134,
+           0.08108184605521955,
+           0.11205824846066319,
+           0.14672938444269953,
+           0.18500591152806958,
+           0.22666707152597876,
+           0.27136499145287996,
+           0.31863258540138706,
+           0.36789486454819575,
+           0.41848337294746385,
+           0.46965338423856484,
+           0.5206034210134901,
+           0.5704965962148457,
+           0.6184832261710739,
+           0.6637241290067596,
+           0.7054140011307133,
+           0.7428042588696053,
+           0.7752247422609185,
+           0.8021037033358099,
+           0.8229855413138983,
+           0.83754580103012,
+           0.845603017303066,
+           0.8471270652032863,
+           0.8422437623826871,
+           0.8312355626480539,
+           0.8145382774936116,
+           0.7927338619222072,
+           0.7665394000981255,
+           0.7367925227064445,
+           0.7044335789306442,
+           0.6704849694144304,
+           0.6360281203416092,
+           0.602178640981354,
+           0.5700602561203256,
+           0.5407781394755043,
+           0.5153922935442219,
+           0.4948916248704401,
+           0.4801693512493258,
+           0.47200034921221207,
+           0.4710210068761742,
+           0.4777120899266649,
+           0.4923850584968602,
+           0.5151721916985259,
+           0.5460207865059763,
+           0.5846916007834534,
+           0.6307616088360701,
+           0.683631034429441,
+           0.74253452329116,
+           0.806556217197836,
+           0.8746483973133612,
+           0.9456532777951806,
+           1.0183274539555365,
+           1.0913684443418787,
+           1.1634427145865291,
+           1.2332145340436267,
+           1.2993749949963203,
+           1.3606705191123807,
+           1.4159301869904677,
+           1.464091253812147,
+           1.5042222566443135,
+           1.5355431757945024,
+           1.557442182428392,
+           1.5694885857182719,
+           1.5714416831311537,
+           1.563255314887241,
+           1.5450780257519139,
+           1.5172488416813015,
+           1.4802887728838303,
+           1.4348882560579046,
+           1.38189084446047,
+           1.3222735427262624,
+           1.2571242618553649,
+           1.187616936621326,
+           1.114984901215611,
+           1.0404931579560022,
+           0.9654101974248565,
+           0.8909800359265929,
+           0.8183951275161216,
+           0.7487707833007196,
+           0.6831216908981493,
+           0.6223410728587154,
+           0.5671829558922815,
+           0.5182479445617059,
+           0.47597280566287103,
+           0.44062407498483097,
+           0.412295798876908,
+           0.39091142150115504,
+           0.3762297273274687,
+           0.3678546498323648,
+           0.3652486639162357,
+           0.3677493935494924,
+           0.3745889896980713,
+           0.38491576852428344,
+           0.3978175477840863,
+           0.4123460814946145,
+           0.4275419702183501,
+           0.44245941721656584,
+           0.45619020938867055,
+           0.467886326067372,
+           0.47678061772782476,
+           0.4822050494701229,
+           0.48360606938338363,
+           0.48055673792337233,
+           0.4727653392952647,
+           0.46008028737253887,
+           0.442491234583211,
+           0.42012639003104113,
+           0.3932461504238115,
+           0.36223324170181165,
+           0.32757965822480606,
+           0.2898707677503502,
+           0.24976702217918423,
+           0.20798377435819423,
+           0.1652697486108499,
+           0.12238474592874424,
+           0.0800771830817929,
+           0.03906206784134905,
+           3.5294093290301597e-16
+          ],
+          [
+           0,
+           -0.03622555029930202,
+           -0.06917065243044145,
+           -0.09849799195903584,
+           -0.12399529542981237,
+           -0.14558199881779504,
+           -0.16331222649471183,
+           -0.17737399103812124,
+           -0.18808462286352237,
+           -0.19588253721317414,
+           -0.20131554198785362,
+           -0.20502598082153464,
+           -0.20773308936107807,
+           -0.2102130167936437,
+           -0.21327702737026827,
+           -0.2177484463956391,
+           -0.22443895060684568,
+           -0.23412482312029076,
+           -0.2475237976390068,
+           -0.26527310523015946,
+           -0.28790930995120456,
+           -0.3158504775628985,
+           -0.34938116553568865,
+           -0.3886406539031673,
+           -0.4336147569313512,
+           -0.4841314670218455,
+           -0.5398605869450303,
+           -0.6003174067749765,
+           -0.6648703802545155,
+           -0.7327526542939301,
+           -0.8030772074274218,
+           -0.8748552607724833,
+           -0.9470175406792419,
+           -1.0184378979484972,
+           -1.0879587261223171,
+           -1.1544175725008632,
+           -1.2166743014727925,
+           -1.2736381513589725,
+           -1.3242940237685434,
+           -1.3677273585606016,
+           -1.403146977598832,
+           -1.4299053258884318,
+           -1.4475155983229075,
+           -1.4556653127169759,
+           -1.4542259733158116,
+           -1.443258561528808,
+           -1.4230146899894158,
+           -1.3939333597716086,
+           -1.356633366165997,
+           -1.3119015032531198,
+           -1.260676819040104,
+           -1.2040312686599048,
+           -1.143147200717809,
+           -1.0792921891541163,
+           -1.0137917880701028,
+           -0.9480008382303303,
+           -0.8832739901381083,
+           -0.8209361287816412,
+           -0.7622533888561848,
+           -0.7084054363760424,
+           -0.6604596634003347,
+           -0.6193478978073553,
+           -0.58584617074661,
+           -0.5605580120126193,
+           -0.543901659878606,
+           -0.5361014789364915,
+           -0.5371837794746492,
+           -0.546977127320437,
+           -0.5651171264261282,
+           -0.5910555503788156,
+           -0.6240735960467164,
+           -0.6632989352371572,
+           -0.7077261508967889,
+           -0.7562400651957214,
+           -0.807641399716898,
+           -0.8606741545348625,
+           -0.9140540544914209,
+           -0.9664973883685972,
+           -1.0167495604395917,
+           -1.0636126841620421,
+           -1.1059715742739178,
+           -1.142817535573634,
+           -1.173269403143499,
+           -1.19659135828786,
+           -1.2122071252640958,
+           -1.2197102439711545,
+           -1.2188702108874758,
+           -1.2096343823092834,
+           -1.1921256378141618,
+           -1.1666359052989703,
+           -1.1336157493679995,
+           -1.0936603198089234,
+           -1.0474920440633606,
+           -0.9959405248467961,
+           -0.9399201695208047,
+           -0.8804061298875535,
+           -0.818409168516467,
+           -0.7549500896459672,
+           -0.6910343786368572,
+           -0.6276276837945864,
+           -0.5656327484327625,
+           -0.5058683600193669,
+           -0.44905082820445535,
+           -0.3957784358952476,
+           -0.3465192290538423,
+           -0.30160242354520167,
+           -0.2612136133760193,
+           -0.22539386641867545,
+           -0.19404269369057617,
+           -0.16692477897987876,
+           -0.14368025957337227,
+           -0.12383825846485105,
+           -0.10683328597119165,
+           -0.09202405622462201,
+           -0.07871420335587567,
+           -0.06617433484764614,
+           -0.05366482669819954,
+           -0.04045874750246405,
+           -0.025864296757972985,
+           -0.009246156664857548,
+           0.009954813954996755,
+           0.03220407099965593,
+           0.05785853155960961,
+           0.08715477582935867,
+           0.12020062492084535,
+           0.15697032693827107,
+           0.1973034895479179,
+           0.24090779951512764,
+           0.2873654707633066,
+           0.3361432649467035,
+           0.38660583479737975,
+           0.43803205298994735,
+           0.4896339101937544,
+           0.5405774973692009,
+           0.5900055309695973,
+           0.6370608369840475,
+           0.6809101818098038,
+           0.7207678255140799,
+           0.7559181764861219,
+           0.7857369457430632,
+           0.8097102337931661,
+           0.8274510321461856,
+           0.8387126840951395,
+           0.8433989237424665,
+           0.8415701965728619,
+           0.8334460570981892,
+           0.8194035369280218,
+           0.7999714776188267,
+           0.7758209243071308,
+           0.7477517758973872,
+           0.7166759829545697,
+           0.6835976730497949,
+           0.6495906628927502,
+           0.6157738851449056,
+           0.583285313599362,
+           0.5532550120070421,
+           0.5267779581444054,
+           0.5048873050511105,
+           0.48852873540798564,
+           0.47853654286983144,
+           0.4756120363093661,
+           0.48030481025200844,
+           0.49299735853909826,
+           0.5138934300397608,
+           0.5430104369279871,
+           0.5801761297931167,
+           0.6250296520002958,
+           0.6770269807460614,
+           0.7354506567278597,
+           0.7994236008476016,
+           0.8679267174349856,
+           0.939819891534631,
+           1.0138659051117307,
+           1.088756725629985,
+           1.1631415621031296,
+           1.2356560398608127,
+           1.304951816989237,
+           1.3697259534145243,
+           1.4287493482012552,
+           1.4808935817426359,
+           1.5251555366206666,
+           1.5606792231207627,
+           1.586774301431833,
+           1.6029308708469334,
+           1.6088301848989042,
+           1.6043510481639787,
+           1.5895717530892688,
+           1.5647675211496588,
+           1.530403519338199,
+           1.4871236278466813,
+           1.4357352352515866,
+           1.3771904311460375,
+           1.3125640506816623,
+           1.243029098860845,
+           1.169830142880642,
+           1.0942553069242749,
+           1.0176075344280802,
+           0.9411757973054914,
+           0.8662069295669544,
+           0.7938787443240992,
+           0.7252750587979061,
+           0.661363202545295,
+           0.6029745209255324,
+           0.5507883104330242,
+           0.5053195368097327,
+           0.4669105929520397,
+           0.4357272538750102,
+           0.41175888286168094,
+           0.39482283895536263,
+           0.3845729337129663,
+           0.3805116871423398,
+           0.3820060414017516,
+           0.3883061083797775,
+           0.3985664557089106,
+           0.4118693768313863,
+           0.4272495458491529,
+           0.44371942811754955,
+           0.46029480357252395,
+           0.47601976190773937,
+           0.48999054683352394,
+           0.5013776602493181,
+           0.5094456853549055,
+           0.513570349261918,
+           0.5132524189635257,
+           0.5081281077044745,
+           0.4979757597499179,
+           0.48271867797363116,
+           0.46242405813592175,
+           0.43729809368852907,
+           0.4076774129098488,
+           0.37401710367431895,
+           0.3368756678463912,
+           0.2968973249881737,
+           0.2547921518350441,
+           0.21131459815714884,
+           0.16724095983711526,
+           0.12334641525807988,
+           0.08038224079099511,
+           0.03905381506809361,
+           3.5146057292891096e-16
+          ],
+          [
+           0,
+           -0.03581210792269225,
+           -0.06812011128042693,
+           -0.09664446484037308,
+           -0.12123719335064144,
+           -0.14188661777474354,
+           -0.15871825504718864,
+           -0.17199185727860097,
+           -0.1820946572240894,
+           -0.18953098613248734,
+           -0.19490852529439787,
+           -0.1989215412832898,
+           -0.2023315347781389,
+           -0.20594580192927223,
+           -0.21059446371250226,
+           -0.21710656115640847,
+           -0.2262858416213648,
+           -0.23888687273360212,
+           -0.2555921158080635,
+           -0.2769905697112659,
+           -0.3035585596058004,
+           -0.3356431937605084,
+           -0.373448946855356,
+           -0.417027751548888,
+           -0.4662728934015905,
+           -0.5209169097077787,
+           -0.5805335927302429,
+           -0.6445440947473113,
+           -0.7122270287836074,
+           -0.7827323574931965,
+           -0.855098765938661,
+           -0.9282741243933663,
+           -1.0011385670458102,
+           -1.0725296436362122,
+           -1.141268945358682,
+           -1.2061895652470296,
+           -1.2661637277991724,
+           -1.320129913468675,
+           -1.3671188111432941,
+           -1.4062774557089868,
+           -1.4368909477251104,
+           -1.4584012071775243,
+           -1.4704222819232242,
+           -1.4727518121435725,
+           -1.4653783429327305,
+           -1.4484842758599605,
+           -1.4224443545563288,
+           -1.3878196865453398,
+           -1.3453474110433539,
+           -1.295926227666416,
+           -1.2405981013151952,
+           -1.1805265515044885,
+           -1.116972017770729,
+           -1.051264864475946,
+           -0.9847766465598258,
+           -0.9188903011311385,
+           -0.8549699571576885,
+           -0.7943310662232201,
+           -0.7382115510902099,
+           -0.6877446457751548,
+           -0.643934061554414,
+           -0.6076320587195825,
+           -0.5795209353124826,
+           -0.5600983631546294,
+           -0.5496669102103338,
+           -0.5483279889053608,
+           -0.5559803648830065,
+           -0.5723232523742223,
+           -0.5968639135228438,
+           -0.6289295722874292,
+           -0.6676833515309323,
+           -0.7121438470846314,
+           -0.7612078672318576,
+           -0.8136757922639024,
+           -0.8682789482945634,
+           -0.9237083438310821,
+           -0.9786440877749211,
+           -1.031784794261474,
+           -1.0818762833326696,
+           -1.1277389067452288,
+           -1.1682928647145483,
+           -1.2025809311475888,
+           -1.229788070621665,
+           -1.2492575083737334,
+           -1.2605029029298618,
+           -1.2632163675302968,
+           -1.2572721887972977,
+           -1.2427261966197702,
+           -1.2198108453847452,
+           -1.1889261708551524,
+           -1.150626886615317,
+           -1.10560597663711,
+           -1.0546752238963921,
+           -0.9987431870610022,
+           -0.9387911963319647,
+           -0.8758479841300003,
+           -0.8109635954224962,
+           -0.7451832354121475,
+           -0.679521708791421,
+           -0.6149390849498497,
+           -0.5523181879530177,
+           -0.4924444597321966,
+           -0.4359886810392703,
+           -0.38349295897350283,
+           -0.3353603042085834,
+           -0.2918480276181653,
+           -0.2530650871828431,
+           -0.21897341435886228,
+           -0.18939314706387228,
+           -0.1640115966565076,
+           -0.14239568126257787,
+           -0.12400746991611858,
+           -0.10822240344057353,
+           -0.09434969075860741,
+           -0.0816543250663697,
+           -0.06938012438916218,
+           -0.056773176438222675,
+           -0.04310505901415341,
+           -0.027695214651711448,
+           -0.00993188156753695,
+           0.010708978349456649,
+           0.03464726076745981,
+           0.062185249657854824,
+           0.09349746060012645,
+           0.1286240731061707,
+           0.1674681347139653,
+           0.20979662113843603,
+           0.2552453360515828,
+           0.3033275336502553,
+           0.35344604960751225,
+           0.404908633771527,
+           0.45694609342097114,
+           0.508732781163073,
+           0.5594088985800761,
+           0.6081040371077499,
+           0.6539613426484415,
+           0.6961616709962228,
+           0.7339470978089682,
+           0.766643159724046,
+           0.7936792319962476,
+           0.8146064920541044,
+           0.8291129765557371,
+           0.8370353104524068,
+           0.8383667684897904,
+           0.8332614204670978,
+           0.8220342091779697,
+           0.8051569118467575,
+           0.7832500395097408,
+           0.7570708315838289,
+           0.7274976022417018,
+           0.6955107886780105,
+           0.6621711365532486,
+           0.6285955326885285,
+           0.5959310575573151,
+           0.5653278786837156,
+           0.5379116394566152,
+           0.5147560152247678,
+           0.4968561093653613,
+           0.4851033462420205,
+           0.48026248592313175,
+           0.48295133795688977,
+           0.49362368952025165,
+           0.5125558883581891,
+           0.5398374349127698,
+           0.5753658429920009,
+           0.618845926556318,
+           0.6697935641865127,
+           0.7275438851298075,
+           0.7912637141354234,
+           0.8599680092017745,
+           0.9325399293944996,
+           1.0077540814416976,
+           1.0843024160469006,
+           1.160822179700237,
+           1.2359252768239202,
+           1.3082283616241852,
+           1.3763829599230184,
+           1.4391049189944398,
+           1.4952024981045395,
+           1.5436024437089257,
+           1.583373440348032,
+           1.6137463900624394,
+           1.6341310481309659,
+           1.6441286292928678,
+           1.6435400942537706,
+           1.632369928866509,
+           1.6108253354272584,
+           1.5793108644298348,
+           1.5384186232281258,
+           1.4889143027402882,
+           1.4317193620462352,
+           1.3678898010871576,
+           1.2985920314845931,
+           1.2250764228294884,
+           1.1486491550286604,
+           1.0706430451650435,
+           0.9923880389347943,
+           0.9151820615747079,
+           0.840262911205652,
+           0.7687818490228736,
+           0.7017794964988195,
+           0.6401645908505094,
+           0.5846960779428904,
+           0.5359689383534271,
+           0.49440404958985523,
+           0.4602422877354556,
+           0.4335429675647789,
+           0.414186614003801,
+           0.40188195232115126,
+           0.39617690222758095,
+           0.39647326463887805,
+           0.40204470158404393,
+           0.4120575317696617,
+           0.42559379853698154,
+           0.4416760149577044,
+           0.4592929538496459,
+           0.47742582942044653,
+           0.4950742125356072,
+           0.5112810333180483,
+           0.5251560525727424,
+           0.535897226645424,
+           0.5428094476418565,
+           0.5453202109750639,
+           0.542991843179529,
+           0.5355300127710692,
+           0.5227883433597056,
+           0.5047690487997868,
+           0.4816196123481209,
+           0.4536256330215764,
+           0.42120006005431226,
+           0.3848691280972973,
+           0.34525538927827915,
+           0.30305831135917605,
+           0.25903297216279003,
+           0.2139674276734072,
+           0.16865936357384095,
+           0.12389265666758413,
+           0.08041447324696042,
+           0.03891351600926232,
+           3.488114063755102e-16
+          ],
+          [
+           0,
+           -0.03528828746502177,
+           -0.0668732489152217,
+           -0.0945379610234385,
+           -0.11820260002822153,
+           -0.13792710179591086,
+           -0.1539098896249807,
+           -0.16648269390120057,
+           -0.17610158995124242,
+           -0.183334479572974,
+           -0.1888453352236685,
+           -0.1933756113436289,
+           -0.19772330260292967,
+           -0.20272019205824285,
+           -0.20920788167311416,
+           -0.21801323211033644,
+           -0.22992385724708236,
+           -0.24566432098897417,
+           -0.26587366957698305,
+           -0.29108490201428283,
+           -0.32170693521921156,
+           -0.35800956015471325,
+           -0.4001118119751115,
+           -0.44797409297381235,
+           -0.5013942938969457,
+           -0.560008059322966,
+           -0.623293238782873,
+           -0.6905784597053244,
+           -0.7610556537554799,
+           -0.8337962673151037,
+           -0.9077707922566283,
+           -0.9818711671791108,
+           -1.0549355240728977,
+           -1.125774692873241,
+           -1.1931998281499883,
+           -1.2560504895084035,
+           -1.3132224910093895,
+           -1.3636948355149785,
+           -1.4065550673688623,
+           -1.4410224108547054,
+           -1.4664681116500722,
+           -1.482432462832286,
+           -1.4886380743534535,
+           -1.4849990334190768,
+           -1.47162570073276,
+           -1.448824991736571,
+           -1.4170961002424691,
+           -1.3771217315689483,
+           -1.3297550207825422,
+           -1.2760024162354147,
+           -1.217002906719237,
+           -1.1540040598078296,
+           -1.0883354171375188,
+           -1.0213798575446205,
+           -0.9545435895307736,
+           -0.8892254692027495,
+           -0.8267863577654452,
+           -0.7685192333771028,
+           -0.7156207556665928,
+           -0.6691649478497516,
+           -0.6300796119632525,
+           -0.5991260284525106,
+           -0.5768824137611274,
+           -0.5637315205558904,
+           -0.5598526669461792,
+           -0.565218375908885,
+           -0.5795956966673016,
+           -0.6025521686571599,
+           -0.6334662786472963,
+           -0.671542155241548,
+           -0.715828144954982,
+           -0.7652388227579116,
+           -0.8185799096262075,
+           -0.8745755021665728,
+           -0.9318969664243127,
+           -0.9891928107938723,
+           -1.0451188324172576,
+           -1.098367828039903,
+           -1.1476981740454515,
+           -1.1919606109360537,
+           -1.230122614077429,
+           -1.2612897939105454,
+           -1.2847238435037034,
+           -1.2998566374164608,
+           -1.30630018122754,
+           -1.3038522133769863,
+           -1.2924973676557607,
+           -1.272403913109165,
+           -1.243916195631098,
+           -1.2075430094702164,
+           -1.1639422246963467,
+           -1.1139020859925715,
+           -1.058319676767825,
+           -0.998177108618657,
+           -0.934516048015316,
+           -0.8684112285104588,
+           -0.8009436169177291,
+           -0.7331739053375536,
+           -0.6661169875907136,
+           -0.6007180489445484,
+           -0.5378308527771279,
+           -0.4781987482013147,
+           -0.42243885020022004,
+           -0.37102976036146673,
+           -0.32430310396408285,
+           -0.2824390603103543,
+           -0.24546596030526513,
+           -0.21326392096441635,
+           -0.18557238340448443,
+           -0.16200132153088745,
+           -0.142045795578563,
+           -0.12510344021542086,
+           -0.11049440319616947,
+           -0.09748318939686346,
+           -0.08530181798950039,
+           -0.07317366869744642,
+           -0.06033737728772082,
+           -0.04607014108246954,
+           -0.0297098122733338,
+           -0.010675189750738653,
+           0.011516031833516866,
+           0.03723213519570574,
+           0.06671548103745223,
+           0.10007415692918503,
+           0.13727740247968534,
+           0.1781549401668529,
+           0.22240023917684462,
+           0.26957763677668917,
+           0.3191331407395363,
+           0.37040863971732696,
+           0.4226591586699224,
+           0.47507271579885674,
+           0.5267922679564965,
+           0.5769391749866286,
+           0.6246375713547959,
+           0.6690390068400183,
+           0.7093467076885395,
+           0.7448388157733884,
+           0.7748899858444133,
+           0.7989907593636468,
+           0.8167641867727389,
+           0.8279792370284913,
+           0.8325606122205231,
+           0.8305946740997115,
+           0.822331286189475,
+           0.8081814774165937,
+           0.7887109383350673,
+           0.7646294664000316,
+           0.7367765797409056,
+           0.7061036168999631,
+           0.6736527305789226,
+           0.640533264285794,
+           0.6078960698489523,
+           0.5769063793042117,
+           0.5487158852364122,
+           0.5244347082098333,
+           0.5051039377882416,
+           0.49166942457399926,
+           0.4849574748545401,
+           0.4856530574174479,
+           0.49428107486829187,
+           0.5111911807221531,
+           0.5365465403492727,
+           0.5703168405494369,
+           0.612275751374148,
+           0.6620029372740004,
+           0.7188906053220718,
+           0.7821544688267099,
+           0.8508488977807133,
+           0.9238859259212576,
+           1.0000576901949867,
+           1.0780617944497015,
+           1.1565290172783995,
+           1.234052725901051,
+           1.309219315222818,
+           1.3806389648207158,
+           1.446975997248923,
+           1.5069781289646118,
+           1.5595039301871987,
+           1.6035478515198975,
+           1.638262232185972,
+           1.6629757758838413,
+           1.67720806382111,
+           1.6806797684181225,
+           1.6733183331942998,
+           1.6552589919839489,
+           1.626841111254557,
+           1.5885999502292159,
+           1.5412540420487912,
+           1.4856885027116093,
+           1.4229346704867356,
+           1.3541465645853696,
+           1.2805747260114773,
+           1.2035380639102928,
+           1.1243943759424375,
+           1.044510240157661,
+           0.9652309878504528,
+           0.8878514616914505,
+           0.8135882412078136,
+           0.7435539790138712,
+           0.6787344370557242,
+           0.6199687438926712,
+           0.5679333134025764,
+           0.5231297742764526,
+           0.4858771605209373,
+           0.45630850837281994,
+           0.43437189713891233,
+           0.41983586316916655,
+           0.41229901011787473,
+           0.4112035374521194,
+           0.4158523153078375,
+           0.4254290495644657,
+           0.43902100845818365,
+           0.4556437229364007,
+           0.4742670286906368,
+           0.4938417894379459,
+           0.5133266292021373,
+           0.5317140063123458,
+           0.5480549834073962,
+           0.5614820853162915,
+           0.5712296892875846,
+           0.576651458300451,
+           0.5772344064075704,
+           0.5726092732395064,
+           0.562556980701957,
+           0.5470110460932321,
+           0.526055929803088,
+           0.499921399806391,
+           0.4689730967177018,
+           0.43369957967512274,
+           0.3946962223535395,
+           0.3526464077397675,
+           0.3083005379530288,
+           0.26245342967724855,
+           0.215920705338842,
+           0.1695148140382113,
+           0.12402132384387533,
+           0.0801761182139874,
+           0.03864410426381809,
+           3.4503718535077355e-16
+          ],
+          [
+           0,
+           -0.03466181775572277,
+           -0.06544847006919446,
+           -0.09221001661225013,
+           -0.11493805359628022,
+           -0.13376620106067938,
+           -0.14896658554771247,
+           -0.1609424025112148,
+           -0.17021674547538668,
+           -0.17741798696294508,
+           -0.1832620870570596,
+           -0.18853228683540652,
+           -0.194056713740633,
+           -0.2006844824417059,
+           -0.20926091644107098,
+           -0.2206025415098526,
+           -0.235472511302026,
+           -0.25455711793862895,
+           -0.2784440161172787,
+           -0.30760274896238904,
+           -0.34236810836474846,
+           -0.38292679332408175,
+           -0.4293077485112591,
+           -0.48137647391994176,
+           -0.5388334973483166,
+           -0.6012170970073843,
+           -0.6679102543980971,
+           -0.7381517104141241,
+           -0.8110508930950906,
+           -0.8856063862015721,
+           -0.9607275163067229,
+           -1.035258554710786,
+           -1.1080049612483451,
+           -1.1777610417406952,
+           -1.2433383508716525,
+           -1.303594148680695,
+           -1.3574592123142453,
+           -1.4039643153744032,
+           -1.4422647149475418,
+           -1.4716620305529018,
+           -1.4916229587859102,
+           -1.5017943409217522,
+           -1.5020141864230887,
+           -1.4923183510881182,
+           -1.4729426721539935,
+           -1.4443204715116174,
+           -1.407075449632362,
+           -1.3620101041273924,
+           -1.3100899153264558,
+           -1.2524236442114365,
+           -1.190240182937964,
+           -1.1248624826879985,
+           -1.057679155630615,
+           -0.9901144055450969,
+           -0.9235969837442699,
+           -0.8595288922759149,
+           -0.799254564333799,
+           -0.7440312421614511,
+           -0.6950012456964373,
+           -0.6531667814217442,
+           -0.6193678814163378,
+           -0.5942639888654019,
+           -0.5783196200892146,
+           -0.5717944365700335,
+           -0.5747379558456249,
+           -0.586989020039414,
+           -0.6081800278881593,
+           -0.6377458231542097,
+           -0.6749370220172766,
+           -0.7188374571096875,
+           -0.7683853188363654,
+           -0.8223974878576437,
+           -0.8795964782081739,
+           -0.9386393502724955,
+           -0.9981479081828268,
+           -1.0567394682089586,
+           -1.1130574740256969,
+           -1.1658012415969523,
+           -1.2137541406028682,
+           -1.2558095602288917,
+           -1.290994063694305,
+           -1.318487206701747,
+           -1.3376375782688534,
+           -1.3479747160859352,
+           -1.3492166503045178,
+           -1.341272936981238,
+           -1.3242431526289353,
+           -1.2984109317440884,
+           -1.2642337370707788,
+           -1.2223286550776422,
+           -1.1734546041511944,
+           -1.1184914280274298,
+           -1.0584164199273913,
+           -0.9942788819688864,
+           -0.9271733682797252,
+           -0.8582122878034381,
+           -0.7884985534383372,
+           -0.7190989576785507,
+           -0.6510189315507792,
+           -0.5851793040020773,
+           -0.5223956240348591,
+           -0.4633605392246864,
+           -0.40862964355463766,
+           -0.358611116814204,
+           -0.31355937944222667,
+           -0.27357288313188227,
+           -0.23859605137469167,
+           -0.20842527807380362,
+           -0.18271878907048528,
+           -0.16101007349424684,
+           -0.14272450172035095,
+           -0.12719866665269958,
+           -0.11370191704372362,
+           -0.10145949730870843,
+           -0.08967666913513442,
+           -0.0775631670922222,
+           -0.06435733397124356,
+           -0.04934929187389056,
+           -0.031902531832916296,
+           -0.0114733473005074,
+           0.01237240591739513,
+           0.03994567023058685,
+           0.07142403238137791,
+           0.10684532889412816,
+           0.14610518635126818,
+           0.1889585691592796,
+           0.2350253027091881,
+           0.2837994358077306,
+           0.33466220559925086,
+           0.3868982734725745,
+           0.4397148140620286,
+           0.49226296360924054,
+           0.54366107059081,
+           0.5930191422624622,
+           0.6394638468954257,
+           0.6821634138729604,
+           0.720351772953313,
+           0.7533512899488848,
+           0.7805934884567005,
+           0.8016371953254146,
+           0.8161836100876797,
+           0.8240878740863945,
+           0.8253668016142367,
+           0.8202025309214961,
+           0.8089419550526226,
+           0.7920918986031495,
+           0.7703101139955857,
+           0.7443922770653719,
+           0.7152552639626601,
+           0.6839170870431168,
+           0.6514739541284819,
+           0.6190749910710527,
+           0.5878952300339293,
+           0.559107513700188,
+           0.5338539975097708,
+           0.5132179471461205,
+           0.49819652642314943,
+           0.4896752514501909,
+           0.4884047508979054,
+           0.4949804201879413,
+           0.5098254907167304,
+           0.5331779553983357,
+           0.5650817008000529,
+           0.6053820961547354,
+           0.6537261829989186,
+           0.709567498705218,
+           0.7721754554530806,
+           0.8406490859504975,
+           0.9139348611862322,
+           0.9908481862635377,
+           1.070098090385201,
+           1.1503145485453343,
+           1.2300778073760585,
+           1.3079490375115337,
+           1.3825016010137998,
+           1.4523522057048908,
+           1.5161912190974411,
+           1.5728114330122362,
+           1.6211346054861677,
+           1.6602351583587651,
+           1.6893604757314251,
+           1.7079473287040945,
+           1.7156340434639548,
+           1.7122681307033825,
+           1.6979092020275448,
+           1.6728271108568173,
+           1.6374953686160951,
+           1.5925799989772642,
+           1.5389241008613148,
+           1.477528492191489,
+           1.4095288985618364,
+           1.336170231814268,
+           1.2587785710500357,
+           1.178731511213295,
+           1.0974275808178315,
+           1.016255449783714,
+           0.936563650267988,
+           0.8596315178012874,
+           0.786642027397884,
+           0.7186571504274016,
+           0.6565962941551056,
+           0.6012183085751055,
+           0.5531074564039177,
+           0.5126636440762936,
+           0.48009710672073364,
+           0.45542763098181216,
+           0.4384882888934827,
+           0.42893354651683413,
+           0.4262515054283582,
+           0.42977993597010633,
+           0.43872567087542286,
+           0.45218684866274345,
+           0.46917742996565415,
+           0.4886533583340732,
+           0.509539701227984,
+           0.5307580877654483,
+           0.551253757698855,
+           0.5700215510712996,
+           0.5861301996175243,
+           0.5987443283775092,
+           0.6071436379507962,
+           0.6107388127406467,
+           0.6090837865050358,
+           0.6018840913597048,
+           0.5890011176641465,
+           0.5704522174049721,
+           0.5464066901204333,
+           0.5171777954069513,
+           0.48321103697535833,
+           0.4450690575505746,
+           0.40341356927183347,
+           0.35898481851856057,
+           0.31257914540824133,
+           0.2650252450632506,
+           0.21715976896550465,
+           0.16980291954690396,
+           0.12373468924870942,
+           0.07967237669488306,
+           0.0382499778531406,
+           3.401949067237582e-16
+          ],
+          [
+           0,
+           -0.03394172186256633,
+           -0.06386654822261802,
+           -0.0896953294948997,
+           -0.11149371325181413,
+           -0.12947037115007567,
+           -0.1439711842118235,
+           -0.15546953254736925,
+           -0.1645529377452317,
+           -0.17190640205523047,
+           -0.1782928757120194,
+           -0.18453136006636678,
+           -0.19147321765934913,
+           -0.19997730936187177,
+           -0.21088461194286817,
+           -0.22499298605329046,
+           -0.2430327641656732,
+           -0.2656438104653787,
+           -0.2933546704540892,
+           -0.3265643779231608,
+           -0.3655274222083792,
+           -0.4103423008423934,
+           -0.46094399380076917,
+           -0.5171005976988744,
+           -0.578414253974069,
+           -0.6443263968825541,
+           -0.7141272377569465,
+           -0.7869692941484566,
+           -0.8618846689227692,
+           -0.9378056876969885,
+           -1.0135884156362511,
+           -1.0880384987861251,
+           -1.159938712731745,
+           -1.2280775540474533,
+           -1.2912781789607528,
+           -1.3484269797296038,
+           -1.398501092826316,
+           -1.4405941541051899,
+           -1.4739396542410148,
+           -1.497931301975047,
+           -1.512139871806129,
+           -1.5163260950586284,
+           -1.5104492467577606,
+           -1.494671183177329,
+           -1.4693556938005425,
+           -1.4350631440930746,
+           -1.3925404991721664,
+           -1.3427069303794978,
+           -1.2866353141800733,
+           -1.2255300330724281,
+           -1.1607015788365946,
+           -1.0935385372276922,
+           -1.0254775981955595,
+           -0.9579722852614793,
+           -0.8924611305756711,
+           -0.8303360375849869,
+           -0.7729115707583359,
+           -0.7213958914853492,
+           -0.6768640215566417,
+           -0.6402340614530304,
+           -0.6122469213213008,
+           -0.5934500396733515,
+           -0.584185470521807,
+           -0.5845826161489563,
+           -0.5945557725123635,
+           -0.6138065400987969,
+           -0.6418310376248474,
+           -0.6779317421537389,
+           -0.7212336697195587,
+           -0.770704508081293,
+           -0.8251782202548255,
+           -0.8833815562433406,
+           -0.9439628428669967,
+           -1.005522369406173,
+           -1.0666436511662167,
+           -1.1259248348850002,
+           -1.1820095095495442,
+           -1.2336162036377447,
+           -1.279565884593515,
+           -1.3188068275895537,
+           -1.350436287041726,
+           -1.3737184842508707,
+           -1.3880985159721726,
+           -1.3932118893792886,
+           -1.3888894963072458,
+           -1.375157951170882,
+           -1.3522353298141447,
+           -1.3205224579728396,
+           -1.2805900052930204,
+           -1.2331617413118239,
+           -1.1790944010231936,
+           -1.1193546873978277,
+           -1.0549940045736752,
+           -0.9871215667853918,
+           -0.9168765632382483,
+           -0.8454000772392404,
+           -0.7738074585844225,
+           -0.7031618315099251,
+           -0.6344493869188608,
+           -0.5685570579912484,
+           -0.5062531139594502,
+           -0.44817112944112236,
+           -0.3947976982417033,
+           -0.3464641632170621,
+           -0.3033425300887421,
+           -0.2654456256479167,
+           -0.2326314522772105,
+           -0.20461158389045186,
+           -0.18096334592098462,
+           -0.16114542644685562,
+           -0.14451647931590317,
+           -0.13035620537772383,
+           -0.11788833650396308,
+           -0.10630490050737545,
+           -0.09479111450243928,
+           -0.08255024043130667,
+           -0.06882773973191468,
+           -0.052934084343782196,
+           -0.034265617898266466,
+           -0.012322913077442488,
+           0.013273862586409385,
+           0.04277298145181878,
+           0.07628291082946204,
+           0.11376801075536788,
+           0.1550482937658308,
+           0.19980325976621374,
+           0.2475797124879792,
+           0.2978033597368931,
+           0.3497939002998958,
+           0.40278320852447275,
+           0.4559361455516343,
+           0.5083734560650652,
+           0.5591961530098073,
+           0.6075107514857372,
+           0.6524546880056605,
+           0.6932212531897292,
+           0.7290833749873332,
+           0.759415615484588,
+           0.7837137866536263,
+           0.8016116480015771,
+           0.8128942205689121,
+           0.8175073353442809,
+           0.8155631278341123,
+           0.807341291922537,
+           0.7932860127545275,
+           0.773998607511464,
+           0.7502260118933034,
+           0.7228453561439148,
+           0.6928449748915317,
+           0.6613022873940337,
+           0.6293590666450145,
+           0.5981946851325365,
+           0.5689979800767246,
+           0.542938420285461,
+           0.5211372793275764,
+           0.504639524912196,
+           0.49438712199315243,
+           0.4911944174362495,
+           0.49572622777124636,
+           0.5084791896905744,
+           0.5297668570307582,
+           0.5597089398091901,
+           0.5982249826235402,
+           0.6450326737430006,
+           0.6996508651139252,
+           0.7614072699832164,
+           0.8294506916915197,
+           0.9027675271809203,
+           0.9802021846026704,
+           1.0604809586630992,
+           1.1422388223722475,
+           1.224048521759637,
+           1.3044513026814568,
+           1.3819885574928847,
+           1.4552336551331195,
+           1.5228232116867386,
+           1.5834870699244232,
+           1.636076285432771,
+           1.6795884630260138,
+           1.7131898490856265,
+           1.7362336618010512,
+           1.7482742301374832,
+           1.7490766115788914,
+           1.738621465876,
+           1.7171050745646896,
+           1.6849345111737923,
+           1.642718082012757,
+           1.5912512694243863,
+           1.5314985156849443,
+           1.4645712837533853,
+           1.3917029184375784,
+           1.314220906144741,
+           1.2335171914171572,
+           1.1510172524823465,
+           1.0681486650223975,
+           0.9863098926626261,
+           0.9068400341022647,
+           0.8309902306043846,
+           0.7598973944069589,
+           0.6945608596041651,
+           0.6358224836575587,
+           0.5843506417616163,
+           0.5406284599438391,
+           0.5049465284150614,
+           0.477400226881835,
+           0.45789168100055255,
+           0.44613625666432677,
+           0.441673389133792,
+           0.44388143984229095,
+           0.4519961775727325,
+           0.46513239496189585,
+           0.48230809802001223,
+           0.5024706473275902,
+           0.5245241861994068,
+           0.5473576644081605,
+           0.5698727566419821,
+           0.5910109829054885,
+           0.6097793633037645,
+           0.6252739813862904,
+           0.6367008873778592,
+           0.6433938437093811,
+           0.6448284984622479,
+           0.6406326655368801,
+           0.6305924911852845,
+           0.6146543924594333,
+           0.5929227614505675,
+           0.5656535372024147,
+           0.5332438521604945,
+           0.49621805933701346,
+           0.4552105375400816,
+           0.41094575275883954,
+           0.3642161220995971,
+           0.3158582808343738,
+           0.266728391811604,
+           0.21767715873931553,
+           0.16952521014785682,
+           0.12303950906325713,
+           0.07891141489450801,
+           0.03773697950054535,
+           3.3435443864747144e-16
+          ],
+          [
+           0,
+           -0.033138241708229016,
+           -0.06215043952422576,
+           -0.08703143218853569,
+           -0.10792286670708157,
+           -0.12510909782063215,
+           -0.1390090456867139,
+           -0.15016422051227904,
+           -0.1592232234968019,
+           -0.16692312625655636,
+           -0.1740682135383943,
+           -0.18150664438684994,
+           -0.19010564320093537,
+           -0.2007258728586272,
+           -0.21419566623934266,
+           -0.2312857993954633,
+           -0.2526854791037232,
+           -0.2789801897948506,
+           -0.3106320005770558,
+           -0.3479628733144385,
+           -0.3911414389641437,
+           -0.4401736234389834,
+           -0.4948974082771459,
+           -0.5549819077550727,
+           -0.619930835357932,
+           -0.6890903214408495,
+           -0.7616609332543554,
+           -0.8367136410459421,
+           -0.9132093723887074,
+           -0.99002170378921,
+           -1.065962156345318,
+           -1.139807492852802,
+           -1.21032835907077,
+           -1.2763185732640916,
+           -1.3366243466612848,
+           -1.390172713691798,
+           -1.435998464951447,
+           -1.4732689075003345,
+           -1.5013058255988985,
+           -1.5196040791904653,
+           -1.5278463558074675,
+           -1.5259136822237525,
+           -1.5138914029001993,
+           -1.4920704406245195,
+           -1.460943768084602,
+           -1.4211981346659146,
+           -1.3737012076952344,
+           -1.3194843988432732,
+           -1.2597217517056831,
+           -1.195705363110451,
+           -1.128817896067461,
+           -1.060502814370663,
+           -0.9922330258961903,
+           -0.9254786621894949,
+           -0.8616747449827973,
+           -0.8021894952408233,
+           -0.7482940270507938,
+           -0.7011341374525856,
+           -0.6617048548863665,
+           -0.6308283444805355,
+           -0.6091356894676585,
+           -0.59705297651156,
+           -0.5947920108743102,
+           -0.6023458776210568,
+           -0.6194894501202832,
+           -0.6457848297413693,
+           -0.6805915837335244,
+           -0.7230815346321894,
+           -0.7722577469415179,
+           -0.826977257896266,
+           -0.885977011211771,
+           -0.9479023780128667,
+           -1.0113375893937604,
+           -1.0748373617341045,
+           -1.1369589700123908,
+           -1.196294016516885,
+           -1.25149915271583,
+           -1.3013250403235135,
+           -1.3446428830602062,
+           -1.380467922103548,
+           -1.4079793642265979,
+           -1.4265363002198204,
+           -1.4356892702001334,
+           -1.4351872393679836,
+           -1.4249798600394232,
+           -1.4052150105859207,
+           -1.3762317164337248,
+           -1.338548669694292,
+           -1.2928486695865196,
+           -1.2399594029895507,
+           -1.1808310708639755,
+           -1.1165114398035978,
+           -1.0481189568566998,
+           -0.9768146085790637,
+           -0.9037732310453918,
+           -0.8301549856715867,
+           -0.757077706046397,
+           -0.6855907938380287,
+           -0.6166512979641681,
+           -0.5511027517411803,
+           -0.4896572691954463,
+           -0.4328813160077513,
+           -0.38118547485194865,
+           -0.33481842160718794,
+           -0.2938652206786177,
+           -0.25824993718315487,
+           -0.22774245382325872,
+           -0.2019692736427523,
+           -0.18042798920661093,
+           -0.16250500658903852,
+           -0.14749603119163274,
+           -0.13462875387222514,
+           -0.1230871218464669,
+           -0.11203654066290276,
+           -0.1006493321824638,
+           -0.08812976942629597,
+           -0.07373802246729433,
+           -0.05681237986909669,
+           -0.03678915673219637,
+           -0.013219761993022189,
+           0.014215527336728049,
+           0.04569745071947308,
+           0.08126157723594729,
+           0.12079621430601649,
+           0.16404447185364682,
+           0.21061043309882266,
+           0.2599692756633918,
+           0.3114810831010607,
+           0.36440798993658957,
+           0.4179342152941172,
+           0.47118846345265875,
+           0.5232681061488653,
+           0.5732645127827476,
+           0.6202888621284979,
+           0.663497753562596,
+           0.7021179376225691,
+           0.7354695048921442,
+           0.7629869083256484,
+           0.784237246303324,
+           0.7989353006720381,
+           0.8069549041215731,
+           0.808336302491862,
+           0.8032892777342262,
+           0.7921919037665028,
+           0.775584917708772,
+           0.7541618002062975,
+           0.7287547679511635,
+           0.7003169863562785,
+           0.6699014079743512,
+           0.6386367302241015,
+           0.607701042055861,
+           0.5782937914194589,
+           0.5516067521906234,
+           0.5287946993491885,
+           0.5109465138769614,
+           0.4990574336798447,
+           0.4940031439054119,
+           0.4965163598317687,
+           0.5071664989836739,
+           0.5263429676315035,
+           0.5542425020655184,
+           0.5908609090614615,
+           0.6359894450948573,
+           0.6892159626757226,
+           0.7499308373791295,
+           0.8173375735510578,
+           0.8904678731091266,
+           0.968200843124464,
+           1.0492859166413118,
+           1.1323689699610744,
+           1.2160210406417595,
+           1.2987689856991198,
+           1.3791273705515803,
+           1.4556308473517963,
+           1.526866267299313,
+           1.5915037757016817,
+           1.6483261608683102,
+           1.6962557678604886,
+           1.734378344728919,
+           1.7619632607829405,
+           1.7784796219155092,
+           1.7836079049825782,
+           1.777246839351508,
+           1.7595153764121023,
+           1.7307497043470847,
+           1.691495382953697,
+           1.6424947889383497,
+           1.5846701730618071,
+           1.5191027340989702,
+           1.4470082082818145,
+           1.369709554447577,
+           1.2886073825462439,
+           1.2051488248493296,
+           1.120795583910518,
+           1.0369919082392451,
+           0.9551332453804886,
+           0.8765363027125646,
+           0.8024112092892501,
+           0.7338364184038542,
+           0.6717369215890023,
+           0.6168662622096474,
+           0.5697927427109918,
+           0.5308901162818341,
+           0.5003329437425007,
+           0.4780966825797819,
+           0.4639624600352508,
+           0.45752636883632597,
+           0.45821301532184516,
+           0.4652929480200295,
+           0.4779035026683398,
+           0.49507251946051994,
+           0.5157443219063821,
+           0.5388072956888693,
+           0.5631223715099121,
+           0.5875516989266163,
+           0.6109867989538454,
+           0.6323755016680149,
+           0.6507470106705965,
+           0.6652344881136824,
+           0.6750946207074594,
+           0.6797237070073842,
+           0.6786698972792433,
+           0.6716413170525914,
+           0.6585099115717379,
+           0.639310958060774,
+           0.6142383032733175,
+           0.5836354924201134,
+           0.5479830595343461,
+           0.5078823460420898,
+           0.4640363013373009,
+           0.41722779434686624,
+           0.36829602654185817,
+           0.31811168308373244,
+           0.2675514886506556,
+           0.21747284724452093,
+           0.16868924063920648,
+           0.12194703823847869,
+           0.07790433254512706,
+           0.037112360197905724,
+           3.275979950864031e-16
+          ],
+          [
+           0,
+           -0.0322627477314268,
+           -0.06032506913835416,
+           -0.08425832754395354,
+           -0.10428139460873881,
+           -0.12075417702138577,
+           -0.1341671393566604,
+           -0.14512709478602315,
+           -0.1543396334273189,
+           -0.16258864685545377,
+           -0.17071348440480635,
+           -0.1795843404064281,
+           -0.19007651978980733,
+           -0.2030442612929715,
+           -0.21929481203222875,
+           -0.23956344398474744,
+           -0.2644900820791942,
+           -0.2945981755617215,
+           -0.33027639002892656,
+           -0.37176362832787213,
+           -0.4191378061244819,
+           -0.47230871437865457,
+           -0.531015198564062,
+           -0.5948267757855498,
+           -0.6631496986924079,
+           -0.7352373620716264,
+           -0.8102048370662012,
+           -0.8870472118886592,
+           -0.9646613193624708,
+           -1.041870343115012,
+           -1.1174507180115487,
+           -1.1901606784057062,
+           -1.2587697615835676,
+           -1.3220885446012627,
+           -1.3789978813444452,
+           -1.4284769134161939,
+           -1.4696291532815526,
+           -1.501705980407841,
+           -1.5241269499507406,
+           -1.5364963874466326,
+           -1.538615830204248,
+           -1.5304919745324888,
+           -1.5123398952035918,
+           -1.4845814170160352,
+           -1.4478386352158317,
+           -1.4029226989938344,
+           -1.3508180874171238,
+           -1.2926627171426872,
+           -1.2297243233917519,
+           -1.1633736474124994,
+           -1.0950550427577068,
+           -1.026255177190699,
+           -0.9584705553014734,
+           -0.8931746177564064,
+           -0.8317851857355499,
+           -0.775633013194872,
+           -0.7259321852437709,
+           -0.6837530587206684,
+           -0.6499983819891199,
+           -0.6253831564850575,
+           -0.6104187144231327,
+           -0.6054013874513573,
+           -0.610406032346146,
+           -0.6252845647044559,
+           -0.649669532814453,
+           -0.6829826443584235,
+           -0.7244480412271591,
+           -0.7731100053560914,
+           -0.8278546738590856,
+           -0.8874352473741655,
+           -0.9505000937324652,
+           -1.0156230817935246,
+           -1.0813354291760178,
+           -1.14615831387499,
+           -1.2086354841897213,
+           -1.2673651043393561,
+           -1.321030094510735,
+           -1.3684262633076696,
+           -1.4084875866583437,
+           -1.4403080587815313,
+           -1.463159626027933,
+           -1.4765058111838711,
+           -1.480010741752777,
+           -1.4735434081973862,
+           -1.4571770943577989,
+           -1.431184039395914,
+           -1.3960255057769246,
+           -1.3523375381599412,
+           -1.3009128009329933,
+           -1.2426789749841762,
+           -1.1786742748946994,
+           -1.1100207141233456,
+           -1.037895796333512,
+           -0.9635033445965585,
+           -0.8880441960153871,
+           -0.8126874870192511,
+           -0.7385432343038784,
+           -0.6666368786953834,
+           -0.597886405099257,
+           -0.5330825825597385,
+           -0.472872786074136,
+           -0.41774876828054025,
+           -0.36803864683885124,
+           -0.32390326484089654,
+           -0.2853369696509646,
+           -0.25217274301002307,
+           -0.2240915048613901,
+           -0.20063530793928544,
+           -0.18122404234148137,
+           -0.16517518152539734,
+           -0.15172602561002238,
+           -0.14005783641035494,
+           -0.1293212127964629,
+           -0.11866202588125492,
+           -0.10724722190291479,
+           -0.09428980674366882,
+           -0.07907234963441932,
+           -0.060968384112236,
+           -0.03946114067733235,
+           -0.014159116391973698,
+           0.015191929932248932,
+           0.04870087442481452,
+           0.08632723220727993,
+           0.12788137680042286,
+           0.1730289726209835,
+           0.2212995080643619,
+           0.2720987092567236,
+           0.32472451270013714,
+           0.378386181317575,
+           0.43222606521675594,
+           0.4853434379554015,
+           0.5368197830103966,
+           0.5857448649724467,
+           0.6312428967497996,
+           0.6724981083877862,
+           0.7087790351728164,
+           0.7394608722212309,
+           0.7640452890469493,
+           0.782177159526582,
+           0.7936577387115976,
+           0.7984539061926892,
+           0.7967031940097291,
+           0.7887144229745047,
+           0.7749638820904936,
+           0.7560870987430488,
+           0.7328663596633949,
+           0.7062142515201232,
+           0.6771535926227445,
+           0.6467942210427873,
+           0.6163071870932333,
+           0.5868969674538307,
+           0.5597723725122422,
+           0.5361168563041274,
+           0.5170589587809418,
+           0.5036436124462248,
+           0.496805029560169,
+           0.4973418524494989,
+           0.5058951987491831,
+           0.5229301668427343,
+           0.5487212859526048,
+           0.5833423022116996,
+           0.626660588879936,
+           0.6783363581680749,
+           0.7378267365977795,
+           0.8043946482898454,
+           0.8771223339143599,
+           0.9549292201240073,
+           1.036593747903456,
+           1.12077867102782,
+           1.2060592501338778,
+           1.2909536958914385,
+           1.3739551582083311,
+           1.453564518722762,
+           1.5283232220311915,
+           1.596845377729328,
+           1.6578483805195243,
+           1.7101813290146761,
+           1.7528505746557548,
+           1.7850417991389937,
+           1.8061381003036725,
+           1.8157336605885603,
+           1.8136426766411167,
+           1.799903340921827,
+           1.774776783458981,
+           1.7387410014249645,
+           1.6924799230183392,
+           1.6368678673587016,
+           1.57294977093428,
+           1.501917650943619,
+           1.425083864223178,
+           1.3438517952146773,
+           1.2596846657958125,
+           1.174073202351368,
+           1.0885029201865442,
+           1.0044217917070342,
+           0.9232090525891452,
+           0.8461458697703452,
+           0.7743885472842854,
+           0.7089448819485552,
+           0.650654202289401,
+           0.6001715328112521,
+           0.5579562240549077,
+           0.5242652793522448,
+           0.4991514944820642,
+           0.4824664093879551,
+           0.47386795461365705,
+           0.47283256200437745,
+           0.4786714022836194,
+           0.49055031395653864,
+           0.5075129010020758,
+           0.5285062031054536,
+           0.5524082835251383,
+           0.5780570374830764,
+           0.6042794992016483,
+           0.6299209189392373,
+           0.6538728927046882,
+           0.6750998564155444,
+           0.6926633023225528,
+           0.7057431373492487,
+           0.7136556789973252,
+           0.7158678727032481,
+           0.7120074127554389,
+           0.7018685546073157,
+           0.6854135169796454,
+           0.6627694847515024,
+           0.6342213354623987,
+           0.6002003204835398,
+           0.5612690338537079,
+           0.5181030948670678,
+           0.47147005242502066,
+           0.4222060878839565,
+           0.37119114694216027,
+           0.3193231686854497,
+           0.2674921003350558,
+           0.216554389027724,
+           0.1673086270658955,
+           0.12047299490834708,
+           0.07666509756661942,
+           0.03638472628063099,
+           3.2001946256190825e-16
+          ],
+          [
+           0,
+           -0.03132763444244964,
+           -0.05841709211584577,
+           -0.0814180910022448,
+           -0.10062719748529418,
+           -0.11647895777996314,
+           -0.1295331024073525,
+           -0.14045815800878017,
+           -0.15001189536408574,
+           -0.15901912616267547,
+           -0.16834743173772787,
+           -0.17888146280631562,
+           -0.1914964888251196,
+           -0.2070318978453357,
+           -0.22626535213799004,
+           -0.24988829121832054,
+           -0.2784834425346967,
+           -0.3125049517593167,
+           -0.352261680507768,
+           -0.39790414100393806,
+           -0.4494154466363727,
+           -0.5066065567737366,
+           -0.5691159861273346,
+           -0.6364140360673347,
+           -0.7078114904414646,
+           -0.7824726044909717,
+           -0.8594321052719949,
+           -0.9376158183468837,
+           -1.015864441027237,
+           -1.0929598995236292,
+           -1.1676536580980692,
+           -1.2386962945001767,
+           -1.3048676189920847,
+           -1.3650065951093313,
+           -1.4180403195036846,
+           -1.4630113358519297,
+           -1.4991025935174622,
+           -1.525659414594993,
+           -1.5422079018993435,
+           -1.5484693037246955,
+           -1.5443699467896488,
+           -1.5300464543755603,
+           -1.5058460796882047,
+           -1.4723221021640056,
+           -1.430224353919543,
+           -1.3804850618742037,
+           -1.3242003053512936,
+           -1.2626074963675298,
+           -1.1970593877038318,
+           -1.1289951997910481,
+           -1.0599095293113925,
+           -0.9913197584223681,
+           -0.9247327222530748,
+           -0.861611412825185,
+           -0.8033424992793734,
+           -0.7512054271713078,
+           -0.7063438240289653,
+           -0.669739885178307,
+           -0.6421923443225263,
+           -0.6242985491777384,
+           -0.6164410656620888,
+           -0.6187791270525103,
+           -0.6312451297635155,
+           -0.6535462577534291,
+           -0.685171195933651,
+           -0.725401772302655,
+           -0.7733292517811792,
+           -0.827874894724716,
+           -0.8878142925046016,
+           -0.951804903818085,
+           -1.0184161406584686,
+           -1.0861612939512404,
+           -1.1535305471559736,
+           -1.2190243026380703,
+           -1.2811860408735936,
+           -1.3386339466487354,
+           -1.3900905689749858,
+           -1.4344098316321177,
+           -1.470600777811688,
+           -1.4978475136032743,
+           -1.5155249090233498,
+           -1.5232097196049807,
+           -1.5206869036658233,
+           -1.5079510274868484,
+           -1.4852027698807426,
+           -1.4528406560761191,
+           -1.411448265586226,
+           -1.3617772669606694,
+           -1.304726731394216,
+           -1.24131926467814,
+           -1.172674570807827,
+           -1.0999811189293378,
+           -1.0244666268277658,
+           -0.9473680978620265,
+           -0.8699021536083983,
+           -0.7932363914189188,
+           -0.7184624650178701,
+           -0.6465715379839622,
+           -0.5784326957568583,
+           -0.5147748233168119,
+           -0.45617236492008484,
+           -0.40303528153595247,
+           -0.3556034134727475,
+           -0.31394534282960224,
+           -0.27796173570730937,
+           -0.24739303043728125,
+           -0.22183122829099408,
+           -0.20073543996081236,
+           -0.18345074713268855,
+           -0.16922985604302557,
+           -0.1572569510739403,
+           -0.14667310289700375,
+           -0.1366025487427861,
+           -0.12617914295079993,
+           -0.11457227449924014,
+           -0.10101156473177451,
+           -0.08480969254311692,
+           -0.06538274496934496,
+           -0.04226755714819136,
+           -0.015135585279005291,
+           0.01619705251054673,
+           0.051763631917414975,
+           0.0914451320632958,
+           0.13497284486422567,
+           0.18193521760662432,
+           0.23178875135769106,
+           0.2838726715194332,
+           0.3374269877093269,
+           0.3916134707383389,
+           0.4455389970367451,
+           0.49828064742754785,
+           0.5489118992930142,
+           0.5965292201577835,
+           0.6402783573350955,
+           0.6793796229206578,
+           0.7131514959886305,
+           0.7410319038118022,
+           0.7625966003210192,
+           0.7775741314506832,
+           0.7858569617210789,
+           0.7875084322817932,
+           0.7827653252966728,
+           0.7720359203784919,
+           0.7558935430096472,
+           0.7350657196520651,
+           0.7104191666742327,
+           0.682940947477379,
+           0.6537162315812104,
+           0.6239031784175867,
+           0.5947055449180382,
+           0.5673436777174558,
+           0.543024596341274,
+           0.5229119019060082,
+           0.5080962558819785,
+           0.4995671650307691,
+           0.4981867818846474,
+           0.504666385682048,
+           0.519546147554132,
+           0.5431787074298098,
+           0.5757170004278943,
+           0.6171066696077445,
+           0.6670832923078964,
+           0.7251745315913815,
+           0.7907072053674726,
+           0.862819146488965,
+           0.9404756104617267,
+           1.022489876220745,
+           1.1075475824649406,
+           1.1942342498459648,
+           1.2810653601566862,
+           1.366518299528792,
+           1.449065425125475,
+           1.5272074850979385,
+           1.5995066104218907,
+           1.6646181049444895,
+           1.721320286394827,
+           1.7685416756231283,
+           1.8053848928730103,
+           1.8311466969769234,
+           1.8453336941348428,
+           1.847673345191764,
+           1.8381200115896708,
+           1.8168558977322946,
+           1.784286868509228,
+           1.741033242238136,
+           1.6879157783461933,
+           1.6259371928309927,
+           1.55625964015513,
+           1.4801786951750064,
+           1.399094450683059,
+           1.3144804131726022,
+           1.227850929901466,
+           1.1407279130287575,
+           1.0546076407572758,
+           0.9709284107174418,
+           0.8910397974243756,
+           0.8161742241337158,
+           0.7474215008630103,
+           0.6857069061995936,
+           0.6317733026299953,
+           0.5861676756801716,
+           0.549232378611993,
+           0.5211012494600273,
+           0.5017006486473152,
+           0.4907553462060084,
+           0.4877990706755278,
+           0.4921894199230752,
+           0.5031267301618584,
+           0.5196764058650242,
+           0.5407941323593191,
+           0.5653533265855961,
+           0.592174131420911,
+           0.6200532262526651,
+           0.647793711928431,
+           0.6742343320746932,
+           0.6982773149244512,
+           0.7189141596045596,
+           0.7352487472593472,
+           0.7465172289663623,
+           0.7521042272990555,
+           0.751554984448015,
+           0.7445831945915442,
+           0.7310743690610758,
+           0.7110846969834342,
+           0.6848354786308728,
+           0.6527033207970561,
+           0.6152063903356154,
+           0.5729871208779559,
+           0.5267918562219994,
+           0.47744798975254205,
+           0.4258392206348757,
+           0.37287959290108313,
+           0.31948701181151284,
+           0.26655694234209837,
+           0.21493698708925624,
+           0.1654030155193899,
+           0.11863747398809728,
+           0.07521044741445802,
+           0.035563970420317476,
+           3.1172358503268607e-16
+          ],
+          [
+           0,
+           -0.030346202889008602,
+           -0.056454631192609545,
+           -0.07855444350393512,
+           -0.09701959125313572,
+           -0.11235755606639118,
+           -0.12519427640087938,
+           -0.13625565937236989,
+           -0.14634616372765485,
+           -0.15632501759037795,
+           -0.16708069794255254,
+           -0.1795043461717383,
+           -0.1944628241928497,
+           -0.2127721278529809,
+           -0.23517186820836172,
+           -0.26230150694608406,
+           -0.2946789902890368,
+           -0.332682367193807,
+           -0.3765349039700439,
+           -0.42629412044072473,
+           -0.48184507458848364,
+           -0.5428981157399717,
+           -0.6089912133978941,
+           -0.6794968526649536,
+           -0.7536333707280543,
+           -0.8304804950108359,
+           -0.9089987352246227,
+           -0.988052181387903,
+           -1.0664341704786422,
+           -1.1428952080055637,
+           -1.2161724693869176,
+           -1.2850201611928445,
+           -1.3482399952147723,
+           -1.4047110197088297,
+           -1.4534180622978585,
+           -1.4934780677209964,
+           -1.5241636602417832,
+           -1.5449233239701188,
+           -1.5553976731051682,
+           -1.5554313762677074,
+           -1.5450804024275087,
+           -1.5246143679286706,
+           -1.4945138820385206,
+           -1.455462909406782,
+           -1.4083362888532096,
+           -1.3541826660285208,
+           -1.2942032098055962,
+           -1.2297265859840583,
+           -1.1621807544667901,
+           -1.0930622351964792,
+           -1.0239035518566815,
+           -0.9562396090531138,
+           -0.8915737872209611,
+           -0.831344549121783,
+           -0.7768933422313447,
+           -0.7294345527801285,
+           -0.6900282203595066,
+           -0.6595561579668842,
+           -0.6387020426722632,
+           -0.6279359486719261,
+           -0.6275036896142329,
+           -0.6374212232821326,
+           -0.657474251760368,
+           -0.687223027017482,
+           -0.7260122483882439,
+           -0.7729858177519998,
+           -0.8271061031996395,
+           -0.8871772554599929,
+           -0.9518720259001465,
+           -1.0197614528364594,
+           -1.0893467161780033,
+           -1.1590924106783065,
+           -1.227460456484762,
+           -1.2929438529913424,
+           -1.3540994885002473,
+           -1.4095792436905568,
+           -1.4581586707221241,
+           -1.4987625908654134,
+           -1.5304870303175582,
+           -1.5526170044321232,
+           -1.5646397627101531,
+           -1.566253218048031,
+           -1.5573694011706578,
+           -1.5381129020045832,
+           -1.5088143809942345,
+           -1.4699993520606536,
+           -1.4223725521396342,
+           -1.3667983172494578,
+           -1.304277479270243,
+           -1.2359213787821544,
+           -1.1629236554503801,
+           -1.0865305269792922,
+           -1.0080102994186058,
+           -0.9286228648661106,
+           -0.8495899371091616,
+           -0.7720667516818669,
+           -0.6971159148473407,
+           -0.6256840272485239,
+           -0.5585816339258922,
+           -0.4964669649708054,
+           -0.43983383249410263,
+           -0.38900394233740004,
+           -0.34412376574769227,
+           -0.305165999924423,
+           -0.2719355298542899,
+           -0.24407969009346397,
+           -0.22110251698584665,
+           -0.2023825819209515,
+           -0.18719390712481407,
+           -0.17472938935670632,
+           -0.16412609563873715,
+           -0.1544917502840043,
+           -0.14493170510776082,
+           -0.13457567546064614,
+           -0.12260353381249857,
+           -0.1082694797777527,
+           -0.09092394999288712,
+           -0.07003269198096898,
+           -0.0451925015093223,
+           -0.016143211037638567,
+           0.017224384579896754,
+           0.05486487244147145,
+           0.09657893150373936,
+           0.1420183893446243,
+           0.1906954933477798,
+           0.24199615350933124,
+           0.295196809874899,
+           0.3494844822426368,
+           0.403979475643619,
+           0.45776014437938983,
+           0.5098890618672155,
+           0.5594399046438757,
+           0.6055243376187712,
+           0.6473181846135669,
+           0.6840861834875706,
+           0.715204658374233,
+           0.74018149194055,
+           0.7586728468914354,
+           0.7704961665368889,
+           0.7756390771210815,
+           0.7742639174677033,
+           0.766707731759057,
+           0.7534776761808069,
+           0.7352419068519579,
+           0.7128161319916324,
+           0.6871461227455902,
+           0.6592865816956519,
+           0.6303768631605283,
+           0.601614122554253,
+           0.574224541178772,
+           0.5494333261159897,
+           0.5284342209673921,
+           0.51235928110814,
+           0.502249666367942,
+           0.4990281845780344,
+           0.5034742816512362,
+           0.5162021186654453,
+           0.5376423051090343,
+           0.5680277717310417,
+           0.6073841683920308,
+           0.6555250643151344,
+           0.7120521128241912,
+           0.776360222846897,
+           0.8476476580919006,
+           0.9249308648606674,
+           1.0070637138793208,
+           1.0927607331820468,
+           1.1806238106220914,
+           1.269171758466869,
+           1.3568720608877605,
+           1.4421740697679775,
+           1.5235428765122174,
+           1.5994930684054582,
+           1.6686215780371911,
+           1.7296388534133087,
+           1.7813976141848897,
+           1.8229185150347897,
+           1.8534121093462521,
+           1.8722965930951512,
+           1.8792109083584598,
+           1.8740228955059899,
+           1.856832300378026,
+           1.827968564700394,
+           1.7879834516866913,
+           1.7376386812178997,
+           1.6778888671961494,
+           1.6098601607701055,
+           1.5348251044265175,
+           1.454174290980022,
+           1.369385496115509,
+           1.2819910115441309,
+           1.1935439466221092,
+           1.1055842884814044,
+           1.0196055138195719,
+           0.9370225294470741,
+           0.8591416839192005,
+           0.7871335399687686,
+           0.7220090283245322,
+           0.6645995195716171,
+           0.615541254067549,
+           0.5752644629633201,
+           0.5439873987350018,
+           0.5217153741343526,
+           0.5082447870567007,
+           0.5031719884831768,
+           0.5059067343318574,
+           0.5156898525932487,
+           0.5316146571993646,
+           0.552651552111188,
+           0.5776751952345649,
+           0.6054935337647637,
+           0.6348779817941133,
+           0.664593988444339,
+           0.6934312409018731,
+           0.7202327615727783,
+           0.743922191701573,
+           0.763528604330004,
+           0.7782082560920861,
+           0.7872627683382174,
+           0.7901533213872545,
+           0.7865105489533398,
+           0.7761399303730614,
+           0.7590225933804535,
+           0.7353115569472374,
+           0.7053235591927429,
+           0.6695267266800444,
+           0.6285244457689084,
+           0.5830358914894447,
+           0.5338737522733636,
+           0.4819197577763219,
+           0.42809867024214376,
+           0.3733514360911625,
+           0.31860821278208656,
+           0.26476198607094986,
+           0.2126434746034193,
+           0.1629979828186424,
+           0.116464810350627,
+           0.0735597578466227,
+           0.03466118712901737,
+           3.0282501447570647e-16
+          ],
+          [
+           0,
+           -0.029332531204024855,
+           -0.054466994199385416,
+           -0.07571229951555315,
+           -0.09351867771574,
+           -0.1084640481379693,
+           -0.12123673251579499,
+           -0.13261496937817088,
+           -0.14344376963854838,
+           -0.15460972452883764,
+           -0.16701443220557693,
+           -0.181547247535784,
+           -0.1990580797676194,
+           -0.22033096446715614,
+           -0.24605911918395187,
+           -0.2768221571893109,
+           -0.31306608116504714,
+           -0.35508661019753646,
+           -0.403016310547688,
+           -0.45681590548139295,
+           -0.5162700343286704,
+           -0.5809876185178243,
+           -0.6504068754165616,
+           -0.7238049023357277,
+           -0.8003116359888737,
+           -0.8789278799983696,
+           -0.9585469875393925,
+           -1.0379796905859553,
+           -1.1159814838962085,
+           -1.1912819029741153,
+           -1.2626149825419695,
+           -1.3287501469248213,
+           -1.3885227671197684,
+           -1.4408636216787116,
+           -1.4848265198791304,
+           -1.519613385528645,
+           -1.5445961572190856,
+           -1.5593349345491505,
+           -1.5635918880004487,
+           -1.557340550646292,
+           -1.54077022025261,
+           -1.514285317902372,
+           -1.478499671161969,
+           -1.4342258130205339,
+           -1.3824595093428327,
+           -1.3243598443908122,
+           -1.2612253032060343,
+           -1.194466388604087,
+           -1.1255753967607143,
+           -1.056094046724098,
+           -0.9875797138884047,
+           -0.9215710541359872,
+           -0.8595538230669265,
+           -0.8029276930164034,
+           -0.7529748494207753,
+           -0.7108311080168586,
+           -0.6774602362952477,
+           -0.6536320879694306,
+           -0.6399050697670496,
+           -0.6366133577616706,
+           -0.6438591682167033,
+           -0.6615102682319487,
+           -0.6892027872747781,
+           -0.7263492649610538,
+           -0.7721517462816513,
+           -0.8256196158673925,
+           -0.8855917507544306,
+           -0.9507624691768519,
+           -1.0197106636455553,
+           -1.09093143213389,
+           -1.1628694633780068,
+           -1.233953392502152,
+           -1.302630322343032,
+           -1.3673997044536141,
+           -1.426845791820576,
+           -1.4796679123579195,
+           -1.524707867306217,
+           -1.560973830393779,
+           -1.5876602102185007,
+           -1.6041630376396852,
+           -1.6100905495713662,
+           -1.6052687577378888,
+           -1.5897419128023658,
+           -1.563767897813442,
+           -1.5278087071032398,
+           -1.4825162846169082,
+           -1.4287141062815152,
+           -1.3673749917332767,
+           -1.2995957190711358,
+           -1.226569090156359,
+           -1.1495541515590093,
+           -1.0698453161967214,
+           -0.9887411520914259,
+           -0.9075136070204868,
+           -0.8273784211664551,
+           -0.7494674446533385,
+           -0.6748035240341034,
+           -0.6042785527366875,
+           -0.5386351969571633,
+           -0.47845271263681666,
+           -0.4241371634060436,
+           -0.3759162363933392,
+           -0.3338387354290709,
+           -0.29777871237042913,
+           -0.26744408001522735,
+           -0.24238943729276852,
+           -0.22203273193644188,
+           -0.20567529028413734,
+           -0.1925246605945716,
+           -0.18171964737360013,
+           -0.17235686137446735,
+           -0.16351807446404137,
+           -0.15429765129024628,
+           -0.14382933104244117,
+           -0.13131165249664145,
+           -0.11603135344552305,
+           -0.0973841305411866,
+           -0.07489221611167665,
+           -0.048218312843719115,
+           -0.01717552320168399,
+           0.018266984368052467,
+           0.057982718692111065,
+           0.10169104943468263,
+           0.14896474566918372,
+           0.1992416701929576,
+           0.2518403214445722,
+           0.3059788138581712,
+           0.3607967968846148,
+           0.4153797350323202,
+           0.4687849081194838,
+           0.5200684441023458,
+           0.5683126675592723,
+           0.6126530359351872,
+           0.6523039432924449,
+           0.6865826974113841,
+           0.7149310200110278,
+           0.736933480542619,
+           0.7523323499482653,
+           0.7610384500905215,
+           0.7631376750239134,
+           0.7588929693902321,
+           0.7487416642484884,
+           0.7332881887168572,
+           0.7132922939455478,
+           0.6896530411857057,
+           0.6633889151669862,
+           0.6356145248799887,
+           0.6075144436232242,
+           0.5803148165328721,
+           0.5552534248126219,
+           0.5335489399443032,
+           0.5163701271298867,
+           0.5048057643826351,
+           0.4998360318059194,
+           0.5023060949027854,
+           0.5129025569452281,
+           0.5321333896490226,
+           0.5603118702207074,
+           0.597544958226246,
+           0.6437264399715124,
+           0.6985350537594897,
+           0.7614376892915896,
+           0.8316976315533672,
+           0.908387696786278,
+           0.9904079886166811,
+           1.0765078890374273,
+           1.165311794516425,
+           1.2553480146246176,
+           1.3450801715384255,
+           1.4329403755464476,
+           1.5173634058593035,
+           1.596821098742509,
+           1.6698561369670877,
+           1.7351144460332808,
+           1.7913754333211052,
+           1.8375793555392217,
+           1.8728511664058718,
+           1.8965202788021924,
+           1.908135771701786,
+           1.907476679674661,
+           1.8945571190818267,
+           1.8696261273942858,
+           1.8331622174148956,
+           1.7858627735066297,
+           1.7286285391895402,
+           1.6625435616896034,
+           1.5888510663825528,
+           1.50892582996867,
+           1.424243703316945,
+           1.3363490012429757,
+           1.2468205254374878,
+           1.1572370171693922,
+           1.0691428475332327,
+           0.9840147446522033,
+           0.9032303296186976,
+           0.8280391867620658,
+           0.7595371302383219,
+           0.6986442495254417,
+           0.6460872231529526,
+           0.6023862852044768,
+           0.5678471153957572,
+           0.542557803652172,
+           0.5263909170395179,
+           0.5190105736628855,
+           0.519884307762669,
+           0.5282993956497082,
+           0.543383206129881,
+           0.5641270442511275,
+           0.5894128758606435,
+           0.6180422545469014,
+           0.6487667236346721,
+           0.6803189351518477,
+           0.7114437157929928,
+           0.74092831709614,
+           0.7676311130829866,
+           0.7905080527778766,
+           0.8086362361591221,
+           0.8212340586296056,
+           0.8276774590655767,
+           0.8275119076260681,
+           0.820459879221545,
+           0.806423674081199,
+           0.7854835653168607,
+           0.7578913717841806,
+           0.7240596699221601,
+           0.6845469677259635,
+           0.6400392648433898,
+           0.5913285124727305,
+           0.5392885630522131,
+           0.48484926078157514,
+           0.42896936830256066,
+           0.3726090513084831,
+           0.31670265082396687,
+           0.26213246222974057,
+           0.2097042111076849,
+           0.16012486941258625,
+           0.11398339254426867,
+           0.07173488021301865,
+           0.03368857354818448,
+           2.9344723630643395e-16
+          ],
+          [
+           0,
+           -0.028301334550551067,
+           -0.05248437401758845,
+           -0.07293729495534029,
+           -0.09018469682544375,
+           -0.1048716521704371,
+           -0.11774429624527125,
+           -0.1296274696971803,
+           -0.14140000590633242,
+           -0.15396831753325174,
+           -0.16823898305224227,
+           -0.18509106239077217,
+           -0.20534888050050093,
+           -0.2297560084824204,
+           -0.25895114397824004,
+           -0.29344654659548275,
+           -0.33360962128213517,
+           -0.3796481643621236,
+           -0.43159969532759634,
+           -0.4893251947401299,
+           -0.5525074572858911,
+           -0.6206541519441957,
+           -0.6931055612994526,
+           -0.7690468522646913,
+           -0.8475246139037795,
+           -0.9274672875787314,
+           -1.0077090131004467,
+           -1.0870163245014908,
+           -1.164117052771984,
+           -1.2377307323592421,
+           -1.3065997649950836,
+           -1.369520569620287,
+           -1.4253739415053306,
+           -1.4731538573274499,
+           -1.5119939956829251,
+           -1.5411912935427219,
+           -1.5602259272949972,
+           -1.5687771906279957,
+           -1.5667348385725293,
+           -1.5542055751875532,
+           -1.5315144789983028,
+           -1.4992012825318524,
+           -1.45801154714297,
+           -1.4088828987158575,
+           -1.352926610702456,
+           -1.291404935333102,
+           -1.2257046888836185,
+           -1.1573076900014883,
+           -1.0877587289693138,
+           -1.0186318084497352,
+           -0.9514954411409363,
+           -0.8878778157400876,
+           -0.829232648989717,
+           -0.776906528177152,
+           -0.7321085155616003,
+           -0.6958827345891211,
+           -0.6690845886533547,
+           -0.6523611782308861,
+           -0.6461363835148682,
+           -0.6506009695785,
+           -0.6657079522911615,
+           -0.6911733385689544,
+           -0.7264822270968486,
+           -0.7709001285094721,
+           -0.8234892402531162,
+           -0.883129293981212,
+           -0.9485424852110494,
+           -1.0183218987156113,
+           -1.0909627610746973,
+           -1.1648957859482583,
+           -1.2385218295499758,
+           -1.3102470446409478,
+           -1.3785177118189689,
+           -1.4418539371536279,
+           -1.4988814350311799,
+           -1.5483606636671141,
+           -1.58921264690017,
+           -1.6205408979521045,
+           -1.641648956786765,
+           -1.652053160157355,
+           -1.6514903797395089,
+           -1.639920586045231,
+           -1.6175242210911047,
+           -1.5846944879781615,
+           -1.5420247875631252,
+           -1.4902916482777837,
+           -1.4304336020587336,
+           -1.3635265546845767,
+           -1.2907562802731545,
+           -1.2133887353069754,
+           -1.1327389357651654,
+           -1.0501391706134668,
+           -0.9669073353695783,
+           -0.8843161605258655,
+           -0.8035640815628161,
+           -0.7257484508852463,
+           -0.651841728473656,
+           -0.5826712090023106,
+           -0.5189027506523587,
+           -0.4610288671916252,
+           -0.40936143272415554,
+           -0.364029130659143,
+           -0.3249796578735835,
+           -0.2919865747704085,
+           -0.2646605749742812,
+           -0.24246483768274327,
+           -0.22473402396075268,
+           -0.21069638806186716,
+           -0.1994983984160014,
+           -0.19023120212985736,
+           -0.1819582231944796,
+           -0.17374315914526176,
+           -0.16467763427513285,
+           -0.1539077797907009,
+           -0.14065904217702016,
+           -0.12425856968604755,
+           -0.10415459202730702,
+           -0.07993228834322809,
+           -0.0513257313505618,
+           -0.01822559875708997,
+           0.01931754590765931,
+           0.06109448490010893,
+           0.10674305411971943,
+           0.1557581739495427,
+           0.20750593667451764,
+           0.2612413777423944,
+           0.3161294613151608,
+           0.37126872571728775,
+           0.4257169636831404,
+           0.4785182575464537,
+           0.5287306521064569,
+           0.5754537288182353,
+           0.6178553446992702,
+           0.6551968179559599,
+           0.6868558793745719,
+           0.712346763087806,
+           0.7313368810759544,
+           0.7436596109370346,
+           0.7493228239444775,
+           0.7485128877725715,
+           0.7415939928256665,
+           0.7291027699881972,
+           0.7117382878368755,
+           0.6903476359019146,
+           0.6659074144452548,
+           0.6395015575655572,
+           0.6122960125497283,
+           0.5855108818266042,
+           0.5603907025087334,
+           0.5381735905671926,
+           0.5200600108145702,
+           0.5071819491598751,
+           0.5005732596001183,
+           0.5011419351597763,
+           0.5096450099931692,
+           0.5266667401048531,
+           0.5526006340416978,
+           0.5876358142981565,
+           0.6317480872481059,
+           0.684695986677357,
+           0.7460219361934418,
+           0.815058551867266,
+           0.8909399814564208,
+           0.972618053547032,
+           1.0588828919616726,
+           1.1483875407285986,
+           1.239676045516257,
+           1.3312143511714667,
+           1.4214233040074227,
+           1.5087129935427561,
+           1.5915176328532143,
+           1.6683301604707943,
+           1.7377357502854611,
+           1.7984434391224315,
+           1.8493151240489485,
+           1.889391242005177,
+           1.9179125216031263,
+           1.934337289033994,
+           1.938353914741196,
+           1.9298881023161452,
+           1.909104843170645,
+           1.8764049869678252,
+           1.832416505480099,
+           1.7779806533836011,
+           1.7141333504343832,
+           1.642082222563601,
+           1.5631798419299874,
+           1.4788937953914396,
+           1.3907742850378582,
+           1.300420021572946,
+           1.2094432100703354,
+           1.119434447036955,
+           1.0319283473475438,
+           0.9483706995051832,
+           0.8700879083552943,
+           0.7982594268262465,
+           0.733893803925875,
+           0.6778088869370651,
+           0.630616613738076,
+           0.5927127189455714,
+           0.5642715579069016,
+           0.5452461283988802,
+           0.5353732442739466,
+           0.5341836913120439,
+           0.5410170762225469,
+           0.5550409680091322,
+           0.5752738294826845,
+           0.600611148044542,
+           0.6298541011059574,
+           0.6617400344278468,
+           0.6949739926106332,
+           0.7282605208405352,
+           0.7603349562399571,
+           0.7899934457277149,
+           0.8161209646443112,
+           0.8377166655475087,
+           0.853915958103486,
+           0.8640088070557103,
+           0.8674538336560085,
+           0.8638879141973989,
+           0.8531310846633336,
+           0.8351866800984578,
+           0.8102367581093435,
+           0.7786329748924998,
+           0.7408831963860275,
+           0.6976342337008504,
+           0.6496511882541605,
+           0.5977939756110808,
+           0.5429916658715601,
+           0.48621533082283797,
+           0.4284501227327405,
+           0.37066732575199857,
+           0.31379711805808874,
+           0.2587027612179064,
+           0.2061568933538542,
+           0.1568205456075326,
+           0.11122542857802108,
+           0.06975994873334408,
+           0.03265931646693115,
+           2.837213802581525e-16
+          ],
+          [
+           0,
+           -0.02726781590876383,
+           -0.05053753423617953,
+           -0.0702753000650592,
+           -0.08707736773830309,
+           -0.1016519071859527,
+           -0.11479758244334101,
+           -0.1273794707054076,
+           -0.140302960869397,
+           -0.1544863248112484,
+           -0.1708326912263436,
+           -0.19020216979440482,
+           -0.213384872221838,
+           -0.24107555637472364,
+           -0.2738505807256698,
+           -0.31214779965144857,
+           -0.3562499571357003,
+           -0.40627204896371294,
+           -0.46215302372271233,
+           -0.5236520833322408,
+           -0.5903497271665435,
+           -0.6616535630182242,
+           -0.7368087862229263,
+           -0.8149131082852892,
+           -0.8949358013408749,
+           -0.9757404176626187,
+           -1.0561106468879933,
+           -1.1347786901595553,
+           -1.210455462071332,
+           -1.281861879956488,
+           -1.3477604669790237,
+           -1.406986481592088,
+           -1.4584777916103662,
+           -1.5013027363399447,
+           -1.5346852643561688,
+           -1.5580266965864977,
+           -1.570923542861491,
+           -1.5731808931519862,
+           -1.5648210100581894,
+           -1.546086864190996,
+           -1.5174404760751392,
+           -1.479556054118249,
+           -1.4333080449365503,
+           -1.379754336787022,
+           -1.3201149759574324,
+           -1.255746866766348,
+           -1.1881150255803998,
+           -1.118761045488583,
+           -1.0492694988344624,
+           -0.9812330579304336,
+           -0.9162171486233257,
+           -0.8557249660667586,
+           -0.8011636766842375,
+           -0.7538126049708995,
+           -0.7147941590648587,
+           -0.6850481859808631,
+           -0.6653103675497685,
+           -0.6560951733710081,
+           -0.6576837797521711,
+           -0.6701172462806265,
+           -0.6931951171939826,
+           -0.7264794861126433,
+           -0.7693044330945499,
+           -0.8207906155204105,
+           -0.8798646721161566,
+           -0.9452829854384007,
+           -1.0156592451571702,
+           -1.0894951649677302,
+           -1.1652136321178195,
+           -1.2411935121330029,
+           -1.3158052937164217,
+           -1.3874467408859608,
+           -1.4545777216030904,
+           -1.5157534043631924,
+           -1.5696550558855498,
+           -1.6151177331150197,
+           -1.6511542397296035,
+           -1.676974809328107,
+           -1.6920020821751443,
+           -1.6958810572217609,
+           -1.6884838232704227,
+           -1.6699089996082679,
+           -1.6404759440879266,
+           -1.6007139123619187,
+           -1.5513464726991983,
+           -1.4932715935845804,
+           -1.427537923378832,
+           -1.3553178702239415,
+           -1.277878163969135,
+           -1.196548638406066,
+           -1.112690010199316,
+           -1.027661449702195,
+           -0.9427887379583111,
+           -0.8593337836954977,
+           -0.7784662345945866,
+           -0.7012378596065324,
+           -0.6285603050856199,
+           -0.5611867388994602,
+           -0.499697795721181,
+           -0.44449212596125737,
+           -0.39578173304925,
+           -0.3535921619906486,
+           -0.31776747935713867,
+           -0.287979864193319,
+           -0.26374351375448035,
+           -0.24443246040987363,
+           -0.22930179912994136,
+           -0.21751174112839025,
+           -0.20815384052345082,
+           -0.20027868900679507,
+           -0.19292433972849427,
+           -0.18514470673125197,
+           -0.176037190630583,
+           -0.1647688046897143,
+           -0.15060011734965648,
+           -0.13290638655367865,
+           -0.11119533632363167,
+           -0.08512111507835268,
+           -0.05449407585863735,
+           -0.019286128374405374,
+           0.020368471173798003,
+           0.06417690717321287,
+           0.1116960635722052,
+           0.16234503279683676,
+           0.2154215414138682,
+           0.2701218566253051,
+           0.32556364609923377,
+           0.38081118552997717,
+           0.43490224566979696,
+           0.48687594498809883,
+           0.5358008267673393,
+           0.5808024110536226,
+           0.6210894826838881,
+           0.6559784063670673,
+           0.6849148077826234,
+           0.7074920246962356,
+           0.723465812568058,
+           0.73276488304286,
+           0.7354969587212998,
+           0.7319501410933709,
+           0.7225895076270104,
+           0.7080489757592665,
+           0.6891185928746298,
+           0.6667275292203491,
+           0.6419231621275836,
+           0.6158467420614178,
+           0.5897062213192453,
+           0.5647469023338391,
+           0.5422206225610808,
+           0.5233542352875673,
+           0.509318169261834,
+           0.5011958541822493,
+           0.4999547835948224,
+           0.5064199519831554,
+           0.5212503495687013,
+           0.544919127841998,
+           0.5776979628050735,
+           0.6196460434016504,
+           0.6706040020634104,
+           0.7301929854048227,
+           0.7978189387657627,
+           0.8726820515809521,
+           0.9537911845641461,
+           1.0399829775377754,
+           1.1299452214307932,
+           1.22224397236222,
+           1.315353792444242,
+           1.4076904232963887,
+           1.4976451362258598,
+           1.583619959155712,
+           1.6640629557873383,
+           1.7375027278076847,
+           1.8025813263483415,
+           1.8580847940340939,
+           1.902970612997863,
+           1.9363914058990868,
+           1.9577143245403952,
+           1.9665356620199181,
+           1.9626903370303201,
+           1.9462560201885086,
+           1.9175517992075304,
+           1.8771314092202562,
+           1.8257711834848966,
+           1.7644530049108282,
+           1.6943426572953966,
+           1.6167640839799633,
+           1.5331701581741806,
+           1.4451106511202112,
+           1.3541981495909319,
+           1.262072721363081,
+           1.1703661551489255,
+           1.0806666093523334,
+           0.994484491771372,
+           0.9132203603265979,
+           0.8381355838638717,
+           0.7703264333390248,
+           0.7107021889485388,
+           0.6599677501241225,
+           0.6186111251977757,
+           0.586896058682351,
+           0.5648599294268499,
+           0.5523169254594799,
+           0.5488663742514008,
+           0.5539059835319035,
+           0.5666496306815368,
+           0.5861492309778809,
+           0.6113201191871008,
+           0.6409692975006961,
+           0.6738258375707256,
+           0.7085726769528818,
+           0.7438790217362306,
+           0.7784325581621926,
+           0.8109706867692216,
+           0.8403100227106186,
+           0.8653734545691344,
+           0.885214119962164,
+           0.8990357377986499,
+           0.9062088321323637,
+           0.906282488744081,
+           0.8989914001944496,
+           0.8842580752337023,
+           0.8621902111155215,
+           0.8330733494661536,
+           0.7973590548522198,
+           0.7556489671142544,
+           0.7086751811003704,
+           0.6572774980975284,
+           0.6023781697714924,
+           0.5449548159034728,
+           0.48601224016994143,
+           0.42655389261164606,
+           0.36755373270541036,
+           0.30992923299580816,
+           0.25451623045394467,
+           0.20204628197090907,
+           0.15312711297836273,
+           0.10822666584964573,
+           0.06766115957758871,
+           0.03158746667631069,
+           2.7378492871161564e-16
+          ],
+          [
+           0,
+           -0.026247509264387518,
+           -0.04865748385071863,
+           -0.06777192248540986,
+           -0.08425522587682369,
+           -0.09887385839432791,
+           -0.11247305158520453,
+           -0.12595116906440518,
+           -0.14023241462564148,
+           -0.15623861030911537,
+           -0.1748607974653616,
+           -0.196931420887586,
+           -0.22319784364275075,
+           -0.2542979086008979,
+           -0.2907382126125971,
+           -0.3328756920501303,
+           -0.3809030356771029,
+           -0.434838344604145,
+           -0.4945193518268914,
+           -0.5596023982097469,
+           -0.6295662406728195,
+           -0.7037206448000014,
+           -0.7812195912201723,
+           -0.8610788060165269,
+           -0.9421972130982764,
+           -1.0233818037680074,
+           -1.1033753282455978,
+           -1.1808861379741393,
+           -1.2546194480850927,
+           -1.3233092479816728,
+           -1.3857500657075157,
+           -1.4408277892240198,
+           -1.4875487650555739,
+           -1.5250664316139955,
+           -1.552704800032019,
+           -1.5699781682051408,
+           -1.576606542211724,
+           -1.572526341212156,
+           -1.5578960748395108,
+           -1.5330968032292551,
+           -1.4987273162271721,
+           -1.455594096859312,
+           -1.4046962616820842,
+           -1.3472057940097173,
+           -1.284443502191415,
+           -1.2178512412048574,
+           -1.1489610292122798,
+           -1.0793617690650683,
+           -1.0106643460835636,
+           -0.9444659162367816,
+           -0.8823142220118706,
+           -0.8256727761861163,
+           -0.7758877362827854,
+           -0.7341572550930955,
+           -0.7015040361581146,
+           -0.6787517488737405,
+           -0.6665058676929838,
+           -0.6651393959294936,
+           -0.6747838194310819,
+           -0.6953255116862289,
+           -0.7264076827536985,
+           -0.7674378329042936,
+           -0.817600541231542,
+           -0.8758752929012625,
+           -0.9410589292465992,
+           -1.011792195478985,
+           -1.0865897640345556,
+           -1.1638730298570668,
+           -1.242004909210192,
+           -1.3193258274760145,
+           -1.3941900549371646,
+           -1.4650015433814034,
+           -1.53024843063408,
+           -1.5885354144412869,
+           -1.6386132506286013,
+           -1.6794047018118043,
+           -1.7100263503660476,
+           -1.729805790704878,
+           -1.7382938286794523,
+           -1.7352714373022828,
+           -1.7207513450439686,
+           -1.6949742625252222,
+           -1.6583998823540944,
+           -1.6116929119844003,
+           -1.5557045177406312,
+           -1.4914496666862775,
+           -1.4200809491713438,
+           -1.3428595463561899,
+           -1.2611240718153696,
+           -1.1762580629348567,
+           -1.0896569251397952,
+           -1.0026951394176857,
+           -0.9166945310172294,
+           -0.8328943649851838,
+           -0.7524239832169963,
+           -0.6762786292702196,
+           -0.6052990230798476,
+           -0.5401551500655107,
+           -0.4813346204061219,
+           -0.42913583722256105,
+           -0.38366608999847873,
+           -0.34484456485569503,
+           -0.31241013940748547,
+           -0.2859337099361595,
+           -0.26483468557282813,
+           -0.24840118081035606,
+           -0.23581334661987124,
+           -0.2261692039193059,
+           -0.21851228304373357,
+           -0.21186033066135906,
+           -0.20523432228477664,
+           -0.19768701468736066,
+           -0.1883302882033326,
+           -0.1763605636311289,
+           -0.16108163135877118,
+           -0.14192430001714507,
+           -0.1184623566522144,
+           -0.09042442792425455,
+           -0.05770143970441218,
+           -0.020349487900819117,
+           0.02141194652697308,
+           0.06720638366628658,
+           0.11651115690026587,
+           0.16867236061178595,
+           0.22292353438064025,
+           0.2784075866638811,
+           0.3342013756109222,
+           0.38934229421009314,
+           0.4428561531905871,
+           0.4937856193924512,
+           0.5412184505928426,
+           0.5843147704866508,
+           0.6223326496224819,
+           0.6546512990612,
+           0.6807912423485124,
+           0.7004309066200306,
+           0.7134191634165704,
+           0.7197834518412658,
+           0.7197332284877561,
+           0.7136586073112711,
+           0.7021241753234265,
+           0.6858580935839909,
+           0.665736714327843,
+           0.6427650611419604,
+           0.6180536269607934,
+           0.5927920415441604,
+           0.5682202435734721,
+           0.545597860413681,
+           0.5261725491876256,
+           0.5111480847728304,
+           0.501652992796344,
+           0.49871051829296353,
+           0.5032106935224729,
+           0.5158852221206983,
+           0.5372858323731696,
+           0.5677666714862961,
+           0.6074712172405782,
+           0.6563240756607434,
+           0.7140279159553776,
+           0.7800656698345649,
+           0.8537079944529516,
+           0.9340258697905659,
+           1.0199080754385235,
+           1.1100831716083104,
+           1.2031454977029072,
+           1.2975846017402681,
+           1.3918174277916853,
+           1.4842225185376834,
+           1.573175437810147,
+           1.65708458490143,
+           1.7344265593325292,
+           1.8037802420444837,
+           1.8638587864723044,
+           1.9135387600449751,
+           1.9518857422116245,
+           1.9781757675532285,
+           1.991912099913957,
+           1.992836933423153,
+           1.9809377361140332,
+           1.956448078670776,
+           1.9198429215710977,
+           1.8718284653588928,
+           1.8133267977843586,
+           1.7454556949503783,
+           1.6695040484034858,
+           1.5869034935161093,
+           1.499196904013749,
+           1.4080044909368803,
+           1.3149882999175264,
+           1.2218159370572366,
+           1.1301243700499184,
+           1.04148464712381,
+           0.9573683520075128,
+           0.8791165690777227,
+           0.8079120702250377,
+           0.7447553553368532,
+           0.6904450836166848,
+           0.6455633255762132,
+           0.6104659480986402,
+           0.5852783203699837,
+           0.5698963997712413,
+           0.5639931271765622,
+           0.567029933686311,
+           0.5782730387540306,
+           0.5968141059199923,
+           0.6215947197079017,
+           0.6514340581628042,
+           0.6850590621551352,
+           0.7211363467029727,
+           0.7583050624916166,
+           0.7952098983487546,
+           0.8305334180288465,
+           0.8630269471402964,
+           0.8915392677892054,
+           0.9150424384145357,
+           0.9326541328030791,
+           0.9436559834425565,
+           0.9475075178810887,
+           0.943855389993561,
+           0.9325377281563879,
+           0.9135835462836657,
+           0.8872072883719476,
+           0.8537986995185456,
+           0.8139083332657573,
+           0.7682291136691107,
+           0.7175744679942868,
+           0.6628536299985927,
+           0.6050447822740782,
+           0.5451667574381313,
+           0.4842500508057818,
+           0.42330791078258123,
+           0.363308267278633,
+           0.3051472331548619,
+           0.24962486974923556,
+           0.197423846039162,
+           0.1490915435619027,
+           0.10502606782160874,
+           0.06546652389350308,
+           0.030487801917074352,
+           2.6378033571231434e-16
+          ],
+          [
+           0,
+           -0.025256116855657682,
+           -0.04687514449587627,
+           -0.06547200594579561,
+           -0.08177496332030029,
+           -0.09660325806889701,
+           -0.11084209796222369,
+           -0.1254156573741354,
+           -0.14125881061244894,
+           -0.1592883528383683,
+           -0.18037447858879868,
+           -0.2053132836625741,
+           -0.23480103223297594,
+           -0.2694108880814796,
+           -0.30957274786874345,
+           -0.35555673688022194,
+           -0.4074608356342449,
+           -0.4652030014176851,
+           -0.5285180348281351,
+           -0.5969593206082386,
+           -0.6699054474895766,
+           -0.7465715865523331,
+           -0.8260253849066617,
+           -0.9072070144090579,
+           -0.9889529066043424,
+           -1.0700226078848805,
+           -1.149128105459202,
+           -1.2249649072586264,
+           -1.2962441091252443,
+           -1.361724651822732,
+           -1.420244959427114,
+           -1.4707531598297299,
+           -1.5123351172597106,
+           -1.5442395552504207,
+           -1.565899615192982,
+           -1.5769502789445569,
+           -1.5772411818777432,
+           -1.5668444528916334,
+           -1.5460573375678672,
+           -1.5153994869172696,
+           -1.4756049239254314,
+           -1.4276088301765093,
+           -1.3725294220069353,
+           -1.311645306772647,
+           -1.2463688219063083,
+           -1.1782159597123993,
+           -1.1087735668029983,
+           -1.0396645765677808,
+           -0.9725120843527673,
+           -0.9089031067933615,
+           -0.8503528781854214,
+           -0.7982705275602341,
+           -0.7539269504378201,
+           -0.7184256397552636,
+           -0.6926771723748945,
+           -0.677377962502922,
+           -0.6729937933414336,
+           -0.6797485257732034,
+           -0.6976182605655751,
+           -0.7263311014448961,
+           -0.7653725335734405,
+           -0.8139962986852435,
+           -0.8712405176467839,
+           -0.9359486866767797,
+           -1.0067950579147795,
+           -1.0823138112791628,
+           -1.160931335121059,
+           -1.241000860230007,
+           -1.3208386370445526,
+           -1.3987608107828167,
+           -1.4731201344723068,
+           -1.5423416658613005,
+           -1.6049566207654813,
+           -1.6596336018682487,
+           -1.7052064871898693,
+           -1.740698344750182,
+           -1.7653408373349582,
+           -1.778588691333524,
+           -1.780128923632893,
+           -1.7698846475800059,
+           -1.7480134099385747,
+           -1.714900142361049,
+           -1.6711449399479292,
+           -1.6175460028233555,
+           -1.555078191310776,
+           -1.484867748458824,
+           -1.408163832846979,
+           -1.3263075776452036,
+           -1.2406994470653463,
+           -1.1527656973245088,
+           -1.0639247652174337,
+           -0.9755544030388477,
+           -0.8889603540835721,
+           -0.8053473189567398,
+           -0.725792900604432,
+           -0.6512251369338539,
+           -0.5824041361505535,
+           -0.5199082238769656,
+           -0.4641248954117344,
+           -0.41524674405598194,
+           -0.37327241034570835,
+           -0.33801247044712635,
+           -0.30910005805815205,
+           -0.286005896005304,
+           -0.26805730427123015,
+           -0.25446065315145733,
+           -0.24432664604598422,
+           -0.2366977481176569,
+           -0.23057702636806093,
+           -0.22495763482256062,
+           -0.21885216623490625,
+           -0.21132109928217527,
+           -0.20149959738796633,
+           -0.18862196135924533,
+           -0.17204310174998708,
+           -0.15125647663007846,
+           -0.12590803419651125,
+           -0.09580580502145698,
+           -0.06092490300438841,
+           -0.02140781437650157,
+           0.022440022660622835,
+           0.07015922202259924,
+           0.12114979215829379,
+           0.17468845797682003,
+           0.2299494992658322,
+           0.2860285502438989,
+           0.3419687267648398,
+           0.3967883857703573,
+           0.44950977745217147,
+           0.4991878253717538,
+           0.5449382641545139,
+           0.5859643784926377,
+           0.6215816207265611,
+           0.6512394364097479,
+           0.674539696706369,
+           0.6912512215012049,
+           0.7013199755955473,
+           0.7048746298607855,
+           0.702227296981104,
+           0.6938693744847695,
+           0.6804625530482425,
+           0.6628251724057443,
+           0.6419142274742415,
+           0.6188034404706756,
+           0.594657917987801,
+           0.5707060025841816,
+           0.5482090041193224,
+           0.5284295548811137,
+           0.5125993729809081,
+           0.5018872394590627,
+           0.497367995460187,
+           0.4999933466113448,
+           0.5105652227778716,
+           0.529712383582218,
+           0.557870884823543,
+           0.5952689300389454,
+           0.641916527103199,
+           0.6976002545132209,
+           0.7618833186628926,
+           0.8341109550069141,
+           0.9134210956941319,
+           0.998760097231019,
+           1.0889031971987548,
+           1.1824792520725411,
+           1.2779992016787922,
+           1.373887612421535,
+           1.4685165734429275,
+           1.5602411593059413,
+           1.6474356311286489,
+           1.7285295264235183,
+           1.8020427867767075,
+           1.8666190920121692,
+           1.9210566091872316,
+           1.9643354237279727,
+           1.995640996827212,
+           2.014383086050102,
+           2.0202096726814225,
+           2.0130155571251387,
+           1.992945409774701,
+           1.9603911961500606,
+           1.9159840285517313,
+           1.8605806287686395,
+           1.7952447142775876,
+           1.721223740777507,
+           1.639921543883453,
+           1.5528675196920312,
+           1.4616830653698258,
+           1.3680460649371553,
+           1.2736542504757142,
+           1.180188293999954,
+           1.0892754896096182,
+           1.002454869200796,
+           0.9211445583804269,
+           0.8466121232243228,
+           0.7799485845366169,
+           0.722046686142834,
+           0.6735838997067415,
+           0.6350105331685403,
+           0.6065431859991492,
+           0.5881636650980233,
+           0.5796233435041288,
+           0.5804528133671781,
+           0.5899765580358152,
+           0.6073322487504176,
+           0.6314941621862356,
+           0.6613001186285218,
+           0.6954812592052687,
+           0.7326939163082555,
+           0.7715527856272897,
+           0.8106645821709528,
+           0.8486613568279392,
+           0.8842326645113497,
+           0.9161558092982739,
+           0.9433234453095154,
+           0.9647678829840934,
+           0.9796815370712111,
+           0.9874330528827244,
+           0.987578758584939,
+           0.9798692107538818,
+           0.9642507250700959,
+           0.9408619107611786,
+           0.9100253530411877,
+           0.8722347092090003,
+           0.8281375982272264,
+           0.7785147676718729,
+           0.7242561133407717,
+           0.6663342032777179,
+           0.6057760176292672,
+           0.543633657146151,
+           0.4809547952757091,
+           0.41875365115414,
+           0.3579832433834269,
+           0.2995096477497237,
+           0.24408892697399298,
+           0.19234732860770867,
+           0.14476526014599872,
+           0.10166545055369158,
+           0.06320559723368956,
+           0.02937567981600209,
+           2.5385357101887763e-16
+          ],
+          [
+           0,
+           -0.02430934221584486,
+           -0.04522101381486671,
+           -0.06341913007313893,
+           -0.07969077986662718,
+           -0.09490179098182036,
+           -0.10997018026662972,
+           -0.12583799744674065,
+           -0.14344231476461736,
+           -0.16368613867289666,
+           -0.1874100240015158,
+           -0.21536515518973354,
+           -0.2481886237053758,
+           -0.28638157653422985,
+           -0.3302908389560257,
+           -0.38009452751347456,
+           -0.43579206830674017,
+           -0.497198924028448,
+           -0.5639462132934617,
+           -0.6354852808218105,
+           -0.7110971500447549,
+           -0.7899066639209078,
+           -0.8709009983449764,
+           -0.9529521185756465,
+           -1.034842645490289,
+           -1.115294507828425,
+           -1.1929996812299883,
+           -1.2666522567475496,
+           -1.3349810421268518,
+           -1.3967818795554545,
+           -1.4509488643317912,
+           -1.4965036700572467,
+           -1.5326222270444854,
+           -1.5586580607114553,
+           -1.574161674362668,
+           -1.5788954540785916,
+           -1.5728436801771162,
+           -1.5562173472767222,
+           -1.529453620503499,
+           -1.4932098857644434,
+           -1.4483524840511144,
+           -1.3959403501862964,
+           -1.337203902059714,
+           -1.2735196441075458,
+           -1.206381055653956,
+           -1.1373664280928635,
+           -1.0681043924140756,
+           -1.0002379383252595,
+           -0.9353877666798396,
+           -0.8751158370529651,
+           -0.8208899715737051,
+           -0.7740503544941343,
+           -0.7357787249413443,
+           -0.7070709988443025,
+           -0.6887139766200077,
+           -0.6812666977506445,
+           -0.6850468941890795,
+           -0.7001228742369403,
+           -0.7263110400645837,
+           -0.7631791085051332,
+           -0.8100549694009003,
+           -0.8660409819013408,
+           -0.930033379964083,
+           -1.0007463370359164,
+           -1.0767401294385244,
+           -1.1564527410385979,
+           -1.2382341706974564,
+           -1.3203826407366455,
+           -1.4011818607506652,
+           -1.478938477600501,
+           -1.5520188398842971,
+           -1.6188842236453196,
+           -1.6781237050668325,
+           -1.728483924442479,
+           -1.768895062344017,
+           -1.7984924417391248,
+           -1.8166332765490587,
+           -1.8229082051491106,
+           -1.8171473737019925,
+           -1.7994209658707896,
+           -1.7700342091560652,
+           -1.729517020567237,
+           -1.6786085823342436,
+           -1.618237258769925,
+           -1.5494963752773903,
+           -1.4736164771954305,
+           -1.3919347673544793,
+           -1.3058624849287386,
+           -1.2168510329048592,
+           -1.1263576862036513,
+           -1.0358117166451535,
+           -0.9465817545049144,
+           -0.8599451698460031,
+           -0.7770602010996716,
+           -0.6989414849520997,
+           -0.6264395523560476,
+           -0.5602247526923793,
+           -0.5007759543579139,
+           -0.4483742482186247,
+           -0.4031017535019783,
+           -0.3648454969883305,
+           -0.33330620901680913,
+           -0.30801175702328304,
+           -0.28833482213346107,
+           -0.2735143196037016,
+           -0.26267997222918044,
+           -0.25487936948557255,
+           -0.24910678601076156,
+           -0.24433299250791807,
+           -0.23953527123178991,
+           -0.23372684738454985,
+           -0.22598496696981443,
+           -0.21547689040407256,
+           -0.2014831284446639,
+           -0.18341732128011787,
+           -0.16084225103317829,
+           -0.13348158016257555,
+           -0.10122702070910276,
+           -0.06414075915260173,
+           -0.022453085783516544,
+           0.02344469720656223,
+           0.07301189142635824,
+           0.1255742261491437,
+           0.1803434647121149,
+           0.23644026875887905,
+           0.2929197100192124,
+           0.348798749334843,
+           0.40308495006773715,
+           0.4548056592147128,
+           0.5030368753735435,
+           0.5469310285416293,
+           0.5857429224550856,
+           0.6188531351693524,
+           0.645788236731926,
+           0.666237262535003,
+           0.6800639752732339,
+           0.6873145550117267,
+           0.6882204730235151,
+           0.683196427870452,
+           0.6728333485920754,
+           0.6578865966530354,
+           0.6392596222856995,
+           0.617983448919167,
+           0.5951924685206645,
+           0.5720971281188783,
+           0.5499541710471939,
+           0.530035163403334,
+           0.5135940851389718,
+           0.5018347947837204,
+           0.49587918626747673,
+           0.4967368453286031,
+           0.5052769817867012,
+           0.5222033632260404,
+           0.5480329065748648,
+           0.5830784983311029,
+           0.6274365138488049,
+           0.6809793936018659,
+           0.7433535124290245,
+           0.8139824494235625,
+           0.8920756345149815,
+           0.9766422161386933,
+           1.066509865951708,
+           1.1603481145030312,
+           1.2566956991318936,
+           1.3539913049422199,
+           1.4506069939909778,
+           1.5448835489751886,
+           1.6351669074397048,
+           1.7198448321343278,
+           1.7973829534145516,
+           1.8663593307904776,
+           1.9254967126526268,
+           1.9736917251023338,
+           2.010040291457788,
+           2.033858671701821,
+           2.0446996137723983,
+           2.042363223690147,
+           2.0269022862809436,
+           1.9986218996579015,
+           1.9580734214836462,
+           1.9060428600620933,
+           1.8435339752246955,
+           1.7717464795703006,
+           1.6920498468355898,
+           1.6059533381886186,
+           1.5150729465245631,
+           1.4210960312343965,
+           1.325744469661881,
+           1.2307371852671791,
+           1.1377529255706187,
+           1.0483941549603406,
+           0.964152898630297,
+           0.8863793249987579,
+           0.8162537861615776,
+           0.7547629509400177,
+           0.7026805649904384,
+           0.6605532597214168,
+           0.6286917091869494,
+           0.6071673047056101,
+           0.5958143838705392,
+           0.59423791712522,
+           0.6018264244504866,
+           0.6177697701286943,
+           0.641081368056182,
+           0.6706242264704951,
+           0.7051401717514687,
+           0.7432815182922549,
+           0.7836443970527858,
+           0.8248029205837231,
+           0.8653433478382258,
+           0.9038974182614218,
+           0.939174051241725,
+           0.969988653297942,
+           0.99528934014876,
+           1.014179462399377,
+           1.0259359199022848,
+           1.0300228584640818,
+           1.0261004607357902,
+           1.0140286678676627,
+           0.9938657967010889,
+           0.9658621457013679,
+           0.9304488082980037,
+           0.8882220316673394,
+           0.8399235692975964,
+           0.7864175741832706,
+           0.7286646637691072,
+           0.6676938557287988,
+           0.604573123657704,
+           0.5403793525724201,
+           0.476168485016198,
+           0.41294663934107084,
+           0.3516429526540665,
+           0.2930848527527148,
+           0.23797639738896537,
+           0.18688023709166926,
+           0.14020366165054166,
+           0.09818908267346954,
+           0.060909188117896015,
+           0.028266882328896195,
+           2.441526044796518e-16
+          ],
+          [
+           0,
+           -0.02342272080945969,
+           -0.04372482864209873,
+           -0.06165511685779969,
+           -0.07805375205207923,
+           -0.09382633322611497,
+           -0.10991600463748215,
+           -0.12727436813977888,
+           -0.14683197360870712,
+           -0.16946917889105312,
+           -0.19598816325645363,
+           -0.22708685074599522,
+           -0.2633354527698289,
+           -0.30515627397189804,
+           -0.3528073433790548,
+           -0.40637033623107943,
+           -0.4657431430645106,
+           -0.5306373243240904,
+           -0.6005805639703354,
+           -0.6749241073778296,
+           -0.7528550405034449,
+           -0.8334131420831471,
+           -0.9155119216548459,
+           -0.9979633465164204,
+           -1.0795056630996067,
+           -1.158833635162561,
+           -1.2346304548083313,
+           -1.305600534342208,
+           -1.3705023586509741,
+           -1.4281805698961634,
+           -1.4775964691279202,
+           -1.5178561526968217,
+           -1.5482355543084398,
+           -1.568201734978058,
+           -1.5774298512873006,
+           -1.5758153350874118,
+           -1.5634809326347006,
+           -1.5407783752756243,
+           -1.5082845841786043,
+           -1.4667924450318028,
+           -1.4172963218032708,
+           -1.360972608303471,
+           -1.2991557391918933,
+           -1.2333101951812329,
+           -1.1649991377014342,
+           -1.0958503936847883,
+           -1.0275205792826636,
+           -0.9616582005062224,
+           -0.8998665977434664,
+           -0.8436676090847173,
+           -0.794466814144658,
+           -0.7535211858790462,
+           -0.7219099235513841,
+           -0.7005091667979909,
+           -0.6899712004229239,
+           -0.6907086543025827,
+           -0.7028840851377488,
+           -0.7264051996086518,
+           -0.760925844852891,
+           -0.8058527553435659,
+           -0.8603579085232047,
+           -0.9233962082738995,
+           -0.9937280887186054,
+           -1.0699465140324926,
+           -1.15050774573798,
+           -1.2337651598951538,
+           -1.318005324842317,
+           -1.4014854974274387,
+           -1.482471663270695,
+           -1.5592762352852287,
+           -1.6302945347131734,
+           -1.6940392100417163,
+           -1.7491718005664818,
+           -1.7945307217886748,
+           -1.8291550375247463,
+           -1.8523034864080583,
+           -1.8634683458387697,
+           -1.862383841552839,
+           -1.8490289427614408,
+           -1.8236245180257897,
+           -1.7866249623688488,
+           -1.7387045382754773,
+           -1.6807387989719835,
+           -1.6137815786431957,
+           -1.53903813821789,
+           -1.4578351445171907,
+           -1.371588232771023,
+           -1.2817679560426556,
+           -1.1898649587029526,
+           -1.0973552240010402,
+           -1.0056662377364178,
+           -0.9161448813172469,
+           -0.8300278188695959,
+           -0.7484150758128126,
+           -0.6722474221651538,
+           -0.6022880749353738,
+           -0.5391091227943585,
+           -0.4830829556099804,
+           -0.43437885439949336,
+           -0.3929647669916205,
+           -0.3586141644528621,
+           -0.3309177463693105,
+           -0.3092996425479379,
+           -0.2930376476037356,
+           -0.28128692598375754,
+           -0.2731065406885199,
+           -0.2674880913573679,
+           -0.26338569813783974,
+           -0.25974653804788533,
+           -0.255541131060763,
+           -0.24979258408404786,
+           -0.24160403204247555,
+           -0.2301835655816058,
+           -0.21486600317508348,
+           -0.19513094988295965,
+           -0.17061668350715958,
+           -0.14112951890767575,
+           -0.10664841997668432,
+           -0.06732475319821674,
+           -0.02347720368756659,
+           0.024417999115234703,
+           0.0757412765332911,
+           0.12974793156171235,
+           0.18558992516309333,
+           0.24234061464005635,
+           0.29902179285860064,
+           0.35463230612055124,
+           0.4081774860057717,
+           0.4586986076159217,
+           0.50530158394919,
+           0.5471841237094993,
+           0.5836606172829673,
+           0.6141840719776739,
+           0.6383644915210238,
+           0.6559831844002112,
+           0.6670025886767394,
+           0.6715713148251934,
+           0.6700242300824185,
+           0.6628775346826655,
+           0.6508189090051251,
+           0.6346929378304139,
+           0.6154821403816815,
+           0.5942840495152871,
+           0.5722848874161601,
+           0.5507304757966819,
+           0.5308950935768092,
+           0.5140490524056941,
+           0.5014257986755412,
+           0.49418936885460235,
+           0.49340302250592577,
+           0.49999985425295146,
+           0.5147561427081077,
+           0.5382681320047802,
+           0.5709328615534901,
+           0.6129335639089524,
+           0.6642300415099653,
+           0.7245543132009441,
+           0.7934116937961879,
+           0.8700873376399241,
+           0.953658143403099,
+           1.0430097855401068,
+           1.1368585111636367,
+           1.2337772227214885,
+           1.332225259715673,
+           1.4305811994587672,
+           1.527177919846764,
+           1.6203391082761276,
+           1.7084163616358332,
+           1.7898260037732032,
+           1.8630847494669838,
+           1.9268433677260477,
+           1.9799175416298378,
+           2.0213151858930716,
+           2.050259565346599,
+           2.0662076556074433,
+           2.0688632989973437,
+           2.058184831554566,
+           2.0343869877910428,
+           1.9979370254994298,
+           1.9495451501151855,
+           1.8901494535503527,
+           1.8208957127436818,
+           1.7431125152448712,
+           1.6582822899995093,
+           1.5680089184302184,
+           1.4739826815643953,
+           1.3779433613840346,
+           1.2816423572593438,
+           1.1868047002499669,
+           1.0950918486991634,
+           1.0080661279123826,
+           0.927157635327669,
+           0.8536343714853613,
+           0.7885762778040889,
+           0.7328537666292052,
+           0.6871112195943646,
+           0.6517558097208702,
+           0.6269518738364697,
+           0.6126209279880648,
+           0.6084472828325804,
+           0.613889081837346,
+           0.6281944557824277,
+           0.6504223656852275,
+           0.6794675958131615,
+           0.7140892615900146,
+           0.7529421162722302,
+           0.7946098772120265,
+           0.8376397488296901,
+           0.8805772961008821,
+           0.9220008199347307,
+           0.9605544042657677,
+           0.9949788434819685,
+           1.024139716934784,
+           1.0470519532208402,
+           1.0629003187472128,
+           1.0710553704608297,
+           1.07108452887568,
+           1.0627580517421564,
+           1.046049817753268,
+           1.0211329603413664,
+           0.9883705206224445,
+           0.9483014126771532,
+           0.901622110531369,
+           0.8491645715320478,
+           0.7918710027008778,
+           0.7307661528245087,
+           0.6669278716388218,
+           0.6014567170622215,
+           0.535445411083808,
+           0.46994894417276784,
+           0.4059561070132122,
+           0.34436318756183887,
+           0.28595051194667065,
+           0.23136243111360627,
+           0.18109126335206574,
+           0.13546559823924556,
+           0.09464325280137456,
+           0.058609048720382875,
+           0.027177453315199353,
+           2.3482584682386714e-16
+          ],
+          [
+           0,
+           -0.022611450101783878,
+           -0.042415231707820925,
+           -0.06021954928674037,
+           -0.07691122727697317,
+           -0.0934282529550014,
+           -0.11073076974177495,
+           -0.1297712979522969,
+           -0.1514649816505919,
+           -0.1766606614488742,
+           -0.20611355373632104,
+           -0.24046027740720755,
+           -0.28019691065370356,
+           -0.3256606842503818,
+           -0.3770158258858704,
+           -0.43424396479060656,
+           -0.4971393898077704,
+           -0.5653093300715484,
+           -0.638179298709744,
+           -0.7150034097176643,
+           -0.7948794496420203,
+           -0.8767683622135611,
+           -0.9595176887018035,
+           -1.0418884024629513,
+           -1.1225844855697817,
+           -1.2002845208687745,
+           -1.273674516227024,
+           -1.3414811405868503,
+           -1.4025045347339122,
+           -1.4556498638916846,
+           -1.4999568043469855,
+           -1.534626201732703,
+           -1.5590432032819788,
+           -1.5727962487778542,
+           -1.5756914030642175,
+           -1.567761624472753,
+           -1.549270685634288,
+           -1.5207115928894404,
+           -1.4827994847046784,
+           -1.4364591248303729,
+           -1.3828072390662802,
+           -1.3231300721334602,
+           -1.2588566601251936,
+           -1.1915284213654167,
+           -1.1227657615655742,
+           -1.05423246560988,
+           -0.9875987061919533,
+           -0.9245035374021882,
+           -0.8665177582456276,
+           -0.8151080264901452,
+           -0.7716030772668683,
+           -0.7371628540583991,
+           -0.7127512932159453,
+           -0.6991134185313226,
+           -0.6967573016866916,
+           -0.7059413300449136,
+           -0.7266670979942471,
+           -0.758678104960561,
+           -0.8014643054807615,
+           -0.8542724177408851,
+           -0.9161217601022748,
+           -0.985825253700873,
+           -1.0620151064067533,
+           -1.1431725822622376,
+           -1.2276611636813548,
+           -1.3137623335443658,
+           -1.3997131428034297,
+           -1.4837446878173426,
+           -1.56412060135034,
+           -1.6391746624796428,
+           -1.7073466535087076,
+           -1.7672156357988897,
+           -1.8175298801208324,
+           -1.8572327691109478,
+           -1.8854840876742143,
+           -1.9016762292818035,
+           -1.9054449693136477,
+           -1.8966745878664584,
+           -1.8754972605673441,
+           -1.8422867735685318,
+           -1.7976467546838812,
+           -1.7423937432482488,
+           -1.6775355435541393,
+           -1.6042454176753247,
+           -1.5238327704371846,
+           -1.4377110599012746,
+           -1.3473637290671614,
+           -1.2543089970826877,
+           -1.1600643701088764,
+           -1.0661117326367788,
+           -0.9738638595538204,
+           -0.8846331481829265,
+           -0.7996033089526975,
+           -0.719804674865004,
+           -0.6460936955119987,
+           -0.579137073452215,
+           -0.5194008820099707,
+           -0.4671448770003053,
+           -0.42242208367748774,
+           -0.385083607640917,
+           -0.3547884878171985,
+           -0.33101828422412044,
+           -0.3130959761276021,
+           -0.30020864032862854,
+           -0.29143328727963125,
+           -0.2857651567939047,
+           -0.28214771713548253,
+           -0.2795035726657107,
+           -0.27676546689454395,
+           -0.27290657014762165,
+           -0.2669692640034319,
+           -0.2580916775514883,
+           -0.24553129224559095,
+           -0.2286850110783055,
+           -0.20710518195508287,
+           -0.18051117209105116,
+           -0.14879620726324663,
+           -0.11202931384831792,
+           -0.07045232960720618,
+           -0.024472077893849933,
+           0.025352073900685917,
+           0.07832493050266999,
+           0.1336360068198959,
+           0.19038333536404456,
+           0.24759990481159688,
+           0.3042820221869782,
+           0.35941883999062785,
+           0.41202225787731117,
+           0.4611563970345933,
+           0.5059658545261215,
+           0.5457019743395299,
+           0.5797464209914264,
+           0.6076314090741136,
+           0.6290560263974873,
+           0.6438981872787877,
+           0.6522218635860524,
+           0.6542793615624314,
+           0.6505085392230184,
+           0.641524989034519,
+           0.6281093403875715,
+           0.6111899627761552,
+           0.5918214704115904,
+           0.5711595391835913,
+           0.5504326446358605,
+           0.5309114124532425,
+           0.5138763387343996,
+           0.5005846843432379,
+           0.4922373746541083,
+           0.4899467422870393,
+           0.49470593574332294,
+           0.5073607814939005,
+           0.5285848318548911,
+           0.5588582572141946,
+           0.5984511506230941,
+           0.6474117076311863,
+           0.7055596270833808,
+           0.772484952280044,
+           0.8475524395252697,
+           0.9299114059105067,
+           1.0185108735352035,
+           1.1121196965797453,
+           1.209351233958568,
+           1.3086920167633573,
+           1.4085337591833411,
+           1.5072079765724677,
+           1.60302240695456,
+           1.6942983842199317,
+           1.7794082837981113,
+           1.856812155416628,
+           1.9250926728762072,
+           1.9829875672615607,
+           2.029418766816717,
+           2.0635175424964913,
+           2.0846450511458854,
+           2.092407776117593,
+           2.0866674853076352,
+           2.0675454561583164,
+           2.03542085300151,
+           1.9909232808933082,
+           1.9349196784483556,
+           1.8684958467520238,
+           1.7929330389359148,
+           1.7096801523435559,
+           1.620322169533702,
+           1.5265455831312054,
+           1.4301016105852173,
+           1.3327680565088549,
+           1.236310711208169,
+           1.1424451835223117,
+           1.0528000539769409,
+           0.9688822008148436,
+           0.8920450975483311,
+           0.8234608076164731,
+           0.764096311331711,
+           0.7146946947943309,
+           0.675761612436355,
+           0.6475573072289147,
+           0.6300943384812874,
+           0.6231410298621265,
+           0.6262305131443774,
+           0.6386751095651679,
+           0.6595856638593122,
+           0.6878953290560569,
+           0.7223871958611463,
+           0.7617250713999361,
+           0.8044866404124917,
+           0.8491981893757273,
+           0.894370041715137,
+           0.9385318409899696,
+           0.9802668288999472,
+           1.0182442958535685,
+           1.051249432824168,
+           1.0782098829731925,
+           1.0982183782497816,
+           1.1105509476760331,
+           1.1146802977304011,
+           1.1102840882825304,
+           1.0972479568219158,
+           1.0756632760211393,
+           1.045819761676524,
+           1.0081931764834837,
+           0.9634284967358324,
+           0.9123190208696235,
+           0.8557819980346679,
+           0.794831439122761,
+           0.7305488398429326,
+           0.6640525938738229,
+           0.5964669026765075,
+           0.5288909965525981,
+           0.46236946883320823,
+           0.3978644920544939,
+           0.33623063249468593,
+           0.27819290888244425,
+           0.22432865425573573,
+           0.17505363907960314,
+           0.13061280139603726,
+           0.09107580884070733,
+           0.05633755089492111,
+           0.02612353095870142,
+           2.260205635695391e-16
+          ],
+          [
+           0,
+           -0.0218902209227713,
+           -0.04131944556513211,
+           -0.05914930756495493,
+           -0.07630624996647196,
+           -0.09375276117609335,
+           -0.11245748285776953,
+           -0.1333649917342989,
+           -0.1573660672903462,
+           -0.1852692465637841,
+           -0.2177744358187899,
+           -0.25544929769014735,
+           -0.29870906264622404,
+           -0.3478003270789059,
+           -0.40278929915778977,
+           -0.46355484031931204,
+           -0.5297865277427699,
+           -0.6009878344745481,
+           -0.6764843922389034,
+           -0.7554371707368865,
+           -0.8368602796984375,
+           -0.9196429793434079,
+           -1.0025753742841754,
+           -1.084377168080083,
+           -1.1637287731312178,
+           -1.2393040054971314,
+           -1.3098035482345607,
+           -1.373988341182126,
+           -1.4307120504894855,
+           -1.478951787779591,
+           -1.5178362863027473,
+           -1.546670798925822,
+           -1.5649580589343035,
+           -1.572414737576651,
+           -1.5689829397945954,
+           -1.5548363990375937,
+           -1.530381160529908,
+           -1.496250676689497,
+           -1.4532953752815887,
+           -1.4025668969480445,
+           -1.34529733062118,
+           -1.2828738997387565,
+           -1.2168096660338157,
+           -1.1487109181421291,
+           -1.0802419968387447,
+           -1.0130883752588347,
+           -0.9489188592923501,
+           -0.8893477992651603,
+           -0.8358982083426219,
+           -0.7899666656565116,
+           -0.7527908433397531,
+           -0.7254204373581561,
+           -0.7086922036621577,
+           -0.7032097056218306,
+           -0.7093282682575397,
+           -0.7271455121067028,
+           -0.756497707646884,
+           -0.7969620532292062,
+           -0.8478648388168668,
+           -0.908295317892821,
+           -0.9771249741042546,
+           -1.053031740855078,
+           -1.1345286142668771,
+           -1.2199959955703492,
+           -1.3077170106023972,
+           -1.3959149838164933,
+           -1.4827921937699118,
+           -1.566569007649849,
+           -1.645522484743952,
+           -1.718023553020865,
+           -1.7825718987959034,
+           -1.8378277659235656,
+           -1.882639936682677,
+           -1.9160692596330442,
+           -1.9374071979309264,
+           -1.9461889922336224,
+           -1.9422011624386661,
+           -1.9254832088992568,
+           -1.896323513094242,
+           -1.8552495765999277,
+           -1.8030128722212846,
+           -1.7405687090007231,
+           -1.6690516304242584,
+           -1.5897469696357869,
+           -1.504059274326958,
+           -1.4134783850586425,
+           -1.319544002398573,
+           -1.2238096092195552,
+           -1.1278066240974887,
+           -1.0330096498108017,
+           -0.9408036478375906,
+           -0.8524538163610511,
+           -0.7690788770145452,
+           -0.6916283862764849,
+           -0.6208645833312969,
+           -0.5573491699770848,
+           -0.5014352927082881,
+           -0.4532648655811977,
+           -0.4127712381726337,
+           -0.3796870792207943,
+           -0.35355721672344625,
+           -0.3337560525887421,
+           -0.3195090574299106,
+           -0.3099177515481149,
+           -0.3039874940102203,
+           -0.3006573350622688,
+           -0.2988311395465526,
+           -0.29740916165107995,
+           -0.2953192448470678,
+           -0.2915468353712477,
+           -0.2851630326677863,
+           -0.2753499548870737,
+           -0.26142277042218687,
+           -0.24284783566999138,
+           -0.21925648244681792,
+           -0.1904541131322215,
+           -0.1564243847389654,
+           -0.11732839158260538,
+           -0.07349888678785056,
+           -0.025429712208815947,
+           0.02623926882312574,
+           0.08074132434124408,
+           0.13720557406141776,
+           0.1946826658704971,
+           0.2521727196914366,
+           0.3086547901167927,
+           0.3631170585845026,
+           0.41458694549000813,
+           0.4621603330177824,
+           0.5050291106410613,
+           0.5425062966658015,
+           0.5740480498571883,
+           0.5992719635730305,
+           0.6179711289788952,
+           0.6301235614765698,
+           0.6358967027423169,
+           0.635646836773097,
+           0.6299133889078392,
+           0.6194082086373293,
+           0.6050000668140414,
+           0.587694722341118,
+           0.5686110294050064,
+           0.5489536608729567,
+           0.5299831139396731,
+           0.5129837381593191,
+           0.4992305817285656,
+           0.4899558878364567,
+           0.48631608810184723,
+           0.4893601341293836,
+           0.4999999811090064,
+           0.5189839897670915,
+           0.5468739459675153,
+           0.5840263124616816,
+           0.6305782267478202,
+           0.6864386451676742,
+           0.7512849090249353,
+           0.8245648767041129,
+           0.9055046297418857,
+           0.9931216239091467,
+           1.0862430219829895,
+           1.1835288163512807,
+           1.2834992300882113,
+           1.38456577764072,
+           1.485065273456468,
+           1.583296001088889,
+           1.677555198445291,
+           1.7661769783472405,
+           1.8475697883963522,
+           1.920252520709083,
+           1.9828884102905708,
+           2.0343159100192514,
+           2.0735757992515507,
+           2.0999338702819443,
+           2.112898640211918,
+           2.1122336526976175,
+           2.097964061730478,
+           2.070377324960574,
+           2.030017973811185,
+           1.977676568357322,
+           1.9143730832266508,
+           1.8413351032621263,
+           1.7599713311361331,
+           1.6718410205206002,
+           1.578620045085223,
+           1.4820643931655626,
+           1.3839719384827558,
+           1.2861433773407571,
+           1.1903432413115544,
+           1.0982618911053514,
+           1.011479372209443,
+           0.9314319665982872,
+           0.8593822085172805,
+           0.7963930476634237,
+           0.7433067421149261,
+           0.7007289485835991,
+           0.6690183517989541,
+           0.6482820411678737,
+           0.638376704564048,
+           0.6389155695722991,
+           0.6492808851542811,
+           0.6686416048653525,
+           0.6959758096475254,
+           0.7300972968402621,
+           0.7696856650851086,
+           0.813319144587917,
+           0.859509360662312,
+           0.9067371770646976,
+           0.9534887453002069,
+           0.998290887263236,
+           1.0397449611768352,
+           1.0765584041840928,
+           1.1075732079809053,
+           1.1317906649390796,
+           1.148391819184261,
+           1.15675316760749,
+           1.1564572770148582,
+           1.1472981125109427,
+           1.129281005538366,
+           1.1026173244253439,
+           1.0677140424728404,
+           1.0251585252537838,
+           0.9756989767547448,
+           0.9202210903449849,
+           0.8597215426837795,
+           0.7952790443103022,
+           0.7280237179535307,
+           0.659105613167201,
+           0.5896631828477473,
+           0.520792543159951,
+           0.45351831353095523,
+           0.38876678835530687,
+           0.3273421280635385,
+           0.2699061759006427,
+           0.21696241022732776,
+           0.1688444328648848,
+           0.1257092747407052,
+           0.08753567389017698,
+           0.05412735093844838,
+           0.025121176819868786,
+           2.1788127918481135e-16
+          ],
+          [
+           0,
+           -0.02127305198730117,
+           -0.04046295739032061,
+           -0.05847812819651207,
+           -0.07627702639912654,
+           -0.09483832025242403,
+           -0.11513035521785643,
+           -0.1380807598986298,
+           -0.1645470052668493,
+           -0.19528871247769275,
+           -0.23094246110276195,
+           -0.2719997867795524,
+           -0.31878897663430394,
+           -0.3714611744095557,
+           -0.4299811974332218,
+           -0.494123347159832,
+           -0.5634723670240065,
+           -0.6374295689934402,
+           -0.7152240168300116,
+           -0.7959285230305755,
+           -0.8784800910375795,
+           -0.9617043177617315,
+           -1.0443431667065006,
+           -1.1250854316990913,
+           -1.202599137729204,
+           -1.2755650705743484,
+           -1.342710592184221,
+           -1.4028428851420407,
+           -1.4548807773293138,
+           -1.4978843270685853,
+           -1.5310813988499963,
+           -1.5538905290883476,
+           -1.565939468545548,
+           -1.5670788909783477,
+           -1.5573908737262945,
+           -1.5371918824984834,
+           -1.5070301264438748,
+           -1.4676772874048938,
+           -1.420114765657504,
+           -1.365514720010512,
+           -1.3052163095128166,
+           -1.2406976639858467,
+           -1.1735442181714972,
+           -1.105414136775729,
+           -1.038001632773586,
+           -0.9729990371268764,
+           -0.9120585131274503,
+           -0.8567543220013984,
+           -0.8085465378083988,
+           -0.7687470792031075,
+           -0.7384888739873668,
+           -0.7186989007899847,
+           -0.7100757623741089,
+           -0.7130723391500833,
+           -0.7278839520212055,
+           -0.7544423336028733,
+           -0.7924155692879623,
+           -0.8412140279250598,
+           -0.9000021594777035,
+           -0.9677158974077182,
+           -1.0430852700741224,
+           -1.124661701410882,
+           -1.2108493695632774,
+           -1.2999398957401698,
+           -1.3901495566245206,
+           -1.4796581541945195,
+           -1.5666486381846074,
+           -1.6493465595907104,
+           -1.7260584389936013,
+           -1.7952081608929646,
+           -1.8553705540252114,
+           -1.9053013865727548,
+           -1.943963092558956,
+           -1.9705456494101286,
+           -1.984482144104286,
+           -1.985458693632526,
+           -1.9734185215266695,
+           -1.948560132624116,
+           -1.9113296696132764,
+           -1.8624076737768318,
+           -1.8026906053392502,
+           -1.7332676026927727,
+           -1.6553930715161094,
+           -1.5704557917090585,
+           -1.4799453098114737,
+           -1.3854164452502398,
+           -1.2884527789310463,
+           -1.1906300114386081,
+           -1.0934800750361995,
+           -0.9984568589087318,
+           -0.9069043613541441,
+           -0.8200280170939818,
+           -0.7388698642310082,
+           -0.664288115759468,
+           -0.596941587452751,
+           -0.5372793102628995,
+           -0.4855355241714603,
+           -0.44173011501687376,
+           -0.40567441957150385,
+           -0.37698219044695247,
+           -0.35508538459339634,
+           -0.33925432039733977,
+           -0.32862164161013946,
+           -0.32220943418904485,
+           -0.3189587668651904,
+           -0.31776086970440554,
+           -0.31748912846072247,
+           -0.31703105699805284,
+           -0.3153194158057589,
+           -0.3113616714584459,
+           -0.30426703904106955,
+           -0.2932704158400385,
+           -0.2777525982745138,
+           -0.2572562729602157,
+           -0.23149738443150775,
+           -0.20037160355020708,
+           -0.16395574891071457,
+           -0.12250414535201232,
+           -0.07644003566377013,
+           -0.02634229037998172,
+           0.027072217075051416,
+           0.08297008978741596,
+           0.14042616075847045,
+           0.19845085427058096,
+           0.2560194207797584,
+           0.3121022613591312,
+           0.36569552828698076,
+           0.4158511798118595,
+           0.461705679666469,
+           0.5025065652412652,
+           0.5376361616439482,
+           0.5666317908337491,
+           0.5892019138309326,
+           0.6052377474372848,
+           0.6148200123670419,
+           0.6182205942787423,
+           0.6158990297821971,
+           0.6084938627817594,
+           0.5968090491446251,
+           0.5817957163001606,
+           0.5645297057267064,
+           0.5461854372865609,
+           0.5280067322020475,
+           0.5112753136247727,
+           0.4972777681228246,
+           0.48727179632430667,
+           0.48245260522100064,
+           0.4839202975774713,
+           0.492649095364003,
+           0.5094591945276125,
+           0.5349919886516922,
+           0.5696893205538501,
+           0.6137773255254293,
+           0.6672553200408335,
+           0.7298900680424827,
+           0.8012156263208484,
+           0.8805388342687787,
+           0.9669503747520688,
+           1.0593411954264262,
+           1.1564239469459694,
+           1.2567589694473116,
+           1.3587842445665932,
+           1.460848629901293,
+           1.561247608776993,
+           1.6582607225355561,
+           1.750189806991385,
+           1.835397130379484,
+           1.9123425276944814,
+           1.9796186459083873,
+           2.035983455728065,
+           2.0803892473528993,
+           2.11200740865105,
+           2.1302483823487948,
+           2.1347763118566485,
+           2.125518010504912,
+           2.102666023197298,
+           2.0666756895550837,
+           2.0182562601112513,
+           1.9583562585575602,
+           1.8881434200040874,
+           1.808979664345091,
+           1.7223916819918235,
+           1.6300378135544373,
+           1.5336719929923222,
+           1.4351055931661831,
+           1.3361680619313496,
+           1.2386672647199433,
+           1.1443504553035704,
+           1.054866779982428,
+           0.971732182228789,
+           0.8962975157732933,
+           0.8297205957204864,
+           0.772942821448662,
+           0.7266708941459261,
+           0.6913640285841296,
+           0.6672269261591598,
+           0.6542086375793911,
+           0.652007302257252,
+           0.660080610906905,
+           0.6776617015042365,
+           0.7037800699454939,
+           0.737286958579036,
+           0.7768845811446202,
+           0.8211584540618797,
+           0.8686120335904507,
+           0.9177028078126589,
+           0.9668789628474057,
+           1.0146157348520026,
+           1.0594505733307784,
+           1.1000162766308936,
+           1.1350713163241022,
+           1.1635266420016848,
+           1.1844683499349953,
+           1.1971757057431434,
+           1.2011341299694005,
+           1.1960428833121455,
+           1.1818173219798587,
+           1.1585857298989022,
+           1.1266808698983606,
+           1.0866265271580837,
+           1.039119441877111,
+           0.9850071412364004,
+           0.9252622804988213,
+           0.8609541870558827,
+           0.7932183673398179,
+           0.7232247831668097,
+           0.6521457301474414,
+           0.5811241556961494,
+           0.5112432378259204,
+           0.4434980087936481,
+           0.3787697507511801,
+           0.31780381533806523,
+           0.26119142756260566,
+           0.20935592870466455,
+           0.16254379603289484,
+           0.12082065183865863,
+           0.0840723438332745,
+           0.05201104664641671,
+           0.024186203357073627,
+           2.1054818888701384e-16
+          ],
+          [
+           0,
+           -0.020773129414140307,
+           -0.03986921821745675,
+           -0.058236190987747904,
+           -0.07685643446398548,
+           -0.0967161171892581,
+           -0.11877428406288937,
+           -0.14393255746417583,
+           -0.17300626230676752,
+           -0.20669775707059376,
+           -0.24557269741370252,
+           -0.29003988477349124,
+           -0.3403352612829282,
+           -0.39651050663690807,
+           -0.45842657490132577,
+           -0.525752382621083,
+           -0.5979687271412824,
+           -0.674377379146937,
+           -0.7541151594559378,
+           -0.8361726804549774,
+           -0.9194173105325976,
+           -1.0026198085361984,
+           -1.0844839774963837,
+           -1.1636786051238281,
+           -1.238870894995186,
+           -1.308760548559486,
+           -1.3721136352768668,
+           -1.4277953869875069,
+           -1.4748010731018109,
+           -1.5122841549631094,
+           -1.539580979789459,
+           -1.5562313554714862,
+           -1.561994445236356,
+           -1.5568595334073259,
+           -1.5410513374515864,
+           -1.5150296741755114,
+           -1.4794834260323522,
+           -1.4353188936465158,
+           -1.383642759366543,
+           -1.3257400204991259,
+           -1.2630473765252874,
+           -1.1971226689291288,
+           -1.1296110724242279,
+           -1.0622088198326052,
+           -0.9966253075521746,
+           -0.9345444727969053,
+           -0.8775863564659762,
+           -0.8272697659803435,
+           -0.7849769306489836,
+           -0.7519209985720589,
+           -0.7291171597703671,
+           -0.7173580966775308,
+           -0.7171943623464516,
+           -0.7289201711331423,
+           -0.7525649590244322,
+           -0.7878909342641413,
+           -0.8343966968200305,
+           -0.8913268609764367,
+           -0.9576874724456602,
+           -1.0322668733445695,
+           -1.113661538544816,
+           -1.2003062884388074,
+           -1.290508178956151,
+           -1.382483282254147,
+           -1.4743955030186937,
+           -1.5643965274125997,
+           -1.6506659755566648,
+           -1.7314508246527727,
+           -1.8051031885365025,
+           -1.8701155801101914,
+           -1.9251528447466781,
+           -1.9690800338491607,
+           -2.0009855863063657,
+           -2.020199299172909,
+           -2.026304694743639,
+           -2.0191455261925393,
+           -1.9988263048049528,
+           -1.9657068751004994,
+           -1.9203912063230755,
+           -1.8637107063950917,
+           -1.7967024941448293,
+           -1.7205831842670387,
+           -1.6367188441938567,
+           -1.5465918703093637,
+           -1.4517656006206057,
+           -1.3538475304453435,
+           -1.2544520257391973,
+           -1.155163434738405,
+           -1.0575004825596879,
+           -0.9628827957416289,
+           -0.8726003454314867,
+           -0.787786520524135,
+           -0.7093954475218643,
+           -0.6381840646011492,
+           -0.5746993361006697,
+           -0.5192708634310105,
+           -0.472009012511504,
+           -0.43280853965937915,
+           -0.4013575608344967,
+           -0.37715157668731375,
+           -0.35951214125461556,
+           -0.3476096484803818,
+           -0.34048961081224477,
+           -0.337101720392675,
+           -0.33633091787446406,
+           -0.33702964822846787,
+           -0.33805045816531853,
+           -0.33827808652416624,
+           -0.33666021721390027,
+           -0.33223610351066846,
+           -0.32416233167966474,
+           -0.31173506946025764,
+           -0.2944082389333078,
+           -0.2718071612703138,
+           -0.24373734008992676,
+           -0.2101881775827314,
+           -0.17133154997173705,
+           -0.1275153028931251,
+           -0.07925185951159194,
+           -0.02720226127648057,
+           0.02784392004028947,
+           0.08499225301259278,
+           0.14327006063571937,
+           0.2016552616707088,
+           0.2591066646765342,
+           0.3145949015898874,
+           0.3671331700206972,
+           0.4158069570670286,
+           0.4598019423376893,
+           0.49842932339117496,
+           0.5311478718220083,
+           0.557582111124074,
+           0.5775361061580091,
+           0.5910024660688645,
+           0.5981662850258113,
+           0.5994038751049148,
+           0.5952762797351102,
+           0.5865176909941099,
+           0.574019026267823,
+           0.5588070460283407,
+           0.5420195115398484,
+           0.5248769861926751,
+           0.508651974216029,
+           0.49463616341977706,
+           0.48410659247965454,
+           0.47829159669615107,
+           0.4783373982210814,
+           0.48527619708541325,
+           0.49999658814694053,
+           0.5232170770151063,
+           0.5554633963323701,
+           0.5970502342183901,
+           0.6480678813860632,
+           0.7083741849845255,
+           0.7775920685140192,
+           0.8551127413529265,
+           0.9401045818840497,
+           1.031527538350681,
+           1.1281527548750199,
+           1.228586999922385,
+           1.3313013541305314,
+           1.4346635068450073,
+           1.5369729185999386,
+           1.636498032473748,
+           1.7315146626098847,
+           1.8203446546228208,
+           1.9013939009903498,
+           1.9731888052063855,
+           2.0344103212288123,
+           2.0839247488535184,
+           2.120810539803572,
+           2.144380461770291,
+           2.154198576158196,
+           2.1500916072488145,
+           2.132154412955454,
+           2.1007494070789745,
+           2.056499926597448,
+           2.0002776815368177,
+           1.9331845658691735,
+           1.8565292422381279,
+           1.7717990378434791,
+           1.6806278004954331,
+           1.5847604599515202,
+           1.4860151178373417,
+           1.3862435478234634,
+           1.2872910248691651,
+           1.1909564173527636,
+           1.09895346843325,
+           1.0128741632249485,
+           0.9341550270573653,
+           0.8640471285050416,
+           0.8035904707708381,
+           0.7535933486073355,
+           0.7146171278781103,
+           0.6869667740395649,
+           0.6706873174706076,
+           0.6655663010786506,
+           0.6711421124495611,
+           0.6867179624817947,
+           0.7113811383709947,
+           0.7440270342521589,
+           0.7833873507838796,
+           0.8280617581817112,
+           0.8765522380035403,
+           0.9272992592507002,
+           0.9787189054826612,
+           1.0292400525414527,
+           1.0773407014975498,
+           1.12158259836727,
+           1.1606433202784294,
+           1.193345075819091,
+           1.218679553546827,
+           1.235828254870272,
+           1.2441778631566753,
+           1.2433303270587368,
+           1.2331074695267341,
+           1.213550071439545,
+           1.1849115168199333,
+           1.1476462217589272,
+           1.1023931981038853,
+           1.049955222470062,
+           0.9912741882631158,
+           0.9274033105121839,
+           0.8594769281519484,
+           0.7886787041359101,
+           0.716209059070915,
+           0.6432526881074505,
+           0.5709470033077788,
+           0.5003523148911203,
+           0.4324245154021913,
+           0.36799096225982997,
+           0.3077301680905312,
+           0.25215580694738304,
+           0.20160543054805333,
+           0.15623416494096592,
+           0.11601352767370426,
+           0.08073537190149793,
+           0.050020830326555424,
+           0.023334001785767396,
+           2.041555955207608e-16
+          ],
+          [
+           0,
+           -0.02040265304590808,
+           -0.03955936003829874,
+           -0.058449738769215526,
+           -0.07807158416401798,
+           -0.09940960813101052,
+           -0.12340442796745674,
+           -0.15092263911183654,
+           -0.1827287812430957,
+           -0.2194599591278136,
+           -0.26160381239404945,
+           -0.3094804432496129,
+           -0.36322881019931896,
+           -0.4227979815869653,
+           -0.4879435181664399,
+           -0.5582291220304265,
+           -0.6330335534190458,
+           -0.7115626806220557,
+           -0.7928663948223155,
+           -0.8758599946817263,
+           -0.9593495279673605,
+           -1.0420604725444986,
+           -1.1226690493053797,
+           -1.1998353873618441,
+           -1.2722377089763848,
+           -1.3386066696276855,
+           -1.3977589781743562,
+           -1.4486294336262175,
+           -1.4903005483390819,
+           -1.5220289817560204,
+           -1.5432680828390954,
+           -1.5536859312897158,
+           -1.5531783753113353,
+           -1.541876684397578,
+           -1.520149566472801,
+           -1.4885994364536208,
+           -1.4480529645428388,
+           -1.399546073821074,
+           -1.3443036944674045,
+           -1.2837147127983326,
+           -1.2193026740078203,
+           -1.1526929050078014,
+           -1.0855768154159373,
+           -1.0196742082089538,
+           -0.9566944849942419,
+           -0.8982976628775955,
+           -0.8460561296758305,
+           -0.8014180514400994,
+           -0.7656733111751849,
+           -0.7399228010671575,
+           -0.7250518138015626,
+           -0.72170818349994,
+           -0.7302857157092907,
+           -0.7509133214302492,
+           -0.7834501353787481,
+           -0.8274867568142569,
+           -0.8823526057830217,
+           -0.9471292420571973,
+           -1.0206693519451602,
+           -1.1016209729674276,
+           -1.1884564014311119,
+           -1.2795051162406277,
+           -1.3729899565754715,
+           -1.4670657136796206,
+           -1.5598592398249531,
+           -1.6495101419222886,
+           -1.7342111141188237,
+           -1.812246973350397,
+           -1.8820314939650191,
+           -1.9421411914020599,
+           -1.9913452791712103,
+           -2.028631116198637,
+           -2.053224570714423,
+           -2.064604849567809,
+           -2.0625134751665293,
+           -2.046957232879208,
+           -2.018205056274488,
+           -1.9767789624658654,
+           -1.9234392915512943,
+           -1.8591646392291044,
+           -1.7851269968522214,
+           -1.7026627254154838,
+           -1.613240086544105,
+           -1.5184241321428253,
+           -1.4198398130997665,
+           -1.319134204933777,
+           -1.2179387636720123,
+           -1.1178325182359432,
+           -1.0203070764411915,
+           -0.9267342711699584,
+           -0.8383372026696908,
+           -0.7561653440770656,
+           -0.6810742724184797,
+           -0.6137104691439607,
+           -0.5545015056823787,
+           -0.50365179378396,
+           -0.4611439409335542,
+           -0.42674561135244127,
+           -0.4000216565346233,
+           -0.3803511492748414,
+           -0.36694883495827163,
+           -0.35889040646262665,
+           -0.3551409170144828,
+           -0.3545855709950913,
+           -0.35606207781327076,
+           -0.3583937198706632,
+           -0.3604222731320705,
+           -0.3610399281336235,
+           -0.35921939012029097,
+           -0.3540413885686826,
+           -0.34471889727062777,
+           -0.33061745459396125,
+           -0.31127107722839814,
+           -0.28639337701612017,
+           -0.2558836163949887,
+           -0.2198275703452106,
+           -0.17849319816724063,
+           -0.13232126349523168,
+           -0.08191117224403194,
+           -0.028002422373794647,
+           0.028547826708978402,
+           0.08679045649556011,
+           0.14571266973361618,
+           0.20426808780065728,
+           0.2614078563732974,
+           0.3161119237171576,
+           0.36741965041979974,
+           0.4144589254904244,
+           0.4564730010609306,
+           0.492844315514333,
+           0.5231146512981388,
+           0.5470010670359581,
+           0.5644071514864706,
+           0.5754292667015988,
+           0.580357576390293,
+           0.5796717897596262,
+           0.5740316875940991,
+           0.564262632599978,
+           0.5513363966624268,
+           0.5363477603285859,
+           0.5204874514234166,
+           0.5050120873827736,
+           0.49121186714998694,
+           0.4803768212342583,
+           0.4737624711374355,
+           0.47255577068705085,
+           0.47784220126448623,
+           0.4905748704300507,
+           0.5115464195117676,
+           0.5413644813685581,
+           0.5804313462993644,
+           0.6289283939602246,
+           0.6868057346085211,
+           0.7537773768196425,
+           0.8293221041137754,
+           0.9126901030064497,
+           1.0029152433097066,
+           1.0988327715668922,
+           1.1991020437732467,
+           1.302233797365891,
+           1.4066213480038676,
+           1.5105749967636257,
+           1.6123588505547413,
+           1.7102291949052442,
+           1.8024735153975275,
+           1.8874492430663368,
+           1.9636213005745804,
+           2.0295975499813195,
+           2.084161288878225,
+           2.1263000085218398,
+           2.155229713740499,
+           2.1704142077811515,
+           2.1715788633906556,
+           2.1587185314413886,
+           2.132099377159789,
+           2.0922545781291615,
+           2.039973964209635,
+           1.9762878237954058,
+           1.9024452398976162,
+           1.8198874500112914,
+           1.730216842415938,
+           1.6351623055785696,
+           1.53654173413981,
+           1.4362225624543208,
+           1.3360812431838462,
+           1.2379626128775545,
+           1.1436400882314472,
+           1.0547776157649376,
+           0.9728942545118032,
+           0.8993322070613595,
+           0.8352290304870451,
+           0.7814946574236493,
+           0.7387937412888052,
+           0.7075337112399066,
+           0.6878587850609944,
+           0.6796500451483458,
+           0.6825315376053985,
+           0.695882210711755,
+           0.7188533702023523,
+           0.7503911982602359,
+           0.789263764059454,
+           0.8340918489760695,
+           0.8833828217399994,
+           0.9355667299334229,
+           0.9890337259867565,
+           1.0421719193043175,
+           1.093404741953286,
+           1.1412269335056933,
+           1.1842382906157416,
+           1.2211743876872165,
+           1.250933554971593,
+           1.2725994975967845,
+           1.2854590509011676,
+           1.2890146912183589,
+           1.2829915538195165,
+           1.2673388477540373,
+           1.2422256973906745,
+           1.2080315790615217,
+           1.1653316549068111,
+           1.1148774314952892,
+           1.0575732849507709,
+           0.9944494943371618,
+           0.9266325084872526,
+           0.8553132362690782,
+           0.781714194901461,
+           0.7070563742989053,
+           0.6325266770199643,
+           0.5592467732332466,
+           0.4882441687668094,
+           0.42042622286499,
+           0.356557772338904,
+           0.2972429224218326,
+           0.24291145429681912,
+           0.1938101777667751,
+           0.14999942797977023,
+           0.11135477079582276,
+           0.07757384569422117,
+           0.04818814151171405,
+           0.022579372155996327,
+           1.988303888215097e-16
+          ],
+          [
+           0,
+           -0.020172691312177183,
+           -0.039551934030124934,
+           -0.05914073431261991,
+           -0.07994343417373195,
+           -0.10293413976322663,
+           -0.12902588102540896,
+           -0.15904133521223274,
+           -0.19368590739242625,
+           -0.2335239013441193,
+           -0.27895843554124883,
+           -0.3302156633188469,
+           -0.3873337461325973,
+           -0.4501569068856565,
+           -0.5183347596517734,
+           -0.5913269760718094,
+           -0.6684132106745739,
+           -0.7487080708605899,
+           -0.8311807857439152,
+           -0.91467910480817,
+           -0.9979568455308336,
+           -1.0797044116155516,
+           -1.1585815227431242,
+           -1.233251334889498,
+           -1.3024150888761357,
+           -1.3648464050178308,
+           -1.4194243440807977,
+           -1.4651643792724123,
+           -1.5012464701124322,
+           -1.5270394957018478,
+           -1.5421213905127846,
+           -1.5462944282983946,
+           -1.5395952165676074,
+           -1.5222990924246838,
+           -1.4949187472837042,
+           -1.4581970496640742,
+           -1.4130941784544748,
+           -1.360769320153673,
+           -1.3025573191549649,
+           -1.2399407967642802,
+           -1.1745183691716112,
+           -1.107969694165354,
+           -1.042018158486904,
+           -0.9783920802927261,
+           -0.9187853426250701,
+           -0.8648183930114351,
+           -0.8180005407831252,
+           -0.7796944574509362,
+           -0.7510837370869073,
+           -0.7331443042667998,
+           -0.726620368378716,
+           -0.7320055171275085,
+           -0.7495294214173335,
+           -0.779150491394409,
+           -0.8205546824895656,
+           -0.8731605042395779,
+           -0.9361301370405827,
+           -1.0083864163910061,
+           -1.0886353041632333,
+           -1.1753933354165766,
+           -1.2670194104247379,
+           -1.3617501978370838,
+           -1.457738328755704,
+           -1.5530924950883465,
+           -1.6459185204487843,
+           -1.7343604492158695,
+           -1.8166406996765507,
+           -1.891098350450378,
+           -1.9562246750445673,
+           -2.010695106294507,
+           -2.053396898958006,
+           -2.0834518627288894,
+           -2.100233656864812,
+           -2.10337926857108,
+           -2.0927944370403395,
+           -2.0686529301984606,
+           -2.031389728202913,
+           -1.9816883129936416,
+           -1.9204624031680795,
+           -1.8488326047362358,
+           -1.7680985677222782,
+           -1.6797073432261223,
+           -1.5852187229205115,
+           -1.4862684109435635,
+           -1.3845299251427141,
+           -1.2816761495413382,
+           -1.1793414621890534,
+           -1.0790853422339046,
+           -0.9823583176907374,
+           -0.8904710520889436,
+           -0.8045672855930303,
+           -0.7256012464030682,
+           -0.6543200337816377,
+           -0.5912513477996839,
+           -0.5366968060112745,
+           -0.490730947129492,
+           -0.4532058798771689,
+           -0.4237613950582335,
+           -0.40184022401650005,
+           -0.38670800035937747,
+           -0.37747736724325415,
+           -0.37313557246584367,
+           -0.3725748105409062,
+           -0.3746245068659535,
+           -0.3780846955787206,
+           -0.3817596207617142,
+           -0.3844906907829549,
+           -0.3851879376892399,
+           -0.382859177079281,
+           -0.3766361276269276,
+           -0.36579683174321564,
+           -0.3497838176407162,
+           -0.32821755576552425,
+           -0.3009048863158069,
+           -0.26784222622215476,
+           -0.22921350017979167,
+           -0.1853828776412769,
+           -0.13688253262105773,
+           -0.08439577231367927,
+           -0.0287360006172326,
+           0.029177909355367394,
+           0.08834916653426039,
+           0.14773279370426898,
+           0.20626673979399957,
+           0.2629035362587647,
+           0.31664164634371744,
+           0.36655566304376863,
+           0.41182454029927684,
+           0.45175709166646544,
+           0.48581406013535605,
+           0.5136261501942924,
+           0.5350075164626497,
+           0.5499643196364447,
+           0.5586980871846063,
+           0.561603750004189,
+           0.5592623637167624,
+           0.552428660993638,
+           0.5420137157522162,
+           0.529063127863261,
+           0.5147312549055514,
+           0.5002521224986607,
+           0.4869077341541602,
+           0.47599457311353927,
+           0.46878914043472336,
+           0.46651340428581617,
+           0.47030104416765106,
+           0.481165360325833,
+           0.49996968319295354,
+           0.5274010611364792,
+           0.5639479284210335,
+           0.6098823609658602,
+           0.6652474174814846,
+           0.7298499405918218,
+           0.8032590596062592,
+           0.8848104969723077,
+           0.9736166375587002,
+           1.0685821773258444,
+           1.1684250291694933,
+           1.2717020322232149,
+           1.376838889951038,
+           1.4821636549753547,
+           1.5859429874593727,
+           1.6864203412943557,
+           1.7818551801727727,
+           1.8705622952010124,
+           1.9509502878295968,
+           2.0215582968089696,
+           2.0810900853078684,
+           2.1284446633984953,
+           2.1627427004221804,
+           2.1833480794065214,
+           2.1898840593608497,
+           2.182243638186123,
+           2.1605938460240397,
+           2.1253738428104456,
+           2.077286841090695,
+           2.017286022214638,
+           1.9465547572737236,
+           1.866481580080766,
+           1.7786304848093808,
+           1.6847072325482353,
+           1.58652244626226,
+           1.4859523501666334,
+           1.384898065445668,
+           1.2852444082267729,
+           1.1888191469267473,
+           1.097353664257954,
+           1.012445934613633,
+           0.9355266710995828,
+           0.8678294195337308,
+           0.8103652811869217,
+           0.7639028342323326,
+           0.7289536985491635,
+           0.7057640527584746,
+           0.6943122694780148,
+           0.6943126882623163,
+           0.7052253991226441,
+           0.7262717664732263,
+           0.7564552873089975,
+           0.7945872516918125,
+           0.8393165612541362,
+           0.8891629651355691,
+           0.9425528948624868,
+           0.9978570220216016,
+           1.0534286265205206,
+           1.1076418495930174,
+           1.158928914760456,
+           1.205815431410713,
+           1.2469529486560904,
+           1.2811480003069866,
+           1.3073869732770957,
+           1.3248562391990566,
+           1.3329571097670159,
+           1.3313153073018058,
+           1.3197847799763913,
+           1.2984458325988868,
+           1.2675976853043427,
+           1.2277457104385676,
+           1.1795837289073738,
+           1.123971868073094,
+           1.0619105909277646,
+           0.9945115981144452,
+           0.9229663781599363,
+           0.8485132352338546,
+           0.7724036565701407,
+           0.6958688926176534,
+           0.6200876118154138,
+           0.5461554589577337,
+           0.4750572923114387,
+           0.40764280137993447,
+           0.34460611637049143,
+           0.2864699143436595,
+           0.23357440841790167,
+           0.18607147829003545,
+           0.143924065969655,
+           0.10691082342380265,
+           0.07463586226451473,
+           0.0465433231456442,
+           0.021936357519358428,
+           1.946905840445738e-16
+          ],
+          [
+           0,
+           -0.02009304629816513,
+           -0.03986267296876799,
+           -0.06032655854743409,
+           -0.08248646918756394,
+           -0.10729665251818177,
+           -0.13563345044748518,
+           -0.1682669524996882,
+           -0.20583545945349035,
+           -0.24882345539461367,
+           -0.2975436966022386,
+           -0.35212392021533767,
+           -0.41249855702464777,
+           -0.47840570399710225,
+           -0.5493894765080415,
+           -0.6248077211556865,
+           -0.7038449309769692,
+           -0.7855300693923567,
+           -0.8687588807136045,
+           -0.952320146815983,
+           -1.0349252446164399,
+           -1.115240269994602,
+           -1.1919199230321507,
+           -1.2636422987626779,
+           -1.3291436983537104,
+           -1.387252568586963,
+           -1.4369216929094524,
+           -1.477257794883205,
+           -1.5075477736970717,
+           -1.5272808701195335,
+           -1.5361661579659882,
+           -1.5341448684749965,
+           -1.5213971801877797,
+           -1.4983432419292637,
+           -1.465638337971911,
+           -1.424162248930975,
+           -1.3750030058156606,
+           -1.3194353743749303,
+           -1.2588945389549253,
+           -1.1949455762338492,
+           -1.1292494163900517,
+           -1.06352607979905,
+           -0.9995160489602763,
+           -0.9389406862030151,
+           -0.8834626365000577,
+           -0.8346471606564413,
+           -0.793925327030028,
+           -0.7625599501392216,
+           -0.7416151029388285,
+           -0.7319299476534692,
+           -0.7340975298066462,
+           -0.7484490638845412,
+           -0.7750441097342552,
+           -0.813666899450201,
+           -0.863828928533132,
+           -0.9247777760635156,
+           -0.9955119701433717,
+           -1.0748015705468372,
+           -1.161214003898764,
+           -1.2531445611056697,
+           -1.348850855259675,
+           -1.4464904435445347,
+           -1.5441607411050151,
+           -1.6399403002390156,
+           -1.7319304959666835,
+           -1.8182966498064372,
+           -1.8973076376635858,
+           -1.9673730647624605,
+           -2.0270771496142954,
+           -2.075208538659788,
+           -2.110785371501372,
+           -2.1330750311370457,
+           -2.1416081415191064,
+           -2.1361865129567477,
+           -2.1168848809805474,
+           -2.084046432744007,
+           -2.0382722632285004,
+           -1.9804050478306656,
+           -1.9115073548328931,
+           -1.8328351474621456,
+           -1.7458071376722126,
+           -1.6519707497254843,
+           -1.5529655287981354,
+           -1.4504848863490778,
+           -1.3462371085516363,
+           -1.2419065659034503,
+           -1.139116050983067,
+           -1.0393911375554759,
+           -0.9441273987454685,
+           -0.8545612462330798,
+           -0.7717450583134073,
+           -0.6965271545868765,
+           -0.6295370517781698,
+           -0.5711763018155642,
+           -0.5216150731731798,
+           -0.4807944930830974,
+           -0.4484346251310586,
+           -0.4240478175124399,
+           -0.4069570252935577,
+           -0.39631858865730746,
+           -0.39114884130141286,
+           -0.3903538315476839,
+           -0.3927613655476698,
+           -0.3971545290052588,
+           -0.4023058123432974,
+           -0.40701095494348294,
+           -0.4101216371545326,
+           -0.4105761838013011,
+           -0.4074274989959751,
+           -0.39986752768558703,
+           -0.38724763261382505,
+           -0.36909438383678744,
+           -0.3451203788411269,
+           -0.31522984158930706,
+           -0.2795188851498114,
+           -0.2382704615007747,
+           -0.1919441601032679,
+           -0.14116115043115074,
+           -0.0866846894383069,
+           -0.029396729760059918,
+           0.029728734619120088,
+           0.0896548639964179,
+           0.14931292271089033,
+           0.20763415016755216,
+           0.2635816959591747,
+           0.31618175963399003,
+           0.3645530954511404,
+           0.4079340838467565,
+           0.4457066332658506,
+           0.4774162569441738,
+           0.5027877671159086,
+           0.5217361415145335,
+           0.5343722410953933,
+           0.5410031905127278,
+           0.5421273706858858,
+           0.5384241123094509,
+           0.5307383168722057,
+           0.520060364163311,
+           0.5075017890012664,
+           0.49426732187542405,
+           0.4816239854845409,
+           0.4708680192990077,
+           0.46329046519515804,
+           0.4601422873215652,
+           0.46259991758648034,
+           0.47173211397632286,
+           0.48846899236052255,
+           0.5135740441005147,
+           0.5476198827982294,
+           0.5909683755478138,
+           0.6437557092267074,
+           0.7058828232366797,
+           0.7770115096021145,
+           0.8565663426616585,
+           0.9437424571707149,
+           1.0375190490122952,
+           1.136678330477131,
+           1.2398295357530307,
+           1.3454374452535285,
+           1.4518547828878003,
+           1.5573577411970487,
+           1.660183807952673,
+           1.7585710063883249,
+           1.8507976212941215,
+           1.9352214657810571,
+           2.010317749119677,
+           2.0747146345939496,
+           2.1272256271485923,
+           2.1668780025562193,
+           2.1929365811769466,
+           2.204922257936732,
+           2.2026248232935783,
+           2.186109744713277,
+           2.155718721269972,
+           2.112063971944273,
+           2.056016367412463,
+           1.988687661970051,
+           1.911407223131177,
+           1.8256937879557824,
+           1.7332228940698635,
+           1.63579073675838,
+           1.5352752889015597,
+           1.4335955858101233,
+           1.332670120602018,
+           1.2343753165916063,
+           1.140505040728936,
+           1.0527320964976696,
+           0.9725725864891375,
+           0.9013539653027516,
+           0.8401875141882169,
+           0.7899458621318695,
+           0.7512460565131222,
+           0.7244385529952899,
+           0.70960235223356,
+           0.7065463637552205,
+           0.7148169285893685,
+           0.7337112855246842,
+           0.7622966248279254,
+           0.7994342412925391,
+           0.8438081788077896,
+           0.8939576541388834,
+           0.948312460804693,
+           1.0052304869095245,
+           1.0630364351158001,
+           1.1200608096945324,
+           1.174678235264013,
+           1.2253441943624948,
+           1.270629315773012,
+           1.3092504113544952,
+           1.340097544343303,
+           1.3622565145077021,
+           1.3750262625786462,
+           1.3779308251016407,
+           1.3707256080317411,
+           1.3533978896003698,
+           1.3261616066746333,
+           1.2894466204351942,
+           1.2438827932048184,
+           1.190279335301395,
+           1.1295999957319025,
+           1.0629347705610024,
+           0.9914688854313396,
+           0.9164498719725187,
+           0.8391536001899621,
+           0.7608501493768496,
+           0.6827703981946402,
+           0.6060741904325552,
+           0.5318208872524475,
+           0.4609430506601469,
+           0.3942239182332982,
+           0.3322792279589458,
+           0.2755438369817131,
+           0.2242634520698154,
+           0.1784916558765263,
+           0.13809227500464655,
+           0.10274699697208277,
+           0.07196800694582585,
+           0.04511528500747296,
+           0.021418084026580884,
+           1.9184393642454401e-16
+          ],
+          [
+           0,
+           -0.020172130583057526,
+           -0.0405042806439822,
+           -0.06201975376305619,
+           -0.08570844216887243,
+           -0.11249546962770088,
+           -0.14321154102921438,
+           -0.17856580173457376,
+           -0.2191219456289249,
+           -0.26527822763497344,
+           -0.3172519362907713,
+           -0.3750687673953541,
+           -0.4385574135684352,
+           -0.5073495500367445,
+           -0.580885257445675,
+           -0.6584237815257289,
+           -0.7390593905850336,
+           -0.8217419585696525,
+           -0.9053017772141421,
+           -0.9884779887560394,
+           -1.0699499336696208,
+           -1.1483706283738586,
+           -1.2224015279396088,
+           -1.2907476900274866,
+           -1.352192439669841,
+           -1.4056306405538928,
+           -1.4500997070883608,
+           -1.4848075420980944,
+           -1.5091566562958576,
+           -1.5227638160126191,
+           -1.5254746728338535,
+           -1.5173729501712634,
+           -1.4987838944185008,
+           -1.4702718389310243,
+           -1.4326318741631665,
+           -1.3868757632992919,
+           -1.3342123860089046,
+           -1.2760231299752431,
+           -1.213832777178312,
+           -1.149276546373877,
+           -1.084064051928977,
+           -1.0199410196644085,
+           -0.9586496605736169,
+           -0.9018886416898206,
+           -0.8512736089498435,
+           -0.8082992092048602,
+           -0.7743035276804394,
+           -0.7504358038857742,
+           -0.7376282144647207,
+           -0.7365724175428519,
+           -0.7477014420096281,
+           -0.7711773795633755,
+           -0.8068852002791943,
+           -0.8544328672620033,
+           -0.913157776148082,
+           -0.9821393944649794,
+           -1.0602178278250916,
+           -1.1460178982228075,
+           -1.2379781877868772,
+           -1.3343843824295334,
+           -1.4334061468353505,
+           -1.5331366776622082,
+           -1.631634017748703,
+           -1.7269631721015624,
+           -1.8172380474972194,
+           -1.9006622421331898,
+           -1.9755677397904712,
+           -2.040450613727544,
+           -2.0940029177736244,
+           -2.1351400340511035,
+           -2.163022856181836,
+           -2.1770743110386346,
+           -2.176989858052919,
+           -2.1627417494570653,
+           -2.1345769840980915,
+           -2.0930090379642095,
+           -2.038803602647652,
+           -1.9729587050201505,
+           -1.8966797139688016,
+           -1.8113498599144056,
+           -1.7184969971137574,
+           -1.619757424920869,
+           -1.5168376501890228,
+           -1.4114750172740662,
+           -1.3053981536256967,
+           -1.2002881772659024,
+           -1.097741587662931,
+           -0.9992357142961344,
+           -0.9060975288028726,
+           -0.8194765387567113,
+           -0.7403223760745081,
+           -0.6693675734382114,
+           -0.6071158909486649,
+           -0.5538364157861305,
+           -0.5095635134158994,
+           -0.4741025634382951,
+           -0.4470412701533972,
+           -0.4277662008364334,
+           -0.41548407698865614,
+           -0.40924722858907986,
+           -0.4079825214554234,
+           -0.41052298567055934,
+           -0.4156413106384664,
+           -0.4220843311984159,
+           -0.4286076103117925,
+           -0.43400922754901783,
+           -0.43716190878499306,
+           -0.4370426804385414,
+           -0.4327593000002105,
+           -0.4235728017080661,
+           -0.40891559981151493,
+           -0.3884047092583448,
+           -0.36184977185658024,
+           -0.3292557117399357,
+           -0.2908199838569247,
+           -0.24692451966355877,
+           -0.19812261167179027,
+           -0.14512110951288562,
+           -0.08875842140495793,
+           -0.02997892330359631,
+           0.03019552917426831,
+           0.09069621607468129,
+           0.15043947062716467,
+           0.20835904004316608,
+           0.2634380188731153,
+           0.3147394947685555,
+           0.36143507916663326,
+           0.4028305493711896,
+           0.4383879023921482,
+           0.4677432128642591,
+           0.4907197950826215,
+           0.5073362899521684,
+           0.5178094284070025,
+           0.522551360314049,
+           0.5221615785624572,
+           0.5174136083989901,
+           0.5092367685469762,
+           0.49869343978181935,
+           0.4869523951484109,
+           0.47525885087540154,
+           0.464901985586123,
+           0.4571807453485331,
+           0.4533688016323196,
+           0.4546795570432141,
+           0.4622320990176278,
+           0.4770189842811583,
+           0.49987669716572364,
+           0.531459563764382,
+           0.5722178228394996,
+           0.622380455349055,
+           0.6819432598308531,
+           0.7506625334923259,
+           0.8280545818257762,
+           0.9134011362837364,
+           1.0057606135483539,
+           1.1039850048297535,
+           1.2067420430344193,
+           1.3125421630553233,
+           1.4197696491598755,
+           1.5267172565263194,
+           1.6316235040906288,
+           1.7327117652869402,
+           1.8282302337940028,
+           1.9164918143196839,
+           1.9959129844965597,
+           2.0650506932867327,
+           2.122636403492116,
+           2.1676064500615273,
+           2.199127970362467,
+           2.2166197654227244,
+           2.2197675698699917,
+           2.2085333400375746,
+           2.183158311268158,
+           2.1441597233971255,
+           2.092321264133476,
+           2.0286774299083863,
+           1.9544921490760214,
+           1.8712321495829631,
+           1.7805356790221896,
+           1.6841772962828352,
+           1.5840295480798354,
+           1.4820224182005244,
+           1.3801014905178337,
+           1.2801857973939073,
+           1.1841263322887376,
+           1.093666189025292,
+           1.0104032506490424,
+           0.9357562891278124,
+           0.8709352547810761,
+           0.8169164333252942,
+           0.7744230312478194,
+           0.7439116197446092,
+           0.7255647268690382,
+           0.7192897202765559,
+           0.724723972609876,
+           0.7412461518198687,
+           0.7679933332073569,
+           0.8038834922407624,
+           0.8476428105985779,
+           0.8978371154697256,
+           0.9529066766320298,
+           1.0112035095119836,
+           1.0710302771245992,
+           1.1306798507970282,
+           1.1884745796387501,
+           1.2428043320108342,
+           1.292162408369153,
+           1.335178482853073,
+           1.370647809364842,
+           1.3975560246383831,
+           1.4150989934836156,
+           1.4226972671775564,
+           1.4200048617044791,
+           1.406912204831193,
+           1.3835432462940929,
+           1.3502468700586008,
+           1.3075828880990228,
+           1.2563030279605967,
+           1.1973274482265694,
+           1.131717423922998,
+           1.0606449352074643,
+           0.9853599651797065,
+           0.9071563645709113,
+           0.8273371711795473,
+           0.7471802795380513,
+           0.6679053412926976,
+           0.5906427396005397,
+           0.516405422488654,
+           0.4460643021069647,
+           0.38032783115114366,
+           0.3197262568900886,
+           0.26460093003419943,
+           0.21509891326293615,
+           0.17117299595701288,
+           0.13258708105913344,
+           0.09892677057971072,
+           0.06961484159810015,
+           0.043931178091114804,
+           0.02103660874657007,
+           1.9038664723107605e-16
+          ],
+          [
+           0,
+           -0.02041685729585867,
+           -0.04148625082181759,
+           -0.06422781502062755,
+           -0.08961018493383029,
+           -0.11852017516240912,
+           -0.15173414880915811,
+           -0.18989235333001211,
+           -0.23347692409461077,
+           -0.28279416223141035,
+           -0.33796158338414234,
+           -0.3989001111064851,
+           -0.465331655871033,
+           -0.5367821814184955,
+           -0.6125902179420752,
+           -0.6919206399877461,
+           -0.7737833895402251,
+           -0.8570566950425698,
+           -0.9405142183619467,
+           -1.0228554569918624,
+           -1.1027386407515904,
+           -1.1788152931719336,
+           -1.2497655794366074,
+           -1.31433353645731,
+           -1.3713612771253705,
+           -1.4198212801628516,
+           -1.4588459188771756,
+           -1.4877534455281867,
+           -1.5060697314276383,
+           -1.5135451642880287,
+           -1.5101662212467972,
+           -1.4961613655471648,
+           -1.4720010538706625,
+           -1.4383917863581772,
+           -1.3962642788380837,
+           -1.3467559830441838,
+           -1.2911883220178746,
+           -1.2310391409247194,
+           -1.167910994852232,
+           -1.103496001752266,
+           -1.0395380778654175,
+           -0.9777934424591475,
+           -0.9199903267503957,
+           -0.8677888472186946,
+           -0.8227420054561276,
+           -0.7862587551313258,
+           -0.7595700320306336,
+           -0.7436985765141466,
+           -0.7394332906648987,
+           -0.7473087669991216,
+           -0.7675905043819958,
+           -0.8002661926870565,
+           -0.8450433039996508,
+           -0.9013530782875532,
+           -0.9683608390921852,
+           -1.04498242364425,
+           -1.1299063655642587,
+           -1.2216213305408599,
+           -1.3184481794526715,
+           -1.4185759223891823,
+           -1.520100733646845,
+           -1.6210671243097996,
+           -1.719510317267639,
+           -1.8134988407392918,
+           -1.901176351265796,
+           -1.9808017158282618,
+           -2.0507864247813052,
+           -2.1097284716362443,
+           -2.1564419208054106,
+           -2.189981488146625,
+           -2.2096615789854694,
+           -2.2150693613118286,
+           -2.2060715947934906,
+           -2.1828150856313453,
+           -2.1457207894511083,
+           -2.095471735674427,
+           -2.0329950934536773,
+           -1.9594388377233873,
+           -1.8761436008559471,
+           -1.784610407737375,
+           -1.6864650870906146,
+           -1.5834202272897755,
+           -1.4772355989346722,
+           -1.3696779978260094,
+           -1.2624814699929456,
+           -1.1573088649475114,
+           -1.0557156248252602,
+           -0.9591166565356549,
+           -0.8687570530476716,
+           -0.7856873305359648,
+           -0.7107437328210174,
+           -0.644534026250452,
+           -0.5874290701005623,
+           -0.5395603031745063,
+           -0.5008231401326866,
+           -0.4708861248680073,
+           -0.449205546558376,
+           -0.4350450903952293,
+           -0.42749997269553786,
+           -0.4255249021621857,
+           -0.42796511810623505,
+           -0.43358968469786313,
+           -0.4411261695006274,
+           -0.4492958058702677,
+           -0.45684823291342536,
+           -0.462594923681821,
+           -0.4654404516301579,
+           -0.4644108060393281,
+           -0.4586780475164014,
+           -0.4475806927540195,
+           -0.4306393309495928,
+           -0.40756709975857175,
+           -0.37827478319243873,
+           -0.34287043405406603,
+           -0.3016535657767979,
+           -0.25510409929633365,
+           -0.20386638627596482,
+           -0.1487287571962092,
+           -0.09059915829689169,
+           -0.030477542207752107,
+           0.030574239222617133,
+           0.09146422700165002,
+           0.15110297559635746,
+           0.20843612422133956,
+           0.26247604204932046,
+           0.31233169419054696,
+           0.3572359208286477,
+           0.3965693882290112,
+           0.4298805557813067,
+           0.45690110564775777,
+           0.4775563983819309,
+           0.49197064611341795,
+           0.5004666313258225,
+           0.5035599404430962,
+           0.501947823813139,
+           0.49649293363450886,
+           0.4882023253646378,
+           0.4782022327740114,
+           0.467709238898057,
+           0.45799856182530896,
+           0.4503702530661401,
+           0.44611416513522406,
+           0.4464745824126221,
+           0.4526154243176601,
+           0.46558692189169976,
+           0.48629463816834245,
+           0.5154716499103488,
+           0.5536546346628556,
+           0.6011645143867147,
+           0.6580921974479329,
+           0.7242898371273415,
+           0.7993678901150174,
+           0.8826981159859542,
+           0.9734225119373003,
+           1.070468029737131,
+           1.1725667775476694,
+           1.278281271633054,
+           1.386034175376199,
+           1.4941418487039648,
+           1.6008509328249259,
+           1.7043771155972591,
+           1.8029451638882144,
+           1.8948292724781806,
+           1.9783927653748759,
+           2.0521261952398326,
+           2.1146829198158064,
+           2.1649112900280945,
+           2.201882661505479,
+           2.2249145377923583,
+           2.2335882671844316,
+           2.227760843174066,
+           2.207570497837507,
+           2.1734359247526114,
+           2.1260491196219933,
+           2.06636197900143,
+           1.9955669466860622,
+           1.91507213974855,
+           1.826471518475835,
+           1.7315107832840568,
+           1.632049784200456,
+           1.5300223121809335,
+           1.4273942043366648,
+           1.3261207355375868,
+           1.2281042858580795,
+           1.1351532665160102,
+           1.0489432564997105,
+           0.9709812487255498,
+           0.902573829629091,
+           0.8448000214008959,
+           0.7984894039521321,
+           0.7642060068789032,
+           0.7422383232887744,
+           0.7325956507413707,
+           0.7350108133175838,
+           0.7489491666590639,
+           0.7736236384204171,
+           0.808015413587192,
+           0.8508997410077495,
+           0.900876217493258,
+           0.9564028018575756,
+           1.0158327257997855,
+           1.0774534036197563,
+           1.139526399935705,
+           1.2003274948296587,
+           1.2581858896006337,
+           1.3115216233942661,
+           1.358880320665349,
+           1.398964460424664,
+           1.4306604487079928,
+           1.4530608833914034,
+           1.465481522650223,
+           1.4674726019549522,
+           1.458824286175615,
+           1.439566189593628,
+           1.4099610437599177,
+           1.3704927375376068,
+           1.3218490917520196,
+           1.2648998592293772,
+           1.2006705564775837,
+           1.1303128330148553,
+           1.0550721659489741,
+           0.9762537288739571,
+           0.8951873240104927,
+           0.8131922838421004,
+           0.7315432429260625,
+           0.6514376522950059,
+           0.5739658586867665,
+           0.5000845000690545,
+           0.4305938793969041,
+           0.3661198725573428,
+           0.30710080672801676,
+           0.25377961495650025,
+           0.20620143497030544,
+           0.1642166785505637,
+           0.12748945583443466,
+           0.09551110024549762,
+           0.06761840789336368,
+           0.0430160835653226,
+           0.020802776927534305,
+           1.9040217631105167e-16
+          ],
+          [
+           0,
+           -0.020832544703979678,
+           -0.04281471799674584,
+           -0.06695303249886644,
+           -0.0941854897873894,
+           -0.12535158325253723,
+           -0.16116496506734865,
+           -0.20218952053413025,
+           -0.24881950536362193,
+           -0.30126429678322786,
+           -0.3595381903999203,
+           -0.4234555444641619,
+           -0.4926314348833479,
+           -0.5664878415117148,
+           -0.6442652425107296,
+           -0.7250393525691059,
+           -0.8077426060700778,
+           -0.8911898613171391,
+           -0.9741076898601821,
+           -1.0551665186647676,
+           -1.1330148148095145,
+           -1.20631444459822,
+           -1.2737763029476155,
+           -1.334195295628903,
+           -1.386483766803756,
+           -1.4297024971269403,
+           -1.463088452736573,
+           -1.4860785414107103,
+           -1.4983287272014005,
+           -1.499727966650344,
+           -1.4904065555061043,
+           -1.4707386116079915,
+           -1.4413385639033809,
+           -1.403051665854558,
+           -1.3569387000923454,
+           -1.3042551863940028,
+           -1.2464255432859224,
+           -1.1850127813456968,
+           -1.1216844204034724,
+           -1.0581754204500882,
+           -0.996248994683228,
+           -0.9376562307609808,
+           -0.8840954814975953,
+           -0.8371724979942956,
+           -0.7983622661897579,
+           -0.7689734722675337,
+           -0.7501164640791617,
+           -0.7426754961016336,
+           -0.7472859463443815,
+           -0.7643170774344861,
+           -0.7938607836438023,
+           -0.8357266240379602,
+           -0.8894432926621872,
+           -0.9542665233633936,
+           -1.0291932732165734,
+           -1.1129818783230008,
+           -1.2041777326442593,
+           -1.3011439080255947,
+           -1.4020960148834116,
+           -1.5051405010870955,
+           -1.6083155038492187,
+           -1.7096333079742552,
+           -1.8071234251098123,
+           -1.8988752936430606,
+           -1.9830796079569164,
+           -2.058067318683731,
+           -2.1223454015634204,
+           -2.1746285701591854,
+           -2.213866205107116,
+           -2.239263887394193,
+           -2.2502990525641864,
+           -2.24673042358096,
+           -2.2286010288929816,
+           -2.196234765409316,
+           -2.1502266198801223,
+           -2.091426812827071,
+           -2.020919273025533,
+           -1.9399949841068154,
+           -1.8501208648879977,
+           -1.7529049486491768,
+           -1.6500587112705776,
+           -1.5433574618918229,
+           -1.4345997510574913,
+           -1.3255667692162083,
+           -1.2179827025725534,
+           -1.1134769838644119,
+           -1.0135493234466921,
+           -0.9195383324576824,
+           -0.8325944567050522,
+           -0.753657829590467,
+           -0.6834415276704803,
+           -0.6224205764519086,
+           -0.5708269101395118,
+           -0.5286503408770796,
+           -0.4956454442326914,
+           -0.4713441219648517,
+           -0.4550734640728827,
+           -0.445978403213437,
+           -0.4430485389266331,
+           -0.44514840959433893,
+           -0.45105040907613814,
+           -0.4594694844949125,
+           -0.46909871311783724,
+           -0.47864484059348555,
+           -0.4868628702831948,
+           -0.4925888238071206,
+           -0.4947698453826661,
+           -0.49249089568489723,
+           -0.4849973729091005,
+           -0.47171310710143627,
+           -0.45225329587326674,
+           -0.42643208221846546,
+           -0.3942646149410527,
+           -0.35596357562722,
+           -0.3119302995290997,
+           -0.26274075753906717,
+           -0.2091267990901774,
+           -0.15195317797045207,
+           -0.09219099160389937,
+           -0.030888256590983994,
+           0.03086158310972871,
+           0.09195236589336019,
+           0.15129825940780578,
+           0.2078662553227375,
+           0.2607072368859622,
+           0.3089847809062008,
+           0.35200091408373785,
+           0.38921812198406464,
+           0.4202770054381995,
+           0.4450090913229457,
+           0.4634444296946501,
+           0.4758137439647334,
+           0.48254504181142543,
+           0.4842547382549705,
+           0.48173348514565656,
+           0.4759270396068392,
+           0.4679126342290027,
+           0.4588714307136592,
+           0.4500577431852433,
+           0.44276580484995476,
+           0.43829491983055197,
+           0.4379138890744448,
+           0.44282562397319625,
+           0.45413286305624306,
+           0.4728058857167399,
+           0.49965307285829114,
+           0.5352950986511779,
+           0.5801434518315488,
+           0.634383881247544,
+           0.6979652411862204,
+           0.7705940803290756,
+           0.8517351772251616,
+           0.9406180784208422,
+           1.0362495464778685,
+           1.1374316777422995,
+           1.2427853075617068,
+           1.350778187232739,
+           1.4597572956305953,
+           1.5679845422711913,
+           1.6736750301611154,
+           1.7750369784410962,
+           1.8703123582753427,
+           1.9578172718966906,
+           2.035981104835177,
+           2.1033835052007337,
+           2.158788290941142,
+           2.2011734551615407,
+           2.2297565292327257,
+           2.2440146713868043,
+           2.2436989721995815,
+           2.22884260479835,
+           2.199762593502635,
+           2.1570551263588627,
+           2.1015844909737633,
+           2.034465865433543,
+           1.9570423431981647,
+           1.870856709090762,
+           1.7776186094830757,
+           1.679167870428967,
+           1.5774348101129683,
+           1.4743984642931152,
+           1.3720436936570357,
+           1.2723181689472756,
+           1.1770902326866033,
+           1.088108615272596,
+           1.0069649386288038,
+           0.9350598735876411,
+           0.8735737293772563,
+           0.8234421471387467,
+           0.7853374469143367,
+           0.7596560420158283,
+           0.746512189417014,
+           0.7457381933614133,
+           0.7568910254330006,
+           0.7792651716552463,
+           0.8119113694805286,
+           0.8536607583985623,
+           0.903153840704984,
+           0.958873536807509,
+           1.0191815250118124,
+           1.0823569812870772,
+           1.1466367818317784,
+           1.2102562015754499,
+           1.2714891357250413,
+           1.3286868891757215,
+           1.380314619550495,
+           1.4249845827345045,
+           1.4614854134085067,
+           1.488806775137309,
+           1.5061588324597446,
+           1.5129861281972825,
+           1.5089755895771901,
+           1.4940585332516096,
+           1.4684066882408406,
+           1.4324224035399058,
+           1.3867233499433638,
+           1.3321221600358266,
+           1.2696015729531402,
+           1.2002857584295643,
+           1.1254085851711608,
+           1.0462796695349645,
+           0.9642490901405146,
+           0.880671681222658,
+           0.7968718216426763,
+           0.7141096174769345,
+           0.6335493345440324,
+           0.5562308742214094,
+           0.4830450030839201,
+           0.4147129464065269,
+           0.35177083998654696,
+           0.2945594070075331,
+           0.2432190900369424,
+           0.19769072619185704,
+           0.15772170962130688,
+           0.12287744338178776,
+           0.09255774611647774,
+           0.06601775114034256,
+           0.04239271980930091,
+           0.02072609033126682,
+           1.9196017496292266e-16
+          ],
+          [
+           0,
+           -0.021422836501935733,
+           -0.04449234184807285,
+           -0.07019238696580545,
+           -0.09942106417747588,
+           -0.1329617997118059,
+           -0.1714575906241621,
+           -0.21538906837061553,
+           -0.2650569925321341,
+           -0.3205696638071727,
+           -0.3818356182717323,
+           -0.44856182825688956,
+           -0.5202574924687083,
+           -0.5962433527843625,
+           -0.6756663311770574,
+           -0.7575191411005248,
+           -0.8406643969333518,
+           -0.9238626260699213,
+           -1.0058034839841348,
+           -1.0851393857544775,
+           -1.1605207003611135,
+           -1.230631608294847,
+           -1.294225699867337,
+           -1.350160391730468,
+           -1.3974292625670626,
+           -1.4351914551878326,
+           -1.4627973602711812,
+           -1.4798098850781225,
+           -1.4860207165234665,
+           -1.4814611093928023,
+           -1.466406864279936,
+           -1.4413773026831613,
+           -1.4071281951093284,
+           -1.3646387483139577,
+           -1.3150929062209928,
+           -1.259855361921589,
+           -1.2004428118824977,
+           -1.1384911047536026,
+           -1.0757190429057535,
+           -1.013889682386496,
+           -0.9547700441294285,
+           -0.9000901942698013,
+           -0.8515026731250712,
+           -0.8105432501888888,
+           -0.7785939563436968,
+           -0.7568492949950474,
+           -0.7462864621210097,
+           -0.7476403130133153,
+           -0.7613837029717873,
+           -0.7877137030629716,
+           -0.8265440533193505,
+           -0.8775040678027953,
+           -0.9399440523820161,
+           -1.0129471406185275,
+           -1.0953472996097655,
+           -1.1857531097495564,
+           -1.282576783748376,
+           -1.384067764297969,
+           -1.48835012954868,
+           -1.5934629437912724,
+           -1.6974026196464838,
+           -1.7981663094068452,
+           -1.893795318141096,
+           -1.9824175303766933,
+           -2.062287865643511,
+           -2.1318258253200164,
+           -2.189649262920718,
+           -2.2346036004979255,
+           -2.265785822989074,
+           -2.282562707456471,
+           -2.2845828821821317,
+           -2.2717824581267303,
+           -2.2443841287369484,
+           -2.2028897897467297,
+           -2.148066884671962,
+           -2.0809288303952282,
+           -2.0027100169636958,
+           -1.914836003089792,
+           -1.8188896407695065,
+           -1.7165739562194826,
+           -1.6096726877329035,
+           -1.500009432322188,
+           -1.3894063809568207,
+           -1.279643626196148,
+           -1.1724200060297076,
+           -1.0693164043309702,
+           -0.9717623626405805,
+           -0.8810067717047263,
+           -0.7980933064907816,
+           -0.7238411479229689,
+           -0.6588314013466982,
+           -0.6033994790712293,
+           -0.5576335658117799,
+           -0.5213791351469071,
+           -0.49424933596295284,
+           -0.47564092396577834,
+           -0.46475527825267016,
+           -0.4606239199799545,
+           -0.46213784235062905,
+           -0.4680798711142727,
+           -0.47715920470308193,
+           -0.48804723470565803,
+           -0.4994137217433137,
+           -0.509962399530786,
+           -0.5184651009586131,
+           -0.5237935438294603,
+           -0.5249479792494477,
+           -0.5210819909148088,
+           -0.5115228364462807,
+           -0.49578683987215827,
+           -0.47358947433710497,
+           -0.4448499128118342,
+           -0.4096899684791122,
+           -0.36842749192880214,
+           -0.3215644356293708,
+           -0.2697699337332121,
+           -0.2138588736451153,
+           -0.1547665516985518,
+           -0.09352010582136945,
+           -0.03120750069799139,
+           0.031055096430969015,
+           0.0921566701242772,
+           0.15102454357636497,
+           0.20665650485428463,
+           0.25815100699242727,
+           0.3047346261849367,
+           0.3457860330864988,
+           0.38085582220397984,
+           0.40968165126276057,
+           0.43219826356334795,
+           0.44854209864666467,
+           0.45905033671717926,
+           0.4642543666888155,
+           0.464867812764946,
+           0.4617693964664166,
+           0.4559810463785766,
+           0.4486417931599889,
+           0.44097809935116045,
+           0.4342713693790286,
+           0.4298234624112728,
+           0.4289210873750535,
+           0.43279999403270203,
+           0.44260988556810893,
+           0.45938096632328057,
+           0.4839930033604952,
+           0.5171477232176063,
+           0.5593452869387061,
+           0.6108654890932026,
+           0.6717542124180305,
+           0.7418155417270313,
+           0.8206098019787084,
+           0.9074576393041556,
+           1.0014501139871737,
+           1.1014646245753668,
+           1.2061863362100544,
+           1.3141346475356341,
+           1.4236941026534058,
+           1.5331490407260762,
+           1.6407211788837284,
+           1.7446092464825131,
+           1.8430297325031628,
+           1.9342577744033889,
+           2.016667206951728,
+           2.088768803783054,
+           2.1492457823472995,
+           2.1969857037086995,
+           2.2311079808622045,
+           2.2509863109060526,
+           2.2562654651019254,
+           2.2468720037002434,
+           2.2230186261896936,
+           2.1852020188547097,
+           2.1341942165128054,
+           2.071027650278161,
+           1.9969742043781116,
+           1.9135187487424639,
+           1.8223277467806236,
+           1.7252136562120526,
+           1.624095942123261,
+           1.5209596031084587,
+           1.4178121714096599,
+           1.316640184932815,
+           1.2193661419718322,
+           1.1278069381023372,
+           1.0436347492865368,
+           0.9683412666242366,
+           0.903206107824145,
+           0.8492701303176586,
+           0.8073142534417119,
+           0.7778442651487559,
+           0.7610819454838624,
+           0.7569626880976403,
+           0.7651396460229186,
+           0.7849942726126478,
+           0.8156529766992161,
+           0.8560094663846005,
+           0.9047522219186378,
+           0.9603964181146605,
+           1.0213195135860629,
+           1.0857996402448538,
+           1.1520558639858154,
+           1.2182893477622379,
+           1.2827244322531721,
+           1.3436486573537127,
+           1.3994507795240905,
+           1.4486558947591588,
+           1.489956853173499,
+           1.5222412469980777,
+           1.5446133667315654,
+           1.5564106474455968,
+           1.5572142656227093,
+           1.5468536929550836,
+           1.5254051636163102,
+           1.4931841619099941,
+           1.4507321841722096,
+           1.3987981687265192,
+           1.3383151171113519,
+           1.2703725455389945,
+           1.1961855047699705,
+           1.117060986880112,
+           1.0343625968204926,
+           0.9494744038075088,
+           0.8637649015754146,
+           0.778551997099096,
+           0.6950699148591936,
+           0.6144388489599498,
+           0.5376381198614769,
+           0.4654834981092054,
+           0.3986092466587042,
+           0.33745530903552184,
+           0.2822599358042111,
+           0.23305790007180974,
+           0.18968430761250357,
+           0.15178386234591854,
+           0.11882530699371534,
+           0.09012062533697399,
+           0.06484846996642614,
+           0.0420811708490542,
+           0.020814588163810818,
+           1.9511555178739186e-16
+          ],
+          [
+           0,
+           -0.02218963880608415,
+           -0.046518226964157354,
+           -0.07393750000883288,
+           -0.1052965595567347,
+           -0.1413143762933223,
+           -0.18255585920376796,
+           -0.22941214516344952,
+           -0.282085653869676,
+           -0.3405803298216375,
+           -0.40469735875583884,
+           -0.4740365040148381,
+           -0.5480030623582842,
+           -0.6258202924123404,
+           -0.7065470260043988,
+           -0.7891000366719115,
+           -0.8722806141232039,
+           -0.9548046815623611,
+           -1.0353356974292336,
+           -1.112519506698795,
+           -1.1850202514088473,
+           -1.251556416996917,
+           -1.310936081222562,
+           -1.3620904462447345,
+           -1.4041047715390396,
+           -1.4362458849160809,
+           -1.457985529514986,
+           -1.4690189043421453,
+           -1.469277872269478,
+           -1.4589384395434857,
+           -1.4384222515796714,
+           -1.4083919976491237,
+           -1.3697407683428036,
+           -1.3235755606673765,
+           -1.2711952725271574,
+           -1.2140636675141672,
+           -1.1537779188816355,
+           -1.0920334551040536,
+           -1.0305859256688459,
+           -0.9712111822623366,
+           -0.9156642253505088,
+           -0.8656380978900754,
+           -0.8227237156825096,
+           -0.7883716074385922,
+           -0.7638564972863647,
+           -0.7502455991545125,
+           -0.7483714076871968,
+           -0.7588096661185177,
+           -0.781863070360885,
+           -0.8175511333688176,
+           -0.8656064879047439,
+           -0.9254777527020783,
+           -0.9963389304208183,
+           -1.0771051495400121,
+           -1.1664544102436618,
+           -1.2628548501480867,
+           -1.3645969129161946,
+           -1.4698296846577883,
+           -1.5766005624187323,
+           -1.68289733848107,
+           -1.7866917256082784,
+           -1.8859833132131938,
+           -1.978842933567632,
+           -2.063454430882647,
+           -2.138153864037243,
+           -2.2014652349972845,
+           -2.2521319180512855,
+           -2.2891430678679576,
+           -2.3117544045395637,
+           -2.31950290828223,
+           -2.312215102035225,
+           -2.2900087532843374,
+           -2.2532879832959747,
+           -2.2027319287660316,
+           -2.1392772538429536,
+           -2.0640949558587054,
+           -1.9785620423655823,
+           -1.8842287769793935,
+           -1.7827822941750264,
+           -1.6760074661021254,
+           -1.5657459657068333,
+           -1.453854508518197,
+           -1.3421632695133079,
+           -1.232435461234368,
+           -1.1263290251133793,
+           -1.0253613306744018,
+           -0.9308776984053014,
+           -0.8440244636249913,
+           -0.7657271831022884,
+           -0.6966744564090674,
+           -0.6373076932585973,
+           -0.5878170098985145,
+           -0.5481432856820445,
+           -0.517986259000857,
+           -0.49681839358954305,
+           -0.48390410546461715,
+           -0.47832381090656023,
+           -0.47900214012022163,
+           -0.4847395623477986,
+           -0.49424658866375815,
+           -0.5061796603704257,
+           -0.5191777952214044,
+           -0.5318990514455146,
+           -0.5430558809583442,
+           -0.551448477872105,
+           -0.555995285506189,
+           -0.5557599030621101,
+           -0.549973729939894,
+           -0.5380537988524294,
+           -0.5196153755485436,
+           -0.4944790398602801,
+           -0.46267210646879336,
+           -0.42442439059546755,
+           -0.38015847005564934,
+           -0.3304747370667953,
+           -0.2761316672973287,
+           -0.21802185649570902,
+           -0.1571444835550738,
+           -0.09457495031533257,
+           -0.03143252048103656,
+           0.03115316907176413,
+           0.09207582289010827,
+           0.15028552046388194,
+           0.20482017972420133,
+           0.2548346024401454,
+           0.2996263161008552,
+           0.338657509753251,
+           0.37157246226998386,
+           0.39820997809544256,
+           0.4186104747137443,
+           0.4330175046360515,
+           0.44187363911129474,
+           0.445810787370304,
+           0.4456351703052196,
+           0.44230730738463786,
+           0.4369175067575587,
+           0.43065746756818574,
+           0.4247887074507371,
+           0.42060861433550745,
+           0.419414987854425,
+           0.4224699800639997,
+           0.43096436672633914,
+           0.4459830783972541,
+           0.4684728950451859,
+           0.49921315943577793,
+           0.5387902942105751,
+           0.5875768171588153,
+           0.6457154408293547,
+           0.7131087190089893,
+           0.7894145667440756,
+           0.8740478358567004,
+           0.9661879778857944,
+           1.0647926747886995,
+           1.1686171683386521,
+           1.2762388756713254,
+           1.3860867444533327,
+           1.4964746800246589,
+           1.6056382716496216,
+           1.7117739583559797,
+           1.8130797089525117,
+           1.9077962473865127,
+           1.9942478347768502,
+           2.070881623797005,
+           2.1363046295521366,
+           2.1893174130639133,
+           2.228943647736738,
+           2.2544548339659736,
+           2.2653895400913036,
+           2.26156667647205,
+           2.2430924504540775,
+           2.2103607999884716,
+           2.16404725900228,
+           2.1050963645270504,
+           2.0347028702336036,
+           1.9542871796253551,
+           1.8654655510740465,
+           1.7700157527429397,
+           1.6698389551509367,
+           1.5669187399992763,
+           1.4632781736820821,
+           1.3609359409197554,
+           1.261862557033866,
+           1.167937675953529,
+           1.0809094851359795,
+           1.002357128826446,
+           0.933657028687599,
+           0.8759538775630238,
+           0.830136970279239,
+           0.7968224076679704,
+           0.7763415695229431,
+           0.7687361024217527,
+           0.7737595128972874,
+           0.7908852991246863,
+           0.8193213989309064,
+           0.8580305823146939,
+           0.9057562764205027,
+           0.961053183441158,
+           1.0223219403140795,
+           1.087846976013724,
+           1.1558366499588364,
+           1.2244647052629791,
+           1.2919120444211798,
+           1.3564078331215432,
+           1.4162689601774416,
+           1.4699369274780487,
+           1.516011312156,
+           1.5532790321252488,
+           1.5807387534989992,
+           1.597619901455557,
+           1.6033958717973267,
+           1.5977911853570568,
+           1.5807824779377435,
+           1.5525933708890904,
+           1.513683417946672,
+           1.464731468868203,
+           1.406613926120331,
+           1.340378494061668,
+           1.2672141277140736,
+           1.1884179776889654,
+           1.105360196971066,
+           1.0194475224017705,
+           0.9320865677436045,
+           0.8446477656196911,
+           0.7584308724717536,
+           0.6746329046196828,
+           0.5943193057587199,
+           0.5183990585605164,
+           0.44760434771051877,
+           0.382475261413487,
+           0.3233498861990398,
+           0.2703600091205677,
+           0.22343249573361496,
+           0.1822962652532777,
+           0.14649463974073282,
+           0.11540270570730483,
+           0.08824919764410952,
+           0.06414229693489532,
+           0.04209863931260488,
+           0.02107474200061104,
+           1.999076828119418e-16
+          ],
+          [
+           0,
+           -0.023133074688004362,
+           -0.04888787902788743,
+           -0.07817464007496097,
+           -0.11178467484690131,
+           -0.15036455680567615,
+           -0.19439426743686036,
+           -0.24416993212157856,
+           -0.29979162074284377,
+           -0.3611565622184292,
+           -0.4279579817261844,
+           -0.4996896233378557,
+           -0.5756558728014656,
+           -0.6549872490595273,
+           -0.7366608924681485,
+           -0.8195255461628258,
+           -0.9023304079482677,
+           -0.9837571265112812,
+           -1.062454130321813,
+           -1.1370724125003482,
+           -1.2063018518851563,
+           -1.2689071306752384,
+           -1.3237623129195932,
+           -1.369883175741419,
+           -1.4064564359035305,
+           -1.4328650869354194,
+           -1.448709154799311,
+           -1.4538212907113557,
+           -1.4482767455419108,
+           -1.4323974080982997,
+           -1.4067497361387997,
+           -1.3721365605485805,
+           -1.329582895963761,
+           -1.2803160414550676,
+           -1.2257403989288629,
+           -1.167407571068289,
+           -1.1069824215568658,
+           -1.046205884957261,
+           -0.9868553993129212,
+           -0.9307038991167594,
+           -0.879478348084343,
+           -0.8348188090744041,
+           -0.7982390420006273,
+           -0.7710895897614646,
+           -0.7545242577653258,
+           -0.7494708158179554,
+           -0.7566066537917747,
+           -0.7763400069476555,
+           -0.8087972358145632,
+           -0.8538165023225216,
+           -0.910948031906368,
+           -0.9794609942497278,
+           -1.0583568770481633,
+           -1.1463890715009484,
+           -1.2420882389960977,
+           -1.3437928892835653,
+           -1.449684474743971,
+           -1.5578261962344098,
+           -1.666204626105112,
+           -1.77277318553741,
+           -1.875496468037714,
+           -1.9723943798502674,
+           -2.06158507174807,
+           -2.1413256650430355,
+           -2.210049827037046,
+           -2.2664013262403593,
+           -2.3092627936824766,
+           -2.33777903119172,
+           -2.351374337828123,
+           -2.349763468541,
+           -2.3329559911014437,
+           -2.301253964725598,
+           -2.255243022721466,
+           -2.195777098090738,
+           -2.123957181488431,
+           -2.0411046416323892,
+           -1.9487297657509,
+           -1.848496288877583,
+           -1.7421827730684354,
+           -1.6316417687171507,
+           -1.518757738393879,
+           -1.4054047479073288,
+           -1.2934049290586198,
+           -1.1844886938895467,
+           -1.0802576318014596,
+           -0.982150949990108,
+           -0.8914162260157401,
+           -0.8090851313213733,
+           -0.7359546588894564,
+           -0.6725742501312362,
+           -0.6192390689786753,
+           -0.5759895186558022,
+           -0.5426169425295734,
+           -0.5186752985950603,
+           -0.5034984512872367,
+           -0.4962225880264674,
+           -0.4958131445452723,
+           -0.5010955156302349,
+           -0.5107887390616859,
+           -0.5235412723943831,
+           -0.5379679364237584,
+           -0.5526870767934636,
+           -0.566356996703901,
+           -0.5777107389644903,
+           -0.5855883439872489,
+           -0.588965780463811,
+           -0.5869798355779352,
+           -0.5789483593607473,
+           -0.5643853804385986,
+           -0.5430107448278868,
+           -0.5147540721821837,
+           -0.47975297137534634,
+           -0.43834560577762505,
+           -0.3910578442979374,
+           -0.33858537354660156,
+           -0.28177127580680356,
+           -0.22157969363228608,
+           -0.15906630189020773,
+           -0.09534638942778706,
+           -0.03156141321585436,
+           0.031155073709376827,
+           0.09171120388411375,
+           0.14908937825597102,
+           0.20237677341795254,
+           0.2507929505281066,
+           0.2937138184555375,
+           0.33069129819182647,
+           0.3614681469234313,
+           0.3859875255593115,
+           0.40439702977759706,
+           0.4170470483486057,
+           0.424483459972175,
+           0.427434827400091,
+           0.4267943914592409,
+           0.4235973040965659,
+           0.4189936652620818,
+           0.4142180401273836,
+           0.4105562279484732,
+           0.40931012938711064,
+           0.41176161334944356,
+           0.4191363159595028,
+           0.43256831230061266,
+           0.4530665857607529,
+           0.48148418053576475,
+           0.5184908609930958,
+           0.5645500186615522,
+           0.6199004656028138,
+           0.6845436343327108,
+           0.7582365722087738,
+           0.8404909755468926,
+           0.9305783592025033,
+           1.0275413046583948,
+           1.1302105775970699,
+           1.2372277582887594,
+           1.347072888583649,
+           1.4580965113525761,
+           1.5685553650890698,
+           1.6766509009199118,
+           1.7805697138947678,
+           1.8785249270672086,
+           1.9687975369289707,
+           2.0497767230295407,
+           2.119998143320241,
+           2.178179279518998,
+           2.223250962616722,
+           2.2543842959869136,
+           2.271012300330476,
+           2.2728457283195507,
+           2.2598826343098226,
+           2.2324114325359203,
+           2.191007332190762,
+           2.136522195942548,
+           2.0700680259053064,
+           1.9929944340046548,
+           1.9068605983318012,
+           1.8134023399151817,
+           1.71449507210822,
+           1.6121134746056505,
+           1.508288823511333,
+           1.4050649659366488,
+           1.304453960906122,
+           1.2083924170629758,
+           1.1186995415806116,
+           1.037037874182568,
+           0.9648776162364767,
+           0.903465379074616,
+           0.853798070097059,
+           0.8166025124092111,
+           0.7923212567302012,
+           0.7811048964249501,
+           0.7828110413677555,
+           0.797009947720858,
+           0.8229966424722476,
+           0.859809227574002,
+           0.9062529024991998,
+           0.9609291095357777,
+           1.0222690864159663,
+           1.0885710088303997,
+           1.1580398234484561,
+           1.2288288122155848,
+           1.2990818923332161,
+           1.3669756442770395,
+           1.4307600727056586,
+           1.4887971417793435,
+           1.5395961862805982,
+           1.5818453814662419,
+           1.614438555716359,
+           1.6364967482317032,
+           1.647384046304558,
+           1.646717379745004,
+           1.6343701003212951,
+           1.6104693278356783,
+           1.5753871978937062,
+           1.529726295740748,
+           1.4742997020497566,
+           1.4101062067670278,
+           1.3383013628637774,
+           1.2601651502735305,
+           1.1770670990282806,
+           1.0904297777453262,
+           1.0016915878082293,
+           0.9122698140513483,
+           0.8235248693127432,
+           0.7367266332767225,
+           0.6530237265828609,
+           0.573416480791172,
+           0.4987342655420174,
+           0.42961771868124954,
+           0.36650629618704067,
+           0.3096314197157182,
+           0.25901535400783077,
+           0.2144757979500647,
+           0.1756360255275421,
+           0.1419402699511175,
+           0.11267390951174347,
+           0.08698789059449999,
+           0.06392671487821777,
+           0.04245922678000121,
+           0.021511365963175853,
+           2.0635977570917994e-16
+          ],
+          [
+           0,
+           -0.024251456895742988,
+           -0.05159319827170661,
+           -0.08288478477801614,
+           -0.1188513340978279,
+           -0.1600596133193921,
+           -0.20689850790758005,
+           -0.259564405150737,
+           -0.3180519024562773,
+           -0.3821501126574749,
+           -0.4514446930723956,
+           -0.5253255761058269,
+           -0.603000230480187,
+           -0.6835121374928531,
+           -0.7657640296989804,
+           -0.8485453135952895,
+           -0.9305629864391816,
+           -1.010475263129446,
+           -1.086927054521022,
+           -1.158586385578218,
+           -1.2241808117808424,
+           -1.2825328860039589,
+           -1.3325937459171064,
+           -1.373473933413689,
+           -1.4044706217136935,
+           -1.4250905110412941,
+           -1.4350677580896916,
+           -1.4343764252945208,
+           -1.4232370702721335,
+           -1.4021172403237914,
+           -1.3717257880826457,
+           -1.3330010784354571,
+           -1.28709330995311,
+           -1.2353413223956675,
+           -1.1792444017119759,
+           -1.1204297218250054,
+           -1.0606161751672287,
+           -1.0015754385593456,
+           -0.9450911952062934,
+           -0.8929174854134783,
+           -0.8467371867498074,
+           -0.8081216280322676,
+           -0.7784923205129158,
+           -0.7590857444554239,
+           -0.7509220609351438,
+           -0.7547785287982034,
+           -0.771168297419818,
+           -0.800325119840256,
+           -0.8421943910766552,
+           -0.8964307663010014,
+           -0.9624024567892268,
+           -1.0392021419036286,
+           -1.125664276766167,
+           -1.2203884215890741,
+           -1.321768073611015,
+           -1.4280243497927194,
+           -1.537243751110277,
+           -1.6474191403253613,
+           -1.7564929869401813,
+           -1.8624018775837423,
+           -1.9631212586931703,
+           -2.056709371827368,
+           -2.141349360451393,
+           -2.215388570115295,
+           -2.2773741305770523,
+           -2.326083996964818,
+           -2.360552735381897,
+           -2.3800914637887,
+           -2.38430149849031,
+           -2.3730814067152983,
+           -2.3466273229297507,
+           -2.3054265468608017,
+           -2.25024460080153,
+           -2.1821060787508455,
+           -2.1022697665416876,
+           -2.012198646771771,
+           -1.9135255218131988,
+           -1.8080150895580058,
+           -1.697523387420082,
+           -1.5839555785324901,
+           -1.4692230886780868,
+           -1.3552011124844765,
+           -1.243687492620887,
+           -1.136363936583716,
+           -1.0347604731776507,
+           -0.9402239665900315,
+           -0.8538914021504581,
+           -0.7766685370762387,
+           -0.709214374752053,
+           -0.6519317757417149,
+           -0.6049643663984663,
+           -0.5681997504095411,
+           -0.5412788737332209,
+           -0.5236112429897873,
+           -0.5143955551593529,
+           -0.512645165915975,
+           -0.5172177082868693,
+           -0.5268480753895876,
+           -0.5401839031437292,
+           -0.5558226329475046,
+           -0.5723492016731822,
+           -0.5883733977065824,
+           -0.6025659372716403,
+           -0.6136923544766638,
+           -0.6206438603388968,
+           -0.6224644088701343,
+           -0.6183733099981658,
+           -0.607782847048851,
+           -0.5903104877112443,
+           -0.5657854185167601,
+           -0.534249280303304,
+           -0.49595113217390724,
+           -0.4513368203044503,
+           -0.40103307184947823,
+           -0.3458267695112889,
+           -0.28663998566732274,
+           -0.2245014631919612,
+           -0.16051532054060297,
+           -0.09582782901684361,
+           -0.031593158654927754,
+           0.031060985392293315,
+           0.09106691229518368,
+           0.14744877909717388,
+           0.19935185174716483,
+           0.24606840409150546,
+           0.287059552709456,
+           0.32197243097362516,
+           0.35065222663503903,
+           0.3731487405115594,
+           0.38971726612555235,
+           0.400813737790848,
+           0.4070842439504073,
+           0.40934914973051234,
+           0.40858221397047545,
+           0.40588521781825043,
+           0.4024587409953654,
+           0.39956982499048493,
+           0.3985173470955031,
+           0.4005959931679073,
+           0.4070597586213748,
+           0.41908592530403765,
+           0.4377404560986918,
+           0.4639457193497369,
+           0.49845140226552787,
+           0.5418093975227567,
+           0.5943533522247062,
+           0.6561834554587753,
+           0.7271569127322066,
+           0.8068844156926407,
+           0.8947327672200084,
+           0.9898336688850273,
+           1.0910985237111566,
+           1.1972389559879617,
+           1.3067926053385288,
+           1.4181536179593606,
+           1.5296071372988171,
+           1.6393669924603231,
+           1.7456156979414779,
+           1.846545815111616,
+           1.940401685721228,
+           2.0255205317925675,
+           2.100371924931463,
+           2.163594661287822,
+           2.2140301353332736,
+           2.250751384986861,
+           2.273087080517424,
+           2.2806398476870813,
+           2.2732984489260737,
+           2.2512434917161785,
+           2.21494648727622,
+           2.16516224134245,
+           2.102914718448844,
+           2.0294766777405013,
+           1.9463435281675021,
+           1.855201990241167,
+           1.7578942769752093,
+           1.656378615105944,
+           1.5526870165248505,
+           1.4488812768804853,
+           1.3470082218643908,
+           1.2490552407105724,
+           1.1569071404344233,
+           1.0723053234511444,
+           0.9968102361915869,
+           0.9317679585111398,
+           0.8782817049599438,
+           0.837188891756151,
+           0.8090442904364306,
+           0.7941096438894841,
+           0.7923499663511168,
+           0.8034365897101877,
+           0.8267568580225266,
+           0.8614302143606787,
+           0.9063302728775202,
+           0.9601123279041615,
+           1.0212456244561237,
+           1.0880496037670448,
+           1.1587332460739221,
+           1.2314365630301647,
+           1.3042732454791441,
+           1.37537344996477,
+           1.4429257097720898,
+           1.5052169833553597,
+           1.5606699039918417,
+           1.6078763680793418,
+           1.6456266938013964,
+           1.6729336945369482,
+           1.6890511395650325,
+           1.6934862151050853,
+           1.686005748039711,
+           1.6666361090777386,
+           1.6356568678022878,
+           1.5935884251594288,
+           1.5411739956985204,
+           1.4793564486622008,
+           1.4092506404845353,
+           1.3321119783709299,
+           1.2493020427965493,
+           1.1622521638419845,
+           1.072425890685862,
+           0.9812813142619553,
+           0.890234199624644,
+           0.8006228571158016,
+           0.7136756307508397,
+           0.6304818096828938,
+           0.551966676047221,
+           0.47887129231440223,
+           0.41173750630882505,
+           0.35089851546178624,
+           0.29647518713544996,
+           0.2483781826423102,
+           0.20631578266914488,
+           0.16980716498122053,
+           0.13820074523562506,
+           0.11069706200088263,
+           0.0863755709291173,
+           0.06422461337735835,
+           0.04317374412913415,
+           0.02212754324871162,
+           2.144783963361557e-16
+          ],
+          [
+           0,
+           -0.02554127922068466,
+           -0.05462251061437802,
+           -0.0880437393259272,
+           -0.1264559371300837,
+           -0.17033926970952776,
+           -0.21998610051228992,
+           -0.27548920180720476,
+           -0.3367355082730256,
+           -0.4034056043818565,
+           -0.47497898761925983,
+           -0.5507449990024363,
+           -0.6298191642322765,
+           -0.7111645469045536,
+           -0.7936175831172014,
+           -0.8759177479085516,
+           -0.9567403012821295,
+           -1.0347312777498643,
+           -1.1085438205198153,
+           -1.1768749213047036,
+           -1.2385016103051047,
+           -1.2923156487040783,
+           -1.337355807869741,
+           -1.3728368746665631,
+           -1.3981745995062973,
+           -1.4130059011526777,
+           -1.4172037574493137,
+           -1.410886341237269,
+           -1.3944201025576328,
+           -1.3684166482851987,
+           -1.3337234248891603,
+           -1.2914083652221247,
+           -1.24273881223119,
+           -1.189155177466712,
+           -1.1322399266044056,
+           -1.0736826045184025,
+           -1.015241715712431,
+           -0.9587043595141344,
+           -0.9058445812272665,
+           -0.8583814388168822,
+           -0.817937798648881,
+           -0.7860008628949458,
+           -0.7638853956382524,
+           -0.7527005552757643,
+           -0.7533211589013316,
+           -0.766364101919798,
+           -0.792170535644921,
+           -0.8307942699820802,
+           -0.8819967207776153,
+           -0.9452485656151197,
+           -1.0197381115493351,
+           -1.104386217401028,
+           -1.1978674557213511,
+           -1.2986370492249868,
+           -1.4049629770686092,
+           -1.514962521232981,
+           -1.626642415523808,
+           -1.7379416719858647,
+           -1.8467760939855862,
+           -1.9510834434760436,
+           -2.0488682130500306,
+           -2.1382449617383084,
+           -2.2174792069303675,
+           -2.2850249224784154,
+           -2.33955777359287,
+           -2.3800033205903612,
+           -2.405559543442392,
+           -2.415713174473463,
+           -2.4102494741711555,
+           -2.389255241300211,
+           -2.35311500955106,
+           -2.302500544879025,
+           -2.2383539165627306,
+           -2.161864566966962,
+           -2.0744409463470257,
+           -1.9776774063536058,
+           -1.8733171561115625,
+           -1.7632121751999685,
+           -1.6492810463878598,
+           -1.5334657159576208,
+           -1.4176882098316568,
+           -1.3038083290713856,
+           -1.1935833188190568,
+           -1.0886304511918536,
+           -0.9903933863948606,
+           -0.900113079330039,
+           -0.818803883686131,
+           -0.7472353747883542,
+           -0.6859202696306896,
+           -0.6351086710637329,
+           -0.5947887068285805,
+           -0.5646934768840797,
+           -0.5443140681581826,
+           -0.5329182482700182,
+           -0.5295743125480481,
+           -0.5331794351765969,
+           -0.5424917685549344,
+           -0.5561654475442231,
+           -0.5727875893157037,
+           -0.5909163365680962,
+           -0.6091189729465799,
+           -0.6260091449630436,
+           -0.6402822543713549,
+           -0.6507481379735098,
+           -0.6563602268220523,
+           -0.6562404717947677,
+           -0.6496994351062512,
+           -0.6362510746095605,
+           -0.6156218864888547,
+           -0.5877542186286544,
+           -0.5528037178520405,
+           -0.5111310255335327,
+           -0.46328798399302956,
+           -0.4099987568364095,
+           -0.3521363964819698,
+           -0.2906955082280605,
+           -0.22676175945926655,
+           -0.1614790624662094,
+           -0.09601531786732986,
+           -0.03152764130857968,
+           0.03087199190676124,
+           0.0901497616287223,
+           0.1453807901877127,
+           0.19577687378851885,
+           0.24071040927862053,
+           0.279733866614273,
+           0.31259427311420807,
+           0.33924230517607534,
+           0.35983572325403995,
+           0.37473703300919625,
+           0.3845054059214054,
+           0.38988304248040095,
+           0.391776306554857,
+           0.39123209697551276,
+           0.38941004826573317,
+           0.38755126359981557,
+           0.38694437662222547,
+           0.38888981231463865,
+           0.39466316874580615,
+           0.40547866992307063,
+           0.4224536443063471,
+           0.4465749636703657,
+           0.47866833334054765,
+           0.5193712584106777,
+           0.5691104229771387,
+           0.6280841128283798,
+           0.6962501890233064,
+           0.773319983407742,
+           0.8587583407246611,
+           0.9517898791989244,
+           1.0514113861158616,
+           1.1564101108332636,
+           1.2653875687131846,
+           1.3767883293595493,
+           1.4889331348145576,
+           1.6000555812164738,
+           1.7083415036899718,
+           1.8119701313119414,
+           1.9091560287464653,
+           1.9981908148890333,
+           2.077483647328228,
+           2.1455994847389546,
+           2.2012941869672504,
+           2.2435455834528657,
+           2.271579733085884,
+           2.2848917103972015,
+           2.2832603814469845,
+           2.2667567747928747,
+           2.2357458050440537,
+           2.1908812650373894,
+           2.1330941637433645,
+           2.0635746466899283,
+           1.9837478900783856,
+           1.895244505077669,
+           1.7998661214622422,
+           1.6995469365490885,
+           1.5963121134239258,
+           1.4922339893144,
+           1.389387108775557,
+           1.2898031257702467,
+           1.1954266230210686,
+           1.1080728760627734,
+           1.0293885437345682,
+           0.9608161975262831,
+           0.9035635109147064,
+           0.8585778188187085,
+           0.8265266292680149,
+           0.8077845274409431,
+           0.8024267598405987,
+           0.8102296272605649,
+           0.8306776532160778,
+           0.8629773336284143,
+           0.9060771176623086,
+           0.9586931225159739,
+           1.019339950218831,
+           1.0863658553648134,
+           1.1579914120729802,
+           1.232350748739557,
+           1.3075343622263549,
+           1.3816324903577804,
+           1.4527780137144708,
+           1.519187874845629,
+           1.5792020446889956,
+           1.6313191310980122,
+           1.6742278112677147,
+           1.706833376327145,
+           1.7282787997521103,
+           1.7379598784621877,
+           1.7355341430787612,
+           1.720923388166992,
+           1.6943098305352349,
+           1.6561260599288772,
+           1.6070390978734352,
+           1.5479290232642255,
+           1.4798627540583567,
+           1.404063689898157,
+           1.3218780178694465,
+           1.2347385605147596,
+           1.1441270998366606,
+           1.0515361420543325,
+           0.9584310946222485,
+           0.8662138093944041,
+           0.776188404340601,
+           0.6895302120055987,
+           0.6072586176265894,
+           0.530214445691041,
+           0.4590424333944672,
+           0.3941791960151285,
+           0.3358469460522601,
+           0.2840530787061796,
+           0.2385955846893743,
+           0.19907410127686964,
+           0.1649062677177893,
+           0.13534891528583107,
+           0.10952349876301845,
+           0.08644506813270271,
+           0.06505398941607038,
+           0.04424955417366562,
+           0.02292456994578141,
+           2.242531641306249e-16
+          ],
+          [
+           0,
+           -0.026997226770318048,
+           -0.057960636488907175,
+           -0.09362231031602426,
+           -0.13455168115565408,
+           -0.18113620882030315,
+           -0.23356711630571675,
+           -0.29183058512585114,
+           -0.3557046656531908,
+           -0.42476200964202476,
+           -0.4983783803522815,
+           -0.575746744786564,
+           -0.6558966063322976,
+           -0.7377180982791366,
+           -0.8199902327660961,
+           -0.9014125889147988,
+           -0.9806396310599408,
+           -1.0563167754832214,
+           -1.127117273772226,
+           -1.1917789541855845,
+           -1.249139859945389,
+           -1.2981718453245403,
+           -1.3380112362655256,
+           -1.3679857309726309,
+           -1.3876368058019,
+           -1.3967370006390145,
+           -1.3953015831315572,
+           -1.3835942295426513,
+           -1.3621265081939222,
+           -1.331651105791493,
+           -1.2931488935423459,
+           -1.2478100849673257,
+           -1.19700988683021,
+           -1.1422791848858753,
+           -1.0852709336826416,
+           -1.027723031220137,
+           -0.9714185520407975,
+           -0.9181442839554574,
+           -0.8696485622265895,
+           -0.8275994193772404,
+           -0.7935440681788214,
+           -0.7688707097320518,
+           -0.7547736084464138,
+           -0.7522223023045417,
+           -0.761935721806589,
+           -0.7843618766995372,
+           -0.8196636387613107,
+           -0.8677110046960465,
+           -0.9280800691065805,
+           -1.0000587772937823,
+           -1.0826593651971115,
+           -1.174637233104603,
+           -1.2745158447537306,
+           -1.3806170979136356,
+           -1.4910964800522388,
+           -1.6039822065010232,
+           -1.7172174414916916,
+           -1.828704626941299,
+           -1.9363508917687795,
+           -2.0381134871264854,
+           -2.132044190912337,
+           -2.216331648355863,
+           -2.289340663787842,
+           -2.349647530740049,
+           -2.3960705815311605,
+           -2.427695251190622,
+           -2.443893081186435,
+           -2.444334232774068,
+           -2.4289932343550675,
+           -2.398147848260506,
+           -2.3523711059343952,
+           -2.292516722605175,
+           -2.219698259256801,
+           -2.1352625472380877,
+           -2.0407580256019346,
+           -1.9378987599840882,
+           -1.8285250116500422,
+           -1.714561303862239,
+           -1.5979729880762465,
+           -1.480722343365182,
+           -1.3647252481986512,
+           -1.2518094441889942,
+           -1.1436753672062607,
+           -1.0418604535034057,
+           -0.9477077389117912,
+           -0.862339460024168,
+           -0.7866362403164352,
+           -0.7212223045173427,
+           -0.6664570146950161,
+           -0.6224328652127057,
+           -0.5889799147875447,
+           -0.5656764762950461,
+           -0.5518657325866314,
+           -0.5466778031777887,
+           -0.5490566557399906,
+           -0.5577911410921305,
+           -0.5715493336422806,
+           -0.5889152833177679,
+           -0.6084272317576225,
+           -0.6286163161757656,
+           -0.6480447794876713,
+           -0.6653427250666296,
+           -0.679242498283972,
+           -0.6886098436190146,
+           -0.6924710738592856,
+           -0.6900355944866261,
+           -0.6807132490301891,
+           -0.6641260868357771,
+           -0.6401142999053987,
+           -0.6087362265218994,
+           -0.5702624724708063,
+           -0.5251643519398862,
+           -0.47409699580284465,
+           -0.41787761131054324,
+           -0.35745950079327393,
+           -0.2939025547170494,
+           -0.22834102363380407,
+           -0.16194944198645825,
+           -0.09590762266691581,
+           -0.031365663536938614,
+           0.03059009473714133,
+           0.08896924615119711,
+           0.1429067681500749,
+           0.19168894933177957,
+           0.2347750956017639,
+           0.2718144242690542,
+           0.3026576807717344,
+           0.3273631499801893,
+           0.3461968798755799,
+           0.35962708614318395,
+           0.3683128580349428,
+           0.3730874348922361,
+           0.3749364651948386,
+           0.3749717922928479,
+           0.3744014297151249,
+           0.3744964910976925,
+           0.3765559227188264,
+           0.38186994822389403,
+           0.3916831737650152,
+           0.4071583164354297,
+           0.4293415091131078,
+           0.45913010082214034,
+           0.4972438142612526,
+           0.5442000426133307,
+           0.6002939680705724,
+           0.6655840671275706,
+           0.7398834354979086,
+           0.822757221763699,
+           0.9135263071328985,
+           1.0112772127240337,
+           1.114878059504012,
+           1.2230002532710014,
+           1.3341454217202384,
+           1.4466769963003747,
+           1.5588557116402137,
+           1.6688781928287197,
+           1.7749177183682103,
+           1.8751661863019486,
+           1.9678762744112333,
+           2.0514027734660365,
+           2.124242085671468,
+           2.185068918434419,
+           2.2327692655212252,
+           2.2664688521350205,
+           2.2855563253982867,
+           2.289700594661244,
+           2.2788618640003637,
+           2.2532960488792404,
+           2.213552426578949,
+           2.160464531826089,
+           2.09513447110404,
+           2.018910987465275,
+           1.9333617583947047,
+           1.840240548711782,
+           1.7414499652224826,
+           1.6390006667766972,
+           1.5349679699226735,
+           1.4314468543443593,
+           1.3305064121389063,
+           1.2341447997483026,
+           1.1442457406240287,
+           1.0625375907239814,
+           0.990555918581972,
+           0.9296104684144691,
+           0.8807572705598924,
+           0.8447765410180517,
+           0.8221568739548528,
+           0.8130860811195599,
+           0.8174488738410246,
+           0.8348314204806285,
+           0.8645326488864438,
+           0.9055820034890715,
+           0.9567632140914397,
+           1.0166434918361054,
+           1.0836074407142373,
+           1.1558948633824773,
+           1.2316415506152418,
+           1.3089220765817475,
+           1.3857935788887448,
+           1.4603394839733301,
+           1.5307121453532828,
+           1.5951733942117554,
+           1.6521320579601948,
+           1.700177581344868,
+           1.7381089843392425,
+           1.764958508988978,
+           1.7800094405968463,
+           1.7828077338289605,
+           1.773167227879551,
+           1.751168392939708,
+           1.7171507089618336,
+           1.6716989331749537,
+           1.6156236611555987,
+           1.5499367238486816,
+           1.475822086391385,
+           1.394603020907788,
+           1.3077064120323814,
+           1.2166251187019275,
+           1.122879357189735,
+           1.0279780874909683,
+           0.9333813776554672,
+           0.8404646887744922,
+           0.7504859679356062,
+           0.6645563590257878,
+           0.5836152437947508,
+           0.5084102105927524,
+           0.4394824186077642,
+           0.3771576845432329,
+           0.32154347007426315,
+           0.27253179585865656,
+           0.22980795521445352,
+           0.1928647516590002,
+           0.1610218430878704,
+           0.13344964501347728,
+           0.10919712925898131,
+           0.08722275572524446,
+           0.06642769579219056,
+           0.04569044855803512,
+           0.02390191688956869,
+           2.3565662112874196e-16
+          ],
+          [
+           0,
+           -0.028612205205775034,
+           -0.061588996965975785,
+           -0.09958653354585015,
+           -0.14308595059427662,
+           -0.19237665861277914,
+           -0.2475449869750185,
+           -0.30846849495558337,
+           -0.37481612263867375,
+           -0.44605420235266785,
+           -0.5214581982750532,
+           -0.6001298919554167,
+           -0.681019588518671,
+           -0.762952785872484,
+           -0.8446606307262154,
+           -0.9248133836613168,
+           -1.0020560334802628,
+           -1.0750451407196198,
+           -1.142485953118033,
+           -1.203168822975414,
+           -1.2560039681119617,
+           -1.3000536543038896,
+           -1.334560936793628,
+           -1.3589741803103894,
+           -1.372966679000058,
+           -1.376450817251194,
+           -1.3695863466700229,
+           -1.3527825000821232,
+           -1.3266938168112097,
+           -1.2922097107940567,
+           -1.250437970416249,
+           -1.202682532368068,
+           -1.1504160174838827,
+           -1.0952476507862678,
+           -1.0388873074281653,
+           -0.9831065278917464,
+           -0.9296974270771433,
+           -0.8804304807126391,
+           -0.8370122073086906,
+           -0.8010437737208298,
+           -0.7739815369564665,
+           -0.7571004944580879,
+           -0.7514615506384672,
+           -0.7578834204470153,
+           -0.776919883284399,
+           -0.8088429752384717,
+           -0.853632567417524,
+           -0.9109726265077609,
+           -0.9802542942695213,
+           -1.060585759397276,
+           -1.1508087319895097,
+           -1.249521171797433,
+           -1.355105770341811,
+           -1.4657635476099322,
+           -1.5795517997917436,
+           -1.6944255284402412,
+           -1.8082813961582436,
+           -1.9190031915263117,
+           -2.024507748039934,
+           -2.122790249265278,
+           -2.211967865578151,
+           -2.29032070641581,
+           -2.356329135020823,
+           -2.408706578663534,
+           -2.4464270742075587,
+           -2.468746914031648,
+           -2.4752198976955233,
+           -2.465705846918767,
+           -2.4403722017244736,
+           -2.399688680080705,
+           -2.344415148049213,
+           -2.275583008317069,
+           -2.1944705681335686,
+           -2.10257298938544,
+           -2.0015675503851855,
+           -1.8932750578556399,
+           -1.7796183359470397,
+           -1.6625787848074167,
+           -1.544152042687462,
+           -1.4263038018399292,
+           -1.3109268192319332,
+           -1.1998001286162903,
+           -1.0945514017136704,
+           -0.9966233246462709,
+           -0.9072447534003624,
+           -0.8274072915497844,
+           -0.7578477977595895,
+           -0.6990371830896666,
+           -0.6511757024977319,
+           -0.6141947850571325,
+           -0.587765287212205,
+           -0.5713118968459809,
+           -0.5640332668862938,
+           -0.5649273192869642,
+           -0.5728210368660173,
+           -0.5864039546700474,
+           -0.6042644768280266,
+           -0.6249280813189892,
+           -0.6468964352105936,
+           -0.6686864276419138,
+           -0.6888681374224299,
+           -0.7061007862782778,
+           -0.7191657865628173,
+           -0.726996072141012,
+           -0.7287010010864317,
+           -0.7235862362302831,
+           -0.7111681414763248,
+           -0.691182374790196,
+           -0.663586509260565,
+           -0.628556667805325,
+           -0.586478311065695,
+           -0.5379314679123285,
+           -0.4836708400071558,
+           -0.4246013424515931,
+           -0.3617497584271151,
+           -0.29623328399238497,
+           -0.22922581738318087,
+           -0.16192290331500134,
+           -0.09550627551780706,
+           -0.031108949232382995,
+           0.030218200526483014,
+           0.08753747906281767,
+           0.14005219747810824,
+           0.1871305348478068,
+           0.2283247919232406,
+           0.26338551130859333,
+           0.29227007274581723,
+           0.31514551599662577,
+           0.3323854941944773,
+           0.34456141363871434,
+           0.3524279679351031,
+           0.35690342129565245,
+           0.3590451339628519,
+           0.3600209486031415,
+           0.3610771669103163,
+           0.363503937746482,
+           0.3685989495574442,
+           0.3776303686791907,
+           0.3917999902136777,
+           0.4122075687033773,
+           0.4398172717965815,
+           0.47542715200817676,
+           0.5196424606862255,
+           0.5728535361123952,
+           0.6352188865471994,
+           0.7066539617110104,
+           0.7868259658116392,
+           0.875154915264788,
+           0.9708209884280824,
+           1.0727780568599972,
+           1.1797731317575468,
+           1.2903713092171636,
+           1.4029856575609456,
+           1.5159113627041578,
+           1.6273633366197273,
+           1.7355164021927008,
+           1.838547097495004,
+           1.9346760955612003,
+           2.022210213350566,
+           2.099582986373487,
+           2.165392813453605,
+           2.2184377286801515,
+           2.257745933557588,
+           2.282601319882105,
+           2.292563330630494,
+           2.287480639322001,
+           2.2674982746826164,
+           2.2330579734483758,
+           2.1848917059902244,
+           2.1240084831789887,
+           2.0516747145329273,
+           1.969388543246695,
+           1.8788487293773894,
+           1.7819187846856375,
+           1.6805871781500197,
+           1.5769245271481565,
+           1.4730387633631687,
+           1.3710293127982898,
+           1.2729413546158594,
+           1.1807212232209208,
+           1.0961739920729605,
+           1.0209242267488354,
+           0.9563808200253354,
+           0.9037067250137734,
+           0.8637942860118111,
+           0.8372467335710552,
+           0.8243662635545851,
+           0.8251489632494926,
+           0.8392866847218527,
+           0.8661758005206026,
+           0.9049326135692598,
+           0.9544150355998935,
+           1.0132500006069212,
+           1.0798659451148394,
+           1.1525295688226278,
+           1.2293859902603543,
+           1.3085013348448615,
+           1.3879067389920543,
+           1.4656427249929145,
+           1.5398028978394906,
+           1.608575937119935,
+           1.670284903887243,
+           1.7234229528340088,
+           1.7666846323842487,
+           1.7989920671191406,
+           1.8195154454848217,
+           1.8276873777794782,
+           1.8232108414500718,
+           1.8060605889722348,
+           1.776478054122442,
+           1.7349599513127427,
+           1.6822409159290794,
+           1.6192706775255967,
+           1.5471863887507282,
+           1.4672808478150148,
+           1.3809674483608345,
+           1.2897427654409293,
+           1.1951477381679347,
+           1.0987284372491004,
+           1.0019974084619738,
+           0.9063965611694721,
+           0.8132625248465136,
+           0.7237953275261714,
+           0.6390311598717244,
+           0.559819879567026,
+           0.4868077856816285,
+           0.42042605479461126,
+           0.3608850834527977,
+           0.3081748287234136,
+           0.26207108404061374,
+           0.22214747513935917,
+           0.18779281445873658,
+           0.15823331566365662,
+           0.1325590463145947,
+           0.10975388931152476,
+           0.08872819524129522,
+           0.06835324037973489,
+           0.04749656052006175,
+           0.025057210121704566,
+           2.4864427753583164e-16
+          ],
+          [
+           0,
+           -0.030377388799908728,
+           -0.06548575637427535,
+           -0.10589795389799313,
+           -0.15200077155191968,
+           -0.20398105177699297,
+           -0.2618173921160997,
+           -0.32527767643161015,
+           -0.3939225213255426,
+           -0.46711457019570823,
+           -0.5440334144515505,
+           -0.6236957738695831,
+           -0.7049804296402031,
+           -0.7866572778689618,
+           -0.8674197613553046,
+           -0.945919846194386,
+           -1.0208046394808337,
+           -1.0907536969601943,
+           -1.154516046125715,
+           -1.210945951643536,
+           -1.259036476136519,
+           -1.2979499396727256,
+           -1.32704445458843,
+           -1.3458958067490179,
+           -1.3543140677011547,
+           -1.3523544516061006,
+           -1.3403220731683216,
+           -1.3187704144582317,
+           -1.2884934658037466,
+           -1.2505116648754693,
+           -1.2060519147472075,
+           -1.1565221121578655,
+           -1.1034807576592205,
+           -1.0486023462730159,
+           -0.993639347495417,
+           -0.9403816741796918,
+           -0.89061460868134,
+           -0.8460761998817572,
+           -0.8084151651174256,
+           -0.779150326044255,
+           -0.7596325771017077,
+           -0.7510103301773232,
+           -0.7541993005897945,
+           -0.7698573994700708,
+           -0.7983653784229974,
+           -0.8398137368724943,
+           -0.8939962540137236,
+           -0.9604103494251265,
+           -1.038264312978225,
+           -1.126491279713297,
+           -1.223769662858547,
+           -1.3285496021387442,
+           -1.4390848387725654,
+           -1.5534692966750605,
+           -1.6696775346054842,
+           -1.7856081391580052,
+           -1.8991290559242244,
+           -2.0081238076587002,
+           -2.110537525060022,
+           -2.2044217184297934,
+           -2.2879767469467645,
+           -2.3595909959162435,
+           -2.4178758498343615,
+           -2.461695648564956,
+           -2.490191932949325,
+           -2.5028014218613657,
+           -2.4992673117808053,
+           -2.4796436487569977,
+           -2.4442926873091566,
+           -2.3938753173483107,
+           -2.329334804560208,
+           -2.2518742478617018,
+           -2.1629283056951407,
+           -2.064129877463897,
+           -1.9572725440826144,
+           -1.8442696695800915,
+           -1.7271111415991995,
+           -1.607818780679885,
+           -1.4884014751677184,
+           -1.3708110998605547,
+           -1.2569002521182175,
+           -1.1483827897753836,
+           -1.0467980820886986,
+           -0.9534797899698072,
+           -0.8695298772958537,
+           -0.7957984240114084,
+           -0.7328696673089242,
+           -0.6810545429883161,
+           -0.6403898389736544,
+           -0.6106439108675688,
+           -0.591328749353677,
+           -0.5817180351567928,
+           -0.5808706729261037,
+           -0.587659164354039,
+           -0.6008020662819473,
+           -0.6188996842555564,
+           -0.6404720782765555,
+           -0.6639984071085947,
+           -0.687956611610032,
+           -0.7108624367432759,
+           -0.7313068160880074,
+           -0.7479906911768989,
+           -0.7597564094868596,
+           -0.765614937594425,
+           -0.7647682374539594,
+           -0.7566262811313333,
+           -0.7408183193804979,
+           -0.7171981686319348,
+           -0.6858434354941191,
+           -0.6470487538485348,
+           -0.601313263112347,
+           -0.5493227033858336,
+           -0.49192664029487654,
+           -0.43011145594014816,
+           -0.3649698493757049,
+           -0.29766767778244024,
+           -0.22940903578599436,
+           -0.16140051354532198,
+           -0.09481559324167105,
+           -0.03076013797152436,
+           0.02976010304503177,
+           0.08586910280691963,
+           0.13684648437966093,
+           0.18214907066101166,
+           0.22142747285731562,
+           0.2545372638606871,
+           0.28154442385088163,
+           0.30272489473772923,
+           0.31855823372529096,
+           0.32971551042032865,
+           0.3370417426137882,
+           0.3415333093068401,
+           0.3443109120844159,
+           0.34658877418201256,
+           0.3496408675245977,
+           0.3547650390507012,
+           0.36324596667802383,
+           0.3763179107771085,
+           0.3951282380436961,
+           0.42070268085900575,
+           0.45391325688338685,
+           0.49544971164226775,
+           0.545795262728099,
+           0.6052073200102059,
+           0.6737037344755302,
+           0.751054992020925,
+           0.8367826210555007,
+           0.9301639278089732,
+           1.0302430146344226,
+           1.1358478782955994,
+           1.2456132311956984,
+           1.3580085425948383,
+           1.4713706627421346,
+           1.5839402738951769,
+           1.693901311425341,
+           1.7994224181772187,
+           1.8986994380215538,
+           1.989997921607684,
+           2.071694609581196,
+           2.1423168762587426,
+           2.2005791595895317,
+           2.245415470204122,
+           2.2760071618798934,
+           2.2918052557022577,
+           2.2925467379260964,
+           2.2782643939549905,
+           2.2492898944995954,
+           2.2062500111121057,
+           2.150056002990575,
+           2.081886381181001,
+           2.0031634160569043,
+           1.915523905311032,
+           1.8207848589378064,
+           1.7209048813962327,
+           1.6179421362779904,
+           1.5140098627712806,
+           1.4112304739339279,
+           1.311689302760865,
+           1.2173890723506033,
+           1.1302061508686092,
+           1.0518496108336945,
+           0.9838240465041208,
+           0.9273970144025971,
+           0.8835718524464687,
+           0.853066505403653,
+           0.8362988415842926,
+           0.8333787912783596,
+           0.8441074752192157,
+           0.8679833252414448,
+           0.9042150333501633,
+           0.9517410036640913,
+           1.0092548280660893,
+           1.0752361646204347,
+           1.1479862713297382,
+           1.2256673396618842,
+           1.3063446850816742,
+           1.3880307876583013,
+           1.4687301362072493,
+           1.5464838152766176,
+           1.6194127858907739,
+           1.6857588479724128,
+           1.743922333808124,
+           1.7924956662340814,
+           1.8302920202685036,
+           1.8563684500722712,
+           1.8700429813025052,
+           1.8709053186966567,
+           1.8588209763688026,
+           1.8339287999103515,
+           1.7966320109707345,
+           1.7475830625649236,
+           1.687662743037582,
+           1.6179541047355317,
+           1.539711916623497,
+           1.4543284453223817,
+           1.3632964538069032,
+           1.2681703692362887,
+           1.1705266096380864,
+           1.071924072551071,
+           0.9738657770091842,
+           0.8777626137902967,
+           0.7849000986531097,
+           0.6964089409241812,
+           0.6132401374057231,
+           0.5361451817804795,
+           0.4656618455491502,
+           0.40210584145773204,
+           0.34556852803334365,
+           0.295920658099499,
+           0.2528220189160002,
+           0.21573666079558093,
+           0.1839532684831298,
+           0.156610098825603,
+           0.13272379259201014,
+           0.11122127062038722,
+           0.09097384721436524,
+           0.07083263881123561,
+           0.04966431475785986,
+           0.026386230323861566,
+           2.631548349074569e-16
+          ],
+          [
+           0,
+           -0.032282286969046274,
+           -0.06962600022266754,
+           -0.11251395478632942,
+           -0.16123332671111024,
+           -0.215864752465379,
+           -0.27627721559977736,
+           -0.34212887431706746,
+           -0.4128738285152488,
+           -0.48777466963881955,
+           -0.5659205052092694,
+           -0.6462500060596059,
+           -0.7275788917279641,
+           -0.8086311515505387,
+           -0.8880731987472186,
+           -0.9645500747861662,
+           -1.0367227636120286,
+           -1.1033056414342273,
+           -1.1631030786081076,
+           -1.2150442259942575,
+           -1.2582150587137257,
+           -1.2918868144730522,
+           -1.3155400500597936,
+           -1.3288836460948907,
+           -1.3318682140541764,
+           -1.3246934978772493,
+           -1.3078095117410888,
+           -1.2819113120806471,
+           -1.2479274617921878,
+           -1.2070024037685674,
+           -1.1604731155069143,
+           -1.1098405626226686,
+           -1.0567366030269718,
+           -1.0028871118985758,
+           -0.9500721974081276,
+           -0.9000844558862823,
+           -0.8546862707415053,
+           -0.8155671904705001,
+           -0.7843024267129399,
+           -0.7623134932594081,
+           -0.7508319616389404,
+           -0.7508672394275409,
+           -0.7631791853693194,
+           -0.788256262986506,
+           -0.8262998042796325,
+           -0.8772148105320782,
+           -0.9406075616450743,
+           -1.015790142628944,
+           -1.1017918298368263,
+           -1.1973771143078775,
+           -1.301069979233662,
+           -1.411183897006578,
+           -1.5258568722740937,
+           -1.6430907343267007,
+           -1.7607937780226313,
+           -1.8768257698686035,
+           -1.9890442768772678,
+           -2.0953512418764637,
+           -2.1937387209077355,
+           -2.2823327164423115,
+           -2.3594340839429213,
+           -2.4235555577595624,
+           -2.4734540338139768,
+           -2.508157358783163,
+           -2.5269850058108783,
+           -2.5295621619887574,
+           -2.515826909422559,
+           -2.4860303458238007,
+           -2.440729658248585,
+           -2.380774330764544,
+           -2.3072858293992033,
+           -2.221631261759246,
+           -2.1253916504730426,
+           -2.0203255856648523,
+           -1.9083291289732276,
+           -1.791392927596041,
+           -1.6715575594237044,
+           -1.550868168031207,
+           -1.43132945826977,
+           -1.3148621091966362,
+           -1.2032616215088876,
+           -1.0981605525360114,
+           -1.0009950048278915,
+           -0.9129761266425864,
+           -0.8350672568902762,
+           -0.7679672064621059,
+           -0.7121000158626705,
+           -0.6676113694425739,
+           -0.6343716832431938,
+           -0.6119857205514923,
+           -0.5998084307326219,
+           -0.5969665566590688,
+           -0.6023854177704588,
+           -0.6148201528566622,
+           -0.6328906020494968,
+           -0.6551189237646267,
+           -0.6799689814614184,
+           -0.7058864985180912,
+           -0.7313389680790559,
+           -0.7548543186204741,
+           -0.7750573747676172,
+           -0.7907032155333036,
+           -0.8007066169878467,
+           -0.8041668712249458,
+           -0.8003873956667362,
+           -0.7888896831397192,
+           -0.769421290287192,
+           -0.7419577160367955,
+           -0.706698179118464,
+           -0.6640554600617521,
+           -0.6146401247534514,
+           -0.5592395896936458,
+           -0.4987926199597674,
+           -0.4343599662932958,
+           -0.36709194477499657,
+           -0.29819383882900524,
+           -0.2288900568959789,
+           -0.1603880087150098,
+           -0.09384266803263619,
+           -0.03032276961707917,
+           0.02922045577612833,
+           0.08398117222593396,
+           0.13332270781061797,
+           0.17679656265888788,
+           0.21415614084513332,
+           0.2453648287709991,
+           0.27059819013674236,
+           0.2902402011045402,
+           0.3048736048987879,
+           0.3152646189262299,
+           0.32234237562534007,
+           0.32717361690443947,
+           0.33093328767185826,
+           0.3348717833932032,
+           0.34027969702918953,
+           0.34845097978651246,
+           0.3606454760612947,
+           0.37805181455642844,
+           0.401751634207162,
+           0.4326860952760184,
+           0.4716255734265724,
+           0.5191433590143811,
+           0.5755940870804799,
+           0.6410975079708598,
+           0.715528076982437,
+           0.7985106972059332,
+           0.8894227963770549,
+           0.9874027598733368,
+           1.0913645819605713,
+           1.2000184399974623,
+           1.3118967454912338,
+           1.4253850854464314,
+           1.5387573409006055,
+           1.6502141600925824,
+           1.757923874142353,
+           1.8600648757291904,
+           1.9548684377848058,
+           2.040660930828202,
+           2.1159044047985303,
+           2.179234533996431,
+           2.2294949812967415,
+           2.2657673188042815,
+           2.287395744665694,
+           2.294005957363729,
+           2.2855176865700617,
+           2.262150530179477,
+           2.2244229068304566,
+           2.1731440981422563,
+           2.1093995210375227,
+           2.0345295338075293,
+           1.9501022360124585,
+           1.8578808680531846,
+           1.7597865477224912,
+           1.657857195006233,
+           1.5542035900500952,
+           1.4509635802197338,
+           1.3502554988010695,
+           1.254131878947237,
+           1.164534541440461,
+           1.0832521038003162,
+           1.0118809019709125,
+           0.9517902356140495,
+           0.9040927458646685,
+           0.8696206127485233,
+           0.8489081212762292,
+           0.8421809938742886,
+           0.8493527259751593,
+           0.8700279951790976,
+           0.9035130464695977,
+           0.9488327905961497,
+           1.0047541939518245,
+           1.0698153899242109,
+           1.1423598073827594,
+           1.2205744949328887,
+           1.3025317226396658,
+           1.3862328684281855,
+           1.46965354607683,
+           1.5507889068116478,
+           1.6276980475373262,
+           1.6985464856185981,
+           1.7616457121356366,
+           1.8154889113424952,
+           1.8587820317407346,
+           1.8904695112874006,
+           1.909754092861691,
+           1.9161103128903794,
+           1.9092914023335972,
+           1.8893295011878366,
+           1.8565292512680778,
+           1.8114549932505717,
+           1.7549119488238631,
+           1.687921913506507,
+           1.6116941167034398,
+           1.5275920196946529,
+           1.4370969167105845,
+           1.3417692767739158,
+           1.2432088128520629,
+           1.1430142889349195,
+           1.0427440744139576,
+           0.9438784287079606,
+           0.8477844482002757,
+           0.755684533573619,
+           0.6686291404748613,
+           0.587474462561776,
+           0.5128655662872913,
+           0.44522535456440276,
+           0.3847495853332205,
+           0.33140801484338783,
+           0.28495157811378136,
+           0.24492536450216953,
+           0.2106869984982172,
+           0.18142989845761803,
+           0.15621076246983898,
+           0.13398052399052876,
+           0.11361793293564827,
+           0.09396485279500832,
+           0.07386232259483282,
+           0.05218641524862939,
+           0.027882931393530333,
+           2.7911058610218833e-16
+          ],
+          [
+           0,
+           -0.03431482873161094,
+           -0.07398194684347316,
+           -0.11938813410410382,
+           -0.17071652570818688,
+           -0.2279388430439266,
+           -0.2908135615181588,
+           -0.3588900811667121,
+           -0.43151880893141886,
+           -0.5078669067694453,
+           -0.5869393111043989,
+           -0.6676044903111101,
+           -0.7486242814814436,
+           -0.8286870388478765,
+           -0.9064432367318044,
+           -0.9805426020375292,
+           -1.0496718068914093,
+           -1.1125917322028482,
+           -1.1681733182570948,
+           -1.2154310488655962,
+           -1.2535531703941412,
+           -1.2819278248455004,
+           -1.3001643751939975,
+           -1.3081093189226545,
+           -1.3058563192932684,
+           -1.293750029978061,
+           -1.2723835436701665,
+           -1.242589455311264,
+           -1.205424691635779,
+           -1.1621494168054523,
+           -1.1142004750342784,
+           -1.06315997148475,
+           -1.0107197188140924,
+           -0.9586423853729851,
+           -0.9087202694464883,
+           -0.8627326898104591,
+           -0.8224030245446993,
+           -0.7893564463804356,
+           -0.765079393375067,
+           -0.7508817785503912,
+           -0.7478628820869793,
+           -0.7568817861397729,
+           -0.7785331073147085,
+           -0.8131286578451568,
+           -0.8606855265255445,
+           -0.9209209178935335,
+           -0.9932539267139792,
+           -1.0768142584456313,
+           -1.1704577391314777,
+           -1.2727882941405355,
+           -1.382185918424333,
+           -1.4968400152852708,
+           -1.614787349668575,
+           -1.7339537489115562,
+           -1.8521985915041994,
+           -1.967361055019978,
+           -2.077307049690003,
+           -2.1799757452376842,
+           -2.2734246060533043,
+           -2.3558718834118553,
+           -2.425735572426234,
+           -2.4816679243618647,
+           -2.5225847098129948,
+           -2.547688552511057,
+           -2.556485794183352,
+           -2.5487965044859635,
+           -2.5247574128617973,
+           -2.4848177072613016,
+           -2.4297278139208736,
+           -2.3605214387061073,
+           -2.278491309852486,
+           -2.1851592104068107,
+           -2.082241022689682,
+           -1.971607623420713,
+           -1.8552425639686734,
+           -1.7351975432089097,
+           -1.6135467289517498,
+           -1.4923410067148852,
+           -1.3735632312462818,
+           -1.2590855268038272,
+           -1.1506296275420345,
+           -1.049731170844476,
+           -0.9577087560553788,
+           -0.875638461322054,
+           -0.8043343751507032,
+           -0.7443355501868463,
+           -0.6958996283577032,
+           -0.6590032227771414,
+           -0.6333489767588026,
+           -0.6183790579777202,
+           -0.6132946902565792,
+           -0.617081180445581,
+           -0.6285377669608223,
+           -0.6463115029341793,
+           -0.6689342933612878,
+           -0.6948621343632769,
+           -0.7225155553943641,
+           -0.7503202430232921,
+           -0.7767468282585869,
+           -0.800348848105862,
+           -0.8197979453389214,
+           -0.8339154469240448,
+           -0.8416995591727799,
+           -0.8423475340034662,
+           -0.8352722926950056,
+           -0.8201131378616394,
+           -0.7967403374062442,
+           -0.7652535220534021,
+           -0.7259739967399629,
+           -0.6794312216542505,
+           -0.6263438671554604,
+           -0.5675959844457515,
+           -0.5042089572593731,
+           -0.4373100058886138,
+           -0.36809810093778417,
+           -0.2978082081414162,
+           -0.22767482581794296,
+           -0.1588957920692775,
+           -0.09259732931673709,
+           -0.02980125945201037,
+           0.028604735330060194,
+           0.0818930115690318,
+           0.12951732996812604,
+           0.17112911248679735,
+           0.20658814988274066,
+           0.23596746337943247,
+           0.2595521767247084,
+           0.2778324113238508,
+           0.29149037340836464,
+           0.30138195437174026,
+           0.308513309599789,
+           0.3140130136772691,
+           0.3191005073862939,
+           0.32505165142205855,
+           0.333162280684664,
+           0.34471070932413694,
+           0.36092016894687196,
+           0.38292216966715387,
+           0.411721755764349,
+           0.44816558497471115,
+           0.49291369391972967,
+           0.5464157234628609,
+           0.6088922690647101,
+           0.6803218951504839,
+           0.760434212229373,
+           0.8487092644924218,
+           0.9443833176181546,
+           1.0464609754709513,
+           1.1537333943083692,
+           1.2648022080265984,
+           1.3781086317595428,
+           1.4919670774856975,
+           1.6046024975628783,
+           1.7141905732900982,
+           1.8188997882111573,
+           1.9169343719215997,
+           2.006577071038604,
+           2.0862307005463996,
+           2.1544574511099466,
+           2.2100149756876823,
+           2.2518883507731773,
+           2.2793171021556304,
+           2.2918165999494002,
+           2.2891932600359928,
+           2.271553135782549,
+           2.2393036413841263,
+           2.193148312585462,
+           2.1340746778573423,
+           2.063335479239484,
+           1.9824236429458086,
+           1.893041551510594,
+           1.7970653080080319,
+           1.696504805288223,
+           1.5934605162207627,
+           1.4900780020774558,
+           1.3885011934052016,
+           1.2908255296130935,
+           1.1990520492160346,
+           1.1150435020750193,
+           1.0404835085296023,
+           0.976839719142407,
+           0.9253318345865507,
+           0.8869052302862517,
+           0.8622107975584741,
+           0.8515914654280266,
+           0.8550757085897049,
+           0.872378181029529,
+           0.9029074456306445,
+           0.9457806017932183,
+           0.9998444497830521,
+           1.0637026761574309,
+           1.1357484029441198,
+           1.2142013177013458,
+           1.2971484951958334,
+           1.38258793676285,
+           1.4684737924819993,
+           1.5527621955550008,
+           1.6334566285284466,
+           1.7086517574462976,
+           1.7765747121826645,
+           1.8356228580020904,
+           1.8843971931263086,
+           1.9217306174964597,
+           1.9467104462459608,
+           1.9586946844451567,
+           1.9573217338905056,
+           1.942513364267053,
+           1.9144709459189726,
+           1.8736651056496596,
+           1.8208191263985134,
+           1.75688656239005,
+           1.6830236797301097,
+           1.6005574550555437,
+           1.5109499687477492,
+           1.4157601118870031,
+           1.3166035855771538,
+           1.2151122061124853,
+           1.1128935389086714,
+           1.0114918680290927,
+           0.9123514669935486,
+           0.8167830714678254,
+           0.7259343671039664,
+           0.6407651984869883,
+           0.5620280805927685,
+           0.49025445554741437,
+           0.42574698831912094,
+           0.3685780390446802,
+           0.3185942909319978,
+           0.2754273550888783,
+           0.2385100211722437,
+           0.20709767926088937,
+           0.18029430742822825,
+           0.15708230440797805,
+           0.1363553503817285,
+           0.11695340367531955,
+           0.09769888889980306,
+           0.07743310410104642,
+           0.05505187146653707,
+           0.02953947812674057,
+           2.9641798927082e-16
+          ],
+          [
+           0,
+           -0.03646146435173875,
+           -0.07852319080564008,
+           -0.12647072309751414,
+           -0.18037962544759006,
+           -0.24011096306989071,
+           -0.3053128195028547,
+           -0.3754278266115248,
+           -0.4497065258384988,
+           -0.5272262264564651,
+           -0.6069148820828829,
+           -0.6875793742332624,
+           -0.7679374745901328,
+           -0.8466526589424265,
+           -0.9223708679373956,
+           -0.9937582548937343,
+           -1.0595389303856386,
+           -1.1185317079479964,
+           -1.1696848752658047,
+           -1.2121080601522856,
+           -1.2451003294191707,
+           -1.2681737497278363,
+           -1.2810717504503444,
+           -1.2837817567296208,
+           -1.2765417031355826,
+           -1.2598401910388815,
+           -1.2344102122650162,
+           -1.2012165237723844,
+           -1.161436918964276,
+           -1.1164377967671386,
+           -1.067744575879977,
+           -1.0170076349387631,
+           -0.9659645763753808,
+           -0.916399709510986,
+           -0.8701017244101468,
+           -0.8288205802706032,
+           -0.7942246592563071,
+           -0.7678592379399156,
+           -0.7511073037873771,
+           -0.7451536939173324,
+           -0.7509534588594646,
+           -0.7692052569803597,
+           -0.8003304679658675,
+           -0.844458579073017,
+           -0.9014192490550217,
+           -0.9707412953379602,
+           -1.0516586840715167,
+           -1.1431234341435528,
+           -1.2438251792645965,
+           -1.3522169708878637,
+           -1.4665467529949305,
+           -1.584893801378731,
+           -1.7052092984031484,
+           -1.825360112315026,
+           -1.9431747705512386,
+           -2.0564905610983955,
+           -2.1632006662109333,
+           -2.261300229432553,
+           -2.3489302800078358,
+           -2.424418487877442,
+           -2.486315796347701,
+           -2.5334280764311092,
+           -2.5648420644229297,
+           -2.579944979657462,
+           -2.578437369287203,
+           -2.5603388877041557,
+           -2.5259868859647514,
+           -2.476027857207949,
+           -2.4114019534206177,
+           -2.333320952888442,
+           -2.243240212291607,
+           -2.1428252789112934,
+           -2.0339139633787426,
+           -1.9184747788045482,
+           -1.7985627354351894,
+           -1.676273539204621,
+           -1.5536972762810688,
+           -1.4328726731812933,
+           -1.3157430031082498,
+           -1.2041146643850789,
+           -1.0996193873625824,
+           -1.003680933729857,
+           -0.9174870390793985,
+           -0.8419672186932371,
+           -0.7777769110832882,
+           -0.7252882774458344,
+           -0.6845878117489622,
+           -0.655480749700452,
+           -0.637502099446432,
+           -0.6299339565968131,
+           -0.631828614995113,
+           -0.64203684624765,
+           -0.6592405987757906,
+           -0.6819892640230182,
+           -0.7087385759238156,
+           -0.737891151769802,
+           -0.7678376495479133,
+           -0.7969975094112,
+           -0.8238582652720084,
+           -0.8470124560362093,
+           -0.8651912335562036,
+           -0.8772938542042894,
+           -0.882412350739818,
+           -0.879850808054452,
+           -0.8691388071983791,
+           -0.8500387532445827,
+           -0.8225469602148229,
+           -0.7868885264909765,
+           -0.7435061928335539,
+           -0.6930435283353663,
+           -0.6363229335063496,
+           -0.5743190806096988,
+           -0.5081285260742999,
+           -0.4389363254301679,
+           -0.3679805553716334,
+           -0.29651569840887826,
+           -0.22577587187179987,
+           -0.15693888414910723,
+           -0.09109207698280254,
+           -0.02920086402998714,
+           0.027919195995775324,
+           0.07962604664241897,
+           0.125469868958688,
+           0.1652064007523034,
+           0.19880447754477842,
+           0.22644758383189476,
+           0.24852935971103118,
+           0.2656431659396591,
+           0.27856596603277906,
+           0.2882369331401899,
+           0.29573132837568966,
+           0.302230322462113,
+           0.30898754081411467,
+           0.3172932007335363,
+           0.32843677596173004,
+           0.34366916669160213,
+           0.3641653711555708,
+           0.3909886475634825,
+           0.4250571225925639,
+           0.4671137455894542,
+           0.5177004075075315,
+           0.5771369423284674,
+           0.6455056087960751,
+           0.7226415146861767,
+           0.8081292979100202,
+           0.9013062221778758,
+           1.001271683634705,
+           1.106902962848911,
+           1.2168768978430784,
+           1.3296970024820658,
+           1.443725414285606,
+           1.5572189301475408,
+           1.6683682807028175,
+           1.7753397069302985,
+           1.8763178382526633,
+           1.9695488315702891,
+           2.053382716416208,
+           2.126313903182594,
+           2.1870188489424773,
+           2.2343899379284826,
+           2.267564719769639,
+           2.28594975607883,
+           2.289238452344404,
+           2.2774223942548524,
+           2.2507958621244684,
+           2.2099533602276966,
+           2.1557801656085847,
+           2.089436069206813,
+           2.012332646810312,
+           1.9261045543664395,
+           1.8325754876996923,
+           1.7337195771127154,
+           1.631619099473075,
+           1.5284194814395682,
+           1.426282635203262,
+           1.3273397108218574,
+           1.2336443658379874,
+           1.1471276429553265,
+           1.0695555103154992,
+           1.0024900572320274,
+           0.9472552525775515,
+           0.9049080654577066,
+           0.876215620946694,
+           0.8616389205860663,
+           0.8613235015367283,
+           0.8750972435141403,
+           0.9024753629356151,
+           0.9426724631940013,
+           0.9946213427899167,
+           1.0569981032673421,
+           1.1282529503835144,
+           1.2066459483038816,
+           1.2902868710790645,
+           1.377178201019498,
+           1.4652602521061129,
+           1.552457349963396,
+           1.6367239792629895,
+           1.716089815173748,
+           1.7887025874296654,
+           1.852867782910362,
+           1.9070842738573721,
+           1.950075061936229,
+           1.9808124507186071,
+           1.998537097749522,
+           2.002770548738484,
+           1.993321016817948,
+           1.9702823352804495,
+           1.9340261786540416,
+           1.8851878103043322,
+           1.8246457709477477,
+           1.7534960676959899,
+           1.673021553977568,
+           1.5846573037169294,
+           1.4899528757591765,
+           1.390532434484338,
+           1.288053738203266,
+           1.1841670272174978,
+           1.0804748379402613,
+           0.9784937384396495,
+           0.8796189250372388,
+           0.7850925406479917,
+           0.6959764754279704,
+           0.6131302915761927,
+           0.5371947798453978,
+           0.4685815088660633,
+           0.4074685734880396,
+           0.35380258890802724,
+           0.3073068173983804,
+           0.2674951580087568,
+           0.23369158060747078,
+           0.2050544478014324,
+           0.1806050450738002,
+           0.15925953398614437,
+           0.13986345813731144,
+           0.12122786887044412,
+           0.10216609902200184,
+           0.08153019925610563,
+           0.05824606303967589,
+           0.031346302768166474,
+           3.1496841126988625e-16
+          ],
+          [
+           0,
+           -0.03870728323795299,
+           -0.08321697579513994,
+           -0.1337090441076261,
+           -0.19014889423498163,
+           -0.25228619209770614,
+           -0.31965976861438006,
+           -0.39160849454274843,
+           -0.46728785350868574,
+           -0.5456917921502922,
+           -0.6256792873138577,
+           -0.7060049453530853,
+           -0.7853528409893593,
+           -0.8623727156430614,
+           -0.9357175898962822,
+           -1.0040818034894272,
+           -1.066238480080472,
+           -1.1210754233689169,
+           -1.167628485928269,
+           -1.2051115113849822,
+           -1.2329420329940628,
+           -1.2507620151752563,
+           -1.2584530466389996,
+           -1.256145531328608,
+           -1.2442215731196495,
+           -1.2233114083243601,
+           -1.1942834026054139,
+           -1.1582277918473882,
+           -1.1164345057849374,
+           -1.0703655647466728,
+           -1.0216226799285262,
+           -0.9719108126237419,
+           -0.9229985546391456,
+           -0.8766762779954003,
+           -0.8347130647342098,
+           -0.7988134655986078,
+           -0.7705751484874885,
+           -0.7514484835233334,
+           -0.7426990715732983,
+           -0.7453741580319986,
+           -0.7602737851351552,
+           -0.7879274261373702,
+           -0.8285767159989169,
+           -0.8821647488987263,
+           -0.9483322564292677,
+           -1.0264208155457686,
+           -1.1154830662614998,
+           -1.2142997498404198,
+           -1.3214032129871558,
+           -1.435106866329867,
+           -1.5535399402000645,
+           -1.6746867509144172,
+           -1.7964295796601681,
+           -1.9165941764270453,
+           -2.0329968354398096,
+           -2.1434919478742653,
+           -2.2460189233135184,
+           -2.3386473838035045,
+           -2.419619573225333,
+           -2.487388989096315,
+           -2.5406543322953725,
+           -2.5783879804464673,
+           -2.5998583201155463,
+           -2.604645418440523,
+           -2.5926496727859294,
+           -2.5640932436532466,
+           -2.519514247332182,
+           -2.459753856482497,
+           -2.3859366248163347,
+           -2.2994445122255915,
+           -2.2018852351801788,
+           -2.095055700411224,
+           -1.9809013945670386,
+           -1.8614726959229695,
+           -1.7388791440977802,
+           -1.6152427484163934,
+           -1.4926514340180437,
+           -1.3731137166422105,
+           -1.2585156624861245,
+           -1.1505811295203663,
+           -1.0508362026978693,
+           -0.9605786297091085,
+           -0.8808529389664784,
+           -0.8124317804556389,
+           -0.7558038764727651,
+           -0.7111688068779431,
+           -0.6784386863496374,
+           -0.6572466233447336,
+           -0.6469616861821126,
+           -0.646709944908677,
+           -0.6554010122142794,
+           -0.6717593761855607,
+           -0.6943597053009049,
+           -0.7216652144871122,
+           -0.7520681124790312,
+           -0.783931106766739,
+           -0.8156289240872261,
+           -0.8455888120859472,
+           -0.8723290211588219,
+           -0.8944943236687719,
+           -0.9108877091792179,
+           -0.9204974969506716,
+           -0.9225192280731652,
+           -0.9163718361683874,
+           -0.9017077441232982,
+           -0.8784166910524139,
+           -0.8466232546716674,
+           -0.8066781954469625,
+           -0.7591439062017334,
+           -0.7047744003806189,
+           -0.6444904101234459,
+           -0.579350288253636,
+           -0.5105175131582241,
+           -0.43922567972131593,
+           -0.36674192088055835,
+           -0.2943297414933903,
+           -0.2232122581254701,
+           -0.15453682484080802,
+           -0.08934198645617696,
+           -0.028527638026408595,
+           0.02717081583687879,
+           0.07720361366667144,
+           0.12122253677769601,
+           0.15909112829362243,
+           0.19088895254057822,
+           0.21690977151801294,
+           0.23765367415306876,
+           0.2538133522643575,
+           0.26625487058775943,
+           0.27599342295159146,
+           0.2841646990489024,
+           0.29199260286732265,
+           0.30075416172215264,
+           0.3117425414851128,
+           0.3262291370300621,
+           0.34542573573072627,
+           0.3704477552638299,
+           0.40227953485130485,
+           0.4417426119163218,
+           0.4894678450583388,
+           0.5458721510029425,
+           0.61114051004343,
+           0.6852137642561332,
+           0.7677825886676938,
+           0.8582878611607117,
+           0.9559274960703033,
+           1.0596696431630224,
+           1.1682719920853406,
+           1.280306766473602,
+           1.3941908456488539,
+           1.5082203188652894,
+           1.620608660803599,
+           1.729527620356058,
+           1.833149840212488,
+           1.9296921742552149,
+           2.017458644643584,
+           2.0948819814250133,
+           2.160562714613446,
+           2.21330484134467,
+           2.252147167732398,
+           2.276389524585742,
+           2.2856131758229576,
+           2.2796948753407222,
+           2.258814178952905,
+           2.223453779127875,
+           2.1743927976986672,
+           2.1126931414018224,
+           2.039679192862743,
+           1.956911271371407,
+           1.8661534495086591,
+           1.7693364496550812,
+           1.6685164652401534,
+           1.5658308522837918,
+           1.4634517148497237,
+           1.3635384615293227,
+           1.2681904376622006,
+           1.1794007389698535,
+           1.0990122865739764,
+           1.0286771915905755,
+           0.9698203608716448,
+           0.9236081958542846,
+           0.8909231162830695,
+           0.8723445027101951,
+           0.8681364994976276,
+           0.8782429572448366,
+           0.902289624103772,
+           0.9395935234406377,
+           0.9891792849440666,
+           1.0498020317022287,
+           1.1199762709741723,
+           1.1980100951183474,
+           1.2820438748351524,
+           1.3700925225332206,
+           1.4600903217523473,
+           1.5499372611274416,
+           1.6375457797150632,
+           1.7208868253493799,
+           1.7980341491205936,
+           1.8672058064948946,
+           1.9268019078034915,
+           1.9754377559944287,
+           2.011971625279245,
+           2.0355265677300856,
+           2.0455057826741854,
+           2.041601242228087,
+           2.0237954315923505,
+           1.992356230709077,
+           1.9478251304313186,
+           1.8909991373711073,
+           1.822906873133227,
+           1.7447795119989307,
+           1.6580173229264057,
+           1.5641526840285083,
+           1.4648105180091155,
+           1.3616671534727451,
+           1.25640864825107,
+           1.1506896162256082,
+           1.0460935785242689,
+           0.944095814031525,
+           0.8460296141079012,
+           0.7530567540910025,
+           0.666142881926332,
+           0.58603839502107,
+           0.5132652334160163,
+           0.44810986425504157,
+           0.3906225731680282,
+           0.34062301659147715,
+           0.2977118292980027,
+           0.26128792750593627,
+           0.2305710037536185,
+           0.20462857886020439,
+           0.18240686202679843,
+           0.16276457530801025,
+           0.14450882566184278,
+           0.12643205837189955,
+           0.10734910104135272,
+           0.08613330816862366,
+           0.061750842476372365,
+           0.033292179986283,
+           3.3463903405064364e-16
+          ],
+          [
+           0,
+           -0.041036146987973275,
+           -0.08802849433158214,
+           -0.14104800268388815,
+           -0.19994831310569483,
+           -0.26436796739497365,
+           -0.33373870852313486,
+           -0.4072996545933023,
+           -0.48411698575922135,
+           -0.5631086386202218,
+           -0.6430733704249557,
+           -0.722723439343147,
+           -0.8007200500659994,
+           -0.8757106385603042,
+           -0.9463670178764967,
+           -1.011423379855294,
+           -1.0697131461255753,
+           -1.1202036860293996,
+           -1.1620279684943153,
+           -1.1945122882117267,
+           -1.2171993019828262,
+           -1.2298657264109423,
+           -1.232534180400195,
+           -1.225478801883656,
+           -1.2092244242190184,
+           -1.184539259866576,
+           -1.1524212032509915,
+           -1.1140780269919934,
+           -1.0709019018974555,
+           -1.0244388173161685,
+           -0.9763536109585489,
+           -0.9283914327561469,
+           -0.8823365628070755,
+           -0.8399695764967562,
+           -0.8030238985972709,
+           -0.7731428112391036,
+           -0.7518379774558107,
+           -0.7404505125146907,
+           -0.7401155801071541,
+           -0.751731410960381,
+           -0.7759335394326545,
+           -0.8130749316146905,
+           -0.8632125393253477,
+           -0.9261006615377694,
+           -1.0011913319224177,
+           -1.087641782321706,
+           -1.1843288612081768,
+           -1.2898701177098102,
+           -1.402651099748245,
+           -1.5208582632134122,
+           -1.6425167516262347,
+           -1.765532185812709,
+           -1.8877355036939958,
+           -2.0069298138552307,
+           -2.1209381749960614,
+           -2.2276511879858303,
+           -2.3250732887022507,
+           -2.4113666581234154,
+           -2.4848917206102668,
+           -2.544243280659553,
+           -2.5882814507151175,
+           -2.6161566454234673,
+           -2.6273280580315985,
+           -2.621575189043945,
+           -2.5990021620290964,
+           -2.5600347325895036,
+           -2.5054100698178403,
+           -2.43615956084825,
+           -2.353585054206771,
+           -2.259229112563008,
+           -2.1548399864274317,
+           -2.0423321439114934,
+           -1.923743294886132,
+           -1.8011889282534557,
+           -1.6768154366643684,
+           -1.5527529325582945,
+           -1.4310688621970142,
+           -1.3137235003979162,
+           -1.2025283585824398,
+           -1.0991084638254431,
+           -1.0048693687084234,
+           -0.9209696333947269,
+           -0.8482993854070102,
+           -0.7874654124721683,
+           -0.7387830832254841,
+           -0.7022752235020734,
+           -0.67767790651093,
+           -0.6644529475554288,
+           -0.6618067322516098,
+           -0.6687148553644452,
+           -0.6839519091424108,
+           -0.706125638747677,
+           -0.7337145809917354,
+           -0.7651082235336849,
+           -0.7986486668614332,
+           -0.8326727420303331,
+           -0.8655535339202245,
+           -0.8957402826801847,
+           -0.9217956844019938,
+           -0.9424296846074871,
+           -0.9565289529623521,
+           -0.9631813422994207,
+           -0.9616947666184332,
+           -0.9516100778818288,
+           -0.9327076764702873,
+           -0.9050077511812203,
+           -0.8687642075900158,
+           -0.8244525043494333,
+           -0.7727517715407546,
+           -0.7145217296379662,
+           -0.6507750583893294,
+           -0.5826459786947272,
+           -0.5113559045283402,
+           -0.4381770937918715,
+           -0.364395274910127,
+           -0.2912722488275914,
+           -0.22000946329315318,
+           -0.15171352803623253,
+           -0.08736458638950992,
+           -0.02778838247187368,
+           0.02636723483095039,
+           0.07465074666344196,
+           0.11681984612619464,
+           0.15284842104527233,
+           0.18292744555864746,
+           0.20745974773183504,
+           0.22704878059057795,
+           0.24248168100464954,
+           0.254707050784075,
+           0.26480803334521347,
+           0.2739713838301559,
+           0.2834533374415476,
+           0.2945431672507918,
+           0.30852538662562645,
+           0.32664159104488455,
+           0.3500529483741927,
+           0.3798043352519496,
+           0.41679108031214385,
+           0.4617292134225326,
+           0.5151300354363996,
+           0.577279717219847,
+           0.6482245125326961,
+           0.7277620297852342,
+           0.8154388562321614,
+           0.9105546685710061,
+           1.0121728001682695,
+           1.1191370713379025,
+           1.2300945293486465,
+           1.343523593152922,
+           1.457766958030713,
+           1.5710684909603967,
+           1.681613241721389,
+           1.7875696102020806,
+           1.8871326493087397,
+           1.97856744684665,
+           2.0602515197544222,
+           2.1307151704533225,
+           2.1886787975078286,
+           2.2330862203188695,
+           2.263133168599452,
+           2.27829019974131,
+           2.2783194381658047,
+           2.263284677191814,
+           2.2335545422881555,
+           2.1897985809484846,
+           2.1329763147668386,
+           2.0643194594306626,
+           1.985307684112077,
+           1.8976384390534673,
+           1.8031915251390547,
+           1.7039892083441452,
+           1.6021527919691516,
+           1.4998566477713375,
+           1.3992807713095838,
+           1.30256296541124,
+           1.2117517676737533,
+           1.1287612230000326,
+           1.0553285606648921,
+           0.9929757683040359,
+           0.9429759641172124,
+           0.9063253556826779,
+           0.8837214418250084,
+           0.8755479661641685,
+           0.8818669708911,
+           0.9024181308548533,
+           0.9366253753047863,
+           0.9836106318086751,
+           1.0422143581649204,
+           1.1110223676432174,
+           1.1883983045185889,
+           1.2725209942050293,
+           1.3614257785568147,
+           1.4530488548308589,
+           1.5452735686024603,
+           1.6359775682221593,
+           1.723079712189506,
+           1.8045856314447575,
+           1.8786308857292882,
+           1.9435207158749384,
+           1.9977654805622518,
+           2.0401109745610104,
+           2.06956295302573,
+           2.085405329891505,
+           2.0872116742430724,
+           2.074849792857293,
+           2.0484793558887455,
+           2.008542691721259,
+           1.955749042188304,
+           1.8910527266192716,
+           1.8156258086491652,
+           1.7308259898870464,
+           1.6381605662121734,
+           1.5392473729585405,
+           1.4357737123922332,
+           1.329454299098036,
+           1.2219892752115986,
+           1.1150233375446017,
+           1.0101069828883513,
+           0.9086608171240558,
+           0.8119437898109733,
+           0.7210261108378355,
+           0.6367674822021683,
+           0.559801139173419,
+           0.49052404452098086,
+           0.4290934209559884,
+           0.37542964444592697,
+           0.329225358704578,
+           0.28996051301654296,
+           0.2569228755927974,
+           0.22923343662676632,
+           0.20587599257915673,
+           0.18573009902301282,
+           0.16760649621945786,
+           0.1502840515287889,
+           0.1325472272677282,
+           0.11322307255899573,
+           0.09121675330084372,
+           0.06554467518333726,
+           0.03536431963222056,
+           3.5529391579828295e-16
+          ],
+          [
+           0,
+           -0.04343083630279722,
+           -0.09292121138835485,
+           -0.14843060917915302,
+           -0.2097003072884646,
+           -0.276259027223939,
+           -0.347434606342318,
+           -0.4223713940782921,
+           -0.5000529247262722,
+           -0.5793292801061245,
+           -0.6589484313303521,
+           -0.7375907427771321,
+           -0.8139057359765413,
+           -0.8865501486325649,
+           -0.9542262860529456,
+           -1.0157196498487828,
+           -1.0699348422611017,
+           -1.1159287835863427,
+           -1.152940343976566,
+           -1.1804155778309675,
+           -1.1980278569374414,
+           -1.2056923247998717,
+           -1.2035742360674535,
+           -1.1920908981483624,
+           -1.171907093123627,
+           -1.143924022955713,
+           -1.109261985582839,
+           -1.0692371496759963,
+           -1.025332947583314,
+           -0.9791667454704623,
+           -0.9324525733579818,
+           -0.8869608025145079,
+           -0.8444757408111688,
+           -0.8067521760309728,
+           -0.7754719311985256,
+           -0.7522015038154355,
+           -0.7383518421718781,
+           -0.7351412670286144,
+           -0.7435624769501552,
+           -0.7643544820676739,
+           -0.7979801962939721,
+           -0.8446102847673854,
+           -0.9041137147951768,
+           -0.9760552984116806,
+           -1.059700346769185,
+           -1.154026385045974,
+           -1.257741705589229,
+           -1.3693103708075567,
+           -1.4869831199756598,
+           -1.6088334894882053,
+           -1.7327983277701853,
+           -1.8567217771911984,
+           -1.9784017086406587,
+           -2.095637532059347,
+           -2.206278269754183,
+           -2.3082697696784886,
+           -2.3996999533131382,
+           -2.47884103694441,
+           -2.5441877349567856,
+           -2.594490547568284,
+           -2.628783350968865,
+           -2.6464046422817997,
+           -2.647011941892969,
+           -2.6305890178376243,
+           -2.5974457671582027,
+           -2.5482107633117526,
+           -2.4838166525771417,
+           -2.4054787517638916,
+           -2.314667360242161,
+           -2.2130744474952153,
+           -2.1025755094501686,
+           -1.9851874995740175,
+           -1.8630238314113496,
+           -1.738247515710028,
+           -1.6130235359502831,
+           -1.4894715800135157,
+           -1.3696202326086675,
+           -1.2553636932898646,
+           -1.1484220194745387,
+           -1.0503058044620288,
+           -0.9622860892981616,
+           -0.8853701772037121,
+           -0.8202838734161736,
+           -0.7674605152990939,
+           -0.7270369913573843,
+           -0.6988567774606407,
+           -0.6824798483139188,
+           -0.6771991562099287,
+           -0.6820632114180389,
+           -0.6959041530693092,
+           -0.7173705696290664,
+           -0.7449642171588836,
+           -0.7770796942335669,
+           -0.8120460667317558,
+           -0.8481693953051541,
+           -0.8837751040659525,
+           -0.9172491411791432,
+           -0.9470769202134011,
+           -0.9718790942533184,
+           -0.9904433012498969,
+           -1.0017511266516408,
+           -1.0049996552613545,
+           -0.999617125298416,
+           -0.985272350237404,
+           -0.9618777342844668,
+           -0.929585871301582,
+           -0.8887798804710375,
+           -0.8400577909029372,
+           -0.7842114377439394,
+           -0.7222004703839007,
+           -0.655122195631681,
+           -0.5841780821959134,
+           -0.5106378348915079,
+           -0.4358020056689184,
+           -0.36096414239215396,
+           -0.28737348446079847,
+           -0.2161991967147167,
+           -0.14849709006088566,
+           -0.0851797100408456,
+           -0.026990584843986445,
+           0.02551668563892458,
+           0.07199394543347351,
+           0.11230818994388107,
+           0.14654520445535277,
+           0.17500703159391406,
+           0.19820332705294777,
+           0.2168368228598399,
+           0.23178327193015677,
+           0.24406639271489644,
+           0.2548284646980921,
+           0.2652973409848685,
+           0.27675074028371677,
+           0.29047875476762264,
+           0.3077455606815748,
+           0.32975134383062776,
+           0.3575954515453569,
+           0.39224175634041575,
+           0.4344871648670052,
+           0.4849341301565161,
+           0.543967927409904,
+           0.6117393361140935,
+           0.6881532369707737,
+           0.7728634843393389,
+           0.8652742573040346,
+           0.9645479290079233,
+           1.0696193286407416,
+           1.1792161075648346,
+           1.2918847646037601,
+           1.40602173944113,
+           1.519908851070729,
+           1.6317522436488234,
+           1.7397239078450424,
+           1.8420047742886299,
+           1.9368283288208294,
+           2.022523678242466,
+           2.0975570006993305,
+           2.160570346732124,
+           2.210416814630725,
+           2.2461912057350424,
+           2.2672553697683897,
+           2.2732575746671557,
+           2.2641453766765625,
+           2.240171621285975,
+           2.201893370107253,
+           2.150163719037489,
+           2.086116644825864,
+           2.011145186269895,
+           1.926873428544898,
+           1.8351229106273252,
+           1.7378742126746456,
+           1.6372245991886845,
+           1.5353426918703412,
+           1.4344212208343878,
+           1.336628952425259,
+           1.2440629150081146,
+           1.1587020401983115,
+           1.0823633060966174,
+           1.0166614119358546,
+           0.9629729314823439,
+           0.922405787547479,
+           0.895774764589013,
+           0.8835836336565087,
+           0.8860143073251052,
+           0.9029232755709903,
+           0.9338454008224953,
+           0.9780049758720485,
+           1.034333776199623,
+           1.1014956727211647,
+           1.1779172160559959,
+           1.2618234628637597,
+           1.3512781920379588,
+           1.444227556526251,
+           1.5385461377328526,
+           1.632084315730797,
+           1.7227158411398094,
+           1.8083844941304508,
+           1.887148742554885,
+           1.9572233639782641,
+           2.017017074046754,
+           2.0651653042256473,
+           2.100557392959704,
+           2.1223575927365568,
+           2.130019447938843,
+           2.123293260979492,
+           2.102226533012394,
+           2.0671574363367418,
+           2.0187015442663463,
+           1.9577322065755014,
+           1.8853551106857336,
+           1.802877706810794,
+           1.7117742959722335,
+           1.6136476802136177,
+           1.510188352064568,
+           1.4031322534912878,
+           1.2942181619840873,
+           1.1851457624841697,
+           1.077535438605599,
+           0.9728907657815102,
+           0.8725646139081532,
+           0.777729669727973,
+           0.6893540720849411,
+           0.6081827192912905,
+           0.5347246605656637,
+           0.46924682656629796,
+           0.41177419141081684,
+           0.36209629434232177,
+           0.3197798874976105,
+           0.2841873211143637,
+           0.25450013286483597,
+           0.22974717743968065,
+           0.2088365192835867,
+           0.19059021832112552,
+           0.17378106791311007,
+           0.15717029789002238,
+           0.13954523444868608,
+           0.11975591346211852,
+           0.09674967418129667,
+           0.06960281559674988,
+           0.03754847644786938,
+           3.767851968994969e-16
+          ],
+          [
+           0,
+           -0.04587321033816182,
+           -0.09785720871197155,
+           -0.1557985245933822,
+           -0.21932650038156043,
+           -0.28786237001574416,
+           -0.3606342472363573,
+           -0.43669763646758714,
+           -0.5149609341555476,
+           -0.5942152567288679,
+           -0.6731678165080099,
+           -0.7504779718090767,
+           -0.8247950046053345,
+           -0.8947966303063215,
+           -0.9592272207672952,
+           -1.01693472419121,
+           -1.0669052941185864,
+           -1.1082946935512492,
+           -1.1404556181203258,
+           -1.1629601821781437,
+           -1.1756169313004843,
+           -1.178481880965719,
+           -1.1718632307426966,
+           -1.156319562442531,
+           -1.1326514953964981,
+           -1.1018869381913392,
+           -1.065260239657179,
+           -1.024185698554142,
+           -0.9802260372945291,
+           -0.9350565764815423,
+           -0.8904259607083531,
+           -0.8481143790442003,
+           -0.8098902935471428,
+           -0.7774667341647682,
+           -0.7524582373088591,
+           -0.7363394976570771,
+           -0.7304067684454549,
+           -0.7357429854296029,
+           -0.753187505211948,
+           -0.7833112417662703,
+           -0.8263978583075293,
+           -0.882431528218547,
+           -0.9510916220405471,
+           -1.0317545113817905,
+           -1.1235025090587398,
+           -1.225139792059282,
+           -1.3352149842467718,
+           -1.4520499132787443,
+           -1.573773904996157,
+           -1.6983628422795118,
+           -1.8236820974365349,
+           -1.9475323505064672,
+           -2.0676972328440266,
+           -2.1819916878100893,
+           -2.288309919550547,
+           -2.3846718072407262,
+           -2.469266695693577,
+           -2.5404935330936866,
+           -2.5969964113979356,
+           -2.6376946725973567,
+           -2.661806871962451,
+           -2.6688680344961844,
+           -2.658739799574783,
+           -2.6316132173096682,
+           -2.588004134418217,
+           -2.528741283110149,
+           -2.4549473594086404,
+           -2.3680135432285176,
+           -2.269568067399083,
+           -2.161439582888625,
+           -2.0456161893690283,
+           -1.9242011010059386,
+           -1.7993659945477836,
+           -1.6733031385685968,
+           -1.5481774278731681,
+           -1.4260794450303562,
+           -1.3089806418602052,
+           -1.1986916782271737,
+           -1.096824875092759,
+           -1.0047616354756435,
+           -0.9236255633325288,
+           -0.8542618694818573,
+           -0.7972234990367022,
+           -0.7527642502162409,
+           -0.7208389839290245,
+           -0.7011108513636028,
+           -0.692965297214615,
+           -0.6955304332748393,
+           -0.707703224921548,
+           -0.7281807952318023,
+           -0.7554960314250739,
+           -0.7880565789554039,
+           -0.824186232244287,
+           -0.8621676795686954,
+           -0.9002855341856092,
+           -0.9368685849256932,
+           -0.9703302271048618,
+           -0.9992060879061749,
+           -1.022187937962841,
+           -1.0381530807120414,
+           -1.0461885306256409,
+           -1.045609427609429,
+           -1.0359712842405762,
+           -1.0170758213055062,
+           -0.9889703113017569,
+           -0.9519405150453757,
+           -0.9064974591238185,
+           -0.8533584575770651,
+           -0.7934229259821088,
+           -0.7277436664422173,
+           -0.6574944145951191,
+           -0.5839345318556024,
+           -0.508371795418899,
+           -0.43212428336811154,
+           -0.3564823714655881,
+           -0.2826718514226147,
+           -0.21181914784695233,
+           -0.14491955352514674,
+           -0.08280932169516533,
+           -0.02614235158273242,
+           0.024627917673096803,
+           0.06926092640646553,
+           0.10773539785060003,
+           0.14024955376832898,
+           0.16721513230460097,
+           0.1892453602350255,
+           0.20713719012808898,
+           0.22184826344671904,
+           0.23446919946069103,
+           0.2461919334902657,
+           0.25827493329942475,
+           0.27200620670998776,
+           0.28866507454936324,
+           0.30948371929054286,
+           0.3356095302313965,
+           0.3680692504766614,
+           0.407735889670696,
+           0.45529930037008665,
+           0.5112412267539264,
+           0.5758155242407821,
+           0.6490341202393783,
+           0.7306591428909216,
+           0.8202014898334388,
+           0.9169259465953687,
+           1.0198627982674764,
+           1.1278257127664792,
+           1.239435513441094,
+           1.3531493070213643,
+           1.4672942938044131,
+           1.5801054640253174,
+           1.689766280707352,
+           1.7944513675740392,
+           1.8923701629485614,
+           1.9818104684825841,
+           2.0611808159323477,
+           2.129050596265543,
+           2.1841869427066016,
+           2.2255874318258266,
+           2.2525077627393117,
+           2.264483691615503,
+           2.2613466341560073,
+           2.243232499248041,
+           2.210583478910235,
+           2.1641426890192235,
+           2.1049417279675757,
+           2.0342813921303993,
+           1.9537059535895251,
+           1.8649715628821302,
+           1.7700094837257905,
+           1.6708849941637343,
+           1.5697528962149725,
+           1.4688106612314458,
+           1.370250298634711,
+           1.2762100700062202,
+           1.18872717775851,
+           1.1096925376002706,
+           1.040808697178297,
+           0.9835518907408445,
+           0.9391391231601292,
+           0.9085010585039089,
+           0.892261351416355,
+           0.8907229071770685,
+           0.903861392154061,
+           0.9313261444403227,
+           0.9724484589434487,
+           1.0262570463508736,
+           1.091500295469436,
+           1.1666748075656566,
+           1.250059523417601,
+           1.3397546324166683,
+           1.4337243414068614,
+           1.5298424917143052,
+           1.6259399481431804,
+           1.7198526451349407,
+           1.8094691637035512,
+           1.8927767284060546,
+           1.9679045560514565,
+           2.0331635560032786,
+           2.0870814740723875,
+           2.128432685822451,
+           2.156261977786163,
+           2.1699018033239175,
+           2.168982659978952,
+           2.1534364032386937,
+           2.1234924834591054,
+           2.0796672641188887,
+           2.022746746335054,
+           1.9537631826053437,
+           1.8739662081849289,
+           1.7847892478130432,
+           1.6878120655439457,
+           1.5847204135542652,
+           1.4772637998913758,
+           1.3672124336917797,
+           1.2563144185661042,
+           1.1462542504079702,
+           1.0386136352870985,
+           0.9348355774312148,
+           0.8361925983057412,
+           0.7437598377608236,
+           0.6583936599461608,
+           0.5807162434584395,
+           0.5111064806125966,
+           0.4496973487205771,
+           0.3963797509014696,
+           0.35081265939215955,
+           0.31243923470691964,
+           0.2805084433054513,
+           0.2541015584388925,
+           0.23216280699454606,
+           0.21353332248449075,
+           0.19698748336728944,
+           0.1812706586532197,
+           0.16513735062092777,
+           0.14738871823365982,
+           0.126908484601079,
+           0.10269627704915678,
+           0.07389751785669987,
+           0.03982907570372562,
+           3.9895443921830614e-16
+          ],
+          [
+           0,
+           -0.048344376921091774,
+           -0.10279754639776688,
+           -0.16309262514499542,
+           -0.22874848353353594,
+           -0.29908221953880004,
+           -0.3732273768179477,
+           -0.4501574325236587,
+           -0.5287139417728706,
+           -0.6076386025568852,
+           -0.6856084004459065,
+           -0.7612729093775858,
+           -0.8332927652607722,
+           -0.9003782946177143,
+           -0.9613272719467286,
+           -1.0150607971767116,
+           -1.0606563281091523,
+           -1.0973769710565804,
+           -1.1246962243181653,
+           -1.1423174814294987,
+           -1.1501877315028435,
+           -1.1485050391960792,
+           -1.1377195432947722,
+           -1.118527876655673,
+           -1.0918610772439021,
+           -1.058866226013811,
+           -1.0208822082639708,
+           -0.9794101467889517,
+           -0.9360791938238808,
+           -0.8926084909186791,
+           -0.8507662083782305,
+           -0.8123266561362767,
+           -0.779026513817108,
+           -0.7525212578038449,
+           -0.734342866538526,
+           -0.7258598618504413,
+           -0.7282406943355437,
+           -0.7424214058357355,
+           -0.7690784036650578,
+           -0.8086070617571907,
+           -0.8611067262492673,
+           -0.9263725505111221,
+           -1.0038944209913216,
+           -1.0928630644789583,
+           -1.1921832536548969,
+           -1.3004938553906473,
+           -1.416194299385784,
+           -1.5374768875254456,
+           -1.6623642206668272,
+           -1.7887508929800238,
+           -1.9144484976115406,
+           -2.0372329039535457,
+           -2.1548927082748555,
+           -2.2652777273776104,
+           -2.3663464001157273,
+           -2.456210984208937,
+           -2.533179485298081,
+           -2.5957933304417713,
+           -2.642859897447755,
+           -2.6734791321727456,
+           -2.68706362529143,
+           -2.6833516746499355,
+           -2.662413025428582,
+           -2.624647153907231,
+           -2.5707741374355764,
+           -2.501818328961875,
+           -2.4190852248951806,
+           -2.324132076027191,
+           -2.218732938813397,
+           -2.1048389949302537,
+           -1.9845350775252313,
+           -1.8599934302923073,
+           -1.7334257883309163,
+           -1.6070349061859868,
+           -1.482966667673547,
+           -1.3632638938917114,
+           -1.249822920693707,
+           -1.1443539460116128,
+           -1.0483460525490502,
+           -0.9630376948788208,
+           -0.8893933047826885,
+           -0.8280865181075814,
+           -0.7794903642081789,
+           -0.7436745892033021,
+           -0.7204101109763132,
+           -0.7091804313579827,
+           -0.7091996634763049,
+           -0.7194366739406796,
+           -0.7386446942129484,
+           -0.7653956267410368,
+           -0.7981181623121507,
+           -0.8351387382485532,
+           -0.8747243045897084,
+           -0.915125828742159,
+           -0.9546214590523651,
+           -0.9915582845245535,
+           -1.0243916709578278,
+           -1.0517212219542567,
+           -1.0723225047714708,
+           -1.0851737935014487,
+           -1.08947721267689,
+           -1.084673809818406,
+           -1.0704522419584082,
+           -1.0467509248610967,
+           -1.0137536603811372,
+           -0.9718789229784096,
+           -0.9217631466809209,
+           -0.8642385047519171,
+           -0.8003058121997697,
+           -0.7311033026342019,
+           -0.6578721328034739,
+           -0.5819195479224425,
+           -0.5045806966564199,
+           -0.42718011500186687,
+           -0.3509939025825991,
+           -0.277213592996756,
+           -0.20691267240046388,
+           -0.1410166287364008,
+           -0.08027731975825338,
+           -0.025252333678365217,
+           0.023710115207355834,
+           0.06648035883851429,
+           0.10315027395834728,
+           0.13403002678058387,
+           0.15963864720807258,
+           0.18068867756406645,
+           0.19806529610760717,
+           0.21280046077099615,
+           0.22604274988734824,
+           0.2390236908238929,
+           0.2530214614870833,
+           0.2693229212077822,
+           0.28918497470273813,
+           0.313796294407489,
+           0.3442404218936914,
+           0.3814612383868185,
+           0.42623173831108657,
+           0.4791269596697649,
+           0.5405018228891534,
+           0.6104745080388779,
+           0.68891586211022,
+           0.7754451767280026,
+           0.8694325160642645,
+           0.9700076088282845,
+           1.0760751511822697,
+           1.1863362034670895,
+           1.2993152068416844,
+           1.4133920002961833,
+           1.5268380876763805,
+           1.6378562916774067,
+           1.7446228401040837,
+           1.845330861413966,
+           1.9382342234388217,
+           2.0216906323816826,
+           2.094202919218002,
+           2.154457477333774,
+           2.201358877791294,
+           2.2340597755607816,
+           2.2519853293231926,
+           2.2548514864069507,
+           2.242676629947656,
+           2.21578624391649,
+           2.1748104193825233,
+           2.1206741981536936,
+           2.054580923546266,
+           1.9779889381989086,
+           1.8925821313880244,
+           1.8002349892095775,
+           1.702972936541292,
+           1.6029288765335312,
+           1.502296928596009,
+           1.4032844370781918,
+           1.3080633682965674,
+           1.2187222320846027,
+           1.137219655135463,
+           1.065340697247566,
+           1.0046569390141729,
+           0.956491282011587,
+           0.9218882922409974,
+           0.9015907871306523,
+           0.8960232189672631,
+           0.9052822467752345,
+           0.9291347183058688,
+           0.9670231080759694,
+           1.0180782805778381,
+           1.0811392741689752,
+           1.1547796349588895,
+           1.2373396752789274,
+           1.3269638918033586,
+           1.4216426574663004,
+           1.5192572019121497,
+           1.6176268197213324,
+           1.7145571958744161,
+           1.8078887150307252,
+           1.895543625717019,
+           1.9755709622900415,
+           2.046188185727243,
+           2.105818587440932,
+           2.15312360631873,
+           2.187029335426891,
+           2.206746638138815,
+           2.2117844503205877,
+           2.2019560117436425,
+           2.177377941995309,
+           2.1384622495865537,
+           2.085901533452819,
+           2.020647799430202,
+           1.9438854665705927,
+           1.8569992756237337,
+           1.761537931323511,
+           1.6591744083875506,
+           1.5516639260182459,
+           1.4408006454078712,
+           1.3283741681567849,
+           1.2161269101216543,
+           1.1057133951970548,
+           0.9986624577348311,
+           0.8963432621964792,
+           0.799935946290726,
+           0.710407571896161,
+           0.6284939296137602,
+           0.554687591348143,
+           0.4892324447069839,
+           0.43212477728325116,
+           0.38312081221263566,
+           0.34175043296164836,
+           0.30733667919426294,
+           0.279020450689535,
+           0.25578972625398966,
+           0.2365124926271171,
+           0.21997248729369392,
+           0.20490679114306307,
+           0.1900442637197316,
+           0.17414379643385255,
+           0.15603136793669456,
+           0.13463492064785323,
+           0.1090161372284474,
+           0.07839827907974505,
+           0.04218935357197897,
+           4.216340856778974e-16
+          ],
+          [
+           0,
+           -0.05082487193504389,
+           -0.10770263807634396,
+           -0.17025357981845007,
+           -0.23788859171717486,
+           -0.30982498604172537,
+           -0.3851078233642302,
+           -0.46263621044695163,
+           -0.5411938757476997,
+           -0.6194832194597802,
+           -0.6961619420294552,
+           -0.7698812849338578,
+           -0.8393248719653897,
+           -0.9032471195463154,
+           -0.960510191232334,
+           -1.0101185044365262,
+           -1.0512498557351555,
+           -1.0832823134830112,
+           -1.105816130840811,
+           -1.1186900561168969,
+           -1.1219915574744623,
+           -1.1160606320624107,
+           -1.101487031672562,
+           -1.0791009040543622,
+           -1.0499570168437986,
+           -1.01531289547098,
+           -0.9766013632623528,
+           -0.9353981172911079,
+           -0.8933851036737954,
+           -0.8523105676552035,
+           -0.8139467441137147,
+           -0.7800462207283598,
+           -0.7522980472341286,
+           -0.7322846788399314,
+           -0.7214408295383655,
+           -0.7210152719115794,
+           -0.732036555013243,
+           -0.7552835225070611,
+           -0.7912614016001537,
+           -0.8401841021133859,
+           -0.9019632174591331,
+           -0.9762040589407803,
+           -1.0622088855621674,
+           -1.1589873175810104,
+           -1.2652737476252025,
+           -1.3795513926016172,
+           -1.5000824670641897,
+           -1.6249438081822447,
+           -1.7520671476823058,
+           -1.8792831104666106,
+           -2.0043679259141016,
+           -2.125091768484359,
+           -2.2392676009163544,
+           -2.3447993771499687,
+           -2.4397284735405016,
+           -2.5222772557500317,
+           -2.590888753977767,
+           -2.644261509377996,
+           -2.6813787674406706,
+           -2.7015313270490076,
+           -2.704333503661813,
+           -2.68973182796361,
+           -2.658006273427761,
+           -2.6097639833643984,
+           -2.5459256458708555,
+           -2.4677048393438246,
+           -2.3765808376153243,
+           -2.274265518296313,
+           -2.162665156803207,
+           -2.043838008437178,
+           -1.919948678886245,
+           -1.793220357263943,
+           -1.665886033521943,
+           -1.5401398426506017,
+           -1.4180896710516608,
+           -1.3017121260484856,
+           -1.192810908579421,
+           -1.0929795432370746,
+           -1.003569311117107,
+           -0.9256631021300493,
+           -0.8600557577016398,
+           -0.8072413157465068,
+           -0.7674074013715796,
+           -0.7404368330987965,
+           -0.7259163397620172,
+           -0.7231521119162831,
+           -0.7311917477945925,
+           -0.7488520015599898,
+           -0.7747516045384173,
+           -0.8073483116061508,
+           -0.8449792278048828,
+           -0.8859033968922086,
+           -0.9283455856376842,
+           -0.9705401763424851,
+           -1.0107740857314873,
+           -1.0474276608066266,
+           -1.079012560563361,
+           -1.10420571512014,
+           -1.1218785586559166,
+           -1.131120856907042,
+           -1.1312585906772772,
+           -1.1218655102978243,
+           -1.102768138361885,
+           -1.0740441652607728,
+           -1.0360143498637717,
+           -0.9892282019040646,
+           -0.9344438791473183,
+           -0.8726028773186947,
+           -0.8048002204362887,
+           -0.7322509704203577,
+           -0.6562539648621707,
+           -0.578153758423993,
+           -0.49930178487386817,
+           -0.42101777223831693,
+           -0.3445524326410147,
+           -0.271052411408202,
+           -0.2015284179393367,
+           -0.13682737527175895,
+           -0.07760931840827454,
+           -0.024329646057877102,
+           0.022772810340654846,
+           0.06368158900239348,
+           0.0986021207389807,
+           0.12795498589995635,
+           0.15236308269428944,
+           0.17263304370716073,
+           0.189731388302032,
+           0.20475603707934756,
+           0.21890393712654235,
+           0.23343565031433222,
+           0.24963783872436665,
+           0.2687846393304249,
+           0.2920989527940523,
+           0.32071467780594404,
+           0.3556409025942357,
+           0.3977290194815668,
+           0.44764365780833854,
+           0.505838236879769,
+           0.5725358261520923,
+           0.6477158674867888,
+           0.7311071672650493,
+           0.8221874081348781,
+           0.920189265109636,
+           1.0241130427826564,
+           1.1327455837817872,
+           1.2446850374501357,
+           1.358370926165694,
+           1.4721188085331463,
+           1.584158717400642,
+           1.6926764493623674,
+           1.7958567037030817,
+           1.8919270146648166,
+           1.9792013929013157,
+           2.0561225908198733,
+           2.121301932314508,
+           2.1735556996204637,
+           2.211937147462354,
+           2.235763315492257,
+           2.244635931802416,
+           2.2384558401067993,
+           2.217430537621603,
+           2.182074575972434,
+           2.13320274957489,
+           2.0719161706575218,
+           1.9995815031321578,
+           1.917803794608986,
+           1.8283935028841605,
+           1.733328456318828,
+           1.6347116131380417,
+           1.5347255896902245,
+           1.4355850095062732,
+           1.3394877815342585,
+           1.2485664457702033,
+           1.1648407268797323,
+           1.090172411206902,
+           1.026223610366376,
+           0.9744193966499852,
+           0.9359156936154872,
+           0.9115731819200134,
+           0.9019378386950353,
+           0.9072285719697158,
+           0.9273322436406278,
+           0.9618061993393922,
+           1.009888245522529,
+           1.0705138375275736,
+           1.142340071498484,
+           1.2237759121326062,
+           1.3130179410489105,
+           1.4080907807916774,
+           1.5068912402071029,
+           1.6072351407999372,
+           1.7069057227630098,
+           1.80370249512365,
+           1.895489387663093,
+           1.9802410830594852,
+           2.056086455527678,
+           2.121348115862228,
+           2.1745771603866673,
+           2.2145823404377434,
+           2.240453006710124,
+           2.2515753356448847,
+           2.247641509287421,
+           2.228651691617524,
+           2.1949088190429755,
+           2.147006396257108,
+           2.08580965673597,
+           2.012430605680874,
+           1.9281976083293069,
+           1.8346203147332154,
+           1.7333508202361418,
+           1.6261420463689447,
+           1.5148043876937005,
+           1.401161704837051,
+           1.2870077517985414,
+           1.1740641064934145,
+           1.0639406279606292,
+           0.9580993929561025,
+           0.8578229706020404,
+           0.764187778795607,
+           0.678043133128785,
+           0.5999964515115688,
+           0.5304049192554717,
+           0.4693737540591103,
+           0.4167610423010534,
+           0.37218895150548564,
+           0.33506096297587484,
+           0.30458461741315657,
+           0.2797991286203426,
+           0.2596070995734771,
+           0.24280947420881802,
+           0.22814277973365754,
+           0.2143176600436247,
+           0.20005767223972237,
+           0.18413731595511862,
+           0.16541828923471225,
+           0.14288301440776643,
+           0.11566455145898434,
+           0.08307211292779616,
+           0.04461151087734342,
+           4.446490257965823e-16
+          ],
+          [
+           0,
+           -0.053294846070557046,
+           -0.11253263590053943,
+           -0.17722243496677328,
+           -0.24667067906534323,
+           -0.3200002133370844,
+           -0.3961745880282651,
+           -0.4740269717272567,
+           -0.5522929208747923,
+           -0.6296461417864726,
+           -0.7047363008732069,
+           -0.7762278822673765,
+           -0.8428390611240805,
+           -0.9033795562905182,
+           -0.9567864479822134,
+           -1.002156994064985,
+           -1.0387775513538378,
+           -1.0661478042151857,
+           -1.0839996193257921,
+           -1.0923099798054818,
+           -1.0913076007546414,
+           -1.0814729877766684,
+           -1.063531866358923,
+           -1.038442078855845,
+           -1.0073742130244314,
+           -0.9716863873982844,
+           -0.9328937701828717,
+           -0.892633545982845,
+           -0.8526261650387913,
+           -0.8146338096860893,
+           -0.7804170898831324,
+           -0.7516910318859971,
+           -0.7300814500835253,
+           -0.7170827909138809,
+           -0.7140185095951936,
+           -0.7220049857259547,
+           -0.7419199039125383,
+           -0.7743759223569342,
+           -0.8197003282661826,
+           -0.8779212370266531,
+           -0.9487607357705611,
+           -1.0316352050618864,
+           -1.1256628790271699,
+           -1.2296785286053424,
+           -1.3422549790060982,
+           -1.461731005221934,
+           -1.5862449926603122,
+           -1.7137736075245054,
+           -1.8421745970032892,
+           -1.9692327357255583,
+           -2.092707854880104,
+           -2.2103838359024244,
+           -2.3201174230729986,
+           -2.4198857094792454,
+           -2.507831178611832,
+           -2.5823032387609457,
+           -2.6418952680504026,
+           -2.685476292464723,
+           -2.7122165450680886,
+           -2.7216062987415053,
+           -2.713467523683108,
+           -2.68795809076954,
+           -2.645568418538279,
+           -2.587110640727854,
+           -2.5137005486495623,
+           -2.426732733849635,
+           -2.327849517395085,
+           -2.2189043987728154,
+           -2.1019208862730694,
+           -1.9790476787135176,
+           -1.8525112528426626,
+           -1.7245669697095793,
+           -1.5974498452987007,
+           -1.473326135060518,
+           -1.354246858558432,
+           -1.2421043399151088,
+           -1.1385927633590334,
+           -1.0451736428571636,
+           -0.9630469830691655,
+           -0.8931287686937607,
+           -0.8360352641645084,
+           -0.7920744394207355,
+           -0.7612446642243829,
+           -0.7432406374764672,
+           -0.7374663435287871,
+           -0.7430546588615077,
+           -0.7588930738276058,
+           -0.783654849319026,
+           -0.8158348007058479,
+           -0.853788794322406,
+           -0.8957759576952141,
+           -0.9400025456248543,
+           -0.984666371522817,
+           -1.028000707783881,
+           -1.0683165804916301,
+           -1.1040424317823179,
+           -1.133760196448324,
+           -1.1562369359400684,
+           -1.17045129034348,
+           -1.175614144174645,
+           -1.1711830515126216,
+           -1.1568701263027588,
+           -1.132643270566167,
+           -1.0987207825512337,
+           -1.0555595543129825,
+           -1.003837229614596,
+           -0.9444288443794644,
+           -0.8783786094093534,
+           -0.8068676153052792,
+           -0.7311783395017427,
+           -0.6526569125838877,
+           -0.5726741537062259,
+           -0.4925864116964288,
+           -0.41369724868587443,
+           -0.3372209769039334,
+           -0.26424900731452744,
+           -0.19571989241704005,
+           -0.132393846747184,
+           -0.07483240992794245,
+           -0.0233837815658374,
+           0.02182579168376933,
+           0.06089435515793653,
+           0.0941402538068797,
+           0.12209191649232232,
+           0.14547168790945506,
+           0.1651741350135248,
+           0.18223939989256382,
+           0.1978223015250419,
+           0.21315800147222394,
+           0.22952514040565195,
+           0.24820742110764746,
+           0.27045465743467134,
+           0.2974443265526399,
+           0.33024465304702555,
+           0.36978021845299053,
+           0.4168010291795215,
+           0.471855891196802,
+           0.5352708333045121,
+           0.6071331949419118,
+           0.6872818524685759,
+           0.7753039031795831,
+           0.8705379628857738,
+           0.9720840647803619,
+           1.078819978744836,
+           1.1894236054565284,
+           1.3024009427985312,
+           1.4161189771010474,
+           1.5288427223341183,
+           1.638775519817265,
+           1.7441016221399188,
+           1.8430300200917522,
+           1.9338384321858346,
+           2.0149163638856264,
+           2.0848061583221082,
+           2.1422410018382574,
+           2.1861789151848265,
+           2.215831853028074,
+           2.2306891484225235,
+           2.2305346723025776,
+           2.2154572276204734,
+           2.1858538598625215,
+           2.1424259363505187,
+           2.0861680218006207,
+           2.018349752769749,
+           1.940491084562439,
+           1.8543314466856613,
+           1.7617934930128873,
+           1.6649422667387634,
+           1.5659407146490252,
+           1.467002577349741,
+           1.3703437495906916,
+           1.2781332459787658,
+           1.19244492115139,
+           1.1152110794804195,
+           1.04817906790001,
+           0.9928718774659527,
+           0.9505536863808258,
+           0.9222011616902567,
+           0.9084812014604983,
+           0.9097356472639403,
+           0.9259733319129326,
+           0.9568696535970167,
+           1.0017736891169393,
+           1.0597226801085715,
+           1.1294635513578115,
+           1.2094809537721336,
+           1.298031170341217,
+           1.39318108523171,
+           1.4928512973689638,
+           1.5948623633344878,
+           1.696983082477564,
+           1.7969796915256695,
+           1.892664817756633,
+           1.9819450493701858,
+           2.062866018790217,
+           2.133653958290343,
+           2.192752775961582,
+           2.238855811421029,
+           2.2709315620260124,
+           2.2882428184563777,
+           2.2903588096981666,
+           2.27716012773076,
+           2.2488363773951865,
+           2.20587667269923,
+           2.149053272884506,
+           2.079398815730314,
+           1.9981777577916051,
+           1.9068527678584024,
+           1.80704693757027,
+           1.700502768985287,
+           1.5890389706962178,
+           1.474506140115706,
+           1.3587424287666106,
+           1.2435302794296896,
+           1.1305552891089359,
+           1.0213681909334618,
+           0.9173508629230541,
+           0.8196871642031687,
+           0.7293392725107716,
+           0.6470300539080552,
+           0.5732318401348366,
+           0.5081618249064512,
+           0.4517841218325655,
+           0.40381835772774866,
+           0.3637545101393728,
+           0.33087354105745226,
+           0.30427323390911154,
+           0.2828985116847357,
+           0.26557540360348314,
+           0.25104773883571957,
+           0.23801558064721687,
+           0.22517437450413436,
+           0.21125377013022686,
+           0.19505509052845796,
+           0.1754864601906527,
+           0.15159466908517938,
+           0.12259293686679137,
+           0.08788385083802187,
+           0.04707687871893102,
+           4.678182516238676e-16
+          ],
+          [
+           0,
+           -0.055734257050528015,
+           -0.11724782139805347,
+           -0.18394119994047797,
+           -0.2550208852029298,
+           -0.32952150188516877,
+           -0.4063328914946498,
+           -0.48423141989954255,
+           -0.5619146808678058,
+           -0.6380386779759757,
+           -0.7112564999965387,
+           -0.7802574627393721,
+           -0.8438056744326641,
+           -0.900776992524103,
+           -0.9501933770347123,
+           -0.991253708410246,
+           -1.0233602246491291,
+           -1.0461398411959222,
+           -1.0594597449766443,
+           -1.06343679783243,
+           -1.0584404408894759,
+           -1.04508895617724,
+           -1.0242391109444215,
+           -0.9969693793773295,
+           -0.9645571015405109,
+           -0.9284500961729169,
+           -0.8902333885211924,
+           -0.8515918430104745,
+           -0.8142695999675078,
+           -0.780027303018925,
+           -0.7505981669297046,
+           -0.7276439728637415,
+           -0.7127120883228971,
+           -0.7071945920039241,
+           -0.7122905398338406,
+           -0.7289723385036839,
+           -0.7579570985659004,
+           -0.7996837228464788,
+           -0.8542963503563694,
+           -0.921634624358077,
+           -1.001231089445537,
+           -1.0923158504329546,
+           -1.1938284497387495,
+           -1.3044367441201652,
+           -1.4225623903906457,
+           -1.5464123873586144,
+           -1.6740159716759546,
+           -1.8032660322813732,
+           -1.9319640949708676,
+           -2.0578678381447877,
+           -2.1787400352351067,
+           -2.2923977803649542,
+           -2.396760842440728,
+           -2.4898980094551195,
+           -2.5700703289309157,
+           -2.635770221127899,
+           -2.68575553718337,
+           -2.7190777524649237,
+           -2.73510362323113,
+           -2.7335297888859125,
+           -2.7143899689366684,
+           -2.6780545791743,
+           -2.6252227713234015,
+           -2.5569070800939793,
+           -2.4744110368339007,
+           -2.379300275573411,
+           -2.2733678111218767,
+           -2.158594306286751,
+           -2.037104262904832,
+           -1.9111191663597404,
+           -1.7829086833186647,
+           -1.6547410558765097,
+           -1.5288338511226118,
+           -1.4073062129958276,
+           -1.292133723506667,
+           -1.185106913995454,
+           -1.0877943757295736,
+           -1.0015113050979676,
+           -0.9272941847660167,
+           -0.8658821517227727,
+           -0.8177054398978857,
+           -0.782881112971014,
+           -0.7612161263736206,
+           -0.75221758062877,
+           -0.7551098554234204,
+           -0.7688581493845842,
+           -0.7921977984471741,
+           -0.8236686096564468,
+           -0.8616533305372335,
+           -0.9044192795970822,
+           -0.9501620933691267,
+           -0.9970505012929082,
+           -1.043271022679291,
+           -1.0870714903386445,
+           -1.1268023428204084,
+           -1.1609546905976207,
+           -1.1881942492704716,
+           -1.2073903426948072,
+           -1.217639308058357,
+           -1.218281780048964,
+           -1.208913488714315,
+           -1.1893893714315567,
+           -1.159820969417536,
+           -1.1205672491510492,
+           -1.0722191546918645,
+           -1.01557835402984,
+           -0.9516307873621969,
+           -0.8815157539771098,
+           -0.8064913840226561,
+           -0.7278974291533634,
+           -0.6471163697169218,
+           -0.5655338742221191,
+           -0.48449965841123555,
+           -0.40528977610829414,
+           -0.3290713325624214,
+           -0.256870544347685,
+           -0.18954497974406845,
+           -0.12776070222443903,
+           -0.07197491005599826,
+           -0.02242452039689152,
+           0.02087900968938332,
+           0.058148496202599924,
+           0.08981351259864742,
+           0.11650674857612162,
+           0.1390446065399292,
+           0.1584025500529687,
+           0.17568585649101962,
+           0.19209654738826396,
+           0.20889737151116278,
+           0.22737379493181314,
+           0.24879500725422776,
+           0.2743749822558262,
+           0.30523463376734294,
+           0.3423660835204939,
+           0.38660000750800017,
+           0.43857695234616134,
+           0.4987234150542284,
+           0.5672333609969553,
+           0.6440557184279047,
+           0.728888237519537,
+           0.8211779407340173,
+           0.9201282239073892,
+           1.024712497689857,
+           1.133694091271458,
+           1.245651978848269,
+           1.3590117381249065,
+           1.4720810131302944,
+           1.5830886342258077,
+           1.6902264494564558,
+           1.7916928458750327,
+           1.885736889122033,
+           1.9707019857132366,
+           2.045067975857433,
+           2.1074905952087364,
+           2.1568373010844795,
+           2.1922185410229456,
+           2.2130136471581303,
+           2.2188906662124626,
+           2.209819578895241,
+           2.1860785206417344,
+           2.1482527840749226,
+           2.097226558194967,
+           2.034167535815843,
+           1.9605046948329592,
+           1.8778997262321582,
+           1.7882127382076818,
+           1.6934630074739834,
+           1.5957856723198167,
+           1.4973853640907602,
+           1.4004878520480823,
+           1.3072908289684195,
+           1.2199149900850457,
+           1.1403565553576898,
+           1.0704423546064306,
+           1.011788537453669,
+           0.9657638866484284,
+           0.9334586061969624,
+           0.9156593273732908,
+           0.9128309292363631,
+           0.9251056092851262,
+           0.9522794682454522,
+           0.9938166948726875,
+           1.0488612563992552,
+           1.1162558222402392,
+           1.1945674771190895,
+           1.2821196190573,
+           1.3770292915896023,
+           1.4772490716642903,
+           1.5806125280647219,
+           1.6848821824182971,
+           1.7877988479330804,
+           1.8871311912759052,
+           1.9807243611672223,
+           2.0665465533219307,
+           2.142732434633029,
+           2.207622428631286,
+           2.259796967280763,
+           2.29810493852665,
+           2.3216857016168304,
+           2.329984199548158,
+           2.3227588661619745,
+           2.300082200290983,
+           2.262334056643399,
+           2.210187878451119,
+           2.1445902660137355,
+           2.0667344340083127,
+           1.9780282549390513,
+           1.8800577128628324,
+           1.7745466974835116,
+           1.6633141513171046,
+           1.5482296399314714,
+           1.4311684459282643,
+           1.3139672906936044,
+           1.1983817640078585,
+           1.0860464910596184,
+           0.9784389906002339,
+           0.8768480788712563,
+           0.7823475540810184,
+           0.6957757586514021,
+           0.617721464688261,
+           0.5485163659811356,
+           0.4882342913930278,
+           0.4366970839899772,
+           0.393486921956499,
+           0.3579646954564496,
+           0.32929390217049714,
+           0.3064693870425601,
+           0.28835013220678535,
+           0.2736952041045069,
+           0.2612018888765951,
+           0.24954499608842265,
+           0.23741628594286826,
+           0.2235629769342072,
+           0.2068243192938917,
+           0.18616527381163236,
+           0.16070641426653684,
+           0.12974927274564263,
+           0.09279646797166102,
+           0.04956609432271983,
+           4.909565874815401e-16
+          ],
+          [
+           0,
+           -0.0581230653712635,
+           -0.12180899817176649,
+           -0.19035342767092991,
+           -0.262868384560535,
+           -0.3383073981366598,
+           -0.4154951659253733,
+           -0.4931610100415807,
+           -0.5699752340758651,
+           -0.644587416432478,
+           -0.7156656227909461,
+           -0.7819354931133775,
+           -0.8422181580949477,
+           -0.8954659662094685,
+           -0.9407950549144855,
+           -0.9775138768711408,
+           -1.0051468922957676,
+           -1.0234527593052167,
+           -1.032436492340255,
+           -1.032355211001156,
+           -1.0237172640990844,
+           -1.0072746823453032,
+           -0.9840090836351781,
+           -0.9551113230471158,
+           -0.9219553412305942,
+           -0.8860668157221742,
+           -0.849087356082349,
+           -0.8127351021231254,
+           -0.778762681871289,
+           -0.748913559778644,
+           -0.7248778541220492,
+           -0.70824872423674,
+           -0.7004804225631834,
+           -0.7028490735072374,
+           -0.7164171815423354,
+           -0.7420027862096624,
+           -0.7801540737164245,
+           -0.8311301262914936,
+           -0.8948883444467967,
+           -0.9710789173664699,
+           -1.0590465467111774,
+           -1.157839453345309,
+           -1.2662255191868461,
+           -1.382715241906704,
+           -1.5055910128687329,
+           -1.6329420726378068,
+           -1.7627043574559262,
+           -1.892704327793694,
+           -2.0207057694724617,
+           -2.144458481438286,
+           -2.2617477139782918,
+           -2.370443198290136,
+           -2.468546613460348,
+           -2.5542363700052615,
+           -2.6259086494197104,
+           -2.682213725236697,
+           -2.722086700865109,
+           -2.744771930298504,
+           -2.7498405365136076,
+           -2.737200605399465,
+           -2.7070998064214735,
+           -2.660120370718132,
+           -2.5971665385897382,
+           -2.5194447669606914,
+           -2.428437159037495,
+           -2.3258687388709802,
+           -2.213669338964985,
+           -2.0939309959249552,
+           -1.9688618543357905,
+           -1.8407376600556602,
+           -1.7118519789644375,
+           -1.5844663046036722,
+           -1.4607612174573334,
+           -1.342789729903065,
+           -1.232433894854588,
+           -1.1313656742268554,
+           -1.0410129576288525,
+           -0.9625314947497214,
+           -0.8967833598925463,
+           -0.8443224076079855,
+           -0.80538700831653,
+           -0.7799001763677738,
+           -0.7674770245003152,
+           -0.7674393025125242,
+           -0.7788366084424755,
+           -0.800473701822972,
+           -0.8309432044892293,
+           -0.8686628484679957,
+           -0.9119163257082216,
+           -0.9588967133363805,
+           -1.0077513926547506,
+           -1.0566273515317415,
+           -1.1037157587748243,
+           -1.1472947254614214,
+           -1.1857692212844062,
+           -1.2177071923390839,
+           -1.2418710284068342,
+           -1.2572436500721644,
+           -1.2630486258336404,
+           -1.258763883194046,
+           -1.2441287416600153,
+           -1.219144165521559,
+           -1.184066305952018,
+           -1.139393571070128,
+           -1.085847624911424,
+           -1.0243488677189163,
+           -0.9559870868135931,
+           -0.8819880861480708,
+           -0.8036772005425223,
+           -0.7224406751415741,
+           -0.6396859399945223,
+           -0.5568018326634883,
+           -0.47511981788261104,
+           -0.3958772226798488,
+           -0.3201834488558067,
+           -0.24899004376623465,
+           -0.18306540706381288,
+           -0.12297478806785403,
+           -0.06906608888850382,
+           -0.02146183588982898,
+           0.019942479585925633,
+           0.05547365698461408,
+           0.08566977200211627,
+           0.11126318892849597,
+           0.13315805340741615,
+           0.15240286388443086,
+           0.17015884947370366,
+           0.18766499284940913,
+           0.20620062623796173,
+           0.2270465943606105,
+           0.2514460185587998,
+           0.28056571027125654,
+           0.31545926913140726,
+           0.35703286150111574,
+           0.40601461020513785,
+           0.46292843717874815,
+           0.5280730898929149,
+           0.6015069525325554,
+           0.6830390972120549,
+           0.7722268726581037,
+           0.8683801617249437,
+           0.9705722689957816,
+           1.07765722984008,
+           1.188293166915964,
+           1.3009711634018408,
+           1.4140489781748045,
+           1.525788800380808,
+           1.6343981326184949,
+           1.7380728060601733,
+           1.8350410694825727,
+           1.923607658993295,
+           2.0021967471839024,
+           2.069392689811529,
+           2.123977534520084,
+           2.1649643284985576,
+           2.1916253586286945,
+           2.203514576282091,
+           2.20048359662194,
+           2.182690815702558,
+           2.150603354097696,
+           2.10499170917894,
+           2.0469171752549875,
+           1.9777122672180842,
+           1.8989545547783615,
+           1.8124344765697842,
+           1.7201178523700766,
+           1.6241039436985465,
+           1.5265800248584105,
+           1.4297735152827764,
+           1.335902787598615,
+           1.2471278025282715,
+           1.1655017306503528,
+           1.0929247018690775,
+           1.0311007766097553,
+           0.9814991593654527,
+           0.9453205770140769,
+           0.9234696236667357,
+           0.9165337336082952,
+           0.9247692875433846,
+           0.9480951886564059,
+           0.9860940680281424,
+           1.0380210980242741,
+           1.1028202117806862,
+           1.1791473512451445,
+           1.2654001996655675,
+           1.3597537009895533,
+           1.4602005320834675,
+           1.564595577304151,
+           1.6707033615785405,
+           1.776247330018368,
+           1.8789598208508447,
+           1.9766315650555546,
+           2.067159560852273,
+           2.1485922136845175,
+           2.219170701510332,
+           2.277365619313646,
+           2.3219080734451336,
+           2.3518145327998603,
+           2.366404896567942,
+           2.365313403587624,
+           2.3484921821175266,
+           2.316207416854968,
+           2.269028287892508,
+           2.2078090096686633,
+           2.1336644625941426,
+           2.0479400619080796,
+           1.9521766437485162,
+           1.848071264129294,
+           1.73743489971733,
+           1.6221481077770286,
+           1.5041157447853033,
+           1.3852218580696642,
+           1.267285852108001,
+           1.1520209912611694,
+           1.0409962347681339,
+           0.9356023095437306,
+           0.8370228140058378,
+           0.7462110146887923,
+           0.6638728501100449,
+           0.5904564969700389,
+           0.5261486862962725,
+           0.4708777858000567,
+           0.42432349379400197,
+           0.3859328237957552,
+           0.35494190156893124,
+           0.3304029517460677,
+           0.3112157229342629,
+           0.29616249149939466,
+           0.28394569774191486,
+           0.2732272060372146,
+           0.2626681442236482,
+           0.2509682679380298,
+           0.2369038129066604,
+           0.21936284190886396,
+           0.19737716208639838,
+           0.17014998068900455,
+           0.13707858084900407,
+           0.09777143066292959,
+           0.052059285367366454,
+           5.138764760463572e-16
+          ],
+          [
+           0,
+           -0.06044143155310596,
+           -0.1261778823891616,
+           -0.19640478415747814,
+           -0.2701461107927795,
+           -0.346282240697375,
+           -0.42358198155992494,
+           -0.5007379076220282,
+           -0.5764040709905911,
+           -0.6492350843602732,
+           -0.7179255339095421,
+           -0.7812486691746771,
+           -0.8380933317269005,
+           -0.8874981261380742,
+           -0.9286819040085379,
+           -0.9610697230889357,
+           -0.9843135564936151,
+           -0.9983071588645445,
+           -1.0031946438110546,
+           -0.9993724863340259,
+           -0.9874848312502787,
+           -0.9684121596648435,
+           -0.9432535359955486,
+           -0.9133028236423291,
+           -0.8800194139328219,
+           -0.8449941565044656,
+           -0.8099113061568496,
+           -0.776507408191085,
+           -0.7465281285995943,
+           -0.7216840949937434,
+           -0.7036068472861595,
+           -0.693806002962097,
+           -0.6936287200409351,
+           -0.7042224919911731,
+           -0.7265022340420784,
+           -0.7611225213024416,
+           -0.8084557182276797,
+           -0.8685765991937303,
+           -0.9412539046387899,
+           -1.0259491102127953,
+           -1.1218225117193523,
+           -1.2277465506328662,
+           -1.3423261280043979,
+           -1.463925482995901,
+           -1.5907010503426258,
+           -1.72063956274663,
+           -1.8516005332307095,
+           -1.9813621420918597,
+           -2.1076694660453548,
+           -2.2282839256338147,
+           -2.341032792554447,
+           -2.4438575921328836,
+           -2.534860257957285,
+           -2.6123459452032547,
+           -2.674861485268408,
+           -2.7212285651817463,
+           -2.7505708384347356,
+           -2.762334316425674,
+           -2.756300548166918,
+           -2.7325922664339166,
+           -2.6916713569957205,
+           -2.634329189622417,
+           -2.561669530789827,
+           -2.475084433989107,
+           -2.376223670019375,
+           -2.266958412548826,
+           -2.149340029860172,
+           -2.025554948758862,
+           -1.897876648332342,
+           -1.7686159073914944,
+           -1.6400704684168046,
+           -1.5144752917504005,
+           -1.3939545563902098,
+           -1.2804765185149527,
+           -1.1758122669423188,
+           -1.081499317893873,
+           -0.998810872113552,
+           -0.9287314185161489,
+           -0.8719392135559627,
+           -0.8287959982241944,
+           -0.7993441391211734,
+           -0.7833112007163999,
+           -0.7801217771025909,
+           -0.7889162376460955,
+           -0.8085758761828686,
+           -0.8377538018208418,
+           -0.8749107746678361,
+           -0.9183550751683159,
+           -0.9662854039582949,
+           -1.0168357424218202,
+           -1.068121064017025,
+           -1.1182827738361005,
+           -1.1655327689903776,
+           -1.208195054800681,
+           -1.244743920281873,
+           -1.2738377692510237,
+           -1.2943478181744459,
+           -1.3053810056726862,
+           -1.30629660803242,
+           -1.2967162163564152,
+           -1.2765269000574384,
+           -1.2458775540241864,
+           -1.2051685986326055,
+           -1.1550353685490677,
+           -1.0963256838122497,
+           -1.0300722410677992,
+           -0.957460590479115,
+           -0.8797935715901711,
+           -0.7984531666172286,
+           -0.7148607902099078,
+           -0.6304370691840754,
+           -0.5465621732817695,
+           -0.4645377385256488,
+           -0.3855513787555165,
+           -0.31064470967468155,
+           -0.2406857150411637,
+           -0.17634616894666658,
+           -0.11808469439436965,
+           -0.06613589002604282,
+           -0.02050579763625605,
+           0.01902618290587944,
+           0.05289899331197486,
+           0.08175546000346538,
+           0.10642207059409882,
+           0.12788352457178767,
+           0.14725273614149423,
+           0.165737086969941,
+           0.18460182596565372,
+           0.20513158969692658,
+           0.2285910686347846,
+           0.25618586977275176,
+           0.2890246246444444,
+           0.32808336333474725,
+           0.3741731204387458,
+           0.4279116594034154,
+           0.4897000992567062,
+           0.5597051049321938,
+           0.6378471622956026,
+           0.7237953050728061,
+           0.8169684970194682,
+           0.9165437029696677,
+           1.0214705111172893,
+           1.1304920003298649,
+           1.2421713847201545,
+           1.3549238171896156,
+           1.467052598025259,
+           1.5767889173280247,
+           1.6823341640766267,
+           1.7819037624601175,
+           1.8737714496298274,
+           1.9563128894757682,
+           2.028047525004057,
+           2.087677607276435,
+           2.1341234008840813,
+           2.1665536531152885,
+           2.1844105242608545,
+           2.1874283072246645,
+           2.1756454125990685,
+           2.1494092570194896,
+           2.109373863977513,
+           2.056490163145152,
+           1.9919891522981847,
+           1.9173582607389836,
+           1.8343114203944426,
+           1.7447535063667559,
+           1.6507399487865866,
+           1.554432438878578,
+           1.4580517511800448,
+           1.3638287783721879,
+           1.2739549233080105,
+           1.1905330133146779,
+           1.1155298941520353,
+           1.0507318252560123,
+           0.9977037349069181,
+           0.9577533052304551,
+           0.9319007445870664,
+           0.9208549716398174,
+           0.9249967844325377,
+           0.9443694228159666,
+           0.9786767575332309,
+           1.0272891584683599,
+           1.0892569123674452,
+           1.1633308811914675,
+           1.2479899205089307,
+           1.34147441716114,
+           1.4418251607252015,
+           1.5469266375725603,
+           1.6545537326216597,
+           1.7624207447193203,
+           1.8682315688618152,
+           1.9697298734399884,
+           2.064748103941318,
+           2.1512541759496293,
+           2.227394779045486,
+           2.2915342978524693,
+           2.342288464889707,
+           2.378551989390946,
+           2.3995195536348897,
+           2.4046997299643516,
+           2.3939215435736574,
+           2.3673335840889695,
+           2.3253957485878383,
+           2.2688638756018658,
+           2.1987676994943373,
+           2.116382713259439,
+           2.0231966713911302,
+           1.9208715895370532,
+           1.8112022011686097,
+           1.6960719109843856,
+           1.5774073383401304,
+           1.4571325704288767,
+           1.337124243658252,
+           1.2191685428133658,
+           1.104921151961681,
+           0.9958711101197377,
+           0.893309420555511,
+           0.7983031379090973,
+           0.7116755152480367,
+           0.6339926373261664,
+           0.5655568006155377,
+           0.5064067292947492,
+           0.4563245436024955,
+           0.4148492271254978,
+           0.38129617692617523,
+           0.35478226898071935,
+           0.33425573495700206,
+           0.3185300282960812,
+           0.3063207607870086,
+           0.29628471771978704,
+           0.2870599120461771,
+           0.27730561691202577,
+           0.2657413219187123,
+           0.25118359131599705,
+           0.23257986114071624,
+           0.2090382955610613,
+           0.1798529282174474,
+           0.14452343946316937,
+           0.10276906190569435,
+           0.05453626092757246,
+           5.363898026253207e-16
+          ],
+          [
+           0,
+           -0.06266991286827096,
+           -0.13031748700477427,
+           -0.2020436008934985,
+           -0.27679144864584915,
+           -0.35337695428452426,
+           -0.43052289796710813,
+           -0.5068958462035661,
+           -0.581144903095905,
+           -0.6519412497440669,
+           -0.7180174155098008,
+           -0.7782052284350124,
+           -0.8314714227170804,
+           -0.8769499380151323,
+           -0.9139700271005184,
+           -0.9420793929465843,
+           -0.9610617011749919,
+           -0.9709479557234,
+           -0.9720213811225175,
+           -0.9648156199729033,
+           -0.9501062249476203,
+           -0.9288955966240398,
+           -0.9023916873360074,
+           -0.8719809527748246,
+           -0.8391961831684808,
+           -0.8056799807260256,
+           -0.7731447662139025,
+           -0.7433302920597119,
+           -0.7179597098165684,
+           -0.6986952843249193,
+           -0.6870948642781041,
+           -0.6845702086067554,
+           -0.6923482303069712,
+           -0.7114361548946355,
+           -0.7425915010850567,
+           -0.7862976787131234,
+           -0.8427458660409228,
+           -0.9118236786730377,
+           -0.9931109789709744,
+           -1.0858830021239352,
+           -1.1891207971319075,
+           -1.3015288022641147,
+           -1.4215591994757575,
+           -1.5474425251226533,
+           -1.6772238592439634,
+           -1.8088037765348168,
+           -1.9399831223650859,
+           -2.068510579808464,
+           -2.192131921072031,
+           -2.3086397907987566,
+           -2.415922850638966,
+           -2.512013124754383,
+           -2.595130424336379,
+           -2.6637227949037943,
+           -2.7165020215395472,
+           -2.752473342141168,
+           -2.7709586544310354,
+           -2.7716126556185934,
+           -2.7544315205193484,
+           -2.719753900564102,
+           -2.6682542081863145,
+           -2.600928334130586,
+           -2.519072124829234,
+           -2.424253118779121,
+           -2.3182762006395103,
+           -2.2031439756803137,
+           -2.0810127917438095,
+           -1.9541454380216334,
+           -1.8248616272227136,
+           -1.6954874182546533,
+           -1.5683047591567383,
+           -1.4455023241849339,
+           -1.3291287848353797,
+           -1.2210495930710266,
+           -1.122908267625947,
+           -1.0360930631752017,
+           -0.9617097701247868,
+           -0.9005612430569316,
+           -0.8531340921497675,
+           -0.8195927982057686,
+           -0.7997813325359383,
+           -0.7932321822564378,
+           -0.7991825039847292,
+           -0.8165969588127102,
+           -0.8441966229321824,
+           -0.8804932252471159,
+           -0.9238278391926186,
+           -0.9724130537839519,
+           -1.0243775710847067,
+           -1.0778121256495217,
+           -1.1308155972501366,
+           -1.1815401918412902,
+           -1.2282345970810404,
+           -1.269284076918826,
+           -1.3032465532717303,
+           -1.3288838294680394,
+           -1.3451872372219849,
+           -1.3513971331870163,
+           -1.3470158289706546,
+           -1.3318137059059323,
+           -1.3058284386577264,
+           -1.2693574255673046,
+           -1.2229436941588996,
+           -1.167355713193972,
+           -1.1035616940047468,
+           -1.0326990998105972,
+           -0.9560401989518647,
+           -0.8749545935743773,
+           -0.7908697269196633,
+           -0.7052304182804784,
+           -0.6194584937764395,
+           -0.534913572971867,
+           -0.45285603626262205,
+           -0.3744131368431685,
+           -0.3005491355233024,
+           -0.23204022890263845,
+           -0.1694549141925335,
+           -0.11314029054896041,
+           -0.06321464080044707,
+           -0.019566472890052887,
+           0.018139968619152725,
+           0.05045287970924991,
+           0.07811508638384126,
+           0.10204072664021516,
+           0.12328704932966787,
+           0.1430220825068906,
+           0.16248903281832694,
+           0.18296836439311545,
+           0.20573856835715412,
+           0.2320366708794679,
+           0.2630195376197676,
+           0.2997270152911731,
+           0.34304790717955735,
+           0.39368970994087893,
+           0.45215294554695484,
+           0.5187108071894081,
+           0.5933947041484361,
+           0.6759861414303141,
+           0.7660152091102214,
+           0.8627657878182966,
+           0.9652874049093128,
+           1.072413504884679,
+           1.1827857318991164,
+           1.2948836658700418,
+           1.4070593107741607,
+           1.5175755077951776,
+           1.6246473402928088,
+           1.7264855148115341,
+           1.8213406446863365,
+           1.9075473317581533,
+           1.9835669381502408,
+           2.0480279641612147,
+           2.0997629995954994,
+           2.137841293094696,
+           2.16159608542246,
+           2.170645975755354,
+           2.16490973186241,
+           2.1446141121650295,
+           2.110294436218161,
+           2.0627878160129502,
+           2.003219139350132,
+           1.9329800739686822,
+           1.8537015327582007,
+           1.767220201991577,
+           1.675539882083374,
+           1.5807885202421972,
+           1.485171923306025,
+           1.3909252243025285,
+           1.3002632357125297,
+           1.2153308545189363,
+           1.1381546880479088,
+           1.0705970451993698,
+           1.0143133854608202,
+           0.9707142393251532,
+           0.9409325102682221,
+           0.9257969427695898,
+           0.9258123960135289,
+           0.9411474023913,
+           0.9716293176323819,
+           1.0167471895043618,
+           1.075662288909879,
+           1.147226065326554,
+           1.2300051123055695,
+           1.3223125624522871,
+           1.422245179001261,
+           1.5277252764687317,
+           1.636546489185448,
+           1.746422316535282,
+           1.8550363096230715,
+           1.9600927274063473,
+           2.0593664819157333,
+           2.1507512122312393,
+           2.2323043748515428,
+           2.302288312783163,
+           2.3592063652246558,
+           2.401833201659294,
+           2.429238705483026,
+           2.440804889497797,
+           2.436235494822225,
+           2.4155581018526138,
+           2.3791187625008954,
+           2.3275693426170236,
+           2.261847937876612,
+           2.1831528912235934,
+           2.092911091189467,
+           1.9927413643944756,
+           1.8844138890337692,
+           1.7698066464364335,
+           1.6508599927098935,
+           1.529530470529395,
+           1.4077449914525342,
+           1.28735650157045,
+           1.1701021983785103,
+           1.057565295665565,
+           0.9511412378316584,
+           0.8520091477993018,
+           0.7611091565682014,
+           0.6791261109255518,
+           0.6064799926869969,
+           0.5433232122104064,
+           0.48954476507605155,
+           0.4447810681144469,
+           0.4084331237005504,
+           0.37968950358877684,
+           0.3575544994572997,
+           0.34088066033609427,
+           0.32840483034986584,
+           0.31878671634068506,
+           0.3106489559944567,
+           0.30261762450088997,
+           0.2933621122860963,
+           0.2816333280470238,
+           0.26629922958194363,
+           0.2463767584787297,
+           0.22105935168650975,
+           0.1897393208638449,
+           0.15202452615257733,
+           0.1077489212079862,
+           0.05697670710005489,
+           5.583097389795766e-16
+          ],
+          [
+           0,
+           -0.06478965750891556,
+           -0.13419249570529493,
+           -0.2072214044162032,
+           -0.28274688592305464,
+           -0.3595297829479074,
+           -0.4362572306884942,
+           -0.5115808745169638,
+           -0.5841563339137102,
+           -0.6526828582606127,
+           -0.7159421121794391,
+           -0.7728350474032438,
+           -0.8224158642575436,
+           -0.8639221375752112,
+           -0.8968002774985984,
+           -0.9207256127555727,
+           -0.9356165197101662,
+           -0.9416421713893782,
+           -0.9392236429947741,
+           -0.9290282800477273,
+           -0.9119574080266232,
+           -0.8891276337848131,
+           -0.8618461548655199,
+           -0.8315806488626764,
+           -0.7999244572603199,
+           -0.7685579030997621,
+           -0.7392066861821046,
+           -0.7135983806304278,
+           -0.6934181154022069,
+           -0.6802645472780919,
+           -0.675607237143961,
+           -0.6807465139024851,
+           -0.6967768566633746,
+           -0.7245547462115909,
+           -0.764671833032622,
+           -0.8174341438784263,
+           -0.8828479050236792,
+           -0.9606124014932866,
+           -1.0501201215233766,
+           -1.150464258518787,
+           -1.2604534631421336,
+           -1.378633560338997,
+           -1.5033157744618995,
+           -1.6326108444496785,
+           -1.7644682642470626,
+           -1.8967197549615236,
+           -2.027125967861738,
+           -2.1534253339163074,
+           -2.273383918258624,
+           -2.3848451082113407,
+           -2.4857779621032083,
+           -2.5743230731582014,
+           -2.6488348576282514,
+           -2.7079192577891185,
+           -2.7504659564822656,
+           -2.7756743280165233,
+           -2.7830724973502248,
+           -2.7725290419976183,
+           -2.74425704510215,
+           -2.698810389369156,
+           -2.6370723656467057,
+           -2.560236852409531,
+           -2.4697824987983417,
+           -2.3674405099049367,
+           -2.255156784634058,
+           -2.1350492900304685,
+           -2.0093616681916475,
+           -1.8804141600723814,
+           -1.7505529924975793,
+           -1.622099409043815,
+           -1.4972995313190258,
+           -1.3782762144490335,
+           -1.2669840098575225,
+           -1.1651682709745772,
+           -1.0743293352544896,
+           -0.9956925913582176,
+           -0.9301850966343969,
+           -0.8784192506574594,
+           -0.8406838594725143,
+           -0.816942746558125,
+           -0.8068408847308963,
+           -0.8097178427320689,
+           -0.8246281654678619,
+           -0.8503681420857973,
+           -0.8855082652687205,
+           -0.9284305519746573,
+           -0.9773697835597891,
+           -1.0304576344889105,
+           -1.0857685957706846,
+           -1.1413665633243177,
+           -1.195350953486352,
+           -1.2459012279056938,
+           -1.291318757562328,
+           -1.3300650293128802,
+           -1.3607952963012695,
+           -1.382386893264272,
+           -1.393961576165962,
+           -1.3949013992089825,
+           -1.3848578072225715,
+           -1.3637537935719295,
+           -1.331779148755472,
+           -1.2893789983790296,
+           -1.2372359968883988,
+           -1.176246701128602,
+           -1.10749279156222,
+           -1.0322079352592382,
+           -0.9517411904493708,
+           -0.8675179349088975,
+           -0.7809993577272314,
+           -0.6936415846878219,
+           -0.6068555108968355,
+           -0.5219683903797488,
+           -0.44018818180429475,
+           -0.362571573610452,
+           -0.28999651260019566,
+           -0.22313994001250353,
+           -0.16246130135337672,
+           -0.10819224428013169,
+           -0.06033275652255927,
+           -0.01865382728656752,
+           0.01729345489127717,
+           0.04816262296046348,
+           0.07479078740571955,
+           0.09817239478092779,
+           0.11942849209810925,
+           0.13977231852909106,
+           0.1604721429300855,
+           0.18281233924283113,
+           0.2080537399771576,
+           0.2373943294946023,
+           0.2719313331172067,
+           0.31262572529090316,
+           0.36027012093266103,
+           0.4154609301415395,
+           0.4785755497397262,
+           0.5497552382896936,
+           0.6288941774759154,
+           0.7156350656426718,
+           0.8093714227827856,
+           0.9092566145566877,
+           1.0142194303070762,
+           1.1229858808711644,
+           1.2341067205512446,
+           1.3459900479710154,
+           1.4569382065178067,
+           1.5651880900649717,
+           1.668953866630699,
+           1.7664710639630166,
+           1.8560409185463946,
+           1.9360738743535466,
+           2.0051311302890094,
+           2.0619631754691103,
+           2.1055443183488496,
+           2.1351023076673608,
+           2.1501422580393768,
+           2.150464227996207,
+           2.1361739500955794,
+           2.1076863776697903,
+           2.0657218868263802,
+           2.0112951511809047,
+           1.9456968860849877,
+           1.8704688343921332,
+           1.787372532746439,
+           1.6983525518488922,
+           1.6054950423175698,
+           1.51098253616966,
+           1.4170460496542878,
+           1.325915603749837,
+           1.2397703223143306,
+           1.1606892835108584,
+           1.0906042872755322,
+           1.0312556605083216,
+           0.984152153295483,
+           0.9505358854352757,
+           0.931353185088516,
+           0.9272320233395969,
+           0.9384665931686642,
+           0.9650094125627106,
+           1.00647115332808,
+           1.0621282139369594,
+           1.130937870900298,
+           1.2115606631805897,
+           1.3023894924181132,
+           1.4015847624207212,
+           1.5071147383341157,
+           1.6168001826413203,
+           1.7283622246273493,
+           1.8394723446207315,
+           1.9478033060029056,
+           2.0510798478128436,
+           2.1471279592306614,
+           2.2339215940631014,
+           2.3096257476422632,
+           2.3726349086826093,
+           2.4216060123840273,
+           2.4554851556085437,
+           2.4735274869759274,
+           2.475309850476612,
+           2.4607359366138297,
+           2.4300338758551856,
+           2.383746390866686,
+           2.3227138021738183,
+           2.2480503521935242,
+           2.1611144708581502,
+           2.063473748461803,
+           1.956865504453574,
+           1.8431539417163993,
+           1.724284951995508,
+           1.6022396877823522,
+           1.478988037981501,
+           1.356443138637262,
+           1.2364180161175957,
+           1.1205853993760333,
+           1.010441651834013,
+           0.9072756642641684,
+           0.8121434205968975,
+           0.7258488021009619,
+           0.6489310356028813,
+           0.5816590223308516,
+           0.5240326098403888,
+           0.47579069466024504,
+           0.4364258721561204,
+           0.40520518691235985,
+           0.3811963857371335,
+           0.36329893995558304,
+           0.35027898731781976,
+           0.340807249479916,
+           0.3334989109266716,
+           0.3269544010932126,
+           0.31980000435293454,
+           0.31072723283719217,
+           0.298529934415221,
+           0.2821381715899168,
+           0.2606479949017701,
+           0.23334634441410523,
+           0.19973044215790695,
+           0.15952118374138136,
+           0.11267019497508353,
+           0.05936038531830274,
+           5.794525877546376e-16
+          ],
+          [
+           0,
+           -0.06678259417549484,
+           -0.1377696226555108,
+           -0.21189341737723294,
+           -0.28796061858074495,
+           -0.3646869546261853,
+           -0.4407347248573425,
+           -0.5147519845380502,
+           -0.5854123845017203,
+           -0.6514545986016786,
+           -0.7117202798525157,
+           -0.7651895211435653,
+           -0.8110128577330438,
+           -0.8485389348795848,
+           -0.877337072794691,
+           -0.89721408988968,
+           -0.908224890823075,
+           -0.910676484482698,
+           -0.9051252647802505,
+           -0.8923675597788274,
+           -0.873423627869756,
+           -0.8495154490970711,
+           -0.8220388210163748,
+           -0.7925304175851756,
+           -0.7626306027266397,
+           -0.7340429039928433,
+           -0.7084911432591026,
+           -0.6876752882411828,
+           -0.6732271290857049,
+           -0.6666668972403645,
+           -0.6693619288475812,
+           -0.6824884323012114,
+           -0.7069973503285492,
+           -0.7435852126428611,
+           -0.7926707581157394,
+           -0.8543779683755569,
+           -0.9285260010822963,
+           -1.0146263446138415,
+           -1.111887340605867,
+           -1.2192260410246472,
+           -1.3352871866477019,
+           -1.4584689184198831,
+           -1.5869546664820253,
+           -1.7187505078679708,
+           -1.8517271467571481,
+           -1.9836655541725938,
+           -2.1123052100577704,
+           -2.2353938221167517,
+           -2.3507373544065366,
+           -2.4562491855075144,
+           -2.549997231555334,
+           -2.6302479131790237,
+           -2.695505916443833,
+           -2.7445487945596785,
+           -2.7764555770726904,
+           -2.790628693619624,
+           -2.786808676700651,
+           -2.7650812785028624,
+           -2.7258768164454414,
+           -2.6699617464538106,
+           -2.5984226475221535,
+           -2.51264298140235,
+           -2.414273162875923,
+           -2.3051946348488865,
+           -2.1874787845952928,
+           -2.0633416594106215,
+           -1.9350955387613629,
+           -1.805098493338303,
+           -1.675703107470542,
+           -1.5492055590339058,
+           -1.4277962398877178,
+           -1.3135130602964797,
+           -1.2081985137362317,
+           -1.1134614856178622,
+           -1.0306446730819432,
+           -0.9607983460055903,
+           -0.9046610250875091,
+           -0.8626474851386018,
+           -0.834844314622026,
+           -0.8210130804028596,
+           -0.8206009640426731,
+           -0.832758557274529,
+           -0.8563643338805215,
+           -0.8900551572170694,
+           -0.9322620409289046,
+           -0.981250258389345,
+           -1.0351627970378507,
+           -1.0920660794282067,
+           -1.149996825201779,
+           -1.2070089084462083,
+           -1.2612190733860758,
+           -1.3108504077752903,
+           -1.3542725367274757,
+           -1.390037588371951,
+           -1.4169110943782033,
+           -1.433897120204404,
+           -1.4402570685564073,
+           -1.4355217612424804,
+           -1.4194965753102016,
+           -1.3922595847749235,
+           -1.354152835005219,
+           -1.305767048533075,
+           -1.2479202244283953,
+           -1.1816307443594058,
+           -1.1080857333106402,
+           -1.0286055383173927,
+           -0.9446052816615078,
+           -0.8575545134832991,
+           -0.7689360310428865,
+           -0.6802049469155554,
+           -0.5927490759185783,
+           -0.5078516709209618,
+           -0.4266574719431814,
+           -0.35014294282585806,
+           -0.2790914575587663,
+           -0.214074066991064,
+           -0.15543632944551664,
+           -0.10329152948397624,
+           -0.057520441769554634,
+           -0.017777625892624847,
+           0.01649593248456799,
+           0.04605418443023227,
+           0.07182189128517127,
+           0.09486565920084192,
+           0.11636091168733638,
+           0.13755568401751328,
+           0.15973220752144082,
+           0.18416731120032315,
+           0.21209270116650988,
+           0.24465618431365313,
+           0.2828848811605539,
+           0.327651424504576,
+           0.3796440665531953,
+           0.4393415194099572,
+           0.5069932346101466,
+           0.5826056898093334,
+           0.6659350981689417,
+           0.7564867922825806,
+           0.853521363756633,
+           0.956067466092341,
+           1.062941016685124,
+           1.1727703678968935,
+           1.2840268614637664,
+           1.39506003892339,
+           1.5041366568855659,
+           1.6094825529936554,
+           1.7093263289830036,
+           1.801943763404188,
+           1.8857018397768346,
+           1.9591012769348064,
+           2.020816477185819,
+           2.0697318640131543,
+           2.104973663089428,
+           2.125936286399181,
+           2.13230260672432,
+           2.124057555541637,
+           2.101494637959841,
+           2.0652151297550008,
+           2.016119899640512,
+           1.9553939802486733,
+           1.8844841894587567,
+           1.8050702752780072,
+           1.7190302182184118,
+           1.628400471022151,
+           1.5353320430413147,
+           1.4420434423876412,
+           1.3507715704795022,
+           1.2637217187641763,
+           1.1830178447653,
+           1.1106543034637384,
+           1.0484501803279276,
+           0.998007314733776,
+           0.9606730184060727,
+           0.9375083848777969,
+           0.9292629554109566,
+           0.9363563575018599,
+           0.9588673676191339,
+           0.9965306741819213,
+           1.0487414342436503,
+           1.114567532340091,
+           1.192769266988572,
+           1.2818260138399102,
+           1.379969248779896,
+           1.4852211633840413,
+           1.5954379727169017,
+           1.7083569047518095,
+           1.8216457743530727,
+           1.9329539848981678,
+           2.0399637686607406,
+           2.1404404737810876,
+           2.232280731071497,
+           2.313557387389338,
+           2.3825601725230166,
+           2.4378311714841607,
+           2.478194301188563,
+           2.5027781366038737,
+           2.511031592946258,
+           2.502732143451825,
+           2.477986432385669,
+           2.437223325866974,
+           2.3811796243059504,
+           2.3108788353401746,
+           2.227603570855278,
+           2.13286228197237,
+           2.0283511781387613,
+           1.9159122874774022,
+           1.7974887026722954,
+           1.6750781178239493,
+           1.5506857954791993,
+           1.4262781086801877,
+           1.3037377803416328,
+           1.1848218922048823,
+           1.0711236593613684,
+           0.9640388658636745,
+           0.8647377348203066,
+           0.7741428657040411,
+           0.6929137159486783,
+           0.6214379371853588,
+           0.5598297028637222,
+           0.5079349878632389,
+           0.4653435864272143,
+           0.4314074866919687,
+           0.40526506241738913,
+           0.3858703991652502,
+           0.37202694666606434,
+           0.3624245845580262,
+           0.3556791076371836,
+           0.3503730811976875,
+           0.3450969882943388,
+           0.3384895894821727,
+           0.3292764417451445,
+           0.31630557619568356,
+           0.29857941231706275,
+           0.2752820880051333,
+           0.2458015068365735,
+           0.20974554372148066,
+           0.1669520038250069,
+           0.11749209345275068,
+           0.06166733132442137,
+           5.996396084766755e-16
+          ],
+          [
+           0,
+           -0.06863161510404027,
+           -0.14101795425385466,
+           -0.21601902580357096,
+           -0.2923871024459921,
+           -0.3688032697915923,
+           -0.4439161283133596,
+           -0.5163816134088495,
+           -0.5849028671504801,
+           -0.6482690914580702,
+           -0.7053923360573648,
+           -0.7553412251164203,
+           -0.797370702631906,
+           -0.8309469765762104,
+           -0.8557669630202628,
+           -0.8717716708846964,
+           -0.8791531221494854,
+           -0.8783545674000212,
+           -0.8700639283576768,
+           -0.8552005732115864,
+           -0.8348957027448931,
+           -0.810466791084649,
+           -0.7833866802027494,
+           -0.7552480681148663,
+           -0.7277242534795658,
+           -0.7025271008500507,
+           -0.6813632685596418,
+           -0.6658897931030143,
+           -0.6576701485232713,
+           -0.6581318960224728,
+           -0.6685270077678412,
+           -0.6898958903523145,
+           -0.7230360489519695,
+           -0.7684762249178286,
+           -0.8264567099581865,
+           -0.8969163923574259,
+           -0.9794869284432527,
+           -1.0734942597301569,
+           -1.177967517077018,
+           -1.2916551722112601,
+           -1.413048118557633,
+           -1.5404091918793195,
+           -1.671808481042362,
+           -1.805163634231879,
+           -1.938284239793559,
+           -2.0689192567020367,
+           -2.1948063900885093,
+           -2.313722254311394,
+           -2.4235321410919464,
+           -2.5222382139409003,
+           -2.6080249824476214,
+           -2.679300970261233,
+           -2.734735577347542,
+           -2.7732902482880304,
+           -2.7942431913268604,
+           -2.7972070443608814,
+           -2.782139050440175,
+           -2.7493434825681646,
+           -2.6994662413571757,
+           -2.6334817349405286,
+           -2.5526723339448703,
+           -2.4586008708238047,
+           -2.3530768181498622,
+           -2.238116930534405,
+           -2.1159012660434335,
+           -1.9887256121131187,
+           -1.8589514253941115,
+           -1.7289544526250678,
+           -1.601073229166889,
+           -1.4775586525208861,
+           -1.3605258000164557,
+           -1.2519091035999186,
+           -1.1534219116896278,
+           -1.06652136043804,
+           -0.9923793471172636,
+           -0.9318602499145481,
+           -0.8855058748393072,
+           -0.8535279357221891,
+           -0.8358081917147446,
+           -0.8319061827237161,
+           -0.8410743213362062,
+           -0.8622799244522652,
+           -0.894233603312113,
+           -0.9354232808855445,
+           -0.9841529743080891,
+           -1.0385853703686916,
+           -1.0967871366045834,
+           -1.1567758513659796,
+           -1.2165674046490795,
+           -1.2742227182490862,
+           -1.3278926588426043,
+           -1.375860070258514,
+           -1.4165779300449097,
+           -1.4487027384481101,
+           -1.4711223724556919,
+           -1.4829777804582334,
+           -1.4836780507458056,
+           -1.4729085555076766,
+           -1.450632047021474,
+           -1.417082759921348,
+           -1.3727537483989463,
+           -1.3183778555577355,
+           -1.2549028697251958,
+           -1.1834615654219705,
+           -1.1053374513597167,
+           -1.0219271512207013,
+           -0.9347004225303812,
+           -0.8451588727386226,
+           -0.7547944583934874,
+           -0.6650488524203136,
+           -0.5772747360990612,
+           -0.49270001714599815,
+           -0.4123958948034738,
+           -0.3372495891096711,
+           -0.2679424272246912,
+           -0.2049338380103534,
+           -0.14845165061203058,
+           -0.09848892752803792,
+           -0.054807391775556775,
+           -0.016947335609744152,
+           0.015756270807911775,
+           0.044151914077248285,
+           0.06924450905059422,
+           0.09216393554825278,
+           0.11412998489957416,
+           0.13641465544604117,
+           0.16030280660577842,
+           0.18705222568890406,
+           0.21785417922069095,
+           0.253795510605314,
+           0.2958233087702458,
+           0.3447131088802131,
+           0.4010414978748458,
+           0.4651638866660107,
+           0.5371980801004175,
+           0.617014128523387,
+           0.7042307846638252,
+           0.798218720619714,
+           0.898110486207344,
+           1.0028170162163108,
+           1.1110503245698564,
+           1.2213518623124757,
+           1.3321258678155332,
+           1.4416769053822858,
+           1.5482506759198547,
+           1.6500770934151423,
+           1.7454145559331986,
+           1.832594301461009,
+           1.9100637281972728,
+           1.976427576200333,
+           2.0304859123151666,
+           2.071267931977962,
+           2.098060688148434,
+           2.110431976925485,
+           2.1082467484721916,
+           2.091676567324758,
+           2.0612018141857464,
+           2.017606497783031,
+           1.9619657259717267,
+           1.8956260655144725,
+           1.8201791954424578,
+           1.7374294252305715,
+           1.6493558020874894,
+           1.5580696676556354,
+           1.4657686399431185,
+           1.3746880884722248,
+           1.287051237101033,
+           1.2050190680594706,
+           1.1306412114116018,
+           1.0658089860849282,
+           1.0122117121717427,
+           0.9712973404835068,
+           0.9442383460741507,
+           0.931903710018698,
+           0.934837671088662,
+           0.9532457695520635,
+           0.9869885330063025,
+           1.0355829731080004,
+           1.0982118766944746,
+           1.1737406896043425,
+           1.2607416110056269,
+           1.3575243446216667,
+           1.4621727950799925,
+           1.5725868565451835,
+           1.6865283202640764,
+           1.8016698305775145,
+           1.9156457476898776,
+           2.026103731756408,
+           2.1307558476945547,
+           2.2274280038948167,
+           2.3141065803359773,
+           2.3889811714379703,
+           2.4504824645778833,
+           2.497314394187109,
+           2.528479850805406,
+           2.5432993809576083,
+           2.54142248339375,
+           2.522831285929244,
+           2.487836570457528,
+           2.4370662971959494,
+           2.3714469583822875,
+           2.292178262094014,
+           2.2007018044664193,
+           2.098664529514463,
+           1.9878778966090584,
+           1.8702737735157742,
+           1.7478581454392264,
+           1.6226637760249618,
+           1.4967029737192397,
+           1.371921605936858,
+           1.2501554645017432,
+           1.1330900198611642,
+           1.0222245103530736,
+           0.9188411986710081,
+           0.8239804935268745,
+           0.7384224837549394,
+           0.6626752685295505,
+           0.5969702950940677,
+           0.5412647387356548,
+           0.49525078310586684,
+           0.45837148678537043,
+           0.42984275850817455,
+           0.4086808127548511,
+           0.39373434322644474,
+           0.3837205373324906,
+           0.37726396307707805,
+           0.3729372928441391,
+           0.36930278817880485,
+           0.36495345668130225,
+           0.3585528068304288,
+           0.348872168497521,
+           0.33482461497884247,
+           0.31549461479009727,
+           0.2901626558477542,
+           0.2583242180759704,
+           0.21970261951743505,
+           0.17425542189473847,
+           0.12217425017477138,
+           0.06387805274994278,
+           6.186988061787375e-16
+          ],
+          [
+           0,
+           -0.07032075061075688,
+           -0.14390926927766115,
+           -0.21956220754846448,
+           -0.2959875455773556,
+           -0.37184260769917743,
+           -0.44577365775308325,
+           -0.516456013333872,
+           -0.5826336025892626,
+           -0.6431568992411011,
+           -0.697018210908172,
+           -0.7433833615791873,
+           -0.7816188995929855,
+           -0.8113140754708802,
+           -0.8322969665871222,
+           -0.8446442746334317,
+           -0.848684483393481,
+           -0.8449942344322037,
+           -0.8343879526419874,
+           -0.8179009277786614,
+           -0.796766227766868,
+           -0.7723859803654991,
+           -0.746297707681823,
+           -0.7201365292463724,
+           -0.6955941605585824,
+           -0.6743757223294194,
+           -0.6581554387920622,
+           -0.6485323397603214,
+           -0.646987089588689,
+           -0.6548410465226884,
+           -0.6732186085198011,
+           -0.703013827558657,
+           -0.7448621754929199,
+           -0.7991182230258643,
+           -0.8658398523271096,
+           -0.9447794666229349,
+           -1.0353824906131377,
+           -1.13679327796152,
+           -1.2478683607457197,
+           -1.367196795109987,
+           -1.4931271819085523,
+           -1.623800775205454,
+           -1.7571899392310437,
+           -1.8911410795782506,
+           -2.0234210604229954,
+           -2.151766029235208,
+           -2.273931506093698,
+           -2.3877425579780027,
+           -2.4911428702542806,
+           -2.582241548269648,
+           -2.6593565310796548,
+           -2.721053575717727,
+           -2.7661798722617736,
+           -2.79389147482301,
+           -2.8036738784678215,
+           -2.7953552334835337,
+           -2.769111862402453,
+           -2.725465927582439,
+           -2.665275283474265,
+           -2.58971573345422,
+           -2.500256091744177,
+           -2.398626622083311,
+           -2.286781582288851,
+           -2.1668567438150386,
+           -2.0411228744843823,
+           -1.9119362678300893,
+           -1.7816874716425826,
+           -1.652749409684862,
+           -1.5274261031414587,
+           -1.40790318190689,
+           -1.2962013307291582,
+           -1.194133742627048,
+           -1.1032685536973756,
+           -1.0248971118465098,
+           -0.9600087901152516,
+           -0.9092728966067322,
+           -0.8730280614700128,
+           -0.851279301146137,
+           -0.8437027755634671,
+           -0.8496580696897503,
+           -0.8682076513100966,
+           -0.8981429864803564,
+           -0.938016636949626,
+           -0.9861795237658367,
+           -1.0408224216589816,
+           -1.10002065251215,
+           -1.1617808755745418,
+           -1.2240888287006928,
+           -1.2849568597965317,
+           -1.3424701010968576,
+           -1.3948301804652319,
+           -1.4403954324770756,
+           -1.4777166658353877,
+           -1.5055676602710044,
+           -1.5229697025314086,
+           -1.5292096239134332,
+           -1.5238509671976175,
+           -1.5067380846430294,
+           -1.477993146550815,
+           -1.4380062173603543,
+           -1.387418728881918,
+           -1.3271008438018206,
+           -1.2581233529642686,
+           -1.1817248834195737,
+           -1.0992753075413209,
+           -1.0122363338764424,
+           -0.922120325602009,
+           -0.8304484309542421,
+           -0.7387091208742577,
+           -0.6483182121792966,
+           -0.5605814103138957,
+           -0.47666033534264557,
+           -0.39754290014899957,
+           -0.32401879324537086,
+           -0.25666068316594415,
+           -0.19581161056430763,
+           -0.1415788717155007,
+           -0.09383452725628699,
+           -0.052222497002117015,
+           -0.016172029943419902,
+           0.015082827597656882,
+           0.04247829896489208,
+           0.06709115514328182,
+           0.0901050046422856,
+           0.11277350074826666,
+           0.13638145290585507,
+           0.1622048849828246,
+           0.19147111243029155,
+           0.2253199121088411,
+           0.2647668327431893,
+           0.31066964121945745,
+           0.36369882155523886,
+           0.4243129413053747,
+           0.49273957696590653,
+           0.5689623486898439,
+           0.652714458873946,
+           0.7434789628277089,
+           0.8404958269780994,
+           0.9427756552479694,
+           1.049119791781831,
+           1.1581463424386924,
+           1.2683215026253007,
+           1.3779954390361786,
+           1.4854418512668148,
+           1.5889002391865603,
+           1.686619825979371,
+           1.7769040368671098,
+           1.8581544110572377,
+           1.9289128300585618,
+           1.9879009791392503,
+           2.0340560196159285,
+           2.0665615364348486,
+           2.084872936061848,
+           2.0887366013667377,
+           2.0782022597681102,
+           2.0536281847423665,
+           2.015679024879258,
+           1.9653162347060824,
+           1.9037812630665953,
+           1.8325718334438754,
+           1.7534118218378163,
+           1.6682153973992682,
+           1.5790462350149665,
+           1.4880727338369562,
+           1.397520278232822,
+           1.309621655216205,
+           1.226566793128853,
+           1.1504530088725033,
+           1.0832369447080412,
+           1.0266893406374655,
+           0.9823537254523409,
+           0.9515100201511705,
+           0.9351439337289535,
+           0.9339228960563599,
+           0.9481791189586001,
+           0.9779002083923272,
+           1.0227275718826525,
+           1.081962680462348,
+           1.154581057747727,
+           1.2392536850305569,
+           1.3343753348356027,
+           1.4380991805844037,
+           1.5483768808298222,
+           1.6630032066127949,
+           1.7796641730020673,
+           1.895987553419168,
+           2.009594599921576,
+           2.118151765551894,
+           2.219421226799944,
+           2.311309035097687,
+           2.3919097852948674,
+           2.459546774779374,
+           2.5128067371898597,
+           2.5505683667996557,
+           2.57202400037796,
+           2.576693988952325,
+           2.5644334683400865,
+           2.5354314202609194,
+           2.4902021008091357,
+           2.4295690955314515,
+           2.354642435870851,
+           2.2667893760253115,
+           2.1675995783405106,
+           2.0588455855990513,
+           1.942439566845778,
+           1.8203874071077233,
+           1.6947412685466803,
+           1.5675517798988643,
+           1.4408210118776827,
+           1.31645736861417,
+           1.196233469959732,
+           1.0817480180343302,
+           0.97439253587094,
+           0.8753237390779103,
+           0.7854421563311244,
+           0.7053774548793639,
+           0.6354807571111779,
+           0.5758240578546607,
+           0.5262066738729888,
+           0.4861684814241211,
+           0.45500952914320386,
+           0.4318154560683862,
+           0.415488002264307,
+           0.4047797757176456,
+           0.39833233702975707,
+           0.39471658540976856,
+           0.3924743774664888,
+           0.3901602855437035,
+           0.3863824053906191,
+           0.3798411536598015,
+           0.3693650532381305,
+           0.35394258723005967,
+           0.33274930838195865,
+           0.3051695171378107,
+           0.2708119651168438,
+           0.22951919794038522,
+           0.18137031800976405,
+           0.12667711981423566,
+           0.06597372326275038,
+           6.364666640263556e-16
+          ],
+          [
+           0,
+           -0.07183533331270517,
+           -0.146418334008587,
+           -0.22249191731641552,
+           -0.29873033588525655,
+           -0.3737783445908897,
+           -0.446291352547272,
+           -0.5149754849391459,
+           -0.5786264776284851,
+           -0.6361663554820607,
+           -0.6866769003357923,
+           -0.7294289950895367,
+           -0.7639070346032472,
+           -0.789827719235626,
+           -0.8071526898919119,
+           -0.8160946207377856,
+           -0.8171165533377579,
+           -0.8109244296702224,
+           -0.7984529568800106,
+           -0.7808451093250205,
+           -0.7594257390896894,
+           -0.735669920478127,
+           -0.7111667931423946,
+           -0.6875797888991231,
+           -0.666604225855514,
+           -0.6499233276594605,
+           -0.6391637735680841,
+           -0.6358519053087964,
+           -0.6413717087878623,
+           -0.6569256526873556,
+           -0.6834994026874417,
+           -0.7218313409445029,
+           -0.772387707680351,
+           -0.8353440480215973,
+           -0.9105734958260057,
+           -0.9976422608467922,
+           -1.095812510274102,
+           -1.2040526547690928,
+           -1.3210548670326774,
+           -1.4452594822290517,
+           -1.5748857586416594,
+           -1.7079683180211545,
+           -1.8423984421481792,
+           -1.9759692787480716,
+           -2.106423909154785,
+           -2.2315051545688624,
+           -2.34900594931483,
+           -2.4568190894376527,
+           -2.552985173850128,
+           -2.6357375929062523,
+           -2.7035434848739706,
+           -2.7551396727707855,
+           -2.7895627102127674,
+           -2.806172302520139,
+           -2.804667525000022,
+           -2.785095430321024,
+           -2.747851817081784,
+           -2.693674117679482,
+           -2.623626550881323,
+           -2.539077868534217,
+           -2.4416722021341672,
+           -2.3332936792244445,
+           -2.2160256277996324,
+           -2.092105315453403,
+           -1.963875275792845,
+           -1.8337323550810176,
+           -1.704075665212354,
+           -1.5772546536906045,
+           -1.4555184966857229,
+           -1.3409679876256668,
+           -1.235511031976082,
+           -1.1408227704065148,
+           -1.05831123962137,
+           -0.989089345528079,
+           -0.9339537704343017,
+           -0.8933712683672105,
+           -0.8674726245016122,
+           -0.8560543704332982,
+           -0.8585881611471019,
+           -0.8742375365474857,
+           -0.9018816148058522,
+           -0.9401451008080455,
+           -0.9874338446387833,
+           -1.0419750559069936,
+           -1.1018611729073424,
+           -1.165096303683655,
+           -1.2296441009458097,
+           -1.2934759057651226,
+           -1.3546179966099985,
+           -1.4111968104515087,
+           -1.4614810605302753,
+           -1.5039197594119127,
+           -1.5371752640045389,
+           -1.5601505885150757,
+           -1.5720103786078985,
+           -1.5721951015873488,
+           -1.5604281791978727,
+           -1.5367159673193864,
+           -1.5013406659926452,
+           -1.4548464193737758,
+           -1.3980190340079475,
+           -1.331859901041517,
+           -1.2575548497694407,
+           -1.1764387827435827,
+           -1.0899570435312562,
+           -0.9996245446503604,
+           -0.9069837333716768,
+           -0.8135624957846994,
+           -0.720833094275187,
+           -0.6301732005652568,
+           -0.5428300266208775,
+           -0.4598884706092316,
+           -0.38224408689350137,
+           -0.31058156056593805,
+           -0.245359221527535,
+           -0.18679997433450338,
+           -0.13488885198795206,
+           -0.089377228812747,
+           -0.04979355394535569,
+           -0.01546029713099802,
+           0.014483363178378738,
+           0.041053728934290275,
+           0.06539040182292559,
+           0.08872059995283017,
+           0.1123209308801983,
+           0.13747764718730326,
+           0.16544645173824404,
+           0.19741293326766216,
+           0.23445469875044844,
+           0.2775062273904488,
+           0.3273274030812691,
+           0.3844765895249108,
+           0.449288997159732,
+           0.5218609565291268,
+           0.602040562090849,
+           0.6894249875081813,
+           0.7833646022770115,
+           0.8829738444389318,
+           0.987148629526558,
+           1.094589906193729,
+           1.2038328084957939,
+           1.313280707575248,
+           1.4212433353216558,
+           1.525978042738973,
+           1.6257331690914174,
+           1.7187924366603402,
+           1.8035192517469931,
+           1.878399786345032,
+           1.9420837369309067,
+           1.9934217066236999,
+           2.031498233399086,
+           2.0556595882887607,
+           2.065535591118679,
+           2.0610548343360495,
+           2.042452864357017,
+           2.0102730407421063,
+           1.9653599721758834,
+           1.908845610289462,
+           1.8421282633235083,
+           1.7668449670068458,
+           1.684837815471757,
+           1.5981150064278322,
+           1.5088074883968783,
+           1.4191222102284227,
+           1.3312930615431373,
+           1.2475306549482112,
+           1.169972135236546,
+           1.1006322064056742,
+           1.041356544002148,
+           0.9937787085168381,
+           0.9592815965282666,
+           0.9389643618903665,
+           0.9336156119882992,
+           0.9436935370065713,
+           0.9693134668233916,
+           1.0102431745214944,
+           1.0659060618520284,
+           1.1353921747682898,
+           1.2174768109148217,
+           1.3106463002480397,
+           1.4131303691777304,
+           1.5229403419141412,
+           1.6379122938989104,
+           1.7557541546681494,
+           1.874095664101213,
+           1.9905400190158027,
+           2.102716008099821,
+           2.20832942315723,
+           2.30521255381419,
+           2.3913706206935346,
+           2.465024077428389,
+           2.524645812885925,
+           2.5689924091186063,
+           2.5971287547980704,
+           2.608445474671291,
+           2.602668808964226,
+           2.5798627583941927,
+           2.5404234960899763,
+           2.485066232719096,
+           2.4148049009687576,
+           2.330925195838365,
+           2.2349516638363727,
+           2.1286096733353745,
+           2.013783216666654,
+           1.8924695891871781,
+           1.7667320592760176,
+           1.638651684404428,
+           1.5102794411470355,
+           1.383589821039144,
+           1.2604370000231078,
+           1.142514618047087,
+           1.0313201090304918,
+           0.928124402357649,
+           0.8339476783284341,
+           0.7495417050846377,
+           0.6753791173415795,
+           0.6116498219781167,
+           0.5582645365590144,
+           0.5148652886479302,
+           0.48084253075416045,
+           0.45535836223937526,
+           0.43737519954380893,
+           0.42568910337973803,
+           0.4189668593502338,
+           0.41578581953073024,
+           0.4146754490604522,
+           0.41415948525047575,
+           0.4127976079685583,
+           0.40922553925340166,
+           0.40219253668826394,
+           0.390595317785458,
+           0.37350754960518734,
+           0.3502041565542402,
+           0.3201798367391756,
+           0.2831613298758897,
+           0.23911314369534656,
+           0.18823661686633966,
+           0.1309623703367164,
+           0.06793637126423786,
+           6.527898018164599e-16
+          ],
+          [
+           0,
+           -0.07316215028350286,
+           -0.1485231691758851,
+           -0.22478242408095164,
+           -0.3005913992828364,
+           -0.3745936791018228,
+           -0.4454653120089373,
+           -0.5119544709906665,
+           -0.5729193418223719,
+           -0.6273632147320135,
+           -0.6744658251284618,
+           -0.7136100838797946,
+           -0.7444034546838644,
+           -0.7666933724410693,
+           -0.7805762487935081,
+           -0.7863997753076762,
+           -0.7847584070134755,
+           -0.776482084829825,
+           -0.7626184303692627,
+           -0.7444088162981273,
+           -0.7232588755379229,
+           -0.700704159062969,
+           -0.6783717811499239,
+           -0.6579389993651912,
+           -0.6410897615470366,
+           -0.6294703113426046,
+           -0.6246449759260266,
+           -0.628053263460033,
+           -0.6409693734787202,
+           -0.6644651711788526,
+           -0.6993775978217217,
+           -0.7462813859434955,
+           -0.8054678223455904,
+           -0.8769301569433455,
+           -0.9603560950304717,
+           -1.0551276383042443,
+           -1.1603283603275718,
+           -1.2747580194089478,
+           -1.3969542306749931,
+           -1.5252207438811698,
+           -1.6576617086044303,
+           -1.7922211579912393,
+           -1.926726809951241,
+           -2.0589371739056705,
+           -2.186590864709597,
+           -2.3074569653655734,
+           -2.4193852481791107,
+           -2.520355060933626,
+           -2.608521710632494,
+           -2.6822592318030893,
+           -2.740198508015223,
+           -2.781259822195758,
+           -2.8046790409611737,
+           -2.8100267874168043,
+           -2.797220122078177,
+           -2.7665264287520075,
+           -2.7185593870703193,
+           -2.654267101406718,
+           -2.5749126425436,
+           -2.482047439158006,
+           -2.3774781265506517,
+           -2.2632276159058846,
+           -2.1414912849434193,
+           -2.014589306754463,
+           -1.8849162250845555,
+           -1.7548889491102644,
+           -1.6268943772879059,
+           -1.5032378672524194,
+           -1.3860937468492187,
+           -1.2774590107453054,
+           -1.179111268943755,
+           -1.092571909847745,
+           -1.0190753138389648,
+           -0.9595448067653977,
+           -0.9145758798735272,
+           -0.884427027564052,
+           -0.8690183711888914,
+           -0.8679380504220404,
+           -0.8804561780896846,
+           -0.9055459742653044,
+           -0.9419115253093338,
+           -0.9880214574943763,
+           -1.042147676686799,
+           -1.1024082085883387,
+           -1.1668130810838233,
+           -1.233312123503203,
+           -1.299843518647853,
+           -1.3643819331237812,
+           -1.4249850700318039,
+           -1.4798375348378356,
+           -1.527290979040199,
+           -1.5658995851544268,
+           -1.5944500780220545,
+           -1.6119855884375898,
+           -1.6178228520202482,
+           -1.611562395190321,
+           -1.5930915368112186,
+           -1.5625802141115137,
+           -1.520469820417505,
+           -1.467455415555148,
+           -1.4044618332190724,
+           -1.3326143591097144,
+           -1.2532047855179858,
+           -1.1676537590477947,
+           -1.0774704255957726,
+           -0.9842104384348197,
+           -0.889433429800147,
+           -0.7946610529627112,
+           -0.7013366803063248,
+           -0.6107877940145243,
+           -0.5241920309224851,
+           -0.44254774385130763,
+           -0.36664982087523845,
+           -0.2970713645739058,
+           -0.23415167895062963,
+           -0.17799084628484188,
+           -0.12845100393634182,
+           -0.0851642564031906,
+           -0.04754698518430789,
+           -0.014820152589762764,
+           0.01396496020841356,
+           0.03989628193692059,
+           0.06416657110477784,
+           0.08803605337107294,
+           0.11279308100959635,
+           0.13971387154681086,
+           0.17002240798586069,
+           0.20485158058173034,
+           0.24520661994469453,
+           0.2919318140632961,
+           0.34568141907739897,
+           0.4068955673647379,
+           0.475781849392998,
+           0.5523031010233482,
+           0.6361717691678612,
+           0.726851059896946,
+           0.8235628985154327,
+           0.9253025551800329,
+           1.0308596167605837,
+           1.138844820226135,
+           1.2477221090586006,
+           1.3558451359706307,
+           1.461497316056819,
+           1.562934437493399,
+           1.6584287645276485,
+           1.7463135216593124,
+           1.8250266298478461,
+           1.8931525758241707,
+           1.9494613339821734,
+           1.9929433260072933,
+           2.022839494819358,
+           2.0386656843713045,
+           2.0402306525698592,
+           2.0276471977613366,
+           2.0013360461059806,
+           1.9620223236498204,
+           1.910724618647189,
+           1.8487368222039458,
+           1.7776031140846162,
+           1.699086631124015,
+           1.615132513863886,
+           1.5278261688567778,
+           1.4393477059956192,
+           1.3519236091766609,
+           1.2677767720853483,
+           1.1890760770306497,
+           1.1178867123375311,
+           1.0561224123334185,
+           1.005500763641294,
+           0.9675026532395969,
+           0.9433368391737618,
+           0.9339105061634345,
+           0.9398065284941979,
+           0.9612680048887011,
+           0.9981904583369973,
+           1.0501219122954297,
+           1.116270867649066,
+           1.1955220169231973,
+           1.2864593479991808,
+           1.3873961135259247,
+           1.4964109786101172,
+           1.6113895122019777,
+           1.7300700604546386,
+           1.8500929363183247,
+           1.9690517812661927,
+           2.084545904238024,
+           2.1942323808580175,
+           2.2958767032558565,
+           2.3874008072005326,
+           2.4669273678370596,
+           2.532819346498089,
+           2.5837138865990337,
+           2.618549793673327,
+           2.636587989796715,
+           2.6374245021786873,
+           2.620995725409286,
+           2.5875758823414854,
+           2.537766795327249,
+           2.4724802629493086,
+           2.392913513029451,
+           2.300518366274231,
+           2.196964892470916,
+           2.084100469101493,
+           1.9639052575208311,
+           1.838445191929979,
+           1.7098236293772577,
+           1.580132833718226,
+           1.451406462341962,
+           1.3255741917189134,
+           1.2044195573446357,
+           1.0895419970271412,
+           0.9823239759189938,
+           0.8839039400425281,
+           0.7951556956260267,
+           0.7166746481229523,
+           0.6487711614266595,
+           0.591471118857165,
+           0.54452358745105,
+           0.5074153104140948,
+           0.47939158368920265,
+           0.45948291563571286,
+           0.4465367276905634,
+           0.4392532320636224,
+           0.4362245229963487,
+           0.4359758433096115,
+           0.43700793968512563,
+           0.4378393995009254,
+           0.4370478695158166,
+           0.4333090920076995,
+           0.425432756155865,
+           0.4123942498853515,
+           0.3933615077991988,
+           0.367716281375351,
+           0.3350693049602404,
+           0.2952689914941368,
+           0.2484034612737819,
+           0.1947958810938998,
+           0.13499326539564152,
+           0.06974906116926105,
+           6.675265429218629e-16
+          ],
+          [
+           0,
+           -0.07428958152193181,
+           -0.1502052858367831,
+           -0.22641359719427884,
+           -0.3015544843448075,
+           -0.37428186106627154,
+           -0.44330381309642325,
+           -0.5074215088155964,
+           -0.565565743412172,
+           -0.6168301256635808,
+           -0.660500001397178,
+           -0.6960763160317386,
+           -0.7232937476242712,
+           -0.7421325883175449,
+           -0.7528240123178227,
+           -0.7558485384958759,
+           -0.7519276711137577,
+           -0.7420088786084517,
+           -0.7272442433530457,
+           -0.70896328048736,
+           -0.6886405770732507,
+           -0.6678590400894284,
+           -0.648269659632862,
+           -0.6315487891149404,
+           -0.6193540147629318,
+           -0.6132797305118318,
+           -0.6148135502147112,
+           -0.6252946765236408,
+           -0.6458753050194327,
+           -0.6774860741229307,
+           -0.7208064776119458,
+           -0.7762410394482852,
+           -0.8439019129291292,
+           -0.9235984112756069,
+           -1.0148338084535673,
+           -1.1168095714249195,
+           -1.2284370025294036,
+           -1.3483560878054004,
+           -1.4749611683031292,
+           -1.6064328812607451,
+           -1.7407756606374496,
+           -1.8758599458538394,
+           -2.0094681271993657,
+           -2.1393431592572565,
+           -2.26323870232775,
+           -2.3789696080293603,
+           -2.4844615501773624,
+           -2.5777986161252633,
+           -2.6572677167376133,
+           -2.7213987440583787,
+           -2.7689995028771657,
+           -2.7991845634572505,
+           -2.81139732476449,
+           -2.8054247371951204,
+           -2.7814043071771044,
+           -2.7398231889073816,
+           -2.6815093564415897,
+           -2.6076150378006386,
+           -2.519592777111363,
+           -2.419164666564707,
+           -2.308285452870357,
+           -2.1891003689411694,
+           -2.0638986671934676,
+           -1.935063933039813,
+           -1.8050223333911968,
+           -1.6761900034238724,
+           -1.5509207943306726,
+           -1.4314555948051852,
+           -1.319874399858971,
+           -1.218052233218543,
+           -1.127619935654217,
+           -1.0499307134672082,
+           -0.986033201908749,
+           -0.9366516409476928,
+           -0.9021735893997102,
+           -0.8826454221800072,
+           -0.8777756687771975,
+           -0.8869460635305674,
+           -0.9092299945027428,
+           -0.9434178621531124,
+           -0.9880486959041838,
+           -1.041447230009742,
+           -1.101765513426118,
+           -1.1670280247043874,
+           -1.2351791847376206,
+           -1.3041321093572575,
+           -1.3718174214418486,
+           -1.4362309488413003,
+           -1.4954791697751348,
+           -1.5478213304716564,
+           -1.5917072490296162,
+           -1.6258099325170594,
+           -1.6490522683013835,
+           -1.6606272021460495,
+           -1.6600109809015329,
+           -1.646969212516958,
+           -1.6215556762324141,
+           -1.584103996687082,
+           -1.5352124727949048,
+           -1.4757225212001024,
+           -1.4066913507454464,
+           -1.329359624799125,
+           -1.24511498903609,
+           -1.155452440399557,
+           -1.0619325860913291,
+           -0.9661388877987381,
+           -0.8696350048768796,
+           -0.7739233404813008,
+           -0.6804058570105429,
+           -0.5903481626895714,
+           -0.5048477813971728,
+           -0.4248074052344891,
+           -0.3509137967402688,
+           -0.2836228584717064,
+           -0.22315122569002566,
+           -0.1694745672372145,
+           -0.12233260469744617,
+           -0.08124068504189659,
+           -0.045507571590754595,
+           -0.014258956605640222,
+           0.013533949761442114,
+           0.03902153132864041,
+           0.06343946757823217,
+           0.08807000319774762,
+           0.11420182734634081,
+           0.14308964163941942,
+           0.1759145052597254,
+           0.21374602706611884,
+           0.2575074285341458,
+           0.3079444289699985,
+           0.36559880750153706,
+           0.43078737729588723,
+           0.5035869692711983,
+           0.583825868733378,
+           0.6710819827476946,
+           0.7646878428219973,
+           0.863742371001623,
+           0.9671291622122307,
+           1.0735408660688484,
+           1.1815090916945539,
+           1.289439113416544,
+           1.3956485272419425,
+           1.498408901034558,
+           1.5959893780714267,
+           1.6867011363194964,
+           1.768941575859526,
+           1.841237105234565,
+           1.9022834242477542,
+           1.9509822553036242,
+           1.9864735565070197,
+           2.008162355468244,
+           2.0157394705578304,
+           2.0091955330999363,
+           1.988827886101663,
+           1.9552401086081144,
+           1.9093340953792826,
+           1.852294804847712,
+           1.7855679697029216,
+           1.7108312394627117,
+           1.6299593886841688,
+           1.5449843739456472,
+           1.4580511536600635,
+           1.3713702938752197,
+           1.2871684677259827,
+           1.2076380139767648,
+           1.1348867496346642,
+           1.0708892321222576,
+           1.017440637886821,
+           0.9761143672174291,
+           0.9482244007749757,
+           0.9347933239126469,
+           0.9365268028988136,
+           0.9537951458300411,
+           0.9866224139980534,
+           1.0346833707999523,
+           1.0973083692947372,
+           1.1734960907337124,
+           1.2619338594227614,
+           1.3610250786648408,
+           1.468923162682684,
+           1.5835711844747684,
+           1.7027463232892148,
+           1.8241080811311396,
+           1.9452491482318024,
+           2.063747734879735,
+           2.177220152960898,
+           2.283372425796315,
+           2.380049729503702,
+           2.4652825225268287,
+           2.53732830085078,
+           2.5947080227596597,
+           2.636236376180602,
+           2.661045210520976,
+           2.6685996197926514,
+           2.6587063406874094,
+           2.631514313791103,
+           2.587507443788563,
+           2.527489780733476,
+           2.4525635246960142,
+           2.3641004259681724,
+           2.2637073083769663,
+           2.153186580365848,
+           2.0344927140477695,
+           1.9096857636390516,
+           1.7808830593846345,
+           1.6502102497736006,
+           1.5197528727031608,
+           1.3915096151756379,
+           1.2673483717180944,
+           1.1489661353063234,
+           1.0378536531275377,
+           0.9352656556178104,
+           0.842197323998547,
+           0.7593675026208386,
+           0.687208991796597,
+           0.6258660787232795,
+           0.5751992830404925,
+           0.534797114002682,
+           0.5039944626752683,
+           0.48189708926594726,
+           0.46741151672673814,
+           0.4592795107787281,
+           0.4561162167364766,
+           0.4564509376228784,
+           0.45876947814623537,
+           0.46155694658443314,
+           0.46333990222371185,
+           0.462726759763861,
+           0.4584454133544236,
+           0.44937712030703914,
+           0.4345857860237483,
+           0.413341914674597,
+           0.38514063149900984,
+           0.34971333868624493,
+           0.3070327336375263,
+           0.25731109178621747,
+           0.20099189165341225,
+           0.1387350329954964,
+           0.07139606537088874,
+           6.80548373138949e-16
+          ],
+          [
+           0,
+           -0.07520772324784195,
+           -0.15144988762618244,
+           -0.2273711380090368,
+           -0.3016113702032806,
+           -0.37284632091488695,
+           -0.4398273067724614,
+           -0.5014190412383585,
+           -0.5566345064894269,
+           -0.6046659319330617,
+           -0.644911030071707,
+           -0.676993761454704,
+           -0.7007790404192358,
+           -0.7163809487013478,
+           -0.7241641908810872,
+           -0.7247386998062284,
+           -0.7189474772215604,
+           -0.7078479303409696,
+           -0.69268713459647,
+           -0.6748716119847974,
+           -0.6559323592631428,
+           -0.6374859870292752,
+           -0.6211929362119823,
+           -0.6087138199775164,
+           -0.6016649944048639,
+           -0.6015744890257011,
+           -0.6098394276798292,
+           -0.6276860410282333,
+           -0.6561333151289308,
+           -0.6959612370473248,
+           -0.7476844905386385,
+           -0.8115323250164623,
+           -0.8874351724710459,
+           -0.975018423359903,
+           -1.073603597781148,
+           -1.1822169667614046,
+           -1.2996054947269737,
+           -1.4242597927286118,
+           -1.5544435972599235,
+           -1.6882291258925564,
+           -1.8235375125281565,
+           -1.9581833955500523,
+           -2.0899226248003013,
+           -2.2165019708221263,
+           -2.335709664297827,
+           -2.4454255665200217,
+           -2.543669773803687,
+           -2.6286484900047613,
+           -2.698796061066024,
+           -2.752812152367982,
+           -2.789693161558023,
+           -2.8087570937829187,
+           -2.809661279622334,
+           -2.7924124848050256,
+           -2.757369140892487,
+           -2.705235613162256,
+           -2.6370486113652536,
+           -2.5541560362560016,
+           -2.4581887352392013,
+           -2.351025809742183,
+           -2.2347542708818753,
+           -2.111623974892899,
+           -1.9839988823297332,
+           -1.8543057725082734,
+           -1.7249816048805888,
+           -1.5984207505786965,
+           -1.4769233194580393,
+           -1.3626457805790506,
+           -1.2575550178685608,
+           -1.1633868790875994,
+           -1.081610167257166,
+           -1.0133968920344323,
+           -0.9595994474201647,
+           -0.920735215317367,
+           -0.8969789159379146,
+           -0.8881628402360299,
+           -0.8937849109761422,
+           -0.9130243323212917,
+           -0.9447644075080477,
+           -0.9876219346425785,
+           -1.0399824360259995,
+           -1.1000403404382493,
+           -1.1658431237568188,
+           -1.2353383238928357,
+           -1.30642228341328,
+           -1.3769894388426918,
+           -1.4449809702593972,
+           -1.5084316484633893,
+           -1.5655137690214445,
+           -1.6145771415179835,
+           -1.6541842063210992,
+           -1.6831394774636883,
+           -1.700512655645181,
+           -1.7056549162194812,
+           -1.6982080493145806,
+           -1.6781063086197243,
+           -1.6455710074020584,
+           -1.6010980804452246,
+           -1.5454390043647594,
+           -1.4795756318442648,
+           -1.4046896437230496,
+           -1.3221274528958045,
+           -1.2333615024691529,
+           -1.1399489849139588,
+           -1.043489067020915,
+           -0.9455797359341281,
+           -0.8477753837200701,
+           -0.7515462218525806,
+           -0.6582405633920108,
+           -0.5690509309286218,
+           -0.48498484462040303,
+           -0.40684101955584634,
+           -0.33519155841704557,
+           -0.270370567663965,
+           -0.21246945722149332,
+           -0.16133900920126235,
+           -0.11659812495529205,
+           -0.0776489862043646,
+           -0.043698199505360906,
+           -0.013783338131838598,
+           0.013195844532606525,
+           0.03844237720679009,
+           0.06322415504293438,
+           0.08883416764207282,
+           0.11654994112864707,
+           0.14759328598186006,
+           0.18309143560854016,
+           0.2240406260508588,
+           0.2712731056117814,
+           0.32542847609228825,
+           0.386930156950935,
+           0.45596763279013075,
+           0.5324849964358838,
+           0.61617613823703,
+           0.7064867611382758,
+           0.8026232248932768,
+           0.9035680459279994,
+           1.0081017063125328,
+           1.1148302604344953,
+           1.222218075472802,
+           1.3286249055280144,
+           1.432346382754255,
+           1.5316569150489003,
+           1.6248539112176095,
+           1.7103022128459535,
+           1.786477598506398,
+           1.8520082408419074,
+           1.9057130402141713,
+           1.946635828999224,
+           1.9740745365867758,
+           1.9876045243815215,
+           1.987095439719172,
+           1.9727210941869755,
+           1.9449620415383961,
+           1.9046007090393076,
+           1.8527091192718168,
+           1.7906294226213977,
+           1.7199476393439,
+           1.6424611798122632,
+           1.5601408680528062,
+           1.4750883330892095,
+           1.3894897514247802,
+           1.305567019218443,
+           1.2255275019306977,
+           1.1515135506552916,
+           1.0855529869127785,
+           1.029511740977066,
+           0.9850497831694959,
+           0.9535814140324272,
+           0.9362408796211057,
+           0.9338541547080117,
+           0.946917592446541,
+           0.975583977473535,
+           1.0196563444558209,
+           1.0785897399511393,
+           1.1515009166346533,
+           1.2371857600336478,
+           1.3341440635166937,
+           1.4406110918937516,
+           1.5545952118769255,
+           1.6739207227815962,
+           1.7962748967476263,
+           1.9192581374559425,
+           2.040436092250547,
+           2.15739250655215,
+           2.2677815925818368,
+           2.3693786971029613,
+           2.460128094814822,
+           2.5381868041547184,
+           2.6019634188582637,
+           2.650151069316552,
+           2.6817537695905855,
+           2.696105565419592,
+           2.6928820717835253,
+           2.6721041713109,
+           2.6341338325927612,
+           2.579662195685558,
+           2.5096902561685983,
+           2.4255026545822598,
+           2.3286352406462885,
+           2.220837227401894,
+           2.104028875815481,
+           1.9802557524106892,
+           1.851640678724844,
+           1.7203345400202943,
+           1.588467140609027,
+           1.4580992839683844,
+           1.3311772178523904,
+           1.2094905188642924,
+           1.0946343991605476,
+           0.9879773024543875,
+           0.890634520209392,
+           0.8034484052979325,
+           0.7269755933062533,
+           0.6614814652816083,
+           0.6069419044438649,
+           0.56305221774087,
+           0.5292429156297345,
+           0.5047018745176935,
+           0.48840225007635096,
+           0.47913537000557316,
+           0.4755477152004553,
+           0.4761810015922582,
+           0.4795143035391003,
+           0.48400711524539775,
+           0.4881422303233165,
+           0.49046733160443756,
+           0.48963422328518985,
+           0.48443470436463515,
+           0.4738321743554514,
+           0.4569881770381026,
+           0.43328322263662294,
+           0.40233137978128586,
+           0.36398829214098377,
+           0.3183524464990945,
+           0.26575969494740426,
+           0.2067712093237601,
+           0.1421552165761716,
+           0.0728630250817275,
+           6.917412759595503e-16
+          ],
+          [
+           0,
+           -0.07590849469238507,
+           -0.15224603714898405,
+           -0.2276467543887334,
+           -0.3007619951979526,
+           -0.3703006978806261,
+           -0.4350682924993012,
+           -0.4940030873191048,
+           -0.5462091529826385,
+           -0.5909848071754893,
+           -0.6278459149500609,
+           -0.6565433526333379,
+           -0.677074133011126,
+           -0.6896858524850269,
+           -0.6948742930295044,
+           -0.6933741886911564,
+           -0.6861433436010844,
+           -0.6743404615307176,
+           -0.6592972115262395,
+           -0.6424852059299795,
+           -0.6254787022745198,
+           -0.6099139556626305,
+           -0.5974462403658947,
+           -0.589705626100799,
+           -0.588252634018479,
+           -0.5945349087947569,
+           -0.6098460259564068,
+           -0.6352875080676865,
+           -0.6717350506751958,
+           -0.7198098606979276,
+           -0.7798558886216193,
+           -0.8519235943625912,
+           -0.9357607284657788,
+           -1.0308104392779642,
+           -1.1362168371018038,
+           -1.2508379625240496,
+           -1.3732659226715656,
+           -1.5018537806313907,
+           -1.6347486141145675,
+           -1.769930003864023,
+           -1.9052530741937845,
+           -2.0384950908658026,
+           -2.1674045282168044,
+           -2.289751450412491,
+           -2.403378012656794,
+           -2.5062478781612403,
+           -2.596493366009281,
+           -2.672459193337181,
+           -2.732741751386327,
+           -2.7762229571642707,
+           -2.8020978482425485,
+           -2.809895234592832,
+           -2.799490884784316,
+           -2.771112900375441,
+           -2.7253391176472554,
+           -2.663086565438128,
+           -2.5855931971340924,
+           -2.4943922992335272,
+           -2.391280153843775,
+           -2.2782776937129112,
+           -2.1575870320179975,
+           -2.0315438716162046,
+           -1.9025668968292468,
+           -1.7731053226751847,
+           -1.6455858200351967,
+           -1.522360049488142,
+           -1.405654021122736,
+           -1.2975204529321516,
+           -1.199795227511377,
+           -1.1140589475066136,
+           -1.0416044670445592,
+           -0.9834111322206769,
+           -0.9401263021809517,
+           -0.9120545473468301,
+           -0.899154737188547,
+           -0.9010450411484241,
+           -0.9170156774623445,
+           -0.9460490603292318,
+           -0.9868468206215587,
+           -1.0378630133729074,
+           -1.0973426805461444,
+           -1.1633648135734942,
+           -1.2338886598474363,
+           -1.3068022431210333,
+           -1.379971921393324,
+           -1.4512917883663559,
+           -1.5187317363083175,
+           -1.5803830387627817,
+           -1.6345003799183289,
+           -1.6795393518220938,
+           -1.7141885585745757,
+           -1.7373956051922619,
+           -1.7483864044778754,
+           -1.7466774040883166,
+           -1.7320805138125035,
+           -1.7047006954276789,
+           -1.664926359853051,
+           -1.6134128941343326,
+           -1.5510598096653412,
+           -1.4789821588089915,
+           -1.398477005881461,
+           -1.3109858569021882,
+           -1.2180540476961998,
+           -1.1212881595574375,
+           -1.0223125740786527,
+           -0.9227262929452145,
+           -0.8240611342034241,
+           -0.7277423741885878,
+           -0.6350528350752606,
+           -0.5471013237037844,
+           -0.46479621038248026,
+           -0.3888247997653255,
+           -0.3196389931519659,
+           -0.25744757654157724,
+           -0.20221529568918567,
+           -0.15366870265437058,
+           -0.11130858237807563,
+           -0.07442859712833479,
+           -0.042139625539468234,
+           -0.013399125506304193,
+           0.01295527988631239,
+           0.03816890362909478,
+           0.06353077945255349,
+           0.09033318645339747,
+           0.11983100346322706,
+           0.15320198816689737,
+           0.19150905307492724,
+           0.23566555998911473,
+           0.28640457783588613,
+           0.34425294760388575,
+           0.4095108751522763,
+           0.48223763094730926,
+           0.5622437789046754,
+           0.6490901884171575,
+           0.7420939085709503,
+           0.8403408059203481,
+           0.9427046914897588,
+           1.0478724933524435,
+           1.154374872491842,
+           1.2606215357167867,
+           1.364940373847251,
+           1.4656194494285568,
+           1.5609507785494836,
+           1.6492747980106186,
+           1.7290243835345105,
+           1.7987672876575878,
+           1.8572458974128148,
+           1.903413271205604,
+           1.936464500012036,
+           1.9558625481323886,
+           1.9613578605468445,
+           1.9530011742291495,
+           1.9311491358949309,
+           1.8964625045345116,
+           1.8498968993685585,
+           1.7926862380630353,
+           1.7263191915833942,
+           1.6525091564492351,
+           1.5731584080280197,
+           1.4903172458155955,
+           1.406139069701754,
+           1.3228324317919975,
+           1.2426111887792823,
+           1.167643933076219,
+           1.1000039055412552,
+           1.0416205879749847,
+           0.9942341396608105,
+           0.9593537798324896,
+           0.9382211285277036,
+           0.9317794039580756,
+           0.9406492380326883,
+           0.9651117163050291,
+           1.0050990781307854,
+           1.060193331360598,
+           1.1296328478565891,
+           1.2123268160895382,
+           1.306877239672971,
+           1.411607990489434,
+           1.524600256457815,
+           1.6437335710925074,
+           1.7667314785467616,
+           1.891210777070403,
+           2.014733198449056,
+           2.1348583231076073,
+           2.2491965015645157,
+           2.355460553516246,
+           2.451515045989525,
+           2.535422010976458,
+           2.6054820493116395,
+           2.6602698791406643,
+           2.6986635214265315,
+           2.7198664682583367,
+           2.7234223485093465,
+           2.7092217855083245,
+           2.677501328435003,
+           2.628834528558386,
+           2.5641154185842274,
+           2.4845348337054247,
+           2.3915501820707052,
+           2.286849426198283,
+           2.1723101716411173,
+           2.0499548717105824,
+           1.9219032445923525,
+           1.7903230596667472,
+           1.657380481870088,
+           1.5251911658029667,
+           1.395773265023001,
+           1.2710034672906352,
+           1.152577084902776,
+           1.0419731227491298,
+           0.9404251180684376,
+           0.848898398316375,
+           0.7680742407954125,
+           0.6983412438172655,
+           0.6397940385161391,
+           0.5922392875087676,
+           0.5552087359542066,
+           0.5279789066844438,
+           0.5095968682598462,
+           0.49891135707029843,
+           0.4946084055875451,
+           0.49525052173690276,
+           0.49931838170477394,
+           0.5052539423232425,
+           0.5115038508004451,
+           0.516562029623856,
+           0.5190103428692694,
+           0.5175563061081997,
+           0.5110668841392835,
+           0.49859752674278185,
+           0.47941571984245046,
+           0.4530184745991231,
+           0.41914333635259066,
+           0.3777726649168713,
+           0.32913111321206406,
+           0.27367640813371463,
+           0.21208371143634902,
+           0.1452240048405428,
+           0.0741370983527616,
+           7.010069300183297e-16
+          ],
+          [
+           0,
+           -0.07638572721680471,
+           -0.15258678465400125,
+           -0.22723827606919136,
+           -0.2990145046150325,
+           -0.3666687662794963,
+           -0.42907107161840013,
+           -0.4852427756481356,
+           -0.5343871747013492,
+           -0.5759152322573988,
+           -0.6094657206461319,
+           -0.6349192089434808,
+           -0.6524054857167904,
+           -0.6623041745439325,
+           -0.6652384761511717,
+           -0.6620621491461274,
+           -0.6538400171586022,
+           -0.6418224592895836,
+           -0.6274144988168336,
+           -0.6121402480941017,
+           -0.597603591861862,
+           -0.5854460935754936,
+           -0.5773031872103598,
+           -0.5747597682908406,
+           -0.5793063212421741,
+           -0.5922967149069339,
+           -0.6149087642434478,
+           -0.6481085945873774,
+           -0.6926197568623975,
+           -0.7488979298853281,
+           -0.8171119121487005,
+           -0.8971314534459468,
+           -0.9885223101596607,
+           -1.090548731060764,
+           -1.202183397433126,
+           -1.3221246567731368,
+           -1.4488207077931328,
+           -1.5805002204934293,
+           -1.715208712994263,
+           -1.8508498606856287,
+           -1.985230786723436,
+           -2.1161102791609014,
+           -2.2412488016845145,
+           -2.358459114030849,
+           -2.465656296028041,
+           -2.5609059764603903,
+           -2.64246960449949,
+           -2.7088456664617633,
+           -2.7588058426186595,
+           -2.7914252155148516,
+           -2.806105779941235,
+           -2.8025926620193746,
+           -2.7809826269754883,
+           -2.741724637939795,
+           -2.6856124170593945,
+           -2.6137691507609873,
+           -2.527624668501077,
+           -2.4288856042236113,
+           -2.3194992176190223,
+           -2.2016117040463796,
+           -2.0775219539355128,
+           -1.9496318314067305,
+           -1.8203941250714073,
+           -1.692259379477098,
+           -1.5676228420823142,
+           -1.4487727573480575,
+           -1.337841206602078,
+           -1.2367586305790723,
+           -1.1472130824834117,
+           -1.0706151452441426,
+           -1.0080693101347789,
+           -0.9603524584547924,
+           -0.9278999173221399,
+           -0.9107993789797814,
+           -0.9087927848133776,
+           -0.9212860851072169,
+           -0.9473665980687367,
+           -0.9858275113950499,
+           -1.0351989010201743,
+           -1.0937844887596813,
+           -1.1597032270590804,
+           -1.230934688168724,
+           -1.3053671494654135,
+           -1.3808472083468077,
+           -1.4552297304904256,
+           -1.5264269349386168,
+           -1.5924554483639473,
+           -1.6514802181866963,
+           -1.7018542584575285,
+           -1.7421533114236112,
+           -1.7712046386972917,
+           -1.7881093056377668,
+           -1.7922574871775356,
+           -1.7833364987554987,
+           -1.7613314378776146,
+           -1.7265185055847354,
+           -1.679451258200099,
+           -1.6209402136662783,
+           -1.5520263992624441,
+           -1.473949574510615,
+           -1.3881119910217627,
+           -1.2960386567692588,
+           -1.1993351532391245,
+           -1.0996441081476886,
+           -0.9986014526630064,
+           -0.8977935897435754,
+           -0.7987165694592212,
+           -0.7027383088371821,
+           -0.6110648094238853,
+           -0.524711217560119,
+           -0.44447844311975354,
+           -0.3709359054682541,
+           -0.3044108144057047,
+           -0.2449842229654792,
+           -0.1924939124820809,
+           -0.14654399279361002,
+           -0.10652092630128618,
+           -0.07161551827624449,
+           -0.040850261487843556,
+           -0.013111284827699988,
+           0.01281596338373893,
+           0.03820826329000127,
+           0.06436444018270981,
+           0.0925645326069183,
+           0.12402941174259965,
+           0.1598819408892394,
+           0.20111072487130568,
+           0.24853743316909083,
+           0.30278858921997837,
+           0.3642726039268743,
+           0.43316269683301784,
+           0.5093861970652181,
+           0.5926205518259917,
+           0.6822961970744498,
+           0.7776062674478564,
+           0.8775229449295905,
+           0.9808200727584091,
+           1.0861014969844378,
+           1.1918344470779514,
+           1.2963871329332988,
+           1.3980696219104387,
+           1.4951769691427363,
+           1.5860335095558598,
+           1.6690371825950836,
+           1.7427027515716527,
+           1.8057027991301688,
+           1.8569054282084223,
+           1.8954076729011302,
+           1.9205637240613445,
+           1.9320071978513307,
+           1.9296668187846264,
+           1.9137750485743397,
+           1.8848693643936372,
+           1.8437860707165175,
+           1.7916467132784828,
+           1.729837347311035,
+           1.6599810905021435,
+           1.5839045596810062,
+           1.5035989448137523,
+           1.4211766106590016,
+           1.3388242319326622,
+           1.258753559152784,
+           1.1831509771523308,
+           1.1141270548839826,
+           1.0536672926144304,
+           1.003585250648995,
+           0.9654791928004663,
+           0.9406932990927708,
+           0.930284397529799,
+           0.9349950366646677,
+           0.9552335722557297,
+           0.9910617760797545,
+           1.0421902969928352,
+           1.1079821179077913,
+           1.187463962027117,
+           1.279345412068164,
+           1.3820453219634627,
+           1.493724926108962,
+           1.612326890922976,
+           1.7356194111829264,
+           1.8612443328005752,
+           1.9867681873296115,
+           2.109734953924861,
+           2.227719323387003,
+           2.33837922733117,
+           2.4395064136896774,
+           2.5290738972480633,
+           2.6052791895517022,
+           2.6665823144507894,
+           2.7117377412750474,
+           2.7398195140655925,
+           2.7502390188549546,
+           2.7427550076748686,
+           2.7174756834656333,
+           2.6748528398293674,
+           2.6156682389816988,
+           2.5410125956959457,
+           2.45225771001254,
+           2.3510224527547012,
+           2.2391334515424424,
+           2.1185814475633746,
+           1.9914743918965352,
+           1.859988422346643,
+           1.726317905836612,
+           1.5926257464244726,
+           1.460995144674995,
+           1.3333839508677008,
+           1.211582683514198,
+           1.0971771877258882,
+           0.9915167875893819,
+           0.8956886459177574,
+           0.8104988870953336,
+           0.7364608681745752,
+           0.6737908041806249,
+           0.6224107701993513,
+           0.5819589198311729,
+           0.5518065815264004,
+           0.5310817255875216,
+           0.518698139396551,
+           0.5133895105227417,
+           0.5137475001691718,
+           0.5182627957844157,
+           0.5253680638622188,
+           0.5334816835930435,
+           0.5410511300433031,
+           0.5465948921368549,
+           0.5487418553992496,
+           0.5462671509973025,
+           0.5381235691920221,
+           0.5234677544260498,
+           0.5016805378310004,
+           0.47238091742563404,
+           0.4354333627482425,
+           0.39094829489572214,
+           0.33927577050810087,
+           0.2809925746419809,
+           0.21688309825487004,
+           0.14791453685552883,
+           0.07520709369811895,
+           7.082637558517263e-16
+          ],
+          [
+           0,
+           -0.07663523477398763,
+           -0.15246925751476625,
+           -0.2261497094422779,
+           -0.29638521668618356,
+           -0.3619842601911236,
+           -0.4218913816272525,
+           -0.4752197443909984,
+           -0.5212791622516683,
+           -0.5595988245834578,
+           -0.5899440834873527,
+           -0.6123268210156845,
+           -0.6270090803066674,
+           -0.634499818537044,
+           -0.635544817809482,
+           -0.6311099679006879,
+           -0.6223583077038835,
+           -0.6106213758198944,
+           -0.597365570926524,
+           -0.5841543554591285,
+           -0.5726072483670577,
+           -0.5643566413844519,
+           -0.5610035360691346,
+           -0.564073334163359,
+           -0.5749728206444101,
+           -0.5949494569024235,
+           -0.6250540512667067,
+           -0.6661077967682946,
+           -0.7186745634233025,
+           -0.7830392069319699,
+           -0.8591925105692393,
+           -0.9468232157503236,
+           -1.045317423255935,
+           -1.1537654656769747,
+           -1.2709761667741226,
+           -1.3954982197273833,
+           -1.5256482382385954,
+           -1.6595448665802883,
+           -1.795148181149,
+           -1.9303034807265662,
+           -2.0627884488834836,
+           -2.1903625826518422,
+           -2.3108177190307218,
+           -2.4220284566867893,
+           -2.5220012653032247,
+           -2.608921099615599,
+           -2.6811943887317113,
+           -2.7374873526266343,
+           -2.7767587048116393,
+           -2.798285930535486,
+           -2.801684480351344,
+           -2.7869193858361205,
+           -2.7543089836344437,
+           -2.7045206214598188,
+           -2.6385584106594955,
+           -2.5577432797850963,
+           -2.463685767678808,
+           -2.358252168392882,
+           -2.243524799563999,
+           -2.1217573067720363,
+           -1.9953260354809608,
+           -1.866678596478392,
+           -1.7382808179935265,
+           -1.6125633162379835,
+           -1.491868925038892,
+           -1.378402204302752,
+           -1.2741821967774725,
+           -1.1809995242012896,
+           -1.1003788093625833,
+           -1.0335472824038097,
+           -0.9814102810251553,
+           -0.944534188715434,
+           -0.9231371768076333,
+           -0.9170879293812242,
+           -0.9259123393733646,
+           -0.9488079743667035,
+           -0.9846659260188695,
+           -1.0320994824757528,
+           -1.0894789026070093,
+           -1.1549714284041237,
+           -1.2265855508278236,
+           -1.3022184476882064,
+           -1.3797054420904487,
+           -1.4568702882243947,
+           -1.531575078760925,
+           -1.6017685850643177,
+           -1.6655318873328349,
+           -1.7211202254230549,
+           -1.7670001005975247,
+           -1.801880781228069,
+           -1.8247395084853248,
+           -1.8348398576534022,
+           -1.8317428829289868,
+           -1.8153108540947693,
+           -1.7857035778009671,
+           -1.7433674797635579,
+           -1.6890178024420264,
+           -1.6236144412829412,
+           -1.5483320972511083,
+           -1.4645255603140628,
+           -1.373691054444488,
+           -1.2774246667357856,
+           -1.1773789491673803,
+           -1.075218819841976,
+           -0.9725779002748688,
+           -0.8710164063872358,
+           -0.7719816638008168,
+           -0.6767722441120231,
+           -0.5865066199719432,
+           -0.5020971155675128,
+           -0.42422978859856564,
+           -0.35335072366357173,
+           -0.28965904907963136,
+           -0.23310681383473197,
+           -0.18340568304781593,
+           -0.1400402335110994,
+           -0.10228746008180775,
+           -0.06924194319470027,
+           -0.03984598163690896,
+           -0.012923866652429252,
+           0.012780633341988881,
+           0.03856459094960259,
+           0.06572511114327233,
+           0.09551849524188162,
+           0.12912047795981688,
+           0.16758861067891961,
+           0.2118278092073493,
+           0.26256000319709366,
+           0.32029871913276875,
+           0.38532930203,
+           0.4576953358872018,
+           0.5371916631786244,
+           0.6233642332903518,
+           0.7155168330873027,
+           0.8127245742248279,
+           0.913853835902209,
+           1.0175881929549775,
+           1.122459701783755,
+           1.2268847746247304,
+           1.329203749704826,
+           1.427723164046527,
+           1.5207596596947328,
+           1.6066844049157039,
+           1.6839668907843004,
+           1.7512169711468772,
+           1.8072240501232255,
+           1.850992385275622,
+           1.8817715648138083,
+           1.8990813315496184,
+           1.9027300619850507,
+           1.8928263625962847,
+           1.8697834132901823,
+           1.834315866022723,
+           1.787429290283561,
+           1.730402342018312,
+           1.6647620139922472,
+           1.5922524990819198,
+           1.5147983591893912,
+           1.4344628373746053,
+           1.3534022757586075,
+           1.2738177036128713,
+           1.1979047362313522,
+           1.127802973725245,
+           1.0655461085066955,
+           1.0130139403710092,
+           0.971887458905148,
+           0.9436080853263294,
+           0.9293420713732041,
+           0.9299509337813048,
+           0.9459686620328547,
+           0.9775862778751737,
+           1.0246441514056757,
+           1.0866322945393931,
+           1.1626986628802467,
+           1.2516653060304788,
+           1.3520520188493255,
+           1.4621069666863076,
+           1.579843590548736,
+           1.703082947597456,
+           1.8295005119785979,
+           1.9566763539790029,
+           2.0821475344550104,
+           2.2034614984088705,
+           2.3182292277703422,
+           2.424176919463903,
+           2.519194990553582,
+           2.601383276781195,
+           2.6690913825677924,
+           2.7209532572846284,
+           2.755915211460484,
+           2.7732567441783593,
+           2.772603725372377,
+           2.753933659849195,
+           2.7175729491550555,
+           2.66418625827014,
+           2.594758281883526,
+           2.5105683851137037,
+           2.4131587616139516,
+           2.3042969039635683,
+           2.1859333134208745,
+           2.060155485320306,
+           1.9291392900213773,
+           1.7950989253828902,
+           1.6602366439448883,
+           1.5266934557682335,
+           1.3965019763496325,
+           1.2715425290620674,
+           1.1535035247290528,
+           1.0438470294497457,
+           0.9437802984765202,
+           0.8542339021670344,
+           0.7758469035981023,
+           0.7089593705011726,
+           0.6536123211726866,
+           0.6095550194801134,
+           0.5762593526079375,
+           0.5529408512616012,
+           0.5385857499686146,
+           0.531983338877473,
+           0.5317627316462932,
+           0.5364330697321195,
+           0.5444261041685282,
+           0.5541400436530607,
+           0.5639835336799792,
+           0.5724186360646415,
+           0.5780017113120041,
+           0.5794211669695523,
+           0.5755311217725482,
+           0.5653801457868123,
+           0.5482343680410331,
+           0.5235943919571607,
+           0.49120562143975344,
+           0.451061772639829,
+           0.4034015237966945,
+           0.3486984336877027,
+           0.28764443357224606,
+           0.22112736369370495,
+           0.1502031792022841,
+           0.07606358789859576,
+           7.134478006290146e-16
+          ],
+          [
+           0,
+           -0.07665486491786405,
+           -0.15189470944551425,
+           -0.22439123095888078,
+           -0.2928985068667083,
+           -0.35629059792267165,
+           -0.41359591461223166,
+           -0.46402741367983497,
+           -0.5070077991496708,
+           -0.5421890308255973,
+           -0.5694655899883083,
+           -0.5889811131375189,
+           -0.6011281760854352,
+           -0.6065411881627714,
+           -0.6060825352623932,
+           -0.600822286387531,
+           -0.5920119468309002,
+           -0.5810528978098263,
+           -0.5694603033315621,
+           -0.5588233866631284,
+           -0.550763077911847,
+           -0.5468881083254572,
+           -0.5487506740568,
+           -0.5578028110424085,
+           -0.5753546127567392,
+           -0.6025353840838023,
+           -0.6402587582720143,
+           -0.6891927114784611,
+           -0.7497352929954235,
+           -0.8219967517180333,
+           -0.9057885841236044,
+           -1.0006198598072362,
+           -1.1057010016272728,
+           -1.2199550131833787,
+           -1.34203596124778,
+           -1.470354339494325,
+           -1.603108766934165,
+           -1.738323314187531,
+           -1.8738896071110287,
+           -2.007612733967403,
+           -2.137259882384105,
+           -2.260610558340389,
+           -2.3755071932560528,
+           -2.4799049281510426,
+           -2.5719193763101855,
+           -2.64987120770074,
+           -2.7123264686054496,
+           -2.7581316469037134,
+           -2.786442614848573,
+           -2.7967467241329045,
+           -2.7888774890651096,
+           -2.763021468883966,
+           -2.7197171453809084,
+           -2.6598457825635897,
+           -2.58461444644544,
+           -2.495531550516545,
+           -2.394375471465786,
+           -2.2831569459104344,
+           -2.164076108185888,
+           -2.0394751580040116,
+           -1.9117877518547532,
+           -1.7834862908305362,
+           -1.6570283281686076,
+           -1.5348033409932467,
+           -1.4190811019790726,
+           -1.311962848162759,
+           -1.2153363768452812,
+           -1.1308361040970598,
+           -1.059809002114162,
+           -1.00328719049311,
+           -0.9619677968463873,
+           -0.9362005279734283,
+           -0.9259832082880471,
+           -0.9309653518877647,
+           -0.9504596431755711,
+           -0.9834610129760432,
+           -1.0286728171996273,
+           -1.0845394576716152,
+           -1.1492846338143365,
+           -1.2209542831004059,
+           -1.2974631607277727,
+           -1.3766439273738675,
+           -1.4562975600945585,
+           -1.5342438766861421,
+           -1.608370968649797,
+           -1.6766823720834783,
+           -1.7373408684492888,
+           -1.788707896597876,
+           -1.8293776713919496,
+           -1.8582052398729172,
+           -1.874327859745393,
+           -1.877179253157496,
+           -1.8664964671274114,
+           -1.842319256063684,
+           -1.8049820870706497,
+           -1.755099050527132,
+           -1.6935421322765727,
+           -1.621413465379328,
+           -1.5400123247754882,
+           -1.4507977538241212,
+           -1.355347814457606,
+           -1.2553165301285212,
+           -1.152389640979229,
+           -1.0482403125608453,
+           -0.9444859325085281,
+           -0.8426470941053844,
+           -0.7441098026115135,
+           -0.6500918512603208,
+           -0.5616142012394504,
+           -0.4794780666733785,
+           -0.40424825501929096,
+           -0.3362431492149845,
+           -0.27553154454821815,
+           -0.2219363749488394,
+           -0.17504518475387745,
+           -0.13422702748087667,
+           -0.09865530717716123,
+           -0.06733592468351504,
+           -0.0391399545275226,
+           -0.012839961590836717,
+           0.012851026884654485,
+           0.03923894661538049,
+           0.0676076127415483,
+           0.09917823431310833,
+           0.13507061828548453,
+           0.1762671110821317,
+           0.22358025539566523,
+           0.2776250443351678,
+           0.33879653669377047,
+           0.40725345899202553,
+           0.48290826553365745,
+           0.5654239608888414,
+           0.6542178142097629,
+           0.7484719160077278,
+           0.8471503500038363,
+           0.9490225799161829,
+           1.052692487948593,
+           1.1566323524457305,
+           1.2592209204832805,
+           1.358784620439565,
+           1.4536408726955103,
+           1.5421423957898015,
+           1.622721372221565,
+           1.6939323335598628,
+           1.7544926487884915,
+           1.803319552366769,
+           1.8395627280940656,
+           1.8626315696206417,
+           1.8722163658109046,
+           1.8683028060278724,
+           1.851179363167008,
+           1.8214372869165394,
+           1.7799631219476413,
+           1.727923851030547,
+           1.6667449468344442,
+           1.5980817938301377,
+           1.5237851088455443,
+           1.4458611412482665,
+           1.3664275676232744,
+           1.2876661078066038,
+           1.2117729763891736,
+           1.140908344088993,
+           1.0771460151345715,
+           1.022424529140308,
+           0.9785008687431547,
+           0.9469078980934021,
+           0.9289165734524781,
+           0.9255038576309288,
+           0.9373271374204908,
+           0.9647057907274691,
+           1.0076103814853703,
+           1.0656597797018619,
+           1.1381263155697634,
+           1.2239488850300335,
+           1.3217537341844239,
+           1.4298824661521399,
+           1.5464266408355,
+           1.6692681798349152,
+           1.7961246493012704,
+           1.9245983762445473,
+           2.0522282616003427,
+           2.1765430884474353,
+           2.295115087759344,
+           2.4056125178410994,
+           2.5058500373034316,
+           2.593835704479566,
+           2.667813517296656,
+           2.726300514789955,
+           2.768117592071001,
+           2.792413331437097,
+           2.7986803197485326,
+           2.7867636021116895,
+           2.756861109896035,
+           2.709516092593468,
+           2.645601773331333,
+           2.5662986323411827,
+           2.4730648968782907,
+           2.367600975754043,
+           2.251808717920385,
+           2.127746494023846,
+           1.9975811946604254,
+           1.8635383069548022,
+           1.72785127046859,
+           1.5927113234266137,
+           1.4602190306760383,
+           1.3323386362296916,
+           1.2108563069716132,
+           1.0973432320819256,
+           0.9931244175621778,
+           0.8992538700701993,
+           0.8164967027512648,
+           0.7453185219218512,
+           0.6858822716619047,
+           0.6380525281256472,
+           0.6014070512901968,
+           0.5752552234866075,
+           0.5586628358080066,
+           0.5504825295113714,
+           0.5493890636061353,
+           0.5539184652794926,
+           0.562510029430389,
+           0.5735500695491473,
+           0.5854162860032884,
+           0.5965216102896075,
+           0.6053564050877697,
+           0.6105279493819574,
+           0.6107962141818359,
+           0.6051050354808173,
+           0.5926079144284487,
+           0.572687817102102,
+           0.5449705041054744,
+           0.5093310894808338,
+           0.46589370480069114,
+           0.41502432333174216,
+           0.35731697630791,
+           0.2935737641309728,
+           0.2247792254218678,
+           0.15206977223130408,
+           0.07669902671666334,
+           7.165134511644309e-16
+          ],
+          [
+           0,
+           -0.07644452976551071,
+           -0.15086852879596005,
+           -0.22197911898388314,
+           -0.28858661126214114,
+           -0.34964050868627733,
+           -0.4042617243114531,
+           -0.4517701372919218,
+           -0.49170673088752226,
+           -0.5238496958998683,
+           -0.5482240389499752,
+           -0.5651044030114666,
+           -0.5750109834834465,
+           -0.5786986023767955,
+           -0.577139181358568,
+           -0.5714980269358438,
+           -0.5631045035833258,
+           -0.5534178189947807,
+           -0.5439887760830385,
+           -0.5364184555275379,
+           -0.5323148777617336,
+           -0.5332487520940605,
+           -0.5407094516101648,
+           -0.5560623547505325,
+           -0.5805086678538798,
+           -0.615048788082191,
+           -0.6604501842862247,
+           -0.7172206664961887,
+           -0.7855877854260335,
+           -0.8654849548220024,
+           -0.9565447253148727,
+           -1.0580994626965061,
+           -1.169189500578084,
+           -1.28857865173265,
+           -1.4147767786888545,
+           -1.5460689468990605,
+           -1.6805505174759867,
+           -1.8161673852392446,
+           -1.9507604354336976,
+           -2.0821131823133636,
+           -2.2080014676227706,
+           -2.3262440390347106,
+           -2.4347527993338067,
+           -2.531581517378163,
+           -2.6149718217074267,
+           -2.683395356447085,
+           -2.7355910655212576,
+           -2.7705966830843813,
+           -2.787773642837284,
+           -2.786824773259898,
+           -2.767804316038046,
+           -2.731119986956262,
+           -2.6775269878485863,
+           -2.608114070235318,
+           -2.524281941343553,
+           -2.427714486674309,
+           -2.3203434556570617,
+           -2.2043074140096057,
+           -2.081905904354901,
+           -1.955549872060472,
+           -1.8277095033342468,
+           -1.7008606851253918,
+           -1.5774313298075524,
+           -1.4597488111427734,
+           -1.3499897315482559,
+           -1.2501331848597206,
+           -1.1619185949678807,
+           -1.086809100946494,
+           -1.025961326273925,
+           -0.9802022167261931,
+           -0.9500134622261134,
+           -0.9355238365056792,
+           -0.9365095993053144,
+           -0.9524029136078512,
+           -0.9823080397716438,
+           -1.0250248840267953,
+           -1.0790793051133307,
+           -1.142759424084223,
+           -1.2141570423109331,
+           -1.2912131548904233,
+           -1.371766453786116,
+           -1.453603649350013,
+           -1.5345104019047695,
+           -1.6123216476408158,
+           -1.6849701253032905,
+           -1.75053196137533,
+           -1.8072682503638715,
+           -1.8536616713369596,
+           -1.8884473093962209,
+           -1.9106369980797113,
+           -1.9195366620838268,
+           -1.9147563150829385,
+           -1.8962125504397551,
+           -1.864123548686476,
+           -1.818996810199423,
+           -1.7616099999201476,
+           -1.6929854588873428,
+           -1.6143590906018295,
+           -1.5271444650898882,
+           -1.4328930966634892,
+           -1.3332519400523888,
+           -1.229919211670636,
+           -1.1245996768141202,
+           -1.0189605488049003,
+           -0.9145891224609545,
+           -0.812953212457322,
+           -0.7153653885389278,
+           -0.6229518961976158,
+           -0.5366270260024582,
+           -0.45707355048726145,
+           -0.3847296880348987,
+           -0.31978288261067545,
+           -0.2621705108166634,
+           -0.21158744805957824,
+           -0.1675002481928162,
+           -0.12916752029253226,
+           -0.09566592656859625,
+           -0.06592108082170223,
+           -0.03874250098360649,
+           -0.01286166529000978,
+           0.013027857846328634,
+           0.04022928917075141,
+           0.07000163517724153,
+           0.10351990667232298,
+           0.14183763232080918,
+           0.18585268089445503,
+           0.23627732057668777,
+           0.29361333438342685,
+           0.3581328803004312,
+           0.42986563640512704,
+           0.5085926087814127,
+           0.5938468075540347,
+           0.6849208182252242,
+           0.7808811161976718,
+           0.8805887964557684,
+           0.982726222312965,
+           1.0858289411868465,
+           1.18832207550623,
+           1.2885602766593913,
+           1.384870232443687,
+           1.4755946462933178,
+           1.5591365615330084,
+           1.6340028872425425,
+           1.6988459945236707,
+           1.7525022928176763,
+           1.7940267644924492,
+           1.8227225305703891,
+           1.8381646389154647,
+           1.84021740555294,
+           1.82904479664341,
+           1.8051135091150936,
+           1.7691885878673752,
+           1.7223216023422812,
+           1.6658315905331202,
+           1.6012791595547,
+           1.530434304225721,
+           1.4552386644050528,
+           1.377763084088732,
+           1.3001614569338067,
+           1.224621940853903,
+           1.1533166961311991,
+           1.0883513452577223,
+           1.0317153672888373,
+           0.9852346244173494,
+           0.9505271740425447,
+           0.9289634468230672,
+           0.921631771776529,
+           0.9293101057909934,
+           0.9524446799150945,
+           0.9911361119948815,
+           1.0451333585693332,
+           1.1138356927128887,
+           1.1963027032528146,
+           1.2912721191518726,
+           1.397185075507356,
+           1.5122182591512225,
+           1.634322206603212,
+           1.7612648791711583,
+           1.8906795129302674,
+           2.02011563825691,
+           2.147092087066999,
+           2.269150757790084,
+           2.3839098895795954,
+           2.489115608772646,
+           2.5826905518921843,
+           2.6627784395222753,
+           2.727783572472819,
+           2.776404343410699,
+           2.8076600005942933,
+           2.820910062002426,
+           2.8158659540475193,
+           2.7925946349120094,
+           2.7515141538113865,
+           2.693381289503229,
+           2.6192715994522406,
+           2.5305523906509,
+           2.4288492898226814,
+           2.316007240559105,
+           2.1940468842443948,
+           2.0651173872907265,
+           1.9314468567191159,
+           1.7952915375968133,
+           1.658885008097121,
+           1.524388580517084,
+           1.3938440797390454,
+           1.2691301053459623,
+           1.1519227915860906,
+           1.0436619629761998,
+           0.9455234454762351,
+           0.8583981373279761,
+           0.782878273728175,
+           0.719251139744584,
+           0.6675003007578032,
+           0.627314233820735,
+           0.5981020612780724,
+           0.5790159142817614,
+           0.5689792927585072,
+           0.5667206438924134,
+           0.5708112568188636,
+           0.5797064700151106,
+           0.5917891122656961,
+           0.6054140498807038,
+           0.6189526931684127,
+           0.6308363244134514,
+           0.6395971474664476,
+           0.643906024476453,
+           0.6426059565706904,
+           0.6347404800414292,
+           0.6195762848875359,
+           0.5966195149192492,
+           0.5656253741874823,
+           0.5266008390371513,
+           0.47980045418187633,
+           0.42571537032027673,
+           0.365055955432873,
+           0.2987284776023144,
+           0.22780650980598888,
+           0.15349784279014247,
+           0.07710780742936263,
+           7.174339672743204e-16
+          ],
+          [
+           0,
+           -0.07600621652334698,
+           -0.14940020569176737,
+           -0.2189356245750217,
+           -0.2834893509153016,
+           -0.3420955649437893,
+           -0.3939755274526465,
+           -0.4385622418319183,
+           -0.47551932003632424,
+           -0.5047535223412334,
+           -0.5264206044923636,
+           -0.5409242793105261,
+           -0.5489082785937236,
+           -0.5512416807386948,
+           -0.5489978453323687,
+           -0.5434274635796671,
+           -0.5359263885777341,
+           -0.5279990481658171,
+           -0.5212183618298247,
+           -0.5171831788722113,
+           -0.5174743252956745,
+           -0.5236103897531219,
+           -0.5370043933287671,
+           -0.5589224733904802,
+           -0.5904456685702134,
+           -0.6324358210842175,
+           -0.6855065157887686,
+           -0.7499998549242689,
+           -0.825969726370242,
+           -0.9131720648784297,
+           -1.0110624340708885,
+           -1.1188010762257834,
+           -1.2352653915024068,
+           -1.3590696228811106,
+           -1.4885913423254469,
+           -1.6220041620223886,
+           -1.757315936313855,
+           -1.8924115790690899,
+           -2.0250995013099073,
+           -2.153160577926388,
+           -2.2743984827593704,
+           -2.3866901899797317,
+           -2.4880354276710572,
+           -2.576603887207256,
+           -2.6507790390629653,
+           -2.7091974810297,
+           -2.75078284666261,
+           -2.7747734277225575,
+           -2.780742811379801,
+           -2.7686129974588987,
+           -2.7386596390433686,
+           -2.6915092369981215,
+           -2.6281283108507565,
+           -2.549804760322059,
+           -2.4581218189293983,
+           -2.3549251789323034,
+           -2.2422840310986905,
+           -2.122446909324611,
+           -1.9977933554511247,
+           -1.8707825206181952,
+           -1.7438998936999184,
+           -1.619603392956648,
+           -1.5002700728944771,
+           -1.3881446840478902,
+           -1.2852912793395923,
+           -1.1935489878953474,
+           -1.1144929774761994,
+           -1.0494015024696097,
+           -0.9992297886886605,
+           -0.9645913426212114,
+           -0.9457470952439464,
+           -0.9426026034011065,
+           -0.954713339608955,
+           -0.9812979086672241,
+           -1.021258841324871,
+           -1.0732104360344703,
+           -1.1355129538887205,
+           -1.20631232318343,
+           -1.2835843822847919,
+           -1.3651825856663926,
+           -1.4488880206034958,
+           -1.5324605328939473,
+           -1.613689740245218,
+           -1.6904447220291554,
+           -1.7607212136291615,
+           -1.8226852015344386,
+           -1.874711909919119,
+           -1.915419288275054,
+           -1.9436952497457878,
+           -1.9587180676190912,
+           -1.9599695090281446,
+           -1.94724046600793,
+           -1.9206290301481854,
+           -1.8805311435588465,
+           -1.8276241411009249,
+           -1.7628436723330958,
+           -1.6873546521074116,
+           -1.6025170322746292,
+           -1.5098473100192515,
+           -1.4109767879419124,
+           -1.30760767473853,
+           -1.2014681614369969,
+           -1.0942676255814354,
+           -0.9876531041563432,
+           -0.8831681357996989,
+           -0.7822150050604962,
+           -0.6860213278950428,
+           -0.5956118006904424,
+           -0.5117857978570826,
+           -0.43510134895150016,
+           -0.36586585930079735,
+           -0.30413376244078655,
+           -0.24971111280433522,
+           -0.2021669475563192,
+           -0.16085107180426214,
+           -0.12491775602921278,
+           -0.09335468265095259,
+           -0.06501634399434894,
+           -0.03866097995043742,
+           -0.012990053194526804,
+           0.013310804792280065,
+           0.0415304808300773,
+           0.07289181301803264,
+           0.10851286255255269,
+           0.1493710695036017,
+           0.196271262949315,
+           0.24981839617462237,
+           0.310395755487999,
+           0.3781492496879981,
+           0.45297822989371694,
+           0.5345331203171031,
+           0.622219963876611,
+           0.7152118068016065,
+           0.812466668107232,
+           0.9127516675498434,
+           1.0146727237779625,
+           1.1167090869917686,
+           1.217251841275861,
+           1.314645404182899,
+           1.4072309678901627,
+           1.4933907694923525,
+           1.571592049235492,
+           1.6404295555428108,
+           1.6986654846180578,
+           1.745265799595065,
+           1.77943195828678,
+           1.800627187548665,
+           1.8085965734604166,
+           1.8033803867356848,
+           1.7853202282989642,
+           1.7550577567391197,
+           1.713525942987393,
+           1.6619329835204504,
+           1.6017391870345052,
+           1.5346273262997707,
+           1.4624671123711643,
+           1.387274598356724,
+           1.3111674507602549,
+           1.2363171347158548,
+           1.1648991424675075,
+           1.0990424500841802,
+           1.0407794141802984,
+           0.9919973175840149,
+           0.9543927404414168,
+           0.9294298718766117,
+           0.9183037884710363,
+           0.9219096115876981,
+           0.9408183186833607,
+           0.9752598275217786,
+           1.0251138004040097,
+           1.0899084323357067,
+           1.168827296911125,
+           1.2607241312404585,
+           1.364145251175809,
+           1.477359105042133,
+           1.5983923025278872,
+           1.7250712995312725,
+           1.855068783408261,
+           1.9859536895676266,
+           2.1152436924886824,
+           2.2404589541556548,
+           2.359175882085279,
+           2.469079648331767,
+           2.5680142501111534,
+           2.6540289512858815,
+           2.725420030461466,
+           2.780766873759324,
+           2.818961585701271,
+           2.8392314467660893,
+           2.841153717269354,
+           2.824662470098224,
+           2.790047325041376,
+           2.7379441503526882,
+           2.6693179880765943,
+           2.585438643897796,
+           2.487849555381397,
+           2.3783307102432425,
+           2.258856524917179,
+           2.1315497098249137,
+           1.9986322386202988,
+           1.8623746021143497,
+           1.7250445621082244,
+           1.5888566252005074,
+           1.4559234317565728,
+           1.32821020132548,
+           1.2074932942729009,
+           1.0953238423530323,
+           0.9929972710788176,
+           0.9015293873376489,
+           0.8216395404825023,
+           0.7537411882328259,
+           0.6979400145517786,
+           0.6540395598022866,
+           0.6215541385567386,
+           0.5997286420173649,
+           0.5875646544988649,
+           0.583852160952305,
+           0.5872059888080231,
+           0.5961060157482866,
+           0.6089400880952376,
+           0.6240485344017557,
+           0.6397691269747728,
+           0.6544813411475922,
+           0.6666487881314086,
+           0.6748587514758232,
+           0.6778578381101122,
+           0.6745828605115692,
+           0.6641861940328359,
+           0.6460549995506146,
+           0.6198238626464937,
+           0.5853805724014352,
+           0.5428649412185009,
+           0.49266074736736737,
+           0.4353810596098617,
+           0.3718473738307942,
+           0.3030631507584381,
+           0.2301824876013856,
+           0.15447478113189198,
+           0.07728634227113072,
+           7.162018293862331e-16
+          ],
+          [
+           0,
+           -0.07534397739993655,
+           -0.14750325821435195,
+           -0.21528878229318166,
+           -0.2776537794926993,
+           -0.33372562486222607,
+           -0.3828329061252835,
+           -0.4245269628263038,
+           -0.45859729968512586,
+           -0.4850804354054816,
+           -0.5042619184069613,
+           -0.5166714183861296,
+           -0.5230709827699805,
+           -0.5244367254395584,
+           -0.5219343870508043,
+           -0.5168893674960098,
+           -0.5107519774297502,
+           -0.5050587835923184,
+           -0.5013910286275893,
+           -0.501331187480556,
+           -0.5064187771550042,
+           -0.518106563162708,
+           -0.5377183036542729,
+           -0.5664091409634575,
+           -0.6051296908210412,
+           -0.6545947932085846,
+           -0.7152577778080844,
+           -0.7872909639645623,
+           -0.870572963275355,
+           -0.9646831860882434,
+           -1.068903775449908,
+           -1.1822290077971764,
+           -1.3033820134988092,
+           -1.4308384868669628,
+           -1.562856879039404,
+           -1.6975144025916258,
+           -1.832748027996329,
+           -1.9663995228489395,
+           -2.0962634783874776,
+           -2.220137186961213,
+           -2.3358711808270036,
+           -2.441419218378552,
+           -2.534886509331465,
+           -2.6145750054528065,
+           -2.679024647362882,
+           -2.7270495492600775,
+           -2.7577682199593374,
+           -2.7706270575987824,
+           -2.765416513407014,
+           -2.7422794932109253,
+           -2.7017117496940473,
+           -2.6445542093043977,
+           -2.571977370506973,
+           -2.4854581000744393,
+           -2.38674933666862,
+           -2.2778433816203507,
+           -2.1609296113890215,
+           -2.038347580888948,
+           -1.9125365984047449,
+           -1.7859829384448322,
+           -1.6611659164963748,
+           -1.5405040778278636,
+           -1.426302750537016,
+           -1.320704181001229,
+           -1.225641408529846,
+           -1.1427969468351504,
+           -1.0735672251060133,
+           -1.0190336037853922,
+           -0.9799406229805241,
+           -0.9566819686071824,
+           -0.949294457103965,
+           -0.9574601483422751,
+           -0.9805165028633157,
+           -1.0174743085069327,
+           -1.0670429175068317,
+           -1.1276621626820764,
+           -1.1975401646374448,
+           -1.2746961046849759,
+           -1.3570069238228488,
+           -1.4422568192958767,
+           -1.5281883491245536,
+           -1.6125539229518067,
+           -1.6931664553270742,
+           -1.767947985099898,
+           -1.8349751211705603,
+           -1.8925202589721306,
+           -1.9390876215880175,
+           -1.9734433115728958,
+           -1.994638711019814,
+           -2.00202673441137,
+           -1.9952706171406756,
+           -1.974345107850715,
+           -1.93953012031902,
+           -1.891397085862247,
+           -1.8307884255744846,
+           -1.758790728747678,
+           -1.6767023754470067,
+           -1.5859964737148646,
+           -1.488280092024407,
+           -1.3852508527307752,
+           -1.2786520103373478,
+           -1.1702271680456944,
+           -1.0616757866436792,
+           -0.9546106113838307,
+           -0.8505180859158459,
+           -0.7507227390664079,
+           -0.6563564224749789,
+           -0.5683331475723914,
+           -0.48733012244680696,
+           -0.4137754265499525,
+           -0.3478425880885815,
+           -0.28945214971142313,
+           -0.23828012727717116,
+           -0.19377308864524564,
+           -0.15516940905730592,
+           -0.12152610107072406,
+           -0.0917504741612596,
+           -0.06463575562672999,
+           -0.038899703402029605,
+           -0.013225165376073022,
+           0.013698509310208103,
+           0.043134322480737355,
+           0.07625785047189634,
+           0.11411991069471487,
+           0.15761267923175318,
+           0.20744017790723135,
+           0.2640939360368127,
+           0.3278344980446231,
+           0.3986792967183344,
+           0.4763972468871258,
+           0.5605102399253439,
+           0.6503015401193296,
+           0.7448309041283852,
+           0.8429560690809123,
+           0.9433600877322775,
+           1.0445838348206635,
+           1.145062871222428,
+           1.2431677352451624,
+           1.337246636416609,
+           1.4256694588618921,
+           1.5068719406007858,
+           1.5793988829438,
+           1.6419452610083323,
+           1.6933941518759659,
+           1.7328504700121927,
+           1.7596695985208564,
+           1.7734801272072651,
+           1.7742000512848362,
+           1.7620459443714218,
+           1.737534792243083,
+           1.7014783553719839,
+           1.6549701140705328,
+           1.5993650354792333,
+           1.536252582053535,
+           1.4674235521212176,
+           1.3948315002184672,
+           1.32054962432346,
+           1.2467241252769383,
+           1.1755251376127882,
+           1.1090963983158975,
+           1.049504858931356,
+           0.9986914559184351,
+           0.9584242338505912,
+           0.93025496641865,
+           0.9154803423347603,
+           0.9151086789925309,
+           0.9298329986020274,
+           0.9600111525677106,
+           1.0056535137112328,
+           1.066418576587471,
+           1.1416166179597624,
+           1.230221377071199,
+           1.3308895233653828,
+           1.4419874924605869,
+           1.561625094032253,
+           1.687695132145515,
+           1.8179181334950787,
+           1.9498911555111544,
+           2.081139547406024,
+           2.2091704653947954,
+           2.3315269002932717,
+           2.445840962538138,
+           2.5498851867211547,
+           2.641620664571377,
+           2.719240890820919,
+           2.7812103087106204,
+           2.8262966685375455,
+           2.853596460526442,
+           2.8625528488137166,
+           2.8529657124266805,
+           2.8249935874543035,
+           2.7791474975474837,
+           2.7162768527558274,
+           2.6375477848097035,
+           2.544414465717882,
+           2.438584121633355,
+           2.321976601345272,
+           2.196679484923564,
+           2.0648998199423287,
+           1.9289136479053133,
+           1.7910145302193177,
+           1.653462300238556,
+           1.5184332551928574,
+           1.3879729596095516,
+           1.2639527612610435,
+           1.1480310235337678,
+           1.0416199568858888,
+           0.9458587897954862,
+           0.8615938598671323,
+           0.7893660325536381,
+           0.7294056725775014,
+           0.6816352061362292,
+           0.6456791249840637,
+           0.6208811011264419,
+           0.6063277076433126,
+           0.600878081337621,
+           0.6031987204072429,
+           0.6118024886449039,
+           0.6250907997385495,
+           0.641397883433649,
+           0.65903599133309,
+           0.6763403849564805,
+           0.6917129626447162,
+           0.7036634245361554,
+           0.7108469450012752,
+           0.7120974177613033,
+           0.7064554579523953,
+           0.6931904845745489,
+           0.6718163625280609,
+           0.6421002518256196,
+           0.6040644883003159,
+           0.5579815007317036,
+           0.5043619492155511,
+           0.4439364442635919,
+           0.3776313711308187,
+           0.3065394950701596,
+           0.23188615680000813,
+           0.15499198007799092,
+           0.0772331020742551,
+           7.128288962184838e-16
+          ],
+          [
+           0,
+           -0.07446389894136872,
+           -0.1451951182393137,
+           -0.2110721627771047,
+           -0.27113375771111387,
+           -0.32460819026841053,
+           -0.3709374189917346,
+           -0.40979528823400496,
+           -0.44109933860414435,
+           -0.4650158702475737,
+           -0.48195809110274124,
+           -0.49257736217256914,
+           -0.4977477318293125,
+           -0.49854412666941306,
+           -0.49621473299593655,
+           -0.4921482563944468,
+           -0.4878368831739877,
+           -0.48483588318300097,
+           -0.484720885707006,
+           -0.48904392642424227,
+           -0.4992894019978878,
+           -0.5168310787710049,
+           -0.5428912828735715,
+           -0.578503351247884,
+           -0.6244783477658451,
+           -0.6813769475573356,
+           -0.749487268348479,
+           -0.828809283064665,
+           -0.9190462867400792,
+           -1.0196037168716832,
+           -1.129595444065095,
+           -1.2478574636654967,
+           -1.3729687336779428,
+           -1.5032787242791619,
+           -1.6369410741048722,
+           -1.7719525925246573,
+           -1.9061967092114598,
+           -2.0374903559555686,
+           -2.1636331738182544,
+           -2.282457873721716,
+           -2.3918805421237668,
+           -2.489949676518861,
+           -2.5748927584042156,
+           -2.645159223578042,
+           -2.6994587699973556,
+           -2.736794050021002,
+           -2.7564869241533514,
+           -2.758197604251722,
+           -2.741936181919801,
+           -2.708066218411952,
+           -2.657300261428244,
+           -2.590687347082346,
+           -2.5095927373672247,
+           -2.4156703299359212,
+           -2.3108283533947516,
+           -2.1971891232566563,
+           -2.077043777253958,
+           -1.9528030303415846,
+           -1.8269450864471541,
+           -1.7019619134642259,
+           -1.5803051284288472,
+           -1.4643327502638408,
+           -1.3562580576533718,
+           -1.2581017399943346,
+           -1.171648451163892,
+           -1.098408770946342,
+           -1.0395874499328406,
+           -0.9960586636901161,
+           -0.9683488346474336,
+           -0.9566273995560888,
+           -0.9607057109353361,
+           -0.9800440672502281,
+           -1.0137666733869202,
+           -1.060684145000513,
+           -1.119322992078492,
+           -1.1879613529142208,
+           -1.2646701035942423,
+           -1.347358343597208,
+           -1.4338221581727715,
+           -1.5217954852011952,
+           -1.6090018699465658,
+           -1.6932058765209475,
+           -1.7722629402525756,
+           -1.8441664900412673,
+           -1.907091243005346,
+           -1.9594316733983106,
+           -1.9998347813742727,
+           -2.0272264315975246,
+           -2.0408306933063334,
+           -2.0401817882191207,
+           -2.025128436261885,
+           -1.995830576939957,
+           -1.9527486316208835,
+           -1.8966256544046975,
+           -1.8284628921346597,
+           -1.7494894331943056,
+           -1.661126766144941,
+           -1.564949189529983,
+           -1.4626411103897887,
+           -1.3559523388786845,
+           -1.2466525282024616,
+           -1.1364859219484438,
+           -1.0271275545345102,
+           -0.9201420054605183,
+           -0.8169457355221993,
+           -0.7187739350457829,
+           -0.6266526930577243,
+           -0.5413771552267932,
+           -0.4634961810073607,
+           -0.3933038406770279,
+           -0.33083791520622025,
+           -0.2758853806224352,
+           -0.22799467832065073,
+           -0.1864943981730689,
+           -0.15051783670881852,
+           -0.1190327422127786,
+           -0.09087542611770025,
+           -0.06478830886497976,
+           -0.03945988127874671,
+           -0.01356600161912878,
+           0.01418858462480287,
+           0.04502961965243705,
+           0.0800746962444902,
+           0.12029764963827173,
+           0.16649694039043325,
+           0.219268886490273,
+           0.2789864771316224,
+           0.3457843557684244,
+           0.41955040003163585,
+           0.4999241548227054,
+           0.5863021967564641,
+           0.6778503276151282,
+           0.7735223161700965,
+           0.8720847361531522,
+           0.9721472876727382,
+           1.0721978440598992,
+           1.1706413397011755,
+           1.2658415101118325,
+           1.3561644160109427,
+           1.4400226305492105,
+           1.5159189445093098,
+           1.5824884489378623,
+           1.638537888243577,
+           1.6830812385481149,
+           1.7153705545379119,
+           1.734921241098287,
+           1.7415310408580316,
+           1.7352921821247058,
+           1.7165962997700215,
+           1.6861319202765708,
+           1.6448744869548566,
+           1.5940690876926118,
+           1.5352062308670733,
+           1.469991190661745,
+           1.4003076065886282,
+           1.3281761694209704,
+           1.2557093532772394,
+           1.1850632580372904,
+           1.1183877049528874,
+           1.0577757792078322,
+           1.0052140349395686,
+           0.96253457022683,
+           0.9313701418809198,
+           0.9131134233903295,
+           0.9088814156112003,
+           0.9194859009962034,
+           0.945410691160879,
+           0.9867962577994472,
+           1.0434321622508969,
+           1.1147575136233463,
+           1.199869493822187,
+           1.297539794765717,
+           1.4062386232243296,
+           1.5241657467264738,
+           1.649287884289689,
+           1.779381592515082,
+           1.9120806645837791,
+           2.044926950179522,
+           2.175423421022947,
+           2.301088251591802,
+           2.4195086590783697,
+           2.52839325133776,
+           2.625621666406206,
+           2.709290351275534,
+           2.7777534194426483,
+           2.8296576440746577,
+           2.8639707835819124,
+           2.880002595560149,
+           2.8774180695675127,
+           2.8562425947872514,
+           2.8168589707680782,
+           2.759996363450711,
+           2.6867114998571497,
+           2.5983625784898896,
+           2.496576544200497,
+           2.3832105318784462,
+           2.2603084190198115,
+           2.1300535397911493,
+           1.9947186999113968,
+           1.8566146904741267,
+           1.718038528356492,
+           1.5812226504603992,
+           1.4482862587964103,
+           1.3211899541739847,
+           1.2016947095379185,
+           1.0913261220006703,
+           0.9913447481897522,
+           0.9027231740339887,
+           0.826130301390297,
+           0.7619231541694733,
+           0.7101463203241918,
+           0.6705389578357949,
+           0.6425491073373029,
+           0.625354875818022,
+           0.6178918893591071,
+           0.6188862621379259,
+           0.6268921976993359,
+           0.640333229919212,
+           0.6575460278044554,
+           0.6768256322734133,
+           0.69647096564705,
+           0.714829456344915,
+           0.7303396520828171,
+           0.7415707538485055,
+           0.7472580885233789,
+           0.7463336479961374,
+           0.7379509541464653,
+           0.7215036587976322,
+           0.6966374518312264,
+           0.6632550249562847,
+           0.6215140187109754,
+           0.5718180615917628,
+           0.5148011881722193,
+           0.4513060932010436,
+           0.38235683666904857,
+           0.30912675673013806,
+           0.23290246958273844,
+           0.15504493489543908,
+           0.07694863959824139,
+           7.073463703085915e-16
+          ],
+          [
+           0,
+           -0.0733740510387285,
+           -0.14249697797282798,
+           -0.20632456942397936,
+           -0.2639894586136317,
+           -0.3148276863815348,
+           -0.358399630107807,
+           -0.39450472086445826,
+           -0.42318953247018215,
+           -0.4447489983758725,
+           -0.4597206911057986,
+           -0.46887227979107104,
+           -0.4731824595738792,
+           -0.4738158178094691,
+           -0.4720922616983108,
+           -0.46945177617675254,
+           -0.4674154058991604,
+           -0.46754345775412437,
+           -0.47139199792624426,
+           -0.48046876802261523,
+           -0.49618966688515476,
+           -0.5198369377726837,
+           -0.5525201647137933,
+           -0.595141117822561,
+           -0.6483633967598582,
+           -0.712587706508274,
+           -0.7879334630186979,
+           -0.874227271437429,
+           -0.9709986503534376,
+           -1.0774831960036906,
+           -1.1926331950925009,
+           -1.3151355084251561,
+           -1.4434363645726584,
+           -1.5757725278439658,
+           -1.7102081423248032,
+           -1.8446764077307705,
+           -1.9770251169976343,
+           -2.1050649830826402,
+           -2.226619605993291,
+           -2.339575882572238,
+           -2.4419336423382245,
+           -2.5318533032817236,
+           -2.6077003817719944,
+           -2.6680857597482364,
+           -2.7119007085282854,
+           -2.7383457895873913,
+           -2.7469528956335005,
+           -2.7375998567840605,
+           -2.710517212720768,
+           -2.6662869380854093,
+           -2.6058331005436055,
+           -2.530404624196799,
+           -2.4415505206457024,
+           -2.341088131362797,
+           -2.2310650936770138,
+           -2.1137158944767886,
+           -1.991414006973511,
+           -1.866620713312085,
+           -1.741831796825542,
+           -1.6195233403090148,
+           -1.5020978895323558,
+           -1.3918322337465565,
+           -1.2908280173332343,
+           -1.2009663299053501,
+           -1.123867327711552,
+           -1.0608558194237425,
+           -1.0129336072144746,
+           -0.9807592129218182,
+           -0.9646354429818385,
+           -0.9645050589747702,
+           -0.9799546276336821,
+           -1.0102264297039496,
+           -1.0542381158513658,
+           -1.1106096145446345,
+           -1.1776966259343953,
+           -1.2536298813578872,
+           -1.336359213948426,
+           -1.4237013751528638,
+           -1.513390447409672,
+           -1.6031296468200058,
+           -1.690643282667062,
+           -1.773727643690667,
+           -1.8502996139523,
+           -1.9184418830434464,
+           -1.9764437046981072,
+           -2.022836272299114,
+           -2.056421916432449,
+           -2.076296485118074,
+           -2.081864437745917,
+           -2.0728463648283397,
+           -2.049278832947395,
+           -2.0115066430854514,
+           -1.9601677762124106,
+           -1.896171477980956,
+           -1.820670100273529,
+           -1.7350254670811993,
+           -1.6407706621155,
+           -1.5395682425005681,
+           -1.4331659642831882,
+           -1.323351159392846,
+           -1.211904928831744,
+           -1.100557312742985,
+           -0.9909445647930513,
+           -0.8845695969350579,
+           -0.7827665727171801,
+           -0.6866705151494399,
+           -0.5971926616279664,
+           -0.5150021469526331,
+           -0.4405144299200172,
+           -0.3738867035317844,
+           -0.31502034797394873,
+           -0.26357030376864865,
+           -0.21896106446584912,
+           -0.1804088184171366,
+           -0.14694911183410406,
+           -0.11746926443816275,
+           -0.0907446480971399,
+           -0.06547784095103161,
+           -0.04033959710724432,
+           -0.014010526844029397,
+           0.014777634478889851,
+           0.04720227853557302,
+           0.08431276635276039,
+           0.12699686200516508,
+           0.17595166513456637,
+           0.23165983267190596,
+           0.2943717426964329,
+           0.36409409902417667,
+           0.44058530778700195,
+           0.523357781179655,
+           0.6116871431755447,
+           0.7046281319134677,
+           0.8010368182053097,
+           0.8995985936595197,
+           0.9988612294781389,
+           1.0972721719528487,
+           1.1932191265112582,
+           1.2850728917826535,
+           1.3712313409033094,
+           1.450163410852643,
+           1.5204519529955958,
+           1.5808343194744416,
+           1.6302396101867391,
+           1.6678215826294163,
+           1.692986330015682,
+           1.705413959271496,
+           1.705073646698933,
+           1.6922316116562797,
+           1.6674517235332453,
+           1.6315886402608282,
+           1.5857735630458294,
+           1.5313928773189054,
+           1.4700601294096551,
+           1.4035819577231197,
+           1.3339187519445697,
+           1.2631409501497626,
+           1.193381998199671,
+           1.1267890855413816,
+           1.065472834215263,
+           1.0114571518441153,
+           0.96663046372093,
+           0.9326995136171378,
+           0.9111468681391636,
+           0.9031931766284884,
+           0.9097651296856228,
+           0.9314699270036569,
+           0.9685769125094079,
+           1.0210068655217701,
+           1.088329254855138,
+           1.1697675729421129,
+           1.2642126737512345,
+           1.3702438462506135,
+           1.4861571691103652,
+           1.6100005167995588,
+           1.7396144265161995,
+           1.87267789343426,
+           2.006758042043639,
+           2.1393625268411594,
+           2.2679934486301274,
+           2.3902015348577397,
+           2.503639324705081,
+           2.6061121222477945,
+           2.6956255333885193,
+           2.770428483157501,
+           2.8290507174204396,
+           2.8703339244071593,
+           2.8934557635805347,
+           2.897946258495438,
+           2.883696192329543,
+           2.8509573352653534,
+           2.8003345272249427,
+           2.732769832874321,
+           2.649519173617766,
+           2.552122018930717,
+           2.442364882523434,
+           2.3222395135371343,
+           2.193896795757611,
+           2.059597465737653,
+           1.9216608314142813,
+           1.7824127146253192,
+           1.6441338529207064,
+           1.5090099780094817,
+           1.3790847406049123,
+           1.256216575575541,
+           1.1420404991184134,
+           1.0379357037285597,
+           0.9449996702112625,
+           0.8640293525365981,
+           0.7955098150462883,
+           0.7396105167748691,
+           0.6961892490245875,
+           0.6648035445059438,
+           0.6447291939623013,
+           0.6349853337319139,
+           0.6343654094015833,
+           0.641473180449947,
+           0.6547628119849389,
+           0.672582005228433,
+           0.6932170505588817,
+           0.7149386472901458,
+           0.7360473238362472,
+           0.7549173106546563,
+           0.7700377658121008,
+           0.7800503278985945,
+           0.7837820713671234,
+           0.7802730626051692,
+           0.7687978579897958,
+           0.7488804441933089,
+           0.7203022920477601,
+           0.6831033740064418,
+           0.6375761771354365,
+           0.5842529240326063,
+           0.5238863885519196,
+           0.45742485731074556,
+           0.38598193754651106,
+           0.31080204320575266,
+           0.23322250089548455,
+           0.1546333027520551,
+           0.07643559224875691,
+           6.998045711564291e-16
+          ],
+          [
+           0,
+           -0.07208441606849679,
+           -0.139433598635254,
+           -0.20108968210245348,
+           -0.25628680853116403,
+           -0.3044746704284098,
+           -0.3453360649982171,
+           -0.3787979720626422,
+           -0.405035836293188,
+           -0.42447091125257186,
+           -0.4377607035503291,
+           -0.4457827355797327,
+           -0.44961202025686603,
+           -0.4504928064813216,
+           -0.44980530547627295,
+           -0.4490282418819694,
+           -0.44969818605042794,
+           -0.45336671252661725,
+           -0.46155649190926307,
+           -0.47571745752684286,
+           -0.4971841937054494,
+           -0.5271356686327473,
+           -0.5665583824539433,
+           -0.6162139215071589,
+           -0.6766118044403421,
+           -0.7479883779141815,
+           -0.8302923718273542,
+           -0.9231775601437429,
+           -1.026002797507895,
+           -1.1378395182662653,
+           -1.2574865978302696,
+           -1.3834922911733858,
+           -1.5141827842711142,
+           -1.6476967259498982,
+           -1.7820249541339725,
+           -1.9150544957342024,
+           -2.04461580681865,
+           -2.1685321321090583,
+           -2.284669802513973,
+           -2.390988257921171,
+           -2.485588580701578,
+           -2.5667593534626905,
+           -2.6330187119325656,
+           -2.683151549132012,
+           -2.716240938186991,
+           -2.7316929755859625,
+           -2.7292544011597992,
+           -2.7090225218178277,
+           -2.6714471489673097,
+           -2.617324450124767,
+           -2.5477828088489223,
+           -2.464260979057919,
+           -2.3684790053441396,
+           -2.262402555524588,
+           -2.1482014710829107,
+           -2.0282034814579357,
+           -1.9048441458656689,
+           -1.7806141786094218,
+           -1.658005378360644,
+           -1.5394564170835712,
+           -1.4272997492499147,
+           -1.3237108766062196,
+           -1.2306611486182475,
+           -1.1498751951569135,
+           -1.0827939780358538,
+           -1.030544314336135,
+           -0.993915570313204,
+           -0.9733440538294645,
+           -0.9689054498557499,
+           -0.9803154521038875,
+           -1.0069385489543596,
+           -1.0478047282713236,
+           -1.1016336781600264,
+           -1.1668658837747654,
+           -1.241699858221004,
+           -1.3241346023356015,
+           -1.4120162671315424,
+           -1.5030878968640593,
+           -1.5950410622996694,
+           -1.6855681544550711,
+           -1.772414099712261,
+           -1.8534262779629511,
+           -1.926601475704393,
+           -1.9901287844891573,
+           -2.0424274598204155,
+           -2.082178883838702,
+           -2.1083519237460586,
+           -2.1202211431454696,
+           -2.117377501220526,
+           -2.0997313605258676,
+           -2.0675078134960203,
+           -2.02123452592559,
+           -1.9617224779841524,
+           -1.8900401553164345,
+           -1.807481900220168,
+           -1.7155312719385076,
+           -1.6158203823641564,
+           -1.5100862660907142,
+           -1.4001254095431581,
+           -1.2877476013267497,
+           -1.174730274115083,
+           -1.062774487245425,
+           -0.9534636493277368,
+           -0.8482260029406921,
+           -0.748301790903647,
+           -0.6547158983254936,
+           -0.5682566198510934,
+           -0.4894610409449309,
+           -0.41860734975147523,
+           -0.35571421641905343,
+           -0.3005471943135657,
+           -0.25263191688737935,
+           -0.21127368966244206,
+           -0.17558291322487427,
+           -0.14450562442449003,
+           -0.11685831286268211,
+           -0.09136606149969557,
+           -0.06670297652855824,
+           -0.04153381463833017,
+           -0.01455568684172418,
+           0.01546128211836948,
+           0.04963543115756319,
+           0.08893821276483058,
+           0.13416296794557012,
+           0.1858986709959568,
+           0.2445093594751505,
+           0.3101198168482873,
+           0.3826079126689893,
+           0.4616038319739932,
+           0.5464962461618028,
+           0.6364452965688634,
+           0.7304020838321186,
+           0.8271341854578358,
+           0.9252565651417982,
+           1.0232670943515767,
+           1.1195857831404095,
+           1.2125967162810904,
+           1.3006916151891281,
+           1.3823138977182592,
+           1.4560020880477287,
+           1.520431438116017,
+           1.5744526602365916,
+           1.6171267367783697,
+           1.647754865522786,
+           1.6659027162695266,
+           1.6714183125923627,
+           1.6644430089425457,
+           1.6454152037010563,
+           1.6150666090729564,
+           1.5744110844212442,
+           1.524726226133189,
+           1.4675280897479137,
+           1.404539594284321,
+           1.3376533201270713,
+           1.2688895563968106,
+           1.2003505778004642,
+           1.1341722313792666,
+           1.0724739877786726,
+           1.0173086577298422,
+           0.97061299112588,
+           0.9341603628901918,
+           0.9095167069999449,
+           0.8980007885089814,
+           0.9006498048861072,
+           0.9181911847918243,
+           0.9510213075164746,
+           0.9991917031942864,
+           1.0624031165440275,
+           1.140007629579207,
+           1.2310188460416098,
+           1.3341299469440262,
+           1.447739237287188,
+           1.5699826233748504,
+           1.6987722926162723,
+           1.8318407173852604,
+           1.9667889750923782,
+           2.10113827130271,
+           2.2323834740916646,
+           2.3580474178174393,
+           2.4757347143436417,
+           2.583183819980879,
+           2.678316146799479,
+           2.759281076526416,
+           2.8244958322926834,
+           2.872679285685126,
+           2.90287892090523,
+           2.9144903408313683,
+           2.9072688774497757,
+           2.8813330571344054,
+           2.837159865036956,
+           2.775571947677729,
+           2.697717083965028,
+           2.6050404376692473,
+           2.4992502744002225,
+           2.382277979262741,
+           2.2562333438940434,
+           2.123356200327657,
+           1.9859655614754548,
+           1.8464074820227243,
+           1.7070028779349569,
+           1.5699965370558926,
+           1.4375085176501161,
+           1.3114890671613813,
+           1.1936781015823987,
+           1.0855701689924797,
+           0.9883856819577063,
+           0.9030490460815014,
+           0.8301741399686557,
+           0.7700574195037905,
+           0.7226787311711981,
+           0.6877097298168326,
+           0.6645296104527181,
+           0.6522476860088874,
+           0.64973217771714,
+           0.6556444361138332,
+           0.6684776821063172,
+           0.6865992522813156,
+           0.7082952531802602,
+           0.731816477515526,
+           0.7554244124483506,
+           0.7774361765677894,
+           0.79626725784097,
+           0.8104709885637003,
+           0.8187737835427285,
+           0.8201052820455359,
+           0.8136226695216131,
+           0.7987286082682028,
+           0.7750823731850754,
+           0.7426039652992389,
+           0.701471157372047,
+           0.6521096080376019,
+           0.5951763589669333,
+           0.5315371990207443,
+           0.46223853597937475,
+           0.3884745562853016,
+           0.31155057279012666,
+           0.2328435567677113,
+           0.15376092102971722,
+           0.075698664099753,
+           6.90272517741743e-16
+          ],
+          [
+           0,
+           -0.07060679883360366,
+           -0.13603308313667625,
+           -0.195415651379986,
+           -0.2480968692427071,
+           -0.2936449769989766,
+           -0.3318681044079477,
+           -0.3628215997605388,
+           -0.3868084538261522,
+           -0.40437277939480293,
+           -0.4162864883622551,
+           -0.42352948626001674,
+           -0.4272638742698264,
+           -0.42880280675773,
+           -0.42957479419129685,
+           -0.4310843633426103,
+           -0.4348700858002117,
+           -0.4424610594583101,
+           -0.4553329739008466,
+           -0.4748649082164999,
+           -0.5022979982503899,
+           -0.5386970698317765,
+           -0.5849162660534011,
+           -0.6415696018599162,
+           -0.7090072603361423,
+           -0.7872983050837227,
+           -0.8762203253847322,
+           -0.975256359370489,
+           -1.0835992593935044,
+           -1.200163477738206,
+           -1.323604064335613,
+           -1.4523424859229424,
+           -1.5845987026704986,
+           -1.7184287780355303,
+           -1.8517671545293606,
+           -1.982472605814909,
+           -2.108376777193613,
+           -2.227334154613794,
+           -2.337272258707186,
+           -2.4362408462097407,
+           -2.5224589168928766,
+           -2.594358369528305,
+           -2.6506232244066066,
+           -2.690223430791259,
+           -2.712442403012814,
+           -2.7168975756819504,
+           -2.703553433179029,
+           -2.672726647168423,
+           -2.6250831440450137,
+           -2.5616271173621037,
+           -2.483682193698431,
+           -2.3928651493680335,
+           -2.291052755232919,
+           -2.180342493236434,
+           -2.0630080370501593,
+           -1.941450516763355,
+           -1.8181466907012078,
+           -1.6955952236920766,
+           -1.5762623185277227,
+           -1.4625279647916916,
+           -1.3566340562221688,
+           -1.260635584622911,
+           -1.1763560460758602,
+           -1.105348095589298,
+           -1.0488603617548213,
+           -1.0078111865138422,
+           -0.9827698903148687,
+           -0.973945983790032,
+           -0.9811865579561054,
+           -1.003981890457029,
+           -1.041479110245578,
+           -1.092503572097895,
+           -1.1555874101080414,
+           -1.2290045702440098,
+           -1.310811470257939,
+           -1.3988923043999246,
+           -1.4910079036371848,
+           -1.584846981984334,
+           -1.678078548003551,
+           -1.7684042387312593,
+           -1.8536093416916941,
+           -1.931611308988355,
+           -2.000504634705262,
+           -2.0586010612772485,
+           -2.1044641997115847,
+           -2.136937789565804,
+           -2.155166983881628,
+           -2.1586122178714664,
+           -2.147055403737547,
+           -2.1205983830218376,
+           -2.0796537576609477,
+           -2.02492840676945,
+           -1.9574001735201159,
+           -1.8782883709740497,
+           -1.7890189033097907,
+           -1.6911849260083047,
+           -1.5865040720868644,
+           -1.4767733489484154,
+           -1.3638228599862536,
+           -1.2494695256170862,
+           -1.1354719694944606,
+           -1.0234876975993183,
+           -0.9150336317603373,
+           -0.8114509666683857,
+           -0.713875203014022,
+           -0.6232120719866991,
+           -0.5401199115376883,
+           -0.4649988864650797,
+           -0.3979872667984614,
+           -0.33896479663627055,
+           -0.2875630031260604,
+           -0.24318211727762776,
+           -0.20501410924392993,
+           -0.17207118484611578,
+           -0.1432189513715301,
+           -0.11721334251673912,
+           -0.09274029773997203,
+           -0.0684571225917121,
+           -0.04303441551769392,
+           -0.015197434187661604,
+           0.01623420911310632,
+           0.05230958852193452,
+           0.09391323525663406,
+           0.14173653329240096,
+           0.19625451466314542,
+           0.2577086882608476,
+           0.3260963789045665,
+           0.40116688395997385,
+           0.48242457720577986,
+           0.5691389084661628,
+           0.6603610673527925,
+           0.7549469048588159,
+           0.8515855419563597,
+           0.9488329439572022,
+           1.0451496070386994,
+           1.1389413924005278,
+           1.2286024568540428,
+           1.3125591685009865,
+           1.3893138641146898,
+           1.4574873017739618,
+           1.5158586883709018,
+           1.5634022162414836,
+           1.599319125056976,
+           1.623064412284918,
+           1.6343674453626091,
+           1.6332458780339585,
+           1.620012438397701,
+           1.595274333015229,
+           1.5599251955415663,
+           1.5151296951931315,
+           1.4623011052924146,
+           1.4030723105112197,
+           1.3392608988018107,
+           1.2728291361542199,
+           1.2058397554119582,
+           1.1404086010461862,
+           1.078655257207098,
+           1.0226528443395306,
+           0.9743781986398649,
+           0.9356636478322218,
+           0.9081515660759338,
+           0.8932528309468394,
+           0.8921102177465153,
+           0.9055676529621323,
+           0.9341461122402711,
+           0.9780267920389677,
+           1.0370420119648982,
+           1.1106741208677915,
+           1.1980624885306046,
+           1.298018470926482,
+           1.4090480452496825,
+           1.5293816259600037,
+           1.6570103994407557,
+           1.789728356818777,
+           1.9251790659133083,
+           2.0609061075782513,
+           2.1944060117289474,
+           2.3231824663241327,
+           2.4448005400447093,
+           2.556939657191297,
+           2.6574440914878332,
+           2.744369803360381,
+           2.8160265314631268,
+           2.871014161656228,
+           2.9082525325719275,
+           2.9270039930280793,
+           2.9268881990612234,
+           2.907888823053323,
+           2.8703520398193523,
+           2.814976849922918,
+           2.7427974941390607,
+           2.6551584001788475,
+           2.553682278982141,
+           2.440232148800787,
+           2.316868207039256,
+           2.185800588974493,
+           2.0493391461792223,
+           1.909841443489023,
+           1.7696602101334709,
+           1.6310914873625955,
+           1.4963246914525512,
+           1.3673957580170488,
+           1.2461444524595107,
+           1.1341768242384138,
+           1.0328336520862016,
+           0.9431655766937007,
+           0.8659154504064775,
+           0.8015082543333937,
+           0.7500487463880654,
+           0.7113268137997609,
+           0.6848303152367023,
+           0.6697650155272636,
+           0.6650810445240812,
+           0.6695051551374394,
+           0.681577917793305,
+           0.6996948729000493,
+           0.7221505721318595,
+           0.7471843756270161,
+           0.7730268370490784,
+           0.7979455026474661,
+           0.8202889740284429,
+           0.8385281366228199,
+           0.851293535413574,
+           0.8574079842872504,
+           0.8559136226944856,
+           0.84609277988668,
+           0.8274821691017743,
+           0.7998801075849791,
+           0.763346638854712,
+           0.7181966165961249,
+           0.6649859903667948,
+           0.6044917073754953,
+           0.5376858075648976,
+           0.4657044369965604,
+           0.3898126333931729,
+           0.3113658444096507,
+           0.23176922111215648,
+           0.15243578420018677,
+           0.07474458734661857,
+           6.788373241547722e-16
+          ],
+          [
+           0,
+           -0.06895471817307365,
+           -0.132326614965831,
+           -0.1893546472661821,
+           -0.23949516746803906,
+           -0.28243880867114607,
+           -0.31812082681758497,
+           -0.346724604597923,
+           -0.3686782002188982,
+           -0.3846440056228703,
+           -0.39550175888313827,
+           -0.40232532969610196,
+           -0.406353860724398,
+           -0.4089579968447748,
+           -0.4116020653123276,
+           -0.41580317911782994,
+           -0.42308832057771734,
+           -0.43495052025982683,
+           -0.4528052761829635,
+           -0.47794835901256594,
+           -0.5115161206140033,
+           -0.5544493664566272,
+           -0.6074617683391222,
+           -0.6710136847667819,
+           -0.745292124724136,
+           -0.8301974397894805,
+           -0.9253371632560697,
+           -1.0300272372781363,
+           -1.1433006844612719,
+           -1.2639235933622721,
+           -1.3904181027184799,
+           -1.521091891509174,
+           -1.6540735156176682,
+           -1.787352781095357,
+           -1.918825212633341,
+           -2.0463395671555986,
+           -2.167747259236324,
+           -2.280952509462774,
+           -2.3839620003833955,
+           -2.474932828050752,
+           -2.55221757040391,
+           -2.6144053561104768,
+           -2.6603579075572905,
+           -2.6892396473064677,
+           -2.700541095750107,
+           -2.6940949455648893,
+           -2.670084372063257,
+           -2.629043323445082,
+           -2.5718487267682684,
+           -2.499704739496912,
+           -2.414119368006837,
+           -2.3168739587418647,
+           -2.209986240300079,
+           -2.095667751351811,
+           -1.9762766260986582,
+           -1.8542668226081815,
+           -1.7321349669979722,
+           -1.6123660459273874,
+           -1.4973792097049534,
+           -1.3894749477788133,
+           -1.2907848674362716,
+           -1.203225245928839,
+           -1.1284554374225761,
+           -1.0678421013003838,
+           -1.0224300802030661,
+           -0.9929205981483694,
+           -0.9796572749578808,
+           -0.9826202672890755,
+           -1.0014286533403314,
+           -1.0353509824736873,
+           -1.0833237173474337,
+           -1.1439771093762388,
+           -1.2156678729761614,
+           -1.2965178643578181,
+           -1.3844578304674149,
+           -1.477275176423731,
+           -1.5726646082750482,
+           -1.6682804442849628,
+           -1.7617893537427367,
+           -1.8509222782530255,
+           -1.9335243166177243,
+           -2.0076014100662425,
+           -2.071362748280779,
+           -2.123257926275789,
+           -2.162008014966681,
+           -2.1866298608778556,
+           -2.1964530990888447,
+           -2.191129544005588,
+           -2.1706348103955992,
+           -2.1352622076916603,
+           -2.085609139143092,
+           -2.0225564193305194,
+           -1.9472410943877925,
+           -1.8610235048069848,
+           -1.7654494671412402,
+           -1.662208564949979,
+           -1.553089628199078,
+           -1.4399345419143053,
+           -1.3245915577508325,
+           -1.2088692855642906,
+           -1.0944925160630568,
+           -0.9830609709337224,
+           -0.8760119949213474,
+           -0.7745880973493167,
+           -0.6798101212369606,
+           -0.5924566698269823,
+           -0.5130502567468388,
+           -0.4418504713515453,
+           -0.3788542694523741,
+           -0.32380331620789854,
+           -0.2761981270676196,
+           -0.2353185788685917,
+           -0.2002502008627479,
+           -0.16991550867292557,
+           -0.14310951661966004,
+           -0.11853845872141103,
+           -0.09486066857412162,
+           -0.07072851525513572,
+           -0.044830267683113975,
+           -0.015930764096535082,
+           0.01709020364350328,
+           0.0552028202228806,
+           0.099196433422743,
+           0.14965382739563293,
+           0.20693128012953965,
+           0.2711449517113346,
+           0.3421639850181743,
+           0.4196105255308645,
+           0.5028666865117805,
+           0.5910883043977067,
+           0.6832251515276289,
+           0.7780471037708582,
+           0.8741756035536759,
+           0.970119618204624,
+           1.0643151730404017,
+           1.1551674412863135,
+           1.241094301278278,
+           1.320570227296755,
+           1.392169365016208,
+           1.4546066563763884,
+           1.5067759214216583,
+           1.5477838753133943,
+           1.5769791555976693,
+           1.5939755555454114,
+           1.5986688010118615,
+           1.5912463672946677,
+           1.572190004970317,
+           1.542270825377526,
+           1.5025369827748651,
+           1.4542941765830673,
+           1.399079378874138,
+           1.338628364838202,
+           1.274837783011864,
+           1.2097226435822142,
+           1.1453702235084409,
+           1.0838914834646673,
+           1.0273711612317042,
+           0.9778177473372817,
+           0.9371145603487868,
+           0.9069731208765033,
+           0.8888899754040757,
+           0.8841080446168762,
+           0.8935834677434472,
+           0.9179587870203112,
+           0.957543167799365,
+           1.0123001836313472,
+           1.0818435159108681,
+           1.1654407287314947,
+           1.262025086081203,
+           1.3702151851361442,
+           1.4883419909160172,
+           1.6144826785656976,
+           1.7465005244166565,
+           1.8820899398143118,
+           2.018825616094102,
+           2.154214648146042,
+           2.2857504302170066,
+           2.4109670727935857,
+           2.52749307470651,
+           2.63310300038497,
+           2.725765958103198,
+           2.80368975000235,
+           2.8653596668270915,
+           2.9095710272093664,
+           2.9354547098790484,
+           2.9424950937681547,
+           2.9305400015475116,
+           2.8998024322961684,
+           2.8508540641255253,
+           2.784610702913614,
+           2.7023100440997627,
+           2.6054822961100474,
+           2.4959143820214584,
+           2.3756085864576013,
+           2.2467366438061043,
+           2.111590368550413,
+           1.9725300063100348,
+           1.831931533239908,
+           1.6921341506180576,
+           1.5553892103493432,
+           1.423811766078437,
+           1.2993358747150159,
+           1.1836746762169543,
+           1.0782861579020444,
+           0.9843453664160005,
+           0.9027236693514713,
+           0.8339754934004848,
+           0.7783327811804416,
+           0.7357072190783556,
+           0.7057000983013819,
+           0.6876194854941984,
+           0.6805042023584983,
+           0.6831539500292556,
+           0.6941647675307792,
+           0.7119688880209075,
+           0.7348779547773998,
+           0.7611284834308027,
+           0.788928409587905,
+           0.8165035428026073,
+           0.8421427591907168,
+           0.8642408054710913,
+           0.8813376557408263,
+           0.892153457053569,
+           0.895618218413107,
+           0.8908955370763043,
+           0.8773998125250052,
+           0.8548065681375777,
+           0.8230556791664133,
+           0.7823474885917724,
+           0.7331319751563796,
+           0.6760913157839156,
+           0.6121163531714706,
+           0.5422776343846571,
+           0.46779182388366297,
+           0.3899844111217916,
+           0.31024972576644155,
+           0.23000934037892576,
+           0.15066997939661408,
+           0.0735820635314906,
+           6.656034140218279e-16
+          ],
+          [
+           0,
+           -0.06714328129962294,
+           -0.12834816586787728,
+           -0.18296236695227253,
+           -0.23056097838353323,
+           -0.27095978101699414,
+           -0.3042218113624581,
+           -0.33065699827583933,
+           -0.350814854484653,
+           -0.36547039119862457,
+           -0.37560360151046956,
+           -0.3823730272126761,
+           -0.38708407974761333,
+           -0.3911529252933053,
+           -0.39606686290755316,
+           -0.40334222015899446,
+           -0.41448086030062115,
+           -0.4309264369721095,
+           -0.45402154552856444,
+           -0.48496690398367426,
+           -0.5247836515568096,
+           -0.5742797799838734,
+           -0.6340216138483631,
+           -0.7043111336268194,
+           -0.7851697919336813,
+           -0.8763293131296899,
+           -0.9772297929960759,
+           -1.0870252328813288,
+           -1.2045964561361704,
+           -1.328571168420306,
+           -1.4573507422479302,
+           -1.5891431344796978,
+           -1.722001187680771,
+           -1.8538654263265801,
+           -1.9826103402929962,
+           -2.1060930539365916,
+           -2.2222032117731256,
+           -2.328912873058854,
+           -2.4243251985242127,
+           -2.506720733425174,
+           -2.5746001415449933,
+           -2.6267223236466575,
+           -2.662136959288083,
+           -2.6802106403519472,
+           -2.680645914995717,
+           -2.6634927283583947,
+           -2.629151927199156,
+           -2.578370685287028,
+           -2.5122299001828288,
+           -2.432123805317138,
+           -2.339732229239597,
+           -2.2369861119864596,
+           -2.1260270523135745,
+           -2.0091618050432265,
+           -1.8888127713928122,
+           -1.767465623841115,
+           -1.6476152784022031,
+           -1.5317114693451976,
+           -1.4221051933604465,
+           -1.3209972716089502,
+           -1.2303902294291202,
+           -1.1520446158786575,
+           -1.087440780632163,
+           -1.0377469965748465,
+           -1.0037946658660442,
+           -0.9860611789546615,
+           -0.9846608141065821,
+           -0.9993438738789243,
+           -1.0295040592991156,
+           -1.0741938870387346,
+           -1.1321477643659186,
+           -1.2018121557443346,
+           -1.2813821080111016,
+           -1.368843252154452,
+           -1.4620182724224482,
+           -1.5586167308909449,
+           -1.6562870601581052,
+           -1.752669490300124,
+           -1.8454486596940753,
+           -1.9324046731241775,
+           -2.011461414329761,
+           -2.0807309926820774,
+           -2.1385533031443793,
+           -2.1835298025670187,
+           -2.2145507505914055,
+           -2.2308153263607116,
+           -2.231844208807323,
+           -2.2174843941276157,
+           -2.187906214562505,
+           -2.1435927130722643,
+           -2.0853217142317946,
+           -2.014141108110879,
+           -1.9313380267161266,
+           -1.8384027377779082,
+           -1.7369882047319025,
+           -1.628866361669149,
+           -1.5158822254139237,
+           -1.3999070120040207,
+           -1.2827914406672523,
+           -1.166320394616814,
+           -1.0521700650693924,
+           -0.9418686339903481,
+           -0.8367614540533811,
+           -0.7379815636766203,
+           -0.6464262338580429,
+           -0.5627400854797837,
+           -0.48730514479989195,
+           -0.42023802533144883,
+           -0.3613942407608236,
+           -0.3103794706087838,
+           -0.26656742259816824,
+           -0.22912376762924241,
+           -0.19703546909859845,
+           -0.16914469189498063,
+           -0.14418636117942615,
+           -0.12082834988546402,
+           -0.09771320902753054,
+           -0.07350031798764746,
+           -0.04690732386310413,
+           -0.016749759876265303,
+           0.018022217783801007,
+           0.05829095877108104,
+           0.10474319535729931,
+           0.15784742508356253,
+           0.2178374133284685,
+           0.28470227014009164,
+           0.3581833842180271,
+           0.4377783180495714,
+           0.5227515864379216,
+           0.6121520606215506,
+           0.7048365664440193,
+           0.7994990820079612,
+           0.8947047920857127,
+           0.9889281270416912,
+           1.0805938064624094,
+           1.1681198248550597,
+           1.2499612608122808,
+           1.3246537634242193,
+           1.3908555712142374,
+           1.447386949516148,
+           1.4932659913021353,
+           1.5277398125994839,
+           1.5503102847081238,
+           1.5607535787283857,
+           1.5591329501450786,
+           1.545804358625708,
+           1.521414696625242,
+           1.4868925854109218,
+           1.4434318841174438,
+           1.3924682417452663,
+           1.3356491990094563,
+           1.2747985121915018,
+           1.2118755204824876,
+           1.1489305079602852,
+           1.0880571180236651,
+           1.0313429590838763,
+           0.9808195934918875,
+           0.9384131256462879,
+           0.905896599291015,
+           0.8848453782226178,
+           0.8765966197711967,
+           0.8822138580057509,
+           0.9024575958361625,
+           0.9377626648641093,
+           0.988222952359911,
+           1.0535839199762704,
+           1.1332431530025047,
+           1.2262589866425158,
+           1.3313670616638436,
+           1.4470044705623426,
+           1.5713409718024685,
+           1.7023165782307461,
+           1.8376846706320658,
+           1.975059652422736,
+           2.11196804997623,
+           2.2459018778132025,
+           2.3743730309687683,
+           2.494967439699268,
+           2.605397724999004,
+           2.7035531271114626,
+           2.787545542540764,
+           2.855750596473722,
+           2.906842794798754,
+           2.939823940209049,
+           2.954044156794503,
+           2.9492150431697555,
+           2.92541466128016,
+           2.883084262020502,
+           2.823016844972006,
+           2.7463378431401604,
+           2.654478409854063,
+           2.5491419594441345,
+           2.4322647717192964,
+           2.305971608784514,
+           2.172527408033385,
+           2.034286204449531,
+           1.8936384965280346,
+           1.7529583017481072,
+           1.614551148883777,
+           1.480604225566379,
+           1.3531398411902578,
+           1.2339732789821491,
+           1.1246759990205997,
+           1.0265450190106093,
+           0.9405791450641589,
+           0.8674625544604501,
+           0.8075560505902508,
+           0.7608961215307714,
+           0.7272017426191274,
+           0.7058886747077101,
+           0.6960908281389949,
+           0.6966880923312004,
+           0.7063398763856733,
+           0.7235234710806202,
+           0.7465762302822009,
+           0.7737404828905364,
+           0.8032100270153255,
+           0.8331770275262559,
+           0.8618781371092139,
+           0.8876386894059185,
+           0.9089138699145831,
+           0.924325854562505,
+           0.9326960150350797,
+           0.9330714212487601,
+           0.924745021430389,
+           0.9072690452921054,
+           0.8804613515829925,
+           0.8444046234081832,
+           0.7994384985346218,
+           0.7461449028170293,
+           0.6853270283248833,
+           0.6179825593730988,
+           0.5452718954003766,
+           0.4684822458486658,
+           0.3889885757194498,
+           0.3082124587357636,
+           0.22757994607920562,
+           0.14847958124161856,
+           0.07222168509188005,
+           6.506915612942926e-16
+          ],
+          [
+           0,
+           -0.06518904210514287,
+           -0.12413417521394642,
+           -0.17629750645906078,
+           -0.22137657033929334,
+           -0.2593139315904474,
+           -0.2902999132256655,
+           -0.31476835861845454,
+           -0.3333855184829786,
+           -0.3470323334967551,
+           -0.3567805565424399,
+           -0.3638633207145353,
+           -0.3696409062152366,
+           -0.3755625873016194,
+           -0.3831255462672846,
+           -0.3938319223241053,
+           -0.4091451170964758,
+           -0.4304465038312187,
+           -0.45899368365389087,
+           -0.4958813992912392,
+           -0.5420061553862923,
+           -0.5980355063270227,
+           -0.664382859539423,
+           -0.7411885072338378,
+           -0.8283074459684734,
+           -0.9253043749092875,
+           -1.0314560845034817,
+           -1.1457612619033146,
+           -1.2669575525013363,
+           -1.3935455330410949,
+           -1.5238190755560026,
+           -1.655901417289362,
+           -1.7877861038947718,
+           -1.9173818453475084,
+           -2.042560219364779,
+           -2.161205078416266,
+           -2.2712624656492997,
+           -2.3707898236086584,
+           -2.458003288129244,
+           -2.5313218981094896,
+           -2.589407619184486,
+           -2.63120017404127,
+           -2.65594579200428,
+           -2.663219132690022,
+           -2.652937799553532,
+           -2.6253690351206234,
+           -2.581128376338248,
+           -2.521170241229053,
+           -2.4467706121951363,
+           -2.3595021721275855,
+           -2.261202432264227,
+           -2.1539355610111413,
+           -2.039948776516234,
+           -1.9216242988747076,
+           -1.8014279671714712,
+           -1.6818557094211224,
+           -1.5653791077933623,
+           -1.4543913259507173,
+           -1.3511546592473989,
+           -1.2577509320612563,
+           -1.1760359005191565,
+           -1.1075987249159216,
+           -1.0537274564912746,
+           -1.0153813408187593,
+           -0.9931705783349791,
+           -0.987344005428849,
+           -0.9977849713273332,
+           -1.0240154913349535,
+           -1.0652085605454291,
+           -1.1202083187222769,
+           -1.1875575713419706,
+           -1.2655319983168305,
+           -1.352180224871168,
+           -1.4453687922328624,
+           -1.542830952523733,
+           -1.642218125205722,
+           -1.7411527937389286,
+           -1.8372815921081531,
+           -1.9283273322212038,
+           -2.0121387547754073,
+           -2.0867368471840737,
+           -2.1503566609894484,
+           -2.201483675616211,
+           -2.238883892469633,
+           -2.2616269998300655,
+           -2.269102120847298,
+           -2.2610258399297125,
+           -2.2374423924229885,
+           -2.198716093997348,
+           -2.145516274888942,
+           -2.0787951654277044,
+           -1.9997593486826242,
+           -1.909835549421797,
+           -1.810631662180887,
+           -1.703894031820246,
+           -1.5914620848662275,
+           -1.4752214671574058,
+           -1.3570568715252251,
+           -1.2388057378284525,
+           -1.1222139767671988,
+           -1.0088948093943324,
+           -0.9002917276995609,
+           -0.7976464703141359,
+           -0.7019727741362544,
+           -0.6140365109127113,
+           -0.5343426513925325,
+           -0.4631293228115294,
+           -0.4003690426456111,
+           -0.34577702739850724,
+           -0.2988262943049475,
+           -0.25876910078262877,
+           -0.2246641056000455,
+           -0.19540849107568953,
+           -0.1697741608071145,
+           -0.14644702556326225,
+           -0.12406831359673925,
+           -0.10127679263759577,
+           -0.07675077041890867,
+           -0.04924874923941108,
+           -0.01764764753967196,
+           0.01902243321922725,
+           0.06154782660777731,
+           0.11050611913537788,
+           0.16624684673173556,
+           0.2288785948788826,
+           0.2982628602912843,
+           0.37401485556681285,
+           0.4555112569377746,
+           0.5419047137384915,
+           0.6321447610816157,
+           0.7250046089994133,
+           0.8191131262379633,
+           0.9129911989430026,
+           1.0050915271702963,
+           1.0938408284992727,
+           1.177683350443471,
+           1.255124553599231,
+           1.3247738166223066,
+           1.3853850325132044,
+           1.4358940129342548,
+           1.4754516922583853,
+           1.503452223946774,
+           1.519555186202113,
+           1.5237012585859937,
+           1.5161208928455974,
+           1.4973356755614482,
+           1.4681522630698278,
+           1.429648955875999,
+           1.3831551657939938,
+           1.33022420967069,
+           1.272600034245527,
+           1.212178633169021,
+           1.1509650555039632,
+           1.0910270216569318,
+           1.0344462546595623,
+           0.9832686996699194,
+           0.9394548407900355,
+           0.9048313308022723,
+           0.8810451259533656,
+           0.8695212649437768,
+           0.8714253500233541,
+           0.8876316804688571,
+           0.9186978572950977,
+           0.964846525994257,
+           1.0259547550872554,
+           1.1015513664124357,
+           1.1908223428000746,
+           1.2926242447313807,
+           1.4055053745043387,
+           1.5277342390551314,
+           1.6573346855106579,
+           1.7921269211252386,
+           1.9297734854796593,
+           2.067829121237211,
+           2.2037933933625897,
+           2.3351648379048373,
+           2.459495381937915,
+           2.574443767041079,
+           2.6778267300412,
+           2.7676667461382207,
+           2.842235219764042,
+           2.900090115648703,
+           2.94010715399139,
+           2.96150384616659,
+           2.9638558173312988,
+           2.947105045504086,
+           2.9115598387037442,
+           2.8578865678925633,
+           2.787093368995572,
+           2.7005062174085386,
+           2.5997379585454894,
+           2.4866510437401144,
+           2.3633148681894403,
+           2.231958733052366,
+           2.0949215542697806,
+           1.9545995137541572,
+           1.813392892574643,
+           1.6736533396245854,
+           1.53763281273072,
+           1.407435382718133,
+           1.284973015792082,
+           1.1719263476458153,
+           1.0697113365203497,
+           0.9794525351847571,
+           0.9019635571439705,
+           0.8377351344082848,
+           0.786930977285078,
+           0.7493914555013482,
+           0.7246449292530117,
+           0.7119263732001493,
+           0.7102027605458523,
+           0.7182045124595856,
+           0.7344621741871982,
+           0.7573473567283715,
+           0.7851168849181032,
+           0.8159590214691842,
+           0.8480405936951394,
+           0.8795538362049747,
+           0.9087617790767776,
+           0.934041056372134,
+           0.9539210831197054,
+           0.9671186481528224,
+           0.9725670928677329,
+           0.9694393889319398,
+           0.9571645875720244,
+           0.9354372852549472,
+           0.9042199309865804,
+           0.8637379845292442,
+           0.8144681179457246,
+           0.757119830402241,
+           0.6926110136461606,
+           0.6220381588139972,
+           0.5466420303829144,
+           0.46776974677520194,
+           0.38683429652443885,
+           0.305272581792633,
+           0.22450311583667945,
+           0.14588450691536672,
+           0.07067583798832817,
+           6.342377667793834e-16
+          ],
+          [
+           0,
+           -0.06310984484180379,
+           -0.11972320426283867,
+           -0.1694212014868243,
+           -0.21202641836861996,
+           -0.2476087028845321,
+           -0.2764840238791614,
+           -0.299206385979727,
+           -0.31655299908212203,
+           -0.32950307355565783,
+           -0.33921077981478254,
+           -0.3469730649050704,
+           -0.3541931553231519,
+           -0.36234069094689575,
+           -0.3729095267268971,
+           -0.3873743043146451,
+           -0.4071469333654726,
+           -0.43353413084532466,
+           -0.4676971460059488,
+           -0.5106147492244582,
+           -0.5630504858055103,
+           -0.625525092988254,
+           -0.6982948523059026,
+           -0.7813365032208545,
+           -0.8743391812205275,
+           -0.976703668347346,
+           -1.0875490608095217,
+           -1.2057267714489217,
+           -1.3298415990979364,
+           -1.4582794168908406,
+           -1.5892408619246667,
+           -1.7207802535616927,
+           -1.8508488310485487,
+           -1.9773412864627504,
+           -2.0981444792151303,
+           -2.2111871557530405,
+           -2.314489464371379,
+           -2.406211051080799,
+           -2.4846965485030954,
+           -2.5485173252182083,
+           -2.5965084466010233,
+           -2.627799907985004,
+           -2.641841334347785,
+           -2.6384194944177346,
+           -2.617668147427671,
+           -2.5800699235526214,
+           -2.5264501299068756,
+           -2.4579625681802417,
+           -2.3760676428112877,
+           -2.2825032253001734,
+           -2.179248916271161,
+           -2.0684845078780163,
+           -1.9525435911385467,
+           -1.8338633722851538,
+           -1.7149318562694902,
+           -1.5982336218277036,
+           -1.4861954493420586,
+           -1.381133069190198,
+           -1.2852002741635244,
+           -1.2003415854183068,
+           -1.1282495785907363,
+           -1.070327867156248,
+           -1.0276606064967386,
+           -1.0009892276980181,
+           -0.9906969385862942,
+           -0.9968013450966595,
+           -1.0189553532340103,
+           -1.05645631532814,
+           -1.1082631887803704,
+           -1.1730212858013522,
+           -1.2490940133565287,
+           -1.3346008380167278,
+           -1.4274605646414171,
+           -1.5254388943233346,
+           -1.6261991287685276,
+           -1.7273548176263762,
+           -1.8265231038916694,
+           -1.9213775113274767,
+           -2.0096989371119576,
+           -2.089423662057541,
+           -2.158687268514769,
+           -2.2158634604848833,
+           -2.259596908900167,
+           -2.2888293942804165,
+           -2.3028186853211583,
+           -2.3011497712853206,
+           -2.2837382539136875,
+           -2.2508258962987897,
+           -2.2029685170538467,
+           -2.1410166034556792,
+           -2.066089192498038,
+           -1.9795417296690605,
+           -1.882928757838182,
+           -1.777962409440609,
+           -1.6664677712654241,
+           -1.5503362602891626,
+           -1.4314781895275255,
+           -1.3117757138953932,
+           -1.1930373273960313,
+           -1.0769550351698602,
+           -0.9650652483104033,
+           -0.8587143478794003,
+           -0.7590297398435619,
+           -0.6668970779060667,
+           -0.5829441701026984,
+           -0.507531911664333,
+           -0.4407524053999862,
+           -0.38243424630349815,
+           -0.33215476388160897,
+           -0.2892588384489671,
+           -0.25288374078765724,
+           -0.22198929230736542,
+           -0.19539250897802876,
+           -0.17180578018269774,
+           -0.14987754604721423,
+           -0.12823437591788256,
+           -0.10552331797769951,
+           -0.08045338630390665,
+           -0.05183507703264481,
+           -0.018616859036866013,
+           0.020082334745990017,
+           0.0649454835461951,
+           0.11643546287965115,
+           0.17477923001646356,
+           0.23995864215778037,
+           0.31170816543966134,
+           0.3895195529081782,
+           0.4726533874664863,
+           0.5601572061053925,
+           0.6508897490574657,
+           0.7435507162507261,
+           0.8367152676869138,
+           0.9288723778496428,
+           1.0184660501973202,
+           1.1039383188901553,
+           1.1837729131865162,
+           1.2565384367860364,
+           1.3209299204444376,
+           1.3758076413540834,
+           1.4202321662589992,
+           1.4534946655260892,
+           1.4751416602232938,
+           1.4849935008377169,
+           1.48315603122935,
+           1.4700250609185128,
+           1.4462834486357574,
+           1.4128907857421509,
+           1.3710658550212191,
+           1.3222622237755794,
+           1.2681375055321888,
+           1.2105169875616877,
+           1.151352467741754,
+           1.0926772703372538,
+           1.0365585128233017,
+           0.9850477723098496,
+           0.940131348450053,
+           0.9036813386340539,
+           0.8774087302175317,
+           0.86281967368316,
+           0.8611760308959805,
+           0.8734611956191289,
+           0.9003520615121463,
+           0.9421978688683134,
+           0.9990064988390721,
+           1.0704386067856893,
+           1.1558097990021725,
+           1.2541008639416278,
+           1.3639758749724344,
+           1.4838077913457892,
+           1.6117110021410206,
+           1.7455800889400486,
+           1.883133931026201,
+           2.021964145751067,
+           2.159586749605849,
+           2.2934958451239638,
+           2.4212180870315057,
+           2.540366659349463,
+           2.6486935040028317,
+           2.744138580722655,
+           2.8248750067096293,
+           2.8893490210123276,
+           2.9363138405277462,
+           2.964856619001207,
+           2.974417883878096,
+           2.9648030043691525,
+           2.936185433292269,
+           2.8891016605449464,
+           2.824438012692515,
+           2.743409626347044,
+           2.6475321080654366,
+           2.5385865659206694,
+           2.418578853516837,
+           2.2896940022615966,
+           2.1542469289217796,
+           2.0146305901982178,
+           1.873262812247488,
+           1.7325330494351843,
+           1.5947503225444555,
+           1.4620935523515703,
+           1.336565440822327,
+           1.2199509608079948,
+           1.1137813983302869,
+           1.019304752268841,
+           0.9374631379745859,
+           0.8688776679630377,
+           0.8138410986924769,
+           0.7723183420576937,
+           0.743954748330756,
+           0.7280918785832403,
+           0.723790303767549,
+           0.7298587990523162,
+           0.7448891498192495,
+           0.7672956536416708,
+           0.7953582937779325,
+           0.8272684768405514,
+           0.8611761723102849,
+           0.89523726572291,
+           0.9276599412075066,
+           0.9567489424021499,
+           0.9809466226851314,
+           0.9988697844984522,
+           1.0093414209983602,
+           1.011416608429752,
+           1.004401951036149,
+           0.9878681480852232,
+           0.9616554304609768,
+           0.9258717977525269,
+           0.880884171229382,
+           0.8273027588910136,
+           0.7659591013710959,
+           0.6978784275336709,
+           0.6242470921108233,
+           0.5463759911112877,
+           0.4656609508989805,
+           0.38354116130950033,
+           0.301456770099537,
+           0.22080677426153597,
+           0.14290833285985133,
+           0.06895858636370435,
+           6.163919815048678e-16
+          ],
+          [
+           0,
+           -0.060924654739736295,
+           -0.11515556877943013,
+           -0.16239644308670356,
+           -0.20259639441442528,
+           -0.2359519095298216,
+           -0.26290182872162354,
+           -0.28411547563860645,
+           -0.30047422994831907,
+           -0.31304701136541807,
+           -0.3230603039103866,
+           -0.33186349374018503,
+           -0.34089041885662735,
+           -0.3516181312481182,
+           -0.3655239489264851,
+           -0.38404192488842526,
+           -0.40851988095126085,
+           -0.4401781460945868,
+           -0.4800711015264433,
+           -0.5290525690594717,
+           -0.587745987113897,
+           -0.656520202016125,
+           -0.7354715641058774,
+           -0.8244128619173656,
+           -0.9228694572371795,
+           -1.0300828034032021,
+           -1.1450213432933116,
+           -1.2663985967044882,
+           -1.3926980639179234,
+           -1.52220439777366,
+           -1.6530401349288848,
+           -1.7832071322272407,
+           -1.9106317299302682,
+           -2.033212563121096,
+           -2.1488698684651673,
+           -2.2555950876368693,
+           -2.3514995523292224,
+           -2.4348610493633553,
+           -2.5041671077690912,
+           -2.558153921843497,
+           -2.5958399234218117,
+           -2.616553140551725,
+           -2.6199516254679014,
+           -2.606036398695838,
+           -2.575156534292053,
+           -2.5280061993116214,
+           -2.4656136539918068,
+           -2.389322413120325,
+           -2.300764958864298,
+           -2.201829576311545,
+           -2.0946210506697556,
+           -1.9814161153510776,
+           -1.864614669331969,
+           -1.7466878870263007,
+           -1.6301244218425217,
+           -1.5173759536694063,
+           -1.4108033495116334,
+           -1.3126246948751819,
+           -1.2248664115318177,
+           -1.1493186059643665,
+           -1.0874956938219584,
+           -1.0406032214877392,
+           -1.0095116593893472,
+           -0.994737776520483,
+           -0.9964340258024894,
+           -1.0143861797707296,
+           -1.0480192602457512,
+           -1.096411608906183,
+           -1.158316752802177,
+           -1.2321925345218743,
+           -1.3162368054231501,
+           -1.408428826222099,
+           -1.5065753860168472,
+           -1.6083605417342035,
+           -1.7113977976366277,
+           -1.813283490879169,
+           -1.9116501254160112,
+           -2.0042184033421853,
+           -2.0888467397896893,
+           -2.163577113805646,
+           -2.226676201535917,
+           -2.2766708571558123,
+           -2.312377148351117,
+           -2.332922313236352,
+           -2.3377591804268976,
+           -2.326672779227512,
+           -2.2997790579819792,
+           -2.257515820834804,
+           -2.200626181754164,
+           -2.1301350150242238,
+           -2.0473190491159126,
+           -1.9536714017928458,
+           -1.850861484831066,
+           -1.7406913136699103,
+           -1.6250493380995528,
+           -1.5058629628167686,
+           -1.3850509501317774,
+           -1.2644768908043185,
+           -1.145904893184102,
+           -1.0309585765212825,
+           -0.9210843631953665,
+           -0.8175199490479367,
+           -0.7212686939634492,
+           -0.6330805198182651,
+           -0.5534397338497221,
+           -0.48256001666418663,
+           -0.4203866300226415,
+           -0.3666057148525903,
+           -0.32066036928225833,
+           -0.2817730244129122,
+           -0.2489734763519392,
+           -0.22113179070672084,
+           -0.19699517384178866,
+           -0.17522780676615132,
+           -0.1544525649872915,
+           -0.13329350283269012,
+           -0.11041796469006598,
+           -0.0845771987198305,
+           -0.054644390479855004,
+           -0.019649103481492004,
+           0.0211927908217059,
+           0.06845449216494155,
+           0.12247961889558985,
+           0.18337002659296775,
+           0.25098043159954003,
+           0.3249199953648554,
+           0.40456084357741556,
+           0.48905331263897095,
+           0.5773475397269687,
+           0.6682208459739604,
+           0.760310209409181,
+           0.8521489891528792,
+           0.9422069483811814,
+           1.0289325337112163,
+           1.1107963052119778,
+           1.1863343758834566,
+           1.2541907131176608,
+           1.3131571775849276,
+           1.362210226666779,
+           1.4005432887489435,
+           1.4275939194688736,
+           1.4430649788093102,
+           1.4469392155893464,
+           1.4394868097697162,
+           1.4212655989887555,
+           1.3931138994970422,
+           1.3561360185763227,
+           1.3116807409372988,
+           1.2613132508437768,
+           1.206781120303791,
+           1.149975147353582,
+           1.092885963351433,
+           1.037557440868397,
+           0.986038021330197,
+           0.9403311417648399,
+           0.9023459712545365,
+           0.8738496691039963,
+           0.8564223481850937,
+           0.8514158690062522,
+           0.8599175041196577,
+           0.8827194005526776,
+           0.9202946327110877,
+           0.9727804829122445,
+           1.0399694151296959,
+           1.1213080238396835,
+           1.2159040485344248,
+           1.3225413501836285,
+           1.439702553441542,
+           1.5655988724343597,
+           1.6982064630899727,
+           1.8353084854929043,
+           1.9745419195926264,
+           2.113448060224958,
+           2.2495255257316003,
+           2.380284550760284,
+           2.503301299694898,
+           2.616270933471892,
+           2.717058189414296,
+           2.80374429053452,
+           2.87466908616554,
+           2.928467437719687,
+           2.9640989991368123,
+           2.9808706978767403,
+           2.9784513953389955,
+           2.956878391150453,
+           2.9165556293362394,
+           2.8582436612734416,
+           2.7830416157332754,
+           2.692361615495769,
+           2.5878962583768312,
+           2.4715799437139965,
+           2.345544969460683,
+           2.212073446557901,
+           2.073546173261432,
+           1.9323896803042968,
+           1.7910226965553049,
+           1.651803293305842,
+           1.5169779433323964,
+           1.3886336790452876,
+           1.2686544536781152,
+           1.1586827026309408,
+           1.0600869714327998,
+           0.9739363255964852,
+           0.9009820896612556,
+           0.8416472821224746,
+           0.7960239242004707,
+           0.7638782081645119,
+           0.7446633199382625,
+           0.7375395256670274,
+           0.7414009573632226,
+           0.7549083729351967,
+           0.7765270247415501,
+           0.8045686517240451,
+           0.8372365160281143,
+           0.8726723380674214,
+           0.9090039457944762,
+           0.9443924453525948,
+           0.9770777414174763,
+           1.0054212857623754,
+           1.0279450105497852,
+           1.0433655065279022,
+           1.050622633018537,
+           1.0489018930830694,
+           1.0376500698157471,
+           1.0165837942171059,
+           0.9856908971322659,
+           0.9452245827072309,
+           0.8956906440646527,
+           0.8378281188230376,
+           0.7725839482414318,
+           0.7010823550031641,
+           0.6245897871764579,
+           0.5444763864007192,
+           0.4621750240962784,
+           0.3791390083594688,
+           0.29679959473933637,
+           0.21652443556593923,
+           0.13957807491420265,
+           0.06708554037388882,
+           5.973166896093752e-16
+          ],
+          [
+           0,
+           -0.058653377259265164,
+           -0.11047295370249664,
+           -0.1552874740405732,
+           -0.19317294244805988,
+           -0.2244507001818273,
+           -0.24967857470491753,
+           -0.26963532068013796,
+           -0.2852987490212842,
+           -0.2978181060734589,
+           -0.30848141671757007,
+           -0.3186786388916211,
+           -0.3298615892775268,
+           -0.3435016878384405,
+           -0.3610466302386849,
+           -0.38387713033368004,
+           -0.4132648789852393,
+           -0.4503328402730957,
+           -0.4960189523063078,
+           -0.5510442185796903,
+           -0.6158860691519561,
+           -0.6907577414663548,
+           -0.7755942815901371,
+           -0.8700456017121511,
+           -0.9734768530095579,
+           -1.0849761888800287,
+           -1.2033698066333736,
+           -1.327243970724777,
+           -1.4549735421315564,
+           -1.5847563710148713,
+           -1.7146527575902817,
+           -1.8426290530091458,
+           -1.9666043614122475,
+           -2.0844992189914398,
+           -2.194285068095034,
+           -2.2940333156692074,
+           -2.381962766454177,
+           -2.456484252423453,
+           -2.5162413402984773,
+           -2.5601460871930573,
+           -2.587408928453008,
+           -2.5975619188239905,
+           -2.590474704896607,
+           -2.566362779539362,
+           -2.5257877535326814,
+           -2.469649571358309,
+           -2.3991707923886616,
+           -2.315873250799056,
+           -2.2215475926773562,
+           -2.118216362478369,
+           -2.0080914688866205,
+           -1.8935269984155543,
+           -1.7769684602635678,
+           -1.660899635212336,
+           -1.5477882624652892,
+           -1.4400318297497248,
+           -1.3399047329350726,
+           -1.2495080417909805,
+           -1.1707230490091738,
+           -1.1051696916618774,
+           -1.0541708199850341,
+           -1.0187231505192673,
+           -0.9994755825580619,
+           -0.9967153823782033,
+           -1.0103625531021097,
+           -1.0399725138023717,
+           -1.0847470143288709,
+           -1.1435530171111545,
+           -1.2149490886084022,
+           -1.2972186657261686,
+           -1.3884094006963241,
+           -1.486377645543533,
+           -1.5888370177789206,
+           -1.6934098952458196,
+           -1.7976806223362696,
+           -1.8992491736540094,
+           -1.9957840154469881,
+           -2.0850729298510924,
+           -2.165070621509135,
+           -2.2339420090588487,
+           -2.290100213226607,
+           -2.3322383860851725,
+           -2.3593546791226236,
+           -2.3707698173227936,
+           -2.36613692827405,
+           -2.3454434649080533,
+           -2.3090052531456737,
+           -2.2574528867498094,
+           -2.1917108763609785,
+           -2.1129701334947963,
+           -2.0226545289625903,
+           -1.9223824048727214,
+           -1.8139240366938645,
+           -1.6991561339876655,
+           -1.580014533152336,
+           -1.4584462713506001,
+           -1.3363622369352657,
+           -1.2155915680829863,
+           -1.0978389186900126,
+           -0.9846456302823102,
+           -0.8773557428409413,
+           -0.77708764876812,
+           -0.6847120460085874,
+           -0.6008366823649113,
+           -0.5257982074581338,
+           -0.45966126602434915,
+           -0.40222478090971986,
+           -0.3530351908941729,
+           -0.31140623193910094,
+           -0.276444685042269,
+           -0.24708136373375816,
+           -0.22210648310995015,
+           -0.20020844344601252,
+           -0.1800149775544679,
+           -0.16013555424070336,
+           -0.1392039018356396,
+           -0.11591951653455196,
+           -0.08908705007930508,
+           -0.05765252939813195,
+           -0.020735445660527634,
+           0.02234414036004266,
+           0.07204419848928519,
+           0.1285856071038668,
+           0.19194371667188245,
+           0.2618468319015126,
+           0.3377816646572881,
+           0.41900562749451886,
+           0.5045656585334473,
+           0.5933230969957783,
+           0.6839839694149575,
+           0.7751339033639253,
+           0.8652767621721955,
+           0.9528759936848546,
+           1.0363976112314996,
+           1.1143536775652385,
+           1.1853451438539502,
+           1.2481029063899116,
+           1.3015259833269337,
+           1.3447157815228679,
+           1.3770055178182385,
+           1.3979839775098473,
+           1.4075129324617712,
+           1.4057376987768955,
+           1.3930904853194002,
+           1.370286365365882,
+           1.3383118897544557,
+           1.2984065464437586,
+           1.2520374537137602,
+           1.2008678477581913,
+           1.146720085765056,
+           1.091534028706529,
+           1.0373217903320113,
+           0.9861199371585587,
+           0.9399402960513386,
+           0.9007205694063861,
+           0.8702759718129001,
+           0.8502530859374363,
+           0.8420870895368334,
+           0.846963431005374,
+           0.8657849294432682,
+           0.8991451493156174,
+           0.9473087523835502,
+           1.0101993642983242,
+           1.0873953140712824,
+           1.1781334159342094,
+           1.2813207694964721,
+           1.3955543603268388,
+           1.5191480538916262,
+           1.6501663958154342,
+           1.7864644651234323,
+           1.9257328785755048,
+           2.065546917080955,
+           2.203418642635626,
+           2.3368507987994134,
+           2.4633912413165517,
+           2.580686629250447,
+           2.6865341213943768,
+           2.7789298674171095,
+           2.8561131571508422,
+           2.91660519285416,
+           2.9592415757368133,
+           2.983197746454156,
+           2.9880067860663346,
+           2.9735691650590135,
+           2.9401542190372774,
+           2.888393325987422,
+           2.8192649567798815,
+           2.734071963077013,
+           2.634411650334962,
+           2.5221393536937597,
+           2.399326387110949,
+           2.268213367419446,
+           2.131160021911673,
+           1.9905926680025758,
+           1.8489506045987183,
+           1.7086326758064851,
+           1.571945258093676,
+           1.441052882268959,
+           1.3179326326999306,
+           1.204333369801268,
+           1.1017407004137467,
+           1.0113484772935049,
+           0.9340374471082848,
+           0.8703614901073004,
+           0.8205417083553616,
+           0.7844684277011534,
+           0.7617109862085298,
+           0.7515349933521847,
+           0.7529265644891465,
+           0.7646228683661803,
+           0.7851481757792378,
+           0.8128544686018709,
+           0.8459655633599926,
+           0.8826236248683247,
+           0.9209368950170872,
+           0.9590274407595015,
+           0.9950777341227973,
+           1.0273749153273999,
+           1.054351656798878,
+           1.0746226392367038,
+           1.0870157685457509,
+           1.0905974013232538,
+           1.0846910031855217,
+           1.0688888345401923,
+           1.0430564381521497,
+           1.0073298874783072,
+           0.9621059396086449,
+           0.9080254171017449,
+           0.8459503145147917,
+           0.7769352837045195,
+           0.7021942930596209,
+           0.6230633761970152,
+           0.5409604823193213,
+           0.45734351099324444,
+           0.373667656832039,
+           0.291343203414916,
+           0.21169489044438075,
+           0.13592393405609351,
+           0.06507370850497284,
+           5.771853649180891e-16
+          ],
+          [
+           0,
+           -0.056316667795001794,
+           -0.10571801374427091,
+           -0.14815917204232226,
+           -0.18384224682129818,
+           -0.21321052461171397,
+           -0.23693586045195641,
+           -0.25589955956121313,
+           -0.27116724717789714,
+           -0.2839583774304465,
+           -0.2956111739205633,
+           -0.30754391644322765,
+           -0.32121358682841594,
+           -0.3380729597325601,
+           -0.35952726944436525,
+           -0.38689160020324165,
+           -0.4213501346859289,
+           -0.46391835346018767,
+           -0.5154092083255783,
+           -0.5764041962579044,
+           -0.6472301405072027,
+           -0.7279423442361241,
+           -0.8183146234250811,
+           -0.9178365535568311,
+           -1.0257180831175619,
+           -1.140901480746128,
+           -1.2620803965872873,
+           -1.3877256367300992,
+           -1.516117077105278,
+           -1.645380984222879,
+           -1.773531868674125,
+           -1.8985178769903979,
+           -2.0182686313219578,
+           -2.130744356947057,
+           -2.2339850966689943,
+           -2.3261587998200133,
+           -2.4056070922499213,
+           -2.4708875819727694,
+           -2.5208116319804046,
+           -2.5544766353005586,
+           -2.571291955207013,
+           -2.570997842501962,
+           -2.553676808377493,
+           -2.5197571114736848,
+           -2.470008206992829,
+           -2.4055281994760676,
+           -2.3277235343541895,
+           -2.2382813518991416,
+           -2.1391351060925414,
+           -2.032424215786766,
+           -1.920448662295366,
+           -1.8056195725847766,
+           -1.6904069274476818,
+           -1.5772856069271053,
+           -1.468681029001395,
+           -1.3669156510216267,
+           -1.2741575862414118,
+           -1.1923725403736583,
+           -1.1232801965698447,
+           -1.0683160733796568,
+           -1.028599751618014,
+           -1.004910215755217,
+           -0.9976688871004821,
+           -1.006930743756949,
+           -1.0323837305176626,
+           -1.0733564652100491,
+           -1.12883405126254,
+           -1.1974816142434934,
+           -1.2776749974750672,
+           -1.3675378829868026,
+           -1.4649844531393417,
+           -1.5677665788698187,
+           -1.6735244158091156,
+           -1.7798392120117206,
+           -1.8842870825672493,
+           -1.9844924880610344,
+           -2.0781801661106103,
+           -2.1632243076670905,
+           -2.237693841335327,
+           -2.2998927878235658,
+           -2.3483947703015384,
+           -2.3820709118420207,
+           -2.400110514630624,
+           -2.402034093199784,
+           -2.3876985211847868,
+           -2.357294243391704,
+           -2.311334697573428,
+           -2.2506382784971275,
+           -2.176303356039393,
+           -2.089677024782295,
+           -1.992318410863497,
+           -1.8859574890561195,
+           -1.772450466147526,
+           -1.6537328631835457,
+           -1.5317714772430686,
+           -1.4085164220128863,
+           -1.285854435183836,
+           -1.1655645999687878,
+           -1.049277558963865,
+           -0.9384392029526705,
+           -0.8342796975617737,
+           -0.7377885699809626,
+           -0.6496964198468194,
+           -0.5704636468639743,
+           -0.5002764071407885,
+           -0.439049825100511,
+           -0.3864383028529151,
+           -0.3418525887215004,
+           -0.3044830957352634,
+           -0.2733288035882532,
+           -0.2472309377742424,
+           -0.22491050080131592,
+           -0.20500863553407087,
+           -0.1861287321458107,
+           -0.1668791495726342,
+           -0.14591541072361278,
+           -0.12198074826524263,
+           -0.0939439240782072,
+           -0.060833319272267976,
+           -0.021866391041297128,
+           0.023526284897935238,
+           0.07568302513527353,
+           0.1346995827938769,
+           0.20042453427499726,
+           0.2724616386920489,
+           0.350179117817103,
+           0.432725623245806,
+           0.5190524822002087,
+           0.6079416483875286,
+           0.6980386338138005,
+           0.7878895652500784,
+           0.8759813985418705,
+           0.9607842379731002,
+           1.0407946486625266,
+           1.1145788190307726,
+           1.1808144285677034,
+           1.2383301035585614,
+           1.2861413994642472,
+           1.3234823319474998,
+           1.3498315870567001,
+           1.3649326721502686,
+           1.3688074195242186,
+           1.3617624206599876,
+           1.344388146408878,
+           1.3175506928475291,
+           1.2823762793660012,
+           1.240228810105645,
+           1.192680987515413,
+           1.1414796330711103,
+           1.0885060209055633,
+           1.0357321614110349,
+           0.9851740804551167,
+           0.9388432229130271,
+           0.8986971646067705,
+           0.866590842982271,
+           0.8442295131975939,
+           0.8331246027272061,
+           0.83455357484033,
+           0.8495248208412298,
+           0.8787484849122028,
+           0.9226139865596503,
+           0.9811748473838248,
+           1.054141255014746,
+           1.1408806118150712,
+           1.2404261238684349,
+           1.3514932915503803,
+           1.4725039713804606,
+           1.6016174945848025,
+           1.7367681553931504,
+           1.8757082258013924,
+           2.016055517210924,
+           2.1553443963839953,
+           2.2910790763351976,
+           2.4207879442806375,
+           2.542077660062469,
+           2.6526857603032954,
+           2.7505305359179806,
+           2.833757012769324,
+           2.900777955715761,
+           2.9503089328872427,
+           2.981396616921747,
+           2.993439659709726,
+           2.9862016530485107,
+           2.959815875230779,
+           2.9147817184204996,
+           2.8519528889691195,
+           2.772517667797504,
+           2.6779717058769417,
+           2.570084006121641,
+           2.4508569033782974,
+           2.3224809947813667,
+           2.18728609013756,
+           2.047689343382925,
+           1.9061417893346693,
+           1.7650745434427082,
+           1.6268459252700849,
+           1.4936907389801126,
+           1.36767288691208,
+           1.250642406848502,
+           1.1441979119653163,
+           1.04965527750486,
+           0.9680232632777563,
+           0.8999865900301379,
+           0.8458968047410679,
+           0.8057710795611863,
+           0.7792988960608201,
+           0.7658563754726935,
+           0.7645278313801696,
+           0.7741339483288964,
+           0.7932658323521926,
+           0.8203240412309816,
+           0.8535615868040918,
+           0.891129811581779,
+           0.9311259794362589,
+           0.9716413867006626,
+           1.0108087963317403,
+           1.0468480238708475,
+           1.0781085590220179,
+           1.1031081892864052,
+           1.120566700097086,
+           1.1294338565095914,
+           1.1289110213856903,
+           1.1184659303522042,
+           1.0978403204362415,
+           1.0670502927138328,
+           1.0263794749396287,
+           0.976365233283999,
+           0.9177783583945361,
+           0.8515968156105148,
+           0.7789742981755483,
+           0.7012044519972608,
+           0.6196817476655829,
+           0.5358600574058344,
+           0.4512100493879066,
+           0.36717653800418387,
+           0.28513692575109917,
+           0.2063618403209809,
+           0.13197901028207834,
+           0.06294133585386008,
+           5.561808166845126e-16
+          ],
+          [
+           0,
+           -0.053935733749469354,
+           -0.10093396395309494,
+           -0.14107642591566924,
+           -0.17468940227017207,
+           -0.20233411647112845,
+           -0.22479046114853116,
+           -0.243034482111907,
+           -0.2582102028658097,
+           -0.2715965237691688,
+           -0.28457006063847445,
+           -0.2985648963218231,
+           -0.31503030277037686,
+           -0.33538754823890987,
+           -0.36098693296571727,
+           -0.3930661962348385,
+           -0.43271140806359526,
+           -0.4808214005737776,
+           -0.5380767088012883,
+           -0.6049138803661109,
+           -0.6815058807834844,
+           -0.7677491695341333,
+           -0.8632578550953726,
+           -0.9673651591244836,
+           -1.0791322353254191,
+           -1.1973642018398938,
+           -1.3206330619643218,
+           -1.4473070112291677,
+           -1.5755854638390203,
+           -1.70353898232945,
+           -1.8291531648321244,
+           -1.9503754378526097,
+           -2.065163621690384,
+           -2.171535082668746,
+           -2.2676152626073396,
+           -2.3516843821522144,
+           -2.4222211506268145,
+           -2.477942380189391,
+           -2.517837494762738,
+           -2.5411970422391064,
+           -2.5476344590220927,
+           -2.5371004956502112,
+           -2.5098898871756234,
+           -2.4666400378830144,
+           -2.408321682285407,
+           -2.3362216784147156,
+           -2.2519182804732774,
+           -2.1572494212319033,
+           -2.0542747056361135,
+           -1.945231971695004,
+           -1.8324894090538593,
+           -1.7184943363640912,
+           -1.6057198229072713,
+           -1.4966103957959145,
+           -1.3935281000475828,
+           -1.298700174230907,
+           -1.2141695692794088,
+           -1.1417494732779994,
+           -1.0829829120921781,
+           -1.0391083768661424,
+           -1.0110322875350717,
+           -0.999308940014949,
+           -1.0041284075692625,
+           -1.0253126783084403,
+           -1.0623201154375086,
+           -1.1142581294789378,
+           -1.1799037570596005,
+           -1.2577316536933651,
+           -1.3459488328599873,
+           -1.4425353248255008,
+           -1.5452897899184168,
+           -1.6518790057223376,
+           -1.759890058645294,
+           -1.8668840097092971,
+           -1.970449773602998,
+           -2.068256949756592,
+           -2.1581063743824545,
+           -2.2379772222823355,
+           -2.306069575228897,
+           -2.360841487676001,
+           -2.401039717592427,
+           -2.4257234469414564,
+           -2.4342804888579326,
+           -2.4264356626381236,
+           -2.4022512087133245,
+           -2.3621193091192785,
+           -2.3067469698468592,
+           -2.237133705182781,
+           -2.1545426362256728,
+           -2.060465771993599,
+           -1.9565843781252845,
+           -1.8447254518141898,
+           -1.7268154095726858,
+           -1.6048321546150772,
+           -1.4807567216782587,
+           -1.3565256982981704,
+           -1.2339855930019301,
+           -1.1148502633710595,
+           -1.0006624320094082,
+           -0.8927602083175286,
+           -0.7922494014632236,
+           -0.6999822584267438,
+           -0.6165430943354089,
+           -0.5422411047038045,
+           -0.47711046514236743,
+           -0.4209176382231229,
+           -0.37317562416541566,
+           -0.3331647164164716,
+           -0.29995915944626067,
+           -0.2724589582438419,
+           -0.24942596077819051,
+           -0.22952322925725394,
+           -0.21135663599516072,
+           -0.19351756704788553,
+           -0.1746255927808838,
+           -0.15336996974531053,
+           -0.12854887248440322,
+           -0.09910531626038284,
+           -0.06415882056988965,
+           -0.02303197642148777,
+           0.024728785207403105,
+           0.0793387739601866,
+           0.14076735356955133,
+           0.2087371958338257,
+           0.28273050119289805,
+           0.36200202973279916,
+           0.4455986080882782,
+           0.5323846077866957,
+           0.6210727334043914,
+           0.7102593184890614,
+           0.7984632071200061,
+           0.8841672023039019,
+           0.9658609916218384,
+           1.0420844174891175,
+           1.1114699452019547,
+           1.172783197039469,
+           1.2249604647433485,
+           1.2671421846614743,
+           1.2987014579624736,
+           1.3192668201926563,
+           1.3287386070422047,
+           1.3272984229752613,
+           1.315411392382369,
+           1.2938210548187747,
+           1.2635369521517184,
+           1.2258151413895073,
+           1.1821320479376127,
+           1.1341522454707287,
+           1.0836909061997404,
+           1.0326718050611958,
+           0.9830818797122141,
+           0.936923442149065,
+           0.896165204857328,
+           0.8626933228827183,
+           0.8382636620288821,
+           0.8244564822209222,
+           0.8226346743438017,
+           0.8339066097309683,
+           0.859094555804267,
+           0.8987094816777176,
+           0.9529329269606605,
+           1.0216064391795403,
+           1.1042289042652593,
+           1.1999619048412482,
+           1.3076430472368206,
+           1.4258070049927158,
+           1.5527138388643125,
+           1.6863839755824543,
+           1.824639064283635,
+           1.965147784602963,
+           2.105475557522831,
+           2.2431370122379004,
+           2.375649991972098,
+           2.500589840632843,
+           2.615642701461868,
+           2.718656578749197,
+           2.8076889637723808,
+           2.8810499052244043,
+           2.9373395106045703,
+           2.9754789958059904,
+           2.9947345522774826,
+           2.9947334709776805,
+           2.9754721457519087,
+           2.937315771290936,
+           2.8809897477956645,
+           2.807563001084301,
+           2.7184236183595716,
+           2.615247381550841,
+           2.4999599476486387,
+           2.3746935746950677,
+           2.2417394194719216,
+           2.1034965353641515,
+           1.9624187739093248,
+           1.8209608393875658,
+           1.6815247613901279,
+           1.5464080353024245,
+           1.4177546354720185,
+           1.297510031665778,
+           1.1873812381276183,
+           1.0888027986625384,
+           1.0029094638319016,
+           0.9305161512051173,
+           0.8721056007641873,
+           0.8278239494179409,
+           0.7974842557910841,
+           0.780577813754404,
+           0.7762929052884149,
+           0.7835404648275331,
+           0.8009859625767652,
+           0.827086667439137,
+           0.8601333247023033,
+           0.8982951825336283,
+           0.9396672270400804,
+           0.9823184399096677,
+           1.0243398764996605,
+           1.063891375972429,
+           1.0992457582587263,
+           1.128829434076474,
+           1.1512584520770521,
+           1.1653691289033143,
+           1.1702425504097644,
+           1.1652223918896039,
+           1.1499256778312665,
+           1.1242462831257356,
+           1.0883511631942029,
+           1.0426694855375698,
+           0.9878750150806562,
+           0.9248622758889322,
+           0.8547171681179867,
+           0.7786828575160488,
+           0.6981218719908922,
+           0.614475432766796,
+           0.5292211141982031,
+           0.4438299647453433,
+           0.3597242310329319,
+           0.2782368071160925,
+           0.20057348261239566,
+           0.1277789874912232,
+           0.06070772999554869,
+           5.344934411386254e-16
+          ],
+          [
+           0,
+           -0.05153213097427422,
+           -0.09616416437742488,
+           -0.13410351118057776,
+           -0.16579759397908703,
+           -0.19192050204854597,
+           -0.213353200142544,
+           -0.23115780713106027,
+           -0.24654661661294994,
+           -0.26084667061817773,
+           -0.2754608159012466,
+           -0.2918262670891542,
+           -0.311371769650205,
+           -0.33547449651310957,
+           -0.3654178241070028,
+           -0.4023511162569112,
+           -0.44725259813648166,
+           -0.5008963284583344,
+           -0.5638241780801962,
+           -0.636323599685561,
+           -0.7184118292191853,
+           -0.8098269988971448,
+           -0.9100264678753422,
+           -1.0181924943864182,
+           -1.1332451869025015,
+           -1.2538624863183843,
+           -1.3785067509373459,
+           -1.5054573457164935,
+           -1.632848481089832,
+           -1.7587114086898967,
+           -1.8810199649435488,
+           -1.9977383618033606,
+           -2.106870059164813,
+           -2.206506517516654,
+           -2.2948746230716197,
+           -2.3703816012866827,
+           -2.4316562878206134,
+           -2.477585707374613,
+           -2.507346018597796,
+           -2.5204270147349432,
+           -2.5166495217769977,
+           -2.4961752048564043,
+           -2.459508475395205,
+           -2.4074903816249384,
+           -2.3412845588998197,
+           -2.262355508964346,
+           -2.1724396642761925,
+           -2.0735098700224444,
+           -1.9677340782470059,
+           -1.8574291915308057,
+           -1.7450111143904061,
+           -1.632942165983771,
+           -1.5236770754511897,
+           -1.4196088195677197,
+           -1.3230155703539965,
+           -1.2360099976419756,
+           -1.1604921188290622,
+           -1.0981068064250437,
+           -1.050206955456641,
+           -1.0178231799606987,
+           -1.0016407538817773,
+           -1.0019843404244846,
+           -1.0188108694519313,
+           -1.0517107293509147,
+           -1.0999172425966948,
+           -1.1623241978393049,
+           -1.2375110204733326,
+           -1.3237749829815932,
+           -1.4191696902461628,
+           -1.5215489275263947,
+           -1.628614833482094,
+           -1.7379692604969708,
+           -1.8471671120374702,
+           -1.9537704035931085,
+           -2.055401780893187,
+           -2.1497962468436533,
+           -2.2348498964892363,
+           -2.308664536053041,
+           -2.3695871658069216,
+           -2.4162434345880506,
+           -2.4475643230157953,
+           -2.462805479176599,
+           -2.4615588106093567,
+           -2.443756125395302,
+           -2.4096648083782477,
+           -2.3598757112624584,
+           -2.2952836228263283,
+           -2.217060863159839,
+           -2.126624709343106,
+           -2.0255995053521176,
+           -1.91577443268257,
+           -1.7990580172432582,
+           -1.6774305201230142,
+           -1.5528954031900724,
+           -1.4274310741641967,
+           -1.3029440995737689,
+           -1.1812250283765937,
+           -1.0639078952200003,
+           -0.9524343722735834,
+           -0.8480234148669201,
+           -0.7516471019676902,
+           -0.6640132115084689,
+           -0.5855548967917958,
+           -0.5164276480591286,
+           -0.45651353738767286,
+           -0.40543256005097544,
+           -0.36256070598553275,
+           -0.327054225538935,
+           -0.2978793984695677,
+           -0.27384697809226993,
+           -0.25365036692718435,
+           -0.23590648907277334,
+           -0.21919826003475978,
+           -0.2021175184744766,
+           -0.183307277155763,
+           -0.16150217240002968,
+           -0.1355660420009158,
+           -0.10452563948015701,
+           -0.06759959577673888,
+           -0.02422186530900099,
+           0.025940961377348,
+           0.08297893516227585,
+           0.14673490025958424,
+           0.216807624754142,
+           0.292561831482877,
+           0.3731448703711763,
+           0.4575095992761015,
+           0.5444428772934908,
+           0.6325989265058529,
+           0.720536689051345,
+           0.8067601994775038,
+           0.8897609103463362,
+           0.9680608540947239,
+           1.040255497661952,
+           1.10505514909537,
+           1.1613238072234058,
+           1.2081144057955555,
+           1.244699490769383,
+           1.2705964815323814,
+           1.2855868010125038,
+           1.2897283125272467,
+           1.2833606690437633,
+           1.2671033590863794,
+           1.2418464183710929,
+           1.2087339627405431,
+           1.1691408814385784,
+           1.1246432055877669,
+           1.076982830484111,
+           1.0280274178605393,
+           0.9797264318501331,
+           0.9340643667464115,
+           0.8930123031273085,
+           0.8584789794366829,
+           0.8322625873480983,
+           0.8160044905411812,
+           0.8111460280144529,
+           0.8188894955936769,
+           0.8401643044461204,
+           0.8755991954348732,
+           0.9255012459279333,
+           0.9898422446552639,
+           1.0682528342969992,
+           1.1600246349772414,
+           1.2641203692913219,
+           1.3791918156280543,
+           1.5036052261231316,
+           1.6354736632799651,
+           1.7726955396117263,
+           1.9129984917841798,
+           2.0539875884545804,
+           2.193196762591284,
+           2.3281422772215925,
+           2.4563769803430318,
+           2.5755440814978328,
+           2.6834291898673786,
+           2.778009391561567,
+           2.857498211175718,
+           2.9203853980601253,
+           2.965470598800938,
+           2.9918901212224167,
+           2.9991361583071887,
+           2.9870680188366574,
+           2.9559151009456324,
+           2.9062715405612307,
+           2.839082664097145,
+           2.755623569001621,
+           2.657470342090824,
+           2.5464645995127517,
+           2.4246721894602072,
+           2.2943370355739345,
+           2.1578312120413146,
+           2.0176024279778013,
+           1.8761201567053454,
+           1.7358216736428298,
+           1.5990592640613979,
+           1.4680498290455135,
+           1.344828055499156,
+           1.2312042255289217,
+           1.128727624292484,
+           1.0386563663186539,
+           0.961934301838873,
+           0.8991754907434125,
+           0.8506565466867003,
+           0.8163169621798089,
+           0.7957673319417968,
+           0.7883052010910294,
+           0.7929380816172898,
+           0.8084130094642691,
+           0.8332518596425406,
+           0.8657915018486889,
+           0.9042277673487588,
+           0.9466621120737462,
+           0.9911498030046099,
+           1.0357484263305077,
+           1.0785655171549668,
+           1.117804141565257,
+           1.151805321797991,
+           1.179086282440641,
+           1.1983736078413658,
+           1.208630535277905,
+           1.2090777615351573,
+           1.1992073084760104,
+           1.1787891717153358,
+           1.1478706611216767,
+           1.106768527931227,
+           1.056054156093553,
+           0.9965322704969631,
+           0.9292137775668243,
+           0.8552835003279404,
+           0.77606369672263,
+           0.6929743536339281,
+           0.607491327116198,
+           0.5211034498675022,
+           0.4352697487670033,
+           0.3513779078480721,
+           0.2707050756209539,
+           0.19438205116373503,
+           0.12336179253809447,
+           0.05839307618986406,
+           5.123193964678516e-16
+          ],
+          [
+           0,
+           -0.049127556636263926,
+           -0.09145170303299421,
+           -0.12730347129111347,
+           -0.15724729601519438,
+           -0.18206404507284052,
+           -0.20272787870956263,
+           -0.2203775440041229,
+           -0.23628285829676396,
+           -0.2518072627124474,
+           -0.2683674319788744,
+           -0.28739100671277534,
+           -0.31027356715594845,
+           -0.33833599160518596,
+           -0.37278333783512263,
+           -0.4146663517320099,
+           -0.46484664494438277,
+           -0.5239664941319824,
+           -0.5924241005517545,
+           -0.6703550130757945,
+           -0.7576202636593958,
+           -0.8538015956049552,
+           -0.9582039859095047,
+           -1.069865478018537,
+           -1.1875741550715264,
+           -1.309891900891642,
+           -1.4351844211440195,
+           -1.5616568346741966,
+           -1.687393999150338,
+           -1.8104046094757311,
+           -1.9286680052212115,
+           -2.040182547182846,
+           -2.1430143750870645,
+           -2.235345339737964,
+           -2.3155189140970407,
+           -2.3820829287286553,
+           -2.4338280468206586,
+           -2.46982099096623,
+           -2.489431655759579,
+           -2.492353384081861,
+           -2.478615847251691,
+           -2.448590146039171,
+           -2.402985936578304,
+           -2.342840577883243,
+           -2.26950049125438,
+           -2.184595111593698,
+           -2.0900039918646027,
+           -1.9878177901598046,
+           -1.8802940199242366,
+           -1.7698085740761655,
+           -1.6588041398433038,
+           -1.5497367004363143,
+           -1.4450213702257844,
+           -1.3469788305833184,
+           -1.2577836234387672,
+           -1.1794155190927416,
+           -1.1136151048493454,
+           -1.0618446432659514,
+           -1.025255125604424,
+           -1.0046603003860903,
+           -1.000518292328518,
+           -1.012921247367941,
+           -1.0415932493078675,
+           -1.085896557502322,
+           -1.1448460176490622,
+           -1.2171313040308935,
+           -1.3011464661105716,
+           -1.395026079760999,
+           -1.4966871477872052,
+           -1.6038757595409077,
+           -1.714217408604059,
+           -1.8252697833943012,
+           -1.9345767901378188,
+           -2.039722542272691,
+           -2.1383840555610876,
+           -2.228381423823437,
+           -2.3077243153383162,
+           -2.3746537229328637,
+           -2.427678019292501,
+           -2.4656025100969425,
+           -2.4875518377411514,
+           -2.492984763663857,
+           -2.4817010433547497,
+           -2.4538403003604006,
+           -2.409872999329884,
+           -2.3505838085784685,
+           -2.2770478251361945,
+           -2.1906003053283762,
+           -2.0928006974624243,
+           -1.9853919064433865,
+           -1.8702558298914478,
+           -1.7493662889585686,
+           -1.624740532560934,
+           -1.4983905198815584,
+           -1.3722751822068624,
+           -1.2482548316387534,
+           -1.1280488219037823,
+           -1.0131974770102825,
+           -0.9050291892005387,
+           -0.8046334514381815,
+           -0.7128404350298467,
+           -0.6302075538247889,
+           -0.5570132770396158,
+           -0.49325826763786146,
+           -0.43867373700806134,
+           -0.39273672410032895,
+           -0.3546918327705721,
+           -0.3235787992016274,
+           -0.298265115957844,
+           -0.27748281409795517,
+           -0.2598684029228888,
+           -0.2440048908836922,
+           -0.2284647627823094,
+           -0.21185276882987938,
+           -0.19284739082306268,
+           -0.17023988936249884,
+           -0.14296990264444695,
+           -0.11015666018086162,
+           -0.07112499146024287,
+           -0.02542544706905121,
+           0.027151995354264706,
+           0.08657099970418371,
+           0.1525488965198824,
+           0.22456366460650173,
+           0.30186768714330103,
+           0.3835079228724918,
+           0.46835196470619406,
+           0.5551193032367757,
+           0.6424169751285266,
+           0.7287786597116171,
+           0.8127061942752922,
+           0.8927124119504419,
+           0.9673641674083218,
+           1.035324405906578,
+           1.0953921507820295,
+           1.1465393328824183,
+           1.1879434614810398,
+           1.2190152380667347,
+           1.2394203395337218,
+           1.2490947426088517,
+           1.2482531232341412,
+           1.2373900390336667,
+           1.2172737855780638,
+           1.1889330033462466,
+           1.1536362974020207,
+           1.1128653112002471,
+           1.0682818650929229,
+           1.0216899247474511,
+           0.974993300896671,
+           0.930150096144569,
+           0.8891250040229542,
+           0.8538406278149365,
+           0.8261290201838831,
+           0.8076846484377518,
+           0.8000199641216524,
+           0.8044247001127185,
+           0.8219299347680316,
+           0.8532778529262853,
+           0.8988980003165804,
+           0.9588906744010242,
+           1.033017924598508,
+           1.120702452349182,
+           1.2210345110425633,
+           1.332786712112229,
+           1.4544364513516477,
+           1.5841954834581897,
+           1.7200459975493203,
+           1.8597823862436567,
+           2.00105775982295,
+           2.141434138487254,
+           2.278435162735672,
+           2.409600096775282,
+           2.5325378642269074,
+           2.644979850182066,
+           2.744830229048497,
+           2.830212633030465,
+           2.8995120602138353,
+           2.9514110320516695,
+           2.9849191449024035,
+           2.9993953158989832,
+           2.994562196051874,
+           2.9705124089224983,
+           2.9277064669417636,
+           2.8669624147823454,
+           2.7894374453263935,
+           2.6966019239346166,
+           2.5902064362976627,
+           2.4722426397760104,
+           2.3448988438176586,
+           2.2105113682559043,
+           2.071512826058888,
+           1.9303785470774693,
+           1.7895723998517905,
+           1.6514932786464414,
+           1.5184235023904473,
+           1.3924803216553043,
+           1.2755716505000227,
+           1.1693570339386623,
+           1.075214731591214,
+           0.9942156469955532,
+           0.9271046638310328,
+           0.8742897690890878,
+           0.835839153493674,
+           0.8114862858946873,
+           0.800642765687525,
+           0.8024185702769504,
+           0.8156491377795312,
+           0.838928562861664,
+           0.8706480397872148,
+           0.9090385648829719,
+           0.9522168136540177,
+           0.9982330380059456,
+           1.0451197880882044,
+           1.0909402520781148,
+           1.1338350259531564,
+           1.1720661733828932,
+           1.2040575120168395,
+           1.2284301646618394,
+           1.2440325395004883,
+           1.2499640493903945,
+           1.2455920426975033,
+           1.2305615929452378,
+           1.204797977394732,
+           1.1685018609090145,
+           1.1221373864195818,
+           1.066413552372265,
+           1.0022594262020144,
+           0.9307938969633429,
+           0.8532908058874515,
+           0.7711404074799802,
+           0.6858082029981817,
+           0.598792250558638,
+           0.5115800902079969,
+           0.4256064272344667,
+           0.3422126927353785,
+           0.26260954764839795,
+           0.18784331648031374,
+           0.1187672318898719,
+           0.056018243791583926,
+           4.898587196589409e-16
+          ]
+         ],
+         "y": [
+          [
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0
+          ],
+          [
+           0,
+           0.0007676059644469046,
+           0.0016216519819783383,
+           0.0025552485258622244,
+           0.003558552558133107,
+           0.004619036972158722,
+           0.00572183685289155,
+           0.00685016344937142,
+           0.007985774966332694,
+           0.009109491771397605,
+           0.010201742419907482,
+           0.011243126051624856,
+           0.012214976234294869,
+           0.013099911231086895,
+           0.013882355955363997,
+           0.014549021540496088,
+           0.01508932947847656,
+           0.0154957686437355,
+           0.015764175184083275,
+           0.01589392718782014,
+           0.01588804817672975,
+           0.015753215775511736,
+           0.015499674311662706,
+           0.015141052545666833,
+           0.01469409015820811,
+           0.014178278967920776,
+           0.013615427060782729,
+           0.013029156024816609,
+           0.01244434325023413,
+           0.011886522730513799,
+           0.01138125894627699,
+           0.01095350920147513,
+           0.010626990189446175,
+           0.010423564583367387,
+           0.010362663069753609,
+           0.010460756482916288,
+           0.01073089157027815,
+           0.01118230244985592,
+           0.011820108047312422,
+           0.012645103763616819,
+           0.013653653375010342,
+           0.014837684759504402,
+           0.016184790537414957,
+           0.017678432168913592,
+           0.01929824353176029,
+           0.021020427569299897,
+           0.022818237312453422,
+           0.024662530496314384,
+           0.026522385163657455,
+           0.028365762119587988,
+           0.030160198911797376,
+           0.031873519189271976,
+           0.033474540859661894,
+           0.03493376643314826,
+           0.03622403931004666,
+           0.037321150532178,
+           0.038204381656200735,
+           0.03885697089338263,
+           0.03926649145889155,
+           0.039425133141121775,
+           0.03932988038775101,
+           0.03898258265466658,
+           0.03838991531711428,
+           0.03756323203735692,
+           0.03651831205670249,
+           0.03527500836941264,
+           0.03385680508123166,
+           0.03229029439912869,
+           0.030604585589319732,
+           0.028830659831944362,
+           0.027000686154489494,
+           0.025147314512031515,
+           0.023302962579502477,
+           0.021499112917902633,
+           0.019765636870935112,
+           0.018130160849040136,
+           0.016617489582015144,
+           0.01524909949629392,
+           0.014042713634019127,
+           0.013011967521430455,
+           0.012166173163534515,
+           0.011510185945596954,
+           0.011044376718762372,
+           0.010764708798639342,
+           0.010662917074565965,
+           0.01072678397552236,
+           0.01094050472623202,
+           0.011285132210285896,
+           0.011739089887578135,
+           0.012278739636195878,
+           0.012878990142071193,
+           0.01351393057284597,
+           0.014157473766214079,
+           0.01478399304871238,
+           0.015368937080022722,
+           0.015889407782052598,
+           0.016324687443580427,
+           0.0166567024631985,
+           0.016870412870380613,
+           0.0169541187039541,
+           0.016899676479841662,
+           0.016702621291235186,
+           0.016362192496111108,
+           0.01588126339855172,
+           0.01526617776019211,
+           0.014526498325423737,
+           0.013674674750097062,
+           0.012725640333360103,
+           0.011696348715948183,
+           0.010605263181952818,
+           0.009471812348441818,
+           0.008315826820113816,
+           0.007156971805223683,
+           0.006014190724499322,
+           0.004905174496516989,
+           0.0038458704604906104,
+           0.0028500438195400352,
+           0.0019289030820290206,
+           0.001090799281526378,
+           0.0003410068106704303,
+           -0.00031840843973974197,
+           -0.0008886302332096258,
+           -0.0013740414024723863,
+           -0.0017820828976026666,
+           -0.002123026202666791,
+           -0.0024096651256012252,
+           -0.0026569350824362315,
+           -0.002881469906671531,
+           -0.003101107868939932,
+           -0.0033343599488470984,
+           -0.003599854425307405,
+           -0.003915772517406689,
+           -0.004299290097424863,
+           -0.0047660404032095335,
+           -0.0053296122003268975,
+           -0.006001096996673902,
+           -0.006788697714204293,
+           -0.007697409703626977,
+           -0.00872878318600957,
+           -0.009880774164965102,
+           -0.01114768862537667,
+           -0.012520222475081265,
+           -0.013985597253648526,
+           -0.015527789188356768,
+           -0.017127846783098012,
+           -0.01876428984153295,
+           -0.02041358070904012,
+           -0.022050656622458392,
+           -0.023649510430514074,
+           -0.02518380563271882,
+           -0.02662751071434276,
+           -0.02795553715519694,
+           -0.029144365276627823,
+           -0.03017264227098006,
+           -0.031021737327702983,
+           -0.031676239717442496,
+           -0.032124386997662076,
+           -0.03235841212949532,
+           -0.032374800206478836,
+           -0.03217444764522552,
+           -0.03176271902365503,
+           -0.031149399217060416,
+           -0.0303485410157076,
+           -0.029378210947662433,
+           -0.028260138514662907,
+           -0.027019276415896847,
+           -0.025683281526077434,
+           -0.02428192835602489,
+           -0.022846468407404685,
+           -0.02140895019647222,
+           -0.020001515730555645,
+           -0.01865568985016681,
+           -0.017401679082950823,
+           -0.01626769648674603,
+           -0.015279328391288276,
+           -0.014458957994780298,
+           -0.01382525945537922,
+           -0.013392774470244763,
+           -0.013171581395908152,
+           -0.013167064780297267,
+           -0.013379790801735361,
+           -0.013805491601281698,
+           -0.014435158912863505,
+           -0.015255244803517835,
+           -0.016247964796735702,
+           -0.017391696227097665,
+           -0.018661462423019207,
+           -0.0200294912911337,
+           -0.02146583512967255,
+           -0.02293903707139798,
+           -0.02441682848358611,
+           -0.02586684095896403,
+           -0.02725731623375388,
+           -0.0285577974737518,
+           -0.029739785873480758,
+           -0.030777347403919793,
+           -0.03164765579869724,
+           -0.03233145945561349,
+           -0.03281346181047595,
+           -0.03308260686690567,
+           -0.03313226388644252,
+           -0.03296030770069315,
+           -0.03256909364092287,
+           -0.03196532862812234,
+           -0.03115984246568542,
+           -0.0301672657662358,
+           -0.02900562316548782,
+           -0.02769585247523402,
+           -0.026261262156126827,
+           -0.024726940907166428,
+           -0.02311913423882212,
+           -0.02146460359525017,
+           -0.01978998390211585,
+           -0.01812115533371313,
+           -0.01648264461979694,
+           -0.014897070361882054,
+           -0.013384645623136111,
+           -0.011962749526577334,
+           -0.010645577782242507,
+           -0.009443880011473045,
+           -0.008364789497453567,
+           -0.007411748622157279,
+           -0.006584530810536899,
+           -0.0058793573544177165,
+           -0.005289105092468097,
+           -0.004803598638779124,
+           -0.004409978737992814,
+           -0.004093136432250196,
+           -0.0038362011015066586,
+           -0.003621069124183563,
+           -0.0034289589320761512,
+           -0.0032409776256857275,
+           -0.003038684088252832,
+           -0.0028046336937406313,
+           -0.002522890241183859,
+           -0.00217949165095346,
+           -0.0017628572041792129,
+           -0.0012641256628124055,
+           -0.0006774154348008261,
+           -6.734692708291278e-18
+          ],
+          [
+           0,
+           0.0015963423292227816,
+           0.003360017028019801,
+           0.005274187330629608,
+           0.007316386113923138,
+           0.009459141642869961,
+           0.011670747032584113,
+           0.013916153118803955,
+           0.016157961163513732,
+           0.0183574891582515,
+           0.020475883492665697,
+           0.02247524648146543,
+           0.024319749722335582,
+           0.02597670350498246,
+           0.027417553502241992,
+           0.028618777723911023,
+           0.029562659159824384,
+           0.030237912620302412,
+           0.0306401479229752,
+           0.03077215568451945,
+           0.030644006451473547,
+           0.030272958634113195,
+           0.029683175572881117,
+           0.028905256945956085,
+           0.02797559449652373,
+           0.026935566598968452,
+           0.025830590379823493,
+           0.024709053855538926,
+           0.02362115374962185,
+           0.02261766722455499,
+           0.021748687642673438,
+           0.02106235560559333,
+           0.020603616882970906,
+           0.020413038416658546,
+           0.02052571238357521,
+           0.02097027634703889,
+           0.021768074867849267,
+           0.022932484646588838,
+           0.02446842140701286,
+           0.02637204240070309,
+           0.028630653720848075,
+           0.031222826672766622,
+           0.03411872238166728,
+           0.03728061874858134,
+           0.0406636289181721,
+           0.04421659571919759,
+           0.04788314219597184,
+           0.05160285447475522,
+           0.05531256989878523,
+           0.05894774070209586,
+           0.062443841542043764,
+           0.06573778802280769,
+           0.06876933294763118,
+           0.07148240744736568,
+           0.073826375338353,
+           0.07575717103572242,
+           0.07723829404178593,
+           0.0782416363786876,
+           0.07874812325897589,
+           0.07874815169233432,
+           0.07824181650453475,
+           0.07723891827977387,
+           0.07575875290758495,
+           0.07382968759481362,
+           0.07148853326579169,
+           0.06877972809677627,
+           0.06575435139675773,
+           0.062468991047450274,
+           0.05898449115366953,
+           0.05536460934817022,
+           0.05167461527502704,
+           0.04797986309293873,
+           0.044344371363296706,
+           0.040829443405822244,
+           0.037492360125130804,
+           0.03438517546235261,
+           0.031553642053382736,
+           0.029036291443597657,
+           0.02686368939817869,
+           0.025057882551844036,
+           0.023632047967882357,
+           0.02259035223909375,
+           0.021928021684056737,
+           0.02163162009578917,
+           0.021679525511296725,
+           0.022042592711738147,
+           0.022684983750118168,
+           0.02356514484391528,
+           0.024636904559820927,
+           0.025850665439007967,
+           0.027154659130476707,
+           0.02849623376606804,
+           0.02982314175411924,
+           0.031084796400591044,
+           0.03223346677837939,
+           0.033225382029683705,
+           0.03402171875638215,
+           0.03458944826558157,
+           0.03490202411227506,
+           0.03493989452495727,
+           0.03469082880824514,
+           0.034150051575325274,
+           0.03332018355269301,
+           0.03221099259744458,
+           0.030838963350674875,
+           0.029226698499762123,
+           0.027402168824025835,
+           0.025397832947865774,
+           0.023249650929984378,
+           0.02099601839742895,
+           0.01867664982551958,
+           0.016331440723154317,
+           0.013999338879890882,
+           0.011717254458143216,
+           0.009519037581695543,
+           0.007434550210487276,
+           0.005488856549524191,
+           0.0037015530821566194,
+           0.002086255625611037,
+           0.0006502566737338669,
+           -0.0006056381763900129,
+           -0.001687090607345006,
+           -0.00260602745991432,
+           -0.0033802615669498394,
+           -0.004032945635654915,
+           -0.004591873646769419,
+           -0.005088648245444333,
+           -0.005557736133865597,
+           -0.006035436449857983,
+           -0.006558789452784604,
+           -0.00716445447807869,
+           -0.007887587022233857,
+           -0.008760744957160007,
+           -0.009812853241804345,
+           -0.011068255114486112,
+           -0.01254587564512457,
+           -0.014258520754221921,
+           -0.01621233143373681,
+           -0.01840640901765782,
+           -0.020832623044049422,
+           -0.0234756086331602,
+           -0.02631295549342414,
+           -0.029315585779519936,
+           -0.032448313186880046,
+           -0.03567057099698367,
+           -0.038937292405259685,
+           -0.04219992247935754,
+           -0.04540753761106308,
+           -0.04850804542916745,
+           -0.05144943590752845,
+           -0.054181052890453385,
+           -0.056654854506577416,
+           -0.05882663097395088,
+           -0.06065714911499825,
+           -0.062113194482781485,
+           -0.0631684843129035,
+           -0.06380442750353386,
+           -0.06401071141764166,
+           -0.06378569940969457,
+           -0.06313662750392865,
+           -0.06207959348239433,
+           -0.0606393366601047,
+           -0.058848811708620746,
+           -0.05674856491331412,
+           -0.05438592608960739,
+           -0.05181403392023828,
+           -0.04909071659682755,
+           -0.04627725325259137,
+           -0.04343704466931068,
+           -0.0406342240558741,
+           -0.03793224026968253,
+           -0.0353924466459216,
+           -0.033072728592246456,
+           -0.031026202296501715,
+           -0.029300015301153823,
+           -0.02793427735779495,
+           -0.026961146944427215,
+           -0.026404095180226073,
+           -0.026277364695297206,
+           -0.026585636407778175,
+           -0.027323912239233517,
+           -0.028477616681179086,
+           -0.030022914935135717,
+           -0.03192724021203051,
+           -0.03415001781891496,
+           -0.03664356900234187,
+           -0.039354173271494916,
+           -0.04222326419332461,
+           -0.04518873052688421,
+           -0.04818629212029019,
+           -0.05115091829001047,
+           -0.05401825547914833,
+           -0.05672603087047477,
+           -0.05921539931296695,
+           -0.06143220238962781,
+           -0.0633281106722197,
+           -0.06486162311977717,
+           -0.06599890110996665,
+           -0.06671441865798038,
+           -0.0669914148761926,
+           -0.06682213954828492,
+           -0.06620788771526873,
+           -0.06515882427429841,
+           -0.06369360464915995,
+           -0.061838802479965836,
+           -0.05962815987943019,
+           -0.05710168000204765,
+           -0.05430458536857208,
+           -0.051286168492034545,
+           -0.04809856378862369,
+           -0.044795471469170296,
+           -0.0414308650548925,
+           -0.03805771432362113,
+           -0.03472675486860394,
+           -0.03148533405932476,
+           -0.02837636106975411,
+           -0.025437385839316158,
+           -0.022699828427514997,
+           -0.02018837630138507,
+           -0.017920562755167076,
+           -0.01590653501347633,
+           -0.014149015729815455,
+           -0.012643456683167215,
+           -0.011378378619661483,
+           -0.010335886505430067,
+           -0.009492345067617512,
+           -0.00881919551245442,
+           -0.008283890821434324,
+           -0.007850924125370872,
+           -0.007482922413010904,
+           -0.007141776300881133,
+           -0.006789775811122095,
+           -0.0063907220923008325,
+           -0.005910985773364163,
+           -0.005320484142504575,
+           -0.004593551551523323,
+           -0.0037096803053114622,
+           -0.002654112732042413,
+           -0.001418269054835131,
+           -1.4054791784244343e-17
+          ],
+          [
+           0,
+           0.0024833296957056604,
+           0.00520718842390496,
+           0.008141938507937587,
+           0.011249983583189585,
+           0.014486829490071788,
+           0.017802344031074783,
+           0.021142182243926465,
+           0.024449339452181227,
+           0.027665790927109385,
+           0.030734174618447373,
+           0.03359947214791022,
+           0.03621064314187798,
+           0.03852216901303855,
+           0.040495464460723385,
+           0.04210011819355521,
+           0.04331492860609869,
+           0.04412870525861968,
+           0.04454081288846129,
+           0.04456144117623965,
+           0.04421159043766041,
+           0.043522770638226314,
+           0.042536418452099156,
+           0.04130304432377126,
+           0.039881128459672725,
+           0.03833579120044175,
+           0.03673726913813746,
+           0.03515923349589955,
+           0.033676991548858635,
+           0.03236561512485446,
+           0.0312980423968571,
+           0.030543200207931213,
+           0.030164194024545007,
+           0.03021661129456738,
+           0.030746981521204107,
+           0.031791432810723386,
+           0.03337458009460517,
+           0.03550867477531814,
+           0.03819303933130925,
+           0.041413803592193925,
+           0.04514395212623555,
+           0.04934368464703171,
+           0.05396108372987566,
+           0.05893307661792295,
+           0.06418667067920701,
+           0.06964043532604343,
+           0.0752061970955161,
+           0.08079090926525277,
+           0.08629865297511927,
+           0.09163272345289875,
+           0.09669775268539167,
+           0.10140181879328243,
+           0.10565849248743131,
+           0.10938877230531657,
+           0.1125228628190365,
+           0.11500175361165177,
+           0.11677856145042559,
+           0.11781960363216779,
+           0.11810517680337036,
+           0.11763002251285005,
+           0.11640346816845472,
+           0.11444923976197695,
+           0.11180495051079996,
+           0.10852127725172303,
+           0.1046608438249877,
+           0.10029683762481104,
+           0.09551139179817546,
+           0.09039377109318807,
+           0.0850384039582644,
+           0.07954280706252684,
+           0.07400545086026292,
+           0.06852361609956831,
+           0.0631912912477587,
+           0.05809715967363739,
+           0.05332272311866329,
+           0.048940604563649966,
+           0.045013069140342234,
+           0.04159079635876685,
+           0.03871193075477717,
+           0.03640143126000291,
+           0.03467073232614073,
+           0.033517722276063644,
+           0.03292703669128237,
+           0.0328706570667524,
+           0.033308797655368046,
+           0.03419105656418262,
+           0.035457800919515614,
+           0.03704175044020806,
+           0.038869719179685076,
+           0.04086447162801638,
+           0.04294664688950207,
+           0.04503670332689538,
+           0.047056835919046074,
+           0.04893281961406379,
+           0.05059573414539996,
+           0.051983529055417727,
+           0.05304239195500346,
+           0.05372788822869722,
+           0.054005846340777576,
+           0.053852969458096964,
+           0.05325716111463716,
+           0.052217559924342655,
+           0.05074428571998971,
+           0.04885790677200486,
+           0.046588644740373004,
+           0.04397534056045951,
+           0.041064210396747916,
+           0.03790742596986512,
+           0.03456155784388973,
+           0.03108592354736652,
+           0.027540884612371513,
+           0.023986137698163643,
+           0.02047904489460418,
+           0.01707304707981004,
+           0.013816201869473431,
+           0.01074988430298973,
+           0.007907684051522588,
+           0.005314527717172674,
+           0.0029860488537397974,
+           0.0009282218294878514,
+           -0.0008627312635506179,
+           -0.0024001585951071882,
+           -0.0037065266129115457,
+           -0.004812710285889268,
+           -0.005757044517650248,
+           -0.006584161935966061,
+           -0.007343647882449639,
+           -0.008088548258332693,
+           -0.008873769803881663,
+           -0.009754415300264111,
+           -0.010784098008634857,
+           -0.012013280354192243,
+           -0.013487681403792747,
+           -0.015246796084228895,
+           -0.017322566383052764,
+           -0.01973824103127131,
+           -0.02250745547992713,
+           -0.025633558466973114,
+           -0.029109205264406975,
+           -0.03291623095337429,
+           -0.03702580996561203,
+           -0.041398900831444485,
+           -0.04598696777085252,
+           -0.05073296363872951,
+           -0.05557255196799719,
+           -0.06043553961588615,
+           -0.06524748596762277,
+           -0.06993144992936609,
+           -0.07440983216952916,
+           -0.0786062673421185,
+           -0.08244751941911069,
+           -0.08586533281506839,
+           -0.08879819272124964,
+           -0.091192949964171,
+           -0.09300626872176258,
+           -0.09420585949777274,
+           -0.09477146477460432,
+           -0.09469557061509831,
+           -0.09398382402287955,
+           -0.09265514293929976,
+           -0.09074151317987116,
+           -0.08828747421230781,
+           -0.08534930326510896,
+           -0.08199391464318087,
+           -0.07829749813301277,
+           -0.07434392683114667,
+           -0.0702229704662227,
+           -0.06602835516419236,
+           -0.06185571450663225,
+           -0.057800479555679074,
+           -0.053955757194426156,
+           -0.05041024661531729,
+           -0.04724624306698999,
+           -0.044537776057578984,
+           -0.04234892615439141,
+           -0.04073236038889629,
+           -0.039728121171380394,
+           -0.039362697664548925,
+           -0.03964840190391271,
+           -0.040583064746502494,
+           -0.042150059153229016,
+           -0.04431865054813577,
+           -0.047044666238560656,
+           -0.05027146831247288,
+           -0.053931207236981006,
+           -0.05794632673998371,
+           -0.06223128462646233,
+           -0.06669444910581895,
+           -0.07124012610978422,
+           -0.07577067006060324,
+           -0.08018862867883024,
+           -0.08439887174336919,
+           -0.08831065424828664,
+           -0.09183956612672341,
+           -0.0949093235880237,
+           -0.09745336106789998,
+           -0.09941618772466154,
+           -0.10075447820496128,
+           -0.10143787390697653,
+           -0.10144947802697861,
+           -0.1007860351130334,
+           -0.09945779348427167,
+           -0.0974880565183815,
+           -0.09491243627645705,
+           -0.09177783004054252,
+           -0.08814114691183436,
+           -0.0840678174967518,
+           -0.07963012475156787,
+           -0.07490539814256818,
+           -0.06997411631022543,
+           -0.06491796533135759,
+           -0.05981790040942127,
+           -0.05475225837572815,
+           -0.04979496676858478,
+           -0.045013892517150336,
+           -0.04046936946401034,
+           -0.036212939212857724,
+           -0.03228633420650774,
+           -0.028720725667476594,
+           -0.025536252227140604,
+           -0.022741837901568345,
+           -0.0203353007226745,
+           -0.018303745986667744,
+           -0.016624230921705365,
+           -0.015264680782031788,
+           -0.01418503011598282,
+           -0.013338557385694737,
+           -0.012673376375221009,
+           -0.01213404402808327,
+           -0.011663241598237365,
+           -0.011203484346991366,
+           -0.010698814511709372,
+           -0.010096432920519397,
+           -0.00934822641203682,
+           -0.008412151093116639,
+           -0.007253435356323094,
+           -0.005845571382185906,
+           -0.004171069446503937,
+           -0.0022219555972444543,
+           -2.1943931114862367e-17
+          ],
+          [
+           0,
+           0.0034246641548217696,
+           0.007153331743936164,
+           0.011140964910712148,
+           0.015332653515663649,
+           0.019665180601642983,
+           0.02406882847961949,
+           0.028469377503397755,
+           0.03279024447302175,
+           0.03695470383369965,
+           0.04088813251692745,
+           0.044520218463616645,
+           0.0477870735979016,
+           0.05063319426872937,
+           0.05301321588985652,
+           0.05489341359610506,
+           0.05625290706859598,
+           0.05708453510657652,
+           0.05739537385314715,
+           0.05720688160841972,
+           0.0565546626603093,
+           0.055487852291993656,
+           0.054068134841524215,
+           0.05236841614845591,
+           0.050471180685954894,
+           0.048466571917857734,
+           0.04645024172941552,
+           0.04452102097164599,
+           0.042778468073552164,
+           0.0413203561866997,
+           0.0402401613402845,
+           0.03962461454647425,
+           0.03955137968863178,
+           0.04008691637119517,
+           0.04128458277020309,
+           0.043183027995494914,
+           0.04580491669197022,
+           0.04915602073191563,
+           0.0532247040747043,
+           0.05798181740828535,
+           0.0633810092704193,
+           0.06935945021993888,
+           0.07583895653852471,
+           0.08272749014026513,
+           0.08992100209172343,
+           0.09730557862891093,
+           0.10475984101073231,
+           0.11215754415890689,
+           0.11937031396167616,
+           0.1262704594902446,
+           0.13273379428499266,
+           0.1386424003675441,
+           0.1438872697402486,
+           0.14837076082257844,
+           0.15200881148152137,
+           0.15473285594005806,
+           0.1564913997591367,
+           0.15725121511745307,
+           0.15699812756554737,
+           0.15573737508920432,
+           0.1534935304474268,
+           0.1503099881062132,
+           0.14624802741924636,
+           0.14138547375922422,
+           0.13581498883449594,
+           0.12964203020324705,
+           0.12298252780850319,
+           0.11596033201218113,
+           0.10870449294417307,
+           0.10134643487416313,
+           0.09401709166619507,
+           0.08684407013331483,
+           0.07994890725541637,
+           0.07344448478069285,
+           0.06743266076172762,
+           0.06200217218048077,
+           0.05722685612633601,
+           0.0531642291736294,
+           0.049854455852766856,
+           0.04731972763789631,
+           0.045564063917192844,
+           0.04457353621374454,
+           0.0443169067359162,
+           0.044746662405357046,
+           0.04580041608113757,
+           0.04740263799966281,
+           0.0494666726933765,
+           0.05189699002453575,
+           0.05459161363293468,
+           0.05744466617564766,
+           0.06034896832464624,
+           0.06319862763901492,
+           0.06589155415816352,
+           0.0683318418474983,
+           0.07043195880658586,
+           0.07211469432314711,
+           0.0733148172911058,
+           0.07398040804321378,
+           0.07407383408741344,
+           0.0735723493679084,
+           0.07246830626694184,
+           0.07076897938055496,
+           0.06849600989512435,
+           0.06568448891637867,
+           0.06238170712121939,
+           0.058645606390482316,
+           0.05454297643196897,
+           0.05014744563564311,
+           0.04553732036318493,
+           0.04079333044058424,
+           0.035996340708770204,
+           0.031225089044280868,
+           0.026554010278998532,
+           0.02205120295302484,
+           0.017776591893782834,
+           0.01378033432962032,
+           0.01010151075344435,
+           0.006767134217361799,
+           0.00379150335515726,
+           0.0011759154091472064,
+           -0.0010912538891561078,
+           -0.0030341063295863625,
+           -0.004688425388297966,
+           -0.006100550010759341,
+           -0.0073259481252928565,
+           -0.008427527877541535,
+           -0.009473731482734535,
+           -0.010536462351916609,
+           -0.0116889006134032,
+           -0.013003265207158827,
+           -0.01454858229853204,
+           -0.0163885197971849,
+           -0.01857934627398068,
+           -0.021168069578473954,
+           -0.024190806045629558,
+           -0.027671425451553204,
+           -0.03162050997662079,
+           -0.03603465753240679,
+           -0.04089615110359996,
+           -0.046173006465504936,
+           -0.051819400994675545,
+           -0.05777647653689174,
+           -0.06397349967843598,
+           -0.07032935352593349,
+           -0.0767543264703647,
+           -0.08315215561090884,
+           -0.08942227574241582,
+           -0.09546221923959605,
+           -0.1011701079449743,
+           -0.10644717539645025,
+           -0.11120025648816148,
+           -0.11534418198146969,
+           -0.11880401716863061,
+           -0.12151708739850187,
+           -0.12343473802200822,
+           -0.12452378248953276,
+           -0.12476759968426496,
+           -0.1241668499265734,
+           -0.12273978823129719,
+           -0.12052216311888511,
+           -0.11756669933434029,
+           -0.11394217296796083,
+           -0.10973209744923017,
+           -0.10503304845374668,
+           -0.09995266468624449,
+           -0.09460736955943536,
+           -0.08911986577844826,
+           -0.08361646058985199,
+           -0.07822428381859464,
+           -0.07306846368559251,
+           -0.06826932669956566,
+           -0.06393968761397323,
+           -0.06018229353779218,
+           -0.05708748283092336,
+           -0.054731114482999325,
+           -0.053172817386282795,
+           -0.05245460142062401,
+           -0.052599863752113424,
+           -0.05361281441342697,
+           -0.05547833530935229,
+           -0.05816227651664805,
+           -0.06161218337293785,
+           -0.06575843762702177,
+           -0.07051578610136007,
+           -0.07578522113534654,
+           -0.08145616875844487,
+           -0.08740893328730055,
+           -0.09351734102642428,
+           -0.09965152112339894,
+           -0.1056807584982512,
+           -0.11147635220732058,
+           -0.1169144126508725,
+           -0.12187853268753326,
+           -0.12626227093483058,
+           -0.12997139023290338,
+           -0.13292580031074208,
+           -0.13506116097080698,
+           -0.13633011041862259,
+           -0.13670309250389615,
+           -0.1361687663837689,
+           -0.13473399222740717,
+           -0.13242339680614107,
+           -0.1292785329042091,
+           -0.12535665619506867,
+           -0.12072915232023655,
+           -0.115479655160451,
+           -0.10970190450247158,
+           -0.10349739730493825,
+           -0.09697289140961748,
+           -0.09023782372011603,
+           -0.08340170650525477,
+           -0.07657156554357741,
+           -0.06984948231277273,
+           -0.06333029938592376,
+           -0.05709954370602303,
+           -0.05123161658745625,
+           -0.045788292287296764,
+           -0.04081755897842528,
+           -0.03635282714346573,
+           -0.032412521015575395,
+           -0.029000058955415017,
+           -0.026104218817433925,
+           -0.02369987466911534,
+           -0.021749081926065415,
+           -0.02020247928561165,
+           -0.019000967997746258,
+           -0.018077622199313043,
+           -0.01735977842364706,
+           -0.01677124812144621,
+           -0.016234594193761102,
+           -0.015673411212590964,
+           -0.015014549218661062,
+           -0.014190222730837695,
+           -0.013139949830177662,
+           -0.011812270809471979,
+           -0.010166201786898123,
+           -0.008172385718557083,
+           -0.005813911229499545,
+           -0.0030867784128778596,
+           -3.037580115434353e-17
+          ],
+          [
+           0,
+           0.004415469164794989,
+           0.00918681853690486,
+           0.01425131203144025,
+           0.019534902027938568,
+           0.02495435814114457,
+           0.030419663555842184,
+           0.03583661518879555,
+           0.04110955849134105,
+           0.046144184026030585,
+           0.05085031113505788,
+           0.05514458411519827,
+           0.05895300832371782,
+           0.06221325751405295,
+           0.06487668934393491,
+           0.0669100132722966,
+           0.06829656378384444,
+           0.06903714183401295,
+           0.06915039834328951,
+           0.06867274521467445,
+           0.06765779140916388,
+           0.06617531378848955,
+           0.06430978441541736,
+           0.06215848748746024,
+           0.05982926977949568,
+           0.05743797811318171,
+           0.05510564571082345,
+           0.05295549611509227,
+           0.051109838487803025,
+           0.049686931406733206,
+           0.04879789367040843,
+           0.04854374005561317,
+           0.049012617458488235,
+           0.05027731244335582,
+           0.05239309502699404,
+           0.05539595568782017,
+           0.05930128329830652,
+           0.06410302116041312,
+           0.06977332683429421,
+           0.07626274927107424,
+           0.08350092418985759,
+           0.09139777598641805,
+           0.09984520203798793,
+           0.10871920338198177,
+           0.11788241469045713,
+           0.1271869765108571,
+           0.1364776841445614,
+           0.14559534050261855,
+           0.1543802349891342,
+           0.16267566705094172,
+           0.17033143158520572,
+           0.17720718395415475,
+           0.18317560490866763,
+           0.18812529021136457,
+           0.19196329606903265,
+           0.19461727948241428,
+           0.1960371821060739,
+           0.1961964169530497,
+           0.19509252901811394,
+           0.19274731334490075,
+           0.1892063869234958,
+           0.18453822376370316,
+           0.1788326752300038,
+           0.17219900993733808,
+           0.1647635188952976,
+           0.15666674187528926,
+           0.14806037991092225,
+           0.13910396620955925,
+           0.12996137337443484,
+           0.12079723857654132,
+           0.11177339008434317,
+           0.1030453583163301,
+           0.09475905233480475,
+           0.0870476785065189,
+           0.08002897202186074,
+           0.07380280423929617,
+           0.06844921959699268,
+           0.06402694533687282,
+           0.06057240577648997,
+           0.05809926062433351,
+           0.0565984741651691,
+           0.056038909354565056,
+           0.056368428269001083,
+           0.057515468267688406,
+           0.059391051929311135,
+           0.06189117860598316,
+           0.06489953653550178,
+           0.06829046708612804,
+           0.07193210705199762,
+           0.07568963110561482,
+           0.07942851463461252,
+           0.0830177372830093,
+           0.0863328495736248,
+           0.08925882895060402,
+           0.09169265734454606,
+           0.0935455597785053,
+           0.0947448524114655,
+           0.09523535853121542,
+           0.0949803621051001,
+           0.09396208029528395,
+           0.09218164854849573,
+           0.0896586241728607,
+           0.08643002640867845,
+           0.08254894258404034,
+           0.07808274073154428,
+           0.07311093876111766,
+           0.06772278869538259,
+           0.06201464137049909,
+           0.05608716221775267,
+           0.0500424721425045,
+           0.04398128902632737,
+           0.038000144961596094,
+           0.032188752000256636,
+           0.02662758502270149,
+           0.02138574441769452,
+           0.016519153762769512,
+           0.012069138798858924,
+           0.008061423930332373,
+           0.004505571508575921,
+           0.001394877552862693,
+           -0.0012932743785747543,
+           -0.0035966114284552487,
+           -0.0055667437559691274,
+           -0.007267544028283465,
+           -0.008773177473790703,
+           -0.010165835056615946,
+           -0.011533230160754134,
+           -0.01296592545672377,
+           -0.014554561203199251,
+           -0.016387058992994634,
+           -0.018545875815148574,
+           -0.02110538224849299,
+           -0.024129435651074126,
+           -0.02766921443595596,
+           -0.0317613730450485,
+           -0.03642656920949549,
+           -0.04166840571769522,
+           -0.047472818434167924,
+           -0.053807930986437096,
+           -0.060624384646785504,
+           -0.06785613977975212,
+           -0.07542173311033809,
+           -0.08322596329738474,
+           -0.09116196616875423,
+           -0.0991136307715047,
+           -0.10695829837039114,
+           -0.11456967892186455,
+           -0.12182091355351755,
+           -0.12858770734618666,
+           -0.13475145435941877,
+           -0.14020227642603506,
+           -0.14484189878506784,
+           -0.14858628909267968,
+           -0.1513679916680444,
+           -0.15313809586970148,
+           -0.15386778608866086,
+           -0.15354943077967723,
+           -0.1521971789899357,
+           -0.14984704471534557,
+           -0.14655647182789652,
+           -0.1424033849682406,
+           -0.13748474437442493,
+           -0.13191463481028842,
+           -0.1258219302640745,
+           -0.11934758662427652,
+           -0.11264162384393765,
+           -0.10585986694481118,
+           -0.09916052139286272,
+           -0.09270066274092122,
+           -0.08663272287177536,
+           -0.08110105562166398,
+           -0.07623866300485745,
+           -0.07216415972901652,
+           -0.06897904827085025,
+           -0.06676536960139523,
+           -0.06558378588236069,
+           -0.0654721413109856,
+           -0.06644453601613659,
+           -0.06849093577628808,
+           -0.07157732763508176,
+           -0.07564641854083072,
+           -0.08061886124743901,
+           -0.08639497919921132,
+           -0.09285695028526465,
+           -0.09987139847854058,
+           -0.10729233273384615,
+           -0.11496436434292537,
+           -0.12272612743035324,
+           -0.13041382257936002,
+           -0.13786480081425861,
+           -0.14492110440123446,
+           -0.15143288217829642,
+           -0.15726160035513403,
+           -0.1622829748530446,
+           -0.16638955815605316,
+           -0.16949292214560358,
+           -0.17152538828253944,
+           -0.17244126753745403,
+           -0.17221758438202647,
+           -0.17085427164680658,
+           -0.16837383581836926,
+           -0.16482050507790702,
+           -0.16025888476273223,
+           -0.1547721566595679,
+           -0.14845986932827154,
+           -0.14143537624478045,
+           -0.13382298671070408,
+           -0.12575490100799633,
+           -0.11736800602498844,
+           -0.10880061043360485,
+           -0.10018919939267926,
+           -0.09166528767342244,
+           -0.08335244708358908,
+           -0.07536357918809856,
+           -0.0677984977129721,
+           -0.06074187684635642,
+           -0.054261612123400214,
+           -0.04840762994222154,
+           -0.043211170274713745,
+           -0.03868455509741419,
+           -0.03482144277616922,
+           -0.031597556401652044,
+           -0.028971862196608807,
+           -0.026888162896100933,
+           -0.02527706071804157,
+           -0.024058235448115153,
+           -0.023142975485567492,
+           -0.022436893623374515,
+           -0.02184275501641952,
+           -0.0212633423288466,
+           -0.020604282504270925,
+           -0.019776760979460805,
+           -0.018700052424585535,
+           -0.01730380215496339,
+           -0.015529999089177316,
+           -0.013334589353382506,
+           -0.010688689141137854,
+           -0.007579365989543868,
+           -0.004009968957242072,
+           -3.9314484311946475e-17
+          ],
+          [
+           0,
+           0.005449960465010133,
+           0.011294384140923331,
+           0.017450882530927487,
+           0.023824842787335876,
+           0.030312166708526225,
+           0.036802288247519944,
+           0.043181389114940454,
+           0.04933572672818451,
+           0.05515498562255843,
+           0.060535562580564695,
+           0.06538369717687711,
+           0.06961836314527975,
+           0.07317384185931043,
+           0.07600190713499505,
+           0.07807356031505233,
+           0.07938026593606919,
+           0.07993465092982607,
+           0.07977064395034804,
+           0.07894304570714387,
+           0.07752653576340204,
+           0.07561413575868509,
+           0.07331516307323437,
+           0.07075272221012088,
+           0.06806079329622526,
+           0.06538098778520413,
+           0.06285905041245603,
+           0.06064119347322315,
+           0.058870354388047524,
+           0.05768247015528513,
+           0.05720286259474661,
+           0.057542826244221024,
+           0.05879650642451939,
+           0.06103814843907766,
+           0.06431979027645898,
+           0.0686694607449394,
+           0.07408993294060835,
+           0.08055806962693503,
+           0.08802478281020656,
+           0.0964156148820707,
+           0.10563193353416454,
+           0.11555271760409216,
+           0.1260368964582534,
+           0.13692619181525612,
+           0.14804839840360115,
+           0.15922102883999503,
+           0.17025523888455368,
+           0.1809599420075264,
+           0.1911460171711769,
+           0.2006305110186534,
+           0.2092407353407778,
+           0.21681816277471813,
+           0.22322202812945832,
+           0.22833254942785586,
+           0.23205369154441646,
+           0.2343154059906935,
+           0.23507529269897384,
+           0.2343196432820948,
+           0.23206383987247348,
+           0.22835209891166855,
+           0.22325656480200845,
+           0.21687577376614597,
+           0.20933252321342452,
+           0.20077119601993532,
+           0.19135460204902013,
+           0.18126041065670673,
+           0.17067725756493862,
+           0.1598006171108487,
+           0.14882853630848325,
+           0.13795733025988652,
+           0.1273773391519811,
+           0.11726884535970107,
+           0.10779824508902958,
+           0.09911456263863602,
+           0.09134638689387144,
+           0.08459929930166472,
+           0.07895385056540254,
+           0.07446412994121368,
+           0.07115695663991198,
+           0.06903170779542617,
+           0.0680607821199175,
+           0.0681906831036975,
+           0.06934369080769488,
+           0.0714200772989661,
+           0.07430080793631834,
+           0.07785065933516291,
+           0.08192167520316612,
+           0.08635687357256783,
+           0.09099411344353334,
+           0.0956700256243504,
+           0.10022391168077843,
+           0.10450151640211801,
+           0.10835858301068842,
+           0.11166410638204427,
+           0.11430320764829896,
+           0.11617956351838847,
+           0.1172173352134728,
+           0.11736255479016863,
+           0.11658394048428641,
+           0.11487312720479387,
+           0.1122443130783418,
+           0.10873333761936571,
+           0.10439622131321033,
+           0.09930720979590996,
+           0.09355637806131568,
+           0.08724686092068705,
+           0.08049178501507279,
+           0.07341098481370824,
+           0.06612759004822566,
+           0.05876457481195515,
+           0.05144135903155318,
+           0.04427055118797881,
+           0.037354917076742516,
+           0.030784653161269295,
+           0.024635034849861757,
+           0.018964500027596146,
+           0.013813216655439355,
+           0.009202170503792158,
+           0.005132795441033607,
+           0.001587154496374091,
+           -0.0014713344789067172,
+           -0.0040966489515708365,
+           -0.006358421739098663,
+           -0.008339757837870504,
+           -0.010134666556557708,
+           -0.011845177571389509,
+           -0.013578217870034296,
+           -0.015442332931144826,
+           -0.017544339733848453,
+           -0.019986001195959124,
+           -0.02286081134823581,
+           -0.02625097796918291,
+           -0.03022468459297043,
+           -0.03483370688051727,
+           -0.040111449482345955,
+           -0.04607145894220544,
+           -0.05270645615687925,
+           -0.05998791872119612,
+           -0.06786622947861175,
+           -0.07627139311857142,
+           -0.08511430807634404,
+           -0.09428856666661876,
+           -0.10367274268043038,
+           -0.11313311294263675,
+           -0.12252674788726625,
+           -0.13170489635197494,
+           -0.14051658177299753,
+           -0.14881232098531388,
+           -0.15644787305577487,
+           -0.1632879241014434,
+           -0.1692096149161446,
+           -0.17410582143147216,
+           -0.17788810350245768,
+           -0.18048924510454092,
+           -0.18186531857580893,
+           -0.18199721680624598,
+           -0.18089160999024428,
+           -0.17858129740964582,
+           -0.17512493936302365,
+           -0.1706061694431553,
+           -0.165132102517465,
+           -0.15883126861194352,
+           -0.1518510170708224,
+           -0.14435444851109927,
+           -0.13651694388653848,
+           -0.1285223701263041,
+           -0.12055905006525772,
+           -0.11281559052886486,
+           -0.1054766663196732,
+           -0.09871885937408398,
+           -0.09270665147506273,
+           -0.08758866563509451,
+           -0.08349424567930708,
+           -0.08053045579337578,
+           -0.07877957204043351,
+           -0.07829712633065083,
+           -0.07911055032483631,
+           -0.08121845258422555,
+           -0.08459054728637287,
+           -0.08916823737588196,
+           -0.09486583948421518,
+           -0.10157242271280437,
+           -0.10915421879887535,
+           -0.11745754762826217,
+           -0.12631218985364528,
+           -0.13553512781658178,
+           -0.14493456731365145,
+           -0.15431414620058495,
+           -0.16347723155118205,
+           -0.17223120518238522,
+           -0.18039163786704165,
+           -0.1877862554666229,
+           -0.19425860545349377,
+           -0.19967133972543055,
+           -0.20390903905949243,
+           -0.2068805157744135,
+           -0.2085205438935381,
+           -0.20879098001063043,
+           -0.20768125281660274,
+           -0.2052082144840646,
+           -0.20141536245504557,
+           -0.1963714552596585,
+           -0.1901685604414243,
+           -0.18291958612634943,
+           -0.1747553599204224,
+           -0.16582132935980157,
+           -0.15627396681563505,
+           -0.14627696836364354,
+           -0.1359973405112868,
+           -0.12560147073181838,
+           -0.11525127744173863,
+           -0.10510053239177994,
+           -0.09529144349542297,
+           -0.08595157902324212,
+           -0.07719120502918686,
+           -0.06910109707773032,
+           -0.06175087508267651,
+           -0.055187896658950096,
+           -0.049436730165516134,
+           -0.04449921393777316,
+           -0.04035509343893933,
+           -0.036963213571213606,
+           -0.03426322954008865,
+           -0.03217778680364495,
+           -0.03061510908215032,
+           -0.029471923437760627,
+           -0.028636643305154603,
+           -0.027992724260723113,
+           -0.02742210340830591,
+           -0.026808631626313608,
+           -0.026041408600030583,
+           -0.02501793353156749,
+           -0.023646989598476033,
+           -0.021851187485210682,
+           -0.019569102452243158,
+           -0.016756950201272124,
+           -0.013389758965878863,
+           -0.009462008495003919,
+           -0.004987720565017396,
+           -4.8714918725756224e-17
+          ],
+          [
+           0,
+           0.006521523232359227,
+           0.013461307685477633,
+           0.020715740022888337,
+           0.028168639962808554,
+           0.03569464365281609,
+           0.04316285958283444,
+           0.05044069942991049,
+           0.05739778147079768,
+           0.06390980206315203,
+           0.06986227123990627,
+           0.07515401167335695,
+           0.07970032606771542,
+           0.08343574628807784,
+           0.08631628802495202,
+           0.08832114726497568,
+           0.0894537889784637,
+           0.08974239388873843,
+           0.0892396455690878,
+           0.08802185700903922,
+           0.08618745277720531,
+           0.08385483955504351,
+           0.08115971370398033,
+           0.07825186925523403,
+           0.07529158290338729,
+           0.07244566390506255,
+           0.06988326594282133,
+           0.0677715647749669,
+           0.06627140967701131,
+           0.06553305817683372,
+           0.06569210234650373,
+           0.06686569096096777,
+           0.06914914525655566,
+           0.07261305697536238,
+           0.07730094608159611,
+           0.08322754225605897,
+           0.09037773933795627,
+           0.09870625565398747,
+           0.10813801605081041,
+           0.11856925384920054,
+           0.129869313299926,
+           0.14188311587784216,
+           0.1544342373284662,
+           0.16732852718738217,
+           0.18035818890483193,
+           0.1933062270644337,
+           0.2059511587775218,
+           0.21807187939990502,
+           0.22945256843222886,
+           0.23988751993999763,
+           0.24918578310835648,
+           0.2571755026047414,
+           0.26370785516596607,
+           0.2686604880956194,
+           0.271940376930977,
+           0.2734860331374045,
+           0.2732690079838433,
+           0.271294655374975,
+           0.26760213396072374,
+           0.26226364688569465,
+           0.2553829356413135,
+           0.24709306220155217,
+           0.23755353052812833,
+           0.22694681421163754,
+           0.21547437108988046,
+           0.20335223781156833,
+           0.19080630719829558,
+           0.17806739866070323,
+           0.16536623666754632,
+           0.15292845423548934,
+           0.14096973755747222,
+           0.1296912242420083,
+           0.11927526128687614,
+           0.10988162001653132,
+           0.10164425399359808,
+           0.09466867264815632,
+           0.08902998838120595,
+           0.08477167855948545,
+           0.08190508652917407,
+           0.08040966796011381,
+           0.08023397092649806,
+           0.08129732057242542,
+           0.08349216242994133,
+           0.08668700286194779,
+           0.09072987107147157,
+           0.09545221499182854,
+           0.10067313344119996,
+           0.10620383942730978,
+           0.11185224460001429,
+           0.11742755268362316,
+           0.1227447503211359,
+           0.12762888710528147,
+           0.1319190425644965,
+           0.1354718863585624,
+           0.13816474869993395,
+           0.13989813077831442,
+           0.14059759940426736,
+           0.1402150258381929,
+           0.13872914543766127,
+           0.13614543192082393,
+           0.132495297276886,
+           0.1278346452261377,
+           0.12224182222148752,
+           0.11581502489088191,
+           0.10866923617585385,
+           0.10093277389564712,
+           0.09274354477652215,
+           0.08424510390424804,
+           0.07558262391701162,
+           0.06689887995297909,
+           0.05833035536542066,
+           0.05000356955023734,
+           0.0420317229943782,
+           0.0345117460118316,
+           0.027521826809620998,
+           0.02111948179714435,
+           0.015340216743472723,
+           0.010196811863458522,
+           0.005679247569588644,
+           0.0017552708776610532,
+           -0.0016284142742737985,
+           -0.004544365818237665,
+           -0.007082079910691059,
+           -0.009345187476857435,
+           -0.011448246141126954,
+           -0.01351321337963438,
+           -0.0156656951721007,
+           -0.01803107045665115,
+           -0.020730595148937807,
+           -0.023877590285514075,
+           -0.02757381696799161,
+           -0.031906136263540996,
+           -0.03694354516973753,
+           -0.04273467035227884,
+           -0.0493057898467709,
+           -0.05665943956823648,
+           -0.06477364662827773,
+           -0.0736018154920528,
+           -0.08307327631634591,
+           -0.09309448781574498,
+           -0.10355087013435015,
+           -0.1143092268812238,
+           -0.12522070013158262,
+           -0.13612418819188526,
+           -0.14685014363166532,
+           -0.15722465881238523,
+           -0.16707373815798654,
+           -0.17622765092077286,
+           -0.18452525534561692,
+           -0.19181818500534975,
+           -0.19797479068312213,
+           -0.20288373645791552,
+           -0.20645715648482507,
+           -0.20863328916597754,
+           -0.20937851773537616,
+           -0.20868876043265217,
+           -0.20659016907174624,
+           -0.2031391115385459,
+           -0.19842143116601627,
+           -0.19255099360801153,
+           -0.18566754932804225,
+           -0.1779339567045687,
+           -0.1695328266118106,
+           -0.1606626637710504,
+           -0.15153359282276285,
+           -0.14236276762856973,
+           -0.13336957050909812,
+           -0.12477071375214048,
+           -0.11677535864067819,
+           -0.10958036737463274,
+           -0.10336580058429766,
+           -0.09829076771685982,
+           -0.0944897295471721,
+           -0.09206934161127207,
+           -0.0911059147370625,
+           -0.09164355435555044,
+           -0.09369302426873788,
+           -0.097231363414718,
+           -0.10220226632280979,
+           -0.10851721982540924,
+           -0.11605737062946207,
+           -0.12467608098609019,
+           -0.1342021133544399,
+           -0.14444337003277408,
+           -0.15519110058910904,
+           -0.16622447888443748,
+           -0.17731544281155026,
+           -0.1882336837813067,
+           -0.19875166962235505,
+           -0.20864958399947306,
+           -0.21772006771074726,
+           -0.22577265223682377,
+           -0.23263778356082337,
+           -0.23817034436538242,
+           -0.24225259499411617,
+           -0.2447964677355522,
+           -0.24574516469929142,
+           -0.2450740264205098,
+           -0.2427906559357976,
+           -0.2389343009891017,
+           -0.23357451481265046,
+           -0.22680913314955045,
+           -0.21876162142228273,
+           -0.20957786080957488,
+           -0.19942245511277182,
+           -0.18847465135511346,
+           -0.1769239757978255,
+           -0.16496569326796798,
+           -0.1527962012298029,
+           -0.1406084708156153,
+           -0.12858764505316636,
+           -0.11690689984341261,
+           -0.10572366597866102,
+           -0.09517630083648745,
+           -0.08538128658582465,
+           -0.07643101809860149,
+           -0.06839222861823807,
+           -0.0613050849766126,
+           -0.055182967182244316,
+           -0.050012929949515034,
+           -0.04575682663298305,
+           -0.04235305949891153,
+           -0.03971890471941462,
+           -0.03775334629908093,
+           -0.036340340690485924,
+           -0.03535242343083541,
+           -0.03465456099292392,
+           -0.03410814538783635,
+           -0.03357502601999827,
+           -0.032921472947089865,
+           -0.032021968040233995,
+           -0.03076272550851114,
+           -0.029044850715189332,
+           -0.026787055977543005,
+           -0.0239278638566812,
+           -0.020427242006047116,
+           -0.016267628611204874,
+           -0.01145432343824817,
+           -0.006015236107340801,
+           -5.852348480925823e-17
+          ],
+          [
+           0,
+           0.0076228005374259535,
+           0.01567161206839065,
+           0.02402043836380985,
+           0.032530978654174106,
+           0.041056675986922454,
+           0.049447014575838937,
+           0.05755195121816289,
+           0.06522636213370367,
+           0.07233438590059955,
+           0.07875354554460492,
+           0.08437853822596651,
+           0.08912458922735338,
+           0.09293027787279433,
+           0.09575975632864886,
+           0.09760429762022188,
+           0.09848312625637952,
+           0.09844350316140826,
+           0.09756005570836791,
+           0.0959333630507883,
+           0.09368782617070928,
+           0.09096887061543679,
+           0.08793954731350363,
+           0.08477661270031689,
+           0.08166618324264976,
+           0.07879907097410906,
+           0.07636591554430411,
+           0.07455223431118257,
+           0.07353351500846968,
+           0.07347047541309686,
+           0.07450461121309374,
+           0.07675414700449298,
+           0.08031049617232483,
+           0.08523532355427228,
+           0.09155829053179586,
+           0.09927554588854427,
+           0.10834900781740481,
+           0.11870646328533864,
+           0.13024249104999422,
+           0.14282019445427757,
+           0.15627371020219807,
+           0.17041144013402545,
+           0.18501993504653805,
+           0.19986834329136574,
+           0.21471332263749726,
+           0.22930430205916075,
+           0.24338897100461715,
+           0.25671886754563167,
+           0.26905493375993206,
+           0.280172906842031,
+           0.2898684177752099,
+           0.2979616758545459,
+           0.3043016267761642,
+           0.3087694841768256,
+           0.31128154912834477,
+           0.3117912488104719,
+           0.3102903439992369,
+           0.3068092746689011,
+           0.30141663343718694,
+           0.29421777728873355,
+           0.28535260848715216,
+           0.27499257533336635,
+           0.26333696196654927,
+           0.25060855328275944,
+           0.23704877585480127,
+           0.2229124281149722,
+           0.20846212270986753,
+           0.19396257061979102,
+           0.17967484019375074,
+           0.1658507246001999,
+           0.1527273483279739,
+           0.14052213736430524,
+           0.12942826867734328,
+           0.1196107028623364,
+           0.11120288956428308,
+           0.10430421891655658,
+           0.09897827413761205,
+           0.09525192105103232,
+           0.09311525011325428,
+           0.09252236604278784,
+           0.0933929998458707,
+           0.09561489842203237,
+           0.09904692848697562,
+           0.10352281471799532,
+           0.10885541721677726,
+           0.11484144095321981,
+           0.12126646009994109,
+           0.127910133321802,
+           0.13455148230730013,
+           0.14097410520219006,
+           0.14697119913528756,
+           0.15235027163919854,
+           0.15693742931566862,
+           0.1605811433550573,
+           0.16315540520408914,
+           0.16456220143804234,
+           0.16473325433469072,
+           0.16363099332861103,
+           0.16124874197708405,
+           0.15761012480582515,
+           0.15276771793124294,
+           0.14680098618920437,
+           0.1398135671701336,
+           0.13192997862844216,
+           0.12329183980345147,
+           0.11405370891252185,
+           0.10437864816777699,
+           0.0944336339047233,
+           0.08438493264521282,
+           0.07439356407499848,
+           0.06461096900129208,
+           0.05517499444896553,
+           0.04620629931102282,
+           0.03780527261640018,
+           0.03004954280794504,
+           0.022992140785406446,
+           0.016660362261384173,
+           0.011055356640399696,
+           0.006152450628672013,
+           0.0019021955972531633,
+           -0.0017678911593396786,
+           -0.004950939224112566,
+           -0.007757756728390502,
+           -0.010313360887953623,
+           -0.0127531005302837,
+           -0.015218474480203312,
+           -0.017852757750522388,
+           -0.02079655269502545,
+           -0.02418338448901231,
+           -0.028135459449008225,
+           -0.03275970080665835,
+           -0.03814416970733442,
+           -0.04435496958106339,
+           -0.0514337198716068,
+           -0.05939567071260228,
+           -0.06822851386796949,
+           -0.07789192751523383,
+           -0.08831787369044333,
+           -0.09941164790370854,
+           -0.11105366106137086,
+           -0.12310191488312092,
+           -0.13539511395897133,
+           -0.14775634090889875,
+           -0.15999720621111937,
+           -0.17192237153329812,
+           -0.18333433516108846,
+           -0.19403836063518853,
+           -0.20384742517810073,
+           -0.21258706303830102,
+           -0.22009998054919222,
+           -0.22625032446199903,
+           -0.23092749285740974,
+           -0.23404938848748505,
+           -0.2355650274942262,
+           -0.23545643177734435,
+           -0.23373975046815645,
+           -0.23046557458911215,
+           -0.2257184285825598,
+           -0.21961544249594955,
+           -0.21230422871826557,
+           -0.203960006777412,
+           -0.1947820383450199,
+           -0.184989451791294,
+           -0.17481655096032694,
+           -0.16450771591333063,
+           -0.15431201388572738,
+           -0.14447764635927077,
+           -0.13524636276720706,
+           -0.1268479728081463,
+           -0.11949508759973165,
+           -0.1133782149918222,
+           -0.10866132639419833,
+           -0.10547800164433366,
+           -0.10392824500571074,
+           -0.10407604966996005,
+           -0.10594777051649731,
+           -0.10953134578817188,
+           -0.1147763882340375,
+           -0.12159514563924428,
+           -0.1298643100088884,
+           -0.13942763449992376,
+           -0.15009929799385693,
+           -0.1616679394402437,
+           -0.17390126820909632,
+           -0.18655114305569098,
+           -0.19935900125500366,
+           -0.21206151127290165,
+           -0.22439631720501974,
+           -0.23610774125488376,
+           -0.24695231178545615,
+           -0.25670398892898405,
+           -0.26515896726708904,
+           -0.2721399455092431,
+           -0.27749976614547567,
+           -0.2811243434064362,
+           -0.28293481515257746,
+           -0.28288887310921157,
+           -0.2809812457040684,
+           -0.27724332816231123,
+           -0.27174197497135594,
+           -0.2645774898442412,
+           -0.2558808673973194,
+           -0.2458103584510227,
+           -0.2345474467318818,
+           -0.22229233841599352,
+           -0.20925907708004254,
+           -0.19567040495025798,
+           -0.18175249666637075,
+           -0.1677296939852353,
+           -0.15381936889305717,
+           -0.1402270385100992,
+           -0.12714184806868956,
+           -0.11473252831005089,
+           -0.10314392113341803,
+           -0.09249415256081339,
+           -0.08287251542675313,
+           -0.07433810608400535,
+           -0.06691924028959743,
+           -0.06061365377898495,
+           -0.055389473342121034,
+           -0.05118692497437066,
+           -0.04792072736679116,
+           -0.04548310207887245,
+           -0.04374731662149601,
+           -0.042571663741758116,
+           -0.04180376976232937,
+           -0.04128511714104097,
+           -0.04085566166692754,
+           -0.0403584230086288,
+           -0.03964392871491073,
+           -0.03857439619275049,
+           -0.037027544537359056,
+           -0.03489993816890584,
+           -0.032109776782420274,
+           -0.028599060818500034,
+           -0.024335078137481883,
+           -0.01931117540885742,
+           -0.013546796457471923,
+           -0.007086788962680756,
+           -6.867870746608346e-17
+          ],
+          [
+           0,
+           0.008745792019826004,
+           0.01790828145055134,
+           0.02733837238351718,
+           0.03687555697048651,
+           0.046352635234073465,
+           0.05560064238359962,
+           0.06445385165505613,
+           0.07275471847131758,
+           0.08035863293948364,
+           0.08713835233851674,
+           0.09298799318843234,
+           0.09782647353516673,
+           0.10160030995751135,
+           0.1042856901572793,
+           0.10588976042138666,
+           0.10645108728238094,
+           0.10603927384858276,
+           0.10475373299434249,
+           0.10272164134758946,
+           0.10009511923694062,
+           0.09704770192734337,
+           0.09377018607034937,
+           0.0904659518498389,
+           0.08734587539377575,
+           0.08462295728568431,
+           0.08250680115429318,
+           0.08119808113184675,
+           0.08088313831941055,
+           0.08172884423577668,
+           0.08387786359747147,
+           0.0874444398095792,
+           0.09251081445281692,
+           0.0991243771220301,
+           0.10729562456676116,
+           0.11699698862984086,
+           0.12816257145102958,
+           0.1406888043157191,
+           0.15443602392712563,
+           0.1692309373217621,
+           0.18486992468994198,
+           0.20112310854964585,
+           0.21773909857014256,
+           0.23445030432818978,
+           0.2509786938294653,
+           0.267041864103762,
+           0.2823592818755358,
+           0.2966585474340629,
+           0.3096815335080384,
+           0.3211902532288954,
+           0.33097231709793284,
+           0.338845848119602,
+           0.34466373670799566,
+           0.3483171323178132,
+           0.3497380866254462,
+           0.34890128305839885,
+           0.3458248090581919,
+           0.3405699501393265,
+           0.33324000802376774,
+           0.32397816832210574,
+           0.3129644658346956,
+           0.30041191700847386,
+           0.286561908885283,
+           0.271678951533496,
+           0.25604491603698476,
+           0.23995289225750566,
+           0.22370080949386417,
+           0.2075849686184557,
+           0.19189363614822785,
+           0.17690084895967867,
+           0.16286057303190415,
+           0.15000135083118393,
+           0.13852155995269566,
+           0.12858539070604996,
+           0.12031963283936467,
+           0.11381134197187714,
+           0.10910643502972481,
+           0.10620924157549287,
+           0.10508301493835352,
+           0.10565138405048291,
+           0.10780070443884678,
+           0.1113832454570114,
+           0.11622113108919557,
+           0.12211093399758444,
+           0.12882880734088215,
+           0.1361360266312695,
+           0.14378480481070766,
+           0.15152423802937523,
+           0.15910623742842828,
+           0.16629130360858038,
+           0.17285400535956388,
+           0.1785880325009155,
+           0.18331070412594605,
+           0.1868668278545286,
+           0.1891318225223109,
+           0.19001403563860553,
+           0.18945620745633387,
+           0.1874360550999774,
+           0.18396597235056478,
+           0.1790918628368752,
+           0.1728911459771494,
+           0.16546999551860425,
+           0.15695988942426709,
+           0.14751356669042276,
+           0.13730050102823418,
+           0.12650201285770096,
+           0.11530614946045782,
+           0.1039024682178781,
+           0.09247685950389227,
+           0.08120654397545846,
+           0.07025537376240816,
+           0.05976955854260666,
+           0.049873925920172195,
+           0.04066881120238274,
+           0.03222765496211344,
+           0.024595368104006032,
+           0.017787503999708486,
+           0.011790256132903713,
+           0.0065612781349976635,
+           0.0020313016443008333,
+           -0.0018934933707801976,
+           -0.005328420793497546,
+           -0.008406625943940713,
+           -0.011274917260996407,
+           -0.014089204033868201,
+           -0.017009662522956704,
+           -0.02019576005992845,
+           -0.023801270644231227,
+           -0.027969416056197113,
+           -0.032828263569492935,
+           -0.03848650503899439,
+           -0.04502973262003814,
+           -0.052517313878388525,
+           -0.06097995388925203,
+           -0.07041801447778326,
+           -0.08080064146022291,
+           -0.09206573008856779,
+           -0.10412073740194046,
+           -0.11684432838602442,
+           -0.130088821287912,
+           -0.14368337667204145,
+           -0.15743785535925714,
+           -0.17114725275891182,
+           -0.18459660173250494,
+           -0.1975662234099341,
+           -0.20983719564377956,
+           -0.22119690228698774,
+           -0.23144452338831503,
+           -0.24039632680672315,
+           -0.24789062565210893,
+           -0.25379227327967385,
+           -0.25799657812790894,
+           -0.26043253424346435,
+           -0.2610652795529832,
+           -0.2598977124281802,
+           -0.2569712173946289,
+           -0.25236547245931196,
+           -0.24619733294550264,
+           -0.23861880937376967,
+           -0.2298141792554974,
+           -0.21999629411774013,
+           -0.20940216312340795,
+           -0.19828791279026128,
+           -0.18692323809359965,
+           -0.1755854732658434,
+           -0.164553420553449,
+           -0.1541010818052161,
+           -0.14449144087518018,
+           -0.13597044434293248,
+           -0.12876132398775378,
+           -0.12305939689177765,
+           -0.11902746816907382,
+           -0.11679194738128718,
+           -0.11643977304094828,
+           -0.11801622062271666,
+           -0.1215236486598867,
+           -0.12692121530392528,
+           -0.13412557470770373,
+           -0.14301253931801475,
+           -0.15341967119616548,
+           -0.16514974338592475,
+           -0.17797499165386685,
+           -0.19164205814200463,
+           -0.20587751205359564,
+           -0.22039381883949116,
+           -0.23489561879582044,
+           -0.24908616877992362,
+           -0.26267379707380145,
+           -0.275378221360102,
+           -0.2869365833235496,
+           -0.2971090604608812,
+           -0.3056839260989759,
+           -0.3124819421260634,
+           -0.31735998520155506,
+           -0.32021382582580094,
+           -0.32098000016425715,
+           -0.3196367364275918,
+           -0.3162039203730522,
+           -0.310742107555555,
+           -0.30335061275559755,
+           -0.29416472898872914,
+           -0.28335214912258216,
+           -0.27110868189127285,
+           -0.25765337054886633,
+           -0.24322313614682742,
+           -0.2280670781257478,
+           -0.21244057232545863,
+           -0.1965993104678834,
+           -0.18079342556749803,
+           -0.16526184457674453,
+           -0.1502270029674719,
+           -0.13589004605917432,
+           -0.12242662898595658,
+           -0.10998341157679278,
+           -0.0986753265037712,
+           -0.08858367928295734,
+           -0.07975511758943842,
+           -0.07220148540161843,
+           -0.06590055526886487,
+           -0.06079761005566122,
+           -0.05680782440074219,
+           -0.0538193763658368,
+           -0.05169720182527513,
+           -0.050287288507568584,
+           -0.0494213936279567,
+           -0.04892205906419013,
+           -0.04860779126856752,
+           -0.048298269738359594,
+           -0.047819447959954145,
+           -0.04700841428817892,
+           -0.045717887123549295,
+           -0.04382022882490153,
+           -0.04121087578187019,
+           -0.03781109763700879,
+           -0.033570016392761526,
+           -0.0284658356113176,
+           -0.02250625062001513,
+           -0.01572803204524861,
+           -0.008195796570306385,
+           -7.911206545913124e-17
+          ],
+          [
+           0,
+           0.009881961576567316,
+           0.02015349359512294,
+           0.03064214572541813,
+           0.041165593656206124,
+           0.05153702230488309,
+           0.06157065703093032,
+           0.07108729446831889,
+           0.07991968432358522,
+           0.08791761703475012,
+           0.09495257946520541,
+           0.10092185163566304,
+           0.1057519316062308,
+           0.10940119265677538,
+           0.111861696450047,
+           0.11316010740823702,
+           0.11335767654823033,
+           0.11254928692462633,
+           0.11086157702029802,
+           0.10845018229133196,
+           0.10549615801329283,
+           0.1022016680077397,
+           0.09878504320743815,
+           0.09547533085184974,
+           0.09250646896015659,
+           0.09011123124991219,
+           0.08851509458071069,
+           0.08793018411904813,
+           0.08854945065221592,
+           0.09054122983186094,
+           0.09404432470479772,
+           0.09916374088718395,
+           0.10596718844528782,
+           0.11448244633141566,
+           0.124695664530283,
+           0.13655065640500325,
+           0.14994920964888536,
+           0.1647524193417717,
+           0.18078302149188755,
+           0.1978286807368737,
+           0.21564616219281216,
+           0.2339662953656093,
+           0.2524996181245064,
+           0.27094257147992856,
+           0.28898410173993727,
+           0.3063125158984349,
+           0.32262242910684064,
+           0.3376216399809297,
+           0.35103777038184647,
+           0.362624511172907,
+           0.37216732418182424,
+           0.37948846298635175,
+           0.3844511908947401,
+           0.3869630932324728,
+           0.3869784023213566,
+           0.3844992768313341,
+           0.37957600193443225,
+           0.372306102292939,
+           0.36283238574768417,
+           0.3513399610085282,
+           0.3380522970685663,
+           0.3232264148714521,
+           0.3071473224021933,
+           0.29012182234324135,
+           0.2724718363024482,
+           0.2545274010162606,
+           0.23661949958409728,
+           0.2190728945135771,
+           0.20219912906280849,
+           0.1862898590652939,
+           0.17161066922327334,
+           0.15839551596002036,
+           0.14684192362458853,
+           0.13710704252068043,
+           0.12930465633536006,
+           0.12350320358650044,
+           0.11972485325332625,
+           0.11794564940137144,
+           0.11809671398200948,
+           0.12006647170376136,
+           0.12370383655462672,
+           0.1288222767937981,
+           0.13520465458008837,
+           0.14260871836314254,
+           0.1507731111667643,
+           0.15942374630044384,
+           0.16828039411981285,
+           0.17706331940245373,
+           0.1854998087998017,
+           0.1933304316586846,
+           0.20031488516997653,
+           0.20623728609505645,
+           0.21091078595210425,
+           0.21418140414058967,
+           0.2159309935978825,
+           0.21607927570954696,
+           0.2145849047786534,
+           0.21144554680851835,
+           0.20669698205669437,
+           0.20041126515985985,
+           0.19269400000396314,
+           0.1836808083414378,
+           0.17353309089725172,
+           0.16243319687091065,
+           0.15057913191052844,
+           0.1381789454616402,
+           0.12544494561572886,
+           0.11258789303027716,
+           0.09981132508722039,
+           0.08730615722018215,
+           0.07524570038912293,
+           0.06378122222324492,
+           0.05303816468609073,
+           0.04311311361783265,
+           0.03407159562647006,
+           0.025946756039143124,
+           0.018738948540797266,
+           0.012416243306468839,
+           0.006915836480074032,
+           0.0021463203741795374,
+           -0.002009248643094878,
+           -0.0056895683782931935,
+           -0.009050697570334209,
+           -0.012261169556210073,
+           -0.015496744154061846,
+           -0.018934938632098698,
+           -0.022749484577369975,
+           -0.02710485965769934,
+           -0.03215104162528494,
+           -0.03801862648001732,
+           -0.0448144436283414,
+           -0.0526177883654271,
+           -0.06147737638694081,
+           -0.07140910669294087,
+           -0.08239469864039954,
+           -0.09438124655013014,
+           -0.10728171174054112,
+           -0.12097634773726357,
+           -0.13531503030264125,
+           -0.15012044045114997,
+           -0.16519202636013738,
+           -0.18031064961439555,
+           -0.19524380305870445,
+           -0.20975127213863357,
+           -0.2235910993820011,
+           -0.2365257029285118,
+           -0.24832799498382752,
+           -0.25878734489484984,
+           -0.26771523425771226,
+           -0.2749504580240314,
+           -0.28036373581372503,
+           -0.2838616113311943,
+           -0.2853895345865511,
+           -0.2849340411372134,
+           -0.28252396431164456,
+           -0.27823063982375246,
+           -0.2721670867575333,
+           -0.2644861739917982,
+           -0.25537780612484723,
+           -0.24506518723048168,
+           -0.2338002437279129,
+           -0.22185830870847295,
+           -0.20953218870659643,
+           -0.19712574966497476,
+           -0.18494717132800645,
+           -0.17330202818758536,
+           -0.16248636017289855,
+           -0.15277989738703945,
+           -0.14443960031070688,
+           -0.13769367007830924,
+           -0.13273617284228617,
+           -0.1297224081284,
+           -0.12876513378598345,
+           -0.1299317400691821,
+           -0.13324244303310573,
+           -0.13866954333402806,
+           -0.14613777127020028,
+           -0.15552571310316526,
+           -0.16666828798622105,
+           -0.17936021982275385,
+           -0.19336042469142065,
+           -0.20839721268441802,
+           -0.22417418363999742,
+           -0.24037667978222793,
+           -0.25667864511035776,
+           -0.2727497318265973,
+           -0.2882624883859878,
+           -0.3028994620320872,
+           -0.3163600509867877,
+           -0.32836694773248304,
+           -0.3386720249036363,
+           -0.3470615289432294,
+           -0.3533604635410655,
+           -0.35743606454041577,
+           -0.3592002899936194,
+           -0.3586112728260055,
+           -0.3556737085479929,
+           -0.35043817602571725,
+           -0.34299941485575974,
+           -0.33349360776601517,
+           -0.3220947400761646,
+           -0.3090101300233721,
+           -0.294475243163759,
+           -0.27874792062916354,
+           -0.2621021643535391,
+           -0.24482163216647998,
+           -0.22719300165329565,
+           -0.20949936376600028,
+           -0.1920138052987268,
+           -0.1749933335734052,
+           -0.15867328717208182,
+           -0.14326236354836488,
+           -0.12893837818529952,
+           -0.11584485105129494,
+           -0.10408849491743377,
+           -0.09373765717185732,
+           -0.08482174267512786,
+           -0.07733162054724534,
+           -0.07122099317774919,
+           -0.06640868181770428,
+           -0.0627817604409862,
+           -0.06019944871414166,
+           -0.05849765640444377,
+           -0.05749405584042972,
+           -0.05699354650331767,
+           -0.056793966776142624,
+           -0.05669190252738665,
+           -0.05648844068146248,
+           -0.055994718257739724,
+           -0.05503712347441543,
+           -0.05346201525012615,
+           -0.051139840540901746,
+           -0.04796854508481875,
+           -0.04387619187780613,
+           -0.038822722592598,
+           -0.032800819646696115,
+           -0.025835850152490375,
+           -0.01798489694597926,
+           -0.009334905681965737,
+           -8.974889810989014e-17
+          ],
+          [
+           0,
+           0.011022352745888276,
+           0.022388864193017933,
+           0.033903951249642,
+           0.04536434496322424,
+           0.056565114366306506,
+           0.06730576103157976,
+           0.07739622059178955,
+           0.08666260960566383,
+           0.09495256242965958,
+           0.1021400130315736,
+           0.10812929069973597,
+           0.11285841600993697,
+           0.11630150377506579,
+           0.11847020250847588,
+           0.11941412460807103,
+           0.11922024739302234,
+           0.11801129164559959,
+           0.11594311075766123,
+           0.11320114928650522,
+           0.10999605403721513,
+           0.10655854309133278,
+           0.10313365792695457,
+           0.09997454041903969,
+           0.09733588964291782,
+           0.09546726268779046,
+           0.09460638887517828,
+           0.0949726677264181,
+           0.09676101769571027,
+           0.10013623514983055,
+           0.10522801150656169,
+           0.1121267411162571,
+           0.12088023375407361,
+           0.13149142393889401,
+           0.14391714523742916,
+           0.15806801183811178,
+           0.1738094226252904,
+           0.19096367541678033,
+           0.2093131516281372,
+           0.22860450507355948,
+           0.24855376356512898,
+           0.2688522290523341,
+           0.2891730418244017,
+           0.30917825728522336,
+           0.3285262704327845,
+           0.34687941377135056,
+           0.36391154919718227,
+           0.3793154735657779,
+           0.3928099612020716,
+           0.40414627447826945,
+           0.4131139855745113,
+           0.4195459683710426,
+           0.4233224387179075,
+           0.4243739436246328,
+           0.42268322466903974,
+           0.418285907541296,
+           0.4112699974704565,
+           0.40177418864950415,
+           0.38998502399105783,
+           0.37613296892242404,
+           0.36048748879871745,
+           0.3433512432460557,
+           0.32505353176517976,
+           0.30594314271737316,
+           0.286380771946329,
+           0.26673118741824703,
+           0.247355322142596,
+           0.22860247912630988,
+           0.2108028291809089,
+           0.19426037511960312,
+           0.17924654443078525,
+           0.16599455717828776,
+           0.15469469703518798,
+           0.14549059147014265,
+           0.13847658271075167,
+           0.13369624480564574,
+           0.13114207454029375,
+           0.1307563558055503,
+           0.13243316896083948,
+           0.13602148946029552,
+           0.14132929418455134,
+           0.1481285701709151,
+           0.15616109933603073,
+           0.1651448748471991,
+           0.17478099045199824,
+           0.1847608336621278,
+           0.1947734074503662,
+           0.20451260319955394,
+           0.21368425007323727,
+           0.22201277268514405,
+           0.22924729974970084,
+           0.23516708101809747,
+           0.23958608786994978,
+           0.24235669398098197,
+           0.24337235599103646,
+           0.2425692394631927,
+           0.23992676201805946,
+           0.2354670526826004,
+           0.22925335353292087,
+           0.22138741596244643,
+           0.21200596871913444,
+           0.20127635761335239,
+           0.18939147693996128,
+           0.17656412968851942,
+           0.16302096711764696,
+           0.14899616791573495,
+           0.13472502272963516,
+           0.12043759118768044,
+           0.1063525956511039,
+           0.09267170888246425,
+           0.07957438180892634,
+           0.06721334286912335,
+           0.055710882443691025,
+           0.045156015042587434,
+           0.03560258878881881,
+           0.027068386887372193,
+           0.019535239831745682,
+           0.012950140736843883,
+           0.00722733006479467,
+           0.0022512907914438974,
+           -0.002119428615236148,
+           -0.006047667568119219,
+           -0.009712506095611433,
+           -0.013303655630238317,
+           -0.017015538662142643,
+           -0.021041216316217914,
+           -0.025566327077648266,
+           -0.030763199867254083,
+           -0.0367853004530339,
+           -0.0437621618810319,
+           -0.051794937423617585,
+           -0.06095269878081484,
+           -0.07126958332521541,
+           -0.08274287252851943,
+           -0.09533205989177414,
+           -0.10895894132096144,
+           -0.12350873458383752,
+           -0.13883220791616124,
+           -0.15474877168655604,
+           -0.17105046194088797,
+           -0.1875067212651339,
+           -0.2038698613244986,
+           -0.21988107319357575,
+           -0.23527683665519875,
+           -0.249795568399878,
+           -0.2631843417973975,
+           -0.2752055078322031,
+           -0.28564304798544865,
+           -0.29430849529342695,
+           -0.30104626939259904,
+           -0.30573828485034443,
+           -0.3083077091546332,
+           -0.30872176698184156,
+           -0.30699351028676675,
+           -0.3031824988016641,
+           -0.29739436207703746,
+           -0.28977924159242474,
+           -0.2805291390344734,
+           -0.269874223900258,
+           -0.25807817946524403,
+           -0.24543269021442377,
+           -0.2322511954725675,
+           -0.21886205264440953,
+           -0.20560126871918769,
+           -0.192804970121364,
+           -0.18080178830892382,
+           -0.16990534154156361,
+           -0.16040699187808038,
+           -0.15256905073776916,
+           -0.14661859640458902,
+           -0.14274205289931446,
+           -0.14108066202662164,
+           -0.141726959544278,
+           -0.14472234280365529,
+           -0.15005579144586095,
+           -0.15766377543080165,
+           -0.16743135649085222,
+           -0.17919446072199635,
+           -0.19274327214409587,
+           -0.20782667035734692,
+           -0.2241576105445739,
+           -0.24141932162487362,
+           -0.25927217890002063,
+           -0.27736109152474236,
+           -0.2953232329649749,
+           -0.31279593457964283,
+           -0.32942455876540655,
+           -0.3448701688279823,
+           -0.35881681786764663,
+           -0.370978288362362,
+           -0.38110412756687384,
+           -0.38898484098892133,
+           -0.39445612663236346,
+           -0.3974020559096043,
+           -0.397757132552527,
+           -0.3955071878688311,
+           -0.39068909863770157,
+           -0.3833893421316114,
+           -0.3737414305012447,
+           -0.3619222933913699,
+           -0.34814770251897975,
+           -0.3326668544375407,
+           -0.3157562472886245,
+           -0.29771300353302366,
+           -0.2788478030704272,
+           -0.2594775995063415,
+           -0.23991829641449264,
+           -0.22047756018514142,
+           -0.20144794146480274,
+           -0.1831004684078433,
+           -0.1656788622057566,
+           -0.14939450896383163,
+           -0.13442230237490332,
+           -0.12089744929239155,
+           -0.10891330579269902,
+           -0.09852028525557632,
+           -0.08972585303260887,
+           -0.08249559509158955,
+           -0.07675532129541218,
+           -0.07239413836260263,
+           -0.06926840369769847,
+           -0.06720644976342983,
+           -0.06601395002330783,
+           -0.06547978217029388,
+           -0.06538223274808641,
+           -0.06549537964630797,
+           -0.06559548548940204,
+           -0.06546723571676574,
+           -0.06490966013762256,
+           -0.06374158580211788,
+           -0.061806481921916824,
+           -0.05897657396524767,
+           -0.055156123521542214,
+           -0.05028379258148486,
+           -0.04433403494713824,
+           -0.03731748296146922,
+           -0.029280323979972243,
+           -0.02030268733357287,
+           -0.01049608828421838,
+           -1.0050939830742653e-16
+          ],
+          [
+           0,
+           0.012157710372977904,
+           0.024595700164894176,
+           0.03709595928976501,
+           0.04943562434013697,
+           0.0613936056205253,
+           0.07275719032157313,
+           0.08332844415768105,
+           0.09293023872749066,
+           0.10141174123563375,
+           0.10865321680175355,
+           0.11457001103895446,
+           0.1191156014708274,
+           0.12228363014951422,
+           0.12410885593870342,
+           0.12466699267800202,
+           0.1240734281494643,
+           0.12248084769894774,
+           0.12007581479341889,
+           0.11707438800086495,
+           0.11371687917213566,
+           0.110261880340729,
+           0.10697970645706985,
+           0.10414541703559857,
+           0.10203159170354383,
+           0.10090104218778649,
+           0.1009996462574297,
+           0.10254948746504794,
+           0.10574247822569989,
+           0.1107346329819254,
+           0.1176411431796537,
+           0.12653238688487528,
+           0.1374309835620165,
+           0.15030997935618656,
+           0.1650922207894639,
+           0.1816509457702148,
+           0.1998115909389109,
+           0.21935478437194983,
+           0.24002046327929058,
+           0.2615130282913968,
+           0.2835074199334278,
+           0.3056559795781717,
+           0.32759593713706925,
+           0.3489573514943211,
+           0.36937131762369,
+           0.3884782467599181,
+           0.4059360231249459,
+           0.4214278426163627,
+           0.43466954551711023,
+           0.4454162665300166,
+           0.4534682410135687,
+           0.45867562582499793,
+           0.46094221619400966,
+           0.46022796599981963,
+           0.4565502470773885,
+           0.4499838130504391,
+           0.4406594639531472,
+           0.42876143881093376,
+           0.4145235936509914,
+           0.3982244513668755,
+           0.38018123676305166,
+           0.3607430342989964,
+           0.3402832269486456,
+           0.31919139168060084,
+           0.29786483993159957,
+           0.2766999997776919,
+           0.2560838401028129,
+           0.23638553583737135,
+           0.21794856732259787,
+           0.20108343619939803,
+           0.18606116518660618,
+           0.17310773007300556,
+           0.16239954966840725,
+           0.15406013389573042,
+           0.1481579622853501,
+           0.14470563553895588,
+           0.1436603122870156,
+           0.14492541241822282,
+           0.14835353816152694,
+           0.1537505351874585,
+           0.16088058906874345,
+           0.16947222815397417,
+           0.17922508284964495,
+           0.18981723398203465,
+           0.2009129697352373,
+           0.21217076194618542,
+           0.22325126848236065,
+           0.23382516911833381,
+           0.2435806477313966,
+           0.2522303436060644,
+           0.25951760891151093,
+           0.2652219276284916,
+           0.2691633728899369,
+           0.27120600431405245,
+           0.27126013383109826,
+           0.2692834170598957,
+           0.2652807567634242,
+           0.2593030345693406,
+           0.25144471624274123,
+           0.24184040362231035,
+           0.23066043218790566,
+           0.21810563647885234,
+           0.20440142565537986,
+           0.18979132789879036,
+           0.17453017467982795,
+           0.1588771038925227,
+           0.143088564265412,
+           0.12741150225065037,
+           0.11207690679725246,
+           0.09729387719532925,
+           0.08324436480218818,
+           0.07007872130082199,
+           0.0579121646632947,
+           0.046822249745181316,
+           0.03684740404066776,
+           0.02798656125260971,
+           0.02019989668570936,
+           0.013410639780555064,
+           0.007507911098700029,
+           0.0023505044535716687,
+           -0.0022284896673291487,
+           -0.006416345105254077,
+           -0.01041478979504499,
+           -0.014433683536753178,
+           -0.01868445383556514,
+           -0.02337346632222216,
+           -0.028695508185618158,
+           -0.03482756038667451,
+           -0.04192302724244596,
+           -0.05010658045008327,
+           -0.05946975904959947,
+           -0.07006744759241791,
+           -0.08191533237205882,
+           -0.09498841054716751,
+           -0.1092205999749608,
+           -0.12450546925537893,
+           -0.14069807857678326,
+           -0.15761789318283012,
+           -0.1750527033747172,
+           -0.19276345863024053,
+           -0.21048989932965279,
+           -0.22795684834179447,
+           -0.24488100688539538,
+           -0.26097808509888876,
+           -0.27597008799075107,
+           -0.2895925721596919,
+           -0.3016016880168751,
+           -0.31178082624228004,
+           -0.31994669577970714,
+           -0.32595467362071273,
+           -0.3297032836384382,
+           -0.3311376823972976,
+           -0.33025205368129995,
+           -0.32709083987031407,
+           -0.3217487666024821,
+           -0.31436964669566864,
+           -0.305143979332648,
+           -0.2943053903010946,
+           -0.28212598788213306,
+           -0.26891073608475646,
+           -0.2549909716528651,
+           -0.24071721300933788,
+           -0.22645142750236247,
+           -0.21255893752442534,
+           -0.19940015592288782,
+           -0.18732234635857165,
+           -0.1766516047541765,
+           -0.16768525368342055,
+           -0.16068483257769642,
+           -0.15586985317856145,
+           -0.15341247206046651,
+           -0.15343321071046656,
+           -0.15599782909417495,
+           -0.1611154314535975,
+           -0.16873785393155205,
+           -0.17876035320694866,
+           -0.19102358439468212,
+           -0.20531682576605492,
+           -0.22138237812818448,
+           -0.2389210386878798,
+           -0.25759852359979,
+           -0.277052690784818,
+           -0.2969013955539735,
+           -0.31675079654884003,
+           -0.3362039188782167,
+           -0.3548692753489842,
+           -0.37236934550197964,
+           -0.38834871579722147,
+           -0.40248169265581835,
+           -0.41447921295127277,
+           -0.4240948936328117,
+           -0.43113008303755807,
+           -0.435437800593856,
+           -0.43692547844252955,
+           -0.43555644734877474,
+           -0.4313501394384472,
+           -0.4243810110310806,
+           -0.41477621940718984,
+           -0.40271211699374604,
+           -0.38840965445731906,
+           -0.3721288098788954,
+           -0.35416218392553667,
+           -0.3348279201831335,
+           -0.31446212510967697,
+           -0.293410973046023,
+           -0.2720226881244905,
+           -0.2506395966014703,
+           -0.22959044008172222,
+           -0.20918313238964562,
+           -0.18969813068165636,
+           -0.17138257509840885,
+           -0.1544453312421605,
+           -0.13905304654021672,
+           -0.1253273057057391,
+           -0.11334294268143638,
+           -0.1031275373466478,
+           -0.09466209561102663,
+           -0.08788288204739893,
+           -0.08268434566514442,
+           -0.0789230525017932,
+           -0.07642251408048266,
+           -0.07497877905198116,
+           -0.07436663704594892,
+           -0.07434626934394556,
+           -0.07467017080553856,
+           -0.07509016177140528,
+           -0.07536430756388955,
+           -0.07526356672099038,
+           -0.07457799713340478,
+           -0.07312236159222814,
+           -0.07074099057581373,
+           -0.06731177998731662,
+           -0.06274922448999184,
+           -0.057006412489780035,
+           -0.05007593603729554,
+           -0.04198969727216414,
+           -0.03281762179224826,
+           -0.022665317769504225,
+           -0.011670747032584479,
+           -1.1130967973816564e-16
+          ],
+          [
+           0,
+           0.013278607064410187,
+           0.02675525881357741,
+           0.040190708946473676,
+           0.053344318458996724,
+           0.06598123396369103,
+           0.07787943112028568,
+           0.08883643336284318,
+           0.09867552424388124,
+           0.10725128452660006,
+           0.11445430232260598,
+           0.1202149256636179,
+           0.12450595138172277,
+           0.12734417143798063,
+           0.12879072719714918,
+           0.12895025285711847,
+           0.12796882053049502,
+           0.1260307305522233,
+           0.1233542206649655,
+           0.12018619605081587,
+           0.11679610801443412,
+           0.11346913182047907,
+           0.11049881316649603,
+           0.10817936754251027,
+           0.10679782690634046,
+           0.1066262334191204,
+           0.10791408028986899,
+           0.11088119504733698,
+           0.1157112508936988,
+           0.12254607742327829,
+           0.1314809232536971,
+           0.14256080046950623,
+           0.15577801477089231,
+           0.17107095648874418,
+           0.18832419687774563,
+           0.2073699020885581,
+           0.2279905447389351,
+           0.24992286085564966,
+           0.2728629689418101,
+           0.2964725388086727,
+           0.3203858713232105,
+           0.3442177270247772,
+           0.36757172223860896,
+           0.3900490963485359,
+           0.4112576436673243,
+           0.43082059812556045,
+           0.44838525893087555,
+           0.46363115044403924,
+           0.4762775196652315,
+           0.4860899896863711,
+           0.49288620688856616,
+           0.4965403430822341,
+           0.4969863406370078,
+           0.49421981828000483,
+           0.48829858693605804,
+           0.4793417579723517,
+           0.4675274596902568,
+           0.4530892110639454,
+           0.43631103375073843,
+           0.41752141351144856,
+           0.39708624964589534,
+           0.37540095519947053,
+           0.35288189094220296,
+           0.32995733196880944,
+           0.3070581768308874,
+           0.2846086151219809,
+           0.26301697024774195,
+           0.24266692970905332,
+           0.22390936571572237,
+           0.20705493456705956,
+           0.19236762433733962,
+           0.18005939745313804,
+           0.17028604830915256,
+           0.1631443667875461,
+           0.15867066714033504,
+           0.15684070893336807,
+           0.1575710034348172,
+           0.1607214657742143,
+           0.16609934120583889,
+           0.17346430366129942,
+           0.18253459720258097,
+           0.19299406665633576,
+           0.20449990320955588,
+           0.2166909145675754,
+           0.2291961178019084,
+           0.24164344651546815,
+           0.2536683625708764,
+           0.2649221663820631,
+           0.27507980855164377,
+           0.2838470192141867,
+           0.2909665894681319,
+           0.29622366128729183,
+           0.29944990773955465,
+           0.3005265135649824,
+           0.2993858964697055,
+           0.2960121411176925,
+           0.2904401499603998,
+           0.282753546933829,
+           0.2730814008815145,
+           0.26159386456645406,
+           0.24849685159812673,
+           0.2340258968705251,
+           0.21843936561263597,
+           0.2020111914181577,
+           0.18502333427743983,
+           0.1677581554285709,
+           0.15049090664512044,
+           0.13348252737934413,
+           0.11697293410095592,
+           0.10117497245406543,
+           0.08626918485573881,
+           0.07239952434277626,
+           0.05967012039773911,
+           0.04814317479109372,
+           0.037838035868560695,
+           0.028731468943626284,
+           0.020759109305361425,
+           0.013818053610618188,
+           0.007770515875867984,
+           0.002448446665419817,
+           -0.0023410109116429032,
+           -0.006809376501579402,
+           -0.011180165111137204,
+           -0.01568187665861471,
+           -0.020540831129636877,
+           -0.025974042169904593,
+           -0.03218232116881394,
+           -0.039343798175033536,
+           -0.04760803547960839,
+           -0.057090894666480665,
+           -0.06787029874135879,
+           -0.07998300808936355,
+           -0.0934225030544828,
+           -0.10813803753274377,
+           -0.12403489784153726,
+           -0.14097587002945625,
+           -0.15878388750940575,
+           -0.17724580022340594,
+           -0.19611717725718794,
+           -0.21512802765954142,
+           -0.2339892998764602,
+           -0.2523999993050312,
+           -0.2700547465430618,
+           -0.2866515863955294,
+           -0.3018998499260872,
+           -0.3155278690211807,
+           -0.3272903451524593,
+           -0.3369751812409151,
+           -0.3444095975795174,
+           -0.34946536937477574,
+           -0.35206304422238877,
+           -0.3521750222342179,
+           -0.3498274089875665,
+           -0.34510058130017224,
+           -0.33812843731172854,
+           -0.3290963346988809,
+           -0.31823775326589426,
+           -0.3058297498344452,
+           -0.29218730351649386,
+           -0.27765667734313887,
+           -0.26260794714352126,
+           -0.24742686989695134,
+           -0.23250628098162449,
+           -0.21823722237864315,
+           -0.20500001163651602,
+           -0.19315546405462936,
+           -0.183036478025455,
+           -0.1749401858328276,
+           -0.1691208596119225,
+           -0.16578374493234233,
+           -0.16507997298037427,
+           -0.16710267710641985,
+           -0.17188441117736464,
+           -0.17939593641713092,
+           -0.18954641097816094,
+           -0.20218498315058153,
+           -0.21710375569547893,
+           -0.2340420560980452,
+           -0.2526919163720425,
+           -0.2727046371689091,
+           -0.2936982850571457,
+           -0.3152659495716649,
+           -0.33698456853146036,
+           -0.35842411662810986,
+           -0.37915694372573144,
+           -0.39876704589237694,
+           -0.4168590539852417,
+           -0.43306673159117953,
+           -0.4470607861069063,
+           -0.45855581343464963,
+           -0.46731621775829985,
+           -0.4731609726370714,
+           -0.47596711760053534,
+           -0.47567191486585714,
+           -0.4722736229800271,
+           -0.4658308773296539,
+           -0.45646070074898476,
+           -0.44433520008100835,
+           -0.4296770357120902,
+           -0.41275378004989305,
+           -0.3938713069452821,
+           -0.37336637654232024,
+           -0.35159859843550145,
+           -0.3289419698807785,
+           -0.30577619481964713,
+           -0.2824779934267962,
+           -0.2594126106999779,
+           -0.23692572632106068,
+           -0.21533595680078726,
+           -0.19492812506891538,
+           -0.17594745259227565,
+           -0.15859480530577305,
+           -0.14302309772612448,
+           -0.12933493026178725,
+           -0.11758150367051036,
+           -0.10776282262441145,
+           -0.0998291682188614,
+           -0.0936837878045698,
+           -0.08918672051263245,
+           -0.08615964902264535,
+           -0.08439164318081677,
+           -0.0836456396217241,
+           -0.0836654841089704,
+           -0.08418335031022715,
+           -0.0849273404730344,
+           -0.08562907016195068,
+           -0.08603104092387584,
+           -0.08589361140978675,
+           -0.08500138891686035,
+           -0.08316887922490288,
+           -0.08024525257329711,
+           -0.07611810714623357,
+           -0.07071613790337376,
+           -0.0640106473356088,
+           -0.056015865010330686,
+           -0.04678807382873191,
+           -0.036423571961583565,
+           -0.02505552967325716,
+           -0.012849828920809755,
+           -1.2206290531976526e-16
+          ],
+          [
+           0,
+           0.014375572875976851,
+           0.028849009621042723,
+           0.04316149755067262,
+           0.05705689312478482,
+           0.07028938564097754,
+           0.08263089964556569,
+           0.09387803625765556,
+           0.103858365283629,
+           0.11243589652791885,
+           0.11951557966593096,
+           0.12504670690956818,
+           0.12902512083943862,
+           0.1314941604917346,
+           0.13254431129777525,
+           0.13231155796004282,
+           0.1309744729643744,
+           0.1287501063235424,
+           0.12588877348938513,
+           0.1226678673632983,
+           0.1193848462403223,
+           0.11634957167853949,
+           0.11387618812414452,
+           0.11227474918168678,
+           0.11184280335576205,
+           0.11285715468958497,
+           0.11556601090525725,
+           0.1201817234633611,
+           0.12687431059317156,
+           0.13576593611645682,
+           0.14692649423670454,
+           0.16037042394213544,
+           0.17605484692322376,
+           0.19387909066359835,
+           0.2136856244207985,
+           0.23526240100820212,
+           0.25834656248261845,
+           0.28262943389669376,
+           0.307762697035106,
+           0.33336560632185874,
+           0.3590330826058232,
+           0.38434449796712583,
+           0.40887294660678075,
+           0.4321947837451915,
+           0.45389920659974303,
+           0.47359764914597446,
+           0.4909327655640478,
+           0.5055867859687845,
+           0.5172890420181816,
+           0.5258224789621029,
+           0.5310289941769102,
+           0.5328134696686659,
+           0.5311463967547039,
+           0.5260650244066393,
+           0.5176729977497098,
+           0.506138489112483,
+           0.4916908599336461,
+           0.47461592688381804,
+           0.45524993889553966,
+           0.43397240260067294,
+           0.41119792119972365,
+           0.3873672353604269,
+           0.36293767378816794,
+           0.33837323516402756,
+           0.314134531865159,
+           0.2906688290550861,
+           0.2684004102824318,
+           0.24772149271719357,
+           0.22898390178176498,
+           0.21249169652837224,
+           0.19849491412749393,
+           0.18718457482698458,
+           0.178689058380946,
+           0.17307192997428097,
+           0.17033125889011305,
+           0.1704004374329664,
+           0.17315047180331852,
+           0.17839368159232113,
+           0.18588871118200226,
+           0.19534672540738335,
+           0.2064386341124176,
+           0.21880316638128314,
+           0.2320555958237482,
+           0.24579690380110156,
+           0.25962315823882104,
+           0.2731348818951015,
+           0.2859461857169203,
+           0.29769345015711673,
+           0.30804334985161697,
+           0.3167000345399999,
+           0.3234113011079315,
+           0.32797361757887133,
+           0.3302358891306237,
+           0.33010188802534174,
+           0.3275313029231618,
+           0.32253939756144523,
+           0.31519530336411866,
+           0.30561900433957884,
+           0.29397710479331135,
+           0.2804775001274081,
+           0.2653630975901985,
+           0.2489047566221038,
+           0.23139363686180028,
+           0.21313315548309406,
+           0.19443076400187723,
+           0.17558975782748315,
+           0.15690132957069827,
+           0.13863706953377627,
+           0.12104210410139622,
+           0.10432904525874648,
+           0.08867290263644274,
+           0.07420708388234341,
+           0.06102058044190531,
+           0.04915640472333741,
+           0.03861131192223834,
+           0.029336806312605587,
+           0.02124139842543968,
+           0.014194047078028304,
+           0.008028689507791365,
+           0.002549734681015798,
+           -0.0024616300984232316,
+           -0.007240490231405352,
+           -0.012030800142049977,
+           -0.017077724347295414,
+           -0.022619929477854312,
+           -0.028882034880341606,
+           -0.036067425526230226,
+           -0.04435162181206668,
+           -0.05387638668564992,
+           -0.06474473172951567,
+           -0.07701696084845197,
+           -0.09070786361989552,
+           -0.10578514084421142,
+           -0.1221691131198265,
+           -0.13973373016568078,
+           -0.1583088649561775,
+           -0.17768384337243845,
+           -0.1976121278526793,
+           -0.2178170432610018,
+           -0.23799840565703043,
+           -0.25783989054065215,
+           -0.27701695708393437,
+           -0.2952051293629328,
+           -0.31208842506919543,
+           -0.32736771689419875,
+           -0.34076881188894825,
+           -0.35205003962008874,
+           -0.36100915075238565,
+           -0.3674893435323798,
+           -0.3713842561499717,
+           -0.3726417876173747,
+           -0.371266638027078,
+           -0.36732149014098536,
+           -0.3609267874575789,
+           -0.352259098384529,
+           -0.3415480910585604,
+           -0.32907217783775694,
+           -0.31515292168781406,
+           -0.30014832776688605,
+           -0.2844451717080857,
+           -0.2684505406985908,
+           -0.2525827838413855,
+           -0.2372620839443356,
+           -0.2229008734118176,
+           -0.20989432204254485,
+           -0.1986111241222329,
+           -0.18938480623649318,
+           -0.18250576584970093,
+           -0.17821423416484214,
+           -0.1766943354902271,
+           -0.17806938980158318,
+           -0.18239857601787252,
+           -0.1896750414116779,
+           -0.19982550832846427,
+           -0.21271139382538515,
+           -0.22813142182475457,
+           -0.24582567178691397,
+           -0.2654809736094557,
+           -0.28673752629103133,
+           -0.3091965886430893,
+           -0.33242906470571637,
+           -0.35598478514960374,
+           -0.37940226934648413,
+           -0.40221874136964453,
+           -0.4239801672223812,
+           -0.4442510802295926,
+           -0.46262396677341755,
+           -0.4787279952777177,
+           -0.4922368872841181,
+           -0.5028757502226162,
+           -0.5104267165528328,
+           -0.5147332627231788,
+           -0.5157031131595924,
+           -0.5133096684756216,
+           -0.5075919324604893,
+           -0.498652948287343,
+           -0.4866567899144974,
+           -0.4718241889622788,
+           -0.45442690960242715,
+           -0.43478101341299474,
+           -0.4132391820173579,
+           -0.39018228701776025,
+           -0.3660104137319765,
+           -0.34113355714281846,
+           -0.31596221499707855,
+           -0.29089810399889005,
+           -0.26632522052439656,
+           -0.2426014573683169,
+           -0.22005097297973145,
+           -0.19895748984177766,
+           -0.17955867460183644,
+           -0.162041724873203,
+           -0.14654025700262188,
+           -0.13313255629825638,
+           -0.12184121705946774,
+           -0.1126341650948045,
+           -0.1054270211199262,
+           -0.10008673034390048,
+           -0.0964363524995639,
+           -0.09426087831815595,
+           -0.09331391368558449,
+           -0.09332505205432869,
+           -0.0940077396244328,
+           -0.09506742673668142,
+           -0.09620979310286694,
+           -0.09714883406228554,
+           -0.09761459999556776,
+           -0.09736039120750864,
+           -0.0961692257395452,
+           -0.0938594172958358,
+           -0.09028912425630502,
+           -0.08535975799614443,
+           -0.07901816873883089,
+           -0.07125755917501488,
+           -0.062117109269746854,
+           -0.05168032921363581,
+           -0.04007219050013681,
+           -0.02745511679520339,
+           -0.014023945805484562,
+           -1.3268046304600178e-16
+          ],
+          [
+           0,
+           0.015439226634623365,
+           0.030858895441867058,
+           0.045982763434863294,
+           0.06054188271386864,
+           0.07428267025398869,
+           0.08697457602738982,
+           0.09841714213753386,
+           0.1084462611784768,
+           0.11693946251338591,
+           0.12382008007800126,
+           0.12906018402969024,
+           0.1326821903576054,
+           0.13475909664263414,
+           0.13541332764751007,
+           0.13481421043115607,
+           0.13317413430629937,
+           0.13074348529345237,
+           0.12780447689641294,
+           0.1246640282164387,
+           0.12164586588958101,
+           0.11908204742195835,
+           0.11730411966723361,
+           0.11663413701782444,
+           0.11737576907803803,
+           0.11980572700540403,
+           0.12416573134229521,
+           0.1306552321543756,
+           0.13942507492766484,
+           0.15057228336867706,
+           0.16413610354304453,
+           0.18009542332913245,
+           0.1983676477011332,
+           0.2188090747142571,
+           0.24121678012224398,
+           0.2653319812282451,
+           0.29084481377954263,
+           0.3174004203787667,
+           0.34460621587939766,
+           0.3720401653857462,
+           0.3992598845352613,
+           0.4258123503568423,
+           0.45124399471447396,
+           0.47511094157767325,
+           0.4969891443902535,
+           0.5164841807756655,
+           0.5332404687132802,
+           0.5469496809920562,
+           0.5573581529000681,
+           0.5642731013090408,
+           0.5675675010060722,
+           0.5671834956426302,
+           0.5631342552511753,
+           0.5555042290837171,
+           0.5444477806598944,
+           0.5301862304468503,
+           0.5130033695904362,
+           0.493239544650713,
+           0.4712844474729272,
+           0.44756877531390904,
+           0.42255495338651033,
+           0.39672713442094587,
+           0.37058070712390967,
+           0.3446115571223919,
+           0.31930532982390314,
+           0.2951269444664968,
+           0.27251060247570336,
+           0.2518505212431502,
+           0.2334926068882738,
+           0.21772725689082434,
+           0.20478345624373087,
+           0.19482429964055106,
+           0.18794403794141015,
+           0.18416671059431544,
+           0.1834463877188038,
+           0.18566900711320838,
+           0.19065575346316857,
+           0.1981678904325572,
+           0.20791292199867673,
+           0.21955192818408437,
+           0.2327078929927953,
+           0.24697481953777028,
+           0.26192740959603145,
+           0.2771310725683908,
+           0.29215202233754234,
+           0.306567219953419,
+           0.3199739254243531,
+           0.33199863300703025,
+           0.3423051809759669,
+           0.35060184848819537,
+           0.3566472782912675,
+           0.36025509399282546,
+           0.3612971136646726,
+           0.35970509686565433,
+           0.3554709988538861,
+           0.3486457429060064,
+           0.33933655834593435,
+           0.32770296719840136,
+           0.31395153544979315,
+           0.298329534904906,
+           0.2811176878354227,
+           0.26262218838280105,
+           0.24316621147552064,
+           0.2230811314439711,
+           0.2026976782964003,
+           0.1823372596285599,
+           0.162303670394697,
+           0.14287540142902572,
+           0.12429874097518151,
+           0.10678184198880335,
+           0.09048990217890353,
+           0.0755415743077136,
+           0.06200669192743829,
+           0.0499053613186582,
+           0.039208434782794455,
+           0.029839344532982426,
+           0.02167724113328188,
+           0.014561346648364067,
+           0.008296401239058008,
+           0.0026590536676753254,
+           -0.002594978224775219,
+           -0.007723170922974466,
+           -0.012988091302884253,
+           -0.018649143697279467,
+           -0.02495439024993263,
+           -0.03213266508713773,
+           -0.040386195408267336,
+           -0.049883929688963255,
+           -0.060755755125418934,
+           -0.07308776368016044,
+           -0.08691869919172,
+           -0.10223768765996832,
+           -0.11898331978056442,
+           -0.13704411990931412,
+           -0.15626039977109335,
+           -0.17642745929487577,
+           -0.1973000618655934,
+           -0.21859807792449046,
+           -0.2400131600695458,
+           -0.26121628539021663,
+           -0.28186597741689257,
+           -0.301617001375052,
+           -0.32012931289122126,
+           -0.33707703225857494,
+           -0.3521572140531976,
+           -0.3650981853737833,
+           -0.3756672351890906,
+           -0.3836774520065776,
+           -0.3889935269719319,
+           -0.39153636409238374,
+           -0.39128636794860805,
+           -0.3882853113191851,
+           -0.3826367198005561,
+           -0.37450474691026503,
+           -0.3641115504126655,
+           -0.35173321778180416,
+           -0.3376943248931697,
+           -0.32236124631453394,
+           -0.30613436709119646,
+           -0.2894393739040353,
+           -0.27271782721717086,
+           -0.2564172349266583,
+           -0.24098086159170726,
+           -0.22683751522534976,
+           -0.21439155563154483,
+           -0.20401336433433226,
+           -0.19603050633248842,
+           -0.19071979845560946,
+           -0.18830047835932157,
+           -0.18892864267381337,
+           -0.19269309312478472,
+           -0.1996126962964606,
+           -0.20963532690555456,
+           -0.2226384268722099,
+           -0.23843117402291003,
+           -0.2567582158774506,
+           -0.2773048865927408,
+           -0.2997037896722105,
+           -0.3235425963663936,
+           -0.3483728805857417,
+           -0.37371978633159036,
+           -0.39909230373135435,
+           -0.4239939152258202,
+           -0.4479333646542892,
+           -0.47043529913174653,
+           -0.4910505367795242,
+           -0.5093657224784978,
+           -0.5250121486374536,
+           -0.5376735381449117,
+           -0.5470926117056246,
+           -0.5530762910395898,
+           -0.5554994222249633,
+           -0.55430693899384,
+           -0.5495144231728499,
+           -0.541207057785602,
+           -0.5295370066658077,
+           -0.5147192918341189,
+           -0.49702627545792927,
+           -0.4767808860776555,
+           -0.4543487581489985,
+           -0.4301294791092837,
+           -0.40454715852255435,
+           -0.3780405489075395,
+           -0.3510529572509033,
+           -0.3240221897410353,
+           -0.29737076985575683,
+           -0.2714966616777288,
+           -0.24676471641532238,
+           -0.22349904093421294,
+           -0.20197646314549356,
+           -0.1824212409562038,
+           -0.16500112987662946,
+           -0.14982489008845498,
+           -0.13694127766643693,
+           -0.126339527614325,
+           -0.11795129934480977,
+           -0.11165401912264555,
+           -0.10727551969409871,
+           -0.10459984569177763,
+           -0.10337406521078586,
+           -0.10331590389167544,
+           -0.10412199850508344,
+           -0.10547655288045302,
+           -0.10706017039465801,
+           -0.10855863433479196,
+           -0.1096714103285068,
+           -0.11011965360605168,
+           -0.10965351788934849,
+           -0.10805858182740478,
+           -0.10516123261961137,
+           -0.1008328741799177,
+           -0.09499285818738276,
+           -0.08761006985267743,
+           -0.07870313535473118,
+           -0.06833925377575767,
+           -0.056631692077355265,
+           -0.0437360163112458,
+           -0.029845164969027803,
+           -0.015183500319209979,
+           -1.430731748338501e-16
+          ],
+          [
+           0,
+           0.01646040726991909,
+           0.032767589840943544,
+           0.04863045721512221,
+           0.06377035696368007,
+           0.07792945880661209,
+           0.0908785842854607,
+           0.10242426995944692,
+           0.11241487169990623,
+           0.12074554227022717,
+           0.12736194333821835,
+           0.13226258564510784,
+           0.13549972642857933,
+           0.13717879047358242,
+           0.1374563194025041,
+           0.1365364920487609,
+           0.1346662960170025,
+           0.13212946587411342,
+           0.1292393359400982,
+           0.1263307845281585,
+           0.12375147098038906,
+           0.12185258632986716,
+           0.12097935238640871,
+           0.12146151212425002,
+           0.12360405622444556,
+           0.12767842642438462,
+           0.13391442603741838,
+           0.14249305186550132,
+           0.1535404401220383,
+           0.1671230924331822,
+           0.1832445171405342,
+           0.20184338674205066,
+           0.22279327522637166,
+           0.24590400019323344,
+           0.27092455496997336,
+           0.2975475764148653,
+           0.32541525572377844,
+           0.35412656328293424,
+           0.38324562534287016,
+           0.4123110608601777,
+           0.44084606200400517,
+           0.4683689821818013,
+           0.49440418150404536,
+           0.5184928717414422,
+           0.5402037012418116,
+           0.5591428250247424,
+           0.5749632162607965,
+           0.5873729923156509,
+           0.5961425510971002,
+           0.6011103410453449,
+           0.6021871200904145,
+           0.5993585944922889,
+           0.592686366816742,
+           0.5823071624521505,
+           0.5684303450626591,
+           0.5513337722028167,
+           0.5313580819924816,
+           0.508899539300435,
+           0.484401604393801,
+           0.45834541763518466,
+           0.4312394198019974,
+           0.40360834832757053,
+           0.37598186471482054,
+           0.34888307718523637,
+           0.3228172250837372,
+           0.2982607876040676,
+           0.27565126912736193,
+           0.25537789713040954,
+           0.23777344662047178,
+           0.2231073779291402,
+           0.21158044311279284,
+           0.2033208809345636,
+           0.19838228230500587,
+           0.19674316806682268,
+           0.19830828009970292,
+           0.20291154589240817,
+           0.21032063697560568,
+           0.22024300389770973,
+           0.23233323567290415,
+           0.24620156067735005,
+           0.2614232795634983,
+           0.27754889953767403,
+           0.2941147238084349,
+           0.31065364052770994,
+           0.326705852328755,
+           0.34182929067527834,
+           0.35560946857933207,
+           0.36766854057295884,
+           0.3776733597342762,
+           0.3853423475396807,
+           0.39045102268351134,
+           0.39283606901084783,
+           0.39239785949602096,
+           0.3891013918497455,
+           0.38297563088840664,
+           0.37411129226665074,
+           0.36265714058006954,
+           0.34881491123808944,
+           0.3328329989899648,
+           0.3149990857352773,
+           0.2956319055355584,
+           0.2750723649493511,
+           0.25367425145096534,
+           0.23179477141500243,
+           0.20978516175446565,
+           0.18798161574324165,
+           0.16669675394126834,
+           0.14621185573149417,
+           0.12677004617509957,
+           0.10857060723302406,
+           0.09176455254616875,
+           0.07645157167638082,
+           0.06267841383322646,
+           0.05043874355914633,
+           0.03967446257023529,
+           0.030278453921030346,
+           0.022098667841534782,
+           0.014943433914047,
+           0.008587852592444198,
+           0.0027810912170164823,
+           -0.0027456136531554443,
+           -0.008270463991984528,
+           -0.01407234720028225,
+           -0.02042205796884932,
+           -0.02757373164848988,
+           -0.03575672029829299,
+           -0.04516813127456879,
+           -0.05596623125561479,
+           -0.06826489639901458,
+           -0.08212926245743568,
+           -0.09757269781300353,
+           -0.11455518830746236,
+           -0.13298318630542058,
+           -0.15271093855109413,
+           -0.17354326902234432,
+           -0.19523975511995792,
+           -0.21752019911439566,
+           -0.24007126273092919,
+           -0.2625541019532066,
+           -0.2846128123507736,
+           -0.30588347317415426,
+           -0.32600356168097666,
+           -0.34462149809597853,
+           -0.36140607656191204,
+           -0.3760555385524647,
+           -0.38830605248367484,
+           -0.3979393765143255,
+           -0.40478950045576995,
+           -0.4087480868625216,
+           -0.40976856016022606,
+           -0.4078687253839952,
+           -0.40313183394459573,
+           -0.39570605192992814,
+           -0.3858023258440659,
+           -0.3736906804106147,
+           -0.3596950221356969,
+           -0.3441865597668326,
+           -0.32757598766402124,
+           -0.31030460954633915,
+           -0.29283460730248273,
+           -0.27563868187076435,
+           -0.25918931003695667,
+           -0.24394787193497794,
+           -0.23035390877867884,
+           -0.21881476876825576,
+           -0.2096958912230783,
+           -0.20331196497066445,
+           -0.19991917719715335,
+           -0.1997087438092191,
+           -0.20280188247439943,
+           -0.20924635561673502,
+           -0.21901467356760607,
+           -0.23200400870719337,
+           -0.24803783073698238,
+           -0.2668692321887586,
+           -0.28818587290074893,
+           -0.31161643346171886,
+           -0.33673843148438,
+           -0.3630872219029957,
+           -0.39016597409470416,
+           -0.4174563951937369,
+           -0.44442995107499716,
+           -0.4705593245656803,
+           -0.4953298447916139,
+           -0.5182506223166937,
+           -0.5388651318698466,
+           -0.5567609977992071,
+           -0.5715787566202513,
+           -0.5830193956623728,
+           -0.5908504962634776,
+           -0.5949108434937964,
+           -0.5951134011881535,
+           -0.5914465902306405,
+           -0.5839738486103845,
+           -0.5728314927615273,
+           -0.5582249401151691,
+           -0.5404233916418881,
+           -0.5197531095061336,
+           -0.49658945790686576,
+           -0.471347903945342,
+           -0.4444741992481483,
+           -0.416433981509593,
+           -0.387702047665787,
+           -0.35875155678197984,
+           -0.33004342078651006,
+           -0.30201613493649404,
+           -0.27507628752476254,
+           -0.2495899701578158,
+           -0.2258752864166567,
+           -0.20419612845301235,
+           -0.18475735878508726,
+           -0.16770149905031026,
+           -0.15310698963584957,
+           -0.14098804488512748,
+           -0.13129608894634662,
+           -0.12392271827138844,
+           -0.1187040992580322,
+           -0.11542667448236872,
+           -0.11383401925525617,
+           -0.11363466263545968,
+           -0.11451066421741113,
+           -0.11612672053727914,
+           -0.11813956322684717,
+           -0.12020740536551486,
+           -0.12199919296028709,
+           -0.12320342509145775,
+           -0.12353631881416924,
+           -0.12274911307114052,
+           -0.12063432917755887,
+           -0.11703083328550899,
+           -0.11182757790946907,
+           -0.10496593428861159,
+           -0.09644056419351367,
+           -0.08629881781948494,
+           -0.0746386826821694,
+           -0.061605345974497634,
+           -0.04738646870798312,
+           -0.03220630323939758,
+           -0.016318815635505635,
+           -1.5315252351621846e-16
+          ],
+          [
+           0,
+           0.01743030352424802,
+           0.03455874735733887,
+           0.051082396906054005,
+           0.06671635918487216,
+           0.08120237789224104,
+           0.09431671085399203,
+           0.10587707605093302,
+           0.11574847640222231,
+           0.12384774233722402,
+           0.13014666422827403,
+           0.13467362314150008,
+           0.1375136671739593,
+           0.13880702090237076,
+           0.13874605615370372,
+           0.13757079239097314,
+           0.1355630334727895,
+           0.133039283415819,
+           0.13034261615243622,
+           0.1278337023053195,
+           0.12588121897784046,
+           0.12485188589071365,
+           0.12510038242890423,
+           0.12695940499770964,
+           0.13073012238240847,
+           0.13667327858456432,
+           0.1450011780557312,
+           0.155870767710417,
+           0.1693780040695063,
+           0.18555366299597115,
+           0.20436071449226642,
+           0.2256933467930237,
+           0.24937768344995814,
+           0.2751741952702069,
+           0.3027817668711244,
+           0.331843336299309,
+           0.3619529866576812,
+           0.39266433197753897,
+           0.4235000065813028,
+           0.45396203873468277,
+           0.48354286620215964,
+           0.5117367339861448,
+           0.5380512034937514,
+           0.5620184979268844,
+           0.5832064109602669,
+           0.6012285147216471,
+           0.6157534185173656,
+           0.6265128512933913,
+           0.6333083679741408,
+           0.6360165119273915,
+           0.6345923020889177,
+           0.6290709528668278,
+           0.6195677768721941,
+           0.6062762637699997,
+           0.5894643720594896,
+           0.569469113314827,
+           0.5466895493028812,
+           0.5215783604466078,
+           0.49463217838984647,
+           0.4663809051042837,
+           0.43737626533571683,
+           0.408179857618767,
+           0.37935098114577914,
+           0.35143452116180407,
+           0.32494917414145247,
+           0.30037628581978093,
+           0.278149560398584,
+           0.25864587829255814,
+           0.24217743312969364,
+           0.22898536702889172,
+           0.2192350472203171,
+           0.21301308772937425,
+           0.2103261780747644,
+           0.2111017377546982,
+           0.21519037176635308,
+           0.2223700595828907,
+           0.23235196894200977,
+           0.24478774747804527,
+           0.25927811058518374,
+           0.27538251376997713,
+           0.2926296728623379,
+           0.3105286764010515,
+           0.32858042174345364,
+           0.34628910026491544,
+           0.3631734575451042,
+           0.3787775616521644,
+           0.3926808263357994,
+           0.4045070557691453,
+           0.4139323029302749,
+           0.420691364142383,
+           0.4245827669309424,
+           0.42547214633767866,
+           0.42329394520571995,
+           0.4180514157112274,
+           0.40981494152566644,
+           0.3987187414048674,
+           0.38495605469101085,
+           0.3687729462017029,
+           0.35046090135571867,
+           0.33034841132908005,
+           0.3087917718413113,
+           0.28616533726286303,
+           0.2628514836774949,
+           0.23923054004874417,
+           0.2156709456094152,
+           0.19251988406304357,
+           0.17009463136455039,
+           0.14867483409889537,
+           0.12849591031425942,
+           0.10974373473752853,
+           0.09255073637054323,
+           0.07699349940060829,
+           0.06309191910050208,
+           0.0508099239377808,
+           0.040057734485391065,
+           0.030695589953456733,
+           0.022538835250968822,
+           0.015364226393488755,
+           0.008917280684727151,
+           0.0029204712078719705,
+           -0.002917956554973377,
+           -0.008894784152349433,
+           -0.015302483689334812,
+           -0.022419996993290434,
+           -0.030503878996955114,
+           -0.039780044562878016,
+           -0.050436342467814824,
+           -0.0626161589992776,
+           -0.076413227124994,
+           -0.09186778614758145,
+           -0.1089642019345358,
+           -0.12763012009649494,
+           -0.14773718482722586,
+           -0.16910331551925034,
+           -0.19149649275656228,
+           -0.21463996588668469,
+           -0.2382187570878157,
+           -0.2618873026208024,
+           -0.2852780416624627,
+           -0.30801073753117836,
+           -0.3297022958957384,
+           -0.34997683022865067,
+           -0.3684757167032651,
+           -0.3848673791615483,
+           -0.39885654975543694,
+           -0.41019276228492124,
+           -0.41867785285443937,
+           -0.42417226582485906,
+           -0.4265999915856672,
+           -0.4259519957144347,
+           -0.42228803581802665,
+           -0.4157368018584938,
+           -0.40649435708090553,
+           -0.39482089875820764,
+           -0.38103589980526875,
+           -0.3655117328505162,
+           -0.34866591657869644,
+           -0.33095215911724346,
+           -0.3128504040550888,
+           -0.29485611058090183,
+           -0.2774690195520814,
+           -0.2611816715372563,
+           -0.2464679506439319,
+           -0.23377192903854688,
+           -0.2234972814422063,
+           -0.21599752666092176,
+           -0.21156733466654568,
+           -0.21043511332213055,
+           -0.21275705912697576,
+           -0.21861282205739396,
+           -0.22800289652810155,
+           -0.2408478096185217,
+           -0.2569891349913072,
+           -0.2761923174166107,
+           -0.2981512495652867,
+           -0.32249450080240116,
+           -0.3487930581227442,
+           -0.37656940308972786,
+           -0.4053077165548794,
+           -0.43446497583168764,
+           -0.46348268753782723,
+           -0.4917989840288228,
+           -0.5188608025982855,
+           -0.5441358646288701,
+           -0.5671241766929994,
+           -0.5873687871050157,
+           -0.6044655493353664,
+           -0.6180716675742772,
+           -0.6279128289929078,
+           -0.6337887611784795,
+           -0.6355770909866529,
+           -0.6332354217365804,
+           -0.6268015882778182,
+           -0.6163920929439273,
+           -0.6021987687147071,
+           -0.5844837579828542,
+           -0.5635729351381931,
+           -0.5398479377769368,
+           -0.5137370038286747,
+           -0.4857048394860717,
+           -0.45624176485926443,
+           -0.4258524002337059,
+           -0.3950441653125143,
+           -0.3643158666572193,
+           -0.3341466446537605,
+           -0.3049855408389887,
+           -0.2772419296045023,
+           -0.25127703558253855,
+           -0.22739672999060476,
+           -0.20584576657533768,
+           -0.1868035813716392,
+           -0.17038174119245472,
+           -0.1566230845685508,
+           -0.14550255679209514,
+           -0.13692969882756914,
+           -0.13075270917678689,
+           -0.12676395932721732,
+           -0.12470680812261199,
+           -0.12428352913954108,
+           -0.125164138697828,
+           -0.12699589112088017,
+           -0.12941319280031155,
+           -0.1320476778653712,
+           -0.13453818601067133,
+           -0.13654038733183094,
+           -0.13773580973061378,
+           -0.1378400412914051,
+           -0.13660990255917704,
+           -0.13384941128342107,
+           -0.1294143942240539,
+           -0.12321563622599614,
+           -0.11522049505251522,
+           -0.10545295045125244,
+           -0.09399209659741599,
+           -0.08096912738631915,
+           -0.06656290301238964,
+           -0.050994222889445634,
+           -0.034518963312838116,
+           -0.0174202674965419,
+           -1.6283188284955877e-16
+          ],
+          [
+           0,
+           0.018340580423799067,
+           0.03621724354815391,
+           0.05331860236640315,
+           0.06935731028653552,
+           0.0840787536242466,
+           0.09726885484471331,
+           0.10876077431728871,
+           0.11844032675198854,
+           0.126249961649759,
+           0.13219119418285039,
+           0.13632541299059653,
+           0.13877303341700403,
+           0.13971100766669384,
+           0.13936874612783534,
+           0.1380225456209266,
+           0.13598865952716072,
+           0.13361518063302513,
+           0.13127293918386365,
+           0.12934564525833134,
+           0.12821952547308518,
+           0.12827271866022377,
+           0.1298647031425952,
+           0.13332602934386245,
+           0.13894862566255176,
+           0.14697693293681935,
+           0.157600103724207,
+           0.17094547747626235,
+           0.1870735121115626,
+           0.20597431722938606,
+           0.22756589512556655,
+           0.2516941538346864,
+           0.27813471266479767,
+           0.3065964761961352,
+           0.3367269085883915,
+           0.36811889738010534,
+           0.4003190558326601,
+           0.4328372762740647,
+           0.46515731475246314,
+           0.49674816042626635,
+           0.5270759221785073,
+           0.5556159504834056,
+           0.5818649049500657,
+           0.6053524774299619,
+           0.6256524871354845,
+           0.6423930777355225,
+           0.6552657665579416,
+           0.6640331223608444,
+           0.6685348800047518,
+           0.6686923369990943,
+           0.664510917422777,
+           0.6560808321474109,
+           0.6435758095676024,
+           0.6272499170633248,
+           0.6074325390629414,
+           0.5845216217281207,
+           0.5589753358651383,
+           0.531302347664568,
+           0.5020509203536189,
+           0.47179709799308034,
+           0.4411322447747132,
+           0.41065022873302615,
+           0.38093454739621146,
+           0.35254569435322564,
+           0.32600905997131735,
+           0.3018036467006532,
+           0.2803518598626768,
+           0.2620106090139574,
+           0.24706392353835732,
+           0.23571724981571146,
+           0.22809355703201115,
+           0.22423133541822432,
+           0.22408452548890972,
+           0.22752437080074486,
+           0.23434314098745263,
+           0.2442596274655573,
+           0.25692627232345616,
+           0.27193775252074476,
+           0.2888408075647343,
+           0.30714507011577397,
+           0.32633463619144454,
+           0.34588009533410996,
+           0.3652507316587626,
+           0.3839266043213695,
+           0.40141022068031007,
+           0.4172375271283244,
+           0.43098796094137287,
+           0.4422933310520653,
+           0.45084532578522113,
+           0.4564014805318719,
+           0.4587894772087441,
+           0.45790968918079855,
+           0.4537359290715778,
+           0.4463144014616623,
+           0.43576090677313295,
+           0.42225638556073314,
+           0.4060409329181215,
+           0.38740644976287264,
+           0.3666881304769007,
+           0.34425501394998637,
+           0.3204998468331197,
+           0.29582852323162206,
+           0.27064937379083615,
+           0.24536257895276492,
+           0.22034997606616716,
+           0.19596551816409896,
+           0.1725266238994025,
+           0.15030663382883946,
+           0.12952855858780984,
+           0.11036027026003892,
+           0.09291125029428572,
+           0.0772309666186947,
+           0.06330891018616196,
+           0.051076278125928645,
+           0.04040924806712081,
+           0.031133747116144157,
+           0.023031580449236245,
+           0.015847749496032196,
+           0.009298759121973851,
+           0.003081687837133728,
+           -0.003116224494186718,
+           -0.009607730202672426,
+           -0.01669573396347764,
+           -0.024663724652031815,
+           -0.033766736966208855,
+           -0.04422308719652765,
+           -0.05620710756073217,
+           -0.0698430777707812,
+           -0.08520052161882243,
+           -0.10229100113363351,
+           -0.12106650216001369,
+           -0.14141946402826572,
+           -0.16318446335031495,
+           -0.18614151898163192,
+           -0.21002094291280418,
+           -0.23450962137339124,
+           -0.25925857277183134,
+           -0.28389159521742313,
+           -0.3080147871389804,
+           -0.33122670067945037,
+           -0.353128869722252,
+           -0.3733364430592229,
+           -0.3914886486460634,
+           -0.4072588172440023,
+           -0.4203637029779232,
+           -0.43057185424104927,
+           -0.43771081056690764,
+           -0.44167292903497085,
+           -0.4424196767965853,
+           -0.4399842635937196,
+           -0.43447252877776166,
+           -0.4260620403165248,
+           -0.414999407541523,
+           -0.4015958538368493,
+           -0.38622113900086374,
+           -0.36929596253795305,
+           -0.35128301762264164,
+           -0.33267689995834676,
+           -0.31399310536102243,
+           -0.2957563738857462,
+           -0.2784886560712418,
+           -0.2626969879456055,
+           -0.24886156552257593,
+           -0.23742430649997884,
+           -0.22877817680404558,
+           -0.22325754273260098,
+           -0.22112978613283074,
+           -0.22258839086069884,
+           -0.22774767440971022,
+           -0.23663929989579083,
+           -0.24921066147967666,
+           -0.2653251918206175,
+           -0.2847645943675331,
+           -0.30723295732151834,
+           -0.33236266106800344,
+           -0.3597219478776169,
+           -0.388823982762424,
+           -0.4191371985247491,
+           -0.45009668712629003,
+           -0.4811163742923482,
+           -0.5116016953672444,
+           -0.5409624783154896,
+           -0.5686257347164654,
+           -0.5940480617522631,
+           -0.616727367487192,
+           -0.6362136479560784,
+           -0.6521185673207521,
+           -0.6641236210640802,
+           -0.6719866961668436,
+           -0.675546880624386,
+           -0.6747274165687972,
+           -0.6695367356451493,
+           -0.6600675610637364,
+           -0.6464941067982696,
+           -0.629067449600693,
+           -0.6081091927570291,
+           -0.5840035807647673,
+           -0.5571882603950469,
+           -0.5281439150354543,
+           -0.49738302503517695,
+           -0.46543802637608267,
+           -0.43284915290735104,
+           -0.4001522533093882,
+           -0.36786687276895974,
+           -0.33648488110106517,
+           -0.30645991396737526,
+           -0.27819787230733506,
+           -0.2520486976657397,
+           -0.2282996084636455,
+           -0.2071699452388376,
+           -0.18880773240502466,
+           -0.17328802115640884,
+           -0.16061303384525843,
+           -0.15071408558536434,
+           -0.14345521508874662,
+           -0.1386384149086718,
+           -0.13601031237095884,
+           -0.13527011748418846,
+           -0.1360786238852674,
+           -0.13806802413695374,
+           -0.14085228204714711,
+           -0.14403779257156438,
+           -0.14723405457347202,
+           -0.15006408335720417,
+           -0.1521742984037942,
+           -0.15324363688317505,
+           -0.1529916648985704,
+           -0.15118548548022642,
+           -0.14764527439146832,
+           -0.142248311020631,
+           -0.13493141108488438,
+           -0.12569170956375747,
+           -0.11458578515386493,
+           -0.1017271605062615,
+           -0.08728225448733422,
+           -0.07146490263258533,
+           -0.05452959883215831,
+           -0.03676364416749064,
+           -0.018478416881187936,
+           -1.720277353083025e-16
+          ],
+          [
+           0,
+           0.019183500924352698,
+           0.037729401775357656,
+           0.05532160480166197,
+           0.07167437339113232,
+           0.08654099948706827,
+           0.09972140402885976,
+           0.11106846317323003,
+           0.12049288598301686,
+           0.1279665067213171,
+           0.13352389591345787,
+           0.13726223790070025,
+           0.1393394676061349,
+           0.13997070452605687,
+           0.13942306640173294,
+           0.13800898748953697,
+           0.13607820575293278,
+           0.13400861864415725,
+           0.1321962375237609,
+           0.13104449540277885,
+           0.13095318094857658,
+           0.13230728309373513,
+           0.135466034821263,
+           0.14075244164156153,
+           0.1484435699819651,
+           0.15876185341470425,
+           0.1718676507658088,
+           0.1878532602534317,
+           0.2067385586284058,
+           0.2284683946951371,
+           0.25291182355193637,
+           0.27986322246946893,
+           0.30904528264873427,
+           0.340113824324369,
+           0.3726643369686467,
+           0.4062401028461332,
+           0.4403417219561106,
+           0.47443782048801014,
+           0.5079766942081496,
+           0.5403986134710355,
+           0.5711484984359806,
+           0.5996886620380492,
+           0.6255113146056146,
+           0.6481505278476898,
+           0.6671933671804947,
+           0.682289919769352,
+           0.6931619707965724,
+           0.6996101117296798,
+           0.7015191010062412,
+           0.6988613386871664,
+           0.6916983612631584,
+           0.6801803098450329,
+           0.6645433732830657,
+           0.6451052561658773,
+           0.6222587689644004,
+           0.5964636826554846,
+           0.568237031880721,
+           0.5381420880484108,
+           0.5067762558555926,
+           0.47475817270705545,
+           0.44271430980168447,
+           0.41126538576977717,
+           0.381012908380178,
+           0.35252615687830297,
+           0.32632990703629267,
+           0.30289318324972403,
+           0.28261929743447456,
+           0.2658374036625511,
+           0.25279576117954344,
+           0.2436568575551732,
+           0.23849449923060967,
+           0.23729292972759444,
+           0.23994798742143747,
+           0.24627026623148007,
+           0.25599019503094866,
+           0.2687649061797918,
+           0.284186721441523,
+           0.3017930456793988,
+           0.3210774260532862,
+           0.34150150774233495,
+           0.3625075971381159,
+           0.3835315304626997,
+           0.4040155401655665,
+           0.4234208133594356,
+           0.4412394459001955,
+           0.45700551224933056,
+           0.4703049945511273,
+           0.4807843438182874,
+           0.48815748100432665,
+           0.49221108517286866,
+           0.492808058965922,
+           0.4898891070528331,
+           0.4834724100771176,
+           0.4736514236470743,
+           0.46059087797308906,
+           0.4445210977017721,
+           0.4257308022513533,
+           0.4045585835127302,
+           0.38138328925132897,
+           0.35661356616018325,
+           0.3306768356555672,
+           0.3040079877168279,
+           0.2770380830693318,
+           0.25018335169167527,
+           0.22383476607631742,
+           0.19834845114805957,
+           0.17403716968241104,
+           0.15116309306377426,
+           0.12993203302706355,
+           0.11048927151002824,
+           0.09291708388835919,
+           0.07723400673479829,
+           0.0633958559557387,
+           0.05129845586045519,
+           0.04078199555413567,
+           0.031636887131441936,
+           0.02361096153980975,
+           0.01641780365422356,
+           0.009745998922439563,
+           0.0032690406360510087,
+           -0.0033443699555952867,
+           -0.010419908421906151,
+           -0.018267377364227563,
+           -0.027170898218272673,
+           -0.03737980931026113,
+           -0.049100516539767686,
+           -0.06248951842993198,
+           -0.07764779693489206,
+           -0.09461673009183202,
+           -0.1133756432427616,
+           -0.13384107312386123,
+           -0.15586777470056706,
+           -0.17925145533836348,
+           -0.20373317588923723,
+           -0.22900531468290336,
+           -0.2547189493469337,
+           -0.2804924738853249,
+           -0.30592123547712063,
+           -0.33058794785939843,
+           -0.3540736166425998,
+           -0.3759686970297287,
+           -0.3958841965677031,
+           -0.41346243496663965,
+           -0.42838717971751283,
+           -0.440392890074228,
+           -0.4492728226175671,
+           -0.4548857785893246,
+           -0.4571613058198705,
+           -0.4561032055730783,
+           -0.4517912360774853,
+           -0.4443809488797726,
+           -0.4341016403490037,
+           -0.42125244753246127,
+           -0.4061966639517335,
+           -0.38935439567564634,
+           -0.3711937199975566,
+           -0.35222054722710655,
+           -0.3329674195217126,
+           -0.3139815084875957,
+           -0.2958120947681286,
+           -0.27899782745745905,
+           -0.2640540685473502,
+           -0.251460627530843,
+           -0.2416501837273848,
+           -0.234997679024661,
+           -0.231810941897215,
+           -0.2323227752782589,
+           -0.23668470680581333,
+           -0.2449625609576406,
+           -0.25713396957481904,
+           -0.27308789129463806,
+           -0.29262616258765384,
+           -0.31546705458595453,
+           -0.3412507618829934,
+           -0.36954670315174526,
+           -0.399862469899903,
+           -0.4316542200228157,
+           -0.46433827799767796,
+           -0.49730367443882484,
+           -0.5299253350177371,
+           -0.5615776129997834,
+           -0.5916478512497568,
+           -0.6195496587170652,
+           -0.6447355931508537,
+           -0.6667089559521643,
+           -0.6850344262990997,
+           -0.6993472894639421,
+           -0.7093610478997817,
+           -0.7148732423864312,
+           -0.7157693533460159,
+           -0.7120246983221963,
+           -0.7037042894440435,
+           -0.6909606632997634,
+           -0.6740297438426263,
+           -0.6532248455685051,
+           -0.6289289681084251,
+           -0.6015855735054421,
+           -0.5716880728219934,
+           -0.5397682784986034,
+           -0.5063841023432124,
+           -0.4721067956145485,
+           -0.43750803698464635,
+           -0.403147176016121,
+           -0.36955893414436014,
+           -0.337241852173211,
+           -0.3066477533152903,
+           -0.2781724643466687,
+           -0.25214800517103475,
+           -0.22883641981337807,
+           -0.2084253805222747,
+           -0.19102565228578744,
+           -0.17667045876455037,
+           -0.16531674356749254,
+           -0.1568482741083795,
+           -0.15108049013989208,
+           -0.1477669565804656,
+           -0.14660724147307655,
+           -0.14725600579562118,
+           -0.149333063212698,
+           -0.15243414541314193,
+           -0.15614209295579712,
+           -0.16003818291819474,
+           -0.16371330330187128,
+           -0.1667786901045335,
+           -0.1688759560514926,
+           -0.16968615983734717,
+           -0.16893769084556895,
+           -0.16641277601469437,
+           -0.16195245199272443,
+           -0.15545988603557934,
+           -0.14690197223556972,
+           -0.1363091745174338,
+           -0.12377363327649225,
+           -0.10944559740660102,
+           -0.09352828664126618,
+           -0.07627132951982421,
+           -0.05796295887353021,
+           -0.03892117858195306,
+           -0.019484141676221582,
+           -1.8066086251924099e-16
+          ],
+          [
+           0,
+           0.01995204119647586,
+           0.03908320384362402,
+           0.05707672732948327,
+           0.0736527742643193,
+           0.0885769429308213,
+           0.10166753138165362,
+           0.11280135451678318,
+           0.12191795293846883,
+           0.12902207403668514,
+           0.1341843505487387,
+           0.13754014863089128,
+           0.1392866050925279,
+           0.13967792066870602,
+           0.13901902184720147,
+           0.1376577466623589,
+           0.13597574892867395,
+           0.13437834961557457,
+           0.13328359258483263,
+           0.1331107839890076,
+           0.13426880968947189,
+           0.1371445326972001,
+           0.14209157265522038,
+           0.1494197617458997,
+           0.15938555628818502,
+           0.17218366104638078,
+           0.18794009443885534,
+           0.20670688811402077,
+           0.22845857460241834,
+           0.2530905729358618,
+           0.28041953532886627,
+           0.31018566940229175,
+           0.342057001200434,
+           0.37563549563498766,
+           0.4104649041942064,
+           0.44604016595257373,
+           0.4818181482030214,
+           0.5172294784089032,
+           0.5516911905112835,
+           0.5846198866575157,
+           0.6154451007043922,
+           0.643622542779733,
+           0.6686469049584135,
+           0.6900639167274261,
+           0.707481355190684,
+           0.7205787385198601,
+           0.7291154614340286,
+           0.7329371677633131,
+           0.7319801965460113,
+           0.7262739836232726,
+           0.7159413492257749,
+           0.7011966524126777,
+           0.682341844197242,
+           0.659760501532269,
+           0.6339099728021772,
+           0.6053118108919684,
+           0.574540711164712,
+           0.5422122077680034,
+           0.508969411721297,
+           0.4754690974733011,
+           0.4423674604908199,
+           0.4103058765567646,
+           0.3798969936145537,
+           0.3517114791925411,
+           0.32626573086415755,
+           0.3040108342261304,
+           0.28532302306849594,
+           0.2704958604932915,
+           0.2597343185903471,
+           0.25315088890261833,
+           0.250763807417172,
+           0.2524974273840342,
+           0.2581847221230004,
+           0.26757184937380185,
+           0.2803246599089589,
+           0.2960369872477846,
+           0.3142405134970434,
+           0.33441596961021797,
+           0.3560053975887227,
+           0.3784251780825118,
+           0.40107951005644576,
+           0.42337402006493835,
+           0.44472917742405166,
+           0.46459319819679623,
+           0.48245413522928643,
+           0.49785087311905535,
+           0.5103827754089069,
+           0.5197177657612011,
+           0.5255986645117394,
+           0.527847645836627,
+           0.5263687276955498,
+           0.5211482555725792,
+           0.5122533906076414,
+           0.4998286617699433,
+           0.48409068905623914,
+           0.4653212291347783,
+           0.44385873530741765,
+           0.42008865913662047,
+           0.39443275071564177,
+           0.3673376376311877,
+           0.3392629786251934,
+           0.3106694964313589,
+           0.28200719505558774,
+           0.2537040598920981,
+           0.2261555247148213,
+           0.19971496813929931,
+           0.1746854741725331,
+           0.15131305767850933,
+           0.12978151685098344,
+           0.1102090320903292,
+           0.09264658511342148,
+           0.07707822484029302,
+           0.0634231587958877,
+           0.05153960164812463,
+           0.041230267264354005,
+           0.032249348448156114,
+           0.024310790381237644,
+           0.017097630701032256,
+           0.010272151925995605,
+           0.0034865712814072286,
+           -0.0036060206028898016,
+           -0.01134076681511019,
+           -0.020030490390040373,
+           -0.02995576398959549,
+           -0.0413558711372857,
+           -0.05442090397105486,
+           -0.06928521303395803,
+           -0.08602238961420987,
+           -0.10464192146037114,
+           -0.1250876193372347,
+           -0.14723786594998406,
+           -0.17090769141073062,
+           -0.19585263185164056,
+           -0.2217742812081525,
+           -0.24832740178627677,
+           -0.27512841811852945,
+           -0.3017650818509263,
+           -0.3278070639281267,
+           -0.3528172049632978,
+           -0.37636313604972177,
+           -0.3980289708804273,
+           -0.4174267661972651,
+           -0.4342074514101277,
+           -0.4480709396370695,
+           -0.4587751511530291,
+           -0.46614370585106624,
+           -0.47007207319473715,
+           -0.47053200549496044,
+           -0.46757412226239353,
+           -0.4613285588339274,
+           -0.45200364032603974,
+           -0.43988259104252136,
+           -0.4253183385404673,
+           -0.4087265194145702,
+           -0.3905768393013322,
+           -0.3713829814947809,
+           -0.3516912958521205,
+           -0.3320685314119023,
+           -0.31308890154432334,
+           -0.2953207888543305,
+           -0.2793134079861678,
+           -0.2655837476396159,
+           -0.2546041084014667,
+           -0.24679054051300073,
+           -0.24249246571982344,
+           -0.24198374035399015,
+           -0.2454553834237003,
+           -0.2530101545349563,
+           -0.2646591228831072,
+           -0.280320321386477,
+           -0.299819530435226,
+           -0.32289318490371116,
+           -0.3491933472630808,
+           -0.37829464007325764,
+           -0.40970298404086236,
+           -0.44286594435425136,
+           -0.4771844492129253,
+           -0.5120256113068601,
+           -0.5467363562850582,
+           -0.5806575426377327,
+           -0.6131382453853512,
+           -0.6435498718170479,
+           -0.6712997813547043,
+           -0.69584409334557,
+           -0.7166993859212107,
+           -0.7334530155325598,
+           -0.7457718197345491,
+           -0.7534090044447569,
+           -0.7562090602955309,
+           -0.7541105997792396,
+           -0.7471470565030827,
+           -0.7354452388135632,
+           -0.7192217810798588,
+           -0.6987775857977772,
+           -0.6744903971790294,
+           -0.646805690871068,
+           -0.6162261038453521,
+           -0.5832996623451018,
+           -0.5486070932833402,
+           -0.5127485249712638,
+           -0.47632989605209397,
+           -0.43994939671767996,
+           -0.40418426358772397,
+           -0.36957823912243537,
+           -0.3366299883986082,
+           -0.30578274097155933,
+           -0.27741539400922494,
+           -0.25183527571522024,
+           -0.2292727261875587,
+           -0.2098776073357584,
+           -0.1937178054358006,
+           -0.18077974053444348,
+           -0.170970847446193,
+           -0.1641239447421194,
+           -0.16000336210318555,
+           -0.15831265383527532,
+           -0.15870368826376965,
+           -0.16078687007334547,
+           -0.16414222622773392,
+           -0.1683310665318885,
+           -0.17290791765070657,
+           -0.17743242475585264,
+           -0.18148091802692823,
+           -0.18465735188443635,
+           -0.1866033427895021,
+           -0.18700705623692265,
+           -0.18561072455158567,
+           -0.18221661347774343,
+           -0.17669129639635045,
+           -0.1689681392778232,
+           -0.15904794605193603,
+           -0.1469977617730195,
+           -0.1329478785705701,
+           -0.1170871356999018,
+           -0.09965664887561757,
+           -0.08094214437650021,
+           -0.061265109138696254,
+           -0.04097299830569517,
+           -0.020428765718055908,
+           -1.8865749344801865e-16
+          ],
+          [
+           0,
+           0.020639998083506333,
+           0.0402684817766162,
+           0.05857233294088259,
+           0.07528207329074252,
+           0.09018008624059803,
+           0.10310740795873044,
+           0.11396890121300997,
+           0.122736667532053,
+           0.12945159891003752,
+           0.13422301859730348,
+           0.1372264102191087,
+           0.13869928429255032,
+           0.13893527990340188,
+           0.13827664562445915,
+           0.13710528652719958,
+           0.13583260226925759,
+           0.1348883737566837,
+           0.1347089819472098,
+           0.13572526130452245,
+           0.1383503017373951,
+           0.14296751625537354,
+           0.14991928693675324,
+           0.15949648922825613,
+           0.1719291743716387,
+           0.18737866236508538,
+           0.20593126398152103,
+           0.22759381081070057,
+           0.2522911280393285,
+           0.27986553682521675,
+           0.3100784228416601,
+           0.34261385611395895,
+           0.37708419592054127,
+           0.413037564566031,
+           0.4499670265008813,
+           0.48732126574736745,
+           0.5245165159881418,
+           0.56094946495517,
+           0.5960108287538752,
+           0.6290992731353291,
+           0.6596353479726622,
+           0.6870750985972102,
+           0.7109230232949292,
+           0.7307440600403755,
+           0.7461743071390805,
+           0.7569302113510383,
+           0.7628159925885487,
+           0.7637291155668493,
+           0.7596636648382622,
+           0.7507115293435034,
+           0.7370613547591767,
+           0.7189952752383602,
+           0.6968834893309072,
+           0.6711767966325025,
+           0.6423972607807605,
+           0.6111272095917354,
+           0.5779968233041607,
+           0.5436705960864674,
+           0.5088329833236703,
+           0.4741735670650763,
+           0.44037208388999094,
+           0.4080836630432835,
+           0.377924617914504,
+           0.350459120896978,
+           0.3261870706827975,
+           0.30553343263625665,
+           0.2888392977343144,
+           0.27635486452515695,
+           0.26823450263578175,
+           0.2645340066766196,
+           0.26521009715703614,
+           0.2701221715132021,
+           0.2790362548627702,
+           0.29163104794071193,
+           0.3075059201054757,
+           0.3261906495372484,
+           0.3471566718889641,
+           0.3698295636824483,
+           0.3936024585074775,
+           0.4178500732547789,
+           0.4419430086863938,
+           0.46526198391481793,
+           0.4872116679203447,
+           0.5072337829745863,
+           0.5248191744464908,
+           0.5395185684415897,
+           0.5509517723813733,
+           0.558815113120028,
+           0.5628869515305717,
+           0.5630311605644873,
+           0.5591985044012252,
+           0.5514259081991637,
+           0.5398336598516946,
+           0.5246206357578513,
+           0.5060576906879921,
+           0.4844793961788297,
+           0.4602743514408479,
+           0.43387432453895636,
+           0.4057425087938047,
+           0.3763611992919437,
+           0.34621920661529865,
+           0.3157993291246716,
+           0.28556620127879967,
+           0.25595482366198175,
+           0.22736006094989836,
+           0.20012736747563215,
+           0.17454496705359093,
+           0.15083767512541987,
+           0.1291625080947905,
+           0.10960617801636079,
+           0.09218452178357191,
+           0.0768438638617314,
+           0.06346426170380234,
+           0.05186453452664183,
+           0.04180893033726193,
+           0.033015244135552735,
+           0.02516416313796637,
+           0.017909583598180595,
+           0.010889619131014994,
+           0.0037380029933943974,
+           -0.00390442302260115,
+           -0.01237844233109575,
+           -0.021995723134561992,
+           -0.033028893226960565,
+           -0.04570269813768762,
+           -0.06018648258065676,
+           -0.07658820083521849,
+           -0.09495012203481065,
+           -0.11524635237839566,
+           -0.13738224912110233,
+           -0.16119575203761324,
+           -0.18646060812955076,
+           -0.21289141593153746,
+           -0.24015036811331528,
+           -0.26785552638793486,
+           -0.29559042215601444,
+           -0.3229147408789134,
+           -0.3493758187871141,
+           -0.3745206579511719,
+           -0.3979081505584731,
+           -0.41912119585229274,
+           -0.4377783938079296,
+           -0.45354500825115407,
+           -0.46614290857340146,
+           -0.4753592230762062,
+           -0.48105346770785024,
+           -0.48316295078891813,
+           -0.4817062963571345,
+           -0.4767849749603329,
+           -0.46858277994825187,
+           -0.45736323833969666,
+           -0.44346499690430347,
+           -0.42729527491431957,
+           -0.4093215238237134,
+           -0.39006147969898103,
+           -0.3700718354152322,
+           -0.34993579540557845,
+           -0.3302498052066897,
+           -0.31160977042826343,
+           -0.2945970945123533,
+           -0.2797648713512495,
+           -0.26762456730913203,
+           -0.25863351745510516,
+           -0.2531835430785779,
+           -0.25159097223525767,
+           -0.2540883127641038,
+           -0.26081778869669253,
+           -0.27182690717920094,
+           -0.28706617500387016,
+           -0.30638903276729323,
+           -0.32955402178006576,
+           -0.35622914543553313,
+           -0.3859983341084688,
+           -0.4183698720840675,
+           -0.45278659775073665,
+           -0.4886376454845904,
+           -0.5252714603583568,
+           -0.5620097859378461,
+           -0.5981623017434483,
+           -0.6330415710351563,
+           -0.6659779518202174,
+           -0.6963341245758852,
+           -0.7235188991147452,
+           -0.7469999800810231,
+           -0.7663153953390586,
+           -0.7810833233962797,
+           -0.7910100942156789,
+           -0.7958961813850323,
+           -0.7956400515582549,
+           -0.7902397881991016,
+           -0.7797924596926827,
+           -0.7644912555538155,
+           -0.7446204674463612,
+           -0.720548442745743,
+           -0.6927186861884768,
+           -0.661639328598585,
+           -0.627871219710463,
+           -0.5920149338045229,
+           -0.5546970014760497,
+           -0.5165556977845432,
+           -0.47822672588543874,
+           -0.44032913583230504,
+           -0.4034518105631994,
+           -0.3681408353604965,
+           -0.33488804370770175,
+           -0.3041210020554894,
+           -0.2761946593208252,
+           -0.25138484489896057,
+           -0.22988375262015243,
+           -0.2117974985869144,
+           -0.1971457894143117,
+           -0.18586368534103637,
+           -0.1778053912712964,
+           -0.17274995931668016,
+           -0.17040874005231155,
+           -0.17043437762157737,
+           -0.17243110704843456,
+           -0.17596608154166116,
+           -0.1805814339411286,
+           -0.18580676032755875,
+           -0.19117170557159088,
+           -0.19621833041525005,
+           -0.2005129475377193,
+           -0.20365712973556566,
+           -0.20529761642843386,
+           -0.2051348745837115,
+           -0.20293010606781342,
+           -0.19851053445819894,
+           -0.19177284944315953,
+           -0.18268473495002688,
+           -0.17128445685945254,
+           -0.1576785363257835,
+           -0.1420375840638684,
+           -0.12459041823579503,
+           -0.10561663258551438,
+           -0.08543782111677371,
+           -0.06440769989288067,
+           -0.042901394594110874,
+           -0.021304183595991188,
+           -1.9595039588423992e-16
+          ],
+          [
+           0,
+           0.02124208735188127,
+           0.04127708823094549,
+           0.059800036561435205,
+           0.07655638528449761,
+           0.0913497979746474,
+           0.10404832885259338,
+           0.1145888207502926,
+           0.12297939686312187,
+           0.12929997165315527,
+           0.1337007577926208,
+           0.13639879825247384,
+           0.13767260422400027,
+           0.13785502920251513,
+           0.13732455600014276,
+           0.13649521550711657,
+           0.1358053926146338,
+           0.13570580490947814,
+           0.13664696277323576,
+           0.1390664347678939,
+           0.14337624926007142,
+           0.14995076192781465,
+           0.15911530911633903,
+           0.17113594918170338,
+           0.18621056840816447,
+           0.2044615954241944,
+           0.22593052907127562,
+           0.25057444035554405,
+           0.27826456052785736,
+           0.3087870156944815,
+           0.34184571493883076,
+           0.3770673450623778,
+           0.4140083720719536,
+           0.4521638987741345,
+           0.49097818055607634,
+           0.5298565588231953,
+           0.5681785347012472,
+           0.6053116754273032,
+           0.6406260231208851,
+           0.673508660930266,
+           0.7033780852790987,
+           0.729698035276809,
+           0.7519904412718625,
+           0.7698471737773457,
+           0.7829403011341659,
+           0.7910305986541412,
+           0.7939740927788999,
+           0.7917264700169567,
+           0.7843452309610088,
+           0.7719895233129079,
+           0.7549176432494434,
+           0.7334822502968829,
+           0.708123395782466,
+           0.679359517554325,
+           0.6477766027192137,
+           0.6140157644378903,
+           0.5787595172543274,
+           0.5427170670732893,
+           0.5066089559629069,
+           0.47115141785183084,
+           0.43704080852095784,
+           0.4049384718739537,
+           0.3754563943391452,
+           0.34914398065165025,
+           0.32647625764002053,
+           0.30784377864377377,
+           0.29354446064498024,
+           0.28377754009654205,
+           0.27863978289575136,
+           0.27812403021588694,
+           0.2821201062805457,
+           0.2904180580000697,
+           0.30271364105393206,
+           0.3186159138428663,
+           0.3376567510408275,
+           0.35930204345416705,
+           0.38296431163238626,
+           0.40801642811749755,
+           0.4338061181476228,
+           0.4596708916403043,
+           0.48495305076807155,
+           0.5090144175902073,
+           0.5312504349940997,
+           0.5511033113885775,
+           0.5680739047352392,
+           0.5817320739623215,
+           0.5917252647602619,
+           0.5977851412316357,
+           0.5997321237492819,
+           0.5974777454474505,
+           0.5910247937378794,
+           0.5804652577679624,
+           0.565976156472961,
+           0.5478133734925179,
+           0.5263036734529232,
+           0.5018351177770412,
+           0.47484613620588123,
+           0.4458135416744088,
+           0.4152398003194012,
+           0.3836398846328544,
+           0.3515280457325018,
+           0.31940484023014276,
+           0.2877447382785499,
+           0.2569846223181268,
+           0.22751346127780228,
+           0.19966341315516123,
+           0.1737025708279371,
+           0.1498295226068589,
+           0.12816985153272292,
+           0.10877464695495828,
+           0.09162104978369492,
+           0.07661480030118302,
+           0.06359470587727332,
+           0.0523388966573758,
+           0.04257269152108478,
+           0.033977855497127375,
+           0.026202994398762523,
+           0.01887480360231688,
+           0.011609866353015579,
+           0.004026683285067569,
+           -0.004242390672234273,
+           -0.01353962302938022,
+           -0.02417110409686978,
+           -0.03639696195395585,
+           -0.05042285653241544,
+           -0.06639298404138361,
+           -0.08438478371810881,
+           -0.1044054946811769,
+           -0.12639066260641113,
+           -0.15020464525787644,
+           -0.17564311387092194,
+           -0.2024374953194999,
+           -0.23026124922658783,
+           -0.2587378259836299,
+           -0.2874501072581355,
+           -0.31595109111936504,
+           -0.34377555040897595,
+           -0.3704523662872105,
+           -0.39551721968647807,
+           -0.4185253122065649,
+           -0.4390637850927521,
+           -0.45676351044556257,
+           -0.47130994260382175,
+           -0.48245273939863004,
+           -0.4900138921718558,
+           -0.4938941393788832,
+           -0.49407748037164173,
+           -0.4906336525564339,
+           -0.4837184853910224,
+           -0.4735720973819537,
+           -0.4605149560579464,
+           -0.4449418744892932,
+           -0.42731406995997984,
+           -0.40814945957768484,
+           -0.38801141269412975,
+           -0.3674962198704187,
+           -0.34721957175209933,
+           -0.3278023677622926,
+           -0.3098561932974918,
+           -0.2939688146297706,
+           -0.2806900426946137,
+           -0.27051831029968143,
+           -0.2638882921635941,
+           -0.2611598739322756,
+           -0.26260874547200586,
+           -0.2684188560396984,
+           -0.27867692528903726,
+           -0.29336915554091275,
+           -0.3123802385052422,
+           -0.335494694959156,
+           -0.3624005300960597,
+           -0.39269513172288556,
+           -0.4258932845561268,
+           -0.46143712287057065,
+           -0.4987077969369313,
+           -0.5370385871940112,
+           -0.5757291649557483,
+           -0.6140606705174583,
+           -0.6513112594863758,
+           -0.6867717565139532,
+           -0.7197610526406807,
+           -0.7496408882553527,
+           -0.7758296780823348,
+           -0.7978150572937076,
+           -0.8151648582473948,
+           -0.8275362647371779,
+           -0.834682934095242,
+           -0.8364599259533544,
+           -0.832826328763532,
+           -0.8238455300285724,
+           -0.8096831322606858,
+           -0.790602572607478,
+           -0.7669585584981046,
+           -0.7391884832462805,
+           -0.707802033049248,
+           -0.6733692390926734,
+           -0.6365072644902837,
+           -0.5978662446879917,
+           -0.5581145210555447,
+           -0.5179236201770899,
+           -0.4779533355431944,
+           -0.4388372638599789,
+           -0.40116913515913155,
+           -0.3654902546583969,
+           -0.33227834542965007,
+           -0.30193804511254774,
+           -0.27479326806677856,
+           -0.2510815975325467,
+           -0.23095082173533082,
+           -0.21445767468690918,
+           -0.20156878801994585,
+           -0.19216380589567228,
+           -0.18604056218478696,
+           -0.1829221690430384,
+           -0.18246581991593522,
+           -0.18427306904082358,
+           -0.18790131466859283,
+           -0.19287618534663478,
+           -0.19870450835947837,
+           -0.2048875272922933,
+           -0.21093403194078233,
+           -0.21637306850466212,
+           -0.22076591102595144,
+           -0.2237169960154167,
+           -0.22488355060065085,
+           -0.22398367959321527,
+           -0.22080271771037033,
+           -0.2151976987567928,
+           -0.20709984271418008,
+           -0.19651501315530187,
+           -0.18352214989091897,
+           -0.1682697339465987,
+           -0.15097039253481834,
+           -0.13189379936133247,
+           -0.1113580691834103,
+           -0.08971988392536788,
+           -0.06736361988955962,
+           -0.044689770870207535,
+           -0.022102979650572285,
+           -2.0247989737671387e-16
+          ],
+          [
+           0,
+           0.021754031455992157,
+           0.04210304328881997,
+           0.06075487832776835,
+           0.07747454402596088,
+           0.09209143207469454,
+           0.10450474999733911,
+           0.11468701395862586,
+           0.12268550243959056,
+           0.12862162348688666,
+           0.13268820260340836,
+           0.1351447526272565,
+           0.13631083977101313,
+           0.13655771002139058,
+           0.13629838605796918,
+           0.13597648556723607,
+           0.13605404626320938,
+           0.1369986701938545,
+           0.1392703193074324,
+           0.1433081052657344,
+           0.14951741882239353,
+           0.158257737652034,
+           0.16983143645753707,
+           0.1844738998522977,
+           0.20234520747408136,
+           0.22352362279322313,
+           0.2480010730622387,
+           0.2756807589008132,
+           0.30637697932965796,
+           0.33981720296472423,
+           0.3756463599288577,
+           0.4134332732296899,
+           0.4526790942833979,
+           0.4928275562869144,
+           0.5332768125352926,
+           0.5733925857196925,
+           0.6125223197631551,
+           0.6500099987333443,
+           0.685211278508031,
+           0.7175085666540044,
+           0.7463256846940087,
+           0.7711417546394852,
+           0.7915039681975415,
+           0.8070389220383183,
+           0.8174622353440991,
+           0.8225862057694182,
+           0.8223253059613672,
+           0.8166993738083123,
+           0.8058344043651657,
+           0.7899609086114735,
+           0.769409862440241,
+           0.7446063271284794,
+           0.7160608785902932,
+           0.6843590355877089,
+           0.6501489254774357,
+           0.6141274688156121,
+           0.5770254001772329,
+           0.5395914709858233,
+           0.5025762002908142,
+           0.46671555077681737,
+           0.4327149095573283,
+           0.4012337464344783,
+           0.37287130645911765,
+           0.34815366918441276,
+           0.3275224745644301,
+           0.31132557579577563,
+           0.2998098335007291,
+           0.29311621462254656,
+           0.29127730449101946,
+           0.2942172830568052,
+           0.3017543576859834,
+           0.31360558657838206,
+           0.3293939702432227,
+           0.34865763490942075,
+           0.37086088256472693,
+           0.3954068386984432,
+           0.4216513918195884,
+           0.44891808932532445,
+           0.47651363300710553,
+           0.5037436049057004,
+           0.5299280506476294,
+           0.5544165528798507,
+           0.576602441808937,
+           0.595935812769182,
+           0.6119350516053776,
+           0.6241966066804788,
+           0.6324027905510403,
+           0.6363274436881685,
+           0.6358393458292398,
+           0.6309033163032505,
+           0.621579001597808,
+           0.6080174051199971,
+           0.5904552691473778,
+           0.5692074710136971,
+           0.5446576433482464,
+           0.5172472705189259,
+           0.4874635492853075,
+           0.45582633018092594,
+           0.422874476629641,
+           0.38915199077633983,
+           0.35519425820762435,
+           0.3215147581026589,
+           0.2885925710576887,
+           0.2568609942550607,
+           0.2266975433898517,
+           0.1984155836063265,
+           0.17225778858510868,
+           0.14839157896002123,
+           0.1269066396503348,
+           0.1078145617775874,
+           0.09105059996043115,
+           0.07647748133196983,
+           0.06389114997505917,
+           0.05302828094807548,
+           0.043575352922561546,
+           0.035179028809386795,
+           0.02745756060641874,
+           0.020012908888467292,
+           0.01244324952456031,
+           0.004355530792282806,
+           -0.004622256704472732,
+           -0.014829427005863358,
+           -0.026561875983181105,
+           -0.04006257766543989,
+           -0.05551355679989639,
+           -0.07302955629760322,
+           -0.09265357413102418,
+           -0.11435439564266382,
+           -0.1380261953226519,
+           -0.1634902282339825,
+           -0.1904985767720148,
+           -0.21873986472163728,
+           -0.24784679898489814,
+           -0.2774053512050871,
+           -0.3069653480363028,
+           -0.33605220111037554,
+           -0.36417947680173945,
+           -0.3908619824831956,
+           -0.41562903071097473,
+           -0.438037536081617,
+           -0.45768460155736834,
+           -0.4742192618332645,
+           -0.4873530705711444,
+           -0.49686924559409706,
+           -0.5026301207580376,
+           -0.5045826943486222,
+           -0.5027621104803188,
+           -0.4972929609493925,
+           -0.4883883490519023,
+           -0.47634671268001316,
+           -0.46154646016667306,
+           -0.444438527460118,
+           -0.4255370178981509,
+           -0.4054081347978873,
+           -0.38465766104920684,
+           -0.3639172777905125,
+           -0.3438300450923417,
+           -0.32503539058997133,
+           -0.30815396659419025,
+           -0.2937727419816757,
+           -0.2824306919516899,
+           -0.2746054365851068,
+           -0.2707011583269203,
+           -0.2710380995208328,
+           -0.27584390464366304,
+           -0.285247028793403,
+           -0.29927238531790284,
+           -0.3178393524105048,
+           -0.34076220233393967,
+           -0.3677529590322633,
+           -0.3984266316654313,
+           -0.43230871447487806,
+           -0.46884478875911306,
+           -0.5074120119439882,
+           -0.5473322330185465,
+           -0.5878864340968619,
+           -0.6283301655299931,
+           -0.667909617626862,
+           -0.7058779562496287,
+           -0.7415115427203923,
+           -0.7741256607838843,
+           -0.8030893847645542,
+           -0.8278392432621832,
+           -0.8478913612585751,
+           -0.8628517996659425,
+           -0.8724248542551322,
+           -0.876419124514151,
+           -0.8747512161199128,
+           -0.8674469970643861,
+           -0.854640385687351,
+           -0.836569707514385,
+           -0.8135717154533966,
+           -0.7860734231643546,
+           -0.7545819529431678,
+           -0.7196726460030769,
+           -0.6819757234702758,
+           -0.6421618197607575,
+           -0.6009267354734795,
+           -0.5589757739165052,
+           -0.5170080334825792,
+           -0.47570102713219514,
+           -0.43569599027203837,
+           -0.3975842196026983,
+           -0.36189475853434033,
+           -0.32908371021735955,
+           -0.2995254179773031,
+           -0.2735057060131667,
+           -0.25121732178695244,
+           -0.23275766688013177,
+           -0.2181288465762971,
+           -0.20724001144845222,
+           -0.19991190819252508,
+           -0.19588350323731377,
+           -0.19482049259626852,
+           -0.19632546623574457,
+           -0.1999494560215732,
+           -0.20520456402390408,
+           -0.21157734338791337,
+           -0.21854258770035825,
+           -0.22557717717657244,
+           -0.23217363122021023,
+           -0.23785302690904464,
+           -0.24217696145632447,
+           -0.24475826319866806,
+           -0.24527018947988707,
+           -0.24345389006523901,
+           -0.23912396040299208,
+           -0.2321719589865864,
+           -0.22256781599343292,
+           -0.21035911494537762,
+           -0.19566828397150798,
+           -0.17868778697258386,
+           -0.159673456233922,
+           -0.13893615552013872,
+           -0.11683200521684563,
+           -0.09375143759327845,
+           -0.07010737983045996,
+           -0.046322884351881546,
+           -0.022818539661676046,
+           -2.0819482253951928e-16
+          ],
+          [
+           0,
+           0.022172635657690284,
+           0.04274265563948582,
+           0.061435455640987034,
+           0.07804020905827957,
+           0.09241637259760928,
+           0.10449823463994462,
+           0.11429737892364675,
+           0.12190299038171135,
+           0.1274799861943162,
+           0.13126501186744627,
+           0.1335603979846977,
+           0.1347262267843747,
+           0.1351707075274662,
+           0.13533910447534947,
+           0.13570150004379647,
+           0.1367397073489249,
+           0.13893367009516241,
+           0.1427477029568654,
+           0.1486169318691795,
+           0.15693429078903953,
+           0.16803841956144963,
+           0.18220278680455004,
+           0.1996263327056941,
+           0.22042589000496987,
+           0.24463059812902604,
+           0.2721784764928607,
+           0.30291526961966475,
+           0.33659562026122625,
+           0.37288656853650887,
+           0.41137331669195015,
+           0.45156714188147523,
+           0.49291528479799707,
+           0.534812591429755,
+           0.5766146399360325,
+           0.6176520457811945,
+           0.6572456068201439,
+           0.6947219267972066,
+           0.7294291413071099,
+           0.7607523650569504,
+           0.7881284834206602,
+           0.8110599247198298,
+           0.8291270720944715,
+           0.8419990047191659,
+           0.8494422967388919,
+           0.8513276477173962,
+           0.8476341695124282,
+           0.838451210077296,
+           0.8239776533855271,
+           0.8045186950546896,
+           0.7804801538326468,
+           0.7523604384234087,
+           0.7207403457181618,
+           0.6862709189728887,
+           0.649659641549385,
+           0.6116552823546042,
+           0.5730317420769723,
+           0.5345712739148165,
+           0.4970474681128154,
+           0.46120839587865914,
+           0.4277603049840575,
+           0.3973522466354054,
+           0.3705619913347177,
+           0.34788356096979733,
+           0.3297166660140067,
+           0.31635829141321914,
+           0.30799662359327445,
+           0.3047074552809641,
+           0.30645314585282823,
+           0.31308415414506957,
+           0.3243430995542987,
+           0.33987124731912643,
+           0.35921725655370496,
+           0.38184797629758527,
+           0.4071610268434831,
+           0.43449886206604793,
+           0.4631639744010818,
+           0.49243487833195854,
+           0.5215824913401808,
+           0.5498865236627698,
+           0.5766514900346184,
+           0.6012219678107547,
+           0.6229967461628407,
+           0.6414415399046312,
+           0.6560999781911636,
+           0.6666026219335989,
+           0.6726738131848384,
+           0.6741362137482366,
+           0.6709129475003177,
+           0.6630273199786288,
+           0.6506001482061301,
+           0.6338447920365098,
+           0.6130600340739322,
+           0.5886210070756006,
+           0.5609684144158299,
+           0.5305963295372913,
+           0.498038893359302,
+           0.4638562535587932,
+           0.42862010589413074,
+           0.39289920493005626,
+           0.35724520949495603,
+           0.32217921704044933,
+           0.2881793210865985,
+           0.25566949765189345,
+           0.22501009071960848,
+           0.1964901243028088,
+           0.17032162062482065,
+           0.14663605155308257,
+           0.12548299504090563,
+           0.1068310113454597,
+           0.09057069664107574,
+           0.0765198157759704,
+           0.06443036273508064,
+           0.053997348209572485,
+           0.04486906976977865,
+           0.036658582594185765,
+           0.028956058462919314,
+           0.02134169853568523,
+           0.01339885185373156,
+           0.004726986868391541,
+           -0.005045832284917677,
+           -0.016251299696855064,
+           -0.02917036476457031,
+           -0.04402415545246316,
+           -0.06096657349676902,
+           -0.080078763745341,
+           -0.10136561103095958,
+           -0.12475436519904032,
+           -0.1500954394860196,
+           -0.17716537077768796,
+           -0.20567187380421148,
+           -0.23526086648350497,
+           -0.26552529180038165,
+           -0.2960155141240021,
+           -0.3262510259314527,
+           -0.355733165593351,
+           -0.3839585190956771,
+           -0.41043265903985704,
+           -0.43468386349370836,
+           -0.4562764555529434,
+           -0.47482341188352056,
+           -0.4899979048874131,
+           -0.5015434680813631,
+           -0.5092825071974608,
+           -0.5131229196024651,
+           -0.5130626309051924,
+           -0.5091919089368074,
+           -0.5016933703777205,
+           -0.49083965280018016,
+           -0.4769887833678246,
+           -0.46057733342475604,
+           -0.4421115042686372,
+           -0.4221563421305241,
+           -0.4013233284547339,
+           -0.3802566337731224,
+           -0.3596183587316699,
+           -0.3400731132542803,
+           -0.3222723037133131,
+           -0.3068385078222921,
+           -0.2943503175004989,
+           -0.28532802113834205,
+           -0.28022047870464983,
+           -0.27939351639735366,
+           -0.283120132679506,
+           -0.2915727653970629,
+           -0.30481782125839585,
+           -0.3228126154398023,
+           -0.3454048117656274,
+           -0.37233439419124126,
+           -0.4032381396485332,
+           -0.43765650217915486,
+           -0.47504276015152785,
+           -0.5147742236578452,
+           -0.5561652492584694,
+           -0.5984817653093264,
+           -0.640956974253701,
+           -0.6828078693906556,
+           -0.7232521834614404,
+           -0.7615253754224364,
+           -0.7968972602740626,
+           -0.82868789483243,
+           -0.8562823496750172,
+           -0.8791440237447498,
+           -0.896826192622255,
+           -0.9089815234349321,
+           -0.915369337742637,
+           -0.9158604573458564,
+           -0.910439525497411,
+           -0.8992047560620017,
+           -0.8823651242966815,
+           -0.860235073632106,
+           -0.8332268716428158,
+           -0.801840803876388,
+           -0.7666534450203024,
+           -0.7283042917919367,
+           -0.6874810798575012,
+           -0.6449041371088753,
+           -0.6013101470368521,
+           -0.557435708231557,
+           -0.5140010789364858,
+           -0.4716944890336932,
+           -0.4311573860282725,
+           -0.3929709569419451,
+           -0.3576442351468014,
+           -0.32560406090037003,
+           -0.29718711769240647,
+           -0.27263421464716336,
+           -0.2520869294337884,
+           -0.23558666780735296,
+           -0.22307613647913185,
+           -0.21440316696595615,
+           -0.20932677085138818,
+           -0.2075252529138556,
+           -0.20860615916323172,
+           -0.2121177931858878,
+           -0.2175619973914015,
+           -0.22440786667211332,
+           -0.2321060413259865,
+           -0.24010321433918852,
+           -0.24785648554020118,
+           -0.2548472017560853,
+           -0.26059393772810874,
+           -0.2646642967588648,
+           -0.2666852422328819,
+           -0.26635171044741485,
+           -0.2634333006025525,
+           -0.2577788881723106,
+           -0.2493190619311326,
+           -0.2380663412735106,
+           -0.22411318771323405,
+           -0.2076278811378033,
+           -0.1888483860942264,
+           -0.1680743847178235,
+           -0.14565769959541278,
+           -0.12199137070648008,
+           -0.09749768458666803,
+           -0.07261548015642824,
+           -0.04778707359790216,
+           -0.023445153799816,
+           -2.1305333457443468e-16
+          ],
+          [
+           0,
+           0.022495851472507048,
+           0.04319461645292752,
+           0.06184401203520992,
+           0.07826191294968537,
+           0.0923420028908107,
+           0.10405730936433585,
+           0.11346152147769747,
+           0.12068804788251393,
+           0.1259468310388868,
+           0.12951899261234284,
+           0.13174944164725136,
+           0.13303763074135846,
+           0.13382669441116843,
+           0.134591246938568,
+           0.13582415312275875,
+           0.13802261359956386,
+           0.14167392600114354,
+           0.1472412936974906,
+           0.15515005490012215,
+           0.1657746964677783,
+           0.1794269990211787,
+           0.19634563336989816,
+           0.2166874934233298,
+           0.24052100855100503,
+           0.26782162981314395,
+           0.29846963079882216,
+           0.33225030631625657,
+           0.3688565923051299,
+           0.40789406957497726,
+           0.44888825383231756,
+           0.4912940164462275,
+           0.534506925971542,
+           0.5778762509691662,
+           0.62071932138231,
+           0.6623369097429211,
+           0.7020292657124406,
+           0.7391124186218251,
+           0.7729343532641779,
+           0.802890664473409,
+           0.8284393060188172,
+           0.8491140688425902,
+           0.8645364522138865,
+           0.8744256282937191,
+           0.8786062450154719,
+           0.8770138630162203,
+           0.8696978783733071,
+           0.8568218427480536,
+           0.8386611547564733,
+           0.8155981594571001,
+           0.7881147552267959,
+           0.7567826674595521,
+           0.7222516049960316,
+           0.6852355665867705,
+           0.6464976097464367,
+           0.6068334319612696,
+           0.5670541434393803,
+           0.5279686307211843,
+           0.4903659209943039,
+           0.45499795761849976,
+           0.4225631881374462,
+           0.39369134715379395,
+           0.3689297883271024,
+           0.34873168310179,
+           0.33344635947428725,
+           0.32331200324219356,
+           0.3184508879813417,
+           0.3188672398373009,
+           0.3244477805606753,
+           0.33496492858570814,
+           0.3500825748973263,
+           0.36936428948589833,
+           0.39228375683183286,
+           0.4182371864847584,
+           0.44655739867204813,
+           0.4765292461020423,
+           0.5074060026499261,
+           0.5384263281556427,
+           0.5688314066281146,
+           0.5978818530084901,
+           0.6248739913263454,
+           0.6491551243746467,
+           0.6701374414837439,
+           0.6873102459193025,
+           0.7002502259835923,
+           0.7086295429982116,
+           0.7122215637641093,
+           0.7109041234781934,
+           0.7046602659862925,
+           0.6935764701622603,
+           0.6778384325933368,
+           0.657724536109545,
+           0.6335971895606199,
+           0.605892275248186,
+           0.5751069853176131,
+           0.541786366111525,
+           0.5065089190746425,
+           0.46987162757045037,
+           0.432474790437607,
+           0.3949070450240774,
+           0.35773095477419764,
+           0.32146951943106705,
+           0.28659394000940713,
+           0.25351293656863466,
+           0.22256387535243263,
+           0.1940059141213048,
+           0.16801532170475345,
+           0.14468307128056299,
+           0.12401474808156354,
+           0.10593275262116608,
+           0.09028072162178583,
+           0.07683003210856977,
+           0.06528820102138529,
+           0.05530894453472611,
+           0.046503619266053765,
+           0.038453732749992246,
+           0.030724183828305274,
+           0.022876875619272635,
+           0.014484334930033158,
+           0.0051429725751725225,
+           -0.005514370958983146,
+           -0.017806930971658454,
+           -0.031995883872484365,
+           -0.04827584547673059,
+           -0.06676823271446708,
+           -0.08751667060442175,
+           -0.1104845730491693,
+           -0.1355549693638586,
+           -0.16253258989186267,
+           -0.19114816507241866,
+           -0.22106483440418057,
+           -0.25188650636543203,
+           -0.2831679589148118,
+           -0.3144264240159304,
+           -0.34515435988462784,
+           -0.3748330823676151,
+           -0.4029469028585634,
+           -0.4289974050677473,
+           -0.4525174871866221,
+           -0.4730847996982054,
+           -0.4903342222091314,
+           -0.5039690449146461,
+           -0.5137705511193751,
+           -0.5196057358743923,
+           -0.5214329413072435,
+           -0.519305240494435,
+           -0.5133714574873847,
+           -0.5038747699699925,
+           -0.491148901535136,
+           -0.47561197121086934,
+           -0.45775812713011876,
+           -0.43814714763693813,
+           -0.4173922452418943,
+           -0.39614635536692905,
+           -0.3750872315793074,
+           -0.3549017009945881,
+           -0.3362694569095305,
+           -0.31984677989932775,
+           -0.30625058319763465,
+           -0.29604317302786276,
+           -0.28971809976579194,
+           -0.2876874517211693,
+           -0.29027091049469633,
+           -0.2976868460787547,
+           -0.31004568210554484,
+           -0.3273457080590145,
+           -0.34947145715692607,
+           -0.3761947073900803,
+           -0.40717810036977314,
+           -0.44198130971658456,
+           -0.4800696292629989,
+           -0.5208247928444861,
+           -0.56355778335369,
+           -0.607523340358892,
+           -0.6519358341306575,
+           -0.6959861404012014,
+           -0.7388591254267887,
+           -0.7797513355484912,
+           -0.8178884798344409,
+           -0.8525422986831245,
+           -0.8830464253742615,
+           -0.9088108711341414,
+           -0.9293347967658572,
+           -0.9442172744938371,
+           -0.95316579139998,
+           -0.9560022995241884,
+           -0.9526666760584437,
+           -0.9432175186598237,
+           -0.9278302642446656,
+           -0.9067926831619199,
+           -0.8804978628333782,
+           -0.8494348542805088,
+           -0.8141772099921291,
+           -0.7753696909906237,
+           -0.7337134635327398,
+           -0.6899501406087893,
+           -0.6448450494497195,
+           -0.5991701229972168,
+           -0.5536868203494216,
+           -0.5091294784137776,
+           -0.4661894844708325,
+           -0.42550063740948896,
+           -0.38762603459742323,
+           -0.35304678247891474,
+           -0.3221527830220963,
+           -0.29523579621776735,
+           -0.2724849222556177,
+           -0.25398458717637035,
+           -0.23971505420261832,
+           -0.22955542111022037,
+           -0.22328900344166797,
+           -0.22061094557376418,
+           -0.22113784805295966,
+           -0.2244191515146593,
+           -0.22994997608014728,
+           -0.23718508138079514,
+           -0.2455535871051914,
+           -0.25447407779943054,
+           -0.26336970894531825,
+           -0.27168293423078277,
+           -0.2788894863074002,
+           -0.2845112648611401,
+           -0.2881278159367559,
+           -0.289386124372659,
+           -0.2880084859480088,
+           -0.28379827627424525,
+           -0.27664348829699437,
+           -0.2665179681207479,
+           -0.25348033826462807,
+           -0.23767065690343495,
+           -0.2193049196454169,
+           -0.1986675654872501,
+           -0.17610219938279584,
+           -0.15200078909040216,
+           -0.12679163249034994,
+           -0.10092642242581717,
+           -0.07486675854741327,
+           -0.049070469075909805,
+           -0.023978109509973256,
+           -2.1702366992562102e-16
+          ],
+          [
+           0,
+           0.02272282655911415,
+           0.04346006456362582,
+           0.06198648140073539,
+           0.07815304792430981,
+           0.09189159892424037,
+           0.10321723062803535,
+           0.11222836488572446,
+           0.11910447057097343,
+           0.12410149393726723,
+           0.12754510964486107,
+           0.12982196139856642,
+           0.13136911415309258,
+           0.1326619873009639,
+           0.13420107894588945,
+           0.13649782423876955,
+           0.14005995496644988,
+           0.14537674250370586,
+           0.15290451146824396,
+           0.16305280680111042,
+           0.17617158262217802,
+           0.19253975741873014,
+           0.21235544748784174,
+           0.23572814986639198,
+           0.26267309824545687,
+           0.29310796175642256,
+           0.3268519983616625,
+           0.36362771332677657,
+           0.40306501041849846,
+           0.44470776062954,
+           0.48802265194962857,
+           0.5324101255162955,
+           0.5772171498513082,
+           0.6217515371707574,
+           0.6652974651563427,
+           0.7071318351260479,
+           0.7465410740775302,
+           0.7828379742096344,
+           0.8153781596321771,
+           0.843575776180957,
+           0.8669180164434069,
+           0.884978117902633,
+           0.8974265069175923,
+           0.9040398042447033,
+           0.904707457937588,
+           0.899435825524899,
+           0.888349588000637,
+           0.871690441891334,
+           0.8498130809352923,
+           0.8231785441256729,
+           0.7923450704352094,
+           0.7579566608975341,
+           0.72072960438697,
+           0.6814372730468388,
+           0.6408935356445946,
+           0.5999351711363846,
+           0.559403689563031,
+           0.5201269824570343,
+           0.4829012298381605,
+           0.44847348548466154,
+           0.41752534661099716,
+           0.39065808873315966,
+           0.3683796119712909,
+           0.3510935021631121,
+           0.33909045998214044,
+           0.3325422949918201,
+           0.3314986205895184,
+           0.3358863215868391,
+           0.3455118002975752,
+           0.36006594106461254,
+           0.379131668755753,
+           0.4021939154605214,
+           0.42865175291314767,
+           0.45783239742490617,
+           0.4890067505582088,
+           0.5214061034640245,
+           0.5542396065789329,
+           0.5867120898599605,
+           0.618041812306999,
+           0.647477723318437,
+           0.6743158323288305,
+           0.6979143068230621,
+           0.7177069516056578,
+           0.7332147632993943,
+           0.7440553024235341,
+           0.7499496798514144,
+           0.7507270136147121,
+           0.7463262744391765,
+           0.7367955025184117,
+           0.7222884422741724,
+           0.7030587046298483,
+           0.6794516260942504,
+           0.6518940492493026,
+           0.62088229870564,
+           0.5869686690296658,
+           0.5507467755267589,
+           0.512836144262593,
+           0.47386643371513626,
+           0.43446168660805323,
+           0.3952250066619601,
+           0.35672404134192665,
+           0.31947762855107,
+           0.2839439332298146,
+           0.25051035979677444,
+           0.21948547933739251,
+           0.19109315761072873,
+           0.1654690126458971,
+           0.14265927038964019,
+           0.12262202507018963,
+           0.1052308492189567,
+           0.09028063819574907,
+           0.07749551710645297,
+           0.06653858561506004,
+           0.057023229648240935,
+           0.04852568953465152,
+           0.0405985426985287,
+           0.03278473642060526,
+           0.024631792949091298,
+           0.015705805713233132,
+           0.005604851641113338,
+           -0.006028539554998419,
+           -0.0194961931971938,
+           -0.03503467500760361,
+           -0.05280751312937447,
+           -0.07289946791947478,
+           -0.0953130071996491,
+           -0.11996708713821325,
+           -0.14669827879683822,
+           -0.17526421913810475,
+           -0.20534930450505112,
+           -0.23657248579636167,
+           -0.26849696926416655,
+           -0.3006415764631127,
+           -0.33249347266472795,
+           -0.36352193615136624,
+           -0.39319281216760826,
+           -0.4209832756757921,
+           -0.44639651695279065,
+           -0.46897596375529726,
+           -0.48831866330289736,
+           -0.5040874664676341,
+           -0.5160216848593931,
+           -0.5239459282713859,
+           -0.5277768742988614,
+           -0.5275277727748791,
+           -0.5233105437230825,
+           -0.5153353874191263,
+           -0.5039078873910928,
+           -0.48942365022427564,
+           -0.47236058829344096,
+           -0.4532690114678517,
+           -0.43275974991799254,
+           -0.4114905809865208,
+           -0.39015127738621497,
+           -0.36944763062995817,
+           -0.3500848316460273,
+           -0.33275060926054095,
+           -0.3180985361425519,
+           -0.3067319106522553,
+           -0.2991886118047793,
+           -0.2959273035057136,
+           -0.297315333818446,
+           -0.30361863600784184,
+           -0.31499389140456874,
+           -0.33148316087579244,
+           -0.3530111331612771,
+           -0.37938507596173415,
+           -0.4102975109683423,
+           -0.44533156857858847,
+           -0.48396891345443305,
+           -0.5256000699266996,
+           -0.569536918058818,
+           -0.6150270783832529,
+           -0.6612698572137894,
+           -0.707433386152433,
+           -0.752672559896707,
+           -0.7961473564423452,
+           -0.837041113767216,
+           -0.874578337328355,
+           -0.9080416232088723,
+           -0.9367873022664108,
+           -0.960259440666804,
+           -0.9780018710085852,
+           -0.9896679749141093,
+           -0.9950279913472074,
+           -0.9939736837166605,
+           -0.9865202616087873,
+           -0.9728055182327808,
+           -0.9530862107716443,
+           -0.9277317762014741,
+           -0.8972155381834497,
+           -0.8621036198152103,
+           -0.8230418309163187,
+           -0.7807408458120672,
+           -0.7359600271299032,
+           -0.6894902819831874,
+           -0.6421363583521142,
+           -0.59469900097756,
+           -0.5479573874012853,
+           -0.5026522559064321,
+           -0.45947011827730544,
+           -0.41902892199287173,
+           -0.38186548941217874,
+           -0.3484250166338416,
+           -0.3190528631382406,
+           -0.2939888063355755,
+           -0.2733638741614082,
+           -0.25719980539541437,
+           -0.24541112299851386,
+           -0.23780974205739688,
+           -0.2341119724623014,
+           -0.23394771873372391,
+           -0.23687162686996888,
+           -0.24237588199252336,
+           -0.24990432203974372,
+           -0.25886750273069714,
+           -0.2686583282064116,
+           -0.2786678506411379,
+           -0.28830084094501984,
+           -0.29699074144741267,
+           -0.3042136299053021,
+           -0.3095008518310114,
+           -0.312450014257125,
+           -0.312734077723196,
+           -0.3101083333614987,
+           -0.30441510720201614,
+           -0.29558609280836257,
+           -0.28364227460331554,
+           -0.26869146619822615,
+           -0.2509235491430146,
+           -0.23060355622455778,
+           -0.20806279828561752,
+           -0.1836882831375239,
+           -0.15791071825474978,
+           -0.1311914244899448,
+           -0.10400851514698642,
+           -0.07684271272354827,
+           -0.05016318404030308,
+           -0.024413773108988266,
+           -2.200847561863644e-16
+          ],
+          [
+           0,
+           0.022853940323905933,
+           0.043542621913924585,
+           0.061872486621815666,
+           0.0777317914764011,
+           0.09109414738926297,
+           0.10201966383809234,
+           0.11065366255502213,
+           0.11722298674585754,
+           0.12202999526804088,
+           0.12544439190326578,
+           0.12789309683189412,
+           0.12984841920059148,
+           0.13181483495105403,
+           0.1343147116879637,
+           0.13787335134161008,
+           0.1430037409741502,
+           0.1501914117724018,
+           0.15987980579662756,
+           0.1724565394012535,
+           0.18824093165279507,
+           0.20747313603517395,
+           0.23030517498365297,
+           0.25679413027617415,
+           0.28689768918168995,
+           0.32047218783386966,
+           0.3572732310154294,
+           0.39695890295279956,
+           0.4390955184432484,
+           0.4831657992981855,
+           0.5285792992985023,
+           0.5746848431720051,
+           0.6207846929719479,
+           0.6661501099772852,
+           0.7100379429992909,
+           0.7517078457188091,
+           0.7904397071258403,
+           0.8255508707815061,
+           0.8564127207127633,
+           0.8824662242654807,
+           0.9032360449063043,
+           0.9183428702510619,
+           0.9275136417411298,
+           0.9305894214026368,
+           0.9275306868236665,
+           0.9184199065215566,
+           0.903461312761472,
+           0.8829778560466781,
+           0.8574053932894974,
+           0.8272842284308694,
+           0.7932481883693148,
+           0.7560114769137333,
+           0.7163536036174466,
+           0.6751027314502096,
+           0.6331178261587939,
+           0.5912700198934506,
+           0.55042362149925,
+           0.5114172152922831,
+           0.47504528891989256,
+           0.44204081906089326,
+           0.4130592215359402,
+           0.38866404040287944,
+           0.3693147095807094,
+           0.35535667147365013,
+           0.34701408114580656,
+           0.3443852631866484,
+           0.34744102300198393,
+           0.35602584645567364,
+           0.36986195322377186,
+           0.3885561015726075,
+           0.4116089771797575,
+           0.4384269376624653,
+           0.46833582913979166,
+           0.5005965427717947,
+           0.5344219389587337,
+           0.5689947357127186,
+           0.603485936376553,
+           0.6370733608606398,
+           0.6689598441456185,
+           0.6983906759425492,
+           0.7246698758412459,
+           0.7471749284856402,
+           0.7653696425283512,
+           0.7788148443505644,
+           0.787176671607769,
+           0.7902322912308274,
+           0.7878729300963534,
+           0.7801041726057262,
+           0.7670435462465425,
+           0.7489154822057686,
+           0.7260438016364485,
+           0.6988419376901762,
+           0.6678011574593054,
+           0.6334770952085884,
+           0.5964749475695121,
+           0.5574337117755226,
+           0.5170098688087061,
+           0.47586092402485564,
+           0.4346292181926709,
+           0.3939264119498929,
+           0.3543190267267185,
+           0.3163153957458303,
+           0.28035434054534847,
+           0.24679584256828135,
+           0.2159139268930571,
+           0.18789191747975148,
+           0.16282016183880785,
+           0.14069625934819732,
+           0.1214277631583703,
+           0.10483726235155671,
+           0.0906696903545859,
+           0.07860164906594604,
+           0.0682524871660811,
+           0.05919682691141871,
+           0.0509781974707483,
+           0.043123405450247294,
+           0.0351572553506223,
+           0.026617224746539287,
+           0.01706770116413172,
+           0.006113399890879185,
+           -0.00658839603603644,
+           -0.021317101216694646,
+           -0.03827988661245925,
+           -0.05760477259226121,
+           -0.07933594411879885,
+           -0.10343141788323468,
+           -0.12976312981797863,
+           -0.15811944822520307,
+           -0.1882100543570554,
+           -0.219673070281367,
+           -0.25208425483912367,
+           -0.28496803394825043,
+           -0.3178100828222913,
+           -0.35007113609584467,
+           -0.38120166844703485,
+           -0.4106570639424577,
+           -0.437912877637187,
+           -0.46247978833467523,
+           -0.4839178469894416,
+           -0.5018496409038279,
+           -0.5159720192599341,
+           -0.5260660600255603,
+           -0.5320050010354946,
+           -0.5337599080250408,
+           -0.5314029083466342,
+           -0.5251078796461046,
+           -0.5151485464080565,
+           -0.5018940024151562,
+           -0.48580174217789224,
+           -0.46740834765332956,
+           -0.4473180364970522,
+           -0.4261893331751072,
+           -0.4047201731126494,
+           -0.3836317914354525,
+           -0.363651780714681,
+           -0.3454967256089949,
+           -0.32985483579648167,
+           -0.31736900173393634,
+           -0.3086206904600999,
+           -0.30411508101931745,
+           -0.3042678115250799,
+           -0.30939367305762877,
+           -0.319697540375292,
+           -0.33526777690356124,
+           -0.35607229291960873,
+           -0.38195737269465757,
+           -0.4126493201304056,
+           -0.4477589047448465,
+           -0.4867885223825085,
+           -0.529141919396952,
+           -0.5741362668892396,
+           -0.6210163144120124,
+           -0.6689703017712735,
+           -0.7171472644284229,
+           -0.7646753335882774,
+           -0.8106806072075726,
+           -0.8543061534910752,
+           -0.8947307043287771,
+           -0.9311866026787383,
+           -0.9629765849660087,
+           -0.9894890067409837,
+           -1.0102111564651723,
+           -1.0247403474816859,
+           -1.032792530884819,
+           -1.0342082308482772,
+           -1.028955667573513,
+           -1.017130999830976,
+           -0.9989556874621673,
+           -0.9747710425255283,
+           -0.9450301043433321,
+           -0.9102870369226201,
+           -0.8711843055467149,
+           -0.8284379413521697,
+           -0.7828212471620241,
+           -0.7351473336692995,
+           -0.6862509013972309,
+           -0.6369697000807822,
+           -0.5881261028424386,
+           -0.5405092276571529,
+           -0.4948580232600197,
+           -0.4518457112460704,
+           -0.41206594129119617,
+           -0.37602097306398896,
+           -0.34411214758577996,
+           -0.31663285379730666,
+           -0.29376413432226556,
+           -0.2755730094120273,
+           -0.2620135314201613,
+           -0.2529305155352421,
+           -0.24806582753678433,
+           -0.24706704762853188,
+           -0.24949827245834758,
+           -0.25485276664575557,
+           -0.26256713174237273,
+           -0.27203662559654235,
+           -0.2826312394192625,
+           -0.29371212405942926,
+           -0.30464795145112517,
+           -0.31483080199730634,
+           -0.3236911836481632,
+           -0.33071181321087995,
+           -0.3354398243394736,
+           -0.33749710882187134,
+           -0.3365885471249054,
+           -0.33250793941826734,
+           -0.32514150807204445,
+           -0.3144689053954494,
+           -0.3005617245708805,
+           -0.2835795757188595,
+           -0.2637638511952607,
+           -0.24142936300992945,
+           -0.2169540891901692,
+           -0.19076731364222838,
+           -0.1633364843951701,
+           -0.13515314703805736,
+           -0.10671833288938473,
+           -0.07852779440530425,
+           -0.05105748322482251,
+           -0.024749659003941132,
+           -2.2222670470174246e-16
+          ],
+          [
+           0,
+           0.022890824677088983,
+           0.043448398551969934,
+           0.0615152922226714,
+           0.07702097130263315,
+           0.0899840900691743,
+           0.10051227804095361,
+           0.10879941876974483,
+           0.11512048570639727,
+           0.11982406399710949,
+           0.12332274785821548,
+           0.12608165921928308,
+           0.12860538318758094,
+           0.1314236582982643,
+           0.1350761933866434,
+           0.1400970073779426,
+           0.1469987026980851,
+           0.1562570869801655,
+           0.16829655115111575,
+           0.18347659497251,
+           0.2020798640812634,
+           0.22430202618508763,
+           0.25024376920490754,
+           0.279905151927065,
+           0.31318247942375266,
+           0.3498678125672064,
+           0.3896511549669737,
+           0.43212529324526006,
+           0.4767931994170554,
+           0.523077838940728,
+           0.5703341663873688,
+           0.6178630341941532,
+           0.6649266900446329,
+           0.7107654963234861,
+           0.7546154718992326,
+           0.7957262330514567,
+           0.833378897294357,
+           0.8669035115151928,
+           0.8956955743382525,
+           0.91923124176807,
+           0.9370808345214455,
+           0.948920304334233,
+           0.9545403639969714,
+           0.9538530407899841,
+           0.9468954740241666,
+           0.9338308430652548,
+           0.914946380926713,
+           0.8906484985815944,
+           0.8614551148524328,
+           0.8279853543819922,
+           0.7909468401061615,
+           0.7511208652720904,
+           0.709345781926475,
+           0.6664989866609027,
+           0.6234779191589536,
+           0.5811805138809797,
+           0.5404855594284834,
+           0.5022334233911169,
+           0.46720759270365214,
+           0.4361174609066708,
+           0.40958276465777776,
+           0.3881200330800023,
+           0.37213136599878627,
+           0.36189580196181526,
+           0.35756347549693945,
+           0.35915269683629847,
+           0.3665500179304296,
+           0.3795132776828689,
+           0.3976775486777991,
+           0.4205638389683594,
+           0.4475903374102879,
+           0.4780859311438109,
+           0.5113056705967278,
+           0.5464478120898799,
+           0.5826720318633002,
+           0.6191183789754906,
+           0.6549265186840655,
+           0.6892548129590585,
+           0.7212987908087027,
+           0.750308577939737,
+           0.7756048824933577,
+           0.796593170502713,
+           0.8127757103802571,
+           0.8237612190217182,
+           0.8292719016808033,
+           0.8291477421458945,
+           0.8233479673420105,
+           0.8119496796174753,
+           0.7951437189496341,
+           0.7732278844198842,
+           0.7465977079171012,
+           0.7157350315724805,
+           0.6811946924788875,
+           0.6435896625390484,
+           0.6035750267493483,
+           0.5618312090111981,
+           0.5190468700632263,
+           0.4759019069953101,
+           0.433050977954871,
+           0.3911079592689029,
+           0.350631715725804,
+           0.3121135288832926,
+           0.27596648391958867,
+           0.24251706386085423,
+           0.21199914231555658,
+           0.18455050359075237,
+           0.16021195383174688,
+           0.13892902026228413,
+           0.12055616938482999,
+           0.10486341079517851,
+           0.09154509268525052,
+           0.08023063967142886,
+           0.07049693468088072,
+           0.06188200547675441,
+           0.05389964403033032,
+           0.04605456415769058,
+           0.0378576901920372,
+           0.028841167266445495,
+           0.018572692078479777,
+           0.006668781576378127,
+           -0.0071933746333322085,
+           -0.023265794931044713,
+           -0.04172159061901673,
+           -0.06264907389247217,
+           -0.08604824948310398,
+           -0.11182978835637143,
+           -0.13981651702409537,
+           -0.16974739029367594,
+           -0.2012838502832536,
+           -0.23401841193881076,
+           -0.26748525668568734,
+           -0.30117256272494863,
+           -0.33453625419960786,
+           -0.3670148131909737,
+           -0.3980447692450308,
+           -0.42707646163096363,
+           -0.4535896603123627,
+           -0.47710863292230327,
+           -0.4972162568681204,
+           -0.5135667977776006,
+           -0.5258970073050656,
+           -0.5340352340680715,
+           -0.5379082901821177,
+           -0.5375458712997293,
+           -0.5330823888682253,
+           -0.5247561379867972,
+           -0.5129057911580255,
+           -0.49796427572181634,
+           -0.4804501591428598,
+           -0.4609567299323334,
+           -0.44013902122184484,
+           -0.4186990773796966,
+           -0.3973698102155219,
+           -0.37689782908558717,
+           -0.35802565761904903,
+           -0.3414737680978333,
+           -0.327922872250403,
+           -0.3179969041355724,
+           -0.31224711693669027,
+           -0.3111376911663709,
+           -0.31503321756430963,
+           -0.32418837466863376,
+           -0.3387400696939289,
+           -0.35870225319670224,
+           -0.383963554462144,
+           -0.41428781715104734,
+           -0.4493175451467785,
+           -0.48858019844056066,
+           -0.5314972100059425,
+           -0.5773955286295,
+           -0.6255214312058006,
+           -0.6750562925820706,
+           -0.7251339530180178,
+           -0.7748592838944601,
+           -0.8233275224371387,
+           -0.8696439266624925,
+           -0.9129432929904548,
+           -0.9524088812325401,
+           -0.9872903049074423,
+           -1.016919968748995,
+           -1.0407276692779353,
+           -1.058253017588356,
+           -1.069155395002774,
+           -1.0732212107260564,
+           -1.0703682946568447,
+           -1.0606473265382683,
+           -1.0442402729931926,
+           -1.0214558749812677,
+           -0.9927222981095043,
+           -0.9585771253262615,
+           -0.919654934201523,
+           -0.8766727577242984,
+           -0.8304137769584646,
+           -0.7817096347990071,
+           -0.7314217914790017,
+           -0.6804223636451839,
+           -0.6295748992500235,
+           -0.5797155399680378,
+           -0.5316350113708178,
+           -0.48606185899404836,
+           -0.4436473162665209,
+           -0.4049521488578353,
+           -0.37043577037632563,
+           -0.34044786774997354,
+           -0.315222712458009,
+           -0.29487626759157043,
+           -0.27940613214599264,
+           -0.2686942946783251,
+           -0.26251260020842676,
+           -0.26053076867860053,
+           -0.26232674202303824,
+           -0.2673990814324398,
+           -0.2751810880821493,
+           -0.2850562805950936,
+           -0.2963748317958408,
+           -0.3084705466090725,
+           -0.32067795274412825,
+           -0.3323490763050612,
+           -0.34286948562391295,
+           -0.35167320811972413,
+           -0.358256156266452,
+           -0.36218773899605694,
+           -0.3631203830340056,
+           -0.3607967435324349,
+           -0.35505444353635723,
+           -0.3458282457653822,
+           -0.3331496263012486,
+           -0.31714378637249213,
+           -0.2980242038449724,
+           -0.2760848886166461,
+           -0.2516905643060043,
+           -0.22526505095827373,
+           -0.1972781686629197,
+           -0.16823151885309465,
+           -0.1386435277251332,
+           -0.10903415398926147,
+           -0.07990967060601369,
+           -0.051747927101543315,
+           -0.024984485578600855,
+           -2.2345117074042277e-16
+          ],
+          [
+           0,
+           0.02283636954845353,
+           0.043185966834339125,
+           0.06093171115614635,
+           0.07604787060632553,
+           0.08860099686683996,
+           0.09874826031785722,
+           0.1067332235701642,
+           0.11287915858578418,
+           0.11758007699384863,
+           0.12128970340181418,
+           0.12450867591335521,
+           0.127770305305817,
+           0.13162526318337783,
+           0.1366255989080956,
+           0.14330850445570228,
+           0.15218025503643193,
+           0.16370075112056237,
+           0.17826907444442125,
+           0.19621044694906797,
+           0.21776494799008952,
+           0.24307830237403544,
+           0.27219500087756743,
+           0.3050539571474634,
+           0.3414868416955175,
+           0.3812191666632304,
+           0.42387412580773376,
+           0.46897912448163426,
+           0.5159748659893951,
+           0.5642267953172841,
+           0.6130386404972936,
+           0.661667737310237,
+           0.7093417760412105,
+           0.7552765707685742,
+           0.7986944231769966,
+           0.8388426348776321,
+           0.8750117151770284,
+           0.906552835372783,
+           0.9328940959033369,
+           0.9535551987011752,
+           0.9681601532850908,
+           0.9764476906172055,
+           0.9782791124514105,
+           0.9736433645138741,
+           0.9626591879119986,
+           0.9455742730573458,
+           0.9227614124044875,
+           0.8947117206900124,
+           0.8620250623302723,
+           0.8253978934609671,
+           0.7856087891089429,
+           0.743501982625326,
+           0.6999692933821515,
+           0.6559308586337794,
+           0.6123151153802078,
+           0.5700384972958348,
+           0.5299853198201914,
+           0.49298832313654334,
+           0.4598103280593253,
+           0.4311274341591158,
+           0.40751415339078995,
+           0.38943082692723957,
+           0.377213618941393,
+           0.37106732003268794,
+           0.37106112634394567,
+           0.37712748978115446,
+           0.3890640618498371,
+           0.4065386802303393,
+           0.42909727511494516,
+           0.4561745032742077,
+           0.4871068534848038,
+           0.521147908896466,
+           0.5574854015459316,
+           0.5952596527568048,
+           0.6335829615918612,
+           0.6715594826011351,
+           0.7083051243257014,
+           0.7429670015900489,
+           0.7747419874832419,
+           0.802893934751308,
+           0.8267691704927453,
+           0.845809911704748,
+           0.859565301277009,
+           0.8676998231757633,
+           0.8699989203336477,
+           0.8663717075561166,
+           0.8568507428715314,
+           0.8415888924350868,
+           0.820853394581464,
+           0.7950172961759513,
+           0.7645484973833286,
+           0.7299966978196427,
+           0.691978586390639,
+           0.6511616577575824,
+           0.6082470693302041,
+           0.5639519732336565,
+           0.5189917673574541,
+           0.47406270816695095,
+           0.4298253155152236,
+           0.38688897658243687,
+           0.3457981229028056,
+           0.30702031207698005,
+           0.2709364952984698,
+           0.23783369453473263,
+           0.20790025055243969,
+           0.18122373654904328,
+           0.15779156362697272,
+           0.13749423544992262,
+           0.12013114188618722,
+           0.10541871696798705,
+           0.0930007266950581,
+           0.08246039858223674,
+           0.07333405873421214,
+           0.06512590477533312,
+           0.05732351509857128,
+           0.04941367731355065,
+           0.04089811189784453,
+           0.03130867104759583,
+           0.020221607468484847,
+           0.007270532961073061,
+           -0.007842278510275722,
+           -0.02533654490872457,
+           -0.04534683763416405,
+           -0.06791784290915186,
+           -0.09300215275732275,
+           -0.12046064919522033,
+           -0.1500654774894546,
+           -0.18150553660780813,
+           -0.2143943490349196,
+           -0.24828010960629818,
+           -0.2826576555289972,
+           -0.31698204876787417,
+           -0.35068341878540643,
+           -0.3831826793377709,
+           -0.4139077085345998,
+           -0.4423095673036223,
+           -0.46787832814176755,
+           -0.4901580936876831,
+           -0.5087608030493126,
+           -0.5233784525262621,
+           -0.5337933956828275,
+           -0.5398864347139787,
+           -0.5416424695443758,
+           -0.5391535317602764,
+           -0.5326190957895481,
+           -0.5223436280899746,
+           -0.5087314047753915,
+           -0.49227869736109053,
+           -0.47356349340892767,
+           -0.4532329821134087,
+           -0.4319890926991417,
+           -0.4105724244358053,
+           -0.38974494982581803,
+           -0.37027190598967225,
+           -0.35290331260007324,
+           -0.33835556728440364,
+           -0.3272935708770177,
+           -0.3203138251848305,
+           -0.3179289252347359,
+           -0.3205538367753132,
+           -0.32849430884468456,
+           -0.34193772147106577,
+           -0.3609466112414831,
+           -0.3854550539462009,
+           -0.41526801532614377,
+           -0.45006370978037624,
+           -0.48939893446970784,
+           -0.5327172743536688,
+           -0.579360004084981,
+           -0.6285794470679089,
+           -0.6795544919790633,
+           -0.7314079141300742,
+           -0.7832251045277571,
+           -0.8340737744613556,
+           -0.883024178788278,
+           -0.9291693874168996,
+           -0.9716451321452252,
+           -1.0096487650785053,
+           -1.042456885108304,
+           -1.0694412199068977,
+           -1.0900823918283575,
+           -1.1039812460209704,
+           -1.1108674767345017,
+           -1.1106053518493628,
+           -1.1031964045065707,
+           -1.088779032703002,
+           -1.067625021085253,
+           -1.040133072143182,
+           -1.0068195047973054,
+           -0.9683063452730374,
+           -0.9253070965362208,
+           -0.8786105269413794,
+           -0.8290628648026576,
+           -0.7775488222282759,
+           -0.7249718978854238,
+           -0.6722344237605636,
+           -0.6202178250954086,
+           -0.5697635554337238,
+           -0.5216551503102183,
+           -0.4766018140249919,
+           -0.43522391491212054,
+           -0.3980407165086326,
+           -0.3654606162592443,
+           -0.33777410124012025,
+           -0.31514956339355255,
+           -0.29763204659300824,
+           -0.28514492623757765,
+           -0.27749445077167434,
+           -0.2743770052936458,
+           -0.27538889195449195,
+           -0.2800383617569707,
+           -0.2877595791115191,
+           -0.29792815538158035,
+           -0.3098778517457863,
+           -0.3229180258757574,
+           -0.3363513817819281,
+           -0.3494915780550591,
+           -0.3616802566927977,
+           -0.37230307253782996,
+           -0.3808043315856998,
+           -0.3866998843076514,
+           -0.3895879666989615,
+           -0.38915773581436647,
+           -0.3851953067129258,
+           -0.3775871624790835,
+           -0.36632087667730556,
+           -0.35148315652640216,
+           -0.33325528351089917,
+           -0.31190609436016503,
+           -0.2877827076600575,
+           -0.26129925825464684,
+           -0.23292395162453955,
+           -0.20316479234493884,
+           -0.1725543734878088,
+           -0.14163413662670016,
+           -0.11093852436976843,
+           -0.08097944879127457,
+           -0.052231489732127316,
+           -0.02511821694637622,
+           -2.237715756273737e-16
+          ],
+          [
+           0,
+           0.02269471294813116,
+           0.042766304844330284,
+           0.06014196641110531,
+           0.0748439755376095,
+           0.08698917073221102,
+           0.09678575495146019,
+           0.10452750894983594,
+           0.11058556118124256,
+           0.115397925484496,
+           0.1194570766678699,
+           0.12329588617193335,
+           0.12747228390569376,
+           0.1325530469927223,
+           0.13909714063805087,
+           0.14763904999459798,
+           0.15867254440218936,
+           0.1726353066058388,
+           0.18989483972873564,
+           0.21073603435354174,
+           0.23535073779405774,
+           0.26382961850748887,
+           0.2961565618188941,
+           0.3322057701113885,
+           0.37174167294478705,
+           0.414421681888319,
+           0.4598017529546406,
+           0.5073446482018111,
+           0.5564307191157217,
+           0.6063709695311666,
+           0.6564220967302618,
+           0.7058031574680105,
+           0.7537134623353751,
+           0.7993512681894378,
+           0.8419328152294224,
+           0.8807112432881863,
+           0.9149949213775213,
+           0.9441647355243826,
+           0.9676899022302703,
+           0.9851419079632662,
+           0.996206218169331,
+           1.0006914513348963,
+           0.998535773391116,
+           0.9898103337726992,
+           0.974719635124764,
+           0.9535988022652946,
+           0.9269077907584917,
+           0.8952226495044386,
+           0.8592240232857032,
+           0.8196831484734224,
+           0.7774456564278495,
+           0.7334135530185533,
+           0.6885257878052353,
+           0.6437378616431463,
+           0.6000009459304363,
+           0.5582409997848321,
+           0.5193383727888227,
+           0.4841083705280147,
+           0.45328323820692096,
+           0.42749598468310557,
+           0.40726642610725455,
+           0.39298977603661905,
+           0.3849280486706049,
+           0.3832044752019265,
+           0.38780106180438806,
+           0.3985593432266342,
+           0.415184310142976,
+           0.4372514131711523,
+           0.46421647363141255,
+           0.4954282624607062,
+           0.5301434458759746,
+           0.5675435409234191,
+           0.6067534772964661,
+           0.6468613248800525,
+           0.6869387202668441,
+           0.7260615106126699,
+           0.763330129995855,
+           0.7978892319733776,
+           0.8289461220533284,
+           0.8557875648134089,
+           0.8777945816057657,
+           0.8944549051666333,
+           0.9053728157386801,
+           0.9102761480661596,
+           0.9090203282329231,
+           0.9015893720597704,
+           0.8880938508651623,
+           0.8687659039974153,
+           0.8439514488582496,
+           0.8140998064085512,
+           0.7797510217326649,
+           0.7415212136368325,
+           0.7000863331510746,
+           0.6561647470859733,
+           0.6104990886010933,
+           0.5638378314667154,
+           0.5169170480177671,
+           0.4704428026651609,
+           0.42507461348653036,
+           0.38141038438515457,
+           0.33997317036727226,
+           0.3012000896733294,
+           0.26543364005654674,
+           0.23291561386853596,
+           0.20378373937410646,
+           0.1780711055753624,
+           0.15570835654724674,
+           0.13652857066655502,
+           0.12027467192806675,
+           0.10660915649464016,
+           0.09512585932619906,
+           0.08536343463202165,
+           0.07682018126536774,
+           0.0689698110884002,
+           0.06127773559680619,
+           0.05321743426463535,
+           0.04428646743286018,
+           0.03402170712042841,
+           0.022013380602949592,
+           0.007917553425986738,
+           -0.008533280118806292,
+           -0.027521781181580773,
+           -0.04913975027380647,
+           -0.07338467316383168,
+           -0.1001589240015797,
+           -0.1292716514666348,
+           -0.16044330357069025,
+           -0.19331267765890733,
+           -0.22744631589998798,
+           -0.26235000481597864,
+           -0.2974820817517061,
+           -0.3322682030396296,
+           -0.3661171892104507,
+           -0.39843753294583456,
+           -0.42865413633543575,
+           -0.45622483589086826,
+           -0.4806562769122272,
+           -0.5015187131437752,
+           -0.5184593328583752,
+           -0.531213747965719,
+           -0.5396153275795612,
+           -0.5436021105991451,
+           -0.5432210919452186,
+           -0.5386297426499672,
+           -0.530094693401039,
+           -0.5179875826515868,
+           -0.5027781422431747,
+           -0.48502466384717924,
+           -0.4653620566462381,
+           -0.44448776886102814,
+           -0.4231459014088105,
+           -0.40210988974706124,
+           -0.38216416859021907,
+           -0.36408526269675945,
+           -0.3486227645635631,
+           -0.336480666159436,
+           -0.32829950658473295,
+           -0.3246397808504447,
+           -0.3259670272027662,
+           -0.332638972228382,
+           -0.3448950652711292,
+           -0.3628486776193295,
+           -0.38648217884110575,
+           -0.41564503408465053,
+           -0.45005499379207853,
+           -0.48930237286687134,
+           -0.5328573417072635,
+           -0.5800800785009811,
+           -0.6302335625641766,
+           -0.6824987240115187,
+           -0.7359916072547698,
+           -0.7897821561706803,
+           -0.8429141884846196,
+           -0.8944260969850256,
+           -0.9433717963626858,
+           -0.9888414272343552,
+           -1.0299813334539218,
+           -1.066012845040098,
+           -1.0962494265744427,
+           -1.1201117890875074,
+           -1.1371406113331275,
+           -1.1470065727920271,
+           -1.1495174643768,
+           -1.1446222120852914,
+           -1.1324117220847645,
+           -1.113116531124134,
+           -1.0871013219322119,
+           -1.054856437524543,
+           -1.0169865993054854,
+           -0.9741970997928411,
+           -0.9272778001109436,
+           -0.8770853136588672,
+           -0.8245237993266283,
+           -0.7705248192956605,
+           -0.7160267370657099,
+           -0.6619541404160715,
+           -0.6091977713354795,
+           -0.5585954306309121,
+           -0.5109142993260258,
+           -0.4668350827357742,
+           -0.4269383371660331,
+           -0.39169328468365283,
+           -0.36144935969015574,
+           -0.33643066364266894,
+           -0.31673343286694167,
+           -0.30232655076332154,
+           -0.29305506163290157,
+           -0.2886465706700187,
+           -0.2887203451631347,
+           -0.29279886732070043,
+           -0.3003215309694013,
+           -0.31066012407367244,
+           -0.3231356978139443,
+           -0.33703639182537504,
+           -0.35163576487551523,
+           -0.3662111712152825,
+           -0.38006172525849996,
+           -0.3925254110317345,
+           -0.402994917606507,
+           -0.410931816825914,
+           -0.4158787441576273,
+           -0.4174692963023542,
+           -0.4154354189148542,
+           -0.4096121229367835,
+           -0.399939436948392,
+           -0.386461573879969,
+           -0.3693233615971155,
+           -0.3487640564971181,
+           -0.3251087255794116,
+           -0.29875744381980307,
+           -0.2701726085508597,
+           -0.23986471956042105,
+           -0.20837701159641894,
+           -0.17626935396744856,
+           -0.14410184926502037,
+           -0.11241856948422904,
+           -0.08173186284284166,
+           -0.052507648535498205,
+           -0.025152089929554408,
+           -2.2321318681993174e-16
+          ],
+          [
+           0,
+           0.022471215538102336,
+           0.04220270939932241,
+           0.059169508651114894,
+           0.07344466722671224,
+           0.08519718855616136,
+           0.0946872333494397,
+           0.10225873451887726,
+           0.10832960925727637,
+           0.11337982152830528,
+           0.11793760506717724,
+           0.12256420598265283,
+           0.12783754394285787,
+           0.13433522069218035,
+           0.14261732351334627,
+           0.15320947871980098,
+           0.166586606126934,
+           0.18315780978628246,
+           0.2032528134443159,
+           0.22711031185734804,
+           0.25486856217208526,
+           0.286558484225158,
+           0.322099476196221,
+           0.3612980841190165,
+           0.40384959200540776,
+           0.4493425255601377,
+           0.4972659885046433,
+           0.5470196782408873,
+           0.5979263587872315,
+           0.649246505341236,
+           0.7001947780757134,
+           0.7499579342947372,
+           0.7977137491029799,
+           0.8426504862785168,
+           0.8839864438304412,
+           0.9209890932348208,
+           0.9529933377519966,
+           0.9794184334164375,
+           0.9997831458463933,
+           1.0137187562508112,
+           1.0209795799559647,
+           1.0214507192320028,
+           1.0151528377551788,
+           1.002243815101503,
+           0.9830172144994861,
+           0.9578975738445608,
+           0.9274326068152302,
+           0.8922824759457839,
+           0.8532063708585675,
+           0.8110466907838532,
+           0.7667111893710974,
+           0.7211534901667803,
+           0.6753524217526713,
+           0.6302906513939401,
+           0.5869331143916023,
+           0.5462057427024954,
+           0.5089749906098907,
+           0.47602863742410906,
+           0.4480583177851993,
+           0.4256441898335294,
+           0.4092421012811594,
+           0.39917355447279723,
+           0.39561870529949145,
+           0.3986125589290977,
+           0.4080444494922533,
+           0.42366081295448405,
+           0.4450711843084085,
+           0.4717572738332679,
+           0.5030849043481788,
+           0.5383185238985373,
+           0.5766379477982383,
+           0.6171569318684954,
+           0.6589431363239486,
+           0.7010390080769431,
+           0.7424830890163655,
+           0.7823312495414836,
+           0.8196773504738863,
+           0.8536728523143781,
+           0.8835449182449374,
+           0.9086125956029911,
+           0.928300708814384,
+           0.9421511537581678,
+           0.9498313478338303,
+           0.9511396600158792,
+           0.946007719179896,
+           0.9344995751419121,
+           0.9168077632930423,
+           0.8932463985546638,
+           0.8642414957901342,
+           0.8303187800399652,
+           0.7920893093830798,
+           0.7502332844233865,
+           0.7054824601216234,
+           0.6586016069377971,
+           0.610369488281892,
+           0.5615598296319507,
+           0.512922751201695,
+           0.46516712085163464,
+           0.41894425745578084,
+           0.37483337785820187,
+           0.33332913383965224,
+           0.2948315303618217,
+           0.2596384541709343,
+           0.22794097420119977,
+           0.19982150383266256,
+           0.17525484172815234,
+           0.15411203454603128,
+           0.13616693314403297,
+           0.12110524575234495,
+           0.10853582870683351,
+           0.0980038992672715,
+           0.08900580719822226,
+           0.08100496335124717,
+           0.07344849540781645,
+           0.06578418391271265,
+           0.05747722615931197,
+           0.048026381503811194,
+           0.03697906911658201,
+           0.023945017569708578,
+           0.008608104279135744,
+           -0.009263929320590145,
+           -0.02981214511177696,
+           -0.053081653905251165,
+           -0.07901956760782165,
+           -0.10747571544307165,
+           -0.1382061094423343,
+           -0.1708790724784104,
+           -0.20508387233369446,
+           -0.24034163945007153,
+           -0.2761182857750413,
+           -0.31183908903166235,
+           -0.34690456215464993,
+           -0.38070719269412084,
+           -0.41264861259308766,
+           -0.4421567455313678,
+           -0.46870247735319887,
+           -0.4918154050246606,
+           -0.5110982408746654,
+           -0.5262394810480573,
+           -0.5370239893557219,
+           -0.5433411990047032,
+           -0.5451906937624631,
+           -0.5426849954877155,
+           -0.5360494550190048,
+           -0.5256192164040467,
+           -0.5118332985537567,
+           -0.49522591175892966,
+           -0.4764151972738586,
+           -0.4560896445691236,
+           -0.4349925012102402,
+           -0.4139045431013073,
+           -0.3936256167002591,
+           -0.37495539864062327,
+           -0.3586738411070142,
+           -0.3455217827005133,
+           -0.3361822040731819,
+           -0.33126259527912444,
+           -0.3312788778483567,
+           -0.33664128959308726,
+           -0.3476425949329969,
+           -0.3644489291607202,
+           -0.38709352287347787,
+           -0.4154734842805159,
+           -0.44934974392675525,
+           -0.488350190337024,
+           -0.5319759480429103,
+           -0.5796106732943654,
+           -0.6305326693508928,
+           -0.6839295543985642,
+           -0.7389151525455131,
+           -0.7945482235555793,
+           -0.8498526013432822,
+           -0.9038382759061027,
+           -0.9555229291939943,
+           -1.0039534230192892,
+           -1.0482267368133584,
+           -1.0875098648628139,
+           -1.1210582063345609,
+           -1.1482320163614166,
+           -1.1685105318673168,
+           -1.1815034405661287,
+           -1.1869594243440147,
+           -1.1847715775087455,
+           -1.1749795744773577,
+           -1.1577685385753316,
+           -1.1334646418613392,
+           -1.1025275433694193,
+           -1.065539847992114,
+           -1.023193838596148,
+           -0.9762757981590998,
+           -0.9256482951861646,
+           -0.8722308530452485,
+           -0.8169794610053067,
+           -0.7608654107875092,
+           -0.7048539567253207,
+           -0.6498832998505242,
+           -0.5968443863461681,
+           -0.5465619890996485,
+           -0.49977750810523774,
+           -0.4571338820365081,
+           -0.41916295052195357,
+           -0.38627554582617635,
+           -0.35875452527464774,
+           -0.33675088353018884,
+           -0.32028300851863534,
+           -0.3092390682667663,
+           -0.3033824400408995,
+           -0.30236001982281996,
+           -0.3057131811280445,
+           -0.3128910891463149,
+           -0.32326602069999205,
+           -0.3361502939172239,
+           -0.3508143749249232,
+           -0.3665057031529065,
+           -0.3824677626046483,
+           -0.3979589240056059,
+           -0.41227059210705747,
+           -0.4247442133287178,
+           -0.43478673080756836,
+           -0.4418841159519233,
+           -0.44561265669683375,
+           -0.4456477415136392,
+           -0.44176994334674974,
+           -0.4338682773849837,
+           -0.4219405791618392,
+           -0.40609102308993783,
+           -0.38652487431843036,
+           -0.363540636931588,
+           -0.3375198272248675,
+           -0.30891466045799887,
+           -0.2782339916037909,
+           -0.24602789388899848,
+           -0.21287129228592322,
+           -0.1793470917371006,
+           -0.14602925122804708,
+           -0.11346625459663984,
+           -0.08216541720512233,
+           -0.05257844461526195,
+           -0.0250886257941545,
+           -2.2181305355445957e-16
+          ],
+          [
+           0,
+           0.022172419861951464,
+           0.04151067938049591,
+           0.05804079162195865,
+           0.07188886153559929,
+           0.08327738287772911,
+           0.09251880156602538,
+           0.10000651166700929,
+           0.10620351766505087,
+           0.11162905819645165,
+           0.11684354048957563,
+           0.12243217995141002,
+           0.12898777452407933,
+           0.13709306769462395,
+           0.14730316674473426,
+           0.16012848363116053,
+           0.1760186547481824,
+           0.19534787299707895,
+           0.21840203162440402,
+           0.2453680350221016,
+           0.27632557819933035,
+           0.3112416352626698,
+           0.3499678295028452,
+           0.39224078526937556,
+           0.43768548652720385,
+           0.4858215907145997,
+           0.5360725711710868,
+           0.5877774888705724,
+           0.6402051263045253,
+           0.6925701548274782,
+           0.7440509531618377,
+           0.7938086504267827,
+           0.8410069331443881,
+           0.8848321330658052,
+           0.9245131019528693,
+           0.959340380953034,
+           0.988684185922485,
+           1.0120107556850215,
+           1.0288966471678993,
+           1.0390406087535584,
+           1.042272719890619,
+           1.0385605496486194,
+           1.0280121579093697,
+           1.0108758385336067,
+           0.9875365822769436,
+           0.9585093165335253,
+           0.9244290572138341,
+           0.8860381832922828,
+           0.8441711149384595,
+           0.7997367399375008,
+           0.753698988733452,
+           0.7070560045165487,
+           0.6608183901753584,
+           0.6159870377629519,
+           0.5735310577810462,
+           0.5343663247635917,
+           0.4993351423437537,
+           0.469187505523491,
+           0.44456440083951476,
+           0.4259835374234115,
+           0.4138278447393174,
+           0.4083370074354877,
+           0.4096022358519212,
+           0.41756439403103524,
+           0.4320155274462345,
+           0.45260375202994496,
+           0.4788413864085955,
+           0.5101161324734498,
+           0.5457050373980423,
+           0.5847909047027889,
+           0.6264807645523917,
+           0.669825965539994,
+           0.7138434129183349,
+           0.7575374524755755,
+           0.7999218856317591,
+           0.8400416001625266,
+           0.8769933122456945,
+           0.9099449389738894,
+           0.9381531554851753,
+           0.96097873655305,
+           0.977899337706057,
+           0.9885194343418031,
+           0.9925772072882116,
+           0.9899482381150325,
+           0.9806459553630137,
+           0.9648188518183121,
+           0.9427445710739507,
+           0.9148210369716175,
+           0.8815548702611391,
+           0.8435474012246302,
+           0.8014786435207918,
+           0.756089641744214,
+           0.7081636420291774,
+           0.6585065605819119,
+           0.6079272387054883,
+           0.5572179743893083,
+           0.507135809874838,
+           0.45838503208744363,
+           0.4116013090415204,
+           0.3673378411617572,
+           0.3260538530532073,
+           0.2881056899601036,
+           0.25374071553517213,
+           0.2230941353089492,
+           0.19618879522522992,
+           0.17293792868348098,
+           0.15315075060955577,
+           0.1365407250414837,
+           0.12273626537088873,
+           0.11129356540544694,
+           0.10171120633409877,
+           0.09344614080437254,
+           0.08593062174704465,
+           0.07858962113421976,
+           0.0708582730789911,
+           0.06219887683040818,
+           0.052117008238766534,
+           0.04017631281674641,
+           0.026011588965447315,
+           0.00933981536089272,
+           -0.010031169254642171,
+           -0.03219656394343577,
+           -0.0571512436129066,
+           -0.08478922802041894,
+           -0.11490599849087563,
+           -0.14720360459713666,
+           -0.181298429993718,
+           -0.21673141682947056,
+           -0.2529804834685459,
+           -0.2894748122675662,
+           -0.325610634369189,
+           -0.3607680981513321,
+           -0.39432877815322703,
+           -0.42569336275670555,
+           -0.4542990521231817,
+           -0.4796362030679129,
+           -0.5012637745867566,
+           -0.5188231562323108,
+           -0.5320500007731226,
+           -0.5407837315974401,
+           -0.5449744529302216,
+           -0.544687055689832,
+           -0.5401023821080951,
+           -0.5315153863213704,
+           -0.519330304159835,
+           -0.504052921413932,
+           -0.48628010403269334,
+           -0.4666868241432202,
+           -0.44601098069780626,
+           -0.4250363713130991,
+           -0.40457422099685025,
+           -0.38544371270672695,
+           -0.3684519930399665,
+           -0.3543741430688753,
+           -0.34393360895946945,
+           -0.33778357938264353,
+           -0.33648977699656873,
+           -0.3405150998937646,
+           -0.3502065066044358,
+           -0.3657844860394329,
+           -0.3873353928991656,
+           -0.4148068610432021,
+           -0.44800643376383803,
+           -0.48660347263009196,
+           -0.5301343274562784,
+           -0.5780106709405386,
+           -0.6295308245534761,
+           -0.6838938292282944,
+           -0.7402159471113765,
+           -0.7975492207369951,
+           -0.8549016649740088,
+           -0.9112586262217298,
+           -0.9656048136249998,
+           -1.0169464892806033,
+           -1.0643332989722878,
+           -1.106879232051602,
+           -1.1437822185205975,
+           -1.1743419027118922,
+           -1.1979751754508974,
+           -1.2142290991999312,
+           -1.2227909221515996,
+           -1.2234949460690003,
+           -1.2163260871920398,
+           -1.2014200479317645,
+           -1.1790600974523444,
+           -1.1496705396390556,
+           -1.1138070254160064,
+           -1.072143941002892,
+           -1.0254591726740243,
+           -0.974616610232574,
+           -0.9205468042463718,
+           -0.8642262348331818,
+           -0.8066556814062321,
+           -0.7488382025411974,
+           -0.6917572425415482,
+           -0.6363553762013047,
+           -0.5835141858399937,
+           -0.5340357353639175,
+           -0.4886260656321943,
+           -0.44788108478925415,
+           -0.4122751677291829,
+           -0.38215271195883477,
+           -0.35772282448314086,
+           -0.3390572377425922,
+           -0.32609147397849386,
+           -0.31862919862243894,
+           -0.3163496263377264,
+           -0.3188177700686916,
+           -0.3254972556705667,
+           -0.3357653640494414,
+           -0.3489299107110423,
+           -0.36424753045405306,
+           -0.3809429036571647,
+           -0.39822844093593457,
+           -0.4153239353333438,
+           -0.43147569580403033,
+           -0.44597469240039517,
+           -0.4581732718142093,
+           -0.4675000410276327,
+           -0.4734725657719198,
+           -0.47570758802721563,
+           -0.47392853145766817,
+           -0.4679701338235092,
+           -0.45778011927281137,
+           -0.4434178991285707,
+           -0.42505036544714714,
+           -0.4029449153324971,
+           -0.37745991390011324,
+           -0.34903286814650003,
+           -0.3181666411879685,
+           -0.2854140849617771,
+           -0.2513615083261661,
+           -0.21661142559381621,
+           -0.1817650471970064,
+           -0.14740497901183297,
+           -0.11407858976078737,
+           -0.08228248706539971,
+           -0.052448512626608684,
+           -0.024931626445537272,
+           -2.196197973710879e-16
+          ],
+          [
+           0,
+           0.021805994561302524,
+           0.04070777047140183,
+           0.05678500757307933,
+           0.07021860028848213,
+           0.08128526998033299,
+           0.09034945304280856,
+           0.09785267604545049,
+           0.10430069536040573,
+           0.11024873777393193,
+           0.116285229111372,
+           0.1230144385988072,
+           0.13103849649907656,
+           0.14093926072256954,
+           0.1532605141444205,
+           0.16849096808448621,
+           0.18704852895917726,
+           0.2092662549355123,
+           0.23538038824387766,
+           0.265520797650492,
+           0.29970410571941747,
+           0.3378297083939664,
+           0.37967882176939066,
+           0.42491661452616103,
+           0.4730974062566047,
+           0.5236728338076557,
+           0.5760028117402624,
+           0.6293690409849086,
+           0.6829907535701039,
+           0.7360423225927764,
+           0.7876723168790403,
+           0.8370235403230128,
+           0.8832535677095613,
+           0.9255552726650709,
+           0.9631768396820557,
+           0.9954407610635735,
+           1.0217613409540238,
+           1.041660261877566,
+           1.0547798136103974,
+           1.0608934387068272,
+           1.0599133122675684,
+           1.0518947440480473,
+           1.0370372670386239,
+           1.0156823563511417,
+           0.9883078036665286,
+           0.9555188536394553,
+           0.9180362875244873,
+           0.8766817139424025,
+           0.8323603953042784,
+           0.7860419992595802,
+           0.7387397161255299,
+           0.6914882243068402,
+           0.645321015202662,
+           0.601247606279395,
+           0.560231175423047,
+           0.5231671412445298,
+           0.4908631928829349,
+           0.4640212395337982,
+           0.44322170521942383,
+           0.4289105392937927,
+           0.421389249166253,
+           0.4208081902874213,
+           0.42716327130155607,
+           0.4402961513060482,
+           0.459897923338469,
+           0.4855161955481991,
+           0.5165654010123638,
+           0.5523400907805798,
+           0.592030894334248,
+           0.6347427689311513,
+           0.6795151057931584,
+           0.7253432180759298,
+           0.7712007040685459,
+           0.816062159858729,
+           0.8589257092148825,
+           0.8988348248162404,
+           0.9348989340282248,
+           0.966312333681876,
+           0.9923709809857792,
+           1.0124867807091495,
+           1.026199050806332,
+           1.0331829181671914,
+           1.0332544714545602,
+           1.0263725771705041,
+           1.0126373462263059,
+           0.9922853193812251,
+           0.9656815189716885,
+           0.9333085894393042,
+           0.895753318448571,
+           0.853690892176291,
+           0.8078672911560163,
+           0.7590802755995358,
+           0.708159440377248,
+           0.6559458390856753,
+           0.6032716834279082,
+           0.5509406183558387,
+           0.49970905525805775,
+           0.45026901541809383,
+           0.4032328948023808,
+           0.359120510028475,
+           0.3183487254218813,
+           0.2812238939189938,
+           0.24793727191536835,
+           0.21856349182765006,
+           0.19306209805662827,
+           0.17128207417075128,
+           0.1529692134272073,
+           0.13777611310685983,
+           0.1252745073502076,
+           0.11496959488463204,
+           0.10631596867859715,
+           0.09873471536957286,
+           0.09163122425584405,
+           0.08441322940372363,
+           0.07650860438894166,
+           0.0673824374448502,
+           0.056552935102302436,
+           0.04360573424522793,
+           0.02820624505112019,
+           0.010109699447024856,
+           -0.010831359842093255,
+           -0.03466234738374261,
+           -0.061324785769157716,
+           -0.09065738905643649,
+           -0.1224000522790218,
+           -0.15620064431687614,
+           -0.19162442796451998,
+           -0.22816586202654746,
+           -0.2652624774822876,
+           -0.3023104647861478,
+           -0.3386815636123734,
+           -0.3737408109846343,
+           -0.4068646796637133,
+           -0.43745912652859975,
+           -0.4649770708058221,
+           -0.4889348343993848,
+           -0.508927100960677,
+           -0.5246399861240267,
+           -0.5358618576415436,
+           -0.5424915998371994,
+           -0.5445440804841335,
+           -0.5421526483070918,
+           -0.5355685640761928,
+           -0.5251573458210692,
+           -0.5113920871141352,
+           -0.49484388468139073,
+           -0.4761695858552487,
+           -0.4560971357153781,
+           -0.4354088664179856,
+           -0.41492312560206046,
+           -0.3954746854958597,
+           -0.3778944082790189,
+           -0.3629886655021116,
+           -0.35151901933211266,
+           -0.34418267078886183,
+           -0.341594164985839,
+           -0.34426881602144027,
+           -0.3526082752215831,
+           -0.3668886168362351,
+           -0.38725125623287787,
+           -0.41369694853723943,
+           -0.44608304217587824,
+           -0.48412408366818344,
+           -0.5273957892064333,
+           -0.5753423170314828,
+           -0.6272866943600455,
+           -0.682444175621099,
+           -0.739938236910558,
+           -0.7988188466489741,
+           -0.8580825960323399,
+           -0.9166942264001994,
+           -0.973609055264928,
+           -1.0277957793373074,
+           -1.0782591220398126,
+           -1.1240617950055767,
+           -1.164345257888875,
+           -1.1983487881178305,
+           -1.225426411352172,
+           -1.2450612934277037,
+           -1.2568772542669147,
+           -1.2606471321663968,
+           -1.256297801388608,
+           -1.243911725278546,
+           -1.2237250092681544,
+           -1.1961220011260625,
+           -1.1616265676399937,
+           -1.1208902555950493,
+           -1.0746776185221005,
+           -1.0238490574503247,
+           -0.9693415821886556,
+           -0.9121479480733673,
+           -0.8532946604862935,
+           -0.7938193648755324,
+           -0.7347481528960322,
+           -0.6770733153372812,
+           -0.6217320597408073,
+           -0.5695866853665599,
+           -0.5214066710853663,
+           -0.4778530837853145,
+           -0.4394656571798456,
+           -0.4066528249282042,
+           -0.37968491935900117,
+           -0.3586906696201394,
+           -0.34365705267400404,
+           -0.33443246919517605,
+           -0.33073313610830907,
+           -0.33215251019571496,
+           -0.3381734847987639,
+           -0.3481830359006989,
+           -0.36148893640852636,
+           -0.3773381096382059,
+           -0.3949361559984667,
+           -0.413467561542292,
+           -0.4321160839981704,
+           -0.45008481138701156,
+           -0.4666154003445911,
+           -0.4810060254621966,
+           -0.4926276066868748,
+           -0.5009379281590103,
+           -0.5054933176186761,
+           -0.505957619261559,
+           -0.5021082630520166,
+           -0.4938393082316383,
+           -0.48116141621166364,
+           -0.46419878625821515,
+           -0.4431831644063273,
+           -0.41844510994187706,
+           -0.39040277272109924,
+           -0.35954849683455536,
+           -0.32643362011624494,
+           -0.2916518834078968,
+           -0.25582189721509807,
+           -0.21956913560709182,
+           -0.1835079373772695,
+           -0.14822399236163303,
+           -0.11425777648187228,
+           -0.08208937291911714,
+           -0.05212507951232379,
+           -0.02468615497001428,
+           -2.1669325852068894e-16
+          ],
+          [
+           0,
+           0.02138066408543496,
+           0.03981342273432394,
+           0.05543378542225215,
+           0.06847859833678917,
+           0.07927893062037007,
+           0.08825027488655536,
+           0.09588031886281612,
+           0.1027146090068086,
+           0.10934048278288937,
+           0.11636969254624639,
+           0.12442017947869291,
+           0.1340974798382655,
+           0.14597625730288658,
+           0.16058245409410615,
+           0.17837653986497548,
+           0.19973831134825346,
+           0.22495365811863458,
+           0.25420366145059614,
+           0.2875563353479073,
+           0.32496125281928756,
+           0.36624722802028764,
+           0.4111231477821858,
+           0.45918196623234386,
+           0.5099077956767046,
+           0.5626859476855616,
+           0.6168157023915368,
+           0.6715255132888053,
+           0.7259902911037988,
+           0.779350355207866,
+           0.8307315959680844,
+           0.8792663575433417,
+           0.9241145288124826,
+           0.9644843209550285,
+           0.999652213964314,
+           1.0289815710090193,
+           1.0519394487029425,
+           1.0681111723143135,
+           1.0772122967698399,
+           1.0790976357387578,
+           1.0737671106315574,
+           1.0613682473256947,
+           1.0421952289829384,
+           1.0166844964795099,
+           0.9854069716920791,
+           0.9490570611132655,
+           0.9084386759856341,
+           0.8644485784023583,
+           0.8180574288157088,
+           0.7702889674871656,
+           0.7221978091873185,
+           0.6748463657435859,
+           0.6292814339532805,
+           0.5865109963456364,
+           0.547481779023217,
+           0.5130580943989449,
+           0.48400246745090575,
+           0.46095850283808343,
+           0.4444363978477806,
+           0.43480144394403436,
+           0.43226578916151415,
+           0.43688365645158517,
+           0.4485501312093601,
+           0.4670035465821184,
+           0.49183140983753465,
+           0.5224797291288706,
+           0.5582655194737763,
+           0.5983921916196829,
+           0.6419674595256549,
+           0.6880233430948118,
+           0.7355377939722161,
+           0.7834574348571404,
+           0.8307208777611861,
+           0.876282074566828,
+           0.9191331543790584,
+           0.9583262164660596,
+           0.9929935746809299,
+           1.0223659884595298,
+           1.0457884658179066,
+           1.0627332839729522,
+           1.0728099417881671,
+           1.0757718335054072,
+           1.07151951330473,
+           1.0601005031642508,
+           1.0417056802299551,
+           1.0166623623957112,
+           0.9854242900148363,
+           0.9485587756800307,
+           0.9067313610141114,
+           0.8606883777826394,
+           0.811237858960847,
+           0.7592292825024938,
+           0.7055326555883111,
+           0.6510174594987923,
+           0.596531974697244,
+           0.5428834922826821,
+           0.4908198920554756,
+           0.44101302971840906,
+           0.3940443271903281,
+           0.3503929018841448,
+           0.31042650457675464,
+           0.2743954628546811,
+           0.24242974989192714,
+           0.21453921845172277,
+           0.19061695950952015,
+           0.17044566579048964,
+           0.15370680478163498,
+           0.13999233530933602,
+           0.12881863832518986,
+           0.11964227769498213,
+           0.11187716189793277,
+           0.10491264372439943,
+           0.0981320731390396,
+           0.0909313089821686,
+           0.08273669833100539,
+           0.07302204803295463,
+           0.06132414073814788,
+           0.0472563869766265,
+           0.03052025443904962,
+           0.010914174359922363,
+           -0.011660308728641763,
+           -0.03719530529573777,
+           -0.0655763521755775,
+           -0.0965851934375643,
+           -0.12990549846652363,
+           -0.16513136805367587,
+           -0.20177840618255033,
+           -0.2392970677231246,
+           -0.27708793213890703,
+           -0.31451850209761034,
+           -0.350941084865677,
+           -0.3857112846131308,
+           -0.41820661602857,
+           -0.44784474441296657,
+           -0.4741008648396111,
+           -0.4965237528724397,
+           -0.5147500512479868,
+           -0.5285164000668487,
+           -0.5376690713448864,
+           -0.5421708309215302,
+           -0.5421048201674277,
+           -0.5376753249452644,
+           -0.5292053779822079,
+           -0.517131221240198,
+           -0.5019937350042435,
+           -0.48442701823541473,
+           -0.46514437829400473,
+           -0.4449220555719112,
+           -0.4245810681726593,
+           -0.40496761202593884,
+           -0.3869324914337582,
+           -0.37131008299252083,
+           -0.35889735138272616,
+           -0.35043343823574363,
+           -0.3465803350634262,
+           -0.3479051282807584,
+           -0.3548642691904232,
+           -0.3677902752613479,
+           -0.38688121223499045,
+           -0.4121932409041626,
+           -0.44363643942344155,
+           -0.4809740335054211,
+           -0.5238250847512264,
+           -0.5716706036677155,
+           -0.6238629706916161,
+           -0.6796384678192918,
+           -0.7381326472184465,
+           -0.7983981933559725,
+           -0.8594248734421753,
+           -0.9201611188961162,
+           -0.9795367393762447,
+           -1.0364862417239586,
+           -1.0899722096719555,
+           -1.139008196800219,
+           -1.1826805950840271,
+           -1.2201689642505513,
+           -1.250764342503372,
+           -1.273885106141995,
+           -1.2890900030646781,
+           -1.2960880517083588,
+           -1.2947450710361472,
+           -1.2850866869336173,
+           -1.2672977438827449,
+           -1.2417181360173235,
+           -1.2088351565540407,
+           -1.169272547075596,
+           -1.1237765062120564,
+           -1.0731989890283418,
+           -1.0184786921387068,
+           -0.9606201736905332,
+           -0.9006716005829183,
+           -0.8397016465709417,
+           -0.7787760835084716,
+           -0.7189346134663084,
+           -0.661168481715554,
+           -0.6063993898003952,
+           -0.5554601946706214,
+           -0.5090778349384169,
+           -0.4678588698875861,
+           -0.4322779522741162,
+           -0.4026694838155043,
+           -0.3792226243558079,
+           -0.3619797439362056,
+           -0.3508383234100783,
+           -0.34555622587173135,
+           -0.3457601800640094,
+           -0.3509572400772271,
+           -0.3605489149261441,
+           -0.3738475987141853,
+           -0.39009487858810615,
+           -0.40848125484038683,
+           -0.4281667763528324,
+           -0.4483020758238206,
+           -0.46804928330493273,
+           -0.4866023035929214,
+           -0.5032059627616013,
+           -0.517173561041474,
+           -0.5279024125276834,
+           -0.5348870057038134,
+           -0.537729481142484,
+           -0.5361471923987159,
+           -0.5299771912851965,
+           -0.5191775575132239,
+           -0.5038255731157253,
+           -0.48411282211937556,
+           -0.46033737359488824,
+           -0.4328932795451439,
+           -0.40225768625910924,
+           -0.3689759170921536,
+           -0.3336449346564393,
+           -0.2968956298801439,
+           -0.2593744133497421,
+           -0.2217246001042457,
+           -0.1845680822302207,
+           -0.14848777415420755,
+           -0.1140112937050369,
+           -0.08159630839335429,
+           -0.05161793179694953,
+           -0.02435850059004337,
+           -2.1310400095194143e-16
+          ],
+          [
+           0,
+           0.02090612457373407,
+           0.03884876278114237,
+           0.05402085484805808,
+           0.06671575136217166,
+           0.07731835023092874,
+           0.08629361660585508,
+           0.09417278804876533,
+           0.10153762831024492,
+           0.10900314493584963,
+           0.11719922718586187,
+           0.12675169039089282,
+           0.13826323010100067,
+           0.15229479376476235,
+           0.1693478690645131,
+           0.1898481666291156,
+           0.21413114116261678,
+           0.24242974989192667,
+           0.27486479176422035,
+           0.31143810639156383,
+           0.3520288399500313,
+           0.3963929078844547,
+           0.444165703281911,
+           0.49486801718581197,
+           0.5479150550007432,
+           0.6026283535512752,
+           0.6582503283117793,
+           0.7139611117156371,
+           0.7688972830210145,
+           0.8221720394962564,
+           0.8728963189914228,
+           0.920200356312397,
+           0.9632551409412566,
+           1.0012932419658567,
+           1.0336284776800206,
+           1.0596739319508919,
+           1.0789578565548221,
+           1.0911370473799187,
+           1.0960073415147733,
+           1.093510950360746,
+           1.0837404193652846,
+           1.0669390859367174,
+           1.0434979915872913,
+           1.0139492902903806,
+           0.9789562803190225,
+           0.9393002693577392,
+           0.8958645604132814,
+           0.8496159170722859,
+           0.8015839292064824,
+           0.752838752756202,
+           0.7044677384217078,
+           0.6575514929272143,
+           0.6131399322644879,
+           0.5722288885624671,
+           0.535737820888198,
+           0.504489155617454,
+           0.47918974460285946,
+           0.4604148801081824,
+           0.44859524555606317,
+           0.4440071120011158,
+           0.4467660135661273,
+           0.45682405272638427,
+           0.47397090029619626,
+           0.49783846735322274,
+           0.5279091392601812,
+           0.5635273775266403,
+           0.603914415547314,
+           0.64818570119334,
+           0.6953706745918181,
+           0.7444344147720444,
+           0.7943006455046429,
+           0.8438755596548683,
+           0.8920719034531029,
+           0.9378327576723368,
+           0.9801544618811227,
+           1.0181081504648952,
+           1.0508594044055728,
+           1.077685569993303,
+           1.0979903535391577,
+           1.1113153683262236,
+           1.1173483848163004,
+           1.1159281156733105,
+           1.1070454514871728,
+           1.090841149108482,
+           1.067600060122023,
+           1.037742070097253,
+           1.001809997823615,
+           0.960454775851338,
+           0.9144182975607495,
+           0.8645143701282836,
+           0.8116082558426567,
+           0.7565953152239302,
+           0.700379283586309,
+           0.6438507176564467,
+           0.5878661405347326,
+           0.5332283919196746,
+           0.48066865667985814,
+           0.43083059943747154,
+           0.3842569769911012,
+           0.3413790355788701,
+           0.3025089278122247,
+           0.2678353064209162,
+           0.23742217070004315,
+           0.21121095878391052,
+           0.18902579666597835,
+           0.17058173529836612,
+           0.15549573212746387,
+           0.14330006492451164,
+           0.1334578054562004,
+           0.12537992990702415,
+           0.11844360326385875,
+           0.11201114707936893,
+           0.1054491848194939,
+           0.09814745672968725,
+           0.08953680685751653,
+           0.07910586825229474,
+           0.06641600781380388,
+           0.051114138867023415,
+           0.0329430661034747,
+           0.011749092607852334,
+           -0.012513309376895177,
+           -0.039779885331692674,
+           -0.06987808434422922,
+           -0.10253160427566921,
+           -0.13736787644387932,
+           -0.17392829305843438,
+           -0.21168090865423525,
+           -0.25003528162154975,
+           -0.28835906527939886,
+           -0.32599591123180116,
+           -0.36228421217837764,
+           -0.3965761878381743,
+           -0.42825680680165557,
+           -0.45676203924555764,
+           -0.48159595049753295,
+           -0.5023461730658944,
+           -0.5186973342808575,
+           -0.5304420671541075,
+           -0.5374892922036136,
+           -0.5398695263156625,
+           -0.5377370495233529,
+           -0.531368840001879,
+           -0.5211602696282979,
+           -0.5076176350700138,
+           -0.4913476804763618,
+           -0.47304434540955675,
+           -0.4534730437072301,
+           -0.4334528436949478,
+           -0.4138369759183043,
+           -0.39549213991607873,
+           -0.37927711534000796,
+           -0.36602120406036154,
+           -0.35650303820504065,
+           -0.35143028411162447,
+           -0.35142075400444267,
+           -0.35698540624836494,
+           -0.36851367200210694,
+           -0.38626149202213445,
+           -0.4103423835553973,
+           -0.4407217852510989,
+           -0.4772148495707431,
+           -0.519487769197061,
+           -0.5670626384674748,
+           -0.6193257649836487,
+           -0.6755392623864234,
+           -0.734855674908248,
+           -0.7963353097066241,
+           -0.8589658859869195,
+           -0.921684052202344,
+           -0.9833982756077227,
+           -1.0430125733164242,
+           -1.09945053164998,
+           -1.1516790515488777,
+           -1.198731262375378,
+           -1.239728064496065,
+           -1.2738977921638346,
+           -1.3005935316848913,
+           -1.319307684612454,
+           -1.329683430433743,
+           -1.3315228163439883,
+           -1.3247912814574505,
+           -1.3096185072545714,
+           -1.2862955731544712,
+           -1.2552684837163444,
+           -1.217128219981846,
+           -1.1725975497829244,
+           -1.1225149084558859,
+           -1.0678157304630511,
+           -1.0095116722540096,
+           -0.9486682158517077,
+           -0.8863811799395966,
+           -0.8237526897606354,
+           -0.761867168336828,
+           -0.7017679091256882,
+           -0.6444347743273108,
+           -0.5907635340538492,
+           -0.5415473202036762,
+           -0.49746061617927206,
+           -0.45904614086186984,
+           -0.4267049140616552,
+           -0.40068971276026255,
+           -0.3811020447743855,
+           -0.36789268103216105,
+           -0.36086570156774667,
+           -0.359685925716528,
+           -0.3638895159058416,
+           -0.3728974688647434,
+           -0.38603163986185585,
+           -0.4025328863779915,
+           -0.42158086885911084,
+           -0.4423150090432606,
+           -0.46385608169073467,
+           -0.4853279039370948,
+           -0.5058785881765948,
+           -0.5247008392815876,
+           -0.5410508046568866,
+           -0.5542650253852073,
+           -0.5637750875114278,
+           -0.5691196330380037,
+           -0.5699534589207447,
+           -0.5660535075223656,
+           -0.5573216317023952,
+           -0.5437840999890048,
+           -0.5255878900239287,
+           -0.5029938996217559,
+           -0.4763672823087565,
+           -0.4461651861683591,
+           -0.412922239427344,
+           -0.37723418186307006,
+           -0.3397400864193607,
+           -0.3011036492699798,
+           -0.2619940481362419,
+           -0.22306687743096285,
+           -0.18494566456848094,
+           -0.1482044546807207,
+           -0.1133519214663017,
+           -0.08081742073913382,
+           -0.05093935149301236,
+           -0.023956128283113613,
+           -2.0893268024778127e-16
+          ],
+          [
+           0,
+           0.02039294675687974,
+           0.03783638260468888,
+           0.05258167991574526,
+           0.0649786098155444,
+           0.07546472596708281,
+           0.08455223073303332,
+           0.09281267077342581,
+           0.10085986654481195,
+           0.1093315272651091,
+           0.1188700384911216,
+           0.1301029326070934,
+           0.14362356263889794,
+           0.15997249661363944,
+           0.17962013323735415,
+           0.20295101035656235,
+           0.23025023621904275,
+           0.2616924209781289,
+           0.29733342349683817,
+           0.3371051578556642,
+           0.38081362681342923,
+           0.42814026774292496,
+           0.47864661230913097,
+           0.531782176491695,
+           0.5868954146036304,
+           0.643247491814707,
+           0.7000285563496818,
+           0.7563761268563286,
+           0.8113951540966959,
+           0.8641792705482808,
+           0.9138327078852896,
+           0.9594923415240943,
+           1.0003493140237967,
+           1.035669695362907,
+           1.0648136578584062,
+           1.0872526763096944,
+           1.1025843090671257,
+           1.110544172065986,
+           1.111014784074039,
+           1.1040310358687409,
+           1.0897821169754378,
+           1.0686098189832782,
+           1.0410032222195411,
+           1.0075898605506879,
+           0.9691235451250076,
+           0.9264691098561362,
+           0.8805844173440339,
+           0.8325000318615767,
+           0.783297024314946,
+           0.734083421263492,
+           0.6859698449793894,
+           0.6400449132592311,
+           0.5973509757108061,
+           0.5588607573071381,
+           0.5254554602468217,
+           0.4979048420445537,
+           0.4768497420864228,
+           0.4627874717181388,
+           0.4560604156700657,
+           0.4568481168884813,
+           0.4651630344739985,
+           0.4808500774251287,
+           0.5035899273613033,
+           0.5329060735313416,
+           0.5681753953851565,
+           0.6086420439382245,
+           0.6534342951322091,
+           0.7015839782855695,
+           0.7520480222349016,
+           0.8037316123551453,
+           0.8555124145063701,
+           0.9062652979771959,
+           0.9548869792475145,
+           1.000320012106745,
+           1.0415755672268097,
+           1.077754475250429,
+           1.1080660510364935,
+           1.1318442718177084,
+           1.1485609473028706,
+           1.1578355935807043,
+           1.159441803230677,
+           1.153309989332884,
+           1.1395264689951288,
+           1.118328940420842,
+           1.0900984942587122,
+           1.0553483828819992,
+           1.0147098483185,
+           0.9689153789152369,
+           0.9187798247933101,
+           0.8651798512816975,
+           0.8090322466385997,
+           0.7512716245993327,
+           0.6928280730756465,
+           0.634605297451748,
+           0.5774597904951158,
+           0.5221815313792534,
+           0.4694766744780983,
+           0.4199526355195504,
+           0.3741059197366369,
+           0.33231296542998345,
+           0.29482419865769166,
+           0.2617614125587109,
+           0.23311850016201965,
+           0.20876548456147018,
+           0.18845570717357424,
+           0.17183595552206837,
+           0.1584592385864227,
+           0.14779985203888168,
+           0.13927031930743244,
+           0.13223974873510108,
+           0.12605311328303753,
+           0.12005093807092651,
+           0.11358887306923154,
+           0.10605663362800032,
+           0.09689581008525691,
+           0.0856160789519265,
+           0.0718093913087276,
+           0.055161767964228975,
+           0.03546239423294341,
+           0.012609778282987896,
+           -0.013385185935319401,
+           -0.042399329094772426,
+           -0.0742004851192846,
+           -0.10845385005323119,
+           -0.1447312525806603,
+           -0.18252309129996003,
+           -0.2212526238025817,
+           -0.2602922305753502,
+           -0.2989812243250534,
+           -0.33664473385030735,
+           -0.3726131621232869,
+           -0.406241701554923,
+           -0.43692938594291186,
+           -0.4641371684512907,
+           -0.4874045379170496,
+           -0.5063642212672679,
+           -0.5207545669871869,
+           -0.5304292622386623,
+           -0.5353641029569927,
+           -0.5356606103895075,
+           -0.5315463672301992,
+           -0.5233720297569361,
+           -0.5116050571044328,
+           -0.4968202828791761,
+           -0.47968753562604927,
+           -0.4609565911397584,
+           -0.4414398093426725,
+           -0.42199286965475274,
+           -0.4034940698998843,
+           -0.3868226935139441,
+           -0.3728369771120719,
+           -0.3623522246123238,
+           -0.35611961470240544,
+           -0.35480623541413303,
+           -0.35897685321358275,
+           -0.3690778849325207,
+           -0.3854239899849541,
+           -0.40818763885270154,
+           -0.43739194327190956,
+           -0.47290695562317364,
+           -0.5144495616224928,
+           -0.5615870035692608,
+           -0.6137439832608436,
+           -0.6702132063974862,
+           -0.7301691460257795,
+           -0.792684723383329,
+           -0.8567505323694498,
+           -0.9212961705641977,
+           -0.9852131868245699,
+           -1.047379114321572,
+           -1.1066820294787354,
+           -1.1620450623526748,
+           -1.2124502829502903,
+           -1.2569614008562426,
+           -1.2947447420570384,
+           -1.3250880063691777,
+           -1.3474163604624807,
+           -1.3613054838743224,
+           -1.366491257127755,
+           -1.3628758603592424,
+           -1.35053013580612,
+           -1.3296921560369896,
+           -1.300762029778468,
+           -1.26429306641195,
+           -1.220979506515258,
+           -1.171641107108854,
+           -1.117204944560248,
+           -1.0586848636006083,
+           -0.9971590560276407,
+           -0.9337462960763715,
+           -0.869581390090615,
+           -0.8057904152908147,
+           -0.7434663257087911,
+           -0.6836454926867961,
+           -0.6272857229991752,
+           -0.5752462602669255,
+           -0.5282702258343361,
+           -0.4869698948944874,
+           -0.45181513388396627,
+           -0.4231252477417902,
+           -0.40106440245388786,
+           -0.38564070143104123,
+           -0.3767089058310888,
+           -0.37397670110581765,
+           -0.3770143269808334,
+           -0.3852673078421501,
+           -0.39807194706214766,
+           -0.41467318393422165,
+           -0.43424435716882975,
+           -0.45590837564856784,
+           -0.47875976637527634,
+           -0.5018870519856244,
+           -0.5243949062523477,
+           -0.545425545677887,
+           -0.5641788383388454,
+           -0.5799306469359276,
+           -0.5920489706122889,
+           -0.6000075082999271,
+           -0.6033963336546638,
+           -0.6019294463379982,
+           -0.5954490446112038,
+           -0.5839264479024142,
+           -0.567459683087988,
+           -0.5462678325612987,
+           -0.5206823236350994,
+           -0.49113541540277306,
+           -0.45814620896075375,
+           -0.42230456813448297,
+           -0.38425338903565126,
+           -0.3446696966459892,
+           -0.3042450741949885,
+           -0.26366594570822977,
+           -0.22359423340838358,
+           -0.1846488996457118,
+           -0.14738885804702168,
+           -0.11229770125535891,
+           -0.07977064395034841,
+           -0.05010402103942172,
+           -0.023487613495028595,
+           -2.0426928051054333e-16
+          ],
+          [
+           0,
+           0.01985246688010141,
+           0.03680009742378555,
+           0.05115306622391169,
+           0.0633168248252045,
+           0.07377974840110432,
+           0.08309839515670903,
+           0.09188076911518828,
+           0.1007680298865027,
+           0.11041513463773125,
+           0.12147092671657464,
+           0.13455820146778252,
+           0.15025428230092508,
+           0.1690726289329714,
+           0.19144597520005247,
+           0.21771145650645543,
+           0.24809813777488104,
+           0.2827172928998012,
+           0.32155571767455254,
+           0.36447228168444823,
+           0.41119784264438003,
+           0.46133856116400257,
+           0.5143825670916238,
+           0.5697098426018194,
+           0.6266051042170889,
+           0.6842733880850564,
+           0.7418579720408142,
+           0.7984602060672634,
+           0.8531607713050608,
+           0.905041848080814,
+           0.953209646549223,
+           0.9968167401967469,
+           1.0350836430103532,
+           1.0673190856091954,
+           1.0929384737569108,
+           1.111480053765758,
+           1.1226183623951267,
+           1.1261746026603017,
+           1.1221236599581472,
+           1.1105975533090415,
+           1.0918852023462549,
+           1.0664284798534232,
+           1.0348146099692186,
+           0.9977650614242947,
+           0.9561211711494613,
+           0.910826814172796,
+           0.862908508912832,
+           0.813453410959462,
+           0.7635857016215887,
+           0.7144419185817578,
+           0.6671458039001192,
+           0.622783258642191,
+           0.582377993195871,
+           0.5468684478711805,
+           0.5170865299696203,
+           0.49373867183940356,
+           0.477389660494825,
+           0.4684496244711482,
+           0.4671644892788014,
+           0.47361013091234516,
+           0.48769036934758947,
+           0.5091388529499902,
+           0.5375247924308137,
+           0.5722624116681047,
+           0.6126238945774518,
+           0.6577555244152409,
+           0.7066966364360581,
+           0.7584009385378382,
+           0.8117596990194815,
+           0.8656262571880153,
+           0.9188412823302287,
+           0.9702581902284477,
+           1.0187681243324247,
+           1.0633239209300898,
+           1.1029625038697104,
+           1.1368251939130485,
+           1.1641754696561262,
+           1.1844137798525165,
+           1.1970890793561875,
+           1.2019068409786693,
+           1.1987333813543957,
+           1.1875964283169098,
+           1.1686819481104946,
+           1.1423273407692112,
+           1.1090111989849434,
+           1.069339907633163,
+           1.0240314358358127,
+           0.9738967392012454,
+           0.9198192451021571,
+           0.8627329372083911,
+           0.8035995859525135,
+           0.7433856884635949,
+           0.683039684388043,
+           0.6234700029018664,
+           0.5655244714293125,
+           0.509971578779925,
+           0.4574840355821676,
+           0.40862501430620873,
+           0.363837381374564,
+           0.32343615662599773,
+           0.28760435267555706,
+           0.2563922605842404,
+           0.22972016087862038,
+           0.20738435253297763,
+           0.18906630920526105,
+           0.1743446938827294,
+           0.16270989208873904,
+           0.15358066169219287,
+           0.1463224456830911,
+           0.1402668543048193,
+           0.13473179564421886,
+           0.12904171983237325,
+           0.12254744172492815,
+           0.11464502028965218,
+           0.10479319956716772,
+           0.09252895529134811,
+           0.07748074204626634,
+           0.059379096894133315,
+           0.03806432517362526,
+           0.013491070862490186,
+           -0.014270344428853637,
+           -0.045035845190424965,
+           -0.07851273449984417,
+           -0.11430789737214768,
+           -0.1519388567042968,
+           -0.19084738875340534,
+           -0.23041533777904144,
+           -0.2699822113684146,
+           -0.3088640905304674,
+           -0.3463733531040676,
+           -0.38183868629119777,
+           -0.4146248547906693,
+           -0.4441516953271348,
+           -0.46991182625609423,
+           -0.49148659194859445,
+           -0.5085598050589735,
+           -0.5209289044823071,
+           -0.528513211456696,
+           -0.5313590392486374,
+           -0.5296414913549713,
+           -0.5236628671733544,
+           -0.5138476805287892,
+           -0.5007343831260141,
+           -0.48496396974568173,
+           -0.46726572267950395,
+           -0.4484404274668565,
+           -0.42934145856200445,
+           -0.4108541904327266,
+           -0.3938742353112723,
+           -0.3792850422065277,
+           -0.3679354119657714,
+           -0.3606174895967305,
+           -0.35804578751832355,
+           -0.36083777204115847,
+           -0.3694965106702596,
+           -0.38439583058903193,
+           -0.40576838005435983,
+           -0.43369691582254194,
+           -0.46810906279964537,
+           -0.5087757087427326,
+           -0.5553131090687536,
+           -0.6071886868073384,
+           -0.6637304226742777,
+           -0.7241396423615469,
+           -0.7875069246051749,
+           -0.8528307764693607,
+           -0.9190386534847247,
+           -0.9850098435094605,
+           -1.0495996859100767,
+           -1.1116645630675521,
+           -1.1700870801800982,
+           -1.223800842397908,
+           -1.271814245685365,
+           -1.3132327193086795,
+           -1.3472788929905166,
+           -1.3733102097221117,
+           -1.3908335648261638,
+           -1.3995166216829669,
+           -1.3991955328783712,
+           -1.3898788805060618,
+           -1.371747738895534,
+           -1.3451518549658037,
+           -1.3106020334886053,
+           -1.2687589045449703,
+           -1.2204183361874623,
+           -1.1664938346937646,
+           -1.1079963458881608,
+           -1.0460119320914427,
+           -0.9816778488583399,
+           -0.9161575825776489,
+           -0.8506154333587048,
+           -0.7861912368554349,
+           -0.7239758135800405,
+           -0.6649877149769139,
+           -0.6101518025557344,
+           -0.5602801505482029,
+           -0.5160557049969341,
+           -0.4780190643350514,
+           -0.4465586700493013,
+           -0.4219046128249049,
+           -0.4041261716962965,
+           -0.39313311333507306,
+           -0.38868068791403404,
+           -0.39037816921627017,
+           -0.3977007019816427,
+           -0.41000414096537835,
+           -0.426542495734574,
+           -0.4464875345549367,
+           -0.46895005128409384,
+           -0.493002262170494,
+           -0.5177007757302121,
+           -0.5421095689790657,
+           -0.5653224074321078,
+           -0.5864841642966058,
+           -0.6048105256843229,
+           -0.6196056126296839,
+           -0.6302771060875962,
+           -0.6363485264827298,
+           -0.6374683931294588,
+           -0.6334160690730143,
+           -0.6241041815952418,
+           -0.6095775956530706,
+           -0.5900090046917854,
+           -0.5656912884160692,
+           -0.5370268680831114,
+           -0.5045143646850628,
+           -0.46873293215272904,
+           -0.4303246947830874,
+           -0.38997576406016266,
+           -0.3483963437729118,
+           -0.30630045301432746,
+           -0.2643858037811228,
+           -0.22331436333198054,
+           -0.18369411139725642,
+           -0.1460624692963723,
+           -0.11087183286840595,
+           -0.07847758501769297,
+           -0.049128898055488764,
+           -0.0229625625549281,
+           -1.992122277649548e-16
+          ],
+          [
+           0,
+           0.01929666679859876,
+           0.0357646851569261,
+           0.04977274589761116,
+           0.06178057227754399,
+           0.07232486603059685,
+           0.08200302727872599,
+           0.09145508084031795,
+           0.10134428917593416,
+           0.1123369676540115,
+           0.1250820400812779,
+           0.14019088094473475,
+           0.15821798532024545,
+           0.17964298803541418,
+           0.20485452089933853,
+           0.23413635143470368,
+           0.26765618969235344,
+           0.3054574828088516,
+           0.34745444165262673,
+           0.3934304620765583,
+           0.44304001700344525,
+           0.49581400698036887,
+           0.5511684681747973,
+           0.6084164502816214,
+           0.6667827946486463,
+           0.7254214671865672,
+           0.7834350332298817,
+           0.8398958041748473,
+           0.8938681399090197,
+           0.9444313579491579,
+           0.990702680690605,
+           1.0318596467753802,
+           1.0671614214911374,
+           1.0959684641463932,
+           1.1177600470045403,
+           1.1321491697363664,
+           1.1388944742858664,
+           1.1379088360652476,
+           1.129264386776926,
+           1.113193809966637,
+           1.0900878405428225,
+           1.060488991741958,
+           1.0250816251091381,
+           0.9846785687289924,
+           0.9402045739699022,
+           0.8926769792908236,
+           0.8431840192631986,
+           0.7928612761493942,
+           0.7428668186761593,
+           0.6943556068593023,
+           0.6484537620065546,
+           0.6062333068234389,
+           0.5686879717007501,
+           0.5367106399603598,
+           0.5110729676219318,
+           0.49240766301227656,
+           0.48119384947735044,
+           0.4777458620713298,
+           0.48220574813881056,
+           0.49453965413762097,
+           0.5145381889965456,
+           0.5418207600009458,
+           0.5758437829422237,
+           0.6159125763461885,
+           0.6611966622456917,
+           0.7107481153075926,
+           0.7635225301223364,
+           0.8184021148632015,
+           0.8742203698132629,
+           0.9297877726415419,
+           0.9839178696644302,
+           1.0354531641905502,
+           1.083290199597262,
+           1.1264032558456119,
+           1.1638661131729928,
+           1.1948713848324417,
+           1.218746980777874,
+           1.2349693346384762,
+           1.2431731054427457,
+           1.2431571513924191,
+           1.2348866634361368,
+           1.2184914392295079,
+           1.1942603710149675,
+           1.1626323117354105,
+           1.1241835700915657,
+           1.079612365158285,
+           1.029720642647134,
+           0.9753937162117454,
+           0.9175782468622765,
+           0.8572591104006343,
+           0.7954357259427387,
+           0.7330984275322532,
+           0.6712054553990099,
+           0.6106611237585368,
+           0.5522956887217234,
+           0.4968473937588512,
+           0.44494711242815954,
+           0.39710594020994594,
+           0.3537060110052654,
+           0.31499473109138404,
+           0.28108253615913636,
+           0.25194418767995214,
+           0.22742353550282868,
+           0.20724158649847035,
+           0.19100763642260846,
+           0.1782331460214128,
+           0.16834797464050408,
+           0.16071852690371566,
+           0.15466732182165352,
+           0.1494934601061835,
+           0.14449344531993455,
+           0.13898180825614181,
+           0.13231099175022262,
+           0.12388997474428609,
+           0.11320114928650547,
+           0.09981501134403398,
+           0.08340228462688638,
+           0.06374316456825024,
+           0.04073344545044328,
+           0.014387375474056286,
+           -0.015162829739362511,
+           -0.047670797320240925,
+           -0.08278302621967557,
+           -0.12004894622201605,
+           -0.1589337386314027,
+           -0.19883357791275444,
+           -0.23909288982832919,
+           -0.2790231682045262,
+           -0.31792285075300253,
+           -0.3550977254242562,
+           -0.38988132333869285,
+           -0.42165475282785647,
+           -0.44986544158499314,
+           -0.4740442800754381,
+           -0.49382069855466654,
+           -0.5089352613175887,
+           -0.5192494238838484,
+           -0.5247521701643266,
+           -0.5255633254724239,
+           -0.5219334255680295,
+           -0.5142401096389426,
+           -0.5029810940314481,
+           -0.4887638714025887,
+           -0.47229236456711615,
+           -0.45435084351505395,
+           -0.4357854858751305,
+           -0.4174840236696149,
+           -0.4003539709490637,
+           -0.38529996647941955,
+           -0.3732007920481027,
+           -0.3648866394557858,
+           -0.3611171975069964,
+           -0.36256111430014254,
+           -0.3697773601955375,
+           -0.383198973704685,
+           -0.403119617221627,
+           -0.4296833033386663,
+           -0.4628775770576802,
+           -0.5025303563610587,
+           -0.5483105453672673,
+           -0.5997324428273783,
+           -0.6561638762672504,
+           -0.7168379009212208,
+           -0.7808678149856552,
+           -0.8472651608098792,
+           -0.9149603074670649,
+           -0.9828251455505415,
+           -1.0496973716309077,
+           -1.1144057989234508,
+           -1.1757961033839193,
+           -1.2327564013730776,
+           -1.284242056556132,
+           -1.3292991298234937,
+           -1.3670859163675804,
+           -1.3968920579094721,
+           -1.4181547743907656,
+           -1.430471826873926,
+           -1.4336109003000586,
+           -1.4275151792735932,
+           -1.4123049801286052,
+           -1.3882753959935255,
+           -1.3558900061384735,
+           -1.3157707942630594,
+           -1.2686845102919253,
+           -1.215525794504515,
+           -1.157297459387274,
+           -1.0950883916017733,
+           -1.0300495922868074,
+           -0.9633689172063241,
+           -0.8962451079752073,
+           -0.8298617210321528,
+           -0.765361561823191,
+           -0.7038222178107102,
+           -0.6462332557891696,
+           -0.5934756072777533,
+           -0.5463036115121693,
+           -0.5053301201184361,
+           -0.4710149925394773,
+           -0.4436572285521294,
+           -0.42339089579565625,
+           -0.41018491830751974,
+           -0.4038466988848168,
+           -0.40402945594434714,
+           -0.4102430666948088,
+           -0.42186812503019305,
+           -0.43817284663453643,
+           -0.4583323871965782,
+           -0.4814500839766454,
+           -0.5065800875820408,
+           -0.5327508207201808,
+           -0.5589886846088313,
+           -0.5843414319803191,
+           -0.6079006382161101,
+           -0.6288227287289373,
+           -0.6463480605655159,
+           -0.6598176082998295,
+           -0.6686868672895415,
+           -0.6725366596731505,
+           -0.6710806082621953,
+           -0.6641691287183802,
+           -0.6517898789562203,
+           -0.6340646943553284,
+           -0.6112431258589089,
+           -0.5836927831649756,
+           -0.5518867648622504,
+           -0.5163885295423172,
+           -0.47783462484290923,
+           -0.4369157434886348,
+           -0.39435661541289957,
+           -0.35089527199150666,
+           -0.307262231646814,
+           -0.26416015528902215,
+           -0.22224450529823628,
+           -0.18210571341794682,
+           -0.14425332176886804,
+           -0.1091025082644954,
+           -0.07696334437377789,
+           -0.048033061050361626,
+           -0.022391519570019596,
+           -1.9386738893974302e-16
+          ],
+          [
+           0,
+           0.018738044529636785,
+           0.034755610372814806,
+           0.048478945043960185,
+           0.06041996157530632,
+           0.07116054102562398,
+           0.08133480028321591,
+           0.09160979729250576,
+           0.10266518757791795,
+           0.115172374542572,
+           0.12977371074404184,
+           0.14706230780562038,
+           0.16756299877881872,
+           0.1917149689608859,
+           0.21985653007161882,
+           0.25221245932348874,
+           0.2888842606049414,
+           0.32984363134244804,
+           0.37492933745340246,
+           0.42384761218145683,
+           0.476176104691174,
+           0.5313713133491303,
+           0.5887793489231298,
+           0.6476497867520397,
+           0.707152286454354,
+           0.7663955849941163,
+           0.8244484057590964,
+           0.8803617743432182,
+           0.9331921923017835,
+           0.9820250942925713,
+           1.025998002420565,
+           1.0643227946071676,
+           1.0963065213814982,
+           1.1213702372541805,
+           1.1390653580413959,
+           1.149087113081655,
+           1.151284729842615,
+           1.1456680662876786,
+           1.1324104916644857,
+           1.1118479070040368,
+           1.084473890357668,
+           1.0509310463452486,
+           1.0119987326126405,
+           0.9685774250033787,
+           0.9216700664319114,
+           0.8723608195412951,
+           0.8217917083699685,
+           0.7711376878152283,
+           0.7215807203225445,
+           0.6742834659229843,
+           0.6303632038003517,
+           0.5908666006685374,
+           0.5567459234184611,
+           0.5288372611599362,
+           0.5078412757005482,
+           0.49430694077331444,
+           0.4886186603608536,
+           0.49098707695629484,
+           0.5014437934756357,
+           0.5198401399063145,
+           0.5458500198920346,
+           0.5789767756448594,
+           0.6185639141962636,
+           0.663809446368779,
+           0.7137835041972442,
+           0.7674488249353641,
+           0.8236836221336863,
+           0.8813063082099893,
+           0.9391014898088584,
+           0.9958466281032741,
+           1.0503387417236427,
+           1.101420530545453,
+           1.1480053140942996,
+           1.1891002084380649,
+           1.2238270093753996,
+           1.251440306403921,
+           1.271342419956719,
+           1.2830948320512705,
+           1.2864258658862906,
+           1.2812344609473536,
+           1.267589984604607,
+           1.245728116688843,
+           1.216042937776419,
+           1.1790754425949335,
+           1.135498784868065,
+           1.0861006369839699,
+           1.0317631152286193,
+           0.9734407773483794,
+           0.9121372425526226,
+           0.8488810137109005,
+           0.7847010967543944,
+           0.7206030128295255,
+           0.6575457846089633,
+           0.5964204497414953,
+           0.5380306124696638,
+           0.48307549004910355,
+           0.4321358451583263,
+           0.3856631206560219,
+           0.3439720107177526,
+           0.30723661464032853,
+           0.27549022864551675,
+           0.2486287391254284,
+           0.22641749024880062,
+           0.2085014119501293,
+           0.1944181132167352,
+           0.18361357228793945,
+           0.1754599917018694,
+           0.1692753336412752,
+           0.16434401102922375,
+           0.15993818328277695,
+           0.15533909318298542,
+           0.1498578832435076,
+           0.14285534617755885,
+           0.13376009413462586,
+           0.12208467451793861,
+           0.10743921528704121,
+           0.0895422482836631,
+           0.06822843361630188,
+           0.04345298960089302,
+           0.0152927191090462,
+           -0.016056387772877483,
+           -0.050284905382340324,
+           -0.08697892137219256,
+           -0.12563194221703844,
+           -0.1656594372844352,
+           -0.20641563415721043,
+           -0.24721211853862485,
+           -0.2873377441387103,
+           -0.326079322652577,
+           -0.36274254220640045,
+           -0.3966725550300885,
+           -0.42727368182773884,
+           -0.4540277012079278,
+           -0.47651022709838936,
+           -0.4944047244517642,
+           -0.5075137725755041,
+           -0.5157672546196597,
+           -0.5192272294035375,
+           -0.5180893259134136,
+           -0.5126805893495701,
+           -0.503453798318979,
+           -0.4909783633785389,
+           -0.4759280053501429,
+           -0.45906549542576236,
+           -0.44122481594222185,
+           -0.42329116887985985,
+           -0.40617931688827125,
+           -0.3908107874844772,
+           -0.37809050381659337,
+           -0.3688834241765041,
+           -0.3639917767611183,
+           -0.36413346586629325,
+           -0.36992220095714995,
+           -0.3818498614595371,
+           -0.40027155857196667,
+           -0.4253937921414065,
+           -0.45726602720947046,
+           -0.49577593300337447,
+           -0.540648438916386,
+           -0.5914486695560487,
+           -0.6475887265056215,
+           -0.7083381903686471,
+           -0.7728381252684124,
+           -0.8401182815117836,
+           -0.9091171127415053,
+           -0.9787041535635903,
+           -1.047704244098161,
+           -1.1149230406513246,
+           -1.1791732179313794,
+           -1.2393007487931578,
+           -1.2942106428976992,
+           -1.342891536064069,
+           -1.3844385472416192,
+           -1.4180738593572955,
+           -1.4431645328576443,
+           -1.4592371253077665,
+           -1.4659887653726287,
+           -1.4632944130767407,
+           -1.4512101283903251,
+           -1.4299722647354915,
+           -1.3999926006473598,
+           -1.3618495192131865,
+           -1.3162754387031825,
+           -1.2641407867191945,
+           -1.2064348920598085,
+           -1.1442442413437193,
+           -1.0787286094791797,
+           -1.0110956228128984,
+           -0.9425743500352749,
+           -0.874388537789745,
+           -0.8077301149145832,
+           -0.7437335811821586,
+           -0.6834518735094004,
+           -0.6278342654724428,
+           -0.577706805495095,
+           -0.5337557365478811,
+           -0.49651426713875135,
+           -0.46635298160124516,
+           -0.4434740892055649,
+           -0.42790961860857746,
+           -0.4195235689041428,
+           -0.4180179333703805,
+           -0.4229424192645284,
+           -0.4337075989538568,
+           -0.4496011464382265,
+           -0.46980674088942115,
+           -0.4934251569564631,
+           -0.5194970117530643,
+           -0.54702660184113,
+           -0.5750062410114154,
+           -0.6024405017477742,
+           -0.628369770091389,
+           -0.6518925449772841,
+           -0.6721859484193401,
+           -0.6885239612497493,
+           -0.7002929592311853,
+           -0.7070041947219544,
+           -0.7083029479023332,
+           -0.7039741568737552,
+           -0.6939444255745082,
+           -0.6782804001664747,
+           -0.6571835960400165,
+           -0.630981846572497,
+           -0.6001176290405893,
+           -0.565133600531278,
+           -0.5266557453992388,
+           -0.48537459407950617,
+           -0.4420250194489841,
+           -0.39736515030319386,
+           -0.3521549610686152,
+           -0.30713510214659345,
+           -0.26300652618158715,
+           -0.2204114423251844,
+           -0.17991609384239068,
+           -0.14199580513163287,
+           -0.10702268367239431,
+           -0.075256292124344,
+           -0.04683752757294884,
+           -0.021785860740657765,
+           -1.8834696688469665e-16
+          ],
+          [
+           0,
+           0.018189476666292146,
+           0.033798735767955376,
+           0.04730993852561034,
+           0.059284435807022154,
+           0.07034550480902858,
+           0.08115927186281155,
+           0.09241433028802011,
+           0.10480059729789842,
+           0.11898797511110246,
+           0.13560538810610318,
+           0.15522075987499737,
+           0.17832247157827896,
+           0.20530280661845682,
+           0.23644383723732304,
+           0.2719061474270951,
+           0.31172071505591536,
+           0.355784196130084,
+           0.4038577676516881,
+           0.45556959474976577,
+           0.5104208949465887,
+           0.5677954799038162,
+           0.6269725651086812,
+           0.6871425529788471,
+           0.7474254169385638,
+           0.8068912451283462,
+           0.8645824443136528,
+           0.9195370587468898,
+           0.970812626399564,
+           1.0175099769719276,
+           1.0587963729045844,
+           1.0939274063904454,
+           1.1222670918738322,
+           1.1433056341173287,
+           1.156674405654687,
+           1.1621577330393302,
+           1.1597011671549533,
+           1.1494159971311868,
+           1.131579858044071,
+           1.1066333773567203,
+           1.075172901641212,
+           1.0379394411397862,
+           0.9958040628021183,
+           0.9497500502738665,
+           0.9008522297325321,
+           0.8502539314715247,
+           0.7991421169520059,
+           0.7487212481770236,
+           0.7001865095056591,
+           0.654697010567963,
+           0.6133496022766072,
+           0.5771539259439159,
+           0.5470092884650235,
+           0.5236839150514465,
+           0.5077970760814086,
+           0.49980451759185957,
+           0.4999875473890406,
+           0.508446042575606,
+           0.5250955515716708,
+           0.5496685666955408,
+           0.5817199444245307,
+           0.6206363519829695,
+           0.6656495232983333,
+           0.7158530169529782,
+           0.7702220857369053,
+           0.8276361937942696,
+           0.8869036549403018,
+           0.9467878160190064,
+           1.0060341733766482,
+           1.0633977895021507,
+           1.117670371131225,
+           1.1677063797503826,
+           1.2124475702169268,
+           1.250945392507849,
+           1.2823807444455435,
+           1.3060806283118738,
+           1.321531339946732,
+           1.3283879033665729,
+           1.3264795550542507,
+           1.3158111776245982,
+           1.296560680215958,
+           1.2690724203040784,
+           1.2338468563007445,
+           1.1915267099746076,
+           1.1428800002325534,
+           1.088780383124012,
+           1.0301852953052588,
+           0.9681124481272203,
+           0.9036152557995841,
+           0.8377578028867443,
+           0.7715899632172666,
+           0.7061232740195987,
+           0.642308145987714,
+           0.5810129526531862,
+           0.5230054918673868,
+           0.4689372496781259,
+           0.41933082401116334,
+           0.3745707841845125,
+           0.3348981544451924,
+           0.30040861763293986,
+           0.2710544410530159,
+           0.24665003303326435,
+           0.22688094778640752,
+           0.2113160703607127,
+           0.1994226347743146,
+           0.19058365884142597,
+           0.1841173204317122,
+           0.17929775340271292,
+           0.1753767083451249,
+           0.17160550438006222,
+           0.16725669398694135,
+           0.16164487329338934,
+           0.15414609512821256,
+           0.14421538076711693,
+           0.13140187768592582,
+           0.11536127345543319,
+           0.09586514855774167,
+           0.0728070315222176,
+           0.04620500631743683,
+           0.01620081219347379,
+           -0.016944532145858424,
+           -0.05285845737588805,
+           -0.09106771514257081,
+           -0.13101210001054908,
+           -0.17206065472177626,
+           -0.2135299264824022,
+           -0.2547037878262438,
+           -0.29485429388158607,
+           -0.33326301966194566,
+           -0.36924230703835753,
+           -0.40215585170010243,
+           -0.43143807567392656,
+           -0.45661176048221525,
+           -0.4773034590526484,
+           -0.49325625997873407,
+           -0.5043395442909865,
+           -0.5105554508705248,
+           -0.5120418501198962,
+           -0.5090717144076223,
+           -0.5020488658915633,
+           -0.49150017528625606,
+           -0.47806437662932477,
+           -0.4624777508131103,
+           -0.4455570123611662,
+           -0.4281798075724299,
+           -0.4112632958538168,
+           -0.39574133818444024,
+           -0.38254085585757447,
+           -0.3725579479051551,
+           -0.3666343662456068,
+           -0.36553494329351705,
+           -0.369926547585367,
+           -0.38035910933612754,
+           -0.3972492105347087,
+           -0.4208666743413919,
+           -0.4513245176109857,
+           -0.48857255005387545,
+           -0.5323948158220628,
+           -0.5824109803157469,
+           -0.6380816690301048,
+           -0.6987176686628506,
+           -0.763492805862259,
+           -0.8314602282559402,
+           -0.9015717280092485,
+           -0.9726996722130407,
+           -1.0436610387839826,
+           -1.1132430029156322,
+           -1.1802294787918441,
+           -1.2434279952875884,
+           -1.3016962734056516,
+           -1.353967877533474,
+           -1.399276332178504,
+           -1.4367771302047234,
+           -1.4657671069354192,
+           -1.4857007156515936,
+           -1.496202812529969,
+           -1.4970776411773694,
+           -1.4883137966409574,
+           -1.4700850439297226,
+           -1.442746964360631,
+           -1.4068295020540553,
+           -1.363025580239746,
+           -1.3121760503288746,
+           -1.2552513236907683,
+           -1.1933301146296054,
+           -1.1275757912784885,
+           -1.059210887360344,
+           -0.989490370645828,
+           -0.9196742924338395,
+           -0.851000455808747,
+           -0.7846577384784341,
+           -0.7217606887328654,
+           -0.6633259809243764,
+           -0.6102512706617936,
+           -0.5632969307783338,
+           -0.5230710785415058,
+           -0.4900182242640223,
+           -0.464411783426405,
+           -0.4463506008001313,
+           -0.4357595381637089,
+           -0.43239407940880775,
+           -0.4358488105333142,
+           -0.4455695395659036,
+           -0.4608687351162802,
+           -0.48094388409613076,
+           -0.504898301101463,
+           -0.5317638656280499,
+           -0.560525120056224,
+           -0.5901441322115502,
+           -0.6195855119555893,
+           -0.647840971991316,
+           -0.6739528388121687,
+           -0.6970359500423141,
+           -0.71629741850864,
+           -0.7310538001129577,
+           -0.7407452704857653,
+           -0.7449464927761715,
+           -0.7433739438109249,
+           -0.735889556101185,
+           -0.7225006265224698,
+           -0.7033560366026828,
+           -0.6787389218727727,
+           -0.6490560163570649,
+           -0.6148239807997481,
+           -0.5766530975921739,
+           -0.5352287797415661,
+           -0.49129139401816374,
+           -0.44561493834017524,
+           -0.39898513953426096,
+           -0.35217754922227806,
+           -0.3059362124749994,
+           -0.26095346615250703,
+           -0.21785139199772857,
+           -0.17716540439681566,
+           -0.13933039543394726,
+           -0.10466979191834891,
+           -0.07338780218404574,
+           -0.045565046617636634,
+           -0.021157677189233382,
+           -1.8276830316432254e-16
+          ],
+          [
+           0,
+           0.017664074162931743,
+           0.032920024389761146,
+           0.0463035970926227,
+           0.05842217021430568,
+           0.06993602213500377,
+           0.08153803568638836,
+           0.09393237967312014,
+           0.10781273805523818,
+           0.12384067009375932,
+           0.14262468295860578,
+           0.1647005815714129,
+           0.190513629210503,
+           0.2204030074119573,
+           0.25458900607678975,
+           0.29316330587635225,
+           0.336082636756337,
+           0.38316601053469707,
+           0.434095634422795,
+           0.4884215180624531,
+           0.5455696917355219,
+           0.604853860159925,
+           0.6654902270915637,
+           0.7266151430625665,
+           0.7873051541071171,
+           0.8465989651541851,
+           0.9035207795455178,
+           0.9571044372155538,
+           1.0064177494663171,
+           1.050586418648461,
+           1.0888169367106464,
+           1.1204178774144709,
+           1.1448190325637024,
+           1.1615878920297757,
+           1.1704430294881452,
+           1.171264029111611,
+           1.1640976712149482,
+           1.149160184990063,
+           1.1268354718045033,
+           1.097669300716937,
+           1.0623595764739175,
+           1.0217428768598977,
+           0.9767775484882465,
+           0.9285237356597683,
+           0.8781207936521748,
+           0.8267626038269916,
+           0.7756713615984056,
+           0.726070448251797,
+           0.6791570228140135,
+           0.6360749800093936,
+           0.5978889145091633,
+           0.5655597103056047,
+           0.5399223376070956,
+           0.5216663890172085,
+           0.51131982314127,
+           0.5092363086883228,
+           0.5155864774187318,
+           0.5303533019795253,
+           0.5533317170103477,
+           0.5841325012647851,
+           0.6221903373213987,
+           0.6667758662167717,
+           0.7170114594338299,
+           0.7718903424313099,
+           0.8302986244508721,
+           0.891039720617919,
+           0.9528605960288727,
+           1.014479218955947,
+           1.0746125825273396,
+           1.1320046419210417,
+           1.1854535175299987,
+           1.233837333615655,
+           1.27613809618333,
+           1.3114630623331853,
+           1.3390631149616055,
+           1.358347729886984,
+           1.3688962054463434,
+           1.3704649153127197,
+           1.3629904414888678,
+           1.3465885437797254,
+           1.321549022099994,
+           1.2883266262865194,
+           1.2475282622572177,
+           1.1998968310946359,
+           1.14629211680096,
+           1.0876692071556544,
+           1.0250549886521252,
+           0.9595232995439685,
+           0.8921693535778337,
+           0.8240840603727949,
+           0.7563288663450577,
+           0.6899117226741381,
+           0.625764754543854,
+           0.5647241596168263,
+           0.5075128046081052,
+           0.4547259184207117,
+           0.4068202003787676,
+           0.3641065746608007,
+           0.3267467292965776,
+           0.29475348237249827,
+           0.26799492178911916,
+           0.24620217043477738,
+           0.22898053833620258,
+           0.21582373946560476,
+           0.20613077550434056,
+           0.19922502384963167,
+           0.19437501410375782,
+           0.19081633750320953,
+           0.18777410819251916,
+           0.1844853845298342,
+           0.1802209629618561,
+           0.174305976279422,
+           0.1661387617423124,
+           0.1552075117625525,
+           0.14110427934067304,
+           0.12353598073245162,
+           0.1023321170886616,
+           0.07744902303710419,
+           0.0489705411711981,
+           0.017105114860639894,
+           -0.017820614665244733,
+           -0.055371529765098515,
+           -0.0950168125261748,
+           -0.13614543192082362,
+           -0.17808392729111427,
+           -0.22011601309616508,
+           -0.26150348164804077,
+           -0.30150784575241985,
+           -0.3394121426524531,
+           -0.3745423149813998,
+           -0.40628759372183915,
+           -0.4341193322290431,
+           -0.45760777861406116,
+           -0.47643632525123614,
+           -0.4904128375940789,
+           -0.4994777382695438,
+           -0.5037086047275451,
+           -0.503321127487228,
+           -0.49866636901572486,
+           -0.4902243581607936,
+           -0.4785941494464477,
+           -0.4644805680490894,
+           -0.4486779475875333,
+           -0.4320512467958927,
+           -0.4155150006964823,
+           -0.40001062027449913,
+           -0.38648260037643684,
+           -0.3758542274228347,
+           -0.36900339569889606,
+           -0.366739142984993,
+           -0.3697795030114129,
+           -0.37873124394696905,
+           -0.3940720195123919,
+           -0.41613540335838695,
+           -0.4450992094103793,
+           -0.48097742260369064,
+           -0.5236159777212459,
+           -0.572692531021312,
+           -0.6277202722871704,
+           -0.6880557262306721,
+           -0.7529103942701038,
+           -0.8213659929979386,
+           -0.8923929565002566,
+           -0.9648717882987645,
+           -1.0376167770829212,
+           -1.1094015303711535,
+           -1.1789857332915858,
+           -1.2451425069894717,
+           -1.3066857235876093,
+           -1.3624966326130525,
+           -1.4115491674428242,
+           -1.4529333293124527,
+           -1.4858760900957733,
+           -1.5097593123634745,
+           -1.5241342547858465,
+           -1.5287323110850193,
+           -1.5234717195247378,
+           -1.5084600751994532,
+           -1.4839925768361946,
+           -1.4505460410355573,
+           -1.408768817390942,
+           -1.3594668352927914,
+           -1.3035861050779163,
+           -1.2421920802889648,
+           -1.1764463621203491,
+           -1.1075812898397661,
+           -1.036873010567565,
+           -0.9656136570703158,
+           -0.8950832823315427,
+           -0.8265222041247389,
+           -0.761104401538432,
+           -0.6999125786816268,
+           -0.6439154693009923,
+           -0.5939479007998076,
+           -0.5506940685299772,
+           -0.5146743929015783,
+           -0.4862362447486914,
+           -0.46554873064788765,
+           -0.4526016318088829,
+           -0.4472084901503406,
+           -0.4490137356862002,
+           -0.4575036528107953,
+           -0.47202089183933604,
+           -0.49178214845396395,
+           -0.5158985595552058,
+           -0.5433983012154749,
+           -0.5732508244832403,
+           -0.6043921288815309,
+           -0.6357504524214064,
+           -0.6662717512792915,
+           -0.6949443520559947,
+           -0.7208221844518282,
+           -0.7430460415895518,
+           -0.7608623680706961,
+           -0.7736391408059692,
+           -0.7808784830646299,
+           -0.7822257361329406,
+           -0.7774748033425517,
+           -0.7665696757553362,
+           -0.7496021451027653,
+           -0.7268058052676711,
+           -0.6985465362765658,
+           -0.6653097521349104,
+           -0.6276847737159013,
+           -0.5863467583276725,
+           -0.5420366767964201,
+           -0.49553987545970274,
+           -0.4476637932302985,
+           -0.3992154220790663,
+           -0.3509791024744984,
+           -0.30369523346296123,
+           -0.2580404505103521,
+           -0.21460978365527758,
+           -0.17390125499857884,
+           -0.13630330945136424,
+           -0.1020853976501948,
+           -0.07139194693761164,
+           -0.044239867412493014,
+           -0.020519647537537572,
+           -1.7725260152674147e-16
+          ],
+          [
+           0,
+           0.01717503309098846,
+           0.03214523595619006,
+           0.045496932042012765,
+           0.0578794759190432,
+           0.06998517230337893,
+           0.08252790571436458,
+           0.09622105282698566,
+           0.11175526940568964,
+           0.1297767483618177,
+           0.15086653482651174,
+           0.17552145842776293,
+           0.20413720283638603,
+           0.2369939790970327,
+           0.27424520362178034,
+           0.3159095056360111,
+           0.36186630423480504,
+           0.4118551041559347,
+           0.4654785641902389,
+           0.5222092952265438,
+           0.5814002487088329,
+           0.6422984631970139,
+           0.704061849124137,
+           0.7657786119538925,
+           0.8264888437953614,
+           0.8852077549202545,
+           0.9409499710591389,
+           0.9927542910124778,
+           1.039708282831632,
+           1.0809720960621554,
+           1.1158008823682928,
+           1.143565246956662,
+           1.163769197890432,
+           1.176065118570316,
+           1.1802653589540946,
+           1.1763501217867562,
+           1.1644714092507717,
+           1.1449528908388134,
+           1.1182856525575302,
+           1.0851198883467732,
+           1.0462526943580757,
+           1.0026122230131898,
+           0.9552385441728983,
+           0.9052616430428716,
+           0.8538770565778817,
+           0.802319710315318,
+           0.7518365642628823,
+           0.7036587085017589,
+           0.6589735657227532,
+           0.6188978585456993,
+           0.5844519841298155,
+           0.5565364076051281,
+           0.5359106399678965,
+           0.5231753063786481,
+           0.5187577387128338,
+           0.5229014434799171,
+           0.5356597048482323,
+           0.5568934847055438,
+           0.5862736798235083,
+           0.6232876927539485,
+           0.6672501705818016,
+           0.7173176665879671,
+           0.7725068866461021,
+           0.8317160970592596,
+           0.8937491956055922,
+           0.9573418846283093,
+           1.021189335600953,
+           1.0839746999206805,
+           1.1443978015644578,
+           1.2012033441396646,
+           1.2532079778328644,
+           1.2993256004762062,
+           1.3385903106923984,
+           1.3701764887615633,
+           1.3934155510509079,
+           1.4078090048304392,
+           1.413037520071858,
+           1.408965831187182,
+           1.3956433822440286,
+           1.3733007315310535,
+           1.3423418329357988,
+           1.3033324099565875,
+           1.2569847309022548,
+           1.2041391786831412,
+           1.1457430835069122,
+           1.0828273499550347,
+           1.0164814598146972,
+           0.9478274674915348,
+           0.8779936250040391,
+           0.808088278013724,
+           0.739174663017519,
+           0.6722472090526098,
+           0.6082099057523538,
+           0.5478572444215962,
+           0.49185817138304133,
+           0.4407434148963454,
+           0.39489646043833726,
+           0.35454835623483444,
+           0.31977643398383937,
+           0.2905069311341323,
+           0.26652140334501334,
+           0.24746672128842032,
+           0.23286835711332937,
+           0.22214658487828207,
+           0.21463514807519454,
+           0.20960188777081346,
+           0.20627077834259752,
+           0.20384478541566606,
+           0.2015289431919671,
+           0.19855304630121454,
+           0.19419336460915929,
+           0.187792817720762,
+           0.17877908846637303,
+           0.1666802103540175,
+           0.151137231377493,
+           0.13191363396271524,
+           0.10890127623898498,
+           0.08212271106326151,
+           0.051729833984928204,
+           0.017998907209779813,
+           -0.01867789882754514,
+           -0.05780421384177635,
+           -0.09879410877570981,
+           -0.14098927569354947,
+           -0.1836782860860003,
+           -0.226117412475825,
+           -0.26755245670543704,
+           -0.3072410010425879,
+           -0.344474485957674,
+           -0.37859952143121944,
+           -0.4090378568825376,
+           -0.43530446782641863,
+           -0.4570232643474258,
+           -0.4739399862619956,
+           -0.48593192092450843,
+           -0.49301416024630446,
+           -0.495342201615509,
+           -0.493210790818465,
+           -0.4870490014219571,
+           -0.47741164195302527,
+           -0.46496717716670033,
+           -0.4504824403219671,
+           -0.43480449739741484,
+           -0.4188400994364496,
+           -0.4035332237987456,
+           -0.38984125735424635,
+           -0.37871041323762,
+           -0.371050996673091,
+           -0.3677131439347956,
+           -0.36946365146088067,
+           -0.37696448961329204,
+           -0.3907535580787699,
+           -0.4112281883230241,
+           -0.4386318340751253,
+           -0.47304431509096795,
+           -0.5143758942655398,
+           -0.562365375614977,
+           -0.616582312999655,
+           -0.6764333191093741,
+           -0.7411723636535306,
+           -0.8099148513767661,
+           -0.8816551768869821,
+           -0.9552873666603711,
+           -1.029628341131169,
+           -1.1034432634139923,
+           -1.1754723876062119,
+           -1.2444587801272808,
+           -1.3091762631764057,
+           -1.3684569207649397,
+           -1.4212175151532314,
+           -1.46648418474916,
+           -1.5034148330725443,
+           -1.5313186713443485,
+           -1.5496724433557507,
+           -1.558132938918721,
+           -1.556545489521418,
+           -1.544948234693272,
+           -1.523572047724229,
+           -1.49283611234753,
+           -1.453339245282136,
+           -1.4058471606266911,
+           -1.3512759685416897,
+           -1.290672290103019,
+           -1.2251904504824014,
+           -1.1560672817562325,
+           -1.0845951229849227,
+           -1.0120936473740503,
+           -0.9398811733080988,
+           -0.8692461271910078,
+           -0.8014193210766734,
+           -0.7375476871632795,
+           -0.6786700748838627,
+           -0.6256956654564869,
+           -0.5793854946197302,
+           -0.5403374984557713,
+           -0.5089754115621187,
+           -0.4855417534798316,
+           -0.4700950405133308,
+           -0.4625112583069311,
+           -0.46248952826793177,
+           -0.4695618006460982,
+           -0.48310631124183806,
+           -0.502364449654165,
+           -0.5264606068573305,
+           -0.554424500650553,
+           -0.5852154208254908,
+           -0.6177477930954203,
+           -0.6509174329374391,
+           -0.6836278481533323,
+           -0.7148159524094678,
+           -0.7434765711340663,
+           -0.7686851554068602,
+           -0.7896181679737851,
+           -0.8055706670093907,
+           -0.8159706861646092,
+           -0.8203900919300209,
+           -0.8185516893338388,
+           -0.8103324422173487,
+           -0.7957627724011589,
+           -0.7750220005204684,
+           -0.7484300877098076,
+           -0.7164359292567248,
+           -0.6796025365361856,
+           -0.6385895198719888,
+           -0.5941333505634263,
+           -0.5470259335517004,
+           -0.4980920617804025,
+           -0.4481663482711279,
+           -0.39807024169994465,
+           -0.34858972561592516,
+           -0.3004542805688216,
+           -0.25431765287053354,
+           -0.2107409244331419,
+           -0.17017831637721917,
+           -0.13296608647221725,
+           -0.09931479881186688,
+           -0.06930515552255152,
+           -0.04288748700558094,
+           -0.01988490159520463,
+           -1.7192358596351585e-16
+          ],
+          [
+           0,
+           0.016735482034390122,
+           0.031499620718039655,
+           0.044925642644827325,
+           0.05770021586897871,
+           0.0705421560209126,
+           0.084180143173051,
+           0.0993300468892612,
+           0.11667246825640147,
+           0.13683110344257296,
+           0.16035251354721963,
+           0.18768785068743465,
+           0.21917704126621357,
+           0.2550358654132501,
+           0.295346298225916,
+           0.3400503955048907,
+           0.3889479162561462,
+           0.44169777859044884,
+           0.49782334719945437,
+           0.5567214518044666,
+           0.6176749393529829,
+           0.6798684707222643,
+           0.742407187610248,
+           0.8043377993145027,
+           0.8646715741581847,
+           0.9224086680841942,
+           0.9765631847565335,
+           1.0261883383843406,
+           1.070401083048015,
+           1.1084055807969018,
+           1.139514905045802,
+           1.1631704152713374,
+           1.1789582927666902,
+           1.1866227939645873,
+           1.186075855967372,
+           1.1774027765269448,
+           1.160863785653839,
+           1.1368914259743859,
+           1.1060837614392212,
+           1.069193536488033,
+           1.0271135077612439,
+           0.9808582654428234,
+           0.9315429489613943,
+           0.8803593398875894,
+           0.8285498814938936,
+           0.777380227917639,
+           0.7281109648388098,
+           0.6819691670567862,
+           0.6401204657092585,
+           0.6036422889028404,
+           0.5734989144005549,
+           0.5505189323157164,
+           0.535375660457686,
+           0.5285709863856007,
+           0.5304230300020872,
+           0.541057930598473,
+           0.5604059648239684,
+           0.5882020994581665,
+           0.6239909776115974,
+           0.6671362316226398,
+           0.7168339130244968,
+           0.7721297320277967,
+           0.8319397083866671,
+           0.8950737544933774,
+           0.9602616420499261,
+           1.026180747383136,
+           1.0914849287682156,
+           1.1548338630125543,
+           1.2149221586528998,
+           1.2705075696641854,
+           1.3204376563934337,
+           1.3636742789455232,
+           1.3993153615031872,
+           1.426613432745378,
+           1.444990525992105,
+           1.45404911101936,
+           1.4535788254846869,
+           1.4435588752266653,
+           1.4241560768671546,
+           1.39571862060421,
+           1.3587657332839147,
+           1.3139735192880713,
+           1.2621573471002057,
+           1.2042512304223312,
+           1.1412847224505476,
+           1.0743578987011908,
+           1.0046150462557322,
+           0.9332177044624053,
+           0.8613177133753943,
+           0.7900309213030533,
+           0.7204121819488009,
+           0.653432235330672,
+           0.5899570159064379,
+           0.5307298674150003,
+           0.4763570684986782,
+           0.42729698810447897,
+           0.3838530971191136,
+           0.34617096499689975,
+           0.31423926973891975,
+           0.2878947489848163,
+           0.2668309216936101,
+           0.25061031636189246,
+           0.23867985527794164,
+           0.23038896707831252,
+           0.22500993376434672,
+           0.22175992497325855,
+           0.21982413298345174,
+           0.21837939761416045,
+           0.21661770142594994,
+           0.213768922620671,
+           0.20912225556180883,
+           0.2020457462844044,
+           0.19200344175971798,
+           0.17856971569668795,
+           0.1614404086578165,
+           0.14044050432520463,
+           0.11552815473120594,
+           0.08679496285357166,
+           0.05446252873927546,
+           0.018875362783495917,
+           -0.019509635521231115,
+           -0.06013684553648055,
+           -0.10236837023045524,
+           -0.14550281528663256,
+           -0.18879589894437576,
+           -0.2314823406888023,
+           -0.2727984427984976,
+           -0.3120047596737641,
+           -0.3484082462996972,
+           -0.38138328925132864,
+           -0.4103910510329474,
+           -0.43499660058439144,
+           -0.45488335843803207,
+           -0.4698644528820041,
+           -0.4798906618794376,
+           -0.485054702444902,
+           -0.48559172250481036,
+           -0.4818759476218985,
+           -0.4744135338939333,
+           -0.46383177634891276,
+           -0.45086491677751644,
+           -0.4363368837733625,
+           -0.4211413785386687,
+           -0.40621979070019326,
+           -0.3925374871598213,
+           -0.38105906236229736,
+           -0.3727231691181849,
+           -0.3684175644547518,
+           -0.3689550044457722,
+           -0.37505060555307274,
+           -0.387301258054001,
+           -0.4061676303741685,
+           -0.43195924270826364,
+           -0.4648230156509657,
+           -0.5047356164398934,
+           -0.5514998338618671,
+           -0.6047451151354519,
+           -0.6639322965580057,
+           -0.728362456895156,
+           -0.797189720932709,
+           -0.869437742818205,
+           -0.9440195072163842,
+           -1.0197600031669147,
+           -1.0954212529362624,
+           -1.1697291179148672,
+           -1.2414012572413113,
+           -1.3091755835128482,
+           -1.3718385444737713,
+           -1.428252560378662,
+           -1.4773819638247252,
+           -1.5183168218547811,
+           -1.5502940682762967,
+           -1.5727154362757176,
+           -1.5851617560399656,
+           -1.5874032674280967,
+           -1.5794056917016595,
+           -1.5613319066437676,
+           -1.5335391736385044,
+           -1.496571970909979,
+           -1.451150591564585,
+           -1.398155765798805,
+           -1.338609661176494,
+           -1.2736537009423796,
+           -1.204523715828679,
+           -1.1325230078931245,
+           -1.0589939540680224,
+           -0.9852888111104089,
+           -0.9127404017034899,
+           -0.8426333631402921,
+           -0.7761766252938661,
+           -0.7144777538188563,
+           -0.6585197485024127,
+           -0.6091408265284483,
+           -0.5670176476224131,
+           -0.5326523543969129,
+           -0.5063637087786249,
+           -0.4882825064337773,
+           -0.47835134804975393,
+           -0.4763287416982182,
+           -0.48179740685910044,
+           -0.49417655055528664,
+           -0.5127377918746076,
+           -0.5366243252277646,
+           -0.5648728370900948,
+           -0.5964376275254617,
+           -0.6302163380130573,
+           -0.6650766521734678,
+           -0.6998833167313523,
+           -0.7335248268825421,
+           -0.7649391331789285,
+           -0.7931377557329129,
+           -0.8172277352133911,
+           -0.8364309076273402,
+           -0.8501000597846258,
+           -0.8577316028548126,
+           -0.8589744905106297,
+           -0.8536352035720979,
+           -0.8416787224251043,
+           -0.8232255093023972,
+           -0.7985446222672683,
+           -0.768043178946321,
+           -0.732252478326922,
+           -0.6918111710301709,
+           -0.6474459403625012,
+           -0.5999502163688751,
+           -0.5501614915909161,
+           -0.4989378391460952,
+           -0.44713425032795595,
+           -0.39557940980605555,
+           -0.3450535116957803,
+           -0.296267689683698,
+           -0.2498455898273507,
+           -0.20630755675571935,
+           -0.16605783426697449,
+           -0.12937510153858175,
+           -0.0964065783667571,
+           -0.06716583927246011,
+           -0.04153437932811139,
+           -0.01926687663500203,
+           -1.6690610814058382e-16
+          ],
+          [
+           0,
+           0.016358327846219604,
+           0.03100761436653275,
+           0.04462367159202027,
+           0.057925239877494955,
+           0.07165163619713977,
+           0.08653973559163712,
+           0.10330090386153659,
+           0.12259850203432779,
+           0.14502656963362068,
+           0.17109026467544355,
+           0.20118859432972505,
+           0.23559991241074987,
+           0.2744705897431835,
+           0.31780718274675757,
+           0.36547233631793663,
+           0.4171845615038015,
+           0.4725219289668421,
+           0.5309296183360952,
+           0.5917311637760274,
+           0.6541431400012865,
+           0.7172929429568554,
+           0.7802392377547525,
+           0.8419945752898531,
+           0.9015496200703026,
+           0.9578983867101386,
+           1.0100638524186991,
+           1.0571232984868577,
+           1.098232735625135,
+           1.1326497860610671,
+           1.1597544291564221,
+           1.1790670661676743,
+           1.1902634224785031,
+           1.1931858806666358,
+           1.1878509233045111,
+           1.1744524583442406,
+           1.1533608999984866,
+           1.1251179817396864,
+           1.0904273828438906,
+           1.0501413532129726,
+           1.0052436204619526,
+           0.9568289559935466,
+           0.906079860692242,
+           0.8542409038613613,
+           0.8025913092698607,
+           0.7524164281534429,
+           0.704978769558052,
+           0.6614892727324592,
+           0.6230795039780274,
+           0.5907754414638625,
+           0.5654734764388168,
+           0.5479192088410072,
+           0.5386895507218414,
+           0.5381785737155327,
+           0.5465874488584327,
+           0.5639187305227247,
+           0.5899751334169475,
+           0.6243628450183949,
+           0.6664993080311068,
+           0.7156253011302719,
+           0.7708210439480426,
+           0.8310259564683401,
+           0.8950616160617718,
+           0.9616573794228171,
+           1.029478073518274,
+           1.0971531108532553,
+           1.1633063510920014,
+           1.2265860141383733,
+           1.285693949587539,
+           1.3394135839990498,
+           1.3866359002951494,
+           1.4263828519407329,
+           1.4578276772178573,
+           1.4803116543236845,
+           1.4933569243408207,
+           1.4966751042324224,
+           1.4901715135677713,
+           1.4739449441984738,
+           1.4482830089986527,
+           1.4136532114419353,
+           1.370689979635568,
+           1.3201780039873379,
+           1.263032304622837,
+           1.2002755308935311,
+           1.1330130589825333,
+           1.062406503199856,
+           0.989646290887154,
+           0.9159239691272286,
+           0.8424049132767021,
+           0.7702020927196089,
+           0.7003515185892929,
+           0.6337899523355917,
+           0.5713353941080547,
+           0.5136707975129535,
+           0.46133137421735615,
+           0.41469576021351223,
+           0.3739812176247017,
+           0.3392429441839059,
+           0.31037745949250256,
+           0.2871299354370882,
+           0.2691052402399073,
+           0.2557823739726524,
+           0.24653189024393013,
+           0.24063582622911844,
+           0.2373096030311138,
+           0.23572531201256836,
+           0.2350357713469459,
+           0.23439872134315598,
+           0.23300052745835073,
+           0.2300787762746901,
+           0.2249431816264665,
+           0.21699426468277708,
+           0.2057393319088433,
+           0.19080534689986606,
+           0.1719483742604777,
+           0.14905936389403107,
+           0.12216613997371495,
+           0.0914315580546611,
+           0.05714789373541775,
+           0.01972762445356498,
+           -0.020309140084749894,
+           -0.06235023606791785,
+           -0.10570961114079414,
+           -0.1496475885926264,
+           -0.19339268637542137,
+           -0.2361644060890799,
+           -0.2771963810030029,
+           -0.3157592617878985,
+           -0.35118272418069496,
+           -0.3828760041725446,
+           -0.41034640296928976,
+           -0.43321525501397845,
+           -0.4512309165078687,
+           -0.4642784075143217,
+           -0.47238542598222094,
+           -0.47572454474152515,
+           -0.4746115003719316,
+           -0.46949958336299497,
+           -0.46097023963608436,
+           -0.449720091743579,
+           -0.4365446814132409,
+           -0.4223193211984813,
+           -0.40797751963896195,
+           -0.3944875095737559,
+           -0.38282746140614915,
+           -0.37396000084420433,
+           -0.3688066729415192,
+           -0.3682230005290345,
+           -0.37297477515093236,
+           -0.3837161925906734,
+           -0.4009704035925514,
+           -0.42511299443203665,
+           -0.4563588429094051,
+           -0.49475271481037036,
+           -0.5401638758578451,
+           -0.5922848968740905,
+           -0.6506347276719272,
+           -0.7145660106135501,
+           -0.7832765003970494,
+           -0.8558243550355629,
+           -0.9311469667007132,
+           -1.0080829125031727,
+           -1.085396526586646,
+           -1.1618045280847058,
+           -1.2360040862109747,
+           -1.3067016653699641,
+           -1.372641970671005,
+           -1.432636308194383,
+           -1.4855896849862906,
+           -1.5305260008261738,
+           -1.566610726691424,
+           -1.5931705225248445,
+           -1.6097093180098654,
+           -1.6159204628658108,
+           -1.6116946456897325,
+           -1.597123380351566,
+           -1.5724979639690548,
+           -1.5383039179961469,
+           -1.4952110313383744,
+           -1.444059229047549,
+           -1.3858405894980959,
+           -1.3216779245892005,
+           -1.2528004192190045,
+           -1.1805168960511914,
+           -1.106187327743279,
+           -1.0311932599670688,
+           -0.9569078337285725,
+           -0.8846661040829406,
+           -0.8157363441411368,
+           -0.7512929984919114,
+           -0.69239190943388,
+           -0.6399483837363115,
+           -0.5947185983980742,
+           -0.5572847627569998,
+           -0.5280443633109031,
+           -0.5072037189808543,
+           -0.49477597069547835,
+           -0.49058352264544675,
+           -0.49426484595557274,
+           -0.5052854514512838,
+           -0.5229527391937463,
+           -0.546434340931825,
+           -0.5747794897895327,
+           -0.6069428813522125,
+           -0.641810433519974,
+           -0.6782263104169811,
+           -0.7150205492687678,
+           -0.7510366190864672,
+           -0.7851582464225553,
+           -0.8163348661754166,
+           -0.8436050938060469,
+           -0.8661176683892718,
+           -0.8831493822931322,
+           -0.8941195912759893,
+           -0.8986009864397809,
+           -0.8963264045730523,
+           -0.8871915535724161,
+           -0.8712536323394834,
+           -0.8487259272475148,
+           -0.8199685673997589,
+           -0.7854757159710357,
+           -0.745859562578257,
+           -0.7018315596972389,
+           -0.6541814127086052,
+           -0.603754386582717,
+           -0.5514275312017288,
+           -0.49808545092888634,
+           -0.4445962517206405,
+           -0.3917882906852346,
+           -0.3404283287744681,
+           -0.29120164790208475,
+           -0.24469464024095477,
+           -0.2013803111441631,
+           -0.16160705976273285,
+           -0.12559101497186742,
+           -0.0934121108711044,
+           -0.0650139882652187,
+           -0.040207708647364934,
+           -0.018679167827785722,
+           -1.6232471968196082e-16
+          ],
+          [
+           0,
+           0.01605610152116577,
+           0.03069253750587646,
+           0.04462277366222587,
+           0.058591845472092674,
+           0.07335312064310957,
+           0.08964473678824879,
+           0.10816634798326429,
+           0.12955680696232597,
+           0.15437338671800008,
+           0.1830731067415779,
+           0.21599667603369346,
+           0.2533554986611542,
+           0.2952221096967116,
+           0.3415243218102414,
+           0.39204326778318804,
+           0.4464154241834615,
+           0.5041385988854985,
+           0.5645817626371196,
+           0.6269985050505563,
+           0.6905438007565231,
+           0.754293684408572,
+           0.817267355975296,
+           0.8784511722838173,
+           0.9368239287616659,
+           0.991382798114443,
+           1.0411692712545173,
+           1.0852944407497975,
+           1.1229629785716624,
+           1.1534951877548487,
+           1.176346551098935,
+           1.191124258208094,
+           1.1976002635826541,
+           1.1957205114092857,
+           1.18561005512243,
+           1.167573899463328,
+           1.1420934971955186,
+           1.109818939273408,
+           1.0715569834696008,
+           1.0282551696178213,
+           0.9809823671622057,
+           0.9309061901946696,
+           0.8792677943777923,
+           0.8273546371084342,
+           0.7764718352929818,
+           0.7279127928351241,
+           0.6829297914125588,
+           0.6427052427696197,
+           0.6083242884217078,
+           0.5807494036154704,
+           0.5607976172884399,
+           0.5491208996916304,
+           0.546190195716075,
+           0.5522834965719776,
+           0.5674782473704044,
+           0.5916482856563947,
+           0.624465398526911,
+           0.6654054762480258,
+           0.7137591309325094,
+           0.7686465425138959,
+           0.8290361935458836,
+           0.8937670617199787,
+           0.9615737566863359,
+           1.0311140177871165,
+           1.100997933371219,
+           1.1698182018131915,
+           1.2361807301898067,
+           1.2987348593565466,
+           1.3562025140790042,
+           1.4074056036577756,
+           1.4512910414736435,
+           1.4869528100102452,
+           1.5136505697514684,
+           1.5308243941335324,
+           1.5381053063990926,
+           1.5353213954548568,
+           1.5224993941938916,
+           1.4998617126057432,
+           1.4678190267007118,
+           1.426958630165774,
+           1.3780288561687446,
+           1.3219199693908479,
+           1.2596420109494246,
+           1.1923001493773113,
+           1.121068147559857,
+           1.0471605971430884,
+           0.9718045974409689,
+           0.8962115647087693,
+           0.8215498496482985,
+           0.748918816420516,
+           0.6793249959222061,
+           0.613660870688711,
+           0.5526867799325313,
+           0.497016352666187,
+           0.4471057866214469,
+           0.40324719303543577,
+           0.36556612477537354,
+           0.3340233002832892,
+           0.30842043105926875,
+           0.2884099584740543,
+           0.27350840914050084,
+           0.26311298927025834,
+           0.256520959590534,
+           0.25295126543630975,
+           0.25156784320546505,
+           0.2515039857660691,
+           0.2518871265615998,
+           0.2518633955999909,
+           0.2506213103567253,
+           0.2474139905800112,
+           0.24157932736332718,
+           0.23255759256778194,
+           0.21990604329582492,
+           0.20331015587927556,
+           0.18259121271089224,
+           0.15771006095618065,
+           0.12876696229748696,
+           0.09599755484384487,
+           0.05976504960105057,
+           0.020548881870475082,
+           -0.021069869849961242,
+           -0.06442590078897575,
+           -0.10878946211069744,
+           -0.15338797611297073,
+           -0.19742890403599805,
+           -0.2401232529156268,
+           -0.2807090904726849,
+           -0.3184744357810269,
+           -0.35277890844496457,
+           -0.38307354987492664,
+           -0.4089182762120985,
+           -0.42999648237069965,
+           -0.44612638904052876,
+           -0.4572688075072988,
+           -0.46353108871911547,
+           -0.46516712085163464,
+           -0.46257334123886007,
+           -0.45628083137958153,
+           -0.4469436652045865,
+           -0.43532377833080255,
+           -0.42227271716372267,
+           -0.4087107091233318,
+           -0.39560356686049497,
+           -0.38393799826659003,
+           -0.374695938838738,
+           -0.3688285523777677,
+           -0.3672305592787591,
+           -0.37071554843916277,
+           -0.3799929090830653,
+           -0.3956469830201689,
+           -0.41811898686364857,
+           -0.4476921887426768,
+           -0.48448074663474794,
+           -0.5284225274944925,
+           -0.57927613002028,
+           -0.6366222315417485,
+           -0.6998692736497435,
+           -0.7682633944365673,
+           -0.8409024102089859,
+           -0.9167535488812295,
+           -0.9946745434507912,
+           -1.0734376093421596,
+           -1.1517557560870613,
+           -1.2283108236334659,
+           -1.3017825880578648,
+           -1.3708782517564317,
+           -1.4343616200824894,
+           -1.491081270244779,
+           -1.5399970390318032,
+           -1.5802041931132473,
+           -1.610954698417576,
+           -1.6316750721383133,
+           -1.641980380670242,
+           -1.6416840372970316,
+           -1.630803152553061,
+           -1.609559295461112,
+           -1.5783746327468982,
+           -1.5378635230027808,
+           -1.4888197509424808,
+           -1.432199690721921,
+           -1.369101784269135,
+           -1.3007428083062593,
+           -1.2284314801215883,
+           -1.1535400153006539,
+           -1.0774742990159172,
+           -1.0016433649311574,
+           -0.9274288915142891,
+           -0.8561554241966146,
+           -0.7890620134111657,
+           -0.7272759235487402,
+           -0.6717890171549392,
+           -0.6234373535057169,
+           -0.5828844626479798,
+           -0.5506086669937221,
+           -0.5268947247957537,
+           -0.5118299657074263,
+           -0.5053049806878934,
+           -0.5070188193986015,
+           -0.5164885406114277,
+           -0.5330628576387932,
+           -0.5559395239207109,
+           -0.5841860160153186,
+           -0.6167629944651402,
+           -0.6525499592009005,
+           -0.6903724668255677,
+           -0.7290302434606861,
+           -0.7673255096141206,
+           -0.8040908331152846,
+           -0.838215842517391,
+           -0.8686721660287029,
+           -0.894536009147145,
+           -0.9150078464952766,
+           -0.9294287782973495,
+           -0.9372931876096299,
+           -0.9382574286506936,
+           -0.9321443770137808,
+           -0.9189437766637527,
+           -0.8988084238263012,
+           -0.8720463315453655,
+           -0.8391091182386122,
+           -0.8005769565513042,
+           -0.757140502896025,
+           -0.7095803011963218,
+           -0.6587442147307033,
+           -0.6055234861263261,
+           -0.5508280563640944,
+           -0.4955617883995285,
+           -0.44059823935108045,
+           -0.38675760724481817,
+           -0.33478544452570286,
+           -0.28533368184053,
+           -0.23894444322884675,
+           -0.1960370594296118,
+           -0.1568986014275417,
+           -0.12167816378138466,
+           -0.0903850290526953,
+           -0.06289074328328277,
+           -0.038935030524830584,
+           -0.018135374489707333,
+           -1.5830222531772736e-16
+          ],
+          [
+           0,
+           0.015840805951609662,
+           0.03057630318771933,
+           0.04495210270706526,
+           0.0597332710276579,
+           0.07568039422984446,
+           0.09352567607046033,
+           0.1139497139226587,
+           0.1375595797773457,
+           0.16486880089416237,
+           0.19627978672594645,
+           0.23206918666030274,
+           0.27237658848149465,
+           0.3171968821292888,
+           0.36637651946347016,
+           0.41961380069578896,
+           0.47646321444574297,
+           0.5363437536289296,
+           0.5985510262427753,
+           0.6622728811841552,
+           0.7266081770250477,
+           0.7905882385299072,
+           0.8532004737425415,
+           0.9134135655453056,
+           0.9702036072206137,
+           1.022580522884253,
+           1.0696141014809437,
+           1.110458977693855,
+           1.1443779145599928,
+           1.1707627803222151,
+           1.1891526651978626,
+           1.1992486510292768,
+           1.2009248265732322,
+           1.1942352315399858,
+           1.179416511196336,
+           1.1568861679763511,
+           1.1272364045210042,
+           1.0912236612276267,
+           1.0497540580427382,
+           1.0038650522319374,
+           0.9547037186721593,
+           0.903502144471047,
+           0.8515505032929617,
+           0.8001684348130935,
+           0.750675399712605,
+           0.7043607094191913,
+           0.6624539416371196,
+           0.6260964472628694,
+           0.5963146316365795,
+           0.5739956537486223,
+           0.5598661319289827,
+           0.5544743750079949,
+           0.5581765756203335,
+           0.5711273092162142,
+           0.5932745806979306,
+           0.6243595528817922,
+           0.6639209798122543,
+           0.7113042560307871,
+           0.7656748829516423,
+           0.8260360481985858,
+           0.8912499156768892,
+           0.9600621356839169,
+           1.0311290076556676,
+           1.1030466650741415,
+           1.1743816041566244,
+           1.2437018463767162,
+           1.3096080103921632,
+           1.3707635719216804,
+           1.4259236104402035,
+           1.4739613787428436,
+           1.5138920845432016,
+           1.5448933410132089,
+           1.566321823873484,
+           1.577725764323742,
+           1.5788530075132432,
+           1.5696544729313713,
+           1.5502829634371766,
+           1.5210873809465943,
+           1.4826025163398548,
+           1.4355346862690328,
+           1.3807435876794605,
+           1.3192208296271521,
+           1.2520656792302465,
+           1.1804586224752567,
+           1.1056333895809978,
+           1.0288481275462422,
+           0.9513564186114484,
+           0.8743788423064378,
+           0.7990757606146814,
+           0.726521971062745,
+           0.6576838221504412,
+           0.5933993207689103,
+           0.5343616837583782,
+           0.48110669749422025,
+           0.43400415258103925,
+           0.3932535178082414,
+           0.3588839110519989,
+           0.3307583174542212,
+           0.30858189964219596,
+           0.29191414359504064,
+           0.2801844895219214,
+           0.272711012120877,
+           0.2687216409295353,
+           0.26737735096607,
+           0.26779670796466565,
+           0.2690811223405206,
+           0.2703401522858695,
+           0.27071619939880504,
+           0.2694079598597629,
+           0.26569202985929696,
+           0.258942114806091,
+           0.24864535648894298,
+           0.2344153691685731,
+           0.21600166256981496,
+           0.1932952247135061,
+           0.16633013805421337,
+           0.13528120592148796,
+           0.10045767017230858,
+           0.06229320261719021,
+           0.021332449607182353,
+           -0.02178550128802119,
+           -0.06634628358637615,
+           -0.1115815258399579,
+           -0.15669166476559998,
+           -0.20086968469795768,
+           -0.2433251458309954,
+           -0.28330785540612125,
+           -0.3201305442807981,
+           -0.35318993597147713,
+           -0.3819856356971381,
+           -0.40613632214505635,
+           -0.4253927932562451,
+           -0.43964749756399085,
+           -0.4489402724993209,
+           -0.45346010834139894,
+           -0.45354285868975613,
+           -0.44966492289234666,
+           -0.4424330301394629,
+           -0.4325703562922374,
+           -0.4208993003886842,
+           -0.40832133572626106,
+           -0.3957944282182857,
+           -0.384308580373596,
+           -0.37486011106637646,
+           -0.3684253179011463,
+           -0.36593418946882816,
+           -0.36824483856766244,
+           -0.37611931437832546,
+           -0.390201421907452,
+           -0.41099713143428046,
+           -0.4388581002958769,
+           -0.47396875558380236,
+           -0.5163373009917336,
+           -0.565790916234115,
+           -0.6219753154757549,
+           -0.6843587245799586,
+           -0.7522402283283538,
+           -0.8247623307747491,
+           -0.9009274672440915,
+           -0.9796181077744225,
+           -1.0596200014823671,
+           -1.1396480316659683,
+           -1.2183740844394308,
+           -1.2944562810106799,
+           -1.3665688867021077,
+           -1.4334321894315316,
+           -1.4938416371595755,
+           -1.5466955378947755,
+           -1.5910206569269632,
+           -1.6259950933116194,
+           -1.650967880131111,
+           -1.6654748292166603,
+           -1.6692502289938995,
+           -1.6622341017885545,
+           -1.644574831930381,
+           -1.616627085773779,
+           -1.5789450566436705,
+           -1.5322711789923182,
+           -1.477520564006815,
+           -1.4157615109076616,
+           -1.3481925417401703,
+           -1.2761164903022169,
+           -1.2009122459551835,
+           -1.1240048087232624,
+           -1.0468343519451677,
+           -0.9708250118356475,
+           -0.897354129084993,
+           -0.8277226559411528,
+           -0.7631274133760492,
+           -0.7046358376501204,
+           -0.6531637949745877,
+           -0.6094569685206144,
+           -0.5740762355682728,
+           -0.5473873562475907,
+           -0.5295551914606573,
+           -0.5205425587315774,
+           -0.5201137235722381,
+           -0.5278424131921938,
+           -0.5431241317226176,
+           -0.5651924541890213,
+           -0.5931388827324261,
+           -0.6259357653153813,
+           -0.6624617063676133,
+           -0.7015288422254491,
+           -0.7419113131465835,
+           -0.7823742390991364,
+           -0.8217024989848992,
+           -0.8587286225934798,
+           -0.8923591311048459,
+           -0.9215987046541683,
+           -0.9455716132388149,
+           -0.9635399186061748,
+           -0.9749180379032395,
+           -0.9792833526972465,
+           -0.9763826471588218,
+           -0.9661342642253233,
+           -0.9486259758085376,
+           -0.9241086699042679,
+           -0.8929860611460526,
+           -0.8558007293484751,
+           -0.8132168804821973,
+           -0.7660003040947952,
+           -0.7149960684829992,
+           -0.6611045482876855,
+           -0.6052564173289583,
+           -0.5483872615136623,
+           -0.4914124720255826,
+           -0.43520306766080646,
+           -0.3805630674272595,
+           -0.32820899112890556,
+           -0.27875200773312525,
+           -0.23268318036873062,
+           -0.19036217464114122,
+           -0.1520097056785959,
+           -0.11770390126355151,
+           -0.08738065604913524,
+           -0.060837947809477586,
+           -0.03774398356342412,
+           -0.017648943855770153,
+           -1.5495823325931208e-16
+          ],
+          [
+           0,
+           0.0157237673285404,
+           0.030679135941943433,
+           0.045637821883813164,
+           0.061378227347421384,
+           0.07866100756378727,
+           0.09820504419723329,
+           0.12066447336124073,
+           0.1466073900040534,
+           0.17649680804853488,
+           0.21067439836434818,
+           0.24934745583980575,
+           0.2925794642842036,
+           0.3402845357045115,
+           0.39222590098337695,
+           0.4480185246461287,
+           0.5071358098748371,
+           0.5689202538982024,
+           0.632597811039087,
+           0.6972956236430893,
+           0.7620626923067714,
+           0.825892978535182,
+           0.8877503671876229,
+           0.9465948645106078,
+           1.0014093715472105,
+           1.0512263532055397,
+           1.095153720807762,
+           1.1323992606419013,
+           1.162292972589743,
+           1.1843067305724915,
+           1.1980707392042957,
+           1.2033863371594193,
+           1.2002347854895177,
+           1.1887817763278739,
+           1.1693775017014492,
+           1.1425522309717335,
+           1.1090074560560539,
+           1.0696027733049844,
+           1.0253387770080216,
+           0.9773363393316518,
+           0.9268127425736293,
+           0.8750552096682397,
+           0.8233924458908094,
+           0.7731648569951542,
+           0.725694145244685,
+           0.6822530040296189,
+           0.6440356334799552,
+           0.612129783597693,
+           0.587490998286881,
+           0.5709196840266005,
+           0.5630415619866693,
+           0.5642919836839878,
+           0.5749044997142909,
+           0.5949039708589955,
+           0.6241044033891304,
+           0.6621115782779802,
+           0.7083304300172125,
+           0.761977017583424,
+           0.8220948205796677,
+           0.8875749903492423,
+           0.9571800914437446,
+           1.029570785526515,
+           1.1033348396372296,
+           1.1770177854431751,
+           1.249154517004101,
+           1.3183010926301784,
+           1.3830660021464016,
+           1.4421401743887587,
+           1.4943250307093605,
+           1.5385579378945735,
+           1.5739344770291237,
+           1.5997270219186304,
+           1.615399209820897,
+           1.62061598624685,
+           1.615249012049692,
+           1.5993773323202147,
+           1.5732833200262895,
+           1.5374440201057464,
+           1.4925181290943743,
+           1.4393289486822365,
+           1.3788437463325534,
+           1.3121500399732136,
+           1.24042939475798,
+           1.1649293762892947,
+           1.0869343451565732,
+           1.0077358012268203,
+           0.928602992299983,
+           0.850754490411673,
+           0.7753314105644165,
+           0.7033729017526799,
+           0.6357944799772616,
+           0.5733696990566483,
+           0.5167155693078171,
+           0.46628203874700674,
+           0.42234574874749226,
+           0.38500816865698734,
+           0.3541981044038616,
+           0.3296784673351639,
+           0.31105708413363803,
+           0.2978012292679912,
+           0.2892554704981621,
+           0.2846623377262942,
+           0.28318525792428034,
+           0.2839331456293499,
+           0.28598600086871667,
+           0.28842084524859823,
+           0.29033732280360225,
+           0.29088230510512647,
+           0.2892728697011529,
+           0.2848170664166734,
+           0.2769319461992246,
+           0.2651584004963341,
+           0.2491724437219291,
+           0.2287926650478358,
+           0.20398367615895754,
+           0.17485548618532235,
+           0.14165884111733545,
+           0.10477666993313409,
+           0.06471188076161556,
+           0.02207184511240712,
+           -0.022450005871874627,
+           -0.06809497421941636,
+           -0.11406171595635813,
+           -0.15953008124175336,
+           -0.20368553304948095,
+           -0.24574348804370924,
+           -0.28497292455538936,
+           -0.3207186206577106,
+           -0.35242141981048913,
+           -0.3796359715360037,
+           -0.40204545884942067,
+           -0.41947290108266067,
+           -0.4318887083784466,
+           -0.4394142602865311,
+           -0.44232138314503666,
+           -0.44102770669873026,
+           -0.43608798702302193,
+           -0.4281815875928796,
+           -0.41809641060717584,
+           -0.40670966390763913,
+           -0.3949659326465181,
+           -0.38385309711911336,
+           -0.3743766970333587,
+           -0.36753338641773536,
+           -0.36428415122105223,
+           -0.36552797268319553,
+           -0.3720766134242615,
+           -0.3846311800082631,
+           -0.40376107601076816,
+           -0.42988590429538515,
+           -0.4632608076109879,
+           -0.503965654447751,
+           -0.5518983843403424,
+           -0.6067727257537752,
+           -0.6681203928158734,
+           -0.7352977571047601,
+           -0.8074968801802015,
+           -0.8837606843012629,
+           -0.9630019354871835,
+           -1.0440256173237608,
+           -1.1255541880836375,
+           -1.2062551399647148,
+           -1.2847702194122412,
+           -1.359745623092043,
+           -1.429862456261897,
+           -1.4938667297758923,
+           -1.5505981790577106,
+           -1.5990172129646056,
+           -1.6382293419759273,
+           -1.667506492601367,
+           -1.6863046869448763,
+           -1.6942776512496887,
+           -1.6912860129395004,
+           -1.677401849844169,
+           -1.6529084654278916,
+           -1.61829537724739,
+           -1.574248619797864,
+           -1.521636574580778,
+           -1.4614916469285857,
+           -1.3949882082458969,
+           -1.3234173114572738,
+           -1.2481587644154466,
+           -1.1706512089438195,
+           -1.0923609005314598,
+           -1.0147499143150027,
+           -0.9392445161287138,
+           -0.8672044327663544,
+           -0.7998937332978463,
+           -0.7384539938732446,
+           -0.6838803628979948,
+           -0.6370010731436837,
+           -0.5984608639941343,
+           -0.5687086826635178,
+           -0.5479899301736653,
+           -0.5363434086652328,
+           -0.5336030139134442,
+           -0.5394041034774287,
+           -0.5531943595009665,
+           -0.5742488585162236,
+           -0.6016889612746513,
+           -0.6345045460500822,
+           -0.6715790311941481,
+           -0.7117165688425612,
+           -0.7536707430992128,
+           -0.7961740739105297,
+           -0.8379676129243627,
+           -0.8778299202200164,
+           -0.9146047307806128,
+           -0.9472266564085734,
+           -0.9747443214974487,
+           -0.9963403983165099,
+           -1.01134808752961,
+           -1.0192636805348216,
+           -1.019754939591269,
+           -1.012665137103707,
+           -0.9980127042292914,
+           -0.9759865484420711,
+           -0.9469372071158125,
+           -0.9113641068988766,
+           -0.869899294112872,
+           -0.8232880872533277,
+           -0.7723671767935624,
+           -0.7180407580773188,
+           -0.6612553286580434,
+           -0.602973810907498,
+           -0.5441496733829123,
+           -0.48570172004056844,
+           -0.4284901950730149,
+           -0.37329481350807814,
+           -0.3207952747302041,
+           -0.2715547491406086,
+           -0.22600674898301204,
+           -0.18444570495185655,
+           -0.1470214728492514,
+           -0.11373789174163763,
+           -0.0844554093979563,
+           -0.0588976849475417,
+           -0.03666197535990981,
+           -0.017233014136308004,
+           -1.524077193334442e-16
+          ],
+          [
+           0,
+           0.015715491921897022,
+           0.031019305636535405,
+           0.046702741842701276,
+           0.06355047346974442,
+           0.08231582865409935,
+           0.10369686284112682,
+           0.12831386649724247,
+           0.1566889185882794,
+           0.18922804393387382,
+           0.2262064660904319,
+           0.26775736821696633,
+           0.3138644844310213,
+           0.36435874573080324,
+           0.41891910012515493,
+           0.4770775188097447,
+           0.5382280917784051,
+           0.6016400099055066,
+           0.666474128972434,
+           0.7318027169163008,
+           0.796631901148837,
+           0.8599262602838098,
+           0.9206349458831213,
+           0.9777186764036181,
+           1.0301769185369323,
+           1.0770745613124342,
+           1.1175673959794745,
+           1.1509257396643777,
+           1.176555582541387,
+           1.1940166957764935,
+           1.2030372094143946,
+           1.2035242539353794,
+           1.1955703543453609,
+           1.1794553690450322,
+           1.1556438748092164,
+           1.1247780113032342,
+           1.087665910897048,
+           1.0452659493251317,
+           0.9986671572526618,
+           0.9490662294432884,
+           0.8977416545665939,
+           0.8460255625697602,
+           0.7952739461069706,
+           0.7468359562603952,
+           0.702022999575068,
+           0.6620783725590854,
+           0.6281481609974555,
+           0.6012541048607549,
+           0.5822690858646852,
+           0.5718958348831373,
+           0.5706493818632707,
+           0.5788436834279415,
+           0.5965827650897122,
+           0.6237566083209826,
+           0.6600419002152944,
+           0.7049076478705127,
+           0.7576255437389148,
+           0.8172848548454016,
+           0.8828115007361298,
+           0.9529908849210431,
+           1.0264939548570888,
+           1.1019058883734947,
+           1.1777567417483925,
+           1.2525533479358786,
+           1.3248117238520358,
+           1.3930892338760534,
+           1.4560157630902386,
+           1.5123231781088735,
+           1.560872395029105,
+           1.6006774320517678,
+           1.6309258972408998,
+           1.650995447928736,
+           1.6604658553190172,
+           1.6591264135187616,
+           1.6469785439513025,
+           1.6242335611399572,
+           1.591305681392984,
+           1.548800469148275,
+           1.497499023893159,
+           1.4383383110316954,
+           1.3723881303932486,
+           1.3008252940789724,
+           1.224905649151023,
+           1.145934628758788,
+           1.065237046533206,
+           0.9841268627470329,
+           0.9038776465529433,
+           0.8256944367305812,
+           0.7506876643918619,
+           0.6798497460261023,
+           0.6140348855226715,
+           0.5539425411586002,
+           0.5001049200668178,
+           0.4528787607555216,
+           0.4124415563832885,
+           0.37879226040147274,
+           0.35175640462276575,
+           0.330995450535007,
+           0.31602009046130775,
+           0.30620711854892296,
+           0.3008194049330982,
+           0.2990284318971389,
+           0.29993879025878445,
+           0.30261398902652703,
+           0.3061029026712872,
+           0.30946616881805583,
+           0.31180185501797963,
+           0.3122697363172032,
+           0.31011356496800296,
+           0.3046807687895482,
+           0.29543908395164015,
+           0.2819897095453907,
+           0.2640766631334735,
+           0.24159211619903082,
+           0.21457759350053945,
+           0.1832210281225408,
+           0.1478497717566597,
+           0.10891976472499867,
+           0.06700116981206848,
+           0.02276086558352492,
+           -0.023057723776652942,
+           -0.06965691604147918,
+           -0.11620857488459484,
+           -0.16187878962664476,
+           -0.2058527671531842,
+           -0.24735926635031197,
+           -0.2856939165824859,
+           -0.3202407898405948,
+           -0.3504916405151653,
+           -0.3760622861882009,
+           -0.3967056758949922,
+           -0.4123212771473107,
+           -0.42296050749658565,
+           -0.4288280381698213,
+           -0.4302789037663972,
+           -0.42781146047362884,
+           -0.42205634300173067,
+           -0.4137616747279892,
+           -0.4037748837313965,
+           -0.39302156699765817,
+           -0.3824819237968638,
+           -0.37316534506742416,
+           -0.3660837968851795,
+           -0.36222467142302617,
+           -0.3625237972773398,
+           -0.3678393021362682,
+           -0.37892700440837224,
+           -0.39641797697115055,
+           -0.42079887641856123,
+           -0.45239556627490723,
+           -0.4913604841695149,
+           -0.5376641128443029,
+           -0.5910908153008431,
+           -0.651239187831215,
+           -0.7175269737438252,
+           -0.7892004680319045,
+           -0.8653482318261796,
+           -0.9449188279888379,
+           -1.026742188317698,
+           -1.1095541310536332,
+           -1.1920234670173964,
+           -1.2727810657628658,
+           -1.35045020131415,
+           -1.4236774616751535,
+           -1.491163488280203,
+           -1.551692811385265,
+           -1.604162065133587,
+           -1.6476059012787299,
+           -1.6812199724921821,
+           -1.7043804235890698,
+           -1.7166594102596975,
+           -1.717836258039255,
+           -1.707903977030887,
+           -1.6870709578266871,
+           -1.6557577884770345,
+           -1.6145892484581232,
+           -1.5643816505536052,
+           -1.5061258125970776,
+           -1.440966045410381,
+           -1.370175638471757,
+           -1.2951294085350864,
+           -1.217273946554964,
+           -1.1380962531413257,
+           -1.0590914910349856,
+           -0.9817306038301156,
+           -0.9074285528702545,
+           -0.837513908850119,
+           -0.7732005015491609,
+           -0.715561781120516,
+           -0.6655084786898143,
+           -0.6237700742947797,
+           -0.5908804883732399,
+           -0.5671683113344471,
+           -0.552751776715303,
+           -0.5475385696960231,
+           -0.5512304471080677,
+           -0.5633325303330248,
+           -0.5831670214610589,
+           -0.609890988453062,
+           -0.6425177693719405,
+           -0.67994146133194,
+           -0.7209638886964237,
+           -0.7643233889392704,
+           -0.8087247148061198,
+           -0.852869328897657,
+           -0.8954853620493198,
+           -0.9353565199628241,
+           -0.9713492530776848,
+           -1.0024375518484214,
+           -1.027724792198962,
+           -1.0464621323653212,
+           -1.058063050677405,
+           -1.0621137118474189,
+           -1.0583789545676208,
+           -1.0468038030430167,
+           -1.0275105167556495,
+           -1.000791303497922,
+           -0.9670969277735678,
+           -0.9270215473950689,
+           -0.881284203017314,
+           -0.8307074661763395,
+           -0.776193819167123,
+           -0.7187003931439172,
+           -0.6592127278792277,
+           -0.5987182367943465,
+           -0.5381800637197599,
+           -0.47851200333636207,
+           -0.42055512580144405,
+           -0.36505669851300954,
+           -0.31265193555084186,
+           -0.26384902966180973,
+           -0.21901783466944377,
+           -0.17838247010420982,
+           -0.1420180171169456,
+           -0.10985136796354572,
+           -0.08166618324264975,
+           -0.057111804368834375,
+           -0.03571586617310518,
+           -0.01690025863584555,
+           -1.50759621388702e-16
+          ],
+          [
+           0,
+           0.01582552992859333,
+           0.03161287935934787,
+           0.04816599129908692,
+           0.06626844202651479,
+           0.08665866338760865,
+           0.11000634340047011,
+           0.13689064385950622,
+           0.1677808273121538,
+           0.20301982419089076,
+           0.24281119556775246,
+           0.28720985985358055,
+           0.33611685498480337,
+           0.3892783036663716,
+           0.4462886406938211,
+           0.5065980510016871,
+           0.5695239576704311,
+           0.6342662934401164,
+           0.6999261900069293,
+           0.7655276290420204,
+           0.8300415197744664,
+           0.8924116021467945,
+           0.9515815236786543,
+           1.0065224035863138,
+           1.056260180321483,
+           1.0999020390026537,
+           1.136661233263815,
+           1.16587965144386,
+           1.1870475289555222,
+           1.199819775861474,
+           1.2040284695194228,
+           1.1996911546660454,
+           1.1870146952243217,
+           1.1663945309338861,
+           1.1384093049355473,
+           1.1038109428943286,
+           1.0635103772837053,
+           1.0185592192692927,
+           0.9701277825135635,
+           0.9194799556305018,
+           0.8679455006357328,
+           0.8168904215357103,
+           0.767686098488397,
+           0.7216779174367841,
+           0.680154141867493,
+           0.6443157719167475,
+           0.6152481164202381,
+           0.5938947661147991,
+           0.5810346019199274,
+           0.5772624023446313,
+           0.5829735302543975,
+           0.5983530835138117,
+           0.6233697887075152,
+           0.6577748047895199,
+           0.7011054868481511,
+           0.7526940420396321,
+           0.8116808930151742,
+           0.8770324516902236,
+           0.9475629007241155,
+           1.0219594841683055,
+           1.098810724743033,
+           1.1766369151667002,
+           1.2539221765992121,
+           1.3291473398964389,
+           1.400822885918465,
+           1.4675211800614951,
+           1.5279072535143763,
+           1.5807674190474539,
+           1.6250350615556326,
+           1.6598130118126204,
+           1.6843919942761183,
+           1.6982647342957369,
+           1.7011354144026478,
+           1.6929242809500176,
+           1.6737673184983308,
+           1.6440110271637034,
+           1.6042024547959215,
+           1.5550747484844325,
+           1.4975285957654665,
+           1.432610022452421,
+           1.3614850988981158,
+           1.28541217767528,
+           1.2057123414251099,
+           1.1237387786491781,
+           1.0408458265983718,
+           0.9583584236706659,
+           0.8775426988418559,
+           0.7995783930416548,
+           0.7255337579096295,
+           0.6563435122940954,
+           0.5927903578470428,
+           0.5354904641153265,
+           0.4848832329194762,
+           0.44122554406716724,
+           0.40459057226029815,
+           0.37487115121835085,
+           0.3517875483864831,
+           0.3348994049188134,
+           0.3236214936148416,
+           0.3172428546570782,
+           0.3149487876339633,
+           0.31584511042640306,
+           0.3189840427415638,
+           0.32339103566606564,
+           0.3280918494431791,
+           0.3321391801830078,
+           0.33463815237665917,
+           0.33477002744869494,
+           0.33181352826097293,
+           0.3251632441822627,
+           0.3143446593943188,
+           0.2990254365169167,
+           0.2790226861199273,
+           0.25430605774380277,
+           0.22499659700275024,
+           0.19136142343478799,
+           0.15380439220140138,
+           0.11285300678255188,
+           0.06914194682929334,
+           0.023393662873855272,
+           -0.023603434556367715,
+           -0.07101860163541582,
+           -0.11800356690212921,
+           -0.16371784835896858,
+           -0.20735390093599643,
+           -0.2481614172046848,
+           -0.2854701255796956,
+           -0.31871046846499984,
+           -0.3474315969246578,
+           -0.37131618712790504,
+           -0.3901916653054438,
+           -0.40403752020716793,
+           -0.4129884827463993,
+           -0.41733345911265823,
+           -0.4175102134431899,
+           -0.4140959063882965,
+           -0.40779370379746516,
+           -0.3994157725583361,
+           -0.3898630757282577,
+           -0.38010246408736037,
+           -0.3711416339415652,
+           -0.3640025795469361,
+           -0.3596942113983309,
+           -0.35918483770009413,
+           -0.3633752149078595,
+           -0.3730728640283832,
+           -0.38896832256265507,
+           -0.41161395819068336,
+           -0.44140591056420714,
+           -0.4785696533364251,
+           -0.5231495816209214,
+           -0.5750029325612502,
+           -0.6337982410022086,
+           -0.6990184209869076,
+           -0.7699684497081883,
+           -0.8457875164430896,
+           -0.9254653877261848,
+           -1.0078626343385984,
+           -1.0917342682396156,
+           -1.175756250783523,
+           -1.258554259624,
+           -1.3387340424768202,
+           -1.41491264289454,
+           -1.4857497575120204,
+           -1.5499784765314997,
+           -1.606434669770576,
+           -1.6540843091861017,
+           -1.6920480647572052,
+           -1.7196225728785852,
+           -1.7362978534942042,
+           -1.7417704422391784,
+           -1.7359519046799605,
+           -1.7189725089079202,
+           -1.6911799475992977,
+           -1.6531331184124713,
+           -1.6055910893845782,
+           -1.5494974909432397,
+           -1.485960685461916,
+           -1.4162301662918872,
+           -1.3416697284343997,
+           -1.2637280302701177,
+           -1.1839072281535945,
+           -1.1037304116849034,
+           -1.024708595967433,
+           -0.9483080374558799,
+           -0.8759186318445152,
+           -0.8088241260459481,
+           -0.7481748323154176,
+           -0.6949634720657505,
+           -0.6500047013778096,
+           -0.6139187814925051,
+           -0.5871197578456582,
+           -0.5698084029174226,
+           -0.5619700639616015,
+           -0.5633774393475994,
+           -0.5735981896530794,
+           -0.5920071746553912,
+           -0.6178029977837911,
+           -0.6500284380749811,
+           -0.6875942586821224,
+           -0.7293058027202406,
+           -0.7738917235706618,
+           -0.8200341492329452,
+           -0.8663995500245087,
+           -0.9116695665791198,
+           -0.9545710609355125,
+           -0.9939046773379056,
+           -1.0285712405492629,
+           -1.0575953769370956,
+           -1.080145815861915,
+           -1.0955519141492698,
+           -1.1033160425094235,
+           -1.103121577273055,
+           -1.0948363511224555,
+           -1.078511529863577,
+           -1.0543759958830448,
+           -1.0228264299450402,
+           -0.9844133886554661,
+           -0.939823772643771,
+           -0.8898601678785336,
+           -0.8354176173969664,
+           -0.7774584412626674,
+           -0.7169857673032749,
+           -0.6550164630503551,
+           -0.5925541696616633,
+           -0.5305631312434304,
+           -0.4699434881435662,
+           -0.41150866112907447,
+           -0.35596539598517124,
+           -0.3038969664647721,
+           -0.2557499495142782,
+           -0.21182489245240138,
+           -0.17227108968460061,
+           -0.13708557919170022,
+           -0.10611635916139425,
+           -0.0790697155198746,
+           -0.055521444542536845,
+           -0.034931653873867506,
+           -0.01666273271673751,
+           -1.5011548028462236e-16
+          ],
+          [
+           0,
+           0.01606234801083481,
+           0.032473494337788976,
+           0.05004272409203558,
+           0.06954491896377542,
+           0.0916959498985329,
+           0.11712964005061045,
+           0.14637692262216523,
+           0.17984776197188534,
+           0.21781633548175902,
+           0.260409889889464,
+           0.30760159123882325,
+           0.35920758465596203,
+           0.41488837142214974,
+           0.47415449903212664,
+           0.5363764479251647,
+           0.6007984891903332,
+           0.6665561835506956,
+           0.732697095965237,
+           0.7982042146963287,
+           0.8620214908595387,
+           0.9230808561726673,
+           0.9803300343619298,
+           1.032760436575879,
+           1.0794344238848954,
+           1.119511230743805,
+           1.1522708719534291,
+           1.177135401512769,
+           1.1936869537149404,
+           1.2016820734102842,
+           1.201061931674737,
+           1.191958122994066,
+           1.1746938480503923,
+           1.1497803996147005,
+           1.1179089851042971,
+           1.0799380351821162,
+           1.0368762604792108,
+           0.9898618253074047,
+           0.940138105430955,
+           0.8890265841260744,
+           0.8378975146851827,
+           0.7881390363513664,
+           0.7411254728997316,
+           0.6981855676251388,
+           0.6605714146938771,
+           0.6294288344650079,
+           0.6057699097375949,
+           0.5904483516361536,
+           0.5841382991464222,
+           0.5873170767019992,
+           0.6002523416136774,
+           0.6229939497642388,
+           0.6553707563662986,
+           0.6969924514099699,
+           0.7472564095605871,
+           0.8053594146237569,
+           0.8703140021924759,
+           0.9409690535714772,
+           1.0160341722355513,
+           1.0941072834088021,
+           1.1737048200658327,
+           1.2532937966423452,
+           1.331325026516893,
+           1.406266711992093,
+           1.4766376267294048,
+           1.541039120589047,
+           1.5981852053487866,
+           1.6469300261218605,
+           1.686292086328657,
+           1.7154746722546035,
+           1.733882014633563,
+           1.741130827094935,
+           1.7370569721990508,
+           1.7217171224491687,
+           1.6953854032602835,
+           1.6585451244672613,
+           1.6118758236529585,
+           1.5562359555312686,
+           1.4926416641357618,
+           1.4222421661578892,
+           1.34629235223806,
+           1.2661232764527364,
+           1.183111251148197,
+           1.0986462935429155,
+           1.0141006814880573,
+           0.9307983682235534,
+           0.8499859801364714,
+           0.772806078110155,
+           0.7002733031699748,
+           0.6332539523122385,
+           0.5724494425396519,
+           0.5183840224310998,
+           0.47139698351964804,
+           0.4316395110161617,
+           0.3990761978070076,
+           0.37349113004801177,
+           0.35449833994156926,
+           0.34155631421003174,
+           0.3339861480097604,
+           0.330992845997423,
+           0.33168919712164247,
+           0.33512158930128366,
+           0.34029708592794283,
+           0.3462110591488917,
+           0.3518746657698266,
+           0.35634146053836896,
+           0.3587324682526571,
+           0.35825907986355504,
+           0.35424319735819926,
+           0.3461341261846101,
+           0.3335218004026186,
+           0.31614602241696993,
+           0.2939015036016526,
+           0.2668386017061938,
+           0.235159762864995,
+           0.19921178747457868,
+           0.1594741473407411,
+           0.11654368359393176,
+           0.07111610834700713,
+           0.02396481556390186,
+           -0.024082423962200773,
+           -0.07216825400968946,
+           -0.11943134278011683,
+           -0.16503212202225898,
+           -0.20817796270486022,
+           -0.24814710876514173,
+           -0.2843107221505644,
+           -0.3161524407050696,
+           -0.34328491421207397,
+           -0.36546286148946994,
+           -0.38259228088233815,
+           -0.3947355455619789,
+           -0.4021122212163055,
+           -0.4050955543261464,
+           -0.4042046914694843,
+           -0.4000928011417093,
+           -0.39353137661141546,
+           -0.38539109863218834,
+           -0.3766197278501857,
+           -0.3682175761632324,
+           -0.36121117206519304,
+           -0.3566257854536065,
+           -0.3554575111746346,
+           -0.358645626827539,
+           -0.3670459385892002,
+           -0.3814058090356059,
+           -0.402341523570395,
+           -0.43031859799968225,
+           -0.4656355603158067,
+           -0.508411656556145,
+           -0.5585788357184872,
+           -0.615878264469403,
+           -0.6798615113426786,
+           -0.7498964250324519,
+           -0.825177615088327,
+           -0.9047413287021772,
+           -0.9874844071883218,
+           -1.072186902943639,
+           -1.1575378447018647,
+           -1.2421635580979395,
+           -1.324657881969146,
+           -1.4036135701276422,
+           -1.4776541348428063,
+           -1.5454653728477763,
+           -1.6058258177647837,
+           -1.6576353844050782,
+           -1.6999415099621011,
+           -1.7319621537574603,
+           -1.7531050895729923,
+           -1.7629830109734062,
+           -1.761424068311132,
+           -1.7484775639300634,
+           -1.7244146468325758,
+           -1.6897239669556097,
+           -1.64510236932342,
+           -1.5914408267794558,
+           -1.529805923859384,
+           -1.4614173108724022,
+           -1.387621643807927,
+           -1.3098636099208705,
+           -1.2296547087126994,
+           -1.1485405118102472,
+           -1.0680671616354795,
+           -0.9897478868691963,
+           -0.9150303120982153,
+           -0.845265319716979,
+           -0.7816781846053383,
+           -0.7253426472460482,
+           -0.6771585201228242,
+           -0.6378333371872592,
+           -0.6078684589829902,
+           -0.5875499390458417,
+           -0.5769443430751555,
+           -0.5758995938821445,
+           -0.5840507951582795,
+           -0.6008308685957646,
+           -0.6254857247189403,
+           -0.657093580725807,
+           -0.6945879412900644,
+           -0.7367836729909963,
+           -0.7824055318760431,
+           -0.8301184483234801,
+           -0.8785588351724892,
+           -0.926366164913454,
+           -0.972214060025703,
+           -1.0148401573002834,
+           -1.053074041724227,
+           -1.085862597320139,
+           -1.1122921899011688,
+           -1.131607178300748,
+           -1.1432243442105552,
+           -1.1467429339587176,
+           -1.1419501158002874,
+           -1.1288217708221646,
+           -1.1075186515332727,
+           -1.0783780567372834,
+           -1.041901281531292,
+           -0.998737204514072,
+           -0.9496624679768281,
+           -0.8955587886859143,
+           -0.8373880048492585,
+           -0.7761655173342622,
+           -0.7129328189130245,
+           -0.6487298234100806,
+           -0.5845677067193077,
+           -0.5214029537917745,
+           -0.46011327037547883,
+           -0.4014759664477074,
+           -0.346149351269202,
+           -0.2946575995328348,
+           -0.2473794562382829,
+           -0.20454104704116677,
+           -0.16621295346662412,
+           -0.13231160126881109,
+           -0.10260489817575237,
+           -0.07672194711989144,
+           -0.054166555604315936,
+           -0.03433416375844196,
+           -0.016531725372861288,
+           -1.5056814338436878e-16
+          ],
+          [
+           0,
+           0.016433212063026816,
+           0.03361215470067645,
+           0.05234386645400184,
+           0.0733867818627306,
+           0.09742653112967131,
+           0.12505370090181042,
+           0.15674416035443833,
+           0.19284249081574362,
+           0.23354897731059446,
+           0.2789105286474373,
+           0.32881579133621286,
+           0.3829946142659009,
+           0.4410219084249645,
+           0.5023258318644769,
+           0.5662001174694535,
+           0.6318202527733846,
+           0.6982631197743205,
+           0.76452961106494,
+           0.8295696589126729,
+           0.8923090482612437,
+           0.9516773346658969,
+           1.006636155224014,
+           1.0562072054999476,
+           1.0994991587001401,
+           1.135732824906773,
+           1.1642638875420999,
+           1.1846026104817535,
+           1.1964299810102226,
+           1.199609839371233,
+           1.194196642917935,
+           1.1804386194242695,
+           1.1587761773542,
+           1.129835558001708,
+           1.094417832510904,
+           1.0534834629302827,
+           1.008132757758172,
+           0.9595826561211263,
+           0.9091403681997343,
+           0.8581744804304116,
+           0.8080842003266079,
+           0.760267465794633,
+           0.7160886762831901,
+           0.6768468171484111,
+           0.6437447438376097,
+           0.6178603689584218,
+           0.6001204535318886,
+           0.591277644704638,
+           0.5918913273198506,
+           0.6023127678148599,
+           0.6226749280693182,
+           0.6528872165124106,
+           0.6926353266872342,
+           0.7413861924123929,
+           0.7983979666226333,
+           0.862734810887448,
+           0.9332861674290901,
+           1.0087900780019041,
+           1.087860016878892,
+           1.1690146207931578,
+           1.2507096290650592,
+           1.3313712940135893,
+           1.4094304864024845,
+           1.4833567039725826,
+           1.5516911934704296,
+           1.6130784179408908,
+           1.666295140885376,
+           1.71027645622197,
+           1.7441381664157947,
+           1.7671949988805646,
+           1.7789742506395134,
+           1.7792245608335175,
+           1.7679196272981608,
+           1.7452568042515781,
+           1.7116506401932619,
+           1.6677215354356112,
+           1.6142798143458754,
+           1.5523056155554995,
+           1.482925101473345,
+           1.4073835740469374,
+           1.3270161547901669,
+           1.2432167419351625,
+           1.1574059948711393,
+           1.0709991149377844,
+           0.9853741917339184,
+           0.9018418654359787,
+           0.8216170187098669,
+           0.7457931576071738,
+           0.6753200707499663,
+           0.6109852719042589,
+           0.5533996348424752,
+           0.502987523613194,
+           0.45998160861734766,
+           0.4244224420446366,
+           0.3961627481588667,
+           0.37487626756646336,
+           0.36007088283962285,
+           0.3511056484548845,
+           0.3472112535208443,
+           0.3475133635241082,
+           0.3510582193294703,
+           0.35683981957819383,
+           0.3638279776869734,
+           0.37099652767869373,
+           0.3773509544436086,
+           0.3819547436458538,
+           0.383953783809613,
+           0.38259820715375936,
+           0.37726112508926546,
+           0.3674537971646236,
+           0.35283686651953744,
+           0.333227398182332,
+           0.308601566195454,
+           0.2790929487936851,
+           0.24498650482188208,
+           0.20670841637941817,
+           0.16481208949054882,
+           0.11996070372542149,
+           0.07290679063301769,
+           0.024469397350732464,
+           -0.024490546104157157,
+           -0.07309599114513968,
+           -0.12047997269761608,
+           -0.16581154393246048,
+           -0.2083207453615317,
+           -0.24732193477475836,
+           -0.2822348465871054,
+           -0.31260280751068775,
+           -0.33810760860203437,
+           -0.3585806198131239,
+           -0.37400983002632887,
+           -0.38454260073367486,
+           -0.390484032373969,
+           -0.3922909560660805,
+           -0.39056167719620605,
+           -0.38602170815150144,
+           -0.37950583263070814,
+           -0.37193694073258843,
+           -0.36430215995943066,
+           -0.35762688017824423,
+           -0.35294732858264133,
+           -0.35128239229047054,
+           -0.3536054103016534,
+           -0.36081666246935884,
+           -0.3737172707013096,
+           -0.39298519706158996,
+           -0.419153975495278,
+           -0.4525947496935326,
+           -0.4935021107090166,
+           -0.5418841362447108,
+           -0.5975569313203929,
+           -0.6601438597850051,
+           -0.7290795406099159,
+           -0.8036185649259062,
+           -0.882848772280997,
+           -0.9657088105169204,
+           -1.051009595831503,
+           -1.1374591907056013,
+           -1.2236905299048642,
+           -1.3082913509186467,
+           -1.3898356268391925,
+           -1.4669157583024834,
+           -1.5381747577806728,
+           -1.6023376548633317,
+           -1.6582413653597154,
+           -1.7048622998014702,
+           -1.7413410374709326,
+           -1.7670034592308403,
+           -1.7813778145829648,
+           -1.7842072935593811,
+           -1.7754577799516247,
+           -1.7553205764432858,
+           -1.724210011660198,
+           -1.6827559610829381,
+           -1.6317914352083545,
+           -1.5723355063380817,
+           -1.5055719570325978,
+           -1.4328241358715912,
+           -1.3555265971977808,
+           -1.2751941787659644,
+           -1.1933892327827043,
+           -1.1116877701987895,
+           -1.0316453042204767,
+           -0.9547631861985181,
+           -0.8824562151597309,
+           -0.816022271556677,
+           -0.7566146770778864,
+           -0.7052179167773445,
+           -0.6626272789526312,
+           -0.629432874103581,
+           -0.6060083892390582,
+           -0.5925048203361142,
+           -0.5888493066654618,
+           -0.5947490688866295,
+           -0.6097003312559859,
+           -0.6330019899422811,
+           -0.6637736771860193,
+           -0.7009777675964728,
+           -0.7434447807587193,
+           -0.7899015557463606,
+           -0.8390015099908408,
+           -0.8893562487507277,
+           -0.9395677632396674,
+           -0.9882604459506709,
+           -1.0341121610370732,
+           -1.0758836354923484,
+           -1.1124454825707828,
+           -1.1428022312298707,
+           -1.166112812766038,
+           -1.181707046302396,
+           -1.1890977660962252,
+           -1.187988343227564,
+           -1.1782754693718416,
+           -1.160047188181734,
+           -1.1335762773784437,
+           -1.0993091990658375,
+           -1.0578509442028061,
+           -1.0099461969254933,
+           -0.9564573330489772,
+           -0.8983398424269251,
+           -0.8366158250727178,
+           -0.772346254592419,
+           -0.7066027285112851,
+           -0.6404394328952379,
+           -0.5748660381371576,
+           -0.5108222142139771,
+           -0.4491544078935643,
+           -0.3905954624803914,
+           -0.33574758433560126,
+           -0.2850690715501615,
+           -0.2388651210589904,
+           -0.19728292368240732,
+           -0.16031114478193542,
+           -0.12778377425513607,
+           -0.09938821635441955,
+           -0.07467738016182161,
+           -0.053085428256424615,
+           -0.03394674678213868,
+           -0.016517617141548094,
+           -1.5220054590144853e-16
+          ],
+          [
+           0,
+           0.016944081643460306,
+           0.035037054641874864,
+           0.05507590779524772,
+           0.07779480047562612,
+           0.10384150903814413,
+           0.13375622006001625,
+           0.16795324784313595,
+           0.20670617823034318,
+           0.25013685240670236,
+           0.29820850521615305,
+           0.35072326512422186,
+           0.4073241100126386,
+           0.4675012573573943,
+           0.5306028519443104,
+           0.5958497020392981,
+           0.6623537087020097,
+           0.7291395354121537,
+           0.7951689788529626,
+           0.8593674287743976,
+           0.9206517472148514,
+           0.9779588564894108,
+           1.0302743023320524,
+           1.0766600540399844,
+           1.1162808175802421,
+           1.1484281700846477,
+           1.172541874222339,
+           1.1882277974007458,
+           1.1952719419951914,
+           1.193650186860506,
+           1.1835334449275174,
+           1.1652880541584438,
+           1.139471336750295,
+           1.1068223813220999,
+           1.068248221925763,
+           1.024805703118718,
+           0.9776794291518311,
+           0.9281562948374237,
+           0.877597183373819,
+           0.8274064901051219,
+           0.7790001890209337,
+           0.7337731992719705,
+           0.6930668310417707,
+           0.658137093172157,
+           0.6301246288593704,
+           0.610027010859137,
+           0.5986740747671837,
+           0.5967068993263214,
+           0.604560958016347,
+           0.6224538684467893,
+           0.650378057657081,
+           0.688098544962424,
+           0.7351559222963374,
+           0.7908744880544808,
+           0.8543753672599435,
+           0.9245943314534387,
+           1.0003039189792395,
+           1.080139353044462,
+           1.162627663601542,
+           1.246219341976249,
+           1.3293217961244017,
+           1.410333830944722,
+           1.4876803532680432,
+           1.5598464955929725,
+           1.6254103664826571,
+           1.6830736684390113,
+           1.7316894752258922,
+           1.7702865287708542,
+           1.7980894992699334,
+           1.8145347489105967,
+           1.8192812473490827,
+           1.812216403098503,
+           1.7934566964705656,
+           1.7633431237025776,
+           1.7224315853699956,
+           1.6714784721267413,
+           1.611421814314362,
+           1.5433584662821902,
+           1.468517888838691,
+           1.388233171875356,
+           1.3039100019812166,
+           1.2169943253029112,
+           1.1289394829358959,
+           1.0411736041446236,
+           0.9550680315607486,
+           0.8719075225275983,
+           0.7928629227388173,
+           0.7189669434948776,
+           0.6510935939202682,
+           0.5899417263649578,
+           0.536023049294123,
+           0.48965484985024754,
+           0.4509575507484844,
+           0.41985710616403277,
+           0.396092121768395,
+           0.3792254680296503,
+           0.3686600461776487,
+           0.3636582655518693,
+           0.363364701870674,
+           0.36683133046715316,
+           0.37304466856461627,
+           0.3809541176591816,
+           0.3895007720571916,
+           0.39764595314950213,
+           0.4043987411973664,
+           0.40884180689310656,
+           0.4101548929244527,
+           0.40763535995949696,
+           0.4007152902215921,
+           0.3889747331199058,
+           0.3721507789104938,
+           0.35014225550118105,
+           0.32300995750984834,
+           0.29097243265084544,
+           0.2543974655230016,
+           0.2137895099980435,
+           0.1697734258534661,
+           0.12307497042309767,
+           0.07449857945266626,
+           0.024903040943974546,
+           -0.0248242802035064,
+           -0.0737939718509164,
+           -0.1211411444463203,
+           -0.166051326005672,
+           -0.20778498472179482,
+           -0.24570001708752476,
+           -0.2792715918638444,
+           -0.3081088083769996,
+           -0.3319677097703871,
+           -0.3507602858942033,
+           -0.364559204113899,
+           -0.3735981168405633,
+           -0.37826750923913965,
+           -0.3791061664537809,
+           -0.3767884538693835,
+           -0.37210771350964195,
+           -0.36595618187175877,
+           -0.359301926715018,
+           -0.35316338020040755,
+           -0.3485821112732051,
+           -0.3465945295994851,
+           -0.34820324542070913,
+           -0.354348823521096,
+           -0.3658826647083956,
+           -0.383541724853852,
+           -0.40792574015013916,
+           -0.4394775688075856,
+           -0.4784671853281259,
+           -0.5249797755760781,
+           -0.5789082812572782,
+           -0.6399506335720786,
+           -0.7076118004076943,
+           -0.7812106523352296,
+           -0.8598915328289628,
+           -0.9426403005079914,
+           -1.0283044987423435,
+           -1.11561720347528,
+           -1.2032240062068784,
+           -1.2897125081216427,
+           -1.3736436353690524,
+           -1.4535840361989651,
+           -1.5281387892826745,
+           -1.5959836399441871,
+           -1.6558959875515717,
+           -1.7067838728702154,
+           -1.7477122581845719,
+           -1.7779259544220551,
+           -1.7968686269007343,
+           -1.80419740281496,
+           -1.7997927069627147,
+           -1.7837630650026204,
+           -1.756444732969568,
+           -1.7183961349709822,
+           -1.6703872149300787,
+           -1.6133839299155333,
+           -1.5485282290282658,
+           -1.4771139701612113,
+           -1.400559324557905,
+           -1.3203763035828153,
+           -1.238138111412699,
+           -1.1554450797670082,
+           -1.0738899750325945,
+           -0.995023483363917,
+           -0.9203206751809458,
+           -0.8511492270425692,
+           -0.7887401367165975,
+           -0.734161607428213,
+           -0.6882967012100321,
+           -0.6518252708581203,
+           -0.6252105774291669,
+           -0.6086908880009825,
+           -0.6022762293016624,
+           -0.6057503496998241,
+           -0.6186778179416226,
+           -0.6404160649436026,
+           -0.6701320578745288,
+           -0.7068231865283542,
+           -0.7493418432526827,
+           -0.7964230918392174,
+           -0.846714749871892,
+           -0.8988091547612059,
+           -0.9512758473547395,
+           -1.002694389445471,
+           -1.0516865330799487,
+           -1.096946980204185,
+           -1.1372720103135117,
+           -1.1715853103764091,
+           -1.1989604139355268,
+           -1.2186392431131956,
+           -1.2300463460786362,
+           -1.232798530893129,
+           -1.2267097118307564,
+           -1.2117909034059782,
+           -1.1882454174647743,
+           -1.1564594368341374,
+           -1.1169882522528802,
+           -1.0705385548308604,
+           -1.017947271507421,
+           -0.9601575135686944,
+           -0.8981922762226492,
+           -0.8331265788746723,
+           -0.7660587698591207,
+           -0.6980817351675233,
+           -0.6302547478346447,
+           -0.5635766732291594,
+           -0.49896120613866285,
+           -0.4372147592791636,
+           -0.3790175511582619,
+           -0.32490835592376066,
+           -0.2752732811182901,
+           -0.23033883360066904,
+           -0.1901694219720752,
+           -0.15466932849882806,
+           -0.12358906767492647,
+           -0.09653593514676924,
+           -0.07298844259560183,
+           -0.05231423406988443,
+           -0.03379098970558927,
+           -0.016629746025206955,
+           -1.5508458470450386e-16
+          ],
+          [
+           0,
+           0.01759951738810651,
+           0.03675343027048783,
+           0.05824073784591546,
+           0.08276350242292617,
+           0.11092418301115346,
+           0.14320569227732646,
+           0.17995472130227302,
+           0.22136879214457258,
+           0.2674874018602915,
+           0.31818751578088683,
+           0.3731835551880642,
+           0.43203190789407436,
+           0.49413987259014763,
+           0.5587788321445578,
+           0.6251013402492777,
+           0.6921617027447864,
+           0.7589395422206971,
+           0.8243657544637448,
+           0.8873502000570826,
+           0.9468104256112151,
+           1.001700678002922,
+           1.0510404624475969,
+           1.093941901602475,
+           1.1296351780896314,
+           1.1574913862635405,
+           1.177042179695619,
+           1.18799567724239,
+           1.1902481808426661,
+           1.183891360139906,
+           1.1692146701396224,
+           1.1467028856455126,
+           1.1170287572625308,
+           1.081040915307191,
+           1.039747267002145,
+           0.9942942458862781,
+           0.9459423776053879,
+           0.8960387205241472,
+           0.8459868205455321,
+           0.7972148850923162,
+           0.7511429297259653,
+           0.7091496810989593,
+           0.6725400310546916,
+           0.6425138283725066,
+           0.6201367670513132,
+           0.6063140837567378,
+           0.6017677132089079,
+           0.6070174703805751,
+           0.6223667343266464,
+           0.6478930025458047,
+           0.6834435695479247,
+           0.7286364615653251,
+           0.7828666340633782,
+           0.8453173129294014,
+           0.914976237016991,
+           0.9906564421049565,
+           1.0710211171710537,
+           1.1546119658512615,
+           1.2398804214551593,
+           1.3252209950071905,
+           1.409005984171178,
+           1.489620737858015,
+           1.5654986576265515,
+           1.6351551230038828,
+           1.697219553429896,
+           1.7504648640493123,
+           1.7938336349464794,
+           1.8264603921209117,
+           1.8476894916127142,
+           1.8570882034326435,
+           1.8544547067616064,
+           1.8398208294565297,
+           1.8134494902678213,
+           1.7758269282818566,
+           1.727649927878624,
+           1.6698083659289156,
+           1.6033635181708565,
+           1.529522661030948,
+           1.4496105911898682,
+           1.3650387558674089,
+           1.2772727404239645,
+           1.187798895179344,
+           1.0980908995173657,
+           1.0095770580325654,
+           0.923609100819481,
+           0.8414332186172208,
+           0.7641640044745126,
+           0.6927618983987006,
+           0.6280146419965541,
+           0.5705231486540087,
+           0.5206920838759113,
+           0.47872533278400276,
+           0.44462641037957873,
+           0.4182037480310203,
+           0.39908066977203677,
+           0.38670975735708335,
+           0.38039119644242164,
+           0.37929460036443585,
+           0.3824837251194862,
+           0.38894342133080495,
+           0.39760811785774164,
+           0.40739109848169586,
+           0.4172138185631332,
+           0.42603451300900613,
+           0.4328753701494776,
+           0.4368475875566102,
+           0.43717368435278886,
+           0.4332065186343652,
+           0.4244445463714175,
+           0.4105429572935852,
+           0.3913204313083887,
+           0.36676137317733737,
+           0.33701360060113966,
+           0.30238157856608905,
+           0.26331540780338114,
+           0.22039588460767656,
+           0.17431605029051628,
+           0.1258597386611631,
+           0.0758777068619552,
+           0.025261996700504635,
+           -0.025080781237820565,
+           -0.0742565210807652,
+           -0.12141032430761152,
+           -0.16575211295230205,
+           -0.20658046312133643,
+           -0.24330401465176693,
+           -0.2754598753872534,
+           -0.302728516197309,
+           -0.3249447435452014,
+           -0.3421044378326636,
+           -0.35436685535190304,
+           -0.36205240668653954,
+           -0.36563594191374504,
+           -0.3657356899949034,
+           -0.3630981133350837,
+           -0.3585790457593301,
+           -0.35312158036809593,
+           -0.3477312603910092,
+           -0.34344919903996873,
+           -0.3413238115943594,
+           -0.34238188304769074,
+           -0.34759971654821714,
+           -0.35787511097257196,
+           -0.3740009001474157,
+           -0.39664075181979563,
+           -0.42630787227861827,
+           -0.4633471938001484,
+           -0.5079215384984178,
+           -0.5600021557505849,
+           -0.6193639235056095,
+           -0.685585389106315,
+           -0.7580537055948757,
+           -0.8359743977954509,
+           -0.9183857717975574,
+           -1.0041776648042133,
+           -1.0921141225714088,
+           -1.1808594915967108,
+           -1.2690073253270824,
+           -1.355111430166156,
+           -1.4377183198335,
+           -1.5154003071291926,
+           -1.5867884414167541,
+           -1.65060449872563,
+           -1.705691249383682,
+           -1.7510402651341064,
+           -1.785816582913483,
+           -1.809379614561731,
+           -1.8212997789761245,
+           -1.8213704335102507,
+           -1.8096147923296948,
+           -1.7862876382797672,
+           -1.751871758707917,
+           -1.7070691615979703,
+           -1.652787253244653,
+           -1.590120279476886,
+           -1.520326446175498,
+           -1.444801238744233,
+           -1.3650475517389427,
+           -1.282643316796977,
+           -1.199207377451546,
+           -1.1163644018818537,
+           -1.0357096480964427,
+           -0.9587743998966997,
+           -0.8869928761227409,
+           -0.8216713805284686,
+           -0.7639604060242744,
+           -0.7148303362727015,
+           -0.6750513014525408,
+           -0.6451776455248988,
+           -0.6255373519701366,
+           -0.6162266564119636,
+           -0.6171099506971112,
+           -0.6278249568766268,
+           -0.6477930242110185,
+           -0.6762342808468879,
+           -0.7121872571401122,
+           -0.7545324925123333,
+           -0.8020195447671291,
+           -0.8532967422020524,
+           -0.9069429565189108,
+           -0.9615006299410613,
+           -1.015509264138744,
+           -1.0675385721231183,
+           -1.1162205073011182,
+           -1.1602794160113803,
+           -1.19855961024146,
+           -1.2300497245655044,
+           -1.2539033039312553,
+           -1.2694551646845964,
+           -1.2762331777470484,
+           -1.2739652374940946,
+           -1.262581299763307,
+           -1.2422104945697938,
+           -1.213173440493435,
+           -1.1759700053231221,
+           -1.1312628684942667,
+           -1.079857342405617,
+           -1.0226779993581256,
+           -0.9607427264317296,
+           -0.8951348902704136,
+           -0.8269743360468972,
+           -0.7573879688266016,
+           -0.6874806706067519,
+           -0.6183072924035808,
+           -0.5508464283053578,
+           -0.48597662827080856,
+           -0.42445563994129715,
+           -0.36690318856833143,
+           -0.3137877104163353,
+           -0.26541735107710623,
+           -0.22193542867070806,
+           -0.18332044573681275,
+           -0.1493906156837817,
+           -0.11981275294347293,
+           -0.09411526342708769,
+           -0.07170486633234507,
+           -0.051886582476702886,
+           -0.03388644054155227,
+           -0.016876283018268573,
+           -1.5928009826931165e-16
+          ],
+          [
+           0,
+           0.01840260258950482,
+           0.038763442130230766,
+           0.06183553250324113,
+           0.08828110629297058,
+           0.1186500741353602,
+           0.15336157074376852,
+           0.19268909294919037,
+           0.23674964210939203,
+           0.28549717954637704,
+           0.33872059188494924,
+           0.39604624611452977,
+           0.456945094844103,
+           0.5207441735892294,
+           0.5866422170284151,
+           0.6537290129112993,
+           0.7210080134471216,
+           0.7874216370700121,
+           0.8518786206931088,
+           0.9132827257996288,
+           0.9705620624497902,
+           1.0226982745453808,
+           1.0687548280632293,
+           1.1079036615413729,
+           1.1394494944928653,
+           1.1628511437755755,
+           1.1777392689542625,
+           1.1839300536268753,
+           1.1814344284467393,
+           1.1704625507276092,
+           1.151423372376172,
+           1.1249192495650853,
+           1.0917356710211175,
+           1.0528263039880514,
+           1.0092936747879648,
+           0.9623659115029942,
+           0.9133700768622675,
+           0.8637027074173913,
+           0.8147982483030081,
+           0.7680961294459271,
+           0.7250072675549688,
+           0.6868807975863525,
+           0.6549718370989644,
+           0.6304110669371304,
+           0.6141768724389958,
+           0.6070707317755876,
+           0.6096964634430512,
+           0.622443855143326,
+           0.645477093459284,
+           0.6787283003463727,
+           0.7218963612749647,
+           0.7744511038128243,
+           0.8356427576059031,
+           0.9045165002163873,
+           0.9799317711992755,
+           1.0605859221272553,
+           1.1450416658143179,
+           1.231757696299616,
+           1.319121774481794,
+           1.4054855145212684,
+           1.4892000647217496,
+           1.5686518545815262,
+           1.6422975776142965,
+           1.708697597435368,
+           1.7665470020592764,
+           1.8147035874481774,
+           1.852212124719221,
+           1.8783243542735253,
+           1.8925142522807687,
+           1.8944882279482862,
+           1.8841900310646216,
+           1.8618002754819338,
+           1.8277306124135269,
+           1.7826127145490724,
+           1.7272823549373453,
+           1.6627589803668432,
+           1.5902212847801078,
+           1.5109793815276762,
+           1.4264442517532752,
+           1.3380952080200796,
+           1.2474461559679513,
+           1.1560114613105639,
+           1.0652722342894099,
+           0.9766438287343145,
+           0.8914453185597498,
+           0.8108716617509956,
+           0.7359691920148429,
+           0.6676149930560367,
+           0.6065006120370731,
+           0.553120459650916,
+           0.5077651271082507,
+           0.4705197281297682,
+           0.44126724977536047,
+           0.4196967727155694,
+           0.4053163024031421,
+           0.39746984047297956,
+           0.39535822334508636,
+           0.39806316493635596,
+           0.40457386480103946,
+           0.4138154837494412,
+           0.4246787474623893,
+           0.4360499158030543,
+           0.44684035193687244,
+           0.4560149410330508,
+           0.462618642785285,
+           0.46580051433379793,
+           0.4648346090296652,
+           0.4591372400788808,
+           0.4482801942955425,
+           0.43199958752687584,
+           0.4102001670835435,
+           0.38295498483051105,
+           0.3505004844704716,
+           0.3132271649525483,
+           0.27166609587364365,
+           0.2264716673342367,
+           0.17840105327820696,
+           0.12829095145560174,
+           0.07703223268218878,
+           0.02554318528238138,
+           -0.0252579238429574,
+           -0.07448023307538162,
+           -0.12128687837987397,
+           -0.16492007844273626,
+           -0.2047240363038572,
+           -0.24016503779188572,
+           -0.27084819967656243,
+           -0.2965304071769807,
+           -0.31712907911544386,
+           -0.33272650708975043,
+           -0.3435696298190607,
+           -0.3500652223958979,
+           -0.35277059954728585,
+           -0.35238004914658283,
+           -0.34970732415208106,
+           -0.34566462503433065,
+           -0.3412385979453426,
+           -0.33746395399864704,
+           -0.3353953800138089,
+           -0.33607845925350643,
+           -0.34052035078594217,
+           -0.34966098733156326,
+           -0.3643455434642956,
+           -0.3852988989780376,
+           -0.4131027767213129,
+           -0.44817617133208015,
+           -0.490759606592746,
+           -0.5409036664934576,
+           -0.5984621408130445,
+           -0.663090012670172,
+           -0.7342463958635578,
+           -0.8112024068732709,
+           -0.8930538331883108,
+           -0.9787383392255071,
+           -1.0670568365151294,
+           -1.1566985389157391,
+           -1.2462691290424992,
+           -1.334321381231195,
+           -1.4193875212627263,
+           -1.500012555400942,
+           -1.5747877722845878,
+           -1.642383611636339,
+           -1.7015811039049398,
+           -1.7513011146494142,
+           -1.7906306760337627,
+           -1.8188457540866412,
+           -1.835429882813846,
+           -1.840088192852092,
+           -1.8327564707886912,
+           -1.8136050029159547,
+           -1.7830370811838145,
+           -1.7416821764413626,
+           -1.690383911613618,
+           -1.6301830921302167,
+           -1.5622961696615736,
+           -1.4880896251207758,
+           -1.4090508552660015,
+           -1.326756231678122,
+           -1.24283706932104,
+           -1.1589442926385318,
+           -1.0767126189535874,
+           -0.9977250910304114,
+           -0.9234787827334573,
+           -0.8553524739611669,
+           -0.7945770441176252,
+           -0.7422092684567383,
+           -0.6991096202738873,
+           -0.6659245861149716,
+           -0.6430738932605331,
+           -0.6307429313566817,
+           -0.6288805260689109,
+           -0.6372020950529949,
+           -0.6551980884783828,
+           -0.6821474909214419,
+           -0.7171360417186464,
+           -0.7590787197403022,
+           -0.8067459387061684,
+           -0.8587928130275868,
+           -0.9137907837987352,
+           -0.9702608416544933,
+           -1.0267075490145758,
+           -1.081653049532109,
+           -1.133670257667454,
+           -1.181414446035322,
+           -1.2236524918628247,
+           -1.2592891054198545,
+           -1.2873894410758453,
+           -1.3071975837354777,
+           -1.3181505074980981,
+           -1.319887216868314,
+           -1.312252900888942,
+           -1.2952980541868615,
+           -1.2692726430499766,
+           -1.2346155162168047,
+           -1.1919393760568753,
+           -1.1420117333928281,
+           -1.0857323657223004,
+           -1.0241078816785343,
+           -0.9582240622015028,
+           -0.889216699443652,
+           -0.818241686701969,
+           -0.7464451259055143,
+           -0.6749342131254057,
+           -0.6047496374247238,
+           -0.5368401848182581,
+           -0.4720401783131831,
+           -0.4110503085283059,
+           -0.35442231920690037,
+           -0.30254791035181317,
+           -0.25565211130873944,
+           -0.21379125970800447,
+           -0.1768556026976962,
+           -0.14457641738429933,
+           -0.11653743086126614,
+           -0.0921902095923181,
+           -0.07087308601396637,
+           -0.051833099597667,
+           -0.03425035254737362,
+           -0.017264118740909922,
+           -1.6483396539325373e-16
+          ],
+          [
+           0,
+           0.019354879975317565,
+           0.041066090044411835,
+           0.06585269020662393,
+           0.09432952365059122,
+           0.1269870360174507,
+           0.1641745274235019,
+           0.20608729759464028,
+           0.2527580435251474,
+           0.3040527587693358,
+           0.3596712665969465,
+           0.41915239875049465,
+           0.48188371048672307,
+           0.5471155040337825,
+           0.6139788195595633,
+           0.681506948098337,
+           0.7486599272886273,
+           0.8143514006267984,
+           0.8774771562954522,
+           0.9369446141543039,
+           0.9917025004261146,
+           1.040769939753802,
+           1.0832642039490832,
+           1.1184263857117482,
+           1.1456443132013021,
+           1.1644720864506561,
+           1.1746456976456126,
+           1.176094292273471,
+           1.1689467347357152,
+           1.1535332575949409,
+           1.13038209532637,
+           1.1002111282517832,
+           1.0639146871464522,
+           1.0225457907184252,
+           0.9772942037251848,
+           0.9294608100217268,
+           0.8804288896510232,
+           0.831632969801533,
+           0.7845259840203573,
+           0.7405455208338418,
+           0.7010799706761368,
+           0.6674353880146248,
+           0.6408038735303583,
+           0.6222342493971131,
+           0.6126057498287311,
+           0.6126053803270993,
+           0.6227095141014077,
+           0.6431701949848599,
+           0.6740065052424733,
+           0.7150012366317677,
+           0.7657029768639844,
+           0.8254335942903146,
+           0.8933009743597059,
+           0.9682167353192138,
+           1.0489185308373088,
+           1.133996436656621,
+           1.2219228197341685,
+           1.3110850040229607,
+           1.3998199791581607,
+           1.4864503485023113,
+           1.56932068250383,
+           1.6468334328853567,
+           1.7174835730667635,
+           1.7798911602072305,
+           1.8328310635955671,
+           1.8752591716275135,
+           1.9063344736382462,
+           1.9254365113588612,
+           1.9321778053347287,
+           1.9264109815844566,
+           1.908230450165969,
+           1.8779686170700867,
+           1.8361867408211647,
+           1.7836606721657198,
+           1.721361836185958,
+           1.6504339281497216,
+           1.5721658946891464,
+           1.4879618580652187,
+           1.3993087112518778,
+           1.3077421636892674,
+           1.2148120505802253,
+           1.1220477317771453,
+           1.0309243993573802,
+           0.9428310861388126,
+           0.8590411213571748,
+           0.7806857156976911,
+           0.7087312774714908,
+           0.6439609669783045,
+           0.5869608893765497,
+           0.5381112103566414,
+           0.4975823564730866,
+           0.4653363361781398,
+           0.441133091533445,
+           0.4245416673743032,
+           0.41495586740409557,
+           0.4116139581906838,
+           0.4136218849843052,
+           0.4199793800490921,
+           0.429608276820407,
+           0.44138229329164114,
+           0.4541575167823593,
+           0.46680281036280874,
+           0.4782293689416144,
+           0.4874186801077593,
+           0.4934481905165111,
+           0.49551404171943103,
+           0.4929503182264965,
+           0.48524434322687215,
+           0.4720476614173333,
+           0.4531824611457229,
+           0.4286433067086907,
+           0.3985941731432449,
+           0.363360897147534,
+           0.3234192757947375,
+           0.27937915648764844,
+           0.23196496432393812,
+           0.18199320411740966,
+           0.13034755145840796,
+           0.07795220845944872,
+           0.02574424368336963,
+           -0.025354338906373074,
+           -0.07446405093069955,
+           -0.12077415255746685,
+           -0.163566961518548,
+           -0.2022395824278214,
+           -0.23632246767846446,
+           -0.26549430339515884,
+           -0.2895928091994297,
+           -0.308621146503938,
+           -0.3227497440034744,
+           -0.33231346809308543,
+           -0.3378041871025872,
+           -0.33985889842178507,
+           -0.33924370375364565,
+           -0.33683402692290254,
+           -0.33359156810665014,
+           -0.3305385755043705,
+           -0.32873008809609705,
+           -0.32922485937899204,
+           -0.3330557103632577,
+           -0.3412000796324536,
+           -0.3545515383869353,
+           -0.37389301903415556,
+           -0.39987246749558036,
+           -0.43298157287433464,
+           -0.4735381548334944,
+           -0.5216727007575993,
+           -0.5773194436730783,
+           -0.6402122604757488,
+           -0.7098855510071992,
+           -0.7856801348841667,
+           -0.8667540777852815,
+           -0.9520982352531082,
+           -1.040556183060102,
+           -1.1308480917904975,
+           -1.2215980022993944,
+           -1.3113638706669355,
+           -1.3986696783947674,
+           -1.4820388477490996,
+           -1.5600281647760816,
+           -1.6312613945841343,
+           -1.6944617755079565,
+           -1.748482600752424,
+           -1.7923351375799252,
+           -1.8252131940887788,
+           -1.8465137207115572,
+           -1.8558529258943535,
+           -1.8530774907761922,
+           -1.8382705835225768,
+           -1.8117524974668295,
+           -1.7740758653731217,
+           -1.7260155318325117,
+           -1.6685532938724599,
+           -1.6028578431715046,
+           -1.5302603588079189,
+           -1.4522263044047703,
+           -1.3703240752925911,
+           -1.2861912176435424,
+           -1.2014990005630393,
+           -1.1179161624042766,
+           -1.0370726731044912,
+           -0.9605243546190035,
+           -0.8897191815352986,
+           -0.8259660441670553,
+           -0.7704066978226235,
+           -0.723991545941736,
+           -0.6874598132502582,
+           -0.6613245602283798,
+           -0.6458628745802855,
+           -0.6411114518525085,
+           -0.6468676488860907,
+           -0.6626959635345933,
+           -0.6879397652078887,
+           -0.7217379764453192,
+           -0.7630462889024551,
+           -0.8106623906861785,
+           -0.863254588468315,
+           -0.9193931295028422,
+           -0.9775834674437608,
+           -1.0363006731660827,
+           -1.0940241686293863,
+           -1.1492719587091216,
+           -1.200633552878016,
+           -1.2468008051779416,
+           -1.2865959561292182,
+           -1.3189962326696887,
+           -1.343154450068307,
+           -1.3584151608097828,
+           -1.364326007169037,
+           -1.3606440537999938,
+           -1.3473370011770391,
+           -1.3245793070592762,
+           -1.2927433681687464,
+           -1.2523860348959235,
+           -1.2042308450959873,
+           -1.1491464661348372,
+           -1.088121924759976,
+           -1.0222392799044087,
+           -0.9526444523526271,
+           -0.8805169658978754,
+           -0.8070393762442409,
+           -0.7333671659785524,
+           -0.6605998664669203,
+           -0.5897541310177323,
+           -0.5217394290705613,
+           -0.4573369599416053,
+           -0.39718229861742543,
+           -0.34175218744365565,
+           -0.291355778819077,
+           -0.24613051794213014,
+           -0.2060427342093986,
+           -0.17089288808239078,
+           -0.1403253001976578,
+           -0.11384207422552688,
+           -0.09082081739056946,
+           -0.07053566536203093,
+           -0.052181033850437826,
+           -0.0348974498281778,
+           -0.017798762569482696,
+           -1.7177933406592033e-16
+          ],
+          [
+           0,
+           0.020456304560240515,
+           0.04365716159622423,
+           0.07027982011487062,
+           0.10088443070505276,
+           0.1358954518937437,
+           0.17558681418955063,
+           0.22007125158027147,
+           0.2692941020427069,
+           0.3230317625261685,
+           0.3808948628252325,
+           0.44233609982832284,
+           0.5066625519325318,
+           0.5730521760394276,
+           0.6405740794735619,
+           0.708212059196756,
+           0.7748908133780587,
+           0.8395041579578054,
+           0.9009445251796581,
+           0.9581329836039103,
+           1.0100490008510097,
+           1.055759171768337,
+           1.0944441558845148,
+           1.125423108438088,
+           1.1481749479822025,
+           1.1623558791549227,
+           1.1678126798218174,
+           1.1645913652195945,
+           1.1529409554081211,
+           1.1333121934627683,
+           1.1063511874072183,
+           1.0728880757785735,
+           1.0339209417717614,
+           0.9905953210071259,
+           0.9441797600983709,
+           0.8960379845531915,
+           0.8475983225629574,
+           0.8003211037026077,
+           0.7556648066203236,
+           0.715051766028623,
+           0.6798342657574465,
+           0.6512618408262549,
+           0.6304505874665481,
+           0.6183552363088178,
+           0.6157446815563523,
+           0.6231815793827761,
+           0.6410065339180684,
+           0.6693272813163834,
+           0.7080131641399111,
+           0.7566950625179644,
+           0.8147708183106174,
+           0.8814160569968271,
+           0.9556001824294583,
+           1.036107195121934,
+           1.1215608684004081,
+           1.2104537114215659,
+           1.301179056303097,
+           1.3920655306944796,
+           1.481413118896594,
+           1.5675299755542595,
+           1.648769136962264,
+           1.7235642766174886,
+           1.7904636737881603,
+           1.848161606023793,
+           1.8955264376739132,
+           1.9316247551329164,
+           1.955740993766942,
+           1.967392109009762,
+           1.9663369623169658,
+           1.9525802186598473,
+           1.9263706829516658,
+           1.8881941350453293,
+           1.8387608535037012,
+           1.7789881440464874,
+           1.7099783063679377,
+           1.6329925800416354,
+           1.5494217038938916,
+           1.460753801278272,
+           1.368540364249062,
+           1.2743611512715576,
+           1.1797888348495091,
+           1.0863542368125254,
+           0.9955129700086491,
+           0.9086142663096011,
+           0.8268727131661957,
+           0.7513435459181402,
+           0.6829020525598437,
+           0.6222275439638894,
+           0.5697922282580892,
+           0.5258552059897522,
+           0.49046167592535866,
+           0.4634473129694495,
+           0.4444476529190378,
+           0.4329121967284894,
+           0.42812283264956424,
+           0.4292160708386307,
+           0.4352084943264871,
+           0.445024754833866,
+           0.4575273836106957,
+           0.47154764767334945,
+           0.48591666144140855,
+           0.4994959632780316,
+           0.5112067857636755,
+           0.5200572871347852,
+           0.525167068170847,
+           0.5257883724340192,
+           0.5213234562590879,
+           0.5113377159922202,
+           0.49556827110858853,
+           0.473927820178,
+           0.4465037091949198,
+           0.413552275444911,
+           0.3754886517201471,
+           0.33287233225432333,
+           0.2863889102852973,
+           0.23682849494076383,
+           0.18506139972003965,
+           0.13201176408995743,
+           0.07862982188918276,
+           0.025863564037886626,
+           -0.025369442362935948,
+           -0.07420932144321427,
+           -0.11987950980893602,
+           -0.1617100421754159,
+           -0.19915787288732403,
+           -0.23182368193358924,
+           -0.259464705386945,
+           -0.2820032334197357,
+           -0.2995305315568641,
+           -0.3123060597752643,
+           -0.3207519864350338,
+           -0.32544311672959286,
+           -0.32709247525944585,
+           -0.3265328964218406,
+           -0.32469508166572897,
+           -0.32258267660318085,
+           -0.3212450010934601,
+           -0.3217481296672079,
+           -0.32514506637416035,
+           -0.33244578609501685,
+           -0.34458792280181677,
+           -0.3624088739150952,
+           -0.3866200590193821,
+           -0.4177840214809298,
+           -0.45629499415555846,
+           -0.5023634670168947,
+           -0.556005197216406,
+           -0.6170349932000728,
+           -0.685065486740391,
+           -0.7595109830118817,
+           -0.8395963522143979,
+           -0.9243707998810552,
+           -1.0127262300472446,
+           -1.1034197989770884,
+           -1.19510015006289,
+           -1.2863367255236813,
+           -1.375651470029239,
+           -1.4615521774095128,
+           -1.542566685815481,
+           -1.61727710026783,
+           -1.6843532151801532,
+           -1.7425843233935505,
+           -1.7909086322287615,
+           -1.828439560273864,
+           -1.8544882598272672,
+           -1.8685817974085526,
+           -1.8704765264296475,
+           -1.8601662995288746,
+           -1.8378852904606149,
+           -1.8041053238279292,
+           -1.7595277422166864,
+           -1.7050699712343549,
+           -1.6418470703750858,
+           -1.5711486784077393,
+           -1.494411873157791,
+           -1.4131905644015819,
+           -1.3291221226870265,
+           -1.2438920141719547,
+           -1.1591972603744167,
+           -1.0767095708543455,
+           -0.9980390055702487,
+           -0.9246990117548348,
+           -0.8580736479108573,
+           -0.799387755723169,
+           -0.749680770572865,
+           -0.7097847746317377,
+           -0.680307295322215,
+           -0.6616192387163334,
+           -0.6538482249769999,
+           -0.6568774642009381,
+           -0.6703501791424683,
+           -0.693679449492064,
+           -0.7260632238607235,
+           -0.7665041235042305,
+           -0.8138335490739941,
+           -0.8667395010338265,
+           -0.9237974382651635,
+           -0.9835034298678585,
+           -1.0443088039100683,
+           -1.104655465098777,
+           -1.1630110417614772,
+           -1.2179030313816677,
+           -1.267951142944899,
+           -1.3118970827619758,
+           -1.3486310969993895,
+           -1.377214667177011,
+           -1.3968988523002677,
+           -1.4071378806390684,
+           -1.4075977127195771,
+           -1.3981594219072409,
+           -1.3789173669315993,
+           -1.3501722586658738,
+           -1.3124193482642126,
+           -1.2663320823007471,
+           -1.212741679932065,
+           -1.1526131846377852,
+           -1.0870186264019268,
+           -1.017107997258841,
+           -0.9440787923280805,
+           -0.8691448986376024,
+           -0.793505624494641,
+           -0.7183156527121858,
+           -0.6446566719367773,
+           -0.5735113924393549,
+           -0.5057405872828036,
+           -0.44206371846161574,
+           -0.3830436125081304,
+           -0.3290755436048803,
+           -0.28038096714178684,
+           -0.23700602583104868,
+           -0.1988248270005363,
+           -0.16554736664977734,
+           -0.13673185637658358,
+           -0.1118010963787705,
+           -0.09006243424718799,
+           -0.07073075779636062,
+           -0.052953893025413125,
+           -0.03583971740050264,
+           -0.01848425552582099,
+           -1.8013499053311108e-16
+          ],
+          [
+           0,
+           0.021705213273331376,
+           0.046529215190566416,
+           0.07509978279390774,
+           0.10791540961847756,
+           0.14532851680387734,
+           0.1875327218744153,
+           0.23455451911555228,
+           0.286249610776895,
+           0.3423040073383463,
+           0.4022398908509021,
+           0.46542611105572973,
+           0.5310930627477723,
+           0.5983515777620492,
+           0.6662153589492167,
+           0.733626389273979,
+           0.799482669124724,
+           0.8626675711210077,
+           0.9220800557975314,
+           0.9766649647323703,
+           1.0254426006991324,
+           1.0675368174868813,
+           1.10220087487485,
+           1.1288403661016742,
+           1.1470325947837179,
+           1.1565418639194711,
+           1.1573302392668068,
+           1.1495634605432488,
+           1.1336117938294394,
+           1.110045744280904,
+           1.0796266766499354,
+           1.0432925189912527,
+           1.0021388490811138,
+           0.9573957804140578,
+           0.9104011722113076,
+           0.8625707829728568,
+           0.8153660673279044,
+           0.770260379245676,
+           0.7287043894359407,
+           0.6920915498265786,
+           0.6617244426708812,
+           0.6387828359294548,
+           0.6242942304186218,
+           0.6191076286480113,
+           0.6238711815946577,
+           0.6390142796387615,
+           0.6647345496832594,
+           0.700990104614788,
+           0.7474972665484775,
+           0.8037338547668803,
+           0.8689479960956711,
+           0.942172282906691,
+           1.0222429752431461,
+           1.107823821872356,
+           1.1974339633707458,
+           1.2894792813739113,
+           1.382286474312725,
+           1.474139073365993,
+           1.5633145646322208,
+           1.6481217558376313,
+           1.7269375189443517,
+           1.7982420539839883,
+           1.8606518539878116,
+           1.9129496051815578,
+           1.9541103293429603,
+           1.9833231646147498,
+           2.0000082849484633,
+           2.003828574194324,
+           1.99469579582703,
+           1.9727711303615698,
+           1.9384600864747554,
+           1.8924019254456983,
+           1.8354538685121444,
+           1.768670479950907,
+           1.6932787321400777,
+           1.6106493598013283,
+           1.5222651966152245,
+           1.4296872563837557,
+           1.3345193712349532,
+           1.2383722298377673,
+           1.1428276685237981,
+           1.049404057404131,
+           0.9595235923429747,
+           0.8744822528245577,
+           0.7954231166267379,
+           0.7233136365423175,
+           0.6589273843199198,
+           0.6028306550340999,
+           0.5553742040299109,
+           0.5166902614311699,
+           0.4866948391076783,
+           0.4650952151845332,
+           0.45140235485175495,
+           0.4449479065066388,
+           0.44490530207573215,
+           0.4503143924162272,
+           0.46010896537590756,
+           0.4731464274162545,
+           0.4882388812760251,
+           0.5041848031166074,
+           0.5198005136043126,
+           0.5339506486064054,
+           0.545576866261083,
+           0.5537240772856714,
+           0.5575635531985543,
+           0.5564123508947888,
+           0.5497485895845906,
+           0.5372222249873766,
+           0.5186610831034009,
+           0.49407203888212353,
+           0.46363735055882505,
+           0.42770628516962267,
+           0.38678229163332206,
+           0.34150609176152,
+           0.29263516375817006,
+           0.2410201845778673,
+           0.18757907462414297,
+           0.13326934875261395,
+           0.07905951988675029,
+           0.02590032470164425,
+           -0.025303455787126,
+           -0.07371982434905257,
+           -0.11861432386608414,
+           -0.15937205571208057,
+           -0.19551636551038995,
+           -0.2267236883710791,
+           -0.25283414558533346,
+           -0.27385759520132025,
+           -0.28997495712625754,
+           -0.3015347563991096,
+           -0.3090449529406668,
+           -0.3131602492518502,
+           -0.31466518607109367,
+           -0.3144534469051671,
+           -0.3135038927912051,
+           -0.3128539360673888,
+           -0.3135709340861165,
+           -0.31672233883779927,
+           -0.3233453749342194,
+           -0.33441703536010553,
+           -0.3508251813610803,
+           -0.37334150981726305,
+           -0.4025971089775203,
+           -0.4390612625111757,
+           -0.48302408394740454,
+           -0.5345834706207957,
+           -0.5936367605088153,
+           -0.6598773594413933,
+           -0.7327964829531357,
+           -0.8116900295913304,
+           -0.8956704739579671,
+           -0.9836835413550893,
+           -1.0745293047781157,
+           -1.166887232195233,
+           -1.2593446103965729,
+           -1.3504276837579337,
+           -1.4386347742692756,
+           -1.522470594965755,
+           -1.6004809338706745,
+           -1.6712868706441955,
+           -1.7336176937627485,
+           -1.7863417121575018,
+           -1.828494201236233,
+           -1.8593017880285154,
+           -1.8782026622898116,
+           -1.8848620978074737,
+           -1.8791828785206406,
+           -1.8613103447234047,
+           -1.8316319026351071,
+           -1.7907709728759893,
+           -1.7395754866544888,
+           -1.6791011694982676,
+           -1.6105899779393247,
+           -1.5354441716184202,
+           -1.4551966089358037,
+           -1.3714779460496298,
+           -1.2859814944578174,
+           -1.2004265497360156,
+           -1.1165210418290565,
+           -1.0359243746679758,
+           -0.9602113193719716,
+           -0.8908378009686461,
+           -0.8291093740098913,
+           -0.7761531187543375,
+           -0.7328936082776465,
+           -0.7000334999384923,
+           -0.6780391944312313,
+           -0.6671318848812385,
+           -0.6672841900284165,
+           -0.6782224326268314,
+           -0.6994344900006897,
+           -0.7301830115044483,
+           -0.7695236706519515,
+           -0.8163280009894827,
+           -0.8693102572677057,
+           -0.927057649717614,
+           -0.9880632215149561,
+           -1.0507605796893504,
+           -1.11355964921954,
+           -1.174882599800159,
+           -1.2331990952137868,
+           -1.2870600363316507,
+           -1.335129009925896,
+           -1.376210715642414,
+           -1.4092757211265854,
+           -1.4334809884579065,
+           -1.4481857213981113,
+           -1.4529621998355509,
+           -1.4476013923063347,
+           -1.4321132664984453,
+           -1.4067218480019357,
+           -1.371855206034098,
+           -1.328130668274245,
+           -1.276335682253057,
+           -1.2174048451274941,
+           -1.1523937145833265,
+           -1.082450088832704,
+           -1.0087835013978688,
+           -0.9326337152172274,
+           -0.8552390196728193,
+           -0.7778051330089174,
+           -0.7014754913847586,
+           -0.6273036650757102,
+           -0.5562285831871803,
+           -0.48905317221299177,
+           -0.42642692281208566,
+           -0.36883279562104754,
+           -0.3165787634029812,
+           -0.2697941662377515,
+           -0.22843093183969204,
+           -0.19226958759697846,
+           -0.16092986772979934,
+           -0.1338856011677179,
+           -0.11048345631587415,
+           -0.08996502056676282,
+           -0.0714916076884074,
+           -0.05417111720573247,
+           -0.0370862183176295,
+           -0.01932309804499445,
+           -1.899048771147814e-16
+          ],
+          [
+           0,
+           0.023098311882311554,
+           0.0496715982673261,
+           0.08029078354581906,
+           0.11538615866212096,
+           0.15523260264843092,
+           0.19993913324214144,
+           0.24944307983183284,
+           0.30350905165611647,
+           0.3617327492567243,
+           0.42354954082961255,
+           0.4882476005301835,
+           0.5549852861337717,
+           0.6228123217717987,
+           0.6906942506013012,
+           0.7575395347957803,
+           0.8222286084096507,
+           0.8836441343180382,
+           0.9407016809824799,
+           0.9923800191828012,
+           1.0377502435309147,
+           1.0760029484799682,
+           1.1064727330912225,
+           1.1286593719566254,
+           1.1422450698647686,
+           1.147107313079335,
+           1.1433269381279327,
+           1.1311911571075415,
+           1.1111914037750126,
+           1.0840159939965548,
+           1.0505377242604432,
+           1.0117966596659707,
+           0.9689784848955595,
+           0.9233889050951163,
+           0.8764246854780156,
+           0.8295420062584564,
+           0.7842228809827437,
+           0.7419404396345606,
+           0.7041239116613727,
+           0.6721241574032438,
+           0.6471805889065027,
+           0.630390292891332,
+           0.6226801203454909,
+           0.6247824399645574,
+           0.6372151680513113,
+           0.6602665875534228,
+           0.6939853560717049,
+           0.7381759796456054,
+           0.7923998989086759,
+           0.8559821999767636,
+           0.9280238274617827,
+           1.0074190445933942,
+           1.0928777588210175,
+           1.1829522135620416,
+           1.2760674408473756,
+           1.3705547780945382,
+           1.464687677363118,
+           1.5567189790633753,
+           1.6449187855898906,
+           1.727612054646153,
+           1.803215037511664,
+           1.8702697140604034,
+           1.927475423332402,
+           1.9737169547520135,
+           2.00808844906814,
+           2.0299125577208756,
+           2.0387544221907,
+           2.0344301582122055,
+           2.0170096605306487,
+           1.9868136789610022,
+           1.9444052525871527,
+           1.8905757227026556,
+           1.8263256732924964,
+           1.7528412673751674,
+           1.671466555469435,
+           1.5836724262103998,
+           1.4910229464558973,
+           1.3951398972439413,
+           1.297666351283376,
+           1.200230156367128,
+           1.1044081867822582,
+           1.0116922015618839,
+           0.9234571049039825,
+           0.8409323413912175,
+           0.7651770783746683,
+           0.6970597320524381,
+           0.6372422847808314,
+           0.5861697217199483,
+           0.5440647880076209,
+           0.5109281364245709,
+           0.4865438032079066,
+           0.47048981955775737,
+           0.4621536416693007,
+           0.46075196587518935,
+           0.46535439055016753,
+           0.4749102953722536,
+           0.4882782335648455,
+           0.5042570756685772,
+           0.5216181055689519,
+           0.5391372518122747,
+           0.5556266400515524,
+           0.569964675637985,
+           0.581123908267125,
+           0.5881959920659517,
+           0.5904131329708052,
+           0.5871655086778101,
+           0.5780142524587666,
+           0.5626997080276303,
+           0.541144785474702,
+           0.513453374947717,
+           0.4799039020507382,
+           0.44093823364186996,
+           0.3971462616976903,
+           0.3492466031825221,
+           0.2980639526434735,
+           0.24450370906892707,
+           0.1895245672741185,
+           0.1341098149944347,
+           0.07923810870682625,
+           0.025854513174857117,
+           -0.025157418463252465,
+           -0.0730017753505924,
+           -0.11699392891234037,
+           -0.1565810461165323,
+           -0.1913589215650138,
+           -0.2210846699085013,
+           -0.24568492784041931,
+           -0.26525933179136146,
+           -0.2800791604585384,
+           -0.29058115734493234,
+           -0.29735667435550095,
+           -0.30113640000880226,
+           -0.3027710518599638,
+           -0.3032085193430954,
+           -0.3034680377100429,
+           -0.3046120536522829,
+           -0.307716506491098,
+           -0.3138402938702031,
+           -0.32399471650302886,
+           -0.339113702018483,
+           -0.3600255931228779,
+           -0.3874272504699709,
+           -0.4218611666260286,
+           -0.46369621563503277,
+           -0.5131125746834732,
+           -0.5700912523946683,
+           -0.6344085448631681,
+           -0.7056356184757783,
+           -0.7831432908849346,
+           -0.8661119513766412,
+           -0.9535464325517125,
+           -1.0442955199454018,
+           -1.1370756680835905,
+           -1.230498383479324,
+           -1.3231006399322045,
+           -1.4133776116123278,
+           -1.4998169468243736,
+           -1.5809337616652062,
+           -1.6553055091549331,
+           -1.7216058764867046,
+           -1.778636880944262,
+           -1.8253583734022725,
+           -1.8609142162706727,
+           -1.8846544789024702,
+           -1.8961530860344766,
+           -1.89522046154444,
+           -1.8819108281042793,
+           -1.8565239503164472,
+           -1.81960124154784,
+           -1.7719162896891452,
+           -1.7144599911689204,
+           -1.648420612460912,
+           -1.575159220858162,
+           -1.496181038443335,
+           -1.4131033722081032,
+           -1.3276208567303074,
+           -1.2414688116514743,
+           -1.1563855627838373,
+           -1.0740746018611083,
+           -0.9961674650755663,
+           -0.9241881944756716,
+           -0.8595202094127241,
+           -0.8033763584108181,
+           -0.7567728464691152,
+           -0.7205076407199781,
+           -0.6951438508019786,
+           -0.6809984618574507,
+           -0.678136670615192,
+           -0.6863719416742184,
+           -0.705271765111039,
+           -0.7341689612006348,
+           -0.772178246661443,
+           -0.8182176525990216,
+           -0.8710342702454199,
+           -0.9292336994335716,
+           -0.9913124889500904,
+           -1.0556927895380177,
+           -1.1207583910056649,
+           -1.1848912858007508,
+           -1.2465078931948361,
+           -1.3040940910416419,
+           -1.3562382355575633,
+           -1.4016614028488918,
+           -1.4392441576185044,
+           -1.4680492428144745,
+           -1.487339686717552,
+           -1.4965919385367163,
+           -1.4955037671387539,
+           -1.4839967870094346,
+           -1.4622136077219905,
+           -1.4305097348046107,
+           -1.389440477705451,
+           -1.33974324140531,
+           -1.2823156891585825,
+           -1.2181903621385486,
+           -1.1485064250294998,
+           -1.0744792728301937,
+           -0.9973687817229685,
+           -0.9184470146998165,
+           -0.8389662000941388,
+           -0.7601277881264339,
+           -0.6830533574269393,
+           -0.608758091141755,
+           -0.5381274720316436,
+           -0.4718977597487167,
+           -0.41064071343541486,
+           -0.35475291148466087,
+           -0.30444990055823695,
+           -0.2597652808173836,
+           -0.22055470694040435,
+           -0.1865046581023522,
+           -0.15714570785838558,
+           -0.13186990988200903,
+           -0.10995181065347763,
+           -0.09057250810489222,
+           -0.07284609821603578,
+           -0.05584779154607741,
+           -0.038642940178910165,
+           -0.020316193585118176,
+           -2.0107776575631545e-16
+          ],
+          [
+           0,
+           0.024630679548970996,
+           0.053070500851106664,
+           0.08582651792757452,
+           0.12325476965804633,
+           0.16554770301340427,
+           0.21272616481307727,
+           0.26463619019787155,
+           0.3209506910056294,
+           0.38117601941677376,
+           0.4446632548414754,
+           0.5106239382830718,
+           0.5781498614771311,
+           0.6462364109475153,
+           0.7138088724721653,
+           0.7797510217326646,
+           0.8429352641809282,
+           0.9022535430173847,
+           0.9566482097963821,
+           1.0051420482201123,
+           1.0468666583042363,
+           1.0810884449324636,
+           1.1072315109918285,
+           1.1248968294370256,
+           1.1338771589594003,
+           1.1341672722140825,
+           1.1259691812135457,
+           1.1096921686640104,
+           1.085947563620031,
+           1.0555383316373412,
+           1.0194436803274982,
+           0.9787990075923525,
+           0.9348716386752186,
+           0.889032906521954,
+           0.8427272250665878,
+           0.7974388845328623,
+           0.7546573596486327,
+           0.7158419642116536,
+           0.6823867076046477,
+           0.6555862100187541,
+           0.6366035132103914,
+           0.62644058301192,
+           0.625912239477955,
+           0.6356241719030531,
+           0.655955600874092,
+           0.6870470403122123,
+           0.7287934917580291,
+           0.7808432738912311,
+           0.8426025555990428,
+           0.9132455241032321,
+           0.991729984065933,
+           1.0768180525391877,
+           1.1671014913139128,
+           1.2610311056867902,
+           1.3569495396639695,
+           1.4531267145944606,
+           1.5477970932207588,
+           1.6391979057565504,
+           1.7256074499784497,
+           1.8053825740700056,
+           1.876994469177862,
+           1.9390619379022376,
+           1.9903813643017723,
+           2.029952689008932,
+           2.0570007878322287,
+           2.0709917614608426,
+           2.071643764927331,
+           2.058932135378243,
+           2.03308871228808,
+           1.9945953822286357,
+           1.944172017316044,
+           1.8827591091705076,
+           1.8114955254150409,
+           1.7316919303730902,
+           1.6448005129257213,
+           1.5523817500120092,
+           1.456069001945891,
+           1.3575317839636034,
+           1.2584385860717833,
+           1.1604201197081816,
+           1.065033854847472,
+           0.9737306754002839,
+           0.8878244249944094,
+           0.8084650409121488,
+           0.736615882960387,
+           0.6730357586505678,
+           0.6182660288948071,
+           0.5726230523975321,
+           0.5361960951667708,
+           0.5088506973482985,
+           0.4902373562152354,
+           0.4798052549134404,
+           0.4768206446472016,
+           0.48038937638012985,
+           0.4894829795504508,
+           0.5029676021563823,
+           0.5196350608658505,
+           0.5382352031176614,
+           0.5575087566044573,
+           0.5762198356550433,
+           0.5931872889417056,
+           0.6073141081862913,
+           0.6176141721802084,
+           0.6232356730395224,
+           0.6234806603130945,
+           0.6178202410768809,
+           0.6059050878682144,
+           0.5875710283515116,
+           0.5628396178701984,
+           0.5319137253118803,
+           0.49516829073325314,
+           0.45313653673277976,
+           0.4064920315148209,
+           0.3560271070456505,
+           0.30262822801394684,
+           0.24724898416382954,
+           0.19088143804645358,
+           0.13452660085441,
+           0.07916482975574171,
+           0.02572694052575634,
+           -0.024933190707152632,
+           -0.07206380260999075,
+           -0.11503752534322984,
+           -0.1533701594386795,
+           -0.18673544885975127,
+           -0.21497544469775906,
+           -0.23810617083902125,
+           -0.2563184253366899,
+           -0.26997367803578926,
+           -0.27959515301440924,
+           -0.285854310370782,
+           -0.28955306260650276,
+           -0.2916021732613393,
+           -0.2929963866821615,
+           -0.29478692527292555,
+           -0.29805206203312945,
+           -0.3038665298069174,
+           -0.31327056303850664,
+           -0.32723938204762965,
+           -0.3466539234919123,
+           -0.37227359387780923,
+           -0.4047117763376962,
+           -0.44441475552643267,
+           -0.4916446429959574,
+           -0.5464667878032441,
+           -0.6087420467994991,
+           -0.6781241687640628,
+           -0.754062419267161,
+           -0.8358094420353972,
+           -0.9224342209184963,
+           -1.0128398776032488,
+           -1.1057859172179527,
+           -1.19991442000434,
+           -1.293779575172653,
+           -1.3858798654783524,
+           -1.4746921401909046,
+           -1.5587067617818973,
+           -1.6364629792006535,
+           -1.7065836689010807,
+           -1.7678085941909205,
+           -1.8190253638299578,
+           -1.859297321424164,
+           -1.8878876668633464,
+           -1.904279198171629,
+           -1.9081891645907871,
+           -1.8995788370219122,
+           -1.8786575273149897,
+           -1.8458809202701174,
+           -1.8019437183716578,
+           -1.7477667358926525,
+           -1.6844787127398642,
+           -1.613393245984404,
+           -1.5359813553104025,
+           -1.4538403047096802,
+           -1.368659394045534,
+           -1.2821835083542645,
+           -1.1961752681170439,
+           -1.1123766588452586,
+           -1.032471032303849,
+           -0.9580463641903986,
+           -0.8905606242600576,
+           -0.8313100654274219,
+           -0.7814011694807943,
+           -0.7417269003833057,
+           -0.7129478138145122,
+           -0.6954784561151733,
+           -0.6894793599477805,
+           -0.694854810840366,
+           -0.7112564215826044,
+           -0.7380924135304323,
+           -0.7745423686029751,
+           -0.8195770864111266,
+           -0.8719830606804319,
+           -0.9303909808365378,
+           -0.9933075709276915,
+           -1.059150001222574,
+           -1.1262820496843169,
+           -1.1930511524629646,
+           -1.2578254654540562,
+           -1.3190300632098553,
+           -1.3751814269067175,
+           -1.4249194189920353,
+           -1.467036007378565,
+           -1.5005000849714472,
+           -1.5244778288206149,
+           -1.5383481548252693,
+           -1.5417129458958796,
+           -1.5344018607721115,
+           -1.5164716640967162,
+           -1.4882001525563802,
+           -1.4500748836084356,
+           -1.4027770392741925,
+           -1.3471608746017816,
+           -1.284229305816427,
+           -1.2151062843128608,
+           -1.1410066772923964,
+           -1.0632044322094638,
+           -0.9829998389308359,
+           -0.9016867197779469,
+           -0.8205203730826987,
+           -0.7406870707221676,
+           -0.6632758650040212,
+           -0.5892533964438088,
+           -0.5194423130636926,
+           -0.4545038159298887,
+           -0.3949247371828482,
+           -0.3410094385599281,
+           -0.2928766933638962,
+           -0.25046158615624975,
+           -0.21352233540143448,
+           -0.181651818110003,
+           -0.15429345540233025,
+           -0.13076100685938954,
+           -0.11026172233153342,
+           -0.09192221502669708,
+           -0.0748163513192347,
+           -0.05799440251635462,
+           -0.04051267303890915,
+           -0.02146280887520191,
+           -2.1362709262396706e-16
+          ],
+          [
+           0,
+           0.026295791157511326,
+           0.05670904423297732,
+           0.09167636842672015,
+           0.13147407038648493,
+           0.1762079537363035,
+           0.22580789144775812,
+           0.2800273303420706,
+           0.33844775833771823,
+           0.40048803542653844,
+           0.4654183620609731,
+           0.5323785368992467,
+           0.6004000427792597,
+           0.6684313982560652,
+           0.7353661246346147,
+           0.8000726073990124,
+           0.8614250781126758,
+           0.9183349096161506,
+           0.9697814045663312,
+           1.0148412654150847,
+           1.0527159626667966,
+           1.0827562670135882,
+           1.1044832785510454,
+           1.1176053710787395,
+           1.1220305694069688,
+           1.1178739901597938,
+           1.105460098998568,
+           1.0853196664513367,
+           1.0581814374059573,
+           1.0249586624956297,
+           0.986730769747039,
+           0.9447205787136307,
+           0.9002675737692857,
+           0.8547978554072091,
+           0.8097914756905933,
+           0.7667479342145427,
+           0.7271506622613944,
+           0.6924313539269578,
+           0.6639350130253528,
+           0.6428865732269238,
+           0.6303599163581427,
+           0.6272500608296862,
+           0.6342492200012482,
+           0.6518273406582029,
+           0.6802176268201322,
+           0.7194074363608908,
+           0.7691348102508938,
+           0.8288907597411371,
+           0.8979272987750664,
+           0.9752710707115106,
+           1.059742283451695,
+           1.1499785385942234,
+           1.2444630214468368,
+           1.3415564125219044,
+           1.4395317901481772,
+           1.5366117202877698,
+           1.6310066753726287,
+           1.720953890316088,
+           1.8047557516553372,
+           1.8808168253573956,
+           1.947678659958917,
+           2.004051553664937,
+           2.048842545549743,
+           2.08117898035118,
+           2.1004271013579943,
+           2.1062052440049697,
+           2.0983913311387536,
+           2.077124506374471,
+           2.0428008812328438,
+           1.9960635114406324,
+           1.9377868544967332,
+           1.8690560910297873,
+           1.791141813435342,
+           1.7054706938503674,
+           1.613592837075855,
+           1.5171466003406084,
+           1.417821718983745,
+           1.3173216138628583,
+           1.2173257717162467,
+           1.1194530834920051,
+           1.0252269980071882,
+           0.9360432999455047,
+           0.8531412533791941,
+           0.7775787664228837,
+           0.7102121314414821,
+           0.6516807809676138,
+           0.6023973749810498,
+           0.562543403553986,
+           0.5320703533323565,
+           0.5107063502543868,
+           0.49796805765857305,
+           0.4931774817826518,
+           0.4954832187229724,
+           0.5038855710948399,
+           0.5172648714872843,
+           0.5344122755488474,
+           0.5540622319587563,
+           0.5749258009469036,
+           0.5957239782431244,
+           0.6152201876590594,
+           0.6322511327058143,
+           0.6457552449799305,
+           0.6547980332608628,
+           0.6585937206388829,
+           0.6565226553920206,
+           0.6481440922420171,
+           0.6332040612225567,
+           0.6116381686310953,
+           0.5835693051910307,
+           0.5493003673262926,
+           0.5093022250508417,
+           0.4641972911909655,
+           0.4147391584436516,
+           0.36178887032577195,
+           0.3062884768932515,
+           0.2492325940868661,
+           0.19163873499788286,
+           0.1345172110162018,
+           0.07884140999855395,
+           0.025519247063354587,
+           -0.024633448307747805,
+           -0.07091689667985832,
+           -0.11276804215830988,
+           -0.14977737877049813,
+           -0.18170147406214235,
+           -0.20847084649234432,
+           -0.23019297435998126,
+           -0.24715034096007787,
+           -0.2597935502331243,
+           -0.26872967604598375,
+           -0.27470613315863907,
+           -0.2785904757123277,
+           -0.28134663672438975,
+           -0.2840082168483531,
+           -0.2876495101303811,
+           -0.2933550166234282,
+           -0.30218823489988067,
+           -0.3151605505980252,
+           -0.33320103951629865,
+           -0.35712798532019024,
+           -0.38762287306088966,
+           -0.42520756134631504,
+           -0.4702252595685258,
+           -0.5228258439471217,
+           -0.5829559395759928,
+           -0.6503540777939818,
+           -0.7245511119600965,
+           -0.804875943237386,
+           -0.8904664745514626,
+           -0.9802855788201273,
+           -1.0731417401540986,
+           -1.1677139072003315,
+           -1.2625799891453349,
+           -1.356248329858936,
+           -1.4471914166494777,
+           -1.5338810191369903,
+           -1.6148239124058825,
+           -1.6885973179636473,
+           -1.7538831966875006,
+           -1.809500549940089,
+           -1.8544349279043046,
+           -1.8878644069337924,
+           -1.9091813788550906,
+           -1.9180095927466823,
+           -1.9142160014070964,
+           -1.897917087803912,
+           -1.8694794782771427,
+           -1.8295147859511154,
+           -1.7788687663517948,
+           -1.7186050042438223,
+           -1.6499834828374704,
+           -1.5744345105297286,
+           -1.4935285931903306,
+           -1.4089429389071373,
+           -1.3224253646301947,
+           -1.2357564382620632,
+           -1.1507107338469955,
+           -1.0690181005142176,
+           -0.9923258471491292,
+           -0.9221627243494072,
+           -0.8599055435519194,
+           -0.8067492112930862,
+           -0.7636808758876866,
+           -0.731458786337136,
+           -0.7105963513762436,
+           -0.7013517629599886,
+           -0.7037234161866155,
+           -0.717451219870815,
+           -0.7420237520739403,
+           -0.7766910762706483,
+           -0.8204828998530728,
+           -0.8722316305986615,
+           -0.9305997716136342,
+           -0.9941109938969719,
+           -1.0611841404966293,
+           -1.13016934929692,
+           -1.19938543438091,
+           -1.267157639762685,
+           -1.3318548746740773,
+           -1.3919255565822093,
+           -1.4459312262403332,
+           -1.4925771573491515,
+           -1.5307392603490702,
+           -1.5594866735396455,
+           -1.5780995427865814,
+           -1.5860816108345837,
+           -1.5831673657195835,
+           -1.5693236317805916,
+           -1.5447456229942815,
+           -1.5098476134314527,
+           -1.4652485102366035,
+           -1.4117527374507846,
+           -1.3503269512218683,
+           -1.2820732057354445,
+           -1.208199272152644,
+           -1.129986877955869,
+           -1.0487586798244166,
+           -0.9658448084192628,
+           -0.8825498276909843,
+           -0.8001209345026451,
+           -0.7197181869697611,
+           -0.6423874929636754,
+           -0.5690370151896819,
+           -0.500417558071488,
+           -0.4371073966836991,
+           -0.3795018918478079,
+           -0.32780811119288045,
+           -0.28204454662648826,
+           -0.24204588753233985,
+           -0.20747267941502032,
+           -0.1778255729116997,
+           -0.15246375122325395,
+           -0.13062701801634796,
+           -0.11146093537062385,
+           -0.09404432470479814,
+           -0.07741838472527025,
+           -0.060616640765256115,
+           -0.04269492040144216,
+           -0.022760551419523524,
+           -2.275109573175121e-16
+          ],
+          [
+           0,
+           0.02808555736260695,
+           0.060567404190281185,
+           0.0978056506880359,
+           0.13999202890289034,
+           0.1871422243193449,
+           0.2390931466326732,
+           0.2955052268143841,
+           0.35586969631291776,
+           0.41952067391995534,
+           0.48565175978720887,
+           0.5533367175035888,
+           0.6215537170559556,
+           0.689212516654699,
+           0.75518388223398,
+           0.8183304819698924,
+           0.8775384509894347,
+           0.931748799677357,
+           0.9799878382236472,
+           1.0213958103619578,
+           1.0552529701698707,
+           1.081002396358619,
+           1.0982689172014812,
+           1.1068736142071138,
+           1.1068434814966137,
+           1.0984159378985627,
+           1.0820380170561565,
+           1.058360194154415,
+           1.0282249429002182,
+           0.9926502497503806,
+           0.9528084407440199,
+           0.9100007964329797,
+           0.8656285392936273,
+           0.8211608728935634,
+           0.7781008305682757,
+           0.7379497514284167,
+           0.7021712416141408,
+           0.6721554977765088,
+           0.6491848672547429,
+           0.6344014953225586,
+           0.6287778647221651,
+           0.6330909675381662,
+           0.6479007658300724,
+           0.6735334973454324,
+           0.7100702684904026,
+           0.7573412513068959,
+           0.8149256675448789,
+           0.882157604282872,
+           0.9581375653255979,
+           1.0417495242260728,
+           1.1316831116315003,
+           1.226460445005776,
+           1.3244669956998614,
+           1.4239857896079005,
+           1.5232341556968219,
+           1.6204021735555225,
+           1.713691928343081,
+           1.8013566601919282,
+           1.881738895784923,
+           1.9533066724799226,
+           2.0146870094679605,
+           2.064695844962061,
+           2.102363741763617,
+           2.126956763721013,
+           2.137992040147784,
+           2.135247661419702,
+           2.118766683652941,
+           2.088855160301616,
+           2.0460742602979485,
+           1.991226672543498,
+           1.9253376317379665,
+           1.8496310274203114,
+           1.7655011736183066,
+           1.674480917861246,
+           1.5782068530599551,
+           1.4783824618621348,
+           1.3767400689723304,
+           1.2750025015053286,
+           1.174845360164729,
+           1.0778607848869144,
+           0.9855235580843258,
+           0.8991603278037201,
+           0.8199226535259857,
+           0.7487644809732567,
+           0.6864245415652088,
+           0.6334140498368611,
+           0.590009941232821,
+           0.5562537564706029,
+           0.5319561404856864,
+           0.516706787242029,
+           0.5098895297788747,
+           0.5107021510067179,
+           0.5181803779943355,
+           0.5312254235557843,
+           0.5486343562529338,
+           0.5691325154691242,
+           0.5914071435196304,
+           0.614141382887041,
+           0.6360477841271076,
+           0.6559004887742365,
+           0.6725652911456114,
+           0.685026842242873,
+           0.6924123364345104,
+           0.6940111152746045,
+           0.689289730278435,
+           0.6779021249969255,
+           0.6596947233035576,
+           0.634706342226774,
+           0.6031629806104112,
+           0.5654676660140485,
+           0.5221856682754286,
+           0.4740255058828668,
+           0.42181627779409736,
+           0.3664819459228878,
+           0.30901326988218353,
+           0.25043815381908824,
+           0.19179120385702533,
+           0.1340833128215977,
+           0.07827208613410537,
+           0.025233899102957244,
+           -0.02426166805379025,
+           -0.06957433413433346,
+           -0.11021195702731613,
+           -0.14584520311261207,
+           -0.1763176481653024,
+           -0.20165103119110336,
+           -0.22204550910122106,
+           -0.23787489063429915,
+           -0.24967695914213575,
+           -0.25813912244393594,
+           -0.2640797506548908,
+           -0.2684256765884248,
+           -0.27218643512134283,
+           -0.27642590519805516,
+           -0.2822320886968868,
+           -0.29068581236970575,
+           -0.30282917114149177,
+           -0.319634542363688,
+           -0.34197499081940824,
+           -0.37059685357464067,
+           -0.4060952428774707,
+           -0.448893135454968,
+           -0.49922462945026497,
+           -0.557122848021902,
+           -0.6224128538177585,
+           -0.6947098139811917,
+           -0.7734225241415729,
+           -0.8577622652518706,
+           -0.9467568325213535,
+           -1.0392694444180326,
+           -1.1340221150744194,
+           -1.229622958554376,
+           -1.3245967912253092,
+           -1.4174183115172418,
+           -1.5065470668535679,
+           -1.5904633672937207,
+           -1.6677042757481404,
+           -1.7368987963154234,
+           -1.7968013956279134,
+           -1.846323026816299,
+           -1.8845588810275866,
+           -1.9108121660540447,
+           -1.9246133037738875,
+           -1.9257340455512437,
+           -1.914196124895105,
+           -1.8902741966177388,
+           -1.8544929482988395,
+           -1.8076184097202201,
+           -1.7506436256676432,
+           -1.6847689936799817,
+           -1.6113776976212433,
+           -1.5320067871828316,
+           -1.448314559659203,
+           -1.3620449909623988,
+           -1.2749900356132162,
+           -1.1889506685667863,
+           -1.1056975738773922,
+           -1.0269323955726373,
+           -0.9542504544157313,
+           -0.8891058007516879,
+           -0.8327794191577068,
+           -0.7863513264634981,
+           -0.7506772126693598,
+           -0.7263701666027738,
+           -0.7137879074348668,
+           -0.7130258123629252,
+           -0.7239158930367694,
+           -0.7460317320165943,
+           -0.7786992491349638,
+           -0.8210130295346421,
+           -0.8718578137220615,
+           -0.9299346284033353,
+           -0.9937909281012302,
+           -1.0618540242166077,
+           -1.1324670025450039,
+           -1.2039262741002827,
+           -1.2745198687648835,
+           -1.3425655675997092,
+           -1.4064479778930614,
+           -1.4646536849557261,
+           -1.515803665494346,
+           -1.5586822178218789,
+           -1.5922617524162233,
+           -1.6157228902053795,
+           -1.6284694328487022,
+           -1.6301378962922386,
+           -1.6206014328515272,
+           -1.59996810470245,
+           -1.5685736095409912,
+           -1.5269686939088694,
+           -1.4759016179616822,
+           -1.416296154134305,
+           -1.3492257083342087,
+           -1.2758842433830817,
+           -1.1975547582258397,
+           -1.115576131163406,
+           -1.031309169748141,
+           -0.9461027232234619,
+           -0.861260705234548,
+           -0.7780108452605735,
+           -0.6974759376209045,
+           -0.6206482882935481,
+           -0.5483679739304426,
+           -0.4813054265634263,
+           -0.41994874414142913,
+           -0.3645960041031583,
+           -0.31535272778499407,
+           -0.27213451086085083,
+           -0.23467470255403752,
+           -0.2025368873857242,
+           -0.1751318009725678,
+           -0.15173819892631268,
+           -0.1315270980589015,
+           -0.1135887243558696,
+           -0.09696143466361795,
+           -0.08066183042247906,
+           -0.06371525326987149,
+           -0.045185844632141654,
+           -0.024205364691567546,
+           -2.42672288485038e-16
+          ],
+          [
+           0,
+           0.029990382108294744,
+           0.06462296776515718,
+           0.10417590712613148,
+           0.1487522160016776,
+           0.1982747744748158,
+           0.25248639051908434,
+           0.31095494090701703,
+           0.37308346895420014,
+           0.43812498881474315,
+           0.5052016224288615,
+           0.5733275809661309,
+           0.6414354006195246,
+           0.7084047554900593,
+           0.7730931002924544,
+           0.834367344513451,
+           0.8911357287976587,
+           0.9423790645450545,
+           0.98718050927533,
+           1.0247530830066467,
+           1.054464183938725,
+           1.0758564338391583,
+           1.0886642729434108,
+           1.0928258286920587,
+           1.0884896996596711,
+           1.0760164226760354,
+           1.0559745242531127,
+           1.0291311936930012,
+           0.9964377512599724,
+           0.9590102171490766,
+           0.9181054123542522,
+           0.8750931377761941,
+           0.8314250801056008,
+           0.7886011795800826,
+           0.7481342634351171,
+           0.7115137979815502,
+           0.6801696404580005,
+           0.6554366783553631,
+           0.638521228557586,
+           0.6304700316951816,
+           0.632142619408359,
+           0.6441877551232713,
+           0.6670245542982893,
+           0.7008287801755306,
+           0.7455246885360803,
+           0.8007826627818962,
+           0.8660227420731201,
+           0.940424003620355,
+           1.022939619032006,
+           1.112317267306932,
+           1.2071244570121153,
+           1.3057781905901609,
+           1.4065782975462766,
+           1.5077436730875005,
+           1.607450586857399,
+           1.7038721745105396,
+           1.7952181942968544,
+           1.8797741223489228,
+           1.9559386742164675,
+           2.0222588760563656,
+           2.0774618659080732,
+           2.120482682289819,
+           2.1504873920815446,
+           2.166891020018271,
+           2.1693698654213645,
+           2.157867925047199,
+           2.1325972808916887,
+           2.0940324550504443,
+           2.0428988768134415,
+           1.9801557465915078,
+           1.9069737136428164,
+           1.824707906678457,
+           1.734866965318849,
+           1.6390788134149081,
+           1.539053990198382,
+           1.4365474102892646,
+           1.3333194574588658,
+           1.231097328940745,
+           1.1315375367541696,
+           1.03619044025773,
+           0.9464676308237716,
+           0.8636129164730739,
+           0.7886775633724755,
+           0.7225003445504866,
+           0.6656928266824352,
+           0.6186301963059108,
+           0.5814477905580197,
+           0.5540433578476534,
+           0.536084934234816,
+           0.5270240851232908,
+           0.526114132527085,
+           0.5324328688140014,
+           0.5449091513757979,
+           0.562352681712234,
+           0.5834861991446381,
+           0.606979265548661,
+           0.6314827843842921,
+           0.6556633856554506,
+           0.6782368184677567,
+           0.6979995242482501,
+           0.7138576155904083,
+           0.7248525567289782,
+           0.7301829299946466,
+           0.7292217759835239,
+           0.7215291109653587,
+           0.7068593503070625,
+           0.6851634982339191,
+           0.6565860987673509,
+           0.6214570767749705,
+           0.5802787283717843,
+           0.5337082431476221,
+           0.48253625377430276,
+           0.4276620086353495,
+           0.3700658477201127,
+           0.310779729023992,
+           0.2508566004330146,
+           0.19133943936651682,
+           0.1332307886433075,
+           0.07746360199361282,
+           0.024874176764777683,
+           -0.023822104409073907,
+           -0.06805157545571465,
+           -0.10739907554809856,
+           -0.141620273043075,
+           -0.1706491898016052,
+           -0.19460071636013254,
+           -0.21376803922423485,
+           -0.22861503449637272,
+           -0.23976381375554442,
+           -0.24797773523344588,
+           -0.2541403126482035,
+           -0.2592305625259941,
+           -0.2642954256966314,
+           -0.27041997746527974,
+           -0.2786962017136354,
+           -0.2901911452972698,
+           -0.30591528950011626,
+           -0.32679197442063745,
+           -0.3536286899692175,
+           -0.3870910041602165,
+           -0.42767983661537556,
+           -0.47571270418634337,
+           -0.5313094683415968,
+           -0.5943830028469215,
+           -0.6646350780504079,
+           -0.7415576277977028,
+           -0.8244394298944341,
+           -0.9123780944706689,
+           -1.0042971200019104,
+           -1.0989676474749377,
+           -1.1950344225026703,
+           -1.2910453661309798,
+           -1.385484060400474,
+           -1.4768043768346018,
+           -1.563466416916926,
+           -1.643972894827657,
+           -1.7169050752646724,
+           -1.7809573835812003,
+           -1.834969831695555,
+           -1.8779574506906163,
+           -1.9091359886186277,
+           -1.9279432181559952,
+           -1.9340553013475654,
+           -1.9273977752635711,
+           -1.9081508501381492,
+           -1.876748847358518,
+           -1.8338737452161369,
+           -1.780442942180978,
+           -1.7175914871440598,
+           -1.646649160166566,
+           -1.5691129124827112,
+           -1.4866152877485144,
+           -1.4008895450196968,
+           -1.3137322852475928,
+           -1.2269644451903008,
+           -1.1423915640030298,
+           -1.061764247361075,
+           -0.9867397512770524,
+           -0.9188455828435592,
+           -0.8594459685503489,
+           -0.8097119737092447,
+           -0.7705959704917063,
+           -0.7428110492277312,
+           -0.7268158504282439,
+           -0.7228051663239977,
+           -0.7307065236919775,
+           -0.750182817698206,
+           -0.7806409228791399,
+           -0.8212460657045988,
+           -0.8709416068568883,
+           -0.9284737537330094,
+           -0.9924206078247463,
+           -1.0612248503586532,
+           -1.1332292853287629,
+           -1.206714393853864,
+           -1.279937009193476,
+           -1.351169198810526,
+           -1.4187364390900252,
+           -1.4810541896825444,
+           -1.5366620173668242,
+           -1.5842544827160312,
+           -1.6227080851051736,
+           -1.651103660649436,
+           -1.6687437410424844,
+           -1.6751645061493852,
+           -1.6701420965024634,
+           -1.6536931902506429,
+           -1.626069889205439,
+           -1.5877490969566168,
+           -1.5394167051958554,
+           -1.4819470291206842,
+           -1.4163780460424997,
+           -1.3438830903315144,
+           -1.2657397401972201,
+           -1.1832966955420265,
+           -1.0979394897217667,
+           -1.0110559004866968,
+           -0.9240019261749993,
+           -0.8380691724414282,
+           -0.7544544530176744,
+           -0.6742323463299328,
+           -0.5983313698485918,
+           -0.5275143378724704,
+           -0.4623633585131225,
+           -0.4032698047406636,
+           -0.3504294655457909,
+           -0.3038429498203913,
+           -0.26332128082789297,
+           -0.22849648651736407,
+           -0.19883686376635612,
+           -0.17366647610845196,
+           -0.15218833758301198,
+           -0.13351064271111912,
+           -0.11667532656556644,
+           -0.10068818135620557,
+           -0.08454971832054758,
+           -0.06728594691622032,
+           -0.047978247754829444,
+           -0.025791541259195017,
+           -2.590391758059263e-16
+          ],
+          [
+           0,
+           0.03199923717468105,
+           0.06885052224549709,
+           0.1107452452203791,
+           0.15769432139381334,
+           0.20952596932520093,
+           0.26588863695674225,
+           0.3262590113481597,
+           0.3899549144509713,
+           0.45615275918639603,
+           0.5239091200859467,
+           0.5921858639568685,
+           0.6598781912204117,
+           0.7258448601646188,
+           0.7889398063693559,
+           0.8480443295529944,
+           0.9020990011100718,
+           0.9501344481827015,
+           0.9913001942197125,
+           1.024890781069562,
+           1.0503684626413072,
+           1.067381843466373,
+           1.0757799350544093,
+           1.075621216299571,
+           1.067177408548753,
+           1.0509318081996226,
+           1.0275721565583789,
+           0.9979781647377858,
+           0.9632039471606292,
+           0.9244557473468862,
+           0.883065460833091,
+           0.8404605692435871,
+           0.7981311939416982,
+           0.7575950549315641,
+           0.720361178777297,
+           0.6878932367453492,
+           0.6615734101585381,
+           0.6426676736109717,
+           0.632293358315062,
+           0.6313898080638605,
+           0.6406928702548571,
+           0.6607138757994425,
+           0.6917236566628339,
+           0.7337420307809167,
+           0.786533054070518,
+           0.84960620135332,
+           0.9222234956162236,
+           1.003412461614809,
+           1.0919846389051824,
+           1.1865592544210288,
+           1.2855915290142819,
+           1.3874049790436853,
+           1.4902269759206759,
+           1.5922267459324173,
+           1.6915549316553131,
+           1.7863837963678997,
+           1.8749471350729472,
+           1.9555789605069793,
+           2.026750059760485,
+           2.087101566212338,
+           2.135474761220431,
+           2.17093640872391,
+           2.192799031451969,
+           2.200635657238659,
+           2.1942886951018754,
+           2.1738727400687057,
+           2.1397712498303005,
+           2.0926271816826802,
+           2.033327821320757,
+           1.9629841724235317,
+           1.8829054042636009,
+           1.7945689706827253,
+           1.6995871148873067,
+           1.5996705581926336,
+           1.4965902350721494,
+           1.3921379801156915,
+           1.288087093752918,
+           1.1861537123798533,
+           1.0879598849145482,
+           0.994999212428535,
+           0.9086058415140923,
+           0.8299275171173204,
+           0.7599032988209296,
+           0.6992464285348846,
+           0.6484327101311647,
+           0.6076946258991455,
+           0.5770212741555065,
+           0.5561640703856615,
+           0.5446480144185146,
+           0.541788191780232,
+           0.5467110518289541,
+           0.5583798916093252,
+           0.5756238753508393,
+           0.5971698375659227,
+           0.6216760547532199,
+           0.6477671282735327,
+           0.6740691000228018,
+           0.6992439235248531,
+           0.7220224359065623,
+           0.7412350202571056,
+           0.7558392119419665,
+           0.7649435848764129,
+           0.7678273524429167,
+           0.7639552301424337,
+           0.7529872303433984,
+           0.7347831905114683,
+           0.7094019717572657,
+           0.6770954010132467,
+           0.6382971642102094,
+           0.5936069861008305,
+           0.5437705516548826,
+           0.4896557312418417,
+           0.432225764440302,
+           0.37251013296078056,
+           0.31157390995932877,
+           0.2504864095502063,
+           0.19028997570414605,
+           0.13196974358445185,
+           0.07642517890835,
+           0.02444415284412918,
+           -0.02331975749722221,
+           -0.06636613801938065,
+           -0.10436227167491587,
+           -0.13715294671265588,
+           -0.16476527182380607,
+           -0.18740836132639577,
+           -0.2054678875755022,
+           -0.21949563202646818,
+           -0.23019429740180317,
+           -0.2383979678907356,
+           -0.2450487190775208,
+           -0.25116998142679,
+           -0.2578373480434037,
+           -0.26614758684363093,
+           -0.27718666743441595,
+           -0.2919976425910148,
+           -0.311549232458811,
+           -0.33670594622708516,
+           -0.3682005413180554,
+           -0.40660956492693745,
+           -0.45233264837750675,
+           -0.5055761330454173,
+           -0.566341499809109,
+           -0.6344189547588066,
+           -0.709386395187684,
+           -0.7906138449088839,
+           -0.8772733100546967,
+           -0.9683538691660836,
+           -1.0626816780131325,
+           -1.158944443548341,
+           -1.255719805858953,
+           -1.3515069648707903,
+           -1.444760802455641,
+           -1.5339276827062232,
+           -1.6174820652180197,
+           -1.693963039514835,
+           -1.7620098840098322,
+           -1.8203957702975038,
+           -1.8680587727680367,
+           -1.9041294036259055,
+           -1.9279539729627069,
+           -1.9391131706783864,
+           -1.9374353794252026,
+           -1.9230043526434948,
+           -1.896161026132082,
+           -1.857499372173568,
+           -1.8078563485814196,
+           -1.7482961376429154,
+           -1.6800890083029005,
+           -1.6046852656700406,
+           -1.523684871813871,
+           -1.4388034279039568,
+           -1.3518352974031522,
+           -1.2646147210463192,
+           -1.1789758249506244,
+           -1.0967124521476932,
+           -1.0195387543674153,
+           -0.9490514648510606,
+           -0.886694734695255,
+           -0.8337283556400533,
+           -0.79120011274846,
+           -0.7599229130032545,
+           -0.7404572228319478,
+           -0.7330992217068814,
+           -0.7378749433137035,
+           -0.7545405336368862,
+           -0.7825886101324684,
+           -0.821260561476532,
+           -0.8695644867099804,
+           -0.9262983393632394,
+           -0.9900777195713774,
+           -1.0593676482508727,
+           -1.1325175647368428,
+           -1.2077987151065102,
+           -1.2834430445179053,
+           -1.35768267454983,
+           -1.428789036487697,
+           -1.4951107439598574,
+           -1.555109322937398,
+           -1.6073919729713684,
+           -1.6507406092383377,
+           -1.6841365285967733,
+           -1.7067801520835835,
+           -1.718105418383845,
+           -1.717788534757248,
+           -1.7057509304349243,
+           -1.682156399187948,
+           -1.6474025591207806,
+           -1.6021068952817208,
+           -1.5470877810323462,
+           -1.4833409940882714,
+           -1.4120123498074213,
+           -1.3343671650682605,
+           -1.2517573387578826,
+           -1.1655868877399935,
+           -1.0772768089535487,
+           -0.9882301482873993,
+           -0.899798144910946,
+           -0.8132482861878618,
+           -0.7297350540685492,
+           -0.6502740703680523,
+           -0.5757202574882988,
+           -0.5067505252637442,
+           -0.44385137639442557,
+           -0.38731169538035987,
+           -0.3372208522123761,
+           -0.29347211568070414,
+           -0.2557712354690896,
+           -0.22364992062082223,
+           -0.19648381779673693,
+           -0.17351447910535997,
+           -0.1538747090148696,
+           -0.1366165954582438,
+           -0.12074146381798644,
+           -0.1052309456719285,
+           -0.08907832814857261,
+           -0.07131934510739282,
+           -0.051061588215703925,
+           -0.027511753887495063,
+           -2.7652536647843334e-16
+          ],
+          [
+           0,
+           0.034099753119031524,
+           0.07322247462777758,
+           0.11746871727652884,
+           0.16675471854037383,
+           0.22081304608500102,
+           0.27919843004662365,
+           0.3412986394965145,
+           0.4063501282907089,
+           0.4734580502156679,
+           0.5416201281178088,
+           0.6097537594841389,
+           0.6767256543329319,
+           0.7413832324969292,
+           0.8025869582097593,
+           0.8592427616206388,
+           0.9103336902206245,
+           0.954949948380125,
+           0.9923165199373294,
+           1.0218176261646634,
+           1.0430173480793854,
+           1.0556758360734373,
+           1.059760638895974,
+           1.0554528054273418,
+           1.043147543418652,
+           1.023449356180008,
+           0.9971617176674582,
+           0.9652714850549864,
+           0.9289283822074852,
+           0.8894200141177577,
+           0.8481429881435755,
+           0.806570819851755,
+           0.7662193868546324,
+           0.7286107610217917,
+           0.695236296135311,
+           0.6675198731998636,
+           0.6467822085219569,
+           0.6342071101877649,
+           0.6308105271039994,
+           0.6374131722740395,
+           0.6546174199380834,
+           0.6827890765743169,
+           0.7220445109400342,
+           0.7722435011096422,
+           0.832988019934667,
+           0.9036270378394036,
+           0.9832672768584475,
+           1.0707897058708036,
+           1.1648714276215313,
+           1.2640124767709908,
+           1.3665669281070087,
+           1.47077760815848,
+           1.5748136143769684,
+           1.6768097760126313,
+           1.7749071415451716,
+           1.867293550274011,
+           1.952243341120774,
+           2.0281552699915464,
+           2.0935877477664095,
+           2.1472905731597973,
+           2.18823241683149,
+           2.2156234132390438,
+           2.2289323323818313,
+           2.2278979319870245,
+           2.2125342287087153,
+           2.1831295711974845,
+           2.140239544940446,
+           2.0846738849956608,
+           2.017477714595715,
+           1.9399075616274604,
+           1.8534027279561929,
+           1.759552695473567,
+           1.6600613449767778,
+           1.5567088373099087,
+           1.4513120588605437,
+           1.3456845642574242,
+           1.2415969572485583,
+           1.1407386360997072,
+           1.0446817928455168,
+           0.9548484973030139,
+           0.8724816183975042,
+           0.798620239018935,
+           0.7340801087261996,
+           0.6794395539293062,
+           0.635031130796442,
+           0.6009391653787435,
+           0.5770031817945276,
+           0.5628270763056772,
+           0.5577937562671893,
+           0.5610848316420954,
+           0.571704826259004,
+           0.5885092691861707,
+           0.6102359360961213,
+           0.6355384384808849,
+           0.663021306769333,
+           0.691275683009563,
+           0.7189147304911403,
+           0.7446078816243473,
+           0.7671130811436628,
+           0.7853062382967236,
+           0.7982071776371041,
+           0.8050014714000078,
+           0.8050576448152051,
+           0.7979393663426949,
+           0.7834123646449903,
+           0.7614459498532322,
+           0.7322091549190702,
+           0.6960616500907976,
+           0.6535397163624413,
+           0.6053376887871226,
+           0.5522853946903055,
+           0.4953222122119033,
+           0.4354684587453545,
+           0.3737948846351985,
+           0.31139109331418563,
+           0.24933373378239004,
+           0.18865531436181393,
+           0.13031446795404958,
+           0.07516845908658068,
+           0.023948662889955487,
+           -0.022760332653828437,
+           -0.06453744529976306,
+           -0.10113719173765584,
+           -0.13249683026433637,
+           -0.15873835724004162,
+           -0.18016529614976648,
+           -0.1972543542532978,
+           -0.21064215616585152,
+           -0.22110739285216705,
+           -0.2295488451577575,
+           -0.23695985007115422,
+           -0.2443998726288808,
+           -0.2529639243181155,
+           -0.26375062799811483,
+           -0.2778297682184029,
+           -0.2962101833367162,
+           -0.3198088515450377,
+           -0.34942199685808395,
+           -0.3856989939125086,
+           -0.42911978320633737,
+           -0.4799764228205455,
+           -0.5383593008159727,
+           -0.604148416908092,
+           -0.6770100155582193,
+           -0.7563987184290022,
+           -0.8415651655808457,
+           -0.9315690352974335,
+           -1.025297175515585,
+           -1.1214864489344647,
+           -1.218750772285159,
+           -1.3156117210236469,
+           -1.4105319766358568,
+           -1.5019508172098652,
+           -1.5883207949033826,
+           -1.668144707899824,
+           -1.7400119603706092,
+           -1.8026334122691923,
+           -1.8548738513430423,
+           -1.8957812718815716,
+           -1.9246122172022282,
+           -1.9408525339892782,
+           -1.9442329941507193,
+           -1.9347393612484458,
+           -1.9126166108375986,
+           -1.8783671540011362,
+           -1.8327430575674961,
+           -1.7767323994240383,
+           -1.7115400394341322,
+           -1.6385632222416928,
+           -1.5593625543645018,
+           -1.4756290113292938,
+           -1.3891477283895448,
+           -1.3017594081716966,
+           -1.2153202384359394,
+           -1.131661251520896,
+           -1.052548072998298,
+           -0.979642000175382,
+           -0.9144633214888899,
+           -0.8583577362324053,
+           -0.8124666616847009,
+           -0.7777021233067893,
+           -0.754726815462265,
+           -0.7439397977141804,
+           -0.7454681581353706,
+           -0.7591648334852239,
+           -0.7846126299974399,
+           -0.821134341442992,
+           -0.8678087166563119,
+           -0.9234918903512302,
+           -0.9868437621659572,
+           -1.0563586925884159,
+           -1.1303997835395678,
+           -1.2072359283674183,
+           -1.2850807528235288,
+           -1.3621325267642745,
+           -1.4366141068222982,
+           -1.506811973562905,
+           -1.5711134525497392,
+           -1.6280412566124067,
+           -1.6762845552166747,
+           -1.7147258644585366,
+           -1.7424631556460637,
+           -1.7588266990963204,
+           -1.763390289713307,
+           -1.755976638908966,
+           -1.7366568600728363,
+           -1.705744118569499,
+           -1.6637816586084915,
+           -1.6115255548175509,
+           -1.549922662638589,
+           -1.4800843556726342,
+           -1.403256737051913,
+           -1.3207880934195741,
+           -1.2340944221936598,
+           -1.1446239040098112,
+           -1.0538212116268915,
+           -0.9630925437347075,
+           -0.8737722471701198,
+           -0.7870918447225788,
+           -0.7041522192191144,
+           -0.625899619647037,
+           -0.5531060538817384,
+           -0.48635451771897187,
+           -0.426029384283199,
+           -0.3723121446771028,
+           -0.3251825533150744,
+           -0.28442509320819853,
+           -0.2496405410143995,
+           -0.2202622823354867,
+           -0.19557690777394715,
+           -0.17474851265738145,
+           -0.15684603078394374,
+           -0.140872857342479,
+           -0.12579796018196363,
+           -0.1105876432267352,
+           -0.09423711191783202,
+           -0.0758009984268644,
+           -0.054422033809319204,
+           -0.02935710446885032,
+           -2.9503092252800394e-16
+          ],
+          [
+           0,
+           0.0362783257932035,
+           0.07770909949364906,
+           0.12429873795958077,
+           0.17586707251101266,
+           0.2320509244302092,
+           0.2923128601190183,
+           0.35595490460437335,
+           0.4221368620103826,
+           0.48989877039206553,
+           0.5581869090373576,
+           0.6258826817773517,
+           0.6918336224181492,
+           0.7548857101100601,
+           0.8139161448106473,
+           0.8678657169689622,
+           0.9157699116081577,
+           0.9567879150066546,
+           0.9902287415159734,
+           1.015573767511361,
+           1.0324950473474561,
+           1.0408688903181877,
+           1.0407842954190745,
+           1.0325459692547603,
+           1.0166717885235386,
+           0.9938847087473017,
+           0.9650992617921347,
+           0.9314029227110241,
+           0.8940327580693562,
+           0.8543478898710284,
+           0.8137984184068258,
+           0.7738915410270252,
+           0.7361556796072812,
+           0.7021034853815211,
+           0.6731946243982753,
+           0.6507992591846874,
+           0.6361631318932642,
+           0.6303751214389265,
+           0.6343380926444234,
+           0.6487437804767742,
+           0.6740523588614965,
+           0.7104772335559477,
+           0.7579754748096706,
+           0.8162441710450623,
+           0.884722842834021,
+           0.9626019104942908,
+           1.0488370622567984,
+           1.142169226753112,
+           1.2411497170592638,
+           1.3441699870688124,
+           1.4494953276725995,
+           1.5553017328945482,
+           1.6597150871831952,
+           1.7608517664499976,
+           1.856859708644033,
+           1.9459589955906522,
+           2.0264809968746267,
+           2.0969051585255585,
+           2.155892573411772,
+           2.2023155452718886,
+           2.235282452401829,
+           2.25415732789234,
+           2.2585736982895908,
+           2.2484423585942195,
+           2.2239529053164895,
+           2.1855689973709014,
+           2.134017463322631,
+           2.0702715192749435,
+           1.9955285009690866,
+           1.911182643074416,
+           1.8187935550386698,
+           1.7200511434288988,
+           1.6167378129953103,
+           1.5106888407548942,
+           1.4037518577389234,
+           1.2977463907317368,
+           1.194424410957835,
+           1.0954328084263507,
+           1.002278660253547,
+           0.9162980900345475,
+           0.8386294250148123,
+           0.7701912506750251,
+           0.7116658410550641,
+           0.663488310711247,
+           0.6258416939028153,
+           0.5986580119024565,
+           0.5816252437870348,
+           0.5741999732674533,
+           0.5756253475643036,
+           0.5849538573707957,
+           0.6010743326641936,
+           0.6227424503091786,
+           0.6486139684299348,
+           0.6772798413537707,
+           0.7073023289944084,
+           0.7372511967644969,
+           0.7657391068494286,
+           0.7914553287430828,
+           0.8131969455912004,
+           0.8298968018256367,
+           0.8406475250160477,
+           0.8447210585714188,
+           0.8415832592483596,
+           0.8309032413882419,
+           0.8125572851739018,
+           0.786627265552857,
+           0.753393698309436,
+           0.7133236365687181,
+           0.6670537813494305,
+           0.6153692903873086,
+           0.5591788773108315,
+           0.4994868856779135,
+           0.4373630970765361,
+           0.3739110876045448,
+           0.3102359812180665,
+           0.24741246084630517,
+           0.18645388853323705,
+           0.12828335445874686,
+           0.07370742233583959,
+           0.02339326672584209,
+           -0.022150191898134615,
+           -0.06258665368951179,
+           -0.09776192489058447,
+           -0.12770826730650744,
+           -0.1526434911922829,
+           -0.17296480840621223,
+           -0.18923759978426163,
+           -0.2021793839582038,
+           -0.21263940089000583,
+           -0.2215743390196651,
+           -0.23002083717823085,
+           -0.23906547869126335,
+           -0.24981306317992413,
+           -0.26335398970258905,
+           -0.28073161181470624,
+           -0.30291043013605584,
+           -0.3307459709304017,
+           -0.3649571604059442,
+           -0.4061019448653859,
+           -0.45455682792466595,
+           -0.510500899720144,
+           -0.5739048217157164,
+           -0.6445251071650229,
+           -0.7219039045531822,
+           -0.8053743527464995,
+           -0.8940714355802275,
+           -0.9869481237440494,
+           -1.0827964565916472,
+           -1.180273089306434,
+           -1.2779287149079404,
+           -1.3742406688177249,
+           -1.4676479387079866,
+           -1.5565877363065346,
+           -1.6395327424383668,
+           -1.715028113046726,
+           -1.7817273329148762,
+           -1.8384260254062141,
+           -1.8840928702956043,
+           -1.9178968466701087,
+           -1.939230102396892,
+           -1.947725853765788,
+           -1.94327083614988,
+           -1.926011956046746,
+           -1.8963569335132948,
+           -1.8549688684047598,
+           -1.802754810441101,
+           -1.7408485583583309,
+           -1.6705880536924973,
+           -1.5934878666395156,
+           -1.5112073916857462,
+           -1.4255154763437474,
+           -1.338252294741827,
+           -1.2512893468111812,
+           -1.1664885116705384,
+           -1.0856611093230264,
+           -1.010527927296558,
+           -0.9426811482855014,
+           -0.8835490716604852,
+           -0.8343644569331676,
+           -0.7961372324511881,
+           -0.7696322098044628,
+           -0.7553523261379295,
+           -0.7535278056582219,
+           -0.7641114912728533,
+           -0.7867804509215667,
+           -0.820943814309818,
+           -0.8657566480526842,
+           -0.9201395342738897,
+           -0.9828033829515941,
+           -1.052278885030239,
+           -1.126949904512586,
+           -1.205090016039082,
+           -1.2849013220620065,
+           -1.3645546323641384,
+           -1.4422300595733144,
+           -1.5161570781549587,
+           -1.5846531112318045,
+           -1.6461597490255824,
+           -1.6992757637276736,
+           -1.74278616664549,
+           -1.775686652509558,
+           -1.797202890395681,
+           -1.806804247971383,
+           -1.8042116725645878,
+           -1.78939959549416,
+           -1.7625918716709978,
+           -1.7242519110915815,
+           -1.6750672989510715,
+           -1.6159293332666338,
+           -1.5479080298938885,
+           -1.4722232516932856,
+           -1.39021270876785,
+           -1.3032976479772236,
+           -1.2129471006362404,
+           -1.120641586243743,
+           -1.0278371766165053,
+           -0.9359308088387611,
+           -0.8462276974537389,
+           -0.7599116373397468,
+           -0.6780189102704842,
+           -0.6014164122779947,
+           -0.5307845080688659,
+           -0.46660499570964303,
+           -0.4091544327129203,
+           -0.3585029368588137,
+           -0.3145184350499038,
+           -0.2768761947440166,
+           -0.2450733385216627,
+           -0.21844791648172182,
+           -0.19620199656869428,
+           -0.17742813247826825,
+           -0.161138484967157,
+           -0.14629580728873118,
+           -0.13184546069581282,
+           -0.11674760259132415,
+           -0.1000086885218307,
+           -0.08071144980067202,
+           -0.058042550565803104,
+           -0.03131719043329235,
+           -3.1444303346169504e-16
+          ],
+          [
+           0,
+           0.038520237442652226,
+           0.08227881290524247,
+           0.13118553546043812,
+           0.18496298472153164,
+           0.24315305222235864,
+           0.30512860853270213,
+           0.37010999629024993,
+           0.43718592257304606,
+           0.5053382080641587,
+           0.5734697482269143,
+           0.6404349558244112,
+           0.7050718867813005,
+           0.7662352043341414,
+           0.8228291108753147,
+           0.8738393735508482,
+           0.9183635886534288,
+           0.9556388707259017,
+           0.9850662140742994,
+           1.0062308555727202,
+           1.018918066225211,
+           1.0231239124922669,
+           1.019060654071839,
+           1.007156579517607,
+           0.9880502214194189,
+           0.9625790353529888,
+           0.9317627678578074,
+           0.8967818747819949,
+           0.8589514790149603,
+           0.8196914726900992,
+           0.7804934704399183,
+           0.7428854046408803,
+           0.7083946186322203,
+           0.6785103579450381,
+           0.6546465814665967,
+           0.6381060135696427,
+           0.6300463345020744,
+           0.6314493602692998,
+           0.6430939959162617,
+           0.6655336591235272,
+           0.6990787664580163,
+           0.7437847549892533,
+           0.799445980199656,
+           0.8655956903917804,
+           0.9415121315633834,
+           1.0262306885621473,
+           1.1185618218796676,
+           1.2171144182971798,
+           1.3203240412275847,
+           1.426485446273402,
+           1.5337886222111001,
+           1.640357529926866,
+           1.7442906439461843,
+           1.8437023548144986,
+           1.9367642668687464,
+           2.021745425503951,
+           2.0970505309297556,
+           2.1612552411009993,
+           2.2131377339071383,
+           2.251705786197784,
+           2.2762187326927745,
+           2.286203788720758,
+           2.2814663541171796,
+           2.26209405825122,
+           2.2284544545750773,
+           2.181186423689717,
+           2.1211854930376175,
+           2.0495834253408636,
+           1.9677225633042899,
+           1.8771255416123198,
+           1.7794610858720408,
+           1.6765067092670962,
+           1.5701091890920322,
+           1.4621437553234706,
+           1.3544729507686333,
+           1.2489061264839239,
+           1.1471605170175212,
+           1.050824798112489,
+           0.9613259658812099,
+           0.8799002927295524,
+           0.8075690135630773,
+           0.7451192785795021,
+           0.6930907791500148,
+           0.6517683141286956,
+           0.6211804188409473,
+           0.6011040315641124,
+           0.5910750261528508,
+           0.5904042981659973,
+           0.5981989588804797,
+           0.613388070178698,
+           0.634752246422677,
+           0.6609563596699567,
+           0.6905845141019769,
+           0.7221764060030792,
+           0.754264158201677,
+           0.78540871316849,
+           0.8142348869990028,
+           0.8394642267625004,
+           0.8599448751010832,
+           0.8746777269087952,
+           0.8828382613298188,
+           0.8837935456722442,
+           0.8771140332594298,
+           0.8625799115587766,
+           0.8401818967470409,
+           0.810116512670461,
+           0.7727760323731697,
+           0.7287333954807952,
+           0.6787225413545771,
+           0.6236147129096266,
+           0.5643913864516459,
+           0.5021145663303925,
+           0.4378952475671733,
+           0.3728608933015579,
+           0.3081227958543576,
+           0.2447441899023249,
+           0.1837099637478834,
+           0.12589877054558105,
+           0.07205827676068245,
+           0.0227842017430429,
+           -0.021496297767544043,
+           -0.06053645857969372,
+           -0.09427664321858699,
+           -0.12284579255346528,
+           -0.14655755620107913,
+           -0.1659011972464646,
+           -0.1815275046497797,
+           -0.19423007766239028,
+           -0.2049224683281054,
+           -0.2146117775977254,
+           -0.22436939494625358,
+           -0.23529964823956442,
+           -0.24850718797714197,
+           -0.2650639664543063,
+           -0.2859766868816949,
+           -0.31215558966278906,
+           -0.34438541301413006,
+           -0.3832993136276462,
+           -0.4293564613708694,
+           -0.4828239318592527,
+           -0.5437634143421403,
+           -0.6120231323583828,
+           -0.6872352440227314,
+           -0.768818850855585,
+           -0.8559886022123067,
+           -0.9477687401550213,
+           -1.0430122906069779,
+           -1.1404249743313568,
+           -1.2385932890181865,
+           -1.3360161046356704,
+           -1.431139020977124,
+           -1.522390661392501,
+           -1.6082200219651073,
+           -1.687133962311928,
+           -1.7577339136472807,
+           -1.8187508920933242,
+           -1.869077940219341,
+           -1.9077991766533622,
+           -1.9342147110004708,
+           -1.947860777375355,
+           -1.948524552299901,
+           -1.9362532488069886,
+           -1.9113572152636062,
+           -1.8744069113463337,
+           -1.8262237812513098,
+           -1.7678651919812238,
+           -1.7006037487961507,
+           -1.6259014370964318,
+           -1.5453791667443089,
+           -1.4607824079993066,
+           -1.3739437050407528,
+           -1.286742931078845,
+           -1.2010662063701611,
+           -1.1187644356173483,
+           -1.041612433351584,
+           -0.9712695946389269,
+           -0.9092430340611944,
+           -0.8568540592076919,
+           -0.8152087672338729,
+           -0.7851734562688469,
+           -0.767355429926408,
+           -0.7620896456461885,
+           -0.7694315191583169,
+           -0.7891560513902349,
+           -0.8207632941662378,
+           -0.8634900207350067,
+           -0.9163273201517672,
+           -0.9780436944118936,
+           -1.0472131073840105,
+           -1.1222473181722201,
+           -1.201431731366865,
+           -1.2829639151402081,
+           -1.364993877266384,
+           -1.4456651503462246,
+           -1.5231557217070004,
+           -1.5957178509694692,
+           -1.661715848902715,
+           -1.7196609441273891,
+           -1.7682424381395612,
+           -1.806354442157745,
+           -1.8331175991248891,
+           -1.8478953180970386,
+           -1.8503041831508342,
+           -1.8402183415088245,
+           -1.8177678222974378,
+           -1.7833308846051867,
+           -1.7375206376799845,
+           -1.6811663136597126,
+           -1.615289700805211,
+           -1.5410773596896294,
+           -1.4598493434124151,
+           -1.373025223268942,
+           -1.282088281493445,
+           -1.1885487712835476,
+           -1.093907160426981,
+           -0.9996182681631857,
+           -0.9070571756685943,
+           -0.8174877395585475,
+           -0.7320344663938984,
+           -0.6516584162145282,
+           -0.5771376969002988,
+           -0.5090529913885325,
+           -0.44777842949359326,
+           -0.3934779785717046,
+           -0.3461073860204687,
+           -0.3054215651509001,
+           -0.2709871778725208,
+           -0.24220003635017037,
+           -0.21830682460928882,
+           -0.19843053301023122,
+           -0.181598906273254,
+           -0.16677513160508534,
+           -0.15288993928827874,
+           -0.13887425517550012,
+           -0.12369153367612475,
+           -0.10636891126999941,
+           -0.08602635400986952,
+           -0.06190302700405978,
+           -0.03338018809839708,
+           -3.3463697705270413e-16
+          ],
+          [
+           0,
+           0.040809791225373926,
+           0.086898469621559,
+           0.1380776317595751,
+           0.19397266795436305,
+           0.2540322778032197,
+           0.3175430102936421,
+           0.3836484510738671,
+           0.4513725572510557,
+           0.5196465305207926,
+           0.5873385253303472,
+           0.6532854125424813,
+           0.7163257626538585,
+           0.7753331774924339,
+           0.8292490863973011,
+           0.8771141325403468,
+           0.9180973070821083,
+           0.9515220425019181,
+           0.9768885503977471,
+           0.9938917814949264,
+           1.0024344942486254,
+           1.0026350405755207,
+           0.9948296098647964,
+           0.9795688121887096,
+           0.9576086250639629,
+           0.9298958716139339,
+           0.8975485379460876,
+           0.8618313704672149,
+           0.8241273163586608,
+           0.7859054794241535,
+           0.7486863562342381,
+           0.714005191553064,
+           0.6833743455343552,
+           0.6582455967100633,
+           0.6399733135070209,
+           0.6297794126188727,
+           0.6287209853112375,
+           0.6376614134935455,
+           0.6572457175449792,
+           0.6878807793416155,
+           0.7297209690716899,
+           0.7826595760293135,
+           0.8463263047680686,
+           0.9200909521625307,
+           1.0030732316361464,
+           1.0941585617284904,
+           1.1920194909562032,
+           1.295142293143659,
+           1.4018581404585457,
+           1.5103781484199628,
+           1.6188314909493569,
+           1.7253057064968016,
+           1.827888260318347,
+           1.9247083945108494,
+           2.0139782872849197,
+           2.094032556458667,
+           2.1633651789896846,
+           2.2206629576626757,
+           2.2648347463966645,
+           2.2950357450930006,
+           2.3106862911086408,
+           2.3114847044931324,
+           2.297413884915858,
+           2.2687415063124057,
+           2.226013807095636,
+           2.1700431256175987,
+           2.1018894787418834,
+           2.0228366222918086,
+           1.9343631623568147,
+           1.8381094028090683,
+           1.7358407140872527,
+           1.6294082889369923,
+           1.5207082104187506,
+           1.4116397946818322,
+           1.3040641848860517,
+           1.199764162931405,
+           1.1004061126104114,
+           1.0075050122791909,
+           0.9223932585532911,
+           0.846194026789463,
+           0.7797997615992074,
+           0.7238562641457669,
+           0.6787527056347866,
+           0.6446177516114587,
+           0.6213218329935485,
+           0.6084854508575939,
+           0.6054932565115662,
+           0.6115135098954506,
+           0.62552239123603,
+           0.6463325262645535,
+           0.6726249869668027,
+           0.7029839501463465,
+           0.7359331369493355,
+           0.7699731193150005,
+           0.8036185649259069,
+           0.8354345009140527,
+           0.8640707080384988,
+           0.88829341042792,
+           0.9070134998745754,
+           0.9193106261659917,
+           0.9244525936783853,
+           0.9219096266648292,
+           0.9113631982538885,
+           0.892709257781982,
+           0.8660558341974393,
+           0.8317151362980053,
+           0.7901904099079433,
+           0.7421579442758806,
+           0.6884447416765126,
+           0.6300024723921962,
+           0.5678784292424844,
+           0.5031842693391296,
+           0.4370633839567494,
+           0.3706577690230788,
+           0.3050752779895704,
+           0.2413581255478207,
+           0.18045347518218582,
+           0.1231868868233044,
+           0.07023932435489715,
+           0.022128328387404562,
+           -0.020806150045051493,
+           -0.058410881588010936,
+           -0.09072321508513075,
+           -0.11796955517769915,
+           -0.14055849835662465,
+           -0.15906880462547104,
+           -0.17423251725194314,
+           -0.1869136704976355,
+           -0.19808314148143985,
+           -0.20879030448981517,
+           -0.22013223148966177,
+           -0.23322124913846712,
+           -0.24915170850759993,
+           -0.26896684784132735,
+           -0.29362663031742275,
+           -0.3239774178705811,
+           -0.3607242991697756,
+           -0.4044068258431176,
+           -0.45537882758671155,
+           -0.5137928759366034,
+           -0.5795898507247779,
+           -0.6524939354591723,
+           -0.7320132312484086,
+           -0.8174460368466177,
+           -0.9078926984774812,
+           -1.0022727909179527,
+           -1.099347254454742,
+           -1.1977449842177321,
+           -1.29599325228143,
+           -1.392551241752261,
+           -1.4858458884044103,
+           -1.5743091614379965,
+           -1.6564158722725597,
+           -1.7307210800927315,
+           -1.7958961657103343,
+           -1.8507626712070722,
+           -1.894323051210038,
+           -1.9257875514052354,
+           -1.9445965193569703,
+           -1.9504375597255994,
+           -1.9432570679760206,
+           -1.9232658106815073,
+           -1.8909383632860162,
+           -1.8470063642040817,
+           -1.79244569378533,
+           -1.728457834277793,
+           -1.6564458088608909,
+           -1.577985230589478,
+           -1.4947911124177118,
+           -1.4086811943801685,
+           -1.3215366308967151,
+           -1.235260947874317,
+           -1.151738224135071,
+           -1.0727914735692552,
+           -1.0001422027243623,
+           -0.935372093300206,
+           -0.8798877108099719,
+           -0.8348890706340482,
+           -0.8013428025195419,
+           -0.7799605464412291,
+           -0.7711830892566555,
+           -0.7751706157549635,
+           -0.7917993028136427,
+           -0.8206643349609086,
+           -0.8610892673499225,
+           -0.9121415116870183,
+           -0.9726535756761795,
+           -1.041249550568309,
+           -1.116376217735864,
+           -1.1963380368289165,
+           -1.279335187627582,
+           -1.363503767368598,
+           -1.446957196775931,
+           -1.527827862416953,
+           -1.6043080209245697,
+           -1.6746890120806601,
+           -1.737397872180503,
+           -1.7910305053612952,
+           -1.8343806570158923,
+           -1.8664640378688042,
+           -1.8865370671686195,
+           -1.8941098357792465,
+           -1.8889530314593743,
+           -1.871098715814429,
+           -1.8408349916629794,
+           -1.798694747211508,
+           -1.7454388058563348,
+           -1.682033944144008,
+           -1.6096263621589622,
+           -1.5295112974097915,
+           -1.4430995625684926,
+           -1.3518818570352715,
+           -1.2573917506007157,
+           -1.161168263335486,
+           -1.0647189686910394,
+           -0.9694845266520555,
+           -0.8768055112210612,
+           -0.7878923326728111,
+           -0.7037989715512394,
+           -0.6254011404411587,
+           -0.5533793737055153,
+           -0.4882074175787873,
+           -0.43014615648125837,
+           -0.3792431696111546,
+           -0.3353378683515868,
+           -0.2980720234008845,
+           -0.2669053543489916,
+           -0.24113572708626796,
+           -0.21992338912420875,
+           -0.2023185725030946,
+           -0.1872917109538674,
+           -0.173765454424991,
+           -0.16064762154271636,
+           -0.14686421007822426,
+           -0.13139158752562083,
+           -0.11328700836186584,
+           -0.09171665081050386,
+           -0.06598043276517594,
+           -0.03553295222892004,
+           -3.554772193663964e-16
+          ],
+          [
+           0,
+           0.04313045783401879,
+           0.09153368066347617,
+           0.14492234709900031,
+           0.2028256446849838,
+           0.26460173971895595,
+           0.32945512321257486,
+           0.3964583796804283,
+           0.4645778089383416,
+           0.5327022290653538,
+           0.5996742037364303,
+           0.664322871441398,
+           0.7254975093612375,
+           0.7821009420416631,
+           0.8331219050962113,
+           0.8776654970260996,
+           0.9149808973285359,
+           0.9444855952858555,
+           0.9657854595588901,
+           0.9786900818306129,
+           0.98322294570152,
+           0.9796261018907639,
+           0.9683591693074746,
+           0.9500926252625196,
+           0.9256954933928216,
+           0.8962176811217403,
+           0.8628673560771528,
+           0.8269838793647412,
+           0.790006929699042,
+           0.7534425531822071,
+           0.7188269564190839,
+           0.6876889235361054,
+           0.6615117788937178,
+           0.6416958357460566,
+           0.6295222662694097,
+           0.626119300292674,
+           0.632431609336258,
+           0.6491936603816982,
+           0.6769077318686605,
+           0.7158271749578473,
+           0.7659453787557851,
+           0.8269907619925859,
+           0.8984279688984782,
+           0.9794652972789969,
+           1.069068235712695,
+           1.1659788380995877,
+           1.2687405211321843,
+           1.3757277371605796,
+           1.4851798546662835,
+           1.5952384741233365,
+           1.7039873210021568,
+           1.8094937922055003,
+           1.9098511889584076,
+           2.0032206492037843,
+           2.087871796410315,
+           2.162221149323797,
+           2.224867387947571,
+           2.2746226437155492,
+           2.3105390746774384,
+           2.331930097308849,
+           2.3383857726076474,
+           2.329781982385309,
+           2.3062831787517997,
+           2.2683386421505936,
+           2.2166723372236663,
+           2.1522666075326895,
+           2.0763400960441905,
+           1.9903204147591222,
+           1.8958122106187383,
+           1.7945613828492284,
+           1.688416296604174,
+           1.5792869069639575,
+           1.4691027543960542,
+           1.3597708165547666,
+           1.2531342012599826,
+           1.1509326416826577,
+           1.0547657078032475,
+           0.9660595792887933,
+           0.886038135782096,
+           0.815699013433905,
+           0.7557951539966977,
+           0.7068222379691104,
+           0.6690122494644086,
+           0.6423332712194706,
+           0.6264954571360614,
+           0.620962980662364,
+           0.6249716138342596,
+           0.63755145741109,
+           0.6575542205364051,
+           0.6836843416944721,
+           0.714533153996818,
+           0.7486152291493332,
+           0.7844059874488755,
+           0.8203796369269292,
+           0.8550465038191937,
+           0.8869888388368699,
+           0.9148942286150136,
+           0.9375858080228777,
+           0.9540485550181093,
+           0.9634510532037528,
+           0.9651622255656297,
+           0.9587626730266483,
+           0.9440503901631618,
+           0.921040774190274,
+           0.8899609885225319,
+           0.8512388852096127,
+           0.8054868277519827,
+           0.7534808837887575,
+           0.6961359727264215,
+           0.6344776536658574,
+           0.569611321498037,
+           0.5026896417367664,
+           0.4348790960016334,
+           0.367326529055544,
+           0.30112658450152957,
+           0.23729088978861224,
+           0.1767198027720141,
+           0.12017746297528215,
+           0.06827080268767724,
+           0.0214330683503421,
+           -0.02008771599117083,
+           -0.05623504104191287,
+           -0.0871447956252881,
+           -0.11314071779116137,
+           -0.13472453251193783,
+           -0.15256103392301074,
+           -0.1674585026281739,
+           -0.18034497124103985,
+           -0.19224096094937043,
+           -0.20422940567672399,
+           -0.21742355597810625,
+           -0.23293371020386014,
+           -0.2518336542655281,
+           -0.2751277026478504,
+           -0.30371922180656447,
+           -0.3383814830200503,
+           -0.3797316359397896,
+           -0.42820851787386227,
+           -0.48405491911743603,
+           -0.547304813760433,
+           -0.6177759411111187,
+           -0.6950679882723837,
+           -0.7785664828562817,
+           -0.86745235986382,
+           -0.9607170220256621,
+           -1.0571825720307735,
+           -1.155526761611821,
+           -1.2543120797768479,
+           -1.3520182936845826,
+           -1.4470776635228682,
+           -1.5379119796246583,
+           -1.6229705178341434,
+           -1.700767979189776,
+           -1.7699214731444608,
+           -1.8291856200450494,
+           -1.8774848881143935,
+           -1.9139423418170705,
+           -1.9379040607917202,
+           -1.948958589530406,
+           -1.9469508952423151,
+           -1.9319904420117608,
+           -1.9044531302669734,
+           -1.8649769982751385,
+           -1.8144517332541403,
+           -1.754002190040664,
+           -1.6849662613815988,
+           -1.6088675822217828,
+           -1.5273836774339047,
+           -1.4423102751331245,
+           -1.3555226032466179,
+           -1.2689345629913857,
+           -1.1844567274529347,
+           -1.1039541451794437,
+           -1.0292049367936438,
+           -0.9618606568422373,
+           -0.9034093537978372,
+           -0.8551421992275416,
+           -0.8181244741258391,
+           -0.7931715982763872,
+           -0.7808307697269025,
+           -0.7813686489112419,
+           -0.7947653788498392,
+           -0.8207150826794413,
+           -0.8586328261556992,
+           -0.9076678794715187,
+           -0.9667229634667753,
+           -1.0344790236979995,
+           -1.1094249453290908,
+           -1.1898915055612105,
+           -1.2740887611575014,
+           -1.360145988930477,
+           -1.446153238764176,
+           -1.5302035232300693,
+           -1.6104346559568192,
+           -1.6850697628820692,
+           -1.7524555260155015,
+           -1.8110972774673468,
+           -1.859690140781619,
+           -1.897145515077837,
+           -1.9226123127006698,
+           -1.9354924901479678,
+           -1.9354505518027696,
+           -1.9224168529849406,
+           -1.8965846794430872,
+           -1.8584012309246225,
+           -1.808552783198296,
+           -1.747944442266797,
+           -1.6776750330939694,
+           -1.5990077798516886,
+           -1.5133375326858276,
+           -1.4221553749473466,
+           -1.3270115028484184,
+           -1.2294773052215122,
+           -1.1311075836742388,
+           -1.0334038427106982,
+           -0.9377795456776233,
+           -0.8455281766065148,
+           -0.757794871623354,
+           -0.6755522885564778,
+           -0.5995812721218284,
+           -0.5304567474311072,
+           -0.4685391397088384,
+           -0.4139714764230399,
+           -0.3666821830979015,
+           -0.32639343952726313,
+           -0.2926348225683553,
+           -0.2647618286834464,
+           -0.24197874723432736,
+           -0.22336524726535079,
+           -0.20790594882588578,
+           -0.1945221770531849,
+           -0.18210504505606076,
+           -0.1695489813817361,
+           -0.15578481023370233,
+           -0.13981150778872486,
+           -0.12072579551420226,
+           -0.0977487903287938,
+           -0.07024901025820886,
+           -0.03776113089419611,
+           -3.768186435540968e-16
+          ],
+          [
+           0,
+           0.045465032762772584,
+           0.09614914801097968,
+           0.15166632347326767,
+           0.21145146143059884,
+           0.27477576447319885,
+           0.34076679216347794,
+           0.4084326718198186,
+           0.47668982702033935,
+           0.5443934940058932,
+           0.6103702213242999,
+           0.6734514937233499,
+           0.7325075888737455,
+           0.7864807658398445,
+           0.8344168975986005,
+           0.8754946960386355,
+           0.9090517358823812,
+           0.9346065624438145,
+           0.9518762651252246,
+           0.9607890116631796,
+           0.9614911645421222,
+           0.9543487375510032,
+           0.9399430937507987,
+           0.9190609325602933,
+           0.8926787595798159,
+           0.8619421744893477,
+           0.8281404463074139,
+           0.7926769680962353,
+           0.7570362917335612,
+           0.7227485348788073,
+           0.6913520243956269,
+           0.6643550913875496,
+           0.6431979613155986,
+           0.6292156876137047,
+           0.6236030585956093,
+           0.6273823656375555,
+           0.6413748565830595,
+           0.6661766135619005,
+           0.7021394909749726,
+           0.7493576297671516,
+           0.8076599311956768,
+           0.8766087303405965,
+           0.9555047600907123,
+           1.043398343936645,
+           1.1391066043540217,
+           1.241236326592996,
+           1.348211978927675,
+           1.4583082632875606,
+           1.5696864578393872,
+           1.6804337182997764,
+           1.7886044298974253,
+           1.892262648842097,
+           1.989524642237757,
+           2.0786005293729053,
+           2.1578340454211906,
+           2.225739490386443,
+           2.281034990643652,
+           2.322671286118482,
+           2.3498553609495834,
+           2.3620683568575087,
+           2.3590773434611085,
+           2.340940665160936,
+           2.308006736418732,
+           2.260906312603427,
+           2.200538418271195,
+           2.128050265039363,
+           2.0448116334491173,
+           1.9523843239354528,
+           1.8524873980632819,
+           1.7469590297351534,
+           1.6377158647479026,
+           1.5267108439797608,
+           1.415890479268111,
+           1.307152580900341,
+           1.2023054213824456,
+           1.1030292821596521,
+           1.0108412692092532,
+           0.9270642014339335,
+           0.852800274599014,
+           0.7889100856920663,
+           0.7359974709569218,
+           0.6944004687178925,
+           0.6641885689688681,
+           0.6451662592261374,
+           0.6368827240792765,
+           0.6386474079495487,
+           0.6495510103989911,
+           0.6684913543460597,
+           0.6942034528727377,
+           0.725293002730674,
+           0.7602724545191727,
+           0.7975987526789003,
+           0.8357118042539342,
+           0.8730727245898393,
+           0.9082009209436939,
+           0.9397091109850022,
+           0.9663354313912488,
+           0.9869718706658763,
+           1.00068835789621,
+           1.0067519529315017,
+           1.0046407105065895,
+           0.9940519279504965,
+           0.974904629843238,
+           0.9473362897022635,
+           0.9116939348094072,
+           0.8685199219714467,
+           0.8185328058001353,
+           0.7626038436622842,
+           0.7017297897361935,
+           0.6370027219291476,
+           0.5695777175035794,
+           0.500639244354186,
+           0.43136716373165673,
+           0.36290324613795205,
+           0.29631908501699755,
+           0.23258625320591636,
+           0.17254948593510058,
+           0.11690359304985909,
+           0.06617470415229511,
+           0.02070633605722843,
+           -0.019349354767221865,
+           -0.05403490802160528,
+           -0.08358539856542917,
+           -0.10842083728285835,
+           -0.12913333482376219,
+           -0.14646936639103791,
+           -0.16130760430954436,
+           -0.1746329018011203,
+           -0.18750711323335204,
+           -0.20103752050884985,
+           -0.21634370005662157,
+           -0.23452370840962616,
+           -0.2566204854690337,
+           -0.28358937269542467,
+           -0.31626761863706937,
+           -0.3553466969905759,
+           -0.4013481939382624,
+           -0.45460393350390405,
+           -0.515240904292214,
+           -0.5831714308455067,
+           -0.6580889009563271,
+           -0.7394692199108671,
+           -0.8265780173162031,
+           -0.918483485527803,
+           -1.0140745844249865,
+           -1.1120842090122431,
+           -1.2111167875422928,
+           -1.3096796618209903,
+           -1.4062175010128952,
+           -1.4991489181812823,
+           -1.5869043970808323,
+           -1.6679645969848333,
+           -1.740898086637632,
+           -1.8043975652723476,
+           -1.857313658934305,
+           -1.8986854334299692,
+           -1.927766839840283,
+           -1.94404840291933,
+           -1.947273574574032,
+           -1.9374493012788891,
+           -1.9148504926409475,
+           -1.8800182250172115,
+           -1.83375166550984,
+           -1.7770938541093104,
+           -1.7113116314756902,
+           -1.6378701431561722,
+           -1.5584024843973912,
+           -1.4746751698270952,
+           -1.388550216174367,
+           -1.3019447112891356,
+           -1.216788806885764,
+           -1.1349831140597604,
+           -1.058356498649954,
+           -0.9886252674576732,
+           -0.9273547062977366,
+           -0.8759238775386059,
+           -0.8354945094593014,
+           -0.8069847142163883,
+           -0.791048157780808,
+           -0.7880591766164273,
+           -0.7981041952476389,
+           -0.8209796496160112,
+           -0.8561964668819039,
+           -0.9029909968352007,
+           -0.9603421371199192,
+           -1.026994247768232,
+           -1.1014853136447809,
+           -1.1821796896452956,
+           -1.2673046558746943,
+           -1.3549899211531522,
+           -1.4433091452069813,
+           -1.5303225044256825,
+           -1.6141193041843025,
+           -1.6928596429401372,
+           -1.7648141595229332,
+           -1.8284009445672316,
+           -1.8822187686333571,
+           -1.9250758714388851,
+           -1.9560136664889978,
+           -1.9743248405279876,
+           -1.9795654645403107,
+           -1.9715608791195587,
+           -1.9504052682984223,
+           -1.9164549886728572,
+           -1.870315871110334,
+           -1.8128248568202057,
+           -1.7450264645534146,
+           -1.6681447078998244,
+           -1.5835511880980537,
+           -1.4927301758937923,
+           -1.3972415636655668,
+           -1.2986826146794597,
+           -1.1986494588827796,
+           -1.0986992836224119,
+           -1.0003141431821563,
+           -0.9048672637632389,
+           -0.81359265173499,
+           -0.7275587244419656,
+           -0.6476465768399067,
+           -0.57453337644625,
+           -0.5086812465925503,
+           -0.4503318571035039,
+           -0.39950679584835125,
+           -0.3560136477758648,
+           -0.31945756373658696,
+           -0.28925796322666586,
+           -0.264669886608052,
+           -0.24480939657447265,
+           -0.2286823285202122,
+           -0.21521560751023633,
+           -0.2032902877672917,
+           -0.19177543049686152,
+           -0.1795619184302288,
+           -0.16559531107498607,
+           -0.1489068731373822,
+           -0.12864195916329346,
+           -0.10408500882074906,
+           -0.07468049758121606,
+           -0.040049294538062365,
+           -3.9850789546107064e-16
+          ],
+          [
+           0,
+           0.04779580263408041,
+           0.1007090130060258,
+           0.1582560617046988,
+           0.2197804116085305,
+           0.2844707627503359,
+           0.3513836969716701,
+           0.41947016529032377,
+           0.4876051193000303,
+           0.5546195041228591,
+           0.6193337665860784,
+           0.6805919900393997,
+           0.7372957476658136,
+           0.7884367697996231,
+           0.8331275475946532,
+           0.8706290447466803,
+           0.9003747596620137,
+           0.9219904707360106,
+           0.9353091050235147,
+           0.9403802928708309,
+           0.9374743049862122,
+           0.9270802106063758,
+           0.9098982423101065,
+           0.8868265009516246,
+           0.8589422794181245,
+           0.8274784227998175,
+           0.7937952715900776,
+           0.7593488504403381,
+           0.725656064832208,
+           0.6942577492458323,
+           0.666680470905694,
+           0.6443980313914068,
+           0.6287936232821516,
+           0.6211235901081721,
+           0.6224837053504914,
+           0.633778830788035,
+           0.655696737437656,
+           0.6886867755045046,
+           0.7329439654897856,
+           0.7883989536596193,
+           0.8547141346014518,
+           0.9312860950143754,
+           1.0172543798356533,
+           1.111516428054483,
+           1.2127483748871355,
+           1.3194312730986977,
+           1.4298821527084968,
+           1.5422892184136947,
+           1.6547503807829158,
+           1.7653142331794889,
+           1.8720225235742753,
+           1.972953130483202,
+           2.0662625362368354,
+           2.150226799094961,
+           2.2232800581983154,
+           2.284049661248483,
+           2.3313870827966996,
+           2.364393899231304,
+           2.3824422026127188,
+           2.385188966606276,
+           2.3725840207286413,
+           2.3448714404827693,
+           2.302584317032032,
+           2.2465330270628163,
+           2.177787277589765,
+           2.0976523479229003,
+           2.007640088257957,
+           1.9094353580381822,
+           1.8048586943682237,
+           1.6958260887457342,
+           1.5843068170913945,
+           1.472280311902509,
+           1.361693085290353,
+           1.2544167072341579,
+           1.152207814739931,
+           1.056671075468286,
+           0.9692259551049471,
+           0.8910780431453375,
+           0.8231955792012575,
+           0.7662916942009254,
+           0.7208127410998824,
+           0.6869329413954735,
+           0.6645554204929544,
+           0.6533195505719457,
+           0.6526143678348274,
+           0.6615976855983774,
+           0.6792203891673548,
+           0.7042552761035159,
+           0.7353296993428164,
+           0.7709611831791446,
+           0.8095951155184441,
+           0.8496435755868992,
+           0.8895243354678085,
+           0.927699076878871,
+           0.9627098913281222,
+           0.9932131814589514,
+           1.0180101527012775,
+           1.0360731754415053,
+           1.0465674064752515,
+           1.0488671817523965,
+           1.0425668272421482,
+           1.0274856777339803,
+           1.0036672409496281,
+           0.9713725927663985,
+           0.9310682349238681,
+           0.8834087856641929,
+           0.829215002870061,
+           0.7694477551986889,
+           0.705178656586305,
+           0.6375581608432284,
+           0.567781973871916,
+           0.4970566798339884,
+           0.42656549343691313,
+           0.3574350430539331,
+           0.2907040588647893,
+           0.22729478742218964,
+           0.1679878803810461,
+           0.11340141246911799,
+           0.06397457450036673,
+           0.01995646412377038,
+           -0.018599736805056017,
+           -0.05183705044205743,
+           -0.0800894537854084,
+           -0.10387123398401747,
+           -0.12386123118714305,
+           -0.14088238596573086,
+           -0.1558771316688456,
+           -0.1698792816399524,
+           -0.1839831542168142,
+           -0.19931075250030925,
+           -0.21697786910215733,
+           -0.2380600170933532,
+           -0.2635590963562984,
+           -0.29437168925553,
+           -0.33125984133123293,
+           -0.3748251225103904,
+           -0.42548668360084735,
+           -0.4834639235801702,
+           -0.548764267878979,
+           -0.6211764293595766,
+           -0.7002693852133076,
+           -0.7853971580085038,
+           -0.875709341248684,
+           -0.9701671627612574,
+           -1.0675647367295986,
+           -1.1665550207997164,
+           -1.2656798718348474,
+           -1.3634034856738155,
+           -1.4581484154307132,
+           -1.5483332917836634,
+           -1.632411319182725,
+           -1.708908595270764,
+           -1.7764612977990555,
+           -1.8338508040880468,
+           -1.880035852198511,
+           -1.9141809194235033,
+           -1.935680080914813,
+           -1.9441757171276057,
+           -1.9395715607454602,
+           -1.9220397088713759,
+           -1.8920213712435394,
+           -1.8502212765116781,
+           -1.797595812481505,
+           -1.7353351289200158,
+           -1.6648395792542547,
+           -1.5876910166459752,
+           -1.5056195870447973,
+           -1.4204667737640977,
+           -1.334145542105201,
+           -1.2485985062335845,
+           -1.1657550920371575,
+           -1.0874886977653333,
+           -1.0155748581267972,
+           -0.9516513970746396,
+           -0.8971815101886977,
+           -0.8534206504201729,
+           -0.8213880025988185,
+           -0.8018432246445272,
+           -0.7952690094697287,
+           -0.8018598841088284,
+           -0.8215175150005484,
+           -0.8538526341632239,
+           -0.8981935439888178,
+           -0.9536010023554704,
+           -1.0188891385140186,
+           -1.0926519074168006,
+           -1.17329445929575,
+           -1.2590686855367437,
+           -1.3481121040430384,
+           -1.4384891696977198,
+           -1.5282340400900694,
+           -1.6153937946882644,
+           -1.6980710978682851,
+           -1.7744653128009613,
+           -1.8429111137130771,
+           -1.9019137074452295,
+           -1.9501798599402254,
+           -1.9866440272021153,
+           -2.010489010789749,
+           -2.0211606920694267,
+           -2.018376543936612,
+           -2.002127769967877,
+           -1.9726750752609867,
+           -1.9305382267759723,
+           -1.8764797100405552,
+           -1.8114829299854698,
+           -1.7367255329932683,
+           -1.6535485418348903,
+           -1.5634220922587123,
+           -1.4679086372521517,
+           -1.3686245405764554,
+           -1.267201013781614,
+           -1.1652453598122334,
+           -1.0643034713774806,
+           -0.9658244939301859,
+           -0.8711285024130152,
+           -0.7813779594666943,
+           -0.697553622652286,
+           -0.6204354519719611,
+           -0.5505889395318153,
+           -0.48835714384770096,
+           -0.43385856556307756,
+           -0.3869908528899505,
+           -0.3474401776236245,
+           -0.31469597981094,
+           -0.28807064463613236,
+           -0.2667235521820611,
+           -0.24968883248362056,
+           -0.235906067398582,
+           -0.22425310952338118,
+           -0.21358013842700263,
+           -0.20274404707658025,
+           -0.1906422471272802,
+           -0.1762450008063969,
+           -0.15862542891321946,
+           -0.13698640788674593,
+           -0.11068365232453294,
+           -0.079244380627897,
+           -0.04238107801364402,
+           -4.203848327372583e-16
+          ],
+          [
+           0,
+           0.0501047188903241,
+           0.10517721486040862,
+           0.16463846648027397,
+           0.22774425924349906,
+           0.2936061144955236,
+           0.3612163725519603,
+           0.42947676654470135,
+           0.4972297310087285,
+           0.5632916159872811,
+           0.626486925364666,
+           0.6856826685798882,
+           0.7398219086098019,
+           0.7879556063313066,
+           0.8292719016808032,
+           0.8631220344468296,
+           0.8890421905222055,
+           0.9067706609494309,
+           0.9162598185933117,
+           0.9176825478379864,
+           0.9114329030689672,
+           0.8981209183501837,
+           0.8785616399630132,
+           0.8537586015882822,
+           0.8248821051540121,
+           0.7932428051264895,
+           0.7602612168802458,
+           0.7274338776241721,
+           0.6962969784352137,
+           0.6683883559444037,
+           0.6452087803149343,
+           0.6281835010727814,
+           0.6186250133960803,
+           0.6176979845315597,
+           0.6263872335729831,
+           0.6454695889810066,
+           0.6754903585787533,
+           0.7167450384752052,
+           0.7692667630686827,
+           0.8328198609875682,
+           0.9068997348858734,
+           0.9907391300239478,
+           1.0833207012835846,
+           1.1833956345103789,
+           1.2895079296329537,
+           1.4000238135434444,
+           1.513165623686852,
+           1.6270493918489612,
+           1.7397252645257897,
+           1.849219823827372,
+           1.9535793229352607,
+           2.0509128239666468,
+           2.139434224386148,
+           2.217502180937147,
+           2.2836569869237686,
+           2.336653528457582,
+           2.3754895363218935,
+           2.3994284602102023,
+           2.408016418604335,
+           2.4010928174079877,
+           2.3787943802505174,
+           2.341552489486102,
+           2.2900838955410783,
+           2.2253750095510556,
+           2.1486601463553625,
+           2.0613942281814333,
+           1.9652205902755921,
+           1.8619346451412324,
+           1.7534442591339208,
+           1.6417277715879457,
+           1.5287906405701774,
+           1.4166217294867083,
+           1.3071502544013693,
+           1.2022043929590067,
+           1.10347251273951,
+           1.0124679107902246,
+           0.9304978686464983,
+           0.8586377205266061,
+           0.7977105092194484,
+           0.7482726675149802,
+           0.7106060162286469,
+           0.6847162165558437,
+           0.6703376584284854,
+           0.666944611561369,
+           0.6737683157663227,
+           0.689819545544337,
+           0.7139160543898938,
+           0.744714189804516,
+           0.7807438734852502,
+           0.8204460648472887,
+           0.8622117717730385,
+           0.9044216415177593,
+           0.9454851577314004,
+           0.9838784866675795,
+           1.0181800563385046,
+           1.0471030155491825,
+           1.0695238037610038,
+           1.0845061654353518,
+           1.0913200612739689,
+           1.0894550605936097,
+           1.078627940617727,
+           1.058784366173743,
+           1.0300946734401637,
+           0.9929439302302175,
+           0.9479165891049789,
+           0.8957761847895778,
+           0.8374406505545379,
+           0.7739539363599973,
+           0.7064547019658853,
+           0.6361429286567543,
+           0.5642453419910048,
+           0.4919805638821074,
+           0.4205249147510061,
+           0.35097976544135084,
+           0.28434129463913316,
+           0.22147344183738488,
+           0.16308476013228834,
+           0.1097097695290597,
+           0.061695292622023536,
+           0.01919212352128265,
+           -0.017847758938671205,
+           -0.04966836780116307,
+           -0.0767013552264483,
+           -0.09955235580680756,
+           -0.1189823902178811,
+           -0.1358848229702713,
+           -0.15125848492050548,
+           -0.16617767251258023,
+           -0.1817598188676602,
+           -0.1991316946937942,
+           -0.21939503793331283,
+           -0.24359252903710846,
+           -0.27267502326420123,
+           -0.3074709225540251,
+           -0.3486585179979046,
+           -0.39674206100684806,
+           -0.4520322287364897,
+           -0.5146315394839812,
+           -0.5844251493513615,
+           -0.6610773255813254,
+           -0.7440337480135527,
+           -0.8325296416904416,
+           -0.925603594486244,
+           -1.022116767494833,
+           -1.1207770664724401,
+           -1.2201677134154907,
+           -1.3187795416358183,
+           -1.4150462384197788,
+           -1.5073816790652126,
+           -1.5942184368522225,
+           -1.67404651687212,
+           -1.7454513486054093,
+           -1.8071500831099583,
+           -1.8580252754647908,
+           -1.8971550909297037,
+           -1.9238392527694896,
+           -1.937620048955373,
+           -1.9382978316020454,
+           -1.9259405741969746,
+           -1.900887194232782,
+           -1.863744499279077,
+           -1.815377769140398,
+           -1.756895141743934,
+           -1.6896261219690945,
+           -1.615094677032686,
+           -1.5349875157096569,
+           -1.4511182682891166,
+           -1.3653883867686099,
+           -1.2797456678189474,
+           -1.196141362428408,
+           -1.1164868743088787,
+           -1.0426110631348262,
+           -0.9762191581007491,
+           -0.9188542523365111,
+           -0.8718622902257283,
+           -0.8363613790197835,
+           -0.8132161552649712,
+           -0.803017817895362,
+           -0.806070306259642,
+           -0.8223829560849135,
+           -0.8516698129597936,
+           -0.8933556250705968,
+           -0.9465883784846209,
+           -1.0102580830956045,
+           -1.0830213692009225,
+           -1.16333131716836,
+           -1.2494718191115217,
+           -1.3395956649243645,
+           -1.431765458006088,
+           -1.5239964006390698,
+           -1.6142999468323993,
+           -1.7007273025121081,
+           -1.7814117596310535,
+           -1.8546088818882203,
+           -1.9187336144929272,
+           -1.9723934674082777,
+           -2.0144170188420083,
+           -2.043877101006254,
+           -2.0601081604892775,
+           -2.0627174277550204,
+           -2.051589680807401,
+           -2.026885543223581,
+           -1.9890334127638511,
+           -1.9387152697820562,
+           -1.8768467609467652,
+           -1.8045520897700384,
+           -1.7231343678192632,
+           -1.634042186291682,
+           -1.538833254310231,
+           -1.439136015780042,
+           -1.336610199382551,
+           -1.232907275299867,
+           -1.1296317871659864,
+           -1.028304498742345,
+           -0.9303282427126898,
+           -0.8369572851582456,
+           -0.7492709256161458,
+           -0.6681519415377021,
+           -0.5942703602718066,
+           -0.5280729045834683,
+           -0.46977831263541947,
+           -0.41937858396112493,
+           -0.37664605298882503,
+           -0.3411460448929843,
+           -0.3122547286197105,
+           -0.28918165234486937,
+           -0.270996330601586,
+           -0.2566581527354587,
+           -0.24504880167235135,
+           -0.23500631219823645,
+           -0.2253598605095212,
+           -0.21496436258907056,
+           -0.20273396830679688,
+           -0.1876735707511889,
+           -0.16890750530274268,
+           -0.14570468893276062,
+           -0.11749954519667319,
+           -0.0839081719584972,
+           -0.04473933418560194,
+           -4.4228406291887707e-16
+          ],
+          [
+           0,
+           0.05237357706344086,
+           0.10951785553221177,
+           0.17076139360012874,
+           0.23527695579734423,
+           0.3021050332875734,
+           0.3701811901334405,
+           0.4383665102864555,
+           0.5054803376156735,
+           0.5703344394772893,
+           0.6317676847348651,
+           0.6886803107965594,
+           0.7400668615868166,
+           0.7850469092644643,
+           0.8228927261931951,
+           0.8530531488454821,
+           0.8751729701165796,
+           0.8891073085849289,
+           0.8949305297852059,
+           0.892939432398685,
+           0.8836505579617137,
+           0.8677916325928331,
+           0.8462872995764058,
+           0.8202394486313943,
+           0.7909025876306296,
+           0.759654831880025,
+           0.7279652015381123,
+           0.6973580164132936,
+           0.6693752566924062,
+           0.6455378160800724,
+           0.6273066088435861,
+           0.6160445034101402,
+           0.6129800420920342,
+           0.6191738694631687,
+           0.6354887317159328,
+           0.662563827408058,
+           0.7007941883234682,
+           0.7503156501741136,
+           0.8109958394505805,
+           0.8824314581411434,
+           0.9639519958189541,
+           1.0546298424787022,
+           1.1532966193252883,
+           1.2585653923251419,
+           1.3688582884874307,
+           1.482438901130268,
+           1.5974487511212987,
+           1.7119469692277343,
+           1.8239522828096073,
+           1.9314863301964893,
+           2.0326172897185484,
+           2.12550279845832,
+           2.208431148690494,
+           2.2798597874152167,
+           2.3384502054951,
+           2.383098386224647,
+           2.412960086694177,
+           2.4274703465620076,
+           2.4263567548858305,
+           2.4096461531895113,
+           2.377664608374317,
+           2.3310306486477246,
+           2.270641915459764,
+           2.1976555406203957,
+           2.1134627065243046,
+           2.0196579851158565,
+           1.9180041745419372,
+           1.8103934583717327,
+           1.6988057982447948,
+           1.58526553476556,
+           1.471797211858271,
+           1.3603816556728134,
+           1.2529133301328519,
+           1.151159957595541,
+           1.0567253357030133,
+           0.971016201787398,
+           0.8952138961261947,
+           0.8302514574134853,
+           0.7767966509288543,
+           0.7352412853274943,
+           0.7056970213005873,
+           0.687997718316907,
+           0.6817082081081356,
+           0.6861392293600977,
+           0.7003681109895417,
+           0.723264655007727,
+           0.7535215476138838,
+           0.7896885217869892,
+           0.8302094087916599,
+           0.8734611517340055,
+           0.9177938131100777,
+           0.9615705911220658,
+           1.0032068667395022,
+           1.041207334792793,
+           1.074200326947552,
+           1.10096851078794,
+           1.120475245465611,
+           1.1318859879897107,
+           1.1345842723571624,
+           1.128181923112787,
+           1.1125233120726346,
+           1.0876836181441862,
+           1.0539612016427824,
+           1.0118643524456465,
+           0.9620928120498868,
+           0.9055145996031582,
+           0.8431387880248461,
+           0.7760849755560494,
+           0.7055502780196704,
+           0.6327747257756147,
+           0.5590059853945739,
+           0.48546433859164745,
+           0.41330883969415155,
+           0.343605538200183,
+           0.2772985957379465,
+           0.21518504844784128,
+           0.15789386849482073,
+           0.10586986456859547,
+           0.0593628337495234,
+           0.018422239254438796,
+           -0.01710245616499803,
+           -0.047555819341486893,
+           -0.07346500388622129,
+           -0.09552314410590032,
+           -0.11456802945164879,
+           -0.1315566271076718,
+           -0.1475361296169494,
+           -0.16361229643941497,
+           -0.18091593069735507,
+           -0.200568383229492,
+           -0.22364700413592264,
+           -0.2511514665108306,
+           -0.2839718678810727,
+           -0.3228594724451908,
+           -0.36840089257339687,
+           -0.42099642277921945,
+           -0.4808431356226523,
+           -0.5479232293361693,
+           -0.6219979843658522,
+           -0.7026075438067285,
+           -0.7890765844478503,
+           -0.8805257945503713,
+           -0.9758889253477308,
+           -1.0739350393385938,
+           -1.1732954433751084,
+           -1.2724946717510555,
+           -1.3699847770877822,
+           -1.464182097542037,
+           -1.5535056000151939,
+           -1.6364158524179064,
+           -1.7114536548785133,
+           -1.777277360736281,
+           -1.8326979432905517,
+           -1.8767109130424013,
+           -1.908524261434683,
+           -1.9275816991765948,
+           -1.9335805679163103,
+           -1.926483930619522,
+           -1.9065264854424506,
+           -1.874214096748977,
+           -1.8303168915667383,
+           -1.7758560264088485,
+           -1.712084384151605,
+           -1.6404616097380131,
+           -1.5626240331884875,
+           -1.4803501552841114,
+           -1.395522482194123,
+           -1.3100865874865941,
+           -1.226008351083476,
+           -1.145230373007621,
+           -1.0696285839876232,
+           -1.0009700744931358,
+           -0.9408731385332424,
+           -0.8907704791335669,
+           -0.8518764499804454,
+           -0.8251591140128473,
+           -0.8113177870100551,
+           -0.8107666051882927,
+           -0.8236245136070368,
+           -0.8497119202455838,
+           -0.8885541026320509,
+           -0.9393912937297009,
+           -1.0011952153036714,
+           -1.0726916740581542,
+           -1.1523886921681796,
+           -1.2386095129223744,
+           -1.3295297072215129,
+           -1.423217510430402,
+           -1.5176764438847352,
+           -1.610889223022719,
+           -1.7008619258929982,
+           -1.7856673923460895,
+           -1.863486845597511,
+           -1.9326487735009232,
+           -1.991664175639145,
+           -2.0392573725133145,
+           -2.074391682448074,
+           -2.0962893976276833,
+           -2.104445629828811,
+           -2.0986357454919813,
+           -2.0789162651080586,
+           -2.0456192596744587,
+           -1.9993404333296687,
+           -1.9409212323786889,
+           -1.8714254630864955,
+           -1.7921110303797805,
+           -1.7043975238097422,
+           -1.6098304730310649,
+           -1.510043170342875,
+           -1.4067170107287186,
+           -1.3015413290940054,
+           -1.1961737193877462,
+           -1.0922018009695709,
+           -0.991107354504258,
+           -0.8942336839823415,
+           -0.8027569748836648,
+           -0.7176623132421833,
+           -0.6397249091148574,
+           -0.5694969337768256,
+           -0.5073002362458664,
+           -0.45322505509712896,
+           -0.4071346897206237,
+           -0.3686759450006859,
+           -0.33729501861134453,
+           -0.3122583643353281,
+           -0.2926779414055756,
+           -0.2775401518993473,
+           -0.2657376783566458,
+           -0.25610336425887253,
+           -0.24744523248956107,
+           -0.23858171255091254,
+           -0.22837614668898568,
+           -0.2157696681518824,
+           -0.19981159093891118,
+           -0.1796865183861106,
+           -0.15473746601788513,
+           -0.12448440001574929,
+           -0.08863771370639403,
+           -0.04710629756707001,
+           -4.640365548799258e-16
+          ],
+          [
+           0,
+           0.05458419976227162,
+           0.11369556713851763,
+           0.17657419362191393,
+           0.2423153424127919,
+           0.3098954005948259,
+           0.37820128874637166,
+           0.4460625462318613,
+           0.5122852389843069,
+           0.5756867869699309,
+           0.635130781999988,
+           0.6895608638223737,
+           0.7380327435872598,
+           0.7797435083358512,
+           0.8140574070190808,
+           0.8405274060607718,
+           0.8589119084631093,
+           0.8691861522691879,
+           0.8715479388041567,
+           0.8664174851431646,
+           0.854431345089077,
+           0.8364304948217747,
+           0.8134428294818555,
+           0.7866604614901146,
+           0.7574123467277473,
+           0.7271328873816312,
+           0.6973272671744292,
+           0.6695343631184022,
+           0.6452881455787204,
+           0.6260785235444368,
+           0.6133126133792871,
+           0.6082774063452431,
+           0.612104782850037,
+           0.6257397702627479,
+           0.6499128674588003,
+           0.6851171647510482,
+           0.7315908748119139,
+           0.7893057613332811,
+           0.8579618106446891,
+           0.9369883407759418,
+           1.0255515862029325,
+           1.1225686385949194,
+           1.2267274681770626,
+           1.3365126006762993,
+           1.4502358849323753,
+           1.5660716595962885,
+           1.6820955170532261,
+           1.7963257715461043,
+           1.9067666687227873,
+           2.011452327245715,
+           2.1084903808802884,
+           2.196104292214486,
+           2.2726733368406102,
+           2.3367693088219617,
+           2.387189073346307,
+           2.422982188839736,
+           2.443472936160518,
+           2.448276224026745,
+           2.4373069843691773,
+           2.4107828253354757,
+           2.369219869463639,
+           2.313421866207073,
+           2.2444628276007967,
+           2.1636635895260974,
+           2.0725628450230724,
+           1.9728833269168695,
+           1.8664939314871087,
+           1.7553686702446412,
+           1.6415434107785478,
+           1.5270714183176388,
+           1.413978735902842,
+           1.3042204422766546,
+           1.1996388027640974,
+           1.1019242801604654,
+           1.012580301166433,
+           0.9328925810008507,
+           0.8639036967782451,
+           0.8063934718315882,
+           0.7608655915578222,
+           0.7275407200502813,
+           0.7063562294777737,
+           0.6969724947348133,
+           0.6987855482275569,
+           0.7109457376305162,
+           0.732381886759909,
+           0.7618303298329615,
+           0.7978680754685282,
+           0.8389492615830337,
+           0.8834439881296715,
+           0.9296785631771937,
+           0.9759761703215861,
+           1.0206969624676498,
+           1.0622766085992326,
+           1.0992623656586613,
+           1.1303458158703934,
+           1.1543914990019026,
+           1.170460776872459,
+           1.1778303911556696,
+           1.1760053120424423,
+           1.1647256211956643,
+           1.143967323968487,
+           1.1139371392747646,
+           1.0750614669535064,
+           1.0279698781776725,
+           0.9734736107905737,
+           0.9125396750216935,
+           0.8462612827748,
+           0.7758254029332419,
+           0.7024783136968391,
+           0.6274900691797958,
+           0.5521188202510767,
+           0.47757592836913926,
+           0.4049927860357675,
+           0.3353902091531237,
+           0.26965119628001866,
+           0.2084977593639849,
+           0.15247242229564048,
+           0.10192486035680617,
+           0.057004018456582,
+           0.017655902409355793,
+           -0.01637291094382652,
+           -0.04552614846408879,
+           -0.07042335073012328,
+           -0.09184040804262279,
+           -0.11068564334891082,
+           -0.12797207990240897,
+           -0.14478663203784528,
+           -0.16225703913076833,
+           -0.1815174235322002,
+           -0.20367339146668118,
+           -0.22976761056154923,
+           -0.26074678843572696,
+           -0.2974309438182789,
+           -0.34048580578868176,
+           -0.3903990993078615,
+           -0.44746137816138987,
+           -0.5117519521792682,
+           -0.5831303269824413,
+           -0.6612334347513438,
+           -0.7454787871181731,
+           -0.835073529951727,
+           -0.9290292283364506,
+           -1.0261820622608773,
+           -1.1252179731551917,
+           -1.2247021720054259,
+           -1.3231123046071278,
+           -1.4188744715402095,
+           -1.5104012221602778,
+           -1.5961305853364565,
+           -1.6745651663087,
+           -1.7443103298014333,
+           -1.8041105047283326,
+           -1.8528826851600368,
+           -1.889746264806944,
+           -1.9140484266163846,
+           -1.9253844131771318,
+           -1.9236121249489162,
+           -1.9088606289416734,
+           -1.8815323070494583,
+           -1.8422985272085193,
+           -1.792088878118886,
+           -1.7320741655674994,
+           -1.663643521540229,
+           -1.5883761225268782,
+           -1.5080081471121816,
+           -1.4243957217892518,
+           -1.3394747049715743,
+           -1.2552182398914837,
+           -1.1735930654278266,
+           -1.0965156084219485,
+           -1.025808890821578,
+           -0.9631612697448979,
+           -0.9100879886064265,
+           -0.8678964537216525,
+           -0.8376560648246729,
+           -0.8201733217542914,
+           -0.8159728057498142,
+           -0.8252844953425236,
+           -0.8480377270882856,
+           -0.8838619539956059,
+           -0.9320942932854123,
+           -0.9917936939931695,
+           -1.0617613978089804,
+           -1.1405672172676267,
+           -1.2265810175778167,
+           -1.3180086653668794,
+           -1.4129316023993657,
+           -1.509349117455608,
+           -1.605222327078739,
+           -1.6985188373183957,
+           -1.7872570448303813,
+           -1.8695490470420684,
+           -1.943641167254176,
+           -2.00795116060486,
+           -2.0611012492719185,
+           -2.1019462380846647,
+           -2.1295960823154387,
+           -2.1434324148440007,
+           -2.1431186867992986,
+           -2.1286037305686616,
+           -2.1001187129225274,
+           -2.058167605038532,
+           -2.0035114515290626,
+           -1.9371468683874173,
+           -1.8602793364670085,
+           -1.7742919793743606,
+           -1.680710619530967,
+           -1.581165991117147,
+           -1.4773540516258514,
+           -1.3709953733448652,
+           -1.263794611353032,
+           -1.1574010352646014,
+           -1.0533710782998664,
+           -0.9531338002158722,
+           -0.8579600816906315,
+           -0.7689362689513363,
+           -0.6869428712923455,
+           -0.6126387835883812,
+           -0.5464513642695467,
+           -0.4885725500538763,
+           -0.4389610357750572,
+           -0.3973503947298988,
+           -0.3632628659242458,
+           -0.3360283931348394,
+           -0.3148083703491708,
+           -0.2986234321314258,
+           -0.2863845286615542,
+           -0.27692644604131017,
+           -0.26904287489455786,
+           -0.2615220957037066,
+           -0.25318233853593486,
+           -0.24290588803961147,
+           -0.2296710414479648,
+           -0.21258108683512664,
+           -0.19088954948341436,
+           -0.16402105386503213,
+           -0.1315872648651055,
+           -0.09339750151250895,
+           -0.04946375633905382,
+           -4.854713071472521e-16
+          ],
+          [
+           0,
+           0.056718621464030616,
+           0.11767587801724162,
+           0.18202824608241866,
+           0.24879982996478,
+           0.31691056076119356,
+           0.385207446604952,
+           0.4524980418730439,
+           0.5175852433968797,
+           0.5793024849566577,
+           0.6365483883588122,
+           0.6883199405517371,
+           0.7337433012760032,
+           0.7721014038187226,
+           0.80285759111398,
+           0.8256746287235806,
+           0.8404285526699254,
+           0.8472169407663173,
+           0.8463613377280051,
+           0.8384037133978682,
+           0.8240969861399478,
+           0.8043897959996235,
+           0.7804058607561192,
+           0.7534183887497662,
+           0.7248201517890193,
+           0.6960899362431727,
+           0.6687561876777451,
+           0.6443587415949436,
+           0.6244095880013045,
+           0.6103536491844764,
+           0.6035305573702943,
+           0.6051384015844846,
+           0.6162003714085984,
+           0.6375351603505239,
+           0.6697319047823658,
+           0.7131303279141702,
+           0.7678066346470246,
+           0.8335655653908991,
+           0.9099388684059481,
+           0.9961902945700034,
+           1.0913270595134272,
+           1.1941175597090832,
+           1.3031149752671198,
+           1.4166862466651142,
+           1.5330457790498329,
+           1.650293109396172,
+           1.7664536716509232,
+           1.8795217155300137,
+           1.9875043778786516,
+           2.0884658728899477,
+           2.1805707598626407,
+           2.26212526480329,
+           2.33161567466306,
+           2.3877428893536625,
+           2.429452305333311,
+           2.455958313365142,
+           2.466762819404189,
+           2.4616673384084704,
+           2.4407783627818085,
+           2.404505866453133,
+           2.353554968408879,
+           2.2889109418632825,
+           2.211817913226876,
+           2.1237517447737577,
+           2.0263877327719215,
+           1.9215638754770892,
+           1.8112405698215024,
+           1.6974576793231675,
+           1.5822899766751373,
+           1.4678020011831971,
+           1.356003382832651,
+           1.2488056710243878,
+           1.1479816672919945,
+           1.0551281985720269,
+           0.9716331824121827,
+           0.8986477299801505,
+           0.8370639094867861,
+           0.7874986547016402,
+           0.7502841540120364,
+           0.7254648986272016,
+           0.712801407905858,
+           0.7117804893250258,
+           0.7216317342348482,
+           0.7413498020764572,
+           0.7697219087933146,
+           0.8053598130663611,
+           0.8467354897025675,
+           0.8922195955132519,
+           0.940121771334794,
+           0.9887317859167437,
+           1.036360514088324,
+           1.081379753159793,
+           1.1222599175521337,
+           1.1576047112017775,
+           1.1861819588027718,
+           1.206949878330642,
+           1.2190781959568293,
+           1.2219636374030816,
+           1.2152394736463628,
+           1.1987789500484167,
+           1.1726925826570869,
+           1.1373194597378526,
+           1.0932128366893898,
+           1.041120454635916,
+           0.9819601436372413,
+           0.9167913873748804,
+           0.8467836244939473,
+           0.7731821400859591,
+           0.6972724571730836,
+           0.6203441711379275,
+           0.5436551790593525,
+           0.46839724069322375,
+           0.3956637688150906,
+           0.3264206848544368,
+           0.2614810928023516,
+           0.20148442240129807,
+           0.14688057423841205,
+           0.09791946758349507,
+           0.05464624999576297,
+           0.01690227947512772,
+           -0.015668160979881728,
+           -0.043605606293646536,
+           -0.06761794438324414,
+           -0.08855821418841779,
+           -0.10739826152137921,
+           -0.12519895639734618,
+           -0.14307776629420046,
+           -0.16217455024945399,
+           -0.18361648703215686,
+           -0.2084830755805917,
+           -0.23777214681584538,
+           -0.272367802773787,
+           -0.3130111522973343,
+           -0.36027464344399257,
+           -0.4145407030018512,
+           -0.4759852853044798,
+           -0.5445668085917098,
+           -0.6200208205793755,
+           -0.7018605890989462,
+           -0.7893836623069318,
+           -0.881684289849072,
+           -0.9776714453514515,
+           -1.0760920455098297,
+           -1.1755588255288814,
+           -1.274582208161492,
+           -1.371605397231876,
+           -1.4650418390163593,
+           -1.553314128456417,
+           -1.6348933936233674,
+           -1.7083381723086524,
+           -1.7723317996480559,
+           -1.8257173552612946,
+           -1.8675292718471224,
+           -1.8970207832702546,
+           -1.9136864870952937,
+           -1.9172794119286332,
+           -1.9078221110215525,
+           -1.8856114471704448,
+           -1.8512168865106897,
+           -1.8054722765958746,
+           -1.7494612433032364,
+           -1.684496497686809,
+           -1.612093494044198,
+           -1.5339390204551069,
+           -1.4518554294164576,
+           -1.3677613257965744,
+           -1.283629619422861,
+           -1.2014439179438126,
+           -1.123154280437699,
+           -1.0506333724240604,
+           -0.9856340579214348,
+           -0.9297494340544321,
+           -0.8843762591334223,
+           -0.8506826473976338,
+           -0.8295808045862023,
+           -0.8217054605631083,
+           -0.8273985212199597,
+           -0.8467003150597019,
+           -0.8793476537859265,
+           -0.9247787646771362,
+           -0.9821449894395675,
+           -1.050328983571791,
+           -1.127968995947367,
+           -1.2134886640814382,
+           -1.3051316299006437,
+           -1.4010001669570515,
+           -1.4990969156788256,
+           -1.5973687507183032,
+           -1.6937517554904271,
+           -1.7862162547642295,
+           -1.8728108572414037,
+           -1.951704486375636,
+           -2.0212254285806797,
+           -2.079896502170035,
+           -2.126465546023181,
+           -2.1599305417140546,
+           -2.1795588138346735,
+           -2.1848998972723948,
+           -2.175791813710177,
+           -2.1523606588452258,
+           -2.1150135628575266,
+           -2.0644252455634273,
+           -2.001518540577199,
+           -1.9274394059472062,
+           -1.843527068651514,
+           -1.7512800638816377,
+           -1.6523190244740378,
+           -1.5483471489045135,
+           -1.4411093262115529,
+           -1.3323509219054614,
+           -1.2237772297971805,
+           -1.1170145708056884,
+           -1.0135739718494172,
+           -0.9148182871640944,
+           -0.8219335326472015,
+           -0.73590509345544,
+           -0.6574993388801239,
+           -0.5872510396871178,
+           -0.5254568351305294,
+           -0.47217484345048494,
+           -0.4272303546883131,
+           -0.3902273919726833,
+           -0.3605657808567239,
+           -0.3374632294675179,
+           -0.3199817985636169,
+           -0.3070580331452896,
+           -0.29753593867701233,
+           -0.2902019174359276,
+           -0.28382073563662225,
+           -0.2771715708734426,
+           -0.26908319254124596,
+           -0.2584673551098624,
+           -0.24434953469825,
+           -0.2258962119969146,
+           -0.20243799734589682,
+           -0.1734880043096836,
+           -0.1387550035747704,
+           -0.09815102623154388,
+           -0.05179323099789313,
+           -5.064170558417859e-16
+          ],
+          [
+           0,
+           0.05875927316336373,
+           0.12142557353803689,
+           0.1870774785381216,
+           0.254675049497862,
+           0.3230900679273443,
+           0.39113888259310703,
+           0.45761699090217284,
+           0.5213344310726827,
+           0.58115103823136,
+           0.6360106185024874,
+           0.6849731203491096,
+           0.7272439312875651,
+           0.7621994994176114,
+           0.7894085712220044,
+           0.8086484474984477,
+           0.8199157853346135,
+           0.8234316125677558,
+           0.8196403687102368,
+           0.8092029391652383,
+           0.7929838038580677,
+           0.772032573279483,
+           0.7475603305441171,
+           0.7209113337248971,
+           0.6935307549910619,
+           0.6669292388389989,
+           0.6426451482543133,
+           0.6222054327476549,
+           0.607086094164241,
+           0.5986732438503404,
+           0.5982257376451282,
+           0.6068403433461134,
+           0.6254203394796297,
+           0.6546483657023299,
+           0.6949642458405182,
+           0.746548386838385,
+           0.8093112235936747,
+           0.8828890340625388,
+           0.9666462946793571,
+           1.0596845868517324,
+           1.1608579049762582,
+           1.2687940590314601,
+           1.3819217142311317,
+           1.4985024701943293,
+           1.6166672560849107,
+           1.734456209331821,
+           1.8498611165822914,
+           1.9608694286995536,
+           2.065508818589683,
+           2.1618912325406483,
+           2.2482553930807643,
+           2.3230067439897737,
+           2.3847538852776897,
+           2.4323406263343386,
+           2.4648728871248906,
+           2.481739797817665,
+           2.482628483669653,
+           2.4675321710587528,
+           2.436751408623786,
+           2.390888360714641,
+           2.330834294797283,
+           2.2577505461022707,
+           2.1730433977184234,
+           2.078333458746527,
+           1.9754202535294187,
+           1.866242848194942,
+           1.7528374340387198,
+           1.637292858374252,
+           1.5217051406723285,
+           1.4081320339697585,
+           1.2985486881323,
+           1.1948054427175419,
+           1.098588723632766,
+           1.0113859408574641,
+           0.9344551861081808,
+           0.868800411897759,
+           0.8151526398771042,
+           0.7739575999342171,
+           0.7453700458608024,
+           0.7292548323021559,
+           0.7251946751292632,
+           0.7325043572909985,
+           0.7502509885289539,
+           0.7772797838128621,
+           0.812244695469356,
+           0.8536431208769649,
+           0.8998538140117914,
+           0.9491770572909664,
+           0.9998761017731617,
+           1.0502188599527111,
+           1.0985188366334961,
+           1.143174309575678,
+           1.1827048220421723,
+           1.2157841227021107,
+           1.2412687826826683,
+           1.258221832487877,
+           1.2659308901579156,
+           1.2639203931751835,
+           1.2519576966813728,
+           1.2300529557870103,
+           1.1984528662446579,
+           1.1576284916101833,
+           1.1082575523977747,
+           1.0512016899782493,
+           0.9874793416717961,
+           0.9182349705859221,
+           0.8447054816085079,
+           0.7681847214321283,
+           0.6899870039465156,
+           0.611410621757319,
+           0.5337022995418104,
+           0.45802351562071764,
+           0.3854195653037427,
+           0.31679216463735344,
+           0.25287629808303796,
+           0.19422190082312965,
+           0.14118083871362905,
+           0.09389950963331868,
+           0.05231724265967052,
+           0.016170519877632003,
+           -0.014997106453042272,
+           -0.04181967732369919,
+           -0.06508848845045884,
+           -0.08572729798796515,
+           -0.10476374533004691,
+           -0.12329774545181263,
+           -0.14246770327421723,
+           -0.16341545093604498,
+           -0.18725084614211362,
+           -0.21501698100474406,
+           -0.24765693769757444,
+           -0.2859829900990366,
+           -0.33064909032544415,
+           -0.38212739713235383,
+           -0.4406895016354575,
+           -0.5063928872027681,
+           -0.5790730276644203,
+           -0.6583413845005486,
+           -0.7435894130024824,
+           -0.833998533345115,
+           -0.9285558689376135,
+           -1.0260754052090328,
+           -1.1252240809059983,
+           -1.2245521946059392,
+           -1.3225273947701932,
+           -1.4175714251958802,
+           -1.508098721652376,
+           -1.5925559017800188,
+           -1.669461160405205,
+           -1.7374425771151005,
+           -1.7952743624534946,
+           -1.8419101130449862,
+           -1.8765122133160816,
+           -1.8984766106629596,
+           -1.9074522997736802,
+           -1.9033549777111294,
+           -1.8863744712363082,
+           -1.8569756882803157,
+           -1.8158930027689206,
+           -1.764118142298771,
+           -1.7028818075093959,
+           -1.6336294064555907,
+           -1.5579914330379807,
+           -1.4777491519808206,
+           -1.3947963706371738,
+           -1.3110981771139978,
+           -1.2286476023567925,
+           -1.1494212189444253,
+           -1.0753347200108063,
+           -1.0081995271231539,
+           -0.9496814559177756,
+           -0.9012624232592209,
+           -0.8642061106993849,
+           -0.8395284077093517,
+           -0.8279733467297096,
+           -0.8299951132204172,
+           -0.8457465707062635,
+           -0.8750745867787963,
+           -0.9175222848694488,
+           -0.9723381822671886,
+           -1.0384920113136449,
+           -1.1146968619473199,
+           -1.1994371336490903,
+           -1.291001647014934,
+           -1.387521143000291,
+           -1.4870092943114919,
+           -1.587406270975039,
+           -1.686623842790357,
+           -1.7825909665923632,
+           -1.8732987968442933,
+           -1.9568440742516313,
+           -2.031469888413759,
+           -2.095602875972555,
+           -2.147886003648922,
+           -2.1872061938026066,
+           -2.212716176034301,
+           -2.2238500887709045,
+           -2.220332506280359,
+           -2.202180725430443,
+           -2.169700308840013,
+           -2.123474042896021,
+           -2.0643446264692202,
+           -1.9933915552162615,
+           -1.9119028034780599,
+           -1.8213420276461734,
+           -1.7233121185254852,
+           -1.6195160131823363,
+           -1.5117157370571006,
+           -1.401690683327899,
+           -1.2911961478239957,
+           -1.1819231240065964,
+           -1.0754603240855238,
+           -0.9732593302562804,
+           -0.8766036959401761,
+           -0.7865827129486342,
+           -0.704070439318197,
+           -0.6297104472423599,
+           -0.5639066044718771,
+           -0.5068200494374229,
+           -0.45837236400610737,
+           -0.4182547921258667,
+           -0.38594320152396133,
+           -0.3607183428697326,
+           -0.3416908299334103,
+           -0.3278301485147709,
+           -0.31799690413557197,
+           -0.31097744109090897,
+           -0.3055199103252931,
+           -0.3003708320666896,
+           -0.2943111919497654,
+           -0.2861911266108706,
+           -0.27496229595066535,
+           -0.2597071033443097,
+           -0.23966401036880539,
+           -0.2142482969173949,
+           -0.1830677382109211,
+           -0.14593280411698356,
+           -0.10286112993985912,
+           -0.054076157792696054,
+           -5.267040044605034e-16
+          ],
+          [
+           0,
+           0.06068916492045286,
+           0.12491304779147933,
+           0.19167886478932714,
+           0.2598904658946378,
+           0.32838037654703417,
+           0.3959439787430066,
+           0.4613749178980982,
+           0.5235007880272631,
+           0.5812181383146405,
+           0.6335258592096876,
+           0.6795560454462715,
+           0.7186014958708864,
+           0.7501390941357722,
+           0.773848418065111,
+           0.7896250462452187,
+           0.7975881650995995,
+           0.7980822250084397,
+           0.7916725462700718,
+           0.7791349310495955,
+           0.7614394920033941,
+           0.7397290581072236,
+           0.7152926595605222,
+           0.6895347229069173,
+           0.6639407214127127,
+           0.6400401213715601,
+           0.6193675398960221,
+           0.6034230819701272,
+           0.5936328526884886,
+           0.5913106439121913,
+           0.5976217728627843,
+           0.6135500039098716,
+           0.6398684150545569,
+           0.6771149790270229,
+           0.7255735177054213,
+           0.7852605604216263,
+           0.8559184947705073,
+           0.9370152462564016,
+           1.0277505642306235,
+           1.1270688300062999,
+           1.2336781427659018,
+           1.3460752838633194,
+           1.4625760142055662,
+           1.5813500262016218,
+           1.7004597546032223,
+           1.8179021523611762,
+           1.931652460845555,
+           2.0397089503698544,
+           2.140137578286899,
+           2.23111550875035,
+           2.31097246069635,
+           2.378228898201581,
+           2.431630149004514,
+           2.4701756309320406,
+           2.493142480000007,
+           2.5001030053042115,
+           2.4909355413114267,
+           2.465828424271206,
+           2.425276982408961,
+           2.3700735953691034,
+           2.3012910430215086,
+           2.2202595232192617,
+           2.1285378685196776,
+           2.027879629593718,
+           1.9201948147016208,
+           1.8075081772480626,
+           1.6919150245578916,
+           1.5755355786692895,
+           1.460468952736653,
+           1.3487478137907982,
+           1.2422947839680123,
+           1.1428815883721282,
+           1.0520918895748042,
+           0.9712886580807055,
+           0.9015868171274306,
+           0.8438317716922527,
+           0.7985842887011926,
+           0.7661120416932553,
+           0.7463879723568041,
+           0.7390954573683745,
+           0.7436401058399653,
+           0.759167854404547,
+           0.7845888774007195,
+           0.818606692394696,
+           0.8597517197287929,
+           0.9064184518462431,
+           0.9569053062833748,
+           1.0094561773887696,
+           1.0623026673993905,
+           1.113705968244657,
+           1.161997381507413,
+           1.2056165048643883,
+           1.2431461779654231,
+           1.273343367410386,
+           1.2951652770245956,
+           1.307790093308376,
+           1.3106319136170212,
+           1.3033495528459278,
+           1.2858490794295636,
+           1.2582800894297483,
+           1.2210258844405164,
+           1.1746878710606676,
+           1.120064642998706,
+           1.0581263379216745,
+           0.9899849766962944,
+           0.9168615898488317,
+           0.8400510125047764,
+           0.7608852828996266,
+           0.6806966094862019,
+           0.6007808770108406,
+           0.5223626426171475,
+           0.44656252960665965,
+           0.3743678600901228,
+           0.30660728012556243,
+           0.24393002431553668,
+           0.18679034395599337,
+           0.13543748682915707,
+           0.08991147107533926,
+           0.05004474396676618,
+           0.015469662690159586,
+           -0.014368417675340521,
+           -0.04019281006885833,
+           -0.06287241324236464,
+           -0.08339450351357566,
+           -0.10283413064940918,
+           -0.12232093742231534,
+           -0.14300429074925522,
+           -0.1660176579418685,
+           -0.19244318329287702,
+           -0.22327741742665566,
+           -0.2593991245965827,
+           -0.3015400420794676,
+           -0.35025939225889985,
+           -0.4059228537341198,
+           -0.4686865851909484,
+           -0.5384867676433124,
+           -0.6150349902084181,
+           -0.6978196553409712,
+           -0.786113425173086,
+           -0.8789865751705099,
+           -0.9753259686419685,
+           -1.0738592195838819,
+           -1.1731834756053934,
+           -1.2717981307052042,
+           -1.368140672571006,
+           -1.4606247835365334,
+           -1.5476797505699373,
+           -1.627790199348864,
+           -1.6995351516903987,
+           -1.7616254148247557,
+           -1.812938345085211,
+           -1.852549086768079,
+           -1.8797574678279538,
+           -1.8941098357792465,
+           -1.8954152372173674,
+           -1.8837554798329337,
+           -1.8594887633616322,
+           -1.8232467219744921,
+           -1.775924881333287,
+           -1.7186666949545122,
+           -1.6528414826579754,
+           -1.5800167448104525,
+           -1.5019254660682773,
+           -1.4204291478954978,
+           -1.3374774171554238,
+           -1.255065145838996,
+           -1.1751880822935254,
+           -1.0997980354903836,
+           -1.030758669850361,
+           -0.9698029584803234,
+           -0.9184933075436242,
+           -0.8781853046943078,
+           -0.8499959614646474,
+           -0.8347772151910726,
+           -0.8330953330051902,
+           -0.8452167215758066,
+           -0.8711004950271787,
+           -0.910397993447393,
+           -0.9624592795257094,
+           -1.026346475127292,
+           -1.1008536370598208,
+           -1.1845327158642365,
+           -1.2757249969540758,
+           -1.3725972933495674,
+           -1.4731820467674066,
+           -1.5754204016666058,
+           -1.6772072472491049,
+           -1.7764371770531382,
+           -1.871050295743935,
+           -1.959076808468487,
+           -2.038679359532487,
+           -2.1081921433869053,
+           -2.166155890578209,
+           -2.2113479324470395,
+           -2.242806668458886,
+           -2.2598498961571654,
+           -2.2620866124969505,
+           -2.2494220530920925,
+           -2.222055898819929,
+           -2.1804737432862127,
+           -2.125432075846478,
+           -2.057937189274077,
+           -1.9792185649989922,
+           -1.89069741862139,
+           -1.7939512009881682,
+           -1.690674942797817,
+           -1.5826404012532531,
+           -1.4716540140479508,
+           -1.3595146878729985,
+           -1.2479724452129066,
+           -1.1386889246238325,
+           -1.033200676749191,
+           -0.9328861224150076,
+           -0.838936942217667,
+           -0.7523345515423138,
+           -0.6738321838587661,
+           -0.6039429617413349,
+           -0.5429341829556452,
+           -0.4908278919638721,
+           -0.44740764924751825,
+           -0.4122312558761309,
+           -0.38464904262128796,
+           -0.3638271953084576,
+           -0.3487754644252639,
+           -0.3383785003190182,
+           -0.33142996824382787,
+           -0.3266685321874894,
+           -0.3228147544020589,
+           -0.31860793987376174,
+           -0.3128419619811551,
+           -0.3043991370686798,
+           -0.29228127075583793,
+           -0.2756370760690785,
+           -0.2537852609273414,
+           -0.22623269763268097,
+           -0.1926872168718894,
+           -0.15306471001393473,
+           -0.10749037259707325,
+           -0.05629407505042415,
+           -5.461655573554045e-16
+          ],
+          [
+           0,
+           0.062492064358746,
+           0.12810864235706015,
+           0.19579289683717777,
+           0.2644009479654487,
+           0.3327354677063274,
+           0.3995809153808323,
+           0.4637394709247685,
+           0.5240667024476263,
+           0.5795060093911754,
+           0.62912091190168,
+           0.6721243102454664,
+           0.7079039138958434,
+           0.736043136411774,
+           0.7563368670040372,
+           0.7688016598688181,
+           0.7736800246964058,
+           0.7714386526588858,
+           0.762760567849702,
+           0.7485313506682671,
+           0.7298197330651875,
+           0.7078530120098462,
+           0.6839878633017225,
+           0.659677259470683,
+           0.6364342998976247,
+           0.6157938457588285,
+           0.5992729147715774,
+           0.5883308293591818,
+           0.5843301257144072,
+           0.5884992198916579,
+           0.6018977906984871,
+           0.6253857786084941,
+           0.6595968166074266,
+           0.7049168048092496,
+           0.7614682183571447,
+           0.8291006005334031,
+           0.9073875435054608,
+           0.9956303013997279,
+           1.092868018299711,
+           1.197894391306312,
+           1.3092804299900787,
+           1.425402822339712,
+           1.5444772774216318,
+           1.6645960898924548,
+           1.783769064371984,
+           1.8999668511741583,
+           2.0111656811892935,
+           2.115392448436891,
+           2.2107690749892974,
+           2.2955551050030034,
+           2.3681875122511125,
+           2.4273167679622087,
+           2.471838301462576,
+           2.5009185930417637,
+           2.5140152640434326,
+           2.5108906703910843,
+           2.49161865917191,
+           2.456584309799628,
+           2.4064766477255586,
+           2.3422744856189652,
+           2.2652257103306184,
+           2.176820489810652,
+           2.078759018679075,
+           1.9729145508272299,
+           1.8612925791065158,
+           1.745987113122695,
+           1.6291350741935522,
+           1.5128698699990974,
+           1.3992752293139994,
+           1.2903403690452244,
+           1.1879175318257031,
+           1.0936828734903665,
+           1.0091015973477462,
+           0.9353981282962535,
+           0.8735319970804537,
+           0.8241799663606806,
+           0.7877247791859131,
+           0.7642507506232992,
+           0.7535462586256078,
+           0.7551130247410494,
+           0.7681819130324584,
+           0.7917348205327611,
+           0.82453208849519,
+           0.8651447340976214,
+           0.9119906902656584,
+           0.9633741495844632,
+           1.0175270390649314,
+           1.0726516074468213,
+           1.1269630867928178,
+           1.1787313957628252,
+           1.2263208829344396,
+           1.2682271640049092,
+           1.3031101852194387,
+           1.329822744900757,
+           1.3474338229697576,
+           1.3552462018583444,
+           1.3528080078576268,
+           1.3399179560578507,
+           1.316624240759374,
+           1.2832171725991404,
+           1.2402158196699857,
+           1.1883490587278784,
+           1.1285315804904446,
+           1.0618355166143723,
+           0.9894584621497142,
+           0.9126887534962019,
+           0.8328689260254992,
+           0.7513583160354969,
+           0.6694957876146017,
+           0.5885635559790396,
+           0.5097530451938864,
+           0.43413366080516513,
+           0.3626252782966168,
+           0.29597514849745693,
+           0.2347398036671901,
+           0.17927241597076016,
+           0.12971591679653174,
+           0.08600203450478022,
+           0.04785625355801216,
+           0.014808543500846807,
+           -0.013790444155502641,
+           -0.038748155617172,
+           -0.061004466563010694,
+           -0.08160225768311803,
+           -0.10165502415078231,
+           -0.12231238734491746,
+           -0.14472443304451685,
+           -0.17000583252839802,
+           -0.19920071069881914,
+           -0.23324920829017814,
+           -0.27295664383106083,
+           -0.31896611631964394,
+           -0.3717353031573176,
+           -0.4315181019198455,
+           -0.49835164168028434,
+           -0.5720490529126353,
+           -0.6521982379306187,
+           -0.7381667300490315,
+           -0.8291125730665848,
+           -0.9240009972065414,
+           -1.0216265172409371,
+           -1.1206399369721287,
+           -1.219579615142519,
+           -1.3169062344759275,
+           -1.4110402208201642,
+           -1.500400885697799,
+           -1.5834463148968636,
+           -1.6587129993900616,
+           -1.7248542036010506,
+           -1.780676089955013,
+           -1.8251706672466332,
+           -1.8575447025034886,
+           -1.8772438299994876,
+           -1.883971204617049,
+           -1.8777001771118234,
+           -1.8586806128196145,
+           -1.827438629435737,
+           -1.7847696899075167,
+           -1.7317251492611132,
+           -1.6695925153167932,
+           -1.599869838746715,
+           -1.5242347939417593,
+           -1.4445091450503942,
+           -1.3626194080214198,
+           -1.2805546166110862,
+           -1.2003221756618507,
+           -1.1239028366160724,
+           -1.0532058568648937,
+           -0.990025405434683,
+           -0.9359992525985922,
+           -0.8925707308202615,
+           -0.8609548801645188,
+           -0.8421095947131586,
+           -0.8367124699200884,
+           -0.8451439170410211,
+           -0.867476963014461,
+           -0.9034739960352663,
+           -0.9525905523886923,
+           -1.0139860729043138,
+           -1.0865413917128681,
+           -1.1688825598768637,
+           -1.2594104558152526,
+           -1.356335496920787,
+           -1.4577166457218134,
+           -1.5615038023122298,
+           -1.6655825950314094,
+           -1.7678205254524513,
+           -1.8661133929803417,
+           -1.958430919503192,
+           -2.0428605156775967,
+           -2.117648177023449,
+           -2.181235568893234,
+           -2.2322924528088066,
+           -2.269743720318927,
+           -2.2927904316231764,
+           -2.300924401507944,
+           -2.2939360310798085,
+           -2.271915246535747,
+           -2.235245571791826,
+           -2.1845915261523077,
+           -2.120879697326121,
+           -2.045273990109154,
+           -1.959145688301782,
+           -1.8640390885947404,
+           -1.76163356730857,
+           -1.653703021561886,
+           -1.5420736837554823,
+           -1.428581340856117,
+           -1.3150289971228672,
+           -1.2031460005463077,
+           -1.094549609903821,
+           -0.9907099121274157,
+           -0.8929189103750519,
+           -0.8022644940778463,
+           -0.7196098760737758,
+           -0.6455789419212509,
+           -0.5805478061365846,
+           -0.5246427131901692,
+           -0.47774426155381794,
+           -0.43949777089993003,
+           -0.4093294596523545,
+           -0.3864679562798779,
+           -0.3699705365715653,
+           -0.358753363880817,
+           -0.3516249128106139,
+           -0.34732168140046366,
+           -0.3445452443982432,
+           -0.3419996719124922,
+           -0.3384283342895918,
+           -0.33264913546923225,
+           -0.3235872627409184,
+           -0.3103046095463392,
+           -0.2920251179632411,
+           -0.2681553964495394,
+           -0.23830009353283724,
+           -0.20227164620756283,
+           -0.16009416933437545,
+           -0.11200140557426015,
+           -0.05842881044232306,
+           -5.646400386019638e-16
+          ],
+          [
+           0,
+           0.06415266919313417,
+           0.1309849684632714,
+           0.1993840253673602,
+           0.2681672885702888,
+           0.336117404088277,
+           0.40201821149324973,
+           0.4646908948345665,
+           0.5230293171776443,
+           0.5760335867313078,
+           0.6228409460767765,
+           0.6627531429440193,
+           0.695259529638653,
+           0.7200552463890117,
+           0.7370539688493584,
+           0.7463948386265339,
+           0.7484433445110038,
+           0.7437860773458334,
+           0.7332194392479694,
+           0.7177325442249881,
+           0.6984846981569639,
+           0.6767779878157326,
+           0.654025637475595,
+           0.6317169044480538,
+           0.6113793786632943,
+           0.594539623807166,
+           0.5826831466194481,
+           0.5772147054605583,
+           0.5794199684647685,
+           0.590429505453565,
+           0.6111860468507708,
+           0.642415868308413,
+           0.6846050633968723,
+           0.7379813508597073,
+           0.802501930398253,
+           0.8778477549703617,
+           0.9634244317395603,
+           1.0583698019266634,
+           1.1615680858849768,
+           1.271670317791855,
+           1.3871206384321175,
+           1.5061878685109902,
+           1.6270016524083404,
+           1.747592346577977,
+           1.865933730803134,
+           1.979987546658575,
+           2.0877488176765597,
+           2.18729088115534,
+           2.276809062951504,
+           2.35466195399006,
+           2.4194092999978567,
+           2.4698455928813425,
+           2.505028551398099,
+           2.5243017979319853,
+           2.5273111744006758,
+           2.5140142903067972,
+           2.4846830560533197,
+           2.439899120992655,
+           2.3805423042227765,
+           2.3077722727820866,
+           2.2230038825711036,
+           2.1278767481308747,
+           2.0242197446633603,
+           1.9140112660462787,
+           1.799336163145853,
+           1.682340365021883,
+           1.5651842397523912,
+           1.4499957802729309,
+           1.3388247031457328,
+           1.2335985245035124,
+           1.1360816281506803,
+           1.0478382671758801,
+           0.9702003442545465,
+           0.90424069947055,
+           0.8507525008243703,
+           0.8102351849071325,
+           0.7828872371287782,
+           0.7686059362703087,
+           0.7669940210137193,
+           0.7773730705742969,
+           0.7988032316581385,
+           0.8301087735880167,
+           0.8699088162372522,
+           0.9166524547077873,
+           0.9686574033963734,
+           1.0241512026399313,
+           1.0813139754023489,
+           1.1383216907568365,
+           1.193388885906913,
+           1.2448098192153738,
+           1.2909970725797966,
+           1.330516691288851,
+           1.3621190414125457,
+           1.3847646764723283,
+           1.3976446337720694,
+           1.4001947231014853,
+           1.3921035229713767,
+           1.3733139582836387,
+           1.344018494408728,
+           1.3046481420215155,
+           1.2558556207656726,
+           1.1984931740599822,
+           1.1335856585541952,
+           1.0622996466476513,
+           0.9859093762744466,
+           0.9057604564914284,
+           0.8232322884775701,
+           0.7397001881485689,
+           0.6564981981070176,
+           0.574883553113531,
+           0.49600371533303317,
+           0.4208668245491039,
+           0.35031631619215736,
+           0.28501034877092096,
+           0.2254065549792335,
+           0.1717524906200976,
+           0.124082006113508,
+           0.08221761052966522,
+           0.04577874174517669,
+           0.01419570242180189,
+           -0.013271126043316744,
+           -0.037507316910714524,
+           -0.05951632804261776,
+           -0.08038808478630406,
+           -0.10126505993413339,
+           -0.12330676098462857,
+           -0.1476535776696854,
+           -0.1753909610108514,
+           -0.20751489854161506,
+           -0.24489961892951576,
+           -0.28826840382277685,
+           -0.3381683067073737,
+           -0.39494947983939965,
+           -0.4587496933844905,
+           -0.529484498681802,
+           -0.6068433433741366,
+           -0.6902917936322119,
+           -0.7790798616891734,
+           -0.87225627934894,
+           -0.9686884040165826,
+           -1.0670872970188452,
+           -1.1660373782591276,
+           -1.2640299400341344,
+           -1.3594996992225057,
+           -1.4508634836981327,
+           -1.5365600878791374,
+           -1.6150902953992181,
+           -1.6850560549844704,
+           -1.7451978091177245,
+           -1.7944290137212213,
+           -1.8318669500074467,
+           -1.8568590153501303,
+           -1.8690037864550035,
+           -1.8681662726846893,
+           -1.8544869170786087,
+           -1.8283840539889706,
+           -1.7905496916117638,
+           -1.7419386511045807,
+           -1.6837512574193592,
+           -1.6174099363961414,
+           -1.5445302241131045,
+           -1.4668868342064243,
+           -1.3863755533805742,
+           -1.3049718415143867,
+           -1.2246870979650608,
+           -1.147523617728626,
+           -1.0754292984444633,
+           -1.0102531708540423,
+           -0.9537028108904635,
+           -0.9073046513780867,
+           -0.8723681462863109,
+           -0.8499546521457524,
+           -0.8408517817116891,
+           -0.8455538568832209,
+           -0.864248944351577,
+           -0.8968128019333067,
+           -0.942809899817747,
+           -1.00150151300113,
+           -1.0718607130772173,
+           -1.1525939233972726,
+           -1.2421685453977818,
+           -1.3388460194259484,
+           -1.4407195541890403,
+           -1.5457556481578023,
+           -1.651838436561493,
+           -1.756815831199775,
+           -1.8585463787719765,
+           -1.954945747785854,
+           -2.0440317647184427,
+           -2.123966956683423,
+           -2.1930976194966156,
+           -2.249988515197361,
+           -2.2934524096754654,
+           -2.3225737864456257,
+           -2.3367262137208926,
+           -2.335582995297809,
+           -2.319120897617676,
+           -2.28761691174603,
+           -2.2416381758458974,
+           -2.1820253469347035,
+           -2.1098698663302704,
+           -2.026485707421667,
+           -1.9333763237464023,
+           -1.8321976266892135,
+           -1.7247179127617576,
+           -1.6127757282136506,
+           -1.4982367020684095,
+           -1.382950396582975,
+           -1.268708216237646,
+           -1.1572033829524986,
+           -1.0499939272048047,
+           -0.948469563604489,
+           -0.8538232173540349,
+           -0.7670278474742659,
+           -0.6888190767664871,
+           -0.6196839906281401,
+           -0.5598563107548001,
+           -0.5093179893535962,
+           -0.4678071087681273,
+           -0.4348318143780278,
+           -0.40968985919137285,
+           -0.3914932004020834,
+           -0.3791969647541116,
+           -0.3716319938818583,
+           -0.36754009547485145,
+           -0.3656110632231729,
+           -0.3645204895524385,
+           -0.3629673810655378,
+           -0.3597105976607499,
+           -0.3536031721498246,
+           -0.34362362689153664,
+           -0.328903485925635,
+           -0.30875028322224096,
+           -0.28266548733160163,
+           -0.25035689687108315,
+           -0.21174520650157463,
+           -0.1669645956309538,
+           -0.11635734816261367,
+           -0.06046266722221511,
+           -5.819723779827007e-16
+          ],
+          [
+           0,
+           0.06565677192051401,
+           0.13351720900621417,
+           0.20242106385631836,
+           0.2711566688757497,
+           0.3384968071410374,
+           0.40323516383192315,
+           0.46422237929721705,
+           0.5204007334036048,
+           0.5708365243253961,
+           0.6147492625448419,
+           0.6515368811121112,
+           0.6807962641546964,
+           0.7023385146991824,
+           0.716198517086206,
+           0.7226384952496797,
+           0.7221454222212573,
+           0.7154222945292372,
+           0.7033734436945766,
+           0.687084211780564,
+           0.667795465010486,
+           0.6468735550992282,
+           0.6257764586999794,
+           0.6060169281624352,
+           0.5891235689943632,
+           0.5766008188849525,
+           0.5698888383211687,
+           0.5703243327467202,
+           0.5791033105454975,
+           0.5972467401840225,
+           0.6255700045584822,
+           0.6646569625083318,
+           0.7148393186987574,
+           0.776181876276567,
+           0.8484741049612297,
+           0.9312283040163568,
+           1.0236844786213848,
+           1.1248218834929753,
+           1.2333770232569647,
+           1.3478677391118676,
+           1.4666228597217437,
+           1.5878167547989075,
+           1.7095080059633818,
+           1.829681304295155,
+           1.9462916001711,
+           2.0573094706228927,
+           2.160766634112879,
+           2.2548005332353953,
+           2.337696922707759,
+           2.4079294427689337,
+           2.464195225767733,
+           2.5054456746956726,
+           2.5309116645263465,
+           2.540122547765604,
+           2.532918491441158,
+           2.509455830334198,
+           2.4702052867549145,
+           2.415943076566505,
+           2.3477350903471943,
+           2.2669145034283438,
+           2.17505332504411,
+           2.073928541161848,
+           1.9654836342168587,
+           1.8517863728171458,
+           1.7349838528408206,
+           1.6172558360736724,
+           1.5007674720590323,
+           1.3876225022049196,
+           1.2798180321042882,
+           1.1792019188097105,
+           1.087433755440955,
+           1.0059503475841725,
+           0.935936466632271,
+           0.8783015372069085,
+           0.8336627722383311,
+           0.8023351136828333,
+           0.7843281730423664,
+           0.7793501978271853,
+           0.7868189219782014,
+           0.8058789941453925,
+           0.8354255216018993,
+           0.8741331232568147,
+           0.9204897562131072,
+           0.972834469718126,
+           1.0293981508309322,
+           1.0883462598179192,
+           1.1478225117440246,
+           1.2059924448958346,
+           1.2610858268634524,
+           1.3114368849853852,
+           1.3555214084564573,
+           1.3919898531355883,
+           1.4196956848219582,
+           1.4377183198335015,
+           1.4453801600117073,
+           1.442257369311698,
+           1.4281841971536111,
+           1.4032508157578918,
+           1.36779480071945,
+           1.3223865420596388,
+           1.2678090230062937,
+           1.2050325420734427,
+           1.1351850772261545,
+           1.0595190959887606,
+           0.9793756997119788,
+           0.8961470518046906,
+           0.8112380770807525,
+           0.7260284316010528,
+           0.6418357292673337,
+           0.5598809733434045,
+           0.4812570790630311,
+           0.4069012891518326,
+           0.3375721796206757,
+           0.27383183126058397,
+           0.21603360599915666,
+           0.164315820137926,
+           0.118601452220523,
+           0.07860386579998803,
+           0.04383837067480622,
+           0.013639294219126463,
+           -0.012817908907107245,
+           -0.03649011148649608,
+           -0.05843625127644776,
+           -0.07978416677192687,
+           -0.10169542273789457,
+           -0.12532907028004464,
+           -0.15180531521029397,
+           -0.18217007246207018,
+           -0.21736136320144078,
+           -0.25817846557775986,
+           -0.30525466089603925,
+           -0.3590343260985292,
+           -0.4197550130898406,
+           -0.4874350283952481,
+           -0.5618668860955434,
+           -0.6426168564676412,
+           -0.7290306760668532,
+           -0.8202453260639249,
+           -0.9152066285091736,
+           -1.0126922588103526,
+           -1.1113396309155685,
+           -1.2096779830893198,
+           -1.3061638800353368,
+           -1.3992192543255628,
+           -1.4872710390319779,
+           -1.5687913959800868,
+           -1.6423375214166576,
+           -1.7065900137576853,
+           -1.7603888164688348,
+           -1.8027658024051596,
+           -1.8329731428538651,
+           -1.8505067032447151,
+           -1.8551238256317453,
+           -1.8468549927329965,
+           -1.8260090162495053,
+           -1.7931715497417042,
+           -1.7491968896440553,
+           -1.6951931930195976,
+           -1.6325014033154723,
+           -1.5626683316484737,
+           -1.487414487145604,
+           -1.408597381953762,
+           -1.3281711514161942,
+           -1.248143424710704,
+           -1.17053045356573,
+           -1.0973115546743208,
+           -1.030383943868321,
+           -0.971519036379056,
+           -0.9223212576221823,
+           -0.8841903535739859,
+           -0.8582881102513724,
+           -0.8455102899625642,
+           -0.8464644703042805,
+           -0.8614543332787101,
+           -0.8904707997433325,
+           -0.9331902423780764,
+           -0.9889798423927914,
+           -1.0569099853875992,
+           -1.1357734242520023,
+           -1.2241107758249936,
+           -1.3202417671635056,
+           -1.422301510355707,
+           -1.5282809652038272,
+           -1.636070649699596,
+           -1.743506581442186,
+           -1.8484173808662552,
+           -1.9486714406205439,
+           -2.0422230652980966,
+           -2.127156511954222,
+           -2.201726913799167,
+           -2.2643971458304146,
+           -2.3138697900898384,
+           -2.349113477257183,
+           -2.369383017497341,
+           -2.3742328835207895,
+           -2.3635237690142903,
+           -2.337422112028931,
+           -2.2963926415029254,
+           -2.2411841717284293,
+           -2.172809030180358,
+           -2.092516654800806,
+           -2.0017620339153583,
+           -1.9021697821287802,
+           -1.7954947459102888,
+           -1.6835801107291002,
+           -1.568314035687154,
+           -1.4515858703629794,
+           -1.3352430113996594,
+           -1.2210494332547046,
+           -1.110646879133869,
+           -1.005519625731384,
+           -0.906963640863535,
+           -0.8160608388221213,
+           -0.7336590071835907,
+           -0.6603578341927306,
+           -0.5965013113298526,
+           -0.5421766251370366,
+           -0.49721948983279296,
+           -0.4612257117369844,
+           -0.43356862205096836,
+           -0.4134218699239363,
+           -0.39978693656418623,
+           -0.3915246166590673,
+           -0.38738961836219893,
+           -0.386067359911515,
+           -0.3862119913272849,
+           -0.3864846447827263,
+           -0.3855909176970596,
+           -0.3823166182924874,
+           -0.3755608535713433,
+           -0.36436561308263815,
+           -0.3479410965533026,
+           -0.3256861470223722,
+           -0.29720328062885204,
+           -0.2623079463625115,
+           -0.22103180027299027,
+           -0.173619935005123,
+           -0.12052216311888639,
+           -0.062378607465133434,
+           -5.98015746042168e-16
+          ],
+          [
+           0,
+           0.06699141487619259,
+           0.13568339708518173,
+           0.2048775517521984,
+           0.27334306140777476,
+           0.33985325079587936,
+           0.40322217931209486,
+           0.4623402768731759,
+           0.5162080621861307,
+           0.5639670302610487,
+           0.6049268674055606,
+           0.6385882450651742,
+           0.6646605563990291,
+           0.6830740885805179,
+           0.6939862662421968,
+           0.6977817536607908,
+           0.6950663613675067,
+           0.6866548628840831,
+           0.6735529851845938,
+           0.6569339882724121,
+           0.6381103910933874,
+           0.618501529275779,
+           0.5995977416243001,
+           0.582922074044965,
+           0.569990459272329,
+           0.5622713765916182,
+           0.5611460164692376,
+           0.5678699700254304,
+           0.5835374326424508,
+           0.6090488553814761,
+           0.6450828985873596,
+           0.6920734409911963,
+           0.7501922772223916,
+           0.8193379998471795,
+           0.8991314122066244,
+           0.9889176591134999,
+           1.0877750978045686,
+           1.1945307654975434,
+           1.3077821365785642,
+           1.425924705896388,
+           1.5471847887548396,
+           1.6696567966109397,
+           1.7913441334924107,
+           1.9102027646067854,
+           2.0241864378878263,
+           2.1312924931177304,
+           2.2296071729763414,
+           2.3173493564677825,
+           2.39291166757828,
+           2.454897969996628,
+           2.5021563409203678,
+           2.5338067214189146,
+           2.549262565022107,
+           2.548245947153382,
+           2.530795752320191,
+           2.4972687198684644,
+           2.4483332986214728,
+           2.384956431733537,
+           2.308383561432774,
+           2.220112304903903,
+           2.1218604034349084,
+           2.0155286834430113,
+           1.9031598867799113,
+           1.7868943258999257,
+           1.6689233946681,
+           1.551442015961456,
+           1.4366011315562692,
+           1.3264613375155827,
+           1.2229487394644083,
+           1.1278140474848297,
+           1.0425958512314297,
+           0.9685889142093935,
+           0.9068182044734031,
+           0.8580192402842942,
+           0.8226251769049129,
+           0.800760898461138,
+           0.7922442106099239,
+           0.7965940597562247,
+           0.8130455368956847,
+           0.8405712629178589,
+           0.8779086013091489,
+           0.9235920073087277,
+           0.9759897030067244,
+           1.0333437685127405,
+           1.0938126625418345,
+           1.1555151333826021,
+           1.2165744544400647,
+           1.2751619179641578,
+           1.3295385461143665,
+           1.3780940294591748,
+           1.4193819780272505,
+           1.452150667183669,
+           1.4753685774257823,
+           1.488244160722985,
+           1.490239412900841,
+           1.481076988106279,
+           1.4607407536700359,
+           1.4294698476544927,
+           1.3877464629556915,
+           1.3362777370030656,
+           1.2759722710226067,
+           1.2079119339163091,
+           1.1333197198328595,
+           1.05352452266424,
+           0.9699237627044115,
+           0.8839448488120956,
+           0.7970064824929638,
+           0.710480807848864,
+           0.6256573834649863,
+           0.5437098997880213,
+           0.46566648977383424,
+           0.39238438351743726,
+           0.3245295417175935,
+           0.26256177113866047,
+           0.20672568107189607,
+           0.15704768683572018,
+           0.11333910847513076,
+           0.07520525402975417,
+           0.04206022106319614,
+           0.01314700152675522,
+           -0.012437662768207786,
+           -0.035714350283858304,
+           -0.057788737761863135,
+           -0.07981695429563049,
+           -0.1029694432860715,
+           -0.1283943037997115,
+           -0.1571810976126348,
+           -0.19032609766459382,
+           -0.228699918015745,
+           -0.2730184055767767,
+           -0.32381759136471655,
+           -0.3814333958871412,
+           -0.4459866620639535,
+           -0.5173739529024586,
+           -0.5952644033726479,
+           -0.6791027603059787,
+           -0.7681185845846054,
+           -0.8613414304263433,
+           -0.9576216612340065,
+           -1.055656414199578,
+           -1.154020090371708,
+           -1.251198626657652,
+           -1.3456267043101042,
+           -1.4357269674647117,
+           -1.5199502673454097,
+           -1.5968159143693212,
+           -1.6649509124776938,
+           -1.7231271678749622,
+           -1.770295707613633,
+           -1.8056170111214482,
+           -1.8284866482222437,
+           -1.8385555282738775,
+           -1.835744194037975,
+           -1.8202507376572954,
+           -1.7925520711231593,
+           -1.753398446055546,
+           -1.7038012834873737,
+           -1.6450145395426612,
+           -1.5785099933341518,
+           -1.5059469950963145,
+           -1.4291373517395345,
+           -1.3500061501872767,
+           -1.2705494229542549,
+           -1.1927896428199944,
+           -1.1187300920584782,
+           -1.0503091849935398,
+           -0.9893558297746792,
+           -0.9375468959666327,
+           -0.8963678092248739,
+           -0.8670772240370328,
+           -0.8506766319108017,
+           -0.8478856477212953,
+           -0.8591235839554837,
+           -0.8844977745207975,
+           -0.9237989502070904,
+           -0.9765038006791483,
+           -1.0417846870956806,
+           -1.1185262992556446,
+           -1.2053488857086967,
+           -1.3006375285642762,
+           -1.4025767906128905,
+           -1.509189934345095,
+           -1.6183818036389155,
+           -1.7279843719336851,
+           -1.8358038977331745,
+           -1.9396685908107358,
+           -2.0374756814270913,
+           -2.1272368004748397,
+           -2.207120620335267,
+           -2.2754917733350113,
+           -2.3309451553650518,
+           -2.3723348342412076,
+           -2.39879691299019,
+           -2.409765844232334,
+           -2.404983849622437,
+           -2.384503264038134,
+           -2.348681793816984,
+           -2.298170847693978,
+           -2.2338972640485006,
+           -2.1570389146156814,
+           -2.068994809146612,
+           -1.971350454116314,
+           -1.8658393283718775,
+           -1.7543014269483685,
+           -1.6386398890527436,
+           -1.5207767659063334,
+           -1.4026089978461829,
+           -1.2859656575581087,
+           -1.1725674779421347,
+           -1.0639896199231305,
+           -0.9616285491560959,
+           -0.8666737832462916,
+           -0.7800851455327422,
+           -0.7025760208387835,
+           -0.6346029564101042,
+           -0.5763617913530953,
+           -0.5277903342503986,
+           -0.4885774453461927,
+           -0.4581782208228456,
+           -0.4358348261761996,
+           -0.42060238726467847,
+           -0.41137922467479204,
+           -0.4069406126353298,
+           -0.40597516037906417,
+           -0.4071228536169862,
+           -0.4090137580976795,
+           -0.4103063768982442,
+           -0.4097246683223027,
+           -0.406092771613376,
+           -0.39836655204870924,
+           -0.3856611636793369,
+           -0.36727393478837106,
+           -0.3427020053120631,
+           -0.311654283834627,
+           -0.27405744080395283,
+           -0.2300558105320273,
+           -0.1800052333833123,
+           -0.12446102728857285,
+           -0.064160430353987,
+           -6.126331205960254e-16
+          ],
+          [
+           0,
+           0.0681450339508187,
+           0.13746466794264584,
+           0.20673207258992998,
+           0.274707567179257,
+           0.3401755669349202,
+           0.4019809963637845,
+           0.4590641878055755,
+           0.5104933220849006,
+           0.555493530199834,
+           0.5934718597371962,
+           0.6240374150518544,
+           0.6470161035412179,
+           0.6624595584870174,
+           0.6706479584479003,
+           0.6720866203016902,
+           0.667496403792694,
+           0.6577981257775776,
+           0.6440913382281644,
+           0.62762797149212,
+           0.6097814795891501,
+           0.5920122439860944,
+           0.5758300932896956,
+           0.562754876023665,
+           0.5542760800476433,
+           0.5518125237405677,
+           0.5566731499388049,
+           0.5700199335598973,
+           0.5928338682729976,
+           0.6258849275520539,
+           0.6697068026351647,
+           0.7245771065527702,
+           0.7905036022351457,
+           0.867216866971835,
+           0.9541696487483516,
+           1.0505430060866472,
+           1.1552591560099654,
+           1.267000788770626,
+           1.3842364471356903,
+           1.5052514163170032,
+           1.628183431838005,
+           1.7510623902176436,
+           1.8718531443919022,
+           1.9885003848815765,
+           2.0989745509075943,
+           2.2013176844182247,
+           2.2936881351639817,
+           2.3744030467246744,
+           2.441977601292896,
+           2.495160073939439,
+           2.532961843301307,
+           2.5546816228396985,
+           2.559923312191894,
+           2.5486070184155705,
+           2.5209729584553466,
+           2.4775781230273757,
+           2.419285754212707,
+           2.34724786018529,
+           2.2628811565069045,
+           2.167836980253292,
+           2.063965867069377,
+           1.9532776085797108,
+           1.8378977152988039,
+           1.7200212956697079,
+           1.6018654230272646,
+           1.4856210976486874,
+           1.3734059197645956,
+           1.2672185712565225,
+           1.1688961592183342,
+           1.0800754047107743,
+           1.0021585666113546,
+           0.9362848757530255,
+           0.8833081213707313,
+           0.843780883501693,
+           0.8179457450479555,
+           0.8057336496239044,
+           0.8067694001743249,
+           0.8203841228401809,
+           0.8456343548278001,
+           0.8813272581375589,
+           0.926051316742321,
+           0.9782117466692769,
+           1.0360697395240408,
+           1.097784572918019,
+           1.161457558090918,
+           1.2251767572403562,
+           1.2870613915305331,
+           1.3453048756550257,
+           1.3982154557249797,
+           1.4442534930522855,
+           1.4820645253951747,
+           1.5105073471570183,
+           1.5286764780934545,
+           1.535918533058952,
+           1.5318421596220302,
+           1.516321372135065,
+           1.489492276021177,
+           1.4517433405223958,
+           1.403699537851734,
+           1.3462008176474707,
+           1.2802755241070796,
+           1.207109485766572,
+           1.128011611577583,
+           1.0443769091863049,
+           0.9576479001426038,
+           0.8692754407611119,
+           0.7806799657386911,
+           0.6932141542666893,
+           0.6081279757689427,
+           0.5265370056857923,
+           0.4493948126511116,
+           0.3774701092721895,
+           0.3113292323197449,
+           0.25132437769586596,
+           0.19758786464767408,
+           0.15003254616928016,
+           0.10835832238195277,
+           0.07206455496188224,
+           0.04046802741714956,
+           0.012725952080303434,
+           -0.0121366062768423,
+           -0.0351956349698973,
+           -0.057594246312159494,
+           -0.08050683301864979,
+           -0.10510227059855916,
+           -0.13250715684986625,
+           -0.16377007876591715,
+           -0.1998278719195088,
+           -0.24147478732935995,
+           -0.28933540718616674,
+           -0.3438420554648127,
+           -0.4052173347682106,
+           -0.47346228961805087,
+           -0.5483505521270166,
+           -0.6294286721883712,
+           -0.7160226748795357,
+           -0.8072507267195035,
+           -0.9020416338162126,
+           -0.9991587428035111,
+           -1.0972286736565806,
+           -1.1947741855953429,
+           -1.2902503666000082,
+           -1.3820832464085715,
+           -1.4687098645835626,
+           -1.5486187811096774,
+           -1.6203899981986638,
+           -1.6827332690859622,
+           -1.7345238025109901,
+           -1.7748344295418774,
+           -1.8029633810700376,
+           -1.8184569277009104,
+           -1.8211262563985744,
+           -1.8110580971133845,
+           -1.788618764331614,
+           -1.75445143930605,
+           -1.7094666846926916,
+           -1.6548263503310494,
+           -1.5919211928283428,
+           -1.5223426883728197,
+           -1.4478496639083815,
+           -1.3703305028169275,
+           -1.2917617942973336,
+           -1.214164387858551,
+           -1.1395578834258102,
+           -1.0699146317264792,
+           -1.0071143377200957,
+           -0.9529003513502374,
+           -0.9088386949636199,
+           -0.8762808161537653,
+           -0.8563309699661579,
+           -0.8498190273699203,
+           -0.857279380227476,
+           -0.8789364697348776,
+           -0.9146973089283421,
+           -0.9641512041506578,
+           -1.0265767093705784,
+           -1.100955675109393,
+           -1.1859940846429267,
+           -1.2801492082348696,
+           -1.3816624553647825,
+           -1.4885971689191297,
+           -1.5988804874310556,
+           -1.7103483045591326,
+           -1.8207922814459563,
+           -1.928007819184369,
+           -2.0298418765152713,
+           -2.1242395226158344,
+           -2.2092881462837353,
+           -2.283258300199108,
+           -2.3446402408369353,
+           -2.392175328992053,
+           -2.424881580203405,
+           -2.442072795572082,
+           -2.4433708580977456,
+           -2.428710943923614,
+           -2.398339567762068,
+           -2.3528055531200605,
+           -2.2929441865736413,
+           -2.219854977144901,
+           -2.1348735928768394,
+           -2.0395386833174167,
+           -1.9355544155086568,
+           -1.824749649368087,
+           -1.7090347536970052,
+           -1.5903571146716002,
+           -1.470656413399711,
+           -1.3518207474296893,
+           -1.2356446431019739,
+           -1.1237899521118806,
+           -1.0177505480050288,
+           -0.9188216385491516,
+           -0.8280743905551139,
+           -0.7463364277721877,
+           -0.6741786133782376,
+           -0.6119083700623236,
+           -0.5595696267191173,
+           -0.5169493154309107,
+           -0.4835901798180447,
+           -0.4588095000288752,
+           -0.44172319447475594,
+           -0.4312746274786727,
+           -0.42626733852109344,
+           -0.4254008155136842,
+           -0.42730836378069953,
+           -0.4305960758822676,
+           -0.43388188616861895,
+           -0.435833698469433,
+           -0.43520560541293285,
+           -0.43087127270952624,
+           -0.4218536398806704,
+           -0.40735018833930586,
+           -0.38675314587665033,
+           -0.35966413045884477,
+           -0.325902882372223,
+           -0.28550988846069303,
+           -0.23874286154378888,
+           -0.1860671980480864,
+           -0.12814069337503187,
+           -0.06579294360227878,
+           -6.256987676951095e-16
+          ],
+          [
+           0,
+           0.06910758937254162,
+           0.13884548145965306,
+           0.20796852335356608,
+           0.2752386828435935,
+           0.33946205871755697,
+           0.3995247920488096,
+           0.4544269096024267,
+           0.5033131827495576,
+           0.5455001611416959,
+           0.580498637963631,
+           0.6080309204039609,
+           0.6280424121172192,
+           0.6407071605503337,
+           0.6464271773869464,
+           0.6458255011068925,
+           0.6397331327058806,
+           0.6291701348749207,
+           0.6153213373672389,
+           0.5995072330146402,
+           0.5831507762899829,
+           0.567740906194847,
+           0.5547937047631835,
+           0.545812169299876,
+           0.5422456188685315,
+           0.5454497723646633,
+           0.5566485262554621,
+           0.5768984248832911,
+           0.6070567559128872,
+           0.6477541194773251,
+           0.6993722138651708,
+           0.7620274557563372,
+           0.8355609121045826,
+           0.9195348672353147,
+           1.0132361863550203,
+           1.1156864694585782,
+           1.225658821707472,
+           1.341700901896983,
+           1.4621637537189283,
+           1.5852357790656668,
+           1.7089810822433367,
+           1.8313813019344112,
+           1.9503799568920333,
+           2.063928263963838,
+           2.1700313448591886,
+           2.2667937222002985,
+           2.3524630162972895,
+           2.4254707915637193,
+           2.484469564691261,
+           2.5283650741444017,
+           2.5563430201336548,
+           2.567889613346687,
+           2.5628054162449665,
+           2.54121211914624,
+           2.5035520607665407,
+           2.450580475319917,
+           2.3833506214733826,
+           2.3031921182101684,
+           2.211682974828036,
+           2.110615952936269,
+           2.001960033740161,
+           1.8878178808113026,
+           1.7703802840839173,
+           1.6518786426624392,
+           1.534536590423841,
+           1.4205218882230117,
+           1.31189969928468,
+           1.2105883302765617,
+           1.11831846044949,
+           1.03659679658085,
+           0.9666749843480036,
+           0.9095244798170429,
+           0.8658179410714332,
+           0.8359175431439853,
+           0.8198704531931814,
+           0.8174115313455005,
+           0.8279731499983607,
+           0.8507018548548725,
+           0.8844814286708903,
+           0.9279617675825654,
+           0.9795928436137529,
+           1.037662908831554,
+           1.1003399994678256,
+           1.1657157244766698,
+           1.2318502741965096,
+           1.2968175621547948,
+           1.3587494170705872,
+           1.4158777725944505,
+           1.4665738584430663,
+           1.509383476873512,
+           1.5430575508411186,
+           1.5665772520952033,
+           1.5791731558118858,
+           1.580338019665857,
+           1.5698329457135667,
+           1.5476868490903684,
+           1.5141893241863849,
+           1.469877162516892,
+           1.4155149328860313,
+           1.3520701797884216,
+           1.2806839267159378,
+           1.2026372839225914,
+           1.1193150524870918,
+           1.0321672859577153,
+           0.9426698157998876,
+           0.8522847662415709,
+           0.7624220775140671,
+           0.6744030241557404,
+           0.5894266578668508,
+           0.5085400238789585,
+           0.43261289801931024,
+           0.3623176712254604,
+           0.29811487227862593,
+           0.24024467144280712,
+           0.1887245512864291,
+           0.1433531701951841,
+           0.10372028303505672,
+           0.06922242617234897,
+           0.03908392458321728,
+           0.012382640870182338,
+           -0.011920236864633216,
+           -0.03494717605269752,
+           -0.05786894127118153,
+           -0.08186784908802143,
+           -0.10810062530166235,
+           -0.13766186484166934,
+           -0.17154908000823826,
+           -0.21063028280596482,
+           -0.25561498286664086,
+           -0.30702939546762925,
+           -0.36519654662056966,
+           -0.4302218368327032,
+           -0.5019844850847399,
+           -0.5801351233523986,
+           -0.6640996534356649,
+           -0.7530893159521568,
+           -0.8461167601895689,
+           -0.9420177471749493,
+           -1.0394779707684199,
+           -1.1370643465741022,
+           -1.233259999421509,
+           -1.3265020801518164,
+           -1.415221464018688,
+           -1.4978833282205464,
+           -1.5730275763696797,
+           -1.6393080738982062,
+           -1.6955296806801818,
+           -1.7406821150395773,
+           -1.7739697557017933,
+           -1.7948365834035116,
+           -1.802985579502433,
+           -1.7983920322095406,
+           -1.7813103487405562,
+           -1.75227413012329,
+           -1.7120894307004635,
+           -1.6618212924507962,
+           -1.6027738109535892,
+           -1.5364641510078265,
+           -1.4645910815770247,
+           -1.3889987380842486,
+           -1.3116364416673767,
+           -1.2345155067698932,
+           -1.1596640478174516,
+           -1.089080850693501,
+           -1.0246894038554692,
+           -0.9682931864373242,
+           -0.9215332864312288,
+           -0.8858493715558518,
+           -0.8624449598731478,
+           -0.8522578384002233,
+           -0.8559363582434178,
+           -0.8738221970411157,
+           -0.9059400270695686,
+           -0.9519943639368672,
+           -1.0113737003330017,
+           -1.083161855964513,
+           -1.1661563028008124,
+           -1.2588930582872926,
+           -1.359677582296768,
+           -1.4666209701223676,
+           -1.5776806072619465,
+           -1.6907043451937551,
+           -1.803477173394513,
+           -1.9137693035493395,
+           -2.019384548691842,
+           -2.118207873695076,
+           -2.2082510142564145,
+           -2.287695108764909,
+           -2.354929360043199,
+           -2.4085848401321637,
+           -2.4475626686730356,
+           -2.471055931160141,
+           -2.4785648540611036,
+           -2.469904915840092,
+           -2.445207742309753,
+           -2.4049148073387583,
+           -2.3497641315416926,
+           -2.2807703379927693,
+           -2.1991985811850348,
+           -2.1065330095848904,
+           -2.0044405497179745,
+           -1.8947309076880055,
+           -1.7793137697854549,
+           -1.6601542453482905,
+           -1.5392276308541761,
+           -1.418474583549424,
+           -1.2997577756064331,
+           -1.1848210563564652,
+           -1.0752520817213294,
+           -0.9724492783324994,
+           -0.877593897315573,
+           -0.7916277821794137,
+           -0.7152373299697661,
+           -0.6488439684715359,
+           -0.5926013086831371,
+           -0.5463989651214021,
+           -0.5098728708945651,
+           -0.48242175401661597,
+           -0.46322929010424535,
+           -0.4512913081369732,
+           -0.4454473037820251,
+           -0.44441541188558215,
+           -0.4468299086211044,
+           -0.4512802564246698,
+           -0.45635067260051415,
+           -0.46065919608110134,
+           -0.4628952463605836,
+           -0.4618547135255737,
+           -0.4564716873849494,
+           -0.4458460251499014,
+           -0.4292660685776653,
+           -0.4062259501095641,
+           -0.3764370700226821,
+           -0.3398334793462968,
+           -0.2965710623889408,
+           -0.24702057414312453,
+           -0.19175474749192745,
+           -0.13152983899239332,
+           -0.0672621261619947,
+           -6.37099620849548e-16
+          ],
+          [
+           0,
+           0.06987068208679013,
+           0.13981381265310747,
+           0.20857633189453428,
+           0.2749324945441483,
+           0.3377206188299656,
+           0.395878172951309,
+           0.4484742509058654,
+           0.49473855598635746,
+           0.5340860994822489,
+           0.5661369318248365,
+           0.5907303508429971,
+           0.6079331737425449,
+           0.6180418123069996,
+           0.621578050784791,
+           0.619278588938201,
+           0.6120785746616678,
+           0.6010895073320072,
+           0.5875720406554102,
+           0.5729043484742734,
+           0.5585468353575241,
+           0.5460040727917008,
+           0.5367849188676406,
+           0.5323618325148535,
+           0.5341304211636309,
+           0.5433702624360909,
+           0.5612080159558707,
+           0.5885837911518716,
+           0.6262216621876006,
+           0.6746051236625987,
+           0.7339581628660026,
+           0.8042324889877661,
+           0.8851013101265472,
+           0.9759598888517823,
+           1.075932940428027,
+           1.1838887687116662,
+           1.29845986737317,
+           1.4180695526382567,
+           1.5409640421976276,
+           1.6652492570897455,
+           1.7889315026659578,
+           1.9099610842364452,
+           2.0262778352111,
+           2.13585748247686,
+           2.2367577467717132,
+           2.3271630756636985,
+           2.4054269334988603,
+           2.470110625760202,
+           2.5200177134460198,
+           2.5542231744767716,
+           2.572096591346224,
+           2.5733187843017093,
+           2.557891463882858,
+           2.5261396419215765,
+           2.4787067120933317,
+           2.416542285626982,
+           2.3408830405768035,
+           2.2532270099239464,
+           2.155301890634756,
+           2.049028098832473,
+           1.9364774219450007,
+           1.8198282240059018,
+           1.7013182426378683,
+           1.5831960736281812,
+           1.4676724700162842,
+           1.3568725865015343,
+           1.2527902766559278,
+           1.1572455004692777,
+           1.071845824392179,
+           0.9979528971254342,
+           0.9366546643595977,
+           0.8887439474367901,
+           0.8547038578737285,
+           0.8347003555949141,
+           0.8285820875894524,
+           0.8358874697046627,
+           0.8558588016694619,
+           0.8874630384068771,
+           0.9294186833110767,
+           0.9802281252505404,
+           1.0382146140991175,
+           1.1015629626524865,
+           1.1683629784228726,
+           1.236654569024866,
+           1.3044734310648038,
+           1.3698962253797224,
+           1.431084161231954,
+           1.4863239580843408,
+           1.5340652246440059,
+           1.5729533891389418,
+           1.601857429882454,
+           1.6198917881757842,
+           1.6264319931548568,
+           1.6211236866038943,
+           1.6038849010786744,
+           1.574901612784014,
+           1.5346167573535332,
+           1.4837130578486895,
+           1.4230901659391568,
+           1.3538367556046944,
+           1.2771983304049115,
+           1.1945416074156985,
+           1.1073164208441069,
+           1.0170161441789534,
+           0.9251376601890321,
+           0.8331419124584871,
+           0.7424160504162319,
+           0.6542381325936251,
+           0.5697452813888909,
+           0.48990608878985337,
+           0.41549795872780537,
+           0.3470899409208082,
+           0.2850314665532198,
+           0.22944724160834162,
+           0.18023839304763292,
+           0.13708980038660354,
+           0.09948338467434382,
+           0.06671697250349364,
+           0.037928208365123395,
+           0.012122858066466591,
+           -0.011793267650553338,
+           -0.03497963384513695,
+           -0.058624482460733686,
+           -0.08390749712388186,
+           -0.11196263713971072,
+           -0.14384214245075222,
+           -0.18048268187139432,
+           -0.22267456245149786,
+           -0.27103483972534487,
+           -0.32598506882825773,
+           -0.3877343175226183,
+           -0.45626792706169983,
+           -0.531342358937749,
+           -0.6124863086391826,
+           -0.6990081055406789,
+           -0.7900092550628275,
+           -0.8844038193874585,
+           -0.9809431803513031,
+           -1.0782455865395089,
+           -1.1748297596655741,
+           -1.2691517262971845,
+           -1.3596439526663302,
+           -1.4447557949706356,
+           -1.522994236943323,
+           -1.5929638716383883,
+           -1.653405095798434,
+           -1.703229522642971,
+           -1.7415516815804066,
+           -1.7677161597224251,
+           -1.7813194480842256,
+           -1.7822258823637838,
+           -1.7705772111034062,
+           -1.746795479340195,
+           -1.7115790797244654,
+           -1.6658919914813324,
+           -1.6109463963426545,
+           -1.5481790254988796,
+           -1.4792217486125991,
+           -1.4058670610849497,
+           -1.3300292554440845,
+           -1.2537021736787195,
+           -1.1789145267724572,
+           -1.1076838333349435,
+           -1.0419700693865706,
+           -0.9836301349720351,
+           -0.9343742299451363,
+           -0.8957251912367235,
+           -0.8689817781024968,
+           -0.8551868017955684,
+           -0.8551008839685041,
+           -0.8691824965750292,
+           -0.8975747882875915,
+           -0.9400995420514576,
+           -0.9962584392516409,
+           -1.0652416321878808,
+           -1.1459434523655117,
+           -1.236984911760865,
+           -1.3367424918626656,
+           -1.4433825648876535,
+           -1.5549006567896706,
+           -1.6691646458180849,
+           -1.783960896261078,
+           -1.8970422569303387,
+           -2.0061768096136934,
+           -2.1091962352211264,
+           -2.204042675098793,
+           -2.2888130017399213,
+           -2.3617994759757774,
+           -2.4215258551381833,
+           -2.4667781265041717,
+           -2.496629169869355,
+           -2.510456799177604,
+           -2.50795479218399,
+           -2.4891366852558034,
+           -2.4543322835142365,
+           -2.4041770103609412,
+           -2.3395943907806322,
+           -2.261772125515427,
+           -2.1721323643149173,
+           -2.0722969223143934,
+           -1.964048300899841,
+           -1.8492874703601787,
+           -1.7299894439138321,
+           -1.6081577196226116,
+           -1.4857786871930276,
+           -1.3647770902892256,
+           -1.2469736019810478,
+           -1.1340455122191198,
+           -1.0274914432942293,
+           -0.9286009042220689,
+           -0.8384293705592399,
+           -0.7577794354392514,
+           -0.6871884241508095,
+           -0.6269227022056136,
+           -0.5769787396111332,
+           -0.5370908261395544,
+           -0.506745167938249,
+           -0.4851999389350495,
+           -0.47151071503165626,
+           -0.464560588635858,
+           -0.4630941488610235,
+           -0.4657544214619644,
+           -0.4711217944932952,
+           -0.47775391240062715,
+           -0.4842255037939369,
+           -0.4891671168673508,
+           -0.49130177102534467,
+           -0.48947859281085476,
+           -0.48270258714125097,
+           -0.4701597989962504,
+           -0.45123724339164784,
+           -0.42553711957651474,
+           -0.3928849753900615,
+           -0.3533316457934078,
+           -0.3071489517396543,
+           -0.2548193076529078,
+           -0.19701954374904118,
+           -0.13459939925158015,
+           -0.06855528044706213,
+           -6.467365433000001e-16
+          ],
+          [
+           0,
+           0.07042765441011148,
+           0.14036130794568624,
+           0.20855061974657674,
+           0.2737927958875502,
+           0.33496875071344334,
+           0.3910770490709671,
+           0.4412647105824799,
+           0.4848540374378349,
+           0.5213647291507355,
+           0.5505306687682474,
+           0.5723109020863756,
+           0.5868944810551068,
+           0.5946990009775608,
+           0.5963628243193254,
+           0.5927311478198561,
+           0.5848362299904206,
+           0.5738722489268243,
+           0.5611654017782536,
+           0.5481399835954408,
+           0.5362812914029561,
+           0.527096286425523,
+           0.5220730111932256,
+           0.5226397970815179,
+           0.5301253106573005,
+           0.5457204735996929,
+           0.5704432512013127,
+           0.6051072394454728,
+           0.6502948919420887,
+           0.7063361177310067,
+           0.7732928518093157,
+           0.8509500553693113,
+           0.938813445705081,
+           1.0361140904282307,
+           1.141819831111916,
+           1.2546533319561204,
+           1.3731163837445626,
+           1.4955199363586742,
+           1.6200191883436204,
+           1.7446529331077676,
+           1.8673862515181823,
+           1.9861555527026729,
+           2.0989149010212884,
+           2.2036825290731548,
+           2.29858642527215,
+           2.381907900312565,
+           2.4521220794407865,
+           2.5079343358774384,
+           2.548311773384246,
+           2.5725089806306234,
+           2.5800874139306074,
+           2.5709279148581565,
+           2.5452360315761333,
+           2.503539983490853,
+           2.4466812839166514,
+           2.3757982105403985,
+           2.292302484345674,
+           2.1978496801220184,
+           2.094304041780191,
+           1.9836985097540865,
+           1.8681908825189517,
+           1.7500171268900078,
+           1.631442920022483,
+           1.5147145482464777,
+           1.402010303008429,
+           1.2953935018883949,
+           1.196768223223904,
+           1.1078387772654743,
+           1.0300738466257096,
+           0.9646761162724338,
+           0.9125580812125084,
+           0.8743245715501817,
+           0.85026237341377,
+           0.8403371542674318,
+           0.8441977265124132,
+           0.8611875082952466,
+           0.8903628693438801,
+           0.9305178866106527,
+           0.9802148834741452,
+           1.0378199909002113,
+           1.1015428525553532,
+           1.1694795012017196,
+           1.239657363041678,
+           1.310081301686503,
+           1.3787795951281527,
+           1.4438487478669813,
+           1.5034960758946674,
+           1.556079063594835,
+           1.6001405772131,
+           1.634439127178258,
+           1.6579734985019872,
+           1.6700012115494491,
+           1.6700504310694406,
+           1.6579251056103137,
+           1.6337032882313758,
+           1.597728758550347,
+           1.5505962314480466,
+           1.4931305950895064,
+           1.4263607664303568,
+           1.3514888824759017,
+           1.2698556570566941,
+           1.182902823057647,
+           1.092133646704553,
+           0.9990725420798559,
+           0.9052248295459507,
+           0.812037670889845,
+           0.7208631771177052,
+           0.63292462292221,
+           0.5492866165448232,
+           0.47082996726686055,
+           0.3982318678234436,
+           0.33195186883652883,
+           0.2722239704793055,
+           0.21905499687470734,
+           0.17222925524732666,
+           0.13131931873259747,
+           0.09570261312788976,
+           0.06458333775801503,
+           0.037019112816202716,
+           0.011951623511855256,
+           -0.011759571810122006,
+           -0.03530098411188073,
+           -0.05986785936747061,
+           -0.08662657339603258,
+           -0.1166777690142381,
+           -0.15102122999433723,
+           -0.19052344204769198,
+           -0.23588872233698968,
+           -0.28763470758172927,
+           -0.3460728789626408,
+           -0.41129467256911745,
+           -0.4831635803324129,
+           -0.5613134918733746,
+           -0.6451533663670816,
+           -0.7338781594637903,
+           -0.8264857676559229,
+           -0.9217995953638355,
+           -1.0184962024150799,
+           -1.115137355265868,
+           -1.2102056876848946,
+           -1.3021430787007793,
+           -1.389390779928176,
+           -1.4704302729036838,
+           -1.54382381114868,
+           -1.6082536020610803,
+           -1.662558610494697,
+           -1.7057680184262773,
+           -1.7371304522036666,
+           -1.7561381886653595,
+           -1.7625456715021868,
+           -1.7563818066653805,
+           -1.7379556570415573,
+           -1.707855318288281,
+           -1.666939925664023,
+           -1.6163249117386198,
+           -1.557360802817943,
+           -1.4916060035850813,
+           -1.4207941708221468,
+           -1.3467969143502312,
+           -1.271582683069283,
+           -1.197172793180321,
+           -1.1255956318168951,
+           -1.0588401204527318,
+           -0.9988095472538464,
+           -0.9472768753193032,
+           -0.9058426044834287,
+           -0.8758962086789849,
+           -0.8585820900825478,
+           -0.8547708872968299,
+           -0.865036850161327,
+           -0.889641851425807,
+           -0.9285264489141585,
+           -0.9813082447467087,
+           -1.0472876147369357,
+           -1.1254607054544816,
+           -1.214539422929868,
+           -1.3129779697985289,
+           -1.4190053309228337,
+           -1.530662965018118,
+           -1.6458468350235254,
+           -1.7623528059494373,
+           -1.8779243582415197,
+           -1.990301509298466,
+           -2.097269807018,
+           -2.196708257824981,
+           -2.2866350775866118,
+           -2.3652502065045646,
+           -2.430973607198863,
+           -2.4824784668482227,
+           -2.5187185469361655,
+           -2.538949064867224,
+           -2.5427406470203784,
+           -2.529986058899228,
+           -2.5008995908621103,
+           -2.4560091532511854,
+           -2.3961413083111625,
+           -2.322399633868635,
+           -2.2361369712566512,
+           -2.138922253594369,
+           -2.032502736792715,
+           -1.9187625615109947,
+           -1.7996786571989116,
+           -1.6772750573559212,
+           -1.553576726873029,
+           -1.4305640070882557,
+           -1.3101287619488646,
+           -1.194033260059526,
+           -1.0838727536827297,
+           -0.9810426188404872,
+           -0.8867108030074096,
+           -0.801796191454472,
+           -0.7269533535031599,
+           -0.6625639695319088,
+           -0.6087350725461269,
+           -0.5653040686391202,
+           -0.531850332945554,
+           -0.5077130158793752,
+           -0.492014542555824,
+           -0.4836891500681751,
+           -0.48151568612169066,
+           -0.4841537913849381,
+           -0.4901825092619829,
+           -0.4981403125115684,
+           -0.5065655075227727,
+           -0.5140359747385066,
+           -0.519207227678454,
+           -0.5208478225735786,
+           -0.5178712244687024,
+           -0.5093633318548711,
+           -0.4946049779798496,
+           -0.47308885997916417,
+           -0.4445304934778191,
+           -0.40887294660678103,
+           -0.36628526948944357,
+           -0.3171546990722871,
+           -0.26207288055253264,
+           -0.20181650151149508,
+           -0.13732287928104323,
+           -0.06966117240343107,
+           -6.54525459273059e-16
+          ],
+          [
+           0,
+           0.07077367379341427,
+           0.1404834053288134,
+           0.20789230824126276,
+           0.271831128257831,
+           0.33123349184422596,
+           0.3851683911835909,
+           0.4328690244026737,
+           0.4737572036144324,
+           0.5074626573452486,
+           0.5338366853850742,
+           0.5529597697237937,
+           0.5651429013413357,
+           0.5709225452599771,
+           0.5710493313334392,
+           0.5664707215618054,
+           0.5583080621457138,
+           0.5478285760320363,
+           0.5364129856033579,
+           0.5255195720088182,
+           0.5166455744309204,
+           0.5112869068362624,
+           0.5108972195334747,
+           0.5168473568345896,
+           0.5303862596062155,
+           0.5526043324855393,
+           0.5844002406677584,
+           0.6264520217384255,
+           0.6791932959353153,
+           0.7427952359587736,
+           0.8171548179949027,
+           0.9018897223957139,
+           0.9963400892484493,
+           1.0995771648941408,
+           1.2104187045120285,
+           1.3274508274143546,
+           1.4490558598861527,
+           1.573445549292215,
+           1.6986988965372272,
+           1.822803735233816,
+           1.9437010880997558,
+           2.0593312566517987,
+           2.167680551098929,
+           2.266827544750528,
+           2.354987741879559,
+           2.4305555797819562,
+           2.4921427440449335,
+           2.5386118594194937,
+           2.5691047252056944,
+           2.5830643911501414,
+           2.580250514460482,
+           2.560747597162788,
+           2.5249658718166463,
+           2.4736347784568076,
+           2.407789152292452,
+           2.3287484158596747,
+           2.23808923674038,
+           2.1376122685438936,
+           2.0293037347706013,
+           1.9152927389711105,
+           1.7978052872527308,
+           1.679116088157395,
+           1.5614992483098713,
+           1.447179008706744,
+           1.3382816654384007,
+           1.236789790035272,
+           1.1444998092072571,
+           1.0629839228585798,
+           0.9935572348901511,
+           0.9372508460017092,
+           0.8947915145421594,
+           0.8665883339293485,
+           0.8527267071196305,
+           0.8529697241572822,
+           0.8667668722307053,
+           0.893269833211918,
+           0.9313549556050955,
+           0.9796518302638657,
+           1.0365772559777127,
+           1.1003737555404394,
+           1.169151698221668,
+           1.2409340031736713,
+           1.3137023421505702,
+           1.3854437303024263,
+           1.4541963913831055,
+           1.5180938084594373,
+           1.5754059224401566,
+           1.6245765171166562,
+           1.664255928965678,
+           1.6933283401805395,
+           1.7109330512423375,
+           1.7164792813551328,
+           1.7096542074479952,
+           1.6904241211405935,
+           1.6590287538808683,
+           1.6159689891522206,
+           1.5619883430355912,
+           1.4980487464867906,
+           1.4253013007045021,
+           1.3450527975311313,
+           1.2587288970003585,
+           1.167834931489398,
+           1.073915358592889,
+           0.9785129115705026,
+           0.8831284964432284,
+           0.7891828585989241,
+           0.6979809898514702,
+           0.6106801706570845,
+           0.528262443609472,
+           0.45151219595211994,
+           0.38099939369287394,
+           0.3170688614304306,
+           0.25983584398088333,
+           0.20918792233619546,
+           0.16479319153993402,
+           0.12611444590355678,
+           0.09242896170934468,
+           0.06285332307642413,
+           0.0363726066522316,
+           0.011873128514125543,
+           -0.011822135042708844,
+           -0.035916409981321666,
+           -0.06160127162177887,
+           -0.09001909619676512,
+           -0.12222682897376966,
+           -0.15916204732317782,
+           -0.20161223822404395,
+           -0.2501881271378382,
+           -0.3053017910254285,
+           -0.3671501651592596,
+           -0.4357044143962775,
+           -0.5107054882343215,
+           -0.5916660190965022,
+           -0.6778785589143922,
+           -0.7684299843684844,
+           -0.8622217402645829,
+           -0.9579954375567341,
+           -1.0543631813580547,
+           -1.1498418785059459,
+           -1.242890667082638,
+           -1.331950524488983,
+           -1.4154850484508432,
+           -1.4920213683377026,
+           -1.5601901333980925,
+           -1.618763540316731,
+           -1.6666904045601456,
+           -1.7031273473298565,
+           -1.7274652609790901,
+           -1.7393503282701055,
+           -1.738699002112307,
+           -1.7257064992112956,
+           -1.7008485197656271,
+           -1.664876072056942,
+           -1.6188034513667697,
+           -1.5638895928914205,
+           -1.501613183984375,
+           -1.4336420780081043,
+           -1.3617976964047696,
+           -1.2880152336828838,
+           -1.2143005886437799,
+           -1.142685031591798,
+           -1.075178679282906,
+           -1.0137238853638117,
+           -0.9601496630733423,
+           -0.916128238719205,
+           -0.8831347892780568,
+           -0.8624113464306569,
+           -0.8549357541122461,
+           -0.861396449504182,
+           -0.8821737011335669,
+           -0.9173277856738726,
+           -0.9665944208361024,
+           -1.0293875993943962,
+           -1.1048097930950858,
+           -1.1916693192483474,
+           -1.2885044914879098,
+           -1.3936140136879371,
+           -1.5050929263157318,
+           -1.6208732812335418,
+           -1.7387686073993172,
+           -1.8565211388332137,
+           -1.9718507098403166,
+           -2.0825041824354757,
+           -2.186304258181039,
+           -2.281196541534633,
+           -2.3652937639459126,
+           -2.43691614630585,
+           -2.494626970266452,
+           -2.5372625441371124,
+           -2.563955883709047,
+           -2.5741535791668704,
+           -2.5676254825307887,
+           -2.544467021844206,
+           -2.5050941243866354,
+           -2.450230907256438,
+           -2.380890465442374,
+           -2.2983492508087013,
+           -2.2041156862894686,
+           -2.099893794369346,
+           -1.9875427343658827,
+           -1.8690332363480697,
+           -1.7464019885017752,
+           -1.621705077761283,
+           -1.4969715995855986,
+           -1.3741585415517772,
+           -1.255108007320984,
+           -1.1415077835244025,
+           -1.0348561638692904,
+           -0.9364318345299081,
+           -0.8472694954505694,
+           -0.7681417468039148,
+           -0.6995476121592721,
+           -0.6417079038623079,
+           -0.5945674658451467,
+           -0.5578041588076059,
+           -0.53084428665807,
+           -0.5128840053844416,
+           -0.5029161100330436,
+           -0.4997614657851145,
+           -0.502104238414111,
+           -0.5085299903801573,
+           -0.5175656436225105,
+           -0.5277202702995947,
+           -0.5375256592153509,
+           -0.5455756187176066,
+           -0.5505630160527037,
+           -0.5513136174503728,
+           -0.5468158809086643,
+           -0.5362459624815118,
+           -0.5189873240468827,
+           -0.49464447280182955,
+           -0.4630505164683724,
+           -0.42426837949555113,
+           -0.3785856903169049,
+           -0.3265035137967925,
+           -0.2687192622225743,
+           -0.20610426854864364,
+           -0.13967664327535484,
+           -0.07057015787584807,
+           -6.603983414639129e-16
+          ],
+          [
+           0,
+           0.07090579870206083,
+           0.14017941691051156,
+           0.2066081664160749,
+           0.2690667425001651,
+           0.32655123916883455,
+           0.3782098733697953,
+           0.42336958309207573,
+           0.4615577705752038,
+           0.4925185870380032,
+           0.5162232962166271,
+           0.5328744070202814,
+           0.5429034269055376,
+           0.5469622530586266,
+           0.5459083839722798,
+           0.5407842953171149,
+           0.5327914770448525,
+           0.5232597695320615,
+           0.5136127616889231,
+           0.5053301201184355,
+           0.49990780288890907,
+           0.49881717208755644,
+           0.5034640544612567,
+           0.5151488081636175,
+           0.5350284356167312,
+           0.5640817381317061,
+           0.6030784382444486,
+           0.6525531023779966,
+           0.7127845817004478,
+           0.7837815557079804,
+           0.8652746143956253,
+           0.9567151545440239,
+           1.0572811976069187,
+           1.165890065091364,
+           1.281217676437971,
+           1.401724068481689,
+           1.5256845787408821,
+           1.6512259909637583,
+           1.7763668141626314,
+           1.8990607589901676,
+           2.017242390476233,
+           2.1288738760154766,
+           2.2319917136347,
+           2.324752318889491,
+           2.4054753694865068,
+           2.472683854469905,
+           2.525139848449632,
+           2.5618751291476696,
+           2.582215876159562,
+           2.585800827395416,
+           2.5725924238290583,
+           2.5428806392097436,
+           2.497279365244347,
+           2.4367154002084677,
+           2.3624102656678705,
+           2.2758552476756506,
+           2.1787802212630565,
+           2.0731169662932665,
+           1.9609578151478502,
+           1.844510585026064,
+           1.7260508371085155,
+           1.6078725692780513,
+           1.4922384869231866,
+           1.3813310066452127,
+           1.2772051301954734,
+           1.1817442811106587,
+           1.0966201253876313,
+           1.0232573018840376,
+           0.9628038702859042,
+           0.9161081473292758,
+           0.8837024488521042,
+           0.8657940899256029,
+           0.8622638218081847,
+           0.8726717070136593,
+           0.8962702567149112,
+           0.932024482327105,
+           0.9786383496227054,
+           1.0345869730930832,
+           1.0981537541362747,
+           1.1674715522551584,
+           1.2405668865428836,
+           1.3154060975037043,
+           1.3899423582880372,
+           1.4621624106427635,
+           1.5301319145522592,
+           1.5920383412577015,
+           1.646230406010974,
+           1.6912531278269674,
+           1.7258777163318628,
+           1.7491256177162937,
+           1.7602861994773977,
+           1.7589277133766146,
+           1.7449013438643801,
+           1.718338320951291,
+           1.6796402478733314,
+           1.6294629606605986,
+           1.5686943947527692,
+           1.4984270792147696,
+           1.4199260083195808,
+           1.334592750119647,
+           1.243926739450734,
+           1.149484766483413,
+           1.0528397099457862,
+           0.9555395756177567,
+           0.8590678854373319,
+           0.7648064210271321,
+           0.6740012587636016,
+           0.5877329434191843,
+           0.5068915362382397,
+           0.4321571439136548,
+           0.3639863906184148,
+           0.30260513968853653,
+           0.2480076087015721,
+           0.19996185567671007,
+           0.15802144914064611,
+           0.12154297502932973,
+           0.08970888286536675,
+           0.061555036163633906,
+           0.03600221104166949,
+           0.01189068559640771,
+           -0.011983016689732201,
+           -0.03682822143528791,
+           -0.0638220573429406,
+           -0.09407229471719833,
+           -0.12858207065448732,
+           -0.16821745438928107,
+           -0.21367873309918403,
+           -0.26547620261119514,
+           -0.3239111313293597,
+           -0.38906243225097087,
+           -0.4607794305233739,
+           -0.5386809563391257,
+           -0.6221608290579821,
+           -0.7103996324253699,
+           -0.8023825168316454,
+           -0.8969226068801105,
+           -0.9926894451079871,
+           -1.0882417692848927,
+           -1.1820638047030976,
+           -1.2726041572461562,
+           -1.358316320244043,
+           -1.4376997600914507,
+           -1.5093405236015702,
+           -1.5719503147214864,
+           -1.624403019511132,
+           -1.66576771548343,
+           -1.69533728316665,
+           -1.712651842111888,
+           -1.7175163579911492,
+           -1.7100119088703065,
+           -1.6905002537207363,
+           -1.6596215109327246,
+           -1.618284924940912,
+           -1.5676528708455684,
+           -1.5091184158463544,
+           -1.4442769181915662,
+           -1.3748922951446658,
+           -1.3028587274068237,
+           -1.2301586850940096,
+           -1.1588182567805358,
+           -1.0908608358376177,
+           -1.02826026544645,
+           -0.9728945640091151,
+           -0.9265013456359119,
+           -0.890636016048034,
+           -0.8666337633664611,
+           -0.8555762772840282,
+           -0.8582640210813316,
+           -0.8751947514628783,
+           -0.9065488343802048,
+           -0.952181744426482,
+           -1.0116239649293866,
+           -1.0840883296805621,
+           -1.1684846696118765,
+           -1.263441452991915,
+           -1.3673339401363194,
+           -1.4783182172959182,
+           -1.594370333129014,
+           -1.7133296384335448,
+           -1.8329453286145885,
+           -1.9509251111704597,
+           -2.0649848691870956,
+           -2.172898167693118,
+           -2.272544453338748,
+           -2.3619548291351227,
+           -2.4393543441617114,
+           -2.503199821797228,
+           -2.552212357108279,
+           -2.5854037419215863,
+           -2.6020962216845396,
+           -2.6019351479267048,
+           -2.584894260071747,
+           -2.551273506366222,
+           -2.501689491495859,
+           -2.43705881371859,
+           -2.3585747227911917,
+           -2.2676776875101807,
+           -2.1660206045069805,
+           -2.055429504579298,
+           -1.9378607163027708,
+           -1.8153555264727208,
+           -1.6899934311831177,
+           -1.5638450987992203,
+           -1.4389261661230384,
+           -1.3171529617641764,
+           -1.2003011968631558,
+           -1.0899685842739126,
+           -0.9875422451179252,
+           -0.8941716388636294,
+           -0.8107476128520854,
+           -0.737888012999075,
+           -0.6759301331082193,
+           -0.6249301099238491,
+           -0.5846691989704383,
+           -0.5546666966355155,
+           -0.5341991110523167,
+           -0.5223250321480188,
+           -0.5179150134891229,
+           -0.5196856586556486,
+           -0.5262370057369581,
+           -0.5360922275676675,
+           -0.5477386143331844,
+           -0.5596687803649042,
+           -0.5704210388534041,
+           -0.5786179167037477,
+           -0.5830018360465626,
+           -0.5824670675636358,
+           -0.5760871617435426,
+           -0.5631371848514646,
+           -0.5431102236891271,
+           -0.515727773635254,
+           -0.4809437841693741,
+           -0.4389423010405449,
+           -0.39012881026848795,
+           -0.3351155520582269,
+           -0.2747012283537015,
+           -0.20984567222110842,
+           -0.14164017689371597,
+           -0.07127429385754776,
+           -6.643040434379734e-16
+          ],
+          [
+           0,
+           0.07082302580373738,
+           0.13945257272913583,
+           0.20471079981393123,
+           0.2655264818287347,
+           0.32096747783389,
+           0.37026940363595395,
+           0.41285972691893785,
+           0.4483766220524917,
+           0.4766820569889065,
+           0.49786873383245644,
+           0.5122606638285684,
+           0.52040732265215,
+           0.523071498795818,
+           0.5212111123420171,
+           0.5159554392768849,
+           0.5085763237581361,
+           0.5004550936356489,
+           0.4930460096490514,
+           0.4878371731396944,
+           0.48630988837837286,
+           0.48989752186545354,
+           0.49994492097096443,
+           0.5176694474686983,
+           0.5441246479714319,
+           0.5801675237544687,
+           0.6264302783738532,
+           0.6832973148729812,
+           0.750888127823453,
+           0.8290465920630087,
+           0.9173369933022929,
+           1.0150469796399024,
+           1.1211974415625239,
+           1.2345591554670952,
+           1.3536758564142406,
+           1.4768932439265376,
+           1.6023932742259175,
+           1.7282329571308448,
+           1.8523867593052024,
+           1.9727916206119716,
+           2.0873935193926285,
+           2.19419447739554,
+           2.2912988770065965,
+           2.3769579729203776,
+           2.4496115172784636,
+           2.507925480765013,
+           2.5508249407029067,
+           2.5775213187306103,
+           2.58753328248425,
+           2.580700774680966,
+           2.557191795491512,
+           2.517501736157742,
+           2.4624452392683835,
+           2.3931407396308595,
+           2.3109880149127267,
+           2.2176392428943035,
+           2.1149642181761004,
+           2.0050105217048966,
+           1.8899595580812627,
+           1.7720794753106588,
+           1.6536760570164497,
+           1.537042726297712,
+           1.4244108221796017,
+           1.3179013034321883,
+           1.2194790005713148,
+           1.1309104759291382,
+           1.0537264652792804,
+           0.9891897647316852,
+           0.9382692961572642,
+           0.9016209364478546,
+           0.8795755340771007,
+           0.8721343646525264,
+           0.8789720996300997,
+           0.8994471834277049,
+           0.9326193381819463,
+           0.9772737466252662,
+           1.031951306117137,
+           1.0949842045604643,
+           1.1645359452126212,
+           1.2386448452379133,
+           1.315269954690259,
+           1.3923382903118633,
+           1.467792253298478,
+           1.5396361025590282,
+           1.6059803848506746,
+           1.6650832796883097,
+           1.7153878986419786,
+           1.7555546834619424,
+           1.784488172757179,
+           1.801357549549003,
+           1.8056105383555277,
+           1.7969803866320626,
+           1.7754858372597206,
+           1.741424172070271,
+           1.6953575768248261,
+           1.6380932414132594,
+           1.5706577612818065,
+           1.4942665434844176,
+           1.4102890399232624,
+           1.320210728389894,
+           1.2255928365681268,
+           1.1280308534297563,
+           1.0291128952965727,
+           0.9303789897694505,
+           0.8332823099236402,
+           0.7391533344920117,
+           0.6491678287032886,
+           0.5643194371153616,
+           0.48539755684397295,
+           0.4129710201795419,
+           0.34737796326298187,
+           0.28872209612620386,
+           0.23687542308687495,
+           0.19148729543114193,
+           0.15199951474614182,
+           0.11766704930793942,
+           0.08758378152540608,
+           0.060712575227577434,
+           0.03591884081698029,
+           0.012006686783172828,
+           -0.012243319968183971,
+           -0.03803580340515774,
+           -0.06652267042768105,
+           -0.09876666701752622,
+           -0.13570738173981334,
+           -0.1781306165179538,
+           -0.2266419575931797,
+           -0.281645271094155,
+           -0.3433267204216114,
+           -0.41164475991083943,
+           -0.48632640457782583,
+           -0.5668699130919573,
+           -0.6525538545639158,
+           -0.742452363507883,
+           -0.8354562256450463,
+           -0.9302992841643378,
+           -1.025589515537737,
+           -1.1198439995832965,
+           -1.2115269033616953,
+           -1.2990895153841018,
+           -1.381011307655417,
+           -1.4558409698303056,
+           -1.5222363531302754,
+           -1.5790022819042169,
+           -1.6251252373850373,
+           -1.6598039902118957,
+           -1.682475353925226,
+           -1.6928343485801325,
+           -1.690848199005826,
+           -1.6767637427406104,
+           -1.651107984585073,
+           -1.6146817040393775,
+           -1.5685461944287584,
+           -1.514003383990009,
+           -1.4525697553229742,
+           -1.3859446362598173,
+           -1.3159735784519684,
+           -1.2446076662249785,
+           -1.1738597043225627,
+           -1.1057583163638647,
+           -1.0423010440432112,
+           -0.9854075687942954,
+           -0.9368741819575256,
+           -0.898330606241699,
+           -0.8712002209508498,
+           -0.8566646672139563,
+           -0.8556337091106291,
+           -0.8687211045284299,
+           -0.8962270987540293,
+           -0.9381279975953739,
+           -0.9940731090424711,
+           -1.0633891671782278,
+           -1.1450921735155266,
+           -1.2379064135153803,
+           -1.3402902340637377,
+           -1.4504680053535348,
+           -1.5664675419025875,
+           -1.6861621259762238,
+           -1.8073161656947765,
+           -1.9276334323095996,
+           -2.0448067586798495,
+           -2.156568045408707,
+           -2.2607374132776727,
+           -2.355270360746366,
+           -2.4383018328757142,
+           -2.508186181923276,
+           -2.5635320982473653,
+           -2.603231710638496,
+           -2.6264831948290293,
+           -2.6328063843050833,
+           -2.622051044864337,
+           -2.594397649546307,
+           -2.5503506693348132,
+           -2.490724573039172,
+           -2.4166229026673633,
+           -2.3294109542076344,
+           -2.23068274406434,
+           -2.1222230748097943,
+           -2.005965627197324,
+           -1.8839480958115418,
+           -1.7582654511556204,
+           -1.6310224498551371,
+           -1.5042865261137606,
+           -1.3800421813818695,
+           -1.2601479458711091,
+           -1.1462969162092704,
+           -1.0399817799627966,
+           -0.9424651223345245,
+           -0.8547556759815313,
+           -0.7775910249646677,
+           -0.7114271120852074,
+           -0.6564347293185352,
+           -0.6125029979361628,
+           -0.5792496725110623,
+           -0.5560379355948586,
+           -0.5419991915729577,
+           -0.5360612229435886,
+           -0.5369809435944329,
+           -0.5433808747116589,
+           -0.5537883823978944,
+           -0.5666766539823416,
+           -0.5805063538477153,
+           -0.5937668901955209,
+           -0.6050162416739832,
+           -0.6129183366805153,
+           -0.6162770472434027,
+           -0.6140659518777137,
+           -0.6054531353087088,
+           -0.5898204245505635,
+           -0.5667766071595413,
+           -0.5361643348246196,
+           -0.498060579820832,
+           -0.4527706790665573,
+           -0.4008161663647413,
+           -0.3429167536787891,
+           -0.2799669729505196,
+           -0.2130081272098224,
+           -0.14319632009434916,
+           -0.07176743336097166,
+           -6.662089672192136e-16
+          ],
+          [
+           0,
+           0.07052631784795943,
+           0.1383100251168258,
+           0.2022185798921409,
+           0.2612445866441439,
+           0.31453641537656296,
+           0.3614245467490537,
+           0.4014429233131523,
+           0.43434471623642246,
+           0.46011206146312256,
+           0.47895947551715434,
+           0.4913308251424531,
+           0.4978898925475418,
+           0.49950474493094404,
+           0.4972262789809951,
+           0.4922614640541494,
+           0.4859419478483482,
+           0.47968881202971897,
+           0.47497436927798603,
+           0.4732819749130068,
+           0.4760648835323206,
+           0.4847052124174159,
+           0.500474077992553,
+           0.524493949152686,
+           0.5577042123004959,
+           0.6008308685957654,
+           0.6543611860091529,
+           0.7185240096661162,
+           0.7932762965791571,
+           0.8782962885746963,
+           0.9729835737808883,
+           1.0764661164974596,
+           1.1876141618470215,
+           1.305060749619695,
+           1.4272284054536784,
+           1.5523614210958652,
+           1.678562992875244,
+           1.8038363622808846,
+           1.926128997826296,
+           2.0433787758616138,
+           2.153561061754854,
+           2.2547355633724955,
+           2.3450918268590337,
+           2.422992270476385,
+           2.48701170516518,
+           2.5359723693084044,
+           2.568973608049237,
+           2.5854154519790007,
+           2.585015493071359,
+           2.5678186139359727,
+           2.5341992959616464,
+           2.4848564085946925,
+           2.4208005615497905,
+           2.3433342797985333,
+           2.2540254333772136,
+           2.154674516190963,
+           2.0472765160991298,
+           1.9339782490205302,
+           1.8170321393996602,
+           1.6987475154385154,
+           1.58144054790988,
+           1.4673839946411733,
+           1.358757918071402,
+           1.2576025204997454,
+           1.1657741913136312,
+           1.084905783830724,
+           1.0163720382829837,
+           0.9612609443777278,
+           0.9203516947959076,
+           0.8940997233987036,
+           0.8826291526561557,
+           0.8857327980146463,
+           0.9028796968940883,
+           0.933229951136376,
+           0.9756564983671169,
+           1.0287732640961877,
+           1.0909689964393656,
+           1.1604459527221056,
+           1.2352624951267488,
+           1.3133785636567359,
+           1.3927029311323165,
+           1.4711411081929928,
+           1.5466427571910137,
+           1.6172474925663283,
+           1.6811279912587953,
+           1.7366294087327154,
+           1.782304192414733,
+           1.8169415023405586,
+           1.839590585597615,
+           1.8495776033108602,
+           1.8465155726476847,
+           1.830307257535789,
+           1.801141016241988,
+           1.7594797873243309,
+           1.7060435634574114,
+           1.6417858610961817,
+           1.567864838987957,
+           1.4856098466088445,
+           1.3964842915625337,
+           1.302045800216392,
+           1.2039047063139563,
+           1.1036819365669004,
+           1.0029673695231056,
+           0.9032797242339555,
+           0.8060289889829239,
+           0.7124823288291949,
+           0.6237343158327839,
+           0.5406822100116121,
+           0.46400688530546835,
+           0.3941598465007407,
+           0.33135662397600235,
+           0.27557666729906904,
+           0.22656969034072988,
+           0.18386825392702041,
+           0.1468062113393483,
+           0.11454249124493163,
+           0.08608955569836013,
+           0.060345751147358274,
+           0.03613067091458649,
+           0.012222570912860943,
+           -0.012603171690209731,
+           -0.03953559320661376,
+           -0.06969070734833933,
+           -0.10407610695531379,
+           -0.14355855907528095,
+           -0.18883547129649933,
+           -0.24041100698873563,
+           -0.2985775067952923,
+           -0.36340273638008624,
+           -0.43472332954062826,
+           -0.5121446351657938,
+           -0.5950470102098812,
+           -0.6825984330816007,
+           -0.7737731468595529,
+           -0.8673758837294407,
+           -0.9620710750084371,
+           -1.056416318822131,
+           -1.1488992633087571,
+           -1.237976970072539,
+           -1.322116752898076,
+           -1.3998374422914528,
+           -1.4697500084209902,
+           -1.53059648401982,
+           -1.581286164637357,
+           -1.6209281254680776,
+           -1.648859180371971,
+           -1.664666517542592,
+           -1.6682043749210642,
+           -1.6596042637425474,
+           -1.6392784069577606,
+           -1.6079162267848328,
+           -1.5664738881667801,
+           -1.5161570781549645,
+           -1.4583973708974485,
+           -1.394822689752509,
+           -1.3272225280238936,
+           -1.2575087241647436,
+           -1.18767270263862,
+           -1.1197401850401694,
+           -1.0557244451823904,
+           -0.9975792248669311,
+           -0.947152442824654,
+           -0.906141817372624,
+           -0.8760534838918141,
+           -0.8581646221769742,
+           -0.8534910175944269,
+           -0.8627603659738877,
+           -0.8863919979937562,
+           -0.9244835477332397,
+           -0.9768049257188802,
+           -1.042799783178583,
+           -1.1215944755583303,
+           -1.2120143540097061,
+           -1.3126070378978842,
+           -1.4216721537010233,
+           -1.537296870074464,
+           -1.6573964191448092,
+           -1.7797586737019393,
+           -1.9020917518236935,
+           -2.02207354700505,
+           -2.1374020348777285,
+           -2.245845188253014,
+           -2.3452893409829967,
+           -2.4337848778047504,
+           -2.5095881910192954,
+           -2.5711989340101087,
+           -2.6173917140499423,
+           -2.647241499836112,
+           -2.660142169486183,
+           -2.6558177886509533,
+           -2.634326381959365,
+           -2.5960561399683715,
+           -2.5417141837878354,
+           -2.472308186203754,
+           -2.3891213171356394,
+           -2.2936811385317646,
+           -2.1877232155177526,
+           -2.073150333345025,
+           -1.9519883104820583,
+           -1.8263394746419064,
+           -1.6983349188353132,
+           -1.5700866775155575,
+           -1.4436409580501133,
+           -1.320933530309683,
+           -1.20374831798177,
+           -1.0936801508249614,
+           -0.9921025296309727,
+           -0.9001411278672062,
+           -0.81865360904339,
+           -0.7482161804074626,
+           -0.6891171355799119,
+           -0.6413574653616464,
+           -0.6046584415010512,
+           -0.5784759070010485,
+           -0.5620208428159404,
+           -0.5542856285653306,
+           -0.5540752779178421,
+           -0.5600428109228962,
+           -0.5707278286768627,
+           -0.5845972826416017,
+           -0.6000873834318641,
+           -0.6156455730552712,
+           -0.6297714908593615,
+           -0.6410558965722317,
+           -0.648216572903476,
+           -0.6501303136417114,
+           -0.6458602088771006,
+           -0.6346775641743638,
+           -0.6160779320216396,
+           -0.5897908880786612,
+           -0.555783347726966,
+           -0.5142563860535068,
+           -0.46563569243546976,
+           -0.41055595509106696,
+           -0.34983962717422196,
+           -0.28447067028066036,
+           -0.21556399996347003,
+           -0.14433146778696063,
+           -0.07204530281365563,
+           -6.660975580198431e-16
+          ],
+          [
+           0,
+           0.0700186118213945,
+           0.13676281330870207,
+           0.19915551438356313,
+           0.256262422772931,
+           0.3073205245502755,
+           0.35176184456564125,
+           0.38923183528057614,
+           0.4196018817637003,
+           0.44297556318184156,
+           0.45968847318004763,
+           0.4703015689798794,
+           0.47558818759884564,
+           0.47651503303185394,
+           0.4742175963398006,
+           0.4699706173423369,
+           0.46515432827349046,
+           0.4612173329665949,
+           0.4596370669843064,
+           0.4618788522279668,
+           0.46935460216775654,
+           0.4833822497878816,
+           0.5051469591628505,
+           0.5356651434744657,
+           0.5757522481222693,
+           0.6259951689047263,
+           0.6867300642029012,
+           0.7580261893953151,
+           0.8396762345815297,
+           0.9311934867201738,
+           1.0318159684498935,
+           1.1405175323443908,
+           1.2560257154666983,
+           1.3768459891637708,
+           1.501291877321952,
+           1.6275202668349311,
+           1.7535711005707688,
+           1.877410529027586,
+           1.9969765050297397,
+           2.1102257385837007,
+           2.215180888127338,
+           2.3099768509614482,
+           2.3929050300656116,
+           2.462454496501658,
+           2.5173490352451737,
+           2.5565791559477424,
+           2.579428266588449,
+           2.5854923444257567,
+           2.574692591815527,
+           2.5472807306066945,
+           2.5038367639261496,
+           2.4452592139559113,
+           2.37274802440426,
+           2.2877804923807386,
+           2.1920807619997666,
+           2.087583567157859,
+           1.9763930497554827,
+           1.8607375987631605,
+           1.742921752039371,
+           1.6252762743238103,
+           1.510107569593695,
+           1.3996476028769569,
+           1.296005495240324,
+           1.2011219162807472,
+           1.1167273319993327,
+           1.0443050740444308,
+           0.9850600812139868,
+           0.9398940286130866,
+           0.9093874072763153,
+           0.8937889511074674,
+           0.8930126327093477,
+           0.9066422693462034,
+           0.9339435992945564,
+           0.9738835116001937,
+           1.0251559430794077,
+           1.0862137993884475,
+           1.1553061159409277,
+           1.2305195527858943,
+           1.3098232181976146,
+           1.3911157410468955,
+           1.4722734637898898,
+           1.5511986072366104,
+           1.6258662655823721,
+           1.6943691252461057,
+           1.754958862922304,
+           1.8060832653237922,
+           1.84641822315675,
+           1.8748938821528207,
+           1.8907143812168026,
+           1.8933707682531944,
+           1.8826468540109387,
+           1.8586179391134892,
+           1.8216425249854589,
+           1.7723472913044802,
+           1.7116057866540018,
+           1.64051143119107,
+           1.5603455666387205,
+           1.4725414064286477,
+           1.3786448344985782,
+           1.2802730727820715,
+           1.1790722831144342,
+           1.0766751880621988,
+           0.9746597866839058,
+           0.8745102057460657,
+           0.7775806654229352,
+           0.6850634526226169,
+           0.5979616870318544,
+           0.5170675375347533,
+           0.44294640309419325,
+           0.3759274161441069,
+           0.31610046198852876,
+           0.2633197388085094,
+           0.21721371391261654,
+           0.17720116709882372,
+           0.14251285558163723,
+           0.11221819082047457,
+           0.08525618939193302,
+           0.06046985100402898,
+           0.03664302959459326,
+           0.01253880037550402,
+           -0.013061711741414678,
+           -0.04132108773978544,
+           -0.07330898350782386,
+           -0.1099680992080627,
+           -0.15208366815399463,
+           -0.2002572929038422,
+           -0.2548858435248607,
+           -0.31614600175704777,
+           -0.38398488843224254,
+           -0.4581170536859451,
+           -0.5380279442283167,
+           -0.62298379340159,
+           -0.7120477122136247,
+           -0.8041015972504727,
+           -0.8978733184558344,
+           -0.9919685101128629,
+           -1.0849061655356973,
+           -1.175157133118442,
+           -1.261184531144988,
+           -1.3414850432169314,
+           -1.4146300267754537,
+           -1.4793053647889691,
+           -1.5343490153887671,
+           -1.578785265518331,
+           -1.6118547713096438,
+           -1.6330395680659853,
+           -1.6420823539773277,
+           -1.6389994910513266,
+           -1.624087320781025,
+           -1.5979215569865985,
+           -1.5613496899798287,
+           -1.5154765104448529,
+           -1.4616430338726494,
+           -1.4013992727301217,
+           -1.3364714596297746,
+           -1.2687244666805435,
+           -1.2001202903746298,
+           -1.1326735746622414,
+           -1.0684052246586162,
+           -1.0092952176655243,
+           -0.9572357454501907,
+           -0.9139858212504244,
+           -0.8811284566914963,
+           -0.8600314583208853,
+           -0.8518128120768891,
+           -0.8573115186330209,
+           -0.8770646157241875,
+           -0.9112909783179263,
+           -0.9598823273580516,
+           -1.022401706664844,
+           -1.0980895095879482,
+           -1.185876956512467,
+           -1.2844067457198063,
+           -1.3920604277664952,
+           -1.5069918916811773,
+           -1.627166203855611,
+           -1.750402911131609,
+           -1.8744228114360646,
+           -1.9968971110456324,
+           -2.1154978292434303,
+           -2.2279482801997874,
+           -2.332072459134863,
+           -2.42584218528142,
+           -2.5074209072474307,
+           -2.575203155792346,
+           -2.6278487328427573,
+           -2.66431085125331,
+           -2.683857584301015,
+           -2.6860861436613765,
+           -2.6709296757565837,
+           -2.6386564447159073,
+           -2.589861451400281,
+           -2.5254507176034364,
+           -2.4466186382801784,
+           -2.3548189682467178,
+           -2.251730159280882,
+           -2.139215895304215,
+           -2.0192817841760617,
+           -1.894029251912017,
+           -1.765607746778204,
+           -1.6361663952647914,
+           -1.5078062586300631,
+           -1.3825343174417815,
+           -1.2622202629223194,
+           -1.1485570991989968,
+           -1.0430264616811624,
+           -0.9468694362329944,
+           -0.8610635246169198,
+           -0.7863062473315346,
+           -0.7230057093123491,
+           -0.6712782811250207,
+           -0.6309533725505131,
+           -0.6015851011922835,
+           -0.5824704902339826,
+           -0.5726736708959345,
+           -0.5710554203782827,
+           -0.5763072386845296,
+           -0.5869890607979056,
+           -0.6015696168257486,
+           -0.6184683939448111,
+           -0.6360981216559501,
+           -0.6529066967098316,
+           -0.6674174861375612,
+           -0.6782669954729017,
+           -0.6842389631854139,
+           -0.68429403962668,
+           -0.6775943269146627,
+           -0.6635221921175561,
+           -0.6416929163806051,
+           -0.6119609034468205,
+           -0.5744193382763679,
+           -0.5293933559359731,
+           -0.4774269483256655,
+           -0.4192639974098595,
+           -0.3558239743612101,
+           -0.2881729806118373,
+           -0.21749092580010942,
+           -0.14503573601086972,
+           -0.0721055610618618,
+           -6.639726198458997e-16
+          ],
+          [
+           0,
+           0.06930480716877524,
+           0.13482578841097395,
+           0.19555105957644625,
+           0.2506281354561326,
+           0.2993899989390592,
+           0.3413760402421116,
+           0.3763472895668206,
+           0.4042955146768391,
+           0.42544591423015105,
+           0.4402533042075228,
+           0.44939186423621025,
+           0.45373867872067647,
+           0.45435147019520217,
+           0.45244107507875453,
+           0.449339351152575,
+           0.446463328045921,
+           0.4452765136825304,
+           0.4472483483926558,
+           0.4538128521876769,
+           0.4663275381044239,
+           0.4860336647923326,
+           0.5140188745557964,
+           0.5511832094764169,
+           0.5982094192934274,
+           0.6555383723210456,
+           0.7233502573253111,
+           0.8015521229959314,
+           0.8897721459110715,
+           0.9873608515538419,
+           1.0933993401203852,
+           1.2067143938538658,
+           1.325900169803357,
+           1.4493460155548186,
+           1.5752697897745296,
+           1.701755928250359,
+           1.8267973730669842,
+           1.9483403807206028,
+           2.064331146960293,
+           2.172763133946267,
+           2.2717239603139947,
+           2.3594407176317773,
+           2.4343226075536193,
+           2.494999852025146,
+           2.540357912849778,
+           2.5695661647758534,
+           2.582100295439782,
+           2.577757852882719,
+           2.5566665233814687,
+           2.519284895065157,
+           2.46639564202439,
+           2.3990912449899455,
+           2.3187525437352625,
+           2.2270205887637267,
+           2.1257624213583908,
+           2.0170315577418174,
+           1.9030240813201804,
+           1.7860313536209036,
+           1.668390436955803,
+           1.552433378022057,
+           1.440436530203541,
+           1.3345710925429377,
+           1.2368560152023937,
+           1.1491143653935887,
+           1.0729341655906994,
+           1.0096346093405566,
+           0.9602384317472251,
+           0.9254510648586433,
+           0.905647046301306,
+           0.9008639765412564,
+           0.9108041403122704,
+           0.9348437254258,
+           0.972049391801177,
+           1.0212017695157931,
+           1.0808253012011533,
+           1.1492236951659076,
+           1.2245201248146962,
+           1.3047012004053136,
+           1.3876636535745346,
+           1.471262615400506,
+           1.5533603364541806,
+           1.631874193045127,
+           1.7048228477196326,
+           1.770369483361298,
+           1.8268611076417227,
+           1.872863026097983,
+           1.9071877052088595,
+           1.9289173884127178,
+           1.937419984515587,
+           1.9323579154773292,
+           1.9136897849709724,
+           1.8816649060595227,
+           1.836810901446419,
+           1.7799147587066664,
+           1.7119978815340338,
+           1.6342858224498258,
+           1.548173509076339,
+           1.4551868818979772,
+           1.3569419438546328,
+           1.255102279162552,
+           1.1513361291006292,
+           1.0472741154659302,
+           0.9444686780065656,
+           0.8443562410800426,
+           0.7482230484226868,
+           0.6571755052416369,
+           0.5721157464250171,
+           0.49372301159168314,
+           0.42244125548991357,
+           0.35847325977213407,
+           0.3017813435394707,
+           0.25209459953213664,
+           0.20892241474684825,
+           0.1715738728315331,
+           0.13918248490800567,
+           0.11073555929850143,
+           0.08510740240574415,
+           0.061095445687679856,
+           0.037458319717397714,
+           0.012954847576491662,
+           -0.013617092489192744,
+           -0.043382880570224866,
+           -0.07735565867678515,
+           -0.11640398080456205,
+           -0.16122348378746398,
+           -0.21231334865737234,
+           -0.2699581978086077,
+           -0.33421593215345186,
+           -0.4049118582265399,
+           -0.48163929175398074,
+           -0.563766655686275,
+           -0.6504509213715965,
+           -0.7406570757112249,
+           -0.8331831390015039,
+           -0.9266901117470399,
+           -1.019736097758619,
+           -1.11081373867308,
+           -1.1983900045301725,
+           -1.28094731855183,
+           -1.3570249535312893,
+           -1.425259623348701,
+           -1.4844242065101705,
+           -1.5334635789989546,
+           -1.571526600194358,
+           -1.597993386563631,
+           -1.612497121057254,
+           -1.614939778868592,
+           -1.6055012991919397,
+           -1.5846418941523532,
+           -1.5530973561886081,
+           -1.5118673996265455,
+           -1.4621972466455018,
+           -1.405552837966817,
+           -1.34359021012995,
+           -1.2781197301217166,
+           -1.2110660106456368,
+           -1.1444244421171281,
+           -1.0802153676845971,
+           -1.0204369928971901,
+           -0.9670181603702874,
+           -0.9217721308970417,
+           -0.8863524955572889,
+           -0.8622122988138216,
+           -0.8505673813744459,
+           -0.8523648554105013,
+           -0.8682575058516352,
+           -0.8985847727795623,
+           -0.9433608147705551,
+           -1.0022699851492738,
+           -1.0746698765960576,
+           -1.1596019086954632,
+           -1.2558092522379358,
+           -1.361761707805497,
+           -1.4756869886981976,
+           -1.5956077036910554,
+           -1.7193831972404974,
+           -1.8447552869669663,
+           -1.969396843420298,
+           -2.090962087619166,
+           -2.2071374393595793,
+           -2.315691734863389,
+           -2.4145246463522025,
+           -2.5017121782553695,
+           -2.575548183973931,
+           -2.6345809417452215,
+           -2.677643945880618,
+           -2.7038802076143456,
+           -2.7127595146402514,
+           -2.7040882663514507,
+           -2.678011678741011,
+           -2.6350083345583024,
+           -2.5758772362218436,
+           -2.5017176967386234,
+           -2.4139025731514527,
+           -2.314045503721003,
+           -2.203962950352934,
+           -2.0856319683135833,
+           -1.961144723140539,
+           -1.8326608475080284,
+           -1.7023587769297337,
+           -1.572387221511184,
+           -1.4448179211219578,
+           -1.32160079366141,
+           -1.204522521539628,
+           -1.0951695317477257,
+           -0.9948962122249868,
+           -0.9047990744815655,
+           -0.8256974229306391,
+           -0.7581209288552524,
+           -0.7023043354296022,
+           -0.6581893439901435,
+           -0.6254335551755369,
+           -0.603426165990906,
+           -0.5913099595569921,
+           -0.5880089723195395,
+           -0.5922610875453292,
+           -0.6026546873386321,
+           -0.6176684010069527,
+           -0.635712917661578,
+           -0.6551737871162896,
+           -0.6744541164528444,
+           -0.6920160803818428,
+           -0.7064202013853409,
+           -0.716361419549726,
+           -0.7207010603024644,
+           -0.7184939186667996,
+           -0.7090098083085397,
+           -0.6917490692565216,
+           -0.666451686027269,
+           -0.6330998339691366,
+           -0.5919138417554183,
+           -0.5433417277992074,
+           -0.4880426336476989,
+           -0.4268646339727001,
+           -0.3608175466646593,
+           -0.2910414941397051,
+           -0.21877207507634777,
+           -0.1453030916976161,
+           -0.07194783925349059,
+           -6.598554475674729e-16
+          ],
+          [
+           0,
+           0.06839173407783541,
+           0.13251749925874046,
+           0.19143987609534655,
+           0.24439623220675902,
+           0.29082212645243316,
+           0.330369213757019,
+           0.36291715462453383,
+           0.38857918922117685,
+           0.4077012006885435,
+           0.42085426189882924,
+           0.4288208298838406,
+           0.432574918347905,
+           0.4332567367915712,
+           0.4321424308073797,
+           0.4306096883394417,
+           0.4301000877965937,
+           0.432079153022542,
+           0.43799514495219566,
+           0.4492376586245897,
+           0.4670971060323001,
+           0.4927261496947582,
+           0.5271041091646883,
+           0.5710052939090571,
+           0.6249721228000062,
+           0.6892937750741459,
+           0.7639909828965401,
+           0.8488074249148497,
+           0.943208017133017,
+           1.0463842261118708,
+           1.1572663541704729,
+           1.2745425712810647,
+           1.3966842980872434,
+           1.5219773831874504,
+           1.6485583695579895,
+           1.7744550134718096,
+           1.8976301078232969,
+           2.0160275732272552,
+           2.1276197168921462,
+           2.230454522724738,
+           2.322701827396284,
+           2.4026972564935227,
+           2.4689828420009396,
+           2.5203433161374735,
+           2.555837175264448,
+           2.574821728837193,
+           2.576971489274457,
+           2.5622894157623337,
+           2.531110694581374,
+           2.4840989164234557,
+           2.4222346930140075,
+           2.3467969367367574,
+           2.2593372034384136,
+           2.161647665850808,
+           2.0557234390094163,
+           1.9437201158944237,
+           1.8279074879126096,
+           1.7106205179134926,
+           1.5942087008984456,
+           1.4809849877697834,
+           1.3731754593786272,
+           1.2728709214578637,
+           1.1819815461619034,
+           1.102195613960943,
+           1.0349433123001617,
+           0.9813664271011725,
+           0.9422946227839872,
+           0.9182288494431438,
+           0.9093322459486155,
+           0.9154287291992868,
+           0.93600927688381,
+           0.97024572835262,
+           1.017011750022058,
+           1.0749104424470575,
+           1.1423079099207438,
+           1.2173719739722746,
+           1.298115092807251,
+           1.382440452437458,
+           1.4681901242803848,
+           1.553194140048788,
+           1.6353193188077797,
+           1.7125166934707856,
+           1.7828664243600236,
+           1.8446191547080717,
+           1.8962328554006251,
+           1.9364043215173636,
+           1.9640946184193442,
+           1.9785479268748483,
+           1.9793034012259378,
+           1.9661998277840989,
+           1.9393730482079117,
+           1.8992462901632483,
+           1.8465137207115574,
+           1.7821177023479973,
+           1.7072203833763773,
+           1.6231703896447147,
+           1.5314655002719757,
+           1.4337122830694993,
+           1.3315837336618632,
+           1.2267760042250555,
+           1.1209653223285878,
+           1.0157661873194166,
+           0.9126918914354284,
+           0.8131183464780544,
+           0.7182521061503911,
+           0.6291033614271516,
+           0.5464645544596248,
+           0.4708951088990633,
+           0.4027126149008247,
+           0.34199063949765746,
+           0.2885631617454657,
+           0.24203546137637552,
+           0.20180112394769759,
+           0.16706466882785437,
+           0.13686916275345704,
+           0.11012805473546357,
+           0.0856603609738409,
+           0.06222824384449371,
+           0.038575969065562654,
+           0.013469191326821122,
+           -0.014266488188768951,
+           -0.04570872869237693,
+           -0.08180441051965688,
+           -0.12333926687181829,
+           -0.17091200790638464,
+           -0.22491364155674598,
+           -0.28551256033241695,
+           -0.35264581347990304,
+           -0.42601682306257094,
+           -0.5050996348199079,
+           -0.589149624341103,
+           -0.6772204104529954,
+           -0.7681865650576303,
+           -0.8607715560931102,
+           -0.9535802217164874,
+           -1.0451349527553697,
+           -1.1339146600456036,
+           -1.2183955260517272,
+           -1.2970924881614647,
+           -1.3686003756314484,
+           -1.4316336240497778,
+           -1.4850635203992106,
+           -1.527951987694322,
+           -1.559580999399381,
+           -1.57947681844538,
+           -1.5874283811003915,
+           -1.5834992891263688,
+           -1.568033031046956,
+           -1.5416512210611648,
+           -1.505244818007291,
+           -1.4599584624873723,
+           -1.4071682434266297,
+           -1.3484533716395986,
+           -1.285562393241141,
+           -1.2203747160768834,
+           -1.1548583442167533,
+           -1.0910248158702052,
+           -1.030882416283863,
+           -0.9763887873043077,
+           -0.9294040780057773,
+           -0.8916457754447507,
+           -0.8646463212539396,
+           -0.8497145591623356,
+           -0.8479019720365839,
+           -0.8599745567341915,
+           -0.8863910535842213,
+           -0.9272880978366461,
+           -0.9824726965667927,
+           -1.051422260266067,
+           -1.1332922379366002,
+           -1.2269312223358473,
+           -1.3309032125374989,
+           -1.4435165485770989,
+           -1.562858871856579,
+           -1.6868373191400596,
+           -1.8132230309639545,
+           -1.939698950227746,
+           -2.0639098062138506,
+           -2.183513125291594,
+           -2.296230083429006,
+           -2.399895018022663,
+           -2.492502447417731,
+           -2.5722505050883,
+           -2.637579780362619,
+           -2.687206666746802,
+           -2.7201504496659776,
+           -2.7357535146197733,
+           -2.7336942207038195,
+           -2.7139921591856626,
+           -2.6770056980849533,
+           -2.623421897079296,
+           -2.5542390580759884,
+           -2.470742351054164,
+           -2.3744731180596834,
+           -2.2671926065674457,
+           -2.150841013225502,
+           -2.027492827133068,
+           -1.8993095456869296,
+           -1.768490893663419,
+           -1.6372257062388826,
+           -1.5076436384234624,
+           -1.3817688369187404,
+           -1.2614766564333453,
+           -1.1484544223987625,
+           -1.0441671378592114,
+           -0.9498289066916052,
+           -0.8663807013947367,
+           -0.794474945066122,
+           -0.7344672078103798,
+           -0.6864151419028204,
+           -0.6500846019249534,
+           -0.6249627201997153,
+           -0.6102775385225073,
+           -0.605023638576839,
+           -0.6079930694321604,
+           -0.6178107446668935,
+           -0.6329733770038367,
+           -0.6518909374165123,
+           -0.6729295703969033,
+           -0.6944548687573411,
+           -0.7148744105888877,
+           -0.7326784877431206,
+           -0.7464780086871159,
+           -0.7550386373793703,
+           -0.7573103318755787,
+           -0.7524515690683806,
+           -0.7398476821541532,
+           -0.7191228915308034,
+           -0.6901457739488422,
+           -0.6530280847060462,
+           -0.6081170191951687,
+           -0.5559811688543785,
+           -0.49739058827709476,
+           -0.43329154083948757,
+           -0.36477662591247045,
+           -0.29305110813137597,
+           -0.2193963653551854,
+           -0.14513144445016934,
+           -0.07157376106929307,
+           -6.537857729509137e-16
+          ],
+          [
+           0,
+           0.06728810203619852,
+           0.12986004010787744,
+           0.18686153036703065,
+           0.23762709841885224,
+           0.28170058668063247,
+           0.3188498371445671,
+           0.34907513943539087,
+           0.37261119631561135,
+           0.3899225276335086,
+           0.4016924048525674,
+           0.4088055774053858,
+           0.4123252148879401,
+           0.41346464141448647,
+           0.41355457641173116,
+           0.4140067162221167,
+           0.416274590034266,
+           0.42181269931029625,
+           0.43203500006832524,
+           0.4482738107742456,
+           0.4717402245405235,
+           0.5034870728501367,
+           0.544375429837463,
+           0.5950455626525684,
+           0.6558931266355554,
+           0.7270512765454239,
+           0.8083792200581591,
+           0.8994575807518934,
+           0.9995907687699871,
+           1.107816382492048,
+           1.2229214881993353,
+           1.343465451292641,
+           1.4678088264428806,
+           1.5941476592921056,
+           1.7205524128655796,
+           1.8450106112229658,
+           1.965472194127553,
+           2.079896502170033,
+           2.186299763770969,
+           2.2828019350789304,
+           2.367671751573737,
+           2.439368886074114,
+           2.4965821710390976,
+           2.538262932069386,
+           2.563652592244077,
+           2.5723038406666956,
+           2.5640948101150514,
+           2.5392358743216454,
+           2.4982688511300366,
+           2.442058579297965,
+           2.371777019620414,
+           2.288880210855067,
+           2.195078583248145,
+           2.0923012930582163,
+           1.9826553864190952,
+           1.8683807266103956,
+           1.7518017222230153,
+           1.6352769722684415,
+           1.5211479960441685,
+           1.4116882392467203,
+           1.3090535428202392,
+           1.2152352274459695,
+           1.1320168852193602,
+           1.0609358824111867,
+           1.003250465394115,
+           0.9599132285559384,
+           0.9315515515591296,
+           0.9184554473318646,
+           0.9205730857314453,
+           0.9375140752039394,
+           0.9685604004204235,
+           1.0126847322856094,
+           1.0685756523035206,
+           1.1346691702820766,
+           1.2091857667152783,
+           1.290172062468535,
+           1.375546111712148,
+           1.4631452319573335,
+           1.5507752295005504,
+           1.6362598508709028,
+           1.7174892916145843,
+           1.7924666228499373,
+           1.8593510527018453,
+           1.9164970225124376,
+           1.9624882445239238,
+           1.9961659158502976,
+           2.0166504897877555,
+           2.0233565462105756,
+           2.0160004739611326,
+           1.9946008555222141,
+           1.959471623464257,
+           1.9112082347621433,
+           1.850667278722256,
+           1.7789400927795669,
+           1.697321103930227,
+           1.607271738552775,
+           1.5103808468028785,
+           1.4083226671474338,
+           1.3028134100417055,
+           1.1955675660055174,
+           1.0882550418582797,
+           0.9824601997566974,
+           0.8796438177611852,
+           0.781108909420988,
+           0.6879712354270642,
+           0.6011352154242862,
+           0.5212758057964753,
+           0.4488267532621088,
+           0.3839754684050331,
+           0.32666459200906395,
+           0.2766001545964601,
+           0.23326606023952115,
+           0.19594446378843272,
+           0.16374146021172675,
+           0.13561736955905315,
+           0.11042078452246885,
+           0.08692545261229773,
+           0.0638689939515345,
+           0.03999241039894131,
+           0.014079323256836317,
+           -0.015006114349909866,
+           -0.048283648464290785,
+           -0.08662465470597273,
+           -0.13072403761824736,
+           -0.18107705960547643,
+           -0.23796173167009269,
+           -0.3014272533949243,
+           -0.3712888322013976,
+           -0.44712904583528273,
+           -0.5283057414975006,
+           -0.6139662943716839,
+           -0.7030678818323823,
+           -0.7944032715760999,
+           -0.8866314763216196,
+           -0.9783124982871886,
+           -1.0679452766792412,
+           -1.1540078637438045,
+           -1.234998791804857,
+           -1.3094785567971878,
+           -1.3761101340922721,
+           -1.4336974602307972,
+           -1.481220859141006,
+           -1.5178684624824161,
+           -1.5430627691986787,
+           -1.5564816068655838,
+           -1.5580728940983355,
+           -1.5480627557680031,
+           -1.5269567073002426,
+           -1.495533796810463,
+           -1.4548337699817597,
+           -1.406137498026823,
+           -1.3509410794124566,
+           -1.2909241870019046,
+           -1.2279133798458506,
+           -1.163841229311433,
+           -1.100702219280707,
+           -1.040506466975515,
+           -0.9852323723447701,
+           -0.9367793382779378,
+           -0.8969217102474837,
+           -0.8672650620861186,
+           -0.8492059049229261,
+           -0.8438958199744505,
+           -0.852210914712003,
+           -0.8747273783210244,
+           -0.9117037693064242,
+           -0.9630705090390027,
+           -1.0284268838418895,
+           -1.1070456790478704,
+           -1.1978853856865137,
+           -1.299609738548009,
+           -1.410614167767607,
+           -1.5290585791052107,
+           -1.652905724853164,
+           -1.7799642915526197,
+           -1.907935715772696,
+           -2.034463647935212,
+           -2.1571849188035808,
+           -2.2737808254156264,
+           -2.3820275438719944,
+           -2.4798444957427694,
+           -2.5653395424698813,
+           -2.6368499568751105,
+           -2.6929782209211224,
+           -2.7326218217860427,
+           -2.754996361108928,
+           -2.759651451467942,
+           -2.7464790458869186,
+           -2.7157140262464603,
+           -2.6679270605177003,
+           -2.604009922260518,
+           -2.5251536443697926,
+           -2.4328200482750306,
+           -2.3287073455949443,
+           -2.214710647846294,
+           -2.092878337859522,
+           -1.9653653512231755,
+           -1.8343844851034228,
+           -1.7021568935353517,
+           -1.5708629418022015,
+           -1.4425945775453763,
+           -1.319310333219826,
+           -1.2027940045550662,
+           -1.0946179545882249,
+           -0.9961118750059543,
+           -0.908337698925129,
+           -0.8320712052977749,
+           -0.7677906886792425,
+           -0.7156728932858094,
+           -0.6755962314230698,
+           -0.6471511279123412,
+           -0.6296571584836783,
+           -0.6221864855162081,
+           -0.6235929430306661,
+           -0.6325459881820656,
+           -0.6475686219439336,
+           -0.6670782899942651,
+           -0.6894297082076779,
+           -0.7129585172003686,
+           -0.7360246579696207,
+           -0.7570543760357544,
+           -0.7745798041561356,
+           -0.7872751424842978,
+           -0.7939885481875776,
+           -0.7937689616057878,
+           -0.7858872300798934,
+           -0.7698510401829901,
+           -0.7454133304430004,
+           -0.7125740256665226,
+           -0.6715751063809055,
+           -0.6228891983528562,
+           -0.5672020332943092,
+           -0.5053892885463335,
+           -0.43848845679922177,
+           -0.36766652316359083,
+           -0.29418433298687235,
+           -0.21935861705607623,
+           -0.1445226991623389,
+           -0.07098694297531533,
+           -6.458215240931518e-16
+          ],
+          [
+           0,
+           0.06600442907623458,
+           0.12687886151054661,
+           0.18186014453583327,
+           0.2303864503352222,
+           0.27211467891775754,
+           0.3069317587212382,
+           0.3349595251214347,
+           0.35655302435809244,
+           0.3722922618578627,
+           0.38296758519415247,
+           0.3895590586278258,
+           0.39321034408584954,
+           0.3951977485400672,
+           0.3968952263461962,
+           0.3997362339060529,
+           0.4051734202298947,
+           0.4146371983709155,
+           0.4294942776712515,
+           0.45100724435071665,
+           0.4802962579242461,
+           0.5183038836831864,
+           0.5657640081338953,
+           0.6231756866255963,
+           0.6907826528017935,
+           0.7685590809135974,
+           0.856202037858308,
+           0.9531308958686017,
+           1.0584938031948663,
+           1.171181133213942,
+           1.2898456565723824,
+           1.412929010625379,
+           1.538693879830664,
+           1.6652611539347362,
+           1.7906512014472866,
+           1.912828287313746,
+           2.0297470786320777,
+           2.1394001229076887,
+           2.2398651512559806,
+           2.32935105502994,
+           2.40624140875917,
+           2.4691344645249473,
+           2.516878621762066,
+           2.5486024801106604,
+           2.5637387088628665,
+           2.5620411117281687,
+           2.5435944265650035,
+           2.508816572487603,
+           2.4584532371507333,
+           2.3935648806404894,
+           2.3155064147697235,
+           2.225899993229136,
+           2.1266015146508024,
+           2.0196615931122106,
+           1.9072818852000195,
+           1.7917677761523911,
+           1.6754785170119915,
+           1.560775967939553,
+           1.44997313829075,
+           1.3452837208578414,
+           1.2487737956333418,
+           1.16231682808412,
+           1.0875530094426247,
+           1.0258538838030673,
+           0.9782930813490097,
+           0.9456238318848432,
+           0.9282637715306774,
+           0.9262873818946871,
+           0.9394262194852339,
+           0.9670769079864203,
+           1.008316681800508,
+           1.061926090438447,
+           1.1264183042598583,
+           1.2000743068275477,
+           1.2809831215079983,
+           1.3670861032405692,
+           1.4562242334212112,
+           1.546187288821156,
+           1.6347637159684947,
+           1.7197900313632588,
+           1.7991985854776025,
+           1.8710625742113998,
+           1.9336372541378184,
+           1.9853964156321158,
+           2.025063288362729,
+           2.051635193619477,
+           2.064401414062796,
+           2.0629539198155316,
+           2.0471907662055187,
+           2.01731215853412,
+           1.9738093585432497,
+           1.9174467813593625,
+           1.8492377963250406,
+           1.7704148962479884,
+           1.6823950335089348,
+           1.5867410349144184,
+           1.4851200974132535,
+           1.3792604316548784,
+           1.2709071583276368,
+           1.1617785724209748,
+           1.0535238728469483,
+           0.9476834097668424,
+           0.8456524307145005,
+           0.7486492110543328,
+           0.657688336927387,
+           0.5735597726322688,
+           0.49681419283192807,
+           0.4277548969233367,
+           0.36643645248600937,
+           0.31267004124590075,
+           0.2660353088313737,
+           0.22589835309582304,
+           0.19143532912645195,
+           0.16166100618732485,
+           0.13546148634201557,
+           0.11163018951129688,
+           0.08890612786954669,
+           0.06601343581031374,
+           0.041701091622181934,
+           0.014781764245698647,
+           -0.015831256922515545,
+           -0.0510900398936544,
+           -0.09178180960716407,
+           -0.13850338291679024,
+           -0.19164093176482191,
+           -0.2513556283463555,
+           -0.3175755728328335,
+           -0.3899942405637584,
+           -0.46807551567578115,
+           -0.5510652062276307,
+           -0.6380087663588355,
+           -0.7277747881935889,
+           -0.8190836742075618,
+           -0.9105407634855416,
+           -1.0006730662155328,
+           -1.087968662941484,
+           -1.170917751051386,
+           -1.2480542726360269,
+           -1.3179970364984945,
+           -1.3794892533321346,
+           -1.431435436830178,
+           -1.472934683968116,
+           -1.503309433462682,
+           -1.5221289103755555,
+           -1.5292265943262,
+           -1.5247111956185937,
+           -1.5089707841417324,
+           -1.4826698861944814,
+           -1.4467395401800287,
+           -1.4023604790357231,
+           -1.3509397808947172,
+           -1.2940814954718751,
+           -1.2335519078648693,
+           -1.1712402399814756,
+           -1.1091157091480617,
+           -1.0491819605907902,
+           -0.9934299629250349,
+           -0.9437905016607535,
+           -0.9020874238078912,
+           -0.8699927764078439,
+           -0.8489849433865745,
+           -0.8403108193812622,
+           -0.8449529676713132,
+           -0.8636025942223711,
+           -0.8966390338914856,
+           -0.9441162913251036,
+           -1.0057570117304053,
+           -1.0809540795833366,
+           -1.1687798607698745,
+           -1.2680029200979932,
+           -1.3771118660549797,
+           -1.4943458025282303,
+           -1.6177307071777896,
+           -1.7451209121756956,
+           -1.8742447386489498,
+           -2.002753234443243,
+           -2.128270888272719,
+           -2.248447143831917,
+           -2.36100751625376,
+           -2.4638031209413724,
+           -2.5548574611178787,
+           -2.632409384557993,
+           -2.694951210341059,
+           -2.7412611409040832,
+           -2.7704292103953705,
+           -2.781876174032065,
+           -2.775364911106831,
+           -2.751004092381303,
+           -2.709244046510295,
+           -2.6508649453852486,
+           -2.57695761036147,
+           -2.488897415815944,
+           -2.3883119291348507,
+           -2.277043073110504,
+           -2.157104724284089,
+           -2.030636765929891,
+           -1.8998566946173983,
+           -1.7670099327031712,
+           -1.6343200244496587,
+           -1.5039398901881649,
+           -1.3779052811881232,
+           -1.25809151851263,
+           -1.1461745136585622,
+           -1.0435969593636516,
+           -0.9515404483637319,
+           -0.8709041293682115,
+           -0.8022903467928713,
+           -0.74599753789077,
+           -0.7020204821421706,
+           -0.6700578175259135,
+           -0.6495265610470684,
+           -0.6395832010047431,
+           -0.6391507701233335,
+           -0.6469511657189863,
+           -0.6615418590185502,
+           -0.6813560336021945,
+           -0.7047451151637423,
+           -0.7300226032242202,
+           -0.7555080912881027,
+           -0.7795703657069218,
+           -0.8006685050244758,
+           -0.8173899599437139,
+           -0.8284846777318902,
+           -0.8328944416941491,
+           -0.8297767235485684,
+           -0.8185224908774198,
+           -0.7987675696356367,
+           -0.7703973289655209,
+           -0.7335446280626932,
+           -0.688581138205552,
+           -0.6361023229273044,
+           -0.5769065213986492,
+           -0.5119687303250995,
+           -0.4424098142727141,
+           -0.3694619899448431,
+           -0.2944315236465138,
+           -0.21865965065207055,
+           -0.14348276870745952,
+           -0.07019297437767816,
+           -6.360383996543962e-16
+          ],
+          [
+           0,
+           0.0645529523283376,
+           0.12360254611616858,
+           0.17648399814629379,
+           0.2227447306591163,
+           0.2621584884188979,
+           0.29473312637499477,
+           0.32071184204031195,
+           0.34056779769929524,
+           0.3549922501849313,
+           0.3648764758482459,
+           0.37128794117067954,
+           0.3754413210996816,
+           0.3786651037593026,
+           0.38236463821398003,
+           0.3879825784212629,
+           0.3969577489130095,
+           0.4106835042111161,
+           0.4304666732789158,
+           0.45748817187959495,
+           0.4927663297001851,
+           0.5371239163383663,
+           0.5911597622463903,
+           0.6552257596245189,
+           0.7294098967809285,
+           0.8135258308672394,
+           0.9071093418351052,
+           1.009421838960525,
+           1.1194609146137893,
+           1.2359777625180688,
+           1.3575011039711513,
+           1.4823670997540108,
+           1.6087545718780458,
+           1.7347247217978001,
+           1.8582644137148758,
+           1.9773319961219045,
+           2.089904564229932,
+           2.1940255222217804,
+           2.2878512885502507,
+           2.369696000235247,
+           2.438073113086008,
+           2.491732863062516,
+           2.5296946479951403,
+           2.5512735063662215,
+           2.5561000079999006,
+           2.5441330269699782,
+           2.5156650360493162,
+           2.4713197404770555,
+           2.412042052360376,
+           2.339080591172275,
+           2.253963076049924,
+           2.1584651475232794,
+           2.0545733156919397,
+           1.9444428748040297,
+           1.8303517471564963,
+           1.7146513192011492,
+           1.5997154072346045,
+           1.4878885372256163,
+           1.3814347420102882,
+           1.2824880687824782,
+           1.1930059507505193,
+           1.1147265299547982,
+           1.0491309251563203,
+           0.997411321670733,
+           0.9604456218768934,
+           0.9387792392334761,
+           0.9326144487844282,
+           0.9418075274584405,
+           0.965873732342378,
+           1.0039999790384881,
+           1.055064899725721,
+           1.1176657860715125,
+           1.1901517599169797,
+           1.2706623686171086,
+           1.3571706755892223,
+           1.4475298130518017,
+           1.5395218856045574,
+           1.6309080620692507,
+           1.7194786700732427,
+           1.803102113709623,
+           1.8797714690395428,
+           1.9476476743003004,
+           2.005098319856449,
+           2.0507311549511065,
+           2.0834215613683655,
+           2.102333394881326,
+           2.1069327600789656,
+           2.096994458749009,
+           2.0726010321172397,
+           2.034134498454149,
+           1.9822610653872204,
+           1.917909266325326,
+           1.8422421285360298,
+           1.7566241227474448,
+           1.662583767204138,
+           1.5617728599080862,
+           1.4559233888959886,
+           1.3468032200374949,
+           1.2361716838410064,
+           1.125736176670619,
+           1.0171108578554497,
+           0.9117784633494115,
+           0.8110561704830771,
+           0.7160663391737992,
+           0.6277128255315261,
+           0.5466634174215866,
+           0.47333878194500456,
+           0.4079081460181184,
+           0.350291757545755,
+           0.30017000046993797,
+           0.2569988666295791,
+           0.22003132517197427,
+           0.18834398028945604,
+           0.1608682740770078,
+           0.1364253766748766,
+           0.11376381344023273,
+           0.09159881098794392,
+           0.06865230223789427,
+           0.04369251612970895,
+           0.015572090753763226,
+           -0.016736311055682997,
+           -0.05410783815413301,
+           -0.0972376031022511,
+           -0.1466179002307815,
+           -0.20252110785580354,
+           -0.2649887444577323,
+           -0.33382698819044737,
+           -0.4086088005486361,
+           -0.4886826226655924,
+           -0.5731874409122402,
+           -0.6610738515820439,
+           -0.7511305967157168,
+           -0.8420158985576992,
+           -0.9322927924288842,
+           -1.0204675502123162,
+           -1.1050302019439224,
+           -1.1844961033696257,
+           -1.257447464337414,
+           -1.3225737474347945,
+           -1.3787098685649486,
+           -1.4248711806893197,
+           -1.4602842975760861,
+           -1.4844129142523717,
+           -1.4969779025218917,
+           -1.497971100386096,
+           -1.4876623700264553,
+           -1.4665996663075311,
+           -1.4356020323891268,
+           -1.395745616642964,
+           -1.3483429812231786,
+           -1.294916142934658,
+           -1.2371639472093465,
+           -1.176924522010874,
+           -1.1161336866582927,
+           -1.0567802976413596,
+           -1.000859596760469,
+           -0.9503256842167939,
+           -0.9070442690951209,
+           -0.8727468511930492,
+           -0.8489874612255199,
+           -0.8371030316461333,
+           -0.8381783889401844,
+           -0.8530167521825786,
+           -0.8821164944541902,
+           -0.9256547764617066,
+           -0.9834784989731974,
+           -1.0551028464178953,
+           -1.1397175124480168,
+           -1.2362005138542995,
+           -1.3431393164735108,
+           -1.4588588201007187,
+           -1.5814555832524422,
+           -1.7088375169987484,
+           -1.838768143721526,
+           -1.9689144048460019,
+           -2.096896914093219,
+           -2.2203414917771553,
+           -2.336930782640589,
+           -2.4444547555217655,
+           -2.5408589078972357,
+           -2.6242890514733164,
+           -2.693131635222905,
+           -2.746048667645442,
+           -2.7820064280084127,
+           -2.800297303799452,
+           -2.8005542549906584,
+           -2.7827575810160874,
+           -2.747233849322045,
+           -2.6946470305153865,
+           -2.625982069978253,
+           -2.5425213048447297,
+           -2.445814304097103,
+           -2.3376418641412404,
+           -2.219975028819226,
+           -2.0949301181147195,
+           -1.9647208410314765,
+           -1.8316086330991588,
+           -1.6978523961519312,
+           -1.5656588265868967,
+           -1.4371344980977805,
+           -1.3142408164582429,
+           -1.1987528885537548,
+           -1.092223247448787,
+           -0.9959512523544659,
+           -0.9109588400094129,
+           -0.8379731457534758,
+           -0.777416342395049,
+           -0.7294028670686159,
+           -0.6937440250525072,
+           -0.6699597794433895,
+           -0.6572973610997938,
+           -0.6547561686613191,
+           -0.6611182777573665,
+           -0.6749837454203742,
+           -0.6948097834497852,
+           -0.7189527857471232,
+           -0.7457121315810429,
+           -0.7733746508237757,
+           -0.800258629228427,
+           -0.8247562518940883,
+           -0.8453734305990038,
+           -0.8607660343933767,
+           -0.8697716408064973,
+           -0.8714360447090835,
+           -0.8650339002159352,
+           -0.8500830244908055,
+           -0.8263520570276384,
+           -0.7938613397592577,
+           -0.7528770578457373,
+           -0.7038988538193296,
+           -0.6476412945587019,
+           -0.5850097271386844,
+           -0.5170712020215739,
+           -0.44502126675156584,
+           -0.37014753716459314,
+           -0.29379103353861113,
+           -0.2173063240829408,
+           -0.1420215463406075,
+           -0.06919937777100103,
+           -6.245292612340705e-16
+          ],
+          [
+           0,
+           0.06294752070166254,
+           0.12006255151493045,
+           0.17078508543100954,
+           0.21477645271956614,
+           0.2519299991381634,
+           0.2823752606698736,
+           0.30647550568680654,
+           0.32481868862990504,
+           0.33820203158627643,
+           0.34761061716045727,
+           0.35419053353129043,
+           0.3592172565537051,
+           0.36406008053388483,
+           0.37014351563543624,
+           0.3789066530322733,
+           0.3917615567596029,
+           0.4100517722100472,
+           0.43501204453246056,
+           0.4677303156655944,
+           0.5091130169253553,
+           0.559854596196808,
+           0.6204121167498846,
+           0.6909856409999499,
+           0.771504970217566,
+           0.8616231537750249,
+           0.9607170129044792,
+           1.0678947483262409,
+           1.1820105228622493,
+           1.3016857337305874,
+           1.4253365190381708,
+           1.5512068833207944,
+           1.6774066818407487,
+           1.8019535764080794,
+           1.922817969963494,
+           2.037969845745739,
+           2.1454263816674146,
+           2.243299182998674,
+           2.3298399773827625,
+           2.4034836456522286,
+           2.4628875192452617,
+           2.506965958911743,
+           2.5349193378625,
+           2.5462566829558444,
+           2.540811376787572,
+           2.51874948803849,
+           2.480570473138939,
+           2.4271001749510885,
+           2.359476229286682,
+           2.2791261731419064,
+           2.1877387250566755,
+           2.087228873661632,
+           1.979697561191838,
+           1.867386880812971,
+           1.7526318167675579,
+           1.6378096418842334,
+           1.5252881457810168,
+           1.4173738976678405,
+           1.3162617492375448,
+           1.2239867556619424,
+           1.1423796368253456,
+           1.0730268179742606,
+           1.017235980942813,
+           0.9760079266487747,
+           0.9500153998131862,
+           0.9395893614786959,
+           0.9447130179111388,
+           0.9650237301722427,
+           0.9998227415330385,
+           1.0480924745088218,
+           1.1085209701439407,
+           1.1795328736092852,
+           1.2593262162852503,
+           1.3459141090135682,
+           1.437170347383473,
+           1.530877840507226,
+           1.6247787118719554,
+           1.7166248860092066,
+           1.8042279686930252,
+           1.8855072512433566,
+           1.9585347206487396,
+           2.021576035309322,
+           2.073126529258437,
+           2.11194143315741,
+           2.1370596450368073,
+           2.1478205440742326,
+           2.1438735126708766,
+           2.125180011455331,
+           2.0920082341679715,
+           2.044920550164408,
+           1.9847541170710075,
+           1.912595210636552,
+           1.829747969022978,
+           1.7376983809993922,
+           1.638074458535427,
+           1.5326036214538008,
+           1.4230683830165993,
+           1.3112614591542386,
+           1.1989414297519896,
+           1.087790057939837,
+           0.979372323341952,
+           0.8751001490704943,
+           0.7762007018835171,
+           0.6836900229555203,
+           0.5983526062533215,
+           0.5207273861462622,
+           0.4511004295507374,
+           0.3895044548237266,
+           0.3357251241493613,
+           0.289313882728928,
+           0.249606951052521,
+           0.21574992009648383,
+           0.18672725737926896,
+           0.16139590797395093,
+           0.13852207191385726,
+           0.11682016049865712,
+           0.0949928807721259,
+           0.07177137121189144,
+           0.04595431307742262,
+           0.016444970840784504,
+           -0.01771482908344059,
+           -0.057314690920707685,
+           -0.10295041856362555,
+           -0.15500424104752925,
+           -0.21363103188065224,
+           -0.2787509031870051,
+           -0.3500483892903936,
+           -0.42697826237552844,
+           -0.5087778495699415,
+           -0.5944855505962798,
+           -0.6829650923713817,
+           -0.7729349057150295,
+           -0.8630018735289956,
+           -0.9516985828830342,
+           -1.0375231183944296,
+           -1.1189803635607292,
+           -1.1946237321415096,
+           -1.2630962344696621,
+           -1.323169794205412,
+           -1.3737817693278664,
+           -1.4140676961958611,
+           -1.443389365735754,
+           -1.461357454027365,
+           -1.4678480629793365,
+           -1.463012677118472,
+           -1.4472812060412785,
+           -1.4213579547288964,
+           -1.3862105414114652,
+           -1.3430519605565439,
+           -1.2933161624012268,
+           -1.2386276858919165,
+           -1.1807660347822921,
+           -1.1216256231146038,
+           -1.063172232917791,
+           -1.007397020729567,
+           -0.9562691780810095,
+           -0.9116883925846179,
+           -0.875438269620762,
+           -0.8491418593980175,
+           -0.8342203906527322,
+           -0.8318562414355617,
+           -0.8429610809686856,
+           -0.8681499967453568,
+           -0.907722280763311,
+           -0.9616493914262637,
+           -1.0295704370319338,
+           -1.1107953470436067,
+           -1.2043157128994135,
+           -1.308823095457981,
+           -1.4227344158314086,
+           -1.5442238747389967,
+           -1.671260686841677,
+           -1.801651774689256,
+           -1.9330884454240047,
+           -2.063195975232,
+           -2.1895849541478194,
+           -2.3099031989968295,
+           -2.4218870261282253,
+           -2.523410688573505,
+           -2.612532824068975,
+           -2.6875388300109857,
+           -2.7469781771899937,
+           -2.789695793755965,
+           -2.8148567913991887,
+           -2.8219639637727063,
+           -2.8108676588905754,
+           -2.781767808432741,
+           -2.735208083162913,
+           -2.6720623304890236,
+           -2.593513633023412,
+           -2.501026501389746,
+           -2.396312876242778,
+           -2.2812927595969033,
+           -2.1580504205913296,
+           -2.0287872227401533,
+           -1.8957721960830312,
+           -1.7612915266523088,
+           -1.6275981561661994,
+           -1.496862676406568,
+           -1.371126665616785,
+           -1.2522595494367617,
+           -1.1419199780333833,
+           -1.0415225964793202,
+           -0.9522109499529475,
+           -0.8748371123587276,
+           -0.8099484603059794,
+           -0.7577818381694315,
+           -0.7182651785491692,
+           -0.6910264603311643,
+           -0.675409708211603,
+           -0.6704975673734365,
+           -0.6751398291661722,
+           -0.6879871419986824,
+           -0.7075290196590124,
+           -0.7321351598790127,
+           -0.7600990115525691,
+           -0.7896824813553001,
+           -0.8191606506941004,
+           -0.8468653823352924,
+           -0.8712267324150212,
+           -0.8908111468256404,
+           -0.9043555095277017,
+           -0.9107962218644101,
+           -0.9092926235899095,
+           -0.8992442147050943,
+           -0.8803012985533494,
+           -0.8523688368748709,
+           -0.8156034823487754,
+           -0.7704039291563534,
+           -0.7173948928697323,
+           -0.6574051932135494,
+           -0.5914405628898748,
+           -0.5206519389475069,
+           -0.4463001067801332,
+           -0.36971765791733247,
+           -0.2922692890607606,
+           -0.21531150967353693,
+           -0.1401528378790477,
+           -0.06801554918177338,
+           -6.114033491549012e-16
+          ],
+          [
+           0,
+           0.06120347070194756,
+           0.1162929225949672,
+           0.1648186325228528,
+           0.20655949966411274,
+           0.24153016179030923,
+           0.2699814890904767,
+           0.292394425211759,
+           0.3094673190726178,
+           0.3220970614561955,
+           0.33135450305785286,
+           0.3384547814059569,
+           0.34472331905893916,
+           0.3515583712581879,
+           0.36039109481909865,
+           0.37264417905984554,
+           0.3896901222029562,
+           0.4128102518032788,
+           0.4431555749122357,
+           0.4817105031390125,
+           0.5292604304673294,
+           0.5863640492576344,
+           0.6533311745680827,
+           0.7302067116002803,
+           0.816761249061502,
+           0.912488596302675,
+           1.0166104083404204,
+           1.128087864630858,
+           1.2456401891829423,
+           1.3677696257411585,
+           1.4927923166921038,
+           1.6188743822085885,
+           1.7440723607770952,
+           1.866377057089983,
+           1.983759751257735,
+           2.094219656775966,
+           2.1958314754052966,
+           2.286791886156236,
+           2.3654638232824987,
+           2.430417444231578,
+           2.4804667618353435,
+           2.5147010139226986,
+           2.532509965641959,
+           2.533602482155214,
+           2.5180178685667083,
+           2.4861296461064497,
+           2.438641614516131,
+           2.376576235860586,
+           2.3012555600830242,
+           2.214275093001759,
+           2.1174711786841303,
+           2.0128826260223245,
+           1.9027074499898178,
+           1.7892557180091042,
+           1.6748995881470579,
+           1.5620216960881002,
+           1.4529630902671964,
+           1.3499719281053482,
+           1.2551541306167515,
+           1.170427148102783,
+           1.0974779172741258,
+           1.0377259916924053,
+           0.9922927052779145,
+           0.9619770857542633,
+           0.9472390747642745,
+           0.948190437888085,
+           0.9645935651443849,
+           0.9958681752024663,
+           1.0411057490333726,
+           1.0990913356417007,
+           1.1683321982935777,
+           1.2470926085196223,
+           1.333433951028555,
+           1.4252591790026932,
+           1.5203605590404754,
+           1.616469570664939,
+           1.7113077785958777,
+           1.802637477971543,
+           1.8883109237836075,
+           1.966316995619924,
+           2.0348242163541004,
+           2.0922191369578576,
+           2.13713921678651,
+           2.168499466566603,
+           2.1855122764605426,
+           2.1877000201412042,
+           2.1749002036012097,
+           2.147263110050246,
+           2.105242075211668,
+           2.0495767061113477,
+           1.981269526664301,
+           1.901556690836943,
+           1.811873545048187,
+           1.7138159423437276,
+           1.6090983088107664,
+           1.4995095353472596,
+           1.3868678135443595,
+           1.2729755520424275,
+           1.159575498937526,
+           1.048309157011427,
+           0.9406785127953554,
+           0.838012009485842,
+           0.741435579866168,
+           0.6518494215693965,
+           0.569911046662036,
+           0.4960249744501207,
+           0.43033926474143885,
+           0.3727489128752397,
+           0.322905952089486,
+           0.28023593765798877,
+           0.24396032499582668,
+           0.21312410467106915,
+           0.18662792471216044,
+           0.16326381807693008,
+           0.1417535634569743,
+           0.12078864295914933,
+           0.09907072223053465,
+           0.07535156819879693,
+           0.048471337016064535,
+           0.017394209550566687,
+           -0.018759577292287256,
+           -0.060686159836393506,
+           -0.10887567667140303,
+           -0.16359570045599578,
+           -0.22488092380803848,
+           -0.2925293872836226,
+           -0.3661053666313944,
+           -0.444948862529373,
+           -0.5281914632837754,
+           -0.6147781838789462,
+           -0.7034947275610818,
+           -0.792999472816529,
+           -0.8818593628226966,
+           -0.9685887694224993,
+           -1.0516903220991682,
+           -1.129696636418114,
+           -1.2012118474264977,
+           -1.2649518523521972,
+           -1.3197821937166203,
+           -1.3647525680636563,
+           -1.3991270256167783,
+           -1.422409030359345,
+           -1.4343606757335328,
+           -1.4350154952712644,
+           -1.4246844664383183,
+           -1.403954975844263,
+           -1.3736826905183568,
+           -1.3349764587720074,
+           -1.2891765407916957,
+           -1.2378266391080397,
+           -1.1826403581970524,
+           -1.1254628666810196,
+           -1.0682286612628547,
+           -1.012916435456618,
+           -0.9615021357086698,
+           -0.915911340579359,
+           -0.8779721238670313,
+           -0.8493695591857597,
+           -0.8316029915432974,
+           -0.825947141602961,
+           -0.8334180219409579,
+           -0.8547445337764124,
+           -0.8903464800112822,
+           -0.9403195791719776,
+           -1.0044278986597757,
+           -1.082103948634785,
+           -1.1724564941962423,
+           -1.2742859577677252,
+           -1.3861071002969643,
+           -1.5061784935297962,
+           -1.6325381305469744,
+           -1.763044372020153,
+           -1.8954212949373046,
+           -2.027307402094149,
+           -2.156306567129229,
+           -2.2800400333715944,
+           -2.3961982566844755,
+           -2.502591383545141,
+           -2.5971971858045326,
+           -2.6782053322110633,
+           -2.7440569624548923,
+           -2.793478640122645,
+           -2.8255098938678582,
+           -2.8395237080716673,
+           -2.835239491598667,
+           -2.81272823187432,
+           -2.772409727078032,
+           -2.7150419772455034,
+           -2.6417030009334987,
+           -2.553765523302136,
+           -2.452865149662798,
+           -2.340862791644401,
+           -2.2198022474413355,
+           -2.0918639498805467,
+           -1.9593159835834446,
+           -1.8244635332121577,
+           -1.6895979572487687,
+           -1.5569466852267166,
+           -1.428625110793619,
+           -1.3065915991244965,
+           -1.192606646408767,
+           -1.0881971234469183,
+           -0.9946264074674734,
+           -0.9128710593052671,
+           -0.8436045407263643,
+           -0.7871882929723207,
+           -0.7436703168279142,
+           -0.7127912111579736,
+           -0.693997445430958,
+           -0.6864614667129061,
+           -0.6891080772700311,
+           -0.7006463692833328,
+           -0.7196063719022209,
+           -0.7443794561317282,
+           -0.7732614575033676,
+           -0.8044974171616429,
+           -0.8363268102886781,
+           -0.8670281273823498,
+           -0.8949616987871462,
+           -0.9186097053360117,
+           -0.936612396596026,
+           -0.9477996409707246,
+           -0.9512170561514762,
+           -0.9461461109520092,
+           -0.9321177467768152,
+           -0.908919234878937,
+           -0.8765941599089955,
+           -0.8354355966457746,
+           -0.7859727207861756,
+           -0.7289512618841721,
+           -0.6653083627660906,
+           -0.5961425510971023,
+           -0.5226796516944165,
+           -0.44623556960682564,
+           -0.3681769513827293,
+           -0.2898807834110207,
+           -0.21269401047665493,
+           -0.137894254146841,
+           -0.06665267941550491,
+           -5.967853287909973e-16
+          ],
+          [
+           0,
+           0.05933748657657987,
+           0.11232997621343613,
+           0.1586425793477552,
+           0.19817438564987142,
+           0.23106192658269287,
+           0.25767595320446324,
+           0.2786115987134404,
+           0.2946721683452041,
+           0.3068469663457403,
+           0.3162837266086895,
+           0.324256356191014,
+           0.33212882567102453,
+           0.3413161439962478,
+           0.3532434354230707,
+           0.3693041903066077,
+           0.3908187884354288,
+           0.4189943925817963,
+           0.4548872809158403,
+           0.49936863057694647,
+           0.5530946823603512,
+           0.6164821101687366,
+           0.6896892912096598,
+           0.7726040270425937,
+           0.8648381051090845,
+           0.9657289193037191,
+           1.074348190723387,
+           1.1895176503967155,
+           1.3098313690307202,
+           1.433684249049775,
+           1.5593060357100221,
+           1.6848000608461176,
+           1.808185808471204,
+           1.9274442891678676,
+           2.0405651325984757,
+           2.145594256541829,
+           2.24068094798471,
+           2.3241231976244285,
+           2.394410163623842,
+           2.4502607028453185,
+           2.4906569966238843,
+           2.5148724113138714,
+           2.522492868642813,
+           2.5134311540763203,
+           2.48793375922299,
+           2.44658003270512,
+           2.3902735985364405,
+           2.3202261873686725,
+           2.237934209430566,
+           2.1451485740853693,
+           2.043838425348027,
+           1.936149611385708,
+           1.8243588353085742,
+           1.7108245412486303,
+           1.5979356711791302,
+           1.488059482119009,
+           1.383489638935367,
+           1.2863957942426771,
+           1.19877583395749,
+           1.1224119056758446,
+           1.058831258668174,
+           1.0092728110666092,
+           0.9746602244933381,
+           0.9555821122308702,
+           0.952279837810218,
+           0.9646431807058492,
+           0.9922139590589375,
+           1.0341975105455423,
+           1.089481746254691,
+           1.1566633132695876,
+           1.2340802339036663,
+           1.3198502373003211,
+           1.411913866045711,
+           1.5080813297805697,
+           1.6060819921895888,
+           1.703615319238969,
+           1.798402086501131,
+           1.8882346425260148,
+           1.9710250534523817,
+           2.0448500106445,
+           2.107991466641636,
+           2.1589720730106943,
+           2.196584624082898,
+           2.219914859781106,
+           2.2283571450952193,
+           2.221622719164814,
+           2.199740389040986,
+           2.163049727528349,
+           2.1121870165118852,
+           2.0480643523786406,
+           1.9718424942547124,
+           1.8848981847816304,
+           1.7887868034233319,
+           1.6852013206682175,
+           1.5759286053620107,
+           1.4628041947823243,
+           1.3476666666118922,
+           1.2323127530464697,
+           1.1184543099554094,
+           1.007678199074497,
+           0.9014100601139274,
+           0.800882844519354,
+           0.7071108561364465,
+           0.6208698994305779,
+           0.5426839768805558,
+           0.472818807728881,
+           0.4112822647131667,
+           0.3578316481512052,
+           0.3119875422676579,
+           0.2730538313174667,
+           0.24014329707792081,
+           0.21220807855422705,
+           0.18807415279022557,
+           0.16647889553820466,
+           0.1461107047090581,
+           0.1256496198721653,
+           0.10380784881884614,
+           0.07936911786919816,
+           0.05122579601183064,
+           0.018412803243403407,
+           -0.019862600931990562,
+           -0.06419594416334509,
+           -0.11496624931620443,
+           -0.1723228440314362,
+           -0.23617863235953448,
+           -0.30621002022623584,
+           -0.3818635126327291,
+           -0.4623688260253765,
+           -0.5467581886149375,
+           -0.6338913389190965,
+           -0.7224855825776948,
+           -0.8111501333737126,
+           -0.8984238498090971,
+           -0.9828153864686412,
+           -1.0628447121305649,
+           -1.137084905900637,
+           -1.2042031296419415,
+           -1.2629996900351876,
+           -1.3124441464201966,
+           -1.3517074901257082,
+           -1.3801895156068307,
+           -1.3975406210604042,
+           -1.4036774133868923,
+           -1.3987916460189294,
+           -1.3833521844280625,
+           -1.3580998689154393,
+           -1.3240353232303097,
+           -1.2823999361710872,
+           -1.234650417133733,
+           -1.1824274912186945,
+           -1.1275194508457622,
+           -1.0718214150341046,
+           -1.0172912611780958,
+           -0.9659032843874719,
+           -0.9196007039379701,
+           -0.8802481734059469,
+           -0.8495854596250663,
+           -0.8291834353968931,
+           -0.8204034823139705,
+           -0.8243613242218204,
+           -0.8418962105402485,
+           -0.8735462443034943,
+           -0.9195305053571322,
+           -0.9797384581630468,
+           -1.0537269600238008,
+           -1.1407250034756695,
+           -1.2396461405624934,
+           -1.3491083512427477,
+           -1.467460937846778,
+           -1.5928178567172593,
+           -1.7230967411337184,
+           -1.8560627302092907,
+           -1.9893761000949606,
+           -2.1206425994615654,
+           -2.247465323194348,
+           -2.367496918228897,
+           -2.4784909044930235,
+           -2.578350912299387,
+           -2.6651766848412346,
+           -2.7373057695526772,
+           -2.793349923198177,
+           -2.8322253802080413,
+           -2.8531762789561332,
+           -2.8557907028565754,
+           -2.840008968396693,
+           -2.8061239762618784,
+           -2.754773630068566,
+           -2.6869255153230895,
+           -2.60385421449424,
+           -2.5071118080732817,
+           -2.3984922719752553,
+           -2.27999062472031,
+           -2.153757800064899,
+           -2.0220523191844255,
+           -1.8871899087817925,
+           -1.751492255896183,
+           -1.617236105682622,
+           -1.4866038947066078,
+           -1.3616370697475622,
+           -1.2441931718352435,
+           -1.1359076690389895,
+           -1.0381614018086254,
+           -0.9520543644217809,
+           -0.8783863888158325,
+           -0.8176451266788132,
+           -0.7700015463623926,
+           -0.7353129773924659,
+           -0.7131335516212017,
+           -0.7027317109098173,
+           -0.7031142810526174,
+           -0.7130564546165143,
+           -0.7311368853093962,
+           -0.7557769768091547,
+           -0.7852833525745929,
+           -0.8178924223278384,
+           -0.8518159173142917,
+           -0.8852862510983645,
+           -0.9166005758265241,
+           -0.9441624451585734,
+           -0.9665200633103735,
+           -0.9824001930751248,
+           -0.9907369118796211,
+           -0.9906945409095723,
+           -0.9816842246381535,
+           -0.9633738028488892,
+           -0.9356907902885226,
+           -0.8988184560490068,
+           -0.8531851712019481,
+           -0.7994473646567082,
+           -0.7384665893806959,
+           -0.671281349941942,
+           -0.5990744740863202,
+           -0.5231369224548686,
+           -0.4448290188061494,
+           -0.3655401460451612,
+           -0.2866479894235742,
+           -0.20947841659273925,
+           -0.13526706458703888,
+           -0.0651236568193224,
+           -5.808141763773391e-16
+          ],
+          [
+           0,
+           0.05736744614557171,
+           0.1082119612821843,
+           0.1523170313423562,
+           0.18970348642891552,
+           0.22062925037096734,
+           0.24558240085144004,
+           0.26526770965157204,
+           0.2805870033634145,
+           0.29261384721444894,
+           0.30256320430118805,
+           0.3117568557292656,
+           0.3215854805053922,
+           0.33346838461786776,
+           0.3488119342431662,
+           0.36896778672124136,
+           0.39519202381847884,
+           0.42860627450981176,
+           0.47016186943311616,
+           0.5206079973710784,
+           0.580464737342507,
+           0.6500017205106471,
+           0.7292230370857323,
+           0.8178588481564714,
+           0.9153639947868372,
+           1.0209237209341764,
+           1.1334664471691411,
+           1.2516833532986242,
+           1.3740543542930392,
+           1.498879889763135,
+           1.624317796754555,
+           1.7484244026344926,
+           1.869198862710934,
+           1.984629678816547,
+           2.092742272687774,
+           2.1916464532157574,
+           2.2795826104965657,
+           2.3549654923135717,
+           2.4164244697792046,
+           2.4628392771766063,
+           2.4933703147272097,
+           2.5074827295893876,
+           2.5049636368160377,
+           2.4859320047186495,
+           2.450840904145735,
+           2.4004720043159504,
+           2.3359223845749733,
+           2.2585839171977318,
+           2.17011565657716,
+           2.0724098403994273,
+           1.967552264513107,
+           1.8577779313078753,
+           1.7454229881148289,
+           1.6328740645356274,
+           1.5225161834033645,
+           1.416680457627807,
+           1.3175927935248217,
+           1.2273248001338584,
+           1.1477480539687264,
+           1.0804927908164312,
+           1.0269119924679548,
+           0.9880517091411705,
+           0.9646283109196265,
+           0.9570131973613665,
+           0.9652253175178465,
+           0.9889316672457912,
+           1.0274557414018644,
+           1.079793729884251,
+           1.1446380631116593,
+           1.2204077388636096,
+           1.305284702660314,
+           1.3972554119073155,
+           1.4941565933010137,
+           1.593724106395957,
+           1.6936437560882884,
+           1.7916028547363776,
+           1.8853413216931583,
+           1.9727011244228467,
+           2.051672910657261,
+           2.1204387540425125,
+           2.1774100345884286,
+           2.2212595974785554,
+           2.250947476377281,
+           2.265739626736477,
+           2.265219286804242,
+           2.249290764812754,
+           2.2181756357066984,
+           2.1724015152131364,
+           2.112783758512364,
+           2.0404006008452042,
+           1.9565624139238644,
+           1.8627758911840673,
+           1.760704093346432,
+           1.6521233805872113,
+           1.5388783265853245,
+           1.4228357511942327,
+           1.3058390215482132,
+           1.1896637558266807,
+           1.0759760201523778,
+           0.9662940383744023,
+           0.861954338638635,
+           0.7640831421509405,
+           0.6735736614272081,
+           0.591069821115398,
+           0.5169567480799597,
+           0.45135820306623975,
+           0.39414094831077534,
+           0.3449258684127794,
+           0.3031054900823385,
+           0.26786738433912183,
+           0.2382227864102111,
+           0.21303963767474263,
+           0.19107914379142055,
+           0.17103485636372315,
+           0.15157322429559092,
+           0.1313745268710768,
+           0.10917309437580973,
+           0.08379574388434524,
+           0.054197407078702,
+           0.01949300236249427,
+           -0.02101529684281611,
+           -0.06781612443177505,
+           -0.12117290149995509,
+           -0.1811141657766376,
+           -0.24743051657879664,
+           -0.3196782683535741,
+           -0.3971897304749871,
+           -0.47908985751691285,
+           -0.5643188471434718,
+           -0.651660106286532,
+           -0.7397728644006585,
+           -0.8272285889158066,
+           -0.9125502557097478,
+           -0.994253449122761,
+           -1.0708882137623463,
+           -1.1410805554694163,
+           -1.2035724920256023,
+           -1.2572595854551742,
+           -1.3012249463904064,
+           -1.3347687855136758,
+           -1.3574326954978075,
+           -1.3690179764701202,
+           -1.3695974656208196,
+           -1.359520493501548,
+           -1.3394107617871702,
+           -1.3101571155098357,
+           -1.2728973625657245,
+           -1.228995470140675,
+           -1.1800126371629927,
+           -1.1276728997075205,
+           -1.0738240684618872,
+           -1.0203949203223113,
+           -0.9693496667812745,
+           -0.9226407974212777,
+           -0.8821614455703594,
+           -0.8496984437031234,
+           -0.826887227879941,
+           -0.815169713515228,
+           -0.8157561998730745,
+           -0.8295922694182467,
+           -0.8573315326718741,
+           -0.8993149323067442,
+           -0.9555571651755425,
+           -1.0257406115597287,
+           -1.1092169812820072,
+           -1.2050167008273915,
+           -1.3118658788048716,
+           -1.4282105035321064,
+           -1.5522473507462393,
+           -1.6819609157567075,
+           -1.8151655367930923,
+           -1.9495517485038583,
+           -2.082735799691032,
+           -2.212311190023821,
+           -2.3359010286385176,
+           -2.451209994509591,
+           -2.5560746848669202,
+           -2.6485111736173623,
+           -2.7267586658664253,
+           -2.7893182256923996,
+           -2.8349856701043037,
+           -2.86287785981402,
+           -2.8724517737322195,
+           -2.8635159251607885,
+           -2.8362338593442127,
+           -2.7911196599402994,
+           -2.729025581507836,
+           -2.6511221116768553,
+           -2.558870945732629,
+           -2.453991523558933,
+           -2.3384219301951648,
+           -2.214275093001763,
+           -2.083791317419504,
+           -1.9492882869300283,
+           -1.8131097090808899,
+           -1.6775738170069563,
+           -1.5449229341420514,
+           -1.4172752788727412,
+           -1.2965801265584136,
+           -1.184577360142125,
+           -1.0827623296767894,
+           -0.9923568082652497,
+           -0.9142866804708748,
+           -0.8491668329571324,
+           -0.7972935400802179,
+           -0.7586444537638128,
+           -0.7328861217530376,
+           -0.7193887758351263,
+           -0.7172479563099655,
+           -0.7253123751897008,
+           -0.7422172723042071,
+           -0.766422389297866,
+           -0.7962535795507597,
+           -0.8299469899144784,
+           -0.8656946947685907,
+           -0.9016906355603883,
+           -0.9361757202696094,
+           -0.9674809670122274,
+           -0.9940676334251275,
+           -1.0145633570323283,
+           -1.0277934393128363,
+           -1.0328065349061264,
+           -1.0288941540184824,
+           -1.0156035469054794,
+           -0.9927437102305094,
+           -0.9603844318195666,
+           -0.9188484683946846,
+           -0.8686971257939036,
+           -0.8107096785819783,
+           -0.7458572216275692,
+           -0.6752716862737933,
+           -0.6002108746626742,
+           -0.5220204645778412,
+           -0.4420940113909769,
+           -0.36183202150431315,
+           -0.2826011919081815,
+           -0.20569490264796825,
+           -0.1322960133541784,
+           -0.06344295246763862,
+           -5.636419149508749e-16
+          ],
+          [
+           0,
+           0.05531225383177577,
+           0.10397869763732347,
+           0.14590368647568489,
+           0.18123024707205315,
+           0.21033608829665051,
+           0.23382297566984217,
+           0.2524997387780711,
+           0.26735934748171697,
+           0.2795506488215669,
+           0.29034549761442335,
+           0.3011021362734098,
+           0.3132257802616842,
+           0.32812744219935824,
+           0.3471820780103343,
+           0.3716871612945874,
+           0.4028227867101339,
+           0.4416143696237754,
+           0.4888989484240168,
+           0.5452960091547773,
+           0.6111836416481264,
+           0.6866807048314345,
+           0.771635529614405,
+           0.8656215244314441,
+           0.9679398751910492,
+           1.077629352391286,
+           1.1934830579744775,
+           1.3140717676299598,
+           1.437773355152714,
+           1.562807628385535,
+           1.6872757651802337,
+           1.8092034162866333,
+           1.9265864432148632,
+           2.037438185457801,
+           2.139837104925927,
+           2.231973637286584,
+           2.3121950906613176,
+           2.3790474716501695,
+           2.431313186038192,
+           2.468043655222234,
+           2.488586007145576,
+           2.4926031395143293,
+           2.480086609931503,
+           2.451361978512398,
+           2.40708640937371,
+           2.3482385237008856,
+           2.2761006843329734,
+           2.1922340753692495,
+           2.0984471156874296,
+           1.9967579081533673,
+           1.8893515726808847,
+           1.7785334375524535,
+           1.6666791664100604,
+           1.5561829755119574,
+           1.4494051452957188,
+           1.348620050741447,
+           1.2559659259502414,
+           1.1733975399257095,
+           1.1026428936729866,
+           1.0451649550110942,
+           1.0021293291893234,
+           0.9743786233695954,
+           0.96241410467917,
+           0.9663850786973914,
+           0.9860862321160323,
+           1.0209629943575713,
+           1.0701247827435807,
+           1.13236580900022,
+           1.2061929460086886,
+           1.2898599870991894,
+           1.3814074798875204,
+           1.4787071863031447,
+           1.579510113203148,
+           1.6814969763871415,
+           1.7823299068709488,
+           1.8797041832099137,
+           1.9713987780447186,
+           2.0553245407083662,
+           2.1295688998009688,
+           2.192436058529203,
+           2.2424817690865653,
+           2.27854190758253,
+           2.299754224649389,
+           2.3055728150535053,
+           2.295775028250272,
+           2.270460726438539,
+           2.230043982740128,
+           2.1752374950770674,
+           2.1070301666529567,
+           2.026658467373301,
+           1.9355723380734873,
+           1.835396527475195,
+           1.727888357265007,
+           1.6148929910516787,
+           1.4982973363070797,
+           1.3799837335013732,
+           1.261784582979071,
+           1.1454390278795525,
+           1.0325527514824275,
+           0.9245618613407987,
+           0.8227017226856934,
+           0.7279814726634676,
+           0.6411647983446485,
+           0.5627573988908184,
+           0.4930013798996171,
+           0.4318766501171322,
+           0.37910921189028784,
+           0.3341860614237141,
+           0.2963762475047816,
+           0.2647574820593509,
+           0.23824755658192007,
+           0.21563969862254817,
+           0.19564090509112111,
+           0.17691221657164127,
+           0.15810985091211982,
+           0.13792609618460103,
+           0.11512887311108287,
+           0.08859891493168477,
+           0.0573635774573489,
+           0.02062638203050617,
+           -0.022208492990437072,
+           -0.07151742368291165,
+           -0.1274447568362154,
+           -0.18989677052102377,
+           -0.2585423472816913,
+           -0.3328203527642822,
+           -0.4119535371560676,
+           -0.4949686059090947,
+           -0.5807219441936206,
+           -0.6679303304973216,
+           -0.7552058425493486,
+           -0.8410940466799286,
+           -0.9241144726971654,
+           -1.0028023126663392,
+           -1.0757502452714718,
+           -1.1416492787055783,
+           -1.1993275245534447,
+           -1.247785862468074,
+           -1.28622952946826,
+           -1.3140947665969662,
+           -1.3310697770476019,
+           -1.3371093906892384,
+           -1.3324429867102712,
+           -1.3175753949543199,
+           -1.293280673233343,
+           -1.2605888380573194,
+           -1.2207658053077555,
+           -1.1752869709118494,
+           -1.1258050251815879,
+           -1.0741127440426121,
+           -1.0221016321068654,
+           -0.9717174030927169,
+           -0.92491336963795,
+           -0.8836028748472861,
+           -0.8496119303770806,
+           -0.8246332295836538,
+           -0.810182679057909,
+           -0.807559538264594,
+           -0.8178111762317504,
+           -0.8417033482027703,
+           -0.8796967664075596,
+           -0.9319305907356008,
+           -0.9982133006988324,
+           -1.0780212336559507,
+           -1.1705048901362476,
+           -1.2745029197537143,
+           -1.3885635152316609,
+           -1.5109727620292026,
+           -1.639789321401054,
+           -1.7728846696091085,
+           -1.9079879792664316,
+           -2.0427346138127747,
+           -2.174717115747151,
+           -2.3015375057289176,
+           -2.4208596745978106,
+           -2.530460644654798,
+           -2.6282795003674435,
+           -2.7124628414720044,
+           -2.781405691983539,
+           -2.833786904959725,
+           -2.868598232424835,
+           -2.885166379508883,
+           -2.8831675279622426,
+           -2.8626339927325,
+           -2.8239528618989347,
+           -2.7678566604133605,
+           -2.6954062671709984,
+           -2.607966498335725,
+           -2.5071749431157553,
+           -2.3949047971229582,
+           -2.2732225792011054,
+           -2.144341736770839,
+           -2.0105732394411784,
+           -1.8742743286085901,
+           -1.7377966303918422,
+           -1.6034348496193367,
+           -1.4733772434965489,
+           -1.3496590255606147,
+           -1.234119774811362,
+           -1.1283658234057907,
+           -1.0337384715590494,
+           -0.9512887334184251,
+           -0.8817591562680501,
+           -0.8255730814789732,
+           -0.7828315334428184,
+           -0.7533177368117507,
+           -0.7365090772905014,
+           -0.7315961415350307,
+           -0.737508301811976,
+           -0.7529451551169506,
+           -0.7764129882376615,
+           -0.8062653231325364,
+           -0.8407465037999151,
+           -0.8780372187611846,
+           -0.916300813944471,
+           -0.9537292400144283,
+           -0.9885874962159346,
+           -1.0192554790393458,
+           -1.0442662172255617,
+           -1.0623395728953777,
+           -1.0724106093757648,
+           -1.073651966515049,
+           -1.0654897403625379,
+           -1.0476125320791507,
+           -1.0199735065990778,
+           -0.9827854804501739,
+           -0.9365092357619155,
+           -0.8818354293841002,
+           -0.8196606278977471,
+           -0.751058147072102,
+           -0.6772445043174345,
+           -0.5995424016639793,
+           -0.5193412420563512,
+           -0.4380562411826668,
+           -0.35708722920301006,
+           -0.2777782408348029,
+           -0.20137896823098417,
+           -0.129009099596472,
+           -0.061626488865485725,
+           -5.454322126788771e-16
+          ],
+          [
+           0,
+           0.053191662542790466,
+           0.0996711972958141,
+           0.13946524333197263,
+           0.17283837484229878,
+           0.2002853801639731,
+           0.22251701634698465,
+           0.24043960587036392,
+           0.25512900382722326,
+           0.2677996122544059,
+           0.27976924950894216,
+           0.29242079334033594,
+           0.30716160373860574,
+           0.3253817935012099,
+           0.34841244914699687,
+           0.3774849113837716,
+           0.4136922025855359,
+           0.4579536391455731,
+           0.5109835903324623,
+           0.5732652442493674,
+           0.645030118169605,
+           0.7262439079446491,
+           0.8165991128937815,
+           0.9155147025275626,
+           1.022142913872587,
+           1.1353830874922268,
+           1.2539022710630794,
+           1.3761621460693485,
+           1.5004516701781514,
+           1.6249246792712908,
+           1.7476415626961646,
+           1.8666140163785687,
+           1.9798517938033784,
+           2.0854103167077804,
+           2.181437977184144,
+           2.2662219616017216,
+           2.3382314544586262,
+           2.3961571363796423,
+           2.4389459736869967,
+           2.465830405321322,
+           2.4763511637828364,
+           2.4703731170389247,
+           2.4480936843584065,
+           2.410043556743099,
+           2.3570796376948957,
+           2.2903703079525735,
+           2.2113733039497623,
+           2.1218066795118524,
+           2.0236134893017645,
+           1.9189209865766006,
+           1.8099952631242437,
+           1.699192372461398,
+           1.588907065680378,
+           1.4815203305280005,
+           1.37934695684479,
+           1.284584354547509,
+           1.1992638237852897,
+           1.1252054213485507,
+           1.063977484180533,
+           1.0168617619331155,
+           0.9848249785510937,
+           0.9684974910581519,
+           0.9681595457356742,
+           0.9837354518125492,
+           1.0147958049961838,
+           1.0605677022375013,
+           1.1199526996776972,
+           1.1915520823765415,
+           1.2736988416246466,
+           1.3644955975894402,
+           1.4618575655662827,
+           1.5635595465761267,
+           1.6672858303015161,
+           1.770681832607694,
+           1.8714062527144908,
+           1.9671825273255275,
+           2.055848380820102,
+           2.135402321379736,
+           2.204046011357783,
+           2.2602215443287013,
+           2.3026427884709157,
+           2.330320103075144,
+           2.342577898378047,
+           2.33906468455397,
+           2.3197554392168436,
+           2.284946309666576,
+           2.235241851761109,
+           2.1715351871492174,
+           2.0949816302542157,
+           2.006966491711061,
+           1.909067902147598,
+           1.8030156159405166,
+           1.6906468460813064,
+           1.5738602463768534,
+           1.4545691943622163,
+           1.3346555366950934,
+           1.215924938322581,
+           1.1000649279694368,
+           0.9886066568013613,
+           0.8828912864430766,
+           0.7840417994724589,
+           0.6929408832134335,
+           0.6102153797299574,
+           0.5362276253804182,
+           0.47107382640790735,
+           0.4145894372731949,
+           0.3663613303032696,
+           0.3257463731988511,
+           0.29189586932855016,
+           0.26378516857554757,
+           0.24024762746647707,
+           0.22001198961259305,
+           0.2017421738011414,
+           0.18407839945454169,
+           0.1656785490332565,
+           0.14525866500956977,
+           0.12163150528886442,
+           0.09374213469789096,
+           0.06069961000046848,
+           0.02180391978854293,
+           -0.023432534125096702,
+           -0.07526948370979172,
+           -0.1337297819890671,
+           -0.19859707389925563,
+           -0.2694202192451044,
+           -0.3455243596427527,
+           -0.4260283473918554,
+           -0.509868087359777,
+           -0.5958251874329739,
+           -0.6825601728516583,
+           -0.7686493983690151,
+           -0.852624692767979,
+           -0.9330146953791815,
+           -1.0083867958104018,
+           -1.0773885673940018,
+           -1.1387875924619815,
+           -1.1915086133341883,
+           -1.2346670060116458,
+           -1.267597662473274,
+           -1.2898784799993819,
+           -1.3013477893116359,
+           -1.3021152042211446,
+           -1.2925655401624825,
+           -1.273355623357995,
+           -1.2454039920488384,
+           -1.209873671750362,
+           -1.1681483833124633,
+           -1.1218027112466895,
+           -1.0725669160701912,
+           -1.0222872143620987,
+           -0.9728824702784016,
+           -0.9262983393632418,
+           -0.8844599771284383,
+           -0.8492244691778804,
+           -0.8223341554331172,
+           -0.8053720077812613,
+           -0.7997201784455399,
+           -0.8065227665168647,
+           -0.8266537540179943,
+           -0.8606909428897558,
+           -0.9088965832778191,
+           -0.9712052248714179,
+           -1.0472191506576993,
+           -1.1362115705104612,
+           -1.2371375649772232,
+           -1.348652582046428,
+           -1.4691381061708466,
+           -1.5967339439052644,
+           -1.7293764084949697,
+           -1.86484154062339,
+           -2.0007923778814836,
+           -2.1348291844483045,
+           -2.264541477486846,
+           -2.3875606397404256,
+           -2.5016118899554742,
+           -2.6045643945376793,
+           -2.6944783450220413,
+           -2.769647895537108,
+           -2.828638950803803,
+           -2.87032091600882,
+           -2.8938916622095188,
+           -2.898895121311995,
+           -2.885231099223468,
+           -2.853157080272843,
+           -2.803281985935037,
+           -2.73655204166732,
+           -2.6542290926321197,
+           -2.55786188769714,
+           -2.4492510170335637,
+           -2.3304083378515195,
+           -2.2035118517069714,
+           -2.0708571022721274,
+           -1.934806241947268,
+           -1.7977359673077857,
+           -1.661985545913143,
+           -1.529806149957372,
+           -1.4033126758400638,
+           -1.2844391639303836,
+           -1.1748988412275516,
+           -1.0761496935868313,
+           -0.9893663365752722,
+           -0.9154187982656098,
+           -0.8548586572310545,
+           -0.807912798871709,
+           -0.7744848674305443,
+           -0.7541643042181914,
+           -0.7462426792533562,
+           -0.749736848235005,
+           -0.7634183037818213,
+           -0.7858479431787432,
+           -0.8154153480232278,
+           -0.8503815672304681,
+           -0.8889243163280075,
+           -0.9291844547024293,
+           -0.9693125796302311,
+           -1.0075145820005977,
+           -1.0420950433686613,
+           -1.07149741640329,
+           -1.0943400192657209,
+           -1.1094469866821934,
+           -1.1158734535776307,
+           -1.1129243977254868,
+           -1.1001667321212658,
+           -1.07743441154964,
+           -1.0448264967053689,
+           -1.0026982987444923,
+           -0.9516459027755497,
+           -0.8924845361478718,
+           -0.8262214022672819,
+           -0.7540237392011391,
+           -0.6771829810721113,
+           -0.5970759962335516,
+           -0.5151244470938618,
+           -0.432753360471617,
+           -0.3513500134537662,
+           -0.2722242275352027,
+           -0.1965711236900657,
+           -0.12543732401688423,
+           -0.05969149344006156,
+           -5.263588573108712e-16
+          ],
+          [
+           0,
+           0.051026086179067516,
+           0.09533127189854657,
+           0.13306479622958847,
+           0.1646110254126837,
+           0.19057804190484726,
+           0.21177987792037148,
+           0.2292128552935833,
+           0.24402664847096792,
+           0.2574908267859053,
+           0.27095775233022495,
+           0.2858228076418679,
+           0.30348300056422406,
+           0.3252950401087145,
+           0.35253399574559297,
+           0.38635364273673106,
+           0.42774955810025805,
+           0.4775259664619601,
+           0.5362672439917975,
+           0.6043148740838916,
+           0.6817505132464556,
+           0.7683856731791415,
+           0.8637583590238547,
+           0.9671368284216467,
+           1.0775304556757017,
+           1.1937075045252343,
+           1.3142194363145259,
+           1.4374312121405517,
+           1.5615568921232421,
+           1.6846996961970115,
+           1.8048955722952638,
+           1.9201592225197237,
+           2.0285314683096862,
+           2.128126793574673,
+           2.217179891368554,
+           2.2940900553955252,
+           2.3574623021576975,
+           2.406144181874416,
+           2.43925733472685,
+           2.456222971159084,
+           2.4567805979569566,
+           2.4409994721645796,
+           2.409282438686061,
+           2.3623619904160105,
+           2.301288577470811,
+           2.2274113799513255,
+           2.1423519420430264,
+           2.047971239639577,
+           1.946330914762469,
+           1.8396495538642894,
+           1.7302550100866372,
+           1.620533868643028,
+           1.512879227241468,
+           1.4096380080250153,
+           1.3130590327541092,
+           1.2252430784637787,
+           1.1480960869119368,
+           1.0832866288242406,
+           1.0322086249654443,
+           0.995950202810438,
+           0.9752694230301464,
+           0.9705774476514668,
+           0.9819295455363903,
+           1.0090241450343012,
+           1.0512099528085428,
+           1.1075009665635411,
+           1.1765990223515688,
+           1.256923338863982,
+           1.346646355939108,
+           1.4437350164549472,
+           1.5459965134040417,
+           1.6511274203475212,
+           1.7567650461065718,
+           1.860539805319344,
+           1.9601273765253742,
+           2.053299429175332,
+           2.137971740110631,
+           2.21224858760219,
+           2.274462405274335,
+           2.323207796806952,
+           2.357369152254322,
+           2.3761412646672646,
+           2.379042517548892,
+           2.365920395267851,
+           2.336949255418988,
+           2.2926204896617284,
+           2.2337253831748654,
+           2.16133115804362,
+           2.0767508483583814,
+           1.9815078005955176,
+           1.8772957184302237,
+           1.7659352734684484,
+           1.6493283800299463,
+           1.5294112812596465,
+           1.4081076143669806,
+           1.2872826142828095,
+           1.1686995777912876,
+           1.0539796452635835,
+           0.9445658662006339,
+           0.8416924002350695,
+           0.746359569982981,
+           0.6593153296179092,
+           0.5810435471294387,
+           0.5117593231189699,
+           0.45141138908922607,
+           0.39969144802567175,
+           0.3560501441687675,
+           0.31971918164212904,
+           0.28973895721479337,
+           0.2649909347878676,
+           0.24423387163423915,
+           0.22614291190170194,
+           0.20935049374923323,
+           0.19248797441726082,
+           0.17422686354736447,
+           0.15331856946968606,
+           0.12863160555817124,
+           0.0991852730018447,
+           0.06417893066701491,
+           0.02301607971290704,
+           -0.02467737271498437,
+           -0.0790411535341354,
+           -0.13997528517559277,
+           -0.20714151282320967,
+           -0.2799714648476173,
+           -0.357681337643862,
+           -0.439292725142831,
+           -0.5236590519293348,
+           -0.6094969212667695,
+           -0.6954215591590382,
+           -0.7799854261969623,
+           -0.8617189831392702,
+           -0.9391725361767743,
+           -1.0109580551843538,
+           -1.0757898538536932,
+           -1.132523044586271,
+           -1.180188732862166,
+           -1.2180249942366685,
+           -1.2455027802336454,
+           -1.2623460246593114,
+           -1.2685453661498483,
+           -1.264365062505162,
+           -1.2503428435691009,
+           -1.2272826278187936,
+           -1.1962402089585558,
+           -1.158502198136312,
+           -1.1155586804070257,
+           -1.0690702064016777,
+           -1.0208298877213906,
+           -0.9727214936246272,
+           -0.9266745538237247,
+           -0.8846175549045782,
+           -0.848430373884161,
+           -0.8198971202384796,
+           -0.8006605565796037,
+           -0.7921792379638544,
+           -0.7956884512242041,
+           -0.8121659500947266,
+           -0.8423033712628454,
+           -0.886484083499776,
+           -0.9447680698936266,
+           -1.0168842756360663,
+           -1.1022306748750668,
+           -1.1998821242148054,
+           -1.3086058820723019,
+           -1.4268844869111343,
+           -1.5529455079426497,
+           -1.684797513632636,
+           -1.8202714504284017,
+           -1.9570664903074353,
+           -2.0927992943615012,
+           -2.2250555534392533,
+           -2.351442608031135,
+           -2.469641919579183,
+           -2.5774601650107023,
+           -2.6728777555839605,
+           -2.7540936394220474,
+           -2.819565333013214,
+           -2.8680432384098467,
+           -2.8985984371735842,
+           -2.910643306039312,
+           -2.903944469072818,
+           -2.8786277826527384,
+           -2.835175238505179,
+           -2.7744138616673553,
+           -2.697496869995911,
+           -2.6058775450543314,
+           -2.5012764364615547,
+           -2.3856426788799054,
+           -2.2611103389568474,
+           -2.129950825371376,
+           -1.9945224858784372,
+           -1.8572185787187425,
+           -1.7204148404605064,
+           -1.5864178774643158,
+           -1.4574155836405671,
+           -1.3354307336530127,
+           -1.2222788195766658,
+           -1.119531092283578,
+           -1.0284836391709318,
+           -0.9501331804865887,
+           -0.8851601011497288,
+           -0.8339190576990435,
+           -0.7964373152018256,
+           -0.77242078117691,
+           -0.7612675174390625,
+           -0.7620883308289734,
+           -0.7737338744558554,
+           -0.7948275364823246,
+           -0.8238032573841555,
+           -0.858947302315676,
+           -0.8984429254539172,
+           -0.9404168001162286,
+           -0.9829860535166688,
+           -1.0243047390145428,
+           -1.0626086016642573,
+           -1.0962570441289845,
+           -1.1237712782013956,
+           -1.1438677502457029,
+           -1.1554860541844356,
+           -1.157810690002012,
+           -1.1502861854576354,
+           -1.13262526975104,
+           -1.1048099659490234,
+           -1.067085649576329,
+           -1.0199482993643543,
+           -0.9641253382572832,
+           -0.9005506240904615,
+           -0.8303342958506025,
+           -0.7547283094509522,
+           -0.6750886033244877,
+           -0.592834916220907,
+           -0.5094093353681428,
+           -0.42623468126911396,
+           -0.3446738351893193,
+           -0.26599108690323436,
+           -0.19131652427044338,
+           -0.12161440416111167,
+           -0.05765633825407502,
+           -5.066041218302564e-16
+          ],
+          [
+           0,
+           0.04883640464639346,
+           0.09100113029620994,
+           0.1267652235064782,
+           0.1566299907203431,
+           0.1813119724631828,
+           0.20172178727088247,
+           0.21893739900955825,
+           0.2341725081060094,
+           0.24874089627461113,
+           0.2640176623062399,
+           0.2813983706141156,
+           0.3022571923445965,
+           0.32790514944556454,
+           0.3595495743201091,
+           0.39825587147028196,
+           0.44491261346206784,
+           0.5002009229268944,
+           0.5645689871345669,
+           0.6382124245252689,
+           0.7210610766279408,
+           0.8127726376502432,
+           0.9127333617201436,
+           1.020065908597072,
+           1.1336442071377826,
+           1.2521150364532914,
+           1.3739258520378046,
+           1.4973582225401572,
+           1.6205660963677093,
+           1.7416179896782704,
+           1.8585420817814637,
+           1.969373123247627,
+           2.0722000082082235,
+           2.1652128368603467,
+           2.246748297790536,
+           2.315332232420521,
+           2.369718304937488,
+           2.40892178908638,
+           2.432247596081962,
+           2.4393118029334797,
+           2.4300560943996414,
+           2.404754700866722,
+           2.3640135945456286,
+           2.308761893111475,
+           2.2402356086858926,
+           2.1599540662524768,
+           2.0696894946192077,
+           1.971430460486173,
+           1.8673399679076608,
+           1.7597091776999485,
+           1.6509078108575894,
+           1.5433323840744277,
+           1.4393534819151275,
+           1.3412632976184191,
+           1.2512246722138218,
+           1.1712228296084417,
+           1.1030209442870211,
+           1.0481205897162196,
+           1.007728001578576,
+           0.9827269533325868,
+           0.9736588856093086,
+           0.9807107593954942,
+           1.0037109199832701,
+           1.0421330687326817,
+           1.0951082474125216,
+           1.161444549931101,
+           1.239654093258887,
+           1.3279866077253613,
+           1.4244688508084715,
+           1.5269489118105408,
+           1.6331443607362297,
+           1.74069310600817,
+           1.8472057645001883,
+           1.950318315188174,
+           2.0477438052537953,
+           2.1373219047368845,
+           2.217065162100572,
+           2.285200896919495,
+           2.3402077752236474,
+           2.3808462451015453,
+           2.4061821617080152,
+           2.415603098079981,
+           2.4088270170062414,
+           2.3859031652139415,
+           2.3472052397467187,
+           2.293417062984088,
+           2.225511182714144,
+           2.1447209826206324,
+           2.05250704235984,
+           1.9505186213443626,
+           1.8405512531554673,
+           1.724501525463869,
+           1.6043201813614023,
+           1.4819647106759535,
+           1.3593526034470704,
+           1.2383164122909252,
+           1.1205617166112687,
+           1.007629000951348,
+           0.9008603543276983,
+           0.8013717698501447,
+           0.7100316775663917,
+           0.6274461819888602,
+           0.5539513032499465,
+           0.4896123416391501,
+           0.43423030390949263,
+           0.3873551507541107,
+           0.3483054527311461,
+           0.3161938809601032,
+           0.28995781314254493,
+           0.2683942085033403,
+           0.2501978002574374,
+           0.23400157377695208,
+           0.2184184447397819,
+           0.20208302549049456,
+           0.18369237024231802,
+           0.1620446204853348,
+           0.13607453021791993,
+           0.10488493487197019,
+           0.06777333589075996,
+           0.02425290207601944,
+           -0.02593266424596567,
+           -0.08280078722070748,
+           -0.14612842369389004,
+           -0.21545725922773193,
+           -0.2901055598283572,
+           -0.36918637106538366,
+           -0.45163158983973267,
+           -0.5362212796768528,
+           -0.6216174620178974,
+           -0.7064014970779339,
+           -0.7891140714763454,
+           -0.8682967384925135,
+           -0.9425339123046647,
+           -1.0104942011018063,
+           -1.070969975984098,
+           -1.1229141128359088,
+           -1.1654729119071006,
+           -1.1980142930238324,
+           -1.220150480875524,
+           -1.2317545318047516,
+           -1.232970207558869,
+           -1.2242148687088792,
+           -1.2061752367272294,
+           -1.17979605463185,
+           -1.1462618571141026,
+           -1.1069722376273783,
+           -1.063511167576186,
+           -1.0176110772815712,
+           -0.9711125458942829,
+           -0.9259205643865814,
+           -0.883958429184843,
+           -0.8471203914962205,
+           -0.817224227161956,
+           -0.7959649028515554,
+           -0.7848704962236299,
+           -0.7852614806724865,
+           -0.7982144105225281,
+           -0.8245309417843053,
+           -0.864712999253873,
+           -0.9189447558180064,
+           -0.9870819278349517,
+           -1.0686487153367346,
+           -1.1628425318206,
+           -1.2685464800674489,
+           -1.3843493423637194,
+           -1.5085726703325004,
+           -1.6393043858099745,
+           -1.7744381441207997,
+           -1.9117175686687864,
+           -2.0487843444956195,
+           -2.183229061385369,
+           -2.312643626629822,
+           -2.434674025492891,
+           -2.5470721948007213,
+           -2.6477457922938594,
+           -2.734804691035563,
+           -2.806603103178396,
+           -2.861776338957038,
+           -2.8992713324537323,
+           -2.918370212436308,
+           -2.9187063608418184,
+           -2.9002725792855704,
+           -2.863421170997084,
+           -2.808855937276099,
+           -2.7376162792633165,
+           -2.651053782872273,
+           -2.55080184258507,
+           -2.438739044156299,
+           -2.316947173110111,
+           -2.187664841697752,
+           -2.0532378286694946,
+           -1.9160673013579648,
+           -1.7785571363761303,
+           -1.643061572603736,
+           -1.5118344176939829,
+           -1.386980987434337,
+           -1.2704138870168982,
+           -1.1638136463871351,
+           -1.0685951007668864,
+           -0.9858802652003071,
+           -0.9164782920774566,
+           -0.8608729270038732,
+           -0.8192176953915667,
+           -0.7913388642545154,
+           -0.7767460355209467,
+           -0.7746500433433057,
+           -0.7839876528966924,
+           -0.8034523962820497,
+           -0.8315307363334533,
+           -0.8665426248813337,
+           -0.9066854213414312,
+           -0.9500800627894505,
+           -0.9948183297021036,
+           -1.0390100333643717,
+           -1.0808289619117617,
+           -1.118556461723492,
+           -1.1506215983214503,
+           -1.1756369342901807,
+           -1.1924290786035188,
+           -1.2000632991327058,
+           -1.1978616445245285,
+           -1.1854141891639927,
+           -1.1625831913450313,
+           -1.1295001356213972,
+           -1.0865558110540519,
+           -1.034383753178372,
+           -0.973837544576135,
+           -0.9059626227804097,
+           -0.8319633810309865,
+           -0.7531664637332656,
+           -0.6709812514714708,
+           -0.5868585977953019,
+           -0.5022489200915222,
+           -0.4185607587094183,
+           -0.3371209018834903,
+           -0.25913712935616057,
+           -0.18566455611949315,
+           -0.11757646121444382,
+           -0.055540367522827,
+           -4.863570375660247e-16
+          ],
+          [
+           0,
+           0.04664376333502752,
+           0.08672297034970054,
+           0.12062857519358562,
+           0.14897489675885242,
+           0.17258108630306981,
+           0.19244674463235095,
+           0.2097223300972825,
+           0.22567513607050219,
+           0.2416517341782522,
+           0.2590378743447374,
+           0.27921690224647194,
+           0.303527797266725,
+           0.33322394836982483,
+           0.3694337710713956,
+           0.4131242261721469,
+           0.46506823116962126,
+           0.5258168599708337,
+           0.5956771080499654,
+           0.6746958614663163,
+           0.7626505526290985,
+           0.8590468172454175,
+           0.9631232897251486,
+           1.0738634928769508,
+           1.1900145965645754,
+           1.310112643655631,
+           1.4325136745280778,
+           1.5554300278228796,
+           1.6769709589360025,
+           1.795186602395857,
+           1.9081142127269604,
+           2.013825553024255,
+           2.1104742629753726,
+           2.196342029500413,
+           2.2698824038431407,
+           2.329761158431163,
+           2.3748921539954972,
+           2.404467790482532,
+           2.417983241738115,
+           2.4152538207435774,
+           2.396424985775011,
+           2.3619746742553187,
+           2.3127078359630864,
+           2.2497432261242865,
+           2.1744927071060545,
+           2.08863349032734,
+           1.9940739230923674,
+           1.8929135840658087,
+           1.7873985921090298,
+           1.679873152687124,
+           1.5727284610624392,
+           1.4683501496355666,
+           1.369065506359001,
+           1.2770917011120033,
+           1.1944862369924985,
+           1.1231007940917737,
+           1.0645395556317352,
+           1.0201230022189427,
+           0.9908580319106176,
+           0.9774151148895623,
+           0.9801130254140323,
+           0.9989115143757457,
+           1.033412097619368,
+           1.0828669427232807,
+           1.1461956448923252,
+           1.222009495637128,
+           1.3086426705554288,
+           1.4041895990964042,
+           1.5065476336442403,
+           1.6134640111287708,
+           1.722586000657333,
+           1.8315130577640943,
+           1.937849761531164,
+           2.039258296090822,
+           2.133509253183949,
+           2.2185295771068994,
+           2.2924465463862504,
+           2.353626786041737,
+           2.4007094278498284,
+           2.43263268053285,
+           2.4486532336929807,
+           2.4483580945850494,
+           2.431668641154834,
+           2.398836863622458,
+           2.350433955622949,
+           2.2873315998998054,
+           2.210676468279761,
+           2.121858616873121,
+           2.0224746012210426,
+           1.9142862589653886,
+           1.7991762065886163,
+           1.6791011694982703,
+           1.556044309504876,
+           1.4319677295514193,
+           1.3087663221044759,
+           1.1882240853458341,
+           1.0719739613561545,
+           0.961462154692141,
+           0.8579177705957132,
+           0.7623284725841543,
+           0.6754227028993662,
+           0.5976588401971987,
+           0.5292214912011639,
+           0.4700249312990267,
+           0.4197235277895694,
+           0.3777288032326261,
+           0.343232629526242,
+           0.3152358900943156,
+           0.2925818117325789,
+           0.2739930526033959,
+           0.25811154143773346,
+           0.24353999744560106,
+           0.22888402235158026,
+           0.21279364626502137,
+           0.19400322795641747,
+           0.17136865701532336,
+           0.143900879079707,
+           0.11079486394707154,
+           0.07145325737455632,
+           0.025504097657460586,
+           -0.027187865931415776,
+           -0.08651654802395954,
+           -0.15213671532821066,
+           -0.22347292981292932,
+           -0.29973501188185303,
+           -0.37993961775194796,
+           -0.46293736481047437,
+           -0.5474447926880194,
+           -0.6320803198663533,
+           -0.7154032491037321,
+           -0.7959547925325318,
+           -0.8723000310855166,
+           -0.9430696944000007,
+           -1.0070006473000614,
+           -1.062973997416614,
+           -1.110049794807527,
+           -1.1474973772173143,
+           -1.1748205218334302,
+           -1.1917766934015035,
+           -1.1983898261511379,
+           -1.194956239481576,
+           -1.182043460706159,
+           -1.1604819080202982,
+           -1.1313495687321613,
+           -1.0959499871115828,
+           -1.0557840484591403,
+           -1.0125162068289428,
+           -0.967935949187442,
+           -0.9239154149652927,
+           -0.882364193740278,
+           -0.8451824025073594,
+           -0.8142131955969877,
+           -0.7911958834151998,
+           -0.7777208301250816,
+           -0.7751872652189656,
+           -0.7847650804179597,
+           -0.8073615929592867,
+           -0.8435941412416003,
+           -0.8937692417605304,
+           -0.95786888059776,
+           -1.0355443422120019,
+           -1.126117797079567,
+           -1.2285916822792171,
+           -1.341665720007507,
+           -1.4637612328934348,
+           -1.593052236437355,
+           -1.7275026223325918,
+           -1.8649085959553515,
+           -2.002945400657856,
+           -2.1392172539160854,
+           -2.2713093385515686,
+           -2.396840638220706,
+           -2.5135163815194677,
+           -2.619178864046096,
+           -2.7118554525268497,
+           -2.78980263883845,
+           -2.851545102941364,
+           -2.895908860182821,
+           -2.9220477073287547,
+           -2.9294623396788912,
+           -2.918011684878448,
+           -2.8879161833577913,
+           -2.839752936229837,
+           -2.7744428343141214,
+           -2.6932299720483392,
+           -2.5976538327725316,
+           -2.4895149027882524,
+           -2.3708345265557638,
+           -2.243809950639759,
+           -2.110765616274726,
+           -1.974101846988073,
+           -1.8362421365142994,
+           -1.6995802718629416,
+           -1.5664285261870998,
+           -1.438968126090238,
+           -1.3192031389911427,
+           -1.2089188396322903,
+           -1.1096455029325094,
+           -1.0226284359358397,
+           -0.9488049079298807,
+           -0.888788468700705,
+           -0.8428609645318593,
+           -0.8109723743869274,
+           -0.7927483993410488,
+           -0.7875055513960868,
+           -0.7942733079063599,
+           -0.8118227293542132,
+           -0.8387007852537193,
+           -0.8732694992413934,
+           -0.9137489131662779,
+           -0.9582627838873405,
+           -1.0048858675654129,
+           -1.0516916158638367,
+           -1.0967991073009034,
+           -1.1384180649566746,
+           -1.1748908680340597,
+           -1.2047305479132548,
+           -1.226653867162246,
+           -1.23960870970687,
+           -1.2427951587154455,
+           -1.235679801953989,
+           -1.2180029782938178,
+           -1.189778859322608,
+           -1.1512884420905625,
+           -1.1030657083485023,
+           -1.045877377715164,
+           -0.9806968427472479,
+           -0.9086730188756054,
+           -0.8310949680082742,
+           -0.749353258166264,
+           -0.6648991002543849,
+           -0.5792023550476854,
+           -0.49370952743908647,
+           -0.4098028603954437,
+           -0.3287616080761286,
+           -0.25172650706237987,
+           -0.17966837819980952,
+           -0.1133616813949771,
+           -0.05336371464901254,
+           -4.658115920408005e-16
+          ],
+          [
+           0,
+           0.04446936909140338,
+           0.08253856908962462,
+           0.1147154663234348,
+           0.1417224195332687,
+           0.16447438151067087,
+           0.18405148250039738,
+           0.20166681915709217,
+           0.21863029957447427,
+           0.23630949995872155,
+           0.25608856921200435,
+           0.2793262719515567,
+           0.3073142869030276,
+           0.3412368754628035,
+           0.3821330045293673,
+           0.4308619491838956,
+           0.4880733158814577,
+           0.5541823175883864,
+           0.6293510014747385,
+           0.7134759805961927,
+           0.8061830571963243,
+           0.906828950920573,
+           1.0145101647216517,
+           1.128078839079946,
+           1.2461652659387215,
+           1.3672065619758331,
+           1.4894808408369833,
+           1.6111460797911266,
+           1.7302827515999004,
+           1.8449391904050674,
+           1.9531785837568998,
+           2.0531264335332824,
+           2.143017307759236,
+           2.221239713844996,
+           2.286377961406749,
+           2.337249948782353,
+           2.372939900064331,
+           2.392825196736142,
+           2.3965965869930113,
+           2.384271213188543,
+           2.356198069743675,
+           2.3130556860881906,
+           2.25584201731508,
+           2.185856714598399,
+           2.1046761333992006,
+           2.0141216154794472,
+           1.9162217463667057,
+           1.8131694390655824,
+           1.7072748237965563,
+           1.600915029150677,
+           1.496482019640664,
+           1.3963297062026312,
+           1.3027215684402802,
+           1.217780019706744,
+           1.143438708623677,
+           1.0813988842098328,
+           1.0330908580097296,
+           0.9996414777269148,
+           0.9818483857427036,
+           0.9801616759541397,
+           0.994673387471265,
+           1.0251150881189013,
+           1.0708636089005492,
+           1.1309547972633849,
+           1.2041049668532695,
+           1.2887395390894634,
+           1.383028201751415,
+           1.484925755985957,
+           1.5922176894413698,
+           1.702569402852315,
+           1.8135779329990214,
+           1.9228249585723043,
+           2.0279298484301616,
+           2.126601514650797,
+           2.2166878655541598,
+           2.29622171563149,
+           2.3634620985324912,
+           2.41693004368297,
+           2.455438013898914,
+           2.4781123571353625,
+           2.484408296411587,
+           2.474117163771348,
+           2.447365772392887,
+           2.404608011030684,
+           2.3466089321872845,
+           2.2744217851954334,
+           2.1893586133468923,
+           2.092955186244334,
+           1.9869311709868285,
+           1.8731465554303985,
+           1.7535554209653041,
+           1.6301582190284172,
+           1.504953733612096,
+           1.379891910744737,
+           1.2568287054344855,
+           1.1374840377427984,
+           1.0234038640447756,
+           0.9159272593577271,
+           0.8161592747015253,
+           0.7249501831523919,
+           0.6428815633740269,
+           0.570259494118936,
+           0.5071149519021488,
+           0.4532113213122976,
+           0.4080587478216272,
+           0.3709348909794102,
+           0.3409114758154031,
+           0.3168858961280327,
+           0.2976169986672925,
+           0.2817640751314303,
+           0.2679280118953822,
+           0.254693497360068,
+           0.2406711649580913,
+           0.22453855666693667,
+           0.20507882713857664,
+           0.18121617131292206,
+           0.15204704701007135,
+           0.11686637621170937,
+           0.07518804167289503,
+           0.026759145759970838,
+           -0.028432337837478287,
+           -0.09015671578656659,
+           -0.15794854842649242,
+           -0.23111928452474326,
+           -0.3087762229562945,
+           -0.38984730100668014,
+           -0.47311105597253944,
+           -0.557230970351958,
+           -0.6407932946555244,
+           -0.7223473486959968,
+           -0.8004472345189031,
+           -0.8736938536668273,
+           -0.9407761092914351,
+           -1.0005101900928646,
+           -1.0518758778086121,
+           -1.0940488919146527,
+           -1.1264283825753763,
+           -1.148658803279639,
+           -1.160645535039002,
+           -1.1625637910040323,
+           -1.1548604999575416,
+           -1.1382490451279086,
+           -1.1136969166716502,
+           -1.0824065174356516,
+           -1.045789537666472,
+           -1.0054354807487003,
+           -0.9630750746197025,
+           -0.9205394383554228,
+           -0.8797159871154867,
+           -0.8425021482615896,
+           -0.8107580246996463,
+           -0.786259176675295,
+           -0.7706506994004723,
+           -0.7654037507528085,
+           -0.7717756313439846,
+           -0.79077443968941,
+           -0.823129219909562,
+           -0.8692663908759432,
+           -0.9292930970858456,
+           -1.002987956419199,
+           -1.0897995023233722,
+           -1.1888524322305989,
+           -1.2989615846909746,
+           -1.4186533794525986,
+           -1.5461942721728161,
+           -1.6796256031030645,
+           -1.8168040612132275,
+           -1.9554468457192664,
+           -2.093180489315621,
+           -2.2275922145230864,
+           -2.356282628772415,
+           -2.4769185268188,
+           -2.587284561783585,
+           -2.6853325687796543,
+           -2.769227377192553,
+           -2.837388028035233,
+           -2.8885234194503036,
+           -2.9216615338337193,
+           -2.9361715510479436,
+           -2.931778320123938,
+           -2.9085688426460568,
+           -2.8669906102819347,
+           -2.807841832061173,
+           -2.732253779327273,
+           -2.641665663111163,
+           -2.5377926354615368,
+           -2.4225876687223398,
+           -2.298198210928853,
+           -2.1669186379075533,
+           -2.0311396203514844,
+           -1.8932955947514938,
+           -1.7558115689059717,
+           -1.6210505048275248,
+           -1.4912625039623713,
+           -1.3685369722202265,
+           -1.2547588665872342,
+           -1.1515700229598693,
+           -1.0603364388389984,
+           -0.9821222377868072,
+           -0.9176708787058963,
+           -0.8673939960948154,
+           -0.8313680718266507,
+           -0.8093389492534508,
+           -0.8007340112174951,
+           -0.8046816594885788,
+           -0.8200375587456404,
+           -0.8454169477352425,
+           -0.8792321775705403,
+           -0.9197345157369323,
+           -0.9650591571655408,
+           -1.01327231304053,
+           -1.0624192054774524,
+           -1.1105717828029653,
+           -1.1558749861139348,
+           -1.196590442600175,
+           -1.2311365335703468,
+           -1.2581238833300856,
+           -1.276385436497005,
+           -1.2850004328977398,
+           -1.2833117472829416,
+           -1.2709362317197406,
+           -1.2477678773753806,
+           -1.2139737949939082,
+           -1.169983195108113,
+           -1.1164697253712703,
+           -1.0543276889311037,
+           -0.9846428203487787,
+           -0.9086584303932004,
+           -0.827737844770748,
+           -0.743324151673198,
+           -0.656898336735531,
+           -0.5699369200433373,
+           -0.4838702173656251,
+           -0.4000423266789309,
+           -0.31967389187905954,
+           -0.24382861963831795,
+           -0.17338442462110573,
+           -0.10900995530434957,
+           -0.051147110603532074,
+           -4.451648696675859e-16
+          ],
+          [
+           0,
+           0.04233428475072377,
+           0.07848887540873555,
+           0.10908448208095471,
+           0.1349455272379212,
+           0.15707505311931644,
+           0.17662449276066297,
+           0.19485910514622473,
+           0.213119989871696,
+           0.23278368822505666,
+           0.25522044341956507,
+           0.28175223113968934,
+           0.3136116815779498,
+           0.35190299545176396,
+           0.39756590952035126,
+           0.4513436930106925,
+           0.5137560569307774,
+           0.5850777359594306,
+           0.6653233604945905,
+           0.7542390780582827,
+           0.8513012125535743,
+           0.9557220711193507,
+           1.066462826015201,
+           1.1822532176712852,
+           1.301617649320257,
+           1.422907077923348,
+           1.5443359546021065,
+           1.6640233343365258,
+           1.7800371626918303,
+           1.8904406596646093,
+           1.9933396596679913,
+           2.086929733820921,
+           2.1695419169845764,
+           2.2396858875928607,
+           2.296089502717518,
+           2.3377336727391276,
+           2.3638816675230396,
+           2.3741020765448657,
+           2.3682847958171154,
+           2.3466495810814822,
+           2.309746885485202,
+           2.258450886480712,
+           2.193944796399938,
+           2.117698739394046,
+           2.031440659559531,
+           1.9371208965965827,
+           1.836871222023549,
+           1.732959266917704,
+           1.6277393879376565,
+           1.5236011091166484,
+           1.42291634032009,
+           1.3279866077253624,
+           1.2409915363056885,
+           1.1639397989138176,
+           1.098623691732234,
+           1.0465784128751354,
+           1.0090470117756634,
+           0.986951844295621,
+           0.9808732154592196,
+           0.9910357220430239,
+           1.0173026250665995,
+           1.0591783919466038,
+           1.1158193543249837,
+           1.1860522350697538,
+           1.2684001113548864,
+           1.361115204589837,
+           1.4622177265683276,
+           1.5695398684583342,
+           1.6807738986200482,
+           1.793523239634059,
+           1.9053553266496641,
+           2.0138550098563766,
+           2.1166772544606682,
+           2.2115979122041156,
+           2.296561388639578,
+           2.3697241088173158,
+           2.4294927887607645,
+           2.474556648526316,
+           2.5039128515615094,
+           2.516884620819165,
+           2.5131316605639538,
+           2.4926526996270733,
+           2.455780162432692,
+           2.4031671637602927,
+           2.335767207275548,
+           2.2548071418607387,
+           2.1617540894624523,
+           2.0582771996698312,
+           1.9462052061178705,
+           1.8274808551952628,
+           1.704113346154332,
+           1.5781299619677045,
+           1.4515280812539495,
+           1.3262287431306228,
+           1.2040328895053811,
+           1.086581334357405,
+           0.975319408946077,
+           0.8714671081999995,
+           0.7759954199409409,
+           0.6896093587273466,
+           0.6127380540001501,
+           0.5455320622148463,
+           0.48786788927125607,
+           0.4393595274028486,
+           0.39937663431827114,
+           0.36706881620220216,
+           0.3413953243209254,
+           0.3211593412140217,
+           0.3050459201014539,
+           0.29166255296671867,
+           0.2795812809528821,
+           0.26738122672605347,
+           0.2536904231162858,
+           0.23722583571492623,
+           0.2168305285447472,
+           0.19150700007456845,
+           0.1604458197033593,
+           0.12304881975021738,
+           0.07894624176391635,
+           0.028007394943963478,
+           -0.029655445401037584,
+           -0.09368999446658315,
+           -0.16351368544396055,
+           -0.2383299066111007,
+           -0.3171503163687984,
+           -0.3988226452327814,
+           -0.48206324954427215,
+           -0.565493556171916,
+           -0.6476794339450029,
+           -0.7271724486287718,
+           -0.8025519059563837,
+           -0.8724665629281728,
+           -0.9356748919329659,
+           -0.9910828151736814,
+           -1.0377778876055275,
+           -1.0750589936353672,
+           -1.1024607340363268,
+           -1.1197718121435585,
+           -1.1270468791138106,
+           -1.124611463091854,
+           -1.113059782403218,
+           -1.0932454239936056,
+           -1.0662650507154592,
+           -1.0334354801351548,
+           -0.9962646487876894,
+           -0.9564171349137384,
+           -0.9156750556451962,
+           -0.8758952777247514,
+           -0.838963981003764,
+           -0.8067496885789116,
+           -0.7810559245504383,
+           -0.7635746787434645,
+           -0.7558418467719878,
+           -0.7591957737147728,
+           -0.7747399613103689,
+           -0.8033109035661427,
+           -0.8454518962800638,
+           -0.9013935250707119,
+           -0.9710413775169674,
+           -1.053971351796235,
+           -1.1494327510115283,
+           -1.2563591637018063,
+           -1.3733869414709143,
+           -1.4988808989131253,
+           -1.6309666836377443,
+           -1.767569099584295,
+           -1.9064555190493548,
+           -2.0452833915840563,
+           -2.181650754338314,
+           -2.3131485711153124,
+           -2.4374136783086184,
+           -2.5521810962837064,
+           -2.655334475172554,
+           -2.7449534842751775,
+           -2.8193570233733274,
+           -2.877141230618582,
+           -2.9172113829479964,
+           -2.938806928281214,
+           -2.941519050597486,
+           -2.9253003454566606,
+           -2.8904663703318936,
+           -2.8376890267257657,
+           -2.7679819247640927,
+           -2.6826780710934433,
+           -2.5834004028266015,
+           -2.4720258595644014,
+           -2.3506438380606944,
+           -2.2215100061898956,
+           -2.086996561325243,
+           -1.9495401004219772,
+           -1.8115883230507839,
+           -1.6755468130610345,
+           -1.5437271389152156,
+           -1.41829747720539,
+           -1.3012368993519776,
+           -1.194294369618124,
+           -1.0989533856388964,
+           -1.0164030535670756,
+           -0.9475162321187295,
+           -0.8928352071588262,
+           -0.8525651752547242,
+           -0.8265756253504,
+           -0.8144095170258355,
+           -0.815299966378068,
+           -0.8281939709789855,
+           -0.8517825380132541,
+           -0.8845364286508565,
+           -0.9247466006250996,
+           -0.9705683230311536,
+           -1.0200678551159912,
+           -1.0712705262416011,
+           -1.122209028524494,
+           -1.1709707374225518,
+           -1.2157429085616398,
+           -1.2548546604506576,
+           -1.2868147408067032,
+           -1.31034418672246,
+           -1.3244031229766415,
+           -1.328211095005565,
+           -1.3212604995661335,
+           -1.3033228527277636,
+           -1.274447817089392,
+           -1.2349550934542637,
+           -1.1854194620175715,
+           -1.1266494299362833,
+           -1.0596601016715785,
+           -0.9856410317525409,
+           -0.9059199430503747,
+           -0.8219232942228065,
+           -0.7351347552146547,
+           -0.6470526977478085,
+           -0.5591478274523005,
+           -0.4728220752424623,
+           -0.38936982801383535,
+           -0.30994251372870724,
+           -0.23551746516145994,
+           -0.1668718723264199,
+           -0.10456249883609177,
+           -0.04891168557590666,
+           -4.246151540548214e-16
+          ],
+          [
+           0,
+           0.04025922431950193,
+           0.07461360944651997,
+           0.10379160089803362,
+           0.1287127564672834,
+           0.15045966084470141,
+           0.17024513217856993,
+           0.18937559124529987,
+           0.2092115658743992,
+           0.23112638040695668,
+           0.2564641302772448,
+           0.286498063987692,
+           0.32239048819826904,
+           0.3651552764954536,
+           0.41562399948684237,
+           0.4744166047282592,
+           0.5419174618355296,
+           0.6182574537744775,
+           0.703302643108841,
+           0.7966498757190379,
+           0.8976295083466512,
+           1.0053152646870958,
+           1.1185410422083792,
+           1.2359243130109783,
+           1.3558955913728086,
+           1.4767332824585602,
+           1.5966030850243966,
+           1.7136009994230934,
+           1.8257988939216443,
+           1.931291509820769,
+           2.02824374101355,
+           2.1149370076530505,
+           2.1898135570136392,
+           2.2515175671950995,
+           2.298932000073618,
+           2.331210247188073,
+           2.3478017337390975,
+           2.3484707886418446,
+           2.3333082491464725,
+           2.3027354430092277,
+           2.2575003752950806,
+           2.1986661361059854,
+           2.127591735206834,
+           2.045905754992537,
+           1.9554733899277326,
+           1.8583576041257968,
+           1.7567752850633092,
+           1.6530493969130993,
+           1.5495582384938758,
+           1.448682985832423,
+           1.3527547459186493,
+           1.2640023652036068,
+           1.1845022232710556,
+           1.1161311991676088,
+           1.0605239261011767,
+           1.019035351316861,
+           0.992709494305464,
+           0.9822551510732646,
+           0.9880291285197805,
+           1.0100274149997646,
+           1.0478845052060055,
+           1.1008809041662324,
+           1.1679586411002167,
+           1.2477444338500452,
+           1.3385799631980992,
+           1.438558548032719,
+           1.5455673611004208,
+           1.6573341946655868,
+           1.771477678942078,
+           1.8855597762384504,
+           1.9971393222881348,
+           2.1038253644416494,
+           2.203329054772982,
+           2.2935128944526064,
+           2.372436192986901,
+           2.4383957004318657,
+           2.4899604901057053,
+           2.5260003106890587,
+           2.5457067864195784,
+           2.54860701841557,
+           2.5345693247098082,
+           2.5038010468019403,
+           2.4568385417780303,
+           2.394529666613556,
+           2.318009240585483,
+           2.228668138396387,
+           2.1281168166047832,
+           2.018144205626894,
+           1.900673005800497,
+           1.7777125062414167,
+           1.651310097585097,
+           1.523502672990349,
+           1.3962691055125418,
+           1.2714849543848183,
+           1.1508804888587116,
+           1.0360030277310812,
+           0.928184477859274,
+           0.8285148187774116,
+           0.7378221264328757,
+           0.6566595609610196,
+           0.5852995655450078,
+           0.5237353402373551,
+           0.4716894707440809,
+           0.4286294121922419,
+           0.3937893563116548,
+           0.3661978515374892,
+           0.3447104032327211,
+           0.32804615906559276,
+           0.3148276855740854,
+           0.3036227685381046,
+           0.29298712374651664,
+           0.2815068871866273,
+           0.2678397649784202,
+           0.25075376318002635,
+           0.22916248484415322,
+           0.20215607465834032,
+           0.16902700776183835,
+           0.1292900559212427,
+           0.08269591767971948,
+           0.029238165463117714,
+           -0.030846662300370743,
+           -0.09708581665986661,
+           -0.16878375479974217,
+           -0.24504185726217517,
+           -0.324783920191698,
+           -0.4067867455827559,
+           -0.4897150183377797,
+           -0.5721595454880557,
+           -0.6526778430872863,
+           -0.7298359923589955,
+           -0.8022506503137051,
+           -0.8686300922062704,
+           -0.9278131841172036,
+           -0.9788052331294165,
+           -1.0208097388364705,
+           -1.0532551713806944,
+           -1.0758160253632247,
+           -1.0884275427036318,
+           -1.0912936572675445,
+           -1.0848878858320714,
+           -1.0699470694183577,
+           -1.047458051684348,
+           -1.0186375623466903,
+           -0.9849057489222788,
+           -0.9478539650209581,
+           -0.9092075738062121,
+           -0.8707846572499096,
+           -0.8344516320720242,
+           -0.8020768589431155,
+           -0.7754833904110119,
+           -0.7564020335309709,
+           -0.7464259044720998,
+           -0.74696762430901,
+           -0.7592202483841364,
+           -0.7841229373568475,
+           -0.8223322683395087,
+           -0.8741999519935454,
+           -0.939757569327658,
+           -1.0187087739064402,
+           -1.110429225343523,
+           -1.2139743327231365,
+           -1.3280946965637814,
+           -1.4512589497830688,
+           -1.5816835164822136,
+           -1.7173686367288215,
+           -1.856139850102265,
+           -1.9956939944338112,
+           -2.133648662316921,
+           -2.2675939694289617,
+           -2.3951454277205557,
+           -2.513996684647369,
+           -2.621970887681606,
+           -2.7170694614528648,
+           -2.797517142399005,
+           -2.8618022014022575,
+           -2.908710896500192,
+           -2.9373553327102595,
+           -2.947194061031593,
+           -2.9380449200351735,
+           -2.910089806967337,
+           -2.863871256515667,
+           -2.800280899673857,
+           -2.720540067769476,
+           -2.626172993002334,
+           -2.5189732322520397,
+           -2.4009641011893907,
+           -2.274354046975374,
+           -2.1414880066293267,
+           -2.0047958916205904,
+           -1.8667394051323598,
+           -1.7297584351877742,
+           -1.596218273554142,
+           -1.4683588869277036,
+           -1.3482474139612832,
+           -1.2377349805662616,
+           -1.1384188186256163,
+           -1.0516105424596172,
+           -0.9783112863285487,
+           -0.9191942386676227,
+           -0.8745949287584327,
+           -0.8445094335773509,
+           -0.8286004812408305,
+           -0.8262112374824936,
+           -0.836386377596427,
+           -0.8578998727593901,
+           -0.8892887608284212,
+           -0.9288920314555206,
+           -0.9748936370577613,
+           -1.0253685476711036,
+           -1.0783307012217476,
+           -1.131781662821054,
+           -1.183758798169463,
+           -1.2323817871523943,
+           -1.2758963536068313,
+           -1.3127141646959484,
+           -1.3414479563359112,
+           -1.360941067027896,
+           -1.3702907080524713,
+           -1.3688644595923207,
+           -1.3563096558825978,
+           -1.3325555035788006,
+           -1.2978079616327205,
+           -1.2525375934667375,
+           -1.1974607785728237,
+           -1.1335148364366232,
+           -1.0618277667729699,
+           -0.9836834427061859,
+           -0.9004832044544999,
+           -0.8137048875502446,
+           -0.7248603795312811,
+           -0.6354528309285915,
+           -0.5469346495098859,
+           -0.4606673811016942,
+           -0.37788452660743616,
+           -0.29965826447584337,
+           -0.22687094293059726,
+           -0.1601920794416121,
+           -0.10006145944323012,
+           -0.04667876589314745,
+           -4.0436001113043494e-16
+          ],
+          [
+           0,
+           0.03826435089587519,
+           0.07095087276669022,
+           0.09888964142321793,
+           0.12308752993775146,
+           0.1446973598767792,
+           0.16498281560643255,
+           0.18528005529345262,
+           0.20695704035172113,
+           0.2313716670908166,
+           0.25982981860980425,
+           0.29354446064498,
+           0.33359688194314485,
+           0.38090112833588224,
+           0.4361726012908948,
+           0.49990168825036385,
+           0.5723331661031982,
+           0.6534519738168133,
+           0.7429757892047755,
+           0.8403546720600377,
+           0.9447778557707819,
+           1.055187586580536,
+           1.1702997284591856,
+           1.2886306766842879,
+           1.408529959110368,
+           1.5282177548854043,
+           1.6458264298515861,
+           1.75944507937559,
+           1.8671659856823974,
+           1.9671318400929863,
+           2.0575825523980704,
+           2.136900470738104,
+           2.2036528658763053,
+           2.2566305929876287,
+           2.294881930667379,
+           2.317740708730754,
+           2.3248479708383574,
+           2.3161665717848776,
+           2.2919882786842214,
+           2.25293312613469,
+           2.1999409633202793,
+           2.1342553212830175,
+           2.0573999166015584,
+           1.971148288794551,
+           1.8774872384567882,
+           1.7785748872268359,
+           1.676694315349201,
+           1.5742038444755493,
+           1.4734851196471732,
+           1.376890202938758,
+           1.2866889205249485,
+           1.2050177041765109,
+           1.1338311373597385,
+           1.074857355896959,
+           1.0295583649660713,
+           0.9990962201790644,
+           0.9843058833260343,
+           0.9856754064142743,
+           1.0033339246716515,
+           1.0370477544146244,
+           1.0862246995906921,
+           1.1499264760609598,
+           1.2268889700259755,
+           1.3155498611021503,
+           1.4140829659472787,
+           1.5204384992560158,
+           1.6323883092631177,
+           1.747575027992246,
+           1.8635639851997496,
+           1.977896671488371,
+           2.0881445019228733,
+           2.1919616274694573,
+           2.287135567763537,
+           2.3716344944085272,
+           2.443650077820511,
+           2.5016349204717465,
+           2.5443337325263293,
+           2.570807559011526,
+           2.580450537050952,
+           2.572998843128844,
+           2.548531679398302,
+           2.5074643400497427,
+           2.450533589014445,
+           2.3787757641381373,
+           2.293498195933782,
+           2.1962446869002417,
+           2.0887559363438863,
+           1.9729259123074359,
+           1.8507552637950455,
+           1.7243029308107192,
+           1.5956371453023563,
+           1.4667870221440302,
+           1.3396959157446755,
+           1.2161776654251262,
+           1.0978767727541259,
+           0.9862334486542231,
+           0.882454339981385,
+           0.7874895977088782,
+           0.7020167855422595,
+           0.6264319528777201,
+           0.5608480138894784,
+           0.5051003897620346,
+           0.4587596882950414,
+           0.42115101886740475,
+           0.3913793754457874,
+           0.368360370071199,
+           0.35085546778180143,
+           0.3375107644796231,
+           0.32689826451557663,
+           0.3175585568189405,
+           0.30804375862766237,
+           0.2969595949687722,
+           0.2830055099529824,
+           0.26501176191965065,
+           0.24197253702954818,
+           0.21307422291836908,
+           0.1777181127465841,
+           0.13553695712028602,
+           0.08640494316208361,
+           0.030440852363280736,
+           -0.031995672632037286,
+           -0.10031464200731299,
+           -0.17371272600108217,
+           -0.2511962980885296,
+           -0.3316098987950093,
+           -0.4136693625520307,
+           -0.4959987271171221,
+           -0.5771699446981712,
+           -0.6557443386140893,
+           -0.730314701020105,
+           -0.7995469071820748,
+           -0.8622199305428817,
+           -0.9172631802037937,
+           -0.9637901475421334,
+           -1.0011274399024976,
+           -1.0288383943721535,
+           -1.0467406007186817,
+           -1.0549168162345923,
+           -1.0537189226570074,
+           -1.043764752316507,
+           -1.0259277927767991,
+           -1.0013199618782418,
+           -0.971267823694062,
+           -0.9372827859415354,
+           -0.901025976560175,
+           -0.8642686374873826,
+           -0.8288489935539679,
+           -0.7966266508160779,
+           -0.7694356490443351,
+           -0.7490373356575567,
+           -0.7370742419588708,
+           -0.7350261266685485,
+           -0.744169306744436,
+           -0.7655403223575138,
+           -0.7999048833684207,
+           -0.8477329211122799,
+           -0.9091804247272333,
+           -0.9840785791685921,
+           -1.071930546389819,
+           -1.1719160462427174,
+           -1.2829037039903708,
+           -1.4034709416020197,
+           -1.5319310048856747,
+           -1.6663665425836254,
+           -1.804668991162154,
+           -1.9445828741989626,
+           -2.0837540016132556,
+           -2.2197804545818256,
+           -2.350265169337238,
+           -2.472868888992267,
+           -2.585362238220634,
+           -2.6856756914598816,
+           -2.7719462509602875,
+           -2.842559725423824,
+           -2.8961876013912673,
+           -2.9318176255124713,
+           -2.94877736333738,
+           -2.946750165726859,
+           -2.925783153393102,
+           -2.8862870190848122,
+           -2.8290276409409554,
+           -2.7551096948326945,
+           -2.6659526433710696,
+           -2.563259660061718,
+           -2.4489802144408923,
+           -2.3252671938638425,
+           -2.1944295662993207,
+           -2.0588816928948694,
+           -1.921090476693667,
+           -1.7835215828385718,
+           -1.6485859847308615,
+           -1.5185880794866813,
+           -1.39567657496428,
+           -1.2817992806619052,
+           -1.1786628376593375,
+           -1.0876983009103853,
+           -1.0100333436050684,
+           -0.9464716915554928,
+           -0.8974802196054148,
+           -0.8631839562495026,
+           -0.8433690515388927,
+           -0.8374935716316741,
+           -0.8447057957145656,
+           -0.8638695120594359,
+           -0.8935956440483306,
+           -0.9322793881362629,
+           -0.9781419175264983,
+           -1.0292756008954136,
+           -1.0836916073181104,
+           -1.1393687184518009,
+           -1.1943021481747609,
+           -1.2465511786711676,
+           -1.294284460078767,
+           -1.335821887233831,
+           -1.369672060013902,
+           -1.3945644508975388,
+           -1.4094755416400855,
+           -1.413648346896996,
+           -1.406604912270865,
+           -1.3881515533424365,
+           -1.358376786272036,
+           -1.3176420849142265,
+           -1.2665657794662801,
+           -1.2060005829765705,
+           -1.1370053903079615,
+           -1.060812135453271,
+           -0.9787886139362383,
+           -0.8923982744225952,
+           -0.8031580552242334,
+           -0.7125953853693318,
+           -0.6222054852903514,
+           -0.5334100886276598,
+           -0.44751866456318423,
+           -0.36569315060572705,
+           -0.28891711065481557,
+           -0.21797011492200064,
+           -0.15340799991554277,
+           -0.09554951172872632,
+           -0.04446966826030092,
+           -3.845943725452794e-16
+          ],
+          [
+           0,
+           0.036369079392308594,
+           0.06753677332659992,
+           0.09442773906511236,
+           0.11812752278625817,
+           0.1398492027425286,
+           0.16089630537735802,
+           0.18262298316546755,
+           0.20639251639687195,
+           0.2335352474007009,
+           0.2653070736007427,
+           0.30284961482378103,
+           0.3471531306846346,
+           0.39902319660966584,
+           0.45905205379216824,
+           0.5275954314135858,
+           0.6047555017280035,
+           0.690370473534217,
+           0.7840111610311551,
+           0.8849846872938237,
+           0.9923452990822028,
+           1.1049120869960338,
+           1.22129322671807,
+           1.3399161877487982,
+           1.4590631999132624,
+           1.5769111289798248,
+           1.6915747945137711,
+           1.8011526686274961,
+           1.9037738260281099,
+           1.9976449754986705,
+           2.081096391781921,
+           2.152625585143783,
+           2.2109375933224666,
+           2.2549808560368514,
+           2.2839777339535705,
+           2.2974488595579863,
+           2.295230653704731,
+           2.2774855051806218,
+           2.2447042874031595,
+           2.1977010720712817,
+           2.1376000896211518,
+           2.0658151760411054,
+           1.9840221302868706,
+           1.8941245816459746,
+           1.798214127590795,
+           1.6985256459303153,
+           1.5973888068524318,
+           1.497176907696285,
+           1.4002542235606632,
+           1.3089231083533763,
+           1.225372092535822,
+           1.151626205266987,
+           1.0895007002938957,
+           1.0405592878955983,
+           1.0060778712953378,
+           0.9870146577016083,
+           0.983987364614907,
+           0.9972580748585601,
+           1.026726113010695,
+           1.071929125917751,
+           1.1320523553739539,
+           1.205945896586845,
+           1.2921495464457322,
+           1.3889246654794039,
+           1.4942923111123931,
+           1.6060767514463221,
+           1.7219533419083766,
+           1.8394996447980532,
+           1.9562485965002918,
+           2.069742480728175,
+           2.177586449714512,
+           2.277500349157948,
+           2.3673676465705005,
+           2.4452803353632073,
+           2.5095787867297625,
+           2.558885645672154,
+           2.5921330132828775,
+           2.6085823210598473,
+           2.60783648055208,
+           2.5898440786521837,
+           2.5548955807747893,
+           2.5036116962844304,
+           2.4369242481613522,
+           2.356050067437626,
+           2.2624585980491494,
+           2.1578340454211924,
+           2.044033028762863,
+           1.9230387996421823,
+           1.796913165500259,
+           1.6677473045525661,
+           1.5376126769326255,
+           1.4085132256014496,
+           1.2823400198557975,
+           1.160829425324709,
+           1.0455257889509428,
+           0.9377495080664827,
+           0.8385712123337786,
+           0.7487926295951896,
+           0.6689345355335595,
+           0.5992320068039348,
+           0.539637012473137,
+           0.489828193827875,
+           0.44922750249933946,
+           0.41702319589293485,
+           0.3921985313579277,
+           0.3735653602921707,
+           0.35980170391963834,
+           0.34949229674497806,
+           0.34117101402199623,
+           0.3333640576573103,
+           0.3246327617931923,
+           0.3136148951396953,
+           0.29906338149179384,
+           0.2798814315932347,
+           0.25515317672985777,
+           0.22416901464759467,
+           0.1864450185153855,
+           0.14173591611369477,
+           0.09004131524069371,
+           0.031605028197450084,
+           -0.033092471352158793,
+           -0.10334824643213278,
+           -0.17825736315072174,
+           -0.25673907500766047,
+           -0.3375680249476759,
+           -0.4194096332094905,
+           -0.5008587285284822,
+           -0.5804803938712797,
+           -0.6568519378211655,
+           -0.7286048705414441,
+           -0.7944657597662144,
+           -0.853294867627577,
+           -0.904121522722658,
+           -0.94617526233891,
+           -0.9789118851985372,
+           -1.0020336828302974,
+           -1.0155032645416755,
+           -1.0195505532746942,
+           -1.0146727033181429,
+           -1.0016268715596046,
+           -0.9814159571506764,
+           -0.9552676055157396,
+           -0.9246069469920293,
+           -0.8910237036381121,
+           -0.8562344457514689,
+           -0.8220409086279502,
+           -0.7902853867793453,
+           -0.7628043044532425,
+           -0.7413811157444539,
+           -0.7276997133969197,
+           -0.7232995218263494,
+           -0.7295334169359514,
+           -0.7475295536701773,
+           -0.7781580933904344,
+           -0.8220037091779001,
+           -0.8793446108171209,
+           -0.9501386757968378,
+           -1.0340171019686912,
+           -1.1302858157050706,
+           -1.237934680953179,
+           -1.355654364126932,
+           -1.4818605220043861,
+           -1.6147247993426508,
+           -1.7522119542503325,
+           -1.892122276652044,
+           -2.032138332239,
+           -2.1698749544409495,
+           -2.3029313229323334,
+           -2.4289439111239313,
+           -2.5456390584276694,
+           -2.650883926536487,
+           -2.7427346325105035,
+           -2.8194804143458647,
+           -2.879682775441021,
+           -2.9222086707996207,
+           -2.946256937120325,
+           -2.951377327757153,
+           -2.937481688044705,
+           -2.9048469924377835,
+           -2.85411015779906,
+           -2.786254742293505,
+           -2.7025898319695267,
+           -2.604721602539054,
+           -2.4945182176024994,
+           -2.374068882375082,
+           -2.2456380100251874,
+           -2.111615572682193,
+           -1.974464798228371,
+           -1.8366684350070668,
+           -1.7006748380970227,
+           -1.5688451320822967,
+           -1.4434026762908516,
+           -1.3263860000270817,
+           -1.2196062888486636,
+           -1.1246103905868903,
+           -1.0426501743644192,
+           -0.9746589206703784,
+           -0.921235249434606,
+           -0.8826349102114367,
+           -0.8587705685301285,
+           -0.8492195298555726,
+           -0.8532391521461894,
+           -0.8697895143515305,
+           -0.897562735839364,
+           -0.9350181848740101,
+           -0.9804226766878676,
+           -1.0318946467167711,
+           -1.0874511949630186,
+           -1.145056835332171,
+           -1.2026727506014177,
+           -1.258305350141928,
+           -1.3100529536226524,
+           -1.3561494789234307,
+           -1.395004094921462,
+           -1.425235907551317,
+           -1.445702877816472,
+           -1.4555243199375896,
+           -1.4540964927783093,
+           -1.4411009739354959,
+           -1.4165056889890986,
+           -1.3805586537875083,
+           -1.333774670660815,
+           -1.2769153955399928,
+           -1.2109633577293568,
+           -1.1370906634400733,
+           -1.056623244443947,
+           -0.9710016211343094,
+           -0.8817392322345451,
+           -0.7903794393543789,
+           -0.6984523422194368,
+           -0.607432539062943,
+           -0.5186989364696117,
+           -0.43349765472515184,
+           -0.3529089899770934,
+           -0.277819285445508,
+           -0.20889843333579283,
+           -0.1465835803381533,
+           -0.09106944644289366,
+           -0.04230549340876137,
+           -3.6550863886177547e-16
+          ],
+          [
+           0,
+           0.03459188608033418,
+           0.06440506909359281,
+           0.09045085751478413,
+           0.11388408402462659,
+           0.13596751953581848,
+           0.1580331043781812,
+           0.18144103220955285,
+           0.20753778030849349,
+           0.2376142099866117,
+           0.2728648621423763,
+           0.31434954539931265,
+           0.3629582584910821,
+           0.4193804059464409,
+           0.4840791587375985,
+           0.5572716820611628,
+           0.6389158040561751,
+           0.7287035357421465,
+           0.8260616778813751,
+           0.930159569218046,
+           1.0399238471804961,
+           1.1540599112721717,
+           1.2710796055862927,
+           1.3893344745556273,
+           1.5070537993095332,
+           1.6223864945914723,
+           1.7334458413513427,
+           1.8383559505706213,
+           1.9352988016805848,
+           2.0225606754926884,
+           2.0985768075586795,
+           2.1619731232670625,
+           2.2116039799804543,
+           2.2465849326295815,
+           2.266319655230455,
+           2.2705202889831413,
+           2.2592206445885057,
+           2.232781858354463,
+           2.1918902843471186,
+           2.1375475937904165,
+           2.071053243481185,
+           1.993979662465453,
+           1.9081406859834416,
+           1.815553933282737,
+           1.7183979771613487,
+           1.6189652842687225,
+           1.5196120129862165,
+           1.4227058374215167,
+           1.3305730196142596,
+           1.2454459760823775,
+           1.1694125786842757,
+           1.1043683935157576,
+           1.0519729960278357,
+           1.0136114072868982,
+           0.990361577530138,
+           0.9829687017527475,
+           0.9918269914137744,
+           1.0169693503541144,
+           1.0580652159516204,
+           1.1144266329377661,
+           1.185022431873745,
+           1.2685001917839576,
+           1.3632154815548458,
+           1.4672677019245735,
+           1.5785416934164616,
+           1.6947541392093546,
+           1.8135036790014267,
+           1.9323235631471989,
+           2.0487356178250224,
+           2.1603042631279044,
+           2.2646893274385764,
+           2.3596964331843053,
+           2.4433237902583245,
+           2.513804322514432,
+           2.569642167576768,
+           2.609642727918114,
+           2.6329356083501447,
+           2.6389899478665924,
+           2.6276218379377596,
+           2.598993710350433,
+           2.5536057708400697,
+           2.4922797453444328,
+           2.4161353890642405,
+           2.326560380176944,
+           2.2251743758409908,
+           2.1137881442748823,
+           1.9943587999147734,
+           1.868942256234769,
+           1.7396440706821243,
+           1.6085698869505407,
+           1.4777766808255033,
+           1.3492259871603036,
+           1.2247402279881539,
+           1.1059631768661482,
+           0.9943254844758078,
+           0.8910160580876484,
+           0.796959936094977,
+           0.7128031322618619,
+           0.6389047468052267,
+           0.57533645739875,
+           0.5218893172557593,
+           0.47808760426560676,
+           0.44320928929098585,
+           0.4163125275573261,
+           0.3962674286543895,
+           0.3817922316967309,
+           0.37149290583289374,
+           0.36390511516043345,
+           0.3575374331662769,
+           0.3509146663559408,
+           0.3426201503312939,
+           0.33133591406576085,
+           0.3158796686243904,
+           0.2952376634981466,
+           0.26859256481984023,
+           0.23534564215067133,
+           0.1951327008862826,
+           0.14783336179596135,
+           0.0935734635934538,
+           0.032720544311149784,
+           -0.03412746195580379,
+           -0.10615999924032381,
+           -0.1823776521656705,
+           -0.26162125749445936,
+           -0.3426055854785507,
+           -0.42395669160209226,
+           -0.5042519422233434,
+           -0.5820616460459624,
+           -0.6559911791216069,
+           -0.7247224753491197,
+           -0.7870537676206936,
+           -0.8419365065729206,
+           -0.8885084533106348,
+           -0.9261220377678574,
+           -0.9543671931833148,
+           -0.9730880165341445,
+           -0.9823927612053911,
+           -0.9826568377560891,
+           -0.9745186771198149,
+           -0.9588684934632088,
+           -0.9368301666166621,
+           -0.9097366418801033,
+           -0.8790994135989956,
+           -0.8465728139306902,
+           -0.8139139657401027,
+           -0.7829393750675395,
+           -0.7554792311096072,
+           -0.7333305477499886,
+           -0.718210318627446,
+           -0.7117098664902426,
+           -0.7152515468408035,
+           -0.7300489160385945,
+           -0.7570713962448613,
+           -0.79701436570032,
+           -0.8502754753198234,
+           -0.9169378445526876,
+           -0.9967606244968633,
+           -1.0891772384004312,
+           -1.1933014232951207,
+           -1.3079410061644456,
+           -1.4316191584427633,
+           -1.5626026884514606,
+           -1.6989367571616583,
+           -1.838485242748861,
+           -1.9789758377490423,
+           -2.118048842770833,
+           -2.2533085256662533,
+           -2.382375847208404,
+           -2.502941315400286,
+           -2.6128167215647236,
+           -2.709984532628786,
+           -2.792643765060091,
+           -2.859251245548979,
+           -2.908557269867207,
+           -2.9396348018208056,
+           -2.95190150570739,
+           -2.9451340745227617,
+           -2.9194744982467964,
+           -2.8754281074547823,
+           -2.813853422608745,
+           -2.7359440339398424,
+           -2.6432029261053813,
+           -2.5374098411872112,
+           -2.420582438729582,
+           -2.2949321583779656,
+           -2.162815815709382,
+           -2.0266840620056223,
+           -1.8890279115908137,
+           -1.752324584179904,
+           -1.618983923421515,
+           -1.4912966361635924,
+           -1.3713855503610355,
+           -1.2611610141550769,
+           -1.1622814563603734,
+           -1.076120001931216,
+           -1.003737888072443,
+           -0.9458652611576759,
+           -0.902889755590214,
+           -0.8748530675884189,
+           -0.8614555442132193,
+           -0.8620686154995021,
+           -0.8757547100115478,
+           -0.9012941160923669,
+           -0.9372180868525399,
+           -0.9818473405326984,
+           -1.0333349828149299,
+           -1.0897127769588437,
+           -1.1489396136972554,
+           -1.2089509873793527,
+           -1.2677082689218593,
+           -1.3232465800171742,
+           -1.3737201163087347,
+           -1.4174438387093602,
+           -1.4529305498439158,
+           -1.4789224942301442,
+           -1.4944167631735772,
+           -1.4986839448375824,
+           -1.4912796325361635,
+           -1.4720485856456718,
+           -1.4411215230945371,
+           -1.3989047145259579,
+           -1.346062714315211,
+           -1.2834947541761748,
+           -1.2123054668720765,
+           -1.1337707526683698,
+           -1.0492997181946093,
+           -0.9603937114147614,
+           -0.8686035441455237,
+           -0.775486033375923,
+           -0.6825610035975629,
+           -0.5912698742469459,
+           -0.5029369097126323,
+           -0.41873413540935034,
+           -0.3396508240910917,
+           -0.2664683344239172,
+           -0.1997409419954249,
+           -0.1397831450220608,
+           -0.08666375704975535,
+           -0.04020692124942943,
+           -3.4728682187385985e-16
+          ],
+          [
+           0,
+           0.032950126910679146,
+           0.0615868339784887,
+           0.08699934030184955,
+           0.11040171917148184,
+           0.13309538301462692,
+           0.1564289592359359,
+           0.18175663053256633,
+           0.21039605542475864,
+           0.24358699831108832,
+           0.28245178295805295,
+           0.3279586393244979,
+           0.3808889420813104,
+           0.44180924188877924,
+           0.5110488698612221,
+           0.5886837546941671,
+           0.6745269341817285,
+           0.7681260722661457,
+           0.8687681136215231,
+           0.975491024584845,
+           1.0871023866237592,
+           1.202204431080477,
+           1.3192249361410362,
+           1.4364532531020617,
+           1.552080592955407,
+           1.664243589558917,
+           1.7710700651570788,
+           1.8707258601068668,
+           1.961461553040091,
+           2.041657891340254,
+           2.109868774987105,
+           2.16486068904802,
+           2.2056475601692895,
+           2.2315201184436635,
+           2.242068975454357,
+           2.237200778983901,
+           2.2171469711819993,
+           2.182464855842292,
+           2.134030867455672,
+           2.0730261252873854,
+           2.0009145451681802,
+           1.9194139653156694,
+           1.8304609157642802,
+           1.736169819580609,
+           1.6387875540292833,
+           1.5406444177371679,
+           1.4441026427245973,
+           1.3515036555866486,
+           1.2651153284417782,
+           1.1870804665588757,
+           1.119367755603755,
+           1.0637263377328199,
+           1.0216451035575396,
+           0.9943176782618683,
+           0.9826139474835927,
+           0.9870588151674508,
+           1.007818715172331,
+           1.0446962150973926,
+           1.0971328590323075,
+           1.164220200394894,
+           1.244718781450572,
+           1.3370846272458805,
+           1.4395026431289597,
+           1.549926141117766,
+           1.6661215750989726,
+           1.7857174417276866,
+           1.9062562059381185,
+           2.0252480395402572,
+           2.140225120163764,
+           2.2487952268000924,
+           2.34869338762688,
+           2.4378303851720413,
+           2.514337001950274,
+           2.576602994543298,
+           2.623309913103946,
+           2.6534570332603256,
+           2.666379834686889,
+           2.6617606410809214,
+           2.639631225506096,
+           2.6003673783997634,
+           2.544675628255764,
+           2.4735724923797573,
+           2.3883568125993255,
+           2.2905758940773984,
+           2.181986310464297,
+           2.064510362025177,
+           1.940189272131533,
+           1.811134279257162,
+           1.679476824690734,
+           1.5473190496009184,
+           1.4166857986320236,
+           1.289479281373915,
+           1.16743746907055,
+           1.0520972037318936,
+           0.9447628729640621,
+           0.8464813594835595,
+           0.7580238130845194,
+           0.679874618845809,
+           0.6122277529674511,
+           0.5549905313832019,
+           0.5077945708635101,
+           0.4700136023251028,
+           0.44078760597964733,
+           0.41905258200645046,
+           0.4035751324838728,
+           0.39299091376435175,
+           0.3858459261901855,
+           0.38063954227084956,
+           0.3758681367590811,
+           0.3700681733472627,
+           0.36185762310535674,
+           0.3499746387138411,
+           0.3333124847118465,
+           0.31094982540196503,
+           0.28217559611742155,
+           0.24650782708654864,
+           0.2037059484604376,
+           0.1537762761444782,
+           0.09697055654392046,
+           0.03377762966505513,
+           -0.03509155039457657,
+           -0.10872512523678245,
+           -0.1860371972977817,
+           -0.26579962760036935,
+           -0.34667791417112137,
+           -0.42727019179535547,
+           -0.506148310989642,
+           -0.5818998979753045,
+           -0.6531702694787906,
+           -0.718703077099781,
+           -0.7773785857826757,
+           -0.8282485488809077,
+           -0.8705667269862674,
+           -0.9038142070024842,
+           -0.927718809146794,
+           -0.9422680193844671,
+           -0.9477150494855204,
+           -0.9445778023078911,
+           -0.9336307016487841,
+           -0.9158895294916267,
+           -0.8925895940844721,
+           -0.8651577254549407,
+           -0.8351787563136078,
+           -0.804357291726475,
+           -0.7744756967428358,
+           -0.7473493341262928,
+           -0.7247801617970786,
+           -0.708509849528685,
+           -0.7001735955090155,
+           -0.7012558149521935,
+           -0.7130488351416555,
+           -0.7366156649410931,
+           -0.772757813482557,
+           -0.8219890146611792,
+           -0.8845155740846948,
+           -0.9602238966452075,
+           -1.0486755797697196,
+           -1.1491102739054355,
+           -1.2604563224140883,
+           -1.3813490024499846,
+           -1.5101560012834483,
+           -1.6450095835324074,
+           -1.7838447383175462,
+           -1.9244424455966747,
+           -2.064477071593945,
+           -2.2015667975557554,
+           -2.333325906696238,
+           -2.4574177031560036,
+           -2.571606815410604,
+           -2.673809645422603,
+           -2.7621417637850967,
+           -2.8349611192652207,
+           -2.8909060269163653,
+           -2.9289270199994935,
+           -2.948311794425589,
+           -2.9487026368388887,
+           -2.9301059048715996,
+           -2.892893316212269,
+           -2.8377949973728294,
+           -2.7658844386914767,
+           -2.678555694410667,
+           -2.5774933509427194,
+           -2.4646359581950823,
+           -2.34213377389549,
+           -2.212301805462469,
+           -2.077569244840761,
+           -1.9404264761750303,
+           -1.8033708921886353,
+           -1.6688527813242273,
+           -1.5392225434754585,
+           -1.416680457627805,
+           -1.3032301608032804,
+           -1.200636905963305,
+           -1.1103915492386303,
+           -1.0336810769215325,
+           -0.9713663235232175,
+           -0.9239673577824581,
+           -0.8916568280954769,
+           -0.8742613669704522,
+           -0.8712709604929197,
+           -0.881855998156304,
+           -0.9048915354192116,
+           -0.93898813045633,
+           -0.9825284619251594,
+           -1.0337087999212822,
+           -1.0905842908852215,
+           -1.1511169317198626,
+           -1.2132250508000149,
+           -1.2748330852334662,
+           -1.3339204452675513,
+           -1.388568287991156,
+           -1.4370030825878095,
+           -1.4776359367679384,
+           -1.5090967663929948,
+           -1.530262524831279,
+           -1.5402788618435415,
+           -1.538574749915758,
+           -1.5248697947082936,
+           -1.4991741311905273,
+           -1.4617809934508044,
+           -1.4132522294591696,
+           -1.3543972076479638,
+           -1.2862457256992272,
+           -1.2100156793331867,
+           -1.1270763765359606,
+           -1.038908487404795,
+           -0.9470616990620256,
+           -0.8531111969735877,
+           -0.7586141172720112,
+           -0.6650671088148621,
+           -0.5738661089257413,
+           -0.4862693740099306,
+           -0.4033647171547222,
+           -0.32604179171834,
+           -0.2549701256852281,
+           -0.19058345965080242,
+           -0.1330707755680347,
+           -0.0823742280585077,
+           -0.03819400961675005,
+           -3.3010474504090837e-16
+          ],
+          [
+           0,
+           0.031459866475203664,
+           0.05911014953272174,
+           0.08410850703458353,
+           0.10771763946223206,
+           0.13126616420025256,
+           0.15610747892522828,
+           0.18357771652462715,
+           0.21495391979144313,
+           0.25141356102243556,
+           0.2939964996427712,
+           0.3435704108669897,
+           0.4008006316733518,
+           0.46612525917534786,
+           0.539736203598002,
+           0.6215667468339799,
+           0.7112859917577559,
+           0.8083004112789411,
+           0.9117625239494972,
+           1.0205865393920348,
+           1.1334706365178682,
+           1.2489253650107042,
+           1.3653075002337194,
+           1.4808585376464811,
+           1.5937468886663955,
+           1.7021127388587423,
+           1.804114453999748,
+           1.8979753719012402,
+           1.9820297991981723,
+           2.0547670431463656,
+           2.1148723486859335,
+           2.161263679692497,
+           2.193123378848593,
+           2.2099238606350147,
+           2.211446633663071,
+           2.1977941084961885,
+           2.169393821334757,
+           2.1269948881898313,
+           2.0716566939191496,
+           2.0047300110663775,
+           1.9278309301243894,
+           1.8428081610148188,
+           1.7517044308183105,
+           1.656712850992856,
+           1.5601292547833563,
+           1.4643016090609489,
+           1.371577681826165,
+           1.2842521951059243,
+           1.2045147117088078,
+           1.1343994927452254,
+           1.0757385211818902,
+           1.0301188159367316,
+           0.9988450628010297,
+           0.9829084651469601,
+           0.9829625719069318,
+           0.999306676208849,
+           1.0318771992922755,
+           1.0802472852507787,
+           1.14363463733864,
+           1.2209174307822537,
+           1.310657945011628,
+           1.4111333746491865,
+           1.5203731079301233,
+           1.6362016076343082,
+           1.7562858968208213,
+           1.8781865428989881,
+           1.9994109514839182,
+           2.1174677280541605,
+           2.229920841938158,
+           2.3344423341540264,
+           2.4288623479168003,
+           2.5112153272705027,
+           2.5797813236416465,
+           2.633121469813676,
+           2.670106822934074,
+           2.6899399391900625,
+           2.6921687187655277,
+           2.6766922463018044,
+           2.6437585447531142,
+           2.5939543545369452,
+           2.528187240488174,
+           2.447660511682027,
+           2.3538416092500056,
+           2.2484247707446428,
+           2.1332889127004506,
+           2.010451782584671,
+           1.8820215147134578,
+           1.7501467799590815,
+           1.6169667449210727,
+           1.4845620521371656,
+           1.354907999068084,
+           1.229831030936701,
+           1.1109695726825368,
+           0.999740110619206,
+           0.8973092977798991,
+           0.8045727018645958,
+           0.7221406450734872,
+           0.6503314051880186,
+           0.5891718615531414,
+           0.5384054827655697,
+           0.4975073695440711,
+           0.4657058910125675,
+           0.44201028981688767,
+           0.4252434851539109,
+           0.4140791765304253,
+           0.4070822479923872,
+           0.40275139519160297,
+           0.39956284785673907,
+           0.39601403918583256,
+           0.3906660818328569,
+           0.3821839472431492,
+           0.36937331009875746,
+           0.3512131108624421,
+           0.32688300450016394,
+           0.29578499946164827,
+           0.25755874443046123,
+           0.21209008730807857,
+           0.15951270712299928,
+           0.10020280057937857,
+           0.03476698618514037,
+           -0.03597623426944635,
+           -0.11102094915890963,
+           -0.18920358285550587,
+           -0.269237113654816,
+           -0.3497488463066402,
+           -0.4293207280064204,
+           -0.5065311289668071,
+           -0.5799969686077697,
+           -0.6484150570130202,
+           -0.7106015389142254,
+           -0.7655283736660066,
+           -0.8123558583267894,
+           -0.8504603002338162,
+           -0.8794560678789588,
+           -0.899211391393464,
+           -0.9098574429644894,
+           -0.9117903990430751,
+           -0.9056663659517562,
+           -0.8923892339361201,
+           -0.8730917072048424,
+           -0.849109934459373,
+           -0.8219523313502167,
+           -0.793263338978396,
+           -0.7647829971029247,
+           -0.7383033236806237,
+           -0.7156225808478762,
+           -0.6984985691567982,
+           -0.6886021251666319,
+           -0.6874720014369289,
+           -0.6964722823752251,
+           -0.7167534347968878,
+           -0.7492180097220716,
+           -0.794491903820609,
+           -0.8529019576232648,
+           -0.9244605163322243,
+           -1.0088574114742217,
+           -1.105459641849226,
+           -1.2133188446502818,
+           -1.331186456884091,
+           -1.4575362780131358,
+           -1.5905939617475748,
+           -1.7283727926733554,
+           -1.8687149461908394,
+           -2.009337291972175,
+           -2.1478806852811747,
+           -2.28196159994811,
+           -2.409224893844594,
+           -2.5273964639765634,
+           -2.6343345447062605,
+           -2.7280784292853264,
+           -2.806893451247241,
+           -2.869311146951444,
+           -2.914163631680089,
+           -2.940611356496175,
+           -2.9481635683297367,
+           -2.9366909677121984,
+           -2.9064302430599724,
+           -2.857980352938437,
+           -2.7922906236374363,
+           -2.710640923894169,
+           -2.614614366975981,
+           -2.5060631679983683,
+           -2.3870684469783314,
+           -2.259894911753194,
+           -2.1269414760369076,
+           -1.9906889635990264,
+           -1.8536461175154078,
+           -1.718295172016681,
+           -1.5870382527298903,
+           -1.4621458488945491,
+           -1.345708549006139,
+           -1.2395931505987874,
+           -1.145404147526997,
+           -1.0644514667944465,
+           -0.9977251749422292,
+           -0.945877704989554,
+           -0.9092139730689822,
+           -0.8876895636765065,
+           -0.8809169685249001,
+           -0.8881796710907619,
+           -0.908453681792945,
+           -0.9404359518947413,
+           -0.9825789319852299,
+           -1.0331303971998906,
+           -1.0901775396569002,
+           -1.1516942318341503,
+           -1.2155902950934205,
+           -1.2797615668964761,
+           -1.3421395493620545,
+           -1.4007394408538727,
+           -1.4537054007002195,
+           -1.499351973631349,
+           -1.5362007030969835,
+           -1.563011088665659,
+           -1.578805189008141,
+           -1.5828853348314698,
+           -1.5748445914576739,
+           -1.5545697941321106,
+           -1.5222371660094307,
+           -1.478300714433712,
+           -1.4234737809767368,
+           -1.3587042902527948,
+           -1.2851443975851355,
+           -1.2041153723230362,
+           -1.1170686686309736,
+           -1.025544226072583,
+           -0.9311271060906341,
+           -0.8354036060120119,
+           -0.739917998665288,
+           -0.6461310229994864,
+           -0.555381199878847,
+           -0.46884996885660923,
+           -0.38753153823821657,
+           -0.31220821479519195,
+           -0.24343183431142654,
+           -0.18151175343916096,
+           -0.12650969120431899,
+           -0.07824152930639858,
+           -0.036285998656672744,
+           -3.1412832045472506e-16
+          ],
+          [
+           0,
+           0.030135719370387802,
+           0.05699982559539229,
+           0.08180829852056289,
+           0.10586138235861013,
+           0.13050318318698503,
+           0.15707987291922296,
+           0.18689762157186324,
+           0.2211813888550528,
+           0.26103568628892637,
+           0.30740837266510085,
+           0.36105846992837815,
+           0.42252888533343164,
+           0.49212480156345617,
+           0.5698983524914044,
+           0.6556400420312648,
+           0.7488771910912532,
+           0.8488795173396003,
+           0.9546717688675747,
+           1.0650531505147627,
+           1.1786231052146132,
+           1.2938128466893928,
+           1.4089218883863455,
+           1.5221586805564908,
+           1.6316843562346872,
+           1.7356585004450649,
+           1.8322857974775841,
+           1.9198623801383925,
+           1.996820703337786,
+           2.0617717923819954,
+           2.113543773278629,
+           2.1512156769275563,
+           2.1741456192351607,
+           2.1819925923042054,
+           2.174731254680768,
+           2.152659277453264,
+           2.1163969836602115,
+           2.0668792065333266,
+           2.0053394829473037,
+           1.9332868873545348,
+           1.852475993777046,
+           1.764870624587509,
+           1.6726022005805514,
+           1.5779236433302672,
+           1.483159894633795,
+           1.390656206090678,
+           1.302725412325477,
+           1.2215954324689884,
+           1.1493582454341202,
+           1.087921555160185,
+           1.0389643030031193,
+           1.0038970971973644,
+           0.9838285158829979,
+           0.9795381032995445,
+           0.9914567216959218,
+           1.0196547480924814,
+           1.0638384194598156,
+           1.1233544366556032,
+           1.1972027412821942,
+           1.2840571852665854,
+           1.3822936251521145,
+           1.4900247964001618,
+           1.605141161733347,
+           1.7253567856342973,
+           1.848259167999224,
+           1.9713618765276641,
+           2.092158751974131,
+           2.208178424474958,
+           2.3170378736502877,
+           2.4164937901805303,
+           2.504490551432414,
+           2.5792037070975855,
+           2.639077980642304,
+           2.68285892594179,
+           2.7096175324987697,
+           2.718767243337082,
+           2.7100730328281424,
+           2.6836523828599934,
+           2.6399681902158307,
+           2.5798138310365624,
+           2.5042907950890725,
+           2.414779478695875,
+           2.3129038863218336,
+           2.2004911330545314,
+           2.0795267601246796,
+           1.9521069703152536,
+           1.8203889573538568,
+           1.6865405416041812,
+           1.5526903327208494,
+           1.4208796182979924,
+           1.2930171265571515,
+           1.1708377321400691,
+           1.0558660691417519,
+           0.9493858873217812,
+           0.852415839220018,
+           0.7656922214191423,
+           0.6896590165770682,
+           0.6244653985269119,
+           0.5699706753205885,
+           0.5257564592513688,
+           0.4911456732579148,
+           0.4652278341494387,
+           0.446889898985461,
+           0.4348518255009849,
+           0.42770588402205134,
+           0.4239586696445222,
+           0.42207470170264133,
+           0.4205204642080214,
+           0.41780773675503546,
+           0.41253509039425446,
+           0.4034264764690429,
+           0.3893659169757629,
+           0.3694274105522365,
+           0.3428992960047546,
+           0.30930246207827594,
+           0.2684019542109653,
+           0.22021170216779634,
+           0.1649922723172695,
+           0.10324173033437385,
+           0.035679879664692576,
+           -0.03677368638296556,
+           -0.11302711990756456,
+           -0.19184869637872956,
+           -0.27190316412555576,
+           -0.3517910900708142,
+           -0.4300901473410603,
+           -0.5053972383352299,
+           -0.5763703231621978,
+           -0.6417688286815763,
+           -0.7004915475913929,
+           -0.7516109992634489,
+           -0.7944033127867488,
+           -0.8283728057276429,
+           -0.8532705666246899,
+           -0.8691065018356865,
+           -0.8761544742140666,
+           -0.8749503380179495,
+           -0.8662828569950392,
+           -0.8511776761398009,
+           -0.8308746975526401,
+           -0.8067993825941966,
+           -0.7805286617679772,
+           -0.7537522764345332,
+           -0.7282304989206079,
+           -0.7057492766965812,
+           -0.6880739194928488,
+           -0.6769024935906606,
+           -0.6738201038277448,
+           -0.6802552305986675,
+           -0.6974392465367677,
+           -0.726370166602773,
+           -0.7677815876485216,
+           -0.8221176515148281,
+           -0.8895147223141375,
+           -0.9697903072339334,
+           -1.0624395749213815,
+           -1.166639640574977,
+           -1.2812615968253303,
+           -1.4048900790227175,
+           -1.5358499673717672,
+           -1.6722396510765338,
+           -1.8119701156842178,
+           -1.9528089682261638,
+           -2.092428389212032,
+           -2.2284558991864114,
+           -2.35852675296584,
+           -2.480336728741946,
+           -2.5916940631640712,
+           -2.6905692977712823,
+           -2.775141846451092,
+           -2.8438421669437814,
+           -2.8953885200552043,
+           -2.92881742578204,
+           -2.9435070729720527,
+           -2.9391931048779663,
+           -2.9159763830037364,
+           -2.874322521618052,
+           -2.8150531806063688,
+           -2.739329300200219,
+           -2.6486266527944022,
+           -2.5447042698723594,
+           -2.4295664715567433,
+           -2.3054193783582306,
+           -2.1746229156115064,
+           -2.0396394276782774,
+           -1.9029800986766015,
+           -1.7671504273336527,
+           -1.6345960243335893,
+           -1.5076499907575696,
+           -1.3884830961502381,
+           -1.2790579054011724,
+           -1.181087906718983,
+           -1.096002570894923,
+           -1.0249191278091692,
+           -0.9686216832740467,
+           -0.9275481218355095,
+           -0.9017850534196178,
+           -0.8910708683146695,
+           -0.8948067706537486,
+           -0.9120754700542292,
+           -0.9416670290263344,
+           -0.9821111946127288,
+           -1.0317153905707452,
+           -1.0886074149381628,
+           -1.1507817801964244,
+           -1.2161485520322082,
+           -1.2825834898137625,
+           -1.3479782685539574,
+           -1.4102895688086152,
+           -1.4675858573932559,
+           -1.518090746998134,
+           -1.5602219150341519,
+           -1.5926246789794403,
+           -1.6141994641408972,
+           -1.6241225565880195,
+           -1.621859705106673,
+           -1.6071723170607568,
+           -1.580116179507069,
+           -1.5410328241246487,
+           -1.4905338378278368,
+           -1.4294785957738438,
+           -1.3589460555124067,
+           -1.2802013962485315,
+           -1.194658412017558,
+           -1.1038386689407174,
+           -1.0093285121667697,
+           -0.9127350557920497,
+           -0.8156423078665459,
+           -0.7195685721411605,
+           -0.6259262288290471,
+           -0.5359849294044111,
+           -0.45083914710561324,
+           -0.37138090775862603,
+           -0.29827838779629895,
+           -0.2319609114393562,
+           -0.1726107108748573,
+           -0.1201616361933805,
+           -0.07430482032547978,
+           -0.03450112285696434,
+           -2.995119200007167e-16
+          ],
+          [
+           0,
+           0.028990705596795053,
+           0.05527715278241179,
+           0.08012297446581064,
+           0.10485450734970225,
+           0.13081945889377586,
+           0.15934481177732746,
+           0.19169509742984814,
+           0.22903216266703352,
+           0.2723775170634699,
+           0.3225782843084941,
+           0.38027769003040973,
+           0.44589090370399614,
+           0.5195869161538428,
+           0.6012769802457621,
+           0.6906099744868995,
+           0.7869748716545661,
+           0.8895103117169972,
+           0.9971210948075135,
+           1.1085012305016768,
+           1.2221630086669861,
+           1.336471399042305,
+           1.4496829454802018,
+           1.559988200054819,
+           1.6655566450990051,
+           1.764582980201424,
+           1.8553336081329792,
+           1.9361921397526254,
+           2.0057027536101746,
+           2.0626102909249986,
+           2.105896039849805,
+           2.134808262696088,
+           2.1488866437054357,
+           2.1479799799950268,
+           2.1322566009502744,
+           2.102207177600618,
+           2.0586397690668568,
+           2.0026671434401893,
+           1.93568660074748,
+           1.8593527112657966,
+           1.7755435587696005,
+           1.6863212409435417,
+           1.5938875241185801,
+           1.5005356730649915,
+           1.4085995756980614,
+           1.3204013547140312,
+           1.238198701527582,
+           1.164133181288135,
+           1.100180740804495,
+           1.0481056042484271,
+           1.009418665617194,
+           0.9853413839065802,
+           0.9767760592420291,
+           0.9842832189083499,
+           1.0080666749141507,
+           1.0479666334776883,
+           1.1034610460243717,
+           1.1736751955790483,
+           1.2573993165789696,
+           1.3531138548935964,
+           1.4590217928724367,
+           1.573087295984396,
+           1.6930797871601084,
+           1.8166224259658188,
+           1.9412438653625033,
+           2.064432081572508,
+           2.1836890243607128,
+           2.2965848169980076,
+           2.400810247734471,
+           2.494226337440455,
+           2.5749098401076322,
+           2.6411936323568317,
+           2.6917010725217803,
+           2.7253735562066255,
+           2.7414906598533673,
+           2.7396824427635313,
+           2.719933666809989,
+           2.6825798871279187,
+           2.628295561643038,
+           2.5580745176296245,
+           2.473203294951024,
+           2.3752280538073585,
+           2.2659158856193837,
+           2.147211495468599,
+           2.0211903301703567,
+           1.8900093050578743,
+           1.755856333040791,
+           1.6208998803201298,
+           1.4872397638732238,
+           1.3568603667925447,
+           1.2315873798313555,
+           1.113049082842435,
+           1.0026430606239585,
+           0.901509107037837,
+           0.8105089126966734,
+           0.7302129590168056,
+           0.6608948593346096,
+           0.6025332006380005,
+           0.5548207519457493,
+           0.517180722144317,
+           0.4887895757178088,
+           0.4686057536037269,
+           0.45540350235989097,
+           0.4478108914843414,
+           0.4443509991140632,
+           0.4434851728650326,
+           0.44365722703179095,
+           0.443337420804268,
+           0.441065074919995,
+           0.4354887258535748,
+           0.4254027861299557,
+           0.40977977481653866,
+           0.3877973012342789,
+           0.35885912437629025,
+           0.32260976687000237,
+           0.2789423315814303,
+           0.22799934683310355,
+           0.17016664817333088,
+           0.10606048607797391,
+           0.03650822528689615,
+           -0.03747683179182485,
+           -0.11472581225993563,
+           -0.19394900991100017,
+           -0.27377405772592733,
+           -0.35278651089108565,
+           -0.4295717517493522,
+           -0.5027570922251129,
+           -0.5710529422486639,
+           -0.633291934741167,
+           -0.6884649482737484,
+           -0.7357530463305656,
+           -0.7745544552446416,
+           -0.8045058287567823,
+           -0.8254971926167678,
+           -0.8376801240499853,
+           -0.841468894195237,
+           -0.8375344824187229,
+           -0.8267915551695093,
+           -0.8103786841251477,
+           -0.7896322541798718,
+           -0.766054676899256,
+           -0.7412776752125046,
+           -0.7170215365123712,
+           -0.6950513406201659,
+           -0.6771312534349067,
+           -0.6649780343239529,
+           -0.6602149339047566,
+           -0.664327158003343,
+           -0.6786200431784662,
+           -0.7041810299321768,
+           -0.7418464329699567,
+           -0.7921738956976406,
+           -0.8554212812564455,
+           -0.9315325980815864,
+           -1.0201313879949934,
+           -1.1205218233766843,
+           -1.2316975714662532,
+           -1.3523582929727933,
+           -1.4809334536364056,
+           -1.6156129458563933,
+           -1.754383847487417,
+           -1.8950724906362406,
+           -2.0353908786195976,
+           -2.172986377543297,
+           -2.3054935230477507,
+           -2.4305867248207518,
+           -2.546032623002267,
+           -2.6497408523734713,
+           -2.7398120022660173,
+           -2.814581621733238,
+           -2.872659209252836,
+           -2.9129612419450153,
+           -2.9347374382158224,
+           -2.9375896065229297,
+           -2.921482607769353,
+           -2.886747145421815,
+           -2.8340742912931143,
+           -2.764501851309171,
+           -2.6793928697226987,
+           -2.5804067574092917,
+           -2.469463705529781,
+           -2.348703205685783,
+           -2.220437637840722,
+           -2.0871020043150184,
+           -1.9512009792445466,
+           -1.8152545058065597,
+           -1.6817432067444016,
+           -1.5530548764693624,
+           -1.4314332952358675,
+           -1.31893054827573,
+           -1.2173639467681336,
+           -1.1282785352377147,
+           -1.052916034180684,
+           -0.9921909107567358,
+           -0.9466740980829703,
+           -0.9165846992514665,
+           -0.901789820182496,
+           -0.9018124805187714,
+           -0.9158473587256365,
+           -0.9427839410971803,
+           -0.9812364690196662,
+           -1.0295799188712955,
+           -1.0859911082156355,
+           -1.1484939038685156,
+           -1.2150074148151553,
+           -1.283395988022439,
+           -1.3515197894413713,
+           -1.4172847467146767,
+           -1.4786906543412575,
+           -1.5338762956075818,
+           -1.581160517059223,
+           -1.6190782985485748,
+           -1.6464109922195238,
+           -1.662210053873276,
+           -1.6658137562164912,
+           -1.6568565513509264,
+           -1.6352709350664612,
+           -1.6012818534189377,
+           -1.5553938780249406,
+           -1.4983715558620034,
+           -1.4312135076733816,
+           -1.3551210021750395,
+           -1.2714618673711944,
+           -1.1817307121070264,
+           -1.087506517790434,
+           -0.9904087198967803,
+           -0.892052930011301,
+           -0.7940074510604331,
+           -0.6977517110661706,
+           -0.6046376849890379,
+           -0.5158552914800023,
+           -0.43240264378834486,
+           -0.35506190444060554,
+           -0.284381344933923,
+           -0.22066404836176287,
+           -0.16396351876861165,
+           -0.11408628053718305,
+           -0.07060136882835971,
+           -0.032856432642624465,
+           -2.86396857429828e-16
+          ],
+          [
+           0,
+           0.028036121486305535,
+           0.05395968938509014,
+           0.07907086691239305,
+           0.10471037026396803,
+           0.1322175604720771,
+           0.16288841180106498,
+           0.19793448823670975,
+           0.23844403538322562,
+           0.2853462423727391,
+           0.3393796485258239,
+           0.4010655644740418,
+           0.47068724989752014,
+           0.5482754431432717,
+           0.6336006754639728,
+           0.7261726285408592,
+           0.8252466127124352,
+           0.9298370594932167,
+           1.038737740175993,
+           1.150548247165017,
+           1.2637061106248606,
+           1.3765237742184437,
+           1.4872295239410154,
+           1.5940113566573686,
+           1.6950626926859464,
+           1.7886287817908073,
+           1.8730526257071782,
+           1.9468192435897005,
+           2.008597139549691,
+           2.0572758930174766,
+           2.0919988815864667,
+           2.1121902601403697,
+           2.117575456673727,
+           2.1081946009630546,
+           2.0844084733219246,
+           2.046896742878968,
+           1.996648453667826,
+           1.9349449076518932,
+           1.8633352819042606,
+           1.7836054978614795,
+           1.6977410293787396,
+           1.6078844890282993,
+           1.5162889648859852,
+           1.4252681896100148,
+           1.3371447071672093,
+           1.254197257974839,
+           1.178608629063246,
+           1.112415211412077,
+           1.057459471903534,
+           1.0153464831463799,
+           0.9874055622577735,
+           0.9746579517396737,
+           0.9777913346828839,
+           0.9971418160722405,
+           1.0326838258330746,
+           1.084028211722834,
+           1.1504285957877294,
+           1.2307958715997094,
+           1.3237205256470752,
+           1.4275022797937518,
+           1.540186377191129,
+           1.6596056756751727,
+           1.7834275743696395,
+           1.9092046843119295,
+           2.0344280652184485,
+           2.1565817901661455,
+           2.2731975694468667,
+           2.3819081648822635,
+           2.4804983564508727,
+           2.5669522834119296,
+           2.6394960707178052,
+           2.696634766205335,
+           2.7371827520227456,
+           2.760286951594755,
+           2.765442327280108,
+           2.752499349472336,
+           2.7216633106917594,
+           2.673485553499713,
+           2.608846874065516,
+           2.5289335492263043,
+           2.4352066093723166,
+           2.32936513822843,
+           2.2133045197443924,
+           2.08907066849728,
+           1.9588113704680372,
+           1.8247259236351943,
+           1.689014301080773,
+           1.5538270624988857,
+           1.4212172131530538,
+           1.2930951532013495,
+           1.171187776378493,
+           1.0570026674543518,
+           0.951798215471566,
+           0.8565603078533666,
+           0.7719861028930122,
+           0.6984751990962164,
+           0.6361283338283672,
+           0.5847535553647137,
+           0.5438796264456099,
+           0.5127762384235063,
+           0.4904804474924056,
+           0.4758285924584489,
+           0.4674928207898972,
+           0.46402123953379804,
+           0.46388062279289605,
+           0.4655005498711536,
+           0.4673178192841869,
+           0.4678199842368319,
+           0.4655868848035567,
+           0.4593291100863098,
+           0.4479224085358623,
+           0.4304371742024006,
+           0.40616226810912937,
+           0.3746225838542192,
+           0.33558993111729846,
+           0.2890869857881634,
+           0.23538423650074156,
+           0.1749900398500286,
+           0.10863407586770231,
+           0.03724466689088886,
+           -0.038079417566583326,
+           -0.11610190397819022,
+           -0.19548581644157403,
+           -0.27483314651020885,
+           -0.3527263256658127,
+           -0.42777038695499936,
+           -0.498634682969483,
+           -0.5640930370883186,
+           -0.6230612434954448,
+           -0.6746308979811391,
+           -0.7180986342736856,
+           -0.7529899573066849,
+           -0.7790770024830137,
+           -0.796389705191855,
+           -0.8052200336684723,
+           -0.8061191165080426,
+           -0.7998872792633265,
+           -0.7875571879506466,
+           -0.7703704763248335,
+           -0.749748403928972,
+           -0.72725724886211,
+           -0.7045692789442244,
+           -0.683420263923866,
+           -0.6655645865144582,
+           -0.6527290788956474,
+           -0.6465667520648618,
+           -0.6486115969587675,
+           -0.6602356182003147,
+           -0.682609214018254,
+           -0.7166659404174054,
+           -0.7630725958390179,
+           -0.82220543679229,
+           -0.8941331883127664,
+           -0.9786073491895335,
+           -1.0750601147176262,
+           -1.1826100536305546,
+           -1.3000754854377026,
+           -1.4259953143370272,
+           -1.5586568909016918,
+           -1.6961302974403143,
+           -1.836308291666045,
+           -1.9769510001027797,
+           -2.1157343310935524,
+           -2.2503009804146203,
+           -2.378312832793301,
+           -2.4975035218683703,
+           -2.6057299003976957,
+           -2.7010211921500082,
+           -2.781624646511445,
+           -2.8460465952485765,
+           -2.893087916244323,
+           -2.921873038842112,
+           -2.9318717765732303,
+           -2.922913441851533,
+           -2.8951928796095596,
+           -2.8492682483939906,
+           -2.7860505734806904,
+           -2.706785292340514,
+           -2.6130262035198664,
+           -2.506602411047922,
+           -2.3895790234337246,
+           -2.2642125151028827,
+           -2.1329017851194094,
+           -1.9981360501523864,
+           -1.8624407833946555,
+           -1.728322956709677,
+           -1.5982168585726606,
+           -1.4744317450263007,
+           -1.3591025352823982,
+           -1.254144688900111,
+           -1.1612142995056132,
+           -1.0816743132961082,
+           -1.0165676322100134,
+           -0.9665976952865268,
+           -0.9321169514614207,
+           -0.9131234472687915,
+           -0.9092655582835938,
+           -0.9198546984044201,
+           -0.9438856509925108,
+           -0.9800639850824763,
+           -1.0268398527583036,
+           -1.082447314397417,
+           -1.1449482104345696,
+           -1.2122794946641573,
+           -1.2823028673547583,
+           -1.3528554983970429,
+           -1.4218006124387002,
+           -1.4870767198336745,
+           -1.546744318860283,
+           -1.5990289649203722,
+           -1.6423596994935357,
+           -1.6754019530001807,
+           -1.6970841783428816,
+           -1.7066176321462687,
+           -1.703508894571655,
+           -1.6875649016863397,
+           -1.6588904521407755,
+           -1.6178783376672494,
+           -1.5651924299890132,
+           -1.5017442305739734,
+           -1.4286635499771796,
+           -1.347264126332879,
+           -1.2590051143665164,
+           -1.1654494741173362,
+           -1.0682203600166338,
+           -0.9689566543419751,
+           -0.869268803355873,
+           -0.7706960993608063,
+           -0.6746665079187082,
+           -0.5824600677735493,
+           -0.4951767934547983,
+           -0.41370988964762523,
+           -0.3387249452947731,
+           -0.2706456176508041,
+           -0.20964614616120777,
+           -0.15565085741795054,
+           -0.10834064008410323,
+           -0.06716618720825843,
+           -0.031367627363189175,
+           -2.749099969365357e-16
+          ],
+          [
+           0,
+           0.027281427490450743,
+           0.053061084893357764,
+           0.07866419200261046,
+           0.10543397850464106,
+           0.13468956203697446,
+           0.16768434410944308,
+           0.2055660456498208,
+           0.2493394631621487,
+           0.2998329578985898,
+           0.35766959575867857,
+           0.4232437372163853,
+           0.49670373740807955,
+           0.5779412600911282,
+           0.6665875394394536,
+           0.762016744854471,
+           0.8633564206459803,
+           0.9695047892064246,
+           1.079154527796516,
+           1.1908224598020798,
+           1.3028844456076933,
+           1.4136146200264823,
+           1.521228006059298,
+           1.6239254416417195,
+           1.7199396893882608,
+           1.807581560916558,
+           1.885284878184093,
+           1.951649114720488,
+           2.005478609274689,
+           2.0458173220740665,
+           2.071978207764798,
+           2.0835664066658457,
+           2.0804956041223934,
+           2.0629970728690052,
+           2.031621091357794,
+           1.987230617591737,
+           1.930987288525138,
+           1.864330004840854,
+           1.78894654518487,
+           1.70673882815569,
+           1.619782600170305,
+           1.5302824687687024,
+           1.4405233204291736,
+           1.352819256536234,
+           1.2694612483703476,
+           1.1926647501428067,
+           1.1245185171619991,
+           1.066935853911693,
+           1.0216094646165164,
+           0.9899709979716532,
+           0.9731562700363499,
+           0.971977017409772,
+           0.9868998798967988,
+           1.018033141624969,
+           1.0651215761167474,
+           1.1275495486070648,
+           1.2043523325976346,
+           1.2942354020343354,
+           1.3956012703462566,
+           1.5065832675289161,
+           1.6250854808791582,
+           1.7488279379324014,
+           1.875395985199312,
+           2.0022927164932844,
+           2.126993232412419,
+           2.2469994696437667,
+           2.3598943262311014,
+           2.4633938270822613,
+           2.5553961223312047,
+           2.6340261885162444,
+           2.69767520698302,
+           2.7450337229003323,
+           2.7751178386208655,
+           2.7872878631398947,
+           2.781259020984848,
+           2.757104014562534,
+           2.7152474291348265,
+           2.65645216442122,
+           2.581798266585537,
+           2.492654714433076,
+           2.3906448796478825,
+           2.277606528814442,
+           2.1555473612221854,
+           2.026597178012459,
+           1.8929578526763944,
+           1.7568523185018412,
+           1.6204738042648208,
+           1.4859365349729887,
+           1.35522907024627,
+           1.2301713801479113,
+           1.1123766588452582,
+           1.0032187529247831,
+           0.9038059366444654,
+           0.8149616045228795,
+           0.7372122765059201,
+           0.6707831269051613,
+           0.6156010599634016,
+           0.5713051669664986,
+           0.53726421695802,
+           0.5126006598606333,
+           0.49622046145158755,
+           0.4868479481099787,
+           0.48306471902854653,
+           0.4833515876015415,
+           0.4861324442904442,
+           0.48981889209021423,
+           0.49285449372050816,
+           0.4937574870674629,
+           0.49116087168416867,
+           0.48384884308172815,
+           0.47078865117638713,
+           0.45115708202921606,
+           0.42436090477330723,
+           0.39005078472280613,
+           0.34812833504546853,
+           0.2987461586991728,
+           0.24230091503179252,
+           0.17941962689077942,
+           0.11093961968770097,
+           0.037882649167659925,
+           -0.03857607453970631,
+           -0.11714312647922046,
+           -0.19644541904908513,
+           -0.27507102938647177,
+           -0.3516112047738653,
+           -0.42470241727848773,
+           -0.49306733621677074,
+           -0.5555536134775135,
+           -0.6111694315892385,
+           -0.659114846311195,
+           -0.6988080624135475,
+           -0.7299059105091587,
+           -0.7523179410616553,
+           -0.7662137152938397,
+           -0.7720230475378319,
+           -0.7704291351984339,
+           -0.7623546963604052,
+           -0.748941416513947,
+           -0.73152318030848,
+           -0.7115937272500931,
+           -0.6907695176894935,
+           -0.6707487235446293,
+           -0.6532673636839065,
+           -0.6400536840400864,
+           -0.6327819352398969,
+           -0.6330267244097587,
+           -0.64221911216279,
+           -0.6616055906315252,
+           -0.692211014566489,
+           -0.734806466473169,
+           -0.7898829206909859,
+           -0.8576314330382674,
+           -0.9379304255273162,
+           -1.0303404635401134,
+           -1.134106739976953,
+           -1.248169291752588,
+           -1.371180783289543,
+           -1.5015315040667019,
+           -1.6373810474784363,
+           -1.776695970716457,
+           -1.917292584281902,
+           -2.056883888848878,
+           -2.1931295698216267,
+           -2.3236878787704907,
+           -2.446268178068992,
+           -2.5586829018654162,
+           -2.6588976936565274,
+           -2.7450785180923942,
+           -2.8156346113901107,
+           -2.8692562293044994,
+           -2.9049462717451195,
+           -2.922045005956891,
+           -2.9202472722522415,
+           -2.899611733673831,
+           -2.8605619193765075,
+           -2.803879006367701,
+           -2.7306864807974223,
+           -2.6424270134563566,
+           -2.5408320698101026,
+           -2.427884948242963,
+           -2.305778096980311,
+           -2.176865696580861,
+           -2.0436126076143797,
+           -1.9085408694210213,
+           -1.7741749935859967,
+           -1.6429873235593366,
+           -1.5173447290365252,
+           -1.3994578703762064,
+           -1.2913342052942753,
+           -1.1947358188968646,
+           -1.111143041042358,
+           -1.0417246749309355,
+           -0.9873155011486622,
+           -0.9484015460558735,
+           -0.925113416701604,
+           -0.9172278109356576,
+           -0.9241771158072675,
+           -0.9450668144582958,
+           -0.9787002362409827,
+           -1.023610011227472,
+           -1.0780954328433132,
+           -1.1402647948589073,
+           -1.2080816547237512,
+           -1.279413886962393,
+           -1.3520843301581202,
+           -1.4239218003243796,
+           -1.4928112428699154,
+           -1.556741824822255,
+           -1.6138518276650322,
+           -1.6624692875262441,
+           -1.7011474413061352,
+           -1.7286941718077002,
+           -1.7441947986304494,
+           -1.7470277306405397,
+           -1.7368726759978201,
+           -1.71371129249705,
+           -1.6778203497065856,
+           -1.6297576603662087,
+           -1.5703412171177953,
+           -1.5006221374636488,
+           -1.4218521707561633,
+           -1.335446652303145,
+           -1.2429438981074497,
+           -1.1459621167058285,
+           -1.046154970030524,
+           -0.9451669418797305,
+           -0.8445896698630427,
+           -0.7459203647361422,
+           -0.6505233807370365,
+           -0.5595959134749279,
+           -0.47413869036152295,
+           -0.3949323853832349,
+           -0.32252033860070606,
+           -0.25719799499077933,
+           -0.19900930133382616,
+           -0.1477501182641035,
+           -0.1029785219484135,
+           -0.06403169076779626,
+           -0.0300489013834574,
+           -2.6516250255193145e-16
+          ],
+          [
+           0,
+           0.0267341539905712,
+           0.0525909419830553,
+           0.0789089220583691,
+           0.10702192878764188,
+           0.13821710132312182,
+           0.1736940671999282,
+           0.2145263841092456,
+           0.26162628492425294,
+           0.3157136873621495,
+           0.3772903209529756,
+           0.4466196931889628,
+           0.5237134671357632,
+           0.60832465816426,
+           0.6999478819562153,
+           0.7978267039747537,
+           0.9009679567656835,
+           1.0081627104149595,
+           1.118013407815002,
+           1.2289665144939748,
+           1.3393498867547262,
+           1.4474139354795672,
+           1.551375559423522,
+           1.6494637438154414,
+           1.7399656696520576,
+           1.8212721575573876,
+           1.891921278120344,
+           1.9506389981111194,
+           1.9963757980696,
+           2.028338289898731,
+           2.0460149810455817,
+           2.0491954717527494,
+           2.0379825302989376,
+           2.012796664237116,
+           1.9743729891251156,
+           1.9237503856022604,
+           1.8622531262156854,
+           1.7914653404202516,
+           1.713198865022189,
+           1.629455193556725,
+           1.5423823875346594,
+           1.454227941419308,
+           1.367288698359538,
+           1.2838589924437678,
+           1.2061782435375594,
+           1.1363792513058235,
+           1.0764384252124042,
+           1.0281291472955805,
+           0.9929793952405652,
+           0.9722346563362784,
+           0.9668270406217638,
+           0.9773513568336083,
+           1.0040487511500173,
+           1.0467983301497885,
+           1.1051170001974264,
+           1.1781675602269974,
+           1.2647748883775738,
+           1.363449869918743,
+           1.4724205291000436,
+           1.5896696554699425,
+           1.7129780600358435,
+           1.839972462162169,
+           1.9681768976088985,
+           2.095066454291697,
+           2.218122087238666,
+           2.334885239165215,
+           2.443010998691493,
+           2.540318564337153,
+           2.624837848152245,
+           2.6948511465612355,
+           2.74892892540601,
+           2.785958908342367,
+           2.805167819186193,
+           2.8061353055657055,
+           2.7887997589873113,
+           2.7534559405741,
+           2.7007445175443285,
+           2.631633808185441,
+           2.5473942179526725,
+           2.449566021884603,
+           2.339921304594796,
+           2.220421004894696,
+           2.09316812435868,
+           1.9603582451730293,
+           1.8242285603819262,
+           1.6870066478210735,
+           1.550860217009541,
+           1.4178490261964027,
+           1.2898801055136786,
+           1.1686673333731183,
+           1.055696299141214,
+           0.9521952486330506,
+           0.8591127535291615,
+           0.7771025753472287,
+           0.7065160133646535,
+           0.6474018384168129,
+           0.5995137254621712,
+           0.5623249119106023,
+           0.5350496305671888,
+           0.5166707000598435,
+           0.5059725058917443,
+           0.5015784754714898,
+           0.5019920438027142,
+           0.5056400255548209,
+           0.5109172559345913,
+           0.5162313383867763,
+           0.5200463421973871,
+           0.5209243273459171,
+           0.5175636365103832,
+           0.5088329833236706,
+           0.4938004794975459,
+           0.47175687835264557,
+           0.4422324651659808,
+           0.40500719167416077,
+           0.36011382880425685,
+           0.30783409375747367,
+           0.24868789032730673,
+           0.1834159801637152,
+           0.1129565730715695,
+           0.03841648204422645,
+           -0.038962370404954524,
+           -0.11784018750176702,
+           -0.19681927076436578,
+           -0.27448565419217685,
+           -0.3494512807034713,
+           -0.4203955864519687,
+           -0.48610537280501404,
+           -0.5455118887075882,
+           -0.5977241168167711,
+           -0.642057353400201,
+           -0.6780562921250722,
+           -0.7055119625020175,
+           -0.724472031352735,
+           -0.7352441462729963,
+           -0.7383921793630069,
+           -0.7347254129714644,
+           -0.7252808922122835,
+           -0.7112993469345543,
+           -0.6941952541473917,
+           -0.6755217663471758,
+           -0.656931367831553,
+           -0.640133236418212,
+           -0.626848379051321,
+           -0.6187636742105703,
+           -0.6174859901364669,
+           -0.6244975546550596,
+           -0.6411137295622448,
+           -0.6684442905874219,
+           -0.70735923410236,
+           -0.7584600258769435,
+           -0.8220570778652551,
+           -0.8981540893798199,
+           -0.9864397227385692,
+           -1.0862869046302013,
+           -1.196759857443819,
+           -1.3166287742644045,
+           -1.4443918618634108,
+           -1.5783042925097448,
+           -1.7164134323541118,
+           -1.8565995558122461,
+           -1.9966211157491331,
+           -2.1341635218506907,
+           -2.266890287324562,
+           -2.3924953393448156,
+           -2.5087552531181583,
+           -2.6135801640583582,
+           -2.705062137524421,
+           -2.781519830373362,
+           -2.841538361932198,
+           -2.8840034219315465,
+           -2.9081287768357105,
+           -2.9134764906275095,
+           -2.8999693477243267,
+           -2.8678951501555363,
+           -2.817902753942257,
+           -2.7509899060992042,
+           -2.6684831390424177,
+           -2.572010168675235,
+           -2.4634654214189644,
+           -2.3449694795878435,
+           -2.218823379776932,
+           -2.0874588217920502,
+           -1.953385443106937,
+           -1.8191363835099303,
+           -1.6872134048046268,
+           -1.5600328401841752,
+           -1.4398736269772963,
+           -1.3288286253903239,
+           -1.2287603459028529,
+           -1.1412621010832429,
+           -1.0676254663996425,
+           -1.0088147823303724,
+           -0.9654492604576193,
+           -0.9377930734135854,
+           -0.9257536170116366,
+           -0.928887937318222,
+           -0.9464171205792149,
+           -0.9772482545572628,
+           -1.0200033905740569,
+           -1.073054770737389,
+           -1.134565438459996,
+           -1.2025342259782779,
+           -1.2748440131402508,
+           -1.349312079620105,
+           -1.423741329621599,
+           -1.4959711550256083,
+           -1.5639267200493494,
+           -1.6256654973011868,
+           -1.6794199603890028,
+           -1.7236354400244274,
+           -1.7570022762630493,
+           -1.7784815459482382,
+           -1.7873238078949831,
+           -1.7830804847573567,
+           -1.7656076854551892,
+           -1.735062460877225,
+           -1.6918916736275866,
+           -1.636813845168958,
+           -1.5707945163144656,
+           -1.4950158153649524,
+           -1.4108410683772958,
+           -1.319775404641964,
+           -1.223423404549277,
+           -1.1234449043561416,
+           -1.0215101113238803,
+           -0.9192551923911805,
+           -0.818239479815067,
+           -0.7199053886354428,
+           -0.6255420646942201,
+           -0.5362536802554662,
+           -0.4529331696533345,
+           -0.3762420530355325,
+           -0.30659683585910313,
+           -0.24416229941680553,
+           -0.18885181770742007,
+           -0.1403346529781079,
+           -0.09805000089884644,
+           -0.06122738117091291,
+           -0.028912804855846266,
+           -2.5724874122318156e-16
+          ],
+          [
+           0,
+           0.026399826105570016,
+           0.05255471841132148,
+           0.07980471934335819,
+           0.10946242811055305,
+           0.1427715417940938,
+           0.18086718078457992,
+           0.2247390717805102,
+           0.27519858884945847,
+           0.332850554551019,
+           0.3980705813043677,
+           0.47098859111769054,
+           0.5514789930589178,
+           0.6391578264374264,
+           0.7333869979079788,
+           0.8332855571396247,
+           0.937747772953486,
+           1.0454675945496557,
+           1.1549689151098514,
+           1.2646409019307994,
+           1.3727775222158634,
+           1.4776202801837417,
+           1.5774030921629552,
+           1.6703981641413035,
+           1.7549617024752122,
+           1.8295782840714834,
+           1.8929027375364418,
+           1.9437984410091977,
+           1.9813710243938882,
+           2.0049965715214397,
+           2.0143435487969428,
+           2.009387837931935,
+           1.9904204177235727,
+           1.9580474194117936,
+           1.9131824674950724,
+           1.8570314083855175,
+           1.7910697182163353,
+           1.7170130637887058,
+           1.63678166251507,
+           1.5524592439935936,
+           1.4662475536102075,
+           1.3804174538484228,
+           1.297257768879608,
+           1.2190230802157898,
+           1.1478817141202282,
+           1.0858651641947796,
+           1.0348201649469442,
+           0.9963645747804629,
+           0.9718481410818863,
+           0.9623191079238497,
+           0.9684974910581515,
+           0.9907556885991152,
+           1.0291069228777334,
+           1.0832018235711607,
+           1.1523332688826802,
+           1.2354494049670872,
+           1.3311745687527565,
+           1.4378376505586172,
+           1.5535072550456277,
+           1.6760328564181077,
+           1.8030910003702776,
+           1.932235484557928,
+           2.0609503543116676,
+           2.186704483214795,
+           2.30700647068091,
+           2.419458581693641,
+           2.521808477576365,
+           2.611997540455987,
+           2.6882046766466416,
+           2.748884593479919,
+           2.7927996774651564,
+           2.819044755809077,
+           2.8270641944823685,
+           2.8166609700036687,
+           2.787997544419695,
+           2.741588568896141,
+           2.67828563611614,
+           2.5992544905645905,
+           2.50594528416191,
+           2.400056628268667,
+           2.2834943378524164,
+           2.158325886097798,
+           2.026731685011717,
+           1.8909543773137734,
+           1.753247365476947,
+           1.6158238142840662,
+           1.4808073435245868,
+           1.350185578051605,
+           1.2257676446598336,
+           1.109146601137094,
+           1.0016676550371955,
+           0.9044028814530313,
+           0.8181329840664873,
+           0.7433364661533606,
+           0.6801863924662707,
+           0.6285547336385728,
+           0.588024096655441,
+           0.5579064626934567,
+           0.5372683817490715,
+           0.5249619162036923,
+           0.5196604866800937,
+           0.5198986566337542,
+           0.5241147999431836,
+           0.5306955305419633,
+           0.5380207364210977,
+           0.5445080529571428,
+           0.5486556325880787,
+           0.5490821187271319,
+           0.5445628101169026,
+           0.5340611055394621,
+           0.5167544452365862,
+           0.4920541113162445,
+           0.4596184111012398,
+           0.41935894069723606,
+           0.3714398066173409,
+           0.3162698665187583,
+           0.25448823134242393,
+           0.1869434458113265,
+           0.11466692791963495,
+           0.03884139659444194,
+           -0.03923485361983889,
+           -0.11818686449481867,
+           -0.19660406367692196,
+           -0.27308234721373803,
+           -0.3462660631025164,
+           -0.4148887657015187,
+           -0.4778116416677001,
+           -0.534058567175009,
+           -0.582846842045165,
+           -0.6236127569299763,
+           -0.6560312820424439,
+           -0.6800293168115732,
+           -0.6957921054324775,
+           -0.7037625994241888,
+           -0.7046337305475889,
+           -0.6993337411717075,
+           -0.6890048997608239,
+           -0.6749761020130673,
+           -0.6587300189262095,
+           -0.6418655976082152,
+           -0.6260568452989422,
+           -0.6130089286276404,
+           -0.6044126959746754,
+           -0.6018987789503663,
+           -0.6069924481541747,
+           -0.621070387962115,
+           -0.645320515275713,
+           -0.6807058988541965,
+           -0.7279337406584759,
+           -0.7874302608512768,
+           -0.8593221866313329,
+           -0.9434253853867395,
+           -1.0392410086511001,
+           -1.1459593293187949,
+           -1.2624712650645649,
+           -1.3873873906061749,
+           -1.5190640550666443,
+           -1.6556360428663728,
+           -1.7950550517368,
+           -1.9351331137144248,
+           -2.073589958051826,
+           -2.2081032120679307,
+           -2.3363602596644575,
+           -2.4561105295176926,
+           -2.5652169670713056,
+           -2.661705456931047,
+           -2.743811004871625,
+           -2.8100195604430556,
+           -2.8591044604225044,
+           -2.8901565977320085,
+           -2.9026075669459708,
+           -2.8962452026099124,
+           -2.8712211062866855,
+           -2.828049948177844,
+           -2.7676005247195117,
+           -2.6910787499639888,
+           -2.600002951045133,
+           -2.4961720218939316,
+           -2.3816271601347574,
+           -2.2586080655849305,
+           -2.12950461125355,
+           -1.996805105956782,
+           -1.863042348994082,
+           -1.730738729781558,
+           -1.602351647636916,
+           -1.4802205185186232,
+           -1.3665165966517332,
+           -1.2631967705842093,
+           -1.1719623969917465,
+           -1.0942241138472368,
+           -1.0310734303785964,
+           -0.9832617280872303,
+           -0.9511871289843572,
+           -0.9348894984802708,
+           -0.9340536556450695,
+           -0.9480206676031047,
+           -0.9758069124057277,
+           -1.016130410533861,
+           -1.0674437536906047,
+           -1.1279728049131024,
+           -1.1957602099999678,
+           -1.2687126500416488,
+           -1.3446506810894259,
+           -1.4213599516834603,
+           -1.4966425633557667,
+           -1.568367343870777,
+           -1.6345178376582632,
+           -1.693236881683976,
+           -1.742866726230669,
+           -1.7819837763884832,
+           -1.8094271685286223,
+           -1.8243205531646718,
+           -1.8260866274453955,
+           -1.8144541427699363,
+           -1.7894573011209713,
+           -1.751427642989358,
+           -1.700978715511545,
+           -1.6389839870544085,
+           -1.5665486395691146,
+           -1.4849760185256842,
+           -1.395729648485116,
+           -1.300391827230423,
+           -1.2006198903160137,
+           -1.098101289012545,
+           -0.9945086467270056,
+           -0.8914559515976801,
+           -0.7904570063712528,
+           -0.692887191865967,
+           -0.5999495090160609,
+           -0.5126457490455089,
+           -0.4317535047016126,
+           -0.35780958118600464,
+           -0.2911001973853672,
+           -0.23165819049963404,
+           -0.17926725469744667,
+           -0.1334730616224814,
+           -0.09360093205877325,
+           -0.058779558355424706,
+           -0.027970120602576153,
+           -2.5124535087658795e-16
+          ],
+          [
+           0,
+           0.026281908277714323,
+           0.05295366985326224,
+           0.08134493223987314,
+           0.11273539782232518,
+           0.14831423666498675,
+           0.18914189743652005,
+           0.23611535132413877,
+           0.2899377159789246,
+           0.3510930942652949,
+           0.4198273287086642,
+           0.4961352204183323,
+           0.5797545947424524,
+           0.6701674191895256,
+           0.7666079966884148,
+           0.8680780736679949,
+           0.9733685223641628,
+           1.0810870847696563,
+           1.1896915060981332,
+           1.2975272425994495,
+           1.402868805691199,
+           1.50396370481584,
+           1.599077877767296,
+           1.6865414513858723,
+           1.7647936587321873,
+           1.8324257516313933,
+           1.888220789600812,
+           1.931189256676051,
+           1.9605995548597785,
+           1.9760025444906422,
+           1.9772494448106976,
+           1.9645025689014213,
+           1.9382385420098034,
+           1.899243836789458,
+           1.8486026485794596,
+           1.7876773238409394,
+           1.7180817405528352,
+           1.641648216114479,
+           1.560388681706046,
+           1.4764510080311162,
+           1.3920714922442117,
+           1.3095246164998897,
+           1.2310712623910922,
+           1.158906610672492,
+           1.0951089708938229,
+           1.0415907704385914,
+           1.0000528872623677,
+           0.9719434363818306,
+           0.9584220186264141,
+           0.960330313750574,
+           0.9781697517527048,
+           1.0120868297352599,
+           1.0618664609017177,
+           1.1269335517067476,
+           1.2063628073901924,
+           1.298896569900409,
+           1.402970300330671,
+           1.5167451351345307,
+           1.6381467760154416,
+           1.764909821638588,
+           1.894626518895447,
+           2.0247988055501964,
+           2.152892437298706,
+           2.27639194249934,
+           2.3928551283043817,
+           2.499965873104118,
+           2.5955839818154534,
+           2.6777909515787655,
+           2.7449305941286393,
+           2.7956435850561423,
+           2.8288951563461704,
+           2.843995313375046,
+           2.8406111369586218,
+           2.8187709206641753,
+           2.778860088807548,
+           2.7216090365868526,
+           2.6480732258767574,
+           2.5596060536476632,
+           2.457825180324925,
+           2.3445731585352014,
+           2.2218733349000654,
+           2.0918821056510035,
+           1.9568386882725397,
+           1.8190136242099677,
+           1.6806572506908095,
+           1.5439493724271833,
+           1.4109513266588922,
+           1.2835615686740716,
+           1.1634758113279515,
+           1.052152633563707,
+           0.9507853325255539,
+           0.8602806350797129,
+           0.7812447114082317,
+           0.7139767501433342,
+           0.6584701658361857,
+           0.6144213200980883,
+           0.5812454522175576,
+           0.5580993380390359,
+           0.5439100317609366,
+           0.5374088981153287,
+           0.5371700157409419,
+           0.5416519295478952,
+           0.5492416529933523,
+           0.55829977228154,
+           0.5672054847066981,
+           0.5744004130812755,
+           0.5784300771032425,
+           0.5779819695553979,
+           0.5719192786333458,
+           0.5593094150478775,
+           0.5394466408255273,
+           0.5118682524025459,
+           0.4763639397048471,
+           0.4329781211313582,
+           0.38200523718805235,
+           0.3239781683221061,
+           0.25965012065333726,
+           0.1899704922876347,
+           0.11605538845387026,
+           0.039153591901703234,
+           -0.03939108765734146,
+           -0.11818006775240684,
+           -0.19580176633240423,
+           -0.2708737697795473,
+           -0.3420842610186845,
+           -0.4082315915377204,
+           -0.46826092837598327,
+           -0.5212969818809083,
+           -0.5666719203996889,
+           -0.6039477015356057,
+           -0.6329321930495652,
+           -0.6536886163107601,
+           -0.6665380173657751,
+           -0.6720546508580504,
+           -0.6710543456376743,
+           -0.6645761033123798,
+           -0.6538573575843929,
+           -0.6403034885156225,
+           -0.6254523376376517,
+           -0.61093460320395,
+           -0.5984311064556944,
+           -0.5896280066663102,
+           -0.5861711026845045,
+           -0.5896203901223027,
+           -0.6014060453568233,
+           -0.6227869799891119,
+           -0.6548130529266363,
+           -0.6982919431488822,
+           -0.7537615764920698,
+           -0.8214688671072654,
+           -0.9013553818428348,
+           -0.9930503674125659,
+           -1.0958713999774297,
+           -1.2088327291378262,
+           -1.330661197945597,
+           -1.4598194321200064,
+           -1.5945358098722309,
+           -1.7328405531350275,
+           -1.8726071258202206,
+           -2.011597988873319,
+           -2.1475136487808837,
+           -2.278043848674546,
+           -2.400919691502307,
+           -2.5139654544560988,
+           -2.6151488537844223,
+           -2.7026285493679088,
+           -2.7747977383328695,
+           -2.8303227751313704,
+           -2.8681758698366946,
+           -2.8876610541520114,
+           -2.8884327624906274,
+           -2.8705065496407984,
+           -2.8342616527545843,
+           -2.780435299173774,
+           -2.71010885821199,
+           -2.624686129660434,
+           -2.5258642497298514,
+           -2.415597871796047,
+           -2.2960574403689424,
+           -2.1695825182209014,
+           -2.0386312451332067,
+           -1.9057270993534194,
+           -1.7734041973391672,
+           -1.6441524021220522,
+           -1.520363514811667,
+           -1.404279797277811,
+           -1.2979460175499884,
+           -1.2031661243462641,
+           -1.121465545474689,
+           -1.0540599693771473,
+           -1.0018313131249468,
+           -0.965311407544178,
+           -0.944673745069637,
+           -0.9397334429213414,
+           -0.9499553779803074,
+           -0.9744702550963121,
+           -1.012098182231264,
+           -1.061379148407933,
+           -1.1206096382017108,
+           -1.1878844734093632,
+           -1.2611428520042398,
+           -1.3382174594321368,
+           -1.4168854599748315,
+           -1.4949201378815398,
+           -1.5701419500910971,
+           -1.6404677747433503,
+           -1.7039571916657081,
+           -1.758854711249624,
+           -1.8036269745378593,
+           -1.8369940772198101,
+           -1.8579543202994508,
+           -1.8658018566856955,
+           -1.8601368816885313,
+           -1.8408682019221552,
+           -1.8082082067719505,
+           -1.7626604546618847,
+           -1.7050002681987304,
+           -1.6362489033714773,
+           -1.5576420141271639,
+           -1.470593270988988,
+           -1.3766541075659204,
+           -1.2774706590220477,
+           -1.1747390196537526,
+           -1.0701599811706344,
+           -0.9653944183167875,
+           -0.8620204640645834,
+           -0.7614935634608138,
+           -0.6651104147214083,
+           -0.573977700453555,
+           -0.48898638365933167,
+           -0.41079219572942477,
+           -0.3398027807322268,
+           -0.27617178608898624,
+           -0.21980000862357485,
+           -0.17034352157818217,
+           -0.12722852713812446,
+           -0.08967250489027649,
+           -0.056711063852684616,
+           -0.027229758370786658,
+           -2.472104830677019e-16
+          ],
+          [
+           0,
+           0.026381769213302823,
+           0.05378483429113204,
+           0.08351665392825176,
+           0.11681265980530947,
+           0.15479689224477444,
+           0.19844562736306048,
+           0.24855498329475217,
+           0.30571339086518784,
+           0.370279689015338,
+           0.44236746049081915,
+           0.5218360624467642,
+           0.6082886337515604,
+           0.7010771802606794,
+           0.799314655739392,
+           0.9018937740852941,
+           1.007512112649841,
+           1.1147029012450915,
+           1.2218707410492082,
+           1.327331365927142,
+           1.4293544490339771,
+           1.5262083727924882,
+           1.6162058226397198,
+           1.6977490358511966,
+           1.7693735370931347,
+           1.8297892222050995,
+           1.8779177104218945,
+           1.9129249714252203,
+           1.9342483452043129,
+           1.94161720699298,
+           1.9350666832583263,
+           1.9149439940724489,
+           1.8819071780326355,
+           1.8369161437427268,
+           1.7812161820784205,
+           1.7163142613128644,
+           1.6439486080043497,
+           1.5660522458372412,
+           1.4847113181286193,
+           1.402119153615726,
+           1.3205271460499415,
+           1.2421936032301253,
+           1.1693317782319521,
+           1.1040583232381505,
+           1.048343403779186,
+           1.0039636783322337,
+           0.9724592858214836,
+           0.9550958930677448,
+           0.9528327377970812,
+           0.9662974632261608,
+           0.9957683808595075,
+           1.041164622815926,
+           1.1020444580002025,
+           1.1776118522964159,
+           1.2667311564065338,
+           1.3679496107824995,
+           1.4795271700386048,
+           1.5994729738503264,
+           1.72558763193023,
+           1.8555103511168352,
+           1.9867698163307854,
+           2.1168376469868346,
+           2.243183188606258,
+           2.363328367363242,
+           2.4749013339035897,
+           2.5756876520267804,
+           2.6636778470056552,
+           2.7371102159819563,
+           2.794507916873286,
+           2.8347094897683447,
+           2.8568921225061272,
+           2.860587146175039,
+           2.84568743237491,
+           2.8124465577134097,
+           2.7614697974326012,
+           2.693697204492393,
+           2.610379218140985,
+           2.513045422414796,
+           2.403467235851447,
+           2.28361545507792,
+           2.155613693443875,
+           2.021688848667439,
+           1.884119798343992,
+           1.745185557624355,
+           1.607114138611856,
+           1.4720333260164924,
+           1.3419245290442476,
+           1.2185807868217367,
+           1.103569895983347,
+           0.9982034971390882,
+           0.9035128051239161,
+           0.8202315000153751,
+           0.7487861160977177,
+           0.6892940787339157,
+           0.641569349141872,
+           0.6051354490754974,
+           0.5792454560423046,
+           0.5629083894298287,
+           0.5549212529593687,
+           0.553905863043561,
+           0.5583494792160169,
+           0.5666481645825493,
+           0.5771517433363683,
+           0.5882091902202569,
+           0.5982132841227736,
+           0.6056433847411148,
+           0.6091052466725619,
+           0.6073668679357405,
+           0.5993894776197579,
+           0.5843528973376678,
+           0.5616746600906695,
+           0.5310224342310194,
+           0.49231947527046743,
+           0.4457430098727862,
+           0.3917156398913766,
+           0.33089003512013826,
+           0.26412735694592426,
+           0.19247001693916466,
+           0.11710952050887631,
+           0.03935027239182075,
+           -0.039429675252411304,
+           -0.11781987263155229,
+           -0.194419609001581,
+           -0.2678798023086054,
+           -0.3369435140565825,
+           -0.4004839968359665,
+           -0.4575392452093218,
+           -0.5073421104088901,
+           -0.5493451532969232,
+           -0.5832395453991699,
+           -0.6089674811324358,
+           -0.6267277317407476,
+           -0.6369741487057218,
+           -0.6404071070273049,
+           -0.6379580621626705,
+           -0.6307675739210074,
+           -0.620157321688602,
+           -0.6075967936564866,
+           -0.594665474210743,
+           -0.5830114747081333,
+           -0.5743076503885216,
+           -0.5702063176469526,
+           -0.5722937294276896,
+           -0.5820454809317155,
+           -0.6007840026967223,
+           -0.6296392537021561,
+           -0.6695136544919051,
+           -0.7210522011226417,
+           -0.7846185774320227,
+           -0.8602779386806986,
+           -0.94778687759209,
+           -1.0465909081771603,
+           -1.155829617818962,
+           -1.274349448475441,
+           -1.4007238782381182,
+           -1.5332805895689197,
+           -1.670135034932099,
+           -1.809229648625819,
+           -1.9483778094532294,
+           -2.0853115360785175,
+           -2.2177317985919807,
+           -2.343360258462715,
+           -2.4599912065303555,
+           -2.56554245611215,
+           -2.658103966074567,
+           -2.7359830164896417,
+           -2.7977448361729396,
+           -2.8422476851773513,
+           -2.868671523719386,
+           -2.8765395489559062,
+           -2.8657320488893334,
+           -2.8364922043921728,
+           -2.789423661495109,
+           -2.7254798920274506,
+           -2.6459455566619705,
+           -2.5524102756195988,
+           -2.4467353940671055,
+           -2.3310144971535642,
+           -2.2075285795763,
+           -2.078696902878858,
+           -1.9470246772249453,
+           -1.8150487806318272,
+           -1.6852827757186795,
+           -1.5601625007810282,
+           -1.4419934980311533,
+           -1.3329014974915343,
+           -1.2347871013796807,
+           -1.1492857126829383,
+           -1.0777336254671248,
+           -1.0211410463799147,
+           -0.9801726504222169,
+           -0.9551360934352939,
+           -0.9459787133024548,
+           -0.9522924562412151,
+           -0.9733268685370485,
+           -1.008009802419794,
+           -1.0549753021714654,
+           -1.1125979674152247,
+           -1.1790329389680263,
+           -1.2522605223047858,
+           -1.3301343577133082,
+           -1.4104319671467576,
+           -1.4909064574670232,
+           -1.56933813937192,
+           -1.6435848312257695,
+           -1.7116296569335088,
+           -1.7716252158414776,
+           -1.821933098630584,
+           -1.861157843841821,
+           -1.8881745719860143,
+           -1.9021496945593828,
+           -1.9025542696941027,
+           -1.889169760260715,
+           -1.8620861394196604,
+           -1.8216924781888306,
+           -1.7686603348510443,
+           -1.7039204423849457,
+           -1.6286333532125363,
+           -1.5441548464025283,
+           -1.451997027476074,
+           -1.3537861520816383,
+           -1.251218279592646,
+           -1.1460139093504067,
+           -1.039872769746414,
+           -0.9344299182647956,
+           -0.8312142693785631,
+           -0.7316105979315966,
+           -0.6368259701611584,
+           -0.5478614352950376,
+           -0.46548967075584197,
+           -0.39023911699871994,
+           -0.32238496789768745,
+           -0.26194720370263175,
+           -0.20869567045143464,
+           -0.16216202697824383,
+           -0.1216582029330625,
+           -0.08630084301176724,
+           -0.05504105813868435,
+           -0.02669866754523367,
+           -2.451832280263886e-16
+          ],
+          [
+           0,
+           0.02669866754523276,
+           0.05504105813868367,
+           0.08630084301176683,
+           0.12165820293306212,
+           0.16216202697824228,
+           0.20869567045143347,
+           0.261947203702631,
+           0.322384967897685,
+           0.3902391169987184,
+           0.46548967075584163,
+           0.5478614352950345,
+           0.6368259701611545,
+           0.7316105979315941,
+           0.8312142693785607,
+           0.9344299182647925,
+           1.0398727697464123,
+           1.1460139093504067,
+           1.2512182795926432,
+           1.3537861520816354,
+           1.4519970274760723,
+           1.544154846402526,
+           1.6286333532125346,
+           1.7039204423849454,
+           1.7686603348510426,
+           1.82169247818883,
+           1.8620861394196615,
+           1.889169760260716,
+           1.9025542696941022,
+           1.902149694559385,
+           1.8881745719860175,
+           1.8611578438418233,
+           1.8219330986305842,
+           1.7716252158414811,
+           1.7116296569335165,
+           1.643584831225769,
+           1.5693381393719228,
+           1.4909064574670299,
+           1.4104319671467616,
+           1.3301343577133093,
+           1.2522605223047893,
+           1.1790329389680323,
+           1.1125979674152238,
+           1.0549753021714678,
+           1.008009802419796,
+           0.9733268685370501,
+           0.9522924562412155,
+           0.945978713302455,
+           0.9551360934352934,
+           0.9801726504222168,
+           1.0211410463799138,
+           1.0777336254671224,
+           1.1492857126829352,
+           1.2347871013796745,
+           1.33290149749153,
+           1.441993498031146,
+           1.5601625007810231,
+           1.6852827757186777,
+           1.8150487806318212,
+           1.947024677224943,
+           2.0786969028788524,
+           2.207528579576295,
+           2.331014497153559,
+           2.446735394067101,
+           2.5524102756195974,
+           2.645945556661966,
+           2.7254798920274452,
+           2.789423661495106,
+           2.836492204392171,
+           2.865732048889332,
+           2.876539548955906,
+           2.868671523719387,
+           2.8422476851773517,
+           2.797744836172942,
+           2.735983016489644,
+           2.6581039660745676,
+           2.5655424561121545,
+           2.4599912065303573,
+           2.3433602584627145,
+           2.217731798591989,
+           2.0853115360785233,
+           1.9483778094532345,
+           1.8092296486258248,
+           1.670135034932105,
+           1.5332805895689217,
+           1.40072387823812,
+           1.2743494484754483,
+           1.1558296178189635,
+           1.0465909081771643,
+           0.9477868775920916,
+           0.8602779386807011,
+           0.7846185774320251,
+           0.7210522011226437,
+           0.6695136544919075,
+           0.6296392537021572,
+           0.6007840026967225,
+           0.5820454809317158,
+           0.5722937294276892,
+           0.5702063176469521,
+           0.5743076503885209,
+           0.5830114747081329,
+           0.5946654742107421,
+           0.6075967936564861,
+           0.6201573216886003,
+           0.630767573921005,
+           0.63795806216267,
+           0.6404071070273041,
+           0.6369741487057224,
+           0.6267277317407463,
+           0.6089674811324358,
+           0.583239545399169,
+           0.5493451532969227,
+           0.5073421104088909,
+           0.45753924520932165,
+           0.4004839968359682,
+           0.3369435140565829,
+           0.2678798023086061,
+           0.19441960900158298,
+           0.11781987263155302,
+           0.03942967525241338,
+           -0.039350272391818694,
+           -0.11710952050887563,
+           -0.19247001693916277,
+           -0.2641273569459236,
+           -0.330890035120138,
+           -0.39171563989137503,
+           -0.44574300987278637,
+           -0.4923194752704673,
+           -0.5310224342310199,
+           -0.5616746600906704,
+           -0.584352897337668,
+           -0.5993894776197592,
+           -0.60736686793574,
+           -0.6091052466725627,
+           -0.6056433847411152,
+           -0.5982132841227747,
+           -0.5882091902202585,
+           -0.5771517433363699,
+           -0.5666481645825511,
+           -0.5583494792160172,
+           -0.5539058630435616,
+           -0.5549212529593688,
+           -0.562908389429829,
+           -0.579245456042304,
+           -0.6051354490754967,
+           -0.6415693491418699,
+           -0.6892940787339137,
+           -0.7487861160977157,
+           -0.8202315000153725,
+           -0.9035128051239133,
+           -0.9982034971390865,
+           -1.1035698959833429,
+           -1.218580786821735,
+           -1.3419245290442428,
+           -1.4720333260164904,
+           -1.6071141386118508,
+           -1.745185557624349,
+           -1.8841197983439835,
+           -2.0216888486674347,
+           -2.155613693443869,
+           -2.283615455077915,
+           -2.403467235851446,
+           -2.513045422414793,
+           -2.6103792181409813,
+           -2.6936972044923913,
+           -2.7614697974325995,
+           -2.8124465577134083,
+           -2.84568743237491,
+           -2.860587146175039,
+           -2.8568921225061277,
+           -2.8347094897683474,
+           -2.7945079168732883,
+           -2.7371102159819594,
+           -2.6636778470056584,
+           -2.575687652026785,
+           -2.4749013339035946,
+           -2.3633283673632466,
+           -2.24318318860626,
+           -2.1168376469868404,
+           -1.9867698163307945,
+           -1.8555103511168407,
+           -1.7255876319302355,
+           -1.5994729738503317,
+           -1.4795271700386097,
+           -1.3679496107825013,
+           -1.2667311564065376,
+           -1.1776118522964216,
+           -1.1020444580002056,
+           -1.0411646228159297,
+           -0.9957683808595089,
+           -0.9662974632261612,
+           -0.9528327377970812,
+           -0.9550958930677441,
+           -0.9724592858214831,
+           -1.0039636783322317,
+           -1.048343403779182,
+           -1.1040583232381478,
+           -1.169331778231951,
+           -1.2421936032301217,
+           -1.320527146049935,
+           -1.402119153615722,
+           -1.4847113181286153,
+           -1.5660522458372346,
+           -1.6439486080043457,
+           -1.7163142613128635,
+           -1.7812161820784171,
+           -1.836916143742726,
+           -1.8819071780326329,
+           -1.9149439940724464,
+           -1.9350666832583234,
+           -1.9416172069929778,
+           -1.9342483452043135,
+           -1.9129249714252212,
+           -1.877917710421895,
+           -1.8297892222051,
+           -1.7693735370931367,
+           -1.6977490358511975,
+           -1.616205822639722,
+           -1.5262083727924909,
+           -1.4293544490339793,
+           -1.3273313659271433,
+           -1.2218707410492116,
+           -1.1147029012450924,
+           -1.0075121126498436,
+           -0.9018937740852986,
+           -0.7993146557393952,
+           -0.7010771802606824,
+           -0.6082886337515625,
+           -0.5218360624467672,
+           -0.44236746049082,
+           -0.37027968901533986,
+           -0.3057133908651904,
+           -0.24855498329475303,
+           -0.19844562736306176,
+           -0.1547968922447755,
+           -0.11681265980530951,
+           -0.08351665392825221,
+           -0.053784834291132705,
+           -0.026381769213303704,
+           -2.451832280263885e-16
+          ],
+          [
+           0,
+           0.02722975837078571,
+           0.0567110638526839,
+           0.08967250489027606,
+           0.1272285271381245,
+           0.17034352157818114,
+           0.2198000086235736,
+           0.27617178608898546,
+           0.33980278073222425,
+           0.41079219572942316,
+           0.4889863836593312,
+           0.5739777004535519,
+           0.6651104147214068,
+           0.7614935634608114,
+           0.8620204640645808,
+           0.9653944183167844,
+           1.0701599811706328,
+           1.1747390196537526,
+           1.277470659022045,
+           1.3766541075659193,
+           1.4705932709889864,
+           1.5576420141271619,
+           1.636248903371476,
+           1.70500026819873,
+           1.7626604546618834,
+           1.80820820677195,
+           1.8408682019221545,
+           1.8601368816885306,
+           1.8658018566856953,
+           1.8579543202994533,
+           1.8369940772198134,
+           1.8036269745378612,
+           1.7588547112496244,
+           1.7039571916657068,
+           1.640467774743352,
+           1.5701419500910967,
+           1.4949201378815427,
+           1.4168854599748382,
+           1.3382174594321405,
+           1.261142852004241,
+           1.1878844734093663,
+           1.1206096382017117,
+           1.0613791484079322,
+           1.012098182231266,
+           0.9744702550963138,
+           0.9499553779803086,
+           0.9397334429213414,
+           0.9446737450696367,
+           0.9653114075441777,
+           1.001831313124947,
+           1.0540599693771464,
+           1.121465545474686,
+           1.2031661243462604,
+           1.2979460175499817,
+           1.4042797972778065,
+           1.5203635148116654,
+           1.6441524021220466,
+           1.7734041973391648,
+           1.9057270993534137,
+           2.0386312451332045,
+           2.1695825182208957,
+           2.296057440368937,
+           2.4155978717960487,
+           2.5258642497298465,
+           2.6246861296604327,
+           2.7101088582119863,
+           2.7804352991737735,
+           2.8342616527545816,
+           2.8705065496407967,
+           2.8884327624906265,
+           2.887661054152012,
+           2.868175869836694,
+           2.8303227751313713,
+           2.774797738332871,
+           2.702628549367912,
+           2.6151488537844227,
+           2.513965454456103,
+           2.4009196915023083,
+           2.2780438486745456,
+           2.147513648780889,
+           2.0115979888733215,
+           1.8726071258202257,
+           1.7328405531350333,
+           1.5945358098722366,
+           1.4598194321200086,
+           1.330661197945596,
+           1.2088327291378307,
+           1.0958713999774292,
+           0.9930503674125698,
+           0.9013553818428346,
+           0.8214688671072677,
+           0.753761576492071,
+           0.6982919431488837,
+           0.6548130529266377,
+           0.6227869799891127,
+           0.6014060453568235,
+           0.5896203901223026,
+           0.5861711026845037,
+           0.5896280066663103,
+           0.5984311064556934,
+           0.6109346032039507,
+           0.6254523376376506,
+           0.6403034885156219,
+           0.653857357584391,
+           0.6645761033123787,
+           0.6710543456376752,
+           0.6720546508580496,
+           0.6665380173657768,
+           0.6536886163107588,
+           0.6329321930495662,
+           0.6039477015356048,
+           0.566671920399689,
+           0.5212969818809092,
+           0.46826092837598327,
+           0.4082315915377224,
+           0.342084261018685,
+           0.27087376977954813,
+           0.19580176633240623,
+           0.1181800677524076,
+           0.039391087657343525,
+           -0.039153591901701194,
+           -0.11605538845386953,
+           -0.18997049228763288,
+           -0.2596501206533365,
+           -0.3239781683221058,
+           -0.38200523718805035,
+           -0.4329781211313585,
+           -0.4763639397048464,
+           -0.5118682524025459,
+           -0.5394466408255282,
+           -0.5593094150478767,
+           -0.5719192786333472,
+           -0.5779819695553963,
+           -0.5784300771032433,
+           -0.5744004130812747,
+           -0.567205484706699,
+           -0.5582997722815415,
+           -0.5492416529933526,
+           -0.5416519295478959,
+           -0.5371700157409415,
+           -0.5374088981153289,
+           -0.5439100317609362,
+           -0.5580993380390359,
+           -0.5812454522175567,
+           -0.6144213200980877,
+           -0.658470165836184,
+           -0.7139767501433318,
+           -0.7812447114082293,
+           -0.8602806350797114,
+           -0.9507853325255506,
+           -1.0521526335637073,
+           -1.1634758113279469,
+           -1.283561568674072,
+           -1.4109513266588871,
+           -1.543949372427184,
+           -1.6806572506908077,
+           -1.8190136242099622,
+           -1.9568386882725342,
+           -2.091882105650999,
+           -2.221873334900063,
+           -2.3445731585351965,
+           -2.4578251803249254,
+           -2.5596060536476624,
+           -2.6480732258767548,
+           -2.721609036586852,
+           -2.778860088807546,
+           -2.8187709206641745,
+           -2.840611136958622,
+           -2.843995313375045,
+           -2.8288951563461717,
+           -2.795643585056144,
+           -2.744930594128642,
+           -2.6777909515787686,
+           -2.595583981815454,
+           -2.4999658731041223,
+           -2.3928551283043835,
+           -2.276391942499345,
+           -2.152892437298705,
+           -2.024798805550202,
+           -1.8946265188954525,
+           -1.76490982163859,
+           -1.6381467760154467,
+           -1.5167451351345327,
+           -1.4029703003306755,
+           -1.2988965699004102,
+           -1.206362807390196,
+           -1.1269335517067522,
+           -1.0618664609017199,
+           -1.0120868297352619,
+           -0.9781697517527055,
+           -0.9603303137505741,
+           -0.9584220186264143,
+           -0.9719434363818296,
+           -1.000052887262367,
+           -1.041590770438589,
+           -1.09510897089382,
+           -1.1589066106724888,
+           -1.2310712623910933,
+           -1.3095246164998884,
+           -1.392071492244208,
+           -1.476451008031115,
+           -1.5603886817060417,
+           -1.641648216114472,
+           -1.7180817405528321,
+           -1.7876773238409398,
+           -1.8486026485794578,
+           -1.8992438367894595,
+           -1.9382385420098034,
+           -1.9645025689014197,
+           -1.9772494448106959,
+           -1.9760025444906408,
+           -1.9605995548597792,
+           -1.9311892566760522,
+           -1.8882207896008127,
+           -1.8324257516313942,
+           -1.76479365873219,
+           -1.6865414513858727,
+           -1.5990778777672983,
+           -1.5039637048158423,
+           -1.4028688056912013,
+           -1.2975272425994504,
+           -1.1896915060981361,
+           -1.0810870847696565,
+           -0.9733685223641648,
+           -0.8680780736679983,
+           -0.7666079966884171,
+           -0.6701674191895279,
+           -0.5797545947424538,
+           -0.49613522041833513,
+           -0.41982732870866446,
+           -0.3510930942652963,
+           -0.2899377159789268,
+           -0.23611535132413944,
+           -0.18914189743652104,
+           -0.14831423666498764,
+           -0.11273539782232518,
+           -0.0813449322398735,
+           -0.05295366985326285,
+           -0.026281908277715184,
+           -2.472104830677017e-16
+          ],
+          [
+           0,
+           0.027970120602575168,
+           0.05877955835542394,
+           0.09360093205877276,
+           0.13347306162248096,
+           0.17926725469744487,
+           0.2316581904996327,
+           0.29110019738536635,
+           0.357809581186002,
+           0.43175350470161095,
+           0.5126457490455084,
+           0.5999495090160579,
+           0.6928871918659634,
+           0.7904570063712506,
+           0.8914559515976775,
+           0.9945086467270026,
+           1.0981012890125432,
+           1.2006198903160135,
+           1.3003918272304205,
+           1.3957296484851138,
+           1.4849760185256833,
+           1.5665486395691128,
+           1.6389839870544074,
+           1.7009787155115446,
+           1.751427642989357,
+           1.789457301120971,
+           1.8144541427699379,
+           1.8260866274453977,
+           1.8243205531646713,
+           1.809427168528625,
+           1.7819837763884867,
+           1.7428667262306714,
+           1.6932368816839765,
+           1.634517837658267,
+           1.5683673438707846,
+           1.4966425633557663,
+           1.4213599516834632,
+           1.344650681089432,
+           1.2687126500416523,
+           1.195760209999969,
+           1.1279728049131053,
+           1.0674437536906094,
+           1.0161304105338602,
+           0.9758069124057294,
+           0.9480206676031057,
+           0.9340536556450703,
+           0.9348894984802708,
+           0.9511871289843562,
+           0.983261728087228,
+           1.031073430378597,
+           1.0942241138472357,
+           1.171962396991743,
+           1.2631967705842053,
+           1.3665165966517256,
+           1.4802205185186184,
+           1.6023516476369075,
+           1.7307387297815522,
+           1.8630423489940797,
+           1.9968051059567762,
+           2.1295046112535476,
+           2.258608065584925,
+           2.381627160134752,
+           2.4961720218939267,
+           2.6000029510451284,
+           2.691078749963987,
+           2.7676005247195086,
+           2.8280499481778403,
+           2.8712211062866837,
+           2.896245202609912,
+           2.9026075669459708,
+           2.8901565977320094,
+           2.859104460422505,
+           2.810019560443057,
+           2.743811004871629,
+           2.6617054569310508,
+           2.565216967071307,
+           2.456110529517697,
+           2.3363602596644593,
+           2.2081032120679325,
+           2.0735899580518344,
+           1.9351331137144303,
+           1.7950550517368056,
+           1.6556360428663783,
+           1.5190640550666499,
+           1.3873873906061769,
+           1.2624712650645666,
+           1.1459593293188015,
+           1.0392410086511017,
+           0.9434253853867428,
+           0.8593221866313341,
+           0.7874302608512788,
+           0.7279337406584777,
+           0.6807058988541976,
+           0.6453205152757141,
+           0.6210703879621154,
+           0.6069924481541746,
+           0.6018987789503658,
+           0.6044126959746745,
+           0.6130089286276393,
+           0.626056845298941,
+           0.6418655976082145,
+           0.6587300189262082,
+           0.6749761020130669,
+           0.689004899760822,
+           0.699333741171705,
+           0.7046337305475886,
+           0.7037625994241882,
+           0.6957921054324783,
+           0.680029316811572,
+           0.6560312820424441,
+           0.6236127569299756,
+           0.5828468420451646,
+           0.53405856717501,
+           0.4778116416677002,
+           0.4148887657015205,
+           0.34626606310251684,
+           0.27308234721373875,
+           0.19660406367692398,
+           0.11818686449481942,
+           0.03923485361984097,
+           -0.038841396594439935,
+           -0.11466692791963431,
+           -0.18694344581132472,
+           -0.2544882313424234,
+           -0.31626986651875816,
+           -0.37143980661733933,
+           -0.41935894069723634,
+           -0.4596184111012399,
+           -0.4920541113162454,
+           -0.5167544452365872,
+           -0.5340611055394623,
+           -0.5445628101169039,
+           -0.5490821187271314,
+           -0.5486556325880795,
+           -0.5445080529571431,
+           -0.5380207364210985,
+           -0.5306955305419647,
+           -0.5241147999431847,
+           -0.5198986566337556,
+           -0.5196604866800939,
+           -0.5249619162036924,
+           -0.5372683817490713,
+           -0.5579064626934561,
+           -0.5880240966554394,
+           -0.6285547336385715,
+           -0.6801863924662676,
+           -0.743336466153358,
+           -0.8181329840664846,
+           -0.9044028814530278,
+           -1.001667655037192,
+           -1.1091466011370923,
+           -1.225767644659829,
+           -1.3501855780516032,
+           -1.4808073435245817,
+           -1.615823814284064,
+           -1.7532473654769418,
+           -1.8909543773137678,
+           -2.0267316850117094,
+           -2.1583258860977934,
+           -2.283494337852412,
+           -2.400056628268662,
+           -2.5059452841619083,
+           -2.599254490564588,
+           -2.678285636116138,
+           -2.74158856889614,
+           -2.7879975444196945,
+           -2.8166609700036687,
+           -2.827064194482369,
+           -2.8190447558090774,
+           -2.792799677465158,
+           -2.748884593479923,
+           -2.6882046766466448,
+           -2.6119975404559908,
+           -2.521808477576369,
+           -2.4194585816936454,
+           -2.3070064706809155,
+           -2.1867044832148,
+           -2.06095035431167,
+           -1.9322354845579337,
+           -1.8030910003702867,
+           -1.6760328564181128,
+           -1.5535072550456328,
+           -1.4378376505586221,
+           -1.331174568752761,
+           -1.2354494049670885,
+           -1.1523332688826833,
+           -1.083201823571165,
+           -1.0291069228777352,
+           -0.9907556885991169,
+           -0.9684974910581522,
+           -0.9623191079238496,
+           -0.9718481410818856,
+           -0.9963645747804615,
+           -1.0348201649469433,
+           -1.0858651641947765,
+           -1.147881714120223,
+           -1.2190230802157864,
+           -1.2972577688796065,
+           -1.3804174538484189,
+           -1.4662475536102006,
+           -1.5524592439935907,
+           -1.636781662515066,
+           -1.717013063788699,
+           -1.7910697182163309,
+           -1.8570314083855166,
+           -1.9131824674950695,
+           -1.9580474194117927,
+           -1.990420417723571,
+           -2.009387837931933,
+           -2.0143435487969406,
+           -2.0049965715214384,
+           -1.9813710243938891,
+           -1.9437984410091993,
+           -1.8929027375364424,
+           -1.8295782840714845,
+           -1.754961702475215,
+           -1.6703981641413046,
+           -1.577403092162958,
+           -1.4776202801837444,
+           -1.3727775222158662,
+           -1.2646409019308007,
+           -1.154968915109855,
+           -1.0454675945496563,
+           -0.9377477729534887,
+           -0.8332855571396293,
+           -0.7333869979079817,
+           -0.6391578264374292,
+           -0.5514789930589197,
+           -0.4709885911176932,
+           -0.3980705813043684,
+           -0.3328505545510206,
+           -0.27519858884946075,
+           -0.22473907178051097,
+           -0.18086718078458097,
+           -0.14277154179409465,
+           -0.1094624281105531,
+           -0.07980471934335857,
+           -0.05255471841132206,
+           -0.026399826105570855,
+           -2.512453508765876e-16
+          ],
+          [
+           0,
+           0.02891280485584524,
+           0.06122738117091213,
+           0.09805000089884594,
+           0.140334652978108,
+           0.188851817707419,
+           0.24416229941680412,
+           0.30659683585910236,
+           0.37624205303552977,
+           0.4529331696533329,
+           0.5362536802554658,
+           0.6255420646942169,
+           0.7199053886354411,
+           0.8182394798150647,
+           0.9192551923911783,
+           1.0215101113238776,
+           1.12344490435614,
+           1.2234234045492767,
+           1.3197754046419619,
+           1.4108410683772952,
+           1.4950158153649515,
+           1.570794516314464,
+           1.6368138451689571,
+           1.6918916736275869,
+           1.7350624608772243,
+           1.7656076854551892,
+           1.7830804847573567,
+           1.7873238078949834,
+           1.7784815459482384,
+           1.757002276263052,
+           1.7236354400244318,
+           1.6794199603890057,
+           1.6256654973011877,
+           1.5639267200493479,
+           1.4959711550256107,
+           1.4237413296215988,
+           1.3493120796201092,
+           1.2748440131402572,
+           1.2025342259782812,
+           1.134565438459997,
+           1.0730547707373919,
+           1.0200033905740578,
+           0.9772482545572624,
+           0.9464171205792163,
+           0.9288879373182224,
+           0.9257536170116372,
+           0.9377930734135856,
+           0.9654492604576177,
+           1.0088147823303717,
+           1.0676254663996434,
+           1.1412621010832416,
+           1.2287603459028493,
+           1.3288286253903197,
+           1.4398736269772885,
+           1.5600328401841703,
+           1.687213404804625,
+           1.819136383509925,
+           1.9533854431069348,
+           2.087458821792045,
+           2.2188233797769303,
+           2.3449694795878386,
+           2.46346542141896,
+           2.572010168675236,
+           2.6684831390424146,
+           2.7509899060992034,
+           2.8179027539422545,
+           2.867895150155536,
+           2.8999693477243254,
+           2.913476490627509,
+           2.908128776835711,
+           2.8840034219315487,
+           2.841538361932198,
+           2.7815198303733637,
+           2.7050621375244224,
+           2.6135801640583622,
+           2.50875525311816,
+           2.392495339344821,
+           2.266890287324564,
+           2.1341635218506902,
+           1.9966211157491391,
+           1.8565995558122494,
+           1.7164134323541171,
+           1.5783042925097506,
+           1.4443918618634166,
+           1.3166287742644065,
+           1.1967598574438183,
+           1.0862869046302057,
+           0.9864397227385687,
+           0.8981540893798232,
+           0.8220570778652548,
+           0.7584600258769454,
+           0.7073592341023608,
+           0.6684442905874226,
+           0.6411137295622455,
+           0.6244975546550598,
+           0.6174859901364669,
+           0.6187636742105698,
+           0.6268483790513196,
+           0.6401332364182122,
+           0.6569313678315517,
+           0.6755217663471766,
+           0.6941952541473904,
+           0.711299346934554,
+           0.7252808922122816,
+           0.7347254129714634,
+           0.738392179363008,
+           0.7352441462729958,
+           0.7244720313527367,
+           0.7055119625020163,
+           0.6780562921250735,
+           0.6420573534002003,
+           0.5977241168167713,
+           0.5455118887075895,
+           0.4861053728050142,
+           0.4203955864519707,
+           0.34945128070347187,
+           0.27448565419217763,
+           0.19681927076436787,
+           0.11784018750176778,
+           0.03896237040495659,
+           -0.03841648204422446,
+           -0.11295657307156885,
+           -0.18341598016371344,
+           -0.24868789032730593,
+           -0.30783409375747356,
+           -0.3601138288042551,
+           -0.40500719167416116,
+           -0.4422324651659804,
+           -0.4717568783526455,
+           -0.49380047949754685,
+           -0.5088329833236699,
+           -0.5175636365103845,
+           -0.5209243273459158,
+           -0.520046342197388,
+           -0.5162313383867757,
+           -0.510917255934592,
+           -0.5056400255548221,
+           -0.5019920438027146,
+           -0.50157847547149,
+           -0.505972505891744,
+           -0.5166707000598434,
+           -0.5350496305671882,
+           -0.5623249119106016,
+           -0.5995137254621697,
+           -0.6474018384168121,
+           -0.7065160133646512,
+           -0.7771025753472258,
+           -0.8591127535291585,
+           -0.9521952486330489,
+           -1.0556962991412107,
+           -1.168667333373119,
+           -1.289880105513674,
+           -1.4178490261964036,
+           -1.550860217009536,
+           -1.6870066478210743,
+           -1.8242285603819244,
+           -1.9603582451730235,
+           -2.0931681243586753,
+           -2.220421004894692,
+           -2.3399213045947937,
+           -2.4495660218845994,
+           -2.547394217952673,
+           -2.6316338081854402,
+           -2.7007445175443268,
+           -2.7534559405741,
+           -2.788799758987311,
+           -2.8061353055657046,
+           -2.8051678191861944,
+           -2.7859589083423666,
+           -2.7489289254060116,
+           -2.6948511465612386,
+           -2.624837848152249,
+           -2.540318564337158,
+           -2.443010998691495,
+           -2.3348852391652204,
+           -2.2181220872386684,
+           -2.0950664542917026,
+           -1.9681768976088971,
+           -1.8399724621621747,
+           -1.712978060035849,
+           -1.5896696554699445,
+           -1.4724205291000485,
+           -1.3634498699187447,
+           -1.2647748883775782,
+           -1.178167560226999,
+           -1.105117000197429,
+           -1.046798330149792,
+           -1.0040487511500187,
+           -0.9773513568336091,
+           -0.9668270406217642,
+           -0.9722346563362789,
+           -0.992979395240565,
+           -1.0281291472955787,
+           -1.0764384252124033,
+           -1.13637925130582,
+           -1.206178243537556,
+           -1.2838589924437642,
+           -1.3672886983595396,
+           -1.4542279414193067,
+           -1.5423823875346556,
+           -1.6294551935567239,
+           -1.7131988650221852,
+           -1.7914653404202452,
+           -1.8622531262156832,
+           -1.9237503856022609,
+           -1.9743729891251147,
+           -2.0127966642371176,
+           -2.037982530298938,
+           -2.0491954717527485,
+           -2.046014981045581,
+           -2.0283382898987306,
+           -1.9963757980696013,
+           -1.9506389981111214,
+           -1.891921278120345,
+           -1.8212721575573887,
+           -1.739965669652061,
+           -1.6494637438154425,
+           -1.5513755594235248,
+           -1.4474139354795694,
+           -1.3393498867547289,
+           -1.2289665144939759,
+           -1.118013407815005,
+           -1.00816271041496,
+           -0.9009679567656856,
+           -0.7978267039747569,
+           -0.6999478819562176,
+           -0.6083246581642623,
+           -0.5237134671357647,
+           -0.4466196931889655,
+           -0.37729032095297593,
+           -0.3157136873621508,
+           -0.2616262849242549,
+           -0.2145263841092461,
+           -0.17369406719992908,
+           -0.13821710132312265,
+           -0.10702192878764193,
+           -0.07890892205836941,
+           -0.05259094198305586,
+           -0.02673415399057204,
+           -2.5724874122318116e-16
+          ],
+          [
+           0,
+           0.030048901383456318,
+           0.06403169076779543,
+           0.10297852194841298,
+           0.14775011826410356,
+           0.19900930133382497,
+           0.25719799499077795,
+           0.32252033860070517,
+           0.39493238538323205,
+           0.47413869036152123,
+           0.5595959134749275,
+           0.6505233807370332,
+           0.7459203647361404,
+           0.8445896698630405,
+           0.9451669418797279,
+           1.046154970030521,
+           1.145962116705827,
+           1.2429438981074497,
+           1.3354466523031427,
+           1.4218521707561624,
+           1.5006221374636484,
+           1.5703412171177937,
+           1.629757660366208,
+           1.6778203497065853,
+           1.7137112924970492,
+           1.7368726759978197,
+           1.7470277306405393,
+           1.7441947986304494,
+           1.7286941718077002,
+           1.7011474413061383,
+           1.6624692875262488,
+           1.6138518276650353,
+           1.556741824822256,
+           1.4928112428699136,
+           1.4239218003243816,
+           1.3520843301581187,
+           1.279413886962397,
+           1.208081654723757,
+           1.1402647948589106,
+           1.0780954328433143,
+           1.023610011227474,
+           0.9787002362409832,
+           0.9450668144582952,
+           0.9241771158072681,
+           0.9172278109356576,
+           0.9251134167016037,
+           0.9484015460558732,
+           0.9873155011486604,
+           1.0417246749309346,
+           1.1111430410423588,
+           1.194735818896863,
+           1.291334205294271,
+           1.3994578703762015,
+           1.517344729036517,
+           1.6429873235593313,
+           1.7741749935859947,
+           1.9085408694210153,
+           2.043612607614377,
+           2.176865696580855,
+           2.3057780969803088,
+           2.4278849482429576,
+           2.5408320698100977,
+           2.642427013456358,
+           2.7306864807974187,
+           2.8038790063677004,
+           2.8605619193765057,
+           2.8996117336738307,
+           2.9202472722522406,
+           2.922045005956891,
+           2.904946271745121,
+           2.869256229304501,
+           2.8156346113901103,
+           2.7450785180923964,
+           2.6588976936565296,
+           2.5586829018654202,
+           2.4462681780689937,
+           2.323687878770496,
+           2.1931295698216284,
+           2.056883888848877,
+           1.9172925842819077,
+           1.7766959707164598,
+           1.6373810474784414,
+           1.5015315040667072,
+           1.3711807832895484,
+           1.2481692917525897,
+           1.1341067399769524,
+           1.030340463540117,
+           0.9379304255273156,
+           0.8576314330382703,
+           0.789882920690986,
+           0.7348064664731704,
+           0.6922110145664898,
+           0.6616055906315258,
+           0.6422191121627903,
+           0.6330267244097585,
+           0.6327819352398967,
+           0.6400536840400857,
+           0.6532673636839049,
+           0.6707487235446292,
+           0.6907695176894921,
+           0.711593727250094,
+           0.7315231803084784,
+           0.7489414165139463,
+           0.7623546963604033,
+           0.7704291351984328,
+           0.7720230475378329,
+           0.7662137152938391,
+           0.7523179410616571,
+           0.7299059105091574,
+           0.6988080624135488,
+           0.6591148463111945,
+           0.6111694315892389,
+           0.5555536134775149,
+           0.49306733621677096,
+           0.42470241727848973,
+           0.3516112047738659,
+           0.27507102938647254,
+           0.19644541904908724,
+           0.11714312647922122,
+           0.038576074539708356,
+           -0.03788264916765797,
+           -0.1109396196877003,
+           -0.17941962689077776,
+           -0.24230091503179174,
+           -0.2987461586991727,
+           -0.3481283350454667,
+           -0.3900507847228065,
+           -0.42436090477330685,
+           -0.4511570820292161,
+           -0.47078865117638813,
+           -0.48384884308172754,
+           -0.4911608716841699,
+           -0.49375748706746153,
+           -0.49285449372050893,
+           -0.48981889209021356,
+           -0.4861324442904449,
+           -0.4833515876015425,
+           -0.4830647190285467,
+           -0.48684794810997895,
+           -0.49622046145158727,
+           -0.5126006598606327,
+           -0.5372642169580194,
+           -0.5713051669664976,
+           -0.6156010599633998,
+           -0.6707831269051604,
+           -0.7372122765059176,
+           -0.8149616045228762,
+           -0.9038059366444623,
+           -1.0032187529247814,
+           -1.1123766588452546,
+           -1.2301713801479117,
+           -1.355229070246265,
+           -1.4859365349729896,
+           -1.6204738042648155,
+           -1.7568523185018419,
+           -1.8929578526763924,
+           -2.026597178012454,
+           -2.1555473612221805,
+           -2.277606528814438,
+           -2.3906448796478807,
+           -2.492654714433072,
+           -2.581798266585537,
+           -2.6564521644212187,
+           -2.7152474291348248,
+           -2.757104014562534,
+           -2.7812590209848476,
+           -2.787287863139895,
+           -2.7751178386208677,
+           -2.745033722900331,
+           -2.6976752069830225,
+           -2.634026188516248,
+           -2.5553961223312087,
+           -2.4633938270822657,
+           -2.3598943262311027,
+           -2.2469994696437716,
+           -2.1269932324124214,
+           -2.0022927164932893,
+           -1.8753959851993107,
+           -1.7488279379324068,
+           -1.6250854808791635,
+           -1.506583267528918,
+           -1.395601270346261,
+           -1.294235402034337,
+           -1.2043523325976382,
+           -1.127549548607066,
+           -1.0651215761167496,
+           -1.0180331416249717,
+           -0.9868998798967998,
+           -0.9719770174097722,
+           -0.9731562700363496,
+           -0.9899709979716538,
+           -1.0216094646165157,
+           -1.0669358539116907,
+           -1.124518517161998,
+           -1.192664750142803,
+           -1.269461248370344,
+           -1.35281925653623,
+           -1.440523320429175,
+           -1.530282468768701,
+           -1.619782600170301,
+           -1.7067388281556886,
+           -1.7889465451848663,
+           -1.8643300048408478,
+           -1.9309872885251353,
+           -1.9872306175917376,
+           -2.0316210913577932,
+           -2.0629970728690066,
+           -2.0804956041223934,
+           -2.0835664066658452,
+           -2.0719782077647975,
+           -2.045817322074066,
+           -2.00547860927469,
+           -1.95164911472049,
+           -1.8852848781840936,
+           -1.8075815609165595,
+           -1.719939689388264,
+           -1.6239254416417204,
+           -1.5212280060593009,
+           -1.4136146200264847,
+           -1.302884445607696,
+           -1.1908224598020807,
+           -1.0791545277965189,
+           -0.9695047892064246,
+           -0.8633564206459822,
+           -0.7620167448544741,
+           -0.6665875394394557,
+           -0.5779412600911303,
+           -0.4967037374080808,
+           -0.4232437372163877,
+           -0.3576695957586788,
+           -0.29983295789859093,
+           -0.24933946316215044,
+           -0.20556604564982126,
+           -0.16768434410944386,
+           -0.13468956203697519,
+           -0.1054339785046411,
+           -0.07866419200261078,
+           -0.05306108489335832,
+           -0.02728142749045158,
+           -2.651625025519308e-16
+          ],
+          [
+           0,
+           0.03136762736318803,
+           0.06716618720825755,
+           0.10834064008410266,
+           0.15565085741794998,
+           0.20964614616120567,
+           0.2706456176508026,
+           0.3387249452947722,
+           0.4137098896476224,
+           0.4951767934547967,
+           0.5824600677735491,
+           0.6746665079187051,
+           0.770696099360803,
+           0.8692688033558711,
+           0.9689566543419725,
+           1.0682203600166311,
+           1.165449474117335,
+           1.2590051143665164,
+           1.347264126332877,
+           1.4286635499771785,
+           1.5017442305739732,
+           1.565192429989012,
+           1.6178783376672492,
+           1.6588904521407757,
+           1.6875649016863392,
+           1.7035088945716554,
+           1.7066176321462718,
+           1.6970841783428852,
+           1.6754019530001811,
+           1.6423596994935394,
+           1.5990289649203768,
+           1.546744318860286,
+           1.4870767198336752,
+           1.4218006124387041,
+           1.3528554983970507,
+           1.282302867354757,
+           1.2122794946641613,
+           1.1449482104345747,
+           1.08244731439742,
+           1.0268398527583047,
+           0.9800639850824784,
+           0.9438856509925136,
+           0.9198546984044197,
+           0.9092655582835945,
+           0.9131234472687912,
+           0.9321169514614202,
+           0.9665976952865264,
+           1.0165676322100112,
+           1.0816743132961038,
+           1.161214299505614,
+           1.2541446889001095,
+           1.359102535282394,
+           1.4744317450262958,
+           1.5982168585726524,
+           1.7283229567096718,
+           1.8624407833946466,
+           1.998136050152381,
+           2.132901785119407,
+           2.2642125151028774,
+           2.3895790234337233,
+           2.5066024110479175,
+           2.6130262035198624,
+           2.7067852923405105,
+           2.7860505734806877,
+           2.8492682483939906,
+           2.8951928796095583,
+           2.922913441851532,
+           2.9318717765732307,
+           2.921873038842113,
+           2.893087916244325,
+           2.8460465952485796,
+           2.781624646511445,
+           2.7010211921500114,
+           2.6057299003977015,
+           2.4975035218683743,
+           2.3783128327933025,
+           2.2503009804146257,
+           2.115734331093554,
+           1.976951000102782,
+           1.8363082916660542,
+           1.69613029744032,
+           1.5586568909016971,
+           1.4259953143370327,
+           1.3000754854377077,
+           1.1826100536305564,
+           1.0750601147176277,
+           0.9786073491895391,
+           0.8941331883127678,
+           0.8222054367922924,
+           0.763072595839019,
+           0.7166659404174064,
+           0.6826092140182548,
+           0.6602356182003151,
+           0.648611596958767,
+           0.6465667520648612,
+           0.6527290788956471,
+           0.6655645865144573,
+           0.6834202639238645,
+           0.7045692789442229,
+           0.7272572488621084,
+           0.7497484039289716,
+           0.7703704763248321,
+           0.7875571879506462,
+           0.7998872792633245,
+           0.80611911650804,
+           0.8052200336684722,
+           0.7963897051918547,
+           0.7790770024830146,
+           0.752989957306684,
+           0.7180986342736864,
+           0.6746308979811388,
+           0.6230612434954448,
+           0.5640930370883199,
+           0.4986346829694834,
+           0.4277703869550013,
+           0.35272632566581347,
+           0.2748331465102096,
+           0.19548581644157617,
+           0.11610190397819098,
+           0.038079417566585366,
+           -0.03724466689088697,
+           -0.10863407586770177,
+           -0.17499003985002703,
+           -0.23538423650074114,
+           -0.28908698578816344,
+           -0.3355899311172971,
+           -0.37462258385421965,
+           -0.4061622681091299,
+           -0.4304371742024015,
+           -0.44792240853586324,
+           -0.4593291100863102,
+           -0.4655868848035581,
+           -0.4678199842368316,
+           -0.4673178192841876,
+           -0.4655005498711539,
+           -0.46388062279289655,
+           -0.46402123953379887,
+           -0.46749282078989784,
+           -0.47582859245844933,
+           -0.4904804474924055,
+           -0.5127762384235056,
+           -0.5438796264456089,
+           -0.5847535553647125,
+           -0.6361283338283643,
+           -0.6984751990962144,
+           -0.771986102893008,
+           -0.8565603078533635,
+           -0.9517982154715627,
+           -1.057002667454348,
+           -1.1711877763784893,
+           -1.2930951532013475,
+           -1.421217213153049,
+           -1.553827062498884,
+           -1.689014301080768,
+           -1.8247259236351923,
+           -1.9588113704680328,
+           -2.0890706684972753,
+           -2.2133045197443857,
+           -2.329365138228427,
+           -2.435206609372313,
+           -2.528933549226301,
+           -2.6088468740655157,
+           -2.673485553499712,
+           -2.7216633106917585,
+           -2.752499349472336,
+           -2.765442327280109,
+           -2.760286951594756,
+           -2.7371827520227483,
+           -2.696634766205336,
+           -2.639496070717809,
+           -2.5669522834119354,
+           -2.480498356450877,
+           -2.381908164882269,
+           -2.2731975694468716,
+           -2.1565817901661513,
+           -2.0344280652184543,
+           -1.9092046843119352,
+           -1.7834275743696417,
+           -1.6596056756751782,
+           -1.5401863771911375,
+           -1.4275022797937564,
+           -1.3237205256470796,
+           -1.2307958715997132,
+           -1.150428595787733,
+           -1.084028211722835,
+           -1.0326838258330762,
+           -0.997141816072242,
+           -0.9777913346828844,
+           -0.9746579517396734,
+           -0.9874055622577729,
+           -1.015346483146379,
+           -1.0574594719035317,
+           -1.1124152114120747,
+           -1.178608629063245,
+           -1.254197257974835,
+           -1.337144707167203,
+           -1.425268189610011,
+           -1.5162889648859839,
+           -1.6078844890282966,
+           -1.697741029378733,
+           -1.7836054978614766,
+           -1.8633352819042566,
+           -1.934944907651887,
+           -1.9966484536678222,
+           -2.0468967428789675,
+           -2.0844084733219224,
+           -2.108194600963055,
+           -2.1175754566737264,
+           -2.1121902601403697,
+           -2.0919988815864667,
+           -2.0572758930174766,
+           -2.0085971395496927,
+           -1.946819243589703,
+           -1.873052625707179,
+           -1.78862878179081,
+           -1.6950626926859511,
+           -1.5940113566573704,
+           -1.4872295239410196,
+           -1.376523774218447,
+           -1.2637061106248642,
+           -1.1505482471650188,
+           -1.038737740175997,
+           -0.9298370594932177,
+           -0.8252466127124378,
+           -0.7261726285408637,
+           -0.6336006754639757,
+           -0.5482754431432745,
+           -0.4706872498975219,
+           -0.4010655644740441,
+           -0.3393796485258246,
+           -0.2853462423727405,
+           -0.23844403538322737,
+           -0.19793448823671028,
+           -0.16288841180106578,
+           -0.13221756047207783,
+           -0.10471037026396808,
+           -0.07907086691239336,
+           -0.053959689385090666,
+           -0.02803612148630637,
+           -2.7490999693653496e-16
+          ],
+          [
+           0,
+           0.03285643264262326,
+           0.07060136882835878,
+           0.11408628053718245,
+           0.16396351876861168,
+           0.2206640483617615,
+           0.2843813449339214,
+           0.35506190444060465,
+           0.4324026437883419,
+           0.5158552914800004,
+           0.6046376849890374,
+           0.6977517110661674,
+           0.7940074510604314,
+           0.8920529300112991,
+           0.9904087198967778,
+           1.0875065177904313,
+           1.1817307121070253,
+           1.2714618673711942,
+           1.3551210021750375,
+           1.4312135076733807,
+           1.4983715558620032,
+           1.5553938780249392,
+           1.6012818534189377,
+           1.6352709350664614,
+           1.6568565513509266,
+           1.6658137562164912,
+           1.6622100538732754,
+           1.646410992219524,
+           1.6190782985485748,
+           1.5811605170592262,
+           1.5338762956075864,
+           1.4786906543412601,
+           1.4172847467146774,
+           1.3515197894413697,
+           1.2833959880224426,
+           1.2150074148151537,
+           1.1484939038685191,
+           1.0859911082156406,
+           1.0295799188712984,
+           0.9812364690196668,
+           0.942783941097182,
+           0.9158473587256366,
+           0.9018124805187708,
+           0.9017898201824956,
+           0.9165846992514657,
+           0.9466740980829691,
+           0.9921909107567353,
+           1.0529160341806814,
+           1.1282785352377134,
+           1.2173639467681345,
+           1.3189305482757283,
+           1.4314332952358626,
+           1.5530548764693572,
+           1.6817432067443925,
+           1.8152545058065541,
+           1.9512009792445448,
+           2.087102004315012,
+           2.22043763784072,
+           2.3487032056857773,
+           2.4694637055297792,
+           2.580406757409287,
+           2.6793928697226947,
+           2.7645018513091717,
+           2.834074291293112,
+           2.8867471454218148,
+           2.9214826077693523,
+           2.93758960652293,
+           2.934737438215823,
+           2.9129612419450157,
+           2.872659209252838,
+           2.8145816217332404,
+           2.7398120022660173,
+           2.649740852373474,
+           2.5460326230022687,
+           2.4305867248207567,
+           2.3054935230477525,
+           2.1729863775433027,
+           2.0353908786195998,
+           1.8950724906362397,
+           1.754383847487423,
+           1.6156129458563957,
+           1.4809334536364105,
+           1.3523582929727984,
+           1.231697571466258,
+           1.1205218233766858,
+           1.0201313879949927,
+           0.9315325980815895,
+           0.8554212812564452,
+           0.7921738956976427,
+           0.7418464329699567,
+           0.7041810299321775,
+           0.6786200431784667,
+           0.6643271580033426,
+           0.6602149339047562,
+           0.6649780343239522,
+           0.6771312534349063,
+           0.6950513406201646,
+           0.7170215365123692,
+           0.7412776752125044,
+           0.7660546768992543,
+           0.7896322541798727,
+           0.8103786841251461,
+           0.8267915551695089,
+           0.837534482418721,
+           0.8414688941952362,
+           0.8376801240499863,
+           0.8254971926167674,
+           0.8045058287567843,
+           0.7745544552446407,
+           0.735753046330567,
+           0.6884649482737482,
+           0.6332919347411672,
+           0.5710529422486654,
+           0.5027570922251133,
+           0.4295717517493542,
+           0.3527865108910864,
+           0.27377405772592805,
+           0.1939490099110023,
+           0.11472581225993639,
+           0.03747683179182685,
+           -0.03650822528689427,
+           -0.1060604860779733,
+           -0.17016664817332938,
+           -0.22799934683310283,
+           -0.2789423315814303,
+           -0.3226097668700007,
+           -0.3588591243762907,
+           -0.3877973012342787,
+           -0.4097797748165387,
+           -0.4254027861299567,
+           -0.4354887258535742,
+           -0.44106507491999625,
+           -0.44333742080426675,
+           -0.44365722703179156,
+           -0.443485172865032,
+           -0.44435099911406367,
+           -0.44781089148434206,
+           -0.45540350235989097,
+           -0.4686057536037265,
+           -0.4887895757178086,
+           -0.5171807221443161,
+           -0.5548207519457485,
+           -0.602533200637999,
+           -0.6608948593346073,
+           -0.7302129590168046,
+           -0.8105089126966701,
+           -0.9015091070378333,
+           -1.002643060623955,
+           -1.1130490828424333,
+           -1.2315873798313515,
+           -1.3568603667925452,
+           -1.4872397638732187,
+           -1.6208998803201304,
+           -1.755856333040786,
+           -1.8900093050578748,
+           -2.0211903301703544,
+           -2.147211495468594,
+           -2.2659158856193793,
+           -2.3752280538073554,
+           -2.4732032949510216,
+           -2.5580745176296213,
+           -2.628295561643038,
+           -2.6825798871279183,
+           -2.7199336668099883,
+           -2.739682442763532,
+           -2.741490659853368,
+           -2.725373556206626,
+           -2.6917010725217834,
+           -2.6411936323568304,
+           -2.5749098401076354,
+           -2.4942263374404594,
+           -2.4008102477344755,
+           -2.2965848169980125,
+           -2.183689024360714,
+           -2.064432081572513,
+           -1.9412438653625053,
+           -1.8166224259658241,
+           -1.693079787160107,
+           -1.5730872959844011,
+           -1.4590217928724416,
+           -1.3531138548935981,
+           -1.2573993165789734,
+           -1.1736751955790496,
+           -1.1034610460243746,
+           -1.047966633477689,
+           -1.008066674914152,
+           -0.9842832189083507,
+           -0.9767760592420288,
+           -0.9853413839065794,
+           -1.0094186656171937,
+           -1.0481056042484276,
+           -1.1001807408044941,
+           -1.1641331812881317,
+           -1.2381987015275804,
+           -1.320401354714027,
+           -1.4085995756980572,
+           -1.5005356730649873,
+           -1.5938875241185815,
+           -1.6863212409435404,
+           -1.7755435587695967,
+           -1.859352711265795,
+           -1.9356866007474762,
+           -2.002667143440183,
+           -2.0586397690668545,
+           -2.1022071776006186,
+           -2.1322566009502735,
+           -2.147979979995028,
+           -2.148886643705436,
+           -2.1348082626960885,
+           -2.1058960398498057,
+           -2.062610290924999,
+           -2.005702753610176,
+           -1.936192139752628,
+           -1.8553336081329799,
+           -1.7645829802014255,
+           -1.6655566450990087,
+           -1.5599882000548204,
+           -1.449682945480205,
+           -1.3364713990423072,
+           -1.2221630086669888,
+           -1.1085012305016775,
+           -0.9971210948075165,
+           -0.8895103117169972,
+           -0.786974871654568,
+           -0.6906099744869025,
+           -0.601276980245764,
+           -0.5195869161538448,
+           -0.4458909037039973,
+           -0.38027769003041184,
+           -0.3225782843084944,
+           -0.2723775170634709,
+           -0.22903216266703497,
+           -0.19169509742984844,
+           -0.15934481177732807,
+           -0.1308194588937765,
+           -0.1048545073497023,
+           -0.08012297446581093,
+           -0.055277152782412346,
+           -0.02899070559679592,
+           -2.863968574298271e-16
+          ],
+          [
+           0,
+           0.03450112285696307,
+           0.07430482032547882,
+           0.12016163619337988,
+           0.1726107108748567,
+           0.2319609114393539,
+           0.2982783877962974,
+           0.37138090775862526,
+           0.45083914710561035,
+           0.5359849294044093,
+           0.6259262288290466,
+           0.7195685721411574,
+           0.8156423078665428,
+           0.912735055792048,
+           1.0093285121667672,
+           1.103838668940715,
+           1.1946584120175567,
+           1.2802013962485315,
+           1.358946055512405,
+           1.4294785957738436,
+           1.4905338378278372,
+           1.5410328241246471,
+           1.5801161795070695,
+           1.6071723170607572,
+           1.6218597051066734,
+           1.62412255658802,
+           1.6141994641409008,
+           1.5926246789794454,
+           1.5602219150341523,
+           1.5180907469981375,
+           1.4675858573932612,
+           1.4102895688086183,
+           1.3479782685539583,
+           1.2825834898137662,
+           1.2161485520322166,
+           1.150781780196423,
+           1.0886074149381662,
+           1.0317153905707495,
+           0.9821111946127311,
+           0.9416670290263349,
+           0.9120754700542304,
+           0.8948067706537499,
+           0.8910708683146695,
+           0.9017850534196172,
+           0.927548121835508,
+           0.9686216832740451,
+           1.0249191278091683,
+           1.0960025708949197,
+           1.1810879067189772,
+           1.2790579054011733,
+           1.3884830961502361,
+           1.5076499907575647,
+           1.6345960243335844,
+           1.7671504273336438,
+           1.902980098676596,
+           2.0396394276782686,
+           2.1746229156115016,
+           2.305419378358229,
+           2.429566471556738,
+           2.544704269872358,
+           2.6486266527943987,
+           2.739329300200216,
+           2.8150531806063657,
+           2.874322521618051,
+           2.915976383003736,
+           2.9391931048779663,
+           2.9435070729720536,
+           2.9288174257820407,
+           2.895388520055206,
+           2.843842166943784,
+           2.775141846451095,
+           2.690569297771282,
+           2.5916940631640752,
+           2.480336728741954,
+           2.3585267529658447,
+           2.228455899186413,
+           2.0924283892120377,
+           1.952808968226166,
+           1.8119701156842205,
+           1.672239651076543,
+           1.535849967371773,
+           1.4048900790227223,
+           1.2812615968253351,
+           1.166639640574982,
+           1.062439574921383,
+           0.9697903072339348,
+           0.8895147223141417,
+           0.822117651514829,
+           0.7677815876485233,
+           0.7263701666027735,
+           0.6974392465367683,
+           0.6802552305986675,
+           0.6738201038277442,
+           0.6769024935906591,
+           0.6880739194928479,
+           0.7057492766965807,
+           0.7282304989206065,
+           0.7537522764345314,
+           0.7805286617679755,
+           0.8067993825941949,
+           0.8308746975526393,
+           0.8511776761397996,
+           0.8662828569950387,
+           0.8749503380179476,
+           0.8761544742140646,
+           0.8691065018356862,
+           0.8532705666246897,
+           0.828372805727644,
+           0.7944033127867479,
+           0.7516109992634498,
+           0.7004915475913926,
+           0.6417688286815765,
+           0.5763703231621996,
+           0.5053972383352304,
+           0.4300901473410624,
+           0.35179109007081505,
+           0.2719031641255566,
+           0.19184869637873173,
+           0.11302711990756534,
+           0.036773686382967546,
+           -0.035679879664690786,
+           -0.10324173033437338,
+           -0.1649922723172681,
+           -0.22021170216779595,
+           -0.26840195421096535,
+           -0.3093024620782748,
+           -0.3428992960047551,
+           -0.36942741055223705,
+           -0.38936591697576384,
+           -0.40342647646904384,
+           -0.41253509039425484,
+           -0.4178077367550367,
+           -0.42052046420802114,
+           -0.4220747017026419,
+           -0.4239586696445224,
+           -0.4277058840220517,
+           -0.43485182550098556,
+           -0.44688989898546116,
+           -0.46522783414943825,
+           -0.49114567325791475,
+           -0.5257564592513677,
+           -0.569970675320587,
+           -0.6244653985269101,
+           -0.6896590165770644,
+           -0.7656922214191398,
+           -0.8524158392200127,
+           -0.9493858873217774,
+           -1.0558660691417483,
+           -1.170837732140065,
+           -1.2930171265571475,
+           -1.4208796182979904,
+           -1.5526903327208443,
+           -1.6865405416041797,
+           -1.8203889573538523,
+           -1.952106970315252,
+           -2.0795267601246756,
+           -2.2004911330545265,
+           -2.312903886321828,
+           -2.414779478695872,
+           -2.5042907950890694,
+           -2.57981383103656,
+           -2.6399681902158303,
+           -2.6836523828599934,
+           -2.710073032828143,
+           -2.7187672433370835,
+           -2.709617532498772,
+           -2.6828589259417917,
+           -2.639077980642308,
+           -2.579203707097587,
+           -2.5044905514324185,
+           -2.416493790180538,
+           -2.317037873650293,
+           -2.2081784244749634,
+           -2.0921587519741367,
+           -1.9713618765276697,
+           -1.8482591679992295,
+           -1.7253567856343028,
+           -1.605141161733349,
+           -1.490024796400167,
+           -1.3822936251521223,
+           -1.2840571852665896,
+           -1.197202741282198,
+           -1.123354436655606,
+           -1.063838419459818,
+           -1.019654748092482,
+           -0.9914567216959229,
+           -0.9795381032995447,
+           -0.9838285158829974,
+           -1.0038970971973622,
+           -1.0389643030031175,
+           -1.0879215551601842,
+           -1.1493582454341171,
+           -1.2215954324689848,
+           -1.3027254123254757,
+           -1.3906562060906738,
+           -1.483159894633788,
+           -1.577923643330263,
+           -1.67260220058055,
+           -1.7648706245875063,
+           -1.8524759937770394,
+           -1.9332868873545324,
+           -2.0053394829472997,
+           -2.0668792065333212,
+           -2.1163969836602083,
+           -2.152659277453264,
+           -2.1747312546807667,
+           -2.1819925923042054,
+           -2.1741456192351607,
+           -2.1512156769275568,
+           -2.113543773278631,
+           -2.061771792381996,
+           -1.9968207033377876,
+           -1.9198623801383956,
+           -1.8322857974775852,
+           -1.7356585004450678,
+           -1.6316843562346925,
+           -1.5221586805564928,
+           -1.4089218883863501,
+           -1.2938128466893961,
+           -1.178623105214617,
+           -1.0650531505147642,
+           -0.9546717688675782,
+           -0.8488795173396014,
+           -0.748877191091256,
+           -0.6556400420312692,
+           -0.5698983524914071,
+           -0.49212480156345856,
+           -0.4225288853334332,
+           -0.36105846992838014,
+           -0.3074083726651014,
+           -0.2610356862889276,
+           -0.2211813888550542,
+           -0.18689762157186365,
+           -0.15707987291922343,
+           -0.13050318318698567,
+           -0.10586138235861017,
+           -0.08180829852056314,
+           -0.056999825595392815,
+           -0.030135719370388662,
+           -2.9951192000071565e-16
+          ],
+          [
+           0,
+           0.036285998656671405,
+           0.07824152930639755,
+           0.12650969120431832,
+           0.18151175343916104,
+           0.2434318343114251,
+           0.3122082147951903,
+           0.3875315382382157,
+           0.4688499688566061,
+           0.5553811998788452,
+           0.6461310229994859,
+           0.7399179986652847,
+           0.8354036060120102,
+           0.9311271060906322,
+           1.0255442260725807,
+           1.1170686686309714,
+           1.2041153723230351,
+           1.2851443975851355,
+           1.3587042902527933,
+           1.423473780976736,
+           1.4783007144337121,
+           1.5222371660094294,
+           1.5545697941321113,
+           1.5748445914576743,
+           1.5828853348314704,
+           1.5788051890081412,
+           1.5630110886656583,
+           1.5362007030969842,
+           1.4993519736313494,
+           1.4537054007002232,
+           1.4007394408538778,
+           1.3421395493620574,
+           1.2797615668964768,
+           1.2155902950934192,
+           1.1516942318341534,
+           1.090177539656899,
+           1.0331303971998937,
+           0.982578931985234,
+           0.9404359518947432,
+           0.9084536817929453,
+           0.8881796710907627,
+           0.8809169685248999,
+           0.8876895636765064,
+           0.9092139730689811,
+           0.945877704989552,
+           0.9977251749422272,
+           1.0644514667944454,
+           1.1454041475269936,
+           1.239593150598786,
+           1.34570854900614,
+           1.4621458488945471,
+           1.5870382527298852,
+           1.7182951720166757,
+           1.8536461175153987,
+           1.9906889635990206,
+           2.1269414760369054,
+           2.259894911753188,
+           2.3870684469783296,
+           2.5060631679983634,
+           2.61461436697598,
+           2.7106409238941653,
+           2.792290623637433,
+           2.8579803529384376,
+           2.9064302430599707,
+           2.936690967712198,
+           2.9481635683297363,
+           2.9406113564961758,
+           2.91416363168009,
+           2.869311146951446,
+           2.806893451247243,
+           2.72807842928533,
+           2.63433454470626,
+           2.5273964639765674,
+           2.409224893844596,
+           2.281961599948115,
+           2.1478806852811765,
+           2.00933729197218,
+           1.8687149461908414,
+           1.7283727926733543,
+           1.5905939617475804,
+           1.4575362780131382,
+           1.3311864568840956,
+           1.2133188446502865,
+           1.1054596418492304,
+           1.008857411474223,
+           0.9244605163322238,
+           0.8529019576232673,
+           0.7944919038206089,
+           0.7492180097220729,
+           0.7167534347968881,
+           0.696472282375225,
+           0.687472001436929,
+           0.6886021251666309,
+           0.6984985691567974,
+           0.715622580847875,
+           0.7383033236806231,
+           0.7647829971029232,
+           0.7932633389783939,
+           0.8219523313502165,
+           0.8491099344593711,
+           0.8730917072048435,
+           0.8923892339361186,
+           0.9056663659517558,
+           0.9117903990430732,
+           0.9098574429644887,
+           0.8992113913934651,
+           0.8794560678789586,
+           0.8504603002338184,
+           0.8123558583267887,
+           0.765528373666008,
+           0.7106015389142253,
+           0.6484150570130206,
+           0.5799969686077714,
+           0.5065311289668077,
+           0.4293207280064223,
+           0.34974884630664105,
+           0.2692371136548167,
+           0.189203582855508,
+           0.11102094915891036,
+           0.035976234269448286,
+           -0.034766986185138606,
+           -0.100202800579378,
+           -0.15951270712299795,
+           -0.21209008730807785,
+           -0.2575587444304614,
+           -0.2957849994616467,
+           -0.3268830045001645,
+           -0.351213110862442,
+           -0.36937331009875757,
+           -0.38218394724315013,
+           -0.39066608183285645,
+           -0.3960140391858336,
+           -0.39956284785673796,
+           -0.40275139519160336,
+           -0.40708224799238674,
+           -0.4140791765304254,
+           -0.42524348515391125,
+           -0.44201028981688745,
+           -0.46570589101256665,
+           -0.49750736954407104,
+           -0.5384054827655682,
+           -0.5891718615531403,
+           -0.6503314051880166,
+           -0.7221406450734843,
+           -0.8045727018645944,
+           -0.8973092977798952,
+           -0.999740110619202,
+           -1.1109695726825328,
+           -1.2298310309366989,
+           -1.3549079990680797,
+           -1.4845620521371659,
+           -1.6169667449210678,
+           -1.750146779959082,
+           -1.882021514713453,
+           -2.0104517825846715,
+           -2.133288912700449,
+           -2.2484247707446383,
+           -2.3538416092500016,
+           -2.447660511682024,
+           -2.528187240488172,
+           -2.5939543545369435,
+           -2.6437585447531142,
+           -2.6766922463018044,
+           -2.692168718765528,
+           -2.689939939190063,
+           -2.6701068229340756,
+           -2.6331214698136765,
+           -2.57978132364165,
+           -2.5112153272705013,
+           -2.4288623479168048,
+           -2.3344423341540304,
+           -2.229920841938163,
+           -2.117467728054166,
+           -1.99941095148392,
+           -1.8781865428989932,
+           -1.756285896820823,
+           -1.6362016076343133,
+           -1.520373107930122,
+           -1.411133374649191,
+           -1.3106579450116322,
+           -1.220917430782255,
+           -1.143634637338643,
+           -1.0802472852507796,
+           -1.0318771992922775,
+           -0.9993066762088493,
+           -0.9829625719069318,
+           -0.9829084651469593,
+           -0.9988450628010285,
+           -1.0301188159367296,
+           -1.0757385211818893,
+           -1.1343994927452263,
+           -1.2045147117088069,
+           -1.2842521951059205,
+           -1.3715776818261631,
+           -1.464301609060944,
+           -1.5601292547833503,
+           -1.6567128509928535,
+           -1.751704430818312,
+           -1.8428081610148177,
+           -1.9278309301243859,
+           -2.0047300110663766,
+           -2.0716566939191465,
+           -2.126994888189826,
+           -2.1693938213347552,
+           -2.197794108496189,
+           -2.2114466336630705,
+           -2.2099238606350156,
+           -2.1931233788485938,
+           -2.1612636796924978,
+           -2.1148723486859358,
+           -2.054767043146366,
+           -1.9820297991981743,
+           -1.8979753719012433,
+           -1.804114453999749,
+           -1.702112738858744,
+           -1.5937468886663997,
+           -1.480858537646482,
+           -1.365307500233723,
+           -1.2489253650107066,
+           -1.133470636517871,
+           -1.0205865393920353,
+           -0.9117625239495001,
+           -0.8083004112789414,
+           -0.7112859917577579,
+           -0.6215667468339827,
+           -0.5397362035980037,
+           -0.46612525917534964,
+           -0.40080063167335284,
+           -0.3435704108669916,
+           -0.2939964996427714,
+           -0.2514135610224364,
+           -0.21495391979144432,
+           -0.18357771652462734,
+           -0.15610747892522867,
+           -0.13126616420025314,
+           -0.10771763946223213,
+           -0.08410850703458381,
+           -0.059110149532722304,
+           -0.031459866475204566,
+           -3.141283204547239e-16
+          ],
+          [
+           0,
+           0.03819400961674868,
+           0.0823742280585067,
+           0.13307077556803415,
+           0.19058345965080195,
+           0.25497012568522587,
+           0.3260417917183386,
+           0.40336471715472155,
+           0.48626937400992787,
+           0.5738661089257399,
+           0.6650671088148621,
+           0.758614117272009,
+           0.8531111969735851,
+           0.9470616990620243,
+           1.0389084874047927,
+           1.1270763765359584,
+           1.2100156793331858,
+           1.2862457256992272,
+           1.3543972076479622,
+           1.4132522294591696,
+           1.4617809934508048,
+           1.4991741311905258,
+           1.5248697947082943,
+           1.538574749915758,
+           1.5402788618435421,
+           1.5302625248312791,
+           1.5090967663929977,
+           1.4776359367679424,
+           1.4370030825878073,
+           1.3885682879911572,
+           1.333920445267555,
+           1.274833085233468,
+           1.2132250508000155,
+           1.151116931719866,
+           1.0905842908852266,
+           1.0337087999212808,
+           0.9825284619251603,
+           0.9389881304563319,
+           0.9048915354192121,
+           0.8818559981563034,
+           0.8712709604929201,
+           0.874261366970452,
+           0.891656828095477,
+           0.9239673577824573,
+           0.9713663235232151,
+           1.0336810769215314,
+           1.110391549238631,
+           1.200636905963301,
+           1.303230160803276,
+           1.4166804576278058,
+           1.5392225434754594,
+           1.6688527813242218,
+           1.8033708921886333,
+           1.9404264761750247,
+           2.0775692448407588,
+           2.2123018054624635,
+           2.342133773895485,
+           2.464635958195083,
+           2.5774933509427145,
+           2.6785556944106657,
+           2.765884438691473,
+           2.8377949973728285,
+           2.8928933162122674,
+           2.9301059048715996,
+           2.948702636838889,
+           2.9483117944255897,
+           2.928927019999495,
+           2.890906026916367,
+           2.834961119265222,
+           2.7621417637851,
+           2.6738096454226046,
+           2.571606815410603,
+           2.4574177031560054,
+           2.33332590669624,
+           2.2015667975557602,
+           2.0644770715939433,
+           1.9244424455966807,
+           1.7838447383175453,
+           1.6450095835324094,
+           1.5101560012834538,
+           1.381349002449987,
+           1.2604563224140901,
+           1.1491102739054397,
+           1.0486755797697234,
+           0.9602238966452068,
+           0.8845155740846958,
+           0.8219890146611815,
+           0.7727578134825578,
+           0.7366156649410939,
+           0.7130488351416558,
+           0.7012558149521932,
+           0.7001735955090155,
+           0.7085098495286838,
+           0.7247801617970774,
+           0.7473493341262915,
+           0.7744756967428367,
+           0.8043572917264732,
+           0.835178756313607,
+           0.8651577254549407,
+           0.8925895940844705,
+           0.915889529491626,
+           0.9336307016487829,
+           0.9445778023078922,
+           0.9477150494855188,
+           0.9422680193844665,
+           0.9277188091467939,
+           0.9038142070024844,
+           0.8705667269862686,
+           0.8282485488809078,
+           0.7773785857826774,
+           0.718703077099781,
+           0.6531702694787911,
+           0.5818998979753064,
+           0.5061483109896426,
+           0.42727019179535747,
+           0.34667791417112215,
+           0.2657996276003702,
+           0.18603719729778387,
+           0.1087251252367831,
+           0.03509155039457847,
+           -0.03377762966505342,
+           -0.09697055654392003,
+           -0.15377627614447673,
+           -0.20370594846043721,
+           -0.24650782708654834,
+           -0.28217559611742055,
+           -0.310949825401965,
+           -0.33331248471184644,
+           -0.34997463871384193,
+           -0.3618576231053569,
+           -0.37006817334726294,
+           -0.3758681367590813,
+           -0.38063954227084906,
+           -0.38584592619018515,
+           -0.39299091376435186,
+           -0.4035751324838727,
+           -0.4190525820064504,
+           -0.4407876059796471,
+           -0.47001360232510164,
+           -0.5077945708635098,
+           -0.5549905313832009,
+           -0.6122277529674488,
+           -0.679874618845808,
+           -0.7580238130845163,
+           -0.8464813594835582,
+           -0.9447628729640583,
+           -1.0520972037318894,
+           -1.1674374690705485,
+           -1.2894792813739104,
+           -1.4166857986320218,
+           -1.5473190496009162,
+           -1.6794768246907315,
+           -1.8111342792571599,
+           -1.9401892721315281,
+           -2.064510362025175,
+           -2.181986310464297,
+           -2.290575894077394,
+           -2.3883568125993233,
+           -2.4735724923797573,
+           -2.544675628255762,
+           -2.6003673783997616,
+           -2.6396312255060956,
+           -2.661760641080921,
+           -2.66637983468689,
+           -2.653457033260328,
+           -2.6233099131039443,
+           -2.576602994543301,
+           -2.5143370019502784,
+           -2.4378303851720426,
+           -2.3486933876268776,
+           -2.2487952268001004,
+           -2.1402251201637688,
+           -2.0252480395402555,
+           -1.9062562059381238,
+           -1.7857174417276922,
+           -1.6661215750989775,
+           -1.5499261411177645,
+           -1.4395026431289613,
+           -1.3370846272458845,
+           -1.2447187814505736,
+           -1.1642202003948932,
+           -1.0971328590323102,
+           -1.0446962150973944,
+           -1.007818715172331,
+           -0.9870588151674508,
+           -0.9826139474835922,
+           -0.994317678261868,
+           -1.0216451035575402,
+           -1.063726337732816,
+           -1.119367755603752,
+           -1.1870804665588743,
+           -1.2651153284417744,
+           -1.3515036555866442,
+           -1.4441026427245958,
+           -1.5406444177371694,
+           -1.638787554029276,
+           -1.7361698195806048,
+           -1.8304609157642784,
+           -1.9194139653156663,
+           -2.000914545168174,
+           -2.073026125287383,
+           -2.1340308674556736,
+           -2.1824648558422877,
+           -2.2171469711819967,
+           -2.237200778983901,
+           -2.2420689754543566,
+           -2.2315201184436635,
+           -2.20564756016929,
+           -2.1648606890480218,
+           -2.1098687749871075,
+           -2.0416578913402548,
+           -1.9614615530400927,
+           -1.8707258601068704,
+           -1.77107006515708,
+           -1.66424358955892,
+           -1.5520805929554093,
+           -1.4364532531020602,
+           -1.3192249361410406,
+           -1.2022044310804803,
+           -1.0871023866237597,
+           -0.9754910245848467,
+           -0.8687681136215267,
+           -0.7681260722661466,
+           -0.6745269341817283,
+           -0.588683754694171,
+           -0.5110488698612243,
+           -0.44180924188877957,
+           -0.3808889420813118,
+           -0.32795863932449965,
+           -0.2824517829580534,
+           -0.24358699831108865,
+           -0.21039605542475967,
+           -0.18175663053256647,
+           -0.15642895923593628,
+           -0.13309538301462745,
+           -0.11040171917148188,
+           -0.08699934030184976,
+           -0.061586833978489436,
+           -0.03295012691068006,
+           -3.3010474504090713e-16
+          ],
+          [
+           0,
+           0.04020692124942794,
+           0.08666375704975421,
+           0.1397831450220601,
+           0.19974094199542425,
+           0.26646833442391477,
+           0.33965082409109,
+           0.41873413540934956,
+           0.5029369097126293,
+           0.5912698742469442,
+           0.6825610035975626,
+           0.77548603337592,
+           0.8686035441455209,
+           0.96039371141476,
+           1.0492997181946069,
+           1.1337707526683678,
+           1.2123054668720759,
+           1.283494754176175,
+           1.3460627143152102,
+           1.3989047145259585,
+           1.4411215230945384,
+           1.4720485856456709,
+           1.4912796325361648,
+           1.498683944837583,
+           1.4944167631735787,
+           1.4789224942301444,
+           1.4529305498439196,
+           1.4174438387093662,
+           1.3737201163087356,
+           1.323246580017178,
+           1.2677082689218644,
+           1.2089509873793558,
+           1.148939613697256,
+           1.089712776958847,
+           1.0333349828149367,
+           0.9818473405326975,
+           0.9372180868525423,
+           0.9012941160923699,
+           0.8757547100115491,
+           0.8620686154995024,
+           0.8614555442132195,
+           0.8748530675884183,
+           0.9028897555902139,
+           0.945865261157674,
+           1.0037378880724406,
+           1.0761200019312132,
+           1.1622814563603723,
+           1.2611610141550726,
+           1.3713855503610282,
+           1.4912966361635935,
+           1.6189839234215133,
+           1.7523245841798984,
+           1.889027911590808,
+           2.0266840620056135,
+           2.1628158157093766,
+           2.294932158377957,
+           2.420582438729577,
+           2.537409841187209,
+           2.6432029261053773,
+           2.735944033939842,
+           2.8138534226087417,
+           2.8754281074547805,
+           2.919474498246795,
+           2.945134074522761,
+           2.951901505707391,
+           2.939634801820807,
+           2.90855726986721,
+           2.8592512455489816,
+           2.792643765060094,
+           2.7099845326287904,
+           2.612816721564728,
+           2.5029413154002853,
+           2.382375847208409,
+           2.2533085256662586,
+           2.1180488427708393,
+           1.9789758377490443,
+           1.8384852427488667,
+           1.6989367571616605,
+           1.5626026884514628,
+           1.4316191584427718,
+           1.3079410061644507,
+           1.193301423295125,
+           1.0891772384004352,
+           0.996760624496867,
+           0.9169378445526889,
+           0.8502754753198244,
+           0.7970143657003226,
+           0.7570713962448619,
+           0.7300489160385949,
+           0.7152515468408038,
+           0.7117098664902419,
+           0.7182103186274451,
+           0.7333305477499873,
+           0.7554792311096046,
+           0.782939375067538,
+           0.8139139657401019,
+           0.8465728139306883,
+           0.8790994135989931,
+           0.9097366418801014,
+           0.9368301666166603,
+           0.9588684934632082,
+           0.9745186771198137,
+           0.9826568377560888,
+           0.9823927612053892,
+           0.9730880165341428,
+           0.9543671931833149,
+           0.9261220377678576,
+           0.8885084533106362,
+           0.8419365065729204,
+           0.787053767620695,
+           0.7247224753491202,
+           0.6559911791216073,
+           0.5820616460459646,
+           0.5042519422233441,
+           0.42395669160209426,
+           0.3426055854785517,
+           0.2616212574944602,
+           0.18237765216567267,
+           0.10615999924032456,
+           0.03412746195580565,
+           -0.03272054431114817,
+           -0.09357346359345342,
+           -0.14783336179596016,
+           -0.19513270088628226,
+           -0.2353456421506715,
+           -0.2685925648198393,
+           -0.2952376634981472,
+           -0.315879668624391,
+           -0.33133591406576174,
+           -0.3426201503312947,
+           -0.35091466635594104,
+           -0.35753743316627773,
+           -0.36390511516043317,
+           -0.37149290583289385,
+           -0.3817922316967309,
+           -0.3962674286543893,
+           -0.416312527557326,
+           -0.44320928929098524,
+           -0.4780876042656051,
+           -0.5218893172557587,
+           -0.5753364573987481,
+           -0.6389047468052244,
+           -0.7128031322618597,
+           -0.7969599360949721,
+           -0.8910160580876453,
+           -0.9943254844758018,
+           -1.105963176866144,
+           -1.2247402279881499,
+           -1.349225987160299,
+           -1.4777766808254995,
+           -1.6085698869505387,
+           -1.7396440706821201,
+           -1.8689422562347675,
+           -1.9943587999147692,
+           -2.113788144274881,
+           -2.225174375840988,
+           -2.3265603801769403,
+           -2.4161353890642365,
+           -2.4922797453444314,
+           -2.5536057708400675,
+           -2.5989937103504315,
+           -2.62762183793776,
+           -2.6389899478665937,
+           -2.632935608350145,
+           -2.6096427279181165,
+           -2.569642167576771,
+           -2.5138043225144355,
+           -2.443323790258329,
+           -2.359696433184307,
+           -2.264689327438581,
+           -2.1603042631279132,
+           -2.0487356178250287,
+           -1.9323235631472042,
+           -1.8135036790014316,
+           -1.69475413920936,
+           -1.5785416934164667,
+           -1.4672677019245781,
+           -1.3632154815548476,
+           -1.2685001917839613,
+           -1.1850224318737506,
+           -1.114426632937769,
+           -1.058065215951623,
+           -1.0169693503541157,
+           -0.9918269914137751,
+           -0.9829687017527476,
+           -0.9903615775301373,
+           -1.013611407286896,
+           -1.0519729960278337,
+           -1.1043683935157533,
+           -1.1694125786842728,
+           -1.2454459760823764,
+           -1.330573019614256,
+           -1.4227058374215125,
+           -1.5196120129862147,
+           -1.6189652842687174,
+           -1.7183979771613414,
+           -1.815553933282733,
+           -1.9081406859834407,
+           -1.9939796624654502,
+           -2.0710532434811793,
+           -2.1375475937904143,
+           -2.191890284347116,
+           -2.2327818583544596,
+           -2.2592206445885035,
+           -2.2705202889831417,
+           -2.266319655230455,
+           -2.246584932629582,
+           -2.2116039799804548,
+           -2.1619731232670643,
+           -2.098576807558683,
+           -2.02256067549269,
+           -1.935298801680587,
+           -1.8383559505706253,
+           -1.7334458413513445,
+           -1.6223864945914759,
+           -1.5070537993095392,
+           -1.3893344745556295,
+           -1.2710796055862974,
+           -1.1540599112721752,
+           -1.0399238471805003,
+           -0.9301595692180477,
+           -0.8260616778813787,
+           -0.7287035357421474,
+           -0.6389158040561775,
+           -0.5572716820611665,
+           -0.4840791587376005,
+           -0.4193804059464429,
+           -0.3629582584910833,
+           -0.3143495453993142,
+           -0.27286486214237676,
+           -0.23761420998661248,
+           -0.20753778030849435,
+           -0.1814410322095529,
+           -0.15803310437818138,
+           -0.135967519535819,
+           -0.11388408402462663,
+           -0.09045085751478434,
+           -0.06440506909359334,
+           -0.03459188608033514,
+           -3.4728682187385857e-16
+          ],
+          [
+           0,
+           0.04230549340875981,
+           0.09106944644289246,
+           0.14658358033815255,
+           0.2088984333357929,
+           0.2778192854455064,
+           0.35290898997709175,
+           0.4334976547251509,
+           0.5186989364696087,
+           0.6074325390629414,
+           0.6984523422194363,
+           0.7903794393543758,
+           0.8817392322345433,
+           0.971001621134308,
+           1.0566232444439445,
+           1.1370906634400717,
+           1.2109633577293561,
+           1.2769153955399928,
+           1.3337746706608138,
+           1.3805586537875074,
+           1.4165056889890997,
+           1.4411009739354952,
+           1.4540964927783107,
+           1.4555243199375902,
+           1.445702877816473,
+           1.4252359075513172,
+           1.3950040949214617,
+           1.3561494789234316,
+           1.3100529536226528,
+           1.2583053501419315,
+           1.2026727506014228,
+           1.145056835332174,
+           1.0874511949630192,
+           1.03189464671677,
+           0.9804226766878701,
+           0.9350181848740091,
+           0.8975627358393661,
+           0.8697895143515327,
+           0.8532391521461902,
+           0.8492195298555724,
+           0.858770568530128,
+           0.8826349102114363,
+           0.9212352494346063,
+           0.974658920670376,
+           1.042650174364416,
+           1.124610390586887,
+           1.2196062888486625,
+           1.3263860000270775,
+           1.4434026762908498,
+           1.5688451320822978,
+           1.7006748380970202,
+           1.8366684350070612,
+           1.9744647982283652,
+           2.111615572682184,
+           2.245638010025182,
+           2.3740688823750804,
+           2.4945182176024945,
+           2.6047216025390516,
+           2.7025898319695223,
+           2.786254742293504,
+           2.8541101577990573,
+           2.9048469924377818,
+           2.9374816880447057,
+           2.9513773277571533,
+           2.9462569371203253,
+           2.9222086707996215,
+           2.879682775441023,
+           2.819480414345868,
+           2.7427346325105066,
+           2.650883926536491,
+           2.545639058427674,
+           2.428943911123931,
+           2.302931322932338,
+           2.1698749544409517,
+           2.032138332239006,
+           1.892122276652046,
+           1.7522119542503383,
+           1.614724799342653,
+           1.4818605220043848,
+           1.355654364126937,
+           1.237934680953181,
+           1.1302858157050748,
+           1.0340171019686948,
+           0.950138675796841,
+           0.879344610817122,
+           0.8220037091779,
+           0.7781580933904358,
+           0.7475295536701775,
+           0.7295334169359515,
+           0.7232995218263498,
+           0.7276997133969186,
+           0.7413811157444538,
+           0.7628043044532407,
+           0.7902853867793436,
+           0.8220409086279483,
+           0.8562344457514681,
+           0.8910237036381101,
+           0.9246069469920266,
+           0.9552676055157395,
+           0.9814159571506745,
+           1.0016268715596055,
+           1.0146727033181415,
+           1.019550553274694,
+           1.0155032645416737,
+           1.002033682830297,
+           0.9789118851985381,
+           0.9461752623389105,
+           0.90412152272266,
+           0.8532948676275768,
+           0.7944657597662161,
+           0.7286048705414444,
+           0.656851937821166,
+           0.5804803938712817,
+           0.5008587285284831,
+           0.41940963320949237,
+           0.33756802494767696,
+           0.2567390750076611,
+           0.17825736315072388,
+           0.1033482464321335,
+           0.0330924713521606,
+           -0.03160502819744849,
+           -0.09004131524069324,
+           -0.14173591611369363,
+           -0.18644501851538486,
+           -0.22416901464759484,
+           -0.2551531767298564,
+           -0.27988143159323525,
+           -0.29906338149179373,
+           -0.3136148951396954,
+           -0.324632761793193,
+           -0.33336405765730986,
+           -0.3411710140219969,
+           -0.34949229674497717,
+           -0.35980170391963834,
+           -0.37356536029217036,
+           -0.3921985313579273,
+           -0.4170231958929345,
+           -0.449227502499339,
+           -0.4898281938278737,
+           -0.5396370124731371,
+           -0.5992320068039324,
+           -0.6689345355335581,
+           -0.7487926295951868,
+           -0.8385712123337752,
+           -0.9377495080664812,
+           -1.0455257889509386,
+           -1.1608294253247045,
+           -1.2823400198557933,
+           -1.4085132256014476,
+           -1.5376126769326215,
+           -1.6677473045525661,
+           -1.7969131655002544,
+           -1.9230387996421827,
+           -2.044033028762858,
+           -2.1578340454211924,
+           -2.262458598049148,
+           -2.3560500674376224,
+           -2.43692424816135,
+           -2.503611696284429,
+           -2.554895580774788,
+           -2.589844078652183,
+           -2.6078364805520793,
+           -2.6085823210598473,
+           -2.5921330132828793,
+           -2.558885645672155,
+           -2.509578786729765,
+           -2.445280335363208,
+           -2.367367646570505,
+           -2.2775003491579464,
+           -2.1775864497145165,
+           -2.0697424807281792,
+           -1.9562485965002974,
+           -1.8394996447980585,
+           -1.7219533419083781,
+           -1.606076751446327,
+           -1.494292311112395,
+           -1.388924665479408,
+           -1.2921495464457309,
+           -1.2059458965868486,
+           -1.1320523553739563,
+           -1.071929125917752,
+           -1.0267261130106968,
+           -0.9972580748585607,
+           -0.9839873646149073,
+           -0.9870146577016083,
+           -1.0060778712953364,
+           -1.0405592878955952,
+           -1.0895007002938932,
+           -1.1516262052669837,
+           -1.225372092535821,
+           -1.3089231083533777,
+           -1.4002542235606619,
+           -1.4971769076962804,
+           -1.5973888068524298,
+           -1.6985256459303117,
+           -1.7982141275907886,
+           -1.8941245816459717,
+           -1.984022130286872,
+           -2.0658151760411037,
+           -2.1376000896211487,
+           -2.1977010720712804,
+           -2.244704287403157,
+           -2.277485505180618,
+           -2.2952306537047296,
+           -2.297448859557987,
+           -2.2839777339535714,
+           -2.254980856036852,
+           -2.210937593322468,
+           -2.1526255851437854,
+           -2.0810963917819247,
+           -1.9976449754986723,
+           -1.9037738260281116,
+           -1.8011526686275,
+           -1.6915747945137718,
+           -1.5769111289798263,
+           -1.459063199913267,
+           -1.3399161877487995,
+           -1.221293226718074,
+           -1.1049120869960358,
+           -0.9923452990822059,
+           -0.8849846872938244,
+           -0.7840111610311578,
+           -0.6903704735342171,
+           -0.6047555017280051,
+           -0.5275954314135882,
+           -0.4590520537921698,
+           -0.39902319660966723,
+           -0.34715313068463544,
+           -0.3028496148237824,
+           -0.26530707360074285,
+           -0.23353524740070142,
+           -0.20639251639687264,
+           -0.18262298316546757,
+           -0.1608963053773582,
+           -0.13984920274252918,
+           -0.11812752278625827,
+           -0.09442773906511263,
+           -0.06753677332660053,
+           -0.036369079392309635,
+           -3.655086388617741e-16
+          ],
+          [
+           0,
+           0.04446966826029928,
+           0.09554951172872507,
+           0.153407999915542,
+           0.21797011492200005,
+           0.28891711065481307,
+           0.36569315060572544,
+           0.44751866456318345,
+           0.5334100886276568,
+           0.6222054852903498,
+           0.7125953853693313,
+           0.8031580552242308,
+           0.8923982744225929,
+           0.9787886139362373,
+           1.0608121354532687,
+           1.1370053903079602,
+           1.20600058297657,
+           1.2665657794662804,
+           1.3176420849142256,
+           1.3583767862720368,
+           1.3881515533424382,
+           1.4066049122708641,
+           1.413648346896998,
+           1.4094755416400866,
+           1.3945644508975403,
+           1.3696720600139027,
+           1.335821887233835,
+           1.2942844600787728,
+           1.2465511786711683,
+           1.1943021481747649,
+           1.1393687184518058,
+           1.083691607318113,
+           1.0292756008954143,
+           0.978141917526501,
+           0.9322793881362686,
+           0.8935956440483295,
+           0.8638695120594375,
+           0.8447057957145674,
+           0.8374935716316746,
+           0.8433690515388926,
+           0.8631839562495016,
+           0.8974802196054126,
+           0.9464716915554933,
+           1.0100333436050657,
+           1.087698300910382,
+           1.1786628376593342,
+           1.2817992806619036,
+           1.395676574964275,
+           1.5185880794866733,
+           1.6485859847308628,
+           1.7835215828385698,
+           1.9210904766936616,
+           2.0588816928948637,
+           2.194429566299312,
+           2.325267193863837,
+           2.448980214440885,
+           2.5632596600617137,
+           2.665952643371068,
+           2.755109694832691,
+           2.829027640940955,
+           2.88628701908481,
+           2.925783153393101,
+           2.9467501657268587,
+           2.948777363337381,
+           2.931817625512472,
+           2.896187601391269,
+           2.842559725423828,
+           2.7719462509602915,
+           2.685675691459885,
+           2.5853622382206383,
+           2.4728688889922723,
+           2.3502651693372396,
+           2.219780454581831,
+           2.0837540016132614,
+           1.9445828741989684,
+           1.8046689911621563,
+           1.6663665425836314,
+           1.531931004885677,
+           1.4034709416020217,
+           1.2829037039903783,
+           1.1719160462427218,
+           1.0719305463898225,
+           0.9840785791685952,
+           0.909180424727236,
+           0.847732921112281,
+           0.7999048833684215,
+           0.765540322357515,
+           0.7441693067444363,
+           0.7350261266685484,
+           0.7370742419588707,
+           0.7490373356575553,
+           0.7694356490443337,
+           0.7966266508160759,
+           0.8288489935539645,
+           0.8642686374873806,
+           0.9010259765601745,
+           0.9372827859415334,
+           0.9712678236940594,
+           1.00131996187824,
+           1.0259277927767978,
+           1.0437647523165066,
+           1.0537189226570065,
+           1.0549168162345923,
+           1.0467406007186801,
+           1.0288383943721522,
+           1.0011274399024979,
+           0.9637901475421342,
+           0.9172631802037953,
+           0.8622199305428817,
+           0.7995469071820765,
+           0.7303147010201054,
+           0.65574433861409,
+           0.5771699446981734,
+           0.4959987271171232,
+           0.4136693625520328,
+           0.3316098987950104,
+           0.2511962980885305,
+           0.1737127260010843,
+           0.10031464200731371,
+           0.03199567263203903,
+           -0.030440852363279248,
+           -0.0864049431620833,
+           -0.135536957120285,
+           -0.17771811274658386,
+           -0.21307422291836928,
+           -0.24197253702954738,
+           -0.26501176191965115,
+           -0.28300550995298296,
+           -0.29695959496877294,
+           -0.3080437586276631,
+           -0.31755855681894063,
+           -0.32689826451557724,
+           -0.33751076447962264,
+           -0.3508554677818014,
+           -0.3683603700711989,
+           -0.39137937544578666,
+           -0.4211510188674042,
+           -0.45875968829504044,
+           -0.5051003897620322,
+           -0.5608480138894776,
+           -0.6264319528777177,
+           -0.7020167855422568,
+           -0.7874895977088753,
+           -0.8824543399813795,
+           -0.9862334486542197,
+           -1.0978767727541194,
+           -1.2161776654251217,
+           -1.3396959157446715,
+           -1.4667870221440253,
+           -1.5956371453023526,
+           -1.7243029308107174,
+           -1.8507552637950415,
+           -1.9729259123074345,
+           -2.0887559363438823,
+           -2.1962446869002403,
+           -2.29349819593378,
+           -2.3787757641381346,
+           -2.4505335890144426,
+           -2.507464340049742,
+           -2.5485316793983013,
+           -2.572998843128844,
+           -2.5804505370509525,
+           -2.570807559011528,
+           -2.544333732526332,
+           -2.50163492047175,
+           -2.4436500778205144,
+           -2.371634494408531,
+           -2.2871355677635425,
+           -2.191961627469459,
+           -2.088144501922878,
+           -1.9778966714883799,
+           -1.8635639851997554,
+           -1.7475750279922513,
+           -1.6323883092631224,
+           -1.5204384992560205,
+           -1.4140829659472833,
+           -1.3155498611021545,
+           -1.2268889700259769,
+           -1.149926476060963,
+           -1.0862246995906963,
+           -1.0370477544146262,
+           -1.003333924671653,
+           -0.985675406414275,
+           -0.9843058833260341,
+           -0.9990962201790642,
+           -1.0295583649660698,
+           -1.0748573558969554,
+           -1.1338311373597354,
+           -1.2050177041765053,
+           -1.286688920524945,
+           -1.3768902029387566,
+           -1.4734851196471692,
+           -1.5742038444755448,
+           -1.6766943153491995,
+           -1.778574887226831,
+           -1.8774872384567807,
+           -1.971148288794547,
+           -2.057399916601557,
+           -2.1342553212830153,
+           -2.1999409633202736,
+           -2.252933126134688,
+           -2.2919882786842196,
+           -2.3161665717848754,
+           -2.324847970838356,
+           -2.317740708730755,
+           -2.2948819306673798,
+           -2.2566305929876296,
+           -2.2036528658763066,
+           -2.1369004707381074,
+           -2.0575825523980753,
+           -1.9671318400929885,
+           -1.8671659856823997,
+           -1.7594450793755942,
+           -1.6458264298515877,
+           -1.5282177548854083,
+           -1.4085299591103746,
+           -1.2886306766842903,
+           -1.1702997284591905,
+           -1.0551875865805393,
+           -0.9447778557707858,
+           -0.8403546720600391,
+           -0.7429757892047789,
+           -0.6534519738168142,
+           -0.5723331661032004,
+           -0.499901688250367,
+           -0.43617260129089674,
+           -0.38090112833588385,
+           -0.3335968819431458,
+           -0.29354446064498135,
+           -0.2598298186098045,
+           -0.23137166709081705,
+           -0.20695704035172166,
+           -0.18528005529345257,
+           -0.16498281560643258,
+           -0.1446973598767797,
+           -0.1230875299377515,
+           -0.09888964142321814,
+           -0.07095087276669082,
+           -0.03826435089587624,
+           -3.84594372545278e-16
+          ],
+          [
+           0,
+           0.04667876589314573,
+           0.10006145944322882,
+           0.16019207944161132,
+           0.22687094293059656,
+           0.29965826447584076,
+           0.37788452660743443,
+           0.4606673811016934,
+           0.5469346495098829,
+           0.6354528309285897,
+           0.7248603795312806,
+           0.8137048875502418,
+           0.9004832044544978,
+           0.9836834427061848,
+           1.0618277667729674,
+           1.1335148364366217,
+           1.1974607785728233,
+           1.2525375934667375,
+           1.2978079616327198,
+           1.332555503578802,
+           1.356309655882599,
+           1.3688644595923203,
+           1.3702907080524729,
+           1.3609410670278967,
+           1.3414479563359127,
+           1.312714164695949,
+           1.2758963536068355,
+           1.2323817871524,
+           1.1837587981694635,
+           1.1317816628210575,
+           1.0783307012217522,
+           1.025368547671106,
+           0.9748936370577619,
+           0.9288920314555232,
+           0.8892887608284263,
+           0.8578998727593893,
+           0.8363863775964283,
+           0.8262112374824945,
+           0.8286004812408304,
+           0.8445094335773506,
+           0.874594928758431,
+           0.9191942386676197,
+           0.9783112863285491,
+           1.051610542459614,
+           1.1384188186256128,
+           1.2377349805662576,
+           1.3482474139612812,
+           1.4683588869276982,
+           1.5962182735541335,
+           1.7297584351877753,
+           1.8667394051323571,
+           2.004795891620585,
+           2.141488006629321,
+           2.274354046975365,
+           2.400964101189386,
+           2.5189732322520326,
+           2.62617299300233,
+           2.720540067769475,
+           2.800280899673854,
+           2.863871256515666,
+           2.9100898069673353,
+           2.9380449200351726,
+           2.947194061031593,
+           2.937355332710261,
+           2.908710896500193,
+           2.8618022014022597,
+           2.79751714239901,
+           2.717069461452868,
+           2.62197088768161,
+           2.5139966846473736,
+           2.3951454277205615,
+           2.2675939694289635,
+           2.1336486623169257,
+           1.9956939944338172,
+           1.8561398501022708,
+           1.7173686367288232,
+           1.5816835164822192,
+           1.4512589497830706,
+           1.3280946965637832,
+           1.2139743327231434,
+           1.110429225343527,
+           1.0187087739064433,
+           0.9397575693276607,
+           0.8741999519935477,
+           0.8223322683395092,
+           0.7841229373568479,
+           0.7592202483841369,
+           0.7469676243090101,
+           0.7464259044720992,
+           0.7564020335309707,
+           0.77548339041101,
+           0.802076858943114,
+           0.8344516320720219,
+           0.8707846572499058,
+           0.90920757380621,
+           0.9478539650209574,
+           0.9849057489222766,
+           1.0186375623466877,
+           1.0474580516843461,
+           1.069947069418356,
+           1.0848878858320707,
+           1.0912936572675436,
+           1.0884275427036314,
+           1.0758160253632232,
+           1.0532551713806935,
+           1.0208097388364707,
+           0.9788052331294174,
+           0.927813184117205,
+           0.8686300922062705,
+           0.8022506503137069,
+           0.7298359923589961,
+           0.652677843087287,
+           0.5721595454880579,
+           0.48971501833778064,
+           0.406786745582758,
+           0.32478392019169905,
+           0.24504185726217595,
+           0.16878375479974425,
+           0.0970858166598673,
+           0.030846662300372432,
+           -0.029238165463116295,
+           -0.08269591767971918,
+           -0.12929005592124168,
+           -0.16902700776183804,
+           -0.20215607465834054,
+           -0.22916248484415247,
+           -0.2507537631800268,
+           -0.2678397649784207,
+           -0.281506887186628,
+           -0.29298712374651725,
+           -0.30362276853810466,
+           -0.31482768557408575,
+           -0.3280461590655923,
+           -0.3447104032327208,
+           -0.36619785153748896,
+           -0.39378935631165385,
+           -0.42862941219224115,
+           -0.4716894707440797,
+           -0.5237353402373522,
+           -0.5852995655450071,
+           -0.6566595609610169,
+           -0.7378221264328726,
+           -0.8285148187774085,
+           -0.9281844778592684,
+           -1.0360030277310777,
+           -1.1508804888587052,
+           -1.2714849543848135,
+           -1.3962691055125374,
+           -1.5235026729903443,
+           -1.651310097585093,
+           -1.7777125062414147,
+           -1.9006730058004928,
+           -2.0181442056268923,
+           -2.1281168166047797,
+           -2.228668138396386,
+           -2.3180092405854804,
+           -2.394529666613553,
+           -2.4568385417780285,
+           -2.5038010468019394,
+           -2.534569324709808,
+           -2.54860701841557,
+           -2.545706786419579,
+           -2.5260003106890605,
+           -2.4899604901057075,
+           -2.4383957004318693,
+           -2.372436192986905,
+           -2.2935128944526104,
+           -2.203329054772987,
+           -2.103825364441651,
+           -1.99713932228814,
+           -1.8855597762384586,
+           -1.771477678942083,
+           -1.657334194665592,
+           -1.5455673611004255,
+           -1.4385585480327234,
+           -1.3385799631981037,
+           -1.247744433850049,
+           -1.1679586411002179,
+           -1.100880904166235,
+           -1.0478845052060086,
+           -1.010027414999766,
+           -0.9880291285197811,
+           -0.9822551510732647,
+           -0.9927094943054632,
+           -1.0190353513168606,
+           -1.0605239261011743,
+           -1.1161311991676042,
+           -1.184502223271052,
+           -1.2640023652036008,
+           -1.352754745918645,
+           -1.4486829858324215,
+           -1.5495582384938709,
+           -1.6530493969130926,
+           -1.7567752850633074,
+           -1.8583576041257912,
+           -1.955473389927725,
+           -2.045905754992533,
+           -2.1275917352068325,
+           -2.198666136105983,
+           -2.2575003752950753,
+           -2.302735443009226,
+           -2.3333082491464703,
+           -2.3484707886418423,
+           -2.3478017337390966,
+           -2.331210247188074,
+           -2.298932000073619,
+           -2.2515175671951004,
+           -2.1898135570136414,
+           -2.1149370076530536,
+           -2.0282437410135556,
+           -1.9312915098207715,
+           -1.8257988939216463,
+           -1.7136009994230978,
+           -1.5966030850243982,
+           -1.4767332824585642,
+           -1.3558955913728148,
+           -1.2359243130109807,
+           -1.1185410422083837,
+           -1.0053152646870989,
+           -0.897629508346655,
+           -0.7966498757190394,
+           -0.7033026431088443,
+           -0.6182574537744782,
+           -0.5419174618355316,
+           -0.47441660472826214,
+           -0.41562399948684386,
+           -0.36515527649545504,
+           -0.3223904881982699,
+           -0.28649806398769306,
+           -0.25646413027724496,
+           -0.231126380406957,
+           -0.20921156587439954,
+           -0.18937559124529968,
+           -0.17024513217856987,
+           -0.15045966084470186,
+           -0.12871275646728345,
+           -0.10379160089803383,
+           -0.07461360944652057,
+           -0.04025922431950303,
+           -4.0436001113043336e-16
+          ],
+          [
+           0,
+           0.04891168557590492,
+           0.1045624988360905,
+           0.16687187232641923,
+           0.23551746516145944,
+           0.3099425137287049,
+           0.3893698280138339,
+           0.4728220752424618,
+           0.5591478274522979,
+           0.647052697747807,
+           0.7351347552146543,
+           0.8219232942228044,
+           0.9059199430503728,
+           0.98564103175254,
+           1.0596601016715763,
+           1.1266494299362821,
+           1.185419462017571,
+           1.2349550934542635,
+           1.2744478170893907,
+           1.3033228527277645,
+           1.3212604995661343,
+           1.328211095005564,
+           1.3244031229766426,
+           1.3103441867224597,
+           1.286814740806705,
+           1.2548546604506583,
+           1.215742908561643,
+           1.1709707374225564,
+           1.1222090285244921,
+           1.0712705262416022,
+           1.0200678551159936,
+           0.9705683230311559,
+           0.9247466006251002,
+           0.8845364286508586,
+           0.8517825380132569,
+           0.8281939709789848,
+           0.8152999663780682,
+           0.8144095170258354,
+           0.8265756253503996,
+           0.8525651752547242,
+           0.8928352071588245,
+           0.9475162321187273,
+           1.0164030535670763,
+           1.0989533856388947,
+           1.19429436961812,
+           1.3012368993519763,
+           1.4182974772053913,
+           1.5437271389152105,
+           1.6755468130610287,
+           1.811588323050785,
+           1.9495401004219781,
+           2.086996561325237,
+           2.221510006189893,
+           2.350643838060689,
+           2.4720258595643996,
+           2.5834004028265976,
+           2.682678071093439,
+           2.7679819247640935,
+           2.837689026725763,
+           2.8904663703318927,
+           2.9253003454566597,
+           2.941519050597486,
+           2.9388069282812146,
+           2.917211382947997,
+           2.8771412306185815,
+           2.81935702337333,
+           2.7449534842751806,
+           2.6553344751725576,
+           2.552181096283708,
+           2.4374136783086233,
+           2.3131485711153146,
+           2.1816507543383157,
+           2.0452833915840576,
+           1.9064555190493573,
+           1.7675690995843005,
+           1.6309666836377432,
+           1.4988808989131304,
+           1.3733869414709132,
+           1.2563591637018081,
+           1.149432751011532,
+           1.0539713517962368,
+           0.9710413775169686,
+           0.9013935250707146,
+           0.8454518962800659,
+           0.8033109035661425,
+           0.7747399613103692,
+           0.759195773714773,
+           0.7558418467719877,
+           0.7635746787434645,
+           0.7810559245504378,
+           0.806749688578911,
+           0.8389639810037638,
+           0.8758952777247491,
+           0.915675055645194,
+           0.9564171349137361,
+           0.9962646487876906,
+           1.0334354801351529,
+           1.0662650507154583,
+           1.0932454239936056,
+           1.1130597824032162,
+           1.1246114630918531,
+           1.1270468791138095,
+           1.1197718121435594,
+           1.1024607340363255,
+           1.0750589936353674,
+           1.0377778876055277,
+           0.9910828151736821,
+           0.9356748919329674,
+           0.8724665629281733,
+           0.8025519059563857,
+           0.7271724486287725,
+           0.6476794339450035,
+           0.5654935561719183,
+           0.48206324954427304,
+           0.3988226452327833,
+           0.31715031636879926,
+           0.23832990661110148,
+           0.16351368544396255,
+           0.09368999446658369,
+           0.029655445401039204,
+           -0.028007394943962077,
+           -0.07894624176391607,
+           -0.12304881975021621,
+           -0.16044581970335903,
+           -0.19150700007456828,
+           -0.21683052854474644,
+           -0.23722583571492617,
+           -0.25369042311628576,
+           -0.267381226726054,
+           -0.27958128095288215,
+           -0.2916625529667186,
+           -0.3050459201014539,
+           -0.3211593412140211,
+           -0.3413953243209248,
+           -0.36706881620220194,
+           -0.39937663431827,
+           -0.43935952740284806,
+           -0.48786788927125535,
+           -0.5455320622148441,
+           -0.6127380540001494,
+           -0.6896093587273452,
+           -0.7759954199409377,
+           -0.8714671081999982,
+           -0.9753194089460732,
+           -1.0865813343574033,
+           -1.2040328895053767,
+           -1.326228743130618,
+           -1.4515280812539475,
+           -1.5781299619676998,
+           -1.7041133461543305,
+           -1.8274808551952608,
+           -1.9462052061178703,
+           -2.05827719966983,
+           -2.1617540894624487,
+           -2.2548071418607374,
+           -2.3357672072755475,
+           -2.4031671637602905,
+           -2.4557801624326907,
+           -2.4926526996270724,
+           -2.513131660563954,
+           -2.516884620819166,
+           -2.50391285156151,
+           -2.4745566485263146,
+           -2.429492788760767,
+           -2.3697241088173198,
+           -2.2965613886395766,
+           -2.21159791220412,
+           -2.1166772544606736,
+           -2.0138550098563788,
+           -1.9053553266496623,
+           -1.7935232396340672,
+           -1.6807738986200533,
+           -1.5695398684583328,
+           -1.462217726568332,
+           -1.3611152045898411,
+           -1.26840011135489,
+           -1.1860522350697529,
+           -1.1158193543249848,
+           -1.059178391946606,
+           -1.0173026250666002,
+           -0.9910357220430239,
+           -0.9808732154592197,
+           -0.9869518442956202,
+           -1.009047011775664,
+           -1.0465784128751345,
+           -1.0986236917322312,
+           -1.1639397989138165,
+           -1.2409915363056898,
+           -1.327986607725356,
+           -1.4229163403200855,
+           -1.5236011091166466,
+           -1.6277393879376536,
+           -1.7329592669176976,
+           -1.8368712220235472,
+           -1.9371208965965845,
+           -2.0314406595595234,
+           -2.117698739394042,
+           -2.193944796399937,
+           -2.25845088648071,
+           -2.3097468854851977,
+           -2.346649581081481,
+           -2.3682847958171167,
+           -2.374102076544864,
+           -2.3638816675230387,
+           -2.3377336727391285,
+           -2.2960895027175194,
+           -2.2396858875928616,
+           -2.169541916984579,
+           -2.0869297338209223,
+           -1.993339659667997,
+           -1.890440659664612,
+           -1.7800371626918328,
+           -1.6640233343365305,
+           -1.5443359546021083,
+           -1.422907077923352,
+           -1.3016176493202594,
+           -1.1822532176712837,
+           -1.0664628260152056,
+           -0.9557220711193537,
+           -0.8513012125535746,
+           -0.754239078058284,
+           -0.6653233604945935,
+           -0.5850777359594312,
+           -0.5137560569307772,
+           -0.4513436930106951,
+           -0.3975659095203527,
+           -0.35190299545176423,
+           -0.3136116815779505,
+           -0.2817522311396902,
+           -0.25522044341956523,
+           -0.23278368822505713,
+           -0.21311998987169617,
+           -0.19485910514622445,
+           -0.1766244927606634,
+           -0.15707505311931685,
+           -0.13494552723792122,
+           -0.1090844820809549,
+           -0.07848887540873649,
+           -0.04233428475072494,
+           -4.246151540548198e-16
+          ],
+          [
+           0,
+           0.051147110603530214,
+           0.10900995530434819,
+           0.17338442462110493,
+           0.2438286196383173,
+           0.31967389187905704,
+           0.4000423266789293,
+           0.48387021736562436,
+           0.5699369200433345,
+           0.6568983367355296,
+           0.7433241516731977,
+           0.8277378447707455,
+           0.9086584303931988,
+           0.9846428203487781,
+           1.0543276889311015,
+           1.1164697253712694,
+           1.1699831951081128,
+           1.2139737949939085,
+           1.2477678773753806,
+           1.2709362317197426,
+           1.2833117472829438,
+           1.2850004328977394,
+           1.276385436497007,
+           1.258123883330087,
+           1.2311365335703486,
+           1.1965904426001757,
+           1.155874986113939,
+           1.110571782802971,
+           1.062419205477453,
+           1.0132723130405334,
+           0.9650591571655448,
+           0.9197345157369345,
+           0.879232177570541,
+           0.8454169477352443,
+           0.8200375587456438,
+           0.8046816594885783,
+           0.8007340112174959,
+           0.8093389492534505,
+           0.8313680718266497,
+           0.8673939960948146,
+           0.917670878705894,
+           0.982122237786803,
+           1.060336438838999,
+           1.1515700229598653,
+           1.2547588665872298,
+           1.368536972220222,
+           1.49126250396237,
+           1.6210505048275194,
+           1.755811568905963,
+           1.893295594751495,
+           2.0311396203514818,
+           2.1669186379075485,
+           2.298198210928848,
+           2.4225876687223327,
+           2.5377926354615323,
+           2.6416656631111572,
+           2.73225377932727,
+           2.8078418320611718,
+           2.866990610281933,
+           2.9085688426460563,
+           2.931778320123938,
+           2.936171551047944,
+           2.9216615338337206,
+           2.8885234194503058,
+           2.8373880280352344,
+           2.7692273771925566,
+           2.685332568779661,
+           2.5872845617835893,
+           2.476918526818805,
+           2.35628262877242,
+           2.2275922145230918,
+           2.0931804893156234,
+           1.9554468457192717,
+           1.8168040612132335,
+           1.6796256031030703,
+           1.5461942721728181,
+           1.4186533794526037,
+           1.2989615846909766,
+           1.1888524322306004,
+           1.0897995023233782,
+           1.0029879564192024,
+           0.9292930970858482,
+           0.8692663908759455,
+           0.8231292199095637,
+           0.7907744396894103,
+           0.771775631343985,
+           0.7654037507528079,
+           0.7706506994004722,
+           0.7862591766752937,
+           0.8107580246996459,
+           0.8425021482615874,
+           0.8797159871154846,
+           0.9205394383554202,
+           0.9630750746196985,
+           1.0054354807486978,
+           1.0457895376664714,
+           1.0824065174356496,
+           1.1136969166716475,
+           1.138249045127907,
+           1.1548604999575403,
+           1.1625637910040318,
+           1.1606455350390017,
+           1.1486588032796392,
+           1.1264283825753751,
+           1.0940488919146527,
+           1.0518758778086124,
+           1.000510190092866,
+           0.9407761092914368,
+           0.8736938536668276,
+           0.8004472345189053,
+           0.7223473486959976,
+           0.6407932946555254,
+           0.5572309703519605,
+           0.4731110559725406,
+           0.3898473010066822,
+           0.3087762229562956,
+           0.2311192845247441,
+           0.15794854842649445,
+           0.09015671578656725,
+           0.028432337837479855,
+           -0.026759145759969558,
+           -0.07518804167289478,
+           -0.11686637621170848,
+           -0.15204704701007118,
+           -0.1812161713129223,
+           -0.20507882713857595,
+           -0.22453855666693714,
+           -0.24067116495809165,
+           -0.25469349736006847,
+           -0.2679280118953827,
+           -0.28176407513143015,
+           -0.29761699866729274,
+           -0.31688589612803214,
+           -0.3409114758154024,
+           -0.37093489097940985,
+           -0.4080587478216259,
+           -0.45321132131229636,
+           -0.5071149519021473,
+           -0.5702594941189325,
+           -0.6428815633740261,
+           -0.724950183152389,
+           -0.8161592747015219,
+           -0.9159272593577239,
+           -1.0234038640447698,
+           -1.1374840377427946,
+           -1.2568287054344789,
+           -1.3798919107447327,
+           -1.5049537336120922,
+           -1.630158219028413,
+           -1.7535554209653006,
+           -1.8731465554303965,
+           -1.986931170986825,
+           -2.0929551862443327,
+           -2.189358613346889,
+           -2.274421785195432,
+           -2.346608932187283,
+           -2.404608011030682,
+           -2.4473657723928866,
+           -2.474117163771349,
+           -2.484408296411588,
+           -2.4781123571353634,
+           -2.4554380138989145,
+           -2.416930043682974,
+           -2.363462098532494,
+           -2.296221715631495,
+           -2.216687865554164,
+           -2.1266015146508015,
+           -2.027929848430167,
+           -1.922824958572306,
+           -1.8135779329990265,
+           -1.7025694028523237,
+           -1.592217689441375,
+           -1.4849257559859617,
+           -1.3830282017514195,
+           -1.2887395390894676,
+           -1.2041049668532733,
+           -1.130954797263388,
+           -1.07086360890055,
+           -1.025115088118903,
+           -0.9946733874712664,
+           -0.98016167595414,
+           -0.9818483857427035,
+           -0.999641477726914,
+           -1.0330908580097282,
+           -1.0813988842098319,
+           -1.1434387086236741,
+           -1.2177800197067383,
+           -1.3027215684402762,
+           -1.396329706202624,
+           -1.4964820196406596,
+           -1.6009150291506755,
+           -1.7072748237965534,
+           -1.8131694390655764,
+           -1.916221746366704,
+           -2.0141216154794424,
+           -2.1046761333991935,
+           -2.1858567145983954,
+           -2.255842017315079,
+           -2.313055686088189,
+           -2.3561980697436717,
+           -2.3842712131885424,
+           -2.396596586993011,
+           -2.3928251967361414,
+           -2.372939900064331,
+           -2.3372499487823544,
+           -2.2863779614067514,
+           -2.2212397138449966,
+           -2.143017307759239,
+           -2.053126433533287,
+           -1.9531785837569065,
+           -1.8449391904050707,
+           -1.7302827515999024,
+           -1.6111460797911312,
+           -1.4894808408369853,
+           -1.3672065619758373,
+           -1.2461652659387281,
+           -1.1280788390799483,
+           -1.0145101647216563,
+           -0.906828950920576,
+           -0.8061830571963279,
+           -0.7134759805961941,
+           -0.6293510014747414,
+           -0.5541823175883872,
+           -0.4880733158814594,
+           -0.43086194918389803,
+           -0.3821330045293687,
+           -0.3412368754628045,
+           -0.30731428690302826,
+           -0.2793262719515575,
+           -0.2560885692120045,
+           -0.23630949995872172,
+           -0.2186302995744743,
+           -0.20166681915709184,
+           -0.18405148250039716,
+           -0.16447438151067134,
+           -0.14172241953326875,
+           -0.11471546632343503,
+           -0.08253856908962527,
+           -0.04446936909140461,
+           -4.451648696675842e-16
+          ],
+          [
+           0,
+           0.05336371464901065,
+           0.11336168139497572,
+           0.17966837819980874,
+           0.2517265070623794,
+           0.3287616080761262,
+           0.4098028603954423,
+           0.4937095274390859,
+           0.5792023550476828,
+           0.6648991002543836,
+           0.7493532581662634,
+           0.8310949680082719,
+           0.9086730188756039,
+           0.9806968427472473,
+           1.0458773777151618,
+           1.1030657083485014,
+           1.1512884420905622,
+           1.1897788593226077,
+           1.2180029782938169,
+           1.2356798019539903,
+           1.2427951587154469,
+           1.2396087097068687,
+           1.2266538671622471,
+           1.2047305479132546,
+           1.1748908680340617,
+           1.1384180649566753,
+           1.0967991073009065,
+           1.0516916158638412,
+           1.0048858675654113,
+           0.9582627838873415,
+           0.9137489131662797,
+           0.8732694992413955,
+           0.8387007852537194,
+           0.8118227293542148,
+           0.7942733079063614,
+           0.7875055513960861,
+           0.7927483993410487,
+           0.8109723743869265,
+           0.8428609645318585,
+           0.8887884687007054,
+           0.9488049079298779,
+           1.0226284359358366,
+           1.10964550293251,
+           1.2089188396322885,
+           1.319203138991138,
+           1.4389681260902365,
+           1.5664285261871012,
+           1.699580271862936,
+           1.8362421365142938,
+           1.974101846988074,
+           2.1107656162747266,
+           2.2438099506397533,
+           2.3708345265557615,
+           2.4895149027882475,
+           2.59765383277253,
+           2.6932299720483357,
+           2.7744428343141183,
+           2.839752936229837,
+           2.8879161833577895,
+           2.918011684878448,
+           2.9294623396788912,
+           2.9220477073287547,
+           2.8959088601828222,
+           2.851545102941365,
+           2.78980263883845,
+           2.7118554525268532,
+           2.6191788640461007,
+           2.513516381519472,
+           2.3968406382207084,
+           2.2713093385515744,
+           2.139217253916088,
+           2.002945400657859,
+           1.8649085959553535,
+           1.727502622332594,
+           1.59305223643736,
+           1.4637612328934335,
+           1.3416657200075117,
+           1.2285916822792164,
+           1.1261177970795686,
+           1.0355443422120054,
+           0.9578688805977614,
+           0.8937692417605314,
+           0.8435941412416018,
+           0.8073615929592879,
+           0.7847650804179599,
+           0.7751872652189655,
+           0.7777208301250809,
+           0.7911958834151994,
+           0.8142131955969873,
+           0.8451824025073589,
+           0.8823641937402772,
+           0.9239154149652922,
+           0.9679359491874391,
+           1.0125162068289404,
+           1.055784048459138,
+           1.095949987111584,
+           1.1313495687321593,
+           1.160481908020298,
+           1.182043460706159,
+           1.1949562394815747,
+           1.1983898261511374,
+           1.191776693401503,
+           1.1748205218334313,
+           1.1474973772173136,
+           1.1100497948075274,
+           1.0629739974166141,
+           1.0070006473000626,
+           0.9430696944000023,
+           0.8723000310855171,
+           0.7959547925325338,
+           0.715403249103733,
+           0.6320803198663539,
+           0.5474447926880217,
+           0.46293736481047515,
+           0.37993961775194995,
+           0.2997350118818538,
+           0.22347292981293013,
+           0.1521367153282126,
+           0.08651654802396003,
+           0.027187865931417275,
+           -0.02550409765745932,
+           -0.07145325737455609,
+           -0.1107948639470705,
+           -0.14390087907970678,
+           -0.17136865701532325,
+           -0.1940032279564168,
+           -0.21279364626502129,
+           -0.2288840223515801,
+           -0.2435399974456015,
+           -0.2581115414377334,
+           -0.27399305260339557,
+           -0.2925818117325788,
+           -0.315235890094315,
+           -0.34323262952624134,
+           -0.3777288032326257,
+           -0.4197235277895678,
+           -0.47002493129902617,
+           -0.5292214912011631,
+           -0.597658840197196,
+           -0.6754227028993652,
+           -0.7623284725841526,
+           -0.8579177705957097,
+           -0.9614621546921395,
+           -1.0719739613561503,
+           -1.1882240853458323,
+           -1.3087663221044714,
+           -1.4319677295514148,
+           -1.5560443095048744,
+           -1.6791011694982658,
+           -1.7991762065886128,
+           -1.9142862589653866,
+           -2.0224746012210417,
+           -2.1218586168731197,
+           -2.210676468279759,
+           -2.2873315998998045,
+           -2.3504339556229485,
+           -2.398836863622457,
+           -2.431668641154833,
+           -2.448358094585048,
+           -2.4486532336929816,
+           -2.4326326805328513,
+           -2.4007094278498284,
+           -2.3536267860417355,
+           -2.2924465463862536,
+           -2.218529577106904,
+           -2.1335092531839472,
+           -2.0392582960908263,
+           -1.9378497615311692,
+           -1.8315130577640963,
+           -1.7225860006573313,
+           -1.6134640111287786,
+           -1.5065476336442452,
+           -1.4041895990964028,
+           -1.3086426705554328,
+           -1.2220094956371312,
+           -1.146195644892328,
+           -1.08286694272328,
+           -1.0334120976193686,
+           -0.998911514375747,
+           -0.9801130254140323,
+           -0.9774151148895623,
+           -0.9908580319106168,
+           -1.020123002218941,
+           -1.0645395556317359,
+           -1.1231007940917728,
+           -1.1944862369924947,
+           -1.277091701112002,
+           -1.3690655063590023,
+           -1.468350149635559,
+           -1.5727284610624344,
+           -1.679873152687122,
+           -1.7873985921090267,
+           -1.8929135840658025,
+           -1.9940739230923654,
+           -2.088633490327341,
+           -2.174492707106048,
+           -2.2497432261242833,
+           -2.312707835963085,
+           -2.361974674255317,
+           -2.3964249857750075,
+           -2.4152538207435765,
+           -2.417983241738116,
+           -2.4044677904825313,
+           -2.3748921539954977,
+           -2.3297611584311637,
+           -2.269882403843143,
+           -2.1963420295004137,
+           -2.110474262975376,
+           -2.013825553024257,
+           -1.9081142127269677,
+           -1.79518660239586,
+           -1.6769709589360045,
+           -1.555430027822884,
+           -1.4325136745280798,
+           -1.310112643655635,
+           -1.1900145965645779,
+           -1.0738634928769493,
+           -0.963123289725153,
+           -0.8590468172454202,
+           -0.7626505526290988,
+           -0.6746958614663174,
+           -0.5956771080499679,
+           -0.5258168599708344,
+           -0.4650682311696212,
+           -0.41312422617214895,
+           -0.3694337710713968,
+           -0.3332239483698251,
+           -0.30352779726672546,
+           -0.2792169022464725,
+           -0.25903787434473746,
+           -0.24165173417825275,
+           -0.22567513607050207,
+           -0.20972233009728206,
+           -0.1924467446323514,
+           -0.17258108630307029,
+           -0.14897489675885248,
+           -0.12062857519358583,
+           -0.08672297034970157,
+           -0.046643763335028815,
+           -4.658115920407988e-16
+          ],
+          [
+           0,
+           0.05554036752282504,
+           0.11757646121444242,
+           0.18566455611949234,
+           0.2591371293561601,
+           0.33712090188348803,
+           0.4185607587094168,
+           0.5022489200915217,
+           0.5868585977952995,
+           0.6709812514714695,
+           0.7531664637332651,
+           0.8319633810309844,
+           0.9059626227804086,
+           0.9738375445761347,
+           1.0343837531783697,
+           1.0865558110540516,
+           1.1295001356213967,
+           1.1625831913450306,
+           1.185414189163992,
+           1.19786164452453,
+           1.2000632991327072,
+           1.1924290786035177,
+           1.1756369342901818,
+           1.1506215983214503,
+           1.1185564617234938,
+           1.0808289619117624,
+           1.0390100333643748,
+           0.9948183297021078,
+           0.950080062789449,
+           0.9066854213414319,
+           0.8665426248813355,
+           0.831530736333455,
+           0.8034523962820499,
+           0.7839876528966935,
+           0.7746500433433067,
+           0.7767460355209463,
+           0.7913388642545153,
+           0.8192176953915654,
+           0.8608729270038725,
+           0.9164782920774569,
+           0.985880265200304,
+           1.0685951007668828,
+           1.163813646387136,
+           1.270413887016896,
+           1.3869809874343324,
+           1.511834417693981,
+           1.6430615726037372,
+           1.7785571363761246,
+           1.9160673013579592,
+           2.053237828669496,
+           2.187664841697753,
+           2.316947173110106,
+           2.4387390441562973,
+           2.5508018425850656,
+           2.6510537828722716,
+           2.7376162792633134,
+           2.8088559372760966,
+           2.863421170997084,
+           2.900272579285569,
+           2.9187063608418184,
+           2.918370212436308,
+           2.8992713324537327,
+           2.8617763389570396,
+           2.8066031031783973,
+           2.734804691035563,
+           2.647745792293864,
+           2.5470721948007267,
+           2.434674025492896,
+           2.312643626629824,
+           2.1832290613853744,
+           2.048784344495622,
+           1.9117175686687886,
+           1.7744381441208017,
+           1.6393043858099765,
+           1.5085726703325057,
+           1.384349342363718,
+           1.2685464800674535,
+           1.162842531820599,
+           1.0686487153367359,
+           0.987081927834955,
+           0.9189447558180076,
+           0.864712999253874,
+           0.8245309417843065,
+           0.798214410522529,
+           0.7852614806724867,
+           0.7848704962236298,
+           0.7959649028515545,
+           0.8172242271619553,
+           0.8471203914962201,
+           0.8839584291848425,
+           0.9259205643865805,
+           0.9711125458942822,
+           1.0176110772815683,
+           1.0635111675761837,
+           1.1069722376273758,
+           1.1462618571141039,
+           1.179796054631848,
+           1.2061752367272287,
+           1.2242148687088792,
+           1.232970207558868,
+           1.2317545318047514,
+           1.2201504808755235,
+           1.1980142930238333,
+           1.1654729119070997,
+           1.12291411283591,
+           1.0709699759840985,
+           1.0104942011018077,
+           0.9425339123046664,
+           0.8682967384925142,
+           0.7891140714763475,
+           0.7064014970779349,
+           0.621617462017898,
+           0.5362212796768553,
+           0.4516315898397335,
+           0.3691863710653856,
+           0.290105559828358,
+           0.21545725922773268,
+           0.14612842369389192,
+           0.08280078722070794,
+           0.0259326642459671,
+           -0.024252902076018237,
+           -0.06777333589075975,
+           -0.10488493487196919,
+           -0.13607453021791974,
+           -0.1620446204853347,
+           -0.1836923702423174,
+           -0.20208302549049453,
+           -0.21841844473978173,
+           -0.23400157377695238,
+           -0.2501978002574373,
+           -0.26839420850333984,
+           -0.28995781314254476,
+           -0.3161938809601026,
+           -0.34830545273114527,
+           -0.3873551507541101,
+           -0.43423030390949086,
+           -0.4896123416391494,
+           -0.5539513032499457,
+           -0.6274461819888574,
+           -0.7100316775663906,
+           -0.8013717698501428,
+           -0.9008603543276946,
+           -1.0076290009513464,
+           -1.1205617166112647,
+           -1.2383164122909236,
+           -1.3593526034470658,
+           -1.4819647106759493,
+           -1.6043201813614005,
+           -1.724501525463865,
+           -1.8405512531554642,
+           -1.9505186213443606,
+           -2.052507042359839,
+           -2.144720982620631,
+           -2.2255111827141416,
+           -2.293417062984087,
+           -2.347205239746718,
+           -2.3859031652139406,
+           -2.40882701700624,
+           -2.41560309807998,
+           -2.406182161708016,
+           -2.3808462451015475,
+           -2.3402077752236488,
+           -2.2852008969194944,
+           -2.2170651621005755,
+           -2.1373219047368894,
+           -2.0477438052537935,
+           -1.9503183151881787,
+           -1.8472057645001931,
+           -1.7406931060081716,
+           -1.633144360736228,
+           -1.5269489118105484,
+           -1.4244688508084764,
+           -1.3279866077253601,
+           -1.2396540932588906,
+           -1.1614445499311041,
+           -1.095108247412524,
+           -1.042133068732681,
+           -1.0037109199832706,
+           -0.9807107593954951,
+           -0.9736588856093086,
+           -0.9827269533325868,
+           -1.0077280015785746,
+           -1.0481205897162176,
+           -1.1030209442870222,
+           -1.1712228296084404,
+           -1.2512246722138178,
+           -1.3412632976184176,
+           -1.4393534819151288,
+           -1.54333238407442,
+           -1.650907810857586,
+           -1.759709177699947,
+           -1.8673399679076579,
+           -1.9714304604861672,
+           -2.069689494619206,
+           -2.159954066252477,
+           -2.240235608685886,
+           -2.308761893111472,
+           -2.3640135945456278,
+           -2.404754700866721,
+           -2.430056094399639,
+           -2.4393118029334793,
+           -2.432247596081963,
+           -2.4089217890863805,
+           -2.369718304937488,
+           -2.315332232420522,
+           -2.2467482977905386,
+           -2.165212836860348,
+           -2.0722000082082266,
+           -1.9693731232476288,
+           -1.8585420817814715,
+           -1.7416179896782737,
+           -1.6205660963677115,
+           -1.4973582225401618,
+           -1.3739258520378062,
+           -1.2521150364532951,
+           -1.133644207137785,
+           -1.0200659085970705,
+           -0.912733361720148,
+           -0.8127726376502459,
+           -0.7210610766279409,
+           -0.63821242452527,
+           -0.5645689871345693,
+           -0.5002009229268951,
+           -0.4449126134620679,
+           -0.3982558714702837,
+           -0.3595495743201102,
+           -0.32790514944556476,
+           -0.30225719234459697,
+           -0.28139837061411604,
+           -0.2640176623062399,
+           -0.2487408962746117,
+           -0.23417250810600915,
+           -0.21893739900955778,
+           -0.20172178727088294,
+           -0.1813119724631833,
+           -0.15662999072034314,
+           -0.12676522350647845,
+           -0.09100113029621104,
+           -0.04883640464639483,
+           -4.863570375660231e-16
+          ],
+          [
+           0,
+           0.057656338254072945,
+           0.12161440416111013,
+           0.19131652427044252,
+           0.2659910869032338,
+           0.3446738351893168,
+           0.42623468126911246,
+           0.5094093353681423,
+           0.5928349162209046,
+           0.6750886033244863,
+           0.7547283094509517,
+           0.8303342958506006,
+           0.9005506240904607,
+           0.964125338257283,
+           1.0199482993643527,
+           1.0670856495763288,
+           1.1048099659490238,
+           1.1326252697510402,
+           1.1502861854576354,
+           1.1578106900020142,
+           1.155486054184438,
+           1.1438677502457026,
+           1.123771278201398,
+           1.0962570441289856,
+           1.0626086016642595,
+           1.0243047390145434,
+           0.9829860535166716,
+           0.9404168001162346,
+           0.898442925453918,
+           0.8589473023156787,
+           0.8238032573841585,
+           0.794827536482326,
+           0.7737338744558556,
+           0.7620883308289743,
+           0.7612675174390632,
+           0.7724207811769098,
+           0.7964373152018249,
+           0.833919057699041,
+           0.8851601011497267,
+           0.9501331804865875,
+           1.0284836391709282,
+           1.119531092283572,
+           1.222278819576667,
+           1.335430733653008,
+           1.4574155836405622,
+           1.586417877464311,
+           1.7204148404605046,
+           1.857218578718737,
+           1.9945224858784287,
+           2.129950825371377,
+           2.2611103389568457,
+           2.385642678879901,
+           2.501276436461551,
+           2.6058775450543257,
+           2.6974968699959083,
+           2.7744138616673513,
+           2.8351752385051765,
+           2.8786277826527384,
+           2.9039444690728176,
+           2.9106433060393124,
+           2.8985984371735856,
+           2.8680432384098484,
+           2.8195653330132164,
+           2.754093639422051,
+           2.6728777555839622,
+           2.5774601650107076,
+           2.4696419195791917,
+           2.35144260803114,
+           2.2250555534392586,
+           2.092799294361507,
+           1.9570664903074413,
+           1.8202714504284043,
+           1.6847975136326414,
+           1.5529455079426553,
+           1.4268844869111394,
+           1.3086058820723034,
+           1.1998821242148099,
+           1.102230674875068,
+           1.0168842756360676,
+           0.9447680698936309,
+           0.8864840834997783,
+           0.8423033712628466,
+           0.8121659500947275,
+           0.7956884512242043,
+           0.7921792379638544,
+           0.8006605565796036,
+           0.8198971202384774,
+           0.8484303738841605,
+           0.8846175549045763,
+           0.9266745538237243,
+           0.9727214936246246,
+           1.020829887721388,
+           1.0690702064016746,
+           1.1155586804070212,
+           1.1585021981363095,
+           1.196240208958555,
+           1.2272826278187918,
+           1.2503428435690986,
+           1.2643650625051608,
+           1.2685453661498474,
+           1.2623460246593112,
+           1.2455027802336456,
+           1.2180249942366688,
+           1.1801887328621656,
+           1.1325230445862717,
+           1.0757898538536939,
+           1.0109580551843556,
+           0.9391725361767763,
+           0.8617189831392711,
+           0.7799854261969648,
+           0.6954215591590395,
+           0.6094969212667707,
+           0.5236590519293373,
+           0.43929272514283235,
+           0.357681337643864,
+           0.27997146484761853,
+           0.2071415128232104,
+           0.13997528517559465,
+           0.07904115353413599,
+           0.024677372714985744,
+           -0.02301607971290595,
+           -0.06417893066701472,
+           -0.09918527300184399,
+           -0.12863160555817107,
+           -0.15331856946968622,
+           -0.17422686354736386,
+           -0.1924879744172611,
+           -0.2093504937492333,
+           -0.22614291190170213,
+           -0.24423387163423926,
+           -0.2649909347878671,
+           -0.28973895721479315,
+           -0.3197191816421283,
+           -0.35605014416876635,
+           -0.39969144802567114,
+           -0.45141138908922424,
+           -0.5117593231189682,
+           -0.5810435471294365,
+           -0.6593153296179048,
+           -0.74635956998298,
+           -0.8416924002350661,
+           -0.9445658662006301,
+           -1.05397964526358,
+           -1.1686995777912816,
+           -1.2872826142828062,
+           -1.4081076143669744,
+           -1.5294112812596423,
+           -1.6493283800299428,
+           -1.7659352734684448,
+           -1.8772957184302212,
+           -1.9815078005955165,
+           -2.0767508483583783,
+           -2.1613311580436187,
+           -2.233725383174864,
+           -2.2926204896617284,
+           -2.3369492554189875,
+           -2.3659203952678505,
+           -2.379042517548893,
+           -2.3761412646672664,
+           -2.357369152254323,
+           -2.323207796806954,
+           -2.2744624052743365,
+           -2.212248587602194,
+           -2.137971740110635,
+           -2.0532994291753375,
+           -1.9601273765253795,
+           -1.8605398053193491,
+           -1.7567650461065774,
+           -1.6511274203475235,
+           -1.5459965134040463,
+           -1.4437350164549545,
+           -1.346646355939112,
+           -1.2569233388639862,
+           -1.176599022351572,
+           -1.1075009665635438,
+           -1.051209952808545,
+           -1.009024145034303,
+           -0.9819295455363907,
+           -0.9705774476514669,
+           -0.9752694230301457,
+           -0.9959502028104369,
+           -1.0322086249654423,
+           -1.0832866288242384,
+           -1.1480960869119337,
+           -1.2252430784637778,
+           -1.313059032754105,
+           -1.4096380080250084,
+           -1.5128792272414633,
+           -1.62053386864302,
+           -1.7302550100866343,
+           -1.8396495538642879,
+           -1.9463309147624666,
+           -2.0479712396395713,
+           -2.142351942043025,
+           -2.2274113799513215,
+           -2.3012885774708054,
+           -2.3623619904160083,
+           -2.4092824386860605,
+           -2.440999472164579,
+           -2.4567805979569552,
+           -2.4562229711590837,
+           -2.4392573347268502,
+           -2.406144181874417,
+           -2.3574623021576984,
+           -2.2940900553955275,
+           -2.2171798913685574,
+           -2.128126793574675,
+           -2.0285314683096902,
+           -1.920159222519729,
+           -1.8048955722952715,
+           -1.6846996961970153,
+           -1.5615568921232448,
+           -1.4374312121405568,
+           -1.3142194363145274,
+           -1.1937075045252383,
+           -1.0775304556757082,
+           -0.967136828421649,
+           -0.8637583590238589,
+           -0.7683856731791441,
+           -0.6817505132464587,
+           -0.6043148740838927,
+           -0.5362672439917997,
+           -0.47752596646196055,
+           -0.4277495581002593,
+           -0.3863536427367326,
+           -0.3525339957455939,
+           -0.32529504010871474,
+           -0.3034830005642244,
+           -0.28582280764186824,
+           -0.27095775233022495,
+           -0.2574908267859052,
+           -0.2440266484709676,
+           -0.22921285529358276,
+           -0.21177987792037112,
+           -0.1905780419048478,
+           -0.16461102541268374,
+           -0.13306479622958875,
+           -0.09533127189854734,
+           -0.05102608617906895,
+           -5.06604121830255e-16
+          ],
+          [
+           0,
+           0.05969149344005948,
+           0.12543732401688276,
+           0.19657112369006496,
+           0.2722242275352023,
+           0.35135001345376393,
+           0.4327533604716156,
+           0.5151244470938614,
+           0.5970759962335493,
+           0.6771829810721101,
+           0.7540237392011386,
+           0.82622140226728,
+           0.892484536147871,
+           0.9516459027755495,
+           1.0026982987444903,
+           1.0448264967053689,
+           1.0774344115496404,
+           1.1001667321212656,
+           1.1129243977254863,
+           1.115873453577633,
+           1.1094469866821952,
+           1.09434001926572,
+           1.0714974164032913,
+           1.0420950433686613,
+           1.0075145820006,
+           0.9693125796302319,
+           0.929184454702432,
+           0.8889243163280114,
+           0.8503815672304669,
+           0.8154153480232286,
+           0.7858479431787444,
+           0.7634183037818223,
+           0.749736848235005,
+           0.7462426792533566,
+           0.754164304218191,
+           0.7744848674305443,
+           0.8079127988717086,
+           0.8548586572310524,
+           0.9154187982656087,
+           0.9893663365752726,
+           1.0761496935868275,
+           1.1748988412275476,
+           1.2844391639303847,
+           1.4033126758400618,
+           1.5298061499573667,
+           1.6619855459131414,
+           1.7977359673077875,
+           1.9348062419472625,
+           2.070857102272122,
+           2.2035118517069727,
+           2.330408337851521,
+           2.4492510170335597,
+           2.557861887697139,
+           2.6542290926321166,
+           2.7365520416673195,
+           2.803281985935035,
+           2.8531570802728417,
+           2.885231099223468,
+           2.8988951213119956,
+           2.893891662209519,
+           2.870320916008821,
+           2.8286389508038043,
+           2.7696478955371107,
+           2.694478345022043,
+           2.6045643945376784,
+           2.5016118899554787,
+           2.387560639740428,
+           2.2645414774868513,
+           2.1348291844483063,
+           2.00079237788149,
+           1.8648415406233927,
+           1.729376408494972,
+           1.5967339439052664,
+           1.4691381061708488,
+           1.3486525820464328,
+           1.237137564977222,
+           1.136211570510465,
+           1.0472191506576987,
+           0.971205224871419,
+           0.9088965832778217,
+           0.8606909428897569,
+           0.826653754017995,
+           0.8065227665168653,
+           0.7997201784455398,
+           0.8053720077812621,
+           0.8223341554331168,
+           0.8492244691778789,
+           0.8844599771284376,
+           0.9262983393632414,
+           0.9728824702784011,
+           1.0222872143620976,
+           1.072566916070191,
+           1.1218027112466866,
+           1.168148383312461,
+           1.2098736717503602,
+           1.24540399204884,
+           1.2733556233579935,
+           1.292565540162482,
+           1.3021152042211452,
+           1.3013477893116352,
+           1.2898784799993819,
+           1.2675976624732743,
+           1.2346670060116467,
+           1.1915086133341881,
+           1.1387875924619828,
+           1.0773885673940025,
+           1.0083867958104036,
+           0.9330146953791835,
+           0.8526246927679797,
+           0.7686493983690172,
+           0.6825601728516594,
+           0.5958251874329747,
+           0.5098680873597797,
+           0.42602834739185624,
+           0.3455243596427546,
+           0.2694202192451053,
+           0.19859707389925632,
+           0.13372978198906885,
+           0.07526948370979214,
+           0.023432534125098006,
+           -0.02180391978854186,
+           -0.06069961000046831,
+           -0.09374213469789008,
+           -0.12163150528886427,
+           -0.1452586650095696,
+           -0.16567854903325585,
+           -0.18407839945454163,
+           -0.20174217380114115,
+           -0.22001198961259316,
+           -0.24024762746647696,
+           -0.2637851685755469,
+           -0.29189586932855,
+           -0.3257463731988504,
+           -0.36636133030326873,
+           -0.4145894372731943,
+           -0.47107382640790535,
+           -0.5362276253804175,
+           -0.6102153797299565,
+           -0.6929408832134304,
+           -0.7840417994724578,
+           -0.8828912864430747,
+           -0.9886066568013574,
+           -1.1000649279694352,
+           -1.2159249383225768,
+           -1.3346555366950916,
+           -1.454569194362212,
+           -1.5738602463768492,
+           -1.6906468460813064,
+           -1.8030156159405133,
+           -1.9090679021475951,
+           -2.0069664917110597,
+           -2.0949816302542152,
+           -2.1715351871492166,
+           -2.2352418517611077,
+           -2.284946309666575,
+           -2.319755439216843,
+           -2.33906468455397,
+           -2.342577898378046,
+           -2.330320103075143,
+           -2.3026427884709184,
+           -2.260221544328704,
+           -2.204046011357785,
+           -2.1354023213797353,
+           -2.055848380820106,
+           -1.9671825273255328,
+           -1.8714062527144895,
+           -1.7706818326076992,
+           -1.6672858303015217,
+           -1.563559546576128,
+           -1.4618575655662813,
+           -1.3644955975894468,
+           -1.2736988416246506,
+           -1.1915520823765404,
+           -1.1199526996777,
+           -1.0605677022375035,
+           -1.0147958049961856,
+           -0.9837354518125492,
+           -0.9681595457356743,
+           -0.9684974910581515,
+           -0.9848249785510934,
+           -1.0168617619331162,
+           -1.063977484180531,
+           -1.125205421348548,
+           -1.199263823785291,
+           -1.2845843545475075,
+           -1.3793469568447854,
+           -1.481520330527999,
+           -1.5889070656803799,
+           -1.69919237246139,
+           -1.8099952631242409,
+           -1.9189209865765988,
+           -2.0236134893017614,
+           -2.121806679511847,
+           -2.211373303949761,
+           -2.290370307952575,
+           -2.3570796376948904,
+           -2.4100435567430973,
+           -2.4480936843584056,
+           -2.470373117038924,
+           -2.4763511637828355,
+           -2.465830405321322,
+           -2.4389459736869976,
+           -2.3961571363796446,
+           -2.338231454458628,
+           -2.266221961601724,
+           -2.1814379771841477,
+           -2.0854103167077818,
+           -1.9798517938033826,
+           -1.8666140163785705,
+           -1.7476415626961728,
+           -1.6249246792712944,
+           -1.5004516701781536,
+           -1.3761621460693538,
+           -1.2539022710630814,
+           -1.135383087492231,
+           -1.0221429138725893,
+           -0.9155147025275613,
+           -0.8165991128937855,
+           -0.7262439079446514,
+           -0.6450301181696051,
+           -0.5732652442493684,
+           -0.5109835903324643,
+           -0.45795363914557347,
+           -0.4136922025855361,
+           -0.37748491138377277,
+           -0.34841244914699776,
+           -0.3253817935012101,
+           -0.3071616037386059,
+           -0.29242079334033616,
+           -0.2797692495089421,
+           -0.26779961225440657,
+           -0.25512900382722287,
+           -0.2404396058703633,
+           -0.2225170163469852,
+           -0.20028538016397365,
+           -0.17283837484229883,
+           -0.1394652433319729,
+           -0.09967119729581529,
+           -0.053191662542791986,
+           -5.263588573108698e-16
+          ],
+          [
+           0,
+           0.061626488865483546,
+           0.12900909959647042,
+           0.20137896823098325,
+           0.2777782408348025,
+           0.35708722920300767,
+           0.43805624118266534,
+           0.5193412420563507,
+           0.599542401663977,
+           0.6772445043174334,
+           0.7510581470721016,
+           0.8196606278977454,
+           0.8818354293840999,
+           0.9365092357619158,
+           0.9827854804501724,
+           1.019973506599078,
+           1.0476125320791512,
+           1.0654897403625379,
+           1.0736519665150492,
+           1.0724106093757673,
+           1.0623395728953804,
+           1.0442662172255617,
+           1.0192554790393482,
+           0.9885874962159356,
+           0.9537292400144304,
+           0.9163008139444716,
+           0.8780372187611873,
+           0.8407465037999204,
+           0.8062653231325367,
+           0.7764129882376637,
+           0.7529451551169527,
+           0.7375083018119768,
+           0.7315961415350307,
+           0.7365090772905016,
+           0.7533177368117497,
+           0.7828315334428182,
+           0.8255730814789718,
+           0.8817591562680464,
+           0.9512887334184223,
+           1.0337384715590479,
+           1.1283658234057867,
+           1.2341197748113553,
+           1.3496590255606158,
+           1.473377243496544,
+           1.603434849619331,
+           1.7377966303918373,
+           1.8742743286085883,
+           2.0105732394411735,
+           2.144341736770831,
+           2.2732225792011063,
+           2.394904797122956,
+           2.5071749431157513,
+           2.607966498335722,
+           2.695406267170993,
+           2.767856660413359,
+           2.8239528618989325,
+           2.862633992732499,
+           2.8831675279622426,
+           2.885166379508883,
+           2.8685982324248354,
+           2.833786904959727,
+           2.781405691983542,
+           2.712462841472008,
+           2.6282795003674475,
+           2.5304606446548004,
+           2.420859674597816,
+           2.3015375057289233,
+           2.1747171157471565,
+           2.04273461381278,
+           1.9079879792664378,
+           1.7728846696091143,
+           1.639789321401056,
+           1.5109727620292077,
+           1.3885635152316658,
+           1.2745029197537188,
+           1.170504890136249,
+           1.0780212336559543,
+           0.9982133006988335,
+           0.9319305907356019,
+           0.8796967664075623,
+           0.8417033482027717,
+           0.8178111762317507,
+           0.8075595382645943,
+           0.8101826790579085,
+           0.8246332295836535,
+           0.8496119303770803,
+           0.8836028748472826,
+           0.9249133696379493,
+           0.9717174030927146,
+           1.0221016321068648,
+           1.0741127440426093,
+           1.1258050251815852,
+           1.1752869709118465,
+           1.220765805307751,
+           1.2605888380573176,
+           1.2932806732333426,
+           1.3175753949543183,
+           1.3324429867102694,
+           1.3371093906892375,
+           1.3310697770476014,
+           1.3140947665969662,
+           1.2862295294682606,
+           1.2477858624680744,
+           1.199327524553445,
+           1.1416492787055799,
+           1.0757502452714727,
+           1.0028023126663412,
+           0.9241144726971674,
+           0.8410940466799298,
+           0.7552058425493514,
+           0.6679303304973232,
+           0.580721944193622,
+           0.49496860590909725,
+           0.41195353715606897,
+           0.33282035276428396,
+           0.25854234728169245,
+           0.1898967705210245,
+           0.1274447568362171,
+           0.07151742368291218,
+           0.02220849299043831,
+           -0.0206263820305052,
+           -0.057363577457348734,
+           -0.08859891493168412,
+           -0.1151288731110827,
+           -0.13792609618460114,
+           -0.15810985091211924,
+           -0.1769122165716414,
+           -0.19564090509112095,
+           -0.2156396986225482,
+           -0.2382475565819199,
+           -0.26475748205935007,
+           -0.29637624750478103,
+           -0.3341860614237132,
+           -0.37910921189028635,
+           -0.43187665011713167,
+           -0.49300137989961496,
+           -0.5627573988908166,
+           -0.6411647983446462,
+           -0.7279814726634629,
+           -0.8227017226856924,
+           -0.9245618613407951,
+           -1.0325527514824235,
+           -1.145439027879549,
+           -1.2617845829790648,
+           -1.37998373350137,
+           -1.498297336307074,
+           -1.614892991051675,
+           -1.7278883572650041,
+           -1.8353965274751922,
+           -1.9355723380734853,
+           -2.0266584673732995,
+           -2.1070301666529545,
+           -2.1752374950770665,
+           -2.2300439827401273,
+           -2.2704607264385395,
+           -2.2957750282502727,
+           -2.3055728150535053,
+           -2.2997542246493916,
+           -2.2785419075825333,
+           -2.242481769086568,
+           -2.192436058529206,
+           -2.12956889980097,
+           -2.0553245407083707,
+           -1.971398778044723,
+           -1.879704183209919,
+           -1.7823299068709537,
+           -1.6814969763871463,
+           -1.579510113203153,
+           -1.4787071863031467,
+           -1.3814074798875249,
+           -1.2898599870991958,
+           -1.2061929460086922,
+           -1.132365809000223,
+           -1.0701247827435836,
+           -1.0209629943575735,
+           -0.9860862321160336,
+           -0.9663850786973919,
+           -0.9624141046791701,
+           -0.9743786233695947,
+           -1.002129329189321,
+           -1.0451649550110922,
+           -1.1026428936729842,
+           -1.1733975399257064,
+           -1.255965925950238,
+           -1.3486200507414459,
+           -1.4494051452957142,
+           -1.5561829755119496,
+           -1.6666791664100555,
+           -1.7785334375524453,
+           -1.889351572680882,
+           -1.9967579081533662,
+           -2.0984471156874265,
+           -2.192234075369244,
+           -2.276100684332972,
+           -2.348238523700882,
+           -2.4070864093737057,
+           -2.4513619785123963,
+           -2.480086609931503,
+           -2.4926031395143293,
+           -2.4885860071455754,
+           -2.4680436552222345,
+           -2.431313186038193,
+           -2.379047471650172,
+           -2.31219509066132,
+           -2.2319736372865857,
+           -2.139837104925931,
+           -2.0374381854578028,
+           -1.9265864432148674,
+           -1.8092034162866388,
+           -1.6872757651802421,
+           -1.5628076283855388,
+           -1.4377733551527168,
+           -1.314071767629965,
+           -1.1934830579744793,
+           -1.07762935239129,
+           -0.9679398751910555,
+           -0.8656215244314464,
+           -0.7716355296144085,
+           -0.6866807048314366,
+           -0.6111836416481291,
+           -0.5452960091547782,
+           -0.4888989484240186,
+           -0.4416143696237758,
+           -0.4028227867101347,
+           -0.3716871612945881,
+           -0.34718207801033496,
+           -0.3281274421993581,
+           -0.3132257802616843,
+           -0.3011021362734099,
+           -0.29034549761442324,
+           -0.2795506488215666,
+           -0.2673593474817165,
+           -0.2524997387780704,
+           -0.23382297566984175,
+           -0.21033608829665112,
+           -0.1812302470720532,
+           -0.1459036864756852,
+           -0.10397869763732434,
+           -0.05531225383177737,
+           -5.454322126788757e-16
+          ],
+          [
+           0,
+           0.06344295246763644,
+           0.1322960133541769,
+           0.20569490264796744,
+           0.28260119190818117,
+           0.361832021504311,
+           0.4420940113909756,
+           0.5220204645778409,
+           0.6002108746626721,
+           0.6752716862737922,
+           0.7458572216275688,
+           0.8107096785819766,
+           0.8686971257939032,
+           0.9188484683946847,
+           0.9603844318195648,
+           0.9927437102305097,
+           1.0156035469054796,
+           1.028894154018482,
+           1.0328065349061262,
+           1.0277934393128383,
+           1.0145633570323298,
+           0.9940676334251266,
+           0.9674809670122289,
+           0.9361757202696096,
+           0.9016906355603903,
+           0.8656946947685913,
+           0.8299469899144809,
+           0.7962535795507629,
+           0.7664223892978651,
+           0.7422172723042079,
+           0.7253123751897016,
+           0.717247956309966,
+           0.7193887758351258,
+           0.7328861217530374,
+           0.7586444537638115,
+           0.797293540080218,
+           0.8491668329571317,
+           0.9142866804708721,
+           0.9923568082652484,
+           1.0827623296767903,
+           1.184577360142121,
+           1.2965801265584094,
+           1.4172752788727425,
+           1.5449229341420492,
+           1.677573817006951,
+           1.813109709080888,
+           1.9492882869300296,
+           2.083791317419499,
+           2.2142750930017585,
+           2.338421930195166,
+           2.4539915235589334,
+           2.558870945732625,
+           2.6511221116768544,
+           2.7290255815078335,
+           2.7911196599402994,
+           2.836233859344212,
+           2.8635159251607885,
+           2.8724517737322195,
+           2.862877859814021,
+           2.834985670104305,
+           2.7893182256924023,
+           2.7267586658664267,
+           2.648511173617366,
+           2.556074684866922,
+           2.4512099945095907,
+           2.335901028638523,
+           2.2123111900238235,
+           2.0827357996910374,
+           1.949551748503861,
+           1.8151655367930983,
+           1.6819609157567101,
+           1.552247350746241,
+           1.428210503532108,
+           1.3118658788048736,
+           1.205016700827396,
+           1.1092169812820067,
+           1.0257406115597318,
+           0.9555571651755423,
+           0.8993149323067449,
+           0.8573315326718756,
+           0.8295922694182474,
+           0.8157561998730747,
+           0.8151697135152276,
+           0.8268872278799401,
+           0.849698443703124,
+           0.8821614455703591,
+           0.9226407974212755,
+           0.9693496667812738,
+           1.0203949203223106,
+           1.0738240684618865,
+           1.1276728997075194,
+           1.1800126371629922,
+           1.2289954701406718,
+           1.2728973625657223,
+           1.3101571155098335,
+           1.3394107617871718,
+           1.3595204935015464,
+           1.3695974656208192,
+           1.369017976470121,
+           1.3574326954978075,
+           1.334768785513676,
+           1.3012249463904073,
+           1.2572595854551751,
+           1.2035724920256026,
+           1.1410805554694181,
+           1.070888213762347,
+           0.9942534491227635,
+           0.9125502557097498,
+           0.8272285889158075,
+           0.7397728644006607,
+           0.6516601062865335,
+           0.5643188471434727,
+           0.4790898575169154,
+           0.397189730474988,
+           0.3196782683535759,
+           0.24743051657879747,
+           0.18111416577663833,
+           0.12117290149995674,
+           0.06781612443177543,
+           0.021015296842817284,
+           -0.019493002362493312,
+           -0.05419740707870183,
+           -0.08379574388434445,
+           -0.10917309437580955,
+           -0.1313745268710767,
+           -0.15157322429559036,
+           -0.17103485636372304,
+           -0.19107914379142013,
+           -0.21303963767474254,
+           -0.23822278641021088,
+           -0.2678673843391209,
+           -0.30310549008233817,
+           -0.34492586841277845,
+           -0.39414094831077434,
+           -0.4513582030662391,
+           -0.5169567480799574,
+           -0.5910698211153971,
+           -0.6735736614272071,
+           -0.7640831421509372,
+           -0.8619543386386339,
+           -0.9662940383744002,
+           -1.0759760201523743,
+           -1.1896637558266796,
+           -1.3058390215482092,
+           -1.4228357511942311,
+           -1.5388783265853185,
+           -1.6521233805872073,
+           -1.760704093346432,
+           -1.8627758911840642,
+           -1.9565624139238629,
+           -2.0404006008452034,
+           -2.1127837585123634,
+           -2.1724015152131355,
+           -2.218175635706698,
+           -2.2492907648127543,
+           -2.2652192868042413,
+           -2.2657396267364778,
+           -2.2509474763772808,
+           -2.221259597478554,
+           -2.1774100345884313,
+           -2.120438754042515,
+           -2.051672910657263,
+           -1.9727011244228456,
+           -1.885341321693163,
+           -1.791602854736383,
+           -1.6936437560882867,
+           -1.5937241063959617,
+           -1.4941565933010186,
+           -1.3972554119073173,
+           -1.3052847026603127,
+           -1.2204077388636156,
+           -1.1446380631116628,
+           -1.0797937298842504,
+           -1.0274557414018664,
+           -0.988931667245793,
+           -0.9652253175178472,
+           -0.9570131973613665,
+           -0.9646283109196266,
+           -0.9880517091411694,
+           -1.0269119924679542,
+           -1.0804927908164321,
+           -1.147748053968723,
+           -1.2273248001338546,
+           -1.317592793524823,
+           -1.4166804576278054,
+           -1.5225161834033598,
+           -1.632874064535626,
+           -1.7454229881148307,
+           -1.8577779313078668,
+           -1.967552264513104,
+           -2.072409840399426,
+           -2.1701156565771575,
+           -2.258583917197727,
+           -2.3359223845749724,
+           -2.4004720043159513,
+           -2.450840904145731,
+           -2.4859320047186486,
+           -2.5049636368160377,
+           -2.5074827295893876,
+           -2.49337031472721,
+           -2.4628392771766072,
+           -2.416424469779206,
+           -2.3549654923135748,
+           -2.279582610496568,
+           -2.1916464532157596,
+           -2.0927422726877785,
+           -1.9846296788165487,
+           -1.8691988627109384,
+           -1.7484244026344942,
+           -1.6243177967545637,
+           -1.4988798897631392,
+           -1.3740543542930412,
+           -1.2516833532986293,
+           -1.133466447169143,
+           -1.0209237209341804,
+           -0.9153639947868395,
+           -0.81785884815647,
+           -0.7292230370857359,
+           -0.6500017205106493,
+           -0.5804647373425075,
+           -0.5206079973710793,
+           -0.4701618694331178,
+           -0.428606274509812,
+           -0.395192023818479,
+           -0.36896778672124186,
+           -0.3488119342431668,
+           -0.33346838461786804,
+           -0.32158548050539215,
+           -0.31175685572926565,
+           -0.30256320430118794,
+           -0.2926138472144498,
+           -0.2805870033634141,
+           -0.26526770965157137,
+           -0.24558240085144062,
+           -0.22062925037096795,
+           -0.1897034864289156,
+           -0.15231703134235652,
+           -0.10821196128218559,
+           -0.057367446145573375,
+           -5.636419149508736e-16
+          ],
+          [
+           0,
+           0.06512365681932017,
+           0.13526706458703733,
+           0.20947841659273841,
+           0.28664798942357395,
+           0.36554014604515916,
+           0.4448290188061482,
+           0.5231369224548683,
+           0.5990744740863183,
+           0.6712813499419409,
+           0.7384665893806954,
+           0.7994473646567064,
+           0.853185171201948,
+           0.8988184560490069,
+           0.935690790288521,
+           0.9633738028488898,
+           0.981684224638154,
+           0.9906945409095718,
+           0.9907369118796208,
+           0.9824001930751268,
+           0.9665200633103752,
+           0.9441624451585726,
+           0.9166005758265257,
+           0.8852862510983653,
+           0.8518159173142937,
+           0.8178924223278391,
+           0.7852833525745951,
+           0.7557769768091576,
+           0.7311368853093954,
+           0.713056454616515,
+           0.7031142810526178,
+           0.7027317109098176,
+           0.7131335516212014,
+           0.7353129773924652,
+           0.7700015463623906,
+           0.8176451266788133,
+           0.8783863888158319,
+           0.9520543644217778,
+           1.0381614018086238,
+           1.1359076690389902,
+           1.2441931718352386,
+           1.3616370697475575,
+           1.4866038947066087,
+           1.6172361056826199,
+           1.7514922558961776,
+           1.8871899087817907,
+           2.022052319184427,
+           2.1537578000648936,
+           2.279990624720305,
+           2.3984922719752557,
+           2.507111808073282,
+           2.6038542144942367,
+           2.6869255153230887,
+           2.7547736300685637,
+           2.806123976261879,
+           2.8400089683966927,
+           2.8557907028565754,
+           2.8531762789561337,
+           2.832225380208043,
+           2.7933499231981784,
+           2.7373057695526803,
+           2.6651766848412364,
+           2.578350912299391,
+           2.4784909044930257,
+           2.367496918228899,
+           2.2474653231943535,
+           2.120642599461568,
+           1.9893761000949663,
+           1.856062730209293,
+           1.7230967411337241,
+           1.5928178567172615,
+           1.4674609378467804,
+           1.3491083512427495,
+           1.2396461405624957,
+           1.1407250034756733,
+           1.0537269600238002,
+           0.9797384581630496,
+           0.9195305053571319,
+           0.873546244303495,
+           0.8418962105402494,
+           0.8243613242218208,
+           0.8204034823139704,
+           0.8291834353968922,
+           0.8495854596250653,
+           0.8802481734059479,
+           0.9196007039379694,
+           0.9659032843874693,
+           1.0172912611780949,
+           1.071821415034104,
+           1.1275194508457616,
+           1.1824274912186936,
+           1.2346504171337327,
+           1.2823999361710843,
+           1.3240353232303077,
+           1.3580998689154375,
+           1.383352184428064,
+           1.3987916460189282,
+           1.4036774133868921,
+           1.3975406210604053,
+           1.380189515606831,
+           1.3517074901257085,
+           1.3124441464201972,
+           1.2629996900351887,
+           1.204203129641942,
+           1.1370849059006387,
+           1.062844712130566,
+           0.9828153864686436,
+           0.8984238498090992,
+           0.8111501333737136,
+           0.722485582577697,
+           0.6338913389190981,
+           0.5467581886149384,
+           0.462368826025379,
+           0.38186351263272994,
+           0.3062100202262376,
+           0.23617863235953532,
+           0.17232284403143688,
+           0.11496624931620601,
+           0.06419594416334545,
+           0.019862600931991672,
+           -0.018412803243402505,
+           -0.05122579601183048,
+           -0.07936911786919743,
+           -0.103807848818846,
+           -0.12564961987216516,
+           -0.14611070470905752,
+           -0.16647889553820452,
+           -0.18807415279022507,
+           -0.21220807855422677,
+           -0.2401432970779206,
+           -0.2730538313174656,
+           -0.3119875422676575,
+           -0.35783164815120416,
+           -0.4112822647131656,
+           -0.47281880772888024,
+           -0.542683976880553,
+           -0.620869899430577,
+           -0.7071108561364454,
+           -0.8008828445193505,
+           -0.9014100601139262,
+           -1.007678199074495,
+           -1.1184543099554052,
+           -1.2323127530464684,
+           -1.3476666666118884,
+           -1.462804194782323,
+           -1.5759286053620052,
+           -1.6852013206682137,
+           -1.7887868034233319,
+           -1.8848981847816277,
+           -1.9718424942547108,
+           -2.0480643523786397,
+           -2.1121870165118843,
+           -2.1630497275283487,
+           -2.199740389040986,
+           -2.221622719164814,
+           -2.228357145095219,
+           -2.219914859781107,
+           -2.196584624082898,
+           -2.158972073010693,
+           -2.107991466641639,
+           -2.044850010644503,
+           -1.971025053452383,
+           -1.8882346425260133,
+           -1.7984020865011356,
+           -1.7036153192389742,
+           -1.6060819921895872,
+           -1.508081329780574,
+           -1.4119138660457156,
+           -1.3198502373003227,
+           -1.2340802339036652,
+           -1.156663313269593,
+           -1.089481746254694,
+           -1.0341975105455417,
+           -0.992213959058939,
+           -0.9646431807058503,
+           -0.9522798378102184,
+           -0.9555821122308702,
+           -0.9746602244933378,
+           -1.0092728110666076,
+           -1.0588312586681734,
+           -1.1224119056758453,
+           -1.198775833957487,
+           -1.2863957942426736,
+           -1.3834896389353686,
+           -1.4880594821190074,
+           -1.5979356711791255,
+           -1.710824541248629,
+           -1.8243588353085762,
+           -1.9361496113857,
+           -2.043838425348024,
+           -2.145148574085368,
+           -2.2379342094305636,
+           -2.3202261873686676,
+           -2.390273598536439,
+           -2.4465800327051213,
+           -2.487933759222987,
+           -2.5134311540763195,
+           -2.5224928686428134,
+           -2.5148724113138714,
+           -2.490656996623885,
+           -2.4502607028453194,
+           -2.394410163623843,
+           -2.324123197624432,
+           -2.2406809479847127,
+           -2.145594256541832,
+           -2.04056513259848,
+           -1.9274442891678691,
+           -1.8081858084712088,
+           -1.6848000608461193,
+           -1.5593060357100315,
+           -1.4336842490497788,
+           -1.3098313690307224,
+           -1.1895176503967204,
+           -1.0743481907233885,
+           -0.9657289193037228,
+           -0.8648381051090865,
+           -0.7726040270425925,
+           -0.689689291209663,
+           -0.6164821101687386,
+           -0.5530946823603513,
+           -0.4993686305769472,
+           -0.4548872809158417,
+           -0.41899439258179644,
+           -0.39081878843542905,
+           -0.36930419030660794,
+           -0.3532434354230712,
+           -0.34131614399624804,
+           -0.33212882567102453,
+           -0.3242563561910139,
+           -0.31628372660868936,
+           -0.30684696634574116,
+           -0.29467216834520354,
+           -0.2786115987134397,
+           -0.25767595320446385,
+           -0.23106192658269353,
+           -0.1981743856498715,
+           -0.15864257934775555,
+           -0.11232997621343745,
+           -0.05933748657658161,
+           -5.808141763773378e-16
+          ],
+          [
+           0,
+           0.06665267941550264,
+           0.13789425414683942,
+           0.21269401047665407,
+           0.28988078341102036,
+           0.3681769513827273,
+           0.4462355696068245,
+           0.5226796516944163,
+           0.5961425510971003,
+           0.6653083627660897,
+           0.7289512618841715,
+           0.7859727207861741,
+           0.8354355966457749,
+           0.8765941599089958,
+           0.9089192348789352,
+           0.9321177467768157,
+           0.9461461109520095,
+           0.9512170561514757,
+           0.9477996409707246,
+           0.936612396596028,
+           0.9186097053360135,
+           0.8949616987871454,
+           0.8670281273823521,
+           0.8363268102886788,
+           0.8044974171616446,
+           0.773261457503368,
+           0.7443794561317303,
+           0.7196063719022233,
+           0.7006463692833321,
+           0.6891080772700315,
+           0.6864614667129061,
+           0.6939974454309579,
+           0.7127912111579733,
+           0.7436703168279132,
+           0.7871882929723181,
+           0.8436045407263644,
+           0.9128710593052662,
+           0.9946264074674699,
+           1.0881971234469165,
+           1.192606646408768,
+           1.3065915991244919,
+           1.4286251107936143,
+           1.5569466852267178,
+           1.6895979572487665,
+           1.8244635332121526,
+           1.9593159835834428,
+           2.0918639498805485,
+           2.2198022474413306,
+           2.3408627916443963,
+           2.452865149662799,
+           2.553765523302137,
+           2.6417030009334956,
+           2.7150419772455026,
+           2.7724097270780304,
+           2.8127282318743196,
+           2.835239491598667,
+           2.839523708071668,
+           2.825509893867858,
+           2.7934786401226464,
+           2.7440569624548936,
+           2.6782053322110664,
+           2.597197185804534,
+           2.5025913835451457,
+           2.3961982566844777,
+           2.2800400333715967,
+           2.1563065671292345,
+           2.0273074020941517,
+           1.8954212949373104,
+           1.7630443720201554,
+           1.6325381305469802,
+           1.5061784935297982,
+           1.386107100296966,
+           1.2742859577677268,
+           1.172456494196244,
+           1.0821039486347885,
+           1.004427898659775,
+           0.9403195791719804,
+           0.8903464800112822,
+           0.8547445337764128,
+           0.8334180219409585,
+           0.8259471416029615,
+           0.8316029915432973,
+           0.8493695591857587,
+           0.8779721238670298,
+           0.9159113405793602,
+           0.9615021357086693,
+           1.0129164354566156,
+           1.0682286612628538,
+           1.1254628666810191,
+           1.1826403581970515,
+           1.2378266391080386,
+           1.2891765407916953,
+           1.3349764587720048,
+           1.3736826905183552,
+           1.4039549758442613,
+           1.42468446643832,
+           1.4350154952712635,
+           1.4343606757335325,
+           1.4224090303593464,
+           1.3991270256167787,
+           1.3647525680636565,
+           1.3197821937166216,
+           1.2649518523521979,
+           1.2012118474264983,
+           1.1296966364181162,
+           1.0516903220991691,
+           0.9685887694225017,
+           0.8818593628226987,
+           0.7929994728165299,
+           0.703494727561084,
+           0.6147781838789478,
+           0.5281914632837763,
+           0.44494886252937554,
+           0.3661053666313953,
+           0.2925293872836242,
+           0.2248809238080392,
+           0.16359570045599642,
+           0.10887567667140455,
+           0.060686159836393846,
+           0.018759577292288304,
+           -0.017394209550565833,
+           -0.04847133701606438,
+           -0.07535156819879622,
+           -0.09907072223053448,
+           -0.12078864295914915,
+           -0.14175356345697376,
+           -0.16326381807692994,
+           -0.18662792471215983,
+           -0.2131241046710688,
+           -0.2439603249958264,
+           -0.28023593765798754,
+           -0.3229059520894856,
+           -0.37274891287523865,
+           -0.43033926474143763,
+           -0.49602497445011984,
+           -0.5699110466620333,
+           -0.6518494215693955,
+           -0.7414355798661668,
+           -0.8380120094858384,
+           -0.9406785127953541,
+           -1.048309157011425,
+           -1.1595754989375222,
+           -1.2729755520424264,
+           -1.3868678135443555,
+           -1.49950953534726,
+           -1.609098308810761,
+           -1.7138159423437245,
+           -1.811873545048187,
+           -1.9015566908369406,
+           -1.9812695266643001,
+           -2.049576706111347,
+           -2.1052420752116667,
+           -2.147263110050246,
+           -2.1749002036012097,
+           -2.1877000201412047,
+           -2.1855122764605412,
+           -2.1684994665666046,
+           -2.1371392167865104,
+           -2.092219136957856,
+           -2.0348242163541035,
+           -1.9663169956199278,
+           -1.8883109237836093,
+           -1.802637477971542,
+           -1.7113077785958821,
+           -1.6164695706649441,
+           -1.5203605590404738,
+           -1.4252591790026976,
+           -1.3334339510285598,
+           -1.247092608519624,
+           -1.1683321982935768,
+           -1.0990913356417054,
+           -1.041105749033375,
+           -0.9958681752024658,
+           -0.964593565144386,
+           -0.9481904378880854,
+           -0.9472390747642745,
+           -0.9619770857542638,
+           -0.9922927052779141,
+           -1.037725991692403,
+           -1.0974779172741251,
+           -1.1704271481027841,
+           -1.255154130616748,
+           -1.3499719281053442,
+           -1.4529630902671982,
+           -1.5620216960880984,
+           -1.674899588147053,
+           -1.7892557180091027,
+           -1.9027074499898196,
+           -2.012882626022317,
+           -2.1174711786841276,
+           -2.2142750930017576,
+           -2.3012555600830225,
+           -2.376576235860582,
+           -2.43864161451613,
+           -2.4861296461064506,
+           -2.518017868566706,
+           -2.533602482155214,
+           -2.5325099656419594,
+           -2.5147010139226995,
+           -2.4804667618353453,
+           -2.43041744423158,
+           -2.3654638232825,
+           -2.2867918861562404,
+           -2.195831475405299,
+           -2.094219656775968,
+           -1.9837597512577396,
+           -1.8663770570899847,
+           -1.7440723607771,
+           -1.6188743822085905,
+           -1.4927923166921127,
+           -1.3677696257411622,
+           -1.2456401891829447,
+           -1.1280878646308625,
+           -1.0166104083404224,
+           -0.9124885963026785,
+           -0.816761249061504,
+           -0.7302067116002793,
+           -0.6533311745680858,
+           -0.5863640492576361,
+           -0.5292604304673296,
+           -0.4817105031390132,
+           -0.4431555749122367,
+           -0.41281025180327885,
+           -0.38969012220295646,
+           -0.3726441790598454,
+           -0.36039109481909903,
+           -0.3515583712581882,
+           -0.34472331905893905,
+           -0.33845478140595686,
+           -0.3313545030578528,
+           -0.3220970614561964,
+           -0.3094673190726172,
+           -0.2923944252117583,
+           -0.26998148909047737,
+           -0.24153016179030995,
+           -0.20655949966411286,
+           -0.1648186325228532,
+           -0.11629292259496855,
+           -0.061203470701949376,
+           -5.967853287909961e-16
+          ],
+          [
+           0,
+           0.06801554918177107,
+           0.1401528378790461,
+           0.21531150967353604,
+           0.2922692890607604,
+           0.3697176579173304,
+           0.44630010678013204,
+           0.5206519389475066,
+           0.5914405628898729,
+           0.6574051932135483,
+           0.7173948928697318,
+           0.7704039291563516,
+           0.8156034823487758,
+           0.8523688368748712,
+           0.8803012985533477,
+           0.8992442147050951,
+           0.9092926235899098,
+           0.9107962218644096,
+           0.9043555095277016,
+           0.8908111468256426,
+           0.8712267324150228,
+           0.8468653823352907,
+           0.8191606506941026,
+           0.7896824813553008,
+           0.7600990115525706,
+           0.7321351598790132,
+           0.7075290196590139,
+           0.6879871419986843,
+           0.6751398291661714,
+           0.6704975673734366,
+           0.6754097082116024,
+           0.6910264603311637,
+           0.7182651785491685,
+           0.7577818381694301,
+           0.8099484603059762,
+           0.874837112358728,
+           0.9522109499529464,
+           1.0415225964793164,
+           1.1419199780333815,
+           1.2522595494367628,
+           1.37112666561678,
+           1.496862676406563,
+           1.6275981561662005,
+           1.7612915266523061,
+           1.8957721960830252,
+           2.028787222740151,
+           2.158050420591331,
+           2.2812927595968984,
+           2.396312876242774,
+           2.501026501389747,
+           2.5935136330234125,
+           2.6720623304890214,
+           2.735208083162912,
+           2.7817678084327393,
+           2.8108676588905754,
+           2.8219639637727068,
+           2.814856791399189,
+           2.789695793755964,
+           2.7469781771899955,
+           2.687538830010987,
+           2.6125328240689787,
+           2.523410688573507,
+           2.42188702612823,
+           2.3099031989968317,
+           2.1895849541478216,
+           2.0631959752320053,
+           1.9330884454240072,
+           1.8016517746892617,
+           1.671260686841679,
+           1.5442238747390018,
+           1.4227344158314104,
+           1.308823095457983,
+           1.2043157128994146,
+           1.1107953470436083,
+           1.029570437031937,
+           0.9616493914262633,
+           0.9077222807633128,
+           0.8681499967453564,
+           0.8429610809686857,
+           0.8318562414355619,
+           0.8342203906527323,
+           0.8491418593980171,
+           0.8754382696207604,
+           0.9116883925846162,
+           0.9562691780810106,
+           1.0073970207295662,
+           1.0631722329177882,
+           1.121625623114603,
+           1.1807660347822913,
+           1.2386276858919159,
+           1.2933161624012255,
+           1.3430519605565434,
+           1.386210541411462,
+           1.4213579547288944,
+           1.4472812060412765,
+           1.463012677118473,
+           1.4678480629793358,
+           1.461357454027365,
+           1.443389365735755,
+           1.4140676961958614,
+           1.3737817693278664,
+           1.3231697942054133,
+           1.263096234469663,
+           1.1946237321415103,
+           1.1189803635607312,
+           1.0375231183944302,
+           0.9516985828830368,
+           0.8630018735289976,
+           0.7729349057150303,
+           0.6829650923713837,
+           0.5944855505962813,
+           0.5087778495699423,
+           0.4269782623755309,
+           0.3500483892903944,
+           0.2787509031870067,
+           0.21363103188065294,
+           0.15500424104752983,
+           0.10295041856362697,
+           0.057314690920708,
+           0.017714829083441578,
+           -0.016444970840783692,
+           -0.04595431307742246,
+           -0.07177137121189076,
+           -0.09499288077212571,
+           -0.11682016049865693,
+           -0.13852207191385665,
+           -0.1613959079739507,
+           -0.18672725737926824,
+           -0.21574992009648336,
+           -0.24960695105252065,
+           -0.2893138827289266,
+           -0.3357251241493608,
+           -0.3895044548237255,
+           -0.45110042955073626,
+           -0.5207273861462614,
+           -0.5983526062533188,
+           -0.6836900229555192,
+           -0.776200701883516,
+           -0.8751001490704906,
+           -0.9793723233419506,
+           -1.0877900579398347,
+           -1.1989414297519858,
+           -1.311261459154237,
+           -1.4230683830165969,
+           -1.5326036214538008,
+           -1.6380744585354223,
+           -1.7376983809993887,
+           -1.8297479690229776,
+           -1.9125952106365496,
+           -1.9847541170710066,
+           -2.044920550164407,
+           -2.0920082341679698,
+           -2.125180011455331,
+           -2.1438735126708766,
+           -2.1478205440742326,
+           -2.1370596450368065,
+           -2.111941433157411,
+           -2.073126529258437,
+           -2.021576035309321,
+           -1.9585347206487431,
+           -1.88550725124336,
+           -1.804227968693027,
+           -1.716624886009205,
+           -1.6247787118719599,
+           -1.5308778405072307,
+           -1.4371703473834714,
+           -1.3459141090135724,
+           -1.2593262162852543,
+           -1.1795328736092863,
+           -1.1085209701439396,
+           -1.0480924745088258,
+           -0.9998227415330405,
+           -0.9650237301722424,
+           -0.9447130179111394,
+           -0.9395893614786959,
+           -0.9500153998131853,
+           -0.976007926648775,
+           -1.0172359809428122,
+           -1.0730268179742577,
+           -1.1423796368253443,
+           -1.2239867556619435,
+           -1.3162617492375408,
+           -1.417373897667836,
+           -1.5252881457810181,
+           -1.6378096418842316,
+           -1.7526318167675528,
+           -1.8673868808129692,
+           -1.97969756119184,
+           -2.087228873661624,
+           -2.1877387250566733,
+           -2.2791261731419055,
+           -2.3594762292866798,
+           -2.427100174951084,
+           -2.480570473138937,
+           -2.5187494880384906,
+           -2.54081137678757,
+           -2.5462566829558444,
+           -2.5349193378625,
+           -2.5069659589117435,
+           -2.4628875192452644,
+           -2.40348364565223,
+           -2.3298399773827625,
+           -2.2432991829986784,
+           -2.1454263816674177,
+           -2.0379698457457414,
+           -1.9228179699634982,
+           -1.8019535764080814,
+           -1.6774066818407536,
+           -1.5512068833207957,
+           -1.4253365190381795,
+           -1.3016857337305914,
+           -1.1820105228622513,
+           -1.067894748326245,
+           -0.9607170129044805,
+           -0.8616231537750281,
+           -0.7715049702175677,
+           -0.6909856409999487,
+           -0.6204121167498873,
+           -0.5598545961968096,
+           -0.5091130169253554,
+           -0.4677303156655949,
+           -0.4350120445324614,
+           -0.4100517722100472,
+           -0.39176155675960317,
+           -0.37890665303227283,
+           -0.37014351563543657,
+           -0.364060080533885,
+           -0.35921725655370484,
+           -0.35419053353129026,
+           -0.347610617160457,
+           -0.33820203158627726,
+           -0.3248186886299045,
+           -0.30647550568680576,
+           -0.2823752606698743,
+           -0.2519299991381641,
+           -0.21477645271956616,
+           -0.17078508543100998,
+           -0.12006255151493185,
+           -0.0629475207016644,
+           -6.114033491548998e-16
+          ],
+          [
+           0,
+           0.06919937777099866,
+           0.14202154634060588,
+           0.21730632408293987,
+           0.29379103353861086,
+           0.37014753716459126,
+           0.4450212667515648,
+           0.5170712020215738,
+           0.5850097271386828,
+           0.6476412945587012,
+           0.7038988538193294,
+           0.7528770578457364,
+           0.7938613397592584,
+           0.8263520570276394,
+           0.8500830244908044,
+           0.8650339002159362,
+           0.8714360447090848,
+           0.8697716408064975,
+           0.8607660343933774,
+           0.8453734305990067,
+           0.8247562518940907,
+           0.8002586292284273,
+           0.7733746508237777,
+           0.7457121315810435,
+           0.7189527857471247,
+           0.6948097834497857,
+           0.6749837454203756,
+           0.6611182777573689,
+           0.6547561686613191,
+           0.6572973610997944,
+           0.6699597794433888,
+           0.6937440250525061,
+           0.729402867068615,
+           0.7774163423950472,
+           0.8379731457534707,
+           0.9109588400094132,
+           0.9959512523544627,
+           1.092223247448781,
+           1.1987528885537506,
+           1.3142408164582413,
+           1.4371344980977756,
+           1.5656588265868892,
+           1.6978523961519323,
+           1.8316086330991537,
+           1.9647208410314714,
+           2.094930118114715,
+           2.2199750288192246,
+           2.337641864141236,
+           2.4458143040970977,
+           2.54252130484473,
+           2.625982069978252,
+           2.6946470305153847,
+           2.7472338493220434,
+           2.7827575810160865,
+           2.800554254990659,
+           2.800297303799453,
+           2.782006428008415,
+           2.7460486676454425,
+           2.6931316352229078,
+           2.6242890514733173,
+           2.5408589078972397,
+           2.4444547555217704,
+           2.3369307826405907,
+           2.2203414917771607,
+           2.096896914093225,
+           1.9689144048460077,
+           1.838768143721532,
+           1.708837516998754,
+           1.5814555832524477,
+           1.458858820100724,
+           1.3431393164735157,
+           1.236200513854301,
+           1.1397175124480203,
+           1.0551028464178986,
+           0.9834784989732,
+           0.9256547764617074,
+           0.8821164944541917,
+           0.8530167521825788,
+           0.8381783889401846,
+           0.8371030316461323,
+           0.8489874612255193,
+           0.8727468511930477,
+           0.9070442690951193,
+           0.9503256842167918,
+           1.000859596760468,
+           1.0567802976413587,
+           1.1161336866582876,
+           1.1769245220108728,
+           1.2371639472093439,
+           1.2949161429346574,
+           1.348342981223175,
+           1.3957456166429616,
+           1.4356020323891239,
+           1.4665996663075276,
+           1.4876623700264544,
+           1.4979711003860956,
+           1.4969779025218914,
+           1.4844129142523708,
+           1.4602842975760866,
+           1.4248711806893204,
+           1.378709868564949,
+           1.3225737474347963,
+           1.257447464337415,
+           1.1844961033696269,
+           1.1050302019439253,
+           1.0204675502123173,
+           0.9322927924288869,
+           0.8420158985577014,
+           0.7511305967157184,
+           0.6610738515820468,
+           0.5731874409122419,
+           0.48868262266559404,
+           0.4086088005486386,
+           0.33382698819044876,
+           0.26498874445773385,
+           0.20252110785580457,
+           0.1466179002307821,
+           0.09723760310225246,
+           0.05410783815413343,
+           0.016736311055683933,
+           -0.015572090753762487,
+           -0.0436925161297088,
+           -0.0686523022378937,
+           -0.09159881098794376,
+           -0.11376381344023266,
+           -0.13642537667487595,
+           -0.16086827407700754,
+           -0.1883439802894551,
+           -0.22003132517197374,
+           -0.25699886662957827,
+           -0.30017000046993647,
+           -0.3502917575457538,
+           -0.4079081460181173,
+           -0.4733387819450023,
+           -0.5466634174215856,
+           -0.6277128255315231,
+           -0.7160663391737968,
+           -0.8110561704830744,
+           -0.9117784633494064,
+           -1.0171108578554489,
+           -1.1257361766706155,
+           -1.2361716838410026,
+           -1.3468032200374918,
+           -1.4559233888959837,
+           -1.5617728599080838,
+           -1.6625837672041341,
+           -1.756624122747442,
+           -1.8422421285360282,
+           -1.9179092663253245,
+           -1.9822610653872201,
+           -2.034134498454148,
+           -2.0726010321172397,
+           -2.096994458749009,
+           -2.106932760078966,
+           -2.102333394881326,
+           -2.083421561368368,
+           -2.0507311549511082,
+           -2.005098319856454,
+           -1.9476476743003046,
+           -1.8797714690395464,
+           -1.803102113709627,
+           -1.7194786700732443,
+           -1.6309080620692555,
+           -1.5395218856045618,
+           -1.4475298130518064,
+           -1.3571706755892265,
+           -1.2706623686171128,
+           -1.1901517599169837,
+           -1.1176657860715138,
+           -1.0550648997257235,
+           -1.0039999790384913,
+           -0.9658737323423795,
+           -0.9418075274584414,
+           -0.9326144487844283,
+           -0.9387792392334756,
+           -0.9604456218768925,
+           -0.9974113216707313,
+           -1.0491309251563197,
+           -1.1147265299547953,
+           -1.1930059507505135,
+           -1.2824880687824742,
+           -1.381434742010284,
+           -1.4878885372256119,
+           -1.5997154072345998,
+           -1.7146513192011474,
+           -1.8303517471564914,
+           -1.9444428748040212,
+           -2.054573315691935,
+           -2.158465147523272,
+           -2.2539630760499216,
+           -2.339080591172274,
+           -2.4120420523603743,
+           -2.471319740477052,
+           -2.5156650360493154,
+           -2.5441330269699765,
+           -2.5561000079998997,
+           -2.551273506366222,
+           -2.529694647995141,
+           -2.4917328630625173,
+           -2.4380731130860105,
+           -2.369696000235249,
+           -2.287851288550254,
+           -2.1940255222217857,
+           -2.089904564229936,
+           -1.9773319961219062,
+           -1.8582644137148805,
+           -1.7347247217978023,
+           -1.6087545718780512,
+           -1.4823670997540168,
+           -1.3575011039711602,
+           -1.2359777625180728,
+           -1.1194609146137915,
+           -1.0094218389605292,
+           -0.9071093418351066,
+           -0.8135258308672425,
+           -0.729409896780933,
+           -0.6552257596245205,
+           -0.5911597622463928,
+           -0.5371239163383678,
+           -0.4927663297001863,
+           -0.4574881718795955,
+           -0.4304666732789164,
+           -0.41068350421111616,
+           -0.3969577489130092,
+           -0.38798257842126227,
+           -0.38236463821398026,
+           -0.37866510375930146,
+           -0.37544132109968137,
+           -0.3712879411706793,
+           -0.36487647584824573,
+           -0.35499225018493086,
+           -0.3405677976992947,
+           -0.3207118420403112,
+           -0.29473312637499444,
+           -0.2621584884188987,
+           -0.22274473065911637,
+           -0.17648399814629426,
+           -0.12360254611616973,
+           -0.06455295232833955,
+           -6.245292612340693e-16
+          ],
+          [
+           0,
+           0.07019297437767578,
+           0.1434827687074579,
+           0.21865965065206952,
+           0.2944315236465136,
+           0.36946198994484125,
+           0.44240981427271314,
+           0.5119687303250994,
+           0.5769065213986477,
+           0.6361023229273036,
+           0.6885811382055524,
+           0.7335446280626918,
+           0.7703973289655215,
+           0.7987675696356372,
+           0.8185224908774204,
+           0.8297767235485694,
+           0.8328944416941494,
+           0.8284846777318926,
+           0.8173899599437139,
+           0.800668505024478,
+           0.7795703657069227,
+           0.7555080912881044,
+           0.7300226032242221,
+           0.7047451151637432,
+           0.6813560336021959,
+           0.6615418590185504,
+           0.6469511657189876,
+           0.6391507701233347,
+           0.6395832010047434,
+           0.6495265610470683,
+           0.6700578175259125,
+           0.7020204821421693,
+           0.7459975378907692,
+           0.8022903467928691,
+           0.8709041293682073,
+           0.9515404483637286,
+           1.0435969593636505,
+           1.146174513658558,
+           1.258091518512628,
+           1.3779052811881243,
+           1.50393989018816,
+           1.634320024449654,
+           1.7670099327031663,
+           1.89985669461739,
+           2.0306367659298856,
+           2.1571047242840877,
+           2.277043073110505,
+           2.3883119291348467,
+           2.4888974158159405,
+           2.5769576103614678,
+           2.6508649453852464,
+           2.709244046510294,
+           2.751004092381303,
+           2.7753649111068315,
+           2.7818761740320657,
+           2.7704292103953723,
+           2.7412611409040855,
+           2.6949512103410616,
+           2.6324093845579957,
+           2.5548574611178805,
+           2.463803120941377,
+           2.3610075162537623,
+           2.248447143831922,
+           2.1282708882727217,
+           2.002753234443249,
+           1.8742447386489556,
+           1.7451209121757012,
+           1.6177307071777949,
+           1.4943458025282326,
+           1.3771118660549846,
+           1.2680029200979952,
+           1.1687798607698783,
+           1.080954079583338,
+           1.0057570117304084,
+           0.9441162913251059,
+           0.8966390338914852,
+           0.8636025942223722,
+           0.8449529676713133,
+           0.8403108193812617,
+           0.8489849433865729,
+           0.8699927764078428,
+           0.9020874238078906,
+           0.9437905016607514,
+           0.9934299629250325,
+           1.049181960590791,
+           1.1091157091480586,
+           1.1712402399814703,
+           1.2335519078648658,
+           1.2940814954718747,
+           1.3509397808947143,
+           1.4023604790357225,
+           1.4467395401800263,
+           1.4826698861944785,
+           1.508970784141729,
+           1.5247111956185928,
+           1.5292265943262013,
+           1.5221289103755555,
+           1.5033094334626822,
+           1.4729346839681168,
+           1.431435436830179,
+           1.3794892533321348,
+           1.3179970364984965,
+           1.2480542726360278,
+           1.170917751051387,
+           1.087968662941487,
+           1.0006730662155343,
+           0.9105407634855444,
+           0.8190836742075646,
+           0.7277747881935899,
+           0.6380087663588384,
+           0.5510652062276324,
+           0.46807551567578265,
+           0.38999424056376075,
+           0.3175755728328343,
+           0.25135562834635744,
+           0.19164093176482255,
+           0.1385033829167911,
+           0.09178180960716535,
+           0.051090039893654786,
+           0.015831256922516426,
+           -0.014781764245697937,
+           -0.041701091622181774,
+           -0.06601343581031317,
+           -0.08890612786954656,
+           -0.11163018951129669,
+           -0.1354614863420149,
+           -0.16166100618732462,
+           -0.19143532912645086,
+           -0.22589835309582235,
+           -0.26603530883137283,
+           -0.31267004124589903,
+           -0.36643645248600876,
+           -0.4277548969233345,
+           -0.49681419283192574,
+           -0.5735597726322667,
+           -0.657688336927384,
+           -0.7486492110543304,
+           -0.8456524307144992,
+           -0.9476834097668372,
+           -1.0535238728469456,
+           -1.1617785724209713,
+           -1.2709071583276328,
+           -1.3792604316548758,
+           -1.4851200974132501,
+           -1.5867410349144184,
+           -1.68239503350893,
+           -1.770414896247986,
+           -1.8492377963250402,
+           -1.917446781359361,
+           -1.9738093585432497,
+           -2.01731215853412,
+           -2.0471907662055173,
+           -2.0629539198155333,
+           -2.0644014140627975,
+           -2.051635193619479,
+           -2.0250632883627278,
+           -1.9853964156321207,
+           -1.9336372541378215,
+           -1.8710625742113984,
+           -1.799198585477606,
+           -1.7197900313632626,
+           -1.6347637159684993,
+           -1.546187288821155,
+           -1.456224233421218,
+           -1.367086103240574,
+           -1.2809831215079999,
+           -1.2000743068275515,
+           -1.1264183042598621,
+           -1.06192609043845,
+           -1.0083166818005072,
+           -0.9670769079864242,
+           -0.9394262194852351,
+           -0.9262873818946871,
+           -0.928263771530677,
+           -0.9456238318848418,
+           -0.978293081349008,
+           -1.0258538838030677,
+           -1.0875530094426218,
+           -1.1623168280841167,
+           -1.2487737956333378,
+           -1.3452837208578428,
+           -1.4499731382907426,
+           -1.5607759679395483,
+           -1.6754785170119897,
+           -1.791767776152386,
+           -1.9072818852000133,
+           -2.019661593112206,
+           -2.126601514650803,
+           -2.225899993229129,
+           -2.3155064147697204,
+           -2.3935648806404886,
+           -2.4584532371507306,
+           -2.508816572487599,
+           -2.5435944265650017,
+           -2.562041111728169,
+           -2.563738708862866,
+           -2.5486024801106617,
+           -2.516878621762066,
+           -2.469134464524949,
+           -2.406241408759174,
+           -2.3293510550299437,
+           -2.239865151255983,
+           -2.139400122907696,
+           -2.0297470786320826,
+           -1.912828287313749,
+           -1.7906512014472928,
+           -1.6652611539347384,
+           -1.5386938798306693,
+           -1.4129290106253816,
+           -1.2898456565723924,
+           -1.171181133213948,
+           -1.0584938031948705,
+           -0.9531308958686068,
+           -0.8562020378583102,
+           -0.7685590809136001,
+           -0.6907826528017953,
+           -0.6231756866255962,
+           -0.5657640081338976,
+           -0.5183038836831879,
+           -0.48029625792424646,
+           -0.451007244350717,
+           -0.42949427767125187,
+           -0.41463719837091517,
+           -0.40517342022989494,
+           -0.399736233906052,
+           -0.396895226346196,
+           -0.395197748540067,
+           -0.3932103440858488,
+           -0.3895590586278248,
+           -0.3829675851941519,
+           -0.3722922618578633,
+           -0.3565530243580916,
+           -0.3349595251214336,
+           -0.30693175872123873,
+           -0.2721146789177582,
+           -0.23038645033522215,
+           -0.18186014453583366,
+           -0.12687886151054803,
+           -0.06600442907623655,
+           -6.360383996543952e-16
+          ],
+          [
+           0,
+           0.07098694297531295,
+           0.14452269916233726,
+           0.21935861705607534,
+           0.2941843329868723,
+           0.3676665231635891,
+           0.4384884567992209,
+           0.5053892885463334,
+           0.567202033294308,
+           0.6228891983528553,
+           0.6715751063809048,
+           0.7125740256665213,
+           0.7454133304430013,
+           0.7698510401829908,
+           0.785887230079892,
+           0.7937689616057889,
+           0.7939885481875781,
+           0.7872751424842971,
+           0.7745798041561357,
+           0.7570543760357565,
+           0.7360246579696215,
+           0.7129585172003674,
+           0.6894297082076798,
+           0.6670782899942657,
+           0.6475686219439346,
+           0.6325459881820659,
+           0.623592943030667,
+           0.6221864855162087,
+           0.629657158483678,
+           0.6471511279123412,
+           0.6755962314230683,
+           0.7156728932858077,
+           0.7677906886792415,
+           0.8320712052977727,
+           0.9083376989251241,
+           0.9961118750059549,
+           1.0946179545882233,
+           1.2027940045550618,
+           1.3193103332198242,
+           1.4425945775453775,
+           1.5708629418021962,
+           1.7021568935353466,
+           1.8343844851034241,
+           1.9653653512231735,
+           2.092878337859517,
+           2.2147106478462932,
+           2.328707345594946,
+           2.432820048275027,
+           2.52515364436979,
+           2.604009922260518,
+           2.667927060517701,
+           2.7157140262464594,
+           2.746479045886918,
+           2.7596514514679424,
+           2.7549963611089288,
+           2.732621821786045,
+           2.6929782209211246,
+           2.63684995687511,
+           2.565339542469885,
+           2.479844495742771,
+           2.382027543871999,
+           2.273780825415628,
+           2.157184918803583,
+           2.0344636479352145,
+           1.9079357157726986,
+           1.7799642915526253,
+           1.6529057248531664,
+           1.529058579105216,
+           1.4106141677676092,
+           1.2996097385480136,
+           1.1978853856865155,
+           1.1070456790478722,
+           1.028426883841891,
+           0.9630705090390038,
+           0.911703769306426,
+           0.8747273783210242,
+           0.8522109147120038,
+           0.8438958199744507,
+           0.8492059049229259,
+           0.8672650620861178,
+           0.8969217102474831,
+           0.936779338277937,
+           0.9852323723447679,
+           1.0405064669755126,
+           1.1007022192807083,
+           1.163841229311432,
+           1.2279133798458477,
+           1.2909241870019035,
+           1.3509410794124561,
+           1.4061374980268226,
+           1.4548337699817586,
+           1.4955337968104627,
+           1.5269567073002401,
+           1.548062755768002,
+           1.5580728940983344,
+           1.5564816068655851,
+           1.5430627691986787,
+           1.5178684624824166,
+           1.4812208591410077,
+           1.4336974602307984,
+           1.3761101340922728,
+           1.30947855679719,
+           1.2349987918048575,
+           1.1540078637438058,
+           1.0679452766792439,
+           0.9783124982871896,
+           0.8866314763216226,
+           0.794403271576102,
+           0.7030678818323832,
+           0.6139662943716859,
+           0.5283057414975024,
+           0.4471290458352835,
+           0.37128883220139985,
+           0.30142725339492504,
+           0.2379617316700941,
+           0.18107705960547704,
+           0.13072403761824786,
+           0.08662465470597396,
+           0.04828364846429106,
+           0.0150061143499107,
+           -0.014079323256835618,
+           -0.03999241039894114,
+           -0.06386899395153388,
+           -0.08692545261229753,
+           -0.11042078452246863,
+           -0.13561736955905254,
+           -0.16374146021172648,
+           -0.19594446378843172,
+           -0.2332660602395204,
+           -0.2766001545964597,
+           -0.32666459200906217,
+           -0.38397546840503244,
+           -0.44882675326210747,
+           -0.5212758057964737,
+           -0.6011352154242852,
+           -0.6879712354270612,
+           -0.781108909420987,
+           -0.8796438177611839,
+           -0.9824601997566941,
+           -1.0882550418582786,
+           -1.1955675660055154,
+           -1.302813410041702,
+           -1.4083226671474316,
+           -1.5103808468028765,
+           -1.607271738552775,
+           -1.6973211039302238,
+           -1.7789400927795647,
+           -1.8506672787222553,
+           -1.9112082347621422,
+           -1.9594716234642575,
+           -1.9946008555222132,
+           -2.0160004739611317,
+           -2.0233565462105756,
+           -2.0166504897877573,
+           -1.9961659158502987,
+           -1.9624882445239225,
+           -1.9164970225124403,
+           -1.8593510527018464,
+           -1.792466622849936,
+           -1.7174892916145883,
+           -1.6362598508709068,
+           -1.550775229500552,
+           -1.4631452319573324,
+           -1.3755461117121521,
+           -1.2901720624685398,
+           -1.2091857667152772,
+           -1.13466917028208,
+           -1.0685756523035235,
+           -1.01268473228561,
+           -0.9685604004204228,
+           -0.9375140752039414,
+           -0.920573085731446,
+           -0.9184554473318647,
+           -0.9315515515591286,
+           -0.959913228555937,
+           -1.0032504653941128,
+           -1.0609358824111876,
+           -1.132016885219359,
+           -1.215235227445966,
+           -1.3090535428202377,
+           -1.4116882392467216,
+           -1.521147996044164,
+           -1.6352769722684384,
+           -1.7518017222230156,
+           -1.868380726610394,
+           -1.9826553864190903,
+           -2.092301293058215,
+           -2.1950785832481463,
+           -2.2888802108550603,
+           -2.3717770196204118,
+           -2.442058579297964,
+           -2.4982688511300353,
+           -2.5392358743216437,
+           -2.564094810115051,
+           -2.5723038406666965,
+           -2.5636525922440776,
+           -2.5382629320693875,
+           -2.4965821710390985,
+           -2.4393688860741154,
+           -2.3676717515737415,
+           -2.2828019350789326,
+           -2.1862997637709696,
+           -2.0798965021700395,
+           -1.9654721941275568,
+           -1.845010611222968,
+           -1.7205524128655845,
+           -1.5941476592921073,
+           -1.4678088264428852,
+           -1.3434654512926425,
+           -1.222921488199344,
+           -1.1078163824920517,
+           -0.9995907687699891,
+           -0.8994575807518975,
+           -0.8083792200581604,
+           -0.7270512765454266,
+           -0.655893126635557,
+           -0.5950455626525679,
+           -0.5443754298374648,
+           -0.5034870728501378,
+           -0.47174022454052367,
+           -0.4482738107742459,
+           -0.43203500006832546,
+           -0.4218126993102961,
+           -0.4162745900342665,
+           -0.41400671622211555,
+           -0.41355457641173127,
+           -0.41346464141448674,
+           -0.4123252148879398,
+           -0.4088055774053856,
+           -0.4016924048525672,
+           -0.38992252763350965,
+           -0.37261119631561085,
+           -0.3490751394353902,
+           -0.3188498371445679,
+           -0.28170058668063347,
+           -0.23762709841885235,
+           -0.18686153036703115,
+           -0.129860040107879,
+           -0.06728810203620057,
+           -6.458215240931509e-16
+          ],
+          [
+           0,
+           0.07157376106929068,
+           0.14513144445016776,
+           0.21939636535518456,
+           0.2930511081313759,
+           0.3647766259124689,
+           0.4332915408394868,
+           0.49739058827709476,
+           0.5559811688543773,
+           0.608117019195168,
+           0.6530280847060459,
+           0.6901457739488411,
+           0.7191228915308044,
+           0.739847682154154,
+           0.7524515690683793,
+           0.7573103318755801,
+           0.7550386373793708,
+           0.7464780086871156,
+           0.7326784877431208,
+           0.7148744105888897,
+           0.694454868757342,
+           0.6729295703969022,
+           0.6518909374165142,
+           0.6329733770038374,
+           0.6178107446668943,
+           0.6079930694321605,
+           0.6050236385768398,
+           0.6102775385225074,
+           0.6249627201997151,
+           0.6500846019249532,
+           0.6864151419028186,
+           0.734467207810378,
+           0.7944749450661209,
+           0.866380701394734,
+           0.9498289066916,
+           1.0441671378592121,
+           1.1484544223987614,
+           1.2614766564333408,
+           1.3817688369187386,
+           1.5076436384234637,
+           1.6372257062388775,
+           1.7684908936634143,
+           1.899309545686931,
+           2.027492827133066,
+           2.150841013225498,
+           2.267192606567445,
+           2.374473118059685,
+           2.470742351054161,
+           2.554239058075986,
+           2.6234218970792966,
+           2.677005698084954,
+           2.7139921591856626,
+           2.73369422070382,
+           2.7357535146197742,
+           2.7201504496659785,
+           2.6872066667468046,
+           2.637579780362622,
+           2.5722505050882996,
+           2.4925024474177353,
+           2.399895018022665,
+           2.2962300834290112,
+           2.1835131252915962,
+           2.0639098062138523,
+           1.9396989502277482,
+           1.8132230309639574,
+           1.6868373191400654,
+           1.5628588718565817,
+           1.443516548577104,
+           1.330903212537501,
+           1.226931222335852,
+           1.133292237936602,
+           1.0514222602660686,
+           0.9824726965667937,
+           0.9272880978366471,
+           0.8863910535842229,
+           0.8599745567341919,
+           0.847901972036584,
+           0.8497145591623362,
+           0.8646463212539395,
+           0.8916457754447493,
+           0.9294040780057771,
+           0.9763887873043071,
+           1.0308824162838608,
+           1.091024815870203,
+           1.1548583442167548,
+           1.2203747160768825,
+           1.2855623932411382,
+           1.3484533716395979,
+           1.4071682434266293,
+           1.4599584624873718,
+           1.5052448180072902,
+           1.5416512210611653,
+           1.568033031046954,
+           1.583499289126368,
+           1.587428381100391,
+           1.5794768184453813,
+           1.5595809993993812,
+           1.5279519876943226,
+           1.4850635203992124,
+           1.4316336240497798,
+           1.3686003756314493,
+           1.2970924881614672,
+           1.2183955260517276,
+           1.1339146600456054,
+           1.0451349527553728,
+           0.9535802217164885,
+           0.8607715560931132,
+           0.7681865650576325,
+           0.6772204104529966,
+           0.589149624341105,
+           0.5050996348199098,
+           0.4260168230625719,
+           0.35264581347990537,
+           0.2855125603324177,
+           0.2249136415567473,
+           0.17091200790638522,
+           0.1233392668718188,
+           0.08180441051965803,
+           0.04570872869237718,
+           0.014266488188769742,
+           -0.013469191326820446,
+           -0.03857596906556249,
+           -0.06222824384449309,
+           -0.08566036097384068,
+           -0.11012805473546333,
+           -0.1368691627534564,
+           -0.16706466882785412,
+           -0.20180112394769653,
+           -0.24203546137637472,
+           -0.2885631617454652,
+           -0.34199063949765557,
+           -0.4027126149008241,
+           -0.47089510889906194,
+           -0.5464645544596234,
+           -0.6291033614271506,
+           -0.718252106150388,
+           -0.8131183464780534,
+           -0.9126918914354273,
+           -1.0157661873194133,
+           -1.1209653223285871,
+           -1.2267760042250548,
+           -1.3315837336618601,
+           -1.433712283069497,
+           -1.5314655002719744,
+           -1.6231703896447145,
+           -1.7072203833763744,
+           -1.7821177023479957,
+           -1.8465137207115576,
+           -1.8992462901632472,
+           -1.9393730482079126,
+           -1.9661998277840989,
+           -1.979303401225937,
+           -1.9785479268748491,
+           -1.9640946184193464,
+           -1.9364043215173647,
+           -1.896232855400624,
+           -1.8446191547080744,
+           -1.782866424360025,
+           -1.7125166934707847,
+           -1.6353193188077841,
+           -1.553194140048792,
+           -1.4681901242803868,
+           -1.3824404524374574,
+           -1.298115092807255,
+           -1.2173719739722786,
+           -1.142307909920743,
+           -1.0749104424470606,
+           -1.0170117500220608,
+           -0.9702457283526209,
+           -0.9360092768838096,
+           -0.915428729199288,
+           -0.9093322459486156,
+           -0.9182288494431441,
+           -0.9422946227839861,
+           -0.9813664271011706,
+           -1.0349433123001595,
+           -1.1021956139609437,
+           -1.1819815461619025,
+           -1.2728709214578597,
+           -1.3731754593786258,
+           -1.480984987769785,
+           -1.5942087008984396,
+           -1.7106205179134897,
+           -1.82790748791261,
+           -1.9437201158944226,
+           -2.055723439009412,
+           -2.1616476658508077,
+           -2.2593372034384154,
+           -2.346796936736751,
+           -2.4222346930140066,
+           -2.4840989164234553,
+           -2.5311106945813733,
+           -2.562289415762332,
+           -2.576971489274457,
+           -2.5748217288371937,
+           -2.5558371752644495,
+           -2.5203433161374753,
+           -2.468982842000941,
+           -2.4026972564935254,
+           -2.322701827396289,
+           -2.230454522724741,
+           -2.1276197168921467,
+           -2.0160275732272623,
+           -1.897630107823301,
+           -1.7744550134718124,
+           -1.6485583695579946,
+           -1.5219773831874523,
+           -1.3966842980872485,
+           -1.2745425712810663,
+           -1.1572663541704813,
+           -1.0463842261118743,
+           -0.9432080171330189,
+           -0.8488074249148535,
+           -0.7639909828965414,
+           -0.6892937750741485,
+           -0.6249721228000076,
+           -0.5710052939090566,
+           -0.52710410916469,
+           -0.4927261496947591,
+           -0.4670971060323003,
+           -0.44923765862458986,
+           -0.4379951449521956,
+           -0.4320791530225418,
+           -0.4301000877965944,
+           -0.43060968833944024,
+           -0.43214243080737985,
+           -0.43325673679157156,
+           -0.4325749183479049,
+           -0.42882082988384035,
+           -0.4208542618988291,
+           -0.40770120068854465,
+           -0.38857918922117646,
+           -0.36291715462453317,
+           -0.3303692137570198,
+           -0.29082212645243427,
+           -0.24439623220675916,
+           -0.19143987609534713,
+           -0.13251749925874198,
+           -0.06839173407783752,
+           -6.53785772950913e-16
+          ],
+          [
+           0,
+           0.0719478392534882,
+           0.14530309169761446,
+           0.21877207507634688,
+           0.291041494139705,
+           0.3608175466646578,
+           0.42686463397269925,
+           0.4880426336476988,
+           0.5433417277992063,
+           0.5919138417554176,
+           0.6330998339691359,
+           0.6664516860272679,
+           0.6917490692565225,
+           0.7090098083085404,
+           0.718493918666798,
+           0.7207010603024653,
+           0.7163614195497263,
+           0.7064202013853403,
+           0.6920160803818429,
+           0.6744541164528461,
+           0.6551737871162903,
+           0.6357129176615768,
+           0.6176684010069541,
+           0.6026546873386325,
+           0.5922610875453298,
+           0.5880089723195395,
+           0.5913099595569924,
+           0.6034261659909054,
+           0.6254335551755366,
+           0.6581893439901432,
+           0.7023043354296,
+           0.7581209288552497,
+           0.8256974229306377,
+           0.9047990744815625,
+           0.994896212224981,
+           1.0951695317477264,
+           1.2045225215396262,
+           1.3216007936614051,
+           1.4448179211219558,
+           1.572387221511185,
+           1.7023587769297281,
+           1.8326608475080237,
+           1.96114472314054,
+           2.0856319683135816,
+           2.203962950352929,
+           2.314045503721002,
+           2.4139025731514536,
+           2.5017176967386203,
+           2.575877236221842,
+           2.635008334558303,
+           2.6780116787410106,
+           2.7040882663514507,
+           2.712759514640252,
+           2.7038802076143464,
+           2.677643945880619,
+           2.6345809417452237,
+           2.5755481839739334,
+           2.5017121782553677,
+           2.414524646352206,
+           2.3156917348633907,
+           2.2071374393595837,
+           2.0909620876191677,
+           1.9693968434203,
+           1.8447552869669688,
+           1.7193831972404994,
+           1.5956077036910603,
+           1.4756869886982,
+           1.3617617078055015,
+           1.2558092522379376,
+           1.159601908695467,
+           1.074669876596059,
+           1.0022699851492745,
+           0.943360814770556,
+           0.898584772779563,
+           0.8682575058516361,
+           0.8523648554105013,
+           0.8505673813744455,
+           0.862212298813822,
+           0.8863524955572883,
+           0.9217721308970399,
+           0.967018160370287,
+           1.020436992897189,
+           1.0802153676845943,
+           1.1444244421171248,
+           1.2110660106456381,
+           1.2781197301217155,
+           1.3435902101299466,
+           1.4055528379668163,
+           1.462197246645501,
+           1.5118673996265448,
+           1.5530973561886074,
+           1.584641894152353,
+           1.6055012991919377,
+           1.614939778868591,
+           1.6124971210572536,
+           1.5979933865636318,
+           1.5715266001943582,
+           1.533463578998955,
+           1.484424206510172,
+           1.4252596233487025,
+           1.3570249535312902,
+           1.2809473185518323,
+           1.198390004530173,
+           1.1108137386730814,
+           1.0197360977586218,
+           0.9266901117470411,
+           0.8331831390015066,
+           0.7406570757112267,
+           0.6504509213715975,
+           0.5637666556862769,
+           0.48163929175398235,
+           0.40491185822654063,
+           0.334215932153454,
+           0.26995819780860836,
+           0.21231334865737356,
+           0.16122348378746448,
+           0.1164039808045625,
+           0.07735565867678619,
+           0.043382880570225095,
+           0.01361709248919349,
+           -0.012954847576491008,
+           -0.03745831971739752,
+           -0.061095445687679224,
+           -0.08510740240574391,
+           -0.11073555929850117,
+           -0.13918248490800497,
+           -0.17157387283153272,
+           -0.20892241474684703,
+           -0.2520945995321357,
+           -0.30178134353947017,
+           -0.358473259772132,
+           -0.4224412554899129,
+           -0.49372301159168164,
+           -0.5721157464250154,
+           -0.6571755052416357,
+           -0.7482230484226835,
+           -0.8443562410800415,
+           -0.9444686780065641,
+           -1.0472741154659266,
+           -1.1513361291006279,
+           -1.255102279162551,
+           -1.3569419438546297,
+           -1.4551868818979747,
+           -1.548173509076337,
+           -1.6342858224498253,
+           -1.711997881534031,
+           -1.7799147587066646,
+           -1.836810901446418,
+           -1.8816649060595219,
+           -1.913689784970973,
+           -1.9323579154773287,
+           -1.9374199845155853,
+           -1.9289173884127175,
+           -1.9071877052088615,
+           -1.872863026097984,
+           -1.8268611076417212,
+           -1.7703694833613006,
+           -1.7048228477196328,
+           -1.6318741930451255,
+           -1.5533603364541844,
+           -1.47126261540051,
+           -1.3876636535745361,
+           -1.304701200405312,
+           -1.2245201248147,
+           -1.1492236951659114,
+           -1.080825301201152,
+           -1.0212017695157958,
+           -0.9720493918011791,
+           -0.9348437254258005,
+           -0.9108041403122703,
+           -0.9008639765412566,
+           -0.9056470463013054,
+           -0.9254510648586436,
+           -0.9602384317472232,
+           -1.0096346093405544,
+           -1.0729341655906965,
+           -1.1491143653935891,
+           -1.2368560152023922,
+           -1.3345710925429333,
+           -1.4404365302035391,
+           -1.5524333780220583,
+           -1.6683904369557965,
+           -1.7860313536209003,
+           -1.9030240813201802,
+           -2.017031557741815,
+           -2.125762421358386,
+           -2.2270205887637258,
+           -2.3187525437352643,
+           -2.3990912449899393,
+           -2.466395642024388,
+           -2.519284895065156,
+           -2.5566665233814683,
+           -2.577757852882718,
+           -2.5821002954397816,
+           -2.5695661647758534,
+           -2.54035791284978,
+           -2.494999852025148,
+           -2.43432260755362,
+           -2.3594407176317795,
+           -2.271723960314,
+           -2.17276313394627,
+           -2.0643311469602925,
+           -1.9483403807206094,
+           -1.826797373066988,
+           -1.7017559282503607,
+           -1.5752697897745345,
+           -1.4493460155548206,
+           -1.3259001698033617,
+           -1.206714393853867,
+           -1.093399340120393,
+           -0.9873608515538451,
+           -0.8897721459110732,
+           -0.8015521229959347,
+           -0.7233502573253121,
+           -0.6555383723210477,
+           -0.5982094192934286,
+           -0.5511832094764165,
+           -0.5140188745557974,
+           -0.48603366479233323,
+           -0.466327538104424,
+           -0.45381285218767703,
+           -0.4472483483926555,
+           -0.44527651368253,
+           -0.4464633280459216,
+           -0.44933935115257334,
+           -0.45244107507875453,
+           -0.4543514701952024,
+           -0.4537386787206761,
+           -0.44939186423621,
+           -0.44025330420752257,
+           -0.42544591423015216,
+           -0.4042955146768387,
+           -0.37634728956681995,
+           -0.3413760402421124,
+           -0.29938999893906026,
+           -0.2506281354561327,
+           -0.19555105957644683,
+           -0.1348257884109755,
+           -0.0693048071687774,
+           -6.598554475674721e-16
+          ],
+          [
+           0,
+           0.0721055610618594,
+           0.1450357360108681,
+           0.21749092580010856,
+           0.2881729806118373,
+           0.35582397436120866,
+           0.4192639974098587,
+           0.47742694832566535,
+           0.529393355935972,
+           0.5744193382763672,
+           0.6119609034468199,
+           0.6416929163806039,
+           0.663522192117557,
+           0.6775943269146635,
+           0.6842940396266787,
+           0.684238963185415,
+           0.678266995472902,
+           0.6674174861375607,
+           0.6529066967098316,
+           0.6360981216559519,
+           0.6184683939448119,
+           0.6015696168257476,
+           0.5869890607979068,
+           0.5763072386845298,
+           0.571055420378283,
+           0.5726736708959345,
+           0.5824704902339827,
+           0.6015851011922825,
+           0.6309533725505126,
+           0.6712782811250202,
+           0.7230057093123468,
+           0.7863062473315321,
+           0.8610635246169182,
+           0.9468694362329912,
+           1.0430264616811564,
+           1.1485570991989973,
+           1.262220262922318,
+           1.3825343174417764,
+           1.507806258630061,
+           1.636166395264792,
+           1.765607746778199,
+           1.894029251912012,
+           2.0192817841760626,
+           2.139215895304212,
+           2.251730159280877,
+           2.354818968246717,
+           2.4466186382801793,
+           2.525450717603434,
+           2.589861451400279,
+           2.638656444715907,
+           2.6709296757565837,
+           2.6860861436613765,
+           2.6838575843010153,
+           2.664310851253312,
+           2.6278487328427578,
+           2.5752031557923494,
+           2.507420907247434,
+           2.4258421852814185,
+           2.332072459134867,
+           2.2279482801997896,
+           2.115497829243435,
+           1.9968971110456344,
+           1.8744228114360666,
+           1.750402911131611,
+           1.6271662038556132,
+           1.5069918916811824,
+           1.3920604277664972,
+           1.2844067457198105,
+           1.1858769565124685,
+           1.0980895095879517,
+           1.0224017066648454,
+           0.9598823273580523,
+           0.9112909783179266,
+           0.8770646157241878,
+           0.8573115186330211,
+           0.8518128120768891,
+           0.8600314583208846,
+           0.8811284566914968,
+           0.9139858212504239,
+           0.9572357454501887,
+           1.0092952176655237,
+           1.068405224658615,
+           1.1326735746622383,
+           1.2001202903746269,
+           1.2687244666805448,
+           1.3364714596297735,
+           1.4013992727301186,
+           1.4616430338726487,
+           1.5154765104448524,
+           1.5613496899798278,
+           1.5979215569865977,
+           1.624087320781025,
+           1.6389994910513246,
+           1.642082353977327,
+           1.6330395680659855,
+           1.6118547713096447,
+           1.5787852655183316,
+           1.5343490153887673,
+           1.4793053647889705,
+           1.4146300267754555,
+           1.341485043216932,
+           1.2611845311449907,
+           1.1751571331184423,
+           1.0849061655356993,
+           0.9919685101128659,
+           0.8978733184558354,
+           0.8041015972504757,
+           0.7120477122136265,
+           0.6229837934015908,
+           0.5380279442283186,
+           0.45811705368594663,
+           0.38398488843224327,
+           0.3161460017570498,
+           0.2548858435248613,
+           0.20025729290384342,
+           0.1520836681539951,
+           0.10996809920806314,
+           0.07330898350782483,
+           0.041321087739785684,
+           0.013061711741415393,
+           -0.01253880037550338,
+           -0.036643029594593056,
+           -0.06046985100402834,
+           -0.08525618939193276,
+           -0.11221819082047425,
+           -0.14251285558163646,
+           -0.1772011670988234,
+           -0.21721371391261518,
+           -0.26331973880850845,
+           -0.31610046198852815,
+           -0.37592741614410474,
+           -0.4429464030941924,
+           -0.5170675375347518,
+           -0.5979616870318527,
+           -0.6850634526226157,
+           -0.7775806654229319,
+           -0.8745102057460646,
+           -0.9746597866839048,
+           -1.0766751880621952,
+           -1.1790722831144331,
+           -1.2802730727820708,
+           -1.3786448344985751,
+           -1.4725414064286457,
+           -1.5603455666387185,
+           -1.6405114311910696,
+           -1.7116057866539993,
+           -1.7723472913044787,
+           -1.8216425249854582,
+           -1.8586179391134885,
+           -1.8826468540109393,
+           -1.8933707682531937,
+           -1.8907143812168008,
+           -1.8748938821528212,
+           -1.846418223156752,
+           -1.806083265323793,
+           -1.7549588629223025,
+           -1.6943691252461084,
+           -1.6258662655823728,
+           -1.5511986072366089,
+           -1.4722734637898933,
+           -1.391115741046899,
+           -1.3098232181976162,
+           -1.2305195527858932,
+           -1.155306115940931,
+           -1.0862137993884506,
+           -1.0251559430794066,
+           -0.9738835116001959,
+           -0.9339435992945583,
+           -0.9066422693462036,
+           -0.8930126327093474,
+           -0.8937889511074671,
+           -0.9093874072763144,
+           -0.9398940286130869,
+           -0.9850600812139846,
+           -1.0443050740444282,
+           -1.1167273319993294,
+           -1.2011219162807478,
+           -1.2960054952403226,
+           -1.3996476028769524,
+           -1.5101075695936932,
+           -1.6252762743238116,
+           -1.7429217520393643,
+           -1.8607375987631574,
+           -1.976393049755483,
+           -2.087583567157857,
+           -2.1920807619997613,
+           -2.287780492380737,
+           -2.3727480244042614,
+           -2.445259213955906,
+           -2.5038367639261483,
+           -2.5472807306066936,
+           -2.574692591815526,
+           -2.585492344425756,
+           -2.5794282665884487,
+           -2.5565791559477424,
+           -2.517349035245176,
+           -2.4624544965016604,
+           -2.3929050300656125,
+           -2.3099768509614504,
+           -2.215180888127344,
+           -2.1102257385837033,
+           -1.9969765050297394,
+           -1.877410529027593,
+           -1.753571100570773,
+           -1.6275202668349336,
+           -1.5012918773219568,
+           -1.3768459891637728,
+           -1.2560257154667027,
+           -1.1405175323443917,
+           -1.0318159684499013,
+           -0.9311934867201767,
+           -0.8396762345815311,
+           -0.7580261893953182,
+           -0.6867300642029021,
+           -0.6259951689047282,
+           -0.5757522481222704,
+           -0.5356651434744656,
+           -0.5051469591628511,
+           -0.48338224978788186,
+           -0.46935460216775665,
+           -0.46187885222796676,
+           -0.45963706698430595,
+           -0.4612173329665944,
+           -0.46515432827349107,
+           -0.46997061734233514,
+           -0.47421759633980054,
+           -0.47651503303185416,
+           -0.4755881875988453,
+           -0.4703015689798791,
+           -0.45968847318004746,
+           -0.44297556318184256,
+           -0.4196018817637,
+           -0.3892318352805754,
+           -0.3517618445656421,
+           -0.3073205245502766,
+           -0.2562624227729311,
+           -0.19915551438356374,
+           -0.13676281330870363,
+           -0.07001861182139667,
+           -6.639726198458992e-16
+          ],
+          [
+           0,
+           0.07204530281365329,
+           0.14433146778695904,
+           0.21556399996346925,
+           0.2844706702806604,
+           0.3498396271742207,
+           0.4105559550910663,
+           0.4656356924354699,
+           0.514256386053506,
+           0.5557833477269655,
+           0.5897908880786621,
+           0.6160779320216385,
+           0.6346775641743652,
+           0.6458602088771014,
+           0.6501303136417125,
+           0.6482165729034771,
+           0.6410558965722324,
+           0.6297714908593637,
+           0.6156455730552712,
+           0.6000873834318659,
+           0.5845972826416024,
+           0.570727828676864,
+           0.5600428109228974,
+           0.5540752779178425,
+           0.5542856285653308,
+           0.5620208428159402,
+           0.5784759070010483,
+           0.60465844150105,
+           0.6413574653616451,
+           0.6891171355799115,
+           0.7482161804074602,
+           0.8186536090433872,
+           0.9001411278672049,
+           0.9921025296309696,
+           1.0936801508249554,
+           1.2037483179817658,
+           1.3209335303096814,
+           1.4436409580501088,
+           1.5700866775155558,
+           1.698334918835314,
+           1.8263394746419017,
+           1.9519883104820543,
+           2.0731503333450214,
+           2.1877232155177464,
+           2.293681138531761,
+           2.3891213171356394,
+           2.472308186203755,
+           2.541714183787834,
+           2.5960561399683706,
+           2.6343263819593656,
+           2.6558177886509533,
+           2.6601421694861846,
+           2.647241499836113,
+           2.617391714049945,
+           2.5711989340101105,
+           2.5095881910192994,
+           2.4337848778047544,
+           2.3452893409830016,
+           2.2458451882530195,
+           2.1374020348777307,
+           2.0220735470050553,
+           1.902091751823696,
+           1.779758673701945,
+           1.6573964191448116,
+           1.5372968700744694,
+           1.4216721537010284,
+           1.3126070378978894,
+           1.2120143540097106,
+           1.1215944755583316,
+           1.0427997831785862,
+           0.9768049257188817,
+           0.9244835477332416,
+           0.8863919979937568,
+           0.8627603659738886,
+           0.8534910175944269,
+           0.8581646221769746,
+           0.8760534838918131,
+           0.9061418173726247,
+           0.9471524428246518,
+           0.9975792248669271,
+           1.055724445182388,
+           1.1197401850401687,
+           1.1876727026386171,
+           1.257508724164741,
+           1.3272225280238954,
+           1.3948226897525053,
+           1.4583973708974431,
+           1.5161570781549614,
+           1.5664738881667803,
+           1.6079162267848308,
+           1.6392784069577602,
+           1.659604263742546,
+           1.668204374921063,
+           1.6646665175425908,
+           1.6488591803719717,
+           1.6209281254680794,
+           1.5812861646373584,
+           1.5305964840198212,
+           1.4697500084209922,
+           1.3998374422914555,
+           1.3221167528980775,
+           1.2379769700725418,
+           1.1488992633087578,
+           1.056416318822133,
+           0.9620710750084415,
+           0.8673758837294432,
+           0.7737731468595559,
+           0.6825984330816037,
+           0.5950470102098823,
+           0.5121446351657967,
+           0.43472332954063003,
+           0.3634027363800878,
+           0.2985775067952944,
+           0.2404110069887363,
+           0.18883547129650083,
+           0.14355855907528145,
+           0.1040761069553144,
+           0.06969070734834025,
+           0.039535593206614046,
+           0.012603171690210418,
+           -0.012222570912860326,
+           -0.03613067091458628,
+           -0.06034575114735762,
+           -0.08608955569835983,
+           -0.11454249124493134,
+           -0.1468062113393473,
+           -0.18386825392702005,
+           -0.22656969034072802,
+           -0.275576667299068,
+           -0.33135662397600113,
+           -0.3941598465007386,
+           -0.46400688530546763,
+           -0.5406822100116095,
+           -0.6237343158327812,
+           -0.7124823288291928,
+           -0.8060289889829209,
+           -0.9032797242339533,
+           -1.0029673695231045,
+           -1.1036819365668946,
+           -1.203904706313954,
+           -1.3020458002163902,
+           -1.396484291562531,
+           -1.4856098466088432,
+           -1.5678648389879548,
+           -1.6417858610961815,
+           -1.7060435634574103,
+           -1.7594797873243297,
+           -1.801141016241988,
+           -1.8303072575357897,
+           -1.8465155726476867,
+           -1.849577603310862,
+           -1.8395905855976133,
+           -1.8169415023405615,
+           -1.7823041924147354,
+           -1.7366294087327188,
+           -1.6811279912587946,
+           -1.6172474925663345,
+           -1.5466427571910175,
+           -1.4711411081929917,
+           -1.3927029311323202,
+           -1.3133785636567394,
+           -1.235262495126753,
+           -1.1604459527221047,
+           -1.090968996439371,
+           -1.0287732640961909,
+           -0.9756564983671177,
+           -0.933229951136378,
+           -0.90287969689409,
+           -0.8857327980146472,
+           -0.8826291526561557,
+           -0.8940997233987025,
+           -0.9203516947959065,
+           -0.9612609443777274,
+           -1.0163720382829813,
+           -1.084905783830719,
+           -1.165774191313628,
+           -1.2576025204997467,
+           -1.3587579180713978,
+           -1.467383994641169,
+           -1.5814405479098772,
+           -1.698747515438517,
+           -1.8170321393996522,
+           -1.9339782490205257,
+           -2.0472765160991284,
+           -2.1546745161909584,
+           -2.2540254333772087,
+           -2.34333427979853,
+           -2.420800561549791,
+           -2.484856408594688,
+           -2.534199295961645,
+           -2.567818613935973,
+           -2.585015493071359,
+           -2.5854154519790007,
+           -2.5689736080492374,
+           -2.5359723693084053,
+           -2.487011705165184,
+           -2.422992270476389,
+           -2.345091826859035,
+           -2.2547355633724995,
+           -2.153561061754861,
+           -2.043378775861618,
+           -1.9261289978262985,
+           -1.803836362280895,
+           -1.6785629928752501,
+           -1.552361421095869,
+           -1.4272284054536848,
+           -1.305060749619697,
+           -1.1876141618470262,
+           -1.076466116497462,
+           -0.972983573780897,
+           -0.878296288574701,
+           -0.7932762965791601,
+           -0.7185240096661198,
+           -0.6543611860091545,
+           -0.6008308685957671,
+           -0.5577042123004969,
+           -0.5244939491526861,
+           -0.5004740779925534,
+           -0.48470521241741604,
+           -0.4760648835323206,
+           -0.4732819749130064,
+           -0.4749743692779852,
+           -0.4796888120297182,
+           -0.4859419478483485,
+           -0.49226146405414767,
+           -0.4972262789809947,
+           -0.4995047449309439,
+           -0.49788989254754107,
+           -0.4913308251424521,
+           -0.47895947551715384,
+           -0.4601120614631234,
+           -0.43434471623642196,
+           -0.40144292331315146,
+           -0.3614245467490544,
+           -0.314536415376564,
+           -0.2612445866441439,
+           -0.20221857989214154,
+           -0.13831002511682736,
+           -0.07052631784796165,
+           -6.660975580198429e-16
+          ],
+          [
+           0,
+           0.07176743336096932,
+           0.14319632009434757,
+           0.21300812720982157,
+           0.2799669729505197,
+           0.34291675367878793,
+           0.40081616636474066,
+           0.4527706790665574,
+           0.4980605798208313,
+           0.536164334824619,
+           0.5667766071595406,
+           0.5898204245505626,
+           0.60545313530871,
+           0.6140659518777145,
+           0.6162770472434016,
+           0.6129183366805165,
+           0.6050162416739835,
+           0.5937668901955203,
+           0.5805063538477154,
+           0.566676653982343,
+           0.553788382397895,
+           0.543380874711658,
+           0.5369809435944337,
+           0.5360612229435888,
+           0.5419991915729577,
+           0.5560379355948584,
+           0.5792496725110616,
+           0.6125029979361608,
+           0.6564347293185352,
+           0.7114271120852068,
+           0.7775910249646647,
+           0.8547556759815281,
+           0.942465122334523,
+           1.0399817799627928,
+           1.1462969162092638,
+           1.2601479458711096,
+           1.380042181381868,
+           1.5042865261137557,
+           1.631022449855135,
+           1.7582654511556213,
+           1.8839480958115369,
+           2.00596562719732,
+           2.122223074809795,
+           2.2306827440643384,
+           2.3294109542076304,
+           2.416622902667363,
+           2.4907245730391727,
+           2.550350669334812,
+           2.594397649546306,
+           2.622051044864337,
+           2.6328063843050833,
+           2.6264831948290306,
+           2.6032317106384975,
+           2.563532098247368,
+           2.5081861819232776,
+           2.4383018328757182,
+           2.35527036074637,
+           2.2607374132776745,
+           2.156568045408712,
+           2.0448067586798517,
+           1.9276334323096052,
+           1.8073161656947785,
+           1.686162125976226,
+           1.5664675419025897,
+           1.450468005353537,
+           1.3402902340637426,
+           1.2379064135153823,
+           1.1450921735155302,
+           1.0633891671782292,
+           0.9940731090424737,
+           0.9381279975953751,
+           0.8962270987540302,
+           0.86872110452843,
+           0.8556337091106294,
+           0.8566646672139558,
+           0.8712002209508504,
+           0.8983306062416976,
+           0.9368741819575265,
+           0.9854075687942945,
+           1.0423010440432086,
+           1.105758316363864,
+           1.1738597043225616,
+           1.2446076662249754,
+           1.3159735784519653,
+           1.385944636259819,
+           1.4525697553229735,
+           1.5140033839900064,
+           1.5685461944287575,
+           1.6146817040393775,
+           1.6511079845850727,
+           1.6767637427406097,
+           1.6908481990058266,
+           1.6928343485801312,
+           1.6824753539252264,
+           1.6598039902118962,
+           1.6251252373850382,
+           1.5790022819042182,
+           1.522236353130276,
+           1.4558409698303076,
+           1.3810113076554191,
+           1.2990895153841029,
+           1.2115269033616982,
+           1.119843999583297,
+           1.0255895155377392,
+           0.930299284164341,
+           0.8354562256450476,
+           0.742452363507886,
+           0.6525538545639178,
+           0.5668699130919583,
+           0.4863264045778276,
+           0.4116447599108411,
+           0.3433267204216121,
+           0.2816452710941569,
+           0.2266419575931803,
+           0.17813061651795484,
+           0.13570738173981378,
+           0.09876666701752661,
+           0.06652267042768194,
+           0.03803580340515797,
+           0.012243319968184632,
+           -0.012006686783172207,
+           -0.03591884081698005,
+           -0.06071257522757678,
+           -0.08758378152540577,
+           -0.11766704930793909,
+           -0.15199951474614096,
+           -0.19148729543114149,
+           -0.2368754230868734,
+           -0.28872209612620264,
+           -0.3473779632629812,
+           -0.4129710201795396,
+           -0.4853975568439722,
+           -0.5643194371153599,
+           -0.6491678287032869,
+           -0.7391533344920107,
+           -0.8332823099236372,
+           -0.9303789897694497,
+           -1.0291128952965716,
+           -1.128030853429752,
+           -1.2255928365681261,
+           -1.320210728389893,
+           -1.41028903992326,
+           -1.4942665434844162,
+           -1.5706577612818051,
+           -1.638093241413259,
+           -1.6953575768248248,
+           -1.7414241720702703,
+           -1.77548583725972,
+           -1.7969803866320628,
+           -1.8056105383555294,
+           -1.801357549549003,
+           -1.7844881727571773,
+           -1.7555546834619433,
+           -1.715387898641981,
+           -1.6650832796883106,
+           -1.605980384850673,
+           -1.5396361025590315,
+           -1.467792253298479,
+           -1.3923382903118622,
+           -1.3152699546902624,
+           -1.2386448452379166,
+           -1.1645359452126225,
+           -1.0949842045604636,
+           -1.03195130611714,
+           -0.9772737466252691,
+           -0.9326193381819456,
+           -0.8994471834277062,
+           -0.8789720996301008,
+           -0.8721343646525264,
+           -0.8795755340771005,
+           -0.9016209364478529,
+           -0.9382692961572625,
+           -0.9891897647316857,
+           -1.0537264652792773,
+           -1.1309104759291349,
+           -1.2194790005713108,
+           -1.3179013034321891,
+           -1.4244108221796001,
+           -1.5370427262977073,
+           -1.653676057016448,
+           -1.7720794753106603,
+           -1.8899595580812563,
+           -2.0050105217048935,
+           -2.114964218176101,
+           -2.2176392428943017,
+           -2.310988014912722,
+           -2.3931407396308586,
+           -2.462445239268385,
+           -2.5175017361577385,
+           -2.5571917954915113,
+           -2.5807007746809663,
+           -2.5875332824842503,
+           -2.5775213187306107,
+           -2.550824940702907,
+           -2.5079254807650133,
+           -2.449611517278467,
+           -2.376957972920381,
+           -2.2912988770065983,
+           -2.1941944773955435,
+           -2.087393519392635,
+           -1.9727916206119747,
+           -1.8523867593052024,
+           -1.7282329571308528,
+           -1.6023932742259217,
+           -1.4768932439265396,
+           -1.3536758564142455,
+           -1.2345591554670972,
+           -1.1211974415625283,
+           -1.0150469796399035,
+           -0.9173369933022996,
+           -0.8290465920630115,
+           -0.7508881278234545,
+           -0.6832973148729838,
+           -0.6264302783738539,
+           -0.58016752375447,
+           -0.5441246479714327,
+           -0.5176694474686984,
+           -0.4999449209709644,
+           -0.4898975218654537,
+           -0.4863098883783729,
+           -0.4878371731396944,
+           -0.49304600964905065,
+           -0.5004550936356483,
+           -0.508576323758137,
+           -0.5159554392768829,
+           -0.5212111123420171,
+           -0.5230714987958184,
+           -0.5204073226521497,
+           -0.5122606638285683,
+           -0.4978687338324563,
+           -0.47668205698890764,
+           -0.4483766220524917,
+           -0.41285972691893735,
+           -0.37026940363595495,
+           -0.32096747783389123,
+           -0.2655264818287348,
+           -0.20471079981393192,
+           -0.13945257272913741,
+           -0.07082302580373964,
+           -6.662089672192134e-16
+          ],
+          [
+           0,
+           0.07127429385754543,
+           0.14164017689371441,
+           0.20984567222110775,
+           0.2747012283537016,
+           0.33511555205822585,
+           0.3901288102684874,
+           0.43894230104054494,
+           0.48094378416937345,
+           0.5157277736352536,
+           0.5431102236891282,
+           0.5631371848514638,
+           0.5760871617435438,
+           0.5824670675636365,
+           0.5830018360465639,
+           0.578617916703749,
+           0.5704210388534046,
+           0.559668780364906,
+           0.5477386143331844,
+           0.5360922275676688,
+           0.5262370057369585,
+           0.5196856586556493,
+           0.5179150134891236,
+           0.5223250321480188,
+           0.5341991110523163,
+           0.5546666966355152,
+           0.5846691989704376,
+           0.6249301099238467,
+           0.6759301331082173,
+           0.7378880129990742,
+           0.8107476128520822,
+           0.8941716388636257,
+           0.9875422451179234,
+           1.0899685842739086,
+           1.200301196863149,
+           1.317152961764172,
+           1.4389261661230368,
+           1.5638450987992156,
+           1.689993431183116,
+           1.8153555264727215,
+           1.9378607163027664,
+           2.055429504579294,
+           2.166020604506977,
+           2.2676776875101763,
+           2.358574722791188,
+           2.4370588137185893,
+           2.50168949149586,
+           2.551273506366221,
+           2.584894260071747,
+           2.601935147926705,
+           2.6020962216845405,
+           2.5854037419215876,
+           2.55221235710828,
+           2.503199821797231,
+           2.4393543441617127,
+           2.361954829135127,
+           2.272544453338753,
+           2.1728981676931194,
+           2.064984869187101,
+           1.950925111170462,
+           1.8329453286145938,
+           1.7133296384335468,
+           1.594370333129016,
+           1.47831821729592,
+           1.3673339401363214,
+           1.2634414529919196,
+           1.1684846696118782,
+           1.0840883296805657,
+           1.0116239649293877,
+           0.9521817444264844,
+           0.9065488343802056,
+           0.8751947514628787,
+           0.8582640210813317,
+           0.8555762772840282,
+           0.8666337633664603,
+           0.8906360160480347,
+           0.92650134563591,
+           0.9728945640091161,
+           1.0282602654464494,
+           1.0908608358376148,
+           1.1588182567805352,
+           1.2301586850940087,
+           1.3028587274068206,
+           1.3748922951446627,
+           1.4442769181915682,
+           1.5091184158463538,
+           1.5676528708455655,
+           1.6182849249409113,
+           1.6596215109327241,
+           1.6905002537207363,
+           1.710011908870306,
+           1.71751635799115,
+           1.7126518421118873,
+           1.6953372831666507,
+           1.665767715483431,
+           1.6244030195111328,
+           1.5719503147214882,
+           1.5093405236015713,
+           1.4376997600914527,
+           1.3583163202440456,
+           1.2726041572461573,
+           1.1820638047031007,
+           1.088241769284893,
+           0.9926894451079893,
+           0.8969226068801136,
+           0.8023825168316467,
+           0.710399632425373,
+           0.6221608290579838,
+           0.5386809563391266,
+           0.46077943052337555,
+           0.3890624322509725,
+           0.32391113132936045,
+           0.2654762026111969,
+           0.21367873309918461,
+           0.16821745438928204,
+           0.12858207065448776,
+           0.09407229471719869,
+           0.06382205734294139,
+           0.03682822143528817,
+           0.011983016689732843,
+           -0.011890685596407087,
+           -0.03600221104166923,
+           -0.061555036163633184,
+           -0.08970888286536645,
+           -0.12154297502932937,
+           -0.15802144914064523,
+           -0.1999618556767096,
+           -0.24800760870157051,
+           -0.30260513968853536,
+           -0.3639863906184135,
+           -0.43215714391365245,
+           -0.5068915362382389,
+           -0.5877329434191825,
+           -0.6740012587635987,
+           -0.764806421027131,
+           -0.8590678854373289,
+           -0.9555395756177543,
+           -1.0528397099457865,
+           -1.1494847664834087,
+           -1.2439267394507334,
+           -1.3345927501196455,
+           -1.4199260083195784,
+           -1.4984270792147687,
+           -1.568694394752768,
+           -1.6294629606605981,
+           -1.6796402478733308,
+           -1.7183383209512908,
+           -1.7449013438643801,
+           -1.7589277133766152,
+           -1.7602861994774,
+           -1.7491256177162942,
+           -1.725877716331861,
+           -1.6912531278269685,
+           -1.6462304060109771,
+           -1.5920383412577033,
+           -1.5301319145522578,
+           -1.4621624106427693,
+           -1.3899423582880381,
+           -1.315406097503703,
+           -1.2405668865428872,
+           -1.1674715522551617,
+           -1.0981537541362758,
+           -1.0345869730930823,
+           -0.9786383496227096,
+           -0.9320244823271074,
+           -0.8962702567149117,
+           -0.8726717070136603,
+           -0.8622638218081853,
+           -0.8657940899256029,
+           -0.8837024488521046,
+           -0.9161081473292734,
+           -0.962803870285902,
+           -1.023257301884037,
+           -1.0966201253876278,
+           -1.1817442811106527,
+           -1.2772051301954692,
+           -1.3813310066452138,
+           -1.492238486923185,
+           -1.6078725692780464,
+           -1.726050837108514,
+           -1.8445105850260652,
+           -1.9609578151478426,
+           -2.0731169662932616,
+           -2.178780221263055,
+           -2.2758552476756484,
+           -2.362410265667867,
+           -2.436715400208466,
+           -2.4972793652443475,
+           -2.542880639209741,
+           -2.5725924238290574,
+           -2.5858008273954165,
+           -2.582215876159563,
+           -2.561875129147671,
+           -2.525139848449633,
+           -2.4726838544699055,
+           -2.4054753694865108,
+           -2.324752318889495,
+           -2.2319917136347023,
+           -2.1288738760154806,
+           -2.01724239047624,
+           -1.8990607589901722,
+           -1.776366814162633,
+           -1.6512259909637672,
+           -1.5256845787408866,
+           -1.4017240684816912,
+           -1.2812176764379755,
+           -1.1658900650913657,
+           -1.057281197606923,
+           -0.956715154544026,
+           -0.8652746143956324,
+           -0.7837815557079838,
+           -0.7127845817004497,
+           -0.6525531023779989,
+           -0.6030784382444494,
+           -0.5640817381317071,
+           -0.5350284356167319,
+           -0.5151488081636176,
+           -0.5034640544612562,
+           -0.4988171720875565,
+           -0.49990780288890924,
+           -0.5053301201184348,
+           -0.5136127616889223,
+           -0.5232597695320611,
+           -0.5327914770448535,
+           -0.5407842953171128,
+           -0.5459083839722794,
+           -0.5469622530586264,
+           -0.5429034269055374,
+           -0.532874407020281,
+           -0.5162232962166265,
+           -0.4925185870380044,
+           -0.46155777057520386,
+           -0.42336958309207534,
+           -0.37820987336979606,
+           -0.3265512391688357,
+           -0.26906674250016527,
+           -0.20660816641607566,
+           -0.14017941691051314,
+           -0.07090579870206312,
+           -6.643040434379734e-16
+          ],
+          [
+           0,
+           0.07057015787584578,
+           0.13967664327535328,
+           0.20610426854864297,
+           0.26871926222257425,
+           0.3265035137967913,
+           0.37858569031690414,
+           0.42426837949555096,
+           0.46305051646837153,
+           0.49464447280182877,
+           0.5189873240468834,
+           0.536245962481511,
+           0.5468158809086652,
+           0.551313617450373,
+           0.5505630160527043,
+           0.5455756187176065,
+           0.5375256592153501,
+           0.5277202702995965,
+           0.5175656436225095,
+           0.5085299903801584,
+           0.5021042384141113,
+           0.49976146578511477,
+           0.5029161100330435,
+           0.5128840053844415,
+           0.5308442866580695,
+           0.5578041588076057,
+           0.5945674658451456,
+           0.6417079038623059,
+           0.6995476121592696,
+           0.7681417468039139,
+           0.8472694954505657,
+           0.9364318345299063,
+           1.034856163869291,
+           1.1415077835244007,
+           1.2551080073209793,
+           1.3741585415517725,
+           1.4969715995855992,
+           1.6217050777612778,
+           1.746401988501773,
+           1.8690332363480704,
+           1.9875427343658805,
+           2.0998937943693425,
+           2.2041156862894673,
+           2.2983492508086982,
+           2.3808904654423713,
+           2.450230907256438,
+           2.505094124386636,
+           2.5444670218442056,
+           2.5676254825307887,
+           2.5741535791668704,
+           2.563955883709048,
+           2.537262544137113,
+           2.4946269702664505,
+           2.436916146305853,
+           2.3652937639459117,
+           2.2811965415346376,
+           2.1863042581810403,
+           2.0825041824354806,
+           1.971850709840318,
+           1.8565211388332126,
+           1.7387686073993223,
+           1.6208732812335407,
+           1.5050929263157367,
+           1.3936140136879362,
+           1.288504491487914,
+           1.1916693192483485,
+           1.1048097930950893,
+           1.0293875993943975,
+           0.9665944208361021,
+           0.9173277856738744,
+           0.8821737011335666,
+           0.8613964495041826,
+           0.8549357541122461,
+           0.862411346430656,
+           0.8831347892780563,
+           0.9161282387192057,
+           0.9601496630733416,
+           1.0137238853638129,
+           1.0751786792829028,
+           1.142685031591795,
+           1.2143005886437763,
+           1.288015233682885,
+           1.3617976964047662,
+           1.4336420780081036,
+           1.5016131839843763,
+           1.563889592891417,
+           1.6188034513667668,
+           1.6648760720569389,
+           1.700848519765629,
+           1.7257064992112938,
+           1.7386990021123079,
+           1.7393503282701046,
+           1.7274652609790906,
+           1.703127347329857,
+           1.6666904045601467,
+           1.6187635403167315,
+           1.560190133398094,
+           1.4920213683377028,
+           1.4154850484508457,
+           1.3319505244889853,
+           1.2428906670826398,
+           1.1498418785059488,
+           1.0543631813580547,
+           0.957995437556735,
+           0.8622217402645862,
+           0.7684299843684868,
+           0.6778785589143939,
+           0.5916660190965051,
+           0.5107054882343214,
+           0.4357044143962798,
+           0.36715016515926036,
+           0.30530179102542976,
+           0.2501881271378399,
+           0.2016122382240441,
+           0.15916204732317904,
+           0.12222682897376984,
+           0.09001909619676557,
+           0.06160127162177955,
+           0.0359164099813219,
+           0.011822135042709465,
+           -0.011873128514124913,
+           -0.03637260665223135,
+           -0.06285332307642341,
+           -0.09242896170934421,
+           -0.1261144459035566,
+           -0.16479319153993274,
+           -0.20918792233619538,
+           -0.2598358439808816,
+           -0.31706886143042934,
+           -0.38099939369287317,
+           -0.45151219595211745,
+           -0.5282624436094722,
+           -0.6106801706570816,
+           -0.6979809898514682,
+           -0.7891828585989219,
+           -0.8831284964432254,
+           -0.9785129115705014,
+           -1.073915358592889,
+           -1.1678349314893952,
+           -1.2587288970003567,
+           -1.3450527975311295,
+           -1.4253013007045,
+           -1.4980487464867902,
+           -1.5619883430355896,
+           -1.61596898915222,
+           -1.6590287538808681,
+           -1.6904241211405933,
+           -1.7096542074479955,
+           -1.7164792813551342,
+           -1.7109330512423366,
+           -1.6933283401805417,
+           -1.6642559289656762,
+           -1.624576517116659,
+           -1.5754059224401595,
+           -1.5180938084594409,
+           -1.4541963913831042,
+           -1.385443730302427,
+           -1.3137023421505738,
+           -1.2409340031736698,
+           -1.1691516982216714,
+           -1.1003737555404423,
+           -1.0365772559777156,
+           -0.9796518302638648,
+           -0.931354955605096,
+           -0.8932698332119177,
+           -0.8667668722307057,
+           -0.8529697241572828,
+           -0.8527267071196305,
+           -0.8665883339293476,
+           -0.8947915145421597,
+           -0.9372508460017069,
+           -0.9935572348901516,
+           -1.0629839228585787,
+           -1.1444998092072534,
+           -1.2367897900352705,
+           -1.3382816654383962,
+           -1.4471790087067453,
+           -1.5614992483098682,
+           -1.6791160881573948,
+           -1.7978052872527275,
+           -1.915292738971112,
+           -2.029303734770599,
+           -2.1376122685438887,
+           -2.238089236740379,
+           -2.3287484158596707,
+           -2.4077891522924517,
+           -2.473634778456805,
+           -2.5249658718166463,
+           -2.560747597162788,
+           -2.580250514460482,
+           -2.5830643911501414,
+           -2.5691047252056953,
+           -2.5386118594194946,
+           -2.492142744044933,
+           -2.4305555797819562,
+           -2.3549877418795613,
+           -2.2668275447505324,
+           -2.1676805510989308,
+           -2.0593312566518027,
+           -1.9437010880997585,
+           -1.8228037352338153,
+           -1.6986988965372294,
+           -1.5734455492922197,
+           -1.4490558598861532,
+           -1.3274508274143582,
+           -1.2104187045120343,
+           -1.0995771648941424,
+           -0.9963400892484491,
+           -0.9018897223957155,
+           -0.817154817994906,
+           -0.7427952359587745,
+           -0.6791932959353174,
+           -0.6264520217384276,
+           -0.5844002406677591,
+           -0.5526043324855396,
+           -0.5303862596062161,
+           -0.5168473568345898,
+           -0.5108972195334748,
+           -0.5112869068362619,
+           -0.51664557443092,
+           -0.5255195720088174,
+           -0.5364129856033585,
+           -0.547828576032035,
+           -0.558308062145714,
+           -0.5664707215618056,
+           -0.5710493313334387,
+           -0.5709225452599769,
+           -0.5651429013413349,
+           -0.5529597697237946,
+           -0.5338366853850737,
+           -0.5074626573452494,
+           -0.4737572036144334,
+           -0.43286902440267394,
+           -0.38516839118359164,
+           -0.3312334918442272,
+           -0.27183112825783096,
+           -0.2078923082412635,
+           -0.14048340532881493,
+           -0.07077367379341658,
+           -6.603983414639129e-16
+          ],
+          [
+           0,
+           0.06966117240342884,
+           0.13732287928104173,
+           0.2018165015114945,
+           0.2620728805525328,
+           0.3171546990722863,
+           0.36628526948944307,
+           0.4088729466067812,
+           0.4445304934778187,
+           0.4730888599791639,
+           0.4946049779798506,
+           0.5093633318548704,
+           0.5178712244687038,
+           0.5208478225735795,
+           0.5192072276784556,
+           0.5140359747385077,
+           0.5065655075227731,
+           0.49814031251157004,
+           0.4901825092619829,
+           0.4841537913849391,
+           0.481515686121691,
+           0.48368915006817537,
+           0.49201454255582416,
+           0.5077130158793752,
+           0.531850332945553,
+           0.5653040686391196,
+           0.6087350725461255,
+           0.6625639695319055,
+           0.7269533535031575,
+           0.8017961914544711,
+           0.8867108030074059,
+           0.9810426188404834,
+           1.083872753682728,
+           1.1940332600595223,
+           1.3101287619488575,
+           1.430564007088251,
+           1.5535767268730272,
+           1.6772750573559168,
+           1.7996786571989098,
+           1.9187625615109953,
+           2.03250273679271,
+           2.1389222535943655,
+           2.236136971256648,
+           2.322399633868631,
+           2.39614130831116,
+           2.456009153251185,
+           2.5008995908621108,
+           2.529986058899228,
+           2.542740647020379,
+           2.5389490648672255,
+           2.5187185469361673,
+           2.4824784668482254,
+           2.4309736071988635,
+           2.3652502065045686,
+           2.2866350775866136,
+           2.1967082578249824,
+           2.0972698070180043,
+           1.990301509298468,
+           1.8779243582415248,
+           1.7623528059494393,
+           1.6458468350235305,
+           1.5306629650181198,
+           1.4190053309228357,
+           1.3129779697985307,
+           1.2145394229298696,
+           1.1254607054544854,
+           1.047287614736937,
+           0.9813082447467113,
+           0.9285264489141595,
+           0.8896418514258085,
+           0.8650368501613274,
+           0.8547708872968302,
+           0.8585820900825477,
+           0.8758962086789849,
+           0.905842604483427,
+           0.9472768753193039,
+           0.998809547253844,
+           1.058840120452733,
+           1.1255956318168943,
+           1.197172793180318,
+           1.271582683069282,
+           1.34679691435023,
+           1.4207941708221437,
+           1.4916060035850782,
+           1.557360802817945,
+           1.6163249117386187,
+           1.666939925664021,
+           1.7078553182882803,
+           1.7379556570415575,
+           1.7563818066653807,
+           1.7625456715021866,
+           1.75613818866536,
+           1.7371304522036664,
+           1.7057680184262782,
+           1.662558610494698,
+           1.608253602061081,
+           1.543823811148682,
+           1.470430272903685,
+           1.389390779928178,
+           1.3021430787007824,
+           1.2102056876848954,
+           1.1151373552658714,
+           1.0184962024150803,
+           0.9217995953638378,
+           0.8264857676559263,
+           0.7338781594637916,
+           0.6451533663670846,
+           0.5613134918733764,
+           0.48316358033241374,
+           0.41129467256911906,
+           0.3460728789626423,
+           0.28763470758172993,
+           0.23588872233699124,
+           0.19052344204769245,
+           0.1510212299943381,
+           0.11667776901423847,
+           0.08662657339603289,
+           0.05986785936747133,
+           0.03530098411188095,
+           0.011759571810122622,
+           -0.011951623511854616,
+           -0.037019112816202425,
+           -0.06458333775801421,
+           -0.09570261312788941,
+           -0.13131931873259706,
+           -0.17222925524732569,
+           -0.21905499687470684,
+           -0.27222397047930375,
+           -0.33195186883652755,
+           -0.3982318678234421,
+           -0.4708299672668581,
+           -0.5492866165448224,
+           -0.6329246229222084,
+           -0.7208631771177022,
+           -0.8120376708898441,
+           -0.9052248295459476,
+           -0.999072542079855,
+           -1.092133646704553,
+           -1.1829028230576437,
+           -1.2698556570566935,
+           -1.3514888824759004,
+           -1.426360766430355,
+           -1.4931305950895057,
+           -1.5505962314480453,
+           -1.5977287585503466,
+           -1.6337032882313764,
+           -1.6579251056103135,
+           -1.6700504310694408,
+           -1.6700012115494507,
+           -1.6579734985019898,
+           -1.6344391271782583,
+           -1.6001405772130983,
+           -1.556079063594836,
+           -1.5034960758946707,
+           -1.4438487478669826,
+           -1.3787795951281514,
+           -1.3100813016865087,
+           -1.239657363041679,
+           -1.1694795012017183,
+           -1.1015428525553563,
+           -1.037819990900214,
+           -0.9802148834741463,
+           -0.930517886610652,
+           -0.890362869343883,
+           -0.8611875082952479,
+           -0.8441977265124133,
+           -0.8403371542674319,
+           -0.8502623734137696,
+           -0.8743245715501813,
+           -0.9125580812125087,
+           -0.96467611627243,
+           -1.0300738466257071,
+           -1.1078387772654732,
+           -1.1967682232238999,
+           -1.2953935018883878,
+           -1.4020103030084243,
+           -1.5147145482464788,
+           -1.6314429200224814,
+           -1.750017126890003,
+           -1.8681908825189502,
+           -1.9836985097540878,
+           -2.0943040417801835,
+           -2.1978496801220144,
+           -2.2923024843456727,
+           -2.3757982105403967,
+           -2.4466812839166487,
+           -2.5035399834908523,
+           -2.545236031576134,
+           -2.5709279148581548,
+           -2.5800874139306074,
+           -2.572508980630624,
+           -2.5483117733842477,
+           -2.5079343358774406,
+           -2.452122079440788,
+           -2.381907900312565,
+           -2.2985864252721555,
+           -2.2036825290731588,
+           -2.09891490102129,
+           -1.9861555527026773,
+           -1.86738625151819,
+           -1.7446529331077727,
+           -1.620019188343621,
+           -1.495519936358683,
+           -1.3731163837445668,
+           -1.2546533319561224,
+           -1.1418198311119205,
+           -1.0361140904282322,
+           -0.9388134457050848,
+           -0.8509500553693131,
+           -0.7732928518093218,
+           -0.7063361177310092,
+           -0.6502948919420901,
+           -0.6051072394454745,
+           -0.5704432512013132,
+           -0.5457204735996933,
+           -0.5301253106573012,
+           -0.5226397970815181,
+           -0.5220730111932245,
+           -0.5270962864255228,
+           -0.5362812914029562,
+           -0.5481399835954401,
+           -0.5611654017782526,
+           -0.5738722489268236,
+           -0.5848362299904214,
+           -0.5927311478198539,
+           -0.596362824319325,
+           -0.5946990009775606,
+           -0.5868944810551066,
+           -0.5723109020863754,
+           -0.5505306687682471,
+           -0.5213647291507368,
+           -0.48485403743783523,
+           -0.44126471058247957,
+           -0.3910770490709679,
+           -0.3349687507134446,
+           -0.2737927958875503,
+           -0.20855061974657751,
+           -0.1403613079456878,
+           -0.0704276544101138,
+           -6.545254592730593e-16
+          ],
+          [
+           0,
+           0.06855528044705994,
+           0.13459939925157874,
+           0.1970195437490407,
+           0.254819307652908,
+           0.30714895173965345,
+           0.3533316457934074,
+           0.3928849753900616,
+           0.42553711957651436,
+           0.45123724339164745,
+           0.47015979899625143,
+           0.4827025871412503,
+           0.4894785928108562,
+           0.491301771025346,
+           0.48916711686735237,
+           0.4842255037939379,
+           0.47775391240062753,
+           0.4711217944932968,
+           0.4657544214619642,
+           0.4630941488610244,
+           0.4645605886358582,
+           0.4715107150316562,
+           0.48519993893504926,
+           0.5067451679382488,
+           0.5370908261395532,
+           0.5769787396111326,
+           0.626922702205612,
+           0.6871884241508058,
+           0.7577794354392487,
+           0.838429370559239,
+           0.9286009042220649,
+           1.0274914432942253,
+           1.134045512219118,
+           1.2469736019810438,
+           1.364777090289219,
+           1.485778687193023,
+           1.6081577196226102,
+           1.7299894439138277,
+           1.849287470360177,
+           1.9640483008998417,
+           2.07229692231439,
+           2.1721323643149146,
+           2.261772125515425,
+           2.3395943907806287,
+           2.4041770103609394,
+           2.454332283514237,
+           2.489136685255804,
+           2.50795479218399,
+           2.5104567991776046,
+           2.496629169869357,
+           2.466778126504174,
+           2.421525855138186,
+           2.3617994759757783,
+           2.2888130017399257,
+           2.2040426750987945,
+           2.1091962352211318,
+           2.0061768096136983,
+           1.8970422569303438,
+           1.7839608962610831,
+           1.6691646458180869,
+           1.5549006567896755,
+           1.4433825648876555,
+           1.33674249186267,
+           1.236984911760867,
+           1.1459434523655152,
+           1.0652416321878841,
+           0.9962584392516437,
+           0.9400995420514597,
+           0.8975747882875922,
+           0.8691824965750302,
+           0.8551008839685045,
+           0.8551868017955678,
+           0.8689817781024962,
+           0.895725191236722,
+           0.9343742299451343,
+           0.983630134972036,
+           1.0419700693865679,
+           1.1076838333349444,
+           1.1789145267724535,
+           1.2537021736787137,
+           1.3300292554440811,
+           1.4058670610849489,
+           1.479221748612596,
+           1.5481790254988772,
+           1.610946396342656,
+           1.6658919914813295,
+           1.7115790797244612,
+           1.7467954793401927,
+           1.7705772111034066,
+           1.7822258823637827,
+           1.7813194480842252,
+           1.7677161597224254,
+           1.7415516815804066,
+           1.703229522642972,
+           1.6534050957984359,
+           1.5929638716383892,
+           1.5229942369433254,
+           1.4447557949706369,
+           1.3596439526663329,
+           1.2691517262971874,
+           1.1748297596655763,
+           1.0782455865395124,
+           0.9809431803513032,
+           0.8844038193874609,
+           0.7900092550628318,
+           0.6990081055406812,
+           0.6124863086391854,
+           0.5313423589377516,
+           0.4562679270617007,
+           0.3877343175226205,
+           0.3259850688282592,
+           0.271034839725346,
+           0.22267456245149936,
+           0.18048268187139474,
+           0.1438421424507533,
+           0.11196263713971105,
+           0.0839074971238822,
+           0.05862448246073433,
+           0.03497963384513718,
+           0.011793267650553952,
+           -0.012122858066465927,
+           -0.03792820836512307,
+           -0.06671697250349277,
+           -0.09948338467434328,
+           -0.1370898003866031,
+           -0.1802383930476315,
+           -0.22944724160834104,
+           -0.2850314665532174,
+           -0.3470899409208068,
+           -0.4154979587278039,
+           -0.4899060887898508,
+           -0.5697452813888901,
+           -0.6542381325936224,
+           -0.7424160504162292,
+           -0.833141912458485,
+           -0.9251376601890293,
+           -1.0170161441789525,
+           -1.1073164208441066,
+           -1.1945416074156945,
+           -1.2771983304049106,
+           -1.353836755604693,
+           -1.423090165939155,
+           -1.4837130578486892,
+           -1.534616757353532,
+           -1.5749016127840134,
+           -1.603884901078676,
+           -1.621123686603895,
+           -1.6264319931548568,
+           -1.6198917881757857,
+           -1.6018574298824568,
+           -1.5729533891389442,
+           -1.5340652246440043,
+           -1.4863239580843441,
+           -1.4310841612319571,
+           -1.3698962253797262,
+           -1.3044734310648027,
+           -1.2366545690248716,
+           -1.1683629784228757,
+           -1.1015629626524859,
+           -1.0382146140991204,
+           -0.9802281252505429,
+           -0.9294186833110791,
+           -0.8874630384068766,
+           -0.8558588016694643,
+           -0.8358874697046638,
+           -0.8285820875894524,
+           -0.8347003555949136,
+           -0.8547038578737278,
+           -0.8887439474367886,
+           -0.936654664359598,
+           -0.9979528971254282,
+           -1.0718458243921756,
+           -1.1572455004692763,
+           -1.2527902766559238,
+           -1.3568725865015272,
+           -1.4676724700162795,
+           -1.5831960736281807,
+           -1.7013182426378652,
+           -1.8198282240058956,
+           -1.9364774219449978,
+           -2.0490280988324745,
+           -2.1553018906347488,
+           -2.2532270099239433,
+           -2.3408830405768026,
+           -2.4165422856269787,
+           -2.478706712093328,
+           -2.526139641921575,
+           -2.5578914638828585,
+           -2.5733187843017085,
+           -2.572096591346225,
+           -2.554223174476772,
+           -2.520017713446022,
+           -2.470110625760205,
+           -2.4054269334988625,
+           -2.327163075663699,
+           -2.23675774677172,
+           -2.1358574824768652,
+           -2.0262778352111015,
+           -1.90996108423645,
+           -1.7889315026659656,
+           -1.6652492570897504,
+           -1.5409640421976296,
+           -1.418069552638267,
+           -1.2984598673731755,
+           -1.1838887687116693,
+           -1.0759329404280322,
+           -0.9759598888517838,
+           -0.8851013101265506,
+           -0.8042324889877679,
+           -0.733958162866008,
+           -0.6746051236626014,
+           -0.6262216621876021,
+           -0.5885837911518733,
+           -0.5612080159558709,
+           -0.5433702624360909,
+           -0.5341304211636312,
+           -0.5323618325148538,
+           -0.5367849188676389,
+           -0.5460040727917002,
+           -0.5585468353575237,
+           -0.5729043484742726,
+           -0.5875720406554086,
+           -0.6010895073320058,
+           -0.612078574661668,
+           -0.6192785889381988,
+           -0.6215780507847907,
+           -0.6180418123069995,
+           -0.6079331737425442,
+           -0.5907303508429965,
+           -0.5661369318248362,
+           -0.5340860994822498,
+           -0.4947385559863577,
+           -0.44847425090586485,
+           -0.39587817295130984,
+           -0.33772061882996707,
+           -0.2749324945441484,
+           -0.20857633189453512,
+           -0.139813812653109,
+           -0.06987068208679245,
+           -6.467365433000005e-16
+          ],
+          [
+           0,
+           0.06726212616199256,
+           0.1315298389923919,
+           0.19175474749192703,
+           0.24702057414312478,
+           0.29657106238894015,
+           0.3398334793462965,
+           0.3764370700226823,
+           0.40622595010956386,
+           0.42926606857766497,
+           0.4458460251499024,
+           0.45647168738494875,
+           0.46185471352557456,
+           0.46289524636058493,
+           0.4606591960811028,
+           0.45635067260051504,
+           0.45128025642467007,
+           0.4468299086211058,
+           0.444415411885582,
+           0.4454473037820257,
+           0.4512913081369734,
+           0.46322929010424513,
+           0.48242175401661547,
+           0.509872870894565,
+           0.5463989651214006,
+           0.5926013086831363,
+           0.648843968471534,
+           0.7152373299697621,
+           0.7916277821794108,
+           0.8775938973155719,
+           0.9724492783324953,
+           1.0752520817213254,
+           1.184821056356463,
+           1.299757775606429,
+           1.4184745835494168,
+           1.539227630854172,
+           1.6601542453482891,
+           1.7793137697854506,
+           1.8947309076880041,
+           2.004440549717975,
+           2.1065330095848873,
+           2.1991985811850325,
+           2.280770337992768,
+           2.3497641315416895,
+           2.404914807338757,
+           2.445207742309753,
+           2.4699049158400923,
+           2.478564854061104,
+           2.4710559311601425,
+           2.447562668673038,
+           2.4085848401321663,
+           2.3549293600432026,
+           2.2876951087649102,
+           2.208251014256419,
+           2.1182078736950776,
+           2.0193845486918436,
+           1.9137693035493446,
+           1.803477173394515,
+           1.69070434519376,
+           1.5776806072619485,
+           1.4666209701223725,
+           1.3596775822967697,
+           1.2588930582872944,
+           1.166156302800814,
+           1.0831618559645144,
+           1.0113737003330048,
+           0.9519943639368684,
+           0.9059400270695702,
+           0.8738221970411163,
+           0.8559363582434185,
+           0.8522578384002234,
+           0.8624449598731476,
+           0.8858493715558514,
+           0.9215332864312282,
+           0.968293186437322,
+           1.0246894038554701,
+           1.0890808506934981,
+           1.159664047817453,
+           1.234515506769892,
+           1.3116364416673734,
+           1.3889987380842477,
+           1.4645910815770236,
+           1.5364641510078234,
+           1.6027738109535863,
+           1.6618212924507978,
+           1.712089430700463,
+           1.7522741301232883,
+           1.7813103487405557,
+           1.798392032209541,
+           1.8029855795024332,
+           1.7948365834035116,
+           1.7739697557017944,
+           1.7406821150395773,
+           1.6955296806801836,
+           1.6393080738982082,
+           1.5730275763696804,
+           1.497883328220549,
+           1.415221464018689,
+           1.3265020801518186,
+           1.233259999421512,
+           1.1370643465741035,
+           1.0394779707684232,
+           0.9420177471749492,
+           0.8461167601895713,
+           0.7530893159521599,
+           0.664099653435666,
+           0.5801351233524014,
+           0.5019844850847415,
+           0.43022183683270393,
+           0.36519654662057094,
+           0.30702939546763064,
+           0.2556149828666414,
+           0.21063028280596613,
+           0.17154908000823868,
+           0.1376618648416701,
+           0.10810062530166266,
+           0.0818678490880217,
+           0.05786894127118217,
+           0.034947176052697745,
+           0.011920236864633829,
+           -0.012382640870181667,
+           -0.03908392458321694,
+           -0.06922242617234806,
+           -0.10372028303505632,
+           -0.14335317019518365,
+           -0.188724551286428,
+           -0.24024467144280653,
+           -0.29811487227862404,
+           -0.362317671225459,
+           -0.43261289801930874,
+           -0.5085400238789559,
+           -0.58942665786685,
+           -0.6744030241557386,
+           -0.7624220775140643,
+           -0.8522847662415699,
+           -0.9426698157998847,
+           -1.0321672859577145,
+           -1.1193150524870914,
+           -1.2026372839225885,
+           -1.2806839267159373,
+           -1.35207017978842,
+           -1.41551493288603,
+           -1.469877162516892,
+           -1.5141893241863835,
+           -1.5476868490903677,
+           -1.5698329457135678,
+           -1.5803380196658576,
+           -1.5791731558118864,
+           -1.5665772520952053,
+           -1.5430575508411217,
+           -1.5093834768735128,
+           -1.4665738584430648,
+           -1.4158777725944518,
+           -1.3587494170705903,
+           -1.296817562154796,
+           -1.2318502741965085,
+           -1.1657157244766754,
+           -1.1003399994678265,
+           -1.0376629088315532,
+           -0.9795928436137555,
+           -0.9279617675825677,
+           -0.8844814286708911,
+           -0.850701854854872,
+           -0.8279731499983622,
+           -0.8174115313455013,
+           -0.8198704531931813,
+           -0.8359175431439845,
+           -0.865817941071432,
+           -0.9095244798170422,
+           -0.9666749843480043,
+           -1.0365967965808451,
+           -1.1183184604494865,
+           -1.2105883302765603,
+           -1.3118996992846759,
+           -1.4205218882230044,
+           -1.5345365904238362,
+           -1.6518786426624406,
+           -1.7703802840839158,
+           -1.8878178808112982,
+           -2.0019600337401595,
+           -2.1106159529362705,
+           -2.211682974828029,
+           -2.303192118210165,
+           -2.383350621473382,
+           -2.4505804753199154,
+           -2.5035520607665385,
+           -2.5412121191462393,
+           -2.562805416244968,
+           -2.5678896133466864,
+           -2.556343020133656,
+           -2.5283650741444026,
+           -2.4844695646912633,
+           -2.4254707915637232,
+           -2.3524630162972917,
+           -2.2667937222002985,
+           -2.1700313448591952,
+           -2.0639282639638425,
+           -1.9503799568920352,
+           -1.831381301934416,
+           -1.7089810822433447,
+           -1.5852357790656715,
+           -1.4621637537189294,
+           -1.3417009018969919,
+           -1.2256588217074764,
+           -1.11568646945858,
+           -1.0132361863550243,
+           -0.9195348672353162,
+           -0.8355609121045857,
+           -0.7620274557563388,
+           -0.6993722138651756,
+           -0.6477541194773269,
+           -0.6070567559128882,
+           -0.576898424883292,
+           -0.5566485262554624,
+           -0.5454497723646632,
+           -0.542245618868532,
+           -0.5458121692998765,
+           -0.5547937047631816,
+           -0.5677409061948464,
+           -0.5831507762899829,
+           -0.5995072330146393,
+           -0.6153213373672377,
+           -0.62917013487492,
+           -0.6397331327058816,
+           -0.6458255011068904,
+           -0.6464271773869463,
+           -0.6407071605503335,
+           -0.6280424121172191,
+           -0.6080309204039608,
+           -0.5804986379636305,
+           -0.5455001611416971,
+           -0.5033131827495583,
+           -0.4544269096024265,
+           -0.3995247920488105,
+           -0.33946205871755847,
+           -0.27523868284359365,
+           -0.20796852335356691,
+           -0.1388454814596546,
+           -0.06910758937254394,
+           -6.370996208495486e-16
+          ],
+          [
+           0,
+           0.06579294360227668,
+           0.12814069337503048,
+           0.18606719804808597,
+           0.23874286154378901,
+           0.28550988846069225,
+           0.3259028823722226,
+           0.3596641304588447,
+           0.38675314587664983,
+           0.4073501883393053,
+           0.42185363988067104,
+           0.43087127270952574,
+           0.43520560541293374,
+           0.4358336984694333,
+           0.4338818861686195,
+           0.4305960758822677,
+           0.4273083637806991,
+           0.4254008155136853,
+           0.4262673385210928,
+           0.4312746274786731,
+           0.44172319447475594,
+           0.4588095000288747,
+           0.4835901798180443,
+           0.5169493154309109,
+           0.5595696267191164,
+           0.6119083700623239,
+           0.6741786133782355,
+           0.7463364277721849,
+           0.828074390555111,
+           0.9188216385491507,
+           1.017750548005025,
+           1.1237899521118788,
+           1.2356446431019745,
+           1.3518207474296877,
+           1.4706564133997069,
+           1.590357114671596,
+           1.7090347536970063,
+           1.8247496493680833,
+           1.9355544155086557,
+           2.039538683317417,
+           2.1348735928768376,
+           2.219854977144899,
+           2.292944186573641,
+           2.3528055531200587,
+           2.398339567762067,
+           2.428710943923615,
+           2.443370858097746,
+           2.442072795572082,
+           2.4248815802034063,
+           2.392175328992054,
+           2.344640240836939,
+           2.2832583001991096,
+           2.209288146283734,
+           2.124239522615839,
+           2.029841876515271,
+           1.9280078191843741,
+           1.820792281445958,
+           1.7103483045591379,
+           1.5988804874310574,
+           1.4885971689191289,
+           1.3816624553647874,
+           1.2801492082348689,
+           1.1859940846429309,
+           1.1009556751093925,
+           1.026576709370582,
+           0.9641512041506589,
+           0.914697308928344,
+           0.8789364697348784,
+           0.8572793802274763,
+           0.8498190273699204,
+           0.8563309699661584,
+           0.8762808161537641,
+           0.9088386949636207,
+           0.9529003513502357,
+           1.007114337720095,
+           1.06991463172648,
+           1.1395578834258095,
+           1.2141643878585526,
+           1.29176179429733,
+           1.3703305028169241,
+           1.4478496639083782,
+           1.5223426883728213,
+           1.59192119282834,
+           1.6548263503310494,
+           1.7094666846926936,
+           1.7544514393060477,
+           1.7886187643316125,
+           1.8110580971133834,
+           1.8211262563985764,
+           1.81845692770091,
+           1.802963381070039,
+           1.7748344295418783,
+           1.734523802510991,
+           1.6827332690859642,
+           1.620389998198666,
+           1.548618781109678,
+           1.4687098645835654,
+           1.382083246408572,
+           1.2902503666000114,
+           1.1947741855953453,
+           1.0972286736565833,
+           0.9991587428035149,
+           0.9020416338162125,
+           0.8072507267195048,
+           0.7160226748795391,
+           0.6294286721883736,
+           0.5483505521270182,
+           0.4734622896180534,
+           0.40521733476821054,
+           0.3438420554648148,
+           0.28933540718616735,
+           0.24147478732936095,
+           0.19982787191951001,
+           0.16377007876591734,
+           0.13250715684986714,
+           0.10510227059855938,
+           0.08050683301865005,
+           0.05759424631216011,
+           0.03519563496989751,
+           0.012136606276842921,
+           -0.012725952080302739,
+           -0.040468027417149284,
+           -0.07206455496188142,
+           -0.10835832238195214,
+           -0.15003254616928002,
+           -0.1975878646476726,
+           -0.2513243776958659,
+           -0.311329232319743,
+           -0.3774701092721881,
+           -0.44939481265111086,
+           -0.5265370056857899,
+           -0.6081279757689427,
+           -0.6932141542666869,
+           -0.7806799657386894,
+           -0.8692754407611102,
+           -0.9576479001426015,
+           -1.0443769091863044,
+           -1.1280116115775827,
+           -1.20710948576657,
+           -1.2802755241070791,
+           -1.3462008176474698,
+           -1.4036995378517332,
+           -1.4517433405223952,
+           -1.4894922760211768,
+           -1.5163213721350646,
+           -1.531842159622031,
+           -1.5359185330589533,
+           -1.5286764780934552,
+           -1.5105073471570207,
+           -1.4820645253951739,
+           -1.4442534930522886,
+           -1.3982154557249784,
+           -1.3453048756550294,
+           -1.2870613915305364,
+           -1.22517675724036,
+           -1.161457558090917,
+           -1.0977845729180196,
+           -1.0360697395240437,
+           -0.9782117466692761,
+           -0.9260513167423234,
+           -0.8813272581375607,
+           -0.8456343548278019,
+           -0.8203841228401806,
+           -0.806769400174325,
+           -0.8057336496239046,
+           -0.8179457450479555,
+           -0.8437808835016919,
+           -0.8833081213707319,
+           -0.9362848757530235,
+           -1.002158566611355,
+           -1.0800754047107712,
+           -1.1688961592183351,
+           -1.2672185712565212,
+           -1.3734059197645911,
+           -1.4856210976486857,
+           -1.60186542302726,
+           -1.7200212956697079,
+           -1.8378977152988012,
+           -1.953277608579711,
+           -2.063965867069374,
+           -2.167836980253294,
+           -2.2628811565069036,
+           -2.3472478601852873,
+           -2.419285754212707,
+           -2.4775781230273735,
+           -2.5209729584553475,
+           -2.54860701841557,
+           -2.5599233121918945,
+           -2.554681622839699,
+           -2.532961843301308,
+           -2.4951600739394406,
+           -2.441977601292899,
+           -2.3744030467246766,
+           -2.2936881351639813,
+           -2.201317684418225,
+           -2.098974550907598,
+           -1.9885003848815828,
+           -1.8718531443919049,
+           -1.7510623902176485,
+           -1.6281834318380075,
+           -1.505251416317003,
+           -1.3842364471356927,
+           -1.267000788770631,
+           -1.155259156009966,
+           -1.05054300608665,
+           -0.9541696487483565,
+           -0.8672168669718364,
+           -0.7905036022351456,
+           -0.7245771065527715,
+           -0.6697068026351669,
+           -0.6258849275520546,
+           -0.5928338682729986,
+           -0.5700199335598981,
+           -0.556673149938805,
+           -0.5518125237405682,
+           -0.5542760800476436,
+           -0.5627548760236657,
+           -0.5758300932896955,
+           -0.5920122439860933,
+           -0.6097814795891497,
+           -0.6276279714921191,
+           -0.6440913382281652,
+           -0.6577981257775763,
+           -0.6674964037926944,
+           -0.6720866203016904,
+           -0.6706479584479,
+           -0.6624595584870174,
+           -0.6470161035412176,
+           -0.6240374150518557,
+           -0.593471859737196,
+           -0.5554935301998352,
+           -0.510493322084902,
+           -0.4590641878055758,
+           -0.4019809963637855,
+           -0.34017556693492174,
+           -0.27470756717925715,
+           -0.20673207258993087,
+           -0.1374646679426474,
+           -0.06814503395082099,
+           -6.256987676951096e-16
+          ],
+          [
+           0,
+           0.064160430353985,
+           0.12446102728857157,
+           0.180005233383312,
+           0.23005581053202764,
+           0.2740574408039523,
+           0.31165428383462684,
+           0.34270200531206324,
+           0.3672739347883709,
+           0.3856611636793367,
+           0.3983665520487103,
+           0.4060927716133755,
+           0.40972466832230353,
+           0.41030637689824523,
+           0.40901375809768076,
+           0.40712285361698697,
+           0.40597516037906434,
+           0.40694061263533077,
+           0.4113792246747918,
+           0.4206023872646787,
+           0.4358348261761996,
+           0.45817822082284504,
+           0.48857744534619185,
+           0.5277903342503981,
+           0.5763617913530933,
+           0.6346029564101033,
+           0.7025760208387813,
+           0.7800851455327377,
+           0.8666737832462884,
+           0.9616285491560949,
+           1.0639896199231262,
+           1.1725674779421305,
+           1.2859656575581069,
+           1.4026089978461789,
+           1.520776765906327,
+           1.63863988905274,
+           1.7543014269483674,
+           1.865839328371874,
+           1.971350454116313,
+           2.0689948091466124,
+           2.157038914615679,
+           2.2338972640484993,
+           2.2981708476939766,
+           2.348681793816983,
+           2.384503264038134,
+           2.404983849622438,
+           2.4097658442323344,
+           2.3987969129901914,
+           2.3723348342412103,
+           2.3309451553650544,
+           2.2754917733350144,
+           2.207120620335271,
+           2.127236800474842,
+           2.037475681427096,
+           1.9396685908107378,
+           1.8358038977331796,
+           1.7279843719336903,
+           1.6183818036389206,
+           1.5091899343450996,
+           1.4025767906128925,
+           1.3006375285642808,
+           1.2053488857086985,
+           1.1185262992556482,
+           1.041784687095682,
+           0.976503800679151,
+           0.9237989502070925,
+           0.8844977745207991,
+           0.8591235839554848,
+           0.8478856477212956,
+           0.8506766319108013,
+           0.8670772240370328,
+           0.8963678092248725,
+           0.9375468959666319,
+           0.989355829774677,
+           1.050309184993537,
+           1.1187300920584795,
+           1.1927896428199911,
+           1.2705494229542564,
+           1.350006150187273,
+           1.4291373517395285,
+           1.5059469950963116,
+           1.578509993334151,
+           1.6450145395426585,
+           1.7038012834873715,
+           1.753398446055548,
+           1.7925520711231568,
+           1.8202507376572923,
+           1.8357441940379735,
+           1.8385555282738784,
+           1.8284866482222437,
+           1.8056170111214487,
+           1.7702957076136343,
+           1.7231271678749631,
+           1.6649509124776962,
+           1.5968159143693237,
+           1.5199502673454104,
+           1.435726967464715,
+           1.3456267043101058,
+           1.2511986266576556,
+           1.1540200903717115,
+           1.0556564141995806,
+           0.95762166123401,
+           0.8613414304263433,
+           0.7681185845846078,
+           0.6791027603059829,
+           0.5952644033726502,
+           0.5173739529024612,
+           0.4459866620639559,
+           0.3814333958871419,
+           0.3238175913647184,
+           0.2730184055767777,
+           0.22869991801574585,
+           0.190326097664595,
+           0.15718109761263516,
+           0.1283943037997123,
+           0.10296944328607176,
+           0.07981695429563072,
+           0.05778873776186371,
+           0.035714350283858526,
+           0.012437662768208412,
+           -0.013147001526754475,
+           -0.04206022106319576,
+           -0.07520525402975317,
+           -0.11333910847513012,
+           -0.1570476868357197,
+           -0.2067256810718945,
+           -0.2625617711386599,
+           -0.32452954171759096,
+           -0.3923843835174359,
+           -0.4656664897738327,
+           -0.5437098997880189,
+           -0.6256573834649858,
+           -0.7104808078488614,
+           -0.7970064824929621,
+           -0.883944848812094,
+           -0.9699237627044089,
+           -1.0535245226642396,
+           -1.1333197198328593,
+           -1.207911933916307,
+           -1.2759722710226065,
+           -1.3362777370030645,
+           -1.3877464629556908,
+           -1.4294698476544934,
+           -1.4607407536700359,
+           -1.4810769881062784,
+           -1.4902394129008443,
+           -1.4882441607229866,
+           -1.475368577425783,
+           -1.4521506671836713,
+           -1.419381978027254,
+           -1.378094029459178,
+           -1.3295385461143652,
+           -1.2751619179641616,
+           -1.2165744544400683,
+           -1.1555151333826055,
+           -1.0938126625418336,
+           -1.0333437685127456,
+           -0.9759897030067272,
+           -0.9235920073087269,
+           -0.8779086013091509,
+           -0.8405712629178604,
+           -0.8130455368956861,
+           -0.7965940597562248,
+           -0.7922442106099241,
+           -0.8007608984611378,
+           -0.8226251769049124,
+           -0.8580192402842929,
+           -0.9068182044734013,
+           -0.9685889142093911,
+           -1.0425958512314302,
+           -1.1278140474848217,
+           -1.2229487394644045,
+           -1.3264613375155812,
+           -1.4366011315562648,
+           -1.5514420159614486,
+           -1.6689233946680953,
+           -1.786894325899926,
+           -1.9031598867799084,
+           -2.015528683443006,
+           -2.1218604034349062,
+           -2.2201123049039047,
+           -2.308383561432769,
+           -2.384956431733535,
+           -2.4483332986214723,
+           -2.4972687198684627,
+           -2.530795752320189,
+           -2.548245947153382,
+           -2.549262565022108,
+           -2.5338067214189164,
+           -2.50215634092037,
+           -2.454897969996629,
+           -2.3929116675782836,
+           -2.3173493564677883,
+           -2.229607172976345,
+           -2.131292493117731,
+           -2.0241864378878347,
+           -1.9102027646067918,
+           -1.791344133492413,
+           -1.6696567966109448,
+           -1.5471847887548478,
+           -1.425924705896393,
+           -1.3077821365785665,
+           -1.1945307654975528,
+           -1.0877750978045737,
+           -0.9889176591135028,
+           -0.8991314122066287,
+           -0.8193379998471807,
+           -0.7501922772223942,
+           -0.6920734409911976,
+           -0.6450828985873628,
+           -0.6090488553814773,
+           -0.5835374326424515,
+           -0.5678699700254309,
+           -0.5611460164692375,
+           -0.5622713765916176,
+           -0.5699904592723293,
+           -0.5829220740449657,
+           -0.5995977416242977,
+           -0.6185015292757778,
+           -0.6381103910933871,
+           -0.6569339882724112,
+           -0.673552985184592,
+           -0.6866548628840817,
+           -0.6950663613675071,
+           -0.6977817536607889,
+           -0.6939862662421967,
+           -0.6830740885805179,
+           -0.664660556399029,
+           -0.6385882450651743,
+           -0.6049268674055605,
+           -0.5639670302610498,
+           -0.5162080621861315,
+           -0.46234027687317586,
+           -0.40322217931209586,
+           -0.33985325079588097,
+           -0.273343061407775,
+           -0.20487755175219935,
+           -0.1356833970851833,
+           -0.0669914148761949,
+           -6.126331205960263e-16
+          ],
+          [
+           0,
+           0.062378607465131485,
+           0.12052216311888517,
+           0.17361993500512274,
+           0.22103180027299058,
+           0.26230794636251104,
+           0.29720328062885193,
+           0.3256861470223724,
+           0.3479410965533025,
+           0.36436561308263793,
+           0.37556085357134433,
+           0.382316618292487,
+           0.38559091769706044,
+           0.3864846447827274,
+           0.386211991327286,
+           0.3860673599115156,
+           0.3873896183621991,
+           0.391524616659068,
+           0.399786936564186,
+           0.4134218699239363,
+           0.4335686220509684,
+           0.46122571173698346,
+           0.497219489832792,
+           0.5421766251370361,
+           0.5965013113298505,
+           0.6603578341927298,
+           0.7336590071835883,
+           0.8160608388221164,
+           0.9069636408635318,
+           1.005519625731383,
+           1.1106468791338646,
+           1.2210494332547002,
+           1.3352430113996576,
+           1.4515858703629756,
+           1.5683140356871477,
+           1.6835801107290966,
+           1.7954947459102877,
+           1.9021697821287764,
+           2.001762033915358,
+           2.0925166548008063,
+           2.172809030180356,
+           2.241184171728428,
+           2.296392641502925,
+           2.3374221120289307,
+           2.3635237690142903,
+           2.374232883520791,
+           2.3693830174973414,
+           2.3491134772571853,
+           2.313869790089841,
+           2.264397145830418,
+           2.201726913799171,
+           2.127156511954226,
+           2.042223065298099,
+           1.9486714406205488,
+           1.8484173808662576,
+           1.7435065814421884,
+           1.636070649699601,
+           1.5282809652038292,
+           1.422301510355712,
+           1.3202417671635074,
+           1.2241107758249978,
+           1.135773424252004,
+           1.0569099853876007,
+           0.9889798423927926,
+           0.9331902423780775,
+           0.8904707997433342,
+           0.8614543332787107,
+           0.8464644703042808,
+           0.845510289962564,
+           0.8582881102513716,
+           0.8841903535739856,
+           0.922321257622182,
+           0.9715190363790553,
+           1.0303839438683204,
+           1.0973115546743177,
+           1.1705304535657313,
+           1.2481434247107006,
+           1.3281711514161958,
+           1.408597381953761,
+           1.487414487145601,
+           1.5626683316484735,
+           1.6325014033154719,
+           1.6951931930195951,
+           1.7491968896440535,
+           1.7931715497417062,
+           1.826009016249505,
+           1.8468549927329954,
+           1.855123825631746,
+           1.8505067032447162,
+           1.832973142853866,
+           1.8027658024051598,
+           1.7603888164688364,
+           1.7065900137576866,
+           1.64233752141666,
+           1.5687913959800899,
+           1.4872710390319783,
+           1.3992192543255662,
+           1.3061638800353383,
+           1.2096779830893223,
+           1.1113396309155723,
+           1.012692258810354,
+           0.9152066285091771,
+           0.820245326063925,
+           0.7290306760668556,
+           0.6426168564676443,
+           0.5618668860955446,
+           0.48743502839525066,
+           0.41975501308984203,
+           0.35903432609852987,
+           0.3052546608960404,
+           0.25817846557776086,
+           0.21736136320144125,
+           0.1821700724620712,
+           0.1518053152102943,
+           0.1253290702800453,
+           0.10169542273789482,
+           0.07978416677192707,
+           0.05843625127644831,
+           0.03649011148649629,
+           0.01281790890710789,
+           -0.013639294219125712,
+           -0.04383837067480583,
+           -0.07860386579998696,
+           -0.11860145222052257,
+           -0.16431582013792545,
+           -0.2160336059991555,
+           -0.2738318312605834,
+           -0.33757217962067365,
+           -0.40690128915183127,
+           -0.4812570790630297,
+           -0.5598809733434021,
+           -0.6418357292673331,
+           -0.7260284316010512,
+           -0.8112380770807511,
+           -0.8961470518046899,
+           -0.9793756997119766,
+           -1.0595190959887602,
+           -1.1351850772261542,
+           -1.205032542073441,
+           -1.2678090230062937,
+           -1.322386542059638,
+           -1.3677948007194496,
+           -1.4032508157578925,
+           -1.4281841971536104,
+           -1.4422573693116971,
+           -1.4453801600117098,
+           -1.437718319833503,
+           -1.419695684821959,
+           -1.3919898531355908,
+           -1.3555214084564606,
+           -1.3114368849853861,
+           -1.2610858268634508,
+           -1.2059924448958357,
+           -1.147822511744028,
+           -1.0883462598179208,
+           -1.0293981508309313,
+           -0.9728344697181307,
+           -0.9204897562131078,
+           -0.874133123256814,
+           -0.8354255216019012,
+           -0.8058789941453941,
+           -0.7868189219782018,
+           -0.7793501978271853,
+           -0.7843281730423662,
+           -0.8023351136828328,
+           -0.8336627722383307,
+           -0.8783015372069067,
+           -0.9359364666322689,
+           -1.0059503475841716,
+           -1.0874337554409559,
+           -1.1792019188097045,
+           -1.2798180321042842,
+           -1.387622502204918,
+           -1.5007674720590276,
+           -1.617255836073665,
+           -1.7349838528408161,
+           -1.8517863728171475,
+           -1.9654836342168573,
+           -2.073928541161844,
+           -2.175053325044109,
+           -2.266914503428345,
+           -2.34773509034719,
+           -2.4159430765665033,
+           -2.4702052867549145,
+           -2.5094558303341974,
+           -2.5329184914411575,
+           -2.540122547765604,
+           -2.5309116645263474,
+           -2.505445674695675,
+           -2.4641952257677358,
+           -2.4079294427689355,
+           -2.3376969227077624,
+           -2.254800533235401,
+           -2.160766634112882,
+           -2.0573094706228923,
+           -1.9462916001711077,
+           -1.82968130429516,
+           -1.7095080059633843,
+           -1.5878167547989128,
+           -1.4666228597217517,
+           -1.3478677391118723,
+           -1.2333770232569654,
+           -1.124821883492983,
+           -1.0236844786213883,
+           -0.9312283040163584,
+           -0.848474104961233,
+           -0.7761818762765681,
+           -0.7148393186987596,
+           -0.6646569625083331,
+           -0.6255700045584848,
+           -0.5972467401840231,
+           -0.5791033105454977,
+           -0.5703243327467205,
+           -0.5698888383211687,
+           -0.5766008188849517,
+           -0.5891235689943636,
+           -0.6060169281624359,
+           -0.6257764586999769,
+           -0.6468735550992276,
+           -0.6677954650104861,
+           -0.6870842117805631,
+           -0.7033734436945754,
+           -0.7154222945292367,
+           -0.7221454222212583,
+           -0.7226384952496779,
+           -0.716198517086206,
+           -0.7023385146991824,
+           -0.6807962641546966,
+           -0.6515368811121117,
+           -0.6147492625448419,
+           -0.5708365243253974,
+           -0.5204007334036059,
+           -0.46422237929721716,
+           -0.40323516383192415,
+           -0.33849680714103914,
+           -0.2711566688757499,
+           -0.20242106385631928,
+           -0.1335172090062157,
+           -0.06565677192051629,
+           -5.98015746042169e-16
+          ],
+          [
+           0,
+           0.060462667222213204,
+           0.11635734816261238,
+           0.16696459563095348,
+           0.21174520650157475,
+           0.2503568968710826,
+           0.2826654873316012,
+           0.30875028322224085,
+           0.3289034859256346,
+           0.3436236268915362,
+           0.3536031721498256,
+           0.35971059766074953,
+           0.3629673810655385,
+           0.3645204895524387,
+           0.3656110632231732,
+           0.36754009547485134,
+           0.371631993881858,
+           0.3791969647541121,
+           0.3914932004020829,
+           0.40968985919137263,
+           0.4348318143780277,
+           0.46780710876812603,
+           0.5093179893535955,
+           0.5598563107548005,
+           0.6196839906281388,
+           0.6888190767664873,
+           0.7670278474742632,
+           0.8538232173540314,
+           0.9484695636044854,
+           1.0499939272048033,
+           1.1572033829524941,
+           1.268708216237644,
+           1.3829503965829752,
+           1.4982367020684078,
+           1.6127757282136466,
+           1.7247179127617536,
+           1.8321976266892144,
+           1.9333763237463986,
+           2.026485707421666,
+           2.109869866330271,
+           2.1820253469347026,
+           2.241638175845896,
+           2.28761691174603,
+           2.3191208976176756,
+           2.335582995297809,
+           2.336726213720892,
+           2.3225737864456257,
+           2.2934524096754663,
+           2.249988515197364,
+           2.193097619496617,
+           2.123966956683427,
+           2.044031764718444,
+           1.9549457477858532,
+           1.858546378771981,
+           1.7568158311997741,
+           1.6518384365614984,
+           1.5457556481578043,
+           1.440719554189045,
+           1.3388460194259497,
+           1.2421685453977809,
+           1.1525939233972764,
+           1.0718607130772166,
+           1.0015015130011329,
+           0.9428098998177469,
+           0.8968128019333085,
+           0.8642489443515775,
+           0.8455538568832217,
+           0.8408517817116893,
+           0.8499546521457526,
+           0.8723681462863097,
+           0.9073046513780875,
+           0.9537028108904613,
+           1.0102531708540434,
+           1.0754292984444604,
+           1.1475236177286252,
+           1.2246870979650621,
+           1.304971841514386,
+           1.3863755533805757,
+           1.46688683420642,
+           1.5445302241131011,
+           1.6174099363961383,
+           1.6837512574193612,
+           1.7419386511045782,
+           1.7905496916117642,
+           1.828384053988972,
+           1.8544869170786071,
+           1.8681662726846886,
+           1.8690037864550026,
+           1.856859015350132,
+           1.8318669500074474,
+           1.794429013721222,
+           1.7451978091177256,
+           1.6850560549844713,
+           1.6150902953992206,
+           1.5365600878791406,
+           1.450863483698133,
+           1.3594996992225088,
+           1.2640299400341344,
+           1.1660373782591311,
+           1.0670872970188472,
+           0.9686884040165854,
+           0.8722562793489433,
+           0.7790798616891734,
+           0.690291793632213,
+           0.6068433433741395,
+           0.529484498681804,
+           0.45874969338449195,
+           0.3949494798394017,
+           0.3381683067073737,
+           0.2882684038227784,
+           0.24489961892951623,
+           0.20751489854161567,
+           0.1753909610108523,
+           0.14765357766968557,
+           0.12330676098462921,
+           0.10126505993413362,
+           0.0803880847863042,
+           0.05951632804261836,
+           0.03750731691071473,
+           0.013271126043317403,
+           -0.014195702421801105,
+           -0.04577874174517634,
+           -0.08221761052966427,
+           -0.1240820061135073,
+           -0.1717524906200974,
+           -0.2254065549792318,
+           -0.2850103487709208,
+           -0.3503163161921553,
+           -0.42086682454910257,
+           -0.49600371533303245,
+           -0.5748835531135286,
+           -0.6564981981070176,
+           -0.7397001881485663,
+           -0.8232322884775685,
+           -0.905760456491427,
+           -0.9859093762744444,
+           -1.0622996466476509,
+           -1.1335856585541952,
+           -1.1984931740599807,
+           -1.2558556207656724,
+           -1.3046481420215146,
+           -1.344018494408728,
+           -1.373313958283638,
+           -1.3921035229713772,
+           -1.4001947231014844,
+           -1.3976446337720705,
+           -1.3847646764723298,
+           -1.3621190414125464,
+           -1.3305166912888535,
+           -1.2909970725797957,
+           -1.244809819215377,
+           -1.1933888859069115,
+           -1.1383216907568399,
+           -1.0813139754023515,
+           -1.0241512026399346,
+           -0.9686574033963724,
+           -0.9166524547077878,
+           -0.8699088162372544,
+           -0.830108773588016,
+           -0.7988032316581398,
+           -0.777373070574298,
+           -0.7669940210137199,
+           -0.7686059362703087,
+           -0.782887237128778,
+           -0.810235184907133,
+           -0.8507525008243697,
+           -0.9042406994705477,
+           -0.9702003442545474,
+           -1.0478382671758768,
+           -1.1360816281506811,
+           -1.2335985245035082,
+           -1.338824703145734,
+           -1.449995780272929,
+           -1.5651842397523865,
+           -1.6823403650218811,
+           -1.7993361631458482,
+           -1.9140112660462782,
+           -2.0242197446633576,
+           -2.127876748130875,
+           -2.2230038825711014,
+           -2.3077722727820875,
+           -2.380542304222776,
+           -2.4398991209926537,
+           -2.4846830560533197,
+           -2.5140142903067964,
+           -2.527311174400676,
+           -2.5243017979319857,
+           -2.5050285513980994,
+           -2.469845592881343,
+           -2.4194092999978594,
+           -2.3546619539900613,
+           -2.2768090629515076,
+           -2.1872908811553424,
+           -2.087748817676559,
+           -1.9799875466585757,
+           -1.865933730803138,
+           -1.7475923465779837,
+           -1.6270016524083422,
+           -1.5061878685109953,
+           -1.38712063843212,
+           -1.2716703177918545,
+           -1.161568085884979,
+           -1.0583698019266679,
+           -0.9634244317395608,
+           -0.877847754970364,
+           -0.8025019303982567,
+           -0.7379813508597083,
+           -0.6846050633968725,
+           -0.6424158683084139,
+           -0.611186046850772,
+           -0.5904295054535651,
+           -0.5794199684647685,
+           -0.5772147054605579,
+           -0.5826831466194474,
+           -0.5945396238071667,
+           -0.6113793786632944,
+           -0.6317169044480544,
+           -0.6540256374755946,
+           -0.6767779878157313,
+           -0.6984846981569632,
+           -0.717732544224987,
+           -0.7332194392479703,
+           -0.7437860773458319,
+           -0.7484433445110041,
+           -0.7463948386265342,
+           -0.7370539688493584,
+           -0.7200552463890119,
+           -0.6952595296386529,
+           -0.6627531429440208,
+           -0.6228409460767764,
+           -0.5760335867313089,
+           -0.5230293171776459,
+           -0.4646908948345669,
+           -0.40201821149325084,
+           -0.33611740408827867,
+           -0.26816728857028893,
+           -0.1993840253673611,
+           -0.1309849684632729,
+           -0.06415266919313634,
+           -5.819723779827008e-16
+          ],
+          [
+           0,
+           0.058428810442321254,
+           0.11200140557425901,
+           0.1600941693343753,
+           0.20227164620756308,
+           0.2383000935328369,
+           0.26815539644953923,
+           0.2920251179632413,
+           0.3103046095463392,
+           0.3235872627409183,
+           0.3326491354692332,
+           0.33842833428959135,
+           0.3419996719124928,
+           0.344545244398244,
+           0.34732168140046427,
+           0.3516249128106142,
+           0.358753363880817,
+           0.3699705365715657,
+           0.3864679562798775,
+           0.40932945965235396,
+           0.43949777089992975,
+           0.4777442615538166,
+           0.5246427131901678,
+           0.580547806136584,
+           0.6455789419212483,
+           0.7196098760737746,
+           0.8022644940778434,
+           0.8929189103750464,
+           0.9907099121274118,
+           1.0945496099038197,
+           1.203146000546303,
+           1.3150289971228628,
+           1.428581340856115,
+           1.5420736837554785,
+           1.6537030215618798,
+           1.761633567308566,
+           1.8640390885947393,
+           1.9591456883017786,
+           2.0452739901091532,
+           2.120879697326121,
+           2.1845915261523063,
+           2.235245571791825,
+           2.271915246535747,
+           2.293936031079809,
+           2.300924401507945,
+           2.292790431623177,
+           2.269743720318927,
+           2.232292452808809,
+           2.181235568893237,
+           2.1176481770234528,
+           2.042860515677598,
+           1.9584309195031961,
+           1.8661133929803433,
+           1.7678205254524564,
+           1.6655825950314112,
+           1.561503802312232,
+           1.457716645721818,
+           1.3563354969207886,
+           1.2594104558152566,
+           1.168882559876865,
+           1.0865413917128715,
+           1.013986072904315,
+           0.9525905523886931,
+           0.9034739960352673,
+           0.8674769630144618,
+           0.8451439170410218,
+           0.8367124699200887,
+           0.842109594713158,
+           0.8609548801645187,
+           0.89257073082026,
+           0.9359992525985915,
+           0.990025405434682,
+           1.0532058568648925,
+           1.1239028366160713,
+           1.2003221756618472,
+           1.2805546166110875,
+           1.362619408021416,
+           1.444509145050396,
+           1.5242347939417582,
+           1.5998698387467118,
+           1.6695925153167928,
+           1.7317251492611125,
+           1.7847696899075143,
+           1.8274386294357359,
+           1.858680612819616,
+           1.8777001771118234,
+           1.8839712046170487,
+           1.8772438299994878,
+           1.8575447025034897,
+           1.825170667246634,
+           1.7806760899550134,
+           1.7248542036010523,
+           1.6587129993900631,
+           1.5834463148968665,
+           1.5004008856978024,
+           1.4110402208201644,
+           1.3169062344759312,
+           1.2195796151425202,
+           1.120639936972131,
+           1.0216265172409407,
+           0.9240009972065428,
+           0.8291125730665884,
+           0.7381667300490314,
+           0.652198237930621,
+           0.572049052912638,
+           0.49835164168028534,
+           0.4315181019198477,
+           0.37173530315731884,
+           0.31896611631964444,
+           0.27295664383106183,
+           0.23324920829017892,
+           0.19920071069881945,
+           0.17000583252839882,
+           0.14472443304451713,
+           0.12231238734491802,
+           0.10165502415078252,
+           0.0816022576831182,
+           0.06100446656301121,
+           0.03874815561717221,
+           0.013790444155503331,
+           -0.014808543500845987,
+           -0.047856253558011694,
+           -0.08600203450477903,
+           -0.12971591679653124,
+           -0.17927241597075963,
+           -0.23473980366718875,
+           -0.29597514849745626,
+           -0.36262527829661473,
+           -0.43413366080516386,
+           -0.5097530451938852,
+           -0.5885635559790374,
+           -0.6694957876146003,
+           -0.751358316035495,
+           -0.8328689260254974,
+           -0.9126887534962012,
+           -0.9894584621497122,
+           -1.0618355166143718,
+           -1.128531580490444,
+           -1.1883490587278773,
+           -1.2402158196699855,
+           -1.2832171725991393,
+           -1.316624240759374,
+           -1.3399179560578518,
+           -1.3528080078576261,
+           -1.3552462018583433,
+           -1.3474338229697604,
+           -1.3298227449007585,
+           -1.3031101852194393,
+           -1.2682271640049116,
+           -1.226320882934443,
+           -1.178731395762826,
+           -1.1269630867928164,
+           -1.0726516074468224,
+           -1.017527039064934,
+           -0.9633741495844643,
+           -0.9119906902656575,
+           -0.8651447340976252,
+           -0.8245320884951904,
+           -0.7917348205327605,
+           -0.7681819130324595,
+           -0.7551130247410499,
+           -0.7535462586256078,
+           -0.7642507506232992,
+           -0.7877247791859115,
+           -0.8241799663606794,
+           -0.873531997080453,
+           -0.9353981282962508,
+           -1.0091015973477433,
+           -1.0936828734903652,
+           -1.187917531825704,
+           -1.2903403690452173,
+           -1.399275229313995,
+           -1.512869869999096,
+           -1.6291350741935475,
+           -1.7459871131226872,
+           -1.861292579106511,
+           -1.972914550827231,
+           -2.0787590186790736,
+           -2.176820489810648,
+           -2.265225710330617,
+           -2.3422744856189666,
+           -2.406476647725555,
+           -2.4565843097996263,
+           -2.49161865917191,
+           -2.510890670391084,
+           -2.514015264043433,
+           -2.5009185930417646,
+           -2.471838301462577,
+           -2.427316767962212,
+           -2.3681875122511156,
+           -2.2955551050030047,
+           -2.2107690749893014,
+           -2.1153924484368973,
+           -2.011165681189296,
+           -1.8999668511741574,
+           -1.7837690643719917,
+           -1.6645960898924597,
+           -1.5444772774216335,
+           -1.4254028223397166,
+           -1.3092804299900862,
+           -1.1978943913063165,
+           -1.0928680182997117,
+           -0.9956303013997346,
+           -0.9073875435054638,
+           -0.8291006005334044,
+           -0.7614682183571473,
+           -0.7049168048092503,
+           -0.6595968166074283,
+           -0.6253857786084948,
+           -0.6018977906984883,
+           -0.5884992198916575,
+           -0.5843301257144071,
+           -0.5883308293591814,
+           -0.5992729147715772,
+           -0.6157938457588272,
+           -0.6364342998976247,
+           -0.6596772594706838,
+           -0.6839878633017192,
+           -0.7078530120098455,
+           -0.7298197330651875,
+           -0.7485313506682661,
+           -0.7627605678497009,
+           -0.771438652658885,
+           -0.7736800246964068,
+           -0.7688016598688165,
+           -0.7563368670040373,
+           -0.7360431364117742,
+           -0.7079039138958437,
+           -0.6721243102454669,
+           -0.6291209119016798,
+           -0.5795060093911766,
+           -0.5240667024476275,
+           -0.4637394709247687,
+           -0.39958091538083335,
+           -0.33273546770632917,
+           -0.2644009479654489,
+           -0.1957928968371787,
+           -0.1281086423570616,
+           -0.06249206435874819,
+           -5.646400386019649e-16
+          ],
+          [
+           0,
+           0.05629407505042242,
+           0.10749037259707217,
+           0.15306471001393465,
+           0.1926872168718897,
+           0.22623269763268072,
+           0.2537852609273413,
+           0.2756370760690787,
+           0.292281270755838,
+           0.30439913706867966,
+           0.312841961981156,
+           0.3186079398737614,
+           0.3228147544020595,
+           0.32666853218749015,
+           0.33142996824382837,
+           0.33837850031901845,
+           0.34877546442526386,
+           0.3638271953084579,
+           0.38464904262128763,
+           0.41223125587613024,
+           0.44740764924751797,
+           0.49082789196387056,
+           0.5429341829556437,
+           0.6039429617413343,
+           0.6738321838587634,
+           0.7523345515423125,
+           0.8389369422176641,
+           0.9328861224150021,
+           1.0332006767491875,
+           1.1386889246238314,
+           1.2479724452129024,
+           1.3595146878729945,
+           1.4716540140479488,
+           1.58264040125325,
+           1.6906749427978114,
+           1.7939512009881653,
+           1.8906974186213898,
+           1.9792185649989893,
+           2.0579371892740763,
+           2.1254320758464784,
+           2.180473743286212,
+           2.222055898819929,
+           2.2494220530920934,
+           2.262086612496952,
+           2.2598498961571662,
+           2.242806668458887,
+           2.211347932447039,
+           2.1661558905782123,
+           2.1081921433869093,
+           2.0386793595324915,
+           1.9590768084684913,
+           1.8710502957439394,
+           1.7764371770531402,
+           1.67720724724911,
+           1.575420401666608,
+           1.4731820467674115,
+           1.3725972933495718,
+           1.2757249969540803,
+           1.1845327158642407,
+           1.1008536370598223,
+           1.0263464751272953,
+           0.9624592795257106,
+           0.9103979934473954,
+           0.8711004950271795,
+           0.8452167215758075,
+           0.8330953330051907,
+           0.8347772151910725,
+           0.8499959614646466,
+           0.8781853046943076,
+           0.9184933075436224,
+           0.9698029584803229,
+           1.0307586698503584,
+           1.099798035490383,
+           1.1751880822935223,
+           1.2550651458389928,
+           1.3374774171554251,
+           1.4204291478954945,
+           1.5019254660682788,
+           1.5800167448104492,
+           1.65284148265797,
+           1.7186666949545097,
+           1.7759248813332866,
+           1.8232467219744906,
+           1.8594887633616313,
+           1.8837554798329352,
+           1.895415237217367,
+           1.8941098357792454,
+           1.879757467827954,
+           1.8525490867680803,
+           1.8129383450852123,
+           1.7616254148247565,
+           1.699535151690401,
+           1.627790199348866,
+           1.5476797505699416,
+           1.460624783536537,
+           1.3681406725710061,
+           1.2717981307052078,
+           1.1731834756053952,
+           1.0738592195838856,
+           0.9753259686419722,
+           0.8789865751705126,
+           0.7861134251730894,
+           0.6978196553409711,
+           0.6150349902084206,
+           0.5384867676433163,
+           0.46868658519095036,
+           0.4059228537341219,
+           0.35025939225890174,
+           0.30154004207946816,
+           0.25939912459658404,
+           0.2232774174266563,
+           0.19244318329287755,
+           0.16601765794186926,
+           0.14300429074925544,
+           0.12232093742231583,
+           0.10283413064940936,
+           0.08339450351357573,
+           0.06287241324236517,
+           0.04019281006885856,
+           0.014368417675341236,
+           -0.015469662690158698,
+           -0.05004474396676571,
+           -0.08991147107533805,
+           -0.13543748682915635,
+           -0.1867903439559928,
+           -0.24393002431553493,
+           -0.30660728012556177,
+           -0.37436786009012024,
+           -0.4465625296066584,
+           -0.522362642617146,
+           -0.6007808770108383,
+           -0.6806966094862006,
+           -0.7608852828996245,
+           -0.840051012504775,
+           -0.9168615898488306,
+           -0.9899849766962927,
+           -1.0581263379216743,
+           -1.120064642998706,
+           -1.1746878710606672,
+           -1.2210258844405169,
+           -1.2582800894297477,
+           -1.2858490794295638,
+           -1.3033495528459291,
+           -1.3106319136170221,
+           -1.3077900933083753,
+           -1.2951652770246007,
+           -1.273343367410388,
+           -1.2431461779654243,
+           -1.2056165048643912,
+           -1.1619973815074165,
+           -1.1137059682446602,
+           -1.0623026673993892,
+           -1.0094561773887727,
+           -0.9569053062833777,
+           -0.906418451846246,
+           -0.8597517197287924,
+           -0.8186066923946993,
+           -0.7845888774007211,
+           -0.7591678544045466,
+           -0.7436401058399662,
+           -0.7390954573683746,
+           -0.7463879723568042,
+           -0.7661120416932558,
+           -0.7985842887011905,
+           -0.843831771692251,
+           -0.9015868171274299,
+           -0.9712886580807025,
+           -1.0520918895748013,
+           -1.1428815883721244,
+           -1.2422947839680136,
+           -1.3487478137907885,
+           -1.4604689527366472,
+           -1.5755355786692882,
+           -1.6919150245578867,
+           -1.8075081772480552,
+           -1.9201948147016166,
+           -2.027879629593718,
+           -2.1285378685196754,
+           -2.220259523219258,
+           -2.3012910430215068,
+           -2.3700735953691043,
+           -2.425276982408959,
+           -2.4658284242712054,
+           -2.4909355413114276,
+           -2.500103005304212,
+           -2.493142480000008,
+           -2.4701756309320424,
+           -2.431630149004515,
+           -2.3782288982015856,
+           -2.3109724606963535,
+           -2.231115508750352,
+           -2.1401375782869034,
+           -2.0397089503698616,
+           -1.9316524608455599,
+           -1.8179021523611771,
+           -1.7004597546032316,
+           -1.5813500262016282,
+           -1.4625760142055684,
+           -1.346075283863324,
+           -1.2336781427659094,
+           -1.127068830006304,
+           -1.0277505642306253,
+           -0.9370152462564092,
+           -0.855918494770511,
+           -0.7852605604216283,
+           -0.7255735177054243,
+           -0.6771149790270239,
+           -0.6398684150545582,
+           -0.6135500039098721,
+           -0.5976217728627845,
+           -0.5913106439121906,
+           -0.5936328526884882,
+           -0.6034230819701263,
+           -0.6193675398960213,
+           -0.6400401213715586,
+           -0.6639407214127129,
+           -0.6895347229069182,
+           -0.7152926595605191,
+           -0.7397290581072222,
+           -0.7614394920033936,
+           -0.7791349310495947,
+           -0.7916725462700702,
+           -0.7980822250084385,
+           -0.7975881650996,
+           -0.7896250462452172,
+           -0.7738484180651115,
+           -0.7501390941357725,
+           -0.7186014958708866,
+           -0.6795560454462722,
+           -0.6335258592096878,
+           -0.5812181383146418,
+           -0.5235007880272646,
+           -0.4613749178980985,
+           -0.39594397874300774,
+           -0.328380376547036,
+           -0.25989046589463805,
+           -0.1916788647893281,
+           -0.12491304779148078,
+           -0.06068916492045503,
+           -5.461655573554057e-16
+          ],
+          [
+           0,
+           0.05407615779269436,
+           0.10286112993985799,
+           0.14593280411698337,
+           0.1830677382109212,
+           0.21424829691739444,
+           0.23966401036880502,
+           0.25970710334430935,
+           0.2749622959506647,
+           0.2861911266108698,
+           0.2943111919497662,
+           0.30037083206668924,
+           0.3055199103252934,
+           0.31097744109090897,
+           0.3179969041355718,
+           0.32783014851477055,
+           0.34169082993341016,
+           0.3607183428697325,
+           0.385943201523961,
+           0.4182547921258659,
+           0.4583723640061069,
+           0.506820049437421,
+           0.5639066044718761,
+           0.6297104472423601,
+           0.7040704393181955,
+           0.7865827129486347,
+           0.876603695940173,
+           0.9732593302562764,
+           1.07546032408552,
+           1.1819231240065948,
+           1.2911961478239908,
+           1.4016906833278964,
+           1.5117157370571008,
+           1.619516013182335,
+           1.7233121185254818,
+           1.8213420276461703,
+           1.9119028034780603,
+           1.9933915552162589,
+           2.064344626469219,
+           2.123474042896021,
+           2.169700308840012,
+           2.202180725430443,
+           2.2203325062803594,
+           2.223850088770905,
+           2.212716176034302,
+           2.1872061938026057,
+           2.147886003648921,
+           2.0956028759725553,
+           2.0314698884137625,
+           1.9568440742516329,
+           1.8732987968442973,
+           1.7825909665923645,
+           1.686623842790356,
+           1.5874062709750434,
+           1.4870092943114908,
+           1.3875211430002954,
+           1.2910016470149352,
+           1.199437133649094,
+           1.114696861947321,
+           1.038492011313644,
+           0.9723381822671912,
+           0.9175222848694484,
+           0.8750745867787978,
+           0.8457465707062631,
+           0.8299951132204177,
+           0.8279733467297097,
+           0.8395284077093508,
+           0.8642061106993845,
+           0.9012624232592216,
+           0.9496814559177732,
+           1.008199527123155,
+           1.075334720010803,
+           1.1494212189444264,
+           1.2286476023567885,
+           1.3110981771139965,
+           1.3947963706371749,
+           1.4777491519808195,
+           1.5579914330379818,
+           1.6336294064555867,
+           1.7028818075093928,
+           1.7641181422987682,
+           1.815893002768922,
+           1.8569756882803141,
+           1.8863744712363084,
+           1.9033549777111303,
+           1.907452299773679,
+           1.8984766106629596,
+           1.8765122133160814,
+           1.8419101130449875,
+           1.7952743624534957,
+           1.7374425771151005,
+           1.6694611604052074,
+           1.59255590178002,
+           1.508098721652379,
+           1.4175714251958833,
+           1.3225273947701928,
+           1.2245521946059426,
+           1.1252240809059981,
+           1.0260754052090364,
+           0.9285558689376152,
+           0.8339985333451176,
+           0.7435894130024855,
+           0.6583413845005485,
+           0.5790730276644211,
+           0.5063928872027704,
+           0.4406895016354592,
+           0.382127397132355,
+           0.33064909032544576,
+           0.28598299009903655,
+           0.2476569376975756,
+           0.2150169810047443,
+           0.18725084614211399,
+           0.16341545093604554,
+           0.14246770327421746,
+           0.12329774545181305,
+           0.10476374533004719,
+           0.08572729798796518,
+           0.06508848845045946,
+           0.04181967732369941,
+           0.014997106453043012,
+           -0.016170519877631104,
+           -0.052317242659670124,
+           -0.0938995096333176,
+           -0.14118083871362824,
+           -0.1942219008231294,
+           -0.2528762980830361,
+           -0.3167921646373532,
+           -0.38541956530374055,
+           -0.45802351562071636,
+           -0.5337022995418096,
+           -0.6114106217573165,
+           -0.6899870039465155,
+           -0.768184721432126,
+           -0.8447054816085061,
+           -0.9182349705859211,
+           -0.9874793416717942,
+           -1.0512016899782488,
+           -1.108257552397774,
+           -1.1576284916101824,
+           -1.1984528662446583,
+           -1.2300529557870095,
+           -1.251957696681373,
+           -1.2639203931751826,
+           -1.2659308901579165,
+           -1.2582218324878762,
+           -1.24126878268267,
+           -1.2157841227021124,
+           -1.1827048220421732,
+           -1.1431743095756806,
+           -1.098518836633495,
+           -1.0502188599527138,
+           -0.9998761017731603,
+           -0.9491770572909691,
+           -0.8998538140117939,
+           -0.8536431208769674,
+           -0.8122446954693551,
+           -0.7772797838128622,
+           -0.7502509885289551,
+           -0.732504357290998,
+           -0.7251946751292635,
+           -0.7292548323021555,
+           -0.7453700458608016,
+           -0.7739575999342174,
+           -0.8151526398771032,
+           -0.8688004118977595,
+           -0.9344551861081796,
+           -1.0113859408574608,
+           -1.0985887236327667,
+           -1.1948054427175379,
+           -1.298548688132301,
+           -1.408132033969755,
+           -1.521705140672328,
+           -1.6372928583742503,
+           -1.752837434038715,
+           -1.86624284819494,
+           -1.975420253529414,
+           -2.0783334587465263,
+           -2.173043397718421,
+           -2.25775054610227,
+           -2.3308342947972807,
+           -2.3908883607146416,
+           -2.436751408623786,
+           -2.467532171058752,
+           -2.482628483669653,
+           -2.481739797817665,
+           -2.4648728871248906,
+           -2.43234062633434,
+           -2.38475388527769,
+           -2.323006743989775,
+           -2.248255393080768,
+           -2.1618912325406496,
+           -2.0655088185896866,
+           -1.9608694286995554,
+           -1.8498611165822902,
+           -1.734456209331821,
+           -1.6166672560849138,
+           -1.498502470194335,
+           -1.3819217142311335,
+           -1.2687940590314644,
+           -1.16085790497626,
+           -1.0596845868517317,
+           -0.9666462946793587,
+           -0.8828890340625418,
+           -0.8093112235936748,
+           -0.7465483868383864,
+           -0.6949642458405203,
+           -0.6546483657023304,
+           -0.62542033947963,
+           -0.6068403433461138,
+           -0.5982257376451283,
+           -0.5986732438503403,
+           -0.6070860941642401,
+           -0.6222054327476534,
+           -0.6426451482543122,
+           -0.6669292388389999,
+           -0.6935307549910619,
+           -0.7209113337248979,
+           -0.7475603305441166,
+           -0.7720325732794815,
+           -0.792983803858067,
+           -0.8092029391652372,
+           -0.8196403687102377,
+           -0.8234316125677544,
+           -0.8199157853346138,
+           -0.8086484474984482,
+           -0.7894085712220048,
+           -0.7621994994176116,
+           -0.7272439312875654,
+           -0.6849731203491111,
+           -0.6360106185024875,
+           -0.5811510382313609,
+           -0.5213344310726844,
+           -0.4576169909021731,
+           -0.3911388825931081,
+           -0.32309006792734607,
+           -0.25467504949786224,
+           -0.18707747853812254,
+           -0.12142557353803829,
+           -0.05875927316336571,
+           -5.267040044605034e-16
+          ],
+          [
+           0,
+           0.05179323099789152,
+           0.09815102623154283,
+           0.13875500357477022,
+           0.17348800430968375,
+           0.20243799734589646,
+           0.22589621199691431,
+           0.24434953469824966,
+           0.2584673551098619,
+           0.2690831925412453,
+           0.2771715708734433,
+           0.28382073563662186,
+           0.290201917435928,
+           0.29753593867701245,
+           0.30705803314528946,
+           0.3199817985636167,
+           0.3374632294675177,
+           0.36056578085672364,
+           0.3902273919726829,
+           0.42723035468831205,
+           0.4721748434504844,
+           0.5254568351305273,
+           0.5872510396871168,
+           0.6574993388801244,
+           0.7359050934554383,
+           0.8219335326472018,
+           0.9148182871640914,
+           1.0135739718494132,
+           1.1170145708056844,
+           1.2237772297971792,
+           1.332350921905457,
+           1.4411093262115509,
+           1.5483471489045135,
+           1.6523190244740364,
+           1.7512800638816342,
+           1.843527068651511,
+           1.927439405947207,
+           2.0015185405771967,
+           2.064425245563426,
+           2.1150135628575266,
+           2.1523606588452253,
+           2.175791813710177,
+           2.1848998972723956,
+           2.179558813834675,
+           2.1599305417140564,
+           2.1264655460231805,
+           2.079896502170034,
+           2.021225428580681,
+           1.9517044863756399,
+           1.8728108572414053,
+           1.786216254764234,
+           1.6937517554904291,
+           1.5973687507183019,
+           1.49909691567883,
+           1.4010001669570504,
+           1.3051316299006481,
+           1.2134886640814397,
+           1.1279689959473707,
+           1.050328983571792,
+           0.9821449894395669,
+           0.9247787646771385,
+           0.8793476537859262,
+           0.846700315059703,
+           0.8273985212199598,
+           0.8217054605631086,
+           0.8295808045862024,
+           0.8506826473976327,
+           0.8843762591334218,
+           0.9297494340544331,
+           0.9856340579214322,
+           1.0506333724240615,
+           1.1231542804376955,
+           1.2014439179438139,
+           1.2836296194228571,
+           1.3677613257965733,
+           1.4518554294164587,
+           1.533939020455106,
+           1.6120934940441995,
+           1.6844964976868055,
+           1.7494612433032337,
+           1.8054722765958724,
+           1.8512168865106917,
+           1.8856114471704435,
+           1.9078221110215536,
+           1.9172794119286343,
+           1.9136864870952932,
+           1.897020783270255,
+           1.8675292718471228,
+           1.8257173552612957,
+           1.7723317996480572,
+           1.7083381723086528,
+           1.6348933936233698,
+           1.553314128456418,
+           1.4650418390163626,
+           1.3716053972318796,
+           1.2745822081614921,
+           1.1755588255288854,
+           1.0760920455098295,
+           0.977671445351455,
+           0.881684289849074,
+           0.7893836623069345,
+           0.7018605890989493,
+           0.6200208205793755,
+           0.5445668085917108,
+           0.47598528530448214,
+           0.4145407030018528,
+           0.3602746434439936,
+           0.3130111522973357,
+           0.272367802773787,
+           0.23777214681584644,
+           0.20848307558059198,
+           0.18361648703215716,
+           0.1621745502494545,
+           0.14307776629420071,
+           0.12519895639734657,
+           0.10739826152137949,
+           0.08855821418841782,
+           0.0676179443832448,
+           0.04360560629364678,
+           0.015668160979882505,
+           -0.016902279475126784,
+           -0.05464624999576257,
+           -0.09791946758349393,
+           -0.14688057423841122,
+           -0.2014844224012978,
+           -0.26148109280234977,
+           -0.3264206848544366,
+           -0.3956637688150884,
+           -0.4683972406932224,
+           -0.5436551790593517,
+           -0.6203441711379253,
+           -0.6972724571730835,
+           -0.7731821400859571,
+           -0.8467836244939457,
+           -0.9167913873748796,
+           -0.9819601436372397,
+           -1.0411204546359158,
+           -1.0932128366893892,
+           -1.1373194597378522,
+           -1.1726925826570875,
+           -1.1987789500484158,
+           -1.2152394736463636,
+           -1.2219636374030804,
+           -1.2190781959568306,
+           -1.2069498783306412,
+           -1.1861819588027738,
+           -1.1576047112017798,
+           -1.1222599175521348,
+           -1.0813797531597957,
+           -1.036360514088323,
+           -0.9887317859167466,
+           -0.9401217713347926,
+           -0.8922195955132547,
+           -0.8467354897025697,
+           -0.8053598130663633,
+           -0.7697219087933139,
+           -0.7413498020764573,
+           -0.721631734234849,
+           -0.7117804893250256,
+           -0.7128014079058578,
+           -0.7254648986272011,
+           -0.7502841540120356,
+           -0.7874986547016405,
+           -0.8370639094867853,
+           -0.8986477299801514,
+           -0.9716331824121812,
+           -1.0551281985720231,
+           -1.1479816672919956,
+           -1.2488056710243838,
+           -1.3560033828326519,
+           -1.467802001183194,
+           -1.5822899766751373,
+           -1.6974576793231657,
+           -1.8112405698214973,
+           -1.9215638754770874,
+           -2.0263877327719175,
+           -2.1237517447737573,
+           -2.211817913226874,
+           -2.288910941863283,
+           -2.3535549684088775,
+           -2.4045058664531336,
+           -2.440778362781809,
+           -2.4616673384084704,
+           -2.46676281940419,
+           -2.4559583133651426,
+           -2.4294523053333115,
+           -2.387742889353665,
+           -2.3316156746630603,
+           -2.262125264803292,
+           -2.1805707598626447,
+           -2.088465872889949,
+           -1.9875043778786563,
+           -1.879521715530016,
+           -1.7664536716509223,
+           -1.6502931093961721,
+           -1.5330457790498364,
+           -1.4166862466651207,
+           -1.3031149752671216,
+           -1.1941175597090874,
+           -1.0913270595134292,
+           -0.996190294570003,
+           -0.9099388684059496,
+           -0.8335655653909021,
+           -0.7678066346470247,
+           -0.7131303279141715,
+           -0.6697319047823677,
+           -0.6375351603505244,
+           -0.6162003714085988,
+           -0.6051384015844852,
+           -0.6035305573702943,
+           -0.6103536491844761,
+           -0.6244095880013036,
+           -0.6443587415949419,
+           -0.6687561876777441,
+           -0.696089936243174,
+           -0.7248201517890195,
+           -0.7534183887497671,
+           -0.7804058607561188,
+           -0.804389795999622,
+           -0.8240969861399471,
+           -0.8384037133978672,
+           -0.8463613377280063,
+           -0.847216940766316,
+           -0.8404285526699259,
+           -0.8256746287235815,
+           -0.8028575911139807,
+           -0.7721014038187226,
+           -0.7337433012760035,
+           -0.6883199405517387,
+           -0.6365483883588123,
+           -0.5793024849566588,
+           -0.5175852433968815,
+           -0.4524980418730442,
+           -0.38520744660495315,
+           -0.3169105607611954,
+           -0.2487998299647802,
+           -0.1820282460824196,
+           -0.11767587801724298,
+           -0.05671862146403255,
+           -5.064170558417859e-16
+          ],
+          [
+           0,
+           0.04946375633905234,
+           0.09339750151250803,
+           0.1315872648651055,
+           0.16402105386503243,
+           0.19088954948341427,
+           0.2125810868351269,
+           0.22967104144796505,
+           0.2429058880396116,
+           0.2531823385359348,
+           0.2615220957037073,
+           0.26904287489455747,
+           0.2769264460413105,
+           0.28638452866155456,
+           0.2986234321314257,
+           0.31480837034917053,
+           0.33602839313483923,
+           0.36326286592424545,
+           0.3973503947298982,
+           0.4389610357750561,
+           0.4885725500538758,
+           0.5464513642695445,
+           0.6126387835883791,
+           0.6869428712923449,
+           0.7689362689513333,
+           0.8579600816906304,
+           0.9531338002158694,
+           1.0533710782998609,
+           1.1574010352645978,
+           1.263794611353031,
+           1.3709953733448612,
+           1.477354051625848,
+           1.5811659911171456,
+           1.6807106195309645,
+           1.7742919793743568,
+           1.8602793364670065,
+           1.9371468683874171,
+           2.0035114515290613,
+           2.058167605038532,
+           2.100118712922528,
+           2.1286037305686616,
+           2.1431186867993004,
+           2.1434324148440025,
+           2.129596082315442,
+           2.1019462380846665,
+           2.06110124927192,
+           2.00795116060486,
+           1.9436411672541796,
+           1.8695490470420728,
+           1.787257044830386,
+           1.6985188373184004,
+           1.6052223270787442,
+           1.50934911745561,
+           1.4129316023993705,
+           1.3180086653668817,
+           1.226581017577821,
+           1.1405672172676307,
+           1.061761397808984,
+           0.9917936939931725,
+           0.9320942932854135,
+           0.8838619539956081,
+           0.8480377270882864,
+           0.8252844953425247,
+           0.8159728057498146,
+           0.820173321754291,
+           0.8376560648246721,
+           0.8678964537216515,
+           0.9100879886064246,
+           0.9631612697448974,
+           1.0258088908215754,
+           1.0965156084219476,
+           1.1735930654278235,
+           1.2552182398914826,
+           1.339474704971571,
+           1.4243957217892487,
+           1.5080081471121833,
+           1.5883761225268755,
+           1.6636435215402308,
+           1.7320741655674965,
+           1.7920888781188824,
+           1.8422985272085175,
+           1.8815323070494587,
+           1.908860628941673,
+           1.9236121249489164,
+           1.9253844131771338,
+           1.9140484266163853,
+           1.889746264806945,
+           1.8528826851600384,
+           1.8041105047283348,
+           1.7443103298014353,
+           1.6745651663087011,
+           1.5961305853364596,
+           1.5104012221602807,
+           1.4188744715402144,
+           1.323112304607132,
+           1.224702172005426,
+           1.1252179731551957,
+           1.026182062260879,
+           0.9290292283364542,
+           0.8350735299517306,
+           0.7454787871181758,
+           0.661233434751347,
+           0.5831303269824413,
+           0.5117519521792703,
+           0.44746137816139314,
+           0.3903990993078631,
+           0.3404858057886834,
+           0.29743094381828034,
+           0.2607467884357274,
+           0.2297676105615502,
+           0.2036733914666815,
+           0.1815174235322004,
+           0.16225703913076883,
+           0.14478663203784548,
+           0.12797207990240933,
+           0.11068564334891103,
+           0.0918404080426228,
+           0.07042335073012383,
+           0.045526148464089033,
+           0.016372910943827333,
+           -0.017655902409354784,
+           -0.057004018456581484,
+           -0.10192486035680483,
+           -0.15247242229563968,
+           -0.20849775936398432,
+           -0.2696511962800169,
+           -0.3353902091531231,
+           -0.404992786035765,
+           -0.47757592836913826,
+           -0.5521188202510762,
+           -0.6274900691797939,
+           -0.7024783136968384,
+           -0.7758254029332402,
+           -0.8462612827747988,
+           -0.9125396750216931,
+           -0.9734736107905727,
+           -1.0279698781776727,
+           -1.0750614669535061,
+           -1.1139371392747657,
+           -1.1439673239684884,
+           -1.1647256211956638,
+           -1.1760053120424432,
+           -1.1778303911556718,
+           -1.1704607768724606,
+           -1.154391499001902,
+           -1.1303458158703992,
+           -1.0992623656586635,
+           -1.062276608599234,
+           -1.0206969624676525,
+           -0.9759761703215895,
+           -0.9296785631771967,
+           -0.8834439881296706,
+           -0.8389492615830365,
+           -0.7978680754685303,
+           -0.7618303298329636,
+           -0.7323818867599086,
+           -0.710945737630518,
+           -0.6987855482275577,
+           -0.6969724947348134,
+           -0.7063562294777733,
+           -0.7275407200502806,
+           -0.7608655915578211,
+           -0.8063934718315887,
+           -0.8639036967782413,
+           -0.9328925810008483,
+           -1.0125803011664318,
+           -1.1019242801604623,
+           -1.1996388027640938,
+           -1.3042204422766508,
+           -1.413978735902842,
+           -1.5270714183176304,
+           -1.6415434107785425,
+           -1.7553686702446398,
+           -1.8664939314871047,
+           -1.9728833269168635,
+           -2.0725628450230698,
+           -2.1636635895260974,
+           -2.2444628276007954,
+           -2.31342186620707,
+           -2.3692198694636386,
+           -2.410782825335477,
+           -2.4373069843691773,
+           -2.4482762240267464,
+           -2.4434729361605187,
+           -2.4229821888397383,
+           -2.3871890733463097,
+           -2.336769308821965,
+           -2.2726733368406116,
+           -2.196104292214492,
+           -2.1084903808802933,
+           -2.0114523272457174,
+           -1.9067666687227924,
+           -1.7963257715461123,
+           -1.682095517053231,
+           -1.5660716595962891,
+           -1.4502358849323846,
+           -1.3365126006763055,
+           -1.2267274681770646,
+           -1.1225686385949238,
+           -1.025551586202939,
+           -0.9369883407759453,
+           -0.8579618106446909,
+           -0.7893057613332867,
+           -0.7315908748119165,
+           -0.6851171647510496,
+           -0.649912867458802,
+           -0.6257397702627483,
+           -0.6121047828500373,
+           -0.6082774063452436,
+           -0.6133126133792856,
+           -0.6260785235444348,
+           -0.6452881455787194,
+           -0.6695343631184005,
+           -0.6973272671744281,
+           -0.7271328873816294,
+           -0.7574123467277476,
+           -0.7866604614901157,
+           -0.8134428294818523,
+           -0.8364304948217736,
+           -0.8544313450890769,
+           -0.8664174851431641,
+           -0.8715479388041556,
+           -0.8691861522691872,
+           -0.8589119084631099,
+           -0.8405274060607713,
+           -0.8140574070190819,
+           -0.7797435083358516,
+           -0.7380327435872606,
+           -0.6895608638223752,
+           -0.6351307819999883,
+           -0.575686786969932,
+           -0.512285238984309,
+           -0.4460625462318619,
+           -0.3782012887463728,
+           -0.3098954005948278,
+           -0.24231534241279223,
+           -0.17657419362191495,
+           -0.11369556713851899,
+           -0.05458419976227364,
+           -4.854713071472535e-16
+          ],
+          [
+           0,
+           0.04710629756706851,
+           0.08863771370639299,
+           0.12448440001574902,
+           0.1547374660178851,
+           0.17968651838611027,
+           0.19981159093891093,
+           0.2157696681518821,
+           0.22837614668898515,
+           0.23858171255091196,
+           0.2474452324895612,
+           0.25610336425887176,
+           0.2657376783566456,
+           0.277540151899347,
+           0.2926779414055751,
+           0.3122583643353277,
+           0.3372950186113444,
+           0.3686759450006858,
+           0.40713468972062344,
+           0.45322505509712824,
+           0.5073002362458666,
+           0.5694969337768244,
+           0.6397249091148574,
+           0.7176623132421838,
+           0.8027569748836629,
+           0.8942336839823417,
+           0.9911073545042566,
+           1.0922018009695666,
+           1.1961737193877444,
+           1.3015413290940059,
+           1.4067170107287144,
+           1.5100431703428745,
+           1.6098304730310646,
+           1.7043975238097406,
+           1.7921110303797774,
+           1.8714254630864942,
+           1.9409212323786889,
+           1.9993404333296676,
+           2.0456192596744582,
+           2.078916265108058,
+           2.0986357454919804,
+           2.104445629828812,
+           2.0962893976276837,
+           2.0743916824480757,
+           2.039257372513315,
+           1.9916641756391442,
+           1.9326487735009203,
+           1.8634868455975095,
+           1.7856673923460935,
+           1.7008619258929998,
+           1.6108892230227232,
+           1.5176764438847368,
+           1.4232175104304003,
+           1.3295297072215142,
+           1.2386095129223733,
+           1.1523886921681812,
+           1.0726916740581531,
+           1.0011952153036743,
+           0.9393912937297002,
+           0.8885541026320504,
+           0.8497119202455845,
+           0.8236245136070364,
+           0.8107666051882929,
+           0.8113177870100551,
+           0.8251591140128463,
+           0.8518764499804459,
+           0.890770479133565,
+           0.9408731385332433,
+           1.0009700744931365,
+           1.069628583987622,
+           1.1452303730076223,
+           1.2260083510834745,
+           1.310086587486595,
+           1.395522482194119,
+           1.4803501552841127,
+           1.5626240331884886,
+           1.6404616097380147,
+           1.7120843841516062,
+           1.7758560264088477,
+           1.8303168915667363,
+           1.8742140967489744,
+           1.906526485442452,
+           1.9264839306195223,
+           1.9335805679163118,
+           1.9275816991765957,
+           1.9085242614346827,
+           1.8767109130424025,
+           1.8326979432905526,
+           1.777277360736282,
+           1.7114536548785144,
+           1.6364158524179062,
+           1.5535056000151968,
+           1.4641820975420368,
+           1.3699847770877855,
+           1.2724946717510575,
+           1.173295443375108,
+           1.0739350393385956,
+           0.9758889253477303,
+           0.8805257945503745,
+           0.7890765844478504,
+           0.7026075438067296,
+           0.6219979843658537,
+           0.5479232293361691,
+           0.4808431356226521,
+           0.42099642277922145,
+           0.36840089257339753,
+           0.3228594724451911,
+           0.2839718678810734,
+           0.25115146651083065,
+           0.22364700413592337,
+           0.20056838322949214,
+           0.18091593069735512,
+           0.1636122964394154,
+           0.14753612961694965,
+           0.13155662710767232,
+           0.11456802945164911,
+           0.09552314410590047,
+           0.07346500388622212,
+           0.047555819341487136,
+           0.01710245616499891,
+           -0.01842223925443777,
+           -0.059362833749523065,
+           -0.10586986456859424,
+           -0.15789386849482015,
+           -0.21518504844784095,
+           -0.277298595737945,
+           -0.34360553820018275,
+           -0.4133088396941494,
+           -0.48546433859164634,
+           -0.5590059853945731,
+           -0.6327747257756132,
+           -0.7055502780196702,
+           -0.7760849755560474,
+           -0.8431387880248444,
+           -0.9055145996031576,
+           -0.9620928120498855,
+           -1.011864352445646,
+           -1.0539612016427817,
+           -1.0876836181441858,
+           -1.1125233120726354,
+           -1.1281819231127868,
+           -1.1345842723571606,
+           -1.1318859879897099,
+           -1.1204752454656124,
+           -1.1009685107879388,
+           -1.0742003269475537,
+           -1.0412073347927948,
+           -1.0032068667395029,
+           -0.9615705911220643,
+           -0.9177938131100768,
+           -0.8734611517340081,
+           -0.8302094087916587,
+           -0.7896885217869882,
+           -0.7535215476138853,
+           -0.7232646550077284,
+           -0.700368110989541,
+           -0.6861392293600976,
+           -0.6817082081081357,
+           -0.6879977183169069,
+           -0.705697021300587,
+           -0.7352412853274929,
+           -0.7767966509288526,
+           -0.8302514574134859,
+           -0.8952138961261934,
+           -0.9710162017873988,
+           -1.0567253357030117,
+           -1.1511599575955418,
+           -1.252913330132853,
+           -1.3603816556728103,
+           -1.4717972118582705,
+           -1.5852655347655569,
+           -1.6988057982447946,
+           -1.8103934583717312,
+           -1.9180041745419378,
+           -2.0196579851158547,
+           -2.113462706524301,
+           -2.1976555406203953,
+           -2.2706419154597657,
+           -2.3310306486477246,
+           -2.3776646083743156,
+           -2.4096461531895117,
+           -2.4263567548858305,
+           -2.4274703465620076,
+           -2.4129600866941776,
+           -2.3830983862246464,
+           -2.3384502054951,
+           -2.2798597874152193,
+           -2.2084311486904946,
+           -2.1255027984583217,
+           -2.032617289718552,
+           -1.9314863301964909,
+           -1.8239522828096062,
+           -1.711946969227736,
+           -1.5974487511212976,
+           -1.4824389011302683,
+           -1.368858288487434,
+           -1.2585653923251476,
+           -1.1532966193252896,
+           -1.0546298424787015,
+           -0.9639519958189556,
+           -0.8824314581411429,
+           -0.8109958394505817,
+           -0.750315650174116,
+           -0.7007941883234684,
+           -0.6625638274080589,
+           -0.6354887317159331,
+           -0.6191738694631688,
+           -0.6129800420920348,
+           -0.6160445034101403,
+           -0.6273066088435856,
+           -0.645537816080072,
+           -0.6693752566924046,
+           -0.6973580164132942,
+           -0.727965201538114,
+           -0.7596548318800261,
+           -0.7909025876306296,
+           -0.8202394486313952,
+           -0.8462872995764055,
+           -0.8677916325928319,
+           -0.883650557961713,
+           -0.8929394323986868,
+           -0.8949305297852068,
+           -0.8891073085849277,
+           -0.87517297011658,
+           -0.8530531488454827,
+           -0.8228927261931961,
+           -0.7850469092644646,
+           -0.7400668615868178,
+           -0.6886803107965611,
+           -0.6317676847348653,
+           -0.5703344394772903,
+           -0.5054803376156753,
+           -0.4383665102864558,
+           -0.37018119013344153,
+           -0.30210503328757476,
+           -0.23527695579734403,
+           -0.1707613936001296,
+           -0.10951785553221303,
+           -0.05237357706344265,
+           -4.640365548799258e-16
+          ],
+          [
+           0,
+           0.04473933418560056,
+           0.0839081719584963,
+           0.11749954519667308,
+           0.14570468893276076,
+           0.16890750530274243,
+           0.1876735707511887,
+           0.20273396830679663,
+           0.21496436258907017,
+           0.22535986050952067,
+           0.2350063121982369,
+           0.2450488016723509,
+           0.2566581527354587,
+           0.2709963306015859,
+           0.2891816523448687,
+           0.31225472861970993,
+           0.3411460448929843,
+           0.3766460529888243,
+           0.41937858396112476,
+           0.4697783126354179,
+           0.5280729045834678,
+           0.594270360271804,
+           0.6681519415377009,
+           0.7492709256161464,
+           0.8369572851582439,
+           0.9303282427126902,
+           1.028304498742342,
+           1.1296317871659824,
+           1.2329072752998635,
+           1.33661019938255,
+           1.4391360157800377,
+           1.5388332543102292,
+           1.6340421862916819,
+           1.723134367819262,
+           1.804552089770036,
+           1.8768467609467634,
+           1.9387152697820562,
+           1.9890334127638496,
+           2.0268855432235804,
+           2.0515896808074006,
+           2.06271742775502,
+           2.0601081604892784,
+           2.0438771010062546,
+           2.0144170188420105,
+           1.9723934674082808,
+           1.9187336144929263,
+           1.8546088818882196,
+           1.7814117596310548,
+           1.700727302512112,
+           1.6142999468324009,
+           1.523996400639074,
+           1.4317654580060895,
+           1.3395956649243634,
+           1.249471819111526,
+           1.1633313171683592,
+           1.0830213692009263,
+           1.0102580830956056,
+           0.9465883784846235,
+           0.8933556250705976,
+           0.8516698129597934,
+           0.8223829560849145,
+           0.8060703062596422,
+           0.8030178178953618,
+           0.8132161552649714,
+           0.8363613790197821,
+           0.8718622902257278,
+           0.9188542523365092,
+           0.9762191581007482,
+           1.042611063134827,
+           1.1164868743088756,
+           1.1961413624284094,
+           1.2797456678189438,
+           1.3653883867686114,
+           1.4511182682891128,
+           1.534987515709656,
+           1.6150946770326873,
+           1.6896261219690938,
+           1.7568951417439354,
+           1.8153777691403947,
+           1.8637444992790753,
+           1.9008871942327812,
+           1.9259405741969757,
+           1.938297831602045,
+           1.9376200489553743,
+           1.9238392527694905,
+           1.8971550909297041,
+           1.8580252754647923,
+           1.8071500831099598,
+           1.74545134860541,
+           1.6740465168721221,
+           1.5942184368522225,
+           1.5073816790652157,
+           1.4150462384197804,
+           1.318779541635822,
+           1.2201677134154947,
+           1.1207770664724397,
+           1.0221167674948368,
+           0.925603594486244,
+           0.832529641690445,
+           0.7440337480135544,
+           0.6610773255813278,
+           0.5844251493513642,
+           0.5146315394839811,
+           0.4520322287364905,
+           0.3967420610068499,
+           0.34865851799790576,
+           0.30747092255402597,
+           0.27267502326420223,
+           0.24359252903710854,
+           0.2193950379333135,
+           0.1991316946937943,
+           0.18175981886766016,
+           0.16617767251258053,
+           0.15125848492050575,
+           0.13588482297027157,
+           0.11898239021788144,
+           0.0995523558068075,
+           0.07670135522644903,
+           0.04966836780116334,
+           0.017847758938672093,
+           -0.019192123521281586,
+           -0.061695292622023085,
+           -0.10970976952905843,
+           -0.16308476013228754,
+           -0.22147344183738457,
+           -0.2843412946391313,
+           -0.35097976544135057,
+           -0.42052491475100406,
+           -0.4919805638821064,
+           -0.5642453419910043,
+           -0.636142928656752,
+           -0.7064547019658852,
+           -0.7739539363599957,
+           -0.8374406505545364,
+           -0.8957761847895772,
+           -0.947916589104978,
+           -0.9929439302302175,
+           -1.0300946734401633,
+           -1.058784366173743,
+           -1.0786279406177284,
+           -1.0894550605936095,
+           -1.0913200612739702,
+           -1.0845061654353507,
+           -1.0695238037610053,
+           -1.0471030155491816,
+           -1.0181800563385066,
+           -0.9838784866675816,
+           -0.9454851577314014,
+           -0.9044216415177617,
+           -0.8622117717730378,
+           -0.8204460648472909,
+           -0.7807438734852491,
+           -0.744714189804518,
+           -0.7139160543898952,
+           -0.6898195455443383,
+           -0.6737683157663223,
+           -0.6669446115613686,
+           -0.670337658428485,
+           -0.6847162165558438,
+           -0.7106060162286457,
+           -0.7482726675149783,
+           -0.7977105092194465,
+           -0.8586377205266066,
+           -0.9304978686464972,
+           -1.0124679107902255,
+           -1.1034725127395089,
+           -1.202204392959003,
+           -1.3071502544013691,
+           -1.4166217294867054,
+           -1.5287906405701772,
+           -1.6417277715879428,
+           -1.7534442591339203,
+           -1.861934645141231,
+           -1.9652205902755882,
+           -2.061394228181432,
+           -2.148660146355359,
+           -2.225375009551055,
+           -2.290083895541077,
+           -2.3415524894861024,
+           -2.3787943802505165,
+           -2.401092817407988,
+           -2.4080164186043356,
+           -2.3994284602102027,
+           -2.375489536321895,
+           -2.336653528457584,
+           -2.283656986923769,
+           -2.2175021809371507,
+           -2.139434224386149,
+           -2.050912823966648,
+           -1.953579322935265,
+           -1.8492198238273743,
+           -1.7397252645257943,
+           -1.627049391848963,
+           -1.5131656236868511,
+           -1.400023813543445,
+           -1.289507929632957,
+           -1.1833956345103847,
+           -1.0833207012835862,
+           -0.9907391300239512,
+           -0.9068997348858749,
+           -0.832819860987568,
+           -0.7692667630686837,
+           -0.7167450384752072,
+           -0.6754903585787536,
+           -0.6454695889810074,
+           -0.6263872335729835,
+           -0.6176979845315597,
+           -0.618625013396081,
+           -0.6281835010727814,
+           -0.6452087803149337,
+           -0.6683883559444032,
+           -0.696296978435212,
+           -0.7274338776241698,
+           -0.7602612168802447,
+           -0.7932428051264906,
+           -0.8248821051540122,
+           -0.8537586015882832,
+           -0.8785616399630128,
+           -0.8981209183501824,
+           -0.9114329030689667,
+           -0.9176825478379858,
+           -0.9162598185933128,
+           -0.90677066094943,
+           -0.889042190522206,
+           -0.8631220344468303,
+           -0.8292719016808044,
+           -0.7879556063313069,
+           -0.7398219086098027,
+           -0.68568266857989,
+           -0.6264869253646665,
+           -0.5632916159872821,
+           -0.4972297310087305,
+           -0.42947676654470157,
+           -0.36121637255196143,
+           -0.2936061144955254,
+           -0.22774425924349934,
+           -0.1646384664802749,
+           -0.10517721486040985,
+           -0.05010471889032582,
+           -4.422840629188771e-16
+          ],
+          [
+           0,
+           0.042381078013642756,
+           0.07924438062789622,
+           0.11068365232453298,
+           0.1369864078867461,
+           0.15862542891321957,
+           0.17624500080639707,
+           0.19064224712728037,
+           0.20274404707658022,
+           0.2135801384270025,
+           0.22425310952338154,
+           0.23590606739858155,
+           0.24968883248362053,
+           0.26672355218206106,
+           0.2880706446361315,
+           0.31469597981093933,
+           0.3474401776236241,
+           0.3869908528899496,
+           0.43385856556307667,
+           0.4883571438476994,
+           0.5505889395318146,
+           0.6204354519719587,
+           0.6975536226522835,
+           0.7813779594666935,
+           0.8711285024130119,
+           0.9658244939301845,
+           1.0643034713774777,
+           1.1652453598122279,
+           1.267201013781611,
+           1.3686245405764546,
+           1.4679086372521482,
+           1.563422092258709,
+           1.653548541834889,
+           1.7367255329932667,
+           1.8114829299854671,
+           1.8764797100405541,
+           1.9305382267759723,
+           1.972675075260986,
+           2.0021277699678772,
+           2.018376543936612,
+           2.0211606920694276,
+           2.010489010789751,
+           1.9866440272021177,
+           1.95017985994023,
+           1.9019137074452324,
+           1.842911113713081,
+           1.7744653128009629,
+           1.6980710978682918,
+           1.615393794688269,
+           1.5282340400900742,
+           1.438489169697724,
+           1.3481121040430453,
+           1.259068685536748,
+           1.1732944592957566,
+           1.0926519074168044,
+           1.0188891385140217,
+           0.9536010023554747,
+           0.8981935439888201,
+           0.8538526341632269,
+           0.8215175150005498,
+           0.8018598841088296,
+           0.7952690094697289,
+           0.8018432246445267,
+           0.8213880025988176,
+           0.8534206504201715,
+           0.8971815101886942,
+           0.9516513970746375,
+           1.0155748581267927,
+           1.08748869776533,
+           1.1657550920371518,
+           1.248598506233581,
+           1.3341455421051975,
+           1.420466773764094,
+           1.5056195870447941,
+           1.5876910166459695,
+           1.6648395792542539,
+           1.7353351289200107,
+           1.7975958124815044,
+           1.8502212765116761,
+           1.8920213712435365,
+           1.922039708871375,
+           1.9395715607454593,
+           1.9441757171276048,
+           1.9356800809148136,
+           1.9141809194235044,
+           1.880035852198512,
+           1.8338508040880492,
+           1.7764612977990573,
+           1.7089085952707668,
+           1.6324113191827276,
+           1.548333291783666,
+           1.4581484154307172,
+           1.3634034856738202,
+           1.265679871834853,
+           1.166555020799722,
+           1.0675647367296002,
+           0.9701671627612627,
+           0.8757093412486872,
+           0.7853971580085073,
+           0.7002693852133123,
+           0.6211764293595791,
+           0.5487642678789829,
+           0.48346392358017115,
+           0.4254866836008496,
+           0.37482512251039274,
+           0.33125984133123404,
+           0.2943716892555316,
+           0.26355909635629926,
+           0.23806001709335356,
+           0.2169778691021579,
+           0.1993107525003091,
+           0.18398315421681413,
+           0.1698792816399524,
+           0.15587713166884545,
+           0.14088238596573113,
+           0.12386123118714297,
+           0.10387123398401744,
+           0.08008945378540885,
+           0.0518370504420577,
+           0.018599736805056902,
+           -0.01995646412376924,
+           -0.06397457450036616,
+           -0.11340141246911652,
+           -0.16798788038104528,
+           -0.22729478742218875,
+           -0.2907040588647875,
+           -0.3574350430539325,
+           -0.42656549343691047,
+           -0.4970566798339875,
+           -0.5677819738719155,
+           -0.6375581608432266,
+           -0.7051786565863043,
+           -0.7694477551986877,
+           -0.8292150028700599,
+           -0.8834087856641929,
+           -0.9310682349238677,
+           -0.9713725927663988,
+           -1.0036672409496274,
+           -1.027485677733982,
+           -1.0425668272421502,
+           -1.0488671817523965,
+           -1.0465674064752526,
+           -1.0360731754415091,
+           -1.0180101527012793,
+           -0.9932131814589509,
+           -0.962709891328128,
+           -0.9276990768788752,
+           -0.8895243354678094,
+           -0.8496435755869015,
+           -0.8095951155184483,
+           -0.7709611831791471,
+           -0.7353296993428171,
+           -0.7042552761035178,
+           -0.6792203891673573,
+           -0.6615976855983785,
+           -0.6526143678348274,
+           -0.6533195505719457,
+           -0.6645554204929539,
+           -0.6869329413954732,
+           -0.720812741099881,
+           -0.7662916942009224,
+           -0.8231955792012555,
+           -0.8910780431453382,
+           -0.9692259551049419,
+           -1.0566710754682829,
+           -1.1522078147399297,
+           -1.254416707234154,
+           -1.3616930852903466,
+           -1.472280311902505,
+           -1.584306817091393,
+           -1.6958260887457242,
+           -1.8048586943682174,
+           -1.9094353580381813,
+           -2.0076400882579533,
+           -2.097652347922895,
+           -2.1777872775897626,
+           -2.2465330270628154,
+           -2.302584317032031,
+           -2.3448714404827675,
+           -2.3725840207286413,
+           -2.3851889666062767,
+           -2.3824422026127205,
+           -2.3643938992313056,
+           -2.3313870827967014,
+           -2.2840496612484857,
+           -2.2232800581983203,
+           -2.1502267990949644,
+           -2.066262536236837,
+           -1.9729531304832097,
+           -1.8720225235742802,
+           -1.7653142331794924,
+           -1.6547503807829211,
+           -1.5422892184137027,
+           -1.4298821527085015,
+           -1.3194312730986995,
+           -1.212748374887145,
+           -1.1115164280544896,
+           -1.0172543798356557,
+           -0.9312860950143789,
+           -0.8547141346014574,
+           -0.7883989536596218,
+           -0.7329439654897868,
+           -0.6886867755045077,
+           -0.6556967374376572,
+           -0.6337788307880355,
+           -0.6224837053504915,
+           -0.621123590108172,
+           -0.6287936232821507,
+           -0.6443980313914068,
+           -0.6666804709056908,
+           -0.6942577492458292,
+           -0.7256560648322065,
+           -0.7593488504403352,
+           -0.7937952715900755,
+           -0.8274784227998147,
+           -0.8589422794181238,
+           -0.886826500951625,
+           -0.9098982423101035,
+           -0.9270802106063748,
+           -0.937474304986212,
+           -0.9403802928708299,
+           -0.9353091050235135,
+           -0.9219904707360096,
+           -0.9003747596620142,
+           -0.87062904474668,
+           -0.8331275475946543,
+           -0.7884367697996237,
+           -0.7372957476658146,
+           -0.6805919900394016,
+           -0.6193337665860791,
+           -0.5546195041228603,
+           -0.4876051193000327,
+           -0.4194701652903247,
+           -0.35138369697167143,
+           -0.28447076275033784,
+           -0.21978041160853087,
+           -0.1582560617046998,
+           -0.10070901300602704,
+           -0.04779580263408223,
+           -4.2038483273725974e-16
+          ],
+          [
+           0,
+           0.040049294538061185,
+           0.07468049758121535,
+           0.10408500882074903,
+           0.1286419591632936,
+           0.14890687313738232,
+           0.1655953110749863,
+           0.17956191843022898,
+           0.1917754304968615,
+           0.20329028776729155,
+           0.21521560751023666,
+           0.22868232852021184,
+           0.2448093965744725,
+           0.26466988660805185,
+           0.2892579632266648,
+           0.3194575637365862,
+           0.3560136477758645,
+           0.3995067958483503,
+           0.45033185710350293,
+           0.5086812465925487,
+           0.5745333764462495,
+           0.6476465768399042,
+           0.727558724441963,
+           0.8135926517349893,
+           0.9048672637632355,
+           1.0003141431821552,
+           1.0986992836224092,
+           1.1986494588827743,
+           1.2986826146794566,
+           1.3972415636655662,
+           1.4927301758937892,
+           1.5835511880980513,
+           1.6681447078998233,
+           1.7450264645534135,
+           1.812824856820204,
+           1.8703158711103336,
+           1.9164549886728581,
+           1.9504052682984223,
+           1.9715608791195591,
+           1.979565464540311,
+           1.9743248405279894,
+           1.9560136664890004,
+           1.9250758714388883,
+           1.8822187686333625,
+           1.8284009445672376,
+           1.7648141595229379,
+           1.69285964294014,
+           1.6141193041843094,
+           1.5303225044256872,
+           1.443309145206986,
+           1.3549899211531566,
+           1.2673046558747012,
+           1.1821796896452998,
+           1.1014853136447869,
+           1.0269942477682354,
+           0.9603421371199223,
+           0.9029909968352049,
+           0.8561964668819062,
+           0.8209796496160136,
+           0.7981041952476401,
+           0.7880591766164278,
+           0.7910481577808077,
+           0.8069847142163876,
+           0.8354945094593001,
+           0.8759238775386042,
+           0.927354706297733,
+           0.9886252674576711,
+           1.0583564986499492,
+           1.1349831140597573,
+           1.2167888068857584,
+           1.301944711289132,
+           1.3885502161743635,
+           1.4746751698270915,
+           1.5584024843973883,
+           1.6378701431561669,
+           1.7113116314756893,
+           1.777093854109306,
+           1.8337516655098394,
+           1.8800182250172095,
+           1.9148504926409455,
+           1.937449301278889,
+           1.9472735745740322,
+           1.9440484029193306,
+           1.9277668398402843,
+           1.8986854334299705,
+           1.8573136589343064,
+           1.8043975652723507,
+           1.7408980866376345,
+           1.6679645969848365,
+           1.5869043970808354,
+           1.4991489181812852,
+           1.4062175010128992,
+           1.3096796618209954,
+           1.2111167875422986,
+           1.112084209012249,
+           1.0140745844249883,
+           0.9184834855278083,
+           0.8265780173162063,
+           0.7394692199108706,
+           0.6580889009563317,
+           0.583171430845509,
+           0.5152409042922176,
+           0.45460393350390504,
+           0.40134819393826454,
+           0.3553466969905782,
+           0.3162676186370703,
+           0.28358937269542595,
+           0.2566204854690345,
+           0.2345237084096264,
+           0.216343700056622,
+           0.20103752050884963,
+           0.18750711323335187,
+           0.17463290180112023,
+           0.1613076043095442,
+           0.14646936639103825,
+           0.1291333348237621,
+           0.10842083728285834,
+           0.08358539856542965,
+           0.054034908021605585,
+           0.019349354767222795,
+           -0.020706336057227256,
+           -0.06617470415229454,
+           -0.11690359304985763,
+           -0.17254948593509983,
+           -0.23258625320591556,
+           -0.29631908501699583,
+           -0.3629032461379516,
+           -0.4313671637316543,
+           -0.5006392443541855,
+           -0.5695777175035791,
+           -0.6370027219291461,
+           -0.7017297897361932,
+           -0.762603843662283,
+           -0.8185328058001343,
+           -0.8685199219714468,
+           -0.9116939348094072,
+           -0.9473362897022639,
+           -0.9749046298432374,
+           -0.9940519279504989,
+           -1.0046407105065913,
+           -1.0067519529315017,
+           -1.0006883578962114,
+           -0.9869718706658802,
+           -0.9663354313912508,
+           -0.9397091109850015,
+           -0.9082009209436996,
+           -0.8730727245898434,
+           -0.8357118042539352,
+           -0.7975987526789028,
+           -0.7602724545191768,
+           -0.725293002730676,
+           -0.6942034528727383,
+           -0.6684913543460614,
+           -0.6495510103989931,
+           -0.6386474079495496,
+           -0.6368827240792764,
+           -0.6451662592261372,
+           -0.6641885689688675,
+           -0.6944004687178922,
+           -0.7359974709569201,
+           -0.7889100856920631,
+           -0.8528002745990116,
+           -0.9270642014339344,
+           -1.0108412692092479,
+           -1.103029282159649,
+           -1.2023054213824442,
+           -1.3071525809003373,
+           -1.415890479268105,
+           -1.5267108439797572,
+           -1.6377158647479015,
+           -1.7469590297351443,
+           -1.8524873980632761,
+           -1.9523843239354521,
+           -2.0448116334491147,
+           -2.128050265039359,
+           -2.2005384182711922,
+           -2.260906312603427,
+           -2.3080067364187316,
+           -2.340940665160935,
+           -2.359077343461109,
+           -2.3620683568575096,
+           -2.3498553609495856,
+           -2.3226712861184846,
+           -2.281034990643654,
+           -2.2257394903864465,
+           -2.157834045421196,
+           -2.0786005293729097,
+           -1.9895246422377593,
+           -1.8922626488421053,
+           -1.7886044298974304,
+           -1.6804337182997804,
+           -1.5696864578393923,
+           -1.4583082632875686,
+           -1.3482119789276796,
+           -1.2412363265929982,
+           -1.1391066043540308,
+           -1.0433983439366512,
+           -0.9555047600907145,
+           -0.8766087303405997,
+           -0.8076599311956819,
+           -0.7493576297671538,
+           -0.7021394909749737,
+           -0.6661766135619028,
+           -0.6413748565830603,
+           -0.6273823656375557,
+           -0.6236030585956089,
+           -0.6292156876137044,
+           -0.6431979613155975,
+           -0.6643550913875498,
+           -0.6913520243956234,
+           -0.7227485348788042,
+           -0.7570362917335597,
+           -0.7926769680962322,
+           -0.8281404463074119,
+           -0.8619421744893452,
+           -0.8926787595798156,
+           -0.9190609325602938,
+           -0.9399430937507958,
+           -0.9543487375510022,
+           -0.961491164542122,
+           -0.9607890116631789,
+           -0.9518762651252237,
+           -0.9346065624438137,
+           -0.9090517358823823,
+           -0.8754946960386355,
+           -0.834416897598602,
+           -0.786480765839845,
+           -0.7325075888737468,
+           -0.673451493723352,
+           -0.6103702213243009,
+           -0.5443934940058944,
+           -0.47668982702034207,
+           -0.4084326718198197,
+           -0.34076679216347927,
+           -0.27477576447320085,
+           -0.21145146143059923,
+           -0.15166632347326867,
+           -0.09614914801098084,
+           -0.045465032762774325,
+           -3.985078954610722e-16
+          ],
+          [
+           0,
+           0.03776113089419496,
+           0.07024901025820812,
+           0.09774879032879372,
+           0.12072579551420239,
+           0.1398115077887247,
+           0.15578481023370214,
+           0.16954898138173594,
+           0.18210504505606034,
+           0.1945221770531845,
+           0.20790594882588598,
+           0.22336524726535023,
+           0.24197874723432705,
+           0.2647618286834462,
+           0.29263482256835427,
+           0.32639343952726246,
+           0.3666821830979016,
+           0.4139714764230387,
+           0.46853913970883837,
+           0.5304567474311053,
+           0.5995812721218277,
+           0.675552288556475,
+           0.7577948716233527,
+           0.8455281766065156,
+           0.9377795456776213,
+           1.0334038427106986,
+           1.131107583674236,
+           1.2294773052215087,
+           1.327011502848415,
+           1.4221553749473457,
+           1.513337532685824,
+           1.599007779851687,
+           1.6776750330939687,
+           1.7479444422667962,
+           1.8085527831982944,
+           1.8584012309246218,
+           1.896584679443087,
+           1.9224168529849401,
+           1.9354505518027696,
+           1.9354924901479673,
+           1.9226123127006696,
+           1.8971455150778391,
+           1.8596901407816202,
+           1.8110972774673497,
+           1.7524555260155046,
+           1.6850697628820683,
+           1.6104346559568183,
+           1.5302035232300708,
+           1.4461532387641802,
+           1.3601459889304788,
+           1.2740887611575051,
+           1.1898915055612118,
+           1.1094249453290899,
+           1.0344790236980028,
+           0.9667229634667748,
+           0.9076678794715213,
+           0.8586328261557001,
+           0.8207150826794427,
+           0.7947653788498397,
+           0.781368648911242,
+           0.7808307697269022,
+           0.7931715982763874,
+           0.8181244741258379,
+           0.8551421992275422,
+           0.903409353797835,
+           0.9618606568422365,
+           1.0292049367936411,
+           1.1039541451794426,
+           1.1844567274529358,
+           1.2689345629913822,
+           1.3555226032466194,
+           1.4423102751331207,
+           1.527383677433906,
+           1.6088675822217793,
+           1.684966261381598,
+           1.754002190040665,
+           1.8144517332541399,
+           1.8649769982751396,
+           1.9044531302669712,
+           1.9319904420117597,
+           1.946950895242315,
+           1.9489585895304073,
+           1.9379040607917208,
+           1.9139423418170722,
+           1.877484888114394,
+           1.829185620045051,
+           1.7699214731444632,
+           1.7007679791897783,
+           1.6229705178341438,
+           1.5379119796246612,
+           1.4470776635228682,
+           1.3520182936845864,
+           1.2543120797768494,
+           1.1555267616118248,
+           1.0571825720307773,
+           0.9607170220256621,
+           0.8674523598638236,
+           0.7785664828562814,
+           0.6950679882723868,
+           0.6177759411111201,
+           0.547304813760435,
+           0.4840549191174382,
+           0.42820851787386227,
+           0.3797316359397902,
+           0.33838148302005155,
+           0.3037192218065652,
+           0.2751277026478511,
+           0.25183365426552873,
+           0.23293371020386028,
+           0.21742355597810656,
+           0.20422940567672404,
+           0.19224096094937018,
+           0.18034497124103996,
+           0.16745850262817433,
+           0.15256103392301096,
+           0.13472453251193825,
+           0.11314071779116135,
+           0.08714479562528893,
+           0.05623504104191317,
+           0.020087715991171824,
+           -0.021433068350340923,
+           -0.06827080268767677,
+           -0.1201774629752808,
+           -0.1767198027720133,
+           -0.2372908897886119,
+           -0.3011265845015277,
+           -0.3673265290555437,
+           -0.4348790960016315,
+           -0.5026896417367658,
+           -0.5696113214980365,
+           -0.6344776536658557,
+           -0.696135972726421,
+           -0.7534808837887564,
+           -0.8054868277519814,
+           -0.851238885209613,
+           -0.8899609885225314,
+           -0.9210407741902742,
+           -0.9440503901631612,
+           -0.9587626730266487,
+           -0.9651622255656312,
+           -0.9634510532037527,
+           -0.9540485550181106,
+           -0.9375858080228768,
+           -0.9148942286150153,
+           -0.886988838836869,
+           -0.8550465038191957,
+           -0.8203796369269312,
+           -0.7844059874488762,
+           -0.7486152291493351,
+           -0.7145331539968173,
+           -0.6836843416944739,
+           -0.6575542205364043,
+           -0.6375514574110912,
+           -0.6249716138342604,
+           -0.6209629806623644,
+           -0.6264954571360613,
+           -0.6423332712194703,
+           -0.6690122494644075,
+           -0.7068222379691108,
+           -0.7557951539966956,
+           -0.8156990134339023,
+           -0.8860381357820932,
+           -0.9660595792887942,
+           -1.0547657078032457,
+           -1.150932641682659,
+           -1.253134201259981,
+           -1.3597708165547622,
+           -1.469102754396054,
+           -1.5792869069639544,
+           -1.6884162966041738,
+           -1.7945613828492255,
+           -1.8958122106187383,
+           -1.9903204147591207,
+           -2.0763400960441873,
+           -2.1522666075326886,
+           -2.216672337223664,
+           -2.2683386421505936,
+           -2.3062831787517992,
+           -2.329781982385309,
+           -2.3383857726076474,
+           -2.3319300973088493,
+           -2.310539074677439,
+           -2.2746226437155515,
+           -2.2248673879475724,
+           -2.1622211493238,
+           -2.0878717964103153,
+           -2.0032206492037883,
+           -1.9098511889584082,
+           -1.8094937922055023,
+           -1.7039873210021617,
+           -1.5952384741233383,
+           -1.4851798546662884,
+           -1.3757277371605816,
+           -1.2687405211321836,
+           -1.165978838099588,
+           -1.069068235712698,
+           -0.9794652972790014,
+           -0.8984279688984794,
+           -0.8269907619925886,
+           -0.7659453787557863,
+           -0.7158271749578473,
+           -0.6769077318686612,
+           -0.649193660381699,
+           -0.6324316093362582,
+           -0.6261193002926742,
+           -0.6295222662694089,
+           -0.6416958357460564,
+           -0.6615117788937187,
+           -0.6876889235361052,
+           -0.7188269564190828,
+           -0.7534425531822064,
+           -0.7900069296990402,
+           -0.8269838793647386,
+           -0.8628673560771514,
+           -0.8962176811217416,
+           -0.9256954933928218,
+           -0.9500926252625206,
+           -0.9683591693074742,
+           -0.9796261018907629,
+           -0.9832229457015197,
+           -0.9786900818306123,
+           -0.9657854595588912,
+           -0.944485595285855,
+           -0.9149808973285366,
+           -0.8776654970261006,
+           -0.8331219050962129,
+           -0.7821009420416638,
+           -0.7254975093612387,
+           -0.6643228714413997,
+           -0.5996742037364311,
+           -0.5327022290653548,
+           -0.4645778089383436,
+           -0.3964583796804285,
+           -0.32945512321257603,
+           -0.26460173971895773,
+           -0.20282564468498407,
+           -0.1449223470990012,
+           -0.09153368066347725,
+           -0.043130457834020294,
+           -3.768186435540968e-16
+          ],
+          [
+           0,
+           0.03553295222891896,
+           0.06598043276517529,
+           0.0917166508105038,
+           0.11328700836186595,
+           0.1313915875256206,
+           0.1468642100782241,
+           0.16064762154271614,
+           0.17376545442499058,
+           0.187291710953867,
+           0.20231857250309465,
+           0.21992338912420822,
+           0.2411357270862674,
+           0.2669053543489913,
+           0.2980720234008834,
+           0.3353378683515862,
+           0.37924316961115473,
+           0.4301461564812571,
+           0.4882074175787871,
+           0.5533793737055132,
+           0.625401140441158,
+           0.7037989715512366,
+           0.7878923326728099,
+           0.876805511221062,
+           0.9694845266520535,
+           1.0647189686910397,
+           1.1611682633354832,
+           1.2573917506007122,
+           1.3518818570352682,
+           1.443099562568492,
+           1.529511297409788,
+           1.6096263621589608,
+           1.6820339441440073,
+           1.7454388058563346,
+           1.7986947472115067,
+           1.8408349916629787,
+           1.8710987158144288,
+           1.8889530314593743,
+           1.8941098357792465,
+           1.886537067168619,
+           1.8664640378688044,
+           1.834380657015895,
+           1.7910305053612965,
+           1.7373978721805061,
+           1.6746890120806632,
+           1.604308020924569,
+           1.5278278624169521,
+           1.4469571967759323,
+           1.3635037673686021,
+           1.2793351876275836,
+           1.19633803682892,
+           1.1163762177358656,
+           1.0412495505683084,
+           0.9726535756761825,
+           0.9121415116870177,
+           0.8610892673499247,
+           0.8206643349609095,
+           0.7917993028136439,
+           0.7751706157549635,
+           0.7711830892566556,
+           0.7799605464412286,
+           0.8013428025195424,
+           0.8348890706340466,
+           0.8798877108099727,
+           0.9353720933002035,
+           1.0001422027243612,
+           1.0727914735692519,
+           1.15173822413507,
+           1.2352609478743186,
+           1.3215366308967114,
+           1.40868119438017,
+           1.4947911124177082,
+           1.5779852305894795,
+           1.6564458088608875,
+           1.7284578342777925,
+           1.792445693785331,
+           1.8470063642040817,
+           1.8909383632860173,
+           1.9232658106815055,
+           1.94325706797602,
+           1.9504375597255994,
+           1.9445965193569714,
+           1.9257875514052363,
+           1.8943230512100395,
+           1.850762671207073,
+           1.7958961657103358,
+           1.730721080092734,
+           1.6564158722725622,
+           1.5743091614379972,
+           1.4858458884044137,
+           1.3925512417522605,
+           1.2959932522814335,
+           1.197744984217734,
+           1.099347254454746,
+           1.0022727909179565,
+           0.9078926984774811,
+           0.8174460368466211,
+           0.7320132312484083,
+           0.6524939354591752,
+           0.5795898507247793,
+           0.5137928759366052,
+           0.45537882758671355,
+           0.40440682584311755,
+           0.36072429916977616,
+           0.32397741787058226,
+           0.29362663031742336,
+           0.26896684784132796,
+           0.24915170850760032,
+           0.2332212491384674,
+           0.220132231489662,
+           0.2087903044898152,
+           0.19808314148143952,
+           0.18691367049763563,
+           0.1742325172519435,
+           0.1590688046254712,
+           0.1405584983566251,
+           0.11796955517769912,
+           0.09072321508513162,
+           0.05841088158801125,
+           0.02080615004505253,
+           -0.022128328387403348,
+           -0.07023932435489666,
+           -0.12318688682330303,
+           -0.18045347518218505,
+           -0.24135812554782035,
+           -0.3050752779895686,
+           -0.37065776902307845,
+           -0.43706338395674754,
+           -0.503184269339129,
+           -0.567878429242484,
+           -0.6300024723921949,
+           -0.6884447416765123,
+           -0.7421579442758794,
+           -0.7901904099079422,
+           -0.8317151362980055,
+           -0.8660558341974389,
+           -0.8927092577819822,
+           -0.9113631982538876,
+           -0.9219096266648298,
+           -0.924452593678387,
+           -0.9193106261659916,
+           -0.9070134998745768,
+           -0.8882934104279191,
+           -0.8640707080385007,
+           -0.8354345009140518,
+           -0.8036185649259087,
+           -0.7699731193150023,
+           -0.7359331369493363,
+           -0.7029839501463483,
+           -0.6726249869668023,
+           -0.6463325262645551,
+           -0.6255223912360295,
+           -0.6115135098954515,
+           -0.6054932565115666,
+           -0.608485450857594,
+           -0.6213218329935484,
+           -0.6446177516114581,
+           -0.6787527056347853,
+           -0.7238562641457672,
+           -0.7797997615992048,
+           -0.8461940267894601,
+           -0.9223932585532882,
+           -1.0075050122791918,
+           -1.1004061126104099,
+           -1.1997641629314064,
+           -1.30406418488605,
+           -1.4116397946818278,
+           -1.5207082104187504,
+           -1.6294082889369896,
+           -1.735840714087252,
+           -1.8381094028090654,
+           -1.9343631623568147,
+           -2.0228366222918073,
+           -2.1018894787418807,
+           -2.1700431256175987,
+           -2.226013807095634,
+           -2.268741506312406,
+           -2.2974138849158576,
+           -2.3114847044931324,
+           -2.310686291108641,
+           -2.2950357450930006,
+           -2.2648347463966654,
+           -2.220662957662678,
+           -2.1633651789896864,
+           -2.0940325564586706,
+           -2.01397828728492,
+           -1.9247083945108538,
+           -1.827888260318348,
+           -1.7253057064968034,
+           -1.6188314909493615,
+           -1.5103781484199648,
+           -1.4018581404585502,
+           -1.295142293143661,
+           -1.1920194909562023,
+           -1.0941585617284906,
+           -1.003073231636149,
+           -0.9200909521625348,
+           -0.8463263047680698,
+           -0.7826595760293159,
+           -0.7297209690716907,
+           -0.6878807793416155,
+           -0.6572457175449796,
+           -0.637661413493546,
+           -0.6287209853112378,
+           -0.6297794126188725,
+           -0.6399733135070198,
+           -0.6582455967100631,
+           -0.683374345534356,
+           -0.7140051915530639,
+           -0.7486863562342368,
+           -0.7859054794241528,
+           -0.8241273163586588,
+           -0.8618313704672123,
+           -0.8975485379460862,
+           -0.9298958716139354,
+           -0.9576086250639632,
+           -0.9795688121887105,
+           -0.9948296098647964,
+           -1.0026350405755198,
+           -1.0024344942486254,
+           -0.9938917814949262,
+           -0.9768885503977484,
+           -0.9515220425019174,
+           -0.9180973070821088,
+           -0.8771141325403478,
+           -0.8292490863973029,
+           -0.7753331774924346,
+           -0.7163257626538597,
+           -0.6532854125424831,
+           -0.5873385253303481,
+           -0.5196465305207936,
+           -0.4513725572510576,
+           -0.3836484510738673,
+           -0.3175430102936433,
+           -0.25403227780322146,
+           -0.1939726679543633,
+           -0.138077631759576,
+           -0.08689846962156005,
+           -0.04080979122537535,
+           -3.554772193663964e-16
+          ],
+          [
+           0,
+           0.033380188098396116,
+           0.06190302700405919,
+           0.0860263540098695,
+           0.10636891126999953,
+           0.12369153367612479,
+           0.1388742551755002,
+           0.15288993928827882,
+           0.16677513160508511,
+           0.18159890627325379,
+           0.19843053301023125,
+           0.21830682460928838,
+           0.24220003635016982,
+           0.2709871778725202,
+           0.3054215651508984,
+           0.3461073860204675,
+           0.39347797857170413,
+           0.447778429493592,
+           0.5090529913885314,
+           0.5771376969002969,
+           0.6516584162145277,
+           0.7320344663938957,
+           0.817487739558545,
+           0.9070571756685938,
+           0.9996182681631826,
+           1.0939071604269799,
+           1.1885487712835452,
+           1.2820882814934405,
+           1.3730252232689397,
+           1.4598493434124151,
+           1.5410773596896268,
+           1.6152897008052092,
+           1.6811663136597121,
+           1.7375206376799843,
+           1.7833308846051863,
+           1.8177678222974385,
+           1.8402183415088254,
+           1.8503041831508356,
+           1.8478953180970394,
+           1.833117599124889,
+           1.8063544421577478,
+           1.7682424381395647,
+           1.7196609441273933,
+           1.661715848902721,
+           1.5957178509694754,
+           1.523155721707005,
+           1.4456651503462268,
+           1.3649938772663912,
+           1.2829639151402126,
+           1.201431731366869,
+           1.122247318172224,
+           1.0472131073840163,
+           0.9780436944118972,
+           0.9163273201517719,
+           0.8634900207350091,
+           0.82076329416624,
+           0.789156051390237,
+           0.7694315191583175,
+           0.762089645646189,
+           0.7673554299264079,
+           0.7851734562688456,
+           0.8152087672338717,
+           0.85685405920769,
+           0.9092430340611927,
+           0.9712695946389246,
+           1.0416124333515788,
+           1.1187644356173452,
+           1.2010662063701554,
+           1.2867429310788414,
+           1.373943705040747,
+           1.4607824079993035,
+           1.5453791667443058,
+           1.6259014370964284,
+           1.7006037487961483,
+           1.7678651919812192,
+           1.8262237812513096,
+           1.874406911346331,
+           1.911357215263607,
+           1.936253248806988,
+           1.9485245522999006,
+           1.947860777375356,
+           1.9342147110004717,
+           1.907799176653364,
+           1.869077940219344,
+           1.8187508920933257,
+           1.757733913647283,
+           1.6871339623119326,
+           1.60822002196511,
+           1.522390661392505,
+           1.4311390209771278,
+           1.3360161046356738,
+           1.2385932890181908,
+           1.1404249743313621,
+           1.0430122906069836,
+           0.9477687401550268,
+           0.8559886022123083,
+           0.7688188508555901,
+           0.6872352440227343,
+           0.6120231323583857,
+           0.5437634143421438,
+           0.4828239318592546,
+           0.42935646137087213,
+           0.3832993136276469,
+           0.34438541301413145,
+           0.31215558966279044,
+           0.2859766868816955,
+           0.26506396645430685,
+           0.24850718797714233,
+           0.23529964823956437,
+           0.22436939494625377,
+           0.21461177759772482,
+           0.20492246832810512,
+           0.19423007766239006,
+           0.18152750464977946,
+           0.16590119724646493,
+           0.14655755620107905,
+           0.12284579255346531,
+           0.09427664321858757,
+           0.06053645857969406,
+           0.021496297767545088,
+           -0.022784201743041625,
+           -0.07205827676068187,
+           -0.1258987705455795,
+           -0.18370996374788268,
+           -0.2447441899023239,
+           -0.3081227958543559,
+           -0.3728608933015575,
+           -0.4378952475671713,
+           -0.5021145663303921,
+           -0.5643913864516457,
+           -0.6236147129096253,
+           -0.6787225413545772,
+           -0.7287333954807945,
+           -0.7727760323731688,
+           -0.8101165126704617,
+           -0.8401818967470416,
+           -0.8625799115587771,
+           -0.8771140332594293,
+           -0.8837935456722474,
+           -0.8828382613298209,
+           -0.8746777269087955,
+           -0.859944875101085,
+           -0.8394642267625043,
+           -0.8142348869990049,
+           -0.7854087131684893,
+           -0.7542641582016821,
+           -0.7221764060030826,
+           -0.6905845141019777,
+           -0.6609563596699587,
+           -0.6347522464226801,
+           -0.6133880701786995,
+           -0.59819895888048,
+           -0.5904042981659982,
+           -0.5910750261528511,
+           -0.6011040315641124,
+           -0.6211804188409477,
+           -0.6517683141286937,
+           -0.6930907791500133,
+           -0.7451192785795017,
+           -0.8075690135630749,
+           -0.8799002927295478,
+           -0.961325965881207,
+           -1.05082479811249,
+           -1.1471605170175154,
+           -1.2489061264839205,
+           -1.354472950768632,
+           -1.4621437553234669,
+           -1.5701091890920265,
+           -1.6765067092670927,
+           -1.7794610858720397,
+           -1.8771255416123123,
+           -1.9677225633042852,
+           -2.0495834253408636,
+           -2.121185493037615,
+           -2.1811864236897143,
+           -2.2284544545750764,
+           -2.2620940582512206,
+           -2.28146635411718,
+           -2.2862037887207594,
+           -2.2762187326927763,
+           -2.2517057861977854,
+           -2.2131377339071423,
+           -2.161255241101003,
+           -2.0970505309297582,
+           -2.021745425503955,
+           -1.936764266868753,
+           -1.8437023548145037,
+           -1.7442906439461865,
+           -1.640357529926875,
+           -1.533788622211105,
+           -1.4264854462734056,
+           -1.3203240412275894,
+           -1.2171144182971871,
+           -1.1185618218796718,
+           -1.0262306885621488,
+           -0.941512131563391,
+           -0.8655956903917854,
+           -0.7994459801996577,
+           -0.7437847549892557,
+           -0.6990787664580193,
+           -0.6655336591235285,
+           -0.6430939959162623,
+           -0.6314493602692999,
+           -0.6300463345020736,
+           -0.6381060135696421,
+           -0.654646581466595,
+           -0.6785103579450374,
+           -0.7083946186322182,
+           -0.7428854046408804,
+           -0.7804934704399139,
+           -0.8196914726900953,
+           -0.8589514790149585,
+           -0.8967818747819916,
+           -0.9317627678578055,
+           -0.9625790353529863,
+           -0.9880502214194186,
+           -1.0071565795176074,
+           -1.0190606540718365,
+           -1.0231239124922666,
+           -1.0189180662252113,
+           -1.0062308555727197,
+           -0.9850662140742992,
+           -0.9556388707259014,
+           -0.9183635886534297,
+           -0.873839373550849,
+           -0.8228291108753167,
+           -0.7662352043341423,
+           -0.7050718867813021,
+           -0.6404349558244138,
+           -0.5734697482269153,
+           -0.5053382080641601,
+           -0.437185922573049,
+           -0.37010999629025115,
+           -0.3051286085327034,
+           -0.24315305222236056,
+           -0.18496298472153205,
+           -0.13118553546043904,
+           -0.0822788129052435,
+           -0.03852023744265374,
+           -3.3463697705270556e-16
+          ],
+          [
+           0,
+           0.03131719043329137,
+           0.058042550565802424,
+           0.08071144980067183,
+           0.10000868852183063,
+           0.11674760259132393,
+           0.13184546069581263,
+           0.1462958072887311,
+           0.16113848496715658,
+           0.17742813247826797,
+           0.1962019965686942,
+           0.21844791648172138,
+           0.24507333852166224,
+           0.2768761947440166,
+           0.3145184350499024,
+           0.35850293685881296,
+           0.4091544327129204,
+           0.46660499570964264,
+           0.5307845080688659,
+           0.6014164122779938,
+           0.6780189102704849,
+           0.7599116373397453,
+           0.8462276974537392,
+           0.9359308088387618,
+           1.0278371766165035,
+           1.1206415862437435,
+           1.2129471006362396,
+           1.3032976479772207,
+           1.3902127087678486,
+           1.4722232516932863,
+           1.5479080298938863,
+           1.6159293332666327,
+           1.675067298951071,
+           1.7242519110915817,
+           1.7625918716709974,
+           1.78939959549416,
+           1.8042116725645876,
+           1.8068042479713828,
+           1.7972028903956803,
+           1.7756866525095576,
+           1.7427861666454907,
+           1.6992757637276767,
+           1.6461597490255837,
+           1.5846531112318083,
+           1.5161570781549623,
+           1.4422300595733162,
+           1.3645546323641378,
+           1.284901322062008,
+           1.2050900160390858,
+           1.1269499045125873,
+           1.0522788850302425,
+           0.9828033829515972,
+           0.9201395342738907,
+           0.8657566480526866,
+           0.8209438143098189,
+           0.7867804509215672,
+           0.7641114912728535,
+           0.7535278056582223,
+           0.7553523261379295,
+           0.7696322098044627,
+           0.796137232451187,
+           0.834364456933167,
+           0.8835490716604847,
+           0.9426811482855008,
+           1.010527927296555,
+           1.0856611093230257,
+           1.1664885116705352,
+           1.2512893468111803,
+           1.338252294741826,
+           1.4255154763437439,
+           1.5112073916857454,
+           1.5934878666395147,
+           1.6705880536924962,
+           1.740848558358328,
+           1.8027548104411006,
+           1.8549688684047594,
+           1.896356933513295,
+           1.9260119560467461,
+           1.9432708361498805,
+           1.9477258537657882,
+           1.9392301023968932,
+           1.91789684667011,
+           1.8840928702956061,
+           1.8384260254062161,
+           1.7817273329148773,
+           1.7150281130467278,
+           1.63953274243837,
+           1.5565877363065364,
+           1.4676479387079886,
+           1.374240668817727,
+           1.2779287149079417,
+           1.180273089306438,
+           1.0827964565916488,
+           0.9869481237440534,
+           0.894071435580231,
+           0.805374352746501,
+           0.7219039045531855,
+           0.6445251071650241,
+           0.573904821715719,
+           0.5105008997201455,
+           0.45455682792466673,
+           0.4061019448653877,
+           0.3649571604059448,
+           0.3307459709304021,
+           0.3029104301360567,
+           0.28073161181470646,
+           0.2633539897025896,
+           0.24981306317992458,
+           0.23906547869126338,
+           0.23002083717823094,
+           0.22157433901966508,
+           0.21263940089000544,
+           0.20217938395820392,
+           0.18923759978426172,
+           0.17296480840621287,
+           0.1526434911922831,
+           0.1277082673065077,
+           0.09776192489058542,
+           0.06258665368951213,
+           0.02215019189813573,
+           -0.023393266725840814,
+           -0.07370742233583918,
+           -0.12828335445874547,
+           -0.18645388853323666,
+           -0.2474124608463046,
+           -0.3102359812180649,
+           -0.3739110876045443,
+           -0.4373630970765344,
+           -0.49948688567791305,
+           -0.5591788773108312,
+           -0.6153692903873071,
+           -0.6670537813494305,
+           -0.7133236365687174,
+           -0.7533936983094353,
+           -0.7866272655528564,
+           -0.8125572851739027,
+           -0.8309032413882425,
+           -0.8415832592483592,
+           -0.8447210585714199,
+           -0.8406475250160496,
+           -0.829896801825637,
+           -0.8131969455911991,
+           -0.7914553287430837,
+           -0.7657391068494304,
+           -0.7372511967644962,
+           -0.7073023289944103,
+           -0.6772798413537736,
+           -0.6486139684299355,
+           -0.622742450309178,
+           -0.6010743326641943,
+           -0.5849538573707969,
+           -0.5756253475643038,
+           -0.5741999732674533,
+           -0.5816252437870347,
+           -0.598658011902456,
+           -0.6258416939028155,
+           -0.6634883107112464,
+           -0.7116658410550621,
+           -0.7701912506750244,
+           -0.8386294250148129,
+           -0.9162980900345427,
+           -1.0022786602535438,
+           -1.0954328084263518,
+           -1.1944244109578337,
+           -1.2977463907317381,
+           -1.403751857738922,
+           -1.5106888407548955,
+           -1.6167378129953094,
+           -1.720051143428895,
+           -1.8187935550386687,
+           -1.911182643074413,
+           -1.995528500969086,
+           -2.0702715192749426,
+           -2.1340174633226314,
+           -2.1855689973709014,
+           -2.223952905316489,
+           -2.2484423585942195,
+           -2.2585736982895916,
+           -2.2541573278923415,
+           -2.2352824524018313,
+           -2.2023155452718894,
+           -2.1558925734117733,
+           -2.096905158525562,
+           -2.0264809968746293,
+           -1.9459589955906518,
+           -1.8568597086440348,
+           -1.760851766450002,
+           -1.6597150871831974,
+           -1.5553017328945513,
+           -1.4494953276726044,
+           -1.3441699870688155,
+           -1.2411497170592634,
+           -1.1421692267531136,
+           -1.0488370622567977,
+           -0.962601910494292,
+           -0.8847228428340242,
+           -0.8162441710450666,
+           -0.7579754748096722,
+           -0.7104772335559478,
+           -0.6740523588614976,
+           -0.6487437804767745,
+           -0.6343380926444239,
+           -0.6303751214389265,
+           -0.6361631318932642,
+           -0.6507992591846865,
+           -0.6731946243982752,
+           -0.7021034853815225,
+           -0.7361556796072818,
+           -0.773891541027025,
+           -0.8137984184068242,
+           -0.8543478898710277,
+           -0.8940327580693543,
+           -0.9314029227110242,
+           -0.9650992617921359,
+           -0.9938847087473024,
+           -1.0166717885235386,
+           -1.0325459692547603,
+           -1.040784295419075,
+           -1.0408688903181873,
+           -1.0324950473474561,
+           -1.0155737675113619,
+           -0.9902287415159744,
+           -0.9567879150066543,
+           -0.9157699116081583,
+           -0.8678657169689635,
+           -0.8139161448106492,
+           -0.7548857101100611,
+           -0.6918336224181503,
+           -0.6258826817773537,
+           -0.5581869090373586,
+           -0.48989877039206675,
+           -0.42213686201038464,
+           -0.35595490460437373,
+           -0.2923128601190195,
+           -0.23205092443021036,
+           -0.17586707251101247,
+           -0.12429873795958164,
+           -0.07770909949365003,
+           -0.036278325793204794,
+           -3.144430334616951e-16
+          ],
+          [
+           0,
+           0.029357104468849406,
+           0.054422033809318565,
+           0.0758009984268642,
+           0.09423711191783193,
+           0.11058764322673498,
+           0.12579796018196346,
+           0.1408728573424789,
+           0.15684603078394335,
+           0.1747485126573812,
+           0.195576907773947,
+           0.22026228233548625,
+           0.24964054101439903,
+           0.28442509320819864,
+           0.32518255331507284,
+           0.372312144677102,
+           0.4260293842831992,
+           0.4863545177189715,
+           0.5531060538817383,
+           0.6258996196470361,
+           0.704152219219115,
+           0.7870918447225772,
+           0.8737722471701201,
+           0.9630925437347083,
+           1.05382121162689,
+           1.1446239040098114,
+           1.234094422193659,
+           1.3207880934195715,
+           1.4032567370519118,
+           1.4800843556726349,
+           1.5499226626385865,
+           1.6115255548175504,
+           1.6637816586084913,
+           1.7057441185694993,
+           1.7366568600728363,
+           1.7559766389089664,
+           1.7633902897133071,
+           1.758826699096321,
+           1.742463155646063,
+           1.7147258644585357,
+           1.6762845552166754,
+           1.6280412566124098,
+           1.5711134525497408,
+           1.5068119735629086,
+           1.4366141068223022,
+           1.3621325267642763,
+           1.2850807528235282,
+           1.2072359283674197,
+           1.1303997835395716,
+           1.0563586925884174,
+           0.9868437621659604,
+           0.9234918903512331,
+           0.8678087166563129,
+           0.8211343414429941,
+           0.7846126299974407,
+           0.7591648334852245,
+           0.7454681581353708,
+           0.7439397977141805,
+           0.7547268154622648,
+           0.7777021233067892,
+           0.8124666616846995,
+           0.8583577362324047,
+           0.9144633214888891,
+           0.9796420001753813,
+           1.052548072998295,
+           1.131661251520895,
+           1.215320238435936,
+           1.3017594081716954,
+           1.389147728389544,
+           1.4756290113292905,
+           1.5593625543645013,
+           1.6385632222416922,
+           1.7115400394341316,
+           1.7767323994240363,
+           1.8327430575674963,
+           1.8783671540011357,
+           1.9126166108375995,
+           1.9347393612484456,
+           1.9442329941507195,
+           1.9408525339892786,
+           1.9246122172022295,
+           1.8957812718815727,
+           1.8548738513430445,
+           1.802633412269194,
+           1.7400119603706108,
+           1.6681447078998255,
+           1.588320794903386,
+           1.5019508172098672,
+           1.4105319766358588,
+           1.3156117210236487,
+           1.2187507722851605,
+           1.1214864489344687,
+           1.0252971755155869,
+           0.9315690352974373,
+           0.8415651655808493,
+           0.7563987184290036,
+           0.6770100155582223,
+           0.6041484169080931,
+           0.5383593008159752,
+           0.47997642282054664,
+           0.42911978320633803,
+           0.38569899391251017,
+           0.34942199685808445,
+           0.319808851545038,
+           0.2962101833367169,
+           0.27782976821840316,
+           0.2637506279981153,
+           0.2529639243181158,
+           0.2443998726288808,
+           0.23695985007115422,
+           0.2295488451577575,
+           0.22110739285216666,
+           0.2106421561658516,
+           0.1972543542532979,
+           0.18016529614976717,
+           0.15873835724004184,
+           0.13249683026433662,
+           0.10113719173765681,
+           0.06453744529976344,
+           0.02276033265382959,
+           -0.023948662889954186,
+           -0.07516845908658028,
+           -0.13031446795404816,
+           -0.18865531436181354,
+           -0.24933373378238946,
+           -0.311391093314184,
+           -0.3737948846351981,
+           -0.435468458745353,
+           -0.495322212211903,
+           -0.5522853946903052,
+           -0.6053376887871212,
+           -0.6535397163624413,
+           -0.696061650090797,
+           -0.7322091549190693,
+           -0.7614459498532318,
+           -0.7834123646449913,
+           -0.7979393663426955,
+           -0.8050576448152045,
+           -0.805001471400009,
+           -0.7982071776371064,
+           -0.7853062382967239,
+           -0.7671130811436618,
+           -0.7446078816243482,
+           -0.7189147304911421,
+           -0.6912756830095622,
+           -0.6630213067693349,
+           -0.6355384384808878,
+           -0.6102359360961219,
+           -0.5885092691861702,
+           -0.5717048262590045,
+           -0.5610848316420962,
+           -0.5577937562671893,
+           -0.5628270763056771,
+           -0.577003181794527,
+           -0.6009391653787428,
+           -0.6350311307964424,
+           -0.6794395539293054,
+           -0.7340801087261976,
+           -0.7986202390189341,
+           -0.8724816183975044,
+           -0.9548484973030085,
+           -1.0446817928455134,
+           -1.1407386360997083,
+           -1.2415969572485568,
+           -1.3456845642574258,
+           -1.4513120588605424,
+           -1.5567088373099096,
+           -1.6600613449767767,
+           -1.7595526954735636,
+           -1.8534027279561918,
+           -1.939907561627458,
+           -2.017477714595715,
+           -2.0846738849956608,
+           -2.1402395449404468,
+           -2.183129571197485,
+           -2.212534228708715,
+           -2.2278979319870253,
+           -2.2289323323818317,
+           -2.215623413239044,
+           -2.188232416831492,
+           -2.1472905731597978,
+           -2.0935877477664113,
+           -2.02815526999155,
+           -1.9522433411207758,
+           -1.8672935502740104,
+           -1.7749071415451736,
+           -1.6768097760126364,
+           -1.5748136143769704,
+           -1.4707776081584831,
+           -1.3665669281070134,
+           -1.2640124767709942,
+           -1.1648714276215313,
+           -1.0707897058708051,
+           -0.9832672768584471,
+           -0.9036270378394049,
+           -0.83298801993467,
+           -0.7722435011096459,
+           -0.7220445109400355,
+           -0.682789076574317,
+           -0.6546174199380843,
+           -0.6374131722740398,
+           -0.6308105271039999,
+           -0.6342071101877645,
+           -0.6467822085219567,
+           -0.6675198731998625,
+           -0.695236296135311,
+           -0.7286107610217935,
+           -0.7662193868546331,
+           -0.806570819851755,
+           -0.8481429881435738,
+           -0.8894200141177571,
+           -0.9289283822074831,
+           -0.9652714850549866,
+           -0.9971617176674595,
+           -1.0234493561800089,
+           -1.043147543418652,
+           -1.0554528054273422,
+           -1.0597606388959744,
+           -1.0556758360734368,
+           -1.0430173480793854,
+           -1.0218176261646645,
+           -0.9923165199373306,
+           -0.9549499483801248,
+           -0.9103336902206252,
+           -0.8592427616206403,
+           -0.8025869582097614,
+           -0.7413832324969301,
+           -0.676725654332933,
+           -0.6097537594841408,
+           -0.5416201281178099,
+           -0.47345805021566895,
+           -0.406350128290711,
+           -0.3412986394965149,
+           -0.2791984300466248,
+           -0.22081304608500207,
+           -0.16675471854037363,
+           -0.11746871727652969,
+           -0.07322247462777849,
+           -0.034099753119032745,
+           -2.95030922528004e-16
+          ],
+          [
+           0,
+           0.027511753887494262,
+           0.05106158821570343,
+           0.07131934510739277,
+           0.08907832814857267,
+           0.1052309456719284,
+           0.12074146381798634,
+           0.13661659545824378,
+           0.15387470901486913,
+           0.17351447910535964,
+           0.1964838177967366,
+           0.22364992062082156,
+           0.2557712354690887,
+           0.2934721156807031,
+           0.3372208522123738,
+           0.38731169538035826,
+           0.44385137639442496,
+           0.5067505252637428,
+           0.5757202574882976,
+           0.6502740703680502,
+           0.7297350540685485,
+           0.8132482861878589,
+           0.8997981449109433,
+           0.9882301482873986,
+           1.0772768089535456,
+           1.1655868877399926,
+           1.2517573387578809,
+           1.3343671650682571,
+           1.4120123498074193,
+           1.4833409940882711,
+           1.5470877810323442,
+           1.6021068952817195,
+           1.64740255912078,
+           1.6821563991879482,
+           1.7057509304349252,
+           1.7177885347572488,
+           1.7181054183838458,
+           1.7067801520835848,
+           1.6841365285967738,
+           1.650740609238337,
+           1.6073919729713733,
+           1.5551093229374016,
+           1.4951107439598612,
+           1.4287890364877032,
+           1.3576826745498363,
+           1.2834430445179092,
+           1.207798715106512,
+           1.1325175647368488,
+           1.059367648250876,
+           0.9900777195713809,
+           0.9262983393632422,
+           0.8695644867099847,
+           0.8212605614765344,
+           0.7825886101324712,
+           0.7545405336368874,
+           0.7378749433137044,
+           0.7330992217068815,
+           0.7404572228319474,
+           0.7599229130032529,
+           0.7912001127484587,
+           0.8337283556400501,
+           0.8866947346952526,
+           0.949051464851058,
+           1.0195387543674124,
+           1.09671245214769,
+           1.1789758249506184,
+           1.264614721046316,
+           1.351835297403146,
+           1.4388034279039537,
+           1.5236848718138654,
+           1.6046852656700372,
+           1.6800890083028976,
+           1.7482961376429125,
+           1.8078563485814176,
+           1.8574993721735642,
+           1.896161026132082,
+           1.923004352643493,
+           1.9374353794252028,
+           1.9391131706783864,
+           1.927953972962708,
+           1.9041294036259073,
+           1.8680587727680382,
+           1.8203957702975067,
+           1.762009884009836,
+           1.6939630395148366,
+           1.6174820652180224,
+           1.533927682706228,
+           1.4447608024556446,
+           1.3515069648707942,
+           1.2557198058589567,
+           1.1589444435483442,
+           1.0626816780131363,
+           0.9683538691660887,
+           0.8772733100547019,
+           0.7906138449088889,
+           0.7093863951876852,
+           0.6344189547588107,
+           0.5663414998091112,
+           0.5055761330454195,
+           0.4523326483775094,
+           0.4066095649269388,
+           0.3682005413180572,
+           0.3367059462270856,
+           0.3115492324588115,
+           0.29199764259101524,
+           0.277186667434416,
+           0.2661475868436308,
+           0.2578373480434037,
+           0.25116998142678953,
+           0.24504871907752077,
+           0.23839796789073467,
+           0.2301942974018027,
+           0.21949563202646782,
+           0.20546788757550183,
+           0.18740836132639607,
+           0.164765271823806,
+           0.1371529467126559,
+           0.10436227167491655,
+           0.06636613801938104,
+           0.02331975749722336,
+           -0.024444152844127827,
+           -0.0764251789083494,
+           -0.1319697435844504,
+           -0.19028997570414538,
+           -0.25048640955020546,
+           -0.31157390995932727,
+           -0.37251013296078006,
+           -0.4322257644403004,
+           -0.48965573124184136,
+           -0.5437705516548824,
+           -0.5936069861008297,
+           -0.63829716421021,
+           -0.6770954010132464,
+           -0.7094019717572649,
+           -0.7347831905114692,
+           -0.7529872303433996,
+           -0.7639552301424343,
+           -0.767827352442916,
+           -0.7649435848764163,
+           -0.7558392119419685,
+           -0.741235020257106,
+           -0.722022435906564,
+           -0.6992439235248565,
+           -0.6740691000228035,
+           -0.6477671282735321,
+           -0.6216760547532239,
+           -0.5971698375659252,
+           -0.5756238753508398,
+           -0.5583798916093264,
+           -0.5467110518289557,
+           -0.5417881917802324,
+           -0.5446480144185144,
+           -0.5561640703856613,
+           -0.5770212741555055,
+           -0.6076946258991445,
+           -0.648432710131165,
+           -0.6992464285348813,
+           -0.759903298820927,
+           -0.8299275171173194,
+           -0.9086058415140891,
+           -0.9949992124285296,
+           -1.087959884914545,
+           -1.1861537123798545,
+           -1.2880870937529119,
+           -1.3921379801156886,
+           -1.496590235072148,
+           -1.59967055819263,
+           -1.6995871148873014,
+           -1.7945689706827226,
+           -1.8829054042635998,
+           -1.9629841724235266,
+           -2.0333278213207535,
+           -2.09262718168268,
+           -2.1397712498302996,
+           -2.1738727400687052,
+           -2.1942886951018754,
+           -2.2006356572386596,
+           -2.1927990314519707,
+           -2.1709364087239127,
+           -2.1354747612204332,
+           -2.0871015662123393,
+           -2.02675005976049,
+           -1.955578960506983,
+           -1.874947135072949,
+           -1.786383796367904,
+           -1.6915549316553202,
+           -1.5922267459324224,
+           -1.4902269759206777,
+           -1.3874049790436935,
+           -1.2855915290142863,
+           -1.1865592544210317,
+           -1.0919846389051866,
+           -1.0034124616148148,
+           -0.9222234956162266,
+           -0.8496062013533213,
+           -0.7865330540705233,
+           -0.7337420307809198,
+           -0.691723656662835,
+           -0.6607138757994439,
+           -0.6406928702548579,
+           -0.6313898080638606,
+           -0.6322933583150621,
+           -0.6426676736109695,
+           -0.6615734101585359,
+           -0.6878932367453477,
+           -0.720361178777294,
+           -0.7575950549315629,
+           -0.7981311939416954,
+           -0.8404605692435871,
+           -0.883065460833086,
+           -0.9244557473468822,
+           -0.9632039471606273,
+           -0.9979781647377828,
+           -1.027572156558377,
+           -1.0509318081996204,
+           -1.0671774085487529,
+           -1.0756212162995713,
+           -1.0757799350544077,
+           -1.0673818434663733,
+           -1.0503684626413072,
+           -1.0248907810695622,
+           -0.9913001942197132,
+           -0.9501344481827015,
+           -0.9020990011100722,
+           -0.848044329552996,
+           -0.7889398063693582,
+           -0.7258448601646197,
+           -0.6598781912204132,
+           -0.5921858639568712,
+           -0.5239091200859479,
+           -0.45615275918639714,
+           -0.38995491445097424,
+           -0.32625901134816093,
+           -0.2658886369567434,
+           -0.20952596932520265,
+           -0.15769432139381367,
+           -0.1107452452203799,
+           -0.06885052224549795,
+           -0.031999237174682324,
+           -2.7652536647843447e-16
+          ],
+          [
+           0,
+           0.025791541259194205,
+           0.047978247754828895,
+           0.06728594691622014,
+           0.08454971832054753,
+           0.10068818135620528,
+           0.11667532656556624,
+           0.13351064271111907,
+           0.15218833758301153,
+           0.1736664761084517,
+           0.198836863766356,
+           0.2284964865173637,
+           0.2633212808278924,
+           0.3038429498203914,
+           0.35042946554578913,
+           0.40326980474066276,
+           0.46236335851312277,
+           0.5275143378724698,
+           0.5983313698485917,
+           0.6742323463299317,
+           0.7544544530176749,
+           0.8380691724414269,
+           0.9240019261749997,
+           1.0110559004866975,
+           1.0979394897217651,
+           1.183296695542027,
+           1.2657397401972197,
+           1.3438830903315118,
+           1.4163780460424988,
+           1.4819470291206847,
+           1.5394167051958536,
+           1.5877490969566166,
+           1.6260698892054388,
+           1.6536931902506435,
+           1.6701420965024643,
+           1.6751645061493852,
+           1.6687437410424844,
+           1.6511036606494367,
+           1.6227080851051725,
+           1.5842544827160323,
+           1.5366620173668268,
+           1.481054189682548,
+           1.4187364390900268,
+           1.3511691988105299,
+           1.2799370091934799,
+           1.2067143938538658,
+           1.1332292853287627,
+           1.0612248503586543,
+           0.9924206078247496,
+           0.9284737537330108,
+           0.8709416068568908,
+           0.8212460657046012,
+           0.7806409228791407,
+           0.7501828176982075,
+           0.730706523691978,
+           0.7228051663239982,
+           0.7268158504282438,
+           0.7428110492277303,
+           0.7705959704917059,
+           0.8097119737092442,
+           0.8594459685503467,
+           0.9188455828435586,
+           0.9867397512770515,
+           1.0617642473610744,
+           1.1423915640030267,
+           1.2269644451903,
+           1.3137322852475897,
+           1.4008895450196956,
+           1.4866152877485133,
+           1.5691129124827083,
+           1.6466491601665654,
+           1.7175914871440592,
+           1.7804429421809773,
+           1.833873745216135,
+           1.8767488473585185,
+           1.9081508501381492,
+           1.9273977752635718,
+           1.934055301347566,
+           1.9279432181559955,
+           1.9091359886186294,
+           1.8779574506906185,
+           1.8349698316955563,
+           1.7809573835812027,
+           1.7169050752646746,
+           1.6439728948276586,
+           1.5634664169169274,
+           1.4768043768346055,
+           1.3854840604004757,
+           1.2910453661309818,
+           1.1950344225026721,
+           1.0989676474749392,
+           1.0042971200019142,
+           0.9123780944706704,
+           0.8244394298944376,
+           0.7415576277977062,
+           0.6646350780504091,
+           0.5943830028469242,
+           0.5313094683415976,
+           0.47571270418634537,
+           0.4276798366153766,
+           0.387091004160217,
+           0.35362868996921865,
+           0.3267919744206378,
+           0.3059152895001165,
+           0.29019114529727025,
+           0.2786962017136355,
+           0.27041997746528007,
+           0.2642954256966317,
+           0.259230562525994,
+           0.25414031264820347,
+           0.24797773523344588,
+           0.2397638137555439,
+           0.2286150344963728,
+           0.21376803922423493,
+           0.19460071636013326,
+           0.17064918980160543,
+           0.14162027304307528,
+           0.10739907554809965,
+           0.06805157545571505,
+           0.023822104409075118,
+           -0.024874176764776344,
+           -0.0774636019936124,
+           -0.13323078864330606,
+           -0.19133943936651643,
+           -0.25085660043301405,
+           -0.31077972902399054,
+           -0.3700658477201122,
+           -0.4276620086353482,
+           -0.48253625377430265,
+           -0.5337082431476219,
+           -0.5802787283717831,
+           -0.6214570767749705,
+           -0.6565860987673506,
+           -0.6851634982339186,
+           -0.7068593503070619,
+           -0.7215291109653601,
+           -0.7292217759835244,
+           -0.7301829299946461,
+           -0.7248525567289794,
+           -0.7138576155904102,
+           -0.6979995242482503,
+           -0.6782368184677557,
+           -0.6556633856554512,
+           -0.6314827843842937,
+           -0.6069792655486606,
+           -0.5834861991446396,
+           -0.5623526817122363,
+           -0.5449091513757983,
+           -0.532432868814001,
+           -0.5261141325270854,
+           -0.5270240851232911,
+           -0.5360849342348158,
+           -0.5540433578476534,
+           -0.5814477905580181,
+           -0.6186301963059095,
+           -0.6656928266824358,
+           -0.7225003445504856,
+           -0.7886775633724729,
+           -0.8636129164730729,
+           -0.9464676308237723,
+           -1.0361904402577244,
+           -1.1315375367541662,
+           -1.2310973289407463,
+           -1.3333194574588645,
+           -1.4365474102892661,
+           -1.539053990198381,
+           -1.6390788134149092,
+           -1.7348669653188482,
+           -1.8247079066784542,
+           -1.9069737136428155,
+           -1.9801557465915056,
+           -2.042898876813441,
+           -2.0940324550504443,
+           -2.1325972808916887,
+           -2.1578679250471993,
+           -2.169369865421365,
+           -2.1668910200182716,
+           -2.150487392081545,
+           -2.12048268228982,
+           -2.077461865908076,
+           -2.0222588760563665,
+           -1.9559386742164693,
+           -1.8797741223489268,
+           -1.7952181942968564,
+           -1.7038721745105387,
+           -1.6074505868574007,
+           -1.507743673087505,
+           -1.4065782975462786,
+           -1.3057781905901642,
+           -1.20712445701212,
+           -1.1123172673069348,
+           -1.0229396190320057,
+           -0.9404240036203566,
+           -0.8660227420731198,
+           -0.8007826627818975,
+           -0.7455246885360828,
+           -0.7008287801755332,
+           -0.6670245542982902,
+           -0.6441877551232718,
+           -0.6321426194083595,
+           -0.6304700316951822,
+           -0.638521228557586,
+           -0.6554366783553623,
+           -0.6801696404580002,
+           -0.7115137979815487,
+           -0.7481342634351171,
+           -0.7886011795800845,
+           -0.8314250801056015,
+           -0.875093137776194,
+           -0.9181054123542507,
+           -0.9590102171490762,
+           -0.9964377512599706,
+           -1.0291311936930014,
+           -1.055974524253114,
+           -1.076016422676036,
+           -1.0884896996596711,
+           -1.0928258286920591,
+           -1.0886642729434113,
+           -1.0758564338391585,
+           -1.0544641839387252,
+           -1.0247530830066478,
+           -0.9871805092753312,
+           -0.9423790645450546,
+           -0.8911357287976595,
+           -0.8343673445134525,
+           -0.7730931002924567,
+           -0.7084047554900603,
+           -0.6414354006195255,
+           -0.5733275809661329,
+           -0.5052016224288627,
+           -0.43812498881474415,
+           -0.3730834689542021,
+           -0.31095494090701736,
+           -0.25248639051908545,
+           -0.1982747744748168,
+           -0.14875221600167737,
+           -0.10417590712613226,
+           -0.06462296776515798,
+           -0.029990382108295813,
+           -2.5903917580592635e-16
+          ],
+          [
+           0,
+           0.024205364691566793,
+           0.04518584463214115,
+           0.0637152532698713,
+           0.08066183042247901,
+           0.09696143466361766,
+           0.11358872435586936,
+           0.13152709805890148,
+           0.15173819892631218,
+           0.17513180097256764,
+           0.20253688738572398,
+           0.23467470255403722,
+           0.2721345108608503,
+           0.31535272778499435,
+           0.36459600410315657,
+           0.41994874414142824,
+           0.48130542656342656,
+           0.5483679739304421,
+           0.6206482882935481,
+           0.6974759376209037,
+           0.7780108452605741,
+           0.8612607052345469,
+           0.9461027232234623,
+           1.0313091697481418,
+           1.115576131163405,
+           1.19755475822584,
+           1.2758842433830813,
+           1.3492257083342065,
+           1.4162961541343044,
+           1.4759016179616828,
+           1.526968693908868,
+           1.5685736095409906,
+           1.5999681047024499,
+           1.6206014328515277,
+           1.6301378962922397,
+           1.6284694328487028,
+           1.6157228902053795,
+           1.5922617524162241,
+           1.5586822178218782,
+           1.5158036654943472,
+           1.4646536849557292,
+           1.4064479778930652,
+           1.342565567599711,
+           1.2745198687648873,
+           1.2039262741002865,
+           1.1324670025450057,
+           1.0618540242166072,
+           0.9937909281012316,
+           0.9299346284033386,
+           0.8718578137220628,
+           0.8210130295346446,
+           0.778699249134966,
+           0.746031732016595,
+           0.7239158930367706,
+           0.7130258123629256,
+           0.7137879074348671,
+           0.7263701666027738,
+           0.7506772126693588,
+           0.7863513264634978,
+           0.8327794191577064,
+           0.8891058007516857,
+           0.9542504544157309,
+           1.0269323955726366,
+           1.1056975738773918,
+           1.1889506685667834,
+           1.2749900356132156,
+           1.3620449909623955,
+           1.4483145596592024,
+           1.532006787182831,
+           1.6113776976212406,
+           1.6847689936799812,
+           1.750643625667643,
+           1.80761840972022,
+           1.8544929482988384,
+           1.8902741966177392,
+           1.9141961248951054,
+           1.9257340455512446,
+           1.9246133037738884,
+           1.9108121660540462,
+           1.8845588810275886,
+           1.8463230268163013,
+           1.796801395627915,
+           1.7368987963154265,
+           1.6677042757481428,
+           1.5904633672937223,
+           1.50654706685357,
+           1.4174183115172458,
+           1.3245967912253114,
+           1.2296229585543783,
+           1.1340221150744219,
+           1.0392694444180344,
+           0.9467568325213574,
+           0.8577622652518724,
+           0.7734225241415763,
+           0.6947098139811949,
+           0.6224128538177597,
+           0.5571228480219045,
+           0.49922462945026597,
+           0.44889313545496984,
+           0.4060952428774716,
+           0.3705968535746412,
+           0.34197499081940924,
+           0.31963454236368827,
+           0.30282917114149194,
+           0.290685812369706,
+           0.28223208869688704,
+           0.2764259051980555,
+           0.27218643512134316,
+           0.2684256765884248,
+           0.2640797506548907,
+           0.25813912244393594,
+           0.24967695914213534,
+           0.23787489063429929,
+           0.22204550910122117,
+           0.20165103119110414,
+           0.17631764816530268,
+           0.14584520311261243,
+           0.11021195702731727,
+           0.06957433413433387,
+           0.024261668053791517,
+           -0.025233899102955894,
+           -0.07827208613410493,
+           -0.1340833128215963,
+           -0.19179120385702492,
+           -0.2504381538190878,
+           -0.3090132698821822,
+           -0.36648194592288746,
+           -0.4218162777940962,
+           -0.4740255058828669,
+           -0.5221856682754286,
+           -0.5654676660140474,
+           -0.6031629806104114,
+           -0.634706342226774,
+           -0.659694723303557,
+           -0.677902124996925,
+           -0.6892897302784367,
+           -0.6940111152746052,
+           -0.69241233643451,
+           -0.6850268422428744,
+           -0.6725652911456135,
+           -0.6559004887742369,
+           -0.6360477841271067,
+           -0.6141413828870418,
+           -0.5914071435196321,
+           -0.5691325154691238,
+           -0.5486343562529351,
+           -0.5312254235557864,
+           -0.518180377994336,
+           -0.5107021510067177,
+           -0.5098895297788749,
+           -0.516706787242029,
+           -0.5319561404856863,
+           -0.5562537564706032,
+           -0.5900099412328191,
+           -0.6334140498368598,
+           -0.6864245415652094,
+           -0.7487644809732557,
+           -0.819922653525983,
+           -0.8991603278037194,
+           -0.9855235580843266,
+           -1.0778607848869086,
+           -1.1748453601647257,
+           -1.2750025015053301,
+           -1.3767400689723293,
+           -1.4783824618621366,
+           -1.5782068530599542,
+           -1.6744809178612474,
+           -1.7655011736183062,
+           -1.8496310274203092,
+           -1.925337631737966,
+           -1.9912266725434962,
+           -2.0460742602979485,
+           -2.088855160301616,
+           -2.1187666836529413,
+           -2.1352476614197022,
+           -2.1379920401477848,
+           -2.1269567637210143,
+           -2.1023637417636176,
+           -2.0646958449620634,
+           -2.014687009467964,
+           -1.9533066724799235,
+           -1.881738895784925,
+           -1.8013566601919326,
+           -1.7136919283430836,
+           -1.6204021735555223,
+           -1.5232341556968239,
+           -1.4239857896079056,
+           -1.3244669956998636,
+           -1.2264604450057794,
+           -1.1316831116315045,
+           -1.0417495242260757,
+           -0.9581375653255977,
+           -0.8821576042828737,
+           -0.8149256675448787,
+           -0.7573412513068968,
+           -0.7100702684904046,
+           -0.6735334973454348,
+           -0.647900765830073,
+           -0.6330909675381667,
+           -0.6287778647221656,
+           -0.6344014953225593,
+           -0.6491848672547429,
+           -0.672155497776508,
+           -0.7021712416141405,
+           -0.737949751428415,
+           -0.7781008305682756,
+           -0.8211608728935659,
+           -0.865628539293628,
+           -0.9100007964329797,
+           -0.9528084407440186,
+           -0.9926502497503802,
+           -1.0282249429002164,
+           -1.0583601941544154,
+           -1.082038017056158,
+           -1.0984159378985638,
+           -1.1068434814966142,
+           -1.1068736142071143,
+           -1.098268917201482,
+           -1.0810023963586197,
+           -1.0552529701698712,
+           -1.0213958103619591,
+           -0.9799878382236488,
+           -0.9317487996773575,
+           -0.8775384509894356,
+           -0.8183304819698943,
+           -0.7551838822339829,
+           -0.6892125166547002,
+           -0.6215537170559565,
+           -0.5533367175035908,
+           -0.4856517597872102,
+           -0.41952067391995645,
+           -0.3558696963129198,
+           -0.2955052268143845,
+           -0.2390931466326744,
+           -0.18714222431934585,
+           -0.13999202890289011,
+           -0.09780565068803666,
+           -0.06056740419028196,
+           -0.028085557362607958,
+           -2.426722884850381e-16
+          ],
+          [
+           0,
+           0.022760551419522858,
+           0.042694920401441745,
+           0.06061664076525602,
+           0.0774183847252703,
+           0.09404432470479786,
+           0.11146093537062365,
+           0.1306270180163479,
+           0.1524637512232533,
+           0.17782557291169934,
+           0.20747267941501976,
+           0.24204588753233908,
+           0.28204454662648715,
+           0.32780811119287934,
+           0.37950189184780525,
+           0.4371073966836973,
+           0.5004175580714875,
+           0.5690370151896804,
+           0.6423874929636743,
+           0.7197181869697591,
+           0.8001209345026444,
+           0.882549827690982,
+           0.9658448084192608,
+           1.0487586798244164,
+           1.1299868779558666,
+           1.2081992721526433,
+           1.2820732057354436,
+           1.3503269512218659,
+           1.4117527374507837,
+           1.465248510236604,
+           1.5098476134314518,
+           1.5447456229942813,
+           1.5693236317805916,
+           1.5831673657195846,
+           1.5860816108345859,
+           1.5780995427865832,
+           1.5594866735396464,
+           1.5307392603490726,
+           1.4925771573491544,
+           1.4459312262403345,
+           1.3919255565822148,
+           1.331854874674081,
+           1.267157639762689,
+           1.199385434380916,
+           1.1301693492969258,
+           1.0611841404966331,
+           0.9941109938969735,
+           0.9305997716136393,
+           0.8722316305986643,
+           0.8204828998530751,
+           0.7766910762706501,
+           0.742023752073943,
+           0.7174512198708163,
+           0.7037234161866166,
+           0.7013517629599889,
+           0.7105963513762432,
+           0.7314587863371346,
+           0.7636808758876854,
+           0.8067492112930831,
+           0.8599055435519175,
+           0.922162724349403,
+           0.9923258471491264,
+           1.0690181005142145,
+           1.1507107338469926,
+           1.2357564382620603,
+           1.3224253646301891,
+           1.4089429389071344,
+           1.4935285931903253,
+           1.574434510529726,
+           1.6499834828374658,
+           1.7186050042438203,
+           1.7788687663517928,
+           1.8295147859511134,
+           1.8694794782771418,
+           1.8979170878039102,
+           1.9142160014070968,
+           1.918009592746682,
+           1.9091813788550915,
+           1.8878644069337938,
+           1.8544349279043075,
+           1.8095005499400916,
+           1.753883196687503,
+           1.688597317963652,
+           1.6148239124058876,
+           1.5338810191369925,
+           1.4471914166494813,
+           1.3562483298589418,
+           1.2625799891453389,
+           1.1677139072003353,
+           1.0731417401541024,
+           0.9802855788201308,
+           0.8904664745514662,
+           0.8048759432373908,
+           0.7245511119601012,
+           0.6503540777939862,
+           0.582955939575994,
+           0.5228258439471251,
+           0.4702252595685274,
+           0.4252075613463167,
+           0.38762287306089155,
+           0.35712798532019097,
+           0.33320103951629954,
+           0.3151605505980255,
+           0.30218823489988045,
+           0.29335501662342806,
+           0.28764951013038065,
+           0.2840082168483526,
+           0.2813466367243896,
+           0.27859047571232715,
+           0.274706133158639,
+           0.2687296760459827,
+           0.2597935502331238,
+           0.24715034096007757,
+           0.230192974359981,
+           0.2084708464923448,
+           0.18170147406214232,
+           0.14977737877049827,
+           0.11276804215831072,
+           0.07091689667985875,
+           0.02463344830774904,
+           -0.025519247063353182,
+           -0.0788414099985534,
+           -0.13451721101620037,
+           -0.19163873499788234,
+           -0.24923259408686552,
+           -0.3062884768932502,
+           -0.36178887032577167,
+           -0.41473915844365067,
+           -0.4641972911909656,
+           -0.5093022250508416,
+           -0.5493003673262923,
+           -0.5835693051910319,
+           -0.6116381686310955,
+           -0.6332040612225563,
+           -0.6481440922420184,
+           -0.6565226553920224,
+           -0.6585937206388834,
+           -0.6547980332608625,
+           -0.6457552449799343,
+           -0.6322511327058165,
+           -0.6152201876590597,
+           -0.595723978243126,
+           -0.5749258009469066,
+           -0.5540622319587577,
+           -0.5344122755488471,
+           -0.5172648714872874,
+           -0.5038855710948416,
+           -0.49548321872297285,
+           -0.4931774817826523,
+           -0.49796805765857344,
+           -0.5107063502543866,
+           -0.5320703533323563,
+           -0.5625434035539851,
+           -0.6023973749810476,
+           -0.6516807809676122,
+           -0.7102121314414828,
+           -0.7775787664228795,
+           -0.8531412533791911,
+           -0.936043299945504,
+           -1.025226998007185,
+           -1.1194530834919996,
+           -1.2173257717162438,
+           -1.3173216138628596,
+           -1.417821718983739,
+           -1.5171466003406056,
+           -1.613592837075854,
+           -1.7054706938503648,
+           -1.791141813435338,
+           -1.8690560910297858,
+           -1.9377868544967327,
+           -1.9960635114406289,
+           -2.0428008812328424,
+           -2.077124506374471,
+           -2.0983913311387536,
+           -2.1062052440049714,
+           -2.100427101357996,
+           -2.081178980351182,
+           -2.0488425455497454,
+           -2.004051553664942,
+           -1.9476786599589206,
+           -1.8808168253573965,
+           -1.8047557516553436,
+           -1.7209538903160926,
+           -1.6310066753726309,
+           -1.5366117202877745,
+           -1.4395317901481846,
+           -1.341556412521909,
+           -1.2444630214468388,
+           -1.1499785385942312,
+           -1.0597422834516992,
+           -0.9752710707115133,
+           -0.8979272987750696,
+           -0.8288907597411417,
+           -0.7691348102508964,
+           -0.7194074363608918,
+           -0.6802176268201352,
+           -0.6518273406582045,
+           -0.6342492200012486,
+           -0.6272500608296864,
+           -0.6303599163581418,
+           -0.642886573226923,
+           -0.6639350130253527,
+           -0.6924313539269542,
+           -0.7271506622613912,
+           -0.766747934214541,
+           -0.80979147569059,
+           -0.8547978554072079,
+           -0.9002675737692829,
+           -0.9447205787136308,
+           -0.9867307697470342,
+           -1.024958662495626,
+           -1.0581814374059557,
+           -1.0853196664513345,
+           -1.1054600989985666,
+           -1.1178739901597923,
+           -1.1220305694069692,
+           -1.1176053710787401,
+           -1.1044832785510446,
+           -1.082756267013589,
+           -1.052715962666797,
+           -1.0148412654150856,
+           -0.9697814045663328,
+           -0.9183349096161513,
+           -0.8614250781126767,
+           -0.8000726073990151,
+           -0.7353661246346174,
+           -0.6684313982560665,
+           -0.6004000427792617,
+           -0.5323785368992497,
+           -0.4654183620609745,
+           -0.4004880354265395,
+           -0.3384477583377212,
+           -0.2800273303420719,
+           -0.2258078914477592,
+           -0.17620795373630502,
+           -0.13147407038648526,
+           -0.09167636842672085,
+           -0.05670904423297804,
+           -0.026295791157512377,
+           -2.275109573175131e-16
+          ],
+          [
+           0,
+           0.02146280887520123,
+           0.04051267303890868,
+           0.05799440251635442,
+           0.07481635131923464,
+           0.09192221502669667,
+           0.11026172233153315,
+           0.13076100685938946,
+           0.1542934554023296,
+           0.18165181811000283,
+           0.21352233540143417,
+           0.2504615861562493,
+           0.29287669336389544,
+           0.3410094385599281,
+           0.3949247371828461,
+           0.4545038159298876,
+           0.5194423130636927,
+           0.589253396443808,
+           0.6632758650040209,
+           0.7406870707221666,
+           0.820520373082699,
+           0.9016867197779452,
+           0.9829998389308356,
+           1.0632044322094638,
+           1.1410066772923948,
+           1.2151062843128604,
+           1.2842293058164262,
+           1.3471608746017794,
+           1.4027770392741916,
+           1.4500748836084354,
+           1.4882001525563786,
+           1.5164716640967146,
+           1.5344018607721104,
+           1.5417129458958796,
+           1.5383481548252704,
+           1.5244778288206149,
+           1.5005000849714467,
+           1.4670360073785673,
+           1.424919418992036,
+           1.3751814269067184,
+           1.3190300632098582,
+           1.2578254654540593,
+           1.1930511524629657,
+           1.12628204968432,
+           1.0591500012225772,
+           0.9933075709276926,
+           0.9303909808365372,
+           0.8719830606804327,
+           0.8195770864111288,
+           0.7745423686029758,
+           0.738092413530434,
+           0.7112564215826053,
+           0.6948548108403662,
+           0.6894793599477805,
+           0.6954784561151732,
+           0.7129478138145119,
+           0.7417269003833049,
+           0.7814011694807924,
+           0.831310065427421,
+           0.8905606242600567,
+           0.9580463641903955,
+           1.0324710323038477,
+           1.1123766588452573,
+           1.1961752681170426,
+           1.2821835083542608,
+           1.368659394045533,
+           1.4538403047096766,
+           1.5359813553104014,
+           1.6133932459844027,
+           1.684478712739861,
+           1.7477667358926516,
+           1.8019437183716567,
+           1.8458809202701165,
+           1.8786575273149884,
+           1.8995788370219124,
+           1.9081891645907871,
+           1.9042791981716294,
+           1.8878876668633466,
+           1.8592973214241642,
+           1.8190253638299596,
+           1.7678085941909225,
+           1.706583668901082,
+           1.636462979200656,
+           1.5587067617818993,
+           1.474692140190906,
+           1.3858798654783537,
+           1.2937795751726566,
+           1.1999144200043412,
+           1.1057859172179545,
+           1.0128398776032501,
+           0.9224342209184972,
+           0.8358094420354003,
+           0.7540624192671622,
+           0.6781241687640656,
+           0.6087420467995016,
+           0.546466787803245,
+           0.4916446429959592,
+           0.4444147555264333,
+           0.4047117763376975,
+           0.3722735938778098,
+           0.3466539234919126,
+           0.3272393820476301,
+           0.3132705630385067,
+           0.30386652980691736,
+           0.2980520620331293,
+           0.29478692527292555,
+           0.2929963866821617,
+           0.2916021732613395,
+           0.2895530626065026,
+           0.2858543103707818,
+           0.2795951530144092,
+           0.2699736780357887,
+           0.2563184253366901,
+           0.23810617083902127,
+           0.21497544469775984,
+           0.18673544885975152,
+           0.15337015943867977,
+           0.11503752534323096,
+           0.07206380260999116,
+           0.024933190707153934,
+           -0.02572694052575496,
+           -0.07916482975574123,
+           -0.13452660085440854,
+           -0.19088143804645308,
+           -0.24724898416382896,
+           -0.30262822801394546,
+           -0.3560271070456501,
+           -0.40649203151481966,
+           -0.45313653673277965,
+           -0.49516829073325297,
+           -0.5319137253118789,
+           -0.5628396178701983,
+           -0.5875710283515115,
+           -0.6059050878682138,
+           -0.6178202410768803,
+           -0.6234806603130959,
+           -0.6232356730395228,
+           -0.6176141721802075,
+           -0.6073141081862923,
+           -0.5931872889417072,
+           -0.5762198356550433,
+           -0.5575087566044562,
+           -0.5382352031176618,
+           -0.5196350608658515,
+           -0.5029676021563817,
+           -0.4894829795504516,
+           -0.4803893763801311,
+           -0.4768206446472016,
+           -0.47980525491343995,
+           -0.49023735621523534,
+           -0.5088506973482978,
+           -0.5361960951667702,
+           -0.5726230523975323,
+           -0.6182660288948042,
+           -0.6730357586505656,
+           -0.7366158829603875,
+           -0.8084650409121474,
+           -0.8878244249944062,
+           -0.9737306754002826,
+           -1.0650338548474725,
+           -1.1604201197081754,
+           -1.2584385860717797,
+           -1.3575317839636045,
+           -1.456069001945889,
+           -1.5523817500120098,
+           -1.6448005129257197,
+           -1.7316919303730904,
+           -1.8114955254150396,
+           -1.882759109170505,
+           -1.944172017316043,
+           -1.994595382228634,
+           -2.0330887122880794,
+           -2.058932135378242,
+           -2.0716437649273307,
+           -2.070991761460843,
+           -2.0570007878322296,
+           -2.0299526890089323,
+           -1.9903813643017718,
+           -1.9390619379022385,
+           -1.8769944691778648,
+           -1.8053825740700056,
+           -1.7256074499784513,
+           -1.6391979057565542,
+           -1.5477970932207603,
+           -1.4531267145944597,
+           -1.356949539663971,
+           -1.261031105686794,
+           -1.1671014913139142,
+           -1.0768180525391904,
+           -0.9917299840659363,
+           -0.913245524103234,
+           -0.8426025555990423,
+           -0.780843273891232,
+           -0.7287934917580284,
+           -0.6870470403122129,
+           -0.655955600874093,
+           -0.6356241719030539,
+           -0.6259122394779548,
+           -0.6264405830119204,
+           -0.636603513210391,
+           -0.6555862100187546,
+           -0.6823867076046474,
+           -0.7158419642116519,
+           -0.7546573596486321,
+           -0.7974388845328599,
+           -0.8427272250665873,
+           -0.889032906521956,
+           -0.9348716386752188,
+           -0.9787990075923522,
+           -1.0194436803274964,
+           -1.0555383316373403,
+           -1.085947563620029,
+           -1.1096921686640104,
+           -1.1259691812135464,
+           -1.1341672722140832,
+           -1.1338771589594006,
+           -1.1248968294370258,
+           -1.1072315109918287,
+           -1.0810884449324638,
+           -1.0468666583042363,
+           -1.0051420482201128,
+           -0.9566482097963833,
+           -0.9022535430173851,
+           -0.8429352641809287,
+           -0.7797510217326662,
+           -0.7138088724721678,
+           -0.6462364109475162,
+           -0.5781498614771317,
+           -0.5106239382830735,
+           -0.4446632548414767,
+           -0.3811760194167746,
+           -0.3209506910056311,
+           -0.26463619019787177,
+           -0.2127261648130782,
+           -0.16554770301340502,
+           -0.12325476965804608,
+           -0.08582651792757516,
+           -0.05307050085110732,
+           -0.02463067954897187,
+           -2.1362709262396706e-16
+          ],
+          [
+           0,
+           0.020316193585117534,
+           0.03864294017890972,
+           0.05584779154607721,
+           0.07284609821603574,
+           0.09057250810489179,
+           0.10995181065347732,
+           0.13186990988200897,
+           0.15714570785838494,
+           0.18650465810235198,
+           0.22055470694040397,
+           0.25976528081738315,
+           0.3044499005582362,
+           0.3547529114846609,
+           0.41064071343541264,
+           0.4718977597487155,
+           0.5381274720316437,
+           0.6087580911417544,
+           0.6830533574269388,
+           0.7601277881264327,
+           0.8389662000941392,
+           0.9184470146998148,
+           0.9973687817229682,
+           1.0744792728301937,
+           1.1485064250294983,
+           1.2181903621385481,
+           1.2823156891585819,
+           1.339743241405308,
+           1.38944047770545,
+           1.4305097348046103,
+           1.4622136077219894,
+           1.4839967870094333,
+           1.4955037671387525,
+           1.4965919385367163,
+           1.4873396867175528,
+           1.4680492428144747,
+           1.439244157618504,
+           1.4016614028488938,
+           1.356238235557564,
+           1.3040940910416428,
+           1.246507893194839,
+           1.184891285800754,
+           1.120758391005666,
+           1.0556927895380206,
+           0.9913124889500933,
+           0.9292336994335728,
+           0.8710342702454192,
+           0.8182176525990223,
+           0.772178246661445,
+           0.7341689612006355,
+           0.7052717651110401,
+           0.6863719416742191,
+           0.6781366706151921,
+           0.6809984618574504,
+           0.6951438508019784,
+           0.7205076407199776,
+           0.7567728464691145,
+           0.8033763584108158,
+           0.8595202094127231,
+           0.9241881944756705,
+           0.9961674650755631,
+           1.074074601861107,
+           1.1563855627838362,
+           1.2414688116514732,
+           1.3276208567303036,
+           1.413103372208102,
+           1.4961810384433314,
+           1.575159220858161,
+           1.6484206124609107,
+           1.7144599911689178,
+           1.7719162896891443,
+           1.8196012415478395,
+           1.8565239503164468,
+           1.8819108281042787,
+           1.89522046154444,
+           1.8961530860344764,
+           1.8846544789024708,
+           1.8609142162706729,
+           1.8253583734022731,
+           1.7786368809442643,
+           1.721605876486707,
+           1.6553055091549342,
+           1.580933761665209,
+           1.4998169468243754,
+           1.4133776116123293,
+           1.3231006399322056,
+           1.2304983834793273,
+           1.137075668083592,
+           1.0442955199454036,
+           0.953546432551714,
+           0.8661119513766424,
+           0.7831432908849377,
+           0.7056356184757794,
+           0.6344085448631707,
+           0.5700912523946704,
+           0.5131125746834739,
+           0.46369621563503444,
+           0.4218611666260292,
+           0.38742725046997195,
+           0.36002559312287846,
+           0.33911370201848323,
+           0.32399471650302913,
+           0.31384029387020324,
+           0.3077165064910979,
+           0.3046120536522826,
+           0.30346803771004277,
+           0.3032085193430956,
+           0.30277105185996395,
+           0.3011364000088021,
+           0.29735667435550067,
+           0.2905811573449322,
+           0.2800791604585378,
+           0.2652593317913616,
+           0.24568492784041945,
+           0.22108466990850217,
+           0.19135892156501405,
+           0.15658104611653262,
+           0.11699392891234152,
+           0.07300177535059281,
+           0.025157418463253776,
+           -0.02585451317485573,
+           -0.07923810870682575,
+           -0.13410981499443325,
+           -0.18952456727411804,
+           -0.24450370906892654,
+           -0.29806395264347213,
+           -0.3492466031825217,
+           -0.3971462616976892,
+           -0.44093823364186996,
+           -0.479903902050738,
+           -0.5134533749477156,
+           -0.5411447854747019,
+           -0.5626997080276303,
+           -0.578014252458766,
+           -0.5871655086778095,
+           -0.5904131329708069,
+           -0.5881959920659522,
+           -0.5811239082671242,
+           -0.5699646756379861,
+           -0.5556266400515539,
+           -0.5391372518122747,
+           -0.5216181055689509,
+           -0.5042570756685775,
+           -0.48827823356484645,
+           -0.47491029537225304,
+           -0.46535439055016803,
+           -0.46075196587519013,
+           -0.46215364166930073,
+           -0.4704898195577571,
+           -0.4865438032079065,
+           -0.5109281364245699,
+           -0.5440647880076203,
+           -0.5861697217199484,
+           -0.637242284780828,
+           -0.6970597320524357,
+           -0.7651770783746688,
+           -0.8409323413912161,
+           -0.923457104903979,
+           -1.0116922015618826,
+           -1.1044081867822584,
+           -1.2002301563671218,
+           -1.2976663512833722,
+           -1.395139897243942,
+           -1.4910229464558953,
+           -1.5836724262104007,
+           -1.6714665554694335,
+           -1.7528412673751674,
+           -1.8263256732924955,
+           -1.8905757227026538,
+           -1.9444052525871518,
+           -1.986813678961001,
+           -2.0170096605306482,
+           -2.0344301582122055,
+           -2.0387544221906997,
+           -2.0299125577208756,
+           -2.0080884490681408,
+           -1.973716954752014,
+           -1.9274754233324014,
+           -1.8702697140604045,
+           -1.8032150375116671,
+           -1.7276120546461533,
+           -1.644918785589892,
+           -1.5567189790633793,
+           -1.4646876773631192,
+           -1.370554778094537,
+           -1.2760674408473769,
+           -1.1829522135620456,
+           -1.0928777588210188,
+           -1.0074190445933962,
+           -0.9280238274617858,
+           -0.8559821999767656,
+           -0.7923998989086755,
+           -0.7381759796456063,
+           -0.6939853560717045,
+           -0.660266587553423,
+           -0.6372151680513121,
+           -0.6247824399645576,
+           -0.6226801203454907,
+           -0.6303902928913324,
+           -0.6471805889065019,
+           -0.6721241574032444,
+           -0.7041239116613722,
+           -0.7419404396345588,
+           -0.784222880982743,
+           -0.8295420062584543,
+           -0.876424685478015,
+           -0.9233889050951182,
+           -0.9689784848955598,
+           -1.0117966596659704,
+           -1.0505377242604417,
+           -1.084015993996554,
+           -1.1111914037750108,
+           -1.1311911571075417,
+           -1.1433269381279336,
+           -1.1471073130793357,
+           -1.142245069864769,
+           -1.1286593719566256,
+           -1.1064727330912227,
+           -1.076002948479969,
+           -1.037750243530915,
+           -0.9923800191828017,
+           -0.940701680982481,
+           -0.8836441343180387,
+           -0.8222286084096512,
+           -0.7575395347957818,
+           -0.690694250601304,
+           -0.6228123217717996,
+           -0.5549852861337723,
+           -0.4882476005301851,
+           -0.4235495408296138,
+           -0.3617327492567251,
+           -0.3035090516561182,
+           -0.24944307983183306,
+           -0.19993913324214233,
+           -0.1552326026484316,
+           -0.11538615866212072,
+           -0.08029078354581966,
+           -0.049671598267326714,
+           -0.023098311882312372,
+           -2.0107776575631545e-16
+          ],
+          [
+           0,
+           0.01932309804499384,
+           0.03708621831762916,
+           0.0541711172057323,
+           0.0714916076884074,
+           0.08996502056676234,
+           0.11048345631587367,
+           0.13388560116771794,
+           0.16092986772979873,
+           0.19226958759697765,
+           0.22843093183969168,
+           0.2697941662377511,
+           0.31657876340298047,
+           0.3688327956210462,
+           0.42642692281208355,
+           0.48905317221299077,
+           0.5562285831871786,
+           0.6273036650757098,
+           0.7014754913847584,
+           0.7778051330089164,
+           0.8552390196728178,
+           0.9326337152172262,
+           1.0087835013978688,
+           1.0824500888327027,
+           1.1523937145833236,
+           1.2174048451274941,
+           1.276335682253057,
+           1.328130668274244,
+           1.3718552060340976,
+           1.406721848001936,
+           1.432113266498445,
+           1.447601392306335,
+           1.4529621998355502,
+           1.448185721398112,
+           1.4334809884579083,
+           1.4092757211265863,
+           1.376210715642415,
+           1.3351290099258986,
+           1.287060036331652,
+           1.2331990952137881,
+           1.1748825998001622,
+           1.1135596492195432,
+           1.050760579689352,
+           0.9880632215149592,
+           0.9270576497176171,
+           0.869310257267707,
+           0.8163280009894823,
+           0.7695236706519523,
+           0.73018301150445,
+           0.6994344900006904,
+           0.6782224326268323,
+           0.667284190028417,
+           0.6671318848812386,
+           0.6780391944312307,
+           0.7000334999384921,
+           0.7328936082776464,
+           0.7761531187543369,
+           0.829109374009889,
+           0.8908378009686451,
+           0.9602113193719707,
+           1.035924374667973,
+           1.1165210418290554,
+           1.2004265497360147,
+           1.2859814944578165,
+           1.371477946049627,
+           1.4551966089358033,
+           1.5354441716184175,
+           1.6105899779393242,
+           1.6791011694982672,
+           1.7395754866544868,
+           1.7907709728759893,
+           1.8316319026351073,
+           1.8613103447234047,
+           1.8791828785206401,
+           1.8848620978074746,
+           1.878202662289812,
+           1.859301788028517,
+           1.8284942012362346,
+           1.7863417121575027,
+           1.7336176937627512,
+           1.6712868706441986,
+           1.6004809338706762,
+           1.5224705949657589,
+           1.4386347742692778,
+           1.3504276837579356,
+           1.2593446103965749,
+           1.1668872321952373,
+           1.0745293047781175,
+           0.9836835413550913,
+           0.895670473957969,
+           0.8116900295913319,
+           0.7327964829531388,
+           0.6598773594413945,
+           0.5936367605088179,
+           0.534583470620798,
+           0.48302408394740537,
+           0.4390612625111773,
+           0.4025971089775208,
+           0.37334150981726405,
+           0.3508251813610809,
+           0.33441703536010575,
+           0.32334537493421955,
+           0.31672233883779927,
+           0.3135709340861165,
+           0.3128539360673886,
+           0.313503892791205,
+           0.3144534469051674,
+           0.314665186071094,
+           0.3131602492518501,
+           0.30904495294066664,
+           0.3015347563991096,
+           0.28997495712625704,
+           0.27385759520132047,
+           0.2528341455853336,
+           0.22672368837108003,
+           0.1955163655103903,
+           0.15937205571208096,
+           0.11861432386608539,
+           0.07371982434905296,
+           0.025303455787127324,
+           -0.02590032470164287,
+           -0.07905951988674983,
+           -0.13326934875261254,
+           -0.18757907462414256,
+           -0.24102018457786692,
+           -0.29263516375816895,
+           -0.3415060917615198,
+           -0.3867822916333212,
+           -0.4277062851696229,
+           -0.4636373505588254,
+           -0.4940720388821222,
+           -0.5186610831034012,
+           -0.5372222249873769,
+           -0.549748589584591,
+           -0.5564123508947882,
+           -0.5575635531985562,
+           -0.5537240772856731,
+           -0.5455768662610825,
+           -0.5339506486064065,
+           -0.5198005136043141,
+           -0.5041848031166087,
+           -0.48823888127602433,
+           -0.473146427416255,
+           -0.4601089653759085,
+           -0.4503143924162269,
+           -0.44490530207573264,
+           -0.44494790650663923,
+           -0.45140235485175517,
+           -0.465095215184533,
+           -0.48669483910767813,
+           -0.5166902614311689,
+           -0.5553742040299103,
+           -0.6028306550341004,
+           -0.6589273843199165,
+           -0.7233136365423153,
+           -0.7954231166267386,
+           -0.8744822528245546,
+           -0.9595235923429715,
+           -1.04940405740413,
+           -1.1428276685237977,
+           -1.2383722298377615,
+           -1.3345193712349501,
+           -1.4296872563837557,
+           -1.522265196615222,
+           -1.6106493598013287,
+           -1.693278732140076,
+           -1.7686704799509072,
+           -1.8354538685121444,
+           -1.892401925445697,
+           -1.9384600864747554,
+           -1.9727711303615694,
+           -1.9946957958270306,
+           -2.0038285741943245,
+           -2.0000082849484637,
+           -1.9833231646147513,
+           -1.9541103293429631,
+           -1.912949605181559,
+           -1.8606518539878114,
+           -1.7982420539839898,
+           -1.7269375189443554,
+           -1.648121755837633,
+           -1.5633145646322242,
+           -1.4741390733659985,
+           -1.3822864743127279,
+           -1.2894792813739107,
+           -1.1974339633707476,
+           -1.1078238218723602,
+           -1.0222429752431479,
+           -0.9421722829066943,
+           -0.8689479960956751,
+           -0.8037338547668831,
+           -0.7474972665484778,
+           -0.7009901046147892,
+           -0.6647345496832593,
+           -0.6390142796387617,
+           -0.6238711815946582,
+           -0.6191076286480112,
+           -0.6242942304186214,
+           -0.638782835929455,
+           -0.6617244426708802,
+           -0.6920915498265788,
+           -0.7287043894359404,
+           -0.7702603792456744,
+           -0.8153660673279037,
+           -0.8625707829728547,
+           -0.9104011722113073,
+           -0.9573957804140591,
+           -1.0021388490811138,
+           -1.0432925189912519,
+           -1.0796266766499334,
+           -1.1100457442809035,
+           -1.1336117938294383,
+           -1.1495634605432496,
+           -1.1573302392668081,
+           -1.1565418639194716,
+           -1.1470325947837183,
+           -1.1288403661016748,
+           -1.1022008748748509,
+           -1.0675368174868827,
+           -1.0254426006991328,
+           -0.9766649647323713,
+           -0.9220800557975332,
+           -0.8626675711210086,
+           -0.799482669124725,
+           -0.7336263892739809,
+           -0.6662153589492196,
+           -0.5983515777620505,
+           -0.5310930627477732,
+           -0.46542611105573156,
+           -0.4022398908509036,
+           -0.34230400733834737,
+           -0.2862496107768968,
+           -0.23455451911555264,
+           -0.18753272187441633,
+           -0.1453285168038781,
+           -0.10791540961847744,
+           -0.07509978279390833,
+           -0.04652921519056702,
+           -0.021705213273332156,
+           -1.8990487711478142e-16
+          ],
+          [
+           0,
+           0.018484255525820423,
+           0.03583971740050231,
+           0.05295389302541296,
+           0.07073075779636064,
+           0.0900624342471874,
+           0.11180109637876982,
+           0.13673185637658344,
+           0.16554736664977646,
+           0.19882482700053505,
+           0.23700602583104788,
+           0.2803809671417859,
+           0.32907554360487895,
+           0.3830436125081277,
+           0.4420637184616128,
+           0.5057405872828017,
+           0.5735113924393523,
+           0.644656671936776,
+           0.7183156527121846,
+           0.7935056244946395,
+           0.8691448986376,
+           0.9440787923280786,
+           1.0171079972588397,
+           1.0870186264019253,
+           1.1526131846377823,
+           1.2127416799320647,
+           1.266332082300747,
+           1.3124193482642121,
+           1.3501722586658742,
+           1.3789173669316,
+           1.3981594219072409,
+           1.4075977127195798,
+           1.4071378806390689,
+           1.39689885230027,
+           1.3772146671770147,
+           1.3486310969993927,
+           1.311897082761979,
+           1.2679511429449037,
+           1.217903031381671,
+           1.1630110417614787,
+           1.1046554650987823,
+           1.0443088039100719,
+           0.983503429867862,
+           0.9237974382651686,
+           0.8667395010338311,
+           0.8138335490739972,
+           0.7665041235042316,
+           0.7260632238607266,
+           0.6936794494920657,
+           0.6703501791424695,
+           0.6568774642009386,
+           0.6538482249770005,
+           0.6616192387163332,
+           0.6803072953222139,
+           0.7097847746317367,
+           0.7496807705728634,
+           0.7993877557231658,
+           0.8580736479108548,
+           0.9246990117548303,
+           0.9980390055702459,
+           1.0767095708543404,
+           1.1591972603744136,
+           1.2438920141719516,
+           1.3291221226870238,
+           1.4131905644015792,
+           1.494411873157786,
+           1.5711486784077366,
+           1.6418470703750816,
+           1.7050699712343533,
+           1.7595277422166837,
+           1.8041053238279283,
+           1.8378852904606142,
+           1.8601662995288741,
+           1.8704765264296481,
+           1.868581797408553,
+           1.8544882598272678,
+           1.8284395602738663,
+           1.790908632228763,
+           1.7425843233935527,
+           1.6843532151801577,
+           1.6172771002678332,
+           1.5425666858154843,
+           1.4615521774095186,
+           1.375651470029245,
+           1.2863367255236833,
+           1.1951001500628937,
+           1.1034197989770942,
+           1.0127262300472482,
+           0.9243707998810591,
+           0.8395963522144013,
+           0.7595109830118848,
+           0.6850654867403941,
+           0.6170349932000765,
+           0.5560051972164095,
+           0.5023634670168978,
+           0.45629499415555935,
+           0.4177840214809317,
+           0.3866200590193831,
+           0.3624088739150961,
+           0.3445879228018173,
+           0.33244578609501685,
+           0.32514506637416024,
+           0.3217481296672079,
+           0.32124500109345905,
+           0.32258267660318,
+           0.3246950816657283,
+           0.3265328964218396,
+           0.3270924752594455,
+           0.32544311672959214,
+           0.3207519864350338,
+           0.3123060597752632,
+           0.2995305315568637,
+           0.2820032334197356,
+           0.2594647053869448,
+           0.23182368193358993,
+           0.19915787288732414,
+           0.16171004217541612,
+           0.11987950980893705,
+           0.0742093214432147,
+           0.025369442362937256,
+           -0.025863564037885235,
+           -0.07862982188918227,
+           -0.1320117640899561,
+           -0.18506139972003924,
+           -0.23682849494076347,
+           -0.28638891028529617,
+           -0.33287233225432317,
+           -0.37548865172014684,
+           -0.4135522754449114,
+           -0.4465037091949203,
+           -0.47392782017799995,
+           -0.49556827110859014,
+           -0.5113377159922206,
+           -0.5213234562590886,
+           -0.5257883724340205,
+           -0.5251670681708489,
+           -0.5200572871347867,
+           -0.5112067857636751,
+           -0.49949596327803475,
+           -0.4859166614414102,
+           -0.4715476476733507,
+           -0.4575273836106969,
+           -0.44502475483386805,
+           -0.435208494326488,
+           -0.4292160708386305,
+           -0.4281228326495654,
+           -0.4329121967284896,
+           -0.4444476529190379,
+           -0.463447312969449,
+           -0.4904616759253576,
+           -0.5258552059897511,
+           -0.5697922282580887,
+           -0.6222275439638876,
+           -0.6829020525598402,
+           -0.7513435459181379,
+           -0.8268727131661967,
+           -0.9086142663095944,
+           -0.995512970008646,
+           -1.0863542368125243,
+           -1.1797888348495047,
+           -1.2743611512715525,
+           -1.3685403642490592,
+           -1.4607538012782724,
+           -1.5494217038938858,
+           -1.632992580041633,
+           -1.7099783063679364,
+           -1.7789881440464848,
+           -1.8387608535036994,
+           -1.8881941350453288,
+           -1.926370682951666,
+           -1.9525802186598473,
+           -1.9663369623169669,
+           -1.9673921090097635,
+           -1.955740993766944,
+           -1.9316247551329202,
+           -1.895526437673917,
+           -1.8481616060237949,
+           -1.7904636737881638,
+           -1.7235642766174946,
+           -1.6487691369622683,
+           -1.5675299755542615,
+           -1.4814131188966018,
+           -1.3920655306944851,
+           -1.3011790563031003,
+           -1.21045371142157,
+           -1.1215608684004146,
+           -1.036107195121938,
+           -0.9556001824294601,
+           -0.8814160569968339,
+           -0.8147708183106213,
+           -0.7566950625179669,
+           -0.7080131641399138,
+           -0.6693272813163862,
+           -0.6410065339180693,
+           -0.6231815793827764,
+           -0.6157446815563523,
+           -0.6183552363088173,
+           -0.6304505874665474,
+           -0.6512618408262537,
+           -0.679834265757443,
+           -0.7150517660286209,
+           -0.7556648066203236,
+           -0.8003211037026027,
+           -0.8475983225629533,
+           -0.8960379845531895,
+           -0.9441797600983672,
+           -0.9905953210071238,
+           -1.0339209417717583,
+           -1.0728880757785728,
+           -1.1063511874072136,
+           -1.1333121934627655,
+           -1.1529409554081202,
+           -1.1645913652195934,
+           -1.1678126798218165,
+           -1.162355879154922,
+           -1.1481749479822034,
+           -1.1254231084380886,
+           -1.0944441558845153,
+           -1.0557591717683386,
+           -1.0100490008510103,
+           -0.9581329836039119,
+           -0.9009445251796605,
+           -0.8395041579578066,
+           -0.7748908133780598,
+           -0.7082120591967593,
+           -0.640574079473565,
+           -0.5730521760394289,
+           -0.5066625519325342,
+           -0.44233609982832606,
+           -0.38089486282523405,
+           -0.3230317625261695,
+           -0.26929410204270965,
+           -0.22007125158027271,
+           -0.17558681418955163,
+           -0.135895451893745,
+           -0.10088443070505307,
+           -0.07027982011487119,
+           -0.04365716159622479,
+           -0.020456304560241324,
+           -1.8013499053311168e-16
+          ],
+          [
+           0,
+           0.017798762569482127,
+           0.03489744982817743,
+           0.052181033850437625,
+           0.07053566536203093,
+           0.0908208173905689,
+           0.11384207422552622,
+           0.14032530019765785,
+           0.17089288808239006,
+           0.2060427342093976,
+           0.24613051794212978,
+           0.29135577881907654,
+           0.3417521874436548,
+           0.39718229861742405,
+           0.457336959941603,
+           0.5217394290705601,
+           0.5897541310177306,
+           0.6605998664669197,
+           0.7333671659785521,
+           0.80703937624424,
+           0.8805169658978741,
+           0.9526444523526256,
+           1.0222392799044087,
+           1.0881219247599752,
+           1.149146466134835,
+           1.204230845095987,
+           1.2523860348959233,
+           1.2927433681687455,
+           1.3245793070592757,
+           1.3473370011770387,
+           1.3606440537999938,
+           1.3643260071690375,
+           1.3584151608097819,
+           1.3431544500683077,
+           1.3189962326696907,
+           1.2865959561292188,
+           1.2468008051779427,
+           1.2006335528780185,
+           1.1492719587091225,
+           1.0940241686293875,
+           1.0363006731660855,
+           0.9775834674437638,
+           0.9193931295028432,
+           0.8632545884683177,
+           0.8106623906861808,
+           0.763046288902456,
+           0.7217379764453189,
+           0.6879397652078891,
+           0.6626959635345944,
+           0.646867648886091,
+           0.6411114518525086,
+           0.6458628745802854,
+           0.6613245602283796,
+           0.6874598132502572,
+           0.7239915459417353,
+           0.7704066978226229,
+           0.8259660441670545,
+           0.8897191815352958,
+           0.9605243546190024,
+           1.0370726731044901,
+           1.117916162404273,
+           1.2014990005630382,
+           1.286191217643541,
+           1.37032407529259,
+           1.452226304404767,
+           1.530260358807918,
+           1.6028578431715017,
+           1.6685532938724592,
+           1.726015531832511,
+           1.7740758653731201,
+           1.8117524974668295,
+           1.8382705835225768,
+           1.853077490776192,
+           1.8558529258943537,
+           1.846513720711558,
+           1.825213194088779,
+           1.7923351375799261,
+           1.7484826007524248,
+           1.6944617755079578,
+           1.6312613945841372,
+           1.5600281647760847,
+           1.4820388477491009,
+           1.3986696783947712,
+           1.3113638706669377,
+           1.221598002299396,
+           1.130848091790499,
+           1.0405561830601056,
+           0.9520982352531095,
+           0.8667540777852831,
+           0.7856801348841682,
+           0.7098855510072002,
+           0.6402122604757514,
+           0.5773194436730793,
+           0.5216727007576013,
+           0.4735381548334962,
+           0.4329815728743352,
+           0.3998724674955813,
+           0.37389301903415584,
+           0.3545515383869357,
+           0.341200079632454,
+           0.33305571036325776,
+           0.3292248593789918,
+           0.32873008809609694,
+           0.33053857550437027,
+           0.3335915681066497,
+           0.3368340269229025,
+           0.33924370375364593,
+           0.33985889842178535,
+           0.33780418710258714,
+           0.33231346809308526,
+           0.3227497440034744,
+           0.3086211465039375,
+           0.28959280919943,
+           0.26549430339515906,
+           0.23632246767846543,
+           0.20223958242782172,
+           0.16356696151854855,
+           0.12077415255746811,
+           0.07446405093069995,
+           0.025354338906374403,
+           -0.025744243683368268,
+           -0.07795220845944825,
+           -0.1303475514584066,
+           -0.18199320411740919,
+           -0.23196496432393773,
+           -0.27937915648764744,
+           -0.3234192757947372,
+           -0.36336089714753333,
+           -0.3985941731432452,
+           -0.42864330670869116,
+           -0.45318246114572175,
+           -0.4720476614173335,
+           -0.4852443432268725,
+           -0.49295031822649693,
+           -0.4955140417194305,
+           -0.49344819051651284,
+           -0.4874186801077607,
+           -0.47822936894161383,
+           -0.46680281036280974,
+           -0.4541575167823607,
+           -0.4413822932916421,
+           -0.42960827682040625,
+           -0.4199793800490924,
+           -0.4136218849843057,
+           -0.41161395819068364,
+           -0.4149558674040957,
+           -0.42454166737430293,
+           -0.44113309153344454,
+           -0.46533633617813974,
+           -0.4975823564730862,
+           -0.5381112103566399,
+           -0.5869608893765488,
+           -0.643960966978305,
+           -0.7087312774714868,
+           -0.7806857156976885,
+           -0.8590411213571755,
+           -0.9428310861388102,
+           -1.030924399357377,
+           -1.122047731777144,
+           -1.214812050580225,
+           -1.3077421636892619,
+           -1.3993087112518747,
+           -1.4879618580652185,
+           -1.5721658946891446,
+           -1.6504339281497216,
+           -1.7213618361859564,
+           -1.7836606721657193,
+           -1.8361867408211647,
+           -1.8779686170700858,
+           -1.9082304501659686,
+           -1.9264109815844563,
+           -1.9321778053347292,
+           -1.9254365113588623,
+           -1.906334473638246,
+           -1.8752591716275149,
+           -1.8328310635955702,
+           -1.7798911602072318,
+           -1.717483573066763,
+           -1.646833432885358,
+           -1.5693206825038337,
+           -1.4864503485023126,
+           -1.3998199791581634,
+           -1.311085004022966,
+           -1.2219228197341714,
+           -1.1339964366566204,
+           -1.0489185308373101,
+           -0.9682167353192171,
+           -0.8933009743597072,
+           -0.8254335942903173,
+           -0.7657029768639876,
+           -0.7150012366317696,
+           -0.6740065052424736,
+           -0.6431701949848608,
+           -0.6227095141014078,
+           -0.6126053803270994,
+           -0.6126057498287308,
+           -0.6222342493971119,
+           -0.6408038735303572,
+           -0.667435388014625,
+           -0.7010799706761353,
+           -0.740545520833842,
+           -0.7845259840203569,
+           -0.8316329698015308,
+           -0.8804288896510224,
+           -0.9294608100217243,
+           -0.9772942037251844,
+           -1.0225457907184263,
+           -1.063914687146452,
+           -1.1002111282517824,
+           -1.1303820953263681,
+           -1.1535332575949404,
+           -1.168946734735714,
+           -1.1760942922734716,
+           -1.1746456976456134,
+           -1.1644720864506564,
+           -1.1456443132013028,
+           -1.1184263857117487,
+           -1.0832642039490838,
+           -1.040769939753803,
+           -0.9917025004261153,
+           -0.9369446141543044,
+           -0.8774771562954536,
+           -0.8143514006267994,
+           -0.7486599272886282,
+           -0.6815069480983389,
+           -0.6139788195595662,
+           -0.5471155040337837,
+           -0.4818837104867239,
+           -0.4191523987504963,
+           -0.3596712665969478,
+           -0.30405275876933674,
+           -0.252758043525149,
+           -0.20608729759464056,
+           -0.16417452742350275,
+           -0.12698703601745137,
+           -0.09432952365059111,
+           -0.06585269020662443,
+           -0.04106609004441236,
+           -0.019354879975318248,
+           -1.7177933406592038e-16
+          ],
+          [
+           0,
+           0.017264118740909374,
+           0.034250352547373256,
+           0.0518330995976668,
+           0.07087308601396637,
+           0.0921902095923175,
+           0.11653743086126579,
+           0.1445764173842994,
+           0.1768556026976955,
+           0.21379125970800433,
+           0.25565211130873905,
+           0.3025479103518128,
+           0.3544223192068996,
+           0.411050308528306,
+           0.4720401783131809,
+           0.536840184818257,
+           0.6047496374247241,
+           0.6749342131254055,
+           0.7464451259055138,
+           0.8182416867019682,
+           0.8892166994436526,
+           0.9582240622015017,
+           1.0241078816785343,
+           1.0857323657223008,
+           1.1420117333928268,
+           1.1919393760568753,
+           1.2346155162168047,
+           1.269272643049976,
+           1.2952980541868615,
+           1.312252900888942,
+           1.3198872168683145,
+           1.3181505074980973,
+           1.3071975837354766,
+           1.287389441075846,
+           1.2592891054198567,
+           1.2236524918628255,
+           1.1814144460353233,
+           1.1336702576674569,
+           1.0816530495321102,
+           1.0267075490145772,
+           0.9702608416544963,
+           0.9137907837987383,
+           0.8587928130275879,
+           0.8067459387061707,
+           0.7590787197403044,
+           0.7171360417186473,
+           0.6821474909214418,
+           0.6551980884783833,
+           0.6372020950529957,
+           0.628880526068911,
+           0.6307429313566818,
+           0.6430738932605325,
+           0.6659245861149714,
+           0.699109620273886,
+           0.7422092684567378,
+           0.7945770441176246,
+           0.8553524739611661,
+           0.9234787827334544,
+           0.9977250910304105,
+           1.0767126189535865,
+           1.1589442926385285,
+           1.242837069321039,
+           1.3267562316781212,
+           1.409050855266001,
+           1.488089625120773,
+           1.5622961696615734,
+           1.6301830921302147,
+           1.690383911613618,
+           1.7416821764413626,
+           1.7830370811838139,
+           1.813605002915955,
+           1.8327564707886916,
+           1.8400881928520922,
+           1.835429882813847,
+           1.8188457540866423,
+           1.7906306760337634,
+           1.751301114649416,
+           1.701581103904941,
+           1.6423836116363404,
+           1.574787772284591,
+           1.5000125554009458,
+           1.419387521262728,
+           1.334321381231199,
+           1.2462691290425012,
+           1.1566985389157411,
+           1.0670568365151314,
+           0.9787383392255109,
+           0.8930538331883123,
+           0.8112024068732727,
+           0.7342463958635594,
+           0.6630900126701731,
+           0.5984621408130469,
+           0.5409036664934586,
+           0.4907596065927479,
+           0.44817617133208176,
+           0.41310277672131346,
+           0.3852988989780385,
+           0.3643455434642958,
+           0.34966098733156364,
+           0.34052035078594245,
+           0.3360784592535064,
+           0.3353953800138088,
+           0.337463953998647,
+           0.34123859794534245,
+           0.34566462503433026,
+           0.3497073241520809,
+           0.35238004914658316,
+           0.35277059954728623,
+           0.3500652223958978,
+           0.34356962981906064,
+           0.33272650708975043,
+           0.31712907911544347,
+           0.29653040717698115,
+           0.2708481996765627,
+           0.24016503779188644,
+           0.20472403630385758,
+           0.16492007844273682,
+           0.12128687837987523,
+           0.07448023307538211,
+           0.02525792384295873,
+           -0.025543185282380046,
+           -0.07703223268218833,
+           -0.12829095145560043,
+           -0.17840105327820652,
+           -0.22647166733423635,
+           -0.2716660958736427,
+           -0.3132271649525481,
+           -0.35050048447047105,
+           -0.38295498483051144,
+           -0.4102001670835436,
+           -0.43199958752687473,
+           -0.4482801942955429,
+           -0.45913724007888124,
+           -0.464834609029665,
+           -0.4658005143337975,
+           -0.46261864278528675,
+           -0.4560149410330513,
+           -0.44684035193687194,
+           -0.4360499158030553,
+           -0.42467874746239065,
+           -0.4138154837494414,
+           -0.40457386480103885,
+           -0.39806316493635624,
+           -0.3953582233450867,
+           -0.3974698404729795,
+           -0.405316302403142,
+           -0.4196967727155688,
+           -0.44126724977536036,
+           -0.47051972812976833,
+           -0.5077651271082504,
+           -0.5531204596509145,
+           -0.6065006120370723,
+           -0.6676149930560371,
+           -0.7359691920148388,
+           -0.8108716617509931,
+           -0.8914453185597506,
+           -0.9766438287343132,
+           -1.0652722342894068,
+           -1.1560114613105628,
+           -1.247446155967952,
+           -1.3380952080200743,
+           -1.4264442517532727,
+           -1.5109793815276773,
+           -1.590221284780107,
+           -1.6627589803668446,
+           -1.7272823549373448,
+           -1.7826127145490729,
+           -1.827730612413527,
+           -1.8618002754819338,
+           -1.8841900310646218,
+           -1.8944882279482869,
+           -1.8925142522807692,
+           -1.878324354273526,
+           -1.852212124719221,
+           -1.8147035874481787,
+           -1.7665470020592795,
+           -1.7086975974353693,
+           -1.642297577614296,
+           -1.5686518545815282,
+           -1.4892000647217538,
+           -1.4054855145212688,
+           -1.319121774481796,
+           -1.2317576962996204,
+           -1.1450416658143197,
+           -1.0605859221272549,
+           -0.979931771199277,
+           -0.9045165002163907,
+           -0.8356427576059045,
+           -0.7744511038128262,
+           -0.721896361274967,
+           -0.6787283003463739,
+           -0.645477093459284,
+           -0.6224438551433267,
+           -0.6096964634430514,
+           -0.6070707317755878,
+           -0.6141768724389953,
+           -0.630411066937129,
+           -0.6549718370989637,
+           -0.6868807975863533,
+           -0.7250072675549679,
+           -0.7680961294459283,
+           -0.8147982483030077,
+           -0.8637027074173892,
+           -0.9133700768622668,
+           -0.962365911502992,
+           -1.0092936747879646,
+           -1.0528263039880537,
+           -1.0917356710211183,
+           -1.124919249565086,
+           -1.1514233723761715,
+           -1.170462550727609,
+           -1.1814344284467384,
+           -1.1839300536268762,
+           -1.1777392689542636,
+           -1.1628511437755764,
+           -1.1394494944928664,
+           -1.1079036615413735,
+           -1.0687548280632304,
+           -1.0226982745453823,
+           -0.9705620624497908,
+           -0.9132827257996294,
+           -0.8518786206931103,
+           -0.7874216370700131,
+           -0.7210080134471223,
+           -0.6537290129113011,
+           -0.5866422170284181,
+           -0.5207441735892306,
+           -0.45694509484410345,
+           -0.3960462461145313,
+           -0.3387205918849506,
+           -0.2854971795463778,
+           -0.23674964210939353,
+           -0.1926890929491906,
+           -0.15336157074376933,
+           -0.11865007413536077,
+           -0.08828110629297045,
+           -0.06183553250324158,
+           -0.03876344213023126,
+           -0.01840260258950546,
+           -1.6483396539325375e-16
+          ],
+          [
+           0,
+           0.016876283018268032,
+           0.03388644054155189,
+           0.051886582476702636,
+           0.07170486633234505,
+           0.09411526342708693,
+           0.11981275294347196,
+           0.14939061568378156,
+           0.1833204457368117,
+           0.22193542867070665,
+           0.26541735107710546,
+           0.31378771041633435,
+           0.36690318856833004,
+           0.4244556399412944,
+           0.4859766282708057,
+           0.5508464283053561,
+           0.6183072924035787,
+           0.687480670606751,
+           0.7573879688266008,
+           0.8269743360468961,
+           0.8951348902704123,
+           0.9607427264317284,
+           1.0226779993581248,
+           1.0798573424056166,
+           1.1312628684942656,
+           1.1759700053231221,
+           1.2131734404934353,
+           1.2422104945697943,
+           1.262581299763308,
+           1.2739652374940955,
+           1.2762331777470495,
+           1.2694551646846006,
+           1.2539033039312564,
+           1.230049724565507,
+           1.1985596102414644,
+           1.1602794160113834,
+           1.116220507301122,
+           1.0675385721231234,
+           1.0155092641387473,
+           0.961500629941063,
+           0.9069429565189155,
+           0.8532967422020555,
+           0.8020195447671323,
+           0.7545324925123372,
+           0.7121872571401158,
+           0.67623428084689,
+           0.6477930242110195,
+           0.6278249568766285,
+           0.617109950697112,
+           0.6162266564119641,
+           0.6255373519701363,
+           0.6451776455248975,
+           0.6750513014525399,
+           0.7148303362726991,
+           0.7639604060242726,
+           0.8216713805284666,
+           0.8869928761227367,
+           0.9587743998966971,
+           1.035709648096438,
+           1.116364401881851,
+           1.1992073774515408,
+           1.2826433167969744,
+           1.3650475517389402,
+           1.4448012387442302,
+           1.5203264461754955,
+           1.5901202794768823,
+           1.6527872532446517,
+           1.7070691615979676,
+           1.751871758707916,
+           1.7862876382797659,
+           1.809614792329695,
+           1.8213704335102514,
+           1.821299778976125,
+           1.8093796145617325,
+           1.7858165829134856,
+           1.7510402651341077,
+           1.7056912493836858,
+           1.6506044987256319,
+           1.5867884414167572,
+           1.5154003071291977,
+           1.4377183198335042,
+           1.3551114301661602,
+           1.2690073253270884,
+           1.180859491596717,
+           1.0921141225714106,
+           1.004177664804217,
+           0.9183857717975631,
+           0.8359743977954543,
+           0.7580537055948792,
+           0.6855853891063179,
+           0.619363923505612,
+           0.5600021557505873,
+           0.5079215384984205,
+           0.46334719380015094,
+           0.4263078722786203,
+           0.3966407518197962,
+           0.37400090014741666,
+           0.3578751109725724,
+           0.34759971654821753,
+           0.3423818830476905,
+           0.3413238115943591,
+           0.343449199039968,
+           0.34773126039100927,
+           0.3531215803680945,
+           0.35857904575932903,
+           0.36309811333508296,
+           0.3657356899949024,
+           0.3656359419137449,
+           0.3620524066865389,
+           0.3543668553519031,
+           0.34210443783266264,
+           0.32494474354520114,
+           0.30272851619730917,
+           0.27545987538725347,
+           0.2433040146517678,
+           0.20658046312133693,
+           0.16575211295230244,
+           0.1214103243076127,
+           0.07425652108076568,
+           0.02508078123782188,
+           -0.025261996700503317,
+           -0.07587770686195477,
+           -0.1258597386611619,
+           -0.17431605029051603,
+           -0.2203958846076765,
+           -0.26331540780338036,
+           -0.30238157856608894,
+           -0.3370136006011399,
+           -0.366761373177338,
+           -0.39132043130838945,
+           -0.41054295729358536,
+           -0.4244445463714193,
+           -0.4332065186343659,
+           -0.43717368435278964,
+           -0.43684758755661146,
+           -0.43287537014947947,
+           -0.42603451300900763,
+           -0.41721381856313294,
+           -0.40739109848169847,
+           -0.39760811785774297,
+           -0.3889434213308058,
+           -0.382483725119487,
+           -0.3792946003644371,
+           -0.38039119644242203,
+           -0.38670975735708346,
+           -0.3990806697720364,
+           -0.41820374803101956,
+           -0.4446264103795782,
+           -0.47872533278400164,
+           -0.5206920838759093,
+           -0.5705231486540071,
+           -0.6280146419965533,
+           -0.6927618983986987,
+           -0.7641640044745086,
+           -0.8414332186172184,
+           -0.9236091008194813,
+           -1.0095770580325598,
+           -1.0980908995173628,
+           -1.1877988951793432,
+           -1.277272740423961,
+           -1.3650387558674042,
+           -1.4496105911898667,
+           -1.5295226610309485,
+           -1.603363518170853,
+           -1.6698083659289138,
+           -1.7276499278786237,
+           -1.775826928281856,
+           -1.8134494902678215,
+           -1.8398208294565308,
+           -1.8544547067616073,
+           -1.857088203432646,
+           -1.8476894916127171,
+           -1.826460392120914,
+           -1.7938336349464827,
+           -1.750464864049318,
+           -1.6972195534299006,
+           -1.6351551230038845,
+           -1.5654986576265557,
+           -1.4896207378580217,
+           -1.4090059841711826,
+           -1.3252209950071925,
+           -1.239880421455167,
+           -1.154611965851267,
+           -1.0710211171710569,
+           -0.9906564421049605,
+           -0.9149762370169965,
+           -0.8453173129294045,
+           -0.7828666340633799,
+           -0.7286364615653301,
+           -0.6834435695479275,
+           -0.6478930025458064,
+           -0.6223667343266479,
+           -0.607017470380576,
+           -0.601767713208908,
+           -0.606314083756738,
+           -0.6201367670513113,
+           -0.6425138283725048,
+           -0.6725400310546904,
+           -0.7091496810989572,
+           -0.7511429297259608,
+           -0.7972148850923136,
+           -0.845986820545532,
+           -0.8960387205241418,
+           -0.9459423776053841,
+           -0.9942942458862764,
+           -1.039747267002142,
+           -1.0810409153071894,
+           -1.1170287572625284,
+           -1.1467028856455126,
+           -1.169214670139619,
+           -1.183891360139904,
+           -1.1902481808426661,
+           -1.1879956772423896,
+           -1.1770421796956194,
+           -1.157491386263541,
+           -1.1296351780896332,
+           -1.0939419016024756,
+           -1.0510404624475984,
+           -1.0017006780029243,
+           -0.9468104256112164,
+           -0.8873502000570845,
+           -0.8243657544637479,
+           -0.7589395422206988,
+           -0.6921617027447877,
+           -0.6251013402492813,
+           -0.558778832144561,
+           -0.494139872590149,
+           -0.43203190789407675,
+           -0.3731835551880673,
+           -0.31818751578088833,
+           -0.2674874018602925,
+           -0.22136879214457508,
+           -0.17995472130227413,
+           -0.14320569227732732,
+           -0.11092418301115455,
+           -0.08276350242292642,
+           -0.058240737845915914,
+           -0.036753430270488295,
+           -0.017599517388107163,
+           -1.592800982693119e-16
+          ],
+          [
+           0,
+           0.016629746025206414,
+           0.03379098970558886,
+           0.052314234069884204,
+           0.07298844259560186,
+           0.09653593514676855,
+           0.12358906767492558,
+           0.1546693284988281,
+           0.19016942197207437,
+           0.23033883360066795,
+           0.2752732811182897,
+           0.32490835592376005,
+           0.379017551158261,
+           0.43721475927916215,
+           0.4989612061386607,
+           0.5635766732291584,
+           0.6302547478346432,
+           0.6980817351675229,
+           0.7660587698591204,
+           0.8331265788746715,
+           0.8981922762226482,
+           0.9601575135686932,
+           1.0179472715074207,
+           1.0705385548308601,
+           1.116988252252879,
+           1.156459436834137,
+           1.1882454174647743,
+           1.2117909034059777,
+           1.2267097118307562,
+           1.2327985308931289,
+           1.2300463460786366,
+           1.218639243113197,
+           1.1989604139355272,
+           1.1715853103764098,
+           1.1372720103135137,
+           1.096946980204186,
+           1.0516865330799499,
+           1.0026943894454734,
+           0.9512758473547404,
+           0.8988091547612068,
+           0.8467147498718945,
+           0.7964230918392201,
+           0.7493418432526837,
+           0.7068231865283561,
+           0.6701320578745305,
+           0.6404160649436033,
+           0.6186778179416225,
+           0.6057503496998242,
+           0.6022762293016625,
+           0.6086908880009823,
+           0.625210577429166,
+           0.6518252708581193,
+           0.6882967012100314,
+           0.7341616074282111,
+           0.7887401367165968,
+           0.8511492270425683,
+           0.9203206751809447,
+           0.9950234833639138,
+           1.0738899750325936,
+           1.155445079767007,
+           1.2381381114126955,
+           1.320376303582814,
+           1.400559324557904,
+           1.4771139701612102,
+           1.5485282290282631,
+           1.6133839299155326,
+           1.6703872149300767,
+           1.718396134970982,
+           1.7564447329695678,
+           1.78376306500262,
+           1.799792706962715,
+           1.80419740281496,
+           1.7968686269007346,
+           1.7779259544220565,
+           1.747712258184573,
+           1.7067838728702163,
+           1.655895987551573,
+           1.595983639944188,
+           1.5281387892826757,
+           1.4535840361989687,
+           1.373643635369056,
+           1.2897125081216443,
+           1.203224006206882,
+           1.1156172034752818,
+           1.0283044987423449,
+           0.9426403005079927,
+           0.859891532828966,
+           0.7812106523352309,
+           0.7076118004076958,
+           0.6399506335720799,
+           0.5789082812572791,
+           0.5249797755760801,
+           0.47846718532812665,
+           0.439477568807587,
+           0.4079257401501402,
+           0.38354172485385235,
+           0.36588266470839603,
+           0.3543488235210962,
+           0.3482032454207091,
+           0.3465945295994853,
+           0.34858211127320504,
+           0.35316338020040705,
+           0.35930192671501776,
+           0.3659561818717585,
+           0.37210771350964134,
+           0.3767884538693833,
+           0.37910616645378126,
+           0.37826750923914,
+           0.37359811684056327,
+           0.364559204113899,
+           0.3507602858942034,
+           0.33196770977038675,
+           0.3081088083770001,
+           0.27927159186384465,
+           0.2457000170875256,
+           0.2077849847217952,
+           0.1660513260056725,
+           0.12114114444632157,
+           0.07379397185091685,
+           0.024824280203507704,
+           -0.02490304094397324,
+           -0.0744985794526658,
+           -0.12307497042309644,
+           -0.16977342585346566,
+           -0.21378950999804316,
+           -0.25439746552300074,
+           -0.2909724326508453,
+           -0.3230099575098479,
+           -0.3501422555011815,
+           -0.3721507789104944,
+           -0.3889747331199047,
+           -0.40071529022159236,
+           -0.4076353599594974,
+           -0.4101548929244533,
+           -0.4088418068931062,
+           -0.40439874119736796,
+           -0.3976459531495034,
+           -0.38950077205719114,
+           -0.3809541176591823,
+           -0.3730446685646172,
+           -0.3668313304671537,
+           -0.36336470187067343,
+           -0.3636582655518694,
+           -0.3686600461776487,
+           -0.3792254680296502,
+           -0.39609212176839437,
+           -0.4198571061640315,
+           -0.4509575507484834,
+           -0.4896548498502477,
+           -0.5360230492941225,
+           -0.5899417263649558,
+           -0.6510935939202671,
+           -0.7189669434948781,
+           -0.7928629227388129,
+           -0.8719075225275954,
+           -0.9550680315607486,
+           -1.0411736041446213,
+           -1.1289394829358927,
+           -1.2169943253029103,
+           -1.3039100019812164,
+           -1.3882331718753513,
+           -1.4685178888386887,
+           -1.5433584662821902,
+           -1.6114218143143604,
+           -1.6714784721267415,
+           -1.7224315853699947,
+           -1.7633431237025774,
+           -1.7934566964705658,
+           -1.812216403098503,
+           -1.8192812473490827,
+           -1.8145347489105974,
+           -1.798089499269934,
+           -1.7702865287708556,
+           -1.7316894752258924,
+           -1.683073668439013,
+           -1.6254103664826611,
+           -1.5598464955929738,
+           -1.4876803532680423,
+           -1.4103338309447235,
+           -1.3293217961244053,
+           -1.2462193419762508,
+           -1.1626276636015447,
+           -1.080139353044467,
+           -1.000303918979242,
+           -0.9245943314534381,
+           -0.8543753672599446,
+           -0.7908744880544833,
+           -0.7351559222963384,
+           -0.688098544962426,
+           -0.6503780576570829,
+           -0.6224538684467903,
+           -0.6045609580163472,
+           -0.5967068993263216,
+           -0.598674074767184,
+           -0.6100270108591368,
+           -0.6301246288593695,
+           -0.6581370931721546,
+           -0.6930668310417689,
+           -0.7337731992719707,
+           -0.7790001890209318,
+           -0.8274064901051221,
+           -0.8775971833738184,
+           -0.9281562948374215,
+           -0.9776794291518304,
+           -1.024805703118716,
+           -1.0682482219257625,
+           -1.1068223813221008,
+           -1.1394713367502949,
+           -1.1652880541584432,
+           -1.1835334449275163,
+           -1.1936501868605058,
+           -1.1952719419951912,
+           -1.188227797400747,
+           -1.17254187422234,
+           -1.1484281700846484,
+           -1.1162808175802432,
+           -1.0766600540399849,
+           -1.0302743023320535,
+           -0.9779588564894127,
+           -0.9206517472148522,
+           -0.8593674287743981,
+           -0.7951689788529641,
+           -0.7291395354121548,
+           -0.6623537087020106,
+           -0.5958497020393,
+           -0.5306028519443133,
+           -0.46750125735739545,
+           -0.4073241100126393,
+           -0.3507232651242233,
+           -0.29820850521615433,
+           -0.2501368524067031,
+           -0.20670617823034457,
+           -0.16795324784313623,
+           -0.13375622006001697,
+           -0.10384150903814465,
+           -0.07779480047562605,
+           -0.055075907795248104,
+           -0.03503705464187529,
+           -0.01694408164346088,
+           -1.5508458470450388e-16
+          ],
+          [
+           0,
+           0.01651761714154755,
+           0.03394674678213825,
+           0.053085428256424365,
+           0.07467738016182165,
+           0.09938821635441879,
+           0.12778377425513512,
+           0.1603111447819355,
+           0.19728292368240646,
+           0.23886512105898933,
+           0.285069071550161,
+           0.33574758433560076,
+           0.39059546248039045,
+           0.44915440789356287,
+           0.5108222142139749,
+           0.5748660381371565,
+           0.6404394328952364,
+           0.7066027285112849,
+           0.7723462545924185,
+           0.836615825072717,
+           0.8983398424269242,
+           0.956457333048976,
+           1.009946196925493,
+           1.057850944202806,
+           1.0993091990658364,
+           1.1335762773784432,
+           1.160047188181734,
+           1.1782754693718416,
+           1.1879883432275637,
+           1.1890977660962248,
+           1.1817070463023969,
+           1.1661128127660394,
+           1.1428022312298711,
+           1.1124454825707835,
+           1.0758836354923507,
+           1.0341121610370738,
+           0.988260445950672,
+           0.93956776323967,
+           0.8893562487507286,
+           0.8390015099908416,
+           0.7899015557463629,
+           0.7434447807587217,
+           0.7009777675964737,
+           0.663773677186021,
+           0.6330019899422824,
+           0.6097003312559863,
+           0.5947490688866295,
+           0.5888493066654619,
+           0.5925048203361137,
+           0.6060083892390579,
+           0.6294328741035798,
+           0.6626272789526299,
+           0.7052179167773439,
+           0.7566146770778842,
+           0.8160222715566763,
+           0.8824562151597302,
+           0.9547631861985171,
+           1.0316453042204734,
+           1.1116877701987882,
+           1.1933892327827031,
+           1.275194178765961,
+           1.3555265971977797,
+           1.43282413587159,
+           1.5055719570325972,
+           1.572335506338079,
+           1.631791435208354,
+           1.6827559610829366,
+           1.724210011660198,
+           1.7553205764432858,
+           1.7754577799516242,
+           1.7842072935593816,
+           1.7813778145829655,
+           1.7670034592308406,
+           1.741341037470934,
+           1.7048622998014713,
+           1.6582413653597163,
+           1.6023376548633332,
+           1.5381747577806737,
+           1.4669157583024848,
+           1.389835626839196,
+           1.3082913509186505,
+           1.2236905299048655,
+           1.137459190705605,
+           1.051009595831505,
+           0.9657088105169219,
+           0.8828487722809982,
+           0.8036185649259094,
+           0.729079540609917,
+           0.6601438597850064,
+           0.5975569313203939,
+           0.5418841362447115,
+           0.4935021107090183,
+           0.4525947496935332,
+           0.41915397549527916,
+           0.3929851970615908,
+           0.37371727070130983,
+           0.36081666246935906,
+           0.3536054103016535,
+           0.35128239229047037,
+           0.35294732858264144,
+           0.3576268801782441,
+           0.3643021599594301,
+           0.3719369407325882,
+           0.37950583263070786,
+           0.3860217081515009,
+           0.39056167719620594,
+           0.3922909560660808,
+           0.3904840323739694,
+           0.38454260073367474,
+           0.3740098300263289,
+           0.35858061981312395,
+           0.3381076086020341,
+           0.31260280751068864,
+           0.28223484658710574,
+           0.24732193477475925,
+           0.2083207453615321,
+           0.165811543932461,
+           0.12047997269761734,
+           0.07309599114514012,
+           0.02449054610415845,
+           -0.02446939735073118,
+           -0.07290679063301722,
+           -0.11996070372542034,
+           -0.16481208949054837,
+           -0.20670841637941784,
+           -0.24498650482188136,
+           -0.279092948793685,
+           -0.3086015661954536,
+           -0.33322739818233243,
+           -0.35283686651953805,
+           -0.36745379716462256,
+           -0.37726112508926574,
+           -0.38259820715375986,
+           -0.38395378380961354,
+           -0.38195474364585336,
+           -0.37735095444361005,
+           -0.37099652767869484,
+           -0.36382797768697295,
+           -0.35683981957819444,
+           -0.3510582193294711,
+           -0.3475133635241086,
+           -0.34721125352084387,
+           -0.3511056484548845,
+           -0.3600708828396226,
+           -0.37487626756646336,
+           -0.3961627481588659,
+           -0.4244224420446349,
+           -0.4599816086173465,
+           -0.502987523613194,
+           -0.5533996348424746,
+           -0.6109852719042567,
+           -0.675320070749965,
+           -0.7457931576071742,
+           -0.8216170187098623,
+           -0.901841865435976,
+           -0.9853741917339183,
+           -1.070999114937782,
+           -1.157405994871136,
+           -1.2432167419351616,
+           -1.3270161547901662,
+           -1.4073835740469327,
+           -1.482925101473343,
+           -1.5523056155554995,
+           -1.614279814345874,
+           -1.6677215354356116,
+           -1.711650640193261,
+           -1.7452568042515781,
+           -1.7679196272981612,
+           -1.7792245608335178,
+           -1.7789742506395139,
+           -1.767194998880566,
+           -1.7441381664157956,
+           -1.7102764562219717,
+           -1.666295140885376,
+           -1.6130784179408924,
+           -1.5516911934704336,
+           -1.4833567039725841,
+           -1.409430486402484,
+           -1.3313712940135907,
+           -1.250709629065063,
+           -1.1690146207931595,
+           -1.087860016878895,
+           -1.0087900780019086,
+           -0.9332861674290925,
+           -0.8627348108874473,
+           -0.7983979666226344,
+           -0.7413861924123953,
+           -0.6926353266872349,
+           -0.6528872165124121,
+           -0.6226749280693198,
+           -0.6023127678148603,
+           -0.5918913273198508,
+           -0.5912776447046378,
+           -0.6001204535318888,
+           -0.6178603689584213,
+           -0.6437447438376085,
+           -0.6768468171484082,
+           -0.716088676283188,
+           -0.7602674657946331,
+           -0.8080842003266058,
+           -0.8581744804304118,
+           -0.909140368199734,
+           -0.9595826561211243,
+           -1.0081327577581713,
+           -1.0534834629302805,
+           -1.0944178325109035,
+           -1.1298355580017092,
+           -1.1587761773542,
+           -1.1804386194242693,
+           -1.194196642917934,
+           -1.199609839371233,
+           -1.1964299810102224,
+           -1.1846026104817546,
+           -1.1642638875421005,
+           -1.1357328249067737,
+           -1.0994991587001415,
+           -1.056207205499948,
+           -1.006636155224015,
+           -0.9516773346658991,
+           -0.8923090482612446,
+           -0.8295696589126732,
+           -0.7645296110649415,
+           -0.6982631197743218,
+           -0.6318202527733855,
+           -0.5662001174694554,
+           -0.5023258318644797,
+           -0.44102190842496575,
+           -0.3829946142659016,
+           -0.3288157913362143,
+           -0.2789105286474385,
+           -0.2335489773105952,
+           -0.1928424908157449,
+           -0.15674416035443858,
+           -0.1250537009018111,
+           -0.09742653112967181,
+           -0.07338678186273054,
+           -0.052343866454002165,
+           -0.03361215470067685,
+           -0.016433212063027367,
+           -1.5220054590144855e-16
+          ],
+          [
+           0,
+           0.016531725372860746,
+           0.03433416375844152,
+           0.05416655560431569,
+           0.0767219471198915,
+           0.10260489817575161,
+           0.13231160126881011,
+           0.1662129534666242,
+           0.20454104704116588,
+           0.24737945623828178,
+           0.2946575995328344,
+           0.3461493512692016,
+           0.40147596644770656,
+           0.46011327037547767,
+           0.5214029537917724,
+           0.5845677067193067,
+           0.6487298234100793,
+           0.7129328189130244,
+           0.7761655173342618,
+           0.837388004849258,
+           0.8955587886859139,
+           0.9496624679768273,
+           0.9987372045140718,
+           1.0419012815312922,
+           1.078378056737283,
+           1.1075186515332724,
+           1.128821770822165,
+           1.1419501158002878,
+           1.1467429339587178,
+           1.143224344210555,
+           1.131607178300749,
+           1.1122921899011693,
+           1.0858625973201397,
+           1.053074041724228,
+           1.0148401573002859,
+           0.972214060025704,
+           0.9263661649134554,
+           0.8785588351724918,
+           0.8301184483234811,
+           0.7824055318760441,
+           0.7367836729909986,
+           0.6945879412900666,
+           0.6570935807258079,
+           0.6254857247189416,
+           0.6008308685957658,
+           0.5840507951582801,
+           0.5758995938821447,
+           0.5769443430751555,
+           0.5875499390458413,
+           0.6078684589829901,
+           0.637833337187258,
+           0.6771585201228227,
+           0.7253426472460478,
+           0.7816781846053362,
+           0.8452653197169784,
+           0.9150303120982144,
+           0.9897478868691955,
+           1.0680671616354767,
+           1.1485405118102463,
+           1.2296547087126988,
+           1.3098636099208676,
+           1.3876216438079265,
+           1.4614173108724018,
+           1.5298059238593835,
+           1.5914408267794538,
+           1.64510236932342,
+           1.6897239669556086,
+           1.7244146468325763,
+           1.7484775639300638,
+           1.7614240683111322,
+           1.7629830109734073,
+           1.753105089572993,
+           1.731962153757461,
+           1.699941509962103,
+           1.6576353844050797,
+           1.6058258177647848,
+           1.5454653728477783,
+           1.477654134842808,
+           1.403613570127644,
+           1.3246578819691497,
+           1.2421635580979435,
+           1.1575378447018665,
+           1.0721869029436428,
+           0.9874844071883238,
+           0.9047413287021786,
+           0.8251776150883287,
+           0.749896425032455,
+           0.6798615113426799,
+           0.6158782644694043,
+           0.5585788357184883,
+           0.5084116565561456,
+           0.46563556031580833,
+           0.43031859799968286,
+           0.402341523570396,
+           0.38140580903560656,
+           0.3670459385892005,
+           0.358645626827539,
+           0.35545751117463464,
+           0.35662578545360607,
+           0.36121117206519326,
+           0.3682175761632323,
+           0.3766197278501852,
+           0.3853910986321882,
+           0.3935313766114153,
+           0.40009280114170875,
+           0.4042046914694842,
+           0.4050955543261469,
+           0.40211222121630597,
+           0.3947355455619788,
+           0.3825922808823383,
+           0.36546286148947,
+           0.34328491421207374,
+           0.31615244070507054,
+           0.28431072215056474,
+           0.24814710876514268,
+           0.2081779627048607,
+           0.1650321220222595,
+           0.11943134278011812,
+           0.07216825400968993,
+           0.024082423962202046,
+           -0.023964815563900618,
+           -0.0711161083470067,
+           -0.11654368359393065,
+           -0.15947414734074072,
+           -0.1992117874745784,
+           -0.23515976286499435,
+           -0.2668386017061937,
+           -0.29390150360165235,
+           -0.3161460224169705,
+           -0.33352180040261925,
+           -0.3461341261846091,
+           -0.3542431973581996,
+           -0.3582590798635556,
+           -0.3587324682526577,
+           -0.35634146053836857,
+           -0.351874665769828,
+           -0.3462110591488928,
+           -0.34029708592794244,
+           -0.3351215893012843,
+           -0.33168919712164324,
+           -0.33099284599742335,
+           -0.3339861480097601,
+           -0.34155631421003174,
+           -0.35449833994156893,
+           -0.37349113004801193,
+           -0.39907619780700665,
+           -0.43163951101615994,
+           -0.4713969835196468,
+           -0.5183840224310999,
+           -0.5724494425396514,
+           -0.6332539523122362,
+           -0.7002733031699738,
+           -0.7728060781101558,
+           -0.849985980136467,
+           -0.9307983682235507,
+           -1.0141006814880573,
+           -1.098646293542913,
+           -1.183111251148194,
+           -1.2661232764527355,
+           -1.3462923522380599,
+           -1.4222421661578852,
+           -1.4926416641357603,
+           -1.5562359555312688,
+           -1.6118758236529576,
+           -1.6585451244672618,
+           -1.6953854032602833,
+           -1.721717122449169,
+           -1.7370569721990514,
+           -1.7411308270949362,
+           -1.7338820146335636,
+           -1.7154746722546053,
+           -1.686292086328658,
+           -1.6469300261218625,
+           -1.5981852053487868,
+           -1.5410391205890495,
+           -1.4766376267294092,
+           -1.4062667119920944,
+           -1.3313250265168926,
+           -1.253293796642347,
+           -1.1737048200658367,
+           -1.0941072834088037,
+           -1.0160341722355541,
+           -0.9409690535714818,
+           -0.8703140021924782,
+           -0.8053594146237564,
+           -0.7472564095605881,
+           -0.696992451409972,
+           -0.6553707563662994,
+           -0.6229939497642402,
+           -0.6002523416136786,
+           -0.5873170767019996,
+           -0.5841382991464226,
+           -0.5904483516361534,
+           -0.6057699097375954,
+           -0.6294288344650074,
+           -0.6605714146938758,
+           -0.6981855676251358,
+           -0.7411254728997296,
+           -0.7881390363513668,
+           -0.8378975146851807,
+           -0.8890265841260746,
+           -0.9401381054309547,
+           -0.9898618253074029,
+           -1.0368762604792103,
+           -1.0799380351821144,
+           -1.1179089851042974,
+           -1.1497803996147018,
+           -1.174693848050393,
+           -1.1919581229940661,
+           -1.2010619316747368,
+           -1.2016820734102844,
+           -1.1936869537149408,
+           -1.1771354015127704,
+           -1.1522708719534303,
+           -1.119511230743806,
+           -1.0794344238848972,
+           -1.0327604365758796,
+           -0.9803300343619311,
+           -0.9230808561726698,
+           -0.86202149085954,
+           -0.7982042146963292,
+           -0.7326970959652387,
+           -0.666556183550697,
+           -0.6007984891903342,
+           -0.5363764479251666,
+           -0.4741544990321295,
+           -0.41488837142215096,
+           -0.35920758465596275,
+           -0.30760159123882463,
+           -0.26040988988946523,
+           -0.21781633548175974,
+           -0.17984776197188657,
+           -0.14637692262216545,
+           -0.11712964005061108,
+           -0.0916959498985334,
+           -0.06954491896377538,
+           -0.05004272409203588,
+           -0.032473494337789365,
+           -0.016062348010835347,
+           -1.5056814338436888e-16
+          ],
+          [
+           0,
+           0.016662732716736958,
+           0.03493165387386705,
+           0.05552144454253658,
+           0.07906971551987464,
+           0.10611635916139342,
+           0.1370855791916992,
+           0.1722710896846007,
+           0.2118248924524005,
+           0.255749949514277,
+           0.3038969664647716,
+           0.35596539598517063,
+           0.4115086611290737,
+           0.4699434881435648,
+           0.5305631312434282,
+           0.5925541696616623,
+           0.6550164630503538,
+           0.7169857673032748,
+           0.7774584412626668,
+           0.8354176173969657,
+           0.8898601678785332,
+           0.9398237726437703,
+           0.9844133886554658,
+           1.0228264299450405,
+           1.0543759958830445,
+           1.0785115298635766,
+           1.0948363511224557,
+           1.1031215772730554,
+           1.1033160425094235,
+           1.0955519141492696,
+           1.0801458158619175,
+           1.0575953769370958,
+           1.0285712405492633,
+           0.9939046773379064,
+           0.9545710609355149,
+           0.9116695665791205,
+           0.8663995500245097,
+           0.8200341492329475,
+           0.7738917235706626,
+           0.7293058027202414,
+           0.6875942586821243,
+           0.6500284380749829,
+           0.6178029977837919,
+           0.5920071746553925,
+           0.5735981896530801,
+           0.5633774393475995,
+           0.5619700639616017,
+           0.5698084029174225,
+           0.5871197578456574,
+           0.6139187814925046,
+           0.650004701377808,
+           0.6949634720657487,
+           0.7481748323154168,
+           0.8088241260459456,
+           0.8759186318445145,
+           0.948308037455879,
+           1.0247085959674316,
+           1.1037304116849003,
+           1.1839072281535936,
+           1.263728030270117,
+           1.3416697284343966,
+           1.4162301662918864,
+           1.4859606854619152,
+           1.549497490943239,
+           1.6055910893845762,
+           1.653133118412471,
+           1.6911799475992968,
+           1.7189725089079204,
+           1.7359519046799605,
+           1.7417704422391787,
+           1.736297853494205,
+           1.7196225728785859,
+           1.6920480647572058,
+           1.6540843091861035,
+           1.6064346697705774,
+           1.5499784765315006,
+           1.4857497575120222,
+           1.4149126428945413,
+           1.3387340424768215,
+           1.2585542596240034,
+           1.1757562507835266,
+           1.0917342682396172,
+           1.007862634338602,
+           0.9254653877261865,
+           0.8457875164430909,
+           0.7699684497081897,
+           0.6990184209869105,
+           0.6337982410022095,
+           0.5750029325612513,
+           0.5231495816209222,
+           0.4785696533364257,
+           0.4414059105642084,
+           0.4116139581906837,
+           0.38896832256265584,
+           0.37307286402838363,
+           0.3633752149078595,
+           0.359184837700094,
+           0.3596942113983308,
+           0.36400257954693566,
+           0.3711416339415653,
+           0.38010246408736015,
+           0.389863075728257,
+           0.3994157725583359,
+           0.40779370379746493,
+           0.414095906388296,
+           0.4175102134431898,
+           0.41733345911265857,
+           0.41298848274639977,
+           0.4040375202071679,
+           0.3901916653054441,
+           0.3713161871279051,
+           0.3474315969246575,
+           0.31871046846500084,
+           0.2854701255796959,
+           0.2481614172046858,
+           0.20735390093599684,
+           0.16371784835896908,
+           0.11800356690213046,
+           0.07101860163541628,
+           0.023603434556368964,
+           -0.023393662873854058,
+           -0.0691419468292929,
+           -0.1128530067825508,
+           -0.15380439220140096,
+           -0.1913614234347877,
+           -0.22499659700274963,
+           -0.25430605774380266,
+           -0.279022686119927,
+           -0.2990254365169172,
+           -0.31434465939431944,
+           -0.3251632441822618,
+           -0.33181352826097316,
+           -0.3347700274486954,
+           -0.3346381523766597,
+           -0.33213918018300737,
+           -0.3280918494431803,
+           -0.32339103566606653,
+           -0.31898404274156344,
+           -0.3158451104264035,
+           -0.3149487876339639,
+           -0.3172428546570783,
+           -0.32362149361484127,
+           -0.3348994049188133,
+           -0.3517875483864826,
+           -0.3748711512183509,
+           -0.40459057226029704,
+           -0.4412255440671652,
+           -0.4848832329194747,
+           -0.5354904641153269,
+           -0.5927903578470421,
+           -0.656343512294093,
+           -0.7255337579096283,
+           -0.7995783930416555,
+           -0.8775426988418513,
+           -0.9583584236706633,
+           -1.0408458265983718,
+           -1.1237387786491755,
+           -1.2057123414251067,
+           -1.2854121776752792,
+           -1.3614850988981153,
+           -1.432610022452417,
+           -1.4975285957654645,
+           -1.5550747484844325,
+           -1.6042024547959206,
+           -1.6440110271637038,
+           -1.6737673184983306,
+           -1.6929242809500173,
+           -1.7011354144026485,
+           -1.698264734295738,
+           -1.6843919942761185,
+           -1.6598130118126222,
+           -1.6250350615556335,
+           -1.5807674190474559,
+           -1.5279072535143763,
+           -1.4675211800614971,
+           -1.400822885918469,
+           -1.3291473398964404,
+           -1.2539221765992117,
+           -1.1766369151667018,
+           -1.0988107247430365,
+           -1.0219594841683068,
+           -0.947562900724118,
+           -0.8770324516902275,
+           -0.811680893015176,
+           -0.7526940420396315,
+           -0.7011054868481519,
+           -0.6577748047895217,
+           -0.6233697887075159,
+           -0.5983530835138126,
+           -0.582973530254398,
+           -0.5772624023446312,
+           -0.5810346019199276,
+           -0.5938947661147986,
+           -0.6152481164202386,
+           -0.6443157719167469,
+           -0.6801541418674915,
+           -0.721677917436781,
+           -0.7676860984883946,
+           -0.8168904215357105,
+           -0.8679455006357306,
+           -0.9194799556305018,
+           -0.9701277825135631,
+           -1.0185592192692905,
+           -1.0635103772837047,
+           -1.1038109428943266,
+           -1.1384093049355473,
+           -1.166394530933887,
+           -1.1870146952243221,
+           -1.1996911546660454,
+           -1.2040284695194226,
+           -1.199819775861474,
+           -1.1870475289555225,
+           -1.1658796514438612,
+           -1.1366612332638157,
+           -1.0999020390026546,
+           -1.0562601803214848,
+           -1.0065224035863143,
+           -0.9515815236786556,
+           -0.8924116021467968,
+           -0.8300415197744676,
+           -0.7655276290420208,
+           -0.6999261900069308,
+           -0.6342662934401179,
+           -0.569523957670432,
+           -0.5065980510016889,
+           -0.44628864069382373,
+           -0.38927830366637267,
+           -0.33611685498480404,
+           -0.2872098598535819,
+           -0.24281119556775357,
+           -0.20301982419089143,
+           -0.16778082731215493,
+           -0.13689064385950642,
+           -0.11000634340047066,
+           -0.08665866338760912,
+           -0.06626844202651476,
+           -0.04816599129908719,
+           -0.03161287935934822,
+           -0.015825529928593842,
+           -1.5011548028462238e-16
+          ],
+          [
+           0,
+           0.016900258635844993,
+           0.03571586617310471,
+           0.0571118043688341,
+           0.08166618324264982,
+           0.10985136796354489,
+           0.14201801711694456,
+           0.17838247010420993,
+           0.21901783466944286,
+           0.26384902966180857,
+           0.3126519355508415,
+           0.365056698513009,
+           0.42055512580144316,
+           0.478512003336361,
+           0.5381800637197579,
+           0.5987182367943457,
+           0.6592127278792266,
+           0.7187003931439173,
+           0.7761938191671225,
+           0.8307074661763392,
+           0.8812842030173138,
+           0.9270215473950683,
+           0.9670969277735675,
+           1.0007913034979223,
+           1.02751051675565,
+           1.0468038030430162,
+           1.058378954567621,
+           1.0621137118474195,
+           1.0580630506774051,
+           1.046462132365321,
+           1.0277247921989647,
+           1.002437551848422,
+           0.9713492530776854,
+           0.9353565199628251,
+           0.8954853620493224,
+           0.852869328897658,
+           0.8087247148061208,
+           0.7643233889392728,
+           0.7209638886964247,
+           0.6799414613319409,
+           0.6425177693719424,
+           0.6098909884530638,
+           0.5831670214610597,
+           0.5633325303330257,
+           0.5512304471080683,
+           0.5475385696960234,
+           0.5527517767153033,
+           0.567168311334447,
+           0.5908804883732389,
+           0.6237700742947794,
+           0.6655084786898126,
+           0.7155617811205142,
+           0.7732005015491602,
+           0.8375139088501165,
+           0.9074285528702537,
+           0.9817306038301149,
+           1.059091491034985,
+           1.1380962531413228,
+           1.2172739465549631,
+           1.2951294085350855,
+           1.3701756384717543,
+           1.4409660454103803,
+           1.5061258125970771,
+           1.564381650553605,
+           1.6145892484581221,
+           1.6557577884770347,
+           1.687070957826687,
+           1.7079039770308877,
+           1.7178362580392557,
+           1.7166594102596981,
+           1.704380423589071,
+           1.6812199724921832,
+           1.647605901278731,
+           1.6041620651335895,
+           1.5516928113852668,
+           1.491163488280204,
+           1.4236774616751555,
+           1.3504502013141515,
+           1.2727810657628673,
+           1.1920234670174004,
+           1.1095541310536372,
+           1.0267421883176997,
+           0.9449188279888417,
+           0.8653482318261814,
+           0.7892004680319058,
+           0.7175269737438266,
+           0.6512391878312178,
+           0.5910908153008441,
+           0.537664112844304,
+           0.49136048416951583,
+           0.45239556627490785,
+           0.42079887641856234,
+           0.39641797697115094,
+           0.37892700440837285,
+           0.36783930213626853,
+           0.3625237972773399,
+           0.362224671423026,
+           0.3660837968851795,
+           0.37316534506742366,
+           0.382481923796864,
+           0.393021566997658,
+           0.40377488373139586,
+           0.41376167472798897,
+           0.42205634300173056,
+           0.42781146047362845,
+           0.43027890376639716,
+           0.4288280381698218,
+           0.42296050749658626,
+           0.4123212771473108,
+           0.39670567589499256,
+           0.3760622861882011,
+           0.3504916405151651,
+           0.32024078984059584,
+           0.2856939165824863,
+           0.24735926635031302,
+           0.2058527671531847,
+           0.1618787896266453,
+           0.1162085748845961,
+           0.06965691604147965,
+           0.023057723776654167,
+           -0.022760865583523752,
+           -0.06700116981206808,
+           -0.1089197647249977,
+           -0.14784977175665928,
+           -0.18322102812254057,
+           -0.2145775935005389,
+           -0.24159211619903076,
+           -0.26407666313347333,
+           -0.28198970954539126,
+           -0.2954390839516408,
+           -0.30468076878954736,
+           -0.31011356496800324,
+           -0.31226973631720367,
+           -0.31180185501798025,
+           -0.30946616881805544,
+           -0.30610290267128837,
+           -0.3026139890265279,
+           -0.29993879025878417,
+           -0.29902843189713924,
+           -0.30081940493309867,
+           -0.306207118548923,
+           -0.3160200904613075,
+           -0.330995450535007,
+           -0.3517564046227651,
+           -0.378792260401473,
+           -0.41244155638328733,
+           -0.4528787607555192,
+           -0.5001049200668163,
+           -0.5539425411586005,
+           -0.6140348855226708,
+           -0.6798497460261,
+           -0.7506876643918607,
+           -0.8256944367305817,
+           -0.903877646552939,
+           -0.9841268627470303,
+           -1.065237046533206,
+           -1.145934628758786,
+           -1.2249056491510204,
+           -1.3008252940789717,
+           -1.372388130393248,
+           -1.438338311031692,
+           -1.4974990238931578,
+           -1.5488004691482753,
+           -1.5913056813929836,
+           -1.6242335611399579,
+           -1.6469785439513027,
+           -1.6591264135187618,
+           -1.660465855319018,
+           -1.6509954479287379,
+           -1.6309258972409004,
+           -1.60067743205177,
+           -1.5608723950291061,
+           -1.5123231781088757,
+           -1.4560157630902393,
+           -1.3930892338760557,
+           -1.3248117238520405,
+           -1.2525533479358797,
+           -1.177756741748392,
+           -1.1019058883734962,
+           -1.0264939548570926,
+           -0.9529908849210446,
+           -0.8828115007361319,
+           -0.8172848548454053,
+           -0.7576255437389169,
+           -0.7049076478705125,
+           -0.6600419002152954,
+           -0.6237566083209841,
+           -0.5965827650897129,
+           -0.5788436834279421,
+           -0.5706493818632711,
+           -0.5718958348831371,
+           -0.5822690858646855,
+           -0.6012541048607544,
+           -0.6281481609974561,
+           -0.662078372559085,
+           -0.7020229995750664,
+           -0.746835956260392,
+           -0.7952739461069686,
+           -0.8460255625697605,
+           -0.8977416545665918,
+           -0.9490662294432891,
+           -0.9986671572526613,
+           -1.04526594932513,
+           -1.0876659108970472,
+           -1.1247780113032326,
+           -1.1556438748092166,
+           -1.1794553690450338,
+           -1.1955703543453615,
+           -1.2035242539353799,
+           -1.203037209414395,
+           -1.1940166957764937,
+           -1.1765555825413876,
+           -1.1509257396643793,
+           -1.1175673959794752,
+           -1.077074561312435,
+           -1.0301769185369343,
+           -0.9777186764036186,
+           -0.9206349458831229,
+           -0.8599262602838125,
+           -0.7966319011488382,
+           -0.7318027169163014,
+           -0.6664741289724355,
+           -0.6016400099055081,
+           -0.5382280917784061,
+           -0.4770775188097466,
+           -0.41891910012515765,
+           -0.3643587457308044,
+           -0.3138644844310219,
+           -0.2677573682169676,
+           -0.22620646609043296,
+           -0.18922804393387446,
+           -0.15668891858828043,
+           -0.12831386649724266,
+           -0.10369686284112732,
+           -0.08231582865409978,
+           -0.06355047346974445,
+           -0.046702741842701505,
+           -0.03101930563653576,
+           -0.015715491921897525,
+           -1.5075962138870204e-16
+          ],
+          [
+           0,
+           0.017233014136307435,
+           0.03666197535990932,
+           0.058897684947541405,
+           0.08445540939795637,
+           0.11373789174163673,
+           0.14702147284925032,
+           0.18444570495185664,
+           0.2260067489830111,
+           0.27155474914060745,
+           0.3207952747302037,
+           0.3732948135080775,
+           0.428490195073014,
+           0.48570172004056733,
+           0.5441496733829103,
+           0.602973810907497,
+           0.6612553286580424,
+           0.7180407580773188,
+           0.7723671767935618,
+           0.8232880872533276,
+           0.8698992941128719,
+           0.9113641068988759,
+           0.9469372071158123,
+           0.9759865484420717,
+           0.9980127042292919,
+           1.0126651371037065,
+           1.0197549395912695,
+           1.0192636805348223,
+           1.0113480875296101,
+           0.9963403983165108,
+           0.9747443214974515,
+           0.9472266564085741,
+           0.9146047307806136,
+           0.8778299202200173,
+           0.837967612924365,
+           0.7961740739105306,
+           0.7536707430992139,
+           0.7117165688425633,
+           0.671579031194149,
+           0.6345045460500829,
+           0.6016889612746529,
+           0.574248858516225,
+           0.5531943595009671,
+           0.5394041034774294,
+           0.5336030139134446,
+           0.536343408665233,
+           0.5479899301736655,
+           0.5687086826635176,
+           0.5984608639941332,
+           0.6370010731436833,
+           0.6838803628979929,
+           0.7384539938732424,
+           0.7998937332978455,
+           0.867204432766352,
+           0.9392445161287131,
+           1.014749914315002,
+           1.092360900531459,
+           1.1706512089438168,
+           1.2481587644154457,
+           1.3234173114572734,
+           1.3949882082458942,
+           1.4614916469285852,
+           1.5216365745807776,
+           1.5742486197978638,
+           1.6182953772473891,
+           1.6529084654278918,
+           1.6774018498441687,
+           1.691286012939501,
+           1.6942776512496893,
+           1.6863046869448772,
+           1.6675064926013685,
+           1.6382293419759286,
+           1.5990172129646067,
+           1.5505981790577132,
+           1.493866729775894,
+           1.4298624562618985,
+           1.3597456230920446,
+           1.2847702194122428,
+           1.2062551399647166,
+           1.1255541880836413,
+           1.0440256173237645,
+           0.9630019354871852,
+           0.8837606843012664,
+           0.8074968801802034,
+           0.7352977571047616,
+           0.6681203928158747,
+           0.6067727257537777,
+           0.5518983843403434,
+           0.5039656544477521,
+           0.4632608076109888,
+           0.42988590429538565,
+           0.4037610760107691,
+           0.3846311800082634,
+           0.3720766134242618,
+           0.36552797268319565,
+           0.3642841512210521,
+           0.3675333864177351,
+           0.3743766970333585,
+           0.3838530971191128,
+           0.3949659326465182,
+           0.4067096639076389,
+           0.4180964106071751,
+           0.4281815875928795,
+           0.4360879870230218,
+           0.44102770669872976,
+           0.44232138314503655,
+           0.4394142602865316,
+           0.4318887083784473,
+           0.41947290108266067,
+           0.4020454588494211,
+           0.3796359715360039,
+           0.3524214198104891,
+           0.3207186206577116,
+           0.28497292455538975,
+           0.24574348804371032,
+           0.20368553304948142,
+           0.15953008124175386,
+           0.11406171595635937,
+           0.06809497421941685,
+           0.02245000587187582,
+           -0.02207184511240599,
+           -0.06471188076161515,
+           -0.10477666993313316,
+           -0.14165884111733507,
+           -0.17485548618532215,
+           -0.20398367615895707,
+           -0.22879266504783577,
+           -0.24917244372192895,
+           -0.2651584004963347,
+           -0.27693194619922534,
+           -0.2848170664166727,
+           -0.2892728697011532,
+           -0.2908823051051269,
+           -0.2903373228036028,
+           -0.2884208452485979,
+           -0.2859860008687177,
+           -0.2839331456293507,
+           -0.2831852579242802,
+           -0.2846623377262944,
+           -0.2892554704981624,
+           -0.29780122926799113,
+           -0.31105708413363786,
+           -0.3296784673351638,
+           -0.3541981044038608,
+           -0.3850081686569875,
+           -0.42234574874749087,
+           -0.46628203874700425,
+           -0.5167155693078155,
+           -0.5733696990566485,
+           -0.635794479977261,
+           -0.7033729017526775,
+           -0.7753314105644156,
+           -0.8507544904116737,
+           -0.9286029922999787,
+           -1.0077358012268176,
+           -1.086934345156573,
+           -1.1649293762892927,
+           -1.2404293947579776,
+           -1.312150039973213,
+           -1.3788437463325531,
+           -1.4393289486822338,
+           -1.4925181290943732,
+           -1.5374440201057469,
+           -1.573283320026289,
+           -1.5993773323202152,
+           -1.6152490120496923,
+           -1.6206159862468505,
+           -1.615399209820898,
+           -1.5997270219186321,
+           -1.5739344770291246,
+           -1.5385579378945762,
+           -1.4943250307093616,
+           -1.442140174388761,
+           -1.3830660021464023,
+           -1.3183010926301808,
+           -1.2491545170041054,
+           -1.1770177854431765,
+           -1.103334839637229,
+           -1.0295707855265166,
+           -0.957180091443748,
+           -0.8875749903492436,
+           -0.8220948205796698,
+           -0.7619770175834274,
+           -0.7083304300172143,
+           -0.66211157827798,
+           -0.624104403389131,
+           -0.5949039708589967,
+           -0.5749044997142915,
+           -0.5642919836839881,
+           -0.5630415619866693,
+           -0.5709196840266001,
+           -0.5874909982868813,
+           -0.6121297835976923,
+           -0.6440356334799558,
+           -0.6822530040296182,
+           -0.7256941452446835,
+           -0.7731648569951507,
+           -0.8233924458908072,
+           -0.87505520966824,
+           -0.9268127425736273,
+           -0.9773363393316522,
+           -1.0253387770080213,
+           -1.0696027733049824,
+           -1.1090074560560537,
+           -1.1425522309717324,
+           -1.1693775017014498,
+           -1.1887817763278754,
+           -1.2002347854895183,
+           -1.2033863371594196,
+           -1.1980707392042964,
+           -1.1843067305724917,
+           -1.1622929725897442,
+           -1.1323992606419029,
+           -1.0951537208077629,
+           -1.0512263532055408,
+           -1.0014093715472128,
+           -0.9465948645106084,
+           -0.8877503671876246,
+           -0.8258929785351847,
+           -0.7620626923067727,
+           -0.6972956236430897,
+           -0.6325978110390885,
+           -0.5689202538982041,
+           -0.5071358098748381,
+           -0.4480185246461305,
+           -0.3922259009833795,
+           -0.34028453570451256,
+           -0.29257946428420417,
+           -0.2493474558398069,
+           -0.21067439836434917,
+           -0.17649680804853543,
+           -0.14660739000405437,
+           -0.12066447336124092,
+           -0.09820504419723373,
+           -0.07866100756378772,
+           -0.06137822734742141,
+           -0.045637821883813365,
+           -0.030679135941943773,
+           -0.0157237673285409,
+           -1.5240771933344432e-16
+          ],
+          [
+           0,
+           0.017648943855769556,
+           0.03774398356342359,
+           0.06083794780947726,
+           0.08738065604913528,
+           0.11770390126355057,
+           0.15200970567859476,
+           0.19036217464114127,
+           0.2326831803687296,
+           0.2787520077331241,
+           0.3282089911289051,
+           0.3805630674272587,
+           0.4352030676608056,
+           0.4914124720255813,
+           0.5483872615136602,
+           0.6052564173289573,
+           0.6611045482876845,
+           0.714996068482999,
+           0.7660003040947945,
+           0.8132168804821968,
+           0.855800729348475,
+           0.8929860611460518,
+           0.9241086699042672,
+           0.948625975808538,
+           0.9661342642253238,
+           0.9763826471588208,
+           0.9792833526972468,
+           0.97491803790324,
+           0.9635399186061752,
+           0.9455716132388154,
+           0.9215987046541709,
+           0.8923591311048461,
+           0.8587286225934802,
+           0.8217024989849,
+           0.7823742390991386,
+           0.741911313146584,
+           0.7015288422254499,
+           0.662461706367615,
+           0.6259357653153818,
+           0.5931388827324267,
+           0.5651924541890224,
+           0.5431241317226188,
+           0.5278424131921939,
+           0.5201137235722382,
+           0.5205425587315772,
+           0.5295551914606573,
+           0.5473873562475909,
+           0.5740762355682724,
+           0.6094569685206127,
+           0.653163794974587,
+           0.704635837650118,
+           0.7631274133760466,
+           0.8277226559411516,
+           0.89735412908499,
+           0.9708250118356464,
+           1.0468343519451664,
+           1.1240048087232608,
+           1.2009122459551804,
+           1.2761164903022153,
+           1.3481925417401694,
+           1.4157615109076584,
+           1.477520564006814,
+           1.5322711789923171,
+           1.5789450566436702,
+           1.6166270857737777,
+           1.6445748319303808,
+           1.6622341017885542,
+           1.6692502289938995,
+           1.6654748292166606,
+           1.6509678801311116,
+           1.62599509331162,
+           1.5910206569269638,
+           1.5466955378947762,
+           1.4938416371595775,
+           1.4334321894315325,
+           1.3665688867021089,
+           1.2944562810106814,
+           1.218374084439432,
+           1.1396480316659694,
+           1.0596200014823705,
+           0.9796181077744255,
+           0.9009274672440927,
+           0.8247623307747521,
+           0.7522402283283552,
+           0.6843587245799596,
+           0.6219753154757558,
+           0.5657909162341171,
+           0.5163373009917344,
+           0.47396875558380314,
+           0.43885810029587735,
+           0.41099713143428074,
+           0.39020142190745255,
+           0.3761193143783256,
+           0.36824483856766244,
+           0.36593418946882805,
+           0.3684253179011461,
+           0.3748601110663759,
+           0.3843085803735957,
+           0.39579442821828487,
+           0.408321335726261,
+           0.4208993003886839,
+           0.43257035629223656,
+           0.44243303013946256,
+           0.4496649228923464,
+           0.4535428586897555,
+           0.4534601083413987,
+           0.4489402724993212,
+           0.43964749756399135,
+           0.425392793256245,
+           0.4061363221450566,
+           0.3819856356971383,
+           0.3531899359714771,
+           0.3201305442807991,
+           0.2833078554061215,
+           0.24332514583099643,
+           0.2008696846979581,
+           0.1566916647656004,
+           0.11158152583995908,
+           0.06634628358637659,
+           0.021785501288022337,
+           -0.021332449607181253,
+           -0.062293202617189784,
+           -0.10045767017230767,
+           -0.1352812059214875,
+           -0.16633013805421315,
+           -0.19329522471350566,
+           -0.2160016625698149,
+           -0.23441536916857297,
+           -0.2486453564889435,
+           -0.25894211480609153,
+           -0.2656920298592961,
+           -0.26940795985976307,
+           -0.2707161993988054,
+           -0.2703401522858699,
+           -0.2690811223405203,
+           -0.2677967079646665,
+           -0.26737735096607057,
+           -0.26872164092953504,
+           -0.272711012120877,
+           -0.2801844895219214,
+           -0.2919141435950403,
+           -0.3085818996421958,
+           -0.3307583174542209,
+           -0.3588839110519978,
+           -0.3932535178082415,
+           -0.4340041525810375,
+           -0.4811066974942174,
+           -0.5343616837583762,
+           -0.5933993207689106,
+           -0.6576838221504403,
+           -0.7265219710627424,
+           -0.7990757606146801,
+           -0.874378842306438,
+           -0.9513564186114439,
+           -1.0288481275462393,
+           -1.1056333895809973,
+           -1.1804586224752545,
+           -1.2520656792302438,
+           -1.319220829627151,
+           -1.3807435876794596,
+           -1.4355346862690301,
+           -1.4826025163398537,
+           -1.5210873809465941,
+           -1.550282963437176,
+           -1.5696544729313713,
+           -1.5788530075132432,
+           -1.5777257643237417,
+           -1.5663218238734844,
+           -1.5448933410132104,
+           -1.513892084543202,
+           -1.4739613787428454,
+           -1.4259236104402042,
+           -1.3707635719216822,
+           -1.309608010392163,
+           -1.2437018463767184,
+           -1.1743816041566282,
+           -1.1030466650741426,
+           -1.0311290076556667,
+           -0.9600621356839181,
+           -0.8912499156768923,
+           -0.8260360481985869,
+           -0.7656748829516441,
+           -0.7113042560307901,
+           -0.6639209798122555,
+           -0.6243595528817919,
+           -0.5932745806979312,
+           -0.5711273092162149,
+           -0.5581765756203335,
+           -0.5544743750079947,
+           -0.559866131928982,
+           -0.5739956537486213,
+           -0.5963146316365796,
+           -0.6260964472628684,
+           -0.6624539416371202,
+           -0.7043607094191906,
+           -0.7506753997126031,
+           -0.8001684348130896,
+           -0.851550503292959,
+           -0.9035021444710473,
+           -0.9547037186721572,
+           -1.0038650522319377,
+           -1.0497540580427374,
+           -1.0912236612276247,
+           -1.1272364045210037,
+           -1.1568861679763498,
+           -1.1794165111963362,
+           -1.1942352315399865,
+           -1.2009248265732324,
+           -1.199248651029277,
+           -1.189152665197863,
+           -1.170762780322215,
+           -1.1443779145599933,
+           -1.110458977693856,
+           -1.069614101480944,
+           -1.0225805228842537,
+           -0.9702036072206156,
+           -0.913413565545306,
+           -0.8532004737425427,
+           -0.7905882385299097,
+           -0.7266081770250487,
+           -0.6622728811841551,
+           -0.5985510262427767,
+           -0.5363437536289309,
+           -0.4764632144457437,
+           -0.4196138006957905,
+           -0.3663765194634725,
+           -0.31719688212928965,
+           -0.27237658848149504,
+           -0.23206918666030374,
+           -0.19627978672594731,
+           -0.16486880089416284,
+           -0.13755957977734654,
+           -0.1139497139226588,
+           -0.0935256760704607,
+           -0.07568039422984484,
+           -0.059733271027657915,
+           -0.04495210270706543,
+           -0.030576303187719648,
+           -0.01584080595161015,
+           -1.5495823325931208e-16
+          ],
+          [
+           0,
+           0.018135374489706722,
+           0.038935030524830036,
+           0.06289074328328245,
+           0.09038502905269537,
+           0.1216781637813837,
+           0.15689860142754053,
+           0.19603705942961186,
+           0.23894444322884578,
+           0.2853336818405288,
+           0.3347854445257024,
+           0.38675760724481745,
+           0.4405982393510796,
+           0.4955617883995275,
+           0.5508280563640925,
+           0.6055234861263252,
+           0.6587442147307027,
+           0.7095803011963217,
+           0.7571405028960243,
+           0.8005769565513038,
+           0.8391091182386125,
+           0.8720463315453649,
+           0.8988084238263006,
+           0.9189437766637535,
+           0.9321443770137815,
+           0.938257428650693,
+           0.9372931876096304,
+           0.9294287782973506,
+           0.9150078464952769,
+           0.8945360091471458,
+           0.8686721660287056,
+           0.8382158425173915,
+           0.8040908331152853,
+           0.7673255096141214,
+           0.7290302434606882,
+           0.6903724668255683,
+           0.6525499592009013,
+           0.6167629944651418,
+           0.5841860160153192,
+           0.5559395239207114,
+           0.5330628576387941,
+           0.5164885406114285,
+           0.5070188193986018,
+           0.5053049806878935,
+           0.5118299657074262,
+           0.5268947247957535,
+           0.5506086669937226,
+           0.5828844626479791,
+           0.6234373535057153,
+           0.6717890171549386,
+           0.7272759235487379,
+           0.7890620134111631,
+           0.8561554241966136,
+           0.9274288915142861,
+           1.0016433649311565,
+           1.077474299015916,
+           1.1535400153006528,
+           1.2284314801215854,
+           1.3007428083062582,
+           1.3691017842691344,
+           1.4321996907219188,
+           1.48881975094248,
+           1.5378635230027804,
+           1.5783746327468982,
+           1.6095592954611109,
+           1.6308031525530609,
+           1.6416840372970318,
+           1.6419803806702424,
+           1.6316750721383138,
+           1.6109546984175773,
+           1.5802041931132484,
+           1.5399970390318045,
+           1.49108127024478,
+           1.4343616200824918,
+           1.3708782517564333,
+           1.3017825880578657,
+           1.2283108236334677,
+           1.1517557560870624,
+           1.073437609342161,
+           0.9946745434507948,
+           0.9167535488812328,
+           0.8409024102089873,
+           0.7682633944365703,
+           0.6998692736497448,
+           0.6366222315417496,
+           0.5792761300202809,
+           0.5284225274944944,
+           0.48448074663474866,
+           0.44769218874267747,
+           0.41811898686364907,
+           0.3956469830201691,
+           0.37999290908306566,
+           0.37071554843916293,
+           0.36723055927875903,
+           0.36882855237776735,
+           0.3746959388387378,
+           0.3839379982665894,
+           0.3956035668604948,
+           0.4087107091233311,
+           0.4222727171637227,
+           0.4353237783308022,
+           0.4469436652045858,
+           0.45628083137958136,
+           0.46257334123885985,
+           0.4651671208516342,
+           0.4635310887191154,
+           0.45726880750729937,
+           0.44612638904052937,
+           0.4299964823706997,
+           0.4089182762120989,
+           0.3830735498749269,
+           0.35277890844496457,
+           0.31847443578102796,
+           0.2807090904726852,
+           0.24012325291562786,
+           0.1974289040359985,
+           0.15338797611297117,
+           0.10878946211069865,
+           0.06442590078897623,
+           0.02106986984996236,
+           -0.02054888187047403,
+           -0.05976504960105018,
+           -0.09599755484384404,
+           -0.12876696229748658,
+           -0.15771006095618045,
+           -0.18259121271089185,
+           -0.20331015587927556,
+           -0.2199060432958248,
+           -0.23255759256778247,
+           -0.2415793273633278,
+           -0.24741399058001046,
+           -0.2506213103567255,
+           -0.25186339559999127,
+           -0.25188712656160017,
+           -0.2515039857660688,
+           -0.25156784320546577,
+           -0.2529512654363102,
+           -0.25652095959053384,
+           -0.26311298927025834,
+           -0.2735084091405008,
+           -0.28840995847405376,
+           -0.30842043105926864,
+           -0.33402330028328886,
+           -0.36556612477537237,
+           -0.40324719303543605,
+           -0.4471057866214452,
+           -0.49701635266618405,
+           -0.5526867799325295,
+           -0.6136608706887112,
+           -0.6793249959222054,
+           -0.7489188164205136,
+           -0.8215498496482974,
+           -0.8962115647087701,
+           -0.9718045974409646,
+           -1.047160597143086,
+           -1.1210681475598565,
+           -1.1923001493773095,
+           -1.2596420109494224,
+           -1.321919969390847,
+           -1.378028856168744,
+           -1.426958630165772,
+           -1.4678190267007114,
+           -1.4998617126057432,
+           -1.5224993941938914,
+           -1.535321395454857,
+           -1.5381053063990933,
+           -1.5308243941335324,
+           -1.5136505697514693,
+           -1.4869528100102472,
+           -1.4512910414736446,
+           -1.407405603657778,
+           -1.3562025140790053,
+           -1.2987348593565486,
+           -1.2361807301898065,
+           -1.1698182018131935,
+           -1.100997933371223,
+           -1.0311140177871176,
+           -0.9615737566863354,
+           -0.8937670617199799,
+           -0.8290361935458864,
+           -0.7686465425138969,
+           -0.7137591309325112,
+           -0.6654054762480285,
+           -0.6244653985269122,
+           -0.5916482856563946,
+           -0.5674782473704048,
+           -0.5522834965719782,
+           -0.5461901957160752,
+           -0.54912089969163,
+           -0.560797617288439,
+           -0.5807494036154695,
+           -0.6083242884217079,
+           -0.6427052427696186,
+           -0.6829297914125595,
+           -0.7279127928351233,
+           -0.7764718352929797,
+           -0.8273546371084304,
+           -0.8792677943777899,
+           -0.9309061901946699,
+           -0.9809823671622037,
+           -1.0282551696178215,
+           -1.0715569834696008,
+           -1.1098189392734064,
+           -1.142093497195518,
+           -1.1675738994633267,
+           -1.1856100551224302,
+           -1.1957205114092866,
+           -1.1976002635826544,
+           -1.1911242582080948,
+           -1.176346551098936,
+           -1.1534951877548492,
+           -1.1229629785716633,
+           -1.0852944407497989,
+           -1.0411692712545175,
+           -0.9913827981144439,
+           -0.9368239287616681,
+           -0.8784511722838179,
+           -0.8172673559752975,
+           -0.7542936844085748,
+           -0.6905438007565243,
+           -0.6269985050505564,
+           -0.5645817626371209,
+           -0.5041385988854998,
+           -0.44641542418346225,
+           -0.39204326778318965,
+           -0.34152432181024356,
+           -0.29522210969671253,
+           -0.25335549866115464,
+           -0.2159966760336944,
+           -0.18307310674157867,
+           -0.15437338671800058,
+           -0.12955680696232671,
+           -0.10816634798326441,
+           -0.0896447367882491,
+           -0.07335312064310995,
+           -0.05859184547209271,
+           -0.044622773662226015,
+           -0.030692537505876784,
+           -0.016056101521166266,
+           -1.5830222531772738e-16
+          ],
+          [
+           0,
+           0.01867916782778503,
+           0.04020770864736438,
+           0.06501398826521841,
+           0.0934121108711045,
+           0.1255910149718665,
+           0.1616070597627318,
+           0.2013803111441625,
+           0.24469464024095303,
+           0.29120164790208375,
+           0.3404283287744678,
+           0.3917882906852331,
+           0.4445962517206399,
+           0.4980854509288857,
+           0.5514275312017274,
+           0.6037543865827156,
+           0.6541814127086047,
+           0.7018315596972392,
+           0.7458595625782565,
+           0.7854757159710357,
+           0.8199685673997593,
+           0.8487259272475147,
+           0.871253632339484,
+           0.8871915535724174,
+           0.8963264045730538,
+           0.8986009864397821,
+           0.8941195912759903,
+           0.8831493822931336,
+           0.8661176683892725,
+           0.8436050938060482,
+           0.8163348661754198,
+           0.785158246422556,
+           0.7510366190864681,
+           0.7150205492687688,
+           0.6782263104169832,
+           0.6418104335199749,
+           0.6069428813522134,
+           0.5747794897895346,
+           0.5464343409318256,
+           0.5229527391937469,
+           0.5052854514512849,
+           0.4942648459555735,
+           0.49058352264544697,
+           0.49477597069547846,
+           0.507203718980854,
+           0.5280443633109032,
+           0.5572847627570005,
+           0.5947185983980738,
+           0.6399483837363099,
+           0.6923919094338793,
+           0.7512929984919092,
+           0.8157363441411346,
+           0.8846661040829399,
+           0.95690783372857,
+           1.0311932599670683,
+           1.1061873277432785,
+           1.180516896051191,
+           1.2528004192190023,
+           1.3216779245892003,
+           1.3858405894980956,
+           1.4440592290475476,
+           1.4952110313383744,
+           1.5383039179961473,
+           1.5724979639690553,
+           1.5971233803515663,
+           1.6116946456897336,
+           1.615920462865812,
+           1.6097093180098667,
+           1.5931705225248454,
+           1.5666107266914264,
+           1.5305260008261756,
+           1.4855896849862922,
+           1.4326363081943847,
+           1.372641970671008,
+           1.3067016653699661,
+           1.2360040862109767,
+           1.1618045280847078,
+           1.085396526586648,
+           1.0080829125031743,
+           0.931146966700717,
+           0.8558243550355663,
+           0.7832765003970511,
+           0.7145660106135532,
+           0.6506347276719288,
+           0.5922848968740917,
+           0.5401638758578461,
+           0.49475271481037225,
+           0.456358842909406,
+           0.4251129944320375,
+           0.400970403592552,
+           0.38371619259067374,
+           0.3729747751509327,
+           0.3682230005290346,
+           0.36880667294151914,
+           0.3739600008442041,
+           0.38282746140614915,
+           0.3944875095737553,
+           0.407977519638962,
+           0.4223193211984806,
+           0.4365446814132411,
+           0.44972009174357885,
+           0.46097023963608386,
+           0.469499583362995,
+           0.47461150037193156,
+           0.475724544741525,
+           0.4723854259822211,
+           0.4642784075143224,
+           0.45123091650786884,
+           0.4332152550139786,
+           0.4103464029692905,
+           0.38287600417254497,
+           0.3511827241806951,
+           0.31575926178789976,
+           0.27719638100300337,
+           0.23616440608908112,
+           0.19339268637542187,
+           0.14964758859262686,
+           0.10570961114079536,
+           0.06235023606791833,
+           0.020309140084750977,
+           -0.019727624453563988,
+           -0.05714789373541746,
+           -0.09143155805466037,
+           -0.12216613997371464,
+           -0.149059363894031,
+           -0.17194837426047746,
+           -0.19080534689986609,
+           -0.20573933190884336,
+           -0.21699426468277813,
+           -0.2249431816264672,
+           -0.23007877627468995,
+           -0.233000527458351,
+           -0.23439872134315642,
+           -0.23503577134694634,
+           -0.2357253120125682,
+           -0.23730960303111442,
+           -0.24063582622911886,
+           -0.24653189024393024,
+           -0.2557823739726523,
+           -0.26910524023990723,
+           -0.28712993543708776,
+           -0.3103774594925022,
+           -0.33924294418390566,
+           -0.3739812176247006,
+           -0.4146957602135119,
+           -0.46133137421735454,
+           -0.5136707975129505,
+           -0.571335394108053,
+           -0.6337899523355909,
+           -0.7003515185892925,
+           -0.7702020927196069,
+           -0.8424049132767012,
+           -0.9159239691272293,
+           -0.9896462908871503,
+           -1.062406503199854,
+           -1.133013058982533,
+           -1.2002755308935291,
+           -1.2630323046228356,
+           -1.3201780039873379,
+           -1.3706899796355676,
+           -1.4136532114419342,
+           -1.4482830089986531,
+           -1.4739449441984744,
+           -1.4901715135677718,
+           -1.4966751042324231,
+           -1.4933569243408222,
+           -1.4803116543236854,
+           -1.4578276772178587,
+           -1.4263828519407358,
+           -1.3866359002951507,
+           -1.339413583999053,
+           -1.2856939495875408,
+           -1.226586014138377,
+           -1.163306351092003,
+           -1.0971531108532588,
+           -1.0294780735182796,
+           -0.9616573794228187,
+           -0.8950616160617716,
+           -0.8310259564683415,
+           -0.7708210439480456,
+           -0.7156253011302732,
+           -0.6664993080311092,
+           -0.6243628450183978,
+           -0.5899751334169492,
+           -0.5639187305227252,
+           -0.5465874488584332,
+           -0.5381785737155332,
+           -0.5386895507218418,
+           -0.5479192088410068,
+           -0.5654734764388156,
+           -0.5907754414638615,
+           -0.6230795039780274,
+           -0.6614892727324577,
+           -0.7049787695580524,
+           -0.7524164281534426,
+           -0.8025913092698588,
+           -0.8542409038613576,
+           -0.9060798606922399,
+           -0.9568289559935462,
+           -1.005243620461951,
+           -1.0501413532129726,
+           -1.0904273828438902,
+           -1.1251179817396846,
+           -1.153360899998487,
+           -1.17445245834424,
+           -1.1878509233045118,
+           -1.1931858806666369,
+           -1.190263422478504,
+           -1.1790670661676752,
+           -1.1597544291564237,
+           -1.132649786061068,
+           -1.0982327356251367,
+           -1.0571232984868597,
+           -1.0100638524186998,
+           -0.9578983867101399,
+           -0.9015496200703051,
+           -0.8419945752898541,
+           -0.7802392377547547,
+           -0.7172929429568584,
+           -0.654143140001288,
+           -0.5917311637760282,
+           -0.530929618336097,
+           -0.4725219289668439,
+           -0.41718456150380245,
+           -0.3654723363179385,
+           -0.3178071827467601,
+           -0.2744705897431846,
+           -0.2355999124107504,
+           -0.2011885943297261,
+           -0.17109026467544447,
+           -0.14502656963362123,
+           -0.12259850203432855,
+           -0.10330090386153674,
+           -0.08653973559163744,
+           -0.07165163619714017,
+           -0.057925239877495024,
+           -0.04462367159202038,
+           -0.03100761436653307,
+           -0.0163583278462201,
+           -1.6232471968196038e-16
+          ],
+          [
+           0,
+           0.01926687663500131,
+           0.04153437932811081,
+           0.0671658392724598,
+           0.0964065783667572,
+           0.1293751015385808,
+           0.16605783426697343,
+           0.2063075567557188,
+           0.24984558982734903,
+           0.29626768968369693,
+           0.3450535116957801,
+           0.39557940980605405,
+           0.4471342503279553,
+           0.4989378391460945,
+           0.5501614915909147,
+           0.5999502163688739,
+           0.647445940362501,
+           0.6918111710301712,
+           0.7322524783269214,
+           0.768043178946321,
+           0.798544622267269,
+           0.8232255093023972,
+           0.8416787224251053,
+           0.8536352035720991,
+           0.8589744905106313,
+           0.8577316028548141,
+           0.8501000597846267,
+           0.8364309076273416,
+           0.8172277352133919,
+           0.7931377557329142,
+           0.7649391331789316,
+           0.7335248268825428,
+           0.6998833167313531,
+           0.6650766521734688,
+           0.6302163380130593,
+           0.5964376275254625,
+           0.5648728370900958,
+           0.5366243252277663,
+           0.5127377918746082,
+           0.4941765505552873,
+           0.48179740685910105,
+           0.47632874169821887,
+           0.47835134804975415,
+           0.488282506433777,
+           0.5063637087786244,
+           0.5326523543969129,
+           0.5670176476224138,
+           0.6091408265284478,
+           0.6585197485024109,
+           0.7144777538188556,
+           0.7761766252938639,
+           0.8426333631402897,
+           0.9127404017034894,
+           0.9852888111104064,
+           1.0589939540680222,
+           1.1325230078931243,
+           1.2045237158286783,
+           1.2736537009423776,
+           1.3386096611764935,
+           1.3981557657988049,
+           1.451150591564584,
+           1.4965719709099794,
+           1.5335391736385047,
+           1.5613319066437683,
+           1.57940569170166,
+           1.5874032674280978,
+           1.5851617560399667,
+           1.572715436275719,
+           1.550294068276298,
+           1.5183168218547836,
+           1.4773819638247268,
+           1.4282525603786633,
+           1.371838544473773,
+           1.3091755835128516,
+           1.2414012572413136,
+           1.1697291179148688,
+           1.0954212529362641,
+           1.0197600031669165,
+           0.944019507216386,
+           0.8694377428182086,
+           0.7971897209327125,
+           0.7283624568951576,
+           0.6639322965580087,
+           0.6047451151354534,
+           0.5514998338618683,
+           0.5047356164398943,
+           0.4648230156509674,
+           0.4319592427082643,
+           0.40616763037416914,
+           0.3873012580540015,
+           0.375050605553073,
+           0.3689550044457724,
+           0.368417564454752,
+           0.37272316911818465,
+           0.3810590623622969,
+           0.39253748715982123,
+           0.40621979070019254,
+           0.42114137853866856,
+           0.43633688377336177,
+           0.4508649167775168,
+           0.4638317763489127,
+           0.4744135338939328,
+           0.4818759476218985,
+           0.48559172250481036,
+           0.48505470244490195,
+           0.4798906618794378,
+           0.4698644528820048,
+           0.45488335843803246,
+           0.4349966005843917,
+           0.41039105103294815,
+           0.3813832892513291,
+           0.3484082462996975,
+           0.3120047596737653,
+           0.27279844279849813,
+           0.23148234068880355,
+           0.18879589894437632,
+           0.14550281528663303,
+           0.1023683702304564,
+           0.06013684553648103,
+           0.019509635521232162,
+           -0.018875362783494967,
+           -0.05446252873927519,
+           -0.08679496285357097,
+           -0.11552815473120563,
+           -0.14044050432520455,
+           -0.16144040865781625,
+           -0.17856971569668803,
+           -0.19200344175971804,
+           -0.20204574628440536,
+           -0.20912225556180947,
+           -0.21376892262067088,
+           -0.21661770142595022,
+           -0.2183793976141608,
+           -0.21982413298345208,
+           -0.22175992497325842,
+           -0.22500993376434716,
+           -0.23038896707831286,
+           -0.23867985527794167,
+           -0.2506103163618921,
+           -0.26683092169361,
+           -0.28789474898481565,
+           -0.31423926973891936,
+           -0.3461709649968996,
+           -0.3838530971191123,
+           -0.4272969881044785,
+           -0.47635706849867665,
+           -0.5307298674149973,
+           -0.5899570159064362,
+           -0.6534322353306717,
+           -0.7204121819488004,
+           -0.7900309213030514,
+           -0.8613177133753934,
+           -0.9332177044624062,
+           -1.0046150462557288,
+           -1.0743578987011893,
+           -1.1412847224505478,
+           -1.20425123042233,
+           -1.2621573471002043,
+           -1.3139735192880715,
+           -1.358765733283915,
+           -1.3957186206042094,
+           -1.4241560768671555,
+           -1.443558875226666,
+           -1.4535788254846875,
+           -1.4540491110193612,
+           -1.444990525992106,
+           -1.426613432745379,
+           -1.3993153615031892,
+           -1.3636742789455256,
+           -1.320437656393435,
+           -1.2705075696641883,
+           -1.2149221586529015,
+           -1.1548338630125572,
+           -1.091484928768216,
+           -1.0261807473831386,
+           -0.9602616420499305,
+           -0.8950737544933789,
+           -0.8319397083866669,
+           -0.772129732027798,
+           -0.7168339130244994,
+           -0.6671362316226411,
+           -0.623990977611599,
+           -0.5882020994581687,
+           -0.5604059648239695,
+           -0.5410579305984735,
+           -0.5304230300020876,
+           -0.5285709863856008,
+           -0.5353756604576861,
+           -0.5505189323157158,
+           -0.5734989144005536,
+           -0.6036422889028393,
+           -0.640120465709259,
+           -0.6819691670567853,
+           -0.7281109648388101,
+           -0.7773802279176387,
+           -0.8285498814938919,
+           -0.880359339887586,
+           -0.9315429489613922,
+           -0.9808582654428242,
+           -1.0271135077612426,
+           -1.0691935364880338,
+           -1.1060837614392207,
+           -1.1368914259743845,
+           -1.160863785653839,
+           -1.1774027765269446,
+           -1.186075855967373,
+           -1.1866227939645886,
+           -1.1789582927666915,
+           -1.163170415271339,
+           -1.139514905045804,
+           -1.1084055807969027,
+           -1.070401083048017,
+           -1.0261883383843426,
+           -0.9765631847565343,
+           -0.9224086680841957,
+           -0.8646715741581875,
+           -0.8043377993145036,
+           -0.7424071876102502,
+           -0.6798684707222674,
+           -0.6176749393529843,
+           -0.5567214518044672,
+           -0.49782334719945587,
+           -0.44169777859045045,
+           -0.38894791625614716,
+           -0.3400503955048924,
+           -0.29534629822591824,
+           -0.25503586541325096,
+           -0.21917704126621407,
+           -0.18768785068743563,
+           -0.16035251354722035,
+           -0.13683110344257338,
+           -0.11667246825640212,
+           -0.09933004688926136,
+           -0.08418014317305127,
+           -0.07054215602091299,
+           -0.05770021586897881,
+           -0.04492564264482742,
+           -0.03149962071803999,
+           -0.01673548203439063,
+           -1.6690610814058328e-16
+          ],
+          [
+           0,
+           0.01988490159520388,
+           0.04288748700558034,
+           0.06930515552255116,
+           0.09931479881186693,
+           0.13296608647221622,
+           0.17017831637721803,
+           0.21074092443314127,
+           0.2543176528705318,
+           0.3004542805688205,
+           0.3485897256159248,
+           0.3980702416999431,
+           0.4481663482711272,
+           0.4980920617804017,
+           0.5470259335516988,
+           0.594133350563425,
+           0.6385895198719883,
+           0.6796025365361857,
+           0.7164359292567241,
+           0.7484300877098075,
+           0.7750220005204689,
+           0.7957627724011584,
+           0.8103324422173493,
+           0.81855168933384,
+           0.8203900919300223,
+           0.8159706861646095,
+           0.8055706670093912,
+           0.7896181679737864,
+           0.7686851554068606,
+           0.7434765711340672,
+           0.7148159524094707,
+           0.6836278481533327,
+           0.6509174329374396,
+           0.6177477930954209,
+           0.5852154208254926,
+           0.5544245006505536,
+           0.5264606068573311,
+           0.5023644496541662,
+           0.48310631124183845,
+           0.46956180064609837,
+           0.4624895282679321,
+           0.46251125830693124,
+           0.47009504051333073,
+           0.48554175347983075,
+           0.5089754115621177,
+           0.5403374984557707,
+           0.5793854946197309,
+           0.6256956654564862,
+           0.6786700748838606,
+           0.7375476871632787,
+           0.8014193210766708,
+           0.8692461271910052,
+           0.9398811733080977,
+           1.0120936473740472,
+           1.0845951229849218,
+           1.1560672817562314,
+           1.2251904504824003,
+           1.2906722901030165,
+           1.351275968541689,
+           1.4058471606266905,
+           1.4533392452821345,
+           1.4928361123475296,
+           1.5235720477242287,
+           1.5449482346932721,
+           1.5565454895214177,
+           1.5581329389187217,
+           1.5496724433557518,
+           1.5313186713443494,
+           1.5034148330725452,
+           1.4664841847491623,
+           1.4212175151532322,
+           1.3684569207649409,
+           1.3091762631764068,
+           1.2444587801272837,
+           1.1754723876062132,
+           1.1034432634139937,
+           1.0296283411311706,
+           0.9552873666603722,
+           0.8816551768869834,
+           0.8099148513767692,
+           0.7411723636535335,
+           0.6764333191093752,
+           0.6165823129996575,
+           0.5623653756149782,
+           0.5143758942655404,
+           0.4730443150909686,
+           0.43863183407512657,
+           0.41122818832302466,
+           0.3907535580787703,
+           0.37696448961329226,
+           0.36946365146088084,
+           0.3677131439347955,
+           0.3710509966730909,
+           0.3787104132376195,
+           0.3898412573542457,
+           0.4035332237987454,
+           0.41884009943644873,
+           0.4348044973974146,
+           0.45048244032196627,
+           0.46496717716670044,
+           0.47741164195302493,
+           0.4870490014219565,
+           0.49321079081846486,
+           0.4953422016155089,
+           0.49301416024630434,
+           0.4859319209245085,
+           0.4739399862619962,
+           0.4570232643474261,
+           0.43530446782641874,
+           0.40903785688253824,
+           0.37859952143121967,
+           0.3444744859576742,
+           0.3072410010425889,
+           0.2675524567054374,
+           0.22611741247582615,
+           0.18367828608600073,
+           0.14098927569354985,
+           0.09879410877571089,
+           0.0578042138417768,
+           0.018677898827546138,
+           -0.017998907209778904,
+           -0.05172983398492793,
+           -0.08212271106326083,
+           -0.10890127623898464,
+           -0.1319136339627151,
+           -0.15113723137749277,
+           -0.16668021035401748,
+           -0.17877908846637303,
+           -0.18779281772076284,
+           -0.1941933646091598,
+           -0.19855304630121434,
+           -0.20152894319196724,
+           -0.20384478541566628,
+           -0.20627077834259772,
+           -0.20960188777081323,
+           -0.21463514807519474,
+           -0.2221465848782822,
+           -0.23286835711332932,
+           -0.24746672128841984,
+           -0.2665214033450129,
+           -0.29050693113413145,
+           -0.3197764339838388,
+           -0.35454835623483394,
+           -0.39489646043833576,
+           -0.4407434148963448,
+           -0.49185817138303944,
+           -0.5478572444215931,
+           -0.6082099057523525,
+           -0.6722472090526094,
+           -0.7391746630175184,
+           -0.8080882780137217,
+           -0.8779936250040381,
+           -0.9478274674915353,
+           -1.0164814598146936,
+           -1.0828273499550325,
+           -1.145743083506912,
+           -1.2041391786831397,
+           -1.2569847309022533,
+           -1.3033324099565873,
+           -1.3423418329357986,
+           -1.3733007315310528,
+           -1.3956433822440286,
+           -1.408965831187182,
+           -1.4130375200718583,
+           -1.4078090048304395,
+           -1.3934155510509088,
+           -1.3701764887615635,
+           -1.3385903106923993,
+           -1.2993256004762086,
+           -1.2532079778328655,
+           -1.2012033441396672,
+           -1.144397801564459,
+           -1.0839746999206825,
+           -1.0211893356009532,
+           -0.9573418846283112,
+           -0.893749195605596,
+           -0.8317160970592606,
+           -0.7725068866461017,
+           -0.7173176665879681,
+           -0.6672501705818037,
+           -0.6232876927539492,
+           -0.5862736798235096,
+           -0.5568934847055454,
+           -0.5356597048482331,
+           -0.5229014434799172,
+           -0.5187577387128339,
+           -0.5231753063786475,
+           -0.5359106399678962,
+           -0.5565364076051271,
+           -0.5844519841298137,
+           -0.6188978585456977,
+           -0.6589735657227533,
+           -0.7036587085017578,
+           -0.7518365642628823,
+           -0.8023197103153172,
+           -0.8538770565778796,
+           -0.9052616430428679,
+           -0.955238544172896,
+           -1.00261222301319,
+           -1.0462526943580739,
+           -1.0851198883467736,
+           -1.1182856525575293,
+           -1.144952890838812,
+           -1.1644714092507715,
+           -1.1763501217867556,
+           -1.180265358954095,
+           -1.1760651185703168,
+           -1.163769197890433,
+           -1.1435652469566628,
+           -1.1158008823682943,
+           -1.080972096062156,
+           -1.0397082828316337,
+           -0.9927542910124793,
+           -0.9409499710591392,
+           -0.8852077549202556,
+           -0.8264888437953637,
+           -0.7657786119538931,
+           -0.7040618491241386,
+           -0.6422984631970167,
+           -0.581400248708834,
+           -0.522209295226544,
+           -0.4654785641902401,
+           -0.411855104155936,
+           -0.3618663042348057,
+           -0.3159095056360126,
+           -0.2742452036217823,
+           -0.23699397909703343,
+           -0.20413720283638642,
+           -0.1755214584277637,
+           -0.15086653482651227,
+           -0.12977674836181805,
+           -0.11175526940569015,
+           -0.09622105282698575,
+           -0.08252790571436475,
+           -0.06998517230337929,
+           -0.057879475919043286,
+           -0.04549693204201283,
+           -0.032145235956190385,
+           -0.017175033090988966,
+           -1.7192358596351521e-16
+          ],
+          [
+           0,
+           0.0205196475375368,
+           0.0442398674124924,
+           0.07139194693761128,
+           0.10208539765019486,
+           0.13630330945136324,
+           0.17390125499857767,
+           0.214609783655277,
+           0.2580404505103504,
+           0.3036952334629602,
+           0.3509791024744981,
+           0.39921542207906485,
+           0.4476637932302977,
+           0.4955398754597021,
+           0.5420366767964185,
+           0.5863467583276714,
+           0.627684773715901,
+           0.6653097521349104,
+           0.6985465362765654,
+           0.7268058052676709,
+           0.749602145102766,
+           0.7665696757553359,
+           0.7774748033425524,
+           0.7822257361329418,
+           0.7808784830646316,
+           0.7736391408059696,
+           0.7608623680706966,
+           0.743046041589553,
+           0.7208221844518286,
+           0.6949443520559957,
+           0.6662717512792943,
+           0.6357504524214068,
+           0.6043921288815315,
+           0.573250824483241,
+           0.5433983012154765,
+           0.5158985595552062,
+           0.4917821484539644,
+           0.4720208918393371,
+           0.4575036528107955,
+           0.44901373568620034,
+           0.44720849015034064,
+           0.4526016318088827,
+           0.4655487306478875,
+           0.48623624474869054,
+           0.5146743929015771,
+           0.5506940685299768,
+           0.5939479007998081,
+           0.6439154693009916,
+           0.6999125786816247,
+           0.7611044015384311,
+           0.8265222041247362,
+           0.89508328233154,
+           0.9656136570703147,
+           1.036873010567562,
+           1.1075812898397652,
+           1.1764463621203483,
+           1.242192080288964,
+           1.3035861050779138,
+           1.3594668352927908,
+           1.4087688173909416,
+           1.450546041035556,
+           1.4839925768361943,
+           1.5084600751994532,
+           1.523471719524738,
+           1.5287323110850195,
+           1.524134254785847,
+           1.5097593123634756,
+           1.4858760900957741,
+           1.4529333293124538,
+           1.4115491674428264,
+           1.3624966326130539,
+           1.3066857235876106,
+           1.2451425069894728,
+           1.178985733291589,
+           1.1094015303711549,
+           1.0376167770829223,
+           0.9648717882987663,
+           0.8923929565002579,
+           0.8213659929979398,
+           0.7529103942701068,
+           0.6880557262306748,
+           0.6277202722871715,
+           0.5726925310213142,
+           0.5236159777212469,
+           0.4809774226036914,
+           0.44509920941037995,
+           0.41613540335838795,
+           0.3940720195123923,
+           0.3787312439469694,
+           0.36977950301141305,
+           0.366739142984993,
+           0.3690033956988958,
+           0.37585422742283453,
+           0.3864826003764362,
+           0.4000106202744984,
+           0.41551500069648195,
+           0.4320512467958918,
+           0.44867794758753315,
+           0.4644805680490885,
+           0.4785941494464478,
+           0.4902243581607934,
+           0.49866636901572425,
+           0.503321127487228,
+           0.5037086047275451,
+           0.49947773826954367,
+           0.4904128375940795,
+           0.4764363252512368,
+           0.45760777861406154,
+           0.43411933222904325,
+           0.4062875937218398,
+           0.3745423149814001,
+           0.3394121426524534,
+           0.3015078457524209,
+           0.26150348164804116,
+           0.22011601309616624,
+           0.17808392729111472,
+           0.136145431920824,
+           0.09501681252617586,
+           0.05537152976509896,
+           0.017820614665245687,
+           -0.017105114860639033,
+           -0.04897054117119783,
+           -0.07744902303710355,
+           -0.10233211708866129,
+           -0.12353598073245152,
+           -0.14110427934067285,
+           -0.1552075117625525,
+           -0.1661387617423124,
+           -0.1743059762794228,
+           -0.18022096296185658,
+           -0.18448538452983396,
+           -0.1877741081925193,
+           -0.19081633750320967,
+           -0.19437501410375793,
+           -0.1992250238496315,
+           -0.20613077550434056,
+           -0.21582373946560474,
+           -0.22898053833620252,
+           -0.2462021704347768,
+           -0.2679949217891185,
+           -0.2947534823724973,
+           -0.32674672929657694,
+           -0.36410657466080026,
+           -0.4068202003787659,
+           -0.4547259184207111,
+           -0.5075128046081033,
+           -0.564724159616823,
+           -0.6257647545438527,
+           -0.6899117226741377,
+           -0.7563288663450571,
+           -0.8240840603727927,
+           -0.8921693535778327,
+           -0.9595232995439691,
+           -1.0250549886521219,
+           -1.0876692071556526,
+           -1.1462921168009599,
+           -1.1998968310946347,
+           -1.2475282622572164,
+           -1.288326626286519,
+           -1.3215490220999937,
+           -1.3465885437797247,
+           -1.362990441488868,
+           -1.3704649153127197,
+           -1.3688962054463438,
+           -1.3583477298869844,
+           -1.3390631149616066,
+           -1.3114630623331853,
+           -1.276138096183331,
+           -1.2338373336156574,
+           -1.18545351753,
+           -1.1320046419210443,
+           -1.0746125825273405,
+           -1.014479218955949,
+           -0.952860596028873,
+           -0.891039720617921,
+           -0.8302986244508758,
+           -0.7718903424313108,
+           -0.7170114594338294,
+           -0.6667758662167727,
+           -0.6221903373214007,
+           -0.5841325012647857,
+           -0.5533317170103486,
+           -0.5303533019795267,
+           -0.5155864774187321,
+           -0.5092363086883229,
+           -0.5113198231412699,
+           -0.5216663890172077,
+           -0.5399223376070953,
+           -0.5655597103056036,
+           -0.5978889145091613,
+           -0.6360749800093918,
+           -0.6791570228140138,
+           -0.7260704482517959,
+           -0.7756713615984057,
+           -0.826762603826991,
+           -0.8781207936521728,
+           -0.9285237356597644,
+           -0.9767775484882443,
+           -1.021742876859898,
+           -1.062359576473916,
+           -1.0976693007169376,
+           -1.1268354718045026,
+           -1.1491601849900617,
+           -1.1640976712149482,
+           -1.1712640291116103,
+           -1.1704430294881458,
+           -1.1615878920297764,
+           -1.144819032563703,
+           -1.1204178774144717,
+           -1.0888169367106482,
+           -1.050586418648462,
+           -1.0064177494663191,
+           -0.9571044372155553,
+           -0.903520779545518,
+           -0.8465989651541864,
+           -0.7873051541071195,
+           -0.726615143062567,
+           -0.6654902270915652,
+           -0.6048538601599277,
+           -0.5455696917355232,
+           -0.4884215180624534,
+           -0.43409563442279603,
+           -0.3831660105346984,
+           -0.33608263675633765,
+           -0.29316330587635364,
+           -0.2545890060767916,
+           -0.22040300741195798,
+           -0.19051362921050333,
+           -0.16470058157141362,
+           -0.1426246829586062,
+           -0.12384067009375962,
+           -0.10781273805523862,
+           -0.09393237967312022,
+           -0.08153803568638852,
+           -0.06993602213500412,
+           -0.05842217021430579,
+           -0.04630359709262275,
+           -0.03292002438976147,
+           -0.017664074162932256,
+           -1.772526015267408e-16
+          ],
+          [
+           0,
+           0.021157677189232595,
+           0.04556504661763603,
+           0.07338780218404542,
+           0.10466979191834905,
+           0.13933039543394635,
+           0.17716540439681472,
+           0.21785139199772816,
+           0.2609534661525056,
+           0.3059362124749986,
+           0.35217754922227795,
+           0.3989851395342598,
+           0.4456149383401748,
+           0.4912913940181636,
+           0.5352287797415652,
+           0.5766530975921734,
+           0.6148239807997483,
+           0.6490560163570656,
+           0.6787389218727728,
+           0.7033560366026832,
+           0.7225006265224709,
+           0.7358895561011852,
+           0.7433739438109261,
+           0.7449464927761733,
+           0.7407452704857664,
+           0.7310538001129585,
+           0.7162974185086409,
+           0.6970359500423159,
+           0.6739528388121696,
+           0.6478409719913171,
+           0.6195855119555922,
+           0.590144132211551,
+           0.5605251200562248,
+           0.5317638656280509,
+           0.5048983011014646,
+           0.4809438840961314,
+           0.4608687351162809,
+           0.4455695395659046,
+           0.4358488105333147,
+           0.4323940794088082,
+           0.43575953816370905,
+           0.44635060080013117,
+           0.4644117834264051,
+           0.4900182242640216,
+           0.5230710785415047,
+           0.5632969307783338,
+           0.6102512706617947,
+           0.6633259809243762,
+           0.7217606887328634,
+           0.7846577384784337,
+           0.851000455808745,
+           0.9196742924338375,
+           0.9894903706458279,
+           1.059210887360342,
+           1.1275757912784887,
+           1.1933301146296056,
+           1.2552513236907685,
+           1.3121760503288735,
+           1.3630255802397464,
+           1.4068295020540562,
+           1.442746964360631,
+           1.4700850439297235,
+           1.4883137966409585,
+           1.497077641177371,
+           1.4962028125299704,
+           1.4857007156515951,
+           1.4657671069354214,
+           1.4367771302047252,
+           1.399276332178506,
+           1.3539678775334774,
+           1.301696273405654,
+           1.2434279952875904,
+           1.180229478791846,
+           1.113243002915636,
+           1.0436610387839849,
+           0.9726996722130424,
+           0.9015717280092506,
+           0.8314602282559419,
+           0.7634928058622608,
+           0.6987176686628538,
+           0.6380816690301078,
+           0.5824109803157482,
+           0.5323948158220653,
+           0.4885725500538766,
+           0.45132451761098674,
+           0.4208666743413928,
+           0.39724921053470974,
+           0.38035910933612804,
+           0.3699265475853676,
+           0.36553494329351743,
+           0.366634366245607,
+           0.37255794790515473,
+           0.3825408558575745,
+           0.3957413381844398,
+           0.41126329585381627,
+           0.42817980757242985,
+           0.44555701236116557,
+           0.4624777508131104,
+           0.4780643766293242,
+           0.4915001752862565,
+           0.5020488658915634,
+           0.5090717144076222,
+           0.5120418501198966,
+           0.5105554508705249,
+           0.5043395442909867,
+           0.4932562599787349,
+           0.4773034590526494,
+           0.45661176048221586,
+           0.43143807567392706,
+           0.40215585170010354,
+           0.3692423070383581,
+           0.3332630196619462,
+           0.29485429388158735,
+           0.2547037878262444,
+           0.21352992648240351,
+           0.17206065472177684,
+           0.1310121000105495,
+           0.09106771514257188,
+           0.05285845737588851,
+           0.01694453214585934,
+           -0.016200812193472986,
+           -0.04620500631743662,
+           -0.07280703152221706,
+           -0.09586514855774145,
+           -0.11536127345543319,
+           -0.13140187768592576,
+           -0.144215380767117,
+           -0.15414609512821265,
+           -0.16164487329339017,
+           -0.16725669398694187,
+           -0.17160550438006217,
+           -0.1753767083451251,
+           -0.17929775340271317,
+           -0.18411732043171236,
+           -0.19058365884142603,
+           -0.19942263477431454,
+           -0.2113160703607127,
+           -0.2268809477864075,
+           -0.24665003303326383,
+           -0.27105444105301546,
+           -0.300408617632939,
+           -0.33489815444519194,
+           -0.37457078418451223,
+           -0.4193308240111619,
+           -0.4689372496781256,
+           -0.5230054918673852,
+           -0.5810129526531833,
+           -0.6423081459877126,
+           -0.7061232740195982,
+           -0.7715899632172663,
+           -0.8377578028867428,
+           -0.9036152557995838,
+           -0.9681124481272214,
+           -1.0301852953052566,
+           -1.0887803831240113,
+           -1.1428800002325537,
+           -1.1915267099746065,
+           -1.2338468563007443,
+           -1.269072420304079,
+           -1.2965606802159582,
+           -1.315811177624599,
+           -1.3264795550542523,
+           -1.3283879033665744,
+           -1.321531339946734,
+           -1.306080628311875,
+           -1.2823807444455462,
+           -1.2509453925078504,
+           -1.2124475702169288,
+           -1.167706379750386,
+           -1.1176703711312266,
+           -1.0633977895021545,
+           -1.0060341733766502,
+           -0.94678781601901,
+           -0.8869036549403033,
+           -0.8276361937942728,
+           -0.7702220857369101,
+           -0.7158530169529796,
+           -0.6656495232983332,
+           -0.6206363519829707,
+           -0.5817199444245328,
+           -0.5496685666955418,
+           -0.5250955515716721,
+           -0.5084460425756073,
+           -0.4999875473890412,
+           -0.49980451759186,
+           -0.5077970760814088,
+           -0.5236839150514458,
+           -0.5470092884650235,
+           -0.5771539259439148,
+           -0.6133496022766048,
+           -0.6546970105679617,
+           -0.7001865095056591,
+           -0.7487212481770219,
+           -0.7991421169520064,
+           -0.8502539314715245,
+           -0.9008522297325308,
+           -0.9497500502738636,
+           -0.9958040628021169,
+           -1.0379394411397866,
+           -1.0751729016412115,
+           -1.106633377356721,
+           -1.1315798580440712,
+           -1.1494159971311864,
+           -1.1597011671549542,
+           -1.162157733039331,
+           -1.1566744056546885,
+           -1.14330563411733,
+           -1.1222670918738338,
+           -1.0939274063904474,
+           -1.0587963729045873,
+           -1.0175099769719291,
+           -0.9708126263995667,
+           -0.9195370587468923,
+           -0.8645824443136537,
+           -0.8068912451283479,
+           -0.7474254169385668,
+           -0.6871425529788483,
+           -0.6269725651086833,
+           -0.5677954799038193,
+           -0.5104208949465903,
+           -0.4555695947497665,
+           -0.4038577676516896,
+           -0.3557841961300857,
+           -0.3117207150559162,
+           -0.27190614742709657,
+           -0.23644383723732498,
+           -0.20530280661845762,
+           -0.1783224715782794,
+           -0.1552207598749981,
+           -0.13560538810610365,
+           -0.11898797511110283,
+           -0.10480059729789888,
+           -0.09241433028802025,
+           -0.08115927186281172,
+           -0.07034550480902897,
+           -0.059284435807022286,
+           -0.04730993852561039,
+           -0.03379873576795571,
+           -0.018189476666292684,
+           -1.8276830316432197e-16
+          ],
+          [
+           0,
+           0.021785860740656946,
+           0.046837527572948186,
+           0.07525629212434362,
+           0.10702268367239437,
+           0.14199580513163185,
+           0.17991609384238963,
+           0.22041144232518387,
+           0.26300652618158554,
+           0.3071351021465925,
+           0.352154961068615,
+           0.39736515030319247,
+           0.44202501944898337,
+           0.4853745940795057,
+           0.5266557453992377,
+           0.5651336005312774,
+           0.6001176290405892,
+           0.6309818465724973,
+           0.6571835960400162,
+           0.6782804001664747,
+           0.693944425574509,
+           0.7039741568737549,
+           0.7083029479023341,
+           0.707004194721955,
+           0.7002929592311862,
+           0.6885239612497498,
+           0.6721859484193407,
+           0.6518925449772854,
+           0.6283697700913893,
+           0.6024405017477749,
+           0.5750062410114178,
+           0.5470266018411304,
+           0.5194970117530646,
+           0.49342515695646355,
+           0.46980674088942237,
+           0.44960114643822685,
+           0.4337075989538572,
+           0.4229424192645289,
+           0.4180179333703805,
+           0.4195235689041428,
+           0.42790961860857707,
+           0.4434740892055643,
+           0.46635298160124483,
+           0.4965142671387501,
+           0.5337557365478798,
+           0.5777068054950947,
+           0.6278342654724435,
+           0.6834518735093996,
+           0.7437335811821562,
+           0.8077301149145824,
+           0.8743885377897423,
+           0.9425743500352723,
+           1.0110956228128976,
+           1.0787286094791773,
+           1.1442442413437184,
+           1.206434892059808,
+           1.2641407867191936,
+           1.3162754387031805,
+           1.361849519213186,
+           1.3999926006473598,
+           1.4299722647354909,
+           1.4512101283903251,
+           1.463294413076741,
+           1.4659887653726293,
+           1.4592371253077674,
+           1.4431645328576452,
+           1.418073859357297,
+           1.38443854724162,
+           1.34289153606407,
+           1.2942106428977016,
+           1.239300748793159,
+           1.1791732179313807,
+           1.1149230406513257,
+           1.0477042440981639,
+           0.9787041535635917,
+           0.9091171127415063,
+           0.840118281511785,
+           0.7728381252684136,
+           0.708338190368648,
+           0.6475887265056242,
+           0.591448669556051,
+           0.5406484389163869,
+           0.4957759330033762,
+           0.45726602720947135,
+           0.42539379214140705,
+           0.4002715585719671,
+           0.38184986145953775,
+           0.3699222009571501,
+           0.36413346586629336,
+           0.3639917767611183,
+           0.36888342417650394,
+           0.37809050381659287,
+           0.3908107874844771,
+           0.4061793168882705,
+           0.42329116887985896,
+           0.4412248159422216,
+           0.45906549542576147,
+           0.4759280053501427,
+           0.49097836337853806,
+           0.5034537983189791,
+           0.5126805893495698,
+           0.5180893259134132,
+           0.5192272294035375,
+           0.5157672546196597,
+           0.5075137725755042,
+           0.4944047244517648,
+           0.47651022709839,
+           0.4540277012079283,
+           0.427273681827739,
+           0.3966725550300894,
+           0.3627425422064008,
+           0.32607932265257733,
+           0.2873377441387114,
+           0.2472121185386253,
+           0.20641563415721156,
+           0.1656594372844356,
+           0.12563194221703874,
+           0.08697892137219354,
+           0.05028490538234074,
+           0.01605638777287834,
+           -0.015292719109045432,
+           -0.0434529896008928,
+           -0.06822843361630136,
+           -0.08954224828366282,
+           -0.10743921528704113,
+           -0.12208467451793845,
+           -0.1337600941346259,
+           -0.14285534617755888,
+           -0.14985788324350827,
+           -0.1553390931829858,
+           -0.15993818328277676,
+           -0.16434401102922386,
+           -0.16927533364127528,
+           -0.17545999170186935,
+           -0.18361357228793934,
+           -0.1944181132167349,
+           -0.20850141195012908,
+           -0.22641749024880048,
+           -0.24862873912542763,
+           -0.27549022864551603,
+           -0.30723661464032737,
+           -0.34397201071775185,
+           -0.3856631206560213,
+           -0.43213584515832465,
+           -0.48307549004910283,
+           -0.5380306124696617,
+           -0.596420449741492,
+           -0.6575457846089615,
+           -0.7206030128295247,
+           -0.7847010967543938,
+           -0.8488810137108985,
+           -0.9121372425526216,
+           -0.9734407773483797,
+           -1.0317631152286166,
+           -1.0861006369839685,
+           -1.1354987848680647,
+           -1.1790754425949324,
+           -1.2160429377764181,
+           -1.2457281166888428,
+           -1.2675899846046066,
+           -1.2812344609473538,
+           -1.2864258658862915,
+           -1.283094832051271,
+           -1.2713424199567203,
+           -1.251440306403922,
+           -1.2238270093754013,
+           -1.189100208438066,
+           -1.1480053140943005,
+           -1.1014205305454556,
+           -1.0503387417236438,
+           -0.9958466281032768,
+           -0.9391014898088597,
+           -0.8813063082099921,
+           -0.8236836221336873,
+           -0.7674488249353667,
+           -0.713783504197248,
+           -0.6638094463687797,
+           -0.6185639141962632,
+           -0.57897677564486,
+           -0.5458500198920361,
+           -0.5198401399063151,
+           -0.5014437934756365,
+           -0.49098707695629534,
+           -0.48861866036085355,
+           -0.49430694077331455,
+           -0.5078412757005479,
+           -0.528837261159935,
+           -0.5567459234184609,
+           -0.5908666006685359,
+           -0.6303632038003488,
+           -0.6742834659229823,
+           -0.721580720322544,
+           -0.7711376878152262,
+           -0.8217917083699684,
+           -0.8723608195412943,
+           -0.9216700664319093,
+           -0.9685774250033753,
+           -1.0119987326126385,
+           -1.050931046345248,
+           -1.0844738903576667,
+           -1.111847907004037,
+           -1.1324104916644855,
+           -1.1456680662876777,
+           -1.151284729842615,
+           -1.1490871130816547,
+           -1.1390653580413965,
+           -1.1213702372541812,
+           -1.0963065213814993,
+           -1.0643227946071687,
+           -1.0259980024205675,
+           -0.9820250942925722,
+           -0.9331921923017856,
+           -0.8803617743432198,
+           -0.8244484057590968,
+           -0.7663955849941174,
+           -0.7071522864543565,
+           -0.6476497867520404,
+           -0.5887793489231314,
+           -0.5313713133491328,
+           -0.4761761046911751,
+           -0.4238476121814573,
+           -0.3749293374534036,
+           -0.3298436313424493,
+           -0.28888426060494193,
+           -0.25221245932348996,
+           -0.2198565300716204,
+           -0.19171496896088652,
+           -0.16756299877881903,
+           -0.14706230780562093,
+           -0.12977371074404215,
+           -0.11517237454257223,
+           -0.10266518757791827,
+           -0.09160979729250582,
+           -0.08133480028321598,
+           -0.07116054102562429,
+           -0.060419961575306415,
+           -0.048478945043960185,
+           -0.03475561037281513,
+           -0.01873804452963733,
+           -1.88346966884696e-16
+          ],
+          [
+           0,
+           0.022391519570018757,
+           0.048033061050360974,
+           0.07696334437377751,
+           0.10910250826449547,
+           0.14425332176886707,
+           0.18210571341794582,
+           0.2222445052982358,
+           0.26416015528902065,
+           0.3072622316468131,
+           0.35089527199150644,
+           0.39435661541289835,
+           0.4369157434886343,
+           0.4778346248429089,
+           0.5163885295423162,
+           0.55188676486225,
+           0.5836927831649757,
+           0.6112431258589093,
+           0.6340646943553283,
+           0.6517898789562203,
+           0.6641691287183811,
+           0.6710806082621952,
+           0.6725366596731515,
+           0.6686868672895421,
+           0.6598176082998305,
+           0.6463480605655162,
+           0.628822728728938,
+           0.6079006382161115,
+           0.5843414319803196,
+           0.558988684608832,
+           0.5327508207201831,
+           0.5065800875820412,
+           0.48145008397664585,
+           0.45833238719657876,
+           0.4381728466345375,
+           0.4218681250301935,
+           0.41024306669480914,
+           0.4040294559443475,
+           0.4038466988848169,
+           0.4101849183075197,
+           0.42339089579565575,
+           0.44365722855212875,
+           0.47101499253947693,
+           0.5053301201184348,
+           0.5463036115121677,
+           0.5934756072777528,
+           0.6462332557891702,
+           0.7038222178107095,
+           0.7653615618231887,
+           0.829861721032152,
+           0.8962451079752047,
+           0.9633689172063217,
+           1.0300495922868065,
+           1.095088391601771,
+           1.1572974593872736,
+           1.2155257945045146,
+           1.268684510291925,
+           1.315770794263058,
+           1.3558900061384733,
+           1.3882753959935255,
+           1.412304980128605,
+           1.4275151792735936,
+           1.4336109003000592,
+           1.4304718268739267,
+           1.4181547743907668,
+           1.396892057909473,
+           1.3670859163675821,
+           1.3292991298234946,
+           1.2842420565561332,
+           1.2327564013730805,
+           1.1757961033839206,
+           1.1144057989234522,
+           1.0496973716309093,
+           0.9828251455505445,
+           0.9149603074670665,
+           0.8472651608098806,
+           0.7808678149856566,
+           0.7168379009212219,
+           0.6561638762672514,
+           0.5997324428273806,
+           0.5483105453672694,
+           0.5025303563610596,
+           0.46287757705768184,
+           0.4296833033386671,
+           0.4031196172216274,
+           0.38319897370468536,
+           0.369777360195538,
+           0.36256111430014265,
+           0.3611171975069966,
+           0.3648866394557859,
+           0.3732007920481026,
+           0.3852999664794189,
+           0.4003539709490636,
+           0.417484023669614,
+           0.4357854858751297,
+           0.4543508435150537,
+           0.4722923645671153,
+           0.4887638714025885,
+           0.5029810940314473,
+           0.514240109638943,
+           0.5219334255680295,
+           0.5255633254724236,
+           0.5247521701643266,
+           0.5192494238838485,
+           0.5089352613175888,
+           0.4938206985546672,
+           0.4740442800754389,
+           0.4498654415849938,
+           0.4216547528278568,
+           0.3898813233386938,
+           0.3550977254242566,
+           0.317922850753003,
+           0.27902316820452727,
+           0.23909288982832966,
+           0.1988335779127556,
+           0.15893373863140314,
+           0.1200489462220164,
+           0.0827830262196765,
+           0.047670797320241334,
+           0.015162829739363325,
+           -0.014387375474055568,
+           -0.04073344545044308,
+           -0.06374316456824977,
+           -0.08340228462688612,
+           -0.09981501134403392,
+           -0.11320114928650535,
+           -0.12388997474428612,
+           -0.13231099175022265,
+           -0.13898180825614243,
+           -0.1444934453199349,
+           -0.1494934601061833,
+           -0.15466732182165366,
+           -0.16071852690371569,
+           -0.168347974640504,
+           -0.17823314602141274,
+           -0.19100763642260807,
+           -0.20724158649847008,
+           -0.22742353550282854,
+           -0.2519441876799513,
+           -0.28108253615913553,
+           -0.3149947310913828,
+           -0.3537060110052647,
+           -0.3971059402099454,
+           -0.4449471124281578,
+           -0.4968473937588506,
+           -0.5522956887217214,
+           -0.6106611237585337,
+           -0.671205455399008,
+           -0.7330984275322522,
+           -0.7954357259427381,
+           -0.8572591104006324,
+           -0.9175782468622756,
+           -0.9753937162117458,
+           -1.0297206426471317,
+           -1.0796123651582838,
+           -1.1241835700915654,
+           -1.1626323117354096,
+           -1.1942603710149668,
+           -1.2184914392295079,
+           -1.2348866634361368,
+           -1.24315715139242,
+           -1.2431731054427468,
+           -1.234969334638477,
+           -1.2187469807778752,
+           -1.1948713848324428,
+           -1.163866113172995,
+           -1.1264032558456127,
+           -1.083290199597263,
+           -1.035453164190553,
+           -0.983917869664431,
+           -0.9297877726415447,
+           -0.874220369813264,
+           -0.8184021148632042,
+           -0.7635225301223375,
+           -0.7107481153075951,
+           -0.6611966622456953,
+           -0.6159125763461893,
+           -0.5758437829422235,
+           -0.5418207600009466,
+           -0.5145381889965469,
+           -0.49453965413762135,
+           -0.4822057481388111,
+           -0.47774586207133,
+           -0.4811938494773502,
+           -0.49240766301227673,
+           -0.5110729676219316,
+           -0.5367106399603583,
+           -0.5686879717007498,
+           -0.6062333068234373,
+           -0.6484537620065517,
+           -0.6943556068593005,
+           -0.7428668186761589,
+           -0.7928612761493922,
+           -0.8431840192631987,
+           -0.8926769792908229,
+           -0.9402045739699003,
+           -0.9846785687289893,
+           -1.0250816251091364,
+           -1.0604889917419578,
+           -1.0900878405428214,
+           -1.1131938099666372,
+           -1.1292643867769259,
+           -1.1379088360652474,
+           -1.1388944742858667,
+           -1.1321491697363666,
+           -1.1177600470045412,
+           -1.0959684641463938,
+           -1.0671614214911385,
+           -1.031859646775382,
+           -0.9907026806906074,
+           -0.9444313579491591,
+           -0.8938681399090221,
+           -0.8398958041748492,
+           -0.7834350332298823,
+           -0.7254214671865683,
+           -0.6667827946486488,
+           -0.6084164502816223,
+           -0.5511684681747991,
+           -0.49581400698037154,
+           -0.4430400170034464,
+           -0.39343046207655874,
+           -0.3474544416526279,
+           -0.3054574828088529,
+           -0.26765618969235405,
+           -0.23413635143470476,
+           -0.20485452089933998,
+           -0.17964298803541476,
+           -0.1582179853202457,
+           -0.14019088094473525,
+           -0.1250820400812781,
+           -0.11233696765401173,
+           -0.10134428917593441,
+           -0.09145508084031796,
+           -0.08200302727872606,
+           -0.07232486603059717,
+           -0.06178057227754411,
+           -0.04977274589761116,
+           -0.03576468515692643,
+           -0.01929666679859932,
+           -1.9386738893974233e-16
+          ],
+          [
+           0,
+           0.02296256255492725,
+           0.04912889805548811,
+           0.07847758501769264,
+           0.11087183286840605,
+           0.14606246929637134,
+           0.1836941113972555,
+           0.22331436333198013,
+           0.2643858037811215,
+           0.30630045301432673,
+           0.3483963437729117,
+           0.3899757640601617,
+           0.4303246947830871,
+           0.4687329321527289,
+           0.5045143646850621,
+           0.5370268680831113,
+           0.5656912884160695,
+           0.590009004691786,
+           0.609577595653071,
+           0.6241041815952423,
+           0.6334160690730155,
+           0.6374683931294589,
+           0.6363485264827302,
+           0.630277106087597,
+           0.6196056126296852,
+           0.6048105256843237,
+           0.5864841642966065,
+           0.5653224074321094,
+           0.5421095689790665,
+           0.5177007757302131,
+           0.4930022621704965,
+           0.4689500512840944,
+           0.4464875345549373,
+           0.4265424957345746,
+           0.4100041409653794,
+           0.39770070198164315,
+           0.39037816921627067,
+           0.38868068791403426,
+           0.3931331133350732,
+           0.4041261716962966,
+           0.4219046128249044,
+           0.44655867004930055,
+           0.47801906433505126,
+           0.5160557049969328,
+           0.5602801505482012,
+           0.6101518025557341,
+           0.664987714976915,
+           0.72397581358004,
+           0.7861912368554329,
+           0.8506154333587045,
+           0.916157582577647,
+           0.981677848858338,
+           1.0460119320914425,
+           1.1079963458881592,
+           1.1664938346937646,
+           1.2204183361874623,
+           1.2687589045449705,
+           1.3106020334886046,
+           1.3451518549658041,
+           1.3717477388955346,
+           1.3898788805060622,
+           1.399195532878372,
+           1.399516621682968,
+           1.3908335648261654,
+           1.3733102097221137,
+           1.3472788929905182,
+           1.3132327193086821,
+           1.2718142456853665,
+           1.2238008423979096,
+           1.1700870801801015,
+           1.111664563067554,
+           1.0495996859100785,
+           0.9850098435094622,
+           0.919038653484728,
+           0.8528307764693625,
+           0.7875069246051762,
+           0.7241396423615485,
+           0.6637304226742791,
+           0.6071886868073396,
+           0.5553131090687561,
+           0.5087757087427346,
+           0.46810906279964637,
+           0.43369691582254355,
+           0.4057683800543606,
+           0.3843958305890325,
+           0.3694965106702602,
+           0.36083777204115874,
+           0.3580457875183238,
+           0.3606174895967307,
+           0.36793541196577156,
+           0.3792850422065276,
+           0.3938742353112717,
+           0.4108541904327266,
+           0.4293414585620036,
+           0.4484404274668557,
+           0.4672657226795039,
+           0.484963969745681,
+           0.5007343831260141,
+           0.5138476805287887,
+           0.5236628671733548,
+           0.5296414913549715,
+           0.5313590392486374,
+           0.5285132114566963,
+           0.5209289044823073,
+           0.5085598050589739,
+           0.4914865919485952,
+           0.4699118262560953,
+           0.44415169532713566,
+           0.4146248547906698,
+           0.38183868629119905,
+           0.3463733531040681,
+           0.308864090530468,
+           0.26998221136841577,
+           0.23041533777904197,
+           0.19084738875340654,
+           0.1519388567042973,
+           0.11430789737214801,
+           0.07851273449984511,
+           0.045035845190425375,
+           0.014270344428854411,
+           -0.013491070862489518,
+           -0.03806432517362509,
+           -0.059379096894132906,
+           -0.07748074204626614,
+           -0.0925289552913481,
+           -0.10479319956716764,
+           -0.11464502028965225,
+           -0.12254744172492821,
+           -0.12904171983237384,
+           -0.13473179564421922,
+           -0.14026685430481917,
+           -0.1463224456830912,
+           -0.15358066169219287,
+           -0.16270989208873896,
+           -0.17434469388272944,
+           -0.18906630920526055,
+           -0.20738435253297735,
+           -0.22972016087862027,
+           -0.25639226058423953,
+           -0.2876043526755563,
+           -0.32343615662599656,
+           -0.36383738137456345,
+           -0.4086250143062084,
+           -0.45748403558216605,
+           -0.5099715787799247,
+           -0.5655244714293108,
+           -0.6234700029018635,
+           -0.6830396843880415,
+           -0.7433856884635941,
+           -0.8035995859525131,
+           -0.8627329372083897,
+           -0.9198192451021565,
+           -0.9738967392012462,
+           -1.0240314358358111,
+           -1.0693399076331624,
+           -1.1090111989849438,
+           -1.142327340769211,
+           -1.1686819481104946,
+           -1.1875964283169103,
+           -1.1987333813543959,
+           -1.2019068409786706,
+           -1.1970890793561892,
+           -1.1844137798525178,
+           -1.1641754696561282,
+           -1.1368251939130498,
+           -1.1029625038697133,
+           -1.063323920930091,
+           -1.0187681243324263,
+           -0.9702581902284507,
+           -0.9188412823302299,
+           -0.8656262571880182,
+           -0.811759699019483,
+           -0.758400938537841,
+           -0.7066966364360592,
+           -0.6577555244152433,
+           -0.6126238945774553,
+           -0.5722624116681055,
+           -0.5375247924308137,
+           -0.5091388529499908,
+           -0.48769036934759064,
+           -0.4736101309123456,
+           -0.4671644892788018,
+           -0.4684496244711482,
+           -0.4773896604948249,
+           -0.4937386718394038,
+           -0.5170865299696203,
+           -0.5468684478711789,
+           -0.5823779931958708,
+           -0.6227832586421898,
+           -0.6671458039001162,
+           -0.7144419185817561,
+           -0.7635857016215886,
+           -0.8134534109594602,
+           -0.8629085089128324,
+           -0.9108268141727957,
+           -0.9561211711494597,
+           -0.9977650614242922,
+           -1.0348146099692177,
+           -1.0664284798534238,
+           -1.0918852023462544,
+           -1.110597553309042,
+           -1.1221236599581477,
+           -1.1261746026603021,
+           -1.1226183623951274,
+           -1.111480053765759,
+           -1.092938473756912,
+           -1.0673190856091963,
+           -1.0350836430103547,
+           -0.9968167401967489,
+           -0.9532096465492264,
+           -0.9050418480808154,
+           -0.8531607713050637,
+           -0.7984602060672655,
+           -0.7418579720408147,
+           -0.6842733880850578,
+           -0.6266051042170917,
+           -0.5697098426018207,
+           -0.5143825670916258,
+           -0.46133856116400523,
+           -0.4111978426443813,
+           -0.3644722816844488,
+           -0.32155571767455365,
+           -0.28271729289980246,
+           -0.24809813777488163,
+           -0.21771145650645649,
+           -0.19144597520005385,
+           -0.16907262893297192,
+           -0.15025428230092544,
+           -0.13455820146778302,
+           -0.1214709267165748,
+           -0.11041513463773149,
+           -0.10076802988650294,
+           -0.09188076911518833,
+           -0.0830983951567091,
+           -0.0737797484011047,
+           -0.06331682482520466,
+           -0.051153066223911706,
+           -0.0368000974237859,
+           -0.019852466880102,
+           -1.9921222776495417e-16
+          ],
+          [
+           0,
+           0.023487613495027718,
+           0.05010402103942105,
+           0.07977064395034804,
+           0.11229770125535897,
+           0.14738885804702068,
+           0.18464889964571082,
+           0.2235942334083831,
+           0.2636659457082284,
+           0.3042450741949876,
+           0.3446696966459889,
+           0.3842533890356501,
+           0.4223045681344824,
+           0.4581462089607534,
+           0.4911354154027723,
+           0.5206823236350991,
+           0.5462678325612988,
+           0.5674596830879881,
+           0.5839264479024142,
+           0.595449044611204,
+           0.6019294463379992,
+           0.6033963336546637,
+           0.6000075082999272,
+           0.5920489706122892,
+           0.5799306469359286,
+           0.5641788383388457,
+           0.5454255456778875,
+           0.524394906252349,
+           0.5018870519856248,
+           0.4787597663752769,
+           0.4559083756485698,
+           0.43424435716883,
+           0.4146731839342219,
+           0.398071947062148,
+           0.3852673078421508,
+           0.3770143269808335,
+           0.3739767011058177,
+           0.3767089058310886,
+           0.38564070143104107,
+           0.4010644024538876,
+           0.4231252477417892,
+           0.4518151338839651,
+           0.48696989489448694,
+           0.5282702258343344,
+           0.5752462602669234,
+           0.6272857229991744,
+           0.6836454926867966,
+           0.7434663257087901,
+           0.8057904152908124,
+           0.8695813900906142,
+           0.933746296076369,
+           0.9971590560276384,
+           1.0586848636006074,
+           1.1172049445602454,
+           1.1716411071088535,
+           1.2209795065152573,
+           1.2642930664119494,
+           1.3007620297784668,
+           1.3296921560369892,
+           1.35053013580612,
+           1.3628758603592421,
+           1.3664912571277552,
+           1.3613054838743228,
+           1.3474163604624811,
+           1.3250880063691786,
+           1.2947447420570393,
+           1.2569614008562444,
+           1.2124502829502912,
+           1.162045062352676,
+           1.1066820294787378,
+           1.0473791143215732,
+           0.985213186824571,
+           0.9212961705641985,
+           0.8567505323694523,
+           0.7926847233833301,
+           0.7301691460257806,
+           0.6702132063974874,
+           0.6137439832608443,
+           0.5615870035692616,
+           0.5144495616224947,
+           0.47290695562317525,
+           0.43739194327191017,
+           0.4081876388527026,
+           0.3854239899849547,
+           0.36907788493252097,
+           0.35897685321358286,
+           0.354806235414133,
+           0.35611961470240544,
+           0.3623522246123238,
+           0.37283697711207175,
+           0.3868226935139438,
+           0.40349406989988335,
+           0.42199286965475236,
+           0.4414398093426716,
+           0.4609565911397574,
+           0.47968753562604893,
+           0.4968202828791752,
+           0.5116050571044325,
+           0.5233720297569352,
+           0.5315463672301993,
+           0.5356606103895073,
+           0.5353641029569923,
+           0.5304292622386623,
+           0.5207545669871869,
+           0.5063642212672682,
+           0.48740453791704996,
+           0.46413716845129144,
+           0.4369293859429126,
+           0.4062417015549233,
+           0.37261316212328777,
+           0.33664473385030763,
+           0.2989812243250538,
+           0.26029223057535117,
+           0.22125262380258207,
+           0.18252309129996114,
+           0.1447312525806607,
+           0.10845385005323145,
+           0.07420048511928544,
+           0.04239932909477279,
+           0.01338518593532012,
+           -0.01260977828298727,
+           -0.03546239423294322,
+           -0.05516176796422856,
+           -0.07180939130872735,
+           -0.08561607895192644,
+           -0.0968958100852568,
+           -0.10605663362800032,
+           -0.11358887306923153,
+           -0.12005093807092697,
+           -0.12605311328303775,
+           -0.1322397487351009,
+           -0.13927031930743242,
+           -0.1477998520388815,
+           -0.15845923858642244,
+           -0.17183595552206835,
+           -0.18845570717357346,
+           -0.20876548456146965,
+           -0.23311850016201938,
+           -0.2617614125587097,
+           -0.29482419865769066,
+           -0.332312965429982,
+           -0.37410591973663615,
+           -0.41995263551954976,
+           -0.4694766744780965,
+           -0.5221815313792527,
+           -0.5774597904951138,
+           -0.6346052974517449,
+           -0.6928280730756446,
+           -0.7512716245993317,
+           -0.8090322466385991,
+           -0.8651798512816958,
+           -0.9187798247933092,
+           -0.968915378915237,
+           -1.014709848318498,
+           -1.0553483828819983,
+           -1.0900984942587117,
+           -1.1183289404208414,
+           -1.1395264689951285,
+           -1.1533099893328838,
+           -1.1594418032306768,
+           -1.1578355935807054,
+           -1.148560947302872,
+           -1.1318442718177089,
+           -1.108066051036495,
+           -1.0777544752504298,
+           -1.0415755672268117,
+           -1.0003200121067457,
+           -0.9548869792475155,
+           -0.9062652979771982,
+           -0.8555124145063708,
+           -0.8037316123551477,
+           -0.7520480222349026,
+           -0.7015839782855718,
+           -0.6534342951322097,
+           -0.6086420439382264,
+           -0.5681753953851593,
+           -0.5329060735313421,
+           -0.503589927361303,
+           -0.48085007742512914,
+           -0.46516303447399904,
+           -0.45684811688848137,
+           -0.4560604156700656,
+           -0.46278747171813805,
+           -0.4768497420864221,
+           -0.4979048420445537,
+           -0.5254554602468212,
+           -0.5588607573071361,
+           -0.5973509757108055,
+           -0.6400449132592293,
+           -0.6859698449793862,
+           -0.7340834212634899,
+           -0.7832970243149454,
+           -0.8325000318615746,
+           -0.880584417344034,
+           -0.9264691098561353,
+           -0.969123545125006,
+           -1.007589860550685,
+           -1.0410032222195393,
+           -1.0686098189832782,
+           -1.089782116975437,
+           -1.104031035868741,
+           -1.1110147840740388,
+           -1.110544172065986,
+           -1.1025843090671257,
+           -1.0872526763096948,
+           -1.0648136578584069,
+           -1.0356696953629074,
+           -1.0003493140237978,
+           -0.959492341524096,
+           -0.9138327078852923,
+           -0.8641792705482818,
+           -0.8113951540966983,
+           -0.7563761268563302,
+           -0.700028556349682,
+           -0.6432474918147081,
+           -0.5868954146036325,
+           -0.5317821764916957,
+           -0.47864661230913247,
+           -0.42814026774292724,
+           -0.38081362681343023,
+           -0.3371051578556644,
+           -0.29733342349683906,
+           -0.26169242097812984,
+           -0.23025023621904314,
+           -0.2029510103565632,
+           -0.17962013323735523,
+           -0.1599724966136398,
+           -0.1436235626388982,
+           -0.13010293260709377,
+           -0.11887003849112165,
+           -0.10933152726510925,
+           -0.10085986654481208,
+           -0.09281267077342578,
+           -0.08455223073303329,
+           -0.07546472596708312,
+           -0.06497860981554453,
+           -0.05258167991574523,
+           -0.037836382604689224,
+           -0.020392946756880335,
+           -2.0426928051054264e-16
+          ],
+          [
+           0,
+           0.02395612828311273,
+           0.05093935149301169,
+           0.08081742073913344,
+           0.11335192146630177,
+           0.14820445468071974,
+           0.1849456645684801,
+           0.2230668774309625,
+           0.26199404813624066,
+           0.3011036492699791,
+           0.33974008641936054,
+           0.3772341818630692,
+           0.41292223942734363,
+           0.4461651861683591,
+           0.47636728230875586,
+           0.502993899621756,
+           0.5255878900239291,
+           0.5437840999890052,
+           0.5573216317023956,
+           0.5660535075223659,
+           0.569953458920746,
+           0.5691196330380037,
+           0.5637750875114282,
+           0.5542650253852079,
+           0.5410508046568877,
+           0.5247008392815882,
+           0.5058785881765955,
+           0.4853279039370961,
+           0.4638560816907351,
+           0.4423150090432613,
+           0.42158086885911267,
+           0.40253288637799184,
+           0.3860316398618562,
+           0.37289746886474373,
+           0.36388951590584223,
+           0.3596859257165282,
+           0.36086570156774683,
+           0.36789268103216094,
+           0.38110204477438536,
+           0.40068971276026233,
+           0.42670491406165423,
+           0.45904614086186873,
+           0.49746061617927184,
+           0.5415473202036746,
+           0.5907635340538473,
+           0.6444347743273103,
+           0.7017679091256892,
+           0.7618671683368273,
+           0.8237526897606332,
+           0.8863811799395961,
+           0.9486682158517055,
+           1.0095116722540076,
+           1.0678157304630504,
+           1.1225149084558843,
+           1.1725975497829244,
+           1.217128219981846,
+           1.2552684837163444,
+           1.2862955731544705,
+           1.3096185072545716,
+           1.324791281457451,
+           1.3315228163439887,
+           1.3296834304337437,
+           1.3193076846124547,
+           1.3005935316848924,
+           1.2738977921638364,
+           1.2397280644960664,
+           1.1987312623753805,
+           1.1516790515488788,
+           1.0994505316499816,
+           1.043012573316427,
+           0.983398275607724,
+           0.9216840522023453,
+           0.8589658859869209,
+           0.796335309706627,
+           0.7348556749082494,
+           0.6755392623864245,
+           0.6193257649836499,
+           0.567062638467476,
+           0.519487769197062,
+           0.477214849570745,
+           0.4407217852511004,
+           0.410342383555398,
+           0.3862614920221354,
+           0.36851367200210744,
+           0.3569854062483652,
+           0.35142075400444284,
+           0.35143028411162436,
+           0.35650303820504065,
+           0.3660212040603616,
+           0.37927711534000796,
+           0.3954921399160787,
+           0.41383697591830354,
+           0.4334528436949477,
+           0.4534730437072292,
+           0.473044345409556,
+           0.4913476804763617,
+           0.5076176350700131,
+           0.5211602696282978,
+           0.5313688400018783,
+           0.5377370495233532,
+           0.5398695263156625,
+           0.5374892922036142,
+           0.5304420671541076,
+           0.5186973342808578,
+           0.5023461730658948,
+           0.48159595049753356,
+           0.4567620392455585,
+           0.42825680680165645,
+           0.39657618783817467,
+           0.36228421217837875,
+           0.32599591123180166,
+           0.2883590652793995,
+           0.2500352816215508,
+           0.21168090865423575,
+           0.17392829305843555,
+           0.1373678764438798,
+           0.10253160427566951,
+           0.06987808434423004,
+           0.03977988533169304,
+           0.012513309376895853,
+           -0.011749092607851756,
+           -0.03294306610347455,
+           -0.05111413886702306,
+           -0.06641600781380369,
+           -0.07910586825229472,
+           -0.08953680685751644,
+           -0.09814745672968726,
+           -0.10544918481949389,
+           -0.11201114707936935,
+           -0.11844360326385896,
+           -0.12537992990702398,
+           -0.13345780545620042,
+           -0.14330006492451144,
+           -0.15549573212746354,
+           -0.17058173529836618,
+           -0.18902579666597752,
+           -0.21121095878391002,
+           -0.2374221707000429,
+           -0.26783530642091513,
+           -0.3025089278122238,
+           -0.3413790355788688,
+           -0.3842569769911005,
+           -0.4308305994374706,
+           -0.48066865667985603,
+           -0.5332283919196742,
+           -0.5878661405347305,
+           -0.6438507176564435,
+           -0.7003792835863074,
+           -0.7565953152239295,
+           -0.8116082558426562,
+           -0.8645143701282818,
+           -0.9144182975607487,
+           -0.960454775851338,
+           -1.0018099978236135,
+           -1.0377420700972526,
+           -1.0676000601220232,
+           -1.0908411491084817,
+           -1.107045451487173,
+           -1.1159281156733114,
+           -1.1173483848163004,
+           -1.1113153683262256,
+           -1.0979903535391597,
+           -1.0776855699933043,
+           -1.0508594044055748,
+           -1.0181081504648968,
+           -0.9801544618811251,
+           -0.9378327576723379,
+           -0.8920719034531049,
+           -0.8438755596548717,
+           -0.7943006455046446,
+           -0.7444344147720476,
+           -0.6953706745918199,
+           -0.6481857011933423,
+           -0.6039144155473148,
+           -0.5635273775266422,
+           -0.5279091392601838,
+           -0.4978384673532237,
+           -0.4739709002961965,
+           -0.4568240527263849,
+           -0.4467660135661279,
+           -0.44400711200111603,
+           -0.44859524555606306,
+           -0.4604148801081815,
+           -0.47918974460285874,
+           -0.5044891556174541,
+           -0.5357378208881971,
+           -0.5722288885624652,
+           -0.6131399322644869,
+           -0.6575514929272126,
+           -0.7044677384217047,
+           -0.7528387527562003,
+           -0.801583929206482,
+           -0.8496159170722841,
+           -0.8958645604132818,
+           -0.9393002693577381,
+           -0.9789562803190204,
+           -1.013949290290378,
+           -1.04349799158729,
+           -1.0669390859367176,
+           -1.0837404193652844,
+           -1.0935109503607463,
+           -1.0960073415147737,
+           -1.0911370473799191,
+           -1.0789578565548226,
+           -1.0596739319508928,
+           -1.0336284776800222,
+           -1.0012932419658573,
+           -0.963255140941258,
+           -0.9202003563123992,
+           -0.872896318991426,
+           -0.8221720394962577,
+           -0.7688972830210172,
+           -0.7139611117156394,
+           -0.65825032831178,
+           -0.6026283535512763,
+           -0.5479150550007454,
+           -0.49486801718581286,
+           -0.44416570328191285,
+           -0.39639290788445714,
+           -0.3520288399500325,
+           -0.3114381063915642,
+           -0.27486479176422146,
+           -0.24242974989192773,
+           -0.21413114116261733,
+           -0.1898481666291164,
+           -0.16934786906451407,
+           -0.15229479376476274,
+           -0.13826323010100092,
+           -0.12675169039089315,
+           -0.11719922718586184,
+           -0.10900314493584976,
+           -0.10153762831024506,
+           -0.0941727880487653,
+           -0.08629361660585506,
+           -0.07731835023092905,
+           -0.06671575136217178,
+           -0.05402085484805807,
+           -0.03884876278114272,
+           -0.02090612457373468,
+           -2.089326802477806e-16
+          ],
+          [
+           0,
+           0.024358500590042482,
+           0.05161793179694887,
+           0.08159630839335395,
+           0.11401129370503697,
+           0.14848777415420664,
+           0.18456808223021998,
+           0.22172460010424538,
+           0.259374413349741,
+           0.29689562988014334,
+           0.3336449346564392,
+           0.3689759170921528,
+           0.40225768625910896,
+           0.432893279545144,
+           0.4603373735948878,
+           0.4841128221193758,
+           0.5038255731157258,
+           0.5191775575132245,
+           0.5299771912851969,
+           0.5361471923987163,
+           0.5377294811424846,
+           0.5348870057038136,
+           0.527902412527684,
+           0.5171735610414747,
+           0.5032059627616026,
+           0.48660230359292195,
+           0.4680492833049334,
+           0.44830207582382187,
+           0.42816677635283296,
+           0.40848125484038744,
+           0.3900948785881079,
+           0.3738475987141856,
+           0.36054891492614455,
+           0.35095724007722756,
+           0.3457601800640099,
+           0.34555622587173146,
+           0.3508383234100785,
+           0.36197974393620536,
+           0.37922262435580784,
+           0.40266948381550416,
+           0.43227795227411503,
+           0.4678588698875849,
+           0.5090778349384164,
+           0.5554601946706198,
+           0.6063993898003935,
+           0.6611684817155538,
+           0.7189346134663094,
+           0.778776083508471,
+           0.8397016465709397,
+           0.9006716005829182,
+           0.9606201736905314,
+           1.0184786921387052,
+           1.0731989890283415,
+           1.1237765062120553,
+           1.169272547075596,
+           1.2088351565540412,
+           1.2417181360173235,
+           1.2672977438827446,
+           1.285086686933618,
+           1.2947450710361479,
+           1.29608805170836,
+           1.289090003064679,
+           1.273885106141996,
+           1.2507643425033732,
+           1.2201689642505533,
+           1.1826805950840285,
+           1.1390081968002217,
+           1.089972209671957,
+           1.0364862417239604,
+           0.9795367393762477,
+           0.920161118896118,
+           0.8594248734421769,
+           0.798398193355974,
+           0.7381326472184493,
+           0.6796384678192933,
+           0.6238629706916173,
+           0.5716706036677168,
+           0.5238250847512275,
+           0.48097403350542195,
+           0.4436364394234432,
+           0.412193240904164,
+           0.38688121223499106,
+           0.3677902752613487,
+           0.3548642691904237,
+           0.34790512828075865,
+           0.34658033506342645,
+           0.3504334382357435,
+           0.3588973513827262,
+           0.371310082992521,
+           0.38693249143375824,
+           0.4049676120259388,
+           0.42458106817265845,
+           0.44492205557191117,
+           0.46514437829400396,
+           0.484427018235414,
+           0.5019937350042434,
+           0.5171312212401973,
+           0.529205377982208,
+           0.537675324945264,
+           0.5421048201674282,
+           0.5421708309215297,
+           0.5376690713448871,
+           0.5285164000668491,
+           0.5147500512479871,
+           0.4965237528724403,
+           0.4741008648396118,
+           0.4478447444129675,
+           0.418206616028571,
+           0.3857112846131313,
+           0.3509410848656782,
+           0.31451850209761084,
+           0.27708793213890764,
+           0.23929706772312562,
+           0.20177840618255086,
+           0.16513136805367698,
+           0.12990549846652408,
+           0.09658519343756458,
+           0.0655763521755783,
+           0.03719530529573813,
+           0.011660308728642396,
+           -0.010914174359921829,
+           -0.030520254439049477,
+           -0.04725638697662619,
+           -0.061324140738147695,
+           -0.07302204803295459,
+           -0.08273669833100532,
+           -0.09093130898216864,
+           -0.09813207313903959,
+           -0.10491264372439978,
+           -0.11187716189793291,
+           -0.11964227769498195,
+           -0.12881863832518986,
+           -0.13999233530933577,
+           -0.15370680478163465,
+           -0.17044566579048973,
+           -0.19061695950951926,
+           -0.21453921845172227,
+           -0.24242974989192687,
+           -0.27439546285468,
+           -0.31042650457675375,
+           -0.3503929018841435,
+           -0.39404432719032756,
+           -0.4410130297184087,
+           -0.49081989205547405,
+           -0.5428834922826817,
+           -0.5965319746972423,
+           -0.6510174594987896,
+           -0.70553265558831,
+           -0.7592292825024933,
+           -0.8112378589608471,
+           -0.8606883777826383,
+           -0.9067313610141112,
+           -0.948558775680031,
+           -0.9854242900148356,
+           -1.0166623623957112,
+           -1.0417056802299556,
+           -1.060100503164251,
+           -1.0715195133047304,
+           -1.0757718335054078,
+           -1.0728099417881676,
+           -1.0627332839729544,
+           -1.0457884658179086,
+           -1.0223659884595306,
+           -0.9929935746809321,
+           -0.9583262164660611,
+           -0.9191331543790611,
+           -0.876282074566829,
+           -0.8307208777611873,
+           -0.7834574348571431,
+           -0.7355377939722172,
+           -0.6880233430948143,
+           -0.641967459525656,
+           -0.5983921916196853,
+           -0.5582655194737772,
+           -0.5224797291288723,
+           -0.4918314098375369,
+           -0.46700354658211907,
+           -0.4485501312093602,
+           -0.4368836564515856,
+           -0.43226578916151454,
+           -0.43480144394403464,
+           -0.4444363978477804,
+           -0.4609585028380823,
+           -0.48400246745090497,
+           -0.5130580943989451,
+           -0.5474817790232168,
+           -0.5865109963456344,
+           -0.6292814339532803,
+           -0.6748463657435843,
+           -0.7221978091873154,
+           -0.7702889674871637,
+           -0.8180574288157085,
+           -0.8644485784023567,
+           -0.9084386759856348,
+           -0.9490570611132655,
+           -0.9854069716920784,
+           -1.0166844964795083,
+           -1.0421952289829375,
+           -1.0613682473256951,
+           -1.0737671106315576,
+           -1.0790976357387583,
+           -1.0772122967698403,
+           -1.0681111723143144,
+           -1.0519394487029434,
+           -1.0289815710090209,
+           -0.9996522139643157,
+           -0.9644843209550292,
+           -0.924114528812484,
+           -0.8792663575433437,
+           -0.8307315959680878,
+           -0.7793503552078676,
+           -0.7259902911038015,
+           -0.6715255132888073,
+           -0.6168157023915372,
+           -0.5626859476855629,
+           -0.509907795676707,
+           -0.4591819662323447,
+           -0.4111231477821874,
+           -0.3662472280202898,
+           -0.3249612528192886,
+           -0.28755633534790775,
+           -0.254203661450597,
+           -0.22495365811863544,
+           -0.19973831134825393,
+           -0.17837653986497617,
+           -0.16058245409410696,
+           -0.14597625730288682,
+           -0.13409747983826578,
+           -0.12442017947869324,
+           -0.11636969254624628,
+           -0.10934048278288949,
+           -0.10271460900680869,
+           -0.09588031886281614,
+           -0.08825027488655536,
+           -0.07927893062037043,
+           -0.06847859833678933,
+           -0.05543378542225216,
+           -0.039813422734324325,
+           -0.021380664085435593,
+           -2.1310400095194086e-16
+          ],
+          [
+           0,
+           0.024686154970013377,
+           0.052125079512323105,
+           0.08208937291911678,
+           0.1142577764818723,
+           0.1482239923616321,
+           0.18350793737726873,
+           0.21956913560709151,
+           0.2558218972150969,
+           0.2916518834078962,
+           0.32643362011624477,
+           0.35954849683455453,
+           0.39040277272109875,
+           0.418445109941877,
+           0.44318316440632677,
+           0.4641987862582153,
+           0.481161416211664,
+           0.49383930823163863,
+           0.502108263052017,
+           0.5059576192615591,
+           0.5054933176186764,
+           0.5009379281590104,
+           0.49262760668687505,
+           0.4810060254621972,
+           0.466615400344592,
+           0.4500848113870119,
+           0.43211608399817086,
+           0.4134675615422929,
+           0.394936155998467,
+           0.3773381096382063,
+           0.3614889364085277,
+           0.34818303590069893,
+           0.33817348479876397,
+           0.33215251019571507,
+           0.3307331361083092,
+           0.33443246919517594,
+           0.34365705267400387,
+           0.3586906696201387,
+           0.37968491935900084,
+           0.40665282492820376,
+           0.43946565717984415,
+           0.477853083785313,
+           0.5214066710853656,
+           0.5695866853665579,
+           0.6217320597408051,
+           0.6770733153372805,
+           0.734748152896033,
+           0.7938193648755317,
+           0.8532946604862913,
+           0.9121479480733664,
+           0.9693415821886534,
+           1.0238490574503225,
+           1.0746776185220996,
+           1.1208902555950477,
+           1.1616265676399935,
+           1.1961220011260623,
+           1.223725009268154,
+           1.2439117252785454,
+           1.256297801388608,
+           1.260647132166397,
+           1.256877254266915,
+           1.2450612934277039,
+           1.2254264113521725,
+           1.1983487881178314,
+           1.1643452578888769,
+           1.1240617950055776,
+           1.0782591220398148,
+           1.0277957793373085,
+           0.973609055264929,
+           0.9166942264002019,
+           0.8580825960323409,
+           0.798818846648975,
+           0.739938236910559,
+           0.6824441756211014,
+           0.6272866943600464,
+           0.5753423170314834,
+           0.5273957892064343,
+           0.4841240836681841,
+           0.4460830421758788,
+           0.41369694853724076,
+           0.38725125623287887,
+           0.36688861683623536,
+           0.35260827522158356,
+           0.34426881602144055,
+           0.34159416498583905,
+           0.34418267078886183,
+           0.35151901933211205,
+           0.36298866550211145,
+           0.37789440827901866,
+           0.3954746854958594,
+           0.41492312560206007,
+           0.43540886641798454,
+           0.45609713571537774,
+           0.4761695858552477,
+           0.4948438846813898,
+           0.5113920871141349,
+           0.5251573458210684,
+           0.5355685640761927,
+           0.5421526483070911,
+           0.5445440804841336,
+           0.5424915998371987,
+           0.535861857641544,
+           0.5246399861240267,
+           0.5089271009606771,
+           0.4889348343993853,
+           0.46497707080582257,
+           0.43745912652860053,
+           0.4068646796637141,
+           0.3737408109846346,
+           0.33868156361237445,
+           0.3023104647861482,
+           0.26526247748228815,
+           0.22816586202654834,
+           0.19162442796452034,
+           0.1562006443168772,
+           0.12240005227902216,
+           0.09065738905643668,
+           0.06132478576915842,
+           0.03466234738374292,
+           0.010831359842093836,
+           -0.010109699447024357,
+           -0.028206245051120047,
+           -0.043605734245227616,
+           -0.05655293510230224,
+           -0.06738243744485016,
+           -0.07650860438894155,
+           -0.0844132294037236,
+           -0.09163122425584397,
+           -0.09873471536957307,
+           -0.1063159686785972,
+           -0.11496959488463178,
+           -0.1252745073502075,
+           -0.13777611310685947,
+           -0.15296921342720676,
+           -0.17128207417075125,
+           -0.19306209805662716,
+           -0.21856349182764934,
+           -0.247937271915368,
+           -0.2812238939189926,
+           -0.31834872542188014,
+           -0.3591205100284735,
+           -0.40323289480237995,
+           -0.4502690154180928,
+           -0.4997090552580556,
+           -0.5509406183558381,
+           -0.6032716834279059,
+           -0.6559458390856722,
+           -0.7081594403772465,
+           -0.759080275599535,
+           -0.8078672911560156,
+           -0.8536908921762896,
+           -0.8957533184485702,
+           -0.9333085894393041,
+           -0.9656815189716876,
+           -0.992285319381225,
+           -1.0126373462263059,
+           -1.0263725771705041,
+           -1.0332544714545606,
+           -1.0331829181671919,
+           -1.026199050806332,
+           -1.0124867807091518,
+           -0.9923709809857815,
+           -0.9663123336818764,
+           -0.9348989340282264,
+           -0.8988348248162414,
+           -0.8589257092148848,
+           -0.8160621598587295,
+           -0.7712007040685476,
+           -0.7253432180759327,
+           -0.6795151057931598,
+           -0.634742768931154,
+           -0.5920308943342493,
+           -0.5523400907805813,
+           -0.5165654010123645,
+           -0.4855161955482005,
+           -0.4598979233384707,
+           -0.44029615130604866,
+           -0.4271632713015562,
+           -0.42080819028742134,
+           -0.4213892491662528,
+           -0.4289105392937926,
+           -0.4432217052194232,
+           -0.4640212395337966,
+           -0.49086319288293373,
+           -0.5231671412445298,
+           -0.5602311754230459,
+           -0.6012476062793927,
+           -0.6453210152026607,
+           -0.6914882243068381,
+           -0.7387397161255265,
+           -0.7860419992595781,
+           -0.832360395304278,
+           -0.8766817139424006,
+           -0.9180362875244875,
+           -0.9555188536394541,
+           -0.9883078036665267,
+           -1.0156823563511392,
+           -1.0370372670386228,
+           -1.0518947440480473,
+           -1.0599133122675684,
+           -1.0608934387068274,
+           -1.0547798136103979,
+           -1.0416602618775666,
+           -1.0217613409540238,
+           -0.9954407610635744,
+           -0.9631768396820568,
+           -0.925555272665071,
+           -0.8832535677095624,
+           -0.8370235403230147,
+           -0.7876723168790434,
+           -0.7360423225927776,
+           -0.6829907535701063,
+           -0.6293690409849103,
+           -0.5760028117402627,
+           -0.5236728338076566,
+           -0.4730974062566067,
+           -0.42491661452616164,
+           -0.37967882176939216,
+           -0.3378297083939685,
+           -0.29970410571941836,
+           -0.26552079765049225,
+           -0.23538038824387847,
+           -0.20926625493551304,
+           -0.1870485289591776,
+           -0.16849096808448671,
+           -0.15326051414442105,
+           -0.14093926072256965,
+           -0.13103849649907676,
+           -0.12301443859880741,
+           -0.11628522911137179,
+           -0.11024873777393196,
+           -0.10430069536040577,
+           -0.09785267604545038,
+           -0.0903494530428085,
+           -0.08128526998033331,
+           -0.07021860028848224,
+           -0.0567850075730793,
+           -0.0407077704714022,
+           -0.02180599456130316,
+           -2.166932585206883e-16
+          ],
+          [
+           0,
+           0.02493162644553637,
+           0.05244851262660801,
+           0.08228248706539935,
+           0.11407858976078741,
+           0.1474049790118321,
+           0.18176504719700567,
+           0.21661142559381596,
+           0.25136150832616505,
+           0.2854140849617766,
+           0.3181666411879684,
+           0.3490328681464992,
+           0.3774599139001129,
+           0.40294491533249716,
+           0.42505036544714675,
+           0.44341789912857116,
+           0.4577801192728119,
+           0.4679701338235095,
+           0.473928531457668,
+           0.47570758802721586,
+           0.4734725657719202,
+           0.46750004102763276,
+           0.45817327181420964,
+           0.4459746924003956,
+           0.4314756958040314,
+           0.41532393533334416,
+           0.398228440935935,
+           0.3809429036571657,
+           0.36424753045405334,
+           0.3489299107110427,
+           0.3357653640494425,
+           0.32549725567056675,
+           0.31881777006869166,
+           0.31634962633772656,
+           0.31862919862243894,
+           0.32609147397849375,
+           0.33905723774259217,
+           0.3577228244831402,
+           0.3821527119588343,
+           0.4122751677291825,
+           0.44788108478925265,
+           0.4886260656321928,
+           0.5340357353639169,
+           0.5835141858399917,
+           0.6363553762013027,
+           0.6917572425415477,
+           0.748838202541198,
+           0.8066556814062313,
+           0.8642262348331797,
+           0.9205468042463711,
+           0.974616610232572,
+           1.0254591726740228,
+           1.0721439410028915,
+           1.1138070254160053,
+           1.1496705396390554,
+           1.1790600974523442,
+           1.2014200479317647,
+           1.2163260871920396,
+           1.2234949460690003,
+           1.2227909221516,
+           1.214229099199932,
+           1.197975175450898,
+           1.1743419027118929,
+           1.1437822185205984,
+           1.106879232051604,
+           1.064333298972289,
+           1.0169464892806057,
+           0.9656048136250008,
+           0.911258626221731,
+           0.8549016649740113,
+           0.7975492207369962,
+           0.7402159471113776,
+           0.6838938292282954,
+           0.6295308245534783,
+           0.5780106709405396,
+           0.5301343274562792,
+           0.48660347263009285,
+           0.4480064337638386,
+           0.41480686104320263,
+           0.3873353928991667,
+           0.3657844860394338,
+           0.35020650660443614,
+           0.3405150998937648,
+           0.33648977699656907,
+           0.3377835793826436,
+           0.34393360895946945,
+           0.3543741430688748,
+           0.36845199303996634,
+           0.38544371270672684,
+           0.40457422099685003,
+           0.42503637131309874,
+           0.4460109806978053,
+           0.46668682414322005,
+           0.48628010403269245,
+           0.5040529214139311,
+           0.5193303041598348,
+           0.5315153863213697,
+           0.540102382108095,
+           0.5446870556898316,
+           0.5449744529302221,
+           0.5407837315974396,
+           0.5320500007731233,
+           0.518823156232311,
+           0.5012637745867569,
+           0.4796362030679135,
+           0.4542990521231821,
+           0.42569336275670644,
+           0.39432877815322803,
+           0.36076809815133243,
+           0.32561063436919013,
+           0.2894748122675666,
+           0.2529804834685465,
+           0.21673141682947153,
+           0.18129842999371845,
+           0.14720360459713766,
+           0.114905998490876,
+           0.08478922802041913,
+           0.05715124361290728,
+           0.03219656394343607,
+           0.010031169254642711,
+           -0.009339815360892262,
+           -0.026011588965447183,
+           -0.040176312816746135,
+           -0.05211700823876636,
+           -0.06219887683040814,
+           -0.070858273078991,
+           -0.07858962113421974,
+           -0.08593062174704454,
+           -0.09344614080437268,
+           -0.1017112063340988,
+           -0.1112935654054467,
+           -0.12273626537088865,
+           -0.1365407250414833,
+           -0.15315075060955521,
+           -0.17293792868348107,
+           -0.19618879522522872,
+           -0.2230941353089485,
+           -0.2537407155351717,
+           -0.2881056899601024,
+           -0.3260538530532063,
+           -0.3673378411617558,
+           -0.4116013090415197,
+           -0.45838503208744275,
+           -0.5071358098748359,
+           -0.5572179743893078,
+           -0.6079272387054862,
+           -0.6585065605819092,
+           -0.7081636420291761,
+           -0.7560896417442133,
+           -0.8014786435207911,
+           -0.843547401224629,
+           -0.8815548702611384,
+           -0.9148210369716174,
+           -0.9427445710739502,
+           -0.964818851818312,
+           -0.9806459553630136,
+           -0.9899482381150326,
+           -0.9925772072882122,
+           -0.9885194343418038,
+           -0.9778993377060572,
+           -0.9609787365530525,
+           -0.9381531554851777,
+           -0.9099449389738903,
+           -0.8769933122456963,
+           -0.8400416001625275,
+           -0.7999218856317613,
+           -0.7575374524755762,
+           -0.7138434129183365,
+           -0.6698259655399968,
+           -0.6264807645523931,
+           -0.5847909047027915,
+           -0.5457050373980435,
+           -0.5101161324734513,
+           -0.4788413864085961,
+           -0.4526037520299462,
+           -0.43201552744623584,
+           -0.4175643940310357,
+           -0.4096022358519213,
+           -0.4083370074354878,
+           -0.41382784473931694,
+           -0.42598353742341133,
+           -0.44456440083951404,
+           -0.4691875055234892,
+           -0.4993351423437524,
+           -0.5343663247635917,
+           -0.5735310577810451,
+           -0.6159870377629496,
+           -0.6608183901753572,
+           -0.7070560045165468,
+           -0.7536989887334488,
+           -0.799736739937499,
+           -0.8441711149384591,
+           -0.8860381832922811,
+           -0.9244290572138341,
+           -0.9585093165335243,
+           -0.9875365822769424,
+           -1.0108758385336045,
+           -1.0280121579093688,
+           -1.0385605496486199,
+           -1.0422727198906192,
+           -1.0390406087535589,
+           -1.0288966471678997,
+           -1.0120107556850224,
+           -0.9886841859224856,
+           -0.9593403809530351,
+           -0.9245131019528705,
+           -0.8848321330658054,
+           -0.8410069331443892,
+           -0.7938086504267847,
+           -0.7440509531618408,
+           -0.6925701548274794,
+           -0.6402051263045277,
+           -0.5877774888705741,
+           -0.5360725711710873,
+           -0.4858215907146005,
+           -0.4376854865272058,
+           -0.3922407852693761,
+           -0.3499678295028466,
+           -0.3112416352626717,
+           -0.27632557819933123,
+           -0.24536803502210186,
+           -0.21840203162440477,
+           -0.19534787299707962,
+           -0.17601865474818268,
+           -0.16012848363116097,
+           -0.14730316674473468,
+           -0.137093067694624,
+           -0.12898777452407956,
+           -0.12243217995141022,
+           -0.11684354048957538,
+           -0.11162905819645166,
+           -0.1062035176650509,
+           -0.10000651166700918,
+           -0.09251880156602531,
+           -0.08327738287772944,
+           -0.0718888615355994,
+           -0.058040791621958646,
+           -0.04151067938049628,
+           -0.022172419861952113,
+           -2.1961979737108725e-16
+          ],
+          [
+           0,
+           0.025088625794153607,
+           0.052578444615261316,
+           0.08216541720512201,
+           0.1134662545966399,
+           0.1460292512280463,
+           0.1793470917371,
+           0.2128712922859231,
+           0.24602789388899768,
+           0.2782339916037906,
+           0.30891466045799887,
+           0.33751982722486695,
+           0.3635406369315877,
+           0.38652487431843063,
+           0.40609102308993766,
+           0.42194057916183975,
+           0.43386827738498446,
+           0.44176994334675035,
+           0.44564774151363923,
+           0.4456126566968342,
+           0.4418841159519239,
+           0.4347867308075685,
+           0.42474421332871837,
+           0.41227059210705813,
+           0.39795892400560695,
+           0.3824677626046488,
+           0.36650570315290704,
+           0.3508143749249242,
+           0.3361502939172242,
+           0.32326602069999255,
+           0.312891089146316,
+           0.3057131811280447,
+           0.3023600198228202,
+           0.3033824400408997,
+           0.3092390682667661,
+           0.3202830085186353,
+           0.33675088353018884,
+           0.358754525274647,
+           0.3862755458261761,
+           0.4191629505219533,
+           0.45713388203650684,
+           0.49977750810523636,
+           0.546561989099648,
+           0.5968443863461664,
+           0.6498832998505223,
+           0.7048539567253204,
+           0.7608654107875104,
+           0.8169794610053062,
+           0.872230853045247,
+           0.9256482951861645,
+           0.9762757981590985,
+           1.023193838596147,
+           1.065539847992114,
+           1.1025275433694186,
+           1.1334646418613397,
+           1.1577685385753322,
+           1.1749795744773583,
+           1.1847715775087462,
+           1.1869594243440154,
+           1.1815034405661295,
+           1.1685105318673183,
+           1.1482320163614177,
+           1.121058206334562,
+           1.087509864862815,
+           1.048226736813361,
+           1.0039534230192908,
+           0.9555229291939973,
+           0.903838275906104,
+           0.8498526013432838,
+           0.7945482235555823,
+           0.7389151525455147,
+           0.6839295543985655,
+           0.630532669350894,
+           0.5796106732943679,
+           0.5319759480429114,
+           0.4883501903370249,
+           0.44934974392675614,
+           0.4154734842805167,
+           0.38709352287347853,
+           0.36444892916072125,
+           0.34764259493299765,
+           0.3366412895930876,
+           0.33127887784835697,
+           0.3312625952791247,
+           0.336182204073182,
+           0.34552178270051337,
+           0.3586738411070137,
+           0.37495539864062316,
+           0.3936256167002591,
+           0.41390454310130725,
+           0.43499250121024,
+           0.4560896445691229,
+           0.47641519727385856,
+           0.49522591175892905,
+           0.5118332985537561,
+           0.5256192164040469,
+           0.5360494550190045,
+           0.5426849954877158,
+           0.545190693762463,
+           0.543341199004704,
+           0.5370239893557217,
+           0.5262394810480582,
+           0.5110982408746658,
+           0.491815405024661,
+           0.46870247735319975,
+           0.44215674553136847,
+           0.4126486125930886,
+           0.380707192694122,
+           0.34690456215465043,
+           0.31183908903166363,
+           0.2761182857750417,
+           0.24034163945007225,
+           0.20508387233369546,
+           0.17087907247841083,
+           0.13820610944233533,
+           0.10747571544307204,
+           0.07901956760782186,
+           0.053081653905251824,
+           0.029812145111777256,
+           0.009263929320590648,
+           -0.008608104279135328,
+           -0.02394501756970847,
+           -0.036979069116581754,
+           -0.048026381503811055,
+           -0.057477226159311945,
+           -0.06578418391271255,
+           -0.07344849540781646,
+           -0.08100496335124709,
+           -0.08900580719822238,
+           -0.09800389926727149,
+           -0.10853582870683333,
+           -0.12110524575234491,
+           -0.13616693314403253,
+           -0.15411203454603076,
+           -0.17525484172815248,
+           -0.19982150383266142,
+           -0.22794097420119913,
+           -0.259638454170934,
+           -0.2948315303618205,
+           -0.333329133839651,
+           -0.3748333778582006,
+           -0.41894425745578023,
+           -0.46516712085163403,
+           -0.5129227512016932,
+           -0.5615598296319505,
+           -0.6103694882818902,
+           -0.6586016069377947,
+           -0.7054824601216225,
+           -0.7502332844233863,
+           -0.7920893093830796,
+           -0.8303187800399646,
+           -0.8642414957901341,
+           -0.8932463985546643,
+           -0.9168077632930423,
+           -0.9344995751419127,
+           -0.9460077191798968,
+           -0.9511396600158799,
+           -0.9498313478338315,
+           -0.9421511537581689,
+           -0.9283007088143846,
+           -0.9086125956029943,
+           -0.8835449182449402,
+           -0.8536728523143793,
+           -0.8196773504738886,
+           -0.7823312495414848,
+           -0.7424830890163681,
+           -0.7010390080769442,
+           -0.6589431363239505,
+           -0.6171569318684983,
+           -0.5766379477982398,
+           -0.5383185238985398,
+           -0.50308490434818,
+           -0.4717572738332695,
+           -0.44507118430840903,
+           -0.4236608129544852,
+           -0.4080444494922546,
+           -0.3986125589290981,
+           -0.3956187052994917,
+           -0.39917355447279734,
+           -0.40924210128115884,
+           -0.42564418983352936,
+           -0.4480583177851985,
+           -0.4760286374241071,
+           -0.5089749906098896,
+           -0.5462057427024957,
+           -0.5869331143916016,
+           -0.6302906513939379,
+           -0.6753524217526704,
+           -0.7211534901667788,
+           -0.7667111893710944,
+           -0.8110466907838516,
+           -0.8532063708585674,
+           -0.8922824759457828,
+           -0.9274326068152309,
+           -0.9578975738445603,
+           -0.9830172144994852,
+           -1.0022438151015012,
+           -1.0151528377551786,
+           -1.0214507192320035,
+           -1.0209795799559656,
+           -1.013718756250812,
+           -0.9997831458463944,
+           -0.9794184334164391,
+           -0.9529933377519978,
+           -0.9209890932348228,
+           -0.8839864438304429,
+           -0.8426504862785175,
+           -0.7977137491029813,
+           -0.7499579342947396,
+           -0.7001947780757168,
+           -0.6492465053412374,
+           -0.5979263587872342,
+           -0.5470196782408893,
+           -0.49726598850464393,
+           -0.44934252556013876,
+           -0.4038495920054098,
+           -0.36129808411901726,
+           -0.3220994761962224,
+           -0.28655848422515984,
+           -0.25486856217208614,
+           -0.22711031185734837,
+           -0.20325281344431662,
+           -0.18315780978628307,
+           -0.16658660612693424,
+           -0.15320947871980137,
+           -0.1426173235133467,
+           -0.13433522069218043,
+           -0.1278375439428581,
+           -0.12256420598265305,
+           -0.11793760506717699,
+           -0.11337982152830535,
+           -0.1083296092572764,
+           -0.10225873451887725,
+           -0.0946872333494397,
+           -0.08519718855616175,
+           -0.07344466722671239,
+           -0.05916950865111493,
+           -0.042202709399322816,
+           -0.022471215538103013,
+           -2.2181305355445907e-16
+          ],
+          [
+           0,
+           0.025152089929553537,
+           0.052507648535497595,
+           0.08173186284284138,
+           0.11241856948422915,
+           0.1441018492650197,
+           0.17626935396744808,
+           0.20837701159641897,
+           0.23986471956042044,
+           0.27017260855085956,
+           0.29875744381980324,
+           0.32510872557941134,
+           0.34876405649711817,
+           0.3693233615971161,
+           0.38646157387996904,
+           0.39993943694839285,
+           0.40961212293678445,
+           0.41543541891485497,
+           0.4174692963023544,
+           0.41587874415762793,
+           0.41093181682591484,
+           0.4029949176065075,
+           0.39252541103173516,
+           0.38006172525850074,
+           0.3662111712152837,
+           0.3516357648755159,
+           0.3370363918253757,
+           0.3231356978139453,
+           0.3106601240736729,
+           0.3003215309694018,
+           0.2927988673207014,
+           0.28872034516313505,
+           0.288646570670019,
+           0.2930550616329018,
+           0.3023265507633214,
+           0.3167334328669417,
+           0.336430663642669,
+           0.361449359690155,
+           0.3916932846836528,
+           0.426938337166033,
+           0.46683508273577284,
+           0.5109142993260246,
+           0.5585954306309119,
+           0.6091977713354781,
+           0.66195414041607,
+           0.7160267370657101,
+           0.7705248192956619,
+           0.8245237993266284,
+           0.8770853136588662,
+           0.927277800110944,
+           0.9741970997928405,
+           1.0169865993054847,
+           1.0548564375245437,
+           1.087101321932212,
+           1.113116531124135,
+           1.1324117220847656,
+           1.1446222120852925,
+           1.1495174643768011,
+           1.1470065727920282,
+           1.137140611333129,
+           1.1201117890875094,
+           1.0962494265744442,
+           1.0660128450400999,
+           1.0299813334539238,
+           0.9888414272343582,
+           0.9433717963626878,
+           0.8944260969850288,
+           0.8429141884846214,
+           0.7897821561706819,
+           0.7359916072547729,
+           0.6824987240115203,
+           0.6302335625641783,
+           0.5800800785009824,
+           0.5328573417072661,
+           0.4893023728668726,
+           0.4500549937920795,
+           0.41564503408465153,
+           0.38648217884110664,
+           0.3628486776193302,
+           0.34489506527113023,
+           0.3326389722283827,
+           0.32596702720276666,
+           0.32463978085044487,
+           0.32829950658473345,
+           0.33648066615943617,
+           0.34862276456356334,
+           0.364085262696759,
+           0.3821641685902192,
+           0.40210988974706147,
+           0.42314590140881064,
+           0.4444877688610282,
+           0.4653620566462375,
+           0.48502466384717946,
+           0.5027781422431743,
+           0.5179875826515866,
+           0.5300946934010393,
+           0.5386297426499672,
+           0.5432210919452191,
+           0.5436021105991453,
+           0.5396153275795622,
+           0.531213747965719,
+           0.5184593328583763,
+           0.5015187131437758,
+           0.48065627691222784,
+           0.4562248358908694,
+           0.4286541363354364,
+           0.3984375329458357,
+           0.36611718921045205,
+           0.33226820303963034,
+           0.29748208175170754,
+           0.26235000481597925,
+           0.22744631589998884,
+           0.19331267765890836,
+           0.16044330357069078,
+           0.12927165146663583,
+           0.10015892400158012,
+           0.07338467316383193,
+           0.049139750273807105,
+           0.027521781181581065,
+           0.008533280118806759,
+           -0.007917553425986355,
+           -0.0220133806029495,
+           -0.03402170712042819,
+           -0.04428646743286008,
+           -0.053217434264635335,
+           -0.06127773559680611,
+           -0.06896981108840024,
+           -0.07682018126536769,
+           -0.08536343463202171,
+           -0.09512585932619906,
+           -0.10660915649463998,
+           -0.12027467192806675,
+           -0.1365285706665546,
+           -0.15570835654724624,
+           -0.17807110557536263,
+           -0.20378373937410527,
+           -0.23291561386853538,
+           -0.26543364005654657,
+           -0.3012000896733284,
+           -0.3399731703672712,
+           -0.38141038438515346,
+           -0.42507461348653,
+           -0.4704428026651604,
+           -0.5169170480177657,
+           -0.5638378314667154,
+           -0.6104990886010919,
+           -0.6561647470859716,
+           -0.7000863331510743,
+           -0.7415212136368325,
+           -0.779751021732665,
+           -0.814099806408551,
+           -0.8439514488582499,
+           -0.868765903997416,
+           -0.888093850865163,
+           -0.9015893720597717,
+           -0.9090203282329241,
+           -0.9102761480661611,
+           -0.9053728157386822,
+           -0.894454905166635,
+           -0.8777945816057667,
+           -0.8557875648134124,
+           -0.8289461220533315,
+           -0.7978892319733791,
+           -0.7633301299958577,
+           -0.7260615106126714,
+           -0.6869387202668468,
+           -0.646861324880054,
+           -0.6067534772964681,
+           -0.5675435409234221,
+           -0.5301434458759764,
+           -0.4954282624607087,
+           -0.46421647363141405,
+           -0.4372514131711539,
+           -0.41518431014297674,
+           -0.39855934322663533,
+           -0.387801061804389,
+           -0.38320447520192696,
+           -0.38492804867060537,
+           -0.39298977603661917,
+           -0.4072664261072541,
+           -0.4274959846831056,
+           -0.45328323820692024,
+           -0.4841083705280129,
+           -0.5193383727888217,
+           -0.5582409997848327,
+           -0.6000009459304356,
+           -0.6437378616431444,
+           -0.6885257878052348,
+           -0.733413553018552,
+           -0.7774456564278472,
+           -0.8196831484734215,
+           -0.8592240232857038,
+           -0.8952226495044382,
+           -0.9269077907584928,
+           -0.9535988022652948,
+           -0.9747196351247637,
+           -0.9898103337726988,
+           -0.9985357733911165,
+           -1.0006914513348975,
+           -0.9962062181693324,
+           -0.9851419079632676,
+           -0.9676899022302718,
+           -0.9441647355243848,
+           -0.9149949213775228,
+           -0.8807112432881888,
+           -0.8419328152294249,
+           -0.7993512681894387,
+           -0.7537134623353768,
+           -0.7058031574680131,
+           -0.6564220967302655,
+           -0.6063709695311684,
+           -0.5564307191157247,
+           -0.5073446482018132,
+           -0.4598017529546413,
+           -0.4144216818883202,
+           -0.3717416729447891,
+           -0.33220577011138935,
+           -0.29615656181889555,
+           -0.2638296185074907,
+           -0.23535073779405863,
+           -0.21073603435354216,
+           -0.18989483972873633,
+           -0.17263530660583934,
+           -0.1586725444021897,
+           -0.14763904999459834,
+           -0.13909714063805123,
+           -0.13255304699272236,
+           -0.127472283905694,
+           -0.1232958861719336,
+           -0.11945707666786967,
+           -0.11539792548449611,
+           -0.11058556118124263,
+           -0.10452750894983595,
+           -0.09678575495146022,
+           -0.08698917073221143,
+           -0.0748439755376097,
+           -0.06014196641110536,
+           -0.042766304844330714,
+           -0.022694712948131857,
+           -2.232131868199314e-16
+          ],
+          [
+           0,
+           0.025118216946375324,
+           0.052231489732126664,
+           0.08097944879127424,
+           0.11093852436976846,
+           0.1416341366266994,
+           0.17255437348780828,
+           0.2031647923449387,
+           0.23292395162453883,
+           0.2612992582546465,
+           0.2877827076600574,
+           0.3119060943601645,
+           0.3332552835108989,
+           0.35148315652640244,
+           0.36632087667730534,
+           0.37758716247908414,
+           0.38519530671292596,
+           0.38915773581436697,
+           0.38958796669896156,
+           0.3866998843076517,
+           0.3808043315857003,
+           0.37230307253783007,
+           0.36168025669279796,
+           0.34949157805505954,
+           0.3363513817819289,
+           0.3229180258757577,
+           0.30987785174578664,
+           0.297928155381581,
+           0.2877595791115193,
+           0.280038361756971,
+           0.27538889195449245,
+           0.27437700529364567,
+           0.27749445077167423,
+           0.28514492623757753,
+           0.2976320465930078,
+           0.31514956339355227,
+           0.33777410124012003,
+           0.36546061625924325,
+           0.3980407165086321,
+           0.43522391491212004,
+           0.4766018140249902,
+           0.5216551503102166,
+           0.5697635554337233,
+           0.6202178250954067,
+           0.6722344237605618,
+           0.7249718978854235,
+           0.7775488222282768,
+           0.8290628648026568,
+           0.8786105269413778,
+           0.9253070965362202,
+           0.9683063452730358,
+           1.006819504797304,
+           1.040133072143182,
+           1.0676250210852527,
+           1.0887790327030022,
+           1.103196404506571,
+           1.1106053518493633,
+           1.110867476734502,
+           1.1039812460209708,
+           1.0900823918283582,
+           1.069441219906899,
+           1.042456885108305,
+           1.0096487650785062,
+           0.9716451321452263,
+           0.9291693874169018,
+           0.8830241787882791,
+           0.8340737744613579,
+           0.7832251045277583,
+           0.7314079141300752,
+           0.6795544919790656,
+           0.6285794470679099,
+           0.5793600040849819,
+           0.5327172743536697,
+           0.4893989344697096,
+           0.450063709780377,
+           0.41526801532614427,
+           0.38545505394620155,
+           0.36094661124148353,
+           0.3419377214710661,
+           0.3284943088446851,
+           0.32055383677531346,
+           0.3179289252347359,
+           0.32031382518483026,
+           0.3272935708770177,
+           0.3383555672844036,
+           0.3529033126000731,
+           0.37027190598967147,
+           0.3897449498258178,
+           0.4105724244358052,
+           0.43198909269914154,
+           0.45323298211340834,
+           0.4735634934089267,
+           0.4922786973610903,
+           0.5087314047753907,
+           0.522343628089974,
+           0.5326190957895481,
+           0.5391535317602761,
+           0.5416424695443759,
+           0.5398864347139786,
+           0.5337933956828279,
+           0.523378452526262,
+           0.5087608030493133,
+           0.4901580936876834,
+           0.46787832814176783,
+           0.4423095673036231,
+           0.4139077085346001,
+           0.3831826793377717,
+           0.3506834187854074,
+           0.31698204876787456,
+           0.2826576555289983,
+           0.24828010960629854,
+           0.21439434903492022,
+           0.18150553660780894,
+           0.15006547748945495,
+           0.1204606491952212,
+           0.09300215275732307,
+           0.06791784290915201,
+           0.04534683763416459,
+           0.025336544908724813,
+           0.007842278510276145,
+           -0.0072705329610727055,
+           -0.020221607468484754,
+           -0.031308671047595604,
+           -0.0408981118978444,
+           -0.0494136773135506,
+           -0.05732351509857116,
+           -0.06512590477533307,
+           -0.07333405873421195,
+           -0.08246039858223668,
+           -0.09300072669505798,
+           -0.10541871696798677,
+           -0.12013114188618708,
+           -0.13749423544992204,
+           -0.15779156362697203,
+           -0.1812237365490434,
+           -0.20790025055243835,
+           -0.23783369453473188,
+           -0.2709364952984694,
+           -0.30702031207697844,
+           -0.3457981229028042,
+           -0.38688897658243554,
+           -0.42982531551522296,
+           -0.47406270816695,
+           -0.5189917673574523,
+           -0.5639519732336561,
+           -0.6082470693302026,
+           -0.6511616577575802,
+           -0.6919785863906381,
+           -0.7299966978196422,
+           -0.7645484973833283,
+           -0.7950172961759506,
+           -0.8208533945814637,
+           -0.8415888924350869,
+           -0.8568507428715316,
+           -0.8663717075561173,
+           -0.8699989203336478,
+           -0.867699823175764,
+           -0.8595653012770103,
+           -0.845809911704749,
+           -0.8267691704927457,
+           -0.8028939347513108,
+           -0.7747419874832441,
+           -0.7429670015900497,
+           -0.7083051243257033,
+           -0.671559482601136,
+           -0.6335829615918631,
+           -0.5952596527568056,
+           -0.557485401545933,
+           -0.5211479088964681,
+           -0.48710685348480487,
+           -0.4561745032742096,
+           -0.429097275114946,
+           -0.40653868023034034,
+           -0.38906406184983744,
+           -0.377127489781155,
+           -0.37106112634394595,
+           -0.3710673200326879,
+           -0.3772136189413931,
+           -0.3894308269272392,
+           -0.4075141533907889,
+           -0.43112743415911553,
+           -0.45981032805932415,
+           -0.49298832313654106,
+           -0.5299853198201898,
+           -0.5700384972958348,
+           -0.6123151153802066,
+           -0.655930858633777,
+           -0.6999692933821504,
+           -0.7435019826253241,
+           -0.7856087891089402,
+           -0.8253978934609655,
+           -0.862025062330272,
+           -0.8947117206900113,
+           -0.9227614124044877,
+           -0.9455742730573451,
+           -0.9626591879119979,
+           -0.9736433645138729,
+           -0.9782791124514102,
+           -0.9764476906172057,
+           -0.9681601532850914,
+           -0.9535551987011758,
+           -0.9328940959033379,
+           -0.9065528353727846,
+           -0.8750117151770291,
+           -0.8388426348776338,
+           -0.7986944231769979,
+           -0.7552765707685744,
+           -0.7093417760412116,
+           -0.6616677373102392,
+           -0.6130386404972967,
+           -0.5642267953172854,
+           -0.5159748659893976,
+           -0.4689791244816358,
+           -0.42387412580773415,
+           -0.3812191666632312,
+           -0.34148684169551907,
+           -0.3050539571474639,
+           -0.2721950008775686,
+           -0.24307830237403683,
+           -0.21776494799009014,
+           -0.1962104469490682,
+           -0.1782690744444217,
+           -0.1637007511205627,
+           -0.15218025503643204,
+           -0.14330850445570245,
+           -0.1366255989080957,
+           -0.1316252631833777,
+           -0.12777030530581715,
+           -0.12450867591335532,
+           -0.12128970340181379,
+           -0.11758007699384866,
+           -0.11287915858578418,
+           -0.10673322357016411,
+           -0.09874826031785719,
+           -0.08860099686684032,
+           -0.07604787060632567,
+           -0.06093171115614637,
+           -0.043185966834339534,
+           -0.022836369548454215,
+           -2.237715756273732e-16
+          ],
+          [
+           0,
+           0.024984485578599988,
+           0.051747927101542704,
+           0.0799096706060134,
+           0.10903415398926151,
+           0.13864352772513253,
+           0.16823151885309426,
+           0.19727816866291975,
+           0.22526505095827318,
+           0.2516905643060041,
+           0.2760848886166462,
+           0.29802420384497214,
+           0.317143786372492,
+           0.33314962630124906,
+           0.34582824576538224,
+           0.35505444353635807,
+           0.36079674353243574,
+           0.3631203830340062,
+           0.36218773899605766,
+           0.3582561562664525,
+           0.3516732081197253,
+           0.3428694856239133,
+           0.3323490763050623,
+           0.32067795274412936,
+           0.30847054660907397,
+           0.29637483179584184,
+           0.285056280595094,
+           0.27518108808214997,
+           0.2673990814324401,
+           0.26232674202303885,
+           0.2605307686786011,
+           0.26251260020842687,
+           0.268694294678325,
+           0.27940613214599264,
+           0.29487626759157004,
+           0.31522271245800887,
+           0.3404478677499729,
+           0.3704357703763239,
+           0.4049521488578342,
+           0.4436473162665197,
+           0.48606185899404586,
+           0.5316350113708164,
+           0.5797155399680375,
+           0.6295748992500219,
+           0.680422363645181,
+           0.7314217914790002,
+           0.7817096347990071,
+           0.8304137769584633,
+           0.8766727577242972,
+           0.919654934201523,
+           0.9585771253262608,
+           0.9927222981095031,
+           1.0214558749812674,
+           1.0442402729931919,
+           1.060647326538269,
+           1.0703682946568454,
+           1.0732212107260573,
+           1.069155395002775,
+           1.0582530175883575,
+           1.0407276692779368,
+           1.0169199687489974,
+           0.9872903049074443,
+           0.9524088812325414,
+           0.9129432929904574,
+           0.869643926662495,
+           0.8233275224371412,
+           0.7748592838944627,
+           0.7251339530180205,
+           0.6750562925820731,
+           0.6255214312058044,
+           0.5773955286295024,
+           0.5314972100059436,
+           0.48858019844056255,
+           0.44931754514678035,
+           0.414287817151049,
+           0.38396355446214525,
+           0.3587022531967033,
+           0.3387400696939298,
+           0.3241883746686342,
+           0.3150332175643102,
+           0.31113769116637113,
+           0.3122471169366902,
+           0.31799690413557186,
+           0.3279228722504027,
+           0.3414737680978327,
+           0.3580256576190489,
+           0.37689782908558644,
+           0.39736981021552187,
+           0.41869907737969575,
+           0.4401390212218448,
+           0.46095672993233244,
+           0.4804501591428591,
+           0.4979642757218156,
+           0.512905791158025,
+           0.5247561379867962,
+           0.5330823888682249,
+           0.5375458712997281,
+           0.5379082901821175,
+           0.5340352340680719,
+           0.5258970073050659,
+           0.5135667977776007,
+           0.4972162568681211,
+           0.47710863292230377,
+           0.45358966031236325,
+           0.42707646163096474,
+           0.3980447692450313,
+           0.36701481319097484,
+           0.3345362541996091,
+           0.3011725627249494,
+           0.2674852566856885,
+           0.23401841193881148,
+           0.20128385028325427,
+           0.16974739029367697,
+           0.139816517024096,
+           0.11182978835637233,
+           0.08604824948310448,
+           0.06264907389247233,
+           0.04172159061901732,
+           0.02326579493104495,
+           0.0071933746333326136,
+           -0.006668781576377803,
+           -0.018572692078479693,
+           -0.028841167266445294,
+           -0.037857690192037094,
+           -0.04605456415769061,
+           -0.0538996440303302,
+           -0.06188200547675443,
+           -0.07049693468088056,
+           -0.08023063967142878,
+           -0.09154509268525038,
+           -0.10486341079517827,
+           -0.12055616938482974,
+           -0.13892902026228354,
+           -0.16021195383174622,
+           -0.18455050359075253,
+           -0.21199914231555486,
+           -0.24251706386085356,
+           -0.27596648391958845,
+           -0.3121135288832912,
+           -0.35063171572580276,
+           -0.3911079592689017,
+           -0.43305097795487046,
+           -0.4759019069953096,
+           -0.5190468700632248,
+           -0.5618312090111979,
+           -0.6035750267493469,
+           -0.6435896625390466,
+           -0.6811946924788871,
+           -0.7157350315724803,
+           -0.7465977079171016,
+           -0.7732278844198841,
+           -0.7951437189496343,
+           -0.8119496796174758,
+           -0.8233479673420117,
+           -0.8291477421458957,
+           -0.829271901680804,
+           -0.8237612190217192,
+           -0.8127757103802589,
+           -0.7965931705027144,
+           -0.7756048824933583,
+           -0.7503085779397405,
+           -0.7212987908087056,
+           -0.6892548129590595,
+           -0.6549265186840676,
+           -0.6191183789754917,
+           -0.5826720318633024,
+           -0.5464478120898809,
+           -0.5113056705967293,
+           -0.47808593114381326,
+           -0.44759033741028914,
+           -0.42056383896836125,
+           -0.39767754867780003,
+           -0.37951327768286997,
+           -0.3665500179304299,
+           -0.3591526968362989,
+           -0.3575634754969397,
+           -0.3618958019618153,
+           -0.37213136599878655,
+           -0.388120033080002,
+           -0.4095827646577767,
+           -0.4361174609066707,
+           -0.4672075927036512,
+           -0.5022334233911147,
+           -0.5404855594284823,
+           -0.5811805138809794,
+           -0.6234779191589527,
+           -0.6664989866609,
+           -0.7093457819264742,
+           -0.7511208652720891,
+           -0.7909468401061591,
+           -0.827985354381991,
+           -0.8614551148524329,
+           -0.8906484985815938,
+           -0.9149463809267133,
+           -0.9338308430652548,
+           -0.9468954740241665,
+           -0.9538530407899838,
+           -0.954540363996972,
+           -0.9489203043342341,
+           -0.9370808345214467,
+           -0.919231241768071,
+           -0.895695574338254,
+           -0.866903511515195,
+           -0.8333788972943583,
+           -0.7957262330514593,
+           -0.7546154718992345,
+           -0.7107654963234868,
+           -0.6649266900446346,
+           -0.6178630341941556,
+           -0.570334166387372,
+           -0.5230778389407297,
+           -0.47679319941705806,
+           -0.4321252932452617,
+           -0.3896511549669742,
+           -0.3498678125672075,
+           -0.3131824794237545,
+           -0.2799051519270656,
+           -0.2502437692049086,
+           -0.22430202618508904,
+           -0.20207986408126405,
+           -0.1834765949725103,
+           -0.16829655115111625,
+           -0.15625708698016572,
+           -0.1469987026980853,
+           -0.14009700737794273,
+           -0.13507619338664345,
+           -0.13142365829826422,
+           -0.12860538318758108,
+           -0.12608165921928322,
+           -0.12332274785821508,
+           -0.11982406399710953,
+           -0.11512048570639727,
+           -0.10879941876974479,
+           -0.10051227804095358,
+           -0.08998409006917467,
+           -0.07702097130263329,
+           -0.06151529222267146,
+           -0.04344839855197037,
+           -0.02289082467708968,
+           -2.2345117074042243e-16
+          ],
+          [
+           0,
+           0.024749659003940286,
+           0.051057483224821926,
+           0.07852779440530398,
+           0.1067183328893848,
+           0.13515314703805678,
+           0.1633364843951698,
+           0.19076731364222846,
+           0.21695408919016876,
+           0.2414293630099294,
+           0.26376385119526086,
+           0.28357957571885933,
+           0.30056172457088054,
+           0.31446890539544997,
+           0.3251415080720446,
+           0.3325079394182679,
+           0.3365885471249057,
+           0.3374971088218719,
+           0.3354398243394739,
+           0.33071181321088045,
+           0.32369118364816385,
+           0.3148308019973067,
+           0.30464795145112566,
+           0.2937121240594298,
+           0.2826312394192634,
+           0.27203662559654274,
+           0.26256713174237317,
+           0.2548527666457562,
+           0.24949827245834785,
+           0.24706704762853224,
+           0.24806582753678452,
+           0.25293051553524215,
+           0.2620135314201613,
+           0.27557300941202734,
+           0.29376413432226506,
+           0.31663285379730655,
+           0.34411214758577985,
+           0.3760209730639879,
+           0.41206594129119584,
+           0.4518457112460702,
+           0.4948580232600183,
+           0.5405092276571516,
+           0.5881261028424384,
+           0.6369697000807809,
+           0.6862509013972296,
+           0.7351473336692997,
+           0.7828212471620253,
+           0.8284379413521699,
+           0.8711843055467141,
+           0.9102870369226205,
+           0.9450301043433319,
+           0.9747710425255282,
+           0.9989556874621679,
+           1.0171309998309763,
+           1.0289556675735139,
+           1.0342082308482783,
+           1.03279253088482,
+           1.0247403474816874,
+           1.0102111564651735,
+           0.989489006740985,
+           0.9629765849660108,
+           0.9311866026787399,
+           0.8947307043287785,
+           0.8543061534910767,
+           0.8106806072075754,
+           0.7646753335882791,
+           0.7171472644284257,
+           0.6689703017712749,
+           0.6210163144120137,
+           0.5741362668892421,
+           0.5291419193969533,
+           0.4867885223825097,
+           0.4477589047448474,
+           0.41264932013040734,
+           0.38195737269465846,
+           0.35607229291960935,
+           0.33526777690356196,
+           0.3196975403752925,
+           0.3093936730576292,
+           0.30426781152508026,
+           0.30411508101931767,
+           0.30862069046009993,
+           0.3173690017339362,
+           0.3298548357964818,
+           0.345496725608995,
+           0.363651780714681,
+           0.3836317914354518,
+           0.4047201731126494,
+           0.4261893331751074,
+           0.4473180364970523,
+           0.46740834765332956,
+           0.4858017421778916,
+           0.5018940024151565,
+           0.5151485464080563,
+           0.5251078796461045,
+           0.5314029083466345,
+           0.5337599080250405,
+           0.532005001035495,
+           0.5260660600255608,
+           0.5159720192599351,
+           0.5018496409038283,
+           0.4839178469894427,
+           0.46247978833467596,
+           0.43791287763718756,
+           0.41065706394245877,
+           0.3812016684470354,
+           0.3500711360958457,
+           0.3178100828222925,
+           0.284968033948251,
+           0.25208425483912494,
+           0.21967307028136754,
+           0.18821005435705612,
+           0.15811944822520388,
+           0.12976312981797902,
+           0.10343141788323555,
+           0.07933594411879918,
+           0.05760477259226138,
+           0.03827988661245973,
+           0.02131710121669487,
+           0.006588396036036801,
+           -0.006113399890878888,
+           -0.017067701164131647,
+           -0.026617224746539107,
+           -0.03515725535062222,
+           -0.04312340545024727,
+           -0.050978197470748166,
+           -0.05919682691141869,
+           -0.0682524871660809,
+           -0.0786016490659459,
+           -0.09066969035458576,
+           -0.10483726235155648,
+           -0.1214277631583702,
+           -0.14069625934819677,
+           -0.16282016183880724,
+           -0.1878919174797517,
+           -0.21591392689305586,
+           -0.24679584256828074,
+           -0.2803543405453483,
+           -0.316315395745829,
+           -0.35431902672671745,
+           -0.3939264119498918,
+           -0.4346292181926705,
+           -0.47586092402485525,
+           -0.5170098688087049,
+           -0.5574337117755226,
+           -0.596474947569511,
+           -0.6334770952085872,
+           -0.6678011574593051,
+           -0.6988419376901763,
+           -0.7260438016364489,
+           -0.7489154822057689,
+           -0.7670435462465427,
+           -0.7801041726057267,
+           -0.7878729300963547,
+           -0.7902322912308289,
+           -0.78717667160777,
+           -0.7788148443505657,
+           -0.765369642528353,
+           -0.7471749284856417,
+           -0.7246698758412468,
+           -0.6983906759425527,
+           -0.6689598441456212,
+           -0.6370733608606408,
+           -0.6034859363765551,
+           -0.5689947357127197,
+           -0.5344219389587359,
+           -0.5005965427717957,
+           -0.468335829139793,
+           -0.4384269376624675,
+           -0.41160897717975864,
+           -0.38855610157260917,
+           -0.36986195322377263,
+           -0.35602584645567453,
+           -0.3474410230019842,
+           -0.3443852631866487,
+           -0.34701408114580656,
+           -0.3553566714736501,
+           -0.36931470958070967,
+           -0.3886640404028792,
+           -0.4130592215359391,
+           -0.44204081906089315,
+           -0.4750452889198917,
+           -0.5114172152922809,
+           -0.5504236214992487,
+           -0.5912700198934511,
+           -0.6331178261587932,
+           -0.6751027314502078,
+           -0.716353603617446,
+           -0.756011476913732,
+           -0.7932481883693129,
+           -0.8272842284308688,
+           -0.8574053932894979,
+           -0.8829778560466778,
+           -0.9034613127614728,
+           -0.9184199065215567,
+           -0.927530686823667,
+           -0.9305894214026371,
+           -0.9275136417411307,
+           -0.9183428702510629,
+           -0.9032360449063057,
+           -0.8824662242654819,
+           -0.856412720712765,
+           -0.8255508707815085,
+           -0.7904397071258418,
+           -0.7517078457188117,
+           -0.7100379429992929,
+           -0.6661501099772856,
+           -0.6207846929719494,
+           -0.5746848431720075,
+           -0.5285792992985057,
+           -0.483165799298187,
+           -0.4390955184432509,
+           -0.3969589029528011,
+           -0.35727323101542996,
+           -0.3204721878338705,
+           -0.28689768918169145,
+           -0.25679413027617476,
+           -0.230305174983654,
+           -0.20747313603517517,
+           -0.1882409316527956,
+           -0.17245653940125383,
+           -0.15987980579662797,
+           -0.15019141177240194,
+           -0.14300374097415036,
+           -0.13787335134161022,
+           -0.13431471168796366,
+           -0.1318148349510539,
+           -0.1298484192005917,
+           -0.12789309683189426,
+           -0.12544439190326545,
+           -0.12202999526804094,
+           -0.11722298674585761,
+           -0.11065366255502211,
+           -0.10201966383809238,
+           -0.09109414738926341,
+           -0.07773179147640126,
+           -0.06187248662181575,
+           -0.04354262191392504,
+           -0.02285394032390664,
+           -2.2222670470174216e-16
+          ],
+          [
+           0,
+           0.02441377310898743,
+           0.05016318404030248,
+           0.07684271272354797,
+           0.10400851514698642,
+           0.13119142448994417,
+           0.15791071825474945,
+           0.18368828313752392,
+           0.20806279828561702,
+           0.23060355622455758,
+           0.2509235491430147,
+           0.2686914661982258,
+           0.28364227460331537,
+           0.295586092808363,
+           0.3044151072020162,
+           0.31010833336149946,
+           0.31273407772319667,
+           0.3124500142571254,
+           0.30950085183101195,
+           0.3042136299053023,
+           0.29699074144741366,
+           0.2883008409450199,
+           0.27866785064113875,
+           0.2686583282064125,
+           0.25886750273069825,
+           0.2499043220397444,
+           0.2423758819925236,
+           0.23687162686996924,
+           0.2339477187337239,
+           0.2341119724623016,
+           0.23780974205739674,
+           0.24541112299851364,
+           0.257199805395414,
+           0.27336387416140806,
+           0.29398880633557467,
+           0.3190528631382403,
+           0.3484250166338406,
+           0.38186548941217663,
+           0.41902892199287034,
+           0.45947011827730405,
+           0.5026522559064295,
+           0.5479573874012836,
+           0.5946990009775596,
+           0.6421363583521126,
+           0.6894902819831847,
+           0.7359600271299017,
+           0.7807408458120668,
+           0.8230418309163173,
+           0.862103619815209,
+           0.8972155381834492,
+           0.9277317762014734,
+           0.9530862107716433,
+           0.9728055182327806,
+           0.9865202616087869,
+           0.9939736837166607,
+           0.9950279913472081,
+           0.98966797491411,
+           0.9780018710085859,
+           0.9602594406668052,
+           0.9367873022664122,
+           0.9080416232088748,
+           0.8745783373283568,
+           0.8370411137672169,
+           0.7961473564423475,
+           0.752672559896709,
+           0.7074333861524351,
+           0.6612698572137915,
+           0.615027078383255,
+           0.5695369180588201,
+           0.5256000699267026,
+           0.4839689134544349,
+           0.44533156857858924,
+           0.4102975109683437,
+           0.3793850759617355,
+           0.35301113316127813,
+           0.33148316087579316,
+           0.3149938914045694,
+           0.3036186360078423,
+           0.29731533381844616,
+           0.2959273035057136,
+           0.2991886118047792,
+           0.30673191065225486,
+           0.3180985361425509,
+           0.33275060926054034,
+           0.35008483164602644,
+           0.36944763062995795,
+           0.3901512773862141,
+           0.41149058098652064,
+           0.43275974991799165,
+           0.4532690114678516,
+           0.47236058829343985,
+           0.48942365022427486,
+           0.5039078873910919,
+           0.5153353874191258,
+           0.5233105437230814,
+           0.5275277727748785,
+           0.5277768742988604,
+           0.5239459282713856,
+           0.5160216848593933,
+           0.5040874664676345,
+           0.48831866330289747,
+           0.468975963755298,
+           0.4463965169527911,
+           0.4209832756757925,
+           0.3931928121676092,
+           0.3635219361513665,
+           0.33249347266472895,
+           0.3006415764631137,
+           0.2684969692641672,
+           0.23657248579636278,
+           0.20534930450505173,
+           0.17526421913810533,
+           0.14669827879683917,
+           0.11996708713821379,
+           0.09531300719964984,
+           0.07289946791947517,
+           0.05280751312937458,
+           0.035034675007604106,
+           0.019496193197193996,
+           0.0060285395549987564,
+           -0.005604851641113062,
+           -0.015705805713233056,
+           -0.024631792949091104,
+           -0.03278473642060516,
+           -0.04059854269852868,
+           -0.048525689534651334,
+           -0.05702322964824088,
+           -0.06653858561505978,
+           -0.07749551710645274,
+           -0.09028063819574883,
+           -0.1052308492189564,
+           -0.12262202507018923,
+           -0.14265927038963952,
+           -0.16546901264589634,
+           -0.19109315761072887,
+           -0.21948547933739068,
+           -0.25051035979677366,
+           -0.28394393322981426,
+           -0.3194776285510685,
+           -0.35672404134192554,
+           -0.39522500666195887,
+           -0.4344616866080526,
+           -0.4738664337151357,
+           -0.5128361442625917,
+           -0.5507467755267587,
+           -0.5869686690296646,
+           -0.6208822987056387,
+           -0.6518940492493023,
+           -0.67945162609425,
+           -0.7030587046298484,
+           -0.7222884422741725,
+           -0.7367955025184116,
+           -0.7463262744391767,
+           -0.7507270136147131,
+           -0.7499496798514156,
+           -0.7440553024235346,
+           -0.7332147632993951,
+           -0.7177069516056593,
+           -0.6979143068230631,
+           -0.6743158323288307,
+           -0.64747772331844,
+           -0.6180418123070013,
+           -0.5867120898599612,
+           -0.5542396065789345,
+           -0.5214061034640253,
+           -0.4890067505582106,
+           -0.4578323974249068,
+           -0.4286517529131487,
+           -0.40219391546052313,
+           -0.3791316687557537,
+           -0.3600659410646137,
+           -0.3455118002975757,
+           -0.33588632158683956,
+           -0.33149862058951846,
+           -0.33254229499182,
+           -0.3390904599821399,
+           -0.3510935021631118,
+           -0.368379611971291,
+           -0.390658088733159,
+           -0.41752534661099566,
+           -0.44847348548466126,
+           -0.4829012298381592,
+           -0.5201269824570317,
+           -0.5594036895630295,
+           -0.5999351711363842,
+           -0.6408935356445935,
+           -0.6814372730468361,
+           -0.720729604386969,
+           -0.7579566608975327,
+           -0.7923450704352072,
+           -0.8231785441256718,
+           -0.8498130809352924,
+           -0.8716904418913334,
+           -0.888349588000637,
+           -0.8994358255248986,
+           -0.9047074579375879,
+           -0.9040398042447032,
+           -0.8974265069175926,
+           -0.8849781179026334,
+           -0.866918016443408,
+           -0.8435757761809578,
+           -0.8153781596321784,
+           -0.7828379742096365,
+           -0.7465410740775313,
+           -0.70713183512605,
+           -0.6652974651563441,
+           -0.6217515371707576,
+           -0.5772171498513096,
+           -0.5324101255162973,
+           -0.4880226519496314,
+           -0.4447077606295413,
+           -0.40306501041850074,
+           -0.3636277133267778,
+           -0.3268519983616627,
+           -0.29310796175642334,
+           -0.2626730982454582,
+           -0.2357281498663924,
+           -0.21235544748784252,
+           -0.1925397574187311,
+           -0.1761715826221784,
+           -0.1630528068011106,
+           -0.15290451146824421,
+           -0.14537674250370583,
+           -0.1400599549664499,
+           -0.1364978242387695,
+           -0.13420107894588926,
+           -0.13266198730096365,
+           -0.1313691141530927,
+           -0.12982196139856644,
+           -0.12754510964486057,
+           -0.12410149393726722,
+           -0.11910447057097336,
+           -0.11222836488572438,
+           -0.10321723062803531,
+           -0.09189159892424073,
+           -0.07815304792430992,
+           -0.06198648140073544,
+           -0.04346006456362624,
+           -0.022722826559114843,
+           -2.2008475618636407e-16
+          ],
+          [
+           0,
+           0.023978109509972444,
+           0.04907046907590925,
+           0.07486675854741298,
+           0.1009264224258172,
+           0.1267916324903494,
+           0.1520007890904019,
+           0.17610219938279587,
+           0.19866756548724976,
+           0.21930491964541682,
+           0.23767065690343503,
+           0.2534803382646279,
+           0.26651796812074785,
+           0.27664348829699487,
+           0.28379827627424536,
+           0.28800848594800965,
+           0.2893861243726597,
+           0.28812781593675635,
+           0.28451126486114076,
+           0.2788894863074005,
+           0.2716829342307837,
+           0.2633697089453184,
+           0.2544740777994313,
+           0.2455535871051922,
+           0.23718508138079616,
+           0.2299499760801479,
+           0.22441915151465952,
+           0.22113784805295994,
+           0.22061094557376426,
+           0.22328900344166816,
+           0.22955542111022,
+           0.23971505420261793,
+           0.25398458717636985,
+           0.27248492225561755,
+           0.2952357962177666,
+           0.322152783022096,
+           0.3530467824789138,
+           0.3876260345974212,
+           0.42550063740948757,
+           0.4661894844708311,
+           0.5091294784137752,
+           0.5536868203494201,
+           0.5991701229972165,
+           0.644845049449718,
+           0.689950140608787,
+           0.7337134635327387,
+           0.7753696909906236,
+           0.8141772099921282,
+           0.8494348542805079,
+           0.8804978628333783,
+           0.9067926831619193,
+           0.9278302642446651,
+           0.9432175186598237,
+           0.9526666760584439,
+           0.956002299524189,
+           0.9531657913999807,
+           0.9442172744938381,
+           0.9293347967658584,
+           0.9088108711341428,
+           0.8830464253742631,
+           0.8525422986831271,
+           0.8178884798344428,
+           0.7797513355484922,
+           0.7388591254267909,
+           0.6959861404012037,
+           0.6519358341306597,
+           0.6075233403588942,
+           0.563557783353692,
+           0.5208247928444881,
+           0.4800696292630018,
+           0.4419813097165864,
+           0.40717810036977387,
+           0.3761947073900816,
+           0.3494714571569272,
+           0.32734570805901547,
+           0.31004568210554556,
+           0.2976868460787553,
+           0.2902709104946965,
+           0.28768745172116944,
+           0.2897180997657918,
+           0.2960431730278624,
+           0.30625058319763415,
+           0.3198467798993267,
+           0.33626945690952986,
+           0.35490170099458723,
+           0.3750872315793073,
+           0.39614635536692827,
+           0.4173922452418941,
+           0.43814714763693724,
+           0.45775812713011876,
+           0.4756119712108683,
+           0.4911489015351353,
+           0.5038747699699917,
+           0.5133714574873843,
+           0.5193052404944348,
+           0.5214329413072432,
+           0.5196057358743916,
+           0.513770551119375,
+           0.5039690449146464,
+           0.4903342222091319,
+           0.47308479969820566,
+           0.452517487186623,
+           0.4289974050677478,
+           0.402946902858564,
+           0.37483308236761614,
+           0.3451543598846281,
+           0.31442642401593146,
+           0.28316795891481283,
+           0.2518865063654327,
+           0.22106483440418165,
+           0.19114816507241933,
+           0.16253258989186328,
+           0.13555496936385947,
+           0.11048457304916981,
+           0.08751667060442246,
+           0.06676823271446745,
+           0.048275845476730715,
+           0.03199588387248482,
+           0.01780693097165863,
+           0.005514370958983455,
+           -0.00514297257517227,
+           -0.014484334930033087,
+           -0.022876875619272454,
+           -0.030724183828305197,
+           -0.03845373274999222,
+           -0.04650361926605357,
+           -0.055308944534726005,
+           -0.065288201021385,
+           -0.0768300321085695,
+           -0.09028072162178558,
+           -0.10593275262116576,
+           -0.12401474808156315,
+           -0.14468307128056232,
+           -0.1680153217047527,
+           -0.19400591412130494,
+           -0.222563875352431,
+           -0.2535129365686339,
+           -0.28659394000940686,
+           -0.3214695194310657,
+           -0.3577309547741966,
+           -0.3949070450240763,
+           -0.43247479043760645,
+           -0.4698716275704499,
+           -0.5065089190746412,
+           -0.5417863661115248,
+           -0.5751069853176121,
+           -0.6058922752481849,
+           -0.6335971895606197,
+           -0.6577245361095448,
+           -0.677838432593337,
+           -0.6935764701622606,
+           -0.7046602659862927,
+           -0.7109041234781935,
+           -0.7122215637641106,
+           -0.7086295429982128,
+           -0.700250225983593,
+           -0.6873102459193036,
+           -0.6701374414837455,
+           -0.6491551243746478,
+           -0.6248739913263458,
+           -0.5978818530084931,
+           -0.5688314066281169,
+           -0.5384263281556435,
+           -0.5074060026499277,
+           -0.47652924610204306,
+           -0.4465573986720497,
+           -0.418237186484759,
+           -0.39228375683183386,
+           -0.3693642894858999,
+           -0.3500825748973269,
+           -0.33496492858570903,
+           -0.3244477805606757,
+           -0.31886723983730125,
+           -0.31845088798134175,
+           -0.3233120032421934,
+           -0.3334463594742866,
+           -0.34873168310178965,
+           -0.3689297883271025,
+           -0.39369134715379334,
+           -0.42256318813744476,
+           -0.45499795761849937,
+           -0.49036592099430265,
+           -0.5279686307211819,
+           -0.567054143439379,
+           -0.6068334319612692,
+           -0.6464976097464358,
+           -0.6852355665867681,
+           -0.7222516049960309,
+           -0.7567826674595509,
+           -0.788114755226794,
+           -0.8155981594570992,
+           -0.8386611547564734,
+           -0.8568218427480532,
+           -0.8696978783733071,
+           -0.8770138630162204,
+           -0.8786062450154721,
+           -0.8744256282937196,
+           -0.8645364522138871,
+           -0.849114068842591,
+           -0.8284393060188187,
+           -0.8028906644734098,
+           -0.7729343532641794,
+           -0.7391124186218273,
+           -0.7020292657124417,
+           -0.6623369097429234,
+           -0.6207193213823116,
+           -0.5778762509691665,
+           -0.5345069259715434,
+           -0.4912940164462294,
+           -0.44888825383232034,
+           -0.40789406957497854,
+           -0.368856592305132,
+           -0.33225030631625785,
+           -0.2984696307988225,
+           -0.26782162981314467,
+           -0.2405210085510062,
+           -0.21668749342333019,
+           -0.19634563336989885,
+           -0.1794269990211795,
+           -0.1657746964677786,
+           -0.15515005490012235,
+           -0.1472412936974908,
+           -0.14167392600114342,
+           -0.13802261359956386,
+           -0.13582415312275867,
+           -0.1345912469385678,
+           -0.13382669441116815,
+           -0.1330376307413586,
+           -0.1317494416472514,
+           -0.12951899261234237,
+           -0.12594683103888685,
+           -0.1206880478825139,
+           -0.11346152147769742,
+           -0.10405730936433584,
+           -0.0923420028908111,
+           -0.0782619129496855,
+           -0.061844012035210005,
+           -0.04319461645292795,
+           -0.022495851472507742,
+           -2.1702366992562073e-16
+          ],
+          [
+           0,
+           0.02344515379981522,
+           0.04778707359790165,
+           0.072615480156428,
+           0.0974976845866681,
+           0.12199137070647963,
+           0.14565769959541267,
+           0.16807438471782368,
+           0.1888483860942262,
+           0.20762788113780337,
+           0.2241131877132342,
+           0.2380663412735106,
+           0.24931906193113265,
+           0.2577788881723112,
+           0.2634333006025528,
+           0.2663517104474159,
+           0.26668524223288276,
+           0.2646642967588653,
+           0.2605939377281095,
+           0.25484720175608566,
+           0.2478564855402022,
+           0.2401032143391888,
+           0.2321060413259873,
+           0.2244078666721142,
+           0.21756199739140247,
+           0.2121177931858884,
+           0.20860615916323208,
+           0.2075252529138559,
+           0.20932677085138826,
+           0.21440316696595635,
+           0.22307613647913135,
+           0.23558666780735266,
+           0.252086929433788,
+           0.2726342146471633,
+           0.29718711769240574,
+           0.3256040609003698,
+           0.3576442351468006,
+           0.39297095694194323,
+           0.43115738602827147,
+           0.4716944890336922,
+           0.5140010789364836,
+           0.5574357082315559,
+           0.6013101470368521,
+           0.6449041371088743,
+           0.6874810798574994,
+           0.7283042917919361,
+           0.7666534450203029,
+           0.8018408038763877,
+           0.8332268716428156,
+           0.8602350736321065,
+           0.8823651242966817,
+           0.899204756062002,
+           0.9104395254974118,
+           0.9158604573458574,
+           0.9153693377426383,
+           0.9089815234349334,
+           0.8968261926222567,
+           0.8791440237447515,
+           0.856282349675019,
+           0.8286878948324321,
+           0.7968972602740656,
+           0.7615253754224388,
+           0.7232521834614418,
+           0.6828078693906581,
+           0.6409569742537036,
+           0.598481765309329,
+           0.5561652492584719,
+           0.5147742236578474,
+           0.47504276015153,
+           0.43765650217915775,
+           0.40323813964853494,
+           0.3723343941912421,
+           0.3454048117656287,
+           0.32281261543980344,
+           0.3048178212583968,
+           0.29157276539706356,
+           0.2831201326795065,
+           0.2793935163973538,
+           0.2802204787046501,
+           0.285328021138342,
+           0.2943503175004986,
+           0.30683850782229166,
+           0.322272303713312,
+           0.34007311325427986,
+           0.35961835873166925,
+           0.38025663377312247,
+           0.40132332845473323,
+           0.42215634213052416,
+           0.44211150426863666,
+           0.46057733342475626,
+           0.4769887833678241,
+           0.4908396528001799,
+           0.5016933703777202,
+           0.5091919089368074,
+           0.5130626309051926,
+           0.5131229196024653,
+           0.5092825071974606,
+           0.5015434680813633,
+           0.48999790488741385,
+           0.47482341188352145,
+           0.456276455552944,
+           0.43468386349370935,
+           0.4104326590398578,
+           0.38395851909567796,
+           0.3557331655933522,
+           0.32625102593145316,
+           0.29601551412400334,
+           0.2655252918003828,
+           0.23526086648350578,
+           0.20567187380421267,
+           0.1771653707776887,
+           0.1500954394860203,
+           0.12475436519904125,
+           0.10136561103096012,
+           0.0800787637453417,
+           0.060966573496769406,
+           0.044024155452463284,
+           0.029170364764570744,
+           0.016251299696855234,
+           0.005045832284917963,
+           -0.00472698686839131,
+           -0.013398851853731499,
+           -0.02134169853568506,
+           -0.028956058462919262,
+           -0.03665858259418574,
+           -0.044869069769778475,
+           -0.053997348209572416,
+           -0.06443036273508039,
+           -0.07651981577597013,
+           -0.09057069664107553,
+           -0.10683101134545943,
+           -0.1254829950409053,
+           -0.14663605155308196,
+           -0.17032162062481998,
+           -0.19649012430280907,
+           -0.22501009071960704,
+           -0.2556694976518929,
+           -0.28817932108659833,
+           -0.3221792170404481,
+           -0.3572452094949552,
+           -0.3928992049300555,
+           -0.42862010589413047,
+           -0.463856253558793,
+           -0.49803889335930124,
+           -0.5305963295372914,
+           -0.5609684144158296,
+           -0.5886210070756001,
+           -0.6130600340739324,
+           -0.63384479203651,
+           -0.6506001482061308,
+           -0.6630273199786296,
+           -0.6709129475003184,
+           -0.6741362137482372,
+           -0.6726738131848402,
+           -0.6666026219336008,
+           -0.6560999781911645,
+           -0.6414415399046326,
+           -0.6229967461628427,
+           -0.6012219678107562,
+           -0.5766514900346192,
+           -0.549886523662773,
+           -0.5215824913401832,
+           -0.4924348783319596,
+           -0.46316397440108353,
+           -0.4344988620660489,
+           -0.4071610268434848,
+           -0.38184797629758604,
+           -0.35921725655370607,
+           -0.33987124731912793,
+           -0.3243430995542994,
+           -0.3130841541450705,
+           -0.30645314585282873,
+           -0.3047074552809645,
+           -0.30799662359327473,
+           -0.31635829141321903,
+           -0.32971666601400595,
+           -0.34788356096979706,
+           -0.370561991334718,
+           -0.397352246635405,
+           -0.42776030498405615,
+           -0.4612083958786591,
+           -0.4970474681128144,
+           -0.5345712739148144,
+           -0.5730317420769713,
+           -0.6116552823546042,
+           -0.6496596415493845,
+           -0.6862709189728868,
+           -0.7207403457181616,
+           -0.7523604384234082,
+           -0.7804801538326457,
+           -0.8045186950546893,
+           -0.8239776533855278,
+           -0.8384512100772962,
+           -0.8476341695124288,
+           -0.8513276477173967,
+           -0.8494422967388928,
+           -0.8419990047191671,
+           -0.8291270720944727,
+           -0.8110599247198309,
+           -0.788128483420662,
+           -0.7607523650569518,
+           -0.7294291413071117,
+           -0.6947219267972093,
+           -0.6572456068201455,
+           -0.6176520457811971,
+           -0.5766146399360342,
+           -0.5348125914297555,
+           -0.4929152847979986,
+           -0.45156714188147734,
+           -0.41137331669195304,
+           -0.3728865685365103,
+           -0.33659562026122847,
+           -0.3029152696196661,
+           -0.27217847649286114,
+           -0.24463059812902682,
+           -0.22042589000497106,
+           -0.19962633270569458,
+           -0.1822027868045507,
+           -0.16803841956145035,
+           -0.15693429078903984,
+           -0.14861693186917976,
+           -0.14274770295686567,
+           -0.13893367009516228,
+           -0.13673970734892493,
+           -0.13570150004379636,
+           -0.13533910447534928,
+           -0.13517070752746602,
+           -0.13472622678437493,
+           -0.13356039798469782,
+           -0.1312650118674459,
+           -0.1274799861943163,
+           -0.1219029903817114,
+           -0.11429737892364678,
+           -0.1044982346399447,
+           -0.09241637259760974,
+           -0.07804020905827974,
+           -0.06143545564098716,
+           -0.04274265563948629,
+           -0.022172635657690988,
+           -2.1305333457443458e-16
+          ],
+          [
+           0,
+           0.022818539661675283,
+           0.046322884351881026,
+           0.0701073798304597,
+           0.0937514375932784,
+           0.11683200521684506,
+           0.1389361555201384,
+           0.15967345623392193,
+           0.17868778697258347,
+           0.1956682839715077,
+           0.2103591149453774,
+           0.22256781599343253,
+           0.2321719589865859,
+           0.23912396040299244,
+           0.2434538900652387,
+           0.2452701894798874,
+           0.2447582631986682,
+           0.24217696145632422,
+           0.2378530269090446,
+           0.2321736312202099,
+           0.2255771771765727,
+           0.2185425877003579,
+           0.21157734338791387,
+           0.20520456402390425,
+           0.1999494560215735,
+           0.19632546623574462,
+           0.19482049259626835,
+           0.19588350323731366,
+           0.19991190819252494,
+           0.2072400114484521,
+           0.2181288465762965,
+           0.23275766688013116,
+           0.25121732178695205,
+           0.2735057060131668,
+           0.2995254179773026,
+           0.3290837102173596,
+           0.3618947585343399,
+           0.3975842196026968,
+           0.43569599027203765,
+           0.4757010271321954,
+           0.5170080334825775,
+           0.5589757739165055,
+           0.6009267354734797,
+           0.6421618197607567,
+           0.6819757234702742,
+           0.7196726460030765,
+           0.7545819529431681,
+           0.7860734231643536,
+           0.8135717154533965,
+           0.8365697075143851,
+           0.8546403856873509,
+           0.8674469970643858,
+           0.8747512161199127,
+           0.8764191245141512,
+           0.8724248542551323,
+           0.8628517996659423,
+           0.8478913612585758,
+           0.8278392432621828,
+           0.8030893847645553,
+           0.7741256607838848,
+           0.7415115427203938,
+           0.7058779562496292,
+           0.6679096176268615,
+           0.6283301655299938,
+           0.5878864340968616,
+           0.5473322330185482,
+           0.5074120119439879,
+           0.4688447887591146,
+           0.43230871447487873,
+           0.3984266316654327,
+           0.3677529590322638,
+           0.3407622023339394,
+           0.31783935241050515,
+           0.29927238531790273,
+           0.28524702879340347,
+           0.275843904643663,
+           0.2710380995208328,
+           0.27070115832692043,
+           0.27460543658510694,
+           0.28243069195168985,
+           0.2937727419816761,
+           0.30815396659419003,
+           0.3250353905899705,
+           0.34383004509234083,
+           0.36391727779051297,
+           0.3846576610492073,
+           0.405408134797887,
+           0.42553701789815146,
+           0.4444385274601178,
+           0.46154646016667356,
+           0.4763467126800129,
+           0.4883883490519028,
+           0.49729296094939157,
+           0.5027621104803184,
+           0.5045826943486219,
+           0.5026301207580379,
+           0.4968692455940971,
+           0.4873530705711443,
+           0.4742192618332651,
+           0.4576846015573687,
+           0.43803753608161716,
+           0.4156290307109754,
+           0.3908619824831957,
+           0.3641794768017399,
+           0.33605220111037637,
+           0.30696534803630293,
+           0.2774053512050879,
+           0.24784679898489853,
+           0.21873986472163784,
+           0.19049857677201515,
+           0.163490228233983,
+           0.1380261953226519,
+           0.11435439564266454,
+           0.09265357413102424,
+           0.0730295562976035,
+           0.05551355679989669,
+           0.040062577665439976,
+           0.026561875983181472,
+           0.014829427005863437,
+           0.004622256704472987,
+           -0.0043555307922825744,
+           -0.01244324952456024,
+           -0.02001290888846711,
+           -0.027457560606418664,
+           -0.03517902880938672,
+           -0.04357535292256136,
+           -0.05302828094807533,
+           -0.06389114997505897,
+           -0.07647748133196969,
+           -0.09105059996043079,
+           -0.107814561777587,
+           -0.12690663965033486,
+           -0.14839157896002106,
+           -0.17225778858510785,
+           -0.19841558360632636,
+           -0.22669754338985088,
+           -0.2568609942550599,
+           -0.28859257105768826,
+           -0.32151475810265845,
+           -0.35519425820762424,
+           -0.3891519907763387,
+           -0.4228744766296403,
+           -0.45582633018092605,
+           -0.4874635492853062,
+           -0.5172472705189256,
+           -0.544657643348246,
+           -0.5692074710136965,
+           -0.5904552691473776,
+           -0.6080174051199967,
+           -0.6215790015978078,
+           -0.6309033163032501,
+           -0.63583934582924,
+           -0.6363274436881684,
+           -0.6324027905510405,
+           -0.6241966066804788,
+           -0.6119350516053779,
+           -0.5959358127691813,
+           -0.5766024418089385,
+           -0.5544165528798517,
+           -0.5299280506476295,
+           -0.503743604905701,
+           -0.47651363300710553,
+           -0.44891808932532484,
+           -0.4216513918195879,
+           -0.395406838698442,
+           -0.370860882564728,
+           -0.34865763490942114,
+           -0.3293939702432222,
+           -0.31360558657838206,
+           -0.3017543576859837,
+           -0.2942172830568052,
+           -0.29127730449101924,
+           -0.29311621462254644,
+           -0.2998098335007289,
+           -0.3113255757957757,
+           -0.32752247456442984,
+           -0.3481536691844121,
+           -0.3728713064591176,
+           -0.401233746434479,
+           -0.43271490955732644,
+           -0.46671555077681687,
+           -0.5025762002908147,
+           -0.5395914709858226,
+           -0.5770254001772314,
+           -0.6141274688156115,
+           -0.6501489254774365,
+           -0.6843590355877066,
+           -0.7160608785902922,
+           -0.7446063271284799,
+           -0.7694098624402408,
+           -0.7899609086114739,
+           -0.8058344043651656,
+           -0.8166993738083127,
+           -0.8223253059613675,
+           -0.822586205769418,
+           -0.8174622353440992,
+           -0.8070389220383186,
+           -0.7915039681975417,
+           -0.7711417546394856,
+           -0.7463256846940091,
+           -0.717508566654004,
+           -0.6852112785080321,
+           -0.650009998733345,
+           -0.6125223197631545,
+           -0.5733925857196928,
+           -0.5332768125352937,
+           -0.4928275562869145,
+           -0.45267909428339737,
+           -0.4134332732296914,
+           -0.3756463599288586,
+           -0.33981720296472384,
+           -0.3063769793296584,
+           -0.2756807589008141,
+           -0.2480010730622388,
+           -0.22352362279322274,
+           -0.20234520747408222,
+           -0.1844738998522979,
+           -0.1698314364575371,
+           -0.15825773765203424,
+           -0.14951741882239356,
+           -0.14330810526573448,
+           -0.13927031930743264,
+           -0.13699867019385448,
+           -0.13605404626320922,
+           -0.1359764855672363,
+           -0.1362983860579693,
+           -0.13655771002139022,
+           -0.1363108397710132,
+           -0.13514475262725703,
+           -0.13268820260340836,
+           -0.12862162348688663,
+           -0.12268550243959096,
+           -0.11468701395862615,
+           -0.1045047499973391,
+           -0.09209143207469489,
+           -0.07747454402596093,
+           -0.060754878327768574,
+           -0.04210304328882039,
+           -0.02175403145599287,
+           -2.0819482253951928e-16
+          ],
+          [
+           0,
+           0.022102979650571553,
+           0.044689770870207056,
+           0.0673636198895594,
+           0.08971988392536792,
+           0.11135806918340987,
+           0.13189379936133236,
+           0.1509703925348185,
+           0.16826973394659858,
+           0.18352214989091906,
+           0.196515013155302,
+           0.20709984271418005,
+           0.2151976987567931,
+           0.22080271771037088,
+           0.22398367959321588,
+           0.22488355060065177,
+           0.2237169960154174,
+           0.2207659110259523,
+           0.2163730685046627,
+           0.21093403194078306,
+           0.20488752729229412,
+           0.19870450835947892,
+           0.1928761853466354,
+           0.18790131466859344,
+           0.1842730690408242,
+           0.1824658199159356,
+           0.18292216904303868,
+           0.18604056218478698,
+           0.1921638058956722,
+           0.20156878801994568,
+           0.21445767468690824,
+           0.23095082173533027,
+           0.25108159753254605,
+           0.2747932680667779,
+           0.30193804511254624,
+           0.3322783454296491,
+           0.36549025465839596,
+           0.4011691351591296,
+           0.4388372638599777,
+           0.47795333554319325,
+           0.5179236201770877,
+           0.5581145210555428,
+           0.5978662446879907,
+           0.6365072644902818,
+           0.6733692390926719,
+           0.7078020330492474,
+           0.7391884832462808,
+           0.7669585584981042,
+           0.7906025726074775,
+           0.809683132260686,
+           0.8238455300285724,
+           0.8328263287635326,
+           0.8364599259533552,
+           0.8346829340952431,
+           0.8275362647371791,
+           0.8151648582473963,
+           0.797815057293709,
+           0.7758296780823372,
+           0.7496408882553544,
+           0.7197610526406826,
+           0.686771756513956,
+           0.6513112594863778,
+           0.6140606705174603,
+           0.5757291649557504,
+           0.5370385871940143,
+           0.49870779693693335,
+           0.4614371228705735,
+           0.4258932845561285,
+           0.39269513172288717,
+           0.36240053009606193,
+           0.33549469495915735,
+           0.3123802385052434,
+           0.2933691555409136,
+           0.27867692528903826,
+           0.2684188560396989,
+           0.26260874547200613,
+           0.26115987393227574,
+           0.26388829216359405,
+           0.2705183102996812,
+           0.2806900426946129,
+           0.2939688146297697,
+           0.30985619329749126,
+           0.3278023677622913,
+           0.3472195717520987,
+           0.3674962198704179,
+           0.388011412694129,
+           0.40814945957768345,
+           0.4273140699599791,
+           0.4449418744892926,
+           0.4605149560579459,
+           0.4735720973819532,
+           0.4837184853910216,
+           0.4906336525564336,
+           0.49407748037164134,
+           0.49389413937888343,
+           0.49001389217185576,
+           0.48245273939863004,
+           0.4713099426038221,
+           0.4567635104455632,
+           0.43906378509275296,
+           0.4185253122065656,
+           0.395517219686479,
+           0.3704523662872113,
+           0.3437755504089767,
+           0.31595109111936637,
+           0.28745010725813613,
+           0.25873782598363104,
+           0.23026124922658922,
+           0.2024374953195006,
+           0.1756431138709232,
+           0.15020464525787708,
+           0.12639066260641194,
+           0.10440549468117764,
+           0.08438478371810926,
+           0.06639298404138431,
+           0.05042285653241576,
+           0.036396961953956024,
+           0.024171104096870125,
+           0.013539623029380353,
+           0.004242390672234509,
+           -0.004026683285067372,
+           -0.01160986635301552,
+           -0.018874803602316713,
+           -0.02620299439876247,
+           -0.0339778554971273,
+           -0.04257269152108452,
+           -0.052338896657375664,
+           -0.06359470587727291,
+           -0.07661480030118265,
+           -0.09162104978369463,
+           -0.10877464695495795,
+           -0.12816985153272253,
+           -0.14982952260685795,
+           -0.1737025708279364,
+           -0.19966341315516126,
+           -0.22751346127780092,
+           -0.2569846223181263,
+           -0.28774473827854974,
+           -0.31940484023014176,
+           -0.351528045732501,
+           -0.3836398846328537,
+           -0.4152398003194009,
+           -0.4458135416744086,
+           -0.47484613620588056,
+           -0.5018351177770412,
+           -0.5263036734529227,
+           -0.5478133734925177,
+           -0.5659761564729612,
+           -0.5804652577679624,
+           -0.59102479373788,
+           -0.5974777454474511,
+           -0.5997321237492823,
+           -0.5977851412316362,
+           -0.5917252647602638,
+           -0.5817320739623232,
+           -0.56807390473524,
+           -0.5511033113885787,
+           -0.5312504349941015,
+           -0.5090144175902085,
+           -0.48495305076807227,
+           -0.45967089164030706,
+           -0.4338061181476249,
+           -0.4080164281174983,
+           -0.3829643116323877,
+           -0.3593020434541678,
+           -0.3376567510408287,
+           -0.31861591384286686,
+           -0.30271364105393284,
+           -0.2904180580000706,
+           -0.2821201062805461,
+           -0.2781240302158873,
+           -0.2786397828957516,
+           -0.28377754009654194,
+           -0.2935444606449802,
+           -0.3078437786437733,
+           -0.3264762576400194,
+           -0.34914398065164975,
+           -0.3754563943391454,
+           -0.4049384718739531,
+           -0.43704080852095634,
+           -0.47115141785183023,
+           -0.5066089559629057,
+           -0.5427170670732873,
+           -0.5787595172543264,
+           -0.6140157644378902,
+           -0.6477766027192131,
+           -0.6793595175543232,
+           -0.7081233957824656,
+           -0.7334822502968821,
+           -0.7549176432494425,
+           -0.7719895233129074,
+           -0.7843452309610094,
+           -0.7917264700169572,
+           -0.7939740927789004,
+           -0.7910305986541416,
+           -0.7829403011341669,
+           -0.769847173777347,
+           -0.7519904412718637,
+           -0.72969803527681,
+           -0.7033780852791007,
+           -0.673508660930267,
+           -0.6406260231208868,
+           -0.6053116754273057,
+           -0.5681785347012486,
+           -0.5298565588231975,
+           -0.49097818055607784,
+           -0.45216389877413504,
+           -0.414008372071955,
+           -0.3770673450623796,
+           -0.34184571493883315,
+           -0.3087870156944828,
+           -0.27826456052785925,
+           -0.25057444035554505,
+           -0.22593052907127592,
+           -0.20446159542419504,
+           -0.18621056840816538,
+           -0.17113594918170372,
+           -0.15911530911633942,
+           -0.149950761927815,
+           -0.1433762492600715,
+           -0.13906643476789407,
+           -0.13664696277323587,
+           -0.1357058049094778,
+           -0.13580539261463373,
+           -0.13649521550711638,
+           -0.13732455600014237,
+           -0.13785502920251486,
+           -0.13767260422400043,
+           -0.13639879825247392,
+           -0.13370075779262036,
+           -0.12929997165315532,
+           -0.12297939686312194,
+           -0.11458882075029259,
+           -0.10404832885259345,
+           -0.09134979797464782,
+           -0.07655638528449772,
+           -0.059800036561435344,
+           -0.04127708823094593,
+           -0.021242087351881947,
+           -2.0247989737671382e-16
+          ],
+          [
+           0,
+           0.0213041835959905,
+           0.042901394594110444,
+           0.06440769989288048,
+           0.08543782111677378,
+           0.10561663258551404,
+           0.12459041823579503,
+           0.14203758406386865,
+           0.1576785363257835,
+           0.1712844568594527,
+           0.1826847349500271,
+           0.19177284944315967,
+           0.19851053445819936,
+           0.20293010606781403,
+           0.20513487458371218,
+           0.20529761642843478,
+           0.2036571297355664,
+           0.20051294753772017,
+           0.19621833041525066,
+           0.1911717055715916,
+           0.18580676032755952,
+           0.1805814339411292,
+           0.17596608154166177,
+           0.17243110704843514,
+           0.1704343776215779,
+           0.17040874005231185,
+           0.17274995931668038,
+           0.17780539127129638,
+           0.18586368534103628,
+           0.19714578941431157,
+           0.21179749858691338,
+           0.22988375262015198,
+           0.25138484489896,
+           0.2761946593208246,
+           0.30412100205548803,
+           0.33488804370770087,
+           0.36814083536049574,
+           0.4034518105631976,
+           0.4403291358323041,
+           0.47822672588543785,
+           0.5165556977845415,
+           0.5546970014760481,
+           0.5920149338045224,
+           0.6278712197104617,
+           0.6616393285985839,
+           0.6927186861884768,
+           0.7205484427457436,
+           0.7446204674463612,
+           0.7644912555538155,
+           0.7797924596926832,
+           0.7902397881991022,
+           0.795640051558256,
+           0.7958961813850334,
+           0.7910100942156806,
+           0.7810833233962813,
+           0.7663153953390603,
+           0.7469999800810249,
+           0.7235188991147479,
+           0.6963341245758873,
+           0.6659779518202197,
+           0.6330415710351596,
+           0.5981623017434506,
+           0.5620097859378483,
+           0.525271460358359,
+           0.48863764548459343,
+           0.4527865977507387,
+           0.4183698720840704,
+           0.3859983341084705,
+           0.35622914543553474,
+           0.32955402178006793,
+           0.3063890327672945,
+           0.28706617500387116,
+           0.2718269071792017,
+           0.26081778869669336,
+           0.2540883127641043,
+           0.25159097223525784,
+           0.25318354307857793,
+           0.25863351745510504,
+           0.26762456730913176,
+           0.2797648713512488,
+           0.2945970945123524,
+           0.3116097704282628,
+           0.3302498052066885,
+           0.349935795405578,
+           0.3700718354152316,
+           0.3900614796989804,
+           0.4093215238237122,
+           0.427295274914319,
+           0.44346499690430324,
+           0.45736323833969633,
+           0.46858277994825165,
+           0.47678497496033245,
+           0.48170629635713463,
+           0.4831629507889181,
+           0.4810534677078508,
+           0.4753592230762066,
+           0.46614290857340185,
+           0.4535450082511547,
+           0.43777839380793054,
+           0.41912119585229374,
+           0.397908150558474,
+           0.37452065795117306,
+           0.349375818787115,
+           0.3229147408789143,
+           0.2955904221560159,
+           0.2678555263879355,
+           0.24015036811331647,
+           0.21289141593153887,
+           0.18646060812955154,
+           0.16119575203761455,
+           0.137382249121103,
+           0.11524635237839645,
+           0.09495012203481137,
+           0.07658820083521893,
+           0.060186482580657424,
+           0.04570269813768791,
+           0.03302889322696073,
+           0.021995723134562314,
+           0.012378442331095875,
+           0.003904423022601368,
+           -0.003738002993394215,
+           -0.01088961913101494,
+           -0.01790958359818043,
+           -0.025164163137966333,
+           -0.033015244135552665,
+           -0.04180893033726166,
+           -0.0518645345266417,
+           -0.06346426170380191,
+           -0.07684386386173106,
+           -0.09218452178357164,
+           -0.10960617801636052,
+           -0.12916250809479016,
+           -0.15083767512541915,
+           -0.1745449670535903,
+           -0.20012736747563223,
+           -0.22736006094989714,
+           -0.25595482366198136,
+           -0.28556620127879967,
+           -0.31579932912467074,
+           -0.3462192066152982,
+           -0.37636119929194317,
+           -0.4057425087938046,
+           -0.4338743245389564,
+           -0.46027435144084755,
+           -0.48447939617882996,
+           -0.5060576906879921,
+           -0.5246206357578515,
+           -0.5398336598516952,
+           -0.5514259081991643,
+           -0.5591985044012261,
+           -0.5630311605644884,
+           -0.5628869515305724,
+           -0.5588151131200286,
+           -0.5509517723813754,
+           -0.5395185684415916,
+           -0.5248191744464918,
+           -0.5072337829745879,
+           -0.48721166792034665,
+           -0.4652619839148193,
+           -0.4419430086863946,
+           -0.4178500732547818,
+           -0.3936024585074796,
+           -0.36982956368244907,
+           -0.3471566718889655,
+           -0.3261906495372492,
+           -0.30750592010547695,
+           -0.2916310479407125,
+           -0.279036254862771,
+           -0.27012217151320295,
+           -0.2652100971570365,
+           -0.26453400667661986,
+           -0.26823450263578186,
+           -0.2763548645251569,
+           -0.28883929773431444,
+           -0.3055334326362562,
+           -0.32618707068279634,
+           -0.3504591208969777,
+           -0.3779246179145043,
+           -0.40808366304328314,
+           -0.44037208388998955,
+           -0.47417356706507585,
+           -0.5088329833236694,
+           -0.5436705960864656,
+           -0.5779968233041599,
+           -0.6111272095917356,
+           -0.6423972607807604,
+           -0.6711767966325013,
+           -0.6968834893309073,
+           -0.7189952752383597,
+           -0.7370613547591762,
+           -0.7507115293435033,
+           -0.7596636648382631,
+           -0.7637291155668502,
+           -0.7628159925885497,
+           -0.7569302113510392,
+           -0.746174307139082,
+           -0.7307440600403775,
+           -0.7109230232949308,
+           -0.6870750985972114,
+           -0.6596353479726642,
+           -0.6290992731353304,
+           -0.5960108287538771,
+           -0.5609494649551725,
+           -0.5245165159881432,
+           -0.4873212657473698,
+           -0.44996702650088294,
+           -0.4130375645660316,
+           -0.3770841959205425,
+           -0.3426138561139607,
+           -0.3100784228416624,
+           -0.2798655368252179,
+           -0.2522911280393302,
+           -0.22759381081070157,
+           -0.20593126398152137,
+           -0.18737866236508594,
+           -0.17192917437163946,
+           -0.15949648922825643,
+           -0.1499192869367536,
+           -0.14296751625537388,
+           -0.13835030173739524,
+           -0.13572526130452264,
+           -0.13470898194720993,
+           -0.13488837375668342,
+           -0.13583260226925756,
+           -0.13710528652719942,
+           -0.13827664562445885,
+           -0.1389352799034017,
+           -0.13869928429255052,
+           -0.13722641021910884,
+           -0.13422301859730315,
+           -0.12945159891003766,
+           -0.12273666753205316,
+           -0.11396890121301,
+           -0.10310740795873057,
+           -0.0901800862405985,
+           -0.07528207329074268,
+           -0.05857233294088277,
+           -0.040268481776616655,
+           -0.02063999808350701,
+           -1.9595039588424004e-16
+          ],
+          [
+           0,
+           0.02042876571805524,
+           0.040972998305694716,
+           0.06126510913869602,
+           0.08094214437650016,
+           0.09965664887561712,
+           0.11708713569990163,
+           0.13294787857057014,
+           0.14699776177301924,
+           0.15904794605193587,
+           0.16896813927782325,
+           0.17669129639635017,
+           0.18221661347774334,
+           0.1856107245515861,
+           0.1870070562369228,
+           0.18660334278950247,
+           0.18465735188443652,
+           0.18148091802692848,
+           0.17743242475585266,
+           0.1729079176507067,
+           0.16833106653188867,
+           0.16414222622773394,
+           0.1607868700733458,
+           0.15870368826376977,
+           0.15831265383527543,
+           0.16000336210318558,
+           0.16412394474211936,
+           0.17097084744619273,
+           0.1807797405344433,
+           0.19371780543580047,
+           0.20987760733575767,
+           0.22927272618755795,
+           0.25183527571521985,
+           0.2774153940092246,
+           0.3057827409715582,
+           0.3366299883986078,
+           0.3695782391224349,
+           0.40418426358772264,
+           0.4399493967176795,
+           0.47632989605209425,
+           0.5127485249712623,
+           0.5486070932833399,
+           0.5832996623451014,
+           0.616226103845351,
+           0.6468056908710669,
+           0.6744903971790291,
+           0.6987775857977776,
+           0.7192217810798582,
+           0.7354452388135632,
+           0.7471470565030828,
+           0.7541105997792397,
+           0.7562090602955311,
+           0.7534090044447571,
+           0.7457718197345499,
+           0.7334530155325601,
+           0.7166993859212112,
+           0.6958440933455713,
+           0.6712997813547048,
+           0.6435498718170493,
+           0.6131382453853519,
+           0.5806575426377343,
+           0.5467363562850588,
+           0.5120256113068608,
+           0.47718444921292597,
+           0.44286594435425203,
+           0.40970298404086375,
+           0.37829464007325825,
+           0.34919334726308204,
+           0.3228931849037116,
+           0.29981953043522697,
+           0.28032032138647733,
+           0.2646591228831075,
+           0.25301015453495646,
+           0.24545538342370052,
+           0.24198374035399026,
+           0.24249246571982364,
+           0.2467905405130005,
+           0.2546041084014669,
+           0.26558374763961573,
+           0.27931340798616716,
+           0.29532078885433044,
+           0.3130889015443231,
+           0.3320685314119015,
+           0.35169129585211967,
+           0.3713829814947814,
+           0.39057683930133197,
+           0.40872651941456944,
+           0.4253183385404671,
+           0.4398825910425213,
+           0.4520036403260396,
+           0.46132855883392726,
+           0.46757412226239364,
+           0.4705320054949601,
+           0.47007207319473676,
+           0.4661437058510663,
+           0.45877515115302936,
+           0.44807093963706984,
+           0.4342074514101279,
+           0.41742676619726565,
+           0.39802897088042793,
+           0.376363136049722,
+           0.35281720496329866,
+           0.3278070639281268,
+           0.30176508185092693,
+           0.27512841811853067,
+           0.24832740178627713,
+           0.2217742812081534,
+           0.19585263185164115,
+           0.17090769141073117,
+           0.14723786594998464,
+           0.12508761933723522,
+           0.10464192146037136,
+           0.08602238961421046,
+           0.06928521303395808,
+           0.05442090397105518,
+           0.04135587113728593,
+           0.029955763989595617,
+           0.020030490390040644,
+           0.011340766815110256,
+           0.003606020602889998,
+           -0.0034865712814070478,
+           -0.010272151925995543,
+           -0.017097630701032072,
+           -0.02431079038123757,
+           -0.03224934844815607,
+           -0.04123026726435379,
+           -0.05153960164812444,
+           -0.06342315879588743,
+           -0.07707822484029285,
+           -0.09264658511342112,
+           -0.11020903209032883,
+           -0.12978151685098352,
+           -0.15131305767850906,
+           -0.17468547417253236,
+           -0.1997149681392992,
+           -0.22615552471482056,
+           -0.2537040598920975,
+           -0.28200719505558747,
+           -0.31066949643135855,
+           -0.33926297862519333,
+           -0.36733763763118693,
+           -0.3944327507156412,
+           -0.42008865913662063,
+           -0.44385873530741693,
+           -0.4653212291347781,
+           -0.48409068905623887,
+           -0.499828661769943,
+           -0.5122533906076416,
+           -0.5211482555725792,
+           -0.5263687276955495,
+           -0.5278476458366269,
+           -0.5255986645117398,
+           -0.5197177657612011,
+           -0.5103827754089074,
+           -0.4978508731190554,
+           -0.48245413522928676,
+           -0.46459319819679573,
+           -0.4447291774240531,
+           -0.4233740200649392,
+           -0.4010795100564461,
+           -0.37842517808251247,
+           -0.35600539758872285,
+           -0.3344159696102184,
+           -0.314240513497043,
+           -0.2960369872477839,
+           -0.2803246599089596,
+           -0.2675718493738021,
+           -0.25818472212300025,
+           -0.25249742738403425,
+           -0.2507638074171721,
+           -0.25315088890261833,
+           -0.25973431859034735,
+           -0.270495860493291,
+           -0.28532302306849566,
+           -0.3040108342261306,
+           -0.3262657308641573,
+           -0.3517114791925403,
+           -0.3798969936145537,
+           -0.4103058765567654,
+           -0.4423674604908181,
+           -0.47546909747330024,
+           -0.5089694117212975,
+           -0.5422122077680032,
+           -0.5745407111647106,
+           -0.6053118108919682,
+           -0.6339099728021781,
+           -0.6597605015322674,
+           -0.6823418441972415,
+           -0.7011966524126777,
+           -0.715941349225775,
+           -0.7262739836232728,
+           -0.7319801965460114,
+           -0.7329371677633135,
+           -0.7291154614340287,
+           -0.7205787385198603,
+           -0.7074813551906843,
+           -0.6900639167274267,
+           -0.6686469049584138,
+           -0.6436225427797334,
+           -0.6154451007043926,
+           -0.5846198866575151,
+           -0.5516911905112849,
+           -0.517229478408904,
+           -0.48181814820302094,
+           -0.44604016595257406,
+           -0.41046490419420745,
+           -0.37563549563498794,
+           -0.34205700120043364,
+           -0.31018566940229303,
+           -0.280419535328867,
+           -0.2530905729358616,
+           -0.22845857460241878,
+           -0.2067068881140214,
+           -0.18794009443885548,
+           -0.1721836610463807,
+           -0.15938555628818554,
+           -0.14941976174589983,
+           -0.1420915726552205,
+           -0.13714453269720026,
+           -0.13426880968947175,
+           -0.13311078398900766,
+           -0.133283592584833,
+           -0.13437834961557454,
+           -0.13597574892867376,
+           -0.1376577466623591,
+           -0.13901902184720158,
+           -0.13967792066870566,
+           -0.13928660509252797,
+           -0.13754014863089178,
+           -0.13418435054873873,
+           -0.12902207403668514,
+           -0.12191795293846923,
+           -0.11280135451678343,
+           -0.10166753138165367,
+           -0.08857694293082168,
+           -0.07365277426431939,
+           -0.05707672732948348,
+           -0.039083203843624424,
+           -0.019952041196476516,
+           -1.8865749344801872e-16
+          ],
+          [
+           0,
+           0.019484141676220954,
+           0.03892117858195265,
+           0.05796295887353002,
+           0.07627132951982421,
+           0.09352828664126586,
+           0.10944559740660104,
+           0.12377363327649242,
+           0.13630917451743377,
+           0.1469019722355698,
+           0.15545988603557967,
+           0.16195245199272446,
+           0.16641277601469467,
+           0.1689376908455694,
+           0.1696861598373477,
+           0.16887595605149336,
+           0.16677869010453403,
+           0.16371330330187192,
+           0.16003818291819513,
+           0.1561420929557976,
+           0.15243414541314243,
+           0.1493330632126983,
+           0.1472560057956215,
+           0.14660724147307683,
+           0.1477669565804658,
+           0.15108049013989208,
+           0.15684827410837943,
+           0.1653167435674921,
+           0.17667045876455,
+           0.19102565228578705,
+           0.2084253805222733,
+           0.22883641981337738,
+           0.2521480051710339,
+           0.27817246434666787,
+           0.3066477533152887,
+           0.33724185217320996,
+           0.3695589341443592,
+           0.40314717601611916,
+           0.43750803698464535,
+           0.4721067956145475,
+           0.5063841023432106,
+           0.5397682784986019,
+           0.5716880728219925,
+           0.6015855735054405,
+           0.6289289681084238,
+           0.6532248455685049,
+           0.6740297438426264,
+           0.6909606632997632,
+           0.7037042894440434,
+           0.7120246983221965,
+           0.7157693533460163,
+           0.7148732423864321,
+           0.7093610478997826,
+           0.6993472894639435,
+           0.6850344262991009,
+           0.6667089559521657,
+           0.6447355931508552,
+           0.6195496587170676,
+           0.5916478512497583,
+           0.5615776129997849,
+           0.5299253350177396,
+           0.49730367443882645,
+           0.46433827799767957,
+           0.43165422002281734,
+           0.39986246989990537,
+           0.36954670315174676,
+           0.34125076188299547,
+           0.3154670545859557,
+           0.2926261625876548,
+           0.2730878912946394,
+           0.25713396957481977,
+           0.2449625609576411,
+           0.23668470680581366,
+           0.23232277527825906,
+           0.23181094189721496,
+           0.23499767902466076,
+           0.24165018372738453,
+           0.2514606275308426,
+           0.26405406854734964,
+           0.278997827457458,
+           0.2958120947681273,
+           0.31398150848759493,
+           0.3329674195217112,
+           0.3522205472271059,
+           0.37119371999755585,
+           0.3893543956756455,
+           0.4061966639517322,
+           0.42125244753246066,
+           0.43410164034900334,
+           0.44438094887977225,
+           0.4517912360774849,
+           0.4561032055730778,
+           0.45716130581987047,
+           0.4548857785893245,
+           0.4492728226175675,
+           0.4403928900742282,
+           0.4283871797175132,
+           0.4134624349666401,
+           0.39588419656770385,
+           0.3759686970297295,
+           0.35407361664260056,
+           0.3305879478593993,
+           0.3059212354771213,
+           0.28049247388532556,
+           0.2547189493469349,
+           0.22900531468290378,
+           0.20373317588923812,
+           0.1792514553383646,
+           0.15586777470056765,
+           0.13384107312386223,
+           0.1133756432427621,
+           0.09461673009183263,
+           0.07764779693489261,
+           0.06248951842993229,
+           0.04910051653976819,
+           0.03737980931026134,
+           0.027170898218272788,
+           0.01826737736422781,
+           0.010419908421906243,
+           0.003344369955595469,
+           -0.0032690406360508417,
+           -0.009745998922439507,
+           -0.016417803654223382,
+           -0.023610961539809683,
+           -0.031636887131441825,
+           -0.04078199555413534,
+           -0.051298455860455006,
+           -0.0633958559557382,
+           -0.07723400673479786,
+           -0.09291708388835887,
+           -0.1104892715100279,
+           -0.1299320330270633,
+           -0.15116309306377346,
+           -0.17403716968241034,
+           -0.1983484511480596,
+           -0.22383476607631614,
+           -0.2501833516916747,
+           -0.27703808306933164,
+           -0.304007987716827,
+           -0.3306768356555667,
+           -0.3566135661601826,
+           -0.3813832892513287,
+           -0.40455858351273016,
+           -0.4257308022513529,
+           -0.44452109770177217,
+           -0.46059087797308895,
+           -0.47365142364707447,
+           -0.483472410077118,
+           -0.4898891070528332,
+           -0.49280805896592256,
+           -0.49221108517286954,
+           -0.4881574810043272,
+           -0.4807843438182875,
+           -0.47030499455112895,
+           -0.457005512249332,
+           -0.441239445900196,
+           -0.42342081335943677,
+           -0.40401554016556807,
+           -0.38353153046270066,
+           -0.3625075971381163,
+           -0.3415015077423372,
+           -0.32107742605328765,
+           -0.3017930456793992,
+           -0.28418672144152396,
+           -0.26876490617979226,
+           -0.2559901950309494,
+           -0.24627026623148032,
+           -0.23994798742143778,
+           -0.2372929297275947,
+           -0.23849449923060964,
+           -0.2436568575551729,
+           -0.2527957611795433,
+           -0.2658374036625506,
+           -0.2826192974344744,
+           -0.30289318324972325,
+           -0.3263299070362912,
+           -0.3525261568783024,
+           -0.3810129083801781,
+           -0.4112653857697765,
+           -0.4427143098016829,
+           -0.4747581727070548,
+           -0.5067762558555914,
+           -0.538142088048409,
+           -0.56823703188072,
+           -0.5964636826554843,
+           -0.6222587689643999,
+           -0.645105256165876,
+           -0.6645433732830655,
+           -0.6801803098450323,
+           -0.6916983612631579,
+           -0.6988613386871663,
+           -0.7015191010062416,
+           -0.6996101117296802,
+           -0.6931619707965728,
+           -0.6822899197693527,
+           -0.6671933671804958,
+           -0.6481505278476916,
+           -0.6255113146056158,
+           -0.5996886620380499,
+           -0.5711484984359825,
+           -0.5403986134710362,
+           -0.5079766942081513,
+           -0.4744378204880124,
+           -0.44034172195611165,
+           -0.40624010284613504,
+           -0.37266433696864787,
+           -0.3401138243243693,
+           -0.3090452826487353,
+           -0.27986322246947015,
+           -0.25291182355193814,
+           -0.22846839469513805,
+           -0.20673855862840704,
+           -0.18785326025343235,
+           -0.171867650765809,
+           -0.1587618534147046,
+           -0.1484435699819656,
+           -0.14075244164156164,
+           -0.13546603482126307,
+           -0.13230728309373505,
+           -0.13095318094857644,
+           -0.13104449540277893,
+           -0.1321962375237609,
+           -0.13400861864415675,
+           -0.1360782057529326,
+           -0.1380089874895367,
+           -0.13942306640173252,
+           -0.13997070452605656,
+           -0.139339467606135,
+           -0.13726223790070033,
+           -0.1335238959134575,
+           -0.12796650672131715,
+           -0.12049288598301695,
+           -0.11106846317323002,
+           -0.09972140402885986,
+           -0.08654099948706866,
+           -0.07167437339113242,
+           -0.05532160480166212,
+           -0.03772940177535808,
+           -0.019183500924353322,
+           -1.80660862519241e-16
+          ],
+          [
+           0,
+           0.018478416881187357,
+           0.03676364416749029,
+           0.05452959883215817,
+           0.07146490263258537,
+           0.08728225448733398,
+           0.10172716050626159,
+           0.11458578515386517,
+           0.12569170956375758,
+           0.1349314110848846,
+           0.14224831102063146,
+           0.1476452743914685,
+           0.1511854854802268,
+           0.15299166489857094,
+           0.15324363688317563,
+           0.15217429840379498,
+           0.15006408335720473,
+           0.14723405457347266,
+           0.14403779257156488,
+           0.14085228204714761,
+           0.13806802413695424,
+           0.13607862388526773,
+           0.13527011748418877,
+           0.13601031237095917,
+           0.1386384149086719,
+           0.14345521508874665,
+           0.1507140855853643,
+           0.16061303384525802,
+           0.17328802115640854,
+           0.18880773240502435,
+           0.20716994523883622,
+           0.2282996084636449,
+           0.25204869766573906,
+           0.2781978723073344,
+           0.3064599139673738,
+           0.3364848811010644,
+           0.367866872768959,
+           0.40015225330938664,
+           0.4328491529073502,
+           0.4654380263760821,
+           0.4973830250351755,
+           0.5281439150354533,
+           0.5571882603950467,
+           0.5840035807647666,
+           0.6081091927570286,
+           0.6290674496006933,
+           0.6464941067982701,
+           0.6600675610637369,
+           0.6695367356451496,
+           0.674727416568798,
+           0.6755468806243871,
+           0.671986696166845,
+           0.6641236210640815,
+           0.6521185673207539,
+           0.6362136479560799,
+           0.6167273674871938,
+           0.5940480617522649,
+           0.5686257347164678,
+           0.5409624783154914,
+           0.5116016953672462,
+           0.48111637429235093,
+           0.4500966871262919,
+           0.4191371985247509,
+           0.38882398276242575,
+           0.35972194787761924,
+           0.3323626610680049,
+           0.30723295732152034,
+           0.2847645943675343,
+           0.2653251918206185,
+           0.2492106614796779,
+           0.23663929989579158,
+           0.22774767440971078,
+           0.22258839086069923,
+           0.2211297861328309,
+           0.22325754273260107,
+           0.22877817680404544,
+           0.23742430649997862,
+           0.24886156552257557,
+           0.262696987945605,
+           0.2784886560712408,
+           0.29575637388574516,
+           0.3139931053610218,
+           0.33267689995834565,
+           0.35128301762264125,
+           0.3692959625379525,
+           0.3862211390008633,
+           0.4015958538368483,
+           0.4149994075415227,
+           0.4260620403165247,
+           0.43447252877776105,
+           0.43998426359371945,
+           0.44241967679658517,
+           0.4416729290349711,
+           0.43771081056690797,
+           0.43057185424105,
+           0.42036370297792364,
+           0.40725881724400326,
+           0.3914886486460641,
+           0.3733364430592241,
+           0.35312886972225305,
+           0.33122670067945137,
+           0.30801478713898145,
+           0.28389159521742396,
+           0.2592585727718322,
+           0.23450962137339262,
+           0.2100209429128047,
+           0.18614151898163292,
+           0.16318446335031614,
+           0.14141946402826636,
+           0.12106650216001472,
+           0.10229100113363401,
+           0.08520052161882304,
+           0.06984307777078175,
+           0.05620710756073249,
+           0.04422308719652813,
+           0.03376673696620906,
+           0.02466372465203194,
+           0.01669573396347787,
+           0.009607730202672514,
+           0.003116224494186888,
+           -0.0030816878371335704,
+           -0.009298759121973805,
+           -0.01584774949603203,
+           -0.023031580449236196,
+           -0.031133747116144053,
+           -0.040409248067120485,
+           -0.05107627812592847,
+           -0.06330891018616146,
+           -0.07723096661869433,
+           -0.09291125029428546,
+           -0.11036027026003864,
+           -0.12952855858780965,
+           -0.15030663382883877,
+           -0.17252662389940193,
+           -0.19596551816409902,
+           -0.22034997606616613,
+           -0.24536257895276464,
+           -0.27064937379083615,
+           -0.2958285232316214,
+           -0.3204998468331195,
+           -0.34425501394998603,
+           -0.3666881304769007,
+           -0.3874064497628728,
+           -0.40604093291812143,
+           -0.4222563855607334,
+           -0.43576090677313317,
+           -0.4463144014616629,
+           -0.4537359290715785,
+           -0.45790968918079894,
+           -0.458789477208745,
+           -0.4564014805318731,
+           -0.4508453257852219,
+           -0.44229333105206575,
+           -0.43098796094137504,
+           -0.41723752712832624,
+           -0.4014102206803108,
+           -0.3839266043213708,
+           -0.36525073165876426,
+           -0.345880095334111,
+           -0.32633463619144515,
+           -0.3071450701157761,
+           -0.28884080756473574,
+           -0.27193775252074537,
+           -0.25692627232345705,
+           -0.2442596274655578,
+           -0.23434314098745335,
+           -0.2275243708007452,
+           -0.22408452548891009,
+           -0.22423133541822454,
+           -0.22809355703201123,
+           -0.2357172498157112,
+           -0.24706392353835718,
+           -0.262010609013957,
+           -0.2803518598626768,
+           -0.3018036467006527,
+           -0.3260090599713161,
+           -0.3525456943532253,
+           -0.3809345473962118,
+           -0.41065022873302576,
+           -0.44113224477471197,
+           -0.47179709799307995,
+           -0.5020509203536182,
+           -0.5313023476645665,
+           -0.5589753358651378,
+           -0.584521621728121,
+           -0.6074325390629414,
+           -0.6272499170633242,
+           -0.6435758095676027,
+           -0.656080832147411,
+           -0.6645109174227771,
+           -0.6686923369990947,
+           -0.6685348800047528,
+           -0.6640331223608453,
+           -0.6552657665579423,
+           -0.6423930777355235,
+           -0.6256524871354859,
+           -0.6053524774299641,
+           -0.5818649049500674,
+           -0.5556159504834067,
+           -0.5270759221785093,
+           -0.49674816042626746,
+           -0.4651573147524649,
+           -0.43283727627406715,
+           -0.4003190558326614,
+           -0.36811889738010733,
+           -0.33672690858839277,
+           -0.3065964761961357,
+           -0.2781347126647988,
+           -0.25169415383468774,
+           -0.2275658951255683,
+           -0.20597431722938697,
+           -0.1870735121115638,
+           -0.170945477476263,
+           -0.15760010372420724,
+           -0.14697693293681974,
+           -0.1389486256625522,
+           -0.13332602934386265,
+           -0.12986470314259532,
+           -0.12827271866022374,
+           -0.1282195254730851,
+           -0.12934564525833145,
+           -0.13127293918386373,
+           -0.13361518063302472,
+           -0.13598865952716063,
+           -0.13802254562092636,
+           -0.139368746127835,
+           -0.13971100766669362,
+           -0.13877303341700423,
+           -0.1363254129905967,
+           -0.1321911941828501,
+           -0.12624996164975918,
+           -0.11844032675198873,
+           -0.10876077431728878,
+           -0.09726885484471348,
+           -0.08407875362424705,
+           -0.06935731028653565,
+           -0.053318602366403345,
+           -0.03621724354815433,
+           -0.018340580423799678,
+           -1.7202773530830264e-16
+          ],
+          [
+           0,
+           0.017420267496541336,
+           0.034518963312837735,
+           0.050994222889445426,
+           0.06656290301238955,
+           0.08096912738631878,
+           0.09399209659741589,
+           0.10545295045125246,
+           0.11522049505251507,
+           0.123215636225996,
+           0.12941439422405393,
+           0.13384941128342084,
+           0.13660990255917696,
+           0.13784004129140542,
+           0.13773580973061392,
+           0.1365403873318312,
+           0.1345381860106714,
+           0.13204767786537136,
+           0.12941319280031152,
+           0.12699589112088022,
+           0.12516413869782805,
+           0.12428352913954102,
+           0.12470680812261209,
+           0.1267639593272173,
+           0.13075270917678672,
+           0.136929698827569,
+           0.145502556792095,
+           0.1566230845685503,
+           0.17038174119245447,
+           0.18680358137163902,
+           0.2058457665753368,
+           0.22739672999060387,
+           0.25127703558253806,
+           0.2772419296045019,
+           0.3049855408389876,
+           0.33414664465376,
+           0.36431586665721893,
+           0.39504416531251313,
+           0.4258524002337053,
+           0.4562417648592647,
+           0.48570483948607046,
+           0.5137370038286743,
+           0.5398479377769365,
+           0.5635729351381921,
+           0.5844837579828535,
+           0.602198768714707,
+           0.6163920929439274,
+           0.626801588277818,
+           0.6332354217365803,
+           0.6355770909866532,
+           0.6337887611784794,
+           0.6279128289929081,
+           0.6180716675742776,
+           0.6044655493353671,
+           0.5873687871050162,
+           0.5671241766929996,
+           0.5441358646288711,
+           0.5188608025982858,
+           0.49179898402882405,
+           0.46348268753782773,
+           0.4344649758316889,
+           0.4053077165548799,
+           0.37656940308972825,
+           0.34879305812274464,
+           0.3224945008024016,
+           0.29815124956528766,
+           0.2761923174166111,
+           0.256989134991308,
+           0.24084780961852195,
+           0.22800289652810204,
+           0.2186128220573941,
+           0.21275705912697584,
+           0.21043511332213055,
+           0.21156733466654565,
+           0.21599752666092142,
+           0.22349728144220643,
+           0.23377192903854638,
+           0.24646795064393215,
+           0.26118167153725597,
+           0.2774690195520807,
+           0.29485611058090166,
+           0.31285040405508846,
+           0.33095215911724263,
+           0.3486659165786957,
+           0.3655117328505165,
+           0.3810358998052685,
+           0.39482089875820703,
+           0.4064943570809054,
+           0.4157368018584938,
+           0.42228803581802665,
+           0.42595199571443415,
+           0.42659999158566725,
+           0.42417226582485884,
+           0.41867785285443926,
+           0.41019276228492146,
+           0.39885654975543705,
+           0.38486737916154873,
+           0.3684757167032654,
+           0.3499768302286511,
+           0.32970229589573896,
+           0.3080107375311786,
+           0.2852780416624634,
+           0.26188730262080245,
+           0.23821875708781617,
+           0.21463996588668574,
+           0.19149649275656258,
+           0.16910331551925106,
+           0.1477371848272263,
+           0.1276301200964954,
+           0.10896420193453621,
+           0.09186778614758181,
+           0.07641322712499415,
+           0.06261615899927803,
+           0.05043634246781484,
+           0.03978004456287824,
+           0.03050387899695526,
+           0.022419996993290513,
+           0.015302483689335,
+           0.008894784152349487,
+           0.0029179565549735317,
+           -0.0029204712078718166,
+           -0.00891728068472709,
+           -0.015364226393488568,
+           -0.022538835250968746,
+           -0.030695589953456687,
+           -0.04005773448539084,
+           -0.05080992393778058,
+           -0.06309191910050178,
+           -0.07699349940060814,
+           -0.09255073637054287,
+           -0.10974373473752815,
+           -0.12849591031425955,
+           -0.14867483409889506,
+           -0.17009463136454964,
+           -0.19251988406304343,
+           -0.21567094560941455,
+           -0.23923054004874358,
+           -0.2628514836774946,
+           -0.2861653372628627,
+           -0.3087917718413112,
+           -0.33034841132907944,
+           -0.3504609013557182,
+           -0.36877294620170287,
+           -0.38495605469101046,
+           -0.39871874140486724,
+           -0.4098149415256661,
+           -0.4180514157112272,
+           -0.4232939452057203,
+           -0.42547214633767855,
+           -0.42458276693094193,
+           -0.42069136414238284,
+           -0.4139323029302751,
+           -0.40450705576914525,
+           -0.3926808263357998,
+           -0.3787775616521643,
+           -0.36317345754510444,
+           -0.34628910026491494,
+           -0.32858042174345486,
+           -0.31052867640105203,
+           -0.29262967286233804,
+           -0.2753825137699775,
+           -0.2592781105851838,
+           -0.2447877474780455,
+           -0.23235196894200955,
+           -0.22237005958289027,
+           -0.2151903717663534,
+           -0.2111017377546982,
+           -0.2103261780747644,
+           -0.21301308772937422,
+           -0.21923504722031684,
+           -0.2289853670288916,
+           -0.24217743312969392,
+           -0.25864587829255736,
+           -0.27814956039858363,
+           -0.30037628581978115,
+           -0.32494917414145197,
+           -0.35143452116180324,
+           -0.3793509811457791,
+           -0.40817985761876774,
+           -0.4373762653357152,
+           -0.4663809051042828,
+           -0.4946321783898468,
+           -0.5215783604466074,
+           -0.5466895493028802,
+           -0.5694691133148266,
+           -0.5894643720594901,
+           -0.6062762637699984,
+           -0.6195677768721938,
+           -0.6290709528668279,
+           -0.6345923020889178,
+           -0.6360165119273916,
+           -0.6333083679741409,
+           -0.6265128512933914,
+           -0.6157534185173655,
+           -0.6012285147216474,
+           -0.5832064109602672,
+           -0.562018497926885,
+           -0.5380512034937515,
+           -0.5117367339861453,
+           -0.4835428662021599,
+           -0.45396203873468205,
+           -0.4235000065813041,
+           -0.3926643319775396,
+           -0.3619529866576807,
+           -0.33184333629930923,
+           -0.3027817668711252,
+           -0.2751741952702071,
+           -0.24937768344995784,
+           -0.2256933467930246,
+           -0.20436071449226684,
+           -0.18555366299597106,
+           -0.1693780040695066,
+           -0.15587076771041738,
+           -0.1450011780557313,
+           -0.13667327858456435,
+           -0.1307301223824086,
+           -0.1269594049977096,
+           -0.12510038242890437,
+           -0.1248518858907137,
+           -0.12588121897784016,
+           -0.1278337023053195,
+           -0.13034261615243659,
+           -0.13303928341581892,
+           -0.13556303347278928,
+           -0.13757079239097336,
+           -0.1387460561537038,
+           -0.1388070209023704,
+           -0.13751366717395938,
+           -0.13467362314150053,
+           -0.13014666422827403,
+           -0.12384774233722404,
+           -0.1157484764022227,
+           -0.10587707605093319,
+           -0.09431671085399213,
+           -0.08120237789224138,
+           -0.06671635918487219,
+           -0.05108239690605419,
+           -0.03455874735733923,
+           -0.017430303524248594,
+           -1.6283188284955877e-16
+          ],
+          [
+           0,
+           0.016318815635505118,
+           0.03220630323939725,
+           0.047386468707982944,
+           0.061605345974497586,
+           0.07463868268216912,
+           0.08629881781948491,
+           0.09644056419351377,
+           0.10496593428861156,
+           0.11182757790946903,
+           0.11703083328550912,
+           0.12063432917755877,
+           0.12274911307114054,
+           0.12353631881416964,
+           0.12320342509145794,
+           0.12199919296028741,
+           0.12020740536551502,
+           0.11813956322684739,
+           0.1161267205372792,
+           0.11451066421741123,
+           0.11363466263545982,
+           0.11383401925525617,
+           0.1154266744823688,
+           0.11870409925803226,
+           0.12392271827138832,
+           0.1312960889463466,
+           0.14098804488512742,
+           0.15310698963584912,
+           0.1677014990503101,
+           0.18475735878508714,
+           0.2041961284530116,
+           0.22587528641665594,
+           0.24958997015781553,
+           0.2750762875247623,
+           0.30201613493649315,
+           0.33004342078650983,
+           0.35875155678197973,
+           0.38770204766578603,
+           0.4164339815095928,
+           0.44447419924814874,
+           0.47134790394534126,
+           0.49658945790686576,
+           0.5197531095061337,
+           0.5404233916418879,
+           0.5582249401151689,
+           0.5728314927615276,
+           0.5839738486103849,
+           0.5914465902306407,
+           0.5951134011881538,
+           0.5949108434937969,
+           0.590850496263478,
+           0.5830193956623737,
+           0.5715787566202518,
+           0.5567609977992083,
+           0.5388651318698473,
+           0.5182506223166944,
+           0.4953298447916153,
+           0.470559324565681,
+           0.44442995107499855,
+           0.4174563951937375,
+           0.3901659740947056,
+           0.36308722190299636,
+           0.3367384314843806,
+           0.31161643346171947,
+           0.28818587290074954,
+           0.2668692321887596,
+           0.24803783073698288,
+           0.23200400870719415,
+           0.21901467356760637,
+           0.20924635561673552,
+           0.2028018824743997,
+           0.19970874380921927,
+           0.19991917719715338,
+           0.20331196497066456,
+           0.20969589122307802,
+           0.21881476876825603,
+           0.23035390877867842,
+           0.24394787193497833,
+           0.25918931003695656,
+           0.27563868187076374,
+           0.29283460730248273,
+           0.3103046095463391,
+           0.3275759876640207,
+           0.34418655976683205,
+           0.3596950221356975,
+           0.37369068041061465,
+           0.3858023258440656,
+           0.3957060519299283,
+           0.40313183394459645,
+           0.4078687253839955,
+           0.409768560160226,
+           0.40874808686252206,
+           0.40478950045577,
+           0.39793937651432587,
+           0.3883060524836754,
+           0.3760555385524651,
+           0.36140607656191276,
+           0.34462149809597903,
+           0.32600356168097727,
+           0.3058834731741551,
+           0.28461281235077396,
+           0.2625541019532075,
+           0.2400712627309293,
+           0.21752019911439632,
+           0.19523975511995906,
+           0.1735432690223447,
+           0.1527109385510949,
+           0.13298318630542105,
+           0.11455518830746284,
+           0.09757269781300394,
+           0.08212926245743606,
+           0.06826489639901477,
+           0.0559662312556152,
+           0.04516813127456885,
+           0.03575672029829322,
+           0.027573731648490023,
+           0.020422057968849407,
+           0.014072347200282425,
+           0.008270463991984585,
+           0.0027456136531555904,
+           -0.0027810912170163375,
+           -0.008587852592444146,
+           -0.01494343391404682,
+           -0.02209866784153472,
+           -0.030278453921030322,
+           -0.039674462570235096,
+           -0.05043874355914613,
+           -0.06267841383322621,
+           -0.07645157167638071,
+           -0.09176455254616846,
+           -0.10857060723302374,
+           -0.1267700461750998,
+           -0.14621185573149398,
+           -0.1666967539412678,
+           -0.18798161574324163,
+           -0.2097851617544652,
+           -0.2317947714150021,
+           -0.2536742514509652,
+           -0.2750723649493509,
+           -0.2956319055355585,
+           -0.31499908573527696,
+           -0.33283299898996466,
+           -0.34881491123808955,
+           -0.3626571405800695,
+           -0.37411129226665085,
+           -0.38297563088840664,
+           -0.3891013918497456,
+           -0.3923978594960216,
+           -0.39283606901084805,
+           -0.3904510226835111,
+           -0.38534234753968083,
+           -0.3776733597342767,
+           -0.36766854057295906,
+           -0.3556094685793328,
+           -0.3418292906752785,
+           -0.3267058523287555,
+           -0.31065364052770966,
+           -0.2941147238084362,
+           -0.27754889953767475,
+           -0.26142327956349865,
+           -0.2462015606773506,
+           -0.23233323567290434,
+           -0.22024300389771007,
+           -0.21032063697560563,
+           -0.20291154589240798,
+           -0.19830828009970322,
+           -0.19674316806682277,
+           -0.19838228230500599,
+           -0.2033208809345637,
+           -0.2115804431127927,
+           -0.2231073779291403,
+           -0.23777344662047226,
+           -0.25537789713040887,
+           -0.27565126912736176,
+           -0.298260787604068,
+           -0.322817225083737,
+           -0.3488830771852358,
+           -0.37598186471482076,
+           -0.40360834832757153,
+           -0.43123941980199626,
+           -0.4583454176351841,
+           -0.4844016043938016,
+           -0.508899539300435,
+           -0.5313580819924811,
+           -0.5513337722028168,
+           -0.56843034506266,
+           -0.58230716245215,
+           -0.5926863668167422,
+           -0.5993585944922892,
+           -0.602187120090415,
+           -0.6011103410453453,
+           -0.5961425510971008,
+           -0.5873729923156513,
+           -0.5749632162607966,
+           -0.5591428250247432,
+           -0.5402037012418123,
+           -0.5184928717414432,
+           -0.49440418150404586,
+           -0.46836898218180206,
+           -0.44084606200400567,
+           -0.4123110608601774,
+           -0.38324562534287154,
+           -0.354126563282935,
+           -0.3254152557237783,
+           -0.2975475764148658,
+           -0.2709245549699744,
+           -0.2459040001932337,
+           -0.2227932752263715,
+           -0.20184338674205166,
+           -0.18324451714053477,
+           -0.16712309243318227,
+           -0.15354044012203863,
+           -0.14249305186550176,
+           -0.13391442603741857,
+           -0.12767842642438476,
+           -0.12360405622444572,
+           -0.12146151212425005,
+           -0.12097935238640892,
+           -0.12185258632986724,
+           -0.1237514709803888,
+           -0.12633078452815852,
+           -0.12923933594009862,
+           -0.13212946587411345,
+           -0.13466629601700236,
+           -0.13653649204876117,
+           -0.13745631940250427,
+           -0.13717879047358214,
+           -0.13549972642857946,
+           -0.13226258564510837,
+           -0.12736194333821843,
+           -0.12074554227022727,
+           -0.11241487169990662,
+           -0.10242426995944715,
+           -0.09087858428546083,
+           -0.07792945880661248,
+           -0.06377035696368014,
+           -0.04863045721512243,
+           -0.03276758984094392,
+           -0.01646040726991964,
+           -1.5315252351621855e-16
+          ],
+          [
+           0,
+           0.015183500319209519,
+           0.029845164969027543,
+           0.043736016311245705,
+           0.0566316920773553,
+           0.06833925377575754,
+           0.07870313535473134,
+           0.08761006985267766,
+           0.09499285818738294,
+           0.10083287417991792,
+           0.10516123261961176,
+           0.10805858182740499,
+           0.10965351788934884,
+           0.11011965360605211,
+           0.10967141032850727,
+           0.10855863433479256,
+           0.1070601703946584,
+           0.10547655288045349,
+           0.10412199850508375,
+           0.10331590389167575,
+           0.10337406521078617,
+           0.10459984569177778,
+           0.10727551969409883,
+           0.11165401912264564,
+           0.11795129934480958,
+           0.12633952761432485,
+           0.13694127766643677,
+           0.1498248900884544,
+           0.16500112987662907,
+           0.18242124095620346,
+           0.20197646314549217,
+           0.22349904093421233,
+           0.24676471641532177,
+           0.2714966616777283,
+           0.29737076985575567,
+           0.32402218974103475,
+           0.3510529572509028,
+           0.37804054890753847,
+           0.4045471585225539,
+           0.4301294791092835,
+           0.45434875814899783,
+           0.4767808860776551,
+           0.49702627545792954,
+           0.5147192918341189,
+           0.5295370066658078,
+           0.5412070577856026,
+           0.5495144231728506,
+           0.5543069389938406,
+           0.5554994222249643,
+           0.5530762910395908,
+           0.5470926117056261,
+           0.5376735381449134,
+           0.5250121486374549,
+           0.5093657224784999,
+           0.49105053677952576,
+           0.4704352991317482,
+           0.44793336465429084,
+           0.42399391522582247,
+           0.399092303731356,
+           0.37371978633159203,
+           0.34837288058574395,
+           0.3235425963663951,
+           0.2997037896722119,
+           0.27730488659274205,
+           0.25675821587745234,
+           0.2384311740229111,
+           0.2226384268722112,
+           0.20963532690555534,
+           0.19961269629646125,
+           0.19269309312478536,
+           0.18892864267381368,
+           0.18830047835932173,
+           0.19071979845560946,
+           0.19603050633248806,
+           0.20401336433433212,
+           0.21439155563154458,
+           0.2268375152253495,
+           0.2409808615917069,
+           0.25641723492665786,
+           0.2727178272171699,
+           0.28943937390403435,
+           0.30613436709119607,
+           0.3223612463145331,
+           0.3376943248931695,
+           0.35173321778180383,
+           0.3641115504126653,
+           0.37450474691026453,
+           0.3826367198005565,
+           0.3882853113191853,
+           0.391286367948608,
+           0.39153636409238396,
+           0.38899352697193224,
+           0.38367745200657805,
+           0.3756672351890913,
+           0.3650981853737842,
+           0.3521572140531983,
+           0.3370770322585761,
+           0.3201293128912221,
+           0.3016170013750532,
+           0.2818659774168936,
+           0.2612162853902177,
+           0.24001316006954684,
+           0.21859807792449132,
+           0.19730006186559418,
+           0.17642745929487694,
+           0.15626039977109385,
+           0.13704411990931495,
+           0.1189833197805654,
+           0.10223768765996882,
+           0.0869186991917208,
+           0.07308776368016084,
+           0.06075575512541938,
+           0.049883929688963644,
+           0.04038619540826757,
+           0.03213266508713806,
+           0.02495439024993277,
+           0.018649143697279557,
+           0.01298809130288442,
+           0.0077231709229745255,
+           0.0025949782247753567,
+           -0.002659053667675183,
+           -0.00829640123905796,
+           -0.014561346648363897,
+           -0.021677241133281826,
+           -0.02983934453298231,
+           -0.03920843478279412,
+           -0.04990536131865804,
+           -0.06200669192743785,
+           -0.07554157430771327,
+           -0.09048990217890332,
+           -0.10678184198880313,
+           -0.1242987409751814,
+           -0.1428754014290252,
+           -0.16230367039469662,
+           -0.18233725962856,
+           -0.20269767829639965,
+           -0.223081131443971,
+           -0.24316621147552073,
+           -0.2626221883828007,
+           -0.2811176878354227,
+           -0.29832953490490594,
+           -0.31395153544979326,
+           -0.32770296719840175,
+           -0.3393365583459346,
+           -0.34864574290600686,
+           -0.3554709988538867,
+           -0.35970509686565527,
+           -0.36129711366467343,
+           -0.360255093992826,
+           -0.35664727829126835,
+           -0.3506018484881966,
+           -0.3423051809759677,
+           -0.3319986330070306,
+           -0.319973925424355,
+           -0.3065672199534205,
+           -0.292152022337543,
+           -0.27713107256839187,
+           -0.2619274095960328,
+           -0.24697481953777112,
+           -0.23270789299279573,
+           -0.2195519281840859,
+           -0.20791292199867775,
+           -0.19816789043255761,
+           -0.19065575346316918,
+           -0.18566900711320874,
+           -0.18344638771880414,
+           -0.18416671059431566,
+           -0.18794403794141026,
+           -0.19482429964055092,
+           -0.20478345624373084,
+           -0.21772725689082384,
+           -0.23349260688827359,
+           -0.2518505212431498,
+           -0.2725106024757033,
+           -0.2951269444664963,
+           -0.31930532982390186,
+           -0.34461155712239155,
+           -0.3705807071239101,
+           -0.39672713442094565,
+           -0.42255495338650945,
+           -0.447568775313909,
+           -0.47128444747292686,
+           -0.49323954465071224,
+           -0.5130033695904361,
+           -0.5301862304468508,
+           -0.5444477806598947,
+           -0.5555042290837171,
+           -0.5631342552511759,
+           -0.5671834956426307,
+           -0.567567501006073,
+           -0.5642731013090416,
+           -0.5573581529000692,
+           -0.5469496809920573,
+           -0.5332404687132811,
+           -0.5164841807756667,
+           -0.4969891443902553,
+           -0.47511094157767564,
+           -0.4512439947144758,
+           -0.4258123503568434,
+           -0.3992598845352633,
+           -0.37204016538574725,
+           -0.34460621587939916,
+           -0.3174004203787688,
+           -0.29084481377954385,
+           -0.2653319812282468,
+           -0.2412167801222451,
+           -0.2188090747142575,
+           -0.19836764770113405,
+           -0.18009542332913342,
+           -0.16413610354304575,
+           -0.15057228336867767,
+           -0.13942507492766557,
+           -0.13065523215437602,
+           -0.12416573134229542,
+           -0.1198057270054042,
+           -0.11737576907803816,
+           -0.11663413701782452,
+           -0.11730411966723356,
+           -0.11908204742195815,
+           -0.12164586588958085,
+           -0.12466402821643885,
+           -0.12780447689641292,
+           -0.13074348529345192,
+           -0.13317413430629935,
+           -0.13481421043115588,
+           -0.13541332764750985,
+           -0.134759096642634,
+           -0.13268219035760567,
+           -0.12906018402969047,
+           -0.12382008007800112,
+           -0.11693946251338608,
+           -0.10844626117847704,
+           -0.09841714213753396,
+           -0.08697457602739006,
+           -0.07428267025398914,
+           -0.06054188271386876,
+           -0.045982763434863516,
+           -0.03085889544186744,
+           -0.015439226634623894,
+           -1.4307317483385038e-16
+          ],
+          [
+           0,
+           0.014023945805484151,
+           0.02745511679520318,
+           0.04007219050013675,
+           0.051680329213635884,
+           0.06211710926974681,
+           0.07125755917501508,
+           0.07901816873883119,
+           0.0853597579961447,
+           0.09028912425630532,
+           0.09385941729583622,
+           0.09616922573954546,
+           0.09736039120750903,
+           0.09761459999556824,
+           0.09714883406228608,
+           0.09620979310286754,
+           0.09506742673668186,
+           0.09400773962443329,
+           0.09332505205432899,
+           0.09331391368558485,
+           0.09426087831815627,
+           0.09643635249956406,
+           0.10008673034390064,
+           0.1054270211199263,
+           0.11263416509480437,
+           0.12184121705946768,
+           0.13313255629825627,
+           0.14654025700262138,
+           0.16204172487320276,
+           0.17955867460183622,
+           0.19895748984177647,
+           0.22005097297973109,
+           0.2426014573683166,
+           0.26632522052439633,
+           0.2908981039988892,
+           0.3159622149970784,
+           0.3411335571428184,
+           0.36601041373197596,
+           0.3901822870177603,
+           0.413239182017358,
+           0.4347810134129945,
+           0.45442690960242726,
+           0.47182418896227935,
+           0.4866567899144978,
+           0.4986529482873437,
+           0.5075919324604904,
+           0.5133096684756228,
+           0.5157031131595936,
+           0.5147332627231803,
+           0.5104267165528342,
+           0.5028757502226181,
+           0.4922368872841202,
+           0.4787279952777195,
+           0.4626239667734198,
+           0.4442510802295946,
+           0.42398016722238313,
+           0.40221874136964647,
+           0.3794022693464867,
+           0.3559847851496056,
+           0.3324290647057181,
+           0.30919658864309163,
+           0.286737526291033,
+           0.2654809736094572,
+           0.2458256717869153,
+           0.2281314218247562,
+           0.21271139382538623,
+           0.1998255083284655,
+           0.1896750414116787,
+           0.1823985760178732,
+           0.17806938980158374,
+           0.17669433549022748,
+           0.1782142341648424,
+           0.18250576584970105,
+           0.18938480623649298,
+           0.19861112412223286,
+           0.2098943220425447,
+           0.22290087341181752,
+           0.23726208394433537,
+           0.2525827838413853,
+           0.2684505406985902,
+           0.28444517170808503,
+           0.30014832776688594,
+           0.3151529216878135,
+           0.3290721778377571,
+           0.3415480910585605,
+           0.3522590983845292,
+           0.3609267874575788,
+           0.36732149014098603,
+           0.37126663802707865,
+           0.37264178761737515,
+           0.3713842561499722,
+           0.36748934353238044,
+           0.3610091507523865,
+           0.35205003962008974,
+           0.3407688118889493,
+           0.3273677168941998,
+           0.31208842506919693,
+           0.2952051293629338,
+           0.27701695708393576,
+           0.25783989054065337,
+           0.23799840565703165,
+           0.21781704326100298,
+           0.19761212785268026,
+           0.1776838433724393,
+           0.1583088649561787,
+           0.1397337301656813,
+           0.12216911311982737,
+           0.10578514084421241,
+           0.09070786361989608,
+           0.07701696084845275,
+           0.06474473172951607,
+           0.05387638668565036,
+           0.04435162181206707,
+           0.03606742552623045,
+           0.028882034880341908,
+           0.022619929477854447,
+           0.017077724347295504,
+           0.012030800142050133,
+           0.007240490231405412,
+           0.002461630098423364,
+           -0.002549734681015663,
+           -0.008028689507791327,
+           -0.014194047078028148,
+           -0.021241398425439647,
+           -0.029336806312605497,
+           -0.03861131192223804,
+           -0.0491564047233373,
+           -0.06102058044190493,
+           -0.07420708388234315,
+           -0.08867290263644262,
+           -0.10432904525874634,
+           -0.12104210410139613,
+           -0.13863706953377578,
+           -0.15690132957069805,
+           -0.17558975782748332,
+           -0.1944307640018767,
+           -0.2131331554830942,
+           -0.23139363686180062,
+           -0.24890475662210373,
+           -0.2653630975901987,
+           -0.28047750012740835,
+           -0.29397710479331174,
+           -0.3056190043395794,
+           -0.3151953033641193,
+           -0.3225393975614459,
+           -0.32753130292316274,
+           -0.330101888025343,
+           -0.3302358891306248,
+           -0.327973617578872,
+           -0.3234113011079328,
+           -0.3167000345400016,
+           -0.3080433498516183,
+           -0.29769345015711757,
+           -0.2859461857169226,
+           -0.2731348818951034,
+           -0.2596231582388218,
+           -0.2457969038011027,
+           -0.23205559582374985,
+           -0.2188031663812843,
+           -0.20643863411241822,
+           -0.19534672540738499,
+           -0.18588871118200342,
+           -0.17839368159232166,
+           -0.17315047180331913,
+           -0.17040043743296687,
+           -0.1703312588901134,
+           -0.17307192997428134,
+           -0.17868905838094618,
+           -0.1871845748269844,
+           -0.19849491412749387,
+           -0.21249169652837172,
+           -0.22898390178176478,
+           -0.24772149271719332,
+           -0.26840041028243206,
+           -0.2906688290550859,
+           -0.31413453186515805,
+           -0.3383732351640273,
+           -0.3629376737881684,
+           -0.3873672353604267,
+           -0.4111979211997229,
+           -0.4339724026006733,
+           -0.45524993889553983,
+           -0.4746159268838179,
+           -0.49169085993364636,
+           -0.5061384891124838,
+           -0.5176729977497104,
+           -0.5260650244066399,
+           -0.5311463967547049,
+           -0.532813469668667,
+           -0.5310289941769114,
+           -0.5258224789621043,
+           -0.5172890420181829,
+           -0.5055867859687861,
+           -0.49093276556404913,
+           -0.47359764914597596,
+           -0.45389920659974525,
+           -0.43219478374519416,
+           -0.4088729466067828,
+           -0.38434449796712733,
+           -0.3590330826058253,
+           -0.33336560632186,
+           -0.3077626970351077,
+           -0.2826294338966959,
+           -0.2583465624826197,
+           -0.2352624010082039,
+           -0.2136856244207997,
+           -0.19387909066359887,
+           -0.17605484692322462,
+           -0.16037042394213644,
+           -0.14692649423670567,
+           -0.13576593611645743,
+           -0.1268743105931722,
+           -0.12018172346336155,
+           -0.11556601090525756,
+           -0.11285715468958527,
+           -0.1118428033557622,
+           -0.11227474918168691,
+           -0.1138761881241445,
+           -0.11634957167853935,
+           -0.11938484624032221,
+           -0.12266786736329852,
+           -0.1258887734893852,
+           -0.12875010632354209,
+           -0.13097447296437448,
+           -0.1323115579600428,
+           -0.13254431129777514,
+           -0.1314941604917346,
+           -0.12902512083943898,
+           -0.1250467069095685,
+           -0.11951557966593093,
+           -0.11243589652791916,
+           -0.10385836528362938,
+           -0.09387803625765574,
+           -0.08263089964556598,
+           -0.07028938564097804,
+           -0.05705689312478498,
+           -0.04316149755067288,
+           -0.028849009621043108,
+           -0.014375572875977361,
+           -1.3268046304600217e-16
+          ],
+          [
+           0,
+           0.012849828920809356,
+           0.025055529673256905,
+           0.03642357196158343,
+           0.04678807382873185,
+           0.05601586501033057,
+           0.06401064733560882,
+           0.07071613790337383,
+           0.07611810714623357,
+           0.08024525257329711,
+           0.08316887922490297,
+           0.0850013889168603,
+           0.0858936114097868,
+           0.0860310409238761,
+           0.08562907016195082,
+           0.0849273404730346,
+           0.08418335031022725,
+           0.08366548410897054,
+           0.08364563962172411,
+           0.0843916431808168,
+           0.08615964902264543,
+           0.08918672051263242,
+           0.09368378780456973,
+           0.09982916821886138,
+           0.10776282262441118,
+           0.11758150367051026,
+           0.12933493026178713,
+           0.143023097726124,
+           0.15859480530577286,
+           0.1759474525922755,
+           0.19492812506891466,
+           0.21533595680078657,
+           0.2369257263210604,
+           0.25941261069997773,
+           0.2824779934267955,
+           0.30577619481964685,
+           0.32894196988077845,
+           0.3515985984355008,
+           0.3733663765423201,
+           0.3938713069452825,
+           0.41275378004989266,
+           0.4296770357120902,
+           0.44433520008100846,
+           0.4564607007489847,
+           0.46583087732965384,
+           0.47227362298002745,
+           0.47567191486585747,
+           0.4759671176005357,
+           0.4731609726370718,
+           0.4673162177583003,
+           0.45855581343465013,
+           0.44706078610690725,
+           0.43306673159118,
+           0.41685905398524276,
+           0.3987670458923775,
+           0.379156943725732,
+           0.35842411662811097,
+           0.3369845685314609,
+           0.3152659495716661,
+           0.29369828505714624,
+           0.2727046371689101,
+           0.252691916372043,
+           0.23404205609804563,
+           0.21710375569547932,
+           0.20218498315058187,
+           0.18954641097816158,
+           0.1793959364171312,
+           0.171884411177365,
+           0.16710267710642002,
+           0.16507997298037438,
+           0.1657837449323424,
+           0.16912085961192258,
+           0.1749401858328276,
+           0.18303647802545497,
+           0.19315546405462897,
+           0.20500001163651632,
+           0.21823722237864265,
+           0.2325062809816249,
+           0.24742686989695126,
+           0.26260794714352076,
+           0.27765667734313887,
+           0.2921873035164938,
+           0.3058297498344448,
+           0.31823775326589393,
+           0.3290963346988814,
+           0.33812843731172854,
+           0.34510058130017174,
+           0.34982740898756665,
+           0.3521750222342185,
+           0.35206304422238904,
+           0.3494653693747758,
+           0.34440959757951783,
+           0.33697518124091524,
+           0.3272903451524598,
+           0.3155278690211813,
+           0.3018998499260874,
+           0.2866515863955301,
+           0.27005474654306233,
+           0.2523999993050317,
+           0.23398929987646097,
+           0.21512802765954175,
+           0.19611717725718872,
+           0.17724580022340605,
+           0.1587838875094063,
+           0.14097587002945713,
+           0.12403489784153755,
+           0.10813803753274437,
+           0.09342250305448316,
+           0.07998300808936391,
+           0.0678702987413591,
+           0.05709089466648093,
+           0.04760803547960852,
+           0.03934379817503379,
+           0.032182321168813983,
+           0.025974042169904742,
+           0.02054083112963696,
+           0.01568187665861476,
+           0.011180165111137324,
+           0.006809376501579451,
+           0.0023410109116430234,
+           -0.002448446665419688,
+           -0.0077705158758679315,
+           -0.01381805361061801,
+           -0.020759109305361356,
+           -0.02873146894362627,
+           -0.0378380358685605,
+           -0.048143174791093535,
+           -0.05967012039773887,
+           -0.07239952434277618,
+           -0.08626918485573858,
+           -0.10117497245406513,
+           -0.11697293410095601,
+           -0.13348252737934385,
+           -0.15049090664512,
+           -0.1677581554285708,
+           -0.18502333427743944,
+           -0.20201119141815754,
+           -0.21843936561263594,
+           -0.23402589687052486,
+           -0.24849685159812676,
+           -0.26159386456645395,
+           -0.2730814008815144,
+           -0.2827535469338291,
+           -0.29044014996039996,
+           -0.29601214111769264,
+           -0.29938589646970554,
+           -0.3005265135649828,
+           -0.29944990773955515,
+           -0.296223661287292,
+           -0.2909665894681319,
+           -0.283847019214187,
+           -0.2750798085516445,
+           -0.26492216638206345,
+           -0.2536683625708771,
+           -0.24164344651546854,
+           -0.22919611780190874,
+           -0.2166909145675752,
+           -0.204499903209557,
+           -0.19299406665633642,
+           -0.18253459720258122,
+           -0.17346430366129995,
+           -0.1660993412058391,
+           -0.16072146577421445,
+           -0.15757100343481723,
+           -0.1568407089333681,
+           -0.15867066714033504,
+           -0.1631443667875461,
+           -0.17028604830915275,
+           -0.180059397453138,
+           -0.19236762433733917,
+           -0.20705493456705937,
+           -0.2239093657157227,
+           -0.24266692970905263,
+           -0.2630169702477418,
+           -0.28460861512198127,
+           -0.30705817683088715,
+           -0.32995733196880866,
+           -0.3528818909422029,
+           -0.375400955199471,
+           -0.3970862496458941,
+           -0.4175214135114482,
+           -0.436311033750739,
+           -0.45308921106394556,
+           -0.4675274596902565,
+           -0.4793417579723518,
+           -0.4882985869360585,
+           -0.4942198182800048,
+           -0.496986340637008,
+           -0.4965403430822344,
+           -0.4928862068885666,
+           -0.4860899896863715,
+           -0.47627751966523213,
+           -0.46363115044403963,
+           -0.44838525893087544,
+           -0.4308205981255612,
+           -0.41125764366732487,
+           -0.3900490963485369,
+           -0.36757172223860923,
+           -0.34421772702477793,
+           -0.32038587132321095,
+           -0.29647253880867236,
+           -0.27286296894181117,
+           -0.24992286085565024,
+           -0.22799054473893493,
+           -0.20736990208855843,
+           -0.18832419687774637,
+           -0.17107095648874437,
+           -0.15577801477089226,
+           -0.14256080046950687,
+           -0.13148092325369745,
+           -0.12254607742327835,
+           -0.11571125089369898,
+           -0.11088119504733718,
+           -0.1079140802898691,
+           -0.1066262334191206,
+           -0.10679782690634039,
+           -0.10817936754251019,
+           -0.11049881316649621,
+           -0.11346913182047912,
+           -0.11679610801443381,
+           -0.1201861960508159,
+           -0.1233542206649659,
+           -0.1260307305522233,
+           -0.12796882053049488,
+           -0.12895025285711875,
+           -0.12879072719714935,
+           -0.12734417143798046,
+           -0.12450595138172288,
+           -0.12021492566361834,
+           -0.11445430232260603,
+           -0.1072512845266002,
+           -0.09867552424388161,
+           -0.08883643336284335,
+           -0.07787943112028586,
+           -0.06598123396369138,
+           -0.05334431845899678,
+           -0.04019070894647387,
+           -0.02675525881357773,
+           -0.013278607064410634,
+           -1.2206290531976533e-16
+          ],
+          [
+           0,
+           0.011670747032584139,
+           0.022665317769504045,
+           0.032817621792248196,
+           0.041989697272164214,
+           0.05007593603729556,
+           0.057006412489780195,
+           0.06274922448999207,
+           0.06731177998731681,
+           0.07074099057581391,
+           0.07312236159222843,
+           0.07457799713340496,
+           0.07526356672099065,
+           0.07536430756388988,
+           0.07509016177140562,
+           0.07467017080553892,
+           0.07434626934394584,
+           0.0743666370459492,
+           0.07497877905198132,
+           0.07642251408048281,
+           0.07892305250179335,
+           0.0826843456651444,
+           0.08788288204739891,
+           0.09466209561102659,
+           0.10312753734664745,
+           0.11334294268143619,
+           0.12532730570573888,
+           0.13905304654021608,
+           0.15444533124216012,
+           0.17138257509840854,
+           0.18969813068165503,
+           0.20918313238964512,
+           0.2295904400817218,
+           0.2506395966014699,
+           0.2720226881244897,
+           0.2934109730460227,
+           0.31446212510967686,
+           0.3348279201831329,
+           0.35416218392553656,
+           0.3721288098788954,
+           0.38840965445731884,
+           0.40271211699374604,
+           0.4147762194071903,
+           0.4243810110310809,
+           0.4313501394384477,
+           0.4355564473487755,
+           0.4369254784425303,
+           0.43543780059385695,
+           0.43113008303755934,
+           0.42409489363281283,
+           0.41447921295127427,
+           0.40248169265582007,
+           0.3883487157972228,
+           0.3723693455019815,
+           0.35486927534898555,
+           0.33620391887821804,
+           0.3167507965488413,
+           0.2969013955539754,
+           0.2770526907848193,
+           0.25759852359979124,
+           0.23892103868788145,
+           0.22138237812818556,
+           0.20531682576605592,
+           0.191023584394683,
+           0.17876035320694975,
+           0.16873785393155266,
+           0.1611154314535982,
+           0.15599782909417534,
+           0.15343321071046684,
+           0.15341247206046665,
+           0.15586985317856156,
+           0.1606848325776964,
+           0.1676852536834204,
+           0.17665160475417604,
+           0.18732234635857142,
+           0.1994001559228875,
+           0.21255893752442506,
+           0.22645142750236216,
+           0.24071721300933754,
+           0.25499097165286444,
+           0.2689107360847558,
+           0.28212598788213283,
+           0.29430539030109404,
+           0.305143979332648,
+           0.31436964669566864,
+           0.3217487666024818,
+           0.327090839870314,
+           0.33025205368130034,
+           0.3311376823972979,
+           0.3297032836384385,
+           0.3259546736207132,
+           0.31994669577970775,
+           0.31178082624228065,
+           0.301601688016876,
+           0.2895925721596927,
+           0.27597008799075184,
+           0.26097808509889003,
+           0.24488100688539619,
+           0.22795684834179564,
+           0.21048989932965373,
+           0.1927634586302415,
+           0.17505270337471812,
+           0.15761789318283081,
+           0.14069807857678393,
+           0.1245054692553799,
+           0.10922059997496116,
+           0.09498841054716815,
+           0.08191533237205953,
+           0.0700674475924183,
+           0.05946975904960003,
+           0.05010658045008355,
+           0.04192302724244625,
+           0.03482756038667476,
+           0.028695508185618293,
+           0.02337346632222236,
+           0.018684453835565225,
+           0.01443368353675324,
+           0.010414789795045107,
+           0.0064163451052541174,
+           0.0022284896673292645,
+           -0.0023505044535715395,
+           -0.007507911098699985,
+           -0.013410639780554902,
+           -0.02019989668570931,
+           -0.027986561252609603,
+           -0.036847404040667456,
+           -0.04682224974518118,
+           -0.05791216466329432,
+           -0.07007872130082173,
+           -0.08324436480218803,
+           -0.09729387719532909,
+           -0.11207690679725232,
+           -0.12741150225064993,
+           -0.14308856426541175,
+           -0.15887710389252277,
+           -0.17453017467982748,
+           -0.1897913278987904,
+           -0.20440142565538003,
+           -0.21810563647885223,
+           -0.23066043218790588,
+           -0.2418404036223105,
+           -0.25144471624274134,
+           -0.25930303456934106,
+           -0.2652807567634247,
+           -0.26928341705989617,
+           -0.27126013383109904,
+           -0.2712060043140536,
+           -0.2691633728899377,
+           -0.26522192762849206,
+           -0.2595176089115118,
+           -0.25223034360606567,
+           -0.24358064773139743,
+           -0.23382516911833437,
+           -0.22325126848236243,
+           -0.2121707619461868,
+           -0.20091296973523778,
+           -0.18981723398203545,
+           -0.17922508284964606,
+           -0.16947222815397486,
+           -0.16088058906874378,
+           -0.1537505351874595,
+           -0.1483535381615276,
+           -0.14492541241822307,
+           -0.14366031228701584,
+           -0.1447056355389561,
+           -0.1481579622853502,
+           -0.15406013389573053,
+           -0.16239954966840717,
+           -0.1731077300730051,
+           -0.1860611651866059,
+           -0.20108343619939728,
+           -0.21794856732259751,
+           -0.23638553583737096,
+           -0.2560838401028129,
+           -0.27669999977769144,
+           -0.29786483993159857,
+           -0.31919139168060046,
+           -0.34028322694864577,
+           -0.3607430342989962,
+           -0.38018123676305093,
+           -0.39822445136687556,
+           -0.41452359365099145,
+           -0.42876143881093354,
+           -0.4406594639531475,
+           -0.4499838130504397,
+           -0.456550247077389,
+           -0.4602279659998201,
+           -0.4609422161940104,
+           -0.4586756258249987,
+           -0.4534682410135698,
+           -0.44541626653001765,
+           -0.4346695455171112,
+           -0.42142784261636396,
+           -0.4059360231249467,
+           -0.38847824675991915,
+           -0.36937131762369174,
+           -0.3489573514943233,
+           -0.3275959371370708,
+           -0.3056559795781726,
+           -0.2835074199334295,
+           -0.2615130282913976,
+           -0.2400204632792918,
+           -0.2193547843719514,
+           -0.1998115909389118,
+           -0.181650945770216,
+           -0.1650922207894647,
+           -0.1503099793561869,
+           -0.13743098356201705,
+           -0.1265323868848759,
+           -0.11764114317965435,
+           -0.1107346329819257,
+           -0.10574247822570018,
+           -0.10254948746504818,
+           -0.1009996462574299,
+           -0.10090104218778659,
+           -0.1020315917035438,
+           -0.10414541703559856,
+           -0.10697970645706971,
+           -0.11026188034072866,
+           -0.11371687917213545,
+           -0.11707438800086509,
+           -0.1200758147934189,
+           -0.12248084769894735,
+           -0.1240734281494643,
+           -0.12466699267800194,
+           -0.12410885593870329,
+           -0.12228363014951418,
+           -0.11911560147082767,
+           -0.11457001103895471,
+           -0.10865321680175351,
+           -0.10141174123563398,
+           -0.09293023872749097,
+           -0.08332844415768119,
+           -0.07275719032157336,
+           -0.06139360562052569,
+           -0.04943562434013706,
+           -0.03709595928976523,
+           -0.0245957001648945,
+           -0.012157710372978333,
+           -1.1130967973816593e-16
+          ],
+          [
+           0,
+           0.010496088284218085,
+           0.020302687333572735,
+           0.029280323979972222,
+           0.037317482961469334,
+           0.044334034947138314,
+           0.05028379258148508,
+           0.05515612352154247,
+           0.058976573965247914,
+           0.06180648192191706,
+           0.06374158580211821,
+           0.06490966013762278,
+           0.06546723571676603,
+           0.06559548548940239,
+           0.06549537964630833,
+           0.0653822327480868,
+           0.06547978217029418,
+           0.06601395002330813,
+           0.06720644976343,
+           0.06926840369769864,
+           0.07239413836260278,
+           0.07675532129541224,
+           0.08249559509158957,
+           0.0897258530326089,
+           0.09852028525557606,
+           0.10891330579269894,
+           0.12089744929239146,
+           0.13442230237490282,
+           0.14939450896383144,
+           0.1656788622057565,
+           0.18310046840784228,
+           0.20144794146480255,
+           0.22047756018514128,
+           0.2399182964144926,
+           0.25947759950634103,
+           0.2788478030704273,
+           0.2977130035330238,
+           0.31575624728862434,
+           0.332666854437541,
+           0.3481477025189802,
+           0.3619222933913702,
+           0.3737414305012452,
+           0.38338934213161224,
+           0.3906890986377024,
+           0.3955071878688322,
+           0.39775713255252815,
+           0.3974020559096055,
+           0.3944561266323648,
+           0.38898484098892305,
+           0.38110412756687534,
+           0.3709782883623639,
+           0.35881681786764863,
+           0.344870168827984,
+           0.32942455876540866,
+           0.3127959345796445,
+           0.29532323296497653,
+           0.2773610915247439,
+           0.2592721789000226,
+           0.241419321624875,
+           0.22415761054457523,
+           0.2078266703573486,
+           0.19274327214409698,
+           0.17919446072199738,
+           0.1674313564908531,
+           0.15766377543080268,
+           0.15005579144586162,
+           0.14472234280365595,
+           0.1417269595442785,
+           0.14108066202662195,
+           0.1427420528993146,
+           0.14661859640458919,
+           0.15256905073776927,
+           0.1604069918780804,
+           0.1699053415415633,
+           0.18080178830892377,
+           0.19280497012136386,
+           0.20560126871918769,
+           0.21886205264440947,
+           0.23225119547256748,
+           0.24543269021442335,
+           0.2580781794652437,
+           0.2698742239002581,
+           0.2805291390344733,
+           0.2897792415924252,
+           0.29739436207703773,
+           0.3031824988016642,
+           0.30699351028676714,
+           0.3087217669818424,
+           0.3083077091546339,
+           0.30573828485034504,
+           0.3010462693925998,
+           0.2943084952934279,
+           0.28564304798544954,
+           0.27520550783220427,
+           0.26318434179739864,
+           0.249795568399879,
+           0.23527683665520024,
+           0.21988107319357672,
+           0.2038698613244999,
+           0.18750672126513496,
+           0.1710504619408891,
+           0.154748771686557,
+           0.13883220791616208,
+           0.12350873458383824,
+           0.10895894132096243,
+           0.09533205989177457,
+           0.08274287252852007,
+           0.07126958332521612,
+           0.06095269878081523,
+           0.05179493742361811,
+           0.04376216188103218,
+           0.03678530045303419,
+           0.03076319986725433,
+           0.025566327077648412,
+           0.0210412163162181,
+           0.017015538662142726,
+           0.01330365563023839,
+           0.009712506095611547,
+           0.0060476675681192605,
+           0.00211942861523626,
+           -0.002251290791443775,
+           -0.0072273300647946355,
+           -0.01295014073684374,
+           -0.019535239831745658,
+           -0.027068386887372124,
+           -0.03560258878881856,
+           -0.045156015042587365,
+           -0.055710882443690726,
+           -0.06721334286912314,
+           -0.07957438180892625,
+           -0.09267170888246412,
+           -0.10635259565110391,
+           -0.12043759118768019,
+           -0.13472502272963502,
+           -0.1489961679157352,
+           -0.16302096711764677,
+           -0.17656412968851964,
+           -0.1893914769399616,
+           -0.2012763576133526,
+           -0.2120059687191349,
+           -0.22138741596244685,
+           -0.2292533535329213,
+           -0.2354670526826011,
+           -0.2399267620180602,
+           -0.24256923946319345,
+           -0.24337235599103751,
+           -0.2423566939809834,
+           -0.23958608786995095,
+           -0.2351670810180983,
+           -0.22924729974970195,
+           -0.22201277268514547,
+           -0.21368425007323835,
+           -0.2045126031995547,
+           -0.19477340745036797,
+           -0.1847608336621292,
+           -0.17478099045199905,
+           -0.16514487484720017,
+           -0.15616109933603184,
+           -0.14812857017091594,
+           -0.14132929418455187,
+           -0.13602148946029644,
+           -0.13243316896084018,
+           -0.1307563558055507,
+           -0.13114207454029406,
+           -0.13369624480564604,
+           -0.13847658271075172,
+           -0.14549059147014282,
+           -0.15469469703518804,
+           -0.1659945571782874,
+           -0.17924654443078514,
+           -0.1942603751196026,
+           -0.21080282918090876,
+           -0.22860247912630946,
+           -0.24735532214259612,
+           -0.26673118741824664,
+           -0.28638077194632816,
+           -0.30594314271737316,
+           -0.3250535317651803,
+           -0.3433512432460558,
+           -0.3604874887987173,
+           -0.3761329689224246,
+           -0.38998502399105817,
+           -0.40177418864950426,
+           -0.41126999747045706,
+           -0.418285907541297,
+           -0.4226832246690406,
+           -0.4243739436246339,
+           -0.42332243871790864,
+           -0.41954596837104385,
+           -0.41311398557451284,
+           -0.40414627447827095,
+           -0.392809961202073,
+           -0.37931547356577955,
+           -0.3639115491971835,
+           -0.346879413771352,
+           -0.3285262704327864,
+           -0.30917825728522563,
+           -0.2891730418244034,
+           -0.26885222905233525,
+           -0.24855376356513068,
+           -0.22860450507356053,
+           -0.20931315162813852,
+           -0.19096367541678197,
+           -0.17380942262529137,
+           -0.158068011838113,
+           -0.14391714523743,
+           -0.13149142393889446,
+           -0.1208802337540742,
+           -0.11212674111625774,
+           -0.10522801150656232,
+           -0.10013623514983089,
+           -0.0967610176957106,
+           -0.09497266772641838,
+           -0.09460638887517855,
+           -0.09546726268779063,
+           -0.09733588964291787,
+           -0.09997454041903982,
+           -0.10313365792695453,
+           -0.10655854309133259,
+           -0.10999605403721503,
+           -0.11320114928650546,
+           -0.11594311075766137,
+           -0.1180112916455994,
+           -0.11922024739302242,
+           -0.11941412460807113,
+           -0.1184702025084759,
+           -0.1163015037750659,
+           -0.11285841600993732,
+           -0.10812929069973636,
+           -0.10214001303157372,
+           -0.09495256242965992,
+           -0.08666260960566424,
+           -0.07739622059178977,
+           -0.06730576103158008,
+           -0.05656511436630692,
+           -0.045364344963224376,
+           -0.03390395124964225,
+           -0.022388864193018256,
+           -0.011022352745888682,
+           -1.0050939830742693e-16
+          ],
+          [
+           0,
+           0.009334905681965452,
+           0.017984896945979083,
+           0.025835850152490306,
+           0.0328008196466961,
+           0.03882272259259793,
+           0.04387619187780617,
+           0.0479685450848188,
+           0.05113984054090177,
+           0.05346201525012615,
+           0.05503712347441551,
+           0.05599471825773968,
+           0.0564884406814625,
+           0.056691902527386824,
+           0.05679396677614269,
+           0.05699354650331777,
+           0.05749405584042977,
+           0.05849765640444385,
+           0.060199448714141665,
+           0.0627817604409862,
+           0.06640868181770428,
+           0.0712209931777491,
+           0.07733162054724516,
+           0.0848217426751278,
+           0.09373765717185702,
+           0.10408849491743365,
+           0.11584485105129484,
+           0.12893837818529905,
+           0.14326236354836472,
+           0.1586732871720817,
+           0.17499333357340463,
+           0.19201380529872625,
+           0.20949936376600006,
+           0.22719300165329553,
+           0.24482163216647945,
+           0.262102164353539,
+           0.2787479206291635,
+           0.29447524316375856,
+           0.30901013002337197,
+           0.3220947400761648,
+           0.33349360776601494,
+           0.34299941485575985,
+           0.3504381760257175,
+           0.355673708547993,
+           0.35861127282600574,
+           0.3592002899936197,
+           0.35743606454041593,
+           0.35336046354106593,
+           0.3470615289432297,
+           0.3386720249036367,
+           0.3283669477324834,
+           0.3163600509867885,
+           0.3028994620320877,
+           0.2882624883859886,
+           0.27274973182659773,
+           0.25667864511035815,
+           0.24037667978222876,
+           0.2241741836399978,
+           0.20839721268441883,
+           0.193360424691421,
+           0.17936021982275455,
+           0.16666828798622133,
+           0.15552571310316546,
+           0.14613777127020047,
+           0.1386695433340283,
+           0.13324244303310598,
+           0.1299317400691823,
+           0.12876513378598356,
+           0.12972240812840005,
+           0.1327361728422861,
+           0.13769367007830924,
+           0.14443960031070685,
+           0.15277989738703937,
+           0.1624863601728985,
+           0.17330202818758497,
+           0.1849471713280067,
+           0.19712574966497431,
+           0.2095321887065968,
+           0.2218583087084729,
+           0.23380024372791247,
+           0.2450651872304817,
+           0.2553778061248472,
+           0.2644861739917979,
+           0.2721670867575331,
+           0.27823063982375285,
+           0.28252396431164467,
+           0.2849340411372132,
+           0.28538953458655125,
+           0.28386161133119475,
+           0.28036373581372526,
+           0.27495045802403156,
+           0.26771523425771265,
+           0.2587873448948501,
+           0.24832799498382813,
+           0.23652570292851233,
+           0.22359109938200128,
+           0.20975127213863418,
+           0.19524380305870495,
+           0.180310649614396,
+           0.165192026360138,
+           0.15012044045115028,
+           0.13531503030264183,
+           0.12097634773726362,
+           0.10728171174054155,
+           0.0943812465501308,
+           0.08239469864039974,
+           0.07140910669294126,
+           0.06147737638694103,
+           0.052617788365427326,
+           0.0448144436283416,
+           0.03801862648001748,
+           0.03215104162528501,
+           0.02710485965769949,
+           0.022749484577370017,
+           0.0189349386320988,
+           0.015496744154061883,
+           0.01226116955621011,
+           0.009050697570334294,
+           0.005689568378293238,
+           0.002009248643094979,
+           -0.0021463203741794237,
+           -0.006915836480073984,
+           -0.012416243306468672,
+           -0.01873894854079721,
+           -0.02594675603914311,
+           -0.034071595626469886,
+           -0.043113113617832495,
+           -0.05303816468609053,
+           -0.0637812222232448,
+           -0.0752457003891227,
+           -0.08730615722018187,
+           -0.09981132508722045,
+           -0.11258789303027696,
+           -0.1254449456157285,
+           -0.13817894546164014,
+           -0.15057913191052816,
+           -0.16243319687091057,
+           -0.1735330908972517,
+           -0.18368080834143766,
+           -0.19269400000396322,
+           -0.20041126515985988,
+           -0.2066969820566944,
+           -0.21144554680851838,
+           -0.21458490477865375,
+           -0.2160792757095472,
+           -0.21593099359788256,
+           -0.21418140414059006,
+           -0.21091078595210486,
+           -0.20623728609505673,
+           -0.2003148851699765,
+           -0.19333043165868488,
+           -0.1854998087998023,
+           -0.177063319402454,
+           -0.1682803941198134,
+           -0.1594237463004441,
+           -0.1507731111667647,
+           -0.14260871836314254,
+           -0.13520465458008904,
+           -0.12882227679379848,
+           -0.12370383655462691,
+           -0.1200664717037616,
+           -0.11809671398200956,
+           -0.11794564940137152,
+           -0.1197248532533263,
+           -0.12350320358650059,
+           -0.1293046563353598,
+           -0.13710704252068026,
+           -0.14684192362458875,
+           -0.1583955159600203,
+           -0.17161066922327287,
+           -0.1862898590652938,
+           -0.20219912906280876,
+           -0.21907289451357628,
+           -0.2366194995840969,
+           -0.25452740101626065,
+           -0.27247183630244787,
+           -0.2901218223432408,
+           -0.3071473224021932,
+           -0.3232264148714525,
+           -0.3380522970685656,
+           -0.3513399610085281,
+           -0.3628323857476844,
+           -0.37230610229293903,
+           -0.37957600193443214,
+           -0.3844992768313343,
+           -0.3869784023213569,
+           -0.38696309323247313,
+           -0.38445119089474045,
+           -0.37948846298635197,
+           -0.37216732418182474,
+           -0.3626245111729073,
+           -0.35103777038184697,
+           -0.3376216399809299,
+           -0.3226224291068403,
+           -0.30631251589843556,
+           -0.2889841017399376,
+           -0.27094257147992934,
+           -0.2524996181245066,
+           -0.2339662953656099,
+           -0.21564616219281244,
+           -0.1978286807368734,
+           -0.1807830214918883,
+           -0.1647524193417721,
+           -0.14994920964888525,
+           -0.1365506564050035,
+           -0.12469566453028344,
+           -0.11448244633141579,
+           -0.10596718844528784,
+           -0.09916374088718426,
+           -0.09404432470479794,
+           -0.09054122983186103,
+           -0.08854945065221605,
+           -0.08793018411904817,
+           -0.08851509458071073,
+           -0.09011123124991241,
+           -0.0925064689601564,
+           -0.09547533085184962,
+           -0.0987850432074383,
+           -0.1022016680077397,
+           -0.10549615801329253,
+           -0.10845018229133198,
+           -0.11086157702029836,
+           -0.11254928692462633,
+           -0.11335767654823017,
+           -0.11316010740823722,
+           -0.11186169645004714,
+           -0.1094011926567753,
+           -0.10575193160623093,
+           -0.1009218516356634,
+           -0.0949525794652055,
+           -0.08791761703475026,
+           -0.0799196843235855,
+           -0.071087294468319,
+           -0.06157065703093049,
+           -0.051537022304883384,
+           -0.041165593656206166,
+           -0.030642145725418284,
+           -0.020153493595123195,
+           -0.009881961576567648,
+           -8.974889810989019e-17
+          ],
+          [
+           0,
+           0.008195796570306146,
+           0.015728032045248475,
+           0.0225062506200151,
+           0.028465835611317623,
+           0.03357001639276151,
+           0.03781109763700888,
+           0.041210875781870285,
+           0.04382022882490161,
+           0.04571788712354936,
+           0.04700841428817903,
+           0.04781944795995417,
+           0.04829826973835968,
+           0.04860779126856772,
+           0.04892205906419025,
+           0.04942139362795685,
+           0.05028728850756867,
+           0.051697201825275235,
+           0.053819376365836835,
+           0.05680782440074225,
+           0.0607976100556613,
+           0.06590055526886486,
+           0.07220148540161836,
+           0.0797551175894385,
+           0.08858367928295716,
+           0.0986753265037712,
+           0.10998341157679284,
+           0.12242662898595628,
+           0.13589004605917432,
+           0.150227002967472,
+           0.1652618445767442,
+           0.18079342556749778,
+           0.19659931046788348,
+           0.21244057232545877,
+           0.22806707812574764,
+           0.24322313614682758,
+           0.2576533705488666,
+           0.2711086818912729,
+           0.2833521491225825,
+           0.2941647289887297,
+           0.3033506127555978,
+           0.3107421075555554,
+           0.3162039203730528,
+           0.3196367364275924,
+           0.32098000016425776,
+           0.32021382582580166,
+           0.3173599852015555,
+           0.31248194212606434,
+           0.3056839260989766,
+           0.2971090604608819,
+           0.2869365833235503,
+           0.27537822136010304,
+           0.2626737970738021,
+           0.2490861687799247,
+           0.2348956187958211,
+           0.22039381883949183,
+           0.20587751205359664,
+           0.19164205814200524,
+           0.17797499165386774,
+           0.16514974338592525,
+           0.15341967119616626,
+           0.14301253931801514,
+           0.13412557470770411,
+           0.1269212153039256,
+           0.121523648659887,
+           0.11801622062271698,
+           0.11643977304094852,
+           0.11679194738128731,
+           0.11902746816907397,
+           0.12305939689177768,
+           0.12876132398775395,
+           0.13597044434293262,
+           0.1444914408751803,
+           0.15410108180521626,
+           0.16455342055344882,
+           0.17558547326584387,
+           0.1869232380935995,
+           0.19828791279026184,
+           0.20940216312340815,
+           0.21999629411774005,
+           0.22981417925549782,
+           0.23861880937377,
+           0.24619733294550272,
+           0.2523654724593122,
+           0.2569712173946296,
+           0.2598977124281806,
+           0.2610652795529834,
+           0.2604325342434648,
+           0.2579965781279096,
+           0.2537922732796744,
+           0.24789062565210945,
+           0.2403963268067238,
+           0.23144452338831561,
+           0.2211969022869886,
+           0.20983719564378034,
+           0.1975662234099345,
+           0.18459660173250572,
+           0.17114725275891252,
+           0.15743785535925772,
+           0.14368337667204217,
+           0.13008882128791244,
+           0.11684432838602511,
+           0.10412073740194062,
+           0.09206573008856828,
+           0.08080064146022357,
+           0.07041801447778351,
+           0.06097995388925245,
+           0.052517313878388795,
+           0.04502973262003838,
+           0.0384865050389946,
+           0.0328282635694931,
+           0.027969416056197217,
+           0.023801270644231383,
+           0.02019576005992851,
+           0.017009662522956815,
+           0.014089204033868244,
+           0.011274917260996456,
+           0.008406625943940801,
+           0.005328420793497594,
+           0.0018934933707802951,
+           -0.002031301644300728,
+           -0.006561278134997628,
+           -0.011790256132903573,
+           -0.01778750399970845,
+           -0.024595368104006043,
+           -0.032227654962113314,
+           -0.04066881120238266,
+           -0.04987392592017208,
+           -0.05976955854260662,
+           -0.07025537376240805,
+           -0.08120654397545829,
+           -0.09247685950389242,
+           -0.10390246821787803,
+           -0.11530614946045765,
+           -0.12650201285770107,
+           -0.13730050102823416,
+           -0.14751356669042287,
+           -0.15695988942426728,
+           -0.16546999551860433,
+           -0.17289114597714972,
+           -0.17909186283687545,
+           -0.18396597235056508,
+           -0.1874360550999776,
+           -0.18945620745633446,
+           -0.19001403563860605,
+           -0.1891318225223112,
+           -0.18686682785452916,
+           -0.18331070412594688,
+           -0.17858803250091607,
+           -0.17285400535956408,
+           -0.1662913036085808,
+           -0.15910623742842894,
+           -0.15152423802937565,
+           -0.1437848048107083,
+           -0.1361360266312699,
+           -0.12882880734088262,
+           -0.1221109339975846,
+           -0.11622113108919625,
+           -0.11138324545701185,
+           -0.10780070443884705,
+           -0.1056513840504832,
+           -0.1050830149383537,
+           -0.10620924157549301,
+           -0.10910643502972499,
+           -0.11381134197187745,
+           -0.12031963283936453,
+           -0.12858539070604993,
+           -0.13852155995269602,
+           -0.15000135083118404,
+           -0.16286057303190388,
+           -0.1769008489596787,
+           -0.19189363614822835,
+           -0.20758496861845524,
+           -0.22370080949386412,
+           -0.23995289225750602,
+           -0.25604491603698476,
+           -0.2716789515334958,
+           -0.28656190888528327,
+           -0.3004119170084745,
+           -0.3129644658346954,
+           -0.323978168322106,
+           -0.33324000802376846,
+           -0.340569950139327,
+           -0.3458248090581923,
+           -0.3489012830583994,
+           -0.34973808662544686,
+           -0.3483171323178139,
+           -0.34466373670799644,
+           -0.3388458481196027,
+           -0.3309723170979337,
+           -0.32119025322889605,
+           -0.3096815335080393,
+           -0.29665854743406356,
+           -0.28235928187553583,
+           -0.267041864103763,
+           -0.2509786938294659,
+           -0.23445030432819078,
+           -0.21773909857014306,
+           -0.2011231085496466,
+           -0.18486992468994246,
+           -0.16923093732176203,
+           -0.15443602392712646,
+           -0.1406888043157196,
+           -0.12816257145102966,
+           -0.11699698862984122,
+           -0.10729562456676167,
+           -0.09912437712203033,
+           -0.09251081445281704,
+           -0.08744443980957954,
+           -0.08387786359747172,
+           -0.08172884423577685,
+           -0.08088313831941071,
+           -0.08119808113184686,
+           -0.08250680115429332,
+           -0.08462295728568466,
+           -0.08734587539377565,
+           -0.09046595184983888,
+           -0.09377018607034962,
+           -0.0970477019273435,
+           -0.10009511923694046,
+           -0.1027216413475896,
+           -0.10475373299434294,
+           -0.10603927384858289,
+           -0.10645108728238097,
+           -0.10588976042138698,
+           -0.10428569015727956,
+           -0.1016003099575114,
+           -0.09782647353516698,
+           -0.09298799318843279,
+           -0.08713835233851691,
+           -0.08035863293948389,
+           -0.07275471847131795,
+           -0.0644538516550563,
+           -0.055600642383599845,
+           -0.046352635234073784,
+           -0.03687555697048659,
+           -0.02733837238351735,
+           -0.01790828145055159,
+           -0.00874579201982631,
+           -7.911206545913137e-17
+          ],
+          [
+           0,
+           0.007086788962680569,
+           0.013546796457471847,
+           0.019311175408857455,
+           0.024335078137481973,
+           0.02859906081850012,
+           0.03210977678242046,
+           0.03489993816890605,
+           0.03702754453735926,
+           0.03857439619275067,
+           0.03964392871491097,
+           0.04035842300862898,
+           0.040855661666927744,
+           0.04128511714104119,
+           0.04180376976232957,
+           0.04257166374175833,
+           0.04374731662149619,
+           0.04548310207887262,
+           0.04792072736679125,
+           0.05118692497437075,
+           0.05538947334212112,
+           0.060613653778984956,
+           0.06691924028959745,
+           0.07433810608400537,
+           0.0828725154267529,
+           0.09249415256081335,
+           0.103143921133418,
+           0.11473252831005055,
+           0.1271418480686895,
+           0.14022703851009924,
+           0.15381936889305659,
+           0.1677296939852353,
+           0.18175249666637086,
+           0.19567040495025817,
+           0.20925907708004252,
+           0.22229233841599383,
+           0.23454744673188227,
+           0.24581035845102292,
+           0.25588086739731997,
+           0.2645774898442419,
+           0.2717419749713566,
+           0.27724332816231206,
+           0.28098124570406935,
+           0.2828888731092126,
+           0.2829348151525786,
+           0.28112434340643744,
+           0.2774997661454767,
+           0.2721399455092443,
+           0.26515896726709065,
+           0.2567039889289854,
+           0.24695231178545776,
+           0.23610774125488546,
+           0.22439631720502104,
+           0.21206151127290332,
+           0.19935900125500494,
+           0.1865511430556922,
+           0.17390126820909746,
+           0.1616679394402451,
+           0.1500992979938579,
+           0.13942763449992468,
+           0.12986431000888946,
+           0.121595145639245,
+           0.11477638823403816,
+           0.10953134578817246,
+           0.10594777051649784,
+           0.10407604966996045,
+           0.10392824500571105,
+           0.10547800164433392,
+           0.10866132639419852,
+           0.11337821499182216,
+           0.11949508759973175,
+           0.12684797280814636,
+           0.13524636276720708,
+           0.14447764635927055,
+           0.15431201388572746,
+           0.1645077159133307,
+           0.17481655096032706,
+           0.18498945179129414,
+           0.1947820383450201,
+           0.20396000677741197,
+           0.21230422871826565,
+           0.21961544249594994,
+           0.22571842858255975,
+           0.23046557458911276,
+           0.23373975046815706,
+           0.23545643177734485,
+           0.23556502749422684,
+           0.2340493884874859,
+           0.2309274928574106,
+           0.22625032446199989,
+           0.22009998054919308,
+           0.21258706303830208,
+           0.20384742517810164,
+           0.19403836063518964,
+           0.18333433516108946,
+           0.17192237153329898,
+           0.15999720621112068,
+           0.14775634090889958,
+           0.1353951139589724,
+           0.12310191488312176,
+           0.11105366106137175,
+           0.0994116479037093,
+           0.08831787369044394,
+           0.07789192751523437,
+           0.06822851386797017,
+           0.059395670712602586,
+           0.05143371987160724,
+           0.04435496958106386,
+           0.03814416970733468,
+           0.032759700806658666,
+           0.0281354594490084,
+           0.024183384489012475,
+           0.02079655269502561,
+           0.017852757750522478,
+           0.015218474480203423,
+           0.012753100530283754,
+           0.01031336088795368,
+           0.007757756728390592,
+           0.0049509392241126,
+           0.0017678911593397718,
+           -0.0019021955972530597,
+           -0.006152450628671989,
+           -0.011055356640399581,
+           -0.016660362261384162,
+           -0.022992140785406404,
+           -0.030049542807944866,
+           -0.03780527261640016,
+           -0.04620629931102264,
+           -0.05517499444896543,
+           -0.06461096900129208,
+           -0.07439356407499846,
+           -0.08438493264521293,
+           -0.09443363390472324,
+           -0.10437864816777703,
+           -0.11405370891252214,
+           -0.12329183980345157,
+           -0.13192997862844252,
+           -0.13981356717013402,
+           -0.14680098618920476,
+           -0.15276771793124355,
+           -0.15761012480582567,
+           -0.16124874197708453,
+           -0.16363099332861172,
+           -0.16473325433469155,
+           -0.164562201438043,
+           -0.16315540520409008,
+           -0.16058114335505852,
+           -0.15693742931566965,
+           -0.15235027163919923,
+           -0.14697119913528844,
+           -0.14097410520219117,
+           -0.13455148230730093,
+           -0.1279101333218026,
+           -0.12126646009994232,
+           -0.11484144095322076,
+           -0.10885541721677786,
+           -0.103522814717996,
+           -0.09904692848697631,
+           -0.09561489842203287,
+           -0.09339299984587106,
+           -0.09252236604278825,
+           -0.09311525011325458,
+           -0.0952519210510326,
+           -0.09897827413761216,
+           -0.10430421891655677,
+           -0.11120288956428306,
+           -0.11961070286233658,
+           -0.12942826867734336,
+           -0.14052213736430502,
+           -0.1527273483279739,
+           -0.16585072460019956,
+           -0.17967484019375077,
+           -0.1939625706197909,
+           -0.20846212270986778,
+           -0.22291242811497214,
+           -0.23704877585480097,
+           -0.25060855328275966,
+           -0.26333696196655,
+           -0.27499257533336685,
+           -0.2853526084871525,
+           -0.29421777728873433,
+           -0.3014166334371876,
+           -0.3068092746689018,
+           -0.31029034399923777,
+           -0.311791248810473,
+           -0.3112815491283458,
+           -0.3087694841768268,
+           -0.3043016267761654,
+           -0.29796167585454725,
+           -0.28986841777521155,
+           -0.2801729068420325,
+           -0.2690549337599333,
+           -0.2567188675456331,
+           -0.2433889710046182,
+           -0.22930430205916197,
+           -0.21471332263749884,
+           -0.19986834329136766,
+           -0.1850199350465394,
+           -0.17041144013402632,
+           -0.15627371020219935,
+           -0.14282019445427832,
+           -0.13024249104999513,
+           -0.11870646328533974,
+           -0.10834900781740547,
+           -0.09927554588854508,
+           -0.09155829053179641,
+           -0.08523532355427259,
+           -0.08031049617232522,
+           -0.07675414700449336,
+           -0.07450461121309404,
+           -0.07347047541309705,
+           -0.07353351500846979,
+           -0.0745522343111828,
+           -0.07636591554430433,
+           -0.07879907097410921,
+           -0.08166618324264978,
+           -0.084776612700317,
+           -0.08793954731350362,
+           -0.09096887061543667,
+           -0.09368782617070928,
+           -0.09593336305078856,
+           -0.0975600557083681,
+           -0.09844350316140824,
+           -0.09848312625637973,
+           -0.09760429762022205,
+           -0.09575975632864904,
+           -0.09293027787279452,
+           -0.08912458922735372,
+           -0.08437853822596691,
+           -0.07875354554460512,
+           -0.07233438590059989,
+           -0.06522636213370407,
+           -0.0575519512181631,
+           -0.04944701457583924,
+           -0.0410566759869228,
+           -0.03253097865417424,
+           -0.024020438363810064,
+           -0.01567161206839089,
+           -0.007622800537426246,
+           -6.867870746608381e-17
+          ],
+          [
+           0,
+           0.00601523610734062,
+           0.011454323438248058,
+           0.01626762861120483,
+           0.02042724200604711,
+           0.023927863856681164,
+           0.026787055977543033,
+           0.029044850715189363,
+           0.030762725508511155,
+           0.032021968040233995,
+           0.03292147294708991,
+           0.03357502601999825,
+           0.03410814538783636,
+           0.034654560992924,
+           0.035352423430835424,
+           0.036340340690485945,
+           0.037753346299080934,
+           0.039718904719414645,
+           0.04235305949891149,
+           0.04575682663298303,
+           0.05001292994951502,
+           0.05518296718224424,
+           0.061305084976612426,
+           0.06839222861823802,
+           0.07643101809860121,
+           0.08538128658582457,
+           0.09517630083648737,
+           0.10572366597866065,
+           0.11690689984341249,
+           0.1285876450531663,
+           0.1406084708156149,
+           0.1527962012298025,
+           0.16496569326796784,
+           0.17692397579782546,
+           0.18847465135511318,
+           0.19942245511277173,
+           0.2095778608095749,
+           0.21876162142228256,
+           0.22680913314955045,
+           0.2335745148126506,
+           0.23893430098910168,
+           0.24279065593579768,
+           0.24507402642051,
+           0.24574516469929159,
+           0.24479646773555241,
+           0.24225259499411642,
+           0.23817034436538248,
+           0.23263778356082385,
+           0.22577265223682397,
+           0.21772006771074748,
+           0.20864958399947328,
+           0.1987516696223557,
+           0.18823368378130698,
+           0.17731544281155087,
+           0.16622447888443778,
+           0.15519110058910932,
+           0.14444337003277463,
+           0.13420211335444013,
+           0.12467608098609063,
+           0.11605737062946227,
+           0.10851721982540961,
+           0.10220226632280996,
+           0.09723136341471812,
+           0.09369302426873799,
+           0.09164355435555052,
+           0.09110591473706253,
+           0.09206934161127212,
+           0.09448972954717198,
+           0.09829076771685981,
+           0.10336580058429747,
+           0.10958036737463271,
+           0.11677535864067813,
+           0.1247707137521404,
+           0.1333695705090981,
+           0.14236276762856936,
+           0.15153359282276307,
+           0.1606626637710501,
+           0.16953282661181085,
+           0.17793395670456866,
+           0.18566754932804203,
+           0.19255099360801162,
+           0.1984214311660163,
+           0.20313911153854586,
+           0.20659016907174618,
+           0.2086887604326524,
+           0.2093785177353763,
+           0.20863328916597756,
+           0.2064571564848252,
+           0.20288373645791577,
+           0.19797479068312235,
+           0.19181818500534997,
+           0.18452525534561723,
+           0.1762276509207732,
+           0.16707373815798707,
+           0.15722465881238565,
+           0.14685014363166538,
+           0.13612418819188574,
+           0.125220700131583,
+           0.11430922688122408,
+           0.10355087013435059,
+           0.09309448781574516,
+           0.0830732763163463,
+           0.07360181549205283,
+           0.06477364662827799,
+           0.056659439568236894,
+           0.049305789846771024,
+           0.042734670352279076,
+           0.03694354516973766,
+           0.03190613626354112,
+           0.027573816967991716,
+           0.023877590285514148,
+           0.020730595148937842,
+           0.01803107045665123,
+           0.01566569517210073,
+           0.013513213379634445,
+           0.011448246141126965,
+           0.00934518747685746,
+           0.007082079910691119,
+           0.0045443658182377,
+           0.0016284142742738798,
+           -0.00175527087766096,
+           -0.005679247569588604,
+           -0.010196811863458388,
+           -0.015340216743472673,
+           -0.021119481797144332,
+           -0.02752182680962086,
+           -0.03451174601183148,
+           -0.042031722994378046,
+           -0.05000356955023725,
+           -0.05833035536542051,
+           -0.06689887995297888,
+           -0.07558262391701166,
+           -0.08424510390424791,
+           -0.09274354477652194,
+           -0.10093277389564709,
+           -0.10866923617585374,
+           -0.11581502489088193,
+           -0.12224182222148754,
+           -0.1278346452261376,
+           -0.1324952972768861,
+           -0.13614543192082404,
+           -0.1387291454376613,
+           -0.14021502583819284,
+           -0.14059759940426766,
+           -0.13989813077831464,
+           -0.138164748699934,
+           -0.13547188635856267,
+           -0.13191904256449696,
+           -0.1276288871052817,
+           -0.12274475032113585,
+           -0.11742755268362332,
+           -0.11185224460001465,
+           -0.10620383942730993,
+           -0.1006731334412003,
+           -0.09545221499182868,
+           -0.09072987107147179,
+           -0.08668700286194779,
+           -0.08349216242994162,
+           -0.08129732057242559,
+           -0.08023397092649813,
+           -0.08040966796011381,
+           -0.08190508652917411,
+           -0.08477167855948542,
+           -0.08902998838120595,
+           -0.0946686726481565,
+           -0.10164425399359774,
+           -0.10988162001653114,
+           -0.11927526128687636,
+           -0.1296912242420082,
+           -0.14096973755747183,
+           -0.15292845423548918,
+           -0.16536623666754652,
+           -0.17806739866070265,
+           -0.1908063071982953,
+           -0.20335223781156844,
+           -0.21547437108988024,
+           -0.2269468142116372,
+           -0.23755353052812836,
+           -0.24709306220155244,
+           -0.2553829356413131,
+           -0.26226364688569465,
+           -0.26760213396072385,
+           -0.27129465537497516,
+           -0.2732690079838434,
+           -0.27348603313740466,
+           -0.27194037693097717,
+           -0.26866048809561976,
+           -0.2637078551659665,
+           -0.2571755026047416,
+           -0.24918578310835693,
+           -0.23988751993999785,
+           -0.22945256843222933,
+           -0.2180718793999052,
+           -0.2059511587775215,
+           -0.1933062270644343,
+           -0.18035818890483227,
+           -0.1673285271873828,
+           -0.15443423732846634,
+           -0.14188311587784255,
+           -0.12986931329992613,
+           -0.11856925384920043,
+           -0.10813801605081085,
+           -0.09870625565398768,
+           -0.09037773933795627,
+           -0.08322754225605912,
+           -0.07730094608159635,
+           -0.07261305697536247,
+           -0.06914914525655572,
+           -0.06686569096096787,
+           -0.06569210234650381,
+           -0.06553305817683379,
+           -0.06627140967701135,
+           -0.06777156477496683,
+           -0.06988326594282135,
+           -0.07244566390506274,
+           -0.0752915829033871,
+           -0.0782518692552339,
+           -0.08115971370398044,
+           -0.08385483955504351,
+           -0.08618745277720509,
+           -0.08802185700903924,
+           -0.08923964556908803,
+           -0.0897423938887384,
+           -0.08945378897846364,
+           -0.08832114726497584,
+           -0.08631628802495216,
+           -0.08343574628807782,
+           -0.07970032606771553,
+           -0.0751540116733572,
+           -0.06986227123990633,
+           -0.06390980206315215,
+           -0.0573977814707979,
+           -0.05044069942991054,
+           -0.04316285958283458,
+           -0.035694643652816306,
+           -0.028168639962808578,
+           -0.02071574002288844,
+           -0.013461307685477809,
+           -0.006521523232359448,
+           -5.852348480925827e-17
+          ],
+          [
+           0,
+           0.004987720565017255,
+           0.009462008495003844,
+           0.013389758965878854,
+           0.01675695020127215,
+           0.019569102452243164,
+           0.021851187485210748,
+           0.023646989598476106,
+           0.02501793353156755,
+           0.026041408600030635,
+           0.02680863162631369,
+           0.027422103408305937,
+           0.027992724260723165,
+           0.028636643305154724,
+           0.029471923437760672,
+           0.030615109082150378,
+           0.032177786803645005,
+           0.03426322954008873,
+           0.036963213571213634,
+           0.04035509343893938,
+           0.044499213937773216,
+           0.049436730165516155,
+           0.05518789665895003,
+           0.06175087508267658,
+           0.0691010970777302,
+           0.07719120502918692,
+           0.08595157902324221,
+           0.09529144349542283,
+           0.10510053239178002,
+           0.11525127744173881,
+           0.12560147073181824,
+           0.13599734051128673,
+           0.14627696836364368,
+           0.1562739668156353,
+           0.16582132935980165,
+           0.1747553599204227,
+           0.18291958612634981,
+           0.19016856044142452,
+           0.19637145525965885,
+           0.20141536245504602,
+           0.20520821448406498,
+           0.20768125281660324,
+           0.20879098001063096,
+           0.2085205438935387,
+           0.20688051577441416,
+           0.20390903905949298,
+           0.19967133972543094,
+           0.19425860545349455,
+           0.18778625546662345,
+           0.1803916378670422,
+           0.17223120518238574,
+           0.16347723155118285,
+           0.15431414620058548,
+           0.1449345673136522,
+           0.13553512781658228,
+           0.12631218985364576,
+           0.11745754762826284,
+           0.10915421879887575,
+           0.10157242271280492,
+           0.09486583948421551,
+           0.0891682373758824,
+           0.08459054728637314,
+           0.0812184525842258,
+           0.07911055032483655,
+           0.07829712633065103,
+           0.07877957204043363,
+           0.08053045579337596,
+           0.08349424567930712,
+           0.08758866563509465,
+           0.09270665147506273,
+           0.09871885937408413,
+           0.10547666631967335,
+           0.112815590528865,
+           0.12055905006525787,
+           0.12852237012630408,
+           0.13651694388653896,
+           0.14435444851109927,
+           0.1518510170708229,
+           0.1588312686119438,
+           0.16513210251746513,
+           0.17060616944315568,
+           0.1751249393630242,
+           0.17858129740964612,
+           0.18089160999024465,
+           0.18199721680624653,
+           0.18186531857580937,
+           0.1804892451045413,
+           0.17788810350245818,
+           0.17410582143147268,
+           0.1692096149161451,
+           0.1632879241014439,
+           0.1564478730557754,
+           0.14881232098531444,
+           0.14051658177299828,
+           0.13170489635197558,
+           0.12252674788726653,
+           0.11313311294263736,
+           0.10367274268043092,
+           0.0942885666666192,
+           0.08511430807634458,
+           0.07627139311857173,
+           0.06786622947861219,
+           0.05998791872119624,
+           0.05270645615687957,
+           0.04607145894220587,
+           0.04011144948234612,
+           0.03483370688051752,
+           0.0302246845929706,
+           0.026250977969183055,
+           0.02286081134823594,
+           0.019986001195959214,
+           0.017544339733848523,
+           0.015442332931144918,
+           0.013578217870034354,
+           0.011845177571389587,
+           0.010134666556557734,
+           0.008339757837870542,
+           0.006358421739098727,
+           0.004096648951570876,
+           0.0014713344789067933,
+           -0.0015871544963740097,
+           -0.005132795441033581,
+           -0.009202170503792044,
+           -0.01381321665543934,
+           -0.01896450002759617,
+           -0.02463503484986168,
+           -0.03078465316126926,
+           -0.037354917076742454,
+           -0.044270551187978825,
+           -0.05144135903155316,
+           -0.058764574811955086,
+           -0.0661275900482258,
+           -0.07341098481370825,
+           -0.08049178501507277,
+           -0.0872468609206872,
+           -0.09355637806131577,
+           -0.09930720979591016,
+           -0.10439622131321057,
+           -0.10873333761936586,
+           -0.11224431307834208,
+           -0.1148731272047942,
+           -0.11658394048428669,
+           -0.11736255479016881,
+           -0.11721733521347331,
+           -0.11617956351838887,
+           -0.11430320764829921,
+           -0.11166410638204473,
+           -0.10835858301068903,
+           -0.1045015164021184,
+           -0.10022391168077857,
+           -0.09567002562435072,
+           -0.09099411344353382,
+           -0.08635687357256812,
+           -0.08192167520316654,
+           -0.07785065933516318,
+           -0.07430080793631863,
+           -0.07142007729896624,
+           -0.06934369080769522,
+           -0.06819068310369773,
+           -0.06806078211991766,
+           -0.06903170779542626,
+           -0.0711569566399121,
+           -0.07446412994121378,
+           -0.0789538505654027,
+           -0.08459929930166507,
+           -0.09134638689387128,
+           -0.09911456263863605,
+           -0.10779824508902992,
+           -0.11726884535970121,
+           -0.127377339151981,
+           -0.13795733025988666,
+           -0.14882853630848372,
+           -0.1598006171108485,
+           -0.17067725756493868,
+           -0.18126041065670712,
+           -0.1913546020490203,
+           -0.20077119601993546,
+           -0.20933252321342494,
+           -0.21687577376614658,
+           -0.22325656480200862,
+           -0.228352098911669,
+           -0.23206383987247406,
+           -0.23431964328209537,
+           -0.2350752926989744,
+           -0.2343154059906941,
+           -0.23205369154441702,
+           -0.22833254942785672,
+           -0.2232220281294591,
+           -0.21681816277471871,
+           -0.20924073534077856,
+           -0.20063051101865395,
+           -0.19114601717117766,
+           -0.18095994200752688,
+           -0.17025523888455377,
+           -0.1592210288399958,
+           -0.14804839840360168,
+           -0.1369261918152569,
+           -0.12603689645825372,
+           -0.1155527176040927,
+           -0.10563193353416486,
+           -0.09641561488207079,
+           -0.0880247828102071,
+           -0.08055806962693535,
+           -0.07408993294060852,
+           -0.06866946074493967,
+           -0.06431979027645927,
+           -0.06103814843907784,
+           -0.05879650642451956,
+           -0.057542826244221176,
+           -0.05720286259474677,
+           -0.05768247015528532,
+           -0.058870354388047656,
+           -0.06064119347322318,
+           -0.06285905041245614,
+           -0.06538098778520442,
+           -0.06806079329622519,
+           -0.07075272221012091,
+           -0.07331516307323462,
+           -0.07561413575868522,
+           -0.077526535763402,
+           -0.07894304570714404,
+           -0.07977064395034839,
+           -0.07993465092982621,
+           -0.07938026593606928,
+           -0.07807356031505261,
+           -0.07600190713499533,
+           -0.07317384185931054,
+           -0.06961836314527997,
+           -0.06538369717687745,
+           -0.06053556258056487,
+           -0.05515498562255865,
+           -0.049335726728184794,
+           -0.04318138911494057,
+           -0.03680228824752015,
+           -0.030312166708526465,
+           -0.023824842787335945,
+           -0.017450882530927612,
+           -0.011294384140923503,
+           -0.005449960465010328,
+           -4.8714918725756347e-17
+          ],
+          [
+           0,
+           0.004009968957241977,
+           0.007579365989543841,
+           0.010688689141137898,
+           0.013334589353382583,
+           0.015529999089177397,
+           0.017303802154963528,
+           0.01870005242458568,
+           0.019776760979460947,
+           0.020604282504271054,
+           0.02126334232884676,
+           0.02184275501641963,
+           0.02243689362337464,
+           0.023142975485567638,
+           0.02405823544811526,
+           0.025277060718041686,
+           0.026888162896101044,
+           0.028971862196608928,
+           0.031597556401652106,
+           0.0348214427761693,
+           0.038684555097414274,
+           0.04321117027471379,
+           0.0484076299422216,
+           0.054261612123400305,
+           0.06074187684635634,
+           0.06779849771297218,
+           0.0753635791880987,
+           0.083352447083589,
+           0.0916652876734226,
+           0.10018919939267949,
+           0.10880061043360471,
+           0.11736800602498869,
+           0.12575490100799666,
+           0.1338229867107045,
+           0.1414353762447808,
+           0.1484598693282721,
+           0.15477215665956853,
+           0.1602588847627328,
+           0.16482050507790771,
+           0.1683738358183701,
+           0.17085427164680742,
+           0.1722175843820274,
+           0.172441267537455,
+           0.17152538828254046,
+           0.16949292214560466,
+           0.16638955815605422,
+           0.16228297485304552,
+           0.15726160035513506,
+           0.15143288217829767,
+           0.1449211044012355,
+           0.13786480081425984,
+           0.13041382257936127,
+           0.12272612743035421,
+           0.11496436434292652,
+           0.10729233273384706,
+           0.09987139847854141,
+           0.09285695028526542,
+           0.08639497919921221,
+           0.08061886124743964,
+           0.0756464185408313,
+           0.07157732763508237,
+           0.06849093577628854,
+           0.06644453601613699,
+           0.06547214131098594,
+           0.06558378588236097,
+           0.0667653696013955,
+           0.06897904827085038,
+           0.07216415972901673,
+           0.07623866300485765,
+           0.081101055621664,
+           0.08663272287177554,
+           0.09270066274092138,
+           0.0991605213928629,
+           0.10585986694481121,
+           0.1126416238439379,
+           0.11934758662427682,
+           0.12582193026407484,
+           0.13191463481028878,
+           0.13748474437442532,
+           0.14240338496824093,
+           0.14655647182789694,
+           0.14984704471534616,
+           0.15219717898993615,
+           0.15354943077967795,
+           0.15386778608866158,
+           0.15313809586970215,
+           0.1513679916680452,
+           0.14858628909268048,
+           0.14484189878506867,
+           0.14020227642603594,
+           0.1347514543594196,
+           0.12858770734618757,
+           0.12182091355351836,
+           0.1145696789218655,
+           0.10695829837039196,
+           0.09911363077150544,
+           0.09116196616875523,
+           0.0832259632973854,
+           0.07542173311033887,
+           0.06785613977975273,
+           0.06062438464678612,
+           0.053807930986437595,
+           0.04747281843416835,
+           0.04166840571769559,
+           0.03642656920949591,
+           0.03176137304504871,
+           0.02766921443595623,
+           0.02412943565107439,
+           0.021105382248493152,
+           0.01854587581514876,
+           0.01638705899299475,
+           0.014554561203199338,
+           0.012965925456723868,
+           0.011533230160754191,
+           0.010165835056616012,
+           0.008773177473790745,
+           0.007267544028283514,
+           0.005566743755969198,
+           0.003596611428455278,
+           0.0012932743785748246,
+           -0.0013948775528626197,
+           -0.004505571508575905,
+           -0.008061423930332297,
+           -0.01206913879885894,
+           -0.016519153762769523,
+           -0.02138574441769445,
+           -0.02662758502270153,
+           -0.03218875200025659,
+           -0.03800014496159613,
+           -0.043981289026327475,
+           -0.05004247214250458,
+           -0.056087162217752874,
+           -0.06201464137049922,
+           -0.06772278869538277,
+           -0.07311093876111796,
+           -0.07808274073154456,
+           -0.08254894258404075,
+           -0.08643002640867886,
+           -0.08965862417286118,
+           -0.09218164854849631,
+           -0.09396208029528448,
+           -0.09498036210510058,
+           -0.09523535853121602,
+           -0.09474485241146618,
+           -0.09354555977850589,
+           -0.09169265734454679,
+           -0.08925882895060493,
+           -0.08633284957362553,
+           -0.08301773728300983,
+           -0.07942851463461316,
+           -0.07568963110561557,
+           -0.07193210705199818,
+           -0.06829046708612843,
+           -0.06489953653550252,
+           -0.06189117860598374,
+           -0.05939105192931151,
+           -0.0575154682676888,
+           -0.05636842826900146,
+           -0.05603890935456537,
+           -0.05659847416516936,
+           -0.05809926062433366,
+           -0.06057240577649012,
+           -0.06402694533687306,
+           -0.06844921959699277,
+           -0.07380280423929637,
+           -0.08002897202186082,
+           -0.08704767850651912,
+           -0.09475905233480493,
+           -0.10304535831633008,
+           -0.11177339008434337,
+           -0.12079723857654132,
+           -0.1299613733744351,
+           -0.13910396620955945,
+           -0.14806037991092272,
+           -0.1566667418752896,
+           -0.1647635188952978,
+           -0.17219900993733864,
+           -0.17883267523000457,
+           -0.18453822376370385,
+           -0.18920638692349648,
+           -0.19274731334490164,
+           -0.19509252901811486,
+           -0.19619641695305068,
+           -0.19603718210607493,
+           -0.19461727948241533,
+           -0.19196329606903373,
+           -0.1881252902113658,
+           -0.1831756049086688,
+           -0.17720718395415602,
+           -0.1703314315852071,
+           -0.16267566705094302,
+           -0.15438023498913525,
+           -0.14559534050261977,
+           -0.13647768414456224,
+           -0.12718697651085806,
+           -0.11788241469045832,
+           -0.10871920338198311,
+           -0.09984520203798891,
+           -0.09139777598641874,
+           -0.08350092418985847,
+           -0.07626274927107482,
+           -0.06977332683429484,
+           -0.0641030211604138,
+           -0.059301283298306966,
+           -0.05539595568782064,
+           -0.0523930950269944,
+           -0.0502773124433561,
+           -0.04901261745848849,
+           -0.048543740055613384,
+           -0.048797893670408585,
+           -0.04968693140673335,
+           -0.05110983848780309,
+           -0.052955496115092426,
+           -0.05510564571082369,
+           -0.05743797811318188,
+           -0.05982926977949577,
+           -0.06215848748746043,
+           -0.06430978441541747,
+           -0.06617531378848962,
+           -0.06765779140916403,
+           -0.06867274521467479,
+           -0.06915039834328979,
+           -0.06903714183401308,
+           -0.06829656378384472,
+           -0.06691001327229688,
+           -0.0648766893439352,
+           -0.06221325751405323,
+           -0.058953008323718185,
+           -0.055144584115198646,
+           -0.05085031113505813,
+           -0.0461441840260309,
+           -0.0411095584913414,
+           -0.035836615188795766,
+           -0.030419663555842438,
+           -0.02495435814114483,
+           -0.019534902027938672,
+           -0.014251312031440413,
+           -0.009186818536905023,
+           -0.0044154691647951706,
+           -3.931448431194677e-17
+          ],
+          [
+           0,
+           0.0030867784128777677,
+           0.0058139112294994895,
+           0.008172385718557062,
+           0.010166201786898114,
+           0.011812270809471963,
+           0.013139949830177676,
+           0.01419022273083771,
+           0.015014549218661064,
+           0.015673411212590957,
+           0.016234594193761113,
+           0.01677124812144619,
+           0.017359778423647058,
+           0.01807762219931306,
+           0.019000967997746233,
+           0.020202479285611634,
+           0.02174908192606541,
+           0.02369987466911534,
+           0.026104218817433883,
+           0.02900005895541499,
+           0.03241252101557536,
+           0.03635282714346566,
+           0.04081755897842514,
+           0.045788292287296715,
+           0.05123161658745606,
+           0.05709954370602295,
+           0.06333029938592369,
+           0.06984948231277248,
+           0.07657156554357733,
+           0.08340170650525473,
+           0.09023782372011578,
+           0.09697289140961728,
+           0.10349739730493819,
+           0.10970190450247154,
+           0.11547965516045086,
+           0.1207291523202365,
+           0.12535665619506867,
+           0.12927853290420901,
+           0.13242339680614104,
+           0.13473399222740717,
+           0.13616876638376893,
+           0.13670309250389617,
+           0.13633011041862267,
+           0.13506116097080711,
+           0.13292580031074228,
+           0.12997139023290352,
+           0.12626227093483058,
+           0.12187853268753356,
+           0.1169144126508726,
+           0.11147635220732073,
+           0.10568075849825131,
+           0.09965152112339926,
+           0.09351734102642442,
+           0.08740893328730087,
+           0.081456168758445,
+           0.07578522113534666,
+           0.0705157861013603,
+           0.06575843762702185,
+           0.06161218337293803,
+           0.05816227651664813,
+           0.055478335309352415,
+           0.05361281441342702,
+           0.052599863752113445,
+           0.05245460142062404,
+           0.0531728173862828,
+           0.05473111448299926,
+           0.057087482830923346,
+           0.060182293537792045,
+           0.0639396876139732,
+           0.0682693266995655,
+           0.07306846368559247,
+           0.07822428381859459,
+           0.08361646058985192,
+           0.08911986577844822,
+           0.09460736955943513,
+           0.0999526646862446,
+           0.10503304845374652,
+           0.10973209744923029,
+           0.11394217296796079,
+           0.11756669933434004,
+           0.12052216311888513,
+           0.12273978823129732,
+           0.12416684992657336,
+           0.12476759968426497,
+           0.12452378248953289,
+           0.12343473802200827,
+           0.12151708739850196,
+           0.11880401716863068,
+           0.11534418198146977,
+           0.11120025648816162,
+           0.1064471753964504,
+           0.10117010794497444,
+           0.09546221923959626,
+           0.08942227574241617,
+           0.0831521556109091,
+           0.0767543264703647,
+           0.07032935352593374,
+           0.0639734996784362,
+           0.05777647653689189,
+           0.051819400994675774,
+           0.046173006465505026,
+           0.04089615110360016,
+           0.03603465753240678,
+           0.031620509976620914,
+           0.0276714254515534,
+           0.024190806045629606,
+           0.021168069578474058,
+           0.018579346273980737,
+           0.01638851979718494,
+           0.014548582298532084,
+           0.013003265207158844,
+           0.011688900613403214,
+           0.010536462351916638,
+           0.009473731482734556,
+           0.00842752787754157,
+           0.007325948125292856,
+           0.006100550010759352,
+           0.0046884253882980035,
+           0.0030341063295863855,
+           0.001091253889156162,
+           -0.0011759154091471437,
+           -0.00379150335515723,
+           -0.006767134217361704,
+           -0.010101510753444317,
+           -0.013780334329620307,
+           -0.01777659189378274,
+           -0.022051202953024776,
+           -0.026554010278998435,
+           -0.031225089044280823,
+           -0.03599634070877012,
+           -0.04079333044058413,
+           -0.04553732036318493,
+           -0.05014744563564304,
+           -0.054542976431968856,
+           -0.058645606390482316,
+           -0.06238170712121933,
+           -0.0656844889163787,
+           -0.06849600989512436,
+           -0.07076897938055492,
+           -0.07246830626694187,
+           -0.0735723493679085,
+           -0.0740738340874135,
+           -0.07398040804321375,
+           -0.07331481729110602,
+           -0.07211469432314724,
+           -0.07043195880658587,
+           -0.06833184184749845,
+           -0.06589155415816378,
+           -0.06319862763901503,
+           -0.0603489683246462,
+           -0.057444666175647724,
+           -0.05459161363293485,
+           -0.05189699002453582,
+           -0.04946667269337663,
+           -0.04740263799966285,
+           -0.04580041608113764,
+           -0.044746662405357046,
+           -0.04431690673591625,
+           -0.044573536213744554,
+           -0.04556406391719282,
+           -0.04731972763789624,
+           -0.049854455852766835,
+           -0.05316422917362933,
+           -0.057226856126336004,
+           -0.06200217218048091,
+           -0.06743266076172734,
+           -0.0734444847806927,
+           -0.07994890725541647,
+           -0.08684407013331476,
+           -0.0940170916661948,
+           -0.10134643487416302,
+           -0.10870449294417317,
+           -0.1159603320121808,
+           -0.12298252780850302,
+           -0.12964203020324705,
+           -0.13581498883449586,
+           -0.14138547375922403,
+           -0.14624802741924633,
+           -0.1503099881062133,
+           -0.15349353044742667,
+           -0.1557373750892043,
+           -0.15699812756554743,
+           -0.15725121511745313,
+           -0.15649139975913684,
+           -0.15473285594005817,
+           -0.1520088114815214,
+           -0.14837076082257875,
+           -0.14388726974024885,
+           -0.13864240036754422,
+           -0.1327337942849929,
+           -0.12627045949024476,
+           -0.11937031396167642,
+           -0.11215754415890697,
+           -0.10475984101073216,
+           -0.09730557862891125,
+           -0.0899210020917236,
+           -0.08272749014026547,
+           -0.0758389565385248,
+           -0.0693594502199391,
+           -0.06338100927041941,
+           -0.05798181740828529,
+           -0.053224704074704525,
+           -0.04915602073191574,
+           -0.045804916691970225,
+           -0.04318302799549497,
+           -0.04128458277020316,
+           -0.0400869163711952,
+           -0.03955137968863182,
+           -0.03962461454647421,
+           -0.0402401613402845,
+           -0.04132035618669973,
+           -0.04277846807355215,
+           -0.044521020971645925,
+           -0.04645024172941551,
+           -0.04846657191785786,
+           -0.05047118068595474,
+           -0.052368416148455825,
+           -0.05406813484152428,
+           -0.05548785229199366,
+           -0.05655466266030917,
+           -0.05720688160841972,
+           -0.05739537385314728,
+           -0.0570845351065765,
+           -0.05625290706859595,
+           -0.05489341359610514,
+           -0.0530132158898566,
+           -0.050633194268729365,
+           -0.04778707359790168,
+           -0.04452021846361678,
+           -0.04088813251692749,
+           -0.036954703833699726,
+           -0.032790244473021875,
+           -0.02846937750339777,
+           -0.024068828479619584,
+           -0.0196651806016431,
+           -0.015332653515663661,
+           -0.011140964910712208,
+           -0.007153331743936261,
+           -0.0034246641548218854,
+           -3.0375801154343544e-17
+          ],
+          [
+           0,
+           0.0022219555972443966,
+           0.004171069446503912,
+           0.005845571382185912,
+           0.007253435356323115,
+           0.008412151093116658,
+           0.009348226412036868,
+           0.010096432920519444,
+           0.010698814511709412,
+           0.011203484346991402,
+           0.011663241598237417,
+           0.0121340440280833,
+           0.012673376375221045,
+           0.013338557385694795,
+           0.014185030115982846,
+           0.015264680782031815,
+           0.01662423092170541,
+           0.01830374598666781,
+           0.02033530072267454,
+           0.022741837901568397,
+           0.025536252227140673,
+           0.028720725667476642,
+           0.03228633420650775,
+           0.036212939212857814,
+           0.04046936946401033,
+           0.045013892517150454,
+           0.049794966768584914,
+           0.05475225837572817,
+           0.059817900409421414,
+           0.0649179653313578,
+           0.0699741163102255,
+           0.0749053981425683,
+           0.07963012475156811,
+           0.08406781749675207,
+           0.08814114691183457,
+           0.09177783004054282,
+           0.09491243627645742,
+           0.09748805651838181,
+           0.09945779348427203,
+           0.10078603511303379,
+           0.10144947802697901,
+           0.10143787390697695,
+           0.1007544782049617,
+           0.09941618772466203,
+           0.09745336106790048,
+           0.09490932358802415,
+           0.09183956612672374,
+           0.08831065424828718,
+           0.08439887174336957,
+           0.08018862867883064,
+           0.07577067006060362,
+           0.07124012610978471,
+           0.0666944491058193,
+           0.062231284626462775,
+           0.057946326739984025,
+           0.053931207236981284,
+           0.050271468312473234,
+           0.047044666238560885,
+           0.04431865054813605,
+           0.04215005915322921,
+           0.040583064746502716,
+           0.03964840190391288,
+           0.039362697664549084,
+           0.039728121171380554,
+           0.040732360388896445,
+           0.0423489261543915,
+           0.04453777605757913,
+           0.04724624306699005,
+           0.050410246615317435,
+           0.053955757194426204,
+           0.057800479555679254,
+           0.06185571450663244,
+           0.06602835516419255,
+           0.07022297046622293,
+           0.07434392683114677,
+           0.07829749813301314,
+           0.08199391464318104,
+           0.08534930326510937,
+           0.0882874742123081,
+           0.09074151317987134,
+           0.09265514293930013,
+           0.09398382402287998,
+           0.09469557061509866,
+           0.09477146477460471,
+           0.09420585949777316,
+           0.09300626872176296,
+           0.09119294996417142,
+           0.08879819272125004,
+           0.08586533281506878,
+           0.08244751941911108,
+           0.0786062673421189,
+           0.07440983216952954,
+           0.06993144992936651,
+           0.06524748596762328,
+           0.06043553961588657,
+           0.05557255196799741,
+           0.050732963638729894,
+           0.04598696777085284,
+           0.04139890083144474,
+           0.037025809965612326,
+           0.03291623095337447,
+           0.02910920526440722,
+           0.025633558466973207,
+           0.022507455479927302,
+           0.019738241031271513,
+           0.01732256638305286,
+           0.01524679608422902,
+           0.013487681403792836,
+           0.012013280354192312,
+           0.010784098008634927,
+           0.009754415300264154,
+           0.008873769803881704,
+           0.008088548258332738,
+           0.00734364788244968,
+           0.006584161935966113,
+           0.005757044517650267,
+           0.004812710285889296,
+           0.003706526612911588,
+           0.002400158595107215,
+           0.000862731263550664,
+           -0.0009282218294878052,
+           -0.002986048853739785,
+           -0.005314527717172621,
+           -0.007907684051522592,
+           -0.010749884302989758,
+           -0.013816201869473412,
+           -0.01707304707981006,
+           -0.020479044894604184,
+           -0.023986137698163695,
+           -0.02754088461237156,
+           -0.03108592354736655,
+           -0.03456155784388986,
+           -0.0379074259698652,
+           -0.041064210396748006,
+           -0.04397534056045966,
+           -0.04658864474037314,
+           -0.04885790677200508,
+           -0.050744285719989915,
+           -0.05221755992434282,
+           -0.053257161114637394,
+           -0.05385296945809724,
+           -0.05400584634077779,
+           -0.05372788822869738,
+           -0.05304239195500383,
+           -0.05198352905541802,
+           -0.05059573414540017,
+           -0.04893281961406409,
+           -0.047056835919046434,
+           -0.045036703326895626,
+           -0.0429466468895022,
+           -0.040864471628016576,
+           -0.038869719179685326,
+           -0.03704175044020824,
+           -0.035457800919515836,
+           -0.03419105656418278,
+           -0.033308797655368205,
+           -0.03287065706675252,
+           -0.032927036691282496,
+           -0.033517722276063755,
+           -0.03467073232614082,
+           -0.03640143126000298,
+           -0.03871193075477729,
+           -0.04159079635876693,
+           -0.045013069140342386,
+           -0.04894060456365025,
+           -0.05332272311866326,
+           -0.05809715967363748,
+           -0.06319129124775902,
+           -0.06852361609956852,
+           -0.07400545086026297,
+           -0.07954280706252707,
+           -0.08503840395826477,
+           -0.09039377109318816,
+           -0.09551139179817568,
+           -0.10029683762481141,
+           -0.10466084382498801,
+           -0.10852127725172331,
+           -0.11180495051080036,
+           -0.11444923976197743,
+           -0.11640346816845508,
+           -0.1176300225128505,
+           -0.11810517680337083,
+           -0.11781960363216827,
+           -0.11677856145042613,
+           -0.1150017536116523,
+           -0.11252286281903694,
+           -0.10938877230531727,
+           -0.10565849248743191,
+           -0.10140181879328289,
+           -0.09669775268539223,
+           -0.09163272345289916,
+           -0.08629865297511975,
+           -0.08079090926525313,
+           -0.07520619709551626,
+           -0.06964043532604391,
+           -0.06418667067920737,
+           -0.0589330766179234,
+           -0.05396108372987592,
+           -0.049343684647032024,
+           -0.04514395212623579,
+           -0.041413803592194036,
+           -0.03819303933130954,
+           -0.03550867477531834,
+           -0.033374580094605304,
+           -0.03179143281072354,
+           -0.03074698152120425,
+           -0.030216611294567507,
+           -0.030164194024545163,
+           -0.030543200207931283,
+           -0.03129804239685721,
+           -0.03236561512485461,
+           -0.03367699154885873,
+           -0.03515923349589962,
+           -0.03673726913813758,
+           -0.03833579120044198,
+           -0.039881128459672746,
+           -0.04130304432377135,
+           -0.042536418452099344,
+           -0.04352277063822649,
+           -0.04421159043766047,
+           -0.04456144117623981,
+           -0.044540812888461546,
+           -0.044128705258619824,
+           -0.04331492860609884,
+           -0.042100118193555434,
+           -0.04049546446072361,
+           -0.0385221690130387,
+           -0.03621064314187818,
+           -0.03359947214791044,
+           -0.030734174618447515,
+           -0.02766579092710955,
+           -0.024449339452181414,
+           -0.021142182243926555,
+           -0.017802344031074925,
+           -0.014486829490071932,
+           -0.011249983583189635,
+           -0.008141938507937662,
+           -0.005207188423905051,
+           -0.0024833296957057537,
+           -2.1943931114862457e-17
+          ],
+          [
+           0,
+           0.0014182690548351041,
+           0.0026541127320424164,
+           0.0037096803053114926,
+           0.004593551551523369,
+           0.005320484142504626,
+           0.0059109857733642334,
+           0.006390722092300907,
+           0.006789775811122167,
+           0.007141776300881208,
+           0.007482922413010988,
+           0.007850924125370945,
+           0.008283890821434405,
+           0.008819195512454516,
+           0.00949234506761759,
+           0.010335886505430155,
+           0.011378378619661596,
+           0.012643456683167341,
+           0.01414901572981558,
+           0.015906535013476483,
+           0.017920562755167253,
+           0.020188376301385248,
+           0.022699828427515164,
+           0.025437385839316404,
+           0.02837636106975431,
+           0.031485334059325056,
+           0.03472675486860427,
+           0.03805771432362142,
+           0.04143086505489289,
+           0.044795471469170754,
+           0.04809856378862409,
+           0.05128616849203499,
+           0.054304585368572626,
+           0.05710168000204824,
+           0.05962815987943077,
+           0.06183880247996648,
+           0.06369360464916063,
+           0.0651588242742991,
+           0.06620788771526945,
+           0.06682213954828564,
+           0.06699141487619337,
+           0.06671441865798113,
+           0.0659989011099674,
+           0.06486162311977794,
+           0.06332811067222048,
+           0.061432202389628536,
+           0.059215399312967563,
+           0.05672603087047552,
+           0.054018255479148965,
+           0.051150918290011074,
+           0.04818629212029077,
+           0.04518873052688485,
+           0.04222326419332512,
+           0.03935417327149548,
+           0.03664356900234232,
+           0.03415001781891538,
+           0.03192724021203095,
+           0.030022914935136074,
+           0.028477616681179457,
+           0.027323912239233836,
+           0.026585636407778494,
+           0.026277364695297498,
+           0.026404095180226368,
+           0.026961146944427496,
+           0.02793427735779524,
+           0.029300015301154083,
+           0.031026202296502034,
+           0.033072728592246727,
+           0.035392446645921956,
+           0.03793224026968284,
+           0.04063422405587451,
+           0.043437044669311115,
+           0.04627725325259183,
+           0.049090716596828066,
+           0.05181403392023872,
+           0.054385926089608023,
+           0.05674856491331465,
+           0.058848811708621426,
+           0.06063933666010534,
+           0.0620795934823949,
+           0.06313662750392934,
+           0.0637856994096953,
+           0.06401071141764235,
+           0.06380442750353459,
+           0.06316848431290423,
+           0.06211319448278219,
+           0.06065714911499898,
+           0.058826630973951556,
+           0.05665485450657807,
+           0.05418105289045402,
+           0.0514494359075291,
+           0.04850804542916805,
+           0.045407537611063684,
+           0.04219992247935817,
+           0.03893729240526023,
+           0.035670570996984056,
+           0.032448313186880524,
+           0.029315585779520356,
+           0.026312955493424488,
+           0.02347560863316056,
+           0.020832623044049682,
+           0.01840640901765811,
+           0.016212331433736987,
+           0.014258520754222131,
+           0.012545875645124785,
+           0.011068255114486251,
+           0.00981285324180449,
+           0.008760744957160123,
+           0.007887587022233956,
+           0.007164454478078787,
+           0.006558789452784676,
+           0.006035436449858053,
+           0.005557736133865667,
+           0.0050886482454443995,
+           0.004591873646769487,
+           0.004032945635654955,
+           0.003380261566949882,
+           0.002606027459914368,
+           0.0016870906073450367,
+           0.0006056381763900495,
+           -0.0006502566737338392,
+           -0.002086255625611043,
+           -0.003701553082156609,
+           -0.005488856549524232,
+           -0.007434550210487347,
+           -0.009519037581695599,
+           -0.011717254458143311,
+           -0.013999338879890983,
+           -0.016331440723154473,
+           -0.01867664982551975,
+           -0.02099601839742912,
+           -0.023249650929984624,
+           -0.025397832947866007,
+           -0.027402168824026088,
+           -0.029226698499762425,
+           -0.030838963350675184,
+           -0.03221099259744495,
+           -0.03332018355269339,
+           -0.03415005157532562,
+           -0.03469082880824553,
+           -0.0349398945249577,
+           -0.03490202411227546,
+           -0.03458944826558192,
+           -0.03402171875638263,
+           -0.033225382029684114,
+           -0.03223346677837975,
+           -0.031084796400591454,
+           -0.029823141754119684,
+           -0.028496233766068406,
+           -0.027154659130476978,
+           -0.025850665439008273,
+           -0.02463690455982126,
+           -0.023565144843915562,
+           -0.022684983750118463,
+           -0.0220425927117384,
+           -0.02167952551129698,
+           -0.021631620095789394,
+           -0.02192802168405696,
+           -0.022590352239093975,
+           -0.02363204796788258,
+           -0.02505788255184425,
+           -0.026863689398178958,
+           -0.029036291443597918,
+           -0.03155364205338306,
+           -0.034385175462353056,
+           -0.037492360125131054,
+           -0.0408294434058226,
+           -0.04434437136329723,
+           -0.04797986309293921,
+           -0.051674615275027466,
+           -0.055364609348170765,
+           -0.058984491153670215,
+           -0.06246899104745079,
+           -0.06575435139675835,
+           -0.06877972809677702,
+           -0.0714885332657924,
+           -0.07382968759481436,
+           -0.07575875290758576,
+           -0.07723891827977473,
+           -0.07824181650453557,
+           -0.07874815169233518,
+           -0.07874812325897677,
+           -0.07824163637868851,
+           -0.07723829404178685,
+           -0.07575717103572328,
+           -0.0738263753383538,
+           -0.07148240744736667,
+           -0.06876933294763204,
+           -0.06573778802280845,
+           -0.062443841542044555,
+           -0.05894774070209655,
+           -0.05531256989878595,
+           -0.05160285447475581,
+           -0.047883142195972256,
+           -0.04421659571919821,
+           -0.04066362891817261,
+           -0.03728061874858188,
+           -0.03411872238166769,
+           -0.03122282667276704,
+           -0.028630653720848425,
+           -0.026372042400703347,
+           -0.02446842140701321,
+           -0.022932484646589122,
+           -0.021768074867849506,
+           -0.02097027634703913,
+           -0.02052571238357544,
+           -0.02041303841665878,
+           -0.020603616882971156,
+           -0.021062355605593514,
+           -0.021748687642673663,
+           -0.022617667224555254,
+           -0.023621153749622086,
+           -0.02470905385553914,
+           -0.025830590379823756,
+           -0.0269355665989688,
+           -0.027975594496523946,
+           -0.02890525694595635,
+           -0.029683175572881457,
+           -0.030272958634113514,
+           -0.030644006451473804,
+           -0.03077215568451978,
+           -0.03064014792297559,
+           -0.03023791262030273,
+           -0.029562659159824693,
+           -0.028618777723911377,
+           -0.027417553502242335,
+           -0.025976703504982747,
+           -0.024319749722335884,
+           -0.02247524648146574,
+           -0.02047588349266594,
+           -0.018357489158251746,
+           -0.016157961163513968,
+           -0.013916153118804115,
+           -0.011670747032584288,
+           -0.009459141642870122,
+           -0.007316386113923223,
+           -0.005274187330629694,
+           -0.0033600170280198836,
+           -0.0015963423292228531,
+           -1.4054791784244497e-17
+          ],
+          [
+           0,
+           0.0006774154348008294,
+           0.0012641256628124367,
+           0.001762857204179269,
+           0.002179491650953533,
+           0.002522890241183943,
+           0.0028046336937407306,
+           0.003038684088252938,
+           0.0032409776256858373,
+           0.0034289589320762657,
+           0.003621069124183686,
+           0.003836201101506779,
+           0.0040931364322503265,
+           0.004409978737992953,
+           0.004803598638779262,
+           0.005289105092468249,
+           0.005879357354417894,
+           0.0065845308105370965,
+           0.0074117486221574914,
+           0.00836478949745381,
+           0.009443880011473322,
+           0.010645577782242809,
+           0.011962749526577679,
+           0.013384645623136505,
+           0.014897070361882453,
+           0.016482644619797426,
+           0.01812115533371367,
+           0.0197899839021164,
+           0.021464603595250813,
+           0.023119134238822826,
+           0.02472694090716712,
+           0.026261262156127632,
+           0.027695852475234883,
+           0.02900562316548874,
+           0.03016726576623674,
+           0.03115984246568642,
+           0.03196532862812338,
+           0.03256909364092393,
+           0.032960307700694226,
+           0.033132263886443615,
+           0.03308260686690678,
+           0.03281346181047708,
+           0.032331459455614595,
+           0.03164765579869835,
+           0.03077734740392088,
+           0.0297397858734818,
+           0.028557797473752755,
+           0.02725731623375484,
+           0.025866840958964982,
+           0.02441682848358698,
+           0.02293903707139884,
+           0.021465835129673358,
+           0.020029491291134422,
+           0.018661462423019914,
+           0.01739169622709829,
+           0.016247964796736285,
+           0.015255244803518371,
+           0.01443515891286403,
+           0.013805491601282173,
+           0.013379790801735814,
+           0.013167064780297706,
+           0.013171581395908577,
+           0.013392774470245188,
+           0.01382525945537965,
+           0.01445895799478072,
+           0.01527932839128874,
+           0.01626769648674649,
+           0.017401679082951337,
+           0.018655689850167363,
+           0.0200015157305562,
+           0.02140895019647286,
+           0.022846468407405365,
+           0.024281928356025616,
+           0.025683281526078166,
+           0.02701927641589767,
+           0.028260138514663764,
+           0.029378210947663345,
+           0.030348541015708542,
+           0.031149399217061363,
+           0.03176271902365602,
+           0.032174447645226534,
+           0.03237480020647988,
+           0.03235841212949635,
+           0.03212438699766314,
+           0.031676239717443544,
+           0.031021737327704014,
+           0.030172642270981084,
+           0.02914436527662879,
+           0.0279555371551979,
+           0.026627510714343695,
+           0.025183805632719682,
+           0.023649510430514928,
+           0.022050656622459166,
+           0.020413580709040875,
+           0.018764289841533624,
+           0.017127846783098626,
+           0.01552778918835739,
+           0.013985597253649031,
+           0.012520222475081751,
+           0.011147688625377083,
+           0.00988077416496548,
+           0.008728783186009894,
+           0.007697409703627258,
+           0.006788697714204537,
+           0.006001096996674133,
+           0.0053296122003270805,
+           0.004766040403209706,
+           0.004299290097425018,
+           0.003915772517406819,
+           0.0035998544253075288,
+           0.0033343599488472055,
+           0.0031011078689400264,
+           0.002881469906671628,
+           0.0026569350824363143,
+           0.0024096651256013037,
+           0.002123026202666858,
+           0.0017820828976027275,
+           0.0013740414024724413,
+           0.0008886302332096567,
+           0.00031840843973976815,
+           -0.00034100681067042194,
+           -0.001090799281526405,
+           -0.0019289030820290572,
+           -0.0028500438195401185,
+           -0.00384587046049072,
+           -0.004905174496517112,
+           -0.006014190724499502,
+           -0.007156971805223879,
+           -0.008315826820114064,
+           -0.009471812348442113,
+           -0.010605263181953133,
+           -0.011696348715948554,
+           -0.012725640333360494,
+           -0.013674674750097489,
+           -0.014526498325424207,
+           -0.01526617776019261,
+           -0.015881263398552253,
+           -0.016362192496111653,
+           -0.01670262129123575,
+           -0.016899676479842255,
+           -0.01695411870395468,
+           -0.01687041287038117,
+           -0.01665670246319908,
+           -0.01632468744358101,
+           -0.015889407782053142,
+           -0.015368937080023284,
+           -0.014783993048712956,
+           -0.014157473766214597,
+           -0.013513930572846434,
+           -0.012878990142071653,
+           -0.012278739636196336,
+           -0.011739089887578547,
+           -0.01128513221028627,
+           -0.010940504726232422,
+           -0.010726783975522734,
+           -0.010662917074566316,
+           -0.010764708798639687,
+           -0.011044376718762712,
+           -0.01151018594559731,
+           -0.012166173163534891,
+           -0.013011967521430804,
+           -0.01404271363401952,
+           -0.015249099496294384,
+           -0.016617489582015612,
+           -0.018130160849040695,
+           -0.01976563687093567,
+           -0.021499112917903282,
+           -0.023302962579503168,
+           -0.025147314512032216,
+           -0.0270006861544903,
+           -0.028830659831945184,
+           -0.030604585589320665,
+           -0.032290294399129664,
+           -0.03385680508123272,
+           -0.035275008369413725,
+           -0.036518312056703583,
+           -0.037563232037358105,
+           -0.03838991531711552,
+           -0.038982582654667836,
+           -0.03932988038775228,
+           -0.039425133141123066,
+           -0.03926649145889285,
+           -0.03885697089338395,
+           -0.038204381656202026,
+           -0.03732115053217924,
+           -0.0362240393100479,
+           -0.034933766433149493,
+           -0.03347454085966306,
+           -0.031873519189273114,
+           -0.030160198911798494,
+           -0.02836576211958902,
+           -0.026522385163658378,
+           -0.02466253049631529,
+           -0.022818237312454203,
+           -0.021020427569300653,
+           -0.019298243531761034,
+           -0.017678432168914304,
+           -0.016184790537415564,
+           -0.014837684759504923,
+           -0.013653653375010852,
+           -0.012645103763617256,
+           -0.011820108047312839,
+           -0.011182302449856315,
+           -0.010730891570278511,
+           -0.010460756482916634,
+           -0.010362663069753947,
+           -0.01042356458336773,
+           -0.01062699018944651,
+           -0.010953509201475461,
+           -0.011381258946277313,
+           -0.011886522730514146,
+           -0.012444343250234474,
+           -0.013029156024817008,
+           -0.013615427060783166,
+           -0.01417827896792121,
+           -0.014694090158208543,
+           -0.0151410525456673,
+           -0.01549967431166317,
+           -0.015753215775512197,
+           -0.015888048176730233,
+           -0.015893927187820657,
+           -0.01576417518408378,
+           -0.015495768643735973,
+           -0.015089329478477045,
+           -0.014549021540496565,
+           -0.013882355955364464,
+           -0.013099911231087327,
+           -0.012214976234295285,
+           -0.011243126051625254,
+           -0.010201742419907829,
+           -0.009109491771397924,
+           -0.007985774966332994,
+           -0.006850163449371655,
+           -0.0057218368528917625,
+           -0.004619036972158901,
+           -0.003558552558133225,
+           -0.0025552485258623285,
+           -0.0016216519819784133,
+           -0.0007676059644469579,
+           -6.734692708291519e-18
+          ],
+          [
+           0,
+           6.016390498453092e-18,
+           1.1199603539593065e-17,
+           1.559017886370091e-17,
+           1.9257239773958414e-17,
+           2.229641500382736e-17,
+           2.4827004775959874e-17,
+           2.698846538686041e-17,
+           2.893630461065196e-17,
+           3.083749582828554e-17,
+           3.286553165683235e-17,
+           3.519524764745359e-17,
+           3.7997553087756365e-17,
+           4.143420891556367e-17,
+           4.5652792145524936e-17,
+           5.078198203627164e-17,
+           5.692729558255246e-17,
+           6.416738898991927e-17,
+           7.255102784784558e-17,
+           8.209481210556537e-17,
+           9.278172308596529e-17,
+           1.0456053911645112e-16,
+           1.1734614442743105e-16,
+           1.3102073331736546e-16,
+           1.454358887758467e-16,
+           1.6041549236559918e-16,
+           1.7575940075401702e-16,
+           1.9124780439503423e-16,
+           2.066461659959913e-16,
+           2.217106210156068e-16,
+           2.361937099212067e-16,
+           2.498503026083766e-16,
+           2.624435694977139e-16,
+           2.7375085152990506e-16,
+           2.835692826514096e-16,
+           2.9172102339711007e-16,
+           2.980579727213974e-16,
+           3.0246583710537373e-16,
+           3.0486745089220635e-16,
+           3.0522525941599246e-16,
+           3.035428963652688e-16,
+           2.9986580847706206e-16,
+           2.9428090356267246e-16,
+           2.869152214617249e-16,
+           2.779336512278022e-16,
+           2.675357410846177e-16,
+           2.5595166988421765e-16,
+           2.4343746940073696e-16,
+           2.302696052956126e-16,
+           2.1673904053459176e-16,
+           2.0314491802714803e-16,
+           1.8978800897105129e-16,
+           1.7696407957465293e-16,
+           1.6495733133931058e-16,
+           1.540340688464246e-16,
+           1.4443674403216401e-16,
+           1.363785173635895e-16,
+           1.3003846435674104e-16,
+           1.2555754078808754e-16,
+           1.230354021098244e-16,
+           1.2252815241884954e-16,
+           1.240470763377493e-16,
+           1.2755838387783712e-16,
+           1.3298397433503484e-16,
+           1.4020320110305183e-16,
+           1.4905559556234778e-16,
+           1.5934448549442017e-16,
+           1.7084142233063876e-16,
+           1.8329131248625824e-16,
+           1.9641813151518024e-16,
+           2.099310862489631e-16,
+           2.2353107978142134e-16,
+           2.369173273747041e-16,
+           2.4979396825429533e-16,
+           2.6187651889906223e-16,
+           2.7289801779647934e-16,
+           2.8261471960935865e-16,
+           2.908112080873077e-16,
+           2.973048115686948e-16,
+           3.0194922219599e-16,
+           3.0463723958028173e-16,
+           3.0530258111440633e-16,
+           3.039207239185041e-16,
+           3.005087669455144e-16,
+           2.9512432549809744e-16,
+           2.8786349373032164e-16,
+           2.7885793305584824e-16,
+           2.6827116521316107e-16,
+           2.562941675400706e-16,
+           2.4314038432789546e-16,
+           2.2904028156632382e-16,
+           2.1423558263093948e-16,
+           1.989733292645714e-16,
+           1.8349991540456888e-16,
+           1.680552409438985e-16,
+           1.5286712840866177e-16,
+           1.3814613790264096e-16,
+           1.2408090471248164e-16,
+           1.108341099689364e-16,
+           9.853917807906564e-17,
+           8.729777570621087e-17,
+           7.71781663590011e-17,
+           6.821445268091434e-17,
+           6.040671586156754e-17,
+           5.372203878969302e-17,
+           4.8096377207708497e-17,
+           4.343722176861894e-17,
+           3.962697407142171e-17,
+           3.652694195550878e-17,
+           3.398184401034608e-17,
+           3.1824700783905044e-17,
+           2.9881980859701285e-17,
+           2.797886404593146e-17,
+           2.5944481523801593e-17,
+           2.3616993989538237e-17,
+           2.0848373559498374e-17,
+           1.750876336479307e-17,
+           1.3490300129525488e-17,
+           8.710299313116926e-18,
+           3.1137192370004017e-18,
+           -3.3251604201064076e-18,
+           -1.0601889768671503e-17,
+           -1.868185178365348e-17,
+           -2.7501117306515213e-17,
+           -3.6968129682605824e-17,
+           -4.6966175019344706e-17,
+           -5.735657344518147e-17,
+           -6.798250778538264e-17,
+           -7.867338923090749e-17,
+           -8.924964529027302e-17,
+           -9.952780394664636e-17,
+           -1.0932573978542221e-16,
+           -1.1846794312264457e-16,
+           -1.267906719772626e-16,
+           -1.3414684912663473e-16,
+           -1.4041057241109954e-16,
+           -1.4548111576707823e-16,
+           -1.4928631094102754e-16,
+           -1.517852151608098e-16,
+           -1.5296998783677172e-16,
+           -1.5286691918943775e-16,
+           -1.5153657505993984e-16,
+           -1.4907304451941572e-16,
+           -1.4560229969486302e-16,
+           -1.4127969989935888e-16,
+           -1.3628669412435056e-16,
+           -1.3082679666732126e-16,
+           -1.2512092960630662e-16,
+           -1.1940224251332203e-16,
+           -1.1391053379700493e-16,
+           -1.0888640902185886e-16,
+           -1.0456531918355286e-16,
+           -1.0117162602509316e-16,
+           -9.89128419429748e-17,
+           -9.797418883155621e-17,
+           -9.851361341481103e-17,
+           -1.0065738637370627e-16,
+           -1.0449639913695013e-16,
+           -1.1008325588476567e-16,
+           -1.174302395137461e-16,
+           -1.2650820948214049e-16,
+           -1.372464671066015e-16,
+           -1.4953360055967288e-16,
+           -1.632192980934366e-16,
+           -1.7811709447110303e-16,
+           -1.9400799280407658e-16,
+           -2.1064488252849912e-16,
+           -2.2775765464239205e-16,
+           -2.450588980476149e-16,
+           -2.6225004632832853e-16,
+           -2.79027832910902e-16,
+           -2.9509090457410017e-16,
+           -3.1014643891449566e-16,
+           -3.2391661073347125e-16,
+           -3.3614475542071383e-16,
+           -3.4660108419471615e-16,
+           -3.550878163630021e-16,
+           -3.614436073370263e-16,
+           -3.655471676518383e-16,
+           -3.673199872993254e-16,
+           -3.667281008242596e-16,
+           -3.6378285134144313e-16,
+           -3.585406353583237e-16,
+           -3.511016344538965e-16,
+           -3.416075638840738e-16,
+           -3.3023849147211226e-16,
+           -3.172088021342805e-16,
+           -3.0276240355172945e-16,
+           -2.871672863405625e-16,
+           -2.7070956716134294e-16,
+           -2.536871551825705e-16,
+           -2.364031908821141e-16,
+           -2.1915941113209424e-16,
+           -2.022495957507732e-16,
+           -1.8595324819525748e-16,
+           -1.7052965687908454e-16,
+           -1.5621247388679593e-16,
+           -1.4320493486734258e-16,
+           -1.3167582794392606e-16,
+           -1.217563009755319e-16,
+           -1.1353757590352572e-16,
+           -1.07069616724223e-16,
+           -1.023607743928061e-16,
+           -9.937840825729028e-17,
+           -9.805046002597119e-17,
+           -9.826793336660629e-17,
+           -9.988821058090013e-17,
+           -1.027391179221826e-16,
+           -1.0662363351093301e-16,
+           -1.113251168785435e-16,
+           -1.1661292729356846e-16,
+           -1.2224828947971194e-16,
+           -1.2799026032077797e-16,
+           -1.33601648776847e-16,
+           -1.3885474352946894e-16,
+           -1.435367087622247e-16,
+           -1.4745451780807485e-16,
+           -1.5043930691291777e-16,
+           -1.5235004675344262e-16,
+           -1.5307644721352108e-16,
+           -1.5254103081329106e-16,
+           -1.507003315954054e-16,
+           -1.4754519866356639e-16,
+           -1.4310020637599505e-16,
+           -1.3742219584823176e-16,
+           -1.3059799434800529e-16,
+           -1.2274137982135599e-16,
+           -1.1398937665820492e-16,
+           -1.044979854171933e-16,
+           -9.443746317135435e-17,
+           -8.398728206307215e-17,
+           -7.333090130008761e-17,
+           -6.265049199807375e-17,
+           -5.212175488092305e-17,
+           -4.19089678785978e-17,
+           -3.2160394195314494e-17,
+           -2.300417162688395e-17,
+           -1.4544791037752306e-17,
+           -6.860256295321934e-18,
+           -5.999039130647426e-32
+          ]
+         ],
+         "z": [
+          [
+           2,
+           2.130332796838008,
+           2.256753911784933,
+           2.376789638294702,
+           2.488075604138452,
+           2.588407808013885,
+           2.675789958185559,
+           2.7484760201951044,
+           2.805006995826015,
+           2.8442410940625464,
+           2.865376613357637,
+           2.867967029244015,
+           2.8519279679163567,
+           2.817535940324214,
+           2.7654189078139355,
+           2.696538944653189,
+           2.6121674501337298,
+           2.5138535388224583,
+           2.403386397651281,
+           2.2827525390293038,
+           2.154088996640754,
+           2.0196336022438546,
+           1.8816735454341926,
+           1.7424934524981004,
+           1.6043242244022853,
+           1.4692938476366197,
+           1.3393813357838407,
+           1.2163748757950643,
+           1.1018351431545763,
+           0.9970646172067862,
+           0.9030835752431645,
+           0.8206132753387548,
+           0.7500666576036418,
+           0.6915467059718643,
+           0.6448524225548543,
+           0.6094921786570255,
+           0.5847040254418049,
+           0.5694823774212108,
+           0.5626103276043474,
+           0.562696718068872,
+           0.568216977215646,
+           0.5775566477621683,
+           0.589056469720342,
+           0.6010578515962625,
+           0.6119475615298626,
+           0.6202004980084016,
+           0.6244194563522353,
+           0.6233708908814289,
+           0.616015781348306,
+           0.6015348430632947,
+           0.5793474697981014,
+           0.5491239632035355,
+           0.5107907779410832,
+           0.4645286935439924,
+           0.4107640075879514,
+           0.35015302541788323,
+           0.28356029487838363,
+           0.21203119585578453,
+           0.13675963988628234,
+           0.05905176094738821,
+           -0.019713418345185477,
+           -0.09812528316559538,
+           -0.17478377313093832,
+           -0.2483412449370153,
+           -0.3175429240306221,
+           -0.3812648546229005,
+           -0.43854832164009483,
+           -0.4886298089205054,
+           -0.5309656728128324,
+           -0.5652508464155105,
+           -0.5914310435863067,
+           -0.6097080996627086,
+           -0.6205382633289118,
+           -0.6246234367591293,
+           -0.6228955444384521,
+           -0.6164943902707143,
+           -0.606739533182977,
+           -0.5950968690939954,
+           -0.5831407478136716,
+           -0.5725125735862396,
+           -0.564876934495972,
+           -0.5618763763227153,
+           -0.5650859788187031,
+           -0.5759689056289827,
+           -0.5958340827741818,
+           -0.6257971150739303,
+           -0.6667454761620001,
+           -0.7193089075868944,
+           -0.7838358383252534,
+           -0.860376490885721,
+           -0.9486731776038657,
+           -1.0481581147228927,
+           -1.157958896762308,
+           -1.2769115840757097,
+           -1.4035811670905025,
+           -1.536288986213304,
+           -1.6731465113714492,
+           -1.8120947240139385,
+           -1.9509482011513046,
+           -2.0874428792756796,
+           -2.2192863788470563,
+           -2.3442096999359485,
+           -2.4600190583883133,
+           -2.5646466206285163,
+           -2.656198914305576,
+           -2.733001741033373,
+           -2.793640495355376,
+           -2.8369948989436145,
+           -2.8622672884173284,
+           -2.8690037459293434,
+           -2.8571075301766835,
+           -2.8268444476640338,
+           -2.778839995460327,
+           -2.714068302683439,
+           -2.633833093751007,
+           -2.5397410872713246,
+           -2.433668425658943,
+           -2.3177208977183823,
+           -2.194188865460708,
+           -2.0654979336576758,
+           -1.9341565029841026,
+           -1.8027014225470428,
+           -1.673643003315771,
+           -1.5494106693307361,
+           -1.432300508206476,
+           -1.3244259367287958,
+           -1.2276726223996803,
+           -1.143658699438247,
+           -1.0737011905070444,
+           -1.0187893964125891,
+           -0.9795658488710625,
+           -0.9563152402204208,
+           -0.9489615531250435,
+           -0.9570734175169213,
+           -0.9798775260235782,
+           -1.0162797477220724,
+           -1.0648933978872752,
+           -1.1240739528948953,
+           -1.191959348678073,
+           -1.2665148717614474,
+           -1.3455815470181587,
+           -1.426926848416447,
+           -1.5082965099775545,
+           -1.5874661950782214,
+           -1.662291793481848,
+           -1.7307571567074012,
+           -1.791018152441967,
+           -1.8414420158585025,
+           -1.880641097439626,
+           -1.9075002501526428,
+           -1.9211972599688287,
+           -1.9212158987340744,
+           -1.9073513629076277,
+           -1.8797080510947568,
+           -1.8386898229007402,
+           -1.7849830667268025,
+           -1.7195330801350512,
+           -1.643514428987137,
+           -1.558296096711596,
+           -1.4654023592217986,
+           -1.3664704211642016,
+           -1.2632059229044617,
+           -1.1573374731997923,
+           -1.0505713788099913,
+           -0.9445477290492286,
+           -0.8407989508968838,
+           -0.7407118799175634,
+           -0.645494295734913,
+           -0.5561467506582967,
+           -0.47344037936217304,
+           -0.39790121986060634,
+           -0.3298014054193769,
+           -0.2691574078403067,
+           -0.21573532928103656,
+           -0.16906305707992222,
+           -0.1284489185605246,
+           -0.09300630497914189,
+           -0.06168357988930772,
+           -0.03329845111287882,
+           -0.006575870661041266,
+           0.019811563763794626,
+           0.04720179634599987,
+           0.07690121672611482,
+           0.11014341376919395,
+           0.14804989189739776,
+           0.19159381192176567,
+           0.24156774056072752,
+           0.29855628972809545,
+           0.3629144008106004,
+           0.43475188370873713,
+           0.5139246590543266,
+           0.60003297881744,
+           0.6924267198491046,
+           0.7902176613420437,
+           0.8922984753753752,
+           0.9973679842477005,
+           1.1039620736499134,
+           1.210489501072855,
+           1.3152717080029064,
+           1.4165856357825461,
+           1.5127084613030342,
+           1.601963112132467,
+           1.682763392766697,
+           1.7536575552108429,
+           1.8133691781075414,
+           1.8608342784386231,
+           1.8952336670319472,
+           1.9160196716095936,
+           1.922936486185448,
+           1.916033559958485,
+           1.895671608663898,
+           1.8625210124541185,
+           1.8175525523118523,
+           1.762020627093329,
+           1.6974392808435306,
+           1.6255515503499745,
+           1.5482928115106325,
+           1.4677489557673422,
+           1.3861103607672236,
+           1.3056227292110403,
+           1.2285359537427785,
+           1.1570522215788412,
+           1.0932745989052495,
+           1.0391573311513418,
+           0.9964590610873105,
+           0.9667001030453637,
+           0.9511248199133455,
+           0.9506700320705619,
+           0.9659402469434338,
+           0.9971903377389502,
+           1.0443161240403631,
+           1.1068531195884053,
+           1.1839835182767917,
+           1.2745512928931142,
+           1.3770850872253881,
+           1.489828395561497,
+           1.61077634889063,
+           1.7377182685412587,
+           1.868285009436098,
+           1.9999999999999987
+          ],
+          [
+           2.0918833918127375,
+           2.220837794218755,
+           2.344259914887943,
+           2.4597370308582525,
+           2.5649977042183587,
+           2.657960734972634,
+           2.736779746720657,
+           2.7998823772730286,
+           2.8460031757078474,
+           2.8742094582391693,
+           2.883919543933573,
+           2.8749129736538097,
+           2.84733250717748,
+           2.801677889559804,
+           2.738791573701678,
+           2.659836776976977,
+           2.5662684310239836,
+           2.45979775101499,
+           2.342351299835696,
+           2.216025550032304,
+           2.083038049057366,
+           1.9456763688167729,
+           1.8062460670136273,
+           1.6670189042397519,
+           1.5301825468628176,
+           1.3977929419250008,
+           1.2717304776725906,
+           1.153660943846501,
+           1.0450021820120727,
+           0.9468971711194766,
+           0.8601941308079342,
+           0.7854340487687614,
+           0.7228458531603885,
+           0.6723492612351014,
+           0.6335651457058452,
+           0.6058330756495923,
+           0.5882355134769512,
+           0.5796279880157202,
+           0.5786744200266037,
+           0.5838866540094944,
+           0.5936671519486121,
+           0.6063537330539815,
+           0.6202652002862374,
+           0.6337466804926718,
+           0.64521352059225,
+           0.6531926269444629,
+           0.6563602076137602,
+           0.653574975795335,
+           0.6439059946500445,
+           0.6266544860748317,
+           0.6013690848754866,
+           0.5678541913642802,
+           0.5261712552189497,
+           0.4766330069535959,
+           0.4197908359212798,
+           0.3564156907769306,
+           0.28747304530691586,
+           0.2140926252644645,
+           0.13753372648628756,
+           0.05914706771198671,
+           -0.019665789665915007,
+           -0.09749436046273734,
+           -0.17296136462471862,
+           -0.24476393257263826,
+           -0.31171277735275166,
+           -0.372768276523337,
+           -0.42707248643245793,
+           -0.47397621644282223,
+           -0.5130604180851722,
+           -0.5441512908558708,
+           -0.5673286687122783,
+           -0.5829274251605023,
+           -0.5915318157803515,
+           -0.5939628605148796,
+           -0.5912590494212142,
+           -0.5846508302376766,
+           -0.5755294996345505,
+           -0.5654112682216883,
+           -0.5558973985031683,
+           -0.5486314216890218,
+           -0.5452545208449177,
+           -0.5473602221573614,
+           -0.5564495616693248,
+           -0.5738878909713407,
+           -0.6008644520243276,
+           -0.6383557892880606,
+           -0.6870939780981391,
+           -0.7475405339230612,
+           -0.819866730521655,
+           -0.9039408994523177,
+           -0.9993231126826086,
+           -1.1052674684198744,
+           -1.220732012221685,
+           -1.3443961356102592,
+           -1.474685107524109,
+           -1.6098012146463725,
+           -1.7477608194289307,
+           -1.886436493670522,
+           -2.0236032545983598,
+           -2.1569878228507164,
+           -2.284319740295273,
+           -2.403383132338803,
+           -2.512067875688849,
+           -2.608418939090664,
+           -2.6906827013106405,
+           -2.7573491167528177,
+           -2.807188693035342,
+           -2.8392833643872937,
+           -2.853050486987476,
+           -2.848259343926195,
+           -2.8250397244187306,
+           -2.7838823299415156,
+           -2.7256309545263067,
+           -2.651466582795429,
+           -2.5628837426642175,
+           -2.4616596352554474,
+           -2.349816737929789,
+           -2.229579733197622,
+           -2.103327752803413,
+           -1.9735430391224216,
+           -1.8427572124169354,
+           -1.7134963903483176,
+           -1.588226434012619,
+           -1.4692995919764495,
+           -1.3589037804013322,
+           -1.2590156741729583,
+           -1.1713586925401287,
+           -1.0973668453503873,
+           -1.0381552654154858,
+           -0.9944980922846803,
+           -0.9668141966626702,
+           -0.9551610471810107,
+           -0.9592368267939514,
+           -0.9783907094641843,
+           -1.0116410138213918,
+           -1.0577007638377283,
+           -1.1150100118046549,
+           -1.1817741202526957,
+           -1.2560070607663636,
+           -1.3355786722516485,
+           -1.4182647318766854,
+           -1.5017986307467535,
+           -1.583923414814642,
+           -1.6624429502590161,
+           -1.7352710015317103,
+           -1.8004770686805165,
+           -1.8563279168743896,
+           -1.901323843084283,
+           -1.9342288597682933,
+           -1.954094129777405,
+           -1.9602741566687676,
+           -1.9524354159397732,
+           -1.9305573008601167,
+           -1.8949254469030181,
+           -1.8461176865406583,
+           -1.7849830667268023,
+           -1.7126145302849034,
+           -1.6303160154963268,
+           -1.5395648616864643,
+           -1.441970519277953,
+           -1.3392306479367173,
+           -1.2330857440368235,
+           -1.12527346736373,
+           -1.017483836136462,
+           -0.9113164291702436,
+           -0.8082406751691188,
+           -0.7095602232934435,
+           -0.6163822785229086,
+           -0.5295926527807725,
+           -0.44983713169350487,
+           -0.37750959108457866,
+           -0.3127471210567257,
+           -0.2554322332753898,
+           -0.20520204344309292,
+           -0.16146414059516978,
+           -0.1234186823087993,
+           -0.0900860945557176,
+           -0.06033961078971068,
+           -0.032941760576841804,
+           -0.006583816780878787,
+           0.0200728654406756,
+           0.04835473288687367,
+           0.07953427652001971,
+           0.11478975684083488,
+           0.15516749923759224,
+           0.2015477797705843,
+           0.2546152292469411,
+           0.3148345669097035,
+           0.3824323375506611,
+           0.45738517083040464,
+           0.5394149129662515,
+           0.6279908029900343,
+           0.7223386829824179,
+           0.82145704868419,
+           0.9241395683043047,
+           1.0290035277196263,
+           1.1345235039036579,
+           1.2390694293153024,
+           1.3409480916799654,
+           1.4384470191441758,
+           1.5298796326271675,
+           1.6136305071199197,
+           1.6881995727835926,
+           1.7522441053363136,
+           1.804617403012155,
+           1.8444031232201934,
+           1.8709443541126192,
+           1.8838666221172171,
+           1.8830941830301022,
+           1.8688591079053616,
+           1.841702851690574,
+           1.8024701779773369,
+           1.7522955027736227,
+           1.69258190915661,
+           1.6249732683309532,
+           1.551320076419011,
+           1.473639775902057,
+           1.3940724720125741,
+           1.3148330739878562,
+           1.2381609859065619,
+           1.1662685394207637,
+           1.1012893993143662,
+           1.045228181423282,
+           0.9999125007424896,
+           0.9669486159660428,
+           0.9476817564420484,
+           0.9431621104686054,
+           0.9541173225648276,
+           0.9809321949808277,
+           1.023636118942719,
+           1.0818985780778492,
+           1.1550328745784189,
+           1.2420080326082963,
+           1.3414686380162626,
+           1.4517621833579633,
+           1.5709733071896912,
+           1.6969641509808426,
+           1.8274199098483423,
+           1.9598985282465429,
+           2.091883391812736
+          ],
+          [
+           2.1829894085530297,
+           2.3094685569379836,
+           2.428829939403708,
+           2.538742241419929,
+           2.6370461969756547,
+           2.721801043522426,
+           2.7913259774585035,
+           2.844235656054852,
+           2.879468934248715,
+           2.8963101866331558,
+           2.894402742298232,
+           2.8737541486032225,
+           2.834733174882783,
+           2.77805866376104,
+           2.704780531376074,
+           2.6162534036922818,
+           2.5141035496845547,
+           2.400189929307395,
+           2.276560311015218,
+           2.1454035268815415,
+           2.0089990203625434,
+           1.8696649004027999,
+           1.7297057445260262,
+           1.5913613921625183,
+           1.4567579378563213,
+           1.3278620730311892,
+           1.2064398362587938,
+           1.0940207177302674,
+           0.9918679267723209,
+           0.9009554752131078,
+           0.8219525580982149,
+           0.7552155309596845,
+           0.7007875940894032,
+           0.6584061037503197,
+           0.6275172426959509,
+           0.6072976023973184,
+           0.5966820614349793,
+           0.5943971927312728,
+           0.5989993003926866,
+           0.6089160781199926,
+           0.6224907980583378,
+           0.6380278835881509,
+           0.6538386931928818,
+           0.6682863457474187,
+           0.6798284501784133,
+           0.6870566635477483,
+           0.6887320895856365,
+           0.6838156422639579,
+           0.671492633255929,
+           0.6511909946393347,
+           0.62259271508014,
+           0.5856382447399439,
+           0.5405238067955586,
+           0.4876917371178798,
+           0.42781415368673154,
+           0.36177042917200497,
+           0.2906190994531743,
+           0.21556498366231455,
+           0.13792241402250993,
+           0.059075573225947434,
+           -0.019562989147715384,
+           -0.09659454348462022,
+           -0.1706759351124881,
+           -0.2405597839486633,
+           -0.30513204592780224,
+           -0.3634459217044302,
+           -0.41475119261385907,
+           -0.4585181820755601,
+           -0.49445567954971936,
+           -0.5225223203003114,
+           -0.5429310836307727,
+           -0.5561467506582961,
+           -0.5628763455670633,
+           -0.5640527669995951,
+           -0.5608119941780267,
+           -0.5544644209778413,
+           -0.5464610262177475,
+           -0.5383552259294035,
+           -0.5317613698127228,
+           -0.5283109364734655,
+           -0.5296075479853862,
+           -0.537181962084659,
+           -0.5524482088584856,
+           -0.5766620178318785,
+           -0.6108826313244948,
+           -0.6559390220096871,
+           -0.7124014286279744,
+           -0.7805589963091454,
+           -0.8604041600566134,
+           -0.9516242452759796,
+           -1.053600581845209,
+           -1.1654152425106175,
+           -1.2858653269527132,
+           -1.4134845244038454,
+           -1.5465715049072388,
+           -1.6832245167454407,
+           -1.8213814095535736,
+           -1.9588641631352728,
+           -2.093426884533214,
+           -2.222806143450172,
+           -2.3447724510357224,
+           -2.45718165104181,
+           -2.558024986385399,
+           -2.6454766284761893,
+           -2.7179375107629595,
+           -2.774074390577994,
+           -2.8128531725650086,
+           -2.8335656601525474,
+           -2.8358490554779285,
+           -2.819697699156186,
+           -2.7854667251782947,
+           -2.7338674985445492,
+           -2.665954899309792,
+           -2.583106711756814,
+           -2.4869955666616175,
+           -2.379554063445153,
+           -2.2629338630472775,
+           -2.13945968759543,
+           -2.011579285815753,
+           -1.8818105206369133,
+           -1.7526868051747038,
+           -1.6267021535462982,
+           -1.5062571227548192,
+           -1.393606900962124,
+           -1.2908127463365513,
+           -1.1996979005677773,
+           -1.121808994037991,
+           -1.0583838281415754,
+           -1.0103262675658762,
+           -0.9781888052116776,
+           -0.9621631789969062,
+           -0.9620792275274342,
+           -0.9774119752232351,
+           -1.0072967417426861,
+           -1.0505518802176632,
+           -1.1057085685244135,
+           -1.1710469119454991,
+           -1.2446374681422903,
+           -1.3243871799139029,
+           -1.408088600779961,
+           -1.493471225385283,
+           -1.5782536928019295,
+           -1.6601956169957468,
+           -1.7371478152869253,
+           -1.8070997520747962,
+           -1.8682230901892278,
+           -1.9189103440445812,
+           -1.957807754721301,
+           -1.9838416540106059,
+           -1.9962377486425904,
+           -1.9945329332734698,
+           -1.978579426912216,
+           -1.9485412176930432,
+           -1.9048829905289129,
+           -1.8483518965188237,
+           -1.7799526974766566,
+           -1.700916979304661,
+           -1.6126672702145666,
+           -1.5167770205258477,
+           -1.4149274970102697,
+           -1.308862714186609,
+           -1.2003435659548072,
+           -1.0911023325624138,
+           -0.9827987199211321,
+           -0.8769785412796217,
+           -0.7750360764762715,
+           -0.678181043400779,
+           -0.5874109924864116,
+           -0.5034897912118406,
+           -0.42693270538606537,
+           -0.35799841149892564,
+           -0.296688094021943,
+           -0.24275159781077066,
+           -0.19570042333939783,
+           -0.15482717599723836,
+           -0.11923091455811669,
+           -0.08784769237483862,
+           -0.05948545168347185,
+           -0.032862319970965,
+           -0.006647270472054828,
+           0.020497951299412273,
+           0.04987676500377052,
+           0.08271668982181998,
+           0.1201303823907042,
+           0.16307983038008178,
+           0.21234467206267044,
+           0.2684955055514235,
+           0.3318729224040923,
+           0.40257285229324985,
+           0.4804386421456262,
+           0.5650601186959985,
+           0.6557797021899248,
+           0.7517054555917129,
+           0.8517307727540591,
+           0.9545602351716648,
+           1.0587410045880712,
+           1.162698971985586,
+           1.2647787561088055,
+           1.3632865399176661,
+           1.456534653938841,
+           1.542886763455366,
+           1.6208024932314187,
+           1.6888803296800317,
+           1.7458976759776408,
+           1.790846999806345,
+           1.8229671046406726,
+           1.841768671589063,
+           1.8470533569238434,
+           1.8389258872029461,
+           1.8177987654453964,
+           1.784389383936371,
+           1.7397095273992635,
+           1.6850474398139712,
+           1.621942814369544,
+           1.5521552442745188,
+           1.4776268379561324,
+           1.400439851405387,
+           1.3227703193151579,
+           1.2468387719556968,
+           1.1748592037561367,
+           1.1089875102752245,
+           1.0512706313103235,
+           1.0035976286999644,
+           0.967653888058279,
+           0.9448795651190741,
+           0.9364333011658393,
+           0.9431621104686051,
+           0.9655781986547369,
+           1.0038433079814901,
+           1.0577610074984842,
+           1.1267771574087866,
+           1.2099885821478111,
+           1.3061597905457445,
+           1.4137473887072767,
+           1.5309316466393121,
+           1.6556545076953069,
+           1.7856631747916096,
+           1.9185582728835868,
+           2.0518454766619594,
+           2.1829894085530284
+          ],
+          [
+           2.272547252093312,
+           2.395475228637213,
+           2.5097484846564537,
+           2.613136850148115,
+           2.7036115195592982,
+           2.779388615764862,
+           2.838967164604605,
+           2.8811606077319922,
+           2.905121135987933,
+           2.9103562970815986,
+           2.896737515849748,
+           2.8645003582765565,
+           2.8142365670847402,
+           2.746878092266002,
+           2.6636735296453704,
+           2.5661575598587927,
+           2.456114144616453,
+           2.335534382844167,
+           2.2065700527260295,
+           2.0714839638497002,
+           1.932598314242087,
+           1.7922422884202986,
+           1.6527001437345248,
+           1.5161610130539875,
+           1.3846716028000066,
+           1.2600928877501059,
+           1.1440617999131628,
+           1.0379587807468165,
+           0.9428819172781738,
+           0.8596282170239027,
+           0.7886823981236395,
+           0.730213384246224,
+           0.684078503243902,
+           0.649835198939191,
+           0.6267598815213422,
+           0.6138733683412121,
+           0.6099722076980576,
+           0.6136650374128337,
+           0.6234130110175856,
+           0.6375732301464483,
+           0.6544440544558867,
+           0.6723111217184403,
+           0.689492901498106,
+           0.7043846261630713,
+           0.7154994923206189,
+           0.7215061027449428,
+           0.7212612214979381,
+           0.7138370405649155,
+           0.6985423017202573,
+           0.6749367787914514,
+           0.6428387988967282,
+           0.6023256621915927,
+           0.553727003589968,
+           0.49761132217552156,
+           0.4347660799854183,
+           0.3661719370932371,
+           0.29297184027547574,
+           0.21643581423103922,
+           0.13792241402250996,
+           0.05883788236497389,
+           -0.01940588652948835,
+           -0.09543344509005072,
+           -0.1679468203620889,
+           -0.23576436806484827,
+           -0.29785640572144384,
+           -0.3533766615063617,
+           -0.4016886839054525,
+           -0.44238648778430645,
+           -0.4753088617132238,
+           -0.500546925626953,
+           -0.5184447029516129,
+           -0.5295926527807719,
+           -0.5348142909338,
+           -0.5351462091388869,
+           -0.5318119745736964,
+           -0.5261905531730526,
+           -0.5197800453713085,
+           -0.5141576485779327,
+           -0.510936863466734,
+           -0.511723038439619,
+           -0.5180683963881052,
+           -0.5314277087905385,
+           -0.5531157736415983,
+           -0.5842678158420489,
+           -0.6258038623445265,
+           -0.6783980511334811,
+           -0.7424537152682716,
+           -0.8180849436123362,
+           -0.9051051619328666,
+           -1.003023105674078,
+           -1.1110463731417166,
+           -1.2280925596091357,
+           -1.3528077836396069,
+           -1.4835922314244223,
+           -1.6186321677890647,
+           -1.7559376981503274,
+           -1.893385418239226,
+           -2.0287649615506247,
+           -2.159828351451066,
+           -2.2843409882986463,
+           -2.400133053780376,
+           -2.505150096232634,
+           -2.597501572525641,
+           -2.6755061639640956,
+           -2.7377327546416232,
+           -2.7830360591240675,
+           -2.8105860098843487,
+           -2.819890160604493,
+           -2.8108085257829933,
+           -2.783560456058362,
+           -2.738723337935936,
+           -2.677223101578724,
+           -2.600316716241639,
+           -2.509567045009775,
+           -2.4068106140519805,
+           -2.2941190221311487,
+           -2.1737548694478646,
+           -2.048123217277387,
+           -1.9197196980450977,
+           -1.7910764768169762,
+           -1.6647073176600016,
+           -1.5430530306591737,
+           -1.4284285670071482,
+           -1.3229729907050733,
+           -1.2286034869718656,
+           -1.1469744711195502,
+           -1.0794427397640904,
+           -1.0270394617774137,
+           -0.9904496428727886,
+           -0.9699995191422555,
+           -0.9656521455878322,
+           -0.9770112503234488,
+           -1.0033332284328342,
+           -1.0435469562392217,
+           -1.0962809216753113,
+           -1.1598969940306996,
+           -1.23253000077763,
+           -1.3121321441945437,
+           -1.3965211793703465,
+           -1.4834311905399176,
+           -1.570564746577542,
+           -1.655645190160678,
+           -1.7364678191768514,
+           -1.8109487531994768,
+           -1.877170341378631,
+           -1.9334220592361473,
+           -1.9782359582998112,
+           -2.0104158713178464,
+           -2.0290597334772293,
+           -2.0335745526623934,
+           -2.023683745030586,
+           -1.9994267414882763,
+           -1.961150961332185,
+           -1.9094964366475267,
+           -1.8453735504078292,
+           -1.7699345181764892,
+           -1.6845393937688193,
+           -1.5907175095130888,
+           -1.4901253686775806,
+           -1.3845020886242398,
+           -1.2756235463750492,
+           -1.1652564023009913,
+           -1.0551131720588778,
+           -0.9468094819423772,
+           -0.8418245794469894,
+           -0.7414660807485353,
+           -0.6468398223007028,
+           -0.5588255478149473,
+           -0.47805900797205364,
+           -0.40492088225078654,
+           -0.33953275451185116,
+           -0.28176019095053595,
+           -0.2312227853605332,
+           -0.18731085697556063,
+           -0.1492083150098872,
+           -0.11592104571863401,
+           -0.08631003633184367,
+           -0.05912832914314143,
+           -0.03306080139872141,
+           -0.006765694887628913,
+           0.021083224921286194,
+           0.05175501561625411,
+           0.086421531974924,
+           0.12612010630998943,
+           0.1717199434230302,
+           0.2238931422035835,
+           0.28309113605574215,
+           0.3495272040138354,
+           0.42316554716995763,
+           0.5037172548552601,
+           0.5906433061985055,
+           0.6831645697552597,
+           0.7802785814920987,
+           0.8807827041470035,
+           0.9833031033702487,
+           1.0863288223423666,
+           1.1882501006861794,
+           1.2873999689150883,
+           1.3820980593356542,
+           1.4706955105914312,
+           1.5516198075750296,
+           1.6234183922191003,
+           1.6847999039446249,
+           1.7346719607989902,
+           1.7721744723324122,
+           1.7967075811171533,
+           1.8079534589375748,
+           1.8058913329112012,
+           1.7908052824730591,
+           1.76328452618087,
+           1.7242161032731298,
+           1.674770044223307,
+           1.6163773124756327,
+           1.550700981438585,
+           1.4796012821082765,
+           1.4050953131053054,
+           1.3293123425052082,
+           1.2544457461515057,
+           1.1827027172337097,
+           1.1162529444811402,
+           1.0571774897326933,
+           1.007419098977778,
+           0.9687351540493762,
+           0.9426544155592067,
+           0.9304386227029291,
+           0.9330499042383571,
+           0.9511248199133447,
+           0.9849556961424637,
+           1.0344797475620395,
+           1.0992762914073757,
+           1.178572168944247,
+           1.2712552921428029,
+           1.3758960391879835,
+           1.490776034028802,
+           1.613923667585484,
+           1.7431555558033864,
+           1.8761229864447255,
+           2.0103622858551344,
+           2.1433479418922845,
+           2.2725472520933105
+          ],
+          [
+           2.3597992225518465,
+           2.4781301539554037,
+           2.5863309431372823,
+           2.682291444989025,
+           2.7641304992190805,
+           2.830236234780097,
+           2.879300242157822,
+           2.9103448305045294,
+           2.9227427516910347,
+           2.9162289531341665,
+           2.8909041113473775,
+           2.847229893927362,
+           2.786016094360144,
+           2.708399976818907,
+           2.6158183523453395,
+           2.50997307898397,
+           2.3927908324270595,
+           2.266378126805352,
+           2.1329726742242108,
+           1.9948922538890148,
+           1.8544823152414904,
+           1.714063563200774,
+           1.5758807668672508,
+           1.442053996149978,
+           1.3145334247078873,
+           1.1950587440551341,
+           1.0851241150495652,
+           0.9859494422513438,
+           0.898458597336374,
+           0.8232650438569397,
+           0.7606651314925121,
+           0.7106391381031758,
+           0.672859947093388,
+           0.6467090605347959,
+           0.6312994698002663,
+           0.62550473952582,
+           0.6279935116149408,
+           0.6372685073755978,
+           0.6517090008620842,
+           0.6696156576152085,
+           0.689256582133122,
+           0.7089133957369257,
+           0.7269261744659349,
+           0.7417361139526547,
+           0.7519248538610134,
+           0.7562494866918889,
+           0.7536723921750873,
+           0.7433851760837439,
+           0.7248261476077067,
+           0.697690938452165,
+           0.6619360452947056,
+           0.6177752606164428,
+           0.5656691405827825,
+           0.5063078379482703,
+           0.44058779837507034,
+           0.3695829757919084,
+           0.2945113625218362,
+           0.21669774934997169,
+           0.13753372648628756,
+           0.05843600610130626,
+           -0.019195810970473848,
+           -0.09402088869684994,
+           -0.16479710991924795,
+           -0.23041825630952067,
+           -0.289947411942087,
+           -0.3426456864267993,
+           -0.38799547504176396,
+           -0.42571761500244015,
+           -0.45578195531861637,
+           -0.4784110286187119,
+           -0.4940766925355581,
+           -0.50348979121184,
+           -0.5075830695609833,
+           -0.5074877494926232,
+           -0.5045043438967347,
+           -0.5000684365390099,
+           -0.49571229026647595,
+           -0.4930232586211977,
+           -0.49360006421208524,
+           -0.49900806871095765,
+           -0.5107346924971131,
+           -0.5301461458616972,
+           -0.5584466081185209,
+           -0.5966409365090232,
+           -0.6455019047180588,
+           -0.7055428631102285,
+           -0.7769965820752393,
+           -0.8598008893377637,
+           -0.9535915454471077,
+           -1.0577026230293955,
+           -1.1711744691832457,
+           -1.292769141250966,
+           -1.4209930188069884,
+           -1.5541261137464966,
+           -1.6902574303537843,
+           -1.827325572443257,
+           -1.9631636589902222,
+           -2.0955474965315113,
+           -2.222245868894784,
+           -2.3410717447638856,
+           -2.4499331727790556,
+           -2.5468826331589915,
+           -2.630163644327469,
+           -2.6982534820956348,
+           -2.7499009562259698,
+           -2.7841583026199377,
+           -2.800406386215544,
+           -2.79837256665754,
+           -2.7781407521148576,
+           -2.74015335206162,
+           -2.685205032899347,
+           -2.614428376274251,
+           -2.52927173405222,
+           -2.4314697614120715,
+           -2.3230072858184894,
+           -2.2060773304227497,
+           -2.0830342517713545,
+           -1.9563430701126086,
+           -1.828526163170924,
+           -1.7021085587309501,
+           -1.5795630961483749,
+           -1.4632567311182267,
+           -1.355399231569055,
+           -1.2579954560482818,
+           -1.172802320791511,
+           -1.1012914498990338,
+           -1.0446183674005323,
+           -1.0035989337808309,
+           -0.9786935565754018,
+           -0.9699995191422552,
+           -0.977251578199313,
+           -0.9998307838993826,
+           -1.0367812808910952,
+           -1.0868346597357414,
+           -1.1484412498109775,
+           -1.2198075817562606,
+           -1.2989391035481128,
+           -1.383687112908365,
+           -1.4717987728592852,
+           -1.560969009129239,
+           -1.64889304937896,
+           -1.7333183557352918,
+           -1.8120947240139385,
+           -1.8832213746666242,
+           -1.9448899405504005,
+           -1.9955223630402679,
+           -2.0338028380983335,
+           -2.058703104402068,
+           -2.0695005327544607,
+           -2.065788655579711,
+           -2.047479962881758,
+           -2.014800981953123,
+           -1.968279847640381,
+           -1.9087267534170878,
+           -1.8372078463634915,
+           -1.7550132871564572,
+           -1.6636203354619536,
+           -1.5646524382998077,
+           -1.4598353911763098,
+           -1.3509517068424644,
+           -1.2397943629026187,
+           -1.1281211063570091,
+           -1.0176104704362627,
+           -0.9098206074388134,
+           -0.8061519620967998,
+           -0.7078147053403633,
+           -0.6158017209057859,
+           -0.5308677903054976,
+           -0.4535154589951811,
+           -0.38398789227185653,
+           -0.32226884793727106,
+           -0.26808970865744164,
+           -0.22094333489485332,
+           -0.18010432387934147,
+           -0.14465509573963287,
+           -0.1135170787784661,
+           -0.08548613569265383,
+           -0.05927126458701042,
+           -0.03353552561741835,
+           -0.006938088103457627,
+           0.02182373462661697,
+           0.05397359387422474,
+           0.09061745833825625,
+           0.13270825282395243,
+           0.18101473910039848,
+           0.23609548491018906,
+           0.29827863512123237,
+           0.367648048527861,
+           0.44403619866382665,
+           0.5270240613620905,
+           0.615948030130977,
+           0.7099137173146427,
+           0.8078163191089712,
+           0.9083670503772899,
+           1.0101249952288003,
+           1.111533575560681,
+           1.2109607158946143,
+           1.3067416820375939,
+           1.3972234959673442,
+           1.4808097818468042,
+           1.5560048794811583,
+           1.62145607239382,
+           1.6759928178255068,
+           1.7186619344304679,
+           1.7487577986222003,
+           1.7658467201012138,
+           1.7697848081587442,
+           1.760728799428466,
+           1.7391394909312778,
+           1.7057776052439344,
+           1.6616921028839813,
+           1.6082011458625873,
+           1.5468661011094762,
+           1.4794591485076263,
+           1.4079252211831947,
+           1.3343391513876575,
+           1.2608590201123808,
+           1.1896768093278043,
+           1.122967529866739,
+           1.0628380435546738,
+           1.0112768140112618,
+           0.9701058061233075,
+           0.9409357097825108,
+           0.9251255900950053,
+           0.9237479656250493,
+           0.9375601907286132,
+           0.9669828706777547,
+           1.012085872630844,
+           1.0725823155804766,
+           1.1478307325816446,
+           1.2368454034491303,
+           1.338314660473335,
+           1.4506267783154885,
+           1.5719028767855594,
+           1.700036096144956,
+           1.8327361530522597,
+           1.9675782550000736,
+           2.102055245271456,
+           2.233631771676332,
+           2.359799222551845
+          ],
+          [
+           2.444007128776587,
+           2.556734034822584,
+           2.6579293925934877,
+           2.7456209467774944,
+           2.8180911180019272,
+           2.873913706702452,
+           2.9119839740311284,
+           2.9315414126417965,
+           2.9321846945152994,
+           2.913878469463248,
+           2.8769518820328566,
+           2.822088871499008,
+           2.750310514678155,
+           2.6629498596879833,
+           2.561619875930654,
+           2.448175307199781,
+           2.3246693569916226,
+           2.193306254410603,
+           2.0563908426350803,
+           1.916276397523896,
+           1.775311920060191,
+           1.635790152135859,
+           1.4998975406136668,
+           1.3696673203473053,
+           1.2469368043045117,
+           1.1333098602302203,
+           1.0301254211515538,
+           0.9384327247820163,
+           0.8589738083354108,
+           0.7921736046117341,
+           0.7381377969584899,
+           0.6966583995103579,
+           0.6672268396993492,
+           0.6490541370826299,
+           0.6410976005616964,
+           0.642093309287665,
+           0.650593504799759,
+           0.6650079065829881,
+           0.6836478730480163,
+           0.7047722670905237,
+           0.7266338513530456,
+           0.7475250338426926,
+           0.7658218096683111,
+           0.7800247986277283,
+           0.7887963597583008,
+           0.790992870638835,
+           0.7856913884469334,
+           0.7722100582232699,
+           0.7501217976884933,
+           0.7192609631343712,
+           0.6797228829279425,
+           0.6318563294207975,
+           0.5762491818911644,
+           0.5137077079774701,
+           0.4452300544837539,
+           0.3719746863371155,
+           0.2952246411374097,
+           0.21634857292947876,
+           0.13675963988628237,
+           0.05787334448998626,
+           -0.018934539804961417,
+           -0.09236882517129338,
+           -0.16125345175957181,
+           -0.2245666792072737,
+           -0.28147197825596565,
+           -0.33134378537073783,
+           -0.373787416766028,
+           -0.4086525899364469,
+           -0.4360401668300213,
+           -0.45630190898088524,
+           -0.47003321677737847,
+           -0.47805900797205314,
+           -0.4814130699036955,
+           -0.4813113911450073,
+           -0.4791201370595123,
+           -0.47631907600283,
+           -0.47446138500222007,
+           -0.47513086256165316,
+           -0.47989764921546224,
+           -0.4902736016849757,
+           -0.5076684827658666,
+           -0.5333481159004273,
+           -0.5683956110173489,
+           -0.6136766976330579,
+           -0.6698101040931461,
+           -0.7371438005474388,
+           -0.8157377807648647,
+           -0.9053538977079099,
+           -1.0054530938544672,
+           -1.1152001838823422,
+           -1.233476159069011,
+           -1.358897794288932,
+           -1.4898441545111702,
+           -1.6244894228086777,
+           -1.7608413104692993,
+           -1.8967841659043307,
+           -2.0301257763147946,
+           -2.158646757612553,
+           -2.2801513564225466,
+           -2.392518444975234,
+           -2.4937514764902216,
+           -2.5820261856742976,
+           -2.655734865883684,
+           -2.7135261302661364,
+           -2.7543391670244204,
+           -2.7774316263778087,
+           -2.782400425781164,
+           -2.7691949268933036,
+           -2.7381221186210905,
+           -2.6898436309077107,
+           -2.6253645991464487,
+           -2.5460145944221444,
+           -2.4534210254390785,
+           -2.3494755993223637,
+           -2.236294596039437,
+           -2.116173860871128,
+           -1.9915395474948394,
+           -1.8648957476770982,
+           -1.7387702197638129,
+           -1.615659475224285,
+           -1.4979744992820119,
+           -1.3879883677258114,
+           -1.2877869776644966,
+           -1.199224036337615,
+           -1.1238813509116896,
+           -1.0630353359375562,
+           -1.0176305068957208,
+           -0.9882605616256377,
+           -0.9751574704834813,
+           -0.9781888052116768,
+           -0.9968633403826525,
+           -1.0303447646752262,
+           -1.0774731469388041,
+           -1.1367936186727554,
+           -1.2065915646458163,
+           -1.2849334610190892,
+           -1.3697123691970474,
+           -1.4586969868694417,
+           -1.5495830778763036,
+           -1.6400460515163962,
+           -1.7277934409038755,
+           -1.810616039397502,
+           -1.8864364936705222,
+           -1.9533542206070214,
+           -2.009685611137644,
+           -2.0539986049306984,
+           -2.0851408624927523,
+           -2.1022609221318502,
+           -2.104821904380744,
+           -2.0926075115068143,
+           -2.065720260056054,
+           -2.0245720752755005,
+           -1.9698675630136064,
+           -1.9025804527060108,
+           -1.8239238699370484,
+           -1.735315244782925,
+           -1.6383367890833218,
+           -1.534692578871767,
+           -1.4261633549380668,
+           -1.314560203076537,
+           -1.2016782948743847,
+           -1.0892518595304603,
+           -0.978911517520462,
+           -0.8721450390263977,
+           -0.770262495713879,
+           -0.6743666561151298,
+           -0.5853293355987301,
+           -0.503774255237622,
+           -0.43006679381164975,
+           -0.36431083801678293,
+           -0.30635275223681313,
+           -0.2557923056088235,
+           -0.21200021521617518,
+           -0.17414179458172788,
+           -0.14120604048185695,
+           -0.11203935238573415,
+           -0.0853829610294959,
+           -0.05991304871654462,
+           -0.03428247624535049,
+           -0.0071629915949262424,
+           0.022713215368213045,
+           0.05651372960170185,
+           0.09526896947610465,
+           0.13983908323191474,
+           0.190885579234813,
+           0.24884846284156614,
+           0.3139295096333784,
+           0.3860821454018047,
+           0.46500823161914123,
+           0.5501618755366195,
+           0.6407602010784264,
+           0.7358008349755939,
+           0.8340856867211235,
+           0.9342504353937515,
+           1.0347989854051518,
+           1.1341420206255066,
+           1.230638675529556,
+           1.3226402558310812,
+           1.4085348817744934,
+           1.48679189639338,
+           1.556004879481158,
+           1.6149321358692603,
+           1.6625335832564974,
+           1.698003048939771,
+           1.7207950943314634,
+           1.7306456184417482,
+           1.7275856433096721,
+           1.7119478519451805,
+           1.6843656285530837,
+           1.6457645372078948,
+           1.5973463641046506,
+           1.5405660353200064,
+           1.4771019020178413,
+           1.4088200537205606,
+           1.3377334734084876,
+           1.2659569819488483,
+           1.1956590303098298,
+           1.1290114833578597,
+           1.06813859657039,
+           1.0150664152090938,
+           0.9716738235978255,
+           0.9396464400889186,
+           0.9204344917772584,
+           0.9152157134609858,
+           0.9248641998718707,
+           0.949926001571972,
+           0.9906020964765182,
+           1.0467391945502418,
+           1.117828647069757,
+           1.2030135384778204,
+           1.3011038429905861,
+           1.41059933453862,
+           1.5297197520591945,
+           1.656441547177511,
+           1.7885403822057973,
+           1.9236384070535184,
+           2.059255227501694,
+           2.1928613872043523,
+           2.32193312396023,
+           2.444007128776586
+          ],
+          [
+           2.524458533776361,
+           2.630621846837956,
+           2.7239380777440023,
+           2.8025895592714662,
+           2.8650368446554793,
+           2.910051500355182,
+           2.9367418410633195,
+           2.9445710214673495,
+           2.9333670813519057,
+           2.9033247322243043,
+           2.8549988700796414,
+           2.7892899954176813,
+           2.7074219133998416,
+           2.610912269430571,
+           2.5015366440368725,
+           2.3812870816193317,
+           2.252326056817644,
+           2.116936986765778,
+           1.9774724749075572,
+           1.8363015204732738,
+           1.6957569460664352,
+           1.558084283702286,
+           1.4253933174506794,
+           1.299613409678604,
+           1.182453639586311,
+           1.075368659774211,
+           0.9795310320566982,
+           0.8958106412701834,
+           0.8247616094573028,
+           0.7666169469333376,
+           0.7212909859654656,
+           0.6883894518426217,
+           0.667226839699349,
+           0.6568505881739387,
+           0.6560713771856861,
+           0.6634987308201482,
+           0.677580981083555,
+           0.6966485471654891,
+           0.7189594102641848,
+           0.7427456177476853,
+           0.7662596335046504,
+           0.7878193641054009,
+           0.8058507324309474,
+           0.8189267405901136,
+           0.8258020603880434,
+           0.8254423098360295,
+           0.8170473151162555,
+           0.8000678154371856,
+           0.7742152393165216,
+           0.7394643606687112,
+           0.6960488271014259,
+           0.6444497363908154,
+           0.5853776155781214,
+           0.5197483260141949,
+           0.4486535727241446,
+           0.3733268337753846,
+           0.2951056414623462,
+           0.21539123916008207,
+           0.13560670334540853,
+           0.05715465790285293,
+           -0.018624283505237843,
+           -0.09049123171837455,
+           -0.15734582683461504,
+           -0.21825914374826116,
+           -0.2725018106672418,
+           -0.31956657753528,
+           -0.35918471568047705,
+           -0.3913357904203966,
+           -0.4162505207113131,
+           -0.4344066198700999,
+           -0.44651769436178523,
+           -0.4535154589951806,
+           -0.4565257020010972,
+           -0.45683859793259707,
+           -0.45587411593835675,
+           -0.4551434019013571,
+           -0.45620712185322077,
+           -0.46063183816636455,
+           -0.46994554710814995,
+           -0.4855935349051042,
+           -0.508895708716168,
+           -0.541006528791293,
+           -0.582878609271583,
+           -0.6352309689662735,
+           -0.6985228021034893,
+           -0.7729335052148056,
+           -0.8583495432656411,
+           -0.9543585696589919,
+           -1.0602510349878007,
+           -1.1750293328501593,
+           -1.2974243423107434,
+           -1.4259190403947755,
+           -1.5587786789886011,
+           -1.6940868531765385,
+           -1.8297866365702624,
+           -1.9637258274024951,
+           -2.093705240399673,
+           -2.2175288964922633,
+           -2.333054907407335,
+           -2.4382458265690055,
+           -2.531217242236469,
+           -2.610283423421635,
+           -2.6739988930888106,
+           -2.7211948949611244,
+           -2.751009837765307,
+           -2.762912941122544,
+           -2.7567204671542744,
+           -2.7326040973472203,
+           -2.6910912010496877,
+           -2.6330569356030042,
+           -2.559708313824894,
+           -2.472560567574462,
+           -2.373406321719919,
+           -2.2642782664547116,
+           -2.147406173308294,
+           -2.0251692375104757,
+           -1.9000448432183248,
+           -1.7745549356990455,
+           -1.6512112437200144,
+           -1.5324606246621033,
+           -1.4206318035096634,
+           -1.3178847448955502,
+           -1.2261638355564002,
+           -1.1471559643781966,
+           -1.0822544708745754,
+           -1.0325297932703204,
+           -0.9987074877616725,
+           -0.9811541148809596,
+           -0.9798713014854621,
+           -0.9944980922846791,
+           -1.0243215077553565,
+           -1.0682950305658825,
+           -1.1250645549759186,
+           -1.1930011576509698,
+           -1.2702398882030075,
+           -1.3547236374108242,
+           -1.444251023871776,
+           -1.5365271486017091,
+           -1.6292160040031578,
+           -1.7199932901400241,
+           -1.8065983881371535,
+           -1.8868842677659248,
+           -1.958864163135273,
+           -2.0207539354085386,
+           -2.071009152446818,
+           -2.108356049440245,
+           -2.1318156885659705,
+           -2.140720805659063,
+           -2.1347250135690192,
+           -2.1138042207868897,
+           -2.0782503153855507,
+           -2.028657353584431,
+           -1.9659006746613539,
+           -1.8911095349995448,
+           -1.8056340095801355,
+           -1.7110070454078379,
+           -1.6089026648762221,
+           -1.5010914051967186,
+           -1.3893941406261976,
+           -1.2756354659156617,
+           -1.1615978214735836,
+           -1.0489775132380326,
+           -0.9393437239646192,
+           -0.8341015290622882,
+           -0.7344598214239952,
+           -0.6414049187046951,
+           -0.5556804765481449,
+           -0.477774166177959,
+           -0.4079113987395542,
+           -0.34605619626853246,
+           -0.2919191247822187,
+           -0.24497202339911123,
+           -0.20446908916378823,
+           -0.16947371477865278,
+           -0.13889032980475552,
+           -0.11150036877439953,
+           -0.08600138524670727,
+           -0.06104825174759755,
+           -0.0352953337422065,
+           -0.007438502576726941,
+           0.023744141736505887,
+           0.05935393210100645,
+           0.10033671149941022,
+           0.14745226748188747,
+           0.20124895205213053,
+           0.262044180033627,
+           0.329911346111706,
+           0.404673533834589,
+           0.48590421314714644,
+           0.5729349410009501,
+           0.6648698968470026,
+           0.7606069060086474,
+           0.8588644335915319,
+           0.9582138740467834,
+           1.0571163207773033,
+           1.1539628798611568,
+           1.2471174951481148,
+           1.3349611811670705,
+           1.4159365173147132,
+           1.4885912428351566,
+           1.5516198075750296,
+           1.6039017781005338,
+           1.6445360714524233,
+           1.6728700878464033,
+           1.6885229365917696,
+           1.6914020933874754,
+           1.6817129884203206,
+           1.6599611993506846,
+           1.6269471069996508,
+           1.5837530597845593,
+           1.5317232810019896,
+           1.4724369362359908,
+           1.4076749518937035,
+           1.3393813357838413,
+           1.269619892732457,
+           1.2005273488856145,
+           1.1342639945146167,
+           1.0729630243507513,
+           1.0186797949307245,
+           0.973342229037112,
+           0.9387035777118399,
+           0.9162987008942826,
+           0.9074049496148501,
+           0.9130086276977426,
+           0.9337778815965637,
+           0.9700427164131055,
+           1.0217826679715558,
+           1.088622479116411,
+           1.169835937591283,
+           1.264357837587518,
+           1.3708038320928175,
+           1.4874977532868785,
+           1.6125057980712516,
+           1.7436768097989566,
+           1.8786877394592865,
+           2.015093243604573,
+           2.150378275277921,
+           2.282012450602823,
+           2.4075049293468385,
+           2.524458533776359
+          ],
+          [
+           2.600472782260193,
+           2.6991684656772525,
+           2.783798535243183,
+           2.8527153022306497,
+           2.904570497089063,
+           2.938343873651447,
+           2.9533643804962404,
+           2.9493234205945593,
+           2.9262799086731803,
+           2.8846570308099984,
+           2.825230807902708,
+           2.7491107590166894,
+           2.657713147499331,
+           2.552727467607527,
+           2.4360769879937894,
+           2.309874306898299,
+           2.1763729889603134,
+           2.03791644243264,
+           1.8968852561435834,
+           1.7556442463860404,
+           1.6164904643392461,
+           1.4816033847093086,
+           1.3529984368197936,
+           1.2324849519278878,
+           1.1216294873057668,
+           1.0217253514616564,
+           0.9337689991909636,
+           0.858443793829068,
+           0.796111451385756,
+           0.7468112917102291,
+           0.7102672301577094,
+           0.6859022541389779,
+           0.6728599470933878,
+           0.6700324523045555,
+           0.6760941147462852,
+           0.6895399045710413,
+           0.7087276142049959,
+           0.7319227349862193,
+           0.7573448609270874,
+           0.7832144378569968,
+           0.8077986765400619,
+           0.8294554782576353,
+           0.8466742799539768,
+           0.858112811807479,
+           0.8626288707776429,
+           0.8593063464393148,
+           0.8474748868547121,
+           0.8267227584936819,
+           0.7969026310732116,
+           0.7581302011699025,
+           0.7107757529398744,
+           0.6554489356049484,
+           0.5929772109639986,
+           0.5243785856964427,
+           0.450829388582769,
+           0.3736279783275342,
+           0.2941553702877448,
+           0.21383384751866902,
+           0.13408467122851167,
+           0.05628602675364282,
+           -0.018267666979991368,
+           -0.08840399362832582,
+           -0.15310729541946316,
+           -0.21154901453665878,
+           -0.2631128008527632,
+           -0.30741370342796115,
+           -0.3443109172440924,
+           -0.3739137244141365,
+           -0.3965804463235733,
+           -0.41291040533996437,
+           -0.4237290772493095,
+           -0.4300667938116493,
+           -0.4331315242473068,
+           -0.4342764207600349,
+           -0.4349629523908976,
+           -0.43672057001959136,
+           -0.44110394014586685,
+           -0.4496488537425993,
+           -0.4638279571773535,
+           -0.48500746385405535,
+           -0.5144059874611514,
+           -0.5530565908957661,
+           -0.6017730701623608,
+           -0.6611213916197726,
+           -0.7313970763312766,
+           -0.8126091800158174,
+           -0.9044713547847697,
+           -1.006400303491437,
+           -1.117521753468769,
+           -1.2366838882595805,
+           -1.362477988341334,
+           -1.493265849498981,
+           -1.6272133749689737,
+           -1.7623295790959717,
+           -1.8965100999997435,
+           -2.027584200190028,
+           -2.153364140208665,
+           -2.2716957436312475,
+           -2.3805089338686893,
+           -2.4778670152050415,
+           -2.562013492686132,
+           -2.6314152773831134,
+           -2.6848012040081266,
+           -2.721194894961125,
+           -2.7399411360807013,
+           -2.7407250815011834,
+           -2.723583774405172,
+           -2.6889096529947905,
+           -2.637445902245035,
+           -2.570273707286052,
+           -2.4887916588183128,
+           -2.394687750036662,
+           -2.289904583495272,
+           -2.176598570797409,
+           -2.0570940539038367,
+           -1.9338334006344844,
+           -1.809324225541815,
+           -1.6860849583274673,
+           -1.566590023597751,
+           -1.4532159069680708,
+           -1.3481893630355322,
+           -1.2535389709988385,
+           -1.1710511649117894,
+           -1.102231759619874,
+           -1.0482738629216604,
+           -1.010032912592207,
+           -0.9880094073030258,
+           -0.9823397173019607,
+           -0.9927951684380348,
+           -1.0187893964125876,
+           -1.059393771796489,
+           -1.1133605051492252,
+           -1.1791528601550867,
+           -1.2549817354564274,
+           -1.3388477268640624,
+           -1.4285876544587774,
+           -1.5219244368246243,
+           -1.6165191197183615,
+           -1.7100238206505047,
+           -1.800134335184829,
+           -1.8846411655655548,
+           -1.961477777116797,
+           -2.0287649615506247,
+           -2.0848502869852354,
+           -2.128341739569228,
+           -2.158134807991333,
+           -2.1734324261688087,
+           -2.1737573669657695,
+           -2.1589568664842407,
+           -2.129199449667807,
+           -2.0849641189322456,
+           -2.0270222535768117,
+           -1.9564127442541215,
+           -1.874411049452136,
+           -1.7824930057876285,
+           -1.6822943473974947,
+           -1.57556698885054,
+           -1.4641331984086585,
+           -1.3498388324320396,
+           -1.2345068162498631,
+           -1.1198920416418072,
+           -1.0076388066737085,
+           -0.8992418512068473,
+           -0.7960119428556657,
+           -0.699046846052536,
+           -0.6092083643229078,
+           -0.52710598651786,
+           -0.453087495645128,
+           -0.38723671844663515,
+           -0.3293784095566148,
+           -0.2790900805930445,
+           -0.23572040651203247,
+           -0.19841367347196895,
+           -0.16613957853758057,
+           -0.1377275556685279,
+           -0.11190468798970701,
+           -0.0873361761955702,
+           -0.06266726934884131,
+           -0.036565528875239735,
+           -0.007762290101283549,
+           0.024907791627920235,
+           0.062470171973788166,
+           0.10577780901747633,
+           0.15548339459011068,
+           0.21201717872883688,
+           0.2755709947477966,
+           0.3460889309877451,
+           0.4232649222673732,
+           0.5065473537885756,
+           0.5951505873163245,
+           0.6880731385007418,
+           0.7841220598279885,
+           0.8819429203091621,
+           0.9800546248018012,
+           1.076888186589297,
+           1.1708284598294572,
+           1.260257756479567,
+           1.343600217441937,
+           1.419365781402055,
+           1.4861925978870232,
+           1.5428867634553658,
+           1.5884583209056575,
+           1.6221525495071145,
+           1.6434756873740086,
+           1.6522143624609145,
+           1.6484481629182526,
+           1.6325549469086678,
+           1.6052086722501555,
+           1.567369712945499,
+           1.5202678181334421,
+           1.4653780545538306,
+           1.4043902516175601,
+           1.3391726341511658,
+           1.2717304776725915,
+           1.2041607508693688,
+           1.138603816500918,
+           1.0771933425111395,
+           1.0220056276318958,
+           0.9750095687899779,
+           0.938018490534153,
+           0.9126450195527068,
+           0.9002601209779585,
+           0.9019573191179145,
+           0.9185230057495505,
+           0.9504135970182497,
+           0.9977401387415402,
+           1.0602607834186506,
+           1.1373813747895203,
+           1.2281641819336748,
+           1.3313446293816567,
+           1.4453556773084155,
+           1.5683593212985683,
+           1.6982845089412846,
+           1.8328706148537124,
+           1.9697154804709147,
+           2.1063269134044162,
+           2.2401764561109174,
+           2.3687541771292007,
+           2.4896232116409043,
+           2.6004727822601916
+          ],
+          [
+           2.671406759289071,
+           2.7617939559273954,
+           2.8370043185334204,
+           2.8955740891874533,
+           2.9363576027139078,
+           2.958551460310716,
+           2.9617109581245025,
+           2.9457584025763235,
+           2.9109831371669674,
+           2.858033302421526,
+           2.7878995467782746,
+           2.701891096817298,
+           2.6016047756296152,
+           2.488887723971196,
+           2.3657947261123606,
+           2.2345411674254723,
+           2.097452750742858,
+           1.956913170973451,
+           1.8153109906800358,
+           1.6749869722988073,
+           1.538183105182528,
+           1.4069945181704095,
+           1.2833253921702035,
+           1.1688498842237007,
+           1.0649789473144147,
+           0.9728337819547545,
+           0.8932264900599493,
+           0.8266483228967132,
+           0.7732657274223999,
+           0.7329242037477571,
+           0.7051597954976613,
+           0.6892178492174693,
+           0.6840785032439016,
+           0.6884882049390739,
+           0.700996411823339,
+           0.7199965104266466,
+           0.7437698895538618,
+           0.7705320344544629,
+           0.7984794667545018,
+           0.825836342887984,
+           0.8508995413585696,
+           0.8720811159331121,
+           0.8879470665524891,
+           0.8972514803854267,
+           0.8989652194468821,
+           0.8922984753753764,
+           0.8767166726367628,
+           0.8519493745130019,
+           0.8179920273581403,
+           0.775100563180916,
+           0.7237790639866846,
+           0.6647608688606504,
+           0.5989836720329753,
+           0.5275593129320857,
+           0.4517390936728953,
+           0.37287557217438366,
+           0.2923818673377452,
+           0.21168957424325385,
+           0.13220642061602805,
+           0.05527480005493831,
+           -0.017867707366396385,
+           -0.08612476987987508,
+           -0.14857371740784572,
+           -0.2044930623019647,
+           -0.25338438408413566,
+           -0.29498798186296754,
+           -0.3292918605221165,
+           -0.3565337904796542,
+           -0.3771963613969323,
+           -0.39199513309255174,
+           -0.4018601674526897,
+           -0.4079113987395538,
+           -0.41142846197210753,
+           -0.41381574585570213,
+           -0.4165635643231557,
+           -0.4212064458516793,
+           -0.4292796196316703,
+           -0.4422748303084392,
+           -0.4615966370021287,
+           -0.48852034695812113,
+           -0.524152699549205,
+           -0.5693963532357277,
+           -0.6249191380007052,
+           -0.691128920902356,
+           -0.7681547955407627,
+           -0.8558351507882097,
+           -0.9537130039264408,
+           -1.0610388025878692,
+           -1.1767807131037273,
+           -1.2996422246728374,
+           -1.4280867138782543,
+           -1.5603684371217483,
+           -1.694569253957241,
+           -1.828640236225512,
+           -1.9604471900644178,
+           -2.0878190135369046,
+           -2.2085977344534253,
+           -2.320689022991932,
+           -2.4221119532695545,
+           -2.5110467976986888,
+           -2.5858796776249453,
+           -2.6452429625119467,
+           -2.688050406203153,
+           -2.7135261302661364,
+           -2.721226708195499,
+           -2.711055766846245,
+           -2.683270698949039,
+           -2.6384812686071966,
+           -2.5776400857097967,
+           -2.50202512047815,
+           -2.4132146211182124,
+           -2.3130549810829653,
+           -2.2036222732554855,
+           -2.0871783222512312,
+           -1.966122319222926,
+           -1.8429390927530633,
+           -1.7201452319424015,
+           -1.6002343116040516,
+           -1.4856224932107942,
+           -1.3785957683125227,
+           -1.2812600736866075,
+           -1.1954954403996372,
+           -1.1229152438630856,
+           -1.0648315011633376,
+           -1.022227018372627,
+           -0.9957350276937071,
+           -0.9856267761213967,
+           -0.9918073381556682,
+           -1.0138197295786635,
+           -1.0508572021705398,
+           -1.1017834052818818,
+           -1.1651599141179196,
+           -1.239280450939255,
+           -1.3222109683543628,
+           -1.4118346272685072,
+           -1.5059005891548736,
+           -1.6020754558343908,
+           -1.6979961319469727,
+           -1.791322857123554,
+           -1.8797911571454948,
+           -1.9612614959772758,
+           -2.0337654726070618,
+           -2.0955474965315117,
+           -2.1451009911988432,
+           -2.181198312874526,
+           -2.202913729761474,
+           -2.209638978869358,
+           -2.2010911017941006,
+           -2.177312450685709,
+           -2.138662947546813,
+           -2.0858048688801034,
+           -2.0196806089385984,
+           -1.941484043976491,
+           -1.852626272807666,
+           -1.754696641923036,
+           -1.649420073169707,
+           -1.538611795910018,
+           -1.4241306416607928,
+           -1.3078320861618968,
+           -1.1915222210662408,
+           -1.076913805148513,
+           -0.9655854840010012,
+           -0.8589451792369818,
+           -0.7581985355415727,
+           -0.6643231793956977,
+           -0.5780493903889449,
+           -0.49984761862363564,
+           -0.4299231040426824,
+           -0.3682176700835702,
+           -0.3144185795033973,
+           -0.2679741591883398,
+           -0.22811572781285633,
+           -0.1938851996975771,
+           -0.1641675941598244,
+           -0.13772755566852782,
+           -0.11324888930813853,
+           -0.0893760409406575,
+           -0.06475640389875552,
+           -0.038082315218854884,
+           -0.008131614779622792,
+           0.026194320037817142,
+           0.0658360844206086,
+           0.11154622788317546,
+           0.1638645175871223,
+           0.22309915519456897,
+           0.2893144640106397,
+           0.36232539457300367,
+           0.44169901914131693,
+           0.5267630032324749,
+           0.6166208600622202,
+           0.7101736161156668,
+           0.8061473475915769,
+           0.9031258924332488,
+           0.9995879050243651,
+           1.093947303909492,
+           1.1845960700921139,
+           1.269948286967012,
+           1.348484274499587,
+           1.4187936609105802,
+           1.4796162551706398,
+           1.529879632627167,
+           1.5687324229207442,
+           1.595572392144887,
+           1.6100685374517019,
+           1.612176558905862,
+           1.6021472367227245,
+           1.5805274180501692,
+           1.5481535017986654,
+           1.5061374981034046,
+           1.4558459261263121,
+           1.3988719953974829,
+           1.3370016872080628,
+           1.272174509395983,
+           1.2064398362587945,
+           1.1419098617799843,
+           1.0807102858994513,
+           1.0249299178401121,
+           0.9765704158360203,
+           0.937497388022303,
+           0.9093940545121258,
+           0.8937186163140847,
+           0.8916663939835784,
+           0.9041376897055373,
+           0.9317121934828061,
+           0.9746306004567142,
+           1.0327839358311512,
+           1.105710900549574,
+           1.1926033592485228,
+           1.2923198967559644,
+           1.4034071752897894,
+           1.5241286362917614,
+           1.6524999131180333,
+           1.7863301579600235,
+           1.9232683423903576,
+           2.060853469361201,
+           2.1965675383228347,
+           2.327890036756696,
+           2.4523526925259933,
+           2.567593213015272,
+           2.67140675928907
+          ],
+          [
+           2.7366603313193396,
+           2.817968477602511,
+           2.883105282612188,
+           2.9308033154104005,
+           2.9601292282325993,
+           2.970503295005814,
+           2.961710958124503,
+           2.933906129078267,
+           2.8876061844420775,
+           2.8236787958484277,
+           2.7433209260680425,
+           2.648030508528853,
+           2.5395715000060397,
+           2.4199331516405547,
+           2.2912844781311894,
+           2.1559250156494265,
+           2.0162330430924142,
+           1.8746124967191546,
+           1.7334398337155112,
+           1.595012095248185,
+           1.461497384289231,
+           1.3348889088574047,
+           1.2169636489870561,
+           1.1092465880340172,
+           1.012981308815243,
+           0.9291075960552215,
+           0.8582465126365991,
+           0.8006932325448222,
+           0.7564177227297721,
+           0.7250731740940631,
+           0.7060118931936857,
+           0.6983081856434076,
+           0.7007875940894028,
+           0.7120617020588823,
+           0.7305675837151576,
+           0.7546108717196534,
+           0.7824113336238909,
+           0.8121497934258121,
+           0.8420152103675067,
+           0.8702507322374515,
+           0.8951975751404452,
+           0.9153356449487748,
+           0.929319905775712,
+           0.9360116154773371,
+           0.9345036844436333,
+           0.9241395683043059,
+           0.9045252737226325,
+           0.875534234908448,
+           0.837305002335676,
+           0.7902318697599623,
+           0.7349487463463349,
+           0.6723067529888805,
+           0.6033461814064531,
+           0.5292635973294145,
+           0.4513749914778147,
+           0.3710759810124563,
+           0.2898001372498235,
+           0.20897656085604127,
+           0.1299878423580574,
+           0.054129533242195764,
+           -0.017427788503767708,
+           -0.0836728437372947,
+           -0.1437834489212085,
+           -0.19715098359293934,
+           -0.24339886716938067,
+           -0.282394540067442,
+           -0.3142546135306179,
+           -0.33934303072254535,
+           -0.3582622640612679,
+           -0.37183775579534367,
+           -0.3810959858445999,
+           -0.38723671844663476,
+           -0.3916001329030953,
+           -0.3956296797878505,
+           -0.40083161888400226,
+           -0.4087322859083026,
+           -0.42083419941274713,
+           -0.4385721554389216,
+           -0.46327046456084203,
+           -0.49610246363664334,
+           -0.5380533833856259,
+           -0.5898875740279548,
+           -0.6521209865789889,
+           -0.7249996795377318,
+           -0.8084849727943776,
+           -0.9022457062592731,
+           -1.0056578840568156,
+           -1.11781180052173,
+           -1.237526556279179,
+           -1.3633716860749014,
+           -1.493695439415174,
+           -1.6266590850075218,
+           -1.7602764547382797,
+           -1.89245780639993,
+           -2.021056970050475,
+           -2.143920653665646,
+           -2.258938721933157,
+           -2.364094229261214,
+           -2.4575119852402176,
+           -2.5375044580760275,
+           -2.6026138783287527,
+           -2.651649490334846,
+           -2.6837190099530397,
+           -2.698253482095635,
+           -2.695024886637983,
+           -2.674156012985227,
+           -2.6361223076461084,
+           -2.5817455911354616,
+           -2.5121797357143,
+           -2.42888858910653,
+           -2.333616616662535,
+           -2.22835291087797,
+           -2.115289378388378,
+           -1.9967740565820025,
+           -1.8752606313061424,
+           -1.753255320841032,
+           -1.6332623570598903,
+           -1.5177293308479376,
+           -1.4089936745044431,
+           -1.3092315288344825,
+           -1.2204101875366304,
+           -1.1442452276318125,
+           -1.0821633240841138,
+           -1.0352716121189394,
+           -1.0043343053186917,
+           -0.9897571051509291,
+           -0.9915797523547356,
+           -1.009476877085512,
+           -1.0427671076063763,
+           -1.0904302014109757,
+           -1.1511317727307204,
+           -1.2232550110325906,
+           -1.3049386207023448,
+           -1.3941200666128843,
+           -1.4885830872119712,
+           -1.5860083390870823,
+           -1.6840259670115034,
+           -1.78026885289532,
+           -1.8724252867855096,
+           -1.9582898232631119,
+           -2.0358111367059384,
+           -2.103135767622316,
+           -2.1586467576125536,
+           -2.20099629982796,
+           -2.229131681834678,
+           -2.2423139648098003,
+           -2.2401290228481203,
+           -2.222490754378753,
+           -2.189636469625081,
+           -2.1421146489495704,
+           -2.0807654521041212,
+           -2.006694533305562,
+           -1.9212408773881262,
+           -1.825939514134271,
+           -1.7224800878026505,
+           -1.6126623539602207,
+           -1.4983497437093483,
+           -1.381422174684572,
+           -1.2637292978974837,
+           -1.147045349490799,
+           -1.0330267273223082,
+           -0.923173335359067,
+           -0.8187946361343396,
+           -0.7209812256566484,
+           -0.6305825993860358,
+           -0.548191615921884,
+           -0.4741359909924094,
+           -0.40847697260558585,
+           -0.35101516340572836,
+           -0.3013032730405305,
+           -0.25866540629319995,
+           -0.22222232632453423,
+           -0.19092198077790173,
+           -0.16357444552555334,
+           -0.13889032980475538,
+           -0.11552160017828214,
+           -0.09210372130317643,
+           -0.06729798037370377,
+           -0.03983286007423132,
+           -0.008543351957844596,
+           0.027592842353688137,
+           0.06942319229907491,
+           0.11759316466266448,
+           0.17252472837986627,
+           0.23440112291377513,
+           0.3031583118532018,
+           0.3784833690384669,
+           0.45981986365534255,
+           0.546380127936863,
+           0.6371641110157972,
+           0.730984349650575,
+           0.8264964253983763,
+           0.9222341324342178,
+           1.0166484543248822,
+           1.108149344886021,
+           1.19514923043639,
+           1.2761071003375115,
+           1.3495720310072514,
+           1.414224996238534,
+           1.4689178535212166,
+           1.512708461303034,
+           1.5448909741688168,
+           1.5650204795246838,
+           1.5729312776847337,
+           1.5687482638620014,
+           1.5528910415879131,
+           1.526070578281693,
+           1.489278400555993,
+           1.4437685147188248,
+           1.3910324221207877,
+           1.3327677748877433,
+           1.270841380756076,
+           1.2072474120805807,
+           1.1440617999131635,
+           1.0833938961548486,
+           1.027336562547224,
+           0.977915892723721,
+           0.9370417914145853,
+           0.90646062265145,
+           0.8877110966524819,
+           0.8820844939316673,
+           0.8905902267302211,
+           0.9139276144559181,
+           0.9524646044011112,
+           1.0062240051045492,
+           1.0748776213010611,
+           1.157748490806986,
+           1.2538212295166626,
+           1.3617602956799635,
+           1.4799357935648594,
+           1.606456254164685,
+           1.7392076612644294,
+           1.8758978390956593,
+           2.0141051867284943,
+           2.151330637503723,
+           2.2850516418386695,
+           2.412776920632145,
+           2.5321007155241846,
+           2.640755271976487,
+           2.7366603313193387
+          ],
+          [
+           2.7956814236040453,
+           2.867216768829965,
+           2.9217113924624534,
+           2.9581049257042378,
+           2.9756842549364655,
+           2.974098259806954,
+           2.9533643804962404,
+           2.913866875697397,
+           2.856346830096755,
+           2.7818841657619044,
+           2.6918721010752757,
+           2.5879846791004706,
+           2.4721381502107573,
+           2.3464471374998213,
+           2.2131766344644688,
+           2.0746909797884014,
+           1.9334010214880402,
+           1.7917107206154228,
+           1.6519644522850516,
+           1.5163962388830663,
+           1.3870820975587967,
+           1.2658966028532426,
+           1.1544746576467133,
+           1.0541793342154013,
+           0.9660764953591554,
+           0.8909167370820923,
+           0.8291250133585346,
+           0.7807981145825837,
+           0.7457099790513815,
+           0.7233246260126486,
+           0.7128163141136956,
+           0.7130963550572054,
+           0.7228458531603882,
+           0.7405535012112181,
+           0.7645574449264282,
+           0.7930901352903462,
+           0.8243250223127977,
+           0.856423906827118,
+           0.8875837596749873,
+           0.9160818400737631,
+           0.9403179964748052,
+           0.9588531124162536,
+           0.9704427646823934,
+           0.9740652888011715,
+           0.9689435942726853,
+           0.9545602351716658,
+           0.9306654167635994,
+           0.8972778010888036,
+           0.8546781594982881,
+           0.803396103206388,
+           0.7441902994517241,
+           0.6780227463953624,
+           0.6060278302810747,
+           0.5294770198712305,
+           0.4497401624668557,
+           0.36824443019730624,
+           0.2864320226287699,
+           0.20571776067793962,
+           0.1274477066305803,
+           0.052859915790890104,
+           -0.016951632304748724,
+           -0.08106895960526013,
+           -0.13877701779856957,
+           -0.18958489571778941,
+           -0.23324073210009494,
+           -0.2697399242575722,
+           -0.2993263981835766,
+           -0.32248688674926246,
+           -0.33993834534781653,
+           -0.3526088139815918,
+           -0.3616122067973436,
+           -0.3682176700835698,
+           -0.3738142936766152,
+           -0.3798720849047027,
+           -0.3879002154506391,
+           -0.39940362722720385,
+           -0.41583913156574565,
+           -0.4385721554389215,
+           -0.46883527851493073,
+           -0.507689665751575,
+           -0.555990432895027,
+           -0.614356888272162,
+           -0.6831484759492624,
+           -0.7624471055811513,
+           -0.852046396542942,
+           -0.9514481921287067,
+           -1.059866517984665,
+           -1.1762389720404243,
+           -1.299245345674052,
+           -1.4273330923844016,
+           -1.5587490854457648,
+           -1.6915769442783277,
+           -1.8237790646606342,
+           -1.9532423640977692,
+           -2.0778266537929944,
+           -2.195414475314481,
+           -2.3039611951142254,
+           -2.401544134752975,
+           -2.4864095294915107,
+           -2.557016152558038,
+           -2.612074515887289,
+           -2.650580658727443,
+           -2.6718436608300418,
+           -2.675506163964096,
+           -2.661557350674992,
+           -2.630338008533123,
+           -2.582537497221694,
+           -2.519182630084184,
+           -2.4416186764406524,
+           -2.3514828813212545,
+           -2.2506710805874834,
+           -2.141298157263734,
+           -2.025653235155618,
+           -1.9061506347856818,
+           -1.7852777211486444,
+           -1.6655408501911364,
+           -1.5494106693307361,
+           -1.439268045530252,
+           -1.3373518819598893,
+           -1.2457100413876108,
+           -1.1661545221573173,
+           -1.100221932686366,
+           -1.0491401852566578,
+           -1.0138021825239973,
+           -0.9947471042088358,
+           -0.9921497208936257,
+           -1.0058179711303552,
+           -1.0351988417965885,
+           -1.0793923946042212,
+           -1.137173588653335,
+           -1.2070213646239967,
+           -1.2871542850850086,
+           -1.3755718716174996,
+           -1.4701006467214872,
+           -1.5684437799942588,
+           -1.6682331564418063,
+           -1.7670826319483741,
+           -1.8626412181153496,
+           -1.9526449463821638,
+           -2.034966199301273,
+           -2.107659364056881,
+           -2.1690017580763143,
+           -2.2175288964922637,
+           -2.252063313268669,
+           -2.2717363084581836,
+           -2.276002169318993,
+           -2.2646445985361328,
+           -2.2377752739754064,
+           -2.1958246565254496,
+           -2.1395253509202985,
+           -2.0698885043505855,
+           -1.9881738947538248,
+           -1.8958545108385008,
+           -1.794576555486224,
+           -1.6861159100524872,
+           -1.572332176706606,
+           -1.4551214674289354,
+           -1.336369130436416,
+           -1.2179035971842571,
+           -1.1014524959830803,
+           -0.9886021127007315,
+           -0.8807611867171327,
+           -0.779129913661897,
+           -0.6846748884835441,
+           -0.5981105665982184,
+           -0.5198876512045137,
+           -0.45018863562858535,
+           -0.3889305453102813,
+           -0.33577473940382724,
+           -0.2901434515954343,
+           -0.25124257816937673,
+           -0.21809006289045182,
+           -0.18954908688587516,
+           -0.16436515094061607,
+           -0.14120604048185678,
+           -0.118703592437763,
+           -0.0954961398729706,
+           -0.07027049588663149,
+           -0.041802353039761965,
+           -0.008994018153108007,
+           0.02909152644390238,
+           0.07320114705335047,
+           0.12386745953451882,
+           0.18139075766624582,
+           0.24582746212535223,
+           0.31698541305832223,
+           0.3944261506085901,
+           0.47747414526508564,
+           0.5652327581498905,
+           0.6566065349780615,
+           0.7503292708827969,
+           0.8449971308420786,
+           0.9391059759550838,
+           1.0310919327362833,
+           1.1193741538257258,
+           1.2023986563504134,
+           1.2786820902430558,
+           1.3468542840526603,
+           1.4056984403563866,
+           1.4541879062577894,
+           1.4915185253624115,
+           1.5171356840946957,
+           1.5307552946521703,
+           1.532378106095534,
+           1.5222969003569302,
+           1.5010963072133419,
+           1.4696451571096816,
+           1.4290814785199382,
+           1.3807904326134803,
+           1.326375657689201,
+           1.267624664642626,
+           1.2064690783920633,
+           1.1449406548280943,
+           1.0851241150495659,
+           1.0291079255419266,
+           0.9789342122956813,
+           0.9365490270885402,
+           0.9037541844171026,
+           0.8821618577567527,
+           0.8731530645903641,
+           0.8778410823453102,
+           0.8970407240798207,
+           0.9312442661756769,
+           0.9806046637175233,
+           1.0449265164622554,
+           1.1236650635245848,
+           1.2159332926300301,
+           1.3205170547100689,
+           1.4358978815086356,
+           1.5602830174666644,
+           1.6916420020263099,
+           1.8277489789527344,
+           1.9662297692359465,
+           2.104612627060881,
+           2.24038150711461,
+           2.3710306083966644,
+           2.4941189262879266,
+           2.6073235417628178,
+           2.708490404399528,
+           2.795681423604044
+          ],
+          [
+           2.8479706909951092,
+           2.909122166780869,
+           2.9524960229254216,
+           2.9772479360917603,
+           2.9828910802608624,
+           2.969305939685177,
+           2.9367418410633195,
+           2.885810183585182,
+           2.8174695424137797,
+           2.733003013644773,
+           2.6339883521402725,
+           2.522261623420161,
+           2.399875242896975,
+           2.2690514064814264,
+           2.1321320228138214,
+           1.9915263365446012,
+           1.8496574823144267,
+           1.7089092292015735,
+           1.5715741649835888,
+           1.4398045289223806,
+           1.315566831990266,
+           1.200601306286093,
+           1.0963871032925054,
+           1.0041140166533744,
+           0.9246613428926598,
+           0.85858431698384,
+           0.8061083732872769,
+           0.7671312907106018,
+           0.7412330887440567,
+           0.7276933530115097,
+           0.7255154897776724,
+           0.733457242853899,
+           0.7500666576036413,
+           0.7737225488825664,
+           0.802678425850716,
+           0.8351087491568517,
+           0.8691563468481138,
+           0.902979795624741,
+           0.9347995841297985,
+           0.9629419144858109,
+           0.9858790661799373,
+           1.0022653408688953,
+           1.0109677252778773,
+           1.011090549061127,
+           1.0019935717126474,
+           0.9833031033702498,
+           0.9549159443209869,
+           0.916996112645107,
+           0.8699645140749374,
+           0.814481888148353,
+           0.7514255355817299,
+           0.6818604891893608,
+           0.6070059306939006,
+           0.5281977749062551,
+           0.4468484380332197,
+           0.3644048759301212,
+           0.2823060192483677,
+           0.20194074463307957,
+           0.12460750413127565,
+           0.05147668923916784,
+           -0.01644326726624628,
+           -0.0783351475217994,
+           -0.13359678071266246,
+           -0.18185881120363265,
+           -0.22299592129557325,
+           -0.25713119820938857,
+           -0.28463351393792297,
+           -0.30610796916531163,
+           -0.3223796339005619,
+           -0.3344709932002359,
+           -0.34357367189817145,
+           -0.351015163405728,
+           -0.35822142054070716,
+           -0.3666762775893632,
+           -0.37787875954763916,
+           -0.3932993944820914,
+           -0.41433667662494567,
+           -0.4422748303084392,
+           -0.4782439980202363,
+           -0.5231839203297547,
+           -0.5778120925219515,
+           -0.6425972744973523,
+           -0.7177390995113543,
+           -0.8031543768631335,
+           -0.8984705174297742,
+           -1.0030263331016764,
+           -1.1158802761372721,
+           -1.2358259968343073,
+           -1.3614149124019952,
+           -1.4909853011610925,
+           -1.6226972686874972,
+           -1.7545727804690685,
+           -1.8845398229091033,
+           -2.0104796444555806,
+           -2.130275944078939,
+           -2.241864817451041,
+           -2.3432842435006163,
+           -2.4327218963204795,
+           -2.508560099722779,
+           -2.5694168033802605,
+           -2.614181549025822,
+           -2.6420455104887868,
+           -2.6525248296613957,
+           -2.6454766284761893,
+           -2.6211072508050033,
+           -2.579972473635471,
+           -2.52296961941939,
+           -2.4513216964139195,
+           -2.3665538863795534,
+           -2.27046288443667,
+           -2.1650797696615367,
+           -2.0526272428485584,
+           -1.93547220588977,
+           -1.816074772018232,
+           -1.6969348848880959,
+           -1.5805377849163251,
+           -1.4692995919764495,
+           -1.365514273628918,
+           -1.2713032375603406,
+           -1.1885687264995095,
+           -1.1189521050287454,
+           -1.063798012559305,
+           -1.0241252180783393,
+           -1.000604853467912,
+           -0.9935465271027065,
+           -1.0028926323099425,
+           -1.0282209706745467,
+           -1.06875561282812,
+           -1.1233857240710647,
+           -1.1906918936899233,
+           -1.268979329723965,
+           -1.3563171195019392,
+           -1.4505826144200662,
+           -1.5495098785908477,
+           -1.6507410480170557,
+           -1.7518793820570708,
+           -1.8505427536760681,
+           -1.9444163201233793,
+           -2.0313031412935185,
+           -2.1091715684222403,
+           -2.1761983095150206,
+           -2.230806187885116,
+           -2.271695743631248,
+           -2.2978699814791734,
+           -2.308651738324995,
+           -2.303693325834818,
+           -2.2829782930696507,
+           -2.2468153466319505,
+           -2.19582465652545,
+           -2.1309169600919957,
+           -2.0532660495193675,
+           -1.9642753862662188,
+           -1.8655397244760874,
+           -1.7588027416855885,
+           -1.6459117660712905,
+           -1.5287707529580417,
+           -1.4092926978471294,
+           -1.2893526780573998,
+           -1.1707426901866163,
+           -1.055129396714761,
+           -0.9440158136258487,
+           -0.8387078640444253,
+           -0.7402865933202625,
+           -0.649586692063549,
+           -0.567181809123393,
+           -0.49337696058603314,
+           -0.4282081579948436,
+           -0.3714491937765461,
+           -0.3226253389612935,
+           -0.2810335323074107,
+           -0.24576847530166573,
+           -0.2157538983291322,
+           -0.1897781333250655,
+           -0.16653302067940293,
+           -0.14465509573963264,
+           -0.12276794499219804,
+           -0.09952459525385267,
+           -0.07364880161122073,
+           -0.04397413131375269,
+           -0.009479800525472315,
+           0.030677692762894386,
+           0.07713798547667006,
+           0.13031602912497176,
+           0.19038759482657422,
+           0.25728150082909274,
+           0.330678784092971,
+           0.41001885613709904,
+           0.4945125007594744,
+           0.5831613920890429,
+           0.6747836402444951,
+           0.7680447130250312,
+           0.8614929395829652,
+           0.9535986795650638,
+           1.0427961418954597,
+           1.127526763765692,
+           1.2062830144105487,
+           1.2776514711038482,
+           1.3403540270048437,
+           1.3932861317852112,
+           1.435551035399584,
+           1.4664891012519132,
+           1.485701375011819,
+           1.4930667364965404,
+           1.4887521208662668,
+           1.473215467945384,
+           1.447201240489204,
+           1.411728539130045,
+           1.3680720288903438,
+           1.3177360748598896,
+           1.2624226583161626,
+           1.2039938048523977,
+           1.144429398922824,
+           1.0857813809990084,
+           1.0301254211515543,
+           0.9795112338172853,
+           0.9359127409302646,
+           0.9011793033365626,
+           0.8769892230615853,
+           0.8648066718845369,
+           0.8658431258646027,
+           0.8810242827372,
+           0.9109633119059167,
+           0.9559411381553904,
+           1.0158942937967042,
+           1.09041069377066,
+           1.1787334986639417,
+           1.2797730362663609,
+           1.3921265579674003,
+           1.51410541671823,
+           1.6437690731234624,
+           1.778965169902736,
+           1.917374766569902,
+           2.056561699376234,
+           2.1940249294872216,
+           2.327252667540975,
+           2.453777017033812,
+           2.5712278635485166,
+           2.677384752093196,
+           2.770225540413599,
+           2.8479706909951084
+          ],
+          [
+           2.893085742629241,
+           2.9433301328261496,
+           2.9751987220971703,
+           2.988070388042778,
+           2.981688731202419,
+           2.9561668798372644,
+           2.9119839740311284,
+           2.8499734250526885,
+           2.7713032408391243,
+           2.6774488961629186,
+           2.570159401971717,
+           2.451417388279004,
+           2.3233941549599058,
+           2.1884007614917538,
+           2.048836317266916,
+           1.9071346964322993,
+           1.7657109338073658,
+           1.6269085605630709,
+           1.4929491100187129,
+           1.3658849658905399,
+           1.247556639091375,
+           1.1395554469113727,
+           1.0431924329191864,
+           0.9594742105893268,
+           0.8890862423461935,
+           0.832383882665083,
+           0.7893913236129775,
+           0.7598083884431421,
+           0.7430249283256136,
+           0.7381423936833643,
+           0.744001979413056,
+           0.7592185867093213,
+           0.7822197070960178,
+           0.8112882199204624,
+           0.8446080057394607,
+           0.8803112168322197,
+           0.9165260139378647,
+           0.9514235759326731,
+           0.9832632164916485,
+           1.0104344980396431,
+           1.031495316989517,
+           1.0452050432097328,
+           1.050551928057772,
+           1.046774145801283,
+           1.033373998999092,
+           1.0101249952288014,
+           0.9770716859581712,
+           0.9345223437389544,
+           0.8830347365887515,
+           0.8233954338288734,
+           0.756593241364711,
+           0.6837875123302397,
+           0.6062722074728428,
+           0.5254366854257567,
+           0.44272428347413545,
+           0.35958980257741957,
+           0.2774570349642528,
+           0.19767746798631977,
+           0.12149126425849387,
+           0.049991556309573686,
+           -0.015906994386523897,
+           -0.07549453677420268,
+           -0.1282865648133179,
+           -0.1740380962215518,
+           -0.2127511104910513,
+           -0.2446750374507721,
+           -0.270300269242981,
+           -0.29034485102499763,
+           -0.30573468436375517,
+           -0.3175777476225437,
+           -0.3271329953148604,
+           -0.3357747394038269,
+           -0.34495343625795666,
+           -0.3561539003428907,
+           -0.3708520372267022,
+           -0.39047123224418584,
+           -0.41633954603901496,
+           -0.4496488537425993,
+           -0.49141702105225005,
+           -0.5424541389662211,
+           -0.6033337411515423,
+           -0.67436980625714,
+           -0.7556002049374938,
+           -0.8467770914483836,
+           -0.9473645663850184,
+           -1.0565437547661756,
+           -1.173225256774152,
+           -1.2960687417101864,
+           -1.42350927379644,
+           -1.5537897859157705,
+           -1.6849989585732628,
+           -1.81511362029963,
+           -1.9420446659743484,
+           -2.063685394181372,
+           -2.177961096178917,
+           -2.282878689161832,
+           -2.3765751763090996,
+           -2.4573637359927685,
+           -2.523776292086619,
+           -2.5746014954253797,
+           -2.6089171512905556,
+           -2.626116256835177,
+           -2.6259259625006592,
+           -2.6084189390906634,
+           -2.574016813176797,
+           -2.5234855235081692,
+           -2.4579226454401732,
+           -2.378736924330942,
+           -2.287620447622125,
+           -2.186514064288383,
+           -2.0775668251056354,
+           -1.9630903636924415,
+           -1.8455092629058052,
+           -1.7273085508384582,
+           -1.61097954289485,
+           -1.4989652894131489,
+           -1.393606900962124,
+           -1.297092005428184,
+           -1.2114065427247696,
+           -1.1382910255508711,
+           -1.0792022899591602,
+           -1.0352816300969154,
+           -1.0073300604908877,
+           -0.9957912803263581,
+           -1.0007427314258888,
+           -1.0218949495080745,
+           -1.0585992114736935,
+           -1.1098632847125673,
+           -1.1743748925324087,
+           -1.2505323274428217,
+           -1.3364814756095802,
+           -1.4301583654076753,
+           -1.5293362242831872,
+           -1.6316759241862637,
+           -1.734778619152951,
+           -1.8362393310138219,
+           -1.9337002217986328,
+           -2.024902304552766,
+           -2.1077343875973846,
+           -2.1802781196249366,
+           -2.240848102587555,
+           -2.2880261636057146,
+           -2.3206890229919326,
+           -2.338028759318659,
+           -2.3395656501940163,
+           -2.3251531546427606,
+           -2.2949749950968283,
+           -2.24953448924303,
+           -2.189636469625082,
+           -2.1163623073464115,
+           -2.031038721100084,
+           -1.9352012000387473,
+           -1.8305529951111092,
+           -1.7189207353849525,
+           -1.6022078011097243,
+           -1.482346632071209,
+           -1.361251167092347,
+           -1.2407705980098371,
+           -1.1226455795183157,
+           -1.0084679660670928,
+           -0.8996450503633642,
+           -0.7973691574801014,
+           -0.7025933071763294,
+           -0.6160134984159666,
+           -0.5380579982452189,
+           -0.4688838365052987,
+           -0.408380522878245,
+           -0.3561808181487576,
+           -0.31167821195604245,
+           -0.2740505892159222,
+           -0.24228941107738747,
+           -0.21523359764989047,
+           -0.19160718225895257,
+           -0.17005971358295147,
+           -0.1492083150098869,
+           -0.12768027157983616,
+           -0.1041550048904035,
+           -0.07740431555234066,
+           -0.04632982066926468,
+           -0.00999658913624829,
+           0.032337921625857025,
+           0.08120040013453268,
+           0.1368843156172771,
+           0.19943912254735985,
+           0.26866633267455153,
+           0.34412257284187403,
+           0.42512956427944293,
+           0.5107907779410825,
+           0.6000143453983956,
+           0.6915416402793102,
+           0.7839807954204254,
+           0.8758442896146498,
+           0.9655896284335944,
+           1.0516620588967096,
+           1.1325381999367299,
+           1.2067694411899157,
+           1.2730239624241664,
+           1.330126254979826,
+           1.3770930842721536,
+           1.4131649173073408,
+           1.4378319492254574,
+           1.4508539953992161,
+           1.452273667314058,
+           1.4424224175729552,
+           1.4219192177551656,
+           1.391661818067781,
+           1.3528107251384585,
+           1.3067662192181673,
+           1.25513890985707,
+           1.1997144953154308,
+           1.1424135413841765,
+           1.0852472261099428,
+           1.0302701048197944,
+           0.9795310320566987,
+           0.9350234314356746,
+           0.8986361295661632,
+           0.8721059653357133,
+           0.8569733510323839,
+           0.8545418977605925,
+           0.8658431258646023,
+           0.8916071637916064,
+           0.9322401988154569,
+           0.9878092836826483,
+           1.0580349283994435,
+           1.1422917203079095,
+           1.2396170228391021,
+           1.3487276085970015,
+           1.4680438904874298,
+           1.5957212301715604,
+           1.7296876307265254,
+           1.8676869642795448,
+           2.007326749396559,
+           2.1461293805118697,
+           2.2815856254694604,
+           2.4112091494559635,
+           2.5325907956898646,
+           2.6434513559124935,
+           2.7416915969728666,
+           2.8254383728325534,
+           2.89308574262924
+          ],
+          [
+           2.9306448847548214,
+           2.9695512520937815,
+           2.989627414869619,
+           2.99048071871657,
+           2.9720873801782397,
+           2.9347922426550213,
+           2.879300242157822,
+           2.8066597952934202,
+           2.718238513174599,
+           2.615691826288762,
+           2.5009252723709667,
+           2.3760513479636725,
+           2.2433419510115846,
+           2.105177543482249,
+           1.9639942371844166,
+           1.822230050914498,
+           1.6822716017534747,
+           1.546402477462322,
+           1.41675449093367,
+           1.295262942739777,
+           1.1836269158690125,
+           1.083275500322958,
+           0.9953406975089779,
+           0.9206375889823021,
+           0.8596521751682958,
+           0.8125371016559897,
+           0.7791152981404319,
+           0.7588913628470382,
+           0.7510703380223754,
+           0.7545833444158839,
+           0.7681193789522992,
+           0.7901624339973147,
+           0.8190329722893913,
+           0.8529326917492654,
+           0.8899914413734528,
+           0.9283151049855662,
+           0.9660332547634523,
+           1.0013453914484487,
+           1.032564632500712,
+           1.0581577819877552,
+           1.076780814780106,
+           1.087308930126526,
+           1.0888604727545033,
+           1.0808141796462059,
+           1.062819383517371,
+           1.0347989854051527,
+           0.9969451940753137,
+           0.9497082145245814,
+           0.8937782470429202,
+           0.8300613276180665,
+           0.7596496956713295,
+           0.6837875123302398,
+           0.6038328682483654,
+           0.5212171114961478,
+           0.4374025910033739,
+           0.3538399478386107,
+           0.27192609437765936,
+           0.19296399998724667,
+           0.11812535181167338,
+           0.048417081898722326,
+           -0.01534735077681028,
+           -0.07257116021478564,
+           -0.12289129692994448,
+           -0.16618891755920928,
+           -0.2025929754217656,
+           -0.2324768267382182,
+           -0.2564479298347376,
+           -0.2753308954406804,
+           -0.2901443205424036,
+           -0.30207200175038346,
+           -0.31242927261079634,
+           -0.32262533896129314,
+           -0.33412259397922717,
+           -0.34839397723822046,
+           -0.36687949773829187,
+           -0.3909430680457779,
+           -0.4218307946264016,
+           -0.4606318381663647,
+           -0.5082428978752599,
+           -0.5653372868914363,
+           -0.6323394540877144,
+           -0.709405673555603,
+           -0.7964114701434298,
+           -0.8929461814320053,
+           -0.9983148776297017,
+           -1.1115476755180134,
+           -1.2314162954102164,
+           -1.3564575257862592,
+           -1.4850030834619707,
+           -1.6152151922880575,
+           -1.745127054614792,
+           -1.8726872608700023,
+           -1.995807076862798,
+           -2.112409468556587,
+           -2.220478672128383,
+           -2.3181090945331895,
+           -2.4035523371837964,
+           -2.4752611726556544,
+           -2.531929370710227,
+           -2.572526363852594,
+           -2.5963258618684972,
+           -2.602927666460591,
+           -2.592272097800138,
+           -2.564646620628516,
+           -2.520684444201373,
+           -2.4613550633099317,
+           -2.387946902118003,
+           -2.3020424138520568,
+           -2.2054861727780426,
+           -2.100346665882128,
+           -1.9888726460307857,
+           -1.8734450423089466,
+           -1.756525533410064,
+           -1.640602973644715,
+           -1.5281389162574057,
+           -1.4215135039055395,
+           -1.3229729907050733,
+           -1.234580124278458,
+           -1.1581685505950488,
+           -1.0953023106426412,
+           -1.0472413783710466,
+           -1.0149140467986395,
+           -0.9988968071273889,
+           -0.9994021881062797,
+           -1.0162748340334895,
+           -1.048995904285879,
+           -1.0966956798643233,
+           -1.1581740679443548,
+           -1.2319285085502083,
+           -1.3161886127643756,
+           -1.408956703581581,
+           -1.5080532924483099,
+           -1.611166410031005,
+           -1.7159036215814387,
+           -1.8198454975226999,
+           -1.9205992799705727,
+           -2.015851486506568,
+           -2.1034182235549133,
+           -2.1812920423644986,
+           -2.247684259310107,
+           -2.3010617767707258,
+           -2.3401775783511796,
+           -2.364094229261214,
+           -2.37219988535455,
+           -2.3642164983821305,
+           -2.3402000958804217,
+           -2.3005332070899467,
+           -2.24590969663173,
+           -2.1773124506857098,
+           -2.095984531631828,
+           -2.0033945723491446,
+           -1.9011973168431142,
+           -1.7911903263056692,
+           -1.6752679564044335,
+           -1.555373770487633,
+           -1.433452583115966,
+           -1.311403328253815,
+           -1.1910339166745723,
+           -1.0740191884997994,
+           -0.9618629808578931,
+           -0.8558652196484777,
+           -0.7570948111876733,
+           -0.6663689574872819,
+           -0.5842393519510986,
+           -0.5109855345824004,
+           -0.44661550187529875,
+           -0.39087348104398323,
+           -0.34325459579374573,
+           -0.30302597603617,
+           -0.2692537011793403,
+           -0.240834819954174,
+           -0.21653356283191186,
+           -0.1950207591059015,
+           -0.17491539223345098,
+           -0.154827175997238,
+           -0.13339901169489288,
+           -0.10934819342181366,
+           -0.08150526436266001,
+           -0.0488494909083887,
+           -0.010540011719939254,
+           0.03405816674534751,
+           0.08535402116066924,
+           0.14351674833552633,
+           0.2084687608082218,
+           0.2798856368326208,
+           0.35720303876883164,
+           0.4396304316070641,
+           0.526171255218949,
+           0.6156490344669031,
+           0.7067387548191305,
+           0.7980026916007552,
+           0.8879297620218042,
+           0.9749773737072815,
+           1.057614674070329,
+           1.1343660633211319,
+           1.2038538212978498,
+           1.2648387150214122,
+           1.316257499557059,
+           1.3572562983266123,
+           1.3872189486699547,
+           1.4057895217566971,
+           1.412888369857028,
+           1.4087212149290813,
+           1.3937809664698908,
+           1.368842139274702,
+           1.3349479285946346,
+           1.2933901865019064,
+           1.2456827243944304,
+           1.1935285379464857,
+           1.1387817081217588,
+           1.0834048711322903,
+           1.029423267915655,
+           0.978876476806067,
+           0.9337689991909639,
+           0.8960209053362026,
+           0.8674197552033763,
+           0.8495749866813145,
+           0.8438759116641509,
+           0.8514543800188714,
+           0.8731530645903633,
+           0.909500189546001,
+           0.9606913727172863,
+           1.0265790838257896,
+           1.106670038688148,
+           1.2001306591130658,
+           1.305800533885435,
+           1.4222136227377347,
+           1.5476267572840536,
+           1.680054815155235,
+           1.8173117803999406,
+           1.9570567586292384,
+           2.0968438929542565,
+           2.2341750295306086,
+           2.366553911897922,
+           2.4915406430318323,
+           2.6068051441337543,
+           2.7101783599529576,
+           2.7997000113949677,
+           2.873661776110035,
+           2.9306448847548205
+          ],
+          [
+           2.9603303500337628,
+           2.987563682049569,
+           2.9956600279728542,
+           2.98445853562495,
+           2.9541682589626497,
+           2.9053628672411427,
+           2.8389671646046053,
+           2.756235747214782,
+           2.6587243110283096,
+           2.548254296778832,
+           2.4268717154032426,
+           2.296801133278759,
+           2.1603959089214495,
+           2.020085858536208,
+           1.8783235849553006,
+           1.7375307317120683,
+           1.6000454206586567,
+           1.4680720977917772,
+           1.343634948684378,
+           1.2285359537427778,
+           1.1243185367101687,
+           1.0322376203359536,
+           0.9532367443966078,
+           0.8879327272248677,
+           0.8366081668863593,
+           0.7992118867046678,
+           0.7753672366950924,
+           0.764387972373792,
+           0.7653012500277182,
+           0.776877107326256,
+           0.7976636442820523,
+           0.8260269857675722,
+           0.8601949963020334,
+           0.8983036332929655,
+           0.9384447683509891,
+           0.9787142790011073,
+           1.0172592156652098,
+           1.0523228810229253,
+           1.0822867198684076,
+           1.105708005752914,
+           1.1213524237484749,
+           1.128220783683732,
+           1.1255692517451228,
+           1.1129226565062764,
+           1.0900806039902704,
+           1.0571163207773042,
+           1.0143683298008788,
+           0.9624252456634572,
+           0.9021041504775074,
+           0.8344231730381243,
+           0.7605690395150904,
+           0.6818604891893608,
+           0.5997085509341207,
+           0.5155747526222518,
+           0.4309283845473312,
+           0.347203958086624,
+           0.26575999174872916,
+           0.18784021870800097,
+           0.11453824393320705,
+           0.04676658677258736,
+           -0.014769071275285229,
+           -0.06958975093208396,
+           -0.11745662347022211,
+           -0.15837768281988232,
+           -0.1926074585070106,
+           -0.22063976845410815,
+           -0.2431936927728413,
+           -0.2611931272704953,
+           -0.27574044396915554,
+           -0.28808494121026346,
+           -0.299586903933566,
+           -0.3116782119560422,
+           -0.32582052753120866,
+           -0.34346216073622315,
+           -0.3659947505640744,
+           -0.39471090994247776,
+           -0.4307639639392381,
+           -0.4751308625616534,
+           -0.5285792739575471,
+           -0.5916397623192103,
+           -0.6645838298737935,
+           -0.7474084571014853,
+           -0.8398276133582123,
+           -0.9412710354209862,
+           -1.0508903884754162,
+           -1.1675727372980709,
+           -1.2899610695268593,
+           -1.4164814326230049,
+           -1.5453760759425508,
+           -1.6747418335447308,
+           -1.8025728459112993,
+           -1.9268066031285904,
+           -2.0453722012505677,
+           -2.1562396398641157,
+           -2.2574689539953834,
+           -2.347257968393733,
+           -2.4239874871364013,
+           -2.4862627858962876,
+           -2.5329503568591365,
+           -2.5632089652140175,
+           -2.5765142087657815,
+           -2.5726759253325553,
+           -2.5518479624837447,
+           -2.514530006711136,
+           -2.461561359853437,
+           -2.394106744848389,
+           -2.3136344159057685,
+           -2.2218870352405777,
+           -2.1208459549786713,
+           -2.0126897043996115,
+           -1.8997476253265326,
+           -1.7844497186819475,
+           -1.669273860019677,
+           -1.5566916088547822,
+           -1.4491138741629273,
+           -1.3488377055462246,
+           -1.2579954560482818,
+           -1.1785075089812147,
+           -1.112039678675062,
+           -1.059966285755558,
+           -1.0233397740389176,
+           -1.0028675816356176,
+           -0.9988968071273887,
+           -1.0114070268939037,
+           -1.0400114263090914,
+           -1.0839662103026138,
+           -1.1421880624850038,
+           -1.2132792314364624,
+           -1.2955596424896445,
+           -1.387105267770957,
+           -1.4857918404159096,
+           -1.5893428742932225,
+           -1.6953808512635125,
+           -1.8014803663429413,
+           -1.905221978842093,
+           -2.0042455055858373,
+           -2.096301510926573,
+           -2.1792997969262045,
+           -2.2513537745503114,
+           -2.3108197010343883,
+           -2.3563298971339446,
+           -2.3868192075539794,
+           -2.401544134752976,
+           -2.4000942563979706,
+           -2.382395725559031,
+           -2.348706845616112,
+           -2.2996059040604244,
+           -2.2359716361837787,
+           -2.158956866484242,
+           -2.06995603815184,
+           -1.9705674852741017,
+           -1.8625514249180872,
+           -1.7477847440496725,
+           -1.6282137270073145,
+           -1.50580591129672,
+           -1.3825022718712827,
+           -1.260170916604511,
+           -1.1405634288818067,
+           -1.0252749184027774,
+           -0.9157087403510282,
+           -0.8130467186596364,
+           -0.7182255643611246,
+           -0.6319200186431942,
+           -0.5545330763260029,
+           -0.4861934634279541,
+           -0.4267603568835392,
+           -0.375835149988003,
+           -0.332779888401816,
+           -0.2967418330327398,
+           -0.26668345204107125,
+           -0.2414170084311376,
+           -0.2196427955815154,
+           -0.19998998346112598,
+           -0.18105897539229854,
+           -0.16146414059516936,
+           -0.13987578220823532,
+           -0.11506022412316275,
+           -0.08591695215954293,
+           -0.051511824480737975,
+           -0.011105470675585656,
+           0.03582387406923515,
+           0.08956370704166366,
+           0.15015721389771303,
+           0.21740011478351529,
+           0.2908444929133302,
+           0.3698095152131235,
+           0.45339877422065344,
+           0.5405238067955578,
+           0.6299331827502683,
+           0.7202464093981765,
+           0.8099917699793544,
+           0.8976471082391254,
+           0.9816824908131065,
+           1.0606036255983604,
+           1.1329948893675479,
+           1.1975608221979708,
+           1.25316497979248,
+           1.2988650966831023,
+           1.333943602133934,
+           1.3579326441227821,
+           1.370632912281382,
+           1.3721257047569835,
+           1.3627778527964967,
+           1.3432392962439128,
+           1.31443328860559,
+           1.2775393972380344,
+           1.2339696478653546,
+           1.1853383384259388,
+           1.1334262107535116,
+           1.0801398156872064,
+           1.0274670341487984,
+           0.9774298202869136,
+           0.9320353103067046,
+           0.8932264900599498,
+           0.8628336345385155,
+           0.8425277224945839,
+           0.8337769896481667,
+           0.8378077152206004,
+           0.8555702404565865,
+           0.8877110966524808,
+           0.9345519769058147,
+           0.9960761238058916,
+           1.0719225285320688,
+           1.1613881496221365,
+           1.2634381665914194,
+           1.376724089351108,
+           1.4996093537561292,
+           1.630201851292514,
+           1.7663926713789089,
+           1.9059001821870911,
+           2.0463184440513253,
+           2.185168841701526,
+           2.3199537404006416,
+           2.4482109186208336,
+           2.5675675074825177,
+           2.675792175395263,
+           2.7708443350214136,
+           2.850919217924381,
+           2.914487758432978,
+           2.960330350033762
+          ],
+          [
+           2.9818909859969787,
+           2.9972150293853685,
+           2.993245522770234,
+           2.9700547891619404,
+           2.9280829714296277,
+           2.8681277394285747,
+           2.7913259774585035,
+           2.6991278910806598,
+           2.5932641514808963,
+           2.4757068596486134,
+           2.3486252576701094,
+           2.214337236901628,
+           2.0752577897390942,
+           1.9338456208127006,
+           1.7925491730638379,
+           1.653753333392342,
+           1.5197280612227453,
+           1.3925801320083508,
+           1.2742091076852362,
+           1.1662685394207628,
+           1.070133277339875,
+           0.9868736105099536,
+           0.917236792077662,
+           0.8616363232466102,
+           0.8201491802379817,
+           0.7925209751593343,
+           0.7781788495728043,
+           0.7762517132195628,
+           0.7855972643865158,
+           0.8048350670922163,
+           0.832384817548693,
+           0.8665088116832225,
+           0.9053575297847689,
+           0.9470171858555174,
+           0.9895580496004597,
+           1.0310823390607848,
+           1.0697705018338972,
+           1.1039247520267255,
+           1.1320088072361034,
+           1.1526828729253449,
+           1.1648330479138678,
+           1.1675944710874329,
+           1.160367692148458,
+           1.1428279241380075,
+           1.1149270181567474,
+           1.0768881865892979,
+           1.0291936855225692,
+           0.9725658453176244,
+           0.9079420059819421,
+           0.8364440669030357,
+           0.7593434948310673,
+           0.6780227463953625,
+           0.5939341491208618,
+           0.5085573457133385,
+           0.42335643882223695,
+           0.3397379767975807,
+           0.2590108950958961,
+           0.18234947365674256,
+           0.11076028917893146,
+           0.045054034866793456,
+           -0.014177048388206093,
+           -0.06657553299773229,
+           -0.11202852423083769,
+           -0.15067047858408947,
+           -0.1828790417383831,
+           -0.2092640094678555,
+           -0.23064969490044646,
+           -0.24805115843057526,
+           -0.2626449179576492,
+           -0.27573490286357016,
+           -0.28871454153341675,
+           -0.30302597603616965,
+           -0.32011747615277925,
+           -0.34140017623617813,
+           -0.3682052810654965,
+           -0.4017428802868716,
+           -0.44306347532283247,
+           -0.49302325862119795,
+           -0.552254094355141,
+           -0.6211390344054191,
+           -0.6997940664998828,
+           -0.7880566361495339,
+           -0.885481314364216,
+           -0.9913428032833338,
+           -1.104646286309717,
+           -1.2241449427320608,
+           -1.3483642638432423,
+           -1.4756326328074587,
+           -1.6041174684027049,
+           -1.7318660873646474,
+           -1.8568503150739009,
+           -1.977013772950605,
+           -2.090320695756863,
+           -2.1948050850213185,
+           -2.2886189872570295,
+           -2.370078698080586,
+           -2.4377077355513057,
+           -2.4902754970883643,
+           -2.5268306125285274,
+           -2.546728128918303,
+           -2.549649807532532,
+           -2.5356169768700814,
+           -2.504995563028387,
+           -2.4584931065702915,
+           -2.397147768180071,
+           -2.322309519327936,
+           -2.2356139040636087,
+           -2.1389489392702785,
+           -2.034415888766727,
+           -1.9242847974002029,
+           -1.8109458009975663,
+           -1.6968573335201713,
+           -1.5844924313733595,
+           -1.4762843845851081,
+           -1.3745730042267728,
+           -1.2815527644754972,
+           -1.199224036337615,
+           -1.1293485592350174,
+           -1.0734101980948048,
+           -1.0325819096499,
+           -1.0076996953510222,
+           -0.9992441531542162,
+           -1.0073300604908868,
+           -1.0317042303208357,
+           -1.071751685941112,
+           -1.1265100029451336,
+           -1.1946914731932252,
+           -1.2747125605703766,
+           -1.3647299461641738,
+           -1.4626823054710576,
+           -1.5663368260866513,
+           -1.67333936429605,
+           -1.7812670557004129,
+           -1.887682140486171,
+           -1.9901857394458702,
+           -2.0864703229405617,
+           -2.1743696514480035,
+           -2.251905032219115,
+           -2.317326830197236,
+           -2.3691502903916795,
+           -2.406184870369829,
+           -2.427556441925481,
+           -2.4327218963204804,
+           -2.421475873447548,
+           -2.393949527236606,
+           -2.35060143289772,
+           -2.2922009314115,
+           -2.2198043883875904,
+           -2.13472501356902,
+           -2.0384970397393154,
+           -1.9328351918860363,
+           -1.819590485996818,
+           -1.7007034792102547,
+           -1.5781561472665764,
+           -1.4539235900554526,
+           -1.3299267610255683,
+           -1.207987381529919,
+           -1.0897861377964229,
+           -0.9768251678093042,
+           -0.8703957303062182,
+           -0.771551811290799,
+           -0.6810902684171427,
+           -0.5995379442550103,
+           -0.5271460000747111,
+           -0.46389153692238716,
+           -0.409486385041206,
+           -0.36339276079596033,
+           -0.3248453167373634,
+           -0.29287894963916783,
+           -0.26636158727187575,
+           -0.24403105093031988,
+           -0.22453499038269573,
+           -0.20647281343798124,
+           -0.18843848556596726,
+           -0.16906305707992175,
+           -0.14705578671054859,
+           -0.12124277062999403,
+           -0.09060205406791633,
+           -0.05429429683957075,
+           -0.011688181964549633,
+           0.03762010491456818,
+           0.09379384193005814,
+           0.15674953096033625,
+           0.2261576211771256,
+           0.301450184035298,
+           0.38183534567953537,
+           0.46631810571145393,
+           0.5537270035899672,
+           0.6427459398903631,
+           0.7319503231464259,
+           0.8198465975280205,
+           0.9049141151204655,
+           0.9856482514262541,
+           1.0606036255983604,
+           1.1284362788280888,
+           1.1879436855102785,
+           1.2381015218198315,
+           1.2780961939564215,
+           1.3073522316530244,
+           1.3255537790544965,
+           1.3326595616242203,
+           1.328910870691145,
+           1.3148322825495544,
+           1.2912250122955,
+           1.2591529892447766,
+           1.2199219261509144,
+           1.175051833873768,
+           1.126243602124132,
+           1.0753404211628135,
+           1.0242849549575286,
+           0.9750732898467406,
+           0.9297067713179614,
+           0.8901429027861613,
+           0.8582465126365997,
+           0.835742398370973,
+           0.8241706293002751,
+           0.8248456324398455,
+           0.8388201013895351,
+           0.8668546570319865,
+           0.9093940545121243,
+           0.9665505764139211,
+           1.0380950810752811,
+           1.1234559917411278,
+           1.22172632122268,
+           1.3316786325827297,
+           1.4517876438636066,
+           1.5802599987458017,
+           1.7150705498518435,
+           1.854004341510605,
+           1.9947033381221488,
+           2.1347168262957616,
+           2.2715543266044707,
+           2.402739786412699,
+           2.5258657904111006,
+           2.638646521132212,
+           2.7389682279729346,
+           2.824936019517114,
+           2.8949158788969123,
+           2.947570913516962,
+           2.981890985996978
+          ],
+          [
+           2.9951443799079214,
+           2.9984236393354355,
+           2.982404327068349,
+           2.9473913415403885,
+           2.8940522109154307,
+           2.8234018852476996,
+           2.736779746720657,
+           2.635819385195549,
+           2.5224118571031915,
+           2.3986632990443164,
+           2.266847899610916,
+           2.129357340710969,
+           1.9886479004782418,
+           1.847186461747021,
+           1.7073966918479953,
+           1.571606650654809,
+           1.441999044650589,
+           1.3205652763030744,
+           1.2090643419666485,
+           1.1089875102752238,
+           1.0215295695715143,
+           0.9475672708955344,
+           0.8876454164389236,
+           0.8419708565244445,
+           0.8104144656979845,
+           0.7925209751593341,
+           0.7875263492563519,
+           0.7943822127683914,
+           0.8117866676332413,
+           0.8382206867230236,
+           0.8719891419148754,
+           0.9112654171787838,
+           0.9541384772680542,
+           0.9986612107391083,
+           1.04289884363347,
+           1.0849762276796766,
+           1.1231228440268992,
+           1.155714429281044,
+           1.181310223245167,
+           1.1986849548723986,
+           1.206854821520639,
+           1.2050968731253962,
+           1.1929613834122226,
+           1.1702769704449465,
+           1.137148414109823,
+           1.093947303909493,
+           1.0412958320224293,
+           0.9800442194253349,
+           0.9112424226569972,
+           0.8361069115362386,
+           0.7559834302818527,
+           0.6723067529888805,
+           0.5865585168608761,
+           0.5002242612072699,
+           0.4147508159152704,
+           0.3315051695515813,
+           0.2517359048308443,
+           0.1765382190211955,
+           0.10682345075561187,
+           0.043293915145402206,
+           -0.013576290897090991,
+           -0.06355400805940455,
+           -0.10665292338759955,
+           -0.1431325112872156,
+           -0.17349003192390444,
+           -0.19844579384807357,
+           -0.21892206411577728,
+           -0.2360161759241146,
+           -0.2509685365837354,
+           -0.265126373623173,
+           -0.2799041705160543,
+           -0.2967418330327395,
+           -0.3170616902392608,
+           -0.3422254690600145,
+           -0.3734923871542396,
+           -0.41197948542784285,
+           -0.45862526934528725,
+           -0.5141576485779329,
+           -0.5790670593744984,
+           -0.653585525959639,
+           -0.7376722694313119,
+           -0.8310063087114898,
+           -0.9329863221923931,
+           -1.0427378552051993,
+           -1.1591277719121051,
+           -1.280785665362794,
+           -1.4061317609076993,
+           -1.533410680419834,
+           -1.6607302820814343,
+           -1.786104656711469,
+           -1.907500250152644,
+           -2.0228839949603494,
+           -2.130272275778735,
+           -2.227779522911102,
+           -2.313665228536377,
+           -2.3863782098941013,
+           -2.4445970029184347,
+           -2.4872653568794276,
+           -2.5136219135246516,
+           -2.5232232902981764,
+           -2.5159599431594626,
+           -2.492064356546529,
+           -2.452111291934408,
+           -2.3970100177381606,
+           -2.3279886373143173,
+           -2.2465708237650928,
+           -2.1545454554263923,
+           -2.0539298197629874,
+           -1.9469272116124172,
+           -1.8358798904007947,
+           -1.7232184766609928,
+           -1.6114089580380933,
+           -1.502898536721493,
+           -1.400061582337699,
+           -1.305146955938731,
+           -1.220227941741599,
+           -1.1471559643781966,
+           -1.0875191819993968,
+           -1.042606931740025,
+           -1.0133808665390927,
+           -1.000453464450276,
+           -1.0040744171990084,
+           -1.024125218078338,
+           -1.0601220748614946,
+           -1.111227075970434,
+           -1.176267342476397,
+           -1.2537617093763322,
+           -1.3419543015827258,
+           -1.4388542075047897,
+           -1.542280309926735,
+           -1.64991021356801,
+           -1.7593321141425229,
+           -1.8680983871882193,
+           -1.973779637995128,
+           -2.074017947472783,
+           -2.1665780728727704,
+           -2.249395416275812,
+           -2.320619656288824,
+           -2.378653047401351,
+           -2.4221825242011255,
+           -2.4502049008451716,
+           -2.4620446260290927,
+           -2.4573637359927694,
+           -2.43616383834775,
+           -2.3987801530245094,
+           -2.3458678286595323,
+           -2.2783809385625733,
+           -2.197544735475283,
+           -2.1048219043807457,
+           -2.0018736937561834,
+           -1.8905169244610693,
+           -1.7726779690626266,
+           -1.6503448605924727,
+           -1.5255187269581394,
+           -1.4001657546785502,
+           -1.2761708631912672,
+           -1.155294219350089,
+           -1.0391316422779902,
+           -0.9290798435331626,
+           -0.826307319292813,
+           -0.731731563234965,
+           -0.6460031047633266,
+           -0.5694967013251099,
+           -0.5023098302551025,
+           -0.44426843945567335,
+           -0.39493973196664683,
+           -0.35365158171066496,
+           -0.3195180108671038,
+           -0.29147000759693853,
+           -0.26829082999334664,
+           -0.2486548314693101,
+           -0.23116875705369136,
+           -0.21441440136134896,
+           -0.19699148875912142,
+           -0.1775596351794852,
+           -0.154878279114754,
+           -0.12784352580122546,
+           -0.09552093200560255,
+           -0.057173367009648195,
+           -0.012283215585646684,
+           0.03943166235559136,
+           0.098008636970539,
+           0.1632379255379886,
+           0.2346671875221459,
+           0.3116129812525024,
+           0.39317878620057084,
+           0.47827912268898937,
+           0.5656691405827818,
+           0.6539789041639434,
+           0.7417514756574874,
+           0.827483797946331,
+           0.90966930049925,
+           0.98684110341741,
+           1.057614674070329,
+           1.1207287996107131,
+           1.175083776562955,
+           1.2197757847742081,
+           1.2541265056921205,
+           1.2777071619108842,
+           1.290356293315179,
+           1.2921907415149088,
+           1.283609484710645,
+           1.2652901454081615,
+           1.2381781790035873,
+           1.2034689375394743,
+           1.1625829852108742,
+           1.1171352158941312,
+           1.0688984836987963,
+           1.0197626012384482,
+           0.9716896833291111,
+           0.9266669130113523,
+           0.8866578795980015,
+           0.8535536829685912,
+           0.829125013358535,
+           0.8149764009504765,
+           0.8125037849355533,
+           0.8228564783798186,
+           0.8469045049258562,
+           0.8852121584745869,
+           0.9380184905341509,
+           1.0052252654389495,
+           1.0863927451331608,
+           1.18074347703506,
+           1.2871740652547037,
+           1.4042747118655468,
+           1.5303561257851095,
+           1.6634832167553064,
+           1.8015148253687059,
+           1.9421485911762755,
+           2.0829699333220164,
+           2.2215040150480347,
+           2.355269487370934,
+           2.481832760156405,
+           2.598861531914149,
+           2.704176323361822,
+           2.7957988038744723,
+           2.8719957733124604,
+           2.931317762652019,
+           2.9726313428996782,
+           2.995144379907921
+          ],
+          [
+           2.9999784020568754,
+           2.9911792865126894,
+           2.9632281622885337,
+           2.916659935782501,
+           2.8523638930531026,
+           2.7715637056635662,
+           2.675789958185559,
+           2.566845848166663,
+           2.4467668703666585,
+           2.317775438351261,
+           2.182231514679518,
+           2.042580413082396,
+           1.9012989999934593,
+           1.760841557038581,
+           1.6235865698307954,
+           1.4917856816072261,
+           1.3675159935951686,
+           1.2526368089423086,
+           1.1487518057249368,
+           1.0571774897326927,
+           0.9789186227662349,
+           0.9146511509121554,
+           0.8647129739085463,
+           0.8291027058055651,
+           0.807486383356385,
+           0.7992118867046678,
+           0.8033306516686214,
+           0.8186260787899506,
+           0.8436478855655872,
+           0.8767515087694364,
+           0.916141546875301,
+           0.9599181411191696,
+           1.0061251298625504,
+           1.052798776124035,
+           1.0980158631955172,
+           1.1399399781728046,
+           1.1768648572870528,
+           1.2072537486812132,
+           1.2297738556070168,
+           1.2433250531646245,
+           1.2470622213490055,
+           1.2404107025063504,
+           1.2230745681595119,
+           1.1950375640745017,
+           1.1565567887844372,
+           1.1081493448860218,
+           1.0505723796647866,
+           0.9847970975576349,
+           0.9119774774841459,
+           0.8334145594247007,
+           0.7505172735339793,
+           0.6647608688606504,
+           0.5776440553405945,
+           0.4906460007697313,
+           0.4051843232903132,
+           0.3225751896233147,
+           0.2439965706631867,
+           0.17045562064519934,
+           0.10276103609774921,
+           0.04150111901771984,
+           -0.012971881482160618,
+           -0.06055073958533456,
+           -0.10137530095612854,
+           -0.13582755554356116,
+           -0.1645198643351806,
+           -0.1882766485942041,
+           -0.2081100214820856,
+           -0.2251900011490098,
+           -0.24081008731746004,
+           -0.2563491064468598,
+           -0.27323033060702384,
+           -0.2928789496391676,
+           -0.3166790231222405,
+           -0.3459310568569931,
+           -0.3818113375203501,
+           -0.4253341190537824,
+           -0.4773176861873804,
+           -0.5383552259294038,
+           -0.6087913191985512,
+           -0.6887047249811173,
+           -0.7778979719311987,
+           -0.8758941011225314,
+           -0.9819407229802568,
+           -1.0950213657907975,
+           -1.2138739072612308,
+           -1.3370156990465965,
+           -1.4627748215549767,
+           -1.589326747032467,
+           -1.714735546957428,
+           -1.83699865874529,
+           -1.9540941297774062,
+           -2.064029186323108,
+           -2.1648889328709022,
+           -2.254883974867815,
+           -2.3323957752986484,
+           -2.3960186025887213,
+           -2.444597002918435,
+           -2.4772578324177497,
+           -2.493436011418087,
+           -2.492893310924424,
+           -2.4757296471440076,
+           -2.442386539237619,
+           -2.393642574065671,
+           -2.3306009149676776,
+           -2.254669084798162,
+           -2.1675314417964704,
+           -2.071114945753482,
+           -1.967548976941325,
+           -1.8591201173135437,
+           -1.748222928918278,
+           -1.6373078651777675,
+           -1.5288275241581224,
+           -1.4251824973344915,
+           -1.3286680815107785,
+           -1.2414231050829632,
+           -1.1653820730946578,
+           -1.102231759619874,
+           -1.0533732727337755,
+           -1.019890489182722,
+           -1.0025256059364247,
+           -1.001662387729057,
+           -1.0173175075504555,
+           -1.0491401852566562,
+           -1.096420132691845,
+           -1.1581036167345908,
+           -1.2328172592885163,
+           -1.318899010106629,
+           -1.41443555891731,
+           -1.5173053017189397,
+           -1.6252258460017863,
+           -1.735804934184504,
+           -1.846593586256777,
+           -1.9551402133709193,
+           -2.059044435081325,
+           -2.156009344508417,
+           -2.243891007568867,
+           -2.320744053490009,
+           -2.384862312321978,
+           -2.4348135786146807,
+           -2.469467725767339,
+           -2.4880175591828584,
+           -2.4899919742212164,
+           -2.4752611726556553,
+           -2.444033884269141,
+           -2.3968467336426915,
+           -2.3345460813353847,
+           -2.258262848906763,
+           -2.169381004183103,
+           -2.0695005327544624,
+           -1.9603958502817145,
+           -1.84397071469085,
+           -1.7222107752369322,
+           -1.597134944897367,
+           -1.4707468024765173,
+           -1.344987220778999,
+           -1.221689377588879,
+           -1.1025372380609901,
+           -0.9890285022800148,
+           -0.8824428926227347,
+           -0.7838165152182195,
+           -0.693922871809555,
+           -0.6132609266813102,
+           -0.5420504523624973,
+           -0.4802346921023458,
+           -0.4274901913119339,
+           -0.38324346892730776,
+           -0.34669402751511275,
+           -0.31684304220933307,
+           -0.29252692719328266,
+           -0.2724548579390681,
+           -0.2552492307724638,
+           -0.239487970926652,
+           -0.22374755780378797,
+           -0.2066456226944689,
+           -0.18688198999839203,
+           -0.16327707759539378,
+           -0.1348066442612327,
+           -0.10063197003943113,
+           -0.060124676754537344,
+           -0.012885537285186542,
+           0.04124321979661454,
+           0.10217243308984726,
+           0.16956750287651118,
+           0.2428568190366747,
+           0.32124690270176776,
+           0.4037438661364567,
+           0.48918062953720787,
+           0.5762491818911636,
+           0.6635370396102809,
+           0.7495669447460452,
+           0.8328387570628747,
+           0.9118724333554289,
+           0.9852509547189571,
+           1.0516620588967094,
+           1.1099376604772742,
+           1.1590898960048692,
+           1.198342812683506,
+           1.2271588262993223,
+           1.2452592036120793,
+           1.252637973561228,
+           1.249568836483922,
+           1.2366048170399897,
+           1.2145705902706068,
+           1.1845475965817907,
+           1.147852245764431,
+           1.1060076878044338,
+           1.0607097947221198,
+           1.0137881488007718,
+           0.9671629644862263,
+           0.9227989805995621,
+           0.8826574434947958,
+           0.8486473582308305,
+           0.8225772122104624,
+           0.8061083732872772,
+           0.8007113320119248,
+           0.8076258961830519,
+           0.8278263566115364,
+           0.8619925281174117,
+           0.9104874320153188,
+           0.9733422290371095,
+           1.050248838611252,
+           1.1405604958866584,
+           1.243300306365396,
+           1.3571776641882551,
+           1.4806122087590377,
+           1.611764810205917,
+           1.7485749017013477,
+           1.8888033201557477,
+           2.0300796801380216,
+           2.1699531924502136,
+           2.30594575141965,
+           2.4356060558592896,
+           2.55656349928391,
+           2.6665805661259125,
+           2.763602502391911,
+           2.845803090711619,
+           2.911625449595562,
+           2.9598168927810913,
+           2.989457024008576,
+           2.9999784020568754
+          ],
+          [
+           2.99635215442904,
+           2.9755432614201176,
+           2.935879267462139,
+           2.878120573487107,
+           2.803370719875939,
+           2.7130517751325014,
+           2.60887261306241,
+           2.492790827328148,
+           2.3669691820888357,
+           2.233727625473088,
+           2.0954919957817877,
+           1.9547406260906552,
+           1.8139500995086772,
+           1.6755414236527293,
+           1.5418278785690165,
+           1.4149657477671378,
+           1.296909068372378,
+           1.1893694354979074,
+           1.09378177030844,
+           1.0112768140112611,
+           0.942660944815683,
+           0.8884037358295905,
+           0.8486334833273862,
+           0.8231407414679582,
+           0.8113897061147656,
+           0.8125371016559896,
+           0.8254580452596761,
+           0.8487781972072231,
+           0.8809113578624806,
+           0.9201015450415457,
+           0.9644684831048123,
+           1.0120553594442345,
+           1.0608776569630791,
+           1.1089718537096134,
+           1.1544427933603694,
+           1.1955085723396148,
+           1.2305418598636386,
+           1.2581066642632999,
+           1.2769896800618281,
+           1.2862254923705945,
+           1.2851150746023636,
+           1.2732371882540423,
+           1.250452475220992,
+           1.2169002192002703,
+           1.1729879385484532,
+           1.1193741538257265,
+           1.0569448446589014,
+           0.986784268214823,
+           0.9101409515669345,
+           0.8283897890855887,
+           0.7429912707469982,
+           0.6554489356049484,
+           0.5672661849383184,
+           0.4799036008182364,
+           0.3947378978038594,
+           0.31302358868383606,
+           0.23585837086207032,
+           0.1641531400634221,
+           0.09860741507161262,
+           0.039690814350236046,
+           -0.01236893372056366,
+           -0.05759113658580744,
+           -0.09624030801034625,
+           -0.12881741458424764,
+           -0.15604443064905918,
+           -0.17884260927668558,
+           -0.19830504177255745,
+           -0.21566422844275812,
+           -0.2322555152363666,
+           -0.2494773609867009,
+           -0.2687494855119025,
+           -0.2914700075969383,
+           -0.3189727123386872,
+           -0.35248558867755403,
+           -0.3930917500793629,
+           -0.44169379492117394,
+           -0.49898257954421266,
+           -0.5654112682216885,
+           -0.6411753931388069,
+           -0.7261995071545134,
+           -0.8201308463540559,
+           -0.9223402423469034,
+           -1.031930340345023,
+           -1.1477509928820158,
+           -1.2684215152791314,
+           -1.3923593122541225,
+           -1.5178142198607203,
+           -1.642907757419506,
+           -1.7656763540521736,
+           -1.8841175071791059,
+           -1.9962377486425906,
+           -2.1001012401015413,
+           -2.193877794450149,
+           -2.2758891249629993,
+           -2.3446521586425666,
+           -2.3989183140799235,
+           -2.4377077355513057,
+           -2.460337591888732,
+           -2.4664436880748797,
+           -2.4559947961470203,
+           -2.4292992859948734,
+           -2.3870038217572547,
+           -2.3300840812327395,
+           -2.259827649318743,
+           -2.177809427223368,
+           -2.0858600823592526,
+           -1.9860282349094462,
+           -1.88053723182334,
+           -1.7717374936210382,
+           -1.6620555305120228,
+           -1.553940809196033,
+           -1.4498117081794089,
+           -1.3520018260724773,
+           -1.2627079034272701,
+           -1.1839405842730815,
+           -1.117479179401465,
+           -1.0648315011633376,
+           -1.027199721281741,
+           -1.0054530618062374,
+           -1.000107968258656,
+           -1.0113162371493822,
+           -1.0388613816716175,
+           -1.082163324084112,
+           -1.1402913058175836,
+           -1.2119847114868416,
+           -1.2956813154961317,
+           -1.3895522843449721,
+           -1.491543108338937,
+           -1.5994194970500475,
+           -1.7108171569277333,
+           -1.823294279731914,
+           -1.9343855090984596,
+           -2.0416561210121316,
+           -2.1427551529786513,
+           -2.2354662462323205,
+           -2.3177550246168206,
+           -2.387811921334136,
+           -2.4440894783784044,
+           -2.485333280330229,
+           -2.510605840888272,
+           -2.51930293318293,
+           -2.511162039289828,
+           -2.486262785896288,
+           -2.44501942706199,
+           -2.388165626694005,
+           -2.3167319780307887,
+           -2.232016870586096,
+           -2.135551472422016,
+           -2.0290597334772316,
+           -1.914414430640641,
+           -1.793590364572435,
+           -1.6686158798161665,
+           -1.541523912089481,
+           -1.414303769087403,
+           -1.2888548237221609,
+           -1.1669432422397537,
+           -1.0501627855971347,
+           -0.9399006130388091,
+           -0.8373088847861835,
+           -0.7432828095122169,
+           -0.6584456156526559,
+           -0.5831407478136721,
+           -0.5174314050529655,
+           -0.46110735127432745,
+           -0.41369874406270873,
+           -0.3744965516011213,
+           -0.34257896226612683,
+           -0.3168430422093329,
+           -0.29604076641015353,
+           -0.27881844154837504,
+           -0.26375845723767655,
+           -0.2494222476877253,
+           -0.23439332003849378,
+           -0.21731920903037122,
+           -0.19695125019646054,
+           -0.17218112451682208,
+           -0.142073214876997,
+           -0.10589192647486477,
+           -0.06312325665831353,
+           -0.013490051149037422,
+           0.04303945064194758,
+           0.10625000268867434,
+           0.17568471188745366,
+           0.25065722773224847,
+           0.33027044104823394,
+           0.4134412001301822,
+           0.49893039457518523,
+           0.5853776155781206,
+           0.6713394800783935,
+           0.7553306080070699,
+           0.8358661695003792,
+           0.9115048741881095,
+           0.9808912587084349,
+           1.0427961418954594,
+           1.0961541593478867,
+           1.1400973593028567,
+           1.1739839381901434,
+           1.1974213145487047,
+           1.2102828811666861,
+           1.2127179338454968,
+           1.2051544471344544,
+           1.1882945484375271,
+           1.1631027275242145,
+           1.1307870040255137,
+           1.0927734562989033,
+           1.0506746865482655,
+           1.0062529549536436,
+           0.9613788558010075,
+           0.9179865276346785,
+           0.8780264842372691,
+           0.8434172213236939,
+           0.8159967934271716,
+           0.7974755654714009,
+           0.7893913236129777,
+           0.7930678804935548,
+           0.8095782321888862,
+           0.8397132197162627,
+           0.8839565194605924,
+           0.9424666374028362,
+           1.015066415209091,
+           1.101240376128392,
+           1.2001400496532129,
+           1.310597220648713,
+           1.431144855899366,
+           1.560045273496372,
+           1.695324942817979,
+           1.8348151394248546,
+           1.976197534048576,
+           2.117053671593955,
+           2.2549171977741413,
+           2.3873276201105815,
+           2.5118843483474134,
+           2.62629974792615,
+           2.728449959373747,
+           2.816422285857232,
+           2.888558029590536,
+           2.9434897633724306,
+           2.980172153747234,
+           2.9979056039677654,
+           2.99635215442904
+          ],
+          [
+           2.9842963167202434,
+           2.951647851905386,
+           2.900589026614912,
+           2.832099315098488,
+           2.7474871957986804,
+           2.648361131063748,
+           2.536593862371396,
+           2.4142808616665765,
+           2.283693916821419,
+           2.147230942938814,
+           2.007363198497679,
+           1.866581144081653,
+           1.7273402102478244,
+           1.592007739316661,
+           1.4628123335869632,
+           1.3417967805362465,
+           1.2307756355196002,
+           1.1312984265780237,
+           1.0446193070910068,
+           0.971673823597825,
+           0.9130632920821069,
+           0.8690470906565287,
+           0.8395429844618119,
+           0.8241354044277398,
+           0.8220914100963161,
+           0.832383882665083,
+           0.853721322266976,
+           0.8845834674544095,
+           0.9232618186863761,
+           0.9679040346163744,
+           1.0165610828547205,
+           1.0672359676945884,
+           1.1179328274145692,
+           1.166705193840862,
+           1.2117022367653552,
+           1.2512118747283814,
+           1.283699720025738,
+           1.307842937350273,
+           1.3225582293693088,
+           1.3270233153619562,
+           1.3206914369230773,
+           1.303298603444892,
+           1.274863475114279,
+           1.2356799678669244,
+           1.1863028484396876,
+           1.127526763765693,
+           1.0603593130673499,
+           0.9859889190339345,
+           0.9057483827456603,
+           0.8210751123497061,
+           0.7334690953100426,
+           0.6444497363908155,
+           0.555512707133691,
+           0.4680879469173664,
+           0.3834999209425863,
+           0.3029311775992421,
+           0.22739015828039008,
+           0.15768409911349057,
+           0.09439772919061817,
+           0.037878317139609936,
+           -0.011772548823200203,
+           -0.05470023864143481,
+           -0.09129138891418483,
+           -0.12216139737391582,
+           -0.14813543686970235,
+           -0.1702234921370957,
+           -0.18959007955233934,
+           -0.20751945015291579,
+           -0.22537719589124905,
+           -0.24456927531878947,
+           -0.26649954520780067,
+           -0.2925269271932825,
+           -0.32392335223992347,
+           -0.36183361021653576,
+           -0.4072381874365837,
+           -0.4609201027693418,
+           -0.5234366546145091,
+           -0.5950968690939958,
+           -0.6759452972757701,
+           -0.7657526496560577,
+           -0.8640135834716726,
+           -0.9699517770127288,
+           -1.0825322395032255,
+           -1.2004806199732339,
+           -1.3223090985189014,
+           -1.4463482729743664,
+           -1.5707842976096522,
+           -1.6937003919873928,
+           -1.8131217210866721,
+           -1.927062555233644,
+           -2.033574552662394,
+           -2.1307949703978926,
+           -2.216993601629905,
+           -2.2906172601219117,
+           -2.3503306840189655,
+           -2.3950528114963574,
+           -2.4239874871364018,
+           -2.436647788183746,
+           -2.4328733107646787,
+           -2.4128399240977503,
+           -2.37706168157736,
+           -2.3263847669562847,
+           -2.2619735470455273,
+           -2.185288994644014,
+           -2.0980599320724105,
+           -2.002247722110989,
+           -1.900005194970202,
+           -1.793630743145994,
+           -1.6855186370724273,
+           -1.578106710363738,
+           -1.4738226317334182,
+           -1.3750300196601966,
+           -1.2839756645289586,
+           -1.2027391010410815,
+           -1.1331857216462737,
+           -1.0769245408189714,
+           -1.0352716121189394,
+           -1.0092199677322444,
+           -0.9994167967791868,
+           -1.006148407814534,
+           -1.029333336776739,
+           -1.0685237686387155,
+           -1.1229152438630832,
+           -1.1913644242621346,
+           -1.2724145017841086,
+           -1.3643276527374173,
+           -1.4651237734203344,
+           -1.5726245850879343,
+           -1.6845020702485145,
+           -1.7983301014836324,
+           -1.9116380507575281,
+           -2.0219651232740317,
+           -2.126914146384317,
+           -2.224203561134164,
+           -2.3117164113012505,
+           -2.387545201008556,
+           -2.450031595297675,
+           -2.497800065832667,
+           -2.5297847330110574,
+           -2.545248822494792,
+           -2.5437963344245538,
+           -2.5253757129048826,
+           -2.490275497088365,
+           -2.4391121285883064,
+           -2.372810278271482,
+           -2.292576234120674,
+           -2.1998650564536075,
+           -2.0963423533387577,
+           -1.9838416540106085,
+           -1.8643184584499555,
+           -1.7398021146651934,
+           -1.6123467198675552,
+           -1.483982256670648,
+           -1.3566671603940323,
+           -1.2322434689873358,
+           -1.1123956342218528,
+           -0.9986139735260767,
+           -0.8921636187279772,
+           -0.7940596741531777,
+           -0.7050491356667892,
+           -0.6255999484049964,
+           -0.5558973985031687,
+           -0.49584784767699924,
+           -0.4450896337296728,
+           -0.40301077959242754,
+           -0.3687729828666921,
+           -0.3413412012778021,
+           -0.3195180108671035,
+           -0.3019817965777461,
+           -0.2873277420243784,
+           -0.2741105189585838,
+           -0.260887538860201,
+           -0.2462616200996984,
+           -0.22892194439657365,
+           -0.2076822252760229,
+           -0.1815150876129564,
+           -0.1495817591729483,
+           -0.11125629970030229,
+           -0.06614373737811796,
+           -0.014091642716365505,
+           0.04480515796583522,
+           0.11020684768309287,
+           0.18153779821451477,
+           0.2580024186215775,
+           0.33860725307429224,
+           0.42218874434806664,
+           0.5074459303788812,
+           0.5929772109639977,
+           0.6773202133912765,
+           0.7589937022412859,
+           0.836540421979703,
+           0.9085697327141701,
+           0.9737989003868774,
+           1.0310919327362833,
+           1.079494910879211,
+           1.118266851911637,
+           1.1469052483948505,
+           1.1651655632460551,
+           1.1730741100895588,
+           1.1709339157680037,
+           1.1593233392981428,
+           1.1390874056362803,
+           1.1113219985772926,
+           1.0773512402747278,
+           1.0386985606252068,
+           0.9970521236714649,
+           0.9542254260951448,
+           0.9121140110337564,
+           0.8726493455921603,
+           0.8377509898212431,
+           0.8092782365340166,
+           0.7889824237398131,
+           0.7784611140414441,
+           0.779115298140432,
+           0.7921107134539138,
+           0.818344275307005,
+           0.8584164994532649,
+           0.9126106536498161,
+           0.980879216088805,
+           1.0628380435546707,
+           1.1577684665090404,
+           1.2646273364479037,
+           1.3820648575379733,
+           1.508449844475625,
+           1.6419018664060003,
+           1.7803295670880068,
+           1.9214742984905344,
+           2.0629580724513246,
+           2.2023347262201787,
+           2.3371431153621094,
+           2.4649610936859885,
+           2.5834590159645354,
+           2.690451505863598,
+           2.7839462685945557,
+           2.8621887944884428,
+           2.9237018943814763,
+           2.967319128129748,
+           2.9922113308318132,
+           2.997905603967766,
+           2.9842963167202434
+          ],
+          [
+           2.96391288677283,
+           2.9196952239457854,
+           2.8576560111534373,
+           2.778985521287467,
+           2.685186120722606,
+           2.578039085578977,
+           2.45956521704987,
+           2.33198018101761,
+           2.1976456209910586,
+           2.059017191822874,
+           1.9185907323309515,
+           1.7788478361658069,
+           1.64220209106547,
+           1.5109472367992822,
+           1.3872084421501252,
+           1.2728978224866614,
+           1.1696752138044895,
+           1.0789150891955508,
+           1.0016803527577247,
+           0.9387035777118394,
+           0.8903760741007226,
+           0.8567449813701158,
+           0.8375183870457237,
+           0.8320782793861798,
+           0.839500954042777,
+           0.85858431698384,
+           0.8878813625777604,
+           0.9257389607431493,
+           0.9703409639749017,
+           1.0197545468012468,
+           1.0719786191589706,
+           1.1249931129549233,
+           1.176807928657242,
+           1.225510346335636,
+           1.2693097526090744,
+           1.3065786101948633,
+           1.3358886982221736,
+           1.3560417765658959,
+           1.3660939729823136,
+           1.3653733540949773,
+           1.3534903161874257,
+           1.33034061490344,
+           1.296101039734172,
+           1.2512179249028104,
+           1.1963888682953947,
+           1.1325381999367308,
+           1.060786896942332,
+           0.9824177790289396,
+           0.8988369341402109,
+           0.8115324146921674,
+           0.7220313091361424,
+           0.6318563294207978,
+           0.5424830616674488,
+           0.4552990048457669,
+           0.37156547107598253,
+           0.2923833427341765,
+           0.2186635778284968,
+           0.15110322880911564,
+           0.09016759430222367,
+           0.03607896193240777,
+           -0.011187772476169184,
+           -0.05190250405697233,
+           -0.08657041376260924,
+           -0.11591581683004726,
+           -0.14085979666334394,
+           -0.16249221880663034,
+           -0.18203886734537983,
+           -0.2008245747893691,
+           -0.2202333229762421,
+           -0.2416663740688101,
+           -0.2664995452078006,
+           -0.2960407664101534,
+           -0.33148905817219476,
+           -0.3738960329816908,
+           -0.42413096433063446,
+           -0.4828503793338868,
+           -0.5504730188575799,
+           -0.627160874930058,
+           -0.7128068624868812,
+           -0.8070295150021863,
+           -0.9091749154708687,
+           -1.01832588999227,
+           -1.133318305490366,
+           -1.2527641305588322,
+           -1.3750807436419232,
+           -1.498525810169351,
+           -1.6212369039747827,
+           -1.7412749220637538,
+           -1.856670238786538,
+           -1.9654704683695075,
+           -2.0657886555797114,
+           -2.155850694364783,
+           -2.234040784221408,
+           -2.29894377365655,
+           -2.349383308533598,
+           -2.38445479873904,
+           -2.4035523371837972,
+           -2.406388847761895,
+           -2.393008900070298,
+           -2.3637938045219533,
+           -2.3194587876626254,
+           -2.2610422394687606,
+           -2.189887217443627,
+           -2.107615581691166,
+           -2.0160953161613238,
+           -1.9174017594544048,
+           -1.8137736197795042,
+           -1.7075647791291317,
+           -1.601192998208592,
+           -1.4970867134791528,
+           -1.3976311688251455,
+           -1.3051151455244583,
+           -1.2216795448127826,
+           -1.1492690375565924,
+           -1.089587926307201,
+           -1.0440612679407688,
+           -1.0138021825239973,
+           -0.9995861289362459,
+           -1.0018327636351405,
+           -1.020595819752086,
+           -1.0555612537954495,
+           -1.1060537112356243,
+           -1.1710511649117865,
+           -1.249207386332607,
+           -1.338881724255685,
+           -1.4381754919364897,
+           -1.544974108338649,
+           -1.6569940031812194,
+           -1.771833184244778,
+           -1.887024280558482,
+           -2.0000888189824573,
+           -2.1085914656173403,
+           -2.21019296801313,
+           -2.3027005691590428,
+           -2.3841147288151316,
+           -2.4526710802713847,
+           -2.5068766687841713,
+           -2.5455396588105845,
+           -2.5677918572529737,
+           -2.57310357528638,
+           -2.561290537649834,
+           -2.532512740955837,
+           -2.4872653568794285,
+           -2.4263619672662595,
+           -2.3509106015711514,
+           -2.2622832181291197,
+           -2.1620794254057194,
+           -2.0520853738231026,
+           -1.9342288597682962,
+           -1.810531768303078,
+           -1.6830610379028026,
+           -1.5538793579463495,
+           -1.4249968070836074,
+           -1.2983246081868138,
+           -1.175632114252511,
+           -1.0585080509820828,
+           -0.9483269281240411,
+           -0.8462213959206247,
+           -0.7530611686161635,
+           -0.6694389678636032,
+           -0.5956637592743258,
+           -0.5317613698127232,
+           -0.4774823868966704,
+           -0.43231705660690956,
+           -0.3955167229168676,
+           -0.3661211867054577,
+           -0.34299121656819304,
+           -0.324845316737363,
+           -0.3102997538924956,
+           -0.29791076683454876,
+           -0.2862178328086653,
+           -0.2737868428926565,
+           -0.259252046798417,
+           -0.2413556644015806,
+           -0.21898412633208442,
+           -0.191199997332337,
+           -0.1572687514666878,
+           -0.11667970469084991,
+           -0.06916056428027795,
+           -0.014685222250287904,
+           0.0465254030853257,
+           0.11400949137395727,
+           0.18707724209881585,
+           0.2648302480660013,
+           0.34618680557775183,
+           0.42991249060771786,
+           0.5146551916620727,
+           0.5989836720329744,
+           0.6814286398387902,
+           0.7605252360139027,
+           0.8348558100197686,
+           0.9030918415586466,
+           0.9640338843150138,
+           1.016648454324882,
+           1.0601008598516877,
+           1.093783069802157,
+           1.1173358412665422,
+           1.1306644706432878,
+           1.133947693421171,
+           1.1276394310291689,
+           1.1124632648860955,
+           1.0893997033308338,
+           1.0596664918277794,
+           1.024692396070724,
+           0.9860850568299097,
+           0.9455936703204565,
+           0.9050673845834919,
+           0.8664104173783461,
+           0.8315349914340608,
+           0.802313246259112,
+           0.7805293203851517,
+           0.7678328029604514,
+           0.7656947287838268,
+           0.7753672366950923,
+           0.7978479289592796,
+           0.8338498608459496,
+           0.883777957612637,
+           0.9477125037436983,
+           1.025400180275652,
+           1.1162529444811369,
+           1.2193548565293242,
+           1.3334767646436174,
+           1.4570985684856186,
+           1.58843859473277,
+           1.7254894436713766,
+           1.866059505429644,
+           2.007819203198974,
+           2.1483509019495157,
+           2.285201327704437,
+           2.415935276743671,
+           2.5381893578298764,
+           2.649724504634708,
+           2.7484760201951026,
+           2.8325999698999653,
+           2.9005148229129434,
+           2.950937352085529,
+           2.982911936658756,
+           2.9958325671489043,
+           2.9894570240085776,
+           2.9639128867728304
+          ],
+          [
+           2.9353743176277622,
+           2.8799557112325815,
+           2.807443453815929,
+           2.7192285587839518,
+           2.616994589934415,
+           2.5026805950040796,
+           2.378438374293113,
+           2.246585086381021,
+           2.109552302117777,
+           1.9698327003768865,
+           1.8299256525153742,
+           1.6922829658278584,
+           1.5592560489753347,
+           1.4330457246321853,
+           1.3156558473912097,
+           1.2088517899806157,
+           1.1141247404430112,
+           1.0326626100884748,
+           0.9653281902923516,
+           0.9126450195527065,
+           0.8747912350017366,
+           0.8516014893816831,
+           0.8425768200894028,
+           0.8469021660269382,
+           0.8634710453344526,
+           0.8909167370820925,
+           0.9276491567934059,
+           0.9718964829771464,
+           1.02175048285536,
+           1.0752144028004542,
+           1.1302522345837078,
+           1.1848381436409305,
+           1.2370048506932974,
+           1.2848897929941951,
+           1.3267779552397916,
+           1.3611403511032807,
+           1.3866672520816217,
+           1.4022953979201815,
+           1.4072285788097285,
+           1.400951149888386,
+           1.3832342190351705,
+           1.3541344349760969,
+           1.313985489673879,
+           1.2633826321603994,
+           1.2031606658236198,
+           1.1343660633211325,
+           1.0582239787307814,
+           0.9761010616602394,
+           0.8894650797332551,
+           0.7998424316532754,
+           0.7087746810719863,
+           0.6177752606164432,
+           0.528287485236218,
+           0.4416449748404261,
+           0.35903551905031983,
+           0.28146932354454746,
+           0.20975246032583625,
+           0.1444662062909501,
+           0.08595279926174279,
+           0.03430797208789997,
+           -0.0106195521519808,
+           -0.04922160293299386,
+           -0.0821173241416674,
+           -0.1101335133902005,
+           -0.13427906523839453,
+           -0.15571419935610634,
+           -0.17571529182391216,
+           -0.19563624402715926,
+           -0.21686741598383577,
+           -0.24079321709491552,
+           -0.2687494855119025,
+           -0.301981796577746,
+           -0.3416058208397932,
+           -0.388570803418117,
+           -0.4436271602249229,
+           -0.5072990845515095,
+           -0.5798629323978344,
+           -0.6613320097313742,
+           -0.7514482232504056,
+           -0.8496808822340762,
+           -0.9552327570471953,
+           -1.067053314400184,
+           -1.1838588652072357,
+           -1.3041591824806977,
+           -1.4262899786510135,
+           -1.5484504782638024,
+           -1.6687451870761978,
+           -1.7852288455964225,
+           -1.8959534669861011,
+           -1.999016298261788,
+           -2.0926075115068143,
+           -2.1750564292396093,
+           -2.244875115345996,
+           -2.3007982194946206,
+           -2.341818047411763,
+           -2.3672139397915535,
+           -2.3765751763091005,
+           -2.3698167749514747,
+           -2.3471877269450623,
+           -2.309271389784863,
+           -2.256977950798795,
+           -2.1915290666450584,
+           -2.1144349753949054,
+           -2.027464562681399,
+           -1.9326090372301277,
+           -1.8320400296268107,
+           -1.7280630674836996,
+           -1.6230674967736294,
+           -1.5194740100921036,
+           -1.4196810056938773,
+           -1.3260110347244487,
+           -1.2406585972442234,
+           -1.1656405202860645,
+           -1.1027500939063613,
+           -1.0535160553326588,
+           -1.0191673989262073,
+           -1.000604853467912,
+           -0.9983797115293215,
+           -1.0126805222012591,
+           -1.0433279724287914,
+           -1.0897780881592674,
+           -1.1511336891654815,
+           -1.226163835556397,
+           -1.3133308143956464,
+           -1.4108240361227,
+           -1.516600046957196,
+           -1.6284277191338188,
+           -1.743937559164126,
+           -1.8606739782966502,
+           -1.9761493012627351,
+           -2.08789825088309,
+           -2.1935316380732943,
+           -2.2907880093834945,
+           -2.377582056845095,
+           -2.4520486762471836,
+           -2.5125816679969466,
+           -2.55786620674924,
+           -2.5869043587531526,
+           -2.5990330955864716,
+           -2.5939344354499996,
+           -2.5716375339832678,
+           -2.5325127409558372,
+           -2.47725783241775,
+           -2.4068768152301487,
+           -2.322651877767614,
+           -2.2261092226791606,
+           -2.1189796609792895,
+           -2.003154967948264,
+           -1.880641097439629,
+           -1.753509419937405,
+           -1.6238471894703017,
+           -1.4937084543911852,
+           -1.365066606923086,
+           -1.2397697168577269,
+           -1.1194997171956729,
+           -1.005736405859061,
+           -0.8997271005502763,
+           -0.8024626366107952,
+           -0.7146602340840197,
+           -0.6367535842360589,
+           -0.5688903219669695,
+           -0.5109368634667343,
+           -0.4624904028206459,
+           -0.4228976816881534,
+           -0.39127997714660395,
+           -0.3665635985128937,
+           -0.3475150482613024,
+           -0.33277988840181544,
+           -0.32092426467160085,
+           -0.31047797880011874,
+           -0.29997796543412736,
+           -0.2880110258359756,
+           -0.27325469524654333,
+           -0.2545151741478272,
+           -0.23076133416754224,
+           -0.20115391495626628,
+           -0.16506915632500682,
+           -0.12211625698616885,
+           -0.07214821364407147,
+           -0.015265767799349832,
+           0.04818563194828834,
+           0.11762576167492698,
+           0.19225617733846875,
+           0.271082949538792,
+           0.35294497211464665,
+           0.4365470925207441,
+           0.520497184812076,
+           0.6033461814064522,
+           0.6836300002741046,
+           0.7599122518561772,
+           0.8308265862000526,
+           0.8951175461594891,
+           0.951678826947532,
+           0.9995879050243648,
+           1.0381360887129176,
+           1.066853156850101,
+           1.0855258873698335,
+           1.0942099315957448,
+           1.0932346583514427,
+           1.08320077056086,
+           1.0649706813322632,
+           1.0396518219666337,
+           1.0085732362371589,
+           0.9732559890638666,
+           0.9353780789630025,
+           0.8967346882958054,
+           0.8591947296941406,
+           0.8246547479182134,
+           0.7949913112010145,
+           0.7720130728971737,
+           0.7574137017167515,
+           0.7527268664511928,
+           0.7592844190946837,
+           0.7781788495728039,
+           0.8102309875703577,
+           0.8559638045357024,
+           0.9155830247821606,
+           0.988965092206676,
+           1.0756528624603903,
+           1.1748592037561327,
+           1.2854784974615125,
+           1.4061058369230965,
+           1.5350635343438912,
+           1.6704343656483038,
+           1.810100816565025,
+           1.951789443771282,
+           2.093119336584826,
+           2.2316535605648973,
+           2.364952387100609,
+           2.4906270645796806,
+           2.6063928682914193,
+           2.7101201783383067,
+           2.7998823772730272,
+           2.8739994309608803,
+           2.931076115587536,
+           2.9700339784063314,
+           2.990136266743473,
+           2.9910052254006354,
+           2.9726313428996813,
+           2.935374317627763
+          ],
+          [
+           2.8989220584938575,
+           2.8327655280256647,
+           2.7503761755589045,
+           2.6533339985310564,
+           2.5434895346415973,
+           2.4229232262694254,
+           2.293899703901161,
+           2.1588180588991577,
+           2.0201592695419235,
+           1.8804320097549287,
+           1.7421181057475936,
+           1.6076189110419188,
+           1.4792038450270133,
+           1.3589622848591414,
+           1.2487599166397954,
+           1.1502005414342713,
+           1.0645941975766806,
+           0.9929323061595277,
+           0.9358703754388858,
+           0.8937186163140846,
+           0.8664406295761462,
+           0.8536601309609096,
+           0.8546754869603326,
+           0.8684816475611487,
+           0.8937988861524245,
+           0.9291075960552214,
+           0.9726882513797157,
+           1.0226655206317843,
+           1.0770554275349493,
+           1.1338143871363713,
+           1.1908889079733271,
+           1.2462647437128214,
+           1.2980143003228912,
+           1.3443411568283004,
+           1.3836206376585924,
+           1.4144354804360788,
+           1.4356057720608733,
+           1.446212474846469,
+           1.4456140294726307,
+           1.4334556984906341,
+           1.40967149858895,
+           1.3744787571782218,
+           1.3283655143941042,
+           1.2720711707116994,
+           1.2065609485530002,
+           1.1329948893675486,
+           1.052692241880502,
+           0.9670922092151206,
+           0.8777121096538878,
+           0.7861040657793167,
+           0.6938113681896895,
+           0.6023256621915929,
+           0.5130460788401785,
+           0.427241376173708,
+           0.3460160739296032,
+           0.27028145757134936,
+           0.20073219785880758,
+           0.13782918377278455,
+           0.08178900314243451,
+           0.032580330981553135,
+           -0.010072695251700316,
+           -0.046680216906129876,
+           -0.07796979520459857,
+           -0.1048634079579988,
+           -0.12844891856052404,
+           -0.1499467788971639,
+           -0.17067285329829857,
+           -0.19199835349228103,
+           -0.21530795201027614,
+           -0.2419571917002129,
+           -0.27323033060702373,
+           -0.31029975389249564,
+           -0.35418804785266345,
+           -0.40573376632751307,
+           -0.465561828480054,
+           -0.5340593713129038,
+           -0.6113577432676343,
+           -0.6973211702349101,
+           -0.7915424561688689,
+           -0.8933459014849819,
+           -1.0017974380195058,
+           -1.115721794176569,
+           -1.2337263226487662,
+           -1.3542309503430454,
+           -1.4755035502455531,
+           -1.5956998919744707,
+           -1.7129072053411165,
+           -1.8251902925029353,
+           -1.93063905179893,
+           -2.027416232009936,
+           -2.1138042207868897,
+           -2.188249685814636,
+           -2.2494049316597633,
+           -2.2961649081851876,
+           -2.3276989061858715,
+           -2.343476100122171,
+           -2.3432842435006176,
+           -2.3272409860375123,
+           -2.2957974592479298,
+           -2.249733964186829,
+           -2.190147787138638,
+           -2.1184333613823347,
+           -2.0362551810096248,
+           -1.9455140515042864,
+           -1.8483074269765523,
+           -1.7468847314891711,
+           -1.6435986881396776,
+           -1.540853781323672,
+           -1.441053052340693,
+           -1.3465444743222577,
+           -1.2595681681743003,
+           -1.182205706384864,
+           -1.1163327064542472,
+           -1.063575841403731,
+           -1.0252752930737994,
+           -1.002453547171754,
+           -0.9957912803263581,
+           -1.0056109223486434,
+           -1.031868295531407,
+           -1.0741525415465893,
+           -1.131694349966181,
+           -1.2033823054160777,
+           -1.2877869776644935,
+           -1.3831921952336563,
+           -1.487632772872491,
+           -1.598937810576546,
+           -1.7147785504953266,
+           -1.8327196712106306,
+           -1.9502728190855343,
+           -2.0649511255917017,
+           -2.174323438931325,
+           -2.27606700834705,
+           -2.368017399975745,
+           -2.448214492922238,
+           -2.5149435016616692,
+           -2.566770093503233,
+           -2.602568814628668,
+           -2.6215442015811155,
+           -2.6232441329984284,
+           -2.607565164482595,
+           -2.574749783153805,
+           -2.5253757129048835,
+           -2.4603375918887327,
+           -2.3808215256833307,
+           -2.2882731884514667,
+           -2.1843602961412225,
+           -2.070930406684232,
+           -1.949965109089204,
+           -1.8235317437426473,
+           -1.693733848223018,
+           -1.562661545320002,
+           -1.432343082273784,
+           -1.3046986928011666,
+           -1.181497887283806,
+           -1.0643211832961217,
+           -0.9545271708499705,
+           -0.8532256673377295,
+           -0.7612575597033141,
+           -0.6791817598395088,
+           -0.6072695179199498,
+           -0.5455061518776665,
+           -0.4936000642120855,
+           -0.4509987344181597,
+           -0.41691120114753255,
+           -0.390336387068002,
+           -0.3700964752849157,
+           -0.3548744226939494,
+           -0.343254595793745,
+           -0.3337654407462244,
+           -0.3249230536211313,
+           -0.3152744998864276,
+           -0.30343974466594165,
+           -0.28815109670193556,
+           -0.2682891382281142,
+           -0.24291420827486107,
+           -0.2112926258374467,
+           -0.1729169787930805,
+           -0.12751996089377277,
+           -0.0750814086039541,
+           -0.015828367685506373,
+           0.04977179826728035,
+           0.12102506330287478,
+           0.1970307877978511,
+           0.27670762235610996,
+           0.3588245755379695,
+           0.4420364183527696,
+           0.52492248392331,
+           0.6060278302810738,
+           0.6839056701918099,
+           0.757159935891462,
+           0.8244868395773143,
+           0.8847143126641839,
+           0.9368382576604884,
+           0.9800546248018008,
+           1.0137864293659078,
+           1.0377049523049675,
+           1.0517445133088585,
+           1.0561103679996355,
+           1.0512794555799223,
+           1.0379939055393628,
+           1.017247397384151,
+           0.9902646511311938,
+           0.9584745038676895,
+           0.9234771945326733,
+           0.8870066310024085,
+           0.8508885466943817,
+           0.8169955648450682,
+           0.787200274511647,
+           0.763327480963997,
+           0.7471068229130552,
+           0.7401269491226873,
+           0.7437924172704198,
+           0.7592844190946834,
+           0.7875263492563516,
+           0.8291551230079001,
+           0.8844990124059748,
+           0.9535626157016239,
+           1.036019403473344,
+           1.131212102212139,
+           1.2381609859065577,
+           1.3555799533820303,
+           1.481900078469827,
+           1.61530013622208,
+           1.7537434358967712,
+           1.895020134585183,
+           2.03679406804131,
+           2.1766530209208943,
+           2.312161270110701,
+           2.4409131743584362,
+           2.560586552546621,
+           2.668994592509673,
+           2.7641350623464436,
+           2.8442356560548507,
+           2.9077943936032553,
+           2.9536141101470506,
+           2.980830207243889,
+           2.9889309972823366,
+           2.977770147082594,
+           2.9475709135169663,
+           2.8989220584938584
+          ],
+          [
+           2.854864511978224,
+           2.7785239246287654,
+           2.6869369913796555,
+           2.581859338326148,
+           2.4652928408733454,
+           2.3394417628051287,
+           2.2066644412797154,
+           2.069421647339548,
+           1.9302228287698984,
+           1.7915714902539344,
+           1.655910983606633,
+           1.5255719680223971,
+           1.402722757089944,
+           1.2893236969037678,
+           1.1870866197407925,
+           1.0974402929503224,
+           1.021502636010972,
+           0.9600603137581153,
+           0.913556134640801,
+           0.8820844939316673,
+           0.8653949077245439,
+           0.8629034890684887,
+           0.8737120274620757,
+           0.8966341518102052,
+           0.9302278892398694,
+           0.9728337819547548,
+           1.0226175952160672,
+           1.077616544675253,
+           1.1357878931559084,
+           1.1950587174247227,
+           1.2533756256325446,
+           1.3087532163381337,
+           1.3593201099950682,
+           1.4033614523978686,
+           1.4393568850506067,
+           1.4660130972827812,
+           1.4822902161359715,
+           1.4874214490012598,
+           1.4809255666887993,
+           1.4626119967120703,
+           1.432578483500734,
+           1.3912014593380737,
+           1.3391194523786791,
+           1.2772100315889576,
+           1.2065609485530004,
+           1.1284362788280895,
+           1.044238487388386,
+           0.955467440661821,
+           0.8636774593472603,
+           0.770433549862266,
+           0.6772679668872126,
+           0.5856382447399437,
+           0.49688779167425573,
+           0.41221006980803593,
+           0.33261728611092006,
+           0.25891439922328235,
+           0.1916791059295972,
+           0.13124831346840962,
+           0.07771143354360742,
+           0.03091065523889344,
+           -0.009551828432159676,
+           -0.04429984725215792,
+           -0.07416291692298856,
+           -0.10015008801014848,
+           -0.12341868230879877,
+           -0.14523875241667322,
+           -0.16695421308019517,
+           -0.1899416813848238,
+           -0.21556812482644502,
+           -0.2451484501328368,
+           -0.27990417051605426,
+           -0.32092426467160085,
+           -0.36912928787675403,
+           -0.42523971527733617,
+           -0.4897493918770388,
+           -0.5629048354829002,
+           -0.6446909911154568,
+           -0.7348238718575252,
+           -0.8327503458889334,
+           -0.9376551469333942,
+           -1.0484750001160157,
+           -1.163919571959778,
+           -1.28249877655972,
+           -1.4025558043320263,
+           -1.5223050893404568,
+           -1.639874299880761,
+           -1.7533493281114767,
+           -1.8608211708597022,
+           -1.9604335374821018,
+           -2.0504299933233248,
+           -2.129199449667807,
+           -2.195318843169221,
+           -2.2475919088669305,
+           -2.285083039638526,
+           -2.307145339179678,
+           -2.313442112595991,
+           -2.3039611951142267,
+           -2.2790216914599846,
+           -2.2392728818979792,
+           -2.185685241289403,
+           -2.1195337101077123,
+           -2.0423735464232977,
+           -1.9560092707250452,
+           -1.8624573865674152,
+           -1.7639037151702563,
+           -1.662656317396943,
+           -1.5610950886172563,
+           -1.461619198014091,
+           -1.366593601742825,
+           -1.2782958875143549,
+           -1.1988647058914548,
+           -1.130251010853285,
+           -1.0741732697343875,
+           -1.0320777119514255,
+           -1.005104569158423,
+           -0.9940611194263556,
+           -0.9994021881062797,
+           -1.0212185820785205,
+           -1.0592337463806438,
+           -1.112808737302468,
+           -1.1809554086739784,
+           -1.2623575130511646,
+           -1.355399231569051,
+           -1.458200469952116,
+           -1.5686580978358056,
+           -1.6844921680560594,
+           -1.8032960353156575,
+           -1.922589202478456,
+           -2.039871659874422,
+           -2.1526784499282754,
+           -2.258633186928434,
+           -2.35549928985841,
+           -2.441227744198776,
+           -2.5140002950197173,
+           -2.572267086375352,
+           -2.6147778981899203,
+           -2.6406062881316332,
+           -2.649166118549442,
+           -2.6402201331567197,
+           -2.613880440248575,
+           -2.570600954125154,
+           -2.5111620392898284,
+           -2.436647788183747,
+           -2.3484165381655253,
+           -2.248065392890858,
+           -2.1373896533254215,
+           -2.018338180954416,
+           -1.8929658075205567,
+           -1.763383969651902,
+           -1.631710781545375,
+           -1.500021763688232,
+           -1.3703024204104062,
+           -1.244403804588111,
+           -1.124002125511548,
+           -1.0105633479192173,
+           -0.9053135992554309,
+           -0.8092160516535173,
+           -0.7229547787943285,
+           -0.6469259098289326,
+           -0.5812362174580014,
+           -0.525709089666829,
+           -0.479897649215462,
+           -0.4431046064039355,
+           -0.41440826331933434,
+           -0.39269393588010626,
+           -0.3766899272853872,
+           -0.3650070762282793,
+           -0.3561808181487568,
+           -0.3487146399560773,
+           -0.3411237794281299,
+           -0.3319780205623386,
+           -0.3199424654396782,
+           -0.3038152208675825,
+           -0.2825610226735329,
+           -0.25533992983985476,
+           -0.22153035189400488,
+           -0.18074582274164872,
+           -0.13284509863339955,
+           -0.07793533300327934,
+           -0.016368262059141287,
+           0.0512704823574946,
+           0.12417863662782673,
+           0.2013606781119408,
+           0.28165667924072746,
+           0.3637758717422082,
+           0.4463340259233072,
+           0.5278936489628229,
+           0.6070059306938999,
+           0.6822533172996603,
+           0.7522915739582556,
+           0.8158902072767497,
+           0.871970157135618,
+           0.9196377343854855,
+           0.9582138740467829,
+           0.9872578909470799,
+           1.0065850631669218,
+           1.0162775247944185,
+           1.0166881194032305,
+           1.008437045107001,
+           0.9924013064990982,
+           0.969697173618992,
+           0.9416560286377318,
+           0.909794152665152,
+           0.8757771636040395,
+           0.8413799572862022,
+           0.8084431246197475,
+           0.7788269140662362,
+           0.7543638789520088,
+           0.7368113910548602,
+           0.7278052144518286,
+           0.7288153163522496,
+           0.7411050449010858,
+           0.7656947287838257,
+           0.8033306516686215,
+           0.8544602285228365,
+           0.9192140636858556,
+           0.9973954058458877,
+           1.0884773367780667,
+           1.191607843221758,
+           1.3056227292110356,
+           1.4290661342525222,
+           1.560218235703038,
+           1.6971295361608227,
+           1.8376609730460858,
+           1.97952894187497,
+           2.120354200653375,
+           2.257713523438273,
+           2.3891928989340183,
+           2.51244102684507,
+           2.6252218517192656,
+           2.7254648915701476,
+           2.811312166298397,
+           2.881160607731991,
+           2.9336989371507416,
+           2.967938124958956,
+           2.983234697616886,
+           2.9793063254003775,
+           2.956239306946293,
+           2.9144877584329834,
+           2.854864511978225
+          ],
+          [
+           2.803574424860651,
+           2.717689809551228,
+           2.617662625482897,
+           2.5054092861372137,
+           2.383066088043347,
+           2.2529424955678925,
+           2.11747063622496,
+           1.9791521857963246,
+           1.8405038827873368,
+           1.7040029420787268,
+           1.5720336373549726,
+           1.4468362910339048,
+           1.3304598497761617,
+           1.2247191347319886,
+           1.1311577406934525,
+           1.0510174201052287,
+           0.9852146298558856,
+           0.9343247448147,
+           0.8985742564725578,
+           0.8778410823453104,
+           0.8716629167269886,
+           0.879253360712163,
+           0.8995253838478544,
+           0.931121495849007,
+           0.972449848746355,
+           1.0217253514616564,
+           1.0770147634603189,
+           1.1362846445785229,
+           1.1974509764823393,
+           1.258429238917892,
+           1.317183721654401,
+           1.371774880762101,
+           1.420403604818805,
+           1.461451341295391,
+           1.493515143541958,
+           1.5154368316657267,
+           1.526325612785089,
+           1.5255736738159291,
+           1.5128644388747314,
+           1.4881733690763659,
+           1.45176137031264,
+           1.4041610598282717,
+           1.346156320446042,
+           1.2787557377037917,
+           1.2031606658236198,
+           1.1207287996107138,
+           1.0329342378428046,
+           0.9413251068025694,
+           0.8474798683057183,
+           0.7529634635577718,
+           0.659284441825549,
+           0.5678541913642801,
+           0.4799493301595818,
+           0.3966782273970071,
+           0.3189525154022371,
+           0.24746431895762386,
+           0.18266977779249705,
+           0.12477927251847813,
+           0.07375458854918888,
+           0.029313071072240737,
+           -0.009061358462347116,
+           -0.04210063297548017,
+           -0.07072889720973186,
+           -0.09603343036620997,
+           -0.11923091455811617,
+           -0.14162995194906552,
+           -0.16459083254855103,
+           -0.1894836280814713,
+           -0.21764573325258796,
+           -0.25033999290238634,
+           -0.2887145415334167,
+           -0.33376544074622455,
+           -0.38630313126047294,
+           -0.4469236211129283,
+           -0.5159852126845416,
+           -0.5935914313818992,
+           -0.6795806615810426,
+           -0.7735228247733259,
+           -0.8747232550167846,
+           -0.9822337423126573,
+           -1.0948705300395507,
+           -1.2112388727400223,
+           -1.3297635899102236,
+           -1.4487248943156479,
+           -1.5662986337370435,
+           -1.680599966502638,
+           -1.7897293967283712,
+           -1.891820027312669,
+           -1.985084849204578,
+           -2.0678628753673975,
+           -2.1386629475468126,
+           -2.1962040930333147,
+           -2.2394513859607277,
+           -2.2676463714771433,
+           -2.2803312388706503,
+           -2.277366078338019,
+           -2.2589387219331587,
+           -2.2255668482704967,
+           -2.1780922183972535,
+           -2.117667102270675,
+           -2.045733146750935,
+           -1.9639931222199585,
+           -1.8743761612538616,
+           -1.7789972648397214,
+           -1.680111995406237,
+           -1.5800673978471367,
+           -1.4812502867017,
+           -1.3860341072737503,
+           -1.296725618943844,
+           -1.2155126591974024,
+           -1.1444142266354547,
+           -1.0852340708834511,
+           -1.0395188980385008,
+           -1.0085221939776772,
+           -0.9931745370382122,
+           -0.9940611194263553,
+           -1.0114070268939042,
+           -1.045070642855091,
+           -1.0945453506517784,
+           -1.1589695107882019,
+           -1.2371444934351088,
+           -1.3275603551275632,
+           -1.4284285670071442,
+           -1.5377210346052694,
+           -1.6532145000990761,
+           -1.7725392908176656,
+           -1.8932312756186127,
+           -2.01278581606665,
+           -2.128712453926294,
+           -2.238589061411501,
+           -2.340114196255759,
+           -2.431156449562271,
+           -2.509799649412397,
+           -2.5743828854833724,
+           -2.6235344469223305,
+           -2.656198914305577,
+           -2.671656813020148,
+           -2.66953641574152,
+           -2.649817471418278,
+           -2.612826832657264,
+           -2.559226147868264,
+           -2.489991974221217,
+           -2.4063888477618964,
+           -2.309936013534557,
+           -2.202368667230466,
+           -2.085594687124437,
+           -1.9616479378177734,
+           -1.8326393031260697,
+           -1.7007066525533836,
+           -1.5679649631143266,
+           -1.4364578054724264,
+           -1.3081113608741357,
+           -1.1846920643219547,
+           -1.0677688717026794,
+           -0.9586810266779499,
+           -0.8585120601605274,
+           -0.768070594760906,
+           -0.6878783527425346,
+           -0.6181655831393188,
+           -0.558873936352327,
+           -0.5096666274390353,
+           -0.4699455471081497,
+           -0.43887480667310774,
+           -0.41541004419017735,
+           -0.39833267765316316,
+           -0.38628817092681317,
+           -0.37782728203031285,
+           -0.37144919377654523,
+           -0.36564538531125323,
+           -0.3589430907498751,
+           -0.3499472081185131,
+           -0.3373795676718732,
+           -0.3201145421649457,
+           -0.29721008088357276,
+           -0.2679333716353803,
+           -0.23178047733087762,
+           -0.18848945260831432,
+           -0.13804661713011931,
+           -0.08068584135021341,
+           -0.01688088316954863,
+           0.0526690046733656,
+           0.12705980099244552,
+           0.2052092154493826,
+           0.28588824893192655,
+           0.3677569705209875,
+           0.44940355552762046,
+           0.529385542529913,
+           0.6062722074728422,
+           0.6786869212508215,
+           0.7453483546014723,
+           0.8051094206976429,
+           0.8569929008963597,
+           0.9002227813327551,
+           0.9342504353937511,
+           0.9587749168957581,
+           0.973756777779982,
+           0.979424988598343,
+           0.976276715868429,
+           0.9650698931116949,
+           0.9468087074588338,
+           0.9227223064465613,
+           0.8942372054281948,
+           0.8629440404288302,
+           0.8305594601241316,
+           0.7988840801203317,
+           0.7697575295494303,
+           0.7450117014147479,
+           0.7264233720043721,
+           0.7156673795929027,
+           0.7142715478551531,
+           0.7235745049372485,
+           0.7446874857294858,
+           0.7784611140414425,
+           0.8254580452596761,
+           0.8859322114718193,
+           0.9598152533327768,
+           1.0467105499757676,
+           1.145895074267601,
+           1.2563291101909169,
+           1.376673676794424,
+           1.5053153137299422,
+           1.640397701573166,
+           1.7798594204084053,
+           1.921476996758846,
+           2.062912255684043,
+           2.201762885074183,
+           2.33561503560537,
+           2.462096724597788,
+           2.5789307865617506,
+           2.683986118218807,
+           2.775326001189689,
+           2.8512523505468503,
+           2.910344830504528,
+           2.951493897442987,
+           2.9739269723762516,
+           2.977227106448722,
+           2.961343680176932,
+           2.9265948656421013,
+           2.873661776110042,
+           2.8035744248606527
+          ],
+          [
+           2.745485734487182,
+           2.6507778669343587,
+           2.543139170351125,
+           2.424630643999815,
+           2.297504951688574,
+           2.1641572474999076,
+           2.0270729086883144,
+           1.8887733947615404,
+           1.7517614944755373,
+           1.6184672347720879,
+           1.4911957072968336,
+           1.3720780195320648,
+           1.2630264999808793,
+           1.1656951821736747,
+           1.0814464631226224,
+           1.0113246814098484,
+           0.9560371920640037,
+           0.9159433338880207,
+           0.8910514944028372,
+           0.8810242827372005,
+           0.8851916263910132,
+           0.902571418579426,
+           0.9318971634419684,
+           0.9716519011412853,
+           1.0201075477888017,
+           1.0753686597742111,
+           1.1354195314541249,
+           1.1981734616687945,
+           1.2615229799264371,
+           1.3233898083285591,
+           1.3817733506730585,
+           1.4347965451860687,
+           1.4807479907872967,
+           1.5181193567748203,
+           1.5456372097589184,
+           1.5622885364275412,
+           1.5673394026263299,
+           1.5603463642044675,
+           1.54116042871923,
+           1.5099235548066663,
+           1.4670578631218834,
+           1.413247914564382,
+           1.3494165835081235,
+           1.2766952116830297,
+           1.196388868295395,
+           1.1099376604772746,
+           1.0188751323101448,
+           0.9247848581812941,
+           0.8292563754789668,
+           0.7338416117012738,
+           0.6400129417643584,
+           0.5491239632035354,
+           0.4623740013453121,
+           0.3807772553556578,
+           0.30513737194712903,
+           0.23602808963464164,
+           0.1737804364403144,
+           0.11847679193670085,
+           0.06995194485832446,
+           0.02780109476655996,
+           -0.008605434940147441,
+           -0.040101180424033114,
+           -0.06769678942551428,
+           -0.09254826381265978,
+           -0.11592104571863353,
+           -0.13915090957929763,
+           -0.16360270697210577,
+           -0.19062806892044143,
+           -0.2215231997812914,
+           -0.2574878972078314,
+           -0.29958690393356574,
+           -0.3487146399560769,
+           -0.4055642795175411,
+           -0.47060202817884095,
+           -0.5440473239866864,
+           -0.6258595365227523,
+           -0.7157315722644968,
+           -0.8130906183291687,
+           -0.9171060737482429,
+           -1.026704532533818,
+           -1.1405915006127414,
+           -1.2572793538204734,
+           -1.3751208809917594,
+           -1.4923476089008973,
+           -1.6071119781424121,
+           -1.7175323342719069,
+           -1.8217396193491326,
+           -1.9179245975091004,
+           -2.0043844257143415,
+           -2.0795673880715926,
+           -2.14211464894957,
+           -2.190897945792487,
+           -2.22505223544857,
+           -2.244002425803867,
+           -2.2474834646809216,
+           -2.2355532169226695,
+           -2.208597734453427,
+           -2.1673287086310244,
+           -2.1127730848435355,
+           -2.0462550113653024,
+           -1.9693704832294405,
+           -1.8839552226286238,
+           -1.7920465056416044,
+           -1.695839796717157,
+           -1.5976411835498825,
+           -1.4998167124710589,
+           -1.4047398055473987,
+           -1.3147379931729546,
+           -1.2320402186938513,
+           -1.1587259638926959,
+           -1.0966774060999291,
+           -1.0475357501579048,
+           -1.0126627830324149,
+           -0.9931085778235378,
+           -0.9895861301833035,
+           -1.002453547171753,
+           -1.0317042303208366,
+           -1.0769653054510049,
+           -1.137504356193993,
+           -1.2122443209721145,
+           -1.299786219166642,
+           -1.398439186096685,
+           -1.5062571227548147,
+           -1.6210811092326876,
+           -1.7405865942369467,
+           -1.8623342603610262,
+           -1.9838233785750687,
+           -2.102546407809823,
+           -2.216043567922558,
+           -2.3219561173932353,
+           -2.418077100703817,
+           -2.5023983936522836,
+           -2.573152966269361,
+           -2.6288514002744474,
+           -2.668311838233635,
+           -2.6906827013106414,
+           -2.6954576878031338,
+           -2.682482751225439,
+           -2.6519549499585655,
+           -2.6044132557056483,
+           -2.5407216003912274,
+           -2.462044626029093,
+           -2.369816774951476,
+           -2.2657055144414393,
+           -2.151569626447382,
+           -2.029413606389819,
+           -1.9013393023838663,
+           -1.7694959854309762,
+           -1.6360300709115532,
+           -1.5030357113991115,
+           -1.3725074505221067,
+           -1.2462960681704252,
+           -1.1260686603452172,
+           -1.013273884630259,
+           -0.909113167487037,
+           -0.8145185157639406,
+           -0.7301374058437393,
+           -0.6563250439845943,
+           -0.5931441051486579,
+           -0.5403718696201266,
+           -0.49751449168402845,
+           -0.46382795717735353,
+           -0.43834512124540526,
+           -0.4199080682405833,
+           -0.4072049060802131,
+           -0.39881000072473255,
+           -0.39322657535775596,
+           -0.3889305453102802,
+           -0.38441443504479816,
+           -0.37823022814925483,
+           -0.3690300350970756,
+           -0.3556035255872635,
+           -0.33691116096032264,
+           -0.31211237519700286,
+           -0.2805879874452501,
+           -0.24195628144863482,
+           -0.1960823537803729,
+           -0.14308050918373602,
+           -0.08330966309952204,
+           -0.017361894010170662,
+           0.0539555330832625,
+           0.1296441804424647,
+           0.20854383944281887,
+           0.28936653043531274,
+           0.3707341899771714,
+           0.45121903755627896,
+           0.5293855425299131,
+           0.6038328682483646,
+           0.6732366553696794,
+           0.7363890205987129,
+           0.7922356901728143,
+           0.8399092583114789,
+           0.8787576577904902,
+           0.9083670503772896,
+           0.9285784860611092,
+           0.9394978382934903,
+           0.9414986938528128,
+           0.9352180561555034,
+           0.9215449053237427,
+           0.9016018424373364,
+           0.8767202244995076,
+           0.8484093662041979,
+           0.8183205403081608,
+           0.7882066463256336,
+           0.7598785338552221,
+           0.7351590591231545,
+           0.7158360188911917,
+           0.7036151430007372,
+           0.700074334482867,
+           0.7066203240664909,
+           0.7244488545137494,
+           0.7545094306851383,
+           0.7974755654713986,
+           0.853721322266976,
+           0.9233048046378658,
+           1.0059590769100777,
+           1.1010908196565679,
+           1.2077868359009631,
+           1.3248283319143512,
+           1.4507127054892464,
+           1.5836823892527665,
+           1.7217601215173275,
+           1.862789856708397,
+           2.004482385547259,
+           2.144464615446198,
+           2.2803313669956857,
+           2.409698475378414,
+           2.5302559477475404,
+           2.6398199200543155,
+           2.736382179759525,
+           2.818156073818507,
+           2.883617703059922,
+           2.9315414126417956,
+           2.9610287210636086,
+           2.9715299840398033,
+           2.962858260679147,
+           2.9351950337187787,
+           2.889087628557714,
+           2.825438372832561,
+           2.7454857344871844
+          ],
+          [
+           2.6810898974638095,
+           2.5783542020906958,
+           2.4639971281369997,
+           2.340206835779186,
+           2.209333317739443,
+           2.0738371819756125,
+           1.9362360643501777,
+           1.799049919704219,
+           1.6647464645960062,
+           1.5356880391231809,
+           1.4140811189000884,
+           1.3019296423222853,
+           1.2009932243573038,
+           1.1127512085761122,
+           1.0383733669311608,
+           0.9786978953947139,
+           0.9342171769619866,
+           0.9050715960322006,
+           0.891051494402837,
+           0.8916071637916071,
+           0.9058665777110496,
+           0.932660381349179,
+           0.9705534863406536,
+           1.0178824621180491,
+           1.0727977806679556,
+           1.1333098602302203,
+           1.197337768431799,
+           1.262759388548475,
+           1.3274618253461525,
+           1.3893908298445174,
+           1.4465980551998792,
+           1.4972850178113812,
+           1.5398427270891035,
+           1.5728860617826315,
+           1.5952821074357884,
+           1.6061718249453012,
+           1.6049845904386857,
+           1.5914453274713656,
+           1.565574139344129,
+           1.5276785374896211,
+           1.4783385466775565,
+           1.4183851446434885,
+           1.3488726582641328,
+           1.2710458865092065,
+           1.1863028484396876,
+           1.096154159347887,
+           1.0021801171850302,
+           0.9059866327858789,
+           0.8091611598625446,
+           0.7132297738122146,
+           0.6196165123146116,
+           0.5296060264634747,
+           0.44431050046614234,
+           0.36464168310272954,
+           0.2912887381106497,
+           0.22470246692936094,
+           0.16508628972336165,
+           0.11239419356070467,
+           0.06633567455735474,
+           0.026387518325574247,
+           -0.008187915184866211,
+           -0.0383184058711646,
+           -0.06509224657423472,
+           -0.08972407443559685,
+           -0.11351707877846563,
+           -0.13782259912759717,
+           -0.16399819634036805,
+           -0.1933653214143711,
+           -0.22716771929114885,
+           -0.2665316885442841,
+           -0.31242927261079595,
+           -0.3656453853112526,
+           -0.4267497746179347,
+           -0.49607460643669504,
+           -0.5736983076236071,
+           -0.6594361481344835,
+           -0.7528378701029639,
+           -0.8531924910869406,
+           -0.9595402242583961,
+           -1.070691274588343,
+           -1.185251091735563,
+           -1.3016514918976352,
+           -1.4181869065973696,
+           -1.5330548801828796,
+           -1.6443998231946446,
+           -1.7503589386451517,
+           -1.8491091750055986,
+           -1.9389140249726822,
+           -2.018168983860961,
+           -2.08544450596208,
+           -2.139525350920298,
+           -2.1794452938534543,
+           -2.2045162806594796,
+           -2.2143512410981,
+           -2.2088799236439245,
+           -2.188357284078051,
+           -2.1533641402086663,
+           -2.104799993555977,
+           -2.0438681106639343,
+           -1.972053147176684,
+           -1.8910917822311186,
+           -1.8029370044973996,
+           -1.7097168500293474,
+           -1.613688532009222,
+           -1.5171890199879678,
+           -1.4225832183808393,
+           -1.3322109584463064,
+           -1.2483340530988554,
+           -1.1730846687494403,
+           -1.108416242738786,
+           -1.0560581193877656,
+           -1.017474993528669,
+           -0.9938321396016115,
+           -0.9859672696564115,
+           -0.9943697081394627,
+           -1.019167398926206,
+           -1.060122074861496,
+           -1.116632726588201,
+           -1.187747310381229,
+           -1.2721824388529237,
+           -1.3683506085231856,
+           -1.474394338975494,
+           -1.5882264340126147,
+           -1.707575429882159,
+           -1.8300351727966875,
+           -1.953117370611118,
+           -2.07430589400062,
+           -2.1911115624846964,
+           -2.301126141121025,
+           -2.4020742948558502,
+           -2.4918622988223613,
+           -2.568622383044098,
+           -2.6307516970413567,
+           -2.676945011110526,
+           -2.7062204233167715,
+           -2.71793751076296,
+           -2.711807546309907,
+           -2.6878955931447224,
+           -2.646614484741912,
+           -2.5887108920619255,
+           -2.515243868539102,
+           -2.427556441925482,
+           -2.327240986037514,
+           -2.216099250923029,
+           -2.0960980534134586,
+           -1.9693217284868114,
+           -1.8379225129984338,
+           -1.704070075475653,
+           -1.5699014178735873,
+           -1.4374723572500616,
+           -1.3087117477780192,
+           -1.1853795276472865,
+           -1.0690295731829351,
+           -0.9609782165441816,
+           -0.8622791368649457,
+           -0.773705171358572,
+           -0.6957374168452196,
+           -0.628561807790635,
+           -0.572073168883099,
+           -0.5258865531182357,
+           -0.48935549496920006,
+           -0.4615966370021289,
+           -0.4415200314992317,
+           -0.42786428015170674,
+           -0.41923555809403396,
+           -0.41414947633286214,
+           -0.4110746712207987,
+           -0.4084769726055847,
+           -0.4048629945028745,
+           -0.3988220137163409,
+           -0.3890650521467097,
+           -0.37446015625544976,
+           -0.35406297025814754,
+           -0.3271418254605665,
+           -0.2931967134934338,
+           -0.2519716723398362,
+           -0.2034602868780818,
+           -0.14790418578961395,
+           -0.08578459953191313,
+           -0.017807225011635827,
+           0.05511918297467686,
+           0.1319099099582921,
+           0.21133633766433066,
+           0.29206209591542703,
+           0.3726823414869534,
+           0.4517651122098053,
+           0.5278936489628232,
+           0.5997085509341199,
+           0.6659486313718618,
+           0.7254893719697857,
+           0.7773779332879336,
+           0.8208637647276799,
+           0.8554239684169372,
+           0.8807827041470031,
+           0.8969240739120348,
+           0.9040980908378493,
+           0.9028195141732188,
+           0.8938595151048797,
+           0.878230322835112,
+           0.8571631819690276,
+           0.8320801262072822,
+           0.8045602352229096,
+           0.776301187306529,
+           0.7490770461781481,
+           0.7246933230624875,
+           0.7049404320567128,
+           0.6915467059718637,
+           0.6861321598793163,
+           0.6901641799423175,
+           0.7049162759013123,
+           0.7314309676886874,
+           0.7704877816692376,
+           0.8225772122104593,
+           0.8878813625777606,
+           0.9662618189714998,
+           1.0572551367899763,
+           1.1600761331994356,
+           1.273628989368393,
+           1.3965259739800295,
+           1.5271134116097023,
+           1.6635043399005662,
+           1.8036171326458803,
+           1.9452192160432487,
+           2.0859748762618064,
+           2.2234960512949824,
+           2.3553949215081844,
+           2.4793370633337877,
+           2.593093910513028,
+           2.6945932777007706,
+           2.781966741951298,
+           2.853592747661333,
+           2.9081343983098624,
+           2.9445710214673486,
+           2.9622227390902185,
+           2.960767439555588,
+           2.940249727245348,
+           2.9010816154073518,
+           2.8440349238910847,
+           2.770225540413607,
+           2.6810898974638118
+          ],
+          [
+           2.610931731711199,
+           2.5010315519968986,
+           2.380906076329836,
+           2.252852125095082,
+           2.1192971581172833,
+           1.982746447619638,
+           1.8457286240177904,
+           1.7107408618236806,
+           1.5801949796762738,
+           1.4563657045852083,
+           1.341342296477322,
+           1.2369846464182646,
+           1.1448848524875879,
+           1.066335143913358,
+           1.0023028700036456,
+           0.9534130994333022,
+           0.919939191751267,
+           0.9018015110690173,
+           0.8985742564725578,
+           0.9095001895460018,
+           0.933512851243408,
+           0.9692656827809791,
+           1.0151673025600023,
+           1.069422047313868,
+           1.1300747641710576,
+           1.1950587440551348,
+           1.262245618090188,
+           1.3294959990506967,
+           1.3947096402715677,
+           1.455873904957939,
+           1.5111093889010523,
+           1.5587116178832716,
+           1.5971878455144402,
+           1.6252881052122423,
+           1.642029818273649,
+           1.6467154247407318,
+           1.6389426808986223,
+           1.6186074523149445,
+           1.5858990197102119,
+           1.541288101937512,
+           1.485507981292211,
+           1.4195292867744993,
+           1.3445291465677631,
+           1.2618555580296407,
+           1.1729879385484532,
+           1.079494910879211,
+           0.9829904398500001,
+           0.8850894721094629,
+           0.7873642360737553,
+           0.691302335366099,
+           0.598267716498943,
+           0.5094655117208858,
+           0.4259116529133377,
+           0.34840802488091177,
+           0.27752377960163416,
+           0.21358327073477099,
+           0.15666089405701045,
+           0.10658293892515766,
+           0.06293637292940692,
+           0.025084301245624982,
+           -0.007812331602562947,
+           -0.03676739239630657,
+           -0.06293730426698409,
+           -0.08758475615511141,
+           -0.11203935238573368,
+           -0.13765625870145295,
+           -0.16577395463432132,
+           -0.19767222716854077,
+           -0.2345315365929327,
+           -0.277394852344676,
+           -0.3271329953148599,
+           -0.3844144350447976,
+           -0.4496803776865586,
+           -0.5231258463479562,
+           -0.6046873028565121,
+           -0.6940371928892678,
+           -0.7905856190259389,
+           -0.8934891630568061,
+           -1.0016666944322559,
+           -1.1138218207342236,
+           -1.228471463058421,
+           -1.3439798786047532,
+           -1.4585973086628319,
+           -1.5705023062262993,
+           -1.6778466968516565,
+           -1.7788020516951675,
+           -1.8716065048720496,
+           -1.954610729649248,
+           -2.0263219000449326,
+           -2.08544450596208,
+           -2.1309169600919953,
+           -2.1619430318340043,
+           -2.178017265063598,
+           -2.178943679799768,
+           -2.164847219185133,
+           -2.136177578752434,
+           -2.093705240399675,
+           -2.0385097242694545,
+           -1.9719602631198663,
+           -1.8956892910525827,
+           -1.8115593169879325,
+           -1.7216239186128373,
+           -1.628083740558164,
+           -1.533238507589217,
+           -1.4394361664292397,
+           -1.3490203458850358,
+           -1.2642773722645753,
+           -1.187384094432606,
+           -1.1203577597408285,
+           -1.0650091387420437,
+           -1.0229000240449864,
+           -0.9953061285994748,
+           -0.9831862835104792,
+           -0.987158688174872,
+           -1.0074847996725864,
+           -1.0440612679407686,
+           -1.0964201326918466,
+           -1.1637373019341462,
+           -1.2448491350858666,
+           -1.3382767608310497,
+           -1.4422575757450453,
+           -1.5547831988005374,
+           -1.6736430033157697,
+           -1.7964722154618622,
+           -1.9208034603277433,
+           -2.044120555375399,
+           -2.163913298870965,
+           -2.277731978806536,
+           -2.383240336452133,
+           -2.478265757764126,
+           -2.560845534447125,
+           -2.629268132820765,
+           -2.68210853040233,
+           -2.7182568242813288,
+           -2.7369394783881056,
+           -2.737732754641624,
+           -2.7205680613391054,
+           -2.6857291464073936,
+           -2.6338412585206377,
+           -2.5658525908279213,
+           -2.4830085054521605,
+           -2.3868192075539802,
+           -2.2790216914599846,
+           -2.1615369144157808,
+           -2.0364232627377334,
+           -1.9058274578943564,
+           -1.7719341043961012,
+           -1.636915106063882,
+           -1.5028801717677438,
+           -1.3718295963110316,
+           -1.2456104377532633,
+           -1.1258771208025926,
+           -1.0140573793229823,
+           -0.9113243124605159,
+           -0.8185751719033795,
+           -0.736417326306338,
+           -0.6651616672384465,
+           -0.6048235337018643,
+           -0.5551310439981553,
+           -0.5155405391789406,
+           -0.4852586660987457,
+           -0.4632704645608422,
+           -0.448372676257177,
+           -0.4392113667705531,
+           -0.4343228489346573,
+           -0.4321768188463661,
+           -0.43122056665208425,
+           -0.429923104042682,
+           -0.42681805961938835,
+           -0.42054423162734755,
+           -0.40988275395722784,
+           -0.39378992404825736,
+           -0.37142485799047936,
+           -0.3421712757241302,
+           -0.3056528742520505,
+           -0.2617419152655263,
+           -0.2105608312488819,
+           -0.1524768364609288,
+           -0.08808971156524728,
+           -0.018213108472157177,
+           0.05615010934296973,
+           0.1338378204429696,
+           0.21356308431534407,
+           0.29395213966855044,
+           0.37358494280701215,
+           0.45103715944952893,
+           0.5249224839233103,
+           0.5939341491208611,
+           0.6568845092382583,
+           0.7127416246742383,
+           0.7606618533894582,
+           0.8000175536388657,
+           0.8304191267828105,
+           0.8517307727540574,
+           0.8640794910991001,
+           0.8678570332951006,
+           0.863714692922179,
+           0.8525510046887999,
+           0.8354926066137289,
+           0.813868697230191,
+           0.7891796870013107,
+           0.7630607959743886,
+           0.7372414841643008,
+           0.713501713805267,
+           0.6936261305469235,
+           0.679357311609172,
+           0.6723492612351011,
+           0.6741223365884563,
+           0.6860207603630631,
+           0.7091738203781854,
+           0.7444617726251606,
+           0.7924873546021719,
+           0.8535536829685879,
+           0.9276491567934061,
+           1.01443981869319,
+           1.1132694450941585,
+           1.2231674481606425,
+           1.3428644802576444,
+           1.4708154418925232,
+           1.6052294106103018,
+           1.7441058358510164,
+           1.8852761876039599,
+           2.0264501087332776,
+           2.165265005555275,
+           2.2993379215209866,
+           2.426318476973858,
+           2.543941625505567,
+           2.650078975294753,
+           2.7427874521102,
+           2.8203541387707323,
+           2.881336212422179,
+           2.9245950139609262,
+           2.949323420594559,
+           2.955065849590013,
+           2.941730394920047,
+           2.9095927845706524,
+           2.859292040198063,
+           2.7918179179102744,
+           2.7084904043995373,
+           2.610931731711202
+          ],
+          [
+           2.5356048070585513,
+           2.4194641012616596,
+           2.2945690028270547,
+           2.16330557232835,
+           2.028158219474326,
+           1.8916557132636644,
+           1.7563163215914508,
+           1.6245933557098993,
+           1.4988223835387466,
+           1.3811713340021283,
+           1.2735946433809258,
+           1.1777924958732968,
+           1.0951760865870779,
+           1.0268396890959675,
+           0.9735401450661701,
+           0.9356842143409483,
+           0.9133240346475895,
+           0.9061607453969901,
+           0.9135561346408008,
+           0.9345519769058159,
+           0.9678965470039225,
+           1.0120776254606247,
+           1.0653611590268162,
+           1.1258346085160567,
+           1.191453909099539,
+           1.2600928877501056,
+           1.329593930650045,
+           1.3978186712519503,
+           1.4626974777584285,
+           1.5222765567694285,
+           1.574761556701755,
+           1.618556648569279,
+           1.6522981804124637,
+           1.6748821420640414,
+           1.6854848354852316,
+           1.6835763186133759,
+           1.6689263731946373,
+           1.6416029348680246,
+           1.6019631121324684,
+           1.5506371050767116,
+           1.4885055103048002,
+           1.4166706609972557,
+           1.336422796493427,
+           1.2492019805819412,
+           1.1565567887844372,
+           1.0601008598516874,
+           0.9614684536587375,
+           0.8622701755874418,
+           0.7640500159510729,
+           0.6682448124144599,
+           0.5761471747903937,
+           0.488872816844178,
+           0.4073331212627684,
+           0.3322136247845759,
+           0.26395895419778337,
+           0.20276457448217225,
+           0.1485755321011331,
+           0.10109219387389923,
+           0.059782799604454984,
+           0.023902469332920978,
+           -0.007481861800297443,
+           -0.03546126227529794,
+           -0.061250194290804236,
+           -0.08614840857190885,
+           -0.11150036877439908,
+           -0.13865329561614,
+           -0.168914958135259,
+           -0.20351234781137315,
+           -0.24355235046010446,
+           -0.2899854813276178,
+           -0.3435736718981709,
+           -0.40486299450287394,
+           -0.4741620854452359,
+           -0.5515268821821493,
+           -0.6367521287630508,
+           -0.7293699302913283,
+           -0.8286554559964826,
+           -0.9336397061594484,
+           -1.0431290752697064,
+           -1.155731267034271,
+           -1.2698869506824833,
+           -1.3839063966364717,
+           -1.4960101969007569,
+           -1.604373064861675,
+           -1.7071696234274267,
+           -1.8026210318148956,
+           -1.889041271357658,
+           -1.9648819103143949,
+           -2.0287741969061033,
+           -2.0795673880715926,
+           -2.1163623073464106,
+           -2.1385392367906864,
+           -2.145779382323807,
+           -2.138079305899559,
+           -2.115757887909295,
+           -2.0794555648644573,
+           -2.0301257763147964,
+           -1.9690187464463105,
+           -1.8976579151402255,
+           -1.8178095157708465,
+           -1.73144596814469,
+           -1.6407039104761119,
+           -1.547837830273584,
+           -1.4551703670677865,
+           -1.3650404471983828,
+           -1.2797504701725422,
+           -1.2015137958816013,
+           -1.132403781404693,
+           -1.0743055851774335,
+           -1.0288718956442198,
+           -0.9974836525624006,
+           -0.9812167139991483,
+           -0.980815283518853,
+           -0.996672753439129,
+           -1.0288204451736582,
+           -1.0769245408189698,
+           -1.1402913058175856,
+           -1.21788050546635,
+           -1.3083267230320337,
+           -1.4099680990345362,
+           -1.520881834446232,
+           -1.6389256394413207,
+           -1.761784167836527,
+           -1.8870193589395392,
+           -2.0121235160444724,
+           -2.1345738865313524,
+           -2.251887473993076,
+           -2.3616748088570616,
+           -2.4616914306662836,
+           -2.5498858918648204,
+           -2.624443178189453,
+           -2.683822552496654,
+           -2.726788964302814,
+           -2.752437323153618,
+           -2.760209106341203,
+           -2.7499009562259706,
+           -2.721665114969402,
+           -2.676001740133179,
+           -2.6137433385685265,
+           -2.5360317435755757,
+           -2.444288236888792,
+           -2.3401775783511805,
+           -2.225566848270499,
+           -2.1024801269762907,
+           -1.9730501301524814,
+           -1.8394679848731585,
+           -1.7039323683737402,
+           -1.5685992386248646,
+           -1.4355333626635383,
+           -1.3066627960432615,
+           -1.1837373860843168,
+           -1.0682922649234021,
+           -0.9616171684006156,
+           -0.8647322668764571,
+           -0.778371027922183,
+           -0.7029704526493274,
+           -0.6386688417007804,
+           -0.5853110582587673,
+           -0.542461068536754,
+           -0.5094213597617927,
+           -0.48525866609874546,
+           -0.4688352785149311,
+           -0.4588450790437306,
+           -0.45385332660971006,
+           -0.45233913329449266,
+           -0.4527395087901125,
+           -0.45349381826014235,
+           -0.45308749564512657,
+           -0.45009388060867356,
+           -0.4432131020893293,
+           -0.431307013351193,
+           -0.4134292903833371,
+           -0.3888499347307567,
+           -0.35707357003756035,
+           -0.31785108496460396,
+           -0.27118434954946835,
+           -0.21732391307436244,
+           -0.1567597745038532,
+           -0.09020549690864714,
+           -0.018576110433994292,
+           0.05703959008456577,
+           0.13541160090140714,
+           0.21520524011157716,
+           0.2950206710692768,
+           0.37343435752174814,
+           0.4490413380852043,
+           0.5204971848120767,
+           0.5865585168608756,
+           0.6461209755436825,
+           0.698253630422613,
+           0.7422288760774421,
+           0.7775469934238661,
+           0.8039546851631574,
+           0.8214570486841893,
+           0.8303226176552495,
+           0.8310812814113258,
+           0.8245150745826106,
+           0.811642013597698,
+           0.7936933370778634,
+           0.7720846791526994,
+           0.7483818640099505,
+           0.7242621524933919,
+           0.7014718936447812,
+           0.6817816326168907,
+           0.6669397988152771,
+           0.6586261425560124,
+           0.6584061037503194,
+           0.6676872816677062,
+           0.6876791309496636,
+           0.7193569367442744,
+           0.7634310228168982,
+           0.8203220231420084,
+           0.8901429027861573,
+           0.972688251379716,
+           1.0674311961244916,
+           1.1735280954276013,
+           1.2898309834664632,
+           1.4149075449863697,
+           1.5470682131369247,
+           1.684399805791598,
+           1.8248049519757832,
+           1.9660464138354676,
+           2.105795284668928,
+           2.2416819430546404,
+           2.3713485695832524,
+           2.4925019880201913,
+           2.602965578063882,
+           2.700729022658626,
+           2.783994698758986,
+           2.8512195954702415,
+           2.9011517458351066,
+           2.9328602857561914,
+           2.9457584025763235,
+           2.939618603086692,
+           2.9145799121451597,
+           2.871146804262514,
+           2.8101798668071827,
+           2.7328783901143447,
+           2.6407552719764973,
+           2.535604807058554
+          ],
+          [
+           2.4557464233742476,
+           2.3343419474278906,
+           2.2057163583384574,
+           2.072324781835671,
+           1.936687578472329,
+           1.8013356477393687,
+           1.6687556256092106,
+           1.5413362482467885,
+           1.421317125168265,
+           1.3107411057749132,
+           1.211411335412255,
+           1.1248539830657447,
+           1.0522874853087634,
+           0.9945989935435934,
+           0.9523285377869863,
+           0.9256612345079442,
+           0.914427672873444,
+           0.9181124179211275,
+           0.9358703754388858,
+           0.9665505764139223,
+           1.0087267633676602,
+           1.0607340009804227,
+           1.1207103930024067,
+           1.1866428699298701,
+           1.2564159201129275,
+           1.3278620730311899,
+           1.3988129089116546,
+           1.4671493644290514,
+           1.530850129936751,
+           1.5880369887971204,
+           1.6370160324594587,
+           1.676313793829614,
+           1.7047074734122287,
+           1.7212485843447072,
+           1.7252795099613072,
+           1.7164426467213263,
+           1.694681991722131,
+           1.6602372229426339,
+           1.6136305071199213,
+           1.5556464501101896,
+           1.4873057732634805,
+           1.4098334525793759,
+           1.3246221914309184,
+           1.2331922091571244,
+           1.1371484141098231,
+           1.0381360887129178,
+           0.9377962443532287,
+           0.8377218047942415,
+           0.7394157483465402,
+           0.6442522820351163,
+           0.5534420369814769,
+           0.4680021653503089,
+           0.38873208829907957,
+           0.3161954947665854,
+           0.2507090264601674,
+           0.19233790923737681,
+           0.14089860967654444,
+           0.09596841259465352,
+           0.056901635239836205,
+           0.022852021420228748,
+           -0.007199301702136158,
+           -0.034411065959993055,
+           -0.060045190359519614,
+           -0.08542718383649786,
+           -0.11190468798970658,
+           -0.14080527448819571,
+           -0.1733946325322428,
+           -0.21083627327954507,
+           -0.2541538407253831,
+           -0.3041970530745896,
+           -0.3616122067973431,
+           -0.42681805961938774,
+           -0.49998777156822916,
+           -0.5810374283245019,
+           -0.6696215024065545,
+           -0.7651354293939977,
+           -0.8667252929670262,
+           -0.9733044286318908,
+           -1.0835765762669216,
+           -1.1960650406085458,
+           -1.309147160841728,
+           -1.4210932495832873,
+           -1.5301090413471266,
+           -1.6343805941442586,
+           -1.7321205176943486,
+           -1.8216143596543115,
+           -1.9012659684486342,
+           -1.9696406681319325,
+           -2.0255051269033504,
+           -2.0678628753673975,
+           -2.095984531631827,
+           -2.1094319154199046,
+           -2.108075379515895,
+           -2.0921038504920078,
+           -2.0620272477721797,
+           -2.0186711363186176,
+           -1.9631636589902242,
+           -1.8969149852039549,
+           -1.8215896982111164,
+           -1.73907271947136,
+           -1.651429530884309,
+           -1.5608615999727808,
+           -1.4696580358883036,
+           -1.3801446022399784,
+           -1.2946312837445257,
+           -1.2153596457368623,
+           -1.1444512375544267,
+           -1.083858272342208,
+           -1.0353177672949008,
+           -1.0003102508742105,
+           -0.9800240389437901,
+           -0.9753259525507418,
+           -0.9867391993595527,
+           -1.0144289721518847,
+           -1.058196135427249,
+           -1.1174791794014642,
+           -1.1913644242621368,
+           -1.2786042611828512,
+           -1.3776430251017697,
+           -1.4866499123014811,
+           -1.603558187820262,
+           -1.7261097777751344,
+           -1.851904213438722,
+           -1.9784507905083186,
+           -2.1032227309527287,
+           -2.2237120879668,
+           -2.337484118036666,
+           -2.442229858309496,
+           -2.5358156920068993,
+           -2.6163287584149715,
+           -2.682117165205023,
+           -2.7318240869951564,
+           -2.7644149820538853,
+           -2.779197325240088,
+           -2.775832435593954,
+           -2.7543391670244213,
+           -2.715089425630665,
+           -2.6587956725808595,
+           -2.5864907623827835,
+           -2.49950064816673,
+           -2.399410653842157,
+           -2.2880261636057155,
+           -2.1673287086310244,
+           -2.039428535749789,
+           -1.9065148210360334,
+           -1.7708047405929708,
+           -1.634492630389236,
+           -1.499700456310407,
+           -1.3684307750407707,
+           -1.2425232970653197,
+           -1.123616066786174,
+           -1.0131121539478891,
+           -0.9121526083297041,
+           -0.8215962695807877,
+           -0.7420068501720196,
+           -0.6736475260735562,
+           -0.6164830815244066,
+           -0.5701894658330854,
+           -0.5341704362245263,
+           -0.5075807858936209,
+           -0.4893554949691996,
+           -0.4782439980202369,
+           -0.47284863859250365,
+           -0.4716662820633783,
+           -0.4731319852553969,
+           -0.47566357650245694,
+           -0.4777059842576074,
+           -0.4777741661779585,
+           -0.47449353349273166,
+           -0.4666368362004004,
+           -0.4531565713995476,
+           -0.43321209733458266,
+           -0.4061907764448224,
+           -0.3717226282476002,
+           -0.3296881432487145,
+           -0.28021908792487,
+           -0.22369231362195152,
+           -0.1607167643244925,
+           -0.09211405506070407,
+           -0.01889315973628982,
+           0.05778009978989659,
+           0.13661793643878284,
+           0.21624891167190985,
+           0.2952586498584401,
+           0.37223185965081534,
+           0.4457945336686928,
+           0.5146551916620734,
+           0.5776440553405937,
+           0.6337490946537434,
+           0.6821479642021705,
+           0.722234952680962,
+           0.753642195190144,
+           0.7762545447093727,
+           0.7902176613420419,
+           0.795939052004972,
+           0.7940819746886734,
+           0.785552305663696,
+           0.7714786504077344,
+           0.753186154962174,
+           0.7321646394369662,
+           0.710031825276928,
+           0.6884925588603497,
+           0.6692950426696844,
+           0.6541851688533681,
+           0.6448601063097006,
+           0.6429223199683848,
+           0.6498351989391908,
+           0.6668814385935898,
+           0.6951252611365349,
+           0.7353794712272107,
+           0.7881782298235975,
+           0.853756293397569,
+           0.9320353103067003,
+           1.0226175952160677,
+           1.124787620233472,
+           1.2375212723411422,
+           1.359502735442627,
+           1.489148666627116,
+           1.624639154763734,
+           1.7639547797853574,
+           1.9049189372356845,
+           2.045244458677553,
+           2.182583447757682,
+           2.31457916688961,
+           2.438918752813991,
+           2.553385512195352,
+           2.6559095516614444,
+           2.7446155302845403,
+           2.8178663856939905,
+           2.8743019763193693,
+           2.9128716995208115,
+           2.932860285756192,
+           2.9339061290782666,
+           2.916011690275633,
+           2.8795456966009345,
+           2.8252370567113423,
+           2.754160606445109,
+           2.66771499557889,
+           2.567593213015283,
+           2.4557464233742508
+          ],
+          [
+           2.3720322187205896,
+           2.2463852624352394,
+           2.1150998764426996,
+           1.980679492273892,
+           1.8456591181251076,
+           1.7125503996713842,
+           1.583787339180749,
+           1.4616739322377572,
+           1.3483349341221746,
+           1.2456708915044077,
+           1.1553184714949947,
+           1.0786169917689117,
+           1.0165819056267742,
+           0.9698858281296893,
+           0.938847507962038,
+           0.9234289588791279,
+           0.9232407691500375,
+           0.9375554120836824,
+           0.9653281902923516,
+           1.0052252654389509,
+           1.0556580582282997,
+           1.1148231543862126,
+           1.1807467249215269,
+           1.251332366147695,
+           1.3244111892024024,
+           1.3977929419250013,
+           1.469316928996979,
+           1.5369015095452252,
+           1.598590994529678,
+           1.6525988380291234,
+           1.6973461151387814,
+           1.7314944020799676,
+           1.75397231817948,
+           1.7639951509714888,
+           1.7610771607485116,
+           1.745036345056606,
+           1.7159916322938102,
+           1.6743526620295484,
+           1.6208024932314202,
+           1.5562737557122088,
+           1.4819189204865086,
+           1.399075507397947,
+           1.309227169838901,
+           1.2139616936659483,
+           1.114927018156748,
+           1.0137864293659078,
+           0.9121740895359968,
+           0.8116520500550366,
+           0.7136698503112244,
+           0.6195277318918214,
+           0.5303443988122484,
+           0.4470301323949942,
+           0.3702659271782076,
+           0.30048915545518,
+           0.23788609677310726,
+           0.18239148930647608,
+           0.1336950770208034,
+           0.09125494459558044,
+           0.05431725578981702,
+           0.021941844772222788,
+           -0.006967041894369439,
+           -0.03362568858643865,
+           -0.059332487351659385,
+           -0.08542718383649785,
+           -0.1132488893081381,
+           -0.14409398860258102,
+           -0.17917507775279856,
+           -0.2195820398494817,
+           -0.2662463139838953,
+           -0.31990933125780224,
+           -0.3810959858445993,
+           -0.45009388060867284,
+           -0.5269389390646817,
+           -0.6114078122009752,
+           -0.7030173340124382,
+           -0.8010310978907942,
+           -0.9044730418900014,
+           -1.0121477489735253,
+           -1.122666993262762,
+           -1.234481899481369,
+           -1.3459199343927606,
+           -1.455225819842027,
+           -1.5606053503480217,
+           -1.6602710167977577,
+           -1.7524882837965152,
+           -1.835621343065315,
+           -1.9081771696758494,
+           -1.9688467418573625,
+           -2.016542347848169,
+           -2.0504299933233248,
+           -2.069956038151839,
+           -2.074867328831669,
+           -2.0652242495648716,
+           -2.0414062867339946,
+           -2.004109884302739,
+           -1.9543385568856815,
+           -1.8933854182392282,
+           -1.822808470989822,
+           -1.7443991838690196,
+           -1.660145051079623,
+           -1.5721869804738628,
+           -1.4827724891787588,
+           -1.3942057938395822,
+           -1.3087959650257819,
+           -1.2288043694510067,
+           -1.156392648089903,
+           -1.0935724723476012,
+           -1.0421582842189139,
+           -1.0037241606747105,
+           -0.9795658488710624,
+           -0.9706688994209336,
+           -0.9776836827617088,
+           -1.0009079120239626,
+           -1.0402771186680473,
+           -1.0953633388011625,
+           -1.1653820730946571,
+           -1.2492073863326096,
+           -1.345394818632475,
+           -1.4522115940135805,
+           -1.5676734377927295,
+           -1.6895871565061062,
+           -1.815597996540402,
+           -1.9432406837567644,
+           -2.069992958883934,
+           -2.1933303644715125,
+           -2.3107810101621014,
+           -2.419979044660193,
+           -2.5187155949938864,
+           -2.6049859956814285,
+           -2.677032220697817,
+           -2.7333795474659066,
+           -2.7728666216134683,
+           -2.7946682505194,
+           -2.7983104288140432,
+           -2.7836772857112435,
+           -2.751009837765308,
+           -2.7008966266302306,
+           -2.6342565148677632,
+           -2.552314099089873,
+           -2.456568374199053,
+           -2.348755440972173,
+           -2.2308061878851175,
+           -2.1047999935559765,
+           -1.9729155857292302,
+           -1.8373802542110929,
+           -1.7004186471708844,
+           -1.5642023820477775,
+           -1.4308016739959522,
+           -1.302140127154997,
+           -1.179953748562022,
+           -1.0657551334253048,
+           -0.9608036365841974,
+           -0.8660821916714166,
+           -0.7822812706298904,
+           -0.7097902960516341,
+           -0.6486966318066345,
+           -0.5987920882795907,
+           -0.5595866919393405,
+           -0.5303292895623883,
+           -0.5100343896622195,
+           -0.49751449168402784,
+           -0.49141702105225066,
+           -0.4902648784530292,
+           -0.49249952746796366,
+           -0.4965254878809056,
+           -0.5007550739972917,
+           -0.5036522187640108,
+           -0.5037742552376214,
+           -0.4998105861671947,
+           -0.49061725857061794,
+           -0.4752465709541623,
+           -0.4529709734033619,
+           -0.423300671764953,
+           -0.3859945126930184,
+           -0.3410639022349672,
+           -0.2887696924168095,
+           -0.22961215334128157,
+           -0.16431432799840573,
+           -0.09379923875581901,
+           -0.019161573998479862,
+           0.0583653734117705,
+           0.13744662091057727,
+           0.21668526906267496,
+           0.2946640626277973,
+           0.3699876228703384,
+           0.4413242156345542,
+           0.5074459303788821,
+           0.5672661849383175,
+           0.6198735382791111,
+           0.6645608872370327,
+           0.7008492408393059,
+           0.7285054043478016,
+           0.747553061144155,
+           0.7582769100805171,
+           0.7612196946724141,
+           0.7571721440043986,
+           0.7471560288213431,
+           0.7324007153456255,
+           0.7143137693570687,
+           0.6944463196830152,
+           0.6744540294835192,
+           0.6560546420233271,
+           0.6409831619584547,
+           0.6309458010856847,
+           0.6275738572199661,
+           0.632378705291441,
+           0.6467090605347958,
+           0.671711625163163,
+           0.7082961532928835,
+           0.7571058659349879,
+           0.8184940210757403,
+           0.8925072963133116,
+           0.9788764768060622,
+           1.077014763460319,
+           1.1860238297180852,
+           1.3047075646008428,
+           1.4315932495405808,
+           1.5649597316963035,
+           1.7028719815055366,
+           1.8432212615125463,
+           1.9837699910634299,
+           2.122200270833319,
+           2.25616493539277,
+           2.3833399335601597,
+           2.5014767968872107,
+           2.6084539473347093,
+           2.702325616324199,
+           2.78136719845911,
+           2.844115943116628,
+           2.8894059939312347,
+           2.916396917367774,
+           2.924595013960928,
+           2.9138668756973973,
+           2.8844448363214674,
+           2.8369241536040386,
+           2.77225195915582,
+           2.6917082074035097,
+           2.5968790461084525,
+           2.489623211640916,
+           2.3720322187205927
+          ],
+          [
+           2.2851704531500565,
+           2.156338199639598,
+           2.023486213581045,
+           1.889145064262672,
+           1.7558429803980473,
+           1.6260511324341476,
+           1.5021303324578383,
+           1.386280386923851,
+           1.2804932727615432,
+           1.186511214647948,
+           1.105790622640194,
+           1.0394727078516457,
+           0.9883614329021784,
+           0.9529092774164925,
+           0.9332111112038799,
+           0.9290062735164356,
+           0.9396887606948989,
+           0.9643252313559844,
+           1.0016803527577245,
+           1.0502488386112538,
+           1.108293371594667,
+           1.1738874669645614,
+           1.2449622202493906,
+           1.3193557947591974,
+           1.3948644456232573,
+           1.4692938476366202,
+           1.540509494992663,
+           1.6064849718895835,
+           1.665346953169663,
+           1.7154158820063656,
+           1.7552413849405823,
+           1.7836316204050326,
+           1.79967591183489,
+           1.802760186647683,
+           1.7925749235225643,
+           1.7691154979925026,
+           1.7326750057077167,
+           1.6838298291267844,
+           1.6234183922191017,
+           1.5525137145935168,
+           1.4723905271859568,
+           1.3844878425372305,
+           1.2903679805663706,
+           1.191673132971376,
+           1.090080603990271,
+           0.9872578909470798,
+           0.8848187642309523,
+           0.7842814732916197,
+           0.6870301437926564,
+           0.594280342866774,
+           0.5070496767534203,
+           0.426134150866989,
+           0.3520908699792682,
+           0.28522748958813327,
+           0.22559865292419717,
+           0.17300946590289162,
+           0.12702587927981335,
+           0.08699166794882073,
+           0.05205152627398961,
+           0.021179639895204844,
+           -0.006787047400069755,
+           -0.03311177480260231,
+           -0.05911811505717184,
+           -0.08614840857190885,
+           -0.11552160017828167,
+           -0.14849161394972804,
+           -0.18620738861467898,
+           -0.22967565437849696,
+           -0.27972746243996754,
+           -0.33698938289393876,
+           -0.40186016745268915,
+           -0.47449353349273093,
+           -0.5547875688620308,
+           -0.6423810866212187,
+           -0.7366570797335299,
+           -0.8367532421832599,
+           -0.9415793397284685,
+           -1.0498410351174583,
+           -1.1600696036408273,
+           -1.2706568196428496,
+           -1.3798941570314693,
+           -1.4860153304231372,
+           -1.5872411113295575,
+           -1.6818252881309737,
+           -1.7681006012161833,
+           -1.844523476630017,
+           -1.909716403149567,
+           -1.9625068484662234,
+           -2.001961688907069,
+           -2.027416232009936,
+           -2.038497039739314,
+           -2.035137909069169,
+           -2.0175885324204805,
+           -1.986415538955821,
+           -1.9424958046038308,
+           -1.8870021092984746,
+           -1.8213814095535759,
+           -1.7473261784477434,
+           -1.6667394387943757,
+           -1.5816942743854074,
+           -1.4943887447474873,
+           -1.4070972473070915,
+           -1.3221194642376812,
+           -1.2417280971816549,
+           -1.1681166297997638,
+           -1.1033483647146276,
+           -1.049307957637679,
+           -1.0076566178037927,
+           -0.9797920615251381,
+           -0.9668141966626701,
+           -0.9694973827074436,
+           -0.9882699571675788,
+           -1.0232015477915268,
+           -1.0739985059716706,
+           -1.1400076039365037,
+           -1.2202279417415982,
+           -1.3133308143956488,
+           -1.417687099476126,
+           -1.5314015459318095,
+           -1.652353179819062,
+           -1.7782408965001322,
+           -1.906633184912489,
+           -2.0350208309215434,
+           -2.160871375898624,
+           -2.2816840652470898,
+           -2.395044010636348,
+           -2.498674309455045,
+           -2.590484914967696,
+           -2.6686171296208654,
+           -2.731482699953817,
+           -2.7777966220216843,
+           -2.8066029179367624,
+           -2.817292813358382,
+           -2.809614928370472,
+           -2.783677285711243,
+           -2.7399411360807018,
+           -2.679206795469959,
+           -2.602591879372237,
+           -2.5115024987263705,
+           -2.407598148137386,
+           -2.2927511643014635,
+           -2.169001758076316,
+           -2.038509724269454,
+           -1.9035040065692377,
+           -1.7662313393967446,
+           -1.6289052028073174,
+           -1.4936563106570335,
+           -1.362485806556932,
+           -1.2372222678841913,
+           -1.1194835172267468,
+           -1.0106441156803132,
+           -0.9118092665590961,
+           -0.8237956949977836,
+           -0.7471198927051295,
+           -0.6819939321870416,
+           -0.6283288657044679,
+           -0.5857455357744491,
+           -0.5535924408424828,
+           -0.5309701263892405,
+           -0.5167614124694375,
+           -0.5096666274390345,
+           -0.5082428978752606,
+           -0.5109464493551491,
+           -0.5161768041401927,
+           -0.5223217215531273,
+           -0.5278017158517789,
+           -0.5311130048946234,
+           -0.5308677903054971,
+           -0.5258308449103398,
+           -0.5149514839754659,
+           -0.497390120622967,
+           -0.47253874955714037,
+           -0.4400348632344249,
+           -0.3997684767733053,
+           -0.35188211785474915,
+           -0.2967638210420925,
+           -0.23503334770956935,
+           -0.16752202850899547,
+           -0.09524679057737705,
+           -0.019379082314447457,
+           0.058790459270507175,
+           0.13789064327117512,
+           0.2165106205028926,
+           0.29324193985437363,
+           0.36672063443900876,
+           0.4356682048961992,
+           0.4989303945751861,
+           0.5555127071336902,
+           0.6046116999054755,
+           0.6456411941565678,
+           0.678252673351799,
+           0.7023492895218928,
+           0.7180930620060346,
+           0.7259050281086409,
+           0.7264582871312962,
+           0.7206640632279778,
+           0.709651093932152,
+           0.6947388254249636,
+           0.6774050582347214,
+           0.6592488339436974,
+           0.6419494808812712,
+           0.6272228414370891,
+           0.6167757828331797,
+           0.6122601448810874,
+           0.6152273010354897,
+           0.6270845022763883,
+           0.6490541370826298,
+           0.6821369758123624,
+           0.72708037571117,
+           0.7843523057370728,
+           0.8541219112612823,
+           0.9362471808695403,
+           1.0302701048197889,
+           1.135419531454125,
+           1.2506217385363922,
+           1.3745185457720446,
+           1.5054926073897281,
+           1.6416993442785515,
+           1.7811048082473397,
+           1.9215286206692646,
+           2.0606909978631274,
+           2.196262769309029,
+           2.325917214892795,
+           2.447382495865662,
+           2.5584934324422157,
+           2.657241389558233,
+           2.74182107114159,
+           2.8106730914392584,
+           2.8625212878930437,
+           2.8964038614821965,
+           2.911697574437828,
+           2.9081343983098655,
+           2.8858101835851824,
+           2.845185111092812,
+           2.7870758806946947,
+           2.7126397894972962,
+           2.623351045238309,
+           2.520969845889185,
+           2.407504929346851,
+           2.2851704531500596
+          ],
+          [
+           2.195896016504772,
+           2.064962597938978,
+           1.931650462796958,
+           1.7984959204827866,
+           1.6679990504585847,
+           1.5425696689698514,
+           1.424475460667571,
+           1.3157934758143937,
+           1.218366112240183,
+           1.133762592841799,
+           1.0632468168607723,
+           1.0077523096688776,
+           0.9678648251041356,
+           0.9438129707050131,
+           0.9354670339795849,
+           0.9423459918142717,
+           0.9636324900567573,
+           0.998195390953508,
+           1.0446193070910066,
+           1.101240376128394,
+           1.1661873848979318,
+           1.2374272279041498,
+           1.3128135868376811,
+           1.3901376467773718,
+           1.46717962294571,
+           1.5417598601491975,
+           1.6117882855753798,
+           1.675311043883817,
+           1.730553220239196,
+           1.7759566601117625,
+           1.8102120216844304,
+           1.832284344345418,
+           1.8414315812950226,
+           1.83721572163009,
+           1.8195063129574962,
+           1.7884763849992382,
+           1.7445909630754557,
+           1.688588543112232,
+           1.6214560723938214,
+           1.544398138403416,
+           1.4588012078807944,
+           1.3661938762429409,
+           1.2682041808884523,
+           1.1665150983825718,
+           1.0628193835173712,
+           0.958774916895758,
+           0.8559617068686016,
+           0.7558416419687362,
+           0.6597220127625878,
+           0.5687237192956996,
+           0.4837549546945921,
+           0.4054910102255597,
+           0.3343606859104716,
+           0.2705396177646631,
+           0.21395065224853083,
+           0.16427121519003177,
+           0.1209474408843094,
+           0.08321465190396064,
+           0.05012361578931219,
+           0.02057185538733613,
+           -0.006660841054107317,
+           -0.03287367255164393,
+           -0.05940388716267295,
+           -0.08758475615511137,
+           -0.11870359243776256,
+           -0.15396094462925175,
+           -0.19443206858583562,
+           -0.24103172032026268,
+           -0.29448322947737204,
+           -0.355292703017346,
+           -0.42372907724930886,
+           -0.499810586167194,
+           -0.5832980489505427,
+           -0.6736952036680708,
+           -0.7702561320988706,
+           -0.8719996367662257,
+           -0.9777302504119229,
+           -1.0860653848065058,
+           -1.1954679643924446,
+           -1.3042837448990832,
+           -1.4107823914608197,
+           -1.5132012881346897,
+           -1.6097909737010112,
+           -1.6988610492550082,
+           -1.7788253826833285,
+           -1.8482454442701983,
+           -1.9058706462580886,
+           -1.9506746263254389,
+           -1.9818865090525153,
+           -1.9990162982617883,
+           -2.001873693756182,
+           -1.9905797850013638,
+           -1.9655712478051708,
+           -1.927596853767287,
+           -1.877706291670396,
+           -1.817231490373675,
+           -1.747760819428933,
+           -1.671106721928752,
+           -1.5892674995719513,
+           -1.504384118458927,
+           -1.4186930319835287,
+           -1.3344761211474498,
+           -1.2540089300504695,
+           -1.1795084232181159,
+           -1.1130815105297627,
+           -1.056675574251203,
+           -1.0120321912490269,
+           -0.9806451728068986,
+           -0.9637239462343871,
+           -0.9621631789969061,
+           -0.976519400364833,
+           -1.0069952110965348,
+           -1.0534314924156665,
+           -1.1153078358670643,
+           -1.1917512201484668,
+           -1.2815527644754963,
+           -1.3831921952336592,
+           -1.4948694783052363,
+           -1.6145428980293668,
+           -1.7399727094449158,
+           -1.8687693570457162,
+           -1.998445144003874,
+           -2.1264681533570537,
+           -2.2503171690214923,
+           -2.367536320990393,
+           -2.475788186276085,
+           -2.5729041148710436,
+           -2.656930617307957,
+           -2.7261707456386657,
+           -2.7792195204893426,
+           -2.8149926003226584,
+           -2.832747551632295,
+           -2.832097256531482,
+           -2.8130151827277823,
+           -2.775832435593954,
+           -2.7212267081954993,
+           -2.6502034379362263,
+           -2.564069663238986,
+           -2.46440124589881,
+           -2.353004280253491,
+           -2.2318716453528875,
+           -2.1031357676223172,
+           -1.9690187464463098,
+           -1.8317810516386035,
+           -1.6936700286075694,
+           -1.5568694436017882,
+           -1.423451267903431,
+           -1.2953308371451635,
+           -1.1742264316934508,
+           -1.0616242085796825,
+           -0.9587492776993415,
+           -0.8665435584132027,
+           -0.7856508812055216,
+           -0.7164096169744537,
+           -0.6588529283945349,
+           -0.6127165482848,
+           -0.5774538037468072,
+           -0.5522574266192215,
+           -0.5360875249355452,
+           -0.5277049406583135,
+           -0.525709089666828,
+           -0.528579273957548,
+           -0.5347183758505141,
+           -0.5424977916053288,
+           -0.5503024384622658,
+           -0.5565746752370849,
+           -0.5598560119726329,
+           -0.5588255478149468,
+           -0.5523341665588986,
+           -0.5394336338566567,
+           -0.5193998759556934,
+           -0.4917498735551374,
+           -0.4562517720210985,
+           -0.412927986519552,
+           -0.36205126310861857,
+           -0.30413383985516457,
+           -0.2399100309693407,
+           -0.1703127272584411,
+           -0.09644446358194315,
+           -0.019543844465415895,
+           0.05905176094738815,
+           0.1379462468904833,
+           0.215726443598408,
+           0.29100431334035,
+           0.3624585345572847,
+           0.4288743538638483,
+           0.48918062953720887,
+           0.542483061667448,
+           0.588092701591538,
+           0.6255489541254954,
+           0.6546364274044489,
+           0.6753951432796215,
+           0.6881237922185214,
+           0.6933758961963391,
+           0.6919489266191325,
+           0.6848666072428746,
+           0.6733548097164613,
+           0.6588116172766774,
+           0.6427722859926097,
+           0.6268699688754117,
+           0.6127931826598351,
+           0.6022410871811334,
+           0.5968777106752234,
+           0.5982862893464231,
+           0.6079248952084725,
+           0.627084502276388,
+           0.6568505881739387,
+           0.6980692873571712,
+           0.7513190053697782,
+           0.8168882734235855,
+           0.8947604723074498,
+           0.9846058878503857,
+           1.0857813809990025,
+           1.1973377684317994,
+           1.3180348191489033,
+           1.4463635833642097,
+           1.5805755869828246,
+           1.7187182525263434,
+           1.8586757498741486,
+           1.9982143415625615,
+           2.1350311711100995,
+           2.2668053518539146,
+           2.391250150409921,
+           2.506165024749421,
+           2.609486272941887,
+           2.6993350750281437,
+           2.7740617666939644,
+           2.832285268109305,
+           2.872926702477916,
+           2.8952363738462012,
+           2.898813429298639,
+           2.8836177030599264,
+           2.849973425052689,
+           2.7985646696303292,
+           2.730422616818316,
+           2.646904893665895,
+           2.549667452473394,
+           2.4406296211042475,
+           2.3219331239602425,
+           2.195896016504775
+          ],
+          [
+           2.1049642109158984,
+           1.9730315362716981,
+           1.8403695960982234,
+           1.7094989937098195,
+           1.582870527703839,
+           1.4628123002351965,
+           1.351479719164523,
+           1.2508095500730625,
+           1.1624790764489656,
+           1.0878713032954639,
+           1.028046994004915,
+           0.983724166142877,
+           0.9552654928094383,
+           0.9426738668661561,
+           0.9455961901616533,
+           0.9633352537195453,
+           0.9948693824505503,
+           1.0388793339996365,
+           1.0937817703084398,
+           1.1577684665090424,
+           1.2288502885882087,
+           1.3049048620753592,
+           1.3837267714219676,
+           1.463079075704991,
+           1.5407449020466208,
+           1.6145778842056318,
+           1.6825502499227787,
+           1.7427974258147017,
+           1.7936581212126963,
+           1.8337089699675286,
+           1.861792948908975,
+           1.8770409498409795,
+           1.878886054701589,
+           1.867070246501451,
+           1.8416434773120947,
+           1.8029552042118338,
+           1.7516386900056644,
+           1.6885885431122323,
+           1.6149321358692617,
+           1.5319956885888144,
+           1.4412659343615803,
+           1.3443483837480423,
+           1.2429232865796558,
+           1.1387004382562982,
+           1.0333739989990924,
+           0.9285784860611088,
+           0.8258470612121978,
+           0.7265731699285483,
+           0.631976496366603,
+           0.543074081778514,
+           0.46065731652536357,
+           0.3852753607816605,
+           0.3172253803520396,
+           0.25654980602673394,
+           0.20304064210260475,
+           0.15625066672303087,
+           0.11551118817364227,
+           0.07995585172585898,
+           0.04854983533087458,
+           0.020123633380578845,
+           -0.00658949061927799,
+           -0.03291339628634913,
+           -0.06018738590683675,
+           -0.08972407443559684,
+           -0.12276794499219756,
+           -0.16045570762870304,
+           -0.2037795331520024,
+           -0.25355416021823307,
+           -0.3103887746299117,
+           -0.37466443725743304,
+           -0.44651769436178457,
+           -0.525830844910339,
+           -0.6122291677675289,
+           -0.7050852317415156,
+           -0.8035302279217047,
+           -0.9064720811923442,
+           -1.0126199208775086,
+           -1.1205143236505934,
+           -1.228562589367715,
+           -1.3350781762460453,
+           -1.4383233092404537,
+           -1.5365536874726584,
+           -1.6280641554227906,
+           -1.7112341699219826,
+           -1.7845718916937192,
+           -1.8467557564554133,
+           -1.896672435844941,
+           -1.9334501813884613,
+           -1.9564866533902006,
+           -1.9654704683695081,
+           -1.9603958502817131,
+           -1.9415699385206484,
+           -1.9096124854848777,
+           -1.865447863860847,
+           -1.8102894940994412,
+           -1.7456169911189525,
+           -1.6731465113714514,
+           -1.5947949525246965,
+           -1.512638813864021,
+           -1.4288686622025648,
+           -1.3457402621646746,
+           -1.2655235182885778,
+           -1.190450437217538,
+           -1.1226633497316196,
+           -1.0641646336537025,
+           -1.016769149626629,
+           -0.9820605430327698,
+           -0.9613524782757237,
+           -0.9556557583287222,
+           -0.9656521455878321,
+           -0.9916755429462218,
+           -1.0337010204270634,
+           -1.0913419868856549,
+           -1.1638556127306283,
+           -1.2501564130296459,
+           -1.3488377055462233,
+           -1.458200469952116,
+           -1.5762889572694874,
+           -1.700932236845616,
+           -1.8297907258013668,
+           -1.9604066264020465,
+           -2.0902571030952593,
+           -2.2168089653351064,
+           -2.3375735863680354,
+           -2.4501607827692458,
+           -2.552330404818244,
+           -2.642040443165001,
+           -2.7174905413058497,
+           -2.7771599141000096,
+           -2.819838807201506,
+           -2.844652787561031,
+           -2.8510793272684194,
+           -2.8389563277503673,
+           -2.808482424195479,
+           -2.7602091063412026,
+           -2.695024886637984,
+           -2.6141319355579364,
+           -2.519015781847997,
+           -2.4114088385196726,
+           -2.293248659373673,
+           -2.1666319524050466,
+           -2.0337654726070626,
+           -1.896914985203954,
+           -1.7583535295910482,
+           -1.6203102233672106,
+           -1.484920824673729,
+           -1.35418122021681,
+           -1.2299049271898401,
+           -1.1136855918628898,
+           -1.0068653385536193,
+           -0.9105096732943908,
+           -0.8253894805203981,
+           -0.7519704726800386,
+           -0.6904102662671029,
+           -0.6405630680376222,
+           -0.6019917668176552,
+           -0.5739870440016707,
+           -0.5555929440939862,
+           -0.545638189693952,
+           -0.5427723870283666,
+           -0.5455061518776643,
+           -0.5522540943551415,
+           -0.5613795366840537,
+           -0.571239802399034,
+           -0.5802309090818513,
+           -0.5868305198968973,
+           -0.5896380611518001,
+           -0.587410992486411,
+           -0.5790963210188342,
+           -0.5638565781478962,
+           -0.5410896244626983,
+           -0.5104418105951972,
+           -0.47181419573840355,
+           -0.425361706524559,
+           -0.37148530242613714,
+           -0.31081739516189566,
+           -0.24420094417349358,
+           -0.1726628136725167,
+           -0.09738212491394548,
+           -0.019654466489032248,
+           0.05914706771198664,
+           0.13761296133672152,
+           0.21433937284067708,
+           0.28797011441857256,
+           0.35723738251878784,
+           0.4210001415914878,
+           0.4782791226889906,
+           0.5282874852362172,
+           0.5704563015379668,
+           0.6044541565863207,
+           0.6302003071244436,
+           0.6478710098950875,
+           0.657898805365267,
+           0.6609647255191898,
+           0.6579835779415195,
+           0.6500826387252565,
+           0.6385742591629922,
+           0.6249230513389484,
+           0.6107084615554099,
+           0.5975836643282391,
+           0.5872318102955397,
+           0.5813207362008385,
+           0.5814572921790226,
+           0.5891424596227569,
+           0.6057284213965872,
+           0.6323787052914405,
+           0.6700324523045555,
+           0.7193737652324667,
+           0.7808069724936912,
+           0.8544384999852043,
+           0.9400658835986334,
+           1.0371742807122255,
+           1.1449406548280878,
+           1.2622456180901882,
+           1.3876927263888699,
+           1.5196348358490583,
+           1.6562069523370773,
+           1.7953648416244494,
+           1.9349285211185503,
+           2.072629628292996,
+           2.206161559299365,
+           2.3332311962987617,
+           2.451610995746182,
+           2.559190193417682,
+           2.654023895881075,
+           2.7343788721177553,
+           2.7987749321078685,
+           2.846020879675001,
+           2.875244152355352,
+           2.8859134084969447,
+           2.8778534876482262,
+           2.8512523505468557,
+           2.806659795293421,
+           2.744977941964782,
+           2.6674436742231915,
+           2.575603418625732,
+           2.4712808256457612,
+           2.356538086409687,
+           2.233631771676345,
+           2.104964210915902
+          ],
+          [
+           2.013144360605829,
+           1.8813227930187426,
+           1.7504158909221754,
+           1.6229072382158376,
+           1.5011776379574115,
+           1.3874538096602989,
+           1.2837606849527599,
+           1.19187840311719,
+           1.1133049949998575,
+           1.0492256070845498,
+           1.0004889605020841,
+           0.9675915662407331,
+           0.950670032070562,
+           0.9495016032338484,
+           0.9635128825052898,
+           0.9917964805787882,
+           1.0331351596317717,
+           1.086032855926506,
+           1.1487518057249368,
+           1.2193548565293264,
+           1.295751926144991,
+           1.375749478159124,
+           1.4571018163720866,
+           1.5375629640469544,
+           1.6149378873761284,
+           1.687131846371874,
+           1.7521967097963278,
+           1.8083731523531663,
+           1.854127760072635,
+           1.8881842008990657,
+           1.9095477686292615,
+           1.9175227757566304,
+           1.9117224502612273,
+           1.8920711784720277,
+           1.8587991261587393,
+           1.8124294582680103,
+           1.75375855953938,
+           1.6838298291267844,
+           1.603901778100535,
+           1.5154112954873162,
+           1.419933062977089,
+           1.3191361878042396,
+           1.2147391854455682,
+           1.1084644772034997,
+           1.0019935717126471,
+           0.8969240739120339,
+           0.7947296107910264,
+           0.6967236816886507,
+           0.6040283342284019,
+           0.5175484378552057,
+           0.4379521787164469,
+           0.36565823607727244,
+           0.3008299257428104,
+           0.2433764145121106,
+           0.1929609261090891,
+           0.14901567797125934,
+           0.11076311430567662,
+           0.07724283833864637,
+           0.047343499793498924,
+           0.019838766035932928,
+           -0.006573599752546872,
+           -0.033230609925947084,
+           -0.06146198253575047,
+           -0.0925482638126598,
+           -0.1276802715798357,
+           -0.16792095431419282,
+           -0.21417069853317358,
+           -0.2671370285644026,
+           -0.3273095297882552,
+           -0.3949406919767195,
+           -0.47003321677737825,
+           -0.5523341665588982,
+           -0.6413361549563176,
+           -0.7362855969999017,
+           -0.8361978532946711,
+           -0.9398789229828117,
+           -1.045953168725331,
+           -1.1528963980387774,
+           -1.259073483063859,
+           -1.3627795788599015,
+           -1.4622839017435483,
+           -1.5558749565715635,
+           -1.6419060571088206,
+           -1.7188399679321533,
+           -1.7852915101808027,
+           -1.8400670166186668,
+           -1.8821995929324566,
+           -1.9109792402536074,
+           -1.9259770161925927,
+           -1.9270625552336436,
+           -1.9144144306406383,
+           -1.8885230151054575,
+           -1.8501856819104598,
+           -1.800494377813846,
+           -1.7408157885048636,
+           -1.6727645026039313,
+           -1.5981697561906554,
+           -1.519036502336203,
+           -1.437501695026549,
+           -1.355786800547383,
+           -1.2761476487350951,
+           -1.2008228089520712,
+           -1.1319817193488002,
+           -1.0716738117665512,
+           -1.0217798580850943,
+           -0.9839667172510917,
+           -0.9596465866951427,
+           -0.9499417591360458,
+           -0.9556557583287224,
+           -0.9772515781993129,
+           -1.0148375826271385,
+           -1.0681614419277121,
+           -1.136612291263582,
+           -1.2192311004019776,
+           -1.3147290482196143,
+           -1.4215135039055387,
+           -1.5377210346052694,
+           -1.6612566907341069,
+           -1.7898386694825499,
+           -1.9210473278269231,
+           -2.0523774118040317,
+           -2.1812922914673454,
+           -2.305278942706683,
+           -2.4219023991635225,
+           -2.528858410249003,
+           -2.6240230844582095,
+           -2.705498369715003,
+           -2.771652322600672,
+           -2.8211532435668536,
+           -2.852996902544285,
+           -2.8665262451313773,
+           -2.8614431497280317,
+           -2.8378119961687616,
+           -2.7960550019618413,
+           -2.7369394783881047,
+           -2.6615573506749923,
+           -2.5712974695677513,
+           -2.4678114114229524,
+           -2.3529736163347232,
+           -2.2288368450903016,
+           -2.097584042781576,
+           -1.9614777771167982,
+           -1.8228084709898211,
+           -1.6838426704894267,
+           -1.5467725808236927,
+           -1.4136680638963923,
+           -1.286432223545653,
+           -1.1667616094947464,
+           -1.0561119512925181,
+           -0.9556701919676486,
+           -0.8663334313473969,
+           -0.788695215002088,
+           -0.7230394209180191,
+           -0.6693418068549013,
+           -0.627279091611179,
+           -0.5962452578072646,
+           -0.57537458689521,
+           -0.5635707732796013,
+           -0.559541317718879,
+           -0.5618362741652088,
+           -0.5688903219669671,
+           -0.5790670593744991,
+           -0.5907043663708034,
+           -0.6021596661040854,
+           -0.6118539250076545,
+           -0.6183132716944679,
+           -0.6202071828195382,
+           -0.616382278522908,
+           -0.6058908883534027,
+           -0.5880136876889722,
+           -0.5622758610568895,
+           -0.5284564184317627,
+           -0.48659046923961463,
+           -0.4369644418907615,
+           -0.38010441956572705,
+           -0.31675794106004745,
+           -0.24786978425466052,
+           -0.174552404956733,
+           -0.09805184153421867,
+           -0.019710012472919695,
+           0.05907557322594736,
+           0.13689360635648806,
+           0.21236114347596702,
+           0.2841650137849103,
+           0.35110135163236195,
+           0.4121121874780636,
+           0.4663181057114552,
+           0.5130460788401777,
+           0.5518517116697769,
+           0.5825352730717298,
+           0.6051510531468224,
+           0.6200097559915366,
+           0.6276738185120128,
+           0.6289457292473439,
+           0.6248496033177656,
+           0.6166064457887077,
+           0.6056037014678054,
+           0.5933598402143607,
+           0.581484859386907,
+           0.5716376956908527,
+           0.5654816245652396,
+           0.5646387841320643,
+           0.5706449910628738,
+           0.5849060166471811,
+           0.6086564627621983,
+           0.6429223199683839,
+           0.6884882049390739,
+           0.7458701639150378,
+           0.8152947955375835,
+           0.896685293513547,
+           0.9896548408543776,
+           1.0935076070639798,
+           1.2072474120805743,
+           1.3295939306500455,
+           1.4590061228404794,
+           1.5937123952749486,
+           1.7317468278780057,
+           1.8709906467461224,
+           2.009217989031044,
+           2.1441448938615264,
+           2.2734803671599737,
+           2.394978309941535,
+           2.5064890708364396,
+           2.6060093849493478,
+           2.69172949281621,
+           2.76207629444619,
+           2.8157514828210655,
+           2.851763716647065,
+           2.869454030850731,
+           2.868513841939971,
+           2.8489950800774344,
+           2.8113121662984035,
+           2.756235747214783,
+           2.6848782960604924,
+           2.5986718832619715,
+           2.499338607119932,
+           2.388854351088726,
+           2.2694066942408724,
+           2.143347941892298,
+           2.013144360605833
+          ],
+          [
+           1.9212133030571439,
+           1.790612265646713,
+           1.6625503963191206,
+           1.5394532594355383,
+           1.4236115400330118,
+           1.3171317641755291,
+           1.2218912917049258,
+           1.139498619116673,
+           1.0712599028734429,
+           1.0181524642863793,
+           0.9808058697858663,
+           0.9594909990577029,
+           0.954117322564828,
+           0.9642384140688329,
+           0.9890655276858713,
+           1.0274888775339195,
+           1.0781060758100058,
+           1.1392570166014013,
+           1.2090643419666476,
+           1.285478497461515,
+           1.3663262794412103,
+           1.449361698645819,
+           1.5323179356051704,
+           1.612959144403545,
+           1.689130872705636,
+           1.7588079072969558,
+           1.820138424630112,
+           1.8714834231793398,
+           1.9114505363114327,
+           1.9389214678023694,
+           1.953072453461153,
+           1.9533873275268874,
+           1.939662957208864,
+           1.9120069983442989,
+           1.8708281149451673,
+           1.8168189906913041,
+           1.7509326366210956,
+           1.6743526620295486,
+           1.5884583209056584,
+           1.494785270569084,
+           1.3949830794724678,
+           1.2907705949978663,
+           1.183890327735235,
+           1.0760630251366132,
+           0.9689435942726858,
+           0.864079491099101,
+           0.7628726233164578,
+           0.6665457174266004,
+           0.5761139804463609,
+           0.4923627460238513,
+           0.41583163700789744,
+           0.34680560586424486,
+           0.2853130350478069,
+           0.2311308960740344,
+           0.1837967832264132,
+           0.14262746021342687,
+           0.10674339013386337,
+           0.07509856506323118,
+           0.04651481532170449,
+           0.019719663460038023,
+           -0.006613302897837206,
+           -0.03382262969950598,
+           -0.06321689338517185,
+           -0.09603343036620993,
+           -0.13339901169489235,
+           -0.1762935253206991,
+           -0.22551765076816843,
+           -0.28166540814624463,
+           -0.34510233770703275,
+           -0.415949920885169,
+           -0.49407669253555736,
+           -0.5790963210188333,
+           -0.6703727522342281,
+           -0.7670323302348171,
+           -0.8679826253248456,
+           -0.9719375251393125,
+           -1.077447979595131,
+           -1.1829376409686778,
+           -1.2867425095138691,
+           -1.38715358633951,
+           -1.4824614515152355,
+           -1.5710016287518527,
+           -1.6511995700073057,
+           -1.7216140947926912,
+           -1.7809781498465476,
+           -1.8282358145256674,
+           -1.8625745643207123,
+           -1.8834519172510964,
+           -1.890615722796154,
+           -1.8841175071791063,
+           -1.864318458449954,
+           -1.8318878157318903,
+           -1.7877936147310922,
+           -1.7332859315100337,
+           -1.6698729538732078,
+           -1.599290389847576,
+           -1.5234648911627475,
+           -1.4444723221329596,
+           -1.3644918370848345,
+           -1.2857568391129044,
+           -1.2105039766954218,
+           -1.1409213904163207,
+           -1.0790974482548217,
+           -1.026971203887124,
+           -0.9862857782045782,
+           -0.9585458005457589,
+           -0.9449799544491928,
+           -0.9465095552351954,
+           -0.9637239462343873,
+           -0.9968633403826523,
+           -1.0458095580709394,
+           -1.1100849248390667,
+           -1.188859398289364,
+           -1.2809657971977182,
+           -1.384922812005215,
+           -1.4989652894131478,
+           -1.6210811092326876,
+           -1.7490538132256466,
+           -1.8805100072894407,
+           -2.0129704433743654,
+           -2.1439035987899158,
+           -2.2707805102326133,
+           -2.391129589430099,
+           -2.502590147492481,
+           -2.602963385890103,
+           -2.690259672684919,
+           -2.7627410117473987,
+           -2.8189577280141846,
+           -2.857778530564699,
+           -2.8784132740268706,
+           -2.8804279136848,
+           -2.8637513363834404,
+           -2.8286739433496617,
+           -2.775838057642439,
+           -2.7062204233167706,
+           -2.621107250805004,
+           -2.522062438930764,
+           -2.410889764107891,
+           -2.289589967765887,
+           -2.1603137904988934,
+           -2.025312093042427,
+           -1.8868842677659263,
+           -1.7473261784477427,
+           -1.6088788699182865,
+           -1.4736792627090964,
+           -1.3437139918681964,
+           -1.220777465058569,
+           -1.1064351051002597,
+           -1.00199260903393,
+           -0.9084719029279561,
+           -0.8265943028552092,
+           -0.7567712119489018,
+           -0.6991024957088194,
+           -0.6533824874380629,
+           -0.6191133875668413,
+           -0.5955256393201811,
+           -0.5816046931866755,
+           -0.5761234181311479,
+           -0.5776792822559987,
+           -0.5847353129571552,
+           -0.595663759274323,
+           -0.6087913191985519,
+           -0.6224447635819766,
+           -0.6349957866821405,
+           -0.6449039412153651,
+           -0.6507565723034822,
+           -0.651304748373853,
+           -0.6454942957349123,
+           -0.6324911743982738,
+           -0.6117005824019506,
+           -0.582779340589799,
+           -0.5456412853308338,
+           -0.5004555785645715,
+           -0.4476380282266639,
+           -0.3878356928961925,
+           -0.3219052178431939,
+           -0.2508855111655858,
+           -0.17596551431377566,
+           -0.098447947337105,
+           -0.019710012472919695,
+           0.05883788236497381,
+           0.1357942680184276,
+           0.20980849221986222,
+           0.27962120431255166,
+           0.34410235549589197,
+           0.40228568763722045,
+           0.4533987742206547,
+           0.49688779167425484,
+           0.5324363352359263,
+           0.5599777472546642,
+           0.5797005934951528,
+           0.592047100384354,
+           0.5977045487244995,
+           0.5975898025780221,
+           0.5928273311664821,
+           0.5847212521736217,
+           0.5747220824683495,
+           0.5643890229515444,
+           0.5553487243852769,
+           0.5492515775986094,
+           0.5477266418822847,
+           0.5523363678379821,
+           0.5645322842868418,
+           0.5856128026442815,
+           0.6166842467503988,
+           0.6586261425560113,
+           0.7120617020588823,
+           0.7773343118822731,
+           0.8544906919125858,
+           0.9432712270184713,
+           1.043107799057039,
+           1.1531292614735913,
+           1.2721745093959762,
+           1.3988129089116552,
+           1.5313716649000706,
+           1.6679695319686596,
+           1.8065561120763498,
+           1.944955839358966,
+           2.0809156310967225,
+           2.2121550867604145,
+           2.3364180471153184,
+           2.4515242842599254,
+           2.5554200823328173,
+           2.646226487798136,
+           2.722284057335243,
+           2.782193009287324,
+           2.8248477895325452,
+           2.849465192026049,
+           2.8556053250120432,
+           2.8431848823817463,
+           2.8124823617728896,
+           2.7641350623464507,
+           2.6991278910806615,
+           2.61877420211721,
+           2.5246890844057797,
+           2.418755693964053,
+           2.3030853940754463,
+           2.179972615602957,
+           2.0518454766619727,
+           1.9212133030571474
+          ],
+          [
+           1.8299488166159816,
+           1.701667406264156,
+           1.5775164941329887,
+           1.459843115792757,
+           1.3508284782181388,
+           1.2524411201067749,
+           1.1663949824841173,
+           1.0941133547462762,
+           1.0366995205747327,
+           0.9949147677497809,
+           0.9691642497104203,
+           0.9594909990577026,
+           0.9655781986547375,
+           0.9867596192829639,
+           1.022037938762466,
+           1.0701104707557045,
+           1.1294016566848146,
+           1.1981015155408077,
+           1.274209107685236,
+           1.355579953382033,
+           1.4399762575127242,
+           1.52511873084022,
+           1.6087387667168287,
+           1.6886297309717855,
+           1.7626961518065472,
+           1.828999655071663,
+           1.8858005767726633,
+           1.9315942968443114,
+           1.9651414733032577,
+           1.9854915104405626,
+           1.9919987648758282,
+           1.984331174814881,
+           1.9624711862124988,
+           1.9267090400610831,
+           1.8776286729830667,
+           1.8160866640511277,
+           1.7431848298374446,
+           1.6602372229426339,
+           1.5687324229207449,
+           1.470292119338308,
+           1.3666270719981617,
+           1.2594915910796411,
+           1.1506377087441535,
+           1.0417702130019466,
+           0.9345036844436332,
+           0.8303226176552483,
+           0.7305456233179777,
+           0.6362945963757388,
+           0.5484696030848653,
+           0.46773008863399995,
+           0.39448284119222893,
+           0.3288769719250924,
+           0.2708059881837807,
+           0.2199168533396518,
+           0.17562574625018565,
+           0.13714006066246628,
+           0.10348602434364199,
+           0.07354117342181817,
+           0.04607079296110665,
+           0.01976733331458074,
+           -0.006708264148573962,
+           -0.03468444685184956,
+           -0.06543727111520868,
+           -0.10015008801014852,
+           -0.13987578220823477,
+           -0.1855025849088753,
+           -0.2377243895065245,
+           -0.29701638229833005,
+           -0.36361666317991553,
+           -0.43751437639943336,
+           -0.5184447029516127,
+           -0.6058908883534025,
+           -0.6990932968490814,
+           -0.797065300170039,
+           -0.8986156304580794,
+           -1.0023766573809192,
+           -1.1068378931353855,
+           -1.2103838899312904,
+           -1.3113355762336028,
+           -1.4079939835522302,
+           -1.4986852473540018,
+           -1.5818057255219853,
+           -1.655866066793762,
+           -1.7195330801350492,
+           -1.7716683036711989,
+           -1.8113622474998008,
+           -1.8379633866321883,
+           -1.851101105989783,
+           -1.850701945744183,
+           -1.8369986587452898,
+           -1.8105317683030753,
+           -1.7721434998143673,
+           -1.7229641490678445,
+           -1.6643911388173036,
+           -1.5980611986874513,
+           -1.5258162770912211,
+           -1.4496639532501951,
+           -1.371733258620157,
+           -1.294226936474402,
+           -1.2193712630617835,
+           -1.14936462121521,
+           -1.086326055787841,
+           -1.0322450487994634,
+           -0.9889337303841588,
+           -0.9579826899891973,
+           -0.9407214719690531,
+           -0.9381847326404473,
+           -0.9510849045712643,
+           -0.9797920615251385,
+           -1.0243215077553562,
+           -1.084329432350392,
+           -1.1591167775251052,
+           -1.2476412737954772,
+           -1.3485373996476893,
+           -1.4601438333817813,
+           -1.5805377849163238,
+           -1.707575429882159,
+           -1.8389375213591763,
+           -1.9721791297191937,
+           -2.1047823612904786,
+           -2.234210834401726,
+           -2.357964648566427,
+           -2.4736345701862126,
+           -2.578954176492426,
+           -2.671848748065739,
+           -2.750479777989578,
+           -2.813284070608003,
+           -2.8590065324106497,
+           -2.886725908592412,
+           -2.895872887645482,
+           -2.8862401788147602,
+           -2.8579843589310743,
+           -2.8116194813549327,
+           -2.748002635734486,
+           -2.6683118382336346,
+           -2.5740168131767973,
+           -2.4668433942852706,
+           -2.3487324227964357,
+           -2.2217941471614844,
+           -2.0882592316483266,
+           -1.950427556585823,
+           -1.8106160393975033,
+           -1.6711067219287514,
+           -1.5340963555519667,
+           -1.4016486715697751,
+           -1.2756504516930782,
+           -1.1577724137214753,
+           -1.0494358035316118,
+           -0.9517854392119149,
+           -0.8656697903172867,
+           -0.7916284988270319,
+           -0.7298875628724458,
+           -0.6803622142712918,
+           -0.6426673310805286,
+           -0.6161350414558471,
+           -0.5998389996544364,
+           -0.5926246533576859,
+           -0.593144677593045,
+           -0.5998986279178042,
+           -0.6112757671740925,
+           -0.6255999484049933,
+           -0.6411753931388076,
+           -0.6563321901944731,
+           -0.6694703556945947,
+           -0.6791013396125631,
+           -0.6838859367200264,
+           -0.6826676583383461,
+           -0.6745007432834726,
+           -0.658672128696741,
+           -0.6347168604391173,
+           -0.6024265943466476,
+           -0.5618510195422033,
+           -0.5132922186143513,
+           -0.45729216216201146,
+           -0.39461371234671644,
+           -0.3262156772205804,
+           -0.2532226104919709,
+           -0.1768901861990449,
+           -0.09856709108827215,
+           -0.019654466489032255,
+           0.058436006101306184,
+           0.13432424722233627,
+           0.2067030156570772,
+           0.2743771286857301,
+           0.33629960878377424,
+           0.3916037787041536,
+           0.4396304316070655,
+           0.47994933015958097,
+           0.5123744351066032,
+           0.5369724260109328,
+           0.554064250574552,
+           0.5642196197932224,
+           0.568244549586379,
+           0.5671622308395656,
+           0.5621876844003124,
+           0.5546968210461966,
+           0.5461906746354525,
+           0.5382557057739872,
+           0.5325211800793699,
+           0.5306147067404036,
+           0.5341170774343938,
+           0.5445175713273467,
+           0.5631708881162832,
+           0.5912568378846981,
+           0.6297438546760349,
+           0.6793573116091705,
+           0.7405535012112182,
+           0.8135000082046802,
+           0.89806304659902,
+           0.9938021624221506,
+           1.0999725219924845,
+           1.2155348177656489,
+           1.339172634151159,
+           1.4693169289969794,
+           1.6041771073360387,
+           1.7417779969520248,
+           1.8800018845362052,
+           2.016634640463844,
+           2.149414852820157,
+           2.2760848099827773,
+           2.3944421179133513,
+           2.5023907147238553,
+           2.597990051736522,
+           2.6795012470754993,
+           2.745429083996245,
+           2.7945588201306832,
+           2.825986893371403,
+           2.839144752370343,
+           2.833815201157293,
+           2.810140824281617,
+           2.768624246853643,
+           2.7101201783383146,
+           2.6358193851955507,
+           2.5472249306821384,
+           2.4461212056105364,
+           2.33453644706758,
+           2.214699598793149,
+           2.088992503270599,
+           1.9598985282465562,
+           1.8299488166159854
+          ],
+          [
+           1.7401230401352867,
+           1.6152407286294577,
+           1.4960336096545552,
+           1.3847503451267138,
+           1.2834442301504583,
+           1.1939291895757096,
+           1.1177412811787082,
+           1.0561065898796413,
+           1.009916244576726,
+           0.979709118902633,
+           0.965662593649478,
+           0.9675915662407331,
+           0.9849556961424645,
+           1.0168746792891674,
+           1.0621511542171802,
+           1.1193006622789967,
+           1.186587918430481,
+           1.262068501656257,
+           1.3436349486843777,
+           1.429066134252522,
+           1.5160787482180502,
+           1.6023796359695124,
+           1.6857177548950335,
+           1.763934516347977,
+           1.8350113291289993,
+           1.8971132357476939,
+           1.9486276347043918,
+           1.988197208156393,
+           2.014746321425733,
+           2.0275003251797425,
+           2.025997368664361,
+           2.010092518670304,
+           1.9799541693339195,
+           1.9360529176967072,
+           1.8791432644741486,
+           1.810238674162239,
+           1.730580689139739,
+           1.641602934868025,
+           1.5448909741688175,
+           1.4421390649376786,
+           1.335104945208643,
+           1.2255638105766233,
+           1.1152626606759697,
+           1.0058761735078354,
+           0.8989652194468821,
+           0.7959390520049723,
+           0.6980221118437079,
+           0.6062262567089448,
+           0.5213290860856167,
+           0.4438588691135742,
+           0.37408641174248214,
+           0.31202401861573975,
+           0.25743152133171604,
+           0.20982916218490794,
+           0.16851694585066224,
+           0.1325999052016553,
+           0.10101857572357258,
+           0.07258383965242139,
+           0.04601518934179849,
+           0.019981372291020785,
+           -0.006857680089605444,
+           -0.03580877001989223,
+           -0.0681043303255324,
+           -0.10486340795799885,
+           -0.14705578671054803,
+           -0.19547022026745844,
+           -0.25068764021490303,
+           -0.31306007483293724,
+           -0.3826958666355741,
+           -0.4594516134678331,
+           -0.5429310836307726,
+           -0.6324911743982735,
+           -0.7272547999972396,
+           -0.8261304142898414,
+           -0.9278376996093523,
+           -1.030938790875004,
+           -1.1338742573784564,
+           -1.2350029372408222,
+           -1.3326446147501199,
+           -1.4251244513072547,
+           -1.5108180286056996,
+           -1.5881958393343754,
+           -1.6558660667937617,
+           -1.7126145302849014,
+           -1.757440737166154,
+           -1.7895890735534832,
+           -1.808574281566816,
+           -1.8142005089718483,
+           -1.8065733736517322,
+           -1.7861046567114685,
+           -1.7535094199374026,
+           -1.709795531300162,
+           -1.6562457715358958,
+           -1.5943928808570897,
+           -1.5259880828916594,
+           -1.4529637885762,
+           -1.3773913317830477,
+           -1.3014347171899192,
+           -1.2273014660496462,
+           -1.1571917244072283,
+           -1.0932468489076967,
+           -1.0374987063022585,
+           -0.9918209134830703,
+           -0.9578832054956437,
+           -0.9371100503725478,
+           -0.9306445334063344,
+           -0.9393184119202818,
+           -0.9636290976184995,
+           -1.0037241606747114,
+           -1.0593937717964887,
+           -1.1300713098986501,
+           -1.2148421683249366,
+           -1.312460596516038,
+           -1.4213742214186653,
+           -1.5397557084705666,
+           -1.665540850191135,
+           -1.7964722154618622,
+           -1.9301473582910451,
+           -2.0640704745153022,
+           -2.195706311204325,
+           -2.322535078561697,
+           -2.4421070892072105,
+           -2.5520958555038984,
+           -2.6503484119229,
+           -2.734931695440923,
+           -2.8041739110313997,
+           -2.856699929147859,
+           -2.891459904782582,
+           -2.9077504697330414,
+           -2.905228027168338,
+           -2.8839138661281782,
+           -2.8441910086097675,
+           -2.7867928986502823,
+           -2.712784236502995,
+           -2.6235344469223296,
+           -2.520684444201374,
+           -2.4061075137358725,
+           -2.2818652667226003,
+           -2.150159737841786,
+           -2.013282782711537,
+           -1.8735639904758252,
+           -1.7333183557352934,
+           -1.5947949525246958,
+           -1.46012782130148,
+           -1.3312902188009814,
+           -1.2100532917200228,
+           -1.0979501207787954,
+           -0.9962459446725517,
+           -0.9059152172021707,
+           -0.8276259793765037,
+           -0.7617318457871504,
+           -0.7082717156088966,
+           -0.6669771278664721,
+           -0.6372869928537467,
+           -0.6183692514340126,
+           -0.6091488458297853,
+           -0.6083412335586059,
+           -0.6144905441080374,
+           -0.6260113689856283,
+           -0.6412330925636531,
+           -0.6584456156526527,
+           -0.6759452972757709,
+           -0.6920799432449157,
+           -0.7052917026876824,
+           -0.714156794734309,
+           -0.7174210755299284,
+           -0.7140305683028392,
+           -0.7031562134967608,
+           -0.6842122485284222,
+           -0.6568677936732934,
+           -0.621051397670169,
+           -0.5769484793794546,
+           -0.5249917856054872,
+           -0.4658451653551656,
+           -0.4003811328056589,
+           -0.3296528507553691,
+           -0.2548613093159652,
+           -0.17731859746997247,
+           -0.09840826477767205,
+           -0.0195438444654159,
+           0.05787334448998618,
+           0.13249598100934107,
+           0.20307098752457725,
+           0.2684771541572197,
+           0.3277591262639764,
+           0.3801568344620559,
+           0.4251295642794444,
+           0.4623740013453113,
+           0.4918357440350152,
+           0.5137139447682845,
+           0.528458919446706,
+           0.5367627472960212,
+           0.5395430660211613,
+           0.5379204450575149,
+           0.5331898882954965,
+           0.5267871726799805,
+           0.5202508665899893,
+           0.515180988370472,
+           0.5131953578235952,
+           0.5158847594769761,
+           0.5247680742951946,
+           0.5412485451566837,
+           0.5665723205788398,
+           0.6017903712763419,
+           0.6477247963465156,
+           0.704940432056711,
+           0.7737225488825665,
+           0.8540612747262071,
+           0.9456432177595238,
+           1.0478505851455602,
+           1.159767908373099,
+           1.2801962966950848,
+           1.4076749518936964,
+           1.5405094949926634,
+           1.676806483160537,
+           1.8145133372125737,
+           1.9514627607879693,
+           2.0854206149683816,
+           2.2141361197893157,
+           2.3353931891416213,
+           2.447061669658929,
+           2.547147248314276,
+           2.6338388178432663,
+           2.7055521432609506,
+           2.76096875540042,
+           2.7990691066209403,
+           2.8191591570037113,
+           2.8208897132694846,
+           2.804268013594436,
+           2.7696612353237176,
+           2.7177917948179346,
+           2.6497245046347175,
+           2.566845848166665,
+           2.4708358209680332,
+           2.363632966683221,
+           2.2473933993688995,
+           2.124444749064952,
+           1.9972360901631017,
+           1.8682850094361112,
+           1.7401230401352905
+          ],
+          [
+           1.652495940330713,
+           1.5320634415439252,
+           1.4187911249579335,
+           1.314810266257109,
+           1.2220288970603428,
+           1.1420910099915766,
+           1.0763418201177937,
+           1.0257998789457965,
+           0.9911366735139356,
+           0.9726641644148165,
+           0.9703305271978327,
+           0.9837241661428768,
+           1.0120858726308453,
+           1.0543288070525707,
+           1.1090657980958298,
+           1.174643280824693,
+           1.249181039395558,
+           1.330616785299821,
+           1.4167544909336698,
+           1.5053153137299418,
+           1.5939898900490523,
+           1.6804907518153445,
+           1.762603623066409,
+           1.8382363879720336,
+           1.9054645855498547,
+           1.962572377610782,
+           2.0080880530856264,
+           2.0408132708727758,
+           2.0598454012172924,
+           2.064592498438009,
+           2.054780621254158,
+           2.0304534064669975,
+           1.9919639926247794,
+           1.9399595778182206,
+           1.875359075289038,
+           1.799324497665343,
+           1.7132268512617206,
+           1.6186074523149445,
+           1.517135684094696,
+           1.4105642949468271,
+           1.3006833905604764,
+           1.189274297864364,
+           1.078064472444732,
+           0.9686845864706375,
+           0.8626288707776433,
+           0.7612196946724143,
+           0.6655772525177772,
+           0.5765950901858782,
+           0.494922050503653,
+           0.42095104878156686,
+           0.3548149116812914,
+           0.2963893295472323,
+           0.2453027885331962,
+           0.20095316904170418,
+           0.16253052569599172,
+           0.12904540560063615,
+           0.09936192000551418,
+           0.0722346632319285,
+           0.04634847489556026,
+           0.020359969522763734,
+           -0.007060286594459046,
+           -0.03718608692087033,
+           -0.07119550648836562,
+           -0.11013351339020055,
+           -0.1548782791147534,
+           -0.20611210069090846,
+           -0.26429772792637324,
+           -0.3296607488513697,
+           -0.40217852937933585,
+           -0.481576033138057,
+           -0.567328668712278,
+           -0.6586721286967406,
+           -0.7546190026188443,
+           -0.8539817685766565,
+           -0.9554016008505076,
+           -1.0573822770476937,
+           -1.1583283324487528,
+           -1.2565864946167884,
+           -1.3504893409551217,
+           -1.438400058095751,
+           -1.518757146450793,
+           -1.5901179069346107,
+           -1.6511995700073057,
+           -1.7009169793046592,
+           -1.7384158219820927,
+           -1.763100503590773,
+           -1.77465589425217,
+           -1.773062321945775,
+           -1.7586033542071091,
+           -1.7318660873646472,
+           -1.6937338482230155,
+           -1.6453714022156822,
+           -1.5882029497995762,
+           -1.5238833745663074,
+           -1.4542633776589202,
+           -1.3813492893214772,
+           -1.3072584858426504,
+           -1.2341714553131975,
+           -1.1642816455744809,
+           -1.0997442901828187,
+           -1.042625441520185,
+           -0.9948524434308497,
+           -0.9581670487825489,
+           -0.9340823307126583,
+           -0.9238444513307631,
+           -0.9284002403177095,
+           -0.948371400848993,
+           -0.9840360048274097,
+           -1.0353177672949017,
+           -1.1017834052818816,
+           -1.1826481937332194,
+           -1.276789635216368,
+           -1.3827689656497524,
+           -1.4988600300394261,
+           -1.6230848847835357,
+           -1.7532553208410306,
+           -1.8870193589395392,
+           -2.0219116475278875,
+           -2.155406599319483,
+           -2.2849730353560767,
+           -2.4081290681970575,
+           -2.5224959490322543,
+           -2.6258496274052323,
+           -2.716168826245901,
+           -2.7916785177355012,
+           -2.8508877951479783,
+           -2.8926212695578206,
+           -2.9160432749143967,
+           -2.9206743366856145,
+           -2.906399543881828,
+           -2.8734686572830515,
+           -2.8224879834048004,
+           -2.7544042393595483,
+           -2.670480823541973,
+           -2.572267086375351,
+           -2.461561359853438,
+           -2.340368650315319,
+           -2.210854022284502,
+           -2.075292799324578,
+           -1.9360187783737608,
+           -1.795371695262885,
+           -1.6556451901606795,
+           -1.5190365023362034,
+           -1.3875990744377287,
+           -1.2631991687507025,
+           -1.1474774936054555,
+           -1.0418167098987199,
+           -0.9473155387977127,
+           -0.8647700258394118,
+           -0.7946623379611867,
+           -0.7371572829486718,
+           -0.6921065500073862,
+           -0.6590604803821656,
+           -0.6372869928537465,
+           -0.6257971150739308,
+           -0.6233764123348304,
+           -0.6286214644091018,
+           -0.6399804219862935,
+           -0.6557965798538868,
+           -0.674353836597197,
+           -0.6939228718095516,
+           -0.7128068624868821,
+           -0.7293855805664552,
+           -0.7421567628564975,
+           -0.7497737215674984,
+           -0.7510782662840331,
+           -0.745128133857154,
+           -0.7312182681300241,
+           -0.7088954529225058,
+           -0.6779659751859061,
+           -0.6384961762964264,
+           -0.5908059335006861,
+           -0.5354552959071197,
+           -0.4732246755288344,
+           -0.40508915928614964,
+           -0.3321876584041168,
+           -0.255787743503998,
+           -0.17724712357334804,
+           -0.09797281214776213,
+           -0.01937908231444747,
+           0.05715465790285285,
+           0.13032493733890385,
+           0.19894313642387484,
+           0.26197119718130063,
+           0.3185531642832285,
+           0.36804170123901675,
+           0.4100188561371006,
+           0.4443105004661416,
+           0.4709940286414916,
+           0.4903990808026147,
+           0.5031012327995007,
+           0.5099087804584536,
+           0.5118429255673776,
+           0.5101118439716452,
+           0.5060792773287335,
+           0.5012284353294116,
+           0.49712212084592217,
+           0.4953600932916615,
+           0.497534762819271,
+           0.5051863578275526,
+           0.5197587292617166,
+           0.5425569467666483,
+           0.5747078040167125,
+           0.6171242843602418,
+           0.6704749448588397,
+           0.7351590591231524,
+           0.8112882199204626,
+           0.8986749447778997,
+           0.9968286556158062,
+           1.1049592210752703,
+           1.2219880621723822,
+           1.3465666328905037,
+           1.4771019020178342,
+           1.6117882855753802,
+           1.7486453149889225,
+           1.8855601788585852,
+           2.020334149482138,
+           2.15073180240226,
+           2.274531860798933,
+           2.3895784485119154,
+           2.493831517133666,
+           2.5854152245044513,
+           2.662663083870036,
+           2.724158773984595,
+           2.7687715988959076,
+           2.7956857096934584,
+           2.8044223461687268,
+           2.7948545206147672,
+           2.7672137449005083,
+           2.722088591147855,
+           2.6604150712119323,
+           2.583459015964545,
+           2.4927908273281503,
+           2.390253159409543,
+           2.2779222554515117,
+           2.158063820484222,
+           2.033084441760341,
+           1.905479677055604,
+           1.7777800120553646,
+           1.6524959403307165
+          ],
+          [
+           1.5678088821183216,
+           1.452839262494453,
+           1.346442546416279,
+           1.2506146038994266,
+           1.1671020804564898,
+           1.0973651558107012,
+           1.0425468574754189,
+           1.0034496304331852,
+           0.980519691055406,
+           0.9738395077891767,
+           0.9831285575254005,
+           1.0077523096688776,
+           1.046739194550243,
+           1.09880512370411,
+           1.162384951282083,
+           1.235670102797076,
+           1.3166514534529714,
+           1.4031664169734235,
+           1.4929491100187127,
+           1.583682389252766,
+           1.6730505194906466,
+           1.7587912229919775,
+           1.8387458819949734,
+           1.9109067183880353,
+           1.9734598546393296,
+           2.024823266700166,
+           2.0636787698707173,
+           2.0889973292938393,
+           2.1000571540553334,
+           2.096454213645198,
+           2.078105003303738,
+           2.045241575880795,
+           1.9983990475455298,
+           1.938395968313211,
+           1.8663081213806063,
+           1.7834364734323251,
+           1.691270137524538,
+           1.5914453274713662,
+           1.4857013750118198,
+           1.3758349462076227,
+           1.263653629981917,
+           1.150930078641601,
+           1.0393578575552493,
+           0.9305101095460723,
+           0.8258020603880436,
+           0.7264582871312963,
+           0.6334855435315496,
+           0.5476517898835799,
+           0.46947191180931735,
+           0.39920043816389383,
+           0.33683138661962786,
+           0.2821051812638672,
+           0.23452240435601088,
+           0.19336396882846474,
+           0.15771713360956857,
+           0.12650663453446287,
+           0.0985300732464868,
+           0.07249659835086095,
+           0.04706782987579371,
+           0.020899921905911837,
+           -0.007314369520423216,
+           -0.03880474483055859,
+           -0.0746846468545976,
+           -0.11591581683004733,
+           -0.16327707759539317,
+           -0.2173381910553372,
+           -0.27843950514026117,
+           -0.3466779551395408,
+           -0.4218998192683831,
+           -0.5037004528082809,
+           -0.5914310435863065,
+           -0.6842122485284219,
+           -0.7809543911772737,
+           -0.8803837279703366,
+           -0.9810741311042376,
+           -1.0814833920401536,
+           -1.1799932258055852,
+           -1.2749519553971174,
+           -1.3647187803900829,
+           -1.4477084862770075,
+           -1.5224354323598215,
+           -1.5875556667610482,
+           -1.6419060571088204,
+           -1.6845393937688173,
+           -1.7147545175103442,
+           -1.73212064289977,
+           -1.736495189593177,
+           -1.728034592589045,
+           -1.7071977354814964,
+           -1.6747418335447317,
+           -1.6317107815453724,
+           -1.5794161698452334,
+           -1.5194113569205032,
+           -1.4534591622740916,
+           -1.3834939064513017,
+           -1.3115786703966779,
+           -1.2398587710411337,
+           -1.1705125506224419,
+           -1.1057006512469203,
+           -1.0475149916773538,
+           -0.9979286790656213,
+           -0.9587480738551603,
+           -0.9315681816218129,
+           -0.9177324722058856,
+           -0.9182981258344893,
+           -0.9340075804382632,
+           -0.9652671070437193,
+           -1.0121329745287768,
+           -1.0743055851774328,
+           -1.1511317727307202,
+           -1.2416152596255485,
+           -1.3444350745979488,
+           -1.457971540578849,
+           -1.5803392605063118,
+           -1.7094263597821984,
+           -1.842939092753062,
+           -1.9784507905083186,
+           -2.1134540216589452,
+           -2.245414759185825,
+           -2.371827296865757,
+           -2.4902686394237716,
+           -2.598451101911063,
+           -2.6942718956059664,
+           -2.77585854897218,
+           -2.841609111154632,
+           -2.8902262097414138,
+           -2.920744181043428,
+           -2.9325486563706766,
+           -2.9253881676875957,
+           -2.8993775262244386,
+           -2.8549929234727203,
+           -2.7930589007301383,
+           -2.7147275261963664,
+           -2.621450302867582,
+           -2.5149435016616706,
+           -2.3971477681800732,
+           -2.270182984555321,
+           -2.136299476743042,
+           -1.9978267397873917,
+           -1.8571209070740553,
+           -1.7165122131469215,
+           -1.5782536928019308,
+           -1.4444723221329587,
+           -1.3171237409788126,
+           -1.1979516025139152,
+           -1.088452476917297,
+           -0.9898470951379527,
+           -0.903058559282057,
+           -0.8286979720609787,
+           -0.7670577533939276,
+           -0.7181127222333262,
+           -0.6815288306837244,
+           -0.6566792502384131,
+           -0.6426673310805281,
+           -0.6383557892880614,
+           -0.642401327518892,
+           -0.6532937659792697,
+           -0.6693986553266621,
+           -0.6890022641606729,
+           -0.7103577827928929,
+           -0.7317315632349614,
+           -0.7514482232504065,
+           -0.7679334795863576,
+           -0.7797536411103819,
+           -0.7856507847942794,
+           -0.7845727539185081,
+           -0.7756972555248922,
+           -0.7584494895028409,
+           -0.7325129108005399,
+           -0.6978329048143227,
+           -0.6546133395043894,
+           -0.6033061415734626,
+           -0.5445942234873047,
+           -0.47936825868768207,
+           -0.40869795975375733,
+           -0.3337986545471017,
+           -0.2559940750036223,
+           -0.17667636921067936,
+           -0.09726441732483597,
+           -0.019161573998479873,
+           0.056286026753642734,
+           0.12782948422288498,
+           0.1943543858431559,
+           0.2549143010979683,
+           0.3087596094456328,
+           0.3553608785442634,
+           0.39442615060859165,
+           0.42591165291333694,
+           0.4500256192692454,
+           0.4672250884131693,
+           0.4782057281364557,
+           0.48388491599152367,
+           0.4853784839477235,
+           0.4839717009306784,
+           0.48108521953649375,
+           0.47823684747793616,
+           0.4770001170581223,
+           0.47896071427897957,
+           0.4856718907866341,
+           0.49861001511116915,
+           0.5191314236596977,
+           0.5484317064875618,
+           0.5875085085586687,
+           0.6371288452930326,
+           0.6978018236620337,
+           0.769757529549428,
+           0.8529326917492658,
+           0.9469635665232045,
+           1.0511863082019282,
+           1.1646449053093633,
+           1.2861065727342504,
+           1.4140843032747723,
+           1.546866101109469,
+           1.6825502499227791,
+           1.8190858137964847,
+           1.9543174334606717,
+           2.086033367505699,
+           2.2120156405661437,
+           2.330091100550682,
+           2.438182156280276,
+           2.534355966264328,
+           2.6168708788993555,
+           2.684218983483115,
+           2.7351637187309157,
+           2.768771598895908,
+           2.78443725441725,
+           2.7819011409545964,
+           2.7612594439171096,
+           2.722965890955909,
+           2.6678253778506242,
+           2.596979509080608,
+           2.5118843483474245,
+           2.4142808616665787,
+           2.3061587117875213,
+           2.1897142233169684,
+           2.067303479073007,
+           1.9413916264201228,
+           1.8144995647232465,
+           1.6891492493361353,
+           1.567808882118325
+          ],
+          [
+           1.4867783563319206,
+           1.3782384638851501,
+           1.2795999757421603,
+           1.1927064824060805,
+           1.1191284860620354,
+           1.0601300279981332,
+           1.0166423139279328,
+           0.9892449375578269,
+           0.9781551216769757,
+           0.9832252050889175,
+           1.003948407504436,
+           1.0394727078516457,
+           1.0886224791164125,
+           1.1499273394791498,
+           1.2216575096127922,
+           1.3018648136673083,
+           1.3884283303690845,
+           1.4791035939640231,
+           1.5715741649835884,
+           1.663504339900566,
+           1.752591747842414,
+           1.8366185920818898,
+           1.9135003337154248,
+           1.9813306837169629,
+           2.038421865652717,
+           2.083339232325302,
+           2.1149294624405757,
+           2.1323417244818055,
+           2.13504137031482,
+           2.122815906273066,
+           2.0957731799865593,
+           2.054331912306733,
+           1.999204890619646,
+           1.931375318025633,
+           1.852066977914522,
+           1.7627090213376093,
+           1.6648963116619344,
+           1.5603463642044684,
+           1.4508539953992163,
+           1.3382448447256086,
+           1.224328952003616,
+           1.1108555623539154,
+           0.999470291484429,
+           0.8916757160830695,
+           0.788796359758301,
+           0.6919489266191327,
+           0.6020184952647124,
+           0.5196412292196002,
+           0.4451939896922829,
+           0.3787910572686439,
+           0.320287985317151,
+           0.26929242412377247,
+           0.22518157572847863,
+           0.18712576961314595,
+           0.15411749306652867,
+           0.1250050711551623,
+           0.09853007324648677,
+           0.07336742891958557,
+           0.04816716821385423,
+           0.021596661198972435,
+           -0.00761777921097046,
+           -0.040651049170589974,
+           -0.07854223171787598,
+           -0.12216139737391589,
+           -0.1721811245168214,
+           -0.22905351355639772,
+           -0.2929933260221102,
+           -0.36396772043187897,
+           -0.44169288526626915,
+           -0.5256376898766807,
+           -0.6150342912549747,
+           -0.7088954529225053,
+           -0.8060381563684244,
+           -0.9051129199473882,
+           -1.004638089147643,
+           -1.1030382295136685,
+           -1.1986856426476782,
+           -1.2899439394731416,
+           -1.375212545558489,
+           -1.4529709823364996,
+           -1.5218217663695508,
+           -1.5805307965249829,
+           -1.6280641554227904,
+           -1.6636203354619519,
+           -1.6866570090936022,
+           -1.6969115951204665,
+           -1.6944150244191682,
+           -1.679498275867296,
+           -1.6527914322706214,
+           -1.6152151922880584,
+           -1.567964963114324,
+           -1.5124878452997526,
+           -1.4504530009029843,
+           -1.3837160646837543,
+           -1.314278411018771,
+           -1.2442422228094707,
+           -1.1757624194644374,
+           -1.1109965862573195,
+           -1.0520541047871776,
+           -1.0009457123902168,
+           -0.959534716379887,
+           -0.9294910568792145,
+           -0.912249350453167,
+           -0.908971957176688,
+           -0.9205179983071657,
+           -0.9474191131332244,
+           -0.9898625851846595,
+           -1.047682293644903,
+           -1.1203577597408299,
+           -1.2070213646239965,
+           -1.3064736195152866,
+           -1.417206175442601,
+           -1.5374320734898745,
+           -1.6651225616598002,
+           -1.798049645518103,
+           -1.933833400634483,
+           -2.069992958883934,
+           -2.2039999907756727,
+           -2.3333334443527027,
+           -2.4555342693789926,
+           -2.568258854300681,
+           -2.669329932880185,
+           -2.7567837767556926,
+           -2.828912578037564,
+           -2.8843010402841385,
+           -2.9218563340234094,
+           -2.9408307310477486,
+           -2.9408364061555314,
+           -2.9218520815956754,
+           -2.8842213836430495,
+           -2.8286429777655857,
+           -2.7561527439420193,
+           -2.6680984421080143,
+           -2.5661074948712908,
+           -2.452048676247185,
+           -2.3279886373143195,
+           -2.196144318947586,
+           -2.058832395289818,
+           -1.918416957147703,
+           -1.7772566805053103,
+           -1.6376527310309579,
+           -1.5017986307467548,
+           -1.3717332586201576,
+           -1.2492980741362465,
+           -1.1360995440258432,
+           -1.033477620005854,
+           -0.9424809629538888,
+           -0.863849440198799,
+           -0.7980042417646276,
+           -0.7450457729513819,
+           -0.7047592892425272,
+           -0.6766280499298618,
+           -0.6598535837197501,
+           -0.653382487438062,
+           -0.6559390220096879,
+           -0.6660626319906405,
+           -0.6821493994334819,
+           -0.7024963525631809,
+           -0.7253474867910074,
+           -0.7489403214739532,
+           -0.771551811290795,
+           -0.7915424561688696,
+           -0.8073975076357915,
+           -0.8177642508465265,
+           -0.821484448225197,
+           -0.8176211599115373,
+           -0.8054793047040593,
+           -0.7846194891601287,
+           -0.7548648077818552,
+           -0.7163004993439986,
+           -0.6692665288002191,
+           -0.6143433461810798,
+           -0.5523312488833017,
+           -0.4842239373381817,
+           -0.41117700212352526,
+           -0.33447220942797,
+           -0.2554785581569852,
+           -0.17561116322214393,
+           -0.09628907364964784,
+           -0.018893159736289838,
+           0.055274800054938227,
+           0.12503073432385137,
+           0.18934355868876654,
+           0.24736617044136955,
+           0.2984613196567496,
+           0.3422216518759311,
+           0.37848336903846846,
+           0.4073331212627676,
+           0.4291079181498792,
+           0.44438803006191413,
+           0.45398303269236456,
+           0.4589113275645548,
+           0.4603736423135976,
+           0.45972117337329077,
+           0.45841917595763954,
+           0.45800692836259,
+           0.4600550964839451,
+           0.4661215974996772,
+           0.4777071069910913,
+           0.4962113701630353,
+           0.5228914647783897,
+           0.5588231211938258,
+           0.6048661344518985,
+           0.6616348064370562,
+           0.7294742349958685,
+           0.808443124619745,
+           0.8983036332929657,
+           0.9985185963713056,
+           1.1082562851798927,
+           1.226402669951138,
+           1.3515809684453943,
+           1.4821780778043456,
+           1.6163773124756255,
+           1.7521967097963276,
+           1.887532021088623,
+           2.020203383531887,
+           2.1480045697449355,
+           2.268753640457911,
+           2.3803437827354204,
+           2.480793103085556,
+           2.5682921618737478,
+           2.641248082428961,
+           2.698324144017621,
+           2.738473870687564,
+           2.760968755400422,
+           2.765418907813935,
+           2.7517860809483934,
+           2.7203887127273183,
+           2.671898808627391,
+           2.6073306867709034,
+           2.5280218019845107,
+           2.4356060558593007,
+           2.331980181017612,
+           2.2192639551820226,
+           2.0997551501460396,
+           1.9758802486931166,
+           1.8501420657535486,
+           1.7250654860853303,
+           1.603142577636906,
+           1.4867783563319241
+          ],
+          [
+           1.410089917886394,
+           1.3088922022294973,
+           1.2188289313300875,
+           1.1415758306886286,
+           1.0785139921938558,
+           1.0307006525842546,
+           0.9988473536356874,
+           0.9833059784491442,
+           0.9840629707055664,
+           1.0007418490678068,
+           1.0326139317830274,
+           1.0786169917689115,
+           1.1373813747895218,
+           1.2072629372991677,
+           1.286382000423341,
+           1.3726673762279789,
+           1.4639044052857797,
+           1.5577858533923155,
+           1.651964452285052,
+           1.7441058358510169,
+           1.8319406203196826,
+           1.9133144043252948,
+           1.986234521739435,
+           2.0489124653449267,
+           2.0998010105811993,
+           2.137625202938224,
+           2.1614065267448574,
+           2.1704797432398224,
+           2.164502067695658,
+           2.143454544473179,
+           2.1076356705329435,
+           2.0576475073852247,
+           1.9943747040500732,
+           1.9189570248337995,
+           1.8327561314086995,
+           1.7373175050051965,
+           1.6343285081749999,
+           1.52557367381593,
+           1.4128883698570283,
+           1.2981120197690366,
+           1.1830420611958905,
+           1.0693897975430262,
+           0.9587392410905604,
+           0.85250996262309,
+           0.7519248538610136,
+           0.6579835779415197,
+           0.5714423331846046,
+           0.49280039021207916,
+           0.42229368635954456,
+           0.3598955786935414,
+           0.30532467243485395,
+           0.2580594598501921,
+           0.21735933028756146,
+           0.18229134938392674,
+           0.15176205865472212,
+           0.12455341936838851,
+           0.09936192000551414,
+           0.07483978731743565,
+           0.04963718900994558,
+           0.02244429267224809,
+           -0.0079679486828243,
+           -0.042709379370785575,
+           -0.08273562416468042,
+           -0.12881741458424772,
+           -0.1815150876129559,
+           -0.2411589512644874,
+           -0.30783605866158104,
+           -0.38138376549030345,
+           -0.4613902690781873,
+           -0.5472021453909446,
+           -0.637938717562414,
+           -0.7325129108005395,
+           -0.8296580781882459,
+           -0.9279601243535986,
+           -1.0258941132328645,
+           -1.1218644257895374,
+           -1.2142474366701332,
+           -1.3014356078756282,
+           -1.3818818544585325,
+           -1.4541430231762569,
+           -1.5169213403719455,
+           -1.5691027298074018,
+           -1.609790973701011,
+           -1.6383367890833191,
+           -1.654361014367339,
+           -1.6577712447293518,
+           -1.6487714159690074,
+           -1.6278640109829283,
+           -1.5958447465187804,
+           -1.5537897859157712,
+           -1.5030357113991084,
+           -1.4451526724903057,
+           -1.381911300642939,
+           -1.3152441399600212,
+           -1.247202485773057,
+           -1.1799096433765341,
+           -1.1155117152508296,
+           -1.0561270942076395,
+           -1.0037958802536415,
+           -0.9604304494970162,
+           -0.9277683837607696,
+           -0.9073289201055801,
+           -0.9003740013301683,
+           -0.9078749035463908,
+           -0.9304852876231693,
+           -0.9685213707672066,
+           -1.0219497463971605,
+           -1.0903831988498158,
+           -1.1730846687494394,
+           -1.268979329723965,
+           -1.3766745423290236,
+           -1.4944872613078797,
+           -1.6204782923181005,
+           -1.752492628407251,
+           -1.8882049488914296,
+           -2.0251692375104744,
+           -2.160871375898624,
+           -2.292783495006824,
+           -2.418418822959945,
+           -2.5353857540304836,
+           -2.641439880318953,
+           -2.7345327749565835,
+           -2.812856392052936,
+           -2.8748820523489393,
+           -2.9193931120852663,
+           -2.945510562829746,
+           -2.9527109782684797,
+           -2.940836406155532,
+           -2.910095995298289,
+           -2.8610593439621335,
+           -2.794641752625816,
+           -2.712081755827099,
+           -2.6149114902457806,
+           -2.504920624751655,
+           -2.384114728815133,
+           -2.2546690847981643,
+           -2.1188790541060323,
+           -1.979108184488178,
+           -1.8377352940999803,
+           -1.6971017861632718,
+           -1.559460435818018,
+           -1.4269268484164481,
+           -1.3014347171899197,
+           -1.1846959097429823,
+           -1.0781662896896715,
+           -0.9830180350370037,
+           -0.9001190522582244,
+           -0.8300199084377116,
+           -0.7729485177977365,
+           -0.7288126279486286,
+           -0.6972099600618749,
+           -0.6774456705686049,
+           -0.6685566245285219,
+           -0.6693418068549002,
+           -0.678398051133482,
+           -0.6941601404073827,
+           -0.7149442330553926,
+           -0.7389934922003504,
+           -0.7645247507150369,
+           -0.7897750269043389,
+           -0.8130467186596324,
+           -0.8327503458889343,
+           -0.8474437811797821,
+           -0.8558670051065661,
+           -0.8569715428527078,
+           -0.8499438797938453,
+           -0.8342223117820686,
+           -0.8095068570627271,
+           -0.7757620367036406,
+           -0.733212514568531,
+           -0.6823317715718289,
+           -0.6238241675781652,
+           -0.5586009133592168,
+           -0.48775063024173027,
+           -0.4125053125752257,
+           -0.33420262446764254,
+           -0.2542455544698833,
+           -0.1740605177324159,
+           -0.0950550329710379,
+           -0.018576110433994323,
+           0.05412953324219568,
+           0.12195236633239763,
+           0.18395304882585803,
+           0.2393906658124273,
+           0.2877454231082221,
+           0.328735185037202,
+           0.36232539457300533,
+           0.3887320882990789,
+           0.4084178985002307,
+           0.4220811175963877,
+           0.43063808143157906,
+           0.4351993030363167,
+           0.4370399529400445,
+           0.43756543173610674,
+           0.4382729115773499,
+           0.44070983225323146,
+           0.4464304216651575,
+           0.45695136769147393,
+           0.4737077971076588,
+           0.4980107166048116,
+           0.5310070409684908,
+           0.5736432748148569,
+           0.62663382832693,
+           0.6904348362719601,
+           0.7652242159285304,
+           0.850888546694377,
+           0.9470171858555175,
+           1.052903855440771,
+           1.1675557487200074,
+           1.2897100163660178,
+           1.4178573062905953,
+           1.550271852333919,
+           1.6850474398139645,
+           1.8201384246301122,
+           1.9534048509793838,
+           2.082660604120893,
+           2.20572345178662,
+           2.3204657729242397,
+           2.424864746922268,
+           2.517050781036108,
+           2.5953529883907653,
+           2.658340592920598,
+           2.7048592294327745,
+           2.7340612244711253,
+           2.745429083996248,
+           2.738791573701678,
+           2.7143319531849905,
+           2.672588111925476,
+           2.614444548539572,
+           2.541116330369387,
+           2.4541253633293927,
+           2.355269487370946,
+           2.246585086381024,
+           2.130304058554256,
+           2.008806130404695,
+           1.8845676112430478,
+           1.7601077723347545,
+           1.6379340939165155,
+           1.520487652318715,
+           1.4100899178863973
+          ],
+          [
+           1.3383923856729054,
+           1.245387178280643,
+           1.1646435637149992,
+           1.0976552371974846,
+           1.0456022158483447,
+           1.0093260154020114,
+           0.9893125300150665,
+           0.9856829993886064,
+           0.9981932550650635,
+           1.0262412409914115,
+           1.0688826070544788,
+           1.1248539830657445,
+           1.1926033592485246,
+           1.2703268320619512,
+           1.3560108252333056,
+           1.4474787687612993,
+           1.5424411164559486,
+           1.6385475077394074,
+           1.733439833715512,
+           1.8248049519757836,
+           1.9104258095555202,
+           1.9882297784453622,
+           2.056333081923723,
+           2.1130802908182473,
+           2.157077994084301,
+           2.187221894662865,
+           2.202716745788437,
+           2.2030887206715466,
+           2.1881899953668897,
+           2.1581955160272743,
+           2.11359211290503,
+           2.055160309681581,
+           1.9839493534008739,
+           1.9012461531174554,
+           1.8085389603628355,
+           1.7074767481530504,
+           1.5998253445133226,
+           1.4874214490012603,
+           1.3721257047569835,
+           1.2557760131973514,
+           1.1401422633375047,
+           1.0268836033427076,
+           0.9175093094909856,
+           0.8133442091631102,
+           0.7154994923206192,
+           0.6248496033177657,
+           0.5420157454582952,
+           0.4673563585046395,
+           0.4009647487398035,
+           0.342673866737633,
+           0.29206804437069783,
+           0.24850132440385475,
+           0.21112184776929596,
+           0.17890160952354636,
+           0.15067075841511893,
+           0.1251555003526324,
+           0.1010185757235725,
+           0.0769012167261156,
+           0.05146545522294077,
+           0.023435644979917285,
+           -0.008361915343799358,
+           -0.04496232102624671,
+           -0.08722934619737917,
+           -0.1358275555435612,
+           -0.19119999733233647,
+           -0.2535520866988223,
+           -0.32284212682413016,
+           -0.3987787426927688,
+           -0.48082532192392086,
+           -0.5682113742993946,
+           -0.6599505406976928,
+           -0.7548648077818547,
+           -0.851614321410006,
+           -0.9487320435012128,
+           -1.0446623677776798,
+           -1.1378027027283153,
+           -1.2265469480537277,
+           -1.3093297358898521,
+           -1.384670281719022,
+           -1.4512146928004208,
+           -1.507775614188414,
+           -1.5533681532239951,
+           -1.5872411113295573,
+           -1.6089026648762195,
+           -1.6181397720610446,
+           -1.6150307368019448,
+           -1.5999505298241516,
+           -1.5735686471816348,
+           -1.5368394729561035,
+           -1.4909853011610932,
+           -1.4374723572500585,
+           -1.3779803374483763,
+           -1.3143661499400425,
+           -1.2486226915699545,
+           -1.1828336233939403,
+           -1.1191252148306952,
+           -1.0596164066217124,
+           -1.0063682952048716,
+           -0.9613342640629614,
+           -0.926311980455194,
+           -0.9028984387566561,
+           -0.8924491652398427,
+           -0.8960426050800547,
+           -0.9144505928851285,
+           -0.9481156660046371,
+           -0.9971358186917456,
+           -1.0612571187777582,
+           -1.1398744211631016,
+           -1.2320402186938504,
+           -1.3364814756095802,
+           -1.4516240964934757,
+           -1.5756244992372748,
+           -1.7064075884733974,
+           -1.8417102704485757,
+           -1.9791295152399,
+           -2.1161738608711267,
+           -2.2503171690214923,
+           -2.3790533857316096,
+           -2.499951034202961,
+           -2.6107061711268695,
+           -2.7091925728836794,
+           -2.7935079825916707,
+           -2.8620153417991334,
+           -2.913378049352206,
+           -2.9465884317512345,
+           -2.960988770681061,
+           -2.956284410438261,
+           -2.9325486563706775,
+           -2.890219370605202,
+           -2.830087368518332,
+           -2.753276913803823,
+           -2.6612187968871788,
+           -2.5556166562897897,
+           -2.4384073611172608,
+           -2.311716411301252,
+           -2.1778094272233703,
+           -2.0390408891341507,
+           -1.8978013472371213,
+           -1.7564643540224762,
+           -1.617334370724577,
+           -1.4825968697080203,
+           -1.3542717949693934,
+           -1.234171455313198,
+           -1.1238638113426003,
+           -1.0246419810521805,
+           -0.9375006329328053,
+           -0.8631197639844285,
+           -0.8018561771455313,
+           -0.7537427829229105,
+           -0.7184956581379726,
+           -0.6955286054323473,
+           -0.6839747751593721,
+           -0.6827147410013156,
+           -0.6904102662671014,
+           -0.7055428631102297,
+           -0.7264561351336454,
+           -0.751400807712729,
+           -0.778581291921696,
+           -0.8062025985520502,
+           -0.8325164189981935,
+           -0.8558652196484734,
+           -0.8747232550167855,
+           -0.8877334906230022,
+           -0.8937395373477683,
+           -0.89181183179817,
+           -0.8812674487290304,
+           -0.8616830979126814,
+           -0.8329010348165173,
+           -0.7950277975531144,
+           -0.748425867186346,
+           -0.6936985299532813,
+           -0.6316683937255788,
+           -0.5633501727165281,
+           -0.4899184999805172,
+           -0.41267165300136993,
+           -0.3329921804768723,
+           -0.25230549571144995,
+           -0.17203755190401354,
+           -0.09357273583155695,
+           -0.0182131084721572,
+           0.05285991579089002,
+           0.11862042463470883,
+           0.17822846240710416,
+           0.23105526358925943,
+           0.2767025811338493,
+           0.31501557964022747,
+           0.34608893098774673,
+           0.37026592717820694,
+           0.38813060724887644,
+           0.40049307759004127,
+           0.40836838320547636,
+           0.4129494568641318,
+           0.41557482939777945,
+           0.4176919236189642,
+           0.4208168729085705,
+           0.4264919004099713,
+           0.43624136351596215,
+           0.4515276091481234,
+           0.4737077971076586,
+           0.503992831151387,
+           0.5434094907830925,
+           0.592766782144825,
+           0.6526274256435869,
+           0.7232852735131791,
+           0.8047493054442781,
+           0.8967346882958004,
+           0.9986612107391085,
+           1.1096592198302626,
+           1.2285829985274095,
+           1.354031335756432,
+           1.4843748584612977,
+           1.6177895227181873,
+           1.7522955027736156,
+           1.885800576772663,
+           2.016146989520095,
+           2.141160678879298,
+           2.2587016857705846,
+           2.366714529924457,
+           2.463277325608237,
+           2.5466484337696844,
+           2.6153094989778833,
+           2.668003800001057,
+           2.703768949948803,
+           2.721963113065336,
+           2.722284057335247,
+           2.704780531376074,
+           2.669855636533452,
+           2.6182620562243852,
+           2.5510891997311447,
+           2.4697425120635708,
+           2.375915390424795,
+           2.271554326604483,
+           2.158818058899161,
+           2.0400316628845037,
+           1.917636633954848,
+           1.7941381129550686,
+           1.672050477027046,
+           1.5538425592219545,
+           1.4418837714515342,
+           1.3383923856729085
+          ],
+          [
+           1.272292353257484,
+           1.1882606732775454,
+           1.1175023056260776,
+           1.0613162900278785,
+           1.0206716055461333,
+           0.9961869555540986,
+           0.9881185119884569,
+           0.9963558897034507,
+           1.0204264261557594,
+           1.0595076444654508,
+           1.1124475839142318,
+           1.177792495873296,
+           1.2538212295166646,
+           1.3385854746810697,
+           1.4299548926773915,
+           1.5256660530338968,
+           1.6233740077648242,
+           1.7207052768644573,
+           1.8153109906800358,
+           1.904918937235685,
+           1.9873832953340385,
+           2.060730896477443,
+           2.1232029487291704,
+           2.17329127129715,
+           2.209768226963455,
+           2.231709697044476,
+           2.2385106164251183,
+           2.2298927700721753,
+           2.2059047427415055,
+           2.1669141056456382,
+           2.11359211290503,
+           2.046891362013845,
+           1.9680170418560652,
+           1.8783925448655814,
+           1.779620353002373,
+           1.6734392170872372,
+           1.56167873305434,
+           1.44621247484647,
+           1.328910870691145,
+           1.2115950067834103,
+           1.0959925101307204,
+           0.9836966013901651,
+           0.8761293205637943,
+           0.7745098157001076,
+           0.6798284501784134,
+           0.5928273311664822,
+           0.5139876943336318,
+           0.44352440211908145,
+           0.3813876292967765,
+           0.32727162487697936,
+           0.28063025819679766,
+           0.24069888393574226,
+           0.20652190009827973,
+           0.1769852287650984,
+           0.15085282524156524,
+           0.12680622023032245,
+           0.1034860243436419,
+           0.07953427652002053,
+           0.05363649889337801,
+           0.024562330832865107,
+           -0.008796346057671838,
+           -0.04739081323110045,
+           -0.09198537889414322,
+           -0.14313251128721566,
+           -0.20115391495626572,
+           -0.2661280683256705,
+           -0.33788457238277936,
+           -0.41600548266082565,
+           -0.4998336144619332,
+           -0.5884876290186807,
+           -0.6808835306766229,
+           -0.7757620367036403,
+           -0.8717211262807353,
+           -0.9672529375548417,
+           -1.0607840648559081,
+           -1.1507182152949473,
+           -1.2354801173665642,
+           -1.3135595356206797,
+           -1.3835542359835562,
+           -1.4442107662090553,
+           -1.494461964800957,
+           -1.5334601884126353,
+           -1.5606053503480215,
+           -1.5755669888505373,
+           -1.5782997302749286,
+           -1.5690516753756119,
+           -1.5483654127730893,
+           -1.5170715478101067,
+           -1.4762748228971219,
+           -1.427333092384402,
+           -1.3718295963110312,
+           -1.3115391485242462,
+           -1.2483890113337706,
+           -1.1844153671134834,
+           -1.1217164135843907,
+           -1.0624032009427185,
+           -1.0085493931810041,
+           -0.9621411712046918,
+           -0.925028500702211,
+           -0.8988789629516273,
+           -0.8851352923560598,
+           -0.884977681741333,
+           -0.8992918072750814,
+           -0.9286433918855628,
+           -0.9732599724726246,
+           -1.0330203657292143,
+           -1.107452144169324,
+           -1.1957372424489565,
+           -1.2967256189438428,
+           -1.4089567035815809,
+           -1.5306881748653518,
+           -1.6599314314828841,
+           -1.7944929612268414,
+           -1.93202066616066,
+           -2.07005408158837,
+           -2.2060773304227483,
+           -2.3375735863680354,
+           -2.4620797806369277,
+           -2.57724027868089,
+           -2.680858275856639,
+           -2.7709437135573216,
+           -2.8457565988422666,
+           -2.903844719034754,
+           -2.94407487549308,
+           -2.965656914571646,
+           -2.9681600049349637,
+           -2.951520794703938,
+           -2.916043274914398,
+           -2.862390372755593,
+           -2.7915674942388793,
+           -2.704898426553844,
+           -2.603994190770641,
+           -2.4907156013665284,
+           -2.367130436276051,
+           -2.2354662462323214,
+           -2.0980599320724127,
+           -1.9573052910347863,
+           -1.8155997761715545,
+           -1.6752917258437663,
+           -1.5386293026190048,
+           -1.4077123332514159,
+           -1.284448165034539,
+           -1.1705125506224423,
+           -1.067316446014406,
+           -0.9759794579844693,
+           -0.8973105115119195,
+           -0.831796128853666,
+           -0.7795965242332236,
+           -0.740549526347884,
+           -0.7141821497524944,
+           -0.6997294503749324,
+           -0.6961601245228723,
+           -0.7022081490661505,
+           -0.716409616974452,
+           -0.7371438005474401,
+           -0.7626773774399398,
+           -0.7912106842871021,
+           -0.8209248210278917,
+           -0.8500284168499047,
+           -0.8768028862377027,
+           -0.89964505036336,
+           -0.9171060737482439,
+           -0.9279257667922602,
+           -0.9310614288098558,
+           -0.9257105504516945,
+           -0.9113268551498243,
+           -0.8876293324190849,
+           -0.8546040970917166,
+           -0.8124990932756334,
+           -0.7618118453501764,
+           -0.7032706360251524,
+           -0.6378096589205607,
+           -0.5665388460720086,
+           -0.49070920539558005,
+           -0.41167461608668293,
+           -0.33085111835955316,
+           -0.2496747956566682,
+           -0.16955938094324755,
+           -0.0918547231357521,
+           -0.017807225011635872,
+           0.051476689239167754,
+           0.11506309896526827,
+           0.17221823202401249,
+           0.22243048504648646,
+           0.26542622117367737,
+           0.30117890975485806,
+           0.32991134611170764,
+           0.35209086997926753,
+           0.36841768405990694,
+           0.37980655463002805,
+           0.3873623497382027,
+           0.392350032814787,
+           0.39615987634504907,
+           0.40026878789339926,
+           0.40619874593738686,
+           0.4154734229698909,
+           0.4295741260789024,
+           0.4498962093211811,
+           0.4777071069910909,
+           0.5141071024067599,
+           0.5599938838845906,
+           0.6160318496582329,
+           0.6826270088063326,
+           0.7599081885966597,
+           0.8477151034005014,
+           0.9455936703204512,
+           1.0527987761240352,
+           1.1683045134749503,
+           1.2908217164535827,
+           1.418822440654609,
+           1.550570856366602,
+           1.6841598589136064,
+           1.8175525523118456,
+           1.9486276347043914,
+           2.0752276098275595,
+           2.195208670703057,
+           2.306491051864402,
+           2.4071086260465413,
+           2.495256530995755,
+           2.569335651751069,
+           2.6279928525251113,
+           2.670155948565787,
+           2.6950625298234985,
+           2.702281891967147,
+           2.691729492816215,
+           2.6636735296453713,
+           2.6187334207584123,
+           2.5578701686380976,
+           2.482368777121651,
+           2.3938130866533416,
+           2.2940535750319087,
+           2.1851688417015387,
+           2.0694216473395515,
+           1.9492105134888567,
+           1.8270179959911317,
+           1.7053568283045093,
+           1.5867151843951068,
+           1.4735023344370166,
+           1.3679959594361621,
+           1.272292353257487
+          ],
+          [
+           1.2123490568249704,
+           1.1379960033025693,
+           1.077803993438417,
+           1.0328664331164263,
+           1.0039330855316084,
+           0.9913946354323221,
+           0.9952754014886634,
+           1.0152343519120761,
+           1.0505743812896016,
+           1.1002596106633153,
+           1.1629402829446758,
+           1.236984646418264,
+           1.320517054710071,
+           1.411461366152577,
+           1.5075886024849487,
+           1.6065677292406755,
+           1.7060183503293826,
+           1.8035640688638526,
+           1.8968852561435827,
+           1.9837699910634297,
+           2.0621619825018915,
+           2.1302043661558554,
+           2.1862783728236432,
+           2.229035994641002,
+           2.2574259260059018,
+           2.270712223143948,
+           2.2684853063124035,
+           2.250665117054808,
+           2.217496435040702,
+           2.169536550114892,
+           2.1076356705329435,
+           2.0329106234210275,
+           1.9467125639807696,
+           1.8505895519453648,
+           1.7462449738314005,
+           1.6354928847227317,
+           1.5202114113925336,
+           1.4022953979201822,
+           1.2836094847106447,
+           1.1659427918336092,
+           1.0509663284656585,
+           0.9401941732642605,
+           0.834949367739969,
+           0.7363353387755424,
+           0.6452135205922503,
+           0.5621876844003125,
+           0.4875953098059665,
+           0.4215061501905103,
+           0.3637279593196997,
+           0.3138191630473155,
+           0.2711080827598422,
+           0.2347181506228593,
+           0.20359840491330958,
+           0.17655842055697155,
+           0.15230671876632304,
+           0.12949161316433416,
+           0.10674339013386319,
+           0.08271668982182079,
+           0.05613195200939686,
+           0.02581481795894445,
+           -0.009267565344020238,
+           -0.04997430984238847,
+           -0.09696348406622861,
+           -0.15067047858408955,
+           -0.2112926258374459,
+           -0.27878049764977186,
+           -0.35283612944131787,
+           -0.4329182393791552,
+           -0.5182543279360023,
+           -0.6078593632587678,
+           -0.7005605849316964,
+           -0.7950277975531138,
+           -0.8898083801327945,
+           -0.9833661113699911,
+           -1.0741228076151164,
+           -1.1605016924087839,
+           -1.2409713659539507,
+           -1.3140892210483823,
+           -1.3785431595040738,
+           -1.4331904997904366,
+           -1.4770930317078876,
+           -1.5095472657640834,
+           -1.530109041347126,
+           -1.5386117959100158,
+           -1.535177953790327,
+           -1.5202230641157826,
+           -1.4944524982486038,
+           -1.4588507038942562,
+           -1.4146632006871507,
+           -1.3633716860749023,
+           -1.3066627960432586,
+           -1.2463912282411957,
+           -1.1845380812717257,
+           -1.1231653896096554,
+           -1.06436793559525,
+           -1.0102234956171008,
+           -0.9627427249704997,
+           -0.9238199036891438,
+           -0.8951857533579675,
+           -0.8783634927279783,
+           -0.8746292288154457,
+           -0.8849776817413327,
+           -0.9100941181943971,
+           -0.9503332230458346,
+           -1.0057054748164844,
+           -1.0758714123737332,
+           -1.1601439917535576,
+           -1.2574990379610869,
+           -1.3665936017428242,
+           -1.4857918404159094,
+           -1.6131978595647218,
+           -1.7466947832485886,
+           -1.8839891684658527,
+           -2.0226597487298603,
+           -2.160209384961697,
+           -2.2941190221311474,
+           -2.4219023991635225,
+           -2.5411602388520063,
+           -2.649632654411666,
+           -2.7452485496695873,
+           -2.8261708597470694,
+           -2.8908365767721245,
+           -2.937990628300375,
+           -2.9667128217319365,
+           -2.9764372325532538,
+           -2.966963593704645,
+           -2.9384604334101856,
+           -2.8914599047825837,
+           -2.8268444476640346,
+           -2.7458256166906216,
+           -2.649915594769529,
+           -2.5408920835396622,
+           -2.4207574177687095,
+           -2.291692885265357,
+           -2.1560093445084183,
+           -2.016095316161326,
+           -1.8743637799536383,
+           -1.7331989337793279,
+           -1.5949041667292758,
+           -1.4616524623371774,
+           -1.3354403835122668,
+           -1.2180466981166869,
+           -1.1109965862573197,
+           -1.0155322300570504,
+           -0.9325904274517334,
+           -0.8627876973878045,
+           -0.8064131589932497,
+           -0.7634292764370348,
+           -0.7334803689932988,
+           -0.7159085970250201,
+           -0.7097769538405115,
+           -0.7138986250895566,
+           -0.7268719256699303,
+           -0.7471198927051277,
+           -0.7729335052148073,
+           -0.8025174192260558,
+           -0.8340370532085177,
+           -0.8656658341020331,
+           -0.8956314193543915,
+           -0.9222597450701655,
+           -0.9440158136258444,
+           -0.9595402242583969,
+           -0.967680564843952,
+           -0.9675169194027108,
+           -0.9583809003141268,
+           -0.9398677828758705,
+           -0.91184149841655,
+           -0.8744324261607289,
+           -0.8280281088035337,
+           -0.773257197627532,
+           -0.7109671054386467,
+           -0.6421960052806073,
+           -0.5681399558061796,
+           -0.49011605676130904,
+           -0.40952263721462717,
+           -0.32779755247003955,
+           -0.24637571121840676,
+           -0.16664697129783118,
+           -0.08991553004843948,
+           -0.017361894010170707,
+           0.0499915563095736,
+           0.11131048590894761,
+           0.1659732069452842,
+           0.213589299713337,
+           0.25401174633558055,
+           0.28734223986948876,
+           0.31392950963338,
+           0.33436068591047097,
+           0.34944590918370033,
+           0.36019656606134826,
+           0.3677977015782298,
+           0.3735753113370854,
+           0.3789593530700459,
+           0.38544343217170896,
+           0.3945422066327532,
+           0.40774762123805125,
+           0.42648511719965526,
+           0.4520709705913999,
+           0.4856718907866335,
+           0.5282679590593498,
+           0.580619908802823,
+           0.643241644356354,
+           0.7163787677666448,
+           0.799993735088738,
+           0.8937580997042457,
+           0.9970521236714595,
+           1.1089718537096138,
+           1.2283435706533017,
+           1.3537453347815305,
+           1.4835351689948004,
+           1.615885251910199,
+           1.7488213378430426,
+           1.880266484260409,
+           2.0080880530856264,
+           2.1301468631196943,
+           2.2443473091243464,
+           2.348687230405982,
+           2.4413063089587617,
+           2.5205318045364873,
+           2.584920490850055,
+           2.6332957421221557,
+           2.6647788304640714,
+           2.6788136293108207,
+           2.675184073212904,
+           2.6540238958810813,
+           2.615818352345341,
+           2.5613978229383956,
+           2.491923391863234,
+           2.408864686582712,
+           2.313970451436128,
+           2.2092325051518493,
+           2.0968438929542694,
+           1.9791521857963281,
+           1.858608998388242,
+           1.737716891196121,
+           1.6189748871335035,
+           1.5048238696292637,
+           1.3975931342177486,
+           1.2994493405968646,
+           1.2123490568249728
+          ],
+          [
+           1.1590696437878338,
+           1.0950184302087247,
+           1.0458844928368154,
+           1.0125463651263056,
+           0.9955282712583591,
+           0.9949896002334618,
+           1.010722647991985,
+           1.042158665681596,
+           1.0883820551240533,
+           1.1481523595104968,
+           1.2199335130638074,
+           1.3019296423222853,
+           1.3921265579674027,
+           1.4883379434579087,
+           1.5882551383413541,
+           1.6894993325925007,
+           1.789674935614536,
+           1.8864228608632496,
+           1.9774724749075572,
+           2.0606909978631287,
+           2.134129209527897,
+           2.196062410490016,
+           2.2450257075773488,
+           2.2798428352655424,
+           2.2996478855123876,
+           2.303899493941635,
+           2.292387216010145,
+           2.2652300181643783,
+           2.2228670013023266,
+           2.166040662368157,
+           2.0957731799865598,
+           2.013336377277979,
+           1.9202161652981988,
+           1.8180724002579076,
+           1.7086951936602357,
+           1.593958794202249,
+           1.4757742118333395,
+           1.356041776565896,
+           1.2366048170399881,
+           1.119205606744284,
+           1.0054446602137848,
+           0.8967443691920087,
+           0.7943178520545402,
+           0.6991437517383442,
+           0.6119475615298628,
+           0.5331898882954965,
+           0.46306188339109333,
+           0.4014878870936134,
+           0.34813514760766995,
+           0.3024302951630288,
+           0.26358207997286104,
+           0.2306097241753456,
+           0.20237609630654707,
+           0.17762479588973953,
+           0.15502013839227866,
+           0.13318895951529172,
+           0.11076311430567651,
+           0.0864215319749249,
+           0.05893070190843055,
+           0.027182509750311785,
+           -0.009771586474452894,
+           -0.05269095330973373,
+           -0.1021215446912612,
+           -0.15837768281988224,
+           -0.22153035189400383,
+           -0.2914023293937558,
+           -0.3675703010613746,
+           -0.44937392327281167,
+           -0.5359316147746698,
+           -0.6261626833821751,
+           -0.7188152266799468,
+           -0.8124990932756329,
+           -0.9057230566140194,
+           -0.9969352402048914,
+           -1.0845657442557122,
+           -1.1670703614263682,
+           -1.24297423536802,
+           -1.3109143107945556,
+           -1.369679448255129,
+           -1.418247129985193,
+           -1.455815763942704,
+           -1.4818316994246674,
+           -1.4960101969007564,
+           -1.4983497437093456,
+           -1.4891392723491232,
+           -1.4689580151689134,
+           -1.4386679139034446,
+           -1.3993986901188438,
+           -1.3525258685296635,
+           -1.299642224672838,
+           -1.2425232970653195,
+           -1.1830877574845846,
+           -1.1233535675151092,
+           -1.0653909615840835,
+           -1.011273383500788,
+           -0.9630275627724808,
+           -0.9225839471310144,
+           -0.8917287079219803,
+           -0.8720585051767593,
+           -0.8649391399456953,
+           -0.8714691341864146,
+           -0.892449165239842,
+           -0.9283581453995239,
+           -0.9793365805795672,
+           -1.0451776694046298,
+           -1.1253264193803696,
+           -1.2188868646565638,
+           -1.3246372749619295,
+           -1.4410530523406917,
+           -1.5663368260866541,
+           -1.698455081322971,
+           -1.835180497317589,
+           -1.9741390317796939,
+           -2.112860670502988,
+           -2.2488326706976016,
+           -2.3795540634451515,
+           -2.502590147492481,
+           -2.6156257039160304,
+           -2.7165156891386846,
+           -2.803332221712326,
+           -2.8744067648055887,
+           -2.9283665193690336,
+           -2.964164179752409,
+           -2.9811003607998083,
+           -2.9788381793277843,
+           -2.9574096591704953,
+           -2.917213823123429,
+           -2.8590065324106515,
+           -2.7838823299415165,
+           -2.693248732856052,
+           -2.5887935980877894,
+           -2.4724463475754446,
+           -2.3463339833860095,
+           -2.2127329439026115,
+           -2.0740179474727847,
+           -1.9326090372301301,
+           -1.7909180786059153,
+           -1.6512959684738862,
+           -1.5159817918048983,
+           -1.387055108780297,
+           -1.2663924738887966,
+           -1.1556291806729684,
+           -1.05612709420764,
+           -0.9689492813701579,
+           -0.8948419802860403,
+           -0.834224269189702,
+           -0.7871856058141237,
+           -0.7534912159890833,
+           -0.7325951191292049,
+           -0.7236603934303975,
+           -0.7255861094032191,
+           -0.7370402011178677,
+           -0.7564974041021009,
+           -0.7822812706298882,
+           -0.812609180015819,
+           -0.8456391957106585,
+           -0.8795175840167483,
+           -0.9124258019279741,
+           -0.942625784028729,
+           -0.9685024099003955,
+           -0.988602112700727,
+           -1.001666694432257,
+           -1.0066615411973092,
+           -1.0027975791796204,
+           -0.9895464754421293,
+           -0.9666487627436894,
+           -0.9341147500246081,
+           -0.8922182653872092,
+           -0.8414834616384896,
+           -0.7826650911590654,
+           -0.7167228225798339,
+           -0.6447903223306679,
+           -0.5681399558061797,
+           -0.48814407238355295,
+           -0.4062339231002419,
+           -0.32385731735751094,
+           -0.24243615414386607,
+           -0.16332496327124502,
+           -0.08777156302063265,
+           -0.01688088316954868,
+           0.04841708189872224,
+           0.10739433427028015,
+           0.15954622290899148,
+           0.20460650801841157,
+           0.2425557282417978,
+           0.2736226344725142,
+           0.2982786351212339,
+           0.317225380352039,
+           0.33137579242053544,
+           0.3418290212609138,
+           0.3498399645020951,
+           0.3567841350703868,
+           0.36411878378300216,
+           0.37334128567184893,
+           0.3859458745918308,
+           0.4033798589930687,
+           0.4270004712911317,
+           0.45803349349434286,
+           0.49753476281927017,
+           0.546355593854015,
+           0.605113060033599,
+           0.6741659590634694,
+           0.7535971473708737,
+           0.8432027711271739,
+           0.9424887497720873,
+           1.0506746865482597,
+           1.1667051938408624,
+           1.2892684337736047,
+           1.4168214912269368,
+           1.547622021812405,
+           1.6797654557506883,
+           1.8112268941351,
+           1.9399067103766425,
+           2.063678769870717,
+           2.180440107662404,
+           2.288160859026634,
+           2.3849332226308753,
+           2.4690182507890555,
+           2.538889305979088,
+           2.593271096275646,
+           2.6311733029234414,
+           2.6519179385482237,
+           2.655159721461818,
+           2.6408989166111687,
+           2.6094862729418904,
+           2.5616198759306554,
+           2.4983339281756125,
+           2.420979665472567,
+           2.331198805981262,
+           2.2308901112350714,
+           2.122169805417776,
+           2.007326749396565,
+           1.888773394761537,
+           1.7689936473980634,
+           1.6504888473255919,
+           1.5357231197526318,
+           1.4270693703086779,
+           1.3267571847473107,
+           1.2368238503467166,
+           1.1590696437878325
+          ],
+          [
+           1.1129048820895788,
+           1.0596915637119604,
+           1.0220138572401023,
+           1.0005280030276498,
+           0.9955282712583589,
+           1.0069414349285597,
+           1.0343295608030443,
+           1.0769010391341294,
+           1.133529577630307,
+           1.2027806966800314,
+           1.2829450857550864,
+           1.3720780195320643,
+           1.4680438904874324,
+           1.5685647959660125,
+           1.6712720248512345,
+           1.7737592241980362,
+           1.8736359910537355,
+           1.9685806299882997,
+           2.0563908426350803,
+           2.135031171110101,
+           2.202676101105874,
+           2.2577478406237543,
+           2.298947923954796,
+           2.3252819443087276,
+           2.336076888599832,
+           2.330990730109178,
+           2.310014124546562,
+           2.2734642477468054,
+           2.221971004105598,
+           2.1564560191976776,
+           2.0781050033037385,
+           1.9883342305645184,
+           1.8887520173309635,
+           1.7811161996206653,
+           1.6672887006205956,
+           1.5491883427259827,
+           1.4287430931930902,
+           1.3078429373502731,
+           1.1882945484375258,
+           1.07177886925011,
+           0.9598126392872997,
+           0.8537147941771245,
+           0.7545785345161773,
+           0.663249712244233,
+           0.5803120180579371,
+           0.5060792773287335,
+           0.440594978977985,
+           0.38363897639255884,
+           0.3347411164035997,
+           0.2932013761999418,
+           0.25811592322498766,
+           0.22840836374003126,
+           0.2028653155619064,
+           0.18017533274554673,
+           0.15897012736156005,
+           0.1378669780599976,
+           0.11551118817364214,
+           0.0906174583382572,
+           0.06200906989988433,
+           0.02865383491552456,
+           -0.010304145202134178,
+           -0.05551775960010729,
+           -0.10741592124230416,
+           -0.16618891755920923,
+           -0.23178047733087656,
+           -0.30388677714962337,
+           -0.3819624294837543,
+           -0.4652333118097718,
+           -0.5527159171322167,
+           -0.6432427350183116,
+           -0.7354930133918645,
+           -0.8280281088035332,
+           -0.9193305103599055,
+           -1.0078455230894978,
+           -1.0920245228082328,
+           -1.1703686484354545,
+           -1.24147178042722,
+           -1.3040616660366107,
+           -1.3570380932447632,
+           -1.3995070844638295,
+           -1.4308101768187746,
+           -1.4505479756270547,
+           -1.4585973086628317,
+           -1.4551214674289326,
+           -1.4405731940290536,
+           -1.4156902540467944,
+           -1.3814836225639837,
+           -1.3392184974227523,
+           -1.2903885363721768,
+           -1.2366838882595812,
+           -1.1799537485620215,
+           -1.1221643122621672,
+           -1.0653531187366105,
+           -1.0115808808410913,
+           -0.9628819612372839,
+           -0.9212147013571313,
+           -0.888412821095124,
+           -0.8661390899408233,
+           -0.8558424231434006,
+           -0.858719480703905,
+           -0.8756817442994879,
+           -0.9073289201055789,
+           -0.953929366955739,
+           -1.015408082957857,
+           -1.0913426036094738,
+           -1.180966975011202,
+           -1.28318377159213,
+           -1.3965839335860581,
+           -1.5194740100921023,
+           -1.649910213568013,
+           -1.785738525464692,
+           -1.9246399445086122,
+           -2.064179842531451,
+           -2.2018602908654605,
+           -2.3351741456962642,
+           -2.4616596352554465,
+           -2.578954176492426,
+           -2.684846164298552,
+           -2.7773235221232326,
+           -2.8546178778362123,
+           -2.9152433311490897,
+           -2.9580289063361316,
+           -2.982143933301906,
+           -2.9871157676057445,
+           -2.9728394417990835,
+           -2.939579031941879,
+           -2.8879607197808945,
+           -2.818957728014187,
+           -2.7338674985445506,
+           -2.634281666963723,
+           -2.522049556258571,
+           -2.3992360647762956,
+           -2.2680749541502943,
+           -2.130918649021525,
+           -1.990185739445872,
+           -1.8483074269765547,
+           -1.70767417538463,
+           -1.570583816403228,
+           -1.4391923200752765,
+           -1.3154683693151417,
+           -1.2011527809409552,
+           -1.0977236931452068,
+           -1.006368295204872,
+           -0.9279617127786441,
+           -0.8630534854317788,
+           -0.8118618864452661,
+           -0.7742761431167503,
+           -0.7498664233777829,
+           -0.7379012663700325,
+           -0.737371955263309,
+           -0.7470231644532699,
+           -0.7653890644029238,
+           -0.7908339394094442,
+           -0.8215962695807852,
+           -0.8558351507882114,
+           -0.8916778771518614,
+           -0.9272674908409806,
+           -0.9608091140187803,
+           -0.9906139172825795,
+           -1.015139646858885,
+           -1.033026727322304,
+           -1.0431290752697073,
+           -1.0445388991532891,
+           -1.0366049177941912,
+           -1.0189436009675352,
+           -0.9914432155450678,
+           -0.9542606454558938,
+           -0.9078111385231171,
+           -0.852751313406901,
+           -0.7899559309083793,
+           -0.7204890914772077,
+           -0.6455706609745574,
+           -0.5665388460720088,
+           -0.4848099361424808,
+           -0.4018362977530949,
+           -0.3190637491939961,
+           -0.23788945486856672,
+           -0.15962146255461984,
+           -0.08544096098354294,
+           -0.01636826205914134,
+           0.04676658677258728,
+           0.10334777646420779,
+           0.15299165510832474,
+           0.1955581084442088,
+           0.23115508998930986,
+           0.26013616763378505,
+           0.2830911360557436,
+           0.3008299257428102,
+           0.31436021513504964,
+           0.3248593179691453,
+           0.3336410690914316,
+           0.3421185649640014,
+           0.35176372641552023,
+           0.3640647380294915,
+           0.38048247867357055,
+           0.40240708947997106,
+           0.4311158282245175,
+           0.4677333323881789,
+           0.5131953578235939,
+           0.5682169772156446,
+           0.6332661144342286,
+           0.7085431600837454,
+           0.7939672632860587,
+           0.889169728714771,
+           0.9934947702535819,
+           1.106007687804428,
+           1.2255103463356363,
+           1.3505636509250465,
+           1.4795165329639866,
+           1.6105407953329538,
+           1.7416710124574575,
+           1.8708485485447115,
+           1.995968647360094,
+           2.1149294624405752,
+           2.225681839848897,
+           2.3262786379518885,
+           2.4149223710433607,
+           2.490009995969736,
+           2.5501737225544883,
+           2.5943168181272487,
+           2.6216434917250044,
+           2.631682081783474,
+           2.624300929040409,
+           2.599716490101004,
+           2.558493432442219,
+           2.5015366440368743,
+           2.4300752855564944,
+           2.3456392054937627,
+           2.2500282238114124,
+           2.145274963322555,
+           2.0336020656657587,
+           1.917374766569908,
+           1.7990499197042156,
+           1.6811226469391063,
+           1.5660718531018294,
+           1.4563058737857912,
+           1.3541095246819141,
+           1.2615937902118557,
+           1.1806493286716016,
+           1.1129048820895777
+          ],
+          [
+           1.0742453465039652,
+           1.032314285088428,
+           1.0063940430270113,
+           0.9969130276021828,
+           1.0039330855316082,
+           1.0271490215878287,
+           1.0658964147572103,
+           1.1191675360691637,
+           1.1856349803384731,
+           1.2636824417198604,
+           1.3514418946004834,
+           1.4468362910339048,
+           1.5476267572840563,
+           1.651463168201605,
+           1.7559369015891488,
+           1.8586345272462637,
+           1.957191168125154,
+           2.0493422843353915,
+           2.1329726742242108,
+           2.206161559299366,
+           2.267222719515251,
+           2.314738769905162,
+           2.347588815605352,
+           2.364968886346621,
+           2.3664047294178046,
+           2.351756727529674,
+           2.3212169002991696,
+           2.275298140493791,
+           2.214816023992244,
+           2.1408637110217765,
+           2.0547806212541584,
+           1.9581157127554414,
+           1.852586321008557,
+           1.7400336162138996,
+           1.622375812380248,
+           1.5015603085722826,
+           1.3795159600173064,
+           1.2581066642633005,
+           1.139087405636279,
+           1.0240638310111314,
+           0.9144563332319667,
+           0.8114694978953376,
+           0.7160676277335011,
+           0.6289569001095672,
+           0.5505745411894921,
+           0.48108521953649386,
+           0.4203846767443662,
+           0.36811042794860144,
+           0.32365918527234333,
+           0.2862104869886157,
+           0.254755858675773,
+           0.22813269382232607,
+           0.20506192366311288,
+           0.18418845242846188,
+           0.16412326698009674,
+           0.14348609064473608,
+           0.12094744088430923,
+           0.09526896947610568,
+           0.06534101159757315,
+           0.030216345377902843,
+           -0.010860735839242339,
+           -0.05843081265314816,
+           -0.11280182089800295,
+           -0.17403809622155178,
+           -0.24195628144863368,
+           -0.31612821684008324,
+           -0.39589075078949165,
+           -0.4803622273865581,
+           -0.568465232215715,
+           -0.6589550132015243,
+           -0.7504528434450819,
+           -0.8414834616384891,
+           -0.9305156161543199,
+           -1.0160046540936474,
+           -1.0964360386309884,
+           -1.1703686484354547,
+           -1.2364767125802187,
+           -1.2935892632500567,
+           -1.3407260460566424,
+           -1.3771289124914239,
+           -1.4022878289183243,
+           -1.4159607688306206,
+           -1.4181869065973693,
+           -1.4092926978471267,
+           -1.3898906098291057,
+           -1.3608704501124556,
+           -1.3233834292111406,
+           -1.278819277468039,
+           -1.2287769141622056,
+           -1.1750293328501602,
+           -1.1194835172267465,
+           -1.0641363324886959,
+           -1.0110274449783982,
+           -0.9621904050131035,
+           -0.9196030821344542,
+           -0.8851386670991597,
+           -0.8605184500517031,
+           -0.8472675494932276,
+           -0.8466747026497538,
+           -0.8597571361342212,
+           -0.8872314185668807,
+           -0.9294910568792131,
+           -0.986591438757567,
+           -1.058242548948042,
+           -1.1438097011977721,
+           -1.2423223349879544,
+           -1.352490731632899,
+           -1.4727303125452784,
+           -1.6011929982085906,
+           -1.7358049341845072,
+           -1.8743097345562367,
+           -2.0143162574175646,
+           -2.153349814718233,
+           -2.2889056327562236,
+           -2.4185033220092333,
+           -2.5397410872713233,
+           -2.6503484119229,
+           -2.7482359835821186,
+           -2.8315416915824048,
+           -2.8986716181834136,
+           -2.9483350629475478,
+           -2.9795727804572936,
+           -2.9917777720979046,
+           -2.984708149086164,
+           -2.958491772001104,
+           -2.913622567193601,
+           -2.850948617874041,
+           -2.7716523226006746,
+           -2.677223101578725,
+           -2.569423307073985,
+           -2.450248154077772,
+           -2.321880627262725,
+           -2.1866424368615123,
+           -2.0469421865781805,
+           -1.9052219788420948,
+           -1.7639037151702588,
+           -1.6253363513793304,
+           -1.491745338896536,
+           -1.365185425218875,
+           -1.2474979001509563,
+           -1.140273261992379,
+           -1.0448201421604182,
+           -0.9621411712046922,
+           -0.89291629765988,
+           -0.8374938879398739,
+           -0.7958897450316091,
+           -0.7677939907971479,
+           -0.7525855659888623,
+           -0.7493539183090655,
+           -0.7569272765060964,
+           -0.7739067518045623,
+           -0.798705370733326,
+           -0.8295910289658007,
+           -0.8647322668764545,
+           -0.9022457062592751,
+           -0.9402439554719312,
+           -0.9768827878624028,
+           -1.010406425660465,
+           -1.0391898177937375,
+           -1.0617768838173742,
+           -1.0769138051485088,
+           -1.0835765762669225,
+           -1.0809921791238841,
+           -1.0686529098637485,
+           -1.0463235639060486,
+           -1.014041368989688,
+           -0.9721087413189365,
+           -0.9210791228058676,
+           -0.8617363329840458,
+           -0.7950680330720522,
+           -0.7222340477916406,
+           -0.6445304191942413,
+           -0.5633501727165284,
+           -0.48014185633940587,
+           -0.3963669670735711,
+           -0.31345740373527264,
+           -0.23277408052578255,
+           -0.1555678024398714,
+           -0.08294344188501365,
+           -0.01582836768550643,
+           0.04505403486679338,
+           0.09920504820085821,
+           0.1463649581528534,
+           0.18652065454557396,
+           0.21990628613658045,
+           0.24699694096545283,
+           0.2684955055514249,
+           0.2853130350478064,
+           0.29854313681071476,
+           0.30943102755476937,
+           0.3193380653314973,
+           0.32970267837727524,
+           0.3419987103436564,
+           0.35769227303537693,
+           0.3781982416796556,
+           0.40483754276902223,
+           0.43879637021793577,
+           0.48108842224663884,
+           0.5325211800793686,
+           0.5936671519486104,
+           0.6648408844250802,
+           0.7460824007406893,
+           0.8371475660638716,
+           0.9375057065900521,
+           1.0463446271349686,
+           1.1625829852108684,
+           1.284889792994195,
+           1.4117106368341241,
+           1.541300031569755,
+           1.6717591682613937,
+           1.8010781730081833,
+           1.927181874896466,
+           2.0479779858555665,
+           2.1614065267448566,
+           2.2654892941527622,
+           2.3583781522419116,
+           2.438400953877624,
+           2.5041039448377056,
+           2.554289582992204,
+           2.5880488091248046,
+           2.604786935041871,
+           2.60424246467488,
+           2.586498331394241,
+           2.551985215645946,
+           2.501476796887215,
+           2.436076987993791,
+           2.3571993940849865,
+           2.26653942631019,
+           2.166039679928423,
+           2.057849350591217,
+           1.9442786090514594,
+           1.8277489789527404,
+           1.7107408618236775,
+           1.5957394254373356,
+           1.4851801144950922,
+           1.3813950550705745,
+           1.2865616060576814,
+           1.2026542624159253,
+           1.1314010374441468,
+           1.0742453465039643
+          ],
+          [
+           1.0434181141956866,
+           1.0131182185036423,
+           0.9991572008938314,
+           1.0017320231778002,
+           1.0206716055461331,
+           1.055441394884094,
+           1.105156139985866,
+           1.168600562796822,
+           1.2442574279636767,
+           1.3303423383085928,
+           1.424844425602007,
+           1.525571968022397,
+           1.630201851292517,
+           1.736331702423632,
+           1.8415334653866002,
+           1.9434071582668826,
+           2.0396335522216194,
+           2.128024543763683,
+           2.2065700527260295,
+           2.273480367159975,
+           2.3272229711566053,
+           2.3665530292838297,
+           2.3905368585753988,
+           2.3985678918910365,
+           2.39037482070948,
+           2.3660217964682255,
+           2.325900762715787,
+           2.2707161808428498,
+           2.201462595331688,
+           2.1193956558232214,
+           2.025997368664362,
+           1.922936486185448,
+           1.8120250544870298,
+           1.6951722272833138,
+           1.57433651229702,
+           1.45147764646202,
+           1.3285092961281875,
+           1.2072537486812138,
+           1.0893997033308327,
+           0.9764641828421502,
+           0.8697594769209762,
+           0.7703658946694066,
+           0.6791109514042771,
+           0.59655544804268,
+           0.5229867234351969,
+           0.4584191759576397,
+           0.4026019649923994,
+           0.3550336203083255,
+           0.3149831123659023,
+           0.28151677361519173,
+           0.25353031399175,
+           0.2297850467144758,
+           0.20894733631165385,
+           0.18963020213001025,
+           0.1704359593548936,
+           0.14999875703436286,
+           0.12702587927981315,
+           0.10033671149941129,
+           0.06889833726701373,
+           0.03185682159189086,
+           -0.011436649377127303,
+           -0.06140546672185608,
+           -0.11823367651012298,
+           -0.18185881120363256,
+           -0.25197167233983503,
+           -0.3280230803460394,
+           -0.4092374250777027,
+           -0.49463267253147847,
+           -0.5830463136929116,
+           -0.673166584948496,
+           -0.7635681499079486,
+           -0.8527513134069004,
+           -0.9391837429409234,
+           -1.0213436032769962,
+           -1.0977629683038848,
+           -1.1670703614263682,
+           -1.2280312923612955,
+           -1.279585703701284,
+           -1.320881313991263,
+           -1.351301943529101,
+           -1.3704900322111009,
+           -1.3783627024557519,
+           -1.3751208809917592,
+           -1.3612511670923444,
+           -1.3375203173457426,
+           -1.3049624037134249,
+           -1.2648588877713172,
+           -1.218712034986479,
+           -1.1682122641032238,
+           -1.1152001838823429,
+           -1.0616242085796823,
+           -1.0094947611310148,
+           -0.9608361660231142,
+           -0.9176373998750704,
+           -0.8818029050934253,
+           -0.8551046795729798,
+           -0.839136833002126,
+           -0.8352737483508492,
+           -0.8446329067596353,
+           -0.8680433272021593,
+           -0.9060204415180039,
+           -0.9587480738551587,
+           -1.0260680248978091,
+           -1.1074775795850287,
+           -1.2021350667822954,
+           -1.3088734052016069,
+           -1.4262213765351688,
+           -1.552432179016966,
+           -1.6855186370724278,
+           -1.8232942797319172,
+           -1.9634193560897615,
+           -2.1034507338582413,
+           -2.240894530025466,
+           -2.3732602531944145,
+           -2.498115197098019,
+           -2.613137815076467,
+           -2.716168826245901,
+           -2.805258855211371,
+           -2.8787114872685753,
+           -2.935120728176048,
+           -2.9734019891757697,
+           -2.992815870808741,
+           -2.992984189504829,
+           -2.973897874783204,
+           -2.9359165577127317,
+           -2.8797598683628656,
+           -2.8064906565331675,
+           -2.7174905413058528,
+           -2.614428376274253,
+           -2.499222384260248,
+           -2.373996863898348,
+           -2.2410344970398337,
+           -2.1027253874645617,
+           -1.9615140354446328,
+           -1.8198454975227016,
+           -1.6801119954062391,
+           -1.544601221839391,
+           -1.4154475451483353,
+           -1.2945872390546809,
+           -1.1837187622138574,
+           -1.0842689853216698,
+           -0.9973661156990637,
+           -0.923819903689144,
+           -0.8641095360840012,
+           -0.8183794335709569,
+           -0.7864429764925662,
+           -0.7677939907971476,
+           -0.7616256386454056,
+           -0.7668561803285151,
+           -0.7821609102921613,
+           -0.8060094241431427,
+           -0.836707249081719,
+           -0.8724407702557405,
+           -0.9113243124605132,
+           -0.9514481921287088,
+           -0.9909265396718789,
+           -1.0279437072170354,
+           -1.0607981211535,
+           -1.087942511463033,
+           -1.1080195486476043,
+           -1.1198920416418032,
+           -1.1226669932627629,
+           -1.115712969865246,
+           -1.0986704148735025,
+           -1.0714547173816356,
+           -1.034252032473628,
+           -0.9875080346463796,
+           -0.9319099650845972,
+           -0.8683625030385337,
+           -0.7979581469525266,
+           -0.7219429284031105,
+           -0.6416783979058955,
+           -0.5586009133592171,
+           -0.4741793270417923,
+           -0.3898722040741198,
+           -0.3070857132008217,
+           -0.22713330949718688,
+           -0.15119827872587263,
+           -0.08030013586675859,
+           -0.015265767799349891,
+           0.04329391514540214,
+           0.0950011988359453,
+           0.13972219689743537,
+           0.177570607271984,
+           0.20890448665434544,
+           0.23431611827069945,
+           0.2546152292469424,
+           0.27080598818378054,
+           0.2840583770874642,
+           0.2956746803360727,
+           0.3070519631062842,
+           0.31964151932898494,
+           0.3349063520220988,
+           0.35427780462692854,
+           0.37911248928868374,
+           0.41065065612560414,
+           0.44997711641063726,
+           0.4979857729662731,
+           0.5553487243852754,
+           0.6224907980583361,
+           0.6995702331642846,
+           0.7864660820716433,
+           0.8827727308035024,
+           0.9878017605079134,
+           1.1005911867121976,
+           1.2199219261509084,
+           1.3443411568283008,
+           1.47219206033072,
+           1.6016492706886847,
+           1.7307592054611203,
+           1.8574843259425624,
+           1.979750267758306,
+           2.0954947033248947,
+           2.2027167457884365,
+           2.29952568149751,
+           2.384187825480613,
+           2.4551703316987075,
+           2.5111808562079565,
+           2.551202065250483,
+           2.57452009946078,
+           2.5807462469712608,
+           2.5698312387997504,
+           2.542071755605271,
+           2.498108921426532,
+           2.4389187528139953,
+           2.3657947261123624,
+           2.2803228167796554,
+           2.1843495478468,
+           2.0799437554187916,
+           1.9693529332853037,
+           1.8549551524371601,
+           1.7392076612644354,
+           1.6245933557098962,
+           1.5135663635830037,
+           1.4084980122179218,
+           1.3116244430308448,
+           1.2249971003933224,
+           1.150437256435114,
+           1.0894956394932427,
+           1.0434181141956858
+          ],
+          [
+           1.0206839974995527,
+           1.0022657713672298,
+           1.0003645577997182,
+           1.0149442188713114,
+           1.0456022158483447,
+           1.091579188536824,
+           1.1517765814483494,
+           1.2247818935422874,
+           1.3089009480720482,
+           1.4021964135571412,
+           1.5025316601323597,
+           1.6076189110419181,
+           1.7150705498518461,
+           1.8224523724291255,
+           1.9273375305809757,
+           2.0273599024414057,
+           2.120265643468071,
+           2.2039617207542825,
+           2.2765603110152175,
+           2.3364180471153198,
+           2.3821692267506287,
+           2.4127522466791937,
+           2.4274286929871978,
+           2.4257946981513445,
+           2.407784364655941,
+           2.373665247986595,
+           2.324026084200897,
+           2.259757134245989,
+           2.1820236941728948,
+           2.0922334830633984,
+           1.9919987648758288,
+           1.8830941830301025,
+           1.7674113844353372,
+           1.6469115804792704,
+           1.5235772345876468,
+           1.3993640783793113,
+           1.2761546409830133,
+           1.1557144292810444,
+           1.0396518219666322,
+           0.9293826393057628,
+           0.8261002259842776,
+           0.7307517395822154,
+           0.6440211757333376,
+           0.5663194869898821,
+           0.49778197021688264,
+           0.43827291157735,
+           0.387397293510275,
+           0.34451918918169067,
+           0.30878630118703293,
+           0.27915994701873864,
+           0.2544496578355109,
+           0.23335144276331468,
+           0.21448868115835337,
+           0.19645454218529687,
+           0.17785479625193404,
+           0.1573498771242065,
+           0.13369507702080324,
+           0.10577780901747748,
+           0.07265095032333439,
+           0.03356138438639433,
+           -0.012027013326654717,
+           -0.06441655488676344,
+           -0.123665532122243,
+           -0.18958489571778936,
+           -0.26174191526552515,
+           -0.3394707317397444,
+           -0.4218895334444704,
+           -0.507923912821157,
+           -0.5963357990164952,
+           -0.685757213931438,
+           -0.7747279713530448,
+           -0.8617363329840452,
+           -0.9452615544447293,
+           -1.0238172007135509,
+           -1.0959940854014465,
+           -1.1605016924087839,
+           -1.216206971847099,
+           -1.2621694638407586,
+           -1.2976717924617427,
+           -1.322244685421119,
+           -1.335685810445914,
+           -1.338071873157299,
+           -1.3297635899102231,
+           -1.3114033282538125,
+           -1.2839053929512008,
+           -1.2484391222209186,
+           -1.2064051423477515,
+           -1.159405304448304,
+           -1.109206990540547,
+           -1.057702623029396,
+           -1.006865338553619,
+           -0.9587018906084029,
+           -0.915203922802533,
+           -0.8782988040109239,
+           -0.8498012367167396,
+           -0.8313668399035977,
+           -0.8244488681019243,
+           -0.8302591594986097,
+           -0.8497343099901992,
+           -0.8835079489817396,
+           -0.9318898495165611,
+           -0.9948524434308476,
+           -1.0720251355943593,
+           -1.1626966242305228,
+           -1.2658252413776694,
+           -1.3800571334834488,
+           -1.5037519116795686,
+           -1.635015219145264,
+           -1.7717374936210386,
+           -1.9116380507575315,
+           -2.052313482344529,
+           -2.191289255826144,
+           -2.326073320547217,
+           -2.4542104739202246,
+           -2.573336218474585,
+           -2.6812288491412475,
+           -2.77585854897218,
+           -2.8554323398891817,
+           -2.9184338313656637,
+           -2.963656831850168,
+           -2.990232032294951,
+           -2.997646134853533,
+           -2.985752978685507,
+           -2.954776404509171,
+           -2.905304795462247,
+           -2.838277429204827,
+           -2.7549629702286746,
+           -2.6569306173079603,
+           -2.546014594422146,
+           -2.4242728300957954,
+           -2.2939408061393176,
+           -2.157381668952598,
+           -2.0170337821702384,
+           -1.8753569564361503,
+           -1.7347786191529524,
+           -1.5976411835498845,
+           -1.4661518424937825,
+           -1.3423359490188809,
+           -1.2279950541836868,
+           -1.1246705558711825,
+           -1.0336137724516856,
+           -0.9557630962981988,
+           -0.8917287079219806,
+           -0.841785146289148,
+           -0.805871839258378,
+           -0.7836015047646897,
+           -0.7742761431167496,
+           -0.776910158242059,
+           -0.7902599753718332,
+           -0.8128593686613245,
+           -0.8430595783344016,
+           -0.879073186361229,
+           -0.9190206350782217,
+           -0.9609782165441786,
+           -1.0030263331016784,
+           -1.043296832155242,
+           -1.080018250421809,
+           -1.1115578639515122,
+           -1.136459528441178,
+           -1.153476407480067,
+           -1.1615978214735796,
+           -1.1600696036408282,
+           -1.1484075177763657,
+           -1.1264034711479942,
+           -1.0941244404639154,
+           -1.0519042146383835,
+           -1.0003282404484133,
+           -0.9402120315326157,
+           -0.8725737631733276,
+           -0.7986018208785823,
+           -0.7196181963133773,
+           -0.6370387265001741,
+           -0.552331248883302,
+           -0.46697279394557323,
+           -0.38240695738863006,
+           -0.3000025849757876,
+           -0.2210148652581596,
+           -0.14654985956047595,
+           -0.07753340649380182,
+           -0.014685222250287963,
+           0.041501119017719766,
+           0.0907717948373597,
+           0.13311957210817518,
+           0.16878368807331612,
+           0.19824277174459562,
+           0.22220098504766028,
+           0.24156774056072877,
+           0.2574315213317158,
+           0.27102848358698517,
+           0.28370666123534355,
+           0.2968867084001422,
+           0.3120202097774054,
+           0.33054665601157646,
+           0.3538502207519465,
+           0.38321748655218074,
+           0.41979724798025636,
+           0.4645634726304865,
+           0.5182824253138553,
+           0.5814848593869052,
+           0.6544440544558849,
+           0.7371603346462988,
+           0.8293525398587231,
+           0.930456747965631,
+           1.0396323630929851,
+           1.1557754985443978,
+           1.2775393972380287,
+           1.4033614523978681,
+           1.5314962212038958,
+           1.6600536684494878,
+           1.787041739919602,
+           1.9104122496826899,
+           2.0281089747391516,
+           2.1381167868367275,
+           2.2385106164251174,
+           2.3275030386445636,
+           2.403489296153384,
+           2.465088627982014,
+           2.511180856207956,
+           2.5409372911265393,
+           2.553845148140744,
+           2.5497248226127858,
+           2.528739538700244,
+           2.4913970706079294,
+           2.4385434252711597,
+           2.371348569583257,
+           2.2912844781311916,
+           2.2000959642715525,
+           2.0997649336667363,
+           1.9924688607627214,
+           1.8805344311403092,
+           1.766387412685143,
+           1.652499913118039,
+           1.5413362482467856,
+           1.4352986826631335,
+           1.3366743115546311,
+           1.24758432861602,
+           1.1699368712650142,
+           1.1053845517684837,
+           1.0552876734479624,
+           1.0206839974995523
+          ],
+          [
+           1.0062353373301178,
+           0.9998487602927527,
+           1.0100058989589125,
+           1.0364378335285624,
+           1.0785139921938558,
+           1.1352566604591785,
+           1.2053633091138967,
+           1.2872362088251115,
+           1.3790186272319451,
+           1.4786367494745625,
+           1.5838463290335407,
+           1.692282965827858,
+           1.8015148253687086,
+           1.909096558379791,
+           2.012623155953948,
+           2.1097824815650665,
+           2.198405257886126,
+           2.2765113524278853,
+           2.342351299835696,
+           2.394442117913352,
+           2.431596616111531,
+           2.4529455558067044,
+           2.45795219722788,
+           2.4464189540263126,
+           2.418486068637492,
+           2.3746224150262365,
+           2.3156087253830373,
+           2.2425137191964426,
+           2.15666378241587,
+           2.0596069970148787,
+           1.953072453461154,
+           1.8389258872029461,
+           1.7191227626900325,
+           1.5956599827119229,
+           1.4705274257103844,
+           1.3456605086917937,
+           1.2228949386550638,
+           1.1039247520267257,
+           0.9902646511311923,
+           0.8832175315649283,
+           0.7838479574408315,
+           0.6929621863114114,
+           0.6110951761011629,
+           0.5385048268636083,
+           0.47517352515205713,
+           0.42081687290857067,
+           0.37489930069892424,
+           0.3366560914138625,
+           0.30512117956239737,
+           0.2791599470187386,
+           0.2575061121421295,
+           0.23880170864445696,
+           0.2216390759183213,
+           0.20460373558940484,
+           0.18631701095400702,
+           0.16547725711188718,
+           0.14089860967654425,
+           0.11154622788317665,
+           0.0765671019620019,
+           0.03531561238884828,
+           -0.012626832941668841,
+           -0.06743860197946222,
+           -0.12905143177794182,
+           -0.19715098359293926,
+           -0.27118434954946713,
+           -0.3503743187102861,
+           -0.4337400333278672,
+           -0.520123498348388,
+           -0.6082212531270673,
+           -0.6966203777318298,
+           -0.7838378906410683,
+           -0.868362503038533,
+           -0.9486976296301742,
+           -1.0234045186496827,
+           -1.0911443554734572,
+           -1.1507182152949473,
+           -1.201103790139745,
+           -1.2414878929386386,
+           -1.271293844522649,
+           -1.2902029757196303,
+           -1.2981696230879878,
+           -1.2954291595829355,
+           -1.2824987765597198,
+           -1.2601709166045085,
+           -1.2294994431668882,
+           -1.1917788181734394,
+           -1.1485167380773484,
+           -1.1014008476304684,
+           -1.0522603047887058,
+           -1.0030231056740786,
+           -0.9556701919676485,
+           -0.9121874515895176,
+           -0.8745167847431266,
+           -0.8445074397425931,
+           -0.8238688255997839,
+           -0.8141259809561111,
+           -0.8165788221805335,
+           -0.8322662086273266,
+           -0.8619357521617033,
+           -0.906020163774886,
+           -0.9646207756648439,
+           -1.037498706302256,
+           -1.124073952894895,
+           -1.2234325047799204,
+           -1.334341377286685,
+           -1.4552712732812116,
+           -1.5844263936558096,
+           -1.7197807430414354,
+           -1.8591201173135439,
+           -2.0000888189824604,
+           -2.1402400287873733,
+           -2.27708866967804,
+           -2.4081655351718285,
+           -2.531071419435922,
+           -2.6435299822601857,
+           -2.7434381085059334,
+           -2.828912578037564,
+           -2.898331947231416,
+           -2.9503726548680413,
+           -2.9840385008559553,
+           -2.998682802524622,
+           -2.9940227063721316,
+           -2.97014531895563,
+           -2.9275055145551474,
+           -2.8669154746102685,
+           -2.78952620992578,
+           -2.6968015065032422,
+           -2.5904849149676994,
+           -2.472560567574464,
+           -2.34520875172392,
+           -2.2107572912751037,
+           -2.0716298837799734,
+           -1.9302926107352258,
+           -1.7891998774276676,
+           -1.6507410480170572,
+           -1.5171890199879683,
+           -1.3906519305905185,
+           -1.2730291076948026,
+           -1.1659722706232085,
+           -1.0708528556682086,
+           -0.988736189405052,
+           -0.9203630643275357,
+           -0.8661390899408236,
+           -0.8261320027148864,
+           -0.8000769249097728,
+           -0.787389369984578,
+           -0.7871856058141227,
+           -0.7983098108267107,
+           -0.8193672967426152,
+           -0.8487629287645717,
+           -0.884743753308495,
+           -0.9254447475716661,
+           -0.9689365366992168,
+           -1.0132738846302558,
+           -1.0565437547661776,
+           -1.096911756549784,
+           -1.1326658432772116,
+           -1.1622562036613848,
+           -1.1843303928103373,
+           -1.197762874719576,
+           -1.201678294874381,
+           -1.1954679643924457,
+           -1.1787992121874633,
+           -1.1516174444817908,
+           -1.1141409370374455,
+           -1.0668485700351373,
+           -1.0104608939827429,
+           -0.945915082911045,
+           -0.8743344842220702,
+           -0.796993609077539,
+           -0.7152795198078735,
+           -0.6306506586966446,
+           -0.5445942234873051,
+           -0.45858322758173614,
+           -0.3740343863821238,
+           -0.29226794553010604,
+           -0.21447051261559044,
+           -0.14166187267325434,
+           -0.07466666154859786,
+           -0.014091642716365564,
+           0.03969081435023597,
+           0.08655261887675662,
+           0.12661294497851178,
+           0.1602342382621173,
+           0.18801134433994846,
+           0.21075404080556256,
+           0.22946342715112525,
+           0.24530278853319595,
+           0.25956369510438587,
+           0.27362822510976453,
+           0.28892830386771556,
+           0.3069032294500248,
+           0.32895650731312337,
+           0.356413138963497,
+           0.39047850333576495,
+           0.43219993402700846,
+           0.4824320317034622,
+           0.5418066604261849,
+           0.610708461555408,
+           0.6892565821331199,
+           0.7772931596028702,
+           0.8743789352627067,
+           0.9797961891878023,
+           1.0925590039937831,
+           1.2114306783822824,
+           1.3349479285946286,
+           1.4614513412953907,
+           1.589121379417227,
+           1.7160190972188165,
+           1.8401305959271854,
+           1.9594141500435682,
+           2.0718488592953803,
+           2.1754836342778434,
+           2.268485306312403,
+           2.34918466449256,
+           2.416119265084317,
+           2.468071929452908,
+           2.5041039448377056,
+           2.523582105254324,
+           2.526198874608386,
+           2.5119851172538734,
+           2.481315018753411,
+           2.43490300716785,
+           2.373792678230998,
+           2.299337921520989,
+           2.2131766344644705,
+           2.11719759203596,
+           2.0135012078809384,
+           1.9043550731518433,
+           1.7921452888752105,
+           1.679324712951069,
+           1.5683593212985736,
+           1.4616739322377543,
+           1.3615985626748364,
+           1.2703166735134264,
+           1.189816520172532,
+           1.1218467531262206,
+           1.0678773146840963,
+           1.0290665541803306,
+           1.0062353373301176
+          ],
+          [
+           1.000194375890509,
+           1.0058876342876115,
+           1.0279996542624508,
+           1.066031021443582,
+           1.1191284860620347,
+           1.1861042794744132,
+           1.2654629550181868,
+           1.3554351168771017,
+           1.4540172381490624,
+           1.5590166262293488,
+           1.6681004734113387,
+           1.7788478361658062,
+           1.8888033201557504,
+           1.9955312112555452,
+           2.096668786522677,
+           2.189977563321836,
+           2.2733912989792286,
+           2.3450596360714493,
+           2.4033863976512806,
+           2.4470616696589302,
+           2.4750869611591706,
+           2.486792903083464,
+           2.4818491286395266,
+           2.460266168978657,
+           2.4223893913958725,
+           2.36888519952087,
+           2.3007199009267065,
+           2.2191318227882655,
+           2.1255974163895694,
+           2.021792232513286,
+           1.9095477686292623,
+           1.790805282473059,
+           1.6675677328419318,
+           1.541851045689996,
+           1.4156359110536472,
+           1.290821293900167,
+           1.1691807903263243,
+           1.0523228810229255,
+           0.9416560286377303,
+           0.8383594373210838,
+           0.7433601446018853,
+           0.6573169515776333,
+           0.5806115213638263,
+           0.5133467922748044,
+           0.4553526659164069,
+           0.40619874593738714,
+           0.36521372523293727,
+           0.3315108523700492,
+           0.30401875607942663,
+           0.28151677361519156,
+           0.2626738179251104,
+           0.24608973264227466,
+           0.23033802501629763,
+           0.21400883647858346,
+           0.19575100929553718,
+           0.1743121356850277,
+           0.1485755321011329,
+           0.11759316466266574,
+           0.08061365976807428,
+           0.037104664036554734,
+           -0.01323103347680519,
+           -0.07044604011405627,
+           -0.13434580832898477,
+           -0.20449306230196465,
+           -0.2802190879248687,
+           -0.36064159197796436,
+           -0.4446886641364675,
+           -0.5311282150992359,
+           -0.6186021197046233,
+           -0.7056641690682827,
+           -0.7908208337325568,
+           -0.8725737631733269,
+           -0.949462897746348,
+           -1.020109048562393,
+           -1.0832548094296353,
+           -1.1378027027283153,
+           -1.1828495269907457,
+           -1.217715966443274,
+           -1.241970639549704,
+           -1.2554479017877487,
+           -1.2582588740586382,
+           -1.250795338385548,
+           -1.2337263226487658,
+           -1.2079873815299162,
+           -1.1747627669469534,
+           -1.1354608633823091,
+           -1.0916834370550372,
+           -1.0451894084849673,
+           -0.9978540015778307,
+           -0.9516242452759802,
+           -0.9084719029279558,
+           -0.8703449772764824,
+           -0.8391189834440171,
+           -0.8165491973025543,
+           -0.8042250716751578,
+           -0.8035279681987937,
+           -0.8155932793876849,
+           -0.8412779151931703,
+           -0.8811340035521613,
+           -0.9353895080575553,
+           -1.0039363015167249,
+           -1.086326055787838,
+           -1.1817741202526955,
+           -1.2891713682004746,
+           -1.4071037969956466,
+           -1.5338794789374197,
+           -1.667562279840754,
+           -1.806011596016482,
+           -1.9469272116124177,
+           -2.087898250883093,
+           -2.226455097048172,
+           -2.3601230735480643,
+           -2.4864766366164255,
+           -2.603192811362469,
+           -2.7081026174501543,
+           -2.799239274686288,
+           -2.8748820523489393,
+           -2.9335947271476654,
+           -2.974257740876397,
+           -2.9960932970508116,
+           -2.9986828025246224,
+           -2.98197624120911,
+           -2.9462932581790597,
+           -2.8923159289903637,
+           -2.8210733861825714,
+           -2.7339186679010035,
+           -2.6324983376583497,
+           -2.518715594993891,
+           -2.3946877500366637,
+           -2.26269906702455,
+           -2.125150089482425,
+           -1.9845046404276439,
+           -1.843235742720692,
+           -1.7037717262941199,
+           -1.56844377999426,
+           -1.439436166429243,
+           -1.3187402495484002,
+           -1.2081133884154054,
+           -1.1090436291877976,
+           -1.0227209837014395,
+           -0.9500159208416816,
+           -0.8914655200762428,
+           -0.8472675494932278,
+           -0.8172825380389828,
+           -0.8010437181227591,
+           -0.7977745250984422,
+           -0.8064131589932484,
+           -0.8256435456550417,
+           -0.8539318833308512,
+           -0.8895678302368832,
+           -0.9307092820828374,
+           -0.9754296083218192,
+           -1.0217661640038092,
+           -1.067768871702676,
+           -1.1115476755180156,
+           -1.1513177063340965,
+           -1.1854410633243786,
+           -1.2124642093879114,
+           -1.231150095396134,
+           -1.240504266813431,
+           -1.2397943629026151,
+           -1.2285625893677157,
+           -1.2066309256114227,
+           -1.174099013251035,
+           -1.1313348584836458,
+           -1.078958662654835,
+           -1.01782026841539,
+           -0.9489708688245636,
+           -0.8736297696879536,
+           -0.7931471177489579,
+           -0.7089636060531094,
+           -0.6225682404395585,
+           -0.5354552959071203,
+           -0.44908160747804104,
+           -0.3648253267939476,
+           -0.28394723341345185,
+           -0.20755561975418893,
+           -0.136575672645113,
+           -0.07172415499060003,
+           -0.013490051149037485,
+           0.037878317139609874,
+           0.08237936709196166,
+           0.12025736451824447,
+           0.1519945900524605,
+           0.17829676694602095,
+           0.20007213187249573,
+           0.21840469698684142,
+           0.23452240435601068,
+           0.24976100893810493,
+           0.2655246400895024,
+           0.28324408121256783,
+           0.3043338703158729,
+           0.330149359304279,
+           0.36194487581377677,
+           0.4008341081517996,
+           0.4477537819296255,
+           0.5034316175341915,
+           0.5683594526293735,
+           0.6427722859926075,
+           0.7266338513530435,
+           0.8196291661745553,
+           0.9211643246038003,
+           1.0303736204709246,
+           1.146133899878708,
+           1.2670858582201674,
+           1.3916618180677756,
+           1.5181193567748201,
+           1.6445800000565465,
+           1.7690720641446345,
+           1.8895766177390603,
+           2.004075448774531,
+           2.110599862211123,
+           2.207279105210198,
+           2.2923872160101446,
+           2.3643871226757773,
+           2.4219708770211303,
+           2.464094996030986,
+           2.4900099959697357,
+           2.4992833403596273,
+           2.491815178847872,
+           2.467846425879272,
+           2.4279589118578406,
+           2.3730675306255904,
+           2.3044045009260534,
+           2.2234960512949877,
+           2.132132022813823,
+           2.032329057813933,
+           1.9262882006443338,
+           1.8163478751012891,
+           1.7049333186301139,
+           1.5945036430710098,
+           1.4874977532868838,
+           1.386280386923848,
+           1.293089539982898,
+           1.2099865137393095,
+           1.1388097595000437,
+           1.0811336101374216,
+           1.0382328733799033,
+           1.0110541242245428,
+           1.000194375890509
+          ],
+          [
+           1.0026122224480716,
+           1.0203313017451878,
+           1.054193588398198,
+           1.103473410855538,
+           1.1671020804564889,
+           1.2436918517168492,
+           1.3315670489614697,
+           1.4288016240757804,
+           1.5332622586377826,
+           1.642655993691846,
+           1.7545812650788817,
+           1.8665811440816527,
+           1.9761975340485787,
+           2.0810250547809326,
+           2.1787633582214685,
+           2.267266661031364,
+           2.3445893509081617,
+           2.409026622186899,
+           2.459149219915756,
+           2.493831517133667,
+           2.5122723138948384,
+           2.5140079246354117,
+           2.4989173083689096,
+           2.4672191893039437,
+           2.419461309054273,
+           2.356502140909792,
+           2.2794855770240736,
+           2.1898092664454984,
+           2.0890874316082666,
+           1.97910911957768,
+           1.8617929489089762,
+           1.7391394909312778,
+           1.6131824737724665,
+           1.4859400173695168,
+           1.3593670976701249,
+           1.2353103985765954,
+           1.1154666419975845,
+           1.0013453914484491,
+           0.8942372054281934,
+           0.7951878763500514,
+           0.7049793326850002,
+           0.6241176101963817,
+           0.5528281170344165,
+           0.4910582315802319,
+           0.4384870859481066,
+           0.3945422066327534,
+           0.3584225114635292,
+           0.3291270031008087,
+           0.30548835773963895,
+           0.28621048698861534,
+           0.2699090540551163,
+           0.25515385477587776,
+           0.24051193140659421,
+           0.2245902734434535,
+           0.20607697538162234,
+           0.18377976577307117,
+           0.1566608940570102,
+           0.12386745953452015,
+           0.08475638803142387,
+           0.038913403143018985,
+           -0.013834503122132646,
+           -0.07341342500304564,
+           -0.13950386895401737,
+           -0.2115490145366587,
+           -0.28876969241680817,
+           -0.3701856857649405,
+           -0.45464279549931846,
+           -0.5408449581902972,
+           -0.6273905719205214,
+           -0.7128120733737277,
+           -0.7956177217691388,
+           -0.8743344842220695,
+           -0.9475508842786995,
+           -1.0139586716198372,
+           -1.0723921963995715,
+           -1.1218644257895376,
+           -1.16159862172649,
+           -1.1910548056097343,
+           -1.2099502651258813,
+           -1.2182735072777884,
+           -1.2162912263544736,
+           -1.204548031889501,
+           -1.1838588652072353,
+           -1.1552942193500864,
+           -1.120158461340845,
+           -1.079961733229226,
+           -1.0363860747248286,
+           -0.9912465612229381,
+           -0.9464483828522184,
+           -0.9039408994523184,
+           -0.8656697903172864,
+           -0.8335284739359208,
+           -0.8093100003218834,
+           -0.7946606160730993,
+           -0.7910361699899631,
+           -0.7996624656152277,
+           -0.8215005778613691,
+           -0.8572180360807503,
+           -0.9071666382675023,
+           -0.9713675038873358,
+           -1.0495037999330183,
+           -1.1409213904163178,
+           -1.24463746814229,
+           -1.359357033960472,
+           -1.4834968975084457,
+           -1.615216689461603,
+           -1.7524562030178583,
+           -1.8929782260343282,
+           -2.0344158887667274,
+           -2.174323438931328,
+           -2.310229268636674,
+           -2.4396899588059795,
+           -2.5603440775266093,
+           -2.6699644700888645,
+           -2.766507810331334,
+           -2.8481602445661096,
+           -2.913378049352206,
+           -2.960922340563248,
+           -2.9898870107549746,
+           -2.99971923140407,
+           -2.990232032294952,
+           -2.9616086579108343,
+           -2.9143985955831457,
+           -2.8495053676321658,
+           -2.768166374991035,
+           -2.671925268098727,
+           -2.5625974975999415,
+           -2.4422298583095006,
+           -2.313054981082967,
+           -2.1774418452663005,
+           -2.0378434764261506,
+           -1.8967430578789932,
+           -1.7565997186237219,
+           -1.6197952638507755,
+           -1.4885830872119727,
+           -1.3650404471983835,
+           -1.2510252047294501,
+           -1.148138007540491,
+           -1.0576907719445017,
+           -0.980682157387635,
+           -0.9177805577547415,
+           -0.8693149498449748,
+           -0.8352737483508494,
+           -0.8153116227370241,
+           -0.808764039389276,
+           -0.8146691069946828,
+           -0.8317961288536643,
+           -0.8586801069617478,
+           -0.8936613030933506,
+           -0.9349288451473751,
+           -0.9805672754843595,
+           -1.0286048740713347,
+           -1.0770625544393229,
+           -1.1240021255115444,
+           -1.167572737298073,
+           -1.2060543825540315,
+           -1.2378974083206522,
+           -1.2617570986832647,
+           -1.2765225203285357,
+           -1.2813389722438167,
+           -1.2756235463750458,
+           -1.2590734830638592,
+           -1.2316671891586828,
+           -1.1936579732109132,
+           -1.1455607364467435,
+           -1.0881320356340347,
+           -1.0223441001084994,
+           -0.9493535359415839,
+           -0.8704655817748238,
+           -0.7870948899500356,
+           -0.7007238905374336,
+           -0.612859852644707,
+           -0.5249917856054879,
+           -0.4385483216400975,
+           -0.35485769143536444,
+           -0.2751108456154971,
+           -0.20032868979658722,
+           -0.1313342910298217,
+           -0.06873078175678839,
+           -0.012885537285186602,
+           0.036078961932407706,
+           0.07828734708149213,
+           0.11410660181400009,
+           0.1441344545966827,
+           0.1691812292834622,
+           0.1902456320316525,
+           0.20848511192919963,
+           0.2251815757284784,
+           0.24170336024887526,
+           0.25946446617074265,
+           0.27988213153050145,
+           0.3043338703158728,
+           0.33411511991742643,
+           0.37039863030589276,
+           0.4141966878975766,
+           0.466327199096655,
+           0.5273845641241258,
+           0.5977161532861068,
+           0.6774050582347191,
+           0.7662596335046477,
+           0.8638101725884965,
+           0.9693128823175476,
+           1.081761133859794,
+           1.1999037828856567,
+           1.3222701700523671,
+           1.447201240489198,
+           1.5728860617826312,
+           1.6974028780959332,
+           1.8187637171200126,
+           1.9349614696361208,
+           2.0440182910788467,
+           2.144034132466684,
+           2.2332341955620896,
+           2.3100141245465617,
+           2.3729817935187953,
+           2.420994624678954,
+           2.453191474372579,
+           2.469018250789055,
+           2.4682465749887745,
+           2.450984962484135,
+           2.4176821817909957,
+           2.369122634821783,
+           2.306413797093571,
+           2.230965948734835,
+           2.1444646154462035,
+           2.048836317266918,
+           1.9462083878084397,
+           1.8388637734624804,
+           1.7291918473302783,
+           1.6196363731371592,
+           1.5126418276781226,
+           1.4105993345386252,
+           1.315793475814391,
+           1.2303512319199787,
+           1.1561942526836788,
+           1.0949955868746675,
+           1.0481418939112102,
+           1.016702033243601,
+           1.0014027768887426,
+           1.0026122224480716
+          ],
+          [
+           1.01346842092684,
+           1.0430575627029564,
+           1.0883660888304754,
+           1.148448222207131,
+           1.222028897060342,
+           1.3075321602666419,
+           1.4031163203965415,
+           1.5067150165715233,
+           1.6160832399659906,
+           1.7288472249660751,
+           1.8425570374056581,
+           1.9547406260906544,
+           2.0629580724513277,
+           2.1648547723533222,
+           2.2582123138255343,
+           2.340995873953312,
+           2.4113970459361194,
+           2.4678711211263047,
+           2.5091679879197986,
+           2.534355966264329,
+           2.542838069407827,
+           2.5343603690652796,
+           2.5090123318920794,
+           2.467219189303944,
+           2.409726594514276,
+           2.33757800547225,
+           2.252085405663997,
+           2.1547941322634094,
+           2.0474427190641675,
+           1.931918776657825,
+           1.8102120216844315,
+           1.6843656285530832,
+           1.5564271093829745,
+           1.4283999303501052,
+           1.3021970451829699,
+           1.1795974700144838,
+           1.0622069396696352,
+           0.9514235759326735,
+           0.8484093662041964,
+           0.754068099593,
+           0.6690302407265093,
+           0.593645043618615,
+           0.5279800232856944,
+           0.4718277160890557,
+           0.42471947568545015,
+           0.385945874591831,
+           0.3545831161322487,
+           0.32952471204966294,
+           0.30951755104798645,
+           0.29320137619994135,
+           0.2791506071605054,
+           0.265917388470454,
+           0.252074719237404,
+           0.2362585227391374,
+           0.21720754686662117,
+           0.19380004694132127,
+           0.16508628972336142,
+           0.13031602912497314,
+           0.08896023739633682,
+           0.04072652695693658,
+           -0.014432136251378609,
+           -0.0763156512275125,
+           -0.14448197412610275,
+           -0.21825914374826114,
+           -0.29676382104209115,
+           -0.37892585271902496,
+           -0.46351821096079465,
+           -0.5491915195781452,
+           -0.6345122554921949,
+           -0.7180036161432773,
+           -0.7981879709074078,
+           -0.8736297696879529,
+           -0.9429777657263613,
+           -1.0050054227940266,
+           -1.0586484190048893,
+           -1.1030382295136691,
+           -1.1375308666216575,
+           -1.1617299759229847,
+           -1.1755036281081903,
+           -1.1789943043889088,
+           -1.1726217452656487,
+           -1.1570785132348962,
+           -1.1333183054903655,
+           -1.1025372380609877,
+           -1.0661485034827214,
+           -1.0257509754689276,
+           -0.9830924917943782,
+           -0.940028686741634,
+           -0.8984783634075951,
+           -0.8603764908857214,
+           -0.8276259793765035,
+           -0.8020494258457522,
+           -0.7853420328626568,
+           -0.7790268833561255,
+           -0.784413704620503,
+           -0.80256217710643,
+           -0.8342507391834161,
+           -0.8799517106543706,
+           -0.9398134084381323,
+           -1.0136497611392792,
+           -1.1009377492575947,
+           -1.2008228089520676,
+           -1.3121321441945435,
+           -1.4333956995682073,
+           -1.562874358626472,
+           -1.698594755247219,
+           -1.8383899221821067,
+           -1.9799448560521746,
+           -2.1208459549786705,
+           -2.2586331869284337,
+           -2.3908537761529973,
+           -2.515116153598079,
+           -2.6291429059268827,
+           -2.730821477167764,
+           -2.8182514265432967,
+           -2.889787124603224,
+           -2.94407487549308,
+           -2.9800835835027817,
+           -2.9971282338082763,
+           -2.994885626870348,
+           -2.973401989175771,
+           -2.9330922754484448,
+           -2.8747311744459494,
+           -2.799436027201644,
+           -2.708642058291035,
+           -2.6040705027336113,
+           -2.487690379065402,
+           -2.361674808857069,
+           -2.228352910877972,
+           -2.0901584011245795,
+           -1.9495761055594274,
+           -1.8090876388349524,
+           -1.671117518411424,
+           -1.5379809689696884,
+           -1.4118346272685085,
+           -1.294631283744529,
+           -1.1880796960542443,
+           -1.0936103839314306,
+           -1.012348167303032,
+           -0.9450920442201958,
+           -0.8923028259026156,
+           -0.8540987574811348,
+           -0.83025915949861,
+           -0.820235931644314,
+           -0.8231725712979236,
+           -0.837930179865572,
+           -0.8631197639844265,
+           -0.8971399904889601,
+           -0.9382194271611557,
+           -0.9844621987838108,
+           -1.0338959123278846,
+           -1.0845206580098896,
+           -1.1343578755207713,
+           -1.1814978872838005,
+           -1.2241449427320619,
+           -1.2606586881601398,
+           -1.2895910738505965,
+           -1.3097178313987186,
+           -1.3200637963613577,
+           -1.3199215109248772,
+           -1.308862714186606,
+           -1.28674250951387,
+           -1.2536961847105956,
+           -1.2101288467096347,
+           -1.1566982135618873,
+           -1.0942910780863335,
+           -1.0239941153988907,
+           -0.9470598467251373,
+           -0.8648686909442367,
+           -0.7788881302666156,
+           -0.6906300849826226,
+           -0.6016076326659296,
+           -0.513292218614352,
+           -0.42707248643246054,
+           -0.34421581101191434,
+           -0.2658335419755236,
+           -0.19285086584044972,
+           -0.12598207228759803,
+           -0.06571186713923782,
+           -0.012283215585646743,
+           0.03430797208789991,
+           0.0743111791862968,
+           0.10821269510150841,
+           0.13672033219749163,
+           0.16074185292572524,
+           0.18135767791822832,
+           0.19978859615645095,
+           0.2173593302875612,
+           0.23545892039073538,
+           0.2554989751670978,
+           0.27887089843712637,
+           0.3069032294500245,
+           0.34082023702325137,
+           0.38170287985147416,
+           0.4304531891018102,
+           0.4877630460142966,
+           0.554088218706282,
+           0.6296283914247703,
+           0.7143137693570661,
+           0.8077986765400592,
+           0.9094623875382983,
+           1.0184172498182198,
+           1.1335239677380262,
+           1.2534137354732409,
+           1.3765167296295964,
+           1.5010963072133363,
+           1.6252881052122417,
+           1.747143108084552,
+           1.8646736422750474,
+           1.9759011752344384,
+           2.078904742436278,
+           2.17186880100652,
+           2.253129313524328,
+           2.321216900299169,
+           2.374895962217149,
+           2.413198767594362,
+           2.4354536132048183,
+           2.441306308958764,
+           2.4307343942211004,
+           2.404053667623496,
+           2.361916797193611,
+           2.305303969172683,
+           2.235505727318631,
+           2.1540983450402043,
+           2.062912255684049,
+           1.9639942371844192,
+           1.8595642018577738,
+           1.7519675765493414,
+           1.6436243692723052,
+           1.536976103152525,
+           1.434431854773525,
+           1.3383146604733394,
+           1.25080955007306,
+           1.1739144329616986,
+           1.1093949972163402,
+           1.0587446900229527,
+           1.023150729295782,
+           1.003466954925559,
+           1.0001941669386758,
+           1.0134684209268405
+          ],
+          [
+           1.0326711229751988,
+           1.0738741427094647,
+           1.1302280407423932,
+           1.2005749482429935,
+           1.283444230150458,
+           1.377085087225391,
+           1.4795054301106476,
+           1.5885161118076052,
+           1.7017794791547294,
+           1.816861103233481,
+           1.9312834755482935,
+           2.042580413082396,
+           2.14835090194952,
+           2.2463111266286733,
+           2.334343479219401,
+           2.4105414195835113,
+           2.47324916073234,
+           2.5210952818012013,
+           2.5530195202523442,
+           2.568292161873748,
+           2.5665256275753348,
+           2.547678045483606,
+           2.5120487907419795,
+           2.460266168978657,
+           2.3932676078658983,
+           2.3122728999573128,
+           2.2187512046949016,
+           2.1143826641217087,
+           2.001015611869843,
+           1.8806204554086965,
+           1.7552413849405828,
+           1.626947106999649,
+           1.4977818157382858,
+           1.369717599805131,
+           1.2446094381059682,
+           1.1241538647998548,
+           1.009852284524461,
+           0.9029797956247413,
+           0.8045602352229083,
+           0.715347998968205,
+           0.6358170143115299,
+           0.5661570635465748,
+           0.5062774662346643,
+           0.4558179446642387,
+           0.41416631534117415,
+           0.38048247867357066,
+           0.35372802226094435,
+           0.3327006144189391,
+           0.31607224720585,
+           0.3024302951630285,
+           0.29032028952015604,
+           0.27828926936039305,
+           0.26492856209145715,
+           0.24891486569665056,
+           0.2290485540791296,
+           0.20428820307686563,
+           0.17378043644031432,
+           0.13688431561727865,
+           0.09318964139492253,
+           0.042528695630393895,
+           -0.015018876617837584,
+           -0.07912816464032552,
+           -0.1492380068228668,
+           -0.22456667920727363,
+           -0.3041338398551634,
+           -0.38678814707281567,
+           -0.4712398204899207,
+           -0.5560972835765767,
+           -0.6399069177540291,
+           -0.7211948745759014,
+           -0.7985098356766032,
+           -0.870465581774823,
+           -0.9357822327416458,
+           -0.9933250506214186,
+           -1.0421397558214769,
+           -1.0814833920401539,
+           -1.1108498857752178,
+           -1.1299895787118108,
+           -1.1389221626330819,
+           -1.1379426129515922,
+           -1.1276198943628393,
+           -1.1087883960297533,
+           -1.0825322395032253,
+           -1.0501627855971314,
+           -1.0131898420558456,
+           -0.9732872376427141,
+           -0.9322535760908989,
+           -0.8919691114355197,
+           -0.8543497913151441,
+           -0.8212995941857825,
+           -0.7946623379611866,
+           -0.7761741599972509,
+           -0.7674178609166711,
+           -0.769780267604763,
+           -0.7844137046205027,
+           -0.8122025698010505,
+           -0.8537358912195273,
+           -0.9092866017400336,
+           -0.9787981076155765,
+           -1.0618785527840962,
+           -1.1578029950050401,
+           -1.2655235182885742,
+           -1.3836871129083648,
+           -1.510660964409764,
+           -1.6445646111099563,
+           -1.7833082601287162,
+           -1.9246363991839215,
+           -2.066175709027221,
+           -2.2054861727780417,
+           -2.340114196255759,
+           -2.46764649978055,
+           -2.5857635181856784,
+           -2.6922910525971524,
+           -2.785248954781169,
+           -2.8628956916786383,
+           -2.9237677325561386,
+           -2.9667128217319365,
+           -2.990916343180437,
+           -2.9959201460125806,
+           -2.9816333779312325,
+           -2.9483350629475495,
+           -2.896668355321382,
+           -2.8276265991000042,
+           -2.7425315169754767,
+           -2.643004038736914,
+           -2.5309284538252763,
+           -2.4084107301733906,
+           -2.2777319788065404,
+           -2.1412981572637357,
+           -2.001587192033035,
+           -1.86109475878123,
+           -1.7222799878051633,
+           -1.5875123601787309,
+           -1.4590210276069433,
+           -1.3388477268640635,
+           -1.2288043694510093,
+           -1.1304362710093425,
+           -1.044991845957988,
+           -0.9733994342164176,
+           -0.916251752661228,
+           -0.8737982784255781,
+           -0.8459456788575271,
+           -0.8322662086273268,
+           -0.8320138028792217,
+           -0.8441474111488197,
+           -0.8673609445088665,
+           -0.9001190522582222,
+           -0.9406978082187423,
+           -0.9872292736418713,
+           -1.0377488165603284,
+           -1.0902440082142335,
+           -1.1427038873031823,
+           -1.1931673829053773,
+           -1.239769716857721,
+           -1.280785665362795,
+           -1.3146686460182635,
+           -1.340084708112178,
+           -1.3559406380330215,
+           -1.3614055445967104,
+           -1.355925457120573,
+           -1.3392306479367146,
+           -1.311335576233603,
+           -1.2725315369965577,
+           -1.2233722827042448,
+           -1.1646530617329172,
+           -1.0973836817255864,
+           -1.022756354410566,
+           -0.9421092068239011,
+           -0.8568864494252415,
+           -0.7685962715992207,
+           -0.6787675875511691,
+           -0.5889067793759348,
+           -0.5004555785645722,
+           -0.4147511926138616,
+           -0.3329897206474856,
+           -0.25619381268035335,
+           -0.18518541366019928,
+           -0.1205642986109079,
+           -0.06269295252168727,
+           -0.011688181964549692,
+           0.03258033098155308,
+           0.07048450358600551,
+           0.10262550949858032,
+           0.12981494968531315,
+           0.1530500388156579,
+           0.1734834656458678,
+           0.19238872612725103,
+           0.2111218477692957,
+           0.23108052015052633,
+           0.253661716926864,
+           0.2802189374220008,
+           0.31202020977740497,
+           0.3502079822969382,
+           0.3957619853841341,
+           0.449466074408162,
+           0.5118799657177958,
+           0.5833166562793537,
+           0.6638261750702587,
+           0.7531861549621716,
+           0.8508995413585667,
+           0.9561995726276228,
+           1.0680619819367816,
+           1.1852241851080612,
+           1.3062110392290396,
+           1.4293665865109833,
+           1.5528910415879082,
+           1.674882142064041,
+           1.7933798651689836,
+           1.9064134208684527,
+           2.0120493660992222,
+           2.108439647682042,
+           2.1938683739394547,
+           2.26679613739631,
+           2.3259007627157864,
+           2.3701134340374783,
+           2.3986492622459545,
+           2.411031482859655,
+           2.4071086260465435,
+           2.387064168080354,
+           2.3514183542571243,
+           2.301022072474936,
+           2.2370428497002073,
+           2.1609432356573337,
+           2.074452024552398,
+           1.9795289418749757,
+           1.8783235849553033,
+           1.7731295489820131,
+           1.6663347910517796,
+           1.5603693805114662,
+           1.45765185196448,
+           1.3605354161184007,
+           1.271255292142807,
+           1.1918784031171883,
+           1.1242566239651843,
+           1.0699846902154524,
+           1.0303637679359834,
+           1.0063715528524146,
+           0.9986396131772893,
+           1.0074385197614217,
+           1.0326711229751993
+          ],
+          [
+           1.0600578650444963,
+           1.1125203195531947,
+           1.1794252730780268,
+           1.2594125732732473,
+           1.350828478218138,
+           1.451762183357966,
+           1.560088091669138,
+           1.6735128355029087,
+           1.7896259472424687,
+           1.9059529912571842,
+           2.0200099136909273,
+           2.129357340710968,
+           2.2316535605649,
+           2.324704959990393,
+           2.406512750294092,
+           2.4753149111362105,
+           2.529622398417243,
+           2.5682488037280695,
+           2.5903328131068144,
+           2.5953529883907662,
+           2.58313458093652,
+           2.5538482803215734,
+           2.508000995102726,
+           2.446418954026313,
+           2.3702235995839622,
+           2.2808009170083308,
+           2.179764996540884,
+           2.068916761327272,
+           1.9501989043606625,
+           1.8256481628408172,
+           1.697346115138783,
+           1.5673697129454982,
+           1.4377427585599358,
+           1.3103895048050653,
+           1.1870914936536803,
+           1.0694486609213414,
+           0.9588456206353418,
+           0.8564239068271183,
+           0.7630607959743888,
+           0.6793551640479996,
+           0.6056206523646911,
+           0.5418862307301245,
+           0.48790405933449815,
+           0.44316436721653907,
+           0.4069168894271509,
+           0.3781982416796558,
+           0.35586446433070196,
+           0.33862784063748086,
+           0.3250969905176998,
+           0.3138191630473149,
+           0.3033236005669659,
+           0.2921648257350251,
+           0.27896471064177814,
+           0.262452223927512,
+           0.24149981674001292,
+           0.21515549963285277,
+           0.18266977779249677,
+           0.14351674833552783,
+           0.09740881735552555,
+           0.044304662000922784,
+           -0.015589760132506287,
+           -0.08182717010533548,
+           -0.15373172885556557,
+           -0.2304182563095206,
+           -0.31081739516189427,
+           -0.3937060502583505,
+           -0.4777422957760117,
+           -0.5615038242972707,
+           -0.6435289174221762,
+           -0.7223588491811987,
+           -0.7965805929551324,
+           -0.864868690944236,
+           -0.9260251627896195,
+           -0.9790163763360231,
+           -1.023005877610123,
+           -1.0573822770476946,
+           -1.0817814123584155,
+           -1.096102152099315,
+           -1.1005153644517776,
+           -1.0954657488515,
+           -1.0816664096682556,
+           -1.0600862365171553,
+           -1.0319303403450226,
+           -0.9986139735260745,
+           -0.9617305312999586,
+           -0.9230143867127071,
+           -0.8842994478461136,
+           -0.8474744410588905,
+           -0.8144360142631738,
+           -0.7870408175810806,
+           -0.7670577533939273,
+           -0.7561215928481866,
+           -0.7556891310893712,
+           -0.7669989993724097,
+           -0.7910361699899624,
+           -0.8285020816145654,
+           -0.8797911807663451,
+           -0.9449745228849646,
+           -1.0237909076040155,
+           -1.1156458414206885,
+           -1.2196184314645144,
+           -1.3344761211474458,
+           -1.4586969868694417,
+           -1.5904991293816422,
+           -1.7278765184576272,
+           -1.8686404895214996,
+           -2.010465949800882,
+           -2.150941232923392,
+           -2.287620447622124,
+           -2.418077100703817,
+           -2.5399577383283307,
+           -2.6510343438960686,
+           -2.749254255641727,
+           -2.832786421839756,
+           -2.9000628950525518,
+           -2.9498145771051716,
+           -2.9811003607998083,
+           -2.9933289695474605,
+           -2.986272968337305,
+           -2.960074604609459,
+           -2.9152433311490915,
+           -2.852645060375938,
+           -2.7734833955678004,
+           -2.679273274859761,
+           -2.5718076436756423,
+           -2.453117936204642,
+           -2.325429292627985,
+           -2.1911115624847053,
+           -2.0526272428485606,
+           -1.91247757049951,
+           -1.7731480283235677,
+           -1.6370545367982479,
+           -1.5064915813960573,
+           -1.3835834765962498,
+           -1.2702398882030086,
+           -1.1681166297997665,
+           -1.0785826190545722,
+           -1.0026937284515582,
+           -0.9411740965910746,
+           -0.8944052846277014,
+           -0.8624234721686876,
+           -0.8449246927086173,
+           -0.8412779151931705,
+           -0.8505455903215524,
+           -0.8715111023056026,
+           -0.9027124033381112,
+           -0.9424809629538862,
+           -0.9889850413029632,
+           -1.0402761970570624,
+           -1.0943378695780686,
+           -1.149134832754403,
+           -1.2026623055031809,
+           -1.252993521549061,
+           -1.298324608186808,
+           -1.3370156990465978,
+           -1.3676273074451384,
+           -1.3889511121109135,
+           -1.4000344527259885,
+           -1.400197995137168,
+           -1.389046201154117,
+           -1.3664704211641991,
+           -1.33264461475012,
+           -1.2880138904131357,
+           -1.2332762357335059,
+           -1.1693579793446967,
+           -1.0973836817255866,
+           -1.0186412891615804,
+           -0.9345435008916299,
+           -0.8465863905930943,
+           -0.756306387729296,
+           -0.6652367603391847,
+           -0.5748647477407576,
+           -0.48659046923961546,
+           -0.40168868390545504,
+           -0.3212743981464251,
+           -0.24627321420185064,
+           -0.1773971864499375,
+           -0.11512680681662658,
+           -0.059699579287875636,
+           -0.011105470675585715,
+           0.030910655238893414,
+           0.06683969568778718,
+           0.09739231512364689,
+           0.1234767297209215,
+           0.14617086318121694,
+           0.16668961461351686,
+           0.18634810809052635,
+           0.20652190009827948,
+           0.22860520277552898,
+           0.2539682354861224,
+           0.28391484346531803,
+           0.31964151932898444,
+           0.36219893116546875,
+           0.41245700050924866,
+           0.47107448620351144,
+           0.5384739181534303,
+           0.6148225910354538,
+           0.7000201754982571,
+           0.7936933370778607,
+           0.8951975751404423,
+           1.0036263101217964,
+           1.1178270617750121,
+           1.2364243787363336,
+           1.3578490050722267,
+           1.4803726069924779,
+           1.6021472367227196,
+           1.7212485843447063,
+           1.8357219654619246,
+           1.943629915485853,
+           2.043100212178514,
+           2.132373128153063,
+           2.2098467249235543,
+           2.2741190396637703,
+           2.3240260842008964,
+           2.3586746713323032,
+           2.377469204032709,
+           2.380131705610954,
+           2.3667145299244603,
+           2.3376053664406893,
+           2.2935243409538644,
+           2.235513204561268,
+           2.1649167963636007,
+           2.083357154529047,
+           1.9927008311831338,
+           1.8950201345851887,
+           1.7925491730638412,
+           1.6876357054566327,
+           1.5826899090843816,
+           1.48013125592599,
+           1.3823347386327083,
+           1.2915777090223086,
+           1.2099885821478147,
+           1.1394986191166712,
+           1.0817979324649718,
+           1.0382967607116098,
+           1.0100929360571285,
+           0.9979463240064826,
+           1.0022608494943792,
+           1.023074544853993,
+           1.060057865044497
+          ],
+          [
+           1.0953969429041845,
+           1.1586691290904556,
+           1.2355415549898157,
+           1.324463304365809,
+           1.4236115400330105,
+           1.530931646639315,
+           1.6441825392911598,
+           1.7609860769135177,
+           1.8788794233582093,
+           1.9953691313499675,
+           2.1079856860177038,
+           2.214337236901627,
+           2.3121612701107037,
+           2.3993730251346297,
+           2.4741095423593467,
+           2.5347683355625366,
+           2.580039815890837,
+           2.6089327467741983,
+           2.620792179141203,
+           2.6153094989778842,
+           2.592524410230313,
+           2.5528188706003903,
+           2.4969031911570765,
+           2.4257946981513445,
+           2.340789532406065,
+           2.243428323842284,
+           2.1354566221643876,
+           2.018781085991296,
+           1.8954225288769757,
+           1.7674669894245574,
+           1.6370160324594603,
+           1.5061374981034037,
+           1.3768178954396326,
+           1.2509175878798742,
+           1.130129839663339,
+           1.0159446891581434,
+           0.9096184874595582,
+           0.8121497934258123,
+           0.7242621524933907,
+           0.64639411050275,
+           0.5786966297720709,
+           0.521037887397567,
+           0.47301524992163174,
+           0.43397403873697343,
+           0.40303253136701545,
+           0.3791124892886841,
+           0.3609743670748603,
+           0.34725624368937913,
+           0.336515427571375,
+           0.32727162487697864,
+           0.3180505264054142,
+           0.3074266641086608,
+           0.29406441272020156,
+           0.276756065255364,
+           0.2544559915328994,
+           0.2263099943629113,
+           0.19167910592959694,
+           0.15015721389771464,
+           0.10158206914032052,
+           0.04603940058939471,
+           -0.01613995686252288,
+           -0.08438983281499447,
+           -0.15792512130237,
+           -0.23576436806484824,
+           -0.316757941060046,
+           -0.3996210336842932,
+           -0.4829706229357441,
+           -0.5653653999592432,
+           -0.6453476107404702,
+           -0.7214856922073042,
+           -0.7924165650094109,
+           -0.8568864494252408,
+           -0.9137891050972011,
+           -0.9622004577970427,
+           -1.0014086656386725,
+           -1.0309387908750047,
+           -1.050571378809989,
+           -1.0603543990488724,
+           -1.0606081724561656,
+           -1.0519230855799198,
+           -1.0351500784566001,
+           -1.0113840770045575,
+           -0.9819407229802565,
+           -0.9483269281240398,
+           -0.912205940269658,
+           -0.8753577537464994,
+           -0.8396358206844642,
+           -0.806921120657201,
+           -0.7790747208667341,
+           -0.7578900058239645,
+           -0.7450457729513817,
+           -0.7420613781905304,
+           -0.7502550737424051,
+           -0.7707066094468497,
+           -0.8042250716751567,
+           -0.8513228113014192,
+           -0.912196168284151,
+           -0.9867135381273094,
+           -1.0744111489560735,
+           -1.174496731457221,
+           -1.2858610720717665,
+           -1.4070972473070877,
+           -1.536527148601709,
+           -1.672234727481007,
+           -1.8121052242342555,
+           -1.9538694941516317,
+           -2.0951524171964624,
+           -2.2335242730516907,
+           -2.3665538863795526,
+           -2.491862298822361,
+           -2.6071757059970255,
+           -2.710376410008356,
+           -2.7995505805867062,
+           -2.873031689861261,
+           -2.929438585306143,
+           -2.9677072901591073,
+           -2.9871157676057445,
+           -2.987301050693062,
+           -2.9682683202709796,
+           -2.9303917038827865,
+           -2.874406764805591,
+           -2.801394847608113,
+           -2.7127596398512996,
+           -2.610196494207477,
+           -2.4956552268261754,
+           -2.371297262060439,
+           -2.2394481269403483,
+           -2.1025464078098315,
+           -1.9630903636924453,
+           -1.8235834442447423,
+           -1.6864799833224615,
+           -1.5541323316946813,
+           -1.4287406545142247,
+           -1.3123065517550392,
+           -1.2065915646458174,
+           -1.113081510529765,
+           -1.0329574455495152,
+           -0.9670738926263616,
+           -0.9159447953654444,
+           -0.8797374711248193,
+           -0.8582746431400365,
+           -0.8510444370392264,
+           -0.8572180360807503,
+           -0.8756745066638143,
+           -0.9050321355588741,
+           -0.9436854670148932,
+           -0.9898470951379498,
+           -1.0415931578995083,
+           -1.0969113964306294,
+           -1.1537505888416628,
+           -1.2100701429243819,
+           -1.263888637260419,
+           -1.3133301352472606,
+           -1.3566671603940266,
+           -1.3923593122541238,
+           -1.4190866182010253,
+           -1.4357768539566738,
+           -1.4416262218526383,
+           -1.4361129462973738,
+           -1.4190035265436778,
+           -1.390351573061417,
+           -1.3504893409551222,
+           -1.3000122572445805,
+           -1.2397569138732005,
+           -1.1707731606652303,
+           -1.0942910780863337,
+           -1.0116837349660284,
+           -0.9244267382240314,
+           -0.8340556576063446,
+           -0.7421224566356174,
+           -0.6501520802676517,
+           -0.559600339702123,
+           -0.47181419573840455,
+           -0.38799547504176646,
+           -0.3091689604383356,
+           -0.2361556792922656,
+           -0.1695520761360762,
+           -0.10971560054582681,
+           -0.0567570727298778,
+           -0.01054001171993931,
+           0.029313071072240716,
+           0.06340759221575512,
+           0.09255738716916755,
+           0.11775929651329263,
+           0.1401625269611322,
+           0.16103360387516177,
+           0.18171784840827845,
+           0.20359840491330938,
+           0.22805391057082977,
+           0.2564159375591606,
+           0.2899273475295351,
+           0.3297026783772745,
+           0.37669163477544865,
+           0.4316466778442786,
+           0.49509560754615206,
+           0.5673199064496939,
+           0.6483394685099476,
+           0.737904175087173,
+           0.8354926066137262,
+           0.9403179964748022,
+           1.0513413483607752,
+           1.1672914542385247,
+           1.2866913718163961,
+           1.4078907524453224,
+           1.5291032570603194,
+           1.6484481629182481,
+           1.7639951509714884,
+           1.8738111756348783,
+           1.9760082577421387,
+           2.0687910092638147,
+           2.1505026957745317,
+           2.2196686698792067,
+           2.2750360652598745,
+           2.3156087253830373,
+           2.340676451210208,
+           2.349837785831191,
+           2.343015707556543,
+           2.320465772924243,
+           2.28277643314434,
+           2.230861437263588,
+           2.165944428118257,
+           2.089536028211504,
+           2.003403897288216,
+           1.9095364170211329,
+           1.8101008165650307,
+           1.7073966918479984,
+           1.6038059878842426,
+           1.501740604198332,
+           1.4035888463580355,
+           1.311661980017379,
+           1.2281421468909834,
+           1.1550328745784222,
+           1.0941133547462751,
+           1.0468975782039192,
+           1.014599302927367,
+           0.9981036947967393,
+           0.9979463240064822,
+           1.014300026578958,
+           1.0469699543687245,
+           1.0953969429041854
+          ],
+          [
+           1.1383893719644553,
+           1.211930131509987,
+           1.2981021173398788,
+           1.3951767828998438,
+           1.5011776379574104,
+           1.6139236675854867,
+           1.7310772958966585,
+           1.8501957728350045,
+           1.9687847827063516,
+           2.08435302250538,
+           2.194466477685247,
+           2.296801133278758,
+           2.389192898934018,
+           2.4696835964425774,
+           2.536561955966396,
+           2.588398689988861,
+           2.624074858987152,
+           2.642802906371722,
+           2.644139918335839,
+           2.6279928525251117,
+           2.5946156732519405,
+           2.544598525592111,
+           2.4788492713482237,
+           2.3985678918910365,
+           2.3052144318595986,
+           2.2004713095086497,
+           2.086200950462405,
+           1.9643998086137755,
+           1.8371499183419682,
+           1.7065691742143003,
+           1.5747615567017565,
+           1.4437685147188242,
+           1.3155226782881908,
+           1.1918050083580958,
+           1.0742063975031453,
+           0.9640946173222008,
+           0.8625873688193092,
+           0.7705320344544632,
+           0.68849255886035,
+           0.6167437037604968,
+           0.5552727359480628,
+           0.5037884199674791,
+           0.4617370040609613,
+           0.42832471356314983,
+           0.40254610458764883,
+           0.383217486552181,
+           0.36901449840394623,
+           0.3585128233804178,
+           0.35023095322249986,
+           0.3426738667376323,
+           0.3343764705788977,
+           0.32394566242259826,
+           0.3100999180144509,
+           0.2917053727100111,
+           0.2678074633563053,
+           0.23765731519415845,
+           0.20073219785880736,
+           0.1567495309603379,
+           0.10567408915079006,
+           0.04771823472237301,
+           -0.016664811894584564,
+           -0.08679447148316069,
+           -0.1617827061656484,
+           -0.24055978394866329,
+           -0.32190521784319254,
+           -0.4044830539142996,
+           -0.48688056795550133,
+           -0.5676493398850104,
+           -0.6453476107404703,
+           -0.7185827909573249,
+           -0.7860529814001039,
+           -0.8465863905930936,
+           -0.8991775822493479,
+           -0.9430195652846071,
+           -0.9775308420932546,
+           -1.00237665738092,
+           -1.0174838361364598,
+           -1.0230487617273332,
+           -1.019538219548739,
+           -1.0076830137714086,
+           -0.9884644499388046,
+           -0.9630939597994146,
+           -0.9329863221923926,
+           -0.8997271005502753,
+           -0.8650350694151933,
+           -0.830720535423857,
+           -0.7986405691022594,
+           -0.770652249671636,
+           -0.7485650836691269,
+           -0.7340937879727922,
+           -0.7288126279486284,
+           -0.7341124718026061,
+           -0.7511616634598679,
+           -0.7808717297691405,
+           -0.8238688255997827,
+           -0.8804716851619628,
+           -0.9506766929151198,
+           -1.0341505165109977,
+           -1.1302305615239914,
+           -1.2379333177336511,
+           -1.355970474112122,
+           -1.4827724891787548,
+           -1.6165191197183613,
+           -1.755176238562155,
+           -1.896538115475047,
+           -2.0382741980733776,
+           -2.177979315535431,
+           -2.313226139523378,
+           -2.441618676440651,
+           -2.560845534447125,
+           -2.668731708363677,
+           -2.7632876557906383,
+           -2.8427544977637074,
+           -2.905644265667029,
+           -2.9507742308072142,
+           -2.9772944912689634,
+           -2.984708149086164,
+           -2.9728835855384146,
+           -2.9420585292834422,
+           -2.8928358065230277,
+           -2.826170859747072,
+           -2.743351317008912,
+           -2.6459690824016757,
+           -2.5358855958405426,
+           -2.41519107209442,
+           -2.2861586713202047,
+           -2.151194672679118,
+           -2.0127858160666587,
+           -1.8734450423089504,
+           -1.7356568978018985,
+           -1.6018238746563591,
+           -1.4742149318723654,
+           -1.3549173875573495,
+           -1.245793288120645,
+           -1.1484412498109784,
+           -1.0641646336537047,
+           -0.9939467601076512,
+           -0.9384336984116388,
+           -0.8979249818442855,
+           -0.8723724084920771,
+           -0.8613868923105735,
+           -0.8642531360431022,
+           -0.8799517106543708,
+           -0.9071879499027877,
+           -0.9444269077988712,
+           -0.9899334848799841,
+           -1.0418167098987168,
+           -1.0980770695365265,
+           -1.1566557123481525,
+           -1.2154843158615791,
+           -1.272534398426589,
+           -1.3258648801029995,
+           -1.3736667489454601,
+           -1.4143037690873974,
+           -1.4463482729743675,
+           -1.468611209231326,
+           -1.4801657666845538,
+           -1.4803640602256696,
+           -1.4688465413388123,
+           -1.445543980760615,
+           -1.4106720582769736,
+           -1.3647187803900833,
+           -1.3084251258781752,
+           -1.2427594876537271,
+           -1.1688866326201697,
+           -1.0881320356340352,
+           -1.0019425558807333,
+           -0.9118445112111613,
+           -0.8194002661362818,
+           -0.726164480793539,
+           -0.6336411705558712,
+           -0.5432426990592616,
+           -0.4562517720210995,
+           -0.37378741676603044,
+           -0.2967758250040007,
+           -0.2259268068751702,
+           -0.16171645590182354,
+           -0.10437646105215832,
+           -0.05389032778467385,
+           -0.009996589136248344,
+           0.02780109476655994,
+           0.06021723031832727,
+           0.088161631313467,
+           0.1127110221345312,
+           0.13507586339862873,
+           0.15656328584102316,
+           0.17853712117263548,
+           0.20237609630654682,
+           0.229431307717943,
+           0.2609841144788426,
+           0.29820558110957945,
+           0.3421185649640005,
+           0.39356347829631444,
+           0.4531686640355417,
+           0.5213262088798438,
+           0.5981738804926415,
+           0.6835837207528409,
+           0.7771576580577787,
+           0.8782303228351093,
+           0.9858790661799343,
+           1.0989409965297565,
+           1.216036668184185,
+           1.335599882840718,
+           1.4559129055214013,
+           1.5751462533640637,
+           1.6914020933874714,
+           1.8027601866476823,
+           1.9073252437342167,
+           2.003274512210452,
+           2.088904401586564,
+           2.162674966200648,
+           2.2232511107076074,
+           2.2695394557331214,
+           2.300719900926706,
+           2.316271046757713,
+           2.315988781942747,
+           2.2999975068351453,
+           2.2687536404579145,
+           2.22304124577737,
+           2.1639597997068063,
+           2.092904326474842,
+           2.01153830065267,
+           1.9217599046703622,
+           1.8256623906425398,
+           1.7254894436713821,
+           1.6235865698307985,
+           1.5223496336088922,
+           1.424171744142946,
+           1.3313897352283823,
+           1.2462314996361656,
+           1.170765423284981,
+           1.1068531195884082,
+           1.0561065898796402,
+           1.019850833971669,
+           0.9990928080788001,
+           0.9944974785610722,
+           1.0063715528524138,
+           1.0346552875450998,
+           1.0789225823283255,
+           1.1383893719644567
+          ],
+          [
+           1.1886714168211636,
+           1.2718527146304417,
+           1.366577669461758,
+           1.4709547408487404,
+           1.5828705277038384,
+           1.7000360961449599,
+           1.8200371925244263,
+           1.9403871688720264,
+           2.0585813852641732,
+           2.172151820738579,
+           2.2787206220630454,
+           2.3760513479636725,
+           2.4620967245977887,
+           2.5350418146650746,
+           2.5933416154360853,
+           2.6357522373487248,
+           2.6613549713155087,
+           2.6695727256440245,
+           2.6601784982521637,
+           2.6332957421221566,
+           2.589390676969932,
+           2.529256793135253,
+           2.453991980007243,
+           2.364968886346621,
+           2.263799279393102,
+           2.1522933097869608,
+           2.032414706705982,
+           1.9062330194091326,
+           1.7758740854094222,
+           1.6434699402833002,
+           1.511109388901053,
+           1.3807904326134783,
+           1.254375692379112,
+           1.1335518854112303,
+           1.0197943047994207,
+           0.9143371204836704,
+           0.8181501692601147,
+           0.7319227349862194,
+           0.6560546420233275,
+           0.5906547996792408,
+           0.5355471476338503,
+           0.4902837667397923,
+           0.4541647408159325,
+           0.4262641875423878,
+           0.405461724479715,
+           0.3904785033357652,
+           0.3799168351687151,
+           0.37230234395275047,
+           0.3661275279177199,
+           0.35989557869354083,
+           0.35216330821213493,
+           0.34158206247616996,
+           0.32693555889358783,
+           0.30717366838574817,
+           0.28144127271699465,
+           0.24910145865764063,
+           0.20975246032583617,
+           0.16323792553799044,
+           0.1096502570459855,
+           0.04932696070341159,
+           -0.017159884717620488,
+           -0.08902074177859004,
+           -0.16527184653188037,
+           -0.24476393257263823,
+           -0.3262156772205791,
+           -0.40825097605713484,
+           -0.48943905093114615,
+           -0.5683363209093062,
+           -0.6435289174221763,
+           -0.7136747052894136,
+           -0.7775436809241006,
+           -0.8340556576063438,
+           -0.882314214341142,
+           -0.9216359778288241,
+           -0.9515744241659012,
+           -0.9719375251393129,
+           -0.9827987199211293,
+           -0.9845008627074299,
+           -0.9776529761154602,
+           -0.9631198244523274,
+           -0.9420045056576163,
+           -0.9156244411448098,
+           -0.8854813143642156,
+           -0.8532256673377266,
+           -0.8206170056490554,
+           -0.7894803828103614,
+           -0.7616605314784483,
+           -0.7389746791625847,
+           -0.7231652280068119,
+           -0.7158534907984963,
+           -0.7184956581379724,
+           -0.7323421250293763,
+           -0.7584012300825137,
+           -0.7974083588215858,
+           -0.8498012367167381,
+           -0.9157020905333207,
+           -0.9949071920082377,
+           -1.0868841197334258,
+           -1.190776887818872,
+           -1.3054188980247008,
+           -1.4293534803194532,
+           -1.5608615999727753,
+           -1.6979961319469725,
+           -1.8386219399098809,
+           -1.980460851713785,
+           -2.121140499297994,
+           -2.258245891778243,
+           -2.3893725184825985,
+           -2.5121797357142985,
+           -2.624443178189453,
+           -2.724104953793856,
+           -2.809320428160986,
+           -2.878500482483419,
+           -2.930348232108386,
+           -2.963889322340339,
+           -2.9784950683750924,
+           -2.973897874783204,
+           -2.9501985523627026,
+           -2.9078653420665126,
+           -2.8477246524160837,
+           -2.7709437135573247,
+           -2.6790055431121975,
+           -2.573676801558025,
+           -2.4569692835852077,
+           -2.331095942639853,
+           -2.1984224749872534,
+           -2.0614155940024883,
+           -1.9225892024784648,
+           -1.784449718681951,
+           -1.6494418295411002,
+           -1.5198959313119011,
+           -1.3979784746968327,
+           -1.2856463587692954,
+           -1.1846064180010092,
+           -1.096280921675312,
+           -1.0217798580850963,
+           -0.9618806107803548,
+           -0.9170154548102823,
+           -0.8872671118040447,
+           -0.8723724084920768,
+           -0.8717338886440068,
+           -0.8844390381496668,
+           -0.9092866017400336,
+           -0.9448193020486753,
+           -0.9893621214261057,
+           -1.0410651777747786,
+           -1.097950120778792,
+           -1.157958896762307,
+           -1.2190036808623577,
+           -1.2790167553723988,
+           -1.3359991233940782,
+           -1.3880666869719047,
+           -1.4334928875891442,
+           -1.470746802476512,
+           -1.4985258101693524,
+           -1.5157820800857909,
+           -1.5217423000066637,
+           -1.5159202282033746,
+           -1.498121839235312,
+           -1.4684430195525613,
+           -1.4272599563108204,
+           -1.3752125455584894,
+           -1.3131813196384132,
+           -1.2422585539422217,
+           -1.1637143560904395,
+           -1.0789586626548358,
+           -0.9895001666886906,
+           -0.8969032711870707,
+           -0.8027442074263831,
+           -0.7085674718997514,
+           -0.6158437209712764,
+           -0.5259302188539289,
+           -0.4400348632344259,
+           -0.35918471568047944,
+           -0.28419984337715254,
+           -0.21567313783983055,
+           -0.15395661864001994,
+           -0.09915455987172572,
+           -0.051123598411717056,
+           -0.009479800525472365,
+           0.02638751832557423,
+           0.05729560190081107,
+           0.08424223764018676,
+           0.10837461727025167,
+           0.13095390796918685,
+           0.15331648142451176,
+           0.17683283677530653,
+           0.20286531556190612,
+           0.23272574081372477,
+           0.2676341174013044,
+           0.30867950660342064,
+           0.3567841350703858,
+           0.4126717182972833,
+           0.4768408733410499,
+           0.5495443674478211,
+           0.6307748017002877,
+           0.7202571654419528,
+           0.8174485221817391,
+           0.9215449053237399,
+           1.0314953169895136,
+           1.146022540066144,
+           1.2636502970445518,
+           1.3827361236746798,
+           1.50150917515517,
+           1.6181120513202876,
+           1.7306456184417445,
+           1.8372157216300893,
+           1.9359806255785312,
+           2.025197994039871,
+           2.103270220746298,
+           2.1687869565155924,
+           2.2205637383382735,
+           2.257675714887351,
+           2.2794855770240736,
+           2.285664938740058,
+           2.2762085702571175,
+           2.2514410568908163,
+           2.2120156405661477,
+           2.1589051910553834,
+           2.093385446410581,
+           2.017010851941949,
+           1.93158350975662,
+           1.8391159217973594,
+           1.74178836426394,
+           1.641901866406006,
+           1.5418278785690196,
+           1.4439558002471653,
+           1.3506395965746005,
+           1.264144759687658,
+           1.1865968689607238,
+           1.1199329712492678,
+           1.0658569397065758,
+           1.0257998789457956,
+           1.000886527463216,
+           0.9919084681290972,
+           0.9993047975713127,
+           1.0231507292957807,
+           1.063154417674174,
+           1.1186620950415285,
+           1.1886714168211643
+          ],
+          [
+           1.2458176686219353,
+           1.3379299062833419,
+           1.4403888771989604,
+           1.5511560623983327,
+           1.667999050458584,
+           1.788540382205801,
+           1.9103095881941787,
+           2.0307972050020364,
+           2.147509511140606,
+           2.258022708487099,
+           2.3600352909642264,
+           2.4514173882790034,
+           2.5302559477475413,
+           2.5948947197010277,
+           2.643968139156213,
+           2.6764283452037385,
+           2.6915647462561663,
+           2.6890157198065796,
+           2.6687722252465433,
+           2.631173302923442,
+           2.576893627217172,
+           2.506923471228616,
+           2.4225416210669315,
+           2.325281944308728,
+           2.2168944659370147,
+           2.0993019323556568,
+           1.9745529468558496,
+           1.8447728357348114,
+           1.7121134513535785,
+           1.5787031357033419,
+           1.4465980551998796,
+           1.3177360748598874,
+           1.1938942688825163,
+           1.0766510668192493,
+           0.9673539124781914,
+           0.8670931695813309,
+           0.7766828475983083,
+           0.6966485471654894,
+           0.6272228414370893,
+           0.5683481221928744,
+           0.5196867522325029,
+           0.48063818319173846,
+           0.45036252496008694,
+           0.4278098936572218,
+           0.411754723579594,
+           0.40083410815179993,
+           0.3935891386667731,
+           0.38850813982250565,
+           0.3840706594418309,
+           0.3787910572686434,
+           0.3712605546101123,
+           0.36018665234435987,
+           0.34442889821756056,
+           0.3230300835016748,
+           0.29524207141840697,
+           0.2605456021211228,
+           0.21866357782849669,
+           0.16956750287651304,
+           0.11347693264627678,
+           0.05085196798275403,
+           -0.017620986791524757,
+           -0.0910498084471844,
+           -0.1683630226947136,
+           -0.2483412449370153,
+           -0.3296528507553677,
+           -0.41089292178646597,
+           -0.4906244259389776,
+           -0.5674205308618022,
+           -0.6399069177540293,
+           -0.7068029598292547,
+           -0.7669606561139303,
+           -0.8194002661362813,
+           -0.8633416730958478,
+           -0.8982306102557545,
+           -0.9237590148976917,
+           -0.9398789229828122,
+           -0.9468094819423744,
+           -0.945036834657996,
+           -0.9353068102690638,
+           -0.9186105423693887,
+           -0.8961633177650203,
+           -0.8693771346487629,
+           -0.8398276133582129,
+           -0.8092160516535145,
+           -0.7793275458901092,
+           -0.7519862062585045,
+           -0.7290085756649854,
+           -0.712156415710818,
+           -0.7030900481522583,
+           -0.7033234354689996,
+           -0.7141821497524943,
+           -0.736765315805634,
+           -0.7719125236007731,
+           -0.8201765892394922,
+           -0.8818029050934234,
+           -0.9567159622441105,
+           -1.044513455526648,
+           -1.1444681976491047,
+           -1.2555378785227362,
+           -1.3763825137835282,
+           -1.505389237255057,
+           -1.640703910476106,
+           -1.7802688528953199,
+           -1.9218658431311662,
+           -2.0631634086264192,
+           -2.2017673114196925,
+           -2.335273054368838,
+           -2.461319177106727,
+           -2.577640085709796,
+           -2.682117165205023,
+           -2.77282695957454,
+           -2.848085269035079,
+           -2.9064861075398696,
+           -2.946934582450565,
+           -2.968672900296498,
+           -2.9712988640519105,
+           -2.954776404509171,
+           -2.9194378768116884,
+           -2.86597804845664,
+           -2.795439902338729,
+           -2.709192572883683,
+           -2.6089019202819363,
+           -2.496494422728914,
+           -2.37411522515319,
+           -2.2440813213111404,
+           -2.108830960983644,
+           -1.97087046254156,
+           -1.832719671210639,
+           -1.6968573335201746,
+           -1.5656676579525974,
+           -1.4413893007625993,
+           -1.3260679550931787,
+           -1.221513632399108,
+           -1.129263610004718,
+           -1.0505518802176637,
+           -0.9862857782045796,
+           -0.937030291701033,
+           -0.9030003698550255,
+           -0.8840613556480043,
+           -0.8797374711248185,
+           -0.8892280918692866,
+           -0.9114313614928742,
+           -0.9449745228849649,
+           -0.9882501848339418,
+           -1.0394576041998753,
+           -1.0966479484400313,
+           -1.1577724137214718,
+           -1.2207320122216836,
+           -1.2834278099468377,
+           -1.3438103941871036,
+           -1.399927377535509,
+           -1.4499678024343845,
+           -1.49230239497375,
+           -1.5255187269581343,
+           -1.5484504782638036,
+           -1.5602001438519286,
+           -1.5601546976375023,
+           -1.5479939045153122,
+           -1.5236911577194454,
+           -1.4875069066894036,
+           -1.4399749260394819,
+           -1.381881854458533,
+           -1.3142405989738806,
+           -1.238258350864559,
+           -1.1553000908759634,
+           -1.066848570035138,
+           -0.9744618356327106,
+           -0.879729427803352,
+           -0.7842283992702865,
+           -0.6894803086122335,
+           -0.5969103059907909,
+           -0.5078093705026484,
+           -0.423300671764954,
+           -0.3443109172440947,
+           -0.27154741405305083,
+           -0.20548142286612378,
+           -0.14633821608526662,
+           -0.09409407665145272,
+           -0.04848029239346199,
+           -0.008994018153108053,
+           0.025084301245624958,
+           0.05466742526167066,
+           0.08083236599334857,
+           0.10478676986785147,
+           0.12783153428094576,
+           0.15132066006018702,
+           0.17661941423349048,
+           0.20506192366311257,
+           0.23790933746343676,
+           0.2763096842926613,
+           0.3212605098618755,
+           0.3735753113370843,
+           0.4338546904213698,
+           0.5024630281582819,
+           0.5795113448597364,
+           0.6648468515271302,
+           0.7580495286402903,
+           0.8584358885167419,
+           0.9650698931116921,
+           1.0767808147801028,
+           1.1921876478069782,
+           1.3097295079740539,
+           1.4277013003914336,
+           1.544293796272975,
+           1.6576371408360353,
+           1.7658467201012105,
+           1.8670702465014501,
+           1.9595348836707103,
+           2.0415932206536276,
+           2.111766925412318,
+           2.168786956515592,
+           2.211629289157501,
+           2.2395452153385227,
+           2.252085405663997,
+           2.2491170686804933,
+           2.2308337093659207,
+           2.197757167262138,
+           2.150731802402264,
+           2.090910889023224,
+           2.0197354683390683,
+           1.9389060976563146,
+           1.850348109234291,
+           1.756171154161142,
+           1.6586239501019393,
+           1.5600452734963772,
+           1.4628123335869658,
+           1.3692877351029287,
+           1.281766276735401,
+           1.202422842657636,
+           1.1332626239515453,
+           1.0760748563300209,
+           1.0323911811657083,
+           1.0034496304331848,
+           0.9901651052930716,
+           0.9931070658451838,
+           1.0124849797332973,
+           1.0481418939112082,
+           1.09955630142928,
+           1.1658522782484455,
+           1.2458176686219362
+          ],
+          [
+           1.3093446442175627,
+           1.4096026635270336,
+           1.518911264334077,
+           1.6351022080767998,
+           1.7558429803980464,
+           1.8786877394592902,
+           2.001130737589825,
+           2.120660971408367,
+           2.2348167881503014,
+           2.3412391791835696,
+           2.4377225254945794,
+           2.522261623420161,
+           2.593093910513029,
+           2.6487359288900834,
+           2.688013203827341,
+           2.7100828752753,
+           2.7144485954430473,
+           2.700967392330717,
+           2.6698483924999006,
+           2.6216434917250044,
+           2.5572302546895473,
+           2.477787509881473,
+           2.384764278795374,
+           2.2798428352655433,
+           2.1648968274378433,
+           2.0419455082466786,
+           1.913105207583085,
+           1.7805392385557461,
+           1.6464074599905645,
+           1.5128167169484854,
+           1.381773350673059,
+           1.2551389098570678,
+           1.1345901080093401,
+           1.0215839592553537,
+           0.917328889988043,
+           0.8227624698179469,
+           0.7385362361393257,
+           0.6650079065829887,
+           0.6022410871811339,
+           0.5500123958868184,
+           0.5078257358660263,
+           0.4749332753248104,
+           0.4503625249600869,
+           0.43294875453447995,
+           0.4213718602672864,
+           0.41419668789757697,
+           0.4099157350237387,
+           0.40699310262341903,
+           0.40390854078277955,
+           0.3992004381638932,
+           0.3915066384267006,
+           0.37960202877821064,
+           0.3624319344198619,
+           0.3391404656108006,
+           0.3090930984585957,
+           0.27189292295236994,
+           0.22739015828039,
+           0.17568471188745557,
+           0.11712174054449513,
+           0.05228035430874343,
+           -0.018044216984101077,
+           -0.0928645046667643,
+           -0.1710300819050373,
+           -0.25126145536043953,
+           -0.33218765840411546,
+           -0.412386539045929,
+           -0.4904266641700412,
+           -0.5649097177407002,
+           -0.6345122554921953,
+           -0.6980256926529416,
+           -0.7543934441483604,
+           -0.8027442074263824,
+           -0.8424204747975734,
+           -0.873001482566115,
+           -0.8943199452376513,
+           -0.9064720811923448,
+           -0.9098206074388107,
+           -0.9049905611140053,
+           -0.8928579897344688,
+           -0.874531736189694,
+           -0.8513287234539615,
+           -0.8247433134513753,
+           -0.7964114701434305,
+           -0.7680705947609037,
+           -0.7415160176516092,
+           -0.7185552234682235,
+           -0.700960951983232,
+           -0.6904243539605404,
+           -0.6885093892111581,
+           -0.6966096319223045,
+           -0.71590859702502,
+           -0.7473446219358949,
+           -0.7915812323575515,
+           -0.8489837914907825,
+           -0.9196030821344519,
+           -1.0031663043806704,
+           -1.0990757920338943,
+           -1.206415562901775,
+           -1.323965626349546,
+           -1.4502237807094145,
+           -1.583434448008686,
+           -1.7216239186128315,
+           -1.862641218115349,
+           -2.004203667136466,
+           -2.1439460851581345,
+           -2.279472495123875,
+           -2.4084091186565146,
+           -2.5284574141075695,
+           -2.637445902245035,
+           -2.733379547465906,
+           -2.814485515489868,
+           -2.8792542103178307,
+           -2.926474601881441,
+           -2.9552629886642614,
+           -2.965084493441589,
+           -2.9557667614443095,
+           -2.9275055145551474,
+           -2.880861808119897,
+           -2.816751033911981,
+           -2.736423908935738,
+           -2.641439880318957,
+           -2.5336335568895207,
+           -2.4150749437646635,
+           -2.288024403370715,
+           -2.1548833911792875,
+           -2.018142114058468,
+           -1.8803253310806316,
+           -1.7439375591641342,
+           -1.6114089580380966,
+           -1.4850431504362747,
+           -1.3669681846275556,
+           -1.2590917685971315,
+           -1.163061800332269,
+           -1.0802330893303267,
+           -1.0116410138213927,
+           -0.9579826899891986,
+           -0.9196060478139946,
+           -0.8965070175064879,
+           -0.8883348355238653,
+           -0.8944052846277003,
+           -0.9137214931109096,
+           -0.945001738803075,
+           -0.9867135381273097,
+           -1.0371131533375249,
+           -1.094289525667449,
+           -1.1562115414844243,
+           -1.2207774650585652,
+           -1.2858653269527116,
+           -1.3493830423172866,
+           -1.4093170488018654,
+           -1.4637782988929795,
+           -1.5110445150430527,
+           -1.5495977160551984,
+           -1.5781561472665713,
+           -1.5956998919744723,
+           -1.6014896036108746,
+           -1.5950779733113047,
+           -1.5763137313463798,
+           -1.5453381687865877,
+           -1.502574353059457,
+           -1.448709393065464,
+           -1.3846702817190226,
+           -1.3115940019020698,
+           -1.2307927219488883,
+           -1.1437150254679542,
+           -1.0519042146383843,
+           -0.956954793798449,
+           -0.8604682795462838,
+           -0.7640094937834916,
+           -0.6690644769694374,
+           -0.5770011108726176,
+           -0.4890334645822494,
+           -0.4061907764448234,
+           -0.3292918605221187,
+           -0.25892558230906715,
+           -0.1954378884745311,
+           -0.13892570337054327,
+           -0.08923782536927759,
+           -0.0459827732949327,
+           -0.008543351957844638,
+           0.02390246933292095,
+           0.052354935964536664,
+           0.07796086543006923,
+           0.10197783473987435,
+           0.12573515902819812,
+           0.1505927072999106,
+           0.17789865919846587,
+           0.20894733631165355,
+           0.24493824209381818,
+           0.28693741593127375,
+           0.33584214990440847,
+           0.39235003281478575,
+           0.456933177139,
+           0.5298183534633265,
+           0.6109736069264732,
+           0.7001017650138559,
+           0.7966410698539563,
+           0.8997729853965979,
+           1.0084370451069982,
+           1.1213524237484715,
+           1.2370457420508227,
+           1.3538844499971467,
+           1.4701149872489832,
+           1.583904791619901,
+           1.693387121768697,
+           1.7967075811171502,
+           1.8920711784720274,
+           1.977788738328871,
+           2.052321481015646,
+           2.1143226296183473,
+           2.162674966200648,
+           2.1965233526482426,
+           2.215301349316964,
+           2.2187512046949016,
+           2.2069366480978245,
+           2.180248091124653,
+           2.139400027947602,
+           2.085420614968384,
+           2.0196336022438564,
+           1.943632977633742,
+           1.8592508651820006,
+           1.7685193873335394,
+           1.6736273520288483,
+           1.5768727567326686,
+           1.4806122087590428,
+           1.3872084421501283,
+           1.2989771637949814,
+           1.218134484076719,
+           1.1467461794858758,
+           1.0866799964554297,
+           1.0395621380254765,
+           1.00673897942649,
+           0.9892449375578266,
+           0.9877772755442921,
+           1.0026784605480104,
+           1.033926514741835,
+           1.081133610137419,
+           1.1435529624018115,
+           1.2200938816453444,
+           1.3093446442175638
+          ],
+          [
+           1.3787148766482227,
+           1.4862646024029431,
+           1.601480495940159,
+           1.7220829555056376,
+           1.845659118125107,
+           1.9697154804709185,
+           2.09173225269044,
+           2.209218179963403,
+           2.319764557222763,
+           2.4210971838300157,
+           2.5111250564961027,
+           2.58798467910047,
+           2.650078975294754,
+           2.6961099212390778,
+           2.7251041682717343,
+           2.7364310950101554,
+           2.7298129111569716,
+           2.70532662665869,
+           2.6633978951503003,
+           2.6047869350418718,
+           2.5305669204164203,
+           2.442095412510994,
+           2.3409795666026305,
+           2.229035994641004,
+           2.1082462874464913,
+           1.9807092987620656,
+           1.8485913645673555,
+           1.7140756731701063,
+           1.5793120137396124,
+           1.4463681129353418,
+           1.3171837216544013,
+           1.1935285379464837,
+           1.076964949796009,
+           0.9688164553676846,
+           0.8701424716558231,
+           0.7817200789733877,
+           0.7040330724776485,
+           0.6372685073755983,
+           0.581320736200839,
+           0.5358027493026327,
+           0.5000644481000521,
+           0.4732173092410623,
+           0.4541647408159325,
+           0.44163729308577965,
+           0.43423176921461026,
+           0.4304531891018106,
+           0.42875849384656295,
+           0.42760084120565384,
+           0.4254733344876777,
+           0.42095104878156625,
+           0.4127302686313541,
+           0.39966392890753366,
+           0.3807923536677535,
+           0.3553685135904513,
+           0.3228771678811396,
+           0.28304741768242847,
+           0.23585837086207023,
+           0.18153779821451674,
+           0.1205538440165272,
+           0.05360003488670974,
+           -0.0184259945764064,
+           -0.0944494772861527,
+           -0.17325045963507413,
+           -0.2534998575413185,
+           -0.33379865454710034,
+           -0.41271919115763933,
+           -0.48884743877839043,
+           -0.5608251241611606,
+           -0.6273905719205217,
+           -0.6874171634125446,
+           -0.7399483693273478,
+           -0.7842283992702859,
+           -0.8197276222508724,
+           -0.8461620445964707,
+           -0.8635062830364346,
+           -0.871999636766226,
+           -0.8721450390263948,
+           -0.8647008516707854,
+           -0.8506656507417083,
+           -0.8312563325594111,
+           -0.8078800436801966,
+           -0.7821005998770116,
+           -0.7556002049374944,
+           -0.7301374058437369,
+           -0.7075023235723645,
+           -0.6894702756816165,
+           -0.6777549560212296,
+           -0.6739623569880293,
+           -0.679546610155976,
+           -0.695768881974447,
+           -0.7236603934303973,
+           -0.7639905377031069,
+           -0.8172409501765745,
+           -0.8835862436090031,
+           -0.9628819612372814,
+           -1.0546601260295054,
+           -1.1581325794733865,
+           -1.2722021127498968,
+           -1.395481201588778,
+           -1.5263179682706118,
+           -1.6628288147815038,
+           -1.8029370044973936,
+           -1.944416320123379,
+           -2.084938796676405,
+           -2.2221254233108945,
+           -2.353598629394407,
+           -2.477035320442953,
+           -2.5902192096197,
+           -2.691091201049687,
+           -2.777796622021684,
+           -2.8487281713060844,
+           -2.9025635486618837,
+           -2.938296853801108,
+           -2.955262988664262,
+           -2.953154461321378,
+           -2.932030169168708,
+           -2.8923159289903637,
+           -2.8347967172843327,
+           -2.76060078125106,
+           -2.6711759742163417,
+           -2.5682588543006855,
+           -2.4538372573485736,
+           -2.3301072103000435,
+           -2.199425185546602,
+           -2.064256807095734,
+           -1.9271232028938852,
+           -1.7905462524040021,
+           -1.6569940031812276,
+           -1.5288275241581257,
+           -1.4082504268087248,
+           -1.2972622192252128,
+           -1.197616564053518,
+           -1.1107853915178187,
+           -1.0379296763693042,
+           -0.9798775260235787,
+           -0.9371100503725488,
+           -0.9097552961070838,
+           -0.8975903344638136,
+           -0.9000513958581063,
+           -0.9162517526612265,
+           -0.9450068671109815,
+           -0.9848661494974561,
+           -1.0341505165109977,
+           -1.0909948047351392,
+           -1.153393982961484,
+           -1.2192520219579683,
+           -1.2864322235456491,
+           -1.3528077836396055,
+           -1.4163113668627672,
+           -1.4749825032765433,
+           -1.5270116797789344,
+           -1.5707800881717116,
+           -1.604894106490712,
+           -1.6282137270073096,
+           -1.6398742998807623,
+           -1.6393011318493749,
+           -1.626216660312908,
+           -1.6006401101467183,
+           -1.5628797289277268,
+           -1.513517881248333,
+           -1.4533894598453356,
+           -1.3835542359835569,
+           -1.3052639198318075,
+           -1.2199248297940724,
+           -1.1290571747620655,
+           -1.034252032473629,
+           -0.9371271586818505,
+           -0.8392827844458903,
+           -0.7422585520555753,
+           -0.6474927041453303,
+           -0.5562845764164698,
+           -0.469761353753013,
+           -0.38884993473075846,
+           -0.31425461353062006,
+           -0.24644113455319952,
+           -0.18562750751075655,
+           -0.13178179370761675,
+           -0.0846268921085263,
+           -0.04365217125784301,
+           -0.00813161477962283,
+           0.02285202142022873,
+           0.05037769871527616,
+           0.07565203014448292,
+           0.09997157674856065,
+           0.12468251849420287,
+           0.15113878195343683,
+           0.1806597486789641,
+           0.21448868115835307,
+           0.2537529869910804,
+           0.29942739689837544,
+           0.3523010594579923,
+           0.41294945686413037,
+           0.4817119240094084,
+           0.5586754108256772,
+           0.6436649686741106,
+           0.7362412696393366,
+           0.8357052871814115,
+           0.941110082276454,
+           1.051279455579918,
+           1.1648330479138644,
+           1.280217303021855,
+           1.3957415523239776,
+           1.5096183452640977,
+           1.6200070342511317,
+           1.725059533102532,
+           1.8229671046406704,
+           1.9120069983442984,
+           1.990587753682642,
+           2.0572920091886706,
+           2.1109157109503323,
+           2.1505026957745312,
+           2.1753737318688815,
+           2.185149230899692,
+           2.179764996540884,
+           2.159480542437038,
+           2.124879692753887,
+           2.076863366752717,
+           2.0166346404638458,
+           1.9456763688167749,
+           1.8657218358027396,
+           1.7787190738301428,
+           1.6867896520695647,
+           1.5921828733180134,
+           1.4972264362448688,
+           1.4042747118655516,
+           1.315655847391212,
+           1.2336189455724844,
+           1.1602825723581622,
+           1.097585819936788,
+           1.0472430965798727,
+           1.0107037304546838,
+           0.9891173637233884,
+           0.9833059784491441,
+           0.9937432403370576,
+           1.020541673907285,
+           1.0634479975083484,
+           1.1218467531262175,
+           1.1947721689312245,
+           1.2809279967228817,
+           1.3787148766482238
+          ],
+          [
+           1.4533414623571634,
+           1.567267128218257,
+           1.6873979989548165,
+           1.8113624082023614,
+           1.9366875784723283,
+           2.0608534693612044,
+           2.1813476036806185,
+           2.2957195966101756,
+           2.4016341217923345,
+           2.496921087570969,
+           2.5796218653415,
+           2.6480305085288527,
+           2.700729022658627,
+           2.7366158913357634,
+           2.7549272261463402,
+           2.755250086546643,
+           2.7375277043345667,
+           2.702056541695507,
+           2.649475307324205,
+           2.580746246971261,
+           2.4971292082710375,
+           2.4001491504117904,
+           2.2915579229666596,
+           2.173291271297151,
+           2.047422135165947,
+           1.9161113899437585,
+           1.7815572341134207,
+           1.6459444514161612,
+           1.5113947704370403,
+           1.3799195089221983,
+           1.253375625632545,
+           1.1334262107535096,
+           1.0215063291566895,
+           0.9187949921166995,
+           0.8261938759327203,
+           0.7443132342460917,
+           0.6734652689907138,
+           0.6136650374128341,
+           0.5646387841320647,
+           0.5258394024803579,
+           0.49646855294110337,
+           0.4755048027900464,
+           0.461737004060961,
+           0.4538020003433687,
+           0.45022564977269597,
+           0.44946607440816233,
+           0.4499579968691592,
+           0.4501570047756964,
+           0.44858259264360145,
+           0.44385886911357353,
+           0.43475188370873913,
+           0.4202026199791217,
+           0.39935481850621385,
+           0.37157693081144355,
+           0.3364776602213614,
+           0.29391471423841564,
+           0.2439965706631866,
+           0.18707724209881785,
+           0.12374420591395506,
+           0.05479984462180109,
+           -0.0187630895572535,
+           -0.09579131671978129,
+           -0.17500537048449555,
+           -0.2550375135843134,
+           -0.3344722094279686,
+           -0.411888063734205,
+           -0.48590011072544625,
+           -0.5552013076331659,
+           -0.6186021197046238,
+           -0.6750671250658514,
+           -0.7237476435203491,
+           -0.7640094937834908,
+           -0.7954551072569228,
+           -0.8179393701370294,
+           -0.831578725819605,
+           -0.8367532421832602,
+           -0.8341015290622853,
+           -0.8245085755015273,
+           -0.809086759570912,
+           -0.7891504609755952,
+           -0.7661848739353636,
+           -0.741809770578559,
+           -0.7177390995113548,
+           -0.6957374168452176,
+           -0.6775742348956576,
+           -0.6649774347180472,
+           -0.6595869210056499,
+           -0.6629097007368107,
+           -0.6762775401532232,
+           -0.700808298750429,
+           -0.7373719552633091,
+           -0.7865622311275163,
+           -0.8486745842339386,
+           -0.9236911931914454,
+           -1.0112733835007854,
+           -1.1107617661582467,
+           -1.2211841706998856,
+           -1.3412712632130015,
+           -1.4694795501127413,
+           -1.6040212852073403,
+           -1.7429006253042514,
+           -1.8839552226286178,
+           -2.0249023045527657,
+           -2.1633881760220133,
+           -2.2970399905073733,
+           -2.423518573592902,
+           -2.5405710510073285,
+           -2.6460820309055557,
+           -2.73812211862109,
+           -2.814992600322658,
+           -2.8752652186600054,
+           -2.917816076517251,
+           -2.9418528416979988,
+           -2.9469345824505657,
+           -2.932983737406003,
+           -2.900289909536687,
+           -2.8495053676321658,
+           -2.7816323358181547,
+           -2.698002347019669,
+           -2.6002481252332923,
+           -2.490268639423776,
+           -2.370188134461449,
+           -2.242310087808504,
+           -2.109067161155247,
+           -1.9729683109708234,
+           -1.8365442886648742,
+           -1.7022927981427718,
+           -1.5726245850879421,
+           -1.449811708179412,
+           -1.335939188260941,
+           -1.2328611485651826,
+           -1.142162449510624,
+           -1.065126688029673,
+           -1.0027112771378135,
+           -0.955530150304134,
+           -0.9238444513307638,
+           -0.9075613783972576,
+           -0.9062411553753372,
+           -0.9191119092484958,
+           -0.9450920442201939,
+           -0.9828195254486679,
+           -1.0306873226226911,
+           -1.0868841197334258,
+           -1.1494392758742353,
+           -1.216270925628201,
+           -1.2852360388697146,
+           -1.3541812202168058,
+           -1.4209930188069868,
+           -1.483646539672213,
+           -1.5402511981523255,
+           -1.5890925371776472,
+           -1.628669131841038,
+           -1.6577237337953046,
+           -1.6752679564044288,
+           -1.6805999665026394,
+           -1.6733148259286197,
+           -1.6533073112598622,
+           -1.6207672287438653,
+           -1.5761674286064222,
+           -1.520244904055551,
+           -1.4539755308963846,
+           -1.3785431595040747,
+           -1.2953039081218025,
+           -1.2057466216855175,
+           -1.1114505508080221,
+           -1.0140413689896894,
+           -0.9151466810481088,
+           -0.8163521813772665,
+           -0.7191595968959695,
+           -0.6249474970993428,
+           -0.5349359738781851,
+           -0.4501560887932839,
+           -0.3714248579904804,
+           -0.2993263981835786,
+           -0.23419969486273962,
+           -0.17613328023700162,
+           -0.12496692780489138,
+           -0.0803002874510559,
+           -0.04150820423003616,
+           -0.007762290101283585,
+           0.021941844772222763,
+           0.04875244183572797,
+           0.07392539392786555,
+           0.09878496974435896,
+           0.12468251849420281,
+           0.15295426398209527,
+           0.18487932260857287,
+           0.22163907591832094,
+           0.2642789954246751,
+           0.3136739563032041,
+           0.37049798870006223,
+           0.4351993030363152,
+           0.5079812916215604,
+           0.588790056482081,
+           0.6773088463892539,
+           0.7729596088411285,
+           0.8749116796673054,
+           0.9820974486114565,
+           1.0932346583514383,
+           1.2068548215206356,
+           1.3213370797789061,
+           1.4349466849283028,
+           1.545877158152498,
+           1.6522950828575564,
+           1.752386411905726,
+           1.8444031232201914,
+           1.926709040061083,
+           1.9978236442705093,
+           2.0564627522551673,
+           2.1015749934818535,
+           2.1323731281530627,
+           2.148359362181523,
+           2.149343960652506,
+           2.1354566221643876,
+           2.107150251826156,
+           2.065196955958327,
+           2.010676272129352,
+           1.944955839358968,
+           1.8696649004028019,
+           1.7866612063611456,
+           1.6979920589966295,
+           1.6058503739858272,
+           1.5125267751725784,
+           1.4203588325502376,
+           1.3316786325827343,
+           1.2487599166397976,
+           1.173766040536532,
+           1.1086999949311578,
+           1.0553576828974742,
+           1.0152855783432224,
+           0.9897437888042709,
+           0.9796754208991235,
+           0.9856829993886063,
+           1.0080125249095913,
+           1.046545575054792,
+           1.1007996629300096,
+           1.1699368712650107,
+           1.252780583353325,
+           1.347839939339751,
+           1.4533414623571645
+          ],
+          [
+           1.532593026660372,
+           1.651924922950517,
+           1.775936872424431,
+           1.9021852215977433,
+           2.028158219474325,
+           2.151330637503727,
+           2.2692186041395757,
+           2.379433380221514,
+           2.4797328282963567,
+           2.568069385870074,
+           2.6426334380327794,
+           2.701891096817297,
+           2.744615530284541,
+           2.7699111403439596,
+           2.7772300608864517,
+           2.7663806327006726,
+           2.737527704334567,
+           2.691184803839687,
+           2.6281984204146642,
+           2.549724822612786,
+           2.457200016428886,
+           2.352303607942123,
+           2.23691747735617,
+           2.1130802908182487,
+           1.9829389704477465,
+           1.848698309331247,
+           1.712569955298211,
+           1.576721994259678,
+           1.4432303406940918,
+           1.3140330901673418,
+           1.1908889079733276,
+           1.0753404211628115,
+           0.9686834511173024,
+           0.8719427737164721,
+           0.7858549278255184,
+           0.7108584144692421,
+           0.6470914431281104,
+           0.5943971927312731,
+           0.5523363678379826,
+           0.5202066498425765,
+           0.49706847328938575,
+           0.48177640274123557,
+           0.47301524992163135,
+           0.46933995737925477,
+           0.46921818647470875,
+           0.4710744862035119,
+           0.4733348867030717,
+           0.4744707579829637,
+           0.4730408004694932,
+           0.46773008863399923,
+           0.45738517083040675,
+           0.4410443353726454,
+           0.4179622820830985,
+           0.38762858672969536,
+           0.3497795091597697,
+           0.30440287037396,
+           0.25173590483084424,
+           0.1922561773384708,
+           0.12666583433147124,
+           0.05586963258073852,
+           -0.019052649950567185,
+           -0.09687867039885231,
+           -0.17627996711340924,
+           -0.2558614142235033,
+           -0.33420262446764115,
+           -0.4099001884897179,
+           -0.48160961574021777,
+           -0.548085848189349,
+           -0.608221253127068,
+           -0.6610800645257315,
+           -0.705928332198604,
+           -0.7422585520555747,
+           -0.7698082862760117,
+           -0.7885722357846233,
+           -0.7988073951686017,
+           -0.8010310978907945,
+           -0.7960119428556629,
+           -0.7847537774498355,
+           -0.768473092456048,
+           -0.7485703561649699,
+           -0.726595974222783,
+           -0.7042117042036901,
+           -0.6831484759492629,
+           -0.6651616672384456,
+           -0.6519849567943083,
+           -0.6452839210952042,
+           -0.6466105567338543,
+           -0.6573598956801538,
+           -0.6787298370143939,
+           -0.7116852465039645,
+           -0.7569272765060963,
+           -0.8148687354689447,
+           -0.8856161917616365,
+           -0.9689593342169456,
+           -1.064367935595247,
+           -1.1709965795051234,
+           -1.2876971207204448,
+           -1.4130386580240244,
+           -1.5453346124082887,
+           -1.682676326297163,
+           -1.8229724358269992,
+           -1.9639931222199525,
+           -2.1034182235549133,
+           -2.2388880879252775,
+           -2.36805597560986,
+           -2.488640773352305,
+           -2.598478769318821,
+           -2.695573253218841,
+           -2.778140752114857,
+           -2.8446527875610306,
+           -2.893872142122866,
+           -2.9248827505964283,
+           -2.9371124803054034,
+           -2.930348232108387,
+           -2.904742975147144,
+           -2.860814519507365,
+           -2.799436027201644,
+           -2.7218184584457235,
+           -2.6294853422975195,
+           -2.5242404436842056,
+           -2.408129068197062,
+           -2.283393897659431,
+           -2.1524263796749743,
+           -2.017714799970473,
+           -1.8817902447902883,
+           -1.747171709973239,
+           -1.6163116324551345,
+           -1.4915431083389443,
+           -1.3750300196601994,
+           -1.2687212205922465,
+           -1.1743098348470664,
+           -1.0931985918707556,
+           -1.02647198316014,
+           -0.9748758552298602,
+           -0.9388048764789577,
+           -0.9182981258344898,
+           -0.9130428562210999,
+           -0.9223862903816062,
+           -0.9453551151267701,
+           -0.9806821573876326,
+           -1.0268395559240098,
+           -1.0820775903198239,
+           -1.1444681976491047,
+           -1.211952100082552,
+           -1.2823883862804981,
+           -1.3536053375784813,
+           -1.423451267903427,
+           -1.4898441545111687,
+           -1.5508188747141425,
+           -1.6045709307361407,
+           -1.6494956389436164,
+           -1.6842218785464984,
+           -1.7076396354163,
+           -1.7189207353849485,
+           -1.717532334271908,
+           -1.7032429146053265,
+           -1.6761207269864966,
+           -1.6365248026068635,
+           -1.5850888478706397,
+           -1.5226985078241497,
+           -1.4504626477923193,
+           -1.3696794482551296,
+           -1.2817982329780786,
+           -1.188378051679535,
+           -1.0910441136115636,
+           -0.9914432155450692,
+           -0.891199325684285,
+           -0.7918704736185892,
+           -0.6949080559177211,
+           -0.6016195984849066,
+           -0.5131359220955904,
+           -0.430383539116105,
+           -0.3540629702581493,
+           -0.2846335139379249,
+           -0.22230483135678344,
+           -0.16703553211218913,
+           -0.1185387625116662,
+           -0.07629461643007952,
+           -0.039569011142723536,
+           -0.007438502576726971,
+           0.021179639895204817,
+           0.0474929157345302,
+           0.07279556490392153,
+           0.09842805295947062,
+           0.125735159028198,
+           0.1560237935864085,
+           0.19052168148246876,
+           0.23033802501629727,
+           0.27642721260018077,
+           0.329556561806553,
+           0.39027898337502587,
+           0.4589113275645532,
+           0.535519029238433,
+           0.6199075069032522,
+           0.7116205976424047,
+           0.8099461288543462,
+           0.9139285434901129,
+           1.0223883127354172,
+           1.1339476934211667,
+           1.247062221349002,
+           1.360057180403702,
+           1.4711681546477673,
+           1.578584659949848,
+           1.6804957659374564,
+           1.7751365604180502,
+           1.8608342784386218,
+           1.936052917696707,
+           1.9994351911838224,
+           2.0498407261040374,
+           2.086379503909417,
+           2.108439647682042,
+           2.1157087973778648,
+           2.1081884673637665,
+           2.0862009504624055,
+           2.050388514203474,
+           2.0017048236980095,
+           1.941398716848024,
+           1.8709906467461246,
+           1.7922422884203013,
+           1.7071199780093778,
+           1.617752807756343,
+           1.526386336000356,
+           1.4353329842276492,
+           1.346920280359019,
+           1.2634381665914238,
+           1.187086619740795,
+           1.1199248313474761,
+           1.0638231637421207,
+           1.0204190375157374,
+           0.9910778168107033,
+           0.9768596436650818,
+           0.9784930340625169,
+           0.996355889703451,
+           1.030464404657485,
+           1.0804701592199244,
+           1.1456654990155302,
+           1.2249971003933182,
+           1.3170874282329952,
+           1.4202636041834136,
+           1.5325930266603733
+          ],
+          [
+           1.6157990654621017,
+           1.7395217433481989,
+           1.866348037415153,
+           1.993782993592667,
+           2.1192971581172824,
+           2.2403815071146136,
+           2.354601825641346,
+           2.459651274307148,
+           2.553399926337737,
+           2.6339401319287465,
+           2.69962666815191,
+           2.749110759016689,
+           2.7813671984591104,
+           2.7957139753907874,
+           2.7918239804180196,
+           2.7697285640151517,
+           2.7298129111569716,
+           2.6728033929130084,
+           2.599747246512835,
+           2.511985117253874,
+           2.4111171639211157,
+           2.2989635800416393,
+           2.1775205126661112,
+           2.0489124653449275,
+           1.9153423500443707,
+           1.7790404020912804,
+           1.642213191717603,
+           1.5069939550117202,
+           1.375395426431148,
+           1.2492662855873837,
+           1.1302522345837083,
+           1.0197626012384464,
+           0.9189432211286857,
+           0.8286561911355387,
+           0.7494669130887861,
+           0.6816386625566299,
+           0.6251347293909278,
+           0.5796279880157204,
+           0.544517571327347,
+           0.5189521470254534,
+           0.5018591335472856,
+           0.4919790485211115,
+           0.48790405933449765,
+           0.4881197060459086,
+           0.49104869386592875,
+           0.4950956075461526,
+           0.4986913842821422,
+           0.5003363954732234,
+           0.49864103045968056,
+           0.4923627460238506,
+           0.48043864214562837,
+           0.4620127447448917,
+           0.43645731683657346,
+           0.4033876770726812,
+           0.36267017503519045,
+           0.3144231515422101,
+           0.2590108950958961,
+           0.19703078779785316,
+           0.12929401097061166,
+           0.05680034787330485,
+           -0.01929222594439245,
+           -0.09770233881920765,
+           -0.17706346585757307,
+           -0.2559645888866612,
+           -0.33299218047687085,
+           -0.40677238374826996,
+           -0.47601225335175107,
+           -0.5395389458363868,
+           -0.5963357990164958,
+           -0.6455743186535713,
+           -0.6866411947992244,
+           -0.7191595968959689,
+           -0.7430041430189567,
+           -0.758309100784654,
+           -0.7654695513699279,
+           -0.765135429393998,
+           -0.75819853554157,
+           -0.7457728010964785,
+           -0.7291682593988018,
+           -0.70985934417694,
+           -0.6894482845482051,
+           -0.6696244974072558,
+           -0.6521209865789891,
+           -0.6386688417007786,
+           -0.6309509861403341,
+           -0.6305563508497533,
+           -0.6389356491194539,
+           -0.6573598956801537,
+           -0.6868827531983654,
+           -0.7283077013351831,
+           -0.7821609102921613,
+           -0.8486705648918246,
+           -0.9277532300437161,
+           -1.01900767772836,
+           -1.1217164135843876,
+           -1.2348549522926568,
+           -1.3571086998804371,
+           -1.4868971125477475,
+           -1.6224046203235925,
+           -1.761617634300648,
+           -1.9023668025998166,
+           -2.042373546423292,
+           -2.1792997969262045,
+           -2.310799768967396,
+           -2.4345725512492877,
+           -2.54841426539452,
+           -2.650268549876974,
+           -2.738274158423754,
+           -2.810808525782993,
+           -2.866526245131377,
+           -2.904391518702442,
+           -2.9237037836389996,
+           -2.9241158752257412,
+           -2.9056442656670307,
+           -2.8686711041726025,
+           -2.813937978743208,
+           -2.7425315169754767,
+           -2.6558611376356986,
+           -2.555629451948859,
+           -2.443795988948853,
+           -2.322535078561702,
+           -2.1941888654607062,
+           -2.0612165427431055,
+           -1.9261409843053188,
+           -1.7914940162525619,
+           -1.6597615992762635,
+           -1.533330194909729,
+           -1.4144355589173176,
+           -1.305115145524461,
+           -1.207165218225595,
+           -1.122103648679691,
+           -1.0511392475259447,
+           -0.9951483132038698,
+           -0.954658910910458,
+           -0.929843207932884,
+           -0.9205179983071655,
+           -0.9261533537958242,
+           -0.9458891443347104,
+           -0.9785589840960129,
+           -1.022720983701437,
+           -1.076694529159894,
+           -1.1386021676697746,
+           -1.206415562901775,
+           -1.278004390579911,
+           -1.3511869812827646,
+           -1.4237814828797322,
+           -1.493656310657029,
+           -1.5587786789885993,
+           -1.6172600636382723,
+           -1.6673975269853192,
+           -1.7077099475031867,
+           -1.7369683269130602,
+           -1.754219500238781,
+           -1.7588027416855847,
+           -1.7503589386451528,
+           -1.7288321927066759,
+           -1.6944638956725755,
+           -1.6477795155304484,
+           -1.5895685074764154,
+           -1.520857933955978,
+           -1.442880531113797,
+           -1.3570380932447637,
+           -1.264861158523739,
+           -1.1679660657377424,
+           -1.0680105108653901,
+           -0.9666487627436909,
+           -0.8654876980530587,
+           -0.7660447874955959,
+           -0.669709108131453,
+           -0.5777063728802941,
+           -0.4910688593714025,
+           -0.41061098943892627,
+           -0.33691116096032436,
+           -0.2703002692429831,
+           -0.2108571799630784,
+           -0.15841123420223305,
+           -0.11255168301509988,
+           -0.07264376883502147,
+           -0.03785099844691868,
+           -0.007162991594926267,
+           0.020571855387336104,
+           0.04660977657244103,
+           0.07227210193744686,
+           0.0989038460714025,
+           0.1278315342809456,
+           0.160321401156946,
+           0.19753908839138204,
+           0.24051193140659385,
+           0.29009485910316174,
+           0.346940839378903,
+           0.4114766873169311,
+           0.48388491599152206,
+           0.5640921551388187,
+           0.651764494377821,
+           0.7463099294917167,
+           0.846887906983087,
+           0.9524257783265604,
+           1.061641795706023,
+           1.173074110089555,
+           1.2851150746023614,
+           1.3960500153239082,
+           1.5040995114581421,
+           1.607464130390629,
+           1.7043704929510208,
+           1.793117502088531,
+           1.8721215552876314,
+           1.9399595778182201,
+           1.9954087600064607,
+           2.0374819560730204,
+           2.0654578029508435,
+           2.0789047424362774,
+           2.077698276010694,
+           2.06203094512977,
+           2.032414706705982,
+           1.9896755595542595,
+           1.9349404681423736,
+           1.8696168203748635,
+           1.7953648416244516,
+           1.7140635632007766,
+           1.6277711055321096,
+           1.5386801804834511,
+           1.4490698398323962,
+           1.3612545948852082,
+           1.2775321030540747,
+           1.2001306591130696,
+           1.131157740693455,
+           1.0725508389984812,
+           1.0260317570899082,
+           0.9930654805414242,
+           0.9748246205990171,
+           0.9721603007351357,
+           0.9855802067412419,
+           1.0152343519120766,
+           1.0609089265184792,
+           1.1220284090695956,
+           1.1976659204896036,
+           1.2865616060576768,
+           1.387148638563374,
+           1.4975862542772103,
+           1.615799065462103
+          ],
+          [
+           1.7022556180229278,
+           1.8293164806727251,
+           1.9578665745596422,
+           2.0853807655875904,
+           2.2093333177394423,
+           2.3272526675409786,
+           2.4367748874956776,
+           2.5356945991841027,
+           2.6220121589323044,
+           2.69397602942848,
+           2.7501193671823545,
+           2.789289995417681,
+           2.8106730914392584,
+           2.813806092815833,
+           2.7985855135779834,
+           2.7652655554762036,
+           2.7144485954430477,
+           2.647067823969593,
+           2.5643624954242297,
+           2.4678464258792725,
+           2.3592705325326717,
+           2.240580347483015,
+           2.1138695540951935,
+           1.9813306837169646,
+           1.8452041719522518,
+           1.7077270056396716,
+           1.571082193428287,
+           1.4373502644366227,
+           1.3084639417185222,
+           1.1861670516563834,
+           1.071978619158971,
+           0.9671629644862245,
+           0.8727064640442539,
+           0.7893014684499363,
+           0.7173376907929612,
+           0.6569011908315241,
+           0.6077808915129093,
+           0.5694823774212109,
+           0.5412485451566842,
+           0.522086507690491,
+           0.5108000025612228,
+           0.5060264211296264,
+           0.5062774662346641,
+           0.5099823611716772,
+           0.5155324759754089,
+           0.5213262088798444,
+           0.5258129621629059,
+           0.5275350822489734,
+           0.5251666930842104,
+           0.5175484378552049,
+           0.5037172548552623,
+           0.4829304458642579,
+           0.4546834464035258,
+           0.4187208728050297,
+           0.37504059698122477,
+           0.3238907816302536,
+           0.26575999174872905,
+           0.20136067811194272,
+           0.13160650026774567,
+           0.05758411622697148,
+           -0.019479790617412167,
+           -0.09825535337329688,
+           -0.17734923796307417,
+           -0.2553461646694498,
+           -0.33085111835955183,
+           -0.4025311121533217,
+           -0.469155379778688,
+           -0.5296329112357028,
+           -0.5830463136929123,
+           -0.6286810730758793,
+           -0.6660494092321382,
+           -0.6949080559177204,
+           -0.7152694526667251,
+           -0.7274060049534457,
+           -0.731847247667667,
+           -0.7293699302913288,
+           -0.7209812256566458,
+           -0.7078954431404987,
+           -0.6915047970724775,
+           -0.6733449376898567,
+           -0.6550560911757976,
+           -0.6383407736096433,
+           -0.6249191380007055,
+           -0.6164830815244058,
+           -0.6146502798434481,
+           -0.6209193258902727,
+           -0.6366271313538018,
+           -0.6629097007368101,
+           -0.7006673113449846,
+           -0.7505350297544658,
+           -0.8128593686613244,
+           -0.8876817406237358,
+           -0.9747292006690836,
+           -1.0734127920924492,
+           -1.182833623393937,
+           -1.301796613790821,
+           -1.4288316548110713,
+           -1.5622217508375684,
+           -1.7000375267171128,
+           -1.8401773300307367,
+           -1.9804120133534457,
+           -2.1184333613823294,
+           -2.251905032219115,
+           -2.3785148137863454,
+           -2.496026957096653,
+           -2.6023333389290553,
+           -2.6955022277031215,
+           -2.7738234775398807,
+           -2.835849055477928,
+           -2.8804279136848,
+           -2.906734349712797,
+           -2.9142891502389134,
+           -2.902972983619017,
+           -2.8730316898612624,
+           -2.82507330883353,
+           -2.7600568839909574,
+           -2.679273274859761,
+           -2.5843184021681607,
+           -2.477059530226209,
+           -2.359595357515829,
+           -2.2342108344017313,
+           -2.1033277528034118,
+           -1.9694522535062629,
+           -1.8351204700779349,
+           -1.7028435723105824,
+           -1.5750534856639709,
+           -1.4540505460177182,
+           -1.3419543015827324,
+           -1.2406585972442261,
+           -1.151791972795418,
+           -1.0766842780216008,
+           -1.0163402575614184,
+           -0.9714206905828143,
+           -0.94223148867682,
+           -0.9287209644370138,
+           -0.9304852876231687,
+           -0.9467819503793804,
+           -0.976550872455044,
+           -1.0184425963998225,
+           -1.0708528556682055,
+           -1.1319626495231123,
+           -1.1997828311705,
+           -1.2722021127498968,
+           -1.3470373150997024,
+           -1.4220846433895624,
+           -1.4951707528291502,
+           -1.564202382047773,
+           -1.6272133749689723,
+           -1.6824079839213242,
+           -1.728199445466234,
+           -1.7632429434636692,
+           -1.786462218119502,
+           -1.797069241528721,
+           -1.794576555486221,
+           -1.7788020516951684,
+           -1.74986616336065,
+           -1.7081816258106362,
+           -1.6544361475504714,
+           -1.5895685074764156,
+           -1.51473875453883,
+           -1.4312933289988656,
+           -1.3407260460566428,
+           -1.2446359800727813,
+           -1.1446833584977372,
+           -1.0425446172715584,
+           -0.939867782875872,
+           -0.8382293301588346,
+           -0.7390936199991435,
+           -0.6437759480380915,
+           -0.5534101369949785,
+           -0.4689214830417276,
+           -0.3910057244791972,
+           -0.32011454216494745,
+           -0.25644792983473963,
+           -0.19995359299253668,
+           -0.1503333519699908,
+           -0.10705634271691775,
+           -0.06937863248856328,
+           -0.036368701307437724,
+           -0.006938088103457647,
+           0.02012363338057882,
+           0.04611049610639676,
+           0.07235943376200764,
+           0.10020832365512881,
+           0.13095390796918663,
+           0.16581072698897148,
+           0.20587217289745047,
+           0.2520747192374036,
+           0.30516630045952226,
+           0.36567971016551665,
+           0.43391175835835866,
+           0.5099087804584519,
+           0.5934589277481136,
+           0.684091494376301,
+           0.7810833544926431,
+           0.8834723990680364,
+           0.9900776801497344,
+           1.0995257952949387,
+           1.2102828811666824,
+           1.3206914369230751,
+           1.4290110688691573,
+           1.5334621411792024,
+           1.6322712360868021,
+           1.723717272904278,
+           1.8061771100141675,
+           1.878169458297526,
+           1.9383959683132108,
+           1.9857784161681662,
+           2.019491002948986,
+           2.0389868976634187,
+           2.0440182910788463,
+           2.0346493842907347,
+           2.0112619074751326,
+           1.9745529468558498,
+           1.925525046947769,
+           1.8654687459506363,
+           1.7959378900357126,
+           1.7187182525263456,
+           1.635790152135862,
+           1.5492859162962718,
+           1.461443167385455,
+           1.3745550180256416,
+           1.2909183438399465,
+           1.212781356013913,
+           1.142291720307913,
+           1.0814464631226246,
+           1.032044868901796,
+           0.9956455073756045,
+           0.9735284354441628,
+           0.9666634991027699,
+           0.9756855185820976,
+           1.000876978247455,
+           1.0421586656815964,
+           1.0990885160613275,
+           1.1708687230047545,
+           1.2563609802561007,
+           1.3541095246819095,
+           1.4623714648020067,
+           1.5791537050124493,
+           1.7022556180229291
+          ],
+          [
+           1.7912312227861493,
+           1.9205494308137483,
+           2.0497181956210455,
+           2.176203578982973,
+           2.297504951688573,
+           2.4112091494559666,
+           2.5150425684155473,
+           2.6069199939139205,
+           2.684989035544919,
+           2.747669147509871,
+           2.793684344042108,
+           2.822088871499008,
+           2.8322852681093056,
+           2.8240344251189047,
+           2.7974574547361803,
+           2.753029366155603,
+           2.6915647462561663,
+           2.614195831568181,
+           2.5223435381548396,
+           2.4176821817909957,
+           2.3020987682259673,
+           2.1776478588324104,
+           2.0465031175553134,
+           1.910906718388037,
+           1.7731178368959368,
+           1.6353614635800797,
+           1.4997787608629343,
+           1.3683801396707804,
+           1.2430021572037258,
+           1.125269236446126,
+           1.0165610828547207,
+           0.9179865276346768,
+           0.8303643637513125,
+           0.7542115644217999,
+           0.6897390886973049,
+           0.6368552894985526,
+           0.5951767508152037,
+           0.5640461974043155,
+           0.5425569467666489,
+           0.5295832137281483,
+           0.5238154365335501,
+           0.5237996734380037,
+           0.5279800232856937,
+           0.534742954801232,
+           0.5424623889274651,
+           0.5495443674478216,
+           0.5544701595238373,
+           0.5558367051125447,
+           0.55239336923428,
+           0.5430740817785134,
+           0.5270240613620929,
+           0.5036204655139064,
+           0.47248646948040146,
+           0.43349844815249494,
+           0.3867861156305293,
+           0.3327256602033941,
+           0.2719260943776593,
+           0.20520921544938456,
+           0.13358373751700614,
+           0.058214306606807174,
+           -0.019613757087618595,
+           -0.0985330353077505,
+           -0.17713486566858663,
+           -0.2540113737205869,
+           -0.3277975524700382,
+           -0.3972122567817638,
+           -0.46109700727422737,
+           -0.5184515539225503,
+           -0.5684652322157157,
+           -0.6105432522945234,
+           -0.6443271913211325,
+           -0.6697091081314525,
+           -0.6868388632497878,
+           -0.6961244024655409,
+           -0.6982249439654062,
+           -0.6940371928892682,
+           -0.6846748884835416,
+           -0.6714421631699035,
+           -0.6558013554112672,
+           -0.6393360651055583,
+           -0.6237103676241365,
+           -0.610625207270227,
+           -0.601773070162361,
+           -0.5987920882795901,
+           -0.6032207492550756,
+           -0.6164543798087229,
+           -0.6397045345418119,
+           -0.6739623569880284,
+           -0.7199668878547477,
+           -0.7781791785054053,
+           -0.8487629287645716,
+           -0.9315722104652285,
+           -1.0261466656693792,
+           -1.1317143854230973,
+           -1.2472024857730535,
+           -1.3712552072518944,
+           -1.5022591768586266,
+           -1.6383752923687676,
+           -1.7775765220714699,
+           -1.9176907629128848,
+           -2.05644777028905,
+           -2.191529066645053,
+           -2.3206196562888235,
+           -2.441460322461551,
+           -2.5518992610700524,
+           -2.6499418141951514,
+           -2.7337971054143826,
+           -2.8019204472412476,
+           -2.853050486987476,
+           -2.88624017881476,
+           -2.900880813743441,
+           -2.8967185024549047,
+           -2.8738626839154913,
+           -2.8327864218397583,
+           -2.774318446206723,
+           -2.6996270936936906,
+           -2.610196494207477,
+           -2.507795535958623,
+           -2.3944403142206383,
+           -2.2723509248282756,
+           -2.143903598789921,
+           -2.0115792858157517,
+           -1.8779098793752051,
+           -1.745423332025938,
+           -1.6165889358348824,
+           -1.4937640381083792,
+           -1.3791434274831784,
+           -1.2747125605703828,
+           -1.1822057063848663,
+           -1.1030699670147333,
+           -1.0384359913010632,
+           -0.9890960371789991,
+           -0.9554898617212196,
+           -0.9376987301445164,
+           -0.9354476406791429,
+           -0.9481156660046364,
+           -0.9747541187101251,
+           -1.0141120626481186,
+           -1.0646685186305684,
+           -1.1246705558711791,
+           -1.192176323706283,
+           -1.265101964724218,
+           -1.3412712632130015,
+           -1.4184668238627343,
+           -1.49448154629791,
+           -1.5671691618989505,
+           -1.634492630389232,
+           -1.6945692539572395,
+           -1.7457114546779329,
+           -1.7864622744353544,
+           -1.8156247925502704,
+           -1.8322848114499757,
+           -1.8358263310850778,
+           -1.8259395141342682,
+           -1.8026210318148965,
+           -1.7661668696575359,
+           -1.7171578591963668,
+           -1.656438380547882,
+           -1.5850888478706402,
+           -1.5043927405995352,
+           -1.4157990744206859,
+           -1.3208813139912636,
+           -1.221293811786898,
+           -1.118726912198314,
+           -1.0148618858133203,
+           -0.9113268551498261,
+           -0.8096548401285497,
+           -0.7112449902017942,
+           -0.6173279819069147,
+           -0.5289364479787217,
+           -0.4468811699321168,
+           -0.37173361364996066,
+           -0.3038152208675841,
+           -0.2431936927728432,
+           -0.18968631972485836,
+           -0.14287022795443066,
+           -0.10209923468271224,
+           -0.06652683192168704,
+           -0.03513466062882777,
+           -0.006765694887628927,
+           0.019838766035932907,
+           0.045999298475067125,
+           0.07305682151085001,
+           0.10233044924000839,
+           0.13507586339862843,
+           0.17244532890199765,
+           0.21545043333498903,
+           0.2649285620914567,
+           0.3215140254554824,
+           0.38561463484010344,
+           0.4573943856463128,
+           0.5367627472960196,
+           0.6233708908814268,
+           0.7166150058505709,
+           0.8156466737345217,
+           0.919390083751484,
+           1.0265656968325305,
+           1.1357197957229372,
+           1.245259203612076,
+           1.3534903161874234,
+           1.4586614756114105,
+           1.559007622676767,
+           1.652796097698835,
+           1.738372423284305,
+           1.8142048940023678,
+           1.8789268194721347,
+           1.931375318025633,
+           1.970625636735591,
+           1.9960200783363617,
+           2.007190743884097,
+           2.0040754487745303,
+           1.9869263353217825,
+           1.956310883431664,
+           1.9131052075830854,
+           1.8584797187490925,
+           1.7938774193288516,
+           1.7209852829213366,
+           1.6416993442785537,
+           1.5580842837022886,
+           1.4723284305177538,
+           1.3866952285433103,
+           1.3034722996909194,
+           1.2249193076032234,
+           1.1532158598585402,
+           1.0904106937706632,
+           1.0383733669311626,
+           0.9987496198935991,
+           0.9729214960217274,
+           0.9619731944660899,
+           0.9666634991027695,
+           0.9874054722678026,
+           1.0242539309723444,
+           1.0769010391341296,
+           1.1446801566820357,
+           1.2265778898690158,
+           1.3212540915495794,
+           1.427069370308673,
+           1.5421194878001978,
+           1.664275858846218,
+           1.7912312227861507
+          ],
+          [
+           1.88197310587355,
+           2.0124487217296947,
+           2.141125794321851,
+           2.265483031679697,
+           2.383066088043347,
+           2.4915406430318363,
+           2.5887426884038454,
+           2.6727248594273307,
+           2.741797743302077,
+           2.79456521809754,
+           2.8299530193135602,
+           2.847229893927362,
+           2.8460208796750015,
+           2.826312435980345,
+           2.7884493477808654,
+           2.7331235197519392,
+           2.6613549713155087,
+           2.5744655276392328,
+           2.4740458740969595,
+           2.36191679719361,
+           2.2400855699975564,
+           2.1106985514210863,
+           1.9759911535832595,
+           1.8382363879720343,
+           1.6996932278894397,
+           1.5625560211441103,
+           1.428906153326218,
+           1.3006670991790488,
+           1.179563909205549,
+           1.0670880630298667,
+           0.9644684831048126,
+           0.8726493455921591,
+           0.792275153578358,
+           0.7236833555175698,
+           0.6669046034640561,
+           0.6216705559538663,
+           0.5874289440315524,
+           0.5633654405078764,
+           0.5484317064875623,
+           0.5413788396130487,
+           0.5407953190033107,
+           0.5451484356892262,
+           0.5528281170344164,
+           0.5621920011081714,
+           0.5716105934725992,
+           0.5795113448597377,
+           0.5844205235077334,
+           0.5850018195278812,
+           0.580090708909448,
+           0.5687237192956995,
+           0.5501618755366219,
+           0.5239077567652611,
+           0.48971576443601045,
+           0.4475953781407082,
+           0.39780735858042343,
+           0.3408530401910748,
+           0.2774570349642527,
+           0.20854383944282087,
+           0.13520899439655434,
+           0.058685587317034126,
+           -0.01969299193805328,
+           -0.09853303530775052,
+           -0.17642216266072644,
+           -0.2519715089754995,
+           -0.32385731735750967,
+           -0.3908608175568491,
+           -0.451905313316212,
+           -0.5060894732394208,
+           -0.5527159171322171,
+           -0.5913143104807712,
+           -0.6216583208591495,
+           -0.6437759480380904,
+           -0.6579529104195998,
+           -0.6647289498330738,
+           -0.6648871001667325,
+           -0.6594361481344839,
+           -0.6495866920635467,
+           -0.6367213724285417,
+           -0.6223600016876158,
+           -0.6081204568752971,
+           -0.5956763128985704,
+           -0.5867122846216742,
+           -0.5828786092715832,
+           -0.5857455357744484,
+           -0.5967590933759159,
+           -0.6171992880693651,
+           -0.648141822459973,
+           -0.6904243539605394,
+           -0.744618199577225,
+           -0.8110062655804483,
+           -0.8895678302368849,
+           -0.9799706411807791,
+           -1.081570610024032,
+           -1.1934191998589576,
+           -1.3142784110187677,
+           -1.4426430815448243,
+           -1.5767700359602481,
+           -1.7147134437201235,
+           -1.8543655913991703,
+           -1.9935021342296808,
+           -2.129830776496381,
+           -2.261042239468756,
+           -2.3848623123219777,
+           -2.4991037475064526,
+           -2.601716758195365,
+           -2.6908369019489746,
+           -2.7648291910166902,
+           -2.8223273544501577,
+           -2.862267288417329,
+           -2.883913866128178,
+           -2.88688043435743,
+           -2.871140495918034,
+           -2.837031262423217,
+           -2.78524895478117,
+           -2.7168359253968415,
+           -2.6331598712221114,
+           -2.5358855958405426,
+           -2.426939957082208,
+           -2.3084707998851752,
+           -2.182800818265286,
+           -2.0523774118040334,
+           -1.9197196980450963,
+           -1.7873639102584744,
+           -1.6578084485256657,
+           -1.5334598600807114,
+           -1.416581002119704,
+           -1.3092425874247673,
+           -1.213279231436466,
+           -1.130251010853287,
+           -1.0614114110994035,
+           -1.0076823863312807,
+           -0.9696370848112721,
+           -0.9474906086400372,
+           -0.9410989845018269,
+           -0.9499663259344077,
+           -0.9732599724726236,
+           -1.009833201586431,
+           -1.0582549302482704,
+           -1.1168456585687119,
+           -1.183718762213854,
+           -1.25682611677882,
+           -1.3340069389038194,
+           -1.4130386580240273,
+           -1.4916885909026525,
+           -1.567765179449233,
+           -1.6391675709687537,
+           -1.703932368373736,
+           -1.7602764547382808,
+           -1.8066348999003508,
+           -1.8416930839953733,
+           -1.8644123206166612,
+           -1.8740484270299476,
+           -1.8701628663924208,
+           -1.8526262728076637,
+           -1.8216143596543124,
+           -1.7775964002459088,
+           -1.7213166528335324,
+           -1.6537692747255017,
+           -1.5761674286064224,
+           -1.4899074240976444,
+           -1.3965288557842197,
+           -1.2976717924617431,
+           -1.1950321389722387,
+           -1.0903163301205916,
+           -0.9851965249253907,
+           -0.8812674487290311,
+           -0.7800059810779646,
+           -0.6827345101132812,
+           -0.590588971499234,
+           -0.5044923643150708,
+           -0.42513439106483214,
+           -0.352957707729561,
+           -0.2881510967019365,
+           -0.2306496949004483,
+           -0.18014222593788187,
+           -0.13608500356182632,
+           -0.09772229828956959,
+           -0.06411249465764302,
+           -0.03415931695363961,
+           -0.006647270472054833,
+           0.019719663460038,
+           0.04627712446073069,
+           0.07435836496804714,
+           0.10525226868332047,
+           0.14016252696113185,
+           0.1801690751616491,
+           0.2261928332864842,
+           0.27896471064177825,
+           0.3389997249401472,
+           0.40657695491926005,
+           0.48172589552792733,
+           0.5642196197932207,
+           0.6535749757953341,
+           0.7490598651765028,
+           0.8497074658964874,
+           0.9543370811680719,
+           1.061581123242797,
+           1.1699175793684256,
+           1.277707161910881,
+           1.383234219035168,
+           1.4847503796926658,
+           1.5805198296179037,
+           1.6688650656098836,
+           1.748211954887356,
+           1.8171329353679793,
+           1.874387231193211,
+           1.9189570248337993,
+           1.9500786210794454,
+           1.9672677568780856,
+           1.9703383514617752,
+           1.9594141500435678,
+           1.9349328876930416,
+           1.8976427835283942,
+           1.848591364567356,
+           1.7891068087731474,
+           1.7207721832956857,
+           1.6453931320043647,
+           1.5649597316963058,
+           1.4816033847093113,
+           1.397549743349901,
+           1.31506876534345,
+           1.2364230767906377,
+           1.1638158678865063,
+           1.0993395656391263,
+           1.044926516462258,
+           1.0023028700036472,
+           0.9729467848467718,
+           0.9580519784470628,
+           0.9584975201746861,
+           0.9748246205990162,
+           1.00722100568073,
+           1.055513285317667,
+           1.1191675360691646,
+           1.1972981224705,
+           1.2886845849020228,
+           1.3917962292840287,
+           1.5048238696292584,
+           1.6257180031969907,
+           1.7522325438388688,
+           1.8819731058735507
+          ],
+          [
+           1.9737135498930385,
+           2.1042368438345114,
+           2.23131602101464,
+           2.352463779108535,
+           2.4652928408733454,
+           2.5675675074825186,
+           2.6572517110957827,
+           2.7325524567850468,
+           2.7919576548299183,
+           2.834267479213599,
+           2.858618543592151,
+           2.8645003582765565,
+           2.8517637166470653,
+           2.8206208523974547,
+           2.7716374053730948,
+           2.705716428733287,
+           2.6240748589871523,
+           2.528213048532157,
+           2.419878123343462,
+           2.3010220724749346,
+           2.1737555975657434,
+           2.0402988466846486,
+           1.9029302253012632,
+           1.7639345163479776,
+           1.6255515503499718,
+           1.4899266453196123,
+           1.3590639851481219,
+           1.2347840259244902,
+           1.118685914008191,
+           1.0121157704619872,
+           0.9161415468753011,
+           0.8315349914340597,
+           0.7587610854790193,
+           0.6979751241987493,
+           0.6490274251710114,
+           0.6114754599144238,
+           0.584603021113268,
+           0.5674458662432836,
+           0.5588231211938265,
+           0.5573735890126243,
+           0.5615959924813255,
+           0.5698920876942234,
+           0.580611521363826,
+           0.5920972687399024,
+           0.6027304826106451,
+           0.6109736069264744,
+           0.6154106604825963,
+           0.6147836754296644,
+           0.6080243800828737,
+           0.5942803428667738,
+           0.5729349410009524,
+           0.5436206799542306,
+           0.5062255636386829,
+           0.4608923963630358,
+           0.4080110811283812,
+           0.34820416028091844,
+           0.28230601924836757,
+           0.21133633766433266,
+           0.13646852049775213,
+           0.05899397110958685,
+           -0.019716824806027357,
+           -0.0982553533732969,
+           -0.17521715872944182,
+           -0.24924382861298064,
+           -0.3190637491939948,
+           -0.3835305305284793,
+           -0.4416580637948157,
+           -0.4926512579827986,
+           -0.5359316147746703,
+           -0.5711569331835631,
+           -0.5982345867480794,
+           -0.6173279819069136,
+           -0.6288559824081483,
+           -0.6334852667919196,
+           -0.6321157695157291,
+           -0.6258595365227526,
+           -0.6160134984159643,
+           -0.6040268245174221,
+           -0.591463664886411,
+           -0.5799622111699274,
+           -0.5711911077876319,
+           -0.5668043198103145,
+           -0.568395611017349,
+           -0.5774538037468065,
+           -0.5953199807386392,
+           -0.6231477484112397,
+           -0.6618676118345804,
+           -0.7121564157108168,
+           -0.7744126852603969,
+           -0.8487385589685136,
+           -0.934928845147377,
+           -1.0324675601459947,
+           -1.1405321220841813,
+           -1.2580051847481513,
+           -1.3834939064512979,
+           -1.515356262949711,
+           -1.651733836531388,
+           -1.79059034958779,
+           -1.9297550644262513,
+           -2.0669700454747475,
+           -2.1999401785367367,
+           -2.3263847669562803,
+           -2.4440894783784044,
+           -2.5509573994612227,
+           -2.645057969904234,
+           -2.72467261124289,
+           -2.7883359390236695,
+           -2.8348715474973933,
+           -2.8634214814567387,
+           -2.873468657283051,
+           -2.864851661099613,
+           -2.837771532137785,
+           -2.7927903296344265,
+           -2.730821477167765,
+           -2.6531120745410743,
+           -2.5612175593550965,
+           -2.4569692835852077,
+           -2.342435740323779,
+           -2.219878328212747,
+           -2.091702672250268,
+           -1.9604066264020483,
+           -1.8285261631709224,
+           -1.6985804060273233,
+           -1.5730170811377173,
+           -1.4541596546452922,
+           -1.3441573811081309,
+           -1.244939418579875,
+           -1.1581740679443577,
+           -1.085234070883453,
+           -1.0271687552831872,
+           -0.9846836525264633,
+           -0.9581280320005463,
+           -0.9474906086400368,
+           -0.9524034840582559,
+           -0.972154185555768,
+           -1.005705474816483,
+           -1.0517224140936965,
+           -1.108606006620723,
+           -1.1745325739999475,
+           -1.2474979001509525,
+           -1.3253650622369595,
+           -1.4059147864478876,
+           -1.4868971125477506,
+           -1.5660831269370665,
+           -1.6413155301458437,
+           -1.7105568409181717,
+           -1.7719341043960974,
+           -1.8237790646606353,
+           -1.864662879673822,
+           -1.893424596505182,
+           -1.9091927630987917,
+           -1.9113997257733562,
+           -1.8997883448245916,
+           -1.874411049452134,
+           -1.8356213430653159,
+           -1.7840580561250683,
+           -1.7206228214460868,
+           -1.6464514119263718,
+           -1.562879728927727,
+           -1.4714053573654442,
+           -1.3736457078590047,
+           -1.2712938445226494,
+           -1.1660731472643595,
+           -1.0596919786448842,
+           -0.9537995169846123,
+           -0.849943879793846,
+           -0.7495335957709088,
+           -0.6538033912962952,
+           -0.5637851409426382,
+           -0.4802846940128963,
+           -0.40386513402962215,
+           -0.33483685937828056,
+           -0.2732546952465442,
+           -0.21892206411577902,
+           -0.17140205898379737,
+           -0.13003508486088836,
+           -0.09396256439996242,
+           -0.06215604708218508,
+           -0.033450922130713455,
+           -0.00658381678087879,
+           0.019767333314580717,
+           0.04694162352983102,
+           0.07625305248699603,
+           0.10894906207043605,
+           0.14617086318121653,
+           0.1889166193795335,
+           0.23800848718735418,
+           0.2940644127202017,
+           0.3574754619835057,
+           0.4283893196895588,
+           0.50670043241947,
+           0.5920471003843523,
+           0.683815642263957,
+           0.7811515741627304,
+           0.8829775612641628,
+           0.988017723905956,
+           1.0948277130284416,
+           1.2018298175070894,
+           1.3073522316530215,
+           1.4096714985889476,
+           1.507057057179032,
+           1.5978167589975063,
+           1.6803421890801296,
+           1.7531526208236305,
+           1.814936461556094,
+           1.8645891004317812,
+           1.9012461531174552,
+           1.9243112062498111,
+           1.9334772962242686,
+           1.9287415083122428,
+           1.9104122496826894,
+           1.8791089294987542,
+           1.835753966438123,
+           1.7815572341134212,
+           1.7179932432299299,
+           1.646771541228475,
+           1.5698009810873925,
+           1.4891486666271183,
+           1.406994518170412,
+           1.325582516323895,
+           1.2471697700758888,
+           1.1739746160906523,
+           1.10812498743942,
+           1.0516082911840676,
+           1.0062240051045517,
+           0.9735401450661711,
+           0.9548546674217261,
+           0.9511627574988261,
+           0.9631308183472177,
+           0.9910778168107021,
+           1.0349644704415757,
+           1.0943905730006416,
+           1.1686005627968226,
+           1.256497241626249,
+           1.3566633573601954,
+           1.467390575053534,
+           1.586715184395101,
+           1.7124597297233681,
+           1.8422796066345104,
+           1.9737135498930392
+          ],
+          [
+           2.0656763891751853,
+           2.195137228080592,
+           2.319525825570047,
+           2.436409924787001,
+           2.5434895346415964,
+           2.6386465211322125,
+           2.7199900191587014,
+           2.7858966174411255,
+           2.8350443945792985,
+           2.8664400317635295,
+           2.8794383935711862,
+           2.8737541486032225,
+           2.8494651920260496,
+           2.8070078277428157,
+           2.7471638641531295,
+           2.6710399694915146,
+           2.580039815890838,
+           2.4758297111496854,
+           2.3602985695769076,
+           2.2355132045612676,
+           2.1036700325119573,
+           1.9670443579813979,
+           1.8279384612230363,
+           1.6886297309717873,
+           1.5513200764190096,
+           1.4180878134912283,
+           1.2908431526753743,
+           1.1712883205192692,
+           1.0608832269986288,
+           0.9608174492128586,
+           0.871989141914876,
+           0.7949913112010135,
+           0.7301057036347052,
+           0.6773043737354026,
+           0.636258802836045,
+           0.6063562565060523,
+           0.5867228906469837,
+           0.5762529523624019,
+           0.5736432748148576,
+           0.5774321391092481,
+           0.5860414738575581,
+           0.5978212869604028,
+           0.611095176101162,
+           0.6242057455999727,
+           0.6355587679975843,
+           0.6436649686741113,
+           0.6471783798664215,
+           0.6449303048405215,
+           0.6359580512562993,
+           0.6195277318918206,
+           0.5951505873163269,
+           0.5625924548304368,
+           0.5218761867163948,
+           0.4732770040283474,
+           0.4173109551644099,
+           0.3547168266705452,
+           0.2864320226287698,
+           0.21356308431534607,
+           0.13735165965984128,
+           0.059136848918035105,
+           -0.01968505405469327,
+           -0.09770233881920767,
+           -0.17353004875326197,
+           -0.24585141004318656,
+           -0.31345740373527137,
+           -0.37528341324190717,
+           -0.4304419550779229,
+           -0.47825060153461657,
+           -0.5182543279360033,
+           -0.550241660936151,
+           -0.5742541643778624,
+           -0.5905889714992334,
+           -0.5997942523929204,
+           -0.6026576890385341,
+           -0.6001882122988996,
+           -0.5935914313818995,
+           -0.5842393519510964,
+           -0.5736351301063244,
+           -0.5633737419977427,
+           -0.5550995594898676,
+           -0.5504619082062414,
+           -0.5510697432269084,
+           -0.558446608118521,
+           -0.57398704400167,
+           -0.5989155868873629,
+           -0.6342494341681449,
+           -0.6807657762765341,
+           -0.7389746791625832,
+           -0.8090982700732241,
+           -0.8910568263934808,
+           -0.9844621987838108,
+           -1.0886188196713027,
+           -1.2025323607774092,
+           -1.3249259134330236,
+           -1.4542633776589164,
+           -1.5887795650487793,
+           -1.726516350897708,
+           -1.8653640570134358,
+           -2.0031071120967785,
+           -2.137472924874343,
+           -2.2661828191439883,
+           -2.3870038217572502,
+           -2.4978000658326667,
+           -2.59658257296628,
+           -2.68155620993348,
+           -2.7511626766654387,
+           -2.804118471710257,
+           -2.8394468968334623,
+           -2.856503301110315,
+           -2.8549929234727203,
+           -2.834980867359886,
+           -2.7968939276473654,
+           -2.7415141838597634,
+           -2.669964470088868,
+           -2.5836860262530323,
+           -2.4844088226053076,
+           -2.37411522515319,
+           -2.2549978295957063,
+           -2.129412431602254,
+           -1.9998272183208912,
+           -1.8687693570457213,
+           -1.7387702197638113,
+           -1.6123105153025405,
+           -1.4917666031987262,
+           -1.3793592351503596,
+           -1.2771059116794803,
+           -1.1867779548544448,
+           -1.1098632847125713,
+           -1.0475357501579061,
+           -1.0006317079292673,
+           -0.969634369581645,
+           -0.9546662505415049,
+           -0.9554898617212189,
+           -0.9715165876322105,
+           -1.0018235002107065,
+           -1.0451776694046282,
+           -1.1000673545390238,
+           -1.1647392988752434,
+           -1.2372412075160988,
+           -1.3154683693151377,
+           -1.3972132895878988,
+           -1.4802171344275283,
+           -1.5622217508375686,
+           -1.6410210205272138,
+           -1.7145103291389354,
+           -1.7807329862194199,
+           -1.83792251299843,
+           -1.8845398229091017,
+           -1.9193044510315034,
+           -1.9412191399601715,
+           -1.9495872571898811,
+           -1.944022698791177,
+           -1.9244521214283714,
+           -1.8911095349995435,
+           -1.8445234766300178,
+           -1.785497168762345,
+           -1.7150822351615302,
+           -1.6345467045811446,
+           -1.5453381687865886,
+           -1.44904307625977,
+           -1.3473432324312309,
+           -1.2419706395497048,
+           -1.1346618428372026,
+           -1.0271129536423536,
+           -0.9209364948854725,
+           -0.8176211599115393,
+           -0.7184954943759918,
+           -0.6246964041075082,
+           -0.537143262772508,
+           -0.4565182449170502,
+           -0.3832533463654533,
+           -0.3175243791729484,
+           -0.25925204679841835,
+           -0.20811002148208715,
+           -0.16353976463000705,
+           -0.12477165690144608,
+           -0.09085184206389571,
+           -0.06067404162710423,
+           -0.03301546950080355,
+           -0.006575870661041264,
+           0.019981372291020757,
+           0.047987173719554244,
+           0.07872485415393052,
+           0.11338955285648199,
+           0.15305003881565746,
+           0.19861395337325854,
+           0.2507974292589531,
+           0.3100999180144504,
+           0.3767849234898047,
+           0.45086718667483533,
+           0.5321067004377317,
+           0.6200097559915348,
+           0.7138370405649133,
+           0.8126186224295664,
+           0.9151754797758478,
+           1.0201470584869095,
+           1.126024184995624,
+           1.2311865181638229,
+           1.3339436021339313,
+           1.4325784835007314,
+           1.525392783485088,
+           1.6107520709660734,
+           1.6871303664515571,
+           1.7531526208236303,
+           1.8076340557290769,
+           1.8496153238077917,
+           1.8783925448655814,
+           1.8935413962360346,
+           1.8949345789623997,
+           1.8827521425513316,
+           1.8574843259425617,
+           1.819926756685873,
+           1.771168039558443,
+           1.7125699552982114,
+           1.6457406750631913,
+           1.5725015720447808,
+           1.4948483739730165,
+           1.4149075449863746,
+           1.334888908857407,
+           1.2570356247459178,
+           1.1835726989652364,
+           1.1166552598267365,
+           1.0583178363109578,
+           1.0104258646739026,
+           0.9746306004567161,
+           0.9523285377869869,
+           0.9446263351186545,
+           0.9523121191036475,
+           0.975833889184553,
+           1.0152855783432206,
+           1.0704011442844013,
+           1.140556874575297,
+           1.224781893542288,
+           1.3217766628133178,
+           1.4299390760677926,
+           1.547397566486054,
+           1.67205047702704,
+           1.8016107931218388,
+           1.9336552083351302,
+           2.0656763891751866
+          ],
+          [
+           2.1570835764860057,
+           2.2843808160843233,
+           2.405008913126143,
+           2.5166112463365935,
+           2.6169945899344143,
+           2.7041763233618226,
+           2.7764268181169807,
+           2.8323060256579096,
+           2.8706934292349673,
+           2.890810681394513,
+           2.892236423898755,
+           2.8749129736538097,
+           2.839144752370343,
+           2.7855885343649702,
+           2.7152357813540937,
+           2.6293875205630823,
+           2.529622398417245,
+           2.4177587022298015,
+           2.2958112827822172,
+           2.165944428118257,
+           2.030421830430631,
+           1.8915548514337972,
+           1.7516503256068414,
+           1.612959144403547,
+           1.4776268379561308,
+           1.3476473146836656,
+           1.2248208350209708,
+           1.1107171853632458,
+           1.0066448850649772,
+           0.9136271062930036,
+           0.8323848175486935,
+           0.7633274809639964,
+           0.7065514455425258,
+           0.6618459880300698,
+           0.6287067647819778,
+           0.6063562565060521,
+           0.5937706175771921,
+           0.5897121869314117,
+           0.5927667821448258,
+           0.6013847854925051,
+           0.6139249432978601,
+           0.6286997398238656,
+           0.6440211757333366,
+           0.6582457794448954,
+           0.6698177074840761,
+           0.6773088463892546,
+           0.6794549123781649,
+           0.6751866536341316,
+           0.6636553909314675,
+           0.6442522820351156,
+           0.6166208600622225,
+           0.5806625715936018,
+           0.5365352223159217,
+           0.4846444217516954,
+           0.4256282995459241,
+           0.36033593925528373,
+           0.28980013724982345,
+           0.21520524011157918,
+           0.1378509401258855,
+           0.059113011931466466,
+           -0.01959794847898374,
+           -0.09687867039885235,
+           -0.17137510644601137,
+           -0.24182295466230452,
+           -0.30708571320082045,
+           -0.36618924004124026,
+           -0.4183518805206253,
+           -0.4630093399647978,
+           -0.4998336144619342,
+           -0.5287454464060155,
+           -0.5499199389730145,
+           -0.5637851409426377,
+           -0.5710135957604264,
+           -0.5725070318303491,
+           -0.5693745500976828,
+           -0.5629048354829006,
+           -0.554533076326001,
+           -0.5458034166823652,
+           -0.5383278864800841,
+           -0.5337428511188076,
+           -0.5336640925629274,
+           -0.5396416765093275,
+           -0.5531157736415983,
+           -0.5753745868952094,
+           -0.6075154913670383,
+           -0.6504104200550076,
+           -0.7046764287631394,
+           -0.7706522496716341,
+           -0.8483814982727871,
+           -0.9376030361637002,
+           -1.0377488165603284,
+           -1.147949354692384,
+           -1.2670467760289432,
+           -1.3936152062669307,
+           -1.5259880828916557,
+           -1.6622917934818477,
+           -1.8004848851481947,
+           -1.9384019465967566,
+           -2.0738011428952783,
+           -2.20441428616583,
+           -2.327998255603463,
+           -2.442386539237615,
+           -2.5455396588105845,
+           -2.6355932584081434,
+           -2.710902686656817,
+           -2.770082980276254,
+           -2.8120432617082467,
+           -2.8360146929326118,
+           -2.8415712783143006,
+           -2.8286429777655853,
+           -2.7975207735699734,
+           -2.748853525478092,
+           -2.683636644495203,
+           -2.6031928113624727,
+           -2.5091451563168783,
+           -2.4033834976419937,
+           -2.288024403370715,
+           -2.1653659891888544,
+           -2.0378384924753044,
+           -1.9079517643915138,
+           -1.7782408965001373,
+           -1.6512112437200146,
+           -1.529284120397223,
+           -1.4147444305183166,
+           -1.309691446992411,
+           -1.2159938796062548,
+           -1.1352502685499515,
+           -1.0687556128281233,
+           -1.0174749935286702,
+           -0.9820247844664063,
+           -0.9626618612404169,
+           -0.9592810286717653,
+           -0.9714206905828131,
+           -0.9982765897186784,
+           -1.0387232540717246,
+           -1.091342603609472,
+           -1.1544590028499144,
+           -1.2261798939587576,
+           -1.3044410157016444,
+           -1.3870551087802927,
+           -1.4717629303165614,
+           -1.5562853513566373,
+           -1.6383752923687678,
+           -1.7158682631835434,
+           -1.7867303153080079,
+           -1.8491022849281868,
+           -1.9013393023838625,
+           -1.942044665974346,
+           -1.9700973215541153,
+           -1.9846723508954391,
+           -1.9852540471912026,
+           -1.9716413409696185,
+           -1.9439455294932066,
+           -1.90258045270601,
+           -1.848245444270199,
+           -1.7819015626136212,
+           -1.7047417698469738,
+           -1.618155871900901,
+           -1.5236911577194467,
+           -1.4230097757978228,
+           -1.317843960345023,
+           -1.209950265125882,
+           -1.1010639795399968,
+           -0.992854888406696,
+           -0.8868854946656145,
+           -0.78457275391851,
+           -0.6871542732759156,
+           -0.5956598068295971,
+           -0.51088873933375,
+           -0.43339409194132233,
+           -0.363473413122903,
+           -0.301166738530087,
+           -0.24626162009969962,
+           -0.19830504177255892,
+           -0.15662186144447213,
+           -0.12033925066576467,
+           -0.08841644939995026,
+           -0.05967901672916556,
+           -0.03285664319020344,
+           -0.006623499340311741,
+           0.020359969522763702,
+           0.0494049292021785,
+           0.08175285740824534,
+           0.11853617248006364,
+           0.16074185292572474,
+           0.20917903330914436,
+           0.26445145926429386,
+           0.32693555889358733,
+           0.39676474267707146,
+           0.4738203829490435,
+           0.5577297510588102,
+           0.6478710098950857,
+           0.7433851760837417,
+           0.8431947845096741,
+           0.9460288124712117,
+           1.0504532562016913,
+           1.1549066028749377,
+           1.2577393103670116,
+           1.3572562983266099,
+           1.4517613703126373,
+           1.5396024300692737,
+           1.6192163269310553,
+           1.6891721666719188,
+           1.748211954887356,
+           1.7952874995446007,
+           1.829592586247193,
+           1.8505895519453646,
+           1.858029517554331,
+           1.8519656939212927,
+           1.8327593450238042,
+           1.801078173008185,
+           1.7578870772166337,
+           1.7044314290562212,
+           1.6422131917176035,
+           1.5729603936942818,
+           1.4985906332914414,
+           1.4211694436338655,
+           1.3428644802576466,
+           1.265896602853245,
+           1.1924890063365414,
+           1.1248156120110915,
+           1.064949955690187,
+           1.01481580553766,
+           0.9761407080721679,
+           0.9504135970182509,
+           0.9388475079620381,
+           0.942348324257214,
+           0.9614903391422581,
+           0.9964992589592037,
+           1.04724309657987,
+           1.1132312169132192,
+           1.193621602239822,
+           1.2872362088251124,
+           1.3925840925891895,
+           1.5078917952869069,
+           1.6311403082304925,
+           1.7601077723347482,
+           1.892416935054735,
+           2.0255862700024103,
+           2.1570835764860075
+          ],
+          [
+           2.2471617656586265,
+           2.3712125667080097,
+           2.4870420580806663,
+           2.59238920428549,
+           2.685186120722605,
+           2.7636025023919117,
+           2.8260846271134916,
+           2.8713880368413887,
+           2.898603151832364,
+           2.9071732413828264,
+           2.8969043574471094,
+           2.867967029244015,
+           2.8208897132694846,
+           2.756544189178236,
+           2.676123283004089,
+           2.5811114805138735,
+           2.4732491607323404,
+           2.3544913287853997,
+           2.226961854586502,
+           2.0929043264748404,
+           1.9546307042565636,
+           1.8144690024266314,
+           1.6747112506007669,
+           1.537562964046955,
+           1.4050953131053026,
+           1.279201107391526,
+           1.1615556108677072,
+           1.0535830796685914,
+           0.9564297691231247,
+           0.8709439933573977,
+           0.7976636442820527,
+           0.7368113910548597,
+           0.6882975908843646,
+           0.6517307520208179,
+           0.6264352046680837,
+           0.6114754599144238,
+           0.6056865749449312,
+           0.6077096987354857,
+           0.6160318496582337,
+           0.6290288779352969,
+           0.6450104940333529,
+           0.6622662006007278,
+           0.6791109514042769,
+           0.6939293761850519,
+           0.705217454939718,
+           0.711620597642406,
+           0.7119671839474797,
+           0.7052967394085463,
+           0.6908820670815371,
+           0.6682448124144597,
+           0.6371641110157996,
+           0.5976781488790879,
+           0.5500786483628021,
+           0.4948984760353252,
+           0.4328927457758149,
+           0.3650139577999896,
+           0.29238186733774507,
+           0.2162489116719119,
+           0.13796213775721514,
+           0.058922661821573664,
+           -0.019456245031484985,
+           -0.09579131671978132,
+           -0.16877056359473175,
+           -0.23719254502575363,
+           -0.30000258497578625,
+           -0.35632495174691653,
+           -0.40549012762449893,
+           -0.4470564212429724,
+           -0.48082532192392147,
+           -0.5068501572952296,
+           -0.5254377890918234,
+           -0.537143262772507,
+           -0.5427575098891733,
+           -0.5432883833706738,
+           -0.5399354804376423,
+           -0.5340593713129042,
+           -0.5271460000747092,
+           -0.520767153135105,
+           -0.5165379976044935,
+           -0.5160727734735875,
+           -0.5209397779791303,
+           -0.5326168062732618,
+           -0.5524482088584856,
+           -0.5816046931866748,
+           -0.6210469350942663,
+           -0.6714939768182953,
+           -0.7333972743546668,
+           -0.8069211206571989,
+           -0.8919300159726545,
+           -0.9879833862821156,
+           -1.0943378695780708,
+           -1.209957202035587,
+           -1.3335295466926493,
+           -1.4634919207502386,
+           -1.5980611986874476,
+           -1.73527100153171,
+           -1.873013632011946,
+           -2.009086084741856,
+           -2.1412390533317827,
+           -2.267227775141371,
+           -2.3848635013509085,
+           -2.4920643565465253,
+           -2.586904358753152,
+           -2.6676594077354396,
+           -2.7328491156017325,
+           -2.781273447745253,
+           -2.812043261708247,
+           -2.824603973792934,
+           -2.818751744738366,
+           -2.7946417526258154,
+           -2.752788309074225,
+           -2.6940567691708464,
+           -2.6196473817136536,
+           -2.5310714194359236,
+           -2.4301201142224,
+           -2.31882709537872,
+           -2.199425185546602,
+           -2.074298545031936,
+           -1.945931267794593,
+           -1.816853618376496,
+           -1.6895871565061076,
+           -1.5665900235977512,
+           -1.4502036621821415,
+           -1.342602205530296,
+           -1.2457457111842976,
+           -1.1613383203333034,
+           -1.0907923072090764,
+           -1.03519884179659,
+           -0.9953061285994756,
+           -0.9715054078868299,
+           -0.9638251180784423,
+           -0.9719333232801357,
+           -0.9951483132038681,
+           -1.0324570885909703,
+           -1.0825412585238285,
+           -1.14380970119777,
+           -1.2144371810691572,
+           -1.2924079766346734,
+           -1.375563457771075,
+           -1.461652462337173,
+           -1.5483832607282855,
+           -1.633475865698734,
+           -1.7147134437201235,
+           -1.7899916133644191,
+           -1.857364474890154,
+           -1.9150863018399356,
+           -1.96164793781777,
+           -1.9958070768627976,
+           -2.0166117605730007,
+           -2.023416595483669,
+           -2.0158913759199373,
+           -1.994021986098272,
+           -1.9581036459660004,
+           -1.908726753417087,
+           -1.846755756455414,
+           -1.7733016581339454,
+           -1.6896889105180921,
+           -1.597417587747052,
+           -1.4981218392353128,
+           -1.3935257094817137,
+           -1.285397468790803,
+           -1.175503628108191,
+           -1.0655638104994425,
+           -0.9572076216717559,
+           -0.8519346031951518,
+           -0.7510782662840338,
+           -0.6557750933832512,
+           -0.5669392622147431,
+           -0.4852436957749635,
+           -0.4111078758836862,
+           -0.3446926814877253,
+           -0.285902330491452,
+           -0.23439332003849445,
+           -0.18959007955234072,
+           -0.15070687801852917,
+           -0.11677536631628474,
+           -0.08667699093209086,
+           -0.059179390749259556,
+           -0.032975786941370586,
+           -0.006726299858511377,
+           0.02089992190591183,
+           0.051182895124779186,
+           0.08531144397222183,
+           0.12434537821029366,
+           0.1691812292834616,
+           0.22052247383018025,
+           0.27885505793101234,
+           0.3444288982175607,
+           0.4172458812340103,
+           0.4970547140852635,
+           0.5833528016798888,
+           0.6753951432796197,
+           0.7722100582232688,
+           0.8726213722359847,
+           0.9752765261943593,
+           1.07867991290392,
+           1.1812306083416804,
+           1.281263545479341,
+           1.3770930842721518,
+           1.4670578631218807,
+           1.5495657768915483,
+           1.623137915456869,
+           1.686450315187425,
+           1.7383724232843047,
+           1.7780012504548663,
+           1.8046902891701395,
+           1.8180724002579076,
+           1.818076016767656,
+           1.8049341773120378,
+           1.7791860774187427,
+           1.741671012457459,
+           1.6935147748526214,
+           1.636108756854968,
+           1.5710821934282875,
+           1.5002681532370357,
+           1.4256640449553915,
+           1.3493875471607055,
+           1.2736289893683974,
+           1.2006013062860952,
+           1.1324887546951867,
+           1.0713956207569717,
+           1.0192961539509158,
+           0.9779869419847612,
+           0.9490428893179239,
+           0.9337778815965645,
+           0.9332111112038799,
+           0.9480399078401046,
+           0.9786197657199392,
+           1.0249520892916892,
+           1.0866799964554268,
+           1.1630923265327606,
+           1.2531358043861116,
+           1.3554351168771026,
+           1.468320468057232,
+           1.5898619997389372,
+           1.7179102987976689,
+           1.8501420657535423,
+           1.9841098944710565,
+           2.1172950132553647,
+           2.247161765658627
+          ],
+          [
+           2.3351488544517998,
+           2.4548978440495572,
+           2.564931222906877,
+           2.6631026828195252,
+           2.74748719579868,
+           2.8164222858572323,
+           2.8685433186137073,
+           2.9028119994921378,
+           2.9185374334890217,
+           2.9153892770668257,
+           2.893402701386167,
+           2.8529750812066212,
+           2.7948545206147677,
+           2.7201205204856085,
+           2.630157278537765,
+           2.526620286487863,
+           2.411397045936121,
+           2.2865628614246343,
+           2.154332782307023,
+           2.017010851941947,
+           1.8769378812130633,
+           1.736438992124245,
+           1.597772175594692,
+           1.4630790757049916,
+           1.3343391513876548,
+           1.2133282775007654,
+           1.1015827326397631,
+           1.0003693838229628,
+           0.9106627217765383,
+           0.833129228855805,
+           0.7681193789522995,
+           0.7156673795929023,
+           0.6754985755305934,
+           0.6470442451814817,
+           0.6294633409208192,
+           0.6216705559538661,
+           0.6223699483588375,
+           0.6300932206807949,
+           0.6432416443563546,
+           0.660130534906463,
+           0.6790351282384408,
+           0.6982366818438203,
+           0.7160676277335009,
+           0.7309546364450074,
+           0.7414585124824653,
+           0.746309929491718,
+           0.7444401260449188,
+           0.7350058172131452,
+           0.7174077297060669,
+           0.6913023353660988,
+           0.656606534978064,
+           0.6134952272034228,
+           0.5623918813442088,
+           0.503952412939985,
+           0.43904283335177763,
+           0.3687113041509471,
+           0.2941553702877448,
+           0.216685269062677,
+           0.13768431177155158,
+           0.058567409036420805,
+           -0.01926114258748439,
+           -0.09444947728615274,
+           -0.1657384558105142,
+           -0.2319993564943435,
+           -0.29226794553010477,
+           -0.3457740047015473,
+           -0.3919655126390547,
+           -0.43052681428030504,
+           -0.46139026907818786,
+           -0.48474103765740306,
+           -0.5010148448005839,
+           -0.510888739333749,
+           -0.5152650540516566,
+           -0.5152489466470662,
+           -0.5121200711694329,
+           -0.5072990845515098,
+           -0.5023098302551008,
+           -0.4987381575831922,
+           -0.49818842769089566,
+           -0.5022388234068886,
+           -0.5123966179140471,
+           -0.5300545660996993,
+           -0.5564495616693246,
+           -0.5926246533576853,
+           -0.6393954359320666,
+           -0.6973217280273722,
+           -0.7666853217010786,
+           -0.8474744410588883,
+           -0.9393753830071531,
+           -1.0417716361893565,
+           -1.153750588841665,
+           -1.2741177472535177,
+           -1.401418198444916,
+           -1.5339648682588392,
+           -1.6698729538732027,
+           -1.807099752074796,
+           -1.9434889654708618,
+           -2.076818451655083,
+           -2.204850288167995,
+           -2.3253819612608044,
+           -2.436297450675485,
+           -2.5356169768700787,
+           -2.6215442015811155,
+           -2.692509726814761,
+           -2.7472098200484782,
+           -2.7846394026539043,
+           -2.804118471710258,
+           -2.8053112792617596,
+           -2.7882377639625218,
+           -2.7532769138038224,
+           -2.7011619307639463,
+           -2.6329672640798023,
+           -2.550087773633719,
+           -2.454210473920226,
+           -2.347279487584956,
+           -2.231455001240849,
+           -2.109067161155247,
+           -1.9825659689110067,
+           -1.8544683342694122,
+           -1.7273035118135063,
+           -1.6035581878202636,
+           -1.4856224932107944,
+           -1.3757381971181173,
+           -1.2759502841027914,
+           -1.1880630375867354,
+           -1.1136016446239982,
+           -1.053780205302223,
+           -1.0094768770855134,
+           -0.9812167139991488,
+           -0.9691625768764746,
+           -0.973114298416492,
+           -0.9925160902289994,
+           -1.026471983160138,
+           -1.073768901761772,
+           -1.1329067934214805,
+           -1.2021350667822932,
+           -1.2794944466685778,
+           -1.3628632273549988,
+           -1.450006805681205,
+           -1.538629302619,
+           -1.6264260381566868,
+           -1.7111356107733782,
+           -1.7905903495877906,
+           -1.8627639539861074,
+           -1.9258152109329818,
+           -1.97812678231348,
+           -2.0183381809544128,
+           -2.0453722012505677,
+           -2.0584542348860366,
+           -2.057124079883672,
+           -2.041240037711492,
+           -2.01097528379199,
+           -1.9668066867747722,
+           -1.9094964366475267,
+           -1.840067016618668,
+           -1.7597702144067173,
+           -1.6700510111763047,
+           -1.572507307387721,
+           -1.468846541338813,
+           -1.3608403258541695,
+           -1.2502782697693247,
+           -1.1389221626330825,
+           -1.0284616832096356,
+           -0.9204727454446859,
+           -0.8163795208313857,
+           -0.7174210755299292,
+           -0.6246234367591313,
+           -0.538777759066585,
+           -0.46042510076917037,
+           -0.3898481482166188,
+           -0.3270700449479333,
+           -0.27186029885627466,
+           -0.2237475578037886,
+           -0.1820388673453811,
+           -0.14584485778852274,
+           -0.11411015592727894,
+           -0.0856481832660697,
+           -0.059179390749259535,
+           -0.03337189274425693,
+           -0.006883402476738426,
+           0.02159666119897243,
+           0.05330602909111218,
+           0.08937050659325003,
+           0.13076802153799827,
+           0.17829676694602034,
+           0.23254830429659207,
+           0.29388636429668435,
+           0.362431934419862,
+           0.43805505946060713,
+           0.5203736071284284,
+           0.6087590696981503,
+           0.702349289521891,
+           0.8000678154371843,
+           0.900649423360648,
+           1.002671172052449,
+           1.1045882183051878,
+           1.2047734883978547,
+           1.3015601978269231,
+           1.3932861317852097,
+           1.4783385466775538,
+           1.5551985295293294,
+           1.6224836581300468,
+           1.6789878400932863,
+           1.7237172729042778,
+           1.75592155794929,
+           1.7751191172783214,
+           1.7811161996206653,
+           1.774018918571829,
+           1.7542379370471535,
+           1.7224855938222656,
+           1.67976545575069,
+           1.6273544684006347,
+           1.566778063677867,
+           1.4997787608629347,
+           1.4282789629393353,
+           1.3543387989736115,
+           1.2801099918793775,
+           1.2077868359009674,
+           1.139555446911375,
+           1.0775424991011635,
+           1.0237646825017082,
+           0.9800801064302185,
+           0.9481428345031703,
+           0.929361668219735,
+           0.9248641998718712,
+           0.9354670339795843,
+           0.9616529324947434,
+           1.0035554761366898,
+           1.0609516563623445,
+           1.133262623951542,
+           1.2195626255932346,
+           1.3185959639335245,
+           1.4288016240757813,
+           1.5483450252098854,
+           1.6751561844022784,
+           1.8069734248035163,
+           1.9413916264201163,
+           2.075913907442604,
+           2.2080055406273953,
+           2.3351488544518
+          ],
+          [
+           2.4203004322797246,
+           2.5347286327946383,
+           2.6380174300250983,
+           2.7281534139120867,
+           2.803370719875938,
+           2.8621887944884437,
+           2.903443672874759,
+           2.9263120526666264,
+           2.93032762116176,
+           2.915389277066826,
+           2.8817610813107217,
+           2.8300639682059585,
+           2.761259443917109,
+           2.676625689006126,
+           2.5777266611527607,
+           2.466374958644056,
+           2.3445893509081634,
+           2.2145480057193576,
+           2.078538540760292,
+           1.9389060976563126,
+           1.7980006777394806,
+           1.6581249897227788,
+           1.5214840399784972,
+           1.3901376467773723,
+           1.2659569819488456,
+           1.150586138960054,
+           1.0454095980249827,
+           0.9515263097726847,
+           0.8697309529555953,
+           0.8005027428072853,
+           0.7440019794130563,
+           0.7000743344828669,
+           0.6682626849427259,
+           0.6478261174805908,
+           0.6377655541372383,
+           0.6368552894985521,
+           0.6436795889305168,
+           0.6566733780430225,
+           0.6741659590634702,
+           0.6944266223143671,
+           0.7157109821114269,
+           0.7363068570049982,
+           0.754578534516177,
+           0.7690083097688418,
+           0.7782342643662418,
+           0.7810833544926445,
+           0.7765990028861638,
+           0.7640625348061901,
+           0.7430079596962543,
+           0.7132297738122145,
+           0.6747836402444977,
+           0.6279799869266732,
+           0.5733707457373178,
+           0.511729632062508,
+           0.44402652974997353,
+           0.37139669708495887,
+           0.2951056414623462,
+           0.21651062050289466,
+           0.13701981270245123,
+           0.05805025917532399,
+           -0.019014291801943067,
+           -0.09286450466676435,
+           -0.1623044360972575,
+           -0.22628732579299443,
+           -0.28394723341345063,
+           -0.33462566469149435,
+           -0.3778924599270274,
+           -0.41356036703143245,
+           -0.4416928852662697,
+           -0.46260514064916186,
+           -0.4768577352595079,
+           -0.485243695774963,
+           -0.4887688268647408,
+           -0.4886259479821979,
+           -0.48616365324207994,
+           -0.4828503793338871,
+           -0.48023469210234426,
+           -0.4799028052972302,
+           -0.48343442240403456,
+           -0.4923580423962082,
+           -0.5081068913676524,
+           -0.5319766336999349,
+           -0.5650859788187029,
+           -0.6083412335586053,
+           -0.6624057572605595,
+           -0.727675159219819,
+           -0.8042589388588122,
+           -0.8919691114355172,
+           -0.990316190101899,
+           -1.0985127129517476,
+           -1.2154843158615816,
+           -1.339888163100654,
+           -1.4701383625719537,
+           -1.6044378157674395,
+           -1.7408157885048599,
+           -1.8771703413786307,
+           -2.0113146323134283,
+           -2.141026000863109,
+           -2.2640966675727907,
+           -2.378384833794492,
+           -2.481864949091779,
+           -2.572675925332552,
+           -2.649166118549442,
+           -2.7099339707017993,
+           -2.7538633019391434,
+           -2.7801523675005684,
+           -2.788335939023671,
+           -2.7782998342648653,
+           -2.7502874980718652,
+           -2.7048984265538434,
+           -2.643078421160844,
+           -2.566101855061348,
+           -2.4755463260158375,
+           -2.373260253194416,
+           -2.2613241455917104,
+           -2.142006422681108,
+           -2.017714799970473,
+           -1.8909443599295144,
+           -1.7642235097048342,
+           -1.6400590791259526,
+           -1.5208818344462365,
+           -1.4089936745044433,
+           -1.306517736735596,
+           -1.2153525716514189,
+           -1.1371314477200654,
+           -1.0731877263559322,
+           -1.024527101959689,
+           -0.9918073381556689,
+           -0.9753259525507421,
+           -0.9750161128458307,
+           -0.9904508115855033,
+           -1.0208551899961615,
+           -1.0651266880296704,
+           -1.1218625125978503,
+           -1.1893937435487822,
+           -1.265825241377667,
+           -1.3490803857424583,
+           -1.436949562817277,
+           -1.5271412350227187,
+           -1.6173343707245724,
+           -1.7052309853899645,
+           -1.7886075499958025,
+           -1.8653640570134389,
+           -1.9335695981170906,
+           -1.9915033992352604,
+           -2.0376903753578732,
+           -2.0709304066842273,
+           -2.0903206957568634,
+           -2.0952707382265983,
+           -2.085509623524614,
+           -2.061085571416709,
+           -2.0223578014808306,
+           -1.9699810202561094,
+           -1.9048829905289137,
+           -1.8282358145256679,
+           -1.741421713568917,
+           -1.6459942173362943,
+           -1.543635783066778,
+           -1.4361129462973745,
+           -1.3252301580509838,
+           -1.212783487595929,
+           -1.1005153644517782,
+           -0.9900714984563505,
+           -0.8829610534010867,
+           -0.7805210596599705,
+           -0.6838859367200271,
+           -0.5939628605148816,
+           -0.5114135564449803,
+           -0.43664293086066186,
+           -0.36979477585631915,
+           -0.3107545989829868,
+           -0.25915944556627984,
+           -0.2144144013613495,
+           -0.17571529182391335,
+           -0.14207693564568763,
+           -0.11236616838465968,
+           -0.08533873058028199,
+           -0.059679016729165514,
+           -0.03404160936453013,
+           -0.00709347803575295,
+           0.02244429267224809,
+           0.055756368427093306,
+           0.0938957037648092,
+           0.13774976399434602,
+           0.1880113443399478,
+           0.24515478074088395,
+           0.3094182067077131,
+           0.3807923536677536,
+           0.45901622229280525,
+           0.5435797736914734,
+           0.633733606589693,
+           0.7285054043478,
+           0.8267227584936807,
+           0.9270418078883133,
+           1.0279809789453038,
+           1.1279589764181588,
+           1.2253360596249112,
+           1.3184575485465575,
+           1.4056984403563855,
+           1.4855079812922083,
+           1.5564530323464525,
+           1.6172590902636288,
+           1.666847877305608,
+           1.7043704929510208,
+           1.7292352262176436,
+           1.741129256067051,
+           1.7400336162138998,
+           1.7262309659536519,
+           1.7003058862595906,
+           1.6631376059828609,
+           1.615885251910201,
+           1.5599659039911373,
+           1.4970259185616928,
+           1.4289061533262197,
+           1.357601883926579,
+           1.2852183392021495,
+           1.2139228972560132,
+           1.145895074267605,
+           1.0832755003229604,
+           1.0281151097402612,
+           0.9823257765361859,
+           0.9476335986355838,
+           0.9255359777467944,
+           0.9172635568139458,
+           0.9237479656250493,
+           0.9455961901616523,
+           0.9830722258725887,
+           1.0360865029988464,
+           1.104193387543762,
+           1.1865968689607196,
+           1.2821643498114883,
+           1.389448258311229,
+           1.5067150165715244,
+           1.6319807200821128,
+           1.76305272187862,
+           1.8975761719005015,
+           2.033084441760334,
+           2.167052270477849,
+           2.2969504000099517,
+           2.420300432279725
+          ],
+          [
+           2.501896078262448,
+           2.610029528346626,
+           2.705682337051223,
+           2.7869910389423413,
+           2.852363893053102,
+           2.900514822912944,
+           2.9304904171070087,
+           2.9416893752811033,
+           2.933873964527746,
+           2.9071732413828264,
+           2.8620779905945035,
+           2.799427528625409,
+           2.720388712727318,
+           2.6264276806957403,
+           2.519275017597278,
+           2.4008851997173344,
+           2.273391298979231,
+           2.1390560399359315,
+           2.000220383527081,
+           1.8592508651819988,
+           1.718486938296695,
+           1.5801895671200399,
+           1.4464922759002705,
+           1.3193557947591978,
+           1.200527348885612,
+           1.0915055186525875,
+           0.99351145716084,
+           0.9074670920259656,
+           0.8339807639463577,
+           0.7733405700474622,
+           0.7255154897776726,
+           0.6901641799423176,
+           0.6666511380294127,
+           0.6540697539246931,
+           0.6512716038367361,
+           0.6569011908315234,
+           0.6694352074580104,
+           0.6872252906632259,
+           0.7085431600837464,
+           0.7316269797403816,
+           0.7547277613325324,
+           0.7761546351754471,
+           0.7943178520545398,
+           0.807768444860752,
+           0.8152335710888927,
+           0.8156466737345233,
+           0.8081717358210803,
+           0.7922210592085295,
+           0.767466167522146,
+           0.7338416117012736,
+           0.6915416402793126,
+           0.6410098804271522,
+           0.5829223553813709,
+           0.5181643346098859,
+           0.4478016706437254,
+           0.373047416962649,
+           0.2952246411374097,
+           0.21572644359841,
+           0.13597426251272796,
+           0.05737558756012109,
+           -0.018717781144207944,
+           -0.09104980844718445,
+           -0.15849755781564748,
+           -0.2201047792861632,
+           -0.2751108456154959,
+           -0.3229742517179242,
+           -0.3633900338824898,
+           -0.39630062331748495,
+           -0.4218998192683837,
+           -0.4406297459758035,
+           -0.4531708405465291,
+           -0.46042510076916987,
+           -0.463492998400106,
+           -0.4636446299918181,
+           -0.462285829696662,
+           -0.460920102769342,
+           -0.46110735127432606,
+           -0.4644204518806522,
+           -0.47240080730490064,
+           -0.48651402632000124,
+           -0.5081068913676523,
+           -0.538366747512325,
+           -0.5782843923095137,
+           -0.6286214644091013,
+           -0.6898832213490175,
+           -0.7622974666326631,
+           -0.8458002360244572,
+           -0.9400286867416313,
+           -1.0443214549778927,
+           -1.1577265613842485,
+           -1.2790167553724014,
+           -1.406712002097477,
+           -1.5391086353890184,
+           -1.6743145302507445,
+           -1.8102894940994363,
+           -1.9448899405504003,
+           -2.075916796706692,
+           -2.201165507445387,
+           -2.3184769403671113,
+           -2.4257879644567235,
+           -2.5211804749436597,
+           -2.6029276664605883,
+           -2.6695364157415193,
+           -2.7197847224087095,
+           -2.752753269806197,
+           -2.7678503046330487,
+           -2.7648291910166916,
+           -2.7437981678497447,
+           -2.705222023488522,
+           -2.649915594769529,
+           -2.5790291930392484,
+           -2.4940262537327205,
+           -2.3966536932372455,
+           -2.288905632756225,
+           -2.172981309331162,
+           -2.0512381351500557,
+           -1.9261409843053188,
+           -1.8002088783586931,
+           -1.6759603061529247,
+           -1.5558584476929276,
+           -1.4422575757450466,
+           -1.3373518819598893,
+           -1.2431279174520296,
+           -1.1613217522442938,
+           -1.093381845881367,
+           -1.0404384855651596,
+           -1.0032804916729323,
+           -0.9823397173019611,
+           -0.9776836827617084,
+           -0.9890164922318416,
+           -1.0156879828392051,
+           -1.0567108609740021,
+           -1.110785391517816,
+           -1.1763310273889254,
+           -1.2515242037470198,
+           -1.3343413772866823,
+           -1.4226062697582378,
+           -1.5140401790990485,
+           -1.6063141536196595,
+           -1.697101786163267,
+           -1.7841313769148799,
+           -1.8652362357037329,
+           -1.9384019465967597,
+           -2.001809497968102,
+           -2.053873287999708,
+           -2.0932731460231264,
+           -2.118979660979285,
+           -2.130272275778735,
+           -2.126749786316767,
+           -2.108333071862689,
+           -2.075260074840236,
+           -2.0280732379144975,
+           -1.967599790112357,
+           -1.8949254469030192,
+           -1.8113622474998015,
+           -1.7184113922404236,
+           -1.6177220603597697,
+           -1.5110472809444913,
+           -1.4001979951371686,
+           -1.2869964842055561,
+           -1.1732303450943844,
+           -1.060608172456166,
+           -0.9507180545743564,
+           -0.8449899114298816,
+           -0.7446625984885555,
+           -0.6507565723034828,
+           -0.5640527669995969,
+           -0.48507816788655084,
+           -0.41409839396841874,
+           -0.35111741940720986,
+           -0.2958843796485728,
+           -0.24790722558750258,
+           -0.20647281343798168,
+           -0.1706728532982997,
+           -0.13943498991635644,
+           -0.1115581586122009,
+           -0.08575125098447846,
+           -0.060674041627104144,
+           -0.03497927069653245,
+           -0.007354749201265406,
+           0.02343564497991729,
+           0.058513182153148956,
+           0.0988487502711529,
+           0.14523153687888182,
+           0.19824277174459495,
+           0.2582352466678416,
+           0.32531917874906235,
+           0.39935481850621396,
+           0.4799520288080098,
+           0.5664768791043651,
+           0.6580651164713076,
+           0.7536421951901425,
+           0.8519493745130003,
+           0.9515752343031859,
+           1.0509918144537922,
+           1.1485944600538078,
+           1.2427443533655995,
+           1.3318126384050175,
+           1.4142249962385334,
+           1.4885055103047975,
+           1.5533186716814147,
+           1.6075084140659088,
+           1.6501331364029697,
+           1.6804957659374562,
+           1.69816803370208,
+           1.7030082751427635,
+           1.695172227283314,
+           1.67511646661657,
+           1.6435943145035432,
+           1.6016442247329203,
+           1.550570856366604,
+           1.4919192193727067,
+           1.4274424562173347,
+           1.3590639851481237,
+           1.288834876268958,
+           1.2188874560080363,
+           1.1513862360611278,
+           1.0884773367780702,
+           1.0322376203359556,
+           0.9846247646926217,
+           0.9474294947561922,
+           0.922231142705167,
+           0.9103576359535115,
+           0.9128509105975066,
+           0.9304386227029282,
+           0.9635128825052882,
+           1.0121165710593227,
+           1.0759376190986978,
+           1.1543114382230397,
+           1.2462314996361612,
+           1.3503678602730311,
+           1.4650932450477616,
+           1.5885161118076054,
+           1.7185199568497118,
+           1.8528079676872757,
+           1.9889519998499725,
+           2.1244447490649456,
+           2.2567539117849322,
+           2.38337707764465,
+           2.5018960782624484
+          ],
+          [
+           2.5792454563125053,
+           2.680163451055105,
+           2.767353468253092,
+           2.839117764978203,
+           2.8940522109154303,
+           2.931076115587536,
+           2.94945472361546,
+           2.948813868227932,
+           2.9291464599173653,
+           2.8908106813945134,
+           2.834519957091673,
+           2.7613249606069723,
+           2.672588111925476,
+           2.5699511934196146,
+           2.455296875225466,
+           2.3307050827026705,
+           2.1984052578861277,
+           2.0607256602653865,
+           1.9200409176569533,
+           1.778719073830141,
+           1.6390693851007694,
+           1.5032920932574276,
+           1.3734313476182736,
+           1.2513323661476954,
+           1.1386038165009156,
+           1.036586265360453,
+           0.9463273918032225,
+           0.8685644915019661,
+           0.8037146175249886,
+           0.7518725148489072,
+           0.7128163141136958,
+           0.6860207603630636,
+           0.6706775692067741,
+           0.665722330524194,
+           0.6698672227272979,
+           0.6816386625566292,
+           0.6994188997540255,
+           0.7214904755357399,
+           0.7460824007406902,
+           0.7714168753273289,
+           0.7957553662942529,
+           0.8174428861205197,
+           0.8349493677399686,
+           0.8469071134386994,
+           0.8521434017731676,
+           0.8497074658964876,
+           0.8388912052422142,
+           0.8192431565618418,
+           0.7905754256780698,
+           0.7529634635577716,
+           0.7067387548191328,
+           0.6524746689097515,
+           0.5909658993366264,
+           0.5232020800868318,
+           0.4503363166328015,
+           0.37364949794689284,
+           0.29451136252183624,
+           0.2143393728406791,
+           0.13455650703010366,
+           0.0565491022179691,
+           -0.018374119228616065,
+           -0.08902074177859011,
+           -0.15435002887857865,
+           -0.2135040241149318,
+           -0.2658335419755225,
+           -0.31091834200691776,
+           -0.3485809315922013,
+           -0.3788936083804056,
+           -0.40217852937933646,
+           -0.4190007754202441,
+           -0.43015456250936246,
+           -0.43664293086066136,
+           -0.439651413604006,
+           -0.4405163459303004,
+           -0.44068861772521145,
+           -0.4416937949211742,
+           -0.4450896337296716,
+           -0.45242208504920733,
+           -0.46518093177000036,
+           -0.48475621819871956,
+           -0.5123966179140467,
+           -0.5491708442824573,
+           -0.5959331375912739,
+           -0.653293765979269,
+           -0.7215953564175573,
+           -0.8008957298784193,
+           -0.8909577550263411,
+           -0.9912465612229352,
+           -1.1009342686566221,
+           -1.2189122055345483,
+           -1.3438103941871062,
+           -1.4740239043279413,
+           -1.607745497178674,
+           -1.7430038230846518,
+           -1.877706291670391,
+           -2.0096856111376438,
+           -2.136748895107074,
+           -2.2567281639627934,
+           -2.367531024835763,
+           -2.4671903013119363,
+           -2.5539114010919426,
+           -2.6261162568351746,
+           -2.6824827512254386,
+           -2.7219786401185355,
+           -2.7438891150237805,
+           -2.7478372950699526,
+           -2.7337971054143844,
+           -2.7020981797264505,
+           -2.653422614519828,
+           -2.5887935980877894,
+           -2.5095561318516744,
+           -2.417350252295743,
+           -2.3140773426705743,
+           -2.2018602908654623,
+           -2.0829983991736643,
+           -1.959918079433323,
+           -1.8351204700779349,
+           -1.7111271874309057,
+           -1.5904254702552878,
+           -1.4754139929575756,
+           -1.3683506085231896,
+           -1.2713032375603408,
+           -1.1861050458227775,
+           -1.1143149510628256,
+           -1.057184373499116,
+           -1.0156309956479705,
+           -0.9902201303791799,
+           -0.9811541148809596,
+           -0.9882699571675779,
+           -1.0110452654896585,
+           -1.048612294288841,
+           -1.0997797479611735,
+           -1.1630618003322657,
+           -1.2367136178525804,
+           -1.3187725222085624,
+           -1.4071037969956437,
+           -1.4994500364663004,
+           -1.5934828547026676,
+           -1.6868557227545429,
+           -1.7772566805053052,
+           -1.8624596797162982,
+           -1.940373354541205,
+           -2.009086084741856,
+           -2.0669063131074954,
+           -2.1123971997446813,
+           -2.144404838917921,
+           -2.1620794254057154,
+           -2.1648889328709022,
+           -2.1526250521652686,
+           -2.1254013281972277,
+           -2.083643625269074,
+           -2.028073237914497,
+           -1.9596831426280505,
+           -1.8797080510947586,
+           -1.7895890735534838,
+           -1.6909339281519657,
+           -1.58547373548805,
+           -1.4750175144952817,
+           -1.3614055445967113,
+           -1.246462778499554,
+           -1.131953479748256,
+           -1.0195382195487395,
+           -0.9107342995065321,
+           -0.8068805725742846,
+           -0.7091075161247895,
+           -0.6183132716944688,
+           -0.5351462091388888,
+           -0.4599944026954002,
+           -0.39298222707606845,
+           -0.33397409775645054,
+           -0.28258519572911134,
+           -0.2381988377926509,
+           -0.19998998346112637,
+           -0.16695421308019623,
+           -0.1379413726568934,
+           -0.11169296273820623,
+           -0.08688225436937197,
+           -0.06215604708218497,
+           -0.03617694370109855,
+           -0.0076650055009890115,
+           0.024562330832865114,
+           0.061553146377684276,
+           0.10418774109755835,
+           0.15315004100746152,
+           0.20890448665434475,
+           0.27167903541674454,
+           0.3414547510019904,
+           0.4179622820830985,
+           0.5006853526095417,
+           0.588871203494252,
+           0.6815477437592617,
+           0.7775469934238645,
+           0.8755342349084464,
+           0.974042138716294,
+           1.0715089964969904,
+           1.1663200836829146,
+           1.25685108757753,
+           1.3415124772988538,
+           1.4187936609105798,
+           1.4873057732634778,
+           1.5458219656437573,
+           1.5933141246697504,
+           1.6289850316569132,
+           1.6522950828575562,
+           1.6629828229093455,
+           1.6610786952540189,
+           1.6469115804792707,
+           1.621107872354549,
+           1.5845830273383468,
+           1.5385257119038913,
+           1.4843748584612995,
+           1.4237901202886911,
+           1.3586163842231014,
+           1.2908431526753747,
+           1.2225597399686816,
+           1.1559073386781613,
+           1.0930290967465923,
+           1.0360194034733472,
+           0.9868736105099555,
+           0.947439411956954,
+           0.9193710754963333,
+           0.9040876549108814,
+           0.9027362247631708,
+           0.9161610625541543,
+           0.9448795651190729,
+           0.9890655276858695,
+           1.04854023975195,
+           1.1227716659612033,
+           1.2108817870127553,
+           1.3116619800173743,
+           1.4235961244169189,
+           1.5448909333255845,
+           1.6735128355029099,
+           1.8072305744101773,
+           1.9436625518339916,
+           2.0803278277994437,
+           2.2146995987931426,
+           2.3442599148879415,
+           2.466554364730183,
+           2.579245456312506
+          ],
+          [
+           2.6516941556906004,
+           2.7445370361980004,
+           2.822509057954231,
+           2.884092576329796,
+           2.9280829714296273,
+           2.953614110147051,
+           2.960176145785604,
+           2.9476252550729125,
+           2.9161851041588425,
+           2.86644003176353,
+           2.7993201342358156,
+           2.7160786291176913,
+           2.6182620562243852,
+           2.507674043816007,
+           2.386333518072231,
+           2.2564283631468744,
+           2.120265643468073,
+           1.9802195771646378,
+           1.8386784977127912,
+           1.6979920589966275,
+           1.560419926588594,
+           1.4280831555603237,
+           1.3029193836462198,
+           1.1866428699298706,
+           1.080710285899449,
+           0.986293020817747,
+           0.9042566004960886,
+           0.8351476418047469,
+           0.7791885789858002,
+           0.736280206673006,
+           0.7060118931936857,
+           0.6876791309496644,
+           0.6803079130450684,
+           0.6826852612082105,
+           0.6933950834584954,
+           0.7108584144692414,
+           0.7333769902139619,
+           0.75917903369137,
+           0.7864660820716441,
+           0.8134596685534101,
+           0.8384466848934091,
+           0.8598222925540744,
+           0.8761293205637941,
+           0.8860931846560649,
+           0.8886514825495883,
+           0.8829775612641628,
+           0.8684975105375441,
+           0.8449002076948793,
+           0.812140219382968,
+           0.7704335498622659,
+           0.7202464093981789,
+           0.6622773550760324,
+           0.5974333255814779,
+           0.5268002468870048,
+           0.4516090234651937,
+           0.3731978461601191,
+           0.2929718402754758,
+           0.21236114347596902,
+           0.13277854110750303,
+           0.05557779558885152,
+           -0.017986213590482126,
+           -0.08679447148316075,
+           -0.14989693925763684,
+           -0.20654090565492464,
+           -0.25619381268035224,
+           -0.2985599340099914,
+           -0.33359044476273303,
+           -0.3614865934433263,
+           -0.3826958666355747,
+           -0.39790121986060484,
+           -0.4080036292751864,
+           -0.4140983939684183,
+           -0.41744578307225577,
+           -0.4194367715464736,
+           -0.42155473951385686,
+           -0.42533411905378254,
+           -0.43231705660690845,
+           -0.4440092164156126,
+           -0.4618358792133898,
+           -0.48709948988448676,
+           -0.5209397779791296,
+           -0.5642975164627472,
+           -0.6178828982927519,
+           -0.6821493994334811,
+           -0.7572738634535948,
+           -0.843143390184115,
+           -0.9393494428196977,
+           -1.0451894084849644,
+           -1.159675661116775,
+           -1.2815519871663155,
+           -1.4093170488018678,
+           -1.541254380640194,
+           -1.6754682490316453,
+           -1.809924551769527,
+           -1.942495804603826,
+           -2.0710091524468175,
+           -2.1932962604352686,
+           -2.307243885198803,
+           -2.4108439012269147,
+           -2.5022415618555636,
+           -2.5797808090905,
+           -2.642045510488786,
+           -2.687895593144722,
+           -2.7164971622946927,
+           -2.7273458323524276,
+           -2.720282657928173,
+           -2.6955022277031233,
+           -2.6535526706639656,
+           -2.5953275176051567,
+           -2.5220495562585707,
+           -2.4352470111326885,
+           -2.3367225644188574,
+           -2.2285159076078416,
+           -2.11286067050299,
+           -1.9921367112568804,
+           -1.8688188645250705,
+           -1.745423332025938,
+           -1.6244529585613265,
+           -1.5083426654285719,
+           -1.3994063114084878,
+           -1.2997862191666458,
+           -1.2114065427247698,
+           -1.135931561144967,
+           -1.0747298669158296,
+           -1.028845277569209,
+           -0.9989751391945823,
+           -0.9854565146448576,
+           -0.9882605616256368,
+           -1.0069952110965337,
+           -1.040916059229386,
+           -1.0889451913611257,
+           -1.1496974686848698,
+           -1.2215136323991045,
+           -1.3024994199500592,
+           -1.3905697477290142,
+           -1.4834968975084428,
+           -1.578961552828095,
+           -1.6746054686443068,
+           -1.768084524307012,
+           -1.8571209070740506,
+           -1.939553200908557,
+           -2.0133832124829194,
+           -2.0768184516550834,
+           -2.128309295022546,
+           -2.166579995694445,
+           -2.1906528567830126,
+           -2.199865056453604,
+           -2.193877794450149,
+           -2.1726776193143333,
+           -2.136569987356166,
+           -2.086165294072996,
+           -2.0223578014808306,
+           -1.946298056223231,
+           -1.8593595491586197,
+           -1.7631005035907739,
+           -1.6592217930834259,
+           -1.549522078142083,
+           -1.4358513118469645,
+           -1.3200637963613588,
+           -1.2039719744249604,
+           -1.089302112516366,
+           -0.9776529761154608,
+           -0.8704585139136063,
+           -0.7689554590856864,
+           -0.6741566246543281,
+           -0.5868305198968979,
+           -0.507487749492625,
+           -0.4363744808755787,
+           -0.37347308251069505,
+           -0.31850985116264824,
+           -0.2709695643385106,
+           -0.23011641953556491,
+           -0.19502075910590175,
+           -0.164590832548552,
+           -0.13760872054518308,
+           -0.11276944025877009,
+           -0.08872217193454146,
+           -0.06411249465764286,
+           -0.037624495522656606,
+           -0.008021622026235527,
+           0.025814817958944455,
+           0.06485054162776017,
+           0.10986750596571328,
+           0.16143828225199344,
+           0.21990628613657973,
+           0.2853724064513934,
+           0.35768840922380785,
+           0.43645731683657346,
+           0.5210407803961039,
+           0.6105732807432482,
+           0.7039828148006892,
+           0.8000175536388644,
+           0.897277801088802,
+           0.9942524409499128,
+           1.0893589404306823,
+           1.180985880508641,
+           1.2675369129059004,
+           1.3474750002017968,
+           1.419365781402055,
+           1.4819189204865062,
+           1.534026339758857,
+           1.5747963121864346,
+           1.603582485603218,
+           1.6200070342511312,
+           1.6239772766442357,
+           1.6156952596200274,
+           1.5956599827119233,
+           1.5646621203142135,
+           1.5237712869563305,
+           1.4743160786757594,
+           1.417857306290597,
+           1.35615500974611,
+           1.2911300022922165,
+           1.2248208350209713,
+           1.1593371926686913,
+           1.0968108275039639,
+           1.0393452071179141,
+           0.988965092206679,
+           0.9475672708955358,
+           0.9168736564439656,
+           0.8983879056801274,
+           0.8933566373694886,
+           0.9027362247631704,
+           0.9271660073004748,
+           0.966948615966041,
+           1.022037938762464,
+           1.0920350712314328,
+           1.1761924063572582,
+           1.2734258231637725,
+           1.3823347386327034,
+           1.501229597992326,
+           1.6281661985930007,
+           1.7609860769135188,
+           1.8973620407969352,
+           2.034847803424719,
+           2.170930574896429,
+           2.30308539407544,
+           2.428829939403707,
+           2.5457785437796554,
+           2.651694155690601
+          ],
+          [
+           2.718629227616585,
+           2.802605654115625,
+           2.870682464907581,
+           2.9215349657417526,
+           2.9541682589626497,
+           2.9679381249589563,
+           2.9625639755343838,
+           2.9381335920211904,
+           2.8950995561869735,
+           2.8342674792135987,
+           2.756776328456394,
+           2.6640713385961647,
+           2.5578701686380962,
+           2.4401231247512962,
+           2.312968407345364,
+           2.178683455707987,
+           2.0396335522216202,
+           1.8982189085261336,
+           1.756821486584237,
+           1.617752807756341,
+           1.4832039727684667,
+           1.3551990556740772,
+           1.2355529471063402,
+           1.125834608516057,
+           1.0273365625472222,
+           0.9410512886312539,
+           0.867655021171146,
+           0.8074992646040428,
+           0.7606101497129928,
+           0.7266955635025262,
+           0.7051597954976613,
+           0.6951252611365356,
+           0.6954606924776435,
+           0.7048150319073423,
+           0.7216561296820654,
+           0.7443132342460914,
+           0.7710221780263187,
+           0.7999721028738533,
+           0.829352539858725,
+           0.8573996583633519,
+           0.8824405292566104,
+           0.9029343055207827,
+           0.9175093094909854,
+           0.9249951266184508,
+           0.9244489385346922,
+           0.9151754797758498,
+           0.8967401689672664,
+           0.8689751423451088,
+           0.8319781007239166,
+           0.7861040657793162,
+           0.7319503231464282,
+           0.6703350037652619,
+           0.6022699167633501,
+           0.5289283928910865,
+           0.4516090234651937,
+           0.37169628278081857,
+           0.2906190994531743,
+           0.2098084922198642,
+           0.13065540714117002,
+           0.054469885366371935,
+           -0.017557346087034038,
+           -0.0843898328149945,
+           -0.14517596410606115,
+           -0.1992743350391602,
+           -0.24627321420184958,
+           -0.28600358545104265,
+           -0.31854539969593487,
+           -0.3442268497293787,
+           -0.36361666317991576,
+           -0.3775095910845765,
+           -0.38690544776257374,
+           -0.3929822270760673,
+           -0.3970639764873165,
+           -0.40058424957824074,
+           -0.40504607633044487,
+           -0.411979485427843,
+           -0.4228976816881524,
+           -0.4392530226553747,
+           -0.4623939502933518,
+           -0.4935240162384985,
+           -0.5336640925629266,
+           -0.5836187855616517,
+           -0.6439479695060343,
+           -0.7149442330553918,
+           -0.7966168861428963,
+           -0.8886830132262817,
+           -0.9905658838283065,
+           -1.1014008476304675,
+           -1.220048653597355,
+           -1.3451159453821238,
+           -1.474982503276546,
+           -1.607834630782496,
+           -1.7417039258223617,
+           -1.8745105366587205,
+           -2.004109884302737,
+           -2.1283417395692275,
+           -2.245080476392626,
+           -2.3522852852931333,
+           -2.448049123006997,
+           -2.5306451965625305,
+           -2.598569832041624,
+           -2.6505806587274425,
+           -2.685729146407393,
+           -2.7033866647199685,
+           -2.703263385449459,
+           -2.685419517906543,
+           -2.650268549876976,
+           -2.598572357636051,
+           -2.531428243552738,
+           -2.4502481540777716,
+           -2.356730519668832,
+           -2.2528253368259477,
+           -2.1406932765066666,
+           -2.022659748729862,
+           -1.9011649765759664,
+           -1.7787112310062865,
+           -1.6578084485256623,
+           -1.5409194949467275,
+           -1.4304063493445043,
+           -1.3284784624254358,
+           -1.2371444934351123,
+           -1.158168550595049,
+           -1.0930319538027327,
+           -1.042901407527643,
+           -1.0086043196668004,
+           -0.9906118322874508,
+           -0.9890299468146385,
+           -1.0035989337808298,
+           -1.0337010204270634,
+           -1.078376153019298,
+           -1.1363454394959862,
+           -1.2060416966397427,
+           -1.2856463587692941,
+           -1.3731318560272023,
+           -1.4663084432918603,
+           -1.5628743586264722,
+           -1.6604681154358292,
+           -1.7567216869016185,
+           -1.8493133258594812,
+           -1.9360187783737592,
+           -2.0147596944171546,
+           -2.0836481130933544,
+           -2.1410260008631097,
+           -2.185498946701087,
+           -2.2159632648772702,
+           -2.2316259204597944,
+           -2.2320168705860945,
+           -2.2169936016299054,
+           -2.1867378339719896,
+           -2.1417445574291434,
+           -2.082803746792851,
+           -2.01097528379199,
+           -1.927557774785703,
+           -1.8340520986287834,
+           -1.7321206428997695,
+           -1.623543286047388,
+           -1.5101712556113263,
+           -1.3938800367968531,
+           -1.2765225203285369,
+           -1.1598835634115534,
+           -1.0456370932654586,
+           -0.9353068102690627,
+           -0.8302314491666963,
+           -0.7315354345855103,
+           -0.64010562443447,
+           -0.5565746752370856,
+           -0.48131139114500804,
+           -0.4144182376538185,
+           -0.3557360164633093,
+           -0.30485551414963785,
+           -0.26113575897446806,
+           -0.22372835173203545,
+           -0.19160718225895274,
+           -0.16360270697210666,
+           -0.13843984796861739,
+           -0.11477848368695691,
+           -0.0912554371448134,
+           -0.06652683192168699,
+           -0.03930967921777155,
+           -0.008421581639830547,
+           0.027182509750311796,
+           0.06837747044747265,
+           0.11583999149471037,
+           0.17002613834107685,
+           0.23115508998930956,
+           0.2991995076565138,
+           0.37388280932014395,
+           0.4546834464035258,
+           0.5408460960376862,
+           0.6313995014575263,
+           0.7251805187425945,
+           0.8208637647276785,
+           0.9169961126451054,
+           1.0120351527018796,
+           1.1043906276519968,
+           1.1924677712534926,
+           1.2747114224330411,
+           1.3496497614720158,
+           1.4159365173147138,
+           1.472390527185954,
+           1.5180315903592811,
+           1.5521116456889756,
+           1.5741404152762812,
+           1.5839047916199005,
+           1.5814813994783656,
+           1.5672419326424911,
+           1.5418510456899963,
+           1.506256767099819,
+           1.4616735881987528,
+           1.4095585676008262,
+           1.351580968445396,
+           1.2895861113853904,
+           1.2255542757537523,
+           1.1615556108677092,
+           1.0997021257276738,
+           1.0420979057114532,
+           0.9907887571735894,
+           0.9477125037437008,
+           0.9146511509121567,
+           0.8931860982764586,
+           0.8846575124192116,
+           0.8901288793452294,
+           0.9103576359535106,
+           0.9457726380241196,
+           0.9964590610873083,
+           1.062151154217178,
+           1.1422330795418185,
+           1.2357478766499517,
+           1.3414143958287545,
+           1.4576518519644748,
+           1.5826114666832576,
+           1.714214494423361,
+           1.8501957728350058,
+           1.9881518030194003,
+           2.1255922539692027,
+           2.2599937009022764,
+           2.38885435108872,
+           2.509748484656453,
+           2.6203793423889583,
+           2.7186292276165847
+          ],
+          [
+           2.7794843710934973,
+           2.853878018024044,
+           2.9114661202915983,
+           2.951128153656772,
+           2.9720873801782397,
+           2.973926972376252,
+           2.9565980107416183,
+           2.9204191828372092,
+           2.866068209278921,
+           2.79456521809754,
+           2.7072484796015934,
+           2.6057430942537736,
+           2.4919233918632337,
+           2.367869947567909,
+           2.2358222450797047,
+           2.0981281174829127,
+           1.9571911681251564,
+           1.815417417112286,
+           1.6751624316261622,
+           1.5386801804834493,
+           1.4080748055503272,
+           1.2852564260641606,
+           1.171901988535422,
+           1.0694220473138683,
+           0.9789342122956798,
+           0.9012438343273886,
+           0.8368323197518899,
+           0.7858532776820066,
+           0.7481365116250501,
+           0.723199675755791,
+           0.7102672301577093,
+           0.7082961532928841,
+           0.7160077081337892,
+           0.7319244147476391,
+           0.7544112601586851,
+           0.7817200789733866,
+           0.8120359678675588,
+           0.8435245552588292,
+           0.8743789352627078,
+           0.9028650925602898,
+           0.9273646915531024,
+           0.9464141778825381,
+           0.9587392410905601,
+           0.9632838112935236,
+           0.9592329070523097,
+           0.946028812471213,
+           0.923380234861115,
+           0.8912642756713569,
+           0.8499212322480276,
+           0.7998424316532751,
+           0.7417514756574896,
+           0.6765794436234018,
+           0.6054347531322618,
+           0.5295685130208854,
+           0.4503363166328015,
+           0.36915751171464534,
+           0.287473045306916,
+           0.2067030156570791,
+           0.1282050678051889,
+           0.05323474497234763,
+           -0.017091145131415755,
+           -0.08182717010533555,
+           -0.14022704500989983,
+           -0.19176579074320912,
+           -0.2361556792922646,
+           -0.27335552872069263,
+           -0.3035730842810326,
+           -0.32726040248050614,
+           -0.34510233770703336,
+           -0.35799841149892425,
+           -0.36703851813415717,
+           -0.37347308251069467,
+           -0.3786784331557694,
+           -0.3841182808923167,
+           -0.39130229893576246,
+           -0.40174288028687166,
+           -0.4169112011475318,
+           -0.4381937433199073,
+           -0.4668504234760193,
+           -0.5039754428606685,
+           -0.5504619082062405,
+           -0.6069711848996207,
+           -0.673907828934074,
+           -0.7514008077127282,
+           -0.8392915647105894,
+           -0.9371293131870626,
+           -1.0441737637855308,
+           -1.1594053044483008,
+           -1.2815424632628856,
+           -1.4090663003324406,
+           -1.5402511981523277,
+           -1.6732013557107366,
+           -1.8058921437531879,
+           -1.9362153510945788,
+           -2.0620272477721757,
+           -2.181198312874526,
+           -2.2916634250795167,
+           -2.3914712936195213,
+           -2.4788319171641957,
+           -2.5521608978304244,
+           -2.610119506309016,
+           -2.651649490334846,
+           -2.676001740133179,
+           -2.682758068136412,
+           -2.6718455227131064,
+           -2.6435428329454025,
+           -2.598478769318824,
+           -2.5376223989698037,
+           -2.462265409135808,
+           -2.3739968638983475,
+           -2.274670942507009,
+           -2.166368378026379,
+           -2.051352468566369,
+           -1.9320206661606618,
+           -1.8108528571715121,
+           -1.6903575302307094,
+           -1.5730170811377173,
+           -1.4612335274886117,
+           -1.3572758985037408,
+           -1.263230527706041,
+           -1.1809554086739813,
+           -1.112039678675062,
+           -1.0577691738864836,
+           -1.0190988560672352,
+           -0.9966327474548827,
+           -0.9906118322874505,
+           -1.00091019403537,
+           -1.0270394617774121,
+           -1.0681614419277106,
+           -1.123108617515046,
+           -1.1904120111453385,
+           -1.26833573416124,
+           -1.3549173875573453,
+           -1.448013343713255,
+           -1.5453478252604793,
+           -1.6445646111099532,
+           -1.7432801418877013,
+           -1.8391367691101335,
+           -1.9298548949943648,
+           -2.0132827827115327,
+           -2.087442879275682,
+           -2.1505735835181077,
+           -2.2011655074453875,
+           -2.2379914178113047,
+           -2.2601292024896855,
+           -2.2669773792890395,
+           -2.25826284890676,
+           -2.2340407842214085,
+           -2.1946867403599146,
+           -2.1408812592118225,
+           -2.0735874236397476,
+           -1.9940219860982715,
+           -1.9036208495765041,
+           -1.8039998119884875,
+           -1.6969115951204672,
+           -1.5842002633580865,
+           -1.4677541936608403,
+           -1.34945878532409,
+           -1.231150095396135,
+           -1.1145705533667454,
+           -1.001327847817048,
+           -0.8928579897344694,
+           -0.7903934444365154,
+           -0.694937089413782,
+           -0.6072426023353291,
+           -0.5278017158517796,
+           -0.4568385979325987,
+           -0.39431143278308917,
+           -0.3399210925387882,
+           -0.2931266085872075,
+           -0.25316697808021127,
+           -0.21908868032631407,
+           -0.18977813332506557,
+           -0.16399819634036888,
+           -0.14042772321310454,
+           -0.11770309560626149,
+           -0.09446061743019331,
+           -0.06937863248856307,
+           -0.0412182373698284,
+           -0.008861500502459272,
+           0.028653834915524572,
+           0.07210409342305346,
+           0.12205466775439312,
+           0.17884095212614892,
+           0.24255572824179705,
+           0.31304335549907586,
+           0.389900939338134,
+           0.4724864694804014,
+           0.5599337376019529,
+           0.6511736663858686,
+           0.7449615134175583,
+           0.8399092583114778,
+           0.9345223437389527,
+           1.027239824184004,
+           1.116476883285126,
+           1.2006686139261527,
+           1.27831391656185,
+           1.3480183616450736,
+           1.4085348817744943,
+           1.4588012078807917,
+           1.4979730402626574,
+           1.525452047720871,
+           1.5409079139137567,
+           1.5442937962729748,
+           1.5358547257621613,
+           1.516128651393021,
+           1.485940017369517,
+           1.4463859484282828,
+           1.3988153056966321,
+           1.3448010565258925,
+           1.2861065727342524,
+           1.2246466282094337,
+           1.162444004927578,
+           1.1015827326397647,
+           1.044159078797126,
+           0.992231469376874,
+           0.9477705564521909,
+           0.9126106536498183,
+           0.8884037358295913,
+           0.8765771449152724,
+           0.8782960610536477,
+           0.8944316891315669,
+           0.9255359777467932,
+           0.9718235342095705,
+           1.03316122876352,
+           1.109065798095827,
+           1.1987095668179442,
+           1.3009342106114492,
+           1.4142722909177756,
+           1.5369761031525195,
+           1.6670532030548724,
+           1.8023078132966428,
+           1.940387168872027,
+           2.078831738606334,
+           2.2151281643535046,
+           2.3467636914694534,
+           2.4712808256457555,
+           2.586330943137281,
+           2.6897256040446114,
+           2.7794843710934978
+          ],
+          [
+           2.833744724070259,
+           2.897920340523585,
+           2.9445149759269227,
+           2.9726217683140232,
+           2.981688731202419,
+           2.9715299840398037,
+           2.9423287261690847,
+           2.8946318994385267,
+           2.8293366817663608,
+           2.747669147509871,
+           2.651155615684333,
+           2.5415873794314825,
+           2.4209796654725646,
+           2.291525806839753,
+           2.155547722717059,
+           2.0154438830847425,
+           1.873635991053736,
+           1.7325156410085523,
+           1.5943922053946498,
+           1.461443167385453,
+           1.3356680516851713,
+           1.21884701302647,
+           1.1125050238453629,
+           1.0178824621180496,
+           0.9359127409302632,
+           0.8672074469826404,
+           0.8120492702397556,
+           0.7703928158829179,
+           0.7418731973445812,
+           0.7258221202250452,
+           0.7212909859654653,
+           0.7270803757111707,
+           0.7417751229634235,
+           0.7637840520831366,
+           0.7913833516626596,
+           0.8227624698179467,
+           0.8560713645166772,
+           0.8894679173914147,
+           0.9211643246038024,
+           0.949471312997574,
+           0.9728390930414413,
+           0.9898940502442934,
+           0.9994702914844287,
+           1.000635299083108,
+           0.9927090999888591,
+           0.97527652619436,
+           0.9481923212068629,
+           0.9115790315197357,
+           0.8658178069432475,
+           0.8115324146921672,
+           0.7495669447460472,
+           0.6809578438636108,
+           0.6069010587404274,
+           0.5287151915704454,
+           0.4478016706437254,
+           0.3656030121136261,
+           0.28356029487838375,
+           0.20307098752457917,
+           0.12544825407913324,
+           0.051882824253419446,
+           -0.016591554994670108,
+           -0.07912816464032556,
+           -0.13509205206411745,
+           -0.1840787984494695,
+           -0.22592680687516922,
+           -0.26072277210219114,
+           -0.2888001710814861,
+           -0.31073079551783883,
+           -0.3273095297882554,
+           -0.33953275451184917,
+           -0.3485709236044813,
+           -0.355736016463309,
+           -0.36244470309375254,
+           -0.3701781750347201,
+           -0.3804396859056988,
+           -0.3947109099424778,
+           -0.4144082633193336,
+           -0.4408403403917181,
+           -0.47516759498169053,
+           -0.518365345952449,
+           -0.5711911077876307,
+           -0.6341571426111732,
+           -0.7075090026091235,
+           -0.7912106842871013,
+           -0.8849368520654793,
+           -0.9880724124465962,
+           -1.09971953576909,
+           -1.2187120349864782,
+           -1.3436368246573305,
+           -1.4728620030765307,
+           -1.6045709307361429,
+           -1.7368015233532426,
+           -1.867489841454929,
+           -1.9945169444252269,
+           -2.1157578879092935,
+           -2.229131681834678,
+           -2.332650993671032,
+           -2.4244703788156543,
+           -2.502931847330568,
+           -2.5666066330905535,
+           -2.6143321164220894,
+           -2.6452429625119476,
+           -2.65879567258086,
+           -2.654785899805667,
+           -2.633358053478863,
+           -2.5950068987489305,
+           -2.5405710510073316,
+           -2.471218458895702,
+           -2.3884241632300713,
+           -2.2939408061393176,
+           -2.189762540802389,
+           -2.078083153013815,
+           -1.9612493474492865,
+           -1.841710270448577,
+           -1.721964434440366,
+           -1.604505274487406,
+           -1.4917666031987231,
+           -1.3860692355299866,
+           -1.2895700296123014,
+           -1.2042145343030473,
+           -1.1316943499661833,
+           -1.0734101980948048,
+           -1.0304415604709019,
+           -1.0035235928907351,
+           -0.9930318458515667,
+           -0.9989751391945818,
+           -1.0209967440396912,
+           -1.0583838281415734,
+           -1.1100849248390667,
+           -1.1747349958253253,
+           -1.2506874786476343,
+           -1.3360525455035561,
+           -1.4287406545142232,
+           -1.5265103517381335,
+           -1.6270191846977005,
+           -1.7278765184576272,
+           -1.8266970049670597,
+           -1.9211534463811173,
+           -2.0090278135913056,
+           -2.0882592316483253,
+           -2.1569878228507187,
+           -2.2135934039932756,
+           -2.2567281639627943,
+           -2.285342598294493,
+           -2.298704144714175,
+           -2.2964081439323345,
+           -2.278380938562572,
+           -2.2448751153459963,
+           -2.1964570871331444,
+           -2.1339873965977696,
+           -2.0585942988779946,
+           -1.971641340969619,
+           -1.8746897978144834,
+           -1.7694569451815185,
+           -1.6577712447293511,
+           -1.541525584790393,
+           -1.4226297598286655,
+           -1.3029633813169805,
+           -1.1843303928103384,
+           -1.0684163128598785,
+           -0.9567492524377833,
+           -0.8506656507417072,
+           -0.7512815472699834,
+           -0.6594700621315943,
+           -0.5758455943945507,
+           -0.5007550739972922,
+           -0.43427642076003553,
+           -0.37622417893102994,
+           -0.3261621121498653,
+           -0.2834223663238055,
+           -0.24713064114802008,
+           -0.21623665903796846,
+           -0.18954908688587516,
+           -0.16577395463432218,
+           -0.14355552795455245,
+           -0.12151853247644498,
+           -0.09831059551510628,
+           -0.07264376883502138,
+           -0.04333402271322834,
+           -0.009337656701478304,
+           0.030216345377902857,
+           0.07599888163781303,
+           0.1284589557714325,
+           0.18780814629383924,
+           0.25401174633558027,
+           0.32678682476191895,
+           0.4056072786495395,
+           0.48971576443601,
+           0.5781422150040141,
+           0.6697284771450721,
+           0.7631584426596283,
+           0.8569929008963586,
+           0.9497082145245797,
+           1.0397378169953546,
+           1.12551545213832,
+           1.2055190256866872,
+           1.2783139165618502,
+           1.342594603101723,
+           1.3972234959673453,
+           1.441265934361578,
+           1.4740203938794,
+           1.4950430705445368,
+           1.5041661435150508,
+           1.5015091751551692,
+           1.4874832778015672,
+           1.4627878573600106,
+           1.4283999303501054,
+           1.3855561985174207,
+           1.3357282489636333,
+           1.2805914232977609,
+           1.2219880621723838,
+           1.1618859776313601,
+           1.1023331312626068,
+           1.045409598024984,
+           0.9931779711875954,
+           0.9476334111164363,
+           0.9106545583977796,
+           0.8839565194605941,
+           0.8690470906565291,
+           0.8671873156214798,
+           0.8793573723405775,
+           0.9062286630106643,
+           0.9481428345031685,
+           1.0050982934869332,
+           1.076744602048215,
+           1.1623849512820799,
+           1.2609867164215514,
+           1.3711999023592842,
+           1.4913830976698093,
+           1.6196363731371535,
+           1.7538403918071455,
+           1.8917008458724962,
+           2.0307972050020364,
+           2.1686346542695323,
+           2.302698020260312,
+           2.4305064332138917,
+           2.549667452473389,
+           2.6579293925934864,
+           2.753230627993466,
+           2.833744724070259
+          ],
+          [
+           2.8809512194075952,
+           2.934360003636522,
+           2.9695494235400997,
+           2.985833964007534,
+           2.9828910802608624,
+           2.9607674395555876,
+           2.9198768464211904,
+           2.8609899139115753,
+           2.7852157389932564,
+           2.693976029428481,
+           2.588972307715663,
+           2.472146980507485,
+           2.3456392054937623,
+           2.211736608543504,
+           2.0728239990412485,
+           1.9313302985515273,
+           1.789674935614538,
+           1.6502149667542578,
+           1.5151941605525692,
+           1.3866952285433085,
+           1.2665963050751337,
+           1.1565326702459107,
+           1.0578645782348737,
+           0.9716519011412856,
+           0.8986361295661621,
+           0.8392300898355869,
+           0.7935155484480757,
+           0.761248681709537,
+           0.741873197344581,
+           0.7345407098434087,
+           0.7381377969584894,
+           0.751319005369779,
+           0.7725449329771995,
+           0.8001243969653259,
+           0.8322596035697998,
+           0.8670931695813294,
+           0.9027558085917744,
+           0.9374134876383563,
+           0.9693128823175489,
+           0.9968240099607502,
+           1.0184789997076347,
+           1.0330060632110019,
+           1.039357857555249,
+           1.0367335794987598,
+           1.0245942936039447,
+           1.0026711720524493,
+           0.9709665065264261,
+           0.9297475378632363,
+           0.8795333325943723,
+           0.8210751123497059,
+           0.7553306080070719,
+           0.683433161238608,
+           0.606656427978891,
+           0.5263756480253701,
+           0.4440265297499736,
+           0.36106285665281523,
+           0.2789139518067428,
+           0.19894313642387673,
+           0.12240828985459791,
+           0.05042556107062061,
+           -0.01606280243542112,
+           -0.07631565122751258,
+           -0.12981442963264653,
+           -0.17627839359115072,
+           -0.2156731378398296,
+           -0.24821219443291817,
+           -0.2743516456277831,
+           -0.29477787679601336,
+           -0.3103887746299123,
+           -0.32226884793726984,
+           -0.33165890837994905,
+           -0.33992109253878783,
+           -0.3485001310034373,
+           -0.35888187160897617,
+           -0.3725501398618768,
+           -0.3909430680457779,
+           -0.4154100441901769,
+           -0.4471704224619804,
+           -0.4872750977758633,
+           -0.5365719804221779,
+           -0.5956763128985689,
+           -0.6649466531922835,
+           -0.7444672093971824,
+           -0.8340370532085171,
+           -0.9331665684218156,
+           -1.0410813093331237,
+           -1.156733257413255,
+           -1.2788192774680358,
+           -1.4058063913852736,
+           -1.5359633131012844,
+           -1.6673975269853214,
+           -1.7980970475123539,
+           -1.9259758745317528,
+           -2.0489220587893158,
+           -2.1648472191851296,
+           -2.271736308458183,
+           -2.3676964087897945,
+           -2.4510033536885167,
+           -2.520145017191563,
+           -2.573860184885847,
+           -2.6111720217930583,
+           -2.631415277383115,
+           -2.6342565148677637,
+           -2.6197068169293614,
+           -2.5881265991522295,
+           -2.5402223512831985,
+           -2.4770353204429565,
+           -2.3999223447949087,
+           -2.3105292361894363,
+           -2.2107572912751032,
+           -2.102723678054884,
+           -1.9887165947413818,
+           -1.871146226332211,
+           -1.7524926284072526,
+           -1.6352517446613168,
+           -1.5218808127085535,
+           -1.4147444305183166,
+           -1.3160625429930517,
+           -1.2278615649582625,
+           -1.1519297842256946,
+           -1.0897780881592696,
+           -1.042606931740025,
+           -1.0112803175313683,
+           -0.996307391772505,
+           -0.9978320801138433,
+           -1.0156309956479694,
+           -1.0491196555252982,
+           -1.097366845350385,
+           -1.159116777525103,
+           -1.2328185054284275,
+           -1.3166618842728355,
+           -1.4086192158005284,
+           -1.5064915813960527,
+           -1.607958759893646,
+           -1.7106315449459608,
+           -1.8121052242342526,
+           -1.910012960265691,
+           -2.002077820511888,
+           -2.086162242932819,
+           -2.160313790498889,
+           -2.2228061434501747,
+           -2.272174398320834,
+           -2.3072438851988033,
+           -2.327151875737111,
+           -2.33136173008416,
+           -2.3196692168032245,
+           -2.2922009314114993,
+           -2.2494049316597637,
+           -2.192033896356887,
+           -2.1211212947842073,
+           -2.0379512211275435,
+           -1.9440226987911775,
+           -1.8410093892890018,
+           -1.730715746491895,
+           -1.6150307368019456,
+           -1.4958802974355032,
+           -1.3751797272440613,
+           -1.254787196932835,
+           -1.1364595284411794,
+           -1.0218113276506806,
+           -0.9122784622166242,
+           -0.8090867595709126,
+           -0.7132266620154648,
+           -0.6254344198387676,
+           -0.5461802335066223,
+           -0.47566357650245755,
+           -0.41381574585570347,
+           -0.3603095024498051,
+           -0.31457548249664263,
+           -0.2758248896402001,
+           -0.24307781831981448,
+           -0.2151964172576522,
+           -0.19092198077790157,
+           -0.16891495813525972,
+           -0.14779679954950062,
+           -0.1261925139750801,
+           -0.10277279884281897,
+           -0.07629461643007929,
+           -0.0456391347465624,
+           -0.009846021739980807,
+           0.03185682159189088,
+           0.08002888342104275,
+           0.13499867237122992,
+           0.19685185432378743,
+           0.26542622117367665,
+           0.3403136394760886,
+           0.4208689445165861,
+           0.5062255636386824,
+           0.5953174762856186,
+           0.6869069516399653,
+           0.7796173522132122,
+           0.871970157135617,
+           0.9624252456634554,
+           1.0494233924613414,
+           1.1314298638290823,
+           1.206977969856766,
+           1.2747114224330418,
+           1.3334243732935198,
+           1.3820980593356558,
+           1.4199330629770868,
+           1.4463763014366082,
+           1.4611419878671035,
+           1.4642259560835766,
+           1.4559129055214026,
+           1.43677629993466,
+           1.407670837797964,
+           1.3697175998051325,
+           1.3242821645772542,
+           1.2729461630469363,
+           1.2174729104687314,
+           1.1597679083731007,
+           1.1018351431545785,
+           1.045730219950525,
+           0.9935114571608412,
+           0.9471901261386733,
+           0.9086810506838754,
+           0.8797547811490769,
+           0.8619925281174128,
+           0.8567449813701159,
+           0.8650960525998523,
+           0.8878324671062653,
+           0.9254199932453132,
+           0.9779869419847588,
+           1.0453153963357216,
+           1.1268404458817036,
+           1.2216575096127884,
+           1.3285376354862621,
+           1.445950472345682,
+           1.5720944237666954,
+           1.7049333186301079,
+           1.8422387740515815,
+           1.9816372866445213,
+           2.120660971408368,
+           2.2568007767062013,
+           2.387560941082841,
+           2.5105134246464114,
+           2.6233510452383046,
+           2.7239380777440014,
+           2.8103571329965633,
+           2.8809512194075957
+          ],
+          [
+           2.9207044687937698,
+           2.962888711323785,
+           2.9863576603761066,
+           2.9906529595831515,
+           2.975684254936466,
+           2.941730394920047,
+           2.8894323245601963,
+           2.819777852677085,
+           2.7340786641004207,
+           2.633940131928748,
+           2.5212246546192656,
+           2.398009394678813,
+           2.2665394263101897,
+           2.1291774054017747,
+           1.9883509541874838,
+           1.8464990028702495,
+           1.7060183503293849,
+           1.5692116952950694,
+           1.4382383483968029,
+           1.315068765343448,
+           1.2014439439518532,
+           1.0988406052599646,
+           1.0084429345989028,
+           0.9311214958490075,
+           0.8674197552033756,
+           0.8175484639875903,
+           0.7813879580498114,
+           0.7584982386747376,
+           0.7481365116250497,
+           0.7492816813975035,
+           0.7606651314925115,
+           0.780806972493692,
+           0.808056811658903,
+           0.8406379936323101,
+           0.8766941842922588,
+           0.9143371204836691,
+           0.9516943285710262,
+           0.9869556247797495,
+           1.0184172498182211,
+           1.04452255820617,
+           1.0638982772889929,
+           1.0753854696445564,
+           1.0780644724447317,
+           1.071273244753507,
+           1.0546187247313696,
+           1.0279809789453043,
+           0.9915101109065658,
+           0.9456160809168495,
+           0.8909517696480477,
+           0.8283897890855885,
+           0.7589937022412878,
+           0.6839844534433072,
+           0.6047029305345916,
+           0.5225696759827059,
+           0.43904283335177763,
+           0.35557545710185473,
+           0.27357332625687336,
+           0.1943543858431577,
+           0.11911089460452197,
+           0.048875284529896715,
+           -0.015509360939583277,
+           -0.07341342500304572,
+           -0.12443882878940839,
+           -0.16843057112307713,
+           -0.2054814228661229,
+           -0.23592964086105686,
+           -0.26034974898329427,
+           -0.27953661522619455,
+           -0.29448322947737254,
+           -0.30635275223681196,
+           -0.31644555576213407,
+           -0.3261621121498654,
+           -0.3369626942746986,
+           -0.3503249424537023,
+           -0.3677004099338872,
+           -0.39047123224418584,
+           -0.419908068240583,
+           -0.4571304341719853,
+           -0.5030704969061925,
+           -0.5584413099036452,
+           -0.6237103676241349,
+           -0.6990792234510229,
+           -0.7844697661450482,
+           -0.8795175840167474,
+           -0.9835726685550278,
+           -1.0957075245921917,
+           -1.2147325668339128,
+           -1.3392184974227492,
+           -1.4675251807801466,
+           -1.597836364770231,
+           -1.7281994454662364,
+           -1.8565693403171437,
+           -1.9808554246785974,
+           -2.098970402300731,
+           -2.2088799236439214,
+           -2.3086517383249947,
+           -2.396503170365673,
+           -2.470845737264376,
+           -2.53032579554111,
+           -2.5738601848858473,
+           -2.6006659582524443,
+           -2.610283423421637,
+           -2.6025918793722385,
+           -2.5778176044220964,
+           -2.536533838304276,
+           -2.479652692610051,
+           -2.4084091186565186,
+           -2.324337254054568,
+           -2.2292396543445236,
+           -2.125150089482425,
+           -2.014290742428872,
+           -1.8990247847308932,
+           -1.7818054183919096,
+           -1.6651225616598015,
+           -1.551448416427825,
+           -1.4431831852287964,
+           -1.342602205530296,
+           -1.2518057381750598,
+           -1.1726725860759957,
+           -1.10681863011875,
+           -1.055561253795451,
+           -1.019890489182722,
+           -1.0004475578537135,
+           -0.9975113050393726,
+           -1.0109928380877224,
+           -1.0404384855651578,
+           -1.0850409959352598,
+           -1.1436586994382443,
+           -1.214842168324934,
+           -1.296867733550023,
+           -1.3877770546956008,
+           -1.4854217981846523,
+           -1.5875123601787262,
+           -1.6916694777909724,
+           -1.7954775076025449,
+           -1.8965381154750436,
+           -1.9925231171008695,
+           -2.0812252346786018,
+           -2.160605590842949,
+           -2.228836845090298,
+           -2.284340988298648,
+           -2.325820944780576,
+           -2.352285285293134,
+           -2.363065524733079,
+           -2.357825660649683,
+           -2.336563798699465,
+           -2.299605904060424,
+           -2.247591908866931,
+           -2.1814545902266262,
+           -2.102391806814456,
+           -2.011832840167261,
+           -1.9113997257733555,
+           -1.8028645754967398,
+           -1.6881039839911187,
+           -1.5690516753756127,
+           -1.4476505810791669,
+           -1.3258055446540784,
+           -1.2053378244915154,
+           -1.0879425114630341,
+           -0.9751498970030126,
+           -0.8682917201620991,
+           -0.7684730924560486,
+           -0.6765507502222446,
+           -0.5931181194704027,
+           -0.5184975020483844,
+           -0.4527395087901138,
+           -0.3956296797878517,
+           -0.3467020487039188,
+           -0.30525923170899477,
+           -0.27039845662703194,
+           -0.24104279831064435,
+           -0.21597675590154178,
+           -0.1938851996975769,
+           -0.17339463253224352,
+           -0.15311565492105855,
+           -0.13168549610368818,
+           -0.10780947515400888,
+           -0.08030028745105562,
+           -0.0481140711789535,
+           -0.010382294619703242,
+           0.03356138438639434,
+           0.08416000313405989,
+           0.1416184885920964,
+           0.20589556235373568,
+           0.2767025811338486,
+           0.3535093566681494,
+           0.43555681634005616,
+           0.5218761867163947,
+           0.6113142109644293,
+           0.7025637522029734,
+           0.7941989922557452,
+           0.8847143126641828,
+           0.9725658453176226,
+           1.0562146062307494,
+           1.1341700797582068,
+           1.2050331031085302,
+           1.2675369129059018,
+           1.3205852565142178,
+           1.3632865399176681,
+           1.3949830794724656,
+           1.415274644465442,
+           1.424035618188437,
+           1.421425263678146,
+           1.4078907524453237,
+           1.3841627961393632,
+           1.3512439076331122,
+           1.3103895048050656,
+           1.263082252661734,
+           1.2110002128026147,
+           1.1559795292187909,
+           1.099972521992486,
+           1.0450021820120745,
+           0.993114157234142,
+           0.9463273918032236,
+           0.9065846216292104,
+           0.8757039426745943,
+           0.8553326508039149,
+           0.846904504925857,
+           0.851601489381683,
+           0.8703210488818606,
+           0.9036496422139687,
+           0.9518433124975524,
+           1.014815805537657,
+           1.0921345878673876,
+           1.1830249267565263,
+           1.2863820004233366,
+           1.400790812669649,
+           1.5245534969235386,
+           1.655723414867362,
+           1.7921452888752045,
+           1.9315004594736684,
+           2.0713562326270827,
+           2.2092181799634036,
+           2.3425841806249026,
+           2.468998948110024,
+           2.586107770415917,
+           2.6917082074035052,
+           2.783798535243182,
+           2.8606218029715405,
+           2.92070446879377
+          ],
+          [
+           2.9526681417504257,
+           2.9832650978089528,
+           2.994797481145495,
+           2.9870379841576846,
+           2.9601292282325993,
+           2.9145799121451597,
+           2.851252735017348,
+           2.7713443884217686,
+           2.676358099881236,
+           2.5680693858700736,
+           2.4484858321965004,
+           2.3198018594692167,
+           2.184349547846798,
+           2.044546685631609,
+           1.9028432683397158,
+           1.7616677071889715,
+           1.6233740077648249,
+           1.4901911509619297,
+           1.3641758499210919,
+           1.2471697700758873,
+           1.1407621867722124,
+           1.0462589190443705,
+           0.9646582224061591,
+           0.8966341518102054,
+           0.8425277224945832,
+           0.8023460058043725,
+           0.7757691039475297,
+           0.7621647567711847,
+           0.7606101497129925,
+           0.769920319597617,
+           0.7886823981236386,
+           0.8152947955375842,
+           0.8480103124455783,
+           0.8849820787236752,
+           0.9243111571702476,
+           0.9640946173222004,
+           1.002472882430475,
+           1.0376751799173052,
+           1.0680619819367838,
+           1.0921634064318375,
+           1.1087126581447206,
+           1.1166737205896293,
+           1.1152626606759692,
+           1.103962073649917,
+           1.0825283730975863,
+           1.0509918144537929,
+           1.0096493261581392,
+           0.9590504056257442,
+           0.8999765129598977,
+           0.8334145594247007,
+           0.7605252360139046,
+           0.6826070562961938,
+           0.6010570938798758,
+           0.5173294756881558,
+           0.4328927457758148,
+           0.3491872393440221,
+           0.26758360233758804,
+           0.1893435586887683,
+           0.11558396578480946,
+           0.04724511067229044,
+           -0.014935912872646487,
+           -0.0704460401140563,
+           -0.11901072955002397,
+           -0.1606017271745088,
+           -0.19543788847453025,
+           -0.22397902734774391,
+           -0.2469129435295625,
+           -0.2651359587780126,
+           -0.27972746243996793,
+           -0.2919191247822171,
+           -0.30305957759830365,
+           -0.3145754824966419,
+           -0.3279300048430111,
+           -0.34457978306160664,
+           -0.36593152703144893,
+           -0.3932993944820912,
+           -0.4278642801517066,
+           -0.47063610931570937,
+           -0.5224201561485365,
+           -0.5837883099734532,
+           -0.6550560911757959,
+           -0.7362660763978385,
+           -0.8271782331212709,
+           -0.9272674908409798,
+           -1.0357286940489687,
+           -1.151488895724064,
+           -1.2732267636283776,
+           -1.3993986901188429,
+           -1.5282710239555986,
+           -1.6579576840683758,
+           -1.7864622744353564,
+           -1.9117236997114693,
+           -2.0316641860679403,
+           -2.1442385433262316,
+           -2.2474834646809203,
+           -2.339565650194016,
+           -2.418827560160527,
+           -2.4838296539993996,
+           -2.5333880483875144,
+           -2.5666066330905544,
+           -2.582902811851848,
+           -2.5820261856743,
+           -2.564069663238987,
+           -2.529472663976767,
+           -2.4790162690377664,
+           -2.4138103694499446,
+           -2.3352730543688422,
+           -2.245102670744987,
+           -2.1452431643416965,
+           -2.03784347642615,
+           -1.9252119165761092,
+           -1.809766556281045,
+           -1.6939827872907345,
+           -1.5803392605063131,
+           -1.4712634638181852,
+           -1.369078209587696,
+           -1.2759502841027892,
+           -1.1938424627213067,
+           -1.1244700167001433,
+           -1.069262732758989,
+           -1.0293333367767403,
+           -1.0054530618062374,
+           -0.9980349314866899,
+           -1.007125147040324,
+           -1.0324027738054344,
+           -1.0731877263559315,
+           -1.1284568544751166,
+           -1.1968677403722643,
+           -1.2767896352163677,
+           -1.3663407947375967,
+           -1.4634313233941723,
+           -1.5658105080553923,
+           -1.6711175184114222,
+           -1.7769342748771693,
+           -1.8808392374301426,
+           -1.9804608517137856,
+           -2.073529402209498,
+           -2.1579260659427955,
+           -2.231728032912377,
+           -2.2932486593736714,
+           -2.3410717447638874,
+           -2.3740791693141143,
+           -2.3914712936195217,
+           -2.3927796995607804,
+           -2.377872039583096,
+           -2.3469489538133295,
+           -2.3005332070899467,
+           -2.2394513859607286,
+           -2.164808674459414,
+           -2.07795739263193,
+           -1.9804601293187731,
+           -1.874048427029947,
+           -1.7605780788231051,
+           -1.6419821724719883,
+           -1.5202230641157815,
+           -1.3972444809459545,
+           -1.2749249399855,
+           -1.1550336280599716,
+           -1.0391898177937386,
+           -0.9288267977346915,
+           -0.8251611740162165,
+           -0.7291682593988008,
+           -0.641564106700133,
+           -0.562794571550909,
+           -0.4930316084545527,
+           -0.4321768188463666,
+           -0.3798720849047033,
+           -0.3355169429095046,
+           -0.29829217948423703,
+           -0.2671889773630813,
+           -0.24104279831064424,
+           -0.21857107295160252,
+           -0.1984136734719686,
+           -0.17917507775279948,
+           -0.1594670941459733,
+           -0.13795100574785857,
+           -0.11337801188796132,
+           -0.08462689210852618,
+           -0.05073789292826211,
+           -0.010941938229416916,
+           0.0353156123888483,
+           0.08835728963473931,
+           0.14826239779330233,
+           0.21486275652142597,
+           0.2877454231082218,
+           0.3662623345995265,
+           0.4495466280779853,
+           0.5365352223159214,
+           0.6259970794264587,
+           0.7165664152165498,
+           0.8067799955142,
+           0.8951175461594881,
+           0.980044219425333,
+           1.06005400156203,
+           1.1337129164589714,
+           1.1997008798947315,
+           1.256851087577532,
+           1.3041858775015358,
+           1.3409480916799679,
+           1.3666270719981595,
+           1.3809785570575377,
+           1.384037898186843,
+           1.3761261795240425,
+           1.357849005072228,
+           1.3300879004656667,
+           1.2939844642281266,
+           1.2509175878798748,
+           1.2024742417189414,
+           1.1504144890005972,
+           1.0966315413793857,
+           1.0431077990570408,
+           0.9918679267723226,
+           0.9449300988130783,
+           0.9042566004960895,
+           0.8717049986015574,
+           0.8489810883446632,
+           0.8375947896361542,
+           0.8388201013895356,
+           0.853660130960909,
+           0.8828180986346207,
+           0.9266750772049235,
+           0.9852750675298196,
+           1.0583178363109544,
+           1.145159756535648,
+           1.2448226985407151,
+           1.356010825233301,
+           1.4771349533978058,
+           1.6063439589366513,
+           1.7415625318645482,
+           1.880534431140303,
+           2.020870253823362,
+           2.160098620938882,
+           2.2957195966101756,
+           2.4252590996110492,
+           2.546323038951292,
+           2.6566499081503667,
+           2.754160606445105,
+           2.83700431853342,
+           2.9035993760653844,
+           2.9526681417504257
+          ],
+          [
+           2.9765718111406216,
+           2.995316769641939,
+           2.9947974811454956,
+           2.975019622059029,
+           2.936357602713908,
+           2.879545696600934,
+           2.8056610943966396,
+           2.716099290169622,
+           2.6125423884278547,
+           2.4969210875709704,
+           2.371371243799755,
+           2.2381860460158878,
+           2.099764933666736,
+           1.9585604634180986,
+           1.8170243752128865,
+           1.6775541226557562,
+           1.5424411164559506,
+           1.413821883317106,
+           1.2936332673762072,
+           1.1835726989652349,
+           1.0850644286607627,
+           0.9992324764579992,
+           0.9268808801346017,
+           0.868481647561149,
+           0.8241706293002747,
+           0.7937513349613545,
+           0.7767065241894965,
+           0.772217215596663,
+           0.779188578985799,
+           0.7962820122254843,
+           0.8219525580982139,
+           0.8544906919125865,
+           0.8920674106414049,
+           0.9327814812136206,
+           0.9747076610662898,
+           1.015944689158142,
+           1.0546618606269096,
+           1.0891430426636968,
+           1.1178270617750135,
+           1.1393434915040344,
+           1.1525429923340391,
+           1.1565214987600783,
+           1.1506377087441533,
+           1.1345235039036607,
+           1.1080871104481547,
+           1.0715089964969908,
+           1.0252306863120284,
+           0.9699368515237821,
+           0.9065312091177611,
+           0.8361069115362386,
+           0.7599122518561788,
+           0.679312623200412,
+           0.5957497634426027,
+           0.5106993816074299,
+           0.4256282995459244,
+           0.3419522505922507,
+           0.26099545582362504,
+           0.18395304882585972,
+           0.11185734280922864,
+           0.04554883150629919,
+           -0.014347309864745285,
+           -0.06743860197946232,
+           -0.11357605609030169,
+           -0.1528580973078434,
+           -0.1856275075107557,
+           -0.21246146149101633,
+           -0.2341549107209501,
+           -0.2516977435213904,
+           -0.26624631398389575,
+           -0.2790900805930435,
+           -0.29161422532094816,
+           -0.3052592317089945,
+           -0.3214784833483056,
+           -0.3416950000808606,
+           -0.36725845670434526,
+           -0.3994036272272036,
+           -0.43921136677055245,
+           -0.4875731837700488,
+           -0.5451603686298818,
+           -0.6123985335413632,
+           -0.6894482845482031,
+           -0.7761925944295572,
+           -0.8722312773694251,
+           -0.9768827878624018,
+           -1.0891933813270889,
+           -1.2079534870876008,
+           -1.3317209604228426,
+           -1.458850703894253,
+           -1.5875299835905567,
+           -1.715818617429243,
+           -1.841693083995373,
+           -1.9630934948572225,
+           -2.077972293587202,
+           -2.184343492908674,
+           -2.280331238870648,
+           -2.3642164983821305,
+           -2.4344807037347884,
+           -2.4898452540827196,
+           -2.5293058676860123,
+           -2.5521608978304258,
+           -2.558032866847735,
+           -2.546882633158995,
+           -2.5190157818479983,
+           -2.475081015665876,
+           -2.4160605160156923,
+           -2.343252437650814,
+           -2.258245891778247,
+           -2.1628889552950312,
+           -2.059250414495223,
+           -1.9495761055594272,
+           -1.8362408476719383,
+           -1.7216970743943318,
+           -1.608421352228005,
+           -1.4988600300394275,
+           -1.395375287815588,
+           -1.3001928474120599,
+           -1.2153525716514189,
+           -1.142663112170812,
+           -1.0836616723795363,
+           -1.0395798320323166,
+           -1.011316237149383,
+           -0.9994167967791868,
+           -1.0040628503410884,
+           -1.025067580321716,
+           -1.0618807495227012,
+           -1.1136016446239956,
+           -1.1789999133357205,
+           -1.2565437955887786,
+           -1.3444350745979456,
+           -1.4406499154565833,
+           -1.5429846210214044,
+           -1.6491052205509364,
+           -1.7565997186237168,
+           -1.8630317723861263,
+           -1.9659945355677786,
+           -2.0631634086264166,
+           -2.1523464657637947,
+           -2.231531390564452,
+           -2.298927841097923,
+           -2.353004280253488,
+           -2.3925184449752357,
+           -2.416540785504793,
+           -2.4244703788156547,
+           -2.416043004855356,
+           -2.391331265447531,
+           -2.3507368190332185,
+           -2.2949749950968292,
+           -2.2250522354485702,
+           -2.1422369810350053,
+           -2.048024778437312,
+           -1.9440985159121749,
+           -1.8322848114499766,
+           -1.7145076621648194,
+           -1.592740523330319,
+           -1.4689580151689143,
+           -1.3450884554520135,
+           -1.2229683861775589,
+           -1.1043002039029226,
+           -0.9906139172825805,
+           -0.8832339442269743,
+           -0.7832517277161707,
+           -0.6915047970724779,
+           -0.6085627342849635,
+           -0.534720327017247,
+           -0.46999800570837913,
+           -0.4141494763328632,
+           -0.3666762775893643,
+           -0.3268488161229011,
+           -0.2937332702368186,
+           -0.26622360549522717,
+           -0.24307781831981426,
+           -0.22295741931164903,
+           -0.2044690891637878,
+           -0.18620738861467961,
+           -0.16679738117434312,
+           -0.1449360338608253,
+           -0.11943129670411544,
+           -0.08923782536927728,
+           -0.053488401275196176,
+           -0.011520217730942028,
+           0.03710466403655475,
+           0.09258523197999148,
+           0.15487418949660164,
+           0.22367757030649807,
+           0.29846131965674894,
+           0.37846467730613215,
+           0.4627200195926086,
+           0.5500786483628015,
+           0.6392418579604443,
+           0.7287964718153227,
+           0.8172539210080413,
+           0.903091841558646,
+           0.984797097557633,
+           1.0609090954333342,
+           1.1300622417397566,
+           1.1910264132366182,
+           1.2427443533656017,
+           1.2843649824227255,
+           1.3152717080029093,
+           1.335104945208641,
+           1.343778199631523,
+           1.3414872266727096,
+           1.3287119543712798,
+           1.3062110392290411,
+           1.2750091110001394,
+           1.2363769483844071,
+           1.1918050083580962,
+           1.1429709029468897,
+           1.0917015742796017,
+           1.0399310577829084,
+           0.9896548408543788,
+           0.9428819172781754,
+           0.9015857036251115,
+           0.8676550211711476,
+           0.8428463544497375,
+           0.8287385751339432,
+           0.8266912679777475,
+           0.8378077152206004,
+           0.8629034890684876,
+           0.9024814711622451,
+           0.9567139664799776,
+           1.0254324105665005,
+           1.1081249874394161,
+           1.2039422854194066,
+           1.3117109241211642,
+           1.4299548926773866,
+           1.5569241516940537,
+           1.6906298740657828,
+           1.828885536985814,
+           1.9693529332852973,
+           2.109592048200171,
+           2.2471136508184135,
+           2.3794333802215144,
+           2.5041260664391927,
+           2.6188790168085787,
+           2.7215430194438452,
+           2.810179866807179,
+           2.8831052826121866,
+           2.9389262425621494,
+           2.9765718111406216
+          ],
+          [
+           2.9922132411047833,
+           2.998941764225594,
+           2.9863576603761066,
+           2.9546995540689083,
+           2.904570497089063,
+           2.8369241536040386,
+           2.7530431286081756,
+           2.6545099564505454,
+           2.543171439536106,
+           2.4210971838300153,
+           2.290533313741616,
+           2.153852461032211,
+           2.0135012078809362,
+           1.871946221110381,
+           1.7316203414763405,
+           1.594869888257586,
+           1.4639044052857801,
+           1.3407500109223551,
+           1.2272074229313563,
+           1.1248156120110904,
+           1.0348218978546457,
+           0.9581591424848361,
+           0.8954305211942902,
+           0.8469021660269384,
+           0.8125037849355533,
+           0.7918371662630007,
+           0.7841922877762769,
+           0.7885705668007206,
+           0.8037146175249877,
+           0.828143727432674,
+           0.8601941308079333,
+           0.898063046599021,
+           0.9398553632595819,
+           0.9836317965276052,
+           1.0274573187527505,
+           1.069448660921341,
+           1.1078197207890101,
+           1.1409237716106195,
+           1.1672914542385269,
+           1.1856636485538175,
+           1.1950184553962548,
+           1.194591673921256,
+           1.1838903277352348,
+           1.1626989719855894,
+           1.1310786982996304,
+           1.089358940430683,
+           1.0381223660106866,
+           0.9781833143524924,
+           0.9105604024261087,
+           0.8364440669030357,
+           0.7571599358914636,
+           0.6741290265506998,
+           0.5888258416398654,
+           0.502735487336602,
+           0.41731095516440997,
+           0.3339317021252497,
+           0.2538646254156627,
+           0.1782284624071058,
+           0.10796255459446905,
+           0.04380079832124235,
+           -0.013748531763672371,
+           -0.06441655488676348,
+           -0.10818078820692817,
+           -0.14526519613578476,
+           -0.17613328023700084,
+           -0.20147438710978,
+           -0.22218358928809373,
+           -0.2393356628382608,
+           -0.25415384072538344,
+           -0.26797415918833833,
+           -0.28220633178941473,
+           -0.2982921794842368,
+           -0.3176627125817741,
+           -0.3416950000808605,
+           -0.3716699725271007,
+           -0.40873228590830224,
+           -0.45385332660971006,
+           -0.5077983622210066,
+           -0.5710987418625763,
+           -0.6440299251697165,
+           -0.7265959742227809,
+           -0.8185209811366754,
+           -0.9192477297484432,
+           -1.0279437072170345,
+           -1.1435143949419684,
+           -1.2646235826893557,
+           -1.3897202698435,
+           -1.5170715478101058,
+           -1.644800702071525,
+           -1.770929635174237,
+           -1.893424596505182,
+           -2.010244114042372,
+           -2.1193879596921104,
+           -2.218945945026895,
+           -2.307145339179677,
+           -2.3823957255590305,
+           -2.4433301684106916,
+           -2.488841642815541,
+           -2.5181137905325457,
+           -2.530645196562532,
+           -2.526266534228616,
+           -2.505150096232636,
+           -2.467811411422954,
+           -2.4151028374466357,
+           -2.348199213396424,
+           -2.2685758492434953,
+           -2.1779793155354383,
+           -2.0783916729395253,
+           -1.9719889423809691,
+           -1.8610947587812299,
+           -1.7481302712191564,
+           -1.6355614467394104,
+           -1.52584500166133,
+           -1.4213742214186667,
+           -1.3244259367287958,
+           -1.237109900036876,
+           -1.161321752244292,
+           -1.0987006869881535,
+           -1.050592810173113,
+           -1.0180210587105418,
+           -1.0016623877290574,
+           -1.0018327636351405,
+           -1.018480315495736,
+           -1.0511868037789476,
+           -1.099177368226018,
+           -1.1613383203333025,
+           -1.2362425553681164,
+           -1.3221819786569318,
+           -1.4172061754426006,
+           -1.5191664069204391,
+           -1.625763890681105,
+           -1.7346012247122853,
+           -1.84323574272069,
+           -1.9492335465293555,
+           -2.05022294966001,
+           -2.143946085158135,
+           -2.228307479740963,
+           -2.3014184741904815,
+           -2.361636474614077,
+           -2.4075981481373847,
+           -2.4382458265690072,
+           -2.4528465488655447,
+           -2.451003353688517,
+           -2.4326586225272466,
+           -2.398089467101807,
+           -2.347895347305342,
+           -2.282978293069651,
+           -2.20451628065948,
+           -2.113930476693576,
+           -2.01284720769135,
+           -1.9030556356506982,
+           -1.786462218119503,
+           -1.6650431020939063,
+           -1.540795643199942,
+           -1.4156902540467933,
+           -1.2916237681738933,
+           -1.1703754591860787,
+           -1.0535667797458739,
+           -0.94262578402873,
+           -0.8387570726515308,
+           -0.7429179541418942,
+           -0.6558013554112662,
+           -0.5778258395206601,
+           -0.5091329066819124,
+           -0.4495915685119206,
+           -0.39881000072473344,
+           -0.35615390034289135,
+           -0.3207710046190952,
+           -0.29162107440190194,
+           -0.2675105085063075,
+           -0.24713064114801975,
+           -0.22909868450663098,
+           -0.21200021521617468,
+           -0.19443206858583664,
+           -0.17504449846091527,
+           -0.15258148394399249,
+           -0.12591811607378403,
+           -0.09409407665145259,
+           -0.05634232567452144,
+           -0.012112240618021216,
+           0.038913403143019,
+           0.09680805986440984,
+           0.1613979249523155,
+           0.2322654263955815,
+           0.3087596094456326,
+           0.3900131474470451,
+           0.47496553803068475,
+           0.5623918813442083,
+           0.6509364897466577,
+           0.7391504501863029,
+           0.8255321545880857,
+           0.9085697327141696,
+           0.9867842682148212,
+           1.0587726533635764,
+           1.123248941960636,
+           1.1790830930473586,
+           1.225336059624914,
+           1.2612902650192104,
+           1.2864746227110961,
+           1.3006833905604747,
+           1.303988304044576,
+           1.2967436015814444,
+           1.279583734019831,
+           1.2534137354732424,
+           1.219392419225096,
+           1.1789087457536898,
+           1.1335518854112319,
+           1.0850756615171588,
+           1.035358206466065,
+           0.9863577901778463,
+           0.9400658835986346,
+           0.8984585973363753,
+           0.8634476848670942,
+           0.8368323197518904,
+           0.8202528463619609,
+           0.8151476638640384,
+           0.8227143345558245,
+           0.8438759116641501,
+           0.8792533607121615,
+           0.9291448054353719,
+           0.9935121674431122,
+           1.0719755923140992,
+           1.163815867886502,
+           1.2679848477249092,
+           1.3831236988421964,
+           1.5075886024849443,
+           1.6394833548357832,
+           1.7766981453291295,
+           1.9169536380937227,
+           2.0578493505912108,
+           2.1969152160765972,
+           2.331665135738145,
+           2.4596512743071486,
+           2.578517830882256,
+           2.6860530252772556,
+           2.7802380792103425,
+           2.85929204019806,
+           2.921711392462453,
+           2.966303521185682,
+           2.9922132411047833
+          ],
+          [
+           2.999460098067586,
+           2.9941094124654115,
+           2.9695494235401,
+           2.9262496971574565,
+           2.86503684465548,
+           2.7870758806946947,
+           2.6938440094524263,
+           2.587097460897299,
+           2.4688321628243313,
+           2.341239179183571,
+           2.2066559674899557,
+           2.0675146048085393,
+           1.9262882006443331,
+           1.78543675439177,
+           1.6473537239012548,
+           1.5143145500325117,
+           1.3884283303690863,
+           1.2715937548835419,
+           1.1654603092885845,
+           1.0713956207569706,
+           0.9904596688994897,
+           0.9233864161161925,
+           0.8705732298533095,
+           0.8320782793861801,
+           0.807625896183052,
+           0.7966196944426709,
+           0.7981630617605802,
+           0.811086453632194,
+           0.8339807639463562,
+           0.8652359006909398,
+           0.9030835752431634,
+           0.9456432177595249,
+           0.990969862596664,
+           1.0371028079880424,
+           1.0821138442561058,
+           1.124153864799853,
+           1.1614967233655946,
+           1.1925792783601321,
+           1.2160366681841863,
+           1.2307319880924357,
+           1.235779685693495,
+           1.2305621551643486,
+           1.2147391854455678,
+           1.1882501006861823,
+           1.1513086174149763,
+           1.1043906276519972,
+           1.0482152958103108,
+           0.9837200253047775,
+           0.9120300040863211,
+           0.8344231730381244,
+           0.7522915739582574,
+           0.6671001219203183,
+           0.5803439079832261,
+           0.49350517102490754,
+           0.40801108112838136,
+           0.3251934514123901,
+           0.24625144116568987,
+           0.17221823202401407,
+           0.10393255281123931,
+           0.04201580026885952,
+           -0.013144644503113041,
+           -0.06140546672185617,
+           -0.10287057230758373,
+           -0.1378872630380759,
+           -0.16703553211218838,
+           -0.191110759825008,
+           -0.21110026202739993,
+           -0.22815430552510832,
+           -0.2435523504601048,
+           -0.258665406293199,
+           -0.27491549204010074,
+           -0.2937332702368184,
+           -0.31651497569075726,
+           -0.34457978306160636,
+           -0.3791287510796212,
+           -0.4212064458516788,
+           -0.47166628206337763,
+           -0.5311405305068896,
+           -0.6000158254718194,
+           -0.6784148689719697,
+           -0.7661848739353614,
+           -0.8628931192138368,
+           -0.9678298097960041,
+           -1.0800182504218079,
+           -1.1982321545378862,
+           -1.3210197278770188,
+           -1.4467339914876651,
+           -1.5735686471816317,
+           -1.6995986432048584,
+           -1.8228244731552063,
+           -1.941219139960173,
+           -2.0527766416927142,
+           -2.1555607891066164,
+           -2.2477531472781855,
+           -2.32769890618587,
+           -2.393949527236606,
+           -2.4453010837126503,
+           -2.480827311203324,
+           -2.4999065069643063,
+           -2.5022415618555653,
+           -2.4878725715428835,
+           -2.4571816510418145,
+           -2.4108897641078926,
+           -2.350045571847215,
+           -2.2760064985077095,
+           -2.19041240195747,
+           -2.0951524171964704,
+           -1.992325708922667,
+           -1.8841970195392863,
+           -1.7731480283235674,
+           -1.6616256425650444,
+           -1.5520884197030578,
+           -1.4469523688827413,
+           -1.3485373996476904,
+           -1.259015674172961,
+           -1.1803630777422975,
+           -1.1143149510628256,
+           -1.0623271291836012,
+           -1.025543207618971,
+           -1.004768809771426,
+           -1.000453464450276,
+           -1.0126805222012591,
+           -1.0411653486714478,
+           -1.085261836962483,
+           -1.1439770836442429,
+           -1.2159938796062513,
+           -1.2997004819181188,
+           -1.393226960846351,
+           -1.4944872613078766,
+           -1.6012259840822627,
+           -1.711068782293894,
+           -1.8215751856568498,
+           -1.9302926107352205,
+           -2.0348102912908588,
+           -2.1328118692098115,
+           -2.222125423310892,
+           -2.3007697795900053,
+           -2.366996040469144,
+           -2.419323390045313,
+           -2.4565683741990503,
+           -2.4778670152050433,
+           -2.482689296209787,
+           -2.4708457372643764,
+           -2.4424859769322964,
+           -2.3980894671018067,
+           -2.3384485787663,
+           -2.264644598536135,
+           -2.1780172650635983,
+           -2.0801286472706977,
+           -1.9727222985605881,
+           -1.8576787298734772,
+           -1.7369683269130616,
+           -1.6126028911715415,
+           -1.486587009272095,
+           -1.3608704501124562,
+           -1.2373027545590136,
+           -1.1175911189719785,
+           -1.0032625833143298,
+           -0.8956314193543927,
+           -0.7957724774679101,
+           -0.7045010952690725,
+           -0.6223600016876162,
+           -0.5496134704455322,
+           -0.48624879169938157,
+           -0.43198494455787734,
+           -0.3862881709268139,
+           -0.34839397723822146,
+           -0.3173349294336501,
+           -0.29197346211203024,
+           -0.271038798614518,
+           -0.2531669780802108,
+           -0.23694291065404463,
+           -0.22094333489485274,
+           -0.20377953315200306,
+           -0.18413867166158218,
+           -0.16082267203004974,
+           -0.13278358856978034,
+           -0.09915455987172539,
+           -0.05927552063440405,
+           -0.012712998109136378,
+           0.04072652695693658,
+           0.10099004625324079,
+           0.16777841040646366,
+           0.2405536676401134,
+           0.31855316428322783,
+           0.4008100397391313,
+           0.48617958076506734,
+           0.5733707457373173,
+           0.6609820329083066,
+           0.7475407509872428,
+           0.8315446586523029,
+           0.9115048741881093,
+           0.9859889190339327,
+           1.053662750619418,
+           1.113330660720794,
+           1.163971965220167,
+           1.204773488397858,
+           1.2351569478416533,
+           1.254800472176927,
+           1.263653629981915,
+           1.2619455108184945,
+           1.2501855742280414,
+           1.2291571654446436,
+           1.1999037828856582,
+           1.1637083675197937,
+           1.1220660633348891,
+           1.0766510668192508,
+           1.0292783373701397,
+           0.981861075947354,
+           0.9363649926503188,
+           0.8947604723074509,
+           0.858973808335412,
+           0.8308387074353695,
+           0.8120492702397565,
+           0.8041156256403288,
+           0.8083233397942498,
+           0.8256976360267182,
+           0.8569733510323828,
+           0.9025714185794244,
+           0.962582517580755,
+           1.036758350662803,
+           1.1245108363940015,
+           1.2249193076032192,
+           1.3367456143954615,
+           1.4584568383150227,
+           1.588255138341348,
+           1.7241140746059493,
+           1.8638205962054661,
+           2.0050217392016316,
+           2.1452749633225494,
+           2.282100963938222,
+           2.413037731875673,
+           2.5356945991841027,
+           2.647805004950394,
+           2.747276741849093,
+           2.832238500684417,
+           2.901081615407349,
+           2.952496022925421,
+           2.985499587770468,
+           2.999460098067586
+          ],
+          [
+           2.9982510703398844,
+           2.9808605982439467,
+           2.9445149759269227,
+           2.88991074998785,
+           2.8180911180019272,
+           2.730422616818316,
+           2.628564588265357,
+           2.51443214372676,
+           2.390153502212413,
+           2.2580227084870987,
+           2.1204488453489954,
+           1.9799029346768413,
+           1.838863773462478,
+           1.6997639724966855,
+           1.5649374562033942,
+           1.436569642593624,
+           1.3166514534529719,
+           1.2069382084203122,
+           1.108914334970193,
+           1.0237646825017073,
+           0.9523530663263893,
+           0.8952084903519828,
+           0.8525193100444569,
+           0.8241354044277398,
+           0.8095782321888869,
+           0.808058457147846,
+           0.8185006470726522,
+           0.8395743814999355,
+           0.8697309529555943,
+           0.90724471543012,
+           0.9502580272962872,
+           0.9968286556158071,
+           1.0449784568586848,
+           1.0927421266420685,
+           1.138214818638242,
+           1.1795974700144833,
+           1.2152387366257493,
+           1.2436725339507535,
+           1.263650297044554,
+           1.2741672115737361,
+           1.2744818247727778,
+           1.2641286159412108,
+           1.2429232865796556,
+           1.2109607158946174,
+           1.1686057135243348,
+           1.1164768832851266,
+           1.0554240849576941,
+           0.9865001413005908,
+           0.9109275806033503,
+           0.8300613276180666,
+           0.7453483546014741,
+           0.658285377023056,
+           0.5703757234695381,
+           0.4830865253251084,
+           0.3978073585804233,
+           0.3158114280088054,
+           0.23822031405746658,
+           0.16597320694528575,
+           0.09980143309822215,
+           0.0402089392403947,
+           -0.012540757242553692,
+           -0.0584308126531482,
+           -0.0976903352216765,
+           -0.13078671866727615,
+           -0.15841123420223235,
+           -0.18145826061312442,
+           -0.20099869890275715,
+           -0.2182482709244242,
+           -0.23453153659293294,
+           -0.25124257816937556,
+           -0.26980338987642793,
+           -0.2916210744019017,
+           -0.3180449830487101,
+           -0.3503249424537019,
+           -0.3895716877202167,
+           -0.43672057001959086,
+           -0.49249952746796294,
+           -0.5574022033215481,
+           -0.6316669678451522,
+           -0.7152624527641909,
+           -0.8078800436801944,
+           -0.9089336002942879,
+           -1.0175664911312707,
+           -1.1326658432772103,
+           -1.2528837231085928,
+           -1.3766647857427639,
+           -1.5022797634712246,
+           -1.6278640109829277,
+           -1.751460191612218,
+           -1.8710640775601588,
+           -1.9846723508954403,
+           -2.0903312333781385,
+           -2.186184743325481,
+           -2.270521377696092,
+           -2.341818047411763,
+           -2.398780153024509,
+           -2.44037677480536,
+           -2.465870064118034,
+           -2.47483805883917,
+           -2.467190301311938,
+           -2.4431758090883178,
+           -2.403383132338806,
+           -2.3487324227964375,
+           -2.2804596327733346,
+           -2.200093154385084,
+           -2.1094233939261273,
+           -2.01046594980089,
+           -1.9054192202453175,
+           -1.7966174053637143,
+           -1.6864799833224613,
+           -1.5774588300118075,
+           -1.4719842128659761,
+           -1.3724109212648563,
+           -1.280965797197719,
+           -1.1996979005677773,
+           -1.1304324843231668,
+           -1.0747298669158283,
+           -1.033850175515403,
+           -1.0087247956897927,
+           -0.9999352052377035,
+           -1.0076996953510213,
+           -1.0318682955314067,
+           -1.071926024222462,
+           -1.1270043896724662,
+           -1.1959008699128348,
+           -1.2771059116794792,
+           -1.3688368102120758,
+           -1.4690776694594923,
+           -1.5756244992372743,
+           -1.6861343857868825,
+           -1.798177577875836,
+           -1.9092912643188737,
+           -2.0170337821702367,
+           -2.1190379886860335,
+           -2.2130625545858926,
+           -2.2970399905073737,
+           -2.369120301464633,
+           -2.4277092735155335,
+           -2.4715005299834547,
+           -2.499500648166729,
+           -2.5110467976986905,
+           -2.5058165443909948,
+           -2.4838296539994,
+           -2.4454419242053103,
+           -2.391331265447531,
+           -2.322476437352643,
+           -2.240129022848122,
+           -2.145779382323808,
+           -2.0411174715387848,
+           -1.9279895259330009,
+           -1.8083517077366638,
+           -1.6842218785465,
+           -1.5576306973115863,
+           -1.4305732511194855,
+           -1.3049624037134235,
+           -1.1825849949630958,
+           -1.0650619449386558,
+           -0.9538132108730102,
+           -0.8500284168499056,
+           -0.75464382780211,
+           -0.6683261751075903,
+           -0.5914636648864102,
+           -0.5241643164681979,
+           -0.46626159203758705,
+           -0.41732709385198863,
+           -0.3766899272853877,
+           -0.3434621607362239,
+           -0.31656966131747644,
+           -0.29478745200771866,
+           -0.276778624888974,
+           -0.26113575897446745,
+           -0.24642373205113002,
+           -0.2312227853605325,
+           -0.21417069853317464,
+           -0.1940029599559059,
+           -0.16958987393861016,
+           -0.13996962918812658,
+           -0.10437646105215818,
+           -0.06226316999819758,
+           -0.013317407524066816,
+           0.04252869563039386,
+           0.10509580964926438,
+           0.17396166406490232,
+           0.24847217176869313,
+           0.32775912626397585,
+           0.41076400758795,
+           0.49626727191981124,
+           0.5829223553813703,
+           0.6692934976045831,
+           0.7538963884767125,
+           0.83524056469562,
+           0.9118724333554289,
+           0.9824177790289378,
+           1.045622619290332,
+           1.1003913111675934,
+           1.1458208767343259,
+           1.1812306083416837,
+           1.206186130578837,
+           1.220517234046638,
+           1.2243289520036142,
+           1.218005521008553,
+           1.2022070465916574,
+           1.1778588802341454,
+           1.1461338998787096,
+           1.1084280681589798,
+           1.066329815942875,
+           1.0215839592553553,
+           0.9760510011166933,
+           0.9316627926553848,
+           0.8903756268894073,
+           0.8541219112612833,
+           0.824761609457304,
+           0.8040346580347405,
+           0.7935155484480761,
+           0.7945712204743219,
+           0.8083233397942494,
+           0.8356159323100252,
+           0.8769892230615837,
+           0.9326603813491768,
+           1.0025117094229063,
+           1.0860866338598902,
+           1.1825936708688223,
+           1.290918343839942,
+           1.4096428382304282,
+           1.5370729900910685,
+           1.6712720248512283,
+           1.810100296819459,
+           1.9512601313370204,
+           2.0923447443228973,
+           2.230890111235065,
+           2.364428581811146,
+           2.4905429902461544,
+           2.606919993913921,
+           2.7114013877981855,
+           2.8020321861778457,
+           2.877104336769937,
+           2.9351950337187764,
+           2.9751987220971703,
+           2.9963520349068817,
+           2.9982510703398844
+          ],
+          [
+           2.988596386843346,
+           2.959307412524669,
+           2.9114661202915983,
+           2.845990156496706,
+           2.7641304992190805,
+           2.6674436742231897,
+           2.5577571584894843,
+           2.4371287864036266,
+           2.3078011147716326,
+           2.172151820738579,
+           2.032641298581213,
+           1.8917586850111692,
+           1.7519675765493392,
+           1.6156527059273345,
+           1.4850688173012676,
+           1.3622929230378282,
+           1.2491810393955585,
+           1.1473303867127176,
+           1.0580479045062638,
+           0.9823257765361842,
+           0.9208244892365497,
+           0.8738637631948313,
+           0.8414215060988068,
+           0.8231407414679582,
+           0.8183442753070062,
+           0.826056677269941,
+           0.8450329785378903,
+           0.8737933296432484,
+           0.910662721776538,
+           0.9538147580683145,
+           1.0013183697562535,
+           1.0511863082019304,
+           1.1014242088990203,
+           1.1500790186767913,
+           1.1952856022699019,
+           1.2353103985765952,
+           1.268591078818751,
+           1.2937712663202239,
+           1.3097295079740572,
+           1.315601837352405,
+           1.3107974350245752,
+           1.2950070688046744,
+           1.268204180888452,
+           1.2306386755295589,
+           1.1828236453675949,
+           1.1255154521383206,
+           1.0596877438346348,
+           0.9865001413005909,
+           0.9072624589787149,
+           0.8233954338288736,
+           0.7363890205987145,
+           0.6477593685894613,
+           0.5590056234504425,
+           0.4715676966943161,
+           0.38678611563052945,
+           0.3058650080779045,
+           0.22983919106045472,
+           0.1595462229089928,
+           0.09560414659754261,
+           0.03839550209776264,
+           -0.011941979141480787,
+           -0.055517759600107325,
+           -0.09268390409903758,
+           -0.12402363684179539,
+           -0.15033335196999015,
+           -0.1725985539852671,
+           -0.19196436370920916,
+           -0.20970136857146165,
+           -0.22716771929114904,
+           -0.24576847530166462,
+           -0.2669132759959536,
+           -0.2919734621120301,
+           -0.32223979010104803,
+           -0.35888187160897567,
+           -0.40291043047942554,
+           -0.4551434019013564,
+           -0.5161768041401931,
+           -0.5863611950294273,
+           -0.6657843859957872,
+           -0.7542609293137762,
+           -0.8513287234539593,
+           -0.9562529010745324,
+           -1.0680369789240365,
+           -1.1854410633243795,
+           -1.3070067236538627,
+           -1.431087973917365,
+           -1.5558876434284488,
+           -1.6794982758672954,
+           -1.7999465751264594,
+           -1.9152403195071528,
+           -2.023416595483669,
+           -2.1225901602593384,
+           -2.2110007298385157,
+           -2.287058006748538,
+           -2.349383308533598,
+           -2.396846733642691,
+           -2.4285989035704523,
+           -2.4440964466382438,
+           -2.4431205365718784,
+           -2.4257879644567244,
+           -2.3925544017008065,
+           -2.3442096999359516,
+           -2.281865266722602,
+           -2.206933748757552,
+           -2.1211014422710046,
+           -2.026294028805366,
+           -1.9246363991839233,
+           -1.8184074751273325,
+           -1.7099910630204056,
+           -1.601823874656359,
+           -1.4963419228795596,
+           -1.3959265440655755,
+           -1.3028513131849215,
+           -1.2192311004019787,
+           -1.1469744711195504,
+           -1.0877405551936605,
+           -1.042901407527643,
+           -1.013510753897561,
+           -1.000279865760917,
+           -1.0035611395909616,
+           -1.0233397740389165,
+           -1.059233746380645,
+           -1.1105020929142526,
+           -1.176061301024246,
+           -1.2545094283041807,
+           -1.3441573811081295,
+           -1.4430666156280754,
+           -1.549092373178652,
+           -1.659931431482884,
+           -1.7731732485343874,
+           -1.8863532975991184,
+           -1.9970073429808974,
+           -2.10272538746456,
+           -2.2012040342814494,
+           -2.290296048676112,
+           -2.3680559756098605,
+           -2.4327807690208236,
+           -2.483044511905026,
+           -2.5177264522142004,
+           -2.536031743575575,
+           -2.5375044580760293,
+           -2.5220326264243536,
+           -2.4898452540827205,
+           -2.441501455694776,
+           -2.3778720395830955,
+           -2.300114054608208,
+           -2.20963897886936,
+           -2.108075379515895,
+           -1.997227001697292,
+           -1.8790273493068277,
+           -1.755491898168273,
+           -1.6286691318410393,
+           -1.5005916101493042,
+           -1.3732282704826058,
+           -1.248439122220917,
+           -1.1279334263923892,
+           -1.0132323576681548,
+           -0.9056370264888645,
+           -0.8062025985520511,
+           -0.7157190906412345,
+           -0.6346992498513565,
+           -0.563373741997742,
+           -0.5016936889471793,
+           -0.44934040844997847,
+           -0.40574202844397944,
+           -0.370096475284916,
+           -0.3414001762361788,
+           -0.3184816747851249,
+           -0.30003923646110453,
+           -0.28468142580209244,
+           -0.2709695643385099,
+           -0.25746093665874725,
+           -0.24275159781076996,
+           -0.22551765076816954,
+           -0.20455390700127518,
+           -0.17880891517432224,
+           -0.14741544077347102,
+           -0.10971560054582666,
+           -0.06527999690035756,
+           -0.013920355285663839,
+           0.04430466200092278,
+           0.10909061343627115,
+           0.17989537280372625,
+           0.2559539446532289,
+           0.3362996087837737,
+           0.4197908359212784,
+           0.505143265063015,
+           0.5909658993366258,
+           0.6758005650831762,
+           0.7581635910855922,
+           0.8365886036804946,
+           0.9096693004992504,
+           0.9761010616602376,
+           1.034720282525563,
+           1.0845403660533763,
+           1.1247833940118863,
+           1.1549066028749395,
+           1.174622919454247,
+           1.1839149600281524,
+           1.183042061195889,
+           1.1725400868116151,
+           1.1532139387266285,
+           1.1261228850939564,
+           1.0925590039937847,
+           1.054019217489864,
+           1.0121715574515235,
+           0.9688164553676861,
+           0.925843980107168,
+           0.8851880567817896,
+           0.8487787837398745,
+           0.8184940210757411,
+           0.796111451385755,
+           0.783262311052107,
+           0.7813879580498116,
+           0.7917003808505373,
+           0.8151476638640377,
+           0.8523853101311084,
+           0.9037541844171006,
+           0.9692656827809795,
+           1.0485945619306765,
+           1.1410796774372243,
+           1.245732688676122,
+           1.361254594885209,
+           1.4860597757297962,
+           1.6183070259520933,
+           1.755936901589149,
+           1.8967145391271771,
+           2.0382769726897383,
+           2.178183861320084,
+           2.313970451436129,
+           2.4432015407944916,
+           2.5635251812922446,
+           2.6727248594273303,
+           2.768768925249048,
+           2.8498561024273705,
+           2.9144560021915984,
+           2.961343680176932,
+           2.9896274148696187,
+           2.9987690459813585,
+           2.988596386843346
+          ],
+          [
+           2.970577730569146,
+           2.9296322050116927,
+           2.870682464907581,
+           2.794859504779255,
+           2.7036115195592996,
+           2.598671883261971,
+           2.4820207830214427,
+           2.355841410311021,
+           2.2224717389646202,
+           2.0843530225053826,
+           1.9439762187656375,
+           1.8038275960494266,
+           1.666334791051779,
+           1.5338145740596802,
+           1.4084235320209628,
+           1.2921128060231641,
+           1.1865879184304826,
+           1.0932745989052501,
+           1.013291370915844,
+           0.9474294947561916,
+           0.8961406836589944,
+           0.8595328206950855,
+           0.8373737104595536,
+           0.8291027058055649,
+           0.8338498608459508,
+           0.850462081722436,
+           0.8775355806260806,
+           0.9134537902765891,
+           0.9564297691231224,
+           1.0045520249716162,
+           1.055832609020779,
+           1.1082562851798938,
+           1.159829562113415,
+           1.2086283880403579,
+           1.252843350496738,
+           1.2908212939001653,
+           1.3211023649874372,
+           1.342451617522759,
+           1.353884449997148,
+           1.3546853097449703,
+           1.3444192699531554,
+           1.322936268070853,
+           1.2903679805663704,
+           1.2471174951481174,
+           1.193842122807675,
+           1.131429863829083,
+           1.0609701999577064,
+           0.9837200253047778,
+           0.9010656477998457,
+           0.8144818881483533,
+           0.7254893719697872,
+           0.6356111514139555,
+           0.5463298041171302,
+           0.45904613963507734,
+           0.3750405969812251,
+           0.29543834283310966,
+           0.22117898026771085,
+           0.15299165510832616,
+           0.0913762042522905,
+           0.036590831339779695,
+           -0.011353376133579585,
+           -0.052690953309733765,
+           -0.08789363561240052,
+           -0.11765523629420666,
+           -0.14287022795443002,
+           -0.16460659706857173,
+           -0.18407369101057675,
+           -0.20258590912764513,
+           -0.22152319978129154,
+           -0.24228941107738658,
+           -0.26626960206989786,
+           -0.29478745200771833,
+           -0.3290639068819365,
+           -0.3701781750347195,
+           -0.41903212755765323,
+           -0.47631907600282924,
+           -0.5424977916053281,
+           -0.6177724994565854,
+           -0.7020794311278622,
+           -0.7950803538621042,
+           -0.896163317765018,
+           -1.0044506788577416,
+           -1.118814270009418,
+           -1.2378974083206509,
+           -1.3601432510981457,
+           -1.483828847602091,
+           -1.6071040844370577,
+           -1.7280345925890426,
+           -1.8446475770027129,
+           -1.9549794479993394,
+           -2.0571240798836716,
+           -2.14928049721757,
+           -2.2297987941704562,
+           -2.297223127070829,
+           -2.3503306840189655,
+           -2.388165626694005,
+           -2.410067116128122,
+           -2.4156906734205075,
+           -2.4050222847531555,
+           -2.378384833794495,
+           -2.336436629393295,
+           -2.280161987847664,
+           -2.2108540222845043,
+           -2.1300899820494923,
+           -2.0396996677941144,
+           -1.9417276186405754,
+           -1.8383899221821152,
+           -1.7320266323056732,
+           -1.6250508905644518,
+           -1.519895931311901,
+           -1.4189612069084683,
+           -1.3245588955963936,
+           -1.238862050403374,
+           -1.1638556127306292,
+           -1.1012914498990354,
+           -1.052648483392533,
+           -1.0190988560672352,
+           -1.001480945040657,
+           -1.0002798657609167,
+           -1.0156159357858163,
+           -1.047241378371045,
+           -1.0945453506517782,
+           -1.1565671837498173,
+           -1.2320175273492802,
+           -1.319306903893614,
+           -1.4165810021196996,
+           -1.5217618804229271,
+           -1.632594111403299,
+           -1.7466947832485848,
+           -1.8616061841603992,
+           -1.974849934974914,
+           -2.083981303925462,
+           -2.186642436861508,
+           -2.2806132661508105,
+           -2.363858921171913,
+           -2.4345725512492855,
+           -2.4912125858963616,
+           -2.5325335944813663,
+           -2.5576100645180104,
+           -2.56585259082792,
+           -2.55701615255804,
+           -2.5312003469180007,
+           -2.488841642815542,
+           -2.430697909547375,
+           -2.3578256606496826,
+           -2.2715506264101055,
+           -2.1734324261688123,
+           -2.065224249564872,
+           -1.9488285709817434,
+           -1.8262500108519644,
+           -1.6995465190765908,
+           -1.5707800881717127,
+           -1.4419682061725694,
+           -1.3150372318465435,
+           -1.1917788181734401,
+           -1.0738104258471195,
+           -0.9625408589219399,
+           -0.859141622481755,
+           -0.7645247507150379,
+           -0.6793275868753086,
+           -0.6039048185043955,
+           -0.5383278864800844,
+           -0.4823916995593787,
+           -0.4356284018066301,
+           -0.3973277632295034,
+           -0.36656359851289383,
+           -0.342225469060015,
+           -0.32305479333746306,
+           -0.3076843829992523,
+           -0.29468034008209015,
+           -0.28258519572911056,
+           -0.26996114473152377,
+           -0.25543223327538894,
+           -0.2377243895065252,
+           -0.21570224701132812,
+           -0.18840179847666805,
+           -0.1550580283905335,
+           -0.11512680681662622,
+           -0.06830047762016198,
+           -0.014516740183027359,
+           0.0460394005893947,
+           0.11294065976655368,
+           0.18552933476197114,
+           0.2629356871095767,
+           0.3441023554958915,
+           0.42781415368673015,
+           0.5127324652762544,
+           0.5974333255814772,
+           0.6804481826087351,
+           0.760306256348879,
+           0.8355773705871196,
+           0.904914115120466,
+           0.9670922092151188,
+           1.021047979027505,
+           1.065911931546444,
+           1.1010375036762492,
+           1.1260241849956283,
+           1.1407343535165206,
+           1.1453033219223858,
+           1.1401422633375031,
+           1.1259338663743306,
+           1.1036207544951262,
+           1.0743868899537676,
+           1.0396323630929867,
+           1.0009421390094044,
+           0.960049491234563,
+           0.9187949921167008,
+           0.8790820484582405,
+           0.842830065622117,
+           0.8119263913175517,
+           0.7881782298235982,
+           0.7732657274224005,
+           0.7686974099425364,
+           0.7757691039475296,
+           0.7955273953712622,
+           0.8287385751339421,
+           0.8758638929653714,
+           0.9370417914145827,
+           1.0120776254606219,
+           1.100441193319121,
+           1.2012722153615043,
+           1.3133937051545195,
+           1.4353329842276439,
+           1.5653499050232618,
+           1.7014716691958935,
+           1.8415334653865938,
+           1.9832240058457882,
+           2.124134918410206,
+           2.261812852420751,
+           2.3938130866533363,
+           2.51775338601009,
+           2.6313668426528767,
+           2.732552456785046,
+           2.8194222619770404,
+           2.8903438786256284,
+           2.943977484958112,
+           2.9793063254003767,
+           2.9956600279728542,
+           2.9927301719865,
+           2.970577730569146
+          ],
+          [
+           2.944347547502898,
+           2.892086041388761,
+           2.822509057954231,
+           2.7369513832859087,
+           2.6370461969756547,
+           2.5246890844057774,
+           2.401996225868788,
+           2.271257743433638,
+           2.1348872999226796,
+           1.995369131349968,
+           1.855203752598908,
+           1.7168536045934897,
+           1.5826899090843791,
+           1.4549419645214945,
+           1.3356500541583325,
+           1.226623047096442,
+           1.129401656684815,
+           1.0452281814232816,
+           0.975023394725668,
+           0.9193710754963325,
+           0.8785104857584577,
+           0.8523369091111186,
+           0.8404101693094536,
+           0.8419708565244445,
+           0.8559638045357039,
+           0.881068189740091,
+           0.9157334666159643,
+           0.9582202179564393,
+           1.0066448850649767,
+           1.0590272559031553,
+           1.1133395299577158,
+           1.16755574872001,
+           1.219700380784951,
+           1.2678948805740602,
+           1.3104010987235761,
+           1.3456605086917932,
+           1.3723283258891958,
+           1.3893017297590826,
+           1.395741552323979,
+           1.3910869648895208,
+           1.3750628736209691,
+           1.3476799200758507,
+           1.309227169838901,
+           1.2602577564795696,
+           1.2015679245395148,
+           1.1341700797582075,
+           1.0592606031677898,
+           0.9781833143524926,
+           0.8923895748934045,
+           0.8033961032063883,
+           0.7127416246742398,
+           0.6219435049109745,
+           0.5324555086370335,
+           0.44562779218618076,
+           0.36267017503519067,
+           0.2846196465805103,
+           0.21231295098133102,
+           0.14636495815285464,
+           0.08715337636787204,
+           0.034810195297681194,
+           -0.010779928066642798,
+           -0.04997430984238851,
+           -0.08336005760078291,
+           -0.11173539657487663,
+           -0.13608500356182573,
+           -0.15755000543495398,
+           -0.17739343946846045,
+           -0.19696209259965028,
+           -0.21764573325258807,
+           -0.24083481995417305,
+           -0.2678778138709412,
+           -0.30003923646110436,
+           -0.33845959827546107,
+           -0.38411828089231587,
+           -0.4378003821024693,
+           -0.5000684365390091,
+           -0.5712398023990344,
+           -0.6513703627537912,
+           -0.7402450307358686,
+           -0.8373753756064956,
+           -0.9420045056576138,
+           -1.0531191586341264,
+           -1.1694687655278526,
+           -1.2895910738505971,
+           -1.4118437463747109,
+           -1.534441195140058,
+           -1.655495772230414,
+           -1.7730623219457744,
+           -1.8851850065376712,
+           -1.989945252027518,
+           -2.085509623524614,
+           -2.17017643192465,
+           -2.242419896190836,
+           -2.3009307371452694,
+           -2.344652158642567,
+           -2.3728102782714817,
+           -2.384938199785859,
+           -2.380893070160005,
+           -2.360865631833042,
+           -2.3253819612608058,
+           -2.2752972739130812,
+           -2.211781868700122,
+           -2.1362994767430448,
+           -2.050578465687695,
+           -1.9565765268012103,
+           -1.8564396335284767,
+           -1.7524562030178632,
+           -1.647007512798379,
+           -1.5425155202906964,
+           -1.441389300762599,
+           -1.34597135797081,
+           -1.2584850700587096,
+           -1.1809845110388104,
+           -1.115307835867065,
+           -1.0630353359375562,
+           -1.025453163726565,
+           -1.0035235928907351,
+           -0.9978625265711686,
+           -1.0087247956897918,
+           -1.0359976047916042,
+           -1.0792022899591582,
+           -1.1375043561939948,
+           -1.2097315652159957,
+           -1.2943996536523843,
+           -1.3897450807164566,
+           -1.4937640381083777,
+           -1.6042568070464542,
+           -1.7188764216430859,
+           -1.8351804973175851,
+           -1.9506850100131623,
+           -2.062918768405849,
+           -2.169477308086811,
+           -2.2680749541502925,
+           -2.356593846259413,
+           -2.4331287968844095,
+           -2.4960269570966536,
+           -2.543921392479781,
+           -2.5757578212118926,
+           -2.590813933487254,
+           -2.588710892061925,
+           -2.5694168033802622,
+           -2.533242142808119,
+           -2.480827311203325,
+           -2.413122688652176,
+           -2.3313617300841596,
+           -2.237027812285991,
+           -2.131815688565973,
+           -2.017588532420481,
+           -1.896331652016526,
+           -1.770104030733756,
+           -1.6409888936842985,
+           -1.5110445150430538,
+           -1.3822564659064105,
+           -1.2564924577298984,
+           -1.1354608633823076,
+           -1.0206738984028363,
+           -0.9134163217175687,
+           -0.8147203710089916,
+           -0.7253474867910084,
+           -0.6457772050935314,
+           -0.5762034158905384,
+           -0.516537997604493,
+           -0.46642165186926693,
+           -0.4252415818884983,
+           -0.3921554866997735,
+           -0.3661211867054577,
+           -0.34593105685699366,
+           -0.3302503263221786,
+           -0.31765821022298213,
+           -0.30669077238959813,
+           -0.2958843796485719,
+           -0.2838185988527553,
+           -0.2691574078403058,
+           -0.25068764021490425,
+           -0.22735365998489826,
+           -0.19828736371208167,
+           -0.1628327322897634,
+           -0.12056429861090777,
+           -0.07129905752393817,
+           -0.01510151653005844,
+           0.04771823472237299,
+           0.11661337550599193,
+           0.19081588407207425,
+           0.26935833043728136,
+           0.3511013516323615,
+           0.4347660799854168,
+           0.5189706644915731,
+           0.6022699167633493,
+           0.6831970292339229,
+           0.760306256348879,
+           0.832215420905053,
+           0.8976471082391262,
+           0.9554674406618194,
+           1.0047213826705392,
+           1.044663612632188,
+           1.0747841067047925,
+           1.0948277130284436,
+           1.1048071453682315,
+           1.105008991659678,
+           1.0959925101307189,
+           1.0785811694111547,
+           1.0538470746769208,
+           1.0230886047432695,
+           0.9878017605079146,
+           0.949645888819182,
+           0.910404593557693,
+           0.8719427737164732,
+           0.8361608332716763,
+           0.8049471869487874,
+           0.7801302375382295,
+           0.7634310228168997,
+           0.7564177227297715,
+           0.7604631803601086,
+           0.776706524189496,
+           0.806019885761907,
+           0.8489810883446616,
+           0.9058530413778565,
+           0.9765704158360173,
+           1.060734000980423,
+           1.1576129576258247,
+           1.2661549915244572,
+           1.3850042774876488,
+           1.5125267751725793,
+           1.6468423957378098,
+           1.7858633093081955,
+           1.9273375305809757,
+           2.0688967877408726,
+           2.208107571426465,
+           2.3425241785176367,
+           2.4697425120635716,
+           2.5874533751123217,
+           2.693494003174237,
+           2.785896617441125,
+           2.862932847832547,
+           2.9231529698650536,
+           2.9654190199666504,
+           2.9889309972823366,
+           2.9932455227702337,
+           2.9782865045289246,
+           2.9443475475028986
+          ],
+          [
+           2.9101277568626367,
+           2.846986579189957,
+           2.767353468253092,
+           2.672755720928226,
+           2.5649977042183587,
+           2.446121205610534,
+           2.3183605309965607,
+           2.1840934018678118,
+           2.0457888016325225,
+           1.9059529912571846,
+           1.7670749553147995,
+           1.6315725499672664,
+           1.50174060419833,
+           1.3797021752797372,
+           1.2673640802664732,
+           1.1663777192526354,
+           1.0781060758100067,
+           1.0035976286999642,
+           0.9435677403307645,
+           0.8983879056801266,
+           0.8680830549869348,
+           0.8523369091111185,
+           0.8505051928326232,
+           0.8616363232466102,
+           0.8844990124059768,
+           0.9176160597996548,
+           0.9593034651073241,
+           1.0077138684475848,
+           1.0608832269986284,
+           1.1167795657589215,
+           1.1733525979937558,
+           1.228582998527412,
+           1.280530130695813,
+           1.3273770749326697,
+           1.3674718823552363,
+           1.3993640783793106,
+           1.4218355667147835,
+           1.433925229879752,
+           1.4349466849283044,
+           1.424498828311595,
+           1.402468987274598,
+           1.3690286823270732,
+           1.3246221914309182,
+           1.2699482869670147,
+           1.205935686784497,
+           1.133712916458972,
+           1.054573417427329,
+           0.9699368515237823,
+           0.8813076437621481,
+           0.7902318697599626,
+           0.6982536304226145,
+           0.606872063554614,
+           0.5175001198281053,
+           0.4314261796389171,
+           0.3497795091597699,
+           0.2735004503859206,
+           0.20331611382100256,
+           0.1397221968974365,
+           0.08297138997904108,
+           0.03306865895813032,
+           -0.010226486570804948,
+           -0.04739081323110049,
+           -0.07912152618563105,
+           -0.10631420220658891,
+           -0.13003508486088777,
+           -0.15148848104277934,
+           -0.17198012703375487,
+           -0.19287749902011067,
+           -0.21556812482644502,
+           -0.2414170084311368,
+           -0.27172430519952234,
+           -0.3076843829992525,
+           -0.3503473724808337,
+           -0.4005842495782398,
+           -0.4590564061876905,
+           -0.5261905531730517,
+           -0.6021596661040859,
+           -0.6868705317943441,
+           -0.779958286576988,
+           -0.8807881595242774,
+           -0.9884644499388011,
+           -1.1018465830420403,
+           -1.219571905525828,
+           -1.3400847081121785,
+           -1.4616707998987768,
+           -1.5824968131687402,
+           -1.700653291232298,
+           -1.814200508971848,
+           -1.9212158987340726,
+           -2.0198419050673992,
+           -2.1083330718626887,
+           -2.1851011753174387,
+           -2.248757255665448,
+           -2.2981494689129165,
+           -2.332395775298649,
+           -2.350910601571151,
+           -2.353424756546885,
+           -2.339998040326416,
+           -2.311024163076357,
+           -2.267227775141372,
+           -2.2096536018734074,
+           -2.139647869243679,
+           -2.058832395289821,
+           -1.9690719030799606,
+           -1.8724352786787426,
+           -1.771151648416381,
+           -1.6675622798407583,
+           -1.5640694168280813,
+           -1.4630832387793364,
+           -1.3669681846275556,
+           -1.2779899032168898,
+           -1.1982640819153196,
+           -1.1297083652641473,
+           -1.0739985059716715,
+           -1.0325297932703204,
+           -1.006384680906153,
+           -0.996307391772505,
+           -1.0026861119467023,
+           -1.0255432076189697,
+           -1.0645337084657231,
+           -1.1189521050287432,
+           -1.187747310381231,
+           -1.2695454425884267,
+           -1.3626798989167932,
+           -1.465228019923148,
+           -1.5750534856639693,
+           -1.6898534510900407,
+           -1.8072093165101926,
+           -1.9246399445086086,
+           -2.039656078917333,
+           -2.1498146957094852,
+           -2.252772020582355,
+           -2.3463339833860077,
+           -2.428502944517935,
+           -2.4975196213200888,
+           -2.5518992610700524,
+           -2.59046124841638,
+           -2.6123514955792793,
+           -2.617057139365529,
+           -2.604413255705648,
+           -2.574601495425381,
+           -2.5281407395775553,
+           -2.4658700641180347,
+           -2.3889244873308297,
+           -2.2987041447141747,
+           -2.1968376908651055,
+           -2.085140862492755,
+           -1.9655712478051712,
+           -1.8401803924912181,
+           -1.7110644293503496,
+           -1.5803144459998493,
+           -1.449967802434386,
+           -1.3219615776933573,
+           -1.1980892634135165,
+           -1.0799617332292244,
+           -0.9689734031262714,
+           -0.8662743618688968,
+           -0.77274909595888,
+           -0.6890022641606737,
+           -0.6153517967075016,
+           -0.5518294084109295,
+           -0.49818842769089533,
+           -0.4539186597068313,
+           -0.4182678258921801,
+           -0.39026895865471284,
+           -0.36877298286669175,
+           -0.35248558867755464,
+           -0.34000739627420473,
+           -0.3298763350407718,
+           -0.3206111090325123,
+           -0.3107545989829858,
+           -0.2989160586900066,
+           -0.283811000317989,
+           -0.2642977279263745,
+           -0.23940956969590477,
+           -0.20838197452540108,
+           -0.17067377495807945,
+           -0.12598207228759792,
+           -0.07425036726882733,
+           -0.01566973685424688,
+           0.04932696070341155,
+           0.12007768781750745,
+           0.19571029413468025,
+           0.27516753616751116,
+           0.35723738251878745,
+           0.44058779837506895,
+           0.5238050847207925,
+           0.6054347531322611,
+           0.6840238484724233,
+           0.7581635910855922,
+           0.8265311982499051,
+           0.8879297620218053,
+           0.9413251068025679,
+           0.985878623847715,
+           1.0209751797035962,
+           1.046245318715692,
+           1.0615811232427994,
+           1.0671452554475696,
+           1.0633728775074434,
+           1.0509663284656572,
+           1.030882621165735,
+           1.0043140071261218,
+           0.9726620361680817,
+           0.9375057065900535,
+           0.9005644564076357,
+           0.863656882719832,
+           0.8286561911355397,
+           0.7974434674500251,
+           0.7718599270575756,
+           0.7536593322508048,
+           0.744461772625161,
+           0.7457099790513809,
+           0.7586292876131225,
+           0.7841922877762763,
+           0.8230890808058611,
+           0.8757039426745921,
+           0.9420990336027498,
+           1.0220056276318927,
+           1.114823154386213,
+           1.2196261558542356,
+           1.3351790682799531,
+           1.4599585478294177,
+           1.5921828733180141,
+           1.7298477845262221,
+           1.870767954825997,
+           2.0126231559539485,
+           2.153008054310222,
+           2.2894844850959384,
+           2.41963498526967,
+           2.541116330369388,
+           2.651711814653777,
+           2.749381038965454,
+           2.8323060256579096,
+           2.8989325635704657,
+           2.948005796387478,
+           2.9785992021286347,
+           2.990136266743473,
+           2.982404327068349,
+           2.9555602435711563,
+           2.9101277568626376
+          ],
+          [
+           2.868207873561811,
+           2.7947153802732227,
+           2.705682337051223,
+           2.6028156420586215,
+           2.488075604138452,
+           2.3636329666832188,
+           2.2318212942289612,
+           2.095085835385502,
+           1.9559300577072118,
+           1.8168611032334807,
+           1.680335436417069,
+           1.548705948483008,
+           1.4241717441429436,
+           1.3087317689977853,
+           1.2041433405842639,
+           1.111886525226625,
+           1.033135159631772,
+           0.9687351540493762,
+           0.919190536801159,
+           0.8846575124192115,
+           0.8649466121272188,
+           0.8595328206950852,
+           0.867573372562006,
+           0.8879327272248675,
+           0.9192140636858577,
+           0.9597964803823238,
+           1.0078769541972745,
+           1.0615160030707396,
+           1.1186859140081906,
+           1.1773203438643185,
+           1.2353640754170916,
+           1.2908217164535851,
+           1.3418041646359795,
+           1.3865717248359126,
+           1.423572856737371,
+           1.4514776464620196,
+           1.4692052338045345,
+           1.4759445828813837,
+           1.4711681546477688,
+           1.454638220527602,
+           1.4264057427911236,
+           1.3868019346354503,
+           1.3364227964934268,
+           1.2761071003375142,
+           1.2069084562975947,
+           1.1300622417397572,
+           1.0469482984486642,
+           0.9590504056257445,
+           0.8679136125580779,
+           0.7751005631809165,
+           0.6821479642021717,
+           0.5905243385586536,
+           0.5015901670470595,
+           0.41656145406173856,
+           0.3364776602213615,
+           0.2621748276806398,
+           0.19426458610021685,
+           0.13311957210817627,
+           0.07886562658301746,
+           0.031380956506613836,
+           -0.009697734011555952,
+           -0.04496232102624674,
+           -0.07521390126067425,
+           -0.10143751894681763,
+           -0.12477165690144551,
+           -0.1464733071312764,
+           -0.16787955277920946,
+           -0.19036668589900874,
+           -0.21530795201027614,
+           -0.24403105093031918,
+           -0.27777653299844457,
+           -0.3176582102229819,
+           -0.3646266535489978,
+           -0.4194367715464725,
+           -0.4826203642310959,
+           -0.5544644209778404,
+           -0.634995786682141,
+           -0.7239726590841509,
+           -0.8208832065363522,
+           -0.9249514138189964,
+           -1.0351500784565968,
+           -1.1502206960215815,
+           -1.2686997947670333,
+           -1.388951112110914,
+           -1.5092028522505316,
+           -1.627589129414202,
+           -1.7421945883979433,
+           -1.8511011059897824,
+           -1.9524354159397714,
+           -2.044416467905878,
+           -2.1254013281972273,
+           -2.19392845731331,
+           -2.2487572556654474,
+           -2.288902853161554,
+           -2.3136652285363777,
+           -2.3226518777676137,
+           -2.3157934044009973,
+           -2.2933515743773443,
+           -2.255919559862303,
+           -2.2044142861658313,
+           -2.1400609884438277,
+           -2.0643702757547397,
+           -1.979108184488181,
+           -1.8862598766280885,
+           -1.7879877964601767,
+           -1.6865852382515871,
+           -1.5844263936558143,
+           -1.483914038216602,
+           -1.3874260790754755,
+           -1.2972622192252126,
+           -1.2155919965158817,
+           -1.1444054279762241,
+           -1.0854674324753566,
+           -1.0402771186680477,
+           -1.010032912592207,
+           -0.995604362924545,
+           -0.997511305039373,
+           -1.015910891452283,
+           -1.0505928101731112,
+           -1.1009828184583577,
+           -1.1661545221573146,
+           -1.2448491350858688,
+           -1.3355027633984515,
+           -1.436280581370409,
+           -1.5451171016915808,
+           -1.659761599276262,
+           -1.7778276262121553,
+           -1.8968454597429532,
+           -2.0143162574175606,
+           -2.127766655370115,
+           -2.2348025380199816,
+           -2.3331607304530952,
+           -2.420757417768708,
+           -2.49573217741587,
+           -2.5564866189670488,
+           -2.6017167581953635,
+           -2.630438405465408,
+           -2.642005018539552,
+           -2.6361176527559183,
+           -2.612826832657264,
+           -2.5725263638525955,
+           -2.5159392974060513,
+           -2.4440964466382447,
+           -2.3583080333163258,
+           -2.260129202489685,
+           -2.1513202887609073,
+           -2.0338028380983366,
+           -1.9096124854848784,
+           -1.7808498574701368,
+           -1.6496307084451727,
+           -1.5180365093061527,
+           -1.388066686971906,
+           -1.261593663571438,
+           -1.140321766349059,
+           -1.0257509754689262,
+           -0.9191463496022054,
+           -0.8215138216882242,
+           -0.7335828933105623,
+           -0.6557965798538875,
+           -0.5883087744398181,
+           -0.5309890111982093,
+           -0.4834344224040343,
+           -0.44498850404343465,
+           -0.41476613494906495,
+           -0.39168413997524654,
+           -0.3744965516011209,
+           -0.3618336102165364,
+           -0.3522434539666231,
+           -0.34423538658789865,
+           -0.33632357766380916,
+           -0.3270700449479322,
+           -0.31512579290137605,
+           -0.2992690346852511,
+           -0.27843950514026256,
+           -0.2517679776928311,
+           -0.21860022594128248,
+           -0.17851481762639557,
+           -0.13133429102982155,
+           -0.07712943743890477,
+           -0.016216593754527425,
+           0.05085196798275399,
+           0.12330428705132561,
+           0.200171156025914,
+           0.28031415579109287,
+           0.36245853455728444,
+           0.4452300544837525,
+           0.5271948245811728,
+           0.6069010587404267,
+           0.6829216450593384,
+           0.7538963884767128,
+           0.8185727937174783,
+           0.8758442896146511,
+           0.9247848581812925,
+           0.9646791208251188,
+           0.9950470476223832,
+           1.0156625907692847,
+           1.026565696832533,
+           1.0280673203854604,
+           1.0207472398319672,
+           1.0054446602137834,
+           0.9832417729400672,
+           0.9554406240081775,
+           0.923533815816633,
+           0.8891697287147723,
+           0.8541130929025647,
+           0.820201865508249,
+           0.7893014684499371,
+           0.7632575174279458,
+           0.7438482191393164,
+           0.7327376312922302,
+           0.7314309676886881,
+           0.7412330887440564,
+           0.7632112472640633,
+           0.7981630617605795,
+           0.8465905673891536,
+           0.9086810506838728,
+           0.9842952121443299,
+           1.0729630243507475,
+           1.173887466964562,
+           1.2859561282860483,
+           1.4077604707048896,
+           1.5376223691355406,
+           1.6736273520288487,
+           1.8136638082389822,
+           1.9554672740284262,
+           2.096668786522677,
+           2.2348461861778777,
+           2.36757717390551,
+           2.4924928803586917,
+           2.607330686770904,
+           2.7099850491586612,
+           2.798555120414563,
+           2.871388036841388,
+           2.9271168353055965,
+           2.9646920920344892,
+           2.983406521138876,
+           2.982911936658756,
+           2.963228162288534,
+           2.924743663564649,
+           2.8682078735618113
+          ],
+          [
+           2.818942558782108,
+           2.7357146826343803,
+           2.638017430025098,
+           2.5277228713925783,
+           2.406930692510258,
+           2.2779222554515095,
+           2.143110676668496,
+           2.0049880882755318,
+           1.866071313781901,
+           1.7288472249660758,
+           1.5957190514856718,
+           1.4689548890868362,
+           1.3506395965745985,
+           1.2426311874272593,
+           1.1465227111771275,
+           1.0636104851774169,
+           0.9948693824505507,
+           0.9409357097825108,
+           0.9020980263095226,
+           0.8782960610536479,
+           0.8691276929051597,
+           0.8738637631948308,
+           0.8914703039736523,
+           0.9206375889823017,
+           0.9598152533327791,
+           1.0072525860431105,
+           1.0610429801883607,
+           1.1191714314212475,
+           1.1795639092055485,
+           1.2401373878415605,
+           1.2988493170682087,
+           1.3537453347815331,
+           1.4030040765514997,
+           1.4449780167597228,
+           1.4782293822407278,
+           1.5015603085722822,
+           1.5140365583398505,
+           1.5150042860236101,
+           1.5040995114581432,
+           1.4812501486411638,
+           1.446670624387372,
+           1.4008493072439652,
+           1.3445291465677631,
+           1.2786820902430582,
+           1.2044780030085434,
+           1.1232489419606364,
+           1.0364497581887604,
+           0.9456160809168499,
+           0.8523208008460484,
+           0.758130201169903,
+           0.6645608872370339,
+           0.5730386390739894,
+           0.4848602556937596,
+           0.4011593777593931,
+           0.32287716788113974,
+           0.2507385983576576,
+           0.18523494783935482,
+           0.1266129449785128,
+           0.07487082279601061,
+           0.029761366669565657,
+           -0.009198143874810317,
+           -0.0427093793707856,
+           -0.07167024310099813,
+           -0.09714660574266475,
+           -0.12033925066576416,
+           -0.14254691434112848,
+           -0.16512640941854864,
+           -0.1894508958515048,
+           -0.21686741598383566,
+           -0.24865483146930945,
+           -0.2859832926818646,
+           -0.3298763350407716,
+           -0.3811766323006682,
+           -0.4405163459302993,
+           -0.5082928944848256,
+           -0.5846508302376756,
+           -0.6694703556945952,
+           -0.7623628438374359,
+           -0.8626735472723679,
+           -0.9694914973752187,
+           -1.081666409668252,
+           -1.1978322306874072,
+           -1.3164367890778652,
+           -1.4357768539566738,
+           -1.5540377607585798,
+           -1.6693366424765004,
+           -1.779768205555677,
+           -1.8834519172510955,
+           -1.9785794269122141,
+           -2.063461028621224,
+           -2.1365699873561654,
+           -2.1965835951121875,
+           -2.242419896190836,
+           -2.273269120444581,
+           -2.288618987257031,
+           -2.288273188451466,
+           -2.272362521615731,
+           -2.2413483225224855,
+           -2.196018032069188,
+           -2.1374729248743445,
+           -2.0671082186249734,
+           -1.9865859707377216,
+           -1.8978013472371242,
+           -1.8028430135487303,
+           -1.703948544058003,
+           -1.6034558731308262,
+           -1.503751911679573,
+           -1.407219527737717,
+           -1.3161841349854635,
+           -1.2328611485651824,
+           -1.1593055523938507,
+           -1.0973647768250672,
+           -1.0486360109830817,
+           -1.014428972151885,
+           -0.995735027693707,
+           -0.9932034161500146,
+           -1.007125147040324,
+           -1.0374249774690125,
+           -1.083661672379534,
+           -1.1450365588055584,
+           -1.2204101875366271,
+           -1.308326723032036,
+           -1.4070454988659893,
+           -1.5145790059349853,
+           -1.6287364282397718,
+           -1.7471717099732371,
+           -1.8674350310824965,
+           -1.9870264890088012,
+           -2.1034507338582378,
+           -2.214271284024227,
+           -2.3171632597339546,
+           -2.409963312837219,
+           -2.490715601366527,
+           -2.5577127552213277,
+           -2.6095309023423243,
+           -2.645057969904233,
+           -2.663514638788362,
+           -2.6644675078700937,
+           -2.6478342130901598,
+           -2.613880440248575,
+           -2.5632089652140193,
+           -2.496741046015593,
+           -2.415690673420508,
+           -2.3215323556637304,
+           -2.2159632648772694,
+           -2.1008607037920575,
+           -1.9782359582998146,
+           -1.8501856819104605,
+           -1.7188420101269335,
+           -1.5863226250961584,
+           -1.4546819831287245,
+           -1.325864880103001,
+           -1.2016634634109167,
+           -1.0836787057017818,
+           -0.9732872376427127,
+           -0.8716142972504507,
+           -0.7795133955998547,
+           -0.6975531268613523,
+           -0.626011368985629,
+           -0.5648769344959724,
+           -0.5138585434431847,
+           -0.47240080730490047,
+           -0.4397067380369306,
+           -0.4147661349490648,
+           -0.39638905758702603,
+           -0.3832434689273071,
+           -0.37389603298169133,
+           -0.3668549768144764,
+           -0.3606138807907291,
+           -0.35369524368889493,
+           -0.3446926814877241,
+           -0.33231065980044716,
+           -0.3154007289765048,
+           -0.29299332602211164,
+           -0.2643243262517799,
+           -0.228855666928936,
+           -0.1862895215256254,
+           -0.13657567264511286,
+           -0.07991190979773755,
+           -0.016737460574068122,
+           0.05228035430874338,
+           0.12626587471787548,
+           0.20416072883561273,
+           0.28475464657713895,
+           0.36672063443900854,
+           0.4486535727241432,
+           0.5291112053396209,
+           0.6066564279788902,
+           0.6798997441342955,
+           0.7475407509872434,
+           0.8084075390113363,
+           0.8614929395829668,
+           0.9059866327858773,
+           0.941302230991206,
+           0.9670985801185694,
+           0.9832946665828391,
+           0.9900776801497368,
+           0.9879039571954967,
+           0.9774927108163046,
+           0.9598126392872985,
+           0.9360616878678706,
+           0.9076404162597238,
+           0.8761195906638697,
+           0.8432027711271752,
+           0.8106847978587038,
+           0.7804071910321735,
+           0.7542115644218007,
+           0.7338922118119441,
+           0.7211490549184412,
+           0.7175421417197931,
+           0.7244488545137497,
+           0.7430249283256133,
+           0.7741702938609237,
+           0.8185006470726511,
+           0.876325512300746,
+           0.9476334111164334,
+           1.0320845782381465,
+           1.129011483357856,
+           1.2374272279041503,
+           1.356041693339835,
+           1.4832851272912926,
+           1.6173386703344876,
+           1.7561711541611427,
+           1.897581345388297,
+           2.0392446723481528,
+           2.1787633582214685,
+           2.313718795716062,
+           2.4417249383705046,
+           2.560481453023674,
+           2.667825377850625,
+           2.7617800606941216,
+           2.840600212540978,
+           2.9028119994921373,
+           2.9472472113455317,
+           2.9730706831942793,
+           2.979800304903209,
+           2.967319128129748,
+           2.9358792674621395,
+           2.8860974867209186,
+           2.818942558782109
+          ],
+          [
+           2.7627486193793755,
+           2.6704836588735756,
+           2.5649312229068784,
+           2.4481127277497987,
+           2.322249492004644,
+           2.189714223316968,
+           2.0529792102817392,
+           1.9145624282481493,
+           1.7769728154917455,
+           1.6426559936918481,
+           1.5139416934264798,
+           1.3929941018290117,
+           1.2817662767354003,
+           1.1819596713991014,
+           1.0949896886434813,
+           1.0219580362489848,
+           0.9636324900567581,
+           0.9204344917772588,
+           0.892434819229064,
+           0.8793573723405782,
+           0.8805909234854147,
+           0.895208490351982,
+           0.9219938082143342,
+           0.9594742105893255,
+           1.0059590769100804,
+           1.0595828766539923,
+           1.118351734442795,
+           1.180192362485884,
+           1.2430021572037226,
+           1.304699237073561,
+           1.3632712090753376,
+           1.4168214912269383,
+           1.4636120874942924,
+           1.502101807045276,
+           1.5309790399271863,
+           1.5491883427259816,
+           1.5559502470287563,
+           1.5507738765431296,
+           1.5334621411792029,
+           1.5041094636984045,
+           1.4630921819950746,
+           1.4110519530238408,
+           1.3488726582641328,
+           1.2776514711038502,
+           1.1986648896519612,
+           1.1133306607207947,
+           1.0231666190488606,
+           0.9297475378632372,
+           0.8346611308689716,
+           0.7394643606687118,
+           0.6456411941565693,
+           0.5545629020306309,
+           0.4674519283886259,
+           0.38535025926691824,
+           0.3090930984585961,
+           0.23928851809199955,
+           0.17630359386406141,
+           0.12025736451824558,
+           0.07102077646572821,
+           0.028223591909879955,
+           -0.008731942919192041,
+           -0.040651049170589995,
+           -0.06852053265815726,
+           -0.09347776566149785,
+           -0.11677536631628424,
+           -0.13974252173205337,
+           -0.16374398979041518,
+           -0.19013787687580047,
+           -0.22023332297624193,
+           -0.25524923077246287,
+           -0.29627515134925947,
+           -0.3442353865878979,
+           -0.3998572884266551,
+           -0.4636446299918167,
+           -0.5358567957259798,
+           -0.6164943902707132,
+           -0.7052917026876814,
+           -0.8017162877194298,
+           -0.9049757435920618,
+           -1.014031580931441,
+           -1.1276198943628368,
+           -1.244278371911779,
+           -1.3623790118852157,
+           -1.4801657666845522,
+           -1.5957962018089167,
+           -1.7073861495041627,
+           -1.8130562529020886,
+           -1.910979240253606,
+           -1.9994267414882743,
+           -2.076814461612022,
+           -2.141744557429143,
+           -2.1930441250468298,
+           -2.2297987941704576,
+           -2.251380539215126,
+           -2.2574689539953865,
+           -2.2480653928908576,
+           -2.2234995531121493,
+           -2.184428255804273,
+           -2.1318263737278937,
+           -2.0669700454747515,
+           -1.9914125058610195,
+           -1.9069530446108707,
+           -1.8155997761715574,
+           -1.719527058250102,
+           -1.6210285315757393,
+           -1.5224668650994895,
+           -1.4262213765351759,
+           -1.3346347556547422,
+           -1.2499601455936489,
+           -1.1743098348470664,
+           -1.1096067796379785,
+           -1.0575401136567248,
+           -1.0195257112795564,
+           -0.9966727534391296,
+           -0.9897571051509292,
+           -0.9992021536787157,
+           -1.025067580321716,
+           -1.0670463510939534,
+           -1.1244700167001407,
+           -1.1963222149294421,
+           -1.281260073686604,
+           -1.3776430251017695,
+           -1.4835683650755274,
+           -1.5969127325082613,
+           -1.7153785422269465,
+           -1.836544288664869,
+           -1.9579175465080478,
+           -2.0769894319927658,
+           -2.1912892558261374,
+           -2.298438096577464,
+           -2.3962000518770497,
+           -2.482529983134192,
+           -2.555616656289786,
+           -2.6139202941995427,
+           -2.656203692805747,
+           -2.6815562099334795,
+           -2.689410108484163,
+           -2.6795489207467766,
+           -2.6521076929660214,
+           -2.6075651644825957,
+           -2.5467281289183044,
+           -2.470708411300253,
+           -2.3808930701600057,
+           -2.2789085932471687,
+           -2.1665799956944443,
+           -2.0458858468806143,
+           -1.9189103440445872,
+           -1.7877936147310929,
+           -1.6546814649090051,
+           -1.521675794335674,
+           -1.3907868754272783,
+           -1.2638886372604203,
+           -1.1426780138238781,
+           -1.02863930739604,
+           -0.9230143867127077,
+           -0.8267793887424024,
+           -0.7406284262139056,
+           -0.6649646247390655,
+           -0.5998986279178049,
+           -0.5452545208449189,
+           -0.5005829366546889,
+           -0.4651809317700005,
+           -0.43811804781776065,
+           -0.4182678258921797,
+           -0.404343905758056,
+           -0.394939731966646,
+           -0.388570803418117,
+           -0.38371834472268235,
+           -0.3788732481769532,
+           -0.37257913495242895,
+           -0.363473413122901,
+           -0.35032526763701277,
+           -0.33206960175837114,
+           -0.30783605866158176,
+           -0.2769723829821299,
+           -0.23906153181696577,
+           -0.19393210914268788,
+           -0.14166187267325403,
+           -0.08257424337008683,
+           -0.01722793054388073,
+           0.05360003488670969,
+           0.12893739444536442,
+           0.2076452589725038,
+           0.2884514399642546,
+           0.3699876228703382,
+           0.4508293885827676,
+           0.5295380135477477,
+           0.6047029305345908,
+           0.6749837123465467,
+           0.7391504501863042,
+           0.796121436786124,
+           0.8449971308420804,
+           0.8850894721094615,
+           0.9159457334121354,
+           0.937366233874063,
+           0.9494153934416257,
+           0.9524257783265658,
+           0.946994966104398,
+           0.9339752433488256,
+           0.9144563332319655,
+           0.8897415308180874,
+           0.8613177952681533,
+           0.8308205065097661,
+           0.799993735088739,
+           0.7706469943036546,
+           0.7446095402449685,
+           0.7236833555175711,
+           0.7095959943754837,
+           0.7039544795957474,
+           0.7082014242513137,
+           0.7235745049372485,
+           0.7510703380223744,
+           0.791413708910469,
+           0.8450329785378886,
+           0.9120423444514703,
+           0.9922314693768706,
+           1.0850628122221113,
+           1.1896768093278,
+           1.3049048620753545,
+           1.4292898954211608,
+           1.561114065269144,
+           1.6984330154460787,
+           1.8391159217973534,
+           1.9808904156367646,
+           2.1213913550856858,
+           2.2582123138255286,
+           2.3889585849578197,
+           2.511300454851304,
+           2.623025489174691,
+           2.7220885911478514,
+           2.8066586400250593,
+           2.8751605948396883,
+           2.926312052666626,
+           2.9591533795998743,
+           2.9730706831942797,
+           2.96781106364282,
+           2.9434897633724324,
+           2.9005890266149126,
+           2.8399486771836586,
+           2.762748619379375
+          ],
+          [
+           2.7001014815090043,
+           2.599574192969197,
+           2.487042058080666,
+           2.3646587489694975,
+           2.2347484438965624,
+           2.099755150146037,
+           1.9621894480592728,
+           1.8245738973052585,
+           1.6893883764498052,
+           1.5590166262293494,
+           1.435695235693345,
+           1.3214662493423754,
+           1.2181344840767174,
+           1.12723052939308,
+           1.049980265672916,
+           0.9872815770072116,
+           0.9396887606948992,
+           0.9074049496148499,
+           0.8902826706643343,
+           0.8878324671062661,
+           0.8992393197501046,
+           0.9233864161161915,
+           0.9588856426261338,
+           1.0041140166533744,
+           1.0572551367899792,
+           1.116344614276674,
+           1.1793183589670817,
+           1.2440625315755591,
+           1.3084639417185215,
+           1.3704596691012547,
+           1.4280847130808634,
+           1.4795165329639894,
+           1.523115426266344,
+           1.5574598025779471,
+           1.5813755438232304,
+           1.5939587942022488,
+           1.5945916910987863,
+           1.5829507275182262,
+           1.5590076226767682,
+           1.5230227655499833,
+           1.4755314818060308,
+           1.4173235529750303,
+           1.3494165835081235,
+           1.2730239624241684,
+           1.1895182977973089,
+           1.1003913111675938,
+           1.007211262396776,
+           0.9115790315197363,
+           0.8150840114259444,
+           0.719260963134372,
+           0.6255489541254965,
+           0.5352534405243311,
+           0.4495124674580169,
+           0.36926785088046626,
+           0.29524207141840714,
+           0.22792145974393216,
+           0.1675460874704507,
+           0.11410660181400113,
+           0.0673480607262898,
+           0.0267806424978747,
+           -0.008303075415743943,
+           -0.0388047448305586,
+           -0.06579141790775794,
+           -0.09046203875057261,
+           -0.11411015592727845,
+           -0.13808385573452572,
+           -0.16374398979041516,
+           -0.19242181680156784,
+           -0.22537719589124885,
+           -0.263758457237676,
+           -0.30856503521918405,
+           -0.36061388079072887,
+           -0.4205105751230392,
+           -0.4886259479821965,
+           -0.5650788648772539,
+           -0.6497256901496984,
+           -0.742156762856498,
+           -0.8417000427872542,
+           -0.9474318997726119,
+           -1.0581948352261599,
+           -1.1726217452656456,
+           -1.2891661643228205,
+           -1.406137771195047,
+           -1.5217423000066637,
+           -1.6341248800943458,
+           -1.7414157344501402,
+           -1.8417770984936153,
+           -1.9334501813884608,
+           -2.0148009819531207,
+           -2.084363790792675,
+           -2.1408812592118225,
+           -2.1833399926356174,
+           -2.2110007298385153,
+           -2.223422296775088,
+           -2.2204786721283853,
+           -2.2023686672304654,
+           -2.169617901714533,
+           -2.1230729437437645,
+           -2.0638876753150424,
+           -1.993502134229682,
+           -1.913614270134641,
+           -1.8261452279635206,
+           -1.733198933779331,
+           -1.6370169014149205,
+           -1.5399292998407192,
+           -1.4443034178134575,
+           -1.3524907316329031,
+           -1.2667738219844749,
+           -1.1893143958169838,
+           -1.1221036486796907,
+           -1.0669161523547248,
+           -1.0252683731424668,
+           -0.998382819672831,
+           -0.987158688174872,
+           -0.9921497208936256,
+           -1.0135498234766949,
+           -1.0511868037789476,
+           -1.1045244021024179,
+           -1.1726725860759928,
+           -1.2544058869721826,
+           -1.3481893630355282,
+           -1.4522115940135831,
+           -1.5644239439519416,
+           -1.6825851805070005,
+           -1.80431041216277,
+           -1.9271232028938832,
+           -2.0485096494645036,
+           -2.1659731614885067,
+           -2.2770886696780366,
+           -2.3795550037097084,
+           -2.471244227423188,
+           -2.550246794476508,
+           -2.6149114902457793,
+           -2.6638792531365563,
+           -2.696110117430323,
+           -2.710902686656818,
+           -2.707905727161351,
+           -2.6871216615922466,
+           -2.6489019368099815,
+           -2.5939344354500005,
+           -2.5232232902981777,
+           -2.438061641129622,
+           -2.3399980403264165,
+           -2.2307973623841564,
+           -2.11239719974468,
+           -1.9868608301924562,
+           -1.8563279168743931,
+           -1.7229641490678451,
+           -1.5889110490618663,
+           -1.4562371576049784,
+           -1.3268917677258274,
+           -1.2026623055031822,
+           -1.0851363584050426,
+           -0.9756692296471061,
+           -0.875357753746498,
+           -0.7850209476920658,
+           -0.7051878979670312,
+           -0.6360931004181221,
+           -0.5776792822559992,
+           -0.5296075479853867,
+           -0.49127450847343157,
+           -0.46183587921339,
+           -0.4402358744240696,
+           -0.42524158188849775,
+           -0.4154813828731998,
+           -0.40948638504120505,
+           -0.4057337663275138,
+           -0.40269088596797653,
+           -0.398859006236028,
+           -0.39281548518926346,
+           -0.38325334636545116,
+           -0.3690172046770726,
+           -0.34913462682436447,
+           -0.3228421268241315,
+           -0.28960513960063144,
+           -0.24913147437021368,
+           -0.20137792072803237,
+           -0.14654985956047584,
+           -0.08509391360921084,
+           -0.017683854066080456,
+           0.05479984462180104,
+           0.1312962439680213,
+           0.210595265734862,
+           0.2913732594075666,
+           0.37223185965081523,
+           0.4517390936728939,
+           0.5284716382149798,
+           0.6010570938798752,
+           0.6682151415495459,
+           0.7287964718153236,
+           0.7818184330261886,
+           0.8264964253983783,
+           0.8622701755874406,
+           0.888824155531372,
+           0.9061015579921324,
+           0.9143114053269646,
+           0.9139285434901155,
+           0.9056864556883151,
+           0.8905630148961841,
+           0.8697594769209751,
+           0.844673191279469,
+           0.8168646713682797,
+           0.788019814104335,
+           0.7599081885966606,
+           0.7343384201727964,
+           0.7131117774709157,
+           0.6979751241987503,
+           0.690574422112241,
+           0.6924099670590992,
+           0.7047945055832983,
+           0.7288153163522489,
+           0.7653012500277184,
+           0.814795605318646,
+           0.8775355806260794,
+           0.9534388832792801,
+           1.0420979057114494,
+           1.1427816942637956,
+           1.2544457461515013,
+           1.3757494781591237,
+           1.5050810215952282,
+           1.6405888166051557,
+           1.7802193096150591,
+           1.921759904670363,
+           2.0628861865522983,
+           2.201212324133268,
+           2.334343479219401,
+           2.4599289912397717,
+           2.5757150829951994,
+           2.6795958379644067,
+           2.7696612353237176,
+           2.8442410940625455,
+           2.901943870837696,
+           2.941689375281103,
+           2.9627346084975907,
+           2.964692092034491,
+           2.947540231763966,
+           2.9116254495955616,
+           2.857656011153438,
+           2.7866876747641274,
+           2.700101481509005
+          ],
+          [
+           2.6315311683055342,
+           2.523586211089698,
+           2.4050089131261436,
+           2.278066993475516,
+           2.1451678466476896,
+           2.0088061304046927,
+           1.871509512472339,
+           1.7357838391389162,
+           1.6040590006427904,
+           1.478636749474563,
+           1.3616416787256214,
+           1.2549764896256952,
+           1.160282572358161,
+           1.0789067947157893,
+           1.0118752423507609,
+           0.9598744859885594,
+           0.9232407691500377,
+           0.9019573191179145,
+           0.8956597887660501,
+           0.9036496422139699,
+           0.9249151078283345,
+           0.9581591424848357,
+           1.0018336855961802,
+           1.0541793342154009,
+           1.1132694450941596,
+           1.1770575689258889,
+           1.2434270485300296,
+           1.3102415681581896,
+           1.3753954264311474,
+           1.436862320912745,
+           1.4927414775124501,
+           1.5413000315697576,
+           1.5810106676960751,
+           1.6105836496657508,
+           1.6289925167012187,
+           1.6354928847227312,
+           1.629633966447652,
+           1.6112626082294559,
+           1.5805198296179053,
+           1.5378300391038675,
+           1.4838832817149923,
+           1.4196110465240144,
+           1.3461563204460423,
+           1.2648387150214142,
+           1.1771156117505566,
+           1.084540366053377,
+           0.9887186777696659,
+           0.8912642756713576,
+           0.7937550738062034,
+           0.6976909384521659,
+           0.6044541565863216,
+           0.5152736213370643,
+           0.43119364885910505,
+           0.353048217052361,
+           0.2814412727169948,
+           0.21673359377073403,
+           0.15903652112543032,
+           0.1082126951015094,
+           0.06388374841477427,
+           0.025444726438517497,
+           -0.007915169777610002,
+           -0.03718608692087035,
+           -0.06350598839552743,
+           -0.08812493942418749,
+           -0.11236616838465922,
+           -0.13758494941343974,
+           -0.16512640941854848,
+           -0.19628339246354018,
+           -0.2322555152363663,
+           -0.27411051895858324,
+           -0.32274896631286265,
+           -0.3788732481769538,
+           -0.44296175623865036,
+           -0.5152489466470648,
+           -0.5957118700104875,
+           -0.6840635780403201,
+           -0.7797536411103824,
+           -0.8819758283801798,
+           -0.9896828175210963,
+           -1.1016076191439417,
+           -1.2162912263544705,
+           -1.3321158368847765,
+           -1.4473428481025277,
+           -1.5601546976375018,
+           -1.6686995176526476,
+           -1.7711374916272227,
+           -1.8656877509802208,
+           -1.9506746263254382,
+           -2.0245720752754983,
+           -2.0860451454222027,
+           -2.133987396597769,
+           -2.1675532992299207,
+           -2.186184743325481,
+           -2.1896309325067573,
+           -2.177961096178919,
+           -2.1515696264473814,
+           -2.1111734305754366,
+           -2.0578014800445894,
+           -1.9927767289618195,
+           -1.9176907629128863,
+           -1.8343717197241949,
+           -1.7448461914904712,
+           -1.651295968473889,
+           -1.5560106163062921,
+           -1.4613369850512423,
+           -1.3696268294061424,
+           -1.2831837715921337,
+           -1.204210860933197,
+           -1.1347599761410938,
+           -1.0766842780216006,
+           -1.0315948525686405,
+           -1.000822588810173,
+           -0.9853862145931682,
+           -0.9859672696564115,
+           -1.0028926323099423,
+           -1.0361250377650675,
+           -1.0852618369624845,
+           -1.149542049223859,
+           -1.227861564958259,
+           -1.3187961607851304,
+           -1.4206318035096592,
+           -1.5314015459318124,
+           -1.6489281607103707,
+           -1.7708715222538993,
+           -1.8947796341854544,
+           -2.018142114058466,
+           -2.1384448897674595,
+           -2.253224834878894,
+           -2.3601230735480607,
+           -2.4569357196808035,
+           -2.541660878689364,
+           -2.6125408319980052,
+           -2.6680984421080134,
+           -2.7071669566330763,
+           -2.7289125498058597,
+           -2.732849115601733,
+           -2.7188450135165536,
+           -2.687121661592246,
+           -2.638244066769741,
+           -2.5731035752863813,
+           -2.4928933109244253,
+           -2.399076941952178,
+           -2.2933515743773447,
+           -2.177605705858376,
+           -2.053873287999707,
+           -1.9242850320778893,
+           -1.791018152441971,
+           -1.6562457715358965,
+           -1.5220872100650433,
+           -1.3905603553821333,
+           -1.2635372415483994,
+           -1.1427038873031838,
+           -1.0295253255971564,
+           -0.9252166232819756,
+           -0.8307205354238558,
+           -0.7466922694066368,
+           -0.6734916537652222,
+           -0.6111828200587905,
+           -0.5595413177188795,
+           -0.5180683963881056,
+           -0.4860120124139393,
+           -0.46239395029335195,
+           -0.44604230008444046,
+           -0.4356284018066294,
+           -0.4297072608362974,
+           -0.42676035688353803,
+           -0.42523971527733684,
+           -0.42361208426625097,
+           -0.42040206641111244,
+           -0.4142330857193417,
+           -0.4038651340296208,
+           -0.38822832867506957,
+           -0.3664514263404147,
+           -0.33788457238278075,
+           -0.30211571726990444,
+           -0.25898029831797714,
+           -0.20856396134637858,
+           -0.1511982787258723,
+           -0.08744960296472284,
+           -0.018101373821361733,
+           0.05586963258073846,
+           0.13332246635149295,
+           0.2129857907305838,
+           0.2934953849924462,
+           0.3734343575217481,
+           0.45137499147781324,
+           0.5259211013591727,
+           0.5957497634426019,
+           0.6596512969150488,
+           0.7165664152165507,
+           0.765619537615525,
+           0.806147347591579,
+           0.8377218047942403,
+           0.8601669581704403,
+           0.8735690657781663,
+           0.878279697863042,
+           0.8749116796673081,
+           0.8643279146376915,
+           0.8476233125553467,
+           0.8261002259842766,
+           0.8012379677981687,
+           0.774657138103564,
+           0.7480796266728608,
+           0.72328527351318,
+           0.7020662624331027,
+           0.6861803880359837,
+           0.677304373735403,
+           0.6769884261309222,
+           0.686613189108508,
+           0.7073502097893266,
+           0.7401269491226863,
+           0.7855972643865159,
+           0.8441181616614126,
+           0.9157334666159621,
+           1.0001648953335451,
+           1.0968108275039599,
+           1.2047528965030347,
+           1.3227703193151534,
+           1.4493616986458195,
+           1.5827738446387287,
+           1.721036988940289,
+           1.8620056037840398,
+           2.003403897288217,
+           2.1428749368094433,
+           2.278032257973357,
+           2.4065127502940915,
+           2.5260295728102977,
+           2.6344238459001414,
+           2.729713888643685,
+           2.810140824281617,
+           2.874209458239169,
+           2.920723441900486,
+           2.9488138682279317,
+           2.957960599221681,
+           2.948005796387481,
+           2.919159309676996,
+           2.87199577331246,
+           2.8074434538159303,
+           2.7267650916436734,
+           2.631531168305535
+          ],
+          [
+           2.5576178156470863,
+           2.4431626059467315,
+           2.3195258255700475,
+           2.1890700667025493,
+           2.05426559264643,
+           1.9176366339548454,
+           1.7817065968091406,
+           1.6489434578191675,
+           1.52170661320201,
+           1.4021964135571416,
+           1.29240754912487,
+           1.1940873561331304,
+           1.1086999949311565,
+           1.0373973080293368,
+           0.980997004417041,
+           0.9399686395848961,
+           0.914427672873444,
+           0.9041376897055375,
+           0.908520680681897,
+           0.9266750772049248,
+           0.9574010589345354,
+           0.9992324764579981,
+           1.050474577246736,
+           1.109246588034017,
+           1.1735280954276046,
+           1.2412080815323787,
+           1.310135414608424,
+           1.378169567637932,
+           1.4432303406940912,
+           1.5033453960261662,
+           1.5566944768854885,
+           1.6016492706886871,
+           1.6368079918430942,
+           1.6610238965235091,
+           1.6734270974236778,
+           1.6734392170872368,
+           1.660780599569093,
+           1.6354699873547305,
+           1.5978167589975076,
+           1.548406008125424,
+           1.4880769217154972,
+           1.4178950804402664,
+           1.3391194523786794,
+           1.2531649797924818,
+           1.1615617638479392,
+           1.0659119315464447,
+           0.9678453208014649,
+           0.8689751423451094,
+           0.7708547704734654,
+           0.6749367787914523,
+           0.5825352730717307,
+           0.4947924827801261,
+           0.41265045808659695,
+           0.33682858322425585,
+           0.26780746335630545,
+           0.20581957458110503,
+           0.15084688961090148,
+           0.10262550949858125,
+           0.060657149180956105,
+           0.02422714618617944,
+           -0.007571507862018121,
+           -0.035808770019892244,
+           -0.0616835798893077,
+           -0.08648624060019319,
+           -0.11155815861220045,
+           -0.13825002374202952,
+           -0.16787955277920924,
+           -0.20168993318423442,
+           -0.24081008731745976,
+           -0.2862178328086648,
+           -0.338706942154941,
+           -0.3988590062360277,
+           -0.4670208846219753,
+           -0.5432883833706723,
+           -0.627496642040662,
+           -0.7192175398729524,
+           -0.8177642508465269,
+           -0.9222028931270899,
+           -1.031371034954606,
+           -1.1439026408883333,
+           -1.2582588740586353,
+           -1.3727640159328243,
+           -1.4856456290115128,
+           -1.595077973311304,
+           -1.6992275974048772,
+           -1.7962999615204454,
+           -1.8845859154221754,
+           -1.9625068484662234,
+           -2.028657353584429,
+           -2.0818443004796174,
+           -2.121121294784207,
+           -2.1458176073995103,
+           -2.155560789106617,
+           -2.150292336642611,
+           -2.1302759440789423,
+           -2.096098053413458,
+           -2.04866060636712,
+           -1.9891660908253157,
+           -1.9190951654524429,
+           -1.8401773300307382,
+           -1.7543552824638138,
+           -1.6637437618285156,
+           -1.5705838164032306,
+           -1.4771935527519953,
+           -1.385916513753855,
+           -1.2990688976070082,
+           -1.2188868646565674,
+           -1.147475183461462,
+           -1.0867584416425928,
+           -1.0384359913010632,
+           -1.0039417144589848,
+           -0.9844095830571378,
+           -0.9806458532005725,
+           -0.9931085778235369,
+           -1.021894949508074,
+           -1.0667368000155524,
+           -1.1270043896724662,
+           -1.201718422792913,
+           -1.2895700296122976,
+           -1.3889482655148992,
+           -1.4979744992820074,
+           -1.6145428980293697,
+           -1.736366071438444,
+           -1.8610248153477569,
+           -1.9860207977388986,
+           -2.108830960983642,
+           -2.22696237458779,
+           -2.3380062635252115,
+           -2.4396899588059764,
+           -2.5299255686184585,
+           -2.6068542489419704,
+           -2.6688850599528786,
+           -2.7147275261963655,
+           -2.7434171711296123,
+           -2.7543334665111927,
+           -2.7472098200484787,
+           -2.7221354162371227,
+           -2.6795489207467766,
+           -2.6202242532485824,
+           -2.545248822494794,
+           -2.4559947961470217,
+           -2.354084141963739,
+           -2.241348322522487,
+           -2.119783649153534,
+           -1.9915033992352593,
+           -1.8586878721048339,
+           -1.7235336009074216,
+           -1.5882029497995767,
+           -1.454775307834579,
+           -1.3252010431330365,
+           -1.2012593048547024,
+           -1.0845206580098907,
+           -0.9763154099020511,
+           -0.8777083401805602,
+           -0.7894803828103603,
+           -0.7121176318483351,
+           -0.6458078581771399,
+           -0.5904445359049418,
+           -0.5456381896939522,
+           -0.5107346924971137,
+           -0.48483997157418174,
+           -0.4668504234760196,
+           -0.45548819981034894,
+           -0.44934040844997747,
+           -0.44690118228249787,
+           -0.4466155018752974,
+           -0.44692362111292894,
+           -0.44630493681295186,
+           -0.4433201646647805,
+           -0.4366507339506047,
+           -0.42513439106483075,
+           -0.4077961048288481,
+           -0.3838734923466749,
+           -0.35283612944131965,
+           -0.3143982708417658,
+           -0.2685246781530147,
+           -0.21542943384237492,
+           -0.15556780243987112,
+           -0.08962138123871359,
+           -0.018476957403665038,
+           0.05680034787330479,
+           0.13499891883753906,
+           0.21479660903648065,
+           0.2947998625761726,
+           0.37358494280701215,
+           0.4497401624668544,
+           0.5219079816762576,
+           0.5888258416398648,
+           0.6493646324438471,
+           0.7025637522029743,
+           0.7476618005393902,
+           0.7841220598279909,
+           0.8116520500550354,
+           0.8302165941865441,
+           0.840043996837415,
+           0.8416251155995361,
+           0.8357052871814141,
+           0.8232692549247658,
+           0.8055194256385535,
+           0.7838479574408306,
+           0.7598033420195008,
+           0.7350522903045523,
+           0.7113378562741545,
+           0.6904348362719609,
+           0.674103558142366,
+           0.6640432236813848,
+           0.6618459880300701,
+           0.668952950105263,
+           0.6866131891085077,
+           0.715846914455346,
+           0.75741370171675,
+           0.8117866676332416,
+           0.8791332958435008,
+           0.9593034651073216,
+           1.0518250574085244,
+           1.1559073386781573,
+           1.2704521145265957,
+           1.3940724720125695,
+           1.5251187308402199,
+           1.661711048112311,
+           1.8017779543333763,
+           1.9430999488956306,
+           2.0833571545290472,
+           2.2201799253857026,
+           2.3512012252042487,
+           2.474109542359346,
+           2.586701088838457,
+           2.6869300408659367,
+           2.772955619825103,
+           2.8431848823817463,
+           2.896310186633155,
+           2.9313404243590164,
+           2.947625255072912,
+           2.9448717420508834,
+           2.923152969865058,
+           2.882908412825282,
+           2.824936019517114,
+           2.750376175558906,
+           2.6606878999907737,
+           2.5576178156470872
+          ],
+          [
+           2.478986763943325,
+           2.3589837976319044,
+           2.23131602101464,
+           2.098420922922664,
+           1.9628107560953758,
+           1.8270179959911292,
+           1.6935404743724713,
+           1.5647874622676983,
+           1.4430279525900938,
+           1.3303423383085933,
+           1.2285785989563156,
+           1.1393139984866756,
+           1.0638231637421196,
+           1.0030532583743474,
+           0.9576067957372374,
+           0.9277324502642945,
+           0.9133240346475895,
+           0.9139276144559182,
+           0.9287565374466467,
+           0.9567139664799796,
+           0.996422327222289,
+           1.0462589190443699,
+           1.1043967936241839,
+           1.1688498842237005,
+           1.2375212723411433,
+           1.3082534097310554,
+           1.3788790742393626,
+           1.4472718284014172,
+           1.51139477043704,
+           1.5693464175421243,
+           1.6194026398862205,
+           1.6600536684494904,
+           1.6900353280965408,
+           1.7083537958383337,
+           1.7143033493308188,
+           1.7074767481530502,
+           1.6877680758528888,
+           1.6553680595126867,
+           1.6107520709660748,
+           1.5546611951310503,
+           1.4880769217154974,
+           1.4121901725733381,
+           1.3283655143941044,
+           1.238101521819833,
+           1.1429883466809097,
+           1.0446636126321884,
+           0.9447677895374262,
+           0.8449002076948801,
+           0.746576848356431,
+           0.6511909946393357,
+           0.559977747254665,
+           0.4739833045535292,
+           0.39403977892531744,
+           0.32074617483780443,
+           0.25445599153289955,
+           0.19527173971603942,
+           0.14304648091532765,
+           0.09739231512364778,
+           0.05769556151440621,
+           0.02313820302075664,
+           -0.007274997204282997,
+           -0.03468444685184957,
+           -0.06033961078971066,
+           -0.0855598064121604,
+           -0.11169296273820577,
+           -0.1400734518905255,
+           -0.17198012703375462,
+           -0.2085956971826658,
+           -0.2509685365837351,
+           -0.2999779654341269,
+           -0.3563039510487286,
+           -0.4204020664111123,
+           -0.4924844091600111,
+           -0.5725070318303476,
+           -0.6601642674136285,
+           -0.7548901572231419,
+           -0.8558670051065665,
+           -0.962040897857271,
+           -1.07214385088952,
+           -1.1847220654366613,
+           -1.298169623087985,
+           -1.4107667994787065,
+           -1.5207220550633065,
+           -1.6262166603129073,
+           -1.7254508379822167,
+           -1.816690258248364,
+           -1.8983117047967828,
+           -1.9688467418573625,
+           -2.0270222535768094,
+           -2.0717967970140383,
+           -2.102391806814456,
+           -2.118316810932786,
+           -2.1193879596921112,
+           -2.1057393315045783,
+           -2.077826653792997,
+           -2.036423262737735,
+           -1.9826083158697607,
+           -1.9177474625366064,
+           -1.8434663641554903,
+           -1.7616176343006495,
+           -1.6742419336205714,
+           -1.5835241022318616,
+           -1.4917453388965387,
+           -1.401232538774827,
+           -1.3143059772638863,
+           -1.2332265744469044,
+           -1.160143991753561,
+           -1.097046799073868,
+           -1.0457159070242807,
+           -1.0076823863312807,
+           -0.9841906960873529,
+           -0.9761682173390022,
+           -0.984201841097463,
+           -1.008522193977676,
+           -1.0489959042858787,
+           -1.10512612086753,
+           -1.176061301024246,
+           -1.2606120870791073,
+           -1.3572758985037368,
+           -1.4642686826112856,
+           -1.5795630961483702,
+           -1.700932236845619,
+           -1.825997911845296,
+           -1.9522823221341685,
+           -2.0772619612923426,
+           -2.1984224749872516,
+           -2.313313205949298,
+           -2.419600158177078,
+           -2.5151161535980764,
+           -2.597907023372379,
+           -2.666272772768334,
+           -2.7188027806765747,
+           -2.7544042393595474,
+           -2.772323203408114,
+           -2.772157795087898,
+           -2.753863301939144,
+           -2.7177490970271183,
+           -2.6644675078700932,
+           -2.594994952022953,
+           -2.510605840888274,
+           -2.4128399240977516,
+           -2.3034639006116806,
+           -2.1844282558042734,
+           -2.0578203930341328,
+           -1.9258152109329805,
+           -1.790624331929716,
+           -1.654445212113835,
+           -1.5194113569205037,
+           -1.3875448315223264,
+           -1.2607121902147411,
+           -1.1405848571702535,
+           -1.028604874071336,
+           -0.9259567912842689,
+           -0.8335463219156415,
+           -0.7519862062585035,
+           -0.6815895520961058,
+           -0.6223707286405198,
+           -0.5740537032246977,
+           -0.5360875249355455,
+           -0.5076684827658673,
+           -0.48776830195001775,
+           -0.47516759498169064,
+           -0.4684936570157955,
+           -0.4662615920375858,
+           -0.46691767885602803,
+           -0.4688838365052973,
+           -0.4706020281788416,
+           -0.4705774518069014,
+           -0.4674194035152482,
+           -0.45987876643491427,
+           -0.4468811699321146,
+           -0.42755498089762733,
+           -0.4012534262811572,
+           -0.36757030106137617,
+           -0.32634888435507875,
+           -0.2776838641030408,
+           -0.22191625321204347,
+           -0.15962146255461956,
+           -0.09159087420424424,
+           -0.018807427205930576,
+           0.05758411622697142,
+           0.1363114178795243,
+           0.2160124003102801,
+           0.29527565568810454,
+           0.3726823414869535,
+           0.44684843803321833,
+           0.5164662319747093,
+           0.5803439079832253,
+           0.6374421779721363,
+           0.6869069516399665,
+           0.7280971523794173,
+           0.7606069060086499,
+           0.7842814732916185,
+           0.7992264572116813,
+           0.8058099884233844,
+           0.8046577728887839,
+           0.7966410698539589,
+           0.7828578513899646,
+           0.7646075720813472,
+           0.7433601446018844,
+           0.7207198696269349,
+           0.6983852029050223,
+           0.6781053549116298,
+           0.6616348064370569,
+           0.6506868844321542,
+           0.6468875748347399,
+           0.651730752020818,
+           0.6665359777985347,
+           0.6924099670590985,
+           0.7302127336150795,
+           0.7805293203851499,
+           0.8436478855655878,
+           0.9195447639852014,
+           1.007876954197272,
+           1.107982301156574,
+           1.2188874560080318,
+           1.3393235032207642,
+           1.467748955767337,
+           1.6023796359695122,
+           1.7412247875550968,
+           1.882128607681488,
+           2.022816250094578,
+           2.1609432356573346,
+           2.2941471170968137,
+           2.4201001832538336,
+           2.536561955966396,
+           2.641430230844477,
+           2.73278944172385,
+           2.808955186895758,
+           2.868513841939971,
+           2.910356297081598,
+           2.9337049937374466,
+           2.93813359202119,
+           2.923578774639638,
+           2.8903438786256337,
+           2.8390942401999055,
+           2.770844335021413,
+           2.686936991379657,
+           2.5890151427470824,
+           2.478986763943326
+          ],
+          [
+           2.39630326747262,
+           2.271761976954905,
+           2.141125794321851,
+           2.006886494911444,
+           1.8715770862955328,
+           1.7377168911961185,
+           1.6077570704537707,
+           1.4840278502878959,
+           1.3686886758783174,
+           1.2636824417198607,
+           1.1706948500213121,
+           1.0911198240772468,
+           1.0260317570899076,
+           0.9761652119517616,
+           0.9419025080609709,
+           0.9232694417253463,
+           0.9199391917512668,
+           0.9312442661756771,
+           0.9561961545552402,
+           0.9935121674431144,
+           1.041648775104555,
+           1.098840605259963,
+           1.1631441283778887,
+           1.2324849519278873,
+           1.304707564600844,
+           1.3776263197070004,
+           1.4490764249555064,
+           1.5169637140534566,
+           1.5793120137396117,
+           1.6343069869527913,
+           1.680335427079892,
+           1.716019097218819,
+           1.7402423491060663,
+           1.752172915244997,
+           1.7512754408347926,
+           1.7373175050051963,
+           1.710368069037707,
+           1.6707884780088875,
+           1.6192163269310567,
+           1.5565426784081737,
+           1.4838832817149927,
+           1.4025445890252843,
+           1.3139854896738794,
+           1.2197757847742092,
+           1.121552499763268,
+           1.0209751797035966,
+           0.9196813303347452,
+           0.8192431565618425,
+           0.7211267096620955,
+           0.6266544860748327,
+           0.5369724260109335,
+           0.45302214172133104,
+           0.37551906614239944,
+           0.304937056345329,
+           0.24149981674001306,
+           0.18517932863144543,
+           0.13570129002599857,
+           0.09255738716916839,
+           0.055024041786917305,
+           0.022187109894180983,
+           -0.00702814641874167,
+           -0.03382262969950601,
+           -0.05948545168347183,
+           -0.0853534749125361,
+           -0.11276944025876963,
+           -0.14303980683168085,
+           -0.17739343946846015,
+           -0.21694225857051383,
+           -0.2626449179576488,
+           -0.3152744998864271,
+           -0.37539111433624656,
+           -0.4433201646647803,
+           -0.5191368969127899,
+           -0.6026576890385326,
+           -0.6934383632364628,
+           -0.7907796236060627,
+           -0.8937395373477685,
+           -1.0011527950238028,
+           -1.1116563088531193,
+           -1.2237205419862467,
+           -1.3356858104459115,
+           -1.4458026667771697,
+           -1.5522753638212465,
+           -1.6533073112598613,
+           -1.7471473789032301,
+           -1.8321358706739457,
+           -1.906748992714944,
+           -1.9696406681319325,
+           -2.019680608938596,
+           -2.0559876414513307,
+           -2.0779573926319297,
+           -2.085283579012107,
+           -2.0779722935872025,
+           -2.0563488556765908,
+           -2.021056970050478,
+           -1.9730501301524812,
+           -1.9135753913499691,
+           -1.8441498290910825,
+           -1.7665301789523562,
+           -1.6826763262971645,
+           -1.594709468377385,
+           -1.5048659073205068,
+           -1.415447545148338,
+           -1.3287702389257854,
+           -1.247111233124178,
+           -1.1726569157737565,
+           -1.1074521441693266,
+           -1.0533523547214376,
+           -1.0119796107009869,
+           -0.9846836525264632,
+           -0.9725089000066068,
+           -0.9761682173390017,
+           -0.996024093017129,
+           -1.032077711951424,
+           -1.0839662103026135,
+           -1.1509682092952274,
+           -1.2320175273492824,
+           -1.325724775032894,
+           -1.4304063493444998,
+           -1.5441201672627765,
+           -1.6647073176599967,
+           -1.7898386694825532,
+           -1.9170653560022144,
+           -2.0438719628112287,
+           -2.1677311833150275,
+           -2.286158671320203,
+           -2.396766816744468,
+           -2.4973161975640794,
+           -2.5857635181856753,
+           -2.6603049300733876,
+           -2.719413742569695,
+           -2.761871667663746,
+           -2.786792898650282,
+           -2.793640495355377,
+           -2.7822347336506175,
+           -2.7527532698061985,
+           -2.705723166131888,
+           -2.642005018539551,
+           -2.56276961439761,
+           -2.469467725767341,
+           -2.3637938045219546,
+           -2.247644488043763,
+           -2.123072943743766,
+           -1.9922401746856353,
+           -1.8573644748901526,
+           -1.7206702599015202,
+           -1.5843375050932582,
+           -1.4504530009029852,
+           -1.3209645813800244,
+           -1.1976394015044747,
+           -1.0820272317779631,
+           -0.9754296083218205,
+           -0.8788755264448509,
+           -0.7931041991452813,
+           -0.7185552234682226,
+           -0.6553663115187665,
+           -0.603378553876664,
+           -0.5621489958794693,
+           -0.5309701263892405,
+           -0.5088957087161687,
+           -0.494772228541383,
+           -0.48727509777586403,
+           -0.48494863964778556,
+           -0.4862487916993802,
+           -0.4895874019383079,
+           -0.49337696058603153,
+           -0.4960746064366959,
+           -0.4962242727878125,
+           -0.49249589249681075,
+           -0.48372066350664866,
+           -0.46892148304172526,
+           -0.44733778784887207,
+           -0.41844418603826616,
+           -0.381962429483756,
+           -0.3378664502118064,
+           -0.2863803653103397,
+           -0.22796953802819767,
+           -0.16332496327124482,
+           -0.09334141905962066,
+           -0.01908998730409189,
+           0.05821430660680711,
+           0.1372488591416409,
+           0.21662287840765398,
+           0.29491873890321624,
+           0.37073418997717156,
+           0.44272428347413406,
+           0.5096418919194229,
+           0.5703757234695375,
+           0.6239848028597188,
+           0.6697284771450733,
+           0.7070911189121435,
+           0.7358008349755966,
+           0.755841641968735,
+           0.7674587378278561,
+           0.7711566757383226,
+           0.7676904301780316,
+           0.758049528640293,
+           0.743435602793561,
+           0.7252338846776463,
+           0.7049793326849995,
+           0.684318214482385,
+           0.6649660960564202,
+           0.6486632845846924,
+           0.6371288452930332,
+           0.6320143569582212,
+           0.6348585860483114,
+           0.6470442451814816,
+           0.6697579578901447,
+           0.7039544795957465,
+           0.7503261259378283,
+           0.8092782365340144,
+           0.8809113578624812,
+           0.9650106667796376,
+           1.0610429801883576,
+           1.168161510884142,
+           1.2852183392021448,
+           1.4107843794725285,
+           1.5431764341879024,
+           1.6804907518153442,
+           1.8206423407510224,
+           1.961409146098214,
+           2.100480071400701,
+           2.2355057273186314,
+           2.3641507160303648,
+           2.4841462157598793,
+           2.5933416154360853,
+           2.6897539655217684,
+           2.7716140571910084,
+           2.837408017228244,
+           2.8859134084969447,
+           2.916228953134166,
+           2.9277971447088564,
+           2.920419182837209,
+           2.8942618451274225,
+           2.849856102427377,
+           2.788087479527418,
+           2.7101783599529568,
+           2.617662625482899,
+           2.5123532038711733,
+           2.3963032674726215
+          ],
+          [
+           2.3102668660298233,
+           2.182235079986984,
+           2.049718195621046,
+           1.9152412053496648,
+           1.7813364613771145,
+           1.6504888473255894,
+           1.5250821514676236,
+           1.4073478847412515,
+           1.2993177269865697,
+           1.2027806966800318,
+           1.1192460250285452,
+           1.0499125774284606,
+           0.995645507375604,
+           0.9569606538012946,
+           0.9340170067682547,
+           0.9266173730398255,
+           0.9342171769619861,
+           0.9559411381553906,
+           0.9906073804303702,
+           1.0367583506628057,
+           1.0926977663670487,
+           1.1565326702459091,
+           1.2262195524723618,
+           1.2996134096786034,
+           1.3745185457720457,
+           1.4487398852502178,
+           1.520133565405133,
+           1.586655599705496,
+           1.6464074599905638,
+           1.6976775084459605,
+           1.7389773195144447,
+           1.7690720641446394,
+           1.787004280754994,
+           1.7921105251649414,
+           1.784030571311413,
+           1.7627090213376093,
+           1.7283893729545903,
+           1.6816007791250362,
+           1.6231379154568704,
+           1.5540345397568893,
+           1.4755314818060312,
+           1.3890399357975978,
+           1.2961010397341726,
+           1.1983428126835072,
+           1.0974355800597686,
+           0.9950470476223837,
+           0.8927981859900289,
+           0.7922210592085304,
+           0.6947196740801318,
+           0.6015348430632957,
+           0.5137139447682851,
+           0.43208633520612644,
+           0.3572450133487044,
+           0.2895349800429836,
+           0.22904855407912975,
+           0.17562772769196675,
+           0.12887346058157473,
+           0.08816163131346783,
+           0.0526651922642604,
+           0.021381913484677845,
+           -0.006833043974741076,
+           -0.03323060992594709,
+           -0.05912832914314141,
+           -0.08586899175917322,
+           -0.11477848368695637,
+           -0.14712399186040245,
+           -0.18407369101057636,
+           -0.22665900166157513,
+           -0.27574044396915487,
+           -0.33197802056233816,
+           -0.39580694597904265,
+           -0.46741940351524797,
+           -0.5467528557735347,
+           -0.633485266791918,
+           -0.7270374156018033,
+           -0.8265822978959464,
+           -0.9310614288098559,
+           -1.0392076802783217,
+           -1.1495741155714403,
+           -1.2605681257784678,
+           -1.3704900322110982,
+           -1.4775751985369576,
+           -1.5800386000152056,
+           -1.6761207269864957,
+           -1.7641336576139295,
+           -1.842506121926851,
+           -1.9098263959029542,
+           -1.964881910314395,
+           -2.00669453330556,
+           -2.03455058640128,
+           -2.0480247784373113,
+           -2.046997387727231,
+           -2.031664186067941,
+           -2.0025387749335986,
+           -1.960447190064421,
+           -1.9065148210360356,
+           -1.8421458825869375,
+           -1.7689958597710016,
+           -1.6889375247838805,
+           -1.6040212852073417,
+           -1.5164307673790636,
+           -1.4284346610166405,
+           -1.3423359490188835,
+           -1.2604197170511575,
+           -1.184900779276121,
+           -1.117872368308022,
+           -1.0612571187777604,
+           -1.0167615251753548,
+           -0.9858349770054549,
+           -0.9696343695816448,
+           -0.9689951594976622,
+           -0.9844095830571369,
+           -1.0160125873587003,
+           -1.063575841403729,
+           -1.1265100029451336,
+           -1.203875220486764,
+           -1.2943996536523843,
+           -1.3965056038503563,
+           -1.5083426654285672,
+           -1.6278271397760113,
+           -1.7526868051746989,
+           -1.880510007289444,
+           -2.0087979321231435,
+           -2.135018847574024,
+           -2.256663053250851,
+           -2.371297262060437,
+           -2.476617151662783,
+           -2.570496868826094,
+           -2.6510343438960664,
+           -2.7165913741954184,
+           -2.765827561694971,
+           -2.797727338641587,
+           -2.8116194813549322,
+           -2.807188693035343,
+           -2.784479026739242,
+           -2.7438891150237814,
+           -2.6861593683686027,
+           -2.612351495579279,
+           -2.5238208813109964,
+           -2.4221825242011286,
+           -2.3092713897848647,
+           -2.1870981617488825,
+           -2.05780148004459,
+           -1.9235978324306573,
+           -1.7867303153080092,
+           -1.6494174991241832,
+           -1.513803622771184,
+           -1.3819113006429409,
+           -1.2555978564517838,
+           -1.1365163013354889,
+           -1.0260818526862785,
+           -0.9254447475716673,
+           -0.8354699441888541,
+           -0.7567241305283865,
+           -0.6894702756816159,
+           -0.6336697705977529,
+           -0.5889920162781315,
+           -0.554831133080339,
+           -0.5303292895623883,
+           -0.5144059874611522,
+           -0.5057924949600017,
+           -0.5030704969061934,
+           -0.504713931107288,
+           -0.5091329066819108,
+           -0.5147185554138947,
+           -0.5198876512045121,
+           -0.523125846347957,
+           -0.5230284160448676,
+           -0.5183374731654433,
+           -0.5079747119279995,
+           -0.49106885937140027,
+           -0.4669771541839526,
+           -0.43530033001154916,
+           -0.39589075078949343,
+           -0.3488535245930427,
+           -0.29454060543948535,
+           -0.23353807476215013,
+           -0.16664697129783096,
+           -0.09485820540323582,
+           -0.019322247111858638,
+           0.058685587317034056,
+           0.13780331144661428,
+           0.21662287840765396,
+           0.2937321318990146,
+           0.3677569705209877,
+           0.43740259100337264,
+           0.501492698515315,
+           0.5590056234504419,
+           0.6091063625895777,
+           0.6511736663858699,
+           0.6848214206860408,
+           0.7099137173146454,
+           0.7265731699285471,
+           0.7351822053161127,
+           0.7363772414883478,
+           0.7310358479145257,
+           0.7202571654419553,
+           0.7053360391974517,
+           0.687731482639683,
+           0.6690302407265084,
+           0.6509063510603109,
+           0.6350777105250036,
+           0.6232607385309966,
+           0.6171242843602421,
+           0.6182439537524117,
+           0.6280580280104118,
+           0.6478261174805904,
+           0.6785916309705553,
+           0.7211490549184397,
+           0.7760169230231284,
+           0.8434172213236913,
+           0.9232618186863769,
+           1.0151463421156128,
+           1.1183517344427931,
+           1.231853543245531,
+           1.3543387989736067,
+           1.4842301519323837,
+           1.6197167566755037,
+           1.758791222991977,
+           1.8992917992631975,
+           2.038948820353696,
+           2.17543434174247,
+           2.306413797093572,
+           2.429598460062389,
+           2.542797464306224,
+           2.643968139156212,
+           2.731263452208221,
+           2.8030754134522198,
+           2.8580733870028947,
+           2.8952363738462012,
+           2.9138784694632474,
+           2.9136668603493603,
+           2.8946318994385267,
+           2.857168988003971,
+           2.8020321861778537,
+           2.73031967108393,
+           2.6434513559124926,
+           2.543139170351126,
+           2.4313506780558596,
+           2.3102668660298242
+          ],
+          [
+           2.2216054665030556,
+           2.091160544787874,
+           1.9578665745596426,
+           1.8242604148569863,
+           1.6928523578612795,
+           1.5660718531018272,
+           1.4462151846394808,
+           1.3353963128343689,
+           1.235502015533187,
+           1.1481523595104972,
+           1.074667404318313,
+           1.016040890493457,
+           0.9729214960217268,
+           0.9456020631750606,
+           0.9340170067682545,
+           0.9377479191938549,
+           0.9560371920640031,
+           0.9878092836826488,
+           1.0316990805298756,
+           1.0860866338598933,
+           1.1491374034437576,
+           1.2188470130264693,
+           1.2930894192778093,
+           1.3696673203473049,
+           1.446363583364211,
+           1.5209924534169565,
+           1.5914493200263162,
+           1.6557578604689815,
+           1.7121134513535778,
+           1.7589218387343115,
+           1.7948321802441225,
+           1.818763717120017,
+           1.8299254959415583,
+           1.8278287353462694,
+           1.8122916175349824,
+           1.783436473432325,
+           1.7416795192176686,
+           1.6877134859010678,
+           1.6224836581300481,
+           1.547157999165133,
+           1.4630921819950753,
+           1.37179046836751,
+           1.2748634751142798,
+           1.1739839381901445,
+           1.0708416276241342,
+           0.9670985801185699,
+           0.8643458000691953,
+           0.764062534806191,
+           0.6675791570808833,
+           0.5760445891513708,
+           0.49039908080261524,
+           0.4113530114045945,
+           0.33937222729997024,
+           0.274670254465805,
+           0.21720754686662133,
+           0.16669774776370017,
+           0.12262075910878405,
+           0.08424223764018753,
+           0.05063896988078877,
+           0.020729426118227156,
+           -0.006691340527242322,
+           -0.03291339628634913,
+           -0.059271264587010396,
+           -0.08710199544627512,
+           -0.11770309560626104,
+           -0.1522914529232325,
+           -0.1919643637092087,
+           -0.23766371841242298,
+           -0.2901443205424028,
+           -0.3499472081185126,
+           -0.41737871880314964,
+           -0.49249589249681053,
+           -0.5750986422339199,
+           -0.6647289498330722,
+           -0.760677161322895,
+           -0.8619952732674058,
+           -0.9675169194027109,
+           -1.0758835920715417,
+           -1.1855764692416433,
+           -1.2949530695807208,
+           -1.402287828918322,
+           -1.5058155847621477,
+           -1.6037768741039748,
+           -1.6944638956725742,
+           -1.776265962510043,
+           -1.847713274988888,
+           -1.9075178781373023,
+           -1.9546107296492488,
+           -1.9881738947538228,
+           -2.007666999049987,
+           -2.0128472076913497,
+           -2.0037821555811273,
+           -1.9808554246785983,
+           -1.9447643469080271,
+           -1.896510099999747,
+           -1.8373802542110955,
+           -1.7689241155470221,
+           -1.6929213911643708,
+           -1.6113448706154045,
+           -1.5263179682706132,
+           -1.4400681038575684,
+           -1.354877006249527,
+           -1.2730291076948048,
+           -1.196759249494967,
+           -1.1282009443098213,
+           -1.0693364341115519,
+           -1.0219497463971625,
+           -0.9875838854111179,
+           -0.96750320136933,
+           -0.9626618612404167,
+           -0.9736792023952111,
+           -1.0008225888101716,
+           -1.04399821241515,
+           -1.102750093906359,
+           -1.1762673424763967,
+           -1.2633995371867641,
+           -1.3626798989167932,
+           -1.472355735691008,
+           -1.590425470255283,
+           -1.7146814012856917,
+           -1.8427572124169302,
+           -1.972179129719197,
+           -2.100419541104636,
+           -2.2249518325330255,
+           -2.343305167238025,
+           -2.4531179362046402,
+           -2.552188640738145,
+           -2.6385230303696123,
+           -2.7103764100083536,
+           -2.7662901469512935,
+           -2.805121548231869,
+           -2.8260664384087493,
+           -2.8286739433496613,
+           -2.8128531725650094,
+           -2.7788716866186887,
+           -2.727345832352429,
+           -2.6592232223190586,
+           -2.5757578212118917,
+           -2.4784782766695272,
+           -2.3691502903916826,
+           -2.249733964186831,
+           -2.1223371710450185,
+           -1.9891660908253161,
+           -1.8524741115456902,
+           -1.7145103291389372,
+           -1.577468880196124,
+           -1.4434403137090028,
+           -1.3143661499400443,
+           -1.1919976888092778,
+           -1.0778600187937313,
+           -0.9732220431178878,
+           -0.87907318636123,
+           -0.796107275383414,
+           -0.724713907907625,
+           -0.6649774347180467,
+           -0.6166834918870537,
+           -0.5793328324629885,
+           -0.5521620272579583,
+           -0.534170436224526,
+           -0.5241526995492057,
+           -0.5207358647652448,
+           -0.5224201561485367,
+           -0.527622308084659,
+           -0.5347203270172454,
+           -0.5420985183524083,
+           -0.5481916159218823,
+           -0.5515268821821502,
+           -0.550763106397099,
+           -0.5447255140552407,
+           -0.5324357114742401,
+           -0.5131359220955882,
+           -0.48630692197675945,
+           -0.4516792475955,
+           -0.40923742507770466,
+           -0.3592171518778147,
+           -0.3020955451664347,
+           -0.23857475107334003,
+           -0.16955938094324738,
+           -0.09612840053626907,
+           -0.019502241606158342,
+           0.05899397110958678,
+           0.13797008387705192,
+           0.2160124003102801,
+           0.29172587390770094,
+           0.3637758717422085,
+           0.4309283845473299,
+           0.49208759762613646,
+           0.5463298041171293,
+           0.5929327354989692,
+           0.6313995014575269,
+           0.6614764694252553,
+           0.6831645697552624,
+           0.6967236816886497,
+           0.7026699337467978,
+           0.7017659354250885,
+           0.6950041404506029,
+           0.6835837207528433,
+           0.6688815001499087,
+           0.6524176532587288,
+           0.6358170143115297,
+           0.6207669588443041,
+           0.6089729155770172,
+           0.6021126337849402,
+           0.6017903712763424,
+           0.609492178657025,
+           0.6265434365193296,
+           0.6540697539246926,
+           0.6929622601682236,
+           0.7438482191393146,
+           0.8070677691024195,
+           0.882657443494793,
+           0.9703409639749023,
+           1.0695276194931331,
+           1.1793183589670786,
+           1.2985195348259901,
+           1.4256640449553863,
+           1.559039436130728,
+           1.6967223574670052,
+           1.8366185920818898,
+           1.9765077530833235,
+           2.1140916097166293,
+           2.247044914075599,
+           2.3730675306255913,
+           2.4899366316629323,
+           2.5955577127901726,
+           2.6880132038273405,
+           2.7656075018632107,
+           2.8269073331970893,
+           2.8707764578402304,
+           2.8964038614821965,
+           2.9033247322243043,
+           2.8914336892586645,
+           2.8609899139115753,
+           2.8126140256252574,
+           2.747276741849102,
+           2.6662795566691058,
+           2.5712278635485157,
+           2.4639971281370014,
+           2.3466928833235996,
+           2.221605466503057
+          ],
+          [
+           2.131069184452055,
+           1.9993089031370561,
+           1.8663480374151538,
+           1.7347138620902536,
+           1.6068733913032844,
+           1.4851801144950896,
+           1.3718234201964177,
+           1.2687818774240387,
+           1.1777814513140041,
+           1.1002596106633158,
+           1.0373361431938797,
+           0.9897913330708198,
+           0.9580519784470626,
+           0.9421855388895787,
+           0.9419025080609709,
+           0.9565669107303417,
+           0.9852146298558848,
+           1.02657908382579,
+           1.0791236004767089,
+           1.1410796774372274,
+           1.2104901814657851,
+           1.2852564260641588,
+           1.3631879794620976,
+           1.4420539961499776,
+           1.5196348358490595,
+           1.593772734785866,
+           1.6624203252642138,
+           1.723685859948724,
+           1.7758740854094217,
+           1.817521823070229,
+           1.8474274518725398,
+           1.8646736422750516,
+           1.8686428617632094,
+           1.8590253535681722,
+           1.8358194782661803,
+           1.7993244976653429,
+           1.7501260671756969,
+           1.6890748820716264,
+           1.6172590902636301,
+           1.5359712352779804,
+           1.4466706243873728,
+           1.3509421250349525,
+           1.250452475220993,
+           1.1469052483948514,
+           1.0419956393278704,
+           0.9373662338740633,
+           0.834564892631986,
+           0.7350058172131461,
+           0.6399347797193877,
+           0.550399383421624,
+           0.46722508841316984,
+           0.3909975836180323,
+           0.32205191985369724,
+           0.26046864191854124,
+           0.20607697538162248,
+           0.15846494051770077,
+           0.11699608629146599,
+           0.08083236599334931,
+           0.048962517394742666,
+           0.02023516813320299,
+           -0.006604234951532787,
+           -0.03287367255164393,
+           -0.0599130487165446,
+           -0.08904205420470844,
+           -0.12151853247644434,
+           -0.15849847096127667,
+           -0.20099869890275662,
+           -0.249863303939654,
+           -0.30573468436375445,
+           -0.36903003509707505,
+           -0.43992392584913703,
+           -0.518337473165443,
+           -0.603934438113876,
+           -0.6961244024655392,
+           -0.7940729929287786,
+           -0.8967189399242441,
+           -1.0027975791796204,
+           -1.1108702355936535,
+           -1.2193587736604274,
+           -1.3265844612090743,
+           -1.4308101768187726,
+           -1.5302848990063551,
+           -1.6232893495470726,
+           -1.7081816258106346,
+           -1.7834416488022196,
+           -1.8477132749888883,
+           -1.8998429705229023,
+           -1.938914024972683,
+           -1.9642753862662168,
+           -1.975564326711407,
+           -1.972722298560588,
+           -1.956003502992867,
+           -1.9259758745317541,
+           -1.8835143694041991,
+           -1.829786636570266,
+           -1.7662313393967473,
+           -1.694529579512608,
+           -1.6165700476996914,
+           -1.5344086854122705,
+           -1.4502237807094156,
+           -1.3662675405007914,
+           -1.2848152740637142,
+           -1.2081133884154076,
+           -1.1383274326194295,
+           -1.0774914344860616,
+           -1.0274597491504092,
+           -0.989862585184661,
+           -0.9660662914641653,
+           -0.9571393789097177,
+           -0.9638251180784422,
+           -0.986521399576786,
+           -1.025268373142465,
+           -1.0797441971348614,
+           -1.1492690375565897,
+           -1.232817259288516,
+           -1.329037556740885,
+           -1.436280581370409,
+           -1.5526334441169016,
+           -1.6759603061529196,
+           -1.8039481254374434,
+           -1.9341565029840975,
+           -2.0640704745153053,
+           -2.191155022675457,
+           -2.3129100439403403,
+           -2.426924493786216,
+           -2.5309284538252754,
+           -2.622841914976488,
+           -2.7008191500857883,
+           -2.763287655790636,
+           -2.8089807742345454,
+           -2.8369632572735553,
+           -2.8466492053576133,
+           -2.8378119961687616,
+           -2.810586009884349,
+           -2.7654601539237276,
+           -2.703263385449461,
+           -2.62514261996758,
+           -2.5325335944813654,
+           -2.4271254194262313,
+           -2.310819701034392,
+           -2.1856852412894043,
+           -2.0539094232182085,
+           -1.9177474625366073,
+           -1.7794707508932712,
+           -1.6413155301458426,
+           -1.5054331209905953,
+           -1.3738428833411418,
+           -1.2483890113337712,
+           -1.1307021646501663,
+           -1.0221668125717758,
+           -0.923895020981076,
+           -0.8367072490817199,
+           -0.7611205460184357,
+           -0.697344352251159,
+           -0.6452839210952038,
+           -0.6045511869909403,
+           -0.5744827234971418,
+           -0.5541642602553685,
+           -0.5424610685367534,
+           -0.5380533833856267,
+           -0.5394759102866082,
+           -0.5451603686298828,
+           -0.5534799553445111,
+           -0.562794571550907,
+           -0.5714956438778142,
+           -0.578049390388943,
+           -0.5810374283245028,
+           -0.5791936958140363,
+           -0.5714367603995506,
+           -0.5568967110204807,
+           -0.534935973878183,
+           -0.5051635526449457,
+           -0.46744236573581377,
+           -0.4218895334444718,
+           -0.3688696510896983,
+           -0.30898126628244854,
+           -0.24303695440105275,
+           -0.1720375519040134,
+           -0.09714125803312508,
+           -0.019628447952120796,
+           0.059136848918035036,
+           0.1377477654627269,
+           0.21479660903648062,
+           0.2889169387797239,
+           0.35882457553797004,
+           0.4233564388222359,
+           0.48150616066126645,
+           0.5324555086370328,
+           0.5756007577917297,
+           0.6105732807432497,
+           0.6372537739811641,
+           0.6557797021899276,
+           0.6665457174265995,
+           0.6701969916493588,
+           0.6676155848596346,
+           0.6599001523359418,
+           0.64833946850995,
+           0.6343804075471414,
+           0.6195911675110368,
+           0.6056206523646903,
+           0.5941550307307423,
+           0.5868725695902749,
+           0.585397892882301,
+           0.5912568378846983,
+           0.6058330756495919,
+           0.6303276257044397,
+           0.6657223305241932,
+           0.7127482634573533,
+           0.7718599270575734,
+           0.8432159599672029,
+           0.9266669130113491,
+           1.0217504828553605,
+           1.1276944086977756,
+           1.2434270485300263,
+           1.3675954611700434,
+           1.4985906332914365,
+           1.6345793116716563,
+           1.7735417343342783,
+           1.9133144043252945,
+           2.0516369203014646,
+           2.1862017721865046,
+           2.314705930553997,
+           2.4349030071678506,
+           2.5446547425969213,
+           2.641980585635267,
+           2.725104168271734,
+           2.792495548285797,
+           2.8429081876005085,
+           2.8754097560127625,
+           2.8894059939312347,
+           2.8846570308099984,
+           2.8612857341248223,
+           2.8197778526770843,
+           2.760973913134357,
+           2.6860530252772654,
+           2.5965089446293756,
+           2.494118926287929,
+           2.380906076329839,
+           2.2590960629259182,
+           2.131069184452056
+          ],
+          [
+           2.0394239977911073,
+           1.907457261486238,
+           1.7759368724244318,
+           1.64735915140615,
+           1.524126982666137,
+           1.4084980122179198,
+           1.3025362461282801,
+           1.2080681667772077,
+           1.1266443764211678,
+           1.059507644465451,
+           1.007568081016946,
+           0.9713859882944043,
+           0.9511627574988262,
+           0.9467399862862993,
+           0.957606795737237,
+           0.9829151304651973,
+           1.0215026360109707,
+           1.071922528532069,
+           1.132479707372279,
+           1.2012722153615079,
+           1.2762370281686166,
+           1.3551990556740765,
+           1.4359221674861067,
+           1.516161013053987,
+           1.59371239527495,
+           1.666464975243112,
+           1.732446134299767,
+           1.7898648965313544,
+           1.8371499183419675,
+           1.8729816790694362,
+           1.8963181546020882,
+           1.9064134208684531,
+           1.9028288117852892,
+           1.8854364423238623,
+           1.854415097156742,
+           1.810238674162239,
+           1.7536575552108433,
+           1.6856734496090695,
+           1.60750841406591,
+           1.5205688931799854,
+           1.4264057427911248,
+           1.3266712922185016,
+           1.2230745681595128,
+           1.1173358412665428,
+           1.0111416652849223,
+           0.9061015579921328,
+           0.8037074236313341,
+           0.7052967394085472,
+           0.6120204259373466,
+           0.5248161959191169,
+           0.44438803006191463,
+           0.37119226797645005,
+           0.3054306286484093,
+           0.24705029446964527,
+           0.19575100929553732,
+           0.1509989592286575,
+           0.11204702940684855,
+           0.07796086543006996,
+           0.04765001835275743,
+           0.01990332117581294,
+           -0.0065724642001987,
+           -0.033111774802602294,
+           -0.061048251747597544,
+           -0.09167275425949023,
+           -0.1261925139750796,
+           -0.16569253179322538,
+           -0.2111002620273994,
+           -0.2631545442293325,
+           -0.32237963390056096,
+           -0.38906505214670917,
+           -0.46325182446357327,
+           -0.5447255140552405,
+           -0.633016279531912,
+           -0.727406004953444,
+           -0.8269423665722826,
+           -0.9304595199339061,
+           -1.0366049177941907,
+           -1.143871608008823,
+           -1.2506352152457425,
+           -1.3551946847769845,
+           -1.4558157639427025,
+           -1.550776119798582,
+           -1.6384109419727537,
+           -1.717157859196365,
+           -1.7856000069373914,
+           -1.8425061219268515,
+           -1.886866606251107,
+           -1.9179245975091013,
+           -1.9352012000387455,
+           -1.9385141725201482,
+           -1.9279895259330002,
+           -1.9040656589834342,
+           -1.8674898414549301,
+           -1.8193070449477282,
+           -1.7608413104693028,
+           -1.6936700286075719,
+           -1.619591685922458,
+           -1.540587796292052,
+           -1.4587798841153177,
+           -1.3763825137835295,
+           -1.2956534634698662,
+           -1.2188422184167895,
+           -1.1481380075404928,
+           -1.08561862603601,
+           -1.0332012752042659,
+           -0.9925966091287808,
+           -0.9652671070437205,
+           -0.9523907919161104,
+           -0.9548311922543088,
+           -0.9731142984164919,
+           -1.0074131002430706,
+           -1.0575401136567226,
+           -1.1229481143118625,
+           -1.2027391010410782,
+           -1.2956813154961315,
+           -1.4002339518021563,
+           -1.5145790059349853,
+           -1.6366595433886764,
+           -1.7642235097048289,
+           -1.8948720753512898,
+           -2.0261113975193514,
+           -2.1554065993194866,
+           -2.2802367136032444,
+           -2.3981493155259184,
+           -2.506813575554649,
+           -2.6040705027336095,
+           -2.6879792157067848,
+           -2.756858174612507,
+           -2.809320428160984,
+           -2.8443020740206295,
+           -2.8610832935529995,
+           -2.859301499965983,
+           -2.8389563277503673,
+           -2.8004063862155446,
+           -2.744357896289745,
+           -2.671845522713108,
+           -2.5842058986317085,
+           -2.483044511905025,
+           -2.3701967779908206,
+           -2.2476842593101107,
+           -2.1176671022706763,
+           -1.9823938479789764,
+           -1.8441498290910834,
+           -1.7052053919389178,
+           -1.567765179449232,
+           -1.4339196766270281,
+           -1.3056001574217087,
+           -1.184538081271726,
+           -1.0722298718453764,
+           -0.9699078723957234,
+           -0.878518115203853,
+           -0.7987053707333269,
+           -0.7308057596560222,
+           -0.6748470223847075,
+           -0.6305563508497531,
+           -0.5973755006987642,
+           -0.5744827234971416,
+           -0.5608208922753907,
+           -0.5551310439981547,
+           -0.555990432895028,
+           -0.5618540822590139,
+           -0.5710987418625764,
+           -0.5820681054903071,
+           -0.5931181194704007,
+           -0.6026612190058167,
+           -0.6092083643229059,
+           -0.6114078122009762,
+           -0.6080796486442238,
+           -0.5982452229673232,
+           -0.5811507594418315,
+           -0.5562845764164676,
+           -0.523387510560336,
+           -0.48245632132013105,
+           -0.43374003332786876,
+           -0.37772935771755534,
+           -0.315139512471061,
+           -0.2468869324859657,
+           -0.17406051773241582,
+           -0.09788820866105723,
+           -0.019699798386950133,
+           0.05911301193146639,
+           0.1371382371180246,
+           0.21298579073058377,
+           0.2853290913773237,
+           0.3529449721146473,
+           0.4147508159152694,
+           0.46983791136558267,
+           0.5175001198281047,
+           0.5572570658420717,
+           0.5888712034942535,
+           0.612358269318119,
+           0.6279908029900373,
+           0.6362945963757379,
+           0.6380381148081137,
+           0.6342151172109795,
+           0.626020879194728,
+           0.6148225910354559,
+           0.6021246562444919,
+           0.5895297523201867,
+           0.5786966297720701,
+           0.5712957156735011,
+           0.5689636514923454,
+           0.5732579300946221,
+           0.5856128026442815,
+           0.607297602397318,
+           0.6393785796128709,
+           0.6826852612082095,
+           0.73778224229685,
+           0.804947186948785,
+           0.8841556655655197,
+           0.9750732898467374,
+           1.07705542753495,
+           1.1891545923720965,
+           1.3101354146084208,
+           1.4384969086836066,
+           1.5725015720447755,
+           1.7102106770259087,
+           1.8495249605878625,
+           1.9882297784453618,
+           2.124043674166619,
+           2.2546692231586047,
+           2.3778449483612967,
+           2.4913970706079303,
+           2.593289852885626,
+           2.6816733243306476,
+           2.75492722614634,
+           2.811700106436264,
+           2.8509426021937547,
+           2.8719340817213586,
+           2.8743019763193693,
+           2.8580333024215263,
+           2.823478060290371,
+           2.771344388421769,
+           2.702685549250359,
+           2.6188790168085885,
+           2.521598125914159,
+           2.412776920632148,
+           2.2945690028270564,
+           2.1693013256013916,
+           2.0394239977911086
+          ],
+          [
+           1.9474452662692847,
+           1.8163827262871277,
+           1.687397998954817,
+           1.5629353431855213,
+           1.445313204010084,
+           1.3366743115546293,
+           1.238939863280488,
+           1.1537688463592157,
+           1.0825234336480625,
+           1.0262412409914117,
+           0.9856150690637311,
+           0.9609805737095328,
+           0.952312119103648,
+           0.9592268726793344,
+           0.9809970044170407,
+           1.0165696605367587,
+           1.064594197576679,
+           1.1234559917411282,
+           1.1913159844083363,
+           1.2661549915244608,
+           1.3458216954783584,
+           1.4280831555603217,
+           1.5106766192065582,
+           1.5913613921625176,
+           1.667969531968661,
+           1.7384541655408123,
+           1.8009342971014946,
+           1.8537350656210285,
+           1.8954225288769755,
+           1.9248321912543085,
+           1.941090650964381,
+           1.9436299154858563,
+           1.9321941174012909,
+           1.9068385518513125,
+           1.86792114685624,
+           1.8160866640511277,
+           1.7522441053363138,
+           1.6775379661711967,
+           1.5933141246697515,
+           1.5010812836549368,
+           1.4024689872745992,
+           1.299183312146462,
+           1.1929613834122237,
+           1.085525887369834,
+           0.9785407440772762,
+           0.8735690657781664,
+           0.7720344612181492,
+           0.6751866536341323,
+           0.5840722637991455,
+           0.4995114719866453,
+           0.4220811175963886,
+           0.3521046264121833,
+           0.2896489773289232,
+           0.23452873741040597,
+           0.1863170109540071,
+           0.14436296947667074,
+           0.10781545971564942,
+           0.07565203014448361,
+           0.046712577090640854,
+           0.019736692821478982,
+           -0.006596297068172775,
+           -0.03362568858643863,
+           -0.06266726934884129,
+           -0.09497183869775162,
+           -0.13168549610368768,
+           -0.17381277040909074,
+           -0.22218358928809306,
+           -0.277424989374253,
+           -0.3399383453478156,
+           -0.4098827539572264,
+           -0.4871650500681856,
+           -0.5714367603995503,
+           -0.6620981209499479,
+           -0.7583091007846523,
+           -0.8590071924788212,
+           -0.9629315527217236,
+           -1.068652909863748,
+           -1.1746085027731263,
+           -1.2791411811490259,
+           -1.3805416848467924,
+           -1.4770930317078859,
+           -1.5671158821385438,
+           -1.6490137158664984,
+           -1.7213166528335304,
+           -1.7827227762290674,
+           -1.8321358706739466,
+           -1.8686985712355275,
+           -1.89182002731267,
+           -1.9011973168431122,
+           -1.896829997546055,
+           -1.8790273493068275,
+           -1.8484080412152912,
+           -1.8058921437531887,
+           -1.7526855965576618,
+           -1.690257430353788,
+           -1.6203102233672133,
+           -1.5447444432661284,
+           -1.4656174811707219,
+           -1.3850983206059408,
+           -1.305418898024702,
+           -1.2288232998097088,
+           -1.1575160012126744,
+           -1.0936103839314326,
+           -1.0390787700994117,
+           -0.9957051812534838,
+           -0.9650419719870005,
+           -0.9483714008489936,
+           -0.9466730876813642,
+           -0.960598169706675,
+           -0.9904508115855032,
+           -1.036177551152826,
+           -1.0973647768250645,
+           -1.173244439256841,
+           -1.2627079034272666,
+           -1.3643276527374169,
+           -1.4763863686516236,
+           -1.5969127325082646,
+           -1.7237231346842494,
+           -1.8544683342694068,
+           -1.9866839932674025,
+           -2.11784391600486,
+           -2.2454147591858282,
+           -2.3669109424728236,
+           -2.4799484844809343,
+           -2.582296514761341,
+           -2.6719252680987258,
+           -2.7470494518898922,
+           -2.806165988444324,
+           -2.848085269035077,
+           -2.871955212130286,
+           -2.877277590648837,
+           -2.8639162780962444,
+           -2.8320972565314824,
+           -2.7824004257811645,
+           -2.7157434483652065,
+           -2.6333580534788656,
+           -2.5367594014980237,
+           -2.427709273515532,
+           -2.308173994430343,
+           -2.180278119624941,
+           -2.0462550113653037,
+           -1.9083954994550132,
+           -1.768995859771002,
+           -1.6303063532248412,
+           -1.4944815462979115,
+           -1.3635335832049413,
+           -1.2392895002921682,
+           -1.1233535675151096,
+           -1.0170755124510507,
+           -0.9215253325469036,
+           -0.837475234942378,
+           -0.7653890644029245,
+           -0.705419393106397,
+           -0.6574122558990989,
+           -0.6209193258902727,
+           -0.5952171425635924,
+           -0.5793328324629881,
+           -0.5720756051989752,
+           -0.5720731688830978,
+           -0.5778120925219525,
+           -0.5876810512213366,
+           -0.6000158254718206,
+           -0.6131448898355281,
+           -0.6254344198387654,
+           -0.6353315688682492,
+           -0.6414049187046932,
+           -0.6423810866212197,
+           -0.6371765766556753,
+           -0.6249240900342675,
+           -0.6049926565135659,
+           -0.5770011108726155,
+           -0.540824612792531,
+           -0.4965940894903162,
+           -0.4446886641364692,
+           -0.38572131463425113,
+           -0.32051818218287825,
+           -0.25009211277134563,
+           -0.17561116322214385,
+           -0.09836293287975417,
+           -0.01971568925368125,
+           0.058922661821573595,
+           0.13614665572855597,
+           0.210595265734862,
+           0.28099268651304427,
+           0.3461868055777525,
+           0.4051843232903121,
+           0.4571815684080697,
+           0.501590167047059,
+           0.5380568555845048,
+           0.5664768791043666,
+           0.5870005826709137,
+           0.6000329788174429,
+           0.6062262567089439,
+           0.6064653818731972,
+           0.6018471155493148,
+           0.5936529550082825,
+           0.5833166562793557,
+           0.5723871444938742,
+           0.5624877408616384,
+           0.555272735948062,
+           0.5523824138219229,
+           0.5553976788342152,
+           0.565795455000483,
+           0.5849060166471811,
+           0.6138733683412119,
+           0.6536197230789544,
+           0.7048150319073408,
+           0.7678523978977269,
+           0.8428300656221142,
+           0.9295405174625799,
+           1.0274670341487948,
+           1.135787893155909,
+           1.2533881895511614,
+           1.3788790742393588,
+           1.5106240190374445,
+           1.6467715412284696,
+           1.7852936566190056,
+           1.9240291837508499,
+           2.0607308964774425,
+           2.193115420776658,
+           2.3189146970158325,
+           2.4359277828361177,
+           2.5420717556052717,
+           2.635430487488365,
+           2.7143001103457824,
+           2.777230060886451,
+           2.823058697062498,
+           2.850942602193755,
+           2.8603788407432864,
+           2.8512195954702415,
+           2.823678795848428,
+           2.778330537784118,
+           2.716099290169621,
+           2.638242079907508,
+           2.546323038951303,
+           2.442180879947319,
+           2.3278900367566986,
+           2.20571635833846,
+           2.0780683754603686,
+           1.947445266269286
+          ],
+          [
+           1.8559111715761123,
+           1.7268558293192071,
+           1.6014804959401596,
+           1.4821567010481218,
+           1.3710988555661976,
+           1.2703166735134246,
+           1.1815723258296256,
+           1.1063433129915214,
+           1.0457919061355023,
+           1.000741849067807,
+           0.9716628397492099,
+           0.9586631238320967,
+           0.9614903391422587,
+           0.9795405533594188,
+           1.0118752423507607,
+           1.057245768391772,
+           1.1141247404430101,
+           1.1807434770350604,
+           1.2551346500574363,
+           1.335179068279957,
+           1.4186554656221493,
+           1.5032920932574252,
+           1.5868188781351222,
+           1.667018904239751,
+           1.7417779969520262,
+           1.8091312445535686,
+           1.8673053728208473,
+           1.914755996685666,
+           1.950198904360662,
+           1.9726346808291373,
+           1.981366145380407,
+           1.976008257742142,
+           1.9564903348377514,
+           1.923050610619355,
+           1.8762233600726594,
+           1.8168189906913041,
+           1.7458976759776408,
+           1.6647372616292402,
+           1.5747963121864355,
+           1.4776732806976598,
+           1.3750628736209705,
+           1.2687107455686955,
+           1.160367692148459,
+           1.051744513308859,
+           0.9444686942504336,
+           0.8400439968374153,
+           0.7398139729866257,
+           0.6449303048405225,
+           0.5563267474031608,
+           0.4746993010391959,
+           0.4004930775900421,
+           0.333896149010122,
+           0.2748404858066806,
+           0.2230099087796139,
+           0.1778547962519341,
+           0.1386131147378619,
+           0.10433717821226318,
+           0.07392539392786623,
+           0.04615812478566746,
+           0.01973669282147898,
+           -0.006675531918607454,
+           -0.03441106595999303,
+           -0.0647564038987555,
+           -0.09891139577229227,
+           -0.13795100574785776,
+           -0.18279048591573258,
+           -0.23415491072094943,
+           -0.2925539049510393,
+           -0.3582622640612669,
+           -0.4313070133511923,
+           -0.5114612859535012,
+           -0.5982452229673229,
+           -0.6909339168299039,
+           -0.7885722357846219,
+           -0.8899961877117262,
+           -0.9938603101965491,
+           -1.098670414873502,
+           -1.2028208718482545,
+           -1.3046354979996384,
+           -1.40241101432826,
+           -1.4944619648009558,
+           -1.579165944243017,
+           -1.6550079669633557,
+           -1.7206228214460848,
+           -1.7748342993510013,
+           -1.8166902582483648,
+           -1.8454925752735256,
+           -1.8608211708597036,
+           -1.8625514249180855,
+           -1.8508644687717124,
+           -1.8262500108519637,
+           -1.789501538320115,
+           -1.7417039258223628,
+           -1.6842136718339287,
+           -1.6186321677890685,
+           -1.5467725808236954,
+           -1.4706210930852552,
+           -1.3922933851260824,
+           -1.3139873742527175,
+           -1.237933317733655,
+           -1.1663424629458783,
+           -1.1013554699993449,
+           -1.0449918459579897,
+           -0.9991016130503838,
+           -0.9653203865557151,
+           -0.9450289624239038,
+           -0.9393184119202822,
+           -0.9489615531250433,
+           -0.9743915200279817,
+           -1.015687982839205,
+           -1.0725713920352926,
+           -1.1444054279762212,
+           -1.2302076423014152,
+           -1.3286680815107745,
+           -1.438175491936489,
+           -1.5568505233833787,
+           -1.6825851805070005,
+           -1.813087620624536,
+           -1.9459312677945875,
+           -2.0786071088148446,
+           -2.2085779598247965,
+           -2.333333444352706,
+           -2.450444406087423,
+           -2.557615492821484,
+           -2.6527346915841834,
+           -2.733918667901002,
+           -2.7995528625981136,
+           -2.848325425164182,
+           -2.87925421031783,
+           -2.8917062305019177,
+           -2.885409137479633,
+           -2.8604544966372027,
+           -2.8172928133583826,
+           -2.7567204671542744,
+           -2.6798589013277376,
+           -2.5881265991522318,
+           -2.4832045474020608,
+           -2.3669960404691426,
+           -2.241581809559349,
+           -2.1091715684222443,
+           -1.9720531471766853,
+           -1.8325404371594656,
+           -1.6929213911643712,
+           -1.5554073145107652,
+           -1.4220846433895642,
+           -1.2948703389247562,
+           -1.1754719301177503,
+           -1.0653531187366112,
+           -0.9657057173052975,
+           -0.8774285312057866,
+           -0.801113621535778,
+           -0.7370402011178684,
+           -0.6851762265180317,
+           -0.6451875588081228,
+           -0.6164543798087231,
+           -0.5980943732719167,
+           -0.5889920162781307,
+           -0.5878331790619726,
+           -0.5931441051486566,
+           -0.6033337411515429,
+           -0.6167383093293187,
+           -0.6316669678451523,
+           -0.6464473847222084,
+           -0.6594700621315921,
+           -0.6692302875217735,
+           -0.6743666561151278,
+           -0.6736952036680719,
+           -0.6662383066709038,
+           -0.6512476463126723,
+           -0.6282206889978755,
+           -0.596910305990789,
+           -0.5573273335662676,
+           -0.5097360583302364,
+           -0.45464279549932035,
+           -0.39277790626786857,
+           -0.3250717694382626,
+           -0.2526253779816176,
+           -0.1766763692106793,
+           -0.0985614143075106,
+           -0.019675986108390914,
+           0.058567409036420735,
+           0.1347814105215716,
+           0.20764525897250402,
+           0.2759444121342829,
+           0.33860725307429307,
+           0.39473789780385854,
+           0.44364421017720834,
+           0.4848602556937591,
+           0.5181625694860018,
+           0.5435797736914749,
+           0.5613952515430677,
+           0.5721427655157043,
+           0.5765950901858774,
+           0.5757459124520634,
+           0.5707854278153862,
+           0.5630702270618748,
+           0.5540882187062838,
+           0.5454194651010761,
+           0.5386939207889813,
+           0.5355471476338498,
+           0.5375751402680389,
+           0.5462894258832446,
+           0.5630736035159887,
+           0.5891424596227567,
+           0.62550473952582,
+           0.6729305695847766,
+           0.7319244147476376,
+           0.8027043231366996,
+           0.8851880567817865,
+           0.9789865392744547,
+           1.0834048711322866,
+           1.1974509764823398,
+           1.319851754936801,
+           1.4490764249555026,
+           1.5833665642400734,
+           1.7207721832956806,
+           1.8591930144681528,
+           1.9964240643817357,
+           2.130204366155855,
+           2.258267781899939,
+           2.3783946479779456,
+           2.48846302691602,
+           2.586498331394241,
+           2.6707201175675466,
+           2.739584906307194,
+           2.791823980418019,
+           2.8264752213479802,
+           2.8429081876005102,
+           2.8408417956460252,
+           2.820354138770732,
+           2.781884165761905,
+           2.7262251350759525,
+           2.654509956450546,
+           2.5681887260174476,
+           2.4689989481100354,
+           2.3589291125664476,
+           2.24017645611092,
+           2.115099876442702,
+           1.9861690845444229,
+           1.8559111715761134
+          ],
+          [
+           1.7655961335723442,
+           1.6396340086422074,
+           1.5189112643340774,
+           1.4057066488591874,
+           1.302111824304688,
+           1.2099865137393082,
+           1.1309189891016338,
+           1.0661928081467147,
+           1.0167605592274498,
+           0.9832252050889178,
+           0.9658294352468393,
+           0.9644532453367178,
+           0.97861976571994,
+           1.007509165395954,
+           1.0499802656729156,
+           1.1045993157516352,
+           1.169675213804488,
+           1.2433003063653965,
+           1.3233957695299123,
+           1.4077604707048936,
+           1.4941221319469156,
+           1.5801895671200377,
+           1.6637047463064978,
+           1.7424934524980997,
+           1.8145133372125752,
+           1.8778982522111898,
+           1.9309978321239853,
+           1.9724114250361744,
+           2.0010156118698426,
+           2.0159847171012464,
+           2.0168038889425377,
+           2.003274512210455,
+           1.9755119071009946,
+           1.9339354572747722,
+           1.879251496325395,
+           1.8124294582680107,
+           1.7346719607989904,
+           1.64737963573601,
+           1.5521116456889767,
+           1.4505429266054157,
+           1.344419269953157,
+           1.2355114041874438,
+           1.125569251745124,
+           1.0162775247944202,
+           0.9092137807637078,
+           0.8058099884233846,
+           0.7073185588471393,
+           0.6147836754296654,
+           0.5290186163730922,
+           0.45058960527061964,
+           0.3798065546300289,
+           0.31672088772851753,
+           0.26113044062087826,
+           0.21259126307981485,
+           0.1704359593548937,
+           0.13379804138516022,
+           0.10164161273214889,
+           0.07279556490392221,
+           0.045991352355229845,
+           0.01990332117581292,
+           -0.00680949838881388,
+           -0.035461262275297896,
+           -0.06729798037370374,
+           -0.10345809504759158,
+           -0.1449360338608247,
+           -0.19254972277750215,
+           -0.24691294352956178,
+           -0.30841329348799934,
+           -0.3771963613969313,
+           -0.453156571399546,
+           -0.535934974969758,
+           -0.6249240900342672,
+           -0.7192797032902891,
+           -0.8179393701370278,
+           -0.9196471713486468,
+           -1.022984121074723,
+           -1.1264034711479936,
+           -1.2282700258255888,
+           -1.3269024723407146,
+           -1.4206176487979887,
+           -1.507775614188413,
+           -1.586824357133883,
+           -1.6563429811866168,
+           -1.715082235161528,
+           -1.7620013163871586,
+           -1.7962999615204465,
+           -1.8174449515917723,
+           -1.8251902925029364,
+           -1.8195904859968162,
+           -1.8010064753701902,
+           -1.7701040307337559,
+           -1.7278445259678963,
+           -1.6754682490316466,
+           -1.6144705742435914,
+           -1.5465715049072426,
+           -1.4736792627090989,
+           -1.3978487524635674,
+           -1.3212358631902026,
+           -1.2460486758398661,
+           -1.1744967314572243,
+           -1.1087395690311437,
+           -1.0508357682837965,
+           -1.0026937284515594,
+           -0.9660253797274301,
+           -0.9423039602233789,
+           -0.9327268995563839,
+           -0.9381847326404473,
+           -0.9592368267939512,
+           -0.9960945452329488,
+           -1.0486122942888407,
+           -1.1162867145282043,
+           -1.1982640819153163,
+           -1.2933557889716847,
+           -1.4000615823376947,
+           -1.5166000469571959,
+           -1.6409456528379456,
+           -1.7708715222538993,
+           -1.90399693722059,
+           -2.0378384924752986,
+           -2.1698637108404015,
+           -2.297545877910823,
+           -2.418418822959948,
+           -2.5301303735455387,
+           -2.630493242512283,
+           -2.717532167173617,
+           -2.789526209925779,
+           -2.845045245218794,
+           -2.882979796860069,
+           -2.9025635486618833,
+           -2.903388026582664,
+           -2.8854091374796336,
+           -2.848945443826477,
+           -2.794668250519401,
+           -2.723583774405172,
+           -2.6370078546832185,
+           -2.536533838304279,
+           -2.4239944346433204,
+           -2.3014184741904806,
+           -2.170983623395155,
+           -2.034966199301278,
+           -1.895689291052584,
+           -1.7554704292441619,
+           -1.616570047699692,
+           -1.4811419555564114,
+           -1.3511869812827664,
+           -1.2285108659035557,
+           -1.114687372419911,
+           -1.0110274449783985,
+           -0.9185550981201477,
+           -0.8379905472657482,
+           -0.769740910687291,
+           -0.713898625089557,
+           -0.6702475262404014,
+           -0.6382763575809075,
+           -0.6171992880693655,
+           -0.6059828501499828,
+           -0.603378553876663,
+           -0.6079602976591189,
+           -0.6181655831393171,
+           -0.632339454087715,
+           -0.6487800190308073,
+           -0.6657843859957873,
+           -0.6816938359740556,
+           -0.6949370894137796,
+           -0.7040705764672357,
+           -0.7078147053403612,
+           -0.7050852317415166,
+           -0.6950189633033977,
+           -0.6769931826048771,
+           -0.6506383372291384,
+           -0.6158437209712745,
+           -0.5727560523962337,
+           -0.5217710408366971,
+           -0.46351821096079665,
+           -0.39883943066004324,
+           -0.3287617488285117,
+           -0.2544652955467871,
+           -0.17724712357334801,
+           -0.09848197370163378,
+           -0.019581024857654155,
+           0.05805025917532393,
+           0.13305405208930307,
+           0.20416072883561268,
+           0.2702269789266541,
+           0.33027044104823483,
+           0.3834999209425855,
+           0.42934036884935645,
+           0.46745192838862515,
+           0.4977425222092237,
+           0.52037360712843,
+           0.535758908622467,
+           0.5445561269098199,
+           0.5476517898835792,
+           0.5461396071567334,
+           0.5412928499429966,
+           0.5345314390727743,
+           0.5273845641241275,
+           0.521449776836775,
+           0.518349598586856,
+           0.5196867522325023,
+           0.5269991712464822,
+           0.5417159525809303,
+           0.5651154037363499,
+           0.5982862893464228,
+           0.642093309287665,
+           0.6971477406306401,
+           0.7637840520831347,
+           0.8420431549555709,
+           0.9316627926553814,
+           1.0320753952820354,
+           1.1424135413841725,
+           1.2615229799264376,
+           1.387982976690746,
+           1.5201335654051293,
+           1.6561091094427027,
+           1.7938774193288467,
+           1.9312835285661063,
+           2.0660971090313263,
+           2.1960624104900157,
+           2.3189495390795787,
+           2.4326058487448203,
+           2.5350062086636194,
+           2.624300929040409,
+           2.698860176883959,
+           2.7573137913995485,
+           2.7985855135779825,
+           2.82192077395126,
+           2.8269073331970924,
+           2.8134882386717117,
+           2.7819667419512975,
+           2.733003013644774,
+           2.6676026874507492,
+           2.587097460897298,
+           2.493118170653591,
+           2.387560941082853,
+           2.2725471713954417,
+           2.1503782752779235,
+           2.023486213581047,
+           1.8943809624396064,
+           1.7655961335723453
+          ],
+          [
+           1.6772642583475135,
+           1.55545520032738,
+           1.4403888771989608,
+           1.3342319886542793,
+           1.2389357717270162,
+           1.1561942526836777,
+           1.0874084032461275,
+           1.0336570232640925,
+           0.9956750112555812,
+           0.9738395077891767,
+           0.9681642087983553,
+           0.9783019511754066,
+           1.0035554761366907,
+           1.0428960816751687,
+           1.09498968864348,
+           1.158229670177959,
+           1.2307756355195987,
+           1.3105972206487135,
+           1.395521822866518,
+           1.4832851272912966,
+           1.5715832123064941,
+           1.6581249897227768,
+           1.740683734484703,
+           1.817146488106675,
+           1.8855601788585867,
+           1.9441733885114663,
+           1.9914728079840367,
+           2.026213559659329,
+           2.047442719064167,
+           2.0545155391476593,
+           2.047104062304476,
+           2.0251979940398726,
+           1.9890979030823133,
+           1.9394010010894105,
+           1.876979936211501,
+           1.802955204211834,
+           1.7186619344304683,
+           1.625611941860978,
+           1.5254520477208724,
+           1.4199197564504495,
+           1.310797435024577,
+           1.1998661694536656,
+           1.0888604727545044,
+           0.9794249885983446,
+           0.8730742761382269,
+           0.7711566757383227,
+           0.6748231447076533,
+           0.5850018195278822,
+           0.5023789098545246,
+           0.4273863636168803,
+           0.36019656606134903,
+           0.30072415304970673,
+           0.24863483495765454,
+           0.2033609467681201,
+           0.16412326698009683,
+           0.1299584871179751,
+           0.09975156897902558,
+           0.07227210193744754,
+           0.046213670769554904,
+           0.020235168133202967,
+           -0.006997063061833591,
+           -0.03676739239630652,
+           -0.07027049588663148,
+           -0.1085734693903757,
+           -0.15258148394399157,
+           -0.20300791343444385,
+           -0.26034974898329355,
+           -0.3248689773816555,
+           -0.3965804463235723,
+           -0.4752465709541606,
+           -0.5603790586334079,
+           -0.651247646312672,
+           -0.7468956621510341,
+           -0.8461620445964694,
+           -0.9477092826507917,
+           -1.0500565847375418,
+           -1.15161744448179,
+           -1.2507406533466077,
+           -1.3457537154934078,
+           -1.4350075518897691,
+           -1.516921340371945,
+           -1.590026327172613,
+           -1.653007463711852,
+           -1.7047417698469713,
+           -1.744332400180404,
+           -1.771137491627224,
+           -1.7847929957783097,
+           -1.7852288455964238,
+           -1.7726779690626249,
+           -1.7476778385266651,
+           -1.7110644293503492,
+           -1.6639586503832504,
+           -1.6077454971786753,
+           -1.5440463619513758,
+           -1.474685107524113,
+           -1.4016486715697776,
+           -1.327043108332584,
+           -1.2530460941525559,
+           -1.181857017498571,
+           -1.1156458414206916,
+           -1.0565019646136307,
+           -1.0063843156029684,
+           -0.9670738926263626,
+           -0.9401299100316293,
+           -0.926850631638299,
+           -0.9282398644030475,
+           -0.9449799544491919,
+           -0.9774119752232346,
+           -1.0255236279076112,
+           -1.0889451913611257,
+           -1.166953667221862,
+           -1.258485070058706,
+           -1.3621546173719574,
+           -1.476284384585104,
+           -1.5989378105765455,
+           -1.7279602741666586,
+           -1.8610248153477569,
+           -1.9956819505170742,
+           -2.1294124316022485,
+           -2.259681727196852,
+           -2.3839949614174882,
+           -2.4999510342029643,
+           -2.6052946655041636,
+           -2.6979651548133896,
+           -2.776140725564963,
+           -2.838277429204826,
+           -2.8831417136094246,
+           -2.9098359118661556,
+           -2.9178160765172505,
+           -2.9069017670916093,
+           -2.8772775906488377,
+           -2.8294864914587516,
+           -2.7644149820538853,
+           -2.683270698949039,
+           -2.587552847676582,
+           -2.479016269037769,
+           -2.3596300075686227,
+           -2.2315313905644505,
+           -2.096976728538754,
+           -1.9582898232631165,
+           -1.8178095157708478,
+           -1.6778375228506415,
+           -1.5405877962920524,
+           -1.4081385949039924,
+           -1.2823883862804994,
+           -1.1650165953111027,
+           -1.0574500920620995,
+           -0.9608361660231146,
+           -0.8760225704698055,
+           -0.8035450439168125,
+           -0.7436225297270083,
+           -0.6961601245228727,
+           -0.6607595958331688,
+           -0.6367371241071896,
+           -0.6231477484112401,
+           -0.6188158331138258,
+           -0.6223707286405185,
+           -0.6322866764594569,
+           -0.6469259098289307,
+           -0.664583829873794,
+           -0.6835350929626888,
+           -0.7020794311278636,
+           -0.7185860426642783,
+           -0.731535434585508,
+           -0.7395576710947468,
+           -0.7414660807485332,
+           -0.7362855969999028,
+           -0.7232750491746505,
+           -0.7019428800238616,
+           -0.6720559377592168,
+           -0.6336411705558694,
+           -0.5869802353395529,
+           -0.5325972156118021,
+           -0.47123982048992263,
+           -0.40385460457154626,
+           -0.3315569014582493,
+           -0.2555962989316806,
+           -0.17731859746997247,
+           -0.09812528316559678,
+           -0.01943160891662266,
+           0.05737558756012103,
+           0.130979194665726,
+           0.20017115602591395,
+           0.26388875896226244,
+           0.3212469027017687,
+           0.37156547107598176,
+           0.41439106139470944,
+           0.44951246745801643,
+           0.4769694765943085,
+           0.49705471408526514,
+           0.5103084489707973,
+           0.5175064584454916,
+           0.5196412292195995,
+           0.5178969487270119,
+           0.5136189024864902,
+           0.5082780421013173,
+           0.5034316175341931,
+           0.5006808741100943,
+           0.5016268964270039,
+           0.5078257358660258,
+           0.5207439842408562,
+           0.5417159525809301,
+           0.571903581107777,
+           0.6122601448810868,
+           0.6634987308201483,
+           0.7260663479911023,
+           0.8001243969653238,
+           0.8855360690361286,
+           0.9818610759473504,
+           1.0883579297405168,
+           1.2039938048523935,
+           1.327461825346153,
+           1.4572054338472291,
+           1.5914493200263127,
+           1.7282362197965406,
+           1.8654687459506312,
+           2.000955280542268,
+           2.1324588522144734,
+           2.257747840623754,
+           2.3746472971910295,
+           2.481089648027121,
+           2.5751635517003,
+           2.655159721461818,
+           2.7196125878022643,
+           2.767336771232553,
+           2.79745745473618,
+           2.809433887558225,
+           2.803075413452224,
+           2.7785495932899753,
+           2.736382179759525,
+           2.67744889616292,
+           2.6029591673423775,
+           2.5144321437267605,
+           2.4136655446841306,
+           2.302698020260325,
+           2.1837658867448826,
+           2.059255227501697,
+           1.9316504627969606,
+           1.803480578193525,
+           1.6772642583475146
+          ],
+          [
+           1.5916628735366516,
+           1.4750315951844142,
+           1.3665776694617584,
+           1.268337428401384,
+           1.1821051958254787,
+           1.109394997216339,
+           1.0514086875082091,
+           1.009011225806373,
+           0.9827136554970575,
+           0.9726641644148165,
+           0.9786474071630143,
+           1.000092075030157,
+           1.0360865029988477,
+           1.0854019128725796,
+           1.146522711177127,
+           1.2176830946042851,
+           1.2969090683723763,
+           1.3820648575379737,
+           1.4709025910186149,
+           1.5611140652691482,
+           1.650383350909504,
+           1.736438992124243,
+           1.8171045655963602,
+           1.8903464126033451,
+           1.9543174334606732,
+           2.0073959358114566,
+           2.0482186547399874,
+           2.0757072101504748,
+           2.089087431608266,
+           2.0879011587784664,
+           2.072010312288594,
+           2.041593220653629,
+           1.9971333791079728,
+           1.9394010010894107,
+           1.8694278981574342,
+           1.7884763849992384,
+           1.6980030489397715,
+           1.5996183445443213,
+           1.4950430705445377,
+           1.3860628561094155,
+           1.2744818247727798,
+           1.1620766161828617,
+           1.050551928057773,
+           0.9414986938528144,
+           0.836355936936435,
+           0.7363772414883478,
+           0.6426026564761297,
+           0.555836705112545,
+           0.47663301181920886,
+           0.4052858860019553,
+           0.3418290212609146,
+           0.28604128458767725,
+           0.23745938729524624,
+           0.19539705249729242,
+           0.1589701273615601,
+           0.12712693630282512,
+           0.09868303757829923,
+           0.07235943376200832,
+           0.046823199114257204,
+           0.020729426118227125,
+           -0.007236639055658856,
+           -0.038318405871164536,
+           -0.07364880161122071,
+           -0.11421424041897134,
+           -0.1608226720300491,
+           -0.2140765768612147,
+           -0.27435164562778236,
+           -0.34178173409998536,
+           -0.4162505207113121,
+           -0.4973901206229653,
+           -0.5845867289355824,
+           -0.6769931826048766,
+           -0.7735481499038128,
+           -0.8730014825661135,
+           -0.9739451034582945,
+           -1.074848655891988,
+           -1.1740990132510343,
+           -1.2700426427344083,
+           -1.3610297374103615,
+           -1.4454589785119394,
+           -1.5218217663695504,
+           -1.5887447642437718,
+           -1.6450296345262367,
+           -1.6896889105180901,
+           -1.7219770377571224,
+           -1.7414157344501418,
+           -1.7478129581544988,
+           -1.7412749220637551,
+           -1.7222107752369307,
+           -1.691329742640316,
+           -1.649630708445172,
+           -1.5983844149823125,
+           -1.5391086353890198,
+           -1.473536855660593,
+           -1.4035811670905063,
+           -1.3312902188009839,
+           -1.2588032084815726,
+           -1.188300994315423,
+           -1.121955489705456,
+           -1.061878552784097,
+           -1.0100716034644965,
+           -0.968377191361052,
+           -0.9384336984116395,
+           -0.9216342913544416,
+           -0.9190911429530157,
+           -0.9316058193116983,
+           -0.9596465866951416,
+           -1.003333228432834,
+           -1.0624297846957294,
+           -1.136345439495984,
+           -1.2241435847694195,
+           -1.3245588955963896,
+           -1.4360220582821412,
+           -1.5566916088547775,
+           -1.6844921680560558,
+           -1.8171582042985115,
+           -1.9522823221341685,
+           -2.087366963813558,
+           -2.219878328212742,
+           -2.3473012568227065,
+           -2.4671938119796697,
+           -2.577240278680893,
+           -2.6753013580410983,
+           -2.7594603868153484,
+           -2.828064511833555,
+           -2.8797598683628647,
+           -2.9135199544085713,
+           -2.9286665552969593,
+           -2.9248827505964283,
+           -2.902217724194061,
+           -2.8610832935530004,
+           -2.802242271076333,
+           -2.726788964302815,
+           -2.636122307646108,
+           -2.5319122920457495,
+           -2.4160605160156954,
+           -2.290655818356255,
+           -2.1579260659427937,
+           -2.020187256809132,
+           -1.8797911571454995,
+           -1.7390727194713613,
+           -1.6002985274962844,
+           -1.4656174811707225,
+           -1.3370148740190249,
+           -1.2162709256282025,
+           -1.1049247174080952,
+           -1.0042443423363083,
+           -0.9152039228025334,
+           -0.8384679787843817,
+           -0.7743834457040795,
+           -0.7229794519765564,
+           -0.6839747751593724,
+           -0.6567927074809161,
+           -0.6405828809986679,
+           -0.6342494341681456,
+           -0.6364847493205805,
+           -0.6458078581771383,
+           -0.660606503290524,
+           -0.6791817598395068,
+           -0.6997940664998834,
+           -0.720709487472649,
+           -0.7402450307358687,
+           -0.7568118800303629,
+           -0.768955459085684,
+           -0.7753913345256643,
+           -0.7750360764762694,
+           -0.7670323302348183,
+           -0.7507675050121666,
+           -0.7258856528395945,
+           -0.6922922879960512,
+           -0.6501520802676501,
+           -0.5998795393720084,
+           -0.5421229883180537,
+           -0.47774229577601396,
+           -0.40778099736169426,
+           -0.33343357907140686,
+           -0.25600881933587716,
+           -0.17689018619904495,
+           -0.09749436046273872,
+           -0.019229002411769038,
+           0.05654910221796904,
+           0.12857439248352753,
+           0.1957102941346802,
+           0.256983376450084,
+           0.3116129812525034,
+           0.3590355190503191,
+           0.39892276571897245,
+           0.43119364885910466,
+           0.45601918200706887,
+           0.473820382949045,
+           0.48525919499317616,
+           0.4912226125580422,
+           0.4928003902120791,
+           0.4912568828331627,
+           0.4879977195639531,
+           0.4845321517656801,
+           0.48243203170346344,
+           0.48328847123613766,
+           0.48866729593680575,
+           0.5000644481000515,
+           0.5188625009637325,
+           0.5462894258832441,
+           0.5833807045780225,
+           0.630945801085684,
+           0.6895399045710415,
+           0.7594417271620745,
+           0.840637993632308,
+           0.9328150956444828,
+           1.0353582064660611,
+           1.147357966940243,
+           1.2676246646426215,
+           1.3947096402715677,
+           1.5269334730951871,
+           1.6624203252642102,
+           1.799137667310104,
+           1.934940468142369,
+           2.0676188158480913,
+           2.194947843554816,
+           2.3147387699051616,
+           2.4248898279971454,
+           2.5234358509437502,
+           2.6085953067325676,
+           2.6788136293108207,
+           2.73280177553552,
+           2.7695690468613696,
+           2.7884493477808645,
+           2.7891202068781404,
+           2.7716140571910133,
+           2.7363214562506615,
+           2.6839861182188067,
+           2.6156918262887636,
+           2.5328414881824814,
+           2.4371287864036275,
+           2.330503053277491,
+           2.215128164353518,
+           2.093336388456903,
+           1.9675782550000764,
+           1.8403695960982258,
+           1.7142369901897938,
+           1.5916628735366527
+          ],
+          [
+           1.5095162055903253,
+           1.3990436133049136,
+           1.2981021173398788,
+           1.2085804658978678,
+           1.13210090898833,
+           1.0699846902154506,
+           1.023224415773078,
+           0.9924639303723984,
+           0.9779861508866767,
+           0.979709118902633,
+           0.9971903377389509,
+           1.0296392625930149,
+           1.0759376190987,
+           1.1346670404221488,
+           1.2041433405842645,
+           1.2824565861569877,
+           1.3675159935951682,
+           1.4570985684856208,
+           1.5489003185774508,
+           1.6405888166051614,
+           1.729855862925896,
+           1.8144690024266306,
+           1.8923206848294463,
+           1.9614739215035253,
+           2.0202033835318907,
+           2.067031002752477,
+           2.1007552768504945,
+           2.120473637830324,
+           2.125597416389569,
+           2.115859118544427,
+           2.0913119207498205,
+           2.0523214810156474,
+           1.9995503514147013,
+           1.9339354572747727,
+           1.8566592758224676,
+           1.769115497992503,
+           1.672870087846403,
+           1.5696187613815753,
+           1.4611419878671044,
+           1.3492586702796194,
+           1.2357796856934955,
+           1.12246246109567,
+           1.010967725277877,
+           0.9028195141732195,
+           0.7993694169232164,
+           0.701765935425088,
+           0.6109296940629448,
+           0.5275350822489737,
+           0.451998744214675,
+           0.3844751524670462,
+           0.32485931796914536,
+           0.27279650605369127,
+           0.22769864697782505,
+           0.1887669584165662,
+           0.15502013839227868,
+           0.12532734514089774,
+           0.09844505878913594,
+           0.07305682151085072,
+           0.047814780503725854,
+           0.021381913484677835,
+           -0.007526199448972553,
+           -0.04010118042403305,
+           -0.07740431555234081,
+           -0.12033268465799858,
+           -0.16958987393860953,
+           -0.22566206715659684,
+           -0.28880017108148587,
+           -0.35900847406804226,
+           -0.4360401668300202,
+           -0.5193998759556923,
+           -0.6083531780314294,
+           -0.7019428800238621,
+           -0.7990116744418487,
+           -0.898230610255754,
+           -0.9981326668552795,
+           -1.0971505823975558,
+           -1.1936579732109123,
+           -1.2860126904245206,
+           -1.37260129603368,
+           -1.4518835048659513,
+           -1.5224354323598215,
+           -1.5829905109496512,
+           -1.6324769896746893,
+           -1.670051011176303,
+           -1.6951243655993307,
+           -1.7073861495041647,
+           -1.7068177065722945,
+           -1.6937003919873925,
+           -1.668615879816165,
+           -1.6324389181001444,
+           -1.586322625096158,
+           -1.5316766074692514,
+           -1.470138362571955,
+           -1.4035385977003794,
+           -1.3338612551173883,
+           -1.2631991687507023,
+           -1.1937063933421768,
+           -1.1275483365209176,
+           -1.0668508864913995,
+           -1.0136497611392816,
+           -0.9698413074490397,
+           -0.9371359530275528,
+           -0.9170154548102822,
+           -0.9106950049992394,
+           -0.9190911429530153,
+           -0.9427962867806976,
+           -0.9820605430327684,
+           -1.0367812808910961,
+           -1.1065007728106497,
+           -1.1904120111453405,
+           -1.2873726145896922,
+           -1.3959265440655737,
+           -1.5143331597267415,
+           -1.64060297364471,
+           -1.7725392908176651,
+           -1.907784788382065,
+           -2.0438719628112323,
+           -2.1782762804096123,
+           -2.3084707998851735,
+           -2.431980998849043,
+           -2.546438529673702,
+           -2.6496326544116684,
+           -2.739558162859091,
+           -2.8144586610285147,
+           -2.87286422725178,
+           -2.9136225671936016,
+           -2.9359229539527627,
+           -2.939312411388092,
+           -2.9237037836389996,
+           -2.889375527012486,
+           -2.8369632572735553,
+           -2.767443281111807,
+           -2.682108530402329,
+           -2.5825374972216935,
+           -2.470556932068995,
+           -2.3481992133964247,
+           -2.2176554198581298,
+           -2.0812252346786,
+           -1.9412648818847549,
+           -1.8001343351848305,
+           -1.6601450510796245,
+           -1.523509458168581,
+           -1.3922933851260828,
+           -1.2683725317640469,
+           -1.1533939829614857,
+           -1.0487436366734766,
+           -0.9555202679610916,
+           -0.874516784743127,
+           -0.8062090519031802,
+           -0.7507524729442027,
+           -0.7079863272148028,
+           -0.6774456705686049,
+           -0.6583804228541416,
+           -0.6497810914118158,
+           -0.650410420055009,
+           -0.6588401117438621,
+           -0.6734916537652204,
+           -0.6926801796024611,
+           -0.7146602340840174,
+           -0.7376722694313141,
+           -0.7599886903615299,
+           -0.7799582865769895,
+           -0.7960479401908039,
+           -0.8068805725742821,
+           -0.8112683977524452,
+           -0.8082406751691168,
+           -0.7970653001700414,
+           -0.7772637321990825,
+           -0.7486189343598274,
+           -0.7111761792595854,
+           -0.6652367603391832,
+           -0.6113448305444841,
+           -0.5502677666078961,
+           -0.4829706229357468,
+           -0.4105853899707695,
+           -0.3343759041261708,
+           -0.2556993666500894,
+           -0.17596551431377563,
+           -0.0965945434846216,
+           -0.018974919485804844,
+           0.05557779558885145,
+           0.12585999125735442,
+           0.19081588407207423,
+           0.24956925405089297,
+           0.3014501840352982,
+           0.34601607392960254,
+           0.38306635060304595,
+           0.4126504580865966,
+           0.4350688874198292,
+           0.45086718667483694,
+           0.46082307471317085,
+           0.4659269624772536,
+           0.4673563585046394,
+           0.46644479648741527,
+           0.46464606797662733,
+           0.46349466904324005,
+           0.46456347263048764,
+           0.4694197158133705,
+           0.47958044120069454,
+           0.4964685529411025,
+           0.521370639615017,
+           0.5553976788342144,
+           0.5994496724890706,
+           0.6541851688533673,
+           0.7199965104266464,
+           0.7969915073332421,
+           0.8849820787236764,
+           0.9834802328215234,
+           1.091701574279598,
+           1.2085763398686824,
+           1.332767774887739,
+           1.462697477758429,
+           1.59657716367029,
+           1.7324461342997683,
+           1.8682135936541573,
+           2.0017048236980046,
+           2.1307101308092955,
+           2.2530353979090245,
+           2.366553029283829,
+           2.4692520569523024,
+           2.55928618945616,
+           2.6350186259848067,
+           2.6950625298234985,
+           2.738316153587328,
+           2.763991732224062,
+           2.7716374053730943,
+           2.761151594841606,
+           2.7327894417238534,
+           2.6871610967015744,
+           2.6252218517192647,
+           2.548254296778834,
+           2.4578428772653647,
+           2.35584141031102,
+           2.24433428874243,
+           2.125592253969209,
+           2.0020237510068277,
+           1.8761229864447284,
+           1.7504158909221783,
+           1.627405239566108,
+           1.5095162055903277
+          ],
+          [
+           1.4315192524911562,
+           1.3281341474005373,
+           1.2355415549898165,
+           1.155466672086848,
+           1.0893459701094137,
+           1.0382967607116094,
+           1.0030940397331436,
+           0.9841551345692778,
+           0.981532494252663,
+           0.9949147677497805,
+           1.0236361189427192,
+           1.0666935312869428,
+           1.1227716659612048,
+           1.1902746590520796,
+           1.2673640802664727,
+           1.3520021317871838,
+           1.441999044650587,
+           1.5350635343438919,
+           1.6288551094734989,
+           1.7210369889402932,
+           1.8093283749422848,
+           1.891554851433795,
+           1.9656957297795632,
+           2.0299272438963514,
+           2.0826606041208966,
+           2.1225740496830228,
+           2.1486381907194074,
+           2.1601340984636654,
+           2.15666378241587,
+           2.138152881454799,
+           2.104845587346495,
+           2.057292009188672,
+           1.9963283713230915,
+           1.9230506106193557,
+           1.8387820975294231,
+           1.7450363450566067,
+           1.6434756873740088,
+           1.535867002421263,
+           1.4240356181884382,
+           1.309818579027268,
+           1.195018455396257,
+           1.0813588578697395,
+           0.9704427646823947,
+           0.8637146929221804,
+           0.7624276387944763,
+           0.6676155848596347,
+           0.580072225062293,
+           0.5003363954732236,
+           0.4286845240919935,
+           0.3651302312348251,
+           0.30943102755477003,
+           0.26110187426747816,
+           0.21943519428526176,
+           0.18352675812201621,
+           0.15230671876632307,
+           0.12457493898774717,
+           0.0990396460197787,
+           0.07435836496804783,
+           0.04918002571071026,
+           0.022187109894180934,
+           -0.007863294429819635,
+           -0.042100632975480105,
+           -0.08150526436266,
+           -0.12687703730056768,
+           -0.17880891517432118,
+           -0.23766636583019723,
+           -0.3035730842810318,
+           -0.37640345127050767,
+           -0.4557819553186154,
+           -0.5410896244626963,
+           -0.6314773310071572,
+           -0.7258856528395942,
+           -0.8230708028251736,
+           -0.921635977828823,
+           -1.0200673351104106,
+           -1.1167736798642691,
+           -1.2101288467096336,
+           -1.298515682586956,
+           -1.3803704907412189,
+           -1.4542267765517185,
+           -1.5187571464507936,
+           -1.5728122508769489,
+           -1.6154557302127928,
+           -1.645994217336292,
+           -1.6640015694644597,
+           -1.6693366424765026,
+           -1.662154079410645,
+           -1.6429077574195077,
+           -1.6123467198675536,
+           -1.5715036079301679,
+           -1.5216757943356738,
+           -1.464399606081263,
+           -1.4014181984449172,
+           -1.3346438050076506,
+           -1.2661152336086794,
+           -1.1979516025139176,
+           -1.1323034114271284,
+           -1.0713021157448728,
+           -1.0170094177347155,
+           -0.971367503887338,
+           -0.9361514430759721,
+           -0.9129249156155972,
+           -0.9030003698550257,
+           -0.9074046022786704,
+           -0.9268506316382982,
+           -0.9617165903915116,
+           -1.012032191249025,
+           -1.077473146938804,
+           -1.1573637317505705,
+           -1.2506874786476319,
+           -1.3561058104789376,
+           -1.4719842128659717,
+           -1.5964253743513495,
+           -1.7273085508384536,
+           -1.8623342603610222,
+           -1.9990732845069756,
+           -2.135018847574024,
+           -2.267640766349899,
+           -2.3944403142206334,
+           -2.513004524340288,
+           -2.6210586683292507,
+           -2.7165156891386846,
+           -2.797521438312844,
+           -2.862494667166036,
+           -2.910160845955097,
+           -2.9395790319418786,
+           -2.9501611727283827,
+           -2.9416834113797186,
+           -2.914289150238914,
+           -2.8684838263462016,
+           -2.8051215482318708,
+           -2.7253839367669963,
+           -2.630751697041358,
+           -2.5229696194193894,
+           -2.4040058618553455,
+           -2.276006498507713,
+           -2.1412464284785995,
+           -2.0020778205118863,
+           -1.8608773227702642,
+           -1.7199932901400288,
+           -1.5816942743854085,
+           -1.448119985141503,
+           -1.3212358631902033,
+           -1.2027923134155492,
+           -1.0942895256674505,
+           -0.9969486704724916,
+           -0.9116900966535645,
+           -0.8391189834440176,
+           -0.7795187149449501,
+           -0.7328520543598677,
+           -0.6987700040616998,
+           -0.6766280499298618,
+           -0.6655093091623374,
+           -0.6642539343242994,
+           -0.6714939768182964,
+           -0.6856927839016529,
+           -0.7051878979670292,
+           -0.7282363475801655,
+           -0.7530611686161611,
+           -0.7778979719311994,
+           -0.8010403817988451,
+           -0.8208832065363523,
+           -0.8359622683221244,
+           -0.8449899114298792,
+           -0.8468853245856345,
+           -0.8407989508968818,
+           -0.8261304142898427,
+           -0.8025395606637172,
+           -0.76995039073597,
+           -0.7285478452846713,
+           -0.6787675875511677,
+           -0.6212791073055574,
+           -0.556962641971443,
+           -0.48688056795550383,
+           -0.4122440559682971,
+           -0.33437590412617074,
+           -0.25467055898406826,
+           -0.1745524049567331,
+           -0.0954334450900521,
+           -0.01867150979525757,
+           0.05446988536637187,
+           0.12285895604986073,
+           0.1855293347619715,
+           0.24170911859511518,
+           0.2908444929133313,
+           0.3326172861109194,
+           0.36695596849392026,
+           0.39403977892531716,
+           0.414295841804914,
+           0.4283893196895603,
+           0.43720682876582095,
+           0.4418335208492272,
+           0.4435244021190813,
+           0.4436706111678518,
+           0.4437615132636845,
+           0.4453435805573985,
+           0.44997711641063814,
+           0.4591919437883532,
+           0.474443211121588,
+           0.49706847328938464,
+           0.5282471802067736,
+           0.5689636514923443,
+           0.6199745341011029,
+           0.6817816326168886,
+           0.7546108717196534,
+           0.8383980003728783,
+           0.932781481213618,
+           1.0371028305804968,
+           1.150414489000593,
+           1.2714951133892312,
+           1.3988719953974782,
+           1.5308501299367507,
+           1.6655472884361266,
+           1.8009342971014912,
+           1.9348795852346163,
+           2.065196955958323,
+           2.1896954443521635,
+           2.3062300682823436,
+           2.412752246679193,
+           2.5073586595254023,
+           2.5883373534780643,
+           2.6542099562194563,
+           2.703768949948803,
+           2.736109067824085,
+           2.7506520139262265,
+           2.747163864153129,
+           2.7257646785623915,
+           2.6869300408659442,
+           2.631484433529814,
+           2.5605865525466203,
+           2.475706859648615,
+           2.3785978567766444,
+           2.271257743433639,
+           2.1558882778187236,
+           2.0348478034247326,
+           1.910600520626944,
+           1.785663174791612,
+           1.662550396319123,
+           1.5437199622245599,
+           1.431519252491157
+          ],
+          [
+           1.3583319037563824,
+           1.2629031236397317,
+           1.1794252730780277,
+           1.1094454136982284,
+           1.0542021053184731,
+           1.0145993029273663,
+           0.9911878714788008,
+           0.9841551345692776,
+           0.9933226819254007,
+           1.0181524642863786,
+           1.0577610074984847,
+           1.1109413852315424,
+           1.1761924063572602,
+           1.2517543031460319,
+           1.3356500541583318,
+           1.4257313447091315,
+           1.5197280612227433,
+           1.6153001362220807,
+           1.710090509995828,
+           1.8017779543333805,
+           1.8881285135452948,
+           1.9670443579813954,
+           2.03660891436385,
+           2.0951272336989026,
+           2.1411606788793014,
+           2.1735551572925536,
+           2.1914622852281322,
+           2.1943530466069783,
+           2.1820236941728943,
+           2.154593832187319,
+           2.112496811135157,
+           2.0564627522551686,
+           1.9874946982426809,
+           1.9068385518513133,
+           1.815947612296175,
+           1.7164426467213272,
+           1.6100685374517023,
+           1.4986486228170341,
+           1.384037898186844,
+           1.2680762633711988,
+           1.1525429923340413,
+           1.0391135615879528,
+           0.9293199057757131,
+           0.8245150745826119,
+           0.725843146709527,
+           0.6342151172109796,
+           0.5502913176250835,
+           0.47447075798296406,
+           0.40688760030320426,
+           0.3474147890925907,
+           0.2956746803360733,
+           0.25105633110582937,
+           0.21273894176659047,
+           0.17972078607935202,
+           0.15085282524156524,
+           0.12487608353989678,
+           0.10046176879320243,
+           0.07625305248699676,
+           0.05090738414297881,
+           0.023138203020756584,
+           -0.008245072022124957,
+           -0.04429984725215785,
+           -0.08591695215954293,
+           -0.13379193016196916,
+           -0.1884017984766673,
+           -0.2499879110832301,
+           -0.3185453996959341,
+           -0.3938194963289317,
+           -0.47530886171322284,
+           -0.5622758610568875,
+           -0.6537635470647924,
+           -0.7486189343598261,
+           -0.8455219839407848,
+           -0.9430195652846055,
+           -1.039563531004699,
+           -1.1335519280080086,
+           -1.2233722827042433,
+           -1.3074458382503527,
+           -1.3842715906301526,
+           -1.4524689684304368,
+           -1.5108180286057005,
+           -1.558296096711595,
+           -1.5941098636978,
+           -1.6177220603597677,
+           -1.6288719622910335,
+           -1.6275891294142044,
+           -1.61419995116586,
+           -1.589326747032469,
+           -1.5538793579463481,
+           -1.5090393524279608,
+           -1.4562371576049782,
+           -1.3971226046932717,
+           -1.3335295466926507,
+           -1.267435358703837,
+           -1.2009162645617601,
+           -1.1360995440258452,
+           -1.0751137597485876,
+           -1.0200382004667592,
+           -0.9728527648146023,
+           -0.9353895080575572,
+           -0.9092870418427229,
+           -0.8959489154573063,
+           -0.8965070175064878,
+           -0.9117909214886754,
+           -0.9423039602233777,
+           -0.9882066558140594,
+           -1.0493079576376767,
+           -1.1250645549759184,
+           -1.214588337867108,
+           -1.3166618842728355,
+           -1.429761658497807,
+           -1.552088419703053,
+           -1.6816041648731002,
+           -1.816074772018227,
+           -1.953117370611114,
+           -2.0902513506875104,
+           -2.2249518325330255,
+           -2.354704357645472,
+           -2.477059530226204,
+           -2.5896863376072328,
+           -2.6904229078072905,
+           -2.7773235221232326,
+           -2.8487007888633387,
+           -2.9031619988794546,
+           -2.9396388216723643,
+           -2.957409659170495,
+           -2.9561141489617215,
+           -2.935759495539019,
+           -2.896718502454905,
+           -2.839719375436447,
+           -2.7658275616949735,
+           -2.6764200791271286,
+           -2.573152966269362,
+           -2.457922645440174,
+           -2.332822133573503,
+           -2.2000931543850877,
+           -2.0620752988601976,
+           -1.921153446381116,
+           -1.7797046945915544,
+           -1.6400460515164008,
+           -1.5043841184589282,
+           -1.374767937470976,
+           -1.2530460941525565,
+           -1.1408290572961473,
+           -1.0394576041998764,
+           -0.9499780276566899,
+           -0.873124651496362,
+           -0.8093100003218836,
+           -0.7586227802378699,
+           -0.7208336355923297,
+           -0.6954084567815546,
+           -0.681528830683724,
+           -0.6781190528014792,
+           -0.6838789629360439,
+           -0.6973217280273735,
+           -0.7168155800365251,
+           -0.7406284262139032,
+           -0.7669741859531963,
+           -0.7940596741531751,
+           -0.8201308463540565,
+           -0.8435172458989372,
+           -0.862673547272368,
+           -0.8762171711468935,
+           -0.8829610534010843,
+           -0.8819407797073805,
+           -0.8724354459141197,
+           -0.8539817685766581,
+           -0.8263811454598174,
+           -0.7896995481944872,
+           -0.7442603139159683,
+           -0.6906300849826215,
+           -0.6295983211785182,
+           -0.5621509727336529,
+           -0.48943905093114864,
+           -0.4127429622893831,
+           -0.33343357907140686,
+           -0.252931100516209,
+           -0.17266281367251685,
+           -0.09402088869685128,
+           -0.018321340323403698,
+           0.05323474497234757,
+           0.11959667697688572,
+           0.1798953728037264,
+           0.23346947038545837,
+           0.2798856368326219,
+           0.3189525154022365,
+           0.35072792051426965,
+           0.3755190661423991,
+           0.39387579452813576,
+           0.40657695491926144,
+           0.414610261278314,
+           0.419146129092537,
+           0.42150615019050974,
+           0.42312700678771203,
+           0.4255207482083653,
+           0.43023245273020694,
+           0.4387963702179363,
+           0.4526916867405366,
+           0.4732990689905769,
+           0.5018591335472845,
+           0.5394339440939262,
+           0.5868725695902735,
+           0.6447816397972758,
+           0.7135017138052661,
+           0.7930901352903463,
+           0.8833108886132255,
+           0.9836317965276025,
+           1.0932292174798597,
+           1.2110002128026103,
+           1.3355819662068356,
+           1.4653780545538264,
+           1.598590994529678,
+           1.7332603289278572,
+           1.867305372820844,
+           1.9985716175960053,
+           2.1248796927538836,
+           2.2440757140329635,
+           2.354081803692552,
+           2.452945555806704,
+           2.538887236615242,
+           2.6103435570160443,
+           2.6660069300985536,
+           2.7048592294327745,
+           2.726199191190066,
+           2.7296627520209538,
+           2.7152357813540933,
+           2.683258847364981,
+           2.63442384590015,
+           2.5697625164997926,
+           2.4906270645796798,
+           2.3986632990443177,
+           2.2957768754484364,
+           2.184093401867813,
+           2.065913313781063,
+           1.9436625518340054,
+           1.819840179215729,
+           1.6969641509808453,
+           1.5775164941329913,
+           1.4638891734794781,
+           1.3583319037563832
+          ],
+          [
+           1.2905733574739537,
+           1.2039024260008881,
+           1.1302280407423928,
+           1.0709060514028341,
+           1.0269666476144201,
+           0.9990928080787997,
+           0.9876066425810849,
+           0.9924639303723984,
+           1.0132569635820583,
+           1.0492256070845498,
+           1.0992762914073773,
+           1.1620084675600606,
+           1.2357478766499548,
+           1.3185858270951143,
+           1.4084235320209624,
+           1.5030204424186624,
+           1.6000454206586556,
+           1.6971295361608218,
+           1.7919192318965813,
+           1.8821286076814938,
+           1.965589593904875,
+           2.0402988466846477,
+           2.104460280952142,
+           2.156522269494117,
+           2.1952086707030625,
+           2.219543002341477,
+           2.228865249159001,
+           2.2228409744747197,
+           2.2014625953316878,
+           2.1650428728591735,
+           2.114200859300335,
+           2.049840726104039,
+           1.9731240690450123,
+           1.8854364423238625,
+           1.7883490102005184,
+           1.6835763186133765,
+           1.572931277684733,
+           1.4582785069018487,
+           1.34148722667271,
+           1.2243848821904755,
+           1.1087126581447209,
+           0.9960839865730676,
+           0.8879470665524888,
+           0.7855523056636965,
+           0.6899254620260785,
+           0.6018471155493149,
+           0.5218389317042499,
+           0.45015700477569676,
+           0.3867923846867812,
+           0.33147870669719587,
+           0.28370666123534377,
+           0.2427448664095526,
+           0.20766654274820798,
+           0.17738124253427645,
+           0.15067075841511893,
+           0.12622823097816582,
+           0.1026993953072261,
+           0.07872485415393138,
+           0.05298224156655592,
+           0.02422714618617942,
+           -0.008668302214701292,
+           -0.0466802169061298,
+           -0.0906020540679165,
+           -0.1410188601195708,
+           -0.1982873637120809,
+           -0.262522457067292,
+           -0.3335904447627328,
+           -0.41110926162126993,
+           -0.4944556795497184,
+           -0.5827793405897976,
+           -0.6750232747318597,
+           -0.7699503907359696,
+           -0.866175270637169,
+           -0.962200457797042,
+           -1.05645630789875,
+           -1.1473433752572344,
+           -1.2332762357335043,
+           -1.312727604256857,
+           -1.3842715906301526,
+           -1.4466249523542298,
+           -1.4986852473540027,
+           -1.5395648616864634,
+           -1.5686199858195427,
+           -1.5854737354880482,
+           -1.5900327564520667,
+           -1.5824968131687414,
+           -1.5633610354623808,
+           -1.533410680419834,
+           -1.4937084543911838,
+           -1.4455746274604693,
+           -1.390560355382133,
+           -1.3304147971802105,
+           -1.2670467760289443,
+           -1.2024818726568371,
+           -1.1388159607576376,
+           -1.0781662896896715,
+           -1.022621288638368,
+           -0.9741903066070154,
+           -0.9347545129958771,
+           -0.9060201637748874,
+           -0.8894753887400064,
+           -0.8863515771957475,
+           -0.8975903344638135,
+           -0.9238168523839054,
+           -0.9653203865557134,
+           -1.0220423651079762,
+           -1.0935724723475988,
+           -1.1791528601550885,
+           -1.277690445098087,
+           -1.3877770546956032,
+           -1.5077169968424098,
+           -1.6355614467394088,
+           -1.769148880180337,
+           -1.906150634785677,
+           -2.044120555375398,
+           -2.180547579225237,
+           -2.312910043940344,
+           -2.4387304569172468,
+           -2.5556294519488576,
+           -2.661377675810722,
+           -2.753944395254162,
+           -2.8315416915824048,
+           -2.892663214045997,
+           -2.936116592140296,
+           -2.9610487573900763,
+           -2.9669635937046452,
+           -2.9537315177800925,
+           -2.9215907828746097,
+           -2.871140495918034,
+           -2.8033255345539807,
+           -2.7194137425696963,
+           -2.6209659645842347,
+           -2.509799649412395,
+           -2.3879469021180038,
+           -2.2576079937757374,
+           -2.1211014422710055,
+           -1.98081185458484,
+           -1.8391367691101321,
+           -1.6984337545140507,
+           -1.5609690091292405,
+           -1.428868662202566,
+           -1.3040739066724731,
+           -1.1883009943154232,
+           -1.0830070005913048,
+           -0.9893621214261068,
+           -0.9082291011187511,
+           -0.8401502136065774,
+           -0.785342032862657,
+           -0.7436980368450806,
+           -0.7147988979027589,
+           -0.6979301255854758,
+           -0.6921065500073859,
+           -0.6961029696344061,
+           -0.7084901406245683,
+           -0.7276751592198216,
+           -0.7519451872099517,
+           -0.779513395599852,
+           -0.808565955079846,
+           -0.8373088847861807,
+           -0.8640135834716751,
+           -0.8870599091705191,
+           -0.9049757435920652,
+           -0.9164720739716627,
+           -0.9204727454446836,
+           -0.9161381781045785,
+           -0.9028825011573073,
+           -0.8803837279703393,
+           -0.8485867759915676,
+           -0.8076993199266839,
+           -0.7581806505588823,
+           -0.7007238905374327,
+           -0.6362320878495138,
+           -0.5657888632685312,
+           -0.49062442593898026,
+           -0.4120778879607934,
+           -0.33155690145824923,
+           -0.2504957078522636,
+           -0.17031272725844107,
+           -0.0923688251712947,
+           -0.017927373662428598,
+           0.051882824253419384,
+           0.1161007543955849,
+           0.1739616640649025,
+           0.22492002057425958,
+           0.2686663326745518,
+           0.3051373719471285,
+           0.3345195032932774,
+           0.3572450133487041,
+           0.37398150842963285,
+           0.3856146348401048,
+           0.39322454943665786,
+           0.3980567328076069,
+           0.40148788709361316,
+           0.40498779153613906,
+           0.4100780979370775,
+           0.4182891325409467,
+           0.4311158282245179,
+           0.4499739397859454,
+           0.47615769476782066,
+           0.5108000025612216,
+           0.554836286191921,
+           0.6089729155770154,
+           0.6736611102380561,
+           0.7490770461781455,
+           0.8351087491568518,
+           0.9313501886964571,
+           1.0371028079880438,
+           1.1513845388889636,
+           1.272946163046932,
+           1.4002946945470267,
+           1.531723281001985,
+           1.6653469531696625,
+           1.7991434021824209,
+           1.9309978321239867,
+           2.058750827323574,
+           2.180248091124649,
+           2.293390858162844,
+           2.3961857568049227,
+           2.4867929030834635,
+           2.563571042192798,
+           2.625118617630246,
+           2.6703097398848916,
+           2.698324144017621,
+           2.708670365725865,
+           2.7012015251617107,
+           2.676123283004089,
+           2.633993719815413,
+           2.5757150829952034,
+           2.5025175409590683,
+           2.415935276743673,
+           2.317775438351264,
+           2.2100806362596987,
+           2.0950858353855026,
+           1.975170625539343,
+           1.852807967687282,
+           1.7305106003310446,
+           1.6107763488906326,
+           1.496033609654558,
+           1.388588277927491,
+           1.290573357473956
+          ],
+          [
+           1.228816881606515,
+           1.1516312270841547,
+           1.0883660888304758,
+           1.0401746456449463,
+           1.0078700212936174,
+           0.9919084681290973,
+           0.9923806518569952,
+           1.009011225806372,
+           1.0411666861794546,
+           1.0878713032954626,
+           1.1478307325816448,
+           1.2194627276478793,
+           1.3009342106114514,
+           1.3902038059651043,
+           1.485068817301267,
+           1.5832155241754287,
+           1.682271601753472,
+           1.7798594204084028,
+           1.8736489671605545,
+           1.9614091460982184,
+           2.0410562602296403,
+           2.110698551421084,
+           2.168675776280004,
+           2.2135929214975927,
+           2.2443473091243495,
+           2.2601485068509386,
+           2.2605306365121227,
+           2.245356861306193,
+           2.214816023992244,
+           2.1694115998580346,
+           2.109943314823462,
+           2.0374819560730217,
+           1.9533380657558832,
+           1.8590253535681736,
+           1.7562197879046944,
+           1.646715424740733,
+           1.5323781060955342,
+           1.4150982041240354,
+           1.2967436015814453,
+           1.1791140843404646,
+           1.063898277288995,
+           0.9526341825008176,
+           0.846674279953978,
+           0.7471560288213444,
+           0.6549784646094927,
+           0.5707854278153864,
+           0.49495578735953366,
+           0.4276008412056541,
+           0.36856889186003033,
+           0.3174568105168665,
+           0.27362822510976514,
+           0.23623779893095984,
+           0.20426091202109645,
+           0.17652792108383655,
+           0.15176205865472203,
+           0.12861994152337292,
+           0.10573359422900357,
+           0.08175285740824612,
+           0.05538704374875443,
+           0.02544472643851743,
+           -0.009129404288605541,
+           -0.04922160293299378,
+           -0.09552093200560254,
+           -0.14849668407570826,
+           -0.20838197452539986,
+           -0.27516395585141096,
+           -0.3485809315922005,
+           -0.4281264679094411,
+           -0.5130604180851713,
+           -0.6024265943466454,
+           -0.6950766470921593,
+           -0.7896995481944858,
+           -0.8848559267631559,
+           -0.979016376336022,
+           -1.0706027452559705,
+           -1.1580313397275153,
+           -1.239756913873199,
+           -1.314316294476027,
+           -1.380370490741219,
+           -1.4367441713435496,
+           -1.4824614515152372,
+           -1.5167770205258468,
+           -1.5392017524791752,
+           -1.549522078142081,
+           -1.547812549203903,
+           -1.5344411951400607,
+           -1.5100674525319304,
+           -1.4756326328074605,
+           -1.4323430822737826,
+           -1.381646373319041,
+           -1.325201043133036,
+           -1.2648405617792748,
+           -1.2025323607774103,
+           -1.1403328827503967,
+           -1.080339718867209,
+           -1.024641981052182,
+           -0.9752701081551817,
+           -0.9341463280941038,
+           -0.903036990728586,
+           -0.8835079489817408,
+           -0.8768840993179486,
+           -0.8842140986554597,
+           -0.9062411553753368,
+           -0.9433806501471912,
+           -0.9957051812534818,
+           -1.0629374528617979,
+           -1.1444512375544236,
+           -1.2392804509392545,
+           -1.3461361810623043,
+           -1.4634313233941691,
+           -1.5893122880751573,
+           -1.7216970743943267,
+           -1.858318852367115,
+           -1.9967740565819978,
+           -2.1345738865313484,
+           -2.269198023167217,
+           -2.3981493155259184,
+           -2.5190081653431404,
+           -2.629485342297515,
+           -2.727471997788846,
+           -2.811085710142264,
+           -2.8787114872685753,
+           -2.9290367718505492,
+           -2.9610796361774465,
+           -2.974209515363955,
+           -2.9681600049349637,
+           -2.9430334373214464,
+           -2.899297147107046,
+           -2.8377715321377863,
+           -2.759610212061069,
+           -2.6662727727683375,
+           -2.5594907600406214,
+           -2.4412277441987777,
+           -2.3136344159057693,
+           -2.1789997881195324,
+           -2.039699667794118,
+           -1.898143621163225,
+           -1.7567216869016173,
+           -1.6177520914663277,
+           -1.483431190539922,
+           -1.355786800547384,
+           -1.2366359962359716,
+           -1.1275483365209182,
+           -1.0298153440655238,
+           -0.9444269077988722,
+           -0.8720551056687913,
+           -0.8130457616498654,
+           -0.7674178609166719,
+           -0.73487075484921,
+           -0.7147988979027585,
+           -0.7063136760143135,
+           -0.7082717156088959,
+           -0.7193089075868944,
+           -0.7378792456899392,
+           -0.7622974666326647,
+           -0.790784393048917,
+           -0.8215138216882213,
+           -0.8526597697728127,
+           -0.8824428926227319,
+           -0.9091749154708696,
+           -0.9312999809790287,
+           -0.9474318997726121,
+           -0.9563864021029829,
+           -0.9572076216717534,
+           -0.9491881943122891,
+           -0.9318825207616376,
+           -0.9051129199473887,
+           -0.868968582576507,
+           -0.8237974197187161,
+           -0.7701910828663903,
+           -0.7089636060531087,
+           -0.6411242826506942,
+           -0.5678455353759886,
+           -0.49042666417004394,
+           -0.4102544598122974,
+           -0.32876174882851167,
+           -0.24738498551619678,
+           -0.16752202850899567,
+           -0.09049123171837584,
+           -0.01749294294855607,
+           0.05042556107062055,
+           0.11240076539291909,
+           0.16777841040646407,
+           0.21613310137559172,
+           0.25728150082909396,
+           0.2912887381106492,
+           0.31846784737502565,
+           0.33937222729996996,
+           0.3547812981720657,
+           0.3656797101655179,
+           0.3732306260401779,
+           0.37874375783007275,
+           0.38363897639255856,
+           0.3894064313822497,
+           0.39756421425899546,
+           0.40961466588283285,
+           0.4270004712911319,
+           0.4510616962936099,
+           0.48299490318569976,
+           0.5238154365335487,
+           0.5743238957169698,
+           0.6350777105250016,
+           0.7063686120354059,
+           0.788206646325631,
+           0.8803112168322197,
+           0.9821094664058264,
+           1.0927421266420656,
+           1.2110767744731044,
+           1.3357282489636289,
+           1.4650857994452038,
+           1.5973463641046461,
+           1.7305532202391956,
+           1.8626391075876383,
+           1.9914728079840334,
+           2.114908071071623,
+           2.2308337093659176,
+           2.337223648307108,
+           2.4321857091238686,
+           2.514007924635411,
+           2.5812012400933346,
+           2.6325375316220803,
+           2.6670819818606324,
+           2.684218983483115,
+           2.6836708932267928,
+           2.66550912820658,
+           2.6301572785377654,
+           2.5783861011854814,
+           2.511300454851314,
+           2.4303184298294154,
+           2.3371431153621116,
+           2.2337276254730902,
+           2.1222341681719583,
+           2.0049880882755327,
+           1.8844279372976227,
+           1.7630527218786334,
+           1.6433675526323712,
+           1.5278289563270824,
+           1.4187911249579357,
+           1.318454355219011,
+           1.228816881606516
+          ],
+          [
+           1.1735849638850242,
+           1.10653176488535,
+           1.0541935883981979,
+           1.0175111980233944,
+           0.9970737924560595,
+           0.9931070658451844,
+           1.0054695090277932,
+           1.0336570232640916,
+           1.0768157208351234,
+           1.1337625928417985,
+           1.2030135384778222,
+           1.2828180764563069,
+           1.3711999023592878,
+           1.4660023192472622,
+           1.5649374562033935,
+           1.6656381032990923,
+           1.765710933807365,
+           1.862789856708396,
+           1.9545882452442935,
+           2.0389488203537014,
+           2.1138900303734327,
+           2.17764785883241,
+           2.228712108199126,
+           2.265856346168621,
+           2.2881608590266382,
+           2.295028129878593,
+           2.2861905437817414,
+           2.261710212510251,
+           2.221971004105598,
+           2.16766305177662,
+           2.099760198457372,
+           2.0194910029489868,
+           1.9283040869163857,
+           1.8278287353462697,
+           1.7198317731679615,
+           1.6061718249453016,
+           1.488752120866266,
+           1.3694730393844046,
+           1.2501855742280419,
+           1.1326468812562438,
+           1.0184789997076351,
+           0.909131754374911,
+           0.805850732430947,
+           0.709651093932153,
+           0.6212978218716073,
+           0.5412928499429968,
+           0.4698693281568526,
+           0.40699310262341926,
+           0.3523713008184876,
+           0.30546773213826683,
+           0.2655246400895027,
+           0.2315901814054007,
+           0.20255086276227277,
+           0.17716804121363533,
+           0.15411749306652864,
+           0.13203098022204418,
+           0.10953869486266582,
+           0.0853114439722228,
+           0.058101444974927544,
+           0.026780642497874676,
+           -0.009624477111641484,
+           -0.05190250405697224,
+           -0.1006319700394313,
+           -0.15616213625595862,
+           -0.21860022594128162,
+           -0.28780545463553,
+           -0.3633900338824896,
+           -0.44472714192787355,
+           -0.5309656728128315,
+           -0.6210513976701674,
+           -0.7137540035412687,
+           -0.8076993199266832,
+           -0.9014059055148264,
+           -0.9933250506214185,
+           -1.0818831578149835,
+           -1.1655253964030754,
+           -1.2427594876537253,
+           -1.312198467869718,
+           -1.3726012960336798,
+           -1.4229102212768507,
+           -1.4622839017435494,
+           -1.4901253686775797,
+           -1.5061040552426548,
+           -1.5101712556113245,
+           -1.5025685426047173,
+           -1.483828847602094,
+           -1.454770090201722,
+           -1.4164814326230057,
+           -1.3703024204104048,
+           -1.317795451961568,
+           -1.2607121902147407,
+           -1.2009546861946265,
+           -1.1405321220841824,
+           -1.0815141975618625,
+           -1.0259822743576605,
+           -0.9759794579844691,
+           -0.9334608307125626,
+           -0.9002450551063507,
+           -0.8779685426034485,
+           -0.8680433272021598,
+           -0.8716197015826821,
+           -0.8895545638721137,
+           -0.9223862903816061,
+           -0.9703167961967358,
+           -1.0332012752042634,
+           -1.1105459281278953,
+           -1.201513795881598,
+           -1.304938620702347,
+           -1.4193464638614537,
+           -1.5429846210214075,
+           -1.6738571991099302,
+           -1.8097665562810432,
+           -1.9483596631188758,
+           -2.0871783222512263,
+           -2.223712087966799,
+           -2.3554526596429164,
+           -2.479948484480938,
+           -2.5948582971837926,
+           -2.6980023470196675,
+           -2.7874101156696582,
+           -2.861363411090902,
+           -2.9184338313656633,
+           -2.9575137255187474,
+           -2.9778399323424507,
+           -2.979009749626232,
+           -2.960988770681061,
+           -2.924110418187398,
+           -2.8690672024829063,
+           -2.796893927647366,
+           -2.7089432593674116,
+           -2.6068542489419717,
+           -2.4925145735445744,
+           -2.368017399975747,
+           -2.2356139040636096,
+           -2.097662577595346,
+           -1.9565765268012107,
+           -1.8147700092579007,
+           -1.6746054686443055,
+           -1.538342308826639,
+           -1.4080886007799622,
+           -1.2857568391129053,
+           -1.1730247613997564,
+           -1.0713021157448732,
+           -0.9817041132025112,
+           -0.905032135558875,
+           -0.8417620896772365,
+           -0.79204061155468,
+           -0.7556891310893713,
+           -0.7322156170503322,
+           -0.7208336355923292,
+           -0.7204881794378409,
+           -0.7298875628724453,
+           -0.7475405339230623,
+           -0.7717976330045867,
+           -0.8008957298784226,
+           -0.8330046002970822,
+           -0.8662743618688938,
+           -0.8988825764071152,
+           -0.9290798435331599,
+           -0.9552327570471981,
+           -0.9758631702981116,
+           -0.9896828175210981,
+           -0.995622462263424,
+           -0.9928548884066923,
+           -0.9808112102380924,
+           -0.9591901514385993,
+           -0.9279601243536008,
+           -0.8873541259080543,
+           -0.8378576503618703,
+           -0.780189997146388,
+           -0.7152795198078731,
+           -0.6442335154002978,
+           -0.568303588679341,
+           -0.4888474387783931,
+           -0.40728810487114214,
+           -0.3250717694382626,
+           -0.24362525162658963,
+           -0.1643143279984057,
+           -0.0884039936283271,
+           -0.017021723662207628,
+           0.04887528452989667,
+           0.10852801355011496,
+           0.1613979249523157,
+           0.2071830541020018,
+           0.2458274621253525,
+           0.2775237796016337,
+           0.30270875703203987,
+           0.32205191985369697,
+           0.3364376062224077,
+           0.3469408393789042,
+           0.35479764872816183,
+           0.36137060066745935,
+           0.3681104279486012,
+           0.3765147516835917,
+           0.38808497029263267,
+           0.4042824426690341,
+           0.42648511719965526,
+           0.45594575335125986,
+           0.493752848367129,
+           0.5407953190033088,
+           0.5977318986742467,
+           0.664966096056418,
+           0.7426274249238058,
+           0.8305594601241286,
+           0.9283151049855664,
+           1.0351592752830927,
+           1.1500790186767929,
+           1.271800900908196,
+           1.3988153056966275,
+           1.5294071188356184,
+           1.661692102883977,
+           1.7936581212126959,
+           1.9232102427436666,
+           2.0482186547399888,
+           2.1665682331466027,
+           2.2762085702571144,
+           2.3752032392265714,
+           2.4617770847626073,
+           2.5343603690652787,
+           2.5916286708648575,
+           2.6325375316220803,
+           2.6563509643192402,
+           2.662663083870036,
+           2.6514122805425817,
+           2.6228875349847955,
+           2.5777266611527607,
+           2.516906457091529,
+           2.4417249383705104,
+           2.353776020261461,
+           2.254917197774144,
+           2.1472309429388163,
+           2.032980692056218,
+           1.9145624282481486,
+           1.7944529732599621,
+           1.6751561844022849,
+           1.5591483057358912,
+           1.4488237457654056,
+           1.3464425464162815,
+           1.2540807700761152,
+           1.1735849638850258
+          ],
+          [
+           1.1253448913261368,
+           1.0689856012624193,
+           1.027999654262451,
+           1.0031074515603853,
+           0.9946693020830623,
+           1.0026784605480108,
+           1.0267624764390382,
+           1.066192808146713,
+           1.1199024605845032,
+           1.1865112146479466,
+           1.2643578375875186,
+           1.3515384990658013,
+           1.4459504723456842,
+           1.5453400772199966,
+           1.6473537239012523,
+           1.7495908474736122,
+           1.8496574823144238,
+           1.9452192160432462,
+           2.0340522832297627,
+           2.1140916097166333,
+           2.1834746976831734,
+           2.240580347483013,
+           2.284061342174715,
+           2.3128703712850114,
+           2.326278637951891,
+           2.323886774030411,
+           2.305627876541113,
+           2.2717626713357295,
+           2.2228670013023266,
+           2.1598120221229262,
+           2.0837376639744365,
+           1.996020078336363,
+           1.8982339313155099,
+           1.7921105251649432,
+           1.6794928250607604,
+           1.5622885364275425,
+           1.4424224175729552,
+           1.321789022222276,
+           1.2022070465916583,
+           1.085376406502558,
+           0.9728390930414437,
+           0.8659447524223697,
+           0.7658218096683126,
+           0.6733548097164623,
+           0.5891684872906539,
+           0.5136189024864904,
+           0.4467917968928138,
+           0.38850813982250576,
+           0.3383366505118605,
+           0.2956129045896012,
+           0.2594644661707432,
+           0.228841334780213,
+           0.20255086276227274,
+           0.17929618721771698,
+           0.15771713360956854,
+           0.13643248814327633,
+           0.1140825043350245,
+           0.08937050659325087,
+           0.061102480182421266,
+           0.028223591909879876,
+           -0.010149332143703147,
+           -0.05470023864143473,
+           -0.10589192647486476,
+           -0.16395036346622036,
+           -0.22885566692893472,
+           -0.30034000061959176,
+           -0.37789245992702664,
+           -0.4607708344624807,
+           -0.5480199571754828,
+           -0.6384961762964242,
+           -0.730897325192028,
+           -0.8237974197187151,
+           -0.9156851865829906,
+           -1.0050054227940257,
+           -1.090202108181094,
+           -1.169762142173339,
+           -1.2422585539422197,
+           -1.3063920422093473,
+           -1.3610297374103624,
+           -1.4052401436316315,
+           -1.4383233092404561,
+           -1.4598353911763087,
+           -1.4696069156054867,
+           -1.4677541936608385,
+           -1.4546835214234914,
+           -1.431087973917368,
+           -1.3979367891794108,
+           -1.3564575257862623,
+           -1.3081113608741346,
+           -1.2545620710756156,
+           -1.1976394015044745,
+           -1.1392976738424099,
+           -1.0815706100240332,
+           -1.0265234497836881,
+           -0.9762035158065749,
+           -0.9325904274517348,
+           -0.8975471817165959,
+           -0.872773307753733,
+           -0.8597612590352088,
+           -0.8597571361342217,
+           -0.8737267347212149,
+           -0.9023277900933873,
+           -0.9458891443347092,
+           -1.0043973985482149,
+           -1.0774914344860589,
+           -1.1644650016624287,
+           -1.2642773722645715,
+           -1.3755718716174987,
+           -1.496701901375024,
+           -1.6257638906811016,
+           -1.7606364417423659,
+           -1.8990247847308879,
+           -2.038509526432713,
+           -2.176598570797404,
+           -2.310781010162098,
+           -2.4385817353970842,
+           -2.557615492821484,
+           -2.665639126001255,
+           -2.7606007812510565,
+           -2.840684925853569,
+           -2.904352125999132,
+           -2.9503726548680413,
+           -2.9778531471365888,
+           -2.986255680945628,
+           -2.975408848022916,
+           -2.9455105628297464,
+           -2.8971225576825863,
+           -2.831156708012918,
+           -2.748853525478094,
+           -2.651753341819854,
+           -2.5416608786893677,
+           -2.420604053940921,
+           -2.2907880093834994,
+           -2.154545455426393,
+           -2.0142845118097332,
+           -1.8724352786787464,
+           -1.7313963973525768,
+           -1.5934828547026663,
+           -1.4608762492894523,
+           -1.3355786722516525,
+           -1.2193712630617843,
+           -1.1137783819949634,
+           -1.0200382004667596,
+           -0.9390803507859486,
+           -0.8715111023056032,
+           -0.8176063457671218,
+           -0.7773124763957684,
+           -0.7502550737424052,
+           -0.73575508711569,
+           -0.7328520543598668,
+           -0.7403337131430571,
+           -0.7567712119489011,
+           -0.7805589963091455,
+           -0.8099583376635782,
+           -0.843143390184117,
+           -0.8782486068962666,
+           -0.9134163217175656,
+           -0.9468433091225689,
+           -0.9768251678093012,
+           -1.0017974380195067,
+           -1.0203724523810487,
+           -1.0313710349546061,
+           -1.0338482996295089,
+           -1.0271129536423502,
+           -1.0107396808576776,
+           -0.9845743582758218,
+           -0.9487320435012134,
+           -0.9035878559700712,
+           -0.8497610559425783,
+           -0.7880927980595066,
+           -0.719618196313377,
+           -0.6455334805823192,
+           -0.567159147840371,
+           -0.4859001107254492,
+           -0.40320391984242065,
+           -0.3205181821828782,
+           -0.2392483152334472,
+           -0.16071676432449275,
+           -0.08612476987987633,
+           -0.016517702531774918,
+           0.04724511067229039,
+           0.10451526410020281,
+           0.1548741894966021,
+           0.19814560020336694,
+           0.2344011229137763,
+           0.2639589541977829,
+           0.28737556129969144,
+           0.30543062864840903,
+           0.319105628515168,
+           0.3295565618065541,
+           0.33808156882968665,
+           0.34608424609081095,
+           0.3550336203083252,
+           0.36642182188396744,
+           0.3817205647313514,
+           0.4023375759207978,
+           0.429574126078902,
+           0.4645847896261264,
+           0.5083405132278443,
+           0.5615959924813234,
+           0.6248622527664909,
+           0.6983852029050198,
+           0.7821307829389201,
+           0.8757771636040363,
+           0.9787142790011074,
+           1.0900507899398255,
+           1.2086283880403548,
+           1.3330431646066163,
+           1.4616735881987486,
+           1.5927144652504985,
+           1.7242161032731256,
+           1.8541277600726342,
+           1.9803443484383156,
+           2.100755276850491,
+           2.2132942452008675,
+           2.3159887819427416,
+           2.407008306396095,
+           2.484709527292985,
+           2.5476780454836048,
+           2.5947651137245735,
+           2.625118617630247,
+           2.638207476524955,
+           2.633838817843266,
+           2.61216745013373,
+           2.5736973434615034,
+           2.519275017597278,
+           2.4500749331424485,
+           2.367577173905521,
+           2.2735378956759846,
+           2.169953192450216,
+           2.059017191822876,
+           1.9430753327080754,
+           1.8245738973052594,
+           1.7060069623362555,
+           1.5898619997389498,
+           1.4785653925800188,
+           1.37442913703722,
+           1.2795999757421623,
+           1.196012152158491,
+           1.1253448913261375
+          ],
+          [
+           1.0845047967725794,
+           1.0393103937494421,
+           1.0100058989589125,
+           0.9970852684687642,
+           1.0006768932512256,
+           1.0205416739072861,
+           1.056079405951255,
+           1.1063433129915203,
+           1.1700623721123453,
+           1.2456708915044075,
+           1.3313446293816589,
+           1.4250425896047405,
+           1.5245534969235428,
+           1.6275458465501196,
+           1.7316203414763396,
+           1.8343634784942344,
+           1.933401021488039,
+           2.026450108733277,
+           2.1113687793977247,
+           2.18620177218651,
+           2.249221544386006,
+           2.2989635800416384,
+           2.33425519864153,
+           2.3542372369201936,
+           2.358378152241915,
+           2.3464802821181894,
+           2.3186781861596013,
+           2.2754291894321765,
+           2.217496435040702,
+           2.1459249341604543,
+           2.0620112692666583,
+           1.9672677568780865,
+           1.8633820060765358,
+           1.7521729152449974,
+           1.6355442293376568,
+           1.5154368316657274,
+           1.3937809664698897,
+           1.2724495810001044,
+           1.153213938726629,
+           1.0377025896859535,
+           0.927364691553103,
+           0.8234385582220501,
+           0.7269261744659349,
+           0.638574259162993,
+           0.5588622895758721,
+           0.4879977195639531,
+           0.42591843992461287,
+           0.3723023439527507,
+           0.3265836804324928,
+           0.2879757041712902,
+           0.2554989751670983,
+           0.2280145155417127,
+           0.20426091202109628,
+           0.18289435401788992,
+           0.16253052569599166,
+           0.14178722653835063,
+           0.11932657996184613,
+           0.09389570376481028,
+           0.0643647592553963,
+           0.02976136666956563,
+           -0.01069952887371976,
+           -0.05759113658580735,
+           -0.11125629970030247,
+           -0.1717954737800816,
+           -0.23906153181696524,
+           -0.3126615458726247,
+           -0.3919655126390545,
+           -0.4761218086145661,
+           -0.5640789842102654,
+           -0.6546133395043876,
+           -0.7463615717858303,
+           -0.8378576503618699,
+           -0.9275729607883632,
+           -1.0139586716198368,
+           -1.0954892142698371,
+           -1.1707057322519412,
+           -1.238258350864557,
+           -1.2969461424834385,
+           -1.345753715493408,
+           -1.3838834352605718,
+           -1.410782391460821,
+           -1.426163354938066,
+           -1.4300191158841393,
+           -1.4226297598286637,
+           -1.4045626146076313,
+           -1.376664785742765,
+           -1.340048384909008,
+           -1.2960687417101873,
+           -1.2462960681704238,
+           -1.1924812136769003,
+           -1.1365163013354886,
+           -1.0803911709472316,
+           -1.02614666566938,
+           -0.9758258860256747,
+           -0.9314245940364321,
+           -0.8948419802860402,
+           -0.8678330068888933,
+           -0.8519635094499616,
+           -0.8485691818817415,
+           -0.858719480703905,
+           -0.8831873722797516,
+           -0.9224257100454998,
+           -0.9765508724550438,
+           -1.0453341198840866,
+           -1.1282009443098182,
+           -1.2242384937046453,
+           -1.3322109584463024,
+           -1.4505826144200686,
+           -1.5775480315979153,
+           -1.711068782293897,
+           -1.8489158243117383,
+           -1.9887165947413796,
+           -2.128005733671728,
+           -2.2642782664547068,
+           -2.3950440106363478,
+           -2.517881940832504,
+           -2.630493242512286,
+           -2.7307518139550413,
+           -2.81675103391198,
+           -2.8868456993393043,
+           -2.9396881508862154,
+           -2.974257740876397,
+           -2.9898829559934934,
+           -2.986255680945628,
+           -2.963437275810999,
+           -2.921856334023409,
+           -2.8622981853190286,
+           -2.7858864036349917,
+           -2.6940567691708464,
+           -2.5885243119995818,
+           -2.4712442274231896,
+           -2.3443675967653888,
+           -2.2101929680131316,
+           -2.0711149457534828,
+           -1.9295710069282324,
+           -1.7879877964601774,
+           -1.6487281639309612,
+           -1.5140401790990474,
+           -1.386009310772244,
+           -1.2665148717614485,
+           -1.1571917244072292,
+           -1.0593981092006408,
+           -0.9741903066070159,
+           -0.9023046731333526,
+           -0.8441474111488203,
+           -0.7997922424625248,
+           -0.7689859628611297,
+           -0.751161663459868,
+           -0.7454592195269025,
+           -0.7507524729442014,
+           -0.7656823749346123,
+           -0.7886952150020872,
+           -0.8180849436123377,
+           -0.8520385028375885,
+           -0.8886830132262837,
+           -0.926133628077494,
+           -0.9625408589219366,
+           -0.9961361984179218,
+           -1.0252749184027743,
+           -1.0484750001160184,
+           -1.0644512585607453,
+           -1.0721438508895216,
+           -1.0707405063197315,
+           -1.059691978644882,
+           -1.0387203977668162,
+           -1.0078203793969776,
+           -0.9672529375548437,
+           -0.9175324280603865,
+           -0.8594069282632751,
+           -0.7938326243339626,
+           -0.7219429284031103,
+           -0.6450131799030775,
+           -0.5644218953464415,
+           -0.48160961574022043,
+           -0.3980364587795906,
+           -0.3151395124710609,
+           -0.23429120719924174,
+           -0.15675977450385317,
+           -0.08367284373729592,
+           -0.01598514380409358,
+           0.045548831506299146,
+           0.10039646671931876,
+           0.14826239779330252,
+           0.18909720062916416,
+           0.22309915519456924,
+           0.250709026460167,
+           0.2725979859522263,
+           0.289648977328923,
+           0.30293200142455945,
+           0.3136739563032051,
+           0.323223811944806,
+           0.3330140235769958,
+           0.3445191891816902,
+           0.35921303273658434,
+           0.3785248433261264,
+           0.4037965200908762,
+           0.43624136351596154,
+           0.47690571496211576,
+           0.5266344795221353,
+           0.5860414738575563,
+           0.6554854229214571,
+           0.7350522903045497,
+           0.8245444697964673,
+           0.9234771945326701,
+           1.0310823390607848,
+           1.1463196033233523,
+           1.2678948805740617,
+           1.394285428305037,
+           1.523771286956326,
+           1.6544722298922732,
+           1.7843893839363671,
+           1.9114505363114322,
+           2.0335580442839487,
+           2.1486381907194083,
+           2.254690784028678,
+           2.3498377858311867,
+           2.4323697645554674,
+           2.5007890178741454,
+           2.5538482803215725,
+           2.590584032946633,
+           2.6103435570160456,
+           2.612805020594538,
+           2.5979900517365215,
+           2.5662684310239845,
+           2.518354724915808,
+           2.4552968752254665,
+           2.378456954272457,
+           2.2894844850959446,
+           2.190282906915146,
+           2.082969933322019,
+           1.9698327003768894,
+           1.853278730150255,
+           1.735783839138917,
+           1.6198381978011935,
+           1.5078917952869126,
+           1.4023005810742124,
+           1.30527454219631,
+           1.21882893133009,
+           1.144739788250071,
+           1.0845047967725807
+          ],
+          [
+           1.0514102059046313,
+           1.017757208030165,
+           1.0003645577997182,
+           0.9994955991425567,
+           1.0150457390208005,
+           1.0465455750547936,
+           1.093172263074707,
+           1.1537688463592144,
+           1.2268710798695024,
+           1.310741105774913,
+           1.4034071752897916,
+           1.5027084702061846,
+           1.6063439589366555,
+           1.7119241292305587,
+           1.8170243752128858,
+           1.9192387815424623,
+           2.0162330430924125,
+           2.105795284668927,
+           2.185883601204479,
+           2.25466922315861,
+           2.310574322408034,
+           2.3523036079421225,
+           2.3788690148608787,
+           2.389606960672171,
+           2.384187825480616,
+           2.3626175028398215,
+           2.325231061112501,
+           2.272678746397377,
+           2.205904742741506,
+           2.1261192789373458,
+           2.034764829464573,
+           1.9334772962242697,
+           1.8240431742576642,
+           1.7083537958383344,
+           1.588357811005437,
+           1.4660130972827816,
+           1.3432392962439117,
+           1.221872149716982,
+           1.1036207544951264,
+           0.9900287728693503,
+           0.882440529256611,
+           0.7819727934111617,
+           0.689492901498106,
+           0.6056037014678063,
+           0.5306356328736435,
+           0.46464606797662744,
+           0.40742585529750264,
+           0.3585128233804181,
+           0.3172118260255368,
+           0.2826207450547464,
+           0.2536617169268646,
+           0.22911671895479774,
+           0.20766654274820773,
+           0.18793209949483572,
+           0.16851694585066218,
+           0.14804989189739803,
+           0.1252265544903566,
+           0.09884875027115406,
+           0.06786068183669713,
+           0.031380956506613815,
+           -0.011270412388388463,
+           -0.06055073958533446,
+           -0.1166797046908501,
+           -0.17963109401433416,
+           -0.2491314743702127,
+           -0.3246658445462251,
+           -0.40549012762449876,
+           -0.4906501881964082,
+           -0.5790068872816725,
+           -0.6692665288002172,
+           -0.7600159087988407,
+           -0.8497610559425779,
+           -0.9369686521818877,
+           -1.020109048562393,
+           -1.0976997447712593,
+           -1.1683481834398368,
+           -1.2307927219488863,
+           -1.283940685277992,
+           -1.326902472340715,
+           -1.359020783580511,
+           -1.3798941570314711,
+           -1.3893941406261967,
+           -1.3876755867779436,
+           -1.3751797272440598,
+           -1.3526298677087736,
+           -1.321019727877022,
+           -1.2815946394854423,
+           -1.2358259968343082,
+           -1.1853795276472854,
+           -1.132078111910931,
+           -1.0778600187937308,
+           -1.024733553179088,
+           -0.9747292006690844,
+           -0.9298504306181237,
+           -0.8920243589881061,
+           -0.8630534854317787,
+           -0.8445697015943182,
+           -0.8379917205052275,
+           -0.844487001180239,
+           -0.8649391399456946,
+           -0.8999215729835595,
+           -0.9496782862312421,
+           -1.0141120626481184,
+           -1.0927806170177716,
+           -1.1849007792761175,
+           -1.289360693464048,
+           -1.4047398055473947,
+           -1.5293362242831896,
+           -1.6612008596851509,
+           -1.7981775778758358,
+           -1.9379484632946349,
+           -2.078083153013813,
+           -2.2160911064251723,
+           -2.349475599322359,
+           -2.4757881862760844,
+           -2.5926823603274394,
+           -2.6979651548133923,
+           -2.789645478241236,
+           -2.8659780484566393,
+           -2.925501895095182,
+           -2.967072526991873,
+           -2.9898870107549746,
+           -2.9935013744629817,
+           -2.9778399323424507,
+           -2.9431963179085905,
+           -2.890226209741413,
+           -2.819931931045128,
+           -2.73363929660921,
+           -2.6329672640798027,
+           -2.519791116110337,
+           -2.3962000518770545,
+           -2.264450196943073,
+           -2.1269141463843186,
+           -1.9860282349094471,
+           -1.844238777535449,
+           -1.7039485440580036,
+           -1.5674647196556037,
+           -1.436949562817276,
+           -1.3143749014525459,
+           -1.2014815103132315,
+           -1.0997442901828196,
+           -1.0103440247319895,
+           -0.9341463280941043,
+           -0.8716882191188482,
+           -0.823172571297924,
+           -0.7884704951383764,
+           -0.7671315170230589,
+           -0.7584012300825135,
+           -0.7612459129325999,
+           -0.7743834457040777,
+           -0.7963197036633473,
+           -0.8253894805203972,
+           -0.8598008893377653,
+           -0.8976821112877491,
+           -0.9371293131870666,
+           -0.9762545348933523,
+           -1.0132323576681515,
+           -1.0463442041444486,
+           -1.0740191884997963,
+           -1.0948705300395536,
+           -1.1077266621910282,
+           -1.1116563088531208,
+           -1.1059869575715786,
+           -1.0903163301205898,
+           -1.0645166314390377,
+           -1.0287315429444368,
+           -0.9833661113699935,
+           -0.9290698647891253,
+           -0.8667136588793202,
+           -0.7973609144421733,
+           -0.7222340477916406,
+           -0.6426770153417579,
+           -0.5601149895922718,
+           -0.47601225335175373,
+           -0.39182944074154646,
+           -0.30898126628244843,
+           -0.2287958669010596,
+           -0.15247683646092874,
+           -0.0810689596052613,
+           -0.015428553166985362,
+           0.0438007983212423,
+           0.09620646829708214,
+           0.14161848859209683,
+           0.18011440893423872,
+           0.21201717872883716,
+           0.23788609677310688,
+           0.258501055964013,
+           0.2748404858066803,
+           0.28805356115441816,
+           0.29942739689837633,
+           0.3103500814199775,
+           0.322270513122827,
+           0.33665609141386205,
+           0.35494937385964376,
+           0.37852484332612624,
+           0.4086469318514105,
+           0.4464304216651567,
+           0.4928042887556031,
+           0.5484799720170338,
+           0.6139249432978581,
+           0.6893423232624913,
+           0.7746571381035613,
+           0.8695096465132209,
+           0.9732559890638632,
+           1.0849762276796766,
+           1.2034896558105068,
+           1.3273770749326712,
+           1.4550095547401285,
+           1.5845830273383426,
+           1.7141579141263663,
+           1.8417028516905705,
+           1.965141473303257,
+           2.082401118334227,
+           2.1914622852281327,
+           2.2904076161794023,
+           2.3774692040327055,
+           2.4510730442924697,
+           2.50987951673972,
+           2.5528188706003894,
+           2.5791208023663783,
+           2.588337353478066,
+           2.580358512799904,
+           2.5554200823328173,
+           2.514103549684556,
+           2.4573279029434247,
+           2.386333518072231,
+           2.302658440990301,
+           2.208107571426471,
+           2.104715428857173,
+           1.9947033381221515,
+           1.8804320097549314,
+           1.764350604273822,
+           1.6489434578191684,
+           1.536675706394554,
+           1.4299390760677977,
+           1.3309991060340494,
+           1.2419450404078405,
+           1.1646435637150017,
+           1.1006974657505297,
+           1.0514102059046322
+          ],
+          [
+           1.026341113936508,
+           1.0045083938086998,
+           0.9991572008938314,
+           1.0103180510935739,
+           1.037654272454599,
+           1.0804701592199257,
+           1.1377272254534199,
+           1.208068166777205,
+           1.289847956482116,
+           1.3811713340021263,
+           1.47993579356486,
+           1.5838790523760338,
+           1.690629874065786,
+           1.7977610468082286,
+           1.9028432683397136,
+           2.0034986731479942,
+           2.0974527507428555,
+           2.1825834477576804,
+           2.2569663195392,
+           2.318914697015836,
+           2.3670139594847415,
+           2.400149150411789,
+           2.4175253377595634,
+           2.41868029867302,
+           2.403489296153386,
+           2.372161908005828,
+           2.3252310611125013,
+           2.2635346122239963,
+           2.18818999536689,
+           2.1005626212589497,
+           2.002228861778061,
+           1.8949345789624015,
+           1.7805502601771084,
+           1.6610238965235118,
+           1.53833278851529,
+           1.4144354804360804,
+           1.2912250122955,
+           1.1704846363281123,
+           1.0538470746769213,
+           0.9427582981156646,
+           0.8384466848934113,
+           0.7418982771234778,
+           0.6538386931928831,
+           0.5747220824683505,
+           0.5047273274723765,
+           0.44376151326368474,
+           0.3914704986454185,
+           0.3472562436893794,
+           0.31030037742008776,
+           0.2795933326172421,
+           0.253968235486123,
+           0.2321386198798404,
+           0.21273894176659017,
+           0.19436680204221354,
+           0.17562574625018554,
+           0.15516749923759254,
+           0.13173251146627574,
+           0.10418774109755935,
+           0.07156067083936299,
+           0.03306865895813023,
+           -0.011857152754847415,
+           -0.06355400805940445,
+           -0.12211625698616883,
+           -0.18739093127613773,
+           -0.2589802983179757,
+           -0.33625133484160724,
+           -0.4183518805206246,
+           -0.5042330565425778,
+           -0.5926773695747669,
+           -0.6823317715718266,
+           -0.7717448143612712,
+           -0.8594069282632741,
+           -0.9437927689627762,
+           -1.0234045186496827,
+           -1.0968149975970418,
+           -1.16270944166678,
+           -1.21992482979407,
+           -1.2674857026460025,
+           -1.3046354979996397,
+           -1.3308625378751415,
+           -1.345919934392764,
+           -1.3498388324320387,
+           -1.3429345737038036,
+           -1.3258055446540766,
+           -1.2993246552655182,
+           -1.264623582689359,
+           -1.2230700980456186,
+           -1.1762389720404274,
+           -1.1258771208025937,
+           -1.0738638033513632,
+           -1.0221668125717756,
+           -0.972795709169657,
+           -0.9277532300437169,
+           -0.8889860567179141,
+           -0.8583361544789148,
+           -0.8374938879398744,
+           -0.8279540839224281,
+           -0.8309761485763097,
+           -0.8475492540266434,
+           -0.8783634927279773,
+           -0.9237877579223713,
+           -0.9838549495241503,
+           -1.0582549302482664,
+           -1.1463354711137346,
+           -1.2471112331241743,
+           -1.3592806376625404,
+           -1.4812502867016955,
+           -1.6111664100310046,
+           -1.7469526448577761,
+           -1.8863532975991146,
+           -2.0269811022775315,
+           -2.1663683780263736,
+           -2.302020402580466,
+           -2.431469761412067,
+           -2.5523304048182407,
+           -2.6623501484853875,
+           -2.7594603868153484,
+           -2.84182185181029,
+           -2.9078653420665104,
+           -2.95632646421298,
+           -2.9862735701026804,
+           -2.9971282338082763,
+           -2.9886777890874487,
+           -2.961079636177448,
+           -2.914857221978684,
+           -2.850887795147979,
+           -2.7703822325429908,
+           -2.6748574211030967,
+           -2.5661018550613504,
+           -2.4461352680914676,
+           -2.31716325973396,
+           -2.1815279918395065,
+           -2.0416561210121364,
+           -1.9000051949702028,
+           -1.75900977290532,
+           -1.6210285315757431,
+           -1.4882935900372014,
+           -1.3628632273549977,
+           -1.2465790808481427,
+           -1.1410287995727846,
+           -1.0475149916773545,
+           -0.9670311483408395,
+           -0.9002450551063509,
+           -0.8474900177975013,
+           -0.8087640393892763,
+           -0.7837368909001884,
+           -0.7717648283324917,
+           -0.7719125236007726,
+           -0.7829816047630093,
+           -0.8035450439168105,
+           -0.8319864936646669,
+           -0.8665435584132016,
+           -0.9053538977079097,
+           -0.946502997432603,
+           -0.9880724124465962,
+           -1.0281872817922104,
+           -1.0650619449386525,
+           -1.097042543854321,
+           -1.1226455795183126,
+           -1.1405915006127423,
+           -1.1498325337748425,
+           -1.1495741155714405,
+           -1.139289452458259,
+           -1.1187269121983114,
+           -1.0879101340645465,
+           -1.0471309310121788,
+           -0.9969352402048927,
+           -0.938102554220813,
+           -0.8716194295433687,
+           -0.7986478174532536,
+           -0.7204890914772081,
+           -0.6385447519076756,
+           -0.5542748689494396,
+           -0.4691553797786912,
+           -0.38463537990959784,
+           -0.30209554516643466,
+           -0.22280878740449334,
+           -0.14790418578961423,
+           -0.07833514752180054,
+           -0.014852639629100337,
+           0.04201580026885948,
+           0.09198071811614099,
+           0.13499867237123037,
+           0.1712732236010893,
+           0.20124895205213164,
+           0.22559865292419687,
+           0.2452040377416855,
+           0.2611304406208781,
+           0.27459618604200065,
+           0.2869374159312745,
+           0.2995692948408708,
+           0.31394460968824045,
+           0.33151085237004874,
+           0.3536669177365721,
+           0.3817205647313511,
+           0.41684777452407035,
+           0.46005509648394405,
+           0.512146001878109,
+           0.5736921679608342,
+           0.6450104940333502,
+           0.7261465090922866,
+           0.8168646713682768,
+           0.9166458873471824,
+           1.0246923960707204,
+           1.1399399781728041,
+           1.2610772628875044,
+           1.3865717248359095,
+           1.5147017903242694,
+           1.6435943145035392,
+           1.771266550056077,
+           1.8956716086638945,
+           2.0147463214257324,
+           2.126460336080943,
+           2.228865249158998,
+           2.320142561090995,
+           2.398649262245953,
+           2.4629599073971966,
+           2.5119041141558087,
+           2.5445985255921095,
+           2.560472406101688,
+           2.559286189456162,
+           2.5411424652792065,
+           2.506489070836439,
+           2.4561141446164543,
+           2.391133192073193,
+           2.312968407345364,
+           2.2233206830175645,
+           2.1241349184102187,
+           2.017559401086162,
+           1.905900182187094,
+           1.7915714902539372,
+           1.6770433272641267,
+           1.5647874622676992,
+           1.4572230804250932,
+           1.356663357360206,
+           1.2652642102026543,
+           1.1849764279138688,
+           1.1175023056260793,
+           1.0642578026375917,
+           1.0263411139365082
+          ],
+          [
+           1.0095096167301518,
+           0.9996760420485171,
+           1.0063940430270113,
+           1.0294610614810964,
+           1.0683112151292948,
+           1.1220284090695978,
+           1.189367337944322,
+           1.2687818774240367,
+           1.3584601890766845,
+           1.4563657045852083,
+           1.560283017466667,
+           1.6678675962590237,
+           1.776698145329134,
+           1.8843303801187792,
+           1.988350954187483,
+           2.0864302764998217,
+           2.176372988960312,
+           2.256164935392769,
+           2.3240155424394833,
+           2.37839464797795,
+           2.4180629507472364,
+           2.4420954125109935,
+           2.449897117353678,
+           2.4412112773274193,
+           2.4161192650843186,
+           2.375032747629613,
+           2.3186781861596013,
+           2.248074150424908,
+           2.1645020676956594,
+           2.069471182013744,
+           1.9646786352164414,
+           1.8519656939212936,
+           1.7332712335687526,
+           1.6105836496657515,
+           1.4858923961940596,
+           1.3611403511032811,
+           1.2381781790035862,
+           1.1187218024498804,
+           1.0043140071261223,
+           0.8962910950314436,
+           0.7957553662942534,
+           0.703554057900713,
+           0.6202652002862374,
+           0.5461906746354533,
+           0.4813565693594049,
+           0.42552074820836533,
+           0.37818735950551824,
+           0.3386278406374811,
+           0.30590780859881317,
+           0.27891908013791816,
+           0.2564159375591613,
+           0.23705465166758946,
+           0.2194351942852614,
+           0.20214402116473645,
+           0.1837967832264129,
+           0.1630798303800821,
+           0.13878940754960814,
+           0.10986750596571457,
+           0.07543342268216716,
+           0.034810195297681173,
+           -0.012454785884093402,
+           -0.06657553299773218,
+           -0.12751996089377293,
+           -0.19500933383089097,
+           -0.2685246781530136,
+           -0.3473199982683781,
+           -0.43044195507792266,
+           -0.5167554964405482,
+           -0.6049747726233851,
+           -0.6936985299532792,
+           -0.7814490566246731,
+           -0.8667136588793195,
+           -0.9479875760151143,
+           -1.0238172007135509,
+           -1.0928424581086316,
+           -1.15383721323973,
+           -1.205746621685515,
+           -1.2477204111864995,
+           -1.279141181149026,
+           -1.2996469296448816,
+           -1.3091471608417302,
+           -1.307832086161896,
+           -1.296174605877861,
+           -1.2749249399854985,
+           -1.2450979634960129,
+           -1.207953487087604,
+           -1.1649699046927755,
+           -1.1178118005217308,
+           -1.068292264923401,
+           -1.0183308073908788,
+           -0.9699078723957231,
+           -0.9250170565813947,
+           -0.8856161917616372,
+           -0.8535784954195816,
+           -0.8306449979630885,
+           -0.8183794335709568,
+           -0.818126729517378,
+           -0.8309761485763094,
+           -0.8577300323761892,
+           -0.898878962951626,
+           -0.9545840083720356,
+           -1.0246665498876546,
+           -1.1086060066207208,
+           -1.2055455838724753,
+           -1.3143059772638823,
+           -1.4334067719330754,
+           -1.5610950886172517,
+           -1.6953808512635151,
+           -1.8340778882101054,
+           -1.9748499349749173,
+           -2.115260484846904,
+           -2.2528253368259463,
+           -2.3850666214086953,
+           -2.5095670450097707,
+           -2.6240230844582086,
+           -2.7262958842934992,
+           -2.8144586610285147,
+           -2.886839498931731,
+           -2.942058529283442,
+           -2.9790586168896867,
+           -2.997128830705349,
+           -2.9959201460125806,
+           -2.975453009581868,
+           -2.936116592140295,
+           -2.878659749596433,
+           -2.804173911031399,
+           -2.714068302683439,
+           -2.610038098382536,
+           -2.494026253732721,
+           -2.368179929746865,
+           -2.2348025380199834,
+           -2.0963025408325913,
+           -1.955140213370921,
+           -1.8137736197795054,
+           -1.6746050689835716,
+           -1.53992929984072,
+           -1.4118845986576711,
+           -1.2924079766346726,
+           -1.1831954322793061,
+           -1.0856681968281285,
+           -1.0009457123902177,
+           -0.9298259265607556,
+           -0.8727733077537333,
+           -0.8299147969023013,
+           -0.8010437181227591,
+           -0.7856314781817957,
+           -0.7828466968791538,
+           -0.7915812323575506,
+           -0.810482401229735,
+           -0.8379905472657457,
+           -0.8723809877557578,
+           -0.9118092665590949,
+           -0.9543585696589938,
+           -0.9980881144836675,
+           -1.041081309333128,
+           -1.0814924942354676,
+           -1.1175911189719752,
+           -1.1478022866523332,
+           -1.1707426901866134,
+           -1.1852510917355659,
+           -1.1904126385854694,
+           -1.1855764692416448,
+           -1.1703662368034802,
+           -1.1446833584977347,
+           -1.10870298602545,
+           -1.0628628764513322,
+           -1.0078455230894998,
+           -0.9445540757155185,
+           -0.8740827352157163,
+           -0.7976824455853995,
+           -0.7167228225798343,
+           -0.6326513504193534,
+           -0.5469509434812677,
+           -0.46109700727422986,
+           -0.3765151412937325,
+           -0.2945406054394853,
+           -0.21638062211126818,
+           -0.14308050918373594,
+           -0.07549453677420379,
+           -0.014262275679572865,
+           0.04020893924039467,
+           0.08775496793519984,
+           0.12845895577143268,
+           0.16264844505831627,
+           0.19088557923481325,
+           0.2139506522485305,
+           0.23281943007637398,
+           0.24863483495765434,
+           0.26267373157028956,
+           0.27630968429266195,
+           0.2909726625403067,
+           0.3081067541838052,
+           0.3291270031008081,
+           0.3553765145264888,
+           0.38808497029263217,
+           0.4283296652689214,
+           0.47700011705812095,
+           0.5347672146843917,
+           0.6020577607672097,
+           0.6790351282384379,
+           0.7655866003446387,
+           0.8613177952681502,
+           0.9655543983715041,
+           1.0773512402747245,
+           1.1955085723396144,
+           1.3185952073397968,
+           1.444978016759724,
+           1.5728571117333736,
+           1.7003058862595866,
+           1.8253149727794873,
+           1.9458390547512046,
+           2.0598454012172915,
+           2.1653629366049456,
+           2.260530636512123,
+           2.3436440476742875,
+           2.4131987675943605,
+           2.467929785628914,
+           2.5068456811121296,
+           2.5292567931352528,
+           2.534796618023459,
+           2.5234358509437533,
+           2.495488663539936,
+           2.451610995746181,
+           2.392790832427061,
+           2.320330629512523,
+           2.2358222450797056,
+           2.1411149136874434,
+           2.038276972689744,
+           1.929552203035608,
+           1.8173117803999432,
+           1.7040029420787297,
+           1.5920955581916647,
+           1.4840278502878967,
+           1.382152525061236,
+           1.2886845849020274,
+           1.2056520405441256,
+           1.1348506849546849,
+           1.077803993438418,
+           1.0357290949503282,
+           1.0095096167301523
+          ],
+          [
+           1.0010581163682697,
+           1.0033010366321724,
+           1.0220138572401019,
+           1.056762671774933,
+           1.1067571954374327,
+           1.1708687230047563,
+           1.2476557018283188,
+           1.3353963128343658,
+           1.4321272871180637,
+           1.5356880391231789,
+           1.6437690731234633,
+           1.7539635207686546,
+           1.8638205962054688,
+           1.9708997134293262,
+           2.072823999041246,
+           2.1673319527065975,
+           2.2523260568176413,
+           2.325917214892793,
+           2.3864640031394675,
+           2.432605848744824,
+           2.463289398629502,
+           2.4777875098814723,
+           2.4757104737394564,
+           2.4570092743605665,
+           2.4219708770211317,
+           2.3712057331088885,
+           2.3056278765411133,
+           2.2264281635028715,
+           2.1350413703148208,
+           2.0331080088467814,
+           1.9224318416880992,
+           1.8049341773120395,
+           1.6826060963917138,
+           1.55745980257795,
+           1.431480303490336,
+           1.3065786101948649,
+           1.1845475965817907,
+           1.0670215850798452,
+           0.955440624008178,
+           0.8510202971814335,
+           0.7547277613325344,
+           0.6672645451884551,
+           0.5890564697203432,
+           0.5202508665899902,
+           0.46072108572375664,
+           0.4100780979370776,
+           0.3676888192456145,
+           0.33270061441893917,
+           0.3040712826816019,
+           0.2806036920978525,
+           0.26098411447884323,
+           0.2438232224645902,
+           0.22769864697782458,
+           0.21119795806939612,
+           0.19296092610908902,
+           0.17171994342303057,
+           0.14633753820620696,
+           0.11583999149471128,
+           0.07944617213207932,
+           0.0365908313397796,
+           -0.013058255529420835,
+           -0.0695897509320838,
+           -0.1328450986333993,
+           -0.20242184654561426,
+           -0.27768386410303936,
+           -0.3577781889253198,
+           -0.44165806379481515,
+           -0.5281115623823138,
+           -0.6157950548330974,
+           -0.7032706360251498,
+           -0.7890465333082787,
+           -0.8716194295433679,
+           -0.9495175833730671,
+           -1.0213436032769965,
+           -1.0858157357876947,
+           -1.1418065612259096,
+           -1.1883780516795324,
+           -1.2248120342091293,
+           -1.250635215245744,
+           -1.2656380570605832,
+           -1.269886950682487,
+           -1.2637292978974828,
+           -1.2477912937870566,
+           -1.2229683861775573,
+           -1.1904085747504944,
+           -1.1514888957240674,
+           -1.1077856133533146,
+           -1.061038802587872,
+           -1.0131121539478902,
+           -0.9659489583042795,
+           -0.9215253325469033,
+           -0.881801824435292,
+           -0.848674584233939,
+           -0.8239273107138144,
+           -0.8091851691551474,
+           -0.8058718392583784,
+           -0.8151707822443648,
+           -0.8379917205052267,
+           -0.8749432022371832,
+           -0.9263119804551923,
+           -0.9920497741182818,
+           -1.0717678027152133,
+           -1.164739298875241,
+           -1.2699100109471735,
+           -1.3859165137538507,
+           -1.5111119556372545,
+           -1.6435986881396731,
+           -1.7812670557004122,
+           -1.921839470758756,
+           -2.0629187684058454,
+           -2.2020397274793395,
+           -2.3367225644188525,
+           -2.464527154319718,
+           -2.58310671175681,
+           -2.6902596726849164,
+           -2.783978557891061,
+           -2.862494667166036,
+           -2.9243175499401945,
+           -2.9682683202709783,
+           -2.993506028827239,
+           -2.9995464683831177,
+           -2.986272968337305,
+           -2.953938923565139,
+           -2.9031619988794564,
+           -2.8349101477577343,
+           -2.7504797779895793,
+           -2.6514665827954293,
+           -2.539729729248822,
+           -2.417350252295746,
+           -2.2865846385141175,
+           -2.14981469570949,
+           -2.0094948898028018,
+           -1.8680983871882242,
+           -1.7280630674837005,
+           -1.591738767758958,
+           -1.4613369850512459,
+           -1.338884200159546,
+           -1.2261798939587591,
+           -1.1247602100943566,
+           -1.0358680778294507,
+           -0.960430449497017,
+           -0.8990431324035579,
+           -0.8519635094499619,
+           -0.8191112507549002,
+           -0.8000769249097728,
+           -0.7941382279174855,
+           -0.8002833650405359,
+           -0.8172409501765733,
+           -0.8435156331504128,
+           -0.877428531205784,
+           -0.9171614302378862,
+           -0.9608036365841962,
+           -1.0064003034914368,
+           -1.0520010290081507,
+           -1.095707524592194,
+           -1.1357191860049707,
+           -1.1703754591860753,
+           -1.1981939821453682,
+           -1.2179035971842542,
+           -1.2284714630584221,
+           -1.229123650573498,
+           -1.2193587736604288,
+           -1.1989543869492763,
+           -1.1679660657377404,
+           -1.126719270385286,
+           -1.0757942798846956,
+           -1.016004654093649,
+           -0.9483698464820501,
+           -0.8740827352157162,
+           -0.7944729663214489,
+           -0.7109671054386474,
+           -0.6250466717201774,
+           -0.5382051769113311,
+           -0.4519053133162153,
+           -0.36753742578709064,
+           -0.2863803653103396,
+           -0.2095657562085428,
+           -0.13804661713011965,
+           -0.0725711602147867,
+           -0.013662456064558676,
+           0.038395502097762615,
+           0.08356496951296322,
+           0.12205466775439355,
+           0.15431304283514838,
+           0.18101473910039947,
+           0.20304064210260442,
+           0.22145201235302592,
+           0.237459387295246,
+           0.25238706709908776,
+           0.2676341174013049,
+           0.28463291591756845,
+           0.3048063375087503,
+           0.32952471204966216,
+           0.36006370026694945,
+           0.3975642142589947,
+           0.44299546209464746,
+           0.49712212084592067,
+           0.5604765414778948,
+           0.6333367646854321,
+           0.7157109821114237,
+           0.8073289160007078,
+           0.9076404162597206,
+           1.0158213914515666,
+           1.1307870040255101,
+           1.251211874728381,
+           1.3755568613301332,
+           1.5021018070452732,
+           1.6289834986327365,
+           1.7542379370471497,
+           1.875845908183167,
+           1.9917807506575733,
+           2.1000571540553326,
+           2.1987797863021625,
+           2.286190543781739,
+           2.360713242718242,
+           2.4209946246789533,
+           2.465940631568887,
+           2.4947470142412005,
+           2.5069234712286157,
+           2.5023106669172583,
+           2.4810896480271283,
+           2.4437833594033864,
+           2.3912501504099204,
+           2.324669356991624,
+           2.2455192369792023,
+           2.155547722717059,
+           2.0567366310070048,
+           1.9512601313370335,
+           1.8414384154247299,
+           1.7296876307265279,
+           1.6184672347720908,
+           1.5102259936220932,
+           1.4073478847412522,
+           1.312099171171175,
+           1.2265778898690247,
+           1.1526669429886072,
+           1.0919918979978813,
+           1.0458844928368165,
+           1.0153527084651603,
+           1.0010581163682697
+          ],
+          [
+           1.0010581163682695,
+           1.015352708465159,
+           1.0458844928368154,
+           1.0919918979978804,
+           1.152666942988604,
+           1.2265778898690192,
+           1.3120991711711711,
+           1.4073478847412493,
+           1.5102259936220868,
+           1.6184672347720874,
+           1.7296876307265279,
+           1.8414384154247248,
+           1.9512601313370248,
+           2.056736631007,
+           2.155547722717058,
+           2.2455192369791983,
+           2.3246693569916212,
+           2.3912501504099204,
+           2.4437833594033846,
+           2.481089648027125,
+           2.502310666917256,
+           2.506923471228616,
+           2.4947470142412,
+           2.4659406315688877,
+           2.4209946246789547,
+           2.360713242718243,
+           2.2861905437817414,
+           2.198779786302168,
+           2.1000571540553343,
+           1.9917807506575762,
+           1.8758459081831742,
+           1.7542379370471541,
+           1.6289834986327385,
+           1.502101807045277,
+           1.3755568613301414,
+           1.251211874728382,
+           1.1307870040255126,
+           1.0158213914515728,
+           0.9076404162597242,
+           0.8073289160007091,
+           0.7157109821114275,
+           0.633336764685436,
+           0.5604765414778947,
+           0.4971221208459229,
+           0.44299546209464913,
+           0.39756421425899563,
+           0.3600637002669496,
+           0.32952471204966294,
+           0.3048063375087506,
+           0.2846329159175687,
+           0.2676341174013054,
+           0.25238706709908776,
+           0.23745938729524566,
+           0.22145201235302595,
+           0.20304064210260442,
+           0.18101473910039886,
+           0.1543130428351493,
+           0.12205466775439457,
+           0.0835649695129634,
+           0.03839550209776262,
+           -0.013662456064557205,
+           -0.07257116021478549,
+           -0.1380466171301193,
+           -0.20956575620854073,
+           -0.2863803653103383,
+           -0.36753742578708937,
+           -0.4519053133162119,
+           -0.5382051769113291,
+           -0.6250466717201761,
+           -0.7109671054386443,
+           -0.7944729663214469,
+           -0.8740827352157157,
+           -0.9483698464820502,
+           -1.0160046540936476,
+           -1.075794279884695,
+           -1.1267192703852862,
+           -1.16796606573774,
+           -1.1989543869492765,
+           -1.219358773660428,
+           -1.2291236505735001,
+           -1.2284714630584233,
+           -1.2179035971842562,
+           -1.19819398214537,
+           -1.1703754591860773,
+           -1.1357191860049716,
+           -1.0957075245921948,
+           -1.0520010290081554,
+           -1.0064003034914377,
+           -0.9608036365841983,
+           -0.917161430237887,
+           -0.8774285312057863,
+           -0.8435156331504143,
+           -0.8172409501765752,
+           -0.8002833650405375,
+           -0.7941382279174858,
+           -0.8000769249097727,
+           -0.8191112507548994,
+           -0.8519635094499606,
+           -0.8990431324035557,
+           -0.9604304494970142,
+           -1.0358680778294496,
+           -1.124760210094353,
+           -1.2261798939587574,
+           -1.3388842001595413,
+           -1.4613369850512379,
+           -1.591738767758956,
+           -1.728063067483695,
+           -1.868098387188222,
+           -2.009494889802797,
+           -2.149814695709485,
+           -2.286584638514112,
+           -2.417350252295741,
+           -2.5397297292488177,
+           -2.651466582795425,
+           -2.7504797779895775,
+           -2.8349101477577316,
+           -2.903161998879456,
+           -2.953938923565137,
+           -2.9862729683373046,
+           -2.9995464683831177,
+           -2.9935060288272397,
+           -2.9682683202709796,
+           -2.924317549940197,
+           -2.862494667166037,
+           -2.7839785578910647,
+           -2.690259672684918,
+           -2.5831067117568143,
+           -2.464527154319726,
+           -2.3367225644188574,
+           -2.202039727479345,
+           -2.062918768405851,
+           -1.9218394707587612,
+           -1.7812670557004144,
+           -1.6435986881396785,
+           -1.5111119556372565,
+           -1.3859165137538558,
+           -1.2699100109471777,
+           -1.1647392988752447,
+           -1.0717678027152187,
+           -0.9920497741182829,
+           -0.9263119804551947,
+           -0.8749432022371848,
+           -0.8379917205052277,
+           -0.8151707822443651,
+           -0.8058718392583777,
+           -0.8091851691551459,
+           -0.8239273107138132,
+           -0.8486745842339373,
+           -0.8818018244352903,
+           -0.9215253325469007,
+           -0.9659489583042787,
+           -1.0131121539478878,
+           -1.0610388025878712,
+           -1.1077856133533122,
+           -1.1514888957240665,
+           -1.1904085747504913,
+           -1.2229683861775555,
+           -1.2477912937870532,
+           -1.263729297897481,
+           -1.2698869506824861,
+           -1.265638057060583,
+           -1.250635215245744,
+           -1.2248120342091284,
+           -1.188378051679533,
+           -1.141806561225909,
+           -1.0858157357876956,
+           -1.0213436032769982,
+           -0.9495175833730671,
+           -0.8716194295433687,
+           -0.7890465333082809,
+           -0.7032706360251533,
+           -0.6157950548330987,
+           -0.5281115623823158,
+           -0.4416580637948182,
+           -0.35777818892532104,
+           -0.2776838641030411,
+           -0.2024218465456163,
+           -0.1328450986333995,
+           -0.06958975093208497,
+           -0.013058255529422264,
+           0.03659083133977966,
+           0.07944617213207915,
+           0.11583999149471055,
+           0.14633753820620612,
+           0.17171994342303046,
+           0.19296092610908896,
+           0.21119795806939604,
+           0.22769864697782488,
+           0.2438232224645905,
+           0.26098411447884295,
+           0.28060369209785235,
+           0.30407128268160144,
+           0.3327006144189383,
+           0.3676888192456143,
+           0.4100780979370765,
+           0.46072108572375403,
+           0.5202508665899878,
+           0.5890564697203422,
+           0.6672645451884525,
+           0.7547277613325291,
+           0.8510202971814305,
+           0.9554406240081742,
+           1.0670215850798388,
+           1.1845475965817873,
+           1.3065786101948629,
+           1.4314803034903312,
+           1.5574598025779485,
+           1.6826060963917095,
+           1.8049341773120349,
+           1.9224318416880921,
+           2.0331080088467783,
+           2.135041370314819,
+           2.226428163502869,
+           2.305627876541113,
+           2.3712057331088867,
+           2.4219708770211303,
+           2.457009274360567,
+           2.4757104737394577,
+           2.477787509881473,
+           2.463289398629505,
+           2.4326058487448243,
+           2.3864640031394706,
+           2.3259172148927947,
+           2.2523260568176453,
+           2.167331952706605,
+           2.0728239990412494,
+           1.9708997134293331,
+           1.8638205962054724,
+           1.7539635207686595,
+           1.643769073123465,
+           1.5356880391231835,
+           1.4321272871180708,
+           1.3353963128343695,
+           1.2476557018283236,
+           1.1708687230047583,
+           1.1067571954374327,
+           1.0567626717749343,
+           1.022013857240103,
+           1.003301036632173,
+           1.0010581163682692
+          ],
+          [
+           1.0095096167301518,
+           1.035729094950326,
+           1.0778039934384167,
+           1.134850684954684,
+           1.2056520405441264,
+           1.2886845849020259,
+           1.3821525250612319,
+           1.4840278502878936,
+           1.5920955581916583,
+           1.7040029420787262,
+           1.817311780399943,
+           1.9295522030356032,
+           2.0382769726897427,
+           2.141114913687439,
+           2.2358222450797043,
+           2.320330629512519,
+           2.3927908324270586,
+           2.451610995746181,
+           2.4954886635399345,
+           2.5234358509437533,
+           2.534796618023458,
+           2.5292567931352528,
+           2.50684568111213,
+           2.4679297856289146,
+           2.4131987675943622,
+           2.343644047674289,
+           2.2605306365121236,
+           2.1653629366049483,
+           2.0598454012172938,
+           1.9458390547512077,
+           1.8253149727794946,
+           1.700305886259591,
+           1.5728571117333756,
+           1.4449780167597233,
+           1.3185952073398002,
+           1.1955085723396155,
+           1.0773512402747267,
+           0.9655543983715102,
+           0.8613177952681537,
+           0.7655866003446399,
+           0.6790351282384413,
+           0.6020577607672108,
+           0.5347672146843917,
+           0.47700011705812295,
+           0.42832966526892297,
+           0.3880849702926329,
+           0.3553765145264888,
+           0.3291270031008087,
+           0.3081067541838055,
+           0.290972662540307,
+           0.2763096842926624,
+           0.26267373157028945,
+           0.24863483495765393,
+           0.23281943007637398,
+           0.2139506522485305,
+           0.1908855792348134,
+           0.16264844505831721,
+           0.12845895577143374,
+           0.08775496793520005,
+           0.040208939240394675,
+           -0.01426227567957133,
+           -0.07549453677420254,
+           -0.143080509183736,
+           -0.21638062211126605,
+           -0.2945406054394839,
+           -0.37651514129373126,
+           -0.46109700727422726,
+           -0.5469509434812658,
+           -0.6326513504193523,
+           -0.7167228225798313,
+           -0.7976824455853977,
+           -0.8740827352157156,
+           -0.9445540757155187,
+           -1.0078455230894983,
+           -1.062862876451332,
+           -1.1087029860254503,
+           -1.1446833584977345,
+           -1.1703662368034804,
+           -1.1855764692416442,
+           -1.1904126385854703,
+           -1.1852510917355652,
+           -1.1707426901866154,
+           -1.147802286652335,
+           -1.1175911189719772,
+           -1.0814924942354684,
+           -1.0410813093331266,
+           -0.9980881144836697,
+           -0.9543585696589928,
+           -0.911809266559097,
+           -0.8723809877557569,
+           -0.8379905472657478,
+           -0.8104824012297354,
+           -0.7915812323575518,
+           -0.7828466968791543,
+           -0.7856314781817956,
+           -0.801043718122759,
+           -0.8299147969023001,
+           -0.8727733077537315,
+           -0.9298259265607545,
+           -1.0009457123902146,
+           -1.0856681968281294,
+           -1.183195432279302,
+           -1.2924079766346708,
+           -1.4118845986576662,
+           -1.5399292998407146,
+           -1.6746050689835728,
+           -1.8137736197794996,
+           -1.9551402133709217,
+           -2.096302540832586,
+           -2.234802538019981,
+           -2.36817992974686,
+           -2.494026253732719,
+           -2.6100380983825318,
+           -2.7140683026834354,
+           -2.8041739110313992,
+           -2.8786597495964306,
+           -2.936116592140296,
+           -2.9754530095818668,
+           -2.9959201460125806,
+           -2.997128830705349,
+           -2.979058616889688,
+           -2.9420585292834422,
+           -2.8868394989317343,
+           -2.814458661028514,
+           -2.726295884293503,
+           -2.6240230844582078,
+           -2.5095670450097756,
+           -2.3850666214087,
+           -2.252825336825948,
+           -2.115260484846909,
+           -1.9748499349749196,
+           -1.834077888210111,
+           -1.6953808512635142,
+           -1.561095088617257,
+           -1.433406771933074,
+           -1.3143059772638865,
+           -1.2055455838724791,
+           -1.1086060066207222,
+           -1.0246665498876575,
+           -0.9545840083720352,
+           -0.898878962951628,
+           -0.8577300323761899,
+           -0.83097614857631,
+           -0.818126729517378,
+           -0.8183794335709565,
+           -0.8306449979630877,
+           -0.8535784954195801,
+           -0.8856161917616349,
+           -0.9250170565813943,
+           -0.9699078723957201,
+           -1.0183308073908799,
+           -1.0682922649233986,
+           -1.1178118005217321,
+           -1.1649699046927728,
+           -1.2079534870876054,
+           -1.2450979634960124,
+           -1.274924939985497,
+           -1.2961746058778596,
+           -1.3078320861618942,
+           -1.309147160841731,
+           -1.2996469296448812,
+           -1.279141181149027,
+           -1.2477204111864995,
+           -1.205746621685516,
+           -1.1538372132397299,
+           -1.0928424581086325,
+           -1.0238172007135529,
+           -0.9479875760151144,
+           -0.8667136588793201,
+           -0.7814490566246755,
+           -0.6936985299532824,
+           -0.6049747726233864,
+           -0.5167554964405501,
+           -0.4304419550779252,
+           -0.3473199982683794,
+           -0.2685246781530149,
+           -0.19500933383089297,
+           -0.12751996089377288,
+           -0.06657553299773332,
+           -0.012454785884094745,
+           0.03481019529768117,
+           0.07543342268216699,
+           0.10986750596571367,
+           0.13878940754960734,
+           0.16307983038008197,
+           0.18379678322641285,
+           0.20214402116473626,
+           0.2194351942852616,
+           0.23705465166758938,
+           0.2564159375591608,
+           0.27891908013791794,
+           0.3059078085988128,
+           0.33862784063748,
+           0.378187359505518,
+           0.4255207482083641,
+           0.48135656935940274,
+           0.5461906746354506,
+           0.6202652002862377,
+           0.7035540579007116,
+           0.7957553662942495,
+           0.8962910950314422,
+           1.0043140071261185,
+           1.1187218024498737,
+           1.2381781790035837,
+           1.3611403511032798,
+           1.485892396194056,
+           1.6105836496657522,
+           1.7332712335687506,
+           1.8519656939212898,
+           1.9646786352164352,
+           2.069471182013742,
+           2.1645020676956577,
+           2.2480741504249058,
+           2.318678186159601,
+           2.375032747629612,
+           2.416119265084318,
+           2.4412112773274193,
+           2.449897117353679,
+           2.442095412510993,
+           2.418062950747239,
+           2.3783946479779496,
+           2.3240155424394855,
+           2.2561649353927695,
+           2.1763729889603147,
+           2.0864302764998266,
+           1.9883509541874842,
+           1.8843303801187845,
+           1.7766981453291357,
+           1.6678675962590286,
+           1.560283017466667,
+           1.4563657045852112,
+           1.3584601890766899,
+           1.2687818774240394,
+           1.189367337944325,
+           1.1220284090695989,
+           1.0683112151292944,
+           1.0294610614810968,
+           1.0063940430270115,
+           0.9996760420485171,
+           1.0095096167301514
+          ],
+          [
+           1.0263411139365073,
+           1.064257802637589,
+           1.1175023056260776,
+           1.1849764279138675,
+           1.2652642102026506,
+           1.3566633573601992,
+           1.4572230804250885,
+           1.5647874622676958,
+           1.6770433272641199,
+           1.7915714902539337,
+           1.9059001821870938,
+           2.017559401086157,
+           2.1241349184102103,
+           2.2233206830175605,
+           2.312968407345363,
+           2.3911331920731893,
+           2.456114144616452,
+           2.5064890708364387,
+           2.541142465279205,
+           2.5592861894561603,
+           2.5604724061016877,
+           2.544598525592111,
+           2.511904114155809,
+           2.4629599073971966,
+           2.3986492622459554,
+           2.3201425610909965,
+           2.2288652491590013,
+           2.126460336080949,
+           2.014746321425734,
+           1.895671608663898,
+           1.7712665500560845,
+           1.6435943145035439,
+           1.5147017903242714,
+           1.386571724835913,
+           1.2610772628875122,
+           1.139939978172805,
+           1.0246923960707228,
+           0.9166458873471882,
+           0.8168646713682801,
+           0.7261465090922878,
+           0.6450104940333533,
+           0.5736921679608374,
+           0.5121460018781088,
+           0.4600550964839459,
+           0.41684777452407157,
+           0.38172056473135163,
+           0.3536669177365721,
+           0.331510852370049,
+           0.3139446096882402,
+           0.29956929484087125,
+           0.2869374159312749,
+           0.2745961860420004,
+           0.2611304406208776,
+           0.2452040377416854,
+           0.2255986529241968,
+           0.20124895205213095,
+           0.1712732236010903,
+           0.13499867237123148,
+           0.09198071811614122,
+           0.04201580026885949,
+           -0.014852639629098744,
+           -0.07833514752179926,
+           -0.1479041857896139,
+           -0.22280878740449114,
+           -0.3020955451664332,
+           -0.3846353799095967,
+           -0.46915537977868793,
+           -0.5542748689494378,
+           -0.6385447519076746,
+           -0.7204890914772052,
+           -0.7986478174532518,
+           -0.871619429543368,
+           -0.9381025542208135,
+           -0.9969352402048919,
+           -1.0471309310121786,
+           -1.087910134064547,
+           -1.1187269121983114,
+           -1.1392894524582593,
+           -1.149574115571441,
+           -1.149832533774845,
+           -1.1405915006127436,
+           -1.1226455795183148,
+           -1.0970425438543228,
+           -1.0650619449386545,
+           -1.028187281792211,
+           -0.988072412446597,
+           -0.9465029974326074,
+           -0.9053538977079105,
+           -0.8665435584132034,
+           -0.8319864936646675,
+           -0.8035450439168123,
+           -0.7829816047630103,
+           -0.7719125236007734,
+           -0.7717648283324919,
+           -0.7837368909001877,
+           -0.8087640393892759,
+           -0.8474900177974994,
+           -0.9002450551063488,
+           -0.9670311483408365,
+           -1.047514991677351,
+           -1.1410287995727828,
+           -1.2465790808481383,
+           -1.3628632273549959,
+           -1.4882935900371967,
+           -1.6210285315757345,
+           -1.7590097729053182,
+           -1.9000051949701973,
+           -2.0416561210121342,
+           -2.1815279918395016,
+           -2.317163259733954,
+           -2.4461352680914628,
+           -2.5661018550613464,
+           -2.6748574211030927,
+           -2.7703822325429877,
+           -2.850887795147978,
+           -2.9148572219786817,
+           -2.9610796361774474,
+           -2.9886777890874474,
+           -2.9971282338082763,
+           -2.9862735701026817,
+           -2.9563264642129825,
+           -2.9078653420665126,
+           -2.8418218518102933,
+           -2.7594603868153498,
+           -2.662350148485392,
+           -2.5523304048182425,
+           -2.431469761412072,
+           -2.3020204025804745,
+           -2.1663683780263794,
+           -2.026981102277537,
+           -1.8863532975991204,
+           -1.7469526448577815,
+           -1.6111664100310068,
+           -1.4812502867017006,
+           -1.359280637662542,
+           -1.2471112331241785,
+           -1.1463354711137381,
+           -1.0582549302482696,
+           -0.9838549495241544,
+           -0.923787757922372,
+           -0.878363492727979,
+           -0.847549254026644,
+           -0.8309761485763096,
+           -0.827954083922427,
+           -0.8374938879398732,
+           -0.8583361544789121,
+           -0.8889860567179122,
+           -0.9277532300437143,
+           -0.9727957091696545,
+           -1.0221668125717722,
+           -1.0738638033513623,
+           -1.1258771208025913,
+           -1.1762389720404265,
+           -1.2230700980456162,
+           -1.2646235826893581,
+           -1.2993246552655153,
+           -1.325805544654075,
+           -1.3429345737038008,
+           -1.3498388324320372,
+           -1.3459199343927637,
+           -1.3308625378751413,
+           -1.3046354979996395,
+           -1.2674857026460018,
+           -1.219924829794071,
+           -1.1627094416667798,
+           -1.0968149975970432,
+           -1.0234045186496847,
+           -0.9437927689627765,
+           -0.859406928263275,
+           -0.7717448143612735,
+           -0.6823317715718302,
+           -0.5926773695747684,
+           -0.5042330565425798,
+           -0.4183518805206276,
+           -0.3362513348416085,
+           -0.25898029831797736,
+           -0.18739093127613968,
+           -0.122116256986169,
+           -0.06355400805940553,
+           -0.011857152754848718,
+           0.03306865895813029,
+           0.07156067083936284,
+           0.10418774109755873,
+           0.13173251146627496,
+           0.15516749923759243,
+           0.17562574625018545,
+           0.19436680204221327,
+           0.21273894176659025,
+           0.2321386198798403,
+           0.2539682354861225,
+           0.27959333261724184,
+           0.31030037742008704,
+           0.3472562436893782,
+           0.39147049864541816,
+           0.4437615132636832,
+           0.5047273274723733,
+           0.5747220824683477,
+           0.653838693192882,
+           0.7418982771234748,
+           0.8384466848934056,
+           0.9427582981156621,
+           1.0538470746769173,
+           1.1704846363281056,
+           1.2912250122954962,
+           1.414435480436078,
+           1.5383327885152853,
+           1.6610238965235102,
+           1.7805502601771048,
+           1.8949345789623968,
+           2.002228861778055,
+           2.1005626212589474,
+           2.188189995366889,
+           2.263534612223994,
+           2.325231061112501,
+           2.3721619080058276,
+           2.4034892961533862,
+           2.4186802986730207,
+           2.4175253377595656,
+           2.4001491504117904,
+           2.367013959484746,
+           2.3189146970158365,
+           2.256966319539204,
+           2.182583447757682,
+           2.09745275074286,
+           2.003498673148002,
+           1.9028432683397165,
+           1.7977610468082352,
+           1.690629874065789,
+           1.5838790523760387,
+           1.4799357935648616,
+           1.3811713340021305,
+           1.2898479564821221,
+           1.2080681667772084,
+           1.1377272254534236,
+           1.080470159219927,
+           1.037654272454599,
+           1.0103180510935745,
+           0.9991572008938313,
+           1.004508393808699,
+           1.0263411139365068
+          ],
+          [
+           1.051410205904631,
+           1.1006974657505264,
+           1.1646435637149994,
+           1.241945040407839,
+           1.3309991060340507,
+           1.4299390760677964,
+           1.536675706394549,
+           1.648943457819165,
+           1.7643506042738148,
+           1.8804320097549279,
+           1.9947033381221517,
+           2.104715428857168,
+           2.2081075714264693,
+           2.3026584409902964,
+           2.3863335180722305,
+           2.4573279029434216,
+           2.514103549684554,
+           2.555420082332817,
+           2.580358512799903,
+           2.588337353478067,
+           2.5791208023663774,
+           2.5528188706003903,
+           2.509879516739721,
+           2.4510730442924706,
+           2.377469204032708,
+           2.2904076161794036,
+           2.1914622852281336,
+           2.08240111833423,
+           1.9651414733032593,
+           1.8417028516905738,
+           1.714157914126374,
+           1.5845830273383472,
+           1.4550095547401307,
+           1.3273770749326703,
+           1.2034896558105104,
+           1.0849762276796777,
+           0.9732559890638666,
+           0.8695096465132266,
+           0.7746571381035643,
+           0.6893423232624925,
+           0.6139249432978611,
+           0.5484799720170348,
+           0.49280428875560317,
+           0.44643042166515823,
+           0.40864693185141143,
+           0.3785248433261266,
+           0.35494937385964376,
+           0.33665609141386227,
+           0.32227051312282723,
+           0.31035008141997794,
+           0.2994273968983768,
+           0.28805356115441794,
+           0.27484048580667975,
+           0.2585010559640129,
+           0.23788609677310685,
+           0.2120171787288373,
+           0.1801144089342398,
+           0.141618488592098,
+           0.0962064682970824,
+           0.04380079832124232,
+           -0.01542855316698371,
+           -0.08106895960525999,
+           -0.15247683646092874,
+           -0.22879586690105744,
+           -0.30898126628244704,
+           -0.39182944074154535,
+           -0.476012253351751,
+           -0.5601149895922701,
+           -0.642677015341757,
+           -0.7222340477916379,
+           -0.7973609144421716,
+           -0.8667136588793194,
+           -0.9290698647891259,
+           -0.9833661113699919,
+           -1.0287315429444368,
+           -1.0645166314390384,
+           -1.09031633012059,
+           -1.1059869575715793,
+           -1.1116563088531197,
+           -1.1077266621910293,
+           -1.0948705300395531,
+           -1.0740191884997987,
+           -1.0463442041444504,
+           -1.0132323576681537,
+           -0.976254534893353,
+           -0.9371293131870654,
+           -0.8976821112877513,
+           -0.8598008893377642,
+           -0.8253894805203987,
+           -0.7963197036633464,
+           -0.7743834457040794,
+           -0.7612459129325998,
+           -0.7584012300825139,
+           -0.7671315170230586,
+           -0.7884704951383756,
+           -0.8231725712979235,
+           -0.8716882191188462,
+           -0.9341463280941016,
+           -1.0103440247319881,
+           -1.0997442901828156,
+           -1.2014815103132324,
+           -1.314374901452541,
+           -1.4369495628172742,
+           -1.5674647196555986,
+           -1.703948544057998,
+           -1.8442387775354503,
+           -1.9860282349094416,
+           -2.1269141463843195,
+           -2.2644501969430677,
+           -2.396200051877052,
+           -2.5197911161103326,
+           -2.632967264079801,
+           -2.7336392966092062,
+           -2.8199319310451254,
+           -2.890226209741413,
+           -2.943196317908589,
+           -2.9778399323424507,
+           -2.9935013744629817,
+           -2.989887010754975,
+           -2.9670725269918745,
+           -2.925501895095184,
+           -2.8659780484566406,
+           -2.7896454782412397,
+           -2.697965154813391,
+           -2.592682360327444,
+           -2.4757881862760835,
+           -2.349475599322364,
+           -2.2160911064251776,
+           -2.078083153013815,
+           -1.93794846329464,
+           -1.7981775778758378,
+           -1.6612008596851562,
+           -1.5293362242831887,
+           -1.4047398055473996,
+           -1.2893606934640474,
+           -1.1849007792761215,
+           -1.092780617017775,
+           -1.0141120626481195,
+           -0.9496782862312442,
+           -0.8999215729835593,
+           -0.8649391399456958,
+           -0.8444870011802393,
+           -0.837991720505227,
+           -0.8445697015943174,
+           -0.8630534854317782,
+           -0.8920243589881043,
+           -0.9298504306181216,
+           -0.9747292006690815,
+           -1.0247335531790873,
+           -1.0778600187937275,
+           -1.1320781119109324,
+           -1.185379527647283,
+           -1.2358259968343095,
+           -1.2815946394854396,
+           -1.3210197278770233,
+           -1.3526298677087727,
+           -1.3751797272440582,
+           -1.3876755867779427,
+           -1.3893941406261952,
+           -1.3798941570314722,
+           -1.3590207835805115,
+           -1.3269024723407157,
+           -1.283940685277992,
+           -1.2307927219488874,
+           -1.1683481834398368,
+           -1.0976997447712606,
+           -1.020109048562395,
+           -0.9369686521818882,
+           -0.8497610559425783,
+           -0.7600159087988432,
+           -0.6692665288002205,
+           -0.579006887281674,
+           -0.4906501881964103,
+           -0.40549012762450126,
+           -0.32466584454622643,
+           -0.249131474370214,
+           -0.17963109401433608,
+           -0.11667970469085005,
+           -0.0605507395853355,
+           -0.01127041238838968,
+           0.031380956506613815,
+           0.06786068183669701,
+           0.09884875027115324,
+           0.12522655449035586,
+           0.14804989189739792,
+           0.16851694585066204,
+           0.18793209949483536,
+           0.20766654274820773,
+           0.22911671895479738,
+           0.253661716926864,
+           0.28262074505474627,
+           0.31721182602553627,
+           0.3585128233804167,
+           0.4074258552975023,
+           0.4646460679766257,
+           0.530635632873641,
+           0.6056037014678032,
+           0.6894929014981064,
+           0.7819727934111601,
+           0.8824405292566067,
+           0.9900287728693489,
+           1.1036207544951224,
+           1.2218721497169756,
+           1.3432392962439095,
+           1.4660130972827803,
+           1.5883578110054337,
+           1.7083537958383346,
+           1.8240431742576624,
+           1.9334772962242661,
+           2.034764829464568,
+           2.1261192789373444,
+           2.2059047427415046,
+           2.2726787463973754,
+           2.3252310611125004,
+           2.362617502839821,
+           2.3841878254806166,
+           2.3896069606721713,
+           2.378869014860881,
+           2.3523036079421225,
+           2.310574322408037,
+           2.25466922315861,
+           2.1858836012044818,
+           2.1057952846689276,
+           2.016233043092416,
+           1.9192387815424667,
+           1.8170243752128872,
+           1.7119241292305634,
+           1.6063439589366573,
+           1.5027084702061893,
+           1.4034071752897916,
+           1.3107411057749156,
+           1.2268710798695073,
+           1.1537688463592162,
+           1.0931722630747096,
+           1.0465455750547943,
+           1.0150457390208003,
+           0.9994955991425567,
+           1.0003645577997178,
+           1.0177572080301636,
+           1.0514102059046302
+          ],
+          [
+           1.0845047967725792,
+           1.1447397882500672,
+           1.2188289313300877,
+           1.3052745421963083,
+           1.4023005810742135,
+           1.507891795286911,
+           1.6198381978011887,
+           1.7357838391389135,
+           1.853278730150248,
+           1.969832700376886,
+           2.082969933322019,
+           2.190282906915141,
+           2.289484485095943,
+           2.378456954272453,
+           2.4552968752254656,
+           2.5183547249158047,
+           2.5662684310239827,
+           2.5979900517365215,
+           2.6128050205945375,
+           2.610343557016046,
+           2.590584032946633,
+           2.5538482803215734,
+           2.5007890178741468,
+           2.4323697645554683,
+           2.34983778583119,
+           2.2546907840286794,
+           2.1486381907194088,
+           2.033558044283952,
+           1.9114505363114345,
+           1.784389383936371,
+           1.6544722298922814,
+           1.5237712869563311,
+           1.3942854283050392,
+           1.2678948805740609,
+           1.1463196033233556,
+           1.0310823390607848,
+           0.9234771945326732,
+           0.8245444697964729,
+           0.7350522903045527,
+           0.6554854229214581,
+           0.5860414738575589,
+           0.5266344795221362,
+           0.47690571496211576,
+           0.4362413635159628,
+           0.40379652009087696,
+           0.3785248433261265,
+           0.3592130327365843,
+           0.3445191891816904,
+           0.33301402357699594,
+           0.3232238119448065,
+           0.3136739563032055,
+           0.3029320014245591,
+           0.28964897732892236,
+           0.2725979859522262,
+           0.250709026460167,
+           0.2230991551945694,
+           0.1890972006291653,
+           0.14826239779330377,
+           0.10039646671931902,
+           0.04554883150629916,
+           -0.01598514380409187,
+           -0.08367284373729457,
+           -0.15675977450385317,
+           -0.23429120719923954,
+           -0.31513951247105954,
+           -0.39803645877958954,
+           -0.48160961574021766,
+           -0.5644218953464398,
+           -0.6450131799030767,
+           -0.7219429284031077,
+           -0.7938326243339611,
+           -0.8594069282632743,
+           -0.9175324280603873,
+           -0.9672529375548423,
+           -1.0078203793969776,
+           -1.038720397766817,
+           -1.0596919786448826,
+           -1.0707405063197317,
+           -1.0721438508895207,
+           -1.0644512585607464,
+           -1.0484750001160181,
+           -1.0252749184027767,
+           -0.9961361984179237,
+           -0.9625408589219386,
+           -0.9261336280774947,
+           -0.8886830132262825,
+           -0.8520385028375904,
+           -0.8180849436123367,
+           -0.7886952150020885,
+           -0.7656823749346118,
+           -0.7507524729442026,
+           -0.7454592195269024,
+           -0.7511616634598682,
+           -0.7689859628611289,
+           -0.7997922424625233,
+           -0.8441474111488196,
+           -0.9023046731333503,
+           -0.974190306607013,
+           -1.0593981092006393,
+           -1.157191724407225,
+           -1.2665148717614494,
+           -1.3860093107722389,
+           -1.5140401790990452,
+           -1.6487281639309563,
+           -1.7879877964601716,
+           -1.9295710069282335,
+           -2.071114945753477,
+           -2.2101929680131325,
+           -2.344367596765384,
+           -2.4712442274231874,
+           -2.588524311999578,
+           -2.694056769170845,
+           -2.785886403634988,
+           -2.862298185319026,
+           -2.921856334023409,
+           -2.963437275810998,
+           -2.9862556809456287,
+           -2.9898829559934934,
+           -2.9742577408763973,
+           -2.939688150886217,
+           -2.886845699339307,
+           -2.816751033911981,
+           -2.7307518139550453,
+           -2.6304932425122844,
+           -2.5178819408325084,
+           -2.3950440106363464,
+           -2.264278266454712,
+           -2.1280057336717335,
+           -1.9887165947413818,
+           -1.8489158243117436,
+           -1.711068782293899,
+           -1.5775480315979205,
+           -1.4505826144200678,
+           -1.332210958446307,
+           -1.2242384937046444,
+           -1.1282009443098218,
+           -1.0453341198840893,
+           -0.9765508724550448,
+           -0.9224257100455017,
+           -0.8831873722797515,
+           -0.8587194807039055,
+           -0.8485691818817418,
+           -0.8519635094499608,
+           -0.8678330068888919,
+           -0.8948419802860395,
+           -0.9314245940364302,
+           -0.9758258860256723,
+           -1.026146665669377,
+           -1.080391170947231,
+           -1.136516301335485,
+           -1.1924812136769019,
+           -1.2462960681704214,
+           -1.2960687417101888,
+           -1.3400483849090055,
+           -1.3766647857427663,
+           -1.4045626146076309,
+           -1.4226297598286626,
+           -1.4300191158841387,
+           -1.4261633549380646,
+           -1.4107823914608224,
+           -1.383883435260572,
+           -1.3457537154934087,
+           -1.2969461424834388,
+           -1.2382583508645584,
+           -1.1707057322519412,
+           -1.0954892142698387,
+           -1.0139586716198392,
+           -0.9275729607883639,
+           -0.8378576503618702,
+           -0.746361571785833,
+           -0.654613339504391,
+           -0.564078984210267,
+           -0.4761218086145682,
+           -0.39196551263905693,
+           -0.31266154587262596,
+           -0.23906153181696646,
+           -0.17179547378008345,
+           -0.11125629970030244,
+           -0.05759113658580834,
+           -0.010699528873720917,
+           0.02976136666956563,
+           0.06436475925539616,
+           0.0938957037648095,
+           0.11932657996184541,
+           0.1417872265383505,
+           0.16253052569599147,
+           0.18289435401788948,
+           0.2042609120210962,
+           0.22801451554171223,
+           0.2554989751670976,
+           0.2879757041712901,
+           0.3265836804324921,
+           0.372302343952749,
+           0.42591843992461237,
+           0.4879977195639513,
+           0.5588622895758695,
+           0.6385742591629898,
+           0.7269261744659351,
+           0.8234385582220485,
+           0.9273646915530985,
+           1.037702589685952,
+           1.153213938726625,
+           1.272449581000098,
+           1.3937809664698875,
+           1.5154368316657258,
+           1.6355442293376536,
+           1.7521729152449979,
+           1.8633820060765338,
+           1.9672677568780834,
+           2.0620112692666535,
+           2.145924934160453,
+           2.2174964350407005,
+           2.275429189432175,
+           2.318678186159601,
+           2.3464802821181894,
+           2.358378152241916,
+           2.3542372369201936,
+           2.3342551986415323,
+           2.298963580041639,
+           2.2492215443860095,
+           2.18620177218651,
+           2.1113687793977274,
+           2.026450108733277,
+           1.933401021488042,
+           1.8343634784942393,
+           1.7316203414763411,
+           1.6275458465501245,
+           1.5245534969235444,
+           1.4250425896047447,
+           1.3313446293816589,
+           1.24567089150441,
+           1.1700623721123495,
+           1.106343312991522,
+           1.0560794059512573,
+           1.0205416739072866,
+           1.0006768932512256,
+           0.9970852684687642,
+           1.0100058989589118,
+           1.03931039374944,
+           1.084504796772578
+          ],
+          [
+           1.1253448913261357,
+           1.1960121521584866,
+           1.27959997574216,
+           1.3744291370372184,
+           1.4785653925800142,
+           1.5898619997389416,
+           1.7060069623362504,
+           1.824573897305256,
+           1.9430753327080685,
+           2.059017191822873,
+           2.1699531924502162,
+           2.27353789567598,
+           2.3675771739055143,
+           2.4500749331424445,
+           2.519275017597277,
+           2.5736973434615007,
+           2.612167450133729,
+           2.633838817843266,
+           2.6382074765249546,
+           2.625118617630247,
+           2.594765113724574,
+           2.547678045483606,
+           2.4847095272929867,
+           2.407008306396096,
+           2.3159887819427447,
+           2.2132942452008697,
+           2.1007552768504953,
+           1.9803443484383232,
+           1.8541277600726365,
+           1.7242161032731298,
+           1.5927144652505065,
+           1.4616735881987533,
+           1.3330431646066183,
+           1.2086283880403585,
+           1.090050789939833,
+           0.9787142790011073,
+           0.8757771636040393,
+           0.782130782938925,
+           0.6983852029050225,
+           0.6248622527664919,
+           0.5615959924813259,
+           0.5083405132278465,
+           0.4645847896261265,
+           0.42957412607890316,
+           0.4023375759207984,
+           0.3817205647313513,
+           0.3664218218839672,
+           0.3550336203083251,
+           0.34608424609080995,
+           0.3380815688296872,
+           0.32955656180655457,
+           0.31910562851516766,
+           0.3054306286484084,
+           0.28737556129969144,
+           0.263958954197783,
+           0.2344011229137756,
+           0.19814560020336816,
+           0.1548741894966034,
+           0.10451526410020312,
+           0.04724511067229041,
+           -0.016517702531773155,
+           -0.08612476987987495,
+           -0.16071676432449244,
+           -0.23924831523344497,
+           -0.3205181821828768,
+           -0.4032039198424196,
+           -0.48590011072544614,
+           -0.5671591478403695,
+           -0.6455334805823184,
+           -0.7196181963133745,
+           -0.7880927980595053,
+           -0.8497610559425776,
+           -0.9035878559700722,
+           -0.9487320435012134,
+           -0.9845743582758222,
+           -1.0107396808576783,
+           -1.027112953642351,
+           -1.033848299629509,
+           -1.0313710349546068,
+           -1.0203724523810518,
+           -1.0017974380195083,
+           -0.9768251678093035,
+           -0.9468433091225706,
+           -0.9134163217175675,
+           -0.8782486068962673,
+           -0.8431433901841175,
+           -0.8099583376635814,
+           -0.7805589963091459,
+           -0.7567712119489022,
+           -0.7403337131430574,
+           -0.7328520543598676,
+           -0.7357550871156899,
+           -0.7502550737424051,
+           -0.7773124763957665,
+           -0.8176063457671199,
+           -0.8715111023056024,
+           -0.939080350785946,
+           -1.0200382004667563,
+           -1.1137783819949594,
+           -1.21937126306178,
+           -1.335578672251651,
+           -1.460876249289447,
+           -1.5934828547026643,
+           -1.7313963973525714,
+           -1.8724352786787375,
+           -2.0142845118097314,
+           -2.1545454554263874,
+           -2.290788009383497,
+           -2.4206040539409166,
+           -2.5416608786893637,
+           -2.6517533418198505,
+           -2.7488535254780913,
+           -2.8311567080129154,
+           -2.897122557682585,
+           -2.945510562829746,
+           -2.9754088480229157,
+           -2.986255680945628,
+           -2.977853147136589,
+           -2.9503726548680422,
+           -2.9043521259991345,
+           -2.840684925853574,
+           -2.76060078125106,
+           -2.6656391260012593,
+           -2.5576154928214856,
+           -2.4385817353970896,
+           -2.3107810101620996,
+           -2.1765985707974096,
+           -2.038509526432722,
+           -1.8990247847308934,
+           -1.760636441742371,
+           -1.6257638906811072,
+           -1.4967019013750291,
+           -1.3755718716175007,
+           -1.264277372264576,
+           -1.1644650016624298,
+           -1.077491434486062,
+           -1.004397398548217,
+           -0.945889144334711,
+           -0.9023277900933894,
+           -0.873726734721215,
+           -0.8597571361342217,
+           -0.8597612590352084,
+           -0.8727733077537317,
+           -0.897547181716593,
+           -0.9325904274517325,
+           -0.9762035158065708,
+           -1.0265234497836857,
+           -1.0815706100240299,
+           -1.139297673842407,
+           -1.1976394015044707,
+           -1.2545620710756145,
+           -1.308111360874132,
+           -1.3564575257862614,
+           -1.3979367891794088,
+           -1.4310879739173672,
+           -1.4546835214234892,
+           -1.4677541936608374,
+           -1.4696069156054845,
+           -1.4598353911763078,
+           -1.4383233092404561,
+           -1.4052401436316322,
+           -1.3610297374103626,
+           -1.3063920422093473,
+           -1.2422585539422215,
+           -1.169762142173339,
+           -1.0902021081810958,
+           -1.0050054227940286,
+           -0.9156851865829913,
+           -0.823797419718716,
+           -0.7308973251920308,
+           -0.6384961762964282,
+           -0.5480199571754845,
+           -0.46077083446248285,
+           -0.3778924599270296,
+           -0.30034000061959315,
+           -0.2288556669289363,
+           -0.16395036346622213,
+           -0.10589192647486491,
+           -0.054700238641435674,
+           -0.010149332143704266,
+           0.02822359190987993,
+           0.061102480182421134,
+           0.0893705065932503,
+           0.11408250433502377,
+           0.1364324881432762,
+           0.15771713360956827,
+           0.1792961872177163,
+           0.20255086276227252,
+           0.2288413347802124,
+           0.25946446617074226,
+           0.2956129045896007,
+           0.33833665051185935,
+           0.38850813982250404,
+           0.44679179689281323,
+           0.5136189024864884,
+           0.5891684872906497,
+           0.673354809716459,
+           0.7658218096683114,
+           0.8659447524223672,
+           0.9728390930414373,
+           1.0853764065025553,
+           1.2022070465916541,
+           1.3217890222222692,
+           1.442422417572952,
+           1.5622885364275403,
+           1.6794928250607564,
+           1.7921105251649423,
+           1.898233931315507,
+           1.99602007833636,
+           2.083737663974432,
+           2.1598120221229253,
+           2.2228670013023257,
+           2.2717626713357286,
+           2.3056278765411125,
+           2.3238867740304125,
+           2.3262786379518934,
+           2.3128703712850127,
+           2.284061342174719,
+           2.240580347483015,
+           2.1834746976831783,
+           2.114091609716635,
+           2.0340522832297676,
+           1.9452192160432478,
+           1.8496574823144285,
+           1.7495908474736201,
+           1.6473537239012555,
+           1.545340077220003,
+           1.4459504723456873,
+           1.3515384990658055,
+           1.26435783758752,
+           1.18651121464795,
+           1.1199024605845076,
+           1.066192808146715,
+           1.0267624764390404,
+           1.0026784605480115,
+           0.9946693020830623,
+           1.0031074515603848,
+           1.0279996542624497,
+           1.068985601262416,
+           1.1253448913261341
+          ],
+          [
+           1.1735849638850238,
+           1.25408077007611,
+           1.3464425464162786,
+           1.4488237457654038,
+           1.5591483057358924,
+           1.6751561844022826,
+           1.794452973259957,
+           1.914562428248145,
+           2.0329806920562112,
+           2.147230942938813,
+           2.254917197774144,
+           2.3537760202614564,
+           2.4417249383705086,
+           2.5169064570915256,
+           2.5777266611527603,
+           2.6228875349847933,
+           2.651412280542581,
+           2.6626630838700356,
+           2.6563509643192402,
+           2.6325375316220807,
+           2.591628670864858,
+           2.53436036906528,
+           2.4617770847626095,
+           2.3752032392265723,
+           2.2762085702571184,
+           2.166568233146604,
+           2.048218654739989,
+           1.9232102427436701,
+           1.793658121212698,
+           1.661692102883981,
+           1.5294071188356264,
+           1.3988153056966324,
+           1.2718009009081979,
+           1.150079018676792,
+           1.035159275283097,
+           0.9283151049855662,
+           0.8305594601241315,
+           0.7426274249238105,
+           0.6649660960564205,
+           0.5977318986742475,
+           0.5407953190033109,
+           0.4937528483671296,
+           0.4559457533512599,
+           0.42648511719965604,
+           0.40428244266903457,
+           0.3880849702926324,
+           0.3765147516835915,
+           0.368110427948601,
+           0.3613706006674594,
+           0.3547976487281624,
+           0.34694083937890463,
+           0.33643760622240726,
+           0.32205191985369636,
+           0.3027087570320398,
+           0.2775237796016337,
+           0.2458274621253527,
+           0.2071830541020031,
+           0.16139792495231706,
+           0.1085280135501153,
+           0.048875284529896694,
+           -0.01702172366220581,
+           -0.08840399362832572,
+           -0.16431432799840567,
+           -0.24362525162658746,
+           -0.32507176943826116,
+           -0.4072881048711412,
+           -0.48884743877839043,
+           -0.5683035886793397,
+           -0.6442335154002972,
+           -0.7152795198078707,
+           -0.7801899971463869,
+           -0.8378576503618695,
+           -0.8873541259080553,
+           -0.9279601243535994,
+           -0.9591901514385998,
+           -0.980811210238093,
+           -0.9928548884066931,
+           -0.9956224622634245,
+           -0.9896828175210971,
+           -0.9758631702981131,
+           -0.9552327570471978,
+           -0.9290798435331621,
+           -0.8988825764071169,
+           -0.8662743618688956,
+           -0.833004600297083,
+           -0.8008957298784216,
+           -0.7717976330045881,
+           -0.7475405339230616,
+           -0.729887562872446,
+           -0.7204881794378405,
+           -0.7208336355923296,
+           -0.7322156170503318,
+           -0.7556891310893705,
+           -0.7920406115546784,
+           -0.8417620896772345,
+           -0.905032135558874,
+           -0.981704113202508,
+           -1.0713021157448697,
+           -1.1730247613997544,
+           -1.2857568391129004,
+           -1.4080886007799631,
+           -1.5383423088266335,
+           -1.6746054686443035,
+           -1.8147700092578956,
+           -1.9565765268012054,
+           -2.0976625775953472,
+           -2.235613904063604,
+           -2.3680173999757472,
+           -2.4925145735445704,
+           -2.60685424894197,
+           -2.7089432593674085,
+           -2.7968939276473646,
+           -2.869067202482904,
+           -2.9241104181873965,
+           -2.9609887706810607,
+           -2.979009749626232,
+           -2.9778399323424507,
+           -2.9575137255187482,
+           -2.918433831365664,
+           -2.8613634110909048,
+           -2.7874101156696613,
+           -2.6980023470196692,
+           -2.5948582971837975,
+           -2.4799484844809365,
+           -2.3554526596429217,
+           -2.223712087966798,
+           -2.0871783222512317,
+           -1.9483596631188813,
+           -1.8097665562810452,
+           -1.6738571991099354,
+           -1.5429846210214093,
+           -1.4193464638614584,
+           -1.3049386207023461,
+           -1.201513795881602,
+           -1.1105459281278944,
+           -1.0332012752042663,
+           -0.9703167961967377,
+           -0.9223862903816067,
+           -0.8895545638721144,
+           -0.8716197015826822,
+           -0.8680433272021597,
+           -0.8779685426034485,
+           -0.9002450551063489,
+           -0.9334608307125607,
+           -0.9759794579844682,
+           -1.025982274357658,
+           -1.0815141975618596,
+           -1.1405321220841789,
+           -1.200954686194626,
+           -1.260712190214737,
+           -1.3177954519615696,
+           -1.3703024204104022,
+           -1.416481432623007,
+           -1.4547700902017198,
+           -1.4838288476020953,
+           -1.5025685426047166,
+           -1.5101712556113236,
+           -1.5061040552426546,
+           -1.4901253686775788,
+           -1.462283901743551,
+           -1.4229102212768518,
+           -1.3726012960336804,
+           -1.3121984678697183,
+           -1.2427594876537271,
+           -1.1655253964030756,
+           -1.0818831578149855,
+           -0.9933250506214207,
+           -0.9014059055148274,
+           -0.8076993199266835,
+           -0.7137540035412714,
+           -0.6210513976701708,
+           -0.5309656728128331,
+           -0.44472714192787566,
+           -0.36339003388249186,
+           -0.2878054546355312,
+           -0.21860022594128276,
+           -0.15616213625596034,
+           -0.10063197003943125,
+           -0.051902504056973144,
+           -0.009624477111642524,
+           0.026780642497874676,
+           0.05810144497492741,
+           0.08531144397222208,
+           0.1095386948626651,
+           0.13203098022204401,
+           0.15411749306652836,
+           0.17716804121363458,
+           0.20255086276227244,
+           0.2315901814054,
+           0.2655246400895019,
+           0.3054677321382667,
+           0.35237130081848683,
+           0.40699310262341726,
+           0.46986932815685206,
+           0.5412928499429948,
+           0.6212978218716043,
+           0.7096510939321494,
+           0.8058507324309472,
+           0.9091317543749093,
+           1.0184789997076307,
+           1.132646881256242,
+           1.250185574228038,
+           1.3694730393843983,
+           1.488752120866264,
+           1.6061718249453,
+           1.7198317731679584,
+           1.8278287353462699,
+           1.928304086916384,
+           2.019491002948984,
+           2.0997601984573686,
+           2.16766305177662,
+           2.221971004105597,
+           2.26171021251025,
+           2.286190543781741,
+           2.295028129878593,
+           2.2881608590266396,
+           2.265856346168622,
+           2.2287121081991286,
+           2.1776478588324104,
+           2.1138900303734363,
+           2.0389488203537014,
+           1.9545882452442966,
+           1.862789856708396,
+           1.7657109338073682,
+           1.665638103299097,
+           1.5649374562033949,
+           1.4660023192472669,
+           1.3711999023592891,
+           1.2828180764563104,
+           1.2030135384778224,
+           1.1337625928418005,
+           1.0768157208351266,
+           1.0336570232640927,
+           1.0054695090277943,
+           0.9931070658451843,
+           0.9970737924560595,
+           1.017511198023394,
+           1.0541935883981965,
+           1.1065317648853468,
+           1.173584963885022
+          ],
+          [
+           1.2288168816065133,
+           1.3184543552190058,
+           1.418791124957933,
+           1.5278289563270806,
+           1.643367552632366,
+           1.7630527218786247,
+           1.8844279372976174,
+           2.0049880882755295,
+           2.1222341681719517,
+           2.233727625473087,
+           2.3371431153621116,
+           2.4303184298294114,
+           2.511300454851308,
+           2.578386101185478,
+           2.6301572785377645,
+           2.6655091282065784,
+           2.683670893226792,
+           2.6842189834831145,
+           2.6670819818606333,
+           2.632537531622081,
+           2.5812012400933355,
+           2.514007924635412,
+           2.4321857091238717,
+           2.3372236483071087,
+           2.230833709365921,
+           2.1149080710716253,
+           1.9914728079840385,
+           1.8626391075876467,
+           1.730553220239198,
+           1.5973463641046506,
+           1.4650857994452118,
+           1.3357282489636335,
+           1.2110767744731064,
+           1.0927421266420692,
+           0.9821094664058345,
+           0.8803112168322197,
+           0.7882066463256336,
+           0.7063686120354101,
+           0.635077710525004,
+           0.5743238957169705,
+           0.5238154365335506,
+           0.48299490318570104,
+           0.45106169629361015,
+           0.4270004712911325,
+           0.409614665882833,
+           0.397564214258995,
+           0.38940643138224934,
+           0.3836389763925583,
+           0.3787437578300714,
+           0.3732306260401785,
+           0.36567971016551837,
+           0.35478129817206533,
+           0.33937222729996935,
+           0.31846784737502565,
+           0.29128873811064926,
+           0.2572815008290933,
+           0.21613310137559313,
+           0.16777841040646552,
+           0.11240076539291946,
+           0.05042556107062058,
+           -0.017492942948554212,
+           -0.09049123171837443,
+           -0.16752202850899542,
+           -0.24738498551619462,
+           -0.3287617488285102,
+           -0.4102544598122966,
+           -0.4904266641700412,
+           -0.5678455353759871,
+           -0.6411242826506937,
+           -0.7089636060531065,
+           -0.7701910828663893,
+           -0.8237974197187153,
+           -0.8689685825765082,
+           -0.9051129199473894,
+           -0.931882520761638,
+           -0.9491881943122898,
+           -0.9572076216717543,
+           -0.9563864021029835,
+           -0.9474318997726128,
+           -0.9312999809790318,
+           -0.9091749154708713,
+           -0.8824428926227341,
+           -0.8526597697728143,
+           -0.8215138216882232,
+           -0.7907843930489176,
+           -0.7622974666326653,
+           -0.7378792456899418,
+           -0.7193089075868947,
+           -0.7082717156088965,
+           -0.7063136760143135,
+           -0.7147988979027587,
+           -0.734870754849209,
+           -0.7674178609166707,
+           -0.8130457616498625,
+           -0.8720551056687887,
+           -0.944426907798871,
+           -1.0298153440655202,
+           -1.1275483365209142,
+           -1.2366359962359672,
+           -1.355786800547379,
+           -1.48343119053992,
+           -1.6177520914663222,
+           -1.7567216869016151,
+           -1.8981436211632194,
+           -2.0396996677941095,
+           -2.17899978811953,
+           -2.313634415905764,
+           -2.4412277441987755,
+           -2.5594907600406174,
+           -2.666272772768334,
+           -2.759610212061066,
+           -2.837771532137784,
+           -2.8992971471070437,
+           -2.943033437321445,
+           -2.9681600049349632,
+           -2.974209515363956,
+           -2.961079636177447,
+           -2.9290367718505514,
+           -2.878711487268576,
+           -2.811085710142267,
+           -2.7274719977888524,
+           -2.6294853422975195,
+           -2.5190081653431458,
+           -2.39814931552592,
+           -2.2691980231672217,
+           -2.1345738865313506,
+           -1.996774056582003,
+           -1.8583188523671244,
+           -1.721697074394332,
+           -1.5893122880751622,
+           -1.463431323394174,
+           -1.3461361810623087,
+           -1.2392804509392563,
+           -1.1444512375544271,
+           -1.062937452861799,
+           -0.9957051812534841,
+           -0.9433806501471929,
+           -0.9062411553753377,
+           -0.8842140986554603,
+           -0.8768840993179488,
+           -0.88350794898174,
+           -0.9030369907285847,
+           -0.9341463280941019,
+           -0.9752701081551777,
+           -1.0246419810521792,
+           -1.0803397188672041,
+           -1.1403328827503936,
+           -1.2025323607774068,
+           -1.2648405617792717,
+           -1.3252010431330323,
+           -1.38164637331904,
+           -1.4323430822737802,
+           -1.4756326328074598,
+           -1.5100674525319284,
+           -1.5344411951400603,
+           -1.547812549203901,
+           -1.5495220781420804,
+           -1.539201752479174,
+           -1.516777020525846,
+           -1.4824614515152381,
+           -1.436744171343551,
+           -1.3803704907412195,
+           -1.3143162944760274,
+           -1.2397569138732012,
+           -1.1580313397275157,
+           -1.0706027452559728,
+           -0.9790163763360249,
+           -0.8848559267631572,
+           -0.789699548194487,
+           -0.6950766470921622,
+           -0.6024265943466496,
+           -0.513060418085173,
+           -0.42812646790944314,
+           -0.3485809315922033,
+           -0.27516395585141223,
+           -0.20838197452540133,
+           -0.1484966840757099,
+           -0.09552093200560267,
+           -0.04922160293299464,
+           -0.009129404288606549,
+           0.02544472643851748,
+           0.05538704374875429,
+           0.08175285740824555,
+           0.1057335942290028,
+           0.12861994152337272,
+           0.1517620586547217,
+           0.17652792108383566,
+           0.20426091202109603,
+           0.23623779893095878,
+           0.2736282251097639,
+           0.31745681051686603,
+           0.3685688918600288,
+           0.427600841205652,
+           0.49495578735953305,
+           0.5707854278153842,
+           0.6549784646094884,
+           0.7471560288213406,
+           0.8466742799539767,
+           0.9526341825008151,
+           1.063898277288989,
+           1.1791140843404622,
+           1.2967436015814413,
+           1.4150982041240294,
+           1.5323781060955313,
+           1.646715424740731,
+           1.7562197879046906,
+           1.8590253535681727,
+           1.9533380657558808,
+           2.0374819560730195,
+           2.1099433148234588,
+           2.169411599858034,
+           2.2148160239922428,
+           2.245356861306193,
+           2.260530636512123,
+           2.26014850685094,
+           2.244347309124353,
+           2.213592921497595,
+           2.1686757762800086,
+           2.110698551421086,
+           2.0410562602296456,
+           1.9614091460982195,
+           1.8736489671605587,
+           1.7798594204084048,
+           1.682271601753477,
+           1.5832155241754364,
+           1.4850688173012698,
+           1.39020380596511,
+           1.300934210611454,
+           1.2194627276478827,
+           1.147830732581646,
+           1.0878713032954652,
+           1.0411666861794577,
+           1.009011225806373,
+           0.9923806518569954,
+           0.9919084681290972,
+           1.0078700212936174,
+           1.0401746456449452,
+           1.0883660888304736,
+           1.1516312270841498,
+           1.2288168816065115
+          ],
+          [
+           1.290573357473953,
+           1.3885882779274852,
+           1.4960336096545548,
+           1.6107763488906306,
+           1.730510600331046,
+           1.8528079676872804,
+           1.9751706255393375,
+           2.0950858353854995,
+           2.2100806362596916,
+           2.3177754383512603,
+           2.4159352767436726,
+           2.5025175409590648,
+           2.5757150829952025,
+           2.6339937198154098,
+           2.6761232830040886,
+           2.7012015251617094,
+           2.708670365725864,
+           2.698324144017621,
+           2.670309739884892,
+           2.625118617630247,
+           2.5635710421927995,
+           2.486792903083465,
+           2.396185756804926,
+           2.2933908581628453,
+           2.1802480911246533,
+           2.0587508273235757,
+           1.9309978321239871,
+           1.7991434021824246,
+           1.665346953169665,
+           1.5317232810019894,
+           1.400294694547035,
+           1.2729461630469368,
+           1.1513845388889654,
+           1.037102807988043,
+           0.931350188696461,
+           0.8351087491568517,
+           0.749077046178148,
+           0.6736611102380602,
+           0.6089729155770174,
+           0.5548362861919216,
+           0.5108000025612232,
+           0.47615769476782105,
+           0.44997393978594563,
+           0.4311158282245183,
+           0.4182891325409466,
+           0.41007809793707695,
+           0.4049877915361387,
+           0.4014878870936127,
+           0.398056732807607,
+           0.3932245494366585,
+           0.3856146348401053,
+           0.37398150842963246,
+           0.35724501334870346,
+           0.3345195032932775,
+           0.30513737194712853,
+           0.2686663326745521,
+           0.22492002057426108,
+           0.173961664064904,
+           0.11610075439558531,
+           0.05188282425341942,
+           -0.017927373662426693,
+           -0.0923688251712933,
+           -0.17031272725844104,
+           -0.25049570785226144,
+           -0.33155690145824784,
+           -0.41207788796079264,
+           -0.4906244259389776,
+           -0.56578886326853,
+           -0.6362320878495134,
+           -0.7007238905374306,
+           -0.7581806505588814,
+           -0.807699319926683,
+           -0.8485867759915691,
+           -0.880383727970338,
+           -0.902882501157308,
+           -0.9161381781045792,
+           -0.9204727454446844,
+           -0.9164720739716632,
+           -0.9049757435920642,
+           -0.8870599091705207,
+           -0.864013583471675,
+           -0.8373088847861829,
+           -0.8085659550798476,
+           -0.7795133955998537,
+           -0.7519451872099523,
+           -0.7276751592198207,
+           -0.7084901406245694,
+           -0.6961029696344055,
+           -0.692106550007386,
+           -0.6979301255854756,
+           -0.7147988979027584,
+           -0.7436980368450798,
+           -0.7853420328626556,
+           -0.8401502136065752,
+           -0.9082291011187483,
+           -0.9893621214261056,
+           -1.083007000591301,
+           -1.1883009943154192,
+           -1.304073906672471,
+           -1.4288686622025606,
+           -1.5609690091292416,
+           -1.6984337545140449,
+           -1.83913676911013,
+           -1.980811854584835,
+           -2.121101442271,
+           -2.2576079937757387,
+           -2.387946902117999,
+           -2.509799649412396,
+           -2.6209659645842316,
+           -2.719413742569695,
+           -2.803325534553978,
+           -2.8711404959180338,
+           -2.921590782874608,
+           -2.9537315177800925,
+           -2.9669635937046444,
+           -2.9610487573900772,
+           -2.936116592140295,
+           -2.892663214045999,
+           -2.8315416915824057,
+           -2.7539443952541656,
+           -2.6613776758107264,
+           -2.5556294519488594,
+           -2.438730456917252,
+           -2.312910043940342,
+           -2.1805475792252427,
+           -2.044120555375397,
+           -1.9061506347856825,
+           -1.7691488801803426,
+           -1.6355614467394106,
+           -1.5077169968424147,
+           -1.3877770546956052,
+           -1.277690445098091,
+           -1.1791528601550878,
+           -1.093572472347602,
+           -1.0220423651079757,
+           -0.9653203865557153,
+           -0.9238168523839065,
+           -0.8975903344638136,
+           -0.8863515771957474,
+           -0.8894753887400068,
+           -0.9060201637748864,
+           -0.9347545129958764,
+           -0.9741903066070131,
+           -1.0226212886383654,
+           -1.0781662896896702,
+           -1.1388159607576345,
+           -1.202481872656834,
+           -1.2670467760289406,
+           -1.3304147971802098,
+           -1.390560355382129,
+           -1.4455746274604706,
+           -1.4937084543911816,
+           -1.5334106804198353,
+           -1.563361035462379,
+           -1.5824968131687425,
+           -1.5900327564520664,
+           -1.585473735488048,
+           -1.5686199858195429,
+           -1.539564861686463,
+           -1.4986852473540042,
+           -1.4466249523542314,
+           -1.3842715906301533,
+           -1.3127276042568574,
+           -1.2332762357335068,
+           -1.1473433752572344,
+           -1.0564563078987521,
+           -0.9622004577970442,
+           -0.8661752706371703,
+           -0.7699503907359698,
+           -0.6750232747318626,
+           -0.582779340589801,
+           -0.49445567954972014,
+           -0.41110926162127204,
+           -0.33359044476273503,
+           -0.2625224570672932,
+           -0.19828736371208194,
+           -0.14101886011957238,
+           -0.09060205406791645,
+           -0.046680216906130605,
+           -0.00866830221470223,
+           0.024227146186179417,
+           0.052982241566555774,
+           0.07872485415393071,
+           0.10269939530722536,
+           0.1262282309781656,
+           0.15067075841511846,
+           0.17738124253427542,
+           0.20766654274820745,
+           0.2427448664095516,
+           0.28370666123534277,
+           0.33147870669719576,
+           0.3867923846867803,
+           0.4501570047756944,
+           0.5218389317042492,
+           0.6018471155493127,
+           0.6899254620260746,
+           0.7855523056636935,
+           0.887947066552489,
+           0.996083986573066,
+           1.1087126581447164,
+           1.224384882190474,
+           1.3414872266727065,
+           1.4582785069018427,
+           1.5729312776847313,
+           1.683576318613375,
+           1.7883490102005157,
+           1.8854364423238625,
+           1.9731240690450107,
+           2.049840726104037,
+           2.1142008593003325,
+           2.1650428728591735,
+           2.2014625953316873,
+           2.2228409744747197,
+           2.228865249159001,
+           2.2195430023414775,
+           2.1952086707030647,
+           2.1565222694941175,
+           2.1044602809521455,
+           2.0402988466846486,
+           1.9655895939048793,
+           1.8821286076814934,
+           1.7919192318965844,
+           1.6971295361608223,
+           1.600045420658659,
+           1.5030204424186666,
+           1.4084235320209635,
+           1.3185858270951183,
+           1.2357478766499561,
+           1.1620084675600637,
+           1.099276291407377,
+           1.0492256070845511,
+           1.0132569635820605,
+           0.9924639303723988,
+           0.9876066425810848,
+           0.9990928080787992,
+           1.0269666476144204,
+           1.0709060514028332,
+           1.1302280407423908,
+           1.2039024260008835,
+           1.290573357473951
+          ],
+          [
+           1.358331903756382,
+           1.4638891734794737,
+           1.5775164941329896,
+           1.696964150980845,
+           1.8198401792157253,
+           1.943662551833998,
+           2.0659133137810595,
+           2.184093401867811,
+           2.295776875448431,
+           2.3986632990443164,
+           2.4906270645796815,
+           2.5697625164997917,
+           2.6344238459001454,
+           2.6832588473649794,
+           2.7152357813540937,
+           2.7296627520209524,
+           2.726199191190066,
+           2.7048592294327745,
+           2.666006930098555,
+           2.610343557016046,
+           2.5388872366152437,
+           2.452945555806705,
+           2.354081803692555,
+           2.2440757140329644,
+           2.124879692753888,
+           1.998571617596007,
+           1.8673053728208484,
+           1.733260328927865,
+           1.5985909945296772,
+           1.465378054553828,
+           1.3355819662068422,
+           1.2110002128026138,
+           1.0932292174798615,
+           0.9836317965276058,
+           0.8833108886132309,
+           0.7930901352903462,
+           0.713501713805267,
+           0.6447816397972781,
+           0.5868725695902743,
+           0.5394339440939262,
+           0.5018591335472858,
+           0.4732990689905773,
+           0.45269168674053695,
+           0.43879637021793694,
+           0.4302324527302067,
+           0.4255207482083651,
+           0.42312700678771237,
+           0.4215061501905093,
+           0.41914612909253623,
+           0.41461026127831474,
+           0.40657695491926277,
+           0.3938757945281353,
+           0.37551906614239916,
+           0.35072792051427043,
+           0.3189525154022372,
+           0.27988563683262174,
+           0.23346947038545998,
+           0.1798953728037282,
+           0.11959667697688615,
+           0.05323474497234761,
+           -0.018321340323401752,
+           -0.09402088869684992,
+           -0.17266281367251668,
+           -0.25293110051620693,
+           -0.3334335790714055,
+           -0.4127429622893824,
+           -0.48943905093114615,
+           -0.5621509727336518,
+           -0.6295983211785177,
+           -0.6906300849826195,
+           -0.7442603139159668,
+           -0.7896995481944862,
+           -0.826381145459818,
+           -0.853981768576657,
+           -0.8724354459141204,
+           -0.8819407797073798,
+           -0.8829610534010854,
+           -0.8762171711468925,
+           -0.8626735472723687,
+           -0.8435172458989386,
+           -0.8201308463540565,
+           -0.7940596741531756,
+           -0.7669741859531979,
+           -0.7406284262139046,
+           -0.7168155800365242,
+           -0.6973217280273737,
+           -0.6838789629360448,
+           -0.6781190528014794,
+           -0.6815288306837237,
+           -0.6954084567815544,
+           -0.7208336355923294,
+           -0.758622780237869,
+           -0.8093100003218818,
+           -0.8731246514963593,
+           -0.9499780276566867,
+           -1.039457604199877,
+           -1.1408290572961433,
+           -1.2530460941525545,
+           -1.3747679374709738,
+           -1.5043841184589228,
+           -1.6400460515163988,
+           -1.779704694591549,
+           -1.921153446381117,
+           -2.0620752988601927,
+           -2.2000931543850824,
+           -2.3328221335735018,
+           -2.4579226454401697,
+           -2.5731529662693604,
+           -2.6764200791271273,
+           -2.7658275616949726,
+           -2.8397193754364447,
+           -2.8967185024549047,
+           -2.9357594955390187,
+           -2.9561141489617215,
+           -2.9574096591704953,
+           -2.939638821672365,
+           -2.9031619988794555,
+           -2.848700788863341,
+           -2.7773235221232317,
+           -2.690422907807295,
+           -2.5896863376072377,
+           -2.477059530226209,
+           -2.3547043576454745,
+           -2.2249518325330273,
+           -2.090251350687512,
+           -1.9531173706111162,
+           -1.816074772018229,
+           -1.6816041648731057,
+           -1.5520884197030578,
+           -1.4297616584978088,
+           -1.3166618842728397,
+           -1.2145883378671092,
+           -1.1250645549759195,
+           -1.0493079576376778,
+           -0.9882066558140603,
+           -0.9423039602233791,
+           -0.9117909214886757,
+           -0.8965070175064879,
+           -0.8959489154573056,
+           -0.9092870418427226,
+           -0.9353895080575568,
+           -0.9728527648146,
+           -1.0200382004667585,
+           -1.075113759748585,
+           -1.1360995440258441,
+           -1.200916264561757,
+           -1.2674353587038336,
+           -1.3335295466926493,
+           -1.3971226046932683,
+           -1.4562371576049766,
+           -1.5090393524279597,
+           -1.5538793579463481,
+           -1.5893267470324681,
+           -1.6141999511658582,
+           -1.627589129414204,
+           -1.6288719622910346,
+           -1.6177220603597677,
+           -1.5941098636978013,
+           -1.5582960967115962,
+           -1.5108180286057018,
+           -1.4524689684304386,
+           -1.384271590630153,
+           -1.307445838250353,
+           -1.223372282704246,
+           -1.1335519280080095,
+           -1.0395635310046998,
+           -0.9430195652846086,
+           -0.8455219839407863,
+           -0.7486189343598272,
+           -0.6537635470647936,
+           -0.5622758610568918,
+           -0.47530886171322456,
+           -0.39381949632893243,
+           -0.31854539969593676,
+           -0.24998791108323135,
+           -0.18840179847666869,
+           -0.1337919301619701,
+           -0.08591695215954305,
+           -0.04429984725215862,
+           -0.008245072022125833,
+           0.02313820302075654,
+           0.05090738414297866,
+           0.07625305248699618,
+           0.10046176879320151,
+           0.12487608353989654,
+           0.15085282524156468,
+           0.17972078607935102,
+           0.21273894176659036,
+           0.2510563311058279,
+           0.2956746803360718,
+           0.3474147890925901,
+           0.4068876003032024,
+           0.47447075798296157,
+           0.5502913176250829,
+           0.6342151172109798,
+           0.7258431467095223,
+           0.824515074582608,
+           0.9293199057757117,
+           1.03911356158795,
+           1.1525429923340351,
+           1.2680762633711966,
+           1.3840378981868435,
+           1.4986486228170284,
+           1.6100685374516999,
+           1.716442646721325,
+           1.8159476122961717,
+           1.9068385518513125,
+           1.9874946982426793,
+           2.0564627522551673,
+           2.112496811135155,
+           2.1545938321873193,
+           2.182023694172894,
+           2.194353046606979,
+           2.1914622852281322,
+           2.1735551572925558,
+           2.141160678879302,
+           2.0951272336989,
+           2.036608914363855,
+           1.9670443579813977,
+           1.888128513545295,
+           1.801777954333382,
+           1.7100905099958328,
+           1.6153001362220825,
+           1.519728061222742,
+           1.4257313447091386,
+           1.3356500541583345,
+           1.2517543031460316,
+           1.1761924063572624,
+           1.110941385231545,
+           1.0577610074984853,
+           1.018152464286378,
+           0.9933226819254022,
+           0.9841551345692777,
+           0.9911878714788007,
+           1.0145993029273654,
+           1.0542021053184731,
+           1.1094454136982266,
+           1.1794252730780284,
+           1.2629031236397255,
+           1.3583319037563781
+          ],
+          [
+           1.431519252491154,
+           1.5437199622245532,
+           1.6625503963191197,
+           1.78566317479161,
+           1.9106005206269383,
+           2.0348478034247237,
+           2.1558882778187183,
+           2.2712577434336354,
+           2.378597856776638,
+           2.4757068596486125,
+           2.5605865525466207,
+           2.6314844335298115,
+           2.6869300408659393,
+           2.7257646785623892,
+           2.747163864153129,
+           2.750652013926226,
+           2.736109067824085,
+           2.703768949948803,
+           2.6542099562194577,
+           2.5883373534780674,
+           2.507358659525405,
+           2.4127522466791946,
+           2.306230068282347,
+           2.1896954443521652,
+           2.0651969559583274,
+           1.9348795852346183,
+           1.8009342971014966,
+           1.665547288436136,
+           1.530850129936753,
+           1.3988719953974824,
+           1.2714951133892387,
+           1.1504144890005974,
+           1.0371028305804986,
+           0.9327814812136214,
+           0.8383980003728851,
+           0.7546108717196534,
+           0.6817816326168905,
+           0.6199745341011059,
+           0.5689636514923457,
+           0.5282471802067741,
+           0.49706847328938575,
+           0.47444321112158816,
+           0.45919194378835343,
+           0.4499771164106382,
+           0.44534358055739814,
+           0.4437615132636836,
+           0.4436706111678512,
+           0.44352440211908073,
+           0.4418335208492255,
+           0.4372068287658217,
+           0.42838931968956084,
+           0.4142958418049135,
+           0.3940397789253165,
+           0.3669559684939205,
+           0.3326172861109196,
+           0.29084449291333075,
+           0.24170911859511687,
+           0.1855293347619731,
+           0.12285895604986118,
+           0.05446988536637193,
+           -0.01867150979525559,
+           -0.09543344509005067,
+           -0.17455240495673294,
+           -0.25467055898406615,
+           -0.33437590412616935,
+           -0.41224405596829644,
+           -0.4868805679555015,
+           -0.556962641971442,
+           -0.6212791073055572,
+           -0.6787675875511661,
+           -0.7285478452846705,
+           -0.7699503907359692,
+           -0.8025395606637188,
+           -0.8261304142898429,
+           -0.8407989508968828,
+           -0.8468853245856354,
+           -0.8449899114298803,
+           -0.835962268322125,
+           -0.8208832065363529,
+           -0.8010403817988482,
+           -0.7778979719312008,
+           -0.753061168616163,
+           -0.728236347580167,
+           -0.7051878979670304,
+           -0.6856927839016533,
+           -0.6714939768182966,
+           -0.6642539343243005,
+           -0.6655093091623374,
+           -0.6766280499298611,
+           -0.6987700040616993,
+           -0.7328520543598667,
+           -0.779518714944948,
+           -0.8391189834440155,
+           -0.9116900966535598,
+           -0.9969486704724883,
+           -1.094289525667449,
+           -1.2027923134155445,
+           -1.3212358631901986,
+           -1.4481199851414979,
+           -1.581694274385403,
+           -1.719993290140027,
+           -1.8608773227702589,
+           -2.0020778205118845,
+           -2.1412464284785946,
+           -2.276006498507705,
+           -2.4040058618553437,
+           -2.5229696194193845,
+           -2.6307516970413563,
+           -2.7253839367669936,
+           -2.8051215482318685,
+           -2.8684838263462002,
+           -2.914289150238913,
+           -2.941683411379718,
+           -2.950161172728383,
+           -2.9395790319418786,
+           -2.910160845955099,
+           -2.862494667166037,
+           -2.797521438312847,
+           -2.716515689138686,
+           -2.621058668329255,
+           -2.513004524340296,
+           -2.3944403142206383,
+           -2.2676407663499045,
+           -2.135018847574026,
+           -1.999073284506981,
+           -1.8623342603610245,
+           -1.7273085508384587,
+           -1.5964253743513581,
+           -1.4719842128659766,
+           -1.3561058104789419,
+           -1.2506874786476359,
+           -1.1573637317505736,
+           -1.0774731469388052,
+           -1.0120321912490273,
+           -0.961716590391512,
+           -0.9268506316382992,
+           -0.9074046022786705,
+           -0.9030003698550251,
+           -0.9129249156155954,
+           -0.9361514430759714,
+           -0.9713675038873362,
+           -1.0170094177347133,
+           -1.07130211574487,
+           -1.132303411427123,
+           -1.1979516025139139,
+           -1.2661152336086736,
+           -1.3346438050076475,
+           -1.4014181984449132,
+           -1.4643996060812596,
+           -1.52167579433567,
+           -1.5715036079301672,
+           -1.6123467198675518,
+           -1.642907757419507,
+           -1.6621540794106437,
+           -1.6693366424765028,
+           -1.6640015694644585,
+           -1.6459942173362925,
+           -1.6154557302127928,
+           -1.572812250876949,
+           -1.5187571464507952,
+           -1.4542267765517205,
+           -1.3803704907412195,
+           -1.2985156825869568,
+           -1.210128846709636,
+           -1.1167736798642702,
+           -1.020067335110413,
+           -0.9216359778288261,
+           -0.823070802825175,
+           -0.7258856528395952,
+           -0.6314773310071599,
+           -0.5410896244627005,
+           -0.4557819553186171,
+           -0.37640345127050967,
+           -0.30357308428103436,
+           -0.2376663658301984,
+           -0.17880891517432249,
+           -0.12687703730056912,
+           -0.08150526436266012,
+           -0.04210063297548083,
+           -0.007863294429820497,
+           0.022187109894180965,
+           0.0491800257107101,
+           0.07435836496804724,
+           0.09903964601977784,
+           0.12457493898774694,
+           0.15230671876632246,
+           0.1835267581220148,
+           0.21943519428526104,
+           0.2611018742674766,
+           0.30943102755476837,
+           0.36513023123482435,
+           0.42868452409199154,
+           0.5003363954732212,
+           0.5800722250622923,
+           0.6676155848596321,
+           0.7624276387944715,
+           0.8637146929221765,
+           0.9704427646823933,
+           1.0813588578697368,
+           1.1950184553962506,
+           1.3098185790272656,
+           1.4240356181884346,
+           1.5358670024212577,
+           1.6434756873740064,
+           1.7450363450566049,
+           1.8387820975294202,
+           1.923050610619355,
+           1.99632837132309,
+           2.0572920091886706,
+           2.104845587346494,
+           2.1381528814548,
+           2.1566637824158694,
+           2.1601340984636663,
+           2.148638190719408,
+           2.1225740496830254,
+           2.082660604120902,
+           2.029927243896354,
+           1.9656957297795683,
+           1.8915548514337976,
+           1.809328374942291,
+           1.7210369889402948,
+           1.6288551094735033,
+           1.5350635343438936,
+           1.4419990446505915,
+           1.3520021317871904,
+           1.267364080266475,
+           1.1902746590520843,
+           1.1227716659612068,
+           1.066693531286945,
+           1.0236361189427199,
+           0.9949147677497817,
+           0.9815324942526635,
+           0.9841551345692773,
+           1.0030940397331423,
+           1.0382967607116078,
+           1.0893459701094137,
+           1.1554666720868458,
+           1.235541554989813,
+           1.3281341474005306,
+           1.4315192524911515
+          ],
+          [
+           1.5095162055903244,
+           1.6274052395661012,
+           1.7504158909221748,
+           1.8761229864447262,
+           2.002023751006829,
+           2.125592253969207,
+           2.244334288742425,
+           2.355841410311017,
+           2.457842877265359,
+           2.5482542967788318,
+           2.625221851719265,
+           2.6871610967015713,
+           2.7327894417238525,
+           2.7611515948416043,
+           2.7716374053730943,
+           2.7639917322240626,
+           2.7383161535873284,
+           2.6950625298234985,
+           2.635018625984809,
+           2.5592861894561603,
+           2.4692520569523055,
+           2.366553029283831,
+           2.2530353979090285,
+           2.1307101308092973,
+           2.0017048236980095,
+           1.8682135936541593,
+           1.732446134299769,
+           1.5965771636702935,
+           1.4626974777584312,
+           1.3327677748877431,
+           1.20857633986869,
+           1.0917015742796021,
+           0.9834802328215251,
+           0.8849820787236757,
+           0.7969915073332451,
+           0.7199965104266466,
+           0.654185168853369,
+           0.5994496724890731,
+           0.5553976788342156,
+           0.5213706396150172,
+           0.49646855294110337,
+           0.4795804412006948,
+           0.46941971581337094,
+           0.46456347263048753,
+           0.4634946690432396,
+           0.4646460679766263,
+           0.4664447964874148,
+           0.4673563585046388,
+           0.4659269624772537,
+           0.46082307471317163,
+           0.45086718667483744,
+           0.4350688874198288,
+           0.41265045808659595,
+           0.3830663506030462,
+           0.3460160739296028,
+           0.30145018403529855,
+           0.24956925405089475,
+           0.1908158840720759,
+           0.12585999125735492,
+           0.05557779558885151,
+           -0.018974919485802835,
+           -0.09659454348462017,
+           -0.1759655143137756,
+           -0.2556993666500874,
+           -0.3343759041261694,
+           -0.4105853899707689,
+           -0.4829706229357443,
+           -0.5502677666078953,
+           -0.611344830544484,
+           -0.6652367603391817,
+           -0.7111761792595849,
+           -0.7486189343598265,
+           -0.7772637321990841,
+           -0.7970653001700405,
+           -0.8082406751691178,
+           -0.8112683977524461,
+           -0.8068805725742833,
+           -0.7960479401908046,
+           -0.7799582865769885,
+           -0.7599886903615313,
+           -0.737672269431314,
+           -0.7146602340840192,
+           -0.6926801796024623,
+           -0.6734916537652214,
+           -0.6588401117438626,
+           -0.6504104200550086,
+           -0.6497810914118161,
+           -0.6583804228541413,
+           -0.6774456705686039,
+           -0.7079863272148028,
+           -0.7507524729442013,
+           -0.8062090519031789,
+           -0.8745167847431246,
+           -0.9555202679610881,
+           -1.0487436366734728,
+           -1.1533939829614839,
+           -1.2683725317640422,
+           -1.392293385126078,
+           -1.5235094581685786,
+           -1.6601450510796187,
+           -1.8001343351848316,
+           -1.941264881884749,
+           -2.081225234678598,
+           -2.217655419858125,
+           -2.34819921339642,
+           -2.470556932068996,
+           -2.58253749722169,
+           -2.6821085304023295,
+           -2.7674432811118046,
+           -2.836963257273555,
+           -2.889375527012485,
+           -2.9237037836389996,
+           -2.939312411388092,
+           -2.935922953952764,
+           -2.9136225671936007,
+           -2.8728642272517826,
+           -2.814458661028514,
+           -2.739558162859094,
+           -2.64963265441167,
+           -2.546438529673707,
+           -2.4319809988490477,
+           -2.3084707998851757,
+           -2.178276280409618,
+           -2.043871962811231,
+           -1.9077847883820709,
+           -1.7725392908176638,
+           -1.6406029736447154,
+           -1.5143331597267464,
+           -1.3959265440655755,
+           -1.287372614589696,
+           -1.1904120111453418,
+           -1.1065007728106526,
+           -1.036781280891096,
+           -0.9820605430327702,
+           -0.9427962867806974,
+           -0.919091142953016,
+           -0.910695004999239,
+           -0.917015454810282,
+           -0.9371359530275516,
+           -0.9698413074490405,
+           -1.0136497611392794,
+           -1.0668508864913988,
+           -1.1275483365209142,
+           -1.1937063933421734,
+           -1.263199168750701,
+           -1.333861255117385,
+           -1.403538597700376,
+           -1.4701383625719509,
+           -1.531676607469251,
+           -1.5863226250961544,
+           -1.6324389181001457,
+           -1.6686158798161632,
+           -1.6937003919873939,
+           -1.7068177065722931,
+           -1.707386149504166,
+           -1.6951243655993307,
+           -1.6700510111763036,
+           -1.6324769896746905,
+           -1.5829905109496518,
+           -1.5224354323598235,
+           -1.4518835048659535,
+           -1.3726012960336802,
+           -1.2860126904245215,
+           -1.1936579732109152,
+           -1.0971505823975565,
+           -0.9981326668552819,
+           -0.8982306102557561,
+           -0.7990116744418502,
+           -0.7019428800238623,
+           -0.6083531780314322,
+           -0.5193998759556956,
+           -0.43604016683002195,
+           -0.3590084740680442,
+           -0.28880017108148776,
+           -0.22566206715659795,
+           -0.1695898739386104,
+           -0.12033268465799993,
+           -0.07740431555234076,
+           -0.04010118042403373,
+           -0.00752619944897336,
+           0.021381913484677828,
+           0.04781478050372569,
+           0.07305682151085006,
+           0.09844505878913508,
+           0.1253273451408975,
+           0.15502013839227802,
+           0.18876695841656466,
+           0.22769864697782424,
+           0.2727965060536899,
+           0.3248593179691442,
+           0.3844751524670462,
+           0.4519987442146739,
+           0.527535082248971,
+           0.6109296940629441,
+           0.7017659354250861,
+           0.7993694169232122,
+           0.9028195141732162,
+           1.010967725277877,
+           1.122462461095668,
+           1.2357796856934908,
+           1.3492586702796179,
+           1.461141987867101,
+           1.5696187613815702,
+           1.6728700878464013,
+           1.7691154979925017,
+           1.8566592758224654,
+           1.9339354572747722,
+           1.9995503514147002,
+           2.0523214810156465,
+           2.09131192074982,
+           2.115859118544428,
+           2.125597416389569,
+           2.120473637830325,
+           2.100755276850494,
+           2.0670310027524774,
+           2.0202033835318938,
+           1.9614739215035266,
+           1.8923206848294507,
+           1.8144690024266314,
+           1.7298558629259009,
+           1.6405888166051612,
+           1.5489003185774537,
+           1.457098568485621,
+           1.3675159935951708,
+           1.2824565861569914,
+           1.2041433405842656,
+           1.134667040422152,
+           1.075937619098701,
+           1.0296392625930166,
+           0.9971903377389508,
+           0.9797091189026333,
+           0.9779861508866766,
+           0.9924639303723979,
+           1.0232244157730765,
+           1.0699846902154497,
+           1.1321009089883307,
+           1.2085804658978665,
+           1.298102117339876,
+           1.3990436133049078,
+           1.509516205590322
+          ],
+          [
+           1.5916628735366491,
+           1.7142369901897867,
+           1.8403695960982223,
+           1.9675782550000742,
+           2.0933363884568976,
+           2.215128164353509,
+           2.3305030532774866,
+           2.4371287864036244,
+           2.5328414881824757,
+           2.6156918262887614,
+           2.6839861182188063,
+           2.7363214562506597,
+           2.77161405719101,
+           2.7891202068781396,
+           2.7884493477808654,
+           2.76956904686137,
+           2.7328017755355205,
+           2.6788136293108207,
+           2.6085953067325693,
+           2.5234358509437538,
+           2.4248898279971485,
+           2.314738769905164,
+           2.1949478435548206,
+           2.067618815848093,
+           1.934940468142374,
+           1.799137667310106,
+           1.6624203252642158,
+           1.526933473095196,
+           1.3947096402715697,
+           1.2676246646426257,
+           1.14735796694025,
+           1.0353582064660654,
+           0.9328150956444845,
+           0.8406379936323106,
+           0.7594417271620801,
+           0.6895399045710415,
+           0.6309458010856854,
+           0.5833807045780245,
+           0.546289425883245,
+           0.5188625009637328,
+           0.5000644481000519,
+           0.48866729593680513,
+           0.4832884712361382,
+           0.4824320317034632,
+           0.4845321517656795,
+           0.4879977195639519,
+           0.49125688283316205,
+           0.49280039021207833,
+           0.49122261255804034,
+           0.4852591949931769,
+           0.47382038294904566,
+           0.45601918200706854,
+           0.43119364885910405,
+           0.3989227657189729,
+           0.35903551905031944,
+           0.31161298125250303,
+           0.25698337645008584,
+           0.1957102941346819,
+           0.12857439248352803,
+           0.05654910221796909,
+           -0.019229002411767004,
+           -0.09749436046273731,
+           -0.1768901861990448,
+           -0.2560088193358751,
+           -0.33343357907140553,
+           -0.4077809973616937,
+           -0.4777422957760119,
+           -0.542122988318053,
+           -0.5998795393720084,
+           -0.6501520802676487,
+           -0.6922922879960509,
+           -0.7258856528395945,
+           -0.7507675050121682,
+           -0.7670323302348186,
+           -0.7750360764762705,
+           -0.7753913345256651,
+           -0.7689554590856852,
+           -0.7568118800303636,
+           -0.7402450307358693,
+           -0.7207094874726518,
+           -0.6997940664998847,
+           -0.6791817598395083,
+           -0.6606065032905248,
+           -0.645807858177139,
+           -0.6364847493205809,
+           -0.6342494341681457,
+           -0.6405828809986679,
+           -0.6567927074809159,
+           -0.6839747751593712,
+           -0.7229794519765558,
+           -0.7743834457040778,
+           -0.838467978784379,
+           -0.9152039228025305,
+           -1.0042443423363026,
+           -1.1049247174080907,
+           -1.216270925628201,
+           -1.3370148740190202,
+           -1.4656174811707174,
+           -1.600298527496279,
+           -1.7390727194713558,
+           -1.8797911571454977,
+           -2.020187256809127,
+           -2.157926065942792,
+           -2.29065581835625,
+           -2.4160605160156883,
+           -2.5319122920457486,
+           -2.6361223076461044,
+           -2.7267889643028136,
+           -2.802242271076331,
+           -2.861083293552999,
+           -2.90221772419406,
+           -2.9248827505964283,
+           -2.92866655529696,
+           -2.913519954408573,
+           -2.879759868362865,
+           -2.828064511833558,
+           -2.7594603868153498,
+           -2.6753013580411023,
+           -2.5772402786808946,
+           -2.4671938119796746,
+           -2.347301256822715,
+           -2.2198783282127477,
+           -2.087366963813564,
+           -1.9522823221341707,
+           -1.817158204298517,
+           -1.6844921680560578,
+           -1.5566916088547826,
+           -1.436022058282149,
+           -1.3245588955963938,
+           -1.2241435847694233,
+           -1.1363454394959873,
+           -1.062429784695732,
+           -1.003333228432835,
+           -0.9596465866951431,
+           -0.9316058193116985,
+           -0.9190911429530155,
+           -0.921634291354441,
+           -0.9384336984116379,
+           -0.9683771913610489,
+           -1.0100716034644954,
+           -1.0618785527840946,
+           -1.121955489705453,
+           -1.1883009943154192,
+           -1.2588032084815663,
+           -1.3312902188009796,
+           -1.4035811670905,
+           -1.4735368556605897,
+           -1.5391086353890158,
+           -1.5983844149823092,
+           -1.6496307084451685,
+           -1.6913297426403153,
+           -1.7222107752369293,
+           -1.741274922063755,
+           -1.7478129581544979,
+           -1.7414157344501415,
+           -1.7219770377571215,
+           -1.689688910518091,
+           -1.6450296345262376,
+           -1.5887447642437726,
+           -1.5218217663695526,
+           -1.4454589785119418,
+           -1.3610297374103624,
+           -1.2700426427344098,
+           -1.1740990132510372,
+           -1.0748486558919894,
+           -0.9739451034582972,
+           -0.8730014825661168,
+           -0.7735481499038144,
+           -0.6769931826048777,
+           -0.5845867289355852,
+           -0.4973901206229694,
+           -0.4162505207113138,
+           -0.34178173409998724,
+           -0.2743516456277847,
+           -0.21407657686121576,
+           -0.1608226720300503,
+           -0.1142142404189726,
+           -0.07364880161122081,
+           -0.03831840587116518,
+           -0.007236639055659641,
+           0.020729426118227135,
+           0.04682319911425701,
+           0.07235943376200768,
+           0.0986830375782983,
+           0.12712693630282484,
+           0.15897012736155935,
+           0.19539705249729072,
+           0.23745938729524527,
+           0.2860412845876753,
+           0.34182902126091264,
+           0.4052858860019545,
+           0.4766330118192067,
+           0.5558367051125422,
+           0.642602656476129,
+           0.7363772414883454,
+           0.83635593693643,
+           0.9414986938528102,
+           1.0505519280577715,
+           1.162076616182859,
+           1.2744818247727736,
+           1.3860628561094133,
+           1.4950430705445346,
+           1.5996183445443166,
+           1.6980030489397695,
+           1.788476384999237,
+           1.869427898157432,
+           1.9394010010894103,
+           1.997133379107972,
+           2.0415932206536285,
+           2.0720103122885942,
+           2.087901158778468,
+           2.089087431608266,
+           2.0757072101504765,
+           2.0482186547399883,
+           2.00739593581146,
+           1.9543174334606792,
+           1.8903464126033478,
+           1.8171045655963658,
+           1.7364389921242454,
+           1.6503833509095103,
+           1.5611140652691498,
+           1.4709025910186193,
+           1.3820648575379753,
+           1.29690906837238,
+           1.217683094604291,
+           1.1465227111771292,
+           1.0854019128725831,
+           1.0360865029988489,
+           1.0000920750301585,
+           0.9786474071630145,
+           0.9726641644148164,
+           0.9827136554970566,
+           1.0090112258063717,
+           1.0514086875082065,
+           1.1093949972163373,
+           1.1821051958254785,
+           1.2683374284013813,
+           1.3665776694617544,
+           1.4750315951844062,
+           1.5916628735366465
+          ],
+          [
+           1.677264258347511,
+           1.8034805781935177,
+           1.931650462796957,
+           2.059255227501695,
+           2.183765886744877,
+           2.302698020260316,
+           2.413665544684126,
+           2.5144321437267583,
+           2.602959167342372,
+           2.6774488961629177,
+           2.736382179759525,
+           2.7785495932899735,
+           2.803075413452222,
+           2.809433887558224,
+           2.7974574547361803,
+           2.7673367712325536,
+           2.719612587802265,
+           2.655159721461818,
+           2.575163551700302,
+           2.4810896480271256,
+           2.3746472971910326,
+           2.257747840623756,
+           2.132458852214478,
+           2.0009552805422697,
+           1.8654687459506363,
+           1.7282362197965428,
+           1.5914493200263182,
+           1.4572054338472382,
+           1.3274618253461552,
+           1.2039938048523975,
+           1.088357929740524,
+           0.9818610759473541,
+           0.88553606903613,
+           0.8001243969653263,
+           0.7260663479911074,
+           0.6634987308201485,
+           0.6122601448810879,
+           0.5719035811077785,
+           0.5417159525809307,
+           0.5207439842408564,
+           0.507825735866026,
+           0.5016268964270028,
+           0.5006808741100949,
+           0.5034316175341926,
+           0.5082780421013166,
+           0.5136189024864889,
+           0.5178969487270112,
+           0.5196412292195989,
+           0.5175064584454896,
+           0.5103084489707981,
+           0.49705471408526575,
+           0.4769694765943083,
+           0.4495124674580159,
+           0.41439106139470994,
+           0.3715654710759822,
+           0.32124690270176837,
+           0.2638887589622644,
+           0.2001711560259158,
+           0.13097919466572655,
+           0.05737558756012108,
+           -0.01943160891662061,
+           -0.09812528316559536,
+           -0.17731859746997242,
+           -0.2555962989316787,
+           -0.331556901458248,
+           -0.4038546045715458,
+           -0.4712398204899208,
+           -0.5325972156118013,
+           -0.586980235339553,
+           -0.6336411705558682,
+           -0.6720559377592167,
+           -0.7019428800238616,
+           -0.7232750491746521,
+           -0.7362855969999034,
+           -0.7414660807485344,
+           -0.7395576710947476,
+           -0.7315354345855092,
+           -0.7185860426642788,
+           -0.7020794311278642,
+           -0.6835350929626913,
+           -0.6645838298737954,
+           -0.6469259098289323,
+           -0.6322866764594577,
+           -0.6223707286405191,
+           -0.6188158331138258,
+           -0.6231477484112401,
+           -0.6367371241071892,
+           -0.6607595958331683,
+           -0.696160124522871,
+           -0.7436225297270076,
+           -0.8035450439168103,
+           -0.8760225704698027,
+           -0.9608361660231115,
+           -1.0574500920620933,
+           -1.1650165953110982,
+           -1.282388386280498,
+           -1.4081385949039875,
+           -1.5405877962920476,
+           -1.6778375228506361,
+           -1.8178095157708423,
+           -1.9582898232631143,
+           -2.096976728538748,
+           -2.2315313905644483,
+           -2.3596300075686183,
+           -2.479016269037763,
+           -2.587552847676581,
+           -2.683270698949036,
+           -2.764414982053884,
+           -2.8294864914587503,
+           -2.8772775906488364,
+           -2.9069017670916093,
+           -2.9178160765172514,
+           -2.9098359118661565,
+           -2.8831417136094264,
+           -2.838277429204827,
+           -2.776140725564966,
+           -2.697965154813391,
+           -2.605294665504168,
+           -2.499951034202966,
+           -2.3839949614174936,
+           -2.259681727196861,
+           -2.129412431602254,
+           -1.9956819505170798,
+           -1.8610248153477589,
+           -1.7279602741666642,
+           -1.5989378105765475,
+           -1.4762843845851086,
+           -1.3621546173719645,
+           -1.2584850700587098,
+           -1.1669536672218652,
+           -1.0889451913611286,
+           -1.0255236279076132,
+           -0.9774119752232355,
+           -0.944979954449193,
+           -0.9282398644030475,
+           -0.9268506316382984,
+           -0.9401299100316283,
+           -0.9670738926263607,
+           -1.0063843156029646,
+           -1.0565019646136296,
+           -1.115645841420689,
+           -1.1818570174985674,
+           -1.253046094152552,
+           -1.3270431083325775,
+           -1.4016486715697734,
+           -1.4746851075241065,
+           -1.5440463619513722,
+           -1.607745497178671,
+           -1.6639586503832475,
+           -1.7110644293503459,
+           -1.7476778385266645,
+           -1.7726779690626235,
+           -1.7852288455964236,
+           -1.7847929957783093,
+           -1.771137491627224,
+           -1.7443324001804033,
+           -1.7047417698469725,
+           -1.6530074637118535,
+           -1.5900263271726138,
+           -1.5169213403719475,
+           -1.4350075518897718,
+           -1.3457537154934087,
+           -1.2507406533466092,
+           -1.1516174444817933,
+           -1.0500565847375434,
+           -0.9477092826507947,
+           -0.8461620445964727,
+           -0.7468956621510358,
+           -0.6512476463126731,
+           -0.5603790586334106,
+           -0.47524657095416456,
+           -0.396580446323574,
+           -0.3248689773816573,
+           -0.2603497489832958,
+           -0.20300791343444488,
+           -0.15258148394399268,
+           -0.1085734693903769,
+           -0.07027049588663158,
+           -0.03676739239630713,
+           -0.006997063061834347,
+           0.020235168133202967,
+           0.04621367076955468,
+           0.07227210193744686,
+           0.09975156897902458,
+           0.12995848711797484,
+           0.16412326698009594,
+           0.20336094676811822,
+           0.24863483495765348,
+           0.3007241530497046,
+           0.360196566061347,
+           0.4273863636168795,
+           0.5023789098545223,
+           0.5850018195278787,
+           0.6748231447076526,
+           0.77115667573832,
+           0.873074276138222,
+           0.9794249885983406,
+           1.088860472754503,
+           1.1998661694536632,
+           1.310797435024571,
+           1.4199197564504475,
+           1.525452047720869,
+           1.625611941860974,
+           1.718661934430467,
+           1.8029552042118324,
+           1.876979936211499,
+           1.93940100108941,
+           1.989097903082313,
+           2.0251979940398726,
+           2.0471040623044767,
+           2.054515539147661,
+           2.047442719064167,
+           2.0262135596593307,
+           1.9914728079840378,
+           1.94417338851147,
+           1.8855601788585927,
+           1.8171464881066781,
+           1.7406837344847084,
+           1.6581249897227794,
+           1.5715832123065,
+           1.4832851272912981,
+           1.3955218228665225,
+           1.310597220648715,
+           1.2307756355196022,
+           1.1582296701779646,
+           1.0949896886434816,
+           1.042896081675172,
+           1.003555476136692,
+           0.9783019511754075,
+           0.9681642087983552,
+           0.9738395077891762,
+           0.9956750112555794,
+           1.0336570232640907,
+           1.0874084032461242,
+           1.1561942526836753,
+           1.2389357717270162,
+           1.3342319886542766,
+           1.4403888771989561,
+           1.5554552003273718,
+           1.6772642583475081
+          ],
+          [
+           1.7655961335723434,
+           1.8943809624396009,
+           2.023486213581046,
+           2.1503782752779235,
+           2.2725471713954377,
+           2.387560941082847,
+           2.4931181706535885,
+           2.587097460897297,
+           2.6676026874507457,
+           2.733003013644773,
+           2.7819667419512983,
+           2.813488238671712,
+           2.826907333197091,
+           2.82192077395126,
+           2.7985855135779834,
+           2.7573137913995502,
+           2.6988601768839597,
+           2.6243009290404085,
+           2.5350062086636207,
+           2.432605848744824,
+           2.318949539079581,
+           2.196062410490017,
+           2.06609710903133,
+           1.931283528566107,
+           1.793877419328852,
+           1.656109109442705,
+           1.5201335654051338,
+           1.3879829766907537,
+           1.2615229799264371,
+           1.1424135413841738,
+           1.0320753952820398,
+           0.931662792655385,
+           0.8420431549555724,
+           0.7637840520831369,
+           0.6971477406306434,
+           0.6420933092876651,
+           0.5982862893464233,
+           0.5651154037363508,
+           0.5417159525809307,
+           0.5269991712464825,
+           0.5196867522325025,
+           0.5183495985868555,
+           0.5214497768367756,
+           0.5273845641241278,
+           0.5345314390727735,
+           0.5412928499429964,
+           0.5461396071567339,
+           0.5476517898835784,
+           0.5445561269098189,
+           0.5357589086224678,
+           0.5203736071284315,
+           0.49774252220922344,
+           0.46745192838862526,
+           0.42934036884935767,
+           0.38349992094258645,
+           0.33027044104823494,
+           0.2702269789266561,
+           0.20416072883561467,
+           0.13305405208930368,
+           0.058050259175323984,
+           -0.01958102485765209,
+           -0.09848197370163239,
+           -0.177247123573348,
+           -0.2544652955467851,
+           -0.3287617488285103,
+           -0.3988394306600429,
+           -0.46351821096079454,
+           -0.5217710408366965,
+           -0.5727560523962334,
+           -0.6158437209712734,
+           -0.6506383372291374,
+           -0.6769931826048771,
+           -0.6950189633033984,
+           -0.705085231741516,
+           -0.7078147053403625,
+           -0.7040705764672353,
+           -0.6949370894137809,
+           -0.6816938359740549,
+           -0.6657843859957878,
+           -0.6487800190308083,
+           -0.6323394540877149,
+           -0.6181655831393174,
+           -0.6079602976591196,
+           -0.6033785538766633,
+           -0.6059828501499823,
+           -0.6171992880693653,
+           -0.6382763575809068,
+           -0.670247526240401,
+           -0.7138986250895559,
+           -0.76974091068729,
+           -0.8379905472657473,
+           -0.9185550981201461,
+           -1.0110274449783951,
+           -1.1146873724199065,
+           -1.2285108659035509,
+           -1.3511869812827673,
+           -1.4811419555564065,
+           -1.6165700476996896,
+           -1.7554704292441594,
+           -1.895689291052578,
+           -2.0349661993012758,
+           -2.17098362339515,
+           -2.301418474190481,
+           -2.4239944346433164,
+           -2.536533838304275,
+           -2.6370078546832176,
+           -2.723583774405169,
+           -2.7946682505193996,
+           -2.848945443826477,
+           -2.885409137479633,
+           -2.9033880265826646,
+           -2.9025635486618833,
+           -2.882979796860071,
+           -2.8450452452187953,
+           -2.78952620992578,
+           -2.7175321671736183,
+           -2.6304932425122844,
+           -2.530130373545543,
+           -2.418418822959947,
+           -2.2975458779108284,
+           -2.169863710840407,
+           -2.0378384924753044,
+           -1.9039969372205923,
+           -1.7708715222539013,
+           -1.6409456528379476,
+           -1.5166000469571976,
+           -1.4000615823376963,
+           -1.2933557889716891,
+           -1.1982640819153196,
+           -1.1162867145282054,
+           -1.0486122942888432,
+           -0.9960945452329493,
+           -0.9592368267939515,
+           -0.9381847326404475,
+           -0.9327268995563839,
+           -0.9423039602233779,
+           -0.9660253797274294,
+           -1.0026937284515585,
+           -1.050835768283794,
+           -1.1087395690311428,
+           -1.1744967314572239,
+           -1.2460486758398626,
+           -1.3212358631902015,
+           -1.3978487524635637,
+           -1.4736792627090975,
+           -1.5465715049072393,
+           -1.614470574243588,
+           -1.6754682490316453,
+           -1.7278445259678934,
+           -1.7701040307337548,
+           -1.8010064753701895,
+           -1.8195904859968188,
+           -1.8251902925029364,
+           -1.8174449515917719,
+           -1.7962999615204467,
+           -1.7620013163871595,
+           -1.7150822351615294,
+           -1.6563429811866188,
+           -1.5868243571338836,
+           -1.507775614188416,
+           -1.4206176487979918,
+           -1.3269024723407155,
+           -1.2282700258255888,
+           -1.1264034711479969,
+           -1.0229841210747248,
+           -0.9196471713486476,
+           -0.8179393701370312,
+           -0.7192797032902908,
+           -0.6249240900342683,
+           -0.5359349749697588,
+           -0.45315657139954985,
+           -0.3771963613969329,
+           -0.3084132934879999,
+           -0.24691294352956392,
+           -0.19254972277750312,
+           -0.14493603386082576,
+           -0.10345809504759233,
+           -0.06729798037370383,
+           -0.03546126227529847,
+           -0.006809498388814599,
+           0.019903321175812897,
+           0.0459913523552296,
+           0.07279556490392146,
+           0.10164161273214803,
+           0.13379804138515985,
+           0.17043595935489275,
+           0.21259126307981355,
+           0.26113044062087815,
+           0.31672088772851525,
+           0.3798065546300267,
+           0.4505896052706187,
+           0.5290186163730903,
+           0.6147836754296618,
+           0.7073185588471387,
+           0.8058099884233847,
+           0.9092137807637029,
+           1.016277524794416,
+           1.1255692517451226,
+           1.2355114041874415,
+           1.3444192699531514,
+           1.4505429266054137,
+           1.5521116456889756,
+           1.647379635736006,
+           1.7346719607989893,
+           1.812429458268009,
+           1.8792514963253932,
+           1.9339354572747722,
+           1.9755119071009948,
+           2.003274512210454,
+           2.016803888942539,
+           2.0159847171012486,
+           2.001015611869843,
+           1.9724114250361766,
+           1.9309978321239865,
+           1.8778982522111936,
+           1.814513337212576,
+           1.7424934524980966,
+           1.6637047463065036,
+           1.58018956712004,
+           1.4941221319469158,
+           1.407760470704895,
+           1.323395769529916,
+           1.243300306365398,
+           1.1696752138044868,
+           1.10459931575164,
+           1.049980265672917,
+           1.0075091653959538,
+           0.9786197657199407,
+           0.9644532453367183,
+           0.9658294352468392,
+           0.9832252050889179,
+           1.0167605592274471,
+           1.0661928081467122,
+           1.1309189891016334,
+           1.2099865137393055,
+           1.3021118243046879,
+           1.4057066488591843,
+           1.5189112643340785,
+           1.639634008642199,
+           1.7655961335723387
+          ],
+          [
+           1.8559111715761096,
+           1.9861690845444155,
+           2.1150998764426987,
+           2.2401764561109183,
+           2.358929112566442,
+           2.4689989481100283,
+           2.5681887260174436,
+           2.6545099564505437,
+           2.726225135075948,
+           2.7818841657619036,
+           2.8203541387707323,
+           2.8408417956460243,
+           2.8429081876005093,
+           2.8264752213479807,
+           2.79182398041802,
+           2.7395849063071958,
+           2.670720117567548,
+           2.5864983313942416,
+           2.488463026916023,
+           2.378394647977951,
+           2.258267781899943,
+           2.130204366155857,
+           1.9964240643817408,
+           1.859193014468155,
+           1.7207721832956857,
+           1.5833665642400756,
+           1.4490764249555086,
+           1.3198517549368098,
+           1.1974509764823418,
+           1.0834048711322901,
+           0.9789865392744608,
+           0.8851880567817897,
+           0.8027043231367009,
+           0.7319244147476396,
+           0.6729305695847803,
+           0.6255047395258201,
+           0.5891424596227574,
+           0.5630736035159893,
+           0.5462894258832446,
+           0.5375751402680388,
+           0.5355471476338496,
+           0.5386939207889795,
+           0.5454194651010768,
+           0.5540882187062831,
+           0.5630702270618739,
+           0.5707854278153847,
+           0.5757459124520627,
+           0.5765950901858767,
+           0.5721427655157023,
+           0.5613952515430686,
+           0.5435797736914757,
+           0.5181625694860017,
+           0.4848602556937586,
+           0.44364421017720923,
+           0.3947378978038591,
+           0.33860725307429296,
+           0.275944412134285,
+           0.2076452589725059,
+           0.13478141052157222,
+           0.05856740903642079,
+           -0.019675986108388846,
+           -0.0985614143075092,
+           -0.1766763692106793,
+           -0.2526253779816157,
+           -0.3250717694382613,
+           -0.3927779062678683,
+           -0.45464279549931874,
+           -0.5097360583302358,
+           -0.557327333566268,
+           -0.596910305990788,
+           -0.6282206889978755,
+           -0.6512476463126724,
+           -0.6662383066709057,
+           -0.6736952036680725,
+           -0.674366656115129,
+           -0.6692302875217743,
+           -0.6594700621315933,
+           -0.646447384722209,
+           -0.6316669678451526,
+           -0.6167383093293208,
+           -0.6033337411515438,
+           -0.5931441051486576,
+           -0.5878331790619731,
+           -0.5889920162781308,
+           -0.5980943732719165,
+           -0.6164543798087229,
+           -0.6451875588081212,
+           -0.6851762265180312,
+           -0.737040201117866,
+           -0.801113621535777,
+           -0.8774285312057839,
+           -0.9657057173052939,
+           -1.0653531187366074,
+           -1.1754719301177434,
+           -1.2948703389247513,
+           -1.4220846433895624,
+           -1.5554073145107599,
+           -1.692921391164366,
+           -1.8325404371594605,
+           -1.9720531471766798,
+           -2.1091715684222425,
+           -2.241581809559344,
+           -2.3669960404691412,
+           -2.483204547402057,
+           -2.588126599152227,
+           -2.6798589013277363,
+           -2.756720467154272,
+           -2.8172928133583817,
+           -2.8604544966372027,
+           -2.885409137479633,
+           -2.8917062305019186,
+           -2.8792542103178316,
+           -2.8483254251641843,
+           -2.7995528625981168,
+           -2.7339186679010035,
+           -2.6527346915841874,
+           -2.5576154928214856,
+           -2.4504444060874278,
+           -2.333333444352708,
+           -2.2085779598248023,
+           -2.078607108814854,
+           -1.9459312677945932,
+           -1.8130876206245417,
+           -1.6825851805070027,
+           -1.556850523383384,
+           -1.438175491936491,
+           -1.3286680815107788,
+           -1.2302076423014212,
+           -1.1444054279762244,
+           -1.0725713920352948,
+           -1.015687982839207,
+           -0.9743915200279829,
+           -0.9489615531250435,
+           -0.939318411920282,
+           -0.9450289624239034,
+           -0.9653203865557136,
+           -0.9991016130503816,
+           -1.0449918459579872,
+           -1.10135546999934,
+           -1.1663424629458772,
+           -1.2379333177336516,
+           -1.313987374252714,
+           -1.3922933851260781,
+           -1.4706210930852486,
+           -1.546772580823691,
+           -1.6186321677890623,
+           -1.6842136718339256,
+           -1.741703925822359,
+           -1.7895015383201125,
+           -1.8262500108519606,
+           -1.8508644687717117,
+           -1.862551424918085,
+           -1.8608211708597033,
+           -1.8454925752735254,
+           -1.8166902582483653,
+           -1.7748342993510013,
+           -1.7206228214460864,
+           -1.6550079669633582,
+           -1.5791659442430188,
+           -1.494461964800959,
+           -1.4024110143282629,
+           -1.3046354979996393,
+           -1.2028208718482567,
+           -1.0986704148735054,
+           -0.993860310196551,
+           -0.8899961877117292,
+           -0.7885722357846252,
+           -0.6909339168299057,
+           -0.598245222967324,
+           -0.5114612859535038,
+           -0.4313070133511961,
+           -0.3582622640612685,
+           -0.29255390495104094,
+           -0.23415491072095146,
+           -0.1827904859157335,
+           -0.13795100574785873,
+           -0.09891139577229333,
+           -0.06475640389875559,
+           -0.03441106595999357,
+           -0.006675531918608163,
+           0.019736692821478958,
+           0.0461581247856672,
+           0.07392539392786546,
+           0.10433717821226207,
+           0.1386131147378615,
+           0.17785479625193307,
+           0.2230099087796117,
+           0.27484048580667936,
+           0.3338961490101195,
+           0.4004930775900399,
+           0.47469930103919494,
+           0.556326747403159,
+           0.6449303048405188,
+           0.7398139729866249,
+           0.8400439968374126,
+           0.9444686942504286,
+           1.051744513308855,
+           1.1603676921484576,
+           1.268710745568693,
+           1.3750628736209651,
+           1.4776732806976582,
+           1.574796312186433,
+           1.6647372616292366,
+           1.74589767597764,
+           1.8168189906913028,
+           1.876223360072658,
+           1.9230506106193548,
+           1.9564903348377518,
+           1.976008257742143,
+           1.9813661453804092,
+           1.9726346808291397,
+           1.9501989043606622,
+           1.9147559966856684,
+           1.8673053728208489,
+           1.8091312445535725,
+           1.7417779969520326,
+           1.6670189042397539,
+           1.586818878135128,
+           1.5032920932574279,
+           1.418655465622155,
+           1.3351790682799582,
+           1.25513465005744,
+           1.180743477035062,
+           1.1141247404430132,
+           1.057245768391776,
+           1.0118752423507618,
+           0.9795405533594207,
+           0.9614903391422591,
+           0.9586631238320967,
+           0.9716628397492098,
+           1.0007418490678057,
+           1.045791906135499,
+           1.1063433129915188,
+           1.1815723258296211,
+           1.270316673513422,
+           1.3710988555661976,
+           1.4821567010481187,
+           1.6014804959401545,
+           1.7268558293191982,
+           1.8559111715761065
+          ],
+          [
+           1.947445266269284,
+           2.0780683754603633,
+           2.205716358338458,
+           2.327890036756698,
+           2.4421808799473155,
+           2.5463230389512974,
+           2.638242079907506,
+           2.71609929016962,
+           2.7783305377841154,
+           2.8236787958484277,
+           2.851219595470242,
+           2.8603788407432864,
+           2.850942602193755,
+           2.823058697062499,
+           2.7772300608864517,
+           2.7143001103457847,
+           2.6354304874883665,
+           2.542071755605271,
+           2.4359277828361194,
+           2.318914697015837,
+           2.193115420776661,
+           2.060730896477444,
+           1.9240291837508534,
+           1.7852936566190059,
+           1.646771541228475,
+           1.5106240190374465,
+           1.3788790742393635,
+           1.2533881895511687,
+           1.1357878931559084,
+           1.0274670341487961,
+           0.9295405174625838,
+           0.8428300656221173,
+           0.7678523978977279,
+           0.7048150319073426,
+           0.6536197230789567,
+           0.6138733683412121,
+           0.5849060166471812,
+           0.5657954550004834,
+           0.5553976788342154,
+           0.5523824138219234,
+           0.5552727359480617,
+           0.5624877408616374,
+           0.5723871444938748,
+           0.583316656279356,
+           0.5936529550082814,
+           0.6018471155493145,
+           0.6064653818731978,
+           0.6062262567089433,
+           0.6000329788174419,
+           0.5870005826709146,
+           0.5664768791043683,
+           0.5380568555845047,
+           0.5015901670470593,
+           0.4571815684080711,
+           0.4051843232903132,
+           0.3461868055777527,
+           0.28099268651304654,
+           0.21059526573486403,
+           0.13614665572855664,
+           0.058922661821573664,
+           -0.019715689253679183,
+           -0.09836293287975278,
+           -0.17561116322214385,
+           -0.2500921127713437,
+           -0.3205181821828769,
+           -0.38572131463425086,
+           -0.4446886641364675,
+           -0.4965940894903158,
+           -0.5408246127925308,
+           -0.5770011108726146,
+           -0.604992656513565,
+           -0.6249240900342677,
+           -0.637176576655676,
+           -0.6423810866212192,
+           -0.6414049187046943,
+           -0.6353315688682486,
+           -0.6254344198387665,
+           -0.6131448898355274,
+           -0.6000158254718212,
+           -0.5876810512213375,
+           -0.5778120925219523,
+           -0.5720731688830979,
+           -0.5720756051989753,
+           -0.5793328324629878,
+           -0.5952171425635921,
+           -0.6209193258902721,
+           -0.6574122558990974,
+           -0.7054193931063963,
+           -0.765389064402923,
+           -0.8374752349423767,
+           -0.9215253325469025,
+           -1.0170755124510489,
+           -1.1233535675151058,
+           -1.2392895002921633,
+           -1.3635335832049362,
+           -1.4944815462979126,
+           -1.6303063532248363,
+           -1.768995859771,
+           -1.9083954994550105,
+           -2.046255011365298,
+           -2.1802781196249392,
+           -2.308173994430338,
+           -2.427709273515533,
+           -2.53675940149802,
+           -2.633358053478862,
+           -2.7157434483652056,
+           -2.7824004257811623,
+           -2.832097256531481,
+           -2.8639162780962444,
+           -2.877277590648837,
+           -2.8719552121302874,
+           -2.848085269035078,
+           -2.8061659884443264,
+           -2.747049451889893,
+           -2.671925268098727,
+           -2.5822965147613424,
+           -2.4799484844809365,
+           -2.366910942472829,
+           -2.245414759185827,
+           -2.1178439160048654,
+           -1.986683993267408,
+           -1.8544683342694124,
+           -1.7237231346842516,
+           -1.5969127325082664,
+           -1.4763863686516256,
+           -1.3643276527374186,
+           -1.262707903427268,
+           -1.1732444392568442,
+           -1.0973647768250674,
+           -1.0361775511528266,
+           -0.9904508115855046,
+           -0.9605981697066752,
+           -0.9466730876813644,
+           -0.9483714008489936,
+           -0.9650419719870001,
+           -0.9957051812534818,
+           -1.039078770099411,
+           -1.0936103839314315,
+           -1.157516001212671,
+           -1.2288232998097075,
+           -1.305418898024701,
+           -1.385098320605937,
+           -1.4656174811707205,
+           -1.5447444432661244,
+           -1.6203102233672118,
+           -1.6902574303537845,
+           -1.7526855965576587,
+           -1.8058921437531879,
+           -1.8484080412152886,
+           -1.8790273493068246,
+           -1.8968299975460545,
+           -1.9011973168431147,
+           -1.89182002731267,
+           -1.868698571235528,
+           -1.8321358706739468,
+           -1.782722776229068,
+           -1.7213166528335324,
+           -1.6490137158665006,
+           -1.5671158821385445,
+           -1.477093031707889,
+           -1.3805416848467957,
+           -1.2791411811490268,
+           -1.1746085027731263,
+           -1.0686529098637518,
+           -0.9629315527217255,
+           -0.8590071924788217,
+           -0.7583091007846556,
+           -0.6620981209499497,
+           -0.5714367603995514,
+           -0.4871650500681864,
+           -0.40988275395723,
+           -0.3399383453478171,
+           -0.2774249893742534,
+           -0.222183589288095,
+           -0.17381277040909157,
+           -0.13168549610368857,
+           -0.09497183869775233,
+           -0.06266726934884136,
+           -0.03362568858643915,
+           -0.006596297068173467,
+           0.019736692821478958,
+           0.04671257709064056,
+           0.07565203014448277,
+           0.10781545971564849,
+           0.14436296947667032,
+           0.18631701095400596,
+           0.23452873741040453,
+           0.2896489773289231,
+           0.3521046264121807,
+           0.4220811175963862,
+           0.49951147198664425,
+           0.5840722637991436,
+           0.6751866536341288,
+           0.7720344612181484,
+           0.8735690657781664,
+           0.9785407440772713,
+           1.0855258873698301,
+           1.1929613834122221,
+           1.2991833121464595,
+           1.402468987274594,
+           1.5010812836549352,
+           1.5933141246697504,
+           1.6775379661711936,
+           1.7522441053363136,
+           1.8160866640511264,
+           1.8679211468562391,
+           1.9068385518513125,
+           1.9321941174012918,
+           1.9436299154858554,
+           1.941090650964384,
+           1.9248321912543112,
+           1.8954225288769757,
+           1.853735065621031,
+           1.800934297101496,
+           1.7384541655408166,
+           1.6679695319686618,
+           1.5913613921625145,
+           1.510676619206564,
+           1.4280831555603242,
+           1.3458216954783584,
+           1.2661549915244619,
+           1.1913159844083394,
+           1.1234559917411295,
+           1.0645941975766784,
+           1.016569660536762,
+           0.9809970044170415,
+           0.9592268726793345,
+           0.9523121191036479,
+           0.9609805737095322,
+           0.9856150690637305,
+           1.026241240991412,
+           1.082523433648058,
+           1.1537688463592124,
+           1.2389398632804876,
+           1.3366743115546262,
+           1.445313204010084,
+           1.5629353431855177,
+           1.6873979989548182,
+           1.8163827262871188,
+           1.9474452662692792
+          ],
+          [
+           2.039423997791107,
+           2.169301325601386,
+           2.294569002827055,
+           2.4127769206321474,
+           2.521598125914156,
+           2.6188790168085836,
+           2.702685549250357,
+           2.771344388421768,
+           2.823478060290369,
+           2.858033302421526,
+           2.8743019763193693,
+           2.871934081721359,
+           2.8509426021937556,
+           2.8117001064362652,
+           2.7549272261463402,
+           2.6816733243306508,
+           2.593289852885627,
+           2.4913970706079294,
+           2.377844948361299,
+           2.2546692231586096,
+           2.1240436741666224,
+           1.9882297784453629,
+           1.8495249605878663,
+           1.7102106770259093,
+           1.5725015720447806,
+           1.4384969086836086,
+           1.310135414608425,
+           1.1891545923721036,
+           1.0770554275349498,
+           0.9750732898467385,
+           0.8841556655655234,
+           0.8049471869487878,
+           0.737782242296851,
+           0.6826852612082107,
+           0.6393785796128726,
+           0.6072976023973184,
+           0.5856128026442816,
+           0.5732579300946221,
+           0.5689636514923456,
+           0.5712957156735017,
+           0.5786966297720696,
+           0.5895297523201853,
+           0.6021246562444926,
+           0.6148225910354563,
+           0.626020879194727,
+           0.634215117210979,
+           0.6380381148081141,
+           0.6362945963757373,
+           0.6279908029900363,
+           0.61235826931812,
+           0.5888712034942553,
+           0.5572570658420718,
+           0.5175001198281051,
+           0.46983791136558434,
+           0.4147508159152705,
+           0.3529449721146476,
+           0.28532909137732604,
+           0.21298579073058582,
+           0.13713823711802528,
+           0.059113011931466466,
+           -0.019699798386948065,
+           -0.09788820866105585,
+           -0.17406051773241585,
+           -0.2468869324859638,
+           -0.31513951247105965,
+           -0.37772935771755517,
+           -0.43374003332786715,
+           -0.4824563213201307,
+           -0.5233875105603357,
+           -0.5562845764164668,
+           -0.5811507594418307,
+           -0.5982452229673234,
+           -0.6080796486442245,
+           -0.6114078122009756,
+           -0.6092083643229071,
+           -0.6026612190058162,
+           -0.5931181194704018,
+           -0.5820681054903064,
+           -0.5710987418625767,
+           -0.5618540822590146,
+           -0.5559904328950277,
+           -0.5551310439981548,
+           -0.5608208922753904,
+           -0.5744827234971411,
+           -0.597375500698764,
+           -0.6305563508497526,
+           -0.6748470223847058,
+           -0.7308057596560212,
+           -0.7987053707333253,
+           -0.8785181152038518,
+           -0.9699078723957221,
+           -1.0722298718453744,
+           -1.184538081271722,
+           -1.3056001574217038,
+           -1.433919676627023,
+           -1.5677651794492329,
+           -1.7052053919389123,
+           -1.844149829091081,
+           -1.9823938479789738,
+           -2.117667102270671,
+           -2.247684259310109,
+           -2.370196777990816,
+           -2.4830445119050255,
+           -2.5842058986317054,
+           -2.6718455227131055,
+           -2.7443578962897446,
+           -2.800406386215543,
+           -2.8389563277503664,
+           -2.8593014999659836,
+           -2.8610832935529995,
+           -2.8443020740206317,
+           -2.809320428160985,
+           -2.7568581746125096,
+           -2.687979215706786,
+           -2.6040705027336113,
+           -2.506813575554651,
+           -2.39814931552592,
+           -2.2802367136032498,
+           -2.155406599319485,
+           -2.0261113975193568,
+           -1.8948720753512953,
+           -1.7642235097048344,
+           -1.6366595433886786,
+           -1.514579005934987,
+           -1.400233951802158,
+           -1.295681315496133,
+           -1.2027391010410795,
+           -1.1229481143118656,
+           -1.0575401136567248,
+           -1.0074131002430713,
+           -0.9731142984164928,
+           -0.9548311922543088,
+           -0.9523907919161106,
+           -0.9652671070437202,
+           -0.99259660912878,
+           -1.0332012752042636,
+           -1.085618626036009,
+           -1.148138007540492,
+           -1.218842218416786,
+           -1.2956534634698649,
+           -1.3763825137835284,
+           -1.4587798841153137,
+           -1.5405877962920504,
+           -1.6195916859224542,
+           -1.6936700286075703,
+           -1.7608413104692997,
+           -1.8193070449477253,
+           -1.867489841454929,
+           -1.9040656589834322,
+           -1.9279895259329978,
+           -1.9385141725201478,
+           -1.9352012000387477,
+           -1.9179245975091013,
+           -1.886866606251108,
+           -1.842506121926852,
+           -1.785600006937392,
+           -1.7171578591963674,
+           -1.6384109419727557,
+           -1.550776119798583,
+           -1.4558157639427058,
+           -1.355194684776988,
+           -1.2506352152457436,
+           -1.143871608008823,
+           -1.0366049177941943,
+           -0.9304595199339082,
+           -0.826942366572283,
+           -0.7274060049534473,
+           -0.6330162795319138,
+           -0.5447255140552415,
+           -0.46325182446357394,
+           -0.3890650521467126,
+           -0.32237963390056246,
+           -0.263154544229333,
+           -0.21110026202740118,
+           -0.16569253179322616,
+           -0.12619251397508044,
+           -0.0916727542594909,
+           -0.06104825174759759,
+           -0.03311177480260279,
+           -0.006572464200199389,
+           0.019903321175812914,
+           0.047650018352757104,
+           0.07796086543006905,
+           0.11204702940684762,
+           0.15099895922865705,
+           0.1957510092955361,
+           0.24705029446964372,
+           0.3054306286484092,
+           0.37119226797644733,
+           0.44438803006191263,
+           0.5248161959191159,
+           0.6120204259373448,
+           0.7052967394085435,
+           0.8037074236313334,
+           0.9061015579921328,
+           1.0111416652849177,
+           1.117335841266539,
+           1.2230745681595114,
+           1.3266712922184996,
+           1.42640574279112,
+           1.5205688931799841,
+           1.6075084140659088,
+           1.685673449609067,
+           1.7536575552108429,
+           1.8102386741622376,
+           1.8544150971567412,
+           1.8854364423238625,
+           1.9028288117852898,
+           1.9064134208684522,
+           1.8963181546020917,
+           1.8729816790694391,
+           1.837149918341968,
+           1.789864896531357,
+           1.7324461342997681,
+           1.6664649752431158,
+           1.593712395274951,
+           1.5161610130539842,
+           1.4359221674861122,
+           1.355199055674079,
+           1.2762370281686164,
+           1.2012722153615087,
+           1.132479707372282,
+           1.0719225285320702,
+           1.0215026360109702,
+           0.9829151304652,
+           0.9576067957372376,
+           0.9467399862862992,
+           0.9511627574988261,
+           0.9713859882944031,
+           1.0075680810169454,
+           1.0595076444654514,
+           1.1266443764211629,
+           1.208068166777204,
+           1.3025362461282797,
+           1.4084980122179167,
+           1.5241269826661368,
+           1.6473591514061465,
+           1.775936872424433,
+           1.9074572614862288,
+           2.039423997791102
+          ],
+          [
+           2.1310691844520524,
+           2.2590960629259107,
+           2.3809060763298353,
+           2.494118926287927,
+           2.596508944629371,
+           2.686053025277259,
+           2.760973913134354,
+           2.819777852677083,
+           2.86128573412482,
+           2.8846570308099975,
+           2.889405993931235,
+           2.875409756012763,
+           2.8429081876005102,
+           2.7924955482857983,
+           2.725104168271735,
+           2.6419805856352703,
+           2.5446547425969235,
+           2.4349030071678506,
+           2.314705930554,
+           2.186201772186511,
+           2.0516369203014695,
+           1.913314404325297,
+           1.7735417343342836,
+           1.6345793116716583,
+           1.4985906332914414,
+           1.3675954611700452,
+           1.2434270485300303,
+           1.1276944086977845,
+           1.0217504828553623,
+           0.9266669130113521,
+           0.8432159599672079,
+           0.7718599270575758,
+           0.7127482634573541,
+           0.6657223305241942,
+           0.630327625704441,
+           0.6058330756495923,
+           0.591256837884698,
+           0.5853978928823003,
+           0.5868725695902741,
+           0.5941550307307419,
+           0.6056206523646896,
+           0.6195911675110342,
+           0.6343804075471423,
+           0.648339468509949,
+           0.6599001523359408,
+           0.6676155848596329,
+           0.670196991649358,
+           0.6665457174265988,
+           0.6557797021899257,
+           0.637253773981165,
+           0.6105732807432508,
+           0.5756007577917299,
+           0.5324555086370327,
+           0.4815061606612678,
+           0.4233564388222368,
+           0.35882457553797015,
+           0.2889169387797263,
+           0.21479660903648262,
+           0.1377477654627276,
+           0.059136848918035105,
+           -0.019628447952118742,
+           -0.09714125803312375,
+           -0.17203755190401349,
+           -0.24303695440105105,
+           -0.30898126628244743,
+           -0.36886965108969827,
+           -0.42188953344447083,
+           -0.46744236573581355,
+           -0.5051635526449463,
+           -0.5349359738781823,
+           -0.5568967110204809,
+           -0.5714367603995508,
+           -0.5791936958140381,
+           -0.5810374283245034,
+           -0.5780493903889441,
+           -0.5714956438778149,
+           -0.562794571550908,
+           -0.5534799553445114,
+           -0.5451603686298832,
+           -0.5394759102866097,
+           -0.538053383385627,
+           -0.5424610685367537,
+           -0.5541642602553681,
+           -0.5744827234971409,
+           -0.6045511869909398,
+           -0.6452839210952032,
+           -0.6973443522511559,
+           -0.7611205460184347,
+           -0.8367072490817167,
+           -0.9238950209810748,
+           -1.0221668125717724,
+           -1.1307021646501618,
+           -1.248389011333767,
+           -1.373842883341134,
+           -1.50543312099059,
+           -1.6413155301458406,
+           -1.7794707508932661,
+           -1.9177474625366024,
+           -2.0539094232182036,
+           -2.185685241289399,
+           -2.31081970103439,
+           -2.4271254194262273,
+           -2.532533594481364,
+           -2.625142619967577,
+           -2.703263385449458,
+           -2.765460153923727,
+           -2.8105860098843487,
+           -2.837811996168761,
+           -2.846649205357614,
+           -2.8369632572735566,
+           -2.8089807742345476,
+           -2.763287655790639,
+           -2.7008191500857914,
+           -2.622841914976492,
+           -2.5309284538252768,
+           -2.4269244937862213,
+           -2.312910043940342,
+           -2.1911550226754626,
+           -2.0640704745153076,
+           -1.9341565029841032,
+           -1.8039481254374525,
+           -1.675960306152925,
+           -1.5526334441169067,
+           -1.4362805813704107,
+           -1.3290375567408892,
+           -1.2328172592885174,
+           -1.1492690375565928,
+           -1.0797441971348654,
+           -1.0252683731424668,
+           -0.9865213995767871,
+           -0.9638251180784427,
+           -0.9571393789097172,
+           -0.9660662914641651,
+           -0.9898625851846596,
+           -1.027459749150408,
+           -1.0774914344860589,
+           -1.1383274326194261,
+           -1.2081133884154038,
+           -1.2848152740637078,
+           -1.36626754050079,
+           -1.4502237807094118,
+           -1.5344086854122665,
+           -1.616570047699687,
+           -1.6945295795126012,
+           -1.7662313393967433,
+           -1.8297866365702604,
+           -1.8835143694041965,
+           -1.9259758745317508,
+           -1.9560035029928655,
+           -1.9727222985605857,
+           -1.975564326711407,
+           -1.964275386266217,
+           -1.938914024972683,
+           -1.8998429705229034,
+           -1.847713274988889,
+           -1.7834416488022202,
+           -1.7081816258106373,
+           -1.6232893495470762,
+           -1.5302848990063576,
+           -1.4308101768187762,
+           -1.326584461209078,
+           -1.2193587736604286,
+           -1.1108702355936562,
+           -1.002797579179624,
+           -0.8967189399242462,
+           -0.7940729929287818,
+           -0.6961244024655425,
+           -0.6039344381138778,
+           -0.5183374731654441,
+           -0.4399239258491395,
+           -0.3690300350970783,
+           -0.3057346843637557,
+           -0.24986330393965545,
+           -0.20099869890275832,
+           -0.15849847096127737,
+           -0.12151853247644508,
+           -0.0890420542047093,
+           -0.05991304871654463,
+           -0.032873672551644396,
+           -0.006604234951533474,
+           0.02023516813320294,
+           0.048962517394742305,
+           0.08083236599334835,
+           0.11699608629146459,
+           0.1584649405177003,
+           0.20607697538162117,
+           0.26046864191853863,
+           0.3220519198536958,
+           0.39099758361802944,
+           0.46722508841316773,
+           0.550399383421623,
+           0.6399347797193857,
+           0.7350058172131424,
+           0.8345648926319853,
+           0.9373662338740608,
+           1.0419956393278658,
+           1.1469052483948476,
+           1.2504524752209918,
+           1.3509421250349505,
+           1.4466706243873684,
+           1.535971235277979,
+           1.6172590902636284,
+           1.6890748820716242,
+           1.7501260671756969,
+           1.799324497665342,
+           1.83581947826618,
+           1.8590253535681727,
+           1.868642861763211,
+           1.864673642275054,
+           1.8474274518725438,
+           1.8175218230702324,
+           1.7758740854094224,
+           1.7236858599487268,
+           1.662420325264215,
+           1.5937727347858701,
+           1.5196348358490661,
+           1.4420539961499805,
+           1.363187979462103,
+           1.285256426064161,
+           1.21049018146579,
+           1.1410796774372283,
+           1.0791236004767117,
+           1.0265790838257909,
+           0.9852146298558867,
+           0.9565669107303439,
+           0.9419025080609711,
+           0.9421855388895786,
+           0.958051978447062,
+           0.989791333070818,
+           1.0373361431938788,
+           1.1002596106633131,
+           1.1777814513139984,
+           1.2687818774240347,
+           1.3718234201964117,
+           1.4851801144950865,
+           1.6068733913032842,
+           1.7347138620902498,
+           1.866348037415148,
+           1.9993089031370468,
+           2.1310691844520493
+          ],
+          [
+           2.2216054665030547,
+           2.3466928833235943,
+           2.4639971281369997,
+           2.5712278635485157,
+           2.6662795566691027,
+           2.747276741849097,
+           2.8126140256252556,
+           2.860989913911575,
+           2.891433689258663,
+           2.9033247322243043,
+           2.896403861482197,
+           2.8707764578402313,
+           2.8269073331970915,
+           2.7656075018632125,
+           2.6880132038273414,
+           2.5955577127901766,
+           2.489936631662934,
+           2.3730675306255904,
+           2.2470449140756013,
+           2.1140916097166347,
+           1.9765077530833273,
+           1.8366185920818905,
+           1.6967223574670087,
+           1.5590394361307283,
+           1.4256640449553915,
+           1.2985195348259921,
+           1.1793183589670824,
+           1.0695276194931391,
+           0.970340963974902,
+           0.8826574434947941,
+           0.8070677691024225,
+           0.7438482191393166,
+           0.6929622601682242,
+           0.6540697539246932,
+           0.6265434365193302,
+           0.6094921786570255,
+           0.6017903712763422,
+           0.6021126337849396,
+           0.608972915577017,
+           0.6207669588443048,
+           0.6358170143115289,
+           0.6524176532587272,
+           0.6688815001499097,
+           0.6835837207528437,
+           0.6950041404506019,
+           0.7017659354250881,
+           0.7026699337467983,
+           0.6967236816886492,
+           0.6831645697552617,
+           0.6614764694252562,
+           0.6313995014575288,
+           0.5929327354989694,
+           0.5463298041171296,
+           0.4920875976261383,
+           0.4309283845473311,
+           0.36377587174220893,
+           0.29172587390770344,
+           0.21601240031028213,
+           0.13797008387705267,
+           0.05899397110958686,
+           -0.019502241606156306,
+           -0.09612840053626774,
+           -0.16955938094324746,
+           -0.23857475107333825,
+           -0.30209554516643333,
+           -0.35921715187781467,
+           -0.4092374250777027,
+           -0.4516792475954998,
+           -0.4863069219767593,
+           -0.5131359220955878,
+           -0.5324357114742394,
+           -0.544725514055241,
+           -0.5507631063970997,
+           -0.5515268821821497,
+           -0.5481916159218835,
+           -0.5420985183524077,
+           -0.5347203270172461,
+           -0.5276223080846584,
+           -0.5224201561485369,
+           -0.5207358647652452,
+           -0.5241526995492054,
+           -0.534170436224526,
+           -0.5521620272579576,
+           -0.5793328324629873,
+           -0.6166834918870537,
+           -0.6649774347180459,
+           -0.7247139079076225,
+           -0.796107275383413,
+           -0.8790731863612281,
+           -0.9732220431178864,
+           -1.0778600187937297,
+           -1.1919976888092758,
+           -1.31436614994004,
+           -1.4434403137089977,
+           -1.577468880196119,
+           -1.714510329138938,
+           -1.852474111545685,
+           -1.9891660908253141,
+           -2.1223371710450163,
+           -2.2497339641868255,
+           -2.369150290391681,
+           -2.4784782766695233,
+           -2.575757821211892,
+           -2.6592232223190564,
+           -2.727345832352427,
+           -2.7788716866186887,
+           -2.8128531725650086,
+           -2.828673943349661,
+           -2.8260664384087497,
+           -2.8051215482318694,
+           -2.7662901469512957,
+           -2.710376410008355,
+           -2.6385230303696168,
+           -2.5521886407381467,
+           -2.453117936204642,
+           -2.3433051672380274,
+           -2.2249518325330273,
+           -2.100419541104641,
+           -1.9721791297191955,
+           -1.8427572124169358,
+           -1.7146814012856972,
+           -1.590425470255288,
+           -1.47235573569101,
+           -1.362679898916795,
+           -1.2633995371867655,
+           -1.1762673424763979,
+           -1.10275009390636,
+           -1.0439982124151523,
+           -1.000822588810173,
+           -0.9736792023952112,
+           -0.9626618612404169,
+           -0.9675032013693298,
+           -0.9875838854111176,
+           -1.0219497463971619,
+           -1.069336434111551,
+           -1.1282009443098184,
+           -1.196759249494966,
+           -1.2730291076948035,
+           -1.354877006249523,
+           -1.440068103857567,
+           -1.5263179682706123,
+           -1.6113448706154005,
+           -1.6929213911643692,
+           -1.7689241155470181,
+           -1.837380254211094,
+           -1.896510099999744,
+           -1.9447643469080247,
+           -1.9808554246785992,
+           -2.003782155581126,
+           -2.0128472076913475,
+           -2.007666999049987,
+           -1.988173894753825,
+           -1.954610729649249,
+           -1.907517878137304,
+           -1.8477132749888887,
+           -1.7762659625100437,
+           -1.694463895672577,
+           -1.6037768741039773,
+           -1.5058155847621482,
+           -1.4022878289183258,
+           -1.2949530695807248,
+           -1.1855764692416444,
+           -1.0758835920715417,
+           -0.9675169194027144,
+           -0.8619952732674079,
+           -0.7606771613228954,
+           -0.6647289498330754,
+           -0.5750986422339218,
+           -0.4924958924968114,
+           -0.41737871880315025,
+           -0.3499472081185157,
+           -0.290144320542404,
+           -0.23766371841242337,
+           -0.19196436370921025,
+           -0.15229145292323312,
+           -0.11770309560626173,
+           -0.08710199544627581,
+           -0.05927126458701042,
+           -0.03291339628634958,
+           -0.006691340527243021,
+           0.020729426118227142,
+           0.050638969880788386,
+           0.08424223764018651,
+           0.12262075910878302,
+           0.16669774776369964,
+           0.21720754686661992,
+           0.2746702544658033,
+           0.33937222729997013,
+           0.41135301140459163,
+           0.49039908080261313,
+           0.5760445891513697,
+           0.6675791570808813,
+           0.7640625348061874,
+           0.8643458000691947,
+           0.9670985801185698,
+           1.0708416276241297,
+           1.1739839381901407,
+           1.2748634751142787,
+           1.371790468367508,
+           1.463092181995071,
+           1.5471579991651319,
+           1.6224836581300468,
+           1.6877134859010663,
+           1.741679519217669,
+           1.7834364734323243,
+           1.8122916175349826,
+           1.8278287353462697,
+           1.8299254959415598,
+           1.818763717120016,
+           1.7948321802441267,
+           1.7589218387343148,
+           1.7121134513535783,
+           1.6557578604689849,
+           1.5914493200263178,
+           1.5209924534169608,
+           1.446363583364212,
+           1.3696673203473022,
+           1.2930894192778146,
+           1.2188470130264715,
+           1.1491374034437574,
+           1.0860866338598942,
+           1.0316990805298782,
+           0.9878092836826495,
+           0.9560371920640026,
+           0.9377479191938561,
+           0.9340170067682545,
+           0.9456020631750605,
+           0.972921496021726,
+           1.016040890493455,
+           1.074667404318312,
+           1.148152359510498,
+           1.2355020155331808,
+           1.3353963128343644,
+           1.4462151846394804,
+           1.5660718531018234,
+           1.692852357861279,
+           1.8242604148569828,
+           1.957866574559644,
+           2.091160544787865,
+           2.2216054665030502
+          ],
+          [
+           2.3102668660298207,
+           2.431350678055853,
+           2.5431391703511235,
+           2.6434513559124913,
+           2.7303196710839264,
+           2.8020321861778488,
+           2.8571689880039686,
+           2.894631899438526,
+           2.9136668603493585,
+           2.913878469463248,
+           2.8952363738462017,
+           2.8580733870028965,
+           2.8030754134522233,
+           2.7312634522082235,
+           2.6439681391562138,
+           2.542797464306228,
+           2.4295984600623917,
+           2.306413797093572,
+           2.175434341742473,
+           2.0389488203537023,
+           1.8992917992632028,
+           1.7587912229919798,
+           1.6197167566755089,
+           1.4842301519323855,
+           1.3543387989736115,
+           1.2318535432455329,
+           1.1183517344427971,
+           1.0151463421156208,
+           0.9232618186863782,
+           0.8434172213236937,
+           0.7760169230231321,
+           0.7211490549184415,
+           0.6785916309705559,
+           0.6478261174805908,
+           0.6280580280104118,
+           0.6182439537524121,
+           0.6171242843602412,
+           0.623260738530995,
+           0.6350777105250024,
+           0.6509063510603105,
+           0.6690302407265075,
+           0.6877314826396799,
+           0.7053360391974526,
+           0.7202571654419543,
+           0.7310358479145246,
+           0.736377241488346,
+           0.7351822053161119,
+           0.7265731699285468,
+           0.7099137173146436,
+           0.6848214206860418,
+           0.651173666385871,
+           0.609106362589578,
+           0.5590056234504419,
+           0.5014926985153165,
+           0.43740259100337364,
+           0.3677569705209881,
+           0.29373213189901715,
+           0.21662287840765598,
+           0.13780331144661503,
+           0.05868558731703414,
+           -0.019322247111856622,
+           -0.09485820540323456,
+           -0.1666469712978311,
+           -0.23353807476214858,
+           -0.29454060543948435,
+           -0.34885352459304275,
+           -0.39589075078949215,
+           -0.4353003300115491,
+           -0.4669771541839532,
+           -0.4910688593713998,
+           -0.5079747119279998,
+           -0.5183374731654435,
+           -0.5230284160448693,
+           -0.5231258463479577,
+           -0.5198876512045131,
+           -0.5147185554138952,
+           -0.5091329066819116,
+           -0.5047139311072883,
+           -0.5030704969061937,
+           -0.5057924949600023,
+           -0.5144059874611521,
+           -0.530329289562388,
+           -0.5548311330803382,
+           -0.58899201627813,
+           -0.6336697705977521,
+           -0.6894702756816151,
+           -0.7567241305283825,
+           -0.835469944188853,
+           -0.9254447475716634,
+           -1.026081852686277,
+           -1.136516301335485,
+           -1.255597856451779,
+           -1.3819113006429364,
+           -1.5138036227711762,
+           -1.6494174991241781,
+           -1.7867303153080076,
+           -1.923597832430652,
+           -2.0578014800445854,
+           -2.1870981617488776,
+           -2.30927138978486,
+           -2.422182524201127,
+           -2.5238208813109932,
+           -2.612351495579278,
+           -2.6861593683686014,
+           -2.7438891150237796,
+           -2.784479026739242,
+           -2.8071886930353425,
+           -2.811619481354932,
+           -2.797727338641589,
+           -2.765827561694973,
+           -2.716591374195422,
+           -2.65103434389607,
+           -2.570496868826098,
+           -2.4766171516627873,
+           -2.371297262060439,
+           -2.256663053250856,
+           -2.135018847574026,
+           -2.008797932123149,
+           -1.880510007289446,
+           -1.7526868051747042,
+           -1.62782713977602,
+           -1.5083426654285723,
+           -1.396505603850361,
+           -1.2943996536523859,
+           -1.2038752204867673,
+           -1.1265100029451347,
+           -1.0635758414037313,
+           -1.0160125873587027,
+           -0.9844095830571378,
+           -0.9689951594976622,
+           -0.9696343695816441,
+           -0.9858349770054534,
+           -1.0167615251753541,
+           -1.0612571187777582,
+           -1.117872368308021,
+           -1.1849007792761177,
+           -1.2604197170511535,
+           -1.3423359490188793,
+           -1.4284346610166336,
+           -1.516430767379062,
+           -1.6040212852073377,
+           -1.6889375247838763,
+           -1.7689958597709974,
+           -1.842145882586931,
+           -1.906514821036032,
+           -1.960447190064416,
+           -2.0025387749335963,
+           -2.0316641860679385,
+           -2.0469973877272296,
+           -2.0480247784373096,
+           -2.0345505864012803,
+           -2.006694533305561,
+           -1.9648819103143955,
+           -1.909826395902956,
+           -1.842506121926852,
+           -1.764133657613931,
+           -1.6761207269864986,
+           -1.58003860001521,
+           -1.4775751985369603,
+           -1.3704900322111022,
+           -1.2605681257784715,
+           -1.1495741155714416,
+           -1.039207680278324,
+           -0.9310614288098594,
+           -0.8265822978959486,
+           -0.7270374156018062,
+           -0.6334852667919211,
+           -0.5467528557735365,
+           -0.4674194035152489,
+           -0.39580694597904487,
+           -0.3319780205623411,
+           -0.27574044396915603,
+           -0.22665900166157632,
+           -0.18407369101057783,
+           -0.14712399186040304,
+           -0.11477848368695699,
+           -0.08586899175917394,
+           -0.05912832914314143,
+           -0.03323060992594753,
+           -0.006833043974741775,
+           0.021381913484677773,
+           0.05266519226425999,
+           0.08816163131346674,
+           0.12887346058157317,
+           0.17562772769196622,
+           0.2290485540791283,
+           0.2895349800429806,
+           0.35724501334870284,
+           0.4320863352061235,
+           0.5137139447682829,
+           0.6015348430632947,
+           0.6947196740801297,
+           0.7922210592085267,
+           0.8927981859900282,
+           0.9950470476223815,
+           1.0974355800597646,
+           1.1983428126835036,
+           1.2961010397341715,
+           1.389039935797596,
+           1.4755314818060274,
+           1.5540345397568884,
+           1.623137915456869,
+           1.681600779125035,
+           1.728389372954591,
+           1.7627090213376087,
+           1.7840305713114133,
+           1.792110525164942,
+           1.7870042807549957,
+           1.769072064144642,
+           1.7389773195144493,
+           1.697677508445964,
+           1.6464074599905647,
+           1.5866555997054996,
+           1.5201335654051344,
+           1.4487398852502218,
+           1.3745185457720523,
+           1.2996134096786063,
+           1.2262195524723667,
+           1.1565326702459109,
+           1.092697766367053,
+           1.0367583506628064,
+           0.9906073804303723,
+           0.9559411381553914,
+           0.9342171769619873,
+           0.9266173730398259,
+           0.9340170067682542,
+           0.9569606538012931,
+           0.9956455073756026,
+           1.049912577428458,
+           1.119246025028544,
+           1.202780696680028,
+           1.299317726986563,
+           1.4073478847412466,
+           1.525082151467617,
+           1.6504888473255857,
+           1.781336461377114,
+           1.9152412053496612,
+           2.0497181956210397,
+           2.1822350799869756,
+           2.3102668660298176
+          ],
+          [
+           2.3963032674726192,
+           2.5123532038711684,
+           2.6176626254828976,
+           2.7101783599529568,
+           2.788087479527416,
+           2.849856102427374,
+           2.8942618451274207,
+           2.9204191828372084,
+           2.9277971447088564,
+           2.9162289531341665,
+           2.885913408496945,
+           2.8374080172282454,
+           2.771614057191011,
+           2.6897539655217706,
+           2.593341615436086,
+           2.4841462157598837,
+           2.364150716030367,
+           2.2355057273186305,
+           2.1004800714007033,
+           1.961409146098219,
+           1.8206423407510257,
+           1.6804907518153451,
+           1.543176434187906,
+           1.410784379472529,
+           1.2852183392021495,
+           1.1681615108841439,
+           1.0610429801883614,
+           0.9650106667796429,
+           0.8809113578624811,
+           0.8092782365340153,
+           0.7503261259378308,
+           0.7039544795957479,
+           0.669757957890145,
+           0.6470442451814817,
+           0.634858586048311,
+           0.6320143569582218,
+           0.6371288452930327,
+           0.6486632845846916,
+           0.6649660960564201,
+           0.6843182144823858,
+           0.7049793326849985,
+           0.7252338846776445,
+           0.7434356027935619,
+           0.7580495286402934,
+           0.7676904301780305,
+           0.7711566757383221,
+           0.7674587378278566,
+           0.7558416419687347,
+           0.735800834975596,
+           0.7070911189121445,
+           0.6697284771450751,
+           0.6239848028597192,
+           0.5703757234695379,
+           0.509641891919425,
+           0.4427242834741354,
+           0.3707341899771721,
+           0.2949187389032189,
+           0.21662287840765598,
+           0.13724885914164164,
+           0.0582143066068072,
+           -0.019089987304089905,
+           -0.09334141905961937,
+           -0.16332496327124496,
+           -0.22796953802819597,
+           -0.28638036531033845,
+           -0.33786645021180645,
+           -0.3819624294837543,
+           -0.41844418603826616,
+           -0.447337787848872,
+           -0.46892148304172493,
+           -0.4837206635066481,
+           -0.4924958924968109,
+           -0.49622427278781306,
+           -0.4960746064366955,
+           -0.49337696058603253,
+           -0.4895874019383076,
+           -0.48624879169938073,
+           -0.4849486396477852,
+           -0.48727509777586403,
+           -0.49477222854138286,
+           -0.5088957087161682,
+           -0.5309701263892401,
+           -0.5621489958794681,
+           -0.6033785538766622,
+           -0.6553663115187665,
+           -0.7185552234682219,
+           -0.7931041991452782,
+           -0.8788755264448496,
+           -0.9754296083218182,
+           -1.0820272317779616,
+           -1.1976394015044733,
+           -1.3209645813800222,
+           -1.4504530009029806,
+           -1.5843375050932529,
+           -1.7206702599015147,
+           -1.8573644748901539,
+           -1.9922401746856302,
+           -2.1230729437437637,
+           -2.2476444880437607,
+           -2.36379380452195,
+           -2.4694677257673403,
+           -2.5627696143976073,
+           -2.6420050185395514,
+           -2.7057231661318872,
+           -2.752753269806197,
+           -2.7822347336506175,
+           -2.7936404953553775,
+           -2.7867928986502815,
+           -2.7618716676637467,
+           -2.719413742569696,
+           -2.660304930073391,
+           -2.5857635181856766,
+           -2.497316197564084,
+           -2.39676681674447,
+           -2.2861586713202047,
+           -2.1677311833150297,
+           -2.043871962811231,
+           -1.91706535600222,
+           -1.7898386694825517,
+           -1.664707317660002,
+           -1.5441201672627816,
+           -1.4304063493445043,
+           -1.3257247750328955,
+           -1.2320175273492837,
+           -1.1509682092952283,
+           -1.0839662103026144,
+           -1.0320777119514246,
+           -0.9960240930171302,
+           -0.9761682173390022,
+           -0.9725089000066066,
+           -0.9846836525264622,
+           -1.0119796107009862,
+           -1.053352354721437,
+           -1.1074521441693257,
+           -1.1726569157737552,
+           -1.2471112331241743,
+           -1.3287702389257838,
+           -1.4154475451483366,
+           -1.5048659073205026,
+           -1.5947094683773835,
+           -1.6826763262971633,
+           -1.7665301789523522,
+           -1.8441498290910816,
+           -1.9135753913499656,
+           -1.97305013015248,
+           -2.021056970050473,
+           -2.0563488556765885,
+           -2.0779722935872034,
+           -2.085283579012106,
+           -2.0779573926319284,
+           -2.055987641451331,
+           -2.0196806089385984,
+           -1.9696406681319332,
+           -1.906748992714946,
+           -1.8321358706739466,
+           -1.7471473789032306,
+           -1.6533073112598649,
+           -1.552275363821249,
+           -1.4458026667771702,
+           -1.3356858104459153,
+           -1.2237205419862505,
+           -1.1116563088531204,
+           -1.0011527950238026,
+           -0.8937395373477721,
+           -0.7907796236060649,
+           -0.693438363236463,
+           -0.6026576890385356,
+           -0.5191368969127915,
+           -0.44332016466478114,
+           -0.37539111433624706,
+           -0.31527449988642986,
+           -0.2626449179576499,
+           -0.21694225857051422,
+           -0.17739343946846148,
+           -0.14303980683168135,
+           -0.1127694402587702,
+           -0.08535347491253678,
+           -0.05948545168347185,
+           -0.03382262969950644,
+           -0.0070281464187424035,
+           0.02218710989418097,
+           0.05502404178691685,
+           0.09255738716916723,
+           0.13570129002599746,
+           0.18517932863144485,
+           0.24149981674001153,
+           0.30493705634532714,
+           0.37551906614239927,
+           0.453022141721328,
+           0.5369724260109312,
+           0.6266544860748315,
+           0.7211267096620935,
+           0.819243156561839,
+           0.9196813303347446,
+           1.0209751797035964,
+           1.121552499763264,
+           1.219775784774206,
+           1.3139854896738785,
+           1.4025445890252828,
+           1.4838832817149894,
+           1.556542678408173,
+           1.6192163269310553,
+           1.6707884780088869,
+           1.710368069037708,
+           1.7373175050051957,
+           1.7512754408347933,
+           1.7521729152449976,
+           1.7402423491060683,
+           1.716019097218818,
+           1.6803354270798974,
+           1.6343069869527953,
+           1.5793120137396124,
+           1.5169637140534602,
+           1.4490764249555077,
+           1.3776263197070044,
+           1.304707564600845,
+           1.2324849519278847,
+           1.1631441283778932,
+           1.098840605259965,
+           1.0416487751045551,
+           0.9935121674431151,
+           0.956196154555242,
+           0.9312442661756775,
+           0.9199391917512665,
+           0.9232694417253461,
+           0.9419025080609703,
+           0.9761652119517615,
+           1.0260317570899058,
+           1.091119824077244,
+           1.1706948500213108,
+           1.2636824417198618,
+           1.3686886758783103,
+           1.4840278502878912,
+           1.60775707045377,
+           1.7377168911961145,
+           1.8715770862955325,
+           2.00688649491144,
+           2.1411257943218525,
+           2.2717619769548962,
+           2.396303267472615
+          ],
+          [
+           2.478986763943324,
+           2.589015142747078,
+           2.686936991379656,
+           2.7708443350214127,
+           2.8390942401999038,
+           2.8903438786256315,
+           2.9235787746396373,
+           2.9381335920211904,
+           2.933704993737447,
+           2.9103562970815986,
+           2.868513841939971,
+           2.80895518689576,
+           2.732789441723854,
+           2.6414302308444797,
+           2.536561955966397,
+           2.4201001832538385,
+           2.2941471170968155,
+           2.1609432356573337,
+           2.0228162500945803,
+           1.8821286076814931,
+           1.7412247875551001,
+           1.602379635969513,
+           1.4677489557673407,
+           1.339323503220766,
+           1.2188874560080363,
+           1.1079823011565757,
+           1.0078769541972752,
+           0.9195447639852062,
+           0.8436478855655876,
+           0.7805293203851507,
+           0.7302127336150814,
+           0.6924099670590996,
+           0.666535977798535,
+           0.6517307520208175,
+           0.646887574834739,
+           0.650686884432155,
+           0.6616348064370564,
+           0.6781053549116288,
+           0.698385202905022,
+           0.7207198696269358,
+           0.7433601446018832,
+           0.7646075720813453,
+           0.7828578513899656,
+           0.7966410698539595,
+           0.8046577728887829,
+           0.805809988423384,
+           0.7992264572116818,
+           0.7842814732916182,
+           0.7606069060086493,
+           0.7280971523794181,
+           0.6869069516399684,
+           0.6374421779721369,
+           0.5803439079832259,
+           0.5164662319747115,
+           0.4468484380332197,
+           0.3726823414869541,
+           0.2952756556881072,
+           0.21601240031028213,
+           0.1363114178795251,
+           0.0575841162269715,
+           -0.018807427205928623,
+           -0.09159087420424297,
+           -0.15962146255461976,
+           -0.22191625321204186,
+           -0.27768386410303986,
+           -0.32634888435507886,
+           -0.36757030106137456,
+           -0.4012534262811573,
+           -0.4275549808976273,
+           -0.44688116993211424,
+           -0.45987876643491377,
+           -0.4674194035152484,
+           -0.47057745180690197,
+           -0.47060202817884134,
+           -0.46888383650529813,
+           -0.46691767885602764,
+           -0.4662615920375862,
+           -0.46849365701579515,
+           -0.47516759498169076,
+           -0.48776830195001725,
+           -0.5076684827658666,
+           -0.5360875249355449,
+           -0.5740537032246961,
+           -0.6223707286405178,
+           -0.681589552096106,
+           -0.7519862062585024,
+           -0.833546321915638,
+           -0.9259567912842674,
+           -1.0286048740713338,
+           -1.1405848571702517,
+           -1.2607121902147393,
+           -1.387544831522324,
+           -1.5194113569204994,
+           -1.65444521211383,
+           -1.7906243319297108,
+           -1.9258152109329816,
+           -2.057820393034128,
+           -2.184428255804271,
+           -2.303463900611679,
+           -2.4128399240977476,
+           -2.5106058408882728,
+           -2.59499495202295,
+           -2.6644675078700932,
+           -2.717749097027117,
+           -2.7538633019391434,
+           -2.772157795087899,
+           -2.772323203408115,
+           -2.754404239359548,
+           -2.718802780676576,
+           -2.666272772768335,
+           -2.5979070233723833,
+           -2.5151161535980777,
+           -2.4196001581770825,
+           -2.3133132059493002,
+           -2.198422474987254,
+           -2.077261961292345,
+           -1.9522823221341707,
+           -1.8259979118453014,
+           -1.7009322368456177,
+           -1.5795630961483753,
+           -1.4642686826112905,
+           -1.357275898503741,
+           -1.2606120870791089,
+           -1.1760613010242473,
+           -1.1051261208675311,
+           -1.0489959042858796,
+           -1.0085221939776765,
+           -0.9842018410974638,
+           -0.9761682173390017,
+           -0.9841906960873527,
+           -1.0076823863312792,
+           -1.0457159070242799,
+           -1.097046799073867,
+           -1.1601439917535599,
+           -1.233226574446903,
+           -1.314305977263882,
+           -1.4012325387748255,
+           -1.4917453388965372,
+           -1.5835241022318574,
+           -1.6742419336205696,
+           -1.7616176343006484,
+           -1.843466364155486,
+           -1.9177474625366056,
+           -1.9826083158697574,
+           -2.0364232627377343,
+           -2.0778266537929926,
+           -2.1057393315045765,
+           -2.1193879596921117,
+           -2.118316810932785,
+           -2.1023918068144547,
+           -2.0717967970140387,
+           -2.0270222535768117,
+           -1.9688467418573632,
+           -1.898311704796785,
+           -1.816690258248365,
+           -1.7254508379822169,
+           -1.6262166603129111,
+           -1.5207220550633092,
+           -1.4107667994787068,
+           -1.2981696230879889,
+           -1.1847220654366653,
+           -1.0721438508895214,
+           -0.9620408978572705,
+           -0.8558670051065702,
+           -0.7548901572231442,
+           -0.6601642674136289,
+           -0.5725070318303505,
+           -0.4924844091600127,
+           -0.4204020664111131,
+           -0.3563039510487291,
+           -0.29997796543412947,
+           -0.250968536583736,
+           -0.20859569718266618,
+           -0.17198012703375584,
+           -0.14007345189052592,
+           -0.11169296273820628,
+           -0.08555980641216109,
+           -0.06033961078971065,
+           -0.03468444685185,
+           -0.007274997204283754,
+           0.023138203020756625,
+           0.05769556151440573,
+           0.09739231512364656,
+           0.14304648091532648,
+           0.19527173971603884,
+           0.25445599153289794,
+           0.3207461748378025,
+           0.3940397789253173,
+           0.4739833045535261,
+           0.5599777472546625,
+           0.6511909946393345,
+           0.746576848356429,
+           0.8449002076948764,
+           0.9447677895374257,
+           1.0446636126321882,
+           1.142988346680906,
+           1.2381015218198297,
+           1.3283655143941036,
+           1.4121901725733366,
+           1.4880769217154945,
+           1.5546611951310496,
+           1.6107520709660734,
+           1.6553680595126865,
+           1.6877680758528901,
+           1.7074767481530497,
+           1.7143033493308197,
+           1.7083537958383344,
+           1.6900353280965432,
+           1.6600536684494895,
+           1.619402639886226,
+           1.569346417542128,
+           1.5113947704370405,
+           1.4472718284014205,
+           1.378879074239364,
+           1.3082534097310592,
+           1.2375212723411442,
+           1.1688498842236978,
+           1.104396793624188,
+           1.0462589190443718,
+           0.9964223272222889,
+           0.95671396647998,
+           0.928756537446648,
+           0.9139276144559184,
+           0.9133240346475894,
+           0.9277324502642934,
+           0.9576067957372364,
+           1.003053258374347,
+           1.0638231637421178,
+           1.1393139984866723,
+           1.2285785989563138,
+           1.3303423383085944,
+           1.4430279525900858,
+           1.564787462267693,
+           1.6935404743724707,
+           1.8270179959911255,
+           1.9628107560953756,
+           2.09842092292266,
+           2.2313160210146408,
+           2.358983797631896,
+           2.47898676394332
+          ],
+          [
+           2.557617815647086,
+           2.6606878999907697,
+           2.7503761755589045,
+           2.8249360195171134,
+           2.88290841282528,
+           2.923152969865056,
+           2.944871742050883,
+           2.9476252550729125,
+           2.931340424359017,
+           2.8963101866331558,
+           2.843184882381746,
+           2.772955619825104,
+           2.686930040865941,
+           2.58670108883846,
+           2.474109542359347,
+           2.351201225204253,
+           2.2201799253857044,
+           2.083357154529046,
+           1.943099948895633,
+           1.8017779543333814,
+           1.6617110481123145,
+           1.5251187308402208,
+           1.3940724720125741,
+           1.2704521145265975,
+           1.1559073386781613,
+           1.051825057408526,
+           0.9593034651073246,
+           0.8791332958435052,
+           0.8117866676332416,
+           0.7574137017167506,
+           0.7158469144553474,
+           0.6866131891085084,
+           0.6689529501052633,
+           0.6618459880300693,
+           0.6640432236813834,
+           0.6741035581423669,
+           0.6904348362719603,
+           0.7113378562741531,
+           0.735052290304552,
+           0.7598033420195017,
+           0.7838479574408295,
+           0.8055194256385516,
+           0.8232692549247668,
+           0.8357052871814147,
+           0.8416251155995352,
+           0.8400439968374148,
+           0.8302165941865446,
+           0.8116520500550353,
+           0.7841220598279903,
+           0.7476618005393912,
+           0.7025637522029762,
+           0.6493646324438478,
+           0.5888258416398654,
+           0.52190798167626,
+           0.4497401624668557,
+           0.3735849428070128,
+           0.2947998625761753,
+           0.21479660903648265,
+           0.13499891883753987,
+           0.056800347873304874,
+           -0.01847695740366312,
+           -0.08962138123871236,
+           -0.15556780243987134,
+           -0.21542943384237337,
+           -0.2685246781530138,
+           -0.31439827084176597,
+           -0.3528361294413181,
+           -0.383873492346675,
+           -0.40779610482884804,
+           -0.42513439106483053,
+           -0.43665073395060416,
+           -0.4433201646647807,
+           -0.4463049368129524,
+           -0.4469236211129286,
+           -0.4466155018752982,
+           -0.4469011822824975,
+           -0.4493404084499778,
+           -0.45548819981034855,
+           -0.46685042347601957,
+           -0.4848399715741811,
+           -0.5107346924971129,
+           -0.5456381896939516,
+           -0.59044453590494,
+           -0.6458078581771376,
+           -0.7121176318483354,
+           -0.7894803828103591,
+           -0.8777083401805567,
+           -0.9763154099020496,
+           -1.0845206580098885,
+           -1.2012593048547007,
+           -1.3252010431330348,
+           -1.4547753078345769,
+           -1.5882029497995724,
+           -1.7235336009074165,
+           -1.8586878721048286,
+           -1.9915033992352602,
+           -2.1197836491535296,
+           -2.2413483225224846,
+           -2.354084141963737,
+           -2.455994796147018,
+           -2.5452488224947927,
+           -2.6202242532485807,
+           -2.679548920746776,
+           -2.7221354162371227,
+           -2.7472098200484787,
+           -2.754333466511193,
+           -2.743417171129613,
+           -2.714727526196366,
+           -2.6688850599528795,
+           -2.6068542489419713,
+           -2.529925568618463,
+           -2.439689958805978,
+           -2.3380062635252163,
+           -2.2269623745877922,
+           -2.1088309609836435,
+           -1.9860207977389004,
+           -1.8610248153477589,
+           -1.7363660714384492,
+           -1.6145428980293683,
+           -1.4979744992820123,
+           -1.3889482655149037,
+           -1.2895700296123016,
+           -1.2017184227929145,
+           -1.1270043896724673,
+           -1.066736800015553,
+           -1.021894949508075,
+           -0.9931085778235373,
+           -0.9806458532005726,
+           -0.9844095830571369,
+           -1.0039417144589844,
+           -1.0384359913010612,
+           -1.086758441642592,
+           -1.1474751834614612,
+           -1.2188868646565663,
+           -1.2990688976070066,
+           -1.385916513753851,
+           -1.4771935527519937,
+           -1.570583816403229,
+           -1.6637437618285114,
+           -1.7543552824638122,
+           -1.8401773300307374,
+           -1.919095165452439,
+           -1.9891660908253148,
+           -2.0486606063671164,
+           -2.0960980534134594,
+           -2.1302759440789383,
+           -2.15029233664261,
+           -2.1555607891066177,
+           -2.1458176073995103,
+           -2.1211212947842064,
+           -2.081844300479618,
+           -2.028657353584431,
+           -1.962506848466224,
+           -1.8845859154221778,
+           -1.7962999615204467,
+           -1.6992275974048772,
+           -1.595077973311308,
+           -1.4856456290115156,
+           -1.3727640159328245,
+           -1.2582588740586393,
+           -1.1439026408883375,
+           -1.0313710349546075,
+           -0.9222028931270897,
+           -0.8177642508465304,
+           -0.7192175398729546,
+           -0.6274966420406622,
+           -0.5432883833706751,
+           -0.46702088462197683,
+           -0.3988590062360285,
+           -0.33870694215494157,
+           -0.28621783280866714,
+           -0.24081008731746062,
+           -0.2016899331842348,
+           -0.16787955277921038,
+           -0.13825002374202983,
+           -0.1115581586122009,
+           -0.08648624060019391,
+           -0.0616835798893077,
+           -0.035808770019892674,
+           -0.00757150786201891,
+           0.024227146186179428,
+           0.0606571491809556,
+           0.10262550949857996,
+           0.15084688961090026,
+           0.2058195745811044,
+           0.2678074633563038,
+           0.3368285832242538,
+           0.4126504580865967,
+           0.49479248278012306,
+           0.5825352730717284,
+           0.6749367787914512,
+           0.7708547704734635,
+           0.868975142345106,
+           0.9678453208014645,
+           1.0659119315464443,
+           1.1615617638479359,
+           1.2531649797924787,
+           1.3391194523786785,
+           1.417895080440265,
+           1.4880769217154948,
+           1.5484060081254238,
+           1.5978167589975063,
+           1.635469987354731,
+           1.6607805995690943,
+           1.6734392170872363,
+           1.6734270974236787,
+           1.66102389652351,
+           1.6368079918430969,
+           1.6016492706886865,
+           1.5566944768854942,
+           1.5033453960261698,
+           1.443230340694092,
+           1.3781695676379353,
+           1.3101354146084256,
+           1.2412080815323825,
+           1.1735280954276055,
+           1.1092465880340148,
+           1.05047457724674,
+           0.9992324764579994,
+           0.9574010589345354,
+           0.9266750772049254,
+           0.9085206806818977,
+           0.9041376897055375,
+           0.9144276728734438,
+           0.9399686395848942,
+           0.9809970044170396,
+           1.0373973080293366,
+           1.1086999949311542,
+           1.1940873561331264,
+           1.2924075491248688,
+           1.4021964135571428,
+           1.5217066132020018,
+           1.648943457819162,
+           1.7817065968091401,
+           1.9176366339548414,
+           2.05426559264643,
+           2.1890700667025453,
+           2.3195258255700484,
+           2.4431626059467235,
+           2.557617815647082
+          ],
+          [
+           2.631531168305534,
+           2.7267650916436694,
+           2.807443453815929,
+           2.87199577331246,
+           2.9191593096769948,
+           2.9480057963874793,
+           2.9579605992216806,
+           2.948813868227932,
+           2.9207234419004875,
+           2.8742094582391693,
+           2.810140824281617,
+           2.729713888643687,
+           2.6344238459001463,
+           2.5260295728103004,
+           2.4065127502940924,
+           2.278032257973362,
+           2.1428749368094455,
+           2.0034038972882158,
+           1.8620056037840422,
+           1.7210369889402943,
+           1.582773844638732,
+           1.449361698645819,
+           1.3227703193151579,
+           1.2047528965030363,
+           1.0968108275039639,
+           1.0001648953335467,
+           0.9157334666159647,
+           0.8441181616614163,
+           0.785597264386516,
+           0.7401269491226867,
+           0.7073502097893277,
+           0.6866131891085083,
+           0.6769884261309225,
+           0.6773043737354021,
+           0.6861803880359819,
+           0.7020662624331037,
+           0.7232852735131793,
+           0.7480796266728592,
+           0.7746571381035638,
+           0.8012379677981698,
+           0.8261002259842755,
+           0.8476233125553447,
+           0.8643279146376925,
+           0.8749116796673088,
+           0.878279697863041,
+           0.873569065778166,
+           0.8601669581704408,
+           0.8377218047942402,
+           0.8061473475915788,
+           0.7656195376155259,
+           0.7165664152165526,
+           0.6596512969150495,
+           0.5957497634426024,
+           0.5259211013591751,
+           0.4513749914778147,
+           0.3734343575217488,
+           0.293495384992449,
+           0.21298579073058574,
+           0.13332246635149378,
+           0.05586963258073856,
+           -0.018101373821359856,
+           -0.08744960296472166,
+           -0.15119827872587255,
+           -0.20856396134637709,
+           -0.25898029831797625,
+           -0.3021157172699046,
+           -0.3378845723827793,
+           -0.3664514263404149,
+           -0.38822832867506957,
+           -0.4038651340296206,
+           -0.41423308571934125,
+           -0.42040206641111266,
+           -0.42361208426625135,
+           -0.4252397152773365,
+           -0.4267603568835387,
+           -0.42970726083629723,
+           -0.43562840180662943,
+           -0.44604230008444007,
+           -0.4623939502933518,
+           -0.48601201241393854,
+           -0.5180683963881048,
+           -0.5595413177188787,
+           -0.6111828200587885,
+           -0.6734916537652197,
+           -0.7466922694066371,
+           -0.8307205354238545,
+           -0.9252166232819717,
+           -1.0295253255971548,
+           -1.1427038873031812,
+           -1.2635372415483976,
+           -1.3905603553821315,
+           -1.5220872100650409,
+           -1.6562457715358918,
+           -1.791018152441966,
+           -1.924285032077884,
+           -2.0538732879997075,
+           -2.177605705858372,
+           -2.2933515743773434,
+           -2.3990769419521762,
+           -2.492893310924422,
+           -2.5731035752863805,
+           -2.6382440667697393,
+           -2.687121661592246,
+           -2.7188450135165536,
+           -2.732849115601733,
+           -2.72891254980586,
+           -2.707166956633078,
+           -2.668098442108014,
+           -2.6125408319980066,
+           -2.541660878689365,
+           -2.4569357196808075,
+           -2.3601230735480625,
+           -2.253224834878899,
+           -2.138444889767461,
+           -2.018142114058468,
+           -1.8947796341854564,
+           -1.7708715222539013,
+           -1.6489281607103758,
+           -1.531401545931811,
+           -1.420631803509664,
+           -1.3187961607851346,
+           -1.2278615649582625,
+           -1.1495420492238604,
+           -1.0852618369624853,
+           -1.036125037765068,
+           -1.0028926323099427,
+           -0.9859672696564115,
+           -0.9853862145931679,
+           -1.0008225888101716,
+           -1.0315948525686398,
+           -1.0766842780215982,
+           -1.1347599761410927,
+           -1.204210860933196,
+           -1.2831837715921328,
+           -1.3696268294061407,
+           -1.4613369850512379,
+           -1.5560106163062906,
+           -1.6512959684738875,
+           -1.744846191490467,
+           -1.8343717197241933,
+           -1.9176907629128854,
+           -1.9927767289618157,
+           -2.0578014800445885,
+           -2.1111734305754357,
+           -2.1515696264473827,
+           -2.177961096178916,
+           -2.189630932506756,
+           -2.186184743325482,
+           -2.1675532992299207,
+           -2.133987396597769,
+           -2.086045145422203,
+           -2.0245720752755,
+           -1.9506746263254395,
+           -1.8656877509802239,
+           -1.7711374916272238,
+           -1.6686995176526476,
+           -1.560154697637506,
+           -1.4473428481025303,
+           -1.3321158368847767,
+           -1.2162912263544747,
+           -1.1016076191439457,
+           -0.9896828175210977,
+           -0.8819758283801796,
+           -0.7797536411103858,
+           -0.6840635780403223,
+           -0.5957118700104878,
+           -0.5152489466470674,
+           -0.4429617562386518,
+           -0.3788732481769545,
+           -0.3227489663128632,
+           -0.2741105189585854,
+           -0.23225551523636706,
+           -0.19628339246354062,
+           -0.16512640941854953,
+           -0.13758494941344,
+           -0.11236616838465958,
+           -0.08812493942418823,
+           -0.06350598839552739,
+           -0.03718608692087078,
+           -0.007915169777610824,
+           0.02544472643851749,
+           0.06388374841477373,
+           0.10821269510150802,
+           0.15903652112542901,
+           0.21673359377073337,
+           0.2814412727169931,
+           0.3530482170523589,
+           0.4311936488591049,
+           0.5152736213370612,
+           0.6044541565863193,
+           0.6976909384521648,
+           0.7937550738062015,
+           0.8912642756713541,
+           0.9887186777696653,
+           1.0845403660533763,
+           1.1771156117505532,
+           1.2648387150214113,
+           1.3461563204460414,
+           1.4196110465240133,
+           1.4838832817149903,
+           1.5378300391038675,
+           1.5805198296179035,
+           1.6112626082294565,
+           1.6296339664476538,
+           1.635492884722731,
+           1.62899251670122,
+           1.6105836496657517,
+           1.5810106676960778,
+           1.5413000315697567,
+           1.4927414775124561,
+           1.4368623209127487,
+           1.3753954264311483,
+           1.310241568158193,
+           1.2434270485300307,
+           1.1770575689258922,
+           1.1132694450941603,
+           1.0541793342153989,
+           1.0018336855961838,
+           0.9581591424848369,
+           0.9249151078283344,
+           0.90364964221397,
+           0.8956597887660506,
+           0.9019573191179145,
+           0.9232407691500378,
+           0.9598744859885566,
+           1.0118752423507593,
+           1.0789067947157889,
+           1.1602825723581582,
+           1.254976489625691,
+           1.3616416787256194,
+           1.478636749474564,
+           1.604059000642782,
+           1.7357838391389107,
+           1.8715095124723384,
+           2.0088061304046883,
+           2.145167846647689,
+           2.2780669934755124,
+           2.405008913126145,
+           2.52358621108969,
+           2.63153116830553
+          ],
+          [
+           2.7001014815090025,
+           2.786687674764123,
+           2.8576560111534364,
+           2.9116254495955607,
+           2.947540231763964,
+           2.96469209203449,
+           2.962734608497591,
+           2.9416893752811037,
+           2.9019438708376977,
+           2.8442410940625473,
+           2.7696612353237184,
+           2.6795958379644107,
+           2.5757150829952056,
+           2.459928991239776,
+           2.3343434792194033,
+           2.2012123241332735,
+           2.0628861865523023,
+           1.921759904670363,
+           1.780219309615063,
+           1.6405888166051623,
+           1.505081021595233,
+           1.375749478159126,
+           1.2544457461515057,
+           1.1427816942637972,
+           1.0420979057114532,
+           0.9534388832792814,
+           0.8775355806260818,
+           0.8147956053186501,
+           0.7653012500277191,
+           0.7288153163522497,
+           0.704794505583299,
+           0.692409967059099,
+           0.6905744221122408,
+           0.6979751241987491,
+           0.7131117774709123,
+           0.7343384201727975,
+           0.7599081885966585,
+           0.788019814104332,
+           0.8168646713682778,
+           0.8446731912794685,
+           0.8697594769209741,
+           0.8905630148961805,
+           0.9056864556883161,
+           0.9139285434901149,
+           0.9143114053269639,
+           0.906101557992131,
+           0.8888241555313713,
+           0.8622701755874407,
+           0.8264964253983774,
+           0.7818184330261895,
+           0.728796471815325,
+           0.6682151415495468,
+           0.6010570938798756,
+           0.5284716382149823,
+           0.4517390936728953,
+           0.3722318596508161,
+           0.29137325940756936,
+           0.21059526573486406,
+           0.13129624396802214,
+           0.054799844621801125,
+           -0.017683854066078628,
+           -0.0850939136092098,
+           -0.1465498595604759,
+           -0.2013779207280312,
+           -0.2491314743702133,
+           -0.2896051396006317,
+           -0.32284212682413066,
+           -0.3491346268243647,
+           -0.3690172046770733,
+           -0.383253346365451,
+           -0.3928154851892638,
+           -0.39885900623602805,
+           -0.40269088596797775,
+           -0.4057337663275141,
+           -0.4094863850412055,
+           -0.4154813828732002,
+           -0.42524158188849764,
+           -0.4402358744240694,
+           -0.4618358792133898,
+           -0.49127450847343,
+           -0.5296075479853853,
+           -0.5776792822559975,
+           -0.6360931004181196,
+           -0.7051878979670284,
+           -0.7850209476920644,
+           -0.8753577537464967,
+           -0.9756692296471001,
+           -1.085136358405041,
+           -1.2026623055031773,
+           -1.3268917677258256,
+           -1.456237157604974,
+           -1.5889110490618614,
+           -1.722964149067841,
+           -1.8563279168743856,
+           -1.9868608301924515,
+           -2.1123971997446787,
+           -2.2307973623841524,
+           -2.3399980403264133,
+           -2.438061641129619,
+           -2.523223290298175,
+           -2.5939344354499996,
+           -2.6489019368099798,
+           -2.687121661592246,
+           -2.7079057271613514,
+           -2.7109026866568198,
+           -2.6961101174303237,
+           -2.663879253136559,
+           -2.6149114902457797,
+           -2.5502467944765117,
+           -2.471244227423192,
+           -2.3795550037097137,
+           -2.277088669678042,
+           -2.1659731614885125,
+           -2.0485096494645094,
+           -1.9271232028938852,
+           -1.804310412162775,
+           -1.6825851805070027,
+           -1.564423943951947,
+           -1.452211594013585,
+           -1.3481893630355324,
+           -1.2544058869721886,
+           -1.172672586075996,
+           -1.1045244021024205,
+           -1.0511868037789482,
+           -1.0135498234766962,
+           -0.9921497208936257,
+           -0.9871586881748715,
+           -0.9983828196728294,
+           -1.025268373142465,
+           -1.0669161523547221,
+           -1.122103648679688,
+           -1.1893143958169805,
+           -1.266773821984474,
+           -1.3524907316328991,
+           -1.444303417813456,
+           -1.5399292998407148,
+           -1.6370169014149156,
+           -1.7331989337793259,
+           -1.826145227963513,
+           -1.9136142701346397,
+           -1.9935021342296784,
+           -2.063887675315039,
+           -2.1230729437437614,
+           -2.169617901714528,
+           -2.202368667230463,
+           -2.2204786721283827,
+           -2.223422296775087,
+           -2.2110007298385144,
+           -2.1833399926356183,
+           -2.1408812592118225,
+           -2.0843637907926755,
+           -2.014800981953124,
+           -1.933450181388462,
+           -1.8417770984936184,
+           -1.7414157344501413,
+           -1.6341248800943486,
+           -1.5217423000066677,
+           -1.4061377711950527,
+           -1.289166164322824,
+           -1.1726217452656498,
+           -1.058194835226164,
+           -0.9474318997726133,
+           -0.8417000427872571,
+           -0.7421567628565013,
+           -0.6497256901497004,
+           -0.5650788648772563,
+           -0.48862594798219905,
+           -0.4205105751230405,
+           -0.36061388079072954,
+           -0.30856503521918555,
+           -0.2637584572376779,
+           -0.22537719589124944,
+           -0.19242181680156847,
+           -0.16374398979041607,
+           -0.13808385573452592,
+           -0.1141101559272788,
+           -0.09046203875057318,
+           -0.06579141790775792,
+           -0.03880474483055905,
+           -0.008303075415744772,
+           0.02678064249787458,
+           0.06734806072628921,
+           0.11410660181399969,
+           0.16754608747044866,
+           0.2279214597439315,
+           0.2952420714184054,
+           0.36926785088046277,
+           0.44951246745801515,
+           0.5352534405243279,
+           0.625548954125494,
+           0.7192609631343709,
+           0.8150840114259426,
+           0.9115790315197331,
+           1.0072112623967757,
+           1.1003913111675923,
+           1.189518297797306,
+           1.2730239624241657,
+           1.3494165835081229,
+           1.4173235529750292,
+           1.475531481806029,
+           1.5230227655499833,
+           1.5590076226767684,
+           1.5829507275182273,
+           1.5945916910987883,
+           1.5939587942022484,
+           1.5813755438232322,
+           1.5574598025779482,
+           1.523115426266347,
+           1.4795165329639932,
+           1.4280847130808694,
+           1.3704596691012585,
+           1.3084639417185224,
+           1.2440625315755625,
+           1.179318358967083,
+           1.1163446142766773,
+           1.057255136789984,
+           1.0041140166533762,
+           0.9588856426261367,
+           0.9233864161161925,
+           0.8992393197501064,
+           0.8878324671062662,
+           0.8902826706643343,
+           0.9074049496148499,
+           0.9396887606948978,
+           0.9872815770072083,
+           1.0499802656729138,
+           1.1272305293930758,
+           1.2181344840767148,
+           1.3214662493423708,
+           1.4356952356933432,
+           1.5590166262293441,
+           1.6893883764497963,
+           1.8245738973052528,
+           1.9621894480592652,
+           2.099755150146033,
+           2.2347484438965624,
+           2.364658748969494,
+           2.4870420580806605,
+           2.59957419296919,
+           2.700101481509
+          ],
+          [
+           2.7627486193793738,
+           2.8399486771836555,
+           2.900589026614912,
+           2.94348976337243,
+           2.967811063642819,
+           2.9730706831942793,
+           2.9591533795998752,
+           2.926312052666627,
+           2.8751605948396906,
+           2.80665864002506,
+           2.7220885911478554,
+           2.623025489174693,
+           2.5113004548513094,
+           2.3889585849578228,
+           2.2582123138255352,
+           2.121391355085691,
+           1.9808904156367666,
+           1.8391159217973585,
+           1.698433015446081,
+           1.5611140652691493,
+           1.4292898954211626,
+           1.3049048620753592,
+           1.1896768093278043,
+           1.0850628122221129,
+           0.9922314693768741,
+           0.9120423444514713,
+           0.8450329785378906,
+           0.7914137089104715,
+           0.7510703380223754,
+           0.7235745049372486,
+           0.7082014242513142,
+           0.703954479595747,
+           0.7095959943754836,
+           0.7236833555175696,
+           0.7446095402449658,
+           0.7706469943036527,
+           0.7999937350887383,
+           0.8308205065097644,
+           0.861317795268153,
+           0.8897415308180885,
+           0.9144563332319644,
+           0.9339752433488238,
+           0.9469949661043959,
+           0.9524257783265638,
+           0.9494153934416251,
+           0.9373662338740628,
+           0.9159457334121358,
+           0.8850894721094618,
+           0.8449971308420804,
+           0.7961214367861239,
+           0.7391504501863054,
+           0.6749837123465479,
+           0.6047029305345916,
+           0.5295380135477503,
+           0.450829388582769,
+           0.3699876228703391,
+           0.2884514399642574,
+           0.20764525897250596,
+           0.12893739444536526,
+           0.05360003488670978,
+           -0.017227930543878955,
+           -0.08257424337008572,
+           -0.1416618726732543,
+           -0.19393210914268655,
+           -0.23906153181696543,
+           -0.2769723829821302,
+           -0.307836058661581,
+           -0.3320696017583713,
+           -0.35032526763701277,
+           -0.3634734131229008,
+           -0.37257913495242856,
+           -0.3788732481769541,
+           -0.3837183447226828,
+           -0.3885708034181172,
+           -0.39493973196664633,
+           -0.40434390575805584,
+           -0.4182678258921795,
+           -0.4381180478177605,
+           -0.46518093177,
+           -0.500582936654687,
+           -0.5452545208449171,
+           -0.5998986279178039,
+           -0.6649646247390629,
+           -0.7406284262139025,
+           -0.8267793887424026,
+           -0.9230143867127044,
+           -1.0286393073960338,
+           -1.1426780138238741,
+           -1.2638886372604177,
+           -1.390786875427274,
+           -1.5216757943356727,
+           -1.6546814649090003,
+           -1.7877936147310887,
+           -1.91891034404458,
+           -2.04588584688061,
+           -2.166579995694445,
+           -2.278908593247165,
+           -2.380893070160004,
+           -2.470708411300251,
+           -2.546728128918302,
+           -2.607565164482595,
+           -2.6521076929660206,
+           -2.679548920746776,
+           -2.689410108484164,
+           -2.6815562099334818,
+           -2.6562036928057493,
+           -2.613920294199545,
+           -2.5556166562897893,
+           -2.482529983134193,
+           -2.396200051877054,
+           -2.298438096577469,
+           -2.1912892558261423,
+           -2.076989431992771,
+           -1.9579175465080496,
+           -1.8365442886648742,
+           -1.7153785422269485,
+           -1.5969127325082664,
+           -1.4835683650755322,
+           -1.377643025101771,
+           -1.281260073686608,
+           -1.1963222149294475,
+           -1.1244700167001436,
+           -1.0670463510939556,
+           -1.0250675803217173,
+           -0.9992021536787159,
+           -0.9897571051509291,
+           -0.9966727534391294,
+           -1.0195257112795542,
+           -1.0575401136567224,
+           -1.1096067796379756,
+           -1.174309834847063,
+           -1.2499601455936473,
+           -1.334634755654738,
+           -1.4262213765351717,
+           -1.5224668650994848,
+           -1.6210285315757347,
+           -1.7195270582500972,
+           -1.8155997761715557,
+           -1.9069530446108631,
+           -1.9914125058610153,
+           -2.0669700454747484,
+           -2.13182637372789,
+           -2.18442825580427,
+           -2.223499553112147,
+           -2.2480653928908585,
+           -2.257468953995383,
+           -2.251380539215126,
+           -2.2297987941704576,
+           -2.19304412504683,
+           -2.1417445574291434,
+           -2.0768144616120234,
+           -1.999426741488276,
+           -1.9109792402536085,
+           -1.8130562529020922,
+           -1.7073861495041653,
+           -1.5957962018089167,
+           -1.4801657666845582,
+           -1.3623790118852201,
+           -1.2442783719117791,
+           -1.127619894362841,
+           -1.014031580931445,
+           -0.9049757435920648,
+           -0.8017162877194295,
+           -0.705291702687686,
+           -0.6164943902707152,
+           -0.5358567957259812,
+           -0.46364462999181916,
+           -0.39985728842665624,
+           -0.34423538658789904,
+           -0.29627515134925997,
+           -0.25524923077246486,
+           -0.22023332297624248,
+           -0.19013787687580094,
+           -0.163743989790416,
+           -0.1397425217320534,
+           -0.11677536631628452,
+           -0.09347776566149864,
+           -0.0685205326581571,
+           -0.040651049170590446,
+           -0.00873194291919293,
+           0.028223591909879945,
+           0.07102077646572746,
+           0.12025736451824405,
+           0.1763035938640596,
+           0.23928851809199841,
+           0.3090930984585941,
+           0.38535025926691535,
+           0.46745192838862526,
+           0.5545629020306277,
+           0.6456411941565666,
+           0.7394643606687108,
+           0.8346611308689695,
+           0.9297475378632336,
+           1.0231666190488597,
+           1.113330660720794,
+           1.1986648896519587,
+           1.277651471103848,
+           1.3488726582641322,
+           1.4110519530238403,
+           1.4630921819950733,
+           1.5041094636984054,
+           1.5334621411792024,
+           1.5507738765431325,
+           1.5559502470287594,
+           1.5491883427259823,
+           1.5309790399271892,
+           1.5021018070452772,
+           1.4636120874942955,
+           1.4168214912269386,
+           1.3632712090753452,
+           1.3046992370735673,
+           1.243002157203726,
+           1.1801923624858883,
+           1.1183517344427971,
+           1.059582876653995,
+           1.0059590769100812,
+           0.9594742105893248,
+           0.9219938082143372,
+           0.8952084903519832,
+           0.8805909234854149,
+           0.879357372340578,
+           0.8924348192290633,
+           0.920434491777258,
+           0.963632490056758,
+           1.0219580362489806,
+           1.0949896886434782,
+           1.1819596713990996,
+           1.2817662767353963,
+           1.392994101829004,
+           1.513941693426476,
+           1.6426559936918474,
+           1.7769728154917348,
+           1.914562428248142,
+           2.052979210281737,
+           2.189714223316962,
+           2.322249492004642,
+           2.448112727749794,
+           2.5649312229068775,
+           2.6704836588735676,
+           2.7627486193793707
+          ],
+          [
+           2.8189425587821075,
+           2.886097486720916,
+           2.935879267462139,
+           2.9673191281297475,
+           2.979800304903209,
+           2.9730706831942797,
+           2.9472472113455326,
+           2.9028119994921378,
+           2.840600212540981,
+           2.761780060694123,
+           2.667825377850624,
+           2.560481453023676,
+           2.441724938370511,
+           2.3137187957160656,
+           2.1787633582214694,
+           2.0392446723481585,
+           1.8975813453882993,
+           1.7561711541611413,
+           1.6173386703344899,
+           1.4832851272912975,
+           1.3560416933398367,
+           1.2374272279041498,
+           1.1290114833578597,
+           1.0320845782381478,
+           0.9476334111164365,
+           0.876325512300747,
+           0.8185006470726527,
+           0.7741702938609255,
+           0.7430249283256136,
+           0.7244488545137499,
+           0.7175421417197931,
+           0.7211490549184404,
+           0.7338922118119439,
+           0.7542115644217988,
+           0.7804071910321705,
+           0.8106847978587051,
+           0.8432027711271743,
+           0.876119590663868,
+           0.9076404162597235,
+           0.9360616878678717,
+           0.9598126392872973,
+           0.9774927108163027,
+           0.987903957195498,
+           0.9900776801497378,
+           0.9832946665828387,
+           0.9670985801185693,
+           0.9413022309912065,
+           0.9059866327858779,
+           0.861492939582967,
+           0.8084075390113371,
+           0.7475407509872454,
+           0.6798997441342968,
+           0.606656427978891,
+           0.5291112053396235,
+           0.44865357272414463,
+           0.3667206344390095,
+           0.2847546465771418,
+           0.20416072883561462,
+           0.12626587471787634,
+           0.05228035430874347,
+           -0.016737460574066394,
+           -0.07991190979773648,
+           -0.13657567264511292,
+           -0.18628952152562409,
+           -0.2288556669289353,
+           -0.2643243262517802,
+           -0.2929933260221104,
+           -0.315400728976505,
+           -0.33231065980044716,
+           -0.34469268148772403,
+           -0.35369524368889455,
+           -0.3606138807907292,
+           -0.3668549768144768,
+           -0.37389603298169094,
+           -0.3832434689273073,
+           -0.39638905758702586,
+           -0.41476613494906434,
+           -0.43970673803693044,
+           -0.47240080730490014,
+           -0.5138585434431832,
+           -0.5648769344959712,
+           -0.6260113689856279,
+           -0.6975531268613493,
+           -0.7795133955998513,
+           -0.8716142972504513,
+           -0.9732872376427112,
+           -1.0836787057017774,
+           -1.2016634634109147,
+           -1.3258648801029982,
+           -1.4546819831287225,
+           -1.5863226250961566,
+           -1.7188420101269308,
+           -1.8501856819104565,
+           -1.9782359582998101,
+           -2.1008607037920526,
+           -2.21596326487727,
+           -2.3215323556637273,
+           -2.4156906734205066,
+           -2.496741046015592,
+           -2.5632089652140166,
+           -2.6138804402485745,
+           -2.6478342130901598,
+           -2.664467507870093,
+           -2.6635146387883637,
+           -2.6450579699042347,
+           -2.6095309023423248,
+           -2.557712755221331,
+           -2.490715601366528,
+           -2.409963312837221,
+           -2.317163259733956,
+           -2.2142712840242322,
+           -2.1034507338582396,
+           -1.9870264890088063,
+           -1.8674350310824983,
+           -1.747171709973239,
+           -1.6287364282397738,
+           -1.514579005934987,
+           -1.4070454988659937,
+           -1.308326723032035,
+           -1.2204101875366307,
+           -1.1450365588055615,
+           -1.0836616723795363,
+           -1.0374249774690132,
+           -1.0071251470403244,
+           -0.9932034161500146,
+           -0.9957350276937071,
+           -1.0144289721518844,
+           -1.04863601098308,
+           -1.0973647768250645,
+           -1.1593055523938496,
+           -1.2328611485651788,
+           -1.3161841349854617,
+           -1.4072195277377157,
+           -1.5037519116795715,
+           -1.6034558731308244,
+           -1.7039485440579982,
+           -1.8028430135487288,
+           -1.8978013472371225,
+           -1.9865859707377176,
+           -2.067108218624972,
+           -2.137472924874344,
+           -2.1960180320691856,
+           -2.241348322522483,
+           -2.272362521615731,
+           -2.288273188451467,
+           -2.288618987257029,
+           -2.273269120444581,
+           -2.2424198961908366,
+           -2.196583595112189,
+           -2.1365699873561663,
+           -2.0634610286212243,
+           -1.9785794269122157,
+           -1.8834519172510966,
+           -1.779768205555681,
+           -1.6693366424765022,
+           -1.55403776075858,
+           -1.4357768539566782,
+           -1.316436789077868,
+           -1.1978322306874072,
+           -1.0816664096682564,
+           -0.9694914973752227,
+           -0.8626735472723691,
+           -0.7623628438374357,
+           -0.6694703556945983,
+           -0.5846508302376776,
+           -0.5082928944848258,
+           -0.44051634593030153,
+           -0.3811766323006692,
+           -0.3298763350407721,
+           -0.28598329268186506,
+           -0.24865483146931092,
+           -0.2168674159838361,
+           -0.18945089585150526,
+           -0.1651264094185494,
+           -0.14254691434112854,
+           -0.1203392506657644,
+           -0.0971466057426656,
+           -0.07167024310099808,
+           -0.042709379370786074,
+           -0.009198143874811271,
+           0.029761366669565647,
+           0.07487082279600997,
+           0.12661294497851133,
+           0.18523494783935313,
+           0.25073859835765694,
+           0.3228771678811379,
+           0.40115937775939076,
+           0.4848602556937593,
+           0.5730386390739864,
+           0.6645608872370314,
+           0.758130201169902,
+           0.8523208008460467,
+           0.9456160809168469,
+           1.03644975818876,
+           1.123248941960636,
+           1.2044780030085411,
+           1.278682090243056,
+           1.3445291465677625,
+           1.4008493072439645,
+           1.446670624387371,
+           1.4812501486411642,
+           1.504099511458142,
+           1.5150042860236121,
+           1.5140365583398527,
+           1.5015603085722822,
+           1.4782293822407295,
+           1.4449780167597237,
+           1.4030040765515026,
+           1.3537453347815325,
+           1.298849317068215,
+           1.2401373878415642,
+           1.1795639092055492,
+           1.1191714314212506,
+           1.0610429801883616,
+           1.0072525860431134,
+           0.9598152533327797,
+           0.9206375889823005,
+           0.8914703039736543,
+           0.8738637631948313,
+           0.8691276929051596,
+           0.8782960610536477,
+           0.9020980263095216,
+           0.9409357097825103,
+           0.9948693824505512,
+           1.063610485177412,
+           1.146522711177125,
+           1.242631187427259,
+           1.3506395965745954,
+           1.4689548890868311,
+           1.5957190514856698,
+           1.7288472249660771,
+           1.8660713137818918,
+           2.0049880882755264,
+           2.143110676668495,
+           2.2779222554515055,
+           2.4069306925102576,
+           2.527722871392575,
+           2.6380174300250987,
+           2.735714682634374,
+           2.818942558782105
+          ],
+          [
+           2.8682078735618104,
+           2.9247436635646467,
+           2.9632281622885337,
+           2.982911936658756,
+           2.983406521138876,
+           2.9646920920344906,
+           2.927116835305598,
+           2.8713880368413895,
+           2.798555120414566,
+           2.7099850491586626,
+           2.6073306867709034,
+           2.492492880358694,
+           2.367577173905516,
+           2.2348461861778812,
+           2.096668786522678,
+           1.955467274028432,
+           1.8136638082389844,
+           1.6736273520288476,
+           1.5376223691355426,
+           1.4077604707048945,
+           1.28595612828605,
+           1.1738874669645614,
+           1.0729630243507513,
+           0.9842952121443311,
+           0.9086810506838754,
+           0.8465905673891544,
+           0.7981630617605806,
+           0.7632112472640644,
+           0.7412330887440567,
+           0.7314309676886879,
+           0.7327376312922298,
+           0.7438482191393154,
+           0.7632575174279455,
+           0.789301468449935,
+           0.8202018655082456,
+           0.8541130929025661,
+           0.8891697287147714,
+           0.9235338158166312,
+           0.9554406240081773,
+           0.9832417729400684,
+           1.0054446602137823,
+           1.0207472398319652,
+           1.0280673203854616,
+           1.026565696832534,
+           1.0156625907692844,
+           0.9950470476223833,
+           0.964679120825119,
+           0.9247848581812932,
+           0.8758442896146514,
+           0.818572793717479,
+           0.7538963884767147,
+           0.6829216450593396,
+           0.6069010587404274,
+           0.5271948245811756,
+           0.44523005448375397,
+           0.36245853455728544,
+           0.2803141557910957,
+           0.20017115602591584,
+           0.12330428705132646,
+           0.050851967982754084,
+           -0.016216593754525756,
+           -0.07712943743890374,
+           -0.1313342910298216,
+           -0.1785148176263943,
+           -0.2186002259412818,
+           -0.25176797769283144,
+           -0.2784395051402614,
+           -0.29926903468525134,
+           -0.31512579290137605,
+           -0.327070044947932,
+           -0.33632357766380877,
+           -0.3442353865878987,
+           -0.3522434539666234,
+           -0.36183361021653593,
+           -0.37449655160112083,
+           -0.39168413997524654,
+           -0.41476613494906417,
+           -0.4449885040434346,
+           -0.48343442240403384,
+           -0.5309890111982074,
+           -0.5883087744398168,
+           -0.6557965798538864,
+           -0.7335828933105591,
+           -0.8215138216882206,
+           -0.9191463496022059,
+           -1.0257509754689247,
+           -1.1403217663490546,
+           -1.2615936635714362,
+           -1.3880666869719032,
+           -1.5180365093061507,
+           -1.6496307084451707,
+           -1.7808498574701344,
+           -1.9096124854848744,
+           -2.033802838098332,
+           -2.1513202887609033,
+           -2.2601292024896855,
+           -2.3583080333163227,
+           -2.4440964466382438,
+           -2.51593929740605,
+           -2.572526363852594,
+           -2.6128268326572637,
+           -2.6361176527559183,
+           -2.6420050185395505,
+           -2.63043840546541,
+           -2.6017167581953657,
+           -2.5564866189670497,
+           -2.4957321774158734,
+           -2.420757417768709,
+           -2.3331607304530975,
+           -2.234802538019983,
+           -2.1277666553701207,
+           -2.014316257417563,
+           -1.8968454597429587,
+           -1.7778276262121573,
+           -1.6597615992762635,
+           -1.5451171016915826,
+           -1.4362805813704107,
+           -1.3355027633984555,
+           -1.2448491350858677,
+           -1.1661545221573177,
+           -1.10098281845836,
+           -1.050592810173113,
+           -1.0159108914522834,
+           -0.997511305039373,
+           -0.9956043629245448,
+           -1.0100329125922065,
+           -1.0402771186680473,
+           -1.0854674324753544,
+           -1.144405427976221,
+           -1.2155919965158801,
+           -1.2972622192252086,
+           -1.3874260790754738,
+           -1.4839140382166007,
+           -1.584426393655813,
+           -1.6865852382515851,
+           -1.7879877964601718,
+           -1.8862598766280867,
+           -1.9791081844881797,
+           -2.0643702757547358,
+           -2.140060988443827,
+           -2.2044142861658336,
+           -2.2559195598623005,
+           -2.293351574377342,
+           -2.3157934044009973,
+           -2.3226518777676146,
+           -2.313665228536377,
+           -2.288902853161555,
+           -2.2487572556654483,
+           -2.1939284573133113,
+           -2.1254013281972286,
+           -2.044416467905879,
+           -1.952435415939773,
+           -1.8511011059897835,
+           -1.7421945883979473,
+           -1.6275891294142035,
+           -1.5092028522505314,
+           -1.3889511121109184,
+           -1.2686997947670362,
+           -1.1502206960215815,
+           -1.035150078456601,
+           -0.9249514138190004,
+           -0.8208832065363535,
+           -0.7239726590841505,
+           -0.634995786682144,
+           -0.5544644209778422,
+           -0.48262036423109606,
+           -0.4194367715464746,
+           -0.3646266535489987,
+           -0.3176582102229824,
+           -0.27777653299844507,
+           -0.2440310509303204,
+           -0.2153079520102764,
+           -0.19036668589900924,
+           -0.16787955277921016,
+           -0.14647330713127638,
+           -0.12477165690144573,
+           -0.10143751894681849,
+           -0.0752139012606742,
+           -0.04496232102624723,
+           -0.009697734011556958,
+           0.03138095650661383,
+           0.07886562658301673,
+           0.13311957210817474,
+           0.1942645861002151,
+           0.26217482768063916,
+           0.3364776602213596,
+           0.4165614540617361,
+           0.5015901670470592,
+           0.5905243385586507,
+           0.6821479642021694,
+           0.7751005631809155,
+           0.8679136125580762,
+           0.9590504056257418,
+           1.0469482984486638,
+           1.1300622417397566,
+           1.2069084562975927,
+           1.276107100337512,
+           1.3364227964934263,
+           1.38680193463545,
+           1.4264057427911234,
+           1.4546382205276025,
+           1.4711681546477668,
+           1.4759445828813862,
+           1.469205233804537,
+           1.4514776464620198,
+           1.4235728567373733,
+           1.3865717248359135,
+           1.3418041646359826,
+           1.2908217164535847,
+           1.2353640754170976,
+           1.177320343864322,
+           1.1186859140081913,
+           1.0615160030707422,
+           1.0078769541972756,
+           0.9597964803823263,
+           0.919214063685858,
+           0.8879327272248663,
+           0.8675733725620075,
+           0.8595328206950852,
+           0.8649466121272187,
+           0.8846575124192109,
+           0.9191905368011575,
+           0.9687351540493753,
+           1.0331351596317728,
+           1.1118865252266195,
+           1.2041433405842612,
+           1.308731768997785,
+           1.4241717441429405,
+           1.5487059484830024,
+           1.680335436417067,
+           1.8168611032334818,
+           1.9559300577072025,
+           2.0950858353854964,
+           2.2318212942289604,
+           2.3636329666832148,
+           2.488075604138452,
+           2.6028156420586184,
+           2.7056823370512237,
+           2.794715380273217,
+           2.8682078735618077
+          ],
+          [
+           2.9101277568626367,
+           2.9555602435711545,
+           2.982404327068349,
+           2.990136266743473,
+           2.978599202128635,
+           2.9480057963874797,
+           2.8989325635704675,
+           2.832306025657911,
+           2.749381038965458,
+           2.6517118146537793,
+           2.5411163303693876,
+           2.4196349852696724,
+           2.289484485095945,
+           2.153008054310226,
+           2.012623155953949,
+           1.8707679548260023,
+           1.7298477845262241,
+           1.5921828733180128,
+           1.4599585478294197,
+           1.3351790682799578,
+           1.2196261558542372,
+           1.1148231543862126,
+           1.0220056276318958,
+           0.9420990336027506,
+           0.8757039426745943,
+           0.8230890808058616,
+           0.784192287776277,
+           0.758629287613123,
+           0.7457099790513815,
+           0.7444617726251608,
+           0.7536593322508041,
+           0.771859927057574,
+           0.7974434674500247,
+           0.8286561911355375,
+           0.8636568827198283,
+           0.9005644564076372,
+           0.9375057065900525,
+           0.9726620361680798,
+           1.0043140071261216,
+           1.030882621165736,
+           1.050966328465656,
+           1.0633728775074418,
+           1.0671452554475707,
+           1.0615811232428005,
+           1.046245318715692,
+           1.0209751797035964,
+           0.9858786238477153,
+           0.9413251068025686,
+           0.8879297620218058,
+           0.8265311982499058,
+           0.7581635910855941,
+           0.6840238484724247,
+           0.6054347531322619,
+           0.5238050847207952,
+           0.44058779837507045,
+           0.35723738251878845,
+           0.27516753616751394,
+           0.195710294134682,
+           0.1200776878175083,
+           0.049326960703411644,
+           -0.015669736854245272,
+           -0.07425036726882633,
+           -0.125982072287598,
+           -0.17067377495807828,
+           -0.20838197452540044,
+           -0.23940956969590504,
+           -0.2642977279263734,
+           -0.2838110003179892,
+           -0.29891605869000654,
+           -0.3107545989829856,
+           -0.32061110903251183,
+           -0.3298763350407718,
+           -0.340007396274205,
+           -0.35248558867755414,
+           -0.36877298286669163,
+           -0.39026895865471284,
+           -0.4182678258921791,
+           -0.4539186597068313,
+           -0.4981884276908947,
+           -0.5518294084109274,
+           -0.6153517967075002,
+           -0.6890022641606725,
+           -0.7727490959588765,
+           -0.866274361868893,
+           -0.9689734031262719,
+           -1.0799617332292228,
+           -1.1980892634135119,
+           -1.3219615776933555,
+           -1.4499678024343832,
+           -1.5803144459998477,
+           -1.711064429350348,
+           -1.8401803924912157,
+           -1.9655712478051677,
+           -2.085140862492751,
+           -2.1968376908651015,
+           -2.298704144714175,
+           -2.388924487330827,
+           -2.4658700641180338,
+           -2.5281407395775544,
+           -2.5746014954253797,
+           -2.6044132557056483,
+           -2.617057139365529,
+           -2.6123514955792784,
+           -2.590461248416382,
+           -2.551899261070055,
+           -2.4975196213200905,
+           -2.4285029445179385,
+           -2.3463339833860086,
+           -2.252772020582357,
+           -2.1498146957094866,
+           -2.0396560789173384,
+           -1.9246399445086104,
+           -1.807209316510198,
+           -1.689853451090043,
+           -1.5750534856639709,
+           -1.4652280199231498,
+           -1.362679898916795,
+           -1.2695454425884303,
+           -1.18774731038123,
+           -1.1189521050287459,
+           -1.0645337084657254,
+           -1.025543207618971,
+           -1.0026861119467025,
+           -0.996307391772505,
+           -1.0063846809061527,
+           -1.03252979327032,
+           -1.0739985059716706,
+           -1.1297083652641446,
+           -1.1982640819153163,
+           -1.2779899032168882,
+           -1.3669681846275514,
+           -1.4630832387793347,
+           -1.5640694168280798,
+           -1.667562279840757,
+           -1.7711516484163792,
+           -1.872435278678738,
+           -1.9690719030799588,
+           -2.0588323952898193,
+           -2.139647869243675,
+           -2.209653601873406,
+           -2.2672277751413743,
+           -2.311024163076355,
+           -2.3399980403264133,
+           -2.353424756546885,
+           -2.3509106015711514,
+           -2.332395775298649,
+           -2.2981494689129174,
+           -2.248757255665448,
+           -2.1851011753174405,
+           -2.1083330718626905,
+           -2.0198419050674006,
+           -1.921215898734074,
+           -1.8142005089718491,
+           -1.7006532912323025,
+           -1.5824968131687418,
+           -1.4616707998987766,
+           -1.3400847081121832,
+           -1.2195719055258305,
+           -1.1018465830420403,
+           -0.9884644499388053,
+           -0.8807881595242814,
+           -0.7799582865769891,
+           -0.6868705317943438,
+           -0.6021596661040888,
+           -0.5261905531730534,
+           -0.45905640618769067,
+           -0.4005842495782416,
+           -0.3503473724808345,
+           -0.3076843829992529,
+           -0.27172430519952295,
+           -0.2414170084311378,
+           -0.21556812482644516,
+           -0.19287749902011125,
+           -0.1719801270337555,
+           -0.1514884810427793,
+           -0.13003508486088797,
+           -0.10631420220658984,
+           -0.07912152618563097,
+           -0.047390813231100996,
+           -0.01022648657080601,
+           0.033068658958130305,
+           0.08297138997904031,
+           0.13972219689743492,
+           0.20331611382100068,
+           0.27350045038591975,
+           0.349779509159768,
+           0.4314261796389146,
+           0.517500119828105,
+           0.6068720635546111,
+           0.698253630422612,
+           0.7902318697599616,
+           0.8813076437621464,
+           0.9699368515237796,
+           1.054573417427329,
+           1.1337129164589714,
+           1.2059356867844955,
+           1.269948286967013,
+           1.324622191430918,
+           1.369028682327073,
+           1.402468987274598,
+           1.4244988283115958,
+           1.4349466849283024,
+           1.4339252298797545,
+           1.4218355667147862,
+           1.3993640783793106,
+           1.3674718823552388,
+           1.327377074932671,
+           1.2805301306958163,
+           1.2285829985274113,
+           1.1733525979937616,
+           1.1167795657589248,
+           1.060883226998629,
+           1.0077138684475873,
+           0.959303465107325,
+           0.917616059799657,
+           0.8844990124059772,
+           0.8616363232466093,
+           0.850505192832624,
+           0.8523369091111183,
+           0.8680830549869347,
+           0.8983879056801259,
+           0.9435677403307625,
+           1.0035976286999633,
+           1.0781060758100074,
+           1.1663777192526295,
+           1.26736408026647,
+           1.379702175279737,
+           1.5017406041983266,
+           1.6315725499672609,
+           1.7670749553147973,
+           1.905952991257186,
+           2.0457888016325136,
+           2.1840934018678064,
+           2.31836053099656,
+           2.4461212056105306,
+           2.5649977042183587,
+           2.6727557209282233,
+           2.7673534682530923,
+           2.8469865791899522,
+           2.9101277568626345
+          ],
+          [
+           2.9443475475028977,
+           2.9782865045289233,
+           2.993245522770234,
+           2.9889309972823366,
+           2.9654190199666512,
+           2.9231529698650562,
+           2.862932847832549,
+           2.785896617441127,
+           2.6934940031742407,
+           2.587453375112324,
+           2.4697425120635703,
+           2.342524178517639,
+           2.2081075714264715,
+           2.0688967877408766,
+           1.9273375305809766,
+           1.785863309308201,
+           1.6468423957378118,
+           1.5125267751725777,
+           1.3850042774876508,
+           1.2661549915244616,
+           1.1576129576258265,
+           1.0607340009804227,
+           0.9765704158360202,
+           0.9058530413778574,
+           0.8489810883446633,
+           0.8060198857619076,
+           0.7767065241894965,
+           0.7604631803601087,
+           0.7564177227297718,
+           0.7634310228168992,
+           0.7801302375382286,
+           0.8049471869487858,
+           0.8361608332716758,
+           0.8719427737164707,
+           0.910404593557689,
+           0.9496458888191834,
+           0.9878017605079138,
+           1.0230886047432675,
+           1.0538470746769206,
+           1.0785811694111558,
+           1.0959925101307182,
+           1.1050089916596764,
+           1.1048071453682327,
+           1.094827713028445,
+           1.0747841067047923,
+           1.0446636126321882,
+           1.0047213826705395,
+           0.9554674406618204,
+           0.8976471082391269,
+           0.8322154209050536,
+           0.760306256348881,
+           0.6831970292339244,
+           0.6022699167633502,
+           0.5189706644915761,
+           0.4347660799854183,
+           0.3511013516323626,
+           0.26935833043728413,
+           0.19081588407207598,
+           0.11661337550599277,
+           0.04771823472237309,
+           -0.015101516530056891,
+           -0.07129905752393724,
+           -0.12056429861090785,
+           -0.16283273228976225,
+           -0.19828736371208106,
+           -0.2273536599848986,
+           -0.2506876402149032,
+           -0.26915740784030595,
+           -0.28381859885275523,
+           -0.29588437964857167,
+           -0.30669077238959774,
+           -0.31765821022298213,
+           -0.3302503263221787,
+           -0.3459310568569931,
+           -0.36612118670545724,
+           -0.3921554866997735,
+           -0.4252415818884971,
+           -0.46642165186926693,
+           -0.5165379976044925,
+           -0.576203415890536,
+           -0.6457772050935299,
+           -0.7253474867910069,
+           -0.814720371008988,
+           -0.9134163217175647,
+           -1.0206738984028367,
+           -1.135460863382306,
+           -1.2564924577298937,
+           -1.3822564659064087,
+           -1.5110445150430512,
+           -1.6409888936842965,
+           -1.7701040307337546,
+           -1.8963316520165237,
+           -2.0175885324204774,
+           -2.131815688565969,
+           -2.2370278122859877,
+           -2.3313617300841596,
+           -2.413122688652174,
+           -2.4808273112033237,
+           -2.533242142808118,
+           -2.5694168033802613,
+           -2.588710892061925,
+           -2.590813933487255,
+           -2.5757578212118917,
+           -2.5439213924797843,
+           -2.4960269570966567,
+           -2.433128796884411,
+           -2.3565938462594174,
+           -2.2680749541502934,
+           -2.1694773080868126,
+           -2.0629187684058508,
+           -1.9506850100131674,
+           -1.8351804973175871,
+           -1.7188764216430907,
+           -1.604256807046456,
+           -1.4937640381083797,
+           -1.3897450807164582,
+           -1.2943996536523859,
+           -1.2097315652159988,
+           -1.1375043561939941,
+           -1.0792022899591605,
+           -1.0359976047916057,
+           -1.0087247956897927,
+           -0.9978625265711687,
+           -1.0035235928907347,
+           -1.0254531637265643,
+           -1.0630353359375553,
+           -1.115307835867064,
+           -1.1809845110388073,
+           -1.258485070058706,
+           -1.3459713579708086,
+           -1.4413893007625946,
+           -1.5425155202906944,
+           -1.6470075127983774,
+           -1.7524562030178616,
+           -1.8564396335284745,
+           -1.9565765268012054,
+           -2.050578465687693,
+           -2.1362994767430434,
+           -2.2117818687001187,
+           -2.27529727391308,
+           -2.325381961260808,
+           -2.36086563183304,
+           -2.380893070160003,
+           -2.3849381997858594,
+           -2.3728102782714826,
+           -2.3446521586425675,
+           -2.3009307371452707,
+           -2.2424198961908366,
+           -2.170176431924652,
+           -2.085509623524616,
+           -1.9899452520275192,
+           -1.8851850065376723,
+           -1.773062321945776,
+           -1.6554957722304184,
+           -1.5344411951400596,
+           -1.4118437463747107,
+           -1.2895910738506016,
+           -1.1694687655278553,
+           -1.0531191586341264,
+           -0.9420045056576178,
+           -0.8373753756064993,
+           -0.7402450307358698,
+           -0.6513703627537909,
+           -0.571239802399037,
+           -0.5000684365390107,
+           -0.4378003821024695,
+           -0.3841182808923176,
+           -0.3384595982754618,
+           -0.3000392364611047,
+           -0.26787781387094173,
+           -0.24083481995417394,
+           -0.21764573325258812,
+           -0.19696209259965086,
+           -0.17739343946846103,
+           -0.15755000543495387,
+           -0.1360850035618259,
+           -0.11173539657487762,
+           -0.08336005760078284,
+           -0.04997430984238905,
+           -0.010779928066643915,
+           0.03481019529768118,
+           0.08715337636787124,
+           0.146364958152853,
+           0.2123129509813291,
+           0.2846196465805095,
+           0.3626701750351887,
+           0.4456277921861782,
+           0.5324555086370331,
+           0.6219435049109717,
+           0.7127416246742374,
+           0.8033961032063874,
+           0.892389574893403,
+           0.9781833143524902,
+           1.0592606031677896,
+           1.1341700797582068,
+           1.2015679245395134,
+           1.260257756479568,
+           1.3092271698389009,
+           1.3476799200758507,
+           1.3750628736209696,
+           1.3910869648895219,
+           1.395741552323977,
+           1.3893017297590855,
+           1.3723283258891987,
+           1.3456605086917934,
+           1.3104010987235786,
+           1.2678948805740613,
+           1.219700380784954,
+           1.1675557487200092,
+           1.1133395299577216,
+           1.0590272559031584,
+           1.0066448850649774,
+           0.9582202179564415,
+           0.915733466615965,
+           0.8810681897400929,
+           0.8559638045357042,
+           0.8419708565244438,
+           0.8404101693094539,
+           0.8523369091111179,
+           0.8785104857584576,
+           0.9193710754963316,
+           0.9750233947256657,
+           1.0452281814232804,
+           1.1294016566848157,
+           1.2266230470964357,
+           1.3356500541583294,
+           1.4549419645214938,
+           1.5826899090843756,
+           1.7168536045934841,
+           1.8552037525989058,
+           1.995369131349969,
+           2.1348872999226707,
+           2.2712577434336323,
+           2.4019962258687872,
+           2.524689084405774,
+           2.6370461969756547,
+           2.736951383285906,
+           2.8225090579542313,
+           2.8920860413887564,
+           2.944347547502896
+          ],
+          [
+           2.970577730569145,
+           2.9927301719864996,
+           2.9956600279728542,
+           2.9793063254003775,
+           2.9439774849581135,
+           2.8903438786256315,
+           2.8194222619770426,
+           2.7325524567850477,
+           2.6313668426528807,
+           2.517753386010092,
+           2.393813086653341,
+           2.261812852420753,
+           2.124134918410213,
+           1.9832240058457917,
+           1.8415334653866011,
+           1.701471669195899,
+           1.565349905023264,
+           1.4353329842276485,
+           1.3133937051545215,
+           1.2012722153615085,
+           1.100441193319122,
+           1.0120776254606254,
+           0.9370417914145852,
+           0.875863892965372,
+           0.8287385751339436,
+           0.7955273953712624,
+           0.7757691039475297,
+           0.7686974099425359,
+           0.7732657274223995,
+           0.7881782298235976,
+           0.8119263913175505,
+           0.8428300656221152,
+           0.87908204845824,
+           0.918794992116698,
+           0.9600494912345588,
+           1.000942139009402,
+           1.0396323630929856,
+           1.0743868899537656,
+           1.1036207544951258,
+           1.125933866374332,
+           1.1401422633375025,
+           1.1453033219223845,
+           1.1407343535165189,
+           1.1260241849956274,
+           1.1010375036762492,
+           1.0659119315464445,
+           1.0210479790275053,
+           0.9670922092151201,
+           0.9049141151204667,
+           0.8355773705871202,
+           0.7603062563488809,
+           0.6804481826087367,
+           0.5974333255814781,
+           0.5127324652762574,
+           0.42781415368673165,
+           0.3441023554958926,
+           0.2629356871095795,
+           0.18552933476197325,
+           0.1129406597665545,
+           0.0460394005893948,
+           -0.01451674018302587,
+           -0.06830047762016109,
+           -0.11512680681662653,
+           -0.15505802839053245,
+           -0.18840179847666785,
+           -0.2157022470113284,
+           -0.23772438950652472,
+           -0.25543223327538916,
+           -0.26996114473152377,
+           -0.2825851957291103,
+           -0.29468034008208976,
+           -0.3076843829992526,
+           -0.32305479333746323,
+           -0.3422254690600145,
+           -0.3665635985128933,
+           -0.39732776322950353,
+           -0.4356284018066287,
+           -0.4823916995593787,
+           -0.5383278864800829,
+           -0.6039048185043917,
+           -0.6793275868753056,
+           -0.7645247507150364,
+           -0.8591416224817511,
+           -0.9625408589219357,
+           -1.07381042584712,
+           -1.1917788181734361,
+           -1.3150372318465364,
+           -1.4419682061725652,
+           -1.57078008817171,
+           -1.6995465190765864,
+           -1.8262500108519628,
+           -1.948828570981739,
+           -2.065224249564869,
+           -2.173432426168807,
+           -2.2715506264101024,
+           -2.357825660649683,
+           -2.4306979095473733,
+           -2.488841642815541,
+           -2.5312003469179998,
+           -2.55701615255804,
+           -2.5658525908279213,
+           -2.5576100645180118,
+           -2.532533594481365,
+           -2.4912125858963647,
+           -2.4345725512492917,
+           -2.3638589211719174,
+           -2.2806132661508145,
+           -2.1866424368615123,
+           -2.0839813039254644,
+           -1.9748499349749193,
+           -1.8616061841604048,
+           -1.7466947832485904,
+           -1.632594111403304,
+           -1.521761880422929,
+           -1.4165810021197038,
+           -1.3193069038936154,
+           -1.2320175273492837,
+           -1.1565671837498201,
+           -1.094545350651779,
+           -1.0472413783710468,
+           -1.015615935785818,
+           -1.000279865760917,
+           -1.0014809450406565,
+           -1.019098856067234,
+           -1.0526484833925323,
+           -1.101291449899033,
+           -1.163855612730628,
+           -1.238862050403368,
+           -1.3245588955963892,
+           -1.4189612069084636,
+           -1.5198959313118963,
+           -1.6250508905644498,
+           -1.7320266323056686,
+           -1.83838992218211,
+           -1.9417276186405705,
+           -2.03969966779411,
+           -2.130089982049488,
+           -2.210854022284503,
+           -2.2801619878476553,
+           -2.3364366293932917,
+           -2.378384833794495,
+           -2.4050222847531537,
+           -2.415690673420506,
+           -2.4100671161281215,
+           -2.3881656266940055,
+           -2.350330684018967,
+           -2.297223127070831,
+           -2.229798794170457,
+           -2.1492804972175725,
+           -2.057124079883674,
+           -1.954979447999342,
+           -1.844647577002714,
+           -1.7280345925890457,
+           -1.6071040844370619,
+           -1.4838288476020947,
+           -1.3601432510981455,
+           -1.2378974083206575,
+           -1.1188142700094226,
+           -1.0044506788577414,
+           -0.8961633177650219,
+           -0.7950803538621077,
+           -0.7020794311278646,
+           -0.617772499456585,
+           -0.5424977916053317,
+           -0.47631907600283063,
+           -0.4190321275576542,
+           -0.37017817503472095,
+           -0.32906390688193704,
+           -0.29478745200771883,
+           -0.26626960206989847,
+           -0.24228941107738713,
+           -0.2215231997812915,
+           -0.20258590912764549,
+           -0.18407369101057733,
+           -0.16460659706857123,
+           -0.14287022795443016,
+           -0.11765523629420768,
+           -0.08789363561240025,
+           -0.05269095330973434,
+           -0.011353376133580754,
+           0.036590831339779674,
+           0.09137620425228958,
+           0.1529916551083243,
+           0.22117898026770866,
+           0.29543834283310844,
+           0.375040596981223,
+           0.45904613963507424,
+           0.5463298041171294,
+           0.6356111514139529,
+           0.7254893719697849,
+           0.8144818881483524,
+           0.9010656477998441,
+           0.9837200253047755,
+           1.0609701999577064,
+           1.1314298638290823,
+           1.1938421228076743,
+           1.2471174951481163,
+           1.2903679805663701,
+           1.3229362680708536,
+           1.3444192699531563,
+           1.354685309744972,
+           1.353884449997148,
+           1.3424516175227643,
+           1.3211023649874414,
+           1.2908212939001666,
+           1.2528433504967416,
+           1.208628388040359,
+           1.159829562113418,
+           1.1082562851798945,
+           1.0558326090207857,
+           1.0045520249716213,
+           0.9564297691231249,
+           0.9134537902765921,
+           0.8775355806260821,
+           0.8504620817224375,
+           0.8338498608459508,
+           0.8291027058055647,
+           0.8373737104595533,
+           0.8595328206950844,
+           0.8961406836589939,
+           0.9474294947561899,
+           1.0132913709158402,
+           1.0932745989052481,
+           1.1865879184304822,
+           1.2921128060231573,
+           1.4084235320209582,
+           1.5338145740596782,
+           1.6663347910517734,
+           1.8038275960494172,
+           1.9439762187656335,
+           2.084353022505382,
+           2.2224717389646096,
+           2.3558414103110135,
+           2.4820207830214405,
+           2.598671883261966,
+           2.7036115195592982,
+           2.794859504779252,
+           2.8706824649075804,
+           2.9296322050116888,
+           2.9705777305691443
+          ],
+          [
+           2.988596386843346,
+           2.9987690459813585,
+           2.989627414869619,
+           2.961343680176932,
+           2.9144560021915997,
+           2.8498561024273745,
+           2.768768925249051,
+           2.6727248594273316,
+           2.5635251812922495,
+           2.443201540794494,
+           2.3139704514361275,
+           2.178183861320086,
+           2.0382769726897454,
+           1.8967145391271807,
+           1.7559369015891495,
+           1.6183070259520989,
+           1.486059775729798,
+           1.361254594885208,
+           1.245732688676124,
+           1.141079677437228,
+           1.0485945619306778,
+           0.9692656827809791,
+           0.9037541844171028,
+           0.8523853101311089,
+           0.8151476638640387,
+           0.7917003808505375,
+           0.7813879580498111,
+           0.7832623110521058,
+           0.7961114513857559,
+           0.8184940210757407,
+           0.848778783739873,
+           0.8851880567817875,
+           0.9258439801071672,
+           0.968816455367683,
+           1.012171557451519,
+           1.0540192174898655,
+           1.0925590039937836,
+           1.1261228850939546,
+           1.153213938726628,
+           1.1725400868116163,
+           1.1830420611958883,
+           1.183914960028151,
+           1.174622919454248,
+           1.1549066028749408,
+           1.1247833940118865,
+           1.0845403660533768,
+           1.0347202825255633,
+           0.9761010616602391,
+           0.9096693004992513,
+           0.8365886036804953,
+           0.7581635910855941,
+           0.6758005650831779,
+           0.5909658993366267,
+           0.505143265063018,
+           0.4197908359212799,
+           0.3362996087837748,
+           0.2559539446532316,
+           0.17989537280372805,
+           0.10909061343627195,
+           0.04430466200092287,
+           -0.013920355285662414,
+           -0.0652799969003567,
+           -0.10971560054582676,
+           -0.14741544077347002,
+           -0.1788089151743217,
+           -0.2045539070012755,
+           -0.2255176507681686,
+           -0.24275159781077008,
+           -0.2574609366587472,
+           -0.27096956433850955,
+           -0.284681425802092,
+           -0.3000392364611045,
+           -0.3184816747851249,
+           -0.34140017623617813,
+           -0.37009647528491524,
+           -0.4057420284439796,
+           -0.4493404084499769,
+           -0.5016936889471794,
+           -0.5633737419977412,
+           -0.6346992498513536,
+           -0.7157190906412326,
+           -0.8062025985520497,
+           -0.9056370264888606,
+           -1.0132323576681506,
+           -1.1279334263923897,
+           -1.2484391222209155,
+           -1.373228270482601,
+           -1.5005916101493026,
+           -1.6286691318410365,
+           -1.7554918981682712,
+           -1.8790273493068261,
+           -1.9972270016972897,
+           -2.1080753795158924,
+           -2.2096389788693567,
+           -2.300114054608205,
+           -2.3778720395830955,
+           -2.441501455694774,
+           -2.4898452540827196,
+           -2.522032626424353,
+           -2.5375044580760293,
+           -2.5360317435755753,
+           -2.517726452214202,
+           -2.4830445119050246,
+           -2.432780769020827,
+           -2.368055975609864,
+           -2.2902960486761135,
+           -2.201204034281454,
+           -2.1027253874645617,
+           -1.9970073429808997,
+           -1.8863532975991202,
+           -1.773173248534393,
+           -1.659931431482886,
+           -1.5490923731786568,
+           -1.443066615628077,
+           -1.3441573811081309,
+           -1.254509428304182,
+           -1.1760613010242473,
+           -1.110502092914255,
+           -1.0592337463806445,
+           -1.0233397740389178,
+           -1.0035611395909623,
+           -1.0002798657609167,
+           -1.013510753897561,
+           -1.0429014075276422,
+           -1.0877405551936596,
+           -1.1469744711195493,
+           -1.2192311004019774,
+           -1.3028513131849175,
+           -1.3959265440655706,
+           -1.4963419228795578,
+           -1.601823874656354,
+           -1.7099910630204038,
+           -1.8184074751273307,
+           -1.9246363991839217,
+           -2.026294028805364,
+           -2.121101442271,
+           -2.206933748757551,
+           -2.2818652667226007,
+           -2.3442096999359463,
+           -2.392554401700805,
+           -2.425787964456726,
+           -2.443120536571877,
+           -2.4440964466382433,
+           -2.4285989035704527,
+           -2.3968467336426915,
+           -2.3493833085335996,
+           -2.28705800674854,
+           -2.2110007298385157,
+           -2.1225901602593416,
+           -2.0234165954836714,
+           -1.9152403195071543,
+           -1.7999465751264603,
+           -1.679498275867297,
+           -1.5558876434284532,
+           -1.4310879739173665,
+           -1.307006723653862,
+           -1.1854410633243841,
+           -1.068036978924039,
+           -0.9562529010745323,
+           -0.851328723453963,
+           -0.7542609293137795,
+           -0.6657843859957883,
+           -0.586361195029427,
+           -0.5161768041401954,
+           -0.4551434019013576,
+           -0.4029104304794258,
+           -0.35888187160897694,
+           -0.32223979010104836,
+           -0.29197346211203035,
+           -0.2669132759959542,
+           -0.2457684753016651,
+           -0.22716771929114893,
+           -0.20970136857146232,
+           -0.19196436370920966,
+           -0.1725985539852669,
+           -0.15033335196999031,
+           -0.12402363684179649,
+           -0.09268390409903751,
+           -0.055517759600107935,
+           -0.011941979141482028,
+           0.03839550209776263,
+           0.09560414659754175,
+           0.15954622290899104,
+           0.2298391910604526,
+           0.3058650080779037,
+           0.38678611563052745,
+           0.4715676966943134,
+           0.5590056234504421,
+           0.6477593685894588,
+           0.7363890205987123,
+           0.8233954338288728,
+           0.9072624589787135,
+           0.9865001413005889,
+           1.0596877438346348,
+           1.12551545213832,
+           1.1828236453675944,
+           1.2306386755295577,
+           1.268204180888452,
+           1.2950070688046744,
+           1.3107974350245761,
+           1.315601837352406,
+           1.3097295079740552,
+           1.2937712663202272,
+           1.268591078818754,
+           1.2353103985765954,
+           1.1952856022699043,
+           1.1500790186767924,
+           1.1014242088990234,
+           1.0511863082019297,
+           1.0013183697562584,
+           0.9538147580683173,
+           0.9106627217765385,
+           0.8737933296432503,
+           0.8450329785378907,
+           0.8260566772699423,
+           0.8183442753070059,
+           0.8231407414679581,
+           0.8414215060988058,
+           0.8738637631948302,
+           0.9208244892365494,
+           0.9823257765361831,
+           1.0580479045062607,
+           1.1473303867127163,
+           1.2491810393955594,
+           1.3622929230378205,
+           1.485068817301264,
+           1.615652705927334,
+           1.7519675765493352,
+           1.8917586850111634,
+           2.032641298581211,
+           2.1721518207385797,
+           2.307801114771624,
+           2.4371287864036217,
+           2.557757158489484,
+           2.6674436742231866,
+           2.76413049921908,
+           2.845990156496704,
+           2.9114661202915983,
+           2.9593074125246663,
+           2.988596386843345
+          ],
+          [
+           2.9982510703398844,
+           2.9963520349068817,
+           2.9751987220971707,
+           2.9351950337187787,
+           2.8771043367699387,
+           2.80203218617785,
+           2.7114013877981886,
+           2.6069199939139227,
+           2.490542990246159,
+           2.364428581811148,
+           2.2308901112350705,
+           2.0923447443229,
+           1.9512601313370275,
+           1.8101002968194628,
+           1.6712720248512354,
+           1.5370729900910736,
+           1.40964283823043,
+           1.290918343839946,
+           1.1825936708688238,
+           1.086086633859894,
+           1.0025117094229075,
+           0.9326603813491793,
+           0.8769892230615853,
+           0.8356159323100255,
+           0.8083233397942501,
+           0.7945712204743222,
+           0.7935155484480753,
+           0.8040346580347386,
+           0.8247616094573025,
+           0.8541219112612827,
+           0.8903756268894056,
+           0.9316627926553823,
+           0.9760510011166924,
+           1.021583959255352,
+           1.0663298159428705,
+           1.1084280681589773,
+           1.1461338998787087,
+           1.1778588802341436,
+           1.2022070465916574,
+           1.218005521008554,
+           1.224328952003614,
+           1.2205172340466366,
+           1.2061861305788357,
+           1.1812306083416837,
+           1.1458208767343263,
+           1.1003913111675936,
+           1.045622619290332,
+           0.9824177790289393,
+           0.91187243335543,
+           0.8352405646956209,
+           0.7538963884767146,
+           0.6692934976045849,
+           0.5829223553813712,
+           0.49626727191981423,
+           0.4107640075879515,
+           0.327759126263977,
+           0.24847217176869588,
+           0.1739616640649041,
+           0.10509580964926518,
+           0.04252869563039396,
+           -0.013317407524065458,
+           -0.06226316999819676,
+           -0.10437646105215827,
+           -0.1399696291881256,
+           -0.16958987393860966,
+           -0.19400295995590622,
+           -0.21417069853317372,
+           -0.23122278536053262,
+           -0.24642373205113,
+           -0.26113575897446706,
+           -0.2767786248889735,
+           -0.29478745200771855,
+           -0.31656966131747644,
+           -0.34346216073622315,
+           -0.37668992728538675,
+           -0.4173270938519889,
+           -0.46626159203758516,
+           -0.5241643164681982,
+           -0.5914636648864093,
+           -0.6683261751075872,
+           -0.754643827802108,
+           -0.8500284168499042,
+           -0.9538132108730061,
+           -1.0650619449386514,
+           -1.1825849949630962,
+           -1.304962403713422,
+           -1.4305732511194809,
+           -1.5576306973115845,
+           -1.6842218785464969,
+           -1.8083517077366622,
+           -1.9279895259329993,
+           -2.041117471538783,
+           -2.1457793823238056,
+           -2.240129022848119,
+           -2.3224764373526408,
+           -2.3913312654475307,
+           -2.445441924205309,
+           -2.4838296539994,
+           -2.5058165443909943,
+           -2.5110467976986905,
+           -2.49950064816673,
+           -2.4715005299834565,
+           -2.4277092735155317,
+           -2.3691203014646365,
+           -2.2970399905073777,
+           -2.2130625545858944,
+           -2.119037988686038,
+           -2.017033782170238,
+           -1.9092912643188755,
+           -1.7981775778758375,
+           -1.6861343857868878,
+           -1.5756244992372763,
+           -1.469077669459497,
+           -1.3688368102120776,
+           -1.2771059116794803,
+           -1.1959008699128362,
+           -1.1270043896724673,
+           -1.0719260242224637,
+           -1.0318682955314074,
+           -1.0076996953510222,
+           -0.9999352052377035,
+           -1.0087247956897918,
+           -1.033850175515402,
+           -1.0747298669158274,
+           -1.1304324843231657,
+           -1.1996979005677761,
+           -1.2809657971977177,
+           -1.372410921264852,
+           -1.4719842128659715,
+           -1.5774588300118026,
+           -1.6864799833224564,
+           -1.7966174053637123,
+           -1.905419220245316,
+           -2.010465949800885,
+           -2.109423393926125,
+           -2.2000931543850797,
+           -2.28045963277333,
+           -2.3487324227964392,
+           -2.403383132338801,
+           -2.4431758090883173,
+           -2.4671903013119385,
+           -2.474838058839169,
+           -2.4658700641180338,
+           -2.440376774805361,
+           -2.3987801530245094,
+           -2.341818047411765,
+           -2.270521377696095,
+           -2.186184743325482,
+           -2.0903312333781416,
+           -1.9846723508954431,
+           -1.8710640775601606,
+           -1.751460191612219,
+           -1.6278640109829294,
+           -1.5022797634712293,
+           -1.3766647857427659,
+           -1.2528837231085925,
+           -1.132665843277217,
+           -1.0175664911312732,
+           -0.9089336002942877,
+           -0.8078800436801981,
+           -0.7152624527641942,
+           -0.6316669678451531,
+           -0.5574022033215479,
+           -0.4924995274679659,
+           -0.4367205700195919,
+           -0.38957168772021744,
+           -0.350324942453703,
+           -0.31804498304871026,
+           -0.29162107440190194,
+           -0.26980338987642866,
+           -0.25124257816937584,
+           -0.2345315365929327,
+           -0.21824827092442456,
+           -0.20099869890275762,
+           -0.18145826061312384,
+           -0.15841123420223246,
+           -0.13078671866727729,
+           -0.09769033522167642,
+           -0.05843081265314884,
+           -0.012540757242554995,
+           0.040208939240394675,
+           0.0998014330982212,
+           0.16597320694528378,
+           0.23822031405746427,
+           0.3158114280088044,
+           0.39780735858042143,
+           0.48308652532510543,
+           0.5703757234695376,
+           0.6582853770230537,
+           0.7453483546014719,
+           0.8300613276180658,
+           0.910927580603349,
+           0.9865001413005892,
+           1.0554240849576944,
+           1.116476883285126,
+           1.1686057135243346,
+           1.2109607158946165,
+           1.2429232865796556,
+           1.2641286159412117,
+           1.2744818247727794,
+           1.2741672115737384,
+           1.2636502970445531,
+           1.243672533950758,
+           1.2152387366257522,
+           1.1795974700144838,
+           1.1382148186382441,
+           1.0927421266420696,
+           1.0449784568586877,
+           0.9968286556158077,
+           0.9502580272962928,
+           0.9072447154301235,
+           0.8697309529555954,
+           0.839574381499937,
+           0.8185006470726529,
+           0.8080584571478466,
+           0.8095782321888866,
+           0.8241354044277397,
+           0.8525193100444552,
+           0.8952084903519816,
+           0.9523530663263892,
+           1.023764682501705,
+           1.1089143349701893,
+           1.206938208420311,
+           1.3166514534529727,
+           1.4365696425936163,
+           1.5649374562033889,
+           1.6997639724966835,
+           1.8388637734624742,
+           1.979902934676834,
+           2.120448845348991,
+           2.2580227084870996,
+           2.390153502212405,
+           2.5144321437267556,
+           2.6285645882653554,
+           2.730422616818312,
+           2.8180911180019272,
+           2.8899107499878482,
+           2.9445149759269222,
+           2.9808605982439444,
+           2.998251070339884
+          ],
+          [
+           2.999460098067586,
+           2.9854995877704686,
+           2.9524960229254216,
+           2.9010816154073513,
+           2.8322385006844177,
+           2.7472767418490966,
+           2.647805004950395,
+           2.5356945991841036,
+           2.4130377318756766,
+           2.282100963938223,
+           2.1452749633225534,
+           2.0050217392016343,
+           1.8638205962054717,
+           1.7241140746059513,
+           1.5882551383413532,
+           1.4584568383150247,
+           1.3367456143954604,
+           1.2249193076032232,
+           1.1245108363940008,
+           1.036758350662806,
+           0.9625825175807559,
+           0.9025714185794262,
+           0.8569733510323835,
+           0.8256976360267183,
+           0.8083233397942501,
+           0.8041156256403291,
+           0.8120492702397554,
+           0.8308387074353683,
+           0.8589738083354101,
+           0.8947604723074501,
+           0.9363649926503168,
+           0.9818610759473535,
+           1.0292783373701413,
+           1.0766510668192497,
+           1.1220660633348867,
+           1.163708367519791,
+           1.1999037828856594,
+           1.2291571654446418,
+           1.2501855742280412,
+           1.2619455108184958,
+           1.2636536299819165,
+           1.2548004721769261,
+           1.235156947841653,
+           1.204773488397859,
+           1.1639719652201679,
+           1.1133306607207947,
+           1.053662750619418,
+           0.9859889190339345,
+           0.9115048741881105,
+           0.8315446586523036,
+           0.7475407509872452,
+           0.6609820329083081,
+           0.5733707457373178,
+           0.4861795807650704,
+           0.40081003973913243,
+           0.31855316428322905,
+           0.24055366764011576,
+           0.1677784104064656,
+           0.10099004625324141,
+           0.0407265269569366,
+           -0.012712998109135083,
+           -0.05927552063440317,
+           -0.09915455987172567,
+           -0.13278358856977918,
+           -0.1608226720300496,
+           -0.18413867166158204,
+           -0.20377953315200253,
+           -0.2209433348948524,
+           -0.23694291065404424,
+           -0.2531669780802103,
+           -0.2710387986145173,
+           -0.2919734621120301,
+           -0.3173349294336501,
+           -0.3483939772382203,
+           -0.38628817092681317,
+           -0.4319849445578776,
+           -0.48624879169938034,
+           -0.5496134704455324,
+           -0.622360001687614,
+           -0.7045010952690692,
+           -0.7957724774679064,
+           -0.8956314193543928,
+           -1.0032625833143258,
+           -1.117591118971976,
+           -1.237302754559014,
+           -1.3608704501124522,
+           -1.4865870092720903,
+           -1.6126028911715373,
+           -1.7369683269130605,
+           -1.8576787298734738,
+           -1.9727222985605883,
+           -2.080128647270694,
+           -2.1780172650635974,
+           -2.2646445985361323,
+           -2.3384485787662976,
+           -2.3980894671018067,
+           -2.442485976932296,
+           -2.4708457372643755,
+           -2.4826892962097875,
+           -2.477867015205043,
+           -2.4565683741990525,
+           -2.419323390045315,
+           -2.3669960404691426,
+           -2.3007697795900066,
+           -2.2221254233108962,
+           -2.1328118692098164,
+           -2.03481029129086,
+           -1.9302926107352254,
+           -1.8215751856568485,
+           -1.7110687822938988,
+           -1.6012259840822647,
+           -1.4944872613078812,
+           -1.3932269608463554,
+           -1.299700481918118,
+           -1.2159938796062546,
+           -1.143977083644242,
+           -1.0852618369624853,
+           -1.041165348671448,
+           -1.0126805222012594,
+           -1.000453464450276,
+           -1.0047688097714256,
+           -1.0255432076189706,
+           -1.0623271291836003,
+           -1.114314951062823,
+           -1.1803630777422984,
+           -1.2590156741729572,
+           -1.3485373996476917,
+           -1.4469523688827368,
+           -1.5520884197030527,
+           -1.6616256425650426,
+           -1.7731480283235623,
+           -1.8841970195392876,
+           -1.992325708922662,
+           -2.095152417196469,
+           -2.190412401957465,
+           -2.2760064985077055,
+           -2.3500455718472137,
+           -2.410889764107894,
+           -2.4571816510418123,
+           -2.4878725715428813,
+           -2.502241561855566,
+           -2.4999065069643054,
+           -2.480827311203325,
+           -2.445301083712651,
+           -2.393949527236606,
+           -2.327698906185873,
+           -2.2477531472781886,
+           -2.1555607891066173,
+           -2.0527766416927182,
+           -1.9412191399601728,
+           -1.8228244731552101,
+           -1.6995986432048595,
+           -1.5735686471816357,
+           -1.4467339914876698,
+           -1.3210197278770226,
+           -1.198232154537886,
+           -1.0800182504218105,
+           -0.9678298097960082,
+           -0.8628931192138367,
+           -0.7661848739353648,
+           -0.6784148689719727,
+           -0.6000158254718215,
+           -0.5311405305068895,
+           -0.4716662820633788,
+           -0.42120644585167866,
+           -0.3791287510796219,
+           -0.3445797830616073,
+           -0.31651497569075726,
+           -0.2937332702368184,
+           -0.2749154920401015,
+           -0.2586654062931994,
+           -0.2435523504601052,
+           -0.22815430552510865,
+           -0.21110026202740043,
+           -0.19111075982500814,
+           -0.16703553211218855,
+           -0.1378872630380771,
+           -0.10287057230758354,
+           -0.06140546672185704,
+           -0.013144644503114396,
+           0.042015800268859496,
+           0.10393255281123866,
+           0.17221823202401207,
+           0.24625144116568745,
+           0.3251934514123889,
+           0.40801108112837997,
+           0.49350517102490443,
+           0.5803439079832253,
+           0.6671001219203169,
+           0.7522915739582553,
+           0.8344231730381236,
+           0.91203000408632,
+           0.9837200253047758,
+           1.0482152958103106,
+           1.1043906276519966,
+           1.1513086174149751,
+           1.188250100686182,
+           1.214739185445568,
+           1.2305621551643497,
+           1.2357796856934937,
+           1.2307319880924346,
+           1.2160366681841863,
+           1.1925792783601337,
+           1.1614967233655946,
+           1.1241538647998546,
+           1.0821138442561093,
+           1.0371028079880436,
+           0.9909698625966626,
+           0.9456432177595253,
+           0.9030835752431651,
+           0.8652359006909405,
+           0.8339807639463578,
+           0.8110864536321956,
+           0.7981630617605807,
+           0.7966196944426707,
+           0.8076258961830517,
+           0.8320782793861801,
+           0.8705732298533089,
+           0.9233864161161902,
+           0.9904596688994886,
+           1.071395620756968,
+           1.165460309288584,
+           1.2715937548835392,
+           1.3884283303690859,
+           1.5143145500325097,
+           1.6473537239012492,
+           1.7854367543917677,
+           1.9262882006443274,
+           2.0675146048085367,
+           2.2066559674899517,
+           2.34123917918357,
+           2.468832162824328,
+           2.5870974608972985,
+           2.6938440094524245,
+           2.7870758806946907,
+           2.865036844655479,
+           2.9262496971574548,
+           2.9695494235400997,
+           2.994109412465411,
+           2.999460098067586
+          ],
+          [
+           2.9922132411047837,
+           2.9663035211856834,
+           2.921711392462454,
+           2.8592920401980635,
+           2.780238079210345,
+           2.6860530252772614,
+           2.5785178308822587,
+           2.4596512743071504,
+           2.3316651357381506,
+           2.1969152160765995,
+           2.0578493505912165,
+           1.916953638093725,
+           1.7766981453291368,
+           1.639483354835787,
+           1.5075886024849525,
+           1.3831236988422013,
+           1.267984847724911,
+           1.1638158678865056,
+           1.0719755923141006,
+           0.993512167443115,
+           0.9291448054353728,
+           0.8792533607121632,
+           0.8438759116641511,
+           0.8227143345558247,
+           0.815147663864038,
+           0.8202528463619606,
+           0.8368323197518889,
+           0.8634476848670911,
+           0.8984585973363731,
+           0.9400658835986339,
+           0.9863577901778443,
+           1.0353582064660622,
+           1.0850756615171582,
+           1.1335518854112285,
+           1.178908745753685,
+           1.2193924192250933,
+           1.2534137354732413,
+           1.2795837340198295,
+           1.2967436015814446,
+           1.303988304044577,
+           1.3006833905604749,
+           1.2864746227110953,
+           1.2612902650192095,
+           1.2253360596249145,
+           1.1790830930473595,
+           1.1232489419606362,
+           1.0587726533635764,
+           0.986784268214823,
+           0.9085697327141711,
+           0.8255321545880868,
+           0.7391504501863052,
+           0.6509364897466599,
+           0.5623918813442091,
+           0.47496553803068786,
+           0.3900131474470466,
+           0.30875960944563335,
+           0.23226542639558412,
+           0.1613979249523172,
+           0.09680805986441061,
+           0.03891340314301908,
+           -0.012112240618019982,
+           -0.056342325674520695,
+           -0.09409407665145267,
+           -0.12591811607378317,
+           -0.152581483943992,
+           -0.17504449846091547,
+           -0.19443206858583575,
+           -0.21200021521617465,
+           -0.2290986845066309,
+           -0.24713064114801916,
+           -0.26751050850630687,
+           -0.2916210744019017,
+           -0.32077100461909513,
+           -0.3561539003428905,
+           -0.39881000072473205,
+           -0.449591568511921,
+           -0.5091329066819101,
+           -0.5778258395206604,
+           -0.6558013554112652,
+           -0.7429179541418909,
+           -0.8387570726515287,
+           -0.9426257840287284,
+           -1.0535667797458697,
+           -1.170375459186074,
+           -1.2916237681738938,
+           -1.4156902540467915,
+           -1.5407956431999377,
+           -1.6650431020939045,
+           -1.7864622181195002,
+           -1.9030556356506967,
+           -2.0128472076913493,
+           -2.113930476693574,
+           -2.2045162806594782,
+           -2.2829782930696494,
+           -2.3478953473053403,
+           -2.3980894671018063,
+           -2.4326586225272466,
+           -2.451003353688517,
+           -2.452846548865544,
+           -2.4382458265690086,
+           -2.4075981481373856,
+           -2.36163647461408,
+           -2.30141847419048,
+           -2.2283074797409674,
+           -2.1439460851581393,
+           -2.050222949660012,
+           -1.9492335465293604,
+           -1.8432357427206918,
+           -1.734601224712287,
+           -1.625763890681107,
+           -1.5191664069204442,
+           -1.4172061754426024,
+           -1.3221819786569358,
+           -1.2362425553681178,
+           -1.1613383203333034,
+           -1.099177368226019,
+           -1.0511868037789482,
+           -1.0184803154957374,
+           -1.0018327636351405,
+           -1.001662387729057,
+           -1.0180210587105407,
+           -1.0505928101731112,
+           -1.0987006869881515,
+           -1.161321752244291,
+           -1.2371099000368746,
+           -1.3244259367287945,
+           -1.4213742214186649,
+           -1.5258450016613256,
+           -1.6355614467394053,
+           -1.7481302712191509,
+           -1.8610947587812245,
+           -1.971988942380967,
+           -2.0783916729395244,
+           -2.177979315535434,
+           -2.268575849243494,
+           -2.34819921339642,
+           -2.4151028374466343,
+           -2.4678114114229555,
+           -2.5051500962326325,
+           -2.5262665342286157,
+           -2.5306451965625327,
+           -2.518113790532546,
+           -2.4888416428155415,
+           -2.4433301684106925,
+           -2.3823957255590305,
+           -2.307145339179681,
+           -2.218945945026898,
+           -2.1193879596921117,
+           -2.0102441140423766,
+           -1.893424596505185,
+           -1.7709296351742387,
+           -1.6448007020715258,
+           -1.5170715478101078,
+           -1.389720269843505,
+           -1.2646235826893575,
+           -1.143514394941968,
+           -1.027943707217041,
+           -0.9192477297484454,
+           -0.818520981136675,
+           -0.7265959742227842,
+           -0.6440299251697195,
+           -0.571098741862577,
+           -0.5077983622210064,
+           -0.4538533266097123,
+           -0.40873228590830285,
+           -0.37166997252710127,
+           -0.3416950000808613,
+           -0.317662712581774,
+           -0.2982921794842369,
+           -0.2822063317894155,
+           -0.26797415918833833,
+           -0.2541538407253831,
+           -0.2393356628382611,
+           -0.2221835892880942,
+           -0.20147438710977927,
+           -0.17613328023700098,
+           -0.14526519613578603,
+           -0.10818078820692809,
+           -0.06441655488676422,
+           -0.0137485317636738,
+           0.04380079832124232,
+           0.10796255459446807,
+           0.17822846240710377,
+           0.2538646254156602,
+           0.33393170212524875,
+           0.41731095516440814,
+           0.5027354873365991,
+           0.5888258416398648,
+           0.6741290265506978,
+           0.7571599358914616,
+           0.8364440669030351,
+           0.9105604024261077,
+           0.9781833143524912,
+           1.038122366010687,
+           1.089358940430682,
+           1.1310786982996308,
+           1.162698971985589,
+           1.183890327735235,
+           1.1945916739212574,
+           1.1950184553962568,
+           1.18566364855382,
+           1.167291454238526,
+           1.1409237716106242,
+           1.107819720789013,
+           1.0694486609213414,
+           1.027457318752753,
+           0.9836317965276062,
+           0.9398553632595844,
+           0.8980630465990216,
+           0.8601941308079379,
+           0.8281437274326765,
+           0.8037146175249886,
+           0.7885705668007214,
+           0.7841922877762771,
+           0.7918371662630007,
+           0.812503784935553,
+           0.8469021660269385,
+           0.8954305211942872,
+           0.958159142484834,
+           1.0348218978546455,
+           1.1248156120110877,
+           1.2272074229313519,
+           1.3407500109223536,
+           1.4639044052857813,
+           1.5948698882575776,
+           1.7316203414763347,
+           1.8719462211103788,
+           2.0135012078809322,
+           2.153852461032204,
+           2.2905333137416126,
+           2.421097183830016,
+           2.5431714395360987,
+           2.654509956450541,
+           2.7530431286081734,
+           2.836924153604035,
+           2.9045704970890625,
+           2.954699554068907,
+           2.986357660376106,
+           2.998941764225594,
+           2.992213241104784
+          ],
+          [
+           2.976571811140622,
+           2.938926242562151,
+           2.883105282612188,
+           2.8101798668071836,
+           2.721543019443848,
+           2.618879016808584,
+           2.504126066439196,
+           2.379433380221516,
+           2.247113650818419,
+           2.109592048200173,
+           1.969352933285303,
+           1.8288855369858164,
+           1.6906298740657901,
+           1.5569241516940588,
+           1.4299548926773944,
+           1.3117109241211689,
+           1.2039422854194082,
+           1.1081249874394195,
+           1.0254324105665016,
+           0.95671396647998,
+           0.9024814711622455,
+           0.8629034890684887,
+           0.8378077152206006,
+           0.8266912679777473,
+           0.8287385751339424,
+           0.8428463544497373,
+           0.8676550211711457,
+           0.901585703625108,
+           0.9428819172781728,
+           0.9896548408543778,
+           1.0399310577829062,
+           1.091701574279599,
+           1.142970902946889,
+           1.1918050083580929,
+           1.2363769483844025,
+           1.2750091110001367,
+           1.30621103922904,
+           1.3287119543712782,
+           1.3414872266727096,
+           1.3437781996315243,
+           1.3351049452086414,
+           1.3152717080029086,
+           1.2843649824227248,
+           1.2427443533656026,
+           1.1910264132366195,
+           1.1300622417397572,
+           1.0609090954333342,
+           0.984797097557635,
+           0.9030918415586475,
+           0.8172539210080425,
+           0.7287964718153253,
+           0.6392418579604464,
+           0.5500786483628025,
+           0.4627200195926117,
+           0.3784646773061336,
+           0.29846131965675016,
+           0.2236775703065006,
+           0.1548741894966035,
+           0.09258523197999224,
+           0.03710466403655483,
+           -0.011520217730940854,
+           -0.05348840127519548,
+           -0.08923782536927753,
+           -0.11943129670411465,
+           -0.14493603386082513,
+           -0.16679738117434328,
+           -0.1862073886146791,
+           -0.20446908916378773,
+           -0.22295741931164886,
+           -0.2430778183198136,
+           -0.26622360549522656,
+           -0.29373327023681817,
+           -0.3268488161229009,
+           -0.3666762775893629,
+           -0.41414947633286164,
+           -0.4699980057083795,
+           -0.5347203270172446,
+           -0.6085627342849638,
+           -0.6915047970724755,
+           -0.7832517277161655,
+           -0.8832339442269703,
+           -0.9906139172825789,
+           -1.1043002039029184,
+           -1.2229683861775544,
+           -1.3450884554520137,
+           -1.4689580151689106,
+           -1.5927405233303125,
+           -1.7145076621648159,
+           -1.832284811449974,
+           -1.9440985159121722,
+           -2.0480247784373105,
+           -2.1422369810350026,
+           -2.225052235448569,
+           -2.294974995096827,
+           -2.350736819033217,
+           -2.3913312654475307,
+           -2.4160430048553563,
+           -2.4244703788156547,
+           -2.4165407855047945,
+           -2.3925184449752375,
+           -2.353004280253491,
+           -2.298927841097926,
+           -2.23153139056445,
+           -2.152346465763799,
+           -2.063163408626424,
+           -1.9659945355677837,
+           -1.863031772386131,
+           -1.7565997186237217,
+           -1.6491052205509384,
+           -1.542984621021409,
+           -1.440649915456588,
+           -1.34443507459795,
+           -1.2565437955887824,
+           -1.1789999133357216,
+           -1.1136016446239982,
+           -1.0618807495227018,
+           -1.0250675803217173,
+           -1.0040628503410887,
+           -0.9994167967791868,
+           -1.0113162371493822,
+           -1.0395798320323142,
+           -1.0836616723795338,
+           -1.1426631121708093,
+           -1.2153525716514153,
+           -1.3001928474120583,
+           -1.3953752878155836,
+           -1.4988600300394257,
+           -1.608421352227997,
+           -1.7216970743943265,
+           -1.836240847671933,
+           -1.9495761055594218,
+           -2.0592504144952213,
+           -2.162888955295027,
+           -2.258245891778243,
+           -2.343252437650809,
+           -2.4160605160156887,
+           -2.475081015665875,
+           -2.5190157818479992,
+           -2.5468826331589907,
+           -2.5580328668477335,
+           -2.5521608978304267,
+           -2.5293058676860127,
+           -2.4898452540827205,
+           -2.4344807037347898,
+           -2.3642164983821305,
+           -2.2803312388706534,
+           -2.1843434929086776,
+           -2.077972293587203,
+           -1.9630934948572265,
+           -1.8416930839953767,
+           -1.715818617429247,
+           -1.5875299835905574,
+           -1.458850703894257,
+           -1.331720960422847,
+           -1.2079534870876047,
+           -1.0891933813270884,
+           -0.9768827878624079,
+           -0.872231277369429,
+           -0.7761925944295571,
+           -0.6894482845482062,
+           -0.6123985335413659,
+           -0.5451603686298835,
+           -0.4875731837700487,
+           -0.4392113667705544,
+           -0.39940362722720407,
+           -0.3672584567043457,
+           -0.3416950000808611,
+           -0.3214784833483053,
+           -0.3052592317089942,
+           -0.29161422532094894,
+           -0.2790900805930428,
+           -0.26624631398389526,
+           -0.25169774352139074,
+           -0.23415491072095063,
+           -0.21246146149101558,
+           -0.18562750751075588,
+           -0.15285809730784458,
+           -0.11357605609030151,
+           -0.06743860197946304,
+           -0.014347309864746766,
+           0.04554883150629916,
+           0.11185734280922767,
+           0.18395304882585767,
+           0.26099545582362255,
+           0.3419522505922496,
+           0.4256282995459224,
+           0.5106993816074268,
+           0.5957497634426019,
+           0.6793126232004102,
+           0.7599122518561771,
+           0.836106911536238,
+           0.9065312091177603,
+           0.9699368515237811,
+           1.0252306863120293,
+           1.0715089964969904,
+           1.1080871104481558,
+           1.134523503903661,
+           1.1506377087441533,
+           1.1565214987600796,
+           1.1525429923340413,
+           1.1393434915040368,
+           1.1178270617750135,
+           1.0891430426637025,
+           1.0546618606269138,
+           1.0159446891581434,
+           0.9747076610662931,
+           0.9327814812136215,
+           0.8920674106414072,
+           0.8544906919125871,
+           0.821952558098218,
+           0.7962820122254871,
+           0.7791885789858,
+           0.7722172155966638,
+           0.7767065241894964,
+           0.793751334961354,
+           0.8241706293002741,
+           0.8684816475611492,
+           0.9268808801345979,
+           0.9992324764579962,
+           1.0850644286607611,
+           1.183572698965232,
+           1.2936332673762014,
+           1.4138218833171028,
+           1.5424411164559502,
+           1.6775541226557478,
+           1.8170243752128807,
+           1.9585604634180969,
+           2.0997649336667306,
+           2.238186046015879,
+           2.3713712437997514,
+           2.4969210875709695,
+           2.6125423884278467,
+           2.7160992901696166,
+           2.8056610943966382,
+           2.879545696600932,
+           2.9363576027139078,
+           2.975019622059028,
+           2.9947974811454947,
+           2.99531676964194,
+           2.976571811140623
+          ],
+          [
+           2.952668141750426,
+           2.903599376065387,
+           2.837004318533421,
+           2.75416060644511,
+           2.65664990815037,
+           2.5463230389512983,
+           2.4252590996110532,
+           2.2957195966101778,
+           2.1600986209388884,
+           2.0208702538233645,
+           1.8805344311403085,
+           1.7415625318645505,
+           1.6063439589366566,
+           1.4771349533978106,
+           1.3560108252333085,
+           1.2448226985407191,
+           1.1451597565356493,
+           1.0583178363109575,
+           0.9852750675298207,
+           0.9266750772049253,
+           0.8828180986346211,
+           0.8536601309609096,
+           0.8388201013895353,
+           0.8375947896361541,
+           0.8489810883446621,
+           0.8717049986015569,
+           0.9042566004960872,
+           0.9449300988130743,
+           0.9918679267723199,
+           1.0431077990570397,
+           1.0966315413793835,
+           1.1504144890005943,
+           1.2024742417189405,
+           1.2509175878798713,
+           1.293984464228122,
+           1.3300879004656643,
+           1.3578490050722272,
+           1.3761261795240414,
+           1.384037898186843,
+           1.380978557057539,
+           1.3666270719981601,
+           1.3409480916799676,
+           1.3041858775015354,
+           1.256851087577533,
+           1.199700879894733,
+           1.133712916458972,
+           1.06005400156203,
+           0.9800442194253352,
+           0.8951175461594898,
+           0.8067799955142013,
+           0.7165664152165524,
+           0.6259970794264609,
+           0.5365352223159223,
+           0.44954662807798834,
+           0.36626233459952795,
+           0.2877454231082226,
+           0.21486275652142847,
+           0.14826239779330389,
+           0.08835728963474004,
+           0.03531561238884838,
+           -0.010941938229415802,
+           -0.050737892928261454,
+           -0.08462689210852625,
+           -0.11337801188796054,
+           -0.13795100574785815,
+           -0.15946709414597343,
+           -0.17917507775279864,
+           -0.19841367347196845,
+           -0.21857107295160236,
+           -0.24104279831064346,
+           -0.2671889773630806,
+           -0.2982921794842367,
+           -0.3355169429095044,
+           -0.3798720849047022,
+           -0.43217681884636483,
+           -0.493031608454553,
+           -0.5627945715509064,
+           -0.6415641067001333,
+           -0.7291682593987996,
+           -0.8251611740162128,
+           -0.9288267977346891,
+           -1.0391898177937369,
+           -1.1550336280599671,
+           -1.2749249399854954,
+           -1.3972444809459548,
+           -1.5202230641157797,
+           -1.641982172471984,
+           -1.7605780788231034,
+           -1.8740484270299442,
+           -1.9804601293187716,
+           -2.0779573926319292,
+           -2.164808674459412,
+           -2.2394513859607272,
+           -2.3005332070899454,
+           -2.346948953813329,
+           -2.377872039583095,
+           -2.3927796995607813,
+           -2.391471293619522,
+           -2.3740791693141143,
+           -2.3410717447638896,
+           -2.2932486593736727,
+           -2.2317280329123808,
+           -2.1579260659427937,
+           -2.0735294022095028,
+           -1.9804608517137898,
+           -1.8808392374301441,
+           -1.776934274877174,
+           -1.6711175184114238,
+           -1.5658105080553943,
+           -1.4634313233941738,
+           -1.3663407947376014,
+           -1.2767896352163692,
+           -1.1968677403722676,
+           -1.1284568544751177,
+           -1.0731877263559322,
+           -1.032402773805435,
+           -1.0071251470403244,
+           -0.99803493148669,
+           -1.0054530618062374,
+           -1.029333336776739,
+           -1.069262732758987,
+           -1.1244700167001407,
+           -1.1938424627213033,
+           -1.2759502841027877,
+           -1.3690782095876943,
+           -1.4712634638181836,
+           -1.5803392605063113,
+           -1.6939827872907296,
+           -1.8097665562810397,
+           -1.925211916576104,
+           -2.037843476426145,
+           -2.1452431643416943,
+           -2.245102670744986,
+           -2.3352730543688383,
+           -2.413810369449943,
+           -2.4790162690377633,
+           -2.529472663976766,
+           -2.5640696632389877,
+           -2.5820261856742976,
+           -2.582902811851848,
+           -2.5666066330905553,
+           -2.5333880483875153,
+           -2.483829653999401,
+           -2.4188275601605285,
+           -2.339565650194016,
+           -2.247483464680925,
+           -2.1442385433262356,
+           -2.031664186067942,
+           -1.911723699711474,
+           -1.7864622744353602,
+           -1.6579576840683778,
+           -1.528271023955599,
+           -1.3993986901188447,
+           -1.2732267636283823,
+           -1.1514888957240659,
+           -1.0357286940489683,
+           -0.9272674908409857,
+           -0.827178233121273,
+           -0.7362660763978384,
+           -0.6550560911757988,
+           -0.5837883099734557,
+           -0.5224201561485371,
+           -0.47063610931570926,
+           -0.42786428015170813,
+           -0.39329939448209156,
+           -0.3659315270314494,
+           -0.344579783061607,
+           -0.32793000484301066,
+           -0.3145754824966419,
+           -0.3030595775983046,
+           -0.29191912478221677,
+           -0.27972746243996743,
+           -0.26513595877801294,
+           -0.24691294352956306,
+           -0.22397902734774316,
+           -0.19543788847453045,
+           -0.1606017271745102,
+           -0.1190107295500239,
+           -0.07044604011405711,
+           -0.014935912872648041,
+           0.047245110672290404,
+           0.11558396578480849,
+           0.18934355868876618,
+           0.26758360233758555,
+           0.3491872393440212,
+           0.43289274577581305,
+           0.517329475688153,
+           0.6010570938798752,
+           0.6826070562961922,
+           0.7605252360139028,
+           0.8334145594247,
+           0.8999765129598969,
+           0.9590504056257436,
+           1.0096493261581398,
+           1.0509918144537922,
+           1.0825283730975872,
+           1.1039620736499167,
+           1.1152626606759695,
+           1.1166737205896307,
+           1.1087126581447229,
+           1.09216340643184,
+           1.0680619819367831,
+           1.03767517991731,
+           1.002472882430478,
+           0.9640946173222007,
+           0.9243111571702499,
+           0.8849820787236761,
+           0.8480103124455804,
+           0.8152947955375847,
+           0.788682398123642,
+           0.7699203195976188,
+           0.7606101497129928,
+           0.7621647567711846,
+           0.7757691039475296,
+           0.8023460058043717,
+           0.8425277224945823,
+           0.8966341518102058,
+           0.9646582224061547,
+           1.046258919044368,
+           1.140762186772212,
+           1.2471697700758841,
+           1.3641758499210872,
+           1.490191150961928,
+           1.623374007764826,
+           1.7616677071889626,
+           1.9028432683397103,
+           2.0445466856316066,
+           2.184349547846794,
+           2.3198018594692096,
+           2.4484858321964964,
+           2.5680693858700745,
+           2.6763580998812295,
+           2.771344388421765,
+           2.8512527350173467,
+           2.914579912145158,
+           2.9601292282325993,
+           2.987037984157684,
+           2.9947974811454947,
+           2.9832650978089545,
+           2.9526681417504275
+          ],
+          [
+           2.92070446879377,
+           2.8606218029715422,
+           2.7837985352431827,
+           2.6917082074035092,
+           2.5861077704159188,
+           2.468998948110029,
+           2.342584180624905,
+           2.209218179963404,
+           2.0713562326270867,
+           1.931500459473669,
+           1.7921452888752083,
+           1.6557234148673645,
+           1.5245534969235437,
+           1.4007908126696509,
+           1.286382000423341,
+           1.183024926756528,
+           1.092134587867387,
+           1.0148158055376595,
+           0.951843312497552,
+           0.90364964221397,
+           0.8703210488818607,
+           0.8516014893816831,
+           0.8469045049258569,
+           0.8553326508039153,
+           0.875703942674594,
+           0.9065846216292114,
+           0.9463273918032209,
+           0.9931141572341395,
+           1.0450021820120716,
+           1.099972521992485,
+           1.1559795292187884,
+           1.211000212802614,
+           1.2630822526617358,
+           1.3103895048050644,
+           1.3512439076331098,
+           1.384162796139361,
+           1.4078907524453246,
+           1.421425263678145,
+           1.4240356181884375,
+           1.4152746444654432,
+           1.3949830794724674,
+           1.363286539917668,
+           1.320585256514218,
+           1.2675369129059035,
+           1.2050331031085317,
+           1.1341700797582075,
+           1.0562146062307494,
+           0.9725658453176245,
+           0.8847143126641845,
+           0.7941989922557461,
+           0.702563752202976,
+           0.611314210964431,
+           0.521876186716395,
+           0.4355568163400592,
+           0.35350935666815037,
+           0.27670258113384977,
+           0.20589556235373774,
+           0.14161848859209814,
+           0.08416000313406043,
+           0.03356138438639436,
+           -0.010382294619702187,
+           -0.048114071178952784,
+           -0.08030028745105586,
+           -0.10780947515400792,
+           -0.13168549610368802,
+           -0.1531156549210584,
+           -0.17339463253224288,
+           -0.19388519969757648,
+           -0.21597675590154153,
+           -0.24104279831064335,
+           -0.2703984566270314,
+           -0.30525923170899405,
+           -0.346702048703919,
+           -0.3956296797878499,
+           -0.45273950879011277,
+           -0.5184975020483849,
+           -0.593118119470401,
+           -0.676550750222245,
+           -0.7684730924560458,
+           -0.8682917201620952,
+           -0.9751498970030084,
+           -1.0879425114630341,
+           -1.205337824491511,
+           -1.3258055446540755,
+           -1.447650581079167,
+           -1.5690516753756092,
+           -1.6881039839911143,
+           -1.802864575496737,
+           -1.9113997257733542,
+           -2.011832840167259,
+           -2.102391806814456,
+           -2.181454590226624,
+           -2.2475919088669305,
+           -2.2996059040604226,
+           -2.3365637986994643,
+           -2.357825660649682,
+           -2.36306552473308,
+           -2.352285285293133,
+           -2.3258209447805784,
+           -2.2843409882986485,
+           -2.228836845090302,
+           -2.160605590842953,
+           -2.0812252346786,
+           -1.9925231171008713,
+           -1.8965381154750485,
+           -1.7954775076025502,
+           -1.691669477790974,
+           -1.5875123601787309,
+           -1.485421798184651,
+           -1.387777054695605,
+           -1.2968677335500245,
+           -1.2148421683249377,
+           -1.1436586994382472,
+           -1.0850409959352594,
+           -1.0404384855651594,
+           -1.0109928380877222,
+           -0.997511305039373,
+           -1.0004475578537133,
+           -1.0198904891827216,
+           -1.0555612537954493,
+           -1.1068186301187473,
+           -1.1726725860759946,
+           -1.2518057381750587,
+           -1.3426022055302915,
+           -1.4431831852287975,
+           -1.5514484164278204,
+           -1.665122561659803,
+           -1.7818054183919043,
+           -1.8990247847308876,
+           -2.0142907424288703,
+           -2.1251500894824202,
+           -2.229239654344525,
+           -2.324337254054564,
+           -2.4084091186565177,
+           -2.4796526926100473,
+           -2.5365338383042735,
+           -2.577817604422096,
+           -2.6025918793722393,
+           -2.6102834234216368,
+           -2.600665958252444,
+           -2.5738601848858487,
+           -2.5303257955411107,
+           -2.4708457372643764,
+           -2.3965031703656754,
+           -2.3086517383249947,
+           -2.208879923643925,
+           -2.098970402300735,
+           -1.980855424678599,
+           -1.8565693403171486,
+           -1.7281994454662353,
+           -1.5978363647702352,
+           -1.4675251807801473,
+           -1.3392184974227535,
+           -1.2147325668339173,
+           -1.0957075245921954,
+           -0.9835726685550273,
+           -0.8795175840167494,
+           -0.7844697661450516,
+           -0.6990792234510228,
+           -0.6237103676241376,
+           -0.5584413099036474,
+           -0.5030704969061938,
+           -0.4571304341719853,
+           -0.41990806824058374,
+           -0.39047123224418584,
+           -0.36770040993388764,
+           -0.35032494245370255,
+           -0.33696269427469877,
+           -0.3261621121498649,
+           -0.316445555762135,
+           -0.3063527522368122,
+           -0.2944832294773731,
+           -0.27953661522619494,
+           -0.2603497489832949,
+           -0.23592964086105697,
+           -0.20548142286612311,
+           -0.16843057112307844,
+           -0.12443882878940822,
+           -0.07341342500304675,
+           -0.01550936093958488,
+           0.04887528452989668,
+           0.11911089460452126,
+           0.1943543858431556,
+           0.27357332625687075,
+           0.3555754571018537,
+           0.4390428333517763,
+           0.522569675982703,
+           0.6047029305345908,
+           0.6839844534433057,
+           0.7589937022412862,
+           0.828389789085588,
+           0.8909517696480472,
+           0.9456160809168481,
+           0.9915101109065655,
+           1.0279809789453036,
+           1.0546187247313692,
+           1.0712732447535076,
+           1.0780644724447321,
+           1.0753854696445582,
+           1.063898277288992,
+           1.0445225582061688,
+           1.0184172498182213,
+           0.9869556247797513,
+           0.9516943285710262,
+           0.9143371204836704,
+           0.8766941842922618,
+           0.840637993632311,
+           0.808056811658902,
+           0.7808069724936921,
+           0.7606651314925122,
+           0.7492816813975038,
+           0.7481365116250498,
+           0.7584982386747372,
+           0.781387958049811,
+           0.8175484639875903,
+           0.8674197552033746,
+           0.931121495849008,
+           1.0084429345989014,
+           1.0988406052599609,
+           1.2014439439518516,
+           1.315068765343445,
+           1.4382383483968022,
+           1.5692116952950659,
+           1.7060183503293842,
+           1.846499002870247,
+           1.988350954187478,
+           2.1291774054017725,
+           2.2665394263101843,
+           2.3980093946788106,
+           2.5212246546192625,
+           2.633940131928747,
+           2.7340786641004176,
+           2.8197778526770843,
+           2.889432324560195,
+           2.9417303949200457,
+           2.9756842549364655,
+           2.9906529595831515,
+           2.986357660376106,
+           2.9628887113237865,
+           2.9207044687937698
+          ],
+          [
+           2.8809512194075966,
+           2.810357132996567,
+           2.723938077744003,
+           2.62335104523831,
+           2.510513424646415,
+           2.3875609410828478,
+           2.2568007767062057,
+           2.1206609714083697,
+           1.9816372866445269,
+           1.8422387740515838,
+           1.7049333186301134,
+           1.5720944237666976,
+           1.4459504723456866,
+           1.3285376354862664,
+           1.221657509612795,
+           1.1268404458817072,
+           1.0453153963357225,
+           0.9779869419847608,
+           0.9254199932453139,
+           0.8878324671062663,
+           0.8650960525998524,
+           0.8567449813701158,
+           0.8619925281174119,
+           0.8797547811490763,
+           0.9086810506838734,
+           0.9471901261386725,
+           0.9935114571608384,
+           1.04573021995052,
+           1.1018351431545754,
+           1.1597679083730996,
+           1.217472910468729,
+           1.2729461630469334,
+           1.3242821645772536,
+           1.369717599805129,
+           1.4076708377979597,
+           1.436776299934658,
+           1.455912905521402,
+           1.464225956083576,
+           1.461141987867104,
+           1.4463763014366093,
+           1.4199330629770879,
+           1.3820980593356562,
+           1.33342437329352,
+           1.2747114224330436,
+           1.206977969856768,
+           1.131429863829083,
+           1.0494233924613412,
+           0.9624252456634579,
+           0.8719701571356189,
+           0.7796173522132137,
+           0.686906951639968,
+           0.5953174762856208,
+           0.5062255636386834,
+           0.42086894451658907,
+           0.34031363947608995,
+           0.26542622117367787,
+           0.1968518543237898,
+           0.1349986723712316,
+           0.08002888342104342,
+           0.03185682159189095,
+           -0.009846021739979807,
+           -0.04563913474656181,
+           -0.07629461643007948,
+           -0.10277279884281824,
+           -0.12619251397507988,
+           -0.14779679954950065,
+           -0.16891495813525906,
+           -0.19092198077790126,
+           -0.21519641725765196,
+           -0.24307781831981337,
+           -0.27582488964019936,
+           -0.31457548249664175,
+           -0.36030950244980475,
+           -0.4138157458557015,
+           -0.4756635765024555,
+           -0.5461802335066228,
+           -0.6254344198387646,
+           -0.7132266620154651,
+           -0.8090867595709098,
+           -0.9122784622166186,
+           -1.0218113276506766,
+           -1.1364595284411774,
+           -1.2547871969328306,
+           -1.375179727244057,
+           -1.4958802974355034,
+           -1.6150307368019423,
+           -1.7307157464918892,
+           -1.841009389288999,
+           -1.944022698791175,
+           -2.0379512211275412,
+           -2.121121294784207,
+           -2.1920338963568855,
+           -2.2494049316597633,
+           -2.292200931411499,
+           -2.319669216803224,
+           -2.331361730084159,
+           -2.327151875737112,
+           -2.3072438851988037,
+           -2.2721743983208365,
+           -2.2228061434501774,
+           -2.160313790498893,
+           -2.086162242932823,
+           -2.002077820511886,
+           -1.9100129602656957,
+           -1.8121052242342603,
+           -1.710631544945966,
+           -1.607958759893651,
+           -1.506491581396057,
+           -1.4086192158005302,
+           -1.3166618842728397,
+           -1.232818505428431,
+           -1.159116777525106,
+           -1.0973668453503875,
+           -1.049119655525299,
+           -1.0156309956479705,
+           -0.9978320801138435,
+           -0.996307391772505,
+           -1.0112803175313672,
+           -1.0426069317400246,
+           -1.089778088159267,
+           -1.1519297842256897,
+           -1.227861564958259,
+           -1.316062542993048,
+           -1.4147444305183121,
+           -1.5218808127085517,
+           -1.6352517446613117,
+           -1.7524926284072508,
+           -1.8711462263322023,
+           -1.988716594741376,
+           -2.1027236780548786,
+           -2.2107572912750983,
+           -2.3105292361894345,
+           -2.3999223447949047,
+           -2.4770353204429556,
+           -2.5402223512831954,
+           -2.588126599152227,
+           -2.619706816929361,
+           -2.6342565148677646,
+           -2.631415277383114,
+           -2.6111720217930583,
+           -2.5738601848858482,
+           -2.520145017191565,
+           -2.4510033536885185,
+           -2.367696408789797,
+           -2.2717363084581828,
+           -2.164847219185137,
+           -2.0489220587893207,
+           -1.9259758745317543,
+           -1.7980970475123585,
+           -1.6673975269853256,
+           -1.5359633131012886,
+           -1.405806391385274,
+           -1.27881927746804,
+           -1.1567332574132596,
+           -1.0410813093331273,
+           -0.9331665684218151,
+           -0.8340370532085224,
+           -0.7444672093971856,
+           -0.6649466531922833,
+           -0.5956763128985713,
+           -0.5365719804221798,
+           -0.4872750977758643,
+           -0.4471704224619806,
+           -0.4154100441901777,
+           -0.3909430680457777,
+           -0.37255013986187707,
+           -0.3588818716089763,
+           -0.3485001310034365,
+           -0.33992109253878716,
+           -0.33165890837995005,
+           -0.3222688479372687,
+           -0.3103887746299116,
+           -0.29477787679601375,
+           -0.2743516456277837,
+           -0.2482121944329174,
+           -0.21567313783982986,
+           -0.17627839359115208,
+           -0.12981442963264633,
+           -0.07631565122751344,
+           -0.016062802435422786,
+           0.05042556107062057,
+           0.12240828985459694,
+           0.1989431364238746,
+           0.2789139518067401,
+           0.36106285665281423,
+           0.44402652974997175,
+           0.5263756480253672,
+           0.6066564279788902,
+           0.6834331612386068,
+           0.7553306080070704,
+           0.8210751123497054,
+           0.879533332594372,
+           0.9297475378632363,
+           0.9709665065264274,
+           1.0026711720524486,
+           1.0245942936039467,
+           1.0367335794987607,
+           1.0393578575552491,
+           1.0330060632110039,
+           1.0184789997076376,
+           0.9968240099607527,
+           0.9693128823175491,
+           0.937413487638362,
+           0.9027558085917781,
+           0.8670931695813308,
+           0.8322596035698024,
+           0.8001243969653267,
+           0.7725449329772012,
+           0.7513190053697791,
+           0.7381377969584912,
+           0.7345407098434097,
+           0.7418731973445809,
+           0.7612486817095361,
+           0.7935155484480749,
+           0.839230089835585,
+           0.8986361295661609,
+           0.9716519011412862,
+           1.0578645782348681,
+           1.1565326702459064,
+           1.266596305075132,
+           1.3866952285433052,
+           1.5151941605525623,
+           1.6502149667542545,
+           1.7896749356145376,
+           1.9313302985515184,
+           2.072823999041243,
+           2.2117366085435024,
+           2.3456392054937574,
+           2.4721469805074774,
+           2.5889723077156597,
+           2.6939760294284802,
+           2.78521573899325,
+           2.860989913911572,
+           2.91987684642119,
+           2.9607674395555867,
+           2.9828910802608624,
+           2.9858339640075346,
+           2.9695494235400997,
+           2.934360003636526,
+           2.880951219407599
+          ],
+          [
+           2.8337447240702605,
+           2.7532306279934695,
+           2.6579293925934886,
+           2.549667452473395,
+           2.430506433213895,
+           2.3026980202603187,
+           2.1686346542695363,
+           2.030797205002039,
+           1.8917008458725018,
+           1.7538403918071477,
+           1.6196363731371588,
+           1.4913830976698115,
+           1.371199902359289,
+           1.2609867164215556,
+           1.1623849512820856,
+           1.076744602048218,
+           1.0050982934869341,
+           0.9481428345031702,
+           0.906228663010665,
+           0.8793573723405782,
+           0.8671873156214799,
+           0.8690470906565283,
+           0.8839565194605928,
+           0.910654558397779,
+           0.9476334111164342,
+           0.9931779711875945,
+           1.045409598024981,
+           1.1023331312626017,
+           1.161885977631357,
+           1.2219880621723826,
+           1.2805914232977582,
+           1.3357282489636302,
+           1.3855561985174198,
+           1.4283999303501023,
+           1.4627878573600064,
+           1.4874832778015652,
+           1.5015091751551686,
+           1.5041661435150502,
+           1.4950430705445374,
+           1.474020393879401,
+           1.4412659343615795,
+           1.3972234959673457,
+           1.3425946031017233,
+           1.2783139165618524,
+           1.2055190256866892,
+           1.1255154521383208,
+           1.0397378169953544,
+           0.9497082145245823,
+           0.8569929008963608,
+           0.76315844265963,
+           0.6697284771450748,
+           0.5781422150040164,
+           0.48971576443601106,
+           0.40560727864954244,
+           0.3267868247619203,
+           0.254011746335581,
+           0.1878081462938415,
+           0.12845895577143385,
+           0.07599888163781368,
+           0.030216345377902926,
+           -0.009337656701477353,
+           -0.04333402271322777,
+           -0.07264376883502144,
+           -0.09831059551510558,
+           -0.12151853247644458,
+           -0.1435555279545524,
+           -0.16577395463432132,
+           -0.18954908688587468,
+           -0.2162366590379681,
+           -0.24713064114801886,
+           -0.28342236632380463,
+           -0.32616211214986474,
+           -0.3762241789310296,
+           -0.43427642076003425,
+           -0.50075507399729,
+           -0.5758455943945513,
+           -0.6594700621315912,
+           -0.7512815472699838,
+           -0.850665650741706,
+           -0.9567492524377793,
+           -1.068416312859876,
+           -1.1843303928103366,
+           -1.3029633813169759,
+           -1.422629759828661,
+           -1.5415255847903933,
+           -1.6577712447293493,
+           -1.7694569451815148,
+           -1.874689797814482,
+           -1.9716413409696165,
+           -2.0585942988779933,
+           -2.133987396597769,
+           -2.196457087133143,
+           -2.2448751153459963,
+           -2.278380938562572,
+           -2.296408143932335,
+           -2.2987041447141743,
+           -2.2853425982944953,
+           -2.2567281639627947,
+           -2.213593403993276,
+           -2.1569878228507218,
+           -2.088259231648326,
+           -2.0090278135913096,
+           -1.9211534463811157,
+           -1.826697004967064,
+           -1.7278765184576321,
+           -1.6270191846977025,
+           -1.526510351738138,
+           -1.4287406545142247,
+           -1.3360525455035577,
+           -1.2506874786476359,
+           -1.1747349958253284,
+           -1.1100849248390678,
+           -1.0583838281415754,
+           -1.0209967440396919,
+           -0.9989751391945821,
+           -0.9930318458515667,
+           -1.0035235928907347,
+           -1.0304415604709003,
+           -1.0734101980948039,
+           -1.1316943499661807,
+           -1.204214534303044,
+           -1.2895700296122976,
+           -1.3860692355299822,
+           -1.4917666031987213,
+           -1.604505274487404,
+           -1.7219644344403642,
+           -1.8417102704485753,
+           -1.961249347449281,
+           -2.078083153013809,
+           -2.1897625408023838,
+           -2.293940806139313,
+           -2.3884241632300696,
+           -2.471218458895701,
+           -2.5405710510073316,
+           -2.5950068987489296,
+           -2.633358053478861,
+           -2.6547858998056664,
+           -2.658795672580861,
+           -2.645242962511947,
+           -2.61433211642209,
+           -2.5666066330905553,
+           -2.5029318473305704,
+           -2.4244703788156565,
+           -2.3326509936710336,
+           -2.2291316818346774,
+           -2.1157578879092993,
+           -1.9945169444252313,
+           -1.8674898414549308,
+           -1.7368015233532472,
+           -1.604570930736147,
+           -1.4728620030765327,
+           -1.343636824657331,
+           -1.21871203498648,
+           -1.0997195357690943,
+           -0.9880724124465977,
+           -0.8849368520654789,
+           -0.7912106842871063,
+           -0.7075090026091252,
+           -0.6341571426111731,
+           -0.5711911077876329,
+           -0.5183653459524508,
+           -0.4751675949816909,
+           -0.44084034039171816,
+           -0.4144082633193342,
+           -0.3947109099424775,
+           -0.3804396859056991,
+           -0.37017817503472006,
+           -0.3624447030937516,
+           -0.3557360164633089,
+           -0.3485709236044824,
+           -0.33953275451184867,
+           -0.3273095297882547,
+           -0.3107307955178392,
+           -0.28880017108148676,
+           -0.26072277210219036,
+           -0.22592680687516956,
+           -0.18407879844947111,
+           -0.13509205206411737,
+           -0.0791281646403265,
+           -0.016591554994671836,
+           0.0518828242534194,
+           0.12544825407913227,
+           0.203070987524577,
+           0.2835602948783811,
+           0.3656030121136253,
+           0.4478016706437238,
+           0.5287151915704427,
+           0.6069010587404267,
+           0.6809578438636097,
+           0.7495669447460459,
+           0.8115324146921667,
+           0.8658178069432473,
+           0.911579031519736,
+           0.948192321206864,
+           0.975276526194359,
+           0.9927090999888608,
+           1.0006352990831084,
+           0.9994702914844291,
+           0.9898940502442954,
+           0.9728390930414442,
+           0.9494713129975766,
+           0.9211643246038017,
+           0.8894679173914193,
+           0.8560713645166796,
+           0.8227624698179468,
+           0.7913833516626613,
+           0.7637840520831372,
+           0.741775122963425,
+           0.7270803757111708,
+           0.7212909859654664,
+           0.7258221202250456,
+           0.7418731973445806,
+           0.7703928158829167,
+           0.8120492702397549,
+           0.8672074469826382,
+           0.9359127409302619,
+           1.01788246211805,
+           1.112505023845357,
+           1.2188470130264668,
+           1.3356680516851709,
+           1.4614431673854495,
+           1.5943922053946444,
+           1.7325156410085505,
+           1.873635991053737,
+           2.0154438830847337,
+           2.1555477227170527,
+           2.2915258068397506,
+           2.4209796654725615,
+           2.5415873794314767,
+           2.65115561568433,
+           2.7476691475098716,
+           2.8293366817663563,
+           2.894631899438524,
+           2.9423287261690834,
+           2.971529984039803,
+           2.981688731202419,
+           2.972621768314024,
+           2.9445149759269222,
+           2.8979203405235894,
+           2.833744724070263
+          ],
+          [
+           2.779484371093498,
+           2.689725604044614,
+           2.5863309431372814,
+           2.4712808256457603,
+           2.346763691469455,
+           2.21512816435351,
+           2.078831738606336,
+           1.9403871688720273,
+           1.8023078132966466,
+           1.667053203054873,
+           1.5369761031525246,
+           1.4142722909177776,
+           1.3009342106114534,
+           1.1987095668179457,
+           1.1090657980958305,
+           1.0331612287635212,
+           0.9718235342095701,
+           0.9255359777467944,
+           0.8944316891315669,
+           0.8782960610536479,
+           0.8765771449152723,
+           0.8884037358295902,
+           0.9126106536498177,
+           0.9477705564521918,
+           0.9922314693768733,
+           1.044159078797127,
+           1.1015827326397614,
+           1.162444004927575,
+           1.2246466282094304,
+           1.286106572734251,
+           1.34480105652589,
+           1.3988153056966315,
+           1.4463859484282844,
+           1.4859400173695159,
+           1.5161286513930192,
+           1.5358547257621593,
+           1.5442937962729757,
+           1.5409079139137563,
+           1.5254520477208717,
+           1.4979730402626583,
+           1.4588012078807941,
+           1.4085348817744947,
+           1.3480183616450743,
+           1.2783139165618524,
+           1.2006686139261549,
+           1.1164768832851264,
+           1.0272398241840037,
+           0.9345223437389547,
+           0.8399092583114799,
+           0.7449615134175593,
+           0.6511736663858715,
+           0.5599337376019544,
+           0.47248646948040174,
+           0.38990093933813696,
+           0.3130433554990767,
+           0.24255572824179822,
+           0.17884095212615075,
+           0.12205466775439466,
+           0.07210409342305392,
+           0.028653834915524586,
+           -0.008861500502458371,
+           -0.04121823736982779,
+           -0.06937863248856324,
+           -0.09446061743019252,
+           -0.11770309560626122,
+           -0.14042772321310434,
+           -0.16399819634036805,
+           -0.1897781333250651,
+           -0.21908868032631387,
+           -0.2531669780802099,
+           -0.29312660858720696,
+           -0.33992109253878705,
+           -0.3943114327830895,
+           -0.45683859793259635,
+           -0.5278017158517783,
+           -0.6072426023353297,
+           -0.6949370894137802,
+           -0.7903934444365157,
+           -0.8928579897344664,
+           -1.0013278478170438,
+           -1.114570553366741,
+           -1.2311500953961352,
+           -1.3494587853240856,
+           -1.4677541936608376,
+           -1.5842002633580863,
+           -1.6969115951204643,
+           -1.803999811988484,
+           -1.903620849576502,
+           -1.99402198609827,
+           -2.0735874236397462,
+           -2.1408812592118225,
+           -2.1946867403599133,
+           -2.2340407842214085,
+           -2.25826284890676,
+           -2.2669773792890404,
+           -2.2601292024896846,
+           -2.237991417811307,
+           -2.2011655074453857,
+           -2.1505735835181112,
+           -2.0874428792756823,
+           -2.013282782711537,
+           -1.9298548949943686,
+           -1.839136769110132,
+           -1.7432801418877033,
+           -1.6445646111099579,
+           -1.5453478252604842,
+           -1.4480133437132563,
+           -1.354917387557349,
+           -1.268335734161239,
+           -1.1904120111453416,
+           -1.123108617515047,
+           -1.0681614419277128,
+           -1.0270394617774137,
+           -1.0009101940353697,
+           -0.9906118322874509,
+           -0.9966327474548827,
+           -1.019098856067234,
+           -1.057769173886483,
+           -1.112039678675061,
+           -1.180955408673978,
+           -1.2632305277060374,
+           -1.3572758985037392,
+           -1.4612335274886101,
+           -1.5730170811377122,
+           -1.6903575302307108,
+           -1.8108528571715068,
+           -1.9320206661606631,
+           -2.0513524685663636,
+           -2.1663683780263736,
+           -2.274670942507007,
+           -2.373996863898343,
+           -2.4622654091358087,
+           -2.5376223989698,
+           -2.5984787693188234,
+           -2.6435428329453994,
+           -2.671845522713105,
+           -2.682758068136412,
+           -2.6760017401331795,
+           -2.6516494903348473,
+           -2.610119506309017,
+           -2.552160897830426,
+           -2.478831917164199,
+           -2.3914712936195217,
+           -2.2916634250795203,
+           -2.1811983128745256,
+           -2.06202724777218,
+           -1.9362153510945834,
+           -1.8058921437531894,
+           -1.6732013557107415,
+           -1.540251198152327,
+           -1.4090663003324453,
+           -1.2815424632628858,
+           -1.1594053044483048,
+           -1.0441737637855348,
+           -0.937129313187066,
+           -0.839291564710589,
+           -0.7514008077127299,
+           -0.6739078289340767,
+           -0.6069711848996205,
+           -0.5504619082062424,
+           -0.5039754428606701,
+           -0.46685042347601985,
+           -0.43819374331990746,
+           -0.4169112011475324,
+           -0.40174288028687183,
+           -0.3913022989357627,
+           -0.38411828089231653,
+           -0.37867843315576966,
+           -0.3734730825106938,
+           -0.36703851813415833,
+           -0.35799841149892436,
+           -0.345102337707034,
+           -0.3272604024805066,
+           -0.3035730842810333,
+           -0.2733555287206928,
+           -0.23615567929226491,
+           -0.1917657907432106,
+           -0.14022704500989966,
+           -0.08182717010533672,
+           -0.017091145131417528,
+           0.05323474497234758,
+           0.12820506780518817,
+           0.20670301565707697,
+           0.2874730453069133,
+           0.36915751171464445,
+           0.4503363166328001,
+           0.5295685130208827,
+           0.6054347531322611,
+           0.6765794436234005,
+           0.7417514756574883,
+           0.7998424316532746,
+           0.8499212322480276,
+           0.8912642756713557,
+           0.9233802348611145,
+           0.9460288124712126,
+           0.9592329070523097,
+           0.9632838112935251,
+           0.9587392410905603,
+           0.9464141778825401,
+           0.9273646915531017,
+           0.9028650925602887,
+           0.8743789352627082,
+           0.8435245552588309,
+           0.8120359678675587,
+           0.7817200789733877,
+           0.7544112601586873,
+           0.7319244147476397,
+           0.7160077081337886,
+           0.708296153292884,
+           0.710267230157709,
+           0.7231996757557909,
+           0.7481365116250491,
+           0.7858532776820046,
+           0.8368323197518883,
+           0.901243834327389,
+           0.9789342122956782,
+           1.0694220473138691,
+           1.1719019885354205,
+           1.2852564260641561,
+           1.4080748055503252,
+           1.5386801804834456,
+           1.6751624316261615,
+           1.8154174171122825,
+           1.957191168125156,
+           2.0981281174829105,
+           2.2358222450796994,
+           2.367869947567907,
+           2.491923391863229,
+           2.605743094253772,
+           2.7072484796015908,
+           2.7945652180975395,
+           2.86606820927892,
+           2.920419182837209,
+           2.956598010741618,
+           2.9739269723762516,
+           2.9720873801782397,
+           2.9511281536567733,
+           2.9114661202915983,
+           2.853878018024046,
+           2.7794843710934978
+          ],
+          [
+           2.718629227616586,
+           2.6203793423889628,
+           2.509748484656455,
+           2.388854351088727,
+           2.25999370090228,
+           2.12559225396921,
+           1.988151803019404,
+           1.850195772835008,
+           1.7142144944233666,
+           1.5826114666832594,
+           1.4576518519644797,
+           1.3414143958287565,
+           1.2357478766499554,
+           1.142233079541822,
+           1.0621511542171822,
+           0.9964590610873105,
+           0.9457726380241201,
+           0.9103576359535115,
+           0.8901288793452297,
+           0.8846575124192111,
+           0.8931860982764583,
+           0.9146511509121553,
+           0.9477125037436988,
+           0.9907887571735884,
+           1.0420979057114506,
+           1.0997021257276727,
+           1.1615556108677054,
+           1.2255542757537465,
+           1.2895861113853868,
+           1.351580968445395,
+           1.4095585676008238,
+           1.4616735881987497,
+           1.5062567670998182,
+           1.5418510456899932,
+           1.5672419326424876,
+           1.5814813994783639,
+           1.5839047916198996,
+           1.574140415276281,
+           1.5521116456889765,
+           1.518031590359282,
+           1.4723905271859563,
+           1.4159365173147145,
+           1.3496497614720164,
+           1.274711422433044,
+           1.1924677712534948,
+           1.104390627651998,
+           1.0120351527018794,
+           0.9169961126451083,
+           0.8208637647276809,
+           0.7251805187425964,
+           0.6313995014575283,
+           0.5408460960376884,
+           0.45468344640352676,
+           0.37388280932014684,
+           0.29919950765651504,
+           0.23115508998931028,
+           0.1700261383410789,
+           0.11583999149471161,
+           0.06837747044747325,
+           0.02718250975031186,
+           -0.008421581639829688,
+           -0.03930967921777104,
+           -0.06652683192168701,
+           -0.09125543714481275,
+           -0.11477848368695652,
+           -0.1384398479686172,
+           -0.16360270697210577,
+           -0.1916071822589521,
+           -0.2237283517320351,
+           -0.26113575897446656,
+           -0.30485551414963685,
+           -0.35573601646330866,
+           -0.414418237653818,
+           -0.4813113911450065,
+           -0.5565746752370831,
+           -0.6401056244344707,
+           -0.731535434585507,
+           -0.8302314491666967,
+           -0.9353068102690616,
+           -1.0456370932654546,
+           -1.159883563411551,
+           -1.276522520328535,
+           -1.3938800367968487,
+           -1.5101712556113218,
+           -1.623543286047388,
+           -1.732120642899768,
+           -1.83405209862878,
+           -1.9275577747857016,
+           -2.010975283791988,
+           -2.08280374679285,
+           -2.141744557429143,
+           -2.186737833971989,
+           -2.2169936016299063,
+           -2.232016870586095,
+           -2.2316259204597957,
+           -2.2159632648772694,
+           -2.1854989467010895,
+           -2.1410260008631106,
+           -2.0836481130933553,
+           -2.014759694417158,
+           -1.9360187783737608,
+           -1.8493133258594856,
+           -1.7567216869016171,
+           -1.660468115435834,
+           -1.5628743586264766,
+           -1.4663084432918623,
+           -1.3731318560272063,
+           -1.2856463587692952,
+           -1.206041696639744,
+           -1.1363454394959873,
+           -1.0783761530193006,
+           -1.033701020427064,
+           -1.0035989337808309,
+           -0.989029946814639,
+           -0.9906118322874504,
+           -1.0086043196668002,
+           -1.0429014075276422,
+           -1.09303195380273,
+           -1.1581685505950476,
+           -1.2371444934351088,
+           -1.3284784624254315,
+           -1.4304063493444994,
+           -1.5409194949467226,
+           -1.6578084485256603,
+           -1.7787112310062845,
+           -1.9011649765759644,
+           -2.02265974872986,
+           -2.1406932765066617,
+           -2.2528253368259428,
+           -2.3567305196688273,
+           -2.4502481540777676,
+           -2.531428243552734,
+           -2.5985723576360495,
+           -2.6502685498769756,
+           -2.6854195179065425,
+           -2.7032633854494583,
+           -2.703386664719968,
+           -2.6857291464073936,
+           -2.650580658727444,
+           -2.598569832041624,
+           -2.5306451965625323,
+           -2.448049123007,
+           -2.352285285293137,
+           -2.245080476392628,
+           -2.1283417395692266,
+           -2.004109884302744,
+           -1.8745105366587254,
+           -1.7417039258223632,
+           -1.6078346307825009,
+           -1.4749825032765502,
+           -1.3451159453821258,
+           -1.2200486535973551,
+           -1.1014008476304693,
+           -0.9905658838283105,
+           -0.8886830132262832,
+           -0.7966168861428959,
+           -0.7149442330553961,
+           -0.6439479695060356,
+           -0.5836187855616517,
+           -0.5336640925629281,
+           -0.4935240162384997,
+           -0.46239395029335195,
+           -0.43925302265537486,
+           -0.4228976816881523,
+           -0.4119794854278423,
+           -0.40504607633044504,
+           -0.4005842495782404,
+           -0.3970639764873153,
+           -0.39298222707606717,
+           -0.38690544776257496,
+           -0.3775095910845759,
+           -0.36361666317991503,
+           -0.3442268497293792,
+           -0.3185453996959357,
+           -0.2860035854510419,
+           -0.24627321420184994,
+           -0.19927433503916192,
+           -0.1451759641060611,
+           -0.08438983281499553,
+           -0.01755734608703587,
+           0.054469885366371894,
+           0.1306554071411691,
+           0.20980849221986203,
+           0.29061909945317166,
+           0.37169628278081773,
+           0.4516090234651923,
+           0.5289283928910838,
+           0.6022699167633493,
+           0.6703350037652612,
+           0.7319503231464272,
+           0.7861040657793159,
+           0.8319781007239169,
+           0.8689751423451094,
+           0.8967401689672675,
+           0.9151754797758488,
+           0.9244489385346945,
+           0.9249951266184515,
+           0.9175093094909857,
+           0.9029343055207846,
+           0.8824405292566134,
+           0.8573996583633543,
+           0.8293525398587245,
+           0.7999721028738572,
+           0.7710221780263208,
+           0.7443132342460917,
+           0.7216561296820667,
+           0.7048150319073426,
+           0.6954606924776444,
+           0.6951252611365353,
+           0.7051597954976608,
+           0.7266955635025254,
+           0.7606101497129918,
+           0.8074992646040408,
+           0.8676550211711452,
+           0.941051288631251,
+           1.0273365625472204,
+           1.125834608516058,
+           1.2355529471063333,
+           1.3551990556740736,
+           1.483203972768466,
+           1.6177528077563372,
+           1.7568214865842318,
+           1.8982189085261316,
+           2.039633552221621,
+           2.1786834557079784,
+           2.3129684073453585,
+           2.4401231247512944,
+           2.557870168638093,
+           2.6640713385961594,
+           2.7567763284563913,
+           2.834267479213599,
+           2.8950995561869703,
+           2.938133592021189,
+           2.9625639755343833,
+           2.9679381249589563,
+           2.95416825896265,
+           2.9215349657417544,
+           2.8706824649075804,
+           2.8026056541156312,
+           2.7186292276165895
+          ],
+          [
+           2.6516941556906026,
+           2.54577854377966,
+           2.4288299394037094,
+           2.303085394075447,
+           2.1709305748964325,
+           2.0348478034247264,
+           1.8973620407969392,
+           1.7609860769135213,
+           1.628166198593006,
+           1.5012295979923278,
+           1.3823347386327078,
+           1.2734258231637743,
+           1.176192406357262,
+           1.0920350712314357,
+           1.0220379387624678,
+           0.9669486159660428,
+           0.9271660073004752,
+           0.9027362247631708,
+           0.8933566373694888,
+           0.8983879056801264,
+           0.9168736564439651,
+           0.9475672708955339,
+           0.9889650922066767,
+           1.0393452071179132,
+           1.0968108275039608,
+           1.15933719266869,
+           1.2248208350209675,
+           1.2911300022922108,
+           1.3561550097461064,
+           1.4178573062905957,
+           1.4743160786757574,
+           1.5237712869563278,
+           1.5646621203142128,
+           1.5956599827119204,
+           1.6156952596200242,
+           1.6239772766442346,
+           1.620007034251131,
+           1.6035824856032181,
+           1.5747963121864352,
+           1.5340263397588576,
+           1.4819189204865084,
+           1.4193657814020562,
+           1.347475000201798,
+           1.2675369129059035,
+           1.1809858805086435,
+           1.0893589404306832,
+           0.9942524409499125,
+           0.897277801088805,
+           0.8000175536388667,
+           0.7039828148006914,
+           0.6105732807432511,
+           0.5210407803961062,
+           0.43645731683657446,
+           0.3576884092238107,
+           0.28537240645139456,
+           0.21990628613658084,
+           0.16143828225199539,
+           0.10986750596571467,
+           0.06485054162776073,
+           0.025814817958944518,
+           -0.008021622026234708,
+           -0.037624495522656114,
+           -0.06411249465764299,
+           -0.0887221719345408,
+           -0.1127694402587697,
+           -0.13760872054518286,
+           -0.16459083254855103,
+           -0.19502075910590103,
+           -0.2301164195355645,
+           -0.2709695643385089,
+           -0.31850985116264724,
+           -0.3734730825106936,
+           -0.4363744808755782,
+           -0.5074877494926223,
+           -0.5868305198968954,
+           -0.6741566246543286,
+           -0.768955459085683,
+           -0.8704585139136067,
+           -0.977652976115458,
+           -1.0893021125163602,
+           -1.2039719744249562,
+           -1.3200637963613568,
+           -1.4358513118469605,
+           -1.5495220781420789,
+           -1.6592217930834257,
+           -1.7631005035907714,
+           -1.8593595491586157,
+           -1.9462980562232295,
+           -2.0223578014808283,
+           -2.086165294072995,
+           -2.136569987356166,
+           -2.172677619314333,
+           -2.19387779445015,
+           -2.1998650564536066,
+           -2.1906528567830135,
+           -2.166579995694444,
+           -2.128309295022549,
+           -2.0768184516550843,
+           -2.013383212482923,
+           -1.9395532009085605,
+           -1.857120907074055,
+           -1.7680845243070162,
+           -1.6746054686443053,
+           -1.5789615528280998,
+           -1.4834968975084504,
+           -1.3905697477290189,
+           -1.302499419950063,
+           -1.221513632399108,
+           -1.149697468684871,
+           -1.0889451913611283,
+           -1.040916059229388,
+           -1.0069952110965352,
+           -0.9882605616256376,
+           -0.9854565146448576,
+           -0.9989751391945813,
+           -1.0288452775692085,
+           -1.0747298669158274,
+           -1.1359315611449639,
+           -1.2114065427247684,
+           -1.2997862191666418,
+           -1.3994063114084805,
+           -1.508342665428567,
+           -1.6244529585613214,
+           -1.7454233320259327,
+           -1.8688188645250685,
+           -1.9921367112568749,
+           -2.1128606705029878,
+           -2.2285159076078336,
+           -2.336722564418852,
+           -2.435247011132683,
+           -2.5220495562585667,
+           -2.5953275176051527,
+           -2.6535526706639634,
+           -2.6955022277031233,
+           -2.7202826579281707,
+           -2.727345832352427,
+           -2.716497162294693,
+           -2.6878955931447224,
+           -2.642045510488788,
+           -2.5797808090905012,
+           -2.502241561855566,
+           -2.410843901226918,
+           -2.3072438851988064,
+           -2.1932962604352726,
+           -2.071009152446817,
+           -1.942495804603836,
+           -1.8099245517695322,
+           -1.6754682490316473,
+           -1.541254380640199,
+           -1.409317048801872,
+           -1.28155198716632,
+           -1.1596756611167751,
+           -1.0451894084849682,
+           -0.9393494428197016,
+           -0.8431433901841181,
+           -0.7572738634535945,
+           -0.682149399433485,
+           -0.6178828982927541,
+           -0.5642975164627472,
+           -0.5209397779791309,
+           -0.48709948988448765,
+           -0.46183587921339,
+           -0.4440092164156129,
+           -0.432317056606908,
+           -0.4253341190537816,
+           -0.421554739513857,
+           -0.41943677154647313,
+           -0.4174457830722545,
+           -0.41409839396841724,
+           -0.4080036292751877,
+           -0.3979012198606034,
+           -0.3826958666355736,
+           -0.3614865934433268,
+           -0.3335904447627339,
+           -0.2985599340099907,
+           -0.2561938126803527,
+           -0.20654090565492622,
+           -0.1498969392576367,
+           -0.0867944714831618,
+           -0.017986213590483996,
+           0.05557779558885147,
+           0.13277854110750215,
+           0.2123611434759669,
+           0.29297184027547307,
+           0.3731978461601183,
+           0.4516090234651924,
+           0.5268002468870023,
+           0.5974333255814772,
+           0.6622773550760318,
+           0.7202464093981779,
+           0.7704335498622656,
+           0.8121402193829682,
+           0.8449002076948803,
+           0.868497510537546,
+           0.8829775612641625,
+           0.8886514825495911,
+           0.8860931846560663,
+           0.8761293205637946,
+           0.8598222925540762,
+           0.838446684893412,
+           0.8134596685534126,
+           0.7864660820716445,
+           0.7591790336913744,
+           0.7333769902139647,
+           0.710858414469242,
+           0.693395083458497,
+           0.6826852612082109,
+           0.6803079130450689,
+           0.6876791309496639,
+           0.7060118931936843,
+           0.7362802066730045,
+           0.7791885789857985,
+           0.835147641804744,
+           0.9042566004960867,
+           0.9862930208177437,
+           1.0807102858994475,
+           1.1866428699298714,
+           1.3029193836462125,
+           1.4280831555603186,
+           1.560419926588592,
+           1.6979920589966238,
+           1.8386784977127846,
+           1.980219577164634,
+           2.1202656434680724,
+           2.2564283631468665,
+           2.386333518072226,
+           2.5076740438160057,
+           2.6182620562243812,
+           2.716078629117686,
+           2.7993201342358134,
+           2.8664400317635295,
+           2.91618510415884,
+           2.9476252550729116,
+           2.9601761457856037,
+           2.953614110147052,
+           2.928082971429628,
+           2.8840925763297984,
+           2.8225090579542313,
+           2.744537036198008,
+           2.651694155690606
+          ],
+          [
+           2.5792454563125062,
+           2.4665543647301864,
+           2.3442599148879424,
+           2.2146995987931484,
+           2.080327827799446,
+           1.9436625518339974,
+           1.8072305744101793,
+           1.6735128355029087,
+           1.5448909333255862,
+           1.4235961244169175,
+           1.3116619800173788,
+           1.210881787012757,
+           1.1227716659612064,
+           1.048540239751951,
+           0.9890655276858714,
+           0.9448795651190736,
+           0.9161610625541544,
+           0.9027362247631706,
+           0.9040876549108817,
+           0.9193710754963322,
+           0.9474394119569534,
+           0.9868736105099533,
+           1.0360194034733463,
+           1.0930290967465932,
+           1.1559073386781606,
+           1.2225597399686832,
+           1.290843152675371,
+           1.358616384223098,
+           1.4237901202886876,
+           1.4843748584612981,
+           1.5385257119038889,
+           1.5845830273383463,
+           1.6211078723545504,
+           1.6469115804792698,
+           1.661078695254018,
+           1.6629828229093442,
+           1.652295082857557,
+           1.6289850316569139,
+           1.593314124669751,
+           1.5458219656437582,
+           1.4873057732634805,
+           1.4187936609105811,
+           1.3415124772988547,
+           1.2568510875775332,
+           1.1663200836829175,
+           1.0715089964969906,
+           0.9740421387162937,
+           0.8755342349084485,
+           0.7775469934238669,
+           0.6815477437592627,
+           0.5888712034942547,
+           0.5006853526095432,
+           0.41796228208309877,
+           0.34145475100199313,
+           0.2716790354167452,
+           0.2089044866543458,
+           0.15315004100746307,
+           0.10418774109755967,
+           0.06155314637768466,
+           0.024562330832865124,
+           -0.007665005500988228,
+           -0.03617694370109803,
+           -0.062156047082185056,
+           -0.08688225436937123,
+           -0.11169296273820582,
+           -0.13794137265689316,
+           -0.16695421308019512,
+           -0.19998998346112576,
+           -0.2381988377926508,
+           -0.28258519572910956,
+           -0.33397409775645004,
+           -0.39298222707606695,
+           -0.4599944026954006,
+           -0.5351462091388859,
+           -0.6183132716944673,
+           -0.7091075161247901,
+           -0.8068805725742825,
+           -0.9107342995065323,
+           -1.0195382195487366,
+           -1.1319534797482518,
+           -1.2464627784995495,
+           -1.3614055445967108,
+           -1.4750175144952777,
+           -1.5854737354880473,
+           -1.6909339281519655,
+           -1.7895890735534814,
+           -1.8797080510947557,
+           -1.9596831426280492,
+           -2.0280732379144957,
+           -2.0836436252690738,
+           -2.125401328197227,
+           -2.1526250521652686,
+           -2.1648889328709027,
+           -2.1620794254057167,
+           -2.1444048389179224,
+           -2.11239719974468,
+           -2.0669063131074985,
+           -2.009086084741855,
+           -1.9403733545412087,
+           -1.8624596797162987,
+           -1.77725668050531,
+           -1.686855722754547,
+           -1.593482854702666,
+           -1.4994500364663021,
+           -1.407103796995648,
+           -1.3187725222085669,
+           -1.2367136178525815,
+           -1.1630618003322688,
+           -1.0997797479611726,
+           -1.0486122942888432,
+           -1.011045265489659,
+           -0.988269957167579,
+           -0.9811541148809595,
+           -0.9902201303791801,
+           -1.0156309956479692,
+           -1.0571843734991164,
+           -1.114314951062823,
+           -1.1861050458227764,
+           -1.2713032375603395,
+           -1.3683506085231854,
+           -1.475413992957571,
+           -1.5904254702552858,
+           -1.7111271874309042,
+           -1.8351204700779293,
+           -1.9599180794333246,
+           -2.0829983991736585,
+           -2.2018602908654636,
+           -2.314077342670569,
+           -2.417350252295738,
+           -2.5095561318516726,
+           -2.588793598087786,
+           -2.6534226145198287,
+           -2.7020981797264483,
+           -2.7337971054143844,
+           -2.747837295069951,
+           -2.74388911502378,
+           -2.721978640118536,
+           -2.6824827512254386,
+           -2.6261162568351772,
+           -2.553911401091945,
+           -2.467190301311938,
+           -2.367531024835767,
+           -2.2567281639627934,
+           -2.1367488951070785,
+           -2.0096856111376433,
+           -1.8777062916703964,
+           -1.743003823084657,
+           -1.6077454971786758,
+           -1.4740239043279464,
+           -1.3438103941871054,
+           -1.2189122055345523,
+           -1.1009342686566221,
+           -0.9912465612229387,
+           -0.8909577550263448,
+           -0.8008957298784221,
+           -0.7215953564175571,
+           -0.6532937659792704,
+           -0.5959331375912758,
+           -0.5491708442824575,
+           -0.5123966179140478,
+           -0.4847562181987202,
+           -0.46518093177000014,
+           -0.4524220850492077,
+           -0.44508963372967186,
+           -0.44169379492117444,
+           -0.4406886177252115,
+           -0.4405163459302999,
+           -0.43965141360400634,
+           -0.4366429308606603,
+           -0.4301545625093638,
+           -0.4190007754202447,
+           -0.4021785293793369,
+           -0.37889360838040614,
+           -0.3485809315922023,
+           -0.31091834200691804,
+           -0.265833541975523,
+           -0.21350402411493347,
+           -0.15435002887857854,
+           -0.08902074177859136,
+           -0.018374119228617973,
+           0.05654910221796904,
+           0.13455650703010294,
+           0.214339372840677,
+           0.2945113625218335,
+           0.3736494979468922,
+           0.4503363166328001,
+           0.5232020800868294,
+           0.5909658993366257,
+           0.6524746689097504,
+           0.7067387548191321,
+           0.7529634635577714,
+           0.7905754256780703,
+           0.8192431565618409,
+           0.8388912052422137,
+           0.849707465896487,
+           0.8521434017731677,
+           0.846907113438701,
+           0.8349493677399691,
+           0.8174428861205216,
+           0.7957553662942524,
+           0.7714168753273279,
+           0.7460824007406904,
+           0.7214904755357412,
+           0.6994188997540254,
+           0.6816386625566297,
+           0.6698672227272989,
+           0.6657223305241942,
+           0.6706775692067737,
+           0.6860207603630631,
+           0.7128163141136944,
+           0.7518725148489067,
+           0.8037146175249866,
+           0.8685644915019626,
+           0.9463273918032203,
+           1.0365862653604534,
+           1.1386038165009138,
+           1.2513323661476963,
+           1.3734313476182718,
+           1.5032920932574223,
+           1.6390693851007672,
+           1.778719073830137,
+           1.9200409176569524,
+           2.0607256602653834,
+           2.1984052578861273,
+           2.3307050827026687,
+           2.455296875225461,
+           2.5699511934196124,
+           2.672588111925472,
+           2.7613249606069705,
+           2.834519957091671,
+           2.8908106813945125,
+           2.9291464599173644,
+           2.9488138682279317,
+           2.9494547236154602,
+           2.931076115587538,
+           2.894052210915431,
+           2.8391177649782056,
+           2.7673534682530923,
+           2.680163451055108,
+           2.579245456312506
+          ],
+          [
+           2.501896078262449,
+           2.3833770776446537,
+           2.256753911784933,
+           2.124444749064951,
+           1.9889519998499745,
+           1.8528079676872813,
+           1.718519956849714,
+           1.5885161118076043,
+           1.4650932450477638,
+           1.3503678602730302,
+           1.2462314996361652,
+           1.1543114382230413,
+           1.0759376190987007,
+           1.0121165710593236,
+           0.96351288250529,
+           0.9304386227029289,
+           0.9128509105975067,
+           0.9103576359535106,
+           0.9222311427051675,
+           0.9474294947561904,
+           0.984624764692621,
+           1.0322376203359531,
+           1.0884773367780693,
+           1.1513862360611289,
+           1.2188874560080352,
+           1.2888348762689594,
+           1.3590639851481199,
+           1.4274424562173313,
+           1.491919219372703,
+           1.5505708563666027,
+           1.6016442247329183,
+           1.643594314503543,
+           1.6751164666165714,
+           1.6951722272833132,
+           1.7030082751427624,
+           1.698168033702079,
+           1.680495765937457,
+           1.6501331364029703,
+           1.6075084140659095,
+           1.5533186716814156,
+           1.4885055103048002,
+           1.414224996238535,
+           1.3318126384050186,
+           1.2427443533656026,
+           1.1485944600538107,
+           1.0509918144537926,
+           0.9515752343031855,
+           0.8519493745130026,
+           0.753642195190145,
+           0.6580651164713086,
+           0.5664768791043678,
+           0.4799520288080113,
+           0.3993548185062141,
+           0.32531917874906496,
+           0.2582352466678422,
+           0.19824277174459595,
+           0.1452315368788833,
+           0.09884875027115414,
+           0.05851318215314933,
+           0.023435644979917306,
+           -0.007354749201264652,
+           -0.034979270696531936,
+           -0.06067404162710421,
+           -0.08575125098447775,
+           -0.11155815861220045,
+           -0.13943498991635617,
+           -0.17067285329829848,
+           -0.20647281343798102,
+           -0.24790722558750247,
+           -0.2958843796485708,
+           -0.35111741940720925,
+           -0.414098393968417,
+           -0.4850781678865513,
+           -0.5640527669995941,
+           -0.6507565723034813,
+           -0.7446625984885562,
+           -0.8449899114298794,
+           -0.9507180545743569,
+           -1.0606081724561633,
+           -1.1732303450943804,
+           -1.2869964842055521,
+           -1.4001979951371684,
+           -1.5110472809444875,
+           -1.6177220603597673,
+           -1.7184113922404234,
+           -1.8113622474998,
+           -1.8949254469030168,
+           -1.967599790112356,
+           -2.0280732379144952,
+           -2.075260074840236,
+           -2.1083330718626883,
+           -2.1267497863167675,
+           -2.1302722757787356,
+           -2.118979660979287,
+           -2.093273146023128,
+           -2.0538732879997066,
+           -2.0018094979681056,
+           -1.9384019465967581,
+           -1.865236235703737,
+           -1.7841313769148808,
+           -1.6971017861632718,
+           -1.6063141536196637,
+           -1.5140401790990472,
+           -1.4226062697582393,
+           -1.3343413772866863,
+           -1.2515242037470236,
+           -1.1763310273889265,
+           -1.1107853915178187,
+           -1.0567108609740015,
+           -1.015687982839207,
+           -0.9890164922318421,
+           -0.9776836827617088,
+           -0.9823397173019606,
+           -1.0032804916729328,
+           -1.0404384855651576,
+           -1.0933818458813676,
+           -1.161321752244291,
+           -1.2431279174520282,
+           -1.337351881959888,
+           -1.442257575745042,
+           -1.5558584476929227,
+           -1.6759603061529227,
+           -1.8002088783586914,
+           -1.926140984305313,
+           -2.051238135150057,
+           -2.1729813093311567,
+           -2.2889056327562263,
+           -2.3966536932372406,
+           -2.4940262537327156,
+           -2.579029193039247,
+           -2.649915594769526,
+           -2.7052220234885227,
+           -2.7437981678497425,
+           -2.764829191016692,
+           -2.767850304633048,
+           -2.7527532698061976,
+           -2.71978472240871,
+           -2.6695364157415193,
+           -2.6029276664605914,
+           -2.521180474943662,
+           -2.4257879644567257,
+           -2.3184769403671153,
+           -2.2011655074453866,
+           -2.075916796706697,
+           -1.9448899405503994,
+           -1.8102894940994414,
+           -1.6743145302507498,
+           -1.5391086353890204,
+           -1.4067120020974822,
+           -1.2790167553724003,
+           -1.1577265613842525,
+           -1.0443214549778927,
+           -0.9400286867416346,
+           -0.8458002360244606,
+           -0.7622974666326656,
+           -0.6898832213490173,
+           -0.6286214644091025,
+           -0.5782843923095152,
+           -0.5383667475123253,
+           -0.5081068913676531,
+           -0.4865140263200017,
+           -0.4724008073049003,
+           -0.4644204518806525,
+           -0.46110735127432634,
+           -0.4609201027693423,
+           -0.46228582969666193,
+           -0.4636446299918175,
+           -0.46349299840010644,
+           -0.4604251007691687,
+           -0.45317084054653056,
+           -0.44062974597580423,
+           -0.42189981926838416,
+           -0.3963006233174855,
+           -0.36339003388249086,
+           -0.3229742517179245,
+           -0.27511084561549654,
+           -0.22010477928616493,
+           -0.1584975578156474,
+           -0.09104980844718574,
+           -0.018717781144209893,
+           0.05737558756012103,
+           0.1359742625127272,
+           0.21572644359840792,
+           0.29522464113740704,
+           0.3730474169626483,
+           0.447801670643724,
+           0.5181643346098836,
+           0.5829223553813702,
+           0.6410098804271511,
+           0.691541640279312,
+           0.7338416117012735,
+           0.7674661675221465,
+           0.7922210592085287,
+           0.8081717358210798,
+           0.8156466737345227,
+           0.8152335710888929,
+           0.8077684448607537,
+           0.7943178520545403,
+           0.7761546351754489,
+           0.7547277613325319,
+           0.7316269797403807,
+           0.7085431600837466,
+           0.6872252906632271,
+           0.6694352074580103,
+           0.6569011908315239,
+           0.651271603836737,
+           0.6540697539246932,
+           0.6666511380294123,
+           0.6901641799423172,
+           0.7255154897776708,
+           0.7733405700474614,
+           0.8339807639463553,
+           0.9074670920259617,
+           0.9935114571608378,
+           1.0915055186525882,
+           1.20052734888561,
+           1.3193557947591987,
+           1.4464922759002683,
+           1.5801895671200343,
+           1.718486938296693,
+           1.8592508651819948,
+           2.0002203835270804,
+           2.139056039935928,
+           2.27339129897923,
+           2.4008851997173326,
+           2.519275017597273,
+           2.626427680695738,
+           2.7203887127273148,
+           2.7994275286254076,
+           2.862077990594502,
+           2.907173241382826,
+           2.933873964527746,
+           2.941689375281103,
+           2.930490417107009,
+           2.9005148229129456,
+           2.852363893053103,
+           2.786991038942344,
+           2.7056823370512237,
+           2.610029528346629,
+           2.5018960782624484
+          ],
+          [
+           2.420300432279727,
+           2.296950400009957,
+           2.1670522704778508,
+           2.0330844417603418,
+           1.897576171900505,
+           1.7630527218786276,
+           1.6319807200821181,
+           1.5067150165715262,
+           1.3894482583112338,
+           1.2821643498114899,
+           1.1865968689607234,
+           1.1041933875437628,
+           1.0360865029988489,
+           0.98307222587259,
+           0.945596190161654,
+           0.9237479656250496,
+           0.9172635568139454,
+           0.9255359777467932,
+           0.9476335986355835,
+           0.9823257765361838,
+           1.02811510974026,
+           1.0832755003229573,
+           1.1458950742676017,
+           1.2139228972560119,
+           1.2852183392021457,
+           1.357601883926578,
+           1.4289061533262157,
+           1.4970259185616868,
+           1.5599659039911338,
+           1.6158852519101994,
+           1.663137605982859,
+           1.7003058862595883,
+           1.7262309659536519,
+           1.7400336162138976,
+           1.7411292560670493,
+           1.7292352262176434,
+           1.7043704929510206,
+           1.6668478773056092,
+           1.6172590902636301,
+           1.5564530323464532,
+           1.4855079812922112,
+           1.4056984403563872,
+           1.3184575485465593,
+           1.2253360596249154,
+           1.1279589764181617,
+           1.027980978945305,
+           0.9270418078883128,
+           0.8267227584936837,
+           0.7285054043478025,
+           0.633733606589695,
+           0.5435797736914761,
+           0.45901622229280753,
+           0.3807923536677545,
+           0.3094182067077156,
+           0.245154780740885,
+           0.18801134433994876,
+           0.13774976399434774,
+           0.09389570376481036,
+           0.05575636842709375,
+           0.02244429267224814,
+           -0.00709347803575222,
+           -0.03404160936452966,
+           -0.05967901672916554,
+           -0.08533873058028131,
+           -0.11236616838465913,
+           -0.14207693564568716,
+           -0.17571529182391205,
+           -0.21441440136134843,
+           -0.25915944556627923,
+           -0.3107545989829847,
+           -0.3697947758563178,
+           -0.4366429308606601,
+           -0.5114135564449797,
+           -0.5939628605148785,
+           -0.6838859367200243,
+           -0.7805210596599712,
+           -0.8829610534010832,
+           -0.9900714984563507,
+           -1.1005153644517753,
+           -1.2127834875959234,
+           -1.3252301580509798,
+           -1.436112946297373,
+           -1.5436357830667744,
+           -1.6459942173362905,
+           -1.7414217135689167,
+           -1.8282358145256663,
+           -1.904882990528911,
+           -1.9699810202561088,
+           -2.0223578014808288,
+           -2.0610855714167093,
+           -2.0855096235246147,
+           -2.095270738226599,
+           -2.0903206957568656,
+           -2.070930406684231,
+           -2.0376903753578754,
+           -1.991503399235259,
+           -1.9335695981170942,
+           -1.8653640570134402,
+           -1.7886075499958063,
+           -1.7052309853899685,
+           -1.617334370724577,
+           -1.527141235022723,
+           -1.4369495628172757,
+           -1.3490803857424627,
+           -1.2658252413776734,
+           -1.1893937435487858,
+           -1.1218625125978532,
+           -1.065126688029673,
+           -1.020855189996162,
+           -0.9904508115855045,
+           -0.9750161128458311,
+           -0.9753259525507418,
+           -0.9918073381556681,
+           -1.0245271019596887,
+           -1.0731877263559297,
+           -1.1371314477200645,
+           -1.2153525716514153,
+           -1.3065177367355918,
+           -1.4089936745044416,
+           -1.5208818344462316,
+           -1.6400590791259442,
+           -1.7642235097048287,
+           -1.890944359929509,
+           -2.0177147999704674,
+           -2.142006422681106,
+           -2.2613241455917055,
+           -2.373260253194414,
+           -2.47554632601583,
+           -2.5661018550613437,
+           -2.6430784211608427,
+           -2.7048984265538407,
+           -2.7502874980718626,
+           -2.7782998342648644,
+           -2.788335939023671,
+           -2.7801523675005675,
+           -2.753863301939144,
+           -2.7099339707018,
+           -2.6491661185494415,
+           -2.572675925332558,
+           -2.4818649490917815,
+           -2.378384833794494,
+           -2.2640966675727947,
+           -2.1410260008631137,
+           -2.011314632313433,
+           -1.8771703413786298,
+           -1.7408157885048705,
+           -1.6044378157674446,
+           -1.4701383625719555,
+           -1.339888163100659,
+           -1.2154843158615856,
+           -1.0985127129517513,
+           -0.9903161901018992,
+           -0.8919691114355204,
+           -0.8042589388588153,
+           -0.7276751592198212,
+           -0.6624057572605594,
+           -0.6083412335586077,
+           -0.5650859788187044,
+           -0.5319766336999352,
+           -0.5081068913676529,
+           -0.49235804239620845,
+           -0.4834344224040339,
+           -0.47990280529723056,
+           -0.4802346921023429,
+           -0.4828503793338856,
+           -0.48616365324208,
+           -0.48862594798219733,
+           -0.48876882686473916,
+           -0.48524369577496185,
+           -0.47685773525950886,
+           -0.462605140649161,
+           -0.4416928852662687,
+           -0.41356036703143306,
+           -0.3778924599270286,
+           -0.3346256646914938,
+           -0.2839472334134513,
+           -0.2262873257929962,
+           -0.16230443609725742,
+           -0.09286450466676553,
+           -0.01901429180194505,
+           0.05805025917532393,
+           0.13701981270245042,
+           0.2165106205028926,
+           0.2951056414623435,
+           0.3713966970849583,
+           0.4440265297499725,
+           0.5117296320625059,
+           0.5733707457373173,
+           0.6279799869266733,
+           0.6747836402444971,
+           0.7132297738122143,
+           0.7430079596962549,
+           0.7640625348061917,
+           0.7765990028861659,
+           0.7810833544926441,
+           0.778234264366245,
+           0.7690083097688435,
+           0.7545785345161774,
+           0.736306857005,
+           0.7157109821114294,
+           0.6944266223143689,
+           0.6741659590634705,
+           0.6566733780430257,
+           0.6436795889305187,
+           0.6368552894985523,
+           0.6377655541372388,
+           0.6478261174805907,
+           0.6682626849427253,
+           0.7000743344828662,
+           0.7440019794130525,
+           0.8005027428072821,
+           0.8697309529555927,
+           0.9515263097726804,
+           1.0454095980249802,
+           1.1505861389600498,
+           1.2659569819488437,
+           1.3901376467773732,
+           1.5214840399784892,
+           1.6581249897227734,
+           1.7980006777394788,
+           1.938906097656309,
+           2.0785385407602854,
+           2.2145480057193545,
+           2.3445893509081626,
+           2.4663749586440495,
+           2.5777266611527567,
+           2.676625689006124,
+           2.761259443917107,
+           2.8300639682059554,
+           2.8817610813107204,
+           2.9153892770668253,
+           2.9303276211617604,
+           2.9263120526666273,
+           2.9034436728747597,
+           2.862188794488446,
+           2.8033707198759394,
+           2.72815341391209,
+           2.6380174300250987,
+           2.5347286327946477,
+           2.4203004322797312
+          ],
+          [
+           2.335148854451799,
+           2.2080055406273975,
+           2.0759139074426027,
+           1.94139162642012,
+           1.8069734248035167,
+           1.6751561844022838,
+           1.5483450252098874,
+           1.4288016240757804,
+           1.3185959639335258,
+           1.219562625593234,
+           1.1332626239515433,
+           1.060951656362344,
+           1.0035554761366907,
+           0.961652932494743,
+           0.9354670339795849,
+           0.9248641998718714,
+           0.9293616682197353,
+           0.9481428345031699,
+           0.9800801064302193,
+           1.0237646825017073,
+           1.0775424991011644,
+           1.139555446911374,
+           1.2077868359009687,
+           1.2801099918793788,
+           1.3543387989736104,
+           1.4282789629393369,
+           1.4997787608629334,
+           1.5667780636778634,
+           1.627354468400634,
+           1.6797654557506911,
+           1.722485593822264,
+           1.7542379370471555,
+           1.7740189185718307,
+           1.7811161996206646,
+           1.775119117278321,
+           1.7559215579492906,
+           1.7237172729042785,
+           1.6789878400932883,
+           1.6224836581300484,
+           1.55519852952933,
+           1.4783385466775567,
+           1.3932861317852117,
+           1.3015601978269242,
+           1.2047734883978585,
+           1.1045882183051903,
+           1.002671172052449,
+           0.9006494233606466,
+           0.8000678154371853,
+           0.7023492895218936,
+           0.6087590696981513,
+           0.5203736071284311,
+           0.4380550594606086,
+           0.36243193441986216,
+           0.2938863642966862,
+           0.23254830429659257,
+           0.1782967669460209,
+           0.13076802153799932,
+           0.08937050659325113,
+           0.05330602909111243,
+           0.021596661198972442,
+           -0.0068834024767377095,
+           -0.03337189274425644,
+           -0.05917939074925952,
+           -0.08564818326606902,
+           -0.11411015592727833,
+           -0.14584485778852255,
+           -0.1820388673453797,
+           -0.22374755780378822,
+           -0.27186029885627455,
+           -0.3270700449479317,
+           -0.38984814821661823,
+           -0.4604251007691694,
+           -0.5387777590665853,
+           -0.6246234367591282,
+           -0.7174210755299288,
+           -0.8163795208313861,
+           -0.9204727454446852,
+           -1.0284616832096358,
+           -1.1389221626330812,
+           -1.2502782697693209,
+           -1.3608403258541655,
+           -1.4688465413388125,
+           -1.5725073073877185,
+           -1.6700510111763032,
+           -1.7597702144067169,
+           -1.8400670166186666,
+           -1.909496436647525,
+           -1.9668066867747718,
+           -2.010975283791988,
+           -2.041240037711492,
+           -2.057124079883671,
+           -2.0584542348860375,
+           -2.045372201250567,
+           -2.018338180954415,
+           -1.9781267823134803,
+           -1.9258152109329802,
+           -1.862763953986108,
+           -1.7905903495877886,
+           -1.711135610773382,
+           -1.6264260381566846,
+           -1.5386293026190019,
+           -1.4500068056812063,
+           -1.3628632273549974,
+           -1.2794944466685765,
+           -1.2021350667822965,
+           -1.1329067934214816,
+           -1.0737689017617709,
+           -1.0264719831601383,
+           -0.992516090228999,
+           -0.9731142984164927,
+           -0.9691625768764746,
+           -0.9812167139991483,
+           -1.0094768770855127,
+           -1.0537802053022234,
+           -1.1136016446239974,
+           -1.1880630375867363,
+           -1.27595028410279,
+           -1.3757381971181182,
+           -1.4856224932107926,
+           -1.6035581878202616,
+           -1.727303511813501,
+           -1.8544683342694135,
+           -1.982565968911005,
+           -2.1090671611552447,
+           -2.2314550012408505,
+           -2.3472794875849545,
+           -2.4542104739202273,
+           -2.550087773633715,
+           -2.6329672640797988,
+           -2.701161930763945,
+           -2.7532769138038233,
+           -2.788237763962522,
+           -2.8053112792617587,
+           -2.8041184717102583,
+           -2.7846394026539043,
+           -2.74720982004848,
+           -2.6925097268147615,
+           -2.621544201581115,
+           -2.5356169768700823,
+           -2.4362974506754886,
+           -2.3253819612608075,
+           -2.204850288167995,
+           -2.076818451655082,
+           -1.943488965470867,
+           -1.8070997520747951,
+           -1.669872953873208,
+           -1.5339648682588443,
+           -1.4014181984449179,
+           -1.2741177472535175,
+           -1.1537505888416644,
+           -1.0417716361893605,
+           -0.9393753830071532,
+           -0.8474744410588878,
+           -0.7666853217010814,
+           -0.6973217280273741,
+           -0.6393954359320664,
+           -0.5926246533576862,
+           -0.5564495616693257,
+           -0.5300545660996996,
+           -0.5123966179140478,
+           -0.5022388234068885,
+           -0.49818842769089483,
+           -0.49873815758319273,
+           -0.502309830255101,
+           -0.5072990845515103,
+           -0.5121200711694329,
+           -0.5152489466470677,
+           -0.5152650540516571,
+           -0.5108887393337483,
+           -0.501014844800585,
+           -0.484741037657404,
+           -0.4613902690781884,
+           -0.43052681428030576,
+           -0.39196551263905705,
+           -0.3457740047015477,
+           -0.2922679455301055,
+           -0.2319993564943453,
+           -0.16573845581051438,
+           -0.09444947728615408,
+           -0.0192611425874864,
+           0.058567409036420735,
+           0.13768431177155085,
+           0.21668526906267496,
+           0.29415537028774214,
+           0.3687113041509464,
+           0.4390428333517763,
+           0.5039524129399829,
+           0.5623918813442081,
+           0.6134952272034218,
+           0.6566065349780635,
+           0.6913023353660986,
+           0.7174077297060655,
+           0.7350058172131444,
+           0.7444401260449184,
+           0.7463099294917178,
+           0.7414585124824657,
+           0.730954636445009,
+           0.7160676277335013,
+           0.698236681843819,
+           0.6790351282384404,
+           0.6601305349064622,
+           0.6432416443563548,
+           0.6300932206807958,
+           0.6223699483588375,
+           0.6216705559538662,
+           0.6294633409208187,
+           0.6470442451814816,
+           0.6754985755305934,
+           0.7156673795929014,
+           0.7681193789522971,
+           0.8331292288558041,
+           0.9106627217765352,
+           1.0003693838229621,
+           1.1015827326397651,
+           1.213328277500766,
+           1.3343391513876526,
+           1.4630790757049925,
+           1.5977721755946899,
+           1.7364389921242396,
+           1.876937881213061,
+           2.0170108519419494,
+           2.154332782307022,
+           2.2865628614246307,
+           2.4113970459361207,
+           2.5266202864878613,
+           2.6301572785377614,
+           2.7201205204856076,
+           2.7948545206147677,
+           2.8529750812066204,
+           2.8934027013861665,
+           2.9153892770668253,
+           2.918537433489022,
+           2.9028119994921373,
+           2.8685433186137077,
+           2.8164222858572314,
+           2.747487195798677,
+           2.6631026828195283,
+           2.5649312229068775,
+           2.454897844049561,
+           2.3351488544518
+          ],
+          [
+           2.2471617656586274,
+           2.1172950132553687,
+           1.9841098944710571,
+           1.850142065753548,
+           1.7179102987976709,
+           1.5898619997389425,
+           1.468320468057234,
+           1.3554351168771017,
+           1.2531358043861132,
+           1.16309232653276,
+           1.0866799964554295,
+           1.0249520892916901,
+           0.9786197657199406,
+           0.9480399078401047,
+           0.9332111112038799,
+           0.9337778815965643,
+           0.9490428893179244,
+           0.9779869419847592,
+           1.0192961539509169,
+           1.0713956207569688,
+           1.1324887546951856,
+           1.2006013062860919,
+           1.2736289893683963,
+           1.3493875471607069,
+           1.4256640449553903,
+           1.5002681532370374,
+           1.5710821934282833,
+           1.6361087568549646,
+           1.6935147748526183,
+           1.7416710124574581,
+           1.7791860774187416,
+           1.804934177312038,
+           1.8180760167676573,
+           1.8180724002579072,
+           1.8046902891701395,
+           1.7780012504548663,
+           1.7383724232843054,
+           1.6864503151874268,
+           1.6231379154568704,
+           1.5495657768915487,
+           1.4670578631218836,
+           1.377093084272154,
+           1.281263545479342,
+           1.181230608341684,
+           1.0786799129039233,
+           0.9752765261943593,
+           0.8726213722359841,
+           0.7722100582232708,
+           0.6753951432796222,
+           0.5833528016798897,
+           0.4970547140852662,
+           0.41724588123401163,
+           0.34442889821756084,
+           0.27885505793101467,
+           0.22052247383018078,
+           0.1691812292834625,
+           0.12434537821029491,
+           0.08531144397222287,
+           0.05118289512477949,
+           0.020899921905911847,
+           -0.006726299858510679,
+           -0.032975786941370114,
+           -0.059179390749259514,
+           -0.08667699093209019,
+           -0.11677536631628407,
+           -0.15070687801852878,
+           -0.18959007955233922,
+           -0.2343933200384936,
+           -0.2859023304914519,
+           -0.3446926814877229,
+           -0.41110787588368564,
+           -0.4852436957749616,
+           -0.5669392622147437,
+           -0.655775093383248,
+           -0.7510782662840322,
+           -0.8519346031951522,
+           -0.9572076216717536,
+           -1.0655638104994427,
+           -1.1755036281081883,
+           -1.285397468790799,
+           -1.39352570948171,
+           -1.4981218392353122,
+           -1.5974175877470485,
+           -1.68968891051809,
+           -1.773301658133945,
+           -1.8467557564554133,
+           -1.9087267534170858,
+           -1.9581036459660002,
+           -1.9940219860982695,
+           -2.015891375919938,
+           -2.0234165954836683,
+           -2.016611760573002,
+           -1.9958070768627987,
+           -1.9616479378177727,
+           -1.9150863018399387,
+           -1.8573644748901523,
+           -1.7899916133644231,
+           -1.714713443720122,
+           -1.6334758656987383,
+           -1.5483832607282864,
+           -1.4616524623371774,
+           -1.375563457771079,
+           -1.2924079766346723,
+           -1.2144371810691585,
+           -1.1438097011977733,
+           -1.0825412585238314,
+           -1.0324570885909712,
+           -0.9951483132038695,
+           -0.9719333232801355,
+           -0.9638251180784426,
+           -0.9715054078868297,
+           -0.9953061285994743,
+           -1.035198841796588,
+           -1.0907923072090768,
+           -1.1613383203333,
+           -1.2457457111842984,
+           -1.3426022055302915,
+           -1.4502036621821395,
+           -1.5665900235977495,
+           -1.6895871565061023,
+           -1.8168536183764905,
+           -1.9459312677945908,
+           -2.074298545031934,
+           -2.1994251855465965,
+           -2.318827095378721,
+           -2.430120114222395,
+           -2.5310714194359245,
+           -2.61964738171365,
+           -2.694056769170843,
+           -2.7527883090742242,
+           -2.794641752625813,
+           -2.8187517447383663,
+           -2.824603973792934,
+           -2.8120432617082476,
+           -2.781273447745253,
+           -2.7328491156017343,
+           -2.66765940773544,
+           -2.586904358753152,
+           -2.492064356546529,
+           -2.3848635013509125,
+           -2.267227775141374,
+           -2.1412390533317875,
+           -2.0090860847418552,
+           -1.873013632011951,
+           -1.7352710015317092,
+           -1.598061198687453,
+           -1.4634919207502437,
+           -1.3335295466926513,
+           -1.2099572020355918,
+           -1.09433786957807,
+           -0.987983386282119,
+           -0.8919300159726548,
+           -0.8069211206572016,
+           -0.7333972743546694,
+           -0.6714939768182969,
+           -0.6210469350942663,
+           -0.5816046931866756,
+           -0.5524482088584862,
+           -0.5326168062732622,
+           -0.5209397779791303,
+           -0.5160727734735872,
+           -0.5165379976044925,
+           -0.5207671531351056,
+           -0.5271460000747095,
+           -0.5340593713129046,
+           -0.5399354804376423,
+           -0.5432883833706731,
+           -0.542757509889173,
+           -0.5371432627725062,
+           -0.5254377890918245,
+           -0.5068501572952308,
+           -0.4808253219239219,
+           -0.4470564212429732,
+           -0.4054901276245003,
+           -0.3563249517469169,
+           -0.3000025849757871,
+           -0.23719254502575546,
+           -0.16877056359473172,
+           -0.09579131671978268,
+           -0.01945624503148702,
+           0.058922661821573595,
+           0.13796213775721441,
+           0.21624891167190988,
+           0.2923818673377425,
+           0.3650139577999892,
+           0.43289274577581355,
+           0.4948984760353234,
+           0.5500786483628014,
+           0.597678148879087,
+           0.6371641110157993,
+           0.6682448124144597,
+           0.6908820670815378,
+           0.7052967394085455,
+           0.7119671839474793,
+           0.7116205976424058,
+           0.7052174549397184,
+           0.6939293761850536,
+           0.6791109514042774,
+           0.6622662006007294,
+           0.6450104940333524,
+           0.6290288779352962,
+           0.6160318496582335,
+           0.6077096987354863,
+           0.6056865749449312,
+           0.6114754599144235,
+           0.6264352046680831,
+           0.6517307520208174,
+           0.6882975908843644,
+           0.7368113910548586,
+           0.7976636442820499,
+           0.8709439933573966,
+           0.9564297691231213,
+           1.0535830796685863,
+           1.1615556108677045,
+           1.2792011073915266,
+           1.4050953131053003,
+           1.537562964046956,
+           1.6747112506007644,
+           1.8144690024266257,
+           1.9546307042565614,
+           2.092904326474837,
+           2.2269618545865018,
+           2.354491328785397,
+           2.47324916073234,
+           2.5811114805138717,
+           2.6761232830040855,
+           2.7565441891782347,
+           2.8208897132694832,
+           2.867967029244014,
+           2.896904357447109,
+           2.907173241382826,
+           2.898603151832365,
+           2.8713880368413878,
+           2.8260846271134925,
+           2.763602502391915,
+           2.685186120722607,
+           2.5923892042854937,
+           2.4870420580806667,
+           2.3712125667080133,
+           2.247161765658627
+          ],
+          [
+           2.1570835764860092,
+           2.0255862700024156,
+           1.8924169350547373,
+           1.7601077723347556,
+           1.6311403082304945,
+           1.507891795286915,
+           1.3925840925891941,
+           1.287236208825114,
+           1.1936216022398256,
+           1.1132312169132204,
+           1.0472430965798725,
+           0.9964992589592043,
+           0.9614903391422591,
+           0.9423483242572144,
+           0.9388475079620375,
+           0.9504135970182499,
+           0.9761407080721672,
+           1.0148158055376573,
+           1.064949955690186,
+           1.1248156120110886,
+           1.19248900633654,
+           1.2658966028532415,
+           1.3428644802576426,
+           1.4211694436338642,
+           1.4985906332914376,
+           1.5729603936942806,
+           1.6422131917175993,
+           1.7044314290562155,
+           1.7578870772166308,
+           1.801078173008184,
+           1.832759345023803,
+           1.8519656939212914,
+           1.8580295175543313,
+           1.8505895519453632,
+           1.8295925862471922,
+           1.795287499544601,
+           1.748211954887356,
+           1.6891721666719208,
+           1.6192163269310569,
+           1.539602430069274,
+           1.4517613703126409,
+           1.3572562983266123,
+           1.2577393103670136,
+           1.1549066028749424,
+           1.0504532562016948,
+           0.946028812471214,
+           0.8431947845096748,
+           0.7433851760837459,
+           0.6478710098950883,
+           0.5577297510588122,
+           0.47382038294904605,
+           0.39676474267707423,
+           0.3269355588935888,
+           0.2644514592642966,
+           0.20917903330914567,
+           0.16074185292572551,
+           0.11853617248006523,
+           0.0817528574082463,
+           0.04940492920217893,
+           0.02035996952276376,
+           -0.006623499340311055,
+           -0.032856643190202976,
+           -0.05967901672916549,
+           -0.08841644939994941,
+           -0.12033925066576394,
+           -0.15662186144447118,
+           -0.1983050417725573,
+           -0.2462616200996978,
+           -0.3011667385300857,
+           -0.36347341312289966,
+           -0.43339409194131995,
+           -0.5108887393337481,
+           -0.5956598068295953,
+           -0.6871542732759125,
+           -0.7845727539185058,
+           -0.8868854946656138,
+           -0.992854888406691,
+           -1.1010639795399955,
+           -1.2099502651258796,
+           -1.3178439603450178,
+           -1.423009775797819,
+           -1.5236911577194443,
+           -1.6181558719008973,
+           -1.7047417698469707,
+           -1.7819015626136205,
+           -1.8482454442701983,
+           -1.902580452706009,
+           -1.9439455294932069,
+           -1.9716413409696176,
+           -1.9852540471912037,
+           -1.9846723508954414,
+           -1.9700973215541173,
+           -1.9420446659743513,
+           -1.9013393023838676,
+           -1.8491022849281924,
+           -1.786730315308009,
+           -1.71586826318355,
+           -1.638375292368772,
+           -1.5562853513566415,
+           -1.4717629303165682,
+           -1.387055108780297,
+           -1.304441015701651,
+           -1.226179893958759,
+           -1.15445900284992,
+           -1.0913426036094767,
+           -1.038723254071727,
+           -0.9982765897186815,
+           -0.9714206905828141,
+           -0.959281028671766,
+           -0.9626618612404167,
+           -0.9820247844664045,
+           -1.0174749935286687,
+           -1.0687556128281193,
+           -1.1352502685499488,
+           -1.2159938796062513,
+           -1.3096914469924072,
+           -1.4147444305183121,
+           -1.5292841203972147,
+           -1.6512112437200126,
+           -1.7782408965001282,
+           -1.9079517643915047,
+           -2.0378384924752986,
+           -2.165365989188849,
+           -2.28802440337071,
+           -2.4033834976419883,
+           -2.509145156316874,
+           -2.603192811362471,
+           -2.683636644495195,
+           -2.7488535254780886,
+           -2.7975207735699725,
+           -2.828642977765584,
+           -2.841571278314299,
+           -2.836014692932612,
+           -2.812043261708247,
+           -2.7700829802762543,
+           -2.71090268665682,
+           -2.6355932584081443,
+           -2.545539658810584,
+           -2.4423865392376234,
+           -2.327998255603467,
+           -2.2044142861658327,
+           -2.0738011428952836,
+           -1.9384019465967646,
+           -1.8004848851481998,
+           -1.6622917934818469,
+           -1.5259880828916665,
+           -1.3936152062669385,
+           -1.2670467760289448,
+           -1.1479493546923882,
+           -1.037748816560334,
+           -0.9376030361637034,
+           -0.848381498272789,
+           -0.7706522496716364,
+           -0.7046764287631427,
+           -0.6504104200550089,
+           -0.6075154913670385,
+           -0.5753745868952104,
+           -0.5531157736415986,
+           -0.5396416765093276,
+           -0.5336640925629271,
+           -0.5337428511188064,
+           -0.5383278864800829,
+           -0.5458034166823658,
+           -0.5545330763259988,
+           -0.5629048354828987,
+           -0.5693745500976828,
+           -0.5725070318303485,
+           -0.5710135957604237,
+           -0.5637851409426364,
+           -0.5499199389730152,
+           -0.5287454464060144,
+           -0.4998336144619329,
+           -0.46300933996479865,
+           -0.4183518805206268,
+           -0.36618924004124,
+           -0.3070857132008213,
+           -0.24182295466230633,
+           -0.17137510644601128,
+           -0.09687867039885363,
+           -0.01959794847898579,
+           0.05911301193146639,
+           0.13785094012588484,
+           0.21520524011157727,
+           0.2898001372498209,
+           0.3603359392552834,
+           0.4256282995459236,
+           0.4846444217516936,
+           0.5365352223159212,
+           0.5806625715936026,
+           0.6166208600622223,
+           0.6442522820351161,
+           0.6636553909314684,
+           0.6751866536341333,
+           0.6794549123781669,
+           0.6773088463892549,
+           0.6698177074840799,
+           0.6582457794448977,
+           0.6440211757333377,
+           0.6286997398238671,
+           0.6139249432978625,
+           0.6013847854925064,
+           0.5927667821448258,
+           0.5897121869314131,
+           0.5937706175771928,
+           0.6063562565060518,
+           0.6287067647819768,
+           0.6618459880300691,
+           0.7065514455425238,
+           0.763327480963995,
+           0.8323848175486875,
+           0.9136271062929989,
+           1.0066448850649736,
+           1.1107171853632394,
+           1.2248208350209666,
+           1.3476473146836596,
+           1.4776268379561273,
+           1.6129591444035465,
+           1.7516503256068334,
+           1.8915548514337919,
+           2.030421830430629,
+           2.165944428118252,
+           2.29581128278221,
+           2.4177587022297984,
+           2.529622398417244,
+           2.6293875205630766,
+           2.71523578135409,
+           2.7855885343649693,
+           2.8391447523703417,
+           2.874912973653809,
+           2.892236423898755,
+           2.8908106813945125,
+           2.870693429234971,
+           2.8323060256579127,
+           2.776426818116983,
+           2.7041763233618266,
+           2.616994589934417,
+           2.516611246336598,
+           2.405008913126145,
+           2.2843808160843344,
+           2.157083576486014
+          ],
+          [
+           2.065676389175189,
+           1.9336552083351357,
+           1.801610793121841,
+           1.6720504770270452,
+           1.5473975664860558,
+           1.4299390760678001,
+           1.3217766628133223,
+           1.2247818935422896,
+           1.1405568745753003,
+           1.0704011442844024,
+           1.0152855783432224,
+           0.9758338891845537,
+           0.952312119103648,
+           0.9446263351186541,
+           0.9523285377869855,
+           0.9746306004567147,
+           1.010425864673902,
+           1.0583178363109549,
+           1.1166552598267354,
+           1.1835726989652329,
+           1.2570356247459167,
+           1.3348889088574034,
+           1.4149075449863704,
+           1.4948483739730152,
+           1.5725015720447768,
+           1.64574067506319,
+           1.7125699552982077,
+           1.7711680395584373,
+           1.8199267566858701,
+           1.8574843259425606,
+           1.8827521425513307,
+           1.8949345789623984,
+           1.893541396236035,
+           1.8783925448655803,
+           1.8496153238077917,
+           1.8076340557290775,
+           1.7531526208236308,
+           1.6871303664515593,
+           1.610752070966075,
+           1.5253927834850884,
+           1.4325784835007354,
+           1.3339436021339341,
+           1.231186518163825,
+           1.1260241849956292,
+           1.0201470584869141,
+           0.9151754797758503,
+           0.8126186224295672,
+           0.7138370405649175,
+           0.6200097559915374,
+           0.5321067004377336,
+           0.4508671866748378,
+           0.37678492348980747,
+           0.3100999180144518,
+           0.25079742925895565,
+           0.19861395337325977,
+           0.15305003881565818,
+           0.11338955285648349,
+           0.07872485415393145,
+           0.04798717371955462,
+           0.019981372291020802,
+           -0.006575870661040576,
+           -0.03301546950080306,
+           -0.060674041627104124,
+           -0.0908518420638948,
+           -0.12477165690144526,
+           -0.16353976463000602,
+           -0.20811002148208546,
+           -0.25925204679841635,
+           -0.31752437917294696,
+           -0.38325334636544983,
+           -0.4565182449170476,
+           -0.537143262772506,
+           -0.6246964041075064,
+           -0.7184954943759886,
+           -0.8176211599115351,
+           -0.9209364948854716,
+           -1.027112953642349,
+           -1.1346618428372015,
+           -1.2419706395497023,
+           -1.3473432324312262,
+           -1.4490430762597666,
+           -1.5453381687865868,
+           -1.6345467045811415,
+           -1.7150822351615276,
+           -1.7854971687623444,
+           -1.8445234766300174,
+           -1.8911095349995433,
+           -1.9244521214283723,
+           -1.9440226987911768,
+           -1.949587257189883,
+           -1.941219139960174,
+           -1.9193044510315056,
+           -1.8845398229091075,
+           -1.8379225129984353,
+           -1.7807329862194259,
+           -1.714510329138937,
+           -1.6410210205272204,
+           -1.5622217508375726,
+           -1.480217134427532,
+           -1.3972132895879057,
+           -1.3154683693151419,
+           -1.237241207516105,
+           -1.1647392988752445,
+           -1.1000673545390287,
+           -1.0451776694046324,
+           -1.0018235002107088,
+           -0.9715165876322125,
+           -0.9554898617212194,
+           -0.9546662505415049,
+           -0.969634369581644,
+           -1.0006317079292648,
+           -1.0475357501579041,
+           -1.109863284712567,
+           -1.1867779548544415,
+           -1.2771059116794763,
+           -1.3793592351503552,
+           -1.4917666031987213,
+           -1.612310515302532,
+           -1.7387702197638093,
+           -1.8687693570457122,
+           -1.9998272183208818,
+           -2.129412431602248,
+           -2.254997829595701,
+           -2.374115225153185,
+           -2.484408822605303,
+           -2.5836860262530283,
+           -2.669964470088867,
+           -2.7415141838597563,
+           -2.7968939276473628,
+           -2.834980867359885,
+           -2.854992923472719,
+           -2.8565033011103136,
+           -2.8394468968334627,
+           -2.8041184717102583,
+           -2.75116267666544,
+           -2.681556209933484,
+           -2.596582572966281,
+           -2.4978000658326662,
+           -2.387003821757259,
+           -2.2661828191439928,
+           -2.137472924874346,
+           -2.0031071120967834,
+           -1.8653640570134435,
+           -1.7265163508977133,
+           -1.5887795650487784,
+           -1.454263377658927,
+           -1.324925913433031,
+           -1.2025323607774108,
+           -1.088618819671307,
+           -0.9844621987838161,
+           -0.8910568263934838,
+           -0.8090982700732259,
+           -0.7389746791625853,
+           -0.680765776276537,
+           -0.6342494341681459,
+           -0.598915586887363,
+           -0.5739870440016707,
+           -0.5584466081185212,
+           -0.5510697432269085,
+           -0.5504619082062411,
+           -0.5550995594898661,
+           -0.5633737419977413,
+           -0.573635130106325,
+           -0.5842393519510942,
+           -0.5935914313818976,
+           -0.6001882122988996,
+           -0.6026576890385335,
+           -0.5997942523929175,
+           -0.5905889714992323,
+           -0.5742541643778633,
+           -0.55024166093615,
+           -0.5182543279360021,
+           -0.4782506015346174,
+           -0.4304419550779245,
+           -0.375283413241907,
+           -0.31345740373527226,
+           -0.24585141004318845,
+           -0.17353004875326195,
+           -0.09770233881920899,
+           -0.01968505405469533,
+           0.059136848918035036,
+           0.1373516596598406,
+           0.21356308431534418,
+           0.2864320226287673,
+           0.35471682667054494,
+           0.41731095516440947,
+           0.47327700402834566,
+           0.5218761867163945,
+           0.5625924548304378,
+           0.5951505873163269,
+           0.6195277318918213,
+           0.6359580512563003,
+           0.6449303048405234,
+           0.6471783798664235,
+           0.6436649686741116,
+           0.6355587679975879,
+           0.6242057455999747,
+           0.611095176101163,
+           0.597821286960404,
+           0.5860414738575603,
+           0.5774321391092493,
+           0.5736432748148576,
+           0.5762529523624027,
+           0.5867228906469839,
+           0.6063562565060515,
+           0.6362588028360435,
+           0.6773043737354016,
+           0.7301057036347027,
+           0.7949913112010122,
+           0.8719891419148693,
+           0.9608174492128536,
+           1.060883226998625,
+           1.1712883205192623,
+           1.29084315267537,
+           1.418087813491222,
+           1.5513200764190058,
+           1.6886297309717866,
+           1.8279384612230283,
+           1.967044357981392,
+           2.103670032511955,
+           2.235513204561263,
+           2.3602985695769014,
+           2.475829711149682,
+           2.5800398158908378,
+           2.671039969491509,
+           2.7471638641531264,
+           2.8070078277428148,
+           2.8494651920260488,
+           2.8737541486032225,
+           2.879438393571187,
+           2.8664400317635295,
+           2.8350443945793034,
+           2.785896617441129,
+           2.7199900191587036,
+           2.6386465211322174,
+           2.5434895346415987,
+           2.4364099247870064,
+           2.3195258255700484,
+           2.1951372280806036,
+           2.0656763891751937
+          ],
+          [
+           1.9737135498930394,
+           1.8422796066345142,
+           1.7124597297233688,
+           1.5867151843951062,
+           1.4673905750535359,
+           1.3566633573602,
+           1.2564972416262505,
+           1.168600562796822,
+           1.0943905730006427,
+           1.0349644704415752,
+           0.9910778168107034,
+           0.9631308183472179,
+           0.9511627574988262,
+           0.954854667421726,
+           0.9735401450661697,
+           1.006224005104551,
+           1.0516082911840685,
+           1.1081249874394168,
+           1.1739746160906537,
+           1.2471697700758853,
+           1.3255825163238937,
+           1.406994518170408,
+           1.4891486666271168,
+           1.569800981087394,
+           1.6467715412284738,
+           1.7179932432299314,
+           1.7815572341134174,
+           1.8357539664381204,
+           1.8791089294987515,
+           1.9104122496826885,
+           1.9287415083122421,
+           1.9334772962242692,
+           1.9243112062498124,
+           1.9012461531174552,
+           1.864589100431782,
+           1.8149364615560952,
+           1.7531526208236308,
+           1.680342189080132,
+           1.597816758997508,
+           1.5070570571790325,
+           1.4096714985889507,
+           1.3073522316530244,
+           1.2018298175070905,
+           1.0948277130284456,
+           0.9880177239059595,
+           0.8829775612641628,
+           0.7811515741627298,
+           0.683815642263959,
+           0.5920471003843547,
+           0.506700432419471,
+           0.4283893196895612,
+           0.3574754619835069,
+           0.29406441272020184,
+           0.23800848718735615,
+           0.18891661937953397,
+           0.1461708631812172,
+           0.10894906207043714,
+           0.07625305248699688,
+           0.04694162352983129,
+           0.01976733331458074,
+           -0.006583816780878096,
+           -0.03345092213071299,
+           -0.062156047082184945,
+           -0.09396256439996171,
+           -0.1300350848608875,
+           -0.17140205898379687,
+           -0.21892206411577714,
+           -0.2732546952465432,
+           -0.33483685937828045,
+           -0.4038651340296194,
+           -0.48028469401289553,
+           -0.5637851409426361,
+           -0.6538033912962956,
+           -0.7495335957709055,
+           -0.8499438797938443,
+           -0.9537995169846126,
+           -1.059691978644882,
+           -1.1660731472643595,
+           -1.2712938445226472,
+           -1.3736457078590014,
+           -1.471405357365441,
+           -1.5628797289277265,
+           -1.6464514119263693,
+           -1.7206228214460848,
+           -1.7840580561250676,
+           -1.835621343065316,
+           -1.8744110494521335,
+           -1.8997883448245927,
+           -1.9113997257733537,
+           -1.9091927630987935,
+           -1.8934245965051808,
+           -1.8646628796738245,
+           -1.8237790646606364,
+           -1.7719341043961003,
+           -1.710556840918175,
+           -1.6413155301458424,
+           -1.5660831269370705,
+           -1.486897112547749,
+           -1.4059147864478916,
+           -1.3253650622369604,
+           -1.2474979001509563,
+           -1.1745325739999506,
+           -1.1086060066207222,
+           -1.0517224140936974,
+           -1.0057054748164849,
+           -0.9721541855557697,
+           -0.952403484058256,
+           -0.947490608640037,
+           -0.9581280320005463,
+           -0.9846836525264621,
+           -1.0271687552831865,
+           -1.0852340708834503,
+           -1.1581740679443542,
+           -1.2449394185798761,
+           -1.3441573811081262,
+           -1.4541596546452933,
+           -1.5730170811377122,
+           -1.698580406027321,
+           -1.8285261631709204,
+           -1.9604066264020426,
+           -2.0917026722502627,
+           -2.2198783282127454,
+           -2.342435740323778,
+           -2.456969283585203,
+           -2.561217559355098,
+           -2.6531120745410703,
+           -2.730821477167766,
+           -2.792790329634424,
+           -2.8377715321377828,
+           -2.8648516610996126,
+           -2.8734686572830506,
+           -2.8634214814567387,
+           -2.8348715474973947,
+           -2.788335939023671,
+           -2.7246726112428923,
+           -2.645057969904237,
+           -2.5509573994612245,
+           -2.444089478378404,
+           -2.3263847669562847,
+           -2.1999401785367407,
+           -2.06697004547475,
+           -1.9297550644262567,
+           -1.7905903495877895,
+           -1.6517338365313936,
+           -1.51535626294971,
+           -1.383493906451303,
+           -1.258005184748156,
+           -1.1405321220841829,
+           -1.0324675601459985,
+           -0.9349288451473762,
+           -0.8487385589685164,
+           -0.7744126852603971,
+           -0.7121564157108186,
+           -0.6618676118345822,
+           -0.6231477484112404,
+           -0.5953199807386395,
+           -0.5774538037468072,
+           -0.568395611017349,
+           -0.5668043198103152,
+           -0.5711911077876314,
+           -0.5799622111699264,
+           -0.5914636648864093,
+           -0.6040268245174227,
+           -0.6160134984159645,
+           -0.6258595365227531,
+           -0.6321157695157291,
+           -0.633485266791919,
+           -0.6288559824081482,
+           -0.617327981906913,
+           -0.5982345867480806,
+           -0.5711569331835644,
+           -0.5359316147746709,
+           -0.49265125798279946,
+           -0.4416580637948175,
+           -0.3835305305284798,
+           -0.31906374919399577,
+           -0.2492438286129826,
+           -0.17521715872944182,
+           -0.09825535337329828,
+           -0.019716824806029425,
+           0.05899397110958678,
+           0.1364685204977514,
+           0.21133633766433083,
+           0.2823060192483651,
+           0.3482041602809183,
+           0.4080110811283799,
+           0.46089239636303425,
+           0.5062255636386823,
+           0.5436206799542299,
+           0.5729349410009525,
+           0.5942803428667738,
+           0.6080243800828747,
+           0.614783675429664,
+           0.6154106604825959,
+           0.6109736069264742,
+           0.6027304826106454,
+           0.5920972687399039,
+           0.5806115213638264,
+           0.5698920876942245,
+           0.561595992481325,
+           0.5573735890126239,
+           0.5588231211938263,
+           0.5674458662432834,
+           0.5846030211132679,
+           0.611475459914423,
+           0.6490274251710096,
+           0.6979751241987486,
+           0.7587610854790193,
+           0.8315349914340583,
+           0.9161415468752975,
+           1.0121157704619859,
+           1.118685914008187,
+           1.2347840259244844,
+           1.3590639851481188,
+           1.489926645319613,
+           1.6255515503499693,
+           1.7639345163479785,
+           1.9029302253012608,
+           2.0402988466846432,
+           2.1737555975657417,
+           2.301022072474931,
+           2.4198781233434605,
+           2.528213048532155,
+           2.6240748589871523,
+           2.7057164287332856,
+           2.771637405373093,
+           2.8206208523974543,
+           2.851763716647065,
+           2.8645003582765556,
+           2.858618543592152,
+           2.834267479213599,
+           2.79195765482992,
+           2.732552456785046,
+           2.657251711095785,
+           2.567567507482523,
+           2.465292840873347,
+           2.3524637791085397,
+           2.2313160210146408,
+           2.1042368438345154,
+           1.973713549893039
+          ],
+          [
+           1.881973105873551,
+           1.7522325438388726,
+           1.6257180031969927,
+           1.5048238696292633,
+           1.3917962292840305,
+           1.2886845849020268,
+           1.1972981224705013,
+           1.1191675360691637,
+           1.055513285317668,
+           1.0072210056807298,
+           0.9748246205990172,
+           0.9584975201746864,
+           0.9580519784470621,
+           0.9729467848467714,
+           1.0023028700036454,
+           1.0449265164622576,
+           1.0993395656391272,
+           1.1638158678865025,
+           1.2364230767906388,
+           1.315068765343446,
+           1.3975497433498996,
+           1.481603384709307,
+           1.5649597316963044,
+           1.6453931320043662,
+           1.7207721832956846,
+           1.789106808773149,
+           1.8485913645673522,
+           1.8976427835283916,
+           1.934932887693039,
+           1.9594141500435667,
+           1.970338351461775,
+           1.9672677568780863,
+           1.9500786210794467,
+           1.9189570248337995,
+           1.8743872311932122,
+           1.8171329353679806,
+           1.7482119548873565,
+           1.6688650656098865,
+           1.5805198296179055,
+           1.4847503796926662,
+           1.3832342190351712,
+           1.277707161910884,
+           1.1699175793684269,
+           1.0615811232428012,
+           0.9543370811680754,
+           0.8497074658964874,
+           0.7490598651765024,
+           0.653574975795336,
+           0.564219619793223,
+           0.48172589552792827,
+           0.4065769549192623,
+           0.33899972494014824,
+           0.27896471064177836,
+           0.226192833286486,
+           0.1801690751616495,
+           0.14016252696113243,
+           0.10525226868332149,
+           0.07435836496804793,
+           0.046277124460730935,
+           0.019719663460038023,
+           -0.00664727047205413,
+           -0.03415931695363914,
+           -0.06411249465764286,
+           -0.0977222982895689,
+           -0.13608500356182537,
+           -0.18014222593788132,
+           -0.2306496949004463,
+           -0.28815109670193545,
+           -0.3529577077295609,
+           -0.4251343910648292,
+           -0.50449236431507,
+           -0.590588971499232,
+           -0.6827345101132818,
+           -0.7800059810779613,
+           -0.8812674487290294,
+           -0.9851965249253911,
+           -1.0903163301205894,
+           -1.1950321389722387,
+           -1.2976717924617411,
+           -1.3965288557842166,
+           -1.4899074240976415,
+           -1.5761674286064218,
+           -1.6537692747254993,
+           -1.7213166528335304,
+           -1.7775964002459081,
+           -1.8216143596543128,
+           -1.8526262728076635,
+           -1.8701628663924224,
+           -1.8740484270299451,
+           -1.8644123206166636,
+           -1.841693083995372,
+           -1.8066348999003532,
+           -1.760276454738282,
+           -1.7039323683737395,
+           -1.6391675709687572,
+           -1.5677651794492318,
+           -1.4916885909026565,
+           -1.4130386580240257,
+           -1.3340069389038232,
+           -1.2568261167788208,
+           -1.1837187622138576,
+           -1.116845658568715,
+           -1.0582549302482696,
+           -1.009833201586432,
+           -0.9732599724726252,
+           -0.9499663259344089,
+           -0.941098984501827,
+           -0.9474906086400365,
+           -0.9696370848112725,
+           -1.007682386331279,
+           -1.0614114110994026,
+           -1.130251010853284,
+           -1.2132792314364624,
+           -1.3092425874247684,
+           -1.416581002119699,
+           -1.533459860080713,
+           -1.6578084485256603,
+           -1.7873639102584722,
+           -1.9197196980450941,
+           -2.0523774118040277,
+           -2.1828008182652803,
+           -2.3084707998851735,
+           -2.426939957082207,
+           -2.535885595840538,
+           -2.6331598712221127,
+           -2.716835925396838,
+           -2.7852489547811703,
+           -2.837031262423215,
+           -2.8711404959180324,
+           -2.8868804343574297,
+           -2.8839138661281782,
+           -2.8622672884173284,
+           -2.8223273544501595,
+           -2.7648291910166916,
+           -2.690836901948977,
+           -2.6017167581953684,
+           -2.499103747506454,
+           -2.3848623123219768,
+           -2.261042239468761,
+           -2.1298307764963855,
+           -1.9935021342296835,
+           -1.8543655913991757,
+           -1.7147134437201228,
+           -1.5767700359602534,
+           -1.4426430815448235,
+           -1.3142784110187724,
+           -1.193419199858962,
+           -1.0815706100240337,
+           -0.9799706411807829,
+           -0.8895678302368843,
+           -0.8110062655804507,
+           -0.7446181995772253,
+           -0.6904243539605407,
+           -0.6481418224599742,
+           -0.6171992880693655,
+           -0.5967590933759161,
+           -0.5857455357744488,
+           -0.5828786092715829,
+           -0.5867122846216749,
+           -0.5956763128985695,
+           -0.6081204568752961,
+           -0.6223600016876141,
+           -0.6367213724285424,
+           -0.6495866920635469,
+           -0.6594361481344845,
+           -0.6648871001667326,
+           -0.6647289498330733,
+           -0.6579529104195997,
+           -0.6437759480380897,
+           -0.6216583208591508,
+           -0.5913143104807725,
+           -0.5527159171322178,
+           -0.5060894732394217,
+           -0.45190531331621386,
+           -0.39086081755684965,
+           -0.32385731735751067,
+           -0.2519715089755016,
+           -0.17642216266072644,
+           -0.09853303530775191,
+           -0.019692991938055345,
+           0.058685587317034056,
+           0.13520899439655365,
+           0.2085438394428191,
+           0.27745703496425034,
+           0.34085304019107465,
+           0.39780735858042215,
+           0.4475953781407068,
+           0.48971576443600995,
+           0.5239077567652604,
+           0.5501618755366219,
+           0.5687237192956995,
+           0.5800907089094489,
+           0.5850018195278808,
+           0.584420523507733,
+           0.5795113448597374,
+           0.5716105934725996,
+           0.5621920011081727,
+           0.5528281170344167,
+           0.5451484356892272,
+           0.5407953190033101,
+           0.5413788396130482,
+           0.548431706487562,
+           0.5633654405078757,
+           0.5874289440315523,
+           0.6216705559538653,
+           0.6669046034640539,
+           0.7236833555175691,
+           0.7922751535783582,
+           0.8726493455921575,
+           0.9644684831048087,
+           1.0670880630298651,
+           1.1795639092055448,
+           1.3006670991790426,
+           1.4289061533262148,
+           1.5625560211441112,
+           1.699693227889437,
+           1.8382363879720351,
+           1.9759911535832575,
+           2.110698551421081,
+           2.2400855699975546,
+           2.3619167971936066,
+           2.4740458740969586,
+           2.5744655276392305,
+           2.6613549713155087,
+           2.7331235197519375,
+           2.788449347780864,
+           2.826312435980345,
+           2.8460208796750015,
+           2.847229893927362,
+           2.8299530193135616,
+           2.7945652180975395,
+           2.741797743302079,
+           2.6727248594273303,
+           2.588742688403847,
+           2.491540643031841,
+           2.383066088043349,
+           2.2654830316797017,
+           2.1411257943218525,
+           2.0124487217296987,
+           1.8819731058735505
+          ],
+          [
+           1.7912312227861529,
+           1.6642758588462234,
+           1.5421194878001998,
+           1.4270693703086772,
+           1.321254091549581,
+           1.226577889869022,
+           1.1446801566820388,
+           1.0769010391341307,
+           1.0242539309723462,
+           0.987405472267803,
+           0.96666349910277,
+           0.9619731944660901,
+           0.9729214960217262,
+           0.9987496198935973,
+           1.0383733669311588,
+           1.0904106937706606,
+           1.1532158598585391,
+           1.2249193076032194,
+           1.3034722996909178,
+           1.3866952285433063,
+           1.4723284305177522,
+           1.5580842837022844,
+           1.6416993442785492,
+           1.7209852829213352,
+           1.793877419328848,
+           1.8584797187490913,
+           1.913105207583082,
+           1.9563108834316596,
+           1.9869263353217805,
+           2.0040754487745303,
+           2.007190743884097,
+           1.996020078336361,
+           1.9706256367355917,
+           1.9313753180256328,
+           1.8789268194721365,
+           1.8142048940023698,
+           1.7383724232843056,
+           1.6527960976988378,
+           1.5590076226767688,
+           1.4586614756114107,
+           1.3534903161874279,
+           1.245259203612079,
+           1.1357197957229401,
+           1.026565696832536,
+           0.919390083751489,
+           0.8156466737345244,
+           0.7166150058505717,
+           0.623370890881431,
+           0.5367627472960219,
+           0.45739438564631457,
+           0.3856146348401056,
+           0.32151402545548474,
+           0.2649285620914579,
+           0.21545043333499111,
+           0.17244532890199862,
+           0.13507586339862898,
+           0.10233044924000954,
+           0.07305682151085074,
+           0.045999298475067375,
+           0.019838766035932917,
+           -0.006765694887628203,
+           -0.035134660628827204,
+           -0.06652683192168685,
+           -0.10209923468271116,
+           -0.14287022795442963,
+           -0.18968631972485703,
+           -0.24319369277284109,
+           -0.3038152208675818,
+           -0.37173361364995905,
+           -0.44688116993211296,
+           -0.5289364479787191,
+           -0.6173279819069127,
+           -0.7112449902017925,
+           -0.8096548401285463,
+           -0.9113268551498221,
+           -1.0148618858133198,
+           -1.1187269121983099,
+           -1.2212938117868974,
+           -1.3208813139912619,
+           -1.4157990744206823,
+           -1.5043927405995325,
+           -1.5850888478706386,
+           -1.65643838054788,
+           -1.7171578591963657,
+           -1.7661668696575357,
+           -1.802621031814897,
+           -1.8259395141342698,
+           -1.835826331085079,
+           -1.8322848114499766,
+           -1.8156247925502729,
+           -1.7864622744353578,
+           -1.7457114546779358,
+           -1.694569253957246,
+           -1.6344926303892378,
+           -1.5671691618989567,
+           -1.4944815462979115,
+           -1.418466823862741,
+           -1.3412712632130057,
+           -1.2651019647242217,
+           -1.1921763237062883,
+           -1.1246705558711825,
+           -1.0646685186305729,
+           -1.0141120626481195,
+           -0.974754118710128,
+           -0.9481156660046384,
+           -0.9354476406791438,
+           -0.9376987301445162,
+           -0.9554898617212186,
+           -0.9890960371789979,
+           -1.038435991301061,
+           -1.1030699670147288,
+           -1.182205706384863,
+           -1.2747125605703764,
+           -1.379143427483174,
+           -1.4937640381083743,
+           -1.6165889358348775,
+           -1.7454233320259327,
+           -1.8779098793751958,
+           -2.0115792858157495,
+           -2.1439035987899118,
+           -2.272350924828267,
+           -2.394440314220633,
+           -2.5077955359586177,
+           -2.6101964942074725,
+           -2.699627093693684,
+           -2.77431844620672,
+           -2.8327864218397574,
+           -2.873862683915487,
+           -2.8967185024549034,
+           -2.900880813743441,
+           -2.8862401788147602,
+           -2.853050486987477,
+           -2.8019204472412493,
+           -2.7337971054143844,
+           -2.6499418141951536,
+           -2.5518992610700577,
+           -2.4414603224615528,
+           -2.3206196562888226,
+           -2.1915290666450638,
+           -2.0564477702890547,
+           -1.9176907629128876,
+           -1.7775765220714754,
+           -1.6383752923687755,
+           -1.5022591768586318,
+           -1.3712552072518935,
+           -1.2472024857730633,
+           -1.131714385423104,
+           -1.0261466656693805,
+           -0.931572210465232,
+           -0.8487629287645755,
+           -0.7781791785054074,
+           -0.7199668878547488,
+           -0.6739623569880295,
+           -0.639704534541813,
+           -0.6164543798087231,
+           -0.6032207492550761,
+           -0.5987920882795892,
+           -0.6017730701623604,
+           -0.6106252072702268,
+           -0.6237103676241355,
+           -0.639336065105556,
+           -0.6558013554112652,
+           -0.6714421631699043,
+           -0.684674888483539,
+           -0.6940371928892661,
+           -0.6982249439654064,
+           -0.6961244024655403,
+           -0.686838863249785,
+           -0.6697091081314513,
+           -0.6443271913211335,
+           -0.610543252294523,
+           -0.5684652322157149,
+           -0.5184515539225513,
+           -0.4610970072742293,
+           -0.397212256781764,
+           -0.32779755247003933,
+           -0.25401137372058885,
+           -0.17713486566858666,
+           -0.09853303530775191,
+           -0.019613757087620663,
+           0.05821430660680711,
+           0.1335837375170056,
+           0.20520921544938284,
+           0.27192609437765697,
+           0.332725660203394,
+           0.3867861156305292,
+           0.43349844815249367,
+           0.47248646948040124,
+           0.5036204655139077,
+           0.527024061362093,
+           0.5430740817785139,
+           0.5523933692342808,
+           0.5558367051125466,
+           0.5544701595238392,
+           0.549544367447822,
+           0.5424623889274681,
+           0.5347429548012337,
+           0.5279800232856944,
+           0.5237996734380046,
+           0.5238154365335509,
+           0.5295832137281488,
+           0.5425569467666485,
+           0.5640461974043143,
+           0.5951767508152026,
+           0.6368552894985511,
+           0.6897390886973018,
+           0.7542115644217984,
+           0.8303643637513087,
+           0.9179865276346753,
+           1.0165610828547123,
+           1.12526923644612,
+           1.2430021572037213,
+           1.3683801396707727,
+           1.4997787608629296,
+           1.6353614635800737,
+           1.773117836895933,
+           1.9109067183880366,
+           2.0465031175553063,
+           2.177647858832406,
+           2.3020987682259655,
+           2.4176821817909917,
+           2.5223435381548347,
+           2.6141958315681784,
+           2.691564746256166,
+           2.7530293661556002,
+           2.7974574547361795,
+           2.8240344251189042,
+           2.8322852681093065,
+           2.82208887149901,
+           2.79368434404211,
+           2.7476691475098716,
+           2.6849890355449264,
+           2.6069199939139263,
+           2.5150425684155504,
+           2.4112091494559724,
+           2.297504951688576,
+           2.176203578982978,
+           2.049718195621047,
+           1.92054943081376,
+           1.7912312227861575
+          ],
+          [
+           1.7022556180229278,
+           1.5791537050124511,
+           1.4623714648020056,
+           1.354109524681911,
+           1.2563609802560998,
+           1.1708687230047579,
+           1.0990885160613284,
+           1.042158665681596,
+           1.0008769782474554,
+           0.9756855185820977,
+           0.96666349910277,
+           0.9735284354441632,
+           0.995645507375604,
+           1.032044868901797,
+           1.081446463122622,
+           1.142291720307912,
+           1.2127813560139138,
+           1.2909183438399452,
+           1.3745550180256434,
+           1.4614431673854535,
+           1.5492859162962733,
+           1.6357901521358607,
+           1.7187182525263471,
+           1.795937890035714,
+           1.8654687459506352,
+           1.9255250469477705,
+           1.9745529468558487,
+           2.011261907475131,
+           2.0346493842907343,
+           2.044018291078847,
+           2.0389868976634196,
+           2.019491002948987,
+           1.9857784161681675,
+           1.938395968313211,
+           1.878169458297528,
+           1.806177110014169,
+           1.7237172729042778,
+           1.6322712360868046,
+           1.533462141179203,
+           1.4290110688691575,
+           1.3206914369230782,
+           1.2102828811666855,
+           1.09952579529494,
+           0.9900776801497384,
+           0.8834723990680399,
+           0.7810833544926444,
+           0.6840914943763006,
+           0.5934589277481155,
+           0.5099087804584541,
+           0.4339117583583595,
+           0.3656797101655187,
+           0.30516630045952375,
+           0.25207471923740415,
+           0.20587217289745205,
+           0.16581072698897215,
+           0.13095390796918693,
+           0.10020832365512974,
+           0.07235943376200836,
+           0.04611049610639699,
+           0.020123633380578838,
+           -0.006938088103456908,
+           -0.036368701307437176,
+           -0.06937863248856319,
+           -0.10705634271691677,
+           -0.1503333519699897,
+           -0.19995359299253607,
+           -0.25644792983473735,
+           -0.3201145421649463,
+           -0.3910057244791963,
+           -0.4689214830417245,
+           -0.5534101369949767,
+           -0.6437759480380904,
+           -0.7390936199991428,
+           -0.8382293301588312,
+           -0.9398677828758703,
+           -1.0425446172715578,
+           -1.144683358497735,
+           -1.2446359800727804,
+           -1.340726046056642,
+           -1.4312933289988627,
+           -1.5147387545388276,
+           -1.5895685074764148,
+           -1.6544361475504696,
+           -1.7081816258106344,
+           -1.7498661633606496,
+           -1.7788020516951686,
+           -1.7945765554862214,
+           -1.7970692415287213,
+           -1.7864622181195011,
+           -1.7632429434636698,
+           -1.728199445466235,
+           -1.682407983921327,
+           -1.6272133749689734,
+           -1.5642023820477766,
+           -1.4951707528291538,
+           -1.422084643389564,
+           -1.3470373150997061,
+           -1.2722021127498981,
+           -1.1997828311705037,
+           -1.1319626495231132,
+           -1.0708528556682064,
+           -1.018442596399825,
+           -0.9765508724550447,
+           -0.9467819503793807,
+           -0.9304852876231695,
+           -0.9287209644370138,
+           -0.9422314886768198,
+           -0.9714206905828137,
+           -1.0163402575614178,
+           -1.0766842780215982,
+           -1.1517919727954167,
+           -1.2406585972442223,
+           -1.3419543015827282,
+           -1.4540505460177164,
+           -1.5750534856639689,
+           -1.7028435723105806,
+           -1.8351204700779329,
+           -1.9694522535062606,
+           -2.1033277528034096,
+           -2.2342108344017255,
+           -2.3595953575158237,
+           -2.47705953022621,
+           -2.5843184021681593,
+           -2.6792732748597623,
+           -2.7600568839909565,
+           -2.8250733088335274,
+           -2.8730316898612616,
+           -2.9029729836190157,
+           -2.9142891502389126,
+           -2.906734349712797,
+           -2.8804279136848,
+           -2.835849055477929,
+           -2.7738234775398833,
+           -2.695502227703123,
+           -2.602333338929055,
+           -2.4960269570966593,
+           -2.378514813786347,
+           -2.2519050322191143,
+           -2.1184333613823347,
+           -1.9804120133534506,
+           -1.8401773300307396,
+           -1.7000375267171124,
+           -1.5622217508375706,
+           -1.4288316548110762,
+           -1.3017966137908201,
+           -1.1828336233939414,
+           -1.0734127920924554,
+           -0.9747292006690847,
+           -0.8876817406237357,
+           -0.8128593686613252,
+           -0.7505350297544677,
+           -0.7006673113449857,
+           -0.6629097007368103,
+           -0.6366271313538023,
+           -0.6209193258902723,
+           -0.6146502798434487,
+           -0.616483081524406,
+           -0.6249191380007048,
+           -0.6383407736096429,
+           -0.655056091175799,
+           -0.6733449376898542,
+           -0.6915047970724755,
+           -0.7078954431404995,
+           -0.720981225656646,
+           -0.7293699302913295,
+           -0.7318472476676672,
+           -0.7274060049534476,
+           -0.7152694526667245,
+           -0.6949080559177194,
+           -0.6660494092321393,
+           -0.6286810730758805,
+           -0.5830463136929127,
+           -0.5296329112357038,
+           -0.4691553797786906,
+           -0.4025311121533224,
+           -0.330851118359553,
+           -0.2553461646694518,
+           -0.17734923796307422,
+           -0.09825535337329828,
+           -0.01947979061741422,
+           0.057584116226971405,
+           0.131606500267745,
+           0.20136067811194108,
+           0.26575999174872683,
+           0.3238907816302528,
+           0.3750405969812239,
+           0.4187208728050285,
+           0.45468344640352565,
+           0.48293044586425765,
+           0.5037172548552625,
+           0.5175484378552055,
+           0.5251666930842093,
+           0.527535082248973,
+           0.5258129621629054,
+           0.5213262088798446,
+           0.5155324759754096,
+           0.5099823611716785,
+           0.5062774662346646,
+           0.5060264211296257,
+           0.5108000025612224,
+           0.5220865076904908,
+           0.5412485451566837,
+           0.5694823774212098,
+           0.6077808915129088,
+           0.6569011908315222,
+           0.7173376907929598,
+           0.7893014684499373,
+           0.8727064640442532,
+           0.9671629644862226,
+           1.0719786191589664,
+           1.1861670516563818,
+           1.3084639417185175,
+           1.43735026443662,
+           1.5710821934282877,
+           1.7077270056396707,
+           1.845204171952248,
+           1.981330683716964,
+           2.1138695540951913,
+           2.24058034748301,
+           2.3592705325326695,
+           2.4678464258792725,
+           2.564362495424228,
+           2.647067823969591,
+           2.714448595443047,
+           2.7652655554762027,
+           2.7985855135779825,
+           2.8138060928158333,
+           2.810673091439258,
+           2.789289995417681,
+           2.750119367182357,
+           2.6939760294284802,
+           2.6220121589323075,
+           2.5356945991841027,
+           2.4367748874956807,
+           2.327252667540978,
+           2.2093333177394383,
+           2.0853807655875958,
+           1.957866574559644,
+           1.8293164806727298,
+           1.702255618022929
+          ],
+          [
+           1.6157990654621017,
+           1.4975862542772123,
+           1.387148638563373,
+           1.2865616060576783,
+           1.1976659204896027,
+           1.1220284090695984,
+           1.0609089265184801,
+           1.0152343519120763,
+           0.9855802067412424,
+           0.9721603007351358,
+           0.974824620599017,
+           0.9930654805414246,
+           1.0260317570899076,
+           1.0725508389984821,
+           1.1311577406934519,
+           1.2001306591130687,
+           1.2775321030540758,
+           1.3612545948852066,
+           1.4490698398323976,
+           1.5386801804834498,
+           1.627771105532111,
+           1.7140635632007755,
+           1.7953648416244532,
+           1.8696168203748649,
+           1.934940468142373,
+           1.9896755595542608,
+           2.032414706705981,
+           2.0620309451297683,
+           2.077698276010694,
+           2.0789047424362788,
+           2.065457802950844,
+           2.0374819560730217,
+           1.995408760006462,
+           1.9399595778182206,
+           1.8721215552876336,
+           1.793117502088533,
+           1.7043704929510208,
+           1.6074641303906316,
+           1.5040995114581428,
+           1.3960500153239082,
+           1.2851150746023647,
+           1.1730741100895583,
+           1.0616417957060242,
+           0.9524257783265646,
+           0.8468879069830906,
+           0.7463099294917179,
+           0.6517644943778205,
+           0.5640921551388204,
+           0.4838849159915242,
+           0.41147668731693193,
+           0.3469408393789049,
+           0.2900948591031632,
+           0.24051193140659438,
+           0.1975390883913835,
+           0.16032140115694662,
+           0.12783153428094587,
+           0.09890384607140341,
+           0.07227210193744754,
+           0.04660977657244125,
+           0.02057185538733612,
+           -0.007162991594925501,
+           -0.03785099844691811,
+           -0.07264376883502136,
+           -0.11255168301509884,
+           -0.15841123420223188,
+           -0.2108571799630778,
+           -0.2703002692429808,
+           -0.33691116096032314,
+           -0.4106109894389254,
+           -0.4910688593713993,
+           -0.5777063728802924,
+           -0.669709108131452,
+           -0.7660447874955953,
+           -0.8654876980530555,
+           -0.9666487627436893,
+           -1.0680105108653895,
+           -1.1679660657377404,
+           -1.2648611585237381,
+           -1.357038093244763,
+           -1.4428805311137944,
+           -1.5208579339559758,
+           -1.5895685074764145,
+           -1.6477795155304469,
+           -1.694463895672574,
+           -1.7288321927066757,
+           -1.7503589386451526,
+           -1.7588027416855854,
+           -1.7542195002387817,
+           -1.7369683269130598,
+           -1.7077099475031874,
+           -1.6673975269853203,
+           -1.6172600636382755,
+           -1.558778678988601,
+           -1.4936563106570326,
+           -1.4237814828797357,
+           -1.3511869812827662,
+           -1.2780043905799146,
+           -1.206415562901776,
+           -1.1386021676697777,
+           -1.0766945291598944,
+           -1.0227209837014377,
+           -0.9785589840960149,
+           -0.9458891443347109,
+           -0.9261533537958244,
+           -0.9205179983071657,
+           -0.929843207932884,
+           -0.9546589109104573,
+           -0.9951483132038687,
+           -1.0511392475259438,
+           -1.1221036486796878,
+           -1.2071652182255936,
+           -1.305115145524457,
+           -1.4144355589173125,
+           -1.5333301949097273,
+           -1.6597615992762613,
+           -1.7914940162525599,
+           -1.9261409843053166,
+           -2.061216542743103,
+           -2.1941888654607045,
+           -2.3225350785616965,
+           -2.4437959889488483,
+           -2.5556294519488603,
+           -2.6558611376356973,
+           -2.7425315169754776,
+           -2.813937978743207,
+           -2.8686711041726003,
+           -2.9056442656670303,
+           -2.9241158752257403,
+           -2.923703783638999,
+           -2.904391518702442,
+           -2.866526245131377,
+           -2.8108085257829933,
+           -2.738274158423757,
+           -2.650268549876975,
+           -2.548414265394519,
+           -2.4345725512492944,
+           -2.310799768967398,
+           -2.1792997969262036,
+           -2.0423735464232977,
+           -1.902366802599822,
+           -1.7616176343006507,
+           -1.622404620323592,
+           -1.4868971125477495,
+           -1.357108699880442,
+           -1.2348549522926557,
+           -1.1217164135843918,
+           -1.019007677728366,
+           -0.9277532300437172,
+           -0.8486705648918245,
+           -0.7821609102921621,
+           -0.7283077013351844,
+           -0.6868827531983662,
+           -0.6573598956801538,
+           -0.638935649119454,
+           -0.6305563508497528,
+           -0.6309509861403346,
+           -0.6386688417007789,
+           -0.6521209865789882,
+           -0.6696244974072554,
+           -0.6894482845482064,
+           -0.7098593441769371,
+           -0.7291682593987997,
+           -0.7457728010964794,
+           -0.7581985355415704,
+           -0.7651354293939987,
+           -0.765469551369928,
+           -0.758309100784656,
+           -0.7430041430189559,
+           -0.719159596895968,
+           -0.6866411947992255,
+           -0.6455743186535727,
+           -0.5963357990164962,
+           -0.5395389458363881,
+           -0.47601225335175373,
+           -0.4067723837482706,
+           -0.3329921804768721,
+           -0.25596458888666324,
+           -0.1770634658575731,
+           -0.09770233881920903,
+           -0.01929222594439449,
+           0.056800347873304784,
+           0.12929401097061102,
+           0.1970307877978516,
+           0.25901089509589387,
+           0.31442315154220934,
+           0.36267017503518967,
+           0.4033876770726802,
+           0.4364573168365733,
+           0.4620127447448915,
+           0.4804386421456286,
+           0.49236274602385127,
+           0.4986410304596795,
+           0.5003363954732231,
+           0.4986913842821418,
+           0.49509560754615295,
+           0.4910486938659295,
+           0.4881197060459097,
+           0.4879040593344981,
+           0.4919790485211109,
+           0.5018591335472851,
+           0.5189521470254532,
+           0.5445175713273466,
+           0.5796279880157189,
+           0.6251347293909272,
+           0.6816386625566278,
+           0.7494669130887848,
+           0.82865619113554,
+           0.9189432211286852,
+           1.0197626012384444,
+           1.1302522345837034,
+           1.2492662855873822,
+           1.3753954264311432,
+           1.5069939550117175,
+           1.642213191717604,
+           1.77904040209128,
+           1.9153423500443671,
+           2.048912465344927,
+           2.1775205126661095,
+           2.2989635800416344,
+           2.411117163921114,
+           2.5119851172538734,
+           2.5997472465128335,
+           2.6728033929130066,
+           2.7298129111569716,
+           2.769728564015151,
+           2.79182398041802,
+           2.795713975390788,
+           2.7813671984591095,
+           2.7491107590166894,
+           2.699626668151913,
+           2.633940131928747,
+           2.5533999263377405,
+           2.4596512743071486,
+           2.3546018256413497,
+           2.2403815071146127,
+           2.1192971581172784,
+           1.9937829935926725,
+           1.8663480374151549,
+           1.7395217433482035,
+           1.6157990654621028
+          ],
+          [
+           1.5325930266603751,
+           1.4202636041834182,
+           1.317087428232997,
+           1.224997100393322,
+           1.145665499015531,
+           1.0804701592199284,
+           1.0304644046574862,
+           0.9963558897034513,
+           0.978493034062517,
+           0.9768596436650815,
+           0.9910778168107022,
+           1.020419037515737,
+           1.0638231637421183,
+           1.1199248313474728,
+           1.1870866197407894,
+           1.26343816659142,
+           1.3469202803590177,
+           1.4353329842276445,
+           1.5263863360003547,
+           1.6177528077563383,
+           1.7071199780093762,
+           1.792242288420297,
+           1.8709906467461204,
+           1.9413987168480227,
+           2.0017048236980064,
+           2.0503885142034735,
+           2.086200950462403,
+           2.108188467363764,
+           2.115708797377864,
+           2.1084396476820415,
+           2.086379503909418,
+           2.0498407261040383,
+           1.9994351911838233,
+           1.9360529176967076,
+           1.860834278438625,
+           1.775136560418053,
+           1.6804957659374573,
+           1.5785846599498516,
+           1.4711681546477693,
+           1.360057180403702,
+           1.2470622213490081,
+           1.1339476934211703,
+           1.02238831273542,
+           0.9139285434901185,
+           0.8099461288543512,
+           0.7116205976424071,
+           0.619907506903253,
+           0.5355190292384366,
+           0.45891132756455527,
+           0.3902789833750275,
+           0.32955656180655485,
+           0.2764272126001826,
+           0.23033802501629813,
+           0.19052168148247034,
+           0.1560237935864092,
+           0.12573515902819837,
+           0.0984280529594715,
+           0.07279556490392214,
+           0.047492915734530336,
+           0.021179639895204803,
+           -0.00743850257672616,
+           -0.039569011142722856,
+           -0.07629461643007926,
+           -0.11853876251166487,
+           -0.1670355321121879,
+           -0.22230483135678186,
+           -0.28463351393792247,
+           -0.3540629702581467,
+           -0.4303835391161034,
+           -0.5131359220955864,
+           -0.6016195984849037,
+           -0.694908055917719,
+           -0.7918704736185876,
+           -0.8911993256842816,
+           -0.9914432155450655,
+           -1.0910441136115632,
+           -1.1883780516795313,
+           -1.2817982329780777,
+           -1.3696794482551284,
+           -1.4504626477923166,
+           -1.5226985078241477,
+           -1.5850888478706393,
+           -1.6365248026068626,
+           -1.6761207269864966,
+           -1.7032429146053265,
+           -1.7175323342719093,
+           -1.718920735384951,
+           -1.7076396354163024,
+           -1.6842218785465004,
+           -1.6494956389436195,
+           -1.6045709307361442,
+           -1.5508188747141454,
+           -1.4898441545111754,
+           -1.423451267903433,
+           -1.3536053375784876,
+           -1.2823883862804994,
+           -1.211952100082558,
+           -1.144468197649108,
+           -1.0820775903198268,
+           -1.0268395559240138,
+           -0.9806821573876351,
+           -0.9453551151267726,
+           -0.9223862903816066,
+           -0.9130428562211006,
+           -0.9182981258344893,
+           -0.938804876478957,
+           -0.9748758552298576,
+           -1.0264719831601377,
+           -1.093198591870753,
+           -1.1743098348470629,
+           -1.26872122059224,
+           -1.375030019660195,
+           -1.4915431083389363,
+           -1.6163116324551294,
+           -1.7471717099732331,
+           -1.881790244790283,
+           -2.0177147999704674,
+           -2.152426379674965,
+           -2.2833938976594292,
+           -2.4081290681970535,
+           -2.5242404436841976,
+           -2.629485342297515,
+           -2.7218184584457226,
+           -2.799436027201641,
+           -2.8608145195073607,
+           -2.9047429751471427,
+           -2.9303482321083867,
+           -2.9371124803054025,
+           -2.9248827505964283,
+           -2.8938721421228664,
+           -2.844652787561033,
+           -2.7781407521148607,
+           -2.6955732532188446,
+           -2.5984787693188225,
+           -2.4886407733523086,
+           -2.3680559756098676,
+           -2.2388880879252793,
+           -2.103418223554912,
+           -1.9639931222199642,
+           -1.822972435827004,
+           -1.6826763262971658,
+           -1.545334612408294,
+           -1.413038658024032,
+           -1.2876971207204495,
+           -1.1709965795051227,
+           -1.064367935595255,
+           -0.9689593342169509,
+           -0.8856161917616375,
+           -0.8148687354689471,
+           -0.7569272765060986,
+           -0.7116852465039657,
+           -0.6787298370143946,
+           -0.6573598956801538,
+           -0.6466105567338538,
+           -0.6452839210952033,
+           -0.6519849567943088,
+           -0.6651616672384434,
+           -0.6831484759492615,
+           -0.7042117042036897,
+           -0.7265959742227817,
+           -0.748570356164967,
+           -0.7684730924560459,
+           -0.7847537774498364,
+           -0.7960119428556602,
+           -0.8010310978907925,
+           -0.7988073951686018,
+           -0.7885722357846231,
+           -0.7698082862760091,
+           -0.7422585520555739,
+           -0.7059283321986052,
+           -0.661080064525732,
+           -0.6082212531270675,
+           -0.5480858481893502,
+           -0.48160961574022004,
+           -0.4099001884897184,
+           -0.33420262446764254,
+           -0.2558614142235053,
+           -0.17627996711340937,
+           -0.09687867039885377,
+           -0.0190526499505692,
+           0.05586963258073846,
+           0.12666583433147086,
+           0.19225617733846928,
+           0.25173590483084207,
+           0.3044028703739601,
+           0.34977950915976996,
+           0.38762858672969447,
+           0.4179622820830983,
+           0.441044335372647,
+           0.4573851708304071,
+           0.4677300886339999,
+           0.47304080046949415,
+           0.4744707579829653,
+           0.4733348867030731,
+           0.47107448620351217,
+           0.4692181864747109,
+           0.4693399573792556,
+           0.4730152499216316,
+           0.4817764027412358,
+           0.4970684732893851,
+           0.520206649842576,
+           0.5523363678379819,
+           0.59439719273127,
+           0.6470914431281077,
+           0.7108584144692398,
+           0.7858549278255138,
+           0.87194277371647,
+           0.9686834511172977,
+           1.0753404211628097,
+           1.1908889079733178,
+           1.3140330901673352,
+           1.443230340694087,
+           1.5767219942596702,
+           1.7125699552982065,
+           1.8486983093312412,
+           1.9829389704477427,
+           2.1130802908182478,
+           2.236917477356164,
+           2.352303607942119,
+           2.4572000164288843,
+           2.5497248226127835,
+           2.628198420414661,
+           2.691184803839686,
+           2.7375277043345663,
+           2.7663806327006726,
+           2.777230060886452,
+           2.769911140343961,
+           2.744615530284543,
+           2.7018910968173016,
+           2.642633438032783,
+           2.5680693858700745,
+           2.479732828296366,
+           2.37943338022152,
+           2.2692186041395788,
+           2.151330637503733,
+           2.0281582194743275,
+           1.9021852215977488,
+           1.775936872424433,
+           1.6519249229505282,
+           1.5325930266603793
+          ],
+          [
+           1.4533414623571634,
+           1.3478399393397524,
+           1.252780583353324,
+           1.169936871265012,
+           1.100799662930009,
+           1.046545575054794,
+           1.008012524909592,
+           0.9856829993886064,
+           0.9796754208991236,
+           0.9897437888042713,
+           1.0152855783432222,
+           1.0553576828974751,
+           1.1086999949311567,
+           1.1737660405365329,
+           1.248759916639794,
+           1.331678632582733,
+           1.420358832550239,
+           1.5125267751725766,
+           1.6058503739858287,
+           1.697992058996628,
+           1.786661206361147,
+           1.869664900402801,
+           1.9449558393589697,
+           2.0106762721293534,
+           2.0651969559583265,
+           2.1071502518261576,
+           2.135456622164387,
+           2.149343960652505,
+           2.1483593621815236,
+           2.132373128153063,
+           2.101574993481855,
+           2.056462752255169,
+           1.9978236442705102,
+           1.9267090400610836,
+           1.844403123220194,
+           1.7523864119057277,
+           1.6522950828575567,
+           1.5458771581525006,
+           1.4349466849283032,
+           1.3213370797789077,
+           1.20685482152064,
+           1.0932346583514418,
+           0.982097448611458,
+           0.8749116796673095,
+           0.7729596088411319,
+           0.6773088463892551,
+           0.5887900564820805,
+           0.5079812916215619,
+           0.43519930303631726,
+           0.37049798870006295,
+           0.31367395630320577,
+           0.26427899542467637,
+           0.22163907591832138,
+           0.18487932260857412,
+           0.1529542639820958,
+           0.12468251849420307,
+           0.09878496974435981,
+           0.07392539392786615,
+           0.0487524418357282,
+           0.02194184477222277,
+           -0.007762290101282748,
+           -0.041508204230035525,
+           -0.08030028745105577,
+           -0.12496692780489024,
+           -0.1761332802370003,
+           -0.23419969486273892,
+           -0.29932639818357604,
+           -0.3714248579904791,
+           -0.4501560887932829,
+           -0.5349359738781818,
+           -0.6249474970993408,
+           -0.7191595968959685,
+           -0.816352181377266,
+           -0.9151466810481056,
+           -1.0140413689896877,
+           -1.1114505508080217,
+           -1.2057466216855153,
+           -1.2953039081218019,
+           -1.3785431595040738,
+           -1.4539755308963827,
+           -1.5202449040555495,
+           -1.5761674286064216,
+           -1.6207672287438644,
+           -1.6533073112598609,
+           -1.6733148259286195,
+           -1.6805999665026397,
+           -1.6752679564044304,
+           -1.6577237337953052,
+           -1.6286691318410376,
+           -1.589092537177648,
+           -1.5402511981523264,
+           -1.483646539672216,
+           -1.4209930188069881,
+           -1.3541812202168093,
+           -1.2852360388697182,
+           -1.2162709256282023,
+           -1.1494392758742387,
+           -1.086884119733427,
+           -1.0306873226226938,
+           -0.9828195254486684,
+           -0.9450920442201943,
+           -0.9191119092484968,
+           -0.9062411553753376,
+           -0.9075613783972575,
+           -0.9238444513307631,
+           -0.9555301503041334,
+           -1.0027112771378124,
+           -1.065126688029672,
+           -1.1421624495106226,
+           -1.2328611485651788,
+           -1.3359391882609395,
+           -1.4498117081794073,
+           -1.5726245850879368,
+           -1.7022927981427698,
+           -1.836544288664872,
+           -1.9729683109708214,
+           -2.1090671611552447,
+           -2.242310087808502,
+           -2.370188134461447,
+           -2.490268639423771,
+           -2.600248125233288,
+           -2.69800234701967,
+           -2.781632335818154,
+           -2.849505367632166,
+           -2.9002899095366863,
+           -2.932983737406002,
+           -2.9469345824505653,
+           -2.941852841697999,
+           -2.917816076517252,
+           -2.8752652186600054,
+           -2.814992600322658,
+           -2.738122118621091,
+           -2.6460820309055593,
+           -2.5405710510073307,
+           -2.4235185735929012,
+           -2.297039990507381,
+           -2.1633881760220155,
+           -2.0249023045527648,
+           -1.8839552226286236,
+           -1.7429006253042565,
+           -1.6040212852073428,
+           -1.469479550112741,
+           -1.3412712632130035,
+           -1.2211841706998903,
+           -1.110761766158246,
+           -1.0112733835007892,
+           -0.9236911931914502,
+           -0.8486745842339394,
+           -0.7865622311275162,
+           -0.7373719552633096,
+           -0.7008082987504299,
+           -0.6762775401532238,
+           -0.6629097007368109,
+           -0.6595869210056489,
+           -0.664977434718046,
+           -0.6775742348956584,
+           -0.6957374168452176,
+           -0.7177390995113535,
+           -0.7418097705785586,
+           -0.7661848739353653,
+           -0.7891504609755922,
+           -0.8090867595709098,
+           -0.8245085755015283,
+           -0.8341015290622857,
+           -0.8367532421832609,
+           -0.8315787258196053,
+           -0.8179393701370316,
+           -0.7954551072569223,
+           -0.7640094937834901,
+           -0.7237476435203505,
+           -0.6750671250658531,
+           -0.6186021197046243,
+           -0.5552013076331671,
+           -0.485900110725449,
+           -0.4118880637342058,
+           -0.33447220942797,
+           -0.2550375135843155,
+           -0.17500537048449558,
+           -0.09579131671978268,
+           -0.018763089557255485,
+           0.054799844621801035,
+           0.12374420591395446,
+           0.1870772420988164,
+           0.2439965706631846,
+           0.29391471423841486,
+           0.33647766022136055,
+           0.37157693081144266,
+           0.39935481850621385,
+           0.4202026199791217,
+           0.4347518837087395,
+           0.44385886911357414,
+           0.44858259264360045,
+           0.45015700477569615,
+           0.4499579968691588,
+           0.4494660744081626,
+           0.4502256497726964,
+           0.4538020003433692,
+           0.4617370040609612,
+           0.47550480279004603,
+           0.4964685529411025,
+           0.5258394024803579,
+           0.5646387841320639,
+           0.6136650374128321,
+           0.673465268990713,
+           0.744313234246089,
+           0.8261938759327188,
+           0.918794992116701,
+           1.0215063291566888,
+           1.1334262107535076,
+           1.2533756256325397,
+           1.3799195089221965,
+           1.5113947704370356,
+           1.6459444514161585,
+           1.7815572341134216,
+           1.9161113899437576,
+           2.0474221351659434,
+           2.1732912712971504,
+           2.291557922966658,
+           2.400149150411787,
+           2.497129208271036,
+           2.580746246971261,
+           2.6494753073242037,
+           2.7020565416955065,
+           2.7375277043345663,
+           2.755250086546643,
+           2.754927226146341,
+           2.736615891335764,
+           2.7007290226586256,
+           2.6480305085288536,
+           2.5796218653415037,
+           2.4969210875709695,
+           2.4016341217923385,
+           2.2957195966101756,
+           2.181347603680622,
+           2.060853469361204,
+           1.936687578472324,
+           1.811362408202367,
+           1.6873979989548182,
+           1.5672671282182613,
+           1.4533414623571645
+          ],
+          [
+           1.3787148766482227,
+           1.2809279967228833,
+           1.1947721689312236,
+           1.1218467531262184,
+           1.0634479975083477,
+           1.0205416739072863,
+           0.9937432403370577,
+           0.9833059784491442,
+           0.9891173637233881,
+           1.0107037304546844,
+           1.047243096579872,
+           1.0975858199367892,
+           1.160282572358161,
+           1.2336189455724857,
+           1.3156558473912083,
+           1.4042747118655503,
+           1.4972264362448702,
+           1.5921828733180117,
+           1.6867896520695664,
+           1.7787190738301413,
+           1.865721835802741,
+           1.945676368816774,
+           2.0166346404638475,
+           2.0768633667527183,
+           2.1248796927538867,
+           2.159480542437039,
+           2.1797649965408836,
+           2.1851492308996914,
+           2.175373731868882,
+           2.150502695774532,
+           2.110915710950334,
+           2.057292009188672,
+           1.9905877536826426,
+           1.912006998344299,
+           1.8229671046406735,
+           1.7250595331025338,
+           1.6200070342511315,
+           1.5096183452641005,
+           1.3957415523239778,
+           1.2802173030218567,
+           1.164833047913869,
+           1.0512794555799214,
+           0.9411100822764552,
+           0.8357052871814155,
+           0.7362412696393399,
+           0.6436649686741117,
+           0.5586754108256767,
+           0.4817119240094098,
+           0.41294945686413226,
+           0.35230105945799295,
+           0.299427396898377,
+           0.25375298699108156,
+           0.21448868115835346,
+           0.18065974867896523,
+           0.15113878195343733,
+           0.1246825184942031,
+           0.0999715767485615,
+           0.0756520301444835,
+           0.050377698715276385,
+           0.022852021420228734,
+           -0.008131614779621953,
+           -0.04365217125784234,
+           -0.08462689210852616,
+           -0.13178179370761556,
+           -0.18562750751075519,
+           -0.2464411345531988,
+           -0.3142546135306174,
+           -0.3888499347307571,
+           -0.469761353753012,
+           -0.5562845764164663,
+           -0.6474927041453283,
+           -0.7422585520555742,
+           -0.8392827844458898,
+           -0.9371271586818474,
+           -1.0342520324736275,
+           -1.129057174762065,
+           -1.2199248297940701,
+           -1.3052639198318068,
+           -1.3835542359835562,
+           -1.4533894598453339,
+           -1.5135178812483314,
+           -1.562879728927726,
+           -1.6006401101467178,
+           -1.626216660312907,
+           -1.6393011318493749,
+           -1.6398742998807627,
+           -1.6282137270073114,
+           -1.604894106490713,
+           -1.570780088171711,
+           -1.5270116797789353,
+           -1.4749825032765447,
+           -1.4163113668627705,
+           -1.3528077836396069,
+           -1.2864322235456525,
+           -1.2192520219579717,
+           -1.1533939829614854,
+           -1.090994804735142,
+           -1.0341505165109985,
+           -0.9848661494974583,
+           -0.9450068671109817,
+           -0.9162517526612269,
+           -0.900051395858107,
+           -0.8975903344638135,
+           -0.9097552961070835,
+           -0.9371100503725474,
+           -0.9798775260235782,
+           -1.0379296763693031,
+           -1.1107853915178174,
+           -1.1976165640535166,
+           -1.2972622192252083,
+           -1.408250426808723,
+           -1.5288275241581208,
+           -1.6569940031812223,
+           -1.790546252404,
+           -1.9271232028938827,
+           -2.064256807095732,
+           -2.1994251855466,
+           -2.3301072103000413,
+           -2.453837257348572,
+           -2.5682588543006837,
+           -2.6711759742163377,
+           -2.760600781251061,
+           -2.8347967172843322,
+           -2.892315928990364,
+           -2.932030169168707,
+           -2.9531544613213776,
+           -2.955262988664262,
+           -2.9382968538011083,
+           -2.902563548661885,
+           -2.848728171306085,
+           -2.777796622021684,
+           -2.6910912010496877,
+           -2.5902192096197045,
+           -2.477035320442955,
+           -2.3535986293944062,
+           -2.222125423310903,
+           -2.0849387966764077,
+           -1.944416320123378,
+           -1.8029370044973994,
+           -1.662828814781509,
+           -1.5263179682706145,
+           -1.3954812015887774,
+           -1.2722021127498986,
+           -1.1581325794733905,
+           -1.0546601260295048,
+           -0.9628819612372848,
+           -0.8835862436090074,
+           -0.8172409501765753,
+           -0.763990537703107,
+           -0.7236603934303976,
+           -0.6957688819744472,
+           -0.6795466101559767,
+           -0.6739623569880296,
+           -0.6777549560212281,
+           -0.6894702756816151,
+           -0.7075023235723652,
+           -0.730137405843737,
+           -0.7556002049374928,
+           -0.7821005998770112,
+           -0.8078800436801984,
+           -0.8312563325594079,
+           -0.8506656507417061,
+           -0.8647008516707864,
+           -0.8721450390263954,
+           -0.8719996367662266,
+           -0.863506283036435,
+           -0.8461620445964728,
+           -0.8197276222508718,
+           -0.7842283992702853,
+           -0.7399483693273491,
+           -0.6874171634125463,
+           -0.6273905719205223,
+           -0.5608251241611618,
+           -0.4888474387783931,
+           -0.41271919115764005,
+           -0.3337986545471018,
+           -0.2534998575413206,
+           -0.17325045963507416,
+           -0.09444947728615408,
+           -0.018425994576408356,
+           0.05360003488670967,
+           0.12055384401652662,
+           0.18153779821451538,
+           0.23585837086206832,
+           0.2830474176824278,
+           0.32287716788113885,
+           0.3553685135904505,
+           0.3807923536677535,
+           0.3996639289075337,
+           0.41273026863135437,
+           0.42095104878156686,
+           0.42547333448767677,
+           0.42760084120565356,
+           0.42875849384656267,
+           0.4304531891018107,
+           0.4342317692146105,
+           0.44163729308578,
+           0.4541647408159325,
+           0.4732173092410619,
+           0.500064448100051,
+           0.5358027493026326,
+           0.581320736200838,
+           0.637268507375596,
+           0.7040330724776476,
+           0.7817200789733847,
+           0.8701424716558215,
+           0.9688164553676865,
+           1.0769649497960083,
+           1.1935285379464815,
+           1.317183721654396,
+           1.44636811293534,
+           1.5793120137396075,
+           1.7140756731701037,
+           1.8485913645673564,
+           1.980709298762065,
+           2.108246287446488,
+           2.229035994641003,
+           2.3409795666026287,
+           2.4420954125109904,
+           2.5305669204164194,
+           2.6047869350418713,
+           2.6633978951503,
+           2.70532662665869,
+           2.7298129111569716,
+           2.7364310950101562,
+           2.7251041682717365,
+           2.6961099212390787,
+           2.6500789752947527,
+           2.587984679100471,
+           2.5111250564961067,
+           2.421097183830016,
+           2.319764557222767,
+           2.2092181799634036,
+           2.0917322526904436,
+           1.9697154804709176,
+           1.8456591181251027,
+           1.7220829555056432,
+           1.601480495940161,
+           1.4862646024029473,
+           1.3787148766482238
+          ],
+          [
+           1.3093446442175654,
+           1.220093881645348,
+           1.1435529624018124,
+           1.0811336101374212,
+           1.0339265147418355,
+           1.002678460548012,
+           0.9877772755442924,
+           0.9892449375578265,
+           1.006738979426489,
+           1.0395621380254758,
+           1.086679996455427,
+           1.1467461794858749,
+           1.2181344840767157,
+           1.2989771637949774,
+           1.387208442150121,
+           1.4806122087590385,
+           1.576872756732667,
+           1.6736273520288432,
+           1.768519387333538,
+           1.8592508651819961,
+           1.9436329776337402,
+           2.019633602243853,
+           2.0854206149683803,
+           2.1394000279476013,
+           2.1802480911246502,
+           2.206936648097824,
+           2.2187512046949,
+           2.2153013493169627,
+           2.1965233526482426,
+           2.162674966200648,
+           2.1143226296183495,
+           2.052321481015648,
+           1.9777887383288724,
+           1.8920711784720288,
+           1.7967075811171547,
+           1.6933871217687002,
+           1.5839047916199018,
+           1.4701149872489874,
+           1.3538844499971503,
+           1.237045742050824,
+           1.121352423748478,
+           1.0084370451070017,
+           0.8997729853966009,
+           0.7966410698539617,
+           0.7001017650138605,
+           0.6109736069264754,
+           0.5298183534633272,
+           0.4569331771390032,
+           0.3923500328147874,
+           0.3358421499044096,
+           0.2869374159312751,
+           0.2449382420938195,
+           0.20894733631165413,
+           0.17789865919846698,
+           0.15059270729991106,
+           0.12573515902819826,
+           0.10197783473987503,
+           0.0779608654300698,
+           0.05235493596453672,
+           0.023902469332920916,
+           -0.0085433519578437,
+           -0.045982773294931896,
+           -0.08923782536927725,
+           -0.13892570337054172,
+           -0.19543788847452973,
+           -0.2589255823090654,
+           -0.329291860522116,
+           -0.4061907764448207,
+           -0.48903346458224767,
+           -0.5770011108726135,
+           -0.6690644769694345,
+           -0.7640094937834897,
+           -0.8604682795462826,
+           -0.956954793798446,
+           -1.0519042146383815,
+           -1.1437150254679538,
+           -1.2307927219488857,
+           -1.3115940019020693,
+           -1.384670281719022,
+           -1.4487093930654626,
+           -1.5025743530594557,
+           -1.5453381687865877,
+           -1.5763137313463804,
+           -1.5950779733113063,
+           -1.601489603610875,
+           -1.5956998919744743,
+           -1.578156147266575,
+           -1.5495977160552015,
+           -1.5110445150430547,
+           -1.4637782988929828,
+           -1.409317048801869,
+           -1.3493830423172897,
+           -1.285865326952718,
+           -1.220777465058571,
+           -1.1562115414844298,
+           -1.0942895256674503,
+           -1.0371131533375295,
+           -0.986713538127312,
+           -0.9450017388030769,
+           -0.9137214931109121,
+           -0.8944052846277013,
+           -0.8883348355238657,
+           -0.8965070175064878,
+           -0.9196060478139928,
+           -0.9579826899891959,
+           -1.0116410138213903,
+           -1.080233089330322,
+           -1.1630618003322655,
+           -1.2590917685971277,
+           -1.3669681846275512,
+           -1.485043150436267,
+           -1.6114089580380915,
+           -1.743937559164125,
+           -1.880325331080626,
+           -2.0181421140584623,
+           -2.1548833911792817,
+           -2.28802440337071,
+           -2.4150749437646546,
+           -2.533633556889519,
+           -2.64143988031895,
+           -2.7364239089357296,
+           -2.8167510339119772,
+           -2.8808618081198967,
+           -2.9275055145551456,
+           -2.9557667614443077,
+           -2.965084493441589,
+           -2.9552629886642614,
+           -2.926474601881444,
+           -2.8792542103178325,
+           -2.814485515489869,
+           -2.7333795474659097,
+           -2.6374459022450405,
+           -2.5284574141075744,
+           -2.408409118656517,
+           -2.27947249512388,
+           -2.1439460851581433,
+           -2.0042036671364682,
+           -1.8626412181153482,
+           -1.7216239186128435,
+           -1.5834344480086913,
+           -1.4502237807094167,
+           -1.3239656263495507,
+           -1.2064155629017816,
+           -1.099075792033898,
+           -1.0031663043806698,
+           -0.9196030821344582,
+           -0.8489837914907863,
+           -0.7915812323575521,
+           -0.7473446219358963,
+           -0.7159085970250204,
+           -0.6966096319223044,
+           -0.6885093892111585,
+           -0.6904243539605394,
+           -0.70096095198323,
+           -0.7185552234682219,
+           -0.74151601765161,
+           -0.7680705947609004,
+           -0.7964114701434287,
+           -0.8247433134513749,
+           -0.8513287234539599,
+           -0.8745317361896909,
+           -0.8928579897344665,
+           -0.9049905611140062,
+           -0.9098206074388081,
+           -0.9064720811923427,
+           -0.8943199452376518,
+           -0.873001482566115,
+           -0.8424204747975712,
+           -0.802744207426382,
+           -0.7543934441483617,
+           -0.6980256926529428,
+           -0.6345122554921954,
+           -0.5649097177407015,
+           -0.49042666417004377,
+           -0.41238653904592987,
+           -0.33218765840411696,
+           -0.2512614553604416,
+           -0.17103008190503752,
+           -0.09286450466676578,
+           -0.018044216984102992,
+           0.05228035430874336,
+           0.11712174054449487,
+           0.17568471188745427,
+           0.2273901582803881,
+           0.27189292295237016,
+           0.30909309845859617,
+           0.33914046561079986,
+           0.3624319344198618,
+           0.37960202877821214,
+           0.39150663842670086,
+           0.3992004381638938,
+           0.4039085407827802,
+           0.4069931026234202,
+           0.4099157350237398,
+           0.4141966878975771,
+           0.4213718602672873,
+           0.4329487545344798,
+           0.4503625249600867,
+           0.4749332753248098,
+           0.5078257358660242,
+           0.5500123958868172,
+           0.6022410871811328,
+           0.6650079065829837,
+           0.738536236139322,
+           0.8227624698179438,
+           0.9173288899880374,
+           1.0215839592553513,
+           1.1345901080093348,
+           1.2551389098570656,
+           1.3817733506730485,
+           1.512816716948479,
+           1.6464074599905598,
+           1.7805392385557386,
+           1.913105207583081,
+           2.0419455082466733,
+           2.16489682743784,
+           2.279842835265543,
+           2.3847642787953696,
+           2.47778750988147,
+           2.5572302546895465,
+           2.621643491725003,
+           2.6698483924998997,
+           2.7009673923307176,
+           2.714448595443047,
+           2.710082875275303,
+           2.6880132038273437,
+           2.6487359288900847,
+           2.5930939105130326,
+           2.5222616234201674,
+           2.437722525494584,
+           2.34123917918357,
+           2.2348167881503125,
+           2.120660971408374,
+           2.001130737589829,
+           1.8786877394592965,
+           1.7558429803980493,
+           1.6351022080768052,
+           1.5189112643340785,
+           1.409602663527043,
+           1.309344644217569
+          ],
+          [
+           1.2458176686219353,
+           1.1658522782484468,
+           1.0995563014292793,
+           1.0481418939112088,
+           1.0124849797332969,
+           0.9931070658451844,
+           0.9901651052930717,
+           1.0034496304331848,
+           1.0323911811657078,
+           1.076074856330022,
+           1.1332626239515446,
+           1.2024228426576373,
+           1.2817662767353997,
+           1.3692877351029298,
+           1.4628123335869616,
+           1.5600452734963761,
+           1.6586239501019409,
+           1.75617115416114,
+           1.8503481092342926,
+           1.9389060976563135,
+           2.0197354683390696,
+           2.090910889023223,
+           2.150731802402266,
+           2.197757167262139,
+           2.230833709365921,
+           2.2491170686804947,
+           2.2520854056639967,
+           2.2395452153385227,
+           2.211629289157502,
+           2.168786956515593,
+           2.111766925412321,
+           2.041593220653629,
+           1.959534883670711,
+           1.867070246501451,
+           1.7658467201012142,
+           1.6576371408360373,
+           1.5442937962729748,
+           1.427701300391438,
+           1.3097295079740559,
+           1.19218764780698,
+           1.0767808147801075,
+           0.9650698931116957,
+           0.8584358885167432,
+           0.7580495286402941,
+           0.6648468515271334,
+           0.5795113448597375,
+           0.5024630281582815,
+           0.43385469042137115,
+           0.3735753113370859,
+           0.32126050986187604,
+           0.2763096842926626,
+           0.23790933746343762,
+           0.20506192366311288,
+           0.1766194142334914,
+           0.15132066006018746,
+           0.12783153428094593,
+           0.10478676986785233,
+           0.08083236599334914,
+           0.0546674252616709,
+           0.025084301245624965,
+           -0.00899401815310708,
+           -0.04848029239346125,
+           -0.09409407665145259,
+           -0.1463382160852653,
+           -0.20548142286612234,
+           -0.2715474140530501,
+           -0.3443109172440919,
+           -0.4233006717649526,
+           -0.5078093705026473,
+           -0.5969103059907875,
+           -0.6894803086122315,
+           -0.7842283992702854,
+           -0.8797294278033515,
+           -0.9744618356327077,
+           -1.0668485700351364,
+           -1.1553000908759634,
+           -1.238258350864557,
+           -1.3142405989738801,
+           -1.3818818544585325,
+           -1.4399749260394805,
+           -1.4875069066894029,
+           -1.523691157719445,
+           -1.5479939045153122,
+           -1.5601546976375014,
+           -1.560200143851929,
+           -1.548450478263804,
+           -1.525518726958136,
+           -1.4923023949737506,
+           -1.4499678024343847,
+           -1.3999273775355097,
+           -1.343810394187105,
+           -1.2834278099468408,
+           -1.220732012221685,
+           -1.157772413721475,
+           -1.0966479484400344,
+           -1.0394576041998764,
+           -0.9882501848339441,
+           -0.9449745228849655,
+           -0.9114313614928756,
+           -0.8892280918692865,
+           -0.8797374711248187,
+           -0.8840613556480039,
+           -0.903000369855025,
+           -0.9370302917010324,
+           -0.9862857782045773,
+           -1.050551880217663,
+           -1.1292636100047166,
+           -1.2215136323991065,
+           -1.3260679550931773,
+           -1.4413893007625944,
+           -1.5656676579525959,
+           -1.6968573335201695,
+           -1.8327196712106335,
+           -1.9708704625415578,
+           -2.1088309609836413,
+           -2.2440813213111386,
+           -2.3741152251531883,
+           -2.496494422728912,
+           -2.6089019202819346,
+           -2.709192572883682,
+           -2.795439902338726,
+           -2.865978048456641,
+           -2.919437876811688,
+           -2.9547764045091713,
+           -2.97129886405191,
+           -2.968672900296498,
+           -2.9469345824505653,
+           -2.9064861075398714,
+           -2.84808526903508,
+           -2.772826959574541,
+           -2.682117165205022,
+           -2.577640085709797,
+           -2.4613191771067315,
+           -2.33527305436884,
+           -2.2017673114196916,
+           -2.0631634086264277,
+           -1.9218658431311684,
+           -1.7802688528953186,
+           -1.6407039104761116,
+           -1.505389237255062,
+           -1.3763825137835306,
+           -1.2555378785227356,
+           -1.1444681976491065,
+           -1.0445134555266515,
+           -0.9567159622441099,
+           -0.8818029050934262,
+           -0.8201765892394954,
+           -0.7719125236007736,
+           -0.7367653158056343,
+           -0.7141821497524944,
+           -0.7033234354689992,
+           -0.7030900481522587,
+           -0.7121564157108187,
+           -0.7290085756649831,
+           -0.7519862062585025,
+           -0.7793275458901102,
+           -0.8092160516535145,
+           -0.8398276133582111,
+           -0.8693771346487624,
+           -0.8961633177650222,
+           -0.9186105423693856,
+           -0.9353068102690617,
+           -0.9450368346579971,
+           -0.9468094819423748,
+           -0.9398789229828127,
+           -0.9237590148976923,
+           -0.8982306102557565,
+           -0.8633416730958472,
+           -0.8194002661362808,
+           -0.7669606561139318,
+           -0.7068029598292568,
+           -0.63990691775403,
+           -0.5674205308618036,
+           -0.49062442593898026,
+           -0.4108929217864668,
+           -0.32965285075536926,
+           -0.24834124493701734,
+           -0.1683630226947136,
+           -0.09104980844718573,
+           -0.017620986791526634,
+           0.050851967982753966,
+           0.11347693264627627,
+           0.16956750287651184,
+           0.21866357782849494,
+           0.26054560212112216,
+           0.2952420714184064,
+           0.32303008350167417,
+           0.34442889821756056,
+           0.3601866523443599,
+           0.37126055461011254,
+           0.37879105726864387,
+           0.38407065944183005,
+           0.38850813982250526,
+           0.39358913866677275,
+           0.40083410815180004,
+           0.4117547235795939,
+           0.4278098936572213,
+           0.45036252496008655,
+           0.4806381831917383,
+           0.5196867522325013,
+           0.5683481221928746,
+           0.6272228414370882,
+           0.6966485471654865,
+           0.7766828475983074,
+           0.8670931695813273,
+           0.9673539124781892,
+           1.076651066819251,
+           1.1938942688825154,
+           1.3177360748598852,
+           1.4465980551998738,
+           1.57870313570334,
+           1.7121134513535734,
+           1.8447728357348088,
+           1.9745529468558498,
+           2.0993019323556563,
+           2.2168944659370116,
+           2.3252819443087276,
+           2.42254162106693,
+           2.5069234712286135,
+           2.576893627217171,
+           2.6311733029234414,
+           2.6687722252465425,
+           2.6890157198065805,
+           2.691564746256166,
+           2.6764283452037394,
+           2.643968139156216,
+           2.594894719701029,
+           2.5302559477475404,
+           2.4514173882790042,
+           2.3600352909642313,
+           2.2580227084870996,
+           2.1475095111406106,
+           2.0307972050020364,
+           1.9103095881941823,
+           1.7885403822058004,
+           1.66799905045858,
+           1.5511560623983376,
+           1.440388877198962,
+           1.3379299062833454,
+           1.2458176686219362
+          ],
+          [
+           1.1886714168211636,
+           1.1186620950415296,
+           1.0631544176741736,
+           1.023150729295781,
+           0.9993047975713125,
+           0.9919084681290973,
+           1.000886527463216,
+           1.025799878945796,
+           1.0658569397065751,
+           1.119932971249269,
+           1.1865968689607227,
+           1.2641447596876596,
+           1.350639596574599,
+           1.4439558002471669,
+           1.541827878569015,
+           1.6419018664060043,
+           1.7417883642639416,
+           1.8391159217973574,
+           1.9315835097566219,
+           2.017010851941947,
+           2.0933854464105828,
+           2.1589051910553825,
+           2.212015640566149,
+           2.251441056890817,
+           2.2762085702571175,
+           2.285664938740059,
+           2.2794855770240736,
+           2.2576757148873514,
+           2.2205637383382744,
+           2.1687869565155924,
+           2.103270220746301,
+           2.0251979940398726,
+           1.935980625578532,
+           1.8372157216300902,
+           1.7306456184417482,
+           1.6181120513202893,
+           1.5015091751551695,
+           1.3827361236746842,
+           1.263650297044554,
+           1.1460225400661452,
+           1.0314953169895185,
+           0.9215449053237433,
+           0.8174485221817406,
+           0.7202571654419564,
+           0.6307748017002907,
+           0.5495443674478221,
+           0.4768408733410496,
+           0.41267171829728455,
+           0.3567841350703872,
+           0.3086795066034212,
+           0.2676341174013055,
+           0.2327257408137255,
+           0.2028653155619064,
+           0.1768328367753074,
+           0.15331648142451218,
+           0.13095390796918702,
+           0.10837461727025255,
+           0.08424223764018733,
+           0.057295601900811316,
+           0.02638751832557423,
+           -0.00947980052547134,
+           -0.05112359841171628,
+           -0.09915455987172558,
+           -0.15395661864001853,
+           -0.21567313783982903,
+           -0.2841998433771517,
+           -0.35918471568047655,
+           -0.4400348632344245,
+           -0.5259302188539278,
+           -0.615843720971273,
+           -0.7085674718997493,
+           -0.8027442074263822,
+           -0.8969032711870704,
+           -0.9895001666886879,
+           -1.0789586626548342,
+           -1.1637143560904395,
+           -1.24225855394222,
+           -1.3131813196384128,
+           -1.3752125455584892,
+           -1.4272599563108193,
+           -1.4684430195525608,
+           -1.4981218392353117,
+           -1.5159202282033748,
+           -1.5217423000066626,
+           -1.5157820800857913,
+           -1.498525810169353,
+           -1.470746802476514,
+           -1.433492887589145,
+           -1.3880666869719047,
+           -1.3359991233940793,
+           -1.2790167553724001,
+           -1.219003680862361,
+           -1.157958896762308,
+           -1.0979501207787947,
+           -1.0410651777747812,
+           -0.9893621214261066,
+           -0.9448193020486775,
+           -0.9092866017400341,
+           -0.884439038149668,
+           -0.8717338886440068,
+           -0.8723724084920768,
+           -0.8872671118040439,
+           -0.9170154548102819,
+           -0.9618806107803538,
+           -1.0217798580850934,
+           -1.096280921675311,
+           -1.1846064180010076,
+           -1.2856463587692937,
+           -1.397978474696831,
+           -1.519895931311896,
+           -1.6494418295410982,
+           -1.7844497186819457,
+           -1.922589202478459,
+           -2.0614155940024865,
+           -2.1984224749872516,
+           -2.3310959426398514,
+           -2.456969283585206,
+           -2.573676801558023,
+           -2.6790055431121957,
+           -2.7709437135573234,
+           -2.8477246524160806,
+           -2.907865342066513,
+           -2.9501985523627026,
+           -2.9738978747832046,
+           -2.9784950683750924,
+           -2.9638893223403393,
+           -2.9303482321083862,
+           -2.8785004824834215,
+           -2.8093204281609885,
+           -2.724104953793857,
+           -2.6244431781894524,
+           -2.5121797357143,
+           -2.3893725184826033,
+           -2.258245891778245,
+           -2.1211404992979928,
+           -1.980460851713794,
+           -1.838621939909883,
+           -1.6979961319469714,
+           -1.5608615999727806,
+           -1.4293534803194579,
+           -1.305418898024703,
+           -1.1907768878188714,
+           -1.0868841197334271,
+           -0.9949071920082411,
+           -0.9157020905333202,
+           -0.8498012367167405,
+           -0.7974083588215883,
+           -0.7584012300825141,
+           -0.7323421250293768,
+           -0.7184956581379726,
+           -0.7158534907984955,
+           -0.7231652280068123,
+           -0.7389746791625855,
+           -0.7616605314784453,
+           -0.7894803828103591,
+           -0.8206170056490564,
+           -0.8532256673377266,
+           -0.8854813143642138,
+           -0.9156244411448092,
+           -0.9420045056576182,
+           -0.9631198244523241,
+           -0.9776529761154579,
+           -0.9845008627074309,
+           -0.9827987199211299,
+           -0.9719375251393133,
+           -0.9515744241659018,
+           -0.9216359778288262,
+           -0.8823142143411415,
+           -0.8340556576063437,
+           -0.7775436809241022,
+           -0.7136747052894159,
+           -0.643528917422177,
+           -0.5683363209093076,
+           -0.4894390509311488,
+           -0.4082509760571356,
+           -0.32621567722058065,
+           -0.24476393257264026,
+           -0.16527184653188037,
+           -0.08902074177859134,
+           -0.017159884717622316,
+           0.04932696070341154,
+           0.109650257045985,
+           0.1632379255379893,
+           0.20975246032583444,
+           0.24910145865763997,
+           0.2814412727169941,
+           0.3071736683857476,
+           0.32693555889358783,
+           0.34158206247616996,
+           0.3521633082121352,
+           0.3598955786935414,
+           0.3661275279177192,
+           0.37230234395275014,
+           0.37991683516871494,
+           0.39047850333576517,
+           0.4054617244797146,
+           0.42626418754238704,
+           0.4541647408159321,
+           0.49028376673979207,
+           0.5355471476338485,
+           0.590654799679241,
+           0.6560546420233262,
+           0.7319227349862164,
+           0.8181501692601137,
+           0.9143371204836669,
+           1.0197943047994185,
+           1.133551885411232,
+           1.2543756923791112,
+           1.3807904326134761,
+           1.5111093889010472,
+           1.6434699402832982,
+           1.7758740854094175,
+           1.9062330194091301,
+           2.0324147067059823,
+           2.15229330978696,
+           2.2637992793930994,
+           2.364968886346621,
+           2.4539919800072414,
+           2.529256793135251,
+           2.589390676969932,
+           2.6332957421221557,
+           2.660178498252163,
+           2.669572725644026,
+           2.6613549713155087,
+           2.635752237348726,
+           2.5933416154360893,
+           2.5350418146650764,
+           2.462096724597788,
+           2.376051347963674,
+           2.2787206220630503,
+           2.1721518207385797,
+           2.0585813852641777,
+           1.9403871688720267,
+           1.8200371925244299,
+           1.700036096144959,
+           1.5828705277038346,
+           1.4709547408487453,
+           1.3665776694617597,
+           1.271852714630445,
+           1.1886714168211643
+          ],
+          [
+           1.1383893719644558,
+           1.0789225823283264,
+           1.0346552875451016,
+           1.0063715528524142,
+           0.9944974785610722,
+           0.9990928080787993,
+           1.0198508339716668,
+           1.0561065898796411,
+           1.1068531195884075,
+           1.1707654232849778,
+           1.2462314996361643,
+           1.3313897352283837,
+           1.4241717441429442,
+           1.5223496336088873,
+           1.6235865698307936,
+           1.7254894436713806,
+           1.8256623906425349,
+           1.9217599046703602,
+           2.0115383006526715,
+           2.092904326474841,
+           2.1639597997068023,
+           2.2230412457773694,
+           2.2687536404579163,
+           2.2999975068351426,
+           2.3159887819427443,
+           2.316271046757714,
+           2.3007199009267065,
+           2.2695394557331223,
+           2.2232511107076083,
+           2.1626749662006484,
+           2.0889044015865674,
+           2.003274512210455,
+           1.9073252437342174,
+           1.8027601866476834,
+           1.6914020933874754,
+           1.5751462533640659,
+           1.4559129055214026,
+           1.3355998828407227,
+           1.216036668184187,
+           1.098940996529758,
+           0.9858790661799387,
+           0.8782303228351126,
+           0.7771576580577799,
+           0.6835837207528443,
+           0.5981738804926444,
+           0.5213262088798448,
+           0.45316866403554135,
+           0.39356347829631555,
+           0.3421185649640017,
+           0.29820558110957995,
+           0.26098411447884357,
+           0.2294313077179436,
+           0.20237609630654707,
+           0.17853712117263623,
+           0.15656328584102355,
+           0.1350758633986289,
+           0.11271102213453212,
+           0.08816163131346759,
+           0.06021723031832751,
+           0.02780109476655994,
+           -0.009996589136247262,
+           -0.053890327784673016,
+           -0.10437646105215816,
+           -0.1617164559018221,
+           -0.22592680687516867,
+           -0.2967758250039999,
+           -0.37378741676602756,
+           -0.45625177202109807,
+           -0.5432426990592606,
+           -0.6336411705558678,
+           -0.726164480793537,
+           -0.8194002661362809,
+           -0.911844511211161,
+           -1.0019425558807307,
+           -1.0881320356340336,
+           -1.1688866326201695,
+           -1.2427594876537253,
+           -1.308425125878175,
+           -1.364718780390083,
+           -1.4106720582769727,
+           -1.4455439807606147,
+           -1.468846541338812,
+           -1.48036406022567,
+           -1.480165766684553,
+           -1.4686112092313264,
+           -1.4463482729743684,
+           -1.4143037690873999,
+           -1.3736667489454613,
+           -1.3258648801029997,
+           -1.2725343984265902,
+           -1.2154843158615805,
+           -1.1566557123481556,
+           -1.0980770695365276,
+           -1.0418167098987194,
+           -0.9899334848799866,
+           -0.9444269077988721,
+           -0.9071879499027896,
+           -0.8799517106543712,
+           -0.8642531360431029,
+           -0.8613868923105732,
+           -0.872372408492077,
+           -0.8979249818442842,
+           -0.9384336984116378,
+           -0.9939467601076503,
+           -1.0641646336537016,
+           -1.1484412498109773,
+           -1.2457932881206433,
+           -1.3549173875573475,
+           -1.4742149318723636,
+           -1.6018238746563538,
+           -1.7356568978018965,
+           -1.8734450423089448,
+           -2.0127858160666525,
+           -2.151194672679116,
+           -2.2861586713202025,
+           -2.415191072094418,
+           -2.535885595840541,
+           -2.645969082401674,
+           -2.743351317008908,
+           -2.8261708597470707,
+           -2.892835806523025,
+           -2.9420585292834427,
+           -2.972883585538414,
+           -2.984708149086164,
+           -2.9772944912689634,
+           -2.9507742308072156,
+           -2.90564426566703,
+           -2.84275449776371,
+           -2.7632876557906414,
+           -2.6687317083636803,
+           -2.5608455344471235,
+           -2.441618676440653,
+           -2.3132261395233833,
+           -2.177979315535436,
+           -2.038274198073376,
+           -1.8965381154750558,
+           -1.7551762385621603,
+           -1.6165191197183604,
+           -1.48277248917876,
+           -1.3559704741121263,
+           -1.237933317733656,
+           -1.130230561523991,
+           -1.034150516510999,
+           -0.9506766929151228,
+           -0.8804716851619625,
+           -0.8238688255997846,
+           -0.7808717297691422,
+           -0.7511616634598683,
+           -0.7341124718026066,
+           -0.7288126279486282,
+           -0.7340937879727912,
+           -0.748565083669127,
+           -0.7706522496716367,
+           -0.7986405691022563,
+           -0.8307205354238547,
+           -0.8650350694151941,
+           -0.8997271005502734,
+           -0.9329863221923909,
+           -0.9630939597994141,
+           -0.9884644499388058,
+           -1.0076830137714055,
+           -1.0195382195487368,
+           -1.0230487617273332,
+           -1.0174838361364598,
+           -1.00237665738092,
+           -0.9775308420932547,
+           -0.943019565284609,
+           -0.8991775822493476,
+           -0.8465863905930935,
+           -0.7860529814001056,
+           -0.7185827909573274,
+           -0.6453476107404711,
+           -0.5676493398850119,
+           -0.48688056795550405,
+           -0.40448305391430056,
+           -0.32190521784319426,
+           -0.2405597839486653,
+           -0.16178270616564838,
+           -0.08679447148316197,
+           -0.016664811894586344,
+           0.04771823472237298,
+           0.10567408915078967,
+           0.15674953096033692,
+           0.2007321978588059,
+           0.2376573151941578,
+           0.26780746335630473,
+           0.2917053727100106,
+           0.3100999180144509,
+           0.32394566242259865,
+           0.33437647057889824,
+           0.34267386673763295,
+           0.3502309532224994,
+           0.35851282338041757,
+           0.3690144984039461,
+           0.3832174865521809,
+           0.4025461045876482,
+           0.42832471356314866,
+           0.4617370040609606,
+           0.5037884199674786,
+           0.5552727359480605,
+           0.6167437037604965,
+           0.6884925588603485,
+           0.77053203445446,
+           0.862587368819308,
+           0.9640946173221969,
+           1.074206397503143,
+           1.1918050083580964,
+           1.3155226782881888,
+           1.4437685147188204,
+           1.5747615567017497,
+           1.7065691742142988,
+           1.8371499183419637,
+           1.9643998086137733,
+           2.086200950462406,
+           2.2004713095086483,
+           2.305214431859595,
+           2.398567891891036,
+           2.4788492713482224,
+           2.544598525592109,
+           2.59461567325194,
+           2.6279928525251113,
+           2.6441399183358394,
+           2.6428029063717244,
+           2.6240748589871523,
+           2.588398689988863,
+           2.5365619559664006,
+           2.46968359644258,
+           2.3891928989340174,
+           2.2968011332787603,
+           2.194466477685253,
+           2.084353022505382,
+           1.9687847827063572,
+           1.8501957728350056,
+           1.7310772958966627,
+           1.6139236675854867,
+           1.5011776379574078,
+           1.395176782899849,
+           1.2981021173398808,
+           1.2119301315099906,
+           1.1383893719644564
+          ],
+          [
+           1.0953969429041863,
+           1.0469699543687263,
+           1.0143000265789595,
+           0.9979463240064826,
+           0.9981036947967393,
+           1.0145993029273648,
+           1.046897578203915,
+           1.0941133547462742,
+           1.1550328745784193,
+           1.2281421468909777,
+           1.3116619800173748,
+           1.403588846358034,
+           1.5017406041983274,
+           1.6038059878842315,
+           1.7073966918479904,
+           1.8101008165650259,
+           1.909536417021125,
+           2.0034038972882113,
+           2.0895360282115027,
+           2.1659444281182534,
+           2.2308614372635818,
+           2.2827764331443374,
+           2.32046577292424,
+           2.3430157075565394,
+           2.349837785831188,
+           2.340676451210208,
+           2.3156087253830373,
+           2.275036065259876,
+           2.2196686698792085,
+           2.150502695774532,
+           2.0687910092638178,
+           1.9760082577421443,
+           1.87381117563488,
+           1.7639951509714913,
+           1.6484481629182541,
+           1.5291032570603238,
+           1.4078907524453255,
+           1.2866913718164026,
+           1.1672914542385286,
+           1.0513413483607768,
+           0.9403179964748084,
+           0.8354926066137295,
+           0.7379041750871757,
+           0.6483394685099522,
+           0.5673199064496977,
+           0.49509560754615395,
+           0.4316466778442791,
+           0.37669163477545087,
+           0.3297026783772757,
+           0.28992734752953575,
+           0.25641593755916137,
+           0.2280539105708303,
+           0.2035984049133095,
+           0.18171784840827898,
+           0.161033603875162,
+           0.1401625269611321,
+           0.11775929651329317,
+           0.09255738716916813,
+           0.06340759221575512,
+           0.029313071072240654,
+           -0.01054001171993815,
+           -0.05675707272987682,
+           -0.10971560054582644,
+           -0.16955207613607437,
+           -0.23615567929226405,
+           -0.3091689604383338,
+           -0.38799547504176346,
+           -0.47181419573840183,
+           -0.5596003397021213,
+           -0.6501520802676478,
+           -0.7421224566356147,
+           -0.8340556576063433,
+           -0.9244267382240308,
+           -1.011683734966026,
+           -1.094291078086332,
+           -1.1707731606652303,
+           -1.2397569138731994,
+           -1.30001225724458,
+           -1.3504893409551224,
+           -1.3903515730614175,
+           -1.4190035265436776,
+           -1.436112946297375,
+           -1.4416262218526406,
+           -1.4357768539566766,
+           -1.419086618201026,
+           -1.3923593122541267,
+           -1.356667160394031,
+           -1.3133301352472637,
+           -1.2638886372604214,
+           -1.2100701429243852,
+           -1.1537505888416664,
+           -1.0969113964306323,
+           -1.0415931578995135,
+           -0.9898470951379541,
+           -0.943685467014897,
+           -0.9050321355588749,
+           -0.8756745066638167,
+           -0.8572180360807514,
+           -0.8510444370392268,
+           -0.8582746431400361,
+           -0.8797374711248184,
+           -0.915944795365442,
+           -0.9670738926263606,
+           -1.0329574455495107,
+           -1.1130815105297596,
+           -1.2065915646458136,
+           -1.312306551755032,
+           -1.4287406545142196,
+           -1.5541323316946765,
+           -1.6864799833224562,
+           -1.8235834442447336,
+           -1.9630903636924397,
+           -2.102546407809822,
+           -2.239448126940343,
+           -2.3712972620604336,
+           -2.49565522682617,
+           -2.6101964942074725,
+           -2.7127596398512925,
+           -2.80139484760811,
+           -2.8744067648055864,
+           -2.9303917038827816,
+           -2.9682683202709783,
+           -2.987301050693062,
+           -2.9871157676057445,
+           -2.967707290159108,
+           -2.929438585306144,
+           -2.8730316898612616,
+           -2.7995505805867125,
+           -2.7103764100083594,
+           -2.607175705997029,
+           -2.4918622988223658,
+           -2.36655388637956,
+           -2.233524273051696,
+           -2.095152417196468,
+           -1.9538694941516372,
+           -1.8121052242342643,
+           -1.6722347274810123,
+           -1.5365271486017078,
+           -1.4070972473070984,
+           -1.285861072071771,
+           -1.1744967314572254,
+           -1.0744111489560773,
+           -0.9867135381273141,
+           -0.9121961682841535,
+           -0.8513228113014188,
+           -0.8042250716751596,
+           -0.7707066094468508,
+           -0.7502550737424052,
+           -0.7420613781905302,
+           -0.74504577295138,
+           -0.757890005823963,
+           -0.7790747208667343,
+           -0.8069211206571988,
+           -0.8396358206844606,
+           -0.8753577537464968,
+           -0.9122059402696591,
+           -0.9483269281240341,
+           -0.9819407229802546,
+           -1.011384077004557,
+           -1.0351500784565977,
+           -1.0519230855799169,
+           -1.0606081724561633,
+           -1.0603543990488726,
+           -1.0505713788099866,
+           -1.0309387908750027,
+           -1.0014086656386727,
+           -0.962200457797043,
+           -0.9137891050971999,
+           -0.856886449425241,
+           -0.7924165650094126,
+           -0.7214856922073066,
+           -0.6453476107404711,
+           -0.5653653999592447,
+           -0.48297062293574705,
+           -0.3996210336842945,
+           -0.31675794106004784,
+           -0.23576436806485024,
+           -0.1579251213023703,
+           -0.0843898328149959,
+           -0.016139956862524608,
+           0.04603940058939469,
+           0.10158206914032047,
+           0.15015721389771375,
+           0.1916791059295956,
+           0.22630999436291155,
+           0.2544559915328999,
+           0.27675606525536356,
+           0.29406441272020156,
+           0.3074266641086624,
+           0.3180505264054147,
+           0.32727162487697925,
+           0.33651542757137565,
+           0.34725624368937963,
+           0.3609743670748607,
+           0.37911248928868385,
+           0.4030325313670145,
+           0.4339740387369719,
+           0.4730152499216307,
+           0.5210378873975651,
+           0.5786966297720664,
+           0.6463941105027472,
+           0.7242621524933894,
+           0.8121497934258055,
+           0.9096184874595532,
+           1.0159446891581394,
+           1.1301298396633324,
+           1.2509175878798704,
+           1.376817895439626,
+           1.5061374981034001,
+           1.6370160324594487,
+           1.7674669894245514,
+           1.8954225288769717,
+           2.01878108599129,
+           2.135456622164384,
+           2.2434283238422794,
+           2.340789532406062,
+           2.4257946981513445,
+           2.4969031911570743,
+           2.552818870600389,
+           2.592524410230313,
+           2.6153094989778847,
+           2.620792179141205,
+           2.608932746774201,
+           2.5800398158908378,
+           2.5347683355625437,
+           2.474109542359351,
+           2.3993730251346324,
+           2.31216127011071,
+           2.214337236901636,
+           2.1079856860177095,
+           1.995369131349969,
+           1.8788794233582216,
+           1.7609860769135257,
+           1.644182539291164,
+           1.5309316466393212,
+           1.4236115400330136,
+           1.3244633043658138,
+           1.2355415549898174,
+           1.1586691290904627,
+           1.0953969429041885
+          ],
+          [
+           1.0600578650444965,
+           1.0230745448539935,
+           1.0022608494943799,
+           0.9979463240064826,
+           1.0100929360571287,
+           1.0382967607116085,
+           1.081797932464968,
+           1.139498619116672,
+           1.2099885821478136,
+           1.2915777090223046,
+           1.382334738632707,
+           1.4801312559259918,
+           1.5826899090843798,
+           1.6876357054566278,
+           1.7925491730638363,
+           1.8950201345851871,
+           1.9927008311831287,
+           2.0833571545290446,
+           2.1649167963636025,
+           2.235513204561267,
+           2.2935243409538613,
+           2.3376053664406884,
+           2.3667145299244616,
+           2.3801317056109523,
+           2.3774692040327077,
+           2.358674671332304,
+           2.324026084200897,
+           2.274119039663772,
+           2.2098467249235556,
+           2.1323731281530627,
+           2.043100212178518,
+           1.943629915485856,
+           1.835721965461925,
+           1.7212485843447078,
+           1.602147236722724,
+           1.48037260699248,
+           1.357849005072228,
+           1.236424378736338,
+           1.1178270617750141,
+           1.003626310121798,
+           0.8951975751404466,
+           0.7936933370778639,
+           0.7000201754982582,
+           0.6148225910354569,
+           0.5384739181534327,
+           0.4710744862035122,
+           0.4124570005092484,
+           0.36219893116546975,
+           0.3196415193289854,
+           0.2839148434653184,
+           0.25396823548612313,
+           0.2286052027755294,
+           0.20652190009827964,
+           0.186348108090527,
+           0.16668961461351722,
+           0.14617086318121708,
+           0.12347672972092247,
+           0.0973923151236475,
+           0.06683969568778746,
+           0.030910655238893414,
+           -0.011105470675584513,
+           -0.05969957928787473,
+           -0.1151268068166264,
+           -0.17739718644993588,
+           -0.24627321420184897,
+           -0.3212743981464242,
+           -0.401688683905452,
+           -0.4865904692396139,
+           -0.5748647477407565,
+           -0.6652367603391813,
+           -0.7563063877292941,
+           -0.8465863905930934,
+           -0.9345435008916296,
+           -1.0186412891615781,
+           -1.0973836817255853,
+           -1.1693579793446967,
+           -1.233276235733504,
+           -1.2880138904131353,
+           -1.3326446147501203,
+           -1.3664704211641987,
+           -1.389046201154117,
+           -1.4001979951371677,
+           -1.4000344527259894,
+           -1.388951112110913,
+           -1.367627307445139,
+           -1.3370156990465982,
+           -1.2983246081868105,
+           -1.252993521549062,
+           -1.2026623055031809,
+           -1.1491348327544042,
+           -1.0943378695780697,
+           -1.040276197057065,
+           -0.9889850413029644,
+           -0.9424809629538883,
+           -0.9027124033381131,
+           -0.8715111023056031,
+           -0.8505455903215532,
+           -0.8412779151931704,
+           -0.8449246927086169,
+           -0.8624234721686872,
+           -0.894405284627701,
+           -0.9411740965910723,
+           -1.0026937284515571,
+           -1.0785826190545709,
+           -1.1681166297997627,
+           -1.2702398882030073,
+           -1.3835834765962478,
+           -1.506491581396055,
+           -1.637054536798246,
+           -1.773148028323562,
+           -1.912477570499508,
+           -2.052627242848555,
+           -2.1911115624846995,
+           -2.3254292926279834,
+           -2.4531179362046402,
+           -2.5718076436756405,
+           -2.6792732748597623,
+           -2.773483395567799,
+           -2.852645060375935,
+           -2.9152433311490906,
+           -2.9600746046094573,
+           -2.986272968337305,
+           -2.9933289695474605,
+           -2.981100360799808,
+           -2.9498145771051725,
+           -2.9000628950525544,
+           -2.832786421839757,
+           -2.749254255641731,
+           -2.6510343438960726,
+           -2.5399577383283347,
+           -2.418077100703816,
+           -2.2876204476221256,
+           -2.150941232923398,
+           -2.010465949800887,
+           -1.8686404895214985,
+           -1.727876518457636,
+           -1.5904991293816473,
+           -1.4586969868694406,
+           -1.3344761211474507,
+           -1.2196184314645186,
+           -1.1156458414206925,
+           -1.0237909076040153,
+           -0.9449745228849658,
+           -0.8797911807663473,
+           -0.8285020816145653,
+           -0.7910361699899635,
+           -0.7669989993724101,
+           -0.7556891310893706,
+           -0.7561215928481874,
+           -0.7670577533939269,
+           -0.7870408175810788,
+           -0.8144360142631737,
+           -0.8474744410588915,
+           -0.8842994478461099,
+           -0.9230143867127044,
+           -0.9617305312999597,
+           -0.9986139735260735,
+           -1.0319303403450208,
+           -1.0600862365171548,
+           -1.081666409668257,
+           -1.0954657488514974,
+           -1.1005153644517756,
+           -1.0961021520993153,
+           -1.081781412358416,
+           -1.0573822770476944,
+           -1.0230058776101232,
+           -0.9790163763360249,
+           -0.9260251627896193,
+           -0.8648686909442362,
+           -0.7965805929551341,
+           -0.7223588491812014,
+           -0.643528917422177,
+           -0.5615038242972724,
+           -0.4777422957760143,
+           -0.3937060502583514,
+           -0.31081739516189605,
+           -0.2304182563095226,
+           -0.15373172885556555,
+           -0.08182717010533669,
+           -0.015589760132507957,
+           0.04430466200092276,
+           0.09740881735552519,
+           0.14351674833552702,
+           0.1826697777924955,
+           0.21515549963285222,
+           0.24149981674001242,
+           0.2624522239275115,
+           0.2789647106417781,
+           0.2921648257350254,
+           0.3033236005669663,
+           0.3138191630473154,
+           0.32509699051769936,
+           0.3386278406374805,
+           0.35586446433070196,
+           0.3781982416796556,
+           0.4069168894271499,
+           0.4431643672165371,
+           0.48790405933449693,
+           0.541886230730124,
+           0.6056206523646882,
+           0.6793551640479991,
+           0.7630607959743873,
+           0.8564239068271146,
+           0.9588456206353406,
+           1.0694486609213374,
+           1.1870914936536778,
+           1.3103895048050658,
+           1.4377427585599336,
+           1.5673697129454947,
+           1.697346115138776,
+           1.8256481628408157,
+           1.9501989043606582,
+           2.0689167613272694,
+           2.1797649965408845,
+           2.280800917008329,
+           2.3702235995839596,
+           2.4464189540263126,
+           2.508000995102725,
+           2.5538482803215725,
+           2.5831345809365205,
+           2.595352988390765,
+           2.5903328131068144,
+           2.5682488037280726,
+           2.529622398417244,
+           2.475314911136213,
+           2.406512750294097,
+           2.324704959990396,
+           2.2316535605649,
+           2.1293573407109703,
+           2.020009913690933,
+           1.905952991257186,
+           1.789625947242474,
+           1.6735128355029096,
+           1.560088091669142,
+           1.451762183357966,
+           1.3508284782181355,
+           1.2594125732732515,
+           1.1794252730780284,
+           1.1125203195531974,
+           1.060057865044497
+          ],
+          [
+           1.0326711229751988,
+           1.0074385197614222,
+           0.9986396131772894,
+           1.0063715528524144,
+           1.0303637679359836,
+           1.0699846902154502,
+           1.1242566239651834,
+           1.1918784031171894,
+           1.271255292142806,
+           1.360535416118402,
+           1.4576518519644786,
+           1.5603693805114678,
+           1.6663347910517778,
+           1.7731295489820147,
+           1.8783235849552984,
+           1.9795289418749742,
+           2.0744520245523996,
+           2.1609432356573324,
+           2.2370428497002086,
+           2.301022072474935,
+           2.3514183542571256,
+           2.3870641680803537,
+           2.4071086260465453,
+           2.4110314828596557,
+           2.398649262245955,
+           2.3701134340374796,
+           2.325900762715787,
+           2.2667961373963124,
+           2.1938683739394564,
+           2.108439647682042,
+           2.0120493660992267,
+           1.9064134208684531,
+           1.7933798651689836,
+           1.6748821420640425,
+           1.5528910415879127,
+           1.4293665865109852,
+           1.3062110392290411,
+           1.1852241851080658,
+           1.0680619819367836,
+           0.9561995726276242,
+           0.8508995413585709,
+           0.7531861549621746,
+           0.6638261750702599,
+           0.5833166562793566,
+           0.511879965717798,
+           0.44946607440816266,
+           0.395761985384134,
+           0.35020798229693917,
+           0.3120202097774058,
+           0.28021893742200105,
+           0.2536617169268646,
+           0.2310805201505266,
+           0.21112184776929588,
+           0.19238872612725158,
+           0.1734834656458682,
+           0.153050038815658,
+           0.12981494968531415,
+           0.10262550949858096,
+           0.0704845035860058,
+           0.03258033098155308,
+           -0.01168818196454843,
+           -0.06269295252168632,
+           -0.12056429861090773,
+           -0.18518541366019764,
+           -0.2561938126803517,
+           -0.3329897206474848,
+           -0.4147511926138586,
+           -0.5004555785645707,
+           -0.5889067793759338,
+           -0.6787675875511658,
+           -0.7685962715992186,
+           -0.8568864494252407,
+           -0.942109206823901,
+           -1.022756354410564,
+           -1.097383681725585,
+           -1.1646530617329172,
+           -1.223372282704243,
+           -1.2725315369965575,
+           -1.311335576233603,
+           -1.3392306479367144,
+           -1.3559254571205732,
+           -1.3614055445967104,
+           -1.3559406380330223,
+           -1.3400847081121774,
+           -1.3146686460182644,
+           -1.2807856653627958,
+           -1.2397697168577237,
+           -1.1931673829053782,
+           -1.1427038873031827,
+           -1.0902440082142344,
+           -1.0377488165603295,
+           -0.9872292736418737,
+           -0.9406978082187432,
+           -0.9001190522582241,
+           -0.867360944508868,
+           -0.8441474111488202,
+           -0.8320138028792222,
+           -0.8322662086273266,
+           -0.8459456788575264,
+           -0.8737982784255773,
+           -0.9162517526612272,
+           -0.9733994342164153,
+           -1.044991845957987,
+           -1.1304362710093412,
+           -1.2288043694510054,
+           -1.338847726864062,
+           -1.4590210276069413,
+           -1.5875123601787287,
+           -1.7222799878051613,
+           -1.8610947587812243,
+           -2.001587192033033,
+           -2.1412981572637304,
+           -2.277731978806535,
+           -2.408410730173389,
+           -2.5309284538252714,
+           -2.6430040387369123,
+           -2.7425315169754776,
+           -2.827626599100003,
+           -2.8966683553213812,
+           -2.948335062947549,
+           -2.9816333779312316,
+           -2.9959201460125806,
+           -2.990916343180437,
+           -2.966712821731936,
+           -2.9237677325561395,
+           -2.862895691678641,
+           -2.78524895478117,
+           -2.692291052597157,
+           -2.5857635181856824,
+           -2.467646499780552,
+           -2.3401141962557577,
+           -2.2054861727780435,
+           -2.0661757090272266,
+           -1.9246363991839242,
+           -1.7833082601287151,
+           -1.644564611109965,
+           -1.510660964409766,
+           -1.3836871129083637,
+           -1.265523518288579,
+           -1.157802995005044,
+           -1.0618785527840977,
+           -0.9787981076155762,
+           -0.9092866017400345,
+           -0.853735891219529,
+           -0.8122025698010505,
+           -0.7844137046205034,
+           -0.7697802676047629,
+           -0.7674178609166709,
+           -0.7761741599972517,
+           -0.7946623379611861,
+           -0.8212995941857806,
+           -0.8543497913151439,
+           -0.8919691114355206,
+           -0.9322535760908947,
+           -0.9732872376427113,
+           -1.0131898420558467,
+           -1.0501627855971314,
+           -1.0825322395032235,
+           -1.1087883960297529,
+           -1.1276198943628415,
+           -1.1379426129515895,
+           -1.13892216263308,
+           -1.1299895787118117,
+           -1.110849885775219,
+           -1.0814833920401543,
+           -1.042139755821478,
+           -0.9933250506214207,
+           -0.9357822327416456,
+           -0.8704655817748234,
+           -0.798509835676605,
+           -0.7211948745759041,
+           -0.6399069177540299,
+           -0.5560972835765782,
+           -0.47123982048992313,
+           -0.38678814707281656,
+           -0.30413383985516507,
+           -0.22456667920727555,
+           -0.14923800682286678,
+           -0.07912816464032671,
+           -0.015018876617839197,
+           0.04252869563039385,
+           0.09318964139492211,
+           0.13688431561727776,
+           0.17378043644031296,
+           0.20428820307686507,
+           0.22904855407912916,
+           0.24891486569665014,
+           0.26492856209145715,
+           0.278289269360393,
+           0.2903202895201561,
+           0.30243029516302866,
+           0.3160722472058494,
+           0.3327006144189386,
+           0.35372802226094435,
+           0.38048247867357043,
+           0.414166315341173,
+           0.4558179446642365,
+           0.5062774662346632,
+           0.5661570635465747,
+           0.6358170143115275,
+           0.7153479989682054,
+           0.8045602352229068,
+           0.9029797956247373,
+           1.0098522845244597,
+           1.1241538647998504,
+           1.2446094381059658,
+           1.3697175998051327,
+           1.497781815738285,
+           1.6269471069996468,
+           1.7552413849405772,
+           1.8806204554086952,
+           2.001015611869839,
+           2.114382664121706,
+           2.2187512046949016,
+           2.312272899957312,
+           2.393267607865896,
+           2.4602661689786567,
+           2.5120487907419786,
+           2.5476780454836057,
+           2.5665256275753348,
+           2.5682921618737473,
+           2.5530195202523442,
+           2.5210952818012036,
+           2.47324916073234,
+           2.4105414195835135,
+           2.334343479219407,
+           2.246311126628676,
+           2.148350901949518,
+           2.0425804130823977,
+           1.9312834755482986,
+           1.8168611032334818,
+           1.7017794791547336,
+           1.5885161118076052,
+           1.479505430110651,
+           1.3770850872253906,
+           1.2834442301504552,
+           1.200574948242997,
+           1.1302280407423944,
+           1.0738741427094665,
+           1.032671122975199
+          ],
+          [
+           1.0134684209268408,
+           1.0001941669386758,
+           1.0034669549255584,
+           1.0231507292957807,
+           1.058744690022952,
+           1.109394997216336,
+           1.1739144329616913,
+           1.250809550073059,
+           1.3383146604733351,
+           1.4344318547735178,
+           1.5369761031525204,
+           1.6436243692723036,
+           1.7519675765493363,
+           1.859564201857762,
+           1.963994237184411,
+           2.062912255684044,
+           2.1540983450401967,
+           2.235505727318627,
+           2.305303969172682,
+           2.361916797193608,
+           2.4040536676234914,
+           2.430734394221099,
+           2.4413063089587625,
+           2.4354536132048166,
+           2.4131987675943614,
+           2.374895962217149,
+           2.32121690029917,
+           2.2531293135243313,
+           2.171868801006523,
+           2.0789047424362788,
+           1.9759011752344429,
+           1.8646736422750547,
+           1.747143108084554,
+           1.6252881052122448,
+           1.501096307213343,
+           1.3765167296296006,
+           1.2534137354732444,
+           1.1335239677380327,
+           1.0184172498182238,
+           0.9094623875382998,
+           0.8077986765400648,
+           0.714313769357069,
+           0.6296283914247728,
+           0.5540882187062858,
+           0.48776304601429954,
+           0.4304531891018115,
+           0.3817028798514745,
+           0.34082023702325276,
+           0.3069032294500252,
+           0.2788708984371266,
+           0.2554989751670982,
+           0.2354589203907353,
+           0.21735933028756105,
+           0.19978859615645111,
+           0.18135767791822835,
+           0.16074185292572504,
+           0.13672033219749213,
+           0.10821269510150908,
+           0.0743111791862968,
+           0.034307972087899846,
+           -0.012283215585645395,
+           -0.06571186713923671,
+           -0.12598207228759767,
+           -0.1928508658404477,
+           -0.26583354197552195,
+           -0.3442158110119126,
+           -0.4270724864324575,
+           -0.5132922186143495,
+           -0.6016076326659282,
+           -0.6906300849826189,
+           -0.7788881302666133,
+           -0.8648686909442356,
+           -0.9470598467251371,
+           -1.0239941153988887,
+           -1.0942910780863326,
+           -1.1566982135618875,
+           -1.2101288467096343,
+           -1.2536961847105956,
+           -1.286742509513871,
+           -1.3088627141866072,
+           -1.3199215109248779,
+           -1.3200637963613597,
+           -1.3097178313987217,
+           -1.2895910738506002,
+           -1.2606586881601405,
+           -1.224144942732065,
+           -1.1814978872838051,
+           -1.1343578755207744,
+           -1.0845206580098918,
+           -1.0338959123278877,
+           -0.9844621987838139,
+           -0.938219427161158,
+           -0.897139990488964,
+           -0.8631197639844294,
+           -0.837930179865574,
+           -0.8231725712979239,
+           -0.8202359316443144,
+           -0.8302591594986097,
+           -0.854098757481134,
+           -0.892302825902613,
+           -0.9450920442201936,
+           -1.0123481673030275,
+           -1.0936103839314293,
+           -1.1880796960542384,
+           -1.294631283744522,
+           -1.411834627268504,
+           -1.5379809689696802,
+           -1.6711175184114182,
+           -1.809087638834947,
+           -1.9495761055594216,
+           -2.0901584011245706,
+           -2.2283529108779665,
+           -2.3616748088570607,
+           -2.487690379065397,
+           -2.604070502733607,
+           -2.7086420582910335,
+           -2.799436027201641,
+           -2.8747311744459445,
+           -2.933092275448443,
+           -2.973401989175769,
+           -2.9948856268703468,
+           -2.9971282338082763,
+           -2.980083583502783,
+           -2.9440748754930817,
+           -2.8897871246032274,
+           -2.8182514265433003,
+           -2.730821477167765,
+           -2.629142905926892,
+           -2.5151161535980835,
+           -2.3908537761530018,
+           -2.258633186928439,
+           -2.120845954978679,
+           -1.97994485605218,
+           -1.8383899221821127,
+           -1.698594755247224,
+           -1.5628743586264804,
+           -1.4333956995682122,
+           -1.3121321441945428,
+           -1.2008228089520767,
+           -1.100937749257598,
+           -1.0136497611392823,
+           -0.939813408438135,
+           -0.8799517106543734,
+           -0.8342507391834175,
+           -0.8025621771064301,
+           -0.7844137046205029,
+           -0.7790268833561247,
+           -0.7853420328626556,
+           -0.802049425845751,
+           -0.8276259793765,
+           -0.8603764908857191,
+           -0.898478363407595,
+           -0.9400286867416313,
+           -0.9830924917943739,
+           -1.0257509754689247,
+           -1.0661485034827216,
+           -1.1025372380609828,
+           -1.133318305490364,
+           -1.1570785132348957,
+           -1.1726217452656467,
+           -1.1789943043889064,
+           -1.1755036281081885,
+           -1.1617299759229849,
+           -1.1375308666216561,
+           -1.1030382295136674,
+           -1.05864841900489,
+           -1.0050054227940277,
+           -0.9429777657263607,
+           -0.8736297696879536,
+           -0.7981879709074096,
+           -0.7180036161432806,
+           -0.6345122554921963,
+           -0.5491915195781469,
+           -0.4635182109607978,
+           -0.3789258527190266,
+           -0.29676382104209303,
+           -0.218259143748263,
+           -0.14448197412610309,
+           -0.07631565122751387,
+           -0.01443213625138016,
+           0.040726526956936564,
+           0.08896023739633686,
+           0.13031602912497245,
+           0.16508628972336029,
+           0.19380004694132155,
+           0.21720754686662164,
+           0.23625852273913692,
+           0.252074719237404,
+           0.2659173884704551,
+           0.2791506071605056,
+           0.2932013761999416,
+           0.3095175510479865,
+           0.3295247120496625,
+           0.3545831161322485,
+           0.3859458745918306,
+           0.42471947568544777,
+           0.47182771608905305,
+           0.5279800232856927,
+           0.5936450436186123,
+           0.6690302407265032,
+           0.7540680995929965,
+           0.8484093662041948,
+           0.9514235759326656,
+           1.0622069396696299,
+           1.1795974700144796,
+           1.3021970451829632,
+           1.4283999303501014,
+           1.5564271093829682,
+           1.6843656285530797,
+           1.810212021684421,
+           1.9319187766578199,
+           2.047442719064164,
+           2.154794132263404,
+           2.252085405663995,
+           2.337578005472247,
+           2.4097265945142743,
+           2.4672191893039437,
+           2.5090123318920794,
+           2.53436036906528,
+           2.5428380694078276,
+           2.5343559662643305,
+           2.5091679879198026,
+           2.4678711211263082,
+           2.4113970459361207,
+           2.3409958739533203,
+           2.25821231382554,
+           2.1648547723533254,
+           2.0629580724513343,
+           1.9547406260906637,
+           1.8425570374056641,
+           1.7288472249660771,
+           1.6160832399660021,
+           1.5067150165715302,
+           1.4031163203965453,
+           1.3075321602666472,
+           1.2220288970603443,
+           1.1484482222071346,
+           1.0883660888304765,
+           1.0430575627029601,
+           1.0134684209268414
+          ],
+          [
+           1.0026122224480716,
+           1.0014027768887426,
+           1.0167020332436,
+           1.0481418939112097,
+           1.0949955868746681,
+           1.156194252683676,
+           1.230351231919973,
+           1.3157934758143923,
+           1.4105993345386236,
+           1.512641827678118,
+           1.6196363731371575,
+           1.7291918473302799,
+           1.8388637734624786,
+           1.9462083878084346,
+           2.0488363172669137,
+           2.144464615446202,
+           2.230965948734831,
+           2.3064137970935694,
+           2.369122634821785,
+           2.4176821817909953,
+           2.4509849624841324,
+           2.468246574988775,
+           2.469018250789056,
+           2.4531914743725785,
+           2.4209946246789547,
+           2.372981793518796,
+           2.310014124546562,
+           2.2332341955620922,
+           2.144034132466685,
+           2.0440182910788467,
+           1.934961469636126,
+           1.8187637171200168,
+           1.6974028780959354,
+           1.5728860617826326,
+           1.4472012404892027,
+           1.3222701700523696,
+           1.1999037828856582,
+           1.0817611338597988,
+           0.9693128823175495,
+           0.8638101725884978,
+           0.7662596335046515,
+           0.677405058234722,
+           0.5977161532861078,
+           0.5273845641241284,
+           0.466327199096657,
+           0.41419668789757713,
+           0.3703986303058926,
+           0.33411511991742715,
+           0.3043338703158733,
+           0.2798821315305016,
+           0.2594644661707429,
+           0.24170336024887537,
+           0.22518157572847847,
+           0.2084851119292001,
+           0.1902456320316529,
+           0.16918122928346233,
+           0.1441344545966838,
+           0.1141066018140008,
+           0.07828734708149244,
+           0.036078961932407706,
+           -0.012885537285185213,
+           -0.06873078175678735,
+           -0.13133429102982153,
+           -0.20032868979658544,
+           -0.2751108456154954,
+           -0.35485769143536355,
+           -0.4385483216400944,
+           -0.5249917856054863,
+           -0.612859852644706,
+           -0.7007238905374304,
+           -0.7870948899500336,
+           -0.8704655817748228,
+           -0.9493535359415839,
+           -1.0223441001084979,
+           -1.0881320356340334,
+           -1.1455607364467437,
+           -1.1936579732109118,
+           -1.2316671891586828,
+           -1.2590734830638595,
+           -1.275623546375046,
+           -1.2813389722438173,
+           -1.276522520328536,
+           -1.2617570986832662,
+           -1.2378974083206518,
+           -1.2060543825540322,
+           -1.167572737298074,
+           -1.124002125511547,
+           -1.0770625544393237,
+           -1.028604874071335,
+           -0.9805672754843604,
+           -0.934928845147376,
+           -0.8936613030933527,
+           -0.8586801069617485,
+           -0.8317961288536655,
+           -0.8146691069946835,
+           -0.8087640393892762,
+           -0.8153116227370237,
+           -0.8352737483508492,
+           -0.8693149498449734,
+           -0.9177805577547403,
+           -0.9806821573876341,
+           -1.0576907719444983,
+           -1.1481380075404894,
+           -1.2510252047294486,
+           -1.3650404471983786,
+           -1.4885830872119707,
+           -1.6197952638507733,
+           -1.7565997186237192,
+           -1.8967430578789914,
+           -2.037843476426145,
+           -2.1774418452662987,
+           -2.313054981082962,
+           -2.4422298583094952,
+           -2.5625974975999397,
+           -2.6719252680987227,
+           -2.7681663749910337,
+           -2.849505367632166,
+           -2.9143985955831444,
+           -2.961608657910833,
+           -2.9902320322949514,
+           -2.99971923140407,
+           -2.9898870107549746,
+           -2.960922340563249,
+           -2.9133780493522057,
+           -2.8481602445661105,
+           -2.766507810331338,
+           -2.6699644700888663,
+           -2.5603440775266146,
+           -2.4396899588059844,
+           -2.310229268636679,
+           -2.174323438931327,
+           -2.0344158887667296,
+           -1.892978226034334,
+           -1.7524562030178639,
+           -1.6152166894616016,
+           -1.483496897508454,
+           -1.3593570339604768,
+           -1.2446374681422891,
+           -1.1409213904163218,
+           -1.0495037999330212,
+           -0.9713675038873386,
+           -0.9071666382675021,
+           -0.8572180360807509,
+           -0.8215005778613701,
+           -0.7996624656152278,
+           -0.7910361699899628,
+           -0.7946606160730979,
+           -0.8093100003218818,
+           -0.833528473935922,
+           -0.8656697903172856,
+           -0.9039408994523158,
+           -0.9464483828522182,
+           -0.9912465612229393,
+           -1.0363860747248241,
+           -1.0799617332292228,
+           -1.1201584613408453,
+           -1.1552942193500857,
+           -1.1838588652072337,
+           -1.2045480318895008,
+           -1.2162912263544752,
+           -1.2182735072777862,
+           -1.2099502651258798,
+           -1.1910548056097345,
+           -1.1615986217264906,
+           -1.1218644257895376,
+           -1.0723921963995724,
+           -1.0139586716198392,
+           -0.9475508842786995,
+           -0.8743344842220702,
+           -0.7956177217691406,
+           -0.7128120733737306,
+           -0.6273905719205223,
+           -0.5408449581902989,
+           -0.454642795499321,
+           -0.37018568576494154,
+           -0.28876969241681005,
+           -0.21154901453666056,
+           -0.1395038689540173,
+           -0.07341342500304673,
+           -0.013834503122134132,
+           0.038913403143018985,
+           0.0847563880314236,
+           0.1238674595345195,
+           0.15666089405700914,
+           0.18377976577307065,
+           0.20607697538162192,
+           0.22459027344345306,
+           0.2405119314065942,
+           0.2551538547758779,
+           0.2699090540551163,
+           0.2862104869886155,
+           0.30548835773963856,
+           0.3291270031008081,
+           0.3584225114635294,
+           0.3945422066327529,
+           0.438487085948105,
+           0.4910582315802289,
+           0.5528281170344147,
+           0.624117610196381,
+           0.7049793326849968,
+           0.7951878763500508,
+           0.8942372054281915,
+           1.0013453914484447,
+           1.1154666419975832,
+           1.2353103985765914,
+           1.3593670976701222,
+           1.4859400173695174,
+           1.613182473772464,
+           1.7391394909312743,
+           1.8617929489089704,
+           1.9791091195776787,
+           2.089087431608263,
+           2.1898092664454962,
+           2.279485577024074,
+           2.3565021409097913,
+           2.4194613090542716,
+           2.4672191893039437,
+           2.4989173083689096,
+           2.514007924635412,
+           2.5122723138948393,
+           2.4938315171336654,
+           2.4591492199157563,
+           2.4090266221869023,
+           2.3445893509081626,
+           2.267266661031367,
+           2.1787633582214747,
+           2.0810250547809357,
+           1.976197534048579,
+           1.8665811440816549,
+           1.7545812650788877,
+           1.6426559936918474,
+           1.533262258637787,
+           1.4288016240757813,
+           1.3315670489614733,
+           1.2436918517168494,
+           1.1671020804564871,
+           1.1034734108555408,
+           1.0541935883981988,
+           1.020331301745189,
+           1.0026122224480716
+          ],
+          [
+           1.000194375890509,
+           1.0110541242245423,
+           1.0382328733799016,
+           1.0811336101374207,
+           1.1388097595000446,
+           1.2099865137393062,
+           1.2930895399828917,
+           1.3862803869238496,
+           1.4874977532868823,
+           1.5945036430710051,
+           1.704933318630112,
+           1.8163478751012911,
+           1.9262882006443318,
+           2.032329057813928,
+           2.1321320228138188,
+           2.223496051294987,
+           2.30440450092605,
+           2.373067530625589,
+           2.4279589118578424,
+           2.4678464258792716,
+           2.49181517884787,
+           2.4992833403596277,
+           2.490009995969737,
+           2.4640949960309855,
+           2.4219708770211317,
+           2.3643871226757778,
+           2.2923872160101455,
+           2.207279105210201,
+           2.110599862211125,
+           2.0040754487745307,
+           1.8895766177390656,
+           1.769072064144639,
+           1.6445800000565485,
+           1.5181193567748215,
+           1.3916618180677802,
+           1.2670858582201694,
+           1.1461338998787096,
+           1.030373620470929,
+           0.921164324603802,
+           0.8196291661745565,
+           0.7266338513530471,
+           0.6427722859926102,
+           0.5683594526293744,
+           0.5034316175341939,
+           0.4477537819296272,
+           0.4008341081518001,
+           0.36194487581377666,
+           0.3301493593042797,
+           0.30433387031587317,
+           0.28324408121256794,
+           0.2655246400895026,
+           0.24976100893810488,
+           0.23452240435601074,
+           0.2184046969868419,
+           0.20007213187249615,
+           0.17829676694602106,
+           0.1519945900524617,
+           0.12025736451824522,
+           0.082379367091962,
+           0.03787831713960988,
+           -0.013490051149036031,
+           -0.07172415499059895,
+           -0.1365756726451128,
+           -0.20755561975418713,
+           -0.28394723341345013,
+           -0.3648253267939467,
+           -0.449081607478038,
+           -0.5354552959071188,
+           -0.6225682404395576,
+           -0.7089636060531064,
+           -0.7931471177489559,
+           -0.8736297696879529,
+           -0.9489708688245636,
+           -1.0178202684153883,
+           -1.078958662654834,
+           -1.1313348584836462,
+           -1.1740990132510338,
+           -1.2066309256114225,
+           -1.2285625893677161,
+           -1.2397943629026158,
+           -1.2405042668134318,
+           -1.2311500953961343,
+           -1.2124642093879132,
+           -1.1854410633243786,
+           -1.1513177063340974,
+           -1.1115476755180163,
+           -1.0677688717026785,
+           -1.02176616400381,
+           -0.9754296083218195,
+           -0.9307092820828382,
+           -0.889567830236884,
+           -0.8539318833308529,
+           -0.8256435456550423,
+           -0.8064131589932493,
+           -0.7977745250984426,
+           -0.801043718122759,
+           -0.8172825380389821,
+           -0.8472675494932272,
+           -0.8914655200762409,
+           -0.9500159208416802,
+           -1.0227209837014384,
+           -1.1090436291877939,
+           -1.2081133884154036,
+           -1.3187402495483984,
+           -1.439436166429238,
+           -1.5684437799942585,
+           -1.7037717262941174,
+           -1.8432357427206894,
+           -1.9845046404276416,
+           -2.12515008948242,
+           -2.262699067024548,
+           -2.394687750036659,
+           -2.5187155949938886,
+           -2.6324983376583484,
+           -2.733918667901,
+           -2.8210733861825705,
+           -2.892315928990364,
+           -2.9462932581790584,
+           -2.981976241209109,
+           -2.9986828025246224,
+           -2.9960932970508116,
+           -2.9742577408763964,
+           -2.9335947271476672,
+           -2.874882052348939,
+           -2.799239274686289,
+           -2.708102617450159,
+           -2.6031928113624705,
+           -2.486476636616431,
+           -2.360123073548069,
+           -2.2264550970481767,
+           -2.0878982508830917,
+           -1.9469272116124199,
+           -1.8060115960164875,
+           -1.6675622798407594,
+           -1.5338794789374184,
+           -1.4071037969956541,
+           -1.2891713682004786,
+           -1.1817741202526946,
+           -1.0863260557878416,
+           -1.0039363015167273,
+           -0.9353895080575576,
+           -0.8811340035521613,
+           -0.8412779151931706,
+           -0.8155932793876852,
+           -0.803527968198794,
+           -0.8042250716751572,
+           -0.8165491973025523,
+           -0.8391189834440153,
+           -0.8703449772764834,
+           -0.908471902927955,
+           -0.9516242452759774,
+           -0.9978540015778304,
+           -1.0451894084849687,
+           -1.0916834370550326,
+           -1.135460863382306,
+           -1.1747627669469536,
+           -1.2079873815299158,
+           -1.2337263226487643,
+           -1.2507953383855477,
+           -1.2582588740586396,
+           -1.2554479017877467,
+           -1.2419706395497028,
+           -1.2177159664432742,
+           -1.1828495269907469,
+           -1.1378027027283153,
+           -1.083254809429636,
+           -1.020109048562395,
+           -0.949462897746348,
+           -0.8725737631733278,
+           -0.7908208337325588,
+           -0.7056641690682858,
+           -0.6186021197046243,
+           -0.5311282150992377,
+           -0.4446886641364699,
+           -0.3606415919779654,
+           -0.28021908792487055,
+           -0.20449306230196646,
+           -0.13434580832898474,
+           -0.07044604011405732,
+           -0.013231033476806616,
+           0.037104664036554734,
+           0.08061365976807403,
+           0.11759316466266513,
+           0.1485755321011319,
+           0.17431213568502724,
+           0.1957510092955368,
+           0.21400883647858301,
+           0.23033802501629752,
+           0.24608973264227466,
+           0.26267381792511035,
+           0.2815167736151915,
+           0.30401875607942624,
+           0.3315108523700484,
+           0.3652137252329373,
+           0.40619874593738653,
+           0.4553526659164051,
+           0.513346792274801,
+           0.5806115213638242,
+           0.6573169515776326,
+           0.7433601446018815,
+           0.8383594373210833,
+           0.9416560286377285,
+           1.0523228810229213,
+           1.1691807903263227,
+           1.2908212939001626,
+           1.4156359110536445,
+           1.5418510456899968,
+           1.6675677328419298,
+           1.7908052824730558,
+           1.9095477686292566,
+           2.0217922325132847,
+           2.1255974163895663,
+           2.2191318227882633,
+           2.3007199009267065,
+           2.3688851995208693,
+           2.422389391395871,
+           2.4602661689786567,
+           2.481849128639527,
+           2.4867929030834657,
+           2.475086961159172,
+           2.4470616696589285,
+           2.4033863976512815,
+           2.3450596360714537,
+           2.27339129897923,
+           2.1899775633218397,
+           2.096668786522683,
+           1.9955312112555488,
+           1.8888033201557504,
+           1.7788478361658084,
+           1.6681004734113445,
+           1.5590166262293506,
+           1.4540172381490668,
+           1.3554351168771026,
+           1.2654629550181902,
+           1.1861042794744134,
+           1.1191284860620332,
+           1.0660310214435842,
+           1.0279996542624512,
+           1.0058876342876122,
+           1.000194375890509
+          ],
+          [
+           1.0062353373301178,
+           1.02906655418033,
+           1.0678773146840943,
+           1.1218467531262195,
+           1.1898165201725328,
+           1.2703166735134226,
+           1.3615985626748295,
+           1.4616739322377559,
+           1.5683593212985718,
+           1.679324712951064,
+           1.7921452888752087,
+           1.9043550731518453,
+           2.0135012078809367,
+           2.117197592035955,
+           2.2131766344644666,
+           2.2993379215209875,
+           2.373792678230994,
+           2.434903007167849,
+           2.4813150187534125,
+           2.5119851172538734,
+           2.526198874608385,
+           2.5235821052543246,
+           2.5041039448377065,
+           2.4680719294529085,
+           2.416119265084319,
+           2.3491846644925602,
+           2.268485306312404,
+           2.1754836342778465,
+           2.0718488592953825,
+           1.9594141500435676,
+           1.8401305959271905,
+           1.716019097218819,
+           1.5891213794172288,
+           1.461451341295392,
+           1.3349479285946335,
+           1.2114306783822846,
+           1.0925590039937847,
+           0.9797961891878065,
+           0.8743789352627086,
+           0.7772931596028714,
+           0.6892565821331234,
+           0.6107084615554104,
+           0.5418066604261855,
+           0.48243203170346427,
+           0.43219993402700996,
+           0.3904785033357654,
+           0.356413138963497,
+           0.328956507313124,
+           0.30690322945002496,
+           0.2889283038677157,
+           0.27362822510976464,
+           0.25956369510438576,
+           0.24530278853319604,
+           0.2294634271511257,
+           0.21075404080556298,
+           0.18801134433994857,
+           0.16023423826211858,
+           0.12661294497851258,
+           0.08655261887675698,
+           0.039690814350235984,
+           -0.014091642716364051,
+           -0.07466666154859673,
+           -0.1416618726732542,
+           -0.21447051261558858,
+           -0.2922679455301043,
+           -0.3740343863821229,
+           -0.4585832275817331,
+           -0.5445942234873037,
+           -0.6306506586966437,
+           -0.7152795198078706,
+           -0.7969936090775371,
+           -0.8743344842220695,
+           -0.9459150829110452,
+           -1.0104608939827415,
+           -1.0668485700351364,
+           -1.114140937037446,
+           -1.1516174444817897,
+           -1.1787992121874635,
+           -1.1954679643924462,
+           -1.2016782948743816,
+           -1.1977628747195772,
+           -1.1843303928103375,
+           -1.1622562036613864,
+           -1.1326658432772114,
+           -1.0969117565497848,
+           -1.0565437547661787,
+           -1.013273884630258,
+           -0.9689365366992175,
+           -0.9254447475716664,
+           -0.8847437533084955,
+           -0.8487629287645723,
+           -0.8193672967426167,
+           -0.7983098108267113,
+           -0.7871856058141232,
+           -0.7873893699845781,
+           -0.8000769249097727,
+           -0.8261320027148852,
+           -0.8661390899408229,
+           -0.920363064327533,
+           -0.9887361894050506,
+           -1.0708528556682073,
+           -1.1659722706232045,
+           -1.2730291076948008,
+           -1.3906519305905167,
+           -1.5171890199879632,
+           -1.6507410480170552,
+           -1.7891998774276654,
+           -1.9302926107352234,
+           -2.071629883779971,
+           -2.2107572912750983,
+           -2.3452087517239177,
+           -2.472560567574459,
+           -2.5904849149676976,
+           -2.696801506503241,
+           -2.7895262099257763,
+           -2.8669154746102676,
+           -2.927505514555148,
+           -2.9701453189556295,
+           -2.994022706372131,
+           -2.998682802524622,
+           -2.9840385008559562,
+           -2.950372654868041,
+           -2.898331947231419,
+           -2.828912578037563,
+           -2.7434381085059343,
+           -2.64352998226019,
+           -2.5310714194359236,
+           -2.4081655351718334,
+           -2.277088669678045,
+           -2.1402400287873786,
+           -2.0000888189824595,
+           -1.859120117313546,
+           -1.7197807430414414,
+           -1.5844263936558152,
+           -1.4552712732812105,
+           -1.3343413772866923,
+           -1.2234325047799244,
+           -1.1240739528948942,
+           -1.0374987063022592,
+           -0.9646207756648462,
+           -0.906020163774888,
+           -0.8619357521617036,
+           -0.8322662086273268,
+           -0.8165788221805333,
+           -0.8141259809561116,
+           -0.823868825599783,
+           -0.8445074397425905,
+           -0.8745167847431243,
+           -0.9121874515895189,
+           -0.9556701919676474,
+           -1.0030231056740757,
+           -1.0522603047887058,
+           -1.1014008476304697,
+           -1.1485167380773438,
+           -1.1917788181734363,
+           -1.2294994431668884,
+           -1.2601709166045076,
+           -1.2824987765597184,
+           -1.2954291595829353,
+           -1.2981696230879893,
+           -1.2902029757196287,
+           -1.2712938445226476,
+           -1.241487892938639,
+           -1.201103790139746,
+           -1.1507182152949473,
+           -1.0911443554734581,
+           -1.0234045186496847,
+           -0.9486976296301742,
+           -0.8683625030385341,
+           -0.7838378906410703,
+           -0.696620377731833,
+           -0.6082212531270683,
+           -0.5201234983483899,
+           -0.4337400333278696,
+           -0.3503743187102872,
+           -0.27118434954946896,
+           -0.19715098359294098,
+           -0.12905143177794176,
+           -0.06743860197946325,
+           -0.012626832941670205,
+           0.03531561238884828,
+           0.07656710196200166,
+           0.11154622788317609,
+           0.14089860967654327,
+           0.1654772571118867,
+           0.18631701095400663,
+           0.20460373558940437,
+           0.2216390759183212,
+           0.23880170864445685,
+           0.2575061121421292,
+           0.2791599470187384,
+           0.305121179562397,
+           0.33665609141386155,
+           0.3748993006989244,
+           0.42081687290857,
+           0.4751735251520551,
+           0.5385048268636048,
+           0.6110951761011607,
+           0.6929621863114107,
+           0.7838479574408276,
+           0.8832175315649278,
+           0.9902646511311904,
+           1.1039247520267212,
+           1.2228949386550627,
+           1.3456605086917894,
+           1.470527425710382,
+           1.5956599827119236,
+           1.719122762690031,
+           1.8389258872029433,
+           1.9530724534611485,
+           2.0596069970148774,
+           2.156663782415867,
+           2.242513719196441,
+           2.3156087253830373,
+           2.3746224150262356,
+           2.418486068637491,
+           2.4464189540263126,
+           2.457952197227881,
+           2.4529455558067066,
+           2.431596616111533,
+           2.394442117913351,
+           2.342351299835697,
+           2.2765113524278897,
+           2.1984052578861273,
+           2.10978248156507,
+           2.0126231559539547,
+           1.9090965583797945,
+           1.8015148253687086,
+           1.6922829658278604,
+           1.5838463290335467,
+           1.478636749474564,
+           1.3790186272319493,
+           1.2872362088251121,
+           1.2053633091138993,
+           1.1352566604591785,
+           1.0785139921938545,
+           1.0364378335285642,
+           1.010005898958913,
+           0.9998487602927529,
+           1.0062353373301178
+          ],
+          [
+           1.0206839974995523,
+           1.0552876734479617,
+           1.1053845517684815,
+           1.1699368712650133,
+           1.247584328616021,
+           1.3366743115546271,
+           1.4352986826631262,
+           1.541336248246787,
+           1.6524999131180373,
+           1.7663874126851375,
+           1.8805344311403072,
+           1.9924688607627232,
+           2.099764933666735,
+           2.2000959642715476,
+           2.2912844781311876,
+           2.3713485695832555,
+           2.438543425271156,
+           2.491397070607929,
+           2.5287395387002456,
+           2.5497248226127858,
+           2.5538451481407427,
+           2.54093729112654,
+           2.511180856207957,
+           2.465088627982015,
+           2.4034892961533867,
+           2.3275030386445636,
+           2.2385106164251183,
+           2.1381167868367315,
+           2.028108974739154,
+           1.9104122496826894,
+           1.7870417399196095,
+           1.6600536684494902,
+           1.531496221203898,
+           1.40336145239787,
+           1.2775393972380333,
+           1.1557754985444,
+           1.0396323630929867,
+           0.9304567479656352,
+           0.8293525398587248,
+           0.7371603346462999,
+           0.654444054455888,
+           0.5814848593869074,
+           0.518282425313856,
+           0.46456347263048847,
+           0.41979724798025764,
+           0.383217486552181,
+           0.3538502207519465,
+           0.330546656011577,
+           0.3120202097774054,
+           0.2968867084001422,
+           0.2837066612353436,
+           0.271028483586985,
+           0.2574315213317159,
+           0.2415677405607292,
+           0.2222009850476607,
+           0.19824277174459576,
+           0.16878368807331742,
+           0.13311957210817602,
+           0.09077179483736009,
+           0.04150111901771978,
+           -0.014685222250286387,
+           -0.07753340649380065,
+           -0.1465498595604758,
+           -0.2210148652581577,
+           -0.3000025849757858,
+           -0.3824069573886292,
+           -0.4669727939455703,
+           -0.5523312488833005,
+           -0.6370387265001732,
+           -0.7196181963133744,
+           -0.7986018208785804,
+           -0.8725737631733269,
+           -0.9402120315326158,
+           -1.000328240448412,
+           -1.0519042146383826,
+           -1.0941244404639159,
+           -1.1264034711479933,
+           -1.148407517776366,
+           -1.1600696036408285,
+           -1.1615978214735805,
+           -1.1534764074800683,
+           -1.1364595284411787,
+           -1.111557863951514,
+           -1.080018250421809,
+           -1.043296832155243,
+           -1.003026333101679,
+           -0.960978216544181,
+           -0.9190206350782224,
+           -0.8790731863612291,
+           -0.843059578334402,
+           -0.8128593686613251,
+           -0.7902599753718343,
+           -0.7769101582420592,
+           -0.7742761431167499,
+           -0.7836015047646893,
+           -0.8058718392583776,
+           -0.8417851462891464,
+           -0.8917287079219796,
+           -0.9557630962981961,
+           -1.033613772451684,
+           -1.1246705558711811,
+           -1.2279950541836824,
+           -1.342335949018879,
+           -1.4661518424937807,
+           -1.5976411835498792,
+           -1.7347786191529506,
+           -1.8753569564361476,
+           -2.0170337821702358,
+           -2.1573816689525964,
+           -2.2939408061393127,
+           -2.4242728300957936,
+           -2.5460145944221417,
+           -2.6569306173079594,
+           -2.7549629702286733,
+           -2.838277429204824,
+           -2.905304795462246,
+           -2.9547764045091713,
+           -2.9857529786855066,
+           -2.997646134853533,
+           -2.9902320322949514,
+           -2.9636568318501695,
+           -2.918433831365663,
+           -2.8554323398891848,
+           -2.775858548972179,
+           -2.681228849141249,
+           -2.5733362184745894,
+           -2.4542104739202264,
+           -2.326073320547222,
+           -2.1912892558261494,
+           -2.052313482344535,
+           -1.9116380507575301,
+           -1.7717374936210406,
+           -1.6350152191452694,
+           -1.503751911679574,
+           -1.3800571334834477,
+           -1.2658252413776763,
+           -1.1626966242305266,
+           -1.0720251355943586,
+           -0.9948524434308504,
+           -0.9318898495165632,
+           -0.8835079489817412,
+           -0.8497343099901994,
+           -0.83025915949861,
+           -0.8244488681019239,
+           -0.8313668399035982,
+           -0.8498012367167384,
+           -0.8782988040109209,
+           -0.9152039228025305,
+           -0.9587018906084043,
+           -1.0068653385536181,
+           -1.057702623029393,
+           -1.1092069905405468,
+           -1.1594053044483053,
+           -1.2064051423477467,
+           -1.2484391222209157,
+           -1.2839053929512012,
+           -1.3114033282538116,
+           -1.3297635899102218,
+           -1.338071873157299,
+           -1.3356858104459157,
+           -1.3222446854211176,
+           -1.2976717924617414,
+           -1.2621694638407592,
+           -1.2162069718471002,
+           -1.1605016924087839,
+           -1.0959940854014476,
+           -1.0238172007135529,
+           -0.9452615544447294,
+           -0.8617363329840464,
+           -0.7747279713530468,
+           -0.6857572139314413,
+           -0.5963357990164961,
+           -0.5079239128211588,
+           -0.42188953344447266,
+           -0.33947073173974546,
+           -0.2617419152655269,
+           -0.18958489571779105,
+           -0.12366553212224297,
+           -0.06441655488676443,
+           -0.012027013326656014,
+           0.03356138438639433,
+           0.07265095032333417,
+           0.10577780901747691,
+           0.1336950770208023,
+           0.15734987712420606,
+           0.17785479625193365,
+           0.19645454218529634,
+           0.2144886811583533,
+           0.2333514427633145,
+           0.25444965783551043,
+           0.2791599470187383,
+           0.30878630118703254,
+           0.3445191891816896,
+           0.38739729351027524,
+           0.43827291157734927,
+           0.4977819702168804,
+           0.5663194869898782,
+           0.6440211757333352,
+           0.7307517395822146,
+           0.8261002259842735,
+           0.9293826393057621,
+           1.0396518219666302,
+           1.1557144292810397,
+           1.2761546409830118,
+           1.3993640783793067,
+           1.5235772345876442,
+           1.6469115804792707,
+           1.7674113844353356,
+           1.8830941830300993,
+           1.991998764875824,
+           2.0922334830633975,
+           2.182023694172892,
+           2.259757134245987,
+           2.3240260842008964,
+           2.3736652479865947,
+           2.4077843646559405,
+           2.4257946981513445,
+           2.4274286929871987,
+           2.412752246679196,
+           2.382169226750631,
+           2.3364180471153184,
+           2.276560311015219,
+           2.2039617207542874,
+           2.1202656434680724,
+           2.0273599024414097,
+           1.9273375305809823,
+           1.8224523724291288,
+           1.7150705498518464,
+           1.6076189110419206,
+           1.5025316601323653,
+           1.4021964135571428,
+           1.3089009480720524,
+           1.224781893542288,
+           1.1517765814483518,
+           1.091579188536824,
+           1.0456022158483436,
+           1.0149442188713127,
+           1.0003645577997182,
+           1.0022657713672294,
+           1.0206839974995523
+          ],
+          [
+           1.0434181141956862,
+           1.0894956394932418,
+           1.150437256435111,
+           1.224997100393321,
+           1.311624443030846,
+           1.4084980122179176,
+           1.5135663635829961,
+           1.6245933557098975,
+           1.7392076612644334,
+           1.854955152437155,
+           1.969352933285302,
+           2.0799437554187934,
+           2.1843495478467982,
+           2.2803228167796514,
+           2.3657947261123584,
+           2.438918752813994,
+           2.4981089214265286,
+           2.5420717556052703,
+           2.5698312387997513,
+           2.5807462469712608,
+           2.5745200994607793,
+           2.551202065250484,
+           2.5111808562079565,
+           2.4551703316987084,
+           2.3841878254806166,
+           2.2995256814975105,
+           2.2027167457884373,
+           2.0954947033248987,
+           1.979750267758308,
+           1.857484325942562,
+           1.7307592054611278,
+           1.6016492706886871,
+           1.4721920603307217,
+           1.3443411568283024,
+           1.219921926150913,
+           1.1005911867121998,
+           0.9878017605079146,
+           0.8827727308035063,
+           0.7864660820716449,
+           0.6995702331642858,
+           0.6224907980583391,
+           0.5553487243852774,
+           0.4979857729662739,
+           0.44997711641063887,
+           0.4106506561256052,
+           0.3791124892886841,
+           0.35427780462692865,
+           0.3349063520220993,
+           0.3196415193289848,
+           0.3070519631062842,
+           0.29567468033607264,
+           0.2840583770874639,
+           0.27080598818378054,
+           0.25461522924694285,
+           0.2343161182706999,
+           0.2089044866543456,
+           0.1775706072719854,
+           0.13972219689743628,
+           0.09500119883594568,
+           0.043293915145402144,
+           -0.015265767799348254,
+           -0.08030013586675738,
+           -0.15119827872587246,
+           -0.22713330949718494,
+           -0.30708571320082,
+           -0.389872204074119,
+           -0.47417932704178933,
+           -0.5586009133592156,
+           -0.6416783979058946,
+           -0.7219429284031077,
+           -0.7979581469525248,
+           -0.8683625030385332,
+           -0.9319099650845973,
+           -0.9875080346463786,
+           -1.034252032473627,
+           -1.071454717381636,
+           -1.0986704148735014,
+           -1.1157129698652464,
+           -1.1226669932627633,
+           -1.1198920416418041,
+           -1.1080195486476057,
+           -1.0879425114630334,
+           -1.060798121153502,
+           -1.0279437072170354,
+           -0.9909265396718797,
+           -0.9514481921287096,
+           -0.9113243124605152,
+           -0.8724407702557411,
+           -0.836707249081719,
+           -0.8060094241431432,
+           -0.7821609102921617,
+           -0.766856180328516,
+           -0.7616256386454058,
+           -0.7677939907971475,
+           -0.7864429764925654,
+           -0.8183794335709564,
+           -0.8641095360839992,
+           -0.923819903689143,
+           -0.9973661156990605,
+           -1.084268985321668,
+           -1.183718762213856,
+           -1.2945872390546762,
+           -1.4154475451483333,
+           -1.544601221839389,
+           -1.6801119954062336,
+           -1.8198454975226994,
+           -1.9615140354446305,
+           -2.1027253874645595,
+           -2.241034497039832,
+           -2.373996863898343,
+           -2.4992223842602463,
+           -2.6144283762742484,
+           -2.717490541305851,
+           -2.8064906565331666,
+           -2.879759868362863,
+           -2.9359165577127313,
+           -2.9738978747832046,
+           -2.9929841895048286,
+           -2.9928158708087413,
+           -2.97340198917577,
+           -2.93512072817605,
+           -2.878711487268575,
+           -2.8052588552113744,
+           -2.7161688262459003,
+           -2.613137815076468,
+           -2.4981151970980235,
+           -2.373260253194416,
+           -2.2408945300254715,
+           -2.1034507338582467,
+           -1.9634193560897673,
+           -1.823294279731916,
+           -1.6855186370724298,
+           -1.552432179016971,
+           -1.4262213765351737,
+           -1.3088734052016056,
+           -1.2021350667823016,
+           -1.107477579585032,
+           -1.0260680248978085,
+           -0.958748073855161,
+           -0.9060204415180055,
+           -0.8680433272021605,
+           -0.8446329067596356,
+           -0.8352737483508494,
+           -0.8391368330021253,
+           -0.8551046795729803,
+           -0.8818029050934237,
+           -0.9176373998750665,
+           -0.9608361660231113,
+           -1.0094947611310163,
+           -1.0616242085796812,
+           -1.1152001838823398,
+           -1.1682122641032238,
+           -1.2187120349864804,
+           -1.2648588877713123,
+           -1.304962403713422,
+           -1.3375203173457428,
+           -1.361251167092344,
+           -1.375120880991758,
+           -1.3783627024557517,
+           -1.3704900322111024,
+           -1.3513019435291,
+           -1.3208813139912623,
+           -1.2795857037012845,
+           -1.228031292361297,
+           -1.1670703614263682,
+           -1.097762968303886,
+           -1.0213436032769982,
+           -0.9391837429409235,
+           -0.8527513134069017,
+           -0.7635681499079505,
+           -0.6731665849484993,
+           -0.5830463136929126,
+           -0.4946326725314803,
+           -0.40923742507770505,
+           -0.3280230803460405,
+           -0.2519716723398369,
+           -0.18185881120363417,
+           -0.11823367651012293,
+           -0.06140546672185701,
+           -0.01143664937712854,
+           0.03185682159189086,
+           0.06889833726701351,
+           0.10033671149941076,
+           0.1270258792798123,
+           0.14999875703436247,
+           0.17043595935489325,
+           0.1896302021300097,
+           0.2089473363116537,
+           0.22978504671447547,
+           0.2535303139917494,
+           0.2815167736151913,
+           0.31498311236590193,
+           0.3550336203083243,
+           0.40260196499239964,
+           0.4584191759576389,
+           0.5229867234351946,
+           0.5965554480426759,
+           0.6791109514042747,
+           0.7703658946694057,
+           0.869759476920972,
+           0.9764641828421496,
+           1.0893997033308305,
+           1.2072537486812092,
+           1.328509296128186,
+           1.4514776464620158,
+           1.5743365122970174,
+           1.6951722272833145,
+           1.812025054487028,
+           1.9229364861854452,
+           2.025997368664357,
+           2.1193956558232205,
+           2.201462595331686,
+           2.2707161808428484,
+           2.3259007627157864,
+           2.366021796468225,
+           2.3903748207094804,
+           2.398567891891036,
+           2.3905368585753997,
+           2.366553029283833,
+           2.327222971156608,
+           2.2734803671599737,
+           2.206570052726031,
+           2.1280245437636878,
+           2.039633552221621,
+           1.9434071582668866,
+           1.841533465386607,
+           1.7363317024236353,
+           1.630201851292517,
+           1.5255719680223991,
+           1.424844425602012,
+           1.3303423383085944,
+           1.2442574279636802,
+           1.1686005627968226,
+           1.1051561399858683,
+           1.0554413948840937,
+           1.0206716055461327,
+           1.0017320231778009,
+           0.9991572008938313,
+           1.0131182185036414,
+           1.0434181141956858
+          ],
+          [
+           1.074245346503965,
+           1.1314010374441459,
+           1.202654262415922,
+           1.2865616060576799,
+           1.3813950550705756,
+           1.4851801144950874,
+           1.5957394254373274,
+           1.7107408618236788,
+           1.8277489789527386,
+           1.9442786090514543,
+           2.057849350591215,
+           2.1660396799284247,
+           2.2665394263101883,
+           2.357199394084982,
+           2.436076987993787,
+           2.501476796887214,
+           2.5519852156459435,
+           2.5864983313942402,
+           2.6042424646748814,
+           2.6047869350418718,
+           2.588048809124804,
+           2.554289582992205,
+           2.5041039448377065,
+           2.4384009538776255,
+           2.358378152241915,
+           2.2654892941527622,
+           2.161406526744858,
+           2.0479779858555704,
+           1.927181874896468,
+           1.8010781730081848,
+           1.6717591682614015,
+           1.5413000315697574,
+           1.4117106368341263,
+           1.2848897929941965,
+           1.1625829852108729,
+           1.0463446271349706,
+           0.9375057065900534,
+           0.8371475660638754,
+           0.7460824007406909,
+           0.664840884425081,
+           0.5936671519486131,
+           0.5325211800793702,
+           0.4810884222466395,
+           0.4387963702179371,
+           0.404837542769023,
+           0.3781982416796558,
+           0.357692273035377,
+           0.34199871034365686,
+           0.329702678377275,
+           0.3193380653314972,
+           0.3094310275547692,
+           0.2985431368107144,
+           0.2853130350478064,
+           0.2684955055514254,
+           0.2469969409654533,
+           0.21990628613658061,
+           0.18652065454557543,
+           0.1463649581528544,
+           0.09920504820085865,
+           0.0450540348667934,
+           -0.015828367685504732,
+           -0.08294344188501242,
+           -0.15556780243987123,
+           -0.23277408052578058,
+           -0.31345740373527103,
+           -0.3963669670735703,
+           -0.48014185633940293,
+           -0.5633501727165269,
+           -0.6445304191942404,
+           -0.7222340477916379,
+           -0.7950680330720505,
+           -0.8617363329840453,
+           -0.9210791228058679,
+           -0.9721087413189357,
+           -1.0140413689896874,
+           -1.0463235639060493,
+           -1.0686529098637476,
+           -1.0809921791238846,
+           -1.0835765762669232,
+           -1.07691380514851,
+           -1.0617768838173758,
+           -1.039189817793738,
+           -1.0104064256604668,
+           -0.9768827878624028,
+           -0.940243955471932,
+           -0.9022457062592758,
+           -0.8647322668764565,
+           -0.8295910289658013,
+           -0.7987053707333261,
+           -0.7739067518045628,
+           -0.7569272765060967,
+           -0.749353918309066,
+           -0.7525855659888623,
+           -0.7677939907971472,
+           -0.7958897450316078,
+           -0.8374938879398731,
+           -0.8929162976598777,
+           -0.9621411712046909,
+           -1.0448201421604146,
+           -1.1402732619923772,
+           -1.2474979001509547,
+           -1.36518542521887,
+           -1.491745338896534,
+           -1.6253363513793282,
+           -1.7639037151702532,
+           -1.9052219788420928,
+           -2.0469421865781783,
+           -2.18664243686151,
+           -2.3218806272627233,
+           -2.4502481540777676,
+           -2.5694233070739836,
+           -2.677223101578721,
+           -2.771652322600673,
+           -2.85094861787404,
+           -2.913622567193599,
+           -2.9584917720011035,
+           -2.984708149086164,
+           -2.991777772097904,
+           -2.9795727804572945,
+           -2.9483350629475487,
+           -2.898671618183416,
+           -2.831541691582404,
+           -2.748235983582122,
+           -2.6503484119228986,
+           -2.539741087271325,
+           -2.4185033220092387,
+           -2.2889056327562254,
+           -2.153349814718238,
+           -2.01431625741757,
+           -1.8743097345562423,
+           -1.735804934184506,
+           -1.6011929982085926,
+           -1.4727303125452835,
+           -1.3524907316329038,
+           -1.2423223349879535,
+           -1.143809701197778,
+           -1.058242548948045,
+           -0.9865914387575666,
+           -0.9294910568792151,
+           -0.8872314185668818,
+           -0.8597571361342221,
+           -0.8466747026497541,
+           -0.8472675494932275,
+           -0.860518450051702,
+           -0.8851386670991602,
+           -0.9196030821344521,
+           -0.9621904050130994,
+           -1.0110274449783951,
+           -1.0641363324886974,
+           -1.1194835172267454,
+           -1.1750293328501569,
+           -1.2287769141622056,
+           -1.2788192774680405,
+           -1.3233834292111357,
+           -1.3608704501124524,
+           -1.389890609829106,
+           -1.4092926978471263,
+           -1.4181869065973682,
+           -1.4159607688306206,
+           -1.4022878289183263,
+           -1.3771289124914234,
+           -1.3407260460566415,
+           -1.2935892632500572,
+           -1.23647671258022,
+           -1.1703686484354547,
+           -1.0964360386309897,
+           -1.0160046540936494,
+           -0.9305156161543201,
+           -0.8414834616384905,
+           -0.7504528434450839,
+           -0.6589550132015276,
+           -0.5684652322157159,
+           -0.48036222738655987,
+           -0.3958907507894939,
+           -0.3161282168400843,
+           -0.24195628144863546,
+           -0.1740380962215533,
+           -0.11280182089800289,
+           -0.058430812653149054,
+           -0.010860735839243513,
+           0.030216345377902843,
+           0.06534101159757294,
+           0.09526896947610516,
+           0.1209474408843084,
+           0.1434860906447357,
+           0.16412326698009633,
+           0.18418845242846127,
+           0.20506192366311268,
+           0.2281326938223256,
+           0.25475585867577216,
+           0.2862104869886151,
+           0.3236591852723429,
+           0.36811042794860016,
+           0.4203846767443665,
+           0.48108521953649297,
+           0.5505745411894897,
+           0.6289569001095626,
+           0.7160676277334984,
+           0.8114694978953367,
+           0.9144563332319623,
+           1.0240638310111307,
+           1.139087405636277,
+           1.2581066642632956,
+           1.3795159600173053,
+           1.5015603085722786,
+           1.6223758123802459,
+           1.7400336162139003,
+           1.8525863210085551,
+           1.9581157127554385,
+           2.0547806212541544,
+           2.1408637110217756,
+           2.2148160239922423,
+           2.2752981404937898,
+           2.321216900299169,
+           2.351756727529674,
+           2.366404729417805,
+           2.364968886346621,
+           2.3475888156053535,
+           2.3147387699051656,
+           2.2672227195152534,
+           2.2061615592993644,
+           2.132972674224212,
+           2.0493422843353963,
+           1.957191168125156,
+           1.8586345272462677,
+           1.7559369015891553,
+           1.651463168201608,
+           1.5476267572840563,
+           1.4468362910339068,
+           1.3514418946004882,
+           1.2636824417198618,
+           1.1856349803384765,
+           1.1191675360691644,
+           1.0658964147572119,
+           1.0271490215878287,
+           1.0039330855316078,
+           0.9969130276021828,
+           1.0063940430270106,
+           1.0323142850884266,
+           1.0742453465039645
+          ],
+          [
+           1.1129048820895784,
+           1.1806493286716004,
+           1.2615937902118521,
+           1.3541095246819124,
+           1.4563058737857923,
+           1.5660718531018245,
+           1.681122646939098,
+           1.7990499197042171,
+           1.9173747665699061,
+           2.033602065665754,
+           2.145274963322554,
+           2.250028223811414,
+           2.3456392054937614,
+           2.43007528555649,
+           2.501536644036871,
+           2.558493432442219,
+           2.599716490101002,
+           2.6243009290404085,
+           2.6316820817834747,
+           2.6216434917250044,
+           2.594316818127249,
+           2.5501737225544896,
+           2.4900099959697366,
+           2.4149223710433625,
+           2.326278637951893,
+           2.225681839848897,
+           2.1149294624405766,
+           1.9959686473600984,
+           1.870848548544714,
+           1.741671012457459,
+           1.6105407953329618,
+           1.479516532963989,
+           1.3505636509250487,
+           1.2255103463356378,
+           1.1060076878044325,
+           0.9934947702535838,
+           0.8891697287147722,
+           0.7939672632860622,
+           0.7085431600837468,
+           0.6332661144342295,
+           0.568216977215647,
+           0.5131953578235956,
+           0.4677333323881793,
+           0.4311158282245186,
+           0.40240708947997167,
+           0.38048247867357066,
+           0.3640647380294917,
+           0.35176372641552067,
+           0.34211856496400095,
+           0.3336410690914316,
+           0.3248593179691451,
+           0.31436021513504925,
+           0.30082992574281014,
+           0.28309113605574415,
+           0.2601361676337856,
+           0.23115508998931006,
+           0.19555810844421037,
+           0.1529916551083258,
+           0.10334777646420823,
+           0.0467665867725873,
+           -0.016368262059139587,
+           -0.08544096098354169,
+           -0.15962146255461968,
+           -0.23788945486856475,
+           -0.3190637491939945,
+           -0.401836297753094,
+           -0.48480993614247797,
+           -0.5665388460720072,
+           -0.6455706609745567,
+           -0.7204890914772053,
+           -0.7899559309083777,
+           -0.8527513134069007,
+           -0.9078111385231175,
+           -0.9542606454558931,
+           -0.9914432155450671,
+           -1.018943600967536,
+           -1.0366049177941903,
+           -1.0445388991532893,
+           -1.043129075269708,
+           -1.033026727322305,
+           -1.0151396468588862,
+           -0.99061391728258,
+           -0.9608091140187821,
+           -0.9272674908409807,
+           -0.8916778771518621,
+           -0.8558351507882122,
+           -0.8215962695807871,
+           -0.7908339394094448,
+           -0.7653890644029238,
+           -0.7470231644532701,
+           -0.7373719552633095,
+           -0.7379012663700327,
+           -0.7498664233777828,
+           -0.7742761431167492,
+           -0.8118618864452646,
+           -0.8630534854317781,
+           -0.9279617127786415,
+           -1.0063682952048707,
+           -1.0977236931452028,
+           -1.201152780940953,
+           -1.3154683693151399,
+           -1.4391923200752714,
+           -1.570583816403226,
+           -1.707674175384628,
+           -1.848307426976549,
+           -1.9901857394458697,
+           -2.130918649021522,
+           -2.268074954150292,
+           -2.399236064776294,
+           -2.5220495562585663,
+           -2.6342816669637217,
+           -2.733867498544548,
+           -2.818957728014186,
+           -2.8879607197808936,
+           -2.9395790319418773,
+           -2.9728394417990835,
+           -2.9871157676057445,
+           -2.9821439333019057,
+           -2.958028906336133,
+           -2.9152433311490906,
+           -2.854617877836215,
+           -2.7773235221232317,
+           -2.6848461642985564,
+           -2.5789541764924246,
+           -2.4616596352554483,
+           -2.33517414569627,
+           -2.2018602908654628,
+           -2.064179842531457,
+           -1.9246399445086175,
+           -1.7857385254646974,
+           -1.6499102135680117,
+           -1.519474010092104,
+           -1.396583933586063,
+           -1.2831837715921346,
+           -1.180966975011201,
+           -1.0913426036094789,
+           -1.0154080829578593,
+           -0.9539293669557385,
+           -0.9073289201055804,
+           -0.8756817442994884,
+           -0.8587194807039055,
+           -0.8558424231434014,
+           -0.8661390899408231,
+           -0.8884128210951223,
+           -0.9212147013571322,
+           -0.9628819612372814,
+           -1.0115808808410869,
+           -1.0653531187366072,
+           -1.1221643122621687,
+           -1.1799537485620204,
+           -1.2366838882595779,
+           -1.2903885363721768,
+           -1.3392184974227537,
+           -1.3814836225639793,
+           -1.4156902540467917,
+           -1.4405731940290538,
+           -1.4551214674289326,
+           -1.458597308662831,
+           -1.450547975627055,
+           -1.4308101768187764,
+           -1.3995070844638295,
+           -1.357038093244763,
+           -1.3040616660366111,
+           -1.2414717804272217,
+           -1.1703686484354545,
+           -1.0920245228082344,
+           -1.0078455230894998,
+           -0.9193305103599059,
+           -0.8280281088035347,
+           -0.7354930133918665,
+           -0.643242735018315,
+           -0.5527159171322177,
+           -0.4652333118097736,
+           -0.38196242948375647,
+           -0.3038867771496245,
+           -0.2317804773308783,
+           -0.16618891755921072,
+           -0.1074159212423041,
+           -0.055517759600108144,
+           -0.010304145202135294,
+           0.02865383491552456,
+           0.06200906989988413,
+           0.09061745833825671,
+           0.1155111881736413,
+           0.13786697805999726,
+           0.1589701273615597,
+           0.180175332745546,
+           0.20286531556190615,
+           0.2284083637400307,
+           0.25811592322498667,
+           0.293201376199941,
+           0.33474111640359927,
+           0.3836389763925574,
+           0.4405949789779854,
+           0.5060792773287327,
+           0.5803120180579344,
+           0.6632497122442284,
+           0.7545785345161745,
+           0.8537147941771236,
+           0.9598126392872952,
+           1.0717788692501096,
+           1.1882945484375236,
+           1.3078429373502687,
+           1.428743093193089,
+           1.549188342725979,
+           1.6672887006205934,
+           1.7811161996206655,
+           1.888752017330962,
+           1.9883342305645157,
+           2.0781050033037345,
+           2.156456019197677,
+           2.2219710041055967,
+           2.273464247746804,
+           2.3100141245465613,
+           2.3309907301091775,
+           2.336076888599833,
+           2.3252819443087276,
+           2.2989479239547976,
+           2.2577478406237583,
+           2.202676101105877,
+           2.135031171110099,
+           2.056390842635082,
+           1.9685806299883046,
+           1.873635991053737,
+           1.7737592241980402,
+           1.671272024851241,
+           1.5685647959660156,
+           1.4680438904874322,
+           1.3720780195320663,
+           1.2829450857550908,
+           1.2027806966800325,
+           1.1335295776303098,
+           1.0769010391341296,
+           1.0343295608030456,
+           1.00694143492856,
+           0.9955282712583586,
+           1.0005280030276493,
+           1.0220138572401014,
+           1.0596915637119584,
+           1.1129048820895777
+          ],
+          [
+           1.1590696437878334,
+           1.2368238503467153,
+           1.3267571847473068,
+           1.4270693703086763,
+           1.5357231197526333,
+           1.6504888473255868,
+           1.7689936473980545,
+           1.8887733947615386,
+           2.0073267493965634,
+           2.1221698054177707,
+           2.2308901112350696,
+           2.3311988059812636,
+           2.4209796654725655,
+           2.498333928175609,
+           2.5616198759306523,
+           2.60948627294189,
+           2.6408989166111674,
+           2.6551597214618177,
+           2.6519179385482246,
+           2.631173302923442,
+           2.5932710962756467,
+           2.5388893059790894,
+           2.4690182507890555,
+           2.384933222630878,
+           2.2881608590266387,
+           2.180440107662404,
+           2.0636787698707186,
+           1.9399067103766474,
+           1.8112268941351022,
+           1.6797654557506898,
+           1.547622021812413,
+           1.4168214912269392,
+           1.2892684337736067,
+           1.1667051938408637,
+           1.050674686548264,
+           0.9424887497720891,
+           0.8432027711271751,
+           0.7535971473708768,
+           0.6741659590634708,
+           0.6051130600335999,
+           0.5463555938540171,
+           0.4975347628192714,
+           0.4580334934943433,
+           0.42700047129113267,
+           0.4033798589930693,
+           0.38594587459183083,
+           0.3733412856718491,
+           0.3641187837830025,
+           0.3567841350703863,
+           0.349839964502095,
+           0.3418290212609135,
+           0.331375792420535,
+           0.317225380352039,
+           0.2982786351212344,
+           0.2736226344725148,
+           0.24255572824179797,
+           0.2046065080184132,
+           0.15954622290899256,
+           0.10739433427028061,
+           0.048417081898722264,
+           -0.01688088316954688,
+           -0.08777156302063134,
+           -0.1633249632712449,
+           -0.24243615414386405,
+           -0.32385731735750933,
+           -0.40623392310024103,
+           -0.4881440723835502,
+           -0.5681399558061783,
+           -0.6447903223306671,
+           -0.7167228225798314,
+           -0.7826650911590637,
+           -0.8414834616384894,
+           -0.8922182653872095,
+           -0.9341147500246075,
+           -0.9666487627436887,
+           -0.9895464754421299,
+           -1.0027975791796198,
+           -1.0066615411973094,
+           -1.0016666944322574,
+           -0.9886021127007284,
+           -0.968502409900397,
+           -0.9426257840287294,
+           -0.912425801927976,
+           -0.8795175840167483,
+           -0.8456391957106593,
+           -0.8126091800158197,
+           -0.7822812706298897,
+           -0.7564974041021014,
+           -0.7370402011178676,
+           -0.7255861094032192,
+           -0.7236603934303975,
+           -0.7325951191292045,
+           -0.7534912159890832,
+           -0.7871856058141222,
+           -0.8342242691896998,
+           -0.8948419802860393,
+           -0.9689492813701548,
+           -1.0561270942076386,
+           -1.1556291806729644,
+           -1.2663924738887946,
+           -1.387055108780295,
+           -1.515981791804893,
+           -1.6512959684738842,
+           -1.7909180786059133,
+           -1.9326090372301243,
+           -2.0740179474727825,
+           -2.2127329439026093,
+           -2.3463339833860073,
+           -2.4724463475754432,
+           -2.5887935980877854,
+           -2.693248732856051,
+           -2.783882329941514,
+           -2.8590065324106506,
+           -2.917213823123428,
+           -2.9574096591704944,
+           -2.9788381793277843,
+           -2.981100360799808,
+           -2.96416417975241,
+           -2.928366519369036,
+           -2.8744067648055895,
+           -2.8033322217123295,
+           -2.7165156891386837,
+           -2.6156257039160353,
+           -2.50259014749248,
+           -2.3795540634451533,
+           -2.248832670697607,
+           -2.1128606705029904,
+           -1.9741390317796996,
+           -1.8351804973175943,
+           -1.6984550813229764,
+           -1.566336826086653,
+           -1.4410530523406933,
+           -1.324637274961934,
+           -1.218886864656568,
+           -1.125326419380369,
+           -1.0451776694046344,
+           -0.9793365805795693,
+           -0.9283581453995238,
+           -0.8924491652398431,
+           -0.8714691341864147,
+           -0.864939139945695,
+           -0.87205850517676,
+           -0.8917287079219799,
+           -0.9225839471310124,
+           -0.9630275627724817,
+           -1.0112733835007857,
+           -1.0653909615840786,
+           -1.1233535675151056,
+           -1.1830877574845864,
+           -1.2425232970653182,
+           -1.2996422246728347,
+           -1.3525258685296635,
+           -1.3993986901188453,
+           -1.4386679139034402,
+           -1.4689580151689108,
+           -1.4891392723491237,
+           -1.4983497437093458,
+           -1.4960101969007562,
+           -1.4818316994246674,
+           -1.4558157639427058,
+           -1.4182471299851933,
+           -1.369679448255129,
+           -1.3109143107945562,
+           -1.2429742353680218,
+           -1.1670703614263682,
+           -1.084565744255714,
+           -0.9969352402048934,
+           -0.9057230566140198,
+           -0.8124990932756345,
+           -0.7188152266799489,
+           -0.6261626833821784,
+           -0.5359316147746708,
+           -0.4493739232728135,
+           -0.3675703010613766,
+           -0.2914023293937568,
+           -0.22153035189400555,
+           -0.15837768281988368,
+           -0.10212154469126115,
+           -0.052690953309734535,
+           -0.009771586474453949,
+           0.027182509750311782,
+           0.05893070190843036,
+           0.08642153197492441,
+           0.11076311430567569,
+           0.13318895951529142,
+           0.15502013839227824,
+           0.17762479588973876,
+           0.20237609630654682,
+           0.23060972417534492,
+           0.2635820799728598,
+           0.30243029516302794,
+           0.34813514760766945,
+           0.4014878870936118,
+           0.46306188339109366,
+           0.5331898882954955,
+           0.61194756152986,
+           0.6991437517383394,
+           0.7943178520545373,
+           0.8967443691920077,
+           1.00544466021378,
+           1.1192056067442833,
+           1.2366048170399861,
+           1.3560417765658914,
+           1.4757742118333381,
+           1.593958794202245,
+           1.708695193660233,
+           1.8180724002579078,
+           1.920216165298197,
+           2.0133363772779767,
+           2.095773179986556,
+           2.1660406623681565,
+           2.2228670013023257,
+           2.2652300181643774,
+           2.292387216010144,
+           2.303899493941635,
+           2.2996478855123885,
+           2.279842835265543,
+           2.24502570757735,
+           2.1960624104900206,
+           2.1341292095279,
+           2.060690997863127,
+           1.977472474907558,
+           1.8864228608632543,
+           1.7896749356145376,
+           1.6894993325925047,
+           1.5882551383413601,
+           1.488337943457912,
+           1.3921265579674027,
+           1.301929642322287,
+           1.2199335130638114,
+           1.148152359510498,
+           1.088382055124056,
+           1.0421586656815964,
+           1.0107226479919857,
+           0.9949896002334617,
+           0.9955282712583591,
+           1.0125463651263047,
+           1.0458844928368143,
+           1.0950184302087225,
+           1.1590696437878325
+          ],
+          [
+           1.2123490568249693,
+           1.2994493405968581,
+           1.3975931342177443,
+           1.504823869629262,
+           1.6189748871335048,
+           1.7377168911961158,
+           1.858608998388233,
+           1.9791521857963228,
+           2.0968438929542605,
+           2.2092325051518444,
+           2.313970451436126,
+           2.4088646865827075,
+           2.491923391863233,
+           2.561397822938392,
+           2.6158183523453378,
+           2.654023895881078,
+           2.675184073212902,
+           2.67881362931082,
+           2.664778830464072,
+           2.6332957421221566,
+           2.5849204908500565,
+           2.520531804536489,
+           2.4413063089587643,
+           2.348687230405985,
+           2.2443473091243513,
+           2.1301468631196983,
+           2.0080880530856278,
+           1.8802664842604138,
+           1.7488213378430446,
+           1.6158852519102007,
+           1.4835351689948086,
+           1.353745334781533,
+           1.2283435706533037,
+           1.1089718537096152,
+           0.9970521236714636,
+           0.8937580997042474,
+           0.7999937350887389,
+           0.7163787677666478,
+           0.6432416443563551,
+           0.5806199088028239,
+           0.5282679590593518,
+           0.4856718907866345,
+           0.4520709705914001,
+           0.42648511719965604,
+           0.40774762123805147,
+           0.39454220663275325,
+           0.38544343217170923,
+           0.3789593530700463,
+           0.3735753113370848,
+           0.36779770157822955,
+           0.3601965660613479,
+           0.34944590918369994,
+           0.33436068591047097,
+           0.3139295096333806,
+           0.28734223986948937,
+           0.2540117463355807,
+           0.21358929971333876,
+           0.1659732069452854,
+           0.11131048590894813,
+           0.04999155630957363,
+           -0.017361894010168858,
+           -0.08991553004843816,
+           -0.16664697129783107,
+           -0.24637571121840468,
+           -0.327797552470038,
+           -0.40952263721462634,
+           -0.49011605676130626,
+           -0.5681399558061782,
+           -0.6421960052806065,
+           -0.7109671054386445,
+           -0.7732571976275304,
+           -0.8280281088035333,
+           -0.8744324261607294,
+           -0.9118414984165496,
+           -0.9398677828758699,
+           -0.9583809003141277,
+           -0.9675169194027101,
+           -0.9676805648439526,
+           -0.9595402242583976,
+           -0.9440158136258459,
+           -0.922259745070167,
+           -0.8956314193543922,
+           -0.8656658341020349,
+           -0.8340370532085178,
+           -0.8025174192260565,
+           -0.7729335052148079,
+           -0.747119892705129,
+           -0.7268719256699308,
+           -0.7138986250895564,
+           -0.7097769538405116,
+           -0.71590859702502,
+           -0.733480368993298,
+           -0.7634292764370344,
+           -0.806413158993248,
+           -0.8627876973878023,
+           -0.9325904274517324,
+           -1.0155322300570468,
+           -1.1109965862573183,
+           -1.2180466981166824,
+           -1.3354403835122646,
+           -1.4616524623371756,
+           -1.5949041667292703,
+           -1.7331989337793257,
+           -1.8743637799536361,
+           -2.0160953161613206,
+           -2.1560093445084165,
+           -2.2916928852653546,
+           -2.420757417768704,
+           -2.5408920835396605,
+           -2.6499155947695257,
+           -2.7458256166906203,
+           -2.8268444476640324,
+           -2.891459904782583,
+           -2.938460433410185,
+           -2.966963593704644,
+           -2.9764372325532538,
+           -2.966712821731936,
+           -2.9379906283003754,
+           -2.8908365767721267,
+           -2.8261708597470703,
+           -2.7452485496695913,
+           -2.6496326544116675,
+           -2.541160238852011,
+           -2.421902399163521,
+           -2.2941190221311496,
+           -2.1602093849617026,
+           -2.0226597487298625,
+           -1.8839891684658587,
+           -1.7466947832485975,
+           -1.613197859564727,
+           -1.4857918404159112,
+           -1.3665936017428255,
+           -1.257499037961091,
+           -1.1601439917535614,
+           -1.0758714123737325,
+           -1.005705474816488,
+           -0.950333223045836,
+           -0.9100941181943975,
+           -0.8849776817413333,
+           -0.8746292288154454,
+           -0.8783634927279779,
+           -0.8951857533579671,
+           -0.9238199036891432,
+           -0.9627427249704976,
+           -1.0102234956170997,
+           -1.0643679355952471,
+           -1.1231653896096498,
+           -1.184538081271722,
+           -1.246391228241195,
+           -1.3066627960432573,
+           -1.3633716860748988,
+           -1.4146632006871505,
+           -1.4588507038942577,
+           -1.4944524982485994,
+           -1.5202230641157801,
+           -1.5351779537903265,
+           -1.5386117959100154,
+           -1.530109041347126,
+           -1.5095472657640838,
+           -1.477093031707889,
+           -1.4331904997904372,
+           -1.378543159504074,
+           -1.3140892210483828,
+           -1.2409713659539527,
+           -1.1605016924087839,
+           -1.0741228076151184,
+           -0.9833661113699934,
+           -0.889808380132795,
+           -0.7950277975531156,
+           -0.7005605849316984,
+           -0.6078593632587712,
+           -0.5182543279360035,
+           -0.43291823937915735,
+           -0.3528361294413201,
+           -0.2787804976497731,
+           -0.2112926258374478,
+           -0.15067047858409094,
+           -0.09696348406622857,
+           -0.04997430984238924,
+           -0.00926756534402124,
+           0.025814817958944445,
+           0.056131952009396725,
+           0.08271668982182034,
+           0.10674339013386246,
+           0.12949161316433394,
+           0.15230671876632262,
+           0.1765584205569707,
+           0.20359840491330933,
+           0.2347181506228585,
+           0.2711080827598407,
+           0.3138191630473145,
+           0.36372795931969887,
+           0.4215061501905083,
+           0.4875953098059665,
+           0.5621876844003115,
+           0.6452135205922472,
+           0.7363353387755373,
+           0.834949367739966,
+           0.9401941732642586,
+           1.0509663284656539,
+           1.1659427918336078,
+           1.2836094847106418,
+           1.4022953979201769,
+           1.5202114113925325,
+           1.635492884722728,
+           1.7462449738313979,
+           1.8505895519453646,
+           1.946712563980768,
+           2.032910623421025,
+           2.1076356705329404,
+           2.1695365501148918,
+           2.2174964350407014,
+           2.2506651170548073,
+           2.2684853063124026,
+           2.270712223143948,
+           2.2574259260059035,
+           2.229035994641003,
+           2.186278372823646,
+           2.13020436615586,
+           2.062161982501894,
+           1.983769991063429,
+           1.896885256143585,
+           1.8035640688638586,
+           1.7060183503293842,
+           1.6065677292406801,
+           1.5075886024849563,
+           1.4114613661525808,
+           1.320517054710071,
+           1.236984646418266,
+           1.1629402829446802,
+           1.1002596106633167,
+           1.0505743812896038,
+           1.0152343519120763,
+           0.9952754014886639,
+           0.991394635432322,
+           1.0039330855316086,
+           1.0328664331164241,
+           1.0778039934384152,
+           1.1379960033025658,
+           1.2123490568249686
+          ],
+          [
+           1.272292353257483,
+           1.367995959436155,
+           1.473502334437012,
+           1.5867151843951048,
+           1.7053568283045109,
+           1.8270179959911264,
+           1.949210513488848,
+           2.069421647339546,
+           2.1851688417015303,
+           2.2940535750319038,
+           2.3938130866533402,
+           2.482368777121647,
+           2.5578701686380962,
+           2.618733420758409,
+           2.6636735296453695,
+           2.6917294928162123,
+           2.702281891967146,
+           2.6950625298234985,
+           2.6701559485657875,
+           2.6279928525251117,
+           2.56933565175107,
+           2.4952565309957566,
+           2.4071086260465444,
+           2.3064910518644046,
+           2.1952086707030634,
+           2.0752276098275635,
+           1.9486276347043932,
+           1.8175525523118508,
+           1.6841598589136089,
+           1.5505708563666039,
+           1.418822440654617,
+           1.290821716453585,
+           1.1683045134749521,
+           1.0527987761240367,
+           0.945593670320455,
+           0.847715103400503,
+           0.7599081885966606,
+           0.6826270088063355,
+           0.616031849658234,
+           0.5599938838845914,
+           0.5141071024067615,
+           0.4777071069910917,
+           0.4498962093211813,
+           0.42957412607890283,
+           0.4154734229698909,
+           0.40619874593738686,
+           0.4002687878933995,
+           0.3961598763450494,
+           0.39235003281478625,
+           0.38736234973820255,
+           0.3798065546300277,
+           0.3684176840599065,
+           0.3520908699792676,
+           0.32991134611170836,
+           0.3011789097548588,
+           0.26542622117367765,
+           0.22243048504648824,
+           0.17221823202401373,
+           0.1150630989652688,
+           0.05147668923916778,
+           -0.017807225011633978,
+           -0.09185472313575077,
+           -0.1695593809432474,
+           -0.24967479565666614,
+           -0.33085111835955167,
+           -0.4116746160866821,
+           -0.4907092053955774,
+           -0.5665388460720072,
+           -0.6378096589205601,
+           -0.7032706360251504,
+           -0.761811845350175,
+           -0.8124990932756331,
+           -0.8546040970917173,
+           -0.8876293324190847,
+           -0.9113268551498239,
+           -0.9257105504516951,
+           -0.9310614288098551,
+           -0.9279257667922607,
+           -0.9171060737482445,
+           -0.8996450503633614,
+           -0.8768028862377043,
+           -0.850028416849905,
+           -0.8209248210278933,
+           -0.7912106842871021,
+           -0.7626773774399405,
+           -0.7371438005474406,
+           -0.7164096169744533,
+           -0.7022081490661507,
+           -0.696160124522872,
+           -0.6997294503749324,
+           -0.7141821497524943,
+           -0.7405495263478831,
+           -0.7795965242332231,
+           -0.8317961288536636,
+           -0.8973105115119168,
+           -0.9759794579844681,
+           -1.067316446014402,
+           -1.1705125506224405,
+           -1.2844481650345343,
+           -1.4077123332514137,
+           -1.538629302619003,
+           -1.6752917258437607,
+           -1.8155997761715523,
+           -1.9573052910347841,
+           -2.0980599320724074,
+           -2.23546624623232,
+           -2.367130436276048,
+           -2.490715601366524,
+           -2.60399419077064,
+           -2.7048984265538407,
+           -2.7915674942388784,
+           -2.8623903727555913,
+           -2.916043274914397,
+           -2.9515207947039377,
+           -2.9681600049349632,
+           -2.9656569145716465,
+           -2.9440748754930794,
+           -2.9038447190347547,
+           -2.8457565988422697,
+           -2.7709437135573225,
+           -2.680858275856643,
+           -2.577240278680892,
+           -2.462079780636933,
+           -2.337573586368034,
+           -2.20607733042275,
+           -2.070054081588376,
+           -1.9320206661606623,
+           -1.794492961226847,
+           -1.6599314314828926,
+           -1.5306881748653567,
+           -1.4089567035815829,
+           -1.2967256189438445,
+           -1.1957372424489603,
+           -1.107452144169327,
+           -1.0330203657292136,
+           -0.9732599724726277,
+           -0.928643391885564,
+           -0.8992918072750815,
+           -0.8849776817413328,
+           -0.8851352923560591,
+           -0.8988789629516262,
+           -0.9250285007022105,
+           -0.9621411712046911,
+           -1.0085493931810015,
+           -1.0624032009427173,
+           -1.1217164135843878,
+           -1.1844153671134778,
+           -1.2483890113337668,
+           -1.311539148524247,
+           -1.37182959631103,
+           -1.427333092384399,
+           -1.4762748228971219,
+           -1.517071547810108,
+           -1.548365412773085,
+           -1.5690516753756096,
+           -1.578299730274929,
+           -1.5755669888505377,
+           -1.5606053503480217,
+           -1.5334601884126358,
+           -1.494461964800959,
+           -1.4442107662090564,
+           -1.3835542359835569,
+           -1.3135595356206804,
+           -1.2354801173665662,
+           -1.1507182152949473,
+           -1.0607840648559101,
+           -0.9672529375548437,
+           -0.8717211262807358,
+           -0.7757620367036421,
+           -0.6808835306766248,
+           -0.588487629018684,
+           -0.4998336144619343,
+           -0.4160054826608275,
+           -0.3378845723827812,
+           -0.2661280683256715,
+           -0.20115391495626736,
+           -0.14313251128721696,
+           -0.09198537889414318,
+           -0.04739081323110117,
+           -0.008796346057672787,
+           0.024562330832865107,
+           0.05363649889337783,
+           0.07953427652002001,
+           0.10348602434364107,
+           0.12680622023032223,
+           0.15085282524156476,
+           0.17698522876509742,
+           0.2065219000982794,
+           0.24069888393574135,
+           0.28063025819679616,
+           0.3272716248769782,
+           0.38138762929677594,
+           0.4435244021190797,
+           0.5139876943336318,
+           0.5928273311664812,
+           0.6798284501784103,
+           0.7745098157001024,
+           0.8761293205637914,
+           0.9836966013901643,
+           1.0959925101307157,
+           1.2115950067834096,
+           1.3289108706911419,
+           1.4462124748464649,
+           1.561678733054339,
+           1.6734392170872336,
+           1.7796203530023706,
+           1.8783925448655814,
+           1.9680170418560639,
+           2.046891362013843,
+           2.1135921129050272,
+           2.166914105645638,
+           2.2059047427415055,
+           2.2298927700721745,
+           2.2385106164251174,
+           2.2317096970444763,
+           2.2097682269634573,
+           2.1732912712971504,
+           2.1232029487291726,
+           2.060730896477448,
+           1.9873832953340413,
+           1.904918937235684,
+           1.8153109906800373,
+           1.7207052768644624,
+           1.623374007764826,
+           1.5256660530339012,
+           1.429954892677398,
+           1.3385854746810724,
+           1.2538212295166646,
+           1.177792495873298,
+           1.1124475839142351,
+           1.0595076444654514,
+           1.0204264261557607,
+           0.996355889703451,
+           0.9881185119884568,
+           0.9961869555540985,
+           1.020671605546134,
+           1.0613162900278759,
+           1.117502305626076,
+           1.1882606732775416,
+           1.2722923532574821
+          ],
+          [
+           1.3383923856729043,
+           1.4418837714515267,
+           1.5538425592219496,
+           1.672050477027044,
+           1.79413811295507,
+           1.9176366339548425,
+           2.0400316628844943,
+           2.1588180588991555,
+           2.271554326604475,
+           2.3759153904247907,
+           2.469742512063569,
+           2.5510891997311416,
+           2.6182620562243843,
+           2.669855636533449,
+           2.704780531376073,
+           2.7222840573352447,
+           2.7219631130653354,
+           2.703768949948803,
+           2.668003800001058,
+           2.6153094989778847,
+           2.546648433769686,
+           2.4632773256082388,
+           2.3667145299244607,
+           2.258701685770588,
+           2.1411606788793045,
+           2.016146989520097,
+           1.8858005767726647,
+           1.7522955027736207,
+           1.6177895227181898,
+           1.4843748584612995,
+           1.35403133575644,
+           1.2285829985274117,
+           1.1096592198302646,
+           0.9986612107391099,
+           0.8967346882958043,
+           0.8047493054442796,
+           0.72328527351318,
+           0.6526274256435893,
+           0.592766782144826,
+           0.543409490783093,
+           0.5039928311513886,
+           0.4737077971076592,
+           0.4515276091481235,
+           0.4362413635159624,
+           0.4264919004099712,
+           0.42081687290857034,
+           0.41769192361896446,
+           0.4155748293977798,
+           0.41294945686413104,
+           0.4083683832054762,
+           0.40049307759004094,
+           0.388130607248876,
+           0.37026592717820694,
+           0.34608893098774746,
+           0.3150155796402281,
+           0.27670258113384955,
+           0.2310552635892613,
+           0.1782284624071055,
+           0.11862042463470937,
+           0.05285991579089005,
+           -0.01821310847215527,
+           -0.09357273583155558,
+           -0.17203755190401343,
+           -0.25230549571144795,
+           -0.33299218047687074,
+           -0.4126716530013692,
+           -0.4899184999805146,
+           -0.5633501727165268,
+           -0.6316683937255783,
+           -0.6936985299532794,
+           -0.7484258671863445,
+           -0.7950277975531141,
+           -0.8329010348165179,
+           -0.8616830979126814,
+           -0.8812674487290301,
+           -0.8918118317981709,
+           -0.8937395373477677,
+           -0.8877334906230027,
+           -0.8747232550167862,
+           -0.855865219648475,
+           -0.8325164189981951,
+           -0.8062025985520506,
+           -0.7785812919216977,
+           -0.751400807712729,
+           -0.7264561351336458,
+           -0.7055428631102302,
+           -0.6904102662671022,
+           -0.6827147410013158,
+           -0.6839747751593718,
+           -0.6955286054323471,
+           -0.7184956581379724,
+           -0.7537427829229091,
+           -0.8018561771455305,
+           -0.8631197639844259,
+           -0.9375006329328022,
+           -1.0246419810521792,
+           -1.123863811342596,
+           -1.2341714553131962,
+           -1.3542717949693885,
+           -1.4825968697080179,
+           -1.617334370724575,
+           -1.7564643540224705,
+           -1.8978013472371191,
+           -2.039040889134149,
+           -2.1778094272233655,
+           -2.31171641130125,
+           -2.4384073611172585,
+           -2.5556166562897853,
+           -2.6612187968871774,
+           -2.7532769138038193,
+           -2.830087368518331,
+           -2.890219370605201,
+           -2.9325486563706766,
+           -2.956284410438261,
+           -2.9609887706810616,
+           -2.9465884317512345,
+           -2.9133780493522057,
+           -2.862015341799134,
+           -2.793507982591674,
+           -2.709192572883681,
+           -2.6107061711268744,
+           -2.499951034202963,
+           -2.3790533857316154,
+           -2.250317169021491,
+           -2.116173860871129,
+           -1.9791295152399058,
+           -1.8417102704485775,
+           -1.706407588473403,
+           -1.575624499237283,
+           -1.4516240964934808,
+           -1.336481475609582,
+           -1.232040218693852,
+           -1.1398744211631051,
+           -1.0612571187777609,
+           -0.9971358186917451,
+           -0.9481156660046394,
+           -0.9144505928851295,
+           -0.8960426050800548,
+           -0.8924491652398423,
+           -0.9028984387566548,
+           -0.9263119804551926,
+           -0.9613342640629611,
+           -1.0063682952048707,
+           -1.0596164066217097,
+           -1.1191252148306938,
+           -1.1828336233939372,
+           -1.2486226915699488,
+           -1.3143661499400399,
+           -1.377980337448377,
+           -1.4374723572500576,
+           -1.4909853011610898,
+           -1.5368394729561037,
+           -1.5735686471816364,
+           -1.5999505298241479,
+           -1.6150307368019428,
+           -1.618139772061045,
+           -1.6089026648762201,
+           -1.5872411113295577,
+           -1.5533681532239956,
+           -1.507775614188416,
+           -1.4512146928004224,
+           -1.3846702817190226,
+           -1.3093297358898526,
+           -1.2265469480537299,
+           -1.1378027027283153,
+           -1.0446623677776818,
+           -0.9487320435012148,
+           -0.8516143214100064,
+           -0.7548648077818566,
+           -0.6599505406976948,
+           -0.5682113742993979,
+           -0.4808253219239218,
+           -0.39877874269277047,
+           -0.322842126824132,
+           -0.2535520866988233,
+           -0.19119999733233806,
+           -0.13582755554356246,
+           -0.08722934619737911,
+           -0.0449623210262474,
+           -0.00836191534380026,
+           0.023435644979917285,
+           0.05146545522294059,
+           0.07690121672611507,
+           0.10101857572357169,
+           0.12515550035263218,
+           0.15067075841511846,
+           0.17890160952354522,
+           0.21112184776929557,
+           0.24850132440385372,
+           0.2920680443706961,
+           0.3426738667376317,
+           0.40096474873980287,
+           0.46735635850463764,
+           0.5420157454582952,
+           0.6248496033177646,
+           0.7154994923206158,
+           0.8133442091631049,
+           0.9175093094909827,
+           1.0268836033427065,
+           1.1401422633375,
+           1.2557760131973508,
+           1.3721257047569806,
+           1.4874214490012554,
+           1.5998253445133215,
+           1.7074767481530473,
+           1.8085389603628335,
+           1.9012461531174554,
+           1.9839493534008725,
+           2.0551603096815794,
+           2.1135921129050277,
+           2.1581955160272743,
+           2.18818999536689,
+           2.203088720671546,
+           2.202716745788436,
+           2.1872218946628657,
+           2.157077994084303,
+           2.1130802908182478,
+           2.056333081923725,
+           1.9882297784453675,
+           1.910425809555523,
+           1.8248049519757827,
+           1.7334398337155132,
+           1.6385475077394123,
+           1.5424411164559502,
+           1.4474787687613035,
+           1.3560108252333118,
+           1.2703268320619536,
+           1.1926033592485248,
+           1.1248539830657462,
+           1.0688826070544815,
+           1.026241240991412,
+           0.9981932550650645,
+           0.9856829993886063,
+           0.9893125300150659,
+           1.0093260154020112,
+           1.0456022158483456,
+           1.0976552371974813,
+           1.1646435637149977,
+           1.2453871782806387,
+           1.3383923856729032
+          ],
+          [
+           1.4100899178863928,
+           1.520487652318707,
+           1.6379340939165106,
+           1.7601077723347525,
+           1.8845676112430494,
+           2.0088061304046896,
+           2.130304058554247,
+           2.246585086381019,
+           2.355269487370938,
+           2.4541253633293882,
+           2.5411163303693862,
+           2.614444548539569,
+           2.6725881119254753,
+           2.7143319531849883,
+           2.738791573701677,
+           2.7454290839962465,
+           2.7340612244711253,
+           2.7048592294327745,
+           2.658340592920599,
+           2.5953529883907662,
+           2.5170507810361102,
+           2.4248647469222697,
+           2.3204657729242433,
+           2.2057234517866235,
+           2.0826606041209,
+           1.9534048509793858,
+           1.820138424630114,
+           1.6850474398139694,
+           1.550271852333921,
+           1.417857306290597,
+           1.2897100163660256,
+           1.1675557487200097,
+           1.0529038554407728,
+           0.9470171858555189,
+           0.8508885466943805,
+           0.7652242159285317,
+           0.6904348362719609,
+           0.6266338283269324,
+           0.5736432748148578,
+           0.5310070409684913,
+           0.4980107166048127,
+           0.473707797107659,
+           0.45695136769147393,
+           0.44643042166515756,
+           0.4407098322532312,
+           0.4382729115773497,
+           0.437565431736107,
+           0.4370399529400449,
+           0.4351993030363159,
+           0.43063808143157883,
+           0.4220811175963874,
+           0.40841789850023025,
+           0.38873208829907896,
+           0.3623253945730061,
+           0.3287351850372027,
+           0.2877454231082224,
+           0.2393906658124293,
+           0.18395304882585942,
+           0.12195236633239818,
+           0.05412953324219572,
+           -0.018576110433992352,
+           -0.09505503297103653,
+           -0.17406051773241582,
+           -0.25424555446988123,
+           -0.33420262446764115,
+           -0.41250531257522494,
+           -0.48775063024172777,
+           -0.5586009133592155,
+           -0.6238241675781646,
+           -0.6823317715718271,
+           -0.7332125145685295,
+           -0.7757620367036405,
+           -0.8095068570627276,
+           -0.8342223117820688,
+           -0.849943879793845,
+           -0.8569715428527087,
+           -0.8558670051065658,
+           -0.8474437811797828,
+           -0.8327503458889349,
+           -0.8130467186596338,
+           -0.7897750269043404,
+           -0.7645247507150373,
+           -0.7389934922003518,
+           -0.7149442330553925,
+           -0.6941601404073833,
+           -0.6783980511334824,
+           -0.6693418068549007,
+           -0.6685566245285219,
+           -0.6774456705686043,
+           -0.6972099600618744,
+           -0.7288126279486281,
+           -0.7729485177977348,
+           -0.8300199084377106,
+           -0.9001190522582215,
+           -0.9830180350370002,
+           -1.07816628968967,
+           -1.1846959097429781,
+           -1.3014347171899179,
+           -1.426926848416443,
+           -1.5594604358180153,
+           -1.6971017861632696,
+           -1.8377352940999745,
+           -1.9791081844881762,
+           -2.11887905410603,
+           -2.254669084798159,
+           -2.384114728815134,
+           -2.5049206247516533,
+           -2.6149114902457766,
+           -2.712081755827098,
+           -2.7946417526258127,
+           -2.8610593439621326,
+           -2.9100959952982883,
+           -2.9408364061555314,
+           -2.9527109782684797,
+           -2.9455105628297473,
+           -2.9193931120852668,
+           -2.874882052348939,
+           -2.8128563920529364,
+           -2.7345327749565875,
+           -2.6414398803189547,
+           -2.5353857540304885,
+           -2.418418822959947,
+           -2.2927834950068298,
+           -2.1608713758986227,
+           -2.0251692375104766,
+           -1.8882049488914354,
+           -1.7524926284072533,
+           -1.6204782923181058,
+           -1.4944872613078874,
+           -1.376674542329028,
+           -1.2689793297239664,
+           -1.1730846687494407,
+           -1.090383198849819,
+           -1.0219497463971627,
+           -0.9685213707672061,
+           -0.9304852876231707,
+           -0.9078749035463909,
+           -0.9003740013301684,
+           -0.9073289201055792,
+           -0.9277683837607678,
+           -0.9604304494970143,
+           -1.0037958802536409,
+           -1.0561270942076388,
+           -1.1155117152508265,
+           -1.179909643376533,
+           -1.2472024857730537,
+           -1.3152441399600152,
+           -1.3819113006429364,
+           -1.4451526724903063,
+           -1.5030357113991075,
+           -1.5537897859157679,
+           -1.5958447465187808,
+           -1.6278640109829297,
+           -1.6487714159690041,
+           -1.65777124472935,
+           -1.6543610143673395,
+           -1.63833678908332,
+           -1.6097909737010117,
+           -1.5691027298074025,
+           -1.5169213403719475,
+           -1.4541430231762587,
+           -1.3818818544585332,
+           -1.3014356078756288,
+           -1.2142474366701357,
+           -1.1218644257895376,
+           -1.0258941132328665,
+           -0.9279601243536004,
+           -0.8296580781882463,
+           -0.7325129108005415,
+           -0.6379387175624162,
+           -0.5472021453909479,
+           -0.4613902690781882,
+           -0.3813837654903051,
+           -0.3078360586615828,
+           -0.24115895126448836,
+           -0.18151508761295743,
+           -0.1288174145842489,
+           -0.08273562416468036,
+           -0.04270937937078623,
+           -0.007967948682825158,
+           0.02244429267224808,
+           0.04963718900994539,
+           0.07483978731743511,
+           0.09936192000551328,
+           0.12455341936838828,
+           0.15176205865472156,
+           0.18229134938392547,
+           0.21735933028756102,
+           0.2580594598501909,
+           0.305324672434852,
+           0.35989557869354,
+           0.42229368635954395,
+           0.4928003902120772,
+           0.5714423331846045,
+           0.6579835779415185,
+           0.7519248538610103,
+           0.8525099626230844,
+           0.9587392410905573,
+           1.069389797543025,
+           1.1830420611958858,
+           1.2981120197690361,
+           1.4128883698570254,
+           1.5255736738159251,
+           1.6343285081749988,
+           1.7373175050051934,
+           1.8327561314086973,
+           1.9189570248337995,
+           1.994374704050072,
+           2.0576475073852234,
+           2.1076356705329418,
+           2.1434545444731796,
+           2.1645020676956594,
+           2.170479743239822,
+           2.1614065267448566,
+           2.1376252029382248,
+           2.099801010581202,
+           2.048912465344927,
+           1.9862345217394375,
+           1.9133144043253,
+           1.8319406203196857,
+           1.744105835851016,
+           1.6519644522850536,
+           1.5577858533923206,
+           1.4639044052857813,
+           1.3726673762279828,
+           1.2863820004233468,
+           1.2072629372991701,
+           1.137381374789522,
+           1.078616991768913,
+           1.0326139317830294,
+           1.000741849067807,
+           0.9840629707055669,
+           0.9833059784491441,
+           0.9988473536356867,
+           1.0307006525842544,
+           1.0785139921938571,
+           1.1415758306886248,
+           1.2188289313300855,
+           1.3088922022294924,
+           1.410089917886392
+          ],
+          [
+           1.4867783563319192,
+           1.6031425776368975,
+           1.7250654860853252,
+           1.8501420657535466,
+           1.9758802486931182,
+           2.099755150146034,
+           2.219263955182014,
+           2.3319801810176077,
+           2.435606055859293,
+           2.5280218019845067,
+           2.6073306867709025,
+           2.6718988086273883,
+           2.7203887127273174,
+           2.751786080948392,
+           2.7654189078139346,
+           2.7609687554004214,
+           2.738473870687564,
+           2.6983241440176213,
+           2.641248082428963,
+           2.568292161873749,
+           2.4807931030855586,
+           2.3803437827354226,
+           2.268753640457915,
+           2.1480045697449395,
+           2.0202033835318916,
+           1.887532021088625,
+           1.7521967097963291,
+           1.6163773124756309,
+           1.4821780778043478,
+           1.351580968445396,
+           1.2264026699511454,
+           1.1082562851798947,
+           0.9985185963713074,
+           0.8983036332929669,
+           0.8084431246197481,
+           0.7294742349958697,
+           0.6616348064370569,
+           0.6048661344519005,
+           0.5588231211938267,
+           0.5228914647783901,
+           0.4962113701630362,
+           0.4777071069910913,
+           0.4661215974996772,
+           0.460055096483945,
+           0.4580069283625895,
+           0.45841917595763937,
+           0.45972117337329116,
+           0.46037364231359795,
+           0.4589113275645539,
+           0.45398303269236434,
+           0.44438803006191385,
+           0.42910791814987886,
+           0.4073331212627677,
+           0.3784833690384694,
+           0.34222165187593195,
+           0.29846131965674993,
+           0.2473661704413716,
+           0.18934355868876798,
+           0.12503073432385198,
+           0.055274800054938275,
+           -0.01889315973628784,
+           -0.09628907364964645,
+           -0.17561116322214382,
+           -0.25547855815698317,
+           -0.3344722094279686,
+           -0.41117700212352454,
+           -0.48422393733817926,
+           -0.5523312488833005,
+           -0.6143433461810793,
+           -0.6692665288002175,
+           -0.7163004993439974,
+           -0.754864807781855,
+           -0.7846194891601292,
+           -0.8054793047040595,
+           -0.8176211599115369,
+           -0.8214844482251976,
+           -0.8177642508465262,
+           -0.8073975076357921,
+           -0.7915424561688704,
+           -0.7715518112907964,
+           -0.7489403214739547,
+           -0.7253474867910078,
+           -0.7024963525631822,
+           -0.6821493994334816,
+           -0.666062631990641,
+           -0.6559390220096882,
+           -0.6533824874380624,
+           -0.65985358371975,
+           -0.6766280499298611,
+           -0.7047592892425268,
+           -0.7450457729513814,
+           -0.7980042417646251,
+           -0.863849440198798,
+           -0.9424809629538856,
+           -1.0334776200058502,
+           -1.1360995440258417,
+           -1.249298074136242,
+           -1.3717332586201556,
+           -1.5017986307467495,
+           -1.6376527310309554,
+           -1.777256680505308,
+           -1.9184169571476972,
+           -2.058832395289816,
+           -2.1961443189475838,
+           -2.327988637314314,
+           -2.452048676247186,
+           -2.566107494871289,
+           -2.6680984421080103,
+           -2.756152743942019,
+           -2.8286429777655835,
+           -2.8842213836430495,
+           -2.921852081595675,
+           -2.940836406155531,
+           -2.9408307310477486,
+           -2.9218563340234107,
+           -2.8843010402841394,
+           -2.828912578037563,
+           -2.7567837767556935,
+           -2.6693299328801894,
+           -2.568258854300683,
+           -2.4555342693789974,
+           -2.333333444352705,
+           -2.2039999907756784,
+           -2.0699929588839328,
+           -1.9338334006344853,
+           -1.7980496455181088,
+           -1.665122561659802,
+           -1.5374320734898794,
+           -1.4172061754426084,
+           -1.3064736195152906,
+           -1.2070213646239982,
+           -1.1203577597408305,
+           -1.0476822936449055,
+           -0.9898625851846614,
+           -0.9474191131332244,
+           -0.9205179983071664,
+           -0.9089719571766877,
+           -0.9122493504531667,
+           -0.9294910568792133,
+           -0.959534716379885,
+           -1.0009457123902146,
+           -1.0520541047871768,
+           -1.1109965862573181,
+           -1.1757624194644338,
+           -1.2442422228094694,
+           -1.3142784110187677,
+           -1.3837160646837483,
+           -1.4504530009029806,
+           -1.5124878452997519,
+           -1.5679649631143227,
+           -1.6152151922880553,
+           -1.6527914322706219,
+           -1.6794982758672976,
+           -1.6944150244191651,
+           -1.696911595120465,
+           -1.686657009093602,
+           -1.6636203354619523,
+           -1.6280641554227913,
+           -1.5805307965249837,
+           -1.5218217663695526,
+           -1.4529709823365018,
+           -1.37521254555849,
+           -1.2899439394731425,
+           -1.198685642647681,
+           -1.103038229513669,
+           -1.0046380891476456,
+           -0.9051129199473904,
+           -0.8060381563684249,
+           -0.7088954529225073,
+           -0.6150342912549766,
+           -0.525637689876684,
+           -0.44169288526627015,
+           -0.36396772043188097,
+           -0.2929933260221121,
+           -0.22905351355639886,
+           -0.17218112451682305,
+           -0.12216139737391701,
+           -0.07854223171787594,
+           -0.04065104917059059,
+           -0.007617779210971279,
+           0.021596661198972425,
+           0.048167168213854056,
+           0.07336742891958499,
+           0.09853007324648591,
+           0.12500507115516207,
+           0.1541174930665281,
+           0.1871257696131446,
+           0.22518157572847813,
+           0.26929242412377113,
+           0.32028798531714864,
+           0.3787910572686425,
+           0.4451939896922819,
+           0.5196412292195977,
+           0.6020184952647122,
+           0.6919489266191314,
+           0.7887963597582975,
+           0.8916757160830642,
+           0.9994702914844261,
+           1.1108555623539136,
+           1.2243289520036114,
+           1.3382448447256072,
+           1.450853995399214,
+           1.5603463642044637,
+           1.6648963116619337,
+           1.7627090213376067,
+           1.85206697791452,
+           1.931375318025633,
+           1.999204890619645,
+           2.0543319123067323,
+           2.0957731799865584,
+           2.1228159062730665,
+           2.1350413703148217,
+           2.1323417244818055,
+           2.114929462440575,
+           2.083339232325303,
+           2.03842186565272,
+           1.981330683716964,
+           1.9135003337154282,
+           1.8366185920818956,
+           1.7525917478424173,
+           1.6635043399005658,
+           1.5715741649835906,
+           1.4791035939640287,
+           1.3884283303690859,
+           1.301864813667312,
+           1.221657509612798,
+           1.1499273394791523,
+           1.0886224791164125,
+           1.0394727078516468,
+           1.0039484075044378,
+           0.9832252050889179,
+           0.9781551216769758,
+           0.9892449375578268,
+           1.0166423139279313,
+           1.0601300279981325,
+           1.1191284860620365,
+           1.192706482406076,
+           1.2795999757421574,
+           1.3782384638851446,
+           1.4867783563319181
+          ],
+          [
+           1.56780888211832,
+           1.6891492493361266,
+           1.8144995647232407,
+           1.9413916264201205,
+           2.0673034790730083,
+           2.1897142233169635,
+           2.306158711787513,
+           2.4142808616665743,
+           2.511884348347417,
+           2.596979509080604,
+           2.6678253778506233,
+           2.7229658909559062,
+           2.7612594439171088,
+           2.781901140954595,
+           2.7844372544172495,
+           2.768771598895908,
+           2.7351637187309166,
+           2.6842189834831154,
+           2.6168708788993578,
+           2.534355966264329,
+           2.4381821562802792,
+           2.330091100550684,
+           2.212015640566148,
+           2.0860333675057006,
+           1.9543174334606768,
+           1.8190858137964871,
+           1.6825502499227811,
+           1.5468661011094744,
+           1.4140843032747745,
+           1.2861065727342522,
+           1.1646449053093706,
+           1.05118630820193,
+           0.9469635665232059,
+           0.8529326917492668,
+           0.769757529549431,
+           0.6978018236620348,
+           0.6371288452930333,
+           0.5875085085586703,
+           0.5484317064875623,
+           0.5191314236596979,
+           0.4986100151111697,
+           0.48567189078663386,
+           0.4789607142789794,
+           0.477000117058122,
+           0.4782368474779356,
+           0.4810852195364935,
+           0.48397170093067876,
+           0.4853784839477238,
+           0.4838849159915228,
+           0.47820572813645545,
+           0.467225088413169,
+           0.45002561926924506,
+           0.4259116529133371,
+           0.3944261506085927,
+           0.3553608785442642,
+           0.30875960944563313,
+           0.2549143010979704,
+           0.19435438584315742,
+           0.1278294842228856,
+           0.05628602675364279,
+           -0.01916157399847785,
+           -0.09726441732483458,
+           -0.17667636921067928,
+           -0.2559940750036203,
+           -0.3337986545471004,
+           -0.4086979597537566,
+           -0.4793682586876798,
+           -0.5445942234873035,
+           -0.6033061415734622,
+           -0.6546133395043879,
+           -0.6978329048143216,
+           -0.7325129108005399,
+           -0.7584494895028415,
+           -0.7756972555248925,
+           -0.7845727539185079,
+           -0.7856507847942801,
+           -0.7797536411103817,
+           -0.7679334795863582,
+           -0.751448223250407,
+           -0.7317315632349628,
+           -0.7103577827928942,
+           -0.6890022641606732,
+           -0.6693986553266631,
+           -0.6532937659792696,
+           -0.6424013275188922,
+           -0.6383557892880616,
+           -0.6426673310805281,
+           -0.6566792502384129,
+           -0.6815288306837234,
+           -0.7181127222333256,
+           -0.7670577533939268,
+           -0.8286979720609763,
+           -0.903058559282056,
+           -0.9898470951379492,
+           -1.088452476917293,
+           -1.1979516025139136,
+           -1.317123740978808,
+           -1.4444723221329567,
+           -1.5782536928019255,
+           -1.7165122131469188,
+           -1.857120907074053,
+           -1.9978267397873861,
+           -2.1362994767430403,
+           -2.270182984555319,
+           -2.3971477681800684,
+           -2.514943501661672,
+           -2.62145030286758,
+           -2.7147275261963633,
+           -2.7930589007301374,
+           -2.854992923472719,
+           -2.899377526224438,
+           -2.9253881676875957,
+           -2.9325486563706766,
+           -2.9207441810434283,
+           -2.890226209741415,
+           -2.841609111154633,
+           -2.775858548972179,
+           -2.6942718956059672,
+           -2.5984511019110674,
+           -2.4902686394237734,
+           -2.371827296865762,
+           -2.2454147591858273,
+           -2.113454021658951,
+           -1.978450790508317,
+           -1.842939092753064,
+           -1.7094263597822037,
+           -1.5803392605063136,
+           -1.457971540578854,
+           -1.3444350745979556,
+           -1.2416152596255523,
+           -1.1511317727307218,
+           -1.0743055851774337,
+           -1.012132974528779,
+           -0.9652671070437208,
+           -0.9340075804382629,
+           -0.9182981258344896,
+           -0.9177324722058849,
+           -0.9315681816218125,
+           -0.9587480738551587,
+           -0.9979286790656189,
+           -1.0475149916773514,
+           -1.1057006512469194,
+           -1.170512550622441,
+           -1.2398587710411302,
+           -1.3115786703966763,
+           -1.383493906451298,
+           -1.4534591622740856,
+           -1.5194113569204994,
+           -1.579416169845233,
+           -1.631710781545371,
+           -1.6747418335447284,
+           -1.707197735481497,
+           -1.7280345925890463,
+           -1.7364951895931746,
+           -1.7321206428997684,
+           -1.7147545175103442,
+           -1.6845393937688182,
+           -1.6419060571088218,
+           -1.587555666761049,
+           -1.5224354323598235,
+           -1.4477084862770102,
+           -1.3647187803900842,
+           -1.2749519553971183,
+           -1.179993225805588,
+           -1.081483392040154,
+           -0.9810741311042402,
+           -0.8803837279703389,
+           -0.7809543911772743,
+           -0.684212248528424,
+           -0.5914310435863084,
+           -0.5037004528082841,
+           -0.4218998192683841,
+           -0.3466779551395427,
+           -0.278439505140263,
+           -0.2173381910553383,
+           -0.16327707759539467,
+           -0.11591581683004837,
+           -0.07468464685459755,
+           -0.03880474483055917,
+           -0.007314369520424,
+           0.02089992190591183,
+           0.04706782987579352,
+           0.07249659835086032,
+           0.09853007324648587,
+           0.12650663453446265,
+           0.157717133609568,
+           0.1933639688284632,
+           0.23452240435601035,
+           0.2821051812638658,
+           0.33683138661962536,
+           0.3992004381638922,
+           0.4694719118093162,
+           0.5476517898835772,
+           0.6334855435315495,
+           0.7264582871312952,
+           0.82580206038804,
+           0.9305101095460668,
+           1.0393578575552462,
+           1.150930078641599,
+           1.263653629981912,
+           1.3758349462076214,
+           1.485701375011817,
+           1.591445327471362,
+           1.6912701375245371,
+           1.7834364734323227,
+           1.866308121380604,
+           1.9383959683132108,
+           1.9983990475455287,
+           2.0452415758807945,
+           2.078105003303738,
+           2.096454213645199,
+           2.1000571540553357,
+           2.0889973292938393,
+           2.063678769870717,
+           2.024823266700167,
+           1.973459854639333,
+           1.9109067183880366,
+           1.8387458819949765,
+           1.7587912229919833,
+           1.6730505194906498,
+           1.583682389252766,
+           1.4929491100187149,
+           1.4031664169734288,
+           1.3166514534529727,
+           1.2356701027970798,
+           1.1623849512820883,
+           1.0988051237041123,
+           1.046739194550243,
+           1.0077523096688783,
+           0.983128557525402,
+           0.9738395077891766,
+           0.9805196910554055,
+           1.0034496304331848,
+           1.0425468574754169,
+           1.0973651558107003,
+           1.1671020804564909,
+           1.2506146038994213,
+           1.3464425464162761,
+           1.4528392624944473,
+           1.567808882118319
+          ],
+          [
+           1.6524959403307111,
+           1.7777800120553555,
+           1.9054796770555986,
+           2.0330844417603386,
+           2.158063820484223,
+           2.277922255451507,
+           2.390253159409535,
+           2.492790827328146,
+           2.5834590159645385,
+           2.6604150712119288,
+           2.7220885911478545,
+           2.767213744900506,
+           2.7948545206147672,
+           2.804422346168726,
+           2.7956857096934593,
+           2.7687715988959085,
+           2.7241587739845965,
+           2.6626630838700365,
+           2.5854152245044544,
+           2.493831517133667,
+           2.3895784485119185,
+           2.274531860798935,
+           2.1507318024022646,
+           2.0203341494821396,
+           1.8855601788585903,
+           1.7486453149889245,
+           1.6117882855753822,
+           1.4771019020178393,
+           1.346566632890506,
+           1.2219880621723835,
+           1.1049592210752774,
+           0.996828655615808,
+           0.8986749447779012,
+           0.8112882199204636,
+           0.7351590591231549,
+           0.6704749448588408,
+           0.6171242843602421,
+           0.5747078040167137,
+           0.5425569467666489,
+           0.5197587292617167,
+           0.505186357827553,
+           0.49753476281927056,
+           0.49536009329166136,
+           0.4971221208459217,
+           0.5012284353294109,
+           0.5060792773287331,
+           0.5101118439716456,
+           0.511842925567378,
+           0.5099087804584526,
+           0.5031012327995005,
+           0.4903990808026144,
+           0.47099402864149126,
+           0.44431050046614173,
+           0.4100188561371017,
+           0.3680417012390176,
+           0.3185531642832289,
+           0.2619711971813028,
+           0.19894313642387648,
+           0.13032493733890452,
+           0.0571546579028529,
+           -0.019379082314445423,
+           -0.09797281214776073,
+           -0.177247123573348,
+           -0.255787743503996,
+           -0.33218765840411557,
+           -0.40508915928614897,
+           -0.4732246755288323,
+           -0.5354552959071186,
+           -0.5908059335006857,
+           -0.6384961762964252,
+           -0.6779659751859051,
+           -0.7088954529225058,
+           -0.7312182681300249,
+           -0.7451281338571544,
+           -0.751078266284033,
+           -0.7497737215674993,
+           -0.7421567628564972,
+           -0.7293855805664557,
+           -0.7128068624868826,
+           -0.6939228718095528,
+           -0.6743538365971983,
+           -0.6557965798538872,
+           -0.6399804219862945,
+           -0.6286214644091016,
+           -0.6233764123348305,
+           -0.6257971150739309,
+           -0.6372869928537461,
+           -0.6590604803821652,
+           -0.6921065500073852,
+           -0.737157282948671,
+           -0.794662337961186,
+           -0.8647700258394088,
+           -0.9473155387977116,
+           -1.0418167098987159,
+           -1.147477493605451,
+           -1.2631991687507007,
+           -1.3875990744377238,
+           -1.5190365023362014,
+           -1.655645190160674,
+           -1.7953716952628826,
+           -1.9360187783737588,
+           -2.0752927993245724,
+           -2.2108540222845,
+           -2.340368650315317,
+           -2.4615613598534334,
+           -2.572267086375352,
+           -2.6704808235419715,
+           -2.7544042393595456,
+           -2.8224879834048,
+           -2.87346865728305,
+           -2.906399543881828,
+           -2.920674336685615,
+           -2.9160432749143967,
+           -2.8926212695578215,
+           -2.8508877951479805,
+           -2.7916785177355026,
+           -2.7161688262459003,
+           -2.6258496274052336,
+           -2.5224959490322587,
+           -2.4081290681970593,
+           -2.284973035356082,
+           -2.1554065993194853,
+           -2.0219116475278938,
+           -1.8870193589395376,
+           -1.7532553208410326,
+           -1.6230848847835408,
+           -1.498860030039428,
+           -1.3827689656497568,
+           -1.2767896352163743,
+           -1.182648193733223,
+           -1.101783405281883,
+           -1.0353177672949023,
+           -0.9840360048274116,
+           -0.948371400848994,
+           -0.9284002403177095,
+           -0.9238444513307625,
+           -0.9340823307126572,
+           -0.9581670487825484,
+           -0.9948524434308477,
+           -1.042625441520182,
+           -1.0997442901828158,
+           -1.16428164557448,
+           -1.2341714553131962,
+           -1.3072584858426468,
+           -1.3813492893214756,
+           -1.4542633776589167,
+           -1.5238833745663012,
+           -1.588202949799572,
+           -1.6453714022156816,
+           -1.6937338482230142,
+           -1.7318660873646443,
+           -1.7586033542071096,
+           -1.7730623219457762,
+           -1.774655894252168,
+           -1.7631005035907719,
+           -1.7384158219820927,
+           -1.7009169793046603,
+           -1.6511995700073072,
+           -1.5901179069346119,
+           -1.5187571464507952,
+           -1.4384000580957539,
+           -1.350489340955123,
+           -1.2565864946167893,
+           -1.158328332448756,
+           -1.0573822770476942,
+           -0.9554016008505104,
+           -0.8539817685766589,
+           -0.7546190026188448,
+           -0.6586721286967427,
+           -0.5673286687122798,
+           -0.4815760331380602,
+           -0.40217852937933674,
+           -0.32966074885137153,
+           -0.26429772792637496,
+           -0.20611210069090952,
+           -0.15487827911475485,
+           -0.11013351339020157,
+           -0.07119550648836559,
+           -0.037186086920870894,
+           -0.0070602865944598015,
+           0.020359969522763716,
+           0.04634847489556004,
+           0.07223466323192781,
+           0.0993619200055132,
+           0.1290454056006359,
+           0.16253052569599108,
+           0.2009531690417025,
+           0.24530278853319565,
+           0.29638932954723085,
+           0.35481491168128876,
+           0.42095104878156525,
+           0.4949220505036518,
+           0.5765950901858753,
+           0.6655772525177771,
+           0.761219694672413,
+           0.8626288707776396,
+           0.9686845864706319,
+           1.078064472444729,
+           1.1892742978643622,
+           1.300683390560472,
+           1.4105642949468258,
+           1.5171356840946935,
+           1.6186074523149405,
+           1.7132268512617197,
+           1.7993244976653409,
+           1.8753590752890363,
+           1.9399595778182201,
+           1.9919639926247783,
+           2.030453406466997,
+           2.054780621254158,
+           2.06459249843801,
+           2.059845401217295,
+           2.040813270872776,
+           2.0080880530856264,
+           1.9625723776107828,
+           1.905464585549858,
+           1.8382363879720351,
+           1.7626036230664126,
+           1.6804907518153502,
+           1.5939898900490554,
+           1.5053153137299415,
+           1.4167544909336718,
+           1.330616785299826,
+           1.2491810393955594,
+           1.174643280824696,
+           1.1090657980958347,
+           1.0543288070525727,
+           1.012085872630845,
+           0.9837241661428774,
+           0.9703305271978333,
+           0.9726641644148164,
+           0.9911366735139344,
+           1.0257998789457956,
+           1.0763418201177914,
+           1.1420910099915755,
+           1.2220288970603443,
+           1.3148102662571035,
+           1.41879112495793,
+           1.532063441543919,
+           1.65249594033071
+          ],
+          [
+           1.740123040135285,
+           1.868285009436102,
+           1.9972360901630963,
+           2.1244447490649496,
+           2.247393399368901,
+           2.363632966683216,
+           2.4708358209680257,
+           2.5668458481666607,
+           2.6497245046347113,
+           2.7177917948179315,
+           2.769661235323717,
+           2.804268013594434,
+           2.8208897132694846,
+           2.819159157003711,
+           2.799069106620941,
+           2.7609687554004223,
+           2.705552143260952,
+           2.6338388178432672,
+           2.5471472483142796,
+           2.4470616696589307,
+           2.335393189141625,
+           2.214136119789318,
+           2.085420614968384,
+           1.951462760787971,
+           1.8145133372125788,
+           1.6768064831605392,
+           1.5405094949926652,
+           1.4076749518937015,
+           1.2801962966950868,
+           1.1597679083731007,
+           1.047850585145567,
+           0.9456432177595255,
+           0.8540612747262084,
+           0.7737225488825675,
+           0.7049404320567133,
+           0.6477247963465166,
+           0.6017903712763425,
+           0.5665723205788407,
+           0.5412485451566842,
+           0.5247680742951947,
+           0.5158847594769763,
+           0.5131953578235945,
+           0.5151809883704718,
+           0.5202508665899888,
+           0.5267871726799797,
+           0.5331898882954961,
+           0.5379204450575154,
+           0.5395430660211618,
+           0.5367627472960202,
+           0.5284589194467059,
+           0.5137139447682844,
+           0.49183574403501495,
+           0.46237400134531154,
+           0.42512956427944565,
+           0.38015683446205684,
+           0.3277591262639768,
+           0.26847715415722195,
+           0.20307098752457894,
+           0.13249598100934173,
+           0.05787334448998623,
+           -0.019543844465413844,
+           -0.09840826477767065,
+           -0.17731859746997242,
+           -0.25486130931596324,
+           -0.32965285075536793,
+           -0.4003811328056583,
+           -0.4658451653551636,
+           -0.5249917856054861,
+           -0.5769484793794543,
+           -0.6210513976701678,
+           -0.6568677936732923,
+           -0.6842122485284224,
+           -0.7031562134967615,
+           -0.7140305683028397,
+           -0.7174210755299283,
+           -0.7141567947343098,
+           -0.7052917026876822,
+           -0.6920799432449163,
+           -0.6759452972757715,
+           -0.6584456156526538,
+           -0.6412330925636542,
+           -0.6260113689856286,
+           -0.6144905441080382,
+           -0.6083412335586056,
+           -0.6091488458297853,
+           -0.6183692514340126,
+           -0.6372869928537459,
+           -0.6669771278664717,
+           -0.7082717156088952,
+           -0.7617318457871496,
+           -0.8276259793765026,
+           -0.9059152172021676,
+           -0.9962459446725503,
+           -1.0979501207787912,
+           -1.2100532917200182,
+           -1.3312902188009796,
+           -1.4601278213014748,
+           -1.5947949525246936,
+           -1.7333183557352878,
+           -1.8735639904758223,
+           -2.0132827827115354,
+           -2.150159737841781,
+           -2.281865266722598,
+           -2.406107513735871,
+           -2.52068444420137,
+           -2.62353444692233,
+           -2.7127842365029937,
+           -2.7867928986502797,
+           -2.844191008609767,
+           -2.883913866128178,
+           -2.905228027168338,
+           -2.9077504697330423,
+           -2.8914599047825824,
+           -2.85669992914786,
+           -2.8041739110314023,
+           -2.7349316954409244,
+           -2.6503484119228986,
+           -2.5520958555039,
+           -2.4421070892072154,
+           -2.3225350785616987,
+           -2.1957063112043302,
+           -2.0640704745153045,
+           -1.930147358291051,
+           -1.7964722154618609,
+           -1.665540850191137,
+           -1.5397557084705715,
+           -1.421374221418667,
+           -1.3124605965160423,
+           -1.2148421683249424,
+           -1.130071309898653,
+           -1.0593937717964899,
+           -1.0037241606747118,
+           -0.9636290976185008,
+           -0.9393184119202824,
+           -0.9306445334063344,
+           -0.9371100503725464,
+           -0.9578832054956422,
+           -0.9918209134830697,
+           -1.037498706302256,
+           -1.0932468489076936,
+           -1.1571917244072254,
+           -1.227301466049645,
+           -1.301434717189918,
+           -1.377391331783044,
+           -1.4529637885761986,
+           -1.525988082891656,
+           -1.5943928808570835,
+           -1.6562457715358918,
+           -1.7097955313001614,
+           -1.7535094199374013,
+           -1.7861046567114658,
+           -1.8065733736517327,
+           -1.8142005089718498,
+           -1.8085742815668144,
+           -1.789589073553482,
+           -1.7574407371661542,
+           -1.7126145302849027,
+           -1.6558660667937637,
+           -1.5881958393343762,
+           -1.5108180286057018,
+           -1.425124451307258,
+           -1.3326446147501216,
+           -1.235002937240823,
+           -1.1338742573784597,
+           -1.0309387908750045,
+           -0.9278376996093552,
+           -0.8261304142898436,
+           -0.7272547999972402,
+           -0.6324911743982755,
+           -0.5429310836307742,
+           -0.45945161346783614,
+           -0.382695866635575,
+           -0.313060074832939,
+           -0.2506876402149047,
+           -0.19547022026745942,
+           -0.14705578671054936,
+           -0.1048634079579998,
+           -0.06810433032553237,
+           -0.03580877001989276,
+           -0.006857680089606175,
+           0.019981372291020764,
+           0.04601518934179825,
+           0.07258383965242066,
+           0.10101857572357155,
+           0.13259990520165502,
+           0.1685169458506616,
+           0.2098291621849061,
+           0.25743152133171543,
+           0.31202401861573814,
+           0.3740864117424792,
+           0.4438588691135724,
+           0.5213290860856155,
+           0.6062262567089418,
+           0.6980221118437078,
+           0.795939052004971,
+           0.8989652194468785,
+           1.00587617350783,
+           1.1152626606759668,
+           1.2255638105766216,
+           1.3351049452086385,
+           1.4421390649376773,
+           1.544890974168815,
+           1.6416029348680214,
+           1.7305806891397384,
+           1.8102386741622372,
+           1.8791432644741468,
+           1.936052917696707,
+           1.979954169333919,
+           2.0100925186703034,
+           2.025997368664362,
+           2.0275003251797434,
+           2.014746321425736,
+           1.9881972081563937,
+           1.9486276347043907,
+           1.8971132357476947,
+           1.8350113291290033,
+           1.7639345163479785,
+           1.6857177548950373,
+           1.602379635969518,
+           1.516078748218053,
+           1.4290661342525217,
+           1.3436349486843797,
+           1.2620685016562614,
+           1.1865879184304822,
+           1.1193006622789998,
+           1.0621511542171844,
+           1.016874679289169,
+           0.9849556961424646,
+           0.9675915662407333,
+           0.9656625936494779,
+           0.9797091189026325,
+           1.009916244576724,
+           1.0561065898796405,
+           1.1177412811787053,
+           1.193929189575709,
+           1.28344423015046,
+           1.3847503451267076,
+           1.4960336096545517,
+           1.6152407286294514,
+           1.7401230401352838
+          ],
+          [
+           1.8299488166159799,
+           1.9598985282465469,
+           2.088992503270594,
+           2.214699598793147,
+           2.334536447067581,
+           2.446121205610532,
+           2.5472249306821313,
+           2.635819385195547,
+           2.7101201783383098,
+           2.76862424685364,
+           2.8101408242816164,
+           2.8338152011572917,
+           2.839144752370343,
+           2.8259868933714034,
+           2.794558820130685,
+           2.745429083996248,
+           2.6795012470755015,
+           2.597990051736523,
+           2.5023907147238584,
+           2.394442117913353,
+           2.2760848099827817,
+           2.1494148528201595,
+           2.016634640463846,
+           1.8800018845362068,
+           1.7417779969520302,
+           1.604177107336041,
+           1.4693169289969812,
+           1.3391726341511638,
+           1.2155348177656506,
+           1.099972521992486,
+           0.9938021624221568,
+           0.8980630465990217,
+           0.8135000082046814,
+           0.7405535012112191,
+           0.6793573116091726,
+           0.6297438546760356,
+           0.5912568378846983,
+           0.5631708881162839,
+           0.544517571327347,
+           0.5341170774343938,
+           0.5306147067404036,
+           0.532521180079369,
+           0.5382557057739868,
+           0.5461906746354518,
+           0.5546968210461956,
+           0.562187684400312,
+           0.5671622308395661,
+           0.5682445495863794,
+           0.5642196197932214,
+           0.5540642505745519,
+           0.5369724260109328,
+           0.512374435106603,
+           0.4799493301595812,
+           0.4396304316070668,
+           0.3916037787041546,
+           0.33629960878377463,
+           0.2743771286857325,
+           0.20670301565707894,
+           0.13432424722233693,
+           0.05843600610130625,
+           -0.019654466489030187,
+           -0.09856709108827076,
+           -0.17689018619904484,
+           -0.2532226104919689,
+           -0.32621567722057926,
+           -0.39461371234671594,
+           -0.45729216216200946,
+           -0.5132922186143503,
+           -0.561851019542203,
+           -0.6024265943466466,
+           -0.6347168604391163,
+           -0.6586721286967411,
+           -0.6745007432834733,
+           -0.6826676583383466,
+           -0.6838859367200263,
+           -0.679101339612564,
+           -0.6694703556945946,
+           -0.6563321901944736,
+           -0.6411753931388081,
+           -0.6255999484049944,
+           -0.6112757671740934,
+           -0.5998986279178045,
+           -0.5931446775930453,
+           -0.5926246533576855,
+           -0.5998389996544364,
+           -0.6161350414558469,
+           -0.6426673310805275,
+           -0.6803622142712914,
+           -0.7298875628724445,
+           -0.7916284988270309,
+           -0.8656697903172856,
+           -0.9517854392119114,
+           -1.0494358035316103,
+           -1.157772413721471,
+           -1.2756504516930736,
+           -1.4016486715697734,
+           -1.5340963555519616,
+           -1.6711067219287492,
+           -1.8106160393974977,
+           -1.95042755658582,
+           -2.088259231648325,
+           -2.2217941471614786,
+           -2.3487324227964335,
+           -2.466843394285269,
+           -2.574016813176794,
+           -2.6683118382336346,
+           -2.7480026357344842,
+           -2.8116194813549304,
+           -2.8579843589310743,
+           -2.88624017881476,
+           -2.895872887645482,
+           -2.8867259085924135,
+           -2.8590065324106506,
+           -2.813284070608004,
+           -2.750479777989581,
+           -2.6718487480657407,
+           -2.5789541764924246,
+           -2.4736345701862144,
+           -2.3579646485664325,
+           -2.234210834401728,
+           -2.1047823612904843,
+           -1.9721791297191957,
+           -1.838937521359182,
+           -1.7075754298821575,
+           -1.5805377849163258,
+           -1.4601438333817862,
+           -1.3485373996476908,
+           -1.2476412737954814,
+           -1.1591167775251103,
+           -1.0843294323503947,
+           -1.024321507755357,
+           -0.979792061525139,
+           -0.9510849045712649,
+           -0.9381847326404475,
+           -0.9407214719690534,
+           -0.9579826899891951,
+           -0.9889337303841567,
+           -1.0322450487994628,
+           -1.086326055787838,
+           -1.1493646212152067,
+           -1.2193712630617801,
+           -1.294226936474401,
+           -1.3717332586201556,
+           -1.4496639532501912,
+           -1.5258162770912198,
+           -1.5980611986874478,
+           -1.6643911388172976,
+           -1.7229641490678407,
+           -1.772143499814367,
+           -1.8105317683030744,
+           -1.8369986587452873,
+           -1.8507019457441838,
+           -1.851101105989784,
+           -1.8379633866321872,
+           -1.8113622474998006,
+           -1.7716683036711993,
+           -1.719533080135051,
+           -1.655866066793764,
+           -1.5818057255219866,
+           -1.4986852473540042,
+           -1.4079939835522342,
+           -1.3113355762336047,
+           -1.2103838899312915,
+           -1.1068378931353888,
+           -1.00237665738092,
+           -0.8986156304580825,
+           -0.7970653001700412,
+           -0.6990932968490821,
+           -0.6058908883534045,
+           -0.5184447029516144,
+           -0.4375143763994363,
+           -0.3636166631799164,
+           -0.29701638229833177,
+           -0.23772438950652608,
+           -0.18550258490887622,
+           -0.13987578220823604,
+           -0.10015008801014941,
+           -0.06543727111520867,
+           -0.03468444685185008,
+           -0.006708264148574673,
+           0.019767333314580717,
+           0.04607079296110639,
+           0.07354117342181735,
+           0.10348602434364088,
+           0.13714006066246603,
+           0.17562574625018493,
+           0.21991685333964983,
+           0.27080598818378016,
+           0.32887697192509074,
+           0.3944828411922259,
+           0.46773008863399806,
+           0.5484696030848639,
+           0.6362945963757358,
+           0.7305456233179777,
+           0.830322617655247,
+           0.9345036844436296,
+           1.0417702130019413,
+           1.1506377087441508,
+           1.2594915910796394,
+           1.3666270719981573,
+           1.470292119338307,
+           1.5687324229207427,
+           1.6602372229426305,
+           1.743184829837444,
+           1.8160866640511262,
+           1.877628672983065,
+           1.9267090400610827,
+           1.9624711862124984,
+           1.9843311748148813,
+           1.9919987648758295,
+           1.9854915104405644,
+           1.965141473303261,
+           1.9315942968443118,
+           1.8858005767726627,
+           1.8289996550716643,
+           1.7626961518065507,
+           1.6886297309717866,
+           1.6087387667168322,
+           1.5251187308402256,
+           1.439976257512727,
+           1.3555799533820325,
+           1.2742091076852378,
+           1.1981015155408121,
+           1.1294016566848157,
+           1.0701104707557072,
+           1.0220379387624696,
+           0.9867596192829652,
+           0.9655781986547376,
+           0.9594909990577026,
+           0.9691642497104197,
+           0.9949147677497803,
+           1.0366995205747305,
+           1.0941133547462751,
+           1.1663949824841136,
+           1.2524411201067736,
+           1.3508284782181406,
+           1.4598431157927503,
+           1.577516494132985,
+           1.7016674062641493,
+           1.8299488166159787
+          ],
+          [
+           1.9212133030571417,
+           2.0518454766619634,
+           2.1799726156029515,
+           2.303085394075444,
+           2.418755693964054,
+           2.524689084405775,
+           2.6187742021172036,
+           2.699127891080658,
+           2.7641350623464462,
+           2.812482361772888,
+           2.8431848823817454,
+           2.8556053250120423,
+           2.8494651920260496,
+           2.824847789532546,
+           2.782193009287326,
+           2.7222840573352465,
+           2.6462264877981387,
+           2.5554200823328186,
+           2.4515242842599294,
+           2.3364180471153206,
+           2.212155086760419,
+           2.0809156310967247,
+           1.944955839358968,
+           1.8065561120763518,
+           1.667969531968665,
+           1.5313716649000728,
+           1.398812908911657,
+           1.2721745093959809,
+           1.1531292614735933,
+           1.0431077990570405,
+           0.9432712270184771,
+           0.8544906919125872,
+           0.7773343118822742,
+           0.712061702058883,
+           0.658626142556013,
+           0.6166842467503996,
+           0.5856128026442816,
+           0.5645322842868423,
+           0.5523363678379823,
+           0.5477266418822845,
+           0.5492515775986091,
+           0.5553487243852759,
+           0.564389022951544,
+           0.5747220824683488,
+           0.5847212521736206,
+           0.5928273311664817,
+           0.5975898025780225,
+           0.5977045487245001,
+           0.592047100384353,
+           0.5797005934951526,
+           0.5599777472546641,
+           0.5324363352359262,
+           0.4968877916742551,
+           0.4533987742206562,
+           0.40228568763722145,
+           0.3441023554958924,
+           0.2796212043125541,
+           0.209808492219864,
+           0.13579426801842825,
+           0.05883788236497387,
+           -0.019710012472917628,
+           -0.09844794733710362,
+           -0.17596551431377563,
+           -0.25088551116558383,
+           -0.32190521784319287,
+           -0.3878356928961919,
+           -0.447638028226662,
+           -0.5004555785645705,
+           -0.5456412853308336,
+           -0.582779340589798,
+           -0.6117005824019497,
+           -0.632491174398274,
+           -0.645494295734913,
+           -0.6513047483738537,
+           -0.650756572303482,
+           -0.6449039412153659,
+           -0.6349957866821403,
+           -0.6224447635819771,
+           -0.6087913191985524,
+           -0.5956637592743239,
+           -0.5847353129571559,
+           -0.5776792822559988,
+           -0.5761234181311479,
+           -0.581604693186675,
+           -0.5955256393201809,
+           -0.619113387566841,
+           -0.6533824874380615,
+           -0.6991024957088185,
+           -0.7567712119489004,
+           -0.8265943028552082,
+           -0.908471902927955,
+           -1.0019926090339262,
+           -1.1064351051002583,
+           -1.2207774650585643,
+           -1.3437139918681913,
+           -1.4736792627090944,
+           -1.6088788699182812,
+           -1.7473261784477403,
+           -1.8868842677659206,
+           -2.0253120930424244,
+           -2.1603137904988916,
+           -2.2895899677658846,
+           -2.410889764107889,
+           -2.5220624389307633,
+           -2.6211072508050006,
+           -2.706220423316771,
+           -2.7758380576424377,
+           -2.8286739433496604,
+           -2.8637513363834404,
+           -2.8804279136848003,
+           -2.8784132740268715,
+           -2.857778530564701,
+           -2.8189577280141855,
+           -2.7627410117474,
+           -2.6902596726849226,
+           -2.6029633858901047,
+           -2.50259014749248,
+           -2.3911295894301,
+           -2.2707805102326186,
+           -2.143903598789918,
+           -2.012970443374371,
+           -1.880510007289443,
+           -1.749053813225652,
+           -1.6210811092326862,
+           -1.4989652894131493,
+           -1.3849228120052197,
+           -1.2809657971977193,
+           -1.1888593982893676,
+           -1.1100849248390714,
+           -1.0458095580709417,
+           -0.9968633403826531,
+           -0.9637239462343875,
+           -0.9465095552351956,
+           -0.9449799544491921,
+           -0.9585458005457592,
+           -0.9862857782045751,
+           -1.0269712038871215,
+           -1.0790974482548206,
+           -1.1409213904163176,
+           -1.210503976695418,
+           -1.2857568391129008,
+           -1.3644918370848333,
+           -1.444472322132957,
+           -1.5234648911627422,
+           -1.5992903898475745,
+           -1.6698729538732031,
+           -1.7332859315100264,
+           -1.7877936147310884,
+           -1.83188781573189,
+           -1.8643184584499524,
+           -1.8841175071791032,
+           -1.890615722796154,
+           -1.8834519172510966,
+           -1.862574564320711,
+           -1.828235814525667,
+           -1.780978149846548,
+           -1.7216140947926932,
+           -1.651199570007308,
+           -1.5710016287518545,
+           -1.482461451515238,
+           -1.3871535863395144,
+           -1.2867425095138716,
+           -1.1829376409686791,
+           -1.0774479795951346,
+           -0.9719375251393132,
+           -0.8679826253248486,
+           -0.7670323302348192,
+           -0.6703727522342292,
+           -0.5790963210188359,
+           -0.49407669253555947,
+           -0.41594992088517224,
+           -0.3451023377070339,
+           -0.2816654081462462,
+           -0.2255176507681699,
+           -0.17629352532069995,
+           -0.13339901169489352,
+           -0.09603343036621084,
+           -0.06321689338517188,
+           -0.033822629699506494,
+           -0.006613302897837906,
+           0.019719663460038,
+           0.046514815321704206,
+           0.07509856506323027,
+           0.10674339013386219,
+           0.1426274602134266,
+           0.18379678322641224,
+           0.23113089607403234,
+           0.2853130350478059,
+           0.346805605864243,
+           0.41583163700789433,
+           0.4923627460238494,
+           0.5761139804463594,
+           0.6665457174265973,
+           0.7628726233164577,
+           0.8640794910990991,
+           0.9689435942726815,
+           1.0760630251366075,
+           1.1838903277352326,
+           1.2907705949978643,
+           1.3949830794724636,
+           1.4947852705690827,
+           1.5884583209056564,
+           1.6743526620295455,
+           1.750932636621095,
+           1.8168189906913028,
+           1.8708281149451662,
+           1.9120069983442982,
+           1.9396629572088637,
+           1.9533873275268883,
+           1.9530724534611548,
+           1.938921467802371,
+           1.9114505363114365,
+           1.8714834231793414,
+           1.820138424630112,
+           1.758807907296957,
+           1.6891308727056396,
+           1.6129591444035465,
+           1.5323179356051748,
+           1.449361698645825,
+           1.3663262794412139,
+           1.2854784974615148,
+           1.20906434196665,
+           1.1392570166014058,
+           1.0781060758100074,
+           1.0274888775339217,
+           0.989065527685874,
+           0.964238414068834,
+           0.9541173225648278,
+           0.9594909990577022,
+           0.9808058697858648,
+           1.018152464286378,
+           1.07125990287344,
+           1.1394986191166712,
+           1.221891291704922,
+           1.3171317641755271,
+           1.4236115400330134,
+           1.539453259435531,
+           1.6625503963191164,
+           1.7906122656467056,
+           1.9212133030571406
+          ],
+          [
+           2.013144360605827,
+           2.1433479418922885,
+           2.269406694240867,
+           2.388854351088724,
+           2.499338607119933,
+           2.5986718832619675,
+           2.6848782960604867,
+           2.75623574721478,
+           2.8113121662983995,
+           2.8489950800774326,
+           2.8685138419399707,
+           2.8694540308507315,
+           2.8517637166470653,
+           2.815751482821067,
+           2.7620762944461927,
+           2.691729492816214,
+           2.6060093849493513,
+           2.5064890708364405,
+           2.394978309941539,
+           2.273480367159976,
+           2.144144893861528,
+           2.0092179890310464,
+           1.8709906467461248,
+           1.7317468278780077,
+           1.5937123952749537,
+           1.4590061228404814,
+           1.329593930650047,
+           1.2072474120805787,
+           1.0935076070639818,
+           0.9896548408543787,
+           0.8966852935135523,
+           0.8152947955375849,
+           0.7458701639150389,
+           0.6884882049390746,
+           0.6429223199683853,
+           0.6086564627621988,
+           0.5849060166471812,
+           0.570644991062874,
+           0.5646387841320645,
+           0.5654816245652394,
+           0.5716376956908521,
+           0.5814848593869058,
+           0.5933598402143602,
+           0.6056037014678045,
+           0.6166064457887067,
+           0.6248496033177653,
+           0.6289457292473444,
+           0.6276738185120132,
+           0.6200097559915356,
+           0.6051510531468224,
+           0.5825352730717299,
+           0.5518517116697769,
+           0.5130460788401779,
+           0.4663181057114568,
+           0.41211218747806466,
+           0.3511013516323625,
+           0.28416501378491277,
+           0.2123611434759689,
+           0.13689360635648878,
+           0.05907557322594742,
+           -0.019710012472917628,
+           -0.09805184153421728,
+           -0.174552404956733,
+           -0.24786978425465864,
+           -0.31675794106004646,
+           -0.38010441956572655,
+           -0.4369644418907598,
+           -0.48659046923961374,
+           -0.5284564184317626,
+           -0.5622758610568888,
+           -0.5880136876889714,
+           -0.6058908883534029,
+           -0.6163822785229086,
+           -0.6202071828195388,
+           -0.618313271694468,
+           -0.6118539250076552,
+           -0.6021596661040853,
+           -0.5907043663708038,
+           -0.5790670593744995,
+           -0.5688903219669679,
+           -0.5618362741652092,
+           -0.559541317718879,
+           -0.5635707732796011,
+           -0.5753745868952094,
+           -0.5962452578072642,
+           -0.6272790916111787,
+           -0.6693418068548996,
+           -0.7230394209180182,
+           -0.7886952150020864,
+           -0.8663334313473958,
+           -0.9556701919676475,
+           -1.0561119512925141,
+           -1.1667616094947448,
+           -1.2864322235456482,
+           -1.4136680638963872,
+           -1.5467725808236907,
+           -1.6838426704894212,
+           -1.8228084709898191,
+           -1.9614777771167928,
+           -2.0975840427815733,
+           -2.228836845090297,
+           -2.352973616334721,
+           -2.467811411422951,
+           -2.5712974695677495,
+           -2.661557350674989,
+           -2.7369394783881056,
+           -2.79605500196184,
+           -2.8378119961687607,
+           -2.8614431497280317,
+           -2.866526245131378,
+           -2.852996902544286,
+           -2.821153243566856,
+           -2.7716523226006724,
+           -2.705498369715005,
+           -2.624023084458213,
+           -2.5288584102490046,
+           -2.421902399163521,
+           -2.305278942706685,
+           -2.181292291467351,
+           -2.052377411804034,
+           -1.9210473278269289,
+           -1.7898386694825519,
+           -1.6612566907341124,
+           -1.5377210346052679,
+           -1.4215135039055402,
+           -1.3147290482196188,
+           -1.219231100401979,
+           -1.1366122912635852,
+           -1.068161441927716,
+           -1.01483758262714,
+           -0.9772515781993132,
+           -0.9556557583287224,
+           -0.9499417591360456,
+           -0.9596465866951418,
+           -0.9839667172510922,
+           -1.0217798580850908,
+           -1.0716738117665483,
+           -1.1319817193487989,
+           -1.2008228089520678,
+           -1.2761476487350911,
+           -1.3557868005473794,
+           -1.4375016950265478,
+           -1.5190365023362016,
+           -1.5981697561906516,
+           -1.6727645026039297,
+           -1.74081578850486,
+           -1.8004943778138403,
+           -1.8501856819104565,
+           -1.8885230151054573,
+           -1.9144144306406377,
+           -1.9270625552336418,
+           -1.925977016192594,
+           -1.9109792402536085,
+           -1.8821995929324566,
+           -1.840067016618667,
+           -1.7852915101808033,
+           -1.7188399679321558,
+           -1.6419060571088235,
+           -1.5558749565715648,
+           -1.4622839017435507,
+           -1.362779578859906,
+           -1.2590734830638612,
+           -1.1528963980387785,
+           -1.0459531687253347,
+           -0.9398789229828126,
+           -0.8361978532946742,
+           -0.7362855969999037,
+           -0.6413361549563181,
+           -0.5523341665589002,
+           -0.47003321677737986,
+           -0.39494069197672216,
+           -0.327309529788256,
+           -0.26713702856440413,
+           -0.214170698533175,
+           -0.1679209543141936,
+           -0.12768027157983672,
+           -0.09254826381266062,
+           -0.06146198253575046,
+           -0.03323060992594756,
+           -0.006573599752547563,
+           0.0198387660359329,
+           0.04734349979349861,
+           0.0772428383386454,
+           0.11076311430567536,
+           0.14901567797125903,
+           0.1929609261090883,
+           0.24337641451210834,
+           0.3008299257428097,
+           0.36565823607727055,
+           0.4379521787164436,
+           0.5175484378552037,
+           0.6040283342284004,
+           0.6967236816886475,
+           0.7947296107910264,
+           0.8969240739120327,
+           1.0019935717126436,
+           1.1084644772034946,
+           1.2147391854455656,
+           1.3191361878042378,
+           1.419933062977085,
+           1.5154112954873151,
+           1.603901778100533,
+           1.683829829126782,
+           1.7537585595393799,
+           1.8124294582680096,
+           1.8587991261587382,
+           1.892071178472027,
+           1.911722450261227,
+           1.9175227757566309,
+           1.9095477686292637,
+           1.8881842008990677,
+           1.854127760072639,
+           1.8083731523531676,
+           1.752196709796327,
+           1.6871318463718752,
+           1.6149378873761322,
+           1.537562964046956,
+           1.45710181637209,
+           1.3757494781591293,
+           1.295751926144994,
+           1.2193548565293264,
+           1.1487518057249382,
+           1.0860328559265096,
+           1.0331351596317728,
+           0.9917964805787901,
+           0.9635128825052915,
+           0.9495016032338487,
+           0.9506700320705619,
+           0.9675915662407324,
+           1.000488960502082,
+           1.0492256070845485,
+           1.113304994999854,
+           1.1918784031171885,
+           1.2837606849527556,
+           1.3874538096602975,
+           1.5011776379574135,
+           1.6229072382158307,
+           1.7504158909221714,
+           1.8813227930187357,
+           2.013144360605826
+          ],
+          [
+           2.104964210915896,
+           2.233631771676336,
+           2.356538086409682,
+           2.4712808256457595,
+           2.5756034186257333,
+           2.6674436742231875,
+           2.7449779419647773,
+           2.806659795293419,
+           2.8512523505468526,
+           2.8778534876482254,
+           2.885913408496945,
+           2.8752441523553527,
+           2.8460208796750015,
+           2.79877493210787,
+           2.734378872117758,
+           2.6540238958810796,
+           2.559190193417685,
+           2.4516109957461834,
+           2.333231196298766,
+           2.206161559299367,
+           2.0726296282929977,
+           1.934928521118553,
+           1.7953648416244516,
+           1.6562069523370793,
+           1.5196348358490634,
+           1.3876927263888719,
+           1.26224561809019,
+           1.1449406548280923,
+           1.0371742807122273,
+           0.9400658835986346,
+           0.8544384999852092,
+           0.7808069724936925,
+           0.7193737652324677,
+           0.670032452304556,
+           0.6323787052914416,
+           0.6057284213965877,
+           0.5891424596227568,
+           0.5814572921790224,
+           0.5813207362008386,
+           0.5872318102955394,
+           0.5975836643282384,
+           0.6107084615554086,
+           0.6249230513389479,
+           0.6385742591629912,
+           0.6500826387252553,
+           0.6579835779415192,
+           0.6609647255191904,
+           0.6578988053652676,
+           0.6478710098950867,
+           0.6302003071244435,
+           0.6044541565863208,
+           0.5704563015379668,
+           0.5282874852362175,
+           0.47827912268899225,
+           0.42100014159148896,
+           0.35723738251878834,
+           0.2879701144185751,
+           0.214339372840679,
+           0.13761296133672224,
+           0.05914706771198671,
+           -0.019654466489030194,
+           -0.09738212491394412,
+           -0.1726628136725167,
+           -0.24420094417349172,
+           -0.3108173951618947,
+           -0.3714853024261367,
+           -0.4253617065245574,
+           -0.4718141957384028,
+           -0.510441810595197,
+           -0.5410896244626976,
+           -0.5638565781478954,
+           -0.5790963210188343,
+           -0.5874109924864117,
+           -0.5896380611518007,
+           -0.5868305198968972,
+           -0.5802309090818519,
+           -0.5712398023990338,
+           -0.5613795366840542,
+           -0.5522540943551418,
+           -0.5455061518776649,
+           -0.5427723870283669,
+           -0.5456381896939518,
+           -0.5555929440939859,
+           -0.57398704400167,
+           -0.6019917668176548,
+           -0.6405630680376216,
+           -0.6904102662671007,
+           -0.7519704726800378,
+           -0.8253894805203964,
+           -0.9105096732943895,
+           -1.006865338553618,
+           -1.1136855918628856,
+           -1.2299049271898388,
+           -1.3541812202168049,
+           -1.4849208246737238,
+           -1.6203102233672086,
+           -1.7583535295910429,
+           -1.896914985203952,
+           -2.0337654726070573,
+           -2.1666319524050435,
+           -2.2932486593736687,
+           -2.4114088385196704,
+           -2.5190157818479957,
+           -2.614131935557935,
+           -2.695024886637982,
+           -2.760209106341203,
+           -2.8084824241954776,
+           -2.8389563277503664,
+           -2.85107932726842,
+           -2.8446527875610323,
+           -2.819838807201507,
+           -2.7771599141000127,
+           -2.71749054130585,
+           -2.642040443165002,
+           -2.5523304048182482,
+           -2.4501607827692475,
+           -2.337573586368034,
+           -2.216808965335108,
+           -2.0902571030952646,
+           -1.9604066264020488,
+           -1.8297907258013724,
+           -1.700932236845618,
+           -1.5762889572694927,
+           -1.458200469952115,
+           -1.348837705546225,
+           -1.2501564130296496,
+           -1.1638556127306294,
+           -1.0913419868856575,
+           -1.0337010204270665,
+           -0.9916755429462232,
+           -0.9656521455878322,
+           -0.955655758328722,
+           -0.9613524782757231,
+           -0.9820605430327684,
+           -1.0167691496266293,
+           -1.064164633653698,
+           -1.1226633497316165,
+           -1.1904504372175368,
+           -1.2655235182885745,
+           -1.3457402621646704,
+           -1.428868662202561,
+           -1.5126388138640197,
+           -1.5947949525246938,
+           -1.6731465113714463,
+           -1.745616991118951,
+           -1.8102894940994365,
+           -1.86544786386084,
+           -1.9096124854848746,
+           -1.9415699385206482,
+           -1.9603958502817116,
+           -1.9654704683695057,
+           -1.9564866533902012,
+           -1.933450181388462,
+           -1.8966724358449414,
+           -1.846755756455414,
+           -1.7845718916937199,
+           -1.7112341699219855,
+           -1.6280641554227937,
+           -1.5365536874726604,
+           -1.4383233092404561,
+           -1.3350781762460506,
+           -1.2285625893677181,
+           -1.1205143236505946,
+           -1.0126199208775122,
+           -0.9064720811923451,
+           -0.8035302279217078,
+           -0.7050852317415175,
+           -0.61222916776753,
+           -0.5258308449103416,
+           -0.44651769436178657,
+           -0.37466443725743603,
+           -0.31038877462991277,
+           -0.25355416021823446,
+           -0.20377953315200376,
+           -0.1604557076287038,
+           -0.12276794499219851,
+           -0.08972407443559764,
+           -0.06018738590683678,
+           -0.032913396286349594,
+           -0.006589490619278679,
+           0.020123633380578813,
+           0.04854983533087424,
+           0.07995585172585792,
+           0.11551118817364092,
+           0.15625066672303053,
+           0.20304064210260367,
+           0.25654980602673155,
+           0.3172253803520385,
+           0.38527536078165847,
+           0.46065731652536024,
+           0.543074081778512,
+           0.6319764963666017,
+           0.7265731699285451,
+           0.8258470612121978,
+           0.9285784860611069,
+           1.0333739989990884,
+           1.1387004382562926,
+           1.2429232865796536,
+           1.3443483837480406,
+           1.4412659343615766,
+           1.5319956885888135,
+           1.6149321358692599,
+           1.68858854311223,
+           1.7516386900056642,
+           1.802955204211833,
+           1.841643477312094,
+           1.8670702465014501,
+           1.878886054701589,
+           1.877040949840981,
+           1.861792948908978,
+           1.8337089699675309,
+           1.7936581212127005,
+           1.7427974258147032,
+           1.682550249922779,
+           1.614577884205633,
+           1.5407449020466248,
+           1.4630790757049925,
+           1.3837267714219719,
+           1.3049048620753647,
+           1.2288502885882118,
+           1.1577684665090424,
+           1.0937817703084416,
+           1.03887933399964,
+           0.9948693824505512,
+           0.9633352537195465,
+           0.9455961901616544,
+           0.942673866866156,
+           0.9552654928094382,
+           0.9837241661428759,
+           1.0280469940049124,
+           1.0878713032954619,
+           1.1624790764489619,
+           1.25080955007306,
+           1.3514797191645185,
+           1.4628123002351947,
+           1.5828705277038408,
+           1.7094989937098115,
+           1.840369596098219,
+           1.9730315362716908,
+           2.1049642109158953
+          ],
+          [
+           2.19589601650477,
+           2.321933123960234,
+           2.440629621104243,
+           2.5496674524733924,
+           2.6469048936658965,
+           2.7304226168183128,
+           2.798564669630325,
+           2.849973425052687,
+           2.8836177030599237,
+           2.898813429298638,
+           2.8952363738462017,
+           2.8729267024779164,
+           2.832285268109306,
+           2.774061766693966,
+           2.699335075028147,
+           2.6094862729418926,
+           2.506165024749425,
+           2.391250150409922,
+           2.2668053518539164,
+           2.1350311711101018,
+           1.9982143415625633,
+           1.8586757498741513,
+           1.7187182525263456,
+           1.5805755869828266,
+           1.4463635833642148,
+           1.3180348191489053,
+           1.197337768431801,
+           1.085781380999007,
+           0.9846058878503873,
+           0.8947604723074509,
+           0.8168882734235898,
+           0.7513190053697794,
+           0.6980692873571719,
+           0.6568505881739392,
+           0.6270845022763889,
+           0.6079248952084728,
+           0.5982862893464229,
+           0.5968777106752232,
+           0.6022410871811333,
+           0.6127931826598348,
+           0.6268699688754109,
+           0.6427722859926083,
+           0.6588116172766769,
+           0.6733548097164603,
+           0.6848666072428735,
+           0.6919489266191321,
+           0.6933758961963395,
+           0.6881237922185219,
+           0.6753951432796206,
+           0.6546364274044489,
+           0.6255489541254957,
+           0.5880927015915383,
+           0.5424830616674483,
+           0.4891806295372107,
+           0.4288743538638494,
+           0.36245853455728533,
+           0.29100431334035254,
+           0.21572644359840995,
+           0.13794624689048401,
+           0.05905176094738822,
+           -0.01954384446541385,
+           -0.09644446358194182,
+           -0.1703127272584411,
+           -0.23991003096933886,
+           -0.3041338398551638,
+           -0.3620512631086182,
+           -0.41292798651955054,
+           -0.45625177202109773,
+           -0.4917498735551373,
+           -0.5193998759556927,
+           -0.5394336338566559,
+           -0.5523341665588987,
+           -0.5588255478149474,
+           -0.5598560119726336,
+           -0.5565746752370849,
+           -0.5503024384622666,
+           -0.5424977916053286,
+           -0.5347183758505144,
+           -0.5285792739575483,
+           -0.5257090896668283,
+           -0.5277049406583137,
+           -0.5360875249355451,
+           -0.5522574266192208,
+           -0.5774538037468065,
+           -0.6127165482847995,
+           -0.6588529283945342,
+           -0.7164096169744514,
+           -0.7856508812055206,
+           -0.8665435584132009,
+           -0.95874927769934,
+           -1.0616242085796812,
+           -1.1742264316934463,
+           -1.2953308371451617,
+           -1.423451267903426,
+           -1.5568694436017831,
+           -1.6936700286075674,
+           -1.8317810516385984,
+           -1.9690187464463078,
+           -2.1031357676223124,
+           -2.231871645352885,
+           -2.353004280253487,
+           -2.464401245898808,
+           -2.5640696632389846,
+           -2.650203437936225,
+           -2.7212267081954975,
+           -2.775832435593954,
+           -2.813015182727782,
+           -2.832097256531482,
+           -2.832747551632295,
+           -2.81499260032266,
+           -2.7792195204893435,
+           -2.7261707456386692,
+           -2.6569306173079585,
+           -2.5729041148710454,
+           -2.4757881862760893,
+           -2.367536320990395,
+           -2.250317169021491,
+           -2.1264681533570555,
+           -1.9984451440038795,
+           -1.8687693570457182,
+           -1.7399727094449213,
+           -1.6145428980293686,
+           -1.4948694783052416,
+           -1.383192195233658,
+           -1.2815527644754978,
+           -1.1917512201484703,
+           -1.1153078358670652,
+           -1.0534314924156685,
+           -1.0069952110965368,
+           -0.9765194003648339,
+           -0.9621631789969062,
+           -0.9637239462343866,
+           -0.9806451728068973,
+           -1.012032191249025,
+           -1.056675574251204,
+           -1.1130815105297576,
+           -1.1795084232181123,
+           -1.254008930050468,
+           -1.3344761211474458,
+           -1.4186930319835245,
+           -1.504384118458923,
+           -1.5892674995719505,
+           -1.6711067219287496,
+           -1.7477608194289278,
+           -1.817231490373674,
+           -1.8777062916703917,
+           -1.927596853767281,
+           -1.9655712478051677,
+           -1.990579785001364,
+           -2.0018736937561807,
+           -1.9990162982617865,
+           -1.9818865090525162,
+           -1.9506746263254395,
+           -1.9058706462580897,
+           -1.848245444270199,
+           -1.7788253826833291,
+           -1.6988610492550111,
+           -1.6097909737010145,
+           -1.5132012881346917,
+           -1.4107823914608222,
+           -1.304283744899089,
+           -1.195467964392448,
+           -1.086065384806507,
+           -0.9777302504119263,
+           -0.8719996367662264,
+           -0.7702561320988734,
+           -0.6736952036680729,
+           -0.5832980489505439,
+           -0.4998105861671964,
+           -0.4237290772493108,
+           -0.3552927030173488,
+           -0.29448322947737304,
+           -0.241031720320264,
+           -0.1944320685858369,
+           -0.15396094462925242,
+           -0.11870359243776339,
+           -0.08758475615511215,
+           -0.05940388716267297,
+           -0.032873672551644396,
+           -0.006660841054108007,
+           0.02057185538733609,
+           0.05012361578931182,
+           0.0832146519039595,
+           0.12094744088430796,
+           0.16427121519003143,
+           0.2139506522485297,
+           0.2705396177646606,
+           0.33436068591047047,
+           0.4054910102255576,
+           0.4837549546945887,
+           0.5687237192956976,
+           0.6597220127625862,
+           0.755841641968733,
+           0.8559617068686014,
+           0.958774916895756,
+           1.0628193835173674,
+           1.1665150983825665,
+           1.2682041808884503,
+           1.3661938762429393,
+           1.458801207880791,
+           1.544398138403415,
+           1.6214560723938198,
+           1.6885885431122303,
+           1.744590963075456,
+           1.788476384999238,
+           1.8195063129574953,
+           1.837215721630089,
+           1.8414315812950226,
+           1.8322843443454195,
+           1.8102120216844333,
+           1.775956660111765,
+           1.7305532202392004,
+           1.6753110438838186,
+           1.6117882855753798,
+           1.5417598601491986,
+           1.467179622945714,
+           1.3901376467773732,
+           1.3128135868376847,
+           1.2374272279041554,
+           1.166187384897935,
+           1.1012403761283938,
+           1.0446193070910084,
+           0.9981953909535111,
+           0.963632490056758,
+           0.9423459918142726,
+           0.9354670339795851,
+           0.9438129707050127,
+           0.9678648251041355,
+           1.007752309668876,
+           1.063246816860769,
+           1.1337625928417967,
+           1.2183661122401788,
+           1.315793475814391,
+           1.424475460667566,
+           1.5425696689698496,
+           1.6679990504585864,
+           1.7984959204827784,
+           1.9316504627969535,
+           2.0649625979389703,
+           2.1958960165047685
+          ],
+          [
+           2.2851704531500543,
+           2.4075049293468425,
+           2.520969845889181,
+           2.6233510452383078,
+           2.712639789497297,
+           2.787075880694692,
+           2.8451851110928077,
+           2.8858101835851806,
+           2.9081343983098638,
+           2.911697574437828,
+           2.896403861482197,
+           2.862521287893045,
+           2.810673091439259,
+           2.7418210711415925,
+           2.6572413895582367,
+           2.5584934324422215,
+           2.4473824958656665,
+           2.325917214892797,
+           2.196262769309031,
+           2.0606909978631296,
+           1.9215286206692663,
+           1.781104808247342,
+           1.6416993442785537,
+           1.50549260738973,
+           1.3745185457720495,
+           1.250621738536394,
+           1.1354195314541267,
+           1.0302701048197926,
+           0.9362471808695417,
+           0.8541219112612833,
+           0.7843523057370768,
+           0.7270803757111709,
+           0.6821369758123631,
+           0.64905413708263,
+           0.6270845022763886,
+           0.61522730103549,
+           0.612260144881087,
+           0.6167757828331791,
+           0.627222841437089,
+           0.6419494808812709,
+           0.6592488339436966,
+           0.6774050582347199,
+           0.694738825424963,
+           0.709651093932151,
+           0.7206640632279767,
+           0.7264582871312959,
+           0.7259050281086413,
+           0.7180930620060352,
+           0.702349289521892,
+           0.678252673351799,
+           0.6456411941565682,
+           0.6046116999054757,
+           0.5555127071336906,
+           0.49893039457518806,
+           0.4356682048962004,
+           0.36672063443900943,
+           0.29324193985437624,
+           0.21651062050289466,
+           0.13789064327117584,
+           0.058790459270507245,
+           -0.019379082314445437,
+           -0.09524679057737573,
+           -0.16752202850899547,
+           -0.23503334770956755,
+           -0.29676382104209176,
+           -0.35188211785474877,
+           -0.399768476773304,
+           -0.44003486323442415,
+           -0.4725387495571403,
+           -0.49739012062296656,
+           -0.5149514839754653,
+           -0.5258308449103399,
+           -0.5308677903054977,
+           -0.5311130048946242,
+           -0.5278017158517789,
+           -0.5223217215531278,
+           -0.5161768041401925,
+           -0.5109464493551495,
+           -0.5082428978752609,
+           -0.5096666274390346,
+           -0.5167614124694374,
+           -0.5309701263892401,
+           -0.5535924408424819,
+           -0.5857455357744481,
+           -0.6283288657044673,
+           -0.6819939321870409,
+           -0.7471198927051269,
+           -0.8237956949977823,
+           -0.911809266559094,
+           -1.0106441156803116,
+           -1.1194835172267454,
+           -1.2372222678841867,
+           -1.36248580655693,
+           -1.4936563106570282,
+           -1.6289052028073119,
+           -1.7662313393967428,
+           -1.9035040065692324,
+           -2.038509724269452,
+           -2.1690017580763112,
+           -2.2927511643014613,
+           -2.4075981481373825,
+           -2.5115024987263688,
+           -2.6025918793722362,
+           -2.679206795469958,
+           -2.7399411360807004,
+           -2.7836772857112435,
+           -2.8096149283704714,
+           -2.817292813358383,
+           -2.806602917936763,
+           -2.7777966220216865,
+           -2.7314826999538178,
+           -2.6686171296208694,
+           -2.590484914967697,
+           -2.4986743094550468,
+           -2.3950440106363526,
+           -2.2816840652470916,
+           -2.1608713758986227,
+           -2.035020830921545,
+           -1.9066331849124944,
+           -1.7782408965001344,
+           -1.6523531798190674,
+           -1.5314015459318113,
+           -1.4176870994761306,
+           -1.3133308143956477,
+           -1.2202279417415995,
+           -1.1400076039365066,
+           -1.0739985059716715,
+           -1.0232015477915286,
+           -0.98826995716758,
+           -0.9694973827074436,
+           -0.9668141966626702,
+           -0.9797920615251376,
+           -1.007656617803791,
+           -1.0493079576376767,
+           -1.1033483647146283,
+           -1.1681166297997583,
+           -1.2417280971816511,
+           -1.32211946423768,
+           -1.4070972473070875,
+           -1.4943887447474813,
+           -1.5816942743854034,
+           -1.6667394387943748,
+           -1.7473261784477407,
+           -1.8213814095535708,
+           -1.8870021092984735,
+           -1.9424958046038265,
+           -1.9864155389558154,
+           -2.017588532420478,
+           -2.035137909069169,
+           -2.038497039739313,
+           -2.0274162320099345,
+           -2.0019616889070697,
+           -1.962506848466224,
+           -1.9097164031495684,
+           -1.844523476630018,
+           -1.7681006012161844,
+           -1.6818252881309768,
+           -1.5872411113295615,
+           -1.4860153304231394,
+           -1.3798941570314718,
+           -1.2706568196428554,
+           -1.1600696036408307,
+           -1.0498410351174596,
+           -0.9415793397284721,
+           -0.8367532421832605,
+           -0.7366570797335329,
+           -0.6423810866212207,
+           -0.5547875688620321,
+           -0.4744935334927333,
+           -0.40186016745269093,
+           -0.3369893828939414,
+           -0.27972746243996843,
+           -0.2296756543784982,
+           -0.18620738861468014,
+           -0.14849161394972862,
+           -0.11552160017828245,
+           -0.08614840857190958,
+           -0.05911811505717186,
+           -0.033111774802602766,
+           -0.006787047400070454,
+           0.0211796398952048,
+           0.052051526273989214,
+           0.08699166794881949,
+           0.12702587927981182,
+           0.17300946590289126,
+           0.225598652924196,
+           0.2852274895881306,
+           0.35209086997926703,
+           0.42613415086698686,
+           0.5070496767534167,
+           0.5942803428667719,
+           0.6870301437926548,
+           0.7842814732916165,
+           0.8848187642309523,
+           0.987257890947078,
+           1.090080603990267,
+           1.1916731329713706,
+           1.2903679805663686,
+           1.384487842537229,
+           1.4723905271859534,
+           1.552513714593516,
+           1.6234183922191003,
+           1.683829829126783,
+           1.7326750057077172,
+           1.7691154979925032,
+           1.7925749235225639,
+           1.8027601866476821,
+           1.7996759118348902,
+           1.7836316204050346,
+           1.7552413849405861,
+           1.7154158820063679,
+           1.6653469531696674,
+           1.6064849718895855,
+           1.540509494992663,
+           1.4692938476366215,
+           1.3948644456232613,
+           1.3193557947591987,
+           1.2449622202493944,
+           1.1738874669645665,
+           1.10829337159467,
+           1.0502488386112536,
+           1.0016803527577258,
+           0.9643252313559867,
+           0.9396887606948993,
+           0.929006273516436,
+           0.9332111112038797,
+           0.9529092774164917,
+           0.988361432902178,
+           1.0394727078516441,
+           1.1057906226401901,
+           1.1865112146479457,
+           1.2804932727615383,
+           1.3862803869238485,
+           1.5021303324578332,
+           1.6260511324341456,
+           1.755842980398049,
+           1.8891450642626637,
+           2.02348621358104,
+           2.156338199639591,
+           2.285170453150053
+          ],
+          [
+           2.372032218720588,
+           2.489623211640908,
+           2.5968790461084486,
+           2.6917082074035084,
+           2.772251959155821,
+           2.8369241536040364,
+           2.8844448363214643,
+           2.913866875697396,
+           2.924595013960927,
+           2.916396917367774,
+           2.8894059939312355,
+           2.8441159431166296,
+           2.7813671984591113,
+           2.702325616324202,
+           2.608453947334713,
+           2.5014767968872174,
+           2.3833399335601637,
+           2.2561649353927717,
+           2.122200270833321,
+           1.9837699910634319,
+           1.8432212615125485,
+           1.702871981505539,
+           1.5649597316963058,
+           1.4315932495405823,
+           1.3047075646008475,
+           1.186023829718087,
+           1.0770147634603207,
+           0.9788764768060656,
+           0.8925072963133128,
+           0.8184940210757411,
+           0.7571058659349912,
+           0.7082961532928844,
+           0.6717116251631635,
+           0.6467090605347959,
+           0.632378705291441,
+           0.6275738572199663,
+           0.6309458010856842,
+           0.6409831619584538,
+           0.656054642023327,
+           0.6744540294835187,
+           0.6944463196830141,
+           0.7143137693570668,
+           0.7324007153456248,
+           0.7471560288213422,
+           0.7571721440043975,
+           0.7612196946724138,
+           0.7582769100805176,
+           0.7475530611441558,
+           0.7285054043478011,
+           0.700849240839306,
+           0.6645608872370332,
+           0.6198735382791114,
+           0.567266184938318,
+           0.5074459303788841,
+           0.4413242156345555,
+           0.36998762287033904,
+           0.2946640626278,
+           0.216685269062677,
+           0.13744662091057802,
+           0.05836537341177058,
+           -0.019161573998477864,
+           -0.09379923875581771,
+           -0.16431432799840576,
+           -0.22961215334127988,
+           -0.28876969241680883,
+           -0.3410639022349668,
+           -0.38599451269301716,
+           -0.4233006717649523,
+           -0.4529709734033618,
+           -0.4752465709541619,
+           -0.49061725857061733,
+           -0.499810586167195,
+           -0.5037742552376221,
+           -0.5036522187640115,
+           -0.5007550739972917,
+           -0.4965254878809061,
+           -0.4924995274679633,
+           -0.49026487845302946,
+           -0.4914170210522509,
+           -0.4975144916840278,
+           -0.510034389662219,
+           -0.530329289562388,
+           -0.5595866919393392,
+           -0.5987920882795897,
+           -0.6486966318066337,
+           -0.7097902960516331,
+           -0.7822812706298875,
+           -0.8660821916714154,
+           -0.9608036365841953,
+           -1.0657551334253033,
+           -1.1799537485620204,
+           -1.3021401271549922,
+           -1.4308016739959504,
+           -1.5642023820477722,
+           -1.7004186471708789,
+           -1.8373802542110913,
+           -1.9729155857292249,
+           -2.1047999935559742,
+           -2.2308061878851126,
+           -2.3487554409721705,
+           -2.4565683741990494,
+           -2.552314099089872,
+           -2.6342565148677624,
+           -2.7008966266302297,
+           -2.7510098377653067,
+           -2.783677285711243,
+           -2.798310428814043,
+           -2.7946682505194014,
+           -2.772866621613469,
+           -2.7333795474659097,
+           -2.677032220697818,
+           -2.604985995681433,
+           -2.5187155949938878,
+           -2.4199790446601948,
+           -2.3107810101621067,
+           -2.1933303644715143,
+           -2.0699929588839328,
+           -1.9432406837567664,
+           -1.8155979965404079,
+           -1.689587156506108,
+           -1.5676734377927344,
+           -1.452211594013582,
+           -1.3453948186324793,
+           -1.2492073863326085,
+           -1.165382073094658,
+           -1.095363338801165,
+           -1.040277118668048,
+           -1.0009079120239641,
+           -0.9776836827617092,
+           -0.9706688994209333,
+           -0.979565848871062,
+           -1.0037241606747098,
+           -1.0421582842189117,
+           -1.0935724723475986,
+           -1.1563926480899036,
+           -1.2288043694510005,
+           -1.3087959650257774,
+           -1.3942057938395807,
+           -1.4827724891787546,
+           -1.5721869804738569,
+           -1.6601450510796192,
+           -1.7443991838690185,
+           -1.8228084709898191,
+           -1.8933854182392236,
+           -1.9543385568856804,
+           -2.0041098843027356,
+           -2.0414062867339897,
+           -2.0652242495648694,
+           -2.074867328831669,
+           -2.069956038151838,
+           -2.050429993323324,
+           -2.0165423478481705,
+           -1.9688467418573632,
+           -1.9081771696758516,
+           -1.8356213430653168,
+           -1.7524882837965163,
+           -1.660271016797761,
+           -1.5606053503480262,
+           -1.4552258198420291,
+           -1.345919934392763,
+           -1.234481899481375,
+           -1.1226669932627653,
+           -1.0121477489735264,
+           -0.9044730418900051,
+           -0.8010310978907951,
+           -0.7030173340124412,
+           -0.6114078122009771,
+           -0.5269389390646828,
+           -0.4500938806086751,
+           -0.381095985844601,
+           -0.3199093312578047,
+           -0.2662463139838962,
+           -0.21958203984948285,
+           -0.17917507775279967,
+           -0.14409398860258155,
+           -0.11324888930813874,
+           -0.08542718383649854,
+           -0.059332487351659406,
+           -0.0336256885864391,
+           -0.006967041894370154,
+           0.02194184477222274,
+           0.054317255789816575,
+           0.09125494459557913,
+           0.1336950770208018,
+           0.1823914893064757,
+           0.23788609677310596,
+           0.30048915545517724,
+           0.3702659271782064,
+           0.447030132394992,
+           0.5303443988122448,
+           0.6195277318918194,
+           0.713669850311223,
+           0.8116520500550335,
+           0.9121740895359968,
+           1.0137864293659062,
+           1.1149270181567443,
+           1.2139616936659436,
+           1.3092271698388995,
+           1.3990755073979457,
+           1.4819189204865055,
+           1.5562737557122082,
+           1.6208024932314193,
+           1.6743526620295472,
+           1.715991632293811,
+           1.7450363450566069,
+           1.7610771607485118,
+           1.7639951509714882,
+           1.7539723181794802,
+           1.7314944020799699,
+           1.6973461151387854,
+           1.6525988380291257,
+           1.5985909945296828,
+           1.5369015095452274,
+           1.469316928996979,
+           1.3977929419250024,
+           1.3244111892024062,
+           1.2513323661476963,
+           1.1807467249215302,
+           1.1148231543862175,
+           1.0556580582283022,
+           1.0052252654389509,
+           0.9653281902923525,
+           0.9375554120836843,
+           0.9232407691500378,
+           0.9234289588791279,
+           0.9388475079620369,
+           0.9698858281296879,
+           1.0165819056267738,
+           1.0786169917689095,
+           1.1553184714949902,
+           1.2456708915044052,
+           1.3483349341221695,
+           1.4616739322377545,
+           1.5837873391807438,
+           1.712550399671382,
+           1.8456591181251096,
+           1.9806794922738835,
+           2.1150998764426947,
+           2.2463852624352323,
+           2.3720322187205864
+          ],
+          [
+           2.455746423374246,
+           2.567593213015275,
+           2.6677149955788857,
+           2.754160606445108,
+           2.825237056711343,
+           2.8795456966009323,
+           2.9160116902756306,
+           2.933906129078266,
+           2.932860285756192,
+           2.9128716995208124,
+           2.87430197631937,
+           2.8178663856939927,
+           2.744615530284541,
+           2.655909551661448,
+           2.553385512195356,
+           2.438918752813998,
+           2.314579166889612,
+           2.1825834477576844,
+           2.0452444586775553,
+           1.904918937235687,
+           1.7639547797853594,
+           1.6246391547637362,
+           1.489148666627118,
+           1.359502735442629,
+           1.2375212723411466,
+           1.1247876202334735,
+           1.0226175952160688,
+           0.9320353103067035,
+           0.8537562933975701,
+           0.7881782298235983,
+           0.7353794712272135,
+           0.6951252611365356,
+           0.6668814385935902,
+           0.6498351989391907,
+           0.6429223199683844,
+           0.6448601063097006,
+           0.6541851688533677,
+           0.6692950426696835,
+           0.6884925588603494,
+           0.7100318252769274,
+           0.7321646394369651,
+           0.7531861549621722,
+           0.771478650407734,
+           0.785552305663695,
+           0.7940819746886723,
+           0.7959390520049717,
+           0.7902176613420425,
+           0.7762545447093735,
+           0.7536421951901435,
+           0.7222349526809622,
+           0.6821479642021709,
+           0.633749094653744,
+           0.5776440553405943,
+           0.5146551916620756,
+           0.44579453366869415,
+           0.372231859650816,
+           0.29525864985844275,
+           0.21624891167191193,
+           0.1366179364387836,
+           0.05778009978989666,
+           -0.018893159736287857,
+           -0.0921140550607028,
+           -0.16071676432449253,
+           -0.22369231362194988,
+           -0.2802190879248694,
+           -0.32968814324871415,
+           -0.37172262824759905,
+           -0.40619077644482177,
+           -0.43321209733458255,
+           -0.4531565713995473,
+           -0.46663683620039986,
+           -0.4744935334927318,
+           -0.4777741661779591,
+           -0.477705984257608,
+           -0.47566357650245694,
+           -0.47313198525539735,
+           -0.4716662820633781,
+           -0.47284863859250387,
+           -0.47824399802023704,
+           -0.4893554949691994,
+           -0.5075807858936202,
+           -0.5341704362245256,
+           -0.5701894658330838,
+           -0.6164830815244053,
+           -0.6736475260735554,
+           -0.7420068501720186,
+           -0.8215962695807846,
+           -0.9121526083297028,
+           -1.013112153947887,
+           -1.1236160667861723,
+           -1.2425232970653182,
+           -1.3684307750407658,
+           -1.4997004563104053,
+           -1.6344926303892306,
+           -1.7708047405929657,
+           -1.9065148210360316,
+           -2.0394285357497846,
+           -2.1673287086310222,
+           -2.288026163605711,
+           -2.3994106538421547,
+           -2.4995006481667272,
+           -2.5864907623827817,
+           -2.658795672580859,
+           -2.715089425630664,
+           -2.7543391670244204,
+           -2.775832435593954,
+           -2.7791973252400877,
+           -2.764414982053886,
+           -2.7318240869951573,
+           -2.682117165205026,
+           -2.6163287584149724,
+           -2.5358156920069037,
+           -2.4422298583094975,
+           -2.3374841180366674,
+           -2.223712087966805,
+           -2.103222730952731,
+           -1.978450790508317,
+           -1.8519042134387238,
+           -1.7261097777751397,
+           -1.603558187820264,
+           -1.486649912301486,
+           -1.3776430251017715,
+           -1.278604261182855,
+           -1.191364424262136,
+           -1.1174791794014654,
+           -1.0581961354272515,
+           -1.014428972151885,
+           -0.9867391993595532,
+           -0.9753259525507418,
+           -0.9800240389437892,
+           -1.00031025087421,
+           -1.0353177672948999,
+           -1.0838582723422057,
+           -1.1444512375544236,
+           -1.2153596457368634,
+           -1.2946312837445195,
+           -1.3801446022399741,
+           -1.469658035888302,
+           -1.560861599972775,
+           -1.6514295308843028,
+           -1.7390727194713562,
+           -1.8215896982111155,
+           -1.8969149852039522,
+           -1.9631636589902197,
+           -2.0186711363186167,
+           -2.0620272477721766,
+           -2.0921038504920038,
+           -2.1080753795158924,
+           -2.109431915419905,
+           -2.0959845316318266,
+           -2.067862875367397,
+           -2.025505126903352,
+           -1.9696406681319332,
+           -1.9012659684486368,
+           -1.8216143596543135,
+           -1.7321205176943497,
+           -1.6343805941442624,
+           -1.530109041347131,
+           -1.4210932495832898,
+           -1.3091471608417307,
+           -1.196065040608552,
+           -1.0835765762669252,
+           -0.9733044286318921,
+           -0.8667252929670299,
+           -0.7651354293939985,
+           -0.6696215024065574,
+           -0.5810374283245037,
+           -0.49998777156823027,
+           -0.4268180596193898,
+           -0.3616122067973447,
+           -0.30419705307459194,
+           -0.2541538407253839,
+           -0.2108362732795461,
+           -0.17339463253224388,
+           -0.14080527448819616,
+           -0.11190468798970712,
+           -0.0854271838364985,
+           -0.060045190359519635,
+           -0.0344110659599935,
+           -0.007199301702136893,
+           0.0228520214202287,
+           0.05690163523983574,
+           0.09596841259465214,
+           0.14089860967654272,
+           0.1923379092373764,
+           0.25070902646016613,
+           0.31619549476658254,
+           0.3887320882990783,
+           0.4680021653503066,
+           0.5534420369814733,
+           0.6442522820351142,
+           0.7394157483465386,
+           0.8377218047942384,
+           0.9377962443532287,
+           1.038136088712916,
+           1.1371484141098198,
+           1.23319220915712,
+           1.3246221914309169,
+           1.4098334525793743,
+           1.4873057732634776,
+           1.555646450110189,
+           1.6136305071199204,
+           1.660237222942633,
+           1.6946819917221316,
+           1.7164426467213274,
+           1.7252795099613072,
+           1.7212485843447063,
+           1.704707473412229,
+           1.6763137938296164,
+           1.6370160324594627,
+           1.5880369887971229,
+           1.5308501299367558,
+           1.4671493644290534,
+           1.3988129089116548,
+           1.327862073031191,
+           1.2564159201129308,
+           1.1866428699298714,
+           1.12071039300241,
+           1.0607340009804267,
+           1.0087267633676624,
+           0.9665505764139223,
+           0.9358703754388866,
+           0.9181124179211289,
+           0.9144276728734438,
+           0.9256612345079436,
+           0.9523285377869842,
+           0.9945989935435914,
+           1.0522874853087627,
+           1.1248539830657422,
+           1.21141133541225,
+           1.3107411057749103,
+           1.4213171251682597,
+           1.5413362482467858,
+           1.668755625609205,
+           1.8013356477393667,
+           1.9366875784723308,
+           2.0723247818356625,
+           2.205716358338453,
+           2.3343419474278835,
+           2.4557464233742445
+          ],
+          [
+           2.535604807058549,
+           2.64075527197649,
+           2.7328783901143407,
+           2.810179866807182,
+           2.8711468042625143,
+           2.914579912145158,
+           2.9396186030866907,
+           2.9457584025763235,
+           2.9328602857561923,
+           2.9011517458351075,
+           2.851219595470243,
+           2.7839946987589896,
+           2.7007290226586274,
+           2.6029655780638854,
+           2.4925019880201957,
+           2.37134856958326,
+           2.241681943054645,
+           2.10579528466893,
+           1.966046413835473,
+           1.8248049519757856,
+           1.6843998057916034,
+           1.547068213136927,
+           1.4149075449863746,
+           1.2898309834664674,
+           1.173528095427608,
+           1.0674311961244953,
+           0.9726882513797173,
+           0.8901429027861602,
+           0.8203220231420095,
+           0.7634310228168996,
+           0.719356936744277,
+           0.6876791309496644,
+           0.6676872816677062,
+           0.6584061037503193,
+           0.6586261425560119,
+           0.666939798815277,
+           0.681781632616889,
+           0.7014718936447787,
+           0.7242621524933902,
+           0.7483818640099484,
+           0.7720846791526966,
+           0.7936933370778615,
+           0.8116420135976975,
+           0.8245150745826098,
+           0.8310812814113232,
+           0.8303226176552478,
+           0.8214570486841887,
+           0.8039546851631572,
+           0.7775469934238656,
+           0.7422288760774423,
+           0.6982536304226138,
+           0.6461209755436826,
+           0.5865585168608759,
+           0.5204971848120789,
+           0.4490413380852056,
+           0.3734343575217488,
+           0.2950206710692795,
+           0.2152052401115793,
+           0.13541160090140794,
+           0.05703959008456589,
+           -0.018576110433992373,
+           -0.09020549690864599,
+           -0.15675977450385326,
+           -0.21732391307436114,
+           -0.2711843495494678,
+           -0.3178510849646041,
+           -0.35707357003755924,
+           -0.38884993473075685,
+           -0.41342929038333787,
+           -0.4313070133511936,
+           -0.44321310208932974,
+           -0.4500938806086737,
+           -0.453087495645128,
+           -0.45349381826014284,
+           -0.45273950879011327,
+           -0.45233913329449377,
+           -0.45385332660971034,
+           -0.45884507904373123,
+           -0.4688352785149312,
+           -0.485258666098745,
+           -0.5094213597617918,
+           -0.542461068536753,
+           -0.5853110582587648,
+           -0.6386688417007781,
+           -0.7029704526493252,
+           -0.7783710279221817,
+           -0.8647322668764535,
+           -0.9616171684006142,
+           -1.0682922649233977,
+           -1.183737386084315,
+           -1.3066627960432573,
+           -1.4355333626635332,
+           -1.5685992386248604,
+           -1.703932368373735,
+           -1.8394679848731506,
+           -1.9730501301524774,
+           -2.1024801269762814,
+           -2.2255668482704944,
+           -2.3401775783511765,
+           -2.444288236888788,
+           -2.5360317435755735,
+           -2.6137433385685243,
+           -2.676001740133178,
+           -2.721665114969402,
+           -2.74990095622597,
+           -2.7602091063412026,
+           -2.75243732315362,
+           -2.7267889643028163,
+           -2.6838225524966566,
+           -2.624443178189456,
+           -2.5498858918648244,
+           -2.4616914306662876,
+           -2.3616748088570665,
+           -2.251887473993081,
+           -2.1345738865313577,
+           -2.012123516044478,
+           -1.8870193589395376,
+           -1.761784167836532,
+           -1.6389256394413259,
+           -1.520881834446237,
+           -1.4099680990345407,
+           -1.308326723032035,
+           -1.2178805054663535,
+           -1.1402913058175848,
+           -1.0769245408189718,
+           -1.02882044517366,
+           -0.9966727534391299,
+           -0.9808152835188534,
+           -0.9812167139991474,
+           -0.9974836525623992,
+           -1.028871895644219,
+           -1.0743055851774308,
+           -1.13240378140469,
+           -1.2015137958815978,
+           -1.2797504701725433,
+           -1.3650404471983733,
+           -1.455170367067782,
+           -1.5478378302735825,
+           -1.640703910476106,
+           -1.7314459681446837,
+           -1.8178095157708425,
+           -1.8976579151402244,
+           -1.969018746446308,
+           -2.030125776314792,
+           -2.079455564864456,
+           -2.115757887909292,
+           -2.138079305899555,
+           -2.1457793823238056,
+           -2.1385392367906872,
+           -2.1163623073464106,
+           -2.0795673880715926,
+           -2.0287741969061055,
+           -1.9648819103143955,
+           -1.8890412713576616,
+           -1.8026210318148979,
+           -1.7071696234274278,
+           -1.6043730648616787,
+           -1.4960101969007615,
+           -1.3839063966364742,
+           -1.269886950682486,
+           -1.1557312670342776,
+           -1.0431290752697102,
+           -0.9336397061594495,
+           -0.8286554559964863,
+           -0.7293699302913291,
+           -0.6367521287630535,
+           -0.5515268821821511,
+           -0.4741620854452369,
+           -0.40486299450287594,
+           -0.34357367189817245,
+           -0.28998548132762003,
+           -0.24355235046010515,
+           -0.20351234781137406,
+           -0.16891495813525997,
+           -0.13865329561614034,
+           -0.11150036877439953,
+           -0.0861484085719095,
+           -0.06125019429080426,
+           -0.03546126227529838,
+           -0.007481861800298204,
+           0.02390246933292092,
+           0.05978279960445449,
+           0.10109219387389776,
+           0.1485755321011313,
+           0.2027645744821716,
+           0.263958954197782,
+           0.3322136247845726,
+           0.40733312126276705,
+           0.48887281684417566,
+           0.57614717479039,
+           0.6682448124144579,
+           0.7640500159510714,
+           0.8622701755874388,
+           0.961468453658737,
+           1.0601008598516861,
+           1.1565567887844341,
+           1.2492019805819372,
+           1.3364227964934257,
+           1.4166706609972544,
+           1.4885055103047975,
+           1.550637105076711,
+           1.6019631121324678,
+           1.6416029348680246,
+           1.6689263731946384,
+           1.6835763186133776,
+           1.685484835485232,
+           1.674882142064041,
+           1.6522981804124648,
+           1.6185566485692815,
+           1.5747615567017594,
+           1.5222765567694319,
+           1.462697477758434,
+           1.3978186712519522,
+           1.329593930650045,
+           1.2600928877501074,
+           1.191453909099543,
+           1.125834608516058,
+           1.065361159026819,
+           1.0120776254606292,
+           0.9678965470039245,
+           0.9345519769058157,
+           0.9135561346408013,
+           0.9061607453969907,
+           0.9133240346475894,
+           0.935684214340947,
+           0.9735401450661674,
+           1.0268396890959652,
+           1.0951760865870763,
+           1.1777924958732937,
+           1.2735946433809198,
+           1.381171334002125,
+           1.4988223835387402,
+           1.6245933557098964,
+           1.7563163215914441,
+           1.8916557132636616,
+           2.028158219474327,
+           2.1633055723283414,
+           2.29456900282705,
+           2.4194641012616525,
+           2.535604807058548
+          ],
+          [
+           2.6109317317111973,
+           2.7084904043995306,
+           2.7918179179102713,
+           2.859292040198062,
+           2.909592784570653,
+           2.941730394920046,
+           2.955065849590012,
+           2.9493234205945593,
+           2.924595013960928,
+           2.881336212422181,
+           2.8203541387707336,
+           2.7427874521102034,
+           2.650078975294755,
+           2.543941625505571,
+           2.4263184769738624,
+           2.299337921520992,
+           2.165265005555277,
+           2.0264501087332794,
+           1.8852761876039623,
+           1.7441058358510186,
+           1.605229410610304,
+           1.4708154418925254,
+           1.3428644802576466,
+           1.223167448160644,
+           1.1132694450941627,
+           1.0144398186931913,
+           0.9276491567934072,
+           0.8535536829685905,
+           0.792487354602173,
+           0.7444617726251611,
+           0.7091738203781869,
+           0.6860207603630636,
+           0.6741223365884565,
+           0.6723492612351009,
+           0.6793573116091711,
+           0.6936261305469233,
+           0.7135017138052663,
+           0.7372414841642994,
+           0.7630607959743883,
+           0.7891796870013101,
+           0.8138686972301897,
+           0.8354926066137269,
+           0.8525510046887994,
+           0.8637146929221783,
+           0.8678570332950997,
+           0.8640794910990999,
+           0.8517307727540578,
+           0.8304191267828114,
+           0.8000175536388654,
+           0.7606618533894586,
+           0.7127416246742393,
+           0.656884509238259,
+           0.5939341491208616,
+           0.5249224839233128,
+           0.45103715944953027,
+           0.3735849428070128,
+           0.29395213966855316,
+           0.2135630843153462,
+           0.13383782044297032,
+           0.05615010934296982,
+           -0.01821310847215529,
+           -0.0880897115652461,
+           -0.15247683646092883,
+           -0.21056083124888036,
+           -0.2617419152655258,
+           -0.30565287425205023,
+           -0.3421712757241293,
+           -0.37142485799047886,
+           -0.39378992404825736,
+           -0.4098827539572276,
+           -0.4205442316273471,
+           -0.42681805961938857,
+           -0.4299231040426825,
+           -0.4312205666520847,
+           -0.43217681884636605,
+           -0.43432284893465767,
+           -0.4392113667705527,
+           -0.4483726762571771,
+           -0.4632704645608422,
+           -0.4852586660987448,
+           -0.5155405391789395,
+           -0.5551310439981544,
+           -0.6048235337018623,
+           -0.6651616672384449,
+           -0.736417326306337,
+           -0.8185751719033783,
+           -0.911324312460512,
+           -1.0140573793229808,
+           -1.1258771208025902,
+           -1.2456104377532613,
+           -1.3718295963110299,
+           -1.5028801717677387,
+           -1.6369151060638802,
+           -1.771934104396096,
+           -1.9058274578943513,
+           -2.0364232627377317,
+           -2.161536914415774,
+           -2.2790216914599823,
+           -2.3868192075539763,
+           -2.4830085054521587,
+           -2.5658525908279195,
+           -2.6338412585206363,
+           -2.685729146407393,
+           -2.720568061339105,
+           -2.737732754641624,
+           -2.736939478388105,
+           -2.718256824281329,
+           -2.682108530402332,
+           -2.6292681328207665,
+           -2.5608455344471284,
+           -2.478265757764128,
+           -2.3832403364521375,
+           -2.2777319788065373,
+           -2.1639132988709666,
+           -2.0441205553754043,
+           -1.9208034603277455,
+           -1.7964722154618609,
+           -1.6736430033157714,
+           -1.5547831988005423,
+           -1.442257575745047,
+           -1.338276760831054,
+           -1.244849135085868,
+           -1.1637373019341493,
+           -1.096420132691846,
+           -1.044061267940769,
+           -1.0074847996725877,
+           -0.987158688174872,
+           -0.9831862835104789,
+           -0.995306128599473,
+           -1.0229000240449846,
+           -1.065009138742043,
+           -1.1203577597408272,
+           -1.1873840944326026,
+           -1.2642773722645717,
+           -1.349020345885037,
+           -1.4394361664292323,
+           -1.5332385075892123,
+           -1.6280837405581623,
+           -1.7216239186128315,
+           -1.811559316987926,
+           -1.8956892910525787,
+           -1.9719602631198652,
+           -2.038509724269452,
+           -2.0937052403996708,
+           -2.1361775787524326,
+           -2.1648472191851305,
+           -2.1789436797997648,
+           -2.178017265063596,
+           -2.1619430318340056,
+           -2.1309169600919953,
+           -2.0854445059620805,
+           -2.0263219000449344,
+           -1.954610729649249,
+           -1.8716065048720536,
+           -1.7788020516951701,
+           -1.6778466968516579,
+           -1.5705023062263033,
+           -1.4585973086628365,
+           -1.3439798786047557,
+           -1.2284714630584237,
+           -1.1138218207342303,
+           -1.0016666944322596,
+           -0.8934891630568073,
+           -0.7905856190259425,
+           -0.6940371928892686,
+           -0.6046873028565147,
+           -0.5231258463479579,
+           -0.4496803776865595,
+           -0.38441443504479944,
+           -0.3271329953148614,
+           -0.2773948523446779,
+           -0.23453153659293324,
+           -0.1976722271685416,
+           -0.16577395463432226,
+           -0.1376562587014532,
+           -0.11203935238573404,
+           -0.08758475615511203,
+           -0.0629373042669841,
+           -0.036767392396307025,
+           -0.007812331602563737,
+           0.02508430124562492,
+           0.0629363729294064,
+           0.10658293892515608,
+           0.15666089405700853,
+           0.21358327073477051,
+           0.2775237796016327,
+           0.3484080248809087,
+           0.4259116529133364,
+           0.5094655117208834,
+           0.5982677164989394,
+           0.6913023353660971,
+           0.7873642360737539,
+           0.8850894721094599,
+           0.98299043985,
+           1.0794949108792096,
+           1.1729879385484503,
+           1.2618555580296371,
+           1.344529146567762,
+           1.4195292867744982,
+           1.4855079812922085,
+           1.5412881019375118,
+           1.5858990197102116,
+           1.6186074523149445,
+           1.6389426808986234,
+           1.6467154247407338,
+           1.6420298182736495,
+           1.625288105212241,
+           1.5971878455144404,
+           1.5587116178832745,
+           1.5111093889010572,
+           1.4558739049579417,
+           1.3947096402715726,
+           1.3294959990506985,
+           1.2622456180901878,
+           1.195058744055136,
+           1.1300747641710607,
+           1.0694220473138691,
+           1.015167302560005,
+           0.9692656827809826,
+           0.9335128512434094,
+           0.9095001895460018,
+           0.898574256472558,
+           0.9018015110690173,
+           0.9199391917512665,
+           0.9534130994333008,
+           1.002302870003642,
+           1.066335143913355,
+           1.144884852487587,
+           1.2369846464182612,
+           1.3413422964773165,
+           1.4563657045852052,
+           1.5801949796762678,
+           1.7107408618236777,
+           1.8457286240177848,
+           1.9827464476196357,
+           2.119297158117285,
+           2.2528521250950746,
+           2.380906076329832,
+           2.501031551996892,
+           2.6109317317111964
+          ],
+          [
+           2.6810898974638078,
+           2.770225540413602,
+           2.844034923891082,
+           2.901081615407351,
+           2.9402497272453485,
+           2.960767439555587,
+           2.962222739090219,
+           2.94457102146735,
+           2.908134398309865,
+           2.853592747661335,
+           2.781966741951299,
+           2.694593277700774,
+           2.59309391051303,
+           2.479337063333792,
+           2.35539492150819,
+           2.223496051294991,
+           2.0859748762618118,
+           1.9452192160432507,
+           1.803617132645886,
+           1.6635043399005685,
+           1.5271134116097074,
+           1.3965259739800318,
+           1.2736289893683974,
+           1.1600761331994396,
+           1.057255136789982,
+           0.9662618189715029,
+           0.8878813625777616,
+           0.8225772122104617,
+           0.7704877816692383,
+           0.7314309676886881,
+           0.7049162759013132,
+           0.6901641799423176,
+           0.6861321598793158,
+           0.6915467059718634,
+           0.7049404320567116,
+           0.7246933230624872,
+           0.7490770461781459,
+           0.7763011873065258,
+           0.8045602352229076,
+           0.8320801262072799,
+           0.8571631819690247,
+           0.8782303228351102,
+           0.8938595151048793,
+           0.9028195141732182,
+           0.9040980908378471,
+           0.8969240739120333,
+           0.8807827041470022,
+           0.8554239684169374,
+           0.8208637647276797,
+           0.7773779332879337,
+           0.7254893719697867,
+           0.6659486313718623,
+           0.5997085509341203,
+           0.5278936489628256,
+           0.45176511220980675,
+           0.37268234148695417,
+           0.2920620959154298,
+           0.2113363376643328,
+           0.13190990995829294,
+           0.05511918297467699,
+           -0.017807225011634006,
+           -0.08578459953191206,
+           -0.147904185789614,
+           -0.20346028687808063,
+           -0.2519716723398358,
+           -0.293196713493434,
+           -0.32714182546056564,
+           -0.35406297025814776,
+           -0.37446015625545054,
+           -0.38906505214671033,
+           -0.3988220137163413,
+           -0.4048629945028747,
+           -0.4084769726055859,
+           -0.41107467122079905,
+           -0.4141494763328627,
+           -0.41923555809403473,
+           -0.4278642801517068,
+           -0.4415200314992319,
+           -0.4615966370021287,
+           -0.48935549496919895,
+           -0.5258865531182343,
+           -0.5720731688830974,
+           -0.6285618077906316,
+           -0.695737416845217,
+           -0.7737051713585693,
+           -0.8622791368649444,
+           -0.9609782165441776,
+           -1.0690295731829336,
+           -1.1853795276472818,
+           -1.3087117477780172,
+           -1.4374723572500574,
+           -1.569901417873582,
+           -1.7040700754756488,
+           -1.8379225129984285,
+           -1.969321728486804,
+           -2.0960980534134546,
+           -2.216099250923021,
+           -2.3272409860375105,
+           -2.427556441925478,
+           -2.5152438685390988,
+           -2.5887108920619237,
+           -2.6466144847419106,
+           -2.687895593144722,
+           -2.7118075463099074,
+           -2.7179375107629604,
+           -2.706220423316771,
+           -2.676945011110528,
+           -2.63075169704136,
+           -2.5686223830441017,
+           -2.4918622988223653,
+           -2.402074294855855,
+           -2.30112614112103,
+           -2.191111562484702,
+           -2.074305894000626,
+           -1.9531173706111231,
+           -1.830035172796693,
+           -1.7075754298821575,
+           -1.5882264340126195,
+           -1.474394338975499,
+           -1.36835060852319,
+           -1.2721824388529277,
+           -1.1877473103812304,
+           -1.116632726588204,
+           -1.0601220748614952,
+           -1.0191673989262073,
+           -0.9943697081394632,
+           -0.9859672696564115,
+           -0.9938321396016108,
+           -1.0174749935286664,
+           -1.0560581193877632,
+           -1.1084162427387854,
+           -1.1730846687494365,
+           -1.248334053098852,
+           -1.3322109584463024,
+           -1.4225832183808405,
+           -1.5171890199879572,
+           -1.6136885320092171,
+           -1.7097168500293458,
+           -1.8029370044973936,
+           -1.8910917822311126,
+           -1.9720531471766805,
+           -2.043868110663934,
+           -2.1047999935559747,
+           -2.1533641402086627,
+           -2.1883572840780503,
+           -2.2088799236439223,
+           -2.2143512410980977,
+           -2.2045162806594787,
+           -2.179445293853455,
+           -2.139525350920298,
+           -2.085444505962081,
+           -2.0181689838609636,
+           -1.938914024972683,
+           -1.849109175005603,
+           -1.750358938645155,
+           -1.644399823194646,
+           -1.5330548801828838,
+           -1.4181869065973747,
+           -1.3016514918976378,
+           -1.1852510917355654,
+           -1.0706912745883497,
+           -0.9595402242583997,
+           -0.8531924910869418,
+           -0.7528378701029672,
+           -0.6594361481344844,
+           -0.5736983076236096,
+           -0.49607460643669665,
+           -0.4267497746179356,
+           -0.3656453853112544,
+           -0.3124292726107972,
+           -0.26653168854428594,
+           -0.2271677192911494,
+           -0.1933653214143718,
+           -0.16399819634036894,
+           -0.13782259912759737,
+           -0.11351707877846591,
+           -0.08972407443559748,
+           -0.06509224657423475,
+           -0.038318405871165064,
+           -0.008187915184867037,
+           0.026387518325574188,
+           0.06633567455735419,
+           0.11239419356070302,
+           0.16508628972335965,
+           0.22470246692936027,
+           0.2912887381106482,
+           0.36464168310272616,
+           0.444310500466141,
+           0.5296060264634723,
+           0.619616512314608,
+           0.7132297738122129,
+           0.8091611598625431,
+           0.9059866327858759,
+           1.00218011718503,
+           1.0961541593478856,
+           1.186302848439685,
+           1.2710458865092031,
+           1.348872658264132,
+           1.4183851446434874,
+           1.4783385466775545,
+           1.527678537489621,
+           1.565574139344129,
+           1.5914453274713665,
+           1.604984590438687,
+           1.6061718249453034,
+           1.5952821074357888,
+           1.5728860617826308,
+           1.5398427270891049,
+           1.497285017811384,
+           1.4465980551998838,
+           1.3893908298445206,
+           1.327461825346158,
+           1.262759388548477,
+           1.1973377684317987,
+           1.1333098602302218,
+           1.0727977806679592,
+           1.01788246211805,
+           0.970553486340656,
+           0.9326603813491819,
+           0.9058665777110511,
+           0.891607163791607,
+           0.8910514944028369,
+           0.9050715960322001,
+           0.9342171769619858,
+           0.9786978953947116,
+           1.0383733669311566,
+           1.1127512085761089,
+           1.2009932243573027,
+           1.3019296423222815,
+           1.4140811189000815,
+           1.5356880391231773,
+           1.6647464645959988,
+           1.7990499197042158,
+           1.936236064350171,
+           2.07383718197561,
+           2.209333317739445,
+           2.3402068357791777,
+           2.4639971281369952,
+           2.578354202090689,
+           2.681089897463807
+          ],
+          [
+           2.7454857344871804,
+           2.825438372832556,
+           2.889087628557712,
+           2.9351950337187778,
+           2.9628582606791474,
+           2.9715299840398037,
+           2.96102872106361,
+           2.931541412641797,
+           2.8836177030599255,
+           2.81815607381851,
+           2.7363821797595267,
+           2.6398199200543195,
+           2.530255947747542,
+           2.409698475378419,
+           2.280331366995691,
+           2.1444646154462066,
+           2.0044823855472638,
+           1.862789856708399,
+           1.721760121517333,
+           1.5836823892527687,
+           1.4507127054892512,
+           1.3248283319143532,
+           1.2077868359009674,
+           1.1010908196565712,
+           1.005959076910083,
+           0.9233048046378686,
+           0.8537213222669768,
+           0.7974755654714004,
+           0.754509430685139,
+           0.7244488545137499,
+           0.706620324066491,
+           0.7000743344828666,
+           0.7036151430007362,
+           0.7158360188911913,
+           0.7351590591231532,
+           0.7598785338552219,
+           0.7882066463256313,
+           0.8183205403081575,
+           0.8484093662041957,
+           0.8767202244995052,
+           0.9016018424373337,
+           0.9215449053237407,
+           0.9352180561555028,
+           0.941498693852812,
+           0.9394978382934883,
+           0.9285784860611077,
+           0.908367050377289,
+           0.8787576577904905,
+           0.8399092583114789,
+           0.7922356901728147,
+           0.736389020598714,
+           0.6732366553696801,
+           0.6038328682483651,
+           0.5293855425299157,
+           0.45121903755628046,
+           0.37073418997717217,
+           0.28936653043531557,
+           0.208543839442821,
+           0.12964418044246553,
+           0.05395553308326264,
+           -0.017361894010168886,
+           -0.083309663099521,
+           -0.14308050918373608,
+           -0.19608235378037178,
+           -0.24195628144863443,
+           -0.2805879874452504,
+           -0.3121123751970021,
+           -0.3369111609603228,
+           -0.3556035255872642,
+           -0.36903003509707616,
+           -0.3782302281492552,
+           -0.38441443504479833,
+           -0.3889305453102813,
+           -0.3932265753577562,
+           -0.39881000072473294,
+           -0.40720490608021376,
+           -0.41990806824058313,
+           -0.4383451212454051,
+           -0.46382795717735326,
+           -0.4975144916840271,
+           -0.5403718696201248,
+           -0.5931441051486561,
+           -0.6563250439845906,
+           -0.7301374058437362,
+           -0.8145185157639379,
+           -0.9091131674870355,
+           -1.0132738846302547,
+           -1.1260686603452157,
+           -1.24629606817042,
+           -1.3725074505221049,
+           -1.5030357113991073,
+           -1.636030070911548,
+           -1.769495985430972,
+           -1.9013393023838614,
+           -2.029413606389814,
+           -2.1515696264473783,
+           -2.2657055144414318,
+           -2.369816774951473,
+           -2.4620446260290905,
+           -2.5407216003912243,
+           -2.6044132557056474,
+           -2.6519549499585646,
+           -2.682482751225439,
+           -2.695457687803135,
+           -2.6906827013106427,
+           -2.6683118382336346,
+           -2.62885140027445,
+           -2.5731529662693644,
+           -2.5023983936522876,
+           -2.4180771007038215,
+           -2.32195611739324,
+           -2.216043567922563,
+           -2.1025464078098284,
+           -1.9838233785750745,
+           -1.8623342603610316,
+           -1.740586594236952,
+           -1.6210811092326862,
+           -1.5062571227548194,
+           -1.3984391860966894,
+           -1.299786219166646,
+           -1.212244320972118,
+           -1.1375043561939941,
+           -1.076965305451007,
+           -1.0317042303208364,
+           -1.002453547171754,
+           -0.9895861301833037,
+           -0.9931085778235369,
+           -1.0126627830324133,
+           -1.0475357501579015,
+           -1.0966774060999263,
+           -1.1587259638926948,
+           -1.2320402186938475,
+           -1.3147379931729506,
+           -1.4047398055473945,
+           -1.4998167124710602,
+           -1.5976411835498732,
+           -1.6958397967171521,
+           -1.7920465056416028,
+           -1.8839552226286183,
+           -1.9693704832294345,
+           -2.046255011365299,
+           -2.1127730848435347,
+           -2.167328708631023,
+           -2.2085977344534236,
+           -2.235553216922668,
+           -2.24748346468092,
+           -2.2440024258038647,
+           -2.2250522354485693,
+           -2.1908979457924884,
+           -2.1421146489495704,
+           -2.079567388071594,
+           -2.004384425714344,
+           -1.917924597509101,
+           -1.8217396193491375,
+           -1.7175323342719102,
+           -1.6071119781424137,
+           -1.4923476089009016,
+           -1.3751208809917645,
+           -1.257279353820476,
+           -1.1405915006127436,
+           -1.0267045325338244,
+           -0.9171060737482467,
+           -0.81309061832917,
+           -0.7157315722645,
+           -0.625859536522753,
+           -0.5440473239866888,
+           -0.4706020281788424,
+           -0.4055642795175419,
+           -0.34871463995607843,
+           -0.29958690393356685,
+           -0.257487897207833,
+           -0.22152319978129184,
+           -0.19062806892044204,
+           -0.16360270697210666,
+           -0.13915090957929774,
+           -0.11592104571863371,
+           -0.0925482638126604,
+           -0.0676967894255143,
+           -0.04010118042403359,
+           -0.00860543494014831,
+           0.02780109476655989,
+           0.06995194485832386,
+           0.11847679193669913,
+           0.1737804364403123,
+           0.23602808963464092,
+           0.3051373719471274,
+           0.38077725535565426,
+           0.46237400134531076,
+           0.5491239632035331,
+           0.6400129417643549,
+           0.7338416117012719,
+           0.8292563754789651,
+           0.9247848581812912,
+           1.0188751323101444,
+           1.1099376604772733,
+           1.1963888682953925,
+           1.276695211683027,
+           1.3494165835081229,
+           1.4132479145643808,
+           1.4670578631218816,
+           1.509923554806666,
+           1.54116042871923,
+           1.5603463642044686,
+           1.5673394026263312,
+           1.5622885364275438,
+           1.5456372097589193,
+           1.5181193567748197,
+           1.4807479907872978,
+           1.4347965451860714,
+           1.3817733506730634,
+           1.3233898083285622,
+           1.2615229799264422,
+           1.1981734616687965,
+           1.1354195314541249,
+           1.0753686597742125,
+           1.0201075477888046,
+           0.9716519011412862,
+           0.9318971634419704,
+           0.9025714185794284,
+           0.8851916263910143,
+           0.8810242827372002,
+           0.8910514944028366,
+           0.9159433338880195,
+           0.9560371920640026,
+           1.0113246814098455,
+           1.0814464631226175,
+           1.165695182173671,
+           1.263026499980878,
+           1.3720780195320605,
+           1.4911957072968263,
+           1.6184672347720843,
+           1.75176149447553,
+           1.8887733947615373,
+           2.0270729086883077,
+           2.164157247499905,
+           2.2975049516885755,
+           2.424630643999807,
+           2.54313917035112,
+           2.6507778669343525,
+           2.7454857344871795
+          ],
+          [
+           2.803574424860649,
+           2.8736617761100374,
+           2.9265948656420995,
+           2.961343680176931,
+           2.9772271064487223,
+           2.973926972376252,
+           2.951493897442989,
+           2.9103448305045303,
+           2.8512523505468543,
+           2.7753260011896925,
+           2.683986118218808,
+           2.578930786561755,
+           2.4620967245977896,
+           2.335615035605375,
+           2.201762885074188,
+           2.0629122556840525,
+           1.9214769967588516,
+           1.7798594204084073,
+           1.6403977015731712,
+           1.505315313729944,
+           1.3766736767944285,
+           1.2563291101909189,
+           1.145895074267605,
+           1.046710549975771,
+           0.9598152533327816,
+           0.8859322114718217,
+           0.825458045259677,
+           0.7784611140414439,
+           0.7446874857294862,
+           0.7235745049372486,
+           0.7142715478551523,
+           0.715667379592902,
+           0.7264233720043708,
+           0.7450117014147473,
+           0.7697575295494288,
+           0.7988840801203312,
+           0.8305594601241291,
+           0.8629440404288268,
+           0.8942372054281926,
+           0.922722306446559,
+           0.9468087074588311,
+           0.9650698931116929,
+           0.9762767158684288,
+           0.9794249885983426,
+           0.9737567777799803,
+           0.9587749168957569,
+           0.9342504353937506,
+           0.9002227813327556,
+           0.8569929008963599,
+           0.8051094206976432,
+           0.7453483546014736,
+           0.6786869212508225,
+           0.6062722074728428,
+           0.5293855425299158,
+           0.449403555527622,
+           0.3677569705209883,
+           0.2858882489319294,
+           0.20520921544938475,
+           0.12705980099244635,
+           0.05266900467336574,
+           -0.016880883169546907,
+           -0.08068584135021245,
+           -0.1380466171301194,
+           -0.18848945260831332,
+           -0.2317804773308773,
+           -0.2679333716353806,
+           -0.29721008088357204,
+           -0.320114542164946,
+           -0.33737956767187394,
+           -0.34994720811851365,
+           -0.35894309074987546,
+           -0.36564538531125335,
+           -0.3714491937765462,
+           -0.37782728203031296,
+           -0.38628817092681345,
+           -0.39833267765316366,
+           -0.4154100441901769,
+           -0.43887480667310735,
+           -0.4699455471081494,
+           -0.5096666274390337,
+           -0.5588739363523249,
+           -0.6181655831393168,
+           -0.6878783527425303,
+           -0.7680705947609029,
+           -0.8585120601605243,
+           -0.9586810266779484,
+           -1.067768871702675,
+           -1.1846920643219527,
+           -1.3081113608741306,
+           -1.4364578054724244,
+           -1.5679649631143227,
+           -1.7007066525533787,
+           -1.8326393031260657,
+           -1.9616479378177685,
+           -2.085594687124432,
+           -2.2023686672304628,
+           -2.30993601353455,
+           -2.4063888477618938,
+           -2.4899919742212147,
+           -2.5592261478682623,
+           -2.6128268326572632,
+           -2.649817471418277,
+           -2.6695364157415207,
+           -2.67165681302015,
+           -2.656198914305578,
+           -2.6235344469223296,
+           -2.5743828854833755,
+           -2.5097996494124,
+           -2.431156449562276,
+           -2.340114196255764,
+           -2.238589061411506,
+           -2.1287124539262994,
+           -2.012785816066655,
+           -1.8932312756186185,
+           -1.7725392908176707,
+           -1.6532145000990812,
+           -1.5377210346052679,
+           -1.4284285670071486,
+           -1.3275603551275674,
+           -1.2371444934351126,
+           -1.158969510788205,
+           -1.0945453506517793,
+           -1.0450706428550929,
+           -1.011407026893904,
+           -0.9940611194263556,
+           -0.9931745370382119,
+           -1.008522193977676,
+           -1.0395188980384993,
+           -1.085234070883447,
+           -1.1444142266354516,
+           -1.215512659197401,
+           -1.2967256189438399,
+           -1.386034107273746,
+           -1.4812502867016955,
+           -1.5800673978471378,
+           -1.6801119954062271,
+           -1.7789972648397168,
+           -1.8743761612538599,
+           -1.9639931222199525,
+           -2.0457331467509294,
+           -2.117667102270672,
+           -2.178092218397253,
+           -2.2255668482704953,
+           -2.2589387219331556,
+           -2.2773660783380185,
+           -2.2803312388706494,
+           -2.267646371477142,
+           -2.2394513859607277,
+           -2.196204093033316,
+           -2.1386629475468135,
+           -2.0678628753673993,
+           -1.985084849204581,
+           -1.8918200273126697,
+           -1.7897293967283765,
+           -1.680599966502642,
+           -1.5662986337370448,
+           -1.4487248943156523,
+           -1.3297635899102287,
+           -1.2112388727400252,
+           -1.0948705300395531,
+           -0.9822337423126637,
+           -0.8747232550167883,
+           -0.773522824773327,
+           -0.6795806615810457,
+           -0.5935914313819,
+           -0.5159852126845439,
+           -0.4469236211129297,
+           -0.3863031312604737,
+           -0.3337654407462259,
+           -0.28871454153341775,
+           -0.2503399929023878,
+           -0.21764573325258837,
+           -0.1894836280814718,
+           -0.16459083254855192,
+           -0.1416299519490656,
+           -0.11923091455811628,
+           -0.09603343036621056,
+           -0.07072889720973187,
+           -0.04210063297548068,
+           -0.009061358462348028,
+           0.029313071072240668,
+           0.07375458854918826,
+           0.12477927251847631,
+           0.18266977779249483,
+           0.2474643189576231,
+           0.3189525154022355,
+           0.39667822739700354,
+           0.4799493301595805,
+           0.5678541913642777,
+           0.6592844418255456,
+           0.75296346355777,
+           0.8474798683057166,
+           0.9413251068025666,
+           1.0329342378428044,
+           1.1207287996107125,
+           1.2031606658236176,
+           1.2787557377037893,
+           1.3461563204460418,
+           1.4041610598282706,
+           1.4517613703126384,
+           1.4881733690763659,
+           1.5128644388747317,
+           1.525573673815931,
+           1.5263256127850906,
+           1.5154368316657296,
+           1.493515143541959,
+           1.46145134129539,
+           1.4204036048188062,
+           1.371774880762104,
+           1.3171837216544058,
+           1.258429238917895,
+           1.1974509764823444,
+           1.1362846445785248,
+           1.0770147634603189,
+           1.0217253514616578,
+           0.9724498487463578,
+           0.931121495849008,
+           0.8995253838478561,
+           0.8792533607121645,
+           0.871662916726989,
+           0.8778410823453102,
+           0.8985742564725572,
+           0.934324744814698,
+           0.985214629855884,
+           1.0510174201052251,
+           1.131157740693447,
+           1.2247191347319848,
+           1.3304598497761604,
+           1.4468362910339005,
+           1.572033637354965,
+           1.704002942078723,
+           1.8405038827873295,
+           1.9791521857963217,
+           2.117470636224953,
+           2.25294249556789,
+           2.383066088043349,
+           2.5054092861372066,
+           2.6176626254828936,
+           2.7176898095512225,
+           2.8035744248606482
+          ],
+          [
+           2.8548645119782243,
+           2.914487758432981,
+           2.956239306946293,
+           2.979306325400378,
+           2.983234697616886,
+           2.9679381249589563,
+           2.9336989371507434,
+           2.8811606077319922,
+           2.8113121662984004,
+           2.725464891570149,
+           2.625221851719265,
+           2.5124410268450723,
+           2.389192898934017,
+           2.2577135234382784,
+           2.1203542006533778,
+           1.9795289418749757,
+           1.837660973046088,
+           1.6971295361608214,
+           1.5602182357030403,
+           1.4290661342525213,
+           1.3056227292110376,
+           1.1916078432217576,
+           1.0884773367780705,
+           0.9973954058458889,
+           0.9192140636858582,
+           0.8544602285228374,
+           0.8033306516686213,
+           0.7656947287838265,
+           0.7411050449010861,
+           0.7288153163522494,
+           0.7278052144518282,
+           0.7368113910548593,
+           0.7543638789520085,
+           0.7788269140662369,
+           0.8084431246197474,
+           0.8413799572862034,
+           0.8757771636040386,
+           0.9097941526651502,
+           0.9416560286377313,
+           0.9696971736189932,
+           0.9924013064990973,
+           1.0084370451070026,
+           1.0166881194032316,
+           1.0162775247944196,
+           1.0065850631669213,
+           0.9872578909470798,
+           0.9582138740467834,
+           0.9196377343854861,
+           0.8719701571356192,
+           0.8158902072767505,
+           0.7522915739582575,
+           0.6822533172996615,
+           0.6070059306939006,
+           0.5278936489628258,
+           0.4463340259233087,
+           0.3637758717422088,
+           0.28165667924073023,
+           0.20136067811194264,
+           0.12417863662782758,
+           0.05127048235749469,
+           -0.016368262059139604,
+           -0.07793533300327829,
+           -0.1328450986333994,
+           -0.18074582274164744,
+           -0.2215303518940038,
+           -0.2553399298398551,
+           -0.28256102267353117,
+           -0.3038152208675827,
+           -0.31994246543967825,
+           -0.3319780205623385,
+           -0.34112377942812944,
+           -0.3487146399560768,
+           -0.3561808181487572,
+           -0.3650070762282784,
+           -0.37668992728538725,
+           -0.39269393588010615,
+           -0.4144082633193336,
+           -0.44310460640393545,
+           -0.4798976492154621,
+           -0.5257090896668278,
+           -0.581236217458001,
+           -0.6469259098289315,
+           -0.7229547787943253,
+           -0.8092160516535136,
+           -0.9053135992554314,
+           -1.0105633479192178,
+           -1.1240021255115458,
+           -1.2444038045881116,
+           -1.3703024204104033,
+           -1.5000217636882325,
+           -1.6317107815453735,
+           -1.7633839696519018,
+           -1.8929658075205524,
+           -2.0183381809544114,
+           -2.137389653325417,
+           -2.2480653928908585,
+           -2.348416538165522,
+           -2.4366477881837447,
+           -2.5111620392898275,
+           -2.5706009541251524,
+           -2.6138804402485745,
+           -2.640220133156719,
+           -2.6491661185494415,
+           -2.640606288131635,
+           -2.6147778981899226,
+           -2.572267086375351,
+           -2.5140002950197204,
+           -2.4412277441987746,
+           -2.3554992898584146,
+           -2.2586331869284324,
+           -2.1526784499282803,
+           -2.03987165987442,
+           -1.9225892024784614,
+           -1.8032960353156562,
+           -1.684492168056058,
+           -1.5686580978358107,
+           -1.458200469952115,
+           -1.3553992315690555,
+           -1.2623575130511635,
+           -1.1809554086739815,
+           -1.1128087373024673,
+           -1.0592337463806445,
+           -1.0212185820785218,
+           -0.9994021881062797,
+           -0.9940611194263556,
+           -1.0051045691584237,
+           -1.0320777119514237,
+           -1.0741732697343882,
+           -1.130251010853284,
+           -1.198864705891451,
+           -1.2782958875143535,
+           -1.3665936017428262,
+           -1.4616191980140925,
+           -1.5610950886172517,
+           -1.6626563173969426,
+           -1.7639037151702535,
+           -1.8624573865674108,
+           -1.9560092707250434,
+           -2.042373546423298,
+           -2.1195337101077127,
+           -2.1856852412894003,
+           -2.2392728818979784,
+           -2.279021691459987,
+           -2.303961195114224,
+           -2.3134421125959905,
+           -2.3071453391796792,
+           -2.285083039638527,
+           -2.247591908866931,
+           -2.1953188431692223,
+           -2.129199449667807,
+           -2.050429993323325,
+           -1.960433537482105,
+           -1.8608211708597033,
+           -1.7533493281114798,
+           -1.6398742998807618,
+           -1.5223050893404582,
+           -1.4025558043320272,
+           -1.2824987765597256,
+           -1.1639195719597808,
+           -1.048475000116018,
+           -0.9376551469333974,
+           -0.8327503458889338,
+           -0.7348238718575262,
+           -0.6446909911154571,
+           -0.5629048354828986,
+           -0.48974939187704086,
+           -0.42523971527733756,
+           -0.3691292878767535,
+           -0.3209242646716012,
+           -0.2799041705160552,
+           -0.24514845013283776,
+           -0.21556812482644516,
+           -0.1899416813848242,
+           -0.166954213080196,
+           -0.14523875241667356,
+           -0.12341868230879917,
+           -0.10015008801014909,
+           -0.07416291692298856,
+           -0.04429984725215863,
+           -0.009551828432160637,
+           0.030910655238893366,
+           0.07771143354360707,
+           0.13124831346840826,
+           0.19167910592959492,
+           0.25891439922328163,
+           0.33261728611091945,
+           0.4122100698080323,
+           0.4968877916742544,
+           0.5856382447399429,
+           0.6772679668872106,
+           0.7704335498622656,
+           0.8636774593472588,
+           0.9554674406618194,
+           1.0442384873883865,
+           1.1284362788280884,
+           1.2065609485529984,
+           1.2772100315889554,
+           1.3391194523786785,
+           1.391201459338073,
+           1.4325784835007314,
+           1.4626119967120683,
+           1.4809255666888,
+           1.4874214490012585,
+           1.4822902161359697,
+           1.46601309728278,
+           1.4393568850506075,
+           1.403361452397868,
+           1.359320109995065,
+           1.3087532163381366,
+           1.2533756256325446,
+           1.195058717424721,
+           1.1357878931559087,
+           1.0776165446752546,
+           1.0226175952160672,
+           0.9728337819547523,
+           0.9302278892398719,
+           0.8966341518102058,
+           0.8737120274620751,
+           0.8629034890684887,
+           0.8653949077245437,
+           0.8820844939316671,
+           0.9135561346408013,
+           0.9600603137581151,
+           1.0215026360109702,
+           1.0974402929503226,
+           1.1870866197407905,
+           1.2893236969037636,
+           1.4027227570899423,
+           1.525571968022399,
+           1.6559109836066317,
+           1.7915714902539306,
+           1.930222828769898,
+           2.0694216473395515,
+           2.206664441279709,
+           2.339441762805126,
+           2.4652928408733468,
+           2.581859338326147,
+           2.686936991379652,
+           2.778523924628765,
+           2.854864511978225
+          ],
+          [
+           2.898922058493856,
+           2.947570913516963,
+           2.9777701470825937,
+           2.9889309972823366,
+           2.980830207243889,
+           2.953614110147052,
+           2.907794393603259,
+           2.8442356560548534,
+           2.764135062346449,
+           2.668994592509677,
+           2.5605865525466225,
+           2.440913174358441,
+           2.312161270110706,
+           2.176653020920899,
+           2.036794068041319,
+           1.895020134585192,
+           1.7537434358967763,
+           1.6153001362220851,
+           1.4819000784698322,
+           1.355579953382035,
+           1.238160985906562,
+           1.131212102212143,
+           1.0360194034733472,
+           0.9535626157016266,
+           0.8844990124059784,
+           0.8291551230079016,
+           0.7875263492563526,
+           0.7592844190946841,
+           0.7437924172704197,
+           0.7401269491226864,
+           0.7471068229130529,
+           0.7633274809639957,
+           0.7872002745116452,
+           0.8169955648450659,
+           0.8508885466943781,
+           0.8870066310024062,
+           0.9234771945326705,
+           0.9584745038676856,
+           0.9902646511311916,
+           1.0172473973841483,
+           1.0379939055393599,
+           1.051279455579919,
+           1.0561103679996335,
+           1.0517445133088572,
+           1.0377049523049662,
+           1.0137864293659067,
+           0.9800546248018004,
+           0.9368382576604891,
+           0.8847143126641839,
+           0.8244868395773145,
+           0.7571599358914634,
+           0.6839056701918114,
+           0.6060278302810748,
+           0.524922483923313,
+           0.4420364183527713,
+           0.3588245755379705,
+           0.2767076223561128,
+           0.1970307877978534,
+           0.12102506330287563,
+           0.0497717982672805,
+           -0.01582836768550477,
+           -0.07508140860395321,
+           -0.12751996089377302,
+           -0.17291697879307955,
+           -0.21129262583744687,
+           -0.2429142082748614,
+           -0.26828913822811407,
+           -0.2881510967019358,
+           -0.3034397446659423,
+           -0.31527449988642803,
+           -0.3249230536211315,
+           -0.33376544074622505,
+           -0.34325459579374573,
+           -0.35487442269394964,
+           -0.37009647528491557,
+           -0.39033638706800206,
+           -0.4169112011475318,
+           -0.4509987344181589,
+           -0.49360006421208447,
+           -0.5455061518776636,
+           -0.6072695179199462,
+           -0.6791817598395063,
+           -0.7612575597033091,
+           -0.8532256673377258,
+           -0.9545271708499671,
+           -1.0643211832961181,
+           -1.1814978872837991,
+           -1.3046986928011624,
+           -1.4323430822737786,
+           -1.5626615453199977,
+           -1.6937338482230142,
+           -1.8235317437426404,
+           -1.9499651090892005,
+           -2.0709304066842256,
+           -2.1843602961412185,
+           -2.288273188451464,
+           -2.380821525683326,
+           -2.460337591888731,
+           -2.5253757129048813,
+           -2.5747497831538038,
+           -2.6075651644825957,
+           -2.6232441329984284,
+           -2.6215442015811172,
+           -2.60256881462867,
+           -2.5667700935032376,
+           -2.514943501661671,
+           -2.448214492922242,
+           -2.368017399975752,
+           -2.276067008347055,
+           -2.1743234389313333,
+           -2.0649511255917075,
+           -1.9502728190855432,
+           -1.8327196712106357,
+           -1.7147785504953321,
+           -1.5989378105765542,
+           -1.487632772872496,
+           -1.383192195233658,
+           -1.2877869776644972,
+           -1.203382305416081,
+           -1.1316943499661836,
+           -1.0741525415465927,
+           -1.0318682955314074,
+           -1.0056109223486442,
+           -0.9957912803263581,
+           -1.002453547171753,
+           -1.0252752930737972,
+           -1.0635758414037288,
+           -1.116332706454243,
+           -1.1822057063848586,
+           -1.2595681681742963,
+           -1.346544474322256,
+           -1.4410530523406884,
+           -1.5408537813236645,
+           -1.643598688139673,
+           -1.746884731489171,
+           -1.848307426976543,
+           -1.9455140515042817,
+           -2.0362551810096234,
+           -2.11843336138233,
+           -2.1901477871386326,
+           -2.2497339641868264,
+           -2.2957974592479293,
+           -2.327240986037511,
+           -2.343284243500616,
+           -2.3434761001221704,
+           -2.3276989061858715,
+           -2.296164908185188,
+           -2.2494049316597637,
+           -2.1882496858146374,
+           -2.1138042207868906,
+           -2.0274162320099385,
+           -1.9306390517989331,
+           -1.8251902925029362,
+           -1.7129072053411232,
+           -1.5956998919744751,
+           -1.4755035502455547,
+           -1.3542309503430496,
+           -1.2337263226487716,
+           -1.1157217941765714,
+           -1.0017974380195083,
+           -0.8933459014849885,
+           -0.7915424561688724,
+           -0.6973211702349111,
+           -0.6113577432676371,
+           -0.5340593713129045,
+           -0.46556182848005595,
+           -0.4057337663275143,
+           -0.35418804785266406,
+           -0.31029975389249664,
+           -0.27323033060702456,
+           -0.2419571917002139,
+           -0.2153079520102764,
+           -0.19199835349228137,
+           -0.17067285329829937,
+           -0.14994677889716387,
+           -0.128448918560524,
+           -0.10486340795799942,
+           -0.07796979520459858,
+           -0.04668021690613043,
+           -0.010072695251701331,
+           0.032580330981553024,
+           0.08178900314243383,
+           0.1378291837727826,
+           0.20073219785880522,
+           0.2702814575713486,
+           0.3460160739296016,
+           0.4272413761737044,
+           0.5130460788401772,
+           0.6023256621915904,
+           0.6938113681896861,
+           0.7861040657793148,
+           0.8777121096538864,
+           0.9670922092151183,
+           1.0526922418805018,
+           1.1329948893675477,
+           1.2065609485529984,
+           1.272071170711698,
+           1.3283655143941044,
+           1.3744787571782209,
+           1.4096714985889494,
+           1.4334556984906341,
+           1.4456140294726316,
+           1.4462124748464713,
+           1.435605772060875,
+           1.414435480436082,
+           1.3836206376585936,
+           1.3443411568283006,
+           1.298014300322893,
+           1.2462647437128243,
+           1.190888907973332,
+           1.1338143871363746,
+           1.0770554275349544,
+           1.0226655206317858,
+           0.9726882513797157,
+           0.9291075960552229,
+           0.8937988861524268,
+           0.8684816475611492,
+           0.8546754869603332,
+           0.8536601309609098,
+           0.8664406295761458,
+           0.8937186163140843,
+           0.9358703754388845,
+           0.9929323061595247,
+           1.0645941975766784,
+           1.150200541434267,
+           1.2487599166397878,
+           1.3589622848591363,
+           1.4792038450270115,
+           1.6076189110419137,
+           1.7421181057475854,
+           1.8804320097549245,
+           2.020159269541916,
+           2.158818058899154,
+           2.293899703901155,
+           2.4229232262694227,
+           2.543489534641598,
+           2.65333399853105,
+           2.7503761755589013,
+           2.8327655280256603,
+           2.8989220584938558
+          ],
+          [
+           2.935374317627761,
+           2.972631342899679,
+           2.9910052254006354,
+           2.990136266743473,
+           2.970033978406331,
+           2.9310761155875373,
+           2.873999430960884,
+           2.799882377273031,
+           2.7101201783383124,
+           2.606392868291424,
+           2.4906270645796824,
+           2.364952387100614,
+           2.2316535605649026,
+           2.0931193365848313,
+           1.9517894437712908,
+           1.810100816565034,
+           1.670434365648309,
+           1.535063534343896,
+           1.4061058369231014,
+           1.285478497461517,
+           1.1748592037561367,
+           1.075652862460394,
+           0.9889650922066792,
+           0.9155830247821629,
+           0.8559638045357053,
+           0.8102309875703588,
+           0.7781788495728044,
+           0.7592844190946838,
+           0.7527268664511924,
+           0.7574137017167503,
+           0.7720130728971708,
+           0.7949913112010131,
+           0.8246547479182114,
+           0.8591947296941381,
+           0.8967346882958015,
+           0.9353780789630002,
+           0.9732559890638637,
+           1.008573236237155,
+           1.0396518219666315,
+           1.0649706813322606,
+           1.0832007705608575,
+           1.0932346583514394,
+           1.0942099315957432,
+           1.0855258873698321,
+           1.0668531568500996,
+           1.038136088712917,
+           0.9995879050243643,
+           0.9516788269475329,
+           0.8951175461594892,
+           0.8308265862000529,
+           0.7599122518561788,
+           0.6836300002741063,
+           0.6033461814064532,
+           0.5204971848120792,
+           0.4365470925207458,
+           0.3529449721146477,
+           0.27108294953879475,
+           0.19225617733847106,
+           0.11762576167492783,
+           0.0481856319482885,
+           -0.01526576779934829,
+           -0.07214821364407063,
+           -0.12211625698616914,
+           -0.165069156325006,
+           -0.20115391495626647,
+           -0.23076133416754255,
+           -0.2545151741478272,
+           -0.27325469524654356,
+           -0.28801102583597615,
+           -0.29997796543412775,
+           -0.31047797880011885,
+           -0.3209242646716013,
+           -0.332779888401816,
+           -0.34751504826130236,
+           -0.3665635985128934,
+           -0.3912799771466038,
+           -0.4228976816881522,
+           -0.46249040282064496,
+           -0.510936863466733,
+           -0.5688903219669662,
+           -0.636753584236055,
+           -0.7146602340840169,
+           -0.8024626366107901,
+           -0.8997271005502724,
+           -1.0057364058590574,
+           -1.119499717195669,
+           -1.23976971685772,
+           -1.3650666069230817,
+           -1.49370845439118,
+           -1.6238471894702975,
+           -1.7535094199374015,
+           -1.8806410974396224,
+           -2.003154967948261,
+           -2.118979660979284,
+           -2.226109222679157,
+           -2.3226518777676115,
+           -2.4068768152301443,
+           -2.4772578324177488,
+           -2.532512740955836,
+           -2.5716375339832664,
+           -2.593934435450001,
+           -2.599033095586472,
+           -2.5869043587531544,
+           -2.557866206749243,
+           -2.5125816679969515,
+           -2.4520486762471854,
+           -2.377582056845099,
+           -2.290788009383502,
+           -2.1935316380732996,
+           -2.0878982508830983,
+           -1.9761493012627407,
+           -1.860673978296659,
+           -1.7439375591641313,
+           -1.628427719133824,
+           -1.5166000469572039,
+           -1.4108240361227042,
+           -1.3133308143956477,
+           -1.2261638355564004,
+           -1.1511336891654844,
+           -1.0897780881592696,
+           -1.043327972428794,
+           -1.0126805222012594,
+           -0.9983797115293216,
+           -1.000604853467912,
+           -1.019167398926206,
+           -1.0535160553326557,
+           -1.1027500939063586,
+           -1.1656405202860591,
+           -1.2406585972442175,
+           -1.3260110347244443,
+           -1.4196810056938758,
+           -1.5194740100920987,
+           -1.6230674967736232,
+           -1.728063067483695,
+           -1.8320400296268105,
+           -1.9326090372301183,
+           -2.0274645626813945,
+           -2.114434975394904,
+           -2.191529066645053,
+           -2.25697795079879,
+           -2.3092713897848607,
+           -2.3471877269450623,
+           -2.369816774951474,
+           -2.376575176309099,
+           -2.367213939791553,
+           -2.341818047411764,
+           -2.300798219494622,
+           -2.2448751153459963,
+           -2.175056429239611,
+           -2.092607511506816,
+           -1.9990162982617912,
+           -1.8959534669861047,
+           -1.785228845596423,
+           -1.6687451870762047,
+           -1.5484504782638069,
+           -1.4262899786510155,
+           -1.3041591824807022,
+           -1.183858865207241,
+           -1.0670533144001868,
+           -0.9552327570471978,
+           -0.8496808822340826,
+           -0.751448223250409,
+           -0.6613320097313751,
+           -0.579862932397837,
+           -0.5072990845515102,
+           -0.4436271602249247,
+           -0.38857080341811806,
+           -0.3416058208397937,
+           -0.3019817965777469,
+           -0.2687494855119032,
+           -0.2407932170949164,
+           -0.2168674159838359,
+           -0.19563624402715946,
+           -0.175715291823913,
+           -0.15571419935610625,
+           -0.13427906523839442,
+           -0.11013351339020115,
+           -0.08211732414166743,
+           -0.049221602932994456,
+           -0.010619552151981869,
+           0.03430797208789985,
+           0.08595279926174208,
+           0.14446620629094808,
+           0.2097524603258338,
+           0.2814693235445467,
+           0.35903551905031816,
+           0.4416449748404224,
+           0.5282874852362167,
+           0.6177752606164407,
+           0.708774681071983,
+           0.7998424316532736,
+           0.8894650797332536,
+           0.9761010616602371,
+           1.0582239787307814,
+           1.1343660633211319,
+           1.2031606658236182,
+           1.2633826321603985,
+           1.3139854896738796,
+           1.3541344349760962,
+           1.38323421903517,
+           1.4009511498883864,
+           1.4072285788097294,
+           1.4022953979201838,
+           1.3866672520816234,
+           1.361140351103284,
+           1.326777955239793,
+           1.2848897929941945,
+           1.2370048506932987,
+           1.1848381436409336,
+           1.1302522345837125,
+           1.075214402800457,
+           1.0217504828553645,
+           0.9718964829771478,
+           0.9276491567934059,
+           0.8909167370820933,
+           0.8634710453344541,
+           0.8469021660269385,
+           0.8425768200894032,
+           0.8516014893816828,
+           0.8747912350017358,
+           0.912645019552706,
+           0.96532819029235,
+           1.0326626100884715,
+           1.1141247404430092,
+           1.2088517899806108,
+           1.315655847391202,
+           1.4330457246321804,
+           1.5592560489753327,
+           1.6922829658278535,
+           1.829925652515366,
+           1.9698327003768825,
+           2.10955230211777,
+           2.2465850863810175,
+           2.378438374293107,
+           2.5026805950040774,
+           2.6169945899344165,
+           2.719228558783946,
+           2.8074434538159263,
+           2.879955711232578,
+           2.935374317627761
+          ],
+          [
+           2.96391288677283,
+           2.9894570240085767,
+           2.995832567148905,
+           2.982911936658756,
+           2.9509373520855275,
+           2.9005148229129447,
+           2.832599969899968,
+           2.7484760201951044,
+           2.649724504634712,
+           2.538189357829878,
+           2.4159352767436726,
+           2.2852013277044394,
+           2.1483509019495175,
+           2.00781920319898,
+           1.86605950542965,
+           1.7254894436713821,
+           1.588438594732772,
+           1.4570985684856204,
+           1.3334767646436192,
+           1.219354856529326,
+           1.116252944481138,
+           1.0254001802756534,
+           0.9477125037437009,
+           0.8837779576126379,
+           0.8338498608459511,
+           0.7978479289592801,
+           0.7753672366950924,
+           0.7656947287838265,
+           0.7678328029604513,
+           0.7805293203851512,
+           0.8023132462591108,
+           0.8315349914340591,
+           0.8664104173783456,
+           0.905067384583491,
+           0.9455936703204542,
+           0.9860850568299093,
+           1.024692396070723,
+           1.0596664918277774,
+           1.0893997033308338,
+           1.1124632648860966,
+           1.1276394310291682,
+           1.1339476934211712,
+           1.1306644706432876,
+           1.1173358412665424,
+           1.0937830698021571,
+           1.0601008598516877,
+           1.0166484543248822,
+           0.9640338843150148,
+           0.9030918415586476,
+           0.8348558100197693,
+           0.7605252360139046,
+           0.6814286398387919,
+           0.5989836720329753,
+           0.5146551916620757,
+           0.4299124906077193,
+           0.3461868055777526,
+           0.2648302480660041,
+           0.18707724209881774,
+           0.1140094913739581,
+           0.0465254030853258,
+           -0.014685222250286399,
+           -0.06916056428027703,
+           -0.11667970469085,
+           -0.15726875146668673,
+           -0.19119999733233645,
+           -0.21898412633208472,
+           -0.2413556644015796,
+           -0.25925204679841723,
+           -0.2737868428926565,
+           -0.28621783280866503,
+           -0.29791076683454826,
+           -0.31029975389249564,
+           -0.3248453167373631,
+           -0.34299121656819254,
+           -0.36612118670545724,
+           -0.39551672291686785,
+           -0.4323170566069083,
+           -0.4774823868966704,
+           -0.5317613698127225,
+           -0.5956637592743234,
+           -0.6694389678636017,
+           -0.7530611686161622,
+           -0.8462213959206211,
+           -0.948326928124037,
+           -1.0585080509820832,
+           -1.1756321142525092,
+           -1.2983246081868092,
+           -1.4249968070836054,
+           -1.5538793579463466,
+           -1.6830610379028006,
+           -1.8105317683030764,
+           -1.9342288597682937,
+           -2.0520853738231,
+           -2.1620794254057136,
+           -2.2622832181291166,
+           -2.3509106015711514,
+           -2.4263619672662573,
+           -2.487265356879427,
+           -2.532512740955836,
+           -2.561290537649833,
+           -2.57310357528638,
+           -2.5677918572529745,
+           -2.5455396588105836,
+           -2.5068766687841744,
+           -2.4526710802713905,
+           -2.384114728815133,
+           -2.3027005691590468,
+           -2.2101929680131316,
+           -2.1085914656173457,
+           -2.0000888189824595,
+           -1.8870242805584876,
+           -1.77183318424478,
+           -1.6569940031812243,
+           -1.544974108338648,
+           -1.438175491936491,
+           -1.3388817242556892,
+           -1.2492073863326085,
+           -1.1710511649117894,
+           -1.1060537112356235,
+           -1.0555612537954513,
+           -1.0205958197520864,
+           -1.0018327636351405,
+           -0.9995861289362455,
+           -1.013802182523997,
+           -1.0440612679407695,
+           -1.0895879263072004,
+           -1.1492690375565893,
+           -1.2216795448127815,
+           -1.3051151455244565,
+           -1.3976311688251406,
+           -1.4970867134791512,
+           -1.6011929982085935,
+           -1.707564779129132,
+           -1.8137736197794996,
+           -1.9174017594544044,
+           -2.0160953161613206,
+           -2.1076155816911615,
+           -2.1898872174436255,
+           -2.2610422394687615,
+           -2.319458787662626,
+           -2.3637938045219515,
+           -2.3930089000702974,
+           -2.406388847761897,
+           -2.403552337183796,
+           -2.3844547987390396,
+           -2.349383308533599,
+           -2.2989437736565512,
+           -2.2340407842214094,
+           -2.1558506943647853,
+           -2.065788655579711,
+           -1.9654704683695081,
+           -1.8566702387865417,
+           -1.7412749220637542,
+           -1.621236903974786,
+           -1.498525810169352,
+           -1.3750807436419248,
+           -1.2527641305588328,
+           -1.1333183054903715,
+           -1.0183258899922727,
+           -0.9091749154708709,
+           -0.8070295150021892,
+           -0.7128068624868816,
+           -0.627160874930059,
+           -0.5504730188575802,
+           -0.4828503793338855,
+           -0.4241309643306361,
+           -0.37389603298169183,
+           -0.3314890581721945,
+           -0.29604076641015364,
+           -0.2664995452078013,
+           -0.241666374068811,
+           -0.22023332297624248,
+           -0.20082457478936921,
+           -0.18203886734538063,
+           -0.16249221880663076,
+           -0.1408597966633444,
+           -0.11591581683004794,
+           -0.08657041376260925,
+           -0.05190250405697316,
+           -0.01118777247617031,
+           0.03607896193240765,
+           0.09016759430222326,
+           0.1511032288091141,
+           0.2186635778284943,
+           0.2923833427341757,
+           0.37156547107598187,
+           0.45529900484576336,
+           0.5424830616674476,
+           0.6318563294207964,
+           0.7220313091361404,
+           0.8115324146921667,
+           0.8988369341402096,
+           0.9824177790289378,
+           1.060786896942332,
+           1.1325381999367303,
+           1.196388868295393,
+           1.2512179249028086,
+           1.2961010397341712,
+           1.3303406149034396,
+           1.3534903161874232,
+           1.3653733540949746,
+           1.3660939729823152,
+           1.3560417765658952,
+           1.3358886982221716,
+           1.3065786101948627,
+           1.2693097526090757,
+           1.2255103463356358,
+           1.1768079286572393,
+           1.1249931129549262,
+           1.0719786191589709,
+           1.0197545468012457,
+           0.9703409639749022,
+           0.9257389607431504,
+           0.8878813625777604,
+           0.8585843169838386,
+           0.8395009540427782,
+           0.8320782793861801,
+           0.8375183870457235,
+           0.8567449813701155,
+           0.8903760741007214,
+           0.9387035777118389,
+           1.0016803527577258,
+           1.0789150891955503,
+           1.1696752138044868,
+           1.2728978224866612,
+           1.3872084421501225,
+           1.5109472367992767,
+           1.6422020910654678,
+           1.7788478361658082,
+           1.91859073233095,
+           2.0590171918228695,
+           2.1976456209910578,
+           2.3319801810176126,
+           2.4595652170498647,
+           2.578039085578975,
+           2.685186120722607,
+           2.7789855212874657,
+           2.8576560111534346,
+           2.9196952239457845,
+           2.963912886772831
+          ],
+          [
+           2.9842963167202425,
+           2.9979056039677654,
+           2.992211330831814,
+           2.9673191281297484,
+           2.923701894381476,
+           2.8621887944884454,
+           2.7839462685945615,
+           2.6904515058636016,
+           2.5834590159645425,
+           2.464961093685994,
+           2.3371431153621147,
+           2.2023347262201844,
+           2.0629580724513303,
+           1.92147429849054,
+           1.7803295670880157,
+           1.641901866406009,
+           1.5084498444756298,
+           1.3820648575379775,
+           1.264627336447908,
+           1.1577684665090442,
+           1.062838043554674,
+           0.9808792160888078,
+           0.9126106536498185,
+           0.8584164994532663,
+           0.8183442753070068,
+           0.792110713453914,
+           0.7791152981404316,
+           0.7784611140414429,
+           0.7889824237398118,
+           0.8092782365340149,
+           0.8377509898212386,
+           0.8726493455921586,
+           0.912114011033754,
+           0.9542254260951418,
+           0.9970521236714605,
+           1.0386985606252042,
+           1.077351240274725,
+           1.1113219985772889,
+           1.1390874056362783,
+           1.1593233392981406,
+           1.1709339157680017,
+           1.1730741100895559,
+           1.1651655632460534,
+           1.1469052483948496,
+           1.1182668519116363,
+           1.0794949108792105,
+           1.0310919327362829,
+           0.9737989003868788,
+           0.9085697327141707,
+           0.8365404219797036,
+           0.7589937022412879,
+           0.6773202133912783,
+           0.5929772109639989,
+           0.5074459303788846,
+           0.42218874434806847,
+           0.33860725307429335,
+           0.2580024186215803,
+           0.18153779821451704,
+           0.11020684768309368,
+           0.04480515796583538,
+           -0.014091642716364086,
+           -0.0661437373781172,
+           -0.11125629970030258,
+           -0.14958175917294758,
+           -0.18151508761295662,
+           -0.2076822252760232,
+           -0.22892194439657365,
+           -0.24626162009969854,
+           -0.2608875388602014,
+           -0.27411051895858396,
+           -0.2873277420243783,
+           -0.3019817965777463,
+           -0.3195180108671038,
+           -0.34134120127780143,
+           -0.3687729828666913,
+           -0.403010779592427,
+           -0.4450896337296712,
+           -0.4958478476769979,
+           -0.5558973985031669,
+           -0.6255999484049926,
+           -0.7050491356667845,
+           -0.7940596741531747,
+           -0.8921636187279713,
+           -0.9986139735260725,
+           -1.1123956342218493,
+           -1.2322434689873318,
+           -1.3566671603940252,
+           -1.483982256670644,
+           -1.6123467198675503,
+           -1.7398021146651896,
+           -1.8643184584499521,
+           -1.9838416540106028,
+           -2.096342353338755,
+           -2.1998650564536026,
+           -2.2925762341206712,
+           -2.372810278271481,
+           -2.4391121285883037,
+           -2.4902754970883643,
+           -2.5253757129048826,
+           -2.5437963344245538,
+           -2.5452488224947944,
+           -2.5297847330110588,
+           -2.49780006583267,
+           -2.4500315952976783,
+           -2.387545201008562,
+           -2.3117164113012523,
+           -2.224203561134168,
+           -2.126914146384325,
+           -2.021965123274037,
+           -1.9116380507575368,
+           -1.798330101483638,
+           -1.684502070248523,
+           -1.5726245850879392,
+           -1.4651237734203393,
+           -1.3643276527374242,
+           -1.2724145017841124,
+           -1.191364424262136,
+           -1.122915243863086,
+           -1.0685237686387177,
+           -1.0293333367767403,
+           -1.0061484078145349,
+           -0.9994167967791868,
+           -1.0092199677322438,
+           -1.035271612118939,
+           -1.0769245408189694,
+           -1.1331857216462693,
+           -1.202739101041078,
+           -1.2839756645289522,
+           -1.3750300196601895,
+           -1.4738226317334133,
+           -1.5781067103637365,
+           -1.6855186370724238,
+           -1.7936307431459872,
+           -1.9000051949701973,
+           -2.002247722110989,
+           -2.098059932072401,
+           -2.1852889946440097,
+           -2.261973547045526,
+           -2.3263847669562807,
+           -2.377061681577356,
+           -2.4128399240977485,
+           -2.432873310764679,
+           -2.4366477881837456,
+           -2.4239874871364013,
+           -2.3950528114963574,
+           -2.350330684018967,
+           -2.2906172601219144,
+           -2.2169936016299068,
+           -2.1307949703978943,
+           -2.033574552662396,
+           -1.927062555233648,
+           -1.8131217210866761,
+           -1.6937003919873934,
+           -1.5707842976096595,
+           -1.446348272974371,
+           -1.3223090985189032,
+           -1.2004806199732385,
+           -1.082532239503231,
+           -0.9699517770127315,
+           -0.8640135834716748,
+           -0.7657526496560636,
+           -0.6759452972757731,
+           -0.5950968690939966,
+           -0.5234366546145114,
+           -0.46092010276934225,
+           -0.4072381874365852,
+           -0.3618336102165368,
+           -0.32392335223992375,
+           -0.29252692719328294,
+           -0.26649954520780117,
+           -0.24456927531879005,
+           -0.22537719589124902,
+           -0.20751945015291584,
+           -0.1895900795523402,
+           -0.1702234921370955,
+           -0.14813543686970224,
+           -0.12216139737391653,
+           -0.09129138891418484,
+           -0.05470023864143547,
+           -0.01177254882320139,
+           0.03787831713960982,
+           0.09439772919061741,
+           0.15768409911348846,
+           0.22739015828038744,
+           0.30293117759924126,
+           0.3834999209425846,
+           0.46808794691736283,
+           0.5555127071336898,
+           0.6444497363908133,
+           0.7334690953100397,
+           0.8210751123497046,
+           0.9057483827456588,
+           0.9859889190339326,
+           1.0603593130673499,
+           1.1275267637656925,
+           1.1863028484396867,
+           1.2356799678669241,
+           1.2748634751142804,
+           1.3032986034448917,
+           1.3206914369230778,
+           1.3270233153619564,
+           1.3225582293693106,
+           1.3078429373502762,
+           1.2836997200257398,
+           1.2512118747283851,
+           1.2117022367653563,
+           1.166705193840862,
+           1.1179328274145712,
+           1.067235967694591,
+           1.0165610828547247,
+           0.9679040346163775,
+           0.9232618186863801,
+           0.8845834674544107,
+           0.853721322266976,
+           0.8323838826650837,
+           0.822091410096317,
+           0.8241354044277397,
+           0.8395429844618113,
+           0.8690470906565266,
+           0.913063292082105,
+           0.9716738235978242,
+           1.0446193070910046,
+           1.1312984265780188,
+           1.2307756355195973,
+           1.341796780536241,
+           1.4628123335869543,
+           1.5920077393166554,
+           1.7273402102478221,
+           1.8665811440816478,
+           2.0073631984976705,
+           2.1472309429388092,
+           2.283693916821412,
+           2.4142808616665725,
+           2.5365938623713906,
+           2.648361131063745,
+           2.7474871957986813,
+           2.832099315098483,
+           2.90058902661491,
+           2.951647851905384,
+           2.9842963167202425
+          ],
+          [
+           2.99635215442904,
+           2.997905603967766,
+           2.980172153747235,
+           2.9434897633724315,
+           2.8885580295905355,
+           2.8164222858572345,
+           2.7284499593737532,
+           2.626299747926154,
+           2.511884348347421,
+           2.3873276201105864,
+           2.2549171977741467,
+           2.1170536715939607,
+           1.9761975340485816,
+           1.8348151394248602,
+           1.6953249428179877,
+           1.5600452734963806,
+           1.4311448558993707,
+           1.3105972206487173,
+           1.200140049653217,
+           1.1012403761283955,
+           1.0150664152090938,
+           0.9424666374028386,
+           0.8839565194605942,
+           0.8397132197162639,
+           0.8095782321888871,
+           0.7930678804935547,
+           0.7893913236129769,
+           0.7974755654713991,
+           0.8159967934271701,
+           0.8434172213236918,
+           0.8780264842372643,
+           0.9179865276346761,
+           0.9613788558010049,
+           1.0062529549536403,
+           1.0506746865482608,
+           1.0927734562989009,
+           1.1307870040255106,
+           1.1631027275242105,
+           1.1882945484375251,
+           1.2051544471344522,
+           1.2127179338454948,
+           1.2102828811666835,
+           1.1974213145487032,
+           1.173983938190143,
+           1.1400973593028563,
+           1.0961541593478865,
+           1.0427961418954592,
+           0.9808912587084364,
+           0.9115048741881104,
+           0.83586616950038,
+           0.7553306080070722,
+           0.6713394800783955,
+           0.5853776155781218,
+           0.4989303945751886,
+           0.41344120013018404,
+           0.3302704410482351,
+           0.2506572277322512,
+           0.17568471188745588,
+           0.10625000268867514,
+           0.04303945064194774,
+           -0.01349005114903607,
+           -0.06312325665831284,
+           -0.10589192647486506,
+           -0.1420732148769963,
+           -0.17218112451682227,
+           -0.1969512501964608,
+           -0.2173192090303711,
+           -0.23439332003849386,
+           -0.2494222476877256,
+           -0.2637584572376765,
+           -0.2788184415483749,
+           -0.29604076641015364,
+           -0.31684304220933307,
+           -0.34257896226612594,
+           -0.37449655160112044,
+           -0.41369874406270807,
+           -0.46110735127432567,
+           -0.5174314050529638,
+           -0.58314074781367,
+           -0.6584456156526516,
+           -0.743282809512212,
+           -0.8373088847861803,
+           -0.9399006130388031,
+           -1.0501627855971303,
+           -1.1669432422397497,
+           -1.288854823722157,
+           -1.414303769087396,
+           -1.541523912089477,
+           -1.6686158798161617,
+           -1.7935903645724287,
+           -1.9144144306406374,
+           -2.0290597334772262,
+           -2.1355514724220135,
+           -2.232016870586092,
+           -2.316731978030786,
+           -2.388165626694004,
+           -2.445019427061989,
+           -2.486262785896288,
+           -2.511162039289829,
+           -2.5193029331829306,
+           -2.5106058408882754,
+           -2.485333280330231,
+           -2.4440894783784075,
+           -2.3878119213341393,
+           -2.317755024616827,
+           -2.235466246232322,
+           -2.1427551529786557,
+           -2.04165612101214,
+           -1.9343855090984652,
+           -1.8232942797319227,
+           -1.7108171569277384,
+           -1.5994194970500557,
+           -1.4915431083389417,
+           -1.3895522843449766,
+           -1.2956813154961382,
+           -1.2119847114868452,
+           -1.1402913058175848,
+           -1.082163324084114,
+           -1.0388613816716192,
+           -1.0113162371493831,
+           -1.0001079682586562,
+           -1.0054530618062374,
+           -1.0271997212817396,
+           -1.064831501163337,
+           -1.1174791794014622,
+           -1.183940584273076,
+           -1.2627079034272661,
+           -1.3520018260724702,
+           -1.4498117081794013,
+           -1.553940809196028,
+           -1.662055530512021,
+           -1.7717374936210346,
+           -1.8805372318233333,
+           -1.9860282349094414,
+           -2.085860082359252,
+           -2.1778094272233592,
+           -2.259827649318739,
+           -2.330084081232738,
+           -2.3870038217572507,
+           -2.42929928599487,
+           -2.455994796147019,
+           -2.4664436880748797,
+           -2.460337591888732,
+           -2.4377077355513057,
+           -2.398918314079924,
+           -2.344652158642569,
+           -2.275889124963003,
+           -2.1938777944501506,
+           -2.100101240101543,
+           -1.9962377486425928,
+           -1.88411750717911,
+           -1.7656763540521776,
+           -1.6429077574195068,
+           -1.517814219860728,
+           -1.3923593122541276,
+           -1.268421515279133,
+           -1.1477509928820204,
+           -1.0319303403450282,
+           -0.9223402423469059,
+           -0.8201308463540579,
+           -0.7261995071545189,
+           -0.6411753931388098,
+           -0.5654112682216894,
+           -0.49898257954421477,
+           -0.4416937949211744,
+           -0.3930917500793642,
+           -0.35248558867755486,
+           -0.3189727123386873,
+           -0.29147000759693853,
+           -0.268749485511903,
+           -0.24947736098670134,
+           -0.23225551523636648,
+           -0.21566422844275812,
+           -0.1983050417725583,
+           -0.17884260927668538,
+           -0.15604443064905904,
+           -0.1288174145842484,
+           -0.09624030801034626,
+           -0.057591136585808125,
+           -0.01236893372056491,
+           0.03969081435023592,
+           0.09860741507161183,
+           0.1641531400634199,
+           0.23585837086206768,
+           0.31302358868383523,
+           0.39473789780385776,
+           0.4799036008182329,
+           0.5672661849383173,
+           0.6554489356049462,
+           0.7429912707469956,
+           0.8283897890855876,
+           0.9101409515669333,
+           0.9867842682148212,
+           1.0569448446589014,
+           1.1193741538257265,
+           1.1729879385484525,
+           1.2169002192002705,
+           1.2504524752209938,
+           1.2732371882540419,
+           1.285115074602364,
+           1.2862254923705947,
+           1.2769896800618301,
+           1.2581066642633034,
+           1.2305418598636406,
+           1.1955085723396186,
+           1.1544427933603707,
+           1.1089718537096134,
+           1.0608776569630811,
+           1.0120553594442372,
+           0.9644684831048164,
+           0.9201015450415483,
+           0.8809113578624843,
+           0.8487781972072239,
+           0.825458045259676,
+           0.81253710165599,
+           0.8113897061147658,
+           0.8231407414679581,
+           0.8486334833273852,
+           0.8884037358295879,
+           0.942660944815681,
+           1.0112768140112602,
+           1.0937817703084376,
+           1.1893694354979023,
+           1.296909068372375,
+           1.4149657477671318,
+           1.5418278785690074,
+           1.6755414236527235,
+           1.8139500995086748,
+           1.9547406260906497,
+           2.0954919957817797,
+           2.2337276254730836,
+           2.3669691820888286,
+           2.4927908273281445,
+           2.608872613062405,
+           2.7130517751324987,
+           2.8033707198759394,
+           2.8781205734871027,
+           2.935879267462137,
+           2.975543261420116,
+           2.9963521544290397
+          ],
+          [
+           2.9999784020568754,
+           2.9894570240085767,
+           2.959816892781092,
+           2.9116254495955616,
+           2.845803090711617,
+           2.7636025023919126,
+           2.6665805661259165,
+           2.556563499283912,
+           2.4356060558592945,
+           2.3059457514196517,
+           2.169953192450216,
+           2.0300796801380243,
+           1.8888033201557497,
+           1.748574901701353,
+           1.6117648102059223,
+           1.4806122087590428,
+           1.357177664188257,
+           1.2433003063653976,
+           1.1405604958866602,
+           1.0502488386112534,
+           0.9733422290371104,
+           0.9104874320153198,
+           0.861992528117413,
+           0.8278263566115365,
+           0.807625896183052,
+           0.8007113320119246,
+           0.8061083732872769,
+           0.8225772122104612,
+           0.84864735823083,
+           0.8826574434947951,
+           0.9227989805995602,
+           0.9671629644862237,
+           1.0137881488007712,
+           1.0607097947221187,
+           1.1060076878044314,
+           1.1478522457644305,
+           1.1845475965817898,
+           1.2145705902706052,
+           1.2366048170399895,
+           1.2495688364839235,
+           1.252637973561228,
+           1.2452592036120798,
+           1.2271588262993223,
+           1.198342812683507,
+           1.1590898960048701,
+           1.1099376604772746,
+           1.0516620588967096,
+           0.9852509547189586,
+           0.91187243335543,
+           0.8328387570628757,
+           0.7495669447460471,
+           0.6635370396102828,
+           0.5762491818911646,
+           0.4891806295372109,
+           0.40374386613645824,
+           0.32124690270176853,
+           0.24285681903667736,
+           0.16956750287651293,
+           0.10217243308984807,
+           0.04124321979661464,
+           -0.012885537285185227,
+           -0.06012467675453656,
+           -0.10063197003943121,
+           -0.1348066442612318,
+           -0.1632770775953933,
+           -0.18688198999839226,
+           -0.20664562269446804,
+           -0.22374755780378805,
+           -0.23948797092665197,
+           -0.2552492307724633,
+           -0.2724548579390676,
+           -0.2925269271932825,
+           -0.31684304220933307,
+           -0.3466940275151119,
+           -0.38324346892730665,
+           -0.42749019131193416,
+           -0.4802346921023438,
+           -0.5420504523624975,
+           -0.6132609266813093,
+           -0.6939228718095519,
+           -0.7838165152182175,
+           -0.8824428926227331,
+           -0.9890285022800106,
+           -1.1025372380609857,
+           -1.2216893775888795,
+           -1.3449872207789972,
+           -1.4707468024765127,
+           -1.5971349448973655,
+           -1.7222107752369293,
+           -1.8439707146908484,
+           -1.9603958502817114,
+           -2.06950053275446,
+           -2.169381004183101,
+           -2.258262848906759,
+           -2.334546081335383,
+           -2.396846733642691,
+           -2.4440338842691407,
+           -2.4752611726556553,
+           -2.4899919742212164,
+           -2.488017559182859,
+           -2.4694677257673394,
+           -2.434813578614683,
+           -2.3848623123219768,
+           -2.320744053490013,
+           -2.2438910075688736,
+           -2.1560093445084187,
+           -2.0590444350813293,
+           -1.9551402133709208,
+           -1.8465935862567826,
+           -1.7358049341845059,
+           -1.6252258460017912,
+           -1.5173053017189415,
+           -1.4144355589173148,
+           -1.3188990101066278,
+           -1.2328172592885174,
+           -1.158103616734594,
+           -1.096420132691846,
+           -1.049140185256658,
+           -1.0173175075504552,
+           -1.0016623877290574,
+           -1.0025256059364245,
+           -1.0198904891827216,
+           -1.053373272733774,
+           -1.1022317596198732,
+           -1.1653820730946585,
+           -1.241423105082962,
+           -1.3286680815107743,
+           -1.4251824973344898,
+           -1.5288275241581206,
+           -1.6373078651777624,
+           -1.7482229289182762,
+           -1.8591201173135468,
+           -1.9675489769413252,
+           -2.071114945753477,
+           -2.16753144179647,
+           -2.2546690847981594,
+           -2.330600914967673,
+           -2.3936425740656695,
+           -2.44238653923762,
+           -2.475729647144008,
+           -2.492893310924423,
+           -2.4934360114180874,
+           -2.4772578324177505,
+           -2.4445970029184356,
+           -2.396018602588722,
+           -2.3323957752986497,
+           -2.254883974867817,
+           -2.1648889328709044,
+           -2.0640291863231104,
+           -1.9540941297774044,
+           -1.8369986587452907,
+           -1.7147355469574317,
+           -1.589326747032468,
+           -1.4627748215549803,
+           -1.337015699046597,
+           -1.2138739072612323,
+           -1.095021365790798,
+           -0.981940722980262,
+           -0.8758941011225339,
+           -0.7778979719312006,
+           -0.6887047249811197,
+           -0.6087913191985516,
+           -0.5383552259294045,
+           -0.47731768618738074,
+           -0.4253341190537816,
+           -0.38181133752035123,
+           -0.3459310568569938,
+           -0.3166790231222405,
+           -0.29287894963916783,
+           -0.27323033060702423,
+           -0.2563491064468607,
+           -0.24081008731746065,
+           -0.22519000114900972,
+           -0.2081100214820865,
+           -0.18827664859420462,
+           -0.16451986433518107,
+           -0.13582755554356193,
+           -0.10137530095612855,
+           -0.060550739585335515,
+           -0.012971881482161931,
+           0.04150111901771971,
+           0.10276103609774873,
+           0.17045562064519762,
+           0.243996570663184,
+           0.32257518962331394,
+           0.40518432329031223,
+           0.4906460007697278,
+           0.5776440553405934,
+           0.6647608688606491,
+           0.7505172735339772,
+           0.8334145594247,
+           0.9119774774841447,
+           0.984797097557633,
+           1.0505723796647863,
+           1.108149344886022,
+           1.1565567887844355,
+           1.1950375640745006,
+           1.2230745681595114,
+           1.2404107025063502,
+           1.2470622213490032,
+           1.2433250531646214,
+           1.229773855607019,
+           1.2072537486812132,
+           1.1768648572870508,
+           1.139939978172804,
+           1.0980158631955186,
+           1.052798776124035,
+           1.006125129862548,
+           0.9599181411191721,
+           0.9161415468753009,
+           0.8767515087694356,
+           0.8436478855655877,
+           0.8186260787899513,
+           0.8033306516686215,
+           0.7992118867046673,
+           0.8074863833563847,
+           0.8291027058055647,
+           0.8647129739085465,
+           0.9146511509121545,
+           0.9789186227662323,
+           1.0571774897326918,
+           1.1487518057249382,
+           1.2526368089423079,
+           1.3675159935951653,
+           1.491785681607226,
+           1.6235865698307923,
+           1.7608415570385751,
+           1.901298999993457,
+           2.0425804130823972,
+           2.1822315146795166,
+           2.317775438351257,
+           2.4467668703666576,
+           2.566845848166665,
+           2.6757899581855544,
+           2.7715637056635645,
+           2.852363893053103,
+           2.9166599357825,
+           2.9632281622885324,
+           2.9911792865126894,
+           2.9999784020568754
+          ],
+          [
+           2.9951443799079214,
+           2.9726313428996796,
+           2.9313177626520197,
+           2.8719957733124595,
+           2.7957988038744697,
+           2.704176323361824,
+           2.598861531914154,
+           2.4818327601564074,
+           2.3552694873709394,
+           2.2215040150480365,
+           2.0829699333220186,
+           1.9421485911762781,
+           1.8015148253687079,
+           1.663483216755312,
+           1.5303561257851146,
+           1.4042747118655516,
+           1.2871740652547055,
+           1.1807434770350613,
+           1.0863927451331623,
+           1.0052252654389504,
+           0.9380184905341518,
+           0.8852121584745876,
+           0.846904504925857,
+           0.8228564783798187,
+           0.8125037849355533,
+           0.8149764009504764,
+           0.8291250133585346,
+           0.8535536829685898,
+           0.886657879598001,
+           0.9266669130113513,
+           0.971689683329109,
+           1.0197626012384455,
+           1.0688984836987956,
+           1.1171352158941301,
+           1.1625829852108718,
+           1.2034689375394738,
+           1.2381781790035864,
+           1.2652901454081598,
+           1.283609484710645,
+           1.29219074151491,
+           1.290356293315179,
+           1.2777071619108846,
+           1.2541265056921207,
+           1.219775784774209,
+           1.1750837765629558,
+           1.1207287996107138,
+           1.057614674070329,
+           0.9868411034174118,
+           0.9096693004992513,
+           0.8274837979463318,
+           0.7417514756574893,
+           0.6539789041639456,
+           0.5656691405827827,
+           0.4782791226889925,
+           0.39317878620057234,
+           0.31161298125250325,
+           0.23466718752214855,
+           0.1632379255379903,
+           0.09800863697053977,
+           0.03943166235559145,
+           -0.012283215585645432,
+           -0.05717336700964745,
+           -0.09552093200560263,
+           -0.1278435258012246,
+           -0.15487827911475358,
+           -0.17755963517948542,
+           -0.19699148875912056,
+           -0.21441440136134898,
+           -0.23116875705369122,
+           -0.24865483146930956,
+           -0.26829082999334614,
+           -0.2914700075969383,
+           -0.3195180108671037,
+           -0.35365158171066413,
+           -0.3949397319666455,
+           -0.4442684394556736,
+           -0.5023098302551003,
+           -0.5694967013251101,
+           -0.6460031047633255,
+           -0.7317315632349617,
+           -0.8263073192928109,
+           -0.929079843533161,
+           -1.039131642277986,
+           -1.1552942193500844,
+           -1.2761708631912676,
+           -1.4001657546785482,
+           -1.525518726958135,
+           -1.6503448605924709,
+           -1.7726779690626258,
+           -1.8905169244610678,
+           -2.0018736937561807,
+           -2.104821904380744,
+           -2.197544735475281,
+           -2.27838093856257,
+           -2.345867828659531,
+           -2.398780153024509,
+           -2.43616383834775,
+           -2.45736373599277,
+           -2.4620446260290927,
+           -2.4502049008451725,
+           -2.4221825242011263,
+           -2.378653047401354,
+           -2.320619656288822,
+           -2.2493954162758163,
+           -2.166578072872778,
+           -2.074017947472785,
+           -1.973779637995133,
+           -1.8680983871882206,
+           -1.7593321141425282,
+           -1.6499102135680115,
+           -1.54228030992674,
+           -1.4388542075047914,
+           -1.34195430158273,
+           -1.2537617093763314,
+           -1.176267342476398,
+           -1.1112270759704366,
+           -1.0601220748614952,
+           -1.0241252180783391,
+           -1.0040744171990084,
+           -1.000453464450276,
+           -1.0133808665390924,
+           -1.0426069317400246,
+           -1.0875191819993946,
+           -1.1471559643781957,
+           -1.2202279417416,
+           -1.3051469559387294,
+           -1.4000615823376943,
+           -1.5028985367214915,
+           -1.6114089580380913,
+           -1.7232184766609875,
+           -1.8358798904007931,
+           -1.94692721161242,
+           -2.053929819762988,
+           -2.154545455426388,
+           -2.2465708237650923,
+           -2.327988637314315,
+           -2.397010017738157,
+           -2.4521112919344072,
+           -2.4920643565465292,
+           -2.515959943159463,
+           -2.5232232902981764,
+           -2.513621913524652,
+           -2.487265356879429,
+           -2.444597002918436,
+           -2.3863782098941018,
+           -2.3136652285363786,
+           -2.227779522911104,
+           -2.130272275778738,
+           -2.0228839949603517,
+           -1.9075002501526421,
+           -1.7861046567114698,
+           -1.6607302820814382,
+           -1.5334106804198346,
+           -1.406131760907703,
+           -1.2807856653627945,
+           -1.159127771912107,
+           -1.0427378552051998,
+           -0.9329863221923981,
+           -0.8310063087114923,
+           -0.7376722694313138,
+           -0.6535855259596414,
+           -0.5790670593744989,
+           -0.5141576485779336,
+           -0.4586252693452877,
+           -0.41197948542784224,
+           -0.3734923871542405,
+           -0.34222546906001516,
+           -0.3170616902392608,
+           -0.2967418330327397,
+           -0.2799041705160547,
+           -0.265126373623174,
+           -0.25096853658373613,
+           -0.2360161759241145,
+           -0.21892206411577825,
+           -0.1984457938480741,
+           -0.17349003192390497,
+           -0.1431325112872164,
+           -0.10665292338759957,
+           -0.06355400805940555,
+           -0.013576290897092369,
+           0.043293915145402075,
+           0.10682345075561135,
+           0.17653821902119374,
+           0.2517359048308416,
+           0.33150516955158055,
+           0.41475081591526947,
+           0.5002242612072665,
+           0.5865585168608751,
+           0.6723067529888792,
+           0.7559834302818508,
+           0.836106911536238,
+           0.911242422656996,
+           0.9800442194253329,
+           1.0412958320224286,
+           1.0939473039094931,
+           1.1371484141098214,
+           1.1702769704449456,
+           1.1929613834122221,
+           1.2050968731253962,
+           1.206854821520637,
+           1.198684954872396,
+           1.181310223245169,
+           1.1557144292810437,
+           1.1231228440268974,
+           1.0849762276796764,
+           1.0428988436334719,
+           0.9986612107391081,
+           0.954138477268052,
+           0.9112654171787866,
+           0.8719891419148756,
+           0.838220686723023,
+           0.8117866676332416,
+           0.794382212768392,
+           0.7875263492563521,
+           0.7925209751593337,
+           0.8104144656979838,
+           0.8419708565244438,
+           0.8876454164389237,
+           0.947567270895533,
+           1.021529569571511,
+           1.1089875102752227,
+           1.2090643419666496,
+           1.3205652763030737,
+           1.4419990446505855,
+           1.5716066506548083,
+           1.7073966918479921,
+           1.8471864617470148,
+           1.9886479004782396,
+           2.1293573407109703,
+           2.2668478996109136,
+           2.3986632990443115,
+           2.5224118571031906,
+           2.635819385195551,
+           2.7367797467206527,
+           2.8234018852476974,
+           2.894052210915431,
+           2.947391341540388,
+           2.982404327068348,
+           2.9984236393354355,
+           2.995144379907921
+          ],
+          [
+           2.981890985996979,
+           2.947570913516965,
+           2.8949158788969154,
+           2.824936019517115,
+           2.7389682279729337,
+           2.638646521132217,
+           2.525865790411109,
+           2.402739786412704,
+           2.27155432660448,
+           2.134716826295767,
+           1.9947033381221546,
+           1.8540043415106109,
+           1.715070549851849,
+           1.580259998745807,
+           1.4517876438636144,
+           1.331678632582737,
+           1.2217263212226839,
+           1.123455991741131,
+           1.0380950810752843,
+           0.9665505764139233,
+           0.909394054512126,
+           0.8668546570319878,
+           0.8388201013895358,
+           0.8248456324398452,
+           0.8241706293002738,
+           0.8357423983709715,
+           0.8582465126365977,
+           0.8901429027861579,
+           0.9297067713179591,
+           0.9750732898467377,
+           1.0242849549575221,
+           1.0753404211628106,
+           1.1262436021241289,
+           1.1750518338737648,
+           1.2199219261509096,
+           1.259152989244774,
+           1.291225012295497,
+           1.3148322825495513,
+           1.3289108706911432,
+           1.3326595616242185,
+           1.3255537790544956,
+           1.3073522316530226,
+           1.278096193956421,
+           1.238101521819832,
+           1.1879436855102794,
+           1.128436278828089,
+           1.0606036255983604,
+           0.9856482514262561,
+           0.9049141151204672,
+           0.8198465975280216,
+           0.7319503231464287,
+           0.6427459398903655,
+           0.5537270035899686,
+           0.46631810571145754,
+           0.38183534567953725,
+           0.30145018403529916,
+           0.22615762117712815,
+           0.15674953096033836,
+           0.0937938419300589,
+           0.03762010491456834,
+           -0.011688181964548466,
+           -0.054294296839570155,
+           -0.09060205406791659,
+           -0.12124277062999346,
+           -0.14705578671054872,
+           -0.16906305707992192,
+           -0.188438485565967,
+           -0.20647281343798118,
+           -0.22453499038269584,
+           -0.2440310509303194,
+           -0.26636158727187514,
+           -0.2928789496391675,
+           -0.324845316737363,
+           -0.3633927607959584,
+           -0.40948638504120455,
+           -0.46389153692238594,
+           -0.5271460000747088,
+           -0.5995379442550082,
+           -0.6810902684171403,
+           -0.7715518112907939,
+           -0.8703957303062126,
+           -0.9768251678093006,
+           -1.0897861377964166,
+           -1.2079873815299143,
+           -1.3299267610255643,
+           -1.4539235900554486,
+           -1.57815614726657,
+           -1.7007034792102529,
+           -1.8195904859968135,
+           -1.932835191886032,
+           -2.0384970397393127,
+           -2.1347250135690166,
+           -2.2198043883875886,
+           -2.292200931411498,
+           -2.3506014328977187,
+           -2.393949527236606,
+           -2.4214758734475494,
+           -2.4327218963204813,
+           -2.427556441925484,
+           -2.406184870369831,
+           -2.3691502903916843,
+           -2.317326830197239,
+           -2.251905032219119,
+           -2.174369651448008,
+           -2.0864703229405688,
+           -1.9901857394458722,
+           -1.8876821404861759,
+           -1.7812670557004209,
+           -1.673339364296055,
+           -1.5663368260866593,
+           -1.4626823054710623,
+           -1.3647299461641809,
+           -1.2747125605703804,
+           -1.1946914731932285,
+           -1.126510002945138,
+           -1.0717516859411143,
+           -1.0317042303208364,
+           -1.0073300604908877,
+           -0.9992441531542162,
+           -1.0076996953510213,
+           -1.0325819096498976,
+           -1.0734101980948039,
+           -1.1293485592350145,
+           -1.1992240363376137,
+           -1.2815527644754932,
+           -1.3745730042267659,
+           -1.4762843845851035,
+           -1.5844924313733515,
+           -1.6968573335201627,
+           -1.8109458009975608,
+           -1.924284797400201,
+           -2.0344158887667234,
+           -2.1389489392702723,
+           -2.2356139040636043,
+           -2.3223095193279355,
+           -2.397147768180064,
+           -2.4584931065702884,
+           -2.5049955630283858,
+           -2.535616976870079,
+           -2.54964980753253,
+           -2.5467281289183035,
+           -2.526830612528528,
+           -2.490275497088365,
+           -2.4377077355513075,
+           -2.3700786980805875,
+           -2.2886189872570335,
+           -2.194805085021324,
+           -2.090320695756866,
+           -1.9770137729506077,
+           -1.8568503150739033,
+           -1.7318660873646523,
+           -1.6041174684027089,
+           -1.4756326328074592,
+           -1.34836426384325,
+           -1.2241449427320656,
+           -1.1046462863097186,
+           -0.991342803283338,
+           -0.8854813143642208,
+           -0.788056636149536,
+           -0.6997940664998845,
+           -0.6211390344054236,
+           -0.5522540943551433,
+           -0.4930232586211985,
+           -0.443063475322834,
+           -0.4017428802868718,
+           -0.3682052810654972,
+           -0.3414001762361788,
+           -0.320117476152779,
+           -0.3030259760361692,
+           -0.288714541533417,
+           -0.2757349028635702,
+           -0.262644917957649,
+           -0.24805115843057512,
+           -0.23064969490044743,
+           -0.2092640094678552,
+           -0.1828790417383829,
+           -0.15067047858409036,
+           -0.1120285242308377,
+           -0.0665755329977331,
+           -0.014177048388207531,
+           0.04505403486679333,
+           0.11076028917893065,
+           0.18234947365674029,
+           0.2590108950958933,
+           0.3397379767975799,
+           0.4233564388222353,
+           0.5085573457133352,
+           0.5939341491208608,
+           0.6780227463953608,
+           0.7593434948310652,
+           0.8364440669030351,
+           0.9079420059819412,
+           0.9725658453176231,
+           1.0291936855225694,
+           1.0768881865892983,
+           1.1149270181567479,
+           1.1428279241380093,
+           1.1603676921484603,
+           1.1675944710874333,
+           1.1648330479138693,
+           1.1526828729253458,
+           1.1320088072361052,
+           1.1039247520267292,
+           1.0697705018338997,
+           1.0310823390607888,
+           0.9895580496004613,
+           0.9470171858555174,
+           0.9053575297847705,
+           0.8665088116832248,
+           0.8323848175486961,
+           0.8048350670922182,
+           0.7855972643865178,
+           0.776251713219563,
+           0.7781788495728041,
+           0.7925209751593337,
+           0.8201491802379802,
+           0.8616363232466093,
+           0.9172367920776595,
+           0.986873610509949,
+           1.0701332773398717,
+           1.1662685394207617,
+           1.2742091076852324,
+           1.3925801320083442,
+           1.519728061222742,
+           1.6537533333923349,
+           1.792549173063828,
+           1.9338456208126946,
+           2.0752577897390925,
+           2.2143372369016228,
+           2.3486252576701014,
+           2.475706859648609,
+           2.59326415148089,
+           2.6991278910806566,
+           2.7913259774585,
+           2.8681277394285734,
+           2.928082971429628,
+           2.970054789161938,
+           2.9932455227702333,
+           2.997215029385369,
+           2.9818909859969795
+          ],
+          [
+           2.9603303500337637,
+           2.9144877584329816,
+           2.850919217924384,
+           2.7708443350214145,
+           2.675792175395262,
+           2.5675675074825226,
+           2.4482109186208416,
+           2.3199537404006474,
+           2.185168841701535,
+           2.046318444051331,
+           1.9059001821870967,
+           1.7663926713789146,
+           1.6302018512925194,
+           1.4996093537561344,
+           1.3767240893511155,
+           1.2634381665914263,
+           1.16138814962214,
+           1.071922528532072,
+           0.9960761238058943,
+           0.9345519769058169,
+           0.887711096652482,
+           0.8555702404565872,
+           0.8378077152206006,
+           0.8337769896481658,
+           0.8425277224945821,
+           0.8628336345385138,
+           0.8932264900599476,
+           0.9320353103067008,
+           0.9774298202869109,
+           1.0274670341487953,
+           1.0801398156871997,
+           1.1334262107535087,
+           1.185338338425936,
+           1.233969647865351,
+           1.2775393972380298,
+           1.3144332886055878,
+           1.34323929624391,
+           1.3627778527964938,
+           1.3721257047569821,
+           1.3706329122813803,
+           1.3579326441227817,
+           1.3339436021339326,
+           1.2988650966831017,
+           1.2531649797924809,
+           1.1975608221979719,
+           1.1329948893675483,
+           1.0606036255983604,
+           0.9816824908131087,
+           0.8976471082391274,
+           0.8099917699793557,
+           0.7202464093981795,
+           0.6299331827502709,
+           0.5405238067955593,
+           0.453398774220657,
+           0.3698095152131255,
+           0.2908444929133314,
+           0.2174001147835178,
+           0.15015721389771514,
+           0.0895637070416644,
+           0.0358238740692353,
+           -0.01110547067558455,
+           -0.05151182448073742,
+           -0.08591695215954319,
+           -0.11506022412316219,
+           -0.1398757822082354,
+           -0.1614641405951695,
+           -0.1810589753922982,
+           -0.19998998346112587,
+           -0.21964279558151545,
+           -0.24141700843113686,
+           -0.2666834520410705,
+           -0.29674183303273927,
+           -0.33277988840181544,
+           -0.3758351499880009,
+           -0.42676035688353753,
+           -0.4861934634279527,
+           -0.5545330763260005,
+           -0.631920018643192,
+           -0.7182255643611222,
+           -0.8130467186596312,
+           -0.9157087403510226,
+           -1.0252749184027738,
+           -1.1405634288818,
+           -1.2601709166045065,
+           -1.382502271871279,
+           -1.5058059112967164,
+           -1.6282137270073078,
+           -1.747784744049671,
+           -1.862551424918083,
+           -1.9705674852740978,
+           -2.0699560381518376,
+           -2.1589568664842385,
+           -2.2359716361837774,
+           -2.2996059040604226,
+           -2.348706845616111,
+           -2.3823957255590313,
+           -2.4000942563979732,
+           -2.401544134752977,
+           -2.386819207553983,
+           -2.356329897133947,
+           -2.3108197010343936,
+           -2.251353774550315,
+           -2.179299796926209,
+           -2.096301510926578,
+           -2.0042455055858452,
+           -1.9052219788420952,
+           -1.8014803663429464,
+           -1.6953808512635207,
+           -1.5893428742932276,
+           -1.4857918404159172,
+           -1.3871052677709617,
+           -1.2955596424896512,
+           -1.213279231436466,
+           -1.1421880624850067,
+           -1.0839662103026175,
+           -1.040011426309093,
+           -1.011407026893904,
+           -0.9988968071273888,
+           -1.0028675816356172,
+           -1.0233397740389165,
+           -1.059966285755555,
+           -1.112039678675061,
+           -1.1785075089812118,
+           -1.2579954560482802,
+           -1.3488377055462204,
+           -1.4491138741629195,
+           -1.556691608854777,
+           -1.6692738600196686,
+           -1.7844497186819386,
+           -1.8997476253265273,
+           -2.0126897043996093,
+           -2.120845954978666,
+           -2.22188703524057,
+           -2.3136344159057645,
+           -2.3941067448483873,
+           -2.461561359853429,
+           -2.514530006711133,
+           -2.5518479624837442,
+           -2.572675925332553,
+           -2.5765142087657797,
+           -2.563208965214018,
+           -2.5329503568591374,
+           -2.4862627858962885,
+           -2.423987487136404,
+           -2.3472579683937336,
+           -2.257468953995388,
+           -2.1562396398641224,
+           -2.0453722012505713,
+           -1.9268066031285924,
+           -1.802572845911303,
+           -1.674741833544737,
+           -1.545376075942556,
+           -1.4164814326230066,
+           -1.2899610695268682,
+           -1.1675727372980769,
+           -1.0508903884754177,
+           -0.9412710354209902,
+           -0.8398276133582178,
+           -0.7474084571014883,
+           -0.6645838298737952,
+           -0.591639762319215,
+           -0.5285792739575494,
+           -0.47513086256165393,
+           -0.4307639639392394,
+           -0.3947109099424779,
+           -0.36599475056407493,
+           -0.3434621607362238,
+           -0.3258205275312082,
+           -0.31167821195604145,
+           -0.29958690393356596,
+           -0.28808494121026323,
+           -0.2757404439691551,
+           -0.26119312727049515,
+           -0.24319369277284233,
+           -0.22063976845410785,
+           -0.19260745850701042,
+           -0.1583776828198831,
+           -0.11745662347022201,
+           -0.06958975093208475,
+           -0.01476907127528672,
+           0.046766586772587236,
+           0.11453824393320622,
+           0.1878402187079987,
+           0.26575999174872633,
+           0.34720395808662313,
+           0.4309283845473294,
+           0.5155747526222486,
+           0.5997085509341196,
+           0.6818604891893592,
+           0.7605690395150885,
+           0.8344231730381239,
+           0.9021041504775066,
+           0.9624252456634562,
+           1.014368329800879,
+           1.0571163207773047,
+           1.0900806039902713,
+           1.1129226565062784,
+           1.1255692517451252,
+           1.1282207836837326,
+           1.1213524237484764,
+           1.1057080057529152,
+           1.0822867198684099,
+           1.052322881022929,
+           1.0172592156652125,
+           0.9787142790011113,
+           0.9384447683509909,
+           0.8983036332929655,
+           0.8601949963020348,
+           0.8260269857675744,
+           0.7976636442820548,
+           0.7768771073262575,
+           0.7653012500277195,
+           0.7643879723737919,
+           0.7753672366950923,
+           0.7992118867046673,
+           0.8366081668863571,
+           0.8879327272248663,
+           0.9532367443966046,
+           1.0322376203359485,
+           1.1243185367101647,
+           1.2285359537427762,
+           1.343634948684374,
+           1.4680720977917705,
+           1.6000454206586527,
+           1.7375307317120612,
+           1.8783235849552906,
+           2.0200858585362016,
+           2.160395908921447,
+           2.2968011332787537,
+           2.4268717154032347,
+           2.5482542967788286,
+           2.658724311028304,
+           2.7562357472147787,
+           2.8389671646046013,
+           2.9053628672411413,
+           2.95416825896265,
+           2.984458535624949,
+           2.9956600279728542,
+           2.9875636820495703,
+           2.960330350033764
+          ],
+          [
+           2.9306448847548214,
+           2.8736617761100383,
+           2.799700011394969,
+           2.7101783599529568,
+           2.6068051441337503,
+           2.4915406430318376,
+           2.366553911897928,
+           2.2341750295306113,
+           2.0968438929542623,
+           1.9570567586292407,
+           1.8173117803999428,
+           1.6800548151552372,
+           1.5476267572840556,
+           1.4222136227377395,
+           1.3058005338854395,
+           1.2001306591130698,
+           1.1066700386881494,
+           1.0265790838257907,
+           0.9606913727172874,
+           0.9095001895460015,
+           0.8731530645903639,
+           0.8514543800188717,
+           0.8438759116641503,
+           0.849574986681314,
+           0.8674197552033751,
+           0.8960209053362019,
+           0.933768999190963,
+           0.9788764768060647,
+           1.029423267915654,
+           1.0834048711322892,
+           1.1387817081217566,
+           1.1935285379464826,
+           1.2456827243944297,
+           1.2933901865019053,
+           1.3349479285946324,
+           1.3688421392747017,
+           1.39378096646989,
+           1.4087212149290802,
+           1.4128883698570283,
+           1.4057895217566985,
+           1.3872189486699555,
+           1.3572562983266128,
+           1.3162574995570593,
+           1.264838715021414,
+           1.2038538212978511,
+           1.1343660633211325,
+           1.057614674070329,
+           0.9749773737072839,
+           0.8879297620218056,
+           0.7980026916007561,
+           0.7067387548191326,
+           0.6156490344669053,
+           0.5261712552189499,
+           0.43963043160706716,
+           0.357203038768833,
+           0.2798856368326215,
+           0.2084687608082242,
+           0.14351674833552783,
+           0.08535402116066995,
+           0.03405816674534758,
+           -0.010540011719938182,
+           -0.048849490908388075,
+           -0.08150526436266006,
+           -0.1093481934218129,
+           -0.13339901169489246,
+           -0.1548271759972381,
+           -0.17491539223345012,
+           -0.19502075910590128,
+           -0.21653356283191164,
+           -0.24083481995417305,
+           -0.2692537011793396,
+           -0.30302597603616965,
+           -0.34325459579374545,
+           -0.3908734810439821,
+           -0.4466155018752969,
+           -0.5109855345824007,
+           -0.5842393519510958,
+           -0.6663689574872822,
+           -0.7570948111876723,
+           -0.8558652196484738,
+           -0.9618629808578909,
+           -1.0740191884997976,
+           -1.1910339166745678,
+           -1.3114033282538105,
+           -1.4334525831159661,
+           -1.5553737704876311,
+           -1.6752679564044275,
+           -1.7911903263056679,
+           -1.9011973168431129,
+           -2.0033945723491438,
+           -2.095984531631826,
+           -2.177312450685708,
+           -2.245909696631729,
+           -2.3005332070899454,
+           -2.3402000958804208,
+           -2.36421649838213,
+           -2.3721998853545507,
+           -2.3640942292612164,
+           -2.3401775783511796,
+           -2.301061776770728,
+           -2.247684259310108,
+           -2.181292042364502,
+           -2.103418223554912,
+           -2.0158514865065724,
+           -1.9205992799705804,
+           -1.819845497522702,
+           -1.7159036215814434,
+           -1.6111664100310066,
+           -1.5080532924483148,
+           -1.4089567035815829,
+           -1.31618861276438,
+           -1.2319285085502096,
+           -1.1581740679443577,
+           -1.0966956798643228,
+           -1.0489959042858794,
+           -1.0162748340334908,
+           -0.9994021881062797,
+           -0.9988968071273884,
+           -1.01491404679864,
+           -1.0472413783710448,
+           -1.0953023106426403,
+           -1.1581685505950476,
+           -1.2345801242784542,
+           -1.3229729907050718,
+           -1.4215135039055409,
+           -1.5281389162574042,
+           -1.6406029736447096,
+           -1.7565255334100622,
+           -1.8734450423089448,
+           -1.9888726460307804,
+           -2.1003466658821264,
+           -2.205486172778044,
+           -2.302042413852056,
+           -2.3879469021179993,
+           -2.46135506330993,
+           -2.5206844442013705,
+           -2.5646466206285132,
+           -2.5922720978001377,
+           -2.6029276664605914,
+           -2.5963258618684972,
+           -2.5725263638525955,
+           -2.5319293707102277,
+           -2.4752611726556553,
+           -2.4035523371837995,
+           -2.3181090945331904,
+           -2.2204786721283853,
+           -2.112409468556591,
+           -1.9958070768628013,
+           -1.8726872608700043,
+           -1.7451270546147912,
+           -1.6152151922880595,
+           -1.4850030834619763,
+           -1.3564575257862608,
+           -1.231416295410221,
+           -1.111547675518015,
+           -0.9983148776297031,
+           -0.8929461814320055,
+           -0.796411470143435,
+           -0.7094056735556056,
+           -0.632339454087716,
+           -0.5653372868914386,
+           -0.5082428978752604,
+           -0.4606318381663651,
+           -0.4218307946264022,
+           -0.3909430680457777,
+           -0.36687949773829215,
+           -0.348393977238221,
+           -0.33412259397922733,
+           -0.32262533896129314,
+           -0.3124292726107962,
+           -0.3020720017503842,
+           -0.29014432054240413,
+           -0.2753308954406802,
+           -0.2564479298347387,
+           -0.23247682673821882,
+           -0.20259297542176619,
+           -0.16618891755921014,
+           -0.12289129692994441,
+           -0.07257116021478671,
+           -0.015347350776811836,
+           0.048417081898722195,
+           0.11812535181167283,
+           0.19296399998724476,
+           0.2719260943776566,
+           0.3538399478386099,
+           0.43740259100337264,
+           0.5212171114961448,
+           0.6038328682483645,
+           0.6837875123302383,
+           0.7596496956713276,
+           0.8300613276180658,
+           0.8937782470429194,
+           0.9497082145245797,
+           0.9969451940753128,
+           1.0347989854051534,
+           1.0628193835173696,
+           1.0808141796462054,
+           1.0888604727545028,
+           1.0873089301265262,
+           1.0767808147801041,
+           1.0581577819877528,
+           1.0325646325007143,
+           1.0013453914484487,
+           0.9660332547634507,
+           0.9283151049855662,
+           0.8899914413734543,
+           0.8529326917492654,
+           0.8190329722893896,
+           0.7901624339973166,
+           0.7681193789522991,
+           0.7545833444158835,
+           0.7510703380223754,
+           0.7588913628470377,
+           0.7791152981404318,
+           0.81253710165599,
+           0.8596521751682934,
+           0.9206375889823005,
+           0.995340697508978,
+           1.0832755003229562,
+           1.183626915869008,
+           1.2952629427397755,
+           1.4167544909336716,
+           1.5464024774623208,
+           1.6822716017534705,
+           1.8222300509144973,
+           1.963994237184413,
+           2.105177543482243,
+           2.243341951011582,
+           2.3760513479636733,
+           2.5009252723709645,
+           2.6156918262887587,
+           2.7182385131745983,
+           2.806659795293421,
+           2.879300242157819,
+           2.93479224265502,
+           2.9720873801782397,
+           2.99048071871657,
+           2.989627414869619,
+           2.969551252093782,
+           2.9306448847548205
+          ],
+          [
+           2.8930857426292427,
+           2.8254383728325587,
+           2.741691596972871,
+           2.643451355912495,
+           2.5325907956898663,
+           2.411209149455972,
+           2.2815856254694697,
+           2.1461293805118755,
+           2.0073267493965683,
+           1.8676869642795504,
+           1.729687630726531,
+           1.595721230171566,
+           1.4680438904874349,
+           1.3487276085970061,
+           1.2396170228391088,
+           1.142291720307915,
+           1.0580349283994464,
+           0.9878092836826505,
+           0.9322401988154588,
+           0.8916071637916076,
+           0.8658431258646028,
+           0.8545418977605923,
+           0.856973351032383,
+           0.8721059653357117,
+           0.8986361295661602,
+           0.9350234314356721,
+           0.9795310320566959,
+           1.0302701048197898,
+           1.0852472261099397,
+           1.142413541384173,
+           1.1997144953154233,
+           1.2551389098570669,
+           1.3067662192181642,
+           1.352810725138455,
+           1.391661818067777,
+           1.4219192177551634,
+           1.4424224175729525,
+           1.4522736673140555,
+           1.450853995399215,
+           1.437831949225456,
+           1.413164917307341,
+           1.377093084272153,
+           1.3301262549798263,
+           1.273023962424168,
+           1.2067694411899175,
+           1.132538199936731,
+           1.0516620588967096,
+           0.9655896284335969,
+           0.8758442896146522,
+           0.783980795420427,
+           0.6915416402793135,
+           0.6000143453983985,
+           0.5107907779410841,
+           0.4251295642794466,
+           0.3441225728418759,
+           0.26866633267455275,
+           0.19943912254736215,
+           0.13688431561727904,
+           0.08120040013453336,
+           0.03233792162585716,
+           -0.009996589136247295,
+           -0.04632982066926418,
+           -0.07740431555234088,
+           -0.10415500489040297,
+           -0.12768027157983616,
+           -0.14920831500988693,
+           -0.170059713582951,
+           -0.19160718225895226,
+           -0.21523359764989025,
+           -0.24228941107738636,
+           -0.2740505892159212,
+           -0.3116782119560416,
+           -0.3561808181487568,
+           -0.4083805228782424,
+           -0.46888383650529675,
+           -0.5380579982452172,
+           -0.6160134984159636,
+           -0.702593307176327,
+           -0.7973691574800986,
+           -0.8996450503633586,
+           -1.0084679660670868,
+           -1.122645579518312,
+           -1.2407705980098307,
+           -1.3612511670923426,
+           -1.4823466320712058,
+           -1.6022078011097192,
+           -1.7189207353849467,
+           -1.8305529951111077,
+           -1.9352012000387433,
+           -2.031038721100081,
+           -2.11636230734641,
+           -2.18963646962508,
+           -2.2495344892430293,
+           -2.294974995096828,
+           -2.3251531546427597,
+           -2.3395656501940176,
+           -2.3380287593186635,
+           -2.3206890229919352,
+           -2.288026163605719,
+           -2.2408481025875577,
+           -2.1802781196249432,
+           -2.1077343875973886,
+           -2.0249023045527705,
+           -1.9337002217986377,
+           -1.8362393310138296,
+           -1.7347786191529528,
+           -1.6316759241862686,
+           -1.5293362242831947,
+           -1.4301583654076802,
+           -1.3364814756095873,
+           -1.2505323274428255,
+           -1.174374892532414,
+           -1.1098632847125698,
+           -1.0585992114736955,
+           -1.0218949495080765,
+           -1.0007427314258897,
+           -0.9957912803263581,
+           -1.0073300604908868,
+           -1.0352816300969139,
+           -1.079202289959158,
+           -1.1382910255508667,
+           -1.2114065427247682,
+           -1.2970920054281803,
+           -1.3936069009621224,
+           -1.4989652894131442,
+           -1.6109795428948417,
+           -1.727308550838453,
+           -1.8455092629057965,
+           -1.9630903636924328,
+           -2.07756682510563,
+           -2.1865140642883816,
+           -2.28762044762212,
+           -2.378736924330935,
+           -2.4579226454401697,
+           -2.523485523508168,
+           -2.5740168131767907,
+           -2.608418939090661,
+           -2.625925962500659,
+           -2.626116256835176,
+           -2.608917151290555,
+           -2.574601495425381,
+           -2.52377629208662,
+           -2.4573637359927702,
+           -2.3765751763091036,
+           -2.2828786891618327,
+           -2.1779610961789224,
+           -2.06368539418138,
+           -1.942044665974352,
+           -1.8151136202996325,
+           -1.6849989585732665,
+           -1.5537897859157772,
+           -1.4235092737964452,
+           -1.2960687417101884,
+           -1.173225256774161,
+           -1.0565437547661813,
+           -0.9473645663850199,
+           -0.8467770914483874,
+           -0.7556002049374987,
+           -0.6743698062571425,
+           -0.6033337411515437,
+           -0.5424541389662249,
+           -0.49141702105225166,
+           -0.4496488537425996,
+           -0.41633954603901574,
+           -0.39047123224418584,
+           -0.3708520372267023,
+           -0.3561539003428911,
+           -0.344953436257956,
+           -0.33577473940382574,
+           -0.3271329953148602,
+           -0.31757774762254326,
+           -0.3057346843637546,
+           -0.2903448510249974,
+           -0.2703002692429821,
+           -0.24467503745077177,
+           -0.21275111049105117,
+           -0.17403809622155275,
+           -0.12828656481331782,
+           -0.07549453677420358,
+           -0.01590699438652551,
+           0.049991556309573554,
+           0.12149126425849305,
+           0.19767746798631744,
+           0.27745703496424995,
+           0.35958980257741874,
+           0.4427242834741338,
+           0.5254366854257537,
+           0.606272207472842,
+           0.6837875123302384,
+           0.7565932413647095,
+           0.8233954338288733,
+           0.8830347365887508,
+           0.9345223437389538,
+           0.9770716859581716,
+           1.010124995228802,
+           1.033373998999093,
+           1.0467741458012854,
+           1.0505519280577746,
+           1.0452050432097333,
+           1.0314953169895187,
+           1.0104344980396442,
+           0.9832632164916507,
+           0.9514235759326769,
+           0.9165260139378669,
+           0.8803112168322232,
+           0.8446080057394624,
+           0.8112882199204624,
+           0.782219707096019,
+           0.7592185867093229,
+           0.7440019794130573,
+           0.7381423936833651,
+           0.7430249283256136,
+           0.7598083884431414,
+           0.7893913236129774,
+           0.8323838826650818,
+           0.8890862423461904,
+           0.9594742105893248,
+           1.0431924329191826,
+           1.1395554469113658,
+           1.2475566390913704,
+           1.365884965890538,
+           1.4929491100187084,
+           1.6269085605630633,
+           1.7657109338073618,
+           1.907134696432292,
+           2.0488363172669053,
+           2.1884007614917476,
+           2.3233941549599035,
+           2.4514173882789985,
+           2.5701594019717104,
+           2.677448896162915,
+           2.77130324083912,
+           2.8499734250526862,
+           2.911983974031126,
+           2.9561668798372636,
+           2.981688731202419,
+           2.988070388042779,
+           2.9751987220971716,
+           2.9433301328261523,
+           2.893085742629243
+          ],
+          [
+           2.8479706909951115,
+           2.770225540413605,
+           2.677384752093201,
+           2.5712278635485184,
+           2.4537770170338136,
+           2.327252667540984,
+           2.1940249294872305,
+           2.0565616993762394,
+           1.9173747665699112,
+           1.7789651699027418,
+           1.6437690731234678,
+           1.5141054167182353,
+           1.3921265579674047,
+           1.2797730362663653,
+           1.178733498663948,
+           1.0904106937706652,
+           1.0158942937967066,
+           0.9559411381553922,
+           0.910963311905918,
+           0.8810242827372007,
+           0.8658431258646024,
+           0.8648066718845363,
+           0.876989223061584,
+           0.9011793033365608,
+           0.935912740930261,
+           0.9795112338172828,
+           1.0301254211515514,
+           1.0857813809990033,
+           1.1444293989228207,
+           1.203993804852394,
+           1.262422658316155,
+           1.3177360748598865,
+           1.3680720288903407,
+           1.4117285391300414,
+           1.4472012404891996,
+           1.4732154679453822,
+           1.4887521208662642,
+           1.4930667364965382,
+           1.4857013750118184,
+           1.4664891012519121,
+           1.4355510353995844,
+           1.3932861317852108,
+           1.3403540270048437,
+           1.2776514711038502,
+           1.206283014410551,
+           1.127526763765693,
+           1.0427961418954599,
+           0.9535986795650664,
+           0.8614929395829679,
+           0.7680447130250327,
+           0.6747836402444986,
+           0.5831613920890459,
+           0.4945125007594761,
+           0.41001885613710265,
+           0.3306787840929729,
+           0.25728150082909396,
+           0.1903875948265765,
+           0.13031602912497364,
+           0.07713798547667071,
+           0.03067769276289452,
+           -0.00947980052547137,
+           -0.04397413131375221,
+           -0.07364880161122092,
+           -0.09952459525385214,
+           -0.12276794499219798,
+           -0.14465509573963262,
+           -0.16653302067940232,
+           -0.1897781333250651,
+           -0.21575389832913186,
+           -0.24576847530166435,
+           -0.2810335323074096,
+           -0.32262533896129253,
+           -0.3714491937765452,
+           -0.4282081579948407,
+           -0.4933769605860309,
+           -0.5671818091233911,
+           -0.649586692063546,
+           -0.7402865933202599,
+           -0.8387078640444224,
+           -0.944015813625843,
+           -1.055129396714755,
+           -1.1707426901866127,
+           -1.2893526780573934,
+           -1.409292697847125,
+           -1.528770752958038,
+           -1.6459117660712859,
+           -1.7588027416855831,
+           -1.8655397244760863,
+           -1.964275386266215,
+           -2.0532660495193644,
+           -2.130916960091995,
+           -2.1958246565254482,
+           -2.24681534663195,
+           -2.2829782930696507,
+           -2.3036933258348182,
+           -2.308651738324997,
+           -2.2978699814791783,
+           -2.2716957436312506,
+           -2.2308061878851215,
+           -2.1761983095150237,
+           -2.109171568422247,
+           -2.0313031412935225,
+           -1.9444163201233842,
+           -1.8505427536760732,
+           -1.7518793820570786,
+           -1.650741048017058,
+           -1.5495098785908523,
+           -1.4505826144200735,
+           -1.3563171195019434,
+           -1.2689793297239713,
+           -1.1906918936899267,
+           -1.1233857240710694,
+           -1.068755612828122,
+           -1.0282209706745484,
+           -1.0028926323099436,
+           -0.9935465271027065,
+           -1.000604853467912,
+           -1.0241252180783378,
+           -1.0637980125593027,
+           -1.1189521050287428,
+           -1.188568726499504,
+           -1.2713032375603392,
+           -1.3655142736289139,
+           -1.4692995919764478,
+           -1.58053778491632,
+           -1.6969348848880872,
+           -1.8160747720182266,
+           -1.9354722058897613,
+           -2.052627242848548,
+           -2.1650797696615296,
+           -2.2704628844366663,
+           -2.3665538863795486,
+           -2.451321696413913,
+           -2.5229696194193854,
+           -2.5799724736354697,
+           -2.6211072508049975,
+           -2.6454766284761875,
+           -2.652524829661395,
+           -2.6420455104887868,
+           -2.614181549025822,
+           -2.5694168033802627,
+           -2.508560099722781,
+           -2.432721896320482,
+           -2.343284243500621,
+           -2.2418648174510434,
+           -2.130275944078946,
+           -2.0104796444555895,
+           -1.8845398229091082,
+           -1.754572780469072,
+           -1.6226972686875012,
+           -1.4909853011610992,
+           -1.3614149124020005,
+           -1.235825996834309,
+           -1.115880276137281,
+           -1.003026333101682,
+           -0.8984705174297765,
+           -0.803154376863138,
+           -0.7177390995113588,
+           -0.6425972744973545,
+           -0.5778120925219532,
+           -0.5231839203297578,
+           -0.47824399802023776,
+           -0.4422748303084396,
+           -0.4143366766249463,
+           -0.3932993944820912,
+           -0.3778787595476389,
+           -0.3666762775893635,
+           -0.3582214205407063,
+           -0.3510151634057266,
+           -0.3435736718981712,
+           -0.3344709932002354,
+           -0.32237963390056124,
+           -0.3061079691653111,
+           -0.2846335139379239,
+           -0.257131198209388,
+           -0.2229959212955729,
+           -0.1818588112036336,
+           -0.13359678071266237,
+           -0.07833514752180035,
+           -0.016443267266247952,
+           0.05147668923916771,
+           0.12460750413127475,
+           0.20194074463307715,
+           0.28230601924836474,
+           0.36440487593012044,
+           0.4468484380332181,
+           0.5281977749062522,
+           0.6070059306938999,
+           0.6818604891893596,
+           0.7514255355817288,
+           0.8144818881483532,
+           0.8699645140749367,
+           0.9169961126451067,
+           0.9549159443209876,
+           0.9833031033702505,
+           1.0019935717126487,
+           1.0110905490611297,
+           1.0109677252778801,
+           1.002265340868896,
+           0.9858790661799391,
+           0.9629419144858119,
+           0.9347995841298007,
+           0.9029797956247446,
+           0.8691563468481162,
+           0.8351087491568551,
+           0.8026784258507174,
+           0.7737225488825664,
+           0.7500666576036421,
+           0.7334572428539,
+           0.7255154897776731,
+           0.7276933530115101,
+           0.7412330887440564,
+           0.7671312907106009,
+           0.8061083732872766,
+           0.8585843169838385,
+           0.9246613428926563,
+           1.0041140166533726,
+           1.096387103292501,
+           1.2006013062860856,
+           1.315566831990261,
+           1.4398045289223789,
+           1.5715741649835842,
+           1.7089092292015662,
+           1.849657482314422,
+           1.9915263365445943,
+           2.1321320228138108,
+           2.2690514064814207,
+           2.3998752428969725,
+           2.5222616234201567,
+           2.6339883521402663,
+           2.73300301364477,
+           2.817469542413776,
+           2.88581018358518,
+           2.9367418410633177,
+           2.969305939685176,
+           2.9828910802608624,
+           2.9772479360917616,
+           2.952496022925423,
+           2.909122166780873,
+           2.847970690995112
+          ],
+          [
+           2.7956814236040453,
+           2.708490404399532,
+           2.6073235417628196,
+           2.4941189262879284,
+           2.371030608396663,
+           2.2403815071146154,
+           2.1046126270608867,
+           1.966229769235949,
+           1.8277489789527401,
+           1.691642002026312,
+           1.5602830174666666,
+           1.4358978815086376,
+           1.3205170547100704,
+           1.215933292630034,
+           1.1236650635245882,
+           1.044926516462258,
+           0.9806046637175242,
+           0.9312442661756775,
+           0.8970407240798213,
+           0.8778410823453104,
+           0.8731530645903639,
+           0.8821618577567525,
+           0.9037541844171011,
+           0.9365490270885394,
+           0.978934212295679,
+           1.0291079255419258,
+           1.085124115049565,
+           1.1449406548280912,
+           1.2064690783920626,
+           1.2676246646426246,
+           1.3263756576891985,
+           1.3807904326134774,
+           1.4290814785199375,
+           1.4696451571096807,
+           1.5010963072133399,
+           1.5222969003569302,
+           1.5323781060955333,
+           1.5307552946521699,
+           1.5171356840946961,
+           1.4915185253624126,
+           1.454187906257791,
+           1.4056984403563875,
+           1.346854284052661,
+           1.2786820902430582,
+           1.2023986563504154,
+           1.1193741538257265,
+           1.0310919327362833,
+           0.9391059759550865,
+           0.8449971308420801,
+           0.750329270882798,
+           0.6566065349780635,
+           0.5652327581498928,
+           0.4774741452650867,
+           0.394426150608593,
+           0.3169854130583235,
+           0.24582746212535292,
+           0.181390757666248,
+           0.12386745953452014,
+           0.0732011470533511,
+           0.029091526443902452,
+           -0.008994018153107092,
+           -0.04180235303976142,
+           -0.07027049588663152,
+           -0.09549613987296993,
+           -0.11870359243776261,
+           -0.1412060404818567,
+           -0.16436515094061527,
+           -0.18954908688587468,
+           -0.21809006289045155,
+           -0.25124257816937545,
+           -0.29014345159543337,
+           -0.3357747394038266,
+           -0.38893054531028093,
+           -0.450188635628584,
+           -0.5198876512045115,
+           -0.5981105665982189,
+           -0.6846748884835409,
+           -0.7791299136618973,
+           -0.8807611867171314,
+           -0.9886021127007273,
+           -1.1014524959830778,
+           -1.2179035971842551,
+           -1.3363691304364114,
+           -1.4551214674289308,
+           -1.572332176706606,
+           -1.6861159100524856,
+           -1.7945765554862192,
+           -1.8958545108384994,
+           -1.988173894753823,
+           -2.0698885043505846,
+           -2.1395253509202976,
+           -2.1958246565254482,
+           -2.237775273975407,
+           -2.2646445985361336,
+           -2.2760021693189936,
+           -2.2717363084581828,
+           -2.2520633132686707,
+           -2.217528896492267,
+           -2.1690017580763152,
+           -2.107659364056884,
+           -2.034966199301275,
+           -1.9526449463821678,
+           -1.862641218115348,
+           -1.7670826319483792,
+           -1.6682331564418142,
+           -1.5684437799942605,
+           -1.4701006467214914,
+           -1.3755718716175007,
+           -1.2871542850850126,
+           -1.207021364623998,
+           -1.1371735886533378,
+           -1.0793923946042219,
+           -1.03519884179659,
+           -1.0058179711303552,
+           -0.9921497208936256,
+           -0.9947471042088354,
+           -1.013802182523997,
+           -1.049140185256656,
+           -1.1002219326863667,
+           -1.1661545221573142,
+           -1.2457100413876094,
+           -1.3373518819598875,
+           -1.4392680455302471,
+           -1.5494106693307343,
+           -1.665540850191138,
+           -1.7852777211486426,
+           -1.9061506347856765,
+           -2.025653235155616,
+           -2.14129815726373,
+           -2.2506710805874772,
+           -2.351482881321252,
+           -2.441618676440654,
+           -2.519182630084183,
+           -2.5825374972216903,
+           -2.630338008533122,
+           -2.66155735067499,
+           -2.675506163964094,
+           -2.6718436608300413,
+           -2.6505806587274434,
+           -2.6120745158872896,
+           -2.557016152558041,
+           -2.4864095294915125,
+           -2.4015441347529753,
+           -2.3039611951142307,
+           -2.1954144753144837,
+           -2.0778266537929966,
+           -1.953242364097774,
+           -1.8237790646606393,
+           -1.6915769442783315,
+           -1.5587490854457642,
+           -1.4273330923844036,
+           -1.2992453456740571,
+           -1.1762389720404258,
+           -1.0598665179846691,
+           -0.9514481921287082,
+           -0.8520463965429441,
+           -0.7624471055811521,
+           -0.6831484759492664,
+           -0.614356888272164,
+           -0.5559904328950287,
+           -0.5076896657515766,
+           -0.468835278514931,
+           -0.43857215543892175,
+           -0.41583913156574626,
+           -0.39940362722720407,
+           -0.38790021545063863,
+           -0.37987208490470287,
+           -0.37381429367661545,
+           -0.3682176700835697,
+           -0.3616122067973433,
+           -0.3526088139815927,
+           -0.3399383453478172,
+           -0.3224868867492619,
+           -0.2993263981835776,
+           -0.26973992425757265,
+           -0.23324073210009552,
+           -0.18958489571779047,
+           -0.13877701779856952,
+           -0.08106895960526132,
+           -0.016951632304750455,
+           0.052859915790889986,
+           0.1274477066305796,
+           0.20571776067793754,
+           0.286432022628767,
+           0.3682444301973055,
+           0.4497401624668544,
+           0.5294770198712279,
+           0.606027830281074,
+           0.678022746395361,
+           0.7441902994517225,
+           0.8033961032063873,
+           0.8546781594982875,
+           0.8972778010888018,
+           0.9306654167635979,
+           0.9545602351716668,
+           0.9689435942726842,
+           0.9740652888011716,
+           0.9704427646823932,
+           0.9588531124162543,
+           0.9403179964748036,
+           0.9160818400737607,
+           0.8875837596749894,
+           0.856423906827118,
+           0.8243250223127964,
+           0.7930901352903462,
+           0.7645574449264293,
+           0.7405535012112181,
+           0.722845853160387,
+           0.7130963550572061,
+           0.7128163141136952,
+           0.7233246260126485,
+           0.7457099790513811,
+           0.7807981145825822,
+           0.8291250133585341,
+           0.8909167370820933,
+           0.9660764953591514,
+           1.0541793342153989,
+           1.1544746576467135,
+           1.26589660285324,
+           1.3870820975587914,
+           1.516396238883064,
+           1.6519644522850534,
+           1.7917107206154215,
+           1.9334010214880355,
+           2.0746909797884006,
+           2.2131766344644648,
+           2.346447137499816,
+           2.4721381502107547,
+           2.587984679100471,
+           2.691872101075274,
+           2.7818841657619013,
+           2.856346830096754,
+           2.9138668756973978,
+           2.953364380496239,
+           2.9740982598069534,
+           2.9756842549364655,
+           2.958104925704238,
+           2.9217113924624556,
+           2.867216768829966,
+           2.7956814236040435
+          ],
+          [
+           2.73666033131934,
+           2.6407552719764915,
+           2.5321007155241864,
+           2.412776920632147,
+           2.285051641838668,
+           2.151330637503729,
+           2.0141051867285005,
+           1.8758978390956615,
+           1.739207661264435,
+           1.6064562541646872,
+           1.4799357935648612,
+           1.3617602956799655,
+           1.2538212295166642,
+           1.1577484908069893,
+           1.074877621301064,
+           1.006224005104552,
+           0.9524646044011117,
+           0.9139276144559182,
+           0.8905902267302214,
+           0.8820844939316673,
+           0.8877110966524817,
+           0.9064606226514497,
+           0.9370417914145833,
+           0.9779158927237205,
+           1.0273365625472215,
+           1.0833938961548477,
+           1.1440617999131621,
+           1.2072474120805776,
+           1.2708413807560748,
+           1.332767774887742,
+           1.3910324221207855,
+           1.443768514718822,
+           1.4892784005559925,
+           1.526070578281692,
+           1.5528910415879116,
+           1.5687482638620014,
+           1.572931277684733,
+           1.5650204795246838,
+           1.5448909741688177,
+           1.5127084613030348,
+           1.4689178535212186,
+           1.414224996238535,
+           1.349572031007252,
+           1.2761071003375142,
+           1.1951492304363922,
+           1.1081493448860218,
+           1.016648454324882,
+           0.9222341324342207,
+           0.8264964253983779,
+           0.7309843496505761,
+           0.6371641110157992,
+           0.5463801279368652,
+           0.45981986365534344,
+           0.3784833690384698,
+           0.303158311853203,
+           0.23440112291377582,
+           0.17252472837986835,
+           0.11759316466266574,
+           0.06942319229907552,
+           0.027592842353688203,
+           -0.008543351957843726,
+           -0.03983286007423079,
+           -0.06729798037370381,
+           -0.09210372130317576,
+           -0.11552160017828172,
+           -0.13889032980475527,
+           -0.16357444552555245,
+           -0.1909219807779011,
+           -0.22222232632453384,
+           -0.25866540629319845,
+           -0.3013032730405296,
+           -0.35101516340572775,
+           -0.40847697260558546,
+           -0.4741359909924079,
+           -0.5481916159218816,
+           -0.6305825993860363,
+           -0.7209812256566451,
+           -0.8187946361343399,
+           -0.9231733353590655,
+           -1.033026727322304,
+           -1.1470453494907966,
+           -1.263729297897482,
+           -1.3814221746845674,
+           -1.498349743709344,
+           -1.612662353960221,
+           -1.7224800878026492,
+           -1.8259395141342667,
+           -1.9212408773881249,
+           -2.00669453330556,
+           -2.08076545210412,
+           -2.14211464894957,
+           -2.1896364696250803,
+           -2.2224907543787533,
+           -2.2401290228481217,
+           -2.242313964809801,
+           -2.229131681834677,
+           -2.2009962998279624,
+           -2.1586467576125568,
+           -2.103135767622317,
+           -2.0358111367059415,
+           -1.9582898232631136,
+           -1.872425286785514,
+           -1.7802688528953183,
+           -1.684025967011508,
+           -1.5860083390870898,
+           -1.488583087211973,
+           -1.3941200666128888,
+           -1.3049386207023461,
+           -1.2232550110325942,
+           -1.1511317727307215,
+           -1.0904302014109786,
+           -1.0427671076063771,
+           -1.0094768770855134,
+           -0.9915797523547354,
+           -0.989757105150929,
+           -1.0043343053186908,
+           -1.035271612118939,
+           -1.0821633240841113,
+           -1.1442452276318134,
+           -1.220410187536627,
+           -1.309231528834481,
+           -1.4089936745044416,
+           -1.517729330847933,
+           -1.6332623570598883,
+           -1.7532553208410333,
+           -1.8752606313061406,
+           -1.9967740565819974,
+           -2.115289378388377,
+           -2.228352910877966,
+           -2.3336166166625283,
+           -2.428888589106527,
+           -2.5121797357143008,
+           -2.5817455911354608,
+           -2.636122307646105,
+           -2.674156012985226,
+           -2.6950248866379822,
+           -2.698253482095634,
+           -2.6837190099530397,
+           -2.6516494903348473,
+           -2.6026138783287536,
+           -2.5375044580760306,
+           -2.4575119852402203,
+           -2.3640942292612137,
+           -2.2589387219331627,
+           -2.1439206536656488,
+           -2.021056970050477,
+           -1.8924578063999347,
+           -1.760276454738285,
+           -1.6266590850075258,
+           -1.4936954394151734,
+           -1.3633716860749034,
+           -1.237526556279184,
+           -1.1178118005217317,
+           -1.0056578840568198,
+           -0.9022457062592746,
+           -0.8084849727943795,
+           -0.7249996795377327,
+           -0.6521209865789926,
+           -0.5898875740279566,
+           -0.5380533833856272,
+           -0.4961024636366447,
+           -0.4632704645608422,
+           -0.4385721554389216,
+           -0.42083419941274774,
+           -0.40873228590830296,
+           -0.4008316188840016,
+           -0.3956296797878505,
+           -0.3916001329030956,
+           -0.38723671844663465,
+           -0.3810959858445995,
+           -0.37183775579534456,
+           -0.35826226406126854,
+           -0.3393430307225448,
+           -0.314254613530619,
+           -0.28239454006744247,
+           -0.24339886716938122,
+           -0.19715098359294042,
+           -0.14378344892120842,
+           -0.08367284373729592,
+           -0.01742778850376949,
+           0.054129533242195646,
+           0.12998784235805672,
+           0.2089765608560392,
+           0.2898001372498206,
+           0.3710759810124555,
+           0.45137499147781324,
+           0.529263597329412,
+           0.6033461814064526,
+           0.6723067529888792,
+           0.7349487463463334,
+           0.7902318697599616,
+           0.8373050023356755,
+           0.8755342349084464,
+           0.9045252737226311,
+           0.924139568304307,
+           0.9345036844436323,
+           0.9360116154773372,
+           0.9293199057757117,
+           0.9153356449487754,
+           0.8951975751404438,
+           0.8702507322374491,
+           0.8420152103675086,
+           0.8121497934258121,
+           0.7824113336238897,
+           0.7546108717196534,
+           0.7305675837151586,
+           0.7120617020588823,
+           0.7007875940894017,
+           0.698308185643408,
+           0.706011893193685,
+           0.725073174094063,
+           0.7564177227297715,
+           0.8006932325448205,
+           0.8582465126365985,
+           0.9291075960552228,
+           1.0129813088152386,
+           1.1092465880340148,
+           1.2169636489870561,
+           1.3348889088574019,
+           1.4614973842892254,
+           1.5950120952481828,
+           1.733439833715513,
+           1.8746124967191535,
+           2.01623304309241,
+           2.1559250156494256,
+           2.291284478131186,
+           2.4199331516405493,
+           2.539571500006037,
+           2.6480305085288536,
+           2.743320926068041,
+           2.8236787958484255,
+           2.887606184442077,
+           2.933906129078267,
+           2.961710958124502,
+           2.9705032950058143,
+           2.9601292282325993,
+           2.9308033154104014,
+           2.88310528261219,
+           2.817968477602512,
+           2.7366603313193383
+          ],
+          [
+           2.671406759289074,
+           2.5675932130152797,
+           2.4523526925259986,
+           2.3278900367567013,
+           2.1965675383228365,
+           2.06085346936121,
+           1.923268342390367,
+           1.786330157960029,
+           1.6524999131180422,
+           1.5241286362917663,
+           1.403407175289794,
+           1.292319896755969,
+           1.1926033592485266,
+           1.105710900549577,
+           1.032783935831155,
+           0.9746306004567173,
+           0.9317121934828074,
+           0.9041376897055378,
+           0.8916663939835783,
+           0.893718616314084,
+           0.9093940545121244,
+           0.9374973880223013,
+           0.976570415836018,
+           1.0249299178401092,
+           1.0807102858994462,
+           1.141909861779981,
+           1.2064398362587907,
+           1.272174509395977,
+           1.3370016872080592,
+           1.3988719953974789,
+           1.4558459261263046,
+           1.5061374981034017,
+           1.5481535017986625,
+           1.580527418050166,
+           1.6021472367227212,
+           1.6121765589058608,
+           1.6100685374517,
+           1.5955723921448859,
+           1.5687324229207442,
+           1.5298796326271669,
+           1.4796162551706415,
+           1.418793660910581,
+           1.3484842744995877,
+           1.2699482869670153,
+           1.184596070092117,
+           1.0939473039094936,
+           0.9995879050243655,
+           0.9031258924332517,
+           0.80614734759158,
+           0.7101736161156686,
+           0.6166208600622236,
+           0.526763003232478,
+           0.44169901914131854,
+           0.36232539457300716,
+           0.2893144640106415,
+           0.22309915519457008,
+           0.1638645175871243,
+           0.1115462278831771,
+           0.06583608442060916,
+           0.026194320037817253,
+           -0.008131614779621977,
+           -0.03808231521885444,
+           -0.06475640389875564,
+           -0.08937604094065695,
+           -0.11324888930813824,
+           -0.13772755566852765,
+           -0.1641675941598234,
+           -0.1938851996975764,
+           -0.22811572781285566,
+           -0.2679741591883377,
+           -0.3144185795033957,
+           -0.36821767008356876,
+           -0.429923104042681,
+           -0.4998476186236321,
+           -0.5780493903889423,
+           -0.6643231793956956,
+           -0.7581985355415692,
+           -0.8589451792369789,
+           -0.9655854840009983,
+           -1.0769138051485072,
+           -1.191522221066235,
+           -1.3078320861618935,
+           -1.4241306416607853,
+           -1.5386117959100136,
+           -1.6494200731697042,
+           -1.7546966419230325,
+           -1.8526262728076621,
+           -1.9414840439764902,
+           -2.0196806089385957,
+           -2.0858048688801025,
+           -2.138662947546813,
+           -2.177312450685709,
+           -2.201091101794102,
+           -2.20963897886936,
+           -2.2029137297614754,
+           -2.1811983128745287,
+           -2.1451009911988503,
+           -2.095547496531515,
+           -2.033765472607068,
+           -1.9612614959772794,
+           -1.8797911571455028,
+           -1.7913228571235582,
+           -1.6979961319469776,
+           -1.6020754558343955,
+           -1.505900589154881,
+           -1.411834627268509,
+           -1.3222109683543666,
+           -1.2392804509392612,
+           -1.165159914117923,
+           -1.101783405281886,
+           -1.050857202170542,
+           -1.013819729578666,
+           -0.991807338155669,
+           -0.9856267761213969,
+           -0.9957350276937061,
+           -1.0222270183726256,
+           -1.064831501163337,
+           -1.122915243863083,
+           -1.1954954403996336,
+           -1.2812600736866036,
+           -1.3785957683125154,
+           -1.4856224932107924,
+           -1.6002343116040467,
+           -1.7201452319423995,
+           -1.8429390927530578,
+           -1.966122319222917,
+           -2.0871783222512255,
+           -2.203622273255477,
+           -2.3130549810829555,
+           -2.413214621118206,
+           -2.502025120478147,
+           -2.5776400857097927,
+           -2.6384812686071917,
+           -2.6832706989490362,
+           -2.7110557668462443,
+           -2.721226708195496,
+           -2.713526130266136,
+           -2.6880504062031534,
+           -2.645242962511949,
+           -2.5858796776249475,
+           -2.5110467976986923,
+           -2.4221119532695568,
+           -2.3206890229919357,
+           -2.2085977344534315,
+           -2.0878190135369077,
+           -1.9604471900644251,
+           -1.8286402362255223,
+           -1.6945692539572468,
+           -1.5603684371217519,
+           -1.4280867138782585,
+           -1.299642224672844,
+           -1.1767807131037322,
+           -1.0610388025878708,
+           -0.9537130039264486,
+           -0.8558351507882144,
+           -0.7681547955407647,
+           -0.6911289209023596,
+           -0.6249191380007085,
+           -0.5693963532357292,
+           -0.5241526995492061,
+           -0.4885203469581226,
+           -0.4615966370021289,
+           -0.4422748303084392,
+           -0.42927961963167005,
+           -0.42120644585167866,
+           -0.41656356432315483,
+           -0.4138157458557022,
+           -0.41142846197210636,
+           -0.407911398739552,
+           -0.40186016745268943,
+           -0.39199513309255113,
+           -0.3771963613969315,
+           -0.3565337904796537,
+           -0.3292918605221177,
+           -0.29498798186296704,
+           -0.25338438408413555,
+           -0.2044930623019659,
+           -0.14857371740784567,
+           -0.08612476987987615,
+           -0.01786770736639822,
+           0.0552748000549382,
+           0.1322064206160272,
+           0.21168957424325158,
+           0.29238186733774235,
+           0.37287557217438294,
+           0.4517390936728939,
+           0.5275593129320832,
+           0.5989836720329748,
+           0.6647608688606497,
+           0.7237790639866841,
+           0.7751005631809167,
+           0.8179920273581399,
+           0.8519493745130021,
+           0.8767166726367634,
+           0.8922984753753775,
+           0.898965219446884,
+           0.8972514803854301,
+           0.8879470665524921,
+           0.8720811159331128,
+           0.8508995413585716,
+           0.825836342887985,
+           0.7984794667545038,
+           0.7705320344544662,
+           0.7437698895538637,
+           0.7199965104266489,
+           0.7009964118233398,
+           0.6884882049390738,
+           0.6840785032439018,
+           0.6892178492174693,
+           0.7051597954976602,
+           0.7329242037477564,
+           0.7732657274223975,
+           0.8266483228967113,
+           0.8932264900599485,
+           0.9728337819547523,
+           1.0649789473144096,
+           1.1688498842236978,
+           1.283325392170198,
+           1.4069945181704009,
+           1.5381831051825223,
+           1.674986972298805,
+           1.8153109906800307,
+           1.9569131709734435,
+           2.097452750742854,
+           2.2345411674254656,
+           2.3657947261123513,
+           2.4888877239711906,
+           2.6016047756296126,
+           2.701891096817294,
+           2.78789954677827,
+           2.8580333024215236,
+           2.910983137166965,
+           2.945758402576323,
+           2.961710958124503,
+           2.958551460310716,
+           2.9363576027139078,
+           2.8955740891874577,
+           2.8370043185334235,
+           2.7617939559274016,
+           2.671406759289075
+          ],
+          [
+           2.6004727822601934,
+           2.489623211640909,
+           2.368754177129203,
+           2.2401764561109196,
+           2.106326913404415,
+           1.9697154804709205,
+           1.8328706148537182,
+           1.6982845089412868,
+           1.5683593212985734,
+           1.4453556773084175,
+           1.3313446293816584,
+           1.2281641819336766,
+           1.1373813747895216,
+           1.0602607834186533,
+           0.9977401387415423,
+           0.9504135970182511,
+           0.9185230057495506,
+           0.9019573191179145,
+           0.9002601209779583,
+           0.9126450195527065,
+           0.9380184905341525,
+           0.9750095687899774,
+           1.0220056276318932,
+           1.0771933425111384,
+           1.1386038165009147,
+           1.2041607508693677,
+           1.27173047767259,
+           1.3391726341511625,
+           1.4043902516175593,
+           1.4653780545538295,
+           1.5202678181334401,
+           1.5673697129454964,
+           1.605208672250155,
+           1.6325549469086669,
+           1.6484481629182515,
+           1.6522143624609147,
+           1.6434756873740084,
+           1.6221525495071147,
+           1.5884583209056584,
+           1.5428867634553667,
+           1.4861925978870254,
+           1.4193657814020562,
+           1.3436002174419381,
+           1.2602577564795698,
+           1.1708284598294598,
+           1.076888186589298,
+           0.9800546248018008,
+           0.8819429203091652,
+           0.78412205982799,
+           0.6880731385007428,
+           0.5951505873163264,
+           0.5065473537885781,
+           0.42326492226737417,
+           0.34608893098774784,
+           0.27557099474779784,
+           0.21201717872883752,
+           0.15548339459011257,
+           0.10577780901747745,
+           0.062470171973788687,
+           0.02490779162792029,
+           -0.007762290101282757,
+           -0.03656552887523925,
+           -0.06266726934884133,
+           -0.08733617619556955,
+           -0.11190468798970658,
+           -0.13772755566852757,
+           -0.1661395785375796,
+           -0.19841367347196812,
+           -0.23572040651203202,
+           -0.27909008059304274,
+           -0.3293784095566137,
+           -0.38723671844663443,
+           -0.45308749564512746,
+           -0.5271059865178583,
+           -0.6092083643229051,
+           -0.6990468460525366,
+           -0.7960119428556621,
+           -0.8992418512068475,
+           -1.0076388066737072,
+           -1.119892041641803,
+           -1.2345068162498605,
+           -1.3498388324320378,
+           -1.4641331984086545,
+           -1.575566988850536,
+           -1.6822943473974943,
+           -1.7824930057876274,
+           -1.8744110494521324,
+           -1.9564127442541204,
+           -2.0270222535768094,
+           -2.0849641189322448,
+           -2.129199449667807,
+           -2.1589568664842402,
+           -2.173757366965771,
+           -2.173432426168811,
+           -2.1581348079913343,
+           -2.1283417395692266,
+           -2.084850286985238,
+           -2.0287649615506282,
+           -1.9614777771167977,
+           -1.8846411655655586,
+           -1.8001343351848307,
+           -1.7100238206505092,
+           -1.6165191197183602,
+           -1.5219244368246287,
+           -1.4285876544587843,
+           -1.338847726864064,
+           -1.254981735456431,
+           -1.1791528601550876,
+           -1.1133605051492281,
+           -1.0593937717964896,
+           -1.0187893964125894,
+           -0.992795168438035,
+           -0.982339717301961,
+           -0.9880094073030258,
+           -1.0100329125922065,
+           -1.0482738629216586,
+           -1.1022317596198732,
+           -1.1710511649117858,
+           -1.2535389709988394,
+           -1.348189363035528,
+           -1.453215906968069,
+           -1.5665900235977492,
+           -1.6860849583274622,
+           -1.809324225541813,
+           -1.933833400634486,
+           -2.0570940539038345,
+           -2.176598570797404,
+           -2.2899045834952703,
+           -2.394687750036659,
+           -2.4887916588183066,
+           -2.5702737072860495,
+           -2.6374459022450365,
+           -2.6889096529947905,
+           -2.72358377440517,
+           -2.740725081501183,
+           -2.739941136080701,
+           -2.7211948949611244,
+           -2.684801204008127,
+           -2.6314152773831148,
+           -2.5620134926861335,
+           -2.477867015205046,
+           -2.3805089338686924,
+           -2.271695743631247,
+           -2.153364140208671,
+           -2.0275842001900313,
+           -1.8965100999997462,
+           -1.7623295790959768,
+           -1.6272133749689794,
+           -1.4932658494989846,
+           -1.3624779883413332,
+           -1.2366838882595823,
+           -1.1175217534687738,
+           -1.0064003034914386,
+           -0.9044713547847733,
+           -0.8126091800158186,
+           -0.7313970763312785,
+           -0.6611213916197733,
+           -0.6017730701623636,
+           -0.5530565908957673,
+           -0.5144059874611524,
+           -0.485007463854056,
+           -0.46382795717735364,
+           -0.44964885374259905,
+           -0.4411039401458674,
+           -0.43672057001959197,
+           -0.4349629523908965,
+           -0.43427642076003486,
+           -0.43313152424730716,
+           -0.4300667938116491,
+           -0.42372907724930914,
+           -0.4129104053399654,
+           -0.3965804463235741,
+           -0.37391372441413606,
+           -0.34431091724409363,
+           -0.3074137034279617,
+           -0.26311280085276384,
+           -0.21154901453666006,
+           -0.15310729541946314,
+           -0.08840399362832711,
+           -0.018267666979993245,
+           0.0562860267536427,
+           0.13408467122851095,
+           0.21383384751866694,
+           0.294155370287742,
+           0.37362797832753347,
+           0.4508293885827676,
+           0.5243785856964405,
+           0.5929772109639982,
+           0.655448935604947,
+           0.7107757529398732,
+           0.758130201169902,
+           0.7969026310732116,
+           0.8267227584936804,
+           0.8474748868547104,
+           0.8593063464393165,
+           0.8626288707776425,
+           0.8581128118074799,
+           0.8466742799539766,
+           0.8294554782576363,
+           0.8077986765400605,
+           0.7832144378569952,
+           0.7573448609270892,
+           0.7319227349862192,
+           0.7087276142049952,
+           0.6895399045710414,
+           0.6760941147462859,
+           0.6700324523045555,
+           0.6728599470933873,
+           0.6859022541389774,
+           0.7102672301577083,
+           0.7468112917102292,
+           0.7961114513857551,
+           0.8584437938290653,
+           0.9337689991909626,
+           1.0217253514616578,
+           1.1216294873057613,
+           1.2324849519278847,
+           1.3529984368197934,
+           1.4816033847093055,
+           1.6164904643392404,
+           1.7556442463860382,
+           1.8968852561435845,
+           2.037916442432638,
+           2.176372988960309,
+           2.3098743068982976,
+           2.436076987993786,
+           2.552727467607522,
+           2.657713147499329,
+           2.7491107590166894,
+           2.825230807902707,
+           2.8846570308099966,
+           2.92627990867318,
+           2.949323420594559,
+           2.953364380496241,
+           2.938343873651448,
+           2.904570497089063,
+           2.852715302230651,
+           2.783798535243186,
+           2.699168465677254,
+           2.6004727822601916
+          ],
+          [
+           2.5244585337763614,
+           2.407504929346844,
+           2.2820124506028248,
+           2.150378275277923,
+           2.015093243604572,
+           1.8786877394592922,
+           1.7436768097989623,
+           1.6125057980712536,
+           1.4874977532868834,
+           1.3708038320928193,
+           1.2643578375875195,
+           1.1698359375912846,
+           1.088622479116412,
+           1.0217826679715583,
+           0.970042716413107,
+           0.9337778815965645,
+           0.9130086276977427,
+           0.9074049496148499,
+           0.9162987008942823,
+           0.9387035777118394,
+           0.9733422290371112,
+           1.018679794930724,
+           1.0729630243507482,
+           1.1342639945146156,
+           1.200527348885611,
+           1.2696198927324558,
+           1.3393813357838398,
+           1.4076749518937,
+           1.47243693623599,
+           1.5317232810019885,
+           1.5837530597845568,
+           1.6269471069996482,
+           1.659961199350684,
+           1.6817129884203201,
+           1.6914020933874745,
+           1.6885229365917702,
+           1.6728700878464031,
+           1.644536071452424,
+           1.603901778100535,
+           1.5516198075750303,
+           1.4885912428351593,
+           1.4159365173147145,
+           1.3349611811670714,
+           1.247117495148118,
+           1.1539628798611599,
+           1.0571163207773042,
+           0.9582138740467829,
+           0.8588644335915349,
+           0.760606906008649,
+           0.6648698968470036,
+           0.572934941000952,
+           0.48590421314714866,
+           0.4046735338345898,
+           0.3299113461117087,
+           0.2620441800336281,
+           0.20124895205213114,
+           0.14745226748188928,
+           0.10033671149941129,
+           0.05935393210100695,
+           0.023744141736505943,
+           -0.0074385025767261794,
+           -0.035295333742206024,
+           -0.06104825174759757,
+           -0.08600138524670661,
+           -0.11150036877439908,
+           -0.13889032980475513,
+           -0.16947371477865178,
+           -0.20446908916378728,
+           -0.2449720233991107,
+           -0.2919191247822168,
+           -0.34605619626853124,
+           -0.4079113987395534,
+           -0.47777416617795837,
+           -0.5556804765481431,
+           -0.6414049187046924,
+           -0.7344598214239959,
+           -0.8341015290622845,
+           -0.9393437239646194,
+           -1.048977513238031,
+           -1.1615978214735796,
+           -1.275635465915659,
+           -1.3893941406261974,
+           -1.5010914051967148,
+           -1.6089026648762186,
+           -1.7110070454078374,
+           -1.8056340095801342,
+           -1.8911095349995417,
+           -1.9659006746613532,
+           -2.028657353584429,
+           -2.0782503153855503,
+           -2.11380422078689,
+           -2.1347250135690183,
+           -2.1407208056590648,
+           -2.1318156885659736,
+           -2.108356049440247,
+           -2.0710091524468166,
+           -2.0207539354085418,
+           -1.9588641631352768,
+           -1.8868842677659259,
+           -1.8065983881371575,
+           -1.7199932901400257,
+           -1.629216004003162,
+           -1.5365271486017076,
+           -1.4442510238717805,
+           -1.3547236374108311,
+           -1.270239888203009,
+           -1.1930011576509734,
+           -1.1250645549759197,
+           -1.068295030565885,
+           -1.024321507755357,
+           -0.9944980922846803,
+           -0.9798713014854625,
+           -0.9811541148809595,
+           -0.9987074877616728,
+           -1.03252979327032,
+           -1.082254470874573,
+           -1.1471559643781957,
+           -1.2261638355563962,
+           -1.3178847448955513,
+           -1.4206318035096588,
+           -1.5324606246621015,
+           -1.6512112437200124,
+           -1.7745549356990384,
+           -1.9000448432183228,
+           -2.025169237510477,
+           -2.1474061733082928,
+           -2.2642782664547063,
+           -2.3734063217199175,
+           -2.472560567574459,
+           -2.559708313824889,
+           -2.633056935603002,
+           -2.691091201049688,
+           -2.7326040973472203,
+           -2.756720467154273,
+           -2.7629129411225435,
+           -2.7510098377653076,
+           -2.721194894961125,
+           -2.6739988930888114,
+           -2.6102834234216368,
+           -2.5312172422364703,
+           -2.4382458265690103,
+           -2.3330549074073383,
+           -2.217528896492263,
+           -2.09370524039968,
+           -1.9637258274024982,
+           -1.8297866365702649,
+           -1.694086853176544,
+           -1.5587786789886067,
+           -1.425919040394779,
+           -1.2974243423107426,
+           -1.1750293328501613,
+           -1.0602510349878054,
+           -0.9543585696589935,
+           -0.8583495432656445,
+           -0.7729335052148069,
+           -0.6985228021034907,
+           -0.6352309689662744,
+           -0.5828786092715854,
+           -0.5410065287912939,
+           -0.5088957087161688,
+           -0.48559353490510465,
+           -0.4699455471081499,
+           -0.4606318381663642,
+           -0.45620712185322143,
+           -0.45514340190135777,
+           -0.4558741159383555,
+           -0.45683859793259707,
+           -0.4565257020010976,
+           -0.4535154589951804,
+           -0.44651769436178484,
+           -0.434406619870101,
+           -0.4162505207113139,
+           -0.39133579042039623,
+           -0.35918471568047833,
+           -0.3195665775352805,
+           -0.2725018106672425,
+           -0.21825914374826252,
+           -0.157345826834615,
+           -0.09049123171837585,
+           -0.018624283505239765,
+           0.057154657902852825,
+           0.13560670334540784,
+           0.21539123916007996,
+           0.29510564146234347,
+           0.3733268337753839,
+           0.4486535727241431,
+           0.5197483260141927,
+           0.5853776155781213,
+           0.6444497363908142,
+           0.6960488271014249,
+           0.7394643606687108,
+           0.7742152393165215,
+           0.8000678154371842,
+           0.8170473151162537,
+           0.8254423098360311,
+           0.8258020603880429,
+           0.8189267405901145,
+           0.8058507324309471,
+           0.7878193641054019,
+           0.766259633504649,
+           0.7427456177476837,
+           0.7189594102641864,
+           0.6966485471654891,
+           0.6775809810835545,
+           0.6634987308201483,
+           0.6560713771856866,
+           0.6568505881739387,
+           0.6672268396993486,
+           0.6883894518426209,
+           0.7212909859654644,
+           0.7666169469333379,
+           0.8247616094573016,
+           0.8958106412701802,
+           0.9795310320566972,
+           1.0753686597742123,
+           1.1824536395863052,
+           1.299613409678601,
+           1.4253933174506794,
+           1.5580842837022828,
+           1.6957569460664295,
+           1.8363015204732716,
+           1.977472474907558,
+           2.116936986765776,
+           2.25232605681764,
+           2.3812870816193303,
+           2.5015366440368694,
+           2.6109122694305666,
+           2.70742191339984,
+           2.789289995417681,
+           2.8549988700796405,
+           2.9033247322243034,
+           2.9333670813519053,
+           2.9445710214673486,
+           2.936741841063321,
+           2.9100515003551832,
+           2.8650368446554793,
+           2.802589559271468,
+           2.7239380777440068,
+           2.6306218468379576,
+           2.524458533776359
+          ],
+          [
+           2.4440071287765908,
+           2.321933123960239,
+           2.192861387204358,
+           2.0592552275017,
+           1.9236384070535206,
+           1.7885403822058066,
+           1.6564415471775198,
+           1.5297197520591994,
+           1.4105993345386278,
+           1.3011038429905901,
+           1.2030135384778242,
+           1.1178286470697603,
+           1.046739194550244,
+           0.99060209647652,
+           0.9499260015719737,
+           0.9248641998718716,
+           0.9152157134609856,
+           0.9204344917772574,
+           0.9396464400889171,
+           0.9716738235978234,
+           1.0150664152090911,
+           1.0681385965703871,
+           1.1290114833578564,
+           1.195659030309826,
+           1.2659569819488419,
+           1.3377334734084836,
+           1.4088200537205564,
+           1.4771019020178353,
+           1.5405660353200028,
+           1.5973463641046468,
+           1.6457645372078882,
+           1.684365628553081,
+           1.7119478519451785,
+           1.7275856433096695,
+           1.730645618441746,
+           1.720795094331463,
+           1.69800304893977,
+           1.6625335832564978,
+           1.6149321358692612,
+           1.5560048794811587,
+           1.486791896393383,
+           1.4085348817744954,
+           1.3226402558310828,
+           1.23063867552956,
+           1.1341420206255102,
+           1.0347989854051536,
+           0.9342504353937521,
+           0.8340856867211265,
+           0.7358008349755973,
+           0.6407602010784283,
+           0.5501618755366231,
+           0.46500823161914434,
+           0.3860821454018063,
+           0.31392950963338156,
+           0.24884846284156772,
+           0.19088557923481397,
+           0.13983908323191646,
+           0.09526896947610604,
+           0.05651372960170231,
+           0.022713215368213132,
+           -0.007162991594925516,
+           -0.034282476245350066,
+           -0.05991304871654465,
+           -0.08538296102949522,
+           -0.11203935238573358,
+           -0.1412060404818565,
+           -0.17414179458172635,
+           -0.21200021521617415,
+           -0.25579230560882255,
+           -0.3063527522368105,
+           -0.364310838016781,
+           -0.430066793811648,
+           -0.5037742552376203,
+           -0.585329335598726,
+           -0.6743666561151269,
+           -0.7702624957138768,
+           -0.8721450390263941,
+           -0.9789115175204591,
+           -1.0892518595304574,
+           -1.2016782948743792,
+           -1.3145602030765318,
+           -1.4261633549380637,
+           -1.5346925788717607,
+           -1.6383367890833183,
+           -1.735315244782923,
+           -1.8239238699370461,
+           -1.9025804527060082,
+           -1.9698675630136058,
+           -2.0245720752754988,
+           -2.0657202600560547,
+           -2.0926075115068157,
+           -2.104821904380746,
+           -2.1022609221318524,
+           -2.085140862492756,
+           -2.0539986049307006,
+           -2.0096856111376478,
+           -1.9533542206070305,
+           -1.886436493670526,
+           -1.810616039397509,
+           -1.7277934409038795,
+           -1.640046051516404,
+           -1.5495830778763078,
+           -1.4586969868694464,
+           -1.3697123691970516,
+           -1.2849334610190954,
+           -1.2065915646458176,
+           -1.1367936186727585,
+           -1.0774731469388084,
+           -1.0303447646752282,
+           -0.9968633403826549,
+           -0.9781888052116776,
+           -0.9751574704834813,
+           -0.9882605616256367,
+           -1.0176305068957192,
+           -1.0630353359375526,
+           -1.1238813509116867,
+           -1.1992240363376137,
+           -1.2877869776644926,
+           -1.387988367725807,
+           -1.497974499282007,
+           -1.6156594752242766,
+           -1.738770219763809,
+           -1.864895747677091,
+           -1.9915395474948374,
+           -2.1161738608711227,
+           -2.2362945960394285,
+           -2.3494755993223584,
+           -2.453421025439071,
+           -2.5460145944221364,
+           -2.6253645991464434,
+           -2.6898436309077085,
+           -2.738122118621088,
+           -2.769194926893301,
+           -2.782400425781163,
+           -2.7774316263778083,
+           -2.7543391670244213,
+           -2.7135261302661373,
+           -2.6557348658836855,
+           -2.5820261856743025,
+           -2.493751476490226,
+           -2.392518444975239,
+           -2.2801513564225497,
+           -2.1586467576125576,
+           -2.0301257763148017,
+           -1.8967841659043339,
+           -1.7608413104693073,
+           -1.6244894228086881,
+           -1.4898441545111758,
+           -1.3588977942889355,
+           -1.233476159069015,
+           -1.1152001838823484,
+           -1.0054530938544715,
+           -0.9053538977079112,
+           -0.815737780764871,
+           -0.7371438005474424,
+           -0.6698101040931475,
+           -0.6136766976330601,
+           -0.5683956110173509,
+           -0.533348115900428,
+           -0.5076684827658673,
+           -0.4902736016849754,
+           -0.4798976492154612,
+           -0.47513086256165277,
+           -0.4744613850022191,
+           -0.47631907600282897,
+           -0.479120137059511,
+           -0.4813113911450072,
+           -0.4814130699036939,
+           -0.4780590079720511,
+           -0.4700332167773781,
+           -0.4563019089808847,
+           -0.4360401668300205,
+           -0.40865258993644643,
+           -0.37378741676602945,
+           -0.33134378537073744,
+           -0.28147197825596576,
+           -0.22456667920727508,
+           -0.16125345175957176,
+           -0.09236882517129458,
+           -0.018934539804963377,
+           0.05787334448998616,
+           0.13675963988628156,
+           0.21634857292947668,
+           0.29522464113740704,
+           0.3719746863371149,
+           0.4452300544837528,
+           0.5137077079774682,
+           0.5762491818911644,
+           0.6318563294207974,
+           0.6797228829279429,
+           0.7192609631343726,
+           0.7501217976884934,
+           0.7722100582232709,
+           0.7856913884469343,
+           0.7909928706388366,
+           0.7887963597583033,
+           0.7800247986277323,
+           0.7658218096683143,
+           0.7475250338426936,
+           0.7266338513530478,
+           0.7047722670905249,
+           0.683647873048018,
+           0.6650079065829906,
+           0.6505935047997604,
+           0.6420933092876664,
+           0.6410976005616966,
+           0.6490541370826298,
+           0.6672268396993486,
+           0.6966583995103566,
+           0.7381377969584867,
+           0.792173604611732,
+           0.8589738083354065,
+           0.9384327247820129,
+           1.0301254211515525,
+           1.1333098602302172,
+           1.2469368043045055,
+           1.3696673203473022,
+           1.4998975406136608,
+           1.63579015213585,
+           1.7753119200601855,
+           1.916276397523894,
+           2.0563908426350754,
+           2.193306254410596,
+           2.324669356991618,
+           2.448175307199775,
+           2.561619875930647,
+           2.6629498596879797,
+           2.750310514678154,
+           2.8220888714990053,
+           2.8769518820328543,
+           2.913878469463247,
+           2.9321846945152994,
+           2.931541412641797,
+           2.9119839740311306,
+           2.873913706702453,
+           2.8180911180019272,
+           2.7456209467775006,
+           2.6579293925934917,
+           2.556734034822592,
+           2.444007128776592
+          ],
+          [
+           2.359799222551847,
+           2.233631771676338,
+           2.1020552452714583,
+           1.9675782550000755,
+           1.8327361530522581,
+           1.7000360961449617,
+           1.5719028767855645,
+           1.4506267783154905,
+           1.3383146604733391,
+           1.2368454034491319,
+           1.1478307325816457,
+           1.072582315580478,
+           1.012085872630845,
+           0.9669828706777561,
+           0.9375601907286139,
+           0.9237479656250496,
+           0.9251255900950052,
+           0.9409357097825105,
+           0.970105806123307,
+           1.011276814011261,
+           1.062838043554673,
+           1.122967529866738,
+           1.1896768093278007,
+           1.2608590201123795,
+           1.3343391513876537,
+           1.4079252211831936,
+           1.479459148507625,
+           1.5468661011094729,
+           1.608201145862587,
+           1.6616921028839802,
+           1.7057776052439326,
+           1.739139490931276,
+           1.7607287994284657,
+           1.7697848081587437,
+           1.7658467201012136,
+           1.7487577986222007,
+           1.718661934430468,
+           1.675992817825508,
+           1.6214560723938214,
+           1.5560048794811587,
+           1.4808097818468073,
+           1.3972234959673455,
+           1.306741682037595,
+           1.2109607158946176,
+           1.111533575560684,
+           1.0101249952288016,
+           0.9083670503772896,
+           0.8078163191089744,
+           0.7099137173146441,
+           0.6159480301309781,
+           0.5270240613620923,
+           0.4440361986638289,
+           0.36764804852786187,
+           0.2982786351212348,
+           0.23609548491019008,
+           0.18101473910039903,
+           0.13270825282395404,
+           0.0906174583382572,
+           0.05397359387422517,
+           0.02182373462661702,
+           -0.0069380881034569125,
+           -0.03353552561741789,
+           -0.059271264587010396,
+           -0.08548613569265315,
+           -0.11351707877846559,
+           -0.14465509573963237,
+           -0.18010432387934036,
+           -0.22094333489485218,
+           -0.26808970865744103,
+           -0.3222688479372689,
+           -0.38398789227185515,
+           -0.4535154589951802,
+           -0.530867790305497,
+           -0.615801720905784,
+           -0.7078147053403604,
+           -0.8061519620968004,
+           -0.9098206074388099,
+           -1.017610470436263,
+           -1.1281211063570078,
+           -1.2397943629026131,
+           -1.3509517068424615,
+           -1.4598353911763093,
+           -1.5646524382998037,
+           -1.6636203354619503,
+           -1.7550132871564572,
+           -1.8372078463634904,
+           -1.9087267534170855,
+           -1.9682798476403804,
+           -2.0148009819531207,
+           -2.047479962881758,
+           -2.0657886555797123,
+           -2.0695005327544598,
+           -2.0587031044020705,
+           -2.0338028380983375,
+           -1.9955223630402705,
+           -1.9448899405503992,
+           -1.8832213746666278,
+           -1.812094724013943,
+           -1.733318355735293,
+           -1.6488930493789642,
+           -1.5609690091292405,
+           -1.4717987728592894,
+           -1.3836871129083634,
+           -1.2989391035481168,
+           -1.2198075817562668,
+           -1.1484412498109786,
+           -1.0868346597357441,
+           -1.0367812808910957,
+           -0.9998307838993842,
+           -0.9772515781993131,
+           -0.9699995191422555,
+           -0.9786935565754016,
+           -1.0035989337808295,
+           -1.0446183674005327,
+           -1.1012914498990327,
+           -1.172802320791508,
+           -1.2579954560482802,
+           -1.3553992315690506,
+           -1.463256731118228,
+           -1.5795630961483698,
+           -1.7021085587309481,
+           -1.8285261631709202,
+           -1.9563430701126014,
+           -2.0830342517713523,
+           -2.206077330422751,
+           -2.323007285818487,
+           -2.4314697614120666,
+           -2.5292717340522186,
+           -2.6144283762742484,
+           -2.6852050328993426,
+           -2.740153352061619,
+           -2.778140752114858,
+           -2.7983725666575405,
+           -2.8004063862155433,
+           -2.7841583026199377,
+           -2.749900956225971,
+           -2.698253482095637,
+           -2.6301636443274705,
+           -2.5468826331589933,
+           -2.449933172779057,
+           -2.3410717447638913,
+           -2.2222458688947877,
+           -2.095547496531511,
+           -1.9631636589902297,
+           -1.8273255724432607,
+           -1.6902574303537867,
+           -1.5541261137465017,
+           -1.420993018806994,
+           -1.2927691412509696,
+           -1.1711744691832449,
+           -1.057702623029397,
+           -0.9535915454471118,
+           -0.859800889337765,
+           -0.7769965820752422,
+           -0.7055428631102293,
+           -0.64550190471806,
+           -0.596640936509024,
+           -0.5584466081185223,
+           -0.5301461458616976,
+           -0.5107346924971136,
+           -0.4990080687109577,
+           -0.493600064212085,
+           -0.49302325862119706,
+           -0.4957122902664766,
+           -0.5000684365390108,
+           -0.5045043438967332,
+           -0.5074877494926231,
+           -0.5075830695609836,
+           -0.5034897912118399,
+           -0.49407669253555764,
+           -0.4784110286187131,
+           -0.4557819553186172,
+           -0.4257176150024399,
+           -0.3879954750417655,
+           -0.34264568642679993,
+           -0.2899474119420879,
+           -0.23041825630952212,
+           -0.1647971099192479,
+           -0.09402088869685128,
+           -0.019195810970475836,
+           0.058436006101306164,
+           0.13753372648628684,
+           0.21669774934996963,
+           0.29451136252183363,
+           0.36958297579190785,
+           0.4405877983750689,
+           0.5063078379482686,
+           0.5656691405827825,
+           0.6177752606164418,
+           0.6619360452947048,
+           0.6976909384521648,
+           0.7248261476077069,
+           0.7433851760837425,
+           0.753672392175086,
+           0.7562494866918905,
+           0.751924853861013,
+           0.7417361139526557,
+           0.726926174465935,
+           0.7089133957369268,
+           0.6892565821331211,
+           0.669615657615207,
+           0.6517090008620858,
+           0.637268507375598,
+           0.6279935116149404,
+           0.6255047395258198,
+           0.6312994698002662,
+           0.6467090605347958,
+           0.6728599470933878,
+           0.7106391381031738,
+           0.7606651314925101,
+           0.8232650438569394,
+           0.8984585973363722,
+           0.9859494422513404,
+           1.085124115049564,
+           1.1950587440551357,
+           1.314533424707881,
+           1.4420539961499748,
+           1.5758807668672505,
+           1.714063563200771,
+           1.8544823152414849,
+           1.9948922538890128,
+           2.132972674224212,
+           2.266378126805351,
+           2.392790832427056,
+           2.5099730789839683,
+           2.6158183523453364,
+           2.7083999768189035,
+           2.7860160943601433,
+           2.847229893927362,
+           2.890904111347377,
+           2.916228953134166,
+           2.9227427516910343,
+           2.910344830504528,
+           2.8793002421578247,
+           2.8302362347800987,
+           2.76413049921908,
+           2.682291444989027,
+           2.5863309431372867,
+           2.4781301539554055,
+           2.359799222551845
+          ],
+          [
+           2.2725472520933128,
+           2.1433479418922903,
+           2.0103622858551367,
+           1.8761229864447275,
+           1.743155555803385,
+           1.6139236675854893,
+           1.4907760340288072,
+           1.3758960391879855,
+           1.271255292142807,
+           1.1785721689442483,
+           1.099276291407377,
+           1.0344797475620406,
+           0.9849556961424643,
+           0.9511248199133456,
+           0.9330499042383573,
+           0.9304386227029284,
+           0.9426544155592063,
+           0.9687351540493755,
+           1.0074190989777771,
+           1.0571774897326924,
+           1.1162529444811393,
+           1.1827027172337086,
+           1.254445746151502,
+           1.329312342505207,
+           1.4050953131053014,
+           1.4796012821082754,
+           1.550700981438584,
+           1.6163773124756295,
+           1.6747700442233062,
+           1.7242161032731287,
+           1.7632845261808685,
+           1.7908052824730571,
+           1.8058913329112012,
+           1.8079534589375745,
+           1.7967075811171531,
+           1.7721744723324129,
+           1.7346719607989902,
+           1.6847999039446264,
+           1.6234183922191017,
+           1.5516198075750303,
+           1.4706955105914346,
+           1.3820980593356558,
+           1.2873999689150895,
+           1.1882501006861832,
+           1.08632882234237,
+           0.9833031033702498,
+           0.8807827041470031,
+           0.7802785814921019,
+           0.6831645697552612,
+           0.5906433061985065,
+           0.5037172548552619,
+           0.4231655471699598,
+           0.34952720401383625,
+           0.2830911360557445,
+           0.2238931422035845,
+           0.17171994342303074,
+           0.126120106309991,
+           0.08642153197492489,
+           0.05175501561625452,
+           0.021083224921286236,
+           -0.006765694887628211,
+           -0.03306080139872095,
+           -0.05912832914314141,
+           -0.08631003633184296,
+           -0.11592104571863349,
+           -0.1492083150098866,
+           -0.18731085697555944,
+           -0.23122278536053195,
+           -0.2817601909505353,
+           -0.3395327545118488,
+           -0.40492088225078515,
+           -0.47805900797205275,
+           -0.5588255478149468,
+           -0.6468398223007009,
+           -0.7414660807485323,
+           -0.8418245794469899,
+           -0.9468094819423736,
+           -1.055113172058878,
+           -1.1652564023009897,
+           -1.275623546375044,
+           -1.3845020886242374,
+           -1.4901253686775802,
+           -1.5907175095130852,
+           -1.6845393937688165,
+           -1.7699345181764887,
+           -1.8453735504078284,
+           -1.909496436647525,
+           -1.9611509613321845,
+           -1.999426741488274,
+           -2.023683745030586,
+           -2.033574552662395,
+           -2.029059733477229,
+           -2.0104158713178495,
+           -1.978235958299816,
+           -1.9334220592361502,
+           -1.8771703413786296,
+           -1.8109487531994803,
+           -1.7364678191768554,
+           -1.6556451901606792,
+           -1.570564746577546,
+           -1.4834311905399191,
+           -1.3965211793703505,
+           -1.3121321441945426,
+           -1.2325300007776339,
+           -1.159896994030705,
+           -1.0962809216753122,
+           -1.0435469562392239,
+           -1.0033332284328347,
+           -0.9770112503234502,
+           -0.9656521455878321,
+           -0.969999519142255,
+           -0.9904496428727884,
+           -1.0270394617774117,
+           -1.0794427397640909,
+           -1.146974471119549,
+           -1.2286034869718618,
+           -1.3229729907050718,
+           -1.4284285670071435,
+           -1.543053030659175,
+           -1.6647073176599962,
+           -1.791076476816974,
+           -1.919719698045094,
+           -2.0481232172773804,
+           -2.1737548694478623,
+           -2.29411902213115,
+           -2.406810614051979,
+           -2.5095670450097707,
+           -2.600316716241638,
+           -2.677223101578721,
+           -2.7387233379359315,
+           -2.783560456058361,
+           -2.8108085257829933,
+           -2.819890160604493,
+           -2.810586009884349,
+           -2.7830360591240675,
+           -2.7377327546416255,
+           -2.675506163964098,
+           -2.5975015725256427,
+           -2.5051500962326356,
+           -2.400133053780378,
+           -2.2843409882986525,
+           -2.159828351451069,
+           -2.028764961550624,
+           -1.893385418239234,
+           -1.7559376981503307,
+           -1.6186321677890672,
+           -1.4835922314244274,
+           -1.3528077836396126,
+           -1.228092559609139,
+           -1.111046373141716,
+           -1.0030231056740793,
+           -0.9051051619328703,
+           -0.8180849436123374,
+           -0.7424537152682744,
+           -0.6783980511334818,
+           -0.6258038623445273,
+           -0.5842678158420497,
+           -0.5531157736415991,
+           -0.5314277087905386,
+           -0.5180683963881054,
+           -0.5117230384396187,
+           -0.5109368634667337,
+           -0.5141576485779319,
+           -0.5197800453713092,
+           -0.5261905531730535,
+           -0.5318119745736948,
+           -0.5351462091388868,
+           -0.5348142909338004,
+           -0.5295926527807717,
+           -0.5184447029516126,
+           -0.5005469256269544,
+           -0.4753088617132247,
+           -0.4423864877843063,
+           -0.4016886839054541,
+           -0.35337666150636227,
+           -0.2978564057214448,
+           -0.23576436806484985,
+           -0.1679468203620889,
+           -0.0954334450900521,
+           -0.019405886529490365,
+           0.0588378823649738,
+           0.1379224140225092,
+           0.21643581423103717,
+           0.29297184027547324,
+           0.36617193709323653,
+           0.4347660799854168,
+           0.49761132217552007,
+           0.5537270035899681,
+           0.6023256621915917,
+           0.6428387988967276,
+           0.6749367787914511,
+           0.6985423017202576,
+           0.7138370405649143,
+           0.7212612214979367,
+           0.7215061027449444,
+           0.7154994923206187,
+           0.7043846261630722,
+           0.6894929014981063,
+           0.6723111217184413,
+           0.654444054455886,
+           0.637573230146447,
+           0.6234130110175871,
+           0.6136650374128336,
+           0.6099722076980573,
+           0.6138733683412119,
+           0.6267598815213417,
+           0.6498351989391908,
+           0.6840785032439018,
+           0.7302133842462216,
+           0.7886823981236374,
+           0.8596282170239028,
+           0.9428819172781717,
+           1.0379587807468125,
+           1.1440617999131615,
+           1.2600928877501072,
+           1.3846716027999997,
+           1.5161610130539842,
+           1.6527001437345241,
+           1.7922422884202955,
+           1.9325983142420815,
+           2.071483963849698,
+           2.2065700527260304,
+           2.3355343828441653,
+           2.45611414461645,
+           2.566157559858792,
+           2.6636735296453677,
+           2.7468780922659994,
+           2.814236567084739,
+           2.8645003582765556,
+           2.8967375158497477,
+           2.9103562970815986,
+           2.905121135987933,
+           2.881160607731991,
+           2.8389671646046084,
+           2.7793886157648644,
+           2.7036115195592982,
+           2.6131368501481176,
+           2.509748484656459,
+           2.395475228637215,
+           2.2725472520933105
+          ],
+          [
+           2.1829894085530306,
+           2.051845476661965,
+           1.9185582728835893,
+           1.7856631747916114,
+           1.6556545076953055,
+           1.5309316466393175,
+           1.4137473887072818,
+           1.306159790545746,
+           1.2099885821478147,
+           1.126777157408788,
+           1.0577610074984851,
+           1.0038433079814912,
+           0.9655781986547373,
+           0.9431621104686055,
+           0.9364333011658389,
+           0.9448795651190731,
+           0.9676538880582785,
+           1.0035976286999635,
+           1.0512706313103226,
+           1.1089875102752236,
+           1.1748592037561354,
+           1.2468387719556957,
+           1.322770319315154,
+           1.4004398514053857,
+           1.4776268379561284,
+           1.5521552442745175,
+           1.6219428143695427,
+           1.685047439813968,
+           1.7397095273992627,
+           1.78438938393637,
+           1.8177987654453953,
+           1.8389258872029444,
+           1.8470533569238434,
+           1.8417686715890627,
+           1.8229671046406728,
+           1.790846999806346,
+           1.7458976759776406,
+           1.6888803296800337,
+           1.6208024932314202,
+           1.5428867634553665,
+           1.4565346539388448,
+           1.3632865399176677,
+           1.2647787561088064,
+           1.1626989719855896,
+           1.0587410045880745,
+           0.954560235171666,
+           0.8517307727540584,
+           0.7517054555917161,
+           0.6557797021899261,
+           0.5650601186959994,
+           0.48043864214562787,
+           0.40257285229325196,
+           0.33187292240409305,
+           0.2684955055514257,
+           0.21234467206267138,
+           0.16307983038008228,
+           0.12013038239070563,
+           0.08271668982182084,
+           0.04987676500377089,
+           0.02049795129941231,
+           -0.006647270472054136,
+           -0.03286231997096453,
+           -0.05948545168347183,
+           -0.08784769237483787,
+           -0.11923091455811609,
+           -0.15482717599723772,
+           -0.19570042333939655,
+           -0.24275159781076935,
+           -0.2966880940219423,
+           -0.35799841149892314,
+           -0.4269327053860638,
+           -0.5034897912118396,
+           -0.5874109924864109,
+           -0.678181043400777,
+           -0.7750360764762684,
+           -0.8769785412796223,
+           -0.9827987199211285,
+           -1.0911023325624138,
+           -1.2003435659548058,
+           -1.308862714186604,
+           -1.4149274970102672,
+           -1.516777020525847,
+           -1.6126672702145632,
+           -1.7009169793046583,
+           -1.779952697476656,
+           -1.848351896518823,
+           -1.904882990528912,
+           -1.9485412176930426,
+           -1.978579426912214,
+           -1.9945329332734698,
+           -1.9962377486425926,
+           -1.983841654010606,
+           -1.9578077547213044,
+           -1.918910344044586,
+           -1.868223090189231,
+           -1.807099752074795,
+           -1.7371478152869293,
+           -1.6601956169957508,
+           -1.5782536928019306,
+           -1.493471225385287,
+           -1.4080886007799622,
+           -1.3243871799139069,
+           -1.2446374681422891,
+           -1.1710469119455025,
+           -1.1057085685244183,
+           -1.0505518802176639,
+           -1.007296741742688,
+           -0.9774119752232353,
+           -0.962079227527435,
+           -0.9621631789969061,
+           -0.9781888052116768,
+           -1.0103262675658757,
+           -1.058383828141573,
+           -1.1218089940379918,
+           -1.1996979005677757,
+           -1.2908127463365473,
+           -1.3936069009621224,
+           -1.506257122754814,
+           -1.6267021535462998,
+           -1.7526868051746982,
+           -1.8818105206369113,
+           -2.0115792858157495,
+           -2.1394596875954233,
+           -2.2629338630472757,
+           -2.379554063445154,
+           -2.486995566661616,
+           -2.5831067117568094,
+           -2.6659548993097912,
+           -2.7338674985445475,
+           -2.785466725178291,
+           -2.819697699156185,
+           -2.835849055477929,
+           -2.833565660152548,
+           -2.8128531725650094,
+           -2.774074390577994,
+           -2.7179375107629613,
+           -2.645476628476192,
+           -2.558024986385401,
+           -2.457181651041812,
+           -2.3447724510357237,
+           -2.2228061434501787,
+           -2.0934268845332173,
+           -1.958864163135272,
+           -1.8213814095535816,
+           -1.6832245167454438,
+           -1.5465715049072415,
+           -1.4134845244038505,
+           -1.2858653269527187,
+           -1.1654152425106208,
+           -1.0536005818452083,
+           -0.951624245275981,
+           -0.8604041600566168,
+           -0.7805589963091465,
+           -0.7124014286279768,
+           -0.6559390220096878,
+           -0.6108826313244956,
+           -0.5766620178318792,
+           -0.552448208858486,
+           -0.5371819620846588,
+           -0.5296075479853863,
+           -0.5283109364734652,
+           -0.5317613698127226,
+           -0.5383552259294027,
+           -0.5464610262177482,
+           -0.5544644209778423,
+           -0.560811994178025,
+           -0.564052766999595,
+           -0.5628763455670639,
+           -0.5561467506582959,
+           -0.5429310836307726,
+           -0.5225223203003129,
+           -0.4944556795497202,
+           -0.45851818207556,
+           -0.41475119261386073,
+           -0.36344592170443085,
+           -0.3051320459278032,
+           -0.24055978394866495,
+           -0.1706759351124881,
+           -0.09659454348462161,
+           -0.01956298914771742,
+           0.05907557322594735,
+           0.1379224140225092,
+           0.2155649836623126,
+           0.2906190994531718,
+           0.36177042917200436,
+           0.4278141536867301,
+           0.4876917371178785,
+           0.5405238067955587,
+           0.5856382447399429,
+           0.6225927150801394,
+           0.6511909946393345,
+           0.6714926332559292,
+           0.6838156422639567,
+           0.6887320895856349,
+           0.6870566635477501,
+           0.679828450178413,
+           0.6682863457474196,
+           0.653838693192882,
+           0.6380278835881517,
+           0.6224907980583371,
+           0.6089160781199914,
+           0.5989993003926877,
+           0.5943971927312727,
+           0.596682061434979,
+           0.607297602397318,
+           0.62751724269595,
+           0.6584061037503196,
+           0.700787594089403,
+           0.7552155309596817,
+           0.8219525580982124,
+           0.900955475213108,
+           0.9918679267723186,
+           1.094020717730263,
+           1.2064398362587923,
+           1.3278620730311905,
+           1.4567579378563142,
+           1.5913613921625145,
+           1.7297057445260253,
+           1.869664900402796,
+           2.008999020362537,
+           2.145403526881539,
+           2.2765603110152184,
+           2.400189929307394,
+           2.5141035496845516,
+           2.6162534036922804,
+           2.704780531376072,
+           2.778058663761038,
+           2.834733174882782,
+           2.873754148603222,
+           2.8944027422982317,
+           2.896310186633156,
+           2.879468934248715,
+           2.8442356560548507,
+           2.7913259774585075,
+           2.7218010435224285,
+           2.6370461969756547,
+           2.5387422414199317,
+           2.4288299394037134,
+           2.309468556937986,
+           2.1829894085530284
+          ],
+          [
+           2.0918833918127415,
+           1.9598985282465522,
+           1.827419909848348,
+           1.696964150980848,
+           1.570973307189693,
+           1.451762183357971,
+           1.34146863801627,
+           1.2420080326083,
+           1.1550328745784242,
+           1.0818985780778518,
+           1.023636118942721,
+           0.9809321949808291,
+           0.9541173225648282,
+           0.9431621104686052,
+           0.947681756442047,
+           0.9669486159660403,
+           0.9999125007424877,
+           1.0452281814232791,
+           1.1012893993143633,
+           1.1662685394207604,
+           1.238160985906558,
+           1.3148330739878524,
+           1.3940724720125701,
+           1.4736397759020528,
+           1.551320076419004,
+           1.6249732683309492,
+           1.692581909156606,
+           1.752295502773617,
+           1.802470177977334,
+           1.8417028516905707,
+           1.8688591079053567,
+           1.883094183030101,
+           1.883866622117216,
+           1.870944354112618,
+           1.844403123220193,
+           1.8046174030121553,
+           1.7522441053363138,
+           1.688199572783595,
+           1.6136305071199215,
+           1.529879632627169,
+           1.4384470191441803,
+           1.340948091679969,
+           1.2390694293153046,
+           1.134523503903663,
+           1.0290035277196308,
+           0.9241395683043072,
+           0.8214570486841906,
+           0.7223386829824211,
+           0.627990802990038,
+           0.5394149129662537,
+           0.4573851708304081,
+           0.38243233755066386,
+           0.3148345669097049,
+           0.2546152292469437,
+           0.20154777977058558,
+           0.155167499237593,
+           0.11478975684083623,
+           0.07953427652002075,
+           0.048354732886874,
+           0.020072865440675644,
+           -0.0065838167808781,
+           -0.032941760576841325,
+           -0.0603396107897106,
+           -0.09008609455571673,
+           -0.12341868230879832,
+           -0.16146414059516906,
+           -0.20520204344309084,
+           -0.2554322332753883,
+           -0.31274712105672425,
+           -0.37750959108457527,
+           -0.4498371316935024,
+           -0.5295926527807705,
+           -0.6163822785229067,
+           -0.7095602232934389,
+           -0.8082406751691158,
+           -0.9113164291702415,
+           -1.0174838361364587,
+           -1.1252734673637275,
+           -1.23308574403682,
+           -1.3392306479367126,
+           -1.4419705192779488,
+           -1.539564861686462,
+           -1.6303160154963225,
+           -1.7126145302849007,
+           -1.7849830667268016,
+           -1.846117686540658,
+           -1.8949254469030177,
+           -1.9305573008601165,
+           -1.9524354159397732,
+           -1.9602741566687707,
+           -1.9540941297774077,
+           -1.9342288597682973,
+           -1.9013238430842863,
+           -1.856327916874395,
+           -1.8004770686805198,
+           -1.7352710015317145,
+           -1.6624429502590259,
+           -1.5839234148146462,
+           -1.5017986307467606,
+           -1.4182647318766892,
+           -1.3355786722516554,
+           -1.2560070607663671,
+           -1.1817741202526992,
+           -1.115010011804658,
+           -1.0577007638377327,
+           -1.0116410138213927,
+           -0.9783907094641857,
+           -0.9592368267939524,
+           -0.9551610471810107,
+           -0.9668141966626693,
+           -0.9944980922846791,
+           -1.0381552654154824,
+           -1.0973668453503846,
+           -1.1713586925401251,
+           -1.2590156741729521,
+           -1.3589037804013278,
+           -1.4692995919764478,
+           -1.5882264340126138,
+           -1.7134963903483105,
+           -1.8427572124169298,
+           -1.9735430391224125,
+           -2.1033277528034096,
+           -2.229579733197615,
+           -2.349816737929787,
+           -2.461659635255443,
+           -2.5628837426642104,
+           -2.651466582795425,
+           -2.7256309545263013,
+           -2.78388232994151,
+           -2.8250397244187284,
+           -2.8482593439261943,
+           -2.8530504869874753,
+           -2.8392833643872937,
+           -2.8071886930353434,
+           -2.7573491167528186,
+           -2.690682701310646,
+           -2.6084189390906674,
+           -2.5120678756888513,
+           -2.40338313233881,
+           -2.2843197402952797,
+           -2.156987822850723,
+           -2.0236032545983633,
+           -1.886436493670527,
+           -1.7477608194289387,
+           -1.609801214646376,
+           -1.474685107524117,
+           -1.3443961356102694,
+           -1.2207320122216903,
+           -1.1052674684198776,
+           -0.999323112682612,
+           -0.9039408994523226,
+           -0.8198667305216583,
+           -0.7475405339230621,
+           -0.6870939780981428,
+           -0.6383557892880625,
+           -0.6008644520243281,
+           -0.5738878909713414,
+           -0.5564495616693247,
+           -0.5473602221573609,
+           -0.5452545208449178,
+           -0.5486314216890196,
+           -0.5558973985031659,
+           -0.5654112682216873,
+           -0.5755294996345488,
+           -0.5846508302376754,
+           -0.5912590494212124,
+           -0.5939628605148793,
+           -0.5915318157803497,
+           -0.5829274251605001,
+           -0.567328668712278,
+           -0.5441512908558707,
+           -0.5130604180851717,
+           -0.47397621644282223,
+           -0.42707248643245976,
+           -0.37276827652333694,
+           -0.31171277735275216,
+           -0.24476393257263995,
+           -0.17296136462471862,
+           -0.09749436046273867,
+           -0.01966578966591706,
+           0.05914706771198664,
+           0.13753372648628687,
+           0.21409262526446268,
+           0.2874730453069136,
+           0.3564156907769301,
+           0.419790835921279,
+           0.47663300695359484,
+           0.52617125521895,
+           0.5678541913642806,
+           0.6013690848754877,
+           0.6266544860748334,
+           0.6439059946500449,
+           0.6535749757953362,
+           0.6563602076137612,
+           0.6531926269444646,
+           0.6452135205922525,
+           0.6337466804926754,
+           0.62026520028624,
+           0.6063537330539823,
+           0.5936671519486134,
+           0.583886654009495,
+           0.5786744200266045,
+           0.5796279880157208,
+           0.5882355134769515,
+           0.6058330756495919,
+           0.6335651457058442,
+           0.6723492612351012,
+           0.7228458531603869,
+           0.7854340487687583,
+           0.8601941308079285,
+           0.9468971711194728,
+           1.0450021820120663,
+           1.1536609438464966,
+           1.271730477672589,
+           1.3977929419249968,
+           1.5301825468628103,
+           1.6670189042397479,
+           1.806246067013621,
+           1.9456763688167635,
+           2.0830380490573606,
+           2.2160255500323016,
+           2.3423512998356917,
+           2.4597977510149844,
+           2.5662684310239805,
+           2.659836776976973,
+           2.7387915737016737,
+           2.801677889559802,
+           2.8473325071774798,
+           2.874912973653809,
+           2.883919543933574,
+           2.8742094582391706,
+           2.846003175707851,
+           2.799882377273031,
+           2.7367797467206625,
+           2.6579607349726366,
+           2.5649977042183587,
+           2.459737030858262,
+           2.344259914887948,
+           2.220837794218764,
+           2.091883391812743
+          ],
+          [
+           2.000000000000001,
+           1.8682850094361036,
+           1.7377182685412609,
+           1.610776348890632,
+           1.4898283955614957,
+           1.3770850872253926,
+           1.274551292893118,
+           1.1839835182767928,
+           1.1068531195884082,
+           1.044316124040364,
+           0.9971903377389509,
+           0.9659402469434345,
+           0.950670032070562,
+           0.9511248199133449,
+           0.9667001030453626,
+           0.9964590610873088,
+           1.039157331151341,
+           1.0932745989052486,
+           1.1570522215788401,
+           1.2285359537427774,
+           1.3056227292110387,
+           1.3861103607672227,
+           1.467748955767338,
+           1.548292811510631,
+           1.625551550349971,
+           1.6974392808435292,
+           1.7620206270933279,
+           1.8175525523118492,
+           1.862521012454118,
+           1.895671608663897,
+           1.9160335599584843,
+           1.9229364861854468,
+           1.916019671609594,
+           1.895233667031947,
+           1.860834278438624,
+           1.8133691781075427,
+           1.7536575552108433,
+           1.6827633927666994,
+           1.6019631121324684,
+           1.5127084613030346,
+           1.41658563578255,
+           1.3152717080029082,
+           1.2104895010728565,
+           1.1039620736499174,
+           0.9973679842477039,
+           0.8922984753753767,
+           0.7902176613420431,
+           0.6924267198491076,
+           0.6000329788174413,
+           0.5139246590543276,
+           0.4347518837087387,
+           0.3629144008106023,
+           0.29855628972809617,
+           0.24156774056072952,
+           0.19159381192176647,
+           0.14804989189739814,
+           0.11014341376919522,
+           0.0769012167261156,
+           0.047201796346000184,
+           0.019811563763794653,
+           -0.006575870661040576,
+           -0.033298451112878345,
+           -0.06168357988930768,
+           -0.09300630497914109,
+           -0.12844891856052393,
+           -0.16906305707992145,
+           -0.21573532928103517,
+           -0.2691574078403051,
+           -0.32980140541937614,
+           -0.3979012198606036,
+           -0.4734403793621714,
+           -0.5561467506582957,
+           -0.6454942957349123,
+           -0.7407118799175612,
+           -0.8407989508968808,
+           -0.9445477290492291,
+           -1.0505713788099877,
+           -1.157337473199792,
+           -1.2632059229044605,
+           -1.3664704211641971,
+           -1.4654023592217962,
+           -1.5582960967115953,
+           -1.6435144289871344,
+           -1.719533080135049,
+           -1.7849830667268016,
+           -1.8386898229007396,
+           -1.8797080510947568,
+           -1.9073513629076275,
+           -1.921215898734072,
+           -1.9211972599688287,
+           -1.9075002501526457,
+           -1.8806410974396262,
+           -1.8414420158585059,
+           -1.7910181524419728,
+           -1.7307571567074045,
+           -1.6622917934818466,
+           -1.5874661950782254,
+           -1.508296509977559,
+           -1.426926848416448,
+           -1.3455815470181622,
+           -1.2665148717614485,
+           -1.1919593486780764,
+           -1.1240739528948942,
+           -1.0648933978872779,
+           -1.0162797477220762,
+           -0.9798775260235788,
+           -0.9570734175169224,
+           -0.9489615531250433,
+           -0.9563152402204204,
+           -0.9795658488710619,
+           -1.0187893964125874,
+           -1.0737011905070435,
+           -1.1436586994382436,
+           -1.2276726223996812,
+           -1.324425936728794,
+           -1.432300508206471,
+           -1.5494106693307343,
+           -1.6736430033157654,
+           -1.8027014225470426,
+           -1.934156502984097,
+           -2.0654979336576735,
+           -2.194188865460704,
+           -2.3177208977183756,
+           -2.4336684256589414,
+           -2.539741087271326,
+           -2.6338330937510053,
+           -2.7140683026834354,
+           -2.7788399954603262,
+           -2.8268444476640324,
+           -2.857107530176681,
+           -2.869003745929343,
+           -2.8622672884173284,
+           -2.8369948989436153,
+           -2.7936404953553784,
+           -2.733001741033374,
+           -2.656198914305579,
+           -2.5646466206285203,
+           -2.460019058388316,
+           -2.3442096999359507,
+           -2.219286378847058,
+           -2.0874428792756863,
+           -1.9509482011513084,
+           -1.8120947240139378,
+           -1.6731465113714574,
+           -1.5362889862133073,
+           -1.4035811670905047,
+           -1.2769115840757146,
+           -1.1579588967623133,
+           -1.0481581147228956,
+           -0.9486731776038649,
+           -0.8603764908857222,
+           -0.7838358383252563,
+           -0.7193089075868953,
+           -0.6667454761620017,
+           -0.6257971150739307,
+           -0.5958340827741821,
+           -0.5759689056289834,
+           -0.5650859788187027,
+           -0.5618763763227146,
+           -0.5648769344959718,
+           -0.5725125735862389,
+           -0.5831407478136712,
+           -0.5950968690939944,
+           -0.6067395331829778,
+           -0.6164943902707154,
+           -0.6228955444384502,
+           -0.6246234367591292,
+           -0.6205382633289123,
+           -0.6097080996627084,
+           -0.5914310435863066,
+           -0.5652508464155122,
+           -0.5309656728128332,
+           -0.4886298089205055,
+           -0.43854832164009677,
+           -0.38126485462290116,
+           -0.31754292403062323,
+           -0.24834124493701706,
+           -0.17478377313093835,
+           -0.09812528316559678,
+           -0.01971341834518755,
+           0.05905176094738815,
+           0.13675963988628162,
+           0.21203119585578264,
+           0.2835602948783814,
+           0.3501530254178828,
+           0.41076400758794995,
+           0.46452869354399146,
+           0.5107907779410836,
+           0.5491239632035346,
+           0.5793474697981009,
+           0.6015348430632946,
+           0.6160157813483064,
+           0.6233708908814278,
+           0.6244194563522338,
+           0.6202004980084033,
+           0.6119475615298624,
+           0.6010578515962632,
+           0.5890564697203421,
+           0.5775566477621689,
+           0.5682169772156453,
+           0.5626967180688711,
+           0.5626103276043478,
+           0.5694823774212103,
+           0.5847040254418048,
+           0.6094921786570251,
+           0.644852422554853,
+           0.691546705971864,
+           0.7500666576036421,
+           0.8206132753387513,
+           0.9030835752431616,
+           0.9970646172067864,
+           1.101835143154574,
+           1.2163748757950597,
+           1.3393813357838389,
+           1.4692938476366213,
+           1.6043242244022777,
+           1.7424934524980966,
+           1.881673545434192,
+           2.019633602243851,
+           2.1540889966407493,
+           2.282752539029301,
+           2.4033863976512815,
+           2.5138535388224574,
+           2.6121674501337266,
+           2.6965389446531876,
+           2.7654189078139333,
+           2.8175359403242126,
+           2.8519279679163563,
+           2.867967029244014,
+           2.865376613357637,
+           2.844241094062548,
+           2.8050069958260155,
+           2.748476020195102,
+           2.6757899581855646,
+           2.588407808013888,
+           2.488075604138452,
+           2.376789638294705,
+           2.2567539117849393,
+           2.130332796838011,
+           1.9999999999999984
+          ]
+         ]
+        }
+       ],
+       "layout": {
+        "scene": {
+         "xaxis": {
+          "backgroundcolor": "rgb(230, 230,230)",
+          "gridcolor": "rgb(255, 255, 255)",
+          "showbackground": true,
+          "zerolinecolor": "rgb(255, 255, 255)"
+         },
+         "yaxis": {
+          "backgroundcolor": "rgb(230, 230,230)",
+          "gridcolor": "rgb(255, 255, 255)",
+          "showbackground": true,
+          "zerolinecolor": "rgb(255, 255, 255)"
+         },
+         "zaxis": {
+          "backgroundcolor": "rgb(230, 230,230)",
+          "gridcolor": "rgb(255, 255, 255)",
+          "showbackground": true,
+          "zerolinecolor": "rgb(255, 255, 255)"
+         }
+        },
+        "template": {
+         "data": {
+          "bar": [
+           {
+            "error_x": {
+             "color": "#2a3f5f"
+            },
+            "error_y": {
+             "color": "#2a3f5f"
+            },
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             }
+            },
+            "type": "bar"
+           }
+          ],
+          "barpolar": [
+           {
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             }
+            },
+            "type": "barpolar"
+           }
+          ],
+          "carpet": [
+           {
+            "aaxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "baxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "type": "carpet"
+           }
+          ],
+          "choropleth": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "choropleth"
+           }
+          ],
+          "contour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "contour"
+           }
+          ],
+          "contourcarpet": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "contourcarpet"
+           }
+          ],
+          "heatmap": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmap"
+           }
+          ],
+          "heatmapgl": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmapgl"
+           }
+          ],
+          "histogram": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "histogram"
+           }
+          ],
+          "histogram2d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "histogram2d"
+           }
+          ],
+          "histogram2dcontour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "histogram2dcontour"
+           }
+          ],
+          "mesh3d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "mesh3d"
+           }
+          ],
+          "parcoords": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "parcoords"
+           }
+          ],
+          "pie": [
+           {
+            "automargin": true,
+            "type": "pie"
+           }
+          ],
+          "scatter": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatter"
+           }
+          ],
+          "scatter3d": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatter3d"
+           }
+          ],
+          "scattercarpet": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattercarpet"
+           }
+          ],
+          "scattergeo": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergeo"
+           }
+          ],
+          "scattergl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergl"
+           }
+          ],
+          "scattermapbox": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattermapbox"
+           }
+          ],
+          "scatterpolar": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterpolar"
+           }
+          ],
+          "scatterpolargl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterpolargl"
+           }
+          ],
+          "scatterternary": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterternary"
+           }
+          ],
+          "surface": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "surface"
+           }
+          ],
+          "table": [
+           {
+            "cells": {
+             "fill": {
+              "color": "#EBF0F8"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "header": {
+             "fill": {
+              "color": "#C8D4E3"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "type": "table"
+           }
+          ]
+         },
+         "layout": {
+          "annotationdefaults": {
+           "arrowcolor": "#2a3f5f",
+           "arrowhead": 0,
+           "arrowwidth": 1
+          },
+          "coloraxis": {
+           "colorbar": {
+            "outlinewidth": 0,
+            "ticks": ""
+           }
+          },
+          "colorscale": {
+           "diverging": [
+            [
+             0,
+             "#8e0152"
+            ],
+            [
+             0.1,
+             "#c51b7d"
+            ],
+            [
+             0.2,
+             "#de77ae"
+            ],
+            [
+             0.3,
+             "#f1b6da"
+            ],
+            [
+             0.4,
+             "#fde0ef"
+            ],
+            [
+             0.5,
+             "#f7f7f7"
+            ],
+            [
+             0.6,
+             "#e6f5d0"
+            ],
+            [
+             0.7,
+             "#b8e186"
+            ],
+            [
+             0.8,
+             "#7fbc41"
+            ],
+            [
+             0.9,
+             "#4d9221"
+            ],
+            [
+             1,
+             "#276419"
+            ]
+           ],
+           "sequential": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ],
+           "sequentialminus": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ]
+          },
+          "colorway": [
+           "#636efa",
+           "#EF553B",
+           "#00cc96",
+           "#ab63fa",
+           "#FFA15A",
+           "#19d3f3",
+           "#FF6692",
+           "#B6E880",
+           "#FF97FF",
+           "#FECB52"
+          ],
+          "font": {
+           "color": "#2a3f5f"
+          },
+          "geo": {
+           "bgcolor": "white",
+           "lakecolor": "white",
+           "landcolor": "#E5ECF6",
+           "showlakes": true,
+           "showland": true,
+           "subunitcolor": "white"
+          },
+          "hoverlabel": {
+           "align": "left"
+          },
+          "hovermode": "closest",
+          "mapbox": {
+           "style": "light"
+          },
+          "paper_bgcolor": "white",
+          "plot_bgcolor": "#E5ECF6",
+          "polar": {
+           "angularaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "radialaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "scene": {
+           "xaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "yaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "zaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           }
+          },
+          "shapedefaults": {
+           "line": {
+            "color": "#2a3f5f"
+           }
+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        },
+        "title": {
+         "text": "Parametric Plot"
+        }
+       }
+      },
+      "text/html": [
+       "<div>\n",
+       "        \n",
+       "        \n",
+       "            <div id=\"284a1e3b-8dc4-43e6-b7b6-ac7793851bb4\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
+       "            <script type=\"text/javascript\">\n",
+       "                require([\"plotly\"], function(Plotly) {\n",
+       "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
+       "                    \n",
+       "                if (document.getElementById(\"284a1e3b-8dc4-43e6-b7b6-ac7793851bb4\")) {\n",
+       "                    Plotly.newPlot(\n",
+       "                        '284a1e3b-8dc4-43e6-b7b6-ac7793851bb4',\n",
+       "                        [{\"type\": \"surface\", \"x\": [[0.0, 0.056018243791582024, 0.11876723188987023, 0.18784331648031274, 0.26260954764839783, 0.34221269273537636, 0.4256064272344647, 0.5115800902079969, 0.5987922505586359, 0.6858082029981799, 0.7711404074799797, 0.8532908058874493, 0.9307938969633416, 1.0022594262020141, 1.0664135523722633, 1.1221373864195807, 1.168501860909015, 1.2047979773947326, 1.2305615929452358, 1.2455920426975036, 1.249964049390397, 1.2440325395004885, 1.2284301646618387, 1.2040575120168417, 1.172066173382897, 1.1338350259531544, 1.0909402520781157, 1.0451197880882066, 0.9982330380059466, 0.9522168136540172, 0.9090385648829727, 0.8706480397872174, 0.8389285628616627, 0.8156491377795313, 0.802418570276951, 0.8006427656875247, 0.8114862858946872, 0.8358391534936732, 0.874289769089086, 0.9271046638310337, 0.9942156469955521, 1.0752147315912117, 1.1693570339386614, 1.2755716505000183, 1.3924803216553023, 1.5184235023904424, 1.651493278646445, 1.78957239985179, 1.930378547077465, 2.0715128260588864, 2.2105113682559003, 2.3448988438176572, 2.4722426397760056, 2.5902064362976542, 2.6966019239346175, 2.7894374453263917, 2.8669624147823414, 2.927706466941762, 2.9705124089224983, 2.9945621960518736, 2.9993953158989832, 2.984919144902403, 2.95141103205167, 2.899512060213838, 2.8302126330304667, 2.744830229048498, 2.644979850182069, 2.5325378642269136, 2.4096000967752813, 2.2784351627356747, 2.1414341384872597, 2.0010577598229524, 1.859782386243655, 1.720045997549324, 1.5841954834581968, 1.454436451351645, 1.3327867121122297, 1.221034511042566, 1.1207024523491833, 1.0330179245985116, 0.9588906744010262, 0.8988980003165823, 0.8532778529262875, 0.8219299347680321, 0.8044247001127186, 0.8000199641216524, 0.8076846484377509, 0.8261290201838827, 0.8538406278149349, 0.8891250040229537, 0.93015009614457, 0.9749933008966695, 1.0216899247474471, 1.0682818650929202, 1.112865311200247, 1.1536362974020187, 1.1889330033462424, 1.2172737855780649, 1.237390039033666, 1.248253123234139, 1.2490947426088512, 1.2394203395337227, 1.219015238066734, 1.1879434614810382, 1.1465393328824192, 1.09539215078203, 1.0353244059065794, 0.9673641674083236, 0.8927124119504425, 0.8127061942752944, 0.7287786597116185, 0.6424169751285275, 0.5551193032367778, 0.4683519647061953, 0.38350792287249386, 0.30186768714330153, 0.2245636646065025, 0.15254889651988446, 0.0865709997041844, 0.02715199535426616, -0.02542544706904995, -0.07112499146024243, -0.1101566601808608, -0.14296990264444673, -0.17023988936249904, -0.19284739082306204, -0.21185276882987894, -0.22846476278230923, -0.24400489088369218, -0.25986840292288904, -0.2774828140979546, -0.298265115957844, -0.3235787992016268, -0.35469183277057104, -0.39273672410032845, -0.438673737008059, -0.49325826763785996, -0.557013277039616, -0.6302075538247861, -0.7128404350298457, -0.8046334514381782, -0.9050291892005368, -1.013197477010279, -1.1280488219037779, -1.2482548316387538, -1.372275182206858, -1.4983905198815513, -1.6247405325609303, -1.7493662889585662, -1.8702558298914445, -1.985391906443385, -2.0928006974624234, -2.190600305328375, -2.277047825136191, -2.350583808578468, -2.409872999329884, -2.4538403003603992, -2.4817010433547493, -2.4929847636638556, -2.487551837741151, -2.4656025100969456, -2.427678019292502, -2.3746537229328624, -2.3077243153383202, -2.2283814238234356, -2.138384055561092, -2.039722542272693, -1.934576790137821, -1.825269783394303, -1.7142174086040605, -1.6038757595409125, -1.4966871477872068, -1.3950260797610032, -1.3011464661105727, -1.217131304030897, -1.1448460176490634, -1.085896557502323, -1.041593249307868, -1.0129212473679412, -1.000518292328518, -1.00466030038609, -1.0252551256044227, -1.0618446432659507, -1.113615104849343, -1.179415519092741, -1.2577836234387658, -1.3469788305833141, -1.4450213702257828, -1.5497367004363096, -1.6588041398433022, -1.769808574076164, -1.8802940199242353, -1.9878177901598, -2.0900039918646045, -2.184595111593696, -2.269500491254376, -2.3428405778832393, -2.4029859365783026, -2.44859014603917, -2.47861584725169, -2.492353384081862, -2.4894316557595793, -2.4698209909662308, -2.4338280468206586, -2.3820829287286567, -2.315518914097043, -2.2353453397379655, -2.1430143750870663, -2.0401825471828503, -1.9286680052212164, -1.8104046094757327, -1.6873939991503402, -1.5616568346742017, -1.435184421144021, -1.3098919008916443, -1.1875741550715309, -1.0698654780185384, -0.9582039859095083, -0.853801595604957, -0.757620263659397, -0.6703550130757956, -0.592424100551756, -0.5239664941319829, -0.46484664494438344, -0.4146663517320113, -0.372783337835124, -0.33833599160518646, -0.3102735671559489, -0.28739100671277595, -0.2683674319788744, -0.25180726271244763, -0.23628285829676418, -0.22037754400412285, -0.20272787870956255, -0.18206404507284082, -0.15724729601519458, -0.12730347129111383, -0.09145170303299512, -0.04912755663626539, -4.89858719658941e-16], [0.0, 0.05839307618986191, 0.1233617925380928, 0.1943820511637335, 0.2707050756209538, 0.35137790784807, 0.43526974876700136, 0.5211034498675013, 0.6074913271161951, 0.6929743536339265, 0.7760636967226291, 0.8552835003279383, 0.9292137775668231, 0.9965322704969629, 1.0560541560935521, 1.106768527931227, 1.1478706611216773, 1.1787891717153385, 1.1992073084760109, 1.2090777615351576, 1.2086305352779076, 1.1983736078413698, 1.179086282440644, 1.1518053217979933, 1.1178041415652606, 1.0785655171549693, 1.0357484263305083, 0.991149803004612, 0.946662112073751, 0.904227767348762, 0.8657915018486927, 0.8332518596425427, 0.8084130094642701, 0.7929380816172898, 0.7883052010910294, 0.7957673319417965, 0.8163169621798083, 0.850656546686698, 0.8991754907434103, 0.9619343018388712, 1.038656366318649, 1.1287276242924813, 1.231204225528916, 1.3448280554991456, 1.468049829045505, 1.5990592640613925, 1.7358216736428271, 1.8761201567053378, 2.017602427977797, 2.1578312120413066, 2.2943370355739248, 2.4246721894601997, 2.546464599512747, 2.657470342090816, 2.7556235690016173, 2.839082664097144, 2.9062715405612276, 2.955915100945629, 2.987068018836656, 2.9991361583071887, 2.991890121222418, 2.9654705988009393, 2.920385398060126, 2.8574982111757214, 2.7780093915615747, 2.683429189867384, 2.5755440814978363, 2.4563769803430384, 2.328142277221598, 2.193196762591293, 2.0539875884545866, 1.912998491784189, 1.7726955396117317, 1.635473663279969, 1.5036052261231385, 1.3791918156280571, 1.2641203692913279, 1.1600246349772438, 1.0682528342970046, 0.9898422446552699, 0.9255012459279349, 0.8755991954348747, 0.840164304446122, 0.8188894955936774, 0.8111460280144528, 0.8160044905411793, 0.832262587348095, 0.8584789794366825, 0.8930123031273065, 0.9340643667464071, 0.9797264318501301, 1.0280274178605375, 1.076982830484107, 1.12464320558776, 1.169140881438574, 1.2087339627405411, 1.241846418371089, 1.2671033590863767, 1.2833606690437627, 1.289728312527245, 1.285586801012501, 1.2705964815323798, 1.2446994907693827, 1.2081144057955546, 1.1613238072234056, 1.1050551490953704, 1.0402554976619536, 0.9680608540947259, 0.889760910346337, 0.8067601994775061, 0.7205366890513463, 0.6325989265058547, 0.5444428772934938, 0.4575095992761028, 0.37314487037117905, 0.29256183148287823, 0.21680762475414275, 0.14673490025958624, 0.08297893516227652, 0.02594096137734948, -0.024221865308999793, -0.06759959577673874, -0.10452563948015624, -0.1355660420009156, -0.16150217240002984, -0.18330727715576306, -0.20211751847447693, -0.21919826003475956, -0.23590648907277387, -0.2536503669271845, -0.2738469780922695, -0.2978793984695675, -0.32705422553893393, -0.3625607059855315, -0.40543256005097483, -0.4565135373876702, -0.5164276480591268, -0.5855548967917936, -0.6640132115084659, -0.751647101967686, -0.8480234148669165, -0.9524343722735776, -1.0639078952199967, -1.181225028376585, -1.302944099573765, -1.427431074164192, -1.5528954031900657, -1.6774305201230104, -1.7990580172432522, -1.915774432682567, -2.0255995053521128, -2.126624709343103, -2.2170608631598383, -2.2952836228263256, -2.359875711262457, -2.409664808378247, -2.4437561253953013, -2.4615588106093584, -2.462805479176601, -2.4475643230157984, -2.4162434345880546, -2.3695871658069274, -2.308664536053045, -2.23484989648924, -2.149796246843658, -2.0554017808931913, -1.9537704035931167, -1.8471671120374757, -1.7379692604969759, -1.628614833482099, -1.5215489275264023, -1.4191696902461675, -1.3237749829815975, -1.2375110204733382, -1.162324197839308, -1.099917242596699, -1.0517107293509165, -1.0188108694519324, -1.001984340424485, -1.0016407538817766, -1.0178231799606976, -1.0502069554566393, -1.0981068064250397, -1.1604921188290593, -1.2360099976419718, -1.3230155703539923, -1.4196088195677123, -1.5236770754511848, -1.6329421659837626, -1.7450111143903977, -1.8574291915308003, -1.9677340782469974, -2.0735098700224395, -2.1724396642761907, -2.2623555089643412, -2.3412845588998135, -2.4074903816249327, -2.459508475395202, -2.4961752048564003, -2.5166495217769955, -2.5204270147349424, -2.507346018597796, -2.4775857073746135, -2.431656287820614, -2.3703816012866845, -2.2948746230716233, -2.2065065175166567, -2.1068700591648164, -1.9977383618033648, -1.881019964943558, -1.7587114086899003, -1.6328484810898363, -1.5054573457165008, -1.37850675093735, -1.2538624863183885, -1.1332451869025082, -1.0181924943864216, -0.9100264678753457, -0.8098269988971484, -0.7184118292191877, -0.6363235996855633, -0.5638241780801986, -0.5008963284583358, -0.4472525981364828, -0.40235111625691283, -0.36541782410700424, -0.33547449651310995, -0.31137176965020535, -0.29182626708915466, -0.27546081590124627, -0.26084667061817757, -0.24654661661294966, -0.23115780713105977, -0.21335320014254341, -0.19192050204854588, -0.1657975939790869, -0.13410351118057787, -0.09616416437742566, -0.05153213097427566, -5.123193964678499e-16], [0.0, 0.06070772999554664, 0.1277789874912215, 0.20057348261239466, 0.2782368071160924, 0.35972423103292983, 0.44382996474534153, 0.5292211141982028, 0.6144754327667938, 0.6981218719908907, 0.7786828575160483, 0.8547171681179845, 0.924862275888931, 0.9878750150806562, 1.0426694855375682, 1.0883511631942018, 1.1242462831257363, 1.1499256778312672, 1.165222391889602, 1.1702425504097649, 1.1653691289033175, 1.1512584520770528, 1.1288294340764735, 1.0992457582587285, 1.0638913759724327, 1.0243398764996585, 0.9823184399096685, 0.9396672270400827, 0.8982951825336294, 0.8601333247023029, 0.8270866674391376, 0.8009859625767671, 0.7835404648275324, 0.7762929052884145, 0.780577813754404, 0.7974842557910837, 0.827823949417941, 0.8721056007641861, 0.9305161512051146, 1.002909463831903, 1.0888027986625373, 1.1873812381276154, 1.2975100316657768, 1.4177546354720136, 1.5464080353024223, 1.6815247613901227, 1.8209608393875698, 1.962418773909324, 2.1034965353641475, 2.2417394194719202, 2.3746935746950637, 2.499959947648638, 2.615247381550837, 2.7184236183595645, 2.807563001084302, 2.8809897477956636, 2.9373157712909337, 2.9754721457519073, 2.99473347097768, 2.994734552277483, 2.9754789958059926, 2.93733951060457, 2.881049905224405, 2.807688963772384, 2.7186565787492, 2.615642701461868, 2.500589840632847, 2.3756499919721046, 2.243137012237899, 2.105475557522834, 1.9651477846029688, 1.8246390642836372, 1.6863839755824528, 1.552713838864316, 1.425807004992722, 1.3076430472368181, 1.1999619048412489, 1.1042289042652618, 1.0216064391795414, 0.9529329269606629, 0.8987094816777189, 0.859094555804268, 0.8339066097309692, 0.8226346743438022, 0.8244564822209216, 0.8382636620288819, 0.8626933228827166, 0.8961652048573273, 0.9369234421490628, 0.9830818797122134, 1.032671805061197, 1.0836909061997388, 1.1341522454707245, 1.18213204793761, 1.2258151413895069, 1.2635369521517166, 1.2938210548187707, 1.3154113923823705, 1.3272984229752611, 1.328738607042203, 1.319266820192656, 1.2987014579624747, 1.267142184661474, 1.2249604647433479, 1.1727831970394704, 1.1114699452019554, 1.0420844174891193, 0.9658609916218401, 0.8841672023039022, 0.7984632071200084, 0.7102593184890628, 0.6210727334043924, 0.5323846077866977, 0.44559860808827956, 0.3620020297328011, 0.2827305011928985, 0.20873719583382644, 0.1407673535695533, 0.07933877396018724, 0.02472878520740443, -0.023031976421486633, -0.06415882056988918, -0.09910531626038212, -0.12854887248440303, -0.15336996974531067, -0.1746255927808832, -0.19351756704788511, -0.2113566359951604, -0.22952322925725382, -0.24942596077819054, -0.27245895824384125, -0.2999591594462602, -0.33316471641647083, -0.37317562416541433, -0.4209176382231223, -0.47711046514236455, -0.5422411047038026, -0.616543094335409, -0.6999822584267406, -0.7922494014632225, -0.8927602083175248, -1.0006624320094062, -1.1148502633710562, -1.2339855930019257, -1.3565256982981706, -1.480756721678254, -1.6048321546150706, -1.726815409572682, -1.8447254518141873, -1.9565843781252816, -2.0604657719935973, -2.154542636225672, -2.2371337051827807, -2.306746969846857, -2.362119309119278, -2.402251208713324, -2.4264356626381227, -2.434280488857933, -2.4257234469414555, -2.401039717592427, -2.360841487676006, -2.306069575228898, -2.2379772222823338, -2.158106374382458, -2.0682569497565906, -1.9704497736030029, -1.8668840097092985, -1.759890058645296, -1.6518790057223391, -1.5452897899184184, -1.442535324825505, -1.345948832859989, -1.2577316536933687, -1.1799037570596016, -1.1142581294789404, -1.0623201154375093, -1.0253126783084408, -1.0041284075692625, -0.999308940014949, -1.0110322875350708, -1.0391083768661418, -1.0829829120921761, -1.1417494732779985, -1.2141695692794054, -1.2987001742309054, -1.393528100047581, -1.4966103957959098, -1.6057198229072696, -1.7184943363640859, -1.8324894090538577, -1.9452319716950024, -2.054274705636112, -2.157249421231899, -2.251918280473279, -2.336221678414714, -2.408321682285404, -2.4666400378830122, -2.509889887175623, -2.5371004956502112, -2.5476344590220923, -2.5411970422391073, -2.517837494762739, -2.4779423801893925, -2.4222211506268154, -2.3516843821522158, -2.2676152626073427, -2.1715350826687474, -2.0651636216903864, -1.9503754378526144, -1.8291531648321295, -1.7035389823294516, -1.575585463839023, -1.4473070112291726, -1.3206330619643238, -1.1973642018398958, -1.0791322353254238, -0.967365159124485, -0.8632578550953759, -0.7677491695341351, -0.6815058807834854, -0.6049138803661119, -0.5380767088012897, -0.48082140057377803, -0.4327114080635958, -0.3930661962348395, -0.36098693296571827, -0.33538754823891, -0.31503030277037725, -0.2985648963218236, -0.2845700606384744, -0.271596523769169, -0.25821020286580987, -0.24303448211190687, -0.22479046114853093, -0.20233411647112876, -0.17468940227017227, -0.14107642591566966, -0.10093396395309594, -0.053935733749470964, -5.344934411386254e-16], [0.0, 0.06294133585385796, 0.13197901028207656, 0.20636184032097987, 0.28513692575109906, 0.36717653800418176, 0.4512100493879049, 0.5358600574058343, 0.6196817476655808, 0.7012044519972594, 0.7789742981755478, 0.8515968156105127, 0.917778358394535, 0.9763652332839994, 1.0263794749396273, 1.0670502927138317, 1.0978403204362421, 1.1184659303522049, 1.1289110213856883, 1.1294338565095918, 1.120566700097089, 1.1031081892864054, 1.0781085590220174, 1.0468480238708495, 1.0108087963317438, 0.9716413867006607, 0.9311259794362596, 0.891129811581781, 0.8535615868040927, 0.8203240412309811, 0.7932658323521931, 0.7741339483288977, 0.7645278313801688, 0.7658563754726933, 0.7792988960608197, 0.8057710795611857, 0.8458968047410681, 0.8999865900301365, 0.968023263277753, 1.0496552775048613, 1.144197911965315, 1.250642406848499, 1.3676728869120789, 1.4936907389801073, 1.6268459252700822, 1.765074543442703, 1.906141789334673, 2.047689343382924, 2.187286090137556, 2.3224809947813654, 2.4508569033782934, 2.57008400612164, 2.6779717058769372, 2.7725176677974983, 2.8519528889691204, 2.9147817184204983, 2.959815875230777, 2.9862016530485103, 2.993439659709726, 2.981396616921748, 2.9503089328872454, 2.9007779557157605, 2.8337570127693255, 2.7505305359179846, 2.6526857603032985, 2.54207766006247, 2.4207879442806415, 2.2910790763352042, 2.155344396383994, 2.0160555172109262, 1.8757082258013982, 1.7367681553931524, 1.6016174945848012, 1.4725039713804644, 1.3514932915503866, 1.2404261238684327, 1.1408806118150718, 1.0541412550147482, 0.9811748473838257, 0.9226139865596523, 0.878748484912204, 0.8495248208412304, 0.83455357484033, 0.8331246027272065, 0.8442295131975932, 0.8665908429822705, 0.8986971646067684, 0.9388432229130262, 0.9851740804551143, 1.0357321614110342, 1.0885060209055644, 1.1414796330711086, 1.1926809875154085, 1.2402288101056422, 1.2823762793660012, 1.3175506928475273, 1.344388146408874, 1.361762420659989, 1.3688074195242186, 1.364932672150267, 1.3498315870566997, 1.3234823319475009, 1.2861413994642472, 1.238330103558561, 1.1808144285677047, 1.1145788190307733, 1.0407946486625284, 0.9607842379731021, 0.8759813985418708, 0.7878895652500807, 0.6980386338138022, 0.6079416483875297, 0.5190524822002108, 0.43272562324580727, 0.35017911781710487, 0.27246163869204937, 0.200424534274998, 0.13469958279387878, 0.07568302513527415, 0.023526284897936504, -0.02186639104129605, -0.06083331927226754, -0.09394392407820651, -0.12198074826524245, -0.14591541072361291, -0.16687914957263358, -0.18612873214581035, -0.2050086355340705, -0.22491050080131575, -0.24723093777424232, -0.2733288035882525, -0.30448309573526283, -0.34185258872149954, -0.3864383028529135, -0.4390498251005103, -0.5002764071407853, -0.5704636468639722, -0.6496964198468195, -0.7377885699809593, -0.8342796975617724, -0.9384392029526666, -1.0492775589638628, -1.1655645999687843, -1.2858544351838317, -1.4085164220128865, -1.5317714772430642, -1.6537328631835393, -1.7724504661475227, -1.8859574890561177, -1.9923184108634946, -2.0896770247822936, -2.176303356039392, -2.2506382784971266, -2.3113346975734266, -2.3572942433917037, -2.387698521184786, -2.402034093199784, -2.400110514630625, -2.3820709118420194, -2.3483947703015384, -2.2998927878235707, -2.2376938413353287, -2.163224307667089, -2.0781801661106143, -1.9844924880610333, -1.8842870825672542, -1.779839212011722, -1.6735244158091174, -1.5677665788698203, -1.464984453139343, -1.3675378829868068, -1.2776749974750687, -1.1974816142434968, -1.128834051262541, -1.0733564652100513, -1.0323837305176629, -1.0069307437569492, -0.9976688871004821, -1.0049102157552168, -1.0285997516180128, -1.0683160733796562, -1.123280196569842, -1.1923725403736574, -1.274157586241408, -1.3669156510216252, -1.468681029001393, -1.5772856069271004, -1.69040692744768, -1.8056195725847712, -1.9204486622953645, -2.0324242157867647, -2.13913510609254, -2.238281351899137, -2.3277235343541904, -2.405528199476066, -2.4700082069928264, -2.5197571114736825, -2.5536768083774923, -2.570997842501962, -2.5712919552070135, -2.5544766353005595, -2.5208116319804055, -2.4708875819727716, -2.4056070922499218, -2.326158799820015, -2.233985096668998, -2.1307443569470585, -2.01826863132196, -1.8985178769904025, -1.7735318686741306, -1.6453809842228806, -1.5161170771052808, -1.387725636730104, -1.2620803965872889, -1.1409014807461297, -1.0257180831175663, -0.9178365535568325, -0.8183146234250843, -0.7279423442361258, -0.6472301405072035, -0.5764041962579053, -0.5154092083255795, -0.46391835346018795, -0.4213501346859294, -0.3868916002032425, -0.359527269444366, -0.33807295973255996, -0.3212135868284162, -0.30754391644322815, -0.2956111739205632, -0.28395837743044666, -0.2711672471778972, -0.25589955956121296, -0.23693586045195625, -0.21321052461171436, -0.18384224682129838, -0.1481591720423227, -0.10571801374427198, -0.05631666779500349, -5.561808166845126e-16], [0.0, 0.06507370850497066, 0.13592393405609174, 0.2116948904443797, 0.2913432034149159, 0.3736676568320369, 0.45734351099324283, 0.540960482319321, 0.6230633761970132, 0.7021942930596196, 0.7769352837045191, 0.8459503145147895, 0.9080254171017438, 0.9621059396086454, 1.007329887478306, 1.0430564381521485, 1.0688888345401932, 1.0846910031855224, 1.0905974013232516, 1.087015768545751, 1.0746226392367066, 1.0543516567988782, 1.0273749153273992, 0.9950777341227992, 0.9590274407595046, 0.9209368950170852, 0.8826236248683252, 0.8459655633599942, 0.8128544686018716, 0.7851481757792377, 0.7646228683661805, 0.7529265644891475, 0.751534993352184, 0.7617109862085296, 0.7844684277011524, 0.8205417083553609, 0.8703614901073006, 0.9340374471082831, 1.011348477293501, 1.1017407004137483, 1.2043333698012666, 1.317932632699927, 1.4410528822689577, 1.5719452580936701, 1.7086326758064827, 1.8489506045987132, 1.9905926680025792, 2.1311600219116724, 2.268213367419442, 2.3993263871109476, 2.522139353693756, 2.6344116503349606, 2.734071963077009, 2.819264956779876, 2.8883933259874226, 2.9401542190372765, 2.973569165059012, 2.9880067860663346, 2.9831977464541555, 2.9592415757368147, 2.9166051928541634, 2.856113157150842, 2.7789298674171112, 2.686534121394381, 2.58068662925045, 2.4633912413165526, 2.3368507987994174, 2.2034186426356337, 2.065546917080954, 1.9257328785755075, 1.7864644651234383, 1.6501663958154362, 1.5191480538916249, 1.395554360326842, 1.2813207694964779, 1.1781334159342074, 1.087395314071283, 1.0101993642983262, 0.9473087523835511, 0.8991451493156187, 0.8657849294432691, 0.846963431005374, 0.8420870895368328, 0.8502530859374368, 0.8702759718128991, 0.9007205694063857, 0.9399402960513363, 0.9861199371585578, 1.0373217903320087, 1.091534028706528, 1.146720085765057, 1.2008678477581896, 1.2520374537137557, 1.2984065464437564, 1.338311889754456, 1.37028636536588, 1.3930904853193966, 1.4057376987768966, 1.407512932461771, 1.3979839775098462, 1.3770055178182383, 1.3447157815228692, 1.3015259833269337, 1.2481029063899114, 1.1853451438539517, 1.1143536775652392, 1.0363976112315019, 0.9528759936848565, 0.865276762172196, 0.7751339033639277, 0.6839839694149593, 0.5933230969957795, 0.5045656585334494, 0.41900562749452025, 0.33778166465729, 0.261846831901513, 0.19194371667188317, 0.12858560710386863, 0.0720441984892858, 0.02234414036004386, -0.020735445660526614, -0.05765252939813153, -0.08908705007930443, -0.11591951653455179, -0.1392039018356397, -0.16013555424070275, -0.1800149775544676, -0.20020844344601207, -0.22210648310995001, -0.2470813637337579, -0.27644468504226827, -0.31140623193910033, -0.3530351908941719, -0.402224780909718, -0.45966126602434837, -0.5257982074581302, -0.6008366823649092, -0.6847120460085877, -0.7770876487681165, -0.8773557428409401, -0.9846456302823062, -1.0978389186900104, -1.2155915680829825, -1.3363622369352612, -1.4584462713506003, -1.5800145331523316, -1.6991561339876597, -1.8139240366938612, -1.9223824048727196, -2.0226545289625886, -2.1129701334947946, -2.191710876360977, -2.2574528867498085, -2.3090052531456733, -2.3454434649080533, -2.3661369282740488, -2.370769817322794, -2.3593546791226254, -2.332238386085171, -2.2901002132266073, -2.2339420090588544, -2.165070621509136, -2.085072929851091, -1.9957840154469921, -1.8992491736540082, -1.7976806223362745, -1.6934098952458212, -1.5888370177789224, -1.4863776455435345, -1.3884094006963255, -1.2972186657261724, -1.2149490886084033, -1.1435530171111574, -1.0847470143288716, -1.0399725138023734, -1.0103625531021099, -0.9967153823782032, -0.9994755825580619, -1.0187231505192669, -1.0541708199850321, -1.1051696916618763, -1.170723049009171, -1.2495080417909794, -1.3399047329350686, -1.440031829749723, -1.5477882624652874, -1.6608996352123306, -1.776968460263566, -1.893526998415549, -2.0080914688866187, -2.118216362478367, -2.221547592677355, -2.3158732507990516, -2.3991707923886625, -2.4696495713583078, -2.525787753532679, -2.566362779539361, -2.5904747048966064, -2.5975619188239905, -2.5874089284530086, -2.560146087193058, -2.5162413402984782, -2.456484252423455, -2.381962766454178, -2.2940333156692096, -2.194285068095037, -2.084499218991441, -1.9666043614122495, -1.8426290530091505, -1.714652757590287, -1.5847563710148729, -1.4549735421315586, -1.327243970724782, -1.2033698066333751, -1.0849761888800304, -0.9734768530095621, -0.8700456017121522, -0.7755942815901401, -0.6907577414663564, -0.6158860691519569, -0.5510442185796912, -0.4960189523063089, -0.45033284027309595, -0.41326487898523956, -0.38387713033368054, -0.3610466302386855, -0.34350168783844026, -0.329861589277527, -0.3186786388916216, -0.30848141671756996, -0.2978181060734591, -0.28529874902128427, -0.2696353206801378, -0.24967857470491736, -0.2244507001818277, -0.19317294244806013, -0.15528747404057366, -0.11047295370249774, -0.058653377259266934, -5.771853649180891e-16], [0.0, 0.06708554037388642, 0.1395780749142009, 0.21652443556593787, 0.29679959473933626, 0.37913900835946684, 0.46217502409627703, 0.5444763864007187, 0.6245897871764559, 0.7010823550031628, 0.7725839482414321, 0.8378281188230363, 0.8956906440646518, 0.9452245827072316, 0.9856908971322665, 1.016583794217107, 1.0376500698157485, 1.048901893083073, 1.050622633018538, 1.0433655065279026, 1.0279450105497883, 1.0054212857623797, 0.9770777414174796, 0.9443924453525968, 0.9090039457944794, 0.8726723380674233, 0.8372365160281151, 0.8045686517240468, 0.7765270247415532, 0.7549083729351986, 0.7414009573632243, 0.737539525667028, 0.7446633199382624, 0.7638782081645117, 0.7960239242004693, 0.8416472821224718, 0.9009820896612535, 0.9739363255964801, 1.060086971432796, 1.1586827026309376, 1.2686544536781086, 1.3886336790452845, 1.5169779433323896, 1.6518032933058302, 1.791022696555296, 1.9323896803042917, 2.07354617326143, 2.2120734465578944, 2.3455449694606796, 2.4715799437139894, 2.5878962583768232, 2.6923616154957632, 2.7830416157332727, 2.858243661273437, 2.916555629336238, 2.9568783911504526, 2.9784513953389955, 2.980870697876741, 2.964098999136814, 2.9284674377196884, 2.874669086165545, 2.803744290534524, 2.717058189414298, 2.6162709334718963, 2.503301299694908, 2.380284550760291, 2.2495255257316042, 2.1134480602249655, 1.9745419195926328, 1.8353084854929138, 1.6982064630899787, 1.5655988724343681, 1.4397025534415469, 1.3225413501836318, 1.21590404853443, 1.121308023839686, 1.0399694151297, 0.972780482912246, 0.9202946327110902, 0.8827194005526801, 0.8599175041196583, 0.8514158690062521, 0.8564223481850922, 0.8738496691039949, 0.9023459712545354, 0.9403311417648358, 0.9860380213301907, 1.0375574408683963, 1.09288596335143, 1.1499751473535766, 1.2067811203037877, 1.2613132508437752, 1.3116807409372946, 1.356136018576316, 1.393113899497038, 1.4212655989887537, 1.439486809769713, 1.4469392155893446, 1.4430649788093104, 1.427593919468873, 1.4005432887489422, 1.362210226666779, 1.3131571775849278, 1.2541907131176608, 1.1863343758834584, 1.1107963052119787, 1.028932533711219, 0.9422069483811845, 0.8521489891528806, 0.7603102094091837, 0.6682208459739624, 0.5773475397269712, 0.48905331263897417, 0.4045608435774171, 0.32491999536485816, 0.2509804315995412, 0.18337002659296844, 0.12247961889559164, 0.06845449216494215, 0.021192790821707125, -0.01964910348149104, -0.05464439047985483, -0.08457719871982987, -0.11041796469006583, -0.13329350283269017, -0.15445256498729135, -0.17522780676615135, -0.1969951738417882, -0.22113179070672068, -0.24897347635193878, -0.2817730244129108, -0.32066036928225744, -0.3666057148525882, -0.4203866300226396, -0.4825600166641859, -0.5534397338497185, -0.6330805198182629, -0.7212686939634465, -0.8175199490479331, -0.9210843631953618, -1.0309585765212785, -1.145904893184096, -1.264476890804315, -1.3850509501317694, -1.505862962816765, -1.625049338099549, -1.7406913136699051, -1.8508614848310634, -1.9536714017928418, -2.047319049115911, -2.130135015024221, -2.2006261817541626, -2.257515820834803, -2.2997790579819792, -2.326672779227514, -2.337759180426899, -2.3329223132363532, -2.3123771483511226, -2.2766708571558154, -2.2266762015359225, -2.1635771138056517, -2.088846739789694, -2.00421840334219, -1.9116501254160159, -1.8132834908791744, -1.7113977976366326, -1.6083605417342115, -1.5065753860168523, -1.4084288262221036, -1.3162368054231541, -1.23219253452188, -1.1583167528021798, -1.096411608906186, -1.0480192602457545, -1.014386179770731, -0.9964340258024902, -0.994737776520483, -1.0095116593893465, -1.0406032214877377, -1.0874956938219547, -1.1493186059643639, -1.2248664115318146, -1.3126246948751754, -1.4108033495116292, -1.5173759536694018, -1.6301244218425168, -1.7466878870262923, -1.8646146693319638, -1.9814161153510692, -2.094621050669748, -2.2018295763115407, -2.3007649588642916, -2.3893224131203215, -2.4656136539918054, -2.5280061993116183, -2.57515653429205, -2.606036398695836, -2.6199516254679, -2.616553140551724, -2.595839923421813, -2.558153921843498, -2.5041671077690935, -2.4348610493633593, -2.3514995523292255, -2.255595087636873, -2.148869868465173, -2.0332125631211007, -1.910631729930273, -1.7832071322272462, -1.6530401349288955, -1.5222043977736646, -1.3926980639179285, -1.2663985967044955, -1.1450213432933156, -1.0300828034032061, -0.9228694572371855, -0.8244128619173685, -0.7354715641058803, -0.6565202020161279, -0.5877459871138988, -0.5290525690594734, -0.48007110152644483, -0.4401781460945873, -0.40851988095126124, -0.3840419248884256, -0.3655239489264853, -0.3516181312481178, -0.34089041885662724, -0.331863493740185, -0.3230603039103858, -0.31304701136541774, -0.30047422994831846, -0.2841154756386058, -0.2629018287216229, -0.23595190952982156, -0.20259639441442517, -0.1623964430867038, -0.11515556877943113, -0.06092465473973806, -5.973166896093736e-16], [0.0, 0.06895858636370204, 0.1429083328598495, 0.22080677426153494, 0.30145677009953686, 0.3835411613094982, 0.4656609508989791, 0.5463759911112874, 0.6242470921108212, 0.6978784275336699, 0.7659591013710956, 0.8273027588910113, 0.8808841712293813, 0.9258717977525278, 0.9616554304609757, 0.9878681480852223, 1.0044019510361504, 1.0114166084297527, 1.0093414209983582, 0.9988697844984528, 0.9809466226851344, 0.9567489424021504, 0.927659941207506, 0.8952372657229117, 0.8611761723102878, 0.8272684768405497, 0.795358293777933, 0.7672956536416724, 0.7448891498192497, 0.7298587990523155, 0.7237903037675487, 0.72809187858324, 0.7439547483307558, 0.7723183420576932, 0.813841098692475, 0.8688776679630367, 0.9374631379745864, 1.0193047522688392, 1.113781398330283, 1.2199509608079966, 1.3365654408223264, 1.4620935523515668, 1.594750322544455, 1.7325330494351787, 1.8732628122474857, 2.014630590198213, 2.1542469289217845, 2.289694002261596, 2.4185788535168333, 2.5385865659206686, 2.6475321080654335, 2.7434096263470433, 2.824438012692512, 2.889101660544943, 2.9361854332922697, 2.9648030043691525, 2.974417883878096, 2.964856619001208, 2.936313840527746, 2.8893490210123294, 2.824875006709634, 2.744138580722654, 2.648693504002833, 2.5403666593494676, 2.421218087031509, 2.293495845123964, 2.1595867496058534, 2.021964145751074, 1.8831339310261996, 1.745580088940051, 1.6117110021410261, 1.483807791345791, 1.3639758749724331, 1.2541008639416305, 1.1558097990021772, 1.0704386067856877, 0.9990064988390724, 0.9421978688683145, 0.9003520615121468, 0.8734611956191297, 0.8611760308959807, 0.8628196736831594, 0.8774087302175296, 0.9036813386340543, 0.9401313484500516, 0.9850477723098486, 1.036558512823299, 1.0926772703372527, 1.1513524677417506, 1.2105169875616866, 1.26813750553219, 1.3222622237755777, 1.3710658550212147, 1.4128907857421484, 1.4462834486357576, 1.470025060918511, 1.483156031229347, 1.4849935008377182, 1.475141660223294, 1.4534946655260885, 1.4202321662589992, 1.3758076413540847, 1.3209299204444378, 1.2565384367860366, 1.1837729131865182, 1.103938318890156, 1.0184660501973226, 0.9288723778496449, 0.8367152676869142, 0.7435507162507287, 0.6508897490574674, 0.5601572061053938, 0.4726533874664883, 0.38951955290817963, 0.31170816543966307, 0.23995864215778073, 0.17477923001646423, 0.11643546287965285, 0.06494548354619559, 0.020082334745991096, -0.018616859036865094, -0.05183507703264444, -0.08045338630390604, -0.1055233179776993, -0.1282343759178826, -0.1498775460472136, -0.17180578018269743, -0.1953925089780281, -0.22198929230736514, -0.2528837407876567, -0.2892588384489662, -0.33215476388160803, -0.382434246303497, -0.4407524053999841, -0.5075319116643321, -0.5829441701026945, -0.6668970779060642, -0.7590297398435623, -0.8587143478793965, -0.965065248310402, -1.076955035169856, -1.1930373273960289, -1.3117757138953898, -1.4314781895275215, -1.5503362602891628, -1.6664677712654203, -1.7779624094406041, -1.88292875783818, -1.9795417296690587, -2.0660891924980365, -2.1410166034556783, -2.2029685170538453, -2.250825896298789, -2.283738253913688, -2.3011497712853206, -2.3028186853211574, -2.288829394280418, -2.2595969089001686, -2.2158634604848815, -2.1586872685147696, -2.089423662057544, -2.0096989371119593, -1.9213775113274751, -1.8265231038916738, -1.7273548176263749, -1.6261991287685318, -1.525438894323336, -1.427460564641419, -1.3346008380167294, -1.2490940133565298, -1.1730212858013553, -1.1082631887803713, -1.056456315328142, -1.0189553532340105, -0.9968013450966603, -0.990696938586294, -1.0009892276980177, -1.027660606496738, -1.0703278671562473, -1.1282495785907334, -1.2003415854183055, -1.2852002741635205, -1.3811330691901964, -1.486195449342054, -1.5982336218277016, -1.7149318562694882, -1.8338633722851487, -1.9525435911385454, -2.0684845078780114, -2.1792489162711592, -2.282503225300172, -2.376067642811287, -2.457962568180238, -2.526450129906877, -2.5800699235526205, -2.6176681474276693, -2.6384194944177337, -2.641841334347785, -2.627799907985004, -2.5965084466010246, -2.548517325218209, -2.4846965485030967, -2.406211051080802, -2.31448946437138, -2.2111871557530423, -2.0981444792151347, -1.9773412864627522, -1.8508488310485514, -1.720780253561698, -1.5892408619246725, -1.458279416890842, -1.3298415990979386, -1.2057267714489266, -1.0875490608095233, -0.9767036683473477, -0.8743391812205313, -0.7813365032208555, -0.6982948523059053, -0.6255250929882553, -0.5630504858055111, -0.5106147492244587, -0.4676971460059496, -0.43353413084532477, -0.4071469333654728, -0.38737430431464537, -0.3729095267268974, -0.3623406909468952, -0.3541931553231521, -0.3469730649050709, -0.3392107798147823, -0.329503073555658, -0.31655299908212203, -0.2992063859797268, -0.27648402387916116, -0.24760870288453257, -0.21202641836862018, -0.16942120148682482, -0.1197232042628399, -0.06310984484180572, -6.163919815048678e-16], [0.0, 0.07067583798832583, 0.14588450691536492, 0.22450311583667845, 0.3052725817926329, 0.3868342965244368, 0.46776974677520067, 0.546642030382914, 0.622038158813995, 0.6926110136461597, 0.7571198304022406, 0.8144681179457225, 0.8637379845292436, 0.9042199309865815, 0.9354372852549463, 0.9571645875720233, 0.9694393889319411, 0.9725670928677337, 0.9671186481528204, 0.9539210831197057, 0.934041056372137, 0.908761779076778, 0.8795538362049741, 0.8480405936951413, 0.8159590214691869, 0.7851168849181016, 0.757347356728372, 0.7344621741871993, 0.7182045124595856, 0.7102027605458519, 0.7119263732001487, 0.7246449292530113, 0.7493914555013481, 0.7869309772850777, 0.8377351344082828, 0.9019635571439693, 0.9794525351847576, 1.0697113365203479, 1.171926347645811, 1.284973015792084, 1.4074353827181318, 1.5376328127307166, 1.6736533396245847, 1.8133928925746372, 1.9545995137541543, 2.094921554269775, 2.2319587330523705, 2.3633148681894394, 2.486651043740111, 2.5997379585454885, 2.7005062174085355, 2.7870933689955715, 2.8578865678925607, 2.911559838703741, 2.947105045504086, 2.9638558173312988, 2.9615038461665906, 2.9401071539913906, 2.9000901156487027, 2.8422352197640444, 2.7676667461382265, 2.6778267300411986, 2.5744437670410805, 2.45949538193792, 2.335164837904841, 2.20379339336259, 2.0678291212372155, 1.9297734854796669, 1.7921269211252375, 1.6573346855106603, 1.5277342390551365, 1.4055053745043407, 1.2926242447313796, 1.1908223428000773, 1.10155136641244, 1.025954755087254, 0.9648465259942576, 0.9186978572950986, 0.8876316804688572, 0.8714253500233545, 0.8695212649437767, 0.8810451259533644, 0.9048313308022696, 0.9394548407900362, 0.9832686996699175, 1.0344462546595614, 1.091027021656929, 1.1509650555039623, 1.2121786331690176, 1.2726000342455261, 1.3302242096706913, 1.3831551657939924, 1.4296489558759948, 1.4681522630698258, 1.4973356755614484, 1.516120892845596, 1.5237012585859913, 1.5195551862021144, 1.5034522239467745, 1.4754516922583851, 1.4358940129342548, 1.385385032513206, 1.3247738166223073, 1.2551245535992317, 1.1776833504434732, 1.0938408284992736, 1.0050915271702991, 0.9129911989430046, 0.8191131262379633, 0.7250046089994159, 0.6321447610816177, 0.5419047137384927, 0.4555112569377766, 0.3740148555668143, 0.298262860291286, 0.2288785948788829, 0.1662468467317362, 0.11050611913537939, 0.061547826607777766, 0.019022433219228273, -0.017647647539671088, -0.049248749239410736, -0.07675077041890808, -0.10127679263759558, -0.12406831359673921, -0.14644702556326164, -0.16977416080711427, -0.19540849107568878, -0.22466410560004527, -0.2587691007826281, -0.29882629430494656, -0.3457770273985062, -0.4003690426456099, -0.46312932281152713, -0.5343426513925315, -0.6140365109127072, -0.7019727741362519, -0.7976464703141362, -0.900291727699557, -1.008894809394331, -1.1222139767671948, -1.2388057378284503, -1.3570568715252218, -1.4752214671574018, -1.5914620848662278, -1.7038940318202422, -1.8106316621808822, -1.9098355494217947, -1.9997593486826222, -2.0787951654277035, -2.145516274888941, -2.1987160939973465, -2.2374423924229885, -2.2610258399297134, -2.269102120847298, -2.2616269998300647, -2.2388838924696346, -2.2014836756162133, -2.1503566609894493, -2.086736847184074, -2.012138754775411, -1.9283273322212056, -1.8372815921081518, -1.7411527937389328, -1.6422181252057206, -1.5428309525237374, -1.4453687922328637, -1.3521802248711698, -1.2655319983168318, -1.1875575713419717, -1.1202083187222796, -1.06520856054543, -1.024015491334955, -0.9977849713273333, -0.9873440054288494, -0.9931705783349788, -1.0153813408187589, -1.053727456491274, -1.1075987249159205, -1.1760359005191532, -1.257750932061255, -1.3511546592473949, -1.4543913259507157, -1.5653791077933574, -1.6818557094211204, -1.801427967171469, -1.921624298874702, -2.0399487765162316, -2.153935561011136, -2.2612024322642257, -2.359502172127584, -2.446770612195136, -2.5211702412290493, -2.5811283763382487, -2.625369035120622, -2.6529377995535306, -2.6632191326900214, -2.6559457920042795, -2.6312001740412705, -2.589407619184488, -2.53132189810949, -2.458003288129246, -2.370789823608662, -2.2712624656493006, -2.1612050784162684, -2.042560219364783, -1.9173818453475104, -1.7877861038947742, -1.6559014172893671, -1.5238190755560082, -1.3935455330410962, -1.2669575525013386, -1.1457612619033193, -1.0314560845034833, -0.9253043749092891, -0.828307445968477, -0.7411885072338389, -0.6643828595394253, -0.598035506327024, -0.5420061553862927, -0.4958813992912398, -0.45899368365389165, -0.4304465038312187, -0.409145117096476, -0.3938319223241053, -0.38312554626728473, -0.37556258730161873, -0.3696409062152368, -0.3638633207145358, -0.3567805565424396, -0.34703233349675533, -0.33338551848297865, -0.31476835861845437, -0.2902999132256654, -0.25931393159044797, -0.2213765703392936, -0.17629750645906134, -0.1241341752139477, -0.06518904210514488, -6.342377667793834e-16], [0.0, 0.07222168509187751, 0.14847958124161675, 0.22757994607920434, 0.3082124587357634, 0.38898857571944784, 0.4684822458486646, 0.5452718954003763, 0.6179825593730971, 0.6853270283248826, 0.7461449028170299, 0.7994384985346207, 0.8444046234081827, 0.8804613515829938, 0.9072690452921067, 0.9247450214303905, 0.9330714212487614, 0.9326960150350831, 0.9243258545625064, 0.9089138699145837, 0.8876386894059215, 0.861878137109218, 0.8331770275262587, 0.8032100270153273, 0.773740482890539, 0.7465762302822019, 0.7235234710806205, 0.7063398763856737, 0.6966880923312018, 0.6960908281389955, 0.7058886747077097, 0.7272017426191264, 0.7608961215307702, 0.8075560505902506, 0.8674625544604478, 0.9405791450641546, 1.0265450190106065, 1.124675999020593, 1.2339732789821447, 1.353139841190255, 1.480604225566372, 1.614551148883774, 1.7529583017481, 1.8936384965280233, 2.034286204449523, 2.1725274080333814, 2.3059716087845126, 2.4322647717192907, 2.549141959444132, 2.654478409854058, 2.7463378431401546, 2.823016844972003, 2.8830842620205, 2.9254146612801586, 2.9492150431697555, 2.954044156794503, 2.9398239402090502, 2.906842794798758, 2.855750596473725, 2.7875455425407663, 2.703553127111469, 2.6053977249990083, 2.49496743969927, 2.374373030968774, 2.2459018778132127, 2.111968049976238, 1.9750596524227404, 1.837684670632073, 1.7023165782307517, 1.5713409718024771, 1.4470044705623475, 1.3313670616638502, 1.2262589866425193, 1.133243153002507, 1.053583919976274, 0.9882229523599126, 0.9377626648641114, 0.9024575958361629, 0.882213858005751, 0.8765966197711959, 0.8848453782226176, 0.9058965992910133, 0.9384131256462845, 0.9808195934918846, 1.0313429590838743, 1.0880571180236598, 1.1489305079602774, 1.2118755204824865, 1.2747985121914984, 1.3356491990094503, 1.3924682417452625, 1.4434318841174425, 1.4868925854109174, 1.5214146966252355, 1.5458043586257044, 1.5591329501450772, 1.5607535787283835, 1.5503102847081225, 1.5277398125994845, 1.4932659913021356, 1.4473869495161473, 1.3908555712142385, 1.32465376342422, 1.2499612608122816, 1.1681198248550628, 1.0805938064624105, 0.9889281270416942, 0.8947047920857163, 0.7994990820079628, 0.7048365664440218, 0.6121520606215526, 0.5227515864379243, 0.4377783180495746, 0.35818338421802853, 0.2847022701400943, 0.21783741332846965, 0.15784742508356314, 0.10474319535730076, 0.05829095877108148, 0.01802221778380205, -0.016749759876264477, -0.04690732386310397, -0.07350031798764685, -0.09771320902753035, -0.12082834988546393, -0.1441863611794256, -0.16914469189498038, -0.19703546909859762, -0.22912376762924164, -0.26656742259816746, -0.31037947060878185, -0.3613942407608223, -0.4202380253314459, -0.48730514479988957, -0.5627400854797827, -0.6464262338580384, -0.7379815636766177, -0.8367614540533782, -0.9418686339903443, -1.0521700650693875, -1.16632039461681, -1.2827914406672465, -1.3999070120040176, -1.5158822254139166, -1.6288663616691461, -1.736988204731899, -1.8384027377779038, -1.9313380267161246, -2.014141108110876, -2.085321714231794, -2.1435927130722634, -2.187906214562504, -2.217484394127615, -2.2318442088073245, -2.2308153263607147, -2.2145507505914077, -2.183529802567021, -2.1385533031443873, -2.080730992682081, -2.011461414329767, -1.9324046731241842, -1.8454486596940798, -1.752669490300129, -1.6562870601581097, -1.5586167308909498, -1.4620182724224524, -1.3688432521544587, -1.2813821080111059, -1.2018121557443384, -1.1321477643659217, -1.0741938870387386, -1.0295040592991171, -0.9993438738789253, -0.9846608141065825, -0.9860611789546609, -1.0037946658660426, -1.0377469965748447, -1.0874407806321607, -1.1520446158786546, -1.2303902294291145, -1.3209972716089462, -1.4221051933604423, -1.5317114693451896, -1.647615278402198, -1.7674656238411095, -1.8888127713928067, -2.0091618050432176, -2.1260270523135696, -2.236986111986451, -2.3397322292395897, -2.4321238053171337, -2.5122299001828226, -2.5783706852870254, -2.629151927199155, -2.6634927283583925, -2.680645914995716, -2.6802106403519463, -2.662136959288083, -2.626722323646659, -2.574600141544996, -2.5067207334251758, -2.4243251985242154, -2.3289128730588593, -2.2222032117731287, -2.106093053936596, -1.9826103402930033, -1.8538654263265848, -1.722001187680776, -1.5891431344797033, -1.4573507422479408, -1.32857116842031, -1.204596456136175, -1.0870252328813357, -0.9772297929960795, -0.8763293131296932, -0.7851697919336862, -0.7043111336268217, -0.6340216138483652, -0.5742797799838752, -0.5247836515568106, -0.4849669039836751, -0.45402154552856516, -0.43092643697210925, -0.4144808603006208, -0.4033422201589938, -0.39606686290755255, -0.39115292529330453, -0.3870840797476127, -0.3823730272126758, -0.3756036015104687, -0.36547039119862407, -0.3508148544846523, -0.3306569982758385, -0.3042218113624574, -0.2709597810169943, -0.23056097838353312, -0.18296236695227283, -0.12834816586787845, -0.06714328129962494, -6.506915612942914e-16], [0.0, 0.07358206353148818, 0.15066997939661228, 0.23000934037892476, 0.31024972576644144, 0.3899844111217896, 0.4677918238836619, 0.5422776343846568, 0.6121163531714686, 0.6760913157839148, 0.7331319751563795, 0.7823474885917702, 0.8230556791664128, 0.8548065681375789, 0.8773998125250047, 0.8908955370763034, 0.8956182184131085, 0.8921534570535695, 0.8813376557408242, 0.8642408054710917, 0.8421427591907198, 0.8165035428026078, 0.7889284095879043, 0.7611284834308043, 0.7348779547774019, 0.7119688880209061, 0.6941647675307793, 0.6831539500292559, 0.6805042023584981, 0.6876194854941983, 0.7057000983013811, 0.7357072190783541, 0.778332781180442, 0.8339754934004844, 0.9027236693514686, 0.9843453664159992, 1.0782861579020457, 1.1836746762169523, 1.2993358747150114, 1.4238117660784402, 1.555389210349342, 1.6921341506180545, 1.8319315332399073, 1.97253000631003, 2.111590368550411, 2.2467366438061, 2.375608586457605, 2.4959143820214575, 2.6054822961100452, 2.7023100440997627, 2.784610702913612, 2.8508540641255253, 2.899802432296167, 2.930540001547511, 2.9424950937681547, 2.9354547098790493, 2.9095710272093687, 2.865359666827093, 2.8036897500023494, 2.7257659581032008, 2.6331030003849767, 2.527493074706509, 2.410967072793588, 2.285750430217013, 2.154214648146046, 2.0188256160941025, 1.882089939814316, 1.7465005244166636, 1.6144826785656965, 1.4883419909160196, 1.3702151851361488, 1.2620250860812046, 1.1654407287314938, 1.0818435159108704, 1.0123001836313503, 0.9575431677993642, 0.9179587870203115, 0.8935834677434477, 0.8841080446168763, 0.888889975404075, 0.9069731208765028, 0.9371145603487848, 0.9778177473372778, 1.0273711612317047, 1.0838914834646656, 1.1453702235084398, 1.2097226435822108, 1.274837783011863, 1.338628364838199, 1.3990793788741371, 1.4542941765830684, 1.5025369827748634, 1.542270825377522, 1.5721900049703152, 1.5912463672946682, 1.5986688010118602, 1.5939755555454096, 1.5769791555976704, 1.547783875313395, 1.5067759214216587, 1.4546066563763886, 1.3921693650162097, 1.3205702272967559, 1.2410943012782794, 1.155167441286316, 1.0643151730404028, 0.9701196182046272, 0.8741756035536781, 0.7780471037708584, 0.6832251515276315, 0.5910883043977088, 0.5028666865117817, 0.41961052553086625, 0.3421639850181757, 0.2711449517113362, 0.20693128012953993, 0.14965382739563352, 0.09919643342274435, 0.05520282022288102, 0.017090203643504196, -0.01593076409653429, -0.044830267683113656, -0.0707285152551351, -0.0948606685741214, -0.11853845872141087, -0.14310951661965937, -0.16991550867292537, -0.20025020086274695, -0.23531857886859128, -0.2761981270676187, -0.3238033162078974, -0.37885426945237277, -0.4418504713515439, -0.5130502567468362, -0.5924566698269812, -0.6798101212369562, -0.774588097349314, -0.8760119949213476, -0.9830609709337184, -1.0944925160630552, -1.2088692855642869, -1.3245915577508303, -1.4399345419143021, -1.5530896281990745, -1.662208564949979, -1.765449467141237, -1.861023504806981, -1.9472410943877911, -2.0225564193305177, -2.0856091391430915, -2.13526220769166, -2.170634810395598, -2.1911295440055882, -2.196453099088847, -2.186629860877856, -2.1620080149666796, -2.1232579262757914, -2.071362748280782, -2.0076014100662434, -1.9335243166177247, -1.8509222782530297, -1.7617893537427385, -1.6682804442849613, -1.5726646082750524, -1.4772751764237297, -1.384457830467419, -1.2965178643578192, -1.2156678729761625, -1.1439771093762396, -1.0833237173474342, -1.0353509824736893, -1.0014286533403318, -0.9826202672890763, -0.9796572749578806, -0.9929205981483684, -1.0224300802030657, -1.067842101300383, -1.128455437422575, -1.203225245928838, -1.2907848674362676, -1.3894749477788118, -1.4973792097049485, -1.6123660459273856, -1.732134966997967, -1.8542668226081795, -1.9762766260986564, -2.095667751351806, -2.209986240300078, -2.3168739587418603, -2.4141193680068356, -2.4997047394969107, -2.5718487267682675, -2.629043323445079, -2.670084372063258, -2.694094945564889, -2.7005410957501064, -2.689239647306468, -2.660357907557291, -2.614405356110478, -2.5522175704039123, -2.4749328280507523, -2.3839620003833972, -2.280952509462778, -2.1677472592363256, -2.046339567155601, -1.918825212633346, -1.7873527810953591, -1.6540735156176705, -1.5210918915091791, -1.3904181027184852, -1.263923593362274, -1.1433006844612743, -1.0300272372781407, -0.9253371632560712, -0.830197439789482, -0.7452921247241389, -0.6710136847667824, -0.6074617683391241, -0.5544493664566283, -0.5115161206140036, -0.4779483590125663, -0.45280527618296407, -0.4349505202598268, -0.4230883205777174, -0.4158031791178295, -0.41160206531232746, -0.4089579968447739, -0.40635386072439816, -0.40232532969610246, -0.3955017588831381, -0.38464400562287054, -0.36867820021889824, -0.3467246045979228, -0.3181208268175848, -0.2824388086711467, -0.2394951674680393, -0.1893546472661827, -0.1323266149658324, -0.06895471817307579, -6.65603414021828e-16], [0.0, 0.0747445873466161, 0.15243578420018497, 0.2317692211121555, 0.3113658444096506, 0.38981263339317096, 0.4657044369965594, 0.5376858075648971, 0.6044917073754935, 0.6649859903667943, 0.7181966165961248, 0.7633466388547097, 0.7998801075849786, 0.8274821691017755, 0.8460927798866794, 0.8559136226944847, 0.857407984287252, 0.8512935354135746, 0.8385281366228178, 0.8202889740284434, 0.7979455026474689, 0.7730268370490787, 0.7471843756270155, 0.722150572131861, 0.699694872900051, 0.6815779177933037, 0.6695051551374394, 0.6650810445240815, 0.6697650155272632, 0.6848303152367022, 0.7113268137997598, 0.7500487463880635, 0.8015082543333942, 0.8659154504064771, 0.9431655766936979, 1.0328336520862007, 1.1341768242384154, 1.2461444524595084, 1.3673957580170437, 1.4963246914525543, 1.6310914873625946, 1.7696602101334677, 1.9098414434890223, 2.049339146179218, 2.185800588974492, 2.3168682070392523, 2.4402321488007908, 2.553682278982141, 2.655158400178845, 2.7427974941390603, 2.814976849922916, 2.8703520398193523, 2.907888823053322, 2.9268881990612234, 2.927003993028079, 2.908252532571928, 2.871014161656231, 2.8160265314631285, 2.744369803360381, 2.657444091487836, 2.556939657191304, 2.444800540044708, 2.3231824663241345, 2.194406011728953, 2.060906107578255, 1.9251790659133088, 1.7897283568187812, 1.6570103994407628, 1.5293816259600026, 1.4090480452496843, 1.2980184709264864, 1.198062488530606, 1.1106741208677906, 1.0370420119649, 0.9780267920389702, 0.9341461122402704, 0.9055676529621326, 0.8921102177465153, 0.8932528309468395, 0.908151566075933, 0.9356636478322207, 0.9743781986398625, 1.0226528443395264, 1.0786552572070986, 1.140408601046184, 1.205839755411957, 1.2728291361542166, 1.3392608988018095, 1.4030723105112162, 1.4623011052924137, 1.5151296951931326, 1.559925195541565, 1.5952743330152253, 1.6200124383976993, 1.6332458780339592, 1.6343674453626083, 1.6230644122849167, 1.599319125056977, 1.5634022162414845, 1.5158586883709024, 1.4574873017739622, 1.3893138641146918, 1.3125591685009874, 1.2286024568540446, 1.1389413924005307, 1.0451496070387005, 0.9488329439572053, 0.8515855419563619, 0.7549469048588159, 0.6603610673527951, 0.5691389084661649, 0.4824245772057812, 0.4011668839599757, 0.3260963789045679, 0.25770868826084903, 0.19625451466314564, 0.1417365332924015, 0.09391323525663536, 0.05230958852193492, 0.01623420911310719, -0.015197434187660846, -0.043034415517693624, -0.0684571225917115, -0.0927402977399718, -0.11721334251673893, -0.14321895137152943, -0.17207118484611555, -0.20501410924392888, -0.24318211727762734, -0.2875630031260594, -0.3389647966362693, -0.39798726679845997, -0.4649988864650783, -0.5401199115376857, -0.623212071986698, -0.7138752030140174, -0.8114509666683829, -0.9150336317603373, -1.0234876975993146, -1.1354719694944593, -1.2494695256170822, -1.3638228599862512, -1.4767733489484123, -1.5865040720868608, -1.6911849260083045, -1.7890189033097879, -1.8782883709740463, -1.9574001735201145, -2.024928406769449, -2.0796537576609477, -2.1205983830218367, -2.147055403737545, -2.1586122178714664, -2.155166983881631, -2.1369377895658044, -2.1044641997115834, -2.0586010612772507, -2.000504634705265, -1.9316113089883564, -1.853609341691695, -1.768404238731263, -1.6780785480035525, -1.5848469819843325, -1.491007903637189, -1.3988923043999233, -1.3108114702579428, -1.2290045702440107, -1.1555874101080428, -1.092503572097896, -1.0414791102455787, -1.0039818904570303, -0.9811865579561055, -0.9739459837900319, -0.982769890314868, -1.0078111865138406, -1.0488603617548202, -1.105348095589297, -1.1763560460758593, -1.2606355846229096, -1.3566340562221644, -1.4625279647916898, -1.5762623185277178, -1.6955952236920748, -1.8181466907012025, -1.941450516763353, -2.0630080370501576, -2.180342493236429, -2.291052755232917, -2.3928651493680295, -2.48368219369843, -2.561627117362102, -2.625083144045013, -2.6727266471684206, -2.7035534331790294, -2.71689757568195, -2.712442403012814, -2.69022343079126, -2.650623224406607, -2.594358369528306, -2.52245891689288, -2.4362408462097402, -2.3372722587071877, -2.2273341546137986, -2.1083767771936146, -1.9824726058149111, -1.851767154529366, -1.7184287780355323, -1.584598702670501, -1.4523424859229472, -1.3236040643356184, -1.2001634777382075, -1.0835992593935064, -0.9752563593704934, -0.8762203253847334, -0.7872983050837241, -0.709007260336145, -0.6415696018599168, -0.5849162660534027, -0.5386970698317773, -0.5022979982503902, -0.4748649082165002, -0.455332973900847, -0.4424610594583098, -0.4348700858002116, -0.43108436334260986, -0.42957479419129657, -0.428802806757729, -0.42726387426982654, -0.4235294862600174, -0.4162864883622549, -0.40437277939480315, -0.38680845382615237, -0.36282159976053857, -0.33186810440794756, -0.2936449769989774, -0.24809686924270735, -0.19541565137998665, -0.13603308313667767, -0.07060679883360586, -6.788373241547723e-16], [0.0, 0.07569866409975042, 0.15376092102971542, 0.23284355676771024, 0.31155057279012655, 0.38847455628529975, 0.4622385359793738, 0.5315371990207443, 0.5951763589669321, 0.6521096080376013, 0.7014711573720481, 0.7426039652992383, 0.7750823731850751, 0.7987286082682041, 0.8136226695216152, 0.8201052820455376, 0.81877378354273, 0.8104709885637038, 0.7962672578409712, 0.7774361765677898, 0.7554244124483532, 0.7318164775155295, 0.7082952531802623, 0.6865992522813168, 0.6684776821063186, 0.6556444361138337, 0.6497321777171399, 0.6522476860088872, 0.6645296104527176, 0.6877097298168321, 0.7226787311711959, 0.7700574195037883, 0.8301741399686541, 0.9030490460815009, 0.9883856819577032, 1.0855701689924742, 1.1936781015823952, 1.3114890671613737, 1.437508517650111, 1.56999653705589, 1.7070028779349498, 1.8464074820227212, 1.9859655614754481, 2.1233562003276467, 2.2562333438940363, 2.3822779792627373, 2.4992502744002207, 2.6050404376692433, 2.697717083965026, 2.775571947677726, 2.837159865036953, 2.8813330571344045, 2.9072688774497757, 2.914490340831369, 2.9028789209052315, 2.872679285685127, 2.824495832292687, 2.7592810765264226, 2.6783161467994834, 2.583183819980882, 2.4757347143436497, 2.3580474178174446, 2.232383474091667, 2.101138271302716, 1.9667889750923895, 1.8318407173852678, 1.6987722926162763, 1.5699826233748573, 1.447739237287193, 1.3341299469440338, 1.231018846041614, 1.1400076295792128, 1.0624031165440302, 0.999191703194288, 0.9510213075164766, 0.9181911847918247, 0.9006498048861076, 0.898000788508981, 0.9095167069999426, 0.934160362890188, 0.9706129911258788, 1.0173086577298396, 1.0724739877786675, 1.1341722313792626, 1.200350577800462, 1.2688895563968043, 1.3376533201270626, 1.4045395942843197, 1.4675280897479104, 1.5247262261331835, 1.5744110844212411, 1.615066609072955, 1.6454152037010528, 1.664443008942541, 1.67141831259236, 1.6659027162695261, 1.6477548655227852, 1.617126736778369, 1.5744526602365927, 1.5204314381160182, 1.4560020880477293, 1.3823138977182616, 1.3006916151891295, 1.2125967162810922, 1.1195857831404137, 1.0232670943515778, 0.9252565651418017, 0.8271341854578398, 0.7304020838321205, 0.636445296568866, 0.5464962461618049, 0.46160383197399596, 0.38260791266899236, 0.31011981684828865, 0.24450935947515293, 0.18589867099595778, 0.13416296794557064, 0.0889382127648318, 0.04963543115756356, 0.015461282118370364, -0.014555686841723451, -0.04153381463832999, -0.06670297652855761, -0.09136606149969533, -0.11685831286268186, -0.14450562442448917, -0.17558291322487374, -0.21127368966244092, -0.25263191688737807, -0.30054719431356464, -0.3557142164190507, -0.4186073497514737, -0.4894610409449275, -0.5682566198510905, -0.6547158983254924, -0.7483017909036422, -0.8482260029406893, -0.9534636493277338, -1.0627744872454212, -1.1747302741150785, -1.2877476013267457, -1.400125409543153, -1.5100862660907113, -1.6158203823641504, -1.7155312719385054, -1.8074819002201654, -1.8900401553164319, -1.9617224779841518, -2.021234525925589, -2.0675078134960208, -2.0997313605258685, -2.1173775012205263, -2.1202211431454696, -2.1083519237460617, -2.0821788838387065, -2.042427459820419, -1.99012878448916, -1.9266014757043994, -1.8534262779629551, -1.7724140997122682, -1.6855681544550782, -1.595041062299674, -1.503087896864064, -1.4120162671315464, -1.3241346023356062, -1.2416998582210077, -1.1668658837747707, -1.1016336781600293, -1.0478047282713259, -1.0069385489543612, -0.9803154521038893, -0.9689054498557502, -0.973344053829464, -0.993915570313202, -1.0305443143361332, -1.0827939780358498, -1.1498751951569104, -1.230661148618244, -1.3237108766062156, -1.427299749249907, -1.539456417083566, -1.658005378360639, -1.780614178609413, -1.9048441458656635, -2.02820348145793, -2.148201471082905, -2.26240255552458, -2.3684790053441342, -2.464260979057912, -2.547782808848916, -2.617324450124764, -2.6714471489673057, -2.7090225218178263, -2.729254401159799, -2.7316929755859616, -2.7162409381869916, -2.6831515491320133, -2.633018711932567, -2.5667593534626936, -2.4855885807015827, -2.3909882579211743, -2.284669802513977, -2.1685321321090654, -2.0446158068186544, -1.9150544957342068, -1.7820249541339805, -1.6476967259499031, -1.5141827842711193, -1.3834922911733911, -1.2574865978302798, -1.137839518266269, -1.026002797507899, -0.9231775601437487, -0.8302923718273568, -0.7479883779141842, -0.6766118044403457, -0.6162139215071603, -0.5665583824539445, -0.5271356686327485, -0.49718419370544975, -0.4757174575268429, -0.4615564919092631, -0.45336671252661637, -0.4496981860504271, -0.449028241881968, -0.4498053054762717, -0.4504928064813204, -0.4496120202568652, -0.44578273557973236, -0.43776070355032803, -0.4244709112525713, -0.4050358362931874, -0.3787979720626415, -0.3453360649982166, -0.3044746704284101, -0.256286808531164, -0.20108968210245415, -0.1394335986352553, -0.072084416068499, -6.902725177417421e-16], [0.0, 0.07643559224875435, 0.15463330275205334, 0.23322250089548358, 0.3108020432057526, 0.3859819375465093, 0.4574248573107448, 0.5238863885519196, 0.5842529240326052, 0.6375761771354361, 0.6831033740064433, 0.7203022920477598, 0.7488804441933087, 0.7687978579897974, 0.7802730626051714, 0.7837820713671253, 0.7800503278985957, 0.7700377658121044, 0.7549173106546575, 0.7360473238362475, 0.7149386472901482, 0.693217050558885, 0.672582005228435, 0.6547628119849401, 0.6414731804499484, 0.6343654094015837, 0.6349853337319138, 0.6447291939623011, 0.6648035445059431, 0.6961892490245868, 0.7396105167748662, 0.7955098150462856, 0.8640293525365961, 0.9449996702112623, 1.0379357037285564, 1.1420404991184077, 1.2562165755755377, 1.3790847406049047, 1.5090099780094766, 1.6441338529207037, 1.7824127146253121, 1.9216608314142785, 2.059597465737647, 2.1938967957576017, 2.322239513537128, 2.442364882523431, 2.5521220189307163, 2.6495191736177626, 2.73276983287432, 2.800334527224941, 2.850957335265351, 2.883696192329542, 2.8979462584954385, 2.893455763580537, 2.8703339244071615, 2.829050717420441, 2.770428483157504, 2.6956255333885255, 2.606112122247798, 2.503639324705085, 2.390201534857748, 2.267993448630133, 2.139362526841162, 2.0067580420436446, 1.8726778934342694, 1.7396144265162055, 1.6100005167995612, 1.4861571691103703, 1.370243846250618, 1.2642126737512414, 1.1697675729421166, 1.088329254855143, 1.0210068655217723, 0.9685769125094088, 0.9314699270036583, 0.909765129685623, 0.9031931766284885, 0.9111468681391636, 0.9326995136171353, 0.9666304637209252, 1.0114571518441147, 1.0654728342152602, 1.1267890855413765, 1.1933819981996678, 1.2631409501497615, 1.3339187519445632, 1.4035819577231112, 1.470060129409654, 1.5313928773189027, 1.585773563045824, 1.6315886402608253, 1.6674517235332453, 1.6922316116562774, 1.7050736466989285, 1.7054139592714943, 1.6929863300156822, 1.667821582629416, 1.6302396101867394, 1.5808343194744434, 1.5204519529955975, 1.4501634108526442, 1.3712313409033123, 1.2850728917826546, 1.19321912651126, 1.0972721719528535, 0.9988612294781403, 0.8995985936595228, 0.8010368182053138, 0.7046281319134698, 0.6116871431755468, 0.5233577811796569, 0.4405853077870044, 0.3640940990241797, 0.29437174269643424, 0.2316598326719083, 0.17595166513456734, 0.12699686200516558, 0.08431276635276155, 0.04720227853557337, 0.014777634478890685, -0.014010526844028695, -0.04033959710724413, -0.06547784095103099, -0.09074464809713967, -0.11746926443816241, -0.14694911183410306, -0.18040881841713605, -0.21896106446584787, -0.26357030376864726, -0.31502034797394757, -0.37388670353178144, -0.4405144299200155, -0.5150021469526296, -0.5971926616279635, -0.6866705151494389, -0.7827665727171753, -0.8845695969350553, -0.9909445647930486, -1.1005573127429813, -1.2119049288317398, -1.323351159392842, -1.4331659642831833, -1.5395682425005657, -1.640770662115495, -1.7350254670811978, -1.820670100273527, -1.8961714779809538, -1.9601677762124101, -2.011506643085451, -2.049278832947396, -2.0728463648283415, -2.0818644377459177, -2.0762964851180743, -2.056421916432453, -2.022836272299119, -1.9764437046981105, -1.918441883043449, -1.850299613952307, -1.7737276436906717, -1.6906432826670692, -1.6031296468200134, -1.5133904474096767, -1.4237013751528684, -1.3363592139484302, -1.2536298813578912, -1.1776966259343986, -1.1106096145446391, -1.0542381158513687, -1.0102264297039514, -0.9799546276336835, -0.9645050589747709, -0.9646354429818382, -0.9807592129218174, -1.012933607214472, -1.0608558194237405, -1.1238673277115474, -1.2009663299053468, -1.2908280173332303, -1.391832233746552, -1.502097889532348, -1.61952334030901, -1.7418317968255368, -1.8666207133120765, -1.9914140069735058, -2.1137158944767838, -2.231065093677009, -2.3410881313627896, -2.4415505206456984, -2.530404624196793, -2.6058331005436006, -2.666286938085407, -2.7105172127207644, -2.7375998567840596, -2.7469528956335005, -2.7383457895873904, -2.7119007085282867, -2.6680857597482395, -2.6077003817719957, -2.531853303281727, -2.44193364233823, -2.339575882572242, -2.226619605993296, -2.1050649830826473, -1.977025116997639, -1.8446764077307758, -1.7102081423248112, -1.575772527843971, -1.4434363645726638, -1.315135508425161, -1.1926331950925109, -1.0774831960036944, -0.9709986503534416, -0.8742272714374346, -0.7879334630187005, -0.7125877065082765, -0.6483633967598614, -0.5951411178225624, -0.5525201647137945, -0.5198369377726847, -0.49618966688515476, -0.480468768022615, -0.4713919979262441, -0.4675434577541233, -0.46741540589915953, -0.469451776176751, -0.4720922616983094, -0.47381581780946785, -0.4731824595738784, -0.46887227979107077, -0.4597206911057975, -0.444748998375872, -0.4231895324701817, -0.39450472086445754, -0.35839963010780657, -0.3148276863815353, -0.26398945861363166, -0.20632456942398011, -0.14249697797282937, -0.07337405103873076, -6.998045711564284e-16], [0.0, 0.07694863959823885, 0.15504493489543733, 0.2329024695827375, 0.30912675673013795, 0.38235683666904685, 0.4513060932010428, 0.5148011881722188, 0.571818061591761, 0.6215140187109751, 0.6632550249562847, 0.6966374518312243, 0.721503658797632, 0.7379509541464669, 0.7463336479961369, 0.747258088523378, 0.7415707538485068, 0.7303396520828177, 0.7148294563449131, 0.6964709656470504, 0.6768256322734156, 0.6575460278044556, 0.6403332299192114, 0.6268921976993368, 0.6188862621379267, 0.6178918893591063, 0.6253548758180217, 0.6425491073373022, 0.6705389578357942, 0.710146320324192, 0.7619231541694718, 0.826130301390294, 0.9027231740339897, 0.9913447481897516, 1.0913261220006667, 1.201694709537917, 1.3211899541739864, 1.4482862587964076, 1.581222650460394, 1.7180385283564952, 1.8566146904741254, 1.994718699911394, 2.130053539791149, 2.260308419019807, 2.3832105318784444, 2.4965765442004937, 2.5983625784898923, 2.6867114998571493, 2.7599963634507096, 2.816858970768078, 2.8562425947872505, 2.8774180695675127, 2.8800025955601494, 2.8639707835819146, 2.8296576440746573, 2.7777534194426496, 2.7092903512755377, 2.625621666406207, 2.528393251337758, 2.419508659078373, 2.30108825159181, 2.1754234210229457, 2.0449269501795238, 1.912080664583785, 1.7793815925150842, 1.6492878842896879, 1.5241657467264755, 1.4062386232243345, 1.2975397947657161, 1.1998694938221888, 1.1147575136233496, 1.0434321622508977, 0.9867962577994468, 0.9454106911608796, 0.9194859009962041, 0.9088814156112006, 0.9131134233903299, 0.9313701418809195, 0.9625345702268293, 1.0052140349395662, 1.0577757792078315, 1.1183877049528843, 1.185063258037285, 1.2557093532772414, 1.3281761694209693, 1.400307606588627, 1.4699911906617418, 1.5352062308670724, 1.5940690876926085, 1.6448744869548557, 1.6861319202765719, 1.7165962997700217, 1.735292182124704, 1.7415310408580305, 1.734921241098288, 1.7153705545379119, 1.6830812385481149, 1.6385378882435777, 1.5824884489378641, 1.5159189445093113, 1.4400226305492112, 1.356164416010945, 1.2658415101118337, 1.1706413397011772, 1.0721978440599023, 0.9721472876727394, 0.8720847361531552, 0.7735223161700985, 0.6778503276151282, 0.5863021967564662, 0.49992415482270713, 0.4195504000316367, 0.34578435576842603, 0.27898647713162367, 0.21926888649027426, 0.16649694039043345, 0.12029764963827218, 0.0800746962444913, 0.045029619652437375, 0.014188584624803626, -0.013566001619128092, -0.039459881278746445, -0.0647883088649791, -0.0908754261177, -0.11903274221277818, -0.15051783670881774, -0.18649439817306873, -0.22799467832064935, -0.2758853806224347, -0.3308379152062189, -0.39330384067702634, -0.4634961810073589, -0.5413771552267916, -0.6266526930577213, -0.7187739350457816, -0.8169457355221945, -0.9201420054605157, -1.0271275545345102, -1.13648592194844, -1.2466525282024603, -1.3559523388786812, -1.4626411103897867, -1.5649491895299807, -1.6611267661449376, -1.7494894331943054, -1.8284628921346575, -1.896625654404696, -1.9527486316208835, -1.995830576939956, -2.0251284362618858, -2.04018178821912, -2.040830693306331, -2.027226431597525, -1.9998347813742772, -1.959431673398312, -1.9070912430053446, -1.8441664900412704, -1.7722629402525794, -1.6932058765209486, -1.6090018699465667, -1.5217954852011992, -1.4338221581727728, -1.3473583435972067, -1.264670103594246, -1.1879613529142197, -1.119322992078495, -1.0606841450005138, -1.0137666733869208, -0.9800440672502284, -0.9607057109353361, -0.9566273995560887, -0.9683488346474333, -0.9960586636901146, -1.03958744993284, -1.098408770946339, -1.1716484511638907, -1.2581017399943333, -1.3562580576533703, -1.4643327502638388, -1.5803051284288423, -1.7019619134642239, -1.8269450864471488, -1.9528030303415829, -2.0770437772539525, -2.1971891232566545, -2.3108283533947502, -2.415670329935917, -2.5095927373672233, -2.5906873470823424, -2.6573002614282433, -2.7080662184119517, -2.741936181919801, -2.7581976042517216, -2.7564869241533514, -2.736794050021002, -2.6994587699973573, -2.645159223578044, -2.5748927584042165, -2.489949676518863, -2.3918805421237703, -2.2824578737217154, -2.1636331738182566, -2.0374903559555735, -1.9061967092114616, -1.7719525925246598, -1.6369410741048773, -1.5032787242791636, -1.3729687336779448, -1.2478574636655018, -1.1295954440651, -1.0196037168716845, -0.9190462867400809, -0.8288092830646683, -0.7494872683484801, -0.6813769475573367, -0.624478347765847, -0.5785033512478844, -0.5428912828735724, -0.5168310787710054, -0.4992894019978877, -0.4890439264242423, -0.48472088570700617, -0.48483588318300047, -0.48783688317398755, -0.49214825639444604, -0.496214732995936, -0.49854412666941184, -0.49774773182931265, -0.49257736217256987, -0.481958091102741, -0.46501587024757407, -0.44109933860414463, -0.4097952882340048, -0.37093741899173466, -0.3246081902684114, -0.27113375771111436, -0.2110721627771056, -0.14519511823931527, -0.07446389894137108, -7.073463703085915e-16], [0.0, 0.07723310207425255, 0.1549919800779892, 0.23188615680000726, 0.3065394950701595, 0.377631371130817, 0.4439364442635914, 0.5043619492155513, 0.5579815007317028, 0.6040644883003157, 0.6421002518256214, 0.6718163625280607, 0.6931904845745488, 0.7064554579523971, 0.7120974177613055, 0.7108469450012771, 0.7036634245361567, 0.6917129626447194, 0.6763403849564816, 0.6590359913330903, 0.6413978834336512, 0.6250907997385519, 0.6118024886449055, 0.6031987204072438, 0.6008780813376217, 0.6063277076433126, 0.6208811011264418, 0.6456791249840628, 0.6816352061362274, 0.7294056725774999, 0.789366032553634, 0.8615938598671289, 0.9458587897954838, 1.0416199568858884, 1.148031023533764, 1.263952761261037, 1.3879729596095478, 1.5184332551928492, 1.653462300238551, 1.7910145302193148, 1.9289136479053062, 2.064899819942325, 2.1966794849235582, 2.321976601345263, 2.4385841216333484, 2.54441446571788, 2.6375477848097035, 2.716276852755825, 2.7791474975474824, 2.8249935874543026, 2.8529657124266805, 2.862552848813717, 2.8535964605264432, 2.8262966685375495, 2.7812103087106235, 2.7192408908209207, 2.6416206645713816, 2.549885186721162, 2.4458409625381434, 2.3315269002932757, 2.2091704653948043, 2.0811395474060297, 1.9498911555111569, 1.8179181334950845, 1.687695132145524, 1.5616250940322585, 1.441987492460589, 1.3308895233653872, 1.2302213770712027, 1.141616617959768, 1.0664185765874739, 1.0056535137112363, 0.960011152567712, 0.9298329986020277, 0.915108678992531, 0.9154803423347602, 0.930254966418649, 0.9584242338505906, 0.9986914559184312, 1.0495048589313498, 1.1090963983158968, 1.1755251376127849, 1.2467241252769328, 1.320549624323457, 1.3948315002184664, 1.4674235521212111, 1.5362525820535267, 1.5993650354792324, 1.6549701140705295, 1.7014783553719788, 1.7375347922430802, 1.7620459443714225, 1.7742000512848344, 1.7734801272072624, 1.7596695985208557, 1.7328504700121934, 1.6933941518759668, 1.641945261008333, 1.579398882943802, 1.5068719406007882, 1.425669458861894, 1.3372466364166122, 1.2431677352451638, 1.1450628712224302, 1.0445838348206689, 0.9433600877322788, 0.8429560690809156, 0.7448309041283895, 0.6503015401193317, 0.5605102399253459, 0.47639724688712765, 0.3986792967183368, 0.327834498044626, 0.2640939360368139, 0.20744017790723346, 0.15761267923175407, 0.11411991069471532, 0.07625785047189734, 0.04313432248073766, 0.013698509310208863, -0.013225165376072346, -0.038899703402029376, -0.0646357556267293, -0.09175047416125934, -0.12152610107072365, -0.1551694090573047, -0.1937730886452449, -0.23828012727716966, -0.28945214971142147, -0.34784258808858015, -0.4137754265499493, -0.4873301224468052, -0.5683331475723875, -0.6563564224749758, -0.7507227390664067, -0.8505180859158412, -0.9546106113838283, -1.0616757866436766, -1.1702271680456906, -1.278652010337344, -1.3852508527307719, -1.488280092024403, -1.585996473714863, -1.6767023754470027, -1.7587907287476765, -1.8307884255744833, -1.8913970858622462, -1.9395301203190203, -1.9743451078507164, -1.9952706171406775, -2.002026734411373, -1.9946387110198154, -1.9734433115728969, -1.9390876215880226, -1.8925202589721344, -1.8349751211705645, -1.7679479850999011, -1.6931664553270813, -1.612553922951811, -1.5281883491245605, -1.4422568192958838, -1.3570069238228533, -1.2746961046849798, -1.1975401646374484, -1.12766216268208, -1.0670429175068343, -1.0174743085069364, -0.9805165028633174, -0.9574601483422762, -0.9492944571039652, -0.9566819686071816, -0.9799406229805228, -1.0190336037853904, -1.0735672251060093, -1.1427969468351473, -1.2256414085298402, -1.3207041810012248, -1.4263027505370114, -1.5405040778278585, -1.6611659164963664, -1.7859829384448274, -1.9125365984047398, -2.0383475808889395, -2.160929611389016, -2.277843381620346, -2.386749336668615, -2.4854581000744327, -2.57197737050697, -2.6445542093043928, -2.7017117496940433, -2.742279493210924, -2.765416513407012, -2.7706270575987824, -2.757768219959338, -2.7270495492600775, -2.679024647362885, -2.6145750054528105, -2.5348865093314683, -2.4414192183785572, -2.33587118082701, -2.2201371869612174, -2.0962634783874825, -1.9663995228489473, -1.8327480279963335, -1.6975144025916307, -1.5628568790394122, -1.4308384868669675, -1.3033820134988143, -1.1822290077971815, -1.068903775449917, -0.964683186088247, -0.8705729632753586, -0.7872909639645671, -0.7152577778080866, -0.6545947932085865, -0.6051296908210434, -0.5664091409634582, -0.5377183036542733, -0.5181065631627084, -0.5064187771550037, -0.5013311874805554, -0.5013910286275888, -0.5050587835923169, -0.5107519774297491, -0.5168893674960078, -0.5219343870508026, -0.5244367254395571, -0.5230709827699797, -0.5166714183861294, -0.5042619184069603, -0.48508043540548124, -0.4585972996851255, -0.4245269628263032, -0.38283290612528326, -0.3337256248622271, -0.2776537794926996, -0.2152887822931825, -0.14750325821435342, -0.07534397739993894, -7.128288962184834e-16], [0.0, 0.0772863422711282, 0.15447478113189028, 0.23018248760138485, 0.3030631507584379, 0.3718473738307926, 0.4353810596098612, 0.4926607473673676, 0.5428649412185005, 0.5853805724014352, 0.6198238626464956, 0.6460549995506145, 0.6641861940328354, 0.674582860511571, 0.6778578381101144, 0.6748587514758252, 0.6666487881314097, 0.6544813411475954, 0.6397691269747738, 0.6240485344017558, 0.6089400880952394, 0.5961060157482885, 0.5872059888080243, 0.5838521609523055, 0.5875646544988651, 0.599728642017365, 0.6215541385567385, 0.6540395598022855, 0.697940014551776, 0.7537411882328241, 0.8216395404824975, 0.9015293873376453, 0.992997271078815, 1.095323842353032, 1.207493294272897, 1.3282102013254735, 1.455923431756569, 1.5888566252004992, 1.7250445621082193, 1.8623746021143475, 1.9986322386202915, 2.1315497098249105, 2.2588565249171735, 2.378330710243234, 2.4878495553813917, 2.585438643897794, 2.669317988076594, 2.737944150352686, 2.790047325041375, 2.824662470098224, 2.8411537172693544, 2.839231446766091, 2.8189615857012726, 2.780766873759328, 2.7254200304614686, 2.6540289512858837, 2.5680142501111574, 2.4690796483317747, 2.359175882085284, 2.2404589541556583, 2.11524369248869, 1.9859536895676309, 1.8550687834082618, 1.7250712995312767, 1.5983923025278957, 1.4773591050421382, 1.3641452511758112, 1.2607241312404625, 1.1688272969111277, 1.0899084323357109, 1.025113800404011, 0.9752598275217809, 0.9408183186833615, 0.9219096115876985, 0.918303788471036, 0.9294298718766113, 0.9543927404414153, 0.9919973175840141, 1.0407794141802946, 1.0990424500841742, 1.1648991424675068, 1.2363171347158526, 1.31116745076025, 1.387274598356721, 1.4624671123711634, 1.5346273262997658, 1.6017391870344981, 1.6619329835204508, 1.713525942987392, 1.7550577567391163, 1.7853202282989626, 1.8033803867356848, 1.808596573460415, 1.8006271875486635, 1.77943195828678, 1.7452657995950653, 1.6986654846180593, 1.6404295555428117, 1.5715920492354938, 1.4933907694923552, 1.4072309678901647, 1.3146454041829025, 1.2172518412758626, 1.1167090869917708, 1.0146727237779674, 0.9127516675498443, 0.8124666681072354, 0.7152118068016101, 0.6222199638766126, 0.534533120317105, 0.4529782298937187, 0.3781492496880005, 0.31039575548800175, 0.2498183961746235, 0.19627126294931693, 0.14937106950360252, 0.1085128625525531, 0.07289181301803362, 0.041530480830077605, 0.013310804792280796, -0.012990053194526134, -0.03866097995043718, -0.0650163439943482, -0.09335468265095227, -0.12491775602921228, -0.16085107180426078, -0.20216694755631837, -0.24971111280433364, -0.3041337624407847, -0.3658658593007959, -0.43510134895149694, -0.5117857978570808, -0.5956118006904385, -0.6860213278950397, -0.7822150050604949, -0.8831681357996944, -0.9876531041563406, -1.0942676255814328, -1.2014681614369933, -1.3076076747385266, -1.4109767879419093, -1.509847310019248, -1.6025170322746274, -1.6873546521074085, -1.7628436723330951, -1.8276241411009235, -1.8805311435588459, -1.9206290301481863, -1.9472404660079314, -1.9599695090281466, -1.958718067619094, -1.9436952497457896, -1.9154192882750547, -1.8747119099191243, -1.8226852015344421, -1.7607212136291657, -1.690444722029159, -1.6136897402452248, -1.5324605328939518, -1.4488880206035024, -1.3651825856663993, -1.2835843822847963, -1.2063123231834336, -1.1355129538887239, -1.0732104360344734, -1.0212588413248733, -0.9812979086672274, -0.9547133396089562, -0.9426026034011069, -0.9457470952439463, -0.9645913426212096, -0.9992297886886589, -1.0494015024696075, -1.1144929774761945, -1.193548987895344, -1.2852912793395856, -1.3881446840478857, -1.5002700728944725, -1.619603392956643, -1.74389989369991, -1.8707825206181898, -1.9977933554511194, -2.1224469093246032, -2.2422840310986856, -2.354925178932299, -2.4581218189293943, -2.549804760322053, -2.6281283108507534, -2.6915092369981175, -2.738659639043366, -2.7686129974588978, -2.7807428113798003, -2.7747734277225584, -2.7507828466626103, -2.7091974810297015, -2.6507790390629684, -2.576603887207261, -2.4880354276710603, -2.386690189979738, -2.2743984827593775, -2.153160577926392, -2.0250995013099122, -1.892411579069098, -1.75731593631386, -1.622004162022394, -1.488591342325455, -1.3590696228811152, -1.2352653915024117, -1.118801076225788, -1.0110624340708971, -0.9131720648784329, -0.8259697263702451, -0.7499998549242729, -0.6855065157887705, -0.6324358210842193, -0.5904456685702153, -0.5589224733904806, -0.5370043933287673, -0.5236103897531219, -0.5174743252956738, -0.5171831788722107, -0.5212183618298241, -0.5279990481658156, -0.5359263885777329, -0.5434274635796649, -0.5489978453323672, -0.5512416807386935, -0.5489082785937228, -0.5409242793105259, -0.5264206044923626, -0.5047535223412329, -0.4755193200363241, -0.43856224183191767, -0.3939755274526463, -0.34209556494379045, -0.2834893509153018, -0.2189356245750225, -0.1494002056917689, -0.07600621652334939, -7.162018293862328e-16], [0.0, 0.0771078074293601, 0.1534978427901408, 0.227806509805988, 0.29872847760231425, 0.36505595543287145, 0.42571537032027634, 0.47980045418187556, 0.5266008390371497, 0.5656253741874822, 0.5966195149192494, 0.6195762848875339, 0.634740480041429, 0.6426059565706921, 0.6439060244764526, 0.6395971474664468, 0.6308363244134525, 0.618952693168413, 0.6054140498807022, 0.591789112265696, 0.5797064700151122, 0.5708112568188635, 0.5667206438924128, 0.5689792927585074, 0.579015914281761, 0.5981020612780722, 0.6273142338207346, 0.6675003007578016, 0.7192511397445831, 0.7828782737281753, 0.858398137327974, 0.9455234454762308, 1.0436619629762012, 1.1519227915860903, 1.2691301053459583, 1.393844079739044, 1.5243885805170858, 1.6588850080971187, 1.7952915375968082, 1.9314468567191188, 2.0651173872907256, 2.194046884244392, 2.3160072405591046, 2.428849289822678, 2.5305523906508984, 2.6192715994522384, 2.6933812895032303, 2.751514153811386, 2.792594634912009, 2.815865954047519, 2.8209100620024254, 2.807660000594293, 2.7764043434107006, 2.7277835724728234, 2.6627784395222736, 2.5826905518921857, 2.48911560877265, 2.383909889579597, 2.269150757790082, 2.1470920870670027, 2.020115638256917, 1.890679512930264, 1.7612648791711585, 1.634322206603216, 1.5122182591512243, 1.397185075507355, 1.2912721191518741, 1.1963027032528184, 1.1138356927128872, 1.0451333585693334, 0.9911361119948828, 0.9524446799150946, 0.9293101057909934, 0.9216317717765292, 0.9289634468230663, 0.9505271740425462, 0.9852346244173504, 1.0317153672888366, 1.088351345257722, 1.1533166961311971, 1.224621940853902, 1.300161456933804, 1.3777630840887272, 1.455238664405055, 1.5304343042257198, 1.6012791595547005, 1.6658315905331185, 1.7223216023422814, 1.7691885878673737, 1.8051135091150945, 1.8290447966434122, 1.8402174055529408, 1.8381646389154633, 1.8227225305703898, 1.7940267644924506, 1.7525022928176766, 1.698845994523672, 1.634002887242543, 1.5591365615330102, 1.4755946462933203, 1.3848702324436875, 1.2885602766593933, 1.1883220755062311, 1.0858289411868485, 0.9827262223129678, 0.8805887964557692, 0.780881116197675, 0.6849208182252255, 0.5938468075540342, 0.5085926087814144, 0.4298656364051287, 0.35813288030043194, 0.2936133343834282, 0.23627732057668885, 0.1858526808944561, 0.14183763232080937, 0.10351990667232334, 0.07000163517724242, 0.04022928917075168, 0.013027857846329321, -0.012861665290009105, -0.038742500983606244, -0.06592108082170145, -0.09566592656859593, -0.12916752029253167, -0.16750024819281523, -0.21158744805957813, -0.2621705108166617, -0.3197828826106748, -0.38472968803489715, -0.4570735504872598, -0.5366270260024563, -0.6229518961976139, -0.7153653885389247, -0.8129532124573208, -0.9145891224609499, -1.0189605488048978, -1.1245996768141202, -1.2299192116706326, -1.333251940052388, -1.4328930966634863, -1.5271444650898862, -1.6143590906018281, -1.6929854588873408, -1.7616099999201469, -1.8189968101994216, -1.8641235486864758, -1.896212550439756, -1.9147563150829379, -1.9195366620838283, -1.9106369980797109, -1.8884473093962186, -1.8536616713369602, -1.8072682503638744, -1.7505319613753312, -1.684970125303289, -1.6123216476408193, -1.534510401904773, -1.4536036493500144, -1.3717664537861167, -1.2912131548904269, -1.2141570423109345, -1.142759424084222, -1.0790793051133334, -1.0250248840267946, -0.9823080397716454, -0.9524029136078515, -0.9365095993053149, -0.935523836505679, -0.9500134622261128, -0.9802022167261913, -1.0259613262739242, -1.086809100946491, -1.1619185949678792, -1.2501331848597164, -1.3499897315482539, -1.4597488111427714, -1.5774313298075504, -1.7008606851253898, -1.8277095033342412, -1.9555498720604703, -2.0819059043548966, -2.204307414009604, -2.320343455657057, -2.427714486674307, -2.5242819413435513, -2.608114070235315, -2.677526987848586, -2.7311199869562595, -2.767804316038046, -2.7868247732598976, -2.7877736428372843, -2.770596683084382, -2.7355910655212576, -2.6833953564470856, -2.6149718217074294, -2.5315815173781666, -2.434752799333808, -2.3262440390347123, -2.2080014676227755, -2.0821131823133627, -1.9507604354337, -1.8161673852392504, -1.6805505174759885, -1.5460689468990627, -1.4147767786888599, -1.2885786517326518, -1.169189500578086, -1.0580994626965103, -0.9565447253148768, -0.8654849548220036, -0.7855877854260347, -0.7172206664961911, -0.6604501842862254, -0.6150487880821915, -0.5805086678538807, -0.5560623547505326, -0.5407094516101648, -0.5332487520940609, -0.5323148777617333, -0.5364184555275378, -0.5439887760830386, -0.55341781899478, -0.5631045035833254, -0.5714980269358427, -0.5771391813585675, -0.578698602376794, -0.5750109834834467, -0.5651044030114674, -0.548224038949975, -0.5238496958998687, -0.49170673088752276, -0.45177013729192167, -0.40426172431145335, -0.3496405086862789, -0.2885866112621415, -0.22197911898388412, -0.15086852879596166, -0.07644452976551316, -7.174339672743204e-16], [0.0, 0.07669902671666083, 0.15206977223130247, 0.22477922542186696, 0.29357376413097264, 0.3573169763079085, 0.41502432333174183, 0.4658937048006904, 0.5093310894808322, 0.5449705041054743, 0.572687817102102, 0.5926079144284467, 0.6051050354808171, 0.6107962141818376, 0.6105279493819572, 0.6053564050877688, 0.5965216102896085, 0.5854162860032888, 0.5735500695491458, 0.5625100294303889, 0.553918465279494, 0.5493890636061349, 0.5504825295113709, 0.5586628358080067, 0.5752552234866068, 0.6014070512901967, 0.6380525281256468, 0.685882271661903, 0.74531852192185, 0.8164967027512654, 0.8992538700701974, 0.9931244175621738, 1.097343232081927, 1.2108563069716127, 1.3323386362296883, 1.4602190306760374, 1.5927113234266157, 1.727851270468587, 1.8635383069547966, 1.9975811946604292, 2.1277464940238446, 2.251808717920383, 2.3676009757540424, 2.4730648968782876, 2.566298632341182, 2.645601773331331, 2.7095160925934687, 2.7568611098960347, 2.786763602111689, 2.7986803197485326, 2.7924133314370976, 2.768117592071001, 2.7263005147899566, 2.6678135172966613, 2.593835704479564, 2.505850037303433, 2.405612517841104, 2.295115087759345, 2.1765430884474335, 2.0522282616003467, 1.9245983762445544, 1.7961246493012673, 1.6692681798349156, 1.5464266408355039, 1.4298824661521419, 1.3217537341844225, 1.2239488850300353, 1.1381263155697665, 1.0656597797018605, 1.0076103814853707, 0.9647057907274702, 0.9373271374204909, 0.9255038576309288, 0.9289165734524781, 0.9469078980934007, 0.9785008687431564, 1.0224245291403091, 1.0771460151345704, 1.1409083440889929, 1.2117729763891716, 1.287666107806603, 1.366427567623272, 1.4458611412482614, 1.5237851088455465, 1.5980817938301368, 1.6667449468344446, 1.7279238510305452, 1.7799631219476413, 1.821437286916538, 1.8511793631670088, 1.8683028060278746, 1.8722163658109048, 1.8626315696206408, 1.8395627280940663, 1.8033195523667704, 1.7544926487884922, 1.6939323335598648, 1.6227213722215654, 1.5421423957898035, 1.453640872695513, 1.3587846204395655, 1.259220920483282, 1.1566323524457318, 1.0526924879485955, 0.9490225799161855, 0.847150350003837, 0.7484719160077311, 0.6542178142097643, 0.5654239608888406, 0.4829082655336592, 0.4072534589920271, 0.33879653669377113, 0.2776250443351691, 0.22358025539566626, 0.1762671110821327, 0.13507061828548472, 0.09917823431310868, 0.06760761274154914, 0.039238946615380764, 0.012851026884655163, -0.012839961590836037, -0.039139954527522364, -0.06733592468351421, -0.09865530717716087, -0.134227027480876, -0.17504518475387645, -0.22193637494883928, -0.27553154454821627, -0.3362431492149838, -0.40424825501928946, -0.4794780666733768, -0.5616142012394484, -0.6500918512603188, -0.7441098026115103, -0.8426470941053832, -0.9444859325085236, -1.0482403125608428, -1.152389640979229, -1.2553165301285178, -1.3553478144576052, -1.4507977538241188, -1.5400123247754862, -1.6214134653793268, -1.693542132276571, -1.7550990505271313, -1.8049820870706486, -1.8423192560636843, -1.8664964671274127, -1.8771792531574958, -1.8743278597453954, -1.8582052398729172, -1.8293776713919498, -1.7887078965978769, -1.7373408684492917, -1.6766823720834796, -1.6083709686497953, -1.5342438766861457, -1.456297560094562, -1.376643927373869, -1.2974631607277736, -1.220954283100409, -1.1492846338143379, -1.084539457671614, -1.0286728171996298, -0.9834610129760426, -0.9504596431755723, -0.930965351887765, -0.9259832082880471, -0.936200527973428, -0.9619677968463867, -1.0032871904931078, -1.0598090021141608, -1.1308361040970565, -1.2153363768452794, -1.3119628481627545, -1.419081101979071, -1.5348033409932444, -1.6570283281686056, -1.783486290830534, -1.9117877518547477, -2.0394751580040094, -2.1640761081858826, -2.283156945910433, -2.394375471465782, -2.4955315505165436, -2.584614446445438, -2.659845782563587, -2.7197171453809075, -2.7630214688839643, -2.78887748906511, -2.796746724132904, -2.786442614848574, -2.7581316469037147, -2.7123264686054496, -2.6498712077007407, -2.5719193763101886, -2.479904928151046, -2.375507193256054, -2.2606105583403906, -2.13725988238411, -2.007612733967402, -1.8738896071110314, -1.7383233141875358, -1.6031087669341666, -1.4703543394943273, -1.3420359612477848, -1.2199550131833805, -1.1057010016272746, -1.0006198598072402, -0.9057885841236082, -0.8219967517180342, -0.7497352929954247, -0.6891927114784632, -0.6402587582720148, -0.6025353840838029, -0.5753546127567399, -0.5578028110424086, -0.5487506740567997, -0.5468881083254574, -0.5507630779118466, -0.5588233866631281, -0.569460303331562, -0.5810528978098255, -0.5920119468308997, -0.60082228638753, -0.6060825352623926, -0.6065411881627699, -0.6011281760854355, -0.5889811131375198, -0.5694655899883081, -0.5421890308255979, -0.5070077991496714, -0.4640274136798349, -0.41359591461223216, -0.3562905979226732, -0.29289850686670865, -0.22439123095888172, -0.15189470944551592, -0.07665486491786654, -7.165134511644309e-16], [0.0, 0.0760635878985933, 0.15020317920228252, 0.22112736369370437, 0.2876444335722459, 0.3486984336877013, 0.40340152379669425, 0.45106177263982933, 0.49120562143975316, 0.5235943919571607, 0.5482343680410348, 0.5653801457868123, 0.5755311217725481, 0.5794211669695538, 0.5780017113120062, 0.572418636064643, 0.5639835336799802, 0.5541400436530631, 0.5444261041685285, 0.5364330697321196, 0.5317627316462942, 0.5319833388774737, 0.5385857499686149, 0.5529408512616011, 0.5762593526079365, 0.6095550194801126, 0.6536123211726864, 0.7089593705011709, 0.775846903598098, 0.8542339021670317, 0.9437802984765141, 1.0438470294497415, 1.1535035247290495, 1.271542529062067, 1.3965019763496287, 1.526693455768227, 1.660236643944885, 1.7950989253828824, 1.9291392900213724, 2.0601554853203043, 2.1859333134208683, 2.3042969039635666, 2.4131587616139467, 2.510568385113698, 2.5947582818835224, 2.664186258270139, 2.7175729491550555, 2.753933659849194, 2.7726037253723765, 2.7732567441783607, 2.755915211460487, 2.7209532572846316, 2.669091382567794, 2.601383276781201, 2.519194990553585, 2.4241769194639047, 2.3182292277703476, 2.2034614984088785, 2.0821475344550158, 1.9566763539790066, 1.829500511978605, 1.7030829475974598, 1.5798435905487365, 1.462106966686311, 1.3520520188493323, 1.2516653060304823, 1.162698662880248, 1.086632294539396, 1.0246441514056777, 0.9775862778751758, 0.9459686620328553, 0.9299509337813049, 0.9293420713732038, 0.9436080853263293, 0.9718874589051462, 1.0130139403710083, 1.0655461085066928, 1.127802973725244, 1.1979047362313475, 1.273817703612864, 1.3534022757586066, 1.434462837374603, 1.514798359189386, 1.5922524990819165, 1.6647620139922463, 1.7304023420183066, 1.787429290283554, 1.8343158660227232, 1.869783413290181, 1.8928263625962818, 1.9027300619850491, 1.8990813315496191, 1.8817715648138074, 1.8509923852756216, 1.8072240501232266, 1.751216971146878, 1.6839668907843024, 1.6066844049157052, 1.5207596596947348, 1.42772316404653, 1.3292037497048284, 1.2268847746247344, 1.1224597017837563, 1.01758819295498, 0.9138538359022143, 0.8127245742248286, 0.7155168330873061, 0.6233642332903555, 0.5371916631786258, 0.45769533588720346, 0.3853293020300016, 0.3202987191327707, 0.26256000319709594, 0.21182780920735025, 0.16758861067892122, 0.12912047795981746, 0.09551849524188194, 0.0657251111432731, 0.03856459094960283, 0.012780633341989549, -0.012923866652428562, -0.03984598163690864, -0.06924194319469941, -0.10228746008180736, -0.14004023351109868, -0.18340568304781416, -0.23310681383473095, -0.2896590490796294, -0.35335072366356957, -0.424229788598564, -0.5020971155675091, -0.5865066199719412, -0.676772244112019, -0.7719816638008136, -0.8710164063872345, -0.9725779002748645, -1.0752188198419739, -1.1773789491673783, -1.2774246667357825, -1.3736910544444854, -1.4645255603140603, -1.5483320972511054, -1.6236144412829403, -1.6890178024420248, -1.7433674797635577, -1.785703577800966, -1.8153108540947698, -1.8317428829289883, -1.834839857653405, -1.8247395084853277, -1.801880781228074, -1.7670001005975269, -1.7211202254230584, -1.6655318873328409, -1.6017685850643215, -1.5315750787609292, -1.4568702882243982, -1.379705442090455, -1.3022184476882102, -1.2265855508278292, -1.1549714284041293, -1.0894789026070126, -1.0320994824757554, -0.9846659260188715, -0.9488079743667052, -0.9259123393733655, -0.9170879293812246, -0.9231371768076329, -0.9445341887154329, -0.9814102810251533, -1.0335472824038057, -1.1003788093625801, -1.1809995242012863, -1.2741821967774656, -1.3784022043027475, -1.491868925038884, -1.612563316237978, -1.7382808179935212, -1.8666785964783865, -1.9953260354809517, -2.121757306772031, -2.243524799563994, -2.358252168392875, -2.463685767678804, -2.557743279785092, -2.6385584106594924, -2.7045206214598143, -2.7543089836344414, -2.786919385836118, -2.801684480351342, -2.7982859305354855, -2.7767587048116407, -2.737487352626636, -2.681194388731712, -2.608921099615601, -2.522001265303231, -2.422028456686796, -2.310817719030726, -2.1903625826518494, -2.062788448883492, -1.9303034807265713, -1.7951481811490053, -1.6595448665802965, -1.5256482382386003, -1.3954982197273884, -1.2709761667741302, -1.153765465676979, -1.0453174232559392, -0.9468232157503274, -0.8591925105692461, -0.7830392069319722, -0.7186745634233046, -0.6661077967682969, -0.6250540512667075, -0.5949494569024242, -0.5749728206444104, -0.5640733341633584, -0.561003536069134, -0.5643566413844512, -0.5726072483670562, -0.5841543554591271, -0.5973655709265229, -0.6106213758198924, -0.6223583077038818, -0.6311099679006854, -0.6355448178094804, -0.6344998185370425, -0.6270090803066665, -0.6123268210156846, -0.5899440834873518, -0.5595988245834576, -0.5212791622516684, -0.47521974439099796, -0.4218913816272526, -0.361984260191125, -0.29638521668618373, -0.22614970944227875, -0.1524692575147679, -0.07663523477399013, -7.134478006290147e-16], [0.0, 0.07520709369811655, 0.1479145368555273, 0.21688309825486954, 0.2809925746419807, 0.33927577050809954, 0.390948294895722, 0.4354333627482429, 0.47238091742563393, 0.5016805378310005, 0.5234677544260514, 0.5381235691920222, 0.5462671509973023, 0.548741855399251, 0.5465948921368569, 0.5410511300433045, 0.5334816835930443, 0.5253680638622211, 0.518262795784416, 0.5137475001691718, 0.5133895105227426, 0.5186981393965515, 0.5310817255875215, 0.5518065815264003, 0.5819589198311713, 0.6224107701993503, 0.6737908041806245, 0.7364608681745731, 0.8104988870953291, 0.8956886459177542, 0.9915167875893756, 1.097177187725884, 1.2115826835141945, 1.3333839508677, 1.4609951446749914, 1.592625746424466, 1.726317905836609, 1.859988422346635, 1.9914743918965303, 2.118581447563373, 2.2391334515424366, 2.351022452754699, 2.4522577100125362, 2.5410125956959404, 2.6156682389816956, 2.674852839829367, 2.7174756834656333, 2.7427550076748686, 2.7502390188549546, 2.7398195140655948, 2.711737741275051, 2.666582314450793, 2.6052791895517045, 2.5290738972480695, 2.4395064136896805, 2.3383792273311723, 2.2277193233870083, 2.1097349539248698, 1.986768187329617, 1.861244332800579, 1.7356194111829335, 1.6123268909229793, 1.4937249261089625, 1.382045321963466, 1.2793454120681707, 1.1874639620271206, 1.1079821179077927, 1.0421902969928376, 0.9910617760797559, 0.9552335722557312, 0.9349950366646682, 0.9302843975297986, 0.94069329909277, 0.9654791928004658, 1.0035852506489928, 1.0536672926144293, 1.1141270548839797, 1.1831509771523296, 1.2587535591527792, 1.3388242319326544, 1.4211766106590005, 1.5035989448137494, 1.5839045596810009, 1.6599810905021402, 1.7298373473110336, 1.7916467132784784, 1.8437860707165115, 1.8848693643936376, 1.9137750485743386, 1.9296668187846238, 1.9320071978513296, 1.920563724061345, 1.8954076729011298, 1.8569054282084227, 1.8057027991301706, 1.7427027515716536, 1.6690371825950863, 1.586033509555861, 1.4951769691427383, 1.398069621910442, 1.2963871329333017, 1.1918344470779556, 1.0861014969844391, 0.9808200727584118, 0.8775229449295959, 0.7776062674478569, 0.6822961970744529, 0.5926205518259952, 0.5093861970652196, 0.43316269683301944, 0.3642726039268758, 0.3027885892199802, 0.24853743316909294, 0.20111072487130657, 0.15988194088924082, 0.12402941174260017, 0.09256453260691859, 0.06436444018271055, 0.038208263290001515, 0.01281596338373959, -0.013111284827699281, -0.04085026148784321, -0.07161551827624354, -0.10652092630128576, -0.14654399279360927, -0.192493912482079, -0.2449842229654781, -0.3044108144057027, -0.37093590546825195, -0.4444784431197518, -0.5247112175601153, -0.6110648094238832, -0.702738308837178, -0.7987165694592181, -0.8977935897435741, -0.9986014526630019, -1.0996441081476866, -1.1993351532391223, -1.2960386567692561, -1.3881119910217605, -1.4739495745106128, -1.5520263992624417, -1.6209402136662776, -1.6794512582000984, -1.7265185055847356, -1.7613314378776137, -1.7833364987555, -1.792257487177537, -1.78810930563777, -1.7712046386972946, -1.7421533114236132, -1.7018542584575311, -1.6514802181866999, -1.5924554483639533, -1.5264269349386206, -1.4552297304904296, -1.3808472083468109, -1.3053671494654198, -1.2309346881687278, -1.159703227059086, -1.093784488759686, -1.035198901020177, -0.9858275113950521, -0.9473665980687384, -0.9212860851072183, -0.9087927848133781, -0.9107993789797811, -0.9278999173221393, -0.9603524584547909, -1.0080693101347764, -1.0706151452441377, -1.1472130824834086, -1.2367586305790683, -1.3378412066020706, -1.4487727573480527, -1.567622842082306, -1.6922593794770924, -1.820394125071402, -1.9496318314067254, -2.077521953935504, -2.2016117040463743, -2.319499217619018, -2.428885604223604, -2.5276246685010735, -2.6137691507609837, -2.685612417059391, -2.741724637939791, -2.7809826269754865, -2.802592662019373, -2.8061057799412343, -2.7914252155148525, -2.7588058426186617, -2.708845666461765, -2.642469604499491, -2.560905976460392, -2.465656296028047, -2.3584591140308557, -2.241248801684519, -2.116110279160909, -1.9852307867234444, -1.8508498606856338, -1.7152087129942681, -1.5805002204934375, -1.4488207077931374, -1.3221246567731415, -1.202183397433133, -1.090548731060768, -0.9885223101596645, -0.89713145344595, -0.8171119121487065, -0.74889792988533, -0.6926197568623994, -0.6481085945873793, -0.6149087642434483, -0.5922967149069343, -0.5793063212421736, -0.5747597682908399, -0.5773031872103587, -0.5854460935754928, -0.5976035918618604, -0.6121402480941002, -0.6274144988168324, -0.6418224592895815, -0.6538400171586004, -0.6620621491461248, -0.66523847615117, -0.6623041745439311, -0.6524054857167896, -0.634919208943481, -0.6094657206461311, -0.5759152322573988, -0.5343871747013496, -0.4852427756481352, -0.42907107161840036, -0.3666687662794978, -0.29901450461503265, -0.22723827606919228, -0.1525867846540029, -0.07638572721680723, -7.082637558517266e-16], [0.0, 0.07413709835275921, 0.14522400484054135, 0.2120837114363483, 0.27367640813371447, 0.3291311132120628, 0.3777726649168713, 0.41914333635258993, 0.45301847459912176, 0.4794157198424507, 0.4985975267427819, 0.5110668841392817, 0.5175563061081997, 0.5190103428692708, 0.5165620296238558, 0.5115038508004445, 0.5052539423232434, 0.4993183817047742, 0.4952505217369016, 0.49460840558754515, 0.49891135707029904, 0.5095968682598457, 0.5279789066844436, 0.5552087359542063, 0.5922392875087659, 0.6397940385161398, 0.6983412438172653, 0.7680742407954104, 0.8488983983163737, 0.9404251180684386, 1.0419731227491276, 1.1525770849027714, 1.271003467290637, 1.3957732650230008, 1.5251911658029627, 1.6573804818700868, 1.7903230596667499, 1.9219032445923503, 2.049954871710578, 2.1723101716411204, 2.2868494261982826, 2.3915501820707035, 2.484534833705425, 2.5641154185842256, 2.6288345285583854, 2.677501328435003, 2.709221785508325, 2.723422348509346, 2.719866468258337, 2.698663521426532, 2.6602698791406643, 2.60548204931164, 2.535422010976461, 2.4515150459895323, 2.355460553516243, 2.249196501564518, 2.1348583231076126, 2.0147331984490577, 1.8912107770704019, 1.7667314785467654, 1.6437335710925143, 1.5246002564578123, 1.4116079904894345, 1.3068772396729742, 1.2123268160895397, 1.1296328478565882, 1.0601933313605993, 1.0050990781307876, 0.9651117163050288, 0.9406492380326885, 0.9317794039580757, 0.9382211285277038, 0.9593537798324907, 0.9942341396608101, 1.0416205879749822, 1.1000039055412583, 1.167643933076221, 1.2426111887792812, 1.3228324317919975, 1.4061390697017517, 1.4903172458155949, 1.5731584080280172, 1.65250915644923, 1.7263191915833964, 1.7926862380630346, 1.8498968993685587, 1.8964625045345105, 1.9311491358949318, 1.953001174229149, 1.9613578605468458, 1.9558625481323901, 1.9364645000120366, 1.903413271205604, 1.8572458974128168, 1.7987672876575895, 1.7290243835345116, 1.6492747980106222, 1.5609507785494836, 1.4656194494285593, 1.3649403738472543, 1.2606215357167874, 1.1543748724918432, 1.0478724933524448, 0.9427046914897614, 0.8403408059203511, 0.7420939085709509, 0.6490901884171605, 0.5622437789046766, 0.48223763094730915, 0.4095108751522778, 0.34425294760388725, 0.2864045778358868, 0.23566555998911579, 0.19150905307492802, 0.15320198816689823, 0.11983100346322727, 0.09033318645339776, 0.0635307794525542, 0.03816890362909503, 0.012955279886313065, -0.013399125506303466, -0.042139625539468, -0.07442859712833381, -0.11130858237807517, -0.15366870265436977, -0.20221529568918456, -0.2574475765415772, -0.31963899315196387, -0.38882479976532486, -0.4647962103824786, -0.5471013237037825, -0.6350528350752588, -0.7277423741885858, -0.8240611342034211, -0.9227262929452135, -1.0223125740786485, -1.1212881595574358, -1.2180540476961996, -1.3109858569021855, -1.3984770058814604, -1.4789821588089898, -1.5510598096653394, -1.6134128941343322, -1.6649263598530502, -1.704700695427678, -1.7320805138125037, -1.7466774040883188, -1.7483864044778772, -1.737395605192262, -1.714188558574577, -1.679539351822095, -1.6345003799183297, -1.580383038762783, -1.518731736308321, -1.4512917883663572, -1.3799719213933226, -1.3068022431210369, -1.23388865984744, -1.1633648135734953, -1.097342680546145, -1.0378630133729099, -0.9868468206215596, -0.9460490603292314, -0.9170156774623456, -0.9010450411484238, -0.8991547371885469, -0.9120545473468297, -0.9401263021809515, -0.9834111322206761, -1.0416044670445583, -1.1140589475066105, -1.1997952275113757, -1.2975204529321471, -1.4056540211227342, -1.5223600494881373, -1.6455858200351947, -1.7731053226751827, -1.902566896829245, -2.0315438716162033, -2.1575870320179926, -2.2782776937129094, -2.391280153843771, -2.494392299233526, -2.585593197134089, -2.663086565438127, -2.725339117647255, -2.771112900375439, -2.799490884784316, -2.809895234592832, -2.8020978482425494, -2.7762229571642707, -2.732741751386328, -2.672459193337184, -2.5964933660092804, -2.5062478781612416, -2.4033780126567983, -2.2897514504124965, -2.167404528216806, -2.038495090865805, -1.90525307419379, -1.7699300038640224, -1.63474861411457, -1.501853780631396, -1.3732659226715673, -1.2508379625240515, -1.1362168371018084, -1.0308104392779658, -0.9357607284657805, -0.8519235943625942, -0.7798558886216221, -0.7198098606979285, -0.6717350506751967, -0.6352875080676879, -0.6098460259564071, -0.594534908794757, -0.5882526340184788, -0.5897056261007987, -0.5974462403658937, -0.6099139556626307, -0.6254787022745194, -0.6424852059299792, -0.6592972115262397, -0.6743404615307168, -0.6861433436010842, -0.6933741886911552, -0.694874293029504, -0.6896858524850256, -0.6770741330111265, -0.6565433526333391, -0.6278459149500609, -0.59098480717549, -0.5462091529826396, -0.49400308731910497, -0.4350682924993019, -0.37030069788062786, -0.3007619951979529, -0.22764675438873438, -0.15224603714898577, -0.07590849469238757, -7.010069300183296e-16], [0.0, 0.07286302508172521, 0.14215521657617017, 0.20677120932375972, 0.26575969494740403, 0.3183524464990932, 0.3639882921409837, 0.4023313797812862, 0.4332832226366229, 0.45698817703810274, 0.4738321743554531, 0.4844347043646352, 0.48963422328518963, 0.4904673316044388, 0.48814223032331816, 0.4840071152453989, 0.4795143035391009, 0.47618100159225973, 0.4755477152004554, 0.479135370005573, 0.48840225007635113, 0.504701874517693, 0.5292429156297337, 0.5630522177408696, 0.606941904443863, 0.6614814652816072, 0.7269755933062529, 0.8034484052979299, 0.8906345202093873, 0.9879773024543846, 1.094634399160541, 1.2094905188642877, 1.3311772178523877, 1.4580992839683844, 1.588467140609023, 1.7203345400202883, 1.8516406787248412, 1.980255752410682, 2.1040288758154775, 2.2208372274018924, 2.328635240646284, 2.4255026545822584, 2.5096902561685956, 2.5796621956855548, 2.6341338325927595, 2.6721041713109, 2.6928820717835253, 2.6961055654195927, 2.6817537695905855, 2.6501510693165553, 2.6019634188582685, 2.538186804154723, 2.460128094814824, 2.3693786971029684, 2.2677815925818403, 2.1573925065521524, 2.0404360922505522, 1.9192581374559512, 1.7962748967476314, 1.6739207227816, 1.5545952118769322, 1.4406110918937547, 1.334144063516694, 1.2371857600336504, 1.151500916634659, 1.0785897399511417, 1.019656344455822, 0.9755839774735366, 0.9469175924465415, 0.9338541547080118, 0.9362408796211055, 0.9535814140324254, 0.9850497831694944, 1.0295117409770653, 1.0855529869127756, 1.1515135506552903, 1.2255275019306944, 1.3055670192184419, 1.3894897514247744, 1.4750883330892013, 1.5601408680528053, 1.6424611798122604, 1.7199476393438953, 1.790629422621395, 1.8527091192718155, 1.9046007090393036, 1.9449620415383906, 1.9727210941869762, 1.9870954397191716, 1.9876045243815201, 1.974074536586775, 1.9466358289992247, 1.9057130402141718, 1.8520082408419094, 1.7864775985064003, 1.7103022128459546, 1.6248539112176126, 1.5316569150489017, 1.432346382754257, 1.328624905528018, 1.2222180754728054, 1.1148302604344995, 1.0081017063125342, 0.9035680459280021, 0.8026232248932821, 0.7064867611382764, 0.616176138237033, 0.532484996435887, 0.45596763279013247, 0.3869301569509364, 0.3254284760922896, 0.27127310561178297, 0.22404062605086061, 0.18309143560854083, 0.14759328598186122, 0.11654994112864747, 0.08883416764207305, 0.06322415504293505, 0.03844237720679033, 0.013195844532607184, -0.013783338131837845, -0.043698199505360524, -0.07764898620436354, -0.11659812495529163, -0.1613390092012615, -0.21246945722149121, -0.2703705676639638, -0.33519155841704334, -0.406841019555844, -0.48498484462040126, -0.5690509309286179, -0.6582405633920089, -0.7515462218525766, -0.847775383720067, -0.9455797359341269, -1.0434890670209112, -1.139948984913957, -1.233361502469151, -1.3221274528958018, -1.4046896437230483, -1.4795756318442632, -1.5454390043647581, -1.6010980804452244, -1.645571007402059, -1.6781063086197252, -1.6982080493145806, -1.7056549162194834, -1.7005126556451833, -1.683139477463692, -1.6541842063211023, -1.6145771415179866, -1.5655137690214476, -1.5084316484633928, -1.4449809702594032, -1.3769894388426955, -1.3064222834132837, -1.2353383238928388, -1.1658431237568243, -1.1000403404382526, -1.039982436026004, -0.9876219346425824, -0.9447644075080496, -0.9130243323212932, -0.893784910976143, -0.8881628402360302, -0.896978915937914, -0.9207352153173652, -0.9595994474201632, -1.0133968920344296, -1.0816101672571632, -1.1633868790875934, -1.2575550178685568, -1.362645780579046, -1.476923319458031, -1.5984207505786912, -1.7249816048805802, -1.8543057725082677, -1.9839988823297277, -2.1116239748928938, -2.234754270881867, -2.3510258097421777, -2.458188735239197, -2.5541560362559954, -2.6370486113652505, -2.705235613162253, -2.7573691408924854, -2.792412484805023, -2.809661279622333, -2.8087570937829183, -2.789693161558024, -2.752812152367983, -2.6987960610660275, -2.6286484900047644, -2.5436697738036878, -2.4454255665200253, -2.335709664297834, -2.2165019708221343, -2.0899226248003058, -1.9581833955500603, -1.8235375125281652, -1.6882291258925617, -1.5544435972599289, -1.4242597927286198, -1.299605494726978, -1.182216966761409, -1.0736035977811542, -0.9750184233599062, -0.8874351724710489, -0.8115323250164651, -0.747684490538643, -0.6959612370473262, -0.6561333151289319, -0.6276860410282343, -0.6098394276798292, -0.6015744890257008, -0.6016649944048628, -0.6087138199775151, -0.6211929362119809, -0.6374859870292738, -0.6559323592631408, -0.6748716119847956, -0.6926871345964687, -0.7078479303409674, -0.7189474772215586, -0.7247386998062257, -0.7241641908810856, -0.7163809487013467, -0.7007790404192353, -0.6769937614547045, -0.6449110300717069, -0.6046659319330618, -0.5566345064894277, -0.5014190412383581, -0.4398273067724619, -0.3728463209148886, -0.30161137020328077, -0.22737113800903772, -0.15144988762618417, -0.07520772324784447, -6.917412759595509e-16], [0.0, 0.07139606537088652, 0.138735032995495, 0.20099189165341194, 0.25731109178621736, 0.30703273363752515, 0.34971333868624505, 0.3851406314990103, 0.4133419146745972, 0.43458578602374853, 0.4493771203070409, 0.45844541335442385, 0.46272675976386096, 0.4633399022237132, 0.46155694658443486, 0.4587694781462365, 0.456450937622879, 0.45611621673647795, 0.45927951077872825, 0.4674115167267379, 0.48189708926594743, 0.5039944626752677, 0.5347971140026812, 0.5751992830404921, 0.625866078723277, 0.6872089917965954, 0.7593675026208382, 0.8421973239985444, 0.9352656556178051, 1.0378536531275344, 1.1489661353063163, 1.2673483717180898, 1.3915096151756345, 1.5197528727031602, 1.6502102497735973, 1.7808830593846285, 1.909685763639049, 2.0344927140477633, 2.153186580365844, 2.263707308376965, 2.364100425968168, 2.4525635246960134, 2.527489780733475, 2.58750744378856, 2.631514313791102, 2.65870634068741, 2.6685996197926523, 2.6610452105209776, 2.636236376180602, 2.5947080227596637, 2.5373283008507856, 2.4652825225268336, 2.3800497295037055, 2.283372425796323, 2.177220152960902, 2.0637477348797373, 1.9452491482318075, 1.8241080811311483, 1.7027463232892202, 1.583571184474772, 1.4689231626826904, 1.3610250786648441, 1.2619338594227618, 1.1734960907337153, 1.0973083692947418, 1.0346833707999545, 0.9866224139980543, 0.9537951458300422, 0.9365268028988138, 0.9347933239126469, 0.9482244007749753, 0.9761143672174268, 1.0174406378868193, 1.0708892321222567, 1.134886749634661, 1.2076380139767635, 1.287168467725979, 1.3713702938752188, 1.4580511536600578, 1.5449843739456393, 1.6299593886841681, 1.7108312394627094, 1.7855679697029172, 1.8522948048477097, 1.9093340953792821, 1.9552401086081108, 1.9888278861016584, 2.0091955330999363, 2.015739470557831, 2.0081623554682437, 1.9864735565070197, 1.9509822553036258, 1.902283424247755, 1.8412371052345675, 1.7689415758595288, 1.686701136319498, 1.5959893780714303, 1.4984089010345598, 1.3956485272419448, 1.2894391134165475, 1.1815090916945574, 1.073540866068853, 0.9671291622122322, 0.8637423710016255, 0.7646878428220026, 0.6710819827476951, 0.5838258687333809, 0.5035869692712018, 0.43078737729588895, 0.36559880750153845, 0.30794442896999974, 0.2575074285341473, 0.21374602706612045, 0.17591450525972602, 0.14308964163942042, 0.11420182734634117, 0.08807000319774787, 0.06343946757823278, 0.039021531328640655, 0.013533949761442784, -0.014258956605639441, -0.045507571590754185, -0.08124068504189548, -0.12233260469744568, -0.16947456723721355, -0.22315122569002346, -0.2836228584717051, -0.3509137967402666, -0.4248074052344869, -0.5048477813971711, -0.5903481626895676, -0.6804058570105411, -0.7739233404812971, -0.8696350048768766, -0.9661388877987371, -1.0619325860913253, -1.1554524403995556, -1.2451149890360886, -1.3293596247991228, -1.4066913507454455, -1.475722521200101, -1.5352124727949041, -1.5841039966870822, -1.6215556762324155, -1.6469692125169595, -1.6600109809015338, -1.6606272021460524, -1.649052268301386, -1.6258099325170634, -1.5917072490296196, -1.5478213304716595, -1.4954791697751382, -1.436230948841304, -1.3718174214418548, -1.3041321093572613, -1.2351791847376243, -1.1670280247043903, -1.1017655134261235, -1.0414472300097446, -0.9880486959041876, -0.9434178621531158, -0.9092299945027446, -0.8869460635305685, -0.8777756687771976, -0.8826454221800071, -0.9021735893997092, -0.9366516409476903, -0.9860332019087471, -1.0499307134672053, -1.1276199356542136, -1.2180522332185368, -1.3198743998589664, -1.4314555948051808, -1.5509207943306647, -1.6761900034238673, -1.805022333391188, -1.9350639330398078, -2.0638986671934627, -2.1891003689411646, -2.3082854528703494, -2.419164666564703, -2.519592777111359, -2.6076150378006338, -2.6815093564415875, -2.7398231889073794, -2.7814043071771026, -2.8054247371951186, -2.8113973247644894, -2.7991845634572514, -2.7689995028771683, -2.72139874405838, -2.6572677167376177, -2.5777986161252673, -2.4844615501773637, -2.3789696080293643, -2.263238702327757, -2.1393431592572645, -2.0094681271993706, -1.8758599458538476, -1.7407756606374585, -1.6064328812607505, -1.4749611683031345, -1.3483560878054082, -1.2284370025294078, -1.1168095714249238, -1.014833808453573, -0.92359841127561, -0.8439019129291322, -0.7762410394482876, -0.7208064776119498, -0.6774860741229317, -0.6458753050194337, -0.6252946765236412, -0.6148135502147107, -0.6132797305118312, -0.6193540147629304, -0.6315487891149388, -0.6482696596328605, -0.6678590400894272, -0.6886405770732484, -0.7089632804873582, -0.7272442433530444, -0.7420088786084494, -0.751927671113756, -0.7558485384958735, -0.7528240123178214, -0.7421325883175438, -0.7232937476242708, -0.6960763160317393, -0.6605000013971782, -0.616830125663581, -0.5655657434121728, -0.5074215088155963, -0.4433038130964239, -0.3742818610662733, -0.3015544843448077, -0.22641359719427978, -0.15020528583678483, -0.07428958152193432, -6.805483731389498e-16], [0.0, 0.06974906116925877, 0.13499326539564016, 0.1947958810938991, 0.24840346127378168, 0.29526899149413566, 0.33506930496024045, 0.3677162813753501, 0.39336150779919754, 0.41239424988535156, 0.42543275615586507, 0.43330909200769785, 0.43704786951581637, 0.4378393995009265, 0.4370079396851253, 0.43597584330961076, 0.4362245229963491, 0.4392532320636225, 0.4465367276905626, 0.4594829156357126, 0.47939158368920254, 0.507415310414094, 0.5445235874510499, 0.5914711188571643, 0.6487711614266567, 0.7166746481229536, 0.7951556956260263, 0.8839039400425253, 0.9823239759189923, 1.0895419970271425, 1.2044195573446328, 1.3255741917189086, 1.4514064623419638, 1.580132833718226, 1.709823629377254, 1.8384451919299782, 1.963905257520833, 2.084100469101491, 2.196964892470912, 2.300518366274232, 2.3929135130294497, 2.4724802629493072, 2.5377667953272485, 2.5875758823414845, 2.6209957254092853, 2.6374245021786877, 2.6365879897967135, 2.6185497936733255, 2.583713886599034, 2.5328193464980875, 2.4669273678370605, 2.387400807200531, 2.295876703255859, 2.1942323808580255, 2.0845459042380208, 1.9690517812661943, 1.8500929363183298, 1.7300700604546402, 1.6113895122019761, 1.4964109786101187, 1.3873961135259307, 1.2864593479991784, 1.1955220169231975, 1.1162708676490682, 1.0501219122954306, 0.9981904583369969, 0.9612680048887017, 0.9398065284941984, 0.9339105061634351, 0.9433368391737618, 0.967502653239596, 1.005500763641294, 1.0561224123334203, 1.1178867123375298, 1.1890760770306463, 1.2677767720853519, 1.3519236091766627, 1.439347705995618, 1.5278261688567776, 1.6151325138638837, 1.6990866311240145, 1.7776031140846134, 1.848736822203941, 1.9107246186471911, 1.96202232364982, 2.0013360461059806, 2.0276471977613357, 2.0402306525698592, 2.038665684371304, 2.022839494819359, 1.9929433260072937, 1.9494613339821747, 1.8931525758241714, 1.825026629847848, 1.746313521659314, 1.6584287645276496, 1.562934437493403, 1.4614973160568185, 1.355845135970633, 1.2477221090586041, 1.1388448202261354, 1.0308596167605852, 0.9253025551800343, 0.8235628985154353, 0.7268510598969485, 0.6361717691678618, 0.552303101023351, 0.4757818493929985, 0.4068955673647378, 0.3456814190774002, 0.2919318140632972, 0.245206619944695, 0.20485158058173095, 0.1700224079858612, 0.13971387154681145, 0.11279308100959659, 0.08803605337107318, 0.06416657110477844, 0.03989628193692082, 0.013964960208414302, -0.014820152589761946, -0.04754698518430763, -0.08516425640318943, -0.1284510039363416, -0.1779908462848409, -0.23415167895062872, -0.29707136457390565, -0.3666498208752361, -0.44254774385130763, -0.5241920309224836, -0.6107877940145232, -0.7013366803063231, -0.79466105296271, -0.8894334298001442, -0.9842104384348194, -1.0774704255957697, -1.1676537590477931, -1.2532047855179853, -1.3326143591097122, -1.404461833219072, -1.467455415555147, -1.520469820417503, -1.5625802141115142, -1.5930915368112184, -1.6115623951903202, -1.6178228520202493, -1.6119855884375913, -1.5944500780220576, -1.5658995851544253, -1.5272909790402, -1.4798375348378339, -1.4249850700318045, -1.3643819331237796, -1.2998435186478539, -1.2333121235032016, -1.1668130810838222, -1.1024082085883415, -1.0421476766868014, -0.9880214574943772, -0.9419115253093324, -0.9055459742653045, -0.8804561780896841, -0.8679380504220401, -0.8690183711888912, -0.8844270275640522, -0.9145758798735258, -0.9595448067653981, -1.0190753138389637, -1.0925719098477455, -1.1791112689437537, -1.2774590107453008, -1.3860937468492167, -1.5032378672524143, -1.6268943772879065, -1.754888949110259, -1.8849162250845568, -2.014589306754461, -2.1414912849434207, -2.263227615905883, -2.377478126550647, -2.4820474391580047, -2.574912642543596, -2.6542671014067194, -2.718559387070317, -2.766526428752008, -2.7972201220781767, -2.8100267874168035, -2.8046790409611737, -2.781259822195759, -2.7401985080152236, -2.6822592318030885, -2.608521710632494, -2.5203550609336296, -2.4193852481791094, -2.3074569653655748, -2.186590864709602, -2.0589371739056723, -1.92672680995124, -1.7922211579912382, -1.6576617086044356, -1.525220743881169, -1.3969542306749956, -1.2747580194089525, -1.1603283603275736, -1.0551276383042438, -0.9603560950304733, -0.8769301569433451, -0.8054678223455918, -0.7462813859434975, -0.6993775978217236, -0.664465171178853, -0.6409693734787206, -0.6280532634600333, -0.6246449759260271, -0.6294703113426046, -0.6410897615470357, -0.6579389993651907, -0.6783717811499222, -0.7007041590629702, -0.7232588755379221, -0.7444088162981283, -0.7626184303692627, -0.7764820848298255, -0.7847584070134751, -0.7863997753076752, -0.780576248793509, -0.7666933724410679, -0.7444034546838659, -0.7136100838797961, -0.6744658251284624, -0.6273632147320144, -0.5729193418223733, -0.5119544709906667, -0.4454653120089383, -0.3745936791018246, -0.3005913992828365, -0.22478242408095253, -0.14852316917588676, -0.0731621502835053, -6.675265429218629e-16], [0.0, 0.06793637126423578, 0.13096237033671515, 0.1882366168663395, 0.23911314369534634, 0.2831613298758887, 0.32017983673917577, 0.3502041565542405, 0.3735075496051876, 0.39059531778545814, 0.40219253668826566, 0.4092255392534018, 0.41279760796855813, 0.4141594852504767, 0.41467544906045317, 0.41578581953073107, 0.4189668593502342, 0.425689103379739, 0.43737519954380866, 0.45535836223937504, 0.48084253075416017, 0.5148652886479286, 0.558264536559013, 0.6116498219781159, 0.6753791173415766, 0.7495417050846361, 0.8339476783284339, 0.9281244023576459, 1.0313201090304862, 1.142514618047084, 1.2604370000231004, 1.3835898210391393, 1.5102794411470326, 1.6386516844044288, 1.7667320592760143, 1.8924695891871728, 2.0137832166666514, 2.1286096733353683, 2.23495166383637, 2.330925195838364, 2.414804900968755, 2.4850662327190953, 2.5404234960899754, 2.579862758394192, 2.6026688089642263, 2.608445474671292, 2.5971287547980717, 2.5689924091186085, 2.5246458128859266, 2.465024077428393, 2.391370620693541, 2.3052125538141945, 2.2083294231572332, 2.102716008099829, 1.9905400190158065, 1.8740956641012152, 1.755754154668155, 1.637912293898919, 1.522940341914146, 1.4131303691777322, 1.3106463002480453, 1.2174768109148244, 1.13539217476829, 1.0659060618520306, 1.0102431745214977, 0.9693134668233929, 0.9436935370065717, 0.9336156119882992, 0.9389643618903661, 0.9592815965282648, 0.993778708516837, 1.0413565440021448, 1.100632206405672, 1.169972135236545, 1.2475306549482077, 1.331293061543136, 1.4191222102284191, 1.5088074883968767, 1.5981150064278262, 1.6848378154717492, 1.7668449670068456, 1.8421282633235059, 1.9088456102894578, 1.9653599721758812, 2.010273040742106, 2.042452864357014, 2.0610548343360464, 2.06553559111868, 2.0556595882887616, 2.0314982333990854, 1.9934217066237003, 1.9420837369309079, 1.8783997863450332, 1.8035192517469967, 1.7187924366603433, 1.6257331690914185, 1.5259780427389773, 1.4212433353216578, 1.3132807075752502, 1.2038328084957977, 1.0945899061937328, 0.9871486295265628, 0.8829738444389333, 0.7833646022770142, 0.6894249875081866, 0.602040562090849, 0.5218609565291294, 0.4492889971597344, 0.38447658952491237, 0.32732740308127034, 0.2775062273904498, 0.23445469875044955, 0.19741293326766315, 0.16544645173824446, 0.137477647187304, 0.11232093088019852, 0.08872059995283044, 0.06539040182292619, 0.041053728934290504, 0.01448336317837946, -0.015460297130997162, -0.049793553945355215, -0.08937722881274578, -0.13488885198795184, -0.1867999743345024, -0.24535922152753314, -0.3105815605659367, -0.38224408689349904, -0.45988847060923, -0.5428300266208759, -0.6301732005652539, -0.7208330942751854, -0.8135624957846967, -0.906983733371674, -0.9996245446503601, -1.089957043531254, -1.1764387827435812, -1.2575548497694395, -1.3318599010415155, -1.3980190340079475, -1.454846419373775, -1.5013406659926447, -1.5367159673193875, -1.5604281791978754, -1.5721951015873503, -1.5720103786078998, -1.5601505885150775, -1.5371752640045415, -1.5039197594119154, -1.4614810605302788, -1.4111968104515098, -1.3546179966100018, -1.293475905765124, -1.229644100945813, -1.1650963036836561, -1.1018611729073458, -1.041975055906996, -0.9874338446387877, -0.9401451008080479, -0.9018816148058539, -0.8742375365474868, -0.858588161147102, -0.8560543704332986, -0.8674726245016118, -0.8933712683672095, -0.9339537704342998, -0.9890893455280767, -1.0583112396213674, -1.1408227704065137, -1.2355110319760778, -1.3409679876256595, -1.455518496685718, -1.5772546536905991, -1.704075665212349, -1.833732355081012, -1.9638752757928395, -2.092105315453398, -2.2160256277996306, -2.3332936792244396, -2.441672202134161, -2.5390778685342132, -2.6236265508813204, -2.6936741176794796, -2.747851817081782, -2.7850954303210234, -2.804667525000021, -2.8061723025201393, -2.7895627102127687, -2.755139672770788, -2.703543484873973, -2.6357375929062536, -2.552985173850132, -2.456819089437657, -2.349005949314831, -2.2315051545688664, -2.106423909154793, -1.9759692787480772, -1.8423984421481814, -1.70796831802116, -1.574885758641668, -1.4452594822290565, -1.3210548670326823, -1.2040526547691, -1.095812510274106, -0.9976422608467941, -0.910573495826009, -0.8353440480215985, -0.7723877076803533, -0.7218313409445046, -0.683499402687444, -0.6569256526873558, -0.6413717087878629, -0.6358519053087963, -0.6391637735680837, -0.6499233276594594, -0.6666042258555119, -0.6875797888991213, -0.7111667931423928, -0.735669920478127, -0.7594257390896872, -0.7808451093250202, -0.7984529568800092, -0.8109244296702216, -0.8171165533377561, -0.8160946207377835, -0.8071526898919119, -0.7898277192356251, -0.7639070346032477, -0.7294289950895377, -0.6866769003357925, -0.6361663554820612, -0.5786264776284863, -0.514975484939146, -0.4462913525472729, -0.3737783445908916, -0.29873033588525666, -0.22249191731641652, -0.14641833400858875, -0.07183533331270764, -6.527898018164609e-16], [0.0, 0.06597372326274838, 0.12667711981423446, 0.18137031800976394, 0.229519197940385, 0.2708119651168428, 0.30516951713781093, 0.33274930838195904, 0.35394258723006, 0.3693650532381307, 0.3798411536598031, 0.3863824053906192, 0.3901602855437034, 0.39247437746648967, 0.3947165854097694, 0.3983323370297576, 0.40477977571764584, 0.4154880022643076, 0.43181545606838595, 0.4550095291432037, 0.4861684814241204, 0.5262066738729869, 0.5758240578546591, 0.6354807571111771, 0.7053774548793607, 0.7854421563311227, 0.87532373907791, 0.9743925358709369, 1.0817480180343246, 1.1962334699597288, 1.3164573686141627, 1.4408210118776783, 1.5675517798988616, 1.69474126854668, 1.82038740710772, 1.9424395668457728, 2.058845585599049, 2.1675995783405058, 2.266789376025309, 2.35464243587085, 2.429569095531449, 2.490202100809135, 2.5354314202609194, 2.564433468340087, 2.576693988952326, 2.5720240003779615, 2.550568366799657, 2.5128067371898624, 2.459546774779375, 2.3919097852948714, 2.311309035097694, 2.2194212267999487, 2.118151765551897, 2.0095945999215847, 1.895987553419172, 1.7796641730020695, 1.6630032066128002, 1.54837688082983, 1.4380991805844083, 1.3343753348356044, 1.2392536850305618, 1.1545810577477293, 1.0819626804623483, 1.0227275718826538, 0.9779002083923299, 0.9481791189586011, 0.9339228960563603, 0.9351439337289531, 0.9515100201511698, 0.9823537254523388, 1.0266893406374642, 1.0832369447080374, 1.1504530088725011, 1.2265667931288522, 1.3096216552162014, 1.3975202782328204, 1.4880727338369524, 1.5790462350149652, 1.6682153973992622, 1.7534118218378085, 1.832571833443875, 1.9037812630665931, 1.965316234706079, 2.0156790248792564, 2.053628184742366, 2.0782022597681076, 2.0887366013667354, 2.084872936061849, 2.066561536434849, 2.034056019615929, 1.987900979139251, 1.9289128300585636, 1.8581544110572392, 1.7769040368671143, 1.6866198259793748, 1.588900239186562, 1.4854418512668195, 1.3779954390361808, 1.2683215026253034, 1.1581463424386964, 1.0491197917818347, 0.9427756552479737, 0.8404958269781008, 0.7434789628277115, 0.6527144588739511, 0.5689623486898437, 0.49273957696590903, 0.4243129413053769, 0.36369882155524025, 0.3106696412194586, 0.26476683274319024, 0.2253199121088421, 0.19147111243029252, 0.16220488498282495, 0.1363814529058557, 0.11277350074826682, 0.09010500464228588, 0.0670911551432824, 0.042478298964892316, 0.015082827597657632, -0.016172029943419004, -0.05222249700211653, -0.0938345272562857, -0.14157887171550043, -0.19581161056430663, -0.25666068316594226, -0.32401879324536953, -0.39754290014899724, -0.47666033534264407, -0.5605814103138942, -0.648318212179294, -0.738709120874256, -0.8304484309542394, -0.9221203256020062, -1.0122363338764422, -1.0992753075413184, -1.1817248834195726, -1.2581233529642677, -1.3271008438018188, -1.3874187288819178, -1.4380062173603538, -1.4779931465508145, -1.5067380846430305, -1.5238509671976206, -1.5292096239134352, -1.5229697025314104, -1.5055676602710062, -1.4777166658353906, -1.4403954324770787, -1.3948301804652354, -1.3424701010968583, -1.2849568597965348, -1.2240888287006941, -1.161780875574545, -1.1000206525121512, -1.0408224216589848, -0.9861795237658391, -0.93801663694963, -0.8981429864803584, -0.868207651310098, -0.849658069689751, -0.8437027755634673, -0.851279301146137, -0.8730280614700117, -0.9092728966067307, -0.9600087901152494, -1.0248971118465071, -1.1032685536973725, -1.1941337426270466, -1.296201330729154, -1.4079031819068826, -1.5274261031414538, -1.6527494096848572, -1.7816874716425772, -1.911936267830084, -2.0411228744843775, -2.1668567438150332, -2.2867815822888495, -2.398626622083307, -2.5002560917441707, -2.589715733454217, -2.6652752834742626, -2.7254659275824373, -2.7691118624024518, -2.7953552334835337, -2.8036738784678215, -2.793891474823011, -2.7661798722617754, -2.72105357571773, -2.6593565310796587, -2.5822415482696495, -2.491142870254284, -2.387742557978007, -2.2739315060937, -2.1517660292352128, -2.023421060423004, -1.8911410795782566, -1.7571899392310462, -1.6238007752054593, -1.4931271819085605, -1.3671967951099921, -1.2478683607457246, -1.1367932779615268, -1.035382490613141, -0.9447794666229363, -0.8658398523271126, -0.7991182230258654, -0.7448621754929218, -0.7030138275586587, -0.6732186085198024, -0.6548410465226883, -0.6469870895886892, -0.6485323397603211, -0.658155438792062, -0.6743757223294182, -0.6955941605585798, -0.7201365292463704, -0.7462977076818211, -0.7723859803654991, -0.7967662277668658, -0.8179009277786611, -0.8343879526419861, -0.8449942344322028, -0.8486844833934795, -0.8446442746334297, -0.8322969665871225, -0.8113140754708794, -0.7816188995929862, -0.7433833615791883, -0.6970182109081722, -0.6431568992411016, -0.582633602589264, -0.5164560133338723, -0.4457736577530843, -0.37184260769917926, -0.29598754557735574, -0.21956220754846545, -0.1439092692776629, -0.07032075061075932, -6.364666640263568e-16], [0.0, 0.06387805274994085, 0.12217425017477022, 0.1742554218947384, 0.21970261951743478, 0.2583242180759695, 0.29016265584775447, 0.31549461479009755, 0.33482461497884275, 0.3488721684975212, 0.3585528068304303, 0.3649534566813023, 0.3693027881788047, 0.37293729284414, 0.37726396307707866, 0.38372053733249084, 0.39373434322644474, 0.4086808127548513, 0.42984275850817394, 0.4583714867853701, 0.4952507831058659, 0.5412647387356523, 0.5969702950940659, 0.6626752685295496, 0.7384224837549358, 0.8239804935268727, 0.9188411986710078, 1.0222245103530703, 1.1330900198611584, 1.25015546450174, 1.3719216059368504, 1.4967029737192348, 1.622663776024959, 1.7478581454392261, 1.8702737735157706, 1.9878778966090536, 2.09866452951446, 2.200701804466414, 2.2921782620940108, 2.371446958382286, 2.4370662971959467, 2.4878365704575276, 2.522831285929244, 2.5414224833937507, 2.543299380957609, 2.5284798508054074, 2.4973143941871094, 2.4504824645778864, 2.388981171437971, 2.314106580335981, 2.2274280038948233, 2.130755847694559, 2.0261037317564115, 1.9156457476898858, 1.801669830577518, 1.6865283202640782, 1.5725868565451884, 1.46217279508, 1.3575243446216707, 1.2607416110056282, 1.1737406896043472, 1.0982118766944766, 1.0355829731080004, 0.9869885330063036, 0.9532457695520653, 0.9348376710886624, 0.9319037100186982, 0.9442383460741498, 0.9712973404835057, 1.0122117121717398, 1.0658089860849267, 1.1306412114115973, 1.2050190680594681, 1.2870512371010316, 1.3746880884722203, 1.4657686399431165, 1.5580696676556316, 1.649355802087488, 1.7374294252305658, 1.8201791954424502, 1.8956260655144719, 1.9619657259717243, 2.0176064977830275, 2.061201814185744, 2.0916765673247575, 2.108246748472189, 2.1104319769254833, 2.0980606881484345, 2.0712679319779626, 2.030485912315167, 1.9764275762003336, 1.9100637281972743, 1.8325943014610107, 1.745414555933203, 1.6500770934151465, 1.5482506759198562, 1.44167690538229, 1.3321258678155352, 1.221351862312478, 1.11105032456986, 1.0028170162163144, 0.8981104862073486, 0.7982187206197151, 0.7042307846638276, 0.6170141285233924, 0.5371980801004174, 0.4651638866660131, 0.4010414978748478, 0.3447131088802144, 0.29582330877024676, 0.2537955106053148, 0.2178541792206917, 0.18705222568890487, 0.16030280660577864, 0.13641465544604175, 0.11412998489957424, 0.0921639355482531, 0.06924450905059479, 0.04415191407724852, 0.015756270807912556, -0.016947335609743208, -0.05480739177555624, -0.09848892752803656, -0.1484516506120303, -0.20493383801035234, -0.26794242722468914, -0.33724958910966973, -0.4123958948034713, -0.4927000171459966, -0.5772747360990597, -0.6650488524203108, -0.7547944583934859, -0.8451588727386199, -0.9347004225303788, -1.0219271512207009, -1.1053374513597145, -1.1834615654219696, -1.2549028697251952, -1.318377855557734, -1.3727537483989465, -1.4170827599213476, -1.4506320470214737, -1.4729085555076777, -1.483678050745809, -1.4829777804582351, -1.4711223724556954, -1.4487027384481121, -1.4165779300449124, -1.3758600702585169, -1.327892658842608, -1.2742227182490868, -1.2165674046490826, -1.1567758513659805, -1.0967871366045863, -1.0385853703686927, -0.9841529743080919, -0.9354232808855465, -0.894233603312116, -0.8622799244522666, -0.8410743213362067, -0.8319061827237163, -0.8358081917147445, -0.8535279357221882, -0.8855058748393055, -0.9318602499145462, -0.9923793471172606, -1.0665213604380366, -1.1534219116896243, -1.2519091035999168, -1.3605258000164508, -1.477558652520878, -1.6010732291668837, -1.7289544526250626, -1.858951425394106, -1.9887256121131132, -2.1159012660434287, -2.2381169305343995, -2.3530768181498605, -2.4586008708238007, -2.552672333944864, -2.6334817349405255, -2.6994662413571726, -2.7493434825681633, -2.782139050440174, -2.797207044360881, -2.7942431913268604, -2.7732902482880317, -2.7347355773475432, -2.679300970261237, -2.608024982447624, -2.522238213940902, -2.423532141091951, -2.3137222543113984, -2.1948063900885106, -2.0689192567020416, -1.9382842397935673, -1.8051636342318844, -1.671808481042364, -1.5404091918793243, -1.4130481185576411, -1.2916551722112644, -1.1779675170770223, -1.073494259730163, -0.9794869284432558, -0.896916392357427, -0.8264567099581891, -0.7684762249178294, -0.7230360489519708, -0.6898958903523152, -0.6685270077678418, -0.6581318960224725, -0.6576701485232714, -0.6658897931030134, -0.6813632685596415, -0.702527100850049, -0.727724253479563, -0.7552480681148639, -0.7833866802027473, -0.8104667910846491, -0.8348957027448907, -0.855200573211586, -0.8700639283576752, -0.8783545674000204, -0.8791531221494838, -0.8717716708846945, -0.8557669630202629, -0.8309469765762096, -0.7973707026319068, -0.7553412251164214, -0.7053923360573651, -0.648269091458071, -0.5849028671504817, -0.5163816134088497, -0.4439161283133607, -0.36880326979159417, -0.2923871024459922, -0.2160190258035719, -0.14101795425385635, -0.06863161510404266, -6.186988061787385e-16], [0.0, 0.061667331324419525, 0.11749209345274958, 0.16695200382500683, 0.2097455437214804, 0.24580150683657256, 0.2752820880051335, 0.29857941231706314, 0.31630557619568367, 0.32927644174514464, 0.33848958948217395, 0.3450969882943389, 0.3503730811976873, 0.3556791076371843, 0.3624245845580267, 0.3720269466660644, 0.3858703991652502, 0.4052650624173892, 0.43140748669196805, 0.46534358642721396, 0.507934987863238, 0.5598297028637196, 0.6214379371853566, 0.6929137159486776, 0.7741428657040379, 0.8647377348203051, 0.9640388658636742, 1.0711236593613653, 1.184821892204877, 1.3037377803416301, 1.4262781086801801, 1.5506857954791944, 1.6750781178239473, 1.7974887026722963, 1.9159122874773988, 2.028351178138757, 2.1328622819723684, 2.227603570855274, 2.3108788353401724, 2.3811796243059486, 2.437223325866973, 2.477986432385669, 2.502732143451826, 2.5110315929462597, 2.502778136603875, 2.4781943011885654, 2.4378311714841616, 2.3825601725230197, 2.3135573873893387, 2.232280731071501, 2.140440473781095, 2.039963768660746, 1.9329539848981716, 1.8216457743530796, 1.7083569047518132, 1.5954379727169021, 1.485221163384046, 1.3799692487799036, 1.281826013839914, 1.1927692669885737, 1.1145675323400952, 1.048741434243652, 0.9965306741819216, 0.958867367619135, 0.9363563575018609, 0.9292629554109568, 0.937508384877797, 0.9606730184060712, 0.998007314733775, 1.0484501803279243, 1.1106543034637364, 1.1830178447652955, 1.2637217187641738, 1.3507715704795014, 1.4420434423876372, 1.5353320430413129, 1.628400471022147, 1.719030218218411, 1.805070275278002, 1.8844841894587492, 1.9553939802486733, 2.0161198996405103, 2.0652151297549977, 2.10149463795984, 2.124057555541637, 2.132302606724318, 2.12593628639918, 2.104973663089429, 2.0697318640131552, 2.02081647718582, 1.9591012769348075, 1.8857018397768364, 1.8019437634041906, 1.7093263289830085, 1.6094825529936598, 1.5041366568855674, 1.3950600389233947, 1.2840268614637689, 1.172770367896896, 1.0629410166851283, 0.9560674660923448, 0.8535213637566375, 0.7564867922825819, 0.6659350981689441, 0.5826056898093374, 0.5069932346101464, 0.43934151940995947, 0.37964406655319727, 0.32765142450457657, 0.2828848811605548, 0.24465618431365377, 0.21209270116651047, 0.1841673112003239, 0.15973220752144104, 0.13755568401751378, 0.11636091168733659, 0.09486565920084226, 0.07182189128517184, 0.046054184430232514, 0.016495932484568807, -0.017777625892623893, -0.05752044176955409, -0.10329152948397505, -0.15543632944551633, -0.21407406699106332, -0.2790914575587643, -0.3501429428258574, -0.42665747194317966, -0.5078516709209605, -0.5927490759185775, -0.6802049469155528, -0.7689360310428858, -0.8575545134832967, -0.944605281661506, -1.0286055383173922, -1.1080857333106382, -1.1816307443594054, -1.247920224428395, -1.3057670485330737, -1.3541528350052194, -1.3922595847749226, -1.419496575310202, -1.4355217612424809, -1.44025706855641, -1.4338971202044044, -1.416911094378205, -1.390037588371953, -1.3542725367274768, -1.3108504077752934, -1.261219073386077, -1.2070089084462092, -1.1499968252017798, -1.0920660794282078, -1.0351627970378539, -0.9812502583893459, -0.9322620409289053, -0.8900551572170702, -0.8563643338805231, -0.8327585572745295, -0.8206009640426736, -0.8210130804028597, -0.8348443146220257, -0.8626474851386013, -0.9046610250875083, -0.9607983460055897, -1.030644673081942, -1.1134614856178588, -1.2081985137362303, -1.313513060296478, -1.4277962398877158, -1.549205559033901, -1.6757031074705402, -1.8050984933383007, -1.9350955387613573, -2.0633416594106198, -2.187478784595288, -2.3051946348488848, -2.4142731628759218, -2.5126429814023488, -2.598422647522151, -2.6699617464538097, -2.7258768164454414, -2.7650812785028616, -2.78680867670065, -2.7906286936196243, -2.7764555770726913, -2.7445487945596807, -2.6955059164438344, -2.630247913179027, -2.549997231555338, -2.4562491855075166, -2.3507373544065415, -2.235393822116754, -2.1123052100577695, -1.9836655541725958, -1.8517271467571537, -1.7187505078679761, -1.586954666482027, -1.458468918419888, -1.3352871866477072, -1.2192260410246494, -1.1118873406058691, -1.0146263446138455, -0.9285260010822975, -0.8543779683755583, -0.7926707581157416, -0.7435852126428618, -0.7069973503285498, -0.682488432301212, -0.6693619288475814, -0.6666668972403644, -0.6732271290857049, -0.687675288241182, -0.7084911432591021, -0.734042903992843, -0.7626306027266383, -0.7925304175851748, -0.8220388210163744, -0.8495154490970712, -0.8734236278697552, -0.8923675597788272, -0.9051252647802507, -0.9106764844826973, -0.908224890823075, -0.8972140898896794, -0.8773370727946914, -0.8485389348795841, -0.8110128577330447, -0.7651895211435664, -0.7117202798525161, -0.6514545986016795, -0.585412384501722, -0.5147519845380504, -0.4407347248573438, -0.3646869546261873, -0.28796061858074506, -0.21189341737723386, -0.1377696226555125, -0.06678259417549719, -5.996396084766768e-16], [0.0, 0.05936038531830097, 0.11267019497508252, 0.15952118374138133, 0.19973044215790675, 0.23334634441410443, 0.2606479949017704, 0.2821381715899171, 0.29852993441522124, 0.31072723283719234, 0.3198000043529358, 0.32695440109321255, 0.33349891092667144, 0.3408072494799164, 0.3502789873178199, 0.36329893995558293, 0.38119638573713327, 0.4052051869123596, 0.4364258721561195, 0.47579069466024476, 0.5240326098403876, 0.5816590223308484, 0.648931035602879, 0.7258488021009609, 0.8121434205968936, 0.9072756642641664, 1.0104416518340125, 1.12058539937603, 1.2364180161175895, 1.3564431386372588, 1.4789880379814935, 1.6022396877823475, 1.724284951995505, 1.843153941716399, 1.9568655044535705, 2.0634737484617984, 2.1611144708581485, 2.2480503521935207, 2.322713802173816, 2.3837463908666856, 2.4300338758551843, 2.4607359366138293, 2.475309850476613, 2.47352748697593, 2.455485155608546, 2.4216060123840286, 2.3726349086826106, 2.3096257476422664, 2.2339215940631028, 2.147127959230666, 2.0510798478128516, 1.9478033060029105, 1.839472344620735, 1.7283622246273576, 1.6168001826413239, 1.5071147383341175, 1.4015847624207254, 1.3023894924181196, 1.2115606631805933, 1.1309378709002993, 1.062128213936963, 1.0064711533280817, 0.9650094125627106, 0.9384665931686647, 0.927232023339597, 0.9313531850885154, 0.9505358854352756, 0.9841521532954809, 1.0312556605083198, 1.0906042872755282, 1.1606892835108562, 1.2397703223143257, 1.325915603749834, 1.4170460496542863, 1.5109825361696554, 1.6054950423175682, 1.698352551848888, 1.7873725327464376, 1.870468834392127, 1.9456968860849801, 2.0112951511809047, 2.0657218868263785, 2.107686377669787, 2.136173950095578, 2.150464227996207, 2.1501422580393754, 2.13510230766736, 2.1055443183488505, 2.0619631754691117, 2.005131130289011, 1.9360738743535477, 1.8560409185463964, 1.7664710639630186, 1.6689538666307044, 1.5651880900649762, 1.4569382065178083, 1.34599004797102, 1.2341067205512473, 1.1229858808711664, 1.0142194303070802, 0.9092566145566914, 0.80937142278279, 0.715635065642673, 0.6288941774759176, 0.5497552382896985, 0.4785755497397261, 0.41546093014154156, 0.3602701209326628, 0.3126257252909041, 0.2719313331172075, 0.2373943294946028, 0.20805373997715798, 0.18281233924283172, 0.16047214293008555, 0.13977231852909147, 0.11942849209810928, 0.09817239478092814, 0.07479078740572012, 0.048162622960463745, 0.017293454891278023, -0.01865382728656648, -0.06033275652255869, -0.10819224428013022, -0.16246130135337639, -0.22313994001250242, -0.28999651260019355, -0.3625715736104507, -0.44018818180429237, -0.5219683903797474, -0.6068555108968342, -0.6936415846878193, -0.78099935772723, -0.8675179349088952, -0.9517411904493686, -1.0322079352592377, -1.1074927915622181, -1.1762467011286015, -1.2372359968883986, -1.2893789983790285, -1.3317791487554724, -1.3637537935719293, -1.3848578072225717, -1.3949013992089843, -1.3939615761659667, -1.382386893264274, -1.3607952963012735, -1.3300650293128822, -1.2913187575623308, -1.2459012279056967, -1.1953509534863556, -1.1413665633243186, -1.0857685957706875, -1.0304576344889114, -0.9773697835597918, -0.9284305519746581, -0.8855082652687227, -0.8503681420857986, -0.824628165467864, -0.8097178427320697, -0.8068408847308962, -0.8169427465581244, -0.8406838594725138, -0.8784192506574579, -0.9301850966343946, -0.9956925913582152, -1.074329335254486, -1.1651682709745736, -1.2669840098575185, -1.378276214449032, -1.4972995313190205, -1.6220994090438063, -1.750552992497574, -1.880414160072376, -2.0093616681916417, -2.135049290030463, -2.2551567846340532, -2.3674405099049323, -2.46978249879834, -2.5602368524095276, -2.6370723656467008, -2.6988103893691537, -2.744257045102149, -2.7725290419976174, -2.783072497350225, -2.7756743280165233, -2.7504659564822664, -2.707919257789121, -2.648834857628254, -2.5743230731582067, -2.485777962103212, -2.3848451082113424, -2.2733839182586295, -2.1534253339163127, -2.0271259678617395, -1.8967197549615284, -1.7644682642470713, -1.632610844449684, -1.5033157744619017, -1.3786335603390019, -1.260453463142141, -1.1504642585187907, -1.0501201215233804, -0.9606124014932917, -0.8828479050236816, -0.817434143878427, -0.7646718330326236, -0.7245547462115914, -0.6967768566633753, -0.6807465139024853, -0.67560723714396, -0.6802645472780909, -0.6934181154022065, -0.7135983806304266, -0.739206686182104, -0.7685579030997601, -0.7999244572603165, -0.8315806488626739, -0.8618461548655177, -0.889127633784813, -0.9119574080266207, -0.9290282800477269, -0.939223642994773, -0.9416421713893774, -0.9356165197101649, -0.9207256127555712, -0.8968002774985988, -0.8639221375752106, -0.8224158642575445, -0.772835047403245, -0.7159421121794394, -0.6526828582606136, -0.5841563339137121, -0.5115808745169641, -0.43625723068849553, -0.3595297829479094, -0.28274688592305475, -0.20722140441620412, -0.13419249570529662, -0.06478965750891787, -5.79452587754639e-16], [0.0, 0.056976707100053196, 0.10774892120798521, 0.15202452615257733, 0.18973932086384462, 0.22105935168650892, 0.24637675847872986, 0.2662992295819439, 0.2816333280470239, 0.2933621122860964, 0.30261762450089097, 0.3106489559944565, 0.31878671634068484, 0.3284048303498663, 0.3408806603360942, 0.35755449945729945, 0.3796895035887767, 0.40843312370054974, 0.4447810681144459, 0.48954476507605116, 0.543323212210405, 0.6064799926869937, 0.679126110925549, 0.7611091565682004, 0.852009147799298, 0.9511412378316568, 1.0575652956655643, 1.1701021983785067, 1.2873565015704445, 1.4077449914525315, 1.5295304705293877, 1.6508599927098884, 1.7698066464364313, 1.884413889033769, 1.9927413643944725, 2.092911091189463, 2.1831528912235916, 2.2618479378766088, 2.327569342617022, 2.379118762500895, 2.4155581018526133, 2.436235494822225, 2.440804889497799, 2.4292387054830296, 2.4018332016592967, 2.3592063652246575, 2.302288312783163, 2.2323043748515463, 2.150751212231241, 2.0593664819157382, 1.9600927274063547, 1.8550363096230764, 1.7464223165352852, 1.6365464891854544, 1.527725276468735, 1.4222451790012614, 1.3223125624522913, 1.2300051123055753, 1.1472260653265571, 1.0756622889098801, 1.0167471895043647, 0.9716293176323831, 0.9411474023913, 0.9258123960135294, 0.9257969427695892, 0.940932510268221, 0.9707142393251527, 1.014313385460818, 1.070597045199368, 1.1381546880479043, 1.2153308545189343, 1.3002632357125243, 1.3909252243025254, 1.4851719233060237, 1.5807885202421927, 1.6755398820833722, 1.7672202019915728, 1.853701532758199, 1.9329800739686769, 2.0032191393501257, 2.0627878160129502, 2.110294436218159, 2.144614112165027, 2.164909731862409, 2.1706459757553533, 2.1615960854224587, 2.137841293094696, 2.0997629995955, 2.048027964161216, 1.983566938150243, 1.9075473317581544, 1.8213406446863383, 1.7264855148115368, 1.6246473402928145, 1.5175755077951818, 1.407059310774162, 1.2948836658700467, 1.1827857318991188, 1.072413504884681, 0.9652874049093163, 0.8627657878183002, 0.7660152091102255, 0.6759861414303152, 0.5933947041484382, 0.5187108071894115, 0.45215294554695473, 0.39368970994088076, 0.34304790717955885, 0.2997270152911735, 0.2630195376197683, 0.23203667087946828, 0.2057385683571543, 0.182968364393116, 0.16248903281832708, 0.14302208250689097, 0.123287049329668, 0.1020407266402155, 0.07811508638384188, 0.05045287970925016, 0.018139968619153617, -0.019566472890051836, -0.06321464080044648, -0.11314029054895909, -0.16945491419253317, -0.23204022890263773, -0.3005491355233003, -0.37441313684316774, -0.45285603626262017, -0.5349135729718655, -0.6194584937764387, -0.7052304182804757, -0.7908697269196627, -0.874954593574375, -0.9560401989518629, -1.0326990998105965, -1.103561694004745, -1.1673557131939716, -1.2229436941588991, -1.2693574255673035, -1.305828438657727, -1.3318137059059312, -1.347015828970655, -1.3513971331870165, -1.345187237221986, -1.32888382946804, -1.3032465532717321, -1.2692840769188285, -1.2282345970810415, -1.1815401918412929, -1.1308155972501375, -1.0778121256495223, -1.0243775710847074, -0.9724130537839528, -0.9238278391926206, -0.8804932252471166, -0.8441966229321829, -0.8165969588127103, -0.79918250398473, -0.7932321822564379, -0.7997813325359379, -0.8195927982057674, -0.853134092149767, -0.9005612430569307, -0.9617097701247853, -1.0360930631752008, -1.1229082676259452, -1.2210495930710223, -1.3291287848353779, -1.445502324184932, -1.568304759156736, -1.6954874182546478, -1.824861627222712, -1.9541454380216312, -2.0810127917438046, -2.203143975680312, -2.3182762006395055, -2.4242531187791196, -2.5190721248292327, -2.6009283341305847, -2.6682542081863123, -2.7197539005641014, -2.7544315205193484, -2.771612655618593, -2.770958654431036, -2.7524733421411685, -2.7165020215395477, -2.6637227949037965, -2.59513042433638, -2.512013124754387, -2.4159228506389705, -2.3086397907987584, -2.192131921072036, -2.0685105798084664, -1.9399831223650843, -1.8088037765348184, -1.6772238592439688, -1.5474425251226587, -1.4215591994757595, -1.3015288022641192, -1.1891207971319122, -1.0858830021239367, -0.9931109789709759, -0.9118236786730406, -0.8427458660409236, -0.7862976787131244, -0.7425915010850581, -0.7114361548946361, -0.6923482303069716, -0.6845702086067558, -0.687094864278103, -0.6986952843249188, -0.7179597098165682, -0.7433302920597105, -0.7731447662139019, -0.8056799807260252, -0.839196183168479, -0.8719809527748238, -0.9023916873360068, -0.9288955966240399, -0.9501062249476194, -0.9648156199729029, -0.9720213811225178, -0.9709479557233993, -0.9610617011749917, -0.9420793929465832, -0.9139700271005193, -0.8769499380151318, -0.8314714227170813, -0.7782052284350139, -0.7180174155098011, -0.6519412497440679, -0.581144903095907, -0.5068958462035664, -0.43052289796710963, -0.35337695428452626, -0.27679144864584915, -0.20204360089349938, -0.13031748700477594, -0.06266991286827321, -5.58309738979578e-16], [0.0, 0.05453626092757085, 0.10276906190569345, 0.14452343946316942, 0.17985292821744714, 0.20903829556106054, 0.23257986114071644, 0.2511835913159973, 0.26574132191871247, 0.2773056169120258, 0.28705991204617803, 0.29628471771978687, 0.3063207607870083, 0.31853002829608146, 0.3342557349570016, 0.35478226898071885, 0.3812961769261749, 0.41484922712549704, 0.45632454360249447, 0.5064067292947488, 0.5655568006155363, 0.6339926373261628, 0.7116755152480343, 0.7983031379090962, 0.8933094205555071, 0.9958711101197362, 1.1049211519616806, 1.2191685428133623, 1.3371242436582464, 1.4571325704288747, 1.5774073383401233, 1.6960719109843814, 1.8112022011686078, 1.9208715895370532, 2.0231966713911276, 2.1163827132594353, 2.1987676994943364, 2.2688638756018635, 2.3253957485878374, 2.3673335840889695, 2.3939215435736574, 2.4046997299643516, 2.3995195536348914, 2.37855198939095, 2.3422884648897107, 2.2915342978524724, 2.2273947790454867, 2.1512541759496333, 2.0647481039413194, 1.969729873439993, 1.868231568861823, 1.7624207447193256, 1.6545537326216628, 1.5469266375725668, 1.441825160725205, 1.3414744171611404, 1.2479899205089346, 1.163330881191473, 1.089256912367448, 1.027289158468361, 0.9786767575332332, 0.9443694228159676, 0.9249967844325379, 0.9208549716398174, 0.9319007445870652, 0.9577533052304538, 0.9977037349069177, 1.0507318252560098, 1.1155298941520333, 1.1905330133146736, 1.273954923308008, 1.363828778372182, 1.458051751180042, 1.5544324388785766, 1.6507399487865821, 1.744753506366754, 1.8343114203944388, 1.9173582607389827, 1.9919891522981796, 2.0564901631451464, 2.1093738639775133, 2.1494092570194883, 2.1756454125990663, 2.187428307224664, 2.1844105242608545, 2.166553653115288, 2.1341234008840817, 2.087677607276436, 2.0280475250040593, 1.956312889475771, 1.8737714496298292, 1.7819037624601197, 1.6823341640766296, 1.576788917328031, 1.4670525980252642, 1.3549238171896176, 1.2421713847201596, 1.1304920003298675, 1.0214705111172915, 0.9165437029696715, 0.8169684970194717, 0.7237953050728094, 0.6378471622956037, 0.5597051049321959, 0.4897000992567097, 0.4279116594034153, 0.37417312043874756, 0.3280833633347487, 0.2890246246444448, 0.25618586977275254, 0.2285910686347849, 0.20513158969692669, 0.18460182596565414, 0.1657370869699411, 0.1472527361414946, 0.12788352457178787, 0.10642207059409921, 0.081755460003466, 0.052898993311975145, 0.019026182905880384, -0.020505797636254958, -0.0661358900260422, -0.11808469439436829, -0.17634616894666624, -0.24068571504116304, -0.31064470967467944, -0.3855513787555157, -0.46453773852564695, -0.5465621732817683, -0.6304370691840748, -0.7148607902099052, -0.7984531666172281, -0.879793571590169, -0.9574605904791135, -1.0300722410677987, -1.0963256838122484, -1.1550353685490677, -1.2051685986326055, -1.245877554024185, -1.2765269000574397, -1.2967162163564148, -1.3062966080324212, -1.305381005672687, -1.2943478181744477, -1.2738377692510243, -1.2447439202818753, -1.2081950548006835, -1.1655327689903785, -1.1182827738361034, -1.068121064017026, -1.0168357424218208, -0.9662854039582955, -0.9183550751683168, -0.8749107746678383, -0.8377538018208425, -0.8085758761828693, -0.7889162376460955, -0.7801217771025913, -0.7833112007163998, -0.7993441391211727, -0.828795998224193, -0.871939213555962, -0.928731418516148, -0.998810872113551, -1.0814993178938719, -1.1758122669423172, -1.2804765185149483, -1.3939545563902083, -1.5144752917503987, -1.6400704684168026, -1.7686159073914893, -1.8978766483323402, -2.02555494875886, -2.1493400298601673, -2.2669584125488247, -2.3762236700193706, -2.475084433989106, -2.561669530789826, -2.6343291896224166, -2.691671356995719, -2.7325922664339166, -2.756300548166918, -2.762334316425675, -2.7505708384347365, -2.721228565181747, -2.6748614852684094, -2.612345945203258, -2.5348602579572863, -2.443857592132888, -2.341032792554452, -2.228283925633817, -2.107669466045359, -1.981362142091862, -1.8516005332307086, -1.7206395627466318, -1.5907010503426313, -1.463925482995906, -1.3423261280044, -1.2277465506328709, -1.1218225117193568, -1.0259491102127967, -0.9412539046387911, -0.8685765991937332, -0.8084557182276805, -0.7611225213024424, -0.7265022340420796, -0.7042224919911735, -0.6936287200409352, -0.6938060029620973, -0.7036068472861581, -0.7216840949937431, -0.7465281285995942, -0.7765074081910837, -0.809911306156849, -0.8449941565044653, -0.8800194139328202, -0.9133028236423285, -0.9432535359955483, -0.9684121596648435, -0.987484831250278, -0.9993724863340258, -1.0031946438110548, -0.9983071588645438, -0.984313556493614, -0.9610697230889349, -0.928681904008539, -0.8874981261380742, -0.8380933317269015, -0.7812486691746788, -0.7179255339095425, -0.6492350843602744, -0.5764040709905933, -0.5007379076220287, -0.42358198155992655, -0.3462822406973771, -0.27014611079277956, -0.19640478415747906, -0.12617788238916325, -0.06044143155310813, -5.363898026253221e-16], [0.0, 0.05205928536736493, 0.09777143066292875, 0.13707858084900412, 0.17014998068900433, 0.19737716208639763, 0.21936284190886415, 0.23690381290666068, 0.25096826793802995, 0.26266814422364826, 0.2732272060372154, 0.2839456977419146, 0.29616249149939433, 0.311215722934263, 0.33040295174606704, 0.3549419015689306, 0.3859328237957549, 0.4243234937940009, 0.4708777858000554, 0.5261486862962722, 0.5904564969700373, 0.6638728501100413, 0.7462110146887894, 0.8370228140058367, 0.9356023095437267, 1.040996234768132, 1.152020991261169, 1.2672858521079975, 1.3852218580696591, 1.5041157447853009, 1.622148107777022, 1.7374348997173257, 1.848071264129292, 1.9521766437485166, 2.0479400619080774, 2.1336644625941394, 2.2078090096686624, 2.2690282878925063, 2.3162074168549673, 2.3484921821175266, 2.365313403587624, 2.3664048965679423, 2.351814532799863, 2.321908073445139, 2.2773656193136493, 2.2191707015103357, 2.148592213684518, 2.0671595608522773, 1.9766315650555568, 1.8789598208508498, 1.7762473300183763, 1.6707033615785454, 1.5645955773041544, 1.4602005320834737, 1.3597537009895562, 1.265400199665568, 1.179147351245148, 1.1028202117806916, 1.0380210980242763, 0.9860940680281434, 0.9480951886564077, 0.924769287543385, 0.9165337336082953, 0.9234696236667355, 0.9453205770140747, 0.981499159365451, 1.0311007766097549, 1.0929247018690746, 1.1655017306503508, 1.2471278025282666, 1.3359027875986125, 1.4297735152827706, 1.5265800248584074, 1.624103943698545, 1.7201178523700724, 1.8124344765697828, 1.8989545547783582, 1.977712267218083, 2.046917175254983, 2.1049917091789343, 2.1506033540976963, 2.182690815702557, 2.2004835966219387, 2.203514576282091, 2.191625358628695, 2.164964328498558, 2.1239775345200855, 2.06939268981153, 2.0021967471839046, 1.923607658993298, 1.8350410694825743, 1.7380728060601753, 1.6343981326184982, 1.5257888003808147, 1.41404897817481, 1.3009711634018424, 1.188293166915969, 1.0776572298400822, 0.9705722689957837, 0.8683801617249474, 0.7722268726581073, 0.6830390972120581, 0.6015069525325565, 0.5280730898929169, 0.4629284371787512, 0.40601461020513785, 0.35703286150111724, 0.31545926913140854, 0.2805657102712569, 0.25144601855880044, 0.2270465943606107, 0.20620062623796168, 0.1876649928494095, 0.17015884947370377, 0.15240286388443117, 0.1331580534074163, 0.11126318892849638, 0.08566977200211692, 0.05547365698461437, 0.019942479585926622, -0.021461835889827828, -0.0690660888885032, -0.12297478806785261, -0.18306540706381252, -0.2489900437662339, -0.3201834488558045, -0.39587722267984804, -0.47511981788260915, -0.556801832663487, -0.6396859399945216, -0.7224406751415717, -0.8036772005425219, -0.8819880861480689, -0.9559870868135916, -1.0243488677189156, -1.0858476249114226, -1.139393571070128, -1.1840663059520178, -1.219144165521558, -1.2441287416600166, -1.2587638831940453, -1.2630486258336413, -1.257243650072165, -1.2418710284068362, -1.2177071923390845, -1.1857692212844086, -1.147294725461424, -1.1037157587748254, -1.0566273515317441, -1.0077513926547517, -0.9588967133363814, -0.9119163257082223, -0.8686628484679966, -0.8309432044892312, -0.8004737018229726, -0.7788366084424759, -0.7674393025125241, -0.7674770245003152, -0.7799001763677736, -0.8053870083165288, -0.8443224076079836, -0.8967833598925453, -0.9625314947497203, -1.0410129576288512, -1.1313656742268543, -1.2324338948545863, -1.3427897299030604, -1.4607612174573321, -1.5844663046036704, -1.7118519789644355, -1.8407376600556549, -1.9688618543357885, -2.0939309959249535, -2.21366933896498, -2.3258687388709784, -2.428437159037491, -2.5194447669606905, -2.597166538589738, -2.6601203707181313, -2.707099806421472, -2.7372006053994653, -2.7498405365136085, -2.744771930298505, -2.72208670086511, -2.6822137252366978, -2.6259086494197117, -2.554236370005265, -2.4685466134603495, -2.3704431982901406, -2.261747713978297, -2.1444584814382877, -2.020705769472467, -1.8927043277936964, -1.7627043574559256, -1.6329420726378088, -1.505591012868738, -1.382715241906709, -1.2662255191868481, -1.157839453345313, -1.0590465467111811, -0.9710789173664713, -0.8948883444467981, -0.831130126291496, -0.7801540737164253, -0.7420027862096632, -0.7164171815423362, -0.7028490735072375, -0.7004804225631835, -0.7082487242367401, -0.7248778541220473, -0.7489135597786435, -0.7787626818712887, -0.8127351021231236, -0.8490873560823484, -0.8860668157221738, -0.9219553412305924, -0.9551113230471151, -0.9840090836351778, -1.0072746823453034, -1.023717264099084, -1.0323552110011558, -1.0324364923402556, -1.023452759305216, -1.0051468922957667, -0.97751387687114, -0.9407950549144866, -0.8954659662094685, -0.8422181580949488, -0.7819354931133794, -0.7156656227909467, -0.6445874164324793, -0.5699752340758676, -0.4931610100415814, -0.415495165925375, -0.33830739813666183, -0.2628683845605351, -0.1903534276709308, -0.12180899817176807, -0.05812306537126562, -5.138764760463587e-16], [0.0, 0.0495660943227184, 0.0927964679716602, 0.1297492727456427, 0.16070641426653662, 0.1861652738116317, 0.20682431929389192, 0.22356297693420754, 0.23741628594286832, 0.24954499608842273, 0.26120188887659584, 0.2736952041045066, 0.28835013220678496, 0.3064693870425601, 0.3292939021704963, 0.3579646954564488, 0.39348692195649854, 0.436697083989976, 0.48823429139302643, 0.5485163659811353, 0.6177214646882592, 0.6957757586513981, 0.7823475540810156, 0.8768480788712552, 0.97843899060023, 1.0860464910596168, 1.198381764007858, 1.313967290693601, 1.4311684459282592, 1.548229639931469, 1.6633141513170984, 1.774546697483508, 1.8800577128628306, 1.9780282549390515, 2.066734434008311, 2.1445902660137337, 2.2101878784511184, 2.2623340566433976, 2.3000822002909826, 2.3227588661619745, 2.3299841995481585, 2.321685701616831, 2.2981049385266523, 2.2597969672807694, 2.20762242863129, 2.1427324346330323, 2.0665465533219316, 1.9807243611672267, 1.8871311912759068, 1.787798847933085, 1.6848821824183051, 1.5806125280647267, 1.4772490716642934, 1.377029291589608, 1.282119619057303, 1.19456747711909, 1.1162558222402423, 1.0488612563992596, 0.9938166948726895, 0.9522794682454528, 0.9251056092851275, 0.9128309292363632, 0.9156593273732909, 0.9334586061969619, 0.9657638866484258, 1.0117885374536666, 1.0704423546064297, 1.1403565553576869, 1.2199149900850432, 1.3072908289684144, 1.4004878520480795, 1.4973853640907544, 1.5957856723198136, 1.693463007473982, 1.7882127382076782, 1.8778997262321568, 1.9605046948329559, 2.034167535815842, 2.0972265581949627, 2.1482527840749177, 2.186078520641735, 2.2098195788952406, 2.2188906662124617, 2.213013647158131, 2.192218541022946, 2.1568373010844804, 2.107490595208738, 2.0450679758574344, 1.9707019857132388, 1.8857368891220365, 1.7916928458750345, 1.6902264494564578, 1.5830886342258113, 1.4720810131303013, 1.3590117381249116, 1.2456519788482705, 1.1336940912714628, 1.0247124976898594, 0.9201282239073915, 0.8211779407340208, 0.7288882375195397, 0.6440557184279077, 0.5672333609969563, 0.4987234150542302, 0.4385769523461642, 0.3866000075080001, 0.34236608352049525, 0.305234633767344, 0.27437498225582646, 0.2487950072542284, 0.22737379493181314, 0.20889737151116253, 0.1920965473882643, 0.17568585649101973, 0.15840255005296902, 0.13904460653992934, 0.11650674857612205, 0.08981351259864809, 0.05814849620260023, 0.020879009689384356, -0.022424520396890323, -0.07197491005599761, -0.12776070222443758, -0.18954497974406806, -0.2568705443476843, -0.3290713325624192, -0.4052897761082934, -0.48449965841123366, -0.565533874222118, -0.6471163697169211, -0.7278974291533613, -0.8064913840226559, -0.881515753977108, -0.9516307873621952, -1.0155783540298395, -1.0722191546918634, -1.1205672491510492, -1.1598209694175363, -1.1893893714315558, -1.2089134887143165, -1.2182817800489636, -1.2176393080583583, -1.2073903426948076, -1.1881942492704736, -1.1609546905976216, -1.1268023428204106, -1.087071490338647, -1.043271022679292, -0.997050501292911, -0.9501620933691278, -0.9044192795970831, -0.8616533305372341, -0.8236686096564475, -0.7921977984471756, -0.7688581493845846, -0.7551098554234207, -0.7522175806287695, -0.7612161263736202, -0.7828811129710136, -0.817705439897884, -0.8658821517227707, -0.9272941847660158, -1.0015113050979667, -1.087794375729572, -1.1851069139954526, -1.2921337235066652, -1.4073062129958231, -1.5288338511226103, -1.6547410558765079, -1.7829086833186631, -1.9111191663597353, -2.0371042629048297, -2.158594306286749, -2.273367811121872, -2.3793002755734096, -2.4744110368338967, -2.5569070800939784, -2.625222771323401, -2.6780545791742996, -2.7143899689366675, -2.733529788885913, -2.7351036232311303, -2.7190777524649254, -2.6857555371833715, -2.6357702211279, -2.5700703289309166, -2.489898009455123, -2.39676084244073, -2.2923977803649587, -2.178740035235112, -2.0578678381447895, -1.9319640949708732, -1.8032660322813758, -1.6740159716759537, -1.5464123873586164, -1.422562390390651, -1.30443674412017, -1.1938284497387512, -1.0923158504329584, -1.0012310894455407, -0.9216346243580781, -0.8542963503563706, -0.7996837228464807, -0.757957098565901, -0.7289723385036845, -0.7122905398338407, -0.7071945920039241, -0.7127120883228975, -0.7276439728637415, -0.7505981669297023, -0.7800273030189243, -0.8142695999675075, -0.8515918430104726, -0.8902333885211917, -0.9284500961729162, -0.9645571015405091, -0.9969693793773288, -1.0242391109444213, -1.04508895617724, -1.0584404408894754, -1.06343679783243, -1.059459744976645, -1.0461398411959217, -1.0233602246491285, -0.9912537084102454, -0.9501933770347137, -0.9007769925241031, -0.8438056744326653, -0.780257462739374, -0.7112564999965393, -0.6380386779759771, -0.5619146808678084, -0.48423141989954327, -0.40633289149465146, -0.3295215018851708, -0.2550208852029298, -0.18394119994047886, -0.11724782139805504, -0.05573425705053005, -4.909565874815416e-16], [0.0, 0.047076878718929654, 0.0878838508380211, 0.12259293686679143, 0.15159466908517913, 0.17548646019065206, 0.19505509052845812, 0.21125377013022711, 0.22517437450413433, 0.2380155806472168, 0.25104773883572007, 0.2655754036034827, 0.28289851168473523, 0.3042732339091113, 0.33087354105745115, 0.3637545101393718, 0.403818357727748, 0.45178412183256395, 0.5081618249064496, 0.5732318401348362, 0.6470300539080532, 0.7293392725107672, 0.8196871642031655, 0.9173508629230528, 1.0213681909334575, 1.1305552891089339, 1.2435302794296887, 1.358742428766607, 1.4745061401157011, 1.5890389706962154, 1.7005027689852805, 1.807046937570266, 1.9068527678584006, 1.998177757791605, 2.079398815730312, 2.149053272884504, 2.2058766726992296, 2.2488363773951856, 2.27716012773076, 2.2903588096981666, 2.288242818456378, 2.270931562026013, 2.2388558114210317, 2.1927527759615875, 2.133653958290347, 2.0628660187902206, 1.9819450493701858, 1.8926648177566372, 1.7969796915256706, 1.6969830824775685, 1.5948623633344952, 1.4928512973689685, 1.393181085231713, 1.2980311703412226, 1.209480953772136, 1.1294635513578115, 1.0597226801085742, 1.001773689116943, 0.9568696535970181, 0.9259733319129331, 0.9097356472639407, 0.9084812014604983, 0.9222011616902565, 0.9505536863808249, 0.9928718774659493, 1.0481790679000071, 1.1152110794804182, 1.1924449211513863, 1.2781332459787633, 1.3703437495906858, 1.4670025773497382, 1.565940714649019, 1.6649422667387603, 1.7617934930128862, 1.8543314466856566, 1.940491084562437, 2.0183497527697454, 2.0861680218006198, 2.1424259363505143, 2.1858538598625166, 2.215457227620474, 2.2305346723025767, 2.230689148422523, 2.215831853028075, 2.186178915184827, 2.142241001838258, 2.084806158322111, 2.014916363885627, 1.9338384321858368, 1.843030020091756, 1.7441016221399206, 1.6387755198172673, 1.5288427223341214, 1.4161189771010547, 1.3024009427985361, 1.18942360545653, 1.078819978744841, 0.9720840647803641, 0.8705379628857758, 0.7753039031795864, 0.6872818524685784, 0.6071331949419145, 0.535270833304513, 0.4718558911968036, 0.416801029179524, 0.3697802184529906, 0.3302446530470267, 0.2974443265526407, 0.2704546574346715, 0.24820742110764807, 0.22952514040565186, 0.21315800147222352, 0.1978223015250421, 0.1822393998925639, 0.16517413501352507, 0.14547168790945517, 0.12209191649232273, 0.09414025380688038, 0.06089435515793684, 0.02182579168377041, -0.023383781565836148, -0.07483240992794178, -0.1323938467471825, -0.19571989241703963, -0.26424900731452666, -0.33722097690393116, -0.4136972486858737, -0.492586411696427, -0.5726741537062248, -0.6526569125838869, -0.7311783395017404, -0.8068676153052786, -0.8783786094093518, -0.9444288443794628, -1.0038372296145952, -1.0555595543129817, -1.0987207825512337, -1.1326432705661673, -1.1568701263027577, -1.1711830515126234, -1.1756141441746448, -1.1704512903434816, -1.1562369359400688, -1.133760196448326, -1.1040424317823185, -1.0683165804916324, -1.0280007077838835, -0.9846663715228178, -0.9400025456248567, -0.8957759576952151, -0.8537887943224065, -0.8158348007058484, -0.7836548493190262, -0.7588930738276072, -0.7430546588615078, -0.7374663435287871, -0.7432406374764666, -0.761244664224382, -0.792074439420735, -0.8360352641645064, -0.893128768693758, -0.9630469830691646, -1.0451736428571623, -1.1385927633590316, -1.2421043399151073, -1.3542468585584304, -1.473326135060513, -1.5974498452986987, -1.7245669697095773, -1.8525112528426604, -1.9790476787135123, -2.101920886273068, -2.2189043987728128, -2.3278495173950806, -2.426732733849633, -2.513700548649559, -2.587110640727853, -2.645568418538278, -2.6879580907695395, -2.713467523683107, -2.7216062987415053, -2.712216545068089, -2.685476292464725, -2.6418952680504035, -2.582303238760947, -2.507831178611833, -2.419885709479249, -2.320117423073001, -2.210383835902429, -2.0927078548801092, -1.9692327357255601, -1.8421745970032941, -1.7137736075245074, -1.5862449926603106, -1.4617310052219359, -1.342254979006103, -1.2296785286053469, -1.1256628790271714, -1.03163520506189, -0.9487607357705645, -0.8779212370266541, -0.8197003282661833, -0.7743759223569359, -0.7419199039125387, -0.7220049857259551, -0.7140185095951934, -0.7170827909138808, -0.7300814500835251, -0.7516910318859968, -0.7804170898831297, -0.8146338096860885, -0.8526261650387909, -0.8926335459828431, -0.9328937701828709, -0.9716863873982838, -1.0073742130244299, -1.0384420788558442, -1.0635318663589226, -1.0814729877766687, -1.0913076007546407, -1.0923099798054818, -1.0839996193257917, -1.0661478042151855, -1.038777551353837, -1.0021569940649848, -0.9567864479822147, -0.9033795562905184, -0.8428390611240817, -0.7762278822673784, -0.7047363008732074, -0.629646141786474, -0.5522929208747949, -0.4740269717272575, -0.3961745880282669, -0.32000021333708645, -0.24667067906534323, -0.17722243496677414, -0.1125326359005409, -0.05329484607055901, -4.678182516238691e-16], [0.0, 0.044611510877342136, 0.08307211292779544, 0.11566455145898441, 0.1428830144077662, 0.16541828923471164, 0.18413731595511876, 0.2000576722397225, 0.21431766004362474, 0.22814277973365749, 0.24280947420881846, 0.2596070995734766, 0.2797991286203423, 0.3045846174131563, 0.33506096297587346, 0.3721889515054845, 0.4167610423010528, 0.46937375405910886, 0.5304049192554703, 0.5999964515115686, 0.6780431331287834, 0.7641877787956032, 0.8578229706020377, 0.9580993929561016, 1.0639406279606252, 1.174064106493413, 1.2870077517985419, 1.401161704837048, 1.5148043876936959, 1.6261420463689429, 1.7333508202361363, 1.8346203147332127, 1.9281976083293055, 2.0124306056808745, 2.0858096567359685, 2.147006396257107, 2.194908819042976, 2.228651691617524, 2.2476415092874222, 2.251575335644886, 2.240453006710126, 2.2145823404377447, 2.1745771603866713, 2.121348115862233, 2.0560864555276814, 1.9802410830594872, 1.8954893876630936, 1.8037024951236547, 1.7069057227630118, 1.6072351407999423, 1.5068912402071108, 1.408090780791682, 1.313017941048912, 1.2237759121326115, 1.1423400714984853, 1.0705138375275738, 1.0098882455225318, 0.9618061993393953, 0.927332243640629, 0.9072285719697161, 0.9019378386950353, 0.9115731819200131, 0.9359156936154879, 0.9744193966499848, 1.0262236103663724, 1.0901724112068991, 1.1648407268797316, 1.2485664457701995, 1.3394877815342576, 1.4355850095062694, 1.5347255896902237, 1.6347116131380373, 1.733328456318827, 1.8283935028841598, 1.9178037946089823, 1.9995815031321564, 2.0719161706575195, 2.1332027495748895, 2.1820745759724316, 2.2174305376216, 2.2384558401067998, 2.2446359318024167, 2.2357633154922576, 2.211937147462356, 2.1735556996204646, 2.1213019323145095, 2.056122590819877, 1.9792013929013164, 1.8919270146648188, 1.7958567037030855, 1.692676449362369, 1.5841587174006444, 1.47211880853315, 1.3583709261657004, 1.2446850374501404, 1.1327455837817892, 1.0241130427826604, 0.9201892651096375, 0.8221874081348801, 0.7311071672650525, 0.6477158674867913, 0.5725358261520951, 0.50583823687977, 0.4476436578083399, 0.39772901948156897, 0.3556409025942358, 0.32071467780594504, 0.292098952794053, 0.2687846393304251, 0.2496378387243673, 0.23343565031433208, 0.21890393712654183, 0.20475603707934772, 0.18973138830203212, 0.17263304370716104, 0.15236308269428964, 0.12795498589995688, 0.09860212073898145, 0.06368158900239383, 0.022772810340655977, -0.024329646057875805, -0.07760931840827386, -0.13682737527175737, -0.20152841793933632, -0.2710524114082013, -0.34455243264101265, -0.4210177722383162, -0.4993017848738665, -0.5781537584239921, -0.6562539648621702, -0.7322509704203558, -0.8048002204362885, -0.8726028773186932, -0.934443879147317, -0.9892282019040639, -1.0360143498637713, -1.074044165260773, -1.1027681383618853, -1.1218655102978239, -1.1312585906772792, -1.131120856907042, -1.1218785586559183, -1.104205715120141, -1.0790125605633631, -1.0474276608066277, -1.0107740857314897, -0.9705401763424876, -0.9283455856376851, -0.8859033968922112, -0.8449792278048837, -0.8073483116061515, -0.7747516045384176, -0.7488520015599904, -0.7311917477945934, -0.7231521119162833, -0.7259163397620172, -0.7404368330987962, -0.7674074013715785, -0.8072413157465061, -0.8600557577016377, -0.9256631021300464, -1.003569311117106, -1.0929795432370735, -1.1928109085794194, -1.301712126048484, -1.4180896710516588, -1.5401398426505972, -1.6658860335219416, -1.7932203572639411, -1.9199486788862432, -2.0438380084371732, -2.1626651568032047, -2.2742655182963123, -2.376580837615321, -2.4677048393438237, -2.545925645870853, -2.609763983364398, -2.658006273427761, -2.689731827963611, -2.7043335036618132, -2.701531327049009, -2.6813787674406724, -2.644261509377999, -2.5908887539777696, -2.522277255750033, -2.4397284735405034, -2.344799377149973, -2.2392676009163566, -2.125091768484364, -2.0043679259141074, -1.879283110466613, -1.7520671476823115, -1.6249438081822472, -1.5000824670641892, -1.3795513926016192, -1.2652737476252072, -1.158987317581015, -1.0622088855621694, -0.9762040589407837, -0.9019632174591362, -0.8401841021133871, -0.7912614016001546, -0.7552835225070624, -0.7320365550132434, -0.72101527191158, -0.7214408295383653, -0.7322846788399313, -0.7522980472341284, -0.7800462207283599, -0.8139467441137118, -0.8523105676552031, -0.8933851036737951, -0.9353981172911061, -0.9766013632623525, -1.0153128954709796, -1.049957016843797, -1.0791009040543615, -1.101487031672562, -1.1160606320624111, -1.121991557474462, -1.118690056116897, -1.105816130840811, -1.0832823134830112, -1.051249855735155, -1.0101185044365266, -0.9605101912323358, -0.903247119546316, -0.8393248719653911, -0.76988128493386, -0.696161942029456, -0.619483219459782, -0.5411938757477026, -0.4626362104469527, -0.38510782336423216, -0.30982498604172753, -0.23788859171717494, -0.1702535798184509, -0.10770263807634543, -0.050824871935045784, -4.446490257965839e-16], [0.0, 0.04218935357197776, 0.07839827907974438, 0.10901613722844748, 0.13463492064785304, 0.15603136793669403, 0.1741437964338527, 0.19004426371973177, 0.2049067911430629, 0.21997248729369379, 0.23651249262711727, 0.25578972625398916, 0.2790204506895347, 0.30733667919426244, 0.3417504329616467, 0.3831208122126343, 0.4321247772832503, 0.4892324447069821, 0.5546875913481412, 0.6284939296137598, 0.710407571896159, 0.7999359462907216, 0.8963432621964761, 0.9986624577348299, 1.105713395197051, 1.216126910121653, 1.3283741681567842, 1.440800645407868, 1.5516639260182412, 1.659174408387549, 1.7615379313235058, 1.8569992756237303, 1.9438854665705911, 2.020647799430202, 2.0859015334528173, 2.138462249586553, 2.1773779419953097, 2.201956011743643, 2.211784450320588, 2.206746638138816, 2.187029335426893, 2.1531236063187307, 2.1058185874409356, 2.04618818572725, 1.9755709622900468, 1.8955436257170224, 1.8078887150307257, 1.714557195874421, 1.6176268197213342, 1.5192572019121549, 1.4216426574663075, 1.3269638918033626, 1.23733967527893, 1.154779634958894, 1.0811392741689776, 1.0180782805778386, 0.9670231080759714, 0.9291347183058712, 0.9052822467752353, 0.8960232189672632, 0.9015907871306517, 0.9218882922409967, 0.9564912820115871, 1.0046569390141715, 1.0653406972475614, 1.1372196551354599, 1.218722232084602, 1.3080633682965637, 1.403284437078189, 1.5022969285960037, 1.6029288765335286, 1.702972936541286, 1.8002349892095744, 1.8925821313880236, 1.9779889381989049, 2.054580923546265, 2.1206741981536914, 2.1748104193825224, 2.215786243916487, 2.2426766299476535, 2.2548514864069515, 2.251985329323192, 2.2340597755607825, 2.2013588777912956, 2.154457477333775, 2.094202919218004, 2.0216906323816874, 1.9382342234388226, 1.8453308614139692, 1.7446228401040884, 1.6378562916774086, 1.5268380876763827, 1.413392000296187, 1.299315206841692, 1.1863362034670946, 1.0760751511822713, 0.9700076088282894, 0.8694325160642669, 0.7754451767280045, 0.6889158621102232, 0.61047450803888, 0.5405018228891558, 0.4791269596697657, 0.4262317383110879, 0.3814612383868204, 0.34424042189369153, 0.31379629440748985, 0.2891849747027387, 0.2693229212077823, 0.2530214614870838, 0.23902369082389263, 0.22604274988734757, 0.21280046077099626, 0.19806529610760726, 0.18068867756406676, 0.15963864720807278, 0.13403002678058434, 0.10315027395834805, 0.06648035883851464, 0.023710115207357014, -0.02525233367836387, -0.0802773197582527, -0.14101662873639922, -0.2069126724004634, -0.2772135929967553, -0.350993902582597, -0.42718011500186615, -0.5045806966564181, -0.5819195479224415, -0.6578721328034732, -0.7311033026342001, -0.8003058121997694, -0.864238504751916, -0.9217631466809195, -0.971878922978409, -1.0137536603811368, -1.0467509248610969, -1.0704522419584086, -1.0846738098184057, -1.0894772126768903, -1.0851737935014485, -1.0723225047714726, -1.0517212219542573, -1.0243916709578298, -0.9915582845245543, -0.9546214590523674, -0.9151258287421613, -0.8747243045897093, -0.8351387382485554, -0.7981181623121516, -0.7653956267410372, -0.7386446942129489, -0.71943667394068, -0.7091996634763055, -0.7091804313579827, -0.7204101109763131, -0.7436745892033015, -0.7794903642081775, -0.8280865181075806, -0.889393304782686, -0.9630376948788176, -1.0483460525490491, -1.1443539460116112, -1.249822920693705, -1.36326389389171, -1.4829666676735451, -1.6070349061859819, -1.7334257883309145, -1.8599934302923058, -1.9845350775252295, -2.1048389949302493, -2.2187329388133956, -2.3241320760271895, -2.419085224895177, -2.5018183289618743, -2.5707741374355737, -2.624647153907231, -2.662413025428582, -2.683351674649936, -2.6870636252914304, -2.673479132172746, -2.642859897447756, -2.5957933304417744, -2.5331794852980822, -2.456210984208939, -2.3663464001157295, -2.265277727377615, -2.154892708274858, -2.0372329039535506, -1.9144484976115461, -1.7887508929800262, -1.6623642206668328, -1.5374768875254479, -1.4161942993857832, -1.3004938553906493, -1.1921832536549013, -1.0928630644789623, -1.003894420991323, -0.9263725505111249, -0.86110672624927, -0.8086070617571917, -0.7690784036650585, -0.7424214058357362, -0.728240694335544, -0.7258598618504414, -0.7343428665385252, -0.7525212578038447, -0.779026513817108, -0.8123266561362765, -0.8507662083782273, -0.8926084909186783, -0.9360791938238804, -0.9794101467889497, -1.0208822082639704, -1.0588662260138106, -1.0918610772439004, -1.118527876655672, -1.137719543294772, -1.1485050391960798, -1.1501877315028415, -1.1423174814294987, -1.1246962243181655, -1.0973769710565802, -1.0606563281091521, -1.0150607971767118, -0.9613272719467305, -0.9003782946177149, -0.8332927652607736, -0.7612729093775882, -0.6856084004459072, -0.6076386025568868, -0.5287139417728733, -0.4501574325236597, -0.3732273768179496, -0.29908221953880215, -0.22874848353353594, -0.16309262514499626, -0.1027975463977683, -0.048344376921093585, -4.2163408567789886e-16], [0.0, 0.03982907570372447, 0.07389751785669922, 0.10269627704915683, 0.12690848460107879, 0.14738871823365926, 0.16513735062092785, 0.18127065865321976, 0.1969874833672892, 0.21353332248449053, 0.23216280699454603, 0.25410155843889176, 0.2805084433054509, 0.31243923470691903, 0.3508126593921575, 0.396379750901468, 0.4496973487205764, 0.5111064806125947, 0.5807162434584379, 0.6583936599461605, 0.7437598377608218, 0.836192598305737, 0.934835577431212, 1.0386136352870974, 1.1462542504079662, 1.2563144185661022, 1.3672124336917792, 1.4772637998913731, 1.5847204135542607, 1.687812065543944, 1.7847892478130385, 1.873966208184926, 1.9537631826053417, 2.022746746335054, 2.0796672641188874, 2.123492483459105, 2.1534364032386937, 2.168982659978953, 2.169901803323918, 2.156261977786163, 2.128432685822453, 2.087081474072388, 2.0331635560032817, 1.967904556051462, 1.8927767284060584, 1.8094691637035532, 1.7198526451349407, 1.6259399481431849, 1.5298424917143065, 1.4337243414068659, 1.3397546324166751, 1.2500595234176048, 1.1666748075656574, 1.09150029546944, 1.0262570463508744, 0.9724484589434487, 0.9313261444403242, 0.9038613921540626, 0.8907229071770687, 0.892261351416355, 0.9085010585039079, 0.9391391231601284, 0.983551890740845, 1.0408086971782964, 1.1096925376002655, 1.1887271777585062, 1.276210070006219, 1.3702502986347065, 1.468810661231444, 1.5697528962149683, 1.670884994163733, 1.770009483725786, 1.8649715628821282, 1.9537059535895238, 2.0342813921303953, 2.104941727967574, 2.1641426890192212, 2.2105834789102348, 2.243232499248039, 2.2613466341560056, 2.2644836916155033, 2.252507762739312, 2.2255874318258275, 2.1841869427066034, 2.129050596265544, 2.0611808159323495, 1.981810468482588, 1.8923701629485616, 1.7944513675740412, 1.6897662807073557, 1.5801054640253185, 1.467294293804415, 1.353149307021368, 1.2394355134411001, 1.1278257127664835, 1.019862798267478, 0.9169259465953725, 0.8202014898334401, 0.7306591428909232, 0.6490341202393811, 0.575815524240784, 0.5112412267539286, 0.45529930037008726, 0.40773588967069707, 0.3680692504766629, 0.33560953023139656, 0.3094837192905434, 0.2886650745493637, 0.2720062067099878, 0.2582749332994252, 0.24619193349026527, 0.2344691994606902, 0.2218482634467191, 0.20713719012808904, 0.18924536023502578, 0.1672151323046011, 0.14024955376832948, 0.10773539785060085, 0.0692609264064659, 0.024627917673098028, -0.02614235158273102, -0.08280932169516461, -0.14491955352514507, -0.21181914784695188, -0.2826718514226139, -0.35648237146558603, -0.4321242833681108, -0.5083717954188971, -0.5839345318556016, -0.6574944145951187, -0.7277436664422156, -0.7934229259821084, -0.8533584575770639, -0.9064974591238172, -0.9519405150453751, -0.9889703113017564, -1.0170758213055062, -1.0359712842405762, -1.0456094276094297, -1.0461885306256413, -1.0381530807120412, -1.0221879379628427, -0.9992060879061756, -0.9703302271048637, -0.9368685849256941, -0.9002855341856113, -0.8621676795686976, -0.8241862322442878, -0.7880565789554058, -0.7554960314250746, -0.7281807952318027, -0.7077032249215481, -0.6955304332748393, -0.6929652972146152, -0.7011108513636026, -0.7208389839290239, -0.7527642502162399, -0.7972234990367003, -0.8542618694818561, -0.9236255633325255, -1.00476163547564, -1.0968248750927574, -1.1986916782271722, -1.3089806418602032, -1.4260794450303542, -1.5481774278731661, -1.673303138568592, -1.799365994547782, -1.9242011010059366, -2.0456161893690266, -2.1614395828886206, -2.269568067399081, -2.3680135432285163, -2.4549473594086373, -2.5287412831101475, -2.588004134418216, -2.631613217309668, -2.6587397995747826, -2.6688680344961844, -2.661806871962452, -2.637694672597357, -2.5969964113979365, -2.5404935330936897, -2.469266695693578, -2.384671807240728, -2.2883099195505485, -2.1819916878100947, -2.0676972328440284, -1.947532350506472, -1.8236820974365398, -1.6983628422795138, -1.5737739049961619, -1.4520499132787463, -1.3352149842467707, -1.2251397920592835, -1.123502509058744, -1.031754511381794, -0.951091622040548, -0.8824315282185494, -0.8263978583075312, -0.7833112417662709, -0.7531875052119485, -0.7357429854296034, -0.7304067684454548, -0.7363394976570771, -0.7524582373088577, -0.7774667341647676, -0.8098902935471423, -0.8481143790441998, -0.8904259607083496, -0.9350565764815414, -0.9802260372945286, -1.0241856985541398, -1.0652602396571784, -1.1018869381913385, -1.1326514953964963, -1.1563195624425302, -1.1718632307426964, -1.178481880965719, -1.1756169313004825, -1.162960182178144, -1.1404556181203258, -1.1082946935512488, -1.0669052941185864, -1.0169347241912106, -0.959227220767297, -0.8947966303063221, -0.8247950046053358, -0.7504779718090792, -0.6731678165080106, -0.5942152567288695, -0.5149609341555502, -0.4366976364675881, -0.36063424723635923, -0.28786237001574616, -0.21932650038156037, -0.15579852459338295, -0.0978572087119729, -0.045873210338163536, -3.989544392183075e-16], [0.0, 0.03754847644786831, 0.06960281559674929, 0.09674967418129674, 0.11975591346211832, 0.13954523444868552, 0.15717029789002246, 0.17378106791311013, 0.19059021832112527, 0.20883651928358649, 0.22974717743968057, 0.2545001328648353, 0.2841873211143633, 0.3197798874976098, 0.3620962943423195, 0.41177419141081517, 0.46924682656629735, 0.5347246605656619, 0.608182719291289, 0.6893540720849408, 0.7777296697279715, 0.8725646139081492, 0.9728907657815076, 1.077535438605598, 1.1851457624841655, 1.294218161984086, 1.4031322534912882, 1.5101883520645656, 1.6136476802136135, 1.7117742959722324, 1.8028777068107893, 1.8853551106857316, 1.9577322065755003, 2.0187015442663463, 2.0671574363367413, 2.102226533012394, 2.123293260979493, 2.130019447938844, 2.122357592736558, 2.100557392959705, 2.0651653042256504, 2.0170170740467555, 1.9572233639782681, 1.8871487425548914, 1.8083844941304552, 1.7227158411398116, 1.6320843157307976, 1.5385461377328573, 1.4442275565262528, 1.3512781920379633, 1.2618234628637663, 1.1779172160559992, 1.1014956727211662, 1.034333776199627, 0.9780049758720495, 0.9338454008224958, 0.9029232755709914, 0.8860143073251061, 0.8835836336565088, 0.8957747645890131, 0.9224057875474777, 0.9629729314823435, 1.0166614119358557, 1.0823633060966165, 1.1587020401983061, 1.244062915008111, 1.336628952425258, 1.4344212208343836, 1.5353426918703401, 1.6372245991886805, 1.737874212674645, 1.8351229106273215, 1.9268734285448974, 2.0111451862698946, 2.086116644825861, 2.1501637190374887, 2.201893370107251, 2.240171621285975, 2.264145376676561, 2.2732575746671553, 2.267255369768391, 2.2461912057350437, 2.2104168146307264, 2.1605703467321264, 2.0975570006993323, 2.022523678242469, 1.9368283288208348, 1.84200477428863, 1.739723907845045, 1.6317522436488276, 1.519908851070731, 1.4060217394411325, 1.2918847646037641, 1.1792161075648413, 1.069619328640746, 0.964547929007925, 0.8652742573040383, 0.7728634843393404, 0.6881532369707754, 0.6117393361140963, 0.5439679274099058, 0.4849341301565182, 0.43448716486700595, 0.3922417563404167, 0.3575954515453581, 0.32975134383062804, 0.3077455606815753, 0.29047875476762297, 0.2767507402837169, 0.265297340984869, 0.25482846469809173, 0.24406639271489552, 0.23178327193015685, 0.21683682285983996, 0.1982033270529481, 0.1750070315939143, 0.14654520445535335, 0.11230818994388196, 0.07199394543347391, 0.025516685638925864, -0.026990584843985015, -0.0851797100408449, -0.148497090060884, -0.21619919671471627, -0.28737348446079786, -0.360964142392152, -0.43580200566891786, -0.5106378348915063, -0.5841780821959128, -0.6551221956316805, -0.7222004703838991, -0.7842114377439393, -0.8400577909029363, -0.8887798804710364, -0.9295858713015817, -0.9618777342844669, -0.9852723502374044, -0.9996171252984164, -1.0049996552613554, -1.0017511266516415, -0.9904433012498972, -0.9718790942533204, -0.9470769202134021, -0.9172491411791455, -0.8837751040659535, -0.8481693953051563, -0.8120460667317582, -0.7770796942335678, -0.7449642171588855, -0.7173705696290673, -0.6959041530693096, -0.6820632114180393, -0.6771991562099287, -0.682479848313919, -0.6988567774606403, -0.7270369913573841, -0.767460515299093, -0.8202838734161714, -0.8853701772037111, -0.9622860892981585, -1.0503058044620253, -1.1484220194745376, -1.255363693289863, -1.3696202326086655, -1.4894715800135143, -1.6130235359502816, -1.738247515710023, -1.863023831411348, -1.985187499574016, -2.1025755094501672, -2.2130744474952118, -2.3146673602421597, -2.4054787517638907, -2.483816652577139, -2.5482107633117526, -2.597445767158202, -2.630589017837624, -2.64701194189297, -2.6464046422818006, -2.6287833509688667, -2.5944905475682853, -2.5441877349567874, -2.4788410369444134, -2.3996999533131405, -2.308269769678491, -2.2062782697541854, -2.0956375320593525, -1.9784017086406607, -1.8567217771912035, -1.7327983277701906, -1.6088334894882077, -1.4869831199756651, -1.369310370807559, -1.2577417055892284, -1.1540263850459755, -1.0597003467691892, -0.976055298411684, -0.9041137147951779, -0.8446102847673876, -0.7979801962939739, -0.7643544820676744, -0.7435624769501556, -0.7351412670286146, -0.7383518421718779, -0.7522015038154353, -0.7754719311985244, -0.8067521760309724, -0.8444757408111686, -0.8869608025145076, -0.932452573357978, -0.9791667454704615, -1.0253329475833137, -1.0692371496759945, -1.1092619855828385, -1.1439240229557126, -1.171907093123626, -1.1920908981483622, -1.2035742360674537, -1.2056923247998723, -1.1980278569374403, -1.1804155778309682, -1.1529403439765664, -1.1159287835863427, -1.069934842261102, -1.0157196498487842, -0.9542262860529479, -0.886550148632566, -0.8139057359765427, -0.7375907427771348, -0.6589484313303529, -0.5793292801061264, -0.5000529247262752, -0.4223713940782932, -0.34743460634232004, -0.27625902722394097, -0.2097003072884646, -0.14843060917915382, -0.09292121138835616, -0.04343083630279886, -3.767851968994985e-16], [0.0, 0.035364319632219546, 0.06554467518333669, 0.09121675330084375, 0.11322307255899555, 0.13254722726772766, 0.15028405152878885, 0.16760649621945792, 0.1857300990230124, 0.2058759925791564, 0.229233436626766, 0.25692287559279653, 0.2899605130165426, 0.3292253587045771, 0.37542964444592447, 0.4290934209559866, 0.4905240445209801, 0.559801139173417, 0.6367674822021665, 0.7210261108378351, 0.8119437898109715, 0.9086608171240514, 1.0101069828883484, 1.1150233375446006, 1.2219892752115946, 1.3294542990980345, 1.435773712392233, 1.539247372958538, 1.6381605662121697, 1.7308259898870453, 1.8156258086491612, 1.8910527266192696, 1.955749042188303, 2.0085426917212588, 2.0484793558887446, 2.0748497928572935, 2.087211674243073, 2.085405329891507, 2.0695629530257307, 2.040110974561011, 1.9977654805622542, 1.9435207158749395, 1.8786308857292922, 1.8045856314447641, 1.7230797121895103, 1.6359775682221613, 1.5452735686024608, 1.4530488548308633, 1.3614257785568162, 1.272520994205033, 1.1883983045185946, 1.1110223676432205, 1.0422143581649217, 0.9836106318086785, 0.9366253753047872, 0.9024181308548535, 0.8818669708911008, 0.8755479661641685, 0.8837214418250079, 0.9063253556826777, 0.9429759641172106, 0.9929757683040351, 1.055328560664893, 1.1287612230000312, 1.2117517676737473, 1.3025629654112358, 1.3992807713095825, 1.499856647771333, 1.6021527919691503, 1.7039892083441408, 1.803191525139054, 1.8976384390534629, 1.985307684112076, 2.0643194594306618, 2.132976314766836, 2.1897985809484837, 2.233554542288154, 2.263284677191814, 2.2783194381658034, 2.27829019974131, 2.263133168599453, 2.2330862203188704, 2.188678797507831, 2.1307151704533256, 2.0602515197544236, 1.9785674468466528, 1.8871326493087448, 1.7875696102020808, 1.6816132417213916, 1.5710684909604007, 1.4577669580307149, 1.3435235931529244, 1.2300945293486505, 1.1191370713379087, 1.0121728001682735, 0.9105546685710076, 0.8154388562321648, 0.7277620297852354, 0.6482245125326976, 0.5772797172198496, 0.5151300354364013, 0.4617292134225343, 0.41679108031214435, 0.3798043352519503, 0.3500529483741936, 0.32664159104488477, 0.30852538662562673, 0.29454316725079194, 0.2834533374415476, 0.27397138383015635, 0.26480803334521297, 0.254707050784074, 0.24248168100464962, 0.22704878059057798, 0.20745974773183537, 0.18292744555864765, 0.15284842104527288, 0.11681984612619556, 0.07465074666344236, 0.026367234830951717, -0.027788382471872205, -0.08736458638950921, -0.15171352803623087, -0.22000946329315266, -0.2912722488275907, -0.364395274910125, -0.4381770937918708, -0.5113559045283383, -0.5826459786947268, -0.6507750583893289, -0.7145217296379648, -0.7727517715407543, -0.8244525043494324, -0.8687642075900148, -0.9050077511812196, -0.9327076764702876, -0.9516100778818292, -0.9616947666184337, -0.9631813422994217, -0.9565289529623526, -0.942429684607487, -0.9217956844019957, -0.8957402826801854, -0.8655535339202265, -0.832672742030334, -0.7986486668614351, -0.765108223533687, -0.7337145809917358, -0.7061256387476786, -0.6839519091424113, -0.6687148553644453, -0.6618067322516099, -0.6644529475554288, -0.6776779065109294, -0.7022752235020729, -0.7387830832254836, -0.7874654124721672, -0.8482993854070076, -0.9209696333947257, -1.00486936870842, -1.0991084638254394, -1.2025283585824385, -1.3137235003979146, -1.4310688621970122, -1.5527529325582927, -1.6768154366643666, -1.801188928253451, -1.9237432948861306, -2.0423321439114916, -2.15483998642743, -2.259229112563004, -2.35358505420677, -2.436159560848249, -2.5054100698178376, -2.560034732589503, -2.5990021620290955, -2.6215751890439445, -2.627328058031599, -2.616156645423468, -2.5882814507151197, -2.544243280659554, -2.484891720610268, -2.411366658123419, -2.3250732887022525, -2.227651187985832, -2.1209381749960636, -2.0069298138552365, -1.8877355036939982, -1.7655321858127144, -1.6425167516262402, -1.5208582632134144, -1.4026510997482502, -1.2898701177098122, -1.184328861208176, -1.0876417823217075, -1.001191331922421, -0.9261006615377723, -0.8632125393253487, -0.8130749316146922, -0.7759335394326558, -0.7517314109603815, -0.7401155801071543, -0.7404505125146904, -0.7518379774558106, -0.7731428112391031, -0.8030238985972692, -0.8399695764967556, -0.882336562807075, -0.9283914327561464, -0.9763536109585451, -1.0244388173161678, -1.0709019018974548, -1.1140780269919917, -1.1524212032509908, -1.1845392598665758, -1.209224424219017, -1.2254788018836553, -1.2325341804001937, -1.229865726410943, -1.217199301982825, -1.1945122882117272, -1.1620279684943158, -1.1202036860293993, -1.0697131461255758, -1.0114233798552952, -0.9463670178764989, -0.8757106385603052, -0.8007200500660007, -0.7227234393431495, -0.6430733704249564, -0.5631086386202236, -0.48411698575922424, -0.40729965459330336, -0.3337387085231369, -0.2643679673949756, -0.1999483131056948, -0.1410480026838889, -0.08802849433158338, -0.04103614698797482, -3.552939157982844e-16], [0.0, 0.03329217998628205, 0.061750842476371824, 0.08613330816862369, 0.10734910104135258, 0.126432058371899, 0.1445088256618427, 0.16276457530801025, 0.1824068620267979, 0.20462857886020402, 0.230571003753618, 0.2612879275059353, 0.2977118292980023, 0.3406230165914761, 0.39062257316802546, 0.44810986425503946, 0.5132652334160154, 0.5860383950210678, 0.6661428819263301, 0.7530567540910018, 0.8460296141078995, 0.9440958140315204, 1.0460935785242662, 1.1506896162256073, 1.256408648251066, 1.3616671534727436, 1.464810518009115, 1.5641526840285058, 1.6580173229264021, 1.7447795119989296, 1.8229068731332234, 1.890999137371105, 1.9478251304313174, 1.9923562307090765, 2.0237954315923496, 2.041601242228088, 2.045505782674186, 2.0355265677300873, 2.0119716252792457, 1.975437755994429, 1.9268019078034944, 1.8672058064948962, 1.7980341491205976, 1.720886825349386, 1.6375457797150672, 1.549937261127443, 1.4600903217523478, 1.3700925225332248, 1.2820438748351535, 1.1980100951183514, 1.1199762709741776, 1.0498020317022319, 0.9891792849440674, 0.9395935234406402, 0.9022896241037726, 0.8782429572448366, 0.8681364994976278, 0.8723445027101945, 0.8909231162830683, 0.9236081958542838, 0.9698203608716425, 1.0286771915905746, 1.0990122865739773, 1.1794007389698526, 1.2681904376621944, 1.3635384615293185, 1.4634517148497224, 1.5658308522837872, 1.6685164652401516, 1.7693364496550765, 1.8661534495086578, 1.9569112713714025, 2.039679192862742, 2.1126931414018215, 2.174392797698664, 2.2234537791278735, 2.2588141789529033, 2.279694875340722, 2.2856131758229563, 2.276389524585742, 2.2521471677323994, 2.2133048413446708, 2.160562714613448, 2.094881981425016, 2.017458644643585, 1.929692174255218, 1.8331498402124935, 1.729527620356058, 1.6206086608036012, 1.5082203188652932, 1.3941908456488556, 1.280306766473604, 1.1682719920853442, 1.0596696431630284, 0.9559274960703071, 0.858287861160713, 0.767782588667697, 0.6852137642561342, 0.6111405100434314, 0.5458721510029447, 0.4894678450583402, 0.44174261191632325, 0.4022795348513052, 0.37044775526383034, 0.3454257357307268, 0.32622913703006234, 0.311742541485113, 0.3007541617221525, 0.2919926028673225, 0.2841646990489028, 0.27599342295159085, 0.2662548705877583, 0.2538133522643575, 0.23765367415306876, 0.21690977151801327, 0.19088895254057842, 0.159091128293623, 0.12122253677769695, 0.07720361366667185, 0.027170815836880163, -0.028527638026407072, -0.08934198645617623, -0.1545368248408063, -0.22321225812546958, -0.2943297414933896, -0.36674192088055646, -0.4392256797213153, -0.5105175131582222, -0.5793502882536354, -0.6444904101234454, -0.7047744003806176, -0.7591439062017332, -0.8066781954469617, -0.8466232546716664, -0.8784166910524129, -0.9017077441232982, -0.9163718361683875, -0.9225192280731653, -0.9204974969506726, -0.9108877091792186, -0.8944943236687718, -0.8723290211588235, -0.8455888120859478, -0.8156289240872279, -0.7839311067667396, -0.7520681124790328, -0.7216652144871136, -0.6943597053009052, -0.6717593761855618, -0.6554010122142798, -0.6467099449086771, -0.6469616861821125, -0.6572466233447335, -0.6784386863496364, -0.7111688068779425, -0.7558038764727643, -0.8124317804556376, -0.8808529389664753, -0.9605786297091071, -1.0508362026978653, -1.1505811295203618, -1.258515662486123, -1.3731137166422087, -1.4926514340180415, -1.615242748416392, -1.7388791440977782, -1.8614726959229646, -1.9809013945670373, -2.0950557004112222, -2.201885235180177, -2.2994445122255875, -2.3859366248163334, -2.459753856482496, -2.519514247332179, -2.564093243653246, -2.5926496727859285, -2.6046454184405228, -2.5998583201155467, -2.5783879804464678, -2.540654332295374, -2.4873889890963157, -2.4196195732253347, -2.3386473838035085, -2.2460189233135197, -2.1434919478742667, -2.0329968354398114, -1.9165941764270502, -1.7964295796601697, -1.6746867509144219, -1.5535399402000694, -1.4351068663298687, -1.3214032129871602, -1.2142997498404215, -1.115483066261499, -1.0264208155457697, -0.9483322564292707, -0.8821647488987288, -0.8285767159989177, -0.7879274261373713, -0.7602737851351561, -0.7453741580319987, -0.7426990715732984, -0.7514484835233326, -0.7705751484874881, -0.7988134655986074, -0.8347130647342079, -0.8766762779953997, -0.9229985546391452, -0.9719108126237416, -1.021622679928522, -1.0703655647466717, -1.116434505784937, -1.158227791847386, -1.194283402605413, -1.22331140832436, -1.244221573119648, -1.2561455313286074, -1.2584530466389985, -1.250762015175257, -1.2329420329940615, -1.2051115113849824, -1.16762848592827, -1.1210754233689166, -1.0662384800804725, -1.0040818034894288, -0.9357175898962845, -0.8623727156430624, -0.7853528409893606, -0.706004945353088, -0.6256792873138582, -0.5456917921502941, -0.4672878535086887, -0.3916084945427494, -0.31965976861438206, -0.25228619209770803, -0.1901488942349816, -0.13370904410762682, -0.08321697579514113, -0.03870728323795446, -3.3463903405064493e-16], [0.0, 0.03134630276816558, 0.05824606303967538, 0.08153019925610563, 0.10216609902200173, 0.1212278688704436, 0.13986345813731133, 0.1592595339861443, 0.18060504507379962, 0.205054447801432, 0.23369158060747025, 0.26749515800875584, 0.30730681739837995, 0.3538025889080263, 0.4074685734880368, 0.4685815088660614, 0.537194779845397, 0.6131302915761906, 0.6959764754279686, 0.7850925406479913, 0.879618925037237, 0.9784937384396453, 1.080474837940259, 1.1841670272174971, 1.2880537382032624, 1.3905324344843366, 1.4899528757591765, 1.5846573037169271, 1.6730215539775655, 1.7534960676959894, 1.824645770947745, 1.8851878103043311, 1.9340261786540411, 1.9702823352804488, 1.9933210168179476, 2.0027705487384853, 1.9985370977495227, 1.9808124507186102, 1.9500750619362306, 1.907084273857373, 1.8528677829103652, 1.788702587429667, 1.7160898151737525, 1.6367239792629962, 1.5524573499634002, 1.4652602521061147, 1.3771782010194988, 1.2902868710790687, 1.206645948303883, 1.1282529503835181, 1.0569981032673474, 0.9946213427899195, 0.9426724631940024, 0.9024753629356174, 0.875097243514141, 0.8613235015367285, 0.8616389205860663, 0.8762156209466928, 0.9049080654577052, 0.947255252577551, 1.002490057232025, 1.0695555103154983, 1.1471276429553279, 1.2336443658379863, 1.327339710821851, 1.426282635203258, 1.528419481439567, 1.631619099473071, 1.7337195771127143, 1.8325754876996883, 1.9261045543664388, 2.012332646810309, 2.089436069206812, 2.155780165608584, 2.2099533602276953, 2.2507958621244684, 2.2774223942548515, 2.289238452344404, 2.28594975607883, 2.2675647197696396, 2.234389937928485, 2.1870188489424787, 2.1263139031825973, 2.0533827164162117, 1.9695488315702911, 1.8763178382526666, 1.775339706930305, 1.6683682807028177, 1.557218930147543, 1.4437254142856102, 1.3296970024820676, 1.2168768978430808, 1.106902962848915, 1.001271683634711, 0.9013062221778798, 0.8081292979100216, 0.72264151468618, 0.6455056087960763, 0.5771369423284687, 0.5177004075075337, 0.4671137455894555, 0.42505712259256523, 0.390988647563483, 0.3641653711555712, 0.3436691666916026, 0.3284367759617303, 0.3172932007335364, 0.30898754081411467, 0.302230322462113, 0.29573132837569005, 0.2882369331401893, 0.27856596603277795, 0.26564316593965925, 0.24852935971103127, 0.22644758383189517, 0.19880447754477865, 0.16520640075230397, 0.12546986895868906, 0.07962604664241943, 0.02791919599577674, -0.029200864029985594, -0.09109207698280185, -0.15693888414910556, -0.2257758718717994, -0.29651569840887754, -0.36798055537163155, -0.4389363254301674, -0.5081285260742984, -0.5743190806096985, -0.6363229335063495, -0.6930435283353653, -0.7435061928335539, -0.7868885264909762, -0.822546960214822, -0.850038753244582, -0.8691388071983797, -0.8798508080544526, -0.8824123507398186, -0.8772938542042908, -0.8651912335562044, -0.8470124560362096, -0.8238582652720103, -0.7969975094112008, -0.7678376495479152, -0.7378911517698028, -0.7087385759238173, -0.6819892640230197, -0.6592405987757912, -0.6420368462476513, -0.6318286149951133, -0.6299339565968131, -0.6375020994464318, -0.6554807497004518, -0.6845878117489612, -0.7252882774458337, -0.7777769110832874, -0.841967218693236, -0.9174870390793954, -1.0036809337298558, -1.0996193873625784, -1.2041146643850746, -1.3157430031082482, -1.4328726731812922, -1.5536972762810672, -1.6762735392046202, -1.7985627354351879, -1.918474778804544, -2.0339139633787418, -2.142825278911292, -2.2432402122916058, -2.333320952888439, -2.4114019534206177, -2.4760278572079484, -2.5259868859647505, -2.5603388877041557, -2.5784373692872036, -2.579944979657462, -2.5648420644229306, -2.5334280764311106, -2.486315796347704, -2.4244184878774435, -2.348930280007838, -2.2613002294325577, -2.163200666210936, -2.0564905610983977, -1.9431747705512405, -1.8253601123150311, -1.7052092984031504, -1.5848938013787366, -1.4665467529949356, -1.352216970887866, -1.2438251792646016, -1.1431234341435546, -1.051658684071516, -0.9707412953379614, -0.9014192490550246, -0.8444585790730192, -0.8003304679658682, -0.7692052569803607, -0.7509534588594652, -0.7451536939173324, -0.7511073037873771, -0.7678592379399146, -0.7942246592563068, -0.828820580270603, -0.8701017244101448, -0.9163997095109856, -0.9659645763753804, -1.0170076349387631, -1.0677445758799733, -1.1164377967671377, -1.1614369189642757, -1.2012165237723826, -1.2344102122650158, -1.2598401910388817, -1.2765417031355821, -1.283781756729619, -1.2810717504503433, -1.2681737497278374, -1.2451003294191703, -1.212108060152286, -1.169684875265806, -1.1185317079479966, -1.0595389303856395, -0.9937582548937363, -0.9223708679373982, -0.8466526589424278, -0.7679374745901345, -0.6875793742332653, -0.6069148820828838, -0.5272262264564671, -0.4497065258385019, -0.37542782661152596, -0.3053128195028567, -0.2401109630698926, -0.18037962544759004, -0.12647072309751484, -0.07852319080564121, -0.036461464351740136, -3.1496841126988764e-16], [0.0, 0.029539478126739724, 0.055051871466536555, 0.07743310410104638, 0.09769888889980292, 0.11695340367531902, 0.1363553503817283, 0.157082304407978, 0.18029430742822758, 0.20709767926088896, 0.23851002117224313, 0.2754273550888772, 0.3185942909319974, 0.3685780390446793, 0.4257469883191181, 0.4902544555474123, 0.5620280805927678, 0.6407651984869864, 0.725934367103965, 0.8167830714678254, 0.912351466993547, 1.0114918680290887, 1.1128935389086692, 1.215112206112485, 1.31660358557715, 1.4157601118870018, 1.5109499687477495, 1.6005574550555421, 1.6830236797301072, 1.7568865623900496, 1.8208191263985114, 1.8736651056496587, 1.9144709459189726, 1.9425133642670527, 1.9573217338905056, 1.9586946844451587, 1.946710446245962, 1.9217306174964632, 1.8843971931263104, 1.8356228580020904, 1.7765747121826683, 1.7086517574462978, 1.633456628528451, 1.552762195555008, 1.4684737924820033, 1.3825879367628517, 1.297148495195834, 1.2142013177013482, 1.1357484029441203, 1.0637026761574344, 0.9998444497830562, 0.9457806017932207, 0.9029074456306454, 0.8723781810295308, 0.8550757085897055, 0.8515914654280268, 0.8622107975584739, 0.8869052302862499, 0.9253318345865494, 0.9768397191424064, 1.0404835085295996, 1.1150435020750182, 1.1990520492160361, 1.2908255296130928, 1.3885011934051963, 1.4900780020774531, 1.5934605162207631, 1.6965048052882201, 1.797065308008031, 1.8930415515105903, 1.9824236429458078, 2.063335479239481, 2.134074677857342, 2.1931483125854627, 2.2393036413841254, 2.2715531357825496, 2.2891932600359928, 2.291816599949401, 2.279317102155631, 2.2518883507731795, 2.210014975687684, 2.1544574511099484, 2.0862307005464027, 2.006577071038607, 1.916934371921601, 1.8188997882111608, 1.7141905732901046, 1.6046024975628785, 1.4919670774857001, 1.378108631759547, 1.2648022080266, 1.15373339430837, 1.0464609754709542, 0.9443833176181605, 0.8487092644924256, 0.7604342122293744, 0.680321895150487, 0.6088922690647112, 0.5464157234628622, 0.49291369391973155, 0.44816558497471237, 0.4117217557643502, 0.38292216966715414, 0.3609201689468722, 0.34471070932413705, 0.3331622806846644, 0.32505165142205855, 0.3191005073862938, 0.31401301367726897, 0.30851330959978956, 0.3013819543717396, 0.2914903734083635, 0.2778324113238509, 0.25955217672470854, 0.23596746337943292, 0.20658814988274093, 0.17112911248679796, 0.12951732996812715, 0.08189301156903227, 0.028604735330061647, -0.029801259452008795, -0.0925973293167364, -0.15889579206927582, -0.22767482581794243, -0.29780820814141556, -0.3680981009377824, -0.43731000588861335, -0.5042089572593715, -0.5675959844457513, -0.6263438671554604, -0.6794312216542497, -0.725973996739963, -0.7652535220534018, -0.7967403374062434, -0.820113137861639, -0.835272292695006, -0.8423475340034666, -0.8416995591727804, -0.8339154469240463, -0.8197979453389221, -0.8003488481058624, -0.7767468282585888, -0.7503202430232929, -0.722515555394366, -0.6948621343632777, -0.6689342933612894, -0.6463115029341807, -0.6285377669608228, -0.6170811804455818, -0.6132946902565796, -0.6183790579777202, -0.6333489767588024, -0.6590032227771412, -0.6958996283577018, -0.7443355501868455, -0.8043343751507023, -0.8756384613220527, -0.9577087560553755, -1.0497311708444748, -1.1506296275420302, -1.259085526803823, -1.3735632312462804, -1.4923410067148837, -1.6135467289517478, -1.7351975432089084, -1.855242563968672, -1.9716076234207083, -2.082241022689681, -2.1851592104068094, -2.2784913098524857, -2.360521438706105, -2.429727813920873, -2.484817707261301, -2.524757412861797, -2.5487965044859644, -2.5564857941833523, -2.5476885525110573, -2.5225847098129957, -2.481667924361866, -2.4257355724262375, -2.3558718834118566, -2.2734246060533065, -2.179975745237689, -2.0773070496900057, -1.9673610550199805, -1.8521985915042019, -1.7339537489115617, -1.6147873496685774, -1.496840015285276, -1.382185918424338, -1.2727882941405375, -1.1704577391314819, -1.0768142584456326, -0.9932539267139788, -0.9209209178935346, -0.860685526525547, -0.8131286578451586, -0.7785331073147091, -0.7568817861397735, -0.7478628820869796, -0.7508817785503913, -0.765079393375067, -0.7893564463804342, -0.8224030245446988, -0.8627326898104588, -0.908720269446486, -0.9586423853729845, -1.0107197188140922, -1.0631599714847497, -1.1142004750342744, -1.1621494168054514, -1.205424691635779, -1.2425894553112626, -1.2723835436701663, -1.2937500299780613, -1.3058563192932662, -1.308109318922653, -1.300164375193997, -1.2819278248455017, -1.2535531703941407, -1.215431048865597, -1.1681733182570964, -1.1125917322028485, -1.0496718068914104, -0.9805426020375315, -0.9064432367318073, -0.828687038847878, -0.7486242814814451, -0.6676044903111129, -0.5869393111043998, -0.5078669067694471, -0.43151880893142197, -0.3588900811667133, -0.29081356151816085, -0.22793884304392842, -0.17071652570818685, -0.11938813410410448, -0.07398194684347424, -0.03431482873161225, -2.9641798927082116e-16], [0.0, 0.02788293139352952, 0.05218641524862888, 0.07386232259483275, 0.09396485279500823, 0.11361793293564773, 0.1339805239905285, 0.1562107624698389, 0.18142989845761726, 0.21068699849821673, 0.24492536450216879, 0.28495157811378014, 0.33140801484338733, 0.3847495853332195, 0.4452253545643997, 0.5128655662872892, 0.5874744625617752, 0.6686291404748594, 0.7556845335736174, 0.8477844482002754, 0.9438784287079589, 1.0427440744139536, 1.1430142889349173, 1.2432088128520624, 1.3417692767739124, 1.4370969167105831, 1.5275920196946529, 1.6116941167034378, 1.6879219135065051, 1.7549119488238625, 1.8114549932505697, 1.8565292512680767, 1.8893295011878357, 1.9092914023335965, 1.916110312890379, 1.9097540928616927, 1.8904695112874017, 1.8587820317407378, 1.815488911342497, 1.761645712135637, 1.6985464856186014, 1.6276980475373264, 1.550788906811652, 1.4696535460768367, 1.3862328684281893, 1.3025317226396675, 1.220574494932889, 1.1423598073827617, 1.0698153899242109, 1.0047541939518274, 0.9488327905961529, 0.9035130464695996, 0.8700279951790981, 0.8493527259751604, 0.8421809938742887, 0.8489081212762293, 0.8696206127485225, 0.9040927458646661, 0.9517902356140479, 1.0118809019709114, 1.0832521038003131, 1.16453454144046, 1.2541318789472382, 1.3502554988010684, 1.4509635802197283, 1.5542035900500926, 1.6578571950062333, 1.7597865477224888, 1.8578808680531835, 1.950102236012455, 2.0345295338075284, 2.1093995210375196, 2.1731440981422554, 2.2244229068304575, 2.2621505301794764, 2.285517686570062, 2.2940059573637295, 2.2873957446656945, 2.265767318804282, 2.2294949812967437, 2.1792345339964325, 2.1159044047985316, 2.0406609308282055, 1.954868437784809, 1.8600648757291915, 1.7579238741423568, 1.6502141600925888, 1.5387573409006052, 1.4253850854464336, 1.311896745491238, 1.2000184399974636, 1.0913645819605722, 0.9874027598733396, 0.8894227963770605, 0.7985106972059366, 0.7155280769824383, 0.6410975079708625, 0.5755940870804809, 0.5191433590143821, 0.47162557342657396, 0.4326860952760193, 0.4017516342071629, 0.3780518145564287, 0.3606454760612946, 0.3484509797865123, 0.34027969702919003, 0.334871783393203, 0.330933287671858, 0.3271736169044393, 0.3223423756253405, 0.31526461892622915, 0.3048736048987866, 0.29024020110454024, 0.2705981901367424, 0.24536482877099958, 0.2141561408451336, 0.17679656265888852, 0.13332270781061908, 0.08398117222593443, 0.029220455776129813, -0.03032276961707756, -0.0938426680326355, -0.16038800871500808, -0.22889005689597833, -0.29819383882900463, -0.3670919447749948, -0.43435996629329526, -0.4987926199597658, -0.5592395896936456, -0.6146401247534512, -0.6640554600617512, -0.706698179118464, -0.7419577160367954, -0.7694212902871912, -0.7888896831397194, -0.8003873956667368, -0.8041668712249461, -0.8007066169878473, -0.7907032155333049, -0.7750573747676179, -0.7548543186204744, -0.7313389680790576, -0.7058864985180918, -0.67996898146142, -0.6551189237646272, -0.632890602049498, -0.6148201528566632, -0.6023854177704593, -0.5969665566590693, -0.5998084307326219, -0.611985720551492, -0.6343716832431933, -0.6676113694425735, -0.7121000158626687, -0.767967206462105, -0.8350672568902754, -0.9129761266425849, -1.0009950048278877, -1.0981605525360099, -1.2032616215088836, -1.3148621091966317, -1.4313294582697684, -1.5508681680312058, -1.6715575594237027, -1.7913929275960396, -1.9083291289732265, -2.0203255856648483, -2.1253916504730412, -2.221631261759245, -2.307285829399202, -2.3807743307645417, -2.4407296582485842, -2.4860303458238, -2.515826909422558, -2.529562161988758, -2.5269850058108796, -2.5081573587831634, -2.4734540338139777, -2.423555557759564, -2.3594340839429244, -2.2823327164423133, -2.1937387209077377, -2.0953512418764686, -1.9890442768772703, -1.8768257698686055, -1.7607937780226333, -1.6430907343267058, -1.525856872274096, -1.4111838970065826, -1.3010699792336666, -1.197377114307879, -1.1017918298368303, -1.0157901426289455, -0.9406075616450738, -0.8772148105320792, -0.8262998042796342, -0.7882562629865074, -0.7631791853693198, -0.7508672394275409, -0.7508319616389402, -0.762313493259408, -0.7843024267129398, -0.8155671904704984, -0.8546862707415047, -0.9000844558862818, -0.9500721974081251, -1.0028871118985752, -1.0567366030269714, -1.1098405626226686, -1.1604731155069101, -1.2070024037685663, -1.2479274617921876, -1.2819113120806456, -1.3078095117410886, -1.3246934978772493, -1.3318682140541747, -1.3288836460948892, -1.315540050059793, -1.2918868144730533, -1.2582150587137255, -1.2150442259942582, -1.1631030786081091, -1.1033056414342275, -1.0367227636120298, -0.9645500747861686, -0.8880731987472213, -0.8086311515505402, -0.7275788917279655, -0.6462500060596086, -0.5659205052092702, -0.48777466963882143, -0.4128738285152517, -0.34212887431706857, -0.27627721559977936, -0.21586475246538073, -0.1612333267111102, -0.11251395478633003, -0.06962600022266856, -0.0322822869690475, -2.7911058610218946e-16], [0.0, 0.026386230323860796, 0.04966431475785938, 0.07083263881123551, 0.09097384721436517, 0.11122127062038671, 0.13272379259200984, 0.15661009882560287, 0.18395326848312893, 0.21573666079558043, 0.2528220189159993, 0.29592065809949775, 0.34556852803334315, 0.40210584145773104, 0.4656618455491471, 0.5361451817804772, 0.6132401374057223, 0.6964089409241794, 0.7849000986531082, 0.8777626137902966, 0.9738657770091828, 1.071924072551067, 1.1705266096380842, 1.2681703692362885, 1.3632964538069001, 1.4543284453223806, 1.5397119166234974, 1.6179541047355297, 1.6876627430375803, 1.7475830625649236, 1.7966320109707332, 1.8339287999103515, 1.8588209763688022, 1.8709053186966564, 1.8700429813025055, 1.8563684500722735, 1.830292020268505, 1.7924956662340852, 1.7439223338081262, 1.6857588479724126, 1.6194127858907774, 1.5464838152766176, 1.4687301362072538, 1.3880307876583082, 1.3063446850816782, 1.2256673396618858, 1.1479862713297384, 1.075236164620437, 1.0092548280660896, 0.951741003664094, 0.904215033350166, 0.8679833252414465, 0.8441074752192161, 0.83337879127836, 0.8362988415842928, 0.853066505403653, 0.8835718524464679, 0.9273970144025945, 0.983824046504119, 1.0518496108336934, 1.130206150868606, 1.2173890723506022, 1.3116893027608663, 1.411230473933927, 1.5140098627712748, 1.6179421362779878, 1.7209048813962335, 1.8207848589378037, 1.915523905311031, 2.003163416056901, 2.081886381181001, 2.150056002990573, 2.206250011112105, 2.2492898944995963, 2.2782643939549905, 2.292546737926097, 2.2918052557022586, 2.2760071618798943, 2.2454154702041227, 2.2005791595895348, 2.1423168762587443, 2.071694609581198, 1.989997921607688, 1.8986994380215572, 1.79942241817722, 1.693901311425345, 1.583940273895184, 1.4713706627421346, 1.358008542594841, 1.2456132311957024, 1.1358478782956012, 1.030243014634424, 0.9301639278089767, 0.8367826210555062, 0.7510549920209281, 0.6737037344755313, 0.6052073200102086, 0.5457952627280999, 0.4954497116422688, 0.45391325688338824, 0.42070268085900636, 0.39512823804369696, 0.3763179107771088, 0.3632459666780236, 0.35476503905070084, 0.3496408675245982, 0.3465887741820124, 0.3443109120844156, 0.3415333093068399, 0.3370417426137887, 0.32971551042032793, 0.31855823372528974, 0.3027248947377294, 0.28154442385088174, 0.2545372638606877, 0.22142747285731598, 0.1821490706610123, 0.13684648437966213, 0.08586910280692014, 0.029760103045033296, -0.03076013797152274, -0.09481559324167035, -0.16140051354532026, -0.22940903578599384, -0.29766767778243963, -0.36496984937570326, -0.4301114559401478, -0.49192664029487515, -0.5493227033858336, -0.6013132631123468, -0.6470487538485341, -0.6858434354941193, -0.7171981686319349, -0.7408183193804976, -0.7566262811313337, -0.7647682374539602, -0.7656149375944258, -0.7597564094868603, -0.7479906911769003, -0.7313068160880082, -0.710862436743276, -0.6879566116100336, -0.6639984071085955, -0.640472078276557, -0.618899684255557, -0.6008020662819484, -0.58765916435404, -0.580870672926104, -0.5817180351567929, -0.5913287493536771, -0.6106439108675685, -0.6403898389736539, -0.6810545429883157, -0.7328696673089221, -0.7957984240114078, -0.8695298772958525, -0.9534797899698058, -1.0467980820886948, -1.1483827897753822, -1.2569002521182133, -1.3708110998605503, -1.488401475167717, -1.6078187806798838, -1.727111141599198, -1.8442696695800906, -1.9572725440826126, -2.0641298774638934, -2.16292830569514, -2.2518742478617018, -2.329334804560207, -2.393875317348309, -2.444292687309156, -2.4796436487569973, -2.4992673117808053, -2.5028014218613666, -2.4901919329493265, -2.461695648564957, -2.4178758498343633, -2.359590995916245, -2.287976746946768, -2.2044217184297956, -2.1105375250600242, -2.0081238076587056, -1.899129055924227, -1.7856081391580072, -1.6696775346054857, -1.5534692966750658, -1.4390848387725679, -1.3285496021387493, -1.2237696628585517, -1.1264912797132989, -1.0382643129782285, -0.9604103494251282, -0.8939962540137233, -0.8398137368724949, -0.7983653784229992, -0.769857399470072, -0.7541993005897948, -0.751010330177323, -0.7596325771017074, -0.7791503260442549, -0.8084151651174254, -0.8460761998817553, -0.8906146086813392, -0.9403816741796911, -0.9936393474954147, -1.0486023462730152, -1.10348075765922, -1.1565221121578655, -1.2060519147472037, -1.2505116648754686, -1.2884934658037466, -1.3187704144582304, -1.3403220731683216, -1.3523544516060995, -1.3543140677011531, -1.345895806749017, -1.32704445458843, -1.297949939672727, -1.2590364761365191, -1.2109459516435368, -1.1545160461257165, -1.0907536969601945, -1.020804639480835, -0.9459198461943887, -0.8674197613553075, -0.7866572778689636, -0.7049804296402048, -0.6236957738695859, -0.5440334144515515, -0.46711457019571023, -0.3939225213255456, -0.3252776764316113, -0.2618173921161016, -0.20398105177699463, -0.15200077155191966, -0.10589795389799374, -0.06548575637427632, -0.03037738879990989, -2.6315483490745805e-16], [0.0, 0.025057210121703827, 0.0474965605200613, 0.06835324037973478, 0.08872819524129517, 0.10975388931152423, 0.1325590463145943, 0.15823331566365645, 0.18779281445873552, 0.22214747513935848, 0.2620710840406126, 0.3081748287234123, 0.3608850834527971, 0.42042605479460987, 0.48680778568162497, 0.5598198795670235, 0.6390311598717235, 0.7237953275261692, 0.8132625248465116, 0.9063965611694716, 1.001997408461972, 1.0987284372490964, 1.1951477381679323, 1.2897427654409284, 1.3809674483608314, 1.4672808478150137, 1.547186388750728, 1.619270677525595, 1.6822409159290783, 1.7349599513127427, 1.776478054122441, 1.8060605889722345, 1.8232108414500718, 1.8276873777794775, 1.819515445484822, 1.7989920671191428, 1.7666846323842496, 1.723422952834013, 1.6702849038872447, 1.6085759371199362, 1.539802897839494, 1.4656427249929158, 1.3879067389920587, 1.308501334844868, 1.229385990260358, 1.1525295688226291, 1.0798659451148394, 1.013250000606924, 0.9544150355998943, 0.904932613569262, 0.8661758005206052, 0.8392866847218539, 0.8251489632494926, 0.8243662635545849, 0.837246733571055, 0.8637942860118111, 0.9037067250137716, 0.9563808200253315, 1.0209242267488328, 1.0961739920729592, 1.180721223220917, 1.2729413546158581, 1.371029312798291, 1.4730387633631674, 1.5769245271481493, 1.6805871781500157, 1.7819187846856366, 1.878848729377385, 1.9693885432466935, 2.051674714532924, 2.1240084831789887, 2.1848917059902218, 2.233057973448375, 2.267498274682617, 2.2874806393220006, 2.2925633306304944, 2.2826013198821054, 2.2577459335575885, 2.218437728680153, 2.1653928134536087, 2.099582986373489, 2.0222102133505673, 1.934676095561204, 1.838547097495008, 1.7355164021927025, 1.6273633366197309, 1.5159113627041647, 1.4029856575609454, 1.2903713092171658, 1.1797731317575508, 1.0727780568599987, 0.9708209884280844, 0.8751549152647912, 0.7868259658116443, 0.7066539617110134, 0.6352188865472005, 0.5728535361123973, 0.5196424606862263, 0.4754271520081777, 0.43981727179658253, 0.4122075687033777, 0.3917999902136782, 0.3776303686791908, 0.3685989495574438, 0.3635039377464813, 0.3610771669103169, 0.36002094860314104, 0.35904513396285154, 0.35690342129565233, 0.3524279679351036, 0.34456141363871357, 0.332385494194476, 0.31514551599662594, 0.2922700727458173, 0.26338551130859383, 0.2283247919232409, 0.18713053484780745, 0.14005219747810946, 0.08753747906281818, 0.030218200526484565, -0.031108949232381354, -0.09550627551780638, -0.1619229033149996, -0.2292258173831803, -0.2962332839923844, -0.36174975842711354, -0.4246013424515927, -0.4836708400071542, -0.5379314679123286, -0.5864783110656949, -0.6285566678053244, -0.6635865092605651, -0.6911823747901961, -0.7111681414763241, -0.7235862362302833, -0.7287010010864323, -0.7269960721410127, -0.7191657865628178, -0.7061007862782791, -0.6888681374224307, -0.668686427641914, -0.6468964352105951, -0.6249280813189897, -0.604264476828028, -0.5864039546700478, -0.5728210368660179, -0.5649273192869646, -0.564033266886294, -0.5713118968459809, -0.587765287212205, -0.614194785057132, -0.6511757024977313, -0.6990371830896658, -0.7578477977595872, -0.8274072915497835, -0.9072447534003611, -0.9966233246462691, -1.0945514017136666, -1.1998001286162885, -1.3109268192319286, -1.4263038018399243, -1.5441520426874604, -1.662578784807415, -1.7796183359470379, -1.8932750578556383, -2.0015675503851837, -2.1025729893854366, -2.1944705681335677, -2.2755830083170685, -2.344415148049212, -2.399688680080703, -2.4403722017244736, -2.4657058469187674, -2.4752198976955238, -2.468746914031648, -2.4464270742075604, -2.408706578663535, -2.356329135020824, -2.290320706415812, -2.2119678655781545, -2.1227902492652797, -2.0245077480399356, -1.9190031915263166, -1.8082813961582456, -1.6944255284402432, -1.5795517997917452, -1.4657635476099369, -1.3551057703418128, -1.2495211717974373, -1.150808731989514, -1.0605857593972778, -0.9802542942695245, -0.910972626507762, -0.8536325674175236, -0.8088429752384722, -0.7769198832844, -0.7578834204470156, -0.7514615506384674, -0.7571004944580872, -0.7739815369564653, -0.8010437737208294, -0.8370122073086903, -0.8804304807126371, -0.9296974270771428, -0.9831065278917457, -1.0388873074281626, -1.0952476507862672, -1.150416017483882, -1.202682532368068, -1.250437970416245, -1.2922097107940558, -1.3266938168112097, -1.3527825000821223, -1.3695863466700227, -1.376450817251193, -1.3729666790000572, -1.3589741803103883, -1.334560936793628, -1.3000536543038907, -1.2560039681119617, -1.203168822975415, -1.1424859531180347, -1.0750451407196202, -1.0020560334802642, -0.9248133836613197, -0.8446606307262184, -0.7629527858724857, -0.6810195885186725, -0.6001298919554194, -0.521458198275054, -0.44605420235266974, -0.37481612263867675, -0.3084684949555845, -0.24754498697502034, -0.19237665861278067, -0.1430859505942766, -0.09958653354585069, -0.06158899696597667, -0.028612205205776117, -2.4864427753583253e-16], [0.0, 0.023901916889567956, 0.045690448558034655, 0.06642769579219036, 0.08722275572524443, 0.1091971292589808, 0.13344964501347684, 0.16102184308787026, 0.19286475165899913, 0.22980795521445288, 0.27253179585865556, 0.3215434700742619, 0.37715768454323234, 0.439482418607763, 0.5084102105927493, 0.5836152437947486, 0.6645563590257869, 0.7504859679356043, 0.8404646887744908, 0.9333813776554675, 1.0279780874909668, 1.1228793571897313, 1.2166251187019257, 1.3077064120323811, 1.3946030209077853, 1.475822086391384, 1.5499367238486816, 1.6156236611555972, 1.671698933174953, 1.717150708961834, 1.7511683929397073, 1.773167227879551, 1.7828077338289605, 1.7800094405968456, 1.7649585089889785, 1.738108984339245, 1.7001775813448694, 1.6521320579601977, 1.5951733942117563, 1.530712145353283, 1.4603394839733335, 1.385793578888745, 1.3089220765817515, 1.231641550615248, 1.1558948633824808, 1.0836074407142386, 1.0166434918361047, 0.9567632140914416, 0.9055820034890716, 0.8645326488864455, 0.8348314204806303, 0.8174488738410253, 0.8130860811195599, 0.8221568739548523, 0.8447765410180514, 0.880757270559893, 0.9296104684144676, 0.9905559185819683, 1.0625375907239791, 1.1442457406240276, 1.2341447997482988, 1.3305064121389052, 1.4314468543443604, 1.5349679699226721, 1.6390006667766917, 1.7414499652224802, 1.8402405487117826, 1.9333617583947023, 2.0189109874652744, 2.0951344711040374, 2.160464531826088, 2.213552426578947, 2.25329604887924, 2.2788618640003646, 2.289700594661244, 2.285556325398287, 2.266468852135022, 2.2327692655212257, 2.1850689184344207, 2.124242085671472, 2.051402773466038, 1.9678762744112352, 1.8751661863019524, 1.7749177183682137, 1.6688781928287206, 1.5588557116402177, 1.4466769963003816, 1.334145421720238, 1.2230002532710036, 1.1148780595040162, 1.0112772127240353, 0.9135263071328984, 0.8227572217637021, 0.739883435497913, 0.6655840671275732, 0.6002939680705723, 0.5442000426133327, 0.4972438142612533, 0.4591301008221407, 0.42934150911310864, 0.4071583164354299, 0.39168317376501544, 0.38186994822389436, 0.37655592271882576, 0.37449649109769156, 0.37440142971512547, 0.3749717922928475, 0.37493646519483814, 0.373087434892236, 0.368312858034944, 0.35962708614318317, 0.34619687987557923, 0.32736314998018956, 0.30265768077173455, 0.2718144242690549, 0.23477509560176424, 0.19168894933178018, 0.14290676815007616, 0.08896924615119771, 0.0305900947371429, -0.03136566353693696, -0.09590762266691516, -0.16194944198645653, -0.2283410236338035, -0.2939025547170488, -0.35745950079327243, -0.4178776113105429, -0.4740969958028432, -0.5251643519398864, -0.5702624724708061, -0.6087362265218988, -0.6401142999053988, -0.6641260868357765, -0.6807132490301886, -0.6900355944866265, -0.6924710738592865, -0.6886098436190151, -0.6792424982839725, -0.665342725066631, -0.6480447794876719, -0.6286163161757659, -0.6084272317576237, -0.5889152833177684, -0.5715493336422817, -0.5577911410921309, -0.5490566557399914, -0.546677803177789, -0.5518657325866313, -0.5656764762950459, -0.5889799147875446, -0.6224328652127051, -0.6664570146950152, -0.7212223045173418, -0.7866362403164328, -0.8623394600241666, -0.9477077389117898, -1.041860453503404, -1.1436753672062567, -1.2518094441889926, -1.3647252481986465, -1.480722343365177, -1.5979729880762454, -1.7145613038622378, -1.8285250116500402, -1.9378987599840873, -2.0407580256019333, -2.1352625472380846, -2.2196982592568006, -2.292516722605174, -2.3523711059343944, -2.398147848260505, -2.4289932343550675, -2.444334232774068, -2.443893081186436, -2.427695251190623, -2.3960705815311627, -2.3496475307400497, -2.2893406637878435, -2.216331648355865, -2.132044190912341, -2.038113487126487, -1.936350891768782, -1.8287046269413043, -1.7172174414916939, -1.6039822065010254, -1.4910964800522408, -1.3806170979136405, -1.2745158447537326, -1.1746372331046073, -1.0826593651971153, -1.0000587772937837, -0.9280800691065834, -0.8677110046960477, -0.8196636387613104, -0.7843618766995376, -0.7619357218065895, -0.7522223023045418, -0.7547736084464137, -0.7688707097320508, -0.7935440681788203, -0.8275994193772399, -0.869648562226589, -0.9181442839554552, -0.9714185520407966, -1.0277230312201364, -1.085270933682639, -1.1422791848858747, -1.1970098868302095, -1.2478100849673255, -1.2931488935423423, -1.3316511057914926, -1.3621265081939224, -1.3835942295426504, -1.3953015831315572, -1.3967370006390158, -1.3876368058018995, -1.36798573097263, -1.3380112362655272, -1.2981718453245417, -1.2491398599453893, -1.1917789541855854, -1.1271172737722273, -1.056316775483222, -0.9806396310599422, -0.9014125889148005, -0.8199902327660992, -0.7377180982791383, -0.6558966063322992, -0.5757467447865652, -0.4983783803522823, -0.4247620096420267, -0.3557046656531924, -0.29183058512585114, -0.23356711630571855, -0.18113620882030465, -0.13455168115565402, -0.09362231031602476, -0.057960636488908014, -0.02699722677031896, -2.35656621128742e-16], [0.0, 0.0229245699457807, 0.044249554173665155, 0.06505398941607013, 0.08644506813270268, 0.10952349876301791, 0.13534891528583054, 0.16490626771778913, 0.19907410127686845, 0.23859558468937364, 0.28405307870617835, 0.3358469460522587, 0.39417919601512796, 0.45904243339446593, 0.5302144456910377, 0.6072586176265872, 0.6895302120055978, 0.7761884043405991, 0.8662138093944022, 0.9584310946222484, 1.051536142054331, 1.1441270998366568, 1.2347385605147578, 1.321878017869446, 1.4040636898981544, 1.4798627540583555, 1.5479290232642253, 1.6070390978734335, 1.6561260599288765, 1.6943098305352349, 1.7209233881669914, 1.7355341430787607, 1.7379598784621875, 1.7282787997521094, 1.7068333763271448, 1.674227811267717, 1.6313191310980135, 1.5792020446889985, 1.5191878748456298, 1.4527780137144706, 1.3816324903577837, 1.3075343622263544, 1.2323507487395609, 1.1579914120729857, 1.0863658553648163, 1.0193399502188318, 0.9586931225159728, 0.90607711766231, 0.8629773336284141, 0.8306776532160791, 0.8102296272605658, 0.802426759840599, 0.807784527440943, 0.8265266292680139, 0.8585778188187079, 0.903563510914707, 0.9608161975262813, 1.0293885437345638, 1.108072876062771, 1.1954266230210673, 1.2898031257702423, 1.3893871087755552, 1.4922339893144014, 1.5963121134239244, 1.6995469365490827, 1.7998661214622391, 1.895244505077669, 1.9837478900783831, 2.063574646689927, 2.133094163743362, 2.1908812650373894, 2.235745805044052, 2.2667567747928743, 2.2832603814469845, 2.284891710397201, 2.271579733085884, 2.243545583452867, 2.201294186967251, 2.1455994847389563, 2.0774836473282314, 1.9981908148890346, 1.9091560287464668, 1.8119701313119454, 1.7083415036899752, 1.6000555812164745, 1.4889331348145614, 1.3767883293595558, 1.2653875687131841, 1.1564101108332656, 1.0514113861158652, 0.9517898791989258, 0.8587583407246608, 0.7733199834077448, 0.6962501890233106, 0.6280841128283824, 0.5691104229771384, 0.5193712584106793, 0.47866833334054804, 0.446574963670366, 0.4224536443063475, 0.40547866992307063, 0.3946631687458061, 0.3888898123146391, 0.3869443766222247, 0.38755126359981446, 0.38941004826573367, 0.3912320969755122, 0.39177630655485646, 0.38988304248040073, 0.38450540592140675, 0.3747370330091954, 0.35983572325403923, 0.3392423051760756, 0.3125942731142082, 0.2797338666142737, 0.2407104092786209, 0.19577687378851952, 0.14538079018771402, 0.09014976162872292, 0.03087199190676283, -0.03152764130857801, -0.09601531786732921, -0.16147906246620772, -0.22676175945926594, -0.2906955082280599, -0.3521363964819684, -0.4099987568364091, -0.4632879839930282, -0.5111310255335327, -0.5528037178520403, -0.587754218628654, -0.6156218864888549, -0.6362510746095599, -0.6496994351062506, -0.6562404717947681, -0.6563602268220532, -0.6507481379735103, -0.6402822543713553, -0.6260091449630447, -0.6091189729465804, -0.5909163365680963, -0.572787589315705, -0.5561654475442235, -0.5424917685549353, -0.5331794351765972, -0.5295743125480483, -0.5329182482700182, -0.5443140681581824, -0.5646934768840789, -0.5947887068285801, -0.6351086710637323, -0.6859202696306885, -0.7472353747883531, -0.8188038836861279, -0.9001130793300378, -0.9903933863948592, -1.0886304511918516, -1.1935833188190523, -1.303808329071384, -1.4176882098316523, -1.5334657159576164, -1.649281046387858, -1.7632121751999672, -1.8733171561115605, -1.9776774063536045, -2.0744409463470244, -2.1618645669669587, -2.23835391656273, -2.302500544879024, -2.353115009551059, -2.38925524130021, -2.4102494741711555, -2.415713174473463, -2.4055595434423926, -2.380003320590362, -2.3395577735928716, -2.285024922478416, -2.217479206930369, -2.1382449617383092, -2.048868213050035, -1.951083443476045, -1.8467760939855884, -1.7379416719858694, -1.6266424155238097, -1.5149625212329827, -1.4049629770686107, -1.298637049224991, -1.1978674557213531, -1.1043862174010315, -1.0197381115493385, -0.9452485656151207, -0.8819967207776177, -0.8307942699820807, -0.7921705356449206, -0.7663641019197982, -0.7533211589013318, -0.7527005552757641, -0.7638853956382521, -0.7860008628949442, -0.8179377986488795, -0.8583814388168814, -0.9058445812272657, -0.9587043595141319, -1.0152417157124298, -1.0736826045184018, -1.1322399266044028, -1.189155177466711, -1.2427388122311893, -1.2914083652221242, -1.3337234248891565, -1.368416648285198, -1.3944201025576326, -1.410886341237268, -1.4172037574493137, -1.4130059011526788, -1.3981745995062966, -1.3728368746665627, -1.337355807869742, -1.2923156487040797, -1.238501610305105, -1.1768749213047045, -1.1085438205198164, -1.0347312777498647, -0.9567403012821312, -0.8759177479085529, -0.7936175831172042, -0.7111645469045554, -0.6298191642322778, -0.5507449990024375, -0.47497898761926044, -0.4034056043818583, -0.3367355082730271, -0.2754892018072047, -0.2199861005122916, -0.17033926970952912, -0.12645593713008366, -0.08804373932592768, -0.05462251061437879, -0.025541279220685522, -2.242531641306249e-16], [0.0, 0.02212754324871093, 0.0431737441291337, 0.06422461337735809, 0.08637557092911731, 0.11069706200088207, 0.1382007452356245, 0.16980716498122034, 0.20631578266914363, 0.24837818264230951, 0.29647518713544874, 0.35089851546178485, 0.41173750630882444, 0.478871292314401, 0.5519666760472178, 0.6304818096828916, 0.7136756307508387, 0.8006228571157997, 0.8902341996246423, 0.9812813142619553, 1.0724258906858606, 1.162252163841981, 1.2493020427965476, 1.3321119783709299, 1.409250640484533, 1.4793564486622, 1.54117399569852, 1.5935884251594272, 1.6356568678022874, 1.666636109077739, 1.686005748039711, 1.6934862151050856, 1.6890511395650325, 1.672933694536947, 1.6456266938013968, 1.6078763680793446, 1.5606699039918428, 1.5052169833553628, 1.442925709772091, 1.3753734499647698, 1.3042732454791477, 1.2314365630301647, 1.158733246073926, 1.0880496037670506, 1.0212456244561263, 0.9601123279041629, 0.9063302728775198, 0.86143021436068, 0.8267568580225267, 0.8034365897101886, 0.7923499663511173, 0.7941096438894842, 0.8090442904364304, 0.8371888917561495, 0.8782817049599434, 0.9317679585111407, 0.9968102361915848, 1.0723053234511402, 1.156907140434421, 1.2490552407105713, 1.3470082218643866, 1.4488812768804837, 1.552687016524852, 1.6563786151059432, 1.757894276975204, 1.8552019902411645, 1.9463435281675026, 2.0294766777404996, 2.102914718448844, 2.165162241342448, 2.21494648727622, 2.2512434917161763, 2.2732984489260737, 2.2806398476870817, 2.273087080517425, 2.2507513849868612, 2.214030135333276, 2.163594661287823, 2.1003719249314656, 2.025520531792572, 1.940401685721229, 1.846545815111618, 1.7456156979414825, 1.6393669924603267, 1.529607137298818, 1.418153617959365, 1.3067926053385357, 1.1972389559879613, 1.0910985237111586, 0.9898336688850311, 0.8947327672200096, 0.8068844156926407, 0.7271569127322092, 0.6561834554587792, 0.5943533522247084, 0.5418093975227566, 0.49845140226552925, 0.46394571934973733, 0.4377404560986923, 0.41908592530403793, 0.4070597586213745, 0.40059599316790717, 0.3985173470955036, 0.3995698249904841, 0.40245874099536416, 0.4058852178182511, 0.40858221397047484, 0.4093491497305119, 0.40708424395040715, 0.4008137377908494, 0.3897172661255515, 0.3731487405115587, 0.3506522266350394, 0.3219724309736254, 0.28705955270945677, 0.24606840409150585, 0.1993518517471655, 0.14744877909717527, 0.09106691229518432, 0.03106098539229493, -0.03159315865492609, -0.09582782901684299, -0.16051532054060128, -0.22450146319196063, -0.2866399856673222, -0.34582676951128755, -0.4010330718494779, -0.45133682030444905, -0.49595113217390757, -0.534249280303304, -0.5657854185167599, -0.5903104877112445, -0.6077828470488503, -0.6183733099981654, -0.6224644088701347, -0.6206438603388978, -0.6136923544766645, -0.6025659372716409, -0.5883733977065836, -0.5723492016731827, -0.5558226329475048, -0.5401839031437302, -0.526848075389588, -0.51721770828687, -0.5126451659159753, -0.5143955551593531, -0.5236112429897872, -0.5412788737332207, -0.56819975040954, -0.6049643663984661, -0.651931775741714, -0.7092143747520517, -0.7766685370762378, -0.8538914021504552, -0.9402239665900302, -1.0347604731776492, -1.1363639365837142, -1.2436874926208825, -1.3552011124844747, -1.4692230886780822, -1.5839555785324855, -1.6975233874200801, -1.8080150895580045, -1.9135255218131975, -2.0121986467717705, -2.1022697665416863, -2.182106078750843, -2.25024460080153, -2.3054265468608013, -2.34662732292975, -2.3730814067152983, -2.3843014984903106, -2.380091463788701, -2.3605527353818987, -2.326083996964819, -2.277374130577055, -2.2153885701152958, -2.141349360451395, -2.05670937182737, -1.963121258693175, -1.862401877583744, -1.756492986940183, -1.6474191403253662, -1.5372437511102792, -1.4280243497927214, -1.3217680736110167, -1.2203884215890786, -1.1256642767661686, -1.0392021419036321, -0.9624024567892299, -0.8964307663010024, -0.8421943910766572, -0.8003251198402569, -0.771168297419818, -0.7547785287982035, -0.7509220609351438, -0.7590857444554233, -0.7784923205129153, -0.8081216280322661, -0.8467371867498056, -0.8929174854134777, -0.9450911952062926, -1.0015754385593432, -1.0606161751672276, -1.120429721825005, -1.1792444017119732, -1.2353413223956669, -1.2870933099531097, -1.333001078435457, -1.3717257880826426, -1.4021172403237907, -1.4232370702721335, -1.4343764252945201, -1.4350677580896916, -1.425090511041295, -1.4044706217136935, -1.3734739334136887, -1.3325937459171073, -1.2825328860039604, -1.224180811780843, -1.1585863855782188, -1.086927054521023, -1.0104752631294465, -0.9305629864391833, -0.8485453135952913, -0.7657640296989836, -0.6835121374928549, -0.6030002304801886, -0.5253255761058279, -0.4514446930723964, -0.38215011265747667, -0.31805190245627873, -0.259564405150737, -0.20689850790758166, -0.16005961331939345, -0.11885133409782787, -0.08288478477801657, -0.05159319827170734, -0.024251456895743807, -2.144783963361557e-16], [0.0, 0.02151136596317517, 0.04245922678000075, 0.06392671487821748, 0.0869878905945, 0.11267390951174294, 0.1419402699511169, 0.17563602552754193, 0.21447579795006336, 0.25901535400783, 0.3096314197157169, 0.36650629618703917, 0.4296177186812489, 0.49873426554201605, 0.5734164807911687, 0.6530237265828587, 0.7367266332767215, 0.8235248693127415, 0.9122698140513466, 1.0016915878082293, 1.090429777745325, 1.1770670990282774, 1.260165150273529, 1.3383013628637774, 1.4101062067670258, 1.474299702049756, 1.5297262957407478, 1.5753871978937048, 1.6104693278356783, 1.6343701003212956, 1.6467173797450043, 1.647384046304558, 1.6364967482317032, 1.614438555716358, 1.5818453814662425, 1.5395961862806011, 1.488797141779345, 1.430760072705662, 1.3669756442770407, 1.2990818923332161, 1.2288288122155884, 1.1580398234484561, 1.0885710088304033, 1.0222690864159714, 0.9609291095357804, 0.9062529024992009, 0.8598092275740016, 0.8229966424722489, 0.797009947720858, 0.7828110413677561, 0.7811048964249501, 0.7923212567302006, 0.8166025124092109, 0.8537980700970572, 0.9034653790746152, 0.9648776162364776, 1.0370378741825659, 1.1186995415806071, 1.2083924170629732, 1.3044539609061208, 1.4050649659366445, 1.5082888235113314, 1.6121134746056518, 1.7144950721082186, 1.8134023399151762, 1.9068605983317988, 1.9929944340046553, 2.070068025905304, 2.136522195942548, 2.1910073321907606, 2.2324114325359203, 2.2598826343098213, 2.2728457283195507, 2.2710123003304767, 2.2543842959869145, 2.223250962616722, 2.178179279518999, 2.1199981433202417, 2.0497767230295434, 1.9687975369289759, 1.87852492706721, 1.7805697138947698, 1.676650900919916, 1.5685553650890733, 1.458096511352577, 1.3470728885836531, 1.237227758288766, 1.1302105775970697, 1.0275413046583968, 0.9305783592025069, 0.8404909755468939, 0.7582365722087739, 0.6845436343327131, 0.6199004656028174, 0.5645500186615541, 0.5184908609930957, 0.4814841805357659, 0.45306658576075315, 0.43256831230061316, 0.4191363159595029, 0.41176161334944306, 0.40931012938711037, 0.4105562279484738, 0.41421804012738267, 0.4189936652620804, 0.42359730409656654, 0.42679439145924036, 0.4274348274000905, 0.4244834599721748, 0.4170470483486071, 0.4043970297775963, 0.3859875255593108, 0.36146814692343177, 0.3306912981918267, 0.29371381845553834, 0.250792950528107, 0.20237677341795318, 0.14908937825597243, 0.09171120388411434, 0.031155073709378443, -0.0315614132158527, -0.09534638942778646, -0.15906630189020607, -0.2215796936322855, -0.281771275806803, -0.33858537354660034, -0.3910578442979371, -0.4383456057776238, -0.47975297137534667, -0.5147540721821837, -0.5430107448278866, -0.5643853804385988, -0.5789483593607467, -0.5869798355779348, -0.5889657804638113, -0.58558834398725, -0.5777107389644909, -0.5663569967039015, -0.5526870767934647, -0.537967936423759, -0.5235412723943831, -0.5107887390616869, -0.5010955156302351, -0.49581314454527287, -0.4962225880264675, -0.5034984512872366, -0.5186752985950597, -0.542616942529573, -0.5759895186558008, -0.6192390689786748, -0.6725742501312354, -0.7359546588894553, -0.8090851313213724, -0.891416226015737, -0.9821509499901067, -1.080257631801458, -1.184488693889545, -1.2934049290586156, -1.405404747907327, -1.5187577383938748, -1.6316417687171465, -1.7421827730684343, -1.8484962888775822, -1.9487297657508988, -2.0411046416323884, -2.1239571814884295, -2.1957770980907356, -2.255243022721466, -2.3012539647255976, -2.3329559911014437, -2.3497634685410005, -2.351374337828123, -2.3377790311917206, -2.3092627936824783, -2.26640132624036, -2.2100498270370488, -2.1413256650430372, -2.061585071748072, -1.9723943798502694, -1.8754964680377186, -1.772773185537412, -1.6662046261051142, -1.5578261962344147, -1.4496844747439728, -1.3437928892835669, -1.242088238996099, -1.1463890715009522, -1.0583568770481646, -0.9794609942497309, -0.9109480319063707, -0.8538165023225225, -0.8087972358145649, -0.776340006947656, -0.7566066537917746, -0.7494708158179554, -0.7545242577653254, -0.7710895897614638, -0.7982390420006267, -0.8348188090744021, -0.8794783480843409, -0.9307038991167585, -0.9868553993129205, -1.0462058849572584, -1.1069824215568649, -1.1674075710682883, -1.2257403989288602, -1.2803160414550667, -1.329582895963761, -1.3721365605485805, -1.4067497361387968, -1.4323974080983006, -1.4482767455419112, -1.4538212907113555, -1.4487091547993112, -1.4328650869354205, -1.4064564359035308, -1.369883175741419, -1.3237623129195946, -1.26890713067524, -1.2063018518851572, -1.1370724125003493, -1.0624541303218142, -0.9837571265112818, -0.9023304079482696, -0.8195255461628275, -0.7366608924681516, -0.6549872490595292, -0.575655872801467, -0.4996896233378568, -0.42795798172618527, -0.36115656221843095, -0.2997916207428452, -0.24416993212157856, -0.1943942674368619, -0.15036455680567737, -0.11178467484690129, -0.07817464007496139, -0.0488878790278881, -0.023133074688005142, -2.0635977570917997e-16], [0.0, 0.021074742000610363, 0.042098639312604415, 0.06414229693489497, 0.08824919764410959, 0.11540270570730425, 0.14649463974073212, 0.1822962652532775, 0.22343249573361354, 0.27036000912056696, 0.3233498861990384, 0.3824752614134854, 0.44760434771051805, 0.518399058560515, 0.5943193057587166, 0.6746329046196806, 0.7584308724717527, 0.8446477656196894, 0.9320865677436031, 1.0194475224017705, 1.105360196971065, 1.1884179776889625, 1.2672141277140723, 1.340378494061668, 1.4066139261203292, 1.4647314688682025, 1.5136834179466718, 1.5525933708890896, 1.580782477937744, 1.597791185357057, 1.6033958717973273, 1.5976199014555577, 1.5807387534989992, 1.553279032125248, 1.5160113121560006, 1.469936927478052, 1.416268960177443, 1.3564078331215466, 1.291912044421181, 1.2244647052629793, 1.1558366499588395, 1.0878469760137242, 1.022321940314083, 0.9610531834411626, 0.905756276420505, 0.8580305823146949, 0.8193213989309059, 0.7908852991246872, 0.7737595128972874, 0.7687361024217532, 0.7763415695229426, 0.7968224076679695, 0.8301369702792384, 0.8759538775630218, 0.9336570286875983, 1.002357128826447, 1.0809094851359775, 1.1679376759535245, 1.261862557033863, 1.360935940919754, 1.463278173682078, 1.5669187399992748, 1.669838955150938, 1.7700157527429383, 1.8654655510740417, 1.9542871796253531, 2.034702870233604, 2.105096364527048, 2.1640472590022797, 2.21036079998847, 2.243092450454078, 2.2615666764720492, 2.2653895400913036, 2.254454833965974, 2.2289436477367395, 2.1893174130639137, 2.136304629552139, 2.070881623797006, 1.9942478347768533, 1.9077962473865184, 1.8130797089525126, 1.7117739583559817, 1.605638271649626, 1.4964746800246627, 1.3860867444533334, 1.2762388756713294, 1.1686171683386586, 1.0647926747886993, 0.9661879778857962, 0.8740478358567038, 0.7894145667440766, 0.7131087190089892, 0.645715440829357, 0.5875768171588183, 0.5387902942105768, 0.499213159435778, 0.4684728950451868, 0.4459830783972543, 0.4309643667263398, 0.4224699800639997, 0.4194149878544243, 0.42060861433550695, 0.42478870745073766, 0.4306574675681847, 0.43691750675755714, 0.44230730738463864, 0.4456351703052191, 0.4458107873703035, 0.4418736391112945, 0.4330175046360529, 0.4186104747137435, 0.398209978095442, 0.37157246226998447, 0.33865750975325126, 0.29962631610085616, 0.25483460244014583, 0.20482017972420197, 0.1502855204638834, 0.09207582289010888, 0.031153169071765754, -0.03143252048103491, -0.09457495031533199, -0.15714448355507218, -0.21802185649570843, -0.27613166729732824, -0.33047473706679414, -0.3801584700556491, -0.42442439059546627, -0.4626721064687938, -0.49447903986028013, -0.5196153755485435, -0.5380537988524297, -0.5499737299398936, -0.5557599030621099, -0.5559952855061894, -0.551448477872106, -0.5430558809583447, -0.5318990514455151, -0.5191777952214055, -0.5061796603704262, -0.4942465886637581, -0.48473956234779925, -0.4790021401202219, -0.47832381090656056, -0.48390410546461726, -0.49681839358954266, -0.5179862590008563, -0.5481432856820442, -0.5878170098985129, -0.6373076932585966, -0.6966744564090666, -0.7657271831022872, -0.8440244636249903, -0.930877698405298, -1.0253613306744005, -1.1263290251133777, -1.232435461234366, -1.3421632695133037, -1.4538545085181955, -1.5657459657068291, -1.6760074661021214, -1.7827822941750253, -1.884228776979392, -1.9785620423655808, -2.0640949558587045, -2.1392772538429528, -2.20273192876603, -2.2532879832959747, -2.2900087532843374, -2.312215102035225, -2.3195029082822303, -2.3117544045395637, -2.2891430678679576, -2.2521319180512878, -2.201465234997286, -2.138153864037247, -2.0634544308826483, -1.9788429335676339, -1.8859833132131958, -1.7866917256082828, -1.6828973384810717, -1.5766005624187343, -1.4698296846577932, -1.3645969129161966, -1.2628548501480883, -1.1664544102436634, -1.0771051495400157, -0.9963389304208196, -0.925477752702081, -0.8656064879047463, -0.8175511333688186, -0.7818630703608863, -0.7588096661185182, -0.7483714076871969, -0.7502455991545124, -0.763856497286364, -0.7883716074385908, -0.822723715682509, -0.8656380978900733, -0.9156642253505068, -0.9712111822623359, -1.0305859256688454, -1.0920334551040507, -1.1537779188816346, -1.2140636675141663, -1.2711952725271547, -1.3235755606673756, -1.3697407683428031, -1.408391997649124, -1.4384222515796685, -1.4589384395434866, -1.4692778722694781, -1.4690189043421453, -1.4579855295149862, -1.436245884916082, -1.4041047715390405, -1.362090446244735, -1.3109360812225628, -1.2515564169969184, -1.1850202514088484, -1.1125195066987963, -1.0353356974292347, -0.9548046815623614, -0.872280614123206, -0.7891000366719132, -0.7065470260044018, -0.6258202924123423, -0.5480030623582854, -0.4740365040148391, -0.4046973587558396, -0.34058032982163927, -0.28208565386967727, -0.2294121451634495, -0.1825558592037694, -0.14131437629332344, -0.10529655955673467, -0.07393750000883326, -0.04651822696415797, -0.022189638806084894, -1.9990768281194183e-16], [0.0, 0.020814588163810134, 0.04208117084905372, 0.06484846996642576, 0.09012062533697406, 0.11882530699371477, 0.1517838623459178, 0.18968430761250338, 0.23305790007180827, 0.2822599358042103, 0.33745530903552046, 0.39860924665870257, 0.46548349810920475, 0.5376381198614756, 0.6144388489599464, 0.6950699148591915, 0.7785519970990951, 0.8637649015754131, 0.9494744038075073, 1.0343625968204924, 1.117060986880111, 1.1961855047699679, 1.2703725455389934, 1.3383151171113519, 1.3987981687265176, 1.4507321841722092, 1.4931841619099937, 1.5254051636163093, 1.5468536929550842, 1.5572142656227095, 1.556410647445598, 1.5446133667315658, 1.522241246998078, 1.4899568531734981, 1.4486558947591592, 1.3994507795240934, 1.3436486573537139, 1.2827244322531755, 1.218289347762239, 1.1520558639858154, 1.0857996402448569, 1.021319513586063, 0.9603964181146636, 0.9047522219186421, 0.8560094663846027, 0.815652976699217, 0.7849942726126475, 0.7651396460229192, 0.7569626880976403, 0.7610819454838622, 0.7778442651487549, 0.8073142534417106, 0.8492701303176579, 0.9032061078241426, 0.9683412666242358, 1.0436347492865379, 1.127806938102335, 1.2193661419718271, 1.3166401849328124, 1.4178121714096585, 1.5209596031084545, 1.6240959421232595, 1.7252136562120537, 1.8223277467806227, 1.9135187487424592, 1.9969742043781096, 2.0710276502781615, 2.134194216512804, 2.1852020188547097, 2.2230186261896927, 2.2468720037002434, 2.256265465101925, 2.250986310906053, 2.231107980862205, 2.196985703708701, 2.1492457823473003, 2.088768803783056, 2.016667206951729, 1.9342577744033917, 1.8430297325031686, 1.744609246482514, 1.6407211788837304, 1.5331490407260806, 1.4236941026534096, 1.314134647535635, 1.2061863362100584, 1.101464624575373, 1.001450113987173, 0.9074576393041572, 0.8206098019787116, 0.7418155417270326, 0.6717542124180305, 0.6108654890932045, 0.5593452869387087, 0.5171477232176077, 0.4839930033604953, 0.4593809663232813, 0.4426098855681092, 0.43279999403270253, 0.4289210873750533, 0.42982346241127195, 0.43427136937902805, 0.44097809935116117, 0.4486417931599877, 0.45598104637857506, 0.4617693964664174, 0.46486781276494543, 0.464254366688815, 0.45905033671717904, 0.44854209864666605, 0.4321982635633473, 0.40968165126276007, 0.3808558222039804, 0.345786033086499, 0.3047346261849376, 0.25815100699242777, 0.20665650485428527, 0.1510245435763665, 0.09215667012427782, 0.031055096430970642, -0.03120750069798976, -0.09352010582136888, -0.1547665516985502, -0.21385887364511472, -0.2697699337332117, -0.32156443562936976, -0.3684274919288019, -0.40968996847911104, -0.44484991281183467, -0.4735894743371051, -0.49578683987215827, -0.5115228364462809, -0.5210819909148084, -0.5249479792494474, -0.5237935438294606, -0.5184651009586141, -0.5099623995307865, -0.49941372174331417, -0.4880472347056589, -0.4771592047030823, -0.4680798711142727, -0.46213784235062977, -0.4606239199799546, -0.4647552782526703, -0.47564092396577823, -0.4942493359629521, -0.521379135146906, -0.5576335658117794, -0.6033994790712275, -0.6588314013466976, -0.7238411479229679, -0.7980933064907804, -0.881006771704725, -0.971762362640577, -1.0693164043309686, -1.1724200060297063, -1.2796436261961461, -1.3894063809568167, -1.5000094323221866, -1.6096726877328993, -1.7165739562194788, -1.8188896407695054, -1.9148360030897906, -2.002710016963694, -2.080928830395228, -2.1480668846719615, -2.2028897897467288, -2.2443841287369484, -2.2717824581267303, -2.2845828821821317, -2.282562707456472, -2.265785822989075, -2.234603600497926, -2.1896492629207205, -2.1318258253200173, -2.0622878656435146, -1.9824175303766949, -1.8937953181410976, -1.7981663094068467, -1.6974026196464882, -1.593462943791274, -1.488350129548682, -1.3840677642979735, -1.282576783748378, -1.1857531097495582, -1.0953472996097668, -1.012947140618531, -0.9399440523820173, -0.8775040678027978, -0.8265440533193525, -0.7877137030629723, -0.7613837029717881, -0.7476403130133157, -0.7462864621210098, -0.7568492949950469, -0.7785939563436957, -0.8105432501888873, -0.8515026731250707, -0.900090194269799, -0.9547700441294259, -1.0138896823864951, -1.0757190429057528, -1.1384911047536, -1.2004428118824968, -1.2598553619215882, -1.3150929062209904, -1.364638748313957, -1.4071281951093284, -1.4413773026831616, -1.466406864279935, -1.4814611093928034, -1.4860207165234671, -1.479809885078123, -1.4627973602711817, -1.435191455187834, -1.3974292625670637, -1.3501603917304688, -1.2942256998673378, -1.2306316082948487, -1.1605207003611147, -1.0851393857544787, -1.0058034839841357, -0.9238626260699219, -0.8406643969333539, -0.7575191411005264, -0.6756663311770603, -0.5962433527843644, -0.5202574924687097, -0.44856182825689034, -0.381835618271733, -0.32056966380717433, -0.2650569925321353, -0.2153890683706155, -0.17145759062416344, -0.13296179971180697, -0.09942106417747586, -0.0701923869658058, -0.04449234184807345, -0.021422836501936444, -1.9511555178739183e-16], [0.0, 0.020726090331266135, 0.042392719809300435, 0.06601775114034217, 0.09255774611647785, 0.12287744338178717, 0.1577217096213061, 0.19769072619185685, 0.24321909003694084, 0.2945594070075323, 0.35177083998654557, 0.41471294640652534, 0.4830450030839195, 0.5562308742214082, 0.6335493345440293, 0.7141096174769325, 0.7968718216426757, 0.8806716812226567, 0.9642490901405131, 1.0462796695349648, 1.12540858517116, 1.200285758429562, 1.2696015729531391, 1.3321221600358266, 1.3867233499433624, 1.4324224035399056, 1.4684066882408404, 1.494058533251609, 1.508975589577191, 1.5129861281972834, 1.506158832459746, 1.4888067751373102, 1.4614854134085071, 1.4249845827345036, 1.380314619550496, 1.328686889175725, 1.2714891357250429, 1.2102562015754532, 1.1466367818317798, 1.0823569812870775, 1.0191815250118155, 0.9588735368075093, 0.9031538407049868, 0.8536607583985663, 0.8119113694805304, 0.7792651716552471, 0.7568910254330007, 0.7457381933614137, 0.746512189417014, 0.7596560420158279, 0.7853374469143349, 0.8234421471387453, 0.8735737293772559, 0.9350598735876385, 1.0069649386288029, 1.0881086152725972, 1.1770902326866008, 1.2723181689472702, 1.3720436936570328, 1.4743984642931138, 1.577434810112964, 1.679167870428966, 1.7776186094830773, 1.870856709090761, 1.9570423431981605, 2.0344658654335417, 2.101584490973764, 2.157055126358862, 2.1997625935026344, 2.228842604798349, 2.243698972199582, 2.2440146713868048, 2.229756529232726, 2.201173455161542, 2.1587882909411444, 2.1033835052007346, 2.0359811048351792, 1.9578172718966917, 1.870312358275346, 1.775036978441103, 1.673675030161117, 1.5679845422711933, 1.4597572956306, 1.3507781872327425, 1.2427853075617077, 1.1374316777423037, 1.0362495464778747, 0.940618078420842, 0.8517351772251631, 0.7705940803290786, 0.6979652411862214, 0.6343838812475443, 0.5801434518315505, 0.5352950986511802, 0.4996530728582924, 0.4728058857167401, 0.4541328630562436, 0.44282562397319647, 0.43791388907444556, 0.4382949198305517, 0.4427658048499539, 0.45005774318524266, 0.45887143071365993, 0.4679126342290016, 0.4759270396068376, 0.4817334851456574, 0.48425473825497, 0.48254504181142505, 0.47581374396473336, 0.46344442969465166, 0.44500909132294514, 0.4202770054381992, 0.3892181219840653, 0.3520009140837381, 0.30898478090620185, 0.26070723688596276, 0.20786625532273814, 0.15129825940780733, 0.0919523658933608, 0.030861583109730337, -0.03088825659098238, -0.09219099160389883, -0.15195317797045055, -0.2091267990901768, -0.2627407575390668, -0.3119302995290987, -0.3559635756272198, -0.3942646149410517, -0.42643208221846607, -0.45225329587326685, -0.4717131071014364, -0.48499737290910083, -0.492490895684897, -0.494769845382666, -0.49258882380712093, -0.4868628702831957, -0.4786448405934861, -0.4690987131178377, -0.4594694844949134, -0.4510504090761385, -0.44514840959433905, -0.44304853892663343, -0.4459784032134372, -0.4550734640728826, -0.47134412196485165, -0.4956454442326905, -0.5286503408770784, -0.5708269101395113, -0.6224205764519067, -0.6834415276704796, -0.753657829590466, -0.8325944567050508, -0.9195383324576812, -1.0135493234466886, -1.1134769838644107, -1.2179827025725518, -1.3255667692162063, -1.4345997510574873, -1.5433574618918218, -1.6500587112705736, -1.7529049486491732, -1.8501208648879968, -1.9399949841068151, -2.0209192730255316, -2.091426812827071, -2.1502266198801223, -2.1962347654093155, -2.2286010288929825, -2.2467304235809604, -2.250299052564187, -2.239263887394195, -2.2138662051071174, -2.1746285701591868, -2.122345401563423, -2.0580673186837326, -1.9830796079569206, -1.8988752936430624, -1.8071234251098145, -1.7096333079742574, -1.6083155038492238, -1.5051405010870975, -1.4020960148834136, -1.3011439080255993, -1.204177732644261, -1.1129818783230025, -1.0291932732165747, -0.9542665233633966, -0.8894432926621884, -0.8357266240379623, -0.7938607836438041, -0.7643170774344866, -0.7472859463443823, -0.7426754961016339, -0.7501164640791621, -0.7689734722675334, -0.7983622661897566, -0.8371724979942938, -0.8840954814975948, -0.9376562307609783, -0.9962489946832257, -1.0581754204500875, -1.121684420403472, -1.185012781345694, -1.2464255432859215, -1.3042551863940024, -1.3569387000923432, -1.4030516658545578, -1.441338563903381, -1.4707386116079904, -1.4904065555061037, -1.4997279666503451, -1.4983287272014016, -1.4860785414107112, -1.463088452736574, -1.4297024971269416, -1.3864837668037577, -1.3341952956289036, -1.2737763029476166, -1.206314444598222, -1.1330148148095163, -1.0551665186647692, -0.9741076898601831, -0.8911898613171398, -0.8077426060700799, -0.7250393525691076, -0.6442652425107326, -0.5664878415117169, -0.49263143488334926, -0.4234555444641627, -0.3595381903999211, -0.30126429678322936, -0.24881950536362313, -0.20218952053413025, -0.1611649650673499, -0.12535158325253826, -0.09418548978738939, -0.06695303249886679, -0.0428147179967464, -0.020832544703980375, -1.919601749629227e-16], [0.0, 0.0208027769275336, 0.04301608356532208, 0.06761840789336324, 0.09551110024549772, 0.127489455834434, 0.1642166785505628, 0.20620143497030513, 0.2537796149564986, 0.30710080672801593, 0.36611987255734124, 0.4305938793969023, 0.5000845000690537, 0.5739658586867652, 0.6514376522950026, 0.7315432429260604, 0.8131922838420995, 0.8951873240104913, 0.9762537288739556, 1.055072165948974, 1.1303128330148544, 1.2006705564775815, 1.264899859229376, 1.3218490917520194, 1.3704927375376055, 1.4099610437599173, 1.4395661895936274, 1.4588242861756142, 1.4674726019549527, 1.4654815226502231, 1.453060883391405, 1.4306604487079937, 1.3989644604246645, 1.358880320665348, 1.3115216233942668, 1.2581858896006364, 1.2003274948296598, 1.1395263999357077, 1.0774534036197572, 1.0158327257997855, 0.9564028018575783, 0.9008762174932579, 0.8508997410077518, 0.8080154135871951, 0.7736236384204185, 0.7489491666590644, 0.7350108133175834, 0.7325956507413705, 0.7422383232887741, 0.7642060068789019, 0.7984894039521299, 0.8448000214008937, 0.90257382962909, 0.9709812487255468, 1.0489432564997094, 1.1351532665160111, 1.2281042858580766, 1.326120735537581, 1.4273942043366616, 1.5300223121809318, 1.6320497842004518, 1.7315107832840555, 1.8264715184758364, 1.9150721397485488, 1.9955669466860575, 2.0663619790014276, 2.1260491196219933, 2.17343592475261, 2.2075704978375064, 2.2277608431740656, 2.233588267184432, 2.2249145377923587, 2.201882661505479, 2.164911290028095, 2.1146829198158077, 2.0521261952398326, 1.9783927653748783, 1.8948292724781812, 1.8029451638882172, 1.7043771155972653, 1.6008509328249267, 1.4941418487039664, 1.3860341753762033, 1.2782812716330574, 1.1725667775476698, 1.0704680297371347, 0.9734225119373058, 0.8826981159859537, 0.7993678901150189, 0.7242898371273441, 0.6580921974479338, 0.6011645143867146, 0.5536546346628569, 0.5154716499103504, 0.4862946381683433, 0.4655869218916999, 0.4526154243176601, 0.4464745824126221, 0.44611416513522484, 0.4503702530661396, 0.45799856182530785, 0.46770923889805616, 0.4782022327740121, 0.48820232536463637, 0.4964929336345071, 0.5019478238131396, 0.5035599404430955, 0.5004666313258221, 0.4919706461134177, 0.47755639838193237, 0.45690110564775716, 0.42988055578130624, 0.3965693882290118, 0.35723592082864797, 0.31233169419054796, 0.2624760420493209, 0.20843612422134017, 0.151102975596359, 0.0914642270016506, 0.030574239222618736, -0.03047754220775051, -0.09059915829689116, -0.14872875719620768, -0.20386638627596423, -0.2551040992963332, -0.301653565776797, -0.3428704340540658, -0.3782747831924382, -0.40756709975857225, -0.4306393309495928, -0.44758069275401974, -0.4586780475164016, -0.4644108060393277, -0.4654404516301576, -0.4625949236818213, -0.4568482329134262, -0.44929580587026796, -0.4411261695006277, -0.43358968469786374, -0.4279651181062352, -0.4255249021621856, -0.427499972695538, -0.43504509039522915, -0.44920554655837563, -0.4708861248680069, -0.5008231401326855, -0.5395603031745048, -0.5874290701005614, -0.6445340262504496, -0.7107437328210164, -0.7856873305359634, -0.8687570530476701, -0.9591166565356535, -1.055715624825256, -1.1573088649475098, -1.2624814699929443, -1.3696779978260072, -1.4772355989346682, -1.583420227289774, -1.6864650870906106, -1.784610407737371, -1.8761436008559462, -1.9594388377233867, -2.0329950934536765, -2.095471735674427, -2.1457207894511074, -2.1828150856313435, -2.2060715947934906, -2.215069361311829, -2.2096615789854694, -2.189981488146626, -2.1564419208054115, -2.109728471636245, -2.0507864247813083, -1.980801715828263, -1.9011763512657995, -1.8134988407392931, -1.7195103172676405, -1.6210671243098012, -1.5201007336468495, -1.418575922389184, -1.3184481794526732, -1.2216213305408639, -1.12990636556426, -1.0449824236442513, -0.9683608390921863, -0.9013530782875557, -0.8450433039996517, -0.8002661926870579, -0.767590504381997, -0.747308766999122, -0.7394332906648986, -0.7436985765141466, -0.7595700320306339, -0.7862587551313251, -0.8227420054561257, -0.8677888472186924, -0.9199903267503946, -0.9777934424591443, -1.0395380778654146, -1.1034960017522648, -1.167910994852231, -1.2310391409247163, -1.2911883220178733, -1.3467559830441829, -1.3962642788380812, -1.4383917863581765, -1.4720010538706623, -1.4961613655471635, -1.5101662212467966, -1.513545164288029, -1.506069731427639, -1.4877534455281873, -1.458845918877176, -1.4198212801628525, -1.3713612771253723, -1.3143335364573108, -1.249765579436608, -1.1788152931719351, -1.1027386407515918, -1.0228554569918635, -0.9405142183619473, -0.8570566950425704, -0.773783389540227, -0.6919206399877476, -0.6125902179420781, -0.5367821814184974, -0.4653316558710341, -0.3989001111064858, -0.33796158338414295, -0.28279416223141174, -0.23347692409461182, -0.18989235333001206, -0.1517341488091592, -0.11852017516241001, -0.08961018493383026, -0.06422781502062783, -0.04148625082181809, -0.02041685729585934, -1.9040217631105167e-16], [0.0, 0.02103660874656932, 0.043931178091114284, 0.06961484159809968, 0.09892677057971053, 0.13258708105913228, 0.17117299595701208, 0.2150989132629351, 0.2646009300341967, 0.31972625689008777, 0.38032783115114227, 0.44606430210696146, 0.5164054224886516, 0.5906427396005386, 0.6679053412926946, 0.7471802795380478, 0.8273371711795466, 0.9071563645709105, 0.9853599651797038, 1.0606449352074634, 1.1317174239229975, 1.1973274482265681, 1.2563030279605962, 1.3075828880990232, 1.3502468700586003, 1.3835432462940942, 1.4069122048311942, 1.4200048617044811, 1.4226972671775577, 1.4150989934836196, 1.397556024638389, 1.3706478093648435, 1.3351784828530777, 1.2921624083691563, 1.2428043320108395, 1.1884745796387535, 1.130679850797034, 1.0710302771246067, 1.011203509511985, 0.9529066766320341, 0.897837115469732, 0.8476428105985813, 0.8038834922407647, 0.7679933332073599, 0.7412461518198717, 0.7247239726098766, 0.7192897202765567, 0.725564726869038, 0.7439116197446081, 0.7744230312478184, 0.816916433325292, 0.870935254781071, 0.9357562891278115, 1.0104032506490397, 1.0936661890252866, 1.1841263322887343, 1.280185797393905, 1.3801014905178284, 1.4820224182005166, 1.5840295480798348, 1.6841772962828316, 1.7805356790221836, 1.87123214958296, 1.9544921490760214, 2.028677429908383, 2.0923212641334716, 2.1441597233971246, 2.183158311268158, 2.208533340037574, 2.2197675698699912, 2.216619765422726, 2.1991279703624684, 2.1676064500615295, 2.1226364034921192, 2.0650506932867354, 1.9959129844965637, 1.9164918143196907, 1.8282302337940044, 1.7327117652869441, 1.6316235040906362, 1.5267172565263256, 1.419769649159878, 1.3125421630553282, 1.2067420430344273, 1.1039850048297546, 1.0057606135483579, 0.9134011362837421, 0.8280545818257793, 0.7506625334923275, 0.6819432598308559, 0.6223804553490582, 0.5722178228395015, 0.5314595637643832, 0.4998766971657251, 0.4770189842811593, 0.4622320990176282, 0.45467955704321417, 0.4533688016323187, 0.4571807453485327, 0.4649019855861225, 0.4752588508754005, 0.4869523951484082, 0.4986934397818202, 0.5092367685469751, 0.5174136083989884, 0.522161578562456, 0.5225513603140487, 0.5178094284070023, 0.5073362899521668, 0.4907197950826218, 0.4677432128642587, 0.4383879023921479, 0.4028305493711897, 0.3614350791666338, 0.3147394947685568, 0.26343801887311563, 0.2083590400431666, 0.15043947062716628, 0.0906962160746819, 0.030195529174269927, -0.029978923303594772, -0.08875842140495746, -0.14512110951288434, -0.19812261167179002, -0.2469245196635585, -0.29081998385692404, -0.32925571173993606, -0.3618497718565804, -0.3884047092583455, -0.40891559981151654, -0.42357280170806644, -0.4327593000002117, -0.4370426804385421, -0.4371619087849948, -0.43400922754901916, -0.4286076103117942, -0.42208433119841804, -0.4156413106384668, -0.4105229856705606, -0.4079825214554244, -0.4092472285890806, -0.4154840769886562, -0.42776620083643346, -0.44704127015339656, -0.47410256343829493, -0.5095635134158977, -0.5538364157861281, -0.6071158909486623, -0.6693675734382091, -0.7403223760745058, -0.8194765387567086, -0.9060975288028696, -0.9992357142961314, -1.0977415876629257, -1.200288177265899, -1.3053981536256958, -1.4114750172740602, -1.5168376501890173, -1.6197574249208662, -1.7184969971137545, -1.8113498599144011, -1.8966797139688003, -1.9729587050201505, -2.0388036026476497, -2.09300903796421, -2.134576984098091, -2.1627417494570653, -2.17698985805292, -2.1770743110386364, -2.163022856181838, -2.1351400340511075, -2.0940029177736275, -2.0404506137275495, -1.9755677397904745, -1.9006622421331965, -1.817238047497224, -1.7269631721015672, -1.6316340177487079, -1.5331366776622128, -1.433406146835358, -1.334384382429538, -1.2379781877868843, -1.146017898222812, -1.060217827825098, -0.9821393944649829, -0.913157776148085, -0.8544328672620072, -0.8068852002791962, -0.7711773795633778, -0.7477014420096293, -0.7365724175428523, -0.7376282144647206, -0.750435803885773, -0.7743035276804391, -0.8082992092048584, -0.8512736089498403, -0.901888641689817, -0.9586496605736142, -1.019941019664406, -1.0840640519289724, -1.1492765463738766, -1.2138327771783093, -1.2760231299752385, -1.3342123860089017, -1.3868757632992899, -1.432631874163163, -1.4702718389310225, -1.4987838944185015, -1.5173729501712603, -1.5254746728338544, -1.5227638160126196, -1.509156656295858, -1.4848075420980953, -1.4500997070883617, -1.4056306405538945, -1.352192439669844, -1.2907476900274886, -1.2224015279396112, -1.1483706283738615, -1.0699499336696234, -0.9884779887560416, -0.905301777214144, -0.8217419585696545, -0.739059390585037, -0.6584237815257318, -0.5808852574456791, -0.5073495500367484, -0.43855741356843736, -0.37506876739535566, -0.31725193629077264, -0.2652782276349754, -0.21912194562892648, -0.17856580173457415, -0.1432115410292157, -0.11249546962770193, -0.08570844216887256, -0.062019753763056545, -0.0405042806439827, -0.020172130583058195, -1.9038664723107595e-16], [0.0, 0.02141808402658015, 0.04511528500747241, 0.07196800694582536, 0.10274699697208296, 0.13809227500464594, 0.17849165587652543, 0.22426345206981527, 0.2755438369817115, 0.33227922795894504, 0.3942239182332969, 0.46094305066014535, 0.5318208872524471, 0.6060741904325542, 0.682770398194637, 0.7608501493768477, 0.8391536001899618, 0.9164498719725179, 0.9914688854313384, 1.0629347705610022, 1.129599995731902, 1.1902793353013936, 1.2438827932048178, 1.2894466204351942, 1.3261616066746327, 1.353397889600369, 1.3707256080317405, 1.3779308251016404, 1.3750262625786478, 1.362256514507703, 1.3400975443433043, 1.3092504113544954, 1.2706293157730113, 1.2253441943624928, 1.174678235264014, 1.1200608096945357, 1.0630364351158013, 1.0052304869095272, 0.9483124608046938, 0.8939576541388824, 0.843808178807791, 0.7994342412925385, 0.7622966248279268, 0.7337112855246865, 0.7148169285893693, 0.7065463637552206, 0.7096023522335602, 0.7244385529952896, 0.7512460565131224, 0.7899458621318683, 0.8401875141882147, 0.9013539653027498, 0.9725725864891365, 1.052732096497666, 1.1405050407289348, 1.2343753165916074, 1.3326701206020166, 1.433595585810119, 1.5352752889015584, 1.6357907367583802, 1.7332228940698593, 1.8256937879557809, 1.9114072231311783, 1.9886876619700504, 2.056016367412461, 2.1120639719442726, 2.1557187212699733, 2.186109744713277, 2.2026248232935792, 2.2049222579367327, 2.192936581176947, 2.1668780025562207, 2.127225627148593, 2.07471463459395, 2.010317749119679, 1.9352214657810565, 1.8507976212941233, 1.7585710063883246, 1.6601838079526767, 1.5573577411970556, 1.4518547828878003, 1.3454374452535305, 1.2398295357530351, 1.136678330477133, 1.037519049012295, 0.9437424571707184, 0.8565663426616638, 0.7770115096021143, 0.7058828232366812, 0.6437557092267095, 0.5909683755478143, 0.5476198827982296, 0.5135740441005152, 0.4884689923605233, 0.4717321139763232, 0.4625999175864806, 0.460142287321565, 0.46329046519515793, 0.47086801929900857, 0.481623985484541, 0.49426732187542277, 0.5075017890012654, 0.5200603641633118, 0.5307383168722053, 0.538424112309449, 0.5421273706858866, 0.5410031905127283, 0.5343722410953929, 0.5217361415145335, 0.5027877671159101, 0.4774162569441739, 0.4457066332658504, 0.4079340838467573, 0.3645530954511408, 0.3161817596339913, 0.2635816959591752, 0.20763415016755277, 0.14931292271089194, 0.08965486399641848, 0.029728734619121667, -0.029396729760058384, -0.08668468943830637, -0.14116115043114932, -0.19194416010326734, -0.23827046150077438, -0.27951888514981066, -0.31522984158930695, -0.3451203788411265, -0.36909438383678805, -0.3872476326138252, -0.3998675276855873, -0.4074274989959754, -0.41057618380130084, -0.4101216371545324, -0.40701095494348316, -0.402305812343298, -0.3971545290052591, -0.39276136554767, -0.39035383154768416, -0.3911488413014131, -0.39631858865730724, -0.40695702529355754, -0.42404781751243986, -0.4484346251310578, -0.4807944930830971, -0.5216150731731781, -0.5711763018155622, -0.629537051778169, -0.696527154586874, -0.7717450583134063, -0.8545612462330785, -0.9441273987454668, -1.0393911375554745, -1.1391160509830631, -1.2419065659034487, -1.346237108551635, -1.4504848863490758, -1.5529655287981319, -1.651970749725483, -1.745807137672209, -1.8328351474621423, -1.9115073548328925, -1.980405047830665, -2.0382722632284995, -2.0840464327440076, -2.1168848809805474, -2.1361865129567477, -2.1416081415191073, -2.133075031137046, -2.1107853715013727, -2.0752085386597896, -2.0270771496142963, -1.9673730647624617, -1.897307637663589, -1.8182966498064386, -1.7319304959666877, -1.639940300239017, -1.5441607411050169, -1.4464904435445365, -1.3488508552596794, -1.2531445611056715, -1.1612140038987655, -1.0748015705468412, -0.9955119701433731, -0.9247777760635167, -0.8638289285331329, -0.8136668994502028, -0.7750441097342556, -0.748449063884542, -0.7340975298066466, -0.7319299476534694, -0.7416151029388278, -0.7625599501392213, -0.7939253270300285, -0.8346471606564405, -0.8834626365000555, -0.9389406862030129, -0.9995160489602755, -1.063526079799047, -1.1292494163900488, -1.1949455762338483, -1.2588945389549249, -1.3194353743749274, -1.3750030058156595, -1.4241622489309749, -1.4656383379719091, -1.4983432419292633, -1.5213971801877817, -1.5341448684749983, -1.5361661579659884, -1.5272808701195344, -1.5075477736970724, -1.4772577948832062, -1.4369216929094533, -1.3872525685869637, -1.3291436983537124, -1.263642298762678, -1.191919923032151, -1.115240269994604, -1.03492524461644, -0.9523201468159842, -0.8687588807136054, -0.7855300693923574, -0.7038449309769693, -0.6248077211556881, -0.5493894765080444, -0.47840570399710225, -0.4124985570246488, -0.3521239202153383, -0.29754369660223917, -0.2488234553946139, -0.20583545945349127, -0.1682669524996882, -0.13563345044748568, -0.10729665251818253, -0.08248646918756397, -0.060326558547434364, -0.039862672968768435, -0.020093046298165784, -1.918439364245441e-16], [0.0, 0.021936357519357658, 0.04654332314564361, 0.07463586226451417, 0.10691082342380279, 0.1439240659696543, 0.1860714782900345, 0.23357440841790136, 0.28646991434365765, 0.34460611637049043, 0.407642801379933, 0.4750572923114369, 0.5461554589577328, 0.6200876118154125, 0.6958688926176503, 0.7724036565701387, 0.8485132352338538, 0.9229663781599352, 0.9945115981144439, 1.0619105909277642, 1.1239718680730935, 1.1795837289073725, 1.227745710438567, 1.2675976853043427, 1.2984458325988861, 1.319784779976391, 1.331315307301805, 1.3329571097670152, 1.324856239199058, 1.3073869732770964, 1.281148000306989, 1.2469529486560913, 1.2058154314107135, 1.1589289147604551, 1.107641849593018, 1.0534286265205235, 0.9978570220216025, 0.9425528948624893, 0.8891629651355699, 0.8393165612541362, 0.7945872516918145, 0.7564552873089975, 0.7262717664732277, 0.7052253991226457, 0.6943126882623167, 0.6943122694780148, 0.7057640527584746, 0.7289536985491627, 0.7639028342323325, 0.8103652811869198, 0.8678294195337275, 0.93552667109958, 1.0124459346136316, 1.0973536642579504, 1.188819146926746, 1.2852444082267738, 1.3848980654456653, 1.4859523501666279, 1.5865224462622574, 1.684707232548234, 1.7786304848093768, 1.8664815800807646, 1.9465547572737247, 2.017286022214637, 2.0772868410906917, 2.1253738428104447, 2.16059384602404, 2.1822436381861228, 2.1898840593608497, 2.183348079406522, 2.162742700422181, 2.1284446633984966, 2.0810900853078684, 2.02155829680897, 1.950950287829599, 1.8705622952010128, 1.7818551801727753, 1.6864203412943564, 1.5859429874593765, 1.4821636549753614, 1.3768388899510386, 1.2717020322232164, 1.1684250291694973, 1.0685821773258475, 0.9736166375586998, 0.8848104969723107, 0.8032590596062638, 0.7298499405918214, 0.6652474174814857, 0.609882360965862, 0.563947928421034, 0.5274010611364794, 0.49996968319295415, 0.48116536032583346, 0.4703010441676511, 0.46651340428581645, 0.4687891404347228, 0.475994573113539, 0.4869077341541611, 0.5002521224986597, 0.5147312549055499, 0.52906312786326, 0.542013715752217, 0.5524286609936365, 0.5592623637167606, 0.5616037500041898, 0.5586980871846059, 0.5499643196364443, 0.5350075164626495, 0.5136261501942938, 0.4858140601353556, 0.45175709166646516, 0.41182454029927773, 0.3665556630437691, 0.31664164634371866, 0.2629035362587652, 0.20626673979400018, 0.14773279370427053, 0.08834916653426095, 0.02917790935536894, -0.0287360006172311, -0.08439577231367881, -0.13688253262105635, -0.1853828776412763, -0.22921350017979134, -0.2678422262221537, -0.30090488631580675, -0.328217555765524, -0.3497838176407169, -0.3657968317432157, -0.3766361276269278, -0.3828591770792812, -0.3851879376892397, -0.3844906907829547, -0.3817596207617144, -0.37808469557872115, -0.3746245068659538, -0.3725748105409063, -0.37313557246584395, -0.3774773672432542, -0.386708000359377, -0.4018402240164996, -0.42376139505823324, -0.4532058798771679, -0.49073094712949145, -0.5366968060112726, -0.5912513477996817, -0.6543200337816366, -0.7256012464030653, -0.8045672855930291, -0.8904710520889421, -0.9823583176907358, -1.0790853422339033, -1.1793414621890497, -1.281676149541337, -1.3845299251427126, -1.4862684109435615, -1.5852187229205077, -1.6797073432261211, -1.768098567722275, -1.848832604736233, -1.9204624031680786, -1.981688312993641, -2.0313897282029125, -2.0686529301984606, -2.092794437040339, -2.1033792685710804, -2.100233656864813, -2.08345186272889, -2.0533968989580065, -2.0106951062945093, -1.9562246750445684, -1.891098350450379, -1.816640699676554, -1.734360449215871, -1.6459185204487885, -1.5530924950883482, -1.4577383287557057, -1.3617501978370854, -1.267019410424742, -1.1753933354165782, -1.0886353041632348, -1.0083864163910092, -0.9361301370405838, -0.8731605042395788, -0.8205546824895665, -0.7791504913944104, -0.7495294214173339, -0.7320055171275087, -0.7266203683787158, -0.7331443042667994, -0.7510837370869062, -0.7796944574509358, -0.8180005407831258, -0.8648183930114343, -0.9187853426250676, -0.9783920802927233, -1.0420181584869028, -1.1079696941653507, -1.1745183691716081, -1.2399407967642788, -1.302557319154964, -1.3607693201536704, -1.413094178454474, -1.4581970496640735, -1.494918747283702, -1.5222990924246833, -1.5395952165676086, -1.5462944282983944, -1.5421213905127849, -1.5270394957018483, -1.5012464701124328, -1.4651643792724134, -1.4194243440807983, -1.3648464050178313, -1.3024150888761383, -1.2332513348894993, -1.1585815227431246, -1.0797044116155534, -0.9979568455308354, -0.9146791048081712, -0.8311807857439157, -0.7487080708605907, -0.6684132106745762, -0.5913269760718108, -0.5183347596517761, -0.45015690688565824, -0.3873337461325983, -0.33021566331884733, -0.2789584355412493, -0.23352390134412046, -0.1936859073924271, -0.15904133521223274, -0.1290258810254097, -0.10293413976322727, -0.07994343417373197, -0.05914073431262015, -0.03955193403012536, -0.020172691312177832, -1.946905840445738e-16], [0.0, 0.022579372155995456, 0.04818814151171346, 0.07757384569422059, 0.1113547707958225, 0.14999942797976892, 0.19381017776677414, 0.24291145429681793, 0.29724292242182976, 0.3565577723389032, 0.42042622286498865, 0.48824416876680626, 0.5592467732332443, 0.6325266770199633, 0.7070563742989024, 0.781714194901458, 0.8553132362690776, 0.9266325084872521, 0.9944494943371598, 1.0575732849507702, 1.1148774314952892, 1.1653316549068102, 1.2080315790615221, 1.2422256973906745, 1.2673388477540373, 1.2829915538195182, 1.2890146912183607, 1.2854590509011699, 1.272599497596786, 1.2509335549715972, 1.2211743876872228, 1.1842382906157431, 1.141226933505698, 1.0934047419532893, 1.0421719193043226, 0.9890337259867595, 0.935566729933428, 0.8833828217400055, 0.8340918489760701, 0.7892637640594571, 0.7503911982602404, 0.7188533702023544, 0.6958822107117564, 0.6825315376053998, 0.6796500451483463, 0.6878587850609946, 0.7075337112399062, 0.7387937412888027, 0.7814946574236469, 0.8352290304870431, 0.899332207061356, 0.9728942545117966, 1.0547776157649364, 1.1436400882314437, 1.2379626128775483, 1.3360812431838427, 1.4362225624543181, 1.5365417341398053, 1.635162305578562, 1.7302168424159374, 1.819887450011288, 1.9024452398976113, 1.9762878237954034, 2.0399739642096346, 2.092254578129159, 2.132099377159787, 2.1587185314413877, 2.171578863390656, 2.170414207781152, 2.1552297137405008, 2.1263000085218415, 2.084161288878227, 2.0295975499813226, 1.9636213005745846, 1.8874492430663397, 1.8024735153975315, 1.7102291949052515, 1.6123588505547422, 1.51057499676363, 1.4066213480038745, 1.302233797365897, 1.1991020437732485, 1.0988327715668964, 1.0029152433097148, 0.9126901030064494, 0.8293221041137786, 0.753777376819647, 0.6868057346085236, 0.6289283939602256, 0.5804313462993662, 0.5413644813685597, 0.5115464195117686, 0.49057487043005105, 0.47784220126448634, 0.47255577068705007, 0.47376247113743614, 0.48037682123425773, 0.491211867149985, 0.5050120873827727, 0.5204874514234157, 0.5363477603285844, 0.5513363966624237, 0.564262632599979, 0.5740316875940977, 0.5796717897596245, 0.5803575763902918, 0.5754292667015984, 0.5644071514864706, 0.5470010670359567, 0.5231146512981393, 0.49284431551433283, 0.45647300106093047, 0.414458925490425, 0.36741965041980024, 0.31611192371715896, 0.26140785637329794, 0.20426808780065786, 0.1457126697336178, 0.08679045649556073, 0.028547826708979953, -0.028002422373793228, -0.08191117224403155, -0.13232126349523066, -0.1784931981672405, -0.2198275703452107, -0.2558836163949882, -0.2863933770161206, -0.31127107722839853, -0.33061745459396197, -0.34471889727062927, -0.35404138856868295, -0.359219390120292, -0.36103992813362407, -0.36042227313207187, -0.3583937198706642, -0.356062077813272, -0.35458557099509275, -0.355140917014483, -0.35889040646262704, -0.36694883495827196, -0.38035114927484115, -0.4000216565346227, -0.4267456113524406, -0.4611439409335525, -0.5036517937839595, -0.5545015056823758, -0.6137104691439572, -0.6810742724184762, -0.7561653440770628, -0.838337202669688, -0.9267342711699553, -1.0203070764411881, -1.1178325182359403, -1.217938763672007, -1.319134204933774, -1.4198398130997656, -1.51842413214282, -1.6132400865441003, -1.7026627254154811, -1.785126996852219, -1.859164639229101, -1.9234392915512937, -1.9767789624658656, -2.0182050562744873, -2.0469572328792083, -2.0625134751665306, -2.0646048495678104, -2.053224570714425, -2.028631116198639, -1.9913452791712132, -1.9421411914020645, -1.8820314939650227, -1.812246973350403, -1.7342111141188277, -1.6495101419222953, -1.5598592398249573, -1.4670657136796252, -1.372989956575476, -1.2795051162406321, -1.1884564014311185, -1.1016209729674316, -1.020669351945166, -0.9471292420572006, -0.882352605783026, -0.8274867568142591, -0.7834501353787497, -0.7509133214302511, -0.7302857157092915, -0.7217081834999401, -0.7250518138015626, -0.7399228010671568, -0.7656733111751837, -0.8014180514400966, -0.84605612967583, -0.8982976628775929, -0.9566944849942376, -1.019674208208949, -1.0855768154159342, -1.1526929050077983, -1.2193026740078157, -1.2837147127983322, -1.3443036944674018, -1.3995460738210699, -1.4480529645428364, -1.4885994364536188, -1.5201495664727982, -1.5418766843975766, -1.5531783753113357, -1.553685931289714, -1.5432680828390968, -1.5220289817560209, -1.4903005483390828, -1.4486294336262193, -1.3977589781743576, -1.338606669627687, -1.272237708976389, -1.1998353873618466, -1.1226690493053824, -1.0420604725445015, -0.9593495279673638, -0.8758599946817288, -0.7928663948223174, -0.7115626806220577, -0.633033553419049, -0.5582291220304291, -0.4879435181664435, -0.42279798158696863, -0.3632288101993208, -0.30948044324961416, -0.26160381239405056, -0.21945995912781513, -0.18272878124309683, -0.1509226391118368, -0.12340442796745758, -0.09940960813101124, -0.07807158416401803, -0.05844973876921575, -0.039559360038299136, -0.020402653045908718, -1.988303888215092e-16], [0.0, 0.023334001785766577, 0.050020830326554806, 0.08073537190149734, 0.11601352767370447, 0.15623416494096523, 0.2016054305480524, 0.2521558069473828, 0.30773016809052944, 0.3679909622598291, 0.43242451540219, 0.5003523148911186, 0.5709470033077783, 0.6432526881074496, 0.7162090590709124, 0.7886787041359087, 0.859476928151948, 0.9274033105121837, 0.9912741882631146, 1.049955222470062, 1.1023931981038855, 1.147646221758927, 1.1849115168199336, 1.2135500714395453, 1.2331074695267346, 1.2433303270587375, 1.244177863156675, 1.235828254870272, 1.218679553546829, 1.1933450758190922, 1.1606433202784323, 1.1215825983672718, 1.0773407014975507, 1.0292400525414522, 0.9787189054826622, 0.9272992592507032, 0.8765522380035417, 0.8280617581817137, 0.7833873507838806, 0.7440270342521591, 0.7113811383709964, 0.6867179624817951, 0.671142112449562, 0.6655663010786512, 0.6706873174706076, 0.686966774039565, 0.7146171278781109, 0.7535933486073348, 0.8035904707708382, 0.8640471285050394, 0.9341550270573618, 1.0128741632249456, 1.0989534684332491, 1.1909564173527603, 1.2872910248691642, 1.3862435478234651, 1.4860151178373395, 1.5847604599515155, 1.680627800495431, 1.7717990378434787, 1.8565292422381252, 1.9331845658691735, 2.00027768153682, 2.056499926597448, 2.100749407078973, 2.132154412955454, 2.150091607248816, 2.154198576158197, 2.1443804617702917, 2.120810539803574, 2.08392474885352, 2.034410321228816, 1.9731888052063868, 1.901393900990351, 1.8203446546228241, 1.7315146626098854, 1.6364980324737517, 1.5369729185999397, 1.4346635068450118, 1.3313013541305387, 1.2285869999223864, 1.128152754875022, 1.0315275383506852, 0.940104581884054, 0.8551127413529266, 0.7775920685140222, 0.7083741849845296, 0.6480678813860633, 0.5970502342183913, 0.5554633963323715, 0.5232170770151069, 0.49999658814694103, 0.4852761970854134, 0.4783373982210813, 0.47829159669615096, 0.48410659247965526, 0.49463616341977645, 0.5086519742160289, 0.5248769861926762, 0.5420195115398474, 0.5588070460283395, 0.5740190262678222, 0.5865176909941109, 0.5952762797351089, 0.5994038751049132, 0.5981662850258124, 0.5910024660688644, 0.5775361061580092, 0.5575821111240741, 0.5311478718220101, 0.4984293233911749, 0.4598019423376894, 0.4158069570670299, 0.36713317002069773, 0.31459490158988895, 0.25910666467653487, 0.20165526167070943, 0.143270060635721, 0.08499225301259333, 0.027843920040290973, -0.027202261276479164, -0.07925185951159158, -0.12751530289312385, -0.17133154997173677, -0.21018817758273123, -0.24373734008992595, -0.27180716127031385, -0.29440823893330775, -0.3117350694602584, -0.324162331679665, -0.33223610351066885, -0.3366602172139006, -0.3382780865241662, -0.3380504581653185, -0.3370296482284682, -0.33633091787446456, -0.3371017203926753, -0.34048961081224505, -0.34760964848038184, -0.3595121412546156, -0.3771515766873135, -0.401357560834496, -0.43280853965937893, -0.47200901251150257, -0.51927086343101, -0.5746993361006677, -0.6381840646011468, -0.7093954475218635, -0.7877865205241322, -0.8726003454314858, -0.9628827957416277, -1.0575004825596868, -1.155163434738404, -1.254452025739194, -1.3538475304453423, -1.451765600620605, -1.5465918703093624, -1.6367188441938543, -1.7205831842670378, -1.7967024941448273, -1.8637107063950904, -1.9203912063230755, -1.9657068751004994, -1.998826304804953, -2.0191455261925406, -2.0263046947436396, -2.0201992991729107, -2.0009855863063675, -1.9690800338491619, -1.9251528447466795, -1.8701155801101947, -1.8051031885365045, -1.7314508246527744, -1.650665975556669, -1.5643965274126015, -1.4743955030186982, -1.382483282254149, -1.290508178956153, -1.2003062884388094, -1.1136615385448203, -1.0322668733445712, -0.957687472445662, -0.8913268609764399, -0.8343966968200317, -0.787890934264142, -0.752564959024433, -0.7289201711331434, -0.7171943623464521, -0.7173580966775309, -0.7291171597703666, -0.7519209985720586, -0.7849769306489822, -0.8272697659803433, -0.8775863564659772, -0.9345444727969046, -0.9966253075521722, -1.0622088198326027, -1.1296110724242272, -1.197122668929126, -1.2630473765252852, -1.3257400204991254, -1.383642759366543, -1.4353188936465138, -1.4794834260323522, -1.5150296741755118, -1.5410513374515857, -1.5568595334073263, -1.561994445236358, -1.556231355471487, -1.5395809797894608, -1.51228415496311, -1.4748010731018124, -1.4277953869875093, -1.3721136352768677, -1.3087605485594873, -1.2388708949951899, -1.1636786051238304, -1.0844839774963846, -1.0026198085362006, -0.9194173105326, -0.8361726804549791, -0.7541151594559385, -0.6743773791469378, -0.5979687271412846, -0.5257523826210846, -0.45842657490132843, -0.39651050663690984, -0.3403352612829293, -0.2900398847734919, -0.24557269741370308, -0.20669775707059482, -0.1730062623067683, -0.14393255746417585, -0.11877428406288998, -0.0967161171892587, -0.07685643446398555, -0.05823619098774814, -0.039869218217457154, -0.020773129414140976, -2.0415559552076093e-16], [0.0, 0.024186203357072774, 0.052011046646416065, 0.08407234383327387, 0.12082065183865887, 0.16254379603289412, 0.2093559287046636, 0.26119142756260544, 0.31780381533806346, 0.37876975075117925, 0.44349800879364687, 0.5112432378259189, 0.5811241556961488, 0.6521457301474404, 0.7232247831668068, 0.7932183673398161, 0.8609541870558822, 0.925262280498821, 0.9850071412363993, 1.0391194418771104, 1.0866265271580835, 1.12668086989836, 1.158585729898902, 1.1818173219798584, 1.196042883312145, 1.2011341299694, 1.197175705743142, 1.184468349934995, 1.1635266420016865, 1.1350713163241033, 1.1000162766308954, 1.0594505733307789, 1.014615734852002, 0.9668789628474037, 0.9177028078126594, 0.8686120335904529, 0.8211584540618805, 0.776884581144622, 0.7372869585790365, 0.7037800699454934, 0.6776617015042373, 0.6600806109069046, 0.6520073022572522, 0.6542086375793909, 0.667226926159159, 0.6913640285841294, 0.7266708941459263, 0.772942821448661, 0.8297205957204868, 0.8962975157732911, 0.9717321822287855, 1.0548667799824256, 1.1443504553035688, 1.238667264719939, 1.336168061931348, 1.4351055931661845, 1.5336719929923208, 1.6300378135544331, 1.722391681991822, 1.8089796643450908, 1.8881434200040843, 1.9583562585575593, 2.0182562601112517, 2.066675689555083, 2.1026660231972967, 2.125518010504912, 2.134776311856649, 2.130248382348795, 2.1120074086510505, 2.0803892473529007, 2.0359834557280663, 1.9796186459083893, 1.9123425276944823, 1.835397130379484, 1.7501898069913868, 1.6582607225355552, 1.561247608776995, 1.4608486299012924, 1.3587842445665972, 1.256758969447318, 1.1564239469459692, 1.0593411954264278, 0.9669503747520725, 0.8805388342687803, 0.8012156263208481, 0.7298900680424851, 0.6672553200408371, 0.6137773255254291, 0.5696893205538508, 0.5349919886516932, 0.5094591945276125, 0.4926490953640033, 0.48392029757747124, 0.48245260522099975, 0.4872717963243062, 0.49727776812282515, 0.5112753136247717, 0.5280067322020472, 0.546185437286562, 0.5645297057267062, 0.5817957163001589, 0.5968090491446241, 0.6084938627817602, 0.6158990297821967, 0.6182205942787405, 0.6148200123670425, 0.6052377474372854, 0.5892019138309327, 0.5666317908337491, 0.5376361616439497, 0.5025065652412655, 0.4617056796664691, 0.4158511798118606, 0.36569552828698115, 0.31210226135913255, 0.256019420779759, 0.19845085427058146, 0.14042616075847195, 0.08297008978741646, 0.02707221707505287, -0.026342290379980347, -0.07644003566376968, -0.12250414535201111, -0.16395574891071424, -0.2003716035502068, -0.23149738443150683, -0.2572562729602156, -0.27775259827451365, -0.2932704158400391, -0.30426703904106966, -0.3113616714584461, -0.3153194158057591, -0.3170310569980526, -0.31748912846072225, -0.31776086970440565, -0.31895876686519076, -0.32220943418904496, -0.32862164161013946, -0.33925432039733944, -0.35508538459339617, -0.37698219044695186, -0.40567441957150274, -0.4417301150168732, -0.48553552417145857, -0.5372793102628989, -0.5969415874527487, -0.6642881157594652, -0.7388698642310069, -0.8200280170939785, -0.9069043613541429, -0.9984568589087303, -1.0934800750361977, -1.1906300114386066, -1.2884527789310425, -1.3854164452502384, -1.479945309811472, -1.5704557917090567, -1.6553930715161065, -1.7332676026927711, -1.8026906053392475, -1.8624076737768296, -1.9113296696132758, -1.9485601326241158, -1.9734185215266689, -1.9854586936325263, -1.984482144104286, -1.9705456494101292, -1.9439630925589564, -1.9053013865727553, -1.8553705540252123, -1.7952081608929675, -1.7260584389936027, -1.6493465595907115, -1.566648638184611, -1.4796581541945208, -1.3901495566245246, -1.2999398957401709, -1.2108493695632787, -1.1246617014108833, -1.0430852700741258, -0.9677158974077193, -0.9000021594777046, -0.8412140279250622, -0.7924155692879632, -0.7544423336028737, -0.7278839520212058, -0.7130723391500836, -0.7100757623741087, -0.718698900789984, -0.7384888739873658, -0.7687470792031068, -0.8085465378083969, -0.8567543220013976, -0.9120585131274508, -0.9729990371268752, -1.0380016327735828, -1.1054141367757262, -1.1735442181714961, -1.2406976639858434, -1.3052163095128135, -1.3655147200105113, -1.420114765657503, -1.4676772874048916, -1.5070301264438755, -1.5371918824984834, -1.5573908737262936, -1.5670788909783475, -1.5659394685455494, -1.553890529088349, -1.5310813988499978, -1.497884327068586, -1.4548807773293149, -1.4028428851420427, -1.3427105921842217, -1.275565070574349, -1.2025991377292056, -1.1250854316990913, -1.0443431667065008, -0.9617043177617332, -0.8784800910375791, -0.7959285230305767, -0.7152240168300121, -0.6374295689934408, -0.5634723670240064, -0.49412334715983325, -0.42998119743322405, -0.37146117440955567, -0.31878897663430483, -0.27199978677955283, -0.23094246110276237, -0.19528871247769297, -0.16454700526684998, -0.13808075989862983, -0.11513035521785674, -0.09483832025242449, -0.07627702639912659, -0.05847812819651228, -0.040462957390321075, -0.021273051987301846, -2.1054818888701384e-16], [0.0, 0.025121176819867894, 0.054127350938447706, 0.08753567389017637, 0.12570927474070545, 0.16884443286488401, 0.2169624102273268, 0.2699061759006424, 0.32734212806353674, 0.38876678835530604, 0.45351831353095395, 0.5207925431599493, 0.5896631828477467, 0.6591056131672001, 0.7280237179535282, 0.7952790443103006, 0.8597215426837791, 0.9202210903449848, 0.9756989767547437, 1.0251585252537831, 1.0677140424728404, 1.1026173244253437, 1.1292810055383655, 1.1472981125109425, 1.156457277014858, 1.1567531676074894, 1.1483918191842601, 1.1317906649390794, 1.1075732079809075, 1.0765584041840937, 1.0397449611768368, 0.9982908872632362, 0.9534887453002064, 0.9067371770646957, 0.8595093606623125, 0.8133191445879193, 0.7696856650851093, 0.7300972968402639, 0.6959758096475258, 0.668641604865352, 0.6492808851542815, 0.6389155695722987, 0.6383767045640483, 0.648282041167873, 0.669018351798953, 0.7007289485835986, 0.7433067421149265, 0.7963930476634228, 0.8593822085172811, 0.9314319665982852, 1.0114793722094397, 1.098261891105349, 1.190343241311553, 1.286143377340753, 1.3839719384827542, 1.4820643931655635, 1.578620045085221, 1.6718410205205962, 1.7599713311361316, 1.8413351032621263, 1.914373083226648, 1.977676568357321, 2.030017973811186, 2.0703773249605737, 2.097964061730477, 2.112233652697617, 2.1128986402119185, 2.0999338702819443, 2.0735757992515516, 2.034315910019253, 1.9828884102905722, 1.9202525207090855, 1.8475697883963536, 1.7661769783472403, 1.6775551984452926, 1.5832960010888881, 1.4850652734564702, 1.3845657776407192, 1.2834992300882146, 1.183528816351287, 1.086243021982989, 0.9931216239091482, 0.905504629741889, 0.8245648767041144, 0.7512849090249349, 0.6864386451676764, 0.630578226747823, 0.5840263124616814, 0.5468739459675158, 0.5189839897670921, 0.4999999811090065, 0.4893601341293841, 0.4863160881018473, 0.4899558878364555, 0.4992305817285648, 0.5129837381593195, 0.5299831139396721, 0.5489536608729562, 0.5686110294050075, 0.587694722341118, 0.6050000668140397, 0.6194082086373283, 0.6299133889078401, 0.6356468367730965, 0.6358967027423154, 0.6301235614765706, 0.6179711289788958, 0.5992719635730305, 0.5740480498571883, 0.542506296665803, 0.5050291106410616, 0.46216033301778253, 0.4145869454900094, 0.363117058584503, 0.30865479011679414, 0.25217271969143723, 0.19468266587049762, 0.13720557406141928, 0.08074132434124458, 0.02623926882312715, -0.02542971220881462, -0.07349888678785015, -0.11732839158260423, -0.15642438473896506, -0.19045411313222124, -0.2192564824468171, -0.24284783566999132, -0.26142277042218676, -0.2753499548870743, -0.2851630326677864, -0.291546835371248, -0.29531924484706795, -0.29740916165107967, -0.2988311395465524, -0.3006573350622689, -0.3039874940102204, -0.30991775154811496, -0.31950905742991054, -0.3337560525887417, -0.353557216723446, -0.3796870792207937, -0.41277123817263245, -0.4532648655811971, -0.5014352927082862, -0.557349169977084, -0.6208645833312944, -0.6916283862764819, -0.769078877014544, -0.852453816361048, -0.9408036478375894, -1.0330096498108001, -1.1278066240974869, -1.2238096092195538, -1.3195440023985696, -1.413478385058641, -1.5040592743269565, -1.589746969635785, -1.6690516304242557, -1.7405687090007222, -1.8030128722212826, -1.855249576599926, -1.8963235130942417, -1.9254832088992566, -1.942201162438666, -1.9461889922336228, -1.9374071979309264, -1.9160692596330453, -1.882639936682678, -1.8378277659235667, -1.782571898795904, -1.718023553020868, -1.6455224847439534, -1.5665690076498502, -1.4827921937699151, -1.3959149838164944, -1.307717010602401, -1.2199959955703505, -1.1345286142668782, -1.0530317408550791, -0.9771249741042578, -0.908295317892822, -0.8478648388168677, -0.7969620532292082, -0.7564977076468846, -0.7271455121067031, -0.7093282682575399, -0.7032097056218305, -0.7086922036621576, -0.7254204373581551, -0.7527908433397514, -0.789966665656511, -0.8358982083426197, -0.8893477992651594, -0.9489188592923506, -1.0130883752588338, -1.0802419968387416, -1.148710918142126, -1.2168096660338144, -1.2828738997387532, -1.345297330621177, -1.4025668969480436, -1.4532953752815883, -1.496250676689495, -1.530381160529909, -1.5548363990375937, -1.568982939794594, -1.572414737576651, -1.5649580589343048, -1.5466707989258235, -1.5178362863027486, -1.478951787779591, -1.4307120504894864, -1.3739883411821283, -1.3098035482345618, -1.2393040054971318, -1.1637287731312194, -1.0843771680800829, -1.0025753742841756, -0.9196429793434096, -0.8368602796984372, -0.7554371707368875, -0.6764843922389039, -0.6009878344745487, -0.5297865277427699, -0.46355484031931316, -0.40278929915779194, -0.34780032707890585, -0.2987090626462248, -0.25544929769014774, -0.21777443581879025, -0.18526924656378427, -0.1573660672903468, -0.13336499173429897, -0.11245748285776981, -0.09375276117609377, -0.07630624996647203, -0.05914930756495513, -0.04131944556513259, -0.021890220922771993, -2.1788127918481135e-16], [0.0, 0.0261235309587004, 0.056337550894920436, 0.0910758088407067, 0.13061280139603706, 0.17505363907960178, 0.22432865425573487, 0.27819290888244325, 0.3362306324946833, 0.39786449205449326, 0.46236946883320734, 0.5288909965525956, 0.596466902676506, 0.6640525938738223, 0.7305488398429305, 0.7948314391227592, 0.8557819980346678, 0.9123190208696236, 0.9634284967358316, 1.0081931764834842, 1.0458197616765244, 1.0756632760211395, 1.0972479568219176, 1.110284088282531, 1.1146802977304013, 1.1105509476760356, 1.0982183782497839, 1.0782098829731959, 1.0512494328241702, 1.0182442958535731, 0.9802668288999529, 0.9385318409899702, 0.8943700417151406, 0.8491981893757294, 0.8044866404124957, 0.7617250713999384, 0.7223871958611501, 0.6878953290560611, 0.6595856638593128, 0.6386751095651693, 0.6262305131443787, 0.6231410298621269, 0.6300943384812874, 0.6475573072289137, 0.6757616124363526, 0.7146946947943308, 0.7640963113317093, 0.8234608076164694, 0.8920450975483286, 0.968882200814842, 1.0528000539769378, 1.1424451835223053, 1.236310711208168, 1.3327680565088516, 1.4301016105852116, 1.526545583131202, 1.6203221695337013, 1.709680152343553, 1.7929330389359102, 1.8684958467520247, 1.934919678448354, 1.9909232808933053, 2.035420853001509, 2.067545456158317, 2.0866674853076352, 2.092407776117594, 2.084645051145887, 2.0635175424964927, 2.0294187668167205, 1.982987567261566, 1.9250926728762094, 1.8568121554166315, 1.779408283798117, 1.6942983842199362, 1.6030224069545622, 1.507207976572472, 1.4085337591833484, 1.3086920167633573, 1.209351233958572, 1.1121196965797517, 1.018510873535208, 0.9299114059105085, 0.8475524395252735, 0.772484952280049, 0.7055596270833808, 0.6474117076311884, 0.5984511506230968, 0.558858257214196, 0.5285848318548919, 0.5073607814939013, 0.494705935743323, 0.48994674228703916, 0.4922373746541084, 0.5005846843432367, 0.5138763387343972, 0.5309114124532434, 0.5504326446358596, 0.5711595391835889, 0.5918214704115894, 0.6111899627761556, 0.62810934038757, 0.641524989034516, 0.6505085392230194, 0.6542793615624314, 0.6522218635860512, 0.6438981872787871, 0.6290560263974883, 0.6076314090741141, 0.5797464209914258, 0.5457019743395307, 0.505965854526122, 0.4611563970345936, 0.4120222578773124, 0.35941883999062857, 0.3042820221869798, 0.24759990481159766, 0.19038333536404528, 0.1336360068198974, 0.07832493050267063, 0.02535207390068734, -0.024472077893848726, -0.07045232960720582, -0.11202931384831717, -0.14879620726324666, -0.18051117209105136, -0.2071051819550826, -0.22868501107830597, -0.24553129224559145, -0.25809167755148904, -0.26696926400343324, -0.272906570147622, -0.2767654668945448, -0.2795035726657111, -0.2821477171354833, -0.28576515679390535, -0.29143328727963175, -0.30020864032862904, -0.3130959761276021, -0.3310182842241199, -0.3547884878171981, -0.3850836076409154, -0.42242208367748657, -0.46714487700030416, -0.5194008820099679, -0.5791370734522143, -0.6460936955119949, -0.7198046748649999, -0.7996033089526936, -0.8846331481829237, -0.9738638595538179, -1.066111732636776, -1.1600643701088735, -1.254308997082685, -1.3473637290671567, -1.4377110599012726, -1.5238327704371837, -1.6042454176753211, -1.6775355435541361, -1.7423937432482484, -1.7976467546838804, -1.842286773568531, -1.8754972605673446, -1.896674587866459, -1.905444969313649, -1.901676229281805, -1.8854840876742174, -1.8572327691109507, -1.8175298801208357, -1.7672156357988933, -1.7073466535087112, -1.639174662479649, -1.564120601350344, -1.4837446878173493, -1.3997131428034337, -1.3137623335443724, -1.227661163681359, -1.1431725822622418, -1.0620151064067576, -0.9858252537008768, -0.9161217601022797, -0.8542724177408878, -0.8014643054807654, -0.758678104960563, -0.7266670979942492, -0.7059413300449144, -0.6967573016866919, -0.6991134185313221, -0.7127512932159447, -0.7371628540583971, -0.771603077266867, -0.8151080264901436, -0.8665177582456257, -0.924503537402184, -0.9875987061919524, -1.0542324656098772, -1.1227657615655695, -1.1915284213654118, -1.2588566601251907, -1.3231300721334576, -1.382807239066276, -1.4364591248303729, -1.482799484704677, -1.5207115928894392, -1.5492706856342884, -1.5677616244727526, -1.5756914030642166, -1.5727962487778546, -1.5590432032819803, -1.5346262017327046, -1.499956804346988, -1.4556498638916857, -1.4025045347339145, -1.3414811405868539, -1.2736745162270264, -1.2002845208687765, -1.122584485569785, -1.0418884024629524, -0.9595176887018064, -0.8767683622135642, -0.7948794496420216, -0.7150034097176671, -0.6381792987097457, -0.5653093300715503, -0.4971393898077714, -0.4342439647906087, -0.3770158258858734, -0.3256606842503832, -0.2801969106537049, -0.24046027740720854, -0.2061135537363218, -0.17666066144887477, -0.1514649816505927, -0.12977129795229705, -0.11073076974177526, -0.09342825295500176, -0.07691122727697319, -0.06021954928674052, -0.04241523170782139, -0.02261145010178457, -2.2602056356953833e-16], [0.0, 0.027177453315198392, 0.05860904872038216, 0.09464325280137391, 0.13546559823924587, 0.18109126335206496, 0.23136243111360533, 0.2859505119466705, 0.34436318756183715, 0.4059561070132115, 0.4699489441727669, 0.5354454110838065, 0.601456717062221, 0.6669278716388213, 0.7307661528245066, 0.7918710027008766, 0.8491645715320477, 0.9016221105313693, 0.9483014126771524, 0.9883705206224439, 1.0211329603413668, 1.0460498177532682, 1.0627580517421567, 1.0710845288756803, 1.07105537046083, 1.0629003187472126, 1.0470519532208395, 1.0241397169347841, 0.9949788434819709, 0.9605544042657689, 0.9220008199347327, 0.8805772961008826, 0.83763974882969, 0.7946098772120247, 0.7529421162722308, 0.7140892615900167, 0.6794675958131624, 0.6504223656852288, 0.6281944557824282, 0.613889081837346, 0.6084472828325805, 0.6126209279880649, 0.6269518738364696, 0.6517558097208687, 0.6871112195943632, 0.7328537666292048, 0.7885762778040898, 0.8536343714853604, 0.9271576353276701, 1.0080661279123806, 1.09509184869916, 1.1868047002499647, 1.2816423572593425, 1.377943361384031, 1.4739826815643946, 1.5680089184302197, 1.658282289999508, 1.743112515244868, 1.8208957127436813, 1.8901494535503531, 1.9495451501151837, 1.9979370254994295, 2.0343869877910437, 2.0581848315545663, 2.068863298997344, 2.0662076556074442, 2.0502595653466, 2.021315185893073, 1.9799175416298394, 1.9268433677260508, 1.8630847494669858, 1.7898260037732066, 1.7084163616358348, 1.6203391082761276, 1.527177919846766, 1.4305811994587667, 1.332225259715675, 1.233777222721488, 1.1368585111636407, 1.043009785540113, 0.953658143403099, 0.8700873376399256, 0.7934116937961913, 0.7245543132009457, 0.6642300415099653, 0.6129335639089543, 0.5709328615534923, 0.5382681320047804, 0.5147561427081082, 0.49999985425295185, 0.4934030225059258, 0.4941893688546031, 0.501425798675541, 0.5140490524056924, 0.5308950935768083, 0.5507304757966828, 0.5722848874161591, 0.5942840495152869, 0.6154821403816828, 0.634692937830414, 0.6508189090051236, 0.6628775346826646, 0.6700242300824196, 0.6715713148251933, 0.6670025886767383, 0.6559831844002121, 0.6383644915210247, 0.6141840719776743, 0.5836606172829675, 0.5471841237095009, 0.5053015839491903, 0.45869860761592207, 0.4081774860057733, 0.35463230612055185, 0.29902179285860225, 0.24234061464005702, 0.1855899251630939, 0.12974793156171383, 0.07574127653329159, 0.02441799911523603, -0.023477203687565378, -0.06732475319821637, -0.10664841997668331, -0.1411295189076755, -0.17061668350715947, -0.195130949882959, -0.21486600317508353, -0.2301835655816058, -0.24160403204247616, -0.24979258408404803, -0.25554113106076326, -0.25974653804788556, -0.2633856981378396, -0.26748809135736784, -0.2731065406885199, -0.28128692598375754, -0.2930376476037356, -0.30929964254793785, -0.3309177463693098, -0.35861416445286187, -0.3929647669916198, -0.43437885439949186, -0.4830829556099799, -0.5391091227943565, -0.6022880749353731, -0.672247422165151, -0.7484150758128099, -0.8300278188695949, -0.9161448813172439, -1.005666237736417, -1.0973552240010391, -1.1898649587029515, -1.2817679560426545, -1.37158823277102, -1.4578351445171898, -1.5390381382178895, -1.6137815786431944, -1.680738798971982, -1.738704538275477, -1.786624962368848, -1.8236245180257893, -1.849028942761441, -1.8623838415528398, -1.8634683458387702, -1.8523034864080592, -1.829155037524747, -1.7945307217886772, -1.7491718005664834, -1.6940392100417176, -1.6302945347131748, -1.559276235285233, -1.4824716632706967, -1.4014854974274404, -1.3180053248423211, -1.2337651598951553, -1.150507745737984, -1.0699465140324942, -0.993728088718607, -0.9233962082739007, -0.8603579085232075, -0.8058527553435669, -0.7609258448528919, -0.7264051996086534, -0.7028840851377494, -0.6907086543025829, -0.689971200422924, -0.7005091667979904, -0.721909923551384, -0.7535211858790447, -0.7944668141446563, -0.8436676090847167, -0.899866597743464, -0.9616582005062219, -1.0275205792826645, -1.0958503936847874, -1.1649991377014313, -1.23331019518123, -1.2991557391918929, -1.3609726083034686, -1.4172963218032688, -1.4667924450318026, -1.5082845841786061, -1.5407783752756248, -1.5634809326347017, -1.5758153350874124, -1.5774298512873008, -1.5682017349780588, -1.5482355543084414, -1.5178561526968235, -1.4775964691279229, -1.4281805698961638, -1.370502358650976, -1.3056005343422106, -1.2346304548083327, -1.1588336351625617, -1.0795056630996087, -0.9979633465164203, -0.9155119216548463, -0.833413142083149, -0.7528550405034449, -0.6749241073778309, -0.6005805639703359, -0.5306373243240912, -0.4657431430645106, -0.40637033623108054, -0.3528073433790568, -0.30515627397189804, -0.26333545276982967, -0.22708685074599566, -0.195988163256454, -0.16946917889105337, -0.14683197360870773, -0.127274368139779, -0.10991600463748245, -0.09382633322611533, -0.07805375205207934, -0.0616551168577999, -0.043724828642099256, -0.023422720809460437, -2.3482584682386724e-16], [0.0, 0.0282668823288952, 0.060909188117895294, 0.09818908267346886, 0.1402036616505419, 0.18688023709166843, 0.23797639738896442, 0.2930848527527146, 0.3516429526540648, 0.41294663934107007, 0.4761684850161971, 0.5403793525724185, 0.6045731236577035, 0.6676938557287984, 0.7286646637691053, 0.7864175741832694, 0.839923569297596, 0.8882220316673397, 0.9304488082980028, 0.9658621457013673, 0.9938657967010891, 1.0140286678676629, 1.0261004607357904, 1.0300228584640816, 1.0259359199022853, 1.014179462399377, 0.9952893401487592, 0.969988653297942, 0.9391740512417271, 0.9038974182614229, 0.8653433478382276, 0.8248029205837235, 0.7836443970527855, 0.7432815182922534, 0.7051401717514691, 0.6706242264704969, 0.6410813680561827, 0.6177697701286954, 0.6018264244504868, 0.5942379171252198, 0.595814383870539, 0.60716730470561, 0.6286917091869488, 0.6605532597214147, 0.7026805649904364, 0.7547629509400169, 0.8162537861615785, 0.8863793249987569, 0.9641528986302978, 1.0483941549603382, 1.1377529255706151, 1.2307371852671767, 1.3257444696618796, 1.4210960312343932, 1.5150729465245623, 1.6059533381886202, 1.6920498468355887, 1.7717464795702975, 1.8435339752246946, 1.9060428600620933, 1.9580734214836446, 1.9986218996579013, 2.0269022862809445, 2.042363223690147, 2.0446996137723987, 2.033858671701821, 2.0100402914577886, 1.973691725102335, 1.9254967126526281, 1.8663593307904807, 1.7973829534145533, 1.7198448321343314, 1.6351669074397064, 1.5448835489751884, 1.4506069939909796, 1.3539913049422188, 1.2566956991318952, 1.1603481145030305, 1.0665098659517118, 0.9766422161386991, 0.8920756345149814, 0.8139824494235638, 0.7433535124290273, 0.6809793936018673, 0.6274365138488048, 0.5830784983311044, 0.5480329065748666, 0.5222033632260408, 0.5052769817867017, 0.49673684532860296, 0.4958791862674767, 0.5018347947837212, 0.5135940851389716, 0.5300351634033321, 0.5499541710471928, 0.572097128118879, 0.5951924685206632, 0.6179834489191667, 0.6392596222857008, 0.6578865966530355, 0.6728333485920739, 0.6831964278704512, 0.688220473023516, 0.6873145550117266, 0.6800639752732328, 0.6662372625350038, 0.6457882367319268, 0.6188531351693529, 0.5857429224550859, 0.5469310285416309, 0.5030368753735439, 0.45480565921471305, 0.40308495006773865, 0.3487987493348435, 0.29291971001921396, 0.23644026875887963, 0.18034346471211538, 0.12557422614914512, 0.07301189142635867, 0.023444697206563506, -0.02245308578351541, -0.06414075915260138, -0.10122702070910179, -0.13348158016257533, -0.16084225103317812, -0.18341732128011728, -0.2014831284446639, -0.21547689040407256, -0.22598496696981502, -0.23372684738454996, -0.23953527123179008, -0.2443329925079182, -0.24910678601076133, -0.2548793694855724, -0.2626799722291805, -0.2735143196037014, -0.288334822133461, -0.3080117570232828, -0.33330620901680824, -0.3648454969883302, -0.4031017535019776, -0.44837424821862304, -0.5007759543579131, -0.560224752692377, -0.6264395523560469, -0.6989414849520971, -0.7770602010996684, -0.8599451698460021, -0.9465817545049113, -1.0358117166451528, -1.1263576862036502, -1.2168510329048579, -1.3058624849287375, -1.3919347673544764, -1.4736164771954299, -1.5494963752773896, -1.6182372587699236, -1.678608582334242, -1.7295170205672366, -1.7700342091560644, -1.7994209658707891, -1.8171473737019934, -1.8229082051491112, -1.816633276549059, -1.798492441739126, -1.7688950623440176, -1.7284839244424817, -1.678123705066834, -1.6188842236453207, -1.5520188398842985, -1.4789384776005046, -1.4011818607506668, -1.3203826407366468, -1.2382341706974602, -1.1564527410385992, -1.0767401294385277, -1.0007463370359178, -0.9300333799640842, -0.8660409819013419, -0.8100549694009027, -0.763179108505134, -0.7263110400645844, -0.7001228742369414, -0.68504689418908, -0.6812666977506444, -0.6887139766200077, -0.7070709988443014, -0.7357787249413439, -0.7740503544941324, -0.820889971573703, -0.8751158370529644, -0.9353877666798367, -1.0002379383252589, -1.0681043924140765, -1.1373664280928621, -1.2063810556539531, -1.273519644107543, -1.337203902059713, -1.3959403501862935, -1.4483524840511126, -1.493209885764443, -1.5294536205035005, -1.5562173472767222, -1.5728436801771168, -1.5788954540785918, -1.5741616743626683, -1.5586580607114557, -1.5326222270444863, -1.4965036700572478, -1.4509488643317934, -1.3967818795554547, -1.3349810421268533, -1.2666522567475524, -1.1929996812299895, -1.1152945078284253, -1.034842645490291, -0.9529521185756463, -0.8709009983449765, -0.7899066639209095, -0.7110971500447547, -0.6354852808218118, -0.5639462132934622, -0.4971989240284487, -0.43579206830674005, -0.38009452751347556, -0.33029083895602745, -0.2863815765342299, -0.24818862370537645, -0.215365155189734, -0.18741002400151605, -0.16368613867289694, -0.14344231476461786, -0.12583799744674076, -0.10997018026662995, -0.09490179098182068, -0.07969077986662726, -0.06341913007313912, -0.045221013814867254, -0.024309342215845638, -2.4415260447965187e-16], [0.0, 0.029375679816000942, 0.0632055972336888, 0.10166545055369093, 0.1447652601459985, 0.19234732860770726, 0.24408892697399212, 0.29950964774972283, 0.3579832433834245, 0.41875365115413926, 0.48095479527570834, 0.5436336571461489, 0.6057760176292661, 0.6663342032777175, 0.7242561133407701, 0.778514767671872, 0.8281375982272265, 0.872234709209001, 0.9100253530411879, 0.9408619107611793, 0.9642507250700967, 0.9798692107538824, 0.9875787585849414, 0.9874330528827249, 0.9796815370712119, 0.9647678829840962, 0.943323445309518, 0.9161558092982773, 0.884232664511352, 0.8486613568279435, 0.810664582170958, 0.7715527856272903, 0.7326939163082586, 0.6954812592052703, 0.6613001186285251, 0.6314941621862373, 0.6073322487504201, 0.5899765580358174, 0.5804528133671785, 0.5796233435041293, 0.5881636650980231, 0.6065431859991487, 0.63501053316854, 0.6735838997067392, 0.7220466861428296, 0.7799485845366162, 0.8466121232243206, 0.9211445583804222, 1.0024548692007929, 1.0892754896096164, 1.1801882939999506, 1.2736542504757076, 1.3680460649371544, 1.4616830653698225, 1.552867519692026, 1.6399215438834505, 1.7212237407775068, 1.7952447142775856, 1.8605806287686362, 1.915984028551732, 1.9603911961500597, 1.9929454097747001, 2.013015557125139, 2.020209672681424, 2.0143830860501035, 1.9956409968272144, 1.964335423727975, 1.9210566091872334, 1.8666190920121737, 1.8020427867767141, 1.728529526423521, 1.6474356311286529, 1.5602411593059473, 1.4685165734429322, 1.3738876124215373, 1.2779992016787964, 1.1824792520725476, 1.0889031971987548, 0.9987600972310229, 0.9134210956941378, 0.8341109550069176, 0.7618833186628939, 0.6976002545132238, 0.6419165271032026, 0.5952689300389457, 0.5578708848235444, 0.5297123835822194, 0.5105652227778723, 0.49999334661134537, 0.4973679954601868, 0.5018872394590614, 0.5125993729809074, 0.5284295548811135, 0.5482090041193205, 0.5707060025841784, 0.5946579179878019, 0.6188034404706745, 0.641914227474239, 0.6628251724057433, 0.6804625530482429, 0.6938693744847683, 0.7022272969811013, 0.7048746298607866, 0.7013199755955474, 0.6912512215012043, 0.6745396967063688, 0.6512394364097491, 0.621581620726562, 0.5859643784926376, 0.5449382641545151, 0.4991878253717543, 0.4495097774521721, 0.39678838577035896, 0.34196872676484047, 0.28602855024390056, 0.22994949926583313, 0.1746884579768208, 0.12114979215829517, 0.07015922202259983, 0.022440022660624094, -0.02140781437650053, -0.0609249030043881, -0.09580580502145643, -0.12590803419651134, -0.15125647663007866, -0.17204310174998694, -0.18862196135924578, -0.20149959738796677, -0.21132109928217588, -0.21885216623490733, -0.22495763482256084, -0.2305770263680615, -0.2366977481176571, -0.2443266460459845, -0.2544606531514575, -0.26805730427123, -0.28600589600530385, -0.3091000580581519, -0.338012470447125, -0.37327241034570746, -0.41524674405597983, -0.46412489541173274, -0.5199082238769639, -0.5824041361505502, -0.6512251369338532, -0.7257929006044279, -0.8053473189567356, -0.8889603540835681, -0.9755544030388451, -1.0639247652174317, -1.1527656973245064, -1.2406994470653436, -1.3263075776452014, -1.4081638328469757, -1.4848677484588226, -1.5550781913107758, -1.6175460028233533, -1.671144939947928, -1.714900142361049, -1.7480134099385747, -1.769884647580007, -1.7801289236328943, -1.7785886913335252, -1.7653408373349615, -1.7406983447501836, -1.705206487189874, -1.6596336018682518, -1.6049566207654853, -1.5423416658613047, -1.4731201344723108, -1.398760810782823, -1.3208386370445568, -1.2410008602300133, -1.160931335121063, -1.0823138112791688, -1.0067950579147833, -0.935948686676783, -0.871240517646787, -0.8139962986852463, -0.765372533573444, -0.7263311014448978, -0.6976182605655771, -0.6797485257732043, -0.672993793341434, -0.6773779625029218, -0.6926771723748939, -0.7184256397552616, -0.7539269504378187, -0.7982705275602309, -0.8503528781854195, -0.908903106793359, -0.9725120843527647, -1.039664576567776, -1.1087735668029977, -1.1782159597123965, -1.2463688219063038, -1.3116453067726426, -1.3725294220069328, -1.427608830176507, -1.475604923925428, -1.5153994869172713, -1.546057337567868, -1.5668444528916334, -1.5772411818777434, -1.576950278944557, -1.5658996151929827, -1.5442395552504216, -1.5123351172597126, -1.4707531598297319, -1.4202449594271167, -1.361724651822733, -1.296244109125247, -1.2249649072586308, -1.1491281054592046, -1.0700226078848822, -0.9889529066043459, -0.9072070144090593, -0.8260253849066647, -0.7465715865523364, -0.6699054474895777, -0.5969593206082411, -0.5285180348281366, -0.46520300141768683, -0.40746083563424584, -0.3555567368802237, -0.3095727478687458, -0.2694108880814807, -0.23480103223297696, -0.2053132836625748, -0.18037447858879913, -0.15928835283836873, -0.14125881061244946, -0.12541565737413551, -0.11084209796222387, -0.09660325806889718, -0.0817749633203003, -0.0654720059457957, -0.04687514449587676, -0.025256116855658435, -2.538535710188768e-16], [0.0, 0.030487801917073284, 0.0654665238935023, 0.10502606782160806, 0.14909154356190296, 0.19742384603916116, 0.24962486974923467, 0.3051472331548618, 0.36330826727863136, 0.4233079107825805, 0.4842500508057811, 0.5451667574381299, 0.6050447822740778, 0.6628536299985922, 0.7175744679942853, 0.7682291136691101, 0.8139083332657572, 0.8537986995185464, 0.887207288371947, 0.9135835462836653, 0.9325377281563886, 0.9438553899935619, 0.947507517881089, 0.9436559834425569, 0.9326541328030798, 0.9150424384145356, 0.8915392677892048, 0.8630269471402967, 0.8305334180288488, 0.7952098983487556, 0.7583050624916184, 0.7211363467029732, 0.685059062155135, 0.651434058162803, 0.6215947197079023, 0.5968141059199937, 0.5782730387540311, 0.5670299336863117, 0.5639931271765622, 0.5698963997712413, 0.5852783203699832, 0.6104659480986405, 0.6455633255762124, 0.690445083616682, 0.7447553553368511, 0.807912070225037, 0.8791165690777237, 0.9573683520075118, 1.041484647123811, 1.1301243700499162, 1.221815937057233, 1.3149882999175244, 1.4080044909368794, 1.4991969040137456, 1.5869034935161084, 1.6695040484034873, 1.745455694950378, 1.8133267977843563, 1.8718284653588924, 1.9198429215710981, 1.9564480786707754, 1.980937736114034, 1.992836933423154, 1.991912099913958, 1.9781757675532299, 1.9518857422116256, 1.913538760044976, 1.8638587864723057, 1.8037802420444853, 1.7344265593325328, 1.6570845849014322, 1.5731754378101508, 1.4842225185376854, 1.3918174277916853, 1.2975846017402703, 1.2031454977029066, 1.1100831716083124, 1.019908075438523, 0.9340258697905693, 0.8537079944529571, 0.780065669834565, 0.7140279159553788, 0.6563240756607456, 0.6074712172405793, 0.5677666714862963, 0.5372858323731706, 0.5158852221206992, 0.5032106935224733, 0.4987105182929639, 0.5016529927963437, 0.5111480847728302, 0.5261725491876266, 0.5455978604136807, 0.5682202435734699, 0.5927920415441591, 0.6180536269607945, 0.6427650611419591, 0.6657367143278428, 0.6858580935839923, 0.7021241753234267, 0.7136586073112696, 0.7197332284877556, 0.7197834518412667, 0.7134191634165704, 0.70043090662003, 0.6807912423485133, 0.6546512990612012, 0.6223326496224828, 0.5843147704866511, 0.5412184505928441, 0.49378561939245175, 0.44285615319058774, 0.38934229421009475, 0.3342013756109229, 0.27840758666388277, 0.22292353438064091, 0.16867236061178642, 0.11651115690026721, 0.06720638366628699, 0.021411946526974257, -0.0203494879008181, -0.057701439704411876, -0.0904244279242537, -0.11846235665221425, -0.14192430001714496, -0.16108163135877065, -0.1763605636311289, -0.18833028820333267, -0.19768701468736116, -0.20523432228477678, -0.21186033066135918, -0.21851228304373368, -0.22616920391930573, -0.23581334661987097, -0.248401180810356, -0.26483468557282774, -0.28593370993615935, -0.3124101394074852, -0.34484456485569387, -0.3836660899984784, -0.42913583722256027, -0.48133462040612, -0.54015515006551, -0.6052990230798453, -0.6762786292702188, -0.7524239832169937, -0.8328943649851809, -0.9166945310172284, -1.0026951394176828, -1.0896569251397947, -1.1762580629348556, -1.2611240718153682, -1.342859546356189, -1.4200809491713415, -1.491449666686277, -1.5557045177406308, -1.6116929119843995, -1.6583998823540935, -1.6949742625252222, -1.7207513450439684, -1.7352714373022833, -1.7382938286794527, -1.7298057907048792, -1.7100263503660482, -1.6794047018118057, -1.638613250628602, -1.58853541444129, -1.5302484306340818, -1.4650015433814048, -1.3941900549371657, -1.3193258274760182, -1.2420049092101935, -1.163873029857068, -1.0865897640345594, -1.0117921954789866, -0.9410589292466025, -0.8758752929012638, -0.8176005412315431, -0.7674378329042946, -0.7264076827537003, -0.6953255116862295, -0.6747838194310825, -0.6651393959294938, -0.6665058676929838, -0.6787517488737403, -0.7015040361581143, -0.734157255093094, -0.7758877362827851, -0.8256727761861142, -0.8823142220118684, -0.9444659162367808, -1.010664346083561, -1.0793617690650674, -1.1489610292122814, -1.2178512412048565, -1.2844435021914125, -1.3472057940097149, -1.404696261682084, -1.45559409685931, -1.4987273162271726, -1.533096803229257, -1.5578960748395123, -1.5725263412121566, -1.5766065422117248, -1.5699781682051415, -1.5527048000320198, -1.5250664316139966, -1.487548765055575, -1.4408277892240213, -1.3857500657075188, -1.323309247981673, -1.2546194480850945, -1.1808861379741427, -1.1033753282455994, -1.0233818037680078, -0.9421972130982785, -0.8610788060165269, -0.7812195912201725, -0.7037206448000032, -0.6295662406728194, -0.559602398209748, -0.4945193518268917, -0.43483834460414567, -0.3809030356771029, -0.3328756920501312, -0.2907382126125986, -0.2542979086008979, -0.22319784364275136, -0.19693142088758653, -0.1748607974653618, -0.1562386103091157, -0.14023241462564193, -0.12595116906440534, -0.11247305158520474, -0.09887385839432818, -0.08425522587682381, -0.06777192248541009, -0.048657483850719226, -0.02624750926438835, -2.637803357123145e-16], [0.0, 0.03158746667630958, 0.06766115957758789, 0.10822666584964503, 0.15312711297836298, 0.20204628197090815, 0.2545162304539437, 0.309929232995808, 0.36755373270540864, 0.4265538926116453, 0.48601224016994066, 0.5449548159034713, 0.6023781697714918, 0.6572774980975279, 0.7086751811003691, 0.7556489671142538, 0.7973590548522197, 0.8330733494661543, 0.862190211115521, 0.8842580752337016, 0.8989914001944501, 0.9062824887440817, 0.9062088321323639, 0.8990357377986501, 0.8852141199621647, 0.8653734545691342, 0.8403100227106178, 0.8109706867692217, 0.7784325581621946, 0.7438790217362313, 0.7085726769528834, 0.673825837570726, 0.640969297500696, 0.6113201191870998, 0.5861492309778811, 0.5666496306815378, 0.5539059835319038, 0.5488663742514011, 0.5523169254594797, 0.5648599294268498, 0.5868960586823503, 0.6186111251977758, 0.6599677501241216, 0.7107021889485353, 0.7703264333390223, 0.8381355838638709, 0.9132203603265989, 0.9944844917713709, 1.080666609352334, 1.1703661551489228, 1.2620727213630774, 1.3541981495909297, 1.44511065112021, 1.5331701581741775, 1.6167640839799624, 1.6943426572953977, 1.7644530049108271, 1.8257711834848944, 1.8771314092202558, 1.9175517992075306, 1.9462560201885077, 1.9626903370303201, 1.9665356620199186, 1.957714324540396, 1.936391405899088, 1.9029706129978639, 1.858084794034094, 1.802581326348343, 1.737502727807686, 1.6640629557873416, 1.5836199591557139, 1.4976451362258636, 1.4076904232963903, 1.3153537924442413, 1.2222439723622218, 1.1299452214307926, 1.039982977537777, 0.9537911845641457, 0.8726820515809554, 0.7978189387657673, 0.7301929854048226, 0.6706040020634114, 0.6196460434016524, 0.5776979628050746, 0.5449191278419981, 0.5212503495687021, 0.5064199519831557, 0.4999547835948227, 0.5011958541822494, 0.5093181692618333, 0.5233542352875669, 0.5422206225610817, 0.5647469023338387, 0.589706221319243, 0.6158467420614164, 0.6419231621275844, 0.6667275292203477, 0.6891185928746293, 0.7080489757592678, 0.7225895076270105, 0.7319501410933694, 0.7354969587212993, 0.7327648830428608, 0.7234658125680579, 0.7074920246962352, 0.6849148077826241, 0.6559784063670684, 0.6210894826838889, 0.580802411053623, 0.5358008267673409, 0.48687594498809933, 0.43490224566979757, 0.3808111855299788, 0.3255636460992343, 0.2701218566253067, 0.2154215414138688, 0.16234503279683712, 0.11169606357220647, 0.06417690717321325, 0.02036847117379912, -0.019286128374404413, -0.054494075858637074, -0.08512111507835189, -0.11119533632363152, -0.1329063865536785, -0.150600117349656, -0.16476880468971433, -0.176037190630583, -0.18514470673125238, -0.19292433972849438, -0.2002786890067951, -0.20815384052345096, -0.21751174112838997, -0.229301799129941, -0.24443246040987351, -0.2637435137544797, -0.2879798641933189, -0.3177674793571383, -0.3535921619906472, -0.3957817330492495, -0.4444921259612564, -0.4996977957211789, -0.5611867388994595, -0.6285603050856173, -0.7012378596065315, -0.7784662345945838, -0.8593337836954947, -0.9427887379583102, -1.027661449702192, -1.1126900101993151, -1.1965486384060648, -1.277878163969134, -1.3553178702239406, -1.4275379233788297, -1.4932715935845797, -1.551346472699198, -1.6007139123619178, -1.6404759440879257, -1.6699089996082679, -1.6884838232704227, -1.6958810572217613, -1.6920020821751447, -1.6769748093281074, -1.6511542397296042, -1.615117733115021, -1.5696550558855509, -1.5157534043631957, -1.4545777216030917, -1.387446740885962, -1.315805293716423, -1.2411935121330067, -1.165213632117821, -1.0894951649677318, -1.0156592451571735, -0.945282985438402, -0.8798646721161595, -0.8207906155204114, -0.7693044330945508, -0.7264794861126442, -0.693195117193984, -0.6701172462806269, -0.6576837797521714, -0.656095173371008, -0.6653103675497685, -0.685048185980863, -0.7147941590648581, -0.7538126049708977, -0.8011636766842368, -0.8557249660667563, -0.9162171486233232, -0.9812330579304327, -1.0492694988344593, -1.1187610454885821, -1.1881150255804007, -1.255746866766347, -1.3201149759574298, -1.3797543367870195, -1.4333080449365498, -1.4795560541182469, -1.5174404760751392, -1.546086864190997, -1.5648210100581907, -1.5731808931519866, -1.5709235428614918, -1.5580266965864984, -1.5346852643561697, -1.5013027363399454, -1.458477791610367, -1.4069864815920894, -1.3477604669790264, -1.2818618799564878, -1.2104554620713337, -1.1347786901595587, -1.0561106468879944, -0.9757404176626189, -0.894935801340877, -0.814913108285289, -0.7368087862229264, -0.6616535630182258, -0.5903497271665432, -0.5236520833322419, -0.4621530237227125, -0.4062720489637135, -0.3562499571357003, -0.31214779965144934, -0.2738505807256712, -0.2410755563747237, -0.21338487222183847, -0.1902021697944053, -0.17083269122634373, -0.15448632481124872, -0.14030296086939745, -0.12737947070540775, -0.1147975824433412, -0.10165190718595295, -0.0870773677383032, -0.07027530006505942, -0.05053753423618014, -0.027267815908764693, -2.737849287116157e-16], [0.0, 0.0326593164669299, 0.06975994873334329, 0.11122542857802041, 0.1568205456075324, 0.20615689335385282, 0.2587027612179056, 0.313797118058088, 0.3706673257519964, 0.42845012273273986, 0.4862153308228374, 0.5429916658715584, 0.59779397561108, 0.6496511882541603, 0.6976342337008493, 0.7408831963860274, 0.7786329748924997, 0.8102367581093446, 0.8351866800984586, 0.8531310846633349, 0.8638879141973994, 0.8674538336560094, 0.864008807055713, 0.8539159581034864, 0.8377166655475097, 0.8161209646443139, 0.7899934457277173, 0.7603349562399605, 0.7282605208405374, 0.6949739926106371, 0.6617400344278511, 0.6298541011059579, 0.6006111480445443, 0.5752738294826857, 0.5550409680091342, 0.5410170762225479, 0.534183691312045, 0.5353732442739471, 0.5452461283988803, 0.5642715579069012, 0.5927127189455694, 0.6306166137380746, 0.6778088869370643, 0.7338938039258714, 0.7982594268262411, 0.8700879083552936, 0.9483706995051804, 1.0319283473475387, 1.119434447036952, 1.2094432100703334, 1.3004200215729431, 1.390774285037852, 1.478893795391439, 1.5631798419299845, 1.642082222563597, 1.7141333504343814, 1.777980653383601, 1.8324165054800978, 1.8764049869678234, 1.9091048431706459, 1.9298881023161452, 1.9383539147411968, 1.9343372890339954, 1.9179125216031276, 1.8893912420051793, 1.849315124048952, 1.798443439122435, 1.7377357502854631, 1.6683301604707999, 1.5915176328532223, 1.5087129935427583, 1.421423304007427, 1.3312143511714727, 1.2396760455162614, 1.1483875407286006, 1.0588828919616764, 0.972618053547038, 0.8909399814564206, 0.8150585518672692, 0.7460219361934464, 0.6846959866773598, 0.631748087248107, 0.5876358142981584, 0.5526006340416998, 0.5266667401048534, 0.5096450099931696, 0.5011419351597765, 0.5005732596001181, 0.5071819491598755, 0.5200600108145695, 0.5381735905671905, 0.5603907025087324, 0.5855108818266039, 0.612296012549726, 0.6395015575655533, 0.665907414445256, 0.6903476359019135, 0.711738287836873, 0.7291027699881963, 0.741593992825667, 0.7485128877725704, 0.7493228239444755, 0.7436596109370357, 0.7313368810759546, 0.7123467630878062, 0.686855879374572, 0.6551968179559612, 0.6178553446992714, 0.5754537288182358, 0.5287306521064584, 0.47851825754645433, 0.4257169636831412, 0.37126872571728986, 0.31612946131516145, 0.26124137774239603, 0.20750593667451872, 0.15575817394954347, 0.10674305411972085, 0.06109448490010948, 0.019317545907660407, -0.018225598757089102, -0.05132573135056156, -0.07993228834322767, -0.10415459202730713, -0.12425856968604776, -0.14065904217702005, -0.15390777979070125, -0.16467763427513318, -0.17374315914526217, -0.18195822319448027, -0.19023120212985742, -0.19949839841600164, -0.21069638806186705, -0.2247340239607524, -0.24246483768274305, -0.2646605749742803, -0.2919865747704077, -0.32497965787358324, -0.36402913065914105, -0.4093614327241543, -0.4610288671916226, -0.5189027506523568, -0.5826712090023088, -0.6518417284736523, -0.7257484508852456, -0.8035640815628122, -0.8843161605258614, -0.9669073353695747, -1.0501391706134644, -1.1327389357651636, -1.2133887353069734, -1.2907562802731525, -1.3635265546845756, -1.430433602058731, -1.4902916482777833, -1.5420247875631254, -1.5846944879781604, -1.6175242210911047, -1.639920586045232, -1.6514903797395095, -1.6520531601573571, -1.6416489567867671, -1.6205408979521059, -1.5892126469001737, -1.5483606636671157, -1.498881435031185, -1.4418539371536314, -1.3785177118189729, -1.3102470446409515, -1.2385218295499796, -1.1648957859482643, -1.0909627610747012, -1.018321898715617, -0.9485424852110528, -0.8831292939812171, -0.8234892402531191, -0.7709001285094744, -0.726482227096851, -0.691173338568956, -0.6657079522911633, -0.6506009695785008, -0.6461363835148685, -0.6523611782308861, -0.6690845886533535, -0.6958827345891199, -0.7321085155615988, -0.7769065281771488, -0.829232648989715, -0.8878778157400835, -0.951495441140934, -1.0186318084497328, -1.0877587289693111, -1.1573076900014838, -1.2257046888836176, -1.2914049353330992, -1.3529266107024522, -1.4088828987158537, -1.4580115471429678, -1.499201282531851, -1.531514478998302, -1.554205575187555, -1.5667348385725304, -1.5687771906279964, -1.560225927294998, -1.5411912935427228, -1.511993995682927, -1.4731538573274516, -1.4253739415053324, -1.36952056962029, -1.3065997649950873, -1.2377307323592435, -1.164117052771987, -1.0870163245014957, -1.0077090131004496, -0.9274672875787333, -0.847524613903783, -0.7690468522646926, -0.6931055612994553, -0.6206541519441986, -0.5525074572858922, -0.489325194740132, -0.4315996953275977, -0.37964816436212506, -0.3336096212821359, -0.293446546595484, -0.2589511439782417, -0.2297560084824211, -0.2053488805005016, -0.18509106239077272, -0.16823898305224239, -0.15396831753325205, -0.14140000590633273, -0.12962746969718036, -0.11774429624527129, -0.10487165217043716, -0.09018469682544374, -0.0729372949553404, -0.05248437401758901, -0.028301334550551917, -2.8372138025815163e-16], [0.0, 0.03368857354818333, 0.07173488021301784, 0.113983392544268, 0.1601248694125861, 0.20970421110768353, 0.26213246222973985, 0.3167026508239668, 0.3726090513084817, 0.4289693683025601, 0.4848492607815747, 0.5392885630522117, 0.5913285124727298, 0.6400392648433896, 0.6845469677259625, 0.7240596699221595, 0.7578913717841804, 0.7854835653168616, 0.8064236740811985, 0.8204598792215456, 0.8275119076260686, 0.8276774590655777, 0.8212340586296061, 0.8086362361591217, 0.7905080527778768, 0.7676311130829858, 0.7409283170961414, 0.7114437157929953, 0.6803189351518497, 0.648766723634673, 0.6180422545469029, 0.589412875860644, 0.5641270442511269, 0.5433832061298814, 0.5282993956497094, 0.5198843077626695, 0.5190105736628856, 0.5263909170395178, 0.5425578036521719, 0.5678471153957575, 0.6023862852044763, 0.6460872231529511, 0.6986442495254411, 0.7595371302383189, 0.8280391867620641, 0.9032303296186979, 0.9840147446522043, 1.0691428475332316, 1.1572370171693889, 1.2468205254374871, 1.3363490012429726, 1.4242437033169442, 1.50892582996867, 1.5888510663825504, 1.6625435616896038, 1.7286285391895382, 1.7858627735066293, 1.8331622174148943, 1.8696261273942858, 1.8945571190818273, 1.9074766796746616, 1.9081357717017866, 1.8965202788021935, 1.8728511664058727, 1.8375793555392241, 1.7913754333211065, 1.735114446033284, 1.6698561369670895, 1.59682109874251, 1.5173634058593066, 1.4329403755464485, 1.3450801715384284, 1.255348014624618, 1.165311794516429, 1.0765078890374293, 0.9904079886166806, 0.9083876967862796, 0.831697631553367, 0.7614376892915924, 0.6985350537594924, 0.6437264399715148, 0.597544958226246, 0.5603118702207088, 0.5321333896490233, 0.5129025569452285, 0.5023060949027855, 0.49983603180591935, 0.5048057643826347, 0.5163701271298876, 0.5335489399443021, 0.5552534248126226, 0.5803148165328709, 0.6075144436232237, 0.6356145248799875, 0.663388915166985, 0.6896530411857067, 0.7132922939455466, 0.7332881887168582, 0.7487416642484876, 0.7588929693902325, 0.7631376750239124, 0.7610384500905213, 0.7523323499482663, 0.7369334805426192, 0.7149310200110284, 0.6865826974113842, 0.6523039432924461, 0.6126530359351883, 0.5683126675592729, 0.5200684441023472, 0.4687849081194844, 0.4153797350323209, 0.36079679688461647, 0.3059788138581717, 0.2518403214445738, 0.199241670192958, 0.14896474566918444, 0.10169104943468382, 0.057982718692111496, 0.01826698436805348, -0.017175523201683144, -0.04821831284371888, -0.07489221611167597, -0.09738413054118668, -0.11603135344552275, -0.13131165249664134, -0.1438293310424409, -0.15429765129024625, -0.1635180744640417, -0.1723568613744674, -0.18171964737360008, -0.1925246605945715, -0.2056752902841371, -0.22203273193644146, -0.24238943729276813, -0.2674440800152265, -0.2977787123704288, -0.33383873542907105, -0.37591623639333777, -0.4241371634060423, -0.47845271263681577, -0.5386351969571612, -0.604278552736688, -0.6748035240341009, -0.749467444653339, -0.8273784211664522, -0.9075136070204839, -0.988741152091425, -1.069845316196719, -1.1495541515590102, -1.2265690901563568, -1.299595719071136, -1.3673749917332754, -1.4287141062815139, -1.4825162846169073, -1.5278087071032398, -1.5637678978134415, -1.589741912802366, -1.6052687577378888, -1.610090549571367, -1.6041630376396865, -1.5876602102185027, -1.5609738303937788, -1.524707867306218, -1.4796679123579193, -1.426845791820577, -1.3673997044536177, -1.3026303223430313, -1.2339533925021555, -1.1628694633780061, -1.0909314321338937, -1.0197106636455546, -0.9507624691768533, -0.8855917507544336, -0.8256196158673937, -0.7721517462816537, -0.7263492649610535, -0.6892027872747798, -0.6615102682319487, -0.6438591682167041, -0.6366133577616708, -0.6399050697670499, -0.65363208796943, -0.6774602362952473, -0.7108311080168571, -0.7529748494207761, -0.8029276930164014, -0.8595538230669276, -0.9215710541359866, -0.987579713888402, -1.0560940467240973, -1.1255753967607114, -1.1944663886040865, -1.2612253032060352, -1.3243598443908133, -1.3824595093428307, -1.434225813020532, -1.4784996711619687, -1.5142853179023708, -1.5407702202526106, -1.5573405506462934, -1.5635918880004493, -1.5593349345491512, -1.5445961572190863, -1.5196133855286462, -1.484826519879132, -1.4408636216787125, -1.3885227671197695, -1.3287501469248233, -1.2626149825419728, -1.1912819029741164, -1.1159814838962119, -1.0379796905859586, -0.9585469875393954, -0.8789278799983699, -0.8003116359888758, -0.7238049023357276, -0.650406875416563, -0.5809876185178271, -0.5162700343286714, -0.4568159054813949, -0.4030163105476883, -0.35508661019753773, -0.31306608116504725, -0.2768221571893116, -0.24605911918395296, -0.22033096446715644, -0.19905807976761994, -0.18154724753578452, -0.16701443220557696, -0.15460972452883806, -0.14344376963854877, -0.13261496937817113, -0.12123673251579521, -0.10846404813796952, -0.09351867771573996, -0.07571229951555324, -0.054466994199385985, -0.029332531204025764, -2.934472363064341e-16], [0.0, 0.034661187129016176, 0.07355975784662186, 0.11646481035062632, 0.16299798281864222, 0.21264347460341795, 0.2647619860709491, 0.3186082127820865, 0.373351436091161, 0.4280986702421431, 0.4819197577763215, 0.5338737522733624, 0.583035891489444, 0.6285244457689081, 0.6695267266800433, 0.7053235591927424, 0.735311556947237, 0.7590225933804543, 0.7761399303730606, 0.7865105489533405, 0.7901533213872549, 0.7872627683382184, 0.7782082560920864, 0.7635286043300035, 0.7439221917015733, 0.7202327615727775, 0.6934312409018746, 0.6645939884443413, 0.6348779817941149, 0.6054935337647643, 0.577675195234566, 0.5526515521111882, 0.531614657199364, 0.5156898525932491, 0.5059067343318582, 0.5031719884831768, 0.5082447870567007, 0.5217153741343521, 0.5439873987350013, 0.5752644629633203, 0.6155412540675482, 0.6645995195716152, 0.7220090283245313, 0.7871335399687651, 0.8591416839191987, 0.9370225294470741, 1.0196055138195725, 1.105584288481403, 1.1935439466221056, 1.28199101154413, 1.3693854961155054, 1.4541742909800208, 1.5348251044265173, 1.6098601607701029, 1.6778888671961496, 1.7376386812178979, 1.7879834516866908, 1.8279685647003927, 1.8568323003780258, 1.87402289550599, 1.8792109083584603, 1.8722965930951514, 1.853412109346253, 1.8229185150347902, 1.7813976141848917, 1.7296388534133098, 1.6686215780371945, 1.5994930684054598, 1.5235428765122179, 1.4421740697679803, 1.3568720608877611, 1.2691717584668716, 1.180623810622092, 1.0927607331820506, 1.0070637138793224, 0.9249308648606669, 0.847647658091902, 0.7763602228468965, 0.7120521128241937, 0.6555250643151367, 0.6073841683920327, 0.5680277717310415, 0.5376423051090354, 0.5162021186654457, 0.5034742816512364, 0.4990281845780342, 0.5022496663679414, 0.5123592811081392, 0.5284342209673929, 0.5494333261159884, 0.5742245411787726, 0.6016141225542516, 0.630376863160528, 0.6592865816956506, 0.6871461227455888, 0.7128161319916333, 0.7352419068519567, 0.7534776761808079, 0.7667077317590564, 0.7742639174677036, 0.7756390771210805, 0.7704961665368889, 0.7586728468914362, 0.7401814919405502, 0.7152046583742335, 0.6840861834875706, 0.647318184613568, 0.6055243376187723, 0.5594399046438762, 0.5098890618672169, 0.4577601443793904, 0.40397947564361975, 0.3494844822426384, 0.2951968098748993, 0.24199615350933282, 0.19069549334778013, 0.142018389344625, 0.09657893150374047, 0.054864872441471854, 0.017224384579897705, -0.016143211037637772, -0.04519250150932208, -0.07003269198096833, -0.09092394999288719, -0.1082694797777524, -0.12260353381249842, -0.13457567546064586, -0.14493170510776077, -0.15449175028400458, -0.16412609563873715, -0.1747293893567061, -0.187193907124814, -0.20238258192095102, -0.22110251698584618, -0.24407969009346347, -0.27193552985428904, -0.30516599992442267, -0.34412376574769243, -0.3890039423373984, -0.43983383249410124, -0.4964669649708044, -0.5585816339258899, -0.6256840272485243, -0.697115914847338, -0.7720667516818672, -0.8495899371091591, -0.9286228648661077, -1.0080102994186049, -1.0865305269792895, -1.1629236554503808, -1.2359213787821524, -1.3042774792702425, -1.3667983172494564, -1.4223725521396327, -1.469999352060653, -1.5088143809942343, -1.5381129020045825, -1.5573694011706578, -1.5662532180480306, -1.5646397627101538, -1.5526170044321244, -1.5304870303175604, -1.498762590865413, -1.4581586707221248, -1.4095792436905565, -1.3540994885002484, -1.2929438529913457, -1.2274604564847613, -1.1590924106783098, -1.0893467161780024, -1.0197614528364625, -0.9518720259001457, -0.887177255459994, -0.8271061031996421, -0.7729858177520007, -0.7260122483882459, -0.6872230270174817, -0.6574742517603693, -0.6374212232821326, -0.6275036896142333, -0.6279359486719263, -0.6387020426722629, -0.6595561579668834, -0.6900282203595062, -0.7294345527801267, -0.7768933422313453, -0.8313445491217806, -0.8915737872209621, -0.956239609053113, -1.0239035518566786, -1.093062235196478, -1.1621807544667873, -1.2297265859840576, -1.2942032098055973, -1.3541826660285219, -1.4083362888532074, -1.4554629094067797, -1.4945138820385204, -1.5246143679286692, -1.5450804024275093, -1.5554313762677083, -1.5553976731051684, -1.5449233239701194, -1.5241636602417836, -1.4934780677209973, -1.4534180622978603, -1.4047110197088306, -1.3482399952147732, -1.285020161192846, -1.216172469386921, -1.1428952080055648, -1.066434170478645, -0.9880521813879062, -0.9089987352246253, -0.8304804950108359, -0.753633370728056, -0.6794968526649534, -0.6089912133978954, -0.5428981157399742, -0.4818450745884844, -0.42629412044072634, -0.37653490397004413, -0.332682367193808, -0.2946789902890368, -0.2623015069460847, -0.23517186820836267, -0.21277212785298114, -0.19446282419285, -0.17950434617173877, -0.16708069794255243, -0.1563250175903783, -0.14634616372765524, -0.13625565937237008, -0.1251942764008796, -0.11235755606639138, -0.09701959125313565, -0.0785544435039352, -0.056454631192610155, -0.030346202889009535, -3.028250144757066e-16], [0.0, 0.03556397042031615, 0.07521044741445719, 0.11863747398809663, 0.1654030155193898, 0.2149369870892549, 0.26655694234209765, 0.3194870118115124, 0.3728795929010815, 0.4258392206348752, 0.4774479897525418, 0.5267918562219984, 0.5729871208779557, 0.6152063903356156, 0.6527033207970557, 0.6848354786308737, 0.7110846969834344, 0.7310743690610774, 0.7445831945915458, 0.7515549844480166, 0.7521042272990566, 0.746517228966364, 0.7352487472593502, 0.7189141596045603, 0.6982773149244522, 0.6742343320746961, 0.6477937119284333, 0.6200532262526682, 0.5921741314209129, 0.5653533265855993, 0.5407941323593224, 0.5196764058650246, 0.5031267301618599, 0.492189419923076, 0.4877990706755287, 0.49075534620600886, 0.5017006486473152, 0.521101249460026, 0.5492323786119927, 0.5861676756801705, 0.6317733026299921, 0.685706906199592, 0.7474215008630093, 0.8161742241337119, 0.8910397974243695, 0.9709284107174415, 1.0546076407572735, 1.1407279130287526, 1.227850929901463, 1.3144804131726007, 1.3990944506830565, 1.4801786951750018, 1.55625964015513, 1.6259371928309911, 1.6879157783461909, 1.7410332422381354, 1.7842868685092284, 1.8168558977322946, 1.838120011589671, 1.8476733451917653, 1.8453336941348446, 1.8311466969769261, 1.8053848928730127, 1.7685416756231305, 1.7213202863948305, 1.6646181049444946, 1.599506610421895, 1.5272074850979407, 1.4490654251254813, 1.3665182995288008, 1.2810653601566884, 1.194234249845969, 1.1075475824649466, 1.0224898762207493, 0.9404756104617288, 0.8628191464889684, 0.7907072053674776, 0.7251745315913815, 0.6670832923078989, 0.6171066696077477, 0.5757170004278963, 0.5431787074298106, 0.5195461475541331, 0.5046663856820487, 0.498186781884648, 0.499567165030769, 0.5080962558819775, 0.5229119019060073, 0.543024596341274, 0.5673436777174548, 0.5947055449180357, 0.6239031784175855, 0.6537162315812103, 0.6829409474773765, 0.7104191666742291, 0.7350657196520665, 0.7558935430096463, 0.7720359203784898, 0.7827653252966726, 0.787508432281794, 0.7858569617210784, 0.7775741314506822, 0.7625966003210204, 0.7410319038118027, 0.7131514959886313, 0.6793796229206585, 0.640278357335097, 0.5965292201577851, 0.5489118992930152, 0.4982806474275497, 0.4455389970367459, 0.3916134707383399, 0.3374269877093292, 0.28387267151943385, 0.2317887513576927, 0.18193521760662515, 0.1349728448642264, 0.09144513206329705, 0.05176363191741548, 0.016197052510547667, -0.015135585279004582, -0.04226755714819117, -0.06538274496934465, -0.08480969254311703, -0.1010115647317747, -0.11457227449924003, -0.12617914295080024, -0.13660254874278627, -0.14667310289700403, -0.15725695107394067, -0.16922985604302543, -0.18345074713268858, -0.20073543996081195, -0.2218312282909933, -0.24739303043728075, -0.2779617357073079, -0.3139453428296009, -0.35560341347274715, -0.4030352815359501, -0.45617236492008345, -0.5147748233168089, -0.5784326957568564, -0.6465715379839605, -0.7184624650178668, -0.7932363914189182, -0.8699021536083947, -0.947368097862023, -1.024466626827763, -1.0999811189293358, -1.1726745708078259, -1.2413192646781388, -1.304726731394215, -1.361777266960669, -1.4114482655862248, -1.4528406560761196, -1.4852027698807433, -1.507951027486849, -1.5206869036658246, -1.5232097196049825, -1.5155249090233514, -1.4978475136032776, -1.4706007778116914, -1.4344098316321197, -1.3900905689749907, -1.3386339466487376, -1.2811860408735993, -1.2190243026380736, -1.1535305471559776, -1.0861612939512442, -1.0184161406584724, -0.9518049038180906, -0.8878142925046052, -0.8278748947247208, -0.7733292517811817, -0.7254017723026587, -0.6851711959336529, -0.6535462577534308, -0.6312451297635167, -0.6187791270525111, -0.616441065662089, -0.6242985491777382, -0.6421923443225253, -0.669739885178306, -0.706343824028963, -0.7512054271713061, -0.8033424992793715, -0.8616114128251813, -0.9247327222530727, -0.9913197584223638, -1.0599095293113903, -1.1289951997910457, -1.1970593877038298, -1.2626074963675258, -1.3242003053512934, -1.3804850618742015, -1.43022435391954, -1.4723221021640032, -1.505846079688204, -1.5300464543755599, -1.5443699467896495, -1.5484693037246975, -1.542207901899345, -1.5256594145949947, -1.4991025935174636, -1.4630113358519317, -1.4180403195036877, -1.3650065951093338, -1.3048676189920867, -1.2386962945001803, -1.1676536580980734, -1.092959899523631, -1.0158644410272404, -0.937615818346889, -0.8594321052719979, -0.7824726044909734, -0.7078114904414681, -0.6364140360673359, -0.5691159861273372, -0.506606556773739, -0.44941544663637356, -0.39790414100393984, -0.3522616805077691, -0.31250495175931775, -0.27848344253469726, -0.24988829121832146, -0.2262653521379911, -0.2070318978453361, -0.19149648882511994, -0.17888146280631614, -0.16834743173772782, -0.15901912616267574, -0.15001189536408593, -0.14045815800878017, -0.12953310240735247, -0.11647895777996319, -0.10062719748529418, -0.08141809100224494, -0.05841709211584639, -0.0313276344424506, -3.117235850326852e-16], [0.0, 0.03638472628062963, 0.07666509756661856, 0.12047299490834641, 0.16730862706589533, 0.21655438902772273, 0.26749210033505505, 0.3193231686854493, 0.37119114694215877, 0.42220608788395597, 0.47147005242502055, 0.518103094867067, 0.5612690338537075, 0.6002003204835399, 0.6342213354623983, 0.6627694847515032, 0.6854135169796455, 0.7018685546073169, 0.7120074127554404, 0.7158678727032495, 0.713655678997326, 0.70574313734925, 0.6926633023225557, 0.6750998564155447, 0.6538728927046891, 0.6299209189392398, 0.6042794992016504, 0.5780570374830791, 0.5524082835251399, 0.5285062031054564, 0.5075129010020787, 0.490550313956539, 0.4786714022836205, 0.472832562004378, 0.47386795461365727, 0.482466409387955, 0.4991514944820636, 0.5242652793522429, 0.5579562240549074, 0.6001715328112507, 0.6506542022893973, 0.7089448819485533, 0.774388547284284, 0.8461458697703409, 0.9232090525891388, 1.0044217917070335, 1.0885029201865415, 1.174073202351363, 1.2596846657958094, 1.343851795214676, 1.4250838642231756, 1.5019176509436145, 1.57294977093428, 1.6368678673587005, 1.6924799230183367, 1.7387410014249638, 1.7747767834589812, 1.7999033409218268, 1.813642676641117, 1.8157336605885612, 1.806138100303674, 1.7850417991389966, 1.7528505746557574, 1.7101813290146781, 1.6578483805195277, 1.5968453777293337, 1.5283232220311955, 1.4535645187227642, 1.373955158208337, 1.2909536958914474, 1.20605925013388, 1.120778671027824, 1.0365937479034617, 0.954929220124011, 0.8771223339143617, 0.8043946482898485, 0.7378267365977842, 0.6783363581680749, 0.6266605888799381, 0.5833423022117024, 0.5487212859526064, 0.522930166842735, 0.5058951987491838, 0.49734185244949936, 0.49680502956016936, 0.5036436124462244, 0.5170589587809404, 0.5361168563041264, 0.5597723725122421, 0.5868969674538295, 0.6163071870932305, 0.646794221042786, 0.6771535926227443, 0.7062142515201206, 0.7328663596633911, 0.7560870987430499, 0.7749638820904928, 0.7887144229745024, 0.7967031940097288, 0.79845390619269, 0.7936577387115971, 0.782177159526581, 0.7640452890469505, 0.7394608722212314, 0.7087790351728173, 0.6724981083877868, 0.6312428967498009, 0.5857448649724483, 0.5368197830103976, 0.48534343795540325, 0.43222606521675666, 0.378386181317576, 0.3247245127001394, 0.2720987092567243, 0.22129950806436346, 0.17302897262098432, 0.12788137680042358, 0.08632723220728113, 0.048700874424814994, 0.01519192993224981, -0.014159116391973032, -0.039461140677332175, -0.06096838411223571, -0.0790723496344194, -0.09428980674366896, -0.10724722190291466, -0.11866202588125513, -0.12932121279646297, -0.1400578364103551, -0.1517260256100226, -0.165175181525397, -0.18122404234148123, -0.20063530793928488, -0.2240915048613891, -0.25217274301002246, -0.2853369696509631, -0.323903264840895, -0.3680386468388508, -0.4177487682805377, -0.4728727860741346, -0.5330825825597354, -0.597886405099255, -0.6666368786953816, -0.7385432343038748, -0.8126874870192504, -0.8880441960153836, -0.9635033445965551, -1.0378957963335091, -1.1100207141233438, -1.1786742748946986, -1.2426789749841751, -1.3009128009329922, -1.352337538159941, -1.396025505776924, -1.4311840393959145, -1.4571770943577993, -1.4735434081973868, -1.4800107417527788, -1.4765058111838727, -1.463159626027935, -1.440308058781535, -1.4084875866583466, -1.368426263307671, -1.3210300945107398, -1.2673651043393577, -1.2086354841897269, -1.1461583138749936, -1.0813354291760215, -1.0156230817935281, -0.9505000937324687, -0.8874352473741706, -0.8278546738590888, -0.7731100053560955, -0.7244480412271613, -0.6829826443584267, -0.6496695328144547, -0.625284564704457, -0.6104060323461469, -0.6054013874513576, -0.6104187144231321, -0.6253831564850569, -0.6499983819891181, -0.6837530587206673, -0.7259321852437682, -0.7756330131948701, -0.8317851857355477, -0.8931746177564022, -0.958470555301471, -1.0262551771906945, -1.0950550427577044, -1.1633736474124967, -1.2297243233917494, -1.2926627171426834, -1.3508180874171236, -1.4029226989938326, -1.4478386352158306, -1.4845814170160332, -1.5123398952035911, -1.5304919745324885, -1.5386158302042487, -1.5364963874466342, -1.524126949950742, -1.5017059804078425, -1.469629153281554, -1.4284769134161959, -1.3789978813444486, -1.322088544601265, -1.2587697615835696, -1.1901606784057093, -1.1174507180115523, -1.0418703431150134, -0.9646613193624739, -0.8870472118886642, -0.8102048370662042, -0.735237362071628, -0.6631496986924109, -0.5948267757855509, -0.5310151985640643, -0.4723087143786569, -0.4191378061244828, -0.37176362832787363, -0.33027639002892756, -0.29459817556172246, -0.2644900820791947, -0.23956344398474816, -0.21929481203222953, -0.2030442612929717, -0.19007651978980752, -0.17958434040642857, -0.17071348440480622, -0.162588646855454, -0.15433963342731905, -0.14512709478602312, -0.13416713935666036, -0.1207541770213858, -0.10428139460873878, -0.08425832754395358, -0.06032506913835481, -0.032262747731427795, -3.2001946256190746e-16], [0.0, 0.03711236019790447, 0.0779043325451262, 0.12194703823847808, 0.16868924063920637, 0.21747284724451968, 0.2675514886506549, 0.31811168308373244, 0.36829602654185695, 0.4172277943468657, 0.4640363013373008, 0.5078823460420887, 0.5479830595343458, 0.5836354924201134, 0.6142383032733171, 0.6393109580607736, 0.6585099115717379, 0.6716413170525924, 0.6786698972792428, 0.679723707007385, 0.6750946207074601, 0.6652344881136836, 0.6507470106705971, 0.6323755016680145, 0.6109867989538458, 0.5875516989266157, 0.5631223715099132, 0.5388072956888713, 0.5157443219063835, 0.49507251946052067, 0.47790350266834053, 0.46529294802002974, 0.458213015321845, 0.4575263688363262, 0.4639624600352507, 0.47809668257978155, 0.5003329437425007, 0.530890116281833, 0.5697927427109913, 0.6168662622096479, 0.6717369215890014, 0.7338364184038519, 0.8024112092892496, 0.8765363027125608, 0.9551332453804866, 1.0369919082392454, 1.1207955839105193, 1.205148824849329, 1.288607382546241, 1.3697095544475764, 1.4470082082818119, 1.5191027340989698, 1.5846701730618076, 1.642494788938348, 1.6914953829536974, 1.730749704347084, 1.7595153764121023, 1.7772468393515082, 1.7836079049825786, 1.77847962191551, 1.7619632607829419, 1.7343783447289196, 1.6962557678604901, 1.648326160868311, 1.591503775701685, 1.526866267299315, 1.4556308473518003, 1.3791273705515819, 1.2987689856991207, 1.2160210406417622, 1.1323689699610753, 1.0492859166413144, 0.9682008431244646, 0.89046787310913, 0.8173375735510594, 0.7499308373791292, 0.6892159626757238, 0.6359894450948573, 0.5908609090614632, 0.5542425020655201, 0.5263429676315046, 0.5071664989836742, 0.49651635983176917, 0.4940031439054123, 0.4990574336798452, 0.5109465138769608, 0.5287946993491877, 0.5516067521906223, 0.57829379141946, 0.6077010420558595, 0.6386367302241025, 0.6699014079743497, 0.7003169863562781, 0.7287547679511622, 0.7541618002062963, 0.775584917708773, 0.7921919037665021, 0.8032892777342273, 0.8083363024918615, 0.8069549041215738, 0.7989353006720374, 0.7842372463033246, 0.7629869083256492, 0.7354695048921448, 0.7021179376225701, 0.6634977535625967, 0.6202888621284991, 0.5732645127827491, 0.5232681061488658, 0.4711884634526605, 0.41793421529411773, 0.36440798993659046, 0.3114810831010624, 0.2599692756633921, 0.21061043309882413, 0.16404447185364712, 0.12079621430601716, 0.08126157723594826, 0.04569745071947344, 0.014215527336728845, -0.013219761993021542, -0.03678915673219619, -0.05681237986909618, -0.0737380224672944, -0.08812976942629576, -0.10064933218246364, -0.11203654066290261, -0.12308712184646672, -0.13462875387222525, -0.14749603119163268, -0.16250500658903813, -0.18042798920661093, -0.2019692736427517, -0.22774245382325817, -0.2582499371831541, -0.2938652206786165, -0.33481842160718756, -0.3811854748519489, -0.43288131600774954, -0.4896572691954447, -0.5511027517411793, -0.6166512979641658, -0.685590793838029, -0.7570777060463946, -0.8301549856715875, -0.9037732310453893, -0.9768146085790614, -1.048118956856699, -1.116511439803596, -1.180831070863976, -1.2399594029895493, -1.2928486695865196, -1.3385486696942916, -1.3762317164337243, -1.4052150105859207, -1.4249798600394232, -1.4351872393679834, -1.4356892702001345, -1.4265363002198201, -1.4079793642265994, -1.3804679221035503, -1.3446428830602088, -1.3013250403235133, -1.251499152715831, -1.1962940165168845, -1.136958970012392, -1.074837361734108, -1.0113375893937597, -0.9479023780128699, -0.8859770112117703, -0.8269772578962687, -0.7722577469415175, -0.7230815346321904, -0.6805915837335262, -0.64578482974137, -0.6194894501202844, -0.6023458776210568, -0.5947920108743107, -0.5970529765115602, -0.6091356894676581, -0.630828344480536, -0.6617048548863663, -0.7011341374525839, -0.7482940270507934, -0.802189495240821, -0.8616747449827983, -0.9254786621894924, -0.9922330258961916, -1.0605028143706623, -1.1288178960674582, -1.1957053631104508, -1.259721751705681, -1.319484398843273, -1.3737012076952355, -1.421198134665916, -1.4609437680846007, -1.4920704406245187, -1.5138914029001995, -1.5259136822237522, -1.5278463558074686, -1.5196040791904664, -1.5013058255988996, -1.473268907500336, -1.4359984649514477, -1.3901727136918003, -1.3366243466612873, -1.2763185732640931, -1.210328359070771, -1.1398074928528037, -1.0659621563453214, -0.9900217037892112, -0.9132093723887105, -0.8367136410459456, -0.761660933254358, -0.6890903214408496, -0.6199308353579336, -0.5549819077550726, -0.494897408277147, -0.4401736234389855, -0.39114143896414433, -0.3479628733144398, -0.3106320005770561, -0.2789801897948513, -0.2526854791037233, -0.23128579939546376, -0.21419566623934325, -0.2007258728586274, -0.19010564320093545, -0.18150664438685032, -0.17406821353839405, -0.16692312625655684, -0.15922322349680232, -0.15016422051227932, -0.13900904568671416, -0.1251090978206324, -0.10792286670708151, -0.08703143218853582, -0.06215043952422646, -0.03313824170823004, -3.275979950864032e-16], [0.0, 0.03773697950054407, 0.07891141489450709, 0.12303950906325649, 0.16952521014785693, 0.21767715873931456, 0.26672839181160324, 0.3158582808343736, 0.36421612209959575, 0.4109457527588388, 0.45521053754008134, 0.49621805933701224, 0.5332438521604937, 0.5656535372024145, 0.5929227614505669, 0.6146543924594328, 0.6305924911852842, 0.640632665536881, 0.6448284984622472, 0.6433938437093799, 0.6367008873778597, 0.6252739813862913, 0.6097793633037647, 0.5910109829054878, 0.5698727566419821, 0.5473576644081597, 0.5245241861994056, 0.5024706473275897, 0.48230809802001323, 0.4651323949618961, 0.45199617757273297, 0.4438814398422909, 0.44167338913379156, 0.4461362566643266, 0.4578916810005523, 0.4774002268818343, 0.5049465284150612, 0.5406284599438375, 0.5843506417616153, 0.6358224836575591, 0.694560859604164, 0.7598973944069595, 0.8309902306043836, 0.9068400341022604, 0.9863098926626238, 1.0681486650223972, 1.151017252482347, 1.233517191417156, 1.3142209061447416, 1.3917029184375773, 1.4645712837533824, 1.5314985156849434, 1.5912512694243857, 1.6427180820127552, 1.6849345111737923, 1.7171050745646899, 1.738621465876, 1.7490766115788912, 1.748274230137483, 1.736233661801051, 1.7131898490856274, 1.6795884630260138, 1.6360762854327697, 1.5834870699244237, 1.5228232116867415, 1.4552336551331206, 1.381988557492884, 1.3044513026814581, 1.224048521759637, 1.14223882237225, 1.0604809586630997, 0.9802021846026726, 0.9027675271809195, 0.8294506916915192, 0.7614072699832175, 0.6996508651139246, 0.6450326737430014, 0.5982249826235398, 0.5597089398091913, 0.5297668570307593, 0.5084791896905747, 0.49572622777124653, 0.49119441743624925, 0.4943871219931526, 0.5046395249121964, 0.5211372793275753, 0.5429384202854598, 0.5689979800767253, 0.5981946851325373, 0.6293590666450126, 0.6613022873940344, 0.6928449748915327, 0.7228453561439141, 0.750226011893302, 0.7739986075114625, 0.7932860127545283, 0.807341291922536, 0.8155631278341131, 0.817507335344282, 0.8128942205689125, 0.8016116480015765, 0.7837137866536267, 0.7594156154845886, 0.7290833749873336, 0.69322125318973, 0.652454688005661, 0.6075107514857383, 0.5591961530098085, 0.5083734560650655, 0.45593614555163536, 0.40278320852447325, 0.34979390029989665, 0.2978033597368946, 0.24757971248797936, 0.19980325976621482, 0.155048293765831, 0.11376801075536831, 0.07628291082946292, 0.04277298145181902, 0.013273862586410123, -0.012322913077441856, -0.034265617898266286, -0.05293408434378159, -0.06882773973191456, -0.08255024043130645, -0.0947911145024389, -0.10630490050737526, -0.11788833650396276, -0.13035620537772374, -0.14451647931590306, -0.16114542644685512, -0.1809633459209846, -0.20461158389045137, -0.23263145227721027, -0.26544562564791624, -0.30334253008874074, -0.3464641632170622, -0.39479769824170347, -0.4481711294411213, -0.5062531139594494, -0.5685570579912482, -0.6344493869188584, -0.7031618315099254, -0.7738074585844211, -0.8454000772392406, -0.9168765632382468, -0.9871215667853892, -1.0549940045736754, -1.1193546873978257, -1.1790944010231938, -1.233161741311823, -1.2805900052930197, -1.320522457972839, -1.352235329814144, -1.375157951170882, -1.3888894963072451, -1.3932118893792875, -1.3880985159721724, -1.3737184842508698, -1.3504362870417275, -1.3188068275895555, -1.2795658845935156, -1.233616203637744, -1.182009509549543, -1.1259248348849995, -1.066643651166216, -1.0055223694061757, -0.9439628428669959, -0.8833815562433417, -0.8251782202548246, -0.7707045080812936, -0.721233669719558, -0.6779317421537382, -0.6418310376248488, -0.6138065400987965, -0.5945557725123642, -0.5845826161489562, -0.5841854705218068, -0.5934500396733517, -0.6122469213213002, -0.6402340614530307, -0.676864021556642, -0.7213958914853472, -0.7729115707583366, -0.8303360375849859, -0.892461130575672, -0.9579722852614784, -1.0254775981955608, -1.0935385372276911, -1.1607015788365918, -1.225530033072427, -1.2866353141800706, -1.342706930379499, -1.3925404991721684, -1.4350631440930752, -1.469355693800542, -1.4946711831773274, -1.5104492467577604, -1.5163260950586277, -1.5121398718061294, -1.4979313019750475, -1.4739396542410153, -1.4405941541051908, -1.398501092826316, -1.348426979729605, -1.291278178960755, -1.2280775540474544, -1.1599387127317453, -1.0880384987861254, -1.0135884156362542, -0.9378056876969882, -0.8618846689227705, -0.7869692941484597, -0.7141272377569476, -0.644326396882554, -0.5784142539740703, -0.517100597698874, -0.46094399380076906, -0.4103423008423943, -0.36552742220837897, -0.3265643779231613, -0.29335467045408936, -0.2656438104653789, -0.2430327641656733, -0.22499298605329074, -0.21088461194286853, -0.19997730936187197, -0.1914732176593493, -0.18453136006636736, -0.17829287571201932, -0.17190640205523092, -0.16455293774523208, -0.15546953254736948, -0.14397118421182367, -0.1294703711500759, -0.11149371325181416, -0.08969532949489989, -0.06386654822261877, -0.03394172186256741, -3.3435443864747144e-16], [0.0, 0.03824997785313923, 0.07967237669488218, 0.12373468924870884, 0.16980291954690388, 0.21715976896550354, 0.26502524506325, 0.3125791454082412, 0.3589848185185595, 0.40341356927183303, 0.4450690575505747, 0.48321103697535783, 0.5171777954069513, 0.5464066901204335, 0.570452217404972, 0.5890011176641475, 0.6018840913597049, 0.609083786505037, 0.6107388127406481, 0.6071436379507972, 0.5987443283775099, 0.5861301996175258, 0.5700215510713024, 0.5512537576988548, 0.5307580877654486, 0.5095397012279858, 0.48865335833407436, 0.46917742996565576, 0.45218684866274456, 0.43872567087542474, 0.42977993597010783, 0.4262515054283584, 0.4289335465168343, 0.43848828889348285, 0.45542763098181144, 0.48009710672073314, 0.5126636440762923, 0.5531074564039143, 0.6012183085751049, 0.6565962941551038, 0.7186571504273979, 0.7866420273978817, 0.859631517801287, 0.9365636502679845, 1.0162554497837082, 1.0974275808178322, 1.1787315112132926, 1.2587785710500312, 1.336170231814266, 1.4095288985618364, 1.4775284921914873, 1.538924100861312, 1.5925799989772649, 1.6374953686160942, 1.672827110856817, 1.697909202027545, 1.7122681307033831, 1.7156340434639554, 1.7079473287040963, 1.6893604757314258, 1.6602351583587671, 1.621134605486171, 1.5728114330122387, 1.5161912190974427, 1.4523522057048943, 1.3825016010138056, 1.3079490375115377, 1.2300778073760608, 1.150314548545339, 1.070098090385208, 0.9908481862635384, 0.9139348611862359, 0.8406490859505008, 0.7721754554530836, 0.7095674987052194, 0.6537261829989209, 0.6053820961547386, 0.565081700800053, 0.533177955398337, 0.5098254907167314, 0.494980420187942, 0.4884047508979058, 0.4896752514501908, 0.49819652642314854, 0.5132179471461212, 0.5338539975097698, 0.5591075137001869, 0.5878952300339279, 0.6190749910710539, 0.6514739541284804, 0.6839170870431152, 0.7152552639626588, 0.7443922770653718, 0.7703101139955848, 0.7920918986031462, 0.8089419550526238, 0.8202025309214959, 0.8253668016142359, 0.8240878740863945, 0.8161836100876808, 0.8016371953254144, 0.7805934884567005, 0.7533512899488858, 0.7203517729533135, 0.6821634138729619, 0.6394638468954267, 0.5930191422624638, 0.5436610705908117, 0.49226296360924154, 0.4397148140620304, 0.38689827347257516, 0.3346622055992519, 0.28379943580773265, 0.23502530270918875, 0.18895856915928103, 0.14610518635126873, 0.10684532889412882, 0.07142403238137893, 0.03994567023058725, 0.012372405917395852, -0.011473347300506842, -0.03190253183291615, -0.049349291873890214, -0.06435733397124362, -0.07756316709222215, -0.08967666913513427, -0.10145949730870842, -0.11370191704372339, -0.12719866665269958, -0.14272450172035087, -0.16101007349424634, -0.1827187890704852, -0.20842527807380284, -0.23859605137469075, -0.27357288313188144, -0.31355937944222473, -0.3586111168142029, -0.40862964355463804, -0.4633605392246847, -0.5223956240348576, -0.5851793040020753, -0.6510189315507773, -0.7190989576785501, -0.7884985534383351, -0.8582122878034387, -0.9271733682797232, -0.9942788819688837, -1.0584164199273904, -1.1184914280274285, -1.1734546041511946, -1.2223286550776418, -1.2642337370707788, -1.2984109317440888, -1.3242431526289358, -1.341272936981239, -1.3492166503045178, -1.3479747160859368, -1.337637578268855, -1.3184872067017481, -1.290994063694307, -1.255809560228896, -1.2137541406028713, -1.165801241596952, -1.1130574740256998, -1.0567394682089584, -0.9981479081828302, -0.9386393502724988, -0.8795964782081754, -0.8223974878576468, -0.7683853188363666, -0.7188374571096899, -0.6749370220172777, -0.6377458231542117, -0.6081800278881606, -0.5869890200394151, -0.5747379558456257, -0.5717944365700337, -0.5783196200892144, -0.594263988865402, -0.6193678814163368, -0.653166781421744, -0.695001245696436, -0.7440312421614494, -0.7992545643337969, -0.8595288922759126, -0.9235969837442694, -0.9901144055450946, -1.0576791556306144, -1.124862482687996, -1.1902401829379616, -1.2524236442114345, -1.3100899153264536, -1.3620101041273913, -1.4070754496323636, -1.4443204715116174, -1.4729426721539933, -1.4923183510881173, -1.5020141864230887, -1.501794340921753, -1.4916229587859116, -1.471662030552903, -1.4422647149475432, -1.4039643153744055, -1.3574592123142466, -1.3035941486806975, -1.2433383508716565, -1.177761041740698, -1.1080049612483471, -1.0352585547107893, -0.9607275163067267, -0.8856063862015738, -0.8110508930950938, -0.7381517104141287, -0.6679102543980998, -0.6012170970073858, -0.5388334973483193, -0.4813764739199427, -0.42930774851126097, -0.3829267933240835, -0.3423681083647491, -0.30760274896239015, -0.2784440161172794, -0.25455711793862945, -0.23547251130202637, -0.220602541509853, -0.20926091644107123, -0.2006844824417059, -0.19405671374063294, -0.18853228683540696, -0.18326208705705926, -0.17741798696294525, -0.1702167454753868, -0.16094240251121483, -0.14896658554771244, -0.13376620106067957, -0.11493805359628011, -0.0922100166122502, -0.06544847006919519, -0.03466181775572384, -3.4019490672375753e-16], [0.0, 0.03864410426381679, 0.08017611821398651, 0.12402132384387476, 0.16951481403821125, 0.2159207053388409, 0.26245342967724794, 0.30830053795302875, 0.35264640773976647, 0.39469622235353896, 0.43369957967512285, 0.468973096717701, 0.49992139980639105, 0.5260559298030882, 0.5470110460932321, 0.5625569807019568, 0.5726092732395065, 0.5772344064075715, 0.5766514583004504, 0.5712296892875856, 0.5614820853162922, 0.5480549834073977, 0.5317140063123463, 0.513326629202137, 0.4938417894379461, 0.4742670286906363, 0.45564372293640165, 0.439021008458185, 0.42542904956446653, 0.41585231530783795, 0.4112035374521197, 0.41229901011787456, 0.41983586316916643, 0.4343718971389121, 0.4563085083728189, 0.48587716052093666, 0.5231297742764527, 0.5679333134025746, 0.6199687438926705, 0.6787344370557249, 0.7435539790138702, 0.8135882412078113, 0.8878514616914498, 0.965230987850449, 1.0445102401576591, 1.124394375942438, 1.2035380639102942, 1.2805747260114761, 1.3541465645853672, 1.4229346704867354, 1.4856885027116076, 1.5412540420487912, 1.5885999502292165, 1.6268411112545564, 1.6552589919839495, 1.6733183331943002, 1.680679768418123, 1.677208063821111, 1.662975775883842, 1.6382622321859721, 1.603547851519899, 1.5595039301871993, 1.506978128964614, 1.4469759972489238, 1.3806389648207191, 1.30921931522282, 1.234052725901055, 1.1565290172784013, 1.0780617944497024, 1.0000576901949894, 0.9238859259212575, 0.8508488977807164, 0.7821544688267095, 0.7188906053220746, 0.6620029372740016, 0.6122757513741478, 0.5703168405494378, 0.5365465403492728, 0.5111911807221539, 0.49428107486829254, 0.48565305741744824, 0.48495747485454055, 0.49166942457399904, 0.5051039377882417, 0.5244347082098341, 0.5487158852364109, 0.5769063793042104, 0.6078960698489507, 0.6405332642857954, 0.673652730578921, 0.706103616899964, 0.736776579740904, 0.7646294664000313, 0.7887109383350663, 0.808181477416593, 0.8223312861894762, 0.830594674099711, 0.8325606122205244, 0.8279792370284913, 0.8167641867727398, 0.7989907593636467, 0.7748899858444139, 0.7448388157733892, 0.70934670768854, 0.6690390068400196, 0.6246375713547967, 0.5769391749866299, 0.5267922679564981, 0.475072715798857, 0.4226591586699241, 0.3704086397173277, 0.31913314073953736, 0.2695776367766907, 0.22240023917684487, 0.17815494016685424, 0.1372774024796856, 0.10007415692918564, 0.06671548103745305, 0.037232135195706034, 0.011516031833517511, -0.010675189750738131, -0.02970981227333365, -0.04607014108246912, -0.06033737728772084, -0.07317366869744626, -0.08530181798950018, -0.09748318939686333, -0.11049440319616921, -0.12510344021542075, -0.1420457955785629, -0.1620013215308868, -0.1855723834044845, -0.21326392096441543, -0.24546596030526455, -0.2824390603103534, -0.3243031039640814, -0.37102976036146623, -0.4224388502002203, -0.4781987482013128, -0.5378308527771265, -0.6007180489445474, -0.6661169875907115, -0.7331739053375539, -0.800943616917727, -0.8684112285104592, -0.9345160480153142, -0.9981771086186553, -1.0583196767678247, -1.1139020859925701, -1.1639422246963471, -1.207543009470216, -1.243916195631098, -1.2724039131091653, -1.292497367655761, -1.3038522133769872, -1.30630018122754, -1.2998566374164608, -1.2847238435037047, -1.2612897939105452, -1.2301226140774313, -1.1919606109360557, -1.1476981740454546, -1.0983678280399023, -1.0451188324172587, -0.9891928107938719, -0.9318969664243137, -0.8745755021665758, -0.8185799096262073, -0.7652388227579142, -0.7158281449549817, -0.6715421552415501, -0.6334662786472961, -0.6025521686571605, -0.5795956966673026, -0.5652183759088852, -0.5598526669461793, -0.5637315205558906, -0.5768824137611268, -0.5991260284525111, -0.6300796119632512, -0.6691649478497523, -0.7156207556665924, -0.7685192333771009, -0.8267863577654446, -0.889225469202747, -0.9545435895307748, -1.021379857544618, -1.0883354171375204, -1.1540040598078287, -1.2170029067192343, -1.2760024162354144, -1.3297550207825404, -1.3771217315689483, -1.4170961002424705, -1.448824991736572, -1.4716257007327596, -1.4849990334190768, -1.488638074353454, -1.4824324628322867, -1.4664681116500735, -1.4410224108547063, -1.4065550673688638, -1.3636948355149807, -1.31322249100939, -1.2560504895084061, -1.1931998281499911, -1.1257746928732424, -1.0549355240728984, -0.9818711671791125, -0.9077707922566318, -0.833796267315105, -0.7610556537554828, -0.6905784597053274, -0.6232932387828755, -0.5600080593229662, -0.5013942938969471, -0.44797409297381235, -0.4001118119751123, -0.3580095601547148, -0.32170693521921206, -0.29108490201428366, -0.2658736695769834, -0.24566432098897445, -0.22992385724708259, -0.2180132321103367, -0.20920788167311435, -0.20272019205824288, -0.1977233026029295, -0.19337561134362924, -0.18884533522366814, -0.18333447957297455, -0.17610158995124284, -0.16648269390120088, -0.15390988962498098, -0.13792710179591117, -0.1182026000282215, -0.09453796102343869, -0.06687324891522245, -0.03528828746502289, -3.450371853507737e-16], [0.0, 0.03891351600926102, 0.08041447324695952, 0.12389265666758355, 0.16865936357384087, 0.2139674276734061, 0.25903297216278937, 0.30305831135917594, 0.3452553892782781, 0.3848691280972968, 0.42120006005431226, 0.45362563302157555, 0.4816196123481209, 0.5047690487997869, 0.5227883433597056, 0.5355300127710689, 0.5429918431795289, 0.5453202109750649, 0.5428094476418561, 0.5358972266454249, 0.525156052572743, 0.5112810333180495, 0.49507421253560746, 0.47742582942044615, 0.459292953849646, 0.441676014957704, 0.42559379853698237, 0.4120575317696628, 0.40204470158404454, 0.3964732646388782, 0.3961769022275809, 0.40188195232115104, 0.41418661400380086, 0.43354296756477867, 0.46024228773545434, 0.49440404958985434, 0.5359689383534271, 0.5846960779428885, 0.6401645908505085, 0.7017794964988202, 0.7687818490228725, 0.8402629112056493, 0.915182061574707, 0.9923880389347906, 1.0706430451650415, 1.1486491550286604, 1.2250764228294893, 1.2985920314845922, 1.3678898010871552, 1.4317193620462343, 1.4889143027402865, 1.5384186232281254, 1.579310864429835, 1.6108253354272575, 1.6323699288665092, 1.643540094253771, 1.6441286292928683, 1.6341310481309665, 1.61374639006244, 1.583373440348032, 1.5436024437089275, 1.49520249810454, 1.4391049189944416, 1.376382959923019, 1.3082283616241885, 1.2359252768239215, 1.1608221797002403, 1.084302416046902, 1.007754081441698, 0.932539929394502, 0.8599680092017742, 0.7912637141354262, 0.727543885129807, 0.669793564186515, 0.618845926556319, 0.5753658429920006, 0.5398374349127705, 0.512555888358189, 0.4936236895202522, 0.4829513379568901, 0.48026248592313164, 0.48510334624202084, 0.4968561093653606, 0.5147560152247678, 0.5379116394566159, 0.565327878683714, 0.5959310575573138, 0.6285955326885267, 0.6621711365532497, 0.6955107886780089, 0.7274976022417025, 0.7570708315838274, 0.7832500395097405, 0.8051569118467565, 0.8220342091779688, 0.8332614204670986, 0.83836676848979, 0.8370353104524074, 0.8291129765557371, 0.8146064920541053, 0.7936792319962473, 0.7666431597240466, 0.7339470978089688, 0.6961616709962233, 0.6539613426484429, 0.6081040371077506, 0.5594088985800775, 0.5087327811630745, 0.4569460934209713, 0.4049086337715287, 0.35344604960751286, 0.30332753365025616, 0.2552453360515843, 0.20979662113843622, 0.16746813471396657, 0.12862407310617088, 0.09349746060012701, 0.06218524965785555, 0.03464726076746008, 0.010708978349457245, -0.00993188156753646, -0.02769521465171131, -0.043105059014153006, -0.05677317643822266, -0.06938012438916201, -0.08165432506636945, -0.09434969075860729, -0.10822240344057318, -0.12400746991611837, -0.14239568126257773, -0.16401159665650686, -0.18939314706387234, -0.21897341435886125, -0.2530650871828424, -0.2918480276181642, -0.33536030420858187, -0.3834929589735023, -0.4359886810392706, -0.4924444597321946, -0.552318187953016, -0.6149390849498487, -0.6795217087914189, -0.7451832354121478, -0.8109635954224942, -0.8758479841300006, -0.938791196331963, -0.9987431870610003, -1.0546752238963915, -1.105605976637109, -1.1506268866153175, -1.188926170855152, -1.2198108453847445, -1.2427261966197705, -1.2572721887972982, -1.2632163675302979, -1.2605029029298611, -1.2492575083737334, -1.2297880706216666, -1.2025809311475884, -1.1682928647145503, -1.127738906745231, -1.0818762833326725, -1.0317847942614735, -0.9786440877749218, -0.9237083438310815, -0.8682789482945644, -0.8136757922639052, -0.7612078672318571, -0.7121438470846336, -0.6676833515309317, -0.628929572287431, -0.5968639135228435, -0.5723232523742227, -0.5559803648830073, -0.5483279889053608, -0.5496669102103335, -0.5600983631546297, -0.5795209353124817, -0.6076320587195828, -0.6439340615544125, -0.6877446457751556, -0.7382115510902093, -0.7943310662232178, -0.8549699571576878, -0.9188903011311357, -0.9847766465598267, -1.0512648644759433, -1.11697201777073, -1.180526551504488, -1.2405981013151928, -1.2959262276664156, -1.3453474110433519, -1.3878196865453396, -1.4224443545563294, -1.4484842758599614, -1.46537834293273, -1.4727518121435723, -1.4704222819232244, -1.4584012071775245, -1.4368909477251113, -1.4062774557089872, -1.3671188111432953, -1.320129913468677, -1.2661637277991724, -1.206189565247032, -1.1412689453586846, -1.0725296436362135, -1.0011385670458104, -0.9282741243933682, -0.8550987659386643, -0.7827323574931977, -0.7122270287836102, -0.6445440947473141, -0.580533592730245, -0.5209169097077786, -0.4662728934015916, -0.4170277515488879, -0.37344894685535673, -0.3356431937605098, -0.30355855960580075, -0.2769905697112665, -0.25559211580806385, -0.23888687273360226, -0.22628584162136497, -0.21710656115640867, -0.2105944637125024, -0.20594580192927225, -0.2023315347781387, -0.19892154128329012, -0.19490852529439742, -0.1895309861324879, -0.18209465722408982, -0.17199185727860125, -0.1587182550471889, -0.14188661777474385, -0.12123719335064137, -0.09664446484037323, -0.06812011128042768, -0.035812107922693376, -3.4881140637551027e-16], [0.0, 0.03905381506809225, 0.08038224079099426, 0.12334641525807938, 0.16724095983711526, 0.21131459815714787, 0.2547921518350437, 0.29689732498817384, 0.3368756678463906, 0.3740171036743186, 0.40767741290984916, 0.43729809368852907, 0.46242405813592213, 0.48271867797363144, 0.49797575974991815, 0.5081281077044758, 0.513252418963526, 0.5135703492619194, 0.5094456853549072, 0.5013776602493192, 0.4899905468335248, 0.47601976190774076, 0.46029480357252645, 0.44371942811754944, 0.42724954584915315, 0.4118693768313877, 0.39856645570891147, 0.3883061083797786, 0.3820060414017523, 0.3805116871423406, 0.3845729337129665, 0.39482283895536263, 0.4117588828616806, 0.4357272538750101, 0.4669105929520383, 0.5053195368097322, 0.5507883104330223, 0.6029745209255283, 0.6613632025452945, 0.725275058797904, 0.7938787443240953, 0.8662069295669524, 0.9411757973054911, 1.0176075344280773, 1.0942553069242702, 1.1698301428806428, 1.2430290988608435, 1.3125640506816594, 1.3771904311460363, 1.4357352352515869, 1.4871236278466806, 1.5304035193381982, 1.5647675211496597, 1.5895717530892692, 1.6043510481639798, 1.6088301848989057, 1.6029308708469348, 1.586774301431835, 1.5606792231207658, 1.5251555366206677, 1.4808935817426385, 1.428749348201259, 1.369725953414527, 1.304951816989238, 1.2356560398608167, 1.1631415621031354, 1.0887567256299893, 1.0138659051117327, 0.9398198915346357, 0.8679267174349927, 0.7994236008476018, 0.7354506567278628, 0.677026980746064, 0.6250296520002984, 0.5801761297931177, 0.5430104369279888, 0.5138934300397627, 0.4929973585390985, 0.4803048102520089, 0.47561203630936655, 0.47853654286983144, 0.48852873540798647, 0.50488730505111, 0.5267779581444039, 0.5532550120070431, 0.5832853135993606, 0.6157738851449044, 0.6495906628927489, 0.6835976730497965, 0.7166759829545685, 0.7477517758973858, 0.7758209243071298, 0.7999714776188268, 0.8194035369280211, 0.833446057098187, 0.8415701965728632, 0.8433989237424668, 0.8387126840951394, 0.8274510321461864, 0.8097102337931674, 0.7857369457430637, 0.7559181764861231, 0.7207678255140808, 0.6809101818098046, 0.6370608369840494, 0.5900055309695986, 0.5405774973692024, 0.48963391019375635, 0.43803205298994863, 0.38660583479738164, 0.3361432649467047, 0.28736547076330776, 0.24090779951512956, 0.1973034895479185, 0.15697032693827237, 0.12020062492084584, 0.08715477582935924, 0.05785853155961045, 0.03220407099965626, 0.009954813954997338, -0.009246156664857097, -0.025864296757972874, -0.04045874750246377, -0.053664826698199546, -0.06617433484764608, -0.07871420335587544, -0.09202405622462197, -0.10683328597119128, -0.12383825846485084, -0.143680259573372, -0.16692477897987804, -0.194042693690576, -0.22539386641867454, -0.2612136133760181, -0.30160242354520084, -0.3465192290538402, -0.39577843589524647, -0.4490508282044559, -0.5058683600193653, -0.5656327484327612, -0.6276276837945847, -0.6910343786368556, -0.754950089645967, -0.8184091685164654, -0.8804061298875543, -0.9399201695208036, -0.9959405248467943, -1.0474920440633604, -1.093660319808923, -1.1336157493680001, -1.1666359052989708, -1.1921256378141625, -1.2096343823092846, -1.2188702108874776, -1.2197102439711562, -1.212207125264096, -1.196591358287862, -1.1732694031435011, -1.1428175355736356, -1.1059715742739207, -1.0636126841620466, -1.0167495604395949, -0.9664973883685972, -0.914054054491424, -0.8606741545348625, -0.807641399716901, -0.7562400651957243, -0.7077261508967904, -0.6632989352371598, -0.6240735960467173, -0.5910555503788175, -0.5651171264261289, -0.5469771273204381, -0.5371837794746498, -0.5361014789364917, -0.5439016598786058, -0.5605580120126195, -0.5858461707466093, -0.6193478978073553, -0.6604596634003334, -0.708405436376042, -0.7622533888561829, -0.8209361287816394, -0.8832739901381064, -0.9480008382303281, -1.0137917880701026, -1.079292189154114, -1.1431472007178087, -1.2040312686599033, -1.2606768190401025, -1.3119015032531183, -1.3566333661659962, -1.3939333597716081, -1.4230146899894172, -1.4432585615288087, -1.4542259733158127, -1.4556653127169765, -1.4475155983229082, -1.4299053258884333, -1.403146977598834, -1.367727358560603, -1.3242940237685454, -1.2736381513589756, -1.216674301472794, -1.1544175725008665, -1.0879587261223218, -1.0184378979485003, -0.9470175406792442, -0.8748552607724869, -0.8030772074274254, -0.7327526542939317, -0.6648703802545185, -0.6003174067749806, -0.5398605869450326, -0.4841314670218468, -0.43361475693135354, -0.3886406539031681, -0.3493811655356901, -0.31585047756289986, -0.28790930995120506, -0.2652731052301602, -0.2475237976390073, -0.23412482312029087, -0.2244389506068459, -0.21774844639563917, -0.21327702737026819, -0.2102130167936435, -0.20773308936107793, -0.20502598082153511, -0.20131554198785329, -0.19588253721317442, -0.18808462286352254, -0.1773739910381213, -0.16331222649471205, -0.14558199881779535, -0.12399529542981233, -0.09849799195903601, -0.06917065243044221, -0.03622555029930318, -3.5146057292891057e-16], [0.0, 0.039062067841347706, 0.08007718308179203, 0.12238474592874372, 0.1652697486108499, 0.2079837743581933, 0.2497670221791837, 0.2898707677503502, 0.3275796582248054, 0.3622332417018111, 0.3932461504238117, 0.420126390031041, 0.44249123458321105, 0.460080287372539, 0.4727653392952648, 0.4805567379233736, 0.4836060693833833, 0.48220504947012366, 0.4767806177278257, 0.46788632606737285, 0.4561902093886708, 0.44245941721656656, 0.42754197021835233, 0.41234608149461416, 0.3978175477840865, 0.3849157685242845, 0.3745889896980717, 0.3677493935494929, 0.36524866391623595, 0.3678546498323652, 0.3762297273274683, 0.3909114215011548, 0.41229579887690726, 0.44062407498483075, 0.4759728056628697, 0.5182479445617053, 0.56718295589228, 0.6223410728587115, 0.6831216908981492, 0.7487707833007172, 0.8183951275161173, 0.8909800359265904, 0.965410197424856, 1.0404931579559995, 1.1149849012156068, 1.1876169366213272, 1.257124261855364, 1.322273542726259, 1.3818908444604683, 1.4348882560579044, 1.4802887728838294, 1.5172488416813004, 1.5450780257519143, 1.5632553148872415, 1.5714416831311544, 1.569488585718273, 1.5574421824283926, 1.5355431757945046, 1.5042222566443166, 1.464091253812147, 1.4159301869904692, 1.360670519112384, 1.299374994996322, 1.2332145340436267, 1.163442714586533, 1.0913684443418845, 1.01832745395554, 0.9456532777951822, 0.8746483973133644, 0.8065562171978408, 0.7425345232911599, 0.6836310344294421, 0.6307616088360722, 0.5846916007834554, 0.5460207865059771, 0.5151721916985269, 0.4923850584968614, 0.4777120899266652, 0.47102100687617443, 0.47200034921221207, 0.48016935124932536, 0.49489162487044075, 0.5153922935442219, 0.5407781394755024, 0.5700602561203264, 0.6021786409813537, 0.6360281203416078, 0.6704849694144299, 0.7044335789306454, 0.7367925227064444, 0.7665394000981237, 0.7927338619222061, 0.8145382774936116, 0.8312355626480533, 0.8422437623826855, 0.8471270652032874, 0.8456030173030668, 0.8375458010301198, 0.8229855413138989, 0.8021037033358109, 0.7752247422609191, 0.7428042588696065, 0.7054140011307138, 0.6637241290067603, 0.6184832261710754, 0.5704965962148464, 0.5206034210134916, 0.46965338423856623, 0.41848337294746496, 0.3678948645481975, 0.31863258540138806, 0.27136499145288095, 0.22666707152598017, 0.18500591152807008, 0.14672938444270045, 0.11205824846066359, 0.0810818460552199, 0.0537575025051879, 0.02991362571068888, 0.009256412582898938, -0.008620026729668603, -0.024220404606192836, -0.03813221144095629, -0.051007323223096306, -0.0635417551098384, -0.07645410375430649, -0.09046325609332043, -0.10626596243527162, -0.12451487649204124, -0.14579765433683314, -0.17061767839620517, -0.1993769321372304, -0.23236149709499657, -0.26973007764950785, -0.31150588216146585, -0.35757210363822356, -0.40767115116893665, -0.461407687252463, -0.5182554282623667, -0.5775675681180061, -0.6385905912132052, -0.700481152173724, -0.7623256193160868, -0.8231618078174922, -0.8820023693909786, -0.9378592592155759, -0.9897686691954639, -1.036815800155783, -1.0781588447888812, -1.1130515681156838, -1.1408639026028247, -1.1611000201719586, -1.1734134020798868, -1.1776184986213738, -1.1736986520879347, -1.1618100464174588, -1.1422815432873092, -1.1156103646717086, -1.0824536836338075, -1.0436162858425955, -1.0000345615035502, -0.9527571786602826, -0.902922871894353, -0.8517358532519093, -0.8004394129382383, -0.750288324418511, -0.7025207008517698, -0.6583299664352257, -0.6188376067998304, -0.5850673470245179, -0.5579213744700494, -0.538159177207899, -0.5263795084396424, -0.52300591441649, -0.5282761797344658, -0.542235951521015, -0.564736705182694, -0.5954381114508066, -0.6338147599444233, -0.6791670909104863, -0.7306362867189885, -0.7872227805236999, -0.8478079535379103, -0.9111785167115883, -0.9760530090714816, -1.0411097951412023, -1.1050159089021379, -1.1664560725308128, -1.2241612151114694, -1.2769358297353282, -1.323683536522815, -1.3634302634162156, -1.395344514989484, -1.4187542705678349, -1.4331601348919587, -1.4382444553847868, -1.4338762175522641, -1.420111631782752, -1.3971904283105112, -1.365527979845842, -1.325703470839099, -1.2784444261138643, -1.2246079973963548, -1.1651594820042332, -1.1011486118104543, -1.0336842010349026, -0.9639077772405718, -0.8929668402864216, -0.8219883984639687, -0.7520534195604401, -0.6841728074838345, -0.6192654730760327, -0.5581390119177758, -0.5014734337222682, -0.4498083090539418, -0.4035336115879819, -0.3628844401469842, -0.3279397066714913, -0.2986247765556176, -0.2747179488976423, -0.25586056864138007, -0.24157047269312706, -0.23125839011966823, -0.22424684449175042, -0.21979104610894296, -0.217101214703865, -0.21536574042163661, -0.21377457318858367, -0.21154222842702725, -0.20792981045514555, -0.20226548345754475, -0.19396286286845338, -0.1825368562602337, -0.16761655092722863, -0.1489548235555517, -0.1264344336775795, -0.1000704548283716, -0.07000899310595028, -0.036522239756476296, -3.529409329030155e-16], [0.0, 0.03893680812818524, 0.07949999039598225, 0.12101410022679125, 0.16276140015128954, 0.20400302958757632, 0.24400085237021013, 0.28203939818336743, 0.3174473084986028, 0.34961770919342655, 0.37802695845372997, 0.40225125918727617, 0.4219806789852135, 0.43703018631908563, 0.44734738750786524, 0.45301673313040364, 0.4542600528796246, 0.45143337208375606, 0.4450200588833673, 0.4356204459351393, 0.42393816211659313, 0.4107634957109579, 0.39695418877484046, 0.38341413084114434, 0.3710704770346407, 0.3608497596115702, 0.3536535917335891, 0.3503345771572362, 0.35167303904116215, 0.35835516520527194, 0.37095313626325926, 0.3899077578131891, 0.41551405938883296, 0.4479102525585739, 0.4870703601177546, 0.5328007397188278, 0.584740630693257, 0.6423667545651287, 0.7050019002602491, 0.7718273267337259, 0.8418987211066425, 0.9141653617662603, 0.9874920554489387, 1.0606833470971797, 1.132509443020433, 1.201733243060322, 1.267137847203055, 1.327553887176209, 1.3818860344184047, 1.4291380524360302, 1.4684357935904173, 1.4990475870418956, 1.520401524802843, 1.5320992251750274, 1.5339257355232427, 1.5258553273675446, 1.5080530339531852, 1.48087188142105, 1.4448458669973825, 1.4006788387610671, 1.3492295290675989, 1.2914930852365185, 1.2285795244148094, 1.1616896125844256, 1.092088728710499, 1.0210793225446764, 0.9499726074534196, 0.8800601470407358, 0.8125859958643629, 0.7487200401779426, 0.68953315473261, 0.6359747469831517, 0.5888532016713266, 0.5488196681417102, 0.5163555516208741, 0.4917639800529153, 0.4751654221325945, 0.4664975322639275, 0.46551919674252046, 0.47181865499384446, 0.48482547264886006, 0.5038260519669686, 0.5279822818420106, 0.5563528563673068, 0.587916729457412, 0.6215981248011572, 0.6562924865965274, 0.690892737879937, 0.7243152102210462, 0.7555246211338821, 0.7835575033948569, 0.807543532820086, 0.8267242568436114, 0.8404687940289485, 0.8482861527201268, 0.8498339034244704, 0.8449230320460042, 0.8335188974361711, 0.8157383144881798, 0.791842880734287, 0.7622287577036512, 0.7274132058453389, 0.6880182514480788, 0.644751933729132, 0.5983876384037554, 0.5497420691620833, 0.4996524394780524, 0.4489534833167282, 0.3984548842268281, 0.34891970802091843, 0.3010443951544301, 0.2554408257847028, 0.21262091444211523, 0.17298412371948793, 0.13680820911191258, 0.10424342208863839, 0.07531030781676401, 0.04990113998708022, 0.027784940301010187, 0.00861593677074422, -0.008054774569674317, -0.022764683376756942, -0.036122828163439084, -0.04879072800063004, -0.06146179509498128, -0.07483978069427416, -0.0896168327128613, -0.10645175457529393, -0.12594905075468685, -0.14863932542256197, -0.17496156699691834, -0.20524780401042927, -0.23971055780293363, -0.2784334465710336, -0.32136521506151317, -0.36831737668919917, -0.4189655622933117, -0.4728545744495846, -0.5294070506305485, -0.5879355449676025, -0.6476577492818224, -0.7077144916742896, -0.7671900773952204, -0.8251344738219788, -0.8805867907829869, -0.9325994704766001, -0.9802625788232, -1.022727582863987, -1.0592300070129983, -1.0891103844263663, -1.1118329579408601, -1.127001637049839, -1.134372781979874, -1.1338644615406843, -1.1255619162023498, -1.1097190497324025, -1.0867558694460366, -1.057251894304466, -1.0219356492924327, -0.9816704612630027, -0.9374368633583086, -0.8903119999154975, -0.8414464993354208, -0.7920393468393399, -0.743311340748282, -0.6964777535841392, -0.652720841948107, -0.6131628561862623, -0.5788401920917599, -0.5506793024957943, -0.5294749471270012, -0.5158713055044554, -0.5103464111553239, -0.513200287713555, -0.5245470803388714, -0.5443113815054558, -0.5722288508376824, -0.6078511267304464, -0.6505549254635536, -0.6995551238861758, -0.7539215269346372, -0.8125989335631865, -0.8744300362483892, -0.9381806219813585, -1.0025664882239973, -1.0662814469971393, -1.1280257650654817, -1.1865343786926321, -1.2406042278795102, -1.2891200772023192, -1.3310782277763504, -1.3656075765626299, -1.3919875439292684, -1.4096624664849409, -1.418252137846957, -1.4175582730873442, -1.407566770834662, -1.3884457479904775, -1.3605394232773107, -1.3243580248961206, -1.2805639920206735, -1.2299548273952698, -1.1734430368073672, -1.1120336587795367, -1.0467999428406607, -0.9788577758814407, -0.9093394824059178, -0.8393676353580614, -0.7700295094125913, -0.7023527883408869, -0.6372831028472413, -0.575663926037297, -0.5182192916933511, -0.46553972736767646, -0.41807171181523983, -0.37611087654912945, -0.3397990765682171, -0.30912535794873, -0.2839307524410079, -0.2639167339007608, -0.24865708068004985, -0.2376128042568882, -0.23014972946755002, -0.22555824756893308, -0.22307471157335357, -0.22190390512677274, -0.2212419925625551, -0.22029934921010702, -0.2183226777458922, -0.21461583813552204, -0.20855885494502238, -0.19962461554987507, -0.187392834757277, -0.17156093398945363, -0.1519515645980401, -0.12851659301647803, -0.10133745806757871, -0.07062190547477662, -0.03669719907463587, -3.5322219796025685e-16], [0.0, 0.038678023513502545, 0.07865421339403486, 0.11924507462750672, 0.15973682086161817, 0.19940650572490226, 0.23754349615365727, 0.27347071104392623, 0.3065650536002017, 0.3362764854926618, 0.3621452248734253, 0.383816597594478, 0.4010531304334934, 0.41374354527908014, 0.4219083922939698, 0.42570214607666923, 0.4254116796155662, 0.4214511240879347, 0.41435321594743285, 0.4047573239083023, 0.39339443506536215, 0.3810694592886871, 0.36864128216805986, 0.357001057338363, 0.34704927743794767, 0.3396721979834189, 0.33571820916437534, 0.33597475640449664, 0.3411464013055998, 0.3518345904694536, 0.36851966123078694, 0.39154556144540303, 0.42110769640759727, 0.4572442412752805, 0.49983117388131787, 0.5485811925506825, 0.6030465887427311, 0.662626047331614, 0.726575250520985, 0.794021067157762, 0.8639790199011331, 0.9353736405377124, 1.0070612507605425, 1.0778546437741157, 1.146549092707221, 1.211949076260354, 1.272895091196183, 1.328289915750307, 1.3771236979697274, 1.4184972681724675, 1.451643114582154, 1.4759435147832016, 1.4909453816836618, 1.4963714595745976, 1.4921275917791041, 1.4783058742100015, 1.4551836066499213, 1.4232180533616372, 1.3830371243023623, 1.3354261853270686, 1.2813112979575705, 1.2217392743202962, 1.1578550086452215, 1.0908766114257726, 1.022068924390079, 0.9527160325630125, 0.8840934129821681, 0.8174403675088103, 0.7539333794640611, 0.6946610107195815, 0.6406009179561922, 0.5925995150108816, 0.551354743839256, 0.5174023412110554, 0.4911059036835061, 0.4726509617363231, 0.4620431774495568, 0.45911068112373227, 0.4635104632007218, 0.4747386411614683, 0.4921443291092192, 0.5149467527308461, 0.542255176325916, 0.5730911434399512, 0.6064124799007196, 0.6411384689919198, 0.6761755840252003, 0.7104431542455024, 0.7428983460079246, 0.7725598622994585, 0.7985297993755597, 0.8200131486103944, 0.8363344933564304, 0.8469515231061665, 0.8514650687146548, 0.849625450826207, 0.8413350267356194, 0.8266469163749356, 0.8057599835690984, 0.7790102417712894, 0.7468589418595378, 0.7098776810604958, 0.6687309446508448, 0.6241565539845598, 0.5769445440886422, 0.5279150303523854, 0.4778956458347349, 0.4276991379188271, 0.3781017053117045, 0.32982263395396844, 0.28350575387066246, 0.23970318931521828, 0.19886181301571643, 0.1613127435059468, 0.12726414424787502, 0.09679749657246628, 0.0698674275865164, 0.046305081421680924, 0.025824929891565724, 0.008034829113341255, -0.007550955790260642, -0.021496113025380906, -0.034424456682817905, -0.0470003898782241, -0.059908183677286606, -0.0738306283635979, -0.0894276306834984, -0.1073153330577153, -0.12804631831443342, -0.15209143657543414, -0.17982375018431787, -0.2115050390202725, -0.24727524353244684, -0.287145147988698, -0.3309925236374878, -0.3785618628146824, -0.429467742719899, -0.4832017639665382, -0.5391429164389243, -0.5965711358095379, -0.6546837305385311, -0.7126142834182876, -0.7694535656680661, -0.8242719469191643, -0.8761427425684476, -0.9241659120091452, -0.9674915079188325, -1.0053422784772148, -1.0370348411085186, -1.0619988777270235, -1.0797938467756063, -1.0901227655030412, -1.0928426855208342, -1.087971564021376, -1.0756913201865665, -1.0563469591319266, -1.0304417419318752, -0.9986284774846748, -0.9616971077972456, -0.9205588503266194, -0.8762272470201518, -0.8297965475095688, -0.7824179215911279, -0.735274051968747, -0.6895527008409106, -0.6464198721909863, -0.6069932048612114, -0.5723162292897307, -0.543334103182859, -0.5208714087763671, -0.5056125474741792, -0.4980852076564349, -0.49864730976126737, -0.5074777510947381, -0.5245711831866495, -0.5497369590598629, -0.5826022888356, -0.622619542062877, -0.6690775364712194, -0.721116557905247, -0.7777467673201811, -0.8378695700639547, -0.9003014522089715, -0.963799730139656, -1.027089614375293, -1.0888919578084566, -1.1479510429123487, -1.203061762388251, -1.2530955631792098, -1.2970245543800238, -1.3339432245674008, -1.3630872723475391, -1.3838491240360653, -1.3957897926233944, -1.398646820567433, -1.3923381433270623, -1.3769618085927973, -1.352791585486602, -1.3202685961646845, -1.2799891968707775, -1.2326894242495319, -1.1792264034842723, -1.1205571856155152, -1.0577155405197498, -0.9917872780659782, -0.9238847018293815, -0.855120816687995, -0.7865839132889196, -0.7193131387536038, -0.654275634482057, -0.592345779265693, -0.5342870202281649, -0.48073670680341163, -0.4321942657353492, -0.3890129698906479, -0.3513954626551265, -0.31939310511502195, -0.2929091174693553, -0.27170539156557677, -0.2554127604492342, -0.24354442562714726, -0.2355121654707706, -0.23064488073808304, -0.22820897722537017, -0.22743004244148532, -0.2275152439696188, -0.22767586253876457, -0.22714937309642766, -0.22522050230890847, -0.2212407204967225, -0.2146456692598803, -0.20497008183854584, -0.1918598201538681, -0.17508072876883587, -0.1545240897537619, -0.13020855150387642, -0.10227849667465584, -0.07099890723616285, -0.036746875846970325, -3.5228760736007046e-16], [0.0, 0.03828712550982384, 0.07754616413760493, 0.11709220580844178, 0.15622181019314754, 0.1942339043322352, 0.23045069605110405, 0.26423804067438517, 0.29502471178776535, 0.3223200541578798, 0.34572953772397763, 0.3649677847989057, 0.37986870692773894, 0.3903924616359319, 0.39662902070085576, 0.39879822855286534, 0.39724631976375385, 0.3924389560328083, 0.3849509333239018, 0.37545279655816827, 0.364694680326833, 0.35348776739772003, 0.3426838204776433, 0.33315329512973035, 0.325762581576962, 0.3213509493108981, 0.32070778026708907, 0.3245506734826445, 0.33350498663974004, 0.3480853481106597, 0.3686796278015693, 0.39553579732889443, 0.4287520412518073, 0.46827040290300376, 0.513874162720725, 0.5651890559907468, 0.6216883427984623, 0.6827016480913848, 0.7474273964093178, 0.814948576367738, 0.8842514866035255, 0.9542470396888365, 1.0237941353688955, 1.091724561018394, 1.1568688367893616, 1.2180823965720315, 1.2742714842956062, 1.3244181485816398, 1.3676037372820224, 1.403030326569131, 1.4300395662200773, 1.4481284824315217, 1.4569618504830737, 1.4563808301238628, 1.4464076447390786, 1.4272461790225606, 1.399278466762381, 1.3630571380825458, 1.3192939916962365, 1.2688449500708776, 1.2126917416325362, 1.1519207321452891, 1.0876993952892298, 1.0212509685750175, 0.9538278837076327, 0.8866845893030996, 0.8210503977726392, 0.7581029868864045, 0.6989431700537898, 0.6445715181205955, 0.595867370257699, 0.5535707134159683, 0.5182673402768342, 0.4903776163456296, 0.47014909976013164, 0.45765316465403433, 0.4527856827940071, 0.4552717210501181, 0.46467411643502815, 0.48040569829380353, 0.5017448409859235, 0.5278539521676266, 0.5578004334491812, 0.5905795934144663, 0.62513894910819, 0.6604033221582697, 0.6953001204001368, 0.7287841955371487, 0.7598616819678458, 0.7876122510288002, 0.8112092577764641, 0.829937312958503, 0.84320687959116, 0.8505655698744338, 0.8517059021199684, 0.8464693668306029, 0.8348467438169435, 0.8169747059500662, 0.7931288374964744, 0.7637132836673641, 0.7292473308405819, 0.6903492918329629, 0.6477181357669693, 0.6021133558899913, 0.5543336098551583, 0.5051946944661164, 0.45550743007513006, 0.40605602841353977, 0.35757750170141445, 0.3107426408680867, 0.26613904740838623, 0.22425664792409009, 0.18547605418321772, 0.15006005626610638, 0.11814845397624686, 0.08975634427216127, 0.06477589224497804, 0.042981522413831894, 0.02403837813835782, 0.007513812008045932, -0.007108408686923662, -0.020411567875480745, -0.03302758509925205, -0.045617214572590034, -0.05884939146391366, -0.07338028064358737, -0.08983259158190286, -0.10877571704593095, -0.13070723287958277, -0.1560362619617526, -0.18506915827621617, -0.21799790807462502, -0.25489157584904637, -0.29569104499283766, -0.3402072185753824, -0.38812275671375646, -0.4389973358343027, -0.492276323981096, -0.5473026775498404, -0.6033317806528905, -0.6595488708900517, -0.7150886265813913, -0.7690564322683207, -0.820550793004603, -0.8686863348399761, -0.9126168098185573, -0.9515575192961525, -0.9848065795854936, -1.0117644786599824, -1.0319514113150634, -1.0450219318834155, -1.0507765270803182, -1.0491697852770738, -1.0403149206630877, -1.0244844993470557, -1.002107307285972, -0.973761394728547, -0.9401634262741598, -0.9021545573412545, -0.8606831445335734, -0.8167846769314069, -0.7715593857329199, -0.7261480491640059, -0.6817065566665133, -0.6393798298695391, -0.6002757168853208, -0.5654394805433599, -0.5358294901452653, -0.51229470042071, -0.4955544611913158, -0.4861811477550655, -0.48458603646868564, -0.4910087740069949, -0.5055107041525188, -0.5279722247662516, -0.5580942520249611, -0.5954037714050417, -0.6392633576225429, -0.6888844511725, -0.7433440895517588, -0.8016047088810746, -0.8625365584712886, -0.9249422086882765, -0.9875825827758551, -1.0492039073041384, -1.1085649544957714, -1.1644639433602373, -1.2157644754841639, -1.261419905256065, -1.3004955826542877, -1.3321884585496866, -1.355843606494709, -1.3709672896141885, -1.3772362846481452, -1.3745032653776195, -1.3627981423819329, -1.3423253530127537, -1.3134571922580422, -1.276723369445844, -1.2327970652074478, -1.1824778456070806, -1.1266718638513586, -1.0663698427412525, -1.0026233815148917, -0.936520167748574, -0.8691586976672767, -0.8016231160513912, -0.7349587797666879, -0.6701491270139246, -0.6080943982812312, -0.5495927056237414, -0.49532388555383394, -0.4458364990582623, -0.40153826187669756, -0.3626901012000216, -0.3294039435558348, -0.3016442451269715, -0.2792331824280755, -0.2618593304669292, -0.24908956949483071, -0.2403838823332151, -0.23511263400491644, -0.2325758657256022, -0.23202408768392774, -0.23268002061396525, -0.23376071576442872, -0.23449947696756265, -0.23416701721434843, -0.23209130519378007, -0.2276755940353346, -0.22041417404520258, -0.20990545226902685, -0.19586203268135846, -0.17811754988162137, -0.1566300943539411, -0.13148215645814393, -0.10287710709960313, -0.0711323231743337, -0.03666915311860967, -3.501338376429911e-16], [0.0, 0.037766903976489935, 0.07618478725972676, 0.11457372433036747, 0.15224666728850478, 0.1885299225303975, 0.22278333151908877, 0.25441961203528346, 0.2829223372276002, 0.3078620641639067, 0.328910170557987, 0.3458500167306357, 0.35858511819539973, 0.3671440908187636, 0.3716822133658438, 0.3724795393181052, 0.36993557894306633, 0.3645606614575376, 0.35696417350834325, 0.3478399519091777, 0.33794918354441167, 0.3281012316710504, 0.31913286382307104, 0.3118864007086156, 0.30718733674316556, 0.30582200035552576, 0.30851582545548717, 0.31591279433478336, 0.3285565870175694, 0.34687393326783716, 0.3711606120231523, 0.401570480198031, 0.43810784011393783, 0.48062337404300687, 0.5288137874810934, 0.5822252119308075, 0.6402603254182544, 0.7021890569776782, 0.7671626521965087, 0.8342307928344169, 0.9023613866084078, 0.9704625753935543, 1.0374064530272409, 1.1020539390623276, 1.1632802233312387, 1.2200001788710455, 1.271193138083566, 1.315926439068985, 1.3533771756182393, 1.382851624763336, 1.4038018791085234, 1.415839276122794, 1.4187442916017183, 1.412472647790834, 1.3971574761856436, 1.373107468611114, 1.340801045560909, 1.3008766656220045, 1.2541194918133578, 1.2014447175857101, 1.143877934944157, 1.0825329977221558, 1.0185878927347172, 0.9532591789147569, 0.8877755884367465, 0.8233514034322597, 0.761160226729466, 0.7023097549912495, 0.6478181379372011, 0.5985924686239041, 0.5554098979794126, 0.5189018032146641, 0.48954136592753644, 0.46763483348478735, 0.45331664862768073, 0.44654853936876193, 0.44712256640071796, 0.45466803074018863, 0.4686620524842934, 0.48844354460174794, 0.5132302257263623, 0.5421382449056543, 0.5742039308952651, 0.6084071303301293, 0.6436955640941638, 0.6790096102720916, 0.7133069156713977, 0.7455862461619139, 0.774910008745766, 0.8004249147367332, 0.821380302751896, 0.8371437011394474, 0.8472132804415561, 0.8512269257303939, 0.8489677441695536, 0.840365912800847, 0.8254968630995804, 0.8045758899993819, 0.7779493615947174, 0.7460827893908981, 0.7095460957184173, 0.6689964828685592, 0.6251593659717359, 0.578807877225053, 0.530741481676794, 0.48176426361515456, 0.4326634472543011, 0.3841887057863767, 0.33703278925443886, 0.29181396472933957, 0.24906071290794785, 0.20919906476481656, 0.172542891835376, 0.13928738587526707, 0.10950588000959895, 0.08315007618329058, 0.060053654964883685, 0.039939155791134356, 0.022427930796607785, 0.007052895601653127, -0.006726272147560673, -0.019505899245116354, -0.031919514071113105, -0.04461798102941773, -0.05824910681344164, -0.07343726723444485, -0.09076360345551313, -0.11074732248364738, -0.1338286090281081, -0.1603536150276919, -0.19056194030500584, -0.22457695424798194, -0.2623992357447372, -0.30390332863554864, -0.34883792470841063, -0.3968294979012189, -0.44738932411377774, -0.4999237331324818, -0.5537473548544217, -0.6080990434041987, -0.6621600918642755, -0.7150742889963446, -0.7659693190893319, -0.8139789682265547, -0.8582655758095111, -0.8980421597647236, -0.9325936477994964, -0.961296665310147, -0.9836373626734556, -0.9992268099116809, -1.0078135440277096, -1.0092929222708715, -1.003713011558402, -0.9912768283571836, -0.9723408324590043, -0.9474096700632995, -0.917127254141858, -0.8822643609082101, -0.8437030080956778, -0.8024179615008341, -0.759455788858996, -0.715911942768056, -0.6729064054912937, -0.6315584667557075, -0.5929612301406751, -0.5581564536818922, -0.5281103256120042, -0.5036907567994116, -0.48564673786800405, -0.47459026197194853, -0.47098125488113085, -0.47511588382863984, -0.4871185371757141, -0.5069376802832368, -0.5343457011446331, -0.5689427645641941, -0.610164598263122, -0.6572940405858638, -0.7094760897452762, -0.765736110973882, -0.8250007825782016, -0.8861212965609893, -0.9478982757753999, -1.0091078288130682, -1.068528136996886, -1.1249659555990197, -1.1772824140288392, -1.2244175171636678, -1.265412781793872, -1.2994314875389237, -1.3257760794451212, -1.3439023283779714, -1.353429933581552, -1.3541493374752769, -1.3460246137966945, -1.3291923843497946, -1.303956814581205, -1.2707808316637745, -1.230273798441002, -1.1831759602954164, -1.1303400577183247, -1.072710563245795, -1.0113010559002045, -0.9471702880351046, -0.8813975275363162, -0.8150577720360604, -0.7491974308568169, -0.6848110548859119, -0.6228196649191591, -0.5640511859788155, -0.5092234398129617, -0.45893008162643506, -0.41362979174933845, -0.37363895031346056, -0.33912793515126866, -0.3101210922532283, -0.2865003364835341, -0.2680122501419955, -0.2542784606079679, -0.24480899784944746, -0.23901826001346965, -0.2362431524189835, -0.23576291359134033, -0.23682010276645882, -0.23864219749652943, -0.2404632382147592, -0.24154495911900262, -0.24119686141066096, -0.23879471531840343, -0.23379702064576688, -0.22575901068475185, -0.21434384981700305, -0.19933074930493522, -0.18061980676531994, -0.15823346055730889, -0.1323145386280695, -0.10312097000242511, -0.07101731383197186, -0.036463343538007405, -3.4677076094501506e-16], [0.0, 0.03712146651289038, 0.07458150309202567, 0.11171126999941448, 0.14784575241297762, 0.18234364068394895, 0.2146066202535221, 0.2440975507975868, 0.27035704223764384, 0.29301797600602697, 0.31181757236213775, 0.32660666730687093, 0.3373559341565964, 0.34415886331564527, 0.3472313972497816, 0.3469082040074125, 0.34363565967999865, 0.33796169573742896, 0.3305227490516476, 0.3220281285550224, 0.3132421809320953, 0.30496469676721044, 0.29801004665215225, 0.2931855726549739, 0.2912697833240803, 0.2929909094375615, 0.29900637273642405, 0.30988370098108503, 0.32608339027084965, 0.347944170431711, 0.3756710724937725, 0.4093266302239357, 0.448825471989252, 0.49393247675737084, 0.5442645808214411, 0.5992962320191595, 0.6583683980202663, 0.7207009469190507, 0.7854081340826704, 0.8515168510711085, 0.9179872224115753, 0.9837350758338508, 1.0476557627684686, 1.1086487697136098, 1.1656425384173437, 1.2176189042953707, 1.2636365683591673, 1.3028530380601087, 1.3345445064044794, 1.3581231856642488, 1.3731516708793934, 1.3793539777054196, 1.3766229773309306, 1.3650240362821815, 1.3447947588799662, 1.3163408227327906, 1.2802279906851104, 1.2371704738244353, 1.1880159072634315, 1.133727281328471, 1.0753622435303463, 1.0140502494913624, 0.9509680923238011, 0.8873143785466314, 0.824283543550386, 0.7630400102691208, 0.7046930908375303, 0.6502732127003219, 0.6007100183531708, 0.5568128424247228, 0.5192540122746797, 0.4885553500958512, 0.46507817734000134, 0.4490170380286239, 0.44039726822263525, 0.43907644679252505, 0.4447496699030949, 0.4569585005665994, 0.47510335744290144, 0.49845902589456614, 0.5261929011073768, 0.5573855096320849, 0.5910528035183942, 0.626169681544471, 0.6616941658313669, 0.6965916499756339, 0.7298586369912631, 0.7605454017268046, 0.787777042567568, 0.8107724303596187, 0.8288606174963817, 0.8414943355933927, 0.8482602844893646, 0.8488859965846622, 0.8432431467258257, 0.8313472668137428, 0.8133539138364793, 0.7895514278799738, 0.7603505006716827, 0.7262708532854106, 0.6879253918538788, 0.6460022707726525, 0.6012453424512436, 0.5544335099699501, 0.5063595231384511, 0.4578087688593833, 0.40953860315625507, 0.3622587548587877, 0.3166133002246333, 0.2731646645221847, 0.2323800519259476, 0.19462064038900365, 0.16013380511117378, 0.12904855467882925, 0.10137427993578682, 0.07700282928739481, 0.05571383763131495, 0.037183151639765745, 0.02099411382716668, 0.0066513937554050755, -0.006403011270018626, -0.018772039906744968, -0.0310845738512783, -0.04397570000626953, -0.05806675907223279, -0.07394571786138007, -0.09214839479516292, -0.11314104660245786, -0.13730478971745505, -0.16492228315017854, -0.19616704184135694, -0.23109568216895282, -0.2696433260406514, -0.3116223087797972, -0.35672425083936166, -0.40452546640906456, -0.4544955954121603, -0.5060092614111282, -0.5583604786842531, -0.6107794592112212, -0.6624514063632293, -0.7125368283675106, -0.7601928624899639, -0.8045950714473724, -0.8449591576010232, -0.8805620384394699, -0.9107617388255932, -0.9350155812076826, -0.9528961938777948, -0.9641049084747384, -0.9684821800384891, -0.9660147345154038, -0.9568392279374007, -0.9412422866050777, -0.9196568863979663, -0.8926551196218012, -0.860937487347682, -0.8253189417797215, -0.7867119846527487, -0.7461072019787212, -0.7045516807707963, -0.663125808037675, -0.6229189949774573, -0.5850048988239236, -0.5504167304444852, -0.520123237134282, -0.4950059370232171, -0.4758381543943897, -0.46326636463263304, -0.45779430444281305, -0.4597702386696609, -0.4693777010628941, -0.486629944451688, -0.5113682480058281, -0.5432641376989877, -0.5818254829794837, -0.6264063402624852, -0.6762203244364621, -0.7303572053059002, -0.787802348827581, -0.8474585550191504, -0.9081697871846924, -0.96874624200865, -1.0279901782152352, -1.0847219036509637, -1.137805317254414, -1.1861724135084082, -1.228846182347981, -1.2649613764968017, -1.2937826698661654, -1.3147197937054185, -1.3273393100944557, -1.331372763330877, -1.3267210368042577, -1.3134548339386458, -1.2918112944980105, -1.262186849724981, -1.2251265091737125, -1.1813098565277573, -1.1315341091129683, -1.0766946643489732, -1.0177636143769881, -0.9557667561655582, -0.8917596574337411, -0.826803357970573, -0.7619402909391267, -0.6981709994534079, -0.6364322003797072, -0.5775767105601475, -0.5223557014339634, -0.47140368759644485, -0.42522658471607483, -0.38419309419279385, -0.3485295879424363, -0.3183185788349405, -0.29350077278909026, -0.27388060956245996, -0.2591351130811268, -0.2488257908649767, -0.24241324772965414, -0.23927411331716678, -0.2387198277339693, -0.24001678600623666, -0.2424073112504352, -0.2451309091358045, -0.2474452527781855, -0.24864635769769702, -0.2480874305937264, -0.24519591279616604, -0.23948828837434907, -0.23058228675760065, -0.21820617880864543, -0.20220494182958415, -0.18254315102076069, -0.15930454037133057, -0.13268826266847555, -0.1030019640728143, -0.07065187134919769, -0.03613016727364492, -3.4222105640597696e-16], [0.0, 0.03635616368727921, 0.07275002485656257, 0.10852957259284614, 0.14305700869190197, 0.1757278694302714, 0.20598928228811306, 0.2333568642597548, 0.25742980298239815, 0.2779037083358916, 0.2945808792487681, 0.30737769675147186, 0.3163289281770125, 0.3215888069606253, 0.32342883572656955, 0.32223234517015226, 0.3184859255021256, 0.31276792878768955, 0.3057343173149798, 0.2981022032161129, 0.2906314861510296, 0.28410504737421444, 0.27930799861054245, 0.27700651182606895, 0.2779267704594474, 0.282734583575237, 0.2920161916461716, 0.3062607665432033, 0.3258450694202804, 0.3510206794559346, 0.38190414508370785, 0.4184703389033487, 0.46054921964000445, 0.5078261212226313, 0.5598456023393031, 0.6160188018394956, 0.6756341582717547, 0.7378712678319544, 0.8018175761438613, 0.8664875275680337, 0.9308437329331617, 0.993819664284653, 1.0543433447713295, 1.1113614741755862, 1.1638634165530308, 1.2109044763686003, 1.2516279034380358, 1.2852850946019894, 1.3112535007327208, 1.3290518004357084, 1.3383519653968812, 1.3389879152090194, 1.3309605399258186, 1.314438954589643, 1.2897579394700136, 1.2574116105572783, 1.218043454767938, 1.1724329511430571, 1.1214790809410764, 1.0661811039493492, 1.0076170437480727, 0.946920379459096, 0.8852554843627418, 0.8237923816227649, 0.7636814034954662, 0.7060283424220105, 0.6518706702670911, 0.6021553759725325, 0.5577189326808671, 0.519269853914111, 0.4873742359293391, 0.46244461144597077, 0.44473236031112323, 0.43432383728763135, 0.43114028810153776, 0.43494153434740657, 0.44533331802948556, 0.4617781096032925, 0.48360910148981406, 0.5100470341511254, 0.5402194357545732, 0.5731818008058303, 0.6079401892332439, 0.6434746963002665, 0.6787632261352307, 0.7128049979908122, 0.7446432246273753, 0.7733864261596403, 0.7982278796826676, 0.8184627540484214, 0.8335025390499419, 0.8428864474722603, 0.8462895452475498, 0.8435274473818195, 0.8345575033422539, 0.8194764830635711, 0.7985148614734213, 0.7720278832986934, 0.7404836688208459, 0.7044486932513425, 0.6645710357262933, 0.6215618470208337, 0.5761755266653065, 0.5291891292036792, 0.48138153518123344, 0.4335129247264104, 0.3863050802834355, 0.34042302048072687, 0.29645842993918115, 0.25491530100299464, 0.2161981441726103, 0.18060305595200013, 0.14831185762809793, 0.11938943809287196, 0.09378435024052512, 0.07133262584328035, 0.051764690272986656, 0.034715178106373513, 0.01973537556102319, 0.006307947755177843, -0.006136450315152621, -0.018201128940106993, -0.030504372030846705, -0.043660010306418646, -0.05825808251956869, -0.07484610597578792, -0.09391146227376117, -0.11586537585856058, -0.1410289223421378, -0.1696214516298503, -0.20175174900278975, -0.2374121870014908, -0.2764760440084222, -0.3186980837748756, -0.3637184058430215, -0.41106949200600174, -0.4601862907730846, -0.5104191023707609, -0.5610489531306314, -0.6113050820662271, -0.6603841057102977, -0.7074703813275353, -0.7517570546234619, -0.7924672569292512, -0.8288749091252482, -0.8603245955086248, -0.8862499903077593, -0.9061903521529279, -0.9198046467570922, -0.9268829142592264, -0.9273545637702251, -0.9212933520225632, -0.9089188838346574, -0.8905945573694352, -0.8668219647890553, -0.838231846715277, -0.805571784719863, -0.7696908977579674, -0.7315218839837531, -0.6920608168635191, -0.6523451622347719, -0.6134305294946318, -0.5763667042559447, -0.5421735307064631, -0.511817218992698, -0.48618764601245124, -0.4660771971707803, -0.45216166240819206, -0.4449836529527549, -0.4449389468973521, -0.4522661032612724, -0.46703960731375477, -0.4891667264776974, -0.518388168119999, -0.554282540110612, -0.5962745243965937, -0.6436465851987886, -0.6955539489586398, -0.7510425149025646, -0.8090692849610941, -0.8685248414922061, -0.928257352284174, -0.9870975458486959, -1.0438840769486146, -1.0974886931981165, -1.1468406186461155, -1.1909495893780855, -1.2289270088768687, -1.2600047363646254, -1.2835510784907758, -1.2990836221329376, -1.3062786220889029, -1.3049767401966728, -1.295185019902372, -1.2770750703647036, -1.2509775246404986, -1.2173729251333911, -1.17687927414853, -1.1302365660231648, -1.078288687989652, -1.0219631379659484, -0.962249057390558, -0.9001741148321722, -0.8367808005214121, -0.773102702612275, -0.7101413326632544, -0.6488440506566956, -0.5900836093148379, -0.5346397943171973, -0.48318358238033876, -0.43626417441310766, -0.3942991877403197, -0.3575682115339434, -0.3262098451013673, -0.3002222516638105, -0.2794671728810471, -0.26367726381168266, -0.2524665263617855, -0.24534354358675872, -0.24172714933746464, -0.2409641093484576, -0.24234834238073935, -0.24514117460549653, -0.2485920978973686, -0.2519594936202285, -0.2545307880231237, -0.2556415233654144, -0.2546928598685454, -0.25116706673310635, -0.24464061464654915, -0.23479454604673172, -0.22142187126669013, -0.2044318167355383, -0.1838508336644611, -0.15982036001812983, -0.1325914129219556, -0.1025161708488235, -0.07003678288586611, -0.035671714131325784, -3.3651968076615246e-16], [0.0, 0.03547750111680663, 0.07070615230775851, 0.10505610199489504, 0.13792145007855863, 0.16873846398930065, 0.1970026768800167, 0.22228440509087383, 0.2442422624857337, 0.26263430062570964, 0.2773264647197681, 0.28829812433757385, 0.29564451324522306, 0.29957599252824246, 0.30041413338299666, 0.298584698509083, 0.2946076818320845, 0.2890846432801639, 0.28268364657396405, 0.2761221716533785, 0.27014842783035065, 0.26552153762544306, 0.2629910933822472, 0.263276608314603, 0.267047390097257, 0.2749033582583387, 0.2873573066017625, 0.3048190791390657, 0.32758208332175776, 0.35581250881535614, 0.3895415549966796, 0.4286608973786441, 0.4729215440645593, 0.5219361500562637, 0.575184771845092, 0.6320239593168634, 0.6916989987218586, 0.7533590413704574, 0.8160747797878845, 0.8788582681220777, 0.9406844282781331, 1.0005137389474679, 1.0573155725369978, 1.1100916258124796, 1.1578988843615554, 1.199871568934959, 1.2352415331812696, 1.2633566167609738, 1.2836965044974011, 1.2958856999817203, 1.2997032895083884, 1.2950892477474631, 1.282147118331607, 1.2611429885632366, 1.2325007656390226, 1.1967938499972652, 1.154733387468264, 1.1071533637489286, 1.0549928803325561, 0.9992760185564846, 0.941089756234424, 0.8815604480043154, 0.8218294149065681, 0.7630282099717681, 0.7062541342228014, 0.6525465712990063, 0.6028646890430711, 0.5580670233429594, 0.5188934141019771, 0.4859497065331524, 0.45969556442759335, 0.44043566725927463, 0.4283144817901927, 0.42331471321493536, 0.42525945292378997, 0.43381795181493343, 0.44851486189742407, 0.46874270679527685, 0.49377726568402724, 0.522795487008584, 0.5548954896917891, 0.5891181618567382, 0.6244698314907159, 0.6599454608134353, 0.6945518068959895, 0.7273299954967164, 0.75737697298647, 0.783865332147128, 0.8060610507422336, 0.8233387359766154, 0.8351940319099282, 0.841252918957183, 0.8412777129900113, 0.8351696542860705, 0.8229680615976595, 0.8048461118092529, 0.7811033889127523, 0.7521554252873244, 0.7185205315702924, 0.6808042769419083, 0.639682037812464, 0.5958800783244055, 0.5501556596651328, 0.5032766961257771, 0.45600148365251686, 0.4090590211640974, 0.3631304263284732, 0.31883191630691676, 0.27669978100417975, 0.23717772272049226, 0.20060687316353074, 0.167218728154649, 0.13713116385308008, 0.11034761786910689, 0.08675943628340602, 0.06615130542137045, 0.048209607327750946, 0.03253346226887994, 0.01864815216807025, 0.006020557408037438, -0.005923812535305347, -0.017782655318332063, -0.030158068806353973, -0.04363760770033023, -0.05877571410236869, -0.07607602298645301, -0.09597502124186015, -0.11882750434112312, -0.14489422862275608, -0.17433210083070463, -0.2071871813370021, -0.2433907050350725, -0.28275824605564565, -0.3249920711900572, -0.3696866442599931, -0.4163371617389547, -0.46435092078399665, -0.5130612464846834, -0.5617436374703055, -0.6096337297617324, -0.655946629428231, -0.6998971264831119, -0.7407202765173582, -0.7776918235163649, -0.8101479374988025, -0.8375037540951198, -0.859270229650624, -0.8750688642733805, -0.8846438955192153, -0.8878716258959182, -0.884766616600021, -0.8754845561745672, -0.860321694218138, -0.8397108148742238, -0.8142138104928331, -0.784511000458818, -0.7513874216209528, -0.7157163930034011, -0.6784407266318386, -0.6405520166269447, -0.603068488689685, -0.5670119304601352, -0.5333842489930797, -0.5031442140871288, -0.47718494508374004, -0.4563126840072338, -0.44122736987182576, -0.4325054882901295, -0.43058561814509644, -0.43575703428895146, -0.44815165352128367, -0.4677395322086293, -0.49432803975272704, -0.5275647447391478, -0.5669439621284719, -0.6118168224443054, -0.6614046396976416, -0.7148152758207087, -0.7710621275935642, -0.8290852991869126, -0.8877744710507035, -0.9459929352300919, -1.0026022392814553, -1.056486866472203, -1.1065783792324475, -1.151878465899342, -1.1914803573345356, -1.2245881193502122, -1.2505333780846672, -1.268789097270007, -1.2789800972188803, -1.2808900835899966, -1.274465037660204, -1.2598129068897854, -1.2371996228919744, -1.2070415613533594, -1.1698946428693844, -1.1264403530057145, -1.0774690322465428, -1.0238608500941828, -0.9665649309075905, -0.9065771408326301, -0.844917074392772, -0.7826047952942953, -0.7206378884009836, -0.6599693686309687, -0.6014869680394208, -0.5459942852183716, -0.4941942323234784, -0.44667515576755207, -0.4038999383982509, -0.3661983155166939, -0.3337625562842726, -0.30664657792428096, -0.28476847474846884, -0.2679163595478318, -0.255757333376301, -0.24784932324117306, -0.24365545758211724, -0.2425605883828717, -0.24388951780991333, -0.24692644764957958, -0.2509351424732136, -0.2551792830444548, -0.2589424853150563, -0.2615474724254311, -0.26237391209194455, -0.26087446896162114, -0.25658866997772745, -0.24915423927761698, -0.23831562613918106, -0.2239295232946118, -0.20596725166231658, -0.1845139692103084, -0.159764744187222, -0.13201761425057926, -0.1016638310296488, -0.0691755624102802, -0.03509139048347972, -3.297132057972448e-16], [0.0, 0.034493039556088644, 0.06846754445904861, 0.10132069210514436, 0.13248262181418743, 0.1614336139993825, 0.18771992240548205, 0.2109678300000346, 0.23089554474668486, 0.24732260704935058, 0.2601765447308469, 0.2694965823829159, 0.27543428800531383, 0.2782511191180765, 0.278312910979551, 0.27608142913750555, 0.2721031852647347, 0.2669957871367009, 0.2614321588677788, 0.25612302446966795, 0.2517980949716101, 0.2491864355309825, 0.24899651322189337, 0.25189643787312177, 0.25849490710351497, 0.26932335256366696, 0.28481975765141726, 0.30531457825531066, 0.3310191483249956, 0.36201689247880087, 0.39825759989259474, 0.4395549390389277, 0.4855873133006923, 0.5359020750339332, 0.5899230323415547, 0.6469611007112457, 0.7062278728094815, 0.7668518060756411, 0.8278966611677437, 0.8883817664451493, 0.9473036359923442, 1.0036584324013154, 1.0564647415685944, 1.1047861157546284, 1.1477528434070676, 1.1845824197484622, 1.2145982205287216, 1.2372459219809573, 1.252107261930782, 1.2589107989496047, 1.2575393969188768, 1.2480342396795887, 1.2305952627041639, 1.2055779739466748, 1.1734867221273593, 1.1349645555901764, 1.0907798964666118, 1.0418103311930371, 0.9890238875980777, 0.9334582291101494, 0.8761982466582674, 0.818352567328041, 0.7610295248480802, 0.7053131498835359, 0.6522397375879959, 0.6027755359256612, 0.5577960712645008, 0.5180675883192477, 0.4842310306561062, 0.4567889269035344, 0.4360954780395642, 0.42235006435191524, 0.41559430876891434, 0.41571274823719734, 0.42243707875092684, 0.43535385461516796, 0.4539154406229949, 0.4774539390327727, 0.5051977434115927, 0.5362903102519182, 0.5698106882446567, 0.6047953054253895, 0.6402604870420405, 0.6752251625590114, 0.7087332190315991, 0.7398749701462757, 0.7678072351909081, 0.7917715594412442, 0.8111101559717243, 0.8252792074887082, 0.8338592339657938, 0.8365623059474211, 0.8332359625257232, 0.8238637752120567, 0.8085625821734045, 0.7875764995179169, 0.7612678954570464, 0.7301055872886758, 0.6946505884101748, 0.6555397913310842, 0.6134680214758801, 0.5691689342625913, 0.5233952536074591, 0.4768988630357852, 0.4304112606877268, 0.3846248767316759, 0.3401757263953842, 0.297627834667442, 0.25745982067576556, 0.22005397205312432, 0.18568807372999455, 0.15453018323236356, 0.1266364675470087, 0.10195213690418625, 0.08031543043749655, 0.06146452964760993, 0.04504719991892378, 0.03063288992789939, 0.01772695541672195, 0.005786619085052577, -0.005761766343455289, -0.017504618367200065, -0.030022676298500993, -0.043872701238907595, -0.05956981771094423, -0.07757097378004542, -0.09825996780035218, -0.121934449679963, -0.14879525379908623, -0.17893836070780972, -0.21234971699224856, -0.24890306893772168, -0.28836088769759777, -0.330378383565476, -0.3745105266723223, -0.4202219130220327, -0.4668992402266922, -0.5138660885009905, -0.5603996411762293, -0.6057489267649708, -0.6491541227894639, -0.6898664312634604, -0.7271680176844347, -0.7603915001417852, -0.7889384828472028, -0.8122966488931377, -0.8300549598708494, -0.8419165543482836, -0.8477089920475388, -0.8473915545355278, -0.8410593847826149, -0.8289443252930272, -0.8114123957599236, -0.7889579343374807, -0.7621945095914852, -0.7318427909268288, -0.6987156417844204, -0.6637007702410818, -0.6277413340721985, -0.5918149502784348, -0.5569116011964602, -0.5240109595359089, -0.49405967222885044, -0.46794914737400234, -0.44649437965917566, -0.43041432763323095, -0.42031432157786885, -0.41667093431643026, -0.4198196901993646, -0.42994592109718566, -0.4470790041154037, -0.47109013571790515, -0.5016937129489817, -0.538452306523178, -0.5807851247992635, -0.6279797841612973, -0.6792071221337469, -0.7335387165930708, -0.7899667094884971, -0.8474254781371929, -0.9048146527677874, -0.9610229466363034, -1.0149522455219941, -1.0655413972038426, -1.111789148773688, -1.1527757001805947, -1.1876823757200599, -1.2158089604653712, -1.2365883047779183, -1.2495978656554054, -1.2545679271762245, -1.2513863218783055, -1.2400995586271546, -1.2209103483368142, -1.194171604716269, -1.1603770809317524, -1.1201488826658628, -1.0742221715845512, -1.0234274389117122, -0.9686707850720387, -0.9109126868442623, -0.8511457670836499, -0.7903721030338109, -0.7295806170747655, -0.6697250882925504, -0.611703304678735, -0.5563378445722876, -0.5043589329472842, -0.4563897644243308, -0.4129346217994866, -0.3743700480284516, -0.34093925275110504, -0.3127498535117305, -0.28977496883973275, -0.2718575973668317, -0.2587181362277158, -0.2499648151239102, -0.2451067515217531, -0.24356926924908168, -0.2447110688001235, -0.2478427942689669, -0.2522465100575994, -0.25719558110162044, -0.2619744437719583, -0.2658977609696315, -0.2683284740348256, -0.2686942954245167, -0.266502228853282, -0.2613507566338714, -0.25293939593571746, -0.24107539501703495, -0.22567741541342873, -0.20677612467956194, -0.18451170458647678, -0.15912835964215094, -0.1309659884038508, -0.10044925332657541, -0.06807435199169803, -0.03439385179009256, -3.218590316701881e-16], [0.0, 0.033411284279382884, 0.06605347424679822, 0.0973551431466901, 0.1267860399059188, 0.153873117338393, 0.17821500960062325, 0.19949456539331006, 0.21748909350622841, 0.23207803629082357, 0.24324785302830973, 0.2510939672645524, 0.2558197081850921, 0.2577322540829427, 0.2572356639551714, 0.25482115927622606, 0.2510548901081695, 0.24656348608752013, 0.2420177517838014, 0.2381149159486307, 0.2355598839805128, 0.23504597148795406, 0.23723561339090946, 0.2427415471062122, 0.2521089598758663, 0.2657990693923186, 0.28417457403756585, 0.3074873650680816, 0.33586883901023606, 0.3693230857003969, 0.4077231573510981, 0.4508105484740145, 0.4981979373072691, 0.5493751585389531, 0.6037182965967391, 0.6605017105876516, 0.7189127280714288, 0.778068677082575, 0.8370358658793924, 0.8948500693018351, 0.9505380406449664, 1.0031395396218488, 1.0517293510341417, 1.0954387656212077, 1.1334760043346264, 1.1651450897813953, 1.1898627032784042, 1.2071726120440096, 1.2167573074188547, 1.2184465603017134, 1.2122226726294691, 1.1982222819627624, 1.1767346581597797, 1.1481965147365176, 1.1131834407849013, 1.07239814021877, 1.0266557416664563, 0.9768665126569257, 0.9240163741344067, 0.8691456642578583, 0.81332664260114, 0.7576402562349156, 0.7031527069982456, 0.6508923641192683, 0.6018275581007866, 0.5568457706488765, 0.5167347019074443, 0.48216565118824656, 0.45367959185653267, 0.4316762564045075, 0.41640647559797284, 0.4079679376783207, 0.40630445184482605, 0.4112087166258838, 0.42232851031106183, 0.4391761393905645, 0.4611409039103028, 0.4875042676693605, 0.517457357981248, 0.5501203658165098, 0.58456337383685, 0.6198281081523526, 0.6549500903283348, 0.6889806596761918, 0.7210083423060862, 0.7501790626031303, 0.7757147242034794, 0.7969297303829671, 0.8132450669389334, 0.8241996328033991, 0.8294585732112266, 0.8288184455187995, 0.8222091268486846, 0.8096924536553088, 0.791457664056437, 0.7678137923545286, 0.7391792396386323, 0.7060688128757368, 0.669078585786751, 0.6288689865664674, 0.586146558889356, 0.5416448726453894, 0.49610507875993065, 0.45025660785960286, 0.40479850535554013, 0.36038187594510823, 0.31759387911045545, 0.27694367474018855, 0.23885066561667123, 0.20363532254020913, 0.17151280986028722, 0.14258955588412559, 0.11686283589578045, 0.09422335729014661, 0.07446075858566868, 0.057271858792965584, 0.04227142268568106, 0.029005142734977632, 0.016964481464399547, 0.0056029701944080145, -0.005646477220114803, -0.017353703059587756, -0.03007337820338363, -0.044327491392024194, -0.06058872750197099, -0.07926518412084459, -0.10068684122766564, -0.12509415361251533, -0.15262908095254582, -0.18332880757730638, -0.21712233449337262, -0.25383005195050806, -0.2931663235964453, -0.33474503503820324, -0.37808798238513674, -0.4226359020507806, -0.4677618736234873, -0.5127867647476253, -0.5569963322923015, -0.5996595490241619, -0.6400476907071349, -0.6774536959192297, -0.7112113005079087, -0.7407134507984674, -0.765429514407218, -0.7849208344622662, -0.7988542115621254, -0.8070129469784244, -0.8093051392377135, -0.8057689928642667, -0.7965749710931724, -0.7820247019703986, -0.762546627525248, -0.7386884666414408, -0.7111066418553583, -0.6805528965918966, -0.6478584004057837, -0.6139157038505967, -0.5796589600397974, -0.5460428753947326, -0.5140208863391106, -0.48452308091730906, -0.45843439390000207, -0.43657360062108047, -0.4196736186087557, -0.40836359739230604, -0.40315323635444705, -0.404419719120676, -0.4123975919630984, -0.4271718445185483, -0.44867437545340344, -0.4766839453866814, -0.5108296363618267, -0.5505977534580468, -0.595342021794933, -0.6442968532193613, -0.6965933833001006, -0.7512779126940378, -0.8073323291164292, -0.8636960384613643, -0.9192888972451329, -0.9730346143753271, -1.023884078874848, -1.0708380718914157, -1.1129688360594006, -1.1494400026914262, -1.1795244166925514, -1.2026194495460945, -1.2182594509835447, -1.2261250585487504, -1.2260491595219924, -1.218019379744919, -1.2021770568276853, -1.1788127390021717, -1.1483583334681602, -1.1113761074530115, -1.068544819441039, -1.0206433253262277, -0.968532062974055, -0.9131328674301867, -0.8554076066188646, -0.7963361529401645, -0.7368942191096387, -0.6780315866039606, -0.6206512422185715, -0.5655899128615672, -0.5136004514636932, -0.4653364787297154, -0.4213396276116709, -0.3820296713059207, -0.34769774292020655, -0.3185027775397366, -0.2944712271720713, -0.2755000179644353, -0.2613626391751907, -0.25171817662134066, -0.24612303161078478, -0.2440450014667499, -0.2448793412541809, -0.24796637960299475, -0.25261022572347624, -0.2580980806827776, -0.2637196543210764, -0.26878619008515686, -0.2726486134845741, -0.2747143454571613, -0.274462358988723, -0.2714561049032637, -0.2653539895999623, -0.25591715220590633, -0.24301435948989436, -0.22662391214018002, -0.20683253373868077, -0.18383129199670142, -0.15790867857376423, -0.12944104714181068, -0.09888067743003756, -0.06674179407333125, -0.0335849216492584, -3.130244867068193e-16], [0.0, 0.032241565153860195, 0.06348456816826081, 0.09319280721202114, 0.12087861633701416, 0.14611764650565728, 0.16856191847679558, 0.18795079190416936, 0.2041195488234885, 0.2170053513482178, 0.2266504013032714, 0.23320220198382002, 0.23691089740124902, 0.23812374036782138, 0.23727681565116493, 0.2348842163004054, 0.2315249382820544, 0.22782781905914418, 0.2244548981570313, 0.22208362074002808, 0.2213883376653243, 0.22302157653798171, 0.22759556740057024, 0.2356645035892278, 0.24770800301596807, 0.2641162080411471, 0.2851769238229236, 0.31106514649607614, 0.3418352749227271, 0.3774162344836543, 0.417609670046621, 0.4620912896178732, 0.5104153621260821, 0.5620222942407309, 0.6162491340419979, 0.6723427756575827, 0.7294755705048676, 0.786762989240177, 0.8432829254682161, 0.8980961890446907, 0.9502677045138539, 0.9988879096924337, 1.0430938411851423, 1.082089397934981, 1.1151642907046215, 1.1417112142763648, 1.1612408194712338, 1.1733941128639438, 1.1779519720914724, 1.1748415324709696, 1.1641392746157633, 1.1460707210705292, 1.1210067307727878, 1.0894564614195548, 1.052057149592538, 1.0095609348246846, 0.9628190248094329, 0.9127635629246484, 0.8603876146000847, 0.8067237344444547, 0.7528216103534637, 0.6997253032018781, 0.6484506106309805, 0.5999630806330769, 0.5551571851736603, 0.5148371363558462, 0.4796997882976061, 0.45032001792057363, 0.42713891846067664, 0.41045507215584, 0.4004190948897823, 0.3970315673717097, 0.4001443866177441, 0.4094654900413766, 0.4245668243414196, 0.44489535454601886, 0.46978683689663864, 0.4984820144738997, 0.5301448381439181, 0.563882268895151, 0.5987651820549994, 0.6338498700649318, 0.6681996290047922, 0.7009059151391513, 0.7311085713490099, 0.7580146490414543, 0.7809153883296822, 0.7992009669970316, 0.8123726857940511, 0.8200523225331793, 0.8219884586153087, 0.8180596572696719, 0.8082744510295192, 0.7927681748574462, 0.7717967589207925, 0.7457276693808891, 0.7150282548661063, 0.6802518188434129, 0.6420217923541658, 0.6010144262145006, 0.5579404557187158, 0.513526213313817, 0.4684946751121612, 0.423546925255083, 0.37934450811821163, 0.3364931125472983, 0.2955279954139228, 0.25690150474176016, 0.22097300668681188, 0.18800145719094905, 0.15814078978489013, 0.13143821755665308, 0.10783547158755614, 0.08717292210711844, 0.06919645415353394, 0.05356689852870151, 0.03987175309761788, 0.027638870658859636, 0.016351739188057823, 0.005465939499315073, -0.00557366469413017, -0.017315467953391173, -0.030283865853831752, -0.04496266424001251, -0.06177960261608979, -0.08109241045809454, -0.10317677562363216, -0.1282165546473958, -0.1562964967948374, -0.18739768876423932, -0.22139585652115845, -0.2580625866983634, -0.29706945417199104, -0.33799496675011714, -0.3803341643010038, -0.4235106399731255, -0.4668906871892066, -0.5097992194625908, -0.5515370622350517, -0.5913991781009573, -0.6286933599445298, -0.6627589113816968, -0.6929848308801622, -0.7188270251427495, -0.7398240985852822, -0.755611298525316, -0.7659322392362624, -0.7706480812566272, -0.7697439039756006, -0.7633320780308852, -0.7516525177642045, -0.7350697710628505, -0.7140669824621575, -0.6892368434434039, -0.66126971949144, -0.6309392147893222, -0.5990855006392382, -0.566596791173372, -0.5343893982062787, -0.5033868349576636, -0.4744984648718908, -0.44859820618835616, -0.426503804882042, -0.40895717801031933, -0.39660630659417484, -0.3899891224575609, -0.3895197877675769, -0.39547771045259006, -0.407999574562208, -0.42707459352203375, -0.4525431178513962, -0.484098649110198, -0.5212932305644016, -0.563546104290158, -0.6101554461454279, -0.6603129161381833, -0.7131206940186153, -0.7676106100759817, -0.8227649305940546, -0.8775383174505573, -0.9308804529155121, -0.981758804508866, -1.0291810012177567, -1.0722163015372392, -1.1100156554634315, -1.1418298962062094, -1.1670256421788285, -1.1850985446701552, -1.19568358017161, -1.1985621570632183, -1.1936658825339195, -1.1810769153618237, -1.1610249115649918, -1.133880650969382, -1.100146511454879, -1.0604440321192519, -1.0154988750360163, -0.9661235560186237, -0.913198366374705, -0.8576509488019263, -0.8004350203606211, -0.7425087531580448, -0.6848133285942072, -0.6282521736560833, -0.5736713680222686, -0.521841679174344, -0.47344264011561854, -0.42904903175410325, -0.3891200708391093, -0.35399153608503775, -0.3238709914778505, -0.29883618857559835, -0.2788366508036341, -0.2636983642632232, -0.25313142336194144, -0.24674040751753518, -0.24403719905852467, -0.24445589386788968, -0.24736940672270713, -0.2521073338777109, -0.2579746071732931, -0.26427045748761635, -0.270307201071796, -0.27542837027510864, -0.2790257301466161, -0.2805547538534877, -0.27954817196171966, -0.2756272622940454, -0.26851060698709867, -0.2580201099859511, -0.24408413984356836, -0.22673773751721488, -0.20611990497745133, -0.18246806594201348, -0.15610986300872598, -0.12745252404673246, -0.09697009318366084, -0.06518887652313977, -0.03267149846217078, -3.03285825180752e-16], [0.0, 0.030993908897351246, 0.06078253407901817, 0.08886816203903239, 0.1148080768349521, 0.13822801615840616, 0.15883374911697237, 0.17642045937343948, 0.19087967408278725, 0.20220354260240328, 0.21048633762086205, 0.2159231234183342, 0.21880560961367418, 0.2195152821044703, 0.2185139741072107, 0.21633210744763837, 0.21355489582601103, 0.21080685611829264, 0.2087350194818757, 0.2079912699374909, 0.209214263266061, 0.21301139282676074, 0.21994127089162724, 0.23049718421845375, 0.24509196106018938, 0.26404465414058725, 0.28756940109722756, 0.3157667715498843, 0.3486178495750571, 0.385981233440411, 0.4275930626265727, 0.47307010721492093, 0.5219158785071288, 0.5735296441595255, 0.6272181580457071, 0.6822098463290193, 0.7376711285536912, 0.7927244975243072, 0.8464679357268041, 0.8979952102187962, 0.9464165632013667, 0.9908793025241857, 1.0305877955273812, 1.0648223809447637, 1.0929567368412674, 1.1144732771954697, 1.1289761949465158, 1.1362018240224894, 1.1360260557373385, 1.1284686144656995, 1.113694071993006, 1.092009557581229, 1.0638591996973485, 1.029815413597654, 0.9905672246353828, 0.9469058884122548, 0.8997081339827669, 0.8499174136500808, 0.7985235910588766, 0.7465415371125391, 0.694989129790706, 0.644865168565663, 0.5971277164511456, 0.5526733727043173, 0.5123179570830726, 0.4767790528742571, 0.4466608114756332, 0.42244136721916137, 0.40446314868616834, 0.39292630350994806, 0.3878853792784919, 0.38924932545384905, 0.3967848021093469, 0.4101227026789586, 0.4287677217275009, 0.45211072683770465, 0.47944362781524064, 0.5099763781303033, 0.542855694250327, 0.5771850394552918, 0.6120453907950334, 0.6465162917023215, 0.6796966887803203, 0.7107250595037382, 0.7387983577731867, 0.763189335912283, 0.7832618439850639, 0.7984837591657872, 0.8084372580084611, 0.8128262113326352, 0.8114805533951268, 0.8043575522618385, 0.7915399849604089, 0.7732312971821922, 0.7497479011268331, 0.7215088347228483, 0.6890230691996778, 0.6528748082675456, 0.6137071696069496, 0.5722046768283576, 0.5290750166346134, 0.48503053097640847, 0.4407699171964439, 0.3969606004681245, 0.3542222225044702, 0.3131116590874686, 0.27410993726836624, 0.23761137219222203, 0.20391518471026343, 0.1732197957615531, 0.14561992358918027, 0.12110653697979991, 0.09956964372449291, 0.08080382026486306, 0.06451631786060563, 0.05033751437547623, 0.037833420597409254, 0.026519897401074483, 0.0158781963513394, 0.005371402632720718, -0.005538663680502056, -0.017374543453270327, -0.030626686610846398, -0.045737895806753956, -0.06308908556670116, -0.08298674271595236, -0.10565242984318, -0.13121462068048853, -0.15970309592362236, -0.19104606170397537, -0.2250700823317558, -0.26150284584324024, -0.2999787071546083, -0.34004688111865833, -0.38118208833793027, -0.42279739197317284, -0.46425890564476213, -0.5049020023417524, -0.5440486133157365, -0.5810251753015694, -0.6151807648743964, -0.6459049508452314, -0.6726448995477937, -0.6949212836131392, -0.7123425720057711, -0.7246173170585959, -0.7315641020762418, -0.7331188696102079, -0.7293394143585008, -0.7204068942345041, -0.7066242867659339, -0.6884117938013905, -0.6662992736373073, -0.6409158542372412, -0.612976952339197, -0.583268989156152, -0.5526321524173284, -0.5219416051864303, -0.4920875829453555, -0.4639548508009402, -0.4384020115734785, -0.41624116245649684, -0.3982183926895596, -0.38499559735253736, -0.37713405336179145, -0.37508016370650005, -0.37915372585999524, -0.3895390213393157, -0.40627895698900646, -0.4292724163408297, -0.45827490310342045, -0.4929024803218639, -0.532638929930265, -0.576845980224476, -0.6247763750930825, -0.6755894904649379, -0.7283691420344964, -0.7821431754158227, -0.8359043867498964, -0.8886322895054095, -0.9393152225645399, -0.9869722861801523, -1.0306745962416515, -1.0695653634016298, -1.1028783316038535, -1.129954149732797, -1.1502542995202338, -1.1633722612895758, -1.1690416651667372, -1.167141247425753, -1.157696507910059, -1.140878043116455, -1.1169966086313263, -1.0864950422417656, -1.0499372533194615, -1.0079945531891015, -0.9614296634705057, -0.9110787933198218, -0.8578322207916881, -0.8026138471416792, -0.7463602149916455, -0.6899994913780982, -0.6344309145807007, -0.5805051893696651, -0.5290062893017781, -0.48063508760780993, -0.43599519099385065, -0.3955812945178791, -0.35977031201144405, -0.3288154668880675, -0.3028434543514938, -0.28185470982489585, -0.26572674175758354, -0.2542204117270796, -0.2469889728002271, -0.24358961022040643, -0.24349716829229084, -0.24611969531403774, -0.25081539582610696, -0.25691054733487906, -0.26371791779393483, -0.27055521097057766, -0.2767630695809661, -0.2817221806376278, -0.28486905341684265, -0.2857100771354194, -0.28383351187446526, -0.2789191213075955, -0.2707452179753877, -0.25919295961269034, -0.24424780665921123, -0.2259981247508819, -0.20463098983576924, -0.1804253257172667, -0.15374257247764261, -0.12501514764537414, -0.09473301854237848, -0.06342875255807041, -0.031661450931017715, -2.927271359114701e-16], [0.0, 0.029678905092289928, 0.057969880446891386, 0.08441637810634095, 0.1086223780556897, 0.1302644603167274, 0.14910187632086916, 0.16498434341510737, 0.17785734537521855, 0.18776478647439312, 0.19484891534741344, 0.19934750586191924, 0.20158835366181077, 0.20198121717232484, 0.20100739887222877, 0.19920722484255518, 0.19716573640893773, 0.19549695568017664, 0.19482712571798674, 0.19577735494637546, 0.19894611346907612, 0.20489203572540068, 0.21411747917676027, 0.2270532725638649, 0.24404506008032814, 0.2653416102213916, 0.29108541099742924, 0.32130581780056905, 0.3559149578395665, 0.394706527250545, 0.43735754542589445, 0.4834330575545498, 0.5323937026615172, 0.5836059924085163, 0.6363550773688645, 0.6898597141340798, 0.7432890900376284, 0.795781113918774, 0.8464617424220465, 0.8944648828298598, 0.938952396095596, 0.9791337180455711, 1.0142846228276745, 1.0437646704875756, 1.0670329096467535, 1.083661445957364, 1.0933465363713037, 1.0959169270991977, 1.0913392180529682, 1.07972010699011, 1.0613054407977345, 1.0364760775629955, 1.0057406394151782, 0.9697253107296464, 0.9291609073310239, 0.8848675080840557, 0.8377369991050216, 0.7887139313218027, 0.7387751330176823, 0.6889085493075726, 0.640091799469601, 0.5932709502210322, 0.5493399982056048, 0.5091215382632492, 0.47334906588718284, 0.44265132332273927, 0.417539049976142, 0.3983944403692732, 0.38546354819948847, 0.3788518047190211, 0.3785227453523778, 0.38429996203327227, 0.3958722220274768, 0.41280161888180283, 0.43453454942895725, 0.46041524422417973, 0.4897015190049223, 0.5215823631936191, 0.5551969393470124, 0.5896545358002373, 0.6240549943088953, 0.6575091257293479, 0.689158629880618, 0.7181950505925347, 0.743877323166656, 0.7655475083831841, 0.7826443538402099, 0.7947143786350541, 0.8014202398056568, 0.8025462069833917, 0.7980006436719449, 0.7878154676714375, 0.7721426375751599, 0.7512477851371832, 0.7255011828440253, 0.6953663005106805, 0.6613862625779152, 0.6241685675994677, 0.5843684719632901, 0.5426714702119146, 0.4997753236920138, 0.45637209722512023, 0.4131306598886965, 0.3706800909561293, 0.3295944059781465, 0.2903789815834451, 0.2534590117769423, 0.21917027449705834, 0.1877524263396906, 0.15934497721535268, 0.13398602695690665, 0.1116137743055969, 0.09207073708345866, 0.0751105525197237, 0.06040716039940471, 0.04756611061477361, 0.03613768236291037, 0.025631456011601716, 0.015531941712954758, 0.005314842106053362, -0.005536489413773909, -0.01751483797575884, -0.0310736003948617, -0.04661236055208921, -0.06446395659404587, -0.08488339079461728, -0.10803888512727076, -0.1340053299740994, -0.1627603113544146, -0.19418283516083948, -0.22805479683721683, -0.26406517349364256, -0.3018168444395397, -0.3408358773268839, -0.3805830522793618, -0.4204673371885419, -0.4598609752947952, -0.4981158025714076, -0.534580378417031, -0.5686174896171888, -0.5996215750816078, -0.6270356178451403, -0.6503670612940865, -0.6692023283173268, -0.6832195545704387, -0.6921991894985736, -0.6960321701568766, -0.694725431936663, -0.6884045855979595, -0.6773136599123295, -0.661811882003472, -0.6423675413305521, -0.6195490563533015, -0.5940134334261793, -0.5664923736289564, -0.5377763433946365, -0.5086969774296033, -0.480108226205561, -0.4528666941246172, -0.4278116374487217, -0.405745102639737, -0.3874126855554356, -0.3734853799582511, -0.36454296027745653, -0.3610593090664775, -0.3633900549319635, -0.37176283294908485, -0.38627041801325335, -0.4068669137013835, -0.4333671066730501, -0.46544902119784476, -0.5026596318882316, -0.5444236170141754, -0.590054961726482, -0.6387711519066412, -0.689709636871955, -0.7419461843268002, -0.7945147051092489, -0.8464280895623579, -0.8966995726395807, -0.9443641317432669, -0.9884994201192995, -1.0282457494228936, -1.0628246575702807, -1.0915556316524013, -1.113870599689665, -1.1293258582790673, -1.1376111644269091, -1.1385557875782137, -1.132131390396103, -1.1184516824418655, -1.0977688677170114, -1.0704669831815459, -1.0370522990054172, -0.9981410206530787, -0.95444459626268, -0.9067529886282649, -0.8559163180787214, -0.8028253195437046, -0.7483910832238285, -0.6935245629279995, -0.6391163389755871, -0.5860171135476714, -0.5350193957628605, -0.48684080208781205, -0.44210935578022265, -0.4013511179632157, -0.36498042392965074, -0.3332929328498432, -0.3064616288394963, -0.28453583808323246, -0.2674432522220487, -0.25499487434519413, -0.24689273250389995, -0.24274013844673817, -0.24205420791656077, -0.24428030485019667, -0.24880802650118125, -0.25498831096107605, -0.2621512236388045, -0.2696239655560033, -0.27674864413479733, -0.28289935651022036, -0.28749815602202516, -0.290029503878592, -0.29005284922107505, -0.2872130308848764, -0.2812482517750794, -0.27199544047280744, -0.25939288285119366, -0.24348007737381577, -0.22439483958052128, -0.20236775221998157, -0.1777141257739018, -0.15082369801283266, -0.12214835911853544, -0.09218823934586202, -0.061476537910192613, -0.03056350372726787, -2.814391753231576e-16], [0.0, 0.02830756758755581, 0.055069630432630065, 0.07987288417523243, 0.10236913099678915, 0.12228592757450202, 0.13943513771552013, 0.15371915413980192, 0.16513461438814261, 0.17377350091445756, 0.17982158343143193, 0.18355423079361313, 0.18532968836771674, 0.1855799832143638, 0.1847996818025717, 0.18353278181013039, 0.1823580693796244, 0.18187331472582752, 0.18267871115658926, 0.18535998454075428, 0.19047161145232813, 0.19852058432874703, 0.20995115096897998, 0.22513093380929652, 0.2443388021688433, 0.26775482883205964, 0.2954526119500923, 0.327394185534636, 0.3634276782065727, 0.4032878119204925, 0.4465992617982735, 0.4928828267238133, 0.5415642897563743, 0.591985779473568, 0.6434193797565017, 0.6950826778748268, 0.7461558904699123, 0.7958001654416453, 0.8431766258777367, 0.88746570084455, 0.9278862776467165, 0.9637142113467196, 0.994299739921734, 1.019083377147959, 1.0376098895918493, 1.049540008140455, 1.0546595772643739, 1.0528859054052229, 1.0442711460579515, 1.0290026096702816, 1.007399979690216, 0.9799094801733135, 0.9470951155055765, 0.9096271732173639, 0.86826824683527, 0.8238570956263219, 0.7772907104629823, 0.7295049985925958, 0.6814545337604865, 0.6340918410827974, 0.5883466977265047, 0.5451059305389454, 0.5051941802702437, 0.46935607922542255, 0.43824025562169744, 0.41238553442682324, 0.392209652075907, 0.3780007424833369, 0.3699117856458723, 0.36795813948423056, 0.3720182021158762, 0.3818371772804826, 0.39703384196488484, 0.41711014418815184, 0.44146339213647784, 0.4694007350010561, 0.5001555824417836, 0.5329055648635935, 0.5667916017238945, 0.6009376207204581, 0.6344704575098555, 0.6665394638717868, 0.6963353619772533, 0.7231079033688599, 0.7461819228745286, 0.764971419145496, 0.7789913437877519, 0.7878668388807751, 0.791339726602193, 0.7892721231084785, 0.7816471200584724, 0.7685665494414661, 0.7502459188960857, 0.7270066737142246, 0.699266006516088, 0.6675244945667486, 0.6323518964379565, 0.594371482941095, 0.5542433109223119, 0.5126468718131943, 0.4702635592238514, 0.427759401076672, 0.3857684918146033, 0.34487753936232846, 0.30561191032842094, 0.26842351622464694, 0.23368083429467695, 0.20166130014802197, 0.1725462472239642, 0.14641850174432078, 0.12326267293556244, 0.1029681086527707, 0.08533441787954817, 0.07007939564148356, 0.056849124317489425, 0.04522996971269862, 0.034762141967077734, 0.024954451628213158, 0.01529986101157849, 0.00529141106279918, -0.005561905179897696, -0.017719749524644758, -0.03159594010470848, -0.04754523803898955, -0.06585177638400601, -0.08671944576979736, -0.11026450029176191, -0.13651058959347792, -0.16538636008087387, -0.19672570145020227, -0.23027064588154106, -0.2656768580897244, -0.30252158668934437, -0.3403138827391931, -0.37850683152636716, -0.4165114901550146, -0.45371217768629496, -0.48948272761046147, -0.523203285274289, -0.5542772162476186, -0.5821476859390946, -0.6063134762363575, -0.6263436214439906, -0.6418904729409081, -0.6527008391273268, -0.6586248934782806, -0.6596225977344851, -0.6557674481094389, -0.6472474183724491, -0.6343630431479086, -0.6175226560277144, -0.5972348683541833, -0.5740984440189401, -0.5487897916029075, -0.5220483560007639, -0.49466024580165896, -0.4674404787706727, -0.44121426462355107, -0.41679777096752124, -0.3949788341003985, -0.37649808089285625, -0.36203092107716073, -0.352170851064579, -0.347414481327284, -0.3481486600926703, -0.35464001754515145, -0.3670271980796488, -0.38531598477054274, -0.4093774516463026, -0.43894920726017456, -0.47363971917729863, -0.5129356351606671, -0.5562119448363043, -0.6027447572131979, -0.6517264063005612, -0.7022825407516864, -0.7534908053513186, -0.8044006834342129, -0.8540540409289812, -0.9015058953637121, -0.9458449272783419, -0.9862132572129645, -1.0218250286465203, -1.0519833655304733, -1.0760953117107883, -1.0936844076174739, -1.1044006159529745, -1.108027371354723, -1.1044855976014831, -1.0938346082056436, -1.076269880423075, -1.0521177670118158, -1.021827282672526, -0.9859591712426833, -0.9451725237145553, -0.9002092744541014, -0.8518769522297072, -0.8010301026317723, -0.7485508282212511, -0.6953289115840545, -0.6422419939549413, -0.5901362780545842, -0.539808208386346, -0.4919875558730124, -0.4473222970563017, -0.4063656320632653, -0.3695654313224097, -0.33725633994708615, -0.30965470231882464, -0.28685639935181795, -0.26883761894087477, -0.2554585079724953, -0.2464695837950934, -0.24152071593809826, -0.24017242679125328, -0.24190920442705263, -0.24615447312696304, -0.25228682861236545, -0.2596571164127724, -0.26760591390470234, -0.2754809697356167, -0.2826541587422564, -0.2885375259357165, -0.2925980192346252, -0.29437054669602764, -0.29346903908668187, -0.28959525159715777, -0.28254509797453425, -0.27221237482292865, -0.2585898016584641, -0.24176737178846724, -0.22192807845723378, -0.19934114821136611, -0.17435297738428174, -0.14737602637162658, -0.11887597848847056, -0.08935751435556571, -0.059349087847462435, -0.029387114770941764, -2.6951813940619065e-16], [0.0, 0.026891192960926857, 0.052105034202096015, 0.07527293638492909, 0.09609503732886558, 0.114349402383028, 0.1298990644889767, 0.1426967069256061, 0.15278685500290057, 0.16030550776267408, 0.16547720741032645, 0.1686096110525191, 0.17008569465590684, 0.17035378131257908, 0.1699156433176526, 0.16931297877024074, 0.16911260709206222, 0.16989076289686558, 0.17221689313293395, 0.17663737769304377, 0.18365959832967343, 0.19373677458238872, 0.20725396864354087, 0.22451563404934194, 0.24573504643540914, 0.2710259092303341, 0.3003963741889853, 0.3337456573929742, 0.3708633672331053, 0.41143159352591474, 0.4550297379763623, 0.5011419973973519, 0.5491673441503335, 0.5984317848540153, 0.6482026201102276, 0.6977043762839583, 0.746136036554723, 0.7926891636422599, 0.8365664816936031, 0.877000470450146, 0.9132715213818972, 0.9447252131013931, 0.9707882818982646, 0.9909828922439882, 1.0049388509220523, 1.0124034561157256, 1.013248728187237, 1.0074758306696556, 0.9952165566673631, 0.9767318258014648, 0.9524072083383657, 0.9227455644578028, 0.8883569560075433, 0.8499460538575512, 0.8082973244952117, 0.7642583333106555, 0.7187215477858634, 0.672605060397794, 0.626832677572685, 0.582313836830464, 0.5399238189418452, 0.5004847153651748, 0.46474759358960827, 0.4333762747114869, 0.4069330992983834, 0.38586701028107967, 0.37050422640972425, 0.361041718061478, 0.35754363039790243, 0.3599407286684373, 0.36803286855183626, 0.38149442257088473, 0.39988252355537646, 0.4226479195667433, 0.4491481732501787, 0.47866288373469124, 0.5104105622829104, 0.5435667550288747, 0.577282978238539, 0.6107060142428653, 0.6429971099247684, 0.6733506245143719, 0.7010116893140852, 0.7252924684176467, 0.7455866458276152, 0.7613818096940428, 0.7722694575534913, 0.7779524061121347, 0.7782494538011004, 0.7730972124278792, 0.7625490940648839, 0.7467715091268062, 0.7260373996679491, 0.7007172966017059, 0.671268149217466, 0.6382202285838038, 0.6021624518826576, 0.563726511314876, 0.5235702180731415, 0.4823604883582284, 0.4407564041429212, 0.3993927762572082, 0.3588646215422909, 0.31971293972932674, 0.28241214002704795, 0.2473594230737287, 0.21486637206122716, 0.18515294879568223, 0.15834402769745146, 0.13446853485387378, 0.11346119189025337, 0.0951667973186895, 0.07934691285402198, 0.06568876059335271, 0.05381608049029607, 0.04330164763672264, 0.03368110674644717, 0.024467747972838814, 0.015167824617755657, 0.005295999990071502, -0.0056094920231493555, -0.017972380139776454, -0.032164971659227035, -0.04849621185704395, -0.06720150974267428, -0.08843460713781359, -0.11226171490153118, -0.13865808119967513, -0.16750709348206677, -0.19860194989320737, -0.23164986887134054, -0.26627873938455293, -0.3020460502938329, -0.3384498773467815, -0.37494165181888406, -0.4109403872223521, -0.44584800101438193, -0.4790653378739998, -0.5100084806684673, -0.5381249252375598, -0.5629091958665549, -0.5839174898071607, -0.6007809611810355, -0.6132172865410003, -0.6210401954976988, -0.6241666991399878, -0.6226218052743867, -0.6165405713942272, -0.6061674122317616, -0.5918526471108656, -0.5740463414044288, -0.5532895644875514, -0.5302032519646931, -0.5054749209987073, -0.4798435427490546, -0.45408292384464854, -0.4289839882599735, -0.4053363809253082, -0.38390983410953905, -0.3654357465462394, -0.3505894231749084, -0.33997341025646854, -0.33410233678441714, -0.33338963910516817, -0.3381365022899944, -0.3485233001059031, -0.36460375666037337, -0.3863019883682403, -0.41341251637296594, -0.44560326861708216, -0.48242151912787645, -0.5233026415141316, -0.5675814858839514, -0.614506125052501, -0.6632536585644, -0.7129477131162629, -0.7626772366572585, -0.8115161517864293, -0.8585434128356451, -0.9028630007523988, -0.9436233908350259, -0.980036040507631, -1.0113924673623407, -1.037079521084357, -1.0565924957998138, -1.069545780802563, -1.0756808062718235, -1.0748711050586015, -1.06712438032415, -1.0525815400845817, -1.0315127318162733, -1.0043104814521375, -0.9714801096184524, -0.9336276621617359, -0.8914456503384729, -0.8456969470769263, -0.7971972282393112, -0.7467963807946488, -0.6953593224734058, -0.6437466892848958, -0.5927958479751171, -0.543302680097117, -0.49600456314277974, -0.4515649426933256, -0.4105598485874721, -0.37346665871406637, -0.34065535744881037, -0.3123824733860444, -0.28878781441956375, -0.26989404905574427, -0.25560911281172954, -0.2457313493930375, -0.23995722976479944, -0.23789142986746717, -0.23905899111139897, -0.24291923829952347, -0.2488810884772699, -0.2563193523883486, -0.2645916084838869, -0.27305521829809765, -0.28108405170859296, -0.2880845011152541, -0.2935103846006911, -0.29687636911818066, -0.2977695848827685, -0.29585915038419236, -0.29090338256168835, -0.2827545272761499, -0.27136090974539456, -0.2567664714386281, -0.2391077273664371, -0.21860824405021348, -0.19557080203706992, -0.1703674660418956, -0.14342783915793547, -0.11522582374071143, -0.08626524937908148, -0.05706475687494458, -0.02814234564754803, -2.570643896164852e-16], [0.0, 0.02544121773650384, 0.049099282869924175, 0.07065119592891003, 0.08984534513568802, 0.106509260112395, 0.1205551633434363, 0.13198316433414367, 0.1408820027562217, 0.14742731070873982, 0.15187742893173417, 0.1545668757468074, 0.15589762904252455, 0.1563284392077603, 0.1563624430773568, 0.1565333943602028, 0.15739086350716677, 0.15948478857974857, 0.16334977765631872, 0.16948957215860586, 0.17836207894742268, 0.19036536713436136, 0.20582500355630787, 0.2249830692867571, 0.24798915917757067, 0.27489361822457786, 0.30564321371556813, 0.3400793820034861, 0.37793912483956926, 0.418858564087365, 0.46237909696414325, 0.5079560283840258, 0.5549694941463266, 0.6027374301978408, 0.650530290469956, 0.6975871701810208, 0.7431329541579685, 0.7863960816227833, 0.8266265007362145, 0.86311337847532, 0.8952021343677056, 0.9223103801750582, 0.9439423715103427, 0.95970161102975, 0.9693012854627225, 0.9725722693090795, 0.9694684853212707, 0.9600694745143146, 0.9445800948841171, 0.9233273366485159, 0.8967543109796425, 0.8654115371810007, 0.8299457184140758, 0.7910862568010383, 0.7496298135323369, 0.7064232671447747, 0.6623454622376215, 0.6182881705979915, 0.5751367062781333, 0.5337506451202406, 0.494945097332589, 0.4594729690234157, 0.4280086253996485, 0.40113333519754213, 0.379322833635723, 0.36293729079628684, 0.3522139150728932, 0.3472623585708751, 0.3480630246318962, 0.3544683086092877, 0.36620673332107356, 0.382889871951675, 0.40402188522950894, 0.42901143807734216, 0.45718570510928197, 0.48780612568264115, 0.520085528877656, 0.5532062177400797, 0.5863385811190754, 0.6186597909554853, 0.6493721431550271, 0.6777206111833632, 0.7030092029485002, 0.7246157428377191, 0.7420047411562131, 0.7547380616563478, 0.762483153136295, 0.7650186718453004, 0.7622373861481225, 0.7541463219672699, 0.7408641752777727, 0.7226160847013519, 0.6997259213889984, 0.6726063133160444, 0.641746675372441, 0.6076995638880169, 0.5710657133394155, 0.5324781429988436, 0.4925857414892935, 0.4520367471367409, 0.4114625414441064, 0.37146216200321447, 0.3325879200187966, 0.29533247690374465, 0.2601176949163406, 0.22728552956452844, 0.19709117770783915, 0.16969863631413704, 0.14517876417309616, 0.12350987411768448, 0.10458081809550065, 0.08819646340890247, 0.07408539721958911, 0.06190963953030781, 0.05127609374310573, 0.04174941983295109, 0.03286597927169818, 0.024148473988139792, 0.01512088452457364, 0.005323305572909448, -0.0056737195878931385, -0.018255750667956126, -0.03275224943242613, -0.049425955017301626, -0.06846412309312143, -0.08997186791087497, -0.11396779153038261, -0.14038202501366992, -0.1690567435724525, -0.19974915318093536, -0.2321368816374314, -0.26582564411785153, -0.30035899350952117, -0.33522991076492764, -0.36989394157495764, -0.40378354408110734, -0.4363232791935419, -0.4669454512140023, -0.4951057925045645, -0.520298782272339, -0.5420721962759784, -0.5600405012610549, -0.573896734798869, -0.5834225472901157, -0.5884961273217069, -0.5890977832422138, -0.5853130114753194, -0.5773329442958851, -0.565452135007267, -0.5500637050605648, -0.5316519439873357, -0.5107825174208401, -0.4880904993451369, -0.46426650050879537, -0.44004121426554166, -0.4161687427103943, -0.39340909880804176, -0.372510303417255, -0.35419050909425015, -0.3391205849546473, -0.3279075885945735, -0.32107953228709496, -0.3190718218110167, -0.32221570801550387, -0.3307290444895362, -0.34470959061437084, -0.36413103913803146, -0.3888418826826198, -0.4185671658529038, -0.4529131005096813, -0.49137445299161053, -0.5333445452966792, -0.5781276491044061, -0.6249534935801973, -0.6729935565760293, -0.7213787653887551, -0.7692181987281653, -0.8156183568331306, -0.8597025523675257, -0.9006299711856248, -0.9376139593731166, -0.9699391109728288, -0.9969767590600397, -1.018198510655862, -1.0331875124398762, -1.0416471882137783, -1.043407249262061, -1.0384268436872375, -1.0267947788844638, -1.0087268209055305, -0.9845601438513849, -0.9547450699378879, -0.91983430486121, -0.8804699319948893, -0.8373684813535023, -0.7913044338931167, -0.7430925575126239, -0.6935694972177172, -0.6435750576948567, -0.5939336216541709, -0.545436141638944, -0.4988231267306123, -0.4547690191288924, -0.41386831963225945, -0.3766237764933592, -0.3434369000956093, -0.31460100769178767, -0.290296939513029, -0.2705915214609998, -0.2554387819758871, -0.24468386320043217, -0.2380695009009736, -0.23524488537680002, -0.2357766583170327, -0.2391617496512922, -0.2448417151272961, -0.25221820068440665, -0.26066913450895085, -0.26956523254930914, -0.2782863985785679, -0.2862376057023767, -0.29286386233978645, -0.2976638917190012, -0.3002021891457699, -0.30011916480907036, -0.2971391305708766, -0.2910759457508981, -0.28183619792531533, -0.2694198586639653, -0.2539184193166999, -0.2355105767805162, -0.2144556020002652, -0.19108458319551141, -0.16578978997462604, -0.13901245223406958, -0.11122928784885082, -0.08293814463513569, -0.054643144121947505, -0.026839726757521276, -2.4418114816993406e-16], [0.0, 0.02396907605358364, 0.046075227430963345, 0.06604132020383767, 0.0836633302807918, 0.09881666314760448, 0.11146025760714354, 0.12163835737803108, 0.12947989517648176, 0.1351954961738282, 0.13907216991414023, 0.1414658203137886, 0.1427917607099343, 0.14351347361888706, 0.144129901564766, 0.14516159484996, 0.14713607344689086, 0.15057278248583086, 0.155968033511676, 0.1637803264395149, 0.17441643985953298, 0.18821866018295974, 0.20545349348721717, 0.22630216845328777, 0.2508531953572201, 0.2790971957474778, 0.3109241614521945, 0.34612324130109906, 0.38438509091141915, 0.42530675664362105, 0.468399000983097, 0.5130959147435205, 0.5587666031660926, 0.6047286796714643, 0.6502632540516089, 0.6946310624566484, 0.7370893556412674, 0.7769091403819769, 0.8133923573252577, 0.845888577098697, 0.8738108053811994, 0.8966500065983033, 0.9139879845483738, 0.9255082958988793, 0.9310049182195879, 0.930388446940321, 0.9236896540592897, 0.9110603041652264, 0.8927711888452937, 0.8692074072331584, 0.8408609866782364, 0.8083210016673041, 0.772261409631439, 0.733426877640226, 0.6926169228610445, 0.6506687308415869, 0.6084390481436005, 0.5667855688129672, 0.5265482470457119, 0.4885309708784335, 0.45348402372644897, 0.4220877423018188, 0.3949377513064483, 0.37253211799377955, 0.3552607241321026, 0.34339710019081093, 0.33709290799117525, 0.33637519504130864, 0.34114647784567564, 0.3511876442476061, 0.36616359796490544, 0.38563150354054915, 0.4090514285301885, 0.43579912337516313, 0.4651806294289636, 0.4964483632230796, 0.5288182912942145, 0.5614877855550239, 0.5936537348490797, 0.6245304843153803, 0.6533671805721338, 0.6794641173320107, 0.7021877024485891, 0.7209837028941597, 0.7353884678863657, 0.745037881219704, 0.7496738505479034, 0.7491482024938958, 0.7434239165177783, 0.732573695863286, 0.7167759390139589, 0.6963082383156282, 0.6715385922069237, 0.6429145723774553, 0.6109507358024638, 0.5762146127993658, 0.5393116350190625, 0.5008693908381635, 0.46152160940313697, 0.42189227828361936, 0.38258029326136034, 0.34414502240728667, 0.307093140723672, 0.27186705692872554, 0.23883521133346944, 0.20828447429824004, 0.18041481971966464, 0.15533638878697492, 0.13306899735922398, 0.11354407731705615, 0.09660897972396462, 0.08203350716781876, 0.06951848576517539, 0.05870613542808479, 0.049191951417580246, 0.04053777208165607, 0.032285677951603996, 0.023972346790065404, 0.015143478257422415, 0.005367900857108764, -0.005749017247938372, -0.018553013319412903, -0.03332996293731673, -0.05029659623260771, -0.06959314901648864, -0.09127814991584197, -0.11532548897891058, -0.14162385378314057, -0.16997855736461165, -0.20011571986022478, -0.23168870419355211, -0.2642866470058407, -0.29744487083820065, -0.3306569137150716, -0.36338786903512366, -0.3950886931517991, -0.42521111113658744, -0.453222733663247, -0.47862199019618396, -0.5009524859313508, -0.5198164021924842, -0.5348865819476464, -0.5459169732552192, -0.5527511430181653, -0.5553286204510934, -0.5536888829887806, -0.5479728556693437, -0.5384218568652016, -0.5253739870736563, -0.5092580217264535, -0.490584932030509, -0.4699372181323645, -0.447956294895097, -0.4253282208790689, -0.4027681044568901, -0.3810035562674589, -0.36075758352150483, -0.34273133832925784, -0.3275871387851747, -0.3159321778195072, -0.30830332087073775, -0.3051533695585098, -0.3068391353014076, -0.31361162501807405, -0.325608591676994, -0.34284964671176443, -0.3652340705461997, -0.3925413931546817, -0.4244347502852182, -0.46046695431440565, -0.5000891533148512, -0.5426618893981044, -0.5874683092823465, -0.6337292277511624, -0.680619699502573, -0.7272867179486746, -0.7728676317269191, -0.8165088517124196, -0.8573844136248288, -0.8947139640991719, -0.9277797512780718, -0.9559422242674349, -0.9786538786170677, -0.9954710265454173, -1.0060632199142199, -1.010220109774954, -1.007855587296022, -0.9990091155526586, -0.9838442284459579, -0.9626442402877402, -0.935805275707703, -0.9038267929013869, -0.8672998323036181, -0.8268932761108141, -0.7833384503969032, -0.7374124397555254, -0.6899205135400632, -0.6416780821705459, -0.593492611180439, -0.5461459194852386, -0.500377276823145, -0.4568676937538334, -0.416225766559249, -0.37897539965666505, -0.3455456807080149, -0.3162631296771997, -0.2913464839931218, -0.27090411918930085, -0.25493413946819155, -0.2433271071858973, -0.23587131588666982, -0.2322604498217973, -0.23210341537987444, -0.23493607794353805, -0.24023459263817817, -0.24742998034444585, -0.2559235721021248, -0.265102926309785, -0.2743578143561668, -0.28309587169017897, -0.29075752277888806, -0.29682980959804783, -0.30085878368629726, -0.302460160582803, -0.3013279816610105, -0.2972410807879203, -0.2900672105446074, -0.2797647434859942, -0.2663819265586693, -0.250053729752731, -0.23099639174964862, -0.209499824189699, -0.18591809073972257, -0.16065822602460184, -0.13416770146845874, -0.10692087912319838, -0.07940481979286747, -0.05210482756476324, -0.02549011884251869, -2.309731784318247e-16], [0.0, 0.02248605946609083, 0.04305510595381898, 0.06147557213102018, 0.077589809276013, 0.09131900474736397, 0.10266589469968658, 0.11171519336432026, 0.11863171977558344, 0.12365626295539137, 0.12709928574559745, 0.12933262419573888, 0.13077939223190518, 0.13190234890507613, 0.13319102663001745, 0.13514795242537647, 0.1382743193863981, 0.1430554818076054, 0.1499466540939424, 0.1593591906624834, 0.17164781149229627, 0.1870991161180735, 0.2059216982086367, 0.22823813417072397, 0.25407907342095554, 0.2833796062035631, 0.3159780283789844, 0.35161706286937927, 0.3899475359071984, 0.43053444442612837, 0.47286529040406705, 0.5163605002309533, 0.5603856936798108, 0.6042655191545712, 0.6472987307843117, 0.6887741496756146, 0.7279871270752009, 0.7642561119724768, 0.7969389201945164, 0.8254483064821209, 0.8492664553076216, 0.8679580299821645, 0.8811814523454393, 0.8886981262548597, 0.8903793662111065, 0.8862108466103339, 0.8762944459867618, 0.86084742277073, 0.8401989230208756, 0.8147838847331796, 0.7851344661146159, 0.7518691850966945, 0.7156800128847353, 0.6773177141282576, 0.6375757691311177, 0.597273248341313, 0.5572370353092009, 0.5182838107356894, 0.48120221673782476, 0.4467356168702353, 0.4155658538362507, 0.38829838352705703, 0.36544913160267584, 0.3474333780609275, 0.3345569271196582, 0.3270097654335908, 0.3248623525015192, 0.3280646245322214, 0.3364477285518619, 0.34972843872088744, 0.36751614326093635, 0.38932222961685864, 0.4145716389708468, 0.44261631035433596, 0.47275019059875456, 0.5042254502887176, 0.5362695185957554, 0.5681025320249754, 0.5989547841171126, 0.6280837651868365, 0.6547903931719771, 0.6784340582992184, 0.6984461349858143, 0.7143416534173445, 0.7257288695888112, 0.7323165251126402, 0.7339186454744534, 0.7304567862311973, 0.7219596993894712, 0.7085604553238679, 0.6904911175386588, 0.6680751268168763, 0.6417176063845831, 0.611893849296945, 0.5791362921180946, 0.5440203140794806, 0.507149227416765, 0.469138841874339, 0.43060199403063204, 0.3921334299784326, 0.35429541807810416, 0.31760444731473014, 0.2825193367928496, 0.2494310438727949, 0.21865441336807226, 0.19042205923526948, 0.16488051459344416, 0.14208872711836942, 0.1220189163555513, 0.10455974881168316, 0.08952172734652496, 0.07664463488911344, 0.06560682026327411, 0.056036067238323155, 0.047521747990578934, 0.03962792996817553, 0.031907081498330644, 0.023914006949728082, 0.015219637219977003, 0.005424305877126726, -0.0058298446789377505, -0.01884765951721399, -0.03387127074492495, -0.05107216175975676, -0.07054521149120412, -0.09230488228352672, -0.11628365918348865, -0.1423327896882465, -0.1702253129711615, -0.1996613077588263, -0.23027522990030766, -0.2616451557264485, -0.293303696941074, -0.32475030830094376, -0.3554646718647004, -0.3849208120854554, -0.41260157525018626, -0.43801309527657306, -0.4606988659766423, -0.4802530476584954, -0.4963326531919783, -0.5086682850023594, -0.5170731292402779, -0.5214499557560055, -0.5217959214389148, -0.5182050287604865, -0.510868149636331, -0.5000705855520097, -0.486187196764228, -0.4696751947495531, -0.45106475139244084, -0.4309476341958259, -0.40996412765802553, -0.3887885456059648, -0.3681136765750266, -0.34863453332844896, -0.33103179756616075, -0.31595536125923035, -0.3040083665725008, -0.2957321369591671, -0.2915923729266343, -0.29196695762321545, -0.29713568045018773, -0.30727214224730576, -0.3224380543080417, -0.34258008679527374, -0.3675293614259621, -0.39700362005288314, -0.43061203653635693, -0.46786257563947, -0.5081717411554467, -0.5508764975941349, -0.5952480969372016, -0.6405074955173697, -0.6858420071296245, -0.7304228080032219, -0.7734228880065178, -0.8140350309512746, -0.8514894053993834, -0.8850703559973827, -0.9141320038701897, -0.9381122925503877, -0.9565451526273369, -0.9690705028805162, -0.9754418570307063, -0.9755313621510293, -0.9693321558427662, -0.9569579930118118, -0.9386401579296201, -0.91472174164989, -0.8856494272136373, -0.8519629838959424, -0.8142827256008944, -0.7732952360933688, -0.7297377039183575, -0.684381241635451, -0.6380135866286822, -0.5914215937069954, -0.5453739326929027, -0.5006043971564622, -0.45779621358496664, -0.417567714022818, -0.38045970023897646, -0.34692478466146215, -0.31731894373203934, -0.29189546421609963, -0.27080140372343653, -0.25407662472537473, -0.24165539822611565, -0.23337051052024446, -0.22895974568937522, -0.22807455915296893, -0.23029070509678004, -0.23512053423936882, -0.24202663928997567, -0.2504364945447228, -0.2597577141015712, -0.26939354066315385, -0.27875817411968934, -0.2872915560978843, -0.29447324321923757, -0.29983502748741125, -0.30297199634831873, -0.3035517666574873, -0.30132167497939927, -0.296113760104872, -0.2878474310475967, -0.27652977361689174, -0.26225350944860065, -0.24519268157695787, -0.22559619873110223, -0.2037794250799495, -0.1801140517589646, -0.15501652994820472, -0.12893538144585195, -0.10233773069203977, -0.07569542134700454, -0.0494710903420475, -0.024104572563324062, -2.1754546616233328e-16], [0.0, 0.021003180515095428, 0.04006028219161341, 0.05698445210565296, 0.07166268911909286, 0.08405940678974078, 0.0942178263216305, 0.10225915647898015, 0.10837957517507571, 0.11284508493423409, 0.11598437015156313, 0.1181798366253871, 0.1198570618736942, 0.12147292704399408, 0.12350273670393797, 0.12642666054673182, 0.13071585034292577, 0.13681859581222464, 0.14514688419356103, 0.15606372010848052, 0.16987154502473759, 0.1868020696455619, 0.20700779850581355, 0.230555484783018, 0.2574217058455947, 0.287490697536634, 0.3205545289319568, 0.35631564071475885, 0.3943917108360784, 0.43432275226601397, 0.4755802908584735, 0.517578418077151, 0.5596864649031044, 0.6012430008878984, 0.6415708271056012, 0.6799926045917869, 0.7158467414399469, 0.7485031525418414, 0.7773785062667858, 0.8019505821995008, 0.8217713831851929, 0.8364786729214572, 0.8458056465268547, 0.8495884850390498, 0.8477715946017881, 0.8404103859833097, 0.8276715086949685, 0.8098305149192481, 0.7872669902227936, 0.7604572491115413, 0.7299647523848621, 0.6964284585187279, 0.6605493715959515, 0.6230755923672133, 0.5847862157833397, 0.546474446879205, 0.5089303265049447, 0.47292346860161233, 0.43918621124693885, 0.4083975745302833, 0.38116839966944366, 0.3580280161035254, 0.3394127472542025, 0.32565652211663376, 0.31698380987815306, 0.31350503958258497, 0.31521460780303884, 0.32199151579329843, 0.3336026151536955, 0.3497083791902297, 0.3698710573693328, 0.3935650140268469, 0.4201890011425444, 0.44908006978389514, 0.4795287868460917, 0.5107953938825031, 0.5421265238430526, 0.572772079911389, 0.602001878619545, 0.6291216670482728, 0.6534881409837802, 0.6745226169562417, 0.6917230454717208, 0.704674094602472, 0.7130550813742905, 0.7166455818811959, 0.715328608438249, 0.7090913019309748, 0.6980231483546807, 0.6823117888580629, 0.6622365509277353, 0.6381598832413664, 0.6105169268327327, 0.5798034993291699, 0.546562806068994, 0.511371220989693, 0.4748235006026723, 0.43751780565960413, 0.40004090701927447, 0.36295394472673936, 0.3267790926370217, 0.2919874555000395, 0.25898849193551643, 0.2281212160294864, 0.19964738341925523, 0.17374681589476623, 0.15051496304668577, 0.12996274173957248, 0.11201863564065076, 0.09653297916653822, 0.0832842944780226, 0.07198749795691607, 0.06230374524857001, 0.053851642634832005, 0.04621951824791937, 0.03897842030005341, 0.031695491740839965, 0.023947362002129904, 0.015333196959206458, 0.005487057906084538, -0.005910761041677345, -0.01912372061927342, -0.034350617801843765, -0.051718987801860086, -0.07128050598658349, -0.09300851682674655, -0.11679776148976034, -0.14246631830343312, -0.16975971249519464, -0.19835709482454297, -0.2278793344152487, -0.2578988206396866, -0.28795072359563667, -0.3175454237028424, -0.3461817892320481, -0.37336095698034966, -0.3986002564374619, -0.421446912043399, -0.4414911616857999, -0.45837844235822756, -0.4718203156011253, -0.4816038354520363, -0.4875990994067279, -0.4897647674100357, -0.4881513840557141, -0.48290239373617044, -0.47425279609065496, -0.46252544832038467, -0.4481250802937007, -0.4315301463697839, -0.41328269307190907, -0.3939764727536111, -0.37424357893749766, -0.3547399179141884, -0.3361298624775478, -0.31907045653867844, -0.3041955532089158, -0.2921002733977736, -0.2833261668936438, -0.27834744337738465, -0.27755861718980224, -0.28126387748767456, -0.2896684554462627, -0.30287221336014297, -0.3208656279900794, -0.3435282835756908, -0.37062992996749994, -0.4018340997904331, -0.4367042169383473, -0.4747120685240377, -0.5152484551469655, -0.5576357813976781, -0.6011423011953679, -0.6449976920189205, -0.6884095993421953, -0.7305807684319006, -0.770726365711262, -0.8080910865103422, -0.8419656503553249, -0.8717022988974287, -0.8967289348150331, -0.9165615719798381, -0.9308148070859832, -0.9392100698310425, -0.9415814614704427, -0.9378790488592375, -0.9281695415535426, -0.9126343416969799, -0.891565018753237, -0.8653563221484112, -0.8344969030740398, -0.7995579706611906, -0.76118015616028, -0.7200589004796208, -0.6769287144426822, -0.6325466866049125, -0.5876756298204675, -0.5430672645871545, -0.49944583437812295, -0.4574925357822651, -0.4178311246478959, -0.3810150291081361, -0.34751626212703707, -0.31771638100091265, -0.29189969020797163, -0.2702488283908025, -0.252842821460211, -0.23965762328073717, -0.23056910463289373, -0.22535839164260457, -0.22371939808750402, -0.22526834332544704, -0.22955500033031911, -0.2360753776149003, -0.24428550565584098, -0.25361597360835475, -0.2634868461956086, -0.27332258404478843, -0.2825665935513751, -0.29069504448339833, -0.29722961465492553, -0.3017488505457491, -0.303897869956614, -0.30339617671072433, -0.3000434069217835, -0.293722880188045, -0.28440288587652046, -0.27213569299575835, -0.2570543305478005, -0.2393672422296463, -0.21935097348894764, -0.19734109886868986, -0.17372164204967822, -0.14891327890475484, -0.12336064426840786, -0.09751908524333079, -0.07184121716380122, -0.04676364248923939, -0.022694187815095433, -2.0400191725891347e-16], [0.0, 0.019531041661630843, 0.03711099861013011, 0.05259635673429918, 0.06591655909829033, 0.07707627685756153, 0.08615556684643114, 0.09330790615208927, 0.09875614948627691, 0.1027865095596554, 0.10574071257344515, 0.10800652904815666, 0.11000692328485148, 0.11218810170058309, 0.11500677014985987, 0.11891693236851793, 0.12435657528209029, 0.1317345917453272, 0.14141828718088403, 0.15372180364526, 0.16889577337288403, 0.18711848435368214, 0.20848880370644388, 0.23302106142509513, 0.2606420485647103, 0.291190231301433, 0.3244172268536475, 0.3599915303722205, 0.39750442501555067, 0.4364779519442142, 0.47637476429172715, 0.5166096406172714, 0.5565623901481188, 0.5955918453686069, 0.6330506081454683, 0.6683001943514958, 0.7007262094157096, 0.7297531837287713, 0.7548587024843498, 0.7755864792310021, 0.7915580458111998, 0.8024827629245324, 0.8081658945180447, 0.8085145346407645, 0.8035412262027539, 0.7933651660178723, 0.7782109482458751, 0.7584048574741673, 0.7343687817464072, 0.7066118734072492, 0.6757201402773766, 0.6423442000579864, 0.6071854757489101, 0.5709811481432048, 0.5344882121874107, 0.49846700640944464, 0.46366459815680827, 0.4307984117152144, 0.40054048137606246, 0.37350269730327246, 0.35022338895429206, 0.33115555939308194, 0.31665704485446133, 0.3069828283251733, 0.3022796848048192, 0.30258328054201145, 0.3078177902544424, 0.31779803655404004, 0.3322340959642201, 0.3507382574902318, 0.37283416410518194, 0.3979679160929277, 0.4255208691905604, 0.4548238210098365, 0.48517224723948504, 0.515842225405214, 0.5461066690547246, 0.5752514894871642, 0.6025913056815694, 0.62748433578953, 0.649346125111866, 0.6676617953282986, 0.6819965371413846, 0.6920041124953532, 0.6974331820400869, 0.6981313273001826, 0.6940466937453095, 0.6852272392379186, 0.6718176307192469, 0.6540538890467699, 0.6322559362139037, 0.6068182494347889, 0.5781988715358397, 0.5469070656677208, 0.5134899336034345, 0.478518340071, 0.44257250013515687, 0.406227592259519, 0.3700397562394205, 0.33453282281273894, 0.30018610076997476, 0.26742351834785955, 0.23660437935459672, 0.20801595177145277, 0.18186805859403105, 0.15828978863589843, 0.13732839023511736, 0.11895035466448226, 0.10304463996430907, 0.08942793130374216, 0.07785178220500605, 0.06801143333356693, 0.059556063258695564, 0.052100189680843886, 0.04523591099997367, 0.03854565747383225, 0.03161510909659664, 0.024045934011273144, 0.015468006827030817, 0.005550780495074841, -0.005986491966028116, -0.019365959192429807, -0.03474403252983749, -0.05220609884739851, -0.07176322913434169, -0.09335097478558466, -0.11683028897243344, -0.14199055497484886, -0.16855464823149163, -0.19618590554243454, -0.22449682469226218, -0.25305927202488004, -0.28141593536199966, -0.30909272614137234, -0.33561180861919954, -0.3605049161073852, -0.3833266049695598, -0.4036670967331547, -0.42116436721843636, -0.43551515884573455, -0.4464846178464415, -0.45391429134989025, -0.45772825943129297, -0.4579372231963475, -0.45464042070737765, -0.44802529676467623, -0.4383649088959498, -0.4260131089713316, -0.41139759622485783, -0.3950109917136823, -0.3774001350210624, -0.35915385002939054, -0.3408894666917811, -0.3232384188961409, -0.30683126389555365, -0.2922824857160654, -0.2801754529984824, -0.2710479006552518, -0.265378294522963, -0.2635734190878004, -0.2659575007984776, -0.272763144112138, -0.2841243150910619, -0.30007155910311256, -0.3205295861465606, -0.3453173008100127, -0.3741502952685944, -0.4066457644402939, -0.44232974393265684, -0.480646515133769, -0.5209699691246311, -0.5626166733079347, -0.6048603429377865, -0.6469473851255535, -0.6881131562447326, -0.7275985556248812, -0.7646665694620884, -0.7986183792106933, -0.8288086583593787, -0.8546597002080085, -0.8756740466009103, -0.8914453228773364, -0.9016670267153203, -0.9061390670410373, -0.9047719025736968, -0.8975881865770479, -0.884721883606326, -0.8664148840332204, -0.8430112014422992, -0.8149488951786413, -0.7827499139995997, -0.7470081056418493, -0.7083756799755947, -0.667548449246368, -0.6252501968397316, -0.5822165453790017, -0.5391787053243369, -0.4968474863490609, -0.45589794561886277, -0.4169550299118144, -0.3805805427339314, -0.3472617338583755, -0.3174017678933243, -0.2913122815830917, -0.26920818773670085, -0.25120482824352675, -0.23731752094937988, -0.22746348665366925, -0.2214660845916063, -0.21906122890915314, -0.21990580619309588, -0.22358786636764555, -0.22963831737650228, -0.23754381905188685, -0.24676054427336708, -0.2567284565899375, -0.2668857433597671, -0.2766830423747781, -0.2855971078780577, -0.2931435786226607, -0.29888853571395235, -0.3024585707700547, -0.3035491245818702, -0.30193090194157335, -0.29745421847888986, -0.2900511889256838, -0.2797357218661796, -0.26660134231862803, -0.2508169190165168, -0.23262042661749072, -0.21231092292618028, -0.19023896632348816, -0.16679573782088639, -0.14240116452440246, -0.11749136599339124, -0.09250576140164335, -0.06787418314933412, -0.044004341449148596, -0.021269974457218586, -1.904440873366374e-16], [0.0, 0.018079711093681262, 0.03422614664471808, 0.04833726817973926, 0.06038232903736794, 0.07040292938550795, 0.07851203444071038, 0.08489097706534504, 0.089784518664339, 0.09349409322121786, 0.09636940710891113, 0.09879861076787191, 0.1011972963544062, 0.10399660705374547, 0.1076307681139514, 0.11252436615784613, 0.11907971153742725, 0.12766461818322564, 0.13860092655819828, 0.15215407815473447, 0.1685240248863761, 0.18783772433450063, 0.2101434329103862, 0.23540696454537835, 0.26351003362772085, 0.29425074877903, 0.3273462700047107, 0.36243758711032936, 0.39909632341696316, 0.4368334170832912, 0.47510948405080855, 0.5133466229885286, 0.5509413847292441, 0.58727859752447, 0.6217457157981681, 0.6537473445639499, 0.6827195846995784, 0.708143846048194, 0.7295597858231415, 0.7465770488015359, 0.758885512858728, 0.7662637778791652, 0.7685856771515787, 0.7658246370262246, 0.7580557617471075, 0.7454555747283117, 0.7282994037945919, 0.7069564546769357, 0.68188267295333, 0.6536115482820849, 0.622743064871263, 0.5899310474301942, 0.5558691912407762, 0.5212760974942167, 0.48687965985753634, 0.45340116474605374, 0.4215394755686425, 0.39195567008080695, 0.3652584899440727, 0.34199094288461096, 0.32261837091757184, 0.3075182636062978, 0.29697205409265176, 0.29115908866694096, 0.29015290908431923, 0.29391993193279553, 0.30232055245130096, 0.31511264266875383, 0.33195735698550227, 0.35242710372616587, 0.3760154900832489, 0.4021490014835722, 0.43020013586730493, 0.4595016796510041, 0.4893617860621136, 0.519079498705411, 0.5479603540714738, 0.5753316964292385, 0.6005573471474247, 0.6230512877327629, 0.6422900413154464, 0.6578234703113596, 0.6692837477197082, 0.6763923049826911, 0.6789646094103923, 0.6769126776177237, 0.6702452869087361, 0.6590659027073441, 0.6435683955887664, 0.6240306748497858, 0.600806415559233, 0.5743151014304447, 0.545030645548916, 0.5134688840089328, 0.4801742630679428, 0.4457060579092335, 0.41062447010595754, 0.37547695120832564, 0.34078509155218695, 0.30703239664786675, 0.27465324879854425, 0.24402331956053275, 0.2154516601179814, 0.18917465258628405, 0.1653519568023465, 0.14406453553378193, 0.12531478754787503, 0.10902876397368444, 0.09506039022645851, 0.0831975647784022, 0.07316995853286665, 0.06465829568049061, 0.05730485975754547, 0.05072493811549254, 0.044518894905073096, 0.038284547549680845, 0.031629514901665004, 0.024183207001588974, 0.01560813654016974, 0.005610250488717596, -0.0060519935564849504, -0.019560048644147864, -0.03502940035180897, -0.05250554775199308, -0.07196195332692948, -0.09330002025845394, -0.11635110254809825, -0.14088050026309712, -0.16659334020669822, -0.1931421927966776, -0.22013623016365405, -0.24715168961649403, -0.27374337170918306, -0.29945687407648053, -0.32384124170759615, -0.3464617019316662, -0.36691214842635816, -0.3848270431504573, -0.39989241814694254, -0.4118556803564299, -0.420533951408524, -0.42582071011462036, -0.4276905471890579, -0.4262018885420539, -0.4214975941556611, -0.4138033928125441, -0.40342416746854814, -0.39073816048150056, -0.37618922086735895, -0.36027726592143994, -0.34354717565410753, -0.3265763793825017, -0.30996142845534613, -0.2943038765827331, -0.28019580888865353, -0.268205372086009, -0.2588626607834145, -0.25264630877639765, -0.24997111937567287, -0.2511770457196551, -0.2565198011511407, -0.26616334184621615, -0.28017441987921005, -0.29851935585603273, -0.3210631273413709, -0.34757081383219246, -0.377711382345826, -0.41106374118260536, -0.4471249344761433, -0.48532029810765376, -0.5250153497141425, -0.5655291430422335, -0.6061487808381036, -0.6461447517116631, -0.6847867356831828, -0.7213595109310466, -0.7551785909185612, -0.7856052266780948, -0.8120604234450889, -0.8340376437196876, -0.8511138996391698, -0.8629589755249858, -0.8693425657033399, -0.8701391621135266, -0.8653305796127558, -0.8550060629614066, -0.8393599768647628, -0.8186871377604973, -0.7933759018822544, -0.7638991771419658, -0.7308035752706673, -0.6946969642545486, -0.6562347183459067, -0.616104992920139, -0.5750133734709348, -0.5336672615641526, -0.49276036529246087, -0.4529576575905248, -0.4148811528056738, -0.3790968305083321, -0.3461030062137418, -0.3163204122083486, -0.29008420894284975, -0.26763809953285667, -0.2491306679872759, -0.23461400714964842, -0.22404464633892193, -0.21728673269438825, -0.21411736564238798, -0.21423393205013372, -0.21726324178415, -0.22277222071528072, -0.23027988174609582, -0.23927026506090374, -0.24920601721669314, -0.25954226541371567, -0.2697404386080612, -0.27928169114237905, -0.28767959714539343, -0.2944918047438011, -0.29933036759574017, -0.3018705066570742, -0.30185759652316996, -0.2991122170935963, -0.29353316150744335, -0.28509834402240813, -0.27386360543030847, -0.25995946735688824, -0.24358593903272863, -0.2250055295333118, -0.20453466383115881, -0.18253374114694432, -0.15939610802717485, -0.1355362454680574, -0.11137748858151073, -0.0873396082874924, -0.06382658705084689, -0.04121491470771608, -0.019842716107259486, -1.7696995801236689e-16], [0.0, 0.01665860683072475, 0.03142305677696039, 0.044230477548482534, 0.05508691788053341, 0.06406727480880174, 0.07131327843928047, 0.07702958344631655, 0.08147806613146878, 0.08497047300313788, 0.08785961029375206, 0.09052930251066621, 0.09338338103137882, 0.09683399005996658, 0.10128951628205013, 0.1071424597949672, 0.11475756704813028, 0.12446054150855353, 0.13652763467647253, 0.1511763992269897, 0.16855785795225187, 0.18875030751420932, 0.21175493564577896, 0.23749338535823522, 0.2658073510447278, 0.2964602403259642, 0.32914088333818387, 0.3634692192198008, 0.3990038391133786, 0.43525121733123445, 0.4716764186368077, 0.5077150309746027, 0.5427860404195962, 0.5763053394445805, 0.6076995414834944, 0.636419764676799, 0.6619550458993332, 0.6838450527643751, 0.7016917761346358, 0.7151699084118701, 0.7240356429854296, 0.7281336669766759, 0.7274021619350385, 0.7218756743927328, 0.7116857690199498, 0.6970594303010993, 0.6783152328758019, 0.655857354627935, 0.6301675589389918, 0.6017953219624717, 0.5713463261072164, 0.5394695810220234, 0.5068434672607112, 0.4741610246369004, 0.4421148263838144, 0.411381791138258, 0.3826082871918222, 0.3563958773264304, 0.3332880380150992, 0.3137581641680394, 0.2981991404823996, 0.28691472353922987, 0.2801129359780048, 0.27790162640678084, 0.280286297332977, 0.2871702495749399, 0.2983570366467441, 0.313555167834712, 0.33238494543531866, 0.354387271194083, 0.37903421059743486, 0.40574106244858643, 0.43387964610061397, 0.46279249067021205, 0.49180759018613807, 0.5202533764205436, 0.5474735573919155, 0.5728414742901281, 0.5957736427234391, 0.6157421653840304, 0.6322857319365497, 0.6450189574322804, 0.6536398519541856, 0.6579352604754142, 0.6577841619180994, 0.6531587688933267, 0.6441234232907052, 0.6308313364442814, 0.6135192747135253, 0.592500340705485, 0.5681550458185656, 0.5409209102013275, 0.5112808606100029, 0.47975072418618825, 0.4468661362030565, 0.4131691918740443, 0.3791951761106795, 0.3454597005903112, 0.31244656479082317, 0.2805966371120215, 0.25029802437051296, 0.22187776354516742, 0.1955952295448962, 0.17163740799063415, 0.15011613368497195, 0.1310673448077715, 0.11445235120171093, 0.10016106369898661, 0.08801708158147774, 0.07778448821230154, 0.06917616180537883, 0.06186337028805564, 0.05548638720809614, 0.04966584043645247, 0.04401448764510522, 0.03814910263155732, 0.031702154756641676, 0.024332970094489183, 0.015738077192382176, 0.005660462232939175, -0.0061025126802244515, -0.019692739168233872, -0.03518671058676203, -0.052592713844916476, -0.07184994226777981, -0.09282955652785642, -0.11533766973684763, -0.13912018242384763, -0.16386934460837274, -0.18923187673979472, -0.2148184400751976, -0.24021421115584018, -0.26499028533658153, -0.2887156115856935, -0.3109691455927066, -0.3313519009982517, -0.34949857949145935, -0.3650884696019268, -0.377855321034226, -0.387595925943318, -0.39417717002928526, -0.3975413539647441, -0.3977096285276325, -0.3947834338325933, -0.3889438830662736, -0.38044908288878954, -0.3696294348721975, -0.3568810137000598, -0.34265716706132887, -0.3274585279990011, -0.31182167176282205, -0.2963066849199495, -0.28148394368867663, -0.26792042042843933, -0.25616585137309245, -0.2467391046554662, -0.24011508526361575, -0.23671250282444278, -0.23688280926656946, -0.2409005869108926, -0.24895563400403953, -0.2611469549521568, -0.2774788174908153, -0.29785898983407477, -0.3220992186797334, -0.34991795508209356, -0.3809452809560095, -0.41472993567605976, -0.4507482911911312, -0.4884150765424928, -0.5270956098235113, -0.5661192585088554, -0.6047938186282013, -0.6424204802197638, -0.6783090314467193, -0.7117929470742227, -0.7422440088603032, -0.769086115775763, -0.7918079605927636, -0.8099742758231752, -0.8232353856081818, -0.8313348401462677, -0.834114954627742, -0.8315201243180113, -0.8235978401916615, -0.8104973840820128, -0.7924662373494603, -0.769844291248349, -0.7430559991699252, -0.712600659495369, -0.6790410617306644, -0.6429907668502722, -0.6051003244258769, -0.5660427533989312, -0.5264986296915669, -0.48714113185591534, -0.44862139545719915, -0.4115545179009028, -0.37650653818646984, -0.34398269103894474, -0.31441720266638606, -0.2881648568202783, -0.2654945158598185, -0.24658473323056468, -0.2315215423599309, -0.22029845371697523, -0.21281863799546083, -0.20889922038125824, -0.20827755995951494, -0.21061934075092206, -0.21552825780171453, -0.22255704423689704, -0.23121955412890946, -0.241003592180929, -0.2513841651413207, -0.26183682192564034, -0.27185074979402424, -0.28094130257723116, -0.288661653620718, -0.29461329038030404, -0.2984550988249377, -0.29991082317915674, -0.29877472911608965, -0.29491534520913776, -0.2882772070843103, -0.2788805800319926, -0.2668191875433907, -0.2522560240325138, -0.23541737861382742, -0.21658524201028095, -0.1960883093350665, -0.17429182660770606, -0.15158655755614114, -0.12837716880915614, -0.10507034546581391, -0.08206295490209801, -0.059730574402800225, -0.03841668785720714, -0.018422838601824913, -1.6367277411403843e-16], [0.0, 0.015276390442690474, 0.02871731077278387, 0.0402963453344223, 0.05005299590065651, 0.05809157982931345, 0.06457829546537476, 0.06973652905163726, 0.07384052353128526, 0.07720757271786265, 0.0801889432733099, 0.08315976077977744, 0.08650812405053356, 0.0906237329840844, 0.09588632917618746, 0.1026542548011209, 0.11125343378181904, 0.1219670700093552, 0.1350263405620891, 0.1506023379199889, 0.1687994846566614, 0.18965060777256898, 0.21311381860686426, 0.23907129915604694, 0.267330047758295, 0.2976245876673302, 0.32962159227509774, 0.3629263318953644, 0.39709080031723576, 0.4316233359544894, 0.4659995134491352, 0.4996740480238132, 0.53209342757313, 0.5627089671406529, 0.590989967576149, 0.6164366551520651, 0.6385925818904636, 0.657056177265102, 0.6714911605544449, 0.6816355489951178, 0.6873090294059242, 0.688418499338422, 0.6849616271329202, 0.6770283274663544, 0.6648000989206144, 0.6485472215564231, 0.6286238641892128, 0.6054612017612666, 0.5795586916431691, 0.5514737026853391, 0.5218097312679667, 0.4912034734665497, 0.46031105089684904, 0.429793709120771, 0.400303321150547, 0.3724680342375042, 0.34687839562431333, 0.3240742823265667, 0.3045329415401584, 0.2886584223873038, 0.2767726470399753, 0.2691083305857636, 0.26580391526525093, 0.2669006369740539, 0.2723417913466427, 0.2819742145525211, 0.2955519414072197, 0.3127419518078435, 0.3331318670992624, 0.3562394119621126, 0.38152341590339695, 0.40839609242973895, 0.43623630436132704, 0.4644035012136257, 0.4922519996717812, 0.5191452712595304, 0.5444699025146769, 0.5676489022811612, 0.5881540478699736, 0.6055169863912636, 0.6193388389012211, 0.6292980923562917, 0.6351566067949372, 0.6367636116208426, 0.634057614191491, 0.6270661949042521, 0.615903714361751, 0.6007670087254235, 0.5819291977906438, 0.5597317754532234, 0.5345751929836446, 0.5069081808914095, 0.47721608429189305, 0.4460085088830249, 0.4138065893731678, 0.38113019913533125, 0.34848541885093587, 0.3163525730013105, 0.2851751265152433, 0.25534971012424657, 0.2272175126300983, 0.20105724213073348, 0.1770798172030897, 0.15542490414719465, 0.13615936879081134, 0.11927766223983438, 0.10470411057322812, 0.09229703006390218, 0.08185454327340247, 0.07312192847652063, 0.06580029639420598, 0.05955635510932117, 0.05403299713338342, 0.048860422550303484, 0.04366749947877832, 0.03809305807642953, 0.03179681707096704, 0.02446965226569005, 0.015842934353988626, 0.005696688228912674, -0.0061336428469810425, -0.019752008134729836, -0.035198273988707354, -0.05244655585917606, -0.07140540421760626, -0.0919198424198062, -0.1137752060688619, -0.13670268623907866, -0.16038643417281345, -0.18447204390233385, -0.20857619272706632, -0.23229718852504422, -0.2552261482889152, -0.27695851468492133, -0.29710560729576135, -0.3153059027962314, -0.3312357437009481, -0.34461918839729205, -0.35523673562163305, -0.362932683854929, -0.3676209196335927, -0.36928896766492486, -0.3680001789389614, -0.3638939796635314, -0.3571841526542232, -0.34815517256681056, -0.3371566658210069, -0.32459611399060584, -0.3109299646209115, -0.2966533547406851, -0.2822886887173943, -0.26837334263666934, -0.2554467912883492, -0.2440374704944029, -0.23464969647922865, -0.22775096501129638, -0.22375994608419764, -0.2230354751004858, -0.22586681921348634, -0.23246546819754796, -0.2429586636568036, -0.2573848394039878, -0.27569110043752826, -0.2977328192216689, -0.3232753771195544, -0.3519980270867526, -0.38349980237051245, -0.41730734623885946, -0.452884490906176, -0.48964337098211397, -0.5269568190058016, -0.5641717588711869, -0.6006232879895755, -0.63564912149381, -0.6686040621052283, -0.6988741577079193, -0.7258902152540163, -0.7491403542086628, -0.7681813049869368, -0.7826481872029395, -0.7922625383339338, -0.7968384047330432, -0.7962863527997354, -0.7906153074235643, -0.7799321763550763, -0.7644392716751887, -0.7444295917539381, -0.7202800777419298, -0.692443006492779, -0.6614357257108385, -0.6278289759920467, -0.5922340773365781, -0.5552892838672159, -0.5176456292599629, -0.4799525963378259, -0.442843947142323, -0.406924044525157, -0.3727549830399522, -0.3408448260018831, -0.3116372175496539, -0.2855026040919354, -0.26273125950770543, -0.24352826389131438, -0.22801053759271506, -0.21620598198897625, -0.20805472707621156, -0.2034124348556523, -0.20205555785966722, -0.203688405239654, -0.20795182576506854, -0.21443327891080763, -0.22267803286473306, -0.23220120254792584, -0.24250032222162402, -0.25306813639059095, -0.2634052897461386, -0.273032601869508, -0.28150262518703584, -0.2884102048881733, -0.29340178665704186, -0.29618325142802887, -0.29652609510234745, -0.29427181427035454, -0.2893344053809443, -0.2817009333121113, -0.2714301747027906, -0.2586493904622975, -0.2435493293482492, -0.22637760920661473, -0.20743066328000184, -0.1870444748931207, -0.16558435392313978, -0.1434340320098639, -0.12098436987428329, -0.0986219789921107, -0.07671806099932199, -0.05561776157230782, -0.035630321304380964, -0.017020284662138358, -1.5063995523025341e-16], [0.0, 0.01394087157888465, 0.026122578148348383, 0.03655210147727283, 0.045298783162516475, 0.05249230105842002, 0.05831893572633484, 0.0630162229883281, 0.06686613105094914, 0.07018693954734813, 0.07332403223884064, 0.07663984414237356, 0.08050322676489736, 0.08527851133922396, 0.09131455904645902, 0.09893408893422682, 0.10842356853936261, 0.12002393922685602, 0.13392242827551512, 0.1502456732629722, 0.16905435198009347, 0.1903394737372415, 0.21402044643980253, 0.23994498924056334, 0.26789091403378323, 0.2975697517037288, 0.32863215206518276, 0.3606749410143298, 0.39324967568835173, 0.4258724994891466, 0.4580350646470015, 0.48921626145349234, 0.5188944711106478, 0.5465600439000524, 0.5717276964742654, 0.5939485217353816, 0.6128213120259867, 0.6280029110619366, 0.6392173318451139, 0.6462634061915196, 0.6490207658154353, 0.6474539942958875, 0.6416148327618848, 0.6316423687085487, 0.6177611858601751, 0.600277502241468, 0.5795733723971737, 0.5560990768148799, 0.5303638658964654, 0.5029252661988262, 0.4743771921267885, 0.44533713593269436, 0.4164327320209862, 0.3882880075948476, 0.3615096402115538, 0.33667354361381047, 0.31431209624522105, 0.294902312298773, 0.2788552333338564, 0.2665067899538577, 0.25811034845195835, 0.2538311175450124, 0.2537425462893658, 0.2578247970775942, 0.26596532839825954, 0.27796157199846266, 0.2935256394377943, 0.31229094496907056, 0.33382058639319645, 0.3576172841118707, 0.3831346420463167, 0.40978946328706706, 0.43697482903131946, 0.4640736321334207, 0.4904722468493429, 0.5155740143224378, 0.5388122290709556, 0.5596623250431186, 0.5776529803627356, 0.5923758871790618, 0.6034939663766686, 0.6107478454641202, 0.6139604607874437, 0.6130396912455778, 0.6079789787831029, 0.5988559399150724, 0.5858290211944785, 0.5691322986703611, 0.5490685658490468, 0.5260008953764276, 0.5003428956145239, 0.47254791361954157, 0.44309746001087125, 0.41248914827959865, 0.38122445082239337, 0.34979657618608384, 0.31867876664095485, 0.28831330242629377, 0.2591014791728158, 0.23139479862126328, 0.20548758050437457, 0.18161116616473785, 0.15992984309208602, 0.14053857512847936, 0.12346257673076896, 0.10865872256461445, 0.09601873701763951, 0.08537406313253361, 0.07650226810343905, 0.06913480390968861, 0.06296590784218367, 0.057662399450979035, 0.05287410850796837, 0.04824465347699905, 0.04342228208397345, 0.03807048506877527, 0.031878101080491876, 0.024568644762748316, 0.015908611001285714, 0.005714535533531239, -0.006141375046192869, -0.019727193248810764, -0.03504890856686547, -0.052049817035603116, -0.07061168043449367, -0.09055762679500697, -0.1116567182906996, -0.13363006885404455, -0.15615835310253515, -0.17889051140169698, -0.20145342408181174, -0.22346230177149132, -0.24453151918366406, -0.26428560699577464, -0.2823701110397807, -0.298462030010218, -0.3122795522750254, -0.3235908289132296, -0.3322215434048216, -0.33806106788958745, -0.3410670308653079, -0.3412681607452505, -0.3387653128570838, -0.333730633164623, -0.3264048590888868, -0.31709280511728494, -0.30615712723286603, -0.294010504404781, -0.2811064163423396, -0.2679287333930002, -0.25498036592837325, -0.24277124600887917, -0.23180593289205292, -0.2225711455612314, -0.21552352958701573, -0.21107796216512184, -0.2095966881611051, -0.21137956168249772, -0.21665564252098654, -0.2255763653614457, -0.2382104626974195, -0.2545407808184658, -0.2744630830541016, -0.2977868867735943, -0.3242383316161104, -0.35346502726278795, -0.38504278096773936, -0.418484059221164, -0.45324799545391997, -0.488751717656619, -0.5243827371182171, -0.5595121129990452, -0.5935080878005147, -0.6257498764706748, -0.6556412872040799, -0.6826238550820902, -0.706189180490829, -0.7258901824952317, -0.7413510026024112, -0.7522753260076295, -0.7584529247156617, -0.7597642689651805, -0.7561830991336498, -0.7477768986534585, -0.734705258251379, -0.7172161718225801, -0.6956403532519244, -0.6703837103084205, -0.6419181552268564, -0.6107709706989305, -0.5775129837779588, -0.5427458278404548, -0.5070885935801073, -0.47116418353757006, -0.43558569057507296, -0.40094311885790623, -0.36779075636467234, -0.3366354909632437, -0.30792633809024816, -0.28204541766073254, -0.259300581770157, -0.2399198539292036, -0.22404779600503735, -0.21174387183230342, -0.20298282776841187, -0.19765706149956985, -0.195580902360118, -0.19649668048622757, -0.20008241940982202, -0.20596094825147337, -0.2137101964259642, -0.22287440653455268, -0.2329759805365632, -0.24352766085628302, -0.2540447420975376, -0.26405701063065773, -0.27312011841908124, -0.2808261138137631, -0.28681287523105176, -0.2907722230429389, -0.2924565198934683, -0.29168360912233715, -0.2883399840252324, -0.2823821262214059, -0.2738359982839026, -0.2627947228368351, -0.2494145263553874, -0.23390906976387207, -0.21654232851752334, -0.19762022116111208, -0.17748121647707615, -0.15648617449455432, -0.1350076952060381, -0.11341926037397923, -0.09208445802681975, -0.07134657604801095, -0.05151884074455732, -0.03287555871959381, -0.01564439621962, -1.3795209405752813e-16], [0.0, 0.01265892436779199, 0.023650478631931173, 0.033011687111856716, 0.04083790619353218, 0.047279993416877844, 0.052539899842719937, 0.056864800273030584, 0.06053991434653666, 0.06388020610172085, 0.06722117940964749, 0.07090901096805394, 0.07529028069233142, 0.08070157086912465, 0.087459210051068, 0.095849435237139, 0.10611923644986417, 0.11846813161183739, 0.13304109703403624, 0.14992285041250097, 0.16913364969055064, 0.19062673331312596, 0.21428748621948326, 0.23993437241750015, 0.2673216302446268, 0.29614368156752097, 0.326041162330272, 0.3566084401326376, 0.3874024459571766, 0.4179526127431834, 0.44777168410030543, 0.4763671328169981, 0.5032529115578667, 0.5279612477114696, 0.5500541910294069, 0.569134626595545, 0.5848564767089187, 0.5969338332056177, 0.6051487861625634, 0.6093577452368185, 0.609496085368079, 0.6055809883499922, 0.5977123948904373, 0.5860720271799088, 0.570920488560171, 0.5525924934907147, 0.53149032650363, 0.5080756720989881, 0.4828599974963581, 0.45639370583675626, 0.4292543079399506, 0.4020338853073355, 0.37532613510753327, 0.3497132989375539, 0.3257532809345506, 0.30396725721825774, 0.28482806774896846, 0.26874966374654097, 0.2560778592613374, 0.24708260490957426, 0.24195196592254828, 0.24078794638074352, 0.2436042577873583, 0.2503260840433641, 0.2607918475380256, 0.2747569336159616, 0.2918992842777874, 0.3118267277437994, 0.3340858695329273, 0.35817233397637177, 0.38354211348626555, 0.4096237571977685, 0.4358311114162373, 0.46157631208771693, 0.48628272455770577, 0.509397528298456, 0.5304036539968799, 0.5488307971521272, 0.5642652557108238, 0.5763583686829674, 0.5848333674001317, 0.5894904902377562, 0.5902102542555465, 0.5869548222610629, 0.5797674501606738, 0.5687700459884346, 0.5541589175543651, 0.536198829112832, 0.5152155277568856, 0.49158693641329365, 0.46573324146771183, 0.4381061284379635, 0.4091774381280506, 0.3794275278878055, 0.3493336276944563, 0.319358478661148, 0.28993953234060693, 0.2614789730837192, 0.2343348031567618, 0.20881320190087455, 0.18516233666120796, 0.16356776537532752, 0.14414952955029015, 0.12696099291528792, 0.1119894364068364, 0.09915837544847546, 0.08833152184858065, 0.07931827115128395, 0.07188055797408242, 0.06574088770708493, 0.06059132378330787, 0.05610318628063366, 0.051937200463135415, 0.047753823432712936, 0.04322347359238531, 0.038036391195745166, 0.031911868771478225, 0.02460660739142149, 0.01592197815188879, 0.005709997261132017, -0.00612214297013735, -0.019609107016758064, -0.03472609171276882, -0.051389180331348414, -0.06945736708491346, -0.08873620024695894, -0.10898294968947897, -0.12991316460407876, -0.15120845054903057, -0.172525262671187, -0.19350448481502144, -0.21378154294588286, -0.2329967864289457, -0.25080586260677784, -0.2668898090239687, -0.2809645935980175, -0.2927898458955538, -0.3021765421320432, -0.30899343209513813, -0.3131720272659394, -0.31471000520889625, -0.31367292493025634, -0.3101941903795152, -0.30447324352767025, -0.2967720133928324, -0.28740969187138127, -0.2767559501535817, -0.26522274977559185, -0.25325493896782403, -0.24131985697486705, -0.22989619562913322, -0.21946238797660372, -0.21048480764615343, -0.2034060695552065, -0.1986337222581915, -0.19652961475288258, -0.19740020602451813, -0.20148806436506025, -0.20896477605853941, -0.21992545003145172, -0.23438496732666306, -0.2522760826864019, -0.27344944113757574, -0.29767552634542255, -0.324648510768923, -0.35399193146021957, -0.3852660708359971, -0.41797688000748184, -0.45158624431746025, -0.48552335753521203, -0.5191969435264813, -0.5520080428327648, -0.5833630669969142, -0.6126868160291425, -0.6394351543123469, -0.663107047511934, -0.6832556775158452, -0.6994983737417185, -0.7115251267984071, -0.7191054838110066, -0.7220936629054434, -0.7204317664744017, -0.7141510178880764, -0.7033709931763683, -0.6882968667545685, -0.6692147373364916, -0.64648514563327, -0.6205349381684779, -0.5918476705137976, -0.560952777519303, -0.5284137668499722, -0.4948157146521131, -0.46075235792047453, -0.42681308674524066, -0.3935701408894706, -0.36156630906400655, -0.33130341599025986, -0.3032318622101665, -0.2777414551230697, -0.2551537375625194, -0.23571598317182912, -0.21959698681413342, -0.20688473427544923, -0.197585989672929, -0.19162779239456063, -0.1888608092162708, -0.18906444260070263, -0.1919535541715406, -0.19718662400362155, -0.20437513260511012, -0.21309392411118702, -0.2228922869409609, -0.23330547252036662, -0.24386636400827008, -0.25411700547151334, -0.2636197076496777, -0.2719674591656409, -0.27879339143365917, -0.2837790710873085, -0.28666142483723756, -0.2872381374797492, -0.2853714034018484, -0.28098995436397456, -0.27408933051716006, -0.264730406414835, -0.25303622808539256, -0.23918725992897333, -0.22341518022218335, -0.20599540035795635, -0.1872385147087859, -0.167480914390585, -0.1470748185681034, -0.12637799077989859, -0.1057434147345816, -0.08550920397669683, -0.06598901275316985, -0.047463201519106636, -0.03017099016583313, -0.014303805757722055, -1.2568205290437762e-16], [0.0, 0.01143641660225258, 0.021310472072603375, 0.029685639579628817, 0.036679314115255705, 0.04245929378051047, 0.04723882549677317, 0.05127034479741985, 0.0548380737461284, 0.05824967125265698, 0.06182715534342635, 0.06589733664547635, 0.07078201595119415, 0.07678820589345549, 0.0841986372842254, 0.09326280452882721, 0.10418879186522871, 0.11713610329923528, 0.13220969447552286, 0.14945537494934477, 0.16885671514303194, 0.19033355453545467, 0.21374216728251574, 0.23887709951090627, 0.2654746500163468, 0.29321792409798164, 0.3217433498284676, 0.35064850821368343, 0.3795010943934426, 0.4078487971454151, 0.4352298592406777, 0.46118406229567627, 0.48526386716329617, 0.507045434940894, 0.5261392545168034, 0.542200110231498, 0.5549361375285091, 0.5641167350813563, 0.5695791283168279, 0.5712334108772131, 0.5690659266099245, 0.563140894266632, 0.5536002192702163, 0.5406614806353909, 0.5246141253362063, 0.5058139460153118, 0.484675959853217, 0.46166584562763335, 0.43729013152498875, 0.4120853572391335, 0.38660645953744477, 0.36141465015333174, 0.3370650680833823, 0.31409449479217805, 0.2930094202893157, 0.2742747405435877, 0.25830335241126284, 0.24544689151842697, 0.23598783184910682, 0.2301331337953822, 0.22800959089717443, 0.2296609853237148, 0.2350471193011254, 0.24404474521223846, 0.25645037206679755, 0.27198488155717954, 0.29029984405789544, 0.3109853847375922, 0.33357941340550185, 0.3575779996964047, 0.38244664848353654, 0.40763220964196395, 0.4325751419636236, 0.4567218434894039, 0.4795367599464315, 0.5005139893625674, 0.5191881141069065, 0.5351440112400374, 0.5480254176586845, 0.5575420574475239, 0.5634751743386938, 0.565681351347694, 0.5640945415354027, 0.5587262774069663, 0.5496640706271976, 0.5370680574237876, 0.5211659871929252, 0.5022466913860628, 0.4806522057765344, 0.4567687508050991, 0.4310168011198681, 0.40384049602392985, 0.37569665683416303, 0.347043684805297, 0.31833061411750374, 0.2899865884662669, 0.2624110172010412, 0.235964648070017, 0.2109617689332761, 0.1876637209403486, 0.16627387139247984, 0.1469341566946681, 0.12972326540412088, 0.11465648941876501, 0.10168722887749361, 0.09071009442910558, 0.081565510219511, 0.07404568325465066, 0.06790177066036622, 0.06285204662998711, 0.05859084626375216, 0.05479804466919532, 0.051148817070928644, 0.04732341957780868, 0.043016730817048696, 0.037947301842603184, 0.03186567536647816, 0.02456175509194785, 0.01587103123956868, 0.005679498602800566, -0.006072862121415517, -0.019390131286423713, -0.03422007706943716, -0.05045537226479346, -0.06793636969898885, -0.08645536406598146, -0.1057622290081152, -0.1255712821158787, -0.14556919810837454, -0.1654237626117869, -0.18479323638681636, -0.20333608314695806, -0.22072080368969552, -0.2366356152062494, -0.250797717451608, -0.262961896886664, -0.272928235723314, -0.28054871462544184, -0.28573252510638736, -0.28844993974125444, -0.2887346243833368, -0.28668431573945985, -0.2824598289413986, -0.2762824021170077, -0.2684294273533647, -0.25922865879049417, -0.2490510278472666, -0.23830223177001505, -0.22741329389286483, -0.21683032138812014, -0.20700370816460614, -0.19837704637680642, -0.1913760193230816, -0.18639755108291206, -0.1837994839837789, -0.18389104398035322, -0.1869243365222064, -0.19308709189322684, -0.20249684989005284, -0.21519673976995163, -0.2311529734633892, -0.2502541290364108, -0.2723122583042287, -0.2970658083947181, -0.3241843030206578, -0.35327468632499376, -0.3838891914703465, -0.4155345586561727, -0.4476823938913002, -0.4797804314522817, -0.5112644402251639, -0.5415704976274519, -0.5701473449535823, -0.5964685350338557, -0.6200440871269198, -0.6404313748921132, -0.6572449908532199, -0.6701653545496792, -0.6789458610024328, -0.683418400488062, -0.6834971190840241, -0.6791803310862463, -0.6705505381967329, -0.6577725552688161, -0.641089787289983, -0.6208187460856411, -0.5973419368772205, -0.5710992833132399, -0.5425782939788031, -0.5123032028444804, -0.4808233399282999, -0.4487010060414385, -0.4164991364492042, -0.384769042346697, -0.3540385161348928, -0.3248005766713241, -0.2975031142118535, -0.27253967207131147, -0.2502415736781453, -0.23087157038704353, -0.21461914796982798, -0.20159758905478595, -0.19184284593167936, -0.1853142341393959, -0.1818969131877247, -0.18140607771545503, -0.18359274140814333, -0.18815095809142912, -0.19472629050282686, -0.2029253081488723, -0.21232587207697484, -0.22248794689591989, -0.232964669377448, -0.2433133987137775, -0.253106476074625, -0.26194143041519224, -0.2694503832793026, -0.2753084272048363, -0.2792407797070934, -0.28102854698925545, -0.280512967689434, -0.2775980462046981, -0.27225152644360334, -0.26450419920953433, -0.25444757874349894, -0.24223002519541695, -0.22805142891512745, -0.2121566084810324, -0.1948276064174109, -0.1763750937946061, -0.1571291166843756, -0.13742943321886214, -0.1176156993903993, -0.09801776450612097, -0.0789463333179961, -0.060684241395066105, -0.04347857356472359, -0.027533832656255405, -0.013006337911899837, -1.1389416848591106e-16], [0.0, 0.010278152468058733, 0.019109776913471967, 0.026581021752875876, 0.032827254777938054, 0.038028979466888206, 0.04240646212668423, 0.04621321116852675, 0.04972848009973195, 0.05324899172939796, 0.057080101971910935, 0.06152663695540974, 0.0668836465058267, 0.07342732023472073, 0.08140630932046276, 0.0910336877054134, 0.10247977106131444, 0.11586599087723312, 0.13125999491709386, 0.14867211472431552, 0.16805330657967377, 0.18929463519978174, 0.21222833042503564, 0.23663040716491307, 0.26222479894800915, 0.28868891656758794, 0.31566050649952265, 0.34274564992818374, 0.36952771320463457, 0.39557703514426484, 0.4204611163985958, 0.4437550617300289, 0.46505201775786276, 0.48397334685596455, 0.50017828243596, 0.5133728217537382, 0.5233176293824394, 0.5298347472009611, 0.5328129346101057, 0.5322114950365044, 0.5280624808325517, 0.5204712075506719, 0.509615049312546, 0.4957405286104604, 0.4791587553471285, 0.46023931022214576, 0.43940270571461787, 0.417111592950681, 0.3938609138146913, 0.3701672239930677, 0.3465574335747493, 0.3235572268483278, 0.30167943165406563, 0.2814126108444701, 0.2632101440148385, 0.247480056781878, 0.23457583777005955, 0.2247884605208587, 0.21833979932168196, 0.21537759514091187, 0.2159720912478514, 0.22011441857958525, 0.22771676945054534, 0.23861435579260892, 0.2525691057947152, 0.269275011610007, 0.2883650017166506, 0.3094191755050117, 0.3319742055924626, 0.3555336860148602, 0.37957918247140826, 0.40358172473624915, 0.42701347157919706, 0.4493592752889043, 0.4701278762335916, 0.48886246773486514, 0.5051503876175959, 0.5186317147286793, 0.5290065759427434, 0.5360410010168039, 0.5395711983299957, 0.5395061631670132, 0.5358285708224113, 0.5285939484174534, 0.5179281609092063, 0.5040232873131879, 0.487132001663896, 0.4675606087622152, 0.4456609164405859, 0.4218211531482641, 0.3964561614678819, 0.3699971142002359, 0.34288100952043077, 0.3155402051921654, 0.2883922488636033, 0.2618302521536218, 0.23621404082404876, 0.21186229222574515, 0.18904584494832066, 0.1679823348661549, 0.14883227733845392, 0.13169667805978577, 0.11661621591013842, 0.10357200110507288, 0.09248787200266624, 0.08323415508556964, 0.0756327758749733, 0.0694635747660705, 0.06447165184268097, 0.06037553937530883, 0.056875980559451554, 0.05366507860519839, 0.05043557189703586, 0.04688998880378947, 0.042749439874938365, 0.037761815495004326, 0.031709173311026954, 0.024414121479573215, 0.01574503044190739, 0.005619936847736878, -0.005990962378337567, -0.019064290872357784, -0.03352397500393661, -0.04924321454517389, -0.06604789004714781, -0.08372131750737029, -0.10201022555806982, -0.12063179822514097, -0.13928159812025767, -0.15764216145293206, -0.17539203808599793, -0.19221503747439903, -0.20780943504551475, -0.22189689356843495, -0.23423086033080234, -0.24460421334830837, -0.2528559480722721, -0.2588767196865634, -0.262613084512005, -0.264070316558314, -0.2633137110707043, -0.2604683251166, -0.2557171448921061, -0.24929770950469957, -0.24149726050172288, -0.2326465243694933, -0.22311227066777645, -0.21328882049259312, -0.2035887077634627, -0.19443271869977521, -0.18623955219683824, -0.17941535518354484, -0.1743433921365223, -0.17137410659160912, -0.1708158247435999, -0.17292633722989034, -0.17790557527888692, -0.1858895720434074, -0.19694586974240677, -0.21107049893204585, -0.2281866186534253, -0.24814486627596616, -0.2707254245493465, -0.2956417717060441, -0.32254603944477106, -0.3510358642821852, -0.38066258105661893, -0.41094057421023356, -0.441357573686572, -0.47138565857399356, -0.5004927135934514, -0.5281540716242271, -0.5538640699863918, -0.5771472492993852, -0.5975689313961513, -0.6147449268151397, -0.6283501424844945, -0.6381258858718472, -0.643885692480407, -0.64551953838692, -0.6429963376954851, -0.6363646653964425, -0.6257516881848426, -0.611360328285928, -0.5934647272226166, -0.5724041167240752, -0.5485752416367924, -0.5224235138458218, -0.4944331060162125, -0.4651162187017556, -0.4350017734435835, -0.4046237974369217, -0.3745097718732716, -0.3451692160177205, -0.3170827724684387, -0.29069204604059945, -0.26639042964868, -0.2445151259069032, -0.22534054354117422, -0.20907321384212638, -0.19584833512561398, -0.18572801342399195, -0.17870122638824446, -0.17468549565163435, -0.17353021171457048, -0.1750215157669398, -0.17888860573718246, -0.18481130015177896, -0.19242866392317973, -0.20134847567055614, -0.21115729720427998, -0.2214308928216051, -0.2317447393681918, -0.24168436776206254, -0.2508552828375719, -0.2588922207723232, -0.2654675216800464, -0.2702984187118441, -0.2731530735971489, -0.27385522124562656, -0.2722873219932957, -0.26839215840142944, -0.26217285323989936, -0.2536913254088663, -0.2430652400677786, -0.23046354715931214, -0.2161007378907302, -0.20022998068427994, -0.18313532583702702, -0.1651231909515668, -0.1465133565489481, -0.12762971272878076, -0.10879100302229429, -0.09030181057084453, -0.0724440244921894, -0.05546901096413167, -0.039590694506412574, -0.02497973066718855, -0.01175892244124831, -1.0264357380419972e-16], [0.0, 0.00918782940933545, 0.017053318002497136, 0.02370139619084087, 0.029281310725896115, 0.03398210027266008, 0.03802693085825324, 0.04166644073879735, 0.045171270410276514, 0.04882397519432804, 0.05291053450217584, 0.05771168309047744, 0.06349429508012575, 0.07050305106606455, 0.0789526123043505, 0.08902051387188824, 0.1008409711491594, 0.11449977140909262, 0.1300303952650892, 0.14741148191021647, 0.16656571823611174, 0.18736019589977768, 0.20960824311090276, 0.23307270027699492, 0.2574705716141472, 0.2824789493401276, 0.30774207400952924, 0.33287936476485946, 0.3574942275196045, 0.3811834280175588, 0.4035468008696113, 0.4241970554681821, 0.44276943539438496, 0.45893098969092794, 0.4723892221518006, 0.48289989840538544, 0.49027380972246093, 0.4943823167084515, 0.49516152475714054, 0.49261497565524115, 0.48681477524256855, 0.4779011146839049, 0.4660801817741286, 0.45162049782403924, 0.4348477540984457, 0.4161382585537441, 0.3959111378416128, 0.3746194703620268, 0.3527405527983615, 0.330765524387014, 0.30918858961851525, 0.2884960907227568, 0.2691556858854794, 0.2516058875529603, 0.23624620743486302, 0.223428141090636, 0.2134472056085975, 0.20653621932375046, 0.2028599833627786, 0.20251149175794994, 0.20550976073682353, 0.21179932944884305, 0.2212514447646071, 0.23366690284198985, 0.2487804808663235, 0.26626685469456285, 0.2857478629812277, 0.30680094659055784, 0.3289685644751272, 0.35176836439501497, 0.3747038694135958, 0.39727542945487987, 0.4189911816193887, 0.43937776355867103, 0.4579905309786081, 0.47442304310344147, 0.48831559836418653, 0.49936262621611244, 0.5073187692528315, 0.5120035219687292, 0.5133043278318075, 0.5111780738943384, 0.5056509610643256, 0.4968167674306467, 0.48483356071556055, 0.46991895307306153, 0.4523440261530288, 0.43242608576415026, 0.4105204328308583, 0.387011359990394, 0.36230260057274355, 0.3368074684368436, 0.31093893293042985, 0.28509987297515943, 0.2596737479803887, 0.2350159111351832, 0.21144577294027425, 0.1892400000782959, 0.16862690746503503, 0.1497821702705085, 0.13282594863324226, 0.11782148157419177, 0.10477516916022558, 0.09363812421170323, 0.08430913774076723, 0.0766389667747299, 0.07043582014934009, 0.06547188807343783, 0.06149073550949281, 0.058215358321492675, 0.055356685232421064, 0.0526222982970925, 0.04972514008093816, 0.04639197714349921, 0.04237139671001283, 0.037441126381033, 0.03141448504138553, 0.024145796314613704, 0.01553462337395989, 0.005528714965054055, -0.005874413671630979, -0.018627305529123107, -0.03263379598239706, -0.047751623259065006, -0.06379634611748505, -0.0805464653653396, -0.0977496142347242, -0.11512965445201191, -0.13239449081995475, -0.1492443978789788, -0.16538063822802748, -0.18051414372387645, -0.19437402826160152, -0.20671570424083396, -0.21732838406670357, -0.22604176289803724, -0.23273169897382046, -0.2373247327249561, -0.23980131489445175, -0.24019764632280893, -0.23860606709711446, -0.23517396953571565, -0.23010124706401766, -0.22363632848738038, -0.21607088354228113, -0.2077333199898723, -0.19898122403763543, -0.1901929237356801, -0.18175837848450033, -0.17406961630860063, -0.16751095361571378, -0.16244923942970146, -0.15922436735549245, -0.15814029375428645, -0.15945678987475195, -0.16338213924725228, -0.17006696989165118, -0.1795993843362357, -0.19200151973706145, -0.20722763626927726, -0.2251637952664695, -0.24562915020802173, -0.26837883453866834, -0.2931083914097502, -0.319459652715462, -0.3470279391898636, -0.3753704207114981, -0.40401544713988047, -0.43247263569788397, -0.4602434817218587, -0.48683224600833275, -0.5117568643363773, -0.5345596232367105, -0.5548173507604266, -0.5721508817678544, -0.5862335738583272, -0.5967986720978723, -0.6036453476438207, -0.6066432665622744, -0.6057355798307037, -0.6009402628720062, -0.5923497720710672, -0.5801290256299392, -0.5645117558531756, -0.5457953185545953, -0.5243340818027465, -0.500531549787231, -0.47483140737735763, -0.44770769623652945, -0.4196543535388142, -0.39117435892261865, -0.36276874396143144, -0.33492572093071676, -0.3081101839511684, -0.2827538257914844, -0.2592460979682135, -0.23792622067816, -0.2190764230661929, -0.20291656401404554, -0.18960024978394982, -0.17921252830055479, -0.17176920150612263, -0.16721775802097033, -0.16543988924595446, -0.1662555140147301, -0.16942820087050328, -0.17467184388397494, -0.18165841845231637, -0.19002661843705518, -0.1993911559151877, -0.20935249021148947, -0.21950674409310553, -0.2294555622375072, -0.23881567037985757, -0.24722790280325643, -0.2543654808053397, -0.259941345065813, -0.26371436992933867, -0.26549431686605585, -0.2651454170351886, -0.26258850812979, -0.2578016876337878, -0.25081948234709256, -0.24173057158394995, -0.23067413788386423, -0.21783495348285742, -0.20343734231750965, -0.18773818519096439, -0.17101915922784716, -0.15357842130331886, -0.13572195829441178, -0.11775483444968718, -0.09997256773028637, -0.08265286261392445, -0.06604791669443616, -0.05037750271981442, -0.03582300689672833, -0.022522578883388388, -0.010567519544515194, -9.197564447401857e-17], [0.0, 0.008168009553076123, 0.015143704161384068, 0.02104684411171884, 0.026036494111439788, 0.030306181903937367, 0.03407806586720838, 0.037596266045596, 0.04111953522951013, 0.04491346435680716, 0.04924242920994884, 0.05436149279716245, 0.060508479738544944, 0.0678964353722067, 0.07670667323330906, 0.08708260025980398, 0.0991244898944364, 0.112885349658047, 0.12836800235089874, 0.14552346948008982, 0.1642507125755562, 0.18439775356911148, 0.20576416023525224, 0.22810484771279735, 0.2511351132232979, 0.27453678913091445, 0.2979653702578094, 0.3210579456210124, 0.3434417431476462, 0.3647430790099759, 0.3845964914386631, 0.40265383253360537, 0.41859309087361257, 0.43212672266620744, 0.4430092796735833, 0.4510441379585249, 0.45608915224059865, 0.4580610858404734, 0.45693869520987757, 0.45276438019111537, 0.44564434563898964, 0.43574725602544434, 0.4233014012504363, 0.40859042820162694, 0.3919477277457919, 0.3737495999290213, 0.35440735039234256, 0.3343584976248738, 0.3140572930162888, 0.2939647731766485, 0.27453857622488614, 0.2562227603968783, 0.23943786421614652, 0.2245714425722293, 0.2119693024730087, 0.2019276462267667, 0.1946863087499223, 0.19042325009388306, 0.1892504347576211, 0.19121119661644267, 0.19627915314599337, 0.20435869590742897, 0.21528704687700864, 0.22883783305991517, 0.24472609582691499, 0.26261461742865233, 0.282121416001558, 0.3028282328375074, 0.32428981241391697, 0.3460437572349578, 0.3676207263620501, 0.3885547389279058, 0.4083933421106896, 0.42670740702989174, 0.44310032570736035, 0.45721639737030684, 0.4687482125793612, 0.4774428684411734, 0.4831068768978039, 0.48560966006375844, 0.48488556101738545, 0.4809343344983959, 0.4738201187315945, 0.46366892618629474, 0.45066472659520806, 0.4350442291279744, 0.41709050142458853, 0.3971255904942276, 0.3755023336149662, 0.35259556577351725, 0.32879294342335935, 0.3044856121049144, 0.2800589475894669, 0.2558835966460935, 0.23230703439555964, 0.20964584075260065, 0.1881788790452145, 0.16814153603593185, 0.14972115486402685, 0.1330537615821977, 0.11822215275577402, 0.10525537686340626, 0.0941296068581524, 0.08477036610380254, 0.0770560358724676, 0.07082254052549386, 0.06586907719944805, 0.061964731010387866, 0.05885579511232852, 0.05627359793449682, 0.05394262799362304, 0.0515887401209555, 0.048947225912499205, 0.045770535719818845, 0.04183544942310053, 0.036949508307525664, 0.030956540208601557, 0.023741134192596332, 0.01523194877872837, 0.005403768383146205, -0.005721744509508009, -0.01807661979732909, -0.031548456590898714, -0.04598355601011848, -0.06119122666451031, -0.07694914879101045, -0.09300965519199464, -0.10910676290417855, -0.12496376955331165, -0.14030121312093313, -0.15484498375938954, -0.16833437160208478, -0.1805298353541044, -0.19122028280139558, -0.20022966609322929, -0.2074227114462813, -0.212709624374747, -0.21604963713713335, -0.2174532941697769, -0.21698340312401598, -0.2147546129419107, -0.2109316153471534, -0.2057260013163721, -0.19939183864651078, -0.19222006977573308, -0.1845318597137171, -0.17667105151447268, -0.16899591047957224, -0.16187035760438503, -0.15565490717641284, -0.1506975325266506, -0.14732468747702232, -0.1458327089119593, -0.14647981816325042, -0.14947892570748422, -0.1549914253436463, -0.16312214098205174, -0.17391556198980457, -0.18735347236155178, -0.20335404556452374, -0.2217724415603885, -0.24240290609930856, -0.26498233580792085, -0.28919523675279346, -0.3146799699379408, -0.34103614543481453, -0.36783299833224664, -0.39461855513977695, -0.4209293792924286, -0.44630066948825065, -0.47027647511826304, -0.4924197892647569, -0.5123222817518133, -0.5296134424929885, -0.5439689187155073, -0.5551178482315092, -0.5628490143288477, -0.5670156755025103, -0.5675389544741254, -0.5644097049944463, -0.5576888109657395, -0.5475059095821637, -0.5340565675632116, -0.5175979762394463, -0.4984432663492119, -0.4769545760668141, -0.45353503521353394, -0.42861985408890235, -0.40266672628383465, -0.3761457706942706, -0.349529248363337, -0.3232812944944063, -0.29784790488958907, -0.2736474092129154, -0.25106165103073813, -0.23042807685699918, -0.21203291386965956, -0.19610558912701795, -0.18281451266300563, -0.1722643135306854, -0.16449458251403554, -0.15948013870924113, -0.15713280038513958, -0.15730460436998053, -0.15979238356308245, -0.16434357988100268, -0.17066314080434564, -0.17842132239995737, -0.18726220086418255, -0.19681267876459968, -0.20669176162520822, -0.21651987554554422, -0.22592799727120644, -0.2345663745044436, -0.2421126260815788, -0.24827902863691656, -0.25281881808062984, -0.2555313600854474, -0.2562660731458721, -0.25492501990065636, -0.25146411648399936, -0.24589294483604557, -0.23827318827636476, -0.22871574533915676, -0.21737661001890438, -0.20445163735331784, -0.1901703409107655, -0.17478889256611643, -0.1585825143530482, -0.14183746669509797, -0.12484284658801091, -0.1078824131104298, -0.09122665589430284, -0.07512531494564205, -0.059800547663610336, -0.04544092138753305, -0.03219638775823641, -0.020174369176559834, -0.009437058341566313, -8.192557533740725e-17], [0.0, 0.007220105939881797, 0.013381235576858335, 0.01861402863121543, 0.023083398977903836, 0.026983497803041354, 0.030531832414938627, 0.0339626968559471, 0.03752008874969823, 0.04145030065150279, 0.04599438319243461, 0.05138068128550972, 0.05781764348783439, 0.06548709830772571, 0.07453817996187127, 0.08508207010133065, 0.09718770173197368, 0.11087854745902183, 0.12613058688726203, 0.14287151819015179, 0.16098124726877536, 0.18029365534757877, 0.20059961311619748, 0.22165117744934462, 0.24316687612851334, 0.2648379576239213, 0.28633545759186807, 0.30731791194816366, 0.3274395287503733, 0.3463586181153907, 0.36374607135503756, 0.37929367764879324, 0.3927220689785875, 0.403788091684094, 0.4122914156862032, 0.41808020987335687, 0.42105573393332973, 0.4211757225162962, 0.4184564664122685, 0.4129735267153046, 0.40486105096311614, 0.39430969417426126, 0.3815631817220349, 0.3669135842466902, 0.35069540649492287, 0.3332786213040273, 0.31506080619091414, 0.29645856251107094, 0.2778984153582624, 0.2598074058259396, 0.24260359560577258, 0.2266867069421001, 0.2124291186082233, 0.20016743086860206, 0.1901947995187951, 0.18275422135811845, 0.17803293127383854, 0.17615804503486543, 0.17719355253812694, 0.18113873433350533, 0.18792804054803952, 0.19743243665583354, 0.20946218573960526, 0.2237710028091921, 0.2400614842102582, 0.2579916849636726, 0.27718268975597193, 0.29722699991211005, 0.3176975395897531, 0.33815707010099333, 0.35816779203664656, 0.3773009109597038, 0.3951459439364917, 0.4113195510428956, 0.42547368804315794, 0.43730289338789124, 0.4465505440941791, 0.4530139404229578, 0.45654810793067946, 0.45706823673631936, 0.4545507109414144, 0.44903271525626354, 0.4406104401825084, 0.4294359407407879, 0.41571273588957197, 0.39969026567325916, 0.3816573500371065, 0.36193481650182574, 0.34086748294118485, 0.31881569609621835, 0.29614663585024703, 0.27322559946479114, 0.2504074788520234, 0.22802863758051006, 0.20639938285342632, 0.18579721146374154, 0.16646098813810276, 0.14858619025695344, 0.1323213253031729, 0.11776559724421157, 0.10496786615321524, 0.09392691252478964, 0.0845929847647192, 0.0768705760552402, 0.07062234602445472, 0.06567407414695288, 0.06182050628119032, 0.05883193384025431, 0.05646132733738707, 0.05445183288202126, 0.052544431946404645, 0.05048556157375434, 0.0480344942244819, 0.04497028359552408, 0.04109809480904109, 0.03625475403699801, 0.030313373478249715, 0.023186932100736583, 0.01483072007808385, 0.005243584686484956, -0.005532053174520528, -0.017411410512562262, -0.03026974839142275, -0.04394590802588485, -0.05824688257141227, -0.07295330319179825, -0.08782569392518465, -0.10261132952174792, -0.11705151431397609, -0.13088908871545546, -0.14387596342232947, -0.15578047998457206, -0.16639440016484006, -0.17553933532399757, -0.18307244074973697, -0.18889121804101, -0.19293729092496187, -0.19519904566066573, -0.19571305583192636, -0.19456424213338772, -0.19188474993852483, -0.18785156019709268, -0.1826828817196904, -0.1766334043493427, -0.16998852210059173, -0.16305766231675284, -0.15616688057058398, -0.1496509008085583, -0.14384479560605126, -0.13907551196096893, -0.13565345352642896, -0.1338643304150805, -0.13396148267467664, -0.13615887334375382, -0.14062493188338154, -0.14747740910443885, -0.15677938094240623, -0.16853651114844548, -0.18269565283026765, -0.19914483652476642, -0.21771465890644356, -0.23818105215555985, -0.2602693802662164, -0.28365977599907327, -0.3079936015807935, -0.3328808883802278, -0.35790858634149303, -0.3826494335349837, -0.4066712403095982, -0.42954637159238385, -0.45086120516417777, -0.4702253433923418, -0.48728036094337657, -0.5017078813158339, -0.5132367903845116, -0.5216494151638877, -0.5267865202005758, -0.5285510018068281, -0.5269101910766257, -0.5218967095373557, -0.5136078555842708, -0.5022035346885414, -0.4879027809155721, -0.47097895069846923, -0.4517537012698015, -0.4305898948987735, -0.4078835954126067, -0.38405534478616893, -0.35954092434733537, -0.33478181696309217, -0.3102155931605987, -0.28626644534364215, -0.2633360900659324, -0.24179524882839482, -0.22197590331756564, -0.20416450175992165, -0.1885962696101179, -0.17545075070044328, -0.16484867492328611, -0.15685021623877574, -0.15145467109023222, -0.14860155299857128, -0.148173065034807, -0.14999787887107735, -0.15385611799116108, -0.15948541415928708, -0.16658788109268385, -0.1748378280667478, -0.18389001941157368, -0.1933882739334498, -0.20297419149293447, -0.2122957924430377, -0.22101585939674726, -0.22881977974145376, -0.2354227012092976, -0.24057583128573884, -0.24407173381920608, -0.24574850230738082, -0.24549271831866912, -0.24324113462894784, -0.2389810551305353, -0.23274941658702628, -0.22463061003720616, -0.21475311127544566, -0.20328501956595713, -0.19042863084411732, -0.1764141954470268, -0.16149303030898943, -0.14593017106557743, -0.1299967602531177, -0.11396237350951, -0.09808748624450275, -0.08261627864973438, -0.06776996728737582, -0.05374083708385453, -0.04068712873452736, -0.028728913779347977, -0.017945063519997927, -0.008371389180695354, -7.251809163146941e-17], [0.0, 0.006344383630324685, 0.011763940722871716, 0.01639630119328049, 0.020408408655858076, 0.02399140557359874, 0.027354815908589212, 0.030720180071214756, 0.03431431157844219, 0.03836235511237032, 0.043080831355118435, 0.048670854915488934, 0.05531170782660774, 0.06315494257206583, 0.07231917559914472, 0.08288571512261482, 0.09489514613740525, 0.10834497146359923, 0.1231883809445849, 0.13933419227710717, 0.15664797708855288, 0.17495435554206717, 0.19404041270722985, 0.2136601609403317, 0.2335399453062465, 0.2533846643328703, 0.27288465674800505, 0.2917230868601801, 0.3095836473718787, 0.32615838901691024, 0.3411554817432746, 0.35430671235155825, 0.3653745285586645, 0.3741584492782793, 0.3805006752649114, 0.3842907528164461, 0.3854691655247815, 0.3840297545651368, 0.3800208961011734, 0.37354539436878176, 0.3647590801514017, 0.3538681359087413, 0.3411251999919689, 0.3268243324027941, 0.31129495268905183, 0.2948948861182667, 0.27800267659856304, 0.2610093433666864, 0.244309772771404, 0.22829394618636425, 0.21333820994147853, 0.19979679303675352, 0.18799377329024503, 0.17821568258778034, 0.1707049272815109, 0.16565418087639938, 0.16320188340315342, 0.1634289558520243, 0.16635680936436417, 0.17194669824341288, 0.1801004339963968, 0.19066244533066287, 0.20342313708234872, 0.21812347023380746, 0.23446065622516543, 0.2520948323896732, 0.2706565621824966, 0.2897549844901039, 0.30898642117142083, 0.3279432414576045, 0.34622277617624697, 0.36343607410092477, 0.3792162970682076, 0.3932265597392064, 0.4051670337791443, 0.41478115444003094, 0.4218607896067315, 0.42625025675963807, 0.42784910139148336, 0.4266135804998248, 0.42255682612092693, 0.41574769570570075, 0.4063083476840055, 0.39441061104836256, 0.3802712464679502, 0.3641462226204781, 0.3463241544680739, 0.32711906954721126, 0.30686268352782337, 0.28589637696260184, 0.26456307104599425, 0.24319920120391814, 0.22212698343145265, 0.20164715959996643, 0.18203239469889504, 0.16352148150499551, 0.14631448693123897, 0.13056894983925496, 0.11639721302282911, 0.10386494306840979, 0.09299086160126364, 0.08374768079032838, 0.0760642056778145, 0.06982853667811609, 0.06489227818294498, 0.061075634297300556, 0.05817325093171056, 0.055960645328854065, 0.054201050053556306, 0.052652488867093235, 0.05107489697079126, 0.04923709795351111, 0.04692345440598972, 0.0439400184454136, 0.040120022082587754, 0.035328565107664675, 0.029466379513134987, 0.02247257386902796, 0.014326287893093499, 0.0050472160354233945, -0.005305011503796529, -0.016632572034605813, -0.02880227024415948, -0.041649358849121965, -0.0549822580106925, -0.0685880479008691, -0.08223858843305162, -0.09569710352654155, -0.10872505478800074, -0.12108912148401008, -0.1325681003555062, -0.14295954027709973, -0.1520859329619998, -0.15980029170686053, -0.1659909652948261, -0.17058555325468372, -0.17355381123456373, -0.1749094607271765, -0.1747108451430475, -0.1730604035732013, -0.170102963776916, -0.16602288621450176, -0.16104012055696335, -0.15540526429663307, -0.14939373914224452, -0.14329922414727417, -0.13742650439894805, -0.13208391007784542, -0.1275755323713424, -0.12419340978184719, -0.12220988062081378, -0.12187029484928726, -0.12338627096398529, -0.1269296715037718, -0.132627454250281, -0.14055753571327012, -0.1507457795206687, -0.16316419545753777, -0.17773040577290092, -0.19430840471146232, -0.2127106057810275, -0.23270113980937993, -0.2540003361518207, -0.27629029024056806, -0.2992213937416606, -0.3224196795719732, -0.34549481352586586, -0.36804854777980184, -0.3896834394980633, -0.41001163045870326, -0.42866348124553527, -0.44529585617760375, -0.4595998627178618, -0.47130786144194586, -0.48019957946279446, -0.4861071810943436, -0.4889191739940467, -0.4885830564581549, -0.4851066412907034, -0.4785580230050178, -0.4690641872839573, -0.45680829384014543, -0.44202569529665037, -0.4249987846865637, -0.40605079191772514, -0.38553867439238465, -0.3638452683077057, -0.34137088447475733, -0.3185245453627125, -0.2957150681918813, -0.2733422020713453, -0.2517880253324794, -0.2314088024000825, -0.21252748794100107, -0.19542704992609825, -0.18034476303560426, -0.16746760003031638, -0.15692882188987256, -0.14880583834544, -0.1431193796254514, -0.1398339885463102, -0.13885981029237626, -0.1400556261193387, -0.14323304754236055, -0.14816176005851994, -0.15457568077075143, -0.16217987302532483, -0.17065804385871333, -0.17968043708616557, -0.18891192655848363, -0.19802011065496358, -0.20668321053829314, -0.21459758101874735, -0.22148465388731647, -0.2270971489915441, -0.23122440774660666, -0.23369672670151928, -0.23438859463458617, -0.23322076477998105, -0.23016112348020804, -0.22522434707147654, -0.2184703693760517, -0.21000171203326254, -0.19995975830399823, -0.18852007722515343, -0.17588692841892697, -0.1622870978970314, -0.14796323134771977, -0.1331668432582068, -0.11815118751875785, -0.10316417770462857, -0.08844154298470457, -0.07420039862809988, -0.060633398557792755, -0.04790362163328141, -0.03614032373825537, -0.02543566480648016, -0.01584249422515606, -0.007373250264308955, -6.37672973502418e-17], [0.0, 0.005539975578475955, 0.010287642171045889, 0.014383849607753733, 0.017993955368585186, 0.02130274345153727, 0.024508775513467623, 0.027818324898789645, 0.031439055360325645, 0.0355736133256877, 0.04041330528855432, 0.04613203023306156, 0.05288063096782905, 0.06078181800033288, 0.06992580537509205, 0.08036678008310774, 0.09212030566906917, 0.10516173704108892, 0.11942569781636347, 0.13480664445880405, 0.15116051366132346, 0.1683074215954844, 0.1860353564959106, 0.20410478025195208, 0.22225403089751836, 0.24020539672562327, 0.25767171474661055, 0.27436333182008893, 0.28999525639265783, 0.30429432264013484, 0.31700618711191497, 0.32790198076394245, 0.3367844464914119, 0.343493403768062, 0.34791039749445934, 0.3499624072816201, 0.3496245156863309, 0.3469214588286204, 0.3419280097517035, 0.3347681731707556, 0.32561319920442133, 0.3146784525795021, 0.30221920193200136, 0.2885254205012638, 0.2739157140675451, 0.2587305138072602, 0.24332469029075354, 0.22805975966083067, 0.2132958637337526, 0.19938371208576924, 0.18665667596277083, 0.1754232210249813, 0.16595985857252948, 0.15850478316250888, 0.15325234870256219, 0.15034851556955015, 0.14988737852540596, 0.15190885973656953, 0.15639762366560508, 0.16328324166207228, 0.1724416044375928, 0.1836975509879775, 0.19682865364367805, 0.21157007149117038, 0.22762035907947048, 0.24464809472335194, 0.26229917338696535, 0.28020459354689015, 0.29798855596909685, 0.31527668526559527, 0.3317041825917052, 0.34692371996014343, 0.3606128933263097, 0.3724810626717311, 0.3822754225031177, 0.3897861651162501, 0.3948506211786429, 0.39735628711492493, 0.39724267582017925, 0.39450195571427993, 0.3891783723852466, 0.3813664763352725, 0.3712082089233438, 0.3588889257953401, 0.34463246224362615, 0.32869536743252037, 0.3113604537193564, 0.29292982292899183, 0.2737175430296602, 0.25404215593766877, 0.234219199982369, 0.21455392883666569, 0.19533440252012219, 0.17682511557978003, 0.1592613130229513, 0.14284412639036517, 0.12773664098092574, 0.11406098121299793, 0.1018964750380457, 0.09127893086666908, 0.08220103231359616, 0.07461382792189397, 0.06842926559071505, 0.06352369538926078, 0.059742240440008414, 0.056903914192033896, 0.054807344208728535, 0.05323694801145053, 0.05196939590847753, 0.05078018935375417, 0.04945018137269178, 0.04777186800300593, 0.04555528645664206, 0.04263336663460662, 0.03886659743586773, 0.03414688761303456, 0.028400522272284207, 0.021590139948080293, 0.0137156808976801, 0.0048142842023091185, -0.00504086125317613, -0.015742679520048937, -0.027153325160805836, -0.03910817181376722, -0.05142056509354435, -0.0638872130991998, -0.07629407097120854, -0.08842256278037894, -0.10005597488325299, -0.11098584997485175, -0.12101821053988437, -0.1299794442664769, -0.13772169215031854, -0.14412759228170577, -0.14911424836963708, -0.1526363115164294, -0.1546880861277247, -0.15530459556691345, -0.15456156962052453, -0.1525743433681467, -0.14949568495514853, -0.14551259734623903, -0.14084216569716987, -0.135726546849087, -0.13042721999491141, -0.12521863721604498, -0.1203814288384187, -0.11619533099100127, -0.11293201104331871, -0.11084797053002843, -0.1101777046269896, -0.11112729222290989, -0.11386858124315409, -0.11853412034642019, -0.12521297075298754, -0.13394751119330056, -0.1447313252914824, -0.1575082346968752, -0.1721725135838361, -0.18857029143496562, -0.20650212201153056, -0.22572666781189085, -0.24596542183054518, -0.26690836273720386, -0.288220416334197, -0.3095485759001582, -0.3305295172935205, -0.35079753189052604, -0.3699925918927773, -0.38776835847778696, -0.40379994379215367, -0.4177912428974436, -0.42948166135793564, -0.43865207798124695, -0.4451298999573866, -0.44879308886256314, -0.44957306018859794, -0.44745638564141266, -0.4424852557779612, -0.4347566899323505, -0.4244205101046143, -0.4116761248269314, -0.3967681972683316, -0.37998129830319, -0.36163366930753627, -0.3420702404765263, -0.32165506796586235, -0.3007633667257171, -0.2797733251903168, -0.2590578927873157, -0.23897673142600562, -0.21986851771258337, -0.20204377373754587, -0.18577839110786468, -0.17130799578251835, -0.1588232806380618, -0.14846640905074832, -0.14032856671588573, -0.13444871107503964, -0.13081353877153576, -0.12935866221457487, -0.12997095732065952, -0.13249201652712136, -0.1367226149186424, -0.14242807341250444, -0.14934438199124395, -0.15718492845820997, -0.16564766454203073, -0.1744225317138147, -0.1831989640254522, -0.19167328473885298, -0.19955581749244525, -0.20657754112928053, -0.21249612986830912, -0.21710123691146063, -0.22021889942392806, -0.22171496559897436, -0.22149746964568467, -0.2195179073850564, -0.21577139303205586, -0.2102957059796764, -0.2031692642792982, -0.1945080883341678, -0.18446184342154803, -0.17320907241064915, -0.16095174988420083, -0.1479093053117607, -0.13431227555890698, -0.1203957555405922, -0.10639282003501357, -0.09252808947075015, -0.07901160789983619, -0.066033192498456, -0.05375740102762081, -0.04231924707237019, -0.031820772986267176, -0.02232856780671428, -0.013872292553702972, -0.006444248912428583, -5.567666179211715e-17], [0.0, 0.004804912988051165, 0.008946050303977734, 0.012563885618836803, 0.015818828530813435, 0.018886281570583946, 0.02195125510084452, 0.025202683953238436, 0.028827597714670666, 0.033005300753440665, 0.03790171825398277, 0.043664060698205935, 0.05041595148336544, 0.05825315089170057, 0.06723999471036353, 0.07740664781302763, 0.08874725240627906, 0.10121902793027528, 0.11474235535367525, 0.1292018534264521, 0.14444842898411367, 0.1603022582747608, 0.17655663214040998, 0.19298257533678498, 0.20933412989328026, 0.22535417471593552, 0.24078063907384034, 0.25535295655878243, 0.26881859885753484, 0.280939525420132, 0.2914983859406904, 0.3003043174829713, 0.30719818697237894, 0.3120571424316983, 0.31479835245766546, 0.3153818326307169, 0.31381227935495576, 0.3101398555076628, 0.30445989765299575, 0.2969115408199756, 0.2876752833146502, 0.2769695400776937, 0.2650462580681037, 0.25218569043267747, 0.23869044723171245, 0.22487895871075847, 0.21107850208107268, 0.19761795412159308, 0.1848204393552758, 0.17299604689078765, 0.16243478816568185, 0.15339996279109508, 0.14612209059531028, 0.14079355500879895, 0.1375640864360591, 0.13653719461641858, 0.13776763666127673, 0.14125998300926507, 0.14696831755645015, 0.15479708132702863, 0.16460304190465025, 0.17619834410570678, 0.18935457169417297, 0.20380772593759824, 0.21926400506935767, 0.2354062497815046, 0.25190090418534195, 0.2684053296232868, 0.28457530058665653, 0.3000725079846613, 0.31457189521379664, 0.3277686568848617, 0.3393847385644838, 0.34917468826701414, 0.35693072638363293, 0.36248691986400877, 0.3657223683000111, 0.36656333356305265, 0.36498427022664515, 0.3610077405355932, 0.3547032245127387, 0.3461848622665974, 0.3356081910319667, 0.3231659633197271, 0.30908315419191307, 0.2936112845893378, 0.2770222033655603, 0.259601482846157, 0.24164159104810473, 0.22343500796826107, 0.20526745349032458, 0.18741139047657468, 0.17011995861638124, 0.1536214828092758, 0.13811468457119527, 0.12376470655936356, 0.1107000392810668, 0.09901041591587842, 0.08874571652215378, 0.07991589733600016, 0.07249193504464523, 0.06640775047152005, 0.06156305168193393, 0.05782701371365293, 0.055042691521974406, 0.05303204481410397, 0.05160143867437526, 0.05054747261227479, 0.04966298317314888, 0.04874306171555858, 0.04759092945876667, 0.04602351641668562, 0.04387659923803636, 0.041009365046175, 0.03730828380388668, 0.032690190122182494, 0.02710449631756374, 0.020534481366845995, 0.012997624631191416, 0.004544978205918872, -0.004740403134418495, -0.014745930822526747, -0.025332783173083406, -0.03633994906106207, -0.04758890635861098, -0.05888881020015245, -0.0700420526597537, -0.08085004548285292, -0.09111907137091141, -0.10066604713170746, -0.10932404383943728, -0.11694741495597484, -0.12341639300589065, -0.12864102863477633, -0.13256436238391267, -0.1351647388726798, -0.1364571948092409, -0.13649387580562664, -0.13536346176433184, -0.13318960600687535, -0.1301284186910415, -0.12636504977277987, -0.1221094501866829, -0.11759141145238469, -0.11305500301598673, -0.10875254281834, -0.10493824943026614, -0.10186173327570565, -0.09976148973522644, -0.09885855813936846, -0.09935050777970943, -0.10140590514319331, -0.10515940577079463, -0.11070759971061492, -0.11810572182440908, -0.1273653176440007, -0.1384529325605567, -0.15128986742515815, -0.1657530177491633, -0.1816767872537912, -0.19885604018149153, -0.2170500311971297, -0.23598722750779585, -0.2553709156161473, -0.2748854654457727, -0.2942031079288869, -0.31299106894363377, -0.33091889306315825, -0.34766578517191155, -0.3629277967581212, -0.3764246866448985, -0.3879062930126216, -0.39715826462698156, -0.40400701395755084, -0.40832377299675554, -0.4100276536318949, -0.4090876378744641, -0.40552344854318717, -0.3994052775159749, -0.3908523757671431, -0.38003053643068796, -0.36714852842091394, -0.35245356305855097, -0.3362258990877196, -0.31877271186885375, -0.30042136989958795, -0.2815122757282459, -0.26239143844642837, -0.24340295103463863, -0.2248815477429706, -0.2071454143754579, -0.19048941787252144, -0.1751789111141455, -0.1614442546575081, -0.14947617952871656, -0.13942209464375457, -0.1313834194449052, -0.12541399747150905, -0.12151962044884798, -0.1196586657173333, -0.11974382309149958, -0.12164486118823438, -0.12519235853197141, -0.13018230193335353, -0.1363814343008926, -0.14353321667412008, -0.15136425527926192, -0.1595910341378847, -0.16792678744622572, -0.176088343730567, -0.18380277571315887, -0.19081369583231556, -0.19688704728707035, -0.20181625406225637, -0.20542661028498607, -0.20757880903800474, -0.20817153290834056, -0.2071430525224474, -0.20447180450887129, -0.2001759461047035, -0.19431190933798448, -0.18697200273278886, -0.17828113217401823, -0.16839273434618102, -0.15748403548501066, -0.14575076457533823, -0.1334014631900311, -0.12065154357411033, -0.10771725210839543, -0.09480969680886173, -0.08212909500264762, -0.06985939084201556, -0.05816338204561195, -0.04717848145913534, -0.03701322206035296, -0.027744594330894597, -0.019416282982296723, -0.012037846415041657, -0.00558485760713593, -4.8239143628233183e-17], [0.0, 0.004136169694361976, 0.007730883615837248, 0.010920869463157335, 0.013858527655459424, 0.016707222135347248, 0.019636243655940657, 0.022815580316156433, 0.026410635401199204, 0.03057703428839871, 0.03545566024545323, 0.0411680534237499, 0.04781229836913664, 0.055459513158874915, 0.06415103813068611, 0.07389640447606541, 0.08467214316825998, 0.09642147328199911, 0.10905488627495248, 0.12245161980551496, 0.13646199173710835, 0.15091054270419685, 0.1655999145528238, 0.180315372652565, 0.19482986299846097, 0.20890948061686554, 0.22231921442828254, 0.2348288256979518, 0.24621871273312745, 0.25628561368847486, 0.26484800225015037, 0.2717510375249552, 0.2768709395124941, 0.2801186748471764, 0.2814428537432415, 0.28083175786607284, 0.27831443972913106, 0.2739608566672713, 0.2678810259132085, 0.26022321122700603, 0.25117117530890026, 0.24094055527600355, 0.229774440232717, 0.21793824987325983, 0.20571403062719804, 0.19339430065646093, 0.18127558666396673, 0.1696518036853201, 0.15880763359602573, 0.1490120588567012, 0.1405122050098594, 0.13352763869929682, 0.12824525766419576, 0.12481489550992246, 0.12334574740353427, 0.12390370358559268, 0.12650965619666868, 0.13113882190541867, 0.13772109875386845, 0.1461424510895195, 0.15624729203001753, 0.1678418091985947, 0.18069815705426812, 0.1945594185651825, 0.20914522073702604, 0.22415787305431714, 0.23928888559562078, 0.254225714742164, 0.26865857922582187, 0.28228718788035456, 0.2948272228991677, 0.30601642860062517, 0.3156201655025832, 0.32343630266802653, 0.3292993374779159, 0.33308365081610497, 0.33470582665086596, 0.3341259876518482, 0.331348122234132, 0.32641940269003095, 0.3194285182604802, 0.31050307051997017, 0.2998061007283897, 0.28753183929766374, 0.27390078573354754, 0.25915424290330313, 0.24354844187613064, 0.22734840259008857, 0.21082168100595994, 0.1942321550935836, 0.17783399993022952, 0.16186599643711408, 0.1465463089936466, 0.1320678545911295, 0.11859437064097683, 0.10625727043265158, 0.09515335500175993, 0.08534342832908907, 0.07685183989535985, 0.06966695523776771, 0.06374253187736523, 0.05899995539151999, 0.055331269055370294, 0.05260291090039665, 0.05066005472157705, 0.049331436934311614, 0.04843453959758904, 0.04778099166307739, 0.047182045779476205, 0.04645398688739962, 0.04542333140080113, 0.043931681913319684, 0.04184011192900177, 0.03903296784808185, 0.035420991012060046, 0.03094368062928318, 0.025570838402757413, 0.019303257156635924, 0.012172538160767625, 0.004240044614902623, -0.004404978702014718, -0.013648067858407558, -0.023352912101766, -0.033365345372828696, -0.04351785005824912, -0.053634452559131365, -0.06353587985997555, -0.07304483924089906, -0.08199127976653779, -0.09021749429988891, -0.09758292452944005, -0.10396853877276567, -0.10928066294984347, -0.11345415884045908, -0.11645486020992876, -0.11828119619416017, -0.11896495200758472, -0.11857113905703043, -0.11719696935777339, -0.11496995218063742, -0.1120451535304559, -0.10860168079383305, -0.10483847514771438, -0.10096951257568153, -0.0972185301310443, -0.09381340701036656, -0.09098033972452634, -0.08893795692264024, -0.08789152206871301, -0.08802737111341187, -0.0895077275577096, -0.09246602897708982, -0.09700288735980768, -0.10318279079034828, -0.11103163643763013, -0.12053516491370055, -0.1316383443383705, -0.14424572941074867, -0.15822279701588693, -0.17339823596913154, -0.18956714501281782, -0.206495070710534, -0.22392279599034867, -0.24157177128932486, -0.2591500640158243, -0.2763586887798113, -0.2928981708783269, -0.3084751891164409, -0.3228091413592925, -0.3356384773226891, -0.3467266479995471, -0.35586752967555196, -0.3628901925080143, -0.3676628988398073, -0.37009623443000417, -0.37014529616957026, -0.36781088212055046, -0.3631396533304848, -0.35622326125673764, -0.34719645919528486, -0.33623424024783966, -0.3235480674926795, -0.30938128358520406, -0.2940038064796789, -0.2777062348603726, -0.2607935007881199, -0.2435782176696732, -0.2263738786859626, -0.20948806410295825, -0.19321581535816695, -0.17783332948365288, -0.16359211940230764, -0.1507137741180735, -0.13938543809820497, -0.12975611158003186, -0.12193385355910095, -0.11598394732133499, -0.11192806510690985, -0.10974444440888273, -0.10936906410519764, -0.11069778469300152, -0.11358939392347475, -0.11786947768326614, -0.12333501655636464, -0.12975959159793019, -0.1368990688665522, -0.14449762152823542, -0.15229394111782377, -0.16002748598833721, -0.16744461517133985, -0.17430445979495426, -0.18038439175110088, -0.18548496027124237, -0.18943418117735275, -0.19209108046177534, -0.19334841308786635, -0.19313449900703125, -0.19141414082615485, -0.1881886107695692, -0.18349471798076725, -0.17740299021682987, -0.1700150260297291, -0.16146009405552592, -0.15189107453600362, -0.14147985422018097, -0.1304122989409932, -0.11888293811341115, -0.10708950191325058, -0.09522745481622735, -0.08348466844009109, -0.07203637226631722, -0.06104051294031235, -0.050633641666779985, -0.04092743501888631, -0.03200593763070176, -0.023923596172821533, -0.016704133207188446, -0.010340287508320221, -0.004794424783589257, -4.1437450183561373e-17], [0.0, 0.003529719948798484, 0.006632013970769995, 0.009436768442028334, 0.012085655263254322, 0.014727742050179488, 0.017514876706591298, 0.020596970069233417, 0.02411730321100717, 0.02820798563906209, 0.03298568703347613, 0.03854775842770814, 0.044968849000790456, 0.05229811217561558, 0.060557079809293576, 0.06973826629362619, 0.07980454578175421, 0.09068932598814623, 0.10229752157047454, 0.11450730950834252, 0.12717262866477355, 0.14012636636310366, 0.15318415682461833, 0.16614870014782845, 0.17881449658075432, 0.1909728794999545, 0.2024172220571184, 0.21294818710716285, 0.22237888793511007, 0.23053982851592664, 0.2372834965527525, 0.24248849024318173, 0.24606307043927467, 0.24794804333824413, 0.2481188947415347, 0.24658711486347956, 0.24340067221839326, 0.23864361578754748, 0.23243480595672172, 0.22492579609622104, 0.21629790760028145, 0.20675856119317956, 0.1965369458491339, 0.18587912330109269, 0.1750426804148499, 0.16429105332134727, 0.15388765583873168, 0.1440899501568618, 0.1351435998589155, 0.1272768440579906, 0.12069522675499902, 0.11557680758468687, 0.11206796909664395, 0.11027992188099918, 0.11028599252691838, 0.11211976099015045, 0.11577409388952836, 0.12120109903805291, 0.12831300465730872, 0.13698394475591985, 0.1470526106080309, 0.1583257076707702, 0.17058213813168974, 0.1835778120442763, 0.1970509751110365, 0.21072792897136733, 0.2243290106415894, 0.23757469175976179, 0.2501916556522725, 0.2619187110243391, 0.27251240526035814, 0.28175220779724636, 0.2894451446185526, 0.2954297783474858, 0.29957944436165407, 0.30180467141882483, 0.3020547350271747, 0.30031831273068177, 0.2966232320972082, 0.29103532396421206, 0.283656414882833, 0.2746215131834702, 0.2640952621661718, 0.25226775113382444, 0.23934978991867, 0.22556776484349803, 0.21115820341411753, 0.1963621812386287, 0.1814197075690135, 0.16656422540089136, 0.1520173582703133, 0.13798402885689862, 0.12464806442508246, 0.112168391269174, 0.10067590500145518, 0.0902710861239208, 0.08102241129227782, 0.07296559049389413, 0.06610363952542488, 0.06040777619186659, 0.05581910807975223, 0.05225106009511092, 0.049592471689941194, 0.047711277281720706, 0.04645866920425413, 0.04567363096321466, 0.04518771988859879, 0.044829972688863275, 0.044431805049784424, 0.043831777336094016, 0.04288010261448377, 0.04144278051011253, 0.039405250644272166, 0.03667547231380752, 0.033186352331724886, 0.028897460163101473, 0.023795988222130266, 0.01789693496832477, 0.011242508750292436, 0.003900770678541058, -0.00403644535120966, -0.012456278518842909, -0.02122817848942897, -0.03020774458065072, -0.03924096374823571, -0.04816873394142846, -0.056831551780767126, -0.06507423901341398, -0.07275058092328876, -0.07972775184946826, -0.08589040815001332, -0.0911443372119659, -0.09541956224647377, -0.09867281634303689, -0.10088931524518822, -0.10208377615098402, -0.10230064908768619, -0.10161354757736768, -0.10012388589125214, -0.097958750666678, -0.09526805451467892, -0.09222103797595663, -0.08900220331352858, -0.08580677872564337, -0.08283582423700835, -0.08029110045398093, -0.07836982829228575, -0.07725947152068947, -0.07713267440677016, -0.078142483879348, -0.08041797949671782, -0.08406042527229043, -0.08914004527911257, -0.09569351022404896, -0.10372220520854178, -0.11319133008973484, -0.12402986368369769, -0.13613140200676913, -0.14935585934980453, -0.16353199975134838, -0.17846074590443672, -0.19391919320662643, -0.20966523902403153, -0.2254427217270316, -0.2409869510556097, -0.2560305012126345, -0.2703091310208786, -0.2835676916954579, -0.29556588237866843, -0.3060837165766424, -0.31492656896138566, -0.3219296815098388, -0.32696202041771877, -0.3299293903510035, -0.33077673001747937, -0.3294895323335274, -0.32609435315963453, -0.32065839417952036, -0.3132881674772656, -0.30412727118978855, -0.29335332674740777, -0.28117414814856434, -0.2678232319608816, -0.2535546728556736, -0.23863762307483743, -0.22335042496784702, -0.2079745533619477, -0.19278850885689075, -0.17806180406335367, -0.16404918231181315, -0.15098520250998237, -0.13907931476794924, -0.1285115393655335, -0.11942884690351635, -0.11194232042236427, -0.10612516130851578, -0.10201158040506712, -0.09959659440127688, -0.09883672581662782, -0.0996515832525015, -0.10192627758644132, -0.10551460994237008, -0.11024294906753644, -0.11591469962470487, -0.12231524925549132, -0.1292172714154798, -0.13638625318193776, -0.1435861126728083, -0.1505847694931764, -0.15715953376177644, -0.16310218470164187, -0.16822361836050004, -0.17235795553530162, -0.1753660151165882, -0.17713807448295982, -0.17759585684888185, -0.176693705140386, -0.17441892254922994, -0.17079128088165774, -0.1658617186494573, -0.15971027102945337, -0.15244329284116356, -0.14419005308933044, -0.13509879495812516, -0.12533236804906006, -0.11506354980866347, -0.10447018024776396, -0.09373023804036022, -0.08301698681469083, -0.0724943179023488, -0.062312410065221466, -0.052603817926916624, -0.04348008922371436, -0.0350289968589009, -0.027312455455553136, -0.020365174072197036, -0.014194077432343266, -0.008778507913724653, -0.004071200156602179, -3.524442801006606e-17], [0.0, 0.0029806088238126197, 0.0056376348955634835, 0.008091346134285056, 0.0104703447255062, 0.012907571064156638, 0.015536169869117544, 0.01848532942452599, 0.021876205813500613, 0.02581804204904051, 0.03040458722149584, 0.035710913290435194, 0.041790717137419726, 0.048674183215232, 0.056366467885989466, 0.06484685069252147, 0.07406858075244528, 0.08395942863147424, 0.09442293589074117, 0.1053403364703844, 0.11657310662389868, 0.127966083696475, 0.13935107906246208, 0.15055089738351474, 0.16138366335628435, 0.1716673485695977, 0.18122438520829479, 0.1898862502804343, 0.19749790389237146, 0.20392196786582478, 0.20904253662312466, 0.2127685206305331, 0.21503643358563967, 0.21581254770066546, 0.21509435654925843, 0.21291130164107072, 0.20932473675695973, 0.20442712267892948, 0.19834046382466203, 0.1912140169805413, 0.183221320357081, 0.1745566081194074, 0.16543069095199908, 0.156066396717054, 0.14669367652176926, 0.13754449023827356, 0.12884759149959799, 0.12082333527183373, 0.11367863119368583, 0.10760216297052233, 0.10275998827492316, 0.09929162497599386, 0.09730671830056938, 0.09688236998995284, 0.09806119498242358, 0.10085015400008265, 0.10522019206445753, 0.111106693854299, 0.11841074741573178, 0.12700118851141032, 0.13671737931953365, 0.14737265771773653, 0.15875837743659235, 0.17064844533095302, 0.18280425023615973, 0.19497986863655037, 0.2069274258997271, 0.21840248827808262, 0.22916936033378005, 0.23900616491597634, 0.24770958824663108, 0.2550991809188179, 0.2610211164748717, 0.26535132244309995, 0.26799791394590766, 0.26890287687461095, 0.26804296574255765, 0.26542980023427676, 0.2611091637013966, 0.25515952594572044, 0.2476898311101825, 0.23883660891914996, 0.22876048344727612, 0.21764216766461622, 0.20567804386553545, 0.1930754394555835, 0.180047714221535, 0.16680927899012513, 0.1535706664067187, 0.1405337724254234, 0.12788738205944775, 0.11580308512889295, 0.10443167736492473, 0.09390012954975496, 0.08430919271279799, 0.0757316911349116, 0.0682115374438825, 0.06176348585339994, 0.05637362106060527, 0.05200056193650917, 0.04857734137677207, 0.046013906968871754, 0.04420017188963007, 0.04300953205095438, 0.0423027542911546, 0.041932131638975405, 0.04174579557039401, 0.041592071880117126, 0.04132376637582199, 0.0408022690764003, 0.039901370886298825, 0.038510694686460255, 0.036538653221340825, 0.03391485880224915, 0.030591924366118548, 0.02654661145523731, 0.02178029780941924, 0.016318755052284643, 0.01021124495613319, 0.0035289605286693577, -0.003637144770630197, -0.01117908043893092, -0.018975021310600654, -0.026892902746219503, -0.03479431216877023, -0.04253857266335228, -0.04998690920890171, -0.05700658576908134, -0.0634749019960621, -0.06928294168443457, -0.07433897127010668, -0.07857139544791593, -0.08193118816285473, -0.08439373053361482, -0.08596000236018358, -0.08665709037068682, -0.08653799386175313, -0.08568072644100257, -0.08418673073480917, -0.08217864072100203, -0.07979744333463012, -0.07719910674474638, -0.07455075681110937, -0.0720264953417735, -0.06980296357511953, -0.06805476154954411, -0.06694983851089414, -0.06664497112037802, -0.06728144491415154, -0.06898105025305604, -0.07184249698243082, -0.07593834236307452, -0.08131251476694619, -0.08797850144722236, -0.09591825273730692, -0.10508183769756306, -0.1153878679373504, -0.12672468754346122, -0.13895230820793358, -0.15190505023413697, -0.16539483256622564, -0.1792150387689137, -0.1931448713859064, -0.20695409468837087, -0.22040805580101966, -0.23327286681584347, -0.24532062596054227, -0.2563345542990502, -0.2661139258516133, -0.2744786734041494, -0.2812735595305604, -0.28637181230597747, -0.2896781376057051, -0.29113103446524613, -0.2907043563691024, -0.2884080791431361, -0.2842882549150794, -0.2784261509238082, -0.27093659133049436, -0.2619655391422862, -0.25168697344016977, -0.24029913386693882, -0.2280202193704832, -0.21508364114599107, -0.2017329402631666, -0.1882164883453485, -0.17478209469559267, -0.1616716453195133, -0.14911589832790506, -0.13732955623971915, -0.12650672884723513, -0.11681689072019238, -0.10840142535109773, -0.10137083367733231, -0.09580266860793055, -0.0917402396297323, -0.08919211299949992, -0.08813241390052468, -0.08850191772221552, -0.09020989877872276, -0.09313668677732938, -0.09713686461735133, -0.1020430260516749, -0.1076699987397971, -0.1138194275762569, -0.12028460514587987, -0.12685543092665483, -0.13332337855215032, -0.13948635110573634, -0.145153308022481, -0.15014855362295276, -0.1543155864275216, -0.15752041996556373, -0.1596542995067732, -0.1606357546545293, -0.1604119446631572, -0.15895927124692427, -0.1562832520903996, -0.15241766678661836, -0.1474230050597849, -0.14138426442215585, -0.13440816044118575, -0.12661982715651052, -0.1181590975326262, -0.10917646385913832, -0.09982882547167889, -0.0902751358831053, -0.08067206327554248, -0.07116977727001546, -0.06190797099527166, -0.05301222082600027, -0.04459077692711651, -0.036731866163733015, -0.029501575313043885, -0.022942367192838167, -0.017072265692244133, -0.011884728176546688, -0.007349205784400901, -0.003412374198040849, -2.962357926880667e-17], [0.0, 0.0024830343071515363, 0.004734450712215819, 0.006862478518343762, 0.008980717566169425, 0.011204598087193702, 0.013647775249507848, 0.016418555313937915, 0.019616449673657655, 0.023328949932150556, 0.027628611659890785, 0.03257052669646757, 0.038190254026318766, 0.04450226759916073, 0.051498966283033666, 0.05915027675978994, 0.06740386496148235, 0.07618595598454607, 0.08540274670186938, 0.09494237991777754, 0.1046774342666276, 0.11446787051349716, 0.12416436281970904, 0.1336119331954414, 0.14265379904179507, 0.15113533760075906, 0.15890806744333683, 0.16583354593392158, 0.1717870829509212, 0.17666117499453937, 0.18036857008474105, 0.18284488239744545, 0.18405068619958626, 0.1839730310666169, 0.18262633429643604, 0.1800526215305224, 0.17632110248550212, 0.17152708499502306, 0.16579024686038962, 0.15925230090565964, 0.15207410373462024, 0.1444322726178856, 0.13651538735106813, 0.12851986450916167, 0.12064560001202752, 0.11309148209648114, 0.1060508805036935, 0.0997072188388355, 0.09422973560833076, 0.08976953541808039, 0.08645602531604833, 0.08439382243827444, 0.08366020817963002, 0.08430319132257222, 0.08634022822765398, 0.08975763266565225, 0.0945106915295893, 0.10052448590274193, 0.10769540018369315, 0.11589328558992701, 0.1249642287762912, 0.13473386189349293, 0.14501113752568073, 0.1555924808988659, 0.16626622281230116, 0.17681721013011445, 0.1870314865408913, 0.19670093474785247, 0.20562777232799384, 0.21362879716698727, 0.2205392845462907, 0.22621644647714975, 0.23054237453285858, 0.23342639996360612, 0.23480681897938888, 0.23465194640983902, 0.23296047711968432, 0.22976115117907614, 0.22511173545273241, 0.21909735057385663, 0.21182818781073437, 0.20343667473772867, 0.19407416153867543, 0.18390721088720585, 0.17311358339794106, 0.16187801740890176, 0.15038790617954337, 0.138828977371894, 0.12738107888844946, 0.11621417179761798, 0.10548462527639195, 0.09533190039178804, 0.0858756993355806, 0.07721364468038203, 0.06941953964378207, 0.06254224557286427, 0.056605197264648174, 0.05160656070914574, 0.047520021780815394, 0.04429617871128021, 0.04186449624115172, 0.04013576554188065, 0.039005001661000745, 0.03835469967984008, 0.038058362240733314, 0.03798420480868333, 0.0379989411315825, 0.03797154994470957, 0.037776925058139434, 0.03729931453588624, 0.03643546062691559, 0.03509736028497291, 0.03321457630517086, 0.03073604104893522, 0.027631308119969725, 0.02389122185111979, 0.01952798969671591, 0.014574658210253319, 0.009084008827777233, 0.0031269047791165844, -0.0032098652705002083, -0.009826188148685104, -0.01661160139201048, -0.02344856269440761, -0.03021592581519282, -0.03679252970975437, -0.043060804573749716, -0.04891029789078374, -0.05424102546088181, -0.05896655671685374, -0.06301675030055195, -0.06634006470481112, -0.06890537956852306, -0.07070327567161092, -0.07174673550080865, -0.07207124109868591, -0.07173426139369296, -0.07081413694794716, -0.06940838565479791, -0.06763146797568041, -0.06561206444402723, -0.0634899310240198, -0.06141240916618286, -0.05953067676222177, -0.05799583342701629, -0.056954918438104664, -0.056546962111902674, -0.05689917132189906, -0.058123347260615514, -0.060312628470836405, -0.06353864474088662, -0.0678491578509416, -0.07326625360446871, -0.07978513636185139, -0.08737356273500672, -0.09597193555937064, -0.10549406311531928, -0.11582857222293885, -0.12684094768614818, -0.1383761550144219, -0.1502617887887953, -0.16231167582582376, -0.17432985075859922, -0.18611481208685843, -0.19746395938966338, -0.2081781074312388, -0.21806597045159645, -0.22694851008495773, -0.2346630430935129, -0.2410670103805422, -0.2460413164320548, -0.24949315824696003, -0.2513582747146896, -0.25160256099922546, -0.25022300746070114, -0.2472479386271491, -0.24273654433146793, -0.2367777119486, -0.2294881852959855, -0.22101009179166886, -0.21150789450857227, -0.20116483945390112, -0.19017898040600104, -0.17875887366507684, -0.16711904287515822, -0.1554753194633312, -0.14404016708813835, -0.13301809872432815, -0.12260129263161372, -0.11296550852080231, -0.10426639786403959, -0.09663629267883853, -0.09018154548503314, -0.08498047977574098, -0.08108199558591002, -0.07850485894704018, -0.07723768757117434, -0.0772396284136349, -0.07844170623019527, -0.08074880627378132, -0.08404223925730932, -0.08818282300774159, -0.09301440318372402, -0.09836772531590902, -0.10406456249768029, -0.10992199749262578, -0.1157567549631541, -0.12138947902958817, -0.12664885344493299, -0.13137546625775082, -0.13542532781284022, -0.13867296012640298, -0.1410139868346088, -0.14236716576901204, -0.14267582043493904, -0.1419086419023875, -0.14005984848146222, -0.1371487066495537, -0.13321843262401853, -0.12833450933587087, -0.12258246797568684, -0.11606519639570886, -0.10889984813845474, -0.10121443543963789, -0.09314419698784676, -0.08482783633516013, -0.07640372952005618, -0.0680062006264158, -0.059761961662724114, -0.05178680836903943, -0.04418265647222137, -0.03703499369633075, -0.03041081173222803, -0.024357069662453764, -0.018899726348770744, -0.014043364376366047, -0.009771412689605491, -0.006046959441789385, -0.002814131211462107, -2.4529696943190875e-17], [0.0, 0.0020304400161089194, 0.003907884071547167, 0.005726492958941088, 0.007583364410422898, 0.00957549801408649, 0.011796751189099423, 0.014334868169270987, 0.017268662189278833, 0.02066542725044639, 0.024578650058867977, 0.029046085122336796, 0.03408824675449505, 0.0397073610967095, 0.045886809497672015, 0.05259108198373891, 0.05976624642706498, 0.06734092570465837, 0.07522776197578147, 0.08332533452064408, 0.09152048570154063, 0.09969099883033472, 0.10770856232819034, 0.11544194678533203, 0.12276031557089728, 0.1295365856609709, 0.1356507534528769, 0.14099310057014308, 0.14546719703635538, 0.1489926236551397, 0.1515073418733429, 0.15296964767110713, 0.15335965591605216, 0.15268027289834066, 0.15095762715312172, 0.1482409418725963, 0.14460184588689964, 0.14013313401361988, 0.1349470011982232, 0.12917278795423864, 0.12295428683758325, 0.11644667074932516, 0.10981311347907764, 0.1032211808357603, 0.09683907676340696, 0.0908318328528462, 0.0853575315312503, 0.08056365288909956, 0.07658363259037497, 0.07353371366302842, 0.0715101682918589, 0.07058695719369171, 0.07081388395019028, 0.07221529005278234, 0.0747893236582003, 0.07850780147133249, 0.08331666909434587, 0.08913705094973245, 0.0958668668464502, 0.1033829787545941, 0.11154381871409093, 0.12019243733475482, 0.12915990232817892, 0.13826896819030612, 0.14733793172969015, 0.15618458376648192, 0.16463016511684664, 0.17250323497976885, 0.17964336205670878, 0.18590455310402362, 0.1911583400352114, 0.19529645499675524, 0.1982330328331904, 0.19990629178857364, 0.20027965588227434, 0.19934229583832722, 0.19710907941040753, 0.1936199360873237, 0.18893865514139338, 0.183151149453308, 0.17636323018423478, 0.1686979488620891, 0.16029257352586623, 0.15129527398674586, 0.141861597815881, 0.13215082320106017, 0.12232227722261005, 0.11253170833033284, 0.10292779985913177, 0.09364890735614, 0.08482009641376688, 0.07655054976778809, 0.06893140282968548, 0.062034055820651725, 0.05590899853817488, 0.05058517081962778, 0.04606986829532438, 0.04234918938250524, 0.03938900600145239, 0.037136427530229485, 0.035521715376859136, 0.03446059453724142, 0.033856898895201853, 0.033605479043672094, 0.033595295257808494, 0.03371261408040239, 0.03384422488605809, 0.03388059282001199, 0.033718866653591764, 0.03326566430162239, 0.03243956489656904, 0.03117324425021845, 0.029415200052017223, 0.027131024010124603, 0.02430419005983518, 0.020936340440931154, 0.017047064558690893, 0.012673178759963103, 0.007867528140885557, 0.002697343927506035, -0.0027577984799030883, -0.008408365326099074, -0.014157529759548752, -0.01990404481233357, -0.025545246931418852, -0.030980109420772898, -0.03611226375287184, -0.04085290741345921, -0.04512351973855144, -0.04885831201842549, -0.05200634485960028, -0.05453325424454461, -0.05642253769817538, -0.05767636320981755, -0.05831587578658631, -0.058380989421371786, -0.05792966552046308, -0.057036692117712964, -0.05579199116835302, -0.05429849353787282, -0.05266963266713598, -0.05102651801491664, -0.049494857994838624, -0.04820170901399608, -0.047272132206839124, -0.04682584240902666, -0.04697393475130555, -0.04781577294523927, -0.049436119906397236, -0.05190258589500721, -0.05526346197866399, -0.05954599751398669, -0.0647551697251733, -0.07087298158638922, -0.07785831138274749, -0.08564732384674134, -0.09415443897560276, -0.10327384087089211, -0.1128814955455433, -0.12283763394803857, -0.13298964477424485, -0.14317531126607297, -0.15322631739223053, -0.1629719417914062, -0.1722428528099956, -0.18087491501459935, -0.18871291678213453, -0.19561412999221114, -0.2014516164381167, -0.20611720125146127, -0.209524041267012, -0.21160872565603137, -0.21233285710230712, -0.21168407402061318, -0.2096764875264316, -0.20635052073781268, -0.20177215218808203, -0.19603157930628196, -0.1892413317355421, -0.18153387737147622, -0.1730587760936995, -0.16397944693901845, -0.15446962366217365, -0.14470958102535492, -0.1348822195710948, -0.1251690999333533, -0.11574651884893944, -0.10678171792004192, -0.0984293128769756, -0.09082802568026745, -0.08409779441659784, -0.07833732676562777, -0.07362215207009006, -0.07000321499345323, -0.0675060406934384, -0.06613048769557868, -0.06585109055510482, -0.06661798029226096, -0.06835835681987404, -0.0709784744880153, -0.07436608976724024, -0.07839330927267175, -0.08291976705744364, -0.08779605259867075, -0.09286730534107854, -0.09797688818334137, -0.10297005096920504, -0.10769749590538565, -0.11201875984297932, -0.11580533344733297, -0.11894344431076749, -0.12133643985314585, -0.12290671618382927, -0.12359715070429526, -0.12337200882173635, -0.12221730840475058, -0.12014063921120154, -0.1171704481163683, -0.11335481422823711, -0.1087597505670498, -0.10346708059625212, -0.09757194823508293, -0.09118002880477682, -0.08440451544472048, -0.0773629607097934, -0.07017405620145999, -0.06295443411996225, -0.055815573533079504, -0.04886089097151808, -0.04218308976762719, -0.0358618354885583, -0.02996181605971619, -0.02453123495404862, -0.019600774398524742, -0.015183053212144885, -0.011272590953689605, -0.007846276850564644, -0.0048643288374865005, -0.002271715288426123, -1.9909610495908785e-17], [0.0, 0.001615617337400946, 0.003142299233609343, 0.004658525748938165, 0.006243843496931414, 0.007976371165696687, 0.009930335707277405, 0.012173705626256345, 0.01476598538415983, 0.01775623087445583, 0.021181340315537926, 0.025064667896594155, 0.02941499926971312, 0.03422591871812456, 0.03947558777819747, 0.04512694450492538, 0.051128321714115105, 0.057414471683470907, 0.0639079742236016, 0.07052099500644181, 0.07715735181711457, 0.08371483821063432, 0.09008774711622197, 0.0961695314177089, 0.10185553459152079, 0.10704572220809422, 0.11164734456069793, 0.11557746189671735, 0.11876526666594132, 0.12115414180049665, 0.1227034001924376, 0.1233896580893287, 0.12320780390187196, 0.12217153369636594, 0.12031343518868237, 0.11768461310607739, 0.11435386006593862, 0.11040638835749969, 0.10594214892515684, 0.10107377416921771, 0.09592419064477231, 0.09062395611552324, 0.08530838249686101, 0.08011451182291805, 0.07517801635356786, 0.07063009619684127, 0.06659444829971806, 0.06318437933930612, 0.060500131954791335, 0.058626488969719746, 0.05763071387747192, 0.05756087805273944, 0.0584446160963638, 0.06028834063883795, 0.06307693706336943, 0.06677394722639883, 0.07132223962859287, 0.07664515190551006, 0.08264808024651292, 0.08922047968750439, 0.09623822941764777, 0.10356630853146209, 0.11106172025788215, 0.11857659678733837, 0.12596141254055793, 0.13306823118247396, 0.1397539109428067, 0.14588319387882637, 0.15133160757847247, 0.15598811238248245, 0.15975743338958406, 0.16256202414702778, 0.1643436178321633, 0.16506433168104165, 0.1647073011732518, 0.16327683177517568, 0.16079806760035098, 0.15731618788340324, 0.15289515340160764, 0.1476160356418998, 0.1415749713419451, 0.134880793793441, 0.12765239977264414, 0.120015916977615, 0.1121017412605604, 0.10404151564349565, 0.09596512403504937, 0.08799777170824954, 0.08025722198026607, 0.07285125422550161, 0.06587540246490393, 0.05941102645740831, 0.05352375865961601, 0.04826236083299258, 0.04365801370491651, 0.03972405219057297, 0.036456147529208296, 0.0338329265585863, 0.03181700752229146, 0.03035642154443295, 0.029386379469142545, 0.028831335380814494, 0.02860729100126505, 0.02862427947594249, 0.028788962950844647, 0.029007275903156864, 0.02918704547808333, 0.029240521114847883, 0.029086748485711057, 0.02865372714964609, 0.027880297222658654, 0.026717707637283875, 0.025130827018010244, 0.023098967621308954, 0.020616302938578072, 0.017691870179640058, 0.014349159673939396, 0.010625303971949999, 0.006569889828340345, 0.0022434260378556784, -0.0022844909731001397, -0.006937264047617234, -0.01163357837414439, -0.016289819301026846, -0.020822559913916933, -0.02515105152878784, -0.029199650098102492, -0.032900113093575704, -0.0361937046773186, -0.039033051822946696, -0.04138370037807124, -0.043225327710684845, -0.04455257736210605, -0.045375490817568906, -0.04571952185829804, -0.045625129715118215, -0.04514695813186551, -0.04435261819203157, -0.04332110309223162, -0.0421408726993272, -0.0409076544589858, -0.03972201480943667, -0.03868676150085468, -0.037904241966974346, -0.03747360601733707, -0.03748810253248369, -0.03803247950949884, -0.039180554724265446, -0.04099302049590225, -0.04351554064698116, -0.04677719087947067, -0.050789285597377304, -0.055544624902351195, -0.06101718529588685, -0.06716226679162525, -0.07391709794045029, -0.08120188897626462, -0.08892131218108051, -0.09696637792006448, -0.10521666487520319, -0.11354285405777813, -0.12180950842869633, -0.12987803359669273, -0.13760975025827013, -0.14486900591268104, -0.15152625201199943, -0.15746101312882216, -0.16256467693669402, -0.1667430377512434, -0.1699185319805061, -0.1720321109477293, -0.17304470500827904, -0.17293824248016249, -0.1717161974128523, -0.1694036513767944, -0.16604686599511034, -0.1617123745788934, -0.15648561268471062, -0.15046911840835306, -0.14378034349445695, -0.136549125627121, -0.12891488034562953, -0.12102357770496552, -0.11302457391037098, -0.10506737157445531, -0.09729838389144296, -0.08985777785650789, -0.08287646968375878, -0.07647334184336824, -0.07075274573881177, -0.06580234711210797, -0.061691362968667625, -0.05846922935754809, -0.056164728959364835, -0.05478559637718733, -0.054318607565995866, -0.05473014825379116, -0.05596724478495677, -0.05795902983239418, -0.0606186051464918, -0.06384525418562165, -0.06752694933015568, -0.071543091616115, -0.075767415697419, -0.08007098918105447, -0.08432523365987644, -0.08840489473257551, -0.09219089004489872, -0.09557296786190826, -0.0984521137966165, -0.10074264994423285, -0.1023739786348821, -0.10329193211969083, -0.1034596995164952, -0.1028583130110136, -0.10148668637032061, -0.09936121000189242, -0.09651491780520996, -0.09299625164038275, -0.08886745911747304, -0.0842026693470824, -0.07908569906725824, -0.07360764798330324, -0.0678643470691802, -0.06195372686348958, -0.0559731743719652, -0.05001694702735396, -0.0441737102653435, -0.038524261704095605, -0.03313949975914093, -0.028078687918687017, -0.02338805801674435, -0.01909978687479286, -0.01523137086566724, -0.011785412535745082, -0.008749822667969998, -0.006098430351491548, -0.0037919830178885744, -0.0017795082776353264, -1.5703032273566892e-17], [0.0, 0.0012308156873652451, 0.00242123825683391, 0.003632893682619467, 0.004927190472919895, 0.006363387322099254, 0.007996713970726141, 0.009876596020525886, 0.012045031828029048, 0.01453516573811572, 0.01737009691362479, 0.020561956995426255, 0.024111282940259885, 0.02800670380456928, 0.03222495216245217, 0.03673120246847406, 0.041479730212959774, 0.04641487738243124, 0.05147230174213495, 0.05658048000394018, 0.06166242822084382, 0.06663759693041459, 0.07142389380292137, 0.075939782958693, 0.08010640779730804, 0.08384968319078961, 0.08710230326315525, 0.08980561270457071, 0.09191129261120394, 0.09338281612993778, 0.09419663461740245, 0.09434306146364872, 0.09382682802503954, 0.0926672940798209, 0.09089830366737862, 0.08856768589008984, 0.08573640902942457, 0.0824774049381936, 0.07887408890475202, 0.0750186078375895, 0.07100985649903332, 0.06695130745244535, 0.06294870522896132, 0.05910767884489787, 0.05553132911661537, 0.05231784816519252, 0.04955822805170651, 0.04733411364261451, 0.04571585161526291, 0.04476078305080796, 0.044511821432085534, 0.04499635120238981, 0.046225474508405064, 0.04819362552899602, 0.05087856308064722, 0.0542417432017359, 0.058229064370234986, 0.06277196912324048, 0.0677888773384838, 0.07318691851520623, 0.07886392324770006, 0.08471062789374119, 0.09061304135306712, 0.09645491901200078, 0.10212028637328727, 0.10749595373676897, 0.11247396355447864, 0.11695391374621622, 0.12084510328754901, 0.12406845069687272, 0.12655814154564585, 0.1282629676612211, 0.12914732812432458, 0.12919187030110846, 0.1283937577935923, 0.12676656113086227, 0.12433977603823243, 0.12115798299275736, 0.11727967028489013, 0.11277575075073583, 0.10772780952451944, 0.10222612641281126, 0.09636752166020215, 0.09025307783690278, 0.08398579323847981, 0.07766822348520738, 0.07140016791551473, 0.0652764558913496, 0.05938488531361425, 0.05380436155691531, 0.04860327977966722, 0.043838187281540694, 0.03955275542409827, 0.03577708278207107, 0.032527342848801676, 0.029805780988377106, 0.027601056624042265, 0.02588891809405865, 0.02463318940458473, 0.02378704046740817, 0.02329450551705141, 0.023092208426449004, 0.023111248729353218, 0.02327919843029751, 0.023522157228977002, 0.023766812662936447, 0.023942451904751024, 0.023982873527760507, 0.02382815043451362, 0.02342619924851607, 0.022734116696133906, 0.021719249717185002, 0.02035997308089359, 0.018646155969031623, 0.016579307124727594, 0.014172396546985966, 0.011449360124901296, 0.008444301838711369, 0.005200415998820837, 0.0017686592502644937, -0.0017937914447663723, -0.00542525308376657, -0.009061376923242348, -0.012637065278205383, -0.016088413286292985, -0.01935462341118728, -0.022379841111559287, -0.025114862078760614, -0.027518664699623045, -0.029559725848511655, -0.031217083643589025, -0.03248111727708241, -0.03335402128531168, -0.033849959478629295, -0.03399489200624534, -0.03382607747790059, -0.033391260490082446, -0.03274756309582393, -0.031960106506473275, -0.031100396424365, -0.030244511695958404, -0.02947114128486348, -0.028859518756716673, -0.028487306434261166, -0.028428483042937172, -0.028751288978950754, -0.029516282281038458, -0.030774555995858276, -0.032566163950537186, -0.03491879707201635, -0.03784674643914441, -0.04135018236484355, -0.045414771150606104, -0.0500116429220029, -0.05509771534458702, -0.0606163692470928, -0.06649846346030554, -0.07266366773162262, -0.07902208460723872, -0.08547612388463821, -0.0919225868099455, -0.09825491178897663, -0.10436552913396925, -0.11014826938800462, -0.11550076813303423, -0.1203268099392334, -0.12453855526294451, -0.12805859662319927, -0.1308217942243388, -0.1327768462536844, -0.13388755524749701, -0.13413375903718147, -0.1335119026888345, -0.13203523634131356, -0.12973363272483165, -0.12665302718778867, -0.1228544920539259, -0.1184129658557702, -0.11341566623105674, -0.1079602228253555, -0.10215257323218074, -0.0961046706582441, -0.08993205648829886, -0.08375135413189347, -0.07767774238522268, -0.07182246699038396, -0.06629044811113861, -0.06117803909288624, -0.05657098819296743, -0.05254265004623261, -0.04915248759092081, -0.04644489816943889, -0.04444838970948949, -0.043175124474370795, -0.042620839053104244, -0.042765140256872766, -0.043572167617900906, -0.04499160446908477, -0.0469600113295923, -0.04940244773376786, -0.052234341901804635, -0.055363561923436944, -0.05869263754783813, -0.062121078352940416, -0.06554773208333255, -0.06887312634246122, -0.07200173761269213, -0.0748441337321695, -0.07731893942296166, -0.07935457915103583, -0.08089075738561646, -0.08187964306686914, -0.08228673261680158, -0.0820913739498996, -0.08128694245411046, -0.07988066860688445, -0.07789312554861141, -0.07535739334190679, -0.07231792459148018, -0.06882914338936263, -0.06495381600443967, -0.06076123719512684, -0.05632528035636087, -0.051722362811995715, -0.047029379357322494, -0.04232165760270791, -0.0376709877609426, -0.033143777284434836, -0.028799377253682115, -0.024688622736988727, -0.020852623604023658, -0.017321835629658007, -0.014115434339348193, -0.011241006111185097, -0.008694562764309414, -0.006460877438924432, -0.004514131223117793, -0.002818851917589367, -0.0013311187552393273, -1.1843493770707101e-17], [0.0, 0.0008678594917907776, 0.001727667107702416, 0.002623474976496898, 0.0035984330673362193, 0.0046934262827384885, 0.005945770209608244, 0.007388000808831593, 0.009046790933597833, 0.010942023328478614, 0.013086045756747561, 0.015483129233204003, 0.018129145121468154, 0.021011471219844466, 0.024109131050529694, 0.027393164532368244, 0.030827222210059856, 0.034368369384757375, 0.03796808099012057, 0.04157340302389074, 0.04512825190620089, 0.0485748194057023, 0.05185504784915648, 0.05491213828541311, 0.05769205316473922, 0.06014497495007031, 0.06222668290459476, 0.06389981208255101, 0.06513496124569736, 0.06591161997221337, 0.06621888953208316, 0.06605597706835825, 0.06543244812552411, 0.06436822846929399, 0.06289335230102075, 0.061047460232358575, 0.05887905659670701, 0.05644454167913611, 0.053807040096490885, 0.05103505171323492, 0.04820095600732558, 0.04537940459021613, 0.04264563954017704, 0.040073777253180176, 0.037735098597567004, 0.0356963862482625, 0.034018349168452325, 0.0327541723210391, 0.03194822687256966, 0.031634972465486785, 0.03183807866874669, 0.03256978757958697, 0.033830533864713755, 0.035608832435186734, 0.03788143759383052, 0.040613771031686285, 0.043760609638213786, 0.047267017884946194, 0.05106950369543255, 0.05509737136824439, 0.059274240405080385, 0.06351969512764119, 0.06775102684186139, 0.07188502810247703, 0.07583979739854202, 0.07953651235128627, 0.08290113029499609, 0.08586597688007572, 0.08837118605155954, 0.09036595834946204, 0.09180960886128632, 0.09267238122434965, 0.09293600970218956, 0.09259401740750683, 0.09165174506598402, 0.09012611115645215, 0.0880451106660843, 0.0854470659085266, 0.0823796487170571, 0.0788986987016125, 0.0750668670176427, 0.07095211912144037, 0.06662613318424195, 0.06216263312995198, 0.057635696595187476, 0.05311807845552957, 0.04867958991291058, 0.04438557151495309, 0.040295495920846816, 0.0364617328059299, 0.0329285040957307, 0.029731052846076907, 0.026895043661647765, 0.024436206707031984, 0.022360231257895793, 0.020662908517536285, 0.019330517240659054, 0.018340439715160747, 0.017661990002336616, 0.017257431165803208, 0.01708315365678795, 0.01709098318013848, 0.01722958333512459, 0.017445916181039217, 0.01768672267067693, 0.017899984652386354, 0.018036330866799722, 0.01805035103656957, 0.01790178472185086, 0.01755655502370556, 0.016987621374105477, 0.01617563044820133, 0.015109349549535382, 0.013785872516585806, 0.012210594134700643, 0.010396955060540928, 0.008365965224027418, 0.006145519414660234, 0.0037695241397271107, 0.001276859725291308, -0.001289794106477647, -0.003885237415831994, -0.006463099495593103, -0.008977222278746151, -0.011383040492268223, -0.013638921404692663, -0.015707428028170108, -0.01755647157831939, -0.01916032181827339, -0.020500447546103615, -0.021566163835908144, -0.02235506760275226, -0.02287324850542333, -0.023135267991358833, -0.02316390527900663, -0.022989675112949647, -0.022650128063594434, -0.02218894982571071, -0.0216548812543887, -0.021100485628604934, -0.02058079373025272, -0.02015186066508775, -0.019869270845303166, -0.01978662913613445, -0.019954076798436846, -0.02041687051678647, -0.02121406149380584, -0.02237730934575912, -0.02392986240511391, -0.025885732098018806, -0.02824908441412273, -0.031013866236471406, -0.03416367857914741, -0.03767190273066521, -0.04150207907120366, -0.045608532075685444, -0.04993722888764122, -0.05442685300299557, -0.05901006918405726, -0.06361495086747446, -0.0681665371575167, -0.0725884831128694, -0.07680476452701943, -0.0807413968336508, -0.08432812718057542, -0.08750005912582665, -0.09019917081027366, -0.09237568982068865, -0.09398929122019856, -0.09501008931169652, -0.09541939851589812, -0.09521024417309301, -0.09438760998486945, -0.09296841505583717, -0.09098121992387663, -0.08846566742422418, -0.0854716705604539, -0.08205836559984611, -0.07829285422427731, -0.07424876361361799, -0.0700046576935102, -0.06564233633702815, -0.06124506198325165, -0.05689575486006435, -0.05267519873151314, -0.04866029881419618, -0.044922432229340246, -0.041525929109043014, -0.038526719311858054, -0.03597117570211256, -0.03389518020721151, -0.03232343350379356, -0.0312690233283061, -0.030733260203575287, -0.03070578297189679, -0.03116493008336881, -0.03207836626271132, -0.033403948122711705, -0.03509080665488595, -0.037080619444654725, -0.039309041052177744, -0.04170725637701704, -0.044203619071573254, -0.0467253352498224, -0.04920015189616484, -0.051558009531955426, -0.053732619837740886, -0.055662931026262075, -0.057294446760256273, -0.058580368233169006, -0.05948253358306619, -0.059972133975492996, -0.060030191340022764, -0.0596477887363716, -0.05882605050964638, -0.05757587561655815, -0.055917433610644815, -0.053879438613353293, -0.05149822202484659, -0.04881662960981715, -0.04588277280947869, -0.04274866757819154, -0.039468796638160934, -0.03609863272607524, -0.03269316113214593, -0.02930543958939923, -0.025985232368143395, -0.022777753300210746, -0.019722549455920484, -0.016852553401534298, -0.014193327473856791, -0.011762518436454383, -0.009569535358028642, -0.007615457718252371, -0.005893174747981725, -0.004387751001246407, -0.0030770072879582745, -0.0019323005173606921, -0.0009194808539423287, -8.25935980239455e-18], [0.0, 0.0005182704059053997, 0.0010442285879333235, 0.0016040947485557822, 0.0022231041890830496, 0.0029247069438672105, 0.0037298147045610147, 0.0046561154417779525, 0.005717474399494026, 0.006923437923636263, 0.008278853946253169, 0.0097836199469659, 0.011432565929676947, 0.013215476467606633, 0.015117252271629312, 0.01711820811653087, 0.019194500408822146, 0.021318674288113095, 0.023460317007898353, 0.025586801521012458, 0.027664101772020652, 0.029657659235605625, 0.03153327878735282, 0.03325803108928797, 0.03480113834146408, 0.03613482050292361, 0.037235079915990586, 0.03808240365812159, 0.03866236486247615, 0.03896610664575121, 0.03899069510135992, 0.03873933098876508, 0.03822141319778903, 0.037452450705067496, 0.03645382347861976, 0.03525239653319032, 0.0338799950005918, 0.032372751564656174, 0.030770340832660233, 0.029115118093634523, 0.027451182376529003, 0.025823385705672, 0.024276311906883802, 0.02285324920751601, 0.02159518117400361, 0.020539820232165964, 0.019720707124140733, 0.01916639819178718, 0.01889976037407368, 0.018937391313126314, 0.019289179040135787, 0.019958012428769496, 0.020939650039625085, 0.022222751221102115, 0.023789069471239578, 0.025613804195574238, 0.02766610321222965, 0.029909704749550913, 0.032303704341668925, 0.03480342903497139, 0.037361398746669466, 0.03992835252830934, 0.0424543159331999, 0.0448896847052507, 0.04718629962158068, 0.049298487541788144, 0.0511840445375011, 0.05280513837655128, 0.0541291095824843, 0.055129152734410235, 0.05578486255454108, 0.05608263258059457, 0.056015897758051915, 0.05558521602655898, 0.05479818782420062, 0.05366921629902067, 0.052219114804768825, 0.050474571875237566, 0.048467487230812754, 0.046234195390572316, 0.04381459607046414, 0.04125121268006628, 0.03858820183625567, 0.035870337853897274, 0.033141996627466, 0.030446163173917507, 0.027823486371434128, 0.025311403120806278, 0.022943352310127337, 0.020748096626373325, 0.018749167488525068, 0.01696444524591017, 0.015405883370969743, 0.014079381763065222, 0.012984810559356953, 0.01211618211278003, 0.011461965138463665, 0.011005531539210633, 0.010725723184103395, 0.010597523011659619, 0.010592812331452199, 0.010681194166721456, 0.01083086096447534, 0.011009484035168016, 0.011185101693699195, 0.011326983265225509, 0.011406446886598014, 0.011397610356226755, 0.011278056127064664, 0.011029393851487284, 0.010637706613641098, 0.01009387005462247, 0.009393736930391475, 0.008538183156859485, 0.007533015001932667, 0.0063887406890908004, 0.005120213190093907, 0.0037461543167870586, 0.0022885732895011504, 0.000772095684724567, -0.000776779021275886, -0.0023304712518117895, -0.003861145082837748, -0.005341539782018477, -0.006745786757133491, -0.008050189903031723, -0.009233948267936271, -0.010279801433816375, -0.011174579984733157, -0.011909645871715717, -0.012481210311526167, -0.012890520008335571, -0.013143905882376943, -0.013252692042387146, -0.013232966359338733, -0.01310521759604475, -0.012893847529589147, -0.012626569782873291, -0.012333710074500638, -0.012047425226449422, -0.011800860469184438, -0.011627266297373918, -0.011559097311663482, -0.011627116101683684, -0.011859525265345349, -0.012281150116684975, -0.012912693520820554, -0.013770082636013046, -0.014863925179119952, -0.016199090214287788, -0.017774425459387882, -0.019582619784113197, -0.021610216019512532, -0.023837775498715758, -0.0262401919942248, -0.028787149001466037, -0.031443710733665434, -0.03417103382877844, -0.0369271837092262, -0.03966803685620841, -0.04234824802979828, -0.044922259740324065, -0.04734533009980445, -0.04957455458506099, -0.05156985724294466, -0.053294927464614165, -0.05471807963695661, -0.05581301471759809, -0.056559465034310405, -0.056943706325982675, -0.05695892415528444, -0.05660542525741691, -0.05589068806167279, -0.05482925044367498, -0.053442436643169784, -0.051757929120650886, -0.04980919483230445, -0.04763477888633872, -0.04527748171966509, -0.042783438724541316, -0.04020112359202344, -0.037580298465782216, -0.03497093527141865, -0.03242213327183259, -0.02998105798175055, -0.027691926052304836, -0.025595059622414585, -0.02372603195504322, -0.0221149239743346, -0.020785708648140704, -0.019755777084964437, -0.019035616810110224, -0.01862864903613437, -0.018531227936698317, -0.01873280106358732, -0.019216226208343887, -0.019958236296178586, -0.020930040400884704, -0.02209804577032078, -0.023424682930068195, -0.024869313556168227, -0.026389198933385195, -0.027940505487772667, -0.029479323132445005, -0.030962672010115523, -0.032349473657203726, -0.033601463639489335, -0.03468402429137629, -0.03556691828912199, -0.036224906349506696, -0.03663823530469419, -0.03679298608706813, -0.03668127468239385, -0.036301302787725566, -0.035657258650423795, -0.034759072273516795, -0.033622032758460735, -0.03226627893042594, -0.030716177470321678, -0.028999605486162056, -0.027147156727752458, -0.02519129242776485, -0.023165458996184066, -0.021103195474406197, -0.019037253754671492, -0.01699875408926609, -0.015016397365781687, -0.013115754037611739, -0.011318647514151613, -0.009642647286621429, -0.008100684157854268, -0.006700796731994019, -0.005446014884593683, -0.0043343823623319296, -0.003359117045033594, -0.002508903832471501, -0.0017683116848651952, -0.001118323135888138, -0.0005369616914575457, -4.87490771407221e-18], [0.0, 0.00017339323377322909, 0.0003534988980570004, 0.0005489102183198984, 0.0007677470250585584, 0.0010173970330554355, 0.0013042767821381629, 0.0016336187302478664, 0.0020092903179201806, 0.0024336500012493724, 0.0029074442987651133, 0.0034297488404040704, 0.00399795527058505, 0.0046078046709892165, 0.00525346696199217, 0.005927664545323086, 0.006621837294746883, 0.007326344915708905, 0.00803070170656269, 0.008723837888426858, 0.009394380950053254, 0.010030949896901818, 0.010622454914407876, 0.011158394764259505, 0.011629144234748845, 0.01202622416246296, 0.0123425469284251, 0.012572630898223813, 0.012712778009079734, 0.012761209589404557, 0.012718156506645909, 0.012585900852298304, 0.012368767561486782, 0.01207306559914849, 0.011706979594986611, 0.011280414044031859, 0.010804793378115768, 0.010292822326207887, 0.009758211990582612, 0.009215377945851453, 0.008679117396852815, 0.008164272990754654, 0.00768539125416961, 0.007256383807799424, 0.006890199494067591, 0.006598515337216773, 0.00639145384519426, 0.006277333567873083, 0.006262459060870217, 0.006350955486759634, 0.006544652037942172, 0.006843017213163487, 0.007243147750612812, 0.007739811744558678, 0.008325545180642309, 0.008990799848738146, 0.009724139362836566, 0.010512478864720943, 0.011341362940458101, 0.012195275361502904, 0.013057973497961287, 0.013912839658944494, 0.014743241208480268, 0.015532891095055413, 0.01626620042369392, 0.016928614891737463, 0.017506927298474414, 0.017989558914932095, 0.01836680324939007, 0.018631026648157786, 0.018776821207761033, 0.01880110661855517, 0.01870317878296493, 0.018484704324167003, 0.018149661392022974, 0.01770422845096101, 0.017156623968178266, 0.016516901079999993, 0.015796702371353697, 0.015008980832522138, 0.014167693836227527, 0.013287477588006595, 0.01238330992927859, 0.011470169605540984, 0.010562700146587344, 0.009674886341256381, 0.008819750930626442, 0.008009078600172255, 0.00725317363715133, 0.006560656752520504, 0.005938305568868403, 0.005390942172241334, 0.004921369943954013, 0.004530360658001126, 0.004216691581146921, 0.003977231077175342, 0.0038070700247419056, 0.0036996952392450533, 0.0036472000707063624, 0.003640526456832361, 0.003669731965058876, 0.0037242747775645684, 0.0037933091729302182, 0.0038659838467540787, 0.00393173539581447, 0.003980569466155175, 0.004003322429776257, 0.003991896997756781, 0.003939465885469513, 0.0038406384998259575, 0.0036915865973269108, 0.0034901259401139695, 0.0032357521277853116, 0.0029296299762444447, 0.002574537021045081, 0.002174762911044178, 0.0017359675986300608, 0.0012650022965344505, 0.0007696981314061073, 0.0002586282566839654, -0.0002591501291428336, -0.0007743668953041086, -0.0012778159205756516, -0.0017606304114509903, -0.0022145491846591757, -0.002632166733184848, -0.003007160310727114, -0.003334487859471304, -0.003610551355281103, -0.003833321034064544, -0.004002416970695334, -0.004119145582059476, -0.004186489790773496, -0.004209052786453401, -0.004192956526748402, -0.0041456973001760735, -0.0040759617971909785, -0.003993408176325795, -0.003908417542167662, -0.003831822047611891, -0.0037746164738397376, -0.0037476606112100967, -0.0037613800504164643, -0.003825473088095809, -0.003948631351618417, -0.004138281455927854, -0.004400354527745118, -0.004739089780563933, -0.005156877513388607, -0.005654145956837417, -0.006229295325298233, -0.006878681279456899, -0.007596648788188489, -0.008375616132555217, -0.009206207548378429, -0.010077431788502641, -0.010976902731709811, -0.011891097101078746, -0.01280564340706705, -0.013705635423531419, -0.014575962858688101, -0.0154016514140998, -0.01616820414526722, -0.016861935954753444, -0.017470293165581578, -0.01798215043661892, -0.018388077785615894, -0.018680571167640696, -0.018854240900571074, -0.01890595321478849, -0.01883492130747415, -0.01864274347620753, -0.01833338716291674, -0.01791311902706873, -0.017390382454948648, -0.01677562516855534, -0.016081080792367315, -0.015320509339833354, -0.01450890256694947, -0.013662160983608933, -0.01279674999393437, -0.011929343137882308, -0.011076460715789948, -0.010254112187659571, -0.009477450647150505, -0.008760447378741303, -0.00811559402247119, -0.0075536392059324135, -0.007083365674037591, -0.006711412973816461, -0.006442149657919311, -0.0062775977833497585, -0.0062174112302309835, -0.006258908079684602, -0.006397156001535683, -0.006625108342944231, -0.006933787408850538, -0.007312510313461863, -0.007749151785837576, -0.008230437456010023, -0.008742260451603482, -0.009270013615212574, -0.00979892932211851, -0.010314418743840304, -0.01080240246826057, -0.011249624649442083, -0.011643943312719583, -0.01197459007149303, -0.012232393305276073, -0.012409959783893124, -0.012501810776742825, -0.012504469832333302, -0.0124165006232041, -0.01223849449473147, -0.011973008602253034, -0.011624456738543018, -0.011198956112786365, -0.01070413441423269, -0.010148902452278643, -0.00954319848633355, -0.008897711023432314, -0.008223587353093371, -0.007532135395649226, -0.006834526555108241, -0.006141507188255126, -0.005463126030733604, -0.004808484465634655, -0.004185515892593661, -0.0036007996718259694, -0.0030594141980323404, -0.002564832627187794, -0.0021188636611782583, -0.0017216386194808888, -0.0013716448234184244, -0.0010658041174433862, -0.0007995941838110914, -0.000567209201406425, -0.0003617553843263256, -0.00017547603671591895, -1.611457989444377e-18], [-0.0, -0.00017547603671590374, -0.00036175538432630213, -0.0005672092014063924, -0.0007995941838110469, -0.00106580411744332, -0.001371644823418345, -0.0017216386194807934, -0.002118863661178131, -0.002564832627187649, -0.0030594141980321773, -0.0036007996718257604, -0.004185515892593416, -0.004808484465634387, -0.0054631260307333, -0.006141507188254782, -0.00683452655510787, -0.00753213539564883, -0.008223587353092922, -0.008897711023431827, -0.00954319848633304, -0.010148902452278095, -0.010704134414232118, -0.011198956112785775, -0.011624456738542397, -0.0119730086022524, -0.012238494494730835, -0.012416500623203456, -0.012504469832332644, -0.012501810776742183, -0.012409959783892489, -0.012232393305275445, -0.011974590071492403, -0.011643943312718993, -0.011249624649441544, -0.010802402468260001, -0.01031441874383978, -0.009798929322118037, -0.009270013615212114, -0.008742260451603031, -0.008230437456009616, -0.007749151785837207, -0.007312510313461473, -0.006933787408850189, -0.006625108342943896, -0.006397156001535358, -0.006258908079684276, -0.006217411230230658, -0.006277597783349425, -0.006442149657918972, -0.006711412973816104, -0.007083365674037201, -0.007553639205931996, -0.008115594022470723, -0.008760447378740816, -0.009477450647149959, -0.010254112187659, -0.011076460715789355, -0.011929343137881644, -0.012796749993933685, -0.013662160983608179, -0.014508902566948673, -0.015320509339832514, -0.01608108079236644, -0.016775625168554447, -0.017390382454947707, -0.017913119027067756, -0.018333387162915757, -0.01864274347620654, -0.018834921307473156, -0.018905953214787493, -0.018854240900570085, -0.018680571167639718, -0.018388077785614947, -0.01798215043661799, -0.017470293165580665, -0.016861935954752584, -0.016168204145266377, -0.01540165141409899, -0.01457596285868739, -0.013705635423530736, -0.012805643407066412, -0.01189109710107816, -0.010976902731709273, -0.010077431788502126, -0.009206207548377959, -0.008375616132554825, -0.007596648788188102, -0.006878681279456563, -0.006229295325297916, -0.005654145956837137, -0.005156877513388352, -0.004739089780563697, -0.004400354527744902, -0.004138281455927644, -0.00394863135161821, -0.0038254730880956105, -0.003761380050416263, -0.003747660611209896, -0.003774616473839534, -0.003831822047611688, -0.003908417542167451, -0.003993408176325581, -0.004075961797190753, -0.004145697300175841, -0.004192956526748178, -0.004209052786453175, -0.00418648979077328, -0.004119145582059252, -0.004002416970695124, -0.0038333210340643366, -0.0036105513552809098, -0.0033344878594711346, -0.0030071603107269546, -0.0026321667331847204, -0.002214549184659062, -0.0017606304114509022, -0.0012778159205755974, -0.0007743668953040727, -0.0002591501291428336, 0.00025862825668393827, 0.0007696981314060624, 0.0012650022965343718, 0.0017359675986299652, 0.0021747629110440616, 0.0025745370210449358, 0.002929629976244292, 0.0032357521277851407, 0.0034901259401137904, 0.003691586597326723, 0.0038406384998257567, 0.003939465885469314, 0.0039918969977565675, 0.004003322429776052, 0.003980569466154969, 0.0039317353958142716, 0.003865983846753886, 0.0037933091729300283, 0.003724274777564385, 0.003669731965058685, 0.003640526456832173, 0.0036472000707061716, 0.0036996952392448603, 0.0038070700247417022, 0.003977231077175129, 0.004216691581146685, 0.004530360658000874, 0.004921369943953742, 0.005390942172241034, 0.005938305568868073, 0.006560656752520149, 0.0072531736371509205, 0.008009078600171823, 0.008819750930625946, 0.00967488634125586, 0.010562700146586756, 0.011470169605540342, 0.012383309929277882, 0.013287477588005869, 0.014167693836226746, 0.015008980832521316, 0.01579670237135286, 0.016516901079999105, 0.017156623968177343, 0.017704228450960067, 0.01814966139202201, 0.018484704324166025, 0.018703178782963948, 0.018801106618554185, 0.018776821207760048, 0.018631026648156825, 0.018366803249389118, 0.017989558914931172, 0.017506927298473515, 0.0169286148917366, 0.0162662004236931, 0.015532891095054626, 0.014743241208479509, 0.0139128396589438, 0.013057973497960661, 0.0121952753615023, 0.011341362940457542, 0.010512478864720424, 0.009724139362836087, 0.008990799848737685, 0.008325545180641894, 0.007739811744558308, 0.007243147750612451, 0.006843017213163151, 0.006544652037941838, 0.006350955486759302, 0.006262459060869889, 0.006277333567872749, 0.006391453845193922, 0.006598515337216414, 0.0068901994940672034, 0.007256383807799025, 0.007685391254169197, 0.008164272990754201, 0.008679117396852317, 0.009215377945850943, 0.009758211990582072, 0.010292822326207303, 0.010804793378115173, 0.011280414044031262, 0.011706979594985973, 0.012073065599147852, 0.012368767561486117, 0.012585900852297625, 0.012718156506645222, 0.012761209589403872, 0.012712778009079072, 0.012572630898223157, 0.012342546928424455, 0.01202622416246233, 0.011629144234748246, 0.011158394764258926, 0.010622454914407331, 0.010030949896901308, 0.009394380950052775, 0.008723837888426409, 0.00803070170656229, 0.007326344915708526, 0.006621837294746553, 0.005927664545322803, 0.005253466961991915, 0.004607804670988994, 0.003997955270584854, 0.0034297488404039095, 0.002907444298764966, 0.0024336500012492567, 0.002009290317920092, 0.0016336187302477864, 0.0013042767821381026, 0.0010173970330553891, 0.0007677470250585184, 0.0005489102183198725, 0.0003534988980569862, 0.00017339323377322575, 1.6114579894442915e-18], [-0.0, -0.0005369616914575236, -0.0011183231358881168, -0.0017683116848651755, -0.0025089038324714857, -0.0033591170450335524, -0.0043343823623318775, -0.005446014884593633, -0.006700796731993926, -0.008100684157854185, -0.009642647286621361, -0.01131864751415148, -0.013115754037611624, -0.015016397365781546, -0.01699875408926593, -0.019037253754671312, -0.021103195474406027, -0.023165458996183916, -0.02519129242776464, -0.027147156727752267, -0.028999605486161845, -0.030716177470321442, -0.03226627893042571, -0.03362203275846051, -0.034759072273516545, -0.03565725865042356, -0.03630130278772533, -0.0366812746823936, -0.036792986087067894, -0.036638235304694004, -0.03622490634950653, -0.03556691828912181, -0.03468402429137608, -0.03360146363948909, -0.03234947365720355, -0.03096267201011532, -0.029479323132444873, -0.027940505487772622, -0.026389198933385104, -0.02486931355616809, -0.023424682930068108, -0.022098045770320658, -0.02093004040088456, -0.019958236296178496, -0.019216226208343797, -0.018732801063587226, -0.0185312279366982, -0.01862864903613425, -0.0190356168101101, -0.019755777084964316, -0.02078570864814055, -0.022114923974334403, -0.023726031955042998, -0.02559505962241429, -0.027691926052304576, -0.02998105798175033, -0.03242213327183228, -0.03497093527141839, -0.03758029846578187, -0.040201123592023144, -0.04278343872454093, -0.0452774817196647, -0.04763477888633845, -0.049809194832304046, -0.051757929120650525, -0.05344243664316938, -0.05482925044367463, -0.05589068806167239, -0.056605425257416526, -0.05695892415528407, -0.05694370632598232, -0.056559465034310044, -0.05581301471759775, -0.05471807963695629, -0.053294927464613895, -0.05156985724294435, -0.04957455458506076, -0.04734533009980418, -0.044922259740323774, -0.04234824802979812, -0.03966803685620821, -0.03692718370922607, -0.034171033828778334, -0.03144371073366536, -0.028787149001465895, -0.026240191994224615, -0.023837775498715692, -0.021610216019512386, -0.019582619784113145, -0.017774425459387764, -0.01619909021428773, -0.01486392517911988, -0.013770082636012987, -0.0129126935208205, -0.012281150116684913, -0.011859525265345278, -0.01162711610168361, -0.011559097311663394, -0.011627266297373847, -0.011800860469184344, -0.01204742522644936, -0.012333710074500537, -0.012626569782873203, -0.012893847529589029, -0.013105217596044647, -0.013232966359338665, -0.013252692042387047, -0.013143905882376895, -0.012890520008335463, -0.012481210311526108, -0.011909645871715625, -0.011174579984733087, -0.010279801433816328, -0.009233948267936214, -0.008050189903031711, -0.006745786757133457, -0.00534153978201846, -0.003861145082837763, -0.0023304712518117895, -0.0007767790212759219, 0.0007720956847245219, 0.0022885732895011218, 0.0037461543167869988, 0.005120213190093859, 0.0063887406890907545, 0.007533015001932581, 0.008538183156859436, 0.009393736930391403, 0.010093870054622407, 0.010637706613641048, 0.0110293938514872, 0.011278056127064619, 0.011397610356226651, 0.011406446886597959, 0.01132698326522542, 0.011185101693699143, 0.011009484035167974, 0.010830860964475277, 0.010681194166721402, 0.010592812331452123, 0.010597523011659558, 0.01072572318410332, 0.011005531539210564, 0.011461965138463577, 0.012116182112779943, 0.012984810559356838, 0.014079381763065087, 0.015405883370969596, 0.01696444524591003, 0.018749167488524884, 0.0207480966263732, 0.0229433523101271, 0.02531140312080613, 0.02782348637143385, 0.030446163173917323, 0.03314199662746576, 0.03587033785389694, 0.03858820183625532, 0.04125121268006592, 0.043814596070463806, 0.04623419539057193, 0.04846748723081246, 0.050474571875237226, 0.05221911480476844, 0.05366921629902033, 0.05479818782420025, 0.055585216026558616, 0.05601589775805157, 0.0560826325805942, 0.055784862554540744, 0.05512915273440993, 0.05412910958248401, 0.05280513837655101, 0.051184044537500785, 0.049298487541787915, 0.0471862996215804, 0.04488968470525051, 0.0424543159331996, 0.0399283525283092, 0.03736139874666934, 0.03480342903497121, 0.03230370434166883, 0.029909704749550767, 0.027666103212229568, 0.0256138041955741, 0.0237890694712395, 0.02222275122110207, 0.020939650039624995, 0.019958012428769406, 0.019289179040135683, 0.018937391313126196, 0.018899760374073562, 0.01916639819178704, 0.019720707124140598, 0.020539820232165787, 0.02159518117400342, 0.022853249207515806, 0.02427631190688367, 0.025823385705671813, 0.027451182376528757, 0.02911511809363431, 0.03077034083265995, 0.032372751564655834, 0.03387999500059152, 0.0352523965331901, 0.036453823478619495, 0.03745245070506729, 0.03822141319778879, 0.03873933098876481, 0.03899069510135963, 0.03896610664575093, 0.03866236486247592, 0.03808240365812138, 0.03723507991599036, 0.0361348205029234, 0.034801138341463915, 0.03325803108928777, 0.03153327878735266, 0.02965765923560548, 0.02766410177202052, 0.02558680152101231, 0.023460317007898263, 0.021318674288112967, 0.019194500408822066, 0.01711820811653083, 0.015117252271629262, 0.013215476467606594, 0.011432565929676904, 0.009783619946965893, 0.008278853946253124, 0.006923437923636246, 0.005717474399494033, 0.004656115441777936, 0.0037298147045610104, 0.0029247069438672092, 0.0022231041890830353, 0.0016040947485557791, 0.0010442285879333289, 0.0005182704059054134, 4.874907714072175e-18], [-0.0, -0.0009194808539422866, -0.0019323005173606468, -0.003077007287958227, -0.0043877510012463455, -0.005893174747981604, -0.007615457718252246, -0.009569535358028514, -0.01176251843645417, -0.014193327473856588, -0.016852553401534104, -0.019722549455920176, -0.022777753300210382, -0.02598523236814305, -0.029305439589398838, -0.03269316113214549, -0.0360986327260748, -0.039468796638160504, -0.042748667578191006, -0.04588277280947813, -0.0488166296098166, -0.051498222024846003, -0.0538794386133527, -0.05591743361064421, -0.057575875616557505, -0.05882605050964574, -0.059647788736371034, -0.06003019134002221, -0.05997213397549235, -0.059482533583065655, -0.058580368233168506, -0.057294446760255746, -0.0556629310262615, -0.053732619837740435, -0.05155800953195513, -0.0492001518961643, -0.046725335249822, -0.04420361907157298, -0.04170725637701672, -0.039309041052177376, -0.03708061944465443, -0.035090806654885745, -0.03340394812271132, -0.03207836626271103, -0.03116493008336851, -0.030705782971896495, -0.030733260203574964, -0.03126902332830573, -0.03232343350379314, -0.03389518020721117, -0.03597117570211215, -0.03852671931185754, -0.04152592910904244, -0.044922432229339525, -0.0486602988141955, -0.05267519873151231, -0.05689575486006356, -0.06124506198325093, -0.06564233633702725, -0.07000465769350939, -0.07424876361361703, -0.07829285422427631, -0.08205836559984507, -0.08547167056045286, -0.08846566742422321, -0.09098121992387558, -0.09296841505583606, -0.09438760998486839, -0.095210244173092, -0.0954193985158971, -0.09501008931169554, -0.09398929122019757, -0.09237568982068772, -0.09019917081027284, -0.08750005912582584, -0.08432812718057457, -0.0807413968336501, -0.07680476452701868, -0.0725884831128687, -0.06816653715751626, -0.06361495086747396, -0.05901006918405682, -0.05442685300299519, -0.04993722888764088, -0.04560853207568503, -0.04150207907120329, -0.037671902730665036, -0.03416367857914711, -0.03101386623647119, -0.028249084414122473, -0.025885732098018602, -0.023929862405113717, -0.022377309345758923, -0.021214061493805655, -0.02041687051678627, -0.019954076798436637, -0.01978662913613423, -0.01986927084530292, -0.020151860665087503, -0.020580793730252466, -0.021100485628604688, -0.021654881254388428, -0.022188949825710458, -0.022650128063594132, -0.02298967511294932, -0.023163905279006372, -0.023135267991358566, -0.022873248505423115, -0.022355067602751983, -0.021566163835907922, -0.020500447546103376, -0.019160321818273172, -0.017556471578319237, -0.015707428028169948, -0.013638921404692578, -0.011383040492268121, -0.00897722227874608, -0.006463099495593101, -0.0038852374158319775, -0.0012897941064777016, 0.0012768597252912285, 0.00376952413972705, 0.006145519414660111, 0.00836596522402731, 0.010396955060540815, 0.012210594134700464, 0.01378587251658567, 0.015109349549535226, 0.016175630448201188, 0.016987621374105335, 0.017556555023705386, 0.01790178472185072, 0.018050351036569365, 0.01803633086679956, 0.017899984652386174, 0.01768672267067677, 0.01744591618103908, 0.017229583335124452, 0.017090983180138346, 0.017083153656787774, 0.017257431165803028, 0.017661990002336418, 0.01834043971516054, 0.019330517240658797, 0.02066290851753602, 0.02236023125789546, 0.02443620670703164, 0.026895043661647394, 0.029731052846076474, 0.032928504095730234, 0.03646173280592946, 0.04029549592084624, 0.04438557151495256, 0.0486795899129099, 0.05311807845552894, 0.0576356965951867, 0.06216263312995114, 0.066626133184241, 0.07095211912143948, 0.07506686701764176, 0.07889869870161151, 0.08237964871705616, 0.08544706590852562, 0.08804511066608328, 0.09012611115645117, 0.09165174506598303, 0.09259401740750584, 0.09293600970218861, 0.09267238122434868, 0.09180960886128538, 0.09036595834946123, 0.0883711860515587, 0.08586597688007494, 0.08290113029499534, 0.07953651235128557, 0.07583979739854138, 0.07188502810247643, 0.06775102684186074, 0.06351969512764072, 0.05927424040508006, 0.055097371368243976, 0.05106950369543217, 0.04726701788494586, 0.04376060963821347, 0.040613771031685904, 0.03788143759383022, 0.03560883243518649, 0.03383053386471346, 0.03256978757958668, 0.03183807866874637, 0.03163497246548645, 0.03194822687256929, 0.032754172321038715, 0.034018349168451936, 0.03569638624826202, 0.03773509859756644, 0.04007377725317964, 0.04264563954017655, 0.04537940459021552, 0.04820095600732485, 0.051035051713234296, 0.0538070400964902, 0.05644454167913529, 0.05887905659670624, 0.061047460232357895, 0.06289335230101999, 0.0643682284692933, 0.06543244812552336, 0.06605597706835749, 0.06621888953208241, 0.06591161997221262, 0.0651349612456967, 0.06389981208255038, 0.062226682904594134, 0.06014497495006971, 0.05769205316473871, 0.05491213828541256, 0.05185504784915603, 0.04857481940570189, 0.04512825190620051, 0.04157340302389034, 0.037968080990120286, 0.034368369384757035, 0.030827222210059624, 0.0273931645323681, 0.024109131050529538, 0.021011471219844337, 0.018129145121468026, 0.015483129233203927, 0.013086045756747447, 0.010942023328478552, 0.009046790933597813, 0.007388000808831542, 0.0059457702096082175, 0.004693426282738468, 0.003598433067336183, 0.0026234749764968827, 0.0017276671077024169, 0.0008678594917907961, 8.259359802394451e-18], [-0.0, -0.001331118755239276, -0.002818851917589323, -0.004514131223117757, -0.006460877438924418, -0.00869456276430934, -0.011241006111185002, -0.014115434339348119, -0.01732183562965783, -0.020852623604023523, -0.024688622736988648, -0.02879937725368189, -0.03314377728443466, -0.03767098776094239, -0.04232165760270768, -0.04702937935732224, -0.05172236281199549, -0.0563252803563607, -0.06076123719512657, -0.06495381600443946, -0.0688291433893624, -0.07231792459147991, -0.07535739334190654, -0.0778931255486112, -0.0798806686068842, -0.08128694245411021, -0.08209137394989935, -0.08228673261680136, -0.08187964306686892, -0.08089075738561638, -0.0793545791510358, -0.07731893942296157, -0.07484413373216932, -0.07200173761269185, -0.06887312634246114, -0.06554773208333235, -0.06212107835294043, -0.058692637547838246, -0.05536356192343693, -0.05223434190180454, -0.049402447733767854, -0.04696001132959221, -0.04499160446908462, -0.043572167617900844, -0.04276514025687267, -0.04262083905310415, -0.04317512447437068, -0.044448389709489305, -0.04644489816943872, -0.049152487590920696, -0.0525426500462324, -0.0565709881929671, -0.06117803909288586, -0.06629044811113807, -0.07182246699038353, -0.07767774238522238, -0.08375135413189298, -0.0899320564882985, -0.09610467065824359, -0.10215257323218038, -0.10796022282535497, -0.11341566623105621, -0.11841296585576991, -0.1228544920539254, -0.1266530271877883, -0.12973363272483118, -0.1320352363413132, -0.1335119026888341, -0.13413375903718106, -0.1338875552474967, -0.13277684625368413, -0.13082179422433843, -0.128058596623199, -0.12453855526294422, -0.12032680993923325, -0.11550076813303396, -0.11014826938800454, -0.10436552913396908, -0.09825491178897632, -0.09192258680994551, -0.08547612388463811, -0.07902208460723877, -0.07266366773162268, -0.0664984634603056, -0.06061636924709272, -0.05509771534458684, -0.05001164292200296, -0.04541477115060596, -0.04135018236484358, -0.03784674643914429, -0.034918797072016346, -0.03256616395053713, -0.030774555995858228, -0.02951628228103841, -0.028751288978950688, -0.028428483042937096, -0.028487306434261065, -0.02885951875671653, -0.029471141284863403, -0.03024451169595826, -0.031100396424364955, -0.03196010650647312, -0.03274756309582383, -0.033391260490082265, -0.03382607747790045, -0.033994892006245295, -0.03384995947862918, -0.033354021285311675, -0.03248111727708227, -0.031217083643588987, -0.029559725848511548, -0.02751866469962298, -0.0251148620787606, -0.022379841111559235, -0.01935462341118732, -0.016088413286292968, -0.012637065278205383, -0.00906137692324242, -0.00542525308376659, -0.0017937914447664625, 0.001768659250264397, 0.005200415998820792, 0.008444301838711267, 0.011449360124901227, 0.01417239654698592, 0.016579307124727462, 0.018646155969031592, 0.020359973080893514, 0.021719249717184943, 0.02273411669613389, 0.023426199248515977, 0.023828150434513615, 0.02398287352776038, 0.023942451904750993, 0.023766812662936357, 0.023522157228976978, 0.023279198430297503, 0.02311124872935317, 0.023092208426448955, 0.023294505517051336, 0.023787040467408097, 0.024633189404584636, 0.025888918094058546, 0.027601056624042126, 0.02980578098837699, 0.032527342848801474, 0.03577708278207085, 0.03955275542409803, 0.04383818728154049, 0.048603279779666934, 0.05380436155691518, 0.059384885313613876, 0.06527645589134946, 0.07140016791551429, 0.07766822348520722, 0.08398579323847948, 0.09025307783690228, 0.09636752166020165, 0.10222612641281077, 0.10772780952451902, 0.11277575075073533, 0.11727967028488982, 0.12115798299275697, 0.124339776038232, 0.1267665611308619, 0.12839375779359194, 0.1291918703011081, 0.1291473281243243, 0.12826296766122072, 0.1265581415456456, 0.12406845069687253, 0.12084510328754884, 0.11695391374621612, 0.11247396355447838, 0.1074959537367689, 0.10212028637328709, 0.09645491901200076, 0.0906130413530668, 0.0847106278937412, 0.07886392324770009, 0.07318691851520612, 0.06778887733848384, 0.0627719691232404, 0.05822906437023502, 0.05424174320173581, 0.050878563080647206, 0.04819362552899604, 0.04622547450840501, 0.04499635120238971, 0.04451182143208542, 0.04476078305080786, 0.04571585161526278, 0.04733411364261429, 0.04955822805170634, 0.05231784816519222, 0.05553132911661507, 0.05910767884489754, 0.0629487052289612, 0.06695130745244511, 0.07100985649903295, 0.07501860783758925, 0.07887408890475162, 0.08247740493819308, 0.08573640902942423, 0.08856768589008962, 0.09089830366737832, 0.0926672940798207, 0.09382682802503932, 0.09434306146364842, 0.09419663461740216, 0.09338281612993748, 0.09191129261120372, 0.08980561270457055, 0.08710230326315505, 0.08384968319078945, 0.08010640779730797, 0.07593978295869284, 0.0714238938029213, 0.0666375969304145, 0.06166242822084376, 0.05658048000394007, 0.05147230174213495, 0.04641487738243112, 0.04147973021295975, 0.036731202468474104, 0.032224952162452185, 0.028006703804569308, 0.024111282940259885, 0.02056195699542632, 0.017370096913624757, 0.014535165738115738, 0.012045031828029105, 0.009876596020525883, 0.007996713970726158, 0.006363387322099273, 0.004927190472919882, 0.0036328936826194717, 0.002421238256833929, 0.0012308156873652805, 1.1843493770707045e-17], [-0.0, -0.0017795082776352583, -0.0037919830178885163, -0.006098430351491503, -0.008749822667969984, -0.011785412535744987, -0.015231370865667122, -0.01909978687479277, -0.023388058016744134, -0.028078687918686857, -0.03313949975914084, -0.038524261704095335, -0.0441737102653433, -0.05001694702735373, -0.055973174371964945, -0.061953726863489274, -0.06786434706917994, -0.07360764798330309, -0.07908569906725794, -0.08420266934708216, -0.08886745911747282, -0.09299625164038247, -0.09651491780520972, -0.09936121000189221, -0.10148668637032036, -0.10285831301101336, -0.10345969951649496, -0.1032919321196906, -0.1023739786348819, -0.1007426499442328, -0.09845211379661654, -0.09557296786190822, -0.09219089004489857, -0.08840489473257522, -0.08432523365987639, -0.08007098918105421, -0.07576741569741909, -0.07154309161611519, -0.06752694933015574, -0.06384525418562159, -0.060618605146491804, -0.057959029832394086, -0.05596724478495662, -0.054730148253791085, -0.05431860756599576, -0.054785596377187204, -0.05616472895936471, -0.058469229357547864, -0.06169136296866743, -0.06580234711210786, -0.07075274573881152, -0.07647334184336782, -0.08287646968375832, -0.08985777785650721, -0.09729838389144245, -0.10506737157445498, -0.1130245739103704, -0.12102357770496514, -0.12891488034562892, -0.13654912562712057, -0.14378034349445634, -0.15046911840835248, -0.15648561268471037, -0.16171237457889284, -0.16604686599510998, -0.16940365137679392, -0.17171619741285193, -0.17293824248016204, -0.17304470500827868, -0.17203211094772902, -0.16991853198050585, -0.16674303775124302, -0.16256467693669382, -0.15746101312882194, -0.15152625201199937, -0.14486900591268081, -0.13760975025827016, -0.12987803359669256, -0.12180950842869602, -0.11354285405777823, -0.10521666487520312, -0.09696637792006457, -0.08892131218108065, -0.08120188897626476, -0.07391709794045025, -0.06716226679162506, -0.061017185295886935, -0.05554462490235104, -0.050789285597377366, -0.046777190879470576, -0.043515540646981155, -0.04099302049590221, -0.03918055472426539, -0.03803247950949878, -0.037488102532483594, -0.037473606017336986, -0.03790424196697422, -0.03868676150085451, -0.03972201480943659, -0.040907654458985636, -0.04214087269932716, -0.04332110309223144, -0.044352618192031436, -0.0451469581318653, -0.04562512971511805, -0.045719521858298, -0.045375490817568774, -0.044552577362106056, -0.04322532771068469, -0.04138370037807123, -0.039033051822946585, -0.036193704677318535, -0.03290011309357571, -0.029199650098102447, -0.02515105152878791, -0.020822559913916926, -0.016289819301026857, -0.011633578374144488, -0.006937264047617264, -0.0022844909731002563, 0.002243426037855558, 0.006569889828340291, 0.010625303971949877, 0.014349159673939318, 0.017691870179640013, 0.02061630293857792, 0.02309896762130893, 0.02513082701801017, 0.026717707637283827, 0.027880297222658654, 0.028653727149645994, 0.029086748485711075, 0.029240521114847737, 0.029187045478083314, 0.029007275903156767, 0.028788962950844627, 0.02862427947594249, 0.028607291001265, 0.02883133538081445, 0.029386379469142465, 0.030356421544432854, 0.031817007522291364, 0.03383292655858617, 0.03645614752920811, 0.03972405219057283, 0.04365801370491627, 0.0482623608329923, 0.05352375865961572, 0.059411026457408075, 0.06587540246490357, 0.07285125422550148, 0.0802572219802656, 0.08799777170824939, 0.09596512403504885, 0.10404151564349545, 0.11210174126056002, 0.12001591697761442, 0.1276523997726436, 0.13488079379344048, 0.14157497134194466, 0.14761603564189923, 0.15289515340160734, 0.15731618788340282, 0.1607980676003505, 0.16327683177517535, 0.1647073011732514, 0.1650643316810413, 0.16434361783216306, 0.16256202414702733, 0.1597574333895839, 0.15598811238248234, 0.15133160757847242, 0.14588319387882634, 0.13975391094280648, 0.13306823118247396, 0.12596141254055776, 0.11857659678733846, 0.11106172025788184, 0.10356630853146219, 0.09623822941764788, 0.08922047968750431, 0.08264808024651302, 0.07664515190551, 0.07132223962859292, 0.06677394722639876, 0.06307693706336943, 0.060288340638837985, 0.05844461609636373, 0.05756087805273932, 0.05763071387747178, 0.058626488969719656, 0.060500131954791175, 0.06318437933930586, 0.06659444829971783, 0.0706300961968409, 0.0751780163535675, 0.08011451182291765, 0.08530838249686093, 0.09062395611552294, 0.09592419064477187, 0.10107377416921742, 0.10594214892515641, 0.1104063883574991, 0.11435386006593823, 0.11768461310607718, 0.12031343518868208, 0.12217153369636578, 0.12320780390187168, 0.12338965808932843, 0.12270340019243733, 0.12115414180049636, 0.11876526666594113, 0.11557746189671722, 0.11164734456069773, 0.10704572220809407, 0.10185553459152076, 0.09616953141770875, 0.09008774711622196, 0.08371483821063429, 0.07715735181711454, 0.07052099500644171, 0.06390797422360163, 0.05741447168347078, 0.05112832171411511, 0.04512694450492547, 0.03947558777819752, 0.034225918718124616, 0.029414999269713134, 0.025064667896594246, 0.02118134031553789, 0.017756230874455863, 0.014765985384159902, 0.012173705626256349, 0.009930335707277428, 0.007976371165696713, 0.006243843496931404, 0.004658525748938175, 0.003142299233609369, 0.0016156173374009919, 1.570303227356682e-17], [-0.0, -0.0022717152884260297, -0.004864328837486415, -0.007846276850564568, -0.011272590953689514, -0.015183053212144663, -0.019600774398524545, -0.024531234954048443, -0.029961816059715842, -0.03586183548855801, -0.04218308976762697, -0.04886089097151762, -0.05581557353307899, -0.06295443411996181, -0.07017405620145947, -0.07736296070979283, -0.08440451544472, -0.09118002880477641, -0.09757194823508232, -0.10346708059625155, -0.10875975056704927, -0.11335481422823648, -0.11717044811636775, -0.12014063921120097, -0.12221730840475001, -0.12337200882173578, -0.12359715070429489, -0.12290671618382897, -0.1213364398531453, -0.1189434443107672, -0.11580533344733276, -0.11201875984297902, -0.10769749590538519, -0.10297005096920485, -0.09797688818334147, -0.092867305341078, -0.08779605259867063, -0.08291976705744364, -0.0783933092726716, -0.07436608976723996, -0.07097847448801511, -0.06835835681987393, -0.06661798029226061, -0.06585109055510456, -0.06613048769557835, -0.06750604069343803, -0.07000321499345286, -0.07362215207008954, -0.07833732676562707, -0.08409779441659751, -0.0908280256802669, -0.09842931287697482, -0.10678171792004106, -0.11574651884893829, -0.12516909993335235, -0.13488221957109353, -0.14470958102535378, -0.15446962366217276, -0.16397944693901728, -0.17305877609369857, -0.18153387737147506, -0.18924133173554092, -0.19603157930628076, -0.20177215218808087, -0.2063505207378117, -0.20967648752643048, -0.21168407402061207, -0.21233285710230615, -0.21160872565603042, -0.20952404126701116, -0.2061172012514605, -0.20145161643811577, -0.19561412999221048, -0.18871291678213406, -0.18087491501459882, -0.17224285280999493, -0.16297194179140584, -0.15322631739222997, -0.14317531126607247, -0.13298964477424488, -0.12283763394803839, -0.11288149554554314, -0.103273840870892, -0.09415443897560269, -0.08564732384674106, -0.07785831138274722, -0.07087298158638927, -0.06475516972517308, -0.05954599751398659, -0.0552634619786638, -0.05190258589500705, -0.04943611990639706, -0.04781577294523906, -0.04697393475130529, -0.04682584240902641, -0.04727213220683889, -0.04820170901399578, -0.04949485799483828, -0.05102651801491629, -0.05266963266713561, -0.05429849353787253, -0.05579199116835265, -0.05703669211771267, -0.05792966552046268, -0.058380989421371335, -0.05831587578658604, -0.05767636320981724, -0.05642253769817518, -0.0545332542445443, -0.052006344859600095, -0.048858312018425235, -0.045123519738551235, -0.04085290741345913, -0.0361122637528717, -0.030980109420772894, -0.025545246931418786, -0.019904044812333533, -0.01415752975954884, -0.008408365326099091, -0.0027577984799032227, 0.0026973439275058855, 0.00786752814088548, 0.01267317875996293, 0.017047064558690782, 0.020936340440931057, 0.024304190059834974, 0.027131024010124516, 0.029415200052017126, 0.031173244250218366, 0.03243956489656896, 0.03326566430162226, 0.0337188666535917, 0.033880592820011816, 0.03384422488605797, 0.03371261408040225, 0.033595295257808376, 0.033605479043672, 0.03385689889520174, 0.03446059453724129, 0.035521715376858956, 0.03713642753022925, 0.039389006001452134, 0.04234918938250495, 0.04606986829532395, 0.0505851708196274, 0.055908998538174305, 0.0620340558206512, 0.0689314028296849, 0.07655054976778745, 0.08482009641376621, 0.09364890735613944, 0.10292779985913093, 0.11253170833033219, 0.12232227722260912, 0.1321508232010594, 0.14186159781588004, 0.15129527398674475, 0.16029257352586498, 0.16869794886208808, 0.17636323018423364, 0.18315114945330685, 0.18893865514139244, 0.19361993608732272, 0.19710907941040653, 0.1993422958383263, 0.20027965588227345, 0.19990629178857283, 0.19823303283318963, 0.1952964549967544, 0.19115834003521073, 0.18590455310402318, 0.17964336205670828, 0.17250323497976838, 0.16463016511684622, 0.1561845837664816, 0.14733793172968987, 0.1382689681903059, 0.12915990232817848, 0.12019243733475465, 0.111543818714091, 0.10338297875459396, 0.09586686684645007, 0.08913705094973232, 0.08331666909434574, 0.07850780147133218, 0.07478932365820007, 0.0722152900527821, 0.07081388395018998, 0.07058695719369135, 0.07151016829185851, 0.07353371366302802, 0.07658363259037447, 0.08056365288909899, 0.0853575315312498, 0.09083183285284549, 0.09683907676340603, 0.10322118083575954, 0.10981311347907702, 0.11644667074932442, 0.12295428683758218, 0.12917278795423787, 0.13494700119822228, 0.14013313401361877, 0.14460184588689873, 0.14824094187259554, 0.1509576271531209, 0.15268027289833996, 0.1533596559160514, 0.1529696476711064, 0.15150734187334217, 0.14899262365513902, 0.1454671970363548, 0.14099310057014258, 0.1356507534528763, 0.12953658566097045, 0.12276031557089703, 0.11544194678533161, 0.10770856232819012, 0.09969099883033448, 0.09152048570154044, 0.08332533452064382, 0.0752277619757814, 0.06734092570465812, 0.059766246427064906, 0.05259108198373899, 0.045886809497671995, 0.039707361096709505, 0.034088246754495025, 0.02904608512233683, 0.02457865005886791, 0.02066542725044639, 0.01726866218927888, 0.01433486816927096, 0.011796751189099421, 0.0095754980140865, 0.007583364410422866, 0.0057264929589410825, 0.003907884071547187, 0.00203044001610897, 1.9909610495908637e-17], [-0.0, -0.002814131211462, -0.006046959441789297, -0.009771412689605427, -0.014043364376366036, -0.0188997263487706, -0.0243570696624536, -0.030410811732227917, -0.037034993696330454, -0.04418265647222115, -0.05178680836903932, -0.05976196166272376, -0.06800620062641556, -0.07640372952005592, -0.08482783633515979, -0.09314419698784641, -0.10121443543963765, -0.1088998481384546, -0.11606519639570854, -0.12258246797568662, -0.1283345093358707, -0.13321843262401825, -0.1371487066495535, -0.14005984848146208, -0.14190864190238733, -0.14267582043493884, -0.14236716576901182, -0.14101398683460864, -0.13867296012640282, -0.13542532781284036, -0.13137546625775104, -0.12664885344493307, -0.12138947902958805, -0.11575675496315382, -0.10992199749262593, -0.10406456249768002, -0.09836772531590919, -0.09301440318372432, -0.08818282300774172, -0.08404223925730926, -0.08074880627378136, -0.07844170623019517, -0.07723962841363476, -0.07723768757117422, -0.07850485894704001, -0.08108199558590981, -0.08498047977574083, -0.0901815454850328, -0.09663629267883826, -0.1042663978640395, -0.112965508520802, -0.12260129263161314, -0.13301809872432754, -0.1440401670881374, -0.15547531946333054, -0.16711904287515783, -0.1787588736650761, -0.19017898040600056, -0.20116483945390037, -0.21150789450857183, -0.22101009179166814, -0.22948818529598486, -0.23677771194859978, -0.24273654433146744, -0.24724793862714875, -0.2502230074607007, -0.2516025609992252, -0.25135827471468924, -0.24949315824695978, -0.24604131643205465, -0.2410670103805421, -0.2346630430935126, -0.2269485100849577, -0.2180659704515963, -0.20817810743123893, -0.19746395938966327, -0.18611481208685868, -0.1743298507585992, -0.16231167582582345, -0.15026178878879562, -0.13837615501442196, -0.1268409476861484, -0.11582857222293912, -0.10549406311531954, -0.09597193555937067, -0.08737356273500656, -0.07978513636185156, -0.0732662536044686, -0.0678491578509417, -0.06353864474088655, -0.060312628470836384, -0.05812334726061547, -0.056899171321898964, -0.05654696211190256, -0.05695491843810453, -0.057995833427016176, -0.05953067676222159, -0.06141240916618262, -0.06348993102401969, -0.065612064444027, -0.0676314679756804, -0.06940838565479769, -0.07081413694794704, -0.0717342613936927, -0.07207124109868575, -0.07174673550080865, -0.07070327567161079, -0.06890537956852315, -0.06634006470481096, -0.063016750300552, -0.05896655671685364, -0.05424102546088176, -0.048910297890783806, -0.0430608045737497, -0.03679252970975449, -0.030215925815192845, -0.023448562694407645, -0.01661160139201064, -0.009826188148685156, -0.003209865270500376, 0.0031269047791164196, 0.009084008827777169, 0.01457465821025317, 0.01952798969671582, 0.023891221851119762, 0.02763130811996954, 0.030736041048935212, 0.033214576305170794, 0.035097360284972866, 0.036435460626915626, 0.03729931453588614, 0.03777692505813948, 0.037971549944709415, 0.03799894113158251, 0.037984204808683225, 0.0380583622407333, 0.038354699679840086, 0.039005001661000696, 0.040135765541880565, 0.04186449624115165, 0.044296178711280075, 0.04752002178081526, 0.05160656070914553, 0.056605197264647925, 0.0625422455728641, 0.06941953964378171, 0.0772136446803816, 0.0858756993355802, 0.09533190039178775, 0.10548462527639146, 0.11621417179761787, 0.12738107888844885, 0.13882897737189384, 0.15038790617954273, 0.16187801740890156, 0.1731135833979406, 0.18390721088720516, 0.19407416153867482, 0.2034366747377281, 0.21182818781073393, 0.21909735057385613, 0.22511173545273214, 0.22976115117907578, 0.23296047711968393, 0.23465194640983872, 0.23480681897938868, 0.2334263999636058, 0.23054237453285853, 0.22621644647714936, 0.22053928454629068, 0.21362879716698735, 0.20562777232799395, 0.19670093474785263, 0.1870314865408912, 0.17681721013011464, 0.16626622281230113, 0.15559248089886615, 0.14501113752568043, 0.13473386189349318, 0.12496422877629146, 0.11589328558992701, 0.10769540018369335, 0.1005244859027419, 0.09451069152958942, 0.08975763266565218, 0.08634022822765398, 0.08430319132257216, 0.08366020817962988, 0.08439382243827427, 0.0864560253160482, 0.08976953541808032, 0.09422973560833058, 0.0997072188388351, 0.10605088050369324, 0.11309148209648065, 0.12064560001202701, 0.1285198645091611, 0.13651538735106808, 0.14443227261788533, 0.15207410373461974, 0.1592523009056593, 0.16579024686038907, 0.17152708499502234, 0.1763211024855017, 0.1800526215305222, 0.18262633429643574, 0.18397303106661678, 0.18405068619958606, 0.18284488239744526, 0.1803685700847409, 0.17666117499453915, 0.1717870829509211, 0.1658335459339216, 0.1589080674433367, 0.15113533760075898, 0.14265379904179518, 0.13361193319544132, 0.12416436281970915, 0.11446787051349719, 0.10467743426662768, 0.0949423799177775, 0.08540274670186955, 0.07618595598454596, 0.06740386496148243, 0.05915027675979012, 0.05149896628303376, 0.044502267599160844, 0.038190254026318815, 0.032570526696467705, 0.027628611659890775, 0.023328949932150612, 0.019616449673657752, 0.016418555313937922, 0.013647775249507882, 0.011204598087193741, 0.008980717566169416, 0.006862478518343778, 0.0047344507122158595, 0.002483034307151607, 2.452969694319076e-17], [-0.0, -0.003412374198040712, -0.00734920578440078, -0.011884728176546585, -0.017072265692244012, -0.02294236719283786, -0.029501575313043624, -0.03673186616373281, -0.04459077692711606, -0.053012220825999906, -0.06190797099527141, -0.07116977727001492, -0.08067206327554188, -0.09027513588310479, -0.09982882547167829, -0.1091764638591377, -0.11815909753262568, -0.12661982715651005, -0.13440816044118514, -0.14138426442215526, -0.14742300505978442, -0.15241766678661772, -0.15628325209039914, -0.15895927124692377, -0.1604119446631567, -0.16063575465452878, -0.15965429950677298, -0.15752041996556368, -0.15431558642752113, -0.15014855362295262, -0.145153308022481, -0.13948635110573618, -0.13332337855214993, -0.12685543092665474, -0.12028460514588028, -0.11381942757625639, -0.10766999873979706, -0.10204302605167498, -0.09713686461735124, -0.0931366867773291, -0.09020989877872256, -0.08850191772221536, -0.08813241390052437, -0.08919211299949954, -0.09174023962973184, -0.09580266860793006, -0.10137083367733188, -0.10840142535109705, -0.11681689072019141, -0.1265067288472348, -0.13732955623971846, -0.14911589832790406, -0.16167164531951225, -0.17478209469559117, -0.18821648834534727, -0.20173294026316502, -0.21508364114598982, -0.22802021937048222, -0.24029913386693755, -0.25168697344016877, -0.26196553914228493, -0.2709365913304931, -0.2784261509238069, -0.2842882549150783, -0.288408079143135, -0.29070435636910136, -0.2911310344652452, -0.28967813760570416, -0.28637181230597664, -0.2812735595305597, -0.2744786734041487, -0.26611392585161237, -0.2563345542990497, -0.2453206259605421, -0.23327286681584317, -0.22040805580101908, -0.2069540946883707, -0.19314487138590597, -0.17921503876891332, -0.16539483256622592, -0.151905050234137, -0.13895230820793358, -0.12672468754346128, -0.11538786793735047, -0.10508183769756287, -0.09591825273730674, -0.08797850144722248, -0.08131251476694601, -0.07593834236307444, -0.07184249698243063, -0.06898105025305584, -0.06728144491415132, -0.06664497112037773, -0.06694983851089378, -0.06805476154954378, -0.06980296357511924, -0.0720264953417731, -0.0745507568111089, -0.07719910674474594, -0.07979744333462968, -0.08217864072100167, -0.08418673073480874, -0.08568072644100223, -0.08653799386175264, -0.08665709037068632, -0.08596000236018327, -0.08439373053361451, -0.08193118816285457, -0.07857139544791557, -0.07433897127010651, -0.0692829416844343, -0.0634749019960619, -0.057006585769081304, -0.049986909208901587, -0.04253857266335233, -0.03479431216877019, -0.02689290274621949, -0.018975021310600804, -0.011179080438930959, -0.00363714477063038, 0.0035289605286691686, 0.010211244956133106, 0.01631875505228445, 0.021780297809419123, 0.026546611455237228, 0.03059192436611833, 0.03391485880224908, 0.03653865322134075, 0.038510694686460206, 0.03990137088629878, 0.04080226907640019, 0.04132376637582197, 0.04159207188011696, 0.04174579557039392, 0.04193213163897527, 0.042302754291154473, 0.0430095320509543, 0.044200171889629936, 0.04601390696887155, 0.04857734137677188, 0.05200056193650887, 0.05637362106060491, 0.06176348585339956, 0.0682115374438819, 0.07573169113491109, 0.08430919271279719, 0.09390012954975425, 0.104431677364924, 0.11580308512889212, 0.12788738205944689, 0.1405337724254227, 0.15357066640671768, 0.1668092789901244, 0.18004771422153393, 0.19307543945558267, 0.20567804386553437, 0.21764216766461503, 0.22876048344727476, 0.23883660891914882, 0.24768983111018134, 0.25515952594571933, 0.26110916370139564, 0.26542980023427587, 0.26804296574255676, 0.26890287687461006, 0.2679979139459069, 0.2653513224430992, 0.2610211164748712, 0.25509918091881717, 0.24770958824663067, 0.23900616491597626, 0.22916936033377977, 0.21840248827808234, 0.2069274258997269, 0.19497986863655023, 0.18280425023615962, 0.17064844533095297, 0.158758377436592, 0.14737265771773655, 0.13671737931953393, 0.12700118851141026, 0.1184107474157317, 0.1111066938542989, 0.10522019206445737, 0.10085015400008235, 0.09806119498242334, 0.09688236998995252, 0.09730671830056896, 0.09929162497599331, 0.10275998827492262, 0.1076021629705219, 0.11367863119368514, 0.120823335271833, 0.1288475914995974, 0.13754449023827262, 0.14669367652176807, 0.15606639671705302, 0.16543069095199836, 0.17455660811940654, 0.18322132035707972, 0.1912140169805404, 0.198340463824661, 0.20442712267892824, 0.20932473675695867, 0.21291130164107003, 0.21509435654925751, 0.21581254770066474, 0.21503643358563893, 0.2127685206305324, 0.20904253662312414, 0.20392196786582414, 0.1974979038923709, 0.18988625028043396, 0.1812243852082943, 0.17166734856959737, 0.16138366335628432, 0.15055089738351438, 0.13935107906246202, 0.12796608369647486, 0.11657310662389864, 0.10534033647038418, 0.09442293589074122, 0.08395942863147406, 0.07406858075244531, 0.06484685069252168, 0.05636646788598953, 0.04867418321523207, 0.041790717137419726, 0.03571091329043527, 0.03040458722149579, 0.02581804204904054, 0.021876205813500672, 0.01848532942452596, 0.015536169869117537, 0.012907571064156657, 0.010470344725506169, 0.008091346134285053, 0.005637634895563516, 0.0029806088238126943, 2.962357926880646e-17], [-0.0, -0.004071200156602024, -0.00877850791372453, -0.014194077432343176, -0.020365174072197022, -0.027312455455552945, -0.035028996858900686, -0.04348008922371422, -0.052603817926916215, -0.062312410065221216, -0.07249431790234866, -0.0830169868146904, -0.09373023804035994, -0.10447018024776367, -0.11506354980866308, -0.12533236804905967, -0.13509879495812488, -0.1441900530893303, -0.15244329284116323, -0.15971027102945312, -0.16586171864945717, -0.17079128088165743, -0.17441892254922986, -0.17669370514038585, -0.17759585684888174, -0.17713807448295965, -0.17536601511658798, -0.17235795553530153, -0.16822361836049993, -0.16310218470164212, -0.15715953376177685, -0.1505847694931766, -0.14358611267280824, -0.13638625318193745, -0.12921727141548006, -0.12231524925549105, -0.11591469962470509, -0.11024294906753682, -0.10551460994237019, -0.10192627758644127, -0.09965158325250147, -0.09883672581662771, -0.09959659440127677, -0.1020115804050669, -0.10612516130851546, -0.11194232042236392, -0.11942884690351611, -0.12851153936553297, -0.13907931476794894, -0.15098520250998235, -0.16404918231181276, -0.17806180406335292, -0.19278850885688995, -0.20797455336194648, -0.22335042496784618, -0.23863762307483696, -0.25355467285567274, -0.26782323196088115, -0.28117414814856356, -0.29335332674740733, -0.3041272711897879, -0.31328816747726496, -0.3206583941795201, -0.32609435315963403, -0.329489532333527, -0.33077673001747904, -0.32992939035100327, -0.3269620204177186, -0.3219296815098387, -0.3149265689613856, -0.3060837165766425, -0.29556588237866804, -0.2835676916954581, -0.27030913102087856, -0.25603050121263476, -0.24098695105560963, -0.22544272172703197, -0.20966523902403153, -0.19391919320662612, -0.17846074590443717, -0.1635319997513485, -0.14935585934980491, -0.1361314020067695, -0.12402986368369803, -0.11319133008973487, -0.10372220520854164, -0.09569351022404915, -0.08914004527911247, -0.0840604252722905, -0.08041797949671778, -0.0781424838793479, -0.07713267440677009, -0.07725947152068931, -0.07836982829228559, -0.08029110045398073, -0.0828358242370082, -0.08580677872564312, -0.08900220331352826, -0.0922210379759565, -0.09526805451467862, -0.09795875066667802, -0.10012388589125186, -0.10161354757736751, -0.10230064908768587, -0.10208377615098382, -0.10088931524518824, -0.09867281634303678, -0.09541956224647391, -0.09114433721196573, -0.0858904081500134, -0.07972775184946818, -0.07275058092328876, -0.06507423901341411, -0.056831551780767146, -0.04816873394142863, -0.03924096374823577, -0.030207744580650765, -0.021228178489429185, -0.01245627851884298, -0.004036445351209873, 0.003900770678540856, 0.011242508750292361, 0.017896934968324604, 0.023795988222130162, 0.02889746016310146, 0.03318635233172468, 0.03667547231380754, 0.03940525064427212, 0.04144278051011249, 0.042880102614483835, 0.043831777336093926, 0.04443180504978449, 0.0448299726888631, 0.04518771988859879, 0.04567363096321456, 0.04645866920425409, 0.0477112772817207, 0.049592471689941124, 0.05225106009511078, 0.05581910807975217, 0.060407776191866366, 0.06610363952542468, 0.07296559049389384, 0.08102241129227741, 0.09027108612392055, 0.10067590500145467, 0.11216839126917344, 0.1246480644250819, 0.13798402885689823, 0.15201735827031268, 0.16656422540089122, 0.18141970756901277, 0.19636218123862853, 0.21115820341411676, 0.22556776484349783, 0.2393497899186696, 0.25226775113382366, 0.26409526216617113, 0.2746215131834696, 0.28365641488283244, 0.2910353239642115, 0.2966232320972079, 0.30031831273068144, 0.3020547350271744, 0.3018046714188246, 0.29957944436165396, 0.2954297783474855, 0.2894451446185527, 0.28175220779724597, 0.2725124052603583, 0.26191871102433933, 0.25019165565227286, 0.23757469175976215, 0.2243290106415894, 0.2107279289713677, 0.19705097511103653, 0.1835778120442767, 0.1705821381316894, 0.15832570767077053, 0.1470526106080312, 0.13698394475591985, 0.1283130046573089, 0.1212010990380529, 0.11577409388952846, 0.11211976099015035, 0.11028599252691827, 0.11027992188099897, 0.1120679690966437, 0.11557680758468653, 0.12069522675499882, 0.12727684405799056, 0.13514359985891528, 0.14408995015686124, 0.15388765583873135, 0.16429105332134658, 0.17504268041484908, 0.18587912330109221, 0.19653694584913387, 0.20675856119317926, 0.21629790760028084, 0.22492579609622065, 0.2324348059567211, 0.23864361578754664, 0.2434006722183928, 0.2465871148634794, 0.24811889474153445, 0.247948043338244, 0.24606307043927447, 0.2424884902431816, 0.23728349655275252, 0.23053982851592647, 0.22237888793511007, 0.21294818710716298, 0.2024172220571183, 0.1909728794999545, 0.17881449658075463, 0.16614870014782843, 0.15318415682461856, 0.1401263663631038, 0.12717262866477377, 0.11450730950834248, 0.10229752157047478, 0.09068932598814615, 0.07980454578175435, 0.06973826629362642, 0.06055707980929371, 0.052298112175615724, 0.04496884900079053, 0.038547758427708315, 0.032985687033476124, 0.028207985639062155, 0.024117303211007277, 0.020596970069233417, 0.017514876706591322, 0.014727742050179538, 0.012085655263254317, 0.009436768442028355, 0.006632013970770053, 0.003529719948798582, 3.5244428010065886e-17], [-0.0, -0.004794424783589081, -0.010340287508320086, -0.016704133207188363, -0.023923596172821453, -0.032005937630701455, -0.04092743501888608, -0.05063364166677987, -0.061040512940311945, -0.07203637226631697, -0.083484668440091, -0.09522745481622699, -0.10708950191325016, -0.11888293811341089, -0.1304122989409928, -0.14147985422018058, -0.1518910745360034, -0.16146009405552578, -0.17001502602972876, -0.17740299021682968, -0.1834947179807671, -0.1881886107695688, -0.19141414082615477, -0.19313449900703109, -0.1933484130878663, -0.1920910804617752, -0.18943418117735294, -0.18548496027124273, -0.1803843917511004, -0.17430445979495424, -0.16744461517134016, -0.1600274859883373, -0.15229394111782374, -0.1444976215282357, -0.1368990688665527, -0.1297595915979299, -0.12333501655636465, -0.11786947768326626, -0.11358939392347471, -0.11069778469300133, -0.10936906410519759, -0.1097444444088826, -0.11192806510690977, -0.1159839473213348, -0.12193385355910057, -0.12975611158003164, -0.13938543809820494, -0.15071377411807288, -0.16359211940230695, -0.17783332948365285, -0.1932158153581669, -0.2094880641029574, -0.22637387868596212, -0.24357821766967228, -0.2607935007881194, -0.2777062348603717, -0.29400380647967794, -0.30938128358520395, -0.32354806749267867, -0.3362342402478392, -0.34719645919528414, -0.35622326125673726, -0.36313965333048426, -0.36781088212055013, -0.37014529616957, -0.3700962344300039, -0.36766289883980713, -0.3628901925080142, -0.35586752967555174, -0.3467266479995472, -0.3356384773226891, -0.32280914135929206, -0.3084751891164408, -0.292898170878327, -0.2763586887798117, -0.25915006401582386, -0.24157177128932542, -0.22392279599034837, -0.20649507071053408, -0.18956714501281835, -0.1733982359691317, -0.158222797015887, -0.14424572941074906, -0.13163834433837085, -0.12053516491370037, -0.11103163643763016, -0.10318279079034848, -0.0970028873598077, -0.09246602897708983, -0.08950772755770955, -0.08802737111341177, -0.08789152206871292, -0.08893795692264002, -0.09098033972452611, -0.09381340701036629, -0.0972185301310443, -0.10096951257568122, -0.1048384751477142, -0.10860168079383294, -0.11204515353045558, -0.11496995218063724, -0.11719696935777314, -0.11857113905703046, -0.11896495200758439, -0.11828119619415997, -0.11645486020992865, -0.11345415884045898, -0.10928066294984354, -0.10396853877276559, -0.09758292452944017, -0.09021749429988886, -0.08199127976653778, -0.07304483924089925, -0.06353587985997558, -0.053634452559131574, -0.04351785005824917, -0.03336534537282877, -0.023352912101766245, -0.01364806785840763, -0.0044049787020149535, 0.004240044614902404, 0.012172538160767563, 0.019303257156635726, 0.025570838402757336, 0.030943680629283113, 0.035420991012059894, 0.03903296784808181, 0.04184011192900173, 0.043931681913319746, 0.04542333140080111, 0.04645398688739961, 0.04718204577947618, 0.04778099166307729, 0.048434539597588956, 0.049331436934311586, 0.050660054721576996, 0.05260291090039659, 0.05533126905537022, 0.058999955391519796, 0.06374253187736513, 0.0696669552377675, 0.07685183989535949, 0.08534342832908887, 0.09515335500175948, 0.10625727043265132, 0.11859437064097623, 0.13206785459112882, 0.14654630899364623, 0.16186599643711336, 0.17783399993022916, 0.19423215509358313, 0.21082168100595944, 0.22734840259008812, 0.24354844187612984, 0.25915424290330263, 0.2739007857335473, 0.28753183929766296, 0.2998061007283892, 0.31050307051996984, 0.31942851826047963, 0.32641940269003045, 0.3313481222341317, 0.33412598765184787, 0.33470582665086573, 0.33308365081610497, 0.3292993374779154, 0.3234363026680266, 0.3156201655025834, 0.306016428600625, 0.2948272228991672, 0.2822871878803553, 0.26865857922582226, 0.25422571474216354, 0.23928888559562125, 0.22415787305431764, 0.2091452207370265, 0.19455941856518214, 0.18069815705426814, 0.1678418091985951, 0.15624729203001758, 0.14614245108951926, 0.13772109875386865, 0.13113882190541878, 0.12650965619666857, 0.12390370358559256, 0.1233457474035341, 0.12481489550992231, 0.12824525766419576, 0.13352763869929624, 0.14051220500985892, 0.14901205885670094, 0.15880763359602512, 0.16965180368531943, 0.18127558666396637, 0.19339430065646093, 0.2057140306271969, 0.21793824987325908, 0.2297744402327166, 0.24094055527600294, 0.2511711753088993, 0.26022321122700554, 0.2678810259132085, 0.2739608566672705, 0.2783144397291305, 0.28083175786607256, 0.2814428537432412, 0.2801186748471761, 0.2768709395124939, 0.2717510375249552, 0.2648480022501505, 0.25628561368847474, 0.24621871273312745, 0.23482882569795205, 0.22231921442828248, 0.20890948061686576, 0.1948298629984611, 0.18031537265256464, 0.16559991455282422, 0.15091054270419707, 0.1364619917371083, 0.12245161980551506, 0.10905488627495284, 0.09642147328199914, 0.08467214316825988, 0.07389640447606584, 0.06415103813068633, 0.0554595131588749, 0.04781229836913677, 0.04116805342375007, 0.03545566024545325, 0.030577034288398725, 0.026410635401199308, 0.02281558031615643, 0.01963624365594069, 0.0167072221353473, 0.013858527655459417, 0.01092086946315735, 0.0077308836158373325, 0.004136169694362087, 4.1437450183561176e-17], [-0.0, -0.00558485760713571, -0.012037846415041468, -0.019416282982296577, -0.027744594330894434, -0.03701322206035251, -0.04717848145913499, -0.05816338204561168, -0.06985939084201497, -0.08212909500264717, -0.09480969680886144, -0.10771725210839476, -0.12065154357410963, -0.13340146319003057, -0.1457507645753375, -0.15748403548501, -0.16839273434618052, -0.1782811321740178, -0.18697200273278825, -0.1943119093379841, -0.20017594610470318, -0.20447180450887065, -0.20714305252244708, -0.20817153290834015, -0.2075788090380044, -0.2054266102849856, -0.20181625406225637, -0.19688704728707065, -0.19081369583231517, -0.1838027757131589, -0.17608834373056725, -0.16792678744622572, -0.1595910341378844, -0.15136425527926203, -0.1435332166741207, -0.1363814343008921, -0.13018230193335353, -0.1251923585319715, -0.12164486118823423, -0.11974382309149932, -0.119658665717333, -0.1215196204488476, -0.12541399747150875, -0.13138341944490461, -0.13942209464375388, -0.14947617952871584, -0.16144425465750753, -0.1751789111141445, -0.19048941787251994, -0.20714541437545755, -0.22488154774296976, -0.24340295103463722, -0.26239143844642693, -0.2815122757282439, -0.3004213698995865, -0.31877271186885175, -0.3362258990877181, -0.3524535630585498, -0.3671485284209124, -0.3800305364306869, -0.39085237576714166, -0.3994052775159736, -0.40552344854318595, -0.40908763787446306, -0.410027653631894, -0.4083237729967547, -0.4040070139575502, -0.39715826462698084, -0.3879062930126211, -0.3764246866448981, -0.36292779675812087, -0.3476657851719106, -0.3309188930631581, -0.31299106894363377, -0.29420310792888693, -0.2748854654457723, -0.2553709156161475, -0.2359872275077956, -0.21705003119712946, -0.19885604018149222, -0.1816767872537914, -0.16575301774916346, -0.15128986742515835, -0.13845293256055688, -0.12736531764400055, -0.11810572182440891, -0.11070759971061499, -0.10515940577079444, -0.10140590514319311, -0.0993505077797092, -0.09885855813936811, -0.09976148973522607, -0.1018617332757052, -0.1049382494302655, -0.10875254281833953, -0.11305500301598635, -0.11759141145238414, -0.12210945018668228, -0.12636504977277926, -0.13012841869104091, -0.13318960600687496, -0.13536346176433134, -0.13649387580562627, -0.13645719480924032, -0.13516473887267927, -0.13256436238391234, -0.12864102863477603, -0.12341639300589052, -0.11694741495597451, -0.10932404383943721, -0.10066604713170724, -0.09111907137091124, -0.080850045482853, -0.07004205265975363, -0.05888881020015259, -0.047588906358611, -0.03633994906106209, -0.025332783173083646, -0.014745930822526811, -0.004740403134418741, 0.004544978205918636, 0.01299762463119133, 0.020534481366845773, 0.027104496317563634, 0.03269019012218243, 0.037308283803886455, 0.04100936504617497, 0.043876599238036336, 0.046023516416685624, 0.04759092945876667, 0.0487430617155585, 0.049662983173148864, 0.05054747261227462, 0.05160143867437515, 0.05303204481410384, 0.05504269152197423, 0.057827013713652765, 0.0615630516819337, 0.06640775047151963, 0.07249193504464496, 0.0799158973359997, 0.08874571652215325, 0.09901041591587784, 0.11070003928106584, 0.12376470655936281, 0.13811468457119408, 0.15362148280927482, 0.17011995861638027, 0.18741139047657357, 0.2052674534903235, 0.22343500796826027, 0.24164159104810354, 0.2596014828461561, 0.277022203365559, 0.2936112845893369, 0.30908315419191196, 0.32316596331972575, 0.3356081910319653, 0.3461848622665963, 0.35470322451273756, 0.36100774053559215, 0.36498427022664426, 0.3665633335630519, 0.3657223683000103, 0.3624869198640082, 0.35693072638363244, 0.34917468826701376, 0.33938473856448365, 0.32776865688486106, 0.31457189521379647, 0.3000725079846616, 0.2845753005866566, 0.26840532962328684, 0.25190090418534206, 0.23540624978150473, 0.2192640050693578, 0.20380772593759838, 0.18935457169417275, 0.1761983441057069, 0.1646030419046506, 0.15479708132702866, 0.14696831755645012, 0.14125998300926493, 0.13776763666127648, 0.13653719461641825, 0.13756408643605864, 0.14079355500879825, 0.14612209059530967, 0.1533999627910941, 0.16243478816568102, 0.17299604689078704, 0.18482043935527484, 0.19761795412159203, 0.2110785020810719, 0.2248789587107572, 0.23869044723171082, 0.2521856904326763, 0.2650462580681029, 0.2769695400776926, 0.28767528331464864, 0.2969115408199745, 0.3044598976529946, 0.31013985550766154, 0.3138122793549547, 0.3153818326307162, 0.3147983524576647, 0.31205714243169763, 0.30719818697237833, 0.3003043174829708, 0.29149838594069016, 0.28093952542013156, 0.26881859885753445, 0.2553529565587823, 0.24078063907383995, 0.22535417471593544, 0.20933412989328062, 0.19298257533678478, 0.17655663214041015, 0.16030225827476088, 0.14444842898411386, 0.12920185342645202, 0.11474235535367545, 0.10121902793027515, 0.08874725240627919, 0.07740664781302795, 0.06723999471036365, 0.05825315089170071, 0.05041595148336548, 0.043664060698206046, 0.03790171825398274, 0.033005300753440686, 0.02882759771467071, 0.025202683953238374, 0.021951255100844492, 0.01888628157058397, 0.015818828530813404, 0.0125638856188368, 0.008946050303977784, 0.004804912988051286, 4.8239143628232875e-17], [-0.0, -0.00644424891242834, -0.013872292553702778, -0.022328567806714144, -0.031820772986267155, -0.04231924707236991, -0.05375740102762051, -0.06603319249845581, -0.07901160789983568, -0.09252808947074984, -0.10639282003501344, -0.12039575554059166, -0.13431227555890662, -0.14790930531176036, -0.1609517498842003, -0.17320907241064876, -0.1844618434215478, -0.19450808833416766, -0.2031692642792979, -0.21029570597967615, -0.2157713930320559, -0.21951790738505608, -0.22149746964568473, -0.2217149655989743, -0.22021889942392808, -0.21710123691146052, -0.2124961298683089, -0.2065775411292805, -0.19955581749244516, -0.19167328473885337, -0.18319896402545277, -0.174422531713815, -0.1656476645420307, -0.15718492845820967, -0.1493443819912442, -0.14242807341250419, -0.13672261491864263, -0.13249201652712161, -0.12997095732065955, -0.12935866221457473, -0.1308135387715356, -0.13444871107503947, -0.14032856671588567, -0.14846640905074787, -0.1588232806380612, -0.17130799578251774, -0.18577839110786434, -0.20204377373754503, -0.21986851771258287, -0.23897673142600562, -0.25905789278731517, -0.2797733251903157, -0.3007633667257159, -0.32165506796586074, -0.3420702404765252, -0.3616336693075357, -0.37998129830318894, -0.39676819726833096, -0.41167612482693045, -0.42442051010461385, -0.4347566899323498, -0.4424852557779606, -0.4474563856414124, -0.44957306018859766, -0.44879308886256286, -0.4451298999573865, -0.4386520779812469, -0.4294816613579358, -0.4177912428974438, -0.40379994379215395, -0.3877683584777873, -0.36999259189277695, -0.35079753189052654, -0.33052951729352054, -0.3095485759001588, -0.28822041633419704, -0.26690836273720453, -0.24596542183054532, -0.22572666781189055, -0.2065021220115312, -0.18857029143496581, -0.1721725135838366, -0.15750823469687564, -0.14473132529148275, -0.13394751119330064, -0.1252129707529874, -0.11853412034642033, -0.11386858124315404, -0.1111272922229098, -0.11017770462698959, -0.11084797053002816, -0.11293201104331861, -0.11619533099100089, -0.12038142883841833, -0.1252186372160446, -0.1304272199949112, -0.13572654684908658, -0.14084216569716937, -0.14551259734623886, -0.14949568495514814, -0.15257434336814674, -0.15456156962052423, -0.1553045955669133, -0.1546880861277243, -0.15263631151642923, -0.1491142483696371, -0.1441275922817057, -0.13772169215031874, -0.12997944426647678, -0.12101821053988457, -0.11098584997485174, -0.100055974883253, -0.08842256278037917, -0.0762940709712086, -0.06388721309920004, -0.05142056509354446, -0.03910817181376729, -0.027153325160806138, -0.015742679520049034, -0.005040861253176401, 0.004814284202308872, 0.013715680897680016, 0.021590139948080102, 0.028400522272284092, 0.03414688761303457, 0.03886659743586749, 0.04263336663460668, 0.04555528645664201, 0.04777186800300591, 0.04945018137269186, 0.05078018935375407, 0.05196939590847759, 0.05323694801145036, 0.05480734420872849, 0.05690391419203381, 0.05974224044000831, 0.06352369538926068, 0.06842926559071494, 0.0746138279218937, 0.08220103231359611, 0.09127893086666868, 0.10189647503804541, 0.11406098121299743, 0.1277366409809251, 0.14284412639036484, 0.15926131302295057, 0.17682511557977923, 0.1953344025201214, 0.21455392883666521, 0.23421919998236823, 0.2540421559376686, 0.2737175430296593, 0.29292982292899167, 0.31136045371935545, 0.32869536743252015, 0.34463246224362565, 0.3588889257953393, 0.37120820892334316, 0.381366476335272, 0.3891783723852461, 0.3945019557142795, 0.39724267582017886, 0.3973562871149247, 0.3948506211786428, 0.38978616511624997, 0.38227542250311786, 0.37248106267173087, 0.3606128933263101, 0.34692371996014293, 0.3317041825917057, 0.3152766852655959, 0.29798855596909746, 0.2802045935468907, 0.2622991733869654, 0.2446480947233525, 0.22762035907947054, 0.21157007149117088, 0.19682865364367771, 0.18369755098797788, 0.17244160443759307, 0.16328324166207228, 0.15639762366560525, 0.1519088597365695, 0.14988737852540587, 0.15034851556955003, 0.15325234870256188, 0.1585047831625083, 0.16595985857252898, 0.17542322102498067, 0.18665667596277052, 0.19938371208576927, 0.21329586373375223, 0.22805975966082978, 0.24332469029075307, 0.2587305138072595, 0.27391571406754395, 0.2885254205012631, 0.30221920193200136, 0.31467845257950167, 0.32561319920442056, 0.3347681731707552, 0.3419280097517029, 0.34692145882861963, 0.34962451568633046, 0.34996240728162, 0.3479103974944592, 0.3434934037680618, 0.33678444649141187, 0.32790198076394256, 0.3170061871119153, 0.3042943226401349, 0.2899952563926579, 0.27436333182008926, 0.2576717147466105, 0.24020539672562333, 0.22225403089751888, 0.2041047802519521, 0.18603535649591105, 0.1683074215954846, 0.1511605136613238, 0.13480664445880405, 0.11942569781636378, 0.10516173704108886, 0.09212030566906936, 0.08036678008310805, 0.06992580537509223, 0.06078181800033304, 0.052880630967829134, 0.04613203023306174, 0.040413305288554316, 0.03557361332568775, 0.03143905536032573, 0.02781832489878963, 0.02450877551346763, 0.02130274345153734, 0.01799395536858519, 0.014383849607753763, 0.010287642171045974, 0.005539975578476109, 5.56766617921169e-17], [-0.0, -0.00737325026430867, -0.01584249422515582, -0.025435664806479984, -0.0361403237382552, -0.0479036216332809, -0.06063339855779236, -0.0742003986280996, -0.0884415429847039, -0.10316417770462812, -0.11815118751875753, -0.1331668432582061, -0.1479632313477191, -0.1622870978970309, -0.17588692841892628, -0.18852007722515285, -0.19995975830399776, -0.21000171203326215, -0.21847036937605113, -0.2252243470714763, -0.23016112348020784, -0.2332207647799805, -0.234388594634586, -0.23369672670151898, -0.23122440774660646, -0.22709714899154368, -0.22148465388731675, -0.21459758101874785, -0.20668321053829286, -0.19802011065496383, -0.18891192655848404, -0.17968043708616568, -0.17065804385871317, -0.162179873025325, -0.15457568077075207, -0.14816176005851947, -0.14323304754236055, -0.1400556261193387, -0.1388598102923761, -0.13983398854630993, -0.14311937962545096, -0.1488058383454394, -0.15692882188987234, -0.1674676000303156, -0.18034476303560337, -0.1954270499260973, -0.21252748794100038, -0.2314088024000812, -0.25178802533247757, -0.273342202071345, -0.2957150681918804, -0.318524545362711, -0.34137088447475566, -0.36384526830770353, -0.38553867439238304, -0.4060507919177231, -0.42499878468656205, -0.4420256952966492, -0.45680829384014393, -0.4690641872839563, -0.4785580230050166, -0.48510664129070236, -0.48858305645815386, -0.4889191739940459, -0.4861071810943428, -0.48019957946279385, -0.47130786144194564, -0.4595998627178615, -0.44529585617760353, -0.4286634812455352, -0.4100116304587033, -0.38968343949806294, -0.3680485477798019, -0.3454948135258661, -0.32241967957197354, -0.29922139374166035, -0.2762902902405685, -0.2540003361518206, -0.23270113980937981, -0.21271060578102835, -0.19430840471146268, -0.17773040577290117, -0.163164195457538, -0.15074577952066887, -0.14055753571327, -0.13262745425028086, -0.12692967150377174, -0.12338627096398509, -0.12187029484928698, -0.12220988062081352, -0.12419340978184673, -0.1275755323713419, -0.13208391007784484, -0.13742650439894724, -0.14329922414727356, -0.1493937391422441, -0.15540526429663246, -0.16104012055696262, -0.16602288621450112, -0.17010296377691542, -0.17306040357320088, -0.174710845143047, -0.17490946072717614, -0.17355381123456315, -0.1705855532546832, -0.1659909652948258, -0.15980029170686033, -0.15208593296199974, -0.14295954027709945, -0.13256810035550623, -0.12108912148400991, -0.10872505478800064, -0.09569710352654173, -0.08223858843305162, -0.06858804790086931, -0.05498225801069258, -0.04164935884912202, -0.028802270244159777, -0.0166325720346059, -0.005305011503796807, 0.005047216035423139, 0.014326287893093419, 0.022472573869027745, 0.029466379513134886, 0.03532856510766464, 0.040120022082587546, 0.043940018445413606, 0.046923454405989724, 0.049237097953511125, 0.051074896970791275, 0.05265248886709315, 0.0542010500535563, 0.05596064532885389, 0.05817325093171043, 0.06107563429730042, 0.06489227818294471, 0.06982853667811588, 0.07606420567781418, 0.0837476807903278, 0.09299086160126332, 0.1038649430684092, 0.11639721302282842, 0.1305689498392542, 0.14631448693123777, 0.16352148150499463, 0.1820323946988936, 0.2016471595999653, 0.22212698343145154, 0.2431992012039169, 0.2645630710459931, 0.28589637696260095, 0.30686268352782203, 0.3271190695472104, 0.3463241544680726, 0.36414622262047713, 0.380271246467949, 0.3944106110483613, 0.40630834768400426, 0.41574769570569986, 0.422556826120926, 0.4266135804998239, 0.42784910139148263, 0.42625025675963757, 0.421860789606731, 0.4147811544400307, 0.40516703377914404, 0.3932265597392062, 0.37921629706820764, 0.3634360741009243, 0.3462227761762471, 0.3279432414576053, 0.3089864211714212, 0.28975498449010423, 0.2706565621824969, 0.2520948323896735, 0.23446065622516576, 0.2181234702338077, 0.20342313708234858, 0.19066244533066304, 0.1801004339963971, 0.17194669824341285, 0.1663568093643641, 0.1634289558520241, 0.16320188340315306, 0.16565418087639902, 0.1707049272815103, 0.17821568258777937, 0.18799377329024414, 0.19979679303675218, 0.2133382099414775, 0.2282939461863636, 0.24430977277140278, 0.26100934336668513, 0.2780026765985622, 0.2948948861182653, 0.31129495268904994, 0.3268243324027928, 0.341125199991968, 0.3538681359087402, 0.3647590801514001, 0.3735453943687807, 0.38002089610117235, 0.38402975456513566, 0.38546916552478044, 0.38429075281644554, 0.38050067526491077, 0.37415844927827874, 0.36537452855866404, 0.3543067123515581, 0.34115548174327476, 0.32615838901690997, 0.30958364737187855, 0.2917230868601803, 0.2728846567480048, 0.2533846643328705, 0.23353994530624714, 0.2136601609403317, 0.19404041270723024, 0.17495435554206734, 0.15664797708855321, 0.13933419227710717, 0.12318838094458523, 0.10834497146359916, 0.09489514613740542, 0.0828857151226152, 0.07231917559914491, 0.06315494257206597, 0.05531170782660779, 0.04867085491548904, 0.0430808313551184, 0.038362355112370315, 0.03431431157844221, 0.030720180071214683, 0.027354815908589163, 0.02399140557359877, 0.020408408655858044, 0.016396301193280494, 0.01176394072287179, 0.0063443836303248465, 6.376729735024142e-17], [-0.0, -0.00837138918069503, -0.01794506351999766, -0.028728913779347786, -0.04068712873452716, -0.05374083708385397, -0.0677699672873754, -0.08261627864973409, -0.09808748624450203, -0.11396237350950948, -0.12999676025311735, -0.14593017106557668, -0.1614930303089888, -0.1764141954470263, -0.1904286308441166, -0.20328501956595652, -0.2147531112754452, -0.22463061003720577, -0.2327494165870257, -0.2389810551305351, -0.24324113462894767, -0.2454927183186686, -0.24574850230738066, -0.24407173381920577, -0.24057583128573873, -0.23542270120929729, -0.22881977974145407, -0.2210158593967479, -0.21229579244303745, -0.20297419149293475, -0.1933882739334503, -0.1838900194115738, -0.17483782806674764, -0.16658788109268402, -0.15948541415928766, -0.15385611799116067, -0.14999787887107732, -0.14817306503480687, -0.14860155299857103, -0.15145467109023192, -0.15685021623877518, -0.1648486749232853, -0.17545075070044305, -0.188596269610117, -0.2041645017599206, -0.22197590331756453, -0.24179524882839407, -0.263336090065931, -0.28626644534364015, -0.3102155931605984, -0.3347818169630911, -0.35954092434733376, -0.38405534478616726, -0.40788359541260444, -0.43058989489877186, -0.4517537012697994, -0.4709789506984676, -0.48790278091557104, -0.50220353468854, -0.5136078555842698, -0.5218967095373545, -0.5269101910766246, -0.5285510018068271, -0.5267865202005751, -0.5216494151638869, -0.5132367903845111, -0.5017078813158339, -0.4872803609433763, -0.47022534339234173, -0.4508612051641778, -0.42954637159238407, -0.40667124030959784, -0.3826494335349839, -0.3579085863414934, -0.3328808883802282, -0.30799360158079325, -0.28365977599907377, -0.26026938026621627, -0.2381810521555597, -0.21771465890644442, -0.19914483652476683, -0.1826956528302679, -0.16853651114844567, -0.15677938094240643, -0.14747740910443868, -0.14062493188338138, -0.1361588733437537, -0.13396148267467642, -0.13386433041508017, -0.13565345352642869, -0.13907551196096837, -0.14384479560605073, -0.14965090080855764, -0.156166880570583, -0.16305766231675217, -0.1699885221005913, -0.176633404349342, -0.1826828817196896, -0.18785156019709204, -0.19188474993852425, -0.19456424213338727, -0.19571305583192583, -0.19519904566066532, -0.19293729092496129, -0.18889121804100956, -0.1830724407497367, -0.1755393353239974, -0.16639440016484006, -0.15578047998457178, -0.14387596342232956, -0.13088908871545532, -0.11705151431397605, -0.10261132952174815, -0.08782569392518466, -0.07295330319179849, -0.05824688257141236, -0.04394590802588491, -0.03026974839142307, -0.017411410512562352, -0.005532053174520822, 0.005243584686484692, 0.014830720078083767, 0.02318693210073636, 0.03031337347824961, 0.03625475403699799, 0.04109809480904088, 0.04497028359552409, 0.0480344942244819, 0.05048556157375437, 0.05254443194640466, 0.05445183288202118, 0.05646132733738705, 0.05883193384025413, 0.06182050628119015, 0.06567407414695273, 0.07062234602445443, 0.07687057605523993, 0.08459298476471884, 0.09392691252478898, 0.1049678661532149, 0.11776559724421086, 0.1323213253031721, 0.14858619025695263, 0.16646098813810148, 0.18579721146374056, 0.2063993828534248, 0.22802863758050881, 0.25040747885202225, 0.27322559946478986, 0.29614663585024587, 0.3188156960962174, 0.34086748294118346, 0.3619348165018248, 0.38165735003710516, 0.39969026567325816, 0.4157127358895708, 0.42943594074078656, 0.4406104401825073, 0.44903271525626265, 0.45455071094141364, 0.4570682367363185, 0.4565481079306787, 0.45301394042295734, 0.4465505440941787, 0.4373028933878911, 0.42547368804315794, 0.4113195510428956, 0.39514594393649194, 0.3773009109597035, 0.35816779203664684, 0.3381570701009942, 0.3176975395897535, 0.29722699991211043, 0.2771826897559722, 0.257991684963673, 0.24006148421025855, 0.22377100280919238, 0.20946218573960515, 0.19743243665583368, 0.1879280405480398, 0.18113873433350525, 0.17719355253812674, 0.17615804503486512, 0.1780329312738381, 0.18275422135811806, 0.19019479951879434, 0.2001674308686009, 0.2124291186082223, 0.22668670694209858, 0.2426035956057714, 0.2598074058259389, 0.27789841535826104, 0.2964585625110693, 0.31506080619091326, 0.3332786213040258, 0.350695406494921, 0.3669135842466888, 0.381563181722034, 0.39430969417426015, 0.4048610509631146, 0.4129735267153035, 0.4184564664122674, 0.42117572251629515, 0.4210557339333288, 0.41808020987335626, 0.41229141568620264, 0.40378809168409346, 0.39272206897858725, 0.3792936776487931, 0.36374607135503784, 0.34635861811539054, 0.3274395287503731, 0.3073179119481639, 0.28633545759186785, 0.2648379576239216, 0.24316687612851406, 0.22165117744934468, 0.20059961311619792, 0.180293655347579, 0.16098124726877575, 0.14287151819015179, 0.12613058688726242, 0.11087854745902179, 0.09718770173197387, 0.08508207010133104, 0.07453817996187143, 0.06548709830772585, 0.05781764348783445, 0.051380681285509815, 0.04599438319243456, 0.04145030065150278, 0.03752008874969822, 0.033962696855947, 0.030531832414938564, 0.026983497803041386, 0.023083398977903805, 0.018614028631215435, 0.013381235576858419, 0.007220105939881982, 7.251809163146902e-17], [-0.0, -0.00943705834156597, -0.020174369176559584, -0.03219638775823626, -0.04544092138753293, -0.059800547663609836, -0.07512531494564173, -0.09122665589430269, -0.10788241311042923, -0.12484284658801055, -0.14183746669509784, -0.15858251435304768, -0.174788892566116, -0.19017034091076526, -0.20445163735331728, -0.21737661001890404, -0.22871574533915656, -0.23827318827636462, -0.24589294483604524, -0.2514641164839994, -0.2549250199006564, -0.2562660731458717, -0.25553136008544747, -0.2528188180806297, -0.2482790286369168, -0.2421126260815788, -0.23456637450444404, -0.22592799727120721, -0.21651987554554378, -0.2066917616252083, -0.1968126787646, -0.18726220086418294, -0.1784213223999574, -0.17066314080434594, -0.16434357988100312, -0.15979238356308223, -0.15730460436998048, -0.15713280038513947, -0.15948013870924097, -0.16449458251403545, -0.17226431353068494, -0.1828145126630051, -0.19610558912701798, -0.21203291386965914, -0.23042807685699823, -0.25106165103073763, -0.2736474092129155, -0.2978479048895879, -0.323281294494405, -0.349529248363337, -0.37614577069427046, -0.4026667262838333, -0.42861985408890163, -0.4535350352135326, -0.47695457606681346, -0.4984432663492109, -0.5175979762394451, -0.5340565675632114, -0.5475059095821629, -0.557688810965739, -0.5644097049944458, -0.5675389544741251, -0.5670156755025101, -0.5628490143288476, -0.5551178482315088, -0.5439689187155077, -0.5296134424929888, -0.5123222817518137, -0.49241978926475694, -0.4702764751182637, -0.4463006694882508, -0.4209293792924287, -0.394618555139777, -0.367832998332247, -0.3410361454348154, -0.3146799699379404, -0.2891952367527943, -0.26498233580792047, -0.24240290609930873, -0.22177244156038914, -0.20335404556452397, -0.1873534723615519, -0.17391556198980498, -0.16312214098205205, -0.15499142534364616, -0.14947892570748417, -0.1464798181632504, -0.14583270891195918, -0.14732468747702224, -0.15069753252665044, -0.15565490717641262, -0.16187035760438487, -0.16899591047957166, -0.17667105151447215, -0.18453185971371652, -0.19222006977573322, -0.19939183864651028, -0.2057260013163718, -0.2109316153471533, -0.21475461294191026, -0.21698340312401573, -0.21745329416977657, -0.2160496371371334, -0.21270962437474666, -0.20742271144628122, -0.20022966609322923, -0.1912202828013956, -0.1805298353541046, -0.16833437160208478, -0.15484498375938982, -0.14030121312093316, -0.12496376955331169, -0.10910676290417892, -0.09300965519199474, -0.0769491487910108, -0.061191226664510434, -0.0459835560101186, -0.03154845659089908, -0.018076619797329184, -0.00572174450950832, 0.005403768383145931, 0.01523194877872831, 0.023741134192596092, 0.030956540208601488, 0.036949508307525615, 0.041835449423100364, 0.0457705357198188, 0.04894722591249917, 0.05158874012095557, 0.05394262799362302, 0.05627359793449677, 0.058855795112328475, 0.061964731010387734, 0.0658690771994479, 0.07082254052549378, 0.07705603587246733, 0.08477036610380238, 0.0941296068581522, 0.10525537686340578, 0.11822215275577379, 0.13305376158219734, 0.14972115486402615, 0.16814153603593146, 0.18817887904521363, 0.20964584075260023, 0.23230703439555864, 0.2558835966460924, 0.28005894758946637, 0.3044856121049134, 0.32879294342335885, 0.35259556577351664, 0.37550233361496593, 0.39712559049422713, 0.4170905014245876, 0.4350442291279739, 0.45066472659520773, 0.4636689261862941, 0.473820118731594, 0.4809343344983955, 0.48488556101738517, 0.4856096600637582, 0.48310687689780374, 0.4774428684411729, 0.46874821257936145, 0.4572163973703073, 0.44310032570735985, 0.42670740702989235, 0.40839334211069034, 0.38855473892790593, 0.36762072636204957, 0.3460437572349592, 0.32428981241391774, 0.302828232837507, 0.2821214160015586, 0.26261461742865294, 0.24472609582691557, 0.22883783305991484, 0.21528704687700873, 0.20435869590742928, 0.1962791531459934, 0.19121119661644256, 0.189250434757621, 0.1904232500938828, 0.1946863087499223, 0.20192764622676643, 0.21196930247300802, 0.22457144257222894, 0.2394378642161466, 0.25622276039687686, 0.2745385762248851, 0.293964773176648, 0.31405729301628804, 0.33435849762487235, 0.354407350392342, 0.37374959992902135, 0.3919477277457903, 0.40859042820162594, 0.4233014012504358, 0.43574725602544373, 0.44564434563898864, 0.45276438019111476, 0.45693869520987757, 0.4580610858404728, 0.45608915224059815, 0.4510441379585247, 0.4430092796735832, 0.43212672266620733, 0.41859309087361285, 0.4026538325336054, 0.3845964914386641, 0.3647430790099762, 0.3434417431476465, 0.32105794562101314, 0.29796537025780956, 0.27453678913091506, 0.25113511322329823, 0.22810484771279685, 0.20576416023525299, 0.18439775356911192, 0.16425071257555618, 0.14552346948008996, 0.12836800235089924, 0.11288534965804704, 0.09912448989443631, 0.08708260025980445, 0.0767066732333093, 0.0678964353722067, 0.06050847973854505, 0.0543614927971626, 0.04924242920994884, 0.04491346435680722, 0.04111953522951014, 0.037596266045595926, 0.03407806586720844, 0.03030618190393743, 0.026036494111439778, 0.02104684411171887, 0.015143704161384238, 0.008168009553076344, 8.19255753374069e-17], [-0.0, -0.010567519544514792, -0.022522578883388062, -0.03582300689672809, -0.0503775027198142, -0.06604791669443551, -0.08265286261392396, -0.09997256773028604, -0.11775483444968642, -0.13572195829441125, -0.15357842130331853, -0.17101915922784636, -0.18773818519096375, -0.20343734231750918, -0.2178349534828566, -0.23067413788386362, -0.24173057158394953, -0.2508194823470922, -0.25780168763378736, -0.2625885081297899, -0.26514541703518857, -0.2654943168660553, -0.2637143699293386, -0.2599413450658128, -0.25436548080533966, -0.24722790280325616, -0.23881567037985804, -0.22945556223750802, -0.21950674409310533, -0.2093524902114898, -0.19939115591518813, -0.19002661843705532, -0.18165841845231617, -0.17467184388397505, -0.1694282008705037, -0.16625551401472966, -0.1654398892459543, -0.16721775802096997, -0.17176920150612215, -0.1792125283005543, -0.18960024978394902, -0.20291656401404431, -0.21907642306619268, -0.23792622067815875, -0.2592460979682122, -0.282753825791483, -0.3081101839511676, -0.33492572093071515, -0.362768743961429, -0.39117435892261815, -0.419654353538813, -0.4477076962365276, -0.4748314073773557, -0.5005315497872286, -0.5243340818027448, -0.5457953185545931, -0.5645117558531739, -0.580129025629938, -0.5923497720710658, -0.600940262872005, -0.6057355798307026, -0.6066432665622734, -0.6036453476438198, -0.5967986720978716, -0.5862335738583264, -0.5721508817678541, -0.5548173507604268, -0.5345596232367104, -0.5117568643363775, -0.48683224600833297, -0.460243481721859, -0.4324726356978837, -0.40401544713988097, -0.3753704207114986, -0.34702793918986413, -0.3194596527154618, -0.29310839140975076, -0.26837883453866823, -0.2456291502080216, -0.22516379526647035, -0.2072276362692776, -0.19200151973706164, -0.17959938433623587, -0.17006696989165124, -0.16338213924725206, -0.15945678987475173, -0.158140293754286, -0.15922436735549217, -0.1624492394297009, -0.16751095361571341, -0.17406961630859985, -0.18175837848449958, -0.19019292373567923, -0.19898122403763427, -0.20773331998987143, -0.2160708835422806, -0.22363632848737955, -0.23010124706401675, -0.23517396953571493, -0.23860606709711374, -0.24019764632280843, -0.23980131489445128, -0.23732473272495574, -0.23273169897381984, -0.22604176289803685, -0.21732838406670324, -0.20671570424083385, -0.19437402826160152, -0.18051414372387625, -0.16538063822802762, -0.14924439787897872, -0.13239449081995472, -0.11512965445201222, -0.09774961423472428, -0.08054646536533988, -0.06379634611748519, -0.04775162325906509, -0.03263379598239742, -0.01862730552912321, -0.0058744136716312925, 0.0055287149650537805, 0.015534623373959812, 0.024145796314613478, 0.031414485041385436, 0.03744112638103299, 0.042371396710012624, 0.04639197714349922, 0.04972514008093815, 0.05262229829709251, 0.05535668523242106, 0.05821535832149255, 0.06149073550949275, 0.0654718880734376, 0.07043582014933983, 0.07663896677472969, 0.08430913774076682, 0.09363812421170283, 0.10477516916022507, 0.11782148157419087, 0.13282594863324187, 0.1497821702705076, 0.168626907465034, 0.1892400000782949, 0.21144577294027264, 0.235015911135182, 0.2596737479803869, 0.285099872975158, 0.3109389329304285, 0.3368074684368422, 0.3623026005727422, 0.38701135999039293, 0.4105204328308568, 0.4324260857641492, 0.4523440261530273, 0.46991895307306053, 0.48483356071555944, 0.49681676743064546, 0.5056509610643247, 0.5111780738943377, 0.5133043278318067, 0.5120035219687286, 0.5073187692528308, 0.49936262621611227, 0.48831559836418625, 0.4744230431034416, 0.45799053097860826, 0.43937776355867125, 0.4189911816193891, 0.3972754294548796, 0.37470386941359624, 0.3517683643950161, 0.3289685644751276, 0.30680094659055834, 0.2857478629812281, 0.2662668546945632, 0.24878048086632387, 0.23366690284199004, 0.22125144476460692, 0.21179932944884303, 0.20550976073682348, 0.20251149175794964, 0.20285998336277822, 0.2065362193237499, 0.21344720560859684, 0.22342814109063547, 0.23624620743486202, 0.2516058875529587, 0.2691556858854781, 0.2884960907227548, 0.3091885896185138, 0.3307655243870131, 0.3527405527983603, 0.3746194703620249, 0.3959111378416117, 0.4161382585537423, 0.4348477540984435, 0.45162049782403774, 0.4660801817741275, 0.47790111468390384, 0.48681477524256694, 0.49261497565524015, 0.49516152475713965, 0.49438231670845045, 0.4902738097224601, 0.4828998984053849, 0.4723892221518002, 0.4589309896909274, 0.4427694353943848, 0.4241970554681822, 0.40354680086961203, 0.38118342801755883, 0.3574942275196044, 0.3328793647648599, 0.30774207400952913, 0.282478949340128, 0.25747057161414816, 0.233072700276995, 0.20960824311090334, 0.18736019589977798, 0.16656571823611221, 0.1474114819102165, 0.13003039526508955, 0.11449977140909257, 0.10084097114915958, 0.08902051387188857, 0.07895261230435066, 0.07050305106606462, 0.06349429508012576, 0.05771168309047751, 0.05291053450217578, 0.04882397519432798, 0.04517127041027645, 0.0416664407387972, 0.03802693085825313, 0.033982100272660125, 0.02928131072589608, 0.023701396190840877, 0.017053318002497243, 0.00918782940933569, 9.197564447401809e-17], [-0.0, -0.011758922441247889, -0.024979730667188234, -0.03959069450641239, -0.055469010964131545, -0.07244402449218884, -0.09030181057084419, -0.10879100302229412, -0.12762971272878013, -0.1465133565489477, -0.1651231909515666, -0.18313532583702644, -0.20022998068427952, -0.21610073789072998, -0.23046354715931155, -0.24306524006777833, -0.253691325408866, -0.2621728532398992, -0.2683921584014291, -0.27228732199329586, -0.2738552212456267, -0.2731530735971485, -0.27029841871184423, -0.2654675216800462, -0.25889222077232354, -0.2508552828375719, -0.24168436776206303, -0.23174473936819262, -0.22143089282160466, -0.2111572972042801, -0.20134847567055641, -0.1924286639231801, -0.18481130015177888, -0.17888860573718274, -0.17502151576694006, -0.17353021171457023, -0.17468549565163424, -0.1787012263882442, -0.1857280134239917, -0.19584833512561395, -0.20907321384212568, -0.22534054354117344, -0.2445151259069032, -0.2663904296486795, -0.29069204604059823, -0.31708277246843813, -0.34516921601772066, -0.3745097718732702, -0.40462379743692023, -0.4350017734435835, -0.4651162187017555, -0.494433106016211, -0.522423513845821, -0.5485752416367911, -0.5724041167240745, -0.5934647272226156, -0.6113603282859271, -0.6257516881848424, -0.6363646653964418, -0.6429963376954849, -0.6455195383869197, -0.6438856924804066, -0.638125885871847, -0.6283501424844944, -0.6147449268151393, -0.5975689313961517, -0.577147249299386, -0.5538640699863925, -0.5281540716242272, -0.5004927135934524, -0.4713856585739939, -0.44135757368657236, -0.4109405742102337, -0.38066258105661926, -0.3510358642821862, -0.3225460394447706, -0.295641771706045, -0.2707254245493463, -0.24814486627596635, -0.228186618653426, -0.21107049893204605, -0.1969458697424069, -0.18588957204340764, -0.17790557527888712, -0.1729263372298903, -0.1708158247435998, -0.17137410659160887, -0.17434339213652217, -0.17941535518354468, -0.186239552196838, -0.19443271869977494, -0.20358870776346244, -0.2132888204925924, -0.22311227066777584, -0.23264652436949262, -0.24149726050172304, -0.24929770950469904, -0.2557171448921059, -0.2604683251165999, -0.26331371107070384, -0.26407031655831376, -0.26261308451200477, -0.2588767196865635, -0.25285594807227174, -0.24460421334830834, -0.23423086033080226, -0.2218968935684351, -0.207809435045515, -0.19221503747439905, -0.17539203808599826, -0.1576421614529322, -0.13928159812025778, -0.12063179822514143, -0.10201022555806993, -0.08372131750737068, -0.06604789004714795, -0.04924321454517405, -0.03352397500393702, -0.019064290872357885, -0.005990962378337894, 0.005619936847736596, 0.01574503044190733, 0.024414121479572976, 0.03170917331102688, 0.03776181549500427, 0.04274943987493819, 0.046889988803789445, 0.050435571897035784, 0.05366507860519845, 0.05687598055945151, 0.060375539375308734, 0.0644716518426809, 0.06946357476607033, 0.07563277587497311, 0.08323415508556951, 0.09248787200266584, 0.1035720011050727, 0.11661621591013817, 0.13169667805978513, 0.14883227733845358, 0.16798233486615444, 0.1890458449483198, 0.2118622922257447, 0.23621404082404768, 0.2618302521536213, 0.2883922488636021, 0.31554020519216425, 0.3428810095204302, 0.3699971142002348, 0.39645616146788093, 0.4218211531482635, 0.44566091644058553, 0.4675606087622147, 0.4871320016638951, 0.5040232873131875, 0.5179281609092059, 0.5285939484174529, 0.5358285708224109, 0.5395061631670127, 0.5395711983299956, 0.536041001016804, 0.5290065759427431, 0.5186317147286787, 0.5051503876175965, 0.48886246773486586, 0.470127876233591, 0.449359275288905, 0.4270134715791979, 0.40358172473624937, 0.37957918247140765, 0.35553368601486174, 0.33197420559246343, 0.3094191755050113, 0.2883650017166513, 0.26927501161000766, 0.2525691057947157, 0.23861435579260862, 0.22771676945054536, 0.2201144185795854, 0.2159720912478513, 0.21537759514091176, 0.21833979932168168, 0.22478846052085824, 0.23457583777005955, 0.24748005678187762, 0.26321014401483755, 0.2814126108444697, 0.30167943165406574, 0.3235572268483259, 0.34655743357474805, 0.37016722399306706, 0.39386091381469046, 0.4171115929506794, 0.4394027057146172, 0.4602393102221458, 0.47915875534712676, 0.49574052861045953, 0.5096150493125455, 0.5204712075506712, 0.5280624808325507, 0.532211495036504, 0.5328129346101057, 0.5298347472009608, 0.5233176293824392, 0.5133728217537381, 0.5001782824359602, 0.4839733468559645, 0.46505201775786326, 0.4437550617300291, 0.42046111639859707, 0.3955770351442653, 0.36952771320463484, 0.34274564992818457, 0.31566050649952293, 0.28868891656758866, 0.2622247989480095, 0.2366304071649126, 0.21222833042503653, 0.18929463519978224, 0.16805330657967374, 0.14867211472431568, 0.13125999491709434, 0.11586599087723322, 0.10247977106131438, 0.0910336877054138, 0.08140630932046299, 0.07342732023472076, 0.06688364650582677, 0.06152663695540984, 0.057080101971910914, 0.05324899172939805, 0.0497284800997319, 0.04621321116852664, 0.04240646212668431, 0.03802897946688829, 0.032827254777938054, 0.02658102175287591, 0.019109776913472185, 0.010278152468059014, 1.0264357380419932e-16], [-0.0, -0.013006337911899372, -0.027533832656255065, -0.04347857356472338, -0.06068424139506597, -0.0789463333179955, -0.0980177645061206, -0.11761569939039913, -0.1374294332188615, -0.1571291166843752, -0.17637509379460592, -0.19482760641741032, -0.21215660848103202, -0.22805142891512725, -0.2422300251954163, -0.2544475787434987, -0.26450419920953416, -0.27225152644360306, -0.2775980462046978, -0.28051296768943423, -0.28102854698925567, -0.279240779707093, -0.2753084272048365, -0.2694503832793025, -0.2619414304151926, -0.253106476074625, -0.24331339871377805, -0.23296466937744886, -0.22248794689591944, -0.21232587207697493, -0.2029253081488726, -0.1947262905028272, -0.18815095809142907, -0.1835927414081435, -0.18140607771545514, -0.18189691318772452, -0.18531423413939577, -0.19184284593167894, -0.20159758905478567, -0.21461914796982792, -0.2308715703870427, -0.25024157367814437, -0.2725396720713115, -0.2975031142118529, -0.32480057667132284, -0.3540385161348922, -0.3847690423466971, -0.4164991364492027, -0.44870100604143687, -0.48082333992829995, -0.5123032028444803, -0.5425782939788016, -0.5710992833132392, -0.5973419368772193, -0.6208187460856405, -0.641089787289982, -0.6577725552688152, -0.6705505381967326, -0.6791803310862456, -0.6834971190840238, -0.6834184004880617, -0.6789458610024326, -0.6701653545496793, -0.6572449908532199, -0.6404313748921128, -0.6200440871269206, -0.5964685350338564, -0.5701473449535831, -0.5415704976274521, -0.5112644402251649, -0.4797804314522821, -0.44768239389130055, -0.41553455865617295, -0.3838891914703468, -0.35327468632499476, -0.32418430302065737, -0.2970658083947191, -0.2723122583042284, -0.250254129036411, -0.23115297346338978, -0.21519673976995182, -0.20249684989005298, -0.193087091893227, -0.18692433652220652, -0.1838910439803532, -0.1837994839837788, -0.18639755108291176, -0.19137601932308135, -0.19837704637680623, -0.20700370816460592, -0.2168303213881198, -0.2274132938928646, -0.23830223177001422, -0.24905102784726593, -0.2592286587904935, -0.2684294273533649, -0.27628240211700705, -0.28245982894139826, -0.28668431573945974, -0.28873462438333636, -0.2884499397412542, -0.2857325251063871, -0.28054871462544195, -0.2729282357233137, -0.26296189688666405, -0.25079771745160806, -0.2366356152062496, -0.22072080368969582, -0.20333608314695806, -0.18479323638681674, -0.1654237626117871, -0.14556919810837465, -0.12557128211587923, -0.10576222900811533, -0.08645536406598188, -0.067936369698989, -0.05045537226479362, -0.03422007706943758, -0.01939013128642381, -0.006072862121415849, 0.005679498602800282, 0.015871031239568626, 0.02456175509194761, 0.0318656753664781, 0.037947301842603136, 0.04301673081704853, 0.04732341957780865, 0.05114881707092859, 0.054798044669195356, 0.05859084626375213, 0.06285204662998697, 0.06790177066036615, 0.07404568325465048, 0.08156551021951076, 0.09071009442910541, 0.10168722887749317, 0.1146564894187648, 0.1297232654041206, 0.14693415669466736, 0.1662738713924795, 0.18766372094034808, 0.21096176893327515, 0.2359646480700165, 0.2624110172010401, 0.2899865884662664, 0.3183306141175025, 0.3470436848052958, 0.3756966568341625, 0.40384049602392874, 0.43101680111986723, 0.4567687508050985, 0.48065220577653395, 0.5022466913860624, 0.5211659871929244, 0.5370680574237872, 0.5496640706271972, 0.5587262774069659, 0.5640945415354022, 0.5656813513476936, 0.5634751743386937, 0.557542057447524, 0.5480254176586844, 0.5351440112400369, 0.519188114106907, 0.5005139893625683, 0.4795367599464309, 0.45672184348940476, 0.4325751419636246, 0.40763220964196417, 0.382446648483536, 0.3575779996964063, 0.3335794134055028, 0.31098538473759174, 0.29029984405789616, 0.2719848815571801, 0.25645037206679805, 0.24404474521223815, 0.2350471193011254, 0.22966098532371487, 0.22800959089717432, 0.23013313379538206, 0.23598783184910638, 0.24544689151842639, 0.258303352411263, 0.27427474054358725, 0.29300942028931465, 0.3140944947921775, 0.3370650680833825, 0.36141465015332974, 0.3866064595374438, 0.41208535723913287, 0.4372901315249879, 0.46166584562763163, 0.4846759598532164, 0.5058139460153118, 0.5246141253362047, 0.5406614806353898, 0.5536002192702157, 0.5631408942666314, 0.5690659266099236, 0.5712334108772128, 0.569579128316828, 0.5641167350813562, 0.554936137528509, 0.542200110231498, 0.5261392545168038, 0.5070454349408942, 0.4852638671632967, 0.46118406229567643, 0.43522985924067925, 0.40784879714541566, 0.37950109439344293, 0.3506485082136843, 0.32174334982846775, 0.29321792409798236, 0.2654746500163473, 0.2388770995109058, 0.21374216728251666, 0.1903335545354552, 0.16885671514303188, 0.14945537494934494, 0.13220969447552333, 0.11713610329923535, 0.10418879186522868, 0.09326280452882756, 0.08419863728422561, 0.0767882058934555, 0.07078201595119422, 0.06589733664547644, 0.061827155343426324, 0.05824967125265709, 0.05483807374612832, 0.051270344797419695, 0.04723882549677325, 0.04245929378051056, 0.0366793141152557, 0.02968563957962886, 0.02131047207260362, 0.011436416602252895, 1.1389416848591065e-16], [-0.0, -0.01430380575772152, -0.030170990165832707, -0.047463201519106345, -0.06598901275316961, -0.08550920397669608, -0.10574341473458106, -0.12637799077989825, -0.14707481856810253, -0.16748091439058438, -0.18723851470878553, -0.20599540035795555, -0.22341518022218282, -0.23918725992897297, -0.2530362280853917, -0.2647304064148345, -0.2740893305171598, -0.2809899543639742, -0.28537140340184797, -0.28723813747974936, -0.2866614248372377, -0.28377907108730804, -0.2787933914336594, -0.2719674591656408, -0.26361970764967785, -0.2541170054715131, -0.24386636400827041, -0.23330547252036776, -0.22289228694096072, -0.21309392411118738, -0.20437513260511062, -0.19718662400362158, -0.19195355417154034, -0.18906444260070254, -0.1888608092162707, -0.1916277923945603, -0.19758598967292854, -0.2068847342754483, -0.2195969868141326, -0.23571598317182849, -0.25515373756251813, -0.2777414551230678, -0.30323186221016635, -0.33130341599025825, -0.3615663090640048, -0.39357014088946884, -0.4268130867452396, -0.4607523579204725, -0.4948157146521101, -0.5284137668499717, -0.5609527775193017, -0.5918476705137956, -0.620534938168476, -0.6464851456332675, -0.66921473733649, -0.6882968667545664, -0.7033709931763666, -0.7141510178880752, -0.7204317664744004, -0.7220936629054424, -0.7191054838110058, -0.7115251267984064, -0.6994983737417181, -0.683255677515845, -0.6631070475119334, -0.639435154312347, -0.6126868160291437, -0.5833630669969145, -0.5520080428327654, -0.5191969435264819, -0.48552335753521275, -0.45158624431746014, -0.41797688000748257, -0.38526607083599784, -0.3539919314602203, -0.3246485107689229, -0.2976755263454232, -0.2734494411375757, -0.25227608268640184, -0.2343849673266638, -0.21992545003145195, -0.2089647760585394, -0.20148806436506017, -0.19740020602451788, -0.1965296147528823, -0.19863372225819118, -0.20340606955520563, -0.210484807646153, -0.21946238797660292, -0.22989619562913283, -0.241319856974866, -0.253254938967823, -0.2652227497755907, -0.2767559501535801, -0.28740969187138027, -0.29677201339283177, -0.30447324352766936, -0.31019419037951423, -0.3136729249302556, -0.3147100052088956, -0.31317202726593885, -0.3089934320951377, -0.30217654213204276, -0.29278984589555324, -0.28096459359801723, -0.2668898090239685, -0.25080586260677795, -0.23299678642894583, -0.21378154294588275, -0.19350448481502175, -0.17252526267118704, -0.15120845054903065, -0.12991316460407917, -0.10898294968947912, -0.08873620024695929, -0.06945736708491365, -0.051389180331348525, -0.03472609171276923, -0.019609107016758182, -0.006122142970137682, 0.005709997261131737, 0.01592197815188872, 0.024606607391421276, 0.031911868771478134, 0.03803639119574515, 0.0432234735923851, 0.04775382343271294, 0.05193720046313535, 0.056103186280633634, 0.06059132378330781, 0.0657408877070847, 0.07188055797408226, 0.07931827115128366, 0.08833152184858022, 0.09915837544847515, 0.11198943640683576, 0.1269609929152873, 0.1441495295502894, 0.16356776537532622, 0.18516233666120743, 0.20881320190087338, 0.23433480315676053, 0.261478973083718, 0.28993953234060493, 0.3193584786611467, 0.34933362769445425, 0.3794275278878039, 0.409177438128049, 0.438106128437962, 0.46573324146771056, 0.49158693641329265, 0.5152155277568842, 0.5361988291128309, 0.5541589175543639, 0.5687700459884337, 0.5797674501606728, 0.5869548222610619, 0.590210254255546, 0.5894904902377559, 0.5848333674001313, 0.5763583686829672, 0.5642652557108233, 0.5488307971521276, 0.5304036539968802, 0.5093975282984565, 0.48628272455770627, 0.4615763120877175, 0.4358311114162379, 0.40962375719776845, 0.38354211348626616, 0.35817233397637305, 0.33408586953292785, 0.31182672774379994, 0.2918992842777877, 0.27475693361596193, 0.2607918475380257, 0.2503260840433641, 0.24360425778735803, 0.2407879463807432, 0.24195196592254772, 0.24708260490957362, 0.2560778592613365, 0.26874966374654, 0.28482806774896724, 0.303967257218257, 0.32575328093454914, 0.34971329893755165, 0.3753261351075316, 0.4020338853073329, 0.42925430793994923, 0.4563937058367552, 0.4828599974963568, 0.5080756720989859, 0.5314903265036289, 0.5525924934907128, 0.5709204885601687, 0.5860720271799073, 0.5977123948904363, 0.6055809883499911, 0.6094960853680778, 0.6093577452368176, 0.6051487861625626, 0.5969338332056171, 0.584856476708918, 0.5691346265955447, 0.5500541910294069, 0.5279612477114694, 0.5032529115578669, 0.47636713281699883, 0.4477716841003068, 0.4179526127431837, 0.3874024459571766, 0.3566084401326383, 0.32604116233027197, 0.2961436815675216, 0.267321630244628, 0.2399343724175004, 0.214287486219484, 0.19062673331312635, 0.16913364969055117, 0.14992285041250106, 0.1330410970340366, 0.11846813161183732, 0.10611923644986429, 0.09584943523713925, 0.08745921005106812, 0.08070157086912459, 0.07529028069233139, 0.07090901096805392, 0.06722117940964738, 0.06388020610172072, 0.060539914346536494, 0.05686480027303037, 0.05253989984271976, 0.047279993416877907, 0.04083790619353213, 0.03301168711185674, 0.02365047863193133, 0.012658924367792326, 1.2568205290437706e-16], [-0.0, -0.01564439621961945, -0.03287555871959342, -0.05151884074455709, -0.07134657604801083, -0.09208445802681911, -0.11341926037397883, -0.13500769520603795, -0.15648617449455368, -0.1774812164770758, -0.1976202211611119, -0.21654232851752275, -0.23390906976387182, -0.2494145263553873, -0.26279472283683447, -0.27383599828390254, -0.28238212622140585, -0.28833998402523225, -0.29168360912233693, -0.2924565198934687, -0.29077222304293926, -0.2868128752310514, -0.28082611381376343, -0.2731201184190812, -0.26405701063065823, -0.2540447420975377, -0.24352766085628363, -0.23297598053656413, -0.2228744065345523, -0.21371019642596437, -0.20596094825147362, -0.20008241940982222, -0.19649668048622748, -0.19558090236011805, -0.1976570614995697, -0.20298282776841178, -0.21174387183230325, -0.22404779600503666, -0.23991985392920323, -0.2593005817701571, -0.28204541766073155, -0.307926338090247, -0.3366354909632439, -0.3677907563646717, -0.40094311885790473, -0.43558569057507235, -0.4711641835375704, -0.5070885935801056, -0.5427458278404533, -0.5775129837779589, -0.6107709706989305, -0.6419181552268551, -0.6703837103084199, -0.6956403532519234, -0.7172161718225798, -0.7347052582513783, -0.747776898653458, -0.7561830991336495, -0.7597642689651801, -0.7584529247156616, -0.7522753260076296, -0.7413510026024113, -0.7258901824952323, -0.7061891804908292, -0.6826238550820897, -0.655641287204081, -0.6257498764706753, -0.5935080878005158, -0.5595121129990456, -0.5243827371182186, -0.48875171765661957, -0.4532479954539204, -0.4184840592211644, -0.38504278096773986, -0.3534650272627891, -0.32423833161611, -0.2977868867735952, -0.27446308305410133, -0.25454078081846604, -0.2382104626974201, -0.22557636536144593, -0.21665564252098662, -0.2113795616824978, -0.20959668816110502, -0.21107796216512195, -0.21552352958701557, -0.22257114556123092, -0.2318059328920527, -0.24277124600887898, -0.2549803659283731, -0.26792873339299983, -0.2811064163423394, -0.2940105044047801, -0.3061571272328653, -0.3170928051172843, -0.32640485908888706, -0.3337306331646224, -0.3387653128570836, -0.34126816074525057, -0.34106703086530754, -0.3380610678895874, -0.3322215434048215, -0.3235908289132298, -0.31227955227502524, -0.2984620300102182, -0.2823701110397809, -0.264285606995775, -0.2445315191836645, -0.22346230177149146, -0.20145342408181224, -0.17889051140169726, -0.1561583531025353, -0.1336300688540452, -0.11165671829069981, -0.09055762679500741, -0.07061168043449387, -0.05204981703560329, -0.03504890856686592, -0.01972719324881087, -0.006141375046193208, 0.005714535533530956, 0.01590861100128566, 0.024568644762748077, 0.03187810108049183, 0.03807048506877522, 0.04342228208397327, 0.048244653476999015, 0.05287410850796829, 0.05766239945097905, 0.06296590784218363, 0.06913480390968843, 0.07650226810343898, 0.08537406313253339, 0.09601873701763924, 0.10865872256461426, 0.12346257673076841, 0.14053857512847912, 0.15992984309208572, 0.18161116616473702, 0.2054875805043742, 0.2313947986212627, 0.2591014791728147, 0.28831330242629327, 0.3186787666409537, 0.3497965761860833, 0.3812244508223921, 0.41248914827959743, 0.44309746001087114, 0.47254791361954046, 0.500342895614523, 0.526000895376427, 0.5490685658490465, 0.5691322986703607, 0.5858290211944779, 0.598855939915072, 0.6079789787831026, 0.6130396912455776, 0.6139604607874435, 0.6107478454641196, 0.603493966376669, 0.5923758871790623, 0.5776529803627357, 0.5596623250431181, 0.5388122290709566, 0.5155740143224389, 0.4904722468493424, 0.46407363213342184, 0.4369748290313208, 0.40978946328706733, 0.38313464204631614, 0.35761728411187244, 0.3338205863931974, 0.3122909449690702, 0.29352563943779497, 0.27796157199846316, 0.26596532839826, 0.2578247970775941, 0.25374254628936577, 0.25383111754501225, 0.2581103484519582, 0.2665067899538578, 0.27885523333385576, 0.29490231229877223, 0.3143120962452213, 0.3366735436138099, 0.36150964021155246, 0.3882880075948471, 0.4164327320209866, 0.4453371359326921, 0.47437719212678764, 0.5029252661988256, 0.5303638658964644, 0.5560990768148782, 0.5795733723971731, 0.6002775022414683, 0.6177611858601736, 0.631642368708548, 0.6416148327618845, 0.6474539942958871, 0.6490207658154349, 0.6462634061915195, 0.6392173318451139, 0.6280029110619371, 0.6128213120259869, 0.5939485217353819, 0.5717276964742661, 0.5465600439000526, 0.5188944711106487, 0.4892162614534926, 0.4580350646470035, 0.42587249948914746, 0.39324967568835223, 0.360674941014331, 0.32863215206518315, 0.2975697517037298, 0.2678909140337838, 0.23994498924056287, 0.21402044643980353, 0.19033947373724208, 0.16905435198009347, 0.15024567326297242, 0.1339224282755156, 0.12002393922685609, 0.10842356853936261, 0.09893408893422707, 0.09131455904645921, 0.085278511339224, 0.08050322676489739, 0.0766398441423736, 0.07332403223884061, 0.0701869395473483, 0.06686613105094902, 0.06301622298832793, 0.05831893572633496, 0.05249230105842014, 0.04529878316251647, 0.03655210147727289, 0.026122578148348688, 0.013940871578885045, 1.3795209405752768e-16], [-0.0, -0.017020284662137737, -0.035630321304380486, -0.05561776157230751, -0.07671806099932178, -0.09862197899210992, -0.12098436987428275, -0.1434340320098636, -0.16558435392313897, -0.18704447489312015, -0.2074306632800015, -0.22637760920661398, -0.24354932934824886, -0.2586493904622973, -0.27143017470278996, -0.281700933312111, -0.2893344053809441, -0.2942718142703542, -0.2965260951023471, -0.29618325142802926, -0.2934017866570423, -0.28841020488817304, -0.28150262518703617, -0.273032601869508, -0.2634052897461388, -0.25306813639059084, -0.2425003222216245, -0.23220120254792703, -0.22267803286473295, -0.21443327891080796, -0.20795182576506882, -0.203688405239654, -0.20205555785966697, -0.20341243485565214, -0.20805472707621103, -0.21620598198897595, -0.2280105375927144, -0.24352826389131305, -0.2627312595077043, -0.2855026040919347, -0.3116372175496524, -0.34084482600188093, -0.3727549830399521, -0.4069240445251552, -0.44284394714232106, -0.47995259633782394, -0.5176456292599618, -0.5552892838672139, -0.5922340773365751, -0.6278289759920465, -0.6614357257108372, -0.692443006492777, -0.720280077741928, -0.7444295917539359, -0.7644392716751872, -0.7799321763550748, -0.7906153074235632, -0.7962863527997344, -0.7968384047330425, -0.7922625383339331, -0.7826481872029392, -0.7681813049869367, -0.749140354208663, -0.7258902152540165, -0.6988741577079192, -0.6686040621052289, -0.6356491214938109, -0.6006232879895764, -0.5641717588711876, -0.5269568190058027, -0.4896433709821149, -0.45288449090617605, -0.4173073462388604, -0.38349980237051334, -0.35199802708675343, -0.3232753771195544, -0.29773281922166955, -0.27569110043752826, -0.2573848394039878, -0.24295866365680407, -0.2324654681975481, -0.22586681921348614, -0.22303547510048558, -0.2237599460841973, -0.227750965011296, -0.2346496964792283, -0.2440374704944017, -0.2554467912883487, -0.26837334263666834, -0.2822886887173938, -0.29665335474068394, -0.3109299646209103, -0.3245961139906046, -0.3371566658210053, -0.3481551725668096, -0.35718415265422265, -0.3638939796635305, -0.3680001789389604, -0.3692889676649242, -0.3676209196335921, -0.36293268385492855, -0.35523673562163277, -0.3446191883972917, -0.3312357437009477, -0.3153059027962314, -0.2971056072957612, -0.2769585146849216, -0.2552261482889155, -0.23229718852504427, -0.20857619272706682, -0.18447204390233404, -0.16038643417281367, -0.13670268623907922, -0.11377520606886214, -0.09191984241980661, -0.07140540421760651, -0.0524465558591762, -0.03519827398870778, -0.01975200813472996, -0.006133642846981377, 0.005696688228912398, 0.01584293435398856, 0.024469652265689847, 0.031796817070966966, 0.0380930580764295, 0.043667499478778106, 0.04886042255030347, 0.054032997133383304, 0.05955635510932111, 0.06580029639420586, 0.07312192847652031, 0.0818545432734022, 0.09229703006390182, 0.10470411057322757, 0.11927766223983406, 0.13615936879081061, 0.1554249041471939, 0.17707981720308885, 0.20105724213073195, 0.22721751263009773, 0.25534971012424523, 0.2851751265152419, 0.3163525730013091, 0.3484854188509338, 0.3811301991353299, 0.4138065893731657, 0.4460085088830233, 0.4772160842918917, 0.5069081808914081, 0.5345751929836434, 0.5597317754532223, 0.5819291977906426, 0.6007670087254227, 0.61590371436175, 0.6270661949042513, 0.6340576141914904, 0.6367636116208419, 0.6351566067949371, 0.6292980923562917, 0.6193388389012211, 0.6055169863912637, 0.5881540478699733, 0.5676489022811617, 0.5444699025146773, 0.5191452712595311, 0.4922519996717819, 0.4644035012136265, 0.43623630436132793, 0.40839609242973895, 0.3815234159033977, 0.356239411962114, 0.333131867099263, 0.312741951807844, 0.29555194140722, 0.28197421455252136, 0.2723417913466427, 0.26690063697405375, 0.26580391526525066, 0.2691083305857631, 0.2767726470399743, 0.2886584223873029, 0.3045329415401574, 0.3240742823265654, 0.34687839562431194, 0.37246803423750335, 0.4003033211505453, 0.4297937091207683, 0.46031105089684715, 0.49120347346654686, 0.5218097312679654, 0.5514737026853381, 0.5795586916431675, 0.6054612017612644, 0.6286238641892117, 0.6485472215564212, 0.6648000989206124, 0.6770283274663531, 0.6849616271329192, 0.6884184993384213, 0.6873090294059232, 0.6816355489951171, 0.6714911605544445, 0.6570561772651019, 0.6385925818904634, 0.6164366551520649, 0.5909899675761493, 0.5627089671406528, 0.5320934275731306, 0.49967404802381415, 0.465999513449137, 0.43162333595448993, 0.39709080031723604, 0.3629263318953654, 0.32962159227509785, 0.2976245876673309, 0.26733004775829644, 0.23907129915604727, 0.21311381860686504, 0.18965060777256934, 0.16879948465666195, 0.15060233791998898, 0.13502634056208943, 0.12196707000935518, 0.11125343378181912, 0.10265425480112099, 0.09588632917618753, 0.09062373298408423, 0.08650812405053347, 0.08315976077977738, 0.08018894327330979, 0.07720757271786248, 0.07384052353128505, 0.069736529051637, 0.06457829546537458, 0.05809157982931355, 0.05005299590065647, 0.04029634533442234, 0.02871731077278408, 0.015276390442690893, 1.5063995523025282e-16], [-0.0, -0.018422838601824258, -0.03841668785720666, -0.05973057440279993, -0.08206295490209783, -0.10507034546581318, -0.12837716880915562, -0.15158655755614087, -0.17429182660770526, -0.19608830933506594, -0.21658524201028057, -0.23541737861382667, -0.2522560240325134, -0.26681918754339046, -0.2788805800319918, -0.28827720708431004, -0.29491534520913754, -0.29877472911608927, -0.2999108231791563, -0.298455098824938, -0.2946132903803042, -0.2886616536207174, -0.28094130257723127, -0.271850749794024, -0.2618368219256407, -0.2513841651413206, -0.24100359218092945, -0.23121955412891013, -0.22255704423689657, -0.2155282578017145, -0.21061934075092206, -0.20827755995951489, -0.2088992203812579, -0.21281863799546055, -0.2202984537169746, -0.23152154235993064, -0.2465847332305642, -0.2654945158598174, -0.2881648568202776, -0.31441720266638595, -0.34398269103894313, -0.3765065381864682, -0.41155451790090264, -0.448621395457198, -0.4871411318559133, -0.5264986296915659, -0.566042753398931, -0.6051003244258748, -0.64299076685027, -0.6790410617306639, -0.7126006594953684, -0.7430559991699233, -0.769844291248348, -0.7924662373494586, -0.8104973840820118, -0.8235978401916603, -0.8315201243180103, -0.8341149546277409, -0.8313348401462671, -0.8232353856081812, -0.809974275823175, -0.791807960592763, -0.7690861157757632, -0.7422440088603027, -0.7117929470742218, -0.6783090314467201, -0.642420480219764, -0.604793818628202, -0.5661192585088555, -0.5270956098235124, -0.488415076542493, -0.45074829119113125, -0.41472993567605987, -0.38094528095600966, -0.34991795508209445, -0.3220992186797329, -0.2978589898340754, -0.27747881749081493, -0.2611469549521566, -0.2489556340040397, -0.24090058691089253, -0.2368828092665693, -0.23671250282444242, -0.24011508526361527, -0.2467391046554661, -0.25616585137309206, -0.2679204204284384, -0.28148394368867613, -0.296306684919949, -0.31182167176282155, -0.3274585279990005, -0.34265716706132837, -0.3568810137000585, -0.3696294348721964, -0.3804490828887885, -0.38894388306627364, -0.39478343383259246, -0.39770962852763203, -0.3975413539647438, -0.39417717002928476, -0.38759592594331765, -0.3778553210342258, -0.36508846960192676, -0.349498579491459, -0.3313519009982518, -0.31096914559270644, -0.2887156115856938, -0.2649902853365818, -0.24021421115584016, -0.21481844007519799, -0.1892318767397949, -0.1638693446083728, -0.13912018242384822, -0.11533766973684775, -0.09282955652785685, -0.07184994226777996, -0.05259271384491662, -0.035186710586762475, -0.01969273916823396, -0.006102512680224785, 0.00566046223293889, 0.01573807719238211, 0.024332970094488926, 0.03170215475664159, 0.038149102631557234, 0.04401448764510501, 0.049665840436452384, 0.055486387208095955, 0.06186337028805555, 0.0691761618053787, 0.07778448821230119, 0.08801708158147754, 0.10016106369898624, 0.1144523512017105, 0.13106734480777116, 0.15011613368497106, 0.1716374079906337, 0.1955952295448957, 0.22187776354516622, 0.25029802437051235, 0.28059663711202054, 0.3124465647908218, 0.34545970059031045, 0.37919517611067793, 0.41316919187404344, 0.4468661362030543, 0.4797507241861866, 0.5112808606100023, 0.5409209102013259, 0.5681550458185646, 0.5925003407054841, 0.6135192747135243, 0.6308313364442806, 0.6441234232907043, 0.6531587688933259, 0.6577841619180984, 0.6579352604754136, 0.6536398519541848, 0.6450189574322794, 0.6322857319365497, 0.6157421653840306, 0.595773642723439, 0.5728414742901272, 0.5474735573919162, 0.5202533764205445, 0.49180759018613707, 0.4627924906702129, 0.43387964610061497, 0.40574106244858643, 0.37903421059743403, 0.35438727119408436, 0.3323849454353192, 0.31355516783471143, 0.2983570366467444, 0.2871702495749401, 0.280286297332977, 0.27790162640678057, 0.2801129359780045, 0.2869147235392292, 0.2981991404823991, 0.31375816416803926, 0.33328803801509793, 0.35639587732642897, 0.3826082871918222, 0.4113817911382571, 0.44211482638381255, 0.4741610246368994, 0.5068434672607112, 0.5394695810220203, 0.5713463261072149, 0.6017953219624705, 0.6301675589389903, 0.6558573546279329, 0.6783152328758006, 0.697059430301099, 0.711685769019948, 0.7218756743927317, 0.7274021619350376, 0.7281336669766753, 0.7240356429854288, 0.7151699084118697, 0.7016917761346354, 0.6838450527643752, 0.6619550458993331, 0.6364197646767988, 0.6076995414834949, 0.5763053394445803, 0.5427860404195969, 0.5077150309746027, 0.4716764186368097, 0.4352512173312352, 0.39900383911337883, 0.3634692192198018, 0.3291408833381841, 0.29646024032596496, 0.2658073510447282, 0.23749338535823455, 0.21175493564577977, 0.18875030751420976, 0.16855785795225178, 0.15117639922698978, 0.13652763467647286, 0.12446054150855344, 0.11475756704813021, 0.10714245979496723, 0.10128951628205021, 0.09683399005996655, 0.09338338103137869, 0.09052930251066611, 0.08785961029375192, 0.08497047300313802, 0.08147806613146855, 0.07702958344631629, 0.07131327843928055, 0.06406727480880185, 0.055086917880533375, 0.04423047754848258, 0.03142305677696072, 0.016658606830725214, 1.636727741140378e-16], [-0.0, -0.019842716107258795, -0.041214914707715586, -0.0638265870508466, -0.08733960828749228, -0.11137748858151005, -0.13553624546805698, -0.15939610802717472, -0.18253374114694362, -0.20453466383115837, -0.22500552953331154, -0.243585939032728, -0.2599594673568881, -0.27386360543030835, -0.28509834402240747, -0.29353316150744335, -0.2991122170935963, -0.30185759652316974, -0.30187050665707393, -0.2993303675957406, -0.2944918047438015, -0.2876795971453931, -0.2792816911423794, -0.2697404386080613, -0.2595422654137161, -0.24920601721669322, -0.2392702650609043, -0.2302798817460966, -0.2227722207152803, -0.21726324178415002, -0.21423393205013372, -0.2141173656423879, -0.21728673269438806, -0.22404464633892163, -0.2346140071496477, -0.24913066798727587, -0.26763809953285633, -0.2900842089428487, -0.316320412208348, -0.34610300621374185, -0.37909683050833043, -0.41488115280567217, -0.452957657590525, -0.49276036529246, -0.5336672615641507, -0.5750133734709341, -0.6161049929201392, -0.6562347183459047, -0.6946969642545469, -0.7308035752706671, -0.7638991771419656, -0.793375901882253, -0.8186871377604966, -0.8393599768647617, -0.8550060629614062, -0.8653305796127553, -0.8701391621135262, -0.8693425657033395, -0.8629589755249859, -0.8511138996391698, -0.8340376437196882, -0.812060423445089, -0.7856052266780957, -0.7551785909185615, -0.7213595109310468, -0.6847867356831842, -0.6461447517116635, -0.6061487808381051, -0.5655291430422339, -0.5250153497141441, -0.48532029810765426, -0.4471249344761437, -0.4110637411826057, -0.37771138234582646, -0.34757081383219346, -0.32106312734137055, -0.29851935585603345, -0.2801744198792099, -0.26616334184621626, -0.25651980115114087, -0.25117704571965516, -0.2499711193756727, -0.25264630877639727, -0.2588626607834141, -0.26820537208600914, -0.28019580888865314, -0.29430387658273216, -0.3099614284553457, -0.3265763793825014, -0.3435471756541072, -0.36027726592143944, -0.3761892208673587, -0.3907381604814995, -0.40342416746854737, -0.41380339281254325, -0.42149759415566146, -0.4262018885420533, -0.4276905471890576, -0.4258207101146204, -0.42053395140852384, -0.4118556803564297, -0.3998924181469426, -0.3848270431504574, -0.36691214842635805, -0.3464617019316666, -0.3238412417075963, -0.2994568740764811, -0.27374337170918356, -0.2471516896164942, -0.22013623016365463, -0.19314219279667802, -0.1665933402066984, -0.1408805002630978, -0.11635110254809847, -0.09330002025845444, -0.07196195332692967, -0.052505547751993266, -0.03502940035180944, -0.019560048644147964, -0.006051993556485284, 0.005610250488717317, 0.015608136540169683, 0.024183207001588734, 0.03162951490166494, 0.03828454754968078, 0.04451889490507291, 0.050724938115492474, 0.05730485975754528, 0.0646582956804905, 0.07316995853286655, 0.08319756477840182, 0.09506039022645835, 0.10902876397368406, 0.12531478754787465, 0.14406453553378162, 0.16535195680234563, 0.1891746525862837, 0.21545166011798095, 0.24402331956053155, 0.2746532487985437, 0.30703239664786597, 0.3407850915521856, 0.375476951208325, 0.4106244701059562, 0.44570605790923284, 0.48017426306794087, 0.5134688840089313, 0.5450306455489157, 0.5743151014304436, 0.6008064155592322, 0.6240306748497851, 0.6435683955887658, 0.6590659027073437, 0.6702452869087356, 0.6769126776177234, 0.6789646094103917, 0.6763923049826911, 0.669283747719708, 0.6578234703113588, 0.6422900413154469, 0.6230512877327634, 0.6005573471474248, 0.5753316964292378, 0.5479603540714749, 0.5190794987054124, 0.4893617860621129, 0.45950167965100525, 0.4302001358673061, 0.40214900148357247, 0.37601549008324836, 0.35242710372616737, 0.331957356985503, 0.31511264266875344, 0.3023205524513013, 0.2939199319327957, 0.29015290908431923, 0.29115908866694085, 0.29697205409265154, 0.3075182636062972, 0.32261837091757145, 0.341990942884611, 0.36525848994407145, 0.3919556700808057, 0.42153947556864274, 0.453401164746053, 0.4868796598575347, 0.521276097494216, 0.5558691912407764, 0.5899310474301915, 0.6227430648712616, 0.6536115482820841, 0.6818826729533289, 0.7069564546769339, 0.7282994037945911, 0.7454555747283118, 0.7580557617471063, 0.7658246370262238, 0.7685856771515782, 0.766263777879165, 0.758885512858728, 0.7465770488015357, 0.7295597858231415, 0.7081438460481948, 0.6827195846995788, 0.6537473445639503, 0.6217457157981691, 0.5872785975244703, 0.5509413847292454, 0.5133466229885288, 0.47510948405081116, 0.4368334170832922, 0.3990963234169636, 0.3624375871103307, 0.32734627000471106, 0.294250748779031, 0.2635100336277214, 0.23540696454537782, 0.2101434329103871, 0.1878377243345012, 0.1685240248863761, 0.15215407815473458, 0.13860092655819864, 0.1276646181832256, 0.11907971153742726, 0.11252436615784611, 0.1076307681139515, 0.10399660705374549, 0.10119729635440614, 0.09879861076787184, 0.09636940710891104, 0.09349409322121809, 0.08978451866433877, 0.08489097706534478, 0.07851203444071052, 0.07040292938550811, 0.06038232903736794, 0.048337268179739344, 0.03422614664471848, 0.018079711093681786, 1.7696995801236642e-16], [-0.0, -0.02126997445721784, -0.04400434144914805, -0.06787418314933377, -0.09250576140164318, -0.11749136599339048, -0.14240116452440194, -0.16679573782088614, -0.19023896632348736, -0.21231092292617976, -0.23262042661749036, -0.25081691901651604, -0.2666013423186278, -0.27973572186617945, -0.290051188925683, -0.2974542184788897, -0.3019309019415731, -0.3035491245818698, -0.30245857077005434, -0.2988885357139527, -0.29314357862266094, -0.28559710787805725, -0.27668304237477853, -0.2668857433597671, -0.2567284565899377, -0.24676054427336702, -0.23754381905188726, -0.22963831737650284, -0.2235878663676451, -0.21990580619309577, -0.2190612289091529, -0.22146608459160602, -0.22746348665366892, -0.23731752094937927, -0.25120482824352564, -0.2692081877367007, -0.2913122815830911, -0.31740176789332286, -0.3472617338583746, -0.3805805427339312, -0.4169550299118125, -0.45589794561886077, -0.49684748634906073, -0.5391787053243355, -0.5822165453789995, -0.6252501968397305, -0.6675484492463677, -0.7083756799755926, -0.747008105641847, -0.7827499139995993, -0.8149488951786407, -0.8430112014422974, -0.8664148840332192, -0.8847218836063245, -0.897588186577047, -0.904771902573696, -0.9061390670410366, -0.9016670267153192, -0.8914453228773359, -0.8756740466009098, -0.8546597002080087, -0.8288086583593783, -0.798618379210694, -0.7646665694620884, -0.7275985556248812, -0.6881131562447337, -0.6469473851255538, -0.6048603429377878, -0.562616673307935, -0.5209699691246324, -0.48064651513376916, -0.44232974393265695, -0.40664576444029404, -0.37415029526859456, -0.3453173008100135, -0.32052958614656, -0.30007155910311306, -0.28412431509106156, -0.2727631441121378, -0.26595750079847746, -0.26357341908780024, -0.26537829452296274, -0.2710479006552512, -0.28017545299848157, -0.2922824857160654, -0.30683126389555315, -0.3232384188961398, -0.34088946669178044, -0.35915385002939004, -0.3774001350210618, -0.3950109917136816, -0.4113975962248573, -0.42601310897133027, -0.4383649088959487, -0.4480252967646752, -0.4546404207073777, -0.4579372231963468, -0.4577282594312924, -0.4539142913498902, -0.44648461784644117, -0.4355151588457341, -0.42116436721843636, -0.40366709673315454, -0.3833266049695596, -0.36050491610738555, -0.3356118086191995, -0.3090927261413728, -0.28141593536200005, -0.25305927202488004, -0.22449682469226262, -0.19618590554243484, -0.16855464823149172, -0.14199055497484953, -0.11683028897243361, -0.09335097478558509, -0.07176322913434183, -0.052206098847398665, -0.03474403252983793, -0.019365959192429897, -0.005986491966028445, 0.005550780495074562, 0.015468006827030754, 0.024045934011272897, 0.03161510909659656, 0.03854565747383215, 0.04523591099997345, 0.05210018968084379, 0.05955606325869531, 0.06801143333356674, 0.07785178220500588, 0.08942793130374166, 0.1030446399643088, 0.1189503546644818, 0.1373283902351168, 0.158289788635898, 0.18186805859403002, 0.2080159517714523, 0.2366043793545961, 0.26742351834785816, 0.30018610076997404, 0.33453282281273794, 0.3700397562394189, 0.4062275922595182, 0.4425725001351551, 0.47851834007099975, 0.5134899336034323, 0.5469070656677193, 0.578198871535839, 0.6068182494347875, 0.6322559362139027, 0.6540538890467689, 0.6718176307192458, 0.6852272392379177, 0.6940466937453088, 0.6981313273001819, 0.6974331820400858, 0.692004112495353, 0.6819965371413841, 0.6676617953282975, 0.6493461251118663, 0.6274843357895306, 0.6025913056815694, 0.5752514894871633, 0.5461066690547255, 0.5158422254052151, 0.485172247239484, 0.4548238210098374, 0.4255208691905615, 0.39796791609292775, 0.3728341641051812, 0.35073825749023296, 0.33223409596422054, 0.31779803655403954, 0.3078177902544424, 0.3025832805420113, 0.30227968480481887, 0.3069828283251731, 0.3166570448544609, 0.3311555593930809, 0.35022338895429145, 0.3735026973032724, 0.4005404813760609, 0.43079841171521266, 0.4636645981568083, 0.4984670064094436, 0.5344882121874085, 0.5709811481432038, 0.6071854757489099, 0.6423442000579832, 0.675720140277375, 0.7066118734072481, 0.7343687817464057, 0.7584048574741652, 0.7782109482458741, 0.7933651660178717, 0.8035412262027524, 0.8085145346407636, 0.8081658945180439, 0.8024827629245317, 0.7915580458111996, 0.7755864792310019, 0.7548587024843494, 0.729753183728772, 0.70072620941571, 0.6683001943514958, 0.6330506081454691, 0.5955918453686069, 0.5565623901481199, 0.5166096406172714, 0.47637476429172954, 0.43647795194421496, 0.397504425015551, 0.35999153037222154, 0.32441722685364777, 0.2911902313014339, 0.2606420485647107, 0.23302106142509454, 0.20848880370644463, 0.18711848435368247, 0.16889577337288394, 0.15372180364526009, 0.14141828718088423, 0.1317345917453271, 0.12435657528209025, 0.11891693236851776, 0.1150067701498599, 0.11218810170058306, 0.11000692328485133, 0.10800652904815651, 0.10574071257344501, 0.10278650955965558, 0.09875614948627663, 0.09330790615208893, 0.08615556684643126, 0.0770762768575617, 0.0659165590982903, 0.05259635673429924, 0.03711099861013051, 0.019531041661631398, 1.9044408733663681e-16], [-0.0, -0.02269418781509465, -0.04676364248923884, -0.0718412171638009, -0.0975190852433307, -0.12336064426840715, -0.1489132789047544, -0.17372164204967805, -0.19734109886868917, -0.21935097348894722, -0.23936724222964603, -0.2570543305477998, -0.2721356929957583, -0.28440288587652046, -0.2937228801880443, -0.3000434069217836, -0.30339617671072433, -0.3038978699566137, -0.301748850545749, -0.2972296146549261, -0.2906950444833988, -0.2825665935513745, -0.27332258404478904, -0.26348684619560875, -0.2536159736083552, -0.2442855056558411, -0.23607537761490074, -0.2295550003303197, -0.2252683433254467, -0.22371939808750402, -0.22535839164260432, -0.23056910463289337, -0.23965762328073686, -0.2528428214602105, -0.27024882839080133, -0.29189969020797163, -0.31771638100091215, -0.3475162621270357, -0.3810150291081354, -0.41783112464789607, -0.45749253578226323, -0.49944583437812107, -0.5430672645871547, -0.5876756298204664, -0.6325466866049104, -0.6769287144426814, -0.7200589004796211, -0.761180156160278, -0.7995579706611889, -0.8344969030740397, -0.865356322148411, -0.8915650187532359, -0.9126343416969792, -0.9281695415535417, -0.9378790488592371, -0.9415814614704425, -0.9392100698310424, -0.9308148070859825, -0.9165615719798385, -0.8967289348150332, -0.8717022988974296, -0.8419656503553251, -0.8080910865103436, -0.7707263657112624, -0.730580768431901, -0.6884095993421967, -0.6449976920189211, -0.6011423011953695, -0.5576357813976786, -0.515248455146967, -0.47471206852403824, -0.43670421693834777, -0.40183409979043333, -0.3706299299675003, -0.34352828357569165, -0.32086562799007917, -0.30287221336014347, -0.2896684554462625, -0.2812638774876745, -0.27755861718980224, -0.27834744337738454, -0.2833261668936436, -0.292100273397773, -0.3041955532089151, -0.31907045653867866, -0.3361298624775474, -0.35473991791418724, -0.37424357893749716, -0.3939764727536107, -0.4132826930719086, -0.4315301463697833, -0.44812508029370035, -0.4625254483203835, -0.47425279609065407, -0.4829023937361697, -0.4881513840557143, -0.4897647674100353, -0.4875990994067277, -0.48160383545203644, -0.4718203156011252, -0.45837844235822744, -0.44149116168580016, -0.4214469120433991, -0.39860025643746194, -0.37336095698035027, -0.34618178923204823, -0.3175454237028431, -0.2879507235956372, -0.2578988206396868, -0.22787933441524932, -0.19835709482454342, -0.16975971249519486, -0.1424663183034339, -0.11679776148976055, -0.09300851682674705, -0.0712805059865837, -0.05171898780186027, -0.03435061780184423, -0.019123720619273518, -0.005910761041677673, 0.005487057906084266, 0.0153331969592064, 0.023947362002129664, 0.03169549174083989, 0.03897842030005333, 0.046219518247919145, 0.053851642634831914, 0.06230374524856976, 0.07198749795691589, 0.08328429447802245, 0.09653297916653772, 0.11201863564065055, 0.12996274173957204, 0.15051496304668532, 0.17374681589476584, 0.19964738341925423, 0.22812121602948593, 0.25898849193551593, 0.29198745550003824, 0.3267790926370211, 0.3629539447267384, 0.40004090701927303, 0.43751780565960346, 0.47482350060267137, 0.5113712209896929, 0.5465628060689922, 0.5798034993291684, 0.6105169268327324, 0.6381598832413654, 0.6622365509277346, 0.6823117888580623, 0.6980231483546799, 0.7090913019309746, 0.7153286084382489, 0.7166455818811956, 0.7130550813742899, 0.7046740946024723, 0.6917230454717207, 0.674522616956241, 0.653488140983781, 0.6291216670482737, 0.6020018786195453, 0.5727720799113883, 0.5421265238430538, 0.5107953938825044, 0.47952878684609096, 0.4490800697838963, 0.4201890011425456, 0.3935650140268471, 0.3698710573693323, 0.3497083791902309, 0.333602615153696, 0.3219915157932982, 0.3152146078030389, 0.3135050395825848, 0.3169838098781526, 0.32565652211663376, 0.3394127472542021, 0.35802801610352436, 0.3811683996694431, 0.40839757453028347, 0.43918621124693735, 0.47292346860161066, 0.508930326504945, 0.5464744468792043, 0.5847862157833377, 0.6230755923672127, 0.660549371595952, 0.6964284585187249, 0.729964752384861, 0.7604572491115406, 0.7872669902227927, 0.8098305149192463, 0.8276715086949678, 0.8404103859833095, 0.8477715946017871, 0.8495884850390494, 0.8458056465268544, 0.8364786729214571, 0.8217713831851935, 0.8019505821995011, 0.7773785062667856, 0.7485031525418427, 0.7158467414399476, 0.6799926045917875, 0.6415708271056024, 0.6012430008878987, 0.5596864649031057, 0.5175784180771512, 0.47558029085847625, 0.43432275226601513, 0.39439171083607893, 0.35631564071476013, 0.3205545289319572, 0.287490697536635, 0.2574217058455952, 0.23055548478301757, 0.20700779850581438, 0.18680206964556234, 0.16987154502473753, 0.15606372010848063, 0.14514688419356125, 0.13681859581222458, 0.13071585034292582, 0.12642666054673163, 0.12350273670393803, 0.12147292704399408, 0.11985706187369408, 0.118179836625387, 0.11598437015156302, 0.11284508493423435, 0.10837957517507549, 0.10225915647897985, 0.09421782632163068, 0.084059406789741, 0.07166268911909286, 0.05698445210565308, 0.04006028219161385, 0.02100318051509604, 2.0400191725891298e-16], [-0.0, -0.02410457256332321, -0.049471090342046865, -0.07569542134700412, -0.10233773069203957, -0.12893538144585115, -0.1550165299482042, -0.18011405175896433, -0.20377942507994876, -0.2255961987311017, -0.2451926815769575, -0.2622535094486001, -0.27652977361689174, -0.2878474310475967, -0.2961137601048713, -0.30132167497939927, -0.30355176665748734, -0.30297199634831845, -0.2998350274874112, -0.29447324321923823, -0.28729155609788487, -0.2787581741196892, -0.2693935406631543, -0.2597577141015712, -0.25043649454472305, -0.2420266392899756, -0.23512053423936913, -0.23029070509678062, -0.22807455915296868, -0.2289597456893752, -0.233370510520244, -0.241655398226115, -0.2540766247253742, -0.2708014037234356, -0.2918954642160975, -0.3173189437320391, -0.34692478466146065, -0.3804597002389739, -0.41756771402281606, -0.4577962135849656, -0.5006043971564599, -0.5453739326928995, -0.5914215937069951, -0.6380135866286798, -0.6843812416354484, -0.7297377039183551, -0.7732952360933675, -0.8142827256008921, -0.8519629838959393, -0.8856494272136366, -0.9147217416498885, -0.9386401579296183, -0.9569579930118103, -0.9693321558427649, -0.9755313621510283, -0.9754418570307057, -0.9690705028805157, -0.9565451526273361, -0.9381122925503876, -0.914132003870189, -0.8850703559973832, -0.8514894053993842, -0.8140350309512744, -0.7734228880065188, -0.7304228080032231, -0.6858420071296257, -0.6405074955173711, -0.5952480969372029, -0.550876497594136, -0.5081717411554479, -0.46786257563947115, -0.43061203653635693, -0.397003620052884, -0.3675293614259629, -0.34258008679527424, -0.3224380543080416, -0.307272142247306, -0.29713568045018746, -0.29196695762321523, -0.29159237292663365, -0.2957321369591666, -0.3040083665724999, -0.3159553612592294, -0.3310317975661597, -0.34863453332844824, -0.3681136765750259, -0.38878854560596265, -0.40996412765802476, -0.43094763419582444, -0.4510647513924402, -0.4696751947495514, -0.48618719676422656, -0.5000705855520082, -0.5108681496363291, -0.5182050287604855, -0.5217959214389143, -0.5214499557560048, -0.5170731292402772, -0.5086682850023589, -0.496332653191978, -0.480253047658495, -0.46069886597664234, -0.43801309527657284, -0.4126015752501861, -0.384920812085456, -0.3554646718647003, -0.32475030830094437, -0.2933036969410744, -0.2616451557264487, -0.2302752299003084, -0.19966130775882668, -0.1702253129711619, -0.1423327896882472, -0.11628365918348901, -0.09230488228352715, -0.0705452114912044, -0.051072161759756915, -0.03387127074492539, -0.01884765951721411, -0.00582984467893807, 0.005424305877126462, 0.015219637219976934, 0.023914006949727857, 0.03190708149833055, 0.03962792996817546, 0.047521747990578664, 0.056036067238322995, 0.06560682026327372, 0.07664463488911318, 0.08952172734652457, 0.1045597488116825, 0.12201891635555077, 0.14208872711836887, 0.16488051459344316, 0.19042205923526895, 0.218654413368071, 0.24943104387279377, 0.2825193367928483, 0.3176044473147279, 0.3542954180781034, 0.39213342997843087, 0.43060199403063026, 0.4691388418743374, 0.5071492274167627, 0.5440203140794792, 0.5791362921180925, 0.6118938492969432, 0.6417176063845819, 0.668075126816875, 0.6904911175386579, 0.7085604553238669, 0.7219596993894704, 0.7304567862311965, 0.7339186454744528, 0.7323165251126394, 0.7257288695888113, 0.7143416534173442, 0.6984461349858153, 0.678434058299219, 0.6547903931719776, 0.6280837651868373, 0.5989547841171126, 0.5681025320249764, 0.5362695185957564, 0.5042254502887187, 0.4727501905987555, 0.44261631035433685, 0.4145716389708477, 0.3893222296168586, 0.3675161432609369, 0.3497284387208882, 0.336447728551862, 0.3280646245322214, 0.32486235250151885, 0.3270097654335903, 0.3345569271196575, 0.34743337806092656, 0.36544913160267517, 0.38829838352705565, 0.4155658538362483, 0.44673561687023333, 0.4812022167378227, 0.5182838107356872, 0.5572370353091985, 0.5972732483413118, 0.6375757691311152, 0.677317714128254, 0.7156800128847328, 0.7518691850966911, 0.7851344661146141, 0.8147838847331783, 0.8401989230208742, 0.8608474227707279, 0.8762944459867607, 0.8862108466103323, 0.8903793662111051, 0.8886981262548588, 0.8811814523454385, 0.8679580299821641, 0.8492664553076217, 0.8254483064821205, 0.7969389201945166, 0.7642561119724778, 0.7279871270752014, 0.6887741496756147, 0.6472987307843127, 0.6042655191545713, 0.5603856936798121, 0.5163605002309548, 0.4728652904040696, 0.4305344444261293, 0.3899475359071987, 0.3516170628693803, 0.31597802837898453, 0.28337960620356395, 0.2540790734209568, 0.22823813417072425, 0.20592169820863732, 0.18709911611807378, 0.17164781149229652, 0.1593591906624834, 0.14994665409394245, 0.14305548180760524, 0.13827431938639784, 0.1351479524253761, 0.1331910266300174, 0.13190234890507557, 0.13077939223190496, 0.12933262419573863, 0.12709928574559723, 0.12365626295539106, 0.11863171977558312, 0.11171519336431988, 0.10266589469968634, 0.09131900474736415, 0.07758980927601294, 0.06147557213102027, 0.043055105953819325, 0.02248605946609148, 2.1754546616233264e-16], [-0.0, -0.025490118842517805, -0.0521048275647626, -0.07940481979286701, -0.1069208791231982, -0.13416770146845794, -0.1606582260246013, -0.1859180907397223, -0.20949982418969823, -0.23099639174964803, -0.25005372975273094, -0.26638192655866855, -0.2797647434859941, -0.29006721054460727, -0.2972410807879201, -0.3013279816610105, -0.3024601605828028, -0.30085878368629776, -0.29682980959804756, -0.2907575227788885, -0.2830958716901789, -0.27435781435616713, -0.26510292630978544, -0.25592357210212474, -0.24742998034444605, -0.24023459263817795, -0.23493607794353824, -0.23210341537987458, -0.23226044982179714, -0.23587131588666954, -0.24332710718589673, -0.25493413946819077, -0.27090411918930024, -0.29134648399312074, -0.3162631296771978, -0.34554568070801334, -0.37897539965666416, -0.4162257665592469, -0.4568676937538322, -0.5003772768231449, -0.5461459194852363, -0.5934926111804366, -0.6416780821705435, -0.6899205135400596, -0.7374124397555227, -0.783338450396902, -0.8268932761108136, -0.8672998323036156, -0.9038267929013847, -0.9358052757077011, -0.9626442402877384, -0.9838442284459564, -0.9990091155526574, -1.0078555872960209, -1.0102201097749528, -1.0060632199142192, -0.995471026545417, -0.9786538786170677, -0.9559422242674349, -0.9277797512780713, -0.8947139640991725, -0.8573844136248285, -0.8165088517124206, -0.7728676317269191, -0.7272867179486759, -0.6806196995025743, -0.6337292277511637, -0.5874683092823478, -0.5426618893981046, -0.5000891533148524, -0.46046695431440593, -0.42443475028521915, -0.3925413931546817, -0.3652340705462004, -0.3428496467117649, -0.3256085916769936, -0.31361162501807416, -0.30683913530140733, -0.30515336955850925, -0.30830332087073686, -0.31593217781950655, -0.3275871387851742, -0.34273133832925673, -0.36075758352150356, -0.38100355626745885, -0.4027681044568885, -0.4253282208790666, -0.44795629489509525, -0.4699372181323638, -0.4905849320305074, -0.5092580217264528, -0.5253739870736549, -0.5384218568651999, -0.547972855669342, -0.5536888829887796, -0.5553286204510933, -0.5527511430181646, -0.5459169732552186, -0.534886581947646, -0.519816402192484, -0.5009524859313503, -0.4786219901961842, -0.45322273366324684, -0.42521111113658744, -0.39508869315179984, -0.3633878690351238, -0.3306569137150722, -0.29744487083820137, -0.26428664700584076, -0.2316887041935529, -0.2001157198602252, -0.16997855736461204, -0.14162385378314127, -0.11532548897891073, -0.09127814991584259, -0.0695931490164888, -0.050296596232607946, -0.03332996293731716, -0.018553013319413024, -0.005749017247938686, 0.0053679008571085015, 0.015143478257422344, 0.023972346790065175, 0.03228567795160392, 0.040537772081655946, 0.04919195141757996, 0.058706135428084644, 0.06951848576517493, 0.08203350716781842, 0.0966089797239642, 0.11354407731705543, 0.13306899735922365, 0.15533638878697395, 0.18041481971966358, 0.20828447429823904, 0.2388352113334681, 0.27186705692872437, 0.30709314072367117, 0.3441450224072844, 0.3825802932613589, 0.4218922782836176, 0.461521609403135, 0.500869390838162, 0.5393116350190607, 0.5762146127993651, 0.6109507358024614, 0.6429145723774538, 0.6715385922069228, 0.6963082383156268, 0.716775939013958, 0.7325736958632852, 0.7434239165177771, 0.7491482024938956, 0.749673850547903, 0.7450378812197042, 0.7353884678863644, 0.7209837028941606, 0.7021877024485894, 0.6794641173320094, 0.6533671805721345, 0.6245304843153809, 0.5936537348490808, 0.5614877855550229, 0.5288182912942165, 0.4964483632230807, 0.46518062942896365, 0.435799123375164, 0.40905142853018933, 0.38563150354054976, 0.3661635979649048, 0.3511876442476071, 0.3411464778456757, 0.33637519504130825, 0.3370929079911747, 0.34339710019081, 0.3552607241321015, 0.37253211799377933, 0.39493775130644687, 0.42208774230181706, 0.4534840237264471, 0.48853097087843345, 0.5265482470457087, 0.5667855688129648, 0.6084390481435992, 0.6506687308415844, 0.6926169228610414, 0.7334268776402235, 0.7722614096314381, 0.8083210016673007, 0.8408609866782343, 0.8692074072331569, 0.8927711888452919, 0.911060304165224, 0.9236896540592879, 0.9303884469403202, 0.9310049182195869, 0.9255082958988788, 0.9139879845483729, 0.8966500065983031, 0.8738108053811998, 0.8458885770986971, 0.8133923573252575, 0.7769091403819789, 0.7370893556412684, 0.6946310624566486, 0.6502632540516105, 0.6047286796714645, 0.558766603166094, 0.5130959147435207, 0.4683990009831001, 0.4253067566436228, 0.38438509091142026, 0.34612324130110056, 0.310924161452195, 0.27909719574747854, 0.25085319535722045, 0.22630216845328746, 0.20545349348721784, 0.1882186601829601, 0.17441643985953292, 0.16378032643951485, 0.15596803351167596, 0.1505727824858306, 0.14713607344689078, 0.1451615948499595, 0.1441299015647658, 0.14351347361888683, 0.1427917607099339, 0.14146582031378807, 0.13907216991413984, 0.13519549617382828, 0.1294798951764813, 0.12163835737803057, 0.11146025760714362, 0.09881666314760462, 0.08366333028079169, 0.06604132020383774, 0.0460752274309638, 0.023969076053584327, 2.309731784318241e-16], [-0.0, -0.026839726757520364, -0.05464314412194687, -0.08293814463513531, -0.11122928784885072, -0.13901245223406888, -0.16578978997462565, -0.19108458319551125, -0.2144556020002646, -0.2355105767805158, -0.2539184193166995, -0.2694198586639647, -0.28183619792531556, -0.29107594575089824, -0.29713913057087593, -0.30011916480907064, -0.30020218914576996, -0.29766389171900093, -0.2928638623397864, -0.28623760570237733, -0.2782863985785681, -0.2695652325493086, -0.26066913450895146, -0.2522182006844068, -0.24484171512729647, -0.2391617496512922, -0.23577665831703296, -0.2352448853768001, -0.23806950090097337, -0.24468386320043206, -0.25543878197588643, -0.270591521460999, -0.2902969395130285, -0.3146010076917866, -0.3434369000956073, -0.37662377649335926, -0.41386831963225873, -0.45476901912889056, -0.49882312673061135, -0.5454361416389443, -0.5939336216541685, -0.6435750576948546, -0.6935694972177174, -0.7430925575126228, -0.7913044338931146, -0.8373684813535014, -0.8804699319948894, -0.9198343048612083, -0.9547450699378861, -0.9845601438513846, -1.00872682090553, -1.0267947788844631, -1.038426843687237, -1.0434072492620605, -1.041647188213778, -1.0331875124398764, -1.0181985106558626, -0.9969767590600391, -0.9699391109728298, -0.9376139593731169, -0.9006299711856262, -0.8597025523675261, -0.8156183568331309, -0.769218198728166, -0.7213787653887557, -0.6729935565760311, -0.624953493580198, -0.5781276491044077, -0.5333445452966796, -0.49137445299161214, -0.4529131005096818, -0.4185671658529042, -0.38884188268262015, -0.3641310391380317, -0.3447095906143714, -0.33072904448953594, -0.32221570801550403, -0.3190718218110166, -0.32107953228709474, -0.327907588594573, -0.3391205849546471, -0.3541905090942497, -0.37251030341725394, -0.3934090988080407, -0.41616874271039467, -0.44004121426554116, -0.46426650050879403, -0.48809049934513626, -0.5107825174208397, -0.5316519439873352, -0.5500637050605641, -0.5654521350072667, -0.577332944295884, -0.5853130114753189, -0.5890977832422132, -0.5884961273217071, -0.5834225472901153, -0.5738967347988688, -0.5600405012610552, -0.5420721962759786, -0.520298782272339, -0.4951057925045651, -0.4669454512140022, -0.43632327919354236, -0.4037835440811082, -0.36989394157495786, -0.3352299107649286, -0.30035899350952183, -0.2658256441178518, -0.23213688163743204, -0.19974915318093595, -0.16905674357245276, -0.14038202501367072, -0.11396779153038283, -0.08997186791087544, -0.06846412309312164, -0.0494259550173018, -0.03275224943242657, -0.018255750667956223, -0.005673719587893451, 0.0053233055729091806, 0.015120884524573571, 0.024148473988139543, 0.0328659792716981, 0.041749419832950996, 0.05127609374310548, 0.06190963953030767, 0.07408539721958869, 0.08819646340890216, 0.10458081809550045, 0.12350987411768378, 0.14517876417309586, 0.16969863631413643, 0.1970911777078385, 0.22728552956452797, 0.2601176949163394, 0.29533247690374415, 0.332587920018796, 0.3714621620032129, 0.4114625414441058, 0.45203674713673997, 0.49258574148929196, 0.5324781429988424, 0.5710657133394145, 0.6076995638880166, 0.6417466753724395, 0.6726063133160431, 0.699725921388998, 0.7226160847013512, 0.7408641752777726, 0.7541463219672695, 0.7622373861481218, 0.7650186718453001, 0.7624831531362953, 0.7547380616563478, 0.7420047411562123, 0.7246157428377198, 0.7030092029485002, 0.6777206111833624, 0.6493721431550283, 0.6186597909554865, 0.5863385811190759, 0.553206217740079, 0.5200855288776574, 0.4878061256826427, 0.45718570510928136, 0.42901143807734327, 0.40402188522950994, 0.3828898719516751, 0.3662067333210731, 0.3544683086092883, 0.3480630246318964, 0.34726235857087495, 0.3522139150728927, 0.3629372907962861, 0.37932283363572206, 0.4011333351975423, 0.4280086253996479, 0.45947296902341417, 0.49494509733258824, 0.533750645120241, 0.5751367062781314, 0.6182881705979901, 0.6623454622376213, 0.7064232671447738, 0.7496298135323348, 0.7910862568010375, 0.8299457184140762, 0.8654115371809978, 0.8967543109796415, 0.9233273366485152, 0.9445800948841162, 0.9600694745143131, 0.9694684853212701, 0.9725722693090794, 0.9693012854627224, 0.9597016110297499, 0.9439423715103427, 0.9223103801750584, 0.8952021343677068, 0.8631133784753207, 0.8266265007362145, 0.7863960816227854, 0.7431329541579696, 0.6975871701810213, 0.6505302904699575, 0.6027374301978412, 0.5549694941463281, 0.5079560283840261, 0.4623790969641463, 0.41885856408736627, 0.3779391248395698, 0.3400793820034875, 0.30564321371556846, 0.27489361822457875, 0.24798915917757114, 0.2249830692867568, 0.20582500355630845, 0.1903653671343617, 0.17836207894742265, 0.1694895721586059, 0.16334977765631872, 0.15948478857974843, 0.1573908635071669, 0.1565333943602023, 0.15636244307735678, 0.15632843920776032, 0.1558976290425244, 0.15456687574680725, 0.15187742893173403, 0.14742731070874016, 0.14088200275622145, 0.13198316433414337, 0.12055516334343655, 0.10650926011239534, 0.08984534513568801, 0.07065119592891018, 0.04909928286992473, 0.02544121773650461, 2.4418114816993366e-16], [-0.0, -0.028142345647547067, -0.057064756874943896, -0.08626524937908106, -0.11522582374071129, -0.1434278391579347, -0.1703674660418951, -0.19557080203706967, -0.21860824405021276, -0.23910772736643657, -0.25676647143862763, -0.27136090974539384, -0.28275452727614997, -0.2909033825616883, -0.29585915038419147, -0.29776958488276867, -0.2968763691181806, -0.2935103846006906, -0.2880845011152538, -0.2810840517085934, -0.27305521829809765, -0.2645916084838862, -0.25631935238834896, -0.24888108847726992, -0.24291923829952355, -0.23905899111139878, -0.23789142986746714, -0.23995722976479916, -0.24573134939303712, -0.25560911281172916, -0.26989404905574327, -0.28878781441956264, -0.31238247338604364, -0.340655357448809, -0.3734666587140639, -0.4105598485874719, -0.45156494269332464, -0.4960045631427774, -0.5433026800971157, -0.592795847975117, -0.6437466892848931, -0.6953593224734032, -0.7467963807946485, -0.7971972282393096, -0.8456969470769237, -0.8914456503384717, -0.9336276621617353, -0.9714801096184501, -1.0043104814521355, -1.0315127318162727, -1.0525815400845806, -1.0671243803241486, -1.0748711050586004, -1.0756808062718228, -1.0695457808025624, -1.0565924957998136, -1.037079521084357, -1.0113924673623393, -0.9800360405076317, -0.9436233908350257, -0.9028630007523997, -0.858543412835645, -0.8115161517864292, -0.7626772366572585, -0.7129477131162631, -0.6632536585644014, -0.6145061250525012, -0.5675814858839527, -0.5233026415141319, -0.4824215191278777, -0.44560326861708227, -0.413412516372966, -0.38630198836824026, -0.36460375666037337, -0.3485233001059032, -0.3381365022899941, -0.33338963910516783, -0.3341023367844169, -0.33997341025646804, -0.35058942317490743, -0.3654357465462389, -0.3839098341095384, -0.4053363809253069, -0.4289839882599721, -0.4540829238446486, -0.4798435427490538, -0.5054749209987055, -0.5302032519646921, -0.5532895644875506, -0.5740463414044279, -0.5918526471108646, -0.6061674122317611, -0.6165405713942258, -0.6226218052743857, -0.624166699139987, -0.6210401954976987, -0.6132172865409997, -0.6007809611810351, -0.5839174898071607, -0.5629091958665549, -0.5381249252375595, -0.5100084806684676, -0.4790653378739996, -0.445848001014382, -0.4109403872223528, -0.374941651818884, -0.3384498773467824, -0.3020460502938334, -0.2662787393845531, -0.23164986887134106, -0.19860194989320787, -0.16750709348206694, -0.13865808119967588, -0.11226171490153135, -0.08843460713781401, -0.06720150974267443, -0.048496211857044086, -0.032164971659227444, -0.017972380139776534, -0.005609492023149659, 0.005295999990071231, 0.015167824617755574, 0.024467747972838547, 0.03368110674644705, 0.04330164763672249, 0.05381608049029575, 0.06568876059335253, 0.07934691285402148, 0.09516679731868907, 0.11346119189025303, 0.1344685348538729, 0.158344027697451, 0.18515294879568148, 0.21486637206122636, 0.24735942307372802, 0.28241214002704645, 0.31971293972932596, 0.3588646215422901, 0.3993927762572064, 0.4407564041429204, 0.48236048835822765, 0.5235702180731397, 0.5637265113148746, 0.6021624518826563, 0.6382202285838031, 0.671268149217464, 0.7007172966017045, 0.7260373996679483, 0.746771509126805, 0.7625490940648835, 0.7730972124278782, 0.7782494538010992, 0.7779524061121341, 0.7722694575534913, 0.7613818096940425, 0.7455866458276139, 0.725292468417647, 0.7010116893140849, 0.6733506245143707, 0.6429971099247693, 0.6107060142428661, 0.577282978238539, 0.5435667550288737, 0.5104105622829114, 0.47866288373469235, 0.44914817325017775, 0.422647919566744, 0.3998825235553771, 0.3814944225708847, 0.3680328685518357, 0.35994072866843735, 0.35754363039790205, 0.3610417180614777, 0.3705042264097233, 0.38586701028107845, 0.40693309929838195, 0.4333762747114867, 0.4647475935896074, 0.5004847153651727, 0.539923818941844, 0.5823138368304639, 0.626832677572682, 0.6726050603977921, 0.7187215477858627, 0.7642583333106542, 0.808297324495209, 0.8499460538575498, 0.888356956007543, 0.9227455644577993, 0.9524072083383641, 0.9767318258014637, 0.9952165566673619, 1.007475830669654, 1.013248728187236, 1.012403456115725, 1.0049388509220516, 0.9909828922439877, 0.9707882818982642, 0.944725213101393, 0.9132715213818982, 0.8770004704501462, 0.8365664816936023, 0.7926891636422618, 0.7461360365547239, 0.6977043762839585, 0.6482026201102289, 0.5984317848540154, 0.549167344150335, 0.501141997397352, 0.4550297379763652, 0.41143159352591563, 0.37086336723310565, 0.3337456573929753, 0.3003963741889855, 0.2710259092303348, 0.2457350464354094, 0.2245156340493415, 0.20725396864354126, 0.19373677458238883, 0.18365959832967332, 0.17663737769304363, 0.17221689313293373, 0.16989076289686528, 0.1691126070920623, 0.16931297877024, 0.16991564331765244, 0.17035378131257903, 0.17008569465590656, 0.16860961105251882, 0.1654772074103262, 0.16030550776267433, 0.15278685500290023, 0.14269670692560565, 0.12989906448897687, 0.11434940238302829, 0.09609503732886553, 0.07527293638492923, 0.05210503420209656, 0.026891192960927655, 2.5706438961648465e-16], [-0.0, -0.029387114770940775, -0.05934908784746175, -0.08935751435556531, -0.11887597848847052, -0.1473760263716259, -0.17435297738428132, -0.199341148211366, -0.22192807845723328, -0.24176737178846688, -0.2585898016584638, -0.27221237482292804, -0.28254509797453453, -0.289595251597158, -0.29346903908668115, -0.2943705466960279, -0.29259801923462525, -0.2885375259357162, -0.28265415874225636, -0.27548096973561736, -0.2676059139047025, -0.25965711641277184, -0.25228682861236595, -0.24615447312696312, -0.24190920442705274, -0.24017242679125317, -0.24152071593809832, -0.24646958379509307, -0.25545850797249514, -0.26883761894087455, -0.28685639935181695, -0.30965470231882347, -0.3372563399470854, -0.3695654313224084, -0.40636563206326287, -0.44732229705630183, -0.4919875558730116, -0.5398082083863439, -0.5901362780545831, -0.6422419939549414, -0.695328911584052, -0.748550828221249, -0.8010301026317724, -0.8518769522297059, -0.9002092744540993, -0.9451725237145545, -0.9859591712426834, -1.0218272826725248, -1.0521177670118145, -1.0762698804230748, -1.0938346082056432, -1.104485597601483, -1.1080273713547228, -1.1044006159529745, -1.0936844076174739, -1.076095311710789, -1.0519833655304742, -1.0218250286465191, -0.9862132572129658, -0.9458449272783424, -0.9015058953637137, -0.8540540409289816, -0.8044006834342134, -0.7534908053513194, -0.7022825407516871, -0.6517264063005631, -0.6027447572131985, -0.556211944836306, -0.5129356351606676, -0.47363971917729997, -0.438949207260175, -0.40937745164630285, -0.3853159847705429, -0.36702719807964895, -0.3546400175451518, -0.34814866009267026, -0.3474144813272837, -0.3521708510645791, -0.36203092107716034, -0.37649808089285536, -0.39497883410039825, -0.41679777096752074, -0.44121426462354973, -0.46744047877067124, -0.49466024580165935, -0.5220483560007634, -0.5487897916029061, -0.5740984440189394, -0.5972348683541828, -0.6175226560277141, -0.6343630431479081, -0.6472474183724489, -0.6557674481094379, -0.6596225977344844, -0.6586248934782801, -0.652700839127327, -0.641890472940908, -0.6263436214439906, -0.6063134762363579, -0.582147685939095, -0.5542772162476188, -0.5232032852742898, -0.48948272761046147, -0.45371217768629546, -0.41651149015501565, -0.37850683152636744, -0.3403138827391942, -0.30252158668934503, -0.2656768580897247, -0.23027064588154175, -0.19672570145020288, -0.16538636008087415, -0.13651058959347875, -0.11026450029176216, -0.08671944576979783, -0.06585177638400622, -0.04754523803898973, -0.03159594010470889, -0.01771974952464485, -0.005561905179898, 0.005291411062798911, 0.015299861011578408, 0.024954451628212894, 0.03476214196707763, 0.045229969712698506, 0.05684912431748912, 0.0700793956414834, 0.08533441787954764, 0.10296810865277028, 0.12326267293556216, 0.14641850174431995, 0.17254624722396383, 0.20166130014802125, 0.23368083429467618, 0.26842351622464644, 0.3056119103284195, 0.3448775393623279, 0.38576849181460265, 0.4277594010766703, 0.4702635592238507, 0.5126468718131938, 0.5542433109223105, 0.5943714829410939, 0.6323518964379555, 0.6675244945667482, 0.6992660065160868, 0.7270066737142237, 0.750245918896085, 0.7685665494414656, 0.7816471200584724, 0.7892721231084782, 0.7913397266021921, 0.7878668388807749, 0.7789913437877526, 0.7649714191454962, 0.7461819228745277, 0.7231079033688608, 0.6963353619772533, 0.666539463871786, 0.634470457509857, 0.6009376207204595, 0.5667916017238949, 0.5329055648635929, 0.5001555824417849, 0.46940073500105745, 0.44146339213647723, 0.41711014418815273, 0.39703384196488556, 0.38183717728048266, 0.372018202115876, 0.36795813948423056, 0.36991178564587196, 0.3780007424833369, 0.39220965207590613, 0.41238553442682213, 0.4382402556216961, 0.46935607922542266, 0.5051941802702429, 0.5451059305389434, 0.5883466977265038, 0.6340918410827977, 0.6814545337604836, 0.7295049985925943, 0.7772907104629819, 0.8238570956263208, 0.8682682468352677, 0.9096271732173631, 0.9470951155055768, 0.9799094801733108, 1.0073999796902149, 1.029002609670281, 1.0442711460579506, 1.052885905405222, 1.0546595772643732, 1.0495400081404547, 1.0376098895918497, 1.0190833771479595, 0.9942997399217341, 0.9637142113467201, 0.9278862776467185, 0.8874657008445509, 0.8431766258777362, 0.7958001654416479, 0.7461558904699136, 0.6950826778748275, 0.6434193797565035, 0.5919857794735686, 0.5415642897563762, 0.49288282672381356, 0.4465992617982766, 0.40328781192049373, 0.36342767820657323, 0.32739418553463717, 0.2954526119500926, 0.2677548288320605, 0.2443388021688437, 0.2251309338092963, 0.20995115096898032, 0.19852058432874725, 0.19047161145232813, 0.18535998454075425, 0.18267871115658907, 0.18187331472582727, 0.1823580693796246, 0.18353278181012966, 0.1847996818025716, 0.18557998321436386, 0.18532968836771654, 0.18355423079361297, 0.17982158343143176, 0.17377350091445798, 0.16513461438814242, 0.1537191541398016, 0.1394351377155204, 0.12228592757450243, 0.10236913099678917, 0.07987288417523265, 0.055069630432630676, 0.028307567587556676, 2.6951813940619026e-16], [-0.0, -0.030563503727266853, -0.06147653791019192, -0.09218823934586162, -0.12214835911853543, -0.15082369801283205, -0.17771412577390144, -0.2023677522199815, -0.2243948395805208, -0.2434800773738155, -0.25939288285119333, -0.27199544047280694, -0.2812482517750798, -0.2872130308848767, -0.29005284922107444, -0.2900295038785924, -0.28749815602202533, -0.2828993565102201, -0.2767486441347973, -0.26962396555600404, -0.2621512236388048, -0.25498831096107555, -0.24880802650118175, -0.24428030485019678, -0.24205420791656085, -0.2427401384467381, -0.24689273250389995, -0.2549948743451937, -0.26744325222204846, -0.2845358380832322, -0.30646162883949524, -0.33329293284984196, -0.36498042392965, -0.4013511179632143, -0.44210935578022, -0.4868408020878121, -0.5350193957628597, -0.5860171135476692, -0.639116338975586, -0.6935245629279996, -0.7483910832238262, -0.8028253195437025, -0.8559163180787216, -0.9067529886282639, -0.954444596262678, -0.9981410206530783, -1.0370522990054174, -1.0704669831815445, -1.0977688677170103, -1.1184516824418655, -1.1321313903961028, -1.1385557875782137, -1.1376111644269093, -1.1293258582790677, -1.113870599689665, -1.0915556316524024, -1.0628246575702818, -1.0282457494228932, -0.9884994201193011, -0.9443641317432676, -0.8966995726395827, -0.8464280895623586, -0.7945147051092497, -0.7419461843268009, -0.6897096368719557, -0.6387711519066432, -0.5900549617264828, -0.5444236170141771, -0.5026596318882322, -0.4654490211978461, -0.4333671066730506, -0.40686691370138384, -0.38627041801325346, -0.3717628329490849, -0.3633900549319635, -0.36105930906647743, -0.3645429602774561, -0.37348537995825126, -0.38741268555543534, -0.40574510263973607, -0.42781163744872136, -0.4528666941246168, -0.48010822620555965, -0.508696977429602, -0.5377763433946371, -0.5664923736289559, -0.5940134334261779, -0.619549056353301, -0.6423675413305519, -0.6618118820034715, -0.6773136599123292, -0.6884045855979595, -0.6947254319366619, -0.6960321701568762, -0.6921991894985736, -0.683219554570439, -0.6692023283173271, -0.6503670612940865, -0.627035617845141, -0.5996215750816085, -0.568617489617189, -0.5345803784170321, -0.4981158025714076, -0.45986097529479586, -0.42046733718854307, -0.3805830522793622, -0.3408358773268851, -0.3018168444395405, -0.2640651734936429, -0.22805479683721758, -0.19418283516084012, -0.16276031135441488, -0.13400532997410022, -0.108038885127271, -0.08488339079461779, -0.06446395659404608, -0.046612360552089394, -0.031073600394862105, -0.017514837975758937, -0.0055364894137742105, 0.005314842106053089, 0.015531941712954671, 0.025631456011601442, 0.036137682362910255, 0.04756611061477347, 0.06040716039940437, 0.07511055251972353, 0.09207073708345807, 0.11161377430559645, 0.1339860269569064, 0.15934497721535174, 0.18775242633969025, 0.21917027449705764, 0.2534590117769415, 0.29037898158344455, 0.32959440597814504, 0.3706800909561288, 0.41313065988869596, 0.45637209722511873, 0.49977532369201316, 0.5426714702119142, 0.5843684719632888, 0.6241685675994669, 0.6613862625779143, 0.6953663005106803, 0.7255011828440243, 0.7512477851371824, 0.7721426375751597, 0.7878154676714373, 0.7980006436719452, 0.8025462069833915, 0.8014202398056558, 0.7947143786350542, 0.7826443538402109, 0.7655475083831843, 0.7438773231666552, 0.7181950505925359, 0.6891586298806183, 0.6575091257293472, 0.6240549943088968, 0.5896545358002389, 0.555196939347013, 0.5215823631936184, 0.48970151900492365, 0.46041524422418106, 0.4345345494289567, 0.4128016188818037, 0.39587222202747757, 0.3842999620332723, 0.37852274535237757, 0.37885180471902097, 0.385463548199488, 0.39839444036927324, 0.417539049976141, 0.44265132332273804, 0.47334906588718134, 0.5091215382632497, 0.549339998205604, 0.5932709502210302, 0.6400917994696002, 0.6889085493075731, 0.7387751330176793, 0.7887139313218013, 0.8377369991050215, 0.8848675080840547, 0.9291609073310216, 0.9697253107296457, 1.0057406394151784, 1.0364760775629933, 1.0613054407977336, 1.0797201069901092, 1.091339218052968, 1.0959169270991973, 1.0933465363713035, 1.083661445957364, 1.0670329096467541, 1.0437646704875765, 1.0142846228276747, 0.979133718045572, 0.9389523960955982, 0.894464882829861, 0.8464617424220463, 0.7957811139187769, 0.7432890900376301, 0.6898597141340806, 0.6363550773688665, 0.583605992408517, 0.5323937026615191, 0.4834330575545502, 0.43735754542589766, 0.3947065272505462, 0.35591495783956706, 0.3213058178005703, 0.2910854109974296, 0.2653416102213923, 0.2440450600803286, 0.22705327256386476, 0.21411747917676052, 0.20489203572540074, 0.19894611346907615, 0.1957773549463754, 0.19482712571798652, 0.19549695568017642, 0.19716573640893795, 0.1992072248425544, 0.20100739887222877, 0.20198121717232492, 0.20158835366181058, 0.19934750586191907, 0.19484891534741336, 0.18776478647439354, 0.17785734537521838, 0.16498434341510707, 0.1491018763208695, 0.13026446031672784, 0.10862237805568972, 0.0844163781063412, 0.05796988044689204, 0.02967890509229085, 2.8143917532315726e-16], [-0.0, -0.03166145093101665, -0.06342875255806966, -0.09473301854237806, -0.12501514764537405, -0.15374257247764192, -0.18042532571726624, -0.20463098983576908, -0.22599812475088135, -0.2442478066592108, -0.2591929596126905, -0.27074521797538703, -0.2789191213075958, -0.28383351187446537, -0.2857100771354196, -0.28486905341684293, -0.2817221806376278, -0.2767630695809668, -0.2705552109705774, -0.26371791779393533, -0.25691054733487906, -0.25081539582610723, -0.24611969531403802, -0.24349716829229076, -0.24358961022040632, -0.2469889728002268, -0.2542204117270793, -0.2657267417575827, -0.281854709824895, -0.3028434543514933, -0.32881546688806607, -0.3597703120114425, -0.3955812945178782, -0.4359951909938488, -0.4806350876078069, -0.5290062893017758, -0.5805051893696639, -0.634430914580698, -0.6899994913780968, -0.7463602149916453, -0.8026138471416764, -0.8578322207916855, -0.9110787933198192, -0.9614296634705021, -1.0079945531890988, -1.0499372533194604, -1.086495042241765, -1.1169966086313246, -1.1408780431164531, -1.157696507910058, -1.1671412474257519, -1.1690416651667366, -1.1633722612895752, -1.150254299520234, -1.1299541497327965, -1.1028783316038542, -1.0695653634016307, -1.0306745962416524, -0.9869722861801535, -0.93931522256454, -0.8886322895054111, -0.8359043867498968, -0.7821431754158245, -0.7283691420344968, -0.6755894904649395, -0.6247763750930841, -0.5768459802244776, -0.5326389299302663, -0.49290248032186407, -0.45827490310342145, -0.4292724163408299, -0.4062789569890069, -0.3895390213393156, -0.3791537258599953, -0.3750801637064997, -0.37713405336179123, -0.3849955973525366, -0.3982183926895595, -0.4162411624564955, -0.4384020115734764, -0.4639548508009387, -0.49208758294535465, -0.5219416051864285, -0.5526321524173267, -0.5832689891561521, -0.6129769523391949, -0.6409158542372382, -0.6662992736373052, -0.68841179380139, -0.7066242867659323, -0.7204068942345031, -0.7293394143584995, -0.7331188696102067, -0.7315641020762406, -0.7246173170585954, -0.7123425720057711, -0.6949212836131391, -0.6726448995477936, -0.6459049508452316, -0.6151807648743969, -0.5810251753015694, -0.5440486133157373, -0.5049020023417522, -0.4642589056447626, -0.4227973919731744, -0.38118208833793094, -0.3400468811186594, -0.29997870715460934, -0.26150284584324046, -0.22507008233175682, -0.19104606170397598, -0.15970309592362292, -0.1312146206804893, -0.10565242984318018, -0.08298674271595292, -0.0630890855667013, -0.045737895806754185, -0.030626686610846776, -0.01737454345327044, -0.005538663680502352, 0.005371402632720441, 0.015878196351339295, 0.026519897401074168, 0.03783342059740908, 0.05033751437547607, 0.06451631786060515, 0.08080382026486282, 0.09956964372449201, 0.12110653697979934, 0.1456199235891796, 0.17321979576155203, 0.20391518471026296, 0.23761137219222073, 0.2741099372683648, 0.31311165908746735, 0.3542222225044686, 0.39696060046812315, 0.4407699171964431, 0.4850305309764054, 0.5290750166346121, 0.5722046768283563, 0.6137071696069479, 0.6528748082675445, 0.6890230691996763, 0.7215088347228477, 0.7497479011268319, 0.7732312971821911, 0.7915399849604082, 0.804357552261838, 0.8114805533951268, 0.8128262113326352, 0.8084372580084598, 0.7984837591657876, 0.7832618439850643, 0.7631893359122838, 0.7387983577731856, 0.7107250595037403, 0.6796966887803214, 0.6465162917023203, 0.6120453907950345, 0.5771850394552929, 0.5428556942503283, 0.5099763781303024, 0.47944362781524247, 0.4521107268377056, 0.4287677217275009, 0.41012270267895906, 0.3967848021093473, 0.38924932545384905, 0.3878853792784916, 0.3929263035099472, 0.40446314868616745, 0.42244136721916076, 0.44666081147563175, 0.4767790528742544, 0.5123179570830706, 0.5526733727043173, 0.5971277164511433, 0.6448651685656606, 0.6949891297907042, 0.7465415371125391, 0.7985235910588724, 0.8499174136500779, 0.8997081339827655, 0.946905888412252, 0.9905672246353797, 1.0298154135976518, 1.0638591996973479, 1.092009557581226, 1.1136940719930044, 1.1284686144656983, 1.1360260557373376, 1.1362018240224885, 1.1289761949465151, 1.114473277195469, 1.0929567368412683, 1.0648223809447643, 1.030587795527381, 0.9908793025241864, 0.9464165632013689, 0.8979952102187975, 0.8464679357268045, 0.792724497524311, 0.7376711285536932, 0.6822098463290203, 0.6272181580457095, 0.5735296441595258, 0.5219158785071304, 0.47307010721492154, 0.4275930626265761, 0.38598123344041285, 0.34861784957505815, 0.3157667715498857, 0.28756940109722795, 0.26404465414058775, 0.2450919610601896, 0.23049718421845358, 0.21994127089162724, 0.21301139282676063, 0.20921426326606077, 0.20799126993749054, 0.20873501948187512, 0.21080685611829209, 0.21355489582601098, 0.2163321074476374, 0.21851397410721035, 0.21951528210447002, 0.21880560961367368, 0.21592312341833353, 0.21048633762086164, 0.20220354260240345, 0.19087967408278686, 0.17642045937343895, 0.15883374911697254, 0.1382280161584065, 0.114808076834952, 0.08886816203903258, 0.06078253407901881, 0.030993908897352197, 2.927271359114697e-16], [-0.0, -0.032671498462169705, -0.06518887652313904, -0.09697009318366043, -0.12745252404673246, -0.1561098630087254, -0.18246806594201315, -0.20611990497745128, -0.2267377375172145, -0.24408413984356803, -0.25802010998595076, -0.26851060698709817, -0.2756272622940459, -0.27954817196171994, -0.28055475385348705, -0.2790257301466166, -0.27542837027510875, -0.27030720107179573, -0.2642704574876163, -0.2579746071732938, -0.2521073338777111, -0.24736940672270663, -0.24445589386789, -0.24403719905852467, -0.2467404075175351, -0.2531314233619413, -0.2636983642632228, -0.2788366508036332, -0.29883618857559835, -0.32387099147785015, -0.35399153608503636, -0.38912007083910777, -0.4290490317541024, -0.4734426401156167, -0.5218416791743409, -0.5736713680222687, -0.6282521736560825, -0.684813328594205, -0.7425087531580435, -0.8004350203606213, -0.8576509488019237, -0.9131983663747028, -0.9661235560186238, -1.0154988750360152, -1.0604440321192499, -1.1001465114548783, -1.1338806509693822, -1.161024911564991, -1.181076915361823, -1.193665882533919, -1.1985621570632177, -1.1956835801716104, -1.1850985446701552, -1.1670256421788294, -1.14182989620621, -1.110015655463433, -1.072216301537241, -1.0291810012177571, -0.9817588045088678, -0.9308804529155128, -0.8775383174505597, -0.8227649305940553, -0.7676106100759825, -0.7131206940186161, -0.6603129161381841, -0.6101554461454299, -0.5635461042901587, -0.5212932305644031, -0.48409864911019856, -0.45254311785139734, -0.42707459352203414, -0.40799957456220826, -0.39547771045259, -0.38951978776757695, -0.38998912245756057, -0.39660630659417495, -0.4089571780103186, -0.4265038048820423, -0.4485982061883556, -0.4744984648718895, -0.5033868349576631, -0.5343893982062782, -0.5665967911733705, -0.5990855006392366, -0.6309392147893228, -0.6612697194914395, -0.6892368434434025, -0.714066982462157, -0.7350697710628503, -0.7516525177642042, -0.7633320780308848, -0.7697439039756006, -0.7706480812566266, -0.7659322392362623, -0.755611298525316, -0.7398240985852824, -0.71882702514275, -0.6929848308801624, -0.6627589113816976, -0.6286933599445308, -0.5913991781009577, -0.5515370622350532, -0.5097992194625909, -0.4668906871892075, -0.4235106399731269, -0.38033416430100425, -0.3379949667501185, -0.2970694541719919, -0.2580625866983638, -0.2213958565211592, -0.18739768876424, -0.1562964967948377, -0.12821655464739662, -0.10317677562363241, -0.081092410458095, -0.06177960261608999, -0.044962664240012676, -0.030283865853832144, -0.017315467953391273, -0.005573664694130469, 0.0054659394993147896, 0.01635173918805771, 0.027638870658859338, 0.039871753097617736, 0.05356689852870134, 0.06919645415353354, 0.08717292210711823, 0.10783547158755541, 0.1314382175566525, 0.1581407897848898, 0.18800145719094796, 0.2209730066868115, 0.2569015047417593, 0.2955279954139219, 0.3364931125472977, 0.37934450811821013, 0.4235469252550824, 0.46849467511216053, 0.5135262133138149, 0.5579404557187151, 0.6010144262145001, 0.6420217923541645, 0.6802518188434121, 0.7150282548661054, 0.7457276693808886, 0.7717967589207918, 0.7927681748574454, 0.8082744510295188, 0.8180596572696719, 0.8219884586153093, 0.8200523225331792, 0.8123726857940501, 0.7992009669970317, 0.7809153883296832, 0.7580146490414545, 0.731108571349009, 0.7009059151391528, 0.6681996290047926, 0.6338498700649311, 0.5987651820550008, 0.5638822688951524, 0.5301448381439187, 0.49848201447389917, 0.4697868368966399, 0.44489535454601997, 0.42456682434141924, 0.4094654900413771, 0.4001443866177445, 0.3970315673717096, 0.4004190948897821, 0.41045507215583915, 0.4271389184606758, 0.4503200179205738, 0.4796997882976046, 0.5148371363558445, 0.5551571851736584, 0.5999630806330771, 0.6484506106309796, 0.6997253032018759, 0.7528216103534628, 0.8067237344444552, 0.8603876146000815, 0.9127635629246468, 0.9628190248094327, 1.0095609348246837, 1.0520571495925357, 1.089456461419554, 1.1210067307727885, 1.1460707210705274, 1.1641392746157626, 1.1748415324709693, 1.177951972091472, 1.1733941128639438, 1.1612408194712336, 1.1417112142763646, 1.115164290704623, 1.0820893979349824, 1.0430938411851427, 0.9988879096924349, 0.9502677045138567, 0.8980961890446918, 0.8432829254682159, 0.7867629892401803, 0.7294755705048693, 0.6723427756575836, 0.616249134042, 0.5620222942407316, 0.510415362126084, 0.46209128961787355, 0.4176096700466239, 0.37741623448365547, 0.3418352749227277, 0.31106514649607725, 0.2851769238229238, 0.26411620804114766, 0.24770800301596838, 0.23566450358922783, 0.22759556740057013, 0.22302157653798171, 0.2213883376653243, 0.222083620740028, 0.2244548981570309, 0.22782781905914384, 0.23152493828205473, 0.23488421630040437, 0.23727681565116487, 0.2381237403678214, 0.23691089740124885, 0.23320220198381994, 0.2266504013032713, 0.2170053513482183, 0.20411954882348843, 0.1879507919041691, 0.16856191847679597, 0.1461176465056578, 0.12087861633701417, 0.09319280721202142, 0.06348456816826152, 0.032241565153861215, 3.032858251807519e-16], [-0.0, -0.03358492164925728, -0.06674179407333047, -0.09888067743003717, -0.12944104714181062, -0.15790867857376362, -0.18383129199670104, -0.20683253373868066, -0.2266239121401795, -0.24301435948989392, -0.25591715220590655, -0.2653539895999617, -0.2714561049032641, -0.2744623589887232, -0.2747143454571616, -0.2726486134845744, -0.26878619008515686, -0.2637196543210771, -0.25809808068277745, -0.25261022572347674, -0.24796637960299478, -0.244879341254181, -0.24404500146675, -0.2461230316107846, -0.25171817662134033, -0.26136263917519037, -0.2755000179644347, -0.29447122717206997, -0.31850277753973544, -0.347697742920206, -0.3820296713059189, -0.4213396276116688, -0.4653364787297141, -0.5136004514636909, -0.5655899128615637, -0.6206512422185689, -0.6780315866039593, -0.736894219109636, -0.796336152940163, -0.8554076066188644, -0.9131328674301837, -0.9685320629740525, -1.0206433253262253, -1.0685448194410356, -1.1113761074530093, -1.1483583334681593, -1.178812739002171, -1.2021770568276837, -1.218019379744918, -1.226049159521992, -1.2261250585487498, -1.2182594509835445, -1.2026194495460938, -1.1795244166925518, -1.149440002691426, -1.1129688360594017, -1.0708380718914172, -1.0238840788748478, -0.9730346143753287, -0.9192888972451332, -0.8636960384613662, -0.8073323291164295, -0.7512779126940382, -0.696593383300101, -0.6442968532193617, -0.5953420217949348, -0.5505977534580473, -0.5108296363618279, -0.47668394538668163, -0.4486743754534042, -0.4271718445185483, -0.4123975919630983, -0.4044197191206757, -0.40315323635444683, -0.4083635973923054, -0.4196736186087556, -0.43657360062107925, -0.4584343939000021, -0.48452308091730834, -0.5140208863391089, -0.5460428753947317, -0.5796589600397966, -0.6139157038505947, -0.6478584004057818, -0.6805528965918968, -0.7111066418553574, -0.7386884666414391, -0.7625466275252473, -0.782024701970398, -0.7965749710931719, -0.8057689928642657, -0.8093051392377133, -0.8070129469784234, -0.798854211562125, -0.7849208344622661, -0.7654295144072177, -0.7407134507984675, -0.7112113005079086, -0.67745369591923, -0.6400476907071355, -0.599659549024162, -0.5569963322923026, -0.512786764747625, -0.4677618736234879, -0.4226359020507818, -0.37808798238513697, -0.3347450350382044, -0.2931663235964459, -0.25383005195050823, -0.21712233449337326, -0.183328807577307, -0.15262908095254604, -0.12509415361251608, -0.10068684122766582, -0.07926518412084498, -0.06058872750197115, -0.04432749139202433, -0.030073378203383985, -0.017353703059587867, -0.005646477220115099, 0.005602970194407717, 0.01696448146439941, 0.029005142734977268, 0.042271422685680876, 0.057271858792965376, 0.0744607585856682, 0.09422335729014632, 0.11686283589577959, 0.14258955588412492, 0.1715128098602864, 0.20363532254020789, 0.2388506656166707, 0.27694367474018755, 0.31759387911045384, 0.36038187594510745, 0.4047985053555384, 0.4502566078596015, 0.49610507875993043, 0.5416448726453869, 0.5861465588893552, 0.6288689865664662, 0.6690785857867494, 0.7060688128757358, 0.7391792396386311, 0.767813792354528, 0.7914576640564361, 0.8096924536553081, 0.822209126848684, 0.828818445518799, 0.8294585732112271, 0.8241996328033988, 0.8132450669389318, 0.7969297303829669, 0.7757147242034804, 0.7501790626031304, 0.7210083423060852, 0.6889806596761942, 0.6549500903283347, 0.6198281081523515, 0.5845633738368512, 0.5501203658165109, 0.5174573579812483, 0.4875042676693597, 0.4611409039103044, 0.43917613939056527, 0.4223285103110618, 0.411208716625884, 0.40630445184482594, 0.40796793767832035, 0.4164064755979726, 0.4316762564045061, 0.45367959185653134, 0.4821656511882458, 0.5167347019074422, 0.5568457706488733, 0.601827558100784, 0.6508923641192683, 0.7031527069982443, 0.7576402562349128, 0.8133266426011386, 0.8691456642578583, 0.9240163741344024, 0.9768665126569229, 1.0266557416664548, 1.072398140218768, 1.1131834407848988, 1.148196514736516, 1.1767346581597793, 1.19822228196276, 1.2122226726294678, 1.2184465603017125, 1.2167573074188542, 1.2071726120440094, 1.1898627032784037, 1.1651450897813946, 1.1334760043346275, 1.0954387656212088, 1.0517293510341417, 1.0031395396218499, 0.9505380406449692, 0.8948500693018369, 0.8370358658793923, 0.7780686770825787, 0.7189127280714304, 0.6605017105876522, 0.6037182965967408, 0.5493751585389537, 0.4981979373072708, 0.4508105484740152, 0.40772315735110115, 0.3693230857003982, 0.3358688390102367, 0.30748736506808244, 0.284174574037566, 0.2657990693923189, 0.25210895987586646, 0.2427415471062121, 0.23723561339090904, 0.2350459714879539, 0.2355598839805127, 0.23811491594863024, 0.24201775178380078, 0.2465634860875197, 0.2510548901081697, 0.2548211592762249, 0.25723566395517095, 0.2577322540829424, 0.2558197081850918, 0.251093967264552, 0.24324785302830926, 0.23207803629082396, 0.2174890935062283, 0.19949456539330973, 0.1782150096006235, 0.15387311733839346, 0.12678603990591875, 0.09735514314669037, 0.06605347424679892, 0.03341128427938393, 3.13024486706819e-16], [-0.0, -0.03439385179009143, -0.06807435199169726, -0.10044925332657507, -0.1309659884038508, -0.15912835964215033, -0.1845117045864764, -0.2067761246795618, -0.22567741541342826, -0.24107539501703457, -0.25293939593571774, -0.261350756633871, -0.26650222885328234, -0.26869429542451684, -0.26832847403482585, -0.26589776096963147, -0.2619744437719579, -0.2571955811016213, -0.2522465100575989, -0.2478427942689674, -0.2447110688001236, -0.2435692692490818, -0.24510675152175304, -0.2499648151239101, -0.25871813622771545, -0.27185759736683157, -0.2897749688397322, -0.3127498535117295, -0.3409392527511039, -0.37437004802845103, -0.4129346217994848, -0.45638976442433, -0.5043589329472843, -0.5563378445722866, -0.6117033046787327, -0.6697250882925481, -0.7295806170747657, -0.7903721030338082, -0.8511457670836486, -0.9109126868442625, -0.9686707850720374, -1.0234274389117104, -1.0742221715845504, -1.1201488826658608, -1.1603770809317508, -1.194171604716269, -1.2209103483368142, -1.2400995586271544, -1.251386321878305, -1.2545679271762245, -1.2495978656554059, -1.2365883047779183, -1.2158089604653706, -1.187682375720061, -1.1527757001805943, -1.11178914877369, -1.0655413972038432, -1.014952245521996, -0.9610229466363039, -0.9048146527677867, -0.8474254781371954, -0.7899667094884965, -0.733538716593073, -0.6792071221337462, -0.6279797841612994, -0.580785124799264, -0.5384523065231797, -0.5016937129489821, -0.4710901357179049, -0.4470790041154045, -0.4299459210971855, -0.41981969019936477, -0.4166709343164302, -0.42031432157786836, -0.43041432763323073, -0.4464943796591759, -0.46794914737400195, -0.49405967222885083, -0.5240109595359074, -0.5569116011964587, -0.5918149502784329, -0.6277413340721991, -0.6637007702410801, -0.6987156417844199, -0.7318427909268294, -0.7621945095914833, -0.7889579343374793, -0.8114123957599221, -0.8289443252930279, -0.8410593847826139, -0.8473915545355282, -0.8477089920475382, -0.8419165543482835, -0.8300549598708495, -0.8122966488931381, -0.7889384828472031, -0.7603915001417859, -0.7271680176844347, -0.6898664312634614, -0.6491541227894648, -0.6057489267649716, -0.5603996411762308, -0.5138660885009905, -0.46689924022669266, -0.42022191302203427, -0.3745105266723233, -0.33037838356547683, -0.2883608876975991, -0.24890306893772157, -0.2123497169922497, -0.17893836070781005, -0.1487952537990868, -0.1219344496799638, -0.09825996780035223, -0.077570973780046, -0.05956981771094431, -0.04387270123890781, -0.030022676298501322, -0.017504618367200176, -0.005761766343455591, 0.005786619085052269, 0.01772695541672183, 0.030632889927899035, 0.045047199918923544, 0.06146452964760984, 0.08031543043749594, 0.1019521369041862, 0.12663646754700786, 0.1545301832323629, 0.18568807372999416, 0.2200539720531231, 0.25745982067576556, 0.29762783466744064, 0.3401757263953832, 0.3846248767316748, 0.4304112606877253, 0.47689886303578466, 0.523395253607459, 0.5691689342625897, 0.6134680214758791, 0.6555397913310831, 0.6946505884101736, 0.7301055872886754, 0.7612678954570457, 0.7875764995179162, 0.808562582173404, 0.8238637752120563, 0.8332359625257231, 0.8365623059474216, 0.8338592339657932, 0.8252792074887091, 0.8111101559717233, 0.7917715594412457, 0.7678072351909094, 0.7398749701462772, 0.7087332190315985, 0.6752251625590118, 0.6402604870420421, 0.6047953054253888, 0.5698106882446582, 0.5362903102519196, 0.5051977434115942, 0.4774539390327722, 0.4539154406229951, 0.4353538546151677, 0.422437078750927, 0.41571274823719756, 0.4155943087689143, 0.4223500643519148, 0.4360954780395642, 0.45678892690353334, 0.48423103065610634, 0.518067588319247, 0.5577960712644988, 0.6027755359256604, 0.6522397375879937, 0.7053131498835364, 0.7610295248480784, 0.8183525673280407, 0.8761982466582656, 0.9334582291101501, 0.9890238875980767, 1.041810331193035, 1.0907798964666109, 1.1349645555901744, 1.1734867221273588, 1.2055779739466732, 1.2305952627041636, 1.2480342396795883, 1.2575393969188764, 1.2589107989496044, 1.2521072619307823, 1.2372459219809577, 1.2145982205287214, 1.184582419748462, 1.1477528434070687, 1.1047861157546304, 1.056464741568595, 1.0036584324013171, 0.9473036359923453, 0.888381766445149, 0.8278966611677445, 0.7668518060756433, 0.7062278728094816, 0.6469611007112472, 0.5899230323415574, 0.535902075033934, 0.48558731330069216, 0.4395549390389285, 0.3982575998925963, 0.3620168924788012, 0.33101914832499657, 0.3053145782553117, 0.2848197576514176, 0.2693233525636671, 0.25849490710351525, 0.2518964378731218, 0.2489965132218934, 0.24918643553098221, 0.2517980949716099, 0.2561230244696675, 0.26143215886777904, 0.26699578713670025, 0.2721031852647348, 0.27608142913750555, 0.27831291097955074, 0.2782511191180763, 0.2754342880053134, 0.2694965823829163, 0.2601765447308466, 0.2473226070493509, 0.2308955447466853, 0.2109678300000347, 0.18771992240548238, 0.16143361399938308, 0.1324826218141874, 0.10132069210514467, 0.06846754445904935, 0.03449303955608977, 3.2185903167018804e-16], [-0.0, -0.03509139048347859, -0.06917556241027943, -0.10166383102964846, -0.1320176142505793, -0.15976474418722147, -0.18451396921030808, -0.20596725166231655, -0.22392952329461152, -0.2383156261391808, -0.24915423927761737, -0.256588669977727, -0.2608744689616217, -0.2623739120919448, -0.2615474724254318, -0.25894248531505676, -0.2551792830444549, -0.25093514247321425, -0.24692644764957947, -0.24388951780991378, -0.2425605883828718, -0.24365545758211732, -0.24784932324117306, -0.2557573333763009, -0.2679163595478312, -0.2847684747484684, -0.3066465779242802, -0.3337625562842708, -0.36619831551669246, -0.40389993839825034, -0.4466751557675501, -0.4941942323234763, -0.5459942852183707, -0.6014869680394187, -0.6599693686309649, -0.720637888400981, -0.7826047952942942, -0.8449170743927693, -0.9065771408326289, -0.9665649309075904, -1.0238608500941804, -1.0774690322465406, -1.1264403530057128, -1.169894642869382, -1.2070415613533578, -1.237199622891974, -1.2598129068897852, -1.2744650376602034, -1.2808900835899961, -1.2789800972188805, -1.2687890972700075, -1.2505333780846681, -1.2245881193502122, -1.191480357334537, -1.1518784658993424, -1.106578379232448, -1.056486866472205, -1.0026022392814562, -0.9459929352300942, -0.8877744710507042, -0.829085299186915, -0.7710621275935647, -0.7148152758207095, -0.6614046396976424, -0.6118168224443059, -0.5669439621284735, -0.5275647447391484, -0.4943280397527282, -0.4677395322086296, -0.4481516535212843, -0.4357570342889514, -0.4305856181450964, -0.4325054882901293, -0.44122736987182554, -0.4563126840072328, -0.47718494508374026, -0.5031442140871275, -0.5333842489930799, -0.5670119304601344, -0.6030684886896832, -0.6405520166269442, -0.6784407266318379, -0.7157163930033992, -0.751387421620951, -0.7845110004588187, -0.8142138104928324, -0.8397108148742223, -0.8603216942181374, -0.8754845561745671, -0.8847666166000208, -0.8878716258959178, -0.8846438955192153, -0.87506886427338, -0.8592702296506244, -0.8375037540951202, -0.8101479374988024, -0.7776918235163656, -0.7407202765173586, -0.6998971264831128, -0.6559466294282323, -0.6096337297617327, -0.5617436374703069, -0.5130612464846833, -0.46435092078399776, -0.4163371617389562, -0.3696866442599936, -0.3249920711900586, -0.2827582460556464, -0.24339070503507285, -0.2071871813370028, -0.1743321008307053, -0.14489422862275636, -0.11882750434112387, -0.09597502124186036, -0.07607602298645341, -0.05877571410236886, -0.043637607700330365, -0.030158068806354323, -0.01778265531833217, -0.005923812535305653, 0.006020557408037114, 0.018648152168070094, 0.03253346226887952, 0.04820960732775076, 0.06615130542137022, 0.0867594362834055, 0.11034761786910659, 0.13713116385307916, 0.1672187281546483, 0.2006068731635299, 0.2371777227204909, 0.27669978100417925, 0.3188319163069158, 0.36313042632847164, 0.40905902116409687, 0.4560014836525152, 0.5032766961257764, 0.5501556596651326, 0.5958800783244035, 0.6396820378124635, 0.6808042769419074, 0.7185205315702912, 0.7521554252873238, 0.7811033889127513, 0.8048461118092523, 0.8229680615976595, 0.8351696542860702, 0.8412777129900111, 0.8412529189571835, 0.8351940319099292, 0.8233387359766154, 0.8060610507422324, 0.7838653321471282, 0.7573769729864713, 0.7273299954967168, 0.6945518068959886, 0.659945460813438, 0.6244698314907162, 0.5891181618567372, 0.5548954896917905, 0.5227954870085854, 0.4937772656840276, 0.4687427067952763, 0.44851486189742534, 0.433817951814934, 0.4252594529237899, 0.4233147132149352, 0.4283144817901924, 0.44043566725927435, 0.45969556442759335, 0.48594970653315034, 0.5188934141019756, 0.5580670233429584, 0.6028646890430689, 0.6525465712990024, 0.7062541342227987, 0.7630282099717683, 0.821829414906567, 0.8815604480043127, 0.9410897562344228, 0.999276018556485, 1.0549928803325521, 1.1071533637489264, 1.154733387468263, 1.1967938499972637, 1.2325007656390206, 1.2611429885632357, 1.2821471183316073, 1.2950892477474618, 1.299703289508388, 1.2958856999817203, 1.2836965044974011, 1.2633566167609744, 1.2352415331812696, 1.1998715689349586, 1.1578988843615579, 1.1100916258124813, 1.0573155725369983, 1.0005137389474699, 0.9406844282781367, 0.8788582681220798, 0.8160747797878846, 0.7533590413704615, 0.6916989987218606, 0.6320239593168643, 0.575184771845094, 0.5219361500562644, 0.47292154406456105, 0.4286608973786447, 0.3895415549966824, 0.35581250881535725, 0.32758208332175837, 0.30481907913906636, 0.2873573066017627, 0.2749033582583389, 0.2670473900972572, 0.263276608314603, 0.26299109338224647, 0.26552153762544284, 0.2701484278303506, 0.276122171653378, 0.2826836465739634, 0.28908464328016353, 0.29460768183208486, 0.2985846985090817, 0.30041413338299633, 0.2995759925282423, 0.29564451324522284, 0.2882981243375736, 0.27732646471976774, 0.26263430062571025, 0.2442422624857338, 0.22228440509087352, 0.19700267688001702, 0.16873846398930123, 0.13792145007855863, 0.10505610199489537, 0.07070615230775928, 0.03547750111680778, 3.297132057972448e-16], [-0.0, -0.03567171413132461, -0.07003678288586532, -0.10251617084882317, -0.1325914129219556, -0.15982036001812927, -0.18385083366446073, -0.20443181673553823, -0.22142187126668977, -0.23479454604673136, -0.24464061464654951, -0.25116706673310585, -0.25469285986854595, -0.2556415233654149, -0.25453078802312434, -0.25195949362022885, -0.24859209789736866, -0.24514117460549717, -0.24234834238073905, -0.24096410934845788, -0.24172714933746456, -0.2453435435867585, -0.25246652636178524, -0.2636772638116823, -0.2794671728810463, -0.30022225166381, -0.3262098451013662, -0.35756821153394125, -0.3942991877403179, -0.43626417441310683, -0.4831835823803363, -0.5346397943171949, -0.5900836093148365, -0.648844050656693, -0.7101413326632503, -0.7731027026122721, -0.8367808005214106, -0.900174114832169, -0.9622490573905563, -1.0219631379659482, -1.0782886879896492, -1.1302365660231624, -1.176879274148528, -1.2173729251333885, -1.2509775246404966, -1.2770750703647027, -1.2951850199023711, -1.304976740196672, -1.3062786220889024, -1.2990836221329378, -1.2835510784907762, -1.2600047363646258, -1.2289270088768687, -1.1909495893780868, -1.1468406186461155, -1.0974886931981183, -1.0438840769486162, -0.9870975458486978, -0.928257352284176, -0.8685248414922064, -0.809069284961096, -0.751042514902565, -0.6955539489586415, -0.6436465851987891, -0.5962745243965953, -0.5542825401106133, -0.5183881681200001, -0.48916672647769815, -0.4670396073137547, -0.45226610326127265, -0.4449389468973519, -0.4449836529527543, -0.45216166240819144, -0.4660771971707792, -0.4861876460124499, -0.5118172189926982, -0.5421735307064612, -0.5763667042559448, -0.6134305294946296, -0.6523451622347685, -0.6920608168635168, -0.7315218839837521, -0.7696908977579653, -0.805571784719861, -0.8382318467152772, -0.866821964789053, -0.8905945573694323, -0.9089188838346556, -0.9212933520225628, -0.9273545637702238, -0.9268829142592256, -0.9198046467570917, -0.9061903521529272, -0.8862499903077591, -0.8603245955086251, -0.8288749091252481, -0.7924672569292518, -0.7517570546234619, -0.7074703813275363, -0.6603841057102987, -0.6113050820662278, -0.5610489531306327, -0.5104191023707606, -0.4601862907730855, -0.41106949200600373, -0.3637184058430224, -0.3186980837748768, -0.27647604400842335, -0.23741218700149108, -0.20175174900279078, -0.16962145162985087, -0.1410289223421383, -0.11586537585856126, -0.09391146227376133, -0.07484610597578842, -0.058258082519568814, -0.0436600103064188, -0.03050437203084702, -0.018201128940107097, -0.006136450315152936, 0.006307947755177493, 0.019735375561023005, 0.034715178106373035, 0.05176469027298633, 0.07133262584328005, 0.09378435024052431, 0.1193894380928716, 0.14831185762809657, 0.1806030559519993, 0.21619814417260938, 0.25491530100299314, 0.2964584299391805, 0.34042302048072526, 0.38630508028343385, 0.43351292472640895, 0.48138153518123167, 0.5291891292036784, 0.576175526665306, 0.6215618470208312, 0.6645710357262923, 0.7044486932513412, 0.7404836688208446, 0.7720278832986927, 0.7985148614734203, 0.8194764830635702, 0.8345575033422541, 0.8435274473818192, 0.8462895452475492, 0.8428864474722605, 0.8335025390499429, 0.8184627540484222, 0.7982278796826662, 0.7733864261596414, 0.7446432246273763, 0.7128049979908138, 0.6787632261352295, 0.643474696300269, 0.6079401892332452, 0.5731818008058294, 0.5402194357545743, 0.5100470341511264, 0.48360910148981495, 0.4617781096032919, 0.44533331802948645, 0.4349415343474069, 0.43114028810153743, 0.4343238372876308, 0.4447323603111226, 0.46244461144596966, 0.4873742359293389, 0.5192698539141073, 0.5577189326808651, 0.6021553759725314, 0.6518706702670886, 0.7060283424220063, 0.7636814034954632, 0.823792381622764, 0.8852554843627395, 0.9469203794590922, 1.0076170437480705, 1.066181103949349, 1.1214790809410722, 1.1724329511430547, 1.2180434547679366, 1.2574116105572761, 1.289757939470011, 1.3144389545896413, 1.330960539925818, 1.3389879152090178, 1.3383519653968805, 1.3290518004357077, 1.3112535007327208, 1.2852850946019898, 1.251627903438036, 1.2109044763685999, 1.1638634165530337, 1.1113614741755884, 1.0543433447713295, 0.9938196642846545, 0.9308437329331652, 0.8664875275680357, 0.8018175761438618, 0.7378712678319592, 0.675634158271757, 0.6160188018394969, 0.5598456023393055, 0.5078261212226317, 0.4605492196400058, 0.4184703389033493, 0.3819041450837103, 0.35102067945593574, 0.32584506942028096, 0.3062607665432039, 0.29201619164617154, 0.28273458357523684, 0.2779267704594474, 0.2770065118260689, 0.2793079986105414, 0.2841050473742138, 0.2906314861510292, 0.2981022032161123, 0.3057343173149787, 0.3127679287876886, 0.3184859255021255, 0.32223234517015087, 0.32342883572656916, 0.3215888069606251, 0.316328928177012, 0.3073776967514714, 0.29458087924876764, 0.27790370833589184, 0.2574298029823981, 0.2333568642597544, 0.20598928228811336, 0.17572786943027202, 0.1430570086919019, 0.10852957259284647, 0.07275002485656333, 0.03635616368728039, 3.3651968076615236e-16], [-0.0, -0.036130167273643744, -0.07065187134919688, -0.103001964072814, -0.13268826266847558, -0.15930454037133007, -0.1825431510207604, -0.20220494182958407, -0.21820617880864518, -0.23058228675760037, -0.23948828837434943, -0.24519591279616554, -0.2480874305937267, -0.24864635769769752, -0.24744525277818613, -0.2451309091358048, -0.2424073112504352, -0.24001678600623721, -0.23871982773396905, -0.2392741133171669, -0.24241324772965403, -0.24882579086497641, -0.25913511308112636, -0.2738806095624597, -0.29350077278908926, -0.3183185788349399, -0.3485295879424351, -0.3841930941927914, -0.425226584716073, -0.47140368759644385, -0.5223557014339609, -0.577576710560145, -0.6364322003797056, -0.6981709994534052, -0.7619402909391224, -0.8268033579705701, -0.8917596574337397, -0.9557667561655553, -1.0177636143769864, -1.076694664348973, -1.1315341091129656, -1.181309856527755, -1.2251265091737107, -1.2621868497249784, -1.291811294498009, -1.3134548339386451, -1.3267210368042568, -1.3313727633308763, -1.3273393100944555, -1.314719793705419, -1.2937826698661663, -1.2649613764968026, -1.2288461823479808, -1.1861724135084097, -1.1378053172544143, -1.0847219036509639, -1.0279901782152372, -0.9687462420086503, -0.9081697871846945, -0.8474585550191508, -0.7878023488275832, -0.7303572053059006, -0.6762203244364625, -0.6264063402624857, -0.581825482979484, -0.543264137698989, -0.5113682480058284, -0.4866299444516886, -0.4693777010628941, -0.45977023866966094, -0.45779430444281277, -0.4632663646326326, -0.4758381543943891, -0.4950059370232164, -0.5201232371342804, -0.5504167304444852, -0.5850048988239216, -0.6229189949774576, -0.6631258080376737, -0.7045516807707941, -0.7461072019787202, -0.7867119846527476, -0.8253189417797192, -0.8609374873476799, -0.8926551196218014, -0.9196568863979654, -0.9412422866050759, -0.9568392279373998, -0.9660147345154034, -0.9684821800384886, -0.9641049084747377, -0.9528961938777947, -0.9350155812076819, -0.9107617388255934, -0.8805620384394705, -0.8449591576010229, -0.8045950714473733, -0.7601928624899641, -0.7125368283675112, -0.6624514063632306, -0.6107794592112216, -0.5583604786842545, -0.5060092614111278, -0.45449559541216117, -0.404525466409066, -0.35672425083936204, -0.31162230877979846, -0.26964332604065205, -0.2310956821689531, -0.19616704184135753, -0.16492228315017912, -0.13730478971745524, -0.11314104660245851, -0.09214839479516305, -0.07394571786138042, -0.058066759072232924, -0.043975700006269644, -0.031084573851278614, -0.018772039906745076, -0.00640301127001895, 0.00665139375540471, 0.020994113827166486, 0.03718315163976523, 0.0557138376313147, 0.0770028292873945, 0.10137427993578618, 0.12904855467882884, 0.16013380511117267, 0.19462064038900279, 0.23238005192594663, 0.27316466452218313, 0.3166133002246326, 0.3622587548587865, 0.4095386031562533, 0.4578087688593825, 0.5063595231384493, 0.5544335099699493, 0.6012453424512431, 0.6460022707726505, 0.6879253918538781, 0.7262708532854092, 0.7603505006716815, 0.7895514278799732, 0.8133539138364779, 0.8313472668137419, 0.8432431467258258, 0.848885996584662, 0.8482602844893644, 0.8414943355933932, 0.8288606174963828, 0.8107724303596185, 0.7877770425675665, 0.7605454017268047, 0.7298586369912643, 0.696591649975634, 0.6616941658313659, 0.6261696815444735, 0.5910528035183943, 0.557385509632084, 0.5261929011073777, 0.4984590258945671, 0.4751033574429015, 0.45695850056659887, 0.4447496699030954, 0.4390764467925252, 0.44039726822263486, 0.4490170380286232, 0.46507817734000034, 0.48855535009585055, 0.5192540122746796, 0.5568128424247197, 0.6007100183531686, 0.6502732127003207, 0.7046930908375275, 0.7630400102691164, 0.8242835435503828, 0.8873143785466315, 0.9509680923237998, 1.0140502494913592, 1.075362243530345, 1.133727281328471, 1.1880159072634273, 1.237170473824433, 1.2802279906851093, 1.3163408227327889, 1.3447947588799642, 1.3650240362821802, 1.3766229773309302, 1.3793539777054185, 1.3731516708793932, 1.3581231856642482, 1.3345445064044796, 1.3028530380601098, 1.2636365683591673, 1.2176189042953698, 1.1656425384173463, 1.1086487697136114, 1.0476557627684688, 0.9837350758338523, 0.917987222411579, 0.8515168510711104, 0.7854081340826704, 0.7207009469190551, 0.6583683980202681, 0.59929623201916, 0.5442645808214429, 0.49393247675737123, 0.4488254719892533, 0.4093266302239361, 0.3756710724937748, 0.34794417043171166, 0.32608339027085, 0.3098837009810853, 0.299006372736424, 0.2929909094375613, 0.29126978332408027, 0.29318557265497397, 0.29801004665215103, 0.30496469676721, 0.3132421809320951, 0.3220281285550217, 0.33052274905164675, 0.3379616957374284, 0.34363565967999893, 0.3469082040074111, 0.3472313972497812, 0.344158863315645, 0.33735593415659615, 0.32660666730687066, 0.3118175723621374, 0.2930179760060275, 0.27035704223764395, 0.24409755079758652, 0.21460662025352242, 0.18234364068394965, 0.1478457524129776, 0.11171126999941486, 0.07458150309202646, 0.0371214665128916, 3.4222105640597696e-16], [-0.0, -0.036463343538006225, -0.07101731383197106, -0.1031209700024248, -0.1323145386280695, -0.1582334605573084, -0.1806198067653196, -0.19933074930493505, -0.21434384981700266, -0.2257590106847514, -0.23379702064576713, -0.23879471531840302, -0.24119686141066132, -0.24154495911900264, -0.24046323821475937, -0.23864219749652932, -0.23682010276645846, -0.23576291359134083, -0.23624315241898297, -0.23901826001346974, -0.24480899784944732, -0.2542784606079675, -0.26801225014199515, -0.28650033648353407, -0.3101210922532276, -0.3391279351512686, -0.37363895031345923, -0.41362979174933656, -0.45893008162643323, -0.5092234398129608, -0.5640511859788131, -0.6228196649191577, -0.6848110548859118, -0.7491974308568157, -0.8150577720360574, -0.8813975275363134, -0.9471702880351046, -1.0113010559002018, -1.0727105632457936, -1.1303400577183242, -1.1831759602954148, -1.230273798441, -1.2707808316637736, -1.3039568145812035, -1.3291923843497935, -1.346024613796694, -1.3541493374752762, -1.3534299335815516, -1.3439023283779719, -1.325776079445121, -1.2994314875389246, -1.2654127817938723, -1.2244175171636666, -1.1772824140288412, -1.1249659555990186, -1.0685281369968882, -1.0091078288130688, -0.9478982757754023, -0.8861212965609898, -0.8250007825782008, -0.7657361109738842, -0.7094760897452754, -0.6572940405858657, -0.6101645982631213, -0.5689427645641957, -0.5343457011446334, -0.5069376802832376, -0.4871185371757142, -0.47511588382863973, -0.4709812548811306, -0.4745902619719486, -0.48564673786800316, -0.5036907567994117, -0.5281103256120028, -0.5581564536818916, -0.5929612301406755, -0.6315584667557067, -0.6729064054912941, -0.7159119427680536, -0.7594557888589938, -0.8024179615008319, -0.8437030080956782, -0.8822643609082083, -0.9171272541418575, -0.9474096700632999, -0.9723408324590024, -0.991276828357182, -1.0037130115584008, -1.0092929222708722, -1.0078135440277087, -0.9992268099116809, -0.9836373626734554, -0.961296665310147, -0.932593647799497, -0.8980421597647245, -0.8582655758095107, -0.8139789682265559, -0.7659693190893316, -0.7150742889963461, -0.6621600918642764, -0.6080990434042, -0.5537473548544234, -0.49992373313248145, -0.4473893241137782, -0.3968294979012206, -0.3488379247084118, -0.3039033286355494, -0.2623992357447385, -0.2245769542479818, -0.19056194030500684, -0.16035361502769213, -0.13382860902810859, -0.110747322483648, -0.09076360345551317, -0.07343726723444528, -0.05824910681344173, -0.04461798102941786, -0.031919514071113424, -0.019505899245116462, -0.006726272147561012, 0.007052895601652737, 0.022427930796607612, 0.03993915579113388, 0.0600536549648833, 0.08315007618329044, 0.10950588000959806, 0.13928738587526696, 0.17254289183537483, 0.20919906476481567, 0.24906071290794732, 0.29181396472933807, 0.33703278925443875, 0.3841887057863751, 0.4326634472542999, 0.4817642636151534, 0.5307414816767922, 0.5788078772250523, 0.6251593659717355, 0.6689964828685577, 0.7095460957184166, 0.7460827893908971, 0.7779493615947163, 0.8045758899993812, 0.8254968630995798, 0.8403659128008464, 0.8489677441695533, 0.8512269257303943, 0.8472132804415561, 0.8371437011394482, 0.821380302751895, 0.8004249147367344, 0.7749100087457648, 0.7455862461619155, 0.713306915671399, 0.6790096102720934, 0.643695564094163, 0.6084071303301294, 0.5742039308952663, 0.5421382449056537, 0.5132302257263633, 0.48844354460174877, 0.4686620524842941, 0.4546680307401883, 0.4471225664007178, 0.4465485393687618, 0.4533166486276805, 0.46763483348478646, 0.48954136592753644, 0.5189018032146626, 0.5554098979794126, 0.598592468623902, 0.6478181379372013, 0.7023097549912484, 0.7611602267294633, 0.8233514034322583, 0.8877755884367434, 0.9532591789147563, 1.0185878927347152, 1.0825329977221552, 1.143877934944155, 1.2014447175857104, 1.2541194918133567, 1.300876665622002, 1.340801045560908, 1.373107468611112, 1.3971574761856431, 1.412472647790833, 1.418744291601718, 1.4158392761227938, 1.4038018791085234, 1.3828516247633362, 1.3533771756182402, 1.3159264390689853, 1.271193138083565, 1.2200001788710453, 1.1632802233312398, 1.1020539390623303, 1.0374064530272418, 0.9704625753935564, 0.9023613866084087, 0.8342307928344163, 0.7671626521965097, 0.7021890569776804, 0.6402603254182545, 0.5822252119308088, 0.5288137874810958, 0.4806233740430074, 0.43810784011393755, 0.40157048019803143, 0.37116061202315337, 0.3468739332678374, 0.32855658701756973, 0.3159127943347836, 0.30851582545548706, 0.3058220003555259, 0.30718733674316556, 0.3118864007086158, 0.3191328638230707, 0.32810123167104965, 0.3379491835444113, 0.3478399519091771, 0.35696417350834353, 0.3645606614575367, 0.3699355789430664, 0.3724795393181051, 0.3716822133658434, 0.3671440908187634, 0.3585851181953993, 0.34585001673063626, 0.32891017055798677, 0.3078620641639071, 0.28292233722760074, 0.2544196120352835, 0.2227833315190892, 0.18852992253039827, 0.15224666728850478, 0.11457372433036789, 0.07618478725972758, 0.03776690397649118, 3.467707609450149e-16], [-0.0, -0.03666915311860848, -0.07113232317433292, -0.10287710709960284, -0.13148215645814393, -0.15663009435394062, -0.1781175498816211, -0.19586203268135832, -0.20990545226902652, -0.22041417404520225, -0.22767559403533502, -0.23209130519377957, -0.23416701721434866, -0.23449947696756304, -0.23376071576442928, -0.23268002061396542, -0.23202408768392763, -0.2325758657256025, -0.23511263400491605, -0.24038388233321495, -0.24908956949483047, -0.2618593304669286, -0.2792331824280747, -0.30164424512697097, -0.32940394355583336, -0.3626901012000207, -0.4015382618766959, -0.4458364990582592, -0.4953238855538316, -0.5495927056237403, -0.6080943982812282, -0.6701491270139216, -0.7349587797666862, -0.8016231160513884, -0.8691586976672722, -0.936520167748571, -1.0026233815148902, -1.0663698427412494, -1.1266718638513569, -1.18247784560708, -1.232797065207445, -1.276723369445842, -1.3134571922580405, -1.3423253530127515, -1.3627981423819315, -1.3745032653776186, -1.377236284648144, -1.3709672896141878, -1.3558436064947088, -1.3321884585496868, -1.3004955826542883, -1.2614199052560662, -1.2157644754841634, -1.1644639433602386, -1.1085649544957714, -1.0492039073041404, -0.9875825827758571, -0.9249422086882784, -0.8625365584712905, -0.8016047088810748, -0.7433440895517606, -0.6888844511725002, -0.6392633576225443, -0.5954037714050417, -0.558094252024962, -0.5279722247662524, -0.5055107041525193, -0.49100877400699505, -0.48458603646868537, -0.4861811477550647, -0.49555446119131535, -0.5122947004207087, -0.5358294901452644, -0.565439480543358, -0.6002757168853186, -0.6393798298695392, -0.6817065566665105, -0.7261480491640059, -0.771559385732917, -0.8167846769314028, -0.8606831445335711, -0.9021545573412533, -0.9401634262741574, -0.9737613947285448, -1.0021073072859723, -1.0244844993470534, -1.040314920663085, -1.049169785277072, -1.0507765270803178, -1.0450219318834142, -1.0319514113150625, -1.011764478659982, -0.9848065795854931, -0.951557519296153, -0.9126168098185578, -0.8686863348399757, -0.820550793004604, -0.7690564322683207, -0.7150886265813926, -0.659548870890053, -0.6033317806528915, -0.5473026775498419, -0.49227632398109555, -0.4389973358343037, -0.3881227567137585, -0.34020721857538333, -0.2956910449928389, -0.2548915758490475, -0.21799790807462524, -0.1850691582762171, -0.15603626196175305, -0.1307072328795831, -0.10877571704593149, -0.08983259158190297, -0.07338028064358774, -0.05884939146391375, -0.04561721457259012, -0.03302758509925234, -0.02041156787548085, -0.007108408686924013, 0.007513812008045499, 0.024038378138357578, 0.042981522413831276, 0.06477589224497761, 0.08975634427216089, 0.11814845397624583, 0.1500600562661059, 0.18547605418321605, 0.22425664792408906, 0.26613904740838507, 0.31074264086808495, 0.3575775017014137, 0.4060560284135379, 0.45550743007512856, 0.5051946944661151, 0.5543336098551565, 0.6021133558899904, 0.6477181357669686, 0.6903492918329608, 0.729247330840581, 0.7637132836673627, 0.7931288374964732, 0.8169747059500656, 0.8348467438169427, 0.8464693668306017, 0.8517059021199697, 0.8505655698744338, 0.8432068795911597, 0.8299373129585034, 0.8112092577764654, 0.7876122510288012, 0.7598616819678441, 0.7287841955371501, 0.6953001204001381, 0.6604033221582711, 0.6251389491081889, 0.5905795934144684, 0.5578004334491822, 0.5278539521676257, 0.5017448409859242, 0.480405698293804, 0.4646741164350285, 0.45527172105011765, 0.4527856827940068, 0.4576531646540338, 0.470149099760131, 0.4903776163456282, 0.5182673402768326, 0.5535707134159663, 0.5958673702576986, 0.6445715181205902, 0.6989431700537868, 0.7581029868864029, 0.8210503977726359, 0.8866845893030945, 0.9538278837076292, 1.0212509685750164, 1.087699395289227, 1.151920732145285, 1.2126917416325336, 1.2688449500708772, 1.319293991696232, 1.3630571380825431, 1.3992784667623794, 1.4272461790225581, 1.446407644739076, 1.4563808301238614, 1.4569618504830728, 1.448128482431521, 1.4300395662200773, 1.4030303265691306, 1.3676037372820231, 1.3244181485816415, 1.2742714842956069, 1.2180823965720304, 1.1568688367893651, 1.0917245610183968, 1.0237941353688957, 0.9542470396888385, 0.8842514866035291, 0.81494857636774, 0.7474273964093183, 0.6827016480913894, 0.6216883427984645, 0.5651890559907478, 0.5138741627207268, 0.46827040290300403, 0.4287520412518084, 0.3955357973288947, 0.36867962780157076, 0.34808534811066, 0.33350498663974004, 0.32455067348264444, 0.3207077802670887, 0.32135094931089747, 0.32576258157696186, 0.3331532951297304, 0.34268382047764157, 0.3534877673977191, 0.3646946803268324, 0.3754527965581673, 0.3849509333239004, 0.39243895603280715, 0.3972463197637537, 0.3987982285528639, 0.39662902070085543, 0.3903924616359315, 0.37986870692773844, 0.36496778479890535, 0.3457295377239772, 0.32232005415788006, 0.2950247117877655, 0.26423804067438483, 0.2304506960511044, 0.19423390433223595, 0.15622181019314746, 0.11709220580844218, 0.07754616413760572, 0.03828712550982512, 3.501338376429912e-16], [-0.0, -0.036746875846969146, -0.07099890723616208, -0.10227849667465562, -0.13020855150387645, -0.1545240897537615, -0.17508072876883565, -0.19185982015386807, -0.2049700818385456, -0.21464566925988, -0.22124072049672291, -0.225220502308908, -0.22714937309642796, -0.227675862538765, -0.22751524396961928, -0.22743004244148549, -0.22820897722537004, -0.23064488073808329, -0.23551216547077028, -0.24354442562714712, -0.255412760449234, -0.27170539156557594, -0.29290911746935444, -0.3193931051150214, -0.3513954626551249, -0.38901296989064693, -0.43219426573534747, -0.48073670680340835, -0.5342870202281625, -0.5923457792656919, -0.6542756344820537, -0.7193131387536006, -0.7865839132889177, -0.8551208166879922, -0.923884701829377, -0.9917872780659751, -1.0577155405197483, -1.1205571856155119, -1.1792264034842708, -1.2326894242495312, -1.2799891968707748, -1.3202685961646825, -1.3527915854866004, -1.3769618085927957, -1.392338143327061, -1.3986468205674325, -1.3957897926233933, -1.3838491240360653, -1.3630872723475396, -1.3339432245674014, -1.297024554380025, -1.2530955631792113, -1.2030617623882511, -1.1479510429123503, -1.088891957808457, -1.0270896143752934, -0.963799730139658, -0.9003014522089718, -0.8378695700639569, -0.7777467673201814, -0.7211165579052488, -0.6690775364712196, -0.6226195420628772, -0.5826022888356003, -0.5497369590598631, -0.5245711831866501, -0.507477751094738, -0.4986473097612671, -0.49808520765643444, -0.5056125474741783, -0.5208714087763664, -0.5433341031828582, -0.5723162292897299, -0.6069932048612106, -0.646419872190984, -0.6895527008409107, -0.7352740519687444, -0.782417921591128, -0.8297965475095673, -0.8762272470201493, -0.9205588503266184, -0.9616971077972444, -0.9986284774846723, -1.030441741931873, -1.0563469591319266, -1.0756913201865654, -1.0879715640213745, -1.0928426855208335, -1.0901227655030408, -1.079793846775606, -1.0619988777270228, -1.0370348411085186, -1.0053422784772146, -0.9674915079188331, -0.9241659120091462, -0.8761427425684472, -0.8242719469191656, -0.7694535656680663, -0.7126142834182884, -0.6546837305385328, -0.5965711358095381, -0.539142916438926, -0.4832017639665378, -0.4294677427199, -0.3785618628146838, -0.33099252363748816, -0.28714514798869917, -0.24727524353244748, -0.2115050390202727, -0.17982375018431843, -0.15209143657543459, -0.12804631831443358, -0.10731533305771582, -0.08942763068349852, -0.07383062836359822, -0.059908183677286696, -0.04700038987822418, -0.0344244566828182, -0.021496113025381007, -0.007550955790261015, 0.008034829113340806, 0.025824929891565467, 0.04630508142168025, 0.0698674275865161, 0.09679749657246589, 0.1272641442478742, 0.16131274350594632, 0.19886181301571504, 0.23970318931521722, 0.28350575387066135, 0.32982263395396677, 0.3781017053117038, 0.4276991379188257, 0.4778956458347336, 0.5279150303523844, 0.5769445440886404, 0.6241565539845589, 0.668730944650844, 0.709877681060494, 0.746858941859537, 0.7790102417712882, 0.8057599835690974, 0.826646916374935, 0.8413350267356183, 0.8496254508262059, 0.8514650687146554, 0.8469515231061667, 0.8363344933564302, 0.8200131486103952, 0.798529799375561, 0.7725598622994583, 0.7428983460079229, 0.7104431542455024, 0.6761755840252015, 0.6411384689919201, 0.6064124799007184, 0.5730911434399534, 0.5422551763259159, 0.5149467527308452, 0.4921443291092198, 0.47473864116146874, 0.46351046320072165, 0.45911068112373177, 0.4620431774495563, 0.4726509617363223, 0.49110590368350543, 0.5174023412110539, 0.5513547438392543, 0.5925995150108805, 0.6406009179561922, 0.6946610107195772, 0.7539333794640581, 0.8174403675088087, 0.8840934129821646, 0.9527160325630072, 1.0220689243900751, 1.0908766114257726, 1.1578550086452195, 1.2217392743202926, 1.2813112979575687, 1.3354261853270681, 1.3830371243023585, 1.4232180533616348, 1.45518360664992, 1.47830587421, 1.4921275917791026, 1.4963714595745965, 1.4909453816836609, 1.4759435147832012, 1.4516431145821542, 1.4184972681724672, 1.3771236979697286, 1.3282899157503092, 1.2728950911961836, 1.2119490762603526, 1.1465490927072244, 1.0778546437741179, 1.0070612507605432, 0.9353736405377147, 0.8639790199011371, 0.7940210671577641, 0.7265752505209849, 0.6626260473316181, 0.6030465887427326, 0.5485811925506829, 0.49983117388131926, 0.45724424127528085, 0.42110769640759826, 0.3915455614454034, 0.3685196612307881, 0.35183459046945365, 0.3411464013055997, 0.3359747564044965, 0.33571820916437506, 0.3396721979834181, 0.3470492774379475, 0.3570010573383631, 0.368641282168058, 0.3810694592886864, 0.3933944350653618, 0.4047573239083014, 0.4143532159474318, 0.421451124087934, 0.4254116796155664, 0.42570214607666773, 0.42190839229396937, 0.41374354527907975, 0.4010531304334932, 0.3838165975944779, 0.3621452248734249, 0.3362764854926623, 0.30656505360020203, 0.273470711043926, 0.23754349615365764, 0.1994065057249031, 0.1597368208616181, 0.11924507462750715, 0.07865421339403568, 0.03867802351350385, 3.522876073600707e-16], [-0.0, -0.036697199074634694, -0.0706219054747758, -0.10133745806757845, -0.128516593016478, -0.15195156459803963, -0.17156093398945327, -0.1873928347572768, -0.1996246155498747, -0.208558854945022, -0.2146158381355225, -0.2183226777458918, -0.22029934921010733, -0.2212419925625551, -0.22190390512677285, -0.2230747115733534, -0.22555824756893278, -0.23014972946755022, -0.23761280425688774, -0.2486570806800496, -0.2639167339007606, -0.283930752441007, -0.3091253579487294, -0.3397990765682171, -0.37611087654912845, -0.41807171181523983, -0.4655397273676747, -0.5182192916933488, -0.5756639260372945, -0.6372831028472401, -0.7023527883408837, -0.7700295094125896, -0.8393676353580609, -0.9093394824059161, -0.9788577758814377, -1.0467999428406578, -1.1120336587795365, -1.1734430368073645, -1.2299548273952683, -1.2805639920206728, -1.3243580248961193, -1.3605394232773094, -1.3884457479904768, -1.4075667708346609, -1.4175582730873435, -1.4182521378469564, -1.40966246648494, -1.3919875439292682, -1.3656075765626308, -1.3310782277763504, -1.2891200772023208, -1.2406042278795104, -1.1865343786926306, -1.1280257650654837, -1.0662814469971382, -1.002566488224, -0.9381806219813592, -0.8744300362483914, -0.8125989335631869, -0.7539215269346363, -0.6995551238861778, -0.6505549254635529, -0.6078511267304478, -0.5722288508376819, -0.5443113815054564, -0.5245470803388714, -0.5132002877135551, -0.5103464111553238, -0.5158713055044554, -0.5294749471270002, -0.5506793024957944, -0.5788401920917581, -0.6131628561862627, -0.6527208419481049, -0.6964777535841382, -0.7433113407482824, -0.792039346839339, -0.8414464993354213, -0.8903119999154944, -0.9374368633583059, -0.9816704612630002, -1.0219356492924334, -1.0572518943044638, -1.0867558694460362, -1.1097190497324025, -1.125561916202348, -1.1338644615406832, -1.1343727819798728, -1.1270016370498395, -1.1118329579408597, -1.089110384426366, -1.0592300070129985, -1.022727582863987, -0.980262578823201, -0.9325994704766013, -0.8805867907829865, -0.8251344738219804, -0.7671900773952199, -0.7077144916742913, -0.6476577492818233, -0.5879355449676037, -0.5294070506305504, -0.4728545744495844, -0.4189655622933122, -0.3683173766892007, -0.3213652150615142, -0.27843344657103425, -0.2397105578029347, -0.20524780401042914, -0.17496156699691917, -0.14863932542256217, -0.12594905075468718, -0.10645175457529442, -0.08961683271286136, -0.07483978069427451, -0.061461795094981383, -0.048790728000630106, -0.03612282816343943, -0.022764683376757057, -0.008054774569674714, 0.008615936770743739, 0.027784940301009965, 0.04990113998707961, 0.07531030781676354, 0.10424342208863821, 0.13680820911191147, 0.17298412371948774, 0.21262091444211384, 0.25544082578470184, 0.30104439515442954, 0.34891970802091676, 0.39845488422682795, 0.4489534833167264, 0.49965243947805105, 0.5497420691620821, 0.5983876384037538, 0.6447519337291314, 0.6880182514480783, 0.7274132058453376, 0.7622287577036506, 0.7918428807342859, 0.8157383144881791, 0.8335188974361704, 0.8449230320460038, 0.8498339034244694, 0.848286152720127, 0.8404687940289488, 0.8267242568436112, 0.807543532820087, 0.783557503394856, 0.7555246211338835, 0.7243152102210448, 0.6908927378799385, 0.6562924865965287, 0.6215981248011587, 0.5879167294574111, 0.5563528563673067, 0.5279822818420116, 0.503826051966968, 0.48482547264886067, 0.4718186549938448, 0.4655191967425207, 0.46649753226392726, 0.4751654221325941, 0.4917639800529153, 0.5163555516208734, 0.5488196681417085, 0.5888532016713268, 0.6359747469831494, 0.68953315473261, 0.7487200401779397, 0.8125859958643631, 0.8800601470407344, 0.9499726074534162, 1.0210793225446746, 1.0920887287104952, 1.161689612584425, 1.228579524414807, 1.2914930852365178, 1.3492295290675966, 1.4006788387610671, 1.4448458669973814, 1.4808718814210482, 1.5080530339531844, 1.5258553273675433, 1.533925735523242, 1.532099225175027, 1.5204015248028426, 1.4990475870418953, 1.468435793590418, 1.4291380524360304, 1.381886034418406, 1.3275538871762094, 1.2671378472030537, 1.2017332430603218, 1.1325094430204348, 1.060683347097183, 0.9874920554489393, 0.9141653617662627, 0.8418987211066435, 0.7718273267337251, 0.70500190026025, 0.6423667545651308, 0.584740630693257, 0.532800739718829, 0.4870703601177565, 0.44791025255857425, 0.41551405938883285, 0.38990775781318937, 0.37095313626325976, 0.3583551652052719, 0.35167303904116193, 0.3503345771572357, 0.35365359173358857, 0.36084975961157045, 0.3710704770346405, 0.38341413084114456, 0.39695418877484007, 0.4107634957109568, 0.42393816211659247, 0.4356204459351385, 0.44502005888336765, 0.451433372083755, 0.4542600528796246, 0.45301673313040364, 0.447347387507865, 0.4370301863190855, 0.4219806789852132, 0.40225125918727683, 0.37802695845372974, 0.34961770919342705, 0.3174473084986036, 0.2820393981833675, 0.2440008523702106, 0.2040030295875772, 0.16276140015128954, 0.12101410022679175, 0.07949999039598311, 0.03893680812818653, 3.532221979602567e-16], [-0.0, -0.036522239756475144, -0.07000899310594952, -0.10007045482837142, -0.1264344336775796, -0.14895482355555142, -0.1676165509272284, -0.1825368562602337, -0.19396286286845327, -0.20226548345754453, -0.207929810455146, -0.21154222842702688, -0.21377457318858392, -0.21536574042163703, -0.2171012147038653, -0.219791046108943, -0.2242468444917503, -0.2312583901196683, -0.24157047269312668, -0.25586056864137957, -0.274717948897642, -0.2986247765556166, -0.3279397066714902, -0.3628844401469835, -0.40353361158798, -0.4498083090539408, -0.501473433722266, -0.5581390119177722, -0.6192654730760301, -0.6841728074838332, -0.7520534195604368, -0.8219883984639655, -0.8929668402864198, -0.963907777240569, -1.0336842010348983, -1.1011486118104514, -1.165159482004232, -1.2246079973963522, -1.2784444261138628, -1.3257034708390982, -1.3655279798458404, -1.3971904283105099, -1.4201116317827511, -1.4338762175522637, -1.4382444553847864, -1.4331601348919587, -1.418754270567834, -1.3953445149894852, -1.363430263416217, -1.3236835365228166, -1.2769358297353282, -1.2241612151114714, -1.1664560725308133, -1.10501590890214, -1.041109795141203, -0.9760530090714824, -0.9111785167115907, -0.8478079535379108, -0.7872227805237021, -0.730636286718989, -0.679167090910488, -0.6338147599444237, -0.5954381114508068, -0.5647367051826944, -0.5422359515210152, -0.5282761797344658, -0.5230059144164899, -0.5263795084396419, -0.5381591772078986, -0.5579213744700482, -0.5850673470245172, -0.6188376067998296, -0.6583299664352246, -0.7025207008517688, -0.7502883244185085, -0.8004394129382386, -0.8517358532519065, -0.9029228718943533, -0.9527571786602813, -1.0000345615035477, -1.0436162858425946, -1.0824536836338068, -1.1156103646717066, -1.1422815432873077, -1.1618100464174592, -1.173698652087934, -1.177618498621373, -1.1734134020798863, -1.1611000201719586, -1.1408639026028244, -1.1130515681156836, -1.0781588447888817, -1.0368158001557835, -0.989768669195465, -0.9378592592155773, -0.8820023693909783, -0.823161807817494, -0.7623256193160873, -0.7004811521737249, -0.6385905912132069, -0.5775675681180067, -0.5182554282623687, -0.4614076872524628, -0.40767115116893793, -0.35757210363822506, -0.31150588216146624, -0.269730077649509, -0.2323614970949972, -0.19937693213723062, -0.1706176783962057, -0.14579765433683356, -0.12451487649204138, -0.10626596243527209, -0.09046325609332055, -0.07645410375430677, -0.06354175510983849, -0.051007323223096375, -0.03813221144095659, -0.02422040460619295, -0.008620026729669028, 0.009256412582898417, 0.029913625710688573, 0.053757502505187134, 0.08108184605521955, 0.11205824846066319, 0.14672938444269953, 0.18500591152806958, 0.22666707152597876, 0.27136499145287996, 0.31863258540138706, 0.36789486454819575, 0.41848337294746385, 0.46965338423856484, 0.5206034210134901, 0.5704965962148457, 0.6184832261710739, 0.6637241290067596, 0.7054140011307133, 0.7428042588696053, 0.7752247422609185, 0.8021037033358099, 0.8229855413138983, 0.83754580103012, 0.845603017303066, 0.8471270652032863, 0.8422437623826871, 0.8312355626480539, 0.8145382774936116, 0.7927338619222072, 0.7665394000981255, 0.7367925227064445, 0.7044335789306442, 0.6704849694144304, 0.6360281203416092, 0.602178640981354, 0.5700602561203256, 0.5407781394755043, 0.5153922935442219, 0.4948916248704401, 0.4801693512493258, 0.47200034921221207, 0.4710210068761742, 0.4777120899266649, 0.4923850584968602, 0.5151721916985259, 0.5460207865059763, 0.5846916007834534, 0.6307616088360701, 0.683631034429441, 0.74253452329116, 0.806556217197836, 0.8746483973133612, 0.9456532777951806, 1.0183274539555365, 1.0913684443418787, 1.1634427145865291, 1.2332145340436267, 1.2993749949963203, 1.3606705191123807, 1.4159301869904677, 1.464091253812147, 1.5042222566443135, 1.5355431757945024, 1.557442182428392, 1.5694885857182719, 1.5714416831311537, 1.563255314887241, 1.5450780257519139, 1.5172488416813015, 1.4802887728838303, 1.4348882560579046, 1.38189084446047, 1.3222735427262624, 1.2571242618553649, 1.187616936621326, 1.114984901215611, 1.0404931579560022, 0.9654101974248565, 0.8909800359265929, 0.8183951275161216, 0.7487707833007196, 0.6831216908981493, 0.6223410728587154, 0.5671829558922815, 0.5182479445617059, 0.47597280566287103, 0.44062407498483097, 0.412295798876908, 0.39091142150115504, 0.3762297273274687, 0.3678546498323648, 0.3652486639162357, 0.3677493935494924, 0.3745889896980713, 0.38491576852428344, 0.3978175477840863, 0.4123460814946145, 0.4275419702183501, 0.44245941721656584, 0.45619020938867055, 0.467886326067372, 0.47678061772782476, 0.4822050494701229, 0.48360606938338363, 0.48055673792337233, 0.4727653392952647, 0.46008028737253887, 0.442491234583211, 0.42012639003104113, 0.3932461504238115, 0.36223324170181165, 0.32757965822480606, 0.2898707677503502, 0.24976702217918423, 0.20798377435819423, 0.1652697486108499, 0.12238474592874424, 0.0800771830817929, 0.03906206784134905, 3.5294093290301597e-16], [-0.0, -0.03622555029930202, -0.06917065243044145, -0.09849799195903584, -0.12399529542981237, -0.14558199881779504, -0.16331222649471183, -0.17737399103812124, -0.18808462286352237, -0.19588253721317414, -0.20131554198785362, -0.20502598082153464, -0.20773308936107807, -0.2102130167936437, -0.21327702737026827, -0.2177484463956391, -0.22443895060684568, -0.23412482312029076, -0.2475237976390068, -0.26527310523015946, -0.28790930995120456, -0.3158504775628985, -0.34938116553568865, -0.3886406539031673, -0.4336147569313512, -0.4841314670218455, -0.5398605869450303, -0.6003174067749765, -0.6648703802545155, -0.7327526542939301, -0.8030772074274218, -0.8748552607724833, -0.9470175406792419, -1.0184378979484972, -1.0879587261223171, -1.1544175725008632, -1.2166743014727925, -1.2736381513589725, -1.3242940237685434, -1.3677273585606016, -1.403146977598832, -1.4299053258884318, -1.4475155983229075, -1.4556653127169759, -1.4542259733158116, -1.443258561528808, -1.4230146899894158, -1.3939333597716086, -1.356633366165997, -1.3119015032531198, -1.260676819040104, -1.2040312686599048, -1.143147200717809, -1.0792921891541163, -1.0137917880701028, -0.9480008382303303, -0.8832739901381083, -0.8209361287816412, -0.7622533888561848, -0.7084054363760424, -0.6604596634003347, -0.6193478978073553, -0.58584617074661, -0.5605580120126193, -0.543901659878606, -0.5361014789364915, -0.5371837794746492, -0.546977127320437, -0.5651171264261282, -0.5910555503788156, -0.6240735960467164, -0.6632989352371572, -0.7077261508967889, -0.7562400651957214, -0.807641399716898, -0.8606741545348625, -0.9140540544914209, -0.9664973883685972, -1.0167495604395917, -1.0636126841620421, -1.1059715742739178, -1.142817535573634, -1.173269403143499, -1.19659135828786, -1.2122071252640958, -1.2197102439711545, -1.2188702108874758, -1.2096343823092834, -1.1921256378141618, -1.1666359052989703, -1.1336157493679995, -1.0936603198089234, -1.0474920440633606, -0.9959405248467961, -0.9399201695208047, -0.8804061298875535, -0.818409168516467, -0.7549500896459672, -0.6910343786368572, -0.6276276837945864, -0.5656327484327625, -0.5058683600193669, -0.44905082820445535, -0.3957784358952476, -0.3465192290538423, -0.30160242354520167, -0.2612136133760193, -0.22539386641867545, -0.19404269369057617, -0.16692477897987876, -0.14368025957337227, -0.12383825846485105, -0.10683328597119165, -0.09202405622462201, -0.07871420335587567, -0.06617433484764614, -0.05366482669819954, -0.04045874750246405, -0.025864296757972985, -0.009246156664857548, 0.009954813954996755, 0.03220407099965593, 0.05785853155960961, 0.08715477582935867, 0.12020062492084535, 0.15697032693827107, 0.1973034895479179, 0.24090779951512764, 0.2873654707633066, 0.3361432649467035, 0.38660583479737975, 0.43803205298994735, 0.4896339101937544, 0.5405774973692009, 0.5900055309695973, 0.6370608369840475, 0.6809101818098038, 0.7207678255140799, 0.7559181764861219, 0.7857369457430632, 0.8097102337931661, 0.8274510321461856, 0.8387126840951395, 0.8433989237424665, 0.8415701965728619, 0.8334460570981892, 0.8194035369280218, 0.7999714776188267, 0.7758209243071308, 0.7477517758973872, 0.7166759829545697, 0.6835976730497949, 0.6495906628927502, 0.6157738851449056, 0.583285313599362, 0.5532550120070421, 0.5267779581444054, 0.5048873050511105, 0.48852873540798564, 0.47853654286983144, 0.4756120363093661, 0.48030481025200844, 0.49299735853909826, 0.5138934300397608, 0.5430104369279871, 0.5801761297931167, 0.6250296520002958, 0.6770269807460614, 0.7354506567278597, 0.7994236008476016, 0.8679267174349856, 0.939819891534631, 1.0138659051117307, 1.088756725629985, 1.1631415621031296, 1.2356560398608127, 1.304951816989237, 1.3697259534145243, 1.4287493482012552, 1.4808935817426359, 1.5251555366206666, 1.5606792231207627, 1.586774301431833, 1.6029308708469334, 1.6088301848989042, 1.6043510481639787, 1.5895717530892688, 1.5647675211496588, 1.530403519338199, 1.4871236278466813, 1.4357352352515866, 1.3771904311460375, 1.3125640506816623, 1.243029098860845, 1.169830142880642, 1.0942553069242749, 1.0176075344280802, 0.9411757973054914, 0.8662069295669544, 0.7938787443240992, 0.7252750587979061, 0.661363202545295, 0.6029745209255324, 0.5507883104330242, 0.5053195368097327, 0.4669105929520397, 0.4357272538750102, 0.41175888286168094, 0.39482283895536263, 0.3845729337129663, 0.3805116871423398, 0.3820060414017516, 0.3883061083797775, 0.3985664557089106, 0.4118693768313863, 0.4272495458491529, 0.44371942811754955, 0.46029480357252395, 0.47601976190773937, 0.48999054683352394, 0.5013776602493181, 0.5094456853549055, 0.513570349261918, 0.5132524189635257, 0.5081281077044745, 0.4979757597499179, 0.48271867797363116, 0.46242405813592175, 0.43729809368852907, 0.4076774129098488, 0.37401710367431895, 0.3368756678463912, 0.2968973249881737, 0.2547921518350441, 0.21131459815714884, 0.16724095983711526, 0.12334641525807988, 0.08038224079099511, 0.03905381506809361, 3.5146057292891096e-16], [-0.0, -0.03581210792269225, -0.06812011128042693, -0.09664446484037308, -0.12123719335064144, -0.14188661777474354, -0.15871825504718864, -0.17199185727860097, -0.1820946572240894, -0.18953098613248734, -0.19490852529439787, -0.1989215412832898, -0.2023315347781389, -0.20594580192927223, -0.21059446371250226, -0.21710656115640847, -0.2262858416213648, -0.23888687273360212, -0.2555921158080635, -0.2769905697112659, -0.3035585596058004, -0.3356431937605084, -0.373448946855356, -0.417027751548888, -0.4662728934015905, -0.5209169097077787, -0.5805335927302429, -0.6445440947473113, -0.7122270287836074, -0.7827323574931965, -0.855098765938661, -0.9282741243933663, -1.0011385670458102, -1.0725296436362122, -1.141268945358682, -1.2061895652470296, -1.2661637277991724, -1.320129913468675, -1.3671188111432941, -1.4062774557089868, -1.4368909477251104, -1.4584012071775243, -1.4704222819232242, -1.4727518121435725, -1.4653783429327305, -1.4484842758599605, -1.4224443545563288, -1.3878196865453398, -1.3453474110433539, -1.295926227666416, -1.2405981013151952, -1.1805265515044885, -1.116972017770729, -1.051264864475946, -0.9847766465598258, -0.9188903011311385, -0.8549699571576885, -0.7943310662232201, -0.7382115510902099, -0.6877446457751548, -0.643934061554414, -0.6076320587195825, -0.5795209353124826, -0.5600983631546294, -0.5496669102103338, -0.5483279889053608, -0.5559803648830065, -0.5723232523742223, -0.5968639135228438, -0.6289295722874292, -0.6676833515309323, -0.7121438470846314, -0.7612078672318576, -0.8136757922639024, -0.8682789482945634, -0.9237083438310821, -0.9786440877749211, -1.031784794261474, -1.0818762833326696, -1.1277389067452288, -1.1682928647145483, -1.2025809311475888, -1.229788070621665, -1.2492575083737334, -1.2605029029298618, -1.2632163675302968, -1.2572721887972977, -1.2427261966197702, -1.2198108453847452, -1.1889261708551524, -1.150626886615317, -1.10560597663711, -1.0546752238963921, -0.9987431870610022, -0.9387911963319647, -0.8758479841300003, -0.8109635954224962, -0.7451832354121475, -0.679521708791421, -0.6149390849498497, -0.5523181879530177, -0.4924444597321966, -0.4359886810392703, -0.38349295897350283, -0.3353603042085834, -0.2918480276181653, -0.2530650871828431, -0.21897341435886228, -0.18939314706387228, -0.1640115966565076, -0.14239568126257787, -0.12400746991611858, -0.10822240344057353, -0.09434969075860741, -0.0816543250663697, -0.06938012438916218, -0.056773176438222675, -0.04310505901415341, -0.027695214651711448, -0.00993188156753695, 0.010708978349456649, 0.03464726076745981, 0.062185249657854824, 0.09349746060012645, 0.1286240731061707, 0.1674681347139653, 0.20979662113843603, 0.2552453360515828, 0.3033275336502553, 0.35344604960751225, 0.404908633771527, 0.45694609342097114, 0.508732781163073, 0.5594088985800761, 0.6081040371077499, 0.6539613426484415, 0.6961616709962228, 0.7339470978089682, 0.766643159724046, 0.7936792319962476, 0.8146064920541044, 0.8291129765557371, 0.8370353104524068, 0.8383667684897904, 0.8332614204670978, 0.8220342091779697, 0.8051569118467575, 0.7832500395097408, 0.7570708315838289, 0.7274976022417018, 0.6955107886780105, 0.6621711365532486, 0.6285955326885285, 0.5959310575573151, 0.5653278786837156, 0.5379116394566152, 0.5147560152247678, 0.4968561093653613, 0.4851033462420205, 0.48026248592313175, 0.48295133795688977, 0.49362368952025165, 0.5125558883581891, 0.5398374349127698, 0.5753658429920009, 0.618845926556318, 0.6697935641865127, 0.7275438851298075, 0.7912637141354234, 0.8599680092017745, 0.9325399293944996, 1.0077540814416976, 1.0843024160469006, 1.160822179700237, 1.2359252768239202, 1.3082283616241852, 1.3763829599230184, 1.4391049189944398, 1.4952024981045395, 1.5436024437089257, 1.583373440348032, 1.6137463900624394, 1.6341310481309659, 1.6441286292928678, 1.6435400942537706, 1.632369928866509, 1.6108253354272584, 1.5793108644298348, 1.5384186232281258, 1.4889143027402882, 1.4317193620462352, 1.3678898010871576, 1.2985920314845931, 1.2250764228294884, 1.1486491550286604, 1.0706430451650435, 0.9923880389347943, 0.9151820615747079, 0.840262911205652, 0.7687818490228736, 0.7017794964988195, 0.6401645908505094, 0.5846960779428904, 0.5359689383534271, 0.49440404958985523, 0.4602422877354556, 0.4335429675647789, 0.414186614003801, 0.40188195232115126, 0.39617690222758095, 0.39647326463887805, 0.40204470158404393, 0.4120575317696617, 0.42559379853698154, 0.4416760149577044, 0.4592929538496459, 0.47742582942044653, 0.4950742125356072, 0.5112810333180483, 0.5251560525727424, 0.535897226645424, 0.5428094476418565, 0.5453202109750639, 0.542991843179529, 0.5355300127710692, 0.5227883433597056, 0.5047690487997868, 0.4816196123481209, 0.4536256330215764, 0.42120006005431226, 0.3848691280972973, 0.34525538927827915, 0.30305831135917605, 0.25903297216279003, 0.2139674276734072, 0.16865936357384095, 0.12389265666758413, 0.08041447324696042, 0.03891351600926232, 3.488114063755102e-16], [-0.0, -0.03528828746502177, -0.0668732489152217, -0.0945379610234385, -0.11820260002822153, -0.13792710179591086, -0.1539098896249807, -0.16648269390120057, -0.17610158995124242, -0.183334479572974, -0.1888453352236685, -0.1933756113436289, -0.19772330260292967, -0.20272019205824285, -0.20920788167311416, -0.21801323211033644, -0.22992385724708236, -0.24566432098897417, -0.26587366957698305, -0.29108490201428283, -0.32170693521921156, -0.35800956015471325, -0.4001118119751115, -0.44797409297381235, -0.5013942938969457, -0.560008059322966, -0.623293238782873, -0.6905784597053244, -0.7610556537554799, -0.8337962673151037, -0.9077707922566283, -0.9818711671791108, -1.0549355240728977, -1.125774692873241, -1.1931998281499883, -1.2560504895084035, -1.3132224910093895, -1.3636948355149785, -1.4065550673688623, -1.4410224108547054, -1.4664681116500722, -1.482432462832286, -1.4886380743534535, -1.4849990334190768, -1.47162570073276, -1.448824991736571, -1.4170961002424691, -1.3771217315689483, -1.3297550207825422, -1.2760024162354147, -1.217002906719237, -1.1540040598078296, -1.0883354171375188, -1.0213798575446205, -0.9545435895307736, -0.8892254692027495, -0.8267863577654452, -0.7685192333771028, -0.7156207556665928, -0.6691649478497516, -0.6300796119632525, -0.5991260284525106, -0.5768824137611274, -0.5637315205558904, -0.5598526669461792, -0.565218375908885, -0.5795956966673016, -0.6025521686571599, -0.6334662786472963, -0.671542155241548, -0.715828144954982, -0.7652388227579116, -0.8185799096262075, -0.8745755021665728, -0.9318969664243127, -0.9891928107938723, -1.0451188324172576, -1.098367828039903, -1.1476981740454515, -1.1919606109360537, -1.230122614077429, -1.2612897939105454, -1.2847238435037034, -1.2998566374164608, -1.30630018122754, -1.3038522133769863, -1.2924973676557607, -1.272403913109165, -1.243916195631098, -1.2075430094702164, -1.1639422246963467, -1.1139020859925715, -1.058319676767825, -0.998177108618657, -0.934516048015316, -0.8684112285104588, -0.8009436169177291, -0.7331739053375536, -0.6661169875907136, -0.6007180489445484, -0.5378308527771279, -0.4781987482013147, -0.42243885020022004, -0.37102976036146673, -0.32430310396408285, -0.2824390603103543, -0.24546596030526513, -0.21326392096441635, -0.18557238340448443, -0.16200132153088745, -0.142045795578563, -0.12510344021542086, -0.11049440319616947, -0.09748318939686346, -0.08530181798950039, -0.07317366869744642, -0.06033737728772082, -0.04607014108246954, -0.0297098122733338, -0.010675189750738653, 0.011516031833516866, 0.03723213519570574, 0.06671548103745223, 0.10007415692918503, 0.13727740247968534, 0.1781549401668529, 0.22240023917684462, 0.26957763677668917, 0.3191331407395363, 0.37040863971732696, 0.4226591586699224, 0.47507271579885674, 0.5267922679564965, 0.5769391749866286, 0.6246375713547959, 0.6690390068400183, 0.7093467076885395, 0.7448388157733884, 0.7748899858444133, 0.7989907593636468, 0.8167641867727389, 0.8279792370284913, 0.8325606122205231, 0.8305946740997115, 0.822331286189475, 0.8081814774165937, 0.7887109383350673, 0.7646294664000316, 0.7367765797409056, 0.7061036168999631, 0.6736527305789226, 0.640533264285794, 0.6078960698489523, 0.5769063793042117, 0.5487158852364122, 0.5244347082098333, 0.5051039377882416, 0.49166942457399926, 0.4849574748545401, 0.4856530574174479, 0.49428107486829187, 0.5111911807221531, 0.5365465403492727, 0.5703168405494369, 0.612275751374148, 0.6620029372740004, 0.7188906053220718, 0.7821544688267099, 0.8508488977807133, 0.9238859259212576, 1.0000576901949867, 1.0780617944497015, 1.1565290172783995, 1.234052725901051, 1.309219315222818, 1.3806389648207158, 1.446975997248923, 1.5069781289646118, 1.5595039301871987, 1.6035478515198975, 1.638262232185972, 1.6629757758838413, 1.67720806382111, 1.6806797684181225, 1.6733183331942998, 1.6552589919839489, 1.626841111254557, 1.5885999502292159, 1.5412540420487912, 1.4856885027116093, 1.4229346704867356, 1.3541465645853696, 1.2805747260114773, 1.2035380639102928, 1.1243943759424375, 1.044510240157661, 0.9652309878504528, 0.8878514616914505, 0.8135882412078136, 0.7435539790138712, 0.6787344370557242, 0.6199687438926712, 0.5679333134025764, 0.5231297742764526, 0.4858771605209373, 0.45630850837281994, 0.43437189713891233, 0.41983586316916655, 0.41229901011787473, 0.4112035374521194, 0.4158523153078375, 0.4254290495644657, 0.43902100845818365, 0.4556437229364007, 0.4742670286906368, 0.4938417894379459, 0.5133266292021373, 0.5317140063123458, 0.5480549834073962, 0.5614820853162915, 0.5712296892875846, 0.576651458300451, 0.5772344064075704, 0.5726092732395064, 0.562556980701957, 0.5470110460932321, 0.526055929803088, 0.499921399806391, 0.4689730967177018, 0.43369957967512274, 0.3946962223535395, 0.3526464077397675, 0.3083005379530288, 0.26245342967724855, 0.215920705338842, 0.1695148140382113, 0.12402132384387533, 0.0801761182139874, 0.03864410426381809, 3.4503718535077355e-16], [-0.0, -0.03466181775572277, -0.06544847006919446, -0.09221001661225013, -0.11493805359628022, -0.13376620106067938, -0.14896658554771247, -0.1609424025112148, -0.17021674547538668, -0.17741798696294508, -0.1832620870570596, -0.18853228683540652, -0.194056713740633, -0.2006844824417059, -0.20926091644107098, -0.2206025415098526, -0.235472511302026, -0.25455711793862895, -0.2784440161172787, -0.30760274896238904, -0.34236810836474846, -0.38292679332408175, -0.4293077485112591, -0.48137647391994176, -0.5388334973483166, -0.6012170970073843, -0.6679102543980971, -0.7381517104141241, -0.8110508930950906, -0.8856063862015721, -0.9607275163067229, -1.035258554710786, -1.1080049612483451, -1.1777610417406952, -1.2433383508716525, -1.303594148680695, -1.3574592123142453, -1.4039643153744032, -1.4422647149475418, -1.4716620305529018, -1.4916229587859102, -1.5017943409217522, -1.5020141864230887, -1.4923183510881182, -1.4729426721539935, -1.4443204715116174, -1.407075449632362, -1.3620101041273924, -1.3100899153264558, -1.2524236442114365, -1.190240182937964, -1.1248624826879985, -1.057679155630615, -0.9901144055450969, -0.9235969837442699, -0.8595288922759149, -0.799254564333799, -0.7440312421614511, -0.6950012456964373, -0.6531667814217442, -0.6193678814163378, -0.5942639888654019, -0.5783196200892146, -0.5717944365700335, -0.5747379558456249, -0.586989020039414, -0.6081800278881593, -0.6377458231542097, -0.6749370220172766, -0.7188374571096875, -0.7683853188363654, -0.8223974878576437, -0.8795964782081739, -0.9386393502724955, -0.9981479081828268, -1.0567394682089586, -1.1130574740256969, -1.1658012415969523, -1.2137541406028682, -1.2558095602288917, -1.290994063694305, -1.318487206701747, -1.3376375782688534, -1.3479747160859352, -1.3492166503045178, -1.341272936981238, -1.3242431526289353, -1.2984109317440884, -1.2642337370707788, -1.2223286550776422, -1.1734546041511944, -1.1184914280274298, -1.0584164199273913, -0.9942788819688864, -0.9271733682797252, -0.8582122878034381, -0.7884985534383372, -0.7190989576785507, -0.6510189315507792, -0.5851793040020773, -0.5223956240348591, -0.4633605392246864, -0.40862964355463766, -0.358611116814204, -0.31355937944222667, -0.27357288313188227, -0.23859605137469167, -0.20842527807380362, -0.18271878907048528, -0.16101007349424684, -0.14272450172035095, -0.12719866665269958, -0.11370191704372362, -0.10145949730870843, -0.08967666913513442, -0.0775631670922222, -0.06435733397124356, -0.04934929187389056, -0.031902531832916296, -0.0114733473005074, 0.01237240591739513, 0.03994567023058685, 0.07142403238137791, 0.10684532889412816, 0.14610518635126818, 0.1889585691592796, 0.2350253027091881, 0.2837994358077306, 0.33466220559925086, 0.3868982734725745, 0.4397148140620286, 0.49226296360924054, 0.54366107059081, 0.5930191422624622, 0.6394638468954257, 0.6821634138729604, 0.720351772953313, 0.7533512899488848, 0.7805934884567005, 0.8016371953254146, 0.8161836100876797, 0.8240878740863945, 0.8253668016142367, 0.8202025309214961, 0.8089419550526226, 0.7920918986031495, 0.7703101139955857, 0.7443922770653719, 0.7152552639626601, 0.6839170870431168, 0.6514739541284819, 0.6190749910710527, 0.5878952300339293, 0.559107513700188, 0.5338539975097708, 0.5132179471461205, 0.49819652642314943, 0.4896752514501909, 0.4884047508979054, 0.4949804201879413, 0.5098254907167304, 0.5331779553983357, 0.5650817008000529, 0.6053820961547354, 0.6537261829989186, 0.709567498705218, 0.7721754554530806, 0.8406490859504975, 0.9139348611862322, 0.9908481862635377, 1.070098090385201, 1.1503145485453343, 1.2300778073760585, 1.3079490375115337, 1.3825016010137998, 1.4523522057048908, 1.5161912190974411, 1.5728114330122362, 1.6211346054861677, 1.6602351583587651, 1.6893604757314251, 1.7079473287040945, 1.7156340434639548, 1.7122681307033825, 1.6979092020275448, 1.6728271108568173, 1.6374953686160951, 1.5925799989772642, 1.5389241008613148, 1.477528492191489, 1.4095288985618364, 1.336170231814268, 1.2587785710500357, 1.178731511213295, 1.0974275808178315, 1.016255449783714, 0.936563650267988, 0.8596315178012874, 0.786642027397884, 0.7186571504274016, 0.6565962941551056, 0.6012183085751055, 0.5531074564039177, 0.5126636440762936, 0.48009710672073364, 0.45542763098181216, 0.4384882888934827, 0.42893354651683413, 0.4262515054283582, 0.42977993597010633, 0.43872567087542286, 0.45218684866274345, 0.46917742996565415, 0.4886533583340732, 0.509539701227984, 0.5307580877654483, 0.551253757698855, 0.5700215510712996, 0.5861301996175243, 0.5987443283775092, 0.6071436379507962, 0.6107388127406467, 0.6090837865050358, 0.6018840913597048, 0.5890011176641465, 0.5704522174049721, 0.5464066901204333, 0.5171777954069513, 0.48321103697535833, 0.4450690575505746, 0.40341356927183347, 0.35898481851856057, 0.31257914540824133, 0.2650252450632506, 0.21715976896550465, 0.16980291954690396, 0.12373468924870942, 0.07967237669488306, 0.0382499778531406, 3.401949067237582e-16], [-0.0, -0.03394172186256633, -0.06386654822261802, -0.0896953294948997, -0.11149371325181413, -0.12947037115007567, -0.1439711842118235, -0.15546953254736925, -0.1645529377452317, -0.17190640205523047, -0.1782928757120194, -0.18453136006636678, -0.19147321765934913, -0.19997730936187177, -0.21088461194286817, -0.22499298605329046, -0.2430327641656732, -0.2656438104653787, -0.2933546704540892, -0.3265643779231608, -0.3655274222083792, -0.4103423008423934, -0.46094399380076917, -0.5171005976988744, -0.578414253974069, -0.6443263968825541, -0.7141272377569465, -0.7869692941484566, -0.8618846689227692, -0.9378056876969885, -1.0135884156362511, -1.0880384987861251, -1.159938712731745, -1.2280775540474533, -1.2912781789607528, -1.3484269797296038, -1.398501092826316, -1.4405941541051899, -1.4739396542410148, -1.497931301975047, -1.512139871806129, -1.5163260950586284, -1.5104492467577606, -1.494671183177329, -1.4693556938005425, -1.4350631440930746, -1.3925404991721664, -1.3427069303794978, -1.2866353141800733, -1.2255300330724281, -1.1607015788365946, -1.0935385372276922, -1.0254775981955595, -0.9579722852614793, -0.8924611305756711, -0.8303360375849869, -0.7729115707583359, -0.7213958914853492, -0.6768640215566417, -0.6402340614530304, -0.6122469213213008, -0.5934500396733515, -0.584185470521807, -0.5845826161489563, -0.5945557725123635, -0.6138065400987969, -0.6418310376248474, -0.6779317421537389, -0.7212336697195587, -0.770704508081293, -0.8251782202548255, -0.8833815562433406, -0.9439628428669967, -1.005522369406173, -1.0666436511662167, -1.1259248348850002, -1.1820095095495442, -1.2336162036377447, -1.279565884593515, -1.3188068275895537, -1.350436287041726, -1.3737184842508707, -1.3880985159721726, -1.3932118893792886, -1.3888894963072458, -1.375157951170882, -1.3522353298141447, -1.3205224579728396, -1.2805900052930204, -1.2331617413118239, -1.1790944010231936, -1.1193546873978277, -1.0549940045736752, -0.9871215667853918, -0.9168765632382483, -0.8454000772392404, -0.7738074585844225, -0.7031618315099251, -0.6344493869188608, -0.5685570579912484, -0.5062531139594502, -0.44817112944112236, -0.3947976982417033, -0.3464641632170621, -0.3033425300887421, -0.2654456256479167, -0.2326314522772105, -0.20461158389045186, -0.18096334592098462, -0.16114542644685562, -0.14451647931590317, -0.13035620537772383, -0.11788833650396308, -0.10630490050737545, -0.09479111450243928, -0.08255024043130667, -0.06882773973191468, -0.052934084343782196, -0.034265617898266466, -0.012322913077442488, 0.013273862586409385, 0.04277298145181878, 0.07628291082946204, 0.11376801075536788, 0.1550482937658308, 0.19980325976621374, 0.2475797124879792, 0.2978033597368931, 0.3497939002998958, 0.40278320852447275, 0.4559361455516343, 0.5083734560650652, 0.5591961530098073, 0.6075107514857372, 0.6524546880056605, 0.6932212531897292, 0.7290833749873332, 0.759415615484588, 0.7837137866536263, 0.8016116480015771, 0.8128942205689121, 0.8175073353442809, 0.8155631278341123, 0.807341291922537, 0.7932860127545275, 0.773998607511464, 0.7502260118933034, 0.7228453561439148, 0.6928449748915317, 0.6613022873940337, 0.6293590666450145, 0.5981946851325365, 0.5689979800767246, 0.542938420285461, 0.5211372793275764, 0.504639524912196, 0.49438712199315243, 0.4911944174362495, 0.49572622777124636, 0.5084791896905744, 0.5297668570307582, 0.5597089398091901, 0.5982249826235402, 0.6450326737430006, 0.6996508651139252, 0.7614072699832164, 0.8294506916915197, 0.9027675271809203, 0.9802021846026704, 1.0604809586630992, 1.1422388223722475, 1.224048521759637, 1.3044513026814568, 1.3819885574928847, 1.4552336551331195, 1.5228232116867386, 1.5834870699244232, 1.636076285432771, 1.6795884630260138, 1.7131898490856265, 1.7362336618010512, 1.7482742301374832, 1.7490766115788914, 1.738621465876, 1.7171050745646896, 1.6849345111737923, 1.642718082012757, 1.5912512694243863, 1.5314985156849443, 1.4645712837533853, 1.3917029184375784, 1.314220906144741, 1.2335171914171572, 1.1510172524823465, 1.0681486650223975, 0.9863098926626261, 0.9068400341022647, 0.8309902306043846, 0.7598973944069589, 0.6945608596041651, 0.6358224836575587, 0.5843506417616163, 0.5406284599438391, 0.5049465284150614, 0.477400226881835, 0.45789168100055255, 0.44613625666432677, 0.441673389133792, 0.44388143984229095, 0.4519961775727325, 0.46513239496189585, 0.48230809802001223, 0.5024706473275902, 0.5245241861994068, 0.5473576644081605, 0.5698727566419821, 0.5910109829054885, 0.6097793633037645, 0.6252739813862904, 0.6367008873778592, 0.6433938437093811, 0.6448284984622479, 0.6406326655368801, 0.6305924911852845, 0.6146543924594333, 0.5929227614505675, 0.5656535372024147, 0.5332438521604945, 0.49621805933701346, 0.4552105375400816, 0.41094575275883954, 0.3642161220995971, 0.3158582808343738, 0.266728391811604, 0.21767715873931553, 0.16952521014785682, 0.12303950906325713, 0.07891141489450801, 0.03773697950054535, 3.3435443864747144e-16], [-0.0, -0.033138241708229016, -0.06215043952422576, -0.08703143218853569, -0.10792286670708157, -0.12510909782063215, -0.1390090456867139, -0.15016422051227904, -0.1592232234968019, -0.16692312625655636, -0.1740682135383943, -0.18150664438684994, -0.19010564320093537, -0.2007258728586272, -0.21419566623934266, -0.2312857993954633, -0.2526854791037232, -0.2789801897948506, -0.3106320005770558, -0.3479628733144385, -0.3911414389641437, -0.4401736234389834, -0.4948974082771459, -0.5549819077550727, -0.619930835357932, -0.6890903214408495, -0.7616609332543554, -0.8367136410459421, -0.9132093723887074, -0.99002170378921, -1.065962156345318, -1.139807492852802, -1.21032835907077, -1.2763185732640916, -1.3366243466612848, -1.390172713691798, -1.435998464951447, -1.4732689075003345, -1.5013058255988985, -1.5196040791904653, -1.5278463558074675, -1.5259136822237525, -1.5138914029001993, -1.4920704406245195, -1.460943768084602, -1.4211981346659146, -1.3737012076952344, -1.3194843988432732, -1.2597217517056831, -1.195705363110451, -1.128817896067461, -1.060502814370663, -0.9922330258961903, -0.9254786621894949, -0.8616747449827973, -0.8021894952408233, -0.7482940270507938, -0.7011341374525856, -0.6617048548863665, -0.6308283444805355, -0.6091356894676585, -0.59705297651156, -0.5947920108743102, -0.6023458776210568, -0.6194894501202832, -0.6457848297413693, -0.6805915837335244, -0.7230815346321894, -0.7722577469415179, -0.826977257896266, -0.885977011211771, -0.9479023780128667, -1.0113375893937604, -1.0748373617341045, -1.1369589700123908, -1.196294016516885, -1.25149915271583, -1.3013250403235135, -1.3446428830602062, -1.380467922103548, -1.4079793642265979, -1.4265363002198204, -1.4356892702001334, -1.4351872393679836, -1.4249798600394232, -1.4052150105859207, -1.3762317164337248, -1.338548669694292, -1.2928486695865196, -1.2399594029895507, -1.1808310708639755, -1.1165114398035978, -1.0481189568566998, -0.9768146085790637, -0.9037732310453918, -0.8301549856715867, -0.757077706046397, -0.6855907938380287, -0.6166512979641681, -0.5511027517411803, -0.4896572691954463, -0.4328813160077513, -0.38118547485194865, -0.33481842160718794, -0.2938652206786177, -0.25824993718315487, -0.22774245382325872, -0.2019692736427523, -0.18042798920661093, -0.16250500658903852, -0.14749603119163274, -0.13462875387222514, -0.1230871218464669, -0.11203654066290276, -0.1006493321824638, -0.08812976942629597, -0.07373802246729433, -0.05681237986909669, -0.03678915673219637, -0.013219761993022189, 0.014215527336728049, 0.04569745071947308, 0.08126157723594729, 0.12079621430601649, 0.16404447185364682, 0.21061043309882266, 0.2599692756633918, 0.3114810831010607, 0.36440798993658957, 0.4179342152941172, 0.47118846345265875, 0.5232681061488653, 0.5732645127827476, 0.6202888621284979, 0.663497753562596, 0.7021179376225691, 0.7354695048921442, 0.7629869083256484, 0.784237246303324, 0.7989353006720381, 0.8069549041215731, 0.808336302491862, 0.8032892777342262, 0.7921919037665028, 0.775584917708772, 0.7541618002062975, 0.7287547679511635, 0.7003169863562785, 0.6699014079743512, 0.6386367302241015, 0.607701042055861, 0.5782937914194589, 0.5516067521906234, 0.5287946993491885, 0.5109465138769614, 0.4990574336798447, 0.4940031439054119, 0.4965163598317687, 0.5071664989836739, 0.5263429676315035, 0.5542425020655184, 0.5908609090614615, 0.6359894450948573, 0.6892159626757226, 0.7499308373791295, 0.8173375735510578, 0.8904678731091266, 0.968200843124464, 1.0492859166413118, 1.1323689699610744, 1.2160210406417595, 1.2987689856991198, 1.3791273705515803, 1.4556308473517963, 1.526866267299313, 1.5915037757016817, 1.6483261608683102, 1.6962557678604886, 1.734378344728919, 1.7619632607829405, 1.7784796219155092, 1.7836079049825782, 1.777246839351508, 1.7595153764121023, 1.7307497043470847, 1.691495382953697, 1.6424947889383497, 1.5846701730618071, 1.5191027340989702, 1.4470082082818145, 1.369709554447577, 1.2886073825462439, 1.2051488248493296, 1.120795583910518, 1.0369919082392451, 0.9551332453804886, 0.8765363027125646, 0.8024112092892501, 0.7338364184038542, 0.6717369215890023, 0.6168662622096474, 0.5697927427109918, 0.5308901162818341, 0.5003329437425007, 0.4780966825797819, 0.4639624600352508, 0.45752636883632597, 0.45821301532184516, 0.4652929480200295, 0.4779035026683398, 0.49507251946051994, 0.5157443219063821, 0.5388072956888693, 0.5631223715099121, 0.5875516989266163, 0.6109867989538454, 0.6323755016680149, 0.6507470106705965, 0.6652344881136824, 0.6750946207074594, 0.6797237070073842, 0.6786698972792433, 0.6716413170525914, 0.6585099115717379, 0.639310958060774, 0.6142383032733175, 0.5836354924201134, 0.5479830595343461, 0.5078823460420898, 0.4640363013373009, 0.41722779434686624, 0.36829602654185817, 0.31811168308373244, 0.2675514886506556, 0.21747284724452093, 0.16868924063920648, 0.12194703823847869, 0.07790433254512706, 0.037112360197905724, 3.275979950864031e-16], [-0.0, -0.0322627477314268, -0.06032506913835416, -0.08425832754395354, -0.10428139460873881, -0.12075417702138577, -0.1341671393566604, -0.14512709478602315, -0.1543396334273189, -0.16258864685545377, -0.17071348440480635, -0.1795843404064281, -0.19007651978980733, -0.2030442612929715, -0.21929481203222875, -0.23956344398474744, -0.2644900820791942, -0.2945981755617215, -0.33027639002892656, -0.37176362832787213, -0.4191378061244819, -0.47230871437865457, -0.531015198564062, -0.5948267757855498, -0.6631496986924079, -0.7352373620716264, -0.8102048370662012, -0.8870472118886592, -0.9646613193624708, -1.041870343115012, -1.1174507180115487, -1.1901606784057062, -1.2587697615835676, -1.3220885446012627, -1.3789978813444452, -1.4284769134161939, -1.4696291532815526, -1.501705980407841, -1.5241269499507406, -1.5364963874466326, -1.538615830204248, -1.5304919745324888, -1.5123398952035918, -1.4845814170160352, -1.4478386352158317, -1.4029226989938344, -1.3508180874171238, -1.2926627171426872, -1.2297243233917519, -1.1633736474124994, -1.0950550427577068, -1.026255177190699, -0.9584705553014734, -0.8931746177564064, -0.8317851857355499, -0.775633013194872, -0.7259321852437709, -0.6837530587206684, -0.6499983819891199, -0.6253831564850575, -0.6104187144231327, -0.6054013874513573, -0.610406032346146, -0.6252845647044559, -0.649669532814453, -0.6829826443584235, -0.7244480412271591, -0.7731100053560914, -0.8278546738590856, -0.8874352473741655, -0.9505000937324652, -1.0156230817935246, -1.0813354291760178, -1.14615831387499, -1.2086354841897213, -1.2673651043393561, -1.321030094510735, -1.3684262633076696, -1.4084875866583437, -1.4403080587815313, -1.463159626027933, -1.4765058111838711, -1.480010741752777, -1.4735434081973862, -1.4571770943577989, -1.431184039395914, -1.3960255057769246, -1.3523375381599412, -1.3009128009329933, -1.2426789749841762, -1.1786742748946994, -1.1100207141233456, -1.037895796333512, -0.9635033445965585, -0.8880441960153871, -0.8126874870192511, -0.7385432343038784, -0.6666368786953834, -0.597886405099257, -0.5330825825597385, -0.472872786074136, -0.41774876828054025, -0.36803864683885124, -0.32390326484089654, -0.2853369696509646, -0.25217274301002307, -0.2240915048613901, -0.20063530793928544, -0.18122404234148137, -0.16517518152539734, -0.15172602561002238, -0.14005783641035494, -0.1293212127964629, -0.11866202588125492, -0.10724722190291479, -0.09428980674366882, -0.07907234963441932, -0.060968384112236, -0.03946114067733235, -0.014159116391973698, 0.015191929932248932, 0.04870087442481452, 0.08632723220727993, 0.12788137680042286, 0.1730289726209835, 0.2212995080643619, 0.2720987092567236, 0.32472451270013714, 0.378386181317575, 0.43222606521675594, 0.4853434379554015, 0.5368197830103966, 0.5857448649724467, 0.6312428967497996, 0.6724981083877862, 0.7087790351728164, 0.7394608722212309, 0.7640452890469493, 0.782177159526582, 0.7936577387115976, 0.7984539061926892, 0.7967031940097291, 0.7887144229745047, 0.7749638820904936, 0.7560870987430488, 0.7328663596633949, 0.7062142515201232, 0.6771535926227445, 0.6467942210427873, 0.6163071870932333, 0.5868969674538307, 0.5597723725122422, 0.5361168563041274, 0.5170589587809418, 0.5036436124462248, 0.496805029560169, 0.4973418524494989, 0.5058951987491831, 0.5229301668427343, 0.5487212859526048, 0.5833423022116996, 0.626660588879936, 0.6783363581680749, 0.7378267365977795, 0.8043946482898454, 0.8771223339143599, 0.9549292201240073, 1.036593747903456, 1.12077867102782, 1.2060592501338778, 1.2909536958914385, 1.3739551582083311, 1.453564518722762, 1.5283232220311915, 1.596845377729328, 1.6578483805195243, 1.7101813290146761, 1.7528505746557548, 1.7850417991389937, 1.8061381003036725, 1.8157336605885603, 1.8136426766411167, 1.799903340921827, 1.774776783458981, 1.7387410014249645, 1.6924799230183392, 1.6368678673587016, 1.57294977093428, 1.501917650943619, 1.425083864223178, 1.3438517952146773, 1.2596846657958125, 1.174073202351368, 1.0885029201865442, 1.0044217917070342, 0.9232090525891452, 0.8461458697703452, 0.7743885472842854, 0.7089448819485552, 0.650654202289401, 0.6001715328112521, 0.5579562240549077, 0.5242652793522448, 0.4991514944820642, 0.4824664093879551, 0.47386795461365705, 0.47283256200437745, 0.4786714022836194, 0.49055031395653864, 0.5075129010020758, 0.5285062031054536, 0.5524082835251383, 0.5780570374830764, 0.6042794992016483, 0.6299209189392373, 0.6538728927046882, 0.6750998564155444, 0.6926633023225528, 0.7057431373492487, 0.7136556789973252, 0.7158678727032481, 0.7120074127554389, 0.7018685546073157, 0.6854135169796454, 0.6627694847515024, 0.6342213354623987, 0.6002003204835398, 0.5612690338537079, 0.5181030948670678, 0.47147005242502066, 0.4222060878839565, 0.37119114694216027, 0.3193231686854497, 0.2674921003350558, 0.216554389027724, 0.1673086270658955, 0.12047299490834708, 0.07666509756661942, 0.03638472628063099, 3.2001946256190825e-16], [-0.0, -0.03132763444244964, -0.05841709211584577, -0.0814180910022448, -0.10062719748529418, -0.11647895777996314, -0.1295331024073525, -0.14045815800878017, -0.15001189536408574, -0.15901912616267547, -0.16834743173772787, -0.17888146280631562, -0.1914964888251196, -0.2070318978453357, -0.22626535213799004, -0.24988829121832054, -0.2784834425346967, -0.3125049517593167, -0.352261680507768, -0.39790414100393806, -0.4494154466363727, -0.5066065567737366, -0.5691159861273346, -0.6364140360673347, -0.7078114904414646, -0.7824726044909717, -0.8594321052719949, -0.9376158183468837, -1.015864441027237, -1.0929598995236292, -1.1676536580980692, -1.2386962945001767, -1.3048676189920847, -1.3650065951093313, -1.4180403195036846, -1.4630113358519297, -1.4991025935174622, -1.525659414594993, -1.5422079018993435, -1.5484693037246955, -1.5443699467896488, -1.5300464543755603, -1.5058460796882047, -1.4723221021640056, -1.430224353919543, -1.3804850618742037, -1.3242003053512936, -1.2626074963675298, -1.1970593877038318, -1.1289951997910481, -1.0599095293113925, -0.9913197584223681, -0.9247327222530748, -0.861611412825185, -0.8033424992793734, -0.7512054271713078, -0.7063438240289653, -0.669739885178307, -0.6421923443225263, -0.6242985491777384, -0.6164410656620888, -0.6187791270525103, -0.6312451297635155, -0.6535462577534291, -0.685171195933651, -0.725401772302655, -0.7733292517811792, -0.827874894724716, -0.8878142925046016, -0.951804903818085, -1.0184161406584686, -1.0861612939512404, -1.1535305471559736, -1.2190243026380703, -1.2811860408735936, -1.3386339466487354, -1.3900905689749858, -1.4344098316321177, -1.470600777811688, -1.4978475136032743, -1.5155249090233498, -1.5232097196049807, -1.5206869036658233, -1.5079510274868484, -1.4852027698807426, -1.4528406560761191, -1.411448265586226, -1.3617772669606694, -1.304726731394216, -1.24131926467814, -1.172674570807827, -1.0999811189293378, -1.0244666268277658, -0.9473680978620265, -0.8699021536083983, -0.7932363914189188, -0.7184624650178701, -0.6465715379839622, -0.5784326957568583, -0.5147748233168119, -0.45617236492008484, -0.40303528153595247, -0.3556034134727475, -0.31394534282960224, -0.27796173570730937, -0.24739303043728125, -0.22183122829099408, -0.20073543996081236, -0.18345074713268855, -0.16922985604302557, -0.1572569510739403, -0.14667310289700375, -0.1366025487427861, -0.12617914295079993, -0.11457227449924014, -0.10101156473177451, -0.08480969254311692, -0.06538274496934496, -0.04226755714819136, -0.015135585279005291, 0.01619705251054673, 0.051763631917414975, 0.0914451320632958, 0.13497284486422567, 0.18193521760662432, 0.23178875135769106, 0.2838726715194332, 0.3374269877093269, 0.3916134707383389, 0.4455389970367451, 0.49828064742754785, 0.5489118992930142, 0.5965292201577835, 0.6402783573350955, 0.6793796229206578, 0.7131514959886305, 0.7410319038118022, 0.7625966003210192, 0.7775741314506832, 0.7858569617210789, 0.7875084322817932, 0.7827653252966728, 0.7720359203784919, 0.7558935430096472, 0.7350657196520651, 0.7104191666742327, 0.682940947477379, 0.6537162315812104, 0.6239031784175867, 0.5947055449180382, 0.5673436777174558, 0.543024596341274, 0.5229119019060082, 0.5080962558819785, 0.4995671650307691, 0.4981867818846474, 0.504666385682048, 0.519546147554132, 0.5431787074298098, 0.5757170004278943, 0.6171066696077445, 0.6670832923078964, 0.7251745315913815, 0.7907072053674726, 0.862819146488965, 0.9404756104617267, 1.022489876220745, 1.1075475824649406, 1.1942342498459648, 1.2810653601566862, 1.366518299528792, 1.449065425125475, 1.5272074850979385, 1.5995066104218907, 1.6646181049444895, 1.721320286394827, 1.7685416756231283, 1.8053848928730103, 1.8311466969769234, 1.8453336941348428, 1.847673345191764, 1.8381200115896708, 1.8168558977322946, 1.784286868509228, 1.741033242238136, 1.6879157783461933, 1.6259371928309927, 1.55625964015513, 1.4801786951750064, 1.399094450683059, 1.3144804131726022, 1.227850929901466, 1.1407279130287575, 1.0546076407572758, 0.9709284107174418, 0.8910397974243756, 0.8161742241337158, 0.7474215008630103, 0.6857069061995936, 0.6317733026299953, 0.5861676756801716, 0.549232378611993, 0.5211012494600273, 0.5017006486473152, 0.4907553462060084, 0.4877990706755278, 0.4921894199230752, 0.5031267301618584, 0.5196764058650242, 0.5407941323593191, 0.5653533265855961, 0.592174131420911, 0.6200532262526651, 0.647793711928431, 0.6742343320746932, 0.6982773149244512, 0.7189141596045596, 0.7352487472593472, 0.7465172289663623, 0.7521042272990555, 0.751554984448015, 0.7445831945915442, 0.7310743690610758, 0.7110846969834342, 0.6848354786308728, 0.6527033207970561, 0.6152063903356154, 0.5729871208779559, 0.5267918562219994, 0.47744798975254205, 0.4258392206348757, 0.37287959290108313, 0.31948701181151284, 0.26655694234209837, 0.21493698708925624, 0.1654030155193899, 0.11863747398809728, 0.07521044741445802, 0.035563970420317476, 3.1172358503268607e-16], [-0.0, -0.030346202889008602, -0.056454631192609545, -0.07855444350393512, -0.09701959125313572, -0.11235755606639118, -0.12519427640087938, -0.13625565937236989, -0.14634616372765485, -0.15632501759037795, -0.16708069794255254, -0.1795043461717383, -0.1944628241928497, -0.2127721278529809, -0.23517186820836172, -0.26230150694608406, -0.2946789902890368, -0.332682367193807, -0.3765349039700439, -0.42629412044072473, -0.48184507458848364, -0.5428981157399717, -0.6089912133978941, -0.6794968526649536, -0.7536333707280543, -0.8304804950108359, -0.9089987352246227, -0.988052181387903, -1.0664341704786422, -1.1428952080055637, -1.2161724693869176, -1.2850201611928445, -1.3482399952147723, -1.4047110197088297, -1.4534180622978585, -1.4934780677209964, -1.5241636602417832, -1.5449233239701188, -1.5553976731051682, -1.5554313762677074, -1.5450804024275087, -1.5246143679286706, -1.4945138820385206, -1.455462909406782, -1.4083362888532096, -1.3541826660285208, -1.2942032098055962, -1.2297265859840583, -1.1621807544667901, -1.0930622351964792, -1.0239035518566815, -0.9562396090531138, -0.8915737872209611, -0.831344549121783, -0.7768933422313447, -0.7294345527801285, -0.6900282203595066, -0.6595561579668842, -0.6387020426722632, -0.6279359486719261, -0.6275036896142329, -0.6374212232821326, -0.657474251760368, -0.687223027017482, -0.7260122483882439, -0.7729858177519998, -0.8271061031996395, -0.8871772554599929, -0.9518720259001465, -1.0197614528364594, -1.0893467161780033, -1.1590924106783065, -1.227460456484762, -1.2929438529913424, -1.3540994885002473, -1.4095792436905568, -1.4581586707221241, -1.4987625908654134, -1.5304870303175582, -1.5526170044321232, -1.5646397627101531, -1.566253218048031, -1.5573694011706578, -1.5381129020045832, -1.5088143809942345, -1.4699993520606536, -1.4223725521396342, -1.3667983172494578, -1.304277479270243, -1.2359213787821544, -1.1629236554503801, -1.0865305269792922, -1.0080102994186058, -0.9286228648661106, -0.8495899371091616, -0.7720667516818669, -0.6971159148473407, -0.6256840272485239, -0.5585816339258922, -0.4964669649708054, -0.43983383249410263, -0.38900394233740004, -0.34412376574769227, -0.305165999924423, -0.2719355298542899, -0.24407969009346397, -0.22110251698584665, -0.2023825819209515, -0.18719390712481407, -0.17472938935670632, -0.16412609563873715, -0.1544917502840043, -0.14493170510776082, -0.13457567546064614, -0.12260353381249857, -0.1082694797777527, -0.09092394999288712, -0.07003269198096898, -0.0451925015093223, -0.016143211037638567, 0.017224384579896754, 0.05486487244147145, 0.09657893150373936, 0.1420183893446243, 0.1906954933477798, 0.24199615350933124, 0.295196809874899, 0.3494844822426368, 0.403979475643619, 0.45776014437938983, 0.5098890618672155, 0.5594399046438757, 0.6055243376187712, 0.6473181846135669, 0.6840861834875706, 0.715204658374233, 0.74018149194055, 0.7586728468914354, 0.7704961665368889, 0.7756390771210815, 0.7742639174677033, 0.766707731759057, 0.7534776761808069, 0.7352419068519579, 0.7128161319916324, 0.6871461227455902, 0.6592865816956519, 0.6303768631605283, 0.601614122554253, 0.574224541178772, 0.5494333261159897, 0.5284342209673921, 0.51235928110814, 0.502249666367942, 0.4990281845780344, 0.5034742816512362, 0.5162021186654453, 0.5376423051090343, 0.5680277717310417, 0.6073841683920308, 0.6555250643151344, 0.7120521128241912, 0.776360222846897, 0.8476476580919006, 0.9249308648606674, 1.0070637138793208, 1.0927607331820468, 1.1806238106220914, 1.269171758466869, 1.3568720608877605, 1.4421740697679775, 1.5235428765122174, 1.5994930684054582, 1.6686215780371911, 1.7296388534133087, 1.7813976141848897, 1.8229185150347897, 1.8534121093462521, 1.8722965930951512, 1.8792109083584598, 1.8740228955059899, 1.856832300378026, 1.827968564700394, 1.7879834516866913, 1.7376386812178997, 1.6778888671961494, 1.6098601607701055, 1.5348251044265175, 1.454174290980022, 1.369385496115509, 1.2819910115441309, 1.1935439466221092, 1.1055842884814044, 1.0196055138195719, 0.9370225294470741, 0.8591416839192005, 0.7871335399687686, 0.7220090283245322, 0.6645995195716171, 0.615541254067549, 0.5752644629633201, 0.5439873987350018, 0.5217153741343526, 0.5082447870567007, 0.5031719884831768, 0.5059067343318574, 0.5156898525932487, 0.5316146571993646, 0.552651552111188, 0.5776751952345649, 0.6054935337647637, 0.6348779817941133, 0.664593988444339, 0.6934312409018731, 0.7202327615727783, 0.743922191701573, 0.763528604330004, 0.7782082560920861, 0.7872627683382174, 0.7901533213872545, 0.7865105489533398, 0.7761399303730614, 0.7590225933804535, 0.7353115569472374, 0.7053235591927429, 0.6695267266800444, 0.6285244457689084, 0.5830358914894447, 0.5338737522733636, 0.4819197577763219, 0.42809867024214376, 0.3733514360911625, 0.31860821278208656, 0.26476198607094986, 0.2126434746034193, 0.1629979828186424, 0.116464810350627, 0.0735597578466227, 0.03466118712901737, 3.0282501447570647e-16], [-0.0, -0.029332531204024855, -0.054466994199385416, -0.07571229951555315, -0.09351867771574, -0.1084640481379693, -0.12123673251579499, -0.13261496937817088, -0.14344376963854838, -0.15460972452883764, -0.16701443220557693, -0.181547247535784, -0.1990580797676194, -0.22033096446715614, -0.24605911918395187, -0.2768221571893109, -0.31306608116504714, -0.35508661019753646, -0.403016310547688, -0.45681590548139295, -0.5162700343286704, -0.5809876185178243, -0.6504068754165616, -0.7238049023357277, -0.8003116359888737, -0.8789278799983696, -0.9585469875393925, -1.0379796905859553, -1.1159814838962085, -1.1912819029741153, -1.2626149825419695, -1.3287501469248213, -1.3885227671197684, -1.4408636216787116, -1.4848265198791304, -1.519613385528645, -1.5445961572190856, -1.5593349345491505, -1.5635918880004487, -1.557340550646292, -1.54077022025261, -1.514285317902372, -1.478499671161969, -1.4342258130205339, -1.3824595093428327, -1.3243598443908122, -1.2612253032060343, -1.194466388604087, -1.1255753967607143, -1.056094046724098, -0.9875797138884047, -0.9215710541359872, -0.8595538230669265, -0.8029276930164034, -0.7529748494207753, -0.7108311080168586, -0.6774602362952477, -0.6536320879694306, -0.6399050697670496, -0.6366133577616706, -0.6438591682167033, -0.6615102682319487, -0.6892027872747781, -0.7263492649610538, -0.7721517462816513, -0.8256196158673925, -0.8855917507544306, -0.9507624691768519, -1.0197106636455553, -1.09093143213389, -1.1628694633780068, -1.233953392502152, -1.302630322343032, -1.3673997044536141, -1.426845791820576, -1.4796679123579195, -1.524707867306217, -1.560973830393779, -1.5876602102185007, -1.6041630376396852, -1.6100905495713662, -1.6052687577378888, -1.5897419128023658, -1.563767897813442, -1.5278087071032398, -1.4825162846169082, -1.4287141062815152, -1.3673749917332767, -1.2995957190711358, -1.226569090156359, -1.1495541515590093, -1.0698453161967214, -0.9887411520914259, -0.9075136070204868, -0.8273784211664551, -0.7494674446533385, -0.6748035240341034, -0.6042785527366875, -0.5386351969571633, -0.47845271263681666, -0.4241371634060436, -0.3759162363933392, -0.3338387354290709, -0.29777871237042913, -0.26744408001522735, -0.24238943729276852, -0.22203273193644188, -0.20567529028413734, -0.1925246605945716, -0.18171964737360013, -0.17235686137446735, -0.16351807446404137, -0.15429765129024628, -0.14382933104244117, -0.13131165249664145, -0.11603135344552305, -0.0973841305411866, -0.07489221611167665, -0.048218312843719115, -0.01717552320168399, 0.018266984368052467, 0.057982718692111065, 0.10169104943468263, 0.14896474566918372, 0.1992416701929576, 0.2518403214445722, 0.3059788138581712, 0.3607967968846148, 0.4153797350323202, 0.4687849081194838, 0.5200684441023458, 0.5683126675592723, 0.6126530359351872, 0.6523039432924449, 0.6865826974113841, 0.7149310200110278, 0.736933480542619, 0.7523323499482653, 0.7610384500905215, 0.7631376750239134, 0.7588929693902321, 0.7487416642484884, 0.7332881887168572, 0.7132922939455478, 0.6896530411857057, 0.6633889151669862, 0.6356145248799887, 0.6075144436232242, 0.5803148165328721, 0.5552534248126219, 0.5335489399443032, 0.5163701271298867, 0.5048057643826351, 0.4998360318059194, 0.5023060949027854, 0.5129025569452281, 0.5321333896490226, 0.5603118702207074, 0.597544958226246, 0.6437264399715124, 0.6985350537594897, 0.7614376892915896, 0.8316976315533672, 0.908387696786278, 0.9904079886166811, 1.0765078890374273, 1.165311794516425, 1.2553480146246176, 1.3450801715384255, 1.4329403755464476, 1.5173634058593035, 1.596821098742509, 1.6698561369670877, 1.7351144460332808, 1.7913754333211052, 1.8375793555392217, 1.8728511664058718, 1.8965202788021924, 1.908135771701786, 1.907476679674661, 1.8945571190818267, 1.8696261273942858, 1.8331622174148956, 1.7858627735066297, 1.7286285391895402, 1.6625435616896034, 1.5888510663825528, 1.50892582996867, 1.424243703316945, 1.3363490012429757, 1.2468205254374878, 1.1572370171693922, 1.0691428475332327, 0.9840147446522033, 0.9032303296186976, 0.8280391867620658, 0.7595371302383219, 0.6986442495254417, 0.6460872231529526, 0.6023862852044768, 0.5678471153957572, 0.542557803652172, 0.5263909170395179, 0.5190105736628855, 0.519884307762669, 0.5282993956497082, 0.543383206129881, 0.5641270442511275, 0.5894128758606435, 0.6180422545469014, 0.6487667236346721, 0.6803189351518477, 0.7114437157929928, 0.74092831709614, 0.7676311130829866, 0.7905080527778766, 0.8086362361591221, 0.8212340586296056, 0.8276774590655767, 0.8275119076260681, 0.820459879221545, 0.806423674081199, 0.7854835653168607, 0.7578913717841806, 0.7240596699221601, 0.6845469677259635, 0.6400392648433898, 0.5913285124727305, 0.5392885630522131, 0.48484926078157514, 0.42896936830256066, 0.3726090513084831, 0.31670265082396687, 0.26213246222974057, 0.2097042111076849, 0.16012486941258625, 0.11398339254426867, 0.07173488021301865, 0.03368857354818448, 2.9344723630643395e-16], [-0.0, -0.028301334550551067, -0.05248437401758845, -0.07293729495534029, -0.09018469682544375, -0.1048716521704371, -0.11774429624527125, -0.1296274696971803, -0.14140000590633242, -0.15396831753325174, -0.16823898305224227, -0.18509106239077217, -0.20534888050050093, -0.2297560084824204, -0.25895114397824004, -0.29344654659548275, -0.33360962128213517, -0.3796481643621236, -0.43159969532759634, -0.4893251947401299, -0.5525074572858911, -0.6206541519441957, -0.6931055612994526, -0.7690468522646913, -0.8475246139037795, -0.9274672875787314, -1.0077090131004467, -1.0870163245014908, -1.164117052771984, -1.2377307323592421, -1.3065997649950836, -1.369520569620287, -1.4253739415053306, -1.4731538573274499, -1.5119939956829251, -1.5411912935427219, -1.5602259272949972, -1.5687771906279957, -1.5667348385725293, -1.5542055751875532, -1.5315144789983028, -1.4992012825318524, -1.45801154714297, -1.4088828987158575, -1.352926610702456, -1.291404935333102, -1.2257046888836185, -1.1573076900014883, -1.0877587289693138, -1.0186318084497352, -0.9514954411409363, -0.8878778157400876, -0.829232648989717, -0.776906528177152, -0.7321085155616003, -0.6958827345891211, -0.6690845886533547, -0.6523611782308861, -0.6461363835148682, -0.6506009695785, -0.6657079522911615, -0.6911733385689544, -0.7264822270968486, -0.7709001285094721, -0.8234892402531162, -0.883129293981212, -0.9485424852110494, -1.0183218987156113, -1.0909627610746973, -1.1648957859482583, -1.2385218295499758, -1.3102470446409478, -1.3785177118189689, -1.4418539371536279, -1.4988814350311799, -1.5483606636671141, -1.58921264690017, -1.6205408979521045, -1.641648956786765, -1.652053160157355, -1.6514903797395089, -1.639920586045231, -1.6175242210911047, -1.5846944879781615, -1.5420247875631252, -1.4902916482777837, -1.4304336020587336, -1.3635265546845767, -1.2907562802731545, -1.2133887353069754, -1.1327389357651654, -1.0501391706134668, -0.9669073353695783, -0.8843161605258655, -0.8035640815628161, -0.7257484508852463, -0.651841728473656, -0.5826712090023106, -0.5189027506523587, -0.4610288671916252, -0.40936143272415554, -0.364029130659143, -0.3249796578735835, -0.2919865747704085, -0.2646605749742812, -0.24246483768274327, -0.22473402396075268, -0.21069638806186716, -0.1994983984160014, -0.19023120212985736, -0.1819582231944796, -0.17374315914526176, -0.16467763427513285, -0.1539077797907009, -0.14065904217702016, -0.12425856968604755, -0.10415459202730702, -0.07993228834322809, -0.0513257313505618, -0.01822559875708997, 0.01931754590765931, 0.06109448490010893, 0.10674305411971943, 0.1557581739495427, 0.20750593667451764, 0.2612413777423944, 0.3161294613151608, 0.37126872571728775, 0.4257169636831404, 0.4785182575464537, 0.5287306521064569, 0.5754537288182353, 0.6178553446992702, 0.6551968179559599, 0.6868558793745719, 0.712346763087806, 0.7313368810759544, 0.7436596109370346, 0.7493228239444775, 0.7485128877725715, 0.7415939928256665, 0.7291027699881972, 0.7117382878368755, 0.6903476359019146, 0.6659074144452548, 0.6395015575655572, 0.6122960125497283, 0.5855108818266042, 0.5603907025087334, 0.5381735905671926, 0.5200600108145702, 0.5071819491598751, 0.5005732596001183, 0.5011419351597763, 0.5096450099931692, 0.5266667401048531, 0.5526006340416978, 0.5876358142981565, 0.6317480872481059, 0.684695986677357, 0.7460219361934418, 0.815058551867266, 0.8909399814564208, 0.972618053547032, 1.0588828919616726, 1.1483875407285986, 1.239676045516257, 1.3312143511714667, 1.4214233040074227, 1.5087129935427561, 1.5915176328532143, 1.6683301604707943, 1.7377357502854611, 1.7984434391224315, 1.8493151240489485, 1.889391242005177, 1.9179125216031263, 1.934337289033994, 1.938353914741196, 1.9298881023161452, 1.909104843170645, 1.8764049869678252, 1.832416505480099, 1.7779806533836011, 1.7141333504343832, 1.642082222563601, 1.5631798419299874, 1.4788937953914396, 1.3907742850378582, 1.300420021572946, 1.2094432100703354, 1.119434447036955, 1.0319283473475438, 0.9483706995051832, 0.8700879083552943, 0.7982594268262465, 0.733893803925875, 0.6778088869370651, 0.630616613738076, 0.5927127189455714, 0.5642715579069016, 0.5452461283988802, 0.5353732442739466, 0.5341836913120439, 0.5410170762225469, 0.5550409680091322, 0.5752738294826845, 0.600611148044542, 0.6298541011059574, 0.6617400344278468, 0.6949739926106332, 0.7282605208405352, 0.7603349562399571, 0.7899934457277149, 0.8161209646443112, 0.8377166655475087, 0.853915958103486, 0.8640088070557103, 0.8674538336560085, 0.8638879141973989, 0.8531310846633336, 0.8351866800984578, 0.8102367581093435, 0.7786329748924998, 0.7408831963860275, 0.6976342337008504, 0.6496511882541605, 0.5977939756110808, 0.5429916658715601, 0.48621533082283797, 0.4284501227327405, 0.37066732575199857, 0.31379711805808874, 0.2587027612179064, 0.2061568933538542, 0.1568205456075326, 0.11122542857802108, 0.06975994873334408, 0.03265931646693115, 2.837213802581525e-16], [-0.0, -0.02726781590876383, -0.05053753423617953, -0.0702753000650592, -0.08707736773830309, -0.1016519071859527, -0.11479758244334101, -0.1273794707054076, -0.140302960869397, -0.1544863248112484, -0.1708326912263436, -0.19020216979440482, -0.213384872221838, -0.24107555637472364, -0.2738505807256698, -0.31214779965144857, -0.3562499571357003, -0.40627204896371294, -0.46215302372271233, -0.5236520833322408, -0.5903497271665435, -0.6616535630182242, -0.7368087862229263, -0.8149131082852892, -0.8949358013408749, -0.9757404176626187, -1.0561106468879933, -1.1347786901595553, -1.210455462071332, -1.281861879956488, -1.3477604669790237, -1.406986481592088, -1.4584777916103662, -1.5013027363399447, -1.5346852643561688, -1.5580266965864977, -1.570923542861491, -1.5731808931519862, -1.5648210100581894, -1.546086864190996, -1.5174404760751392, -1.479556054118249, -1.4333080449365503, -1.379754336787022, -1.3201149759574324, -1.255746866766348, -1.1881150255803998, -1.118761045488583, -1.0492694988344624, -0.9812330579304336, -0.9162171486233257, -0.8557249660667586, -0.8011636766842375, -0.7538126049708995, -0.7147941590648587, -0.6850481859808631, -0.6653103675497685, -0.6560951733710081, -0.6576837797521711, -0.6701172462806265, -0.6931951171939826, -0.7264794861126433, -0.7693044330945499, -0.8207906155204105, -0.8798646721161566, -0.9452829854384007, -1.0156592451571702, -1.0894951649677302, -1.1652136321178195, -1.2411935121330029, -1.3158052937164217, -1.3874467408859608, -1.4545777216030904, -1.5157534043631924, -1.5696550558855498, -1.6151177331150197, -1.6511542397296035, -1.676974809328107, -1.6920020821751443, -1.6958810572217609, -1.6884838232704227, -1.6699089996082679, -1.6404759440879266, -1.6007139123619187, -1.5513464726991983, -1.4932715935845804, -1.427537923378832, -1.3553178702239415, -1.277878163969135, -1.196548638406066, -1.112690010199316, -1.027661449702195, -0.9427887379583111, -0.8593337836954977, -0.7784662345945866, -0.7012378596065324, -0.6285603050856199, -0.5611867388994602, -0.499697795721181, -0.44449212596125737, -0.39578173304925, -0.3535921619906486, -0.31776747935713867, -0.287979864193319, -0.26374351375448035, -0.24443246040987363, -0.22930179912994136, -0.21751174112839025, -0.20815384052345082, -0.20027868900679507, -0.19292433972849427, -0.18514470673125197, -0.176037190630583, -0.1647688046897143, -0.15060011734965648, -0.13290638655367865, -0.11119533632363167, -0.08512111507835268, -0.05449407585863735, -0.019286128374405374, 0.020368471173798003, 0.06417690717321287, 0.1116960635722052, 0.16234503279683676, 0.2154215414138682, 0.2701218566253051, 0.32556364609923377, 0.38081118552997717, 0.43490224566979696, 0.48687594498809883, 0.5358008267673393, 0.5808024110536226, 0.6210894826838881, 0.6559784063670673, 0.6849148077826234, 0.7074920246962356, 0.723465812568058, 0.73276488304286, 0.7354969587212998, 0.7319501410933709, 0.7225895076270104, 0.7080489757592665, 0.6891185928746298, 0.6667275292203491, 0.6419231621275836, 0.6158467420614178, 0.5897062213192453, 0.5647469023338391, 0.5422206225610808, 0.5233542352875673, 0.509318169261834, 0.5011958541822493, 0.4999547835948224, 0.5064199519831554, 0.5212503495687013, 0.544919127841998, 0.5776979628050735, 0.6196460434016504, 0.6706040020634104, 0.7301929854048227, 0.7978189387657627, 0.8726820515809521, 0.9537911845641461, 1.0399829775377754, 1.1299452214307932, 1.22224397236222, 1.315353792444242, 1.4076904232963887, 1.4976451362258598, 1.583619959155712, 1.6640629557873383, 1.7375027278076847, 1.8025813263483415, 1.8580847940340939, 1.902970612997863, 1.9363914058990868, 1.9577143245403952, 1.9665356620199181, 1.9626903370303201, 1.9462560201885086, 1.9175517992075304, 1.8771314092202562, 1.8257711834848966, 1.7644530049108282, 1.6943426572953966, 1.6167640839799633, 1.5331701581741806, 1.4451106511202112, 1.3541981495909319, 1.262072721363081, 1.1703661551489255, 1.0806666093523334, 0.994484491771372, 0.9132203603265979, 0.8381355838638717, 0.7703264333390248, 0.7107021889485388, 0.6599677501241225, 0.6186111251977757, 0.586896058682351, 0.5648599294268499, 0.5523169254594799, 0.5488663742514008, 0.5539059835319035, 0.5666496306815368, 0.5861492309778809, 0.6113201191871008, 0.6409692975006961, 0.6738258375707256, 0.7085726769528818, 0.7438790217362306, 0.7784325581621926, 0.8109706867692216, 0.8403100227106186, 0.8653734545691344, 0.885214119962164, 0.8990357377986499, 0.9062088321323637, 0.906282488744081, 0.8989914001944496, 0.8842580752337023, 0.8621902111155215, 0.8330733494661536, 0.7973590548522198, 0.7556489671142544, 0.7086751811003704, 0.6572774980975284, 0.6023781697714924, 0.5449548159034728, 0.48601224016994143, 0.42655389261164606, 0.36755373270541036, 0.30992923299580816, 0.25451623045394467, 0.20204628197090907, 0.15312711297836273, 0.10822666584964573, 0.06766115957758871, 0.03158746667631069, 2.7378492871161564e-16], [-0.0, -0.026247509264387518, -0.04865748385071863, -0.06777192248540986, -0.08425522587682369, -0.09887385839432791, -0.11247305158520453, -0.12595116906440518, -0.14023241462564148, -0.15623861030911537, -0.1748607974653616, -0.196931420887586, -0.22319784364275075, -0.2542979086008979, -0.2907382126125971, -0.3328756920501303, -0.3809030356771029, -0.434838344604145, -0.4945193518268914, -0.5596023982097469, -0.6295662406728195, -0.7037206448000014, -0.7812195912201723, -0.8610788060165269, -0.9421972130982764, -1.0233818037680074, -1.1033753282455978, -1.1808861379741393, -1.2546194480850927, -1.3233092479816728, -1.3857500657075157, -1.4408277892240198, -1.4875487650555739, -1.5250664316139955, -1.552704800032019, -1.5699781682051408, -1.576606542211724, -1.572526341212156, -1.5578960748395108, -1.5330968032292551, -1.4987273162271721, -1.455594096859312, -1.4046962616820842, -1.3472057940097173, -1.284443502191415, -1.2178512412048574, -1.1489610292122798, -1.0793617690650683, -1.0106643460835636, -0.9444659162367816, -0.8823142220118706, -0.8256727761861163, -0.7758877362827854, -0.7341572550930955, -0.7015040361581146, -0.6787517488737405, -0.6665058676929838, -0.6651393959294936, -0.6747838194310819, -0.6953255116862289, -0.7264076827536985, -0.7674378329042936, -0.817600541231542, -0.8758752929012625, -0.9410589292465992, -1.011792195478985, -1.0865897640345556, -1.1638730298570668, -1.242004909210192, -1.3193258274760145, -1.3941900549371646, -1.4650015433814034, -1.53024843063408, -1.5885354144412869, -1.6386132506286013, -1.6794047018118043, -1.7100263503660476, -1.729805790704878, -1.7382938286794523, -1.7352714373022828, -1.7207513450439686, -1.6949742625252222, -1.6583998823540944, -1.6116929119844003, -1.5557045177406312, -1.4914496666862775, -1.4200809491713438, -1.3428595463561899, -1.2611240718153696, -1.1762580629348567, -1.0896569251397952, -1.0026951394176857, -0.9166945310172294, -0.8328943649851838, -0.7524239832169963, -0.6762786292702196, -0.6052990230798476, -0.5401551500655107, -0.4813346204061219, -0.42913583722256105, -0.38366608999847873, -0.34484456485569503, -0.31241013940748547, -0.2859337099361595, -0.26483468557282813, -0.24840118081035606, -0.23581334661987124, -0.2261692039193059, -0.21851228304373357, -0.21186033066135906, -0.20523432228477664, -0.19768701468736066, -0.1883302882033326, -0.1763605636311289, -0.16108163135877118, -0.14192430001714507, -0.1184623566522144, -0.09042442792425455, -0.05770143970441218, -0.020349487900819117, 0.02141194652697308, 0.06720638366628658, 0.11651115690026587, 0.16867236061178595, 0.22292353438064025, 0.2784075866638811, 0.3342013756109222, 0.38934229421009314, 0.4428561531905871, 0.4937856193924512, 0.5412184505928426, 0.5843147704866508, 0.6223326496224819, 0.6546512990612, 0.6807912423485124, 0.7004309066200306, 0.7134191634165704, 0.7197834518412658, 0.7197332284877561, 0.7136586073112711, 0.7021241753234265, 0.6858580935839909, 0.665736714327843, 0.6427650611419604, 0.6180536269607934, 0.5927920415441604, 0.5682202435734721, 0.545597860413681, 0.5261725491876256, 0.5111480847728304, 0.501652992796344, 0.49871051829296353, 0.5032106935224729, 0.5158852221206983, 0.5372858323731696, 0.5677666714862961, 0.6074712172405782, 0.6563240756607434, 0.7140279159553776, 0.7800656698345649, 0.8537079944529516, 0.9340258697905659, 1.0199080754385235, 1.1100831716083104, 1.2031454977029072, 1.2975846017402681, 1.3918174277916853, 1.4842225185376834, 1.573175437810147, 1.65708458490143, 1.7344265593325292, 1.8037802420444837, 1.8638587864723044, 1.9135387600449751, 1.9518857422116245, 1.9781757675532285, 1.991912099913957, 1.992836933423153, 1.9809377361140332, 1.956448078670776, 1.9198429215710977, 1.8718284653588928, 1.8133267977843586, 1.7454556949503783, 1.6695040484034858, 1.5869034935161093, 1.499196904013749, 1.4080044909368803, 1.3149882999175264, 1.2218159370572366, 1.1301243700499184, 1.04148464712381, 0.9573683520075128, 0.8791165690777227, 0.8079120702250377, 0.7447553553368532, 0.6904450836166848, 0.6455633255762132, 0.6104659480986402, 0.5852783203699837, 0.5698963997712413, 0.5639931271765622, 0.567029933686311, 0.5782730387540306, 0.5968141059199923, 0.6215947197079017, 0.6514340581628042, 0.6850590621551352, 0.7211363467029727, 0.7583050624916166, 0.7952098983487546, 0.8305334180288465, 0.8630269471402964, 0.8915392677892054, 0.9150424384145357, 0.9326541328030791, 0.9436559834425565, 0.9475075178810887, 0.943855389993561, 0.9325377281563879, 0.9135835462836657, 0.8872072883719476, 0.8537986995185456, 0.8139083332657573, 0.7682291136691107, 0.7175744679942868, 0.6628536299985927, 0.6050447822740782, 0.5451667574381313, 0.4842500508057818, 0.42330791078258123, 0.363308267278633, 0.3051472331548619, 0.24962486974923556, 0.197423846039162, 0.1490915435619027, 0.10502606782160874, 0.06546652389350308, 0.030487801917074352, 2.6378033571231434e-16], [-0.0, -0.025256116855657682, -0.04687514449587627, -0.06547200594579561, -0.08177496332030029, -0.09660325806889701, -0.11084209796222369, -0.1254156573741354, -0.14125881061244894, -0.1592883528383683, -0.18037447858879868, -0.2053132836625741, -0.23480103223297594, -0.2694108880814796, -0.30957274786874345, -0.35555673688022194, -0.4074608356342449, -0.4652030014176851, -0.5285180348281351, -0.5969593206082386, -0.6699054474895766, -0.7465715865523331, -0.8260253849066617, -0.9072070144090579, -0.9889529066043424, -1.0700226078848805, -1.149128105459202, -1.2249649072586264, -1.2962441091252443, -1.361724651822732, -1.420244959427114, -1.4707531598297299, -1.5123351172597106, -1.5442395552504207, -1.565899615192982, -1.5769502789445569, -1.5772411818777432, -1.5668444528916334, -1.5460573375678672, -1.5153994869172696, -1.4756049239254314, -1.4276088301765093, -1.3725294220069353, -1.311645306772647, -1.2463688219063083, -1.1782159597123993, -1.1087735668029983, -1.0396645765677808, -0.9725120843527673, -0.9089031067933615, -0.8503528781854214, -0.7982705275602341, -0.7539269504378201, -0.7184256397552636, -0.6926771723748945, -0.677377962502922, -0.6729937933414336, -0.6797485257732034, -0.6976182605655751, -0.7263311014448961, -0.7653725335734405, -0.8139962986852435, -0.8712405176467839, -0.9359486866767797, -1.0067950579147795, -1.0823138112791628, -1.160931335121059, -1.241000860230007, -1.3208386370445526, -1.3987608107828167, -1.4731201344723068, -1.5423416658613005, -1.6049566207654813, -1.6596336018682487, -1.7052064871898693, -1.740698344750182, -1.7653408373349582, -1.778588691333524, -1.780128923632893, -1.7698846475800059, -1.7480134099385747, -1.714900142361049, -1.6711449399479292, -1.6175460028233555, -1.555078191310776, -1.484867748458824, -1.408163832846979, -1.3263075776452036, -1.2406994470653463, -1.1527656973245088, -1.0639247652174337, -0.9755544030388477, -0.8889603540835721, -0.8053473189567398, -0.725792900604432, -0.6512251369338539, -0.5824041361505535, -0.5199082238769656, -0.4641248954117344, -0.41524674405598194, -0.37327241034570835, -0.33801247044712635, -0.30910005805815205, -0.286005896005304, -0.26805730427123015, -0.25446065315145733, -0.24432664604598422, -0.2366977481176569, -0.23057702636806093, -0.22495763482256062, -0.21885216623490625, -0.21132109928217527, -0.20149959738796633, -0.18862196135924533, -0.17204310174998708, -0.15125647663007846, -0.12590803419651125, -0.09580580502145698, -0.06092490300438841, -0.02140781437650157, 0.022440022660622835, 0.07015922202259924, 0.12114979215829379, 0.17468845797682003, 0.2299494992658322, 0.2860285502438989, 0.3419687267648398, 0.3967883857703573, 0.44950977745217147, 0.4991878253717538, 0.5449382641545139, 0.5859643784926377, 0.6215816207265611, 0.6512394364097479, 0.674539696706369, 0.6912512215012049, 0.7013199755955473, 0.7048746298607855, 0.702227296981104, 0.6938693744847695, 0.6804625530482425, 0.6628251724057443, 0.6419142274742415, 0.6188034404706756, 0.594657917987801, 0.5707060025841816, 0.5482090041193224, 0.5284295548811137, 0.5125993729809081, 0.5018872394590627, 0.497367995460187, 0.4999933466113448, 0.5105652227778716, 0.529712383582218, 0.557870884823543, 0.5952689300389454, 0.641916527103199, 0.6976002545132209, 0.7618833186628926, 0.8341109550069141, 0.9134210956941319, 0.998760097231019, 1.0889031971987548, 1.1824792520725411, 1.2779992016787922, 1.373887612421535, 1.4685165734429275, 1.5602411593059413, 1.6474356311286489, 1.7285295264235183, 1.8020427867767075, 1.8666190920121692, 1.9210566091872316, 1.9643354237279727, 1.995640996827212, 2.014383086050102, 2.0202096726814225, 2.0130155571251387, 1.992945409774701, 1.9603911961500606, 1.9159840285517313, 1.8605806287686395, 1.7952447142775876, 1.721223740777507, 1.639921543883453, 1.5528675196920312, 1.4616830653698258, 1.3680460649371553, 1.2736542504757142, 1.180188293999954, 1.0892754896096182, 1.002454869200796, 0.9211445583804269, 0.8466121232243228, 0.7799485845366169, 0.722046686142834, 0.6735838997067415, 0.6350105331685403, 0.6065431859991492, 0.5881636650980233, 0.5796233435041288, 0.5804528133671781, 0.5899765580358152, 0.6073322487504176, 0.6314941621862356, 0.6613001186285218, 0.6954812592052687, 0.7326939163082555, 0.7715527856272897, 0.8106645821709528, 0.8486613568279392, 0.8842326645113497, 0.9161558092982739, 0.9433234453095154, 0.9647678829840934, 0.9796815370712111, 0.9874330528827244, 0.987578758584939, 0.9798692107538818, 0.9642507250700959, 0.9408619107611786, 0.9100253530411877, 0.8722347092090003, 0.8281375982272264, 0.7785147676718729, 0.7242561133407717, 0.6663342032777179, 0.6057760176292672, 0.543633657146151, 0.4809547952757091, 0.41875365115414, 0.3579832433834269, 0.2995096477497237, 0.24408892697399298, 0.19234732860770867, 0.14476526014599872, 0.10166545055369158, 0.06320559723368956, 0.02937567981600209, 2.5385357101887763e-16], [-0.0, -0.02430934221584486, -0.04522101381486671, -0.06341913007313893, -0.07969077986662718, -0.09490179098182036, -0.10997018026662972, -0.12583799744674065, -0.14344231476461736, -0.16368613867289666, -0.1874100240015158, -0.21536515518973354, -0.2481886237053758, -0.28638157653422985, -0.3302908389560257, -0.38009452751347456, -0.43579206830674017, -0.497198924028448, -0.5639462132934617, -0.6354852808218105, -0.7110971500447549, -0.7899066639209078, -0.8709009983449764, -0.9529521185756465, -1.034842645490289, -1.115294507828425, -1.1929996812299883, -1.2666522567475496, -1.3349810421268518, -1.3967818795554545, -1.4509488643317912, -1.4965036700572467, -1.5326222270444854, -1.5586580607114553, -1.574161674362668, -1.5788954540785916, -1.5728436801771162, -1.5562173472767222, -1.529453620503499, -1.4932098857644434, -1.4483524840511144, -1.3959403501862964, -1.337203902059714, -1.2735196441075458, -1.206381055653956, -1.1373664280928635, -1.0681043924140756, -1.0002379383252595, -0.9353877666798396, -0.8751158370529651, -0.8208899715737051, -0.7740503544941343, -0.7357787249413443, -0.7070709988443025, -0.6887139766200077, -0.6812666977506445, -0.6850468941890795, -0.7001228742369403, -0.7263110400645837, -0.7631791085051332, -0.8100549694009003, -0.8660409819013408, -0.930033379964083, -1.0007463370359164, -1.0767401294385244, -1.1564527410385979, -1.2382341706974564, -1.3203826407366455, -1.4011818607506652, -1.478938477600501, -1.5520188398842971, -1.6188842236453196, -1.6781237050668325, -1.728483924442479, -1.768895062344017, -1.7984924417391248, -1.8166332765490587, -1.8229082051491106, -1.8171473737019925, -1.7994209658707896, -1.7700342091560652, -1.729517020567237, -1.6786085823342436, -1.618237258769925, -1.5494963752773903, -1.4736164771954305, -1.3919347673544793, -1.3058624849287386, -1.2168510329048592, -1.1263576862036513, -1.0358117166451535, -0.9465817545049144, -0.8599451698460031, -0.7770602010996716, -0.6989414849520997, -0.6264395523560476, -0.5602247526923793, -0.5007759543579139, -0.4483742482186247, -0.4031017535019783, -0.3648454969883305, -0.33330620901680913, -0.30801175702328304, -0.28833482213346107, -0.2735143196037016, -0.26267997222918044, -0.25487936948557255, -0.24910678601076156, -0.24433299250791807, -0.23953527123178991, -0.23372684738454985, -0.22598496696981443, -0.21547689040407256, -0.2014831284446639, -0.18341732128011787, -0.16084225103317829, -0.13348158016257555, -0.10122702070910276, -0.06414075915260173, -0.022453085783516544, 0.02344469720656223, 0.07301189142635824, 0.1255742261491437, 0.1803434647121149, 0.23644026875887905, 0.2929197100192124, 0.348798749334843, 0.40308495006773715, 0.4548056592147128, 0.5030368753735435, 0.5469310285416293, 0.5857429224550856, 0.6188531351693524, 0.645788236731926, 0.666237262535003, 0.6800639752732339, 0.6873145550117267, 0.6882204730235151, 0.683196427870452, 0.6728333485920754, 0.6578865966530354, 0.6392596222856995, 0.617983448919167, 0.5951924685206645, 0.5720971281188783, 0.5499541710471939, 0.530035163403334, 0.5135940851389718, 0.5018347947837204, 0.49587918626747673, 0.4967368453286031, 0.5052769817867012, 0.5222033632260404, 0.5480329065748648, 0.5830784983311029, 0.6274365138488049, 0.6809793936018659, 0.7433535124290245, 0.8139824494235625, 0.8920756345149815, 0.9766422161386933, 1.066509865951708, 1.1603481145030312, 1.2566956991318936, 1.3539913049422199, 1.4506069939909778, 1.5448835489751886, 1.6351669074397048, 1.7198448321343278, 1.7973829534145516, 1.8663593307904776, 1.9254967126526268, 1.9736917251023338, 2.010040291457788, 2.033858671701821, 2.0446996137723983, 2.042363223690147, 2.0269022862809436, 1.9986218996579015, 1.9580734214836462, 1.9060428600620933, 1.8435339752246955, 1.7717464795703006, 1.6920498468355898, 1.6059533381886186, 1.5150729465245631, 1.4210960312343965, 1.325744469661881, 1.2307371852671791, 1.1377529255706187, 1.0483941549603406, 0.964152898630297, 0.8863793249987579, 0.8162537861615776, 0.7547629509400177, 0.7026805649904384, 0.6605532597214168, 0.6286917091869494, 0.6071673047056101, 0.5958143838705392, 0.59423791712522, 0.6018264244504866, 0.6177697701286943, 0.641081368056182, 0.6706242264704951, 0.7051401717514687, 0.7432815182922549, 0.7836443970527858, 0.8248029205837231, 0.8653433478382258, 0.9038974182614218, 0.939174051241725, 0.969988653297942, 0.99528934014876, 1.014179462399377, 1.0259359199022848, 1.0300228584640818, 1.0261004607357902, 1.0140286678676627, 0.9938657967010889, 0.9658621457013679, 0.9304488082980037, 0.8882220316673394, 0.8399235692975964, 0.7864175741832706, 0.7286646637691072, 0.6676938557287988, 0.604573123657704, 0.5403793525724201, 0.476168485016198, 0.41294663934107084, 0.3516429526540665, 0.2930848527527148, 0.23797639738896537, 0.18688023709166926, 0.14020366165054166, 0.09818908267346954, 0.060909188117896015, 0.028266882328896195, 2.441526044796518e-16], [-0.0, -0.02342272080945969, -0.04372482864209873, -0.06165511685779969, -0.07805375205207923, -0.09382633322611497, -0.10991600463748215, -0.12727436813977888, -0.14683197360870712, -0.16946917889105312, -0.19598816325645363, -0.22708685074599522, -0.2633354527698289, -0.30515627397189804, -0.3528073433790548, -0.40637033623107943, -0.4657431430645106, -0.5306373243240904, -0.6005805639703354, -0.6749241073778296, -0.7528550405034449, -0.8334131420831471, -0.9155119216548459, -0.9979633465164204, -1.0795056630996067, -1.158833635162561, -1.2346304548083313, -1.305600534342208, -1.3705023586509741, -1.4281805698961634, -1.4775964691279202, -1.5178561526968217, -1.5482355543084398, -1.568201734978058, -1.5774298512873006, -1.5758153350874118, -1.5634809326347006, -1.5407783752756243, -1.5082845841786043, -1.4667924450318028, -1.4172963218032708, -1.360972608303471, -1.2991557391918933, -1.2333101951812329, -1.1649991377014342, -1.0958503936847883, -1.0275205792826636, -0.9616582005062224, -0.8998665977434664, -0.8436676090847173, -0.794466814144658, -0.7535211858790462, -0.7219099235513841, -0.7005091667979909, -0.6899712004229239, -0.6907086543025827, -0.7028840851377488, -0.7264051996086518, -0.760925844852891, -0.8058527553435659, -0.8603579085232047, -0.9233962082738995, -0.9937280887186054, -1.0699465140324926, -1.15050774573798, -1.2337651598951538, -1.318005324842317, -1.4014854974274387, -1.482471663270695, -1.5592762352852287, -1.6302945347131734, -1.6940392100417163, -1.7491718005664818, -1.7945307217886748, -1.8291550375247463, -1.8523034864080583, -1.8634683458387697, -1.862383841552839, -1.8490289427614408, -1.8236245180257897, -1.7866249623688488, -1.7387045382754773, -1.6807387989719835, -1.6137815786431957, -1.53903813821789, -1.4578351445171907, -1.371588232771023, -1.2817679560426556, -1.1898649587029526, -1.0973552240010402, -1.0056662377364178, -0.9161448813172469, -0.8300278188695959, -0.7484150758128126, -0.6722474221651538, -0.6022880749353738, -0.5391091227943585, -0.4830829556099804, -0.43437885439949336, -0.3929647669916205, -0.3586141644528621, -0.3309177463693105, -0.3092996425479379, -0.2930376476037356, -0.28128692598375754, -0.2731065406885199, -0.2674880913573679, -0.26338569813783974, -0.25974653804788533, -0.255541131060763, -0.24979258408404786, -0.24160403204247555, -0.2301835655816058, -0.21486600317508348, -0.19513094988295965, -0.17061668350715958, -0.14112951890767575, -0.10664841997668432, -0.06732475319821674, -0.02347720368756659, 0.024417999115234703, 0.0757412765332911, 0.12974793156171235, 0.18558992516309333, 0.24234061464005635, 0.29902179285860064, 0.35463230612055124, 0.4081774860057717, 0.4586986076159217, 0.50530158394919, 0.5471841237094993, 0.5836606172829673, 0.6141840719776739, 0.6383644915210238, 0.6559831844002112, 0.6670025886767394, 0.6715713148251934, 0.6700242300824185, 0.6628775346826655, 0.6508189090051251, 0.6346929378304139, 0.6154821403816815, 0.5942840495152871, 0.5722848874161601, 0.5507304757966819, 0.5308950935768092, 0.5140490524056941, 0.5014257986755412, 0.49418936885460235, 0.49340302250592577, 0.49999985425295146, 0.5147561427081077, 0.5382681320047802, 0.5709328615534901, 0.6129335639089524, 0.6642300415099653, 0.7245543132009441, 0.7934116937961879, 0.8700873376399241, 0.953658143403099, 1.0430097855401068, 1.1368585111636367, 1.2337772227214885, 1.332225259715673, 1.4305811994587672, 1.527177919846764, 1.6203391082761276, 1.7084163616358332, 1.7898260037732032, 1.8630847494669838, 1.9268433677260477, 1.9799175416298378, 2.0213151858930716, 2.050259565346599, 2.0662076556074433, 2.0688632989973437, 2.058184831554566, 2.0343869877910428, 1.9979370254994298, 1.9495451501151855, 1.8901494535503527, 1.8208957127436818, 1.7431125152448712, 1.6582822899995093, 1.5680089184302184, 1.4739826815643953, 1.3779433613840346, 1.2816423572593438, 1.1868047002499669, 1.0950918486991634, 1.0080661279123826, 0.927157635327669, 0.8536343714853613, 0.7885762778040889, 0.7328537666292052, 0.6871112195943646, 0.6517558097208702, 0.6269518738364697, 0.6126209279880648, 0.6084472828325804, 0.613889081837346, 0.6281944557824277, 0.6504223656852275, 0.6794675958131615, 0.7140892615900146, 0.7529421162722302, 0.7946098772120265, 0.8376397488296901, 0.8805772961008821, 0.9220008199347307, 0.9605544042657677, 0.9949788434819685, 1.024139716934784, 1.0470519532208402, 1.0629003187472128, 1.0710553704608297, 1.07108452887568, 1.0627580517421564, 1.046049817753268, 1.0211329603413664, 0.9883705206224445, 0.9483014126771532, 0.901622110531369, 0.8491645715320478, 0.7918710027008778, 0.7307661528245087, 0.6669278716388218, 0.6014567170622215, 0.535445411083808, 0.46994894417276784, 0.4059561070132122, 0.34436318756183887, 0.28595051194667065, 0.23136243111360627, 0.18109126335206574, 0.13546559823924556, 0.09464325280137456, 0.058609048720382875, 0.027177453315199353, 2.3482584682386714e-16], [-0.0, -0.022611450101783878, -0.042415231707820925, -0.06021954928674037, -0.07691122727697317, -0.0934282529550014, -0.11073076974177495, -0.1297712979522969, -0.1514649816505919, -0.1766606614488742, -0.20611355373632104, -0.24046027740720755, -0.28019691065370356, -0.3256606842503818, -0.3770158258858704, -0.43424396479060656, -0.4971393898077704, -0.5653093300715484, -0.638179298709744, -0.7150034097176643, -0.7948794496420203, -0.8767683622135611, -0.9595176887018035, -1.0418884024629513, -1.1225844855697817, -1.2002845208687745, -1.273674516227024, -1.3414811405868503, -1.4025045347339122, -1.4556498638916846, -1.4999568043469855, -1.534626201732703, -1.5590432032819788, -1.5727962487778542, -1.5756914030642175, -1.567761624472753, -1.549270685634288, -1.5207115928894404, -1.4827994847046784, -1.4364591248303729, -1.3828072390662802, -1.3231300721334602, -1.2588566601251936, -1.1915284213654167, -1.1227657615655742, -1.05423246560988, -0.9875987061919533, -0.9245035374021882, -0.8665177582456276, -0.8151080264901452, -0.7716030772668683, -0.7371628540583991, -0.7127512932159453, -0.6991134185313226, -0.6967573016866916, -0.7059413300449136, -0.7266670979942471, -0.758678104960561, -0.8014643054807615, -0.8542724177408851, -0.9161217601022748, -0.985825253700873, -1.0620151064067533, -1.1431725822622376, -1.2276611636813548, -1.3137623335443658, -1.3997131428034297, -1.4837446878173426, -1.56412060135034, -1.6391746624796428, -1.7073466535087076, -1.7672156357988897, -1.8175298801208324, -1.8572327691109478, -1.8854840876742143, -1.9016762292818035, -1.9054449693136477, -1.8966745878664584, -1.8754972605673441, -1.8422867735685318, -1.7976467546838812, -1.7423937432482488, -1.6775355435541393, -1.6042454176753247, -1.5238327704371846, -1.4377110599012746, -1.3473637290671614, -1.2543089970826877, -1.1600643701088764, -1.0661117326367788, -0.9738638595538204, -0.8846331481829265, -0.7996033089526975, -0.719804674865004, -0.6460936955119987, -0.579137073452215, -0.5194008820099707, -0.4671448770003053, -0.42242208367748774, -0.385083607640917, -0.3547884878171985, -0.33101828422412044, -0.3130959761276021, -0.30020864032862854, -0.29143328727963125, -0.2857651567939047, -0.28214771713548253, -0.2795035726657107, -0.27676546689454395, -0.27290657014762165, -0.2669692640034319, -0.2580916775514883, -0.24553129224559095, -0.2286850110783055, -0.20710518195508287, -0.18051117209105116, -0.14879620726324663, -0.11202931384831792, -0.07045232960720618, -0.024472077893849933, 0.025352073900685917, 0.07832493050266999, 0.1336360068198959, 0.19038333536404456, 0.24759990481159688, 0.3042820221869782, 0.35941883999062785, 0.41202225787731117, 0.4611563970345933, 0.5059658545261215, 0.5457019743395299, 0.5797464209914264, 0.6076314090741136, 0.6290560263974873, 0.6438981872787877, 0.6522218635860524, 0.6542793615624314, 0.6505085392230184, 0.641524989034519, 0.6281093403875715, 0.6111899627761552, 0.5918214704115904, 0.5711595391835913, 0.5504326446358605, 0.5309114124532425, 0.5138763387343996, 0.5005846843432379, 0.4922373746541083, 0.4899467422870393, 0.49470593574332294, 0.5073607814939005, 0.5285848318548911, 0.5588582572141946, 0.5984511506230941, 0.6474117076311863, 0.7055596270833808, 0.772484952280044, 0.8475524395252697, 0.9299114059105067, 1.0185108735352035, 1.1121196965797453, 1.209351233958568, 1.3086920167633573, 1.4085337591833411, 1.5072079765724677, 1.60302240695456, 1.6942983842199317, 1.7794082837981113, 1.856812155416628, 1.9250926728762072, 1.9829875672615607, 2.029418766816717, 2.0635175424964913, 2.0846450511458854, 2.092407776117593, 2.0866674853076352, 2.0675454561583164, 2.03542085300151, 1.9909232808933082, 1.9349196784483556, 1.8684958467520238, 1.7929330389359148, 1.7096801523435559, 1.620322169533702, 1.5265455831312054, 1.4301016105852173, 1.3327680565088549, 1.236310711208169, 1.1424451835223117, 1.0528000539769409, 0.9688822008148436, 0.8920450975483311, 0.8234608076164731, 0.764096311331711, 0.7146946947943309, 0.675761612436355, 0.6475573072289147, 0.6300943384812874, 0.6231410298621265, 0.6262305131443774, 0.6386751095651679, 0.6595856638593122, 0.6878953290560569, 0.7223871958611463, 0.7617250713999361, 0.8044866404124917, 0.8491981893757273, 0.894370041715137, 0.9385318409899696, 0.9802668288999472, 1.0182442958535685, 1.051249432824168, 1.0782098829731925, 1.0982183782497816, 1.1105509476760331, 1.1146802977304011, 1.1102840882825304, 1.0972479568219158, 1.0756632760211393, 1.045819761676524, 1.0081931764834837, 0.9634284967358324, 0.9123190208696235, 0.8557819980346679, 0.794831439122761, 0.7305488398429326, 0.6640525938738229, 0.5964669026765075, 0.5288909965525981, 0.46236946883320823, 0.3978644920544939, 0.33623063249468593, 0.27819290888244425, 0.22432865425573573, 0.17505363907960314, 0.13061280139603726, 0.09107580884070733, 0.05633755089492111, 0.02612353095870142, 2.260205635695391e-16], [-0.0, -0.0218902209227713, -0.04131944556513211, -0.05914930756495493, -0.07630624996647196, -0.09375276117609335, -0.11245748285776953, -0.1333649917342989, -0.1573660672903462, -0.1852692465637841, -0.2177744358187899, -0.25544929769014735, -0.29870906264622404, -0.3478003270789059, -0.40278929915778977, -0.46355484031931204, -0.5297865277427699, -0.6009878344745481, -0.6764843922389034, -0.7554371707368865, -0.8368602796984375, -0.9196429793434079, -1.0025753742841754, -1.084377168080083, -1.1637287731312178, -1.2393040054971314, -1.3098035482345607, -1.373988341182126, -1.4307120504894855, -1.478951787779591, -1.5178362863027473, -1.546670798925822, -1.5649580589343035, -1.572414737576651, -1.5689829397945954, -1.5548363990375937, -1.530381160529908, -1.496250676689497, -1.4532953752815887, -1.4025668969480445, -1.34529733062118, -1.2828738997387565, -1.2168096660338157, -1.1487109181421291, -1.0802419968387447, -1.0130883752588347, -0.9489188592923501, -0.8893477992651603, -0.8358982083426219, -0.7899666656565116, -0.7527908433397531, -0.7254204373581561, -0.7086922036621577, -0.7032097056218306, -0.7093282682575397, -0.7271455121067028, -0.756497707646884, -0.7969620532292062, -0.8478648388168668, -0.908295317892821, -0.9771249741042546, -1.053031740855078, -1.1345286142668771, -1.2199959955703492, -1.3077170106023972, -1.3959149838164933, -1.4827921937699118, -1.566569007649849, -1.645522484743952, -1.718023553020865, -1.7825718987959034, -1.8378277659235656, -1.882639936682677, -1.9160692596330442, -1.9374071979309264, -1.9461889922336224, -1.9422011624386661, -1.9254832088992568, -1.896323513094242, -1.8552495765999277, -1.8030128722212846, -1.7405687090007231, -1.6690516304242584, -1.5897469696357869, -1.504059274326958, -1.4134783850586425, -1.319544002398573, -1.2238096092195552, -1.1278066240974887, -1.0330096498108017, -0.9408036478375906, -0.8524538163610511, -0.7690788770145452, -0.6916283862764849, -0.6208645833312969, -0.5573491699770848, -0.5014352927082881, -0.4532648655811977, -0.4127712381726337, -0.3796870792207943, -0.35355721672344625, -0.3337560525887421, -0.3195090574299106, -0.3099177515481149, -0.3039874940102203, -0.3006573350622688, -0.2988311395465526, -0.29740916165107995, -0.2953192448470678, -0.2915468353712477, -0.2851630326677863, -0.2753499548870737, -0.26142277042218687, -0.24284783566999138, -0.21925648244681792, -0.1904541131322215, -0.1564243847389654, -0.11732839158260538, -0.07349888678785056, -0.025429712208815947, 0.02623926882312574, 0.08074132434124408, 0.13720557406141776, 0.1946826658704971, 0.2521727196914366, 0.3086547901167927, 0.3631170585845026, 0.41458694549000813, 0.4621603330177824, 0.5050291106410613, 0.5425062966658015, 0.5740480498571883, 0.5992719635730305, 0.6179711289788952, 0.6301235614765698, 0.6358967027423169, 0.635646836773097, 0.6299133889078392, 0.6194082086373293, 0.6050000668140414, 0.587694722341118, 0.5686110294050064, 0.5489536608729567, 0.5299831139396731, 0.5129837381593191, 0.4992305817285656, 0.4899558878364567, 0.48631608810184723, 0.4893601341293836, 0.4999999811090064, 0.5189839897670915, 0.5468739459675153, 0.5840263124616816, 0.6305782267478202, 0.6864386451676742, 0.7512849090249353, 0.8245648767041129, 0.9055046297418857, 0.9931216239091467, 1.0862430219829895, 1.1835288163512807, 1.2834992300882113, 1.38456577764072, 1.485065273456468, 1.583296001088889, 1.677555198445291, 1.7661769783472405, 1.8475697883963522, 1.920252520709083, 1.9828884102905708, 2.0343159100192514, 2.0735757992515507, 2.0999338702819443, 2.112898640211918, 2.1122336526976175, 2.097964061730478, 2.070377324960574, 2.030017973811185, 1.977676568357322, 1.9143730832266508, 1.8413351032621263, 1.7599713311361331, 1.6718410205206002, 1.578620045085223, 1.4820643931655626, 1.3839719384827558, 1.2861433773407571, 1.1903432413115544, 1.0982618911053514, 1.011479372209443, 0.9314319665982872, 0.8593822085172805, 0.7963930476634237, 0.7433067421149261, 0.7007289485835991, 0.6690183517989541, 0.6482820411678737, 0.638376704564048, 0.6389155695722991, 0.6492808851542811, 0.6686416048653525, 0.6959758096475254, 0.7300972968402621, 0.7696856650851086, 0.813319144587917, 0.859509360662312, 0.9067371770646976, 0.9534887453002069, 0.998290887263236, 1.0397449611768352, 1.0765584041840928, 1.1075732079809053, 1.1317906649390796, 1.148391819184261, 1.15675316760749, 1.1564572770148582, 1.1472981125109427, 1.129281005538366, 1.1026173244253439, 1.0677140424728404, 1.0251585252537838, 0.9756989767547448, 0.9202210903449849, 0.8597215426837795, 0.7952790443103022, 0.7280237179535307, 0.659105613167201, 0.5896631828477473, 0.520792543159951, 0.45351831353095523, 0.38876678835530687, 0.3273421280635385, 0.2699061759006427, 0.21696241022732776, 0.1688444328648848, 0.1257092747407052, 0.08753567389017698, 0.05412735093844838, 0.025121176819868786, 2.1788127918481135e-16], [-0.0, -0.02127305198730117, -0.04046295739032061, -0.05847812819651207, -0.07627702639912654, -0.09483832025242403, -0.11513035521785643, -0.1380807598986298, -0.1645470052668493, -0.19528871247769275, -0.23094246110276195, -0.2719997867795524, -0.31878897663430394, -0.3714611744095557, -0.4299811974332218, -0.494123347159832, -0.5634723670240065, -0.6374295689934402, -0.7152240168300116, -0.7959285230305755, -0.8784800910375795, -0.9617043177617315, -1.0443431667065006, -1.1250854316990913, -1.202599137729204, -1.2755650705743484, -1.342710592184221, -1.4028428851420407, -1.4548807773293138, -1.4978843270685853, -1.5310813988499963, -1.5538905290883476, -1.565939468545548, -1.5670788909783477, -1.5573908737262945, -1.5371918824984834, -1.5070301264438748, -1.4676772874048938, -1.420114765657504, -1.365514720010512, -1.3052163095128166, -1.2406976639858467, -1.1735442181714972, -1.105414136775729, -1.038001632773586, -0.9729990371268764, -0.9120585131274503, -0.8567543220013984, -0.8085465378083988, -0.7687470792031075, -0.7384888739873668, -0.7186989007899847, -0.7100757623741089, -0.7130723391500833, -0.7278839520212055, -0.7544423336028733, -0.7924155692879623, -0.8412140279250598, -0.9000021594777035, -0.9677158974077182, -1.0430852700741224, -1.124661701410882, -1.2108493695632774, -1.2999398957401698, -1.3901495566245206, -1.4796581541945195, -1.5666486381846074, -1.6493465595907104, -1.7260584389936013, -1.7952081608929646, -1.8553705540252114, -1.9053013865727548, -1.943963092558956, -1.9705456494101286, -1.984482144104286, -1.985458693632526, -1.9734185215266695, -1.948560132624116, -1.9113296696132764, -1.8624076737768318, -1.8026906053392502, -1.7332676026927727, -1.6553930715161094, -1.5704557917090585, -1.4799453098114737, -1.3854164452502398, -1.2884527789310463, -1.1906300114386081, -1.0934800750361995, -0.9984568589087318, -0.9069043613541441, -0.8200280170939818, -0.7388698642310082, -0.664288115759468, -0.596941587452751, -0.5372793102628995, -0.4855355241714603, -0.44173011501687376, -0.40567441957150385, -0.37698219044695247, -0.35508538459339634, -0.33925432039733977, -0.32862164161013946, -0.32220943418904485, -0.3189587668651904, -0.31776086970440554, -0.31748912846072247, -0.31703105699805284, -0.3153194158057589, -0.3113616714584459, -0.30426703904106955, -0.2932704158400385, -0.2777525982745138, -0.2572562729602157, -0.23149738443150775, -0.20037160355020708, -0.16395574891071457, -0.12250414535201232, -0.07644003566377013, -0.02634229037998172, 0.027072217075051416, 0.08297008978741596, 0.14042616075847045, 0.19845085427058096, 0.2560194207797584, 0.3121022613591312, 0.36569552828698076, 0.4158511798118595, 0.461705679666469, 0.5025065652412652, 0.5376361616439482, 0.5666317908337491, 0.5892019138309326, 0.6052377474372848, 0.6148200123670419, 0.6182205942787423, 0.6158990297821971, 0.6084938627817594, 0.5968090491446251, 0.5817957163001606, 0.5645297057267064, 0.5461854372865609, 0.5280067322020475, 0.5112753136247727, 0.4972777681228246, 0.48727179632430667, 0.48245260522100064, 0.4839202975774713, 0.492649095364003, 0.5094591945276125, 0.5349919886516922, 0.5696893205538501, 0.6137773255254293, 0.6672553200408335, 0.7298900680424827, 0.8012156263208484, 0.8805388342687787, 0.9669503747520688, 1.0593411954264262, 1.1564239469459694, 1.2567589694473116, 1.3587842445665932, 1.460848629901293, 1.561247608776993, 1.6582607225355561, 1.750189806991385, 1.835397130379484, 1.9123425276944814, 1.9796186459083873, 2.035983455728065, 2.0803892473528993, 2.11200740865105, 2.1302483823487948, 2.1347763118566485, 2.125518010504912, 2.102666023197298, 2.0666756895550837, 2.0182562601112513, 1.9583562585575602, 1.8881434200040874, 1.808979664345091, 1.7223916819918235, 1.6300378135544373, 1.5336719929923222, 1.4351055931661831, 1.3361680619313496, 1.2386672647199433, 1.1443504553035704, 1.054866779982428, 0.971732182228789, 0.8962975157732933, 0.8297205957204864, 0.772942821448662, 0.7266708941459261, 0.6913640285841296, 0.6672269261591598, 0.6542086375793911, 0.652007302257252, 0.660080610906905, 0.6776617015042365, 0.7037800699454939, 0.737286958579036, 0.7768845811446202, 0.8211584540618797, 0.8686120335904507, 0.9177028078126589, 0.9668789628474057, 1.0146157348520026, 1.0594505733307784, 1.1000162766308936, 1.1350713163241022, 1.1635266420016848, 1.1844683499349953, 1.1971757057431434, 1.2011341299694005, 1.1960428833121455, 1.1818173219798587, 1.1585857298989022, 1.1266808698983606, 1.0866265271580837, 1.039119441877111, 0.9850071412364004, 0.9252622804988213, 0.8609541870558827, 0.7932183673398179, 0.7232247831668097, 0.6521457301474414, 0.5811241556961494, 0.5112432378259204, 0.4434980087936481, 0.3787697507511801, 0.31780381533806523, 0.26119142756260566, 0.20935592870466455, 0.16254379603289484, 0.12082065183865863, 0.0840723438332745, 0.05201104664641671, 0.024186203357073627, 2.1054818888701384e-16], [-0.0, -0.020773129414140307, -0.03986921821745675, -0.058236190987747904, -0.07685643446398548, -0.0967161171892581, -0.11877428406288937, -0.14393255746417583, -0.17300626230676752, -0.20669775707059376, -0.24557269741370252, -0.29003988477349124, -0.3403352612829282, -0.39651050663690807, -0.45842657490132577, -0.525752382621083, -0.5979687271412824, -0.674377379146937, -0.7541151594559378, -0.8361726804549774, -0.9194173105325976, -1.0026198085361984, -1.0844839774963837, -1.1636786051238281, -1.238870894995186, -1.308760548559486, -1.3721136352768668, -1.4277953869875069, -1.4748010731018109, -1.5122841549631094, -1.539580979789459, -1.5562313554714862, -1.561994445236356, -1.5568595334073259, -1.5410513374515864, -1.5150296741755114, -1.4794834260323522, -1.4353188936465158, -1.383642759366543, -1.3257400204991259, -1.2630473765252874, -1.1971226689291288, -1.1296110724242279, -1.0622088198326052, -0.9966253075521746, -0.9345444727969053, -0.8775863564659762, -0.8272697659803435, -0.7849769306489836, -0.7519209985720589, -0.7291171597703671, -0.7173580966775308, -0.7171943623464516, -0.7289201711331423, -0.7525649590244322, -0.7878909342641413, -0.8343966968200305, -0.8913268609764367, -0.9576874724456602, -1.0322668733445695, -1.113661538544816, -1.2003062884388074, -1.290508178956151, -1.382483282254147, -1.4743955030186937, -1.5643965274125997, -1.6506659755566648, -1.7314508246527727, -1.8051031885365025, -1.8701155801101914, -1.9251528447466781, -1.9690800338491607, -2.0009855863063657, -2.020199299172909, -2.026304694743639, -2.0191455261925393, -1.9988263048049528, -1.9657068751004994, -1.9203912063230755, -1.8637107063950917, -1.7967024941448293, -1.7205831842670387, -1.6367188441938567, -1.5465918703093637, -1.4517656006206057, -1.3538475304453435, -1.2544520257391973, -1.155163434738405, -1.0575004825596879, -0.9628827957416289, -0.8726003454314867, -0.787786520524135, -0.7093954475218643, -0.6381840646011492, -0.5746993361006697, -0.5192708634310105, -0.472009012511504, -0.43280853965937915, -0.4013575608344967, -0.37715157668731375, -0.35951214125461556, -0.3476096484803818, -0.34048961081224477, -0.337101720392675, -0.33633091787446406, -0.33702964822846787, -0.33805045816531853, -0.33827808652416624, -0.33666021721390027, -0.33223610351066846, -0.32416233167966474, -0.31173506946025764, -0.2944082389333078, -0.2718071612703138, -0.24373734008992676, -0.2101881775827314, -0.17133154997173705, -0.1275153028931251, -0.07925185951159194, -0.02720226127648057, 0.02784392004028947, 0.08499225301259278, 0.14327006063571937, 0.2016552616707088, 0.2591066646765342, 0.3145949015898874, 0.3671331700206972, 0.4158069570670286, 0.4598019423376893, 0.49842932339117496, 0.5311478718220083, 0.557582111124074, 0.5775361061580091, 0.5910024660688645, 0.5981662850258113, 0.5994038751049148, 0.5952762797351102, 0.5865176909941099, 0.574019026267823, 0.5588070460283407, 0.5420195115398484, 0.5248769861926751, 0.508651974216029, 0.49463616341977706, 0.48410659247965454, 0.47829159669615107, 0.4783373982210814, 0.48527619708541325, 0.49999658814694053, 0.5232170770151063, 0.5554633963323701, 0.5970502342183901, 0.6480678813860632, 0.7083741849845255, 0.7775920685140192, 0.8551127413529265, 0.9401045818840497, 1.031527538350681, 1.1281527548750199, 1.228586999922385, 1.3313013541305314, 1.4346635068450073, 1.5369729185999386, 1.636498032473748, 1.7315146626098847, 1.8203446546228208, 1.9013939009903498, 1.9731888052063855, 2.0344103212288123, 2.0839247488535184, 2.120810539803572, 2.144380461770291, 2.154198576158196, 2.1500916072488145, 2.132154412955454, 2.1007494070789745, 2.056499926597448, 2.0002776815368177, 1.9331845658691735, 1.8565292422381279, 1.7717990378434791, 1.6806278004954331, 1.5847604599515202, 1.4860151178373417, 1.3862435478234634, 1.2872910248691651, 1.1909564173527636, 1.09895346843325, 1.0128741632249485, 0.9341550270573653, 0.8640471285050416, 0.8035904707708381, 0.7535933486073355, 0.7146171278781103, 0.6869667740395649, 0.6706873174706076, 0.6655663010786506, 0.6711421124495611, 0.6867179624817947, 0.7113811383709947, 0.7440270342521589, 0.7833873507838796, 0.8280617581817112, 0.8765522380035403, 0.9272992592507002, 0.9787189054826612, 1.0292400525414527, 1.0773407014975498, 1.12158259836727, 1.1606433202784294, 1.193345075819091, 1.218679553546827, 1.235828254870272, 1.2441778631566753, 1.2433303270587368, 1.2331074695267341, 1.213550071439545, 1.1849115168199333, 1.1476462217589272, 1.1023931981038853, 1.049955222470062, 0.9912741882631158, 0.9274033105121839, 0.8594769281519484, 0.7886787041359101, 0.716209059070915, 0.6432526881074505, 0.5709470033077788, 0.5003523148911203, 0.4324245154021913, 0.36799096225982997, 0.3077301680905312, 0.25215580694738304, 0.20160543054805333, 0.15623416494096592, 0.11601352767370426, 0.08073537190149793, 0.050020830326555424, 0.023334001785767396, 2.041555955207608e-16], [-0.0, -0.02040265304590808, -0.03955936003829874, -0.058449738769215526, -0.07807158416401798, -0.09940960813101052, -0.12340442796745674, -0.15092263911183654, -0.1827287812430957, -0.2194599591278136, -0.26160381239404945, -0.3094804432496129, -0.36322881019931896, -0.4227979815869653, -0.4879435181664399, -0.5582291220304265, -0.6330335534190458, -0.7115626806220557, -0.7928663948223155, -0.8758599946817263, -0.9593495279673605, -1.0420604725444986, -1.1226690493053797, -1.1998353873618441, -1.2722377089763848, -1.3386066696276855, -1.3977589781743562, -1.4486294336262175, -1.4903005483390819, -1.5220289817560204, -1.5432680828390954, -1.5536859312897158, -1.5531783753113353, -1.541876684397578, -1.520149566472801, -1.4885994364536208, -1.4480529645428388, -1.399546073821074, -1.3443036944674045, -1.2837147127983326, -1.2193026740078203, -1.1526929050078014, -1.0855768154159373, -1.0196742082089538, -0.9566944849942419, -0.8982976628775955, -0.8460561296758305, -0.8014180514400994, -0.7656733111751849, -0.7399228010671575, -0.7250518138015626, -0.72170818349994, -0.7302857157092907, -0.7509133214302492, -0.7834501353787481, -0.8274867568142569, -0.8823526057830217, -0.9471292420571973, -1.0206693519451602, -1.1016209729674276, -1.1884564014311119, -1.2795051162406277, -1.3729899565754715, -1.4670657136796206, -1.5598592398249531, -1.6495101419222886, -1.7342111141188237, -1.812246973350397, -1.8820314939650191, -1.9421411914020599, -1.9913452791712103, -2.028631116198637, -2.053224570714423, -2.064604849567809, -2.0625134751665293, -2.046957232879208, -2.018205056274488, -1.9767789624658654, -1.9234392915512943, -1.8591646392291044, -1.7851269968522214, -1.7026627254154838, -1.613240086544105, -1.5184241321428253, -1.4198398130997665, -1.319134204933777, -1.2179387636720123, -1.1178325182359432, -1.0203070764411915, -0.9267342711699584, -0.8383372026696908, -0.7561653440770656, -0.6810742724184797, -0.6137104691439607, -0.5545015056823787, -0.50365179378396, -0.4611439409335542, -0.42674561135244127, -0.4000216565346233, -0.3803511492748414, -0.36694883495827163, -0.35889040646262665, -0.3551409170144828, -0.3545855709950913, -0.35606207781327076, -0.3583937198706632, -0.3604222731320705, -0.3610399281336235, -0.35921939012029097, -0.3540413885686826, -0.34471889727062777, -0.33061745459396125, -0.31127107722839814, -0.28639337701612017, -0.2558836163949887, -0.2198275703452106, -0.17849319816724063, -0.13232126349523168, -0.08191117224403194, -0.028002422373794647, 0.028547826708978402, 0.08679045649556011, 0.14571266973361618, 0.20426808780065728, 0.2614078563732974, 0.3161119237171576, 0.36741965041979974, 0.4144589254904244, 0.4564730010609306, 0.492844315514333, 0.5231146512981388, 0.5470010670359581, 0.5644071514864706, 0.5754292667015988, 0.580357576390293, 0.5796717897596262, 0.5740316875940991, 0.564262632599978, 0.5513363966624268, 0.5363477603285859, 0.5204874514234166, 0.5050120873827736, 0.49121186714998694, 0.4803768212342583, 0.4737624711374355, 0.47255577068705085, 0.47784220126448623, 0.4905748704300507, 0.5115464195117676, 0.5413644813685581, 0.5804313462993644, 0.6289283939602246, 0.6868057346085211, 0.7537773768196425, 0.8293221041137754, 0.9126901030064497, 1.0029152433097066, 1.0988327715668922, 1.1991020437732467, 1.302233797365891, 1.4066213480038676, 1.5105749967636257, 1.6123588505547413, 1.7102291949052442, 1.8024735153975275, 1.8874492430663368, 1.9636213005745804, 2.0295975499813195, 2.084161288878225, 2.1263000085218398, 2.155229713740499, 2.1704142077811515, 2.1715788633906556, 2.1587185314413886, 2.132099377159789, 2.0922545781291615, 2.039973964209635, 1.9762878237954058, 1.9024452398976162, 1.8198874500112914, 1.730216842415938, 1.6351623055785696, 1.53654173413981, 1.4362225624543208, 1.3360812431838462, 1.2379626128775545, 1.1436400882314472, 1.0547776157649376, 0.9728942545118032, 0.8993322070613595, 0.8352290304870451, 0.7814946574236493, 0.7387937412888052, 0.7075337112399066, 0.6878587850609944, 0.6796500451483458, 0.6825315376053985, 0.695882210711755, 0.7188533702023523, 0.7503911982602359, 0.789263764059454, 0.8340918489760695, 0.8833828217399994, 0.9355667299334229, 0.9890337259867565, 1.0421719193043175, 1.093404741953286, 1.1412269335056933, 1.1842382906157416, 1.2211743876872165, 1.250933554971593, 1.2725994975967845, 1.2854590509011676, 1.2890146912183589, 1.2829915538195165, 1.2673388477540373, 1.2422256973906745, 1.2080315790615217, 1.1653316549068111, 1.1148774314952892, 1.0575732849507709, 0.9944494943371618, 0.9266325084872526, 0.8553132362690782, 0.781714194901461, 0.7070563742989053, 0.6325266770199643, 0.5592467732332466, 0.4882441687668094, 0.42042622286499, 0.356557772338904, 0.2972429224218326, 0.24291145429681912, 0.1938101777667751, 0.14999942797977023, 0.11135477079582276, 0.07757384569422117, 0.04818814151171405, 0.022579372155996327, 1.988303888215097e-16], [-0.0, -0.020172691312177183, -0.039551934030124934, -0.05914073431261991, -0.07994343417373195, -0.10293413976322663, -0.12902588102540896, -0.15904133521223274, -0.19368590739242625, -0.2335239013441193, -0.27895843554124883, -0.3302156633188469, -0.3873337461325973, -0.4501569068856565, -0.5183347596517734, -0.5913269760718094, -0.6684132106745739, -0.7487080708605899, -0.8311807857439152, -0.91467910480817, -0.9979568455308336, -1.0797044116155516, -1.1585815227431242, -1.233251334889498, -1.3024150888761357, -1.3648464050178308, -1.4194243440807977, -1.4651643792724123, -1.5012464701124322, -1.5270394957018478, -1.5421213905127846, -1.5462944282983946, -1.5395952165676074, -1.5222990924246838, -1.4949187472837042, -1.4581970496640742, -1.4130941784544748, -1.360769320153673, -1.3025573191549649, -1.2399407967642802, -1.1745183691716112, -1.107969694165354, -1.042018158486904, -0.9783920802927261, -0.9187853426250701, -0.8648183930114351, -0.8180005407831252, -0.7796944574509362, -0.7510837370869073, -0.7331443042667998, -0.726620368378716, -0.7320055171275085, -0.7495294214173335, -0.779150491394409, -0.8205546824895656, -0.8731605042395779, -0.9361301370405827, -1.0083864163910061, -1.0886353041632333, -1.1753933354165766, -1.2670194104247379, -1.3617501978370838, -1.457738328755704, -1.5530924950883465, -1.6459185204487843, -1.7343604492158695, -1.8166406996765507, -1.891098350450378, -1.9562246750445673, -2.010695106294507, -2.053396898958006, -2.0834518627288894, -2.100233656864812, -2.10337926857108, -2.0927944370403395, -2.0686529301984606, -2.031389728202913, -1.9816883129936416, -1.9204624031680795, -1.8488326047362358, -1.7680985677222782, -1.6797073432261223, -1.5852187229205115, -1.4862684109435635, -1.3845299251427141, -1.2816761495413382, -1.1793414621890534, -1.0790853422339046, -0.9823583176907374, -0.8904710520889436, -0.8045672855930303, -0.7256012464030682, -0.6543200337816377, -0.5912513477996839, -0.5366968060112745, -0.490730947129492, -0.4532058798771689, -0.4237613950582335, -0.40184022401650005, -0.38670800035937747, -0.37747736724325415, -0.37313557246584367, -0.3725748105409062, -0.3746245068659535, -0.3780846955787206, -0.3817596207617142, -0.3844906907829549, -0.3851879376892399, -0.382859177079281, -0.3766361276269276, -0.36579683174321564, -0.3497838176407162, -0.32821755576552425, -0.3009048863158069, -0.26784222622215476, -0.22921350017979167, -0.1853828776412769, -0.13688253262105773, -0.08439577231367927, -0.0287360006172326, 0.029177909355367394, 0.08834916653426039, 0.14773279370426898, 0.20626673979399957, 0.2629035362587647, 0.31664164634371744, 0.36655566304376863, 0.41182454029927684, 0.45175709166646544, 0.48581406013535605, 0.5136261501942924, 0.5350075164626497, 0.5499643196364447, 0.5586980871846063, 0.561603750004189, 0.5592623637167624, 0.552428660993638, 0.5420137157522162, 0.529063127863261, 0.5147312549055514, 0.5002521224986607, 0.4869077341541602, 0.47599457311353927, 0.46878914043472336, 0.46651340428581617, 0.47030104416765106, 0.481165360325833, 0.49996968319295354, 0.5274010611364792, 0.5639479284210335, 0.6098823609658602, 0.6652474174814846, 0.7298499405918218, 0.8032590596062592, 0.8848104969723077, 0.9736166375587002, 1.0685821773258444, 1.1684250291694933, 1.2717020322232149, 1.376838889951038, 1.4821636549753547, 1.5859429874593727, 1.6864203412943557, 1.7818551801727727, 1.8705622952010124, 1.9509502878295968, 2.0215582968089696, 2.0810900853078684, 2.1284446633984953, 2.1627427004221804, 2.1833480794065214, 2.1898840593608497, 2.182243638186123, 2.1605938460240397, 2.1253738428104456, 2.077286841090695, 2.017286022214638, 1.9465547572737236, 1.866481580080766, 1.7786304848093808, 1.6847072325482353, 1.58652244626226, 1.4859523501666334, 1.384898065445668, 1.2852444082267729, 1.1888191469267473, 1.097353664257954, 1.012445934613633, 0.9355266710995828, 0.8678294195337308, 0.8103652811869217, 0.7639028342323326, 0.7289536985491635, 0.7057640527584746, 0.6943122694780148, 0.6943126882623163, 0.7052253991226441, 0.7262717664732263, 0.7564552873089975, 0.7945872516918125, 0.8393165612541362, 0.8891629651355691, 0.9425528948624868, 0.9978570220216016, 1.0534286265205206, 1.1076418495930174, 1.158928914760456, 1.205815431410713, 1.2469529486560904, 1.2811480003069866, 1.3073869732770957, 1.3248562391990566, 1.3329571097670159, 1.3313153073018058, 1.3197847799763913, 1.2984458325988868, 1.2675976853043427, 1.2277457104385676, 1.1795837289073738, 1.123971868073094, 1.0619105909277646, 0.9945115981144452, 0.9229663781599363, 0.8485132352338546, 0.7724036565701407, 0.6958688926176534, 0.6200876118154138, 0.5461554589577337, 0.4750572923114387, 0.40764280137993447, 0.34460611637049143, 0.2864699143436595, 0.23357440841790167, 0.18607147829003545, 0.143924065969655, 0.10691082342380265, 0.07463586226451473, 0.0465433231456442, 0.021936357519358428, 1.946905840445738e-16], [-0.0, -0.02009304629816513, -0.03986267296876799, -0.06032655854743409, -0.08248646918756394, -0.10729665251818177, -0.13563345044748518, -0.1682669524996882, -0.20583545945349035, -0.24882345539461367, -0.2975436966022386, -0.35212392021533767, -0.41249855702464777, -0.47840570399710225, -0.5493894765080415, -0.6248077211556865, -0.7038449309769692, -0.7855300693923567, -0.8687588807136045, -0.952320146815983, -1.0349252446164399, -1.115240269994602, -1.1919199230321507, -1.2636422987626779, -1.3291436983537104, -1.387252568586963, -1.4369216929094524, -1.477257794883205, -1.5075477736970717, -1.5272808701195335, -1.5361661579659882, -1.5341448684749965, -1.5213971801877797, -1.4983432419292637, -1.465638337971911, -1.424162248930975, -1.3750030058156606, -1.3194353743749303, -1.2588945389549253, -1.1949455762338492, -1.1292494163900517, -1.06352607979905, -0.9995160489602763, -0.9389406862030151, -0.8834626365000577, -0.8346471606564413, -0.793925327030028, -0.7625599501392216, -0.7416151029388285, -0.7319299476534692, -0.7340975298066462, -0.7484490638845412, -0.7750441097342552, -0.813666899450201, -0.863828928533132, -0.9247777760635156, -0.9955119701433717, -1.0748015705468372, -1.161214003898764, -1.2531445611056697, -1.348850855259675, -1.4464904435445347, -1.5441607411050151, -1.6399403002390156, -1.7319304959666835, -1.8182966498064372, -1.8973076376635858, -1.9673730647624605, -2.0270771496142954, -2.075208538659788, -2.110785371501372, -2.1330750311370457, -2.1416081415191064, -2.1361865129567477, -2.1168848809805474, -2.084046432744007, -2.0382722632285004, -1.9804050478306656, -1.9115073548328931, -1.8328351474621456, -1.7458071376722126, -1.6519707497254843, -1.5529655287981354, -1.4504848863490778, -1.3462371085516363, -1.2419065659034503, -1.139116050983067, -1.0393911375554759, -0.9441273987454685, -0.8545612462330798, -0.7717450583134073, -0.6965271545868765, -0.6295370517781698, -0.5711763018155642, -0.5216150731731798, -0.4807944930830974, -0.4484346251310586, -0.4240478175124399, -0.4069570252935577, -0.39631858865730746, -0.39114884130141286, -0.3903538315476839, -0.3927613655476698, -0.3971545290052588, -0.4023058123432974, -0.40701095494348294, -0.4101216371545326, -0.4105761838013011, -0.4074274989959751, -0.39986752768558703, -0.38724763261382505, -0.36909438383678744, -0.3451203788411269, -0.31522984158930706, -0.2795188851498114, -0.2382704615007747, -0.1919441601032679, -0.14116115043115074, -0.0866846894383069, -0.029396729760059918, 0.029728734619120088, 0.0896548639964179, 0.14931292271089033, 0.20763415016755216, 0.2635816959591747, 0.31618175963399003, 0.3645530954511404, 0.4079340838467565, 0.4457066332658506, 0.4774162569441738, 0.5027877671159086, 0.5217361415145335, 0.5343722410953933, 0.5410031905127278, 0.5421273706858858, 0.5384241123094509, 0.5307383168722057, 0.520060364163311, 0.5075017890012664, 0.49426732187542405, 0.4816239854845409, 0.4708680192990077, 0.46329046519515804, 0.4601422873215652, 0.46259991758648034, 0.47173211397632286, 0.48846899236052255, 0.5135740441005147, 0.5476198827982294, 0.5909683755478138, 0.6437557092267074, 0.7058828232366797, 0.7770115096021145, 0.8565663426616585, 0.9437424571707149, 1.0375190490122952, 1.136678330477131, 1.2398295357530307, 1.3454374452535285, 1.4518547828878003, 1.5573577411970487, 1.660183807952673, 1.7585710063883249, 1.8507976212941215, 1.9352214657810571, 2.010317749119677, 2.0747146345939496, 2.1272256271485923, 2.1668780025562193, 2.1929365811769466, 2.204922257936732, 2.2026248232935783, 2.186109744713277, 2.155718721269972, 2.112063971944273, 2.056016367412463, 1.988687661970051, 1.911407223131177, 1.8256937879557824, 1.7332228940698635, 1.63579073675838, 1.5352752889015597, 1.4335955858101233, 1.332670120602018, 1.2343753165916063, 1.140505040728936, 1.0527320964976696, 0.9725725864891375, 0.9013539653027516, 0.8401875141882169, 0.7899458621318695, 0.7512460565131222, 0.7244385529952899, 0.70960235223356, 0.7065463637552205, 0.7148169285893685, 0.7337112855246842, 0.7622966248279254, 0.7994342412925391, 0.8438081788077896, 0.8939576541388834, 0.948312460804693, 1.0052304869095245, 1.0630364351158001, 1.1200608096945324, 1.174678235264013, 1.2253441943624948, 1.270629315773012, 1.3092504113544952, 1.340097544343303, 1.3622565145077021, 1.3750262625786462, 1.3779308251016407, 1.3707256080317411, 1.3533978896003698, 1.3261616066746333, 1.2894466204351942, 1.2438827932048184, 1.190279335301395, 1.1295999957319025, 1.0629347705610024, 0.9914688854313396, 0.9164498719725187, 0.8391536001899621, 0.7608501493768496, 0.6827703981946402, 0.6060741904325552, 0.5318208872524475, 0.4609430506601469, 0.3942239182332982, 0.3322792279589458, 0.2755438369817131, 0.2242634520698154, 0.1784916558765263, 0.13809227500464655, 0.10274699697208277, 0.07196800694582585, 0.04511528500747296, 0.021418084026580884, 1.9184393642454401e-16], [-0.0, -0.020172130583057526, -0.0405042806439822, -0.06201975376305619, -0.08570844216887243, -0.11249546962770088, -0.14321154102921438, -0.17856580173457376, -0.2191219456289249, -0.26527822763497344, -0.3172519362907713, -0.3750687673953541, -0.4385574135684352, -0.5073495500367445, -0.580885257445675, -0.6584237815257289, -0.7390593905850336, -0.8217419585696525, -0.9053017772141421, -0.9884779887560394, -1.0699499336696208, -1.1483706283738586, -1.2224015279396088, -1.2907476900274866, -1.352192439669841, -1.4056306405538928, -1.4500997070883608, -1.4848075420980944, -1.5091566562958576, -1.5227638160126191, -1.5254746728338535, -1.5173729501712634, -1.4987838944185008, -1.4702718389310243, -1.4326318741631665, -1.3868757632992919, -1.3342123860089046, -1.2760231299752431, -1.213832777178312, -1.149276546373877, -1.084064051928977, -1.0199410196644085, -0.9586496605736169, -0.9018886416898206, -0.8512736089498435, -0.8082992092048602, -0.7743035276804394, -0.7504358038857742, -0.7376282144647207, -0.7365724175428519, -0.7477014420096281, -0.7711773795633755, -0.8068852002791943, -0.8544328672620033, -0.913157776148082, -0.9821393944649794, -1.0602178278250916, -1.1460178982228075, -1.2379781877868772, -1.3343843824295334, -1.4334061468353505, -1.5331366776622082, -1.631634017748703, -1.7269631721015624, -1.8172380474972194, -1.9006622421331898, -1.9755677397904712, -2.040450613727544, -2.0940029177736244, -2.1351400340511035, -2.163022856181836, -2.1770743110386346, -2.176989858052919, -2.1627417494570653, -2.1345769840980915, -2.0930090379642095, -2.038803602647652, -1.9729587050201505, -1.8966797139688016, -1.8113498599144056, -1.7184969971137574, -1.619757424920869, -1.5168376501890228, -1.4114750172740662, -1.3053981536256967, -1.2002881772659024, -1.097741587662931, -0.9992357142961344, -0.9060975288028726, -0.8194765387567113, -0.7403223760745081, -0.6693675734382114, -0.6071158909486649, -0.5538364157861305, -0.5095635134158994, -0.4741025634382951, -0.4470412701533972, -0.4277662008364334, -0.41548407698865614, -0.40924722858907986, -0.4079825214554234, -0.41052298567055934, -0.4156413106384664, -0.4220843311984159, -0.4286076103117925, -0.43400922754901783, -0.43716190878499306, -0.4370426804385414, -0.4327593000002105, -0.4235728017080661, -0.40891559981151493, -0.3884047092583448, -0.36184977185658024, -0.3292557117399357, -0.2908199838569247, -0.24692451966355877, -0.19812261167179027, -0.14512110951288562, -0.08875842140495793, -0.02997892330359631, 0.03019552917426831, 0.09069621607468129, 0.15043947062716467, 0.20835904004316608, 0.2634380188731153, 0.3147394947685555, 0.36143507916663326, 0.4028305493711896, 0.4383879023921482, 0.4677432128642591, 0.4907197950826215, 0.5073362899521684, 0.5178094284070025, 0.522551360314049, 0.5221615785624572, 0.5174136083989901, 0.5092367685469762, 0.49869343978181935, 0.4869523951484109, 0.47525885087540154, 0.464901985586123, 0.4571807453485331, 0.4533688016323196, 0.4546795570432141, 0.4622320990176278, 0.4770189842811583, 0.49987669716572364, 0.531459563764382, 0.5722178228394996, 0.622380455349055, 0.6819432598308531, 0.7506625334923259, 0.8280545818257762, 0.9134011362837364, 1.0057606135483539, 1.1039850048297535, 1.2067420430344193, 1.3125421630553233, 1.4197696491598755, 1.5267172565263194, 1.6316235040906288, 1.7327117652869402, 1.8282302337940028, 1.9164918143196839, 1.9959129844965597, 2.0650506932867327, 2.122636403492116, 2.1676064500615273, 2.199127970362467, 2.2166197654227244, 2.2197675698699917, 2.2085333400375746, 2.183158311268158, 2.1441597233971255, 2.092321264133476, 2.0286774299083863, 1.9544921490760214, 1.8712321495829631, 1.7805356790221896, 1.6841772962828352, 1.5840295480798354, 1.4820224182005244, 1.3801014905178337, 1.2801857973939073, 1.1841263322887376, 1.093666189025292, 1.0104032506490424, 0.9357562891278124, 0.8709352547810761, 0.8169164333252942, 0.7744230312478194, 0.7439116197446092, 0.7255647268690382, 0.7192897202765559, 0.724723972609876, 0.7412461518198687, 0.7679933332073569, 0.8038834922407624, 0.8476428105985779, 0.8978371154697256, 0.9529066766320298, 1.0112035095119836, 1.0710302771245992, 1.1306798507970282, 1.1884745796387501, 1.2428043320108342, 1.292162408369153, 1.335178482853073, 1.370647809364842, 1.3975560246383831, 1.4150989934836156, 1.4226972671775564, 1.4200048617044791, 1.406912204831193, 1.3835432462940929, 1.3502468700586008, 1.3075828880990228, 1.2563030279605967, 1.1973274482265694, 1.131717423922998, 1.0606449352074643, 0.9853599651797065, 0.9071563645709113, 0.8273371711795473, 0.7471802795380513, 0.6679053412926976, 0.5906427396005397, 0.516405422488654, 0.4460643021069647, 0.38032783115114366, 0.3197262568900886, 0.26460093003419943, 0.21509891326293615, 0.17117299595701288, 0.13258708105913344, 0.09892677057971072, 0.06961484159810015, 0.043931178091114804, 0.02103660874657007, 1.9038664723107605e-16], [-0.0, -0.02041685729585867, -0.04148625082181759, -0.06422781502062755, -0.08961018493383029, -0.11852017516240912, -0.15173414880915811, -0.18989235333001211, -0.23347692409461077, -0.28279416223141035, -0.33796158338414234, -0.3989001111064851, -0.465331655871033, -0.5367821814184955, -0.6125902179420752, -0.6919206399877461, -0.7737833895402251, -0.8570566950425698, -0.9405142183619467, -1.0228554569918624, -1.1027386407515904, -1.1788152931719336, -1.2497655794366074, -1.31433353645731, -1.3713612771253705, -1.4198212801628516, -1.4588459188771756, -1.4877534455281867, -1.5060697314276383, -1.5135451642880287, -1.5101662212467972, -1.4961613655471648, -1.4720010538706625, -1.4383917863581772, -1.3962642788380837, -1.3467559830441838, -1.2911883220178746, -1.2310391409247194, -1.167910994852232, -1.103496001752266, -1.0395380778654175, -0.9777934424591475, -0.9199903267503957, -0.8677888472186946, -0.8227420054561276, -0.7862587551313258, -0.7595700320306336, -0.7436985765141466, -0.7394332906648987, -0.7473087669991216, -0.7675905043819958, -0.8002661926870565, -0.8450433039996508, -0.9013530782875532, -0.9683608390921852, -1.04498242364425, -1.1299063655642587, -1.2216213305408599, -1.3184481794526715, -1.4185759223891823, -1.520100733646845, -1.6210671243097996, -1.719510317267639, -1.8134988407392918, -1.901176351265796, -1.9808017158282618, -2.0507864247813052, -2.1097284716362443, -2.1564419208054106, -2.189981488146625, -2.2096615789854694, -2.2150693613118286, -2.2060715947934906, -2.1828150856313453, -2.1457207894511083, -2.095471735674427, -2.0329950934536773, -1.9594388377233873, -1.8761436008559471, -1.784610407737375, -1.6864650870906146, -1.5834202272897755, -1.4772355989346722, -1.3696779978260094, -1.2624814699929456, -1.1573088649475114, -1.0557156248252602, -0.9591166565356549, -0.8687570530476716, -0.7856873305359648, -0.7107437328210174, -0.644534026250452, -0.5874290701005623, -0.5395603031745063, -0.5008231401326866, -0.4708861248680073, -0.449205546558376, -0.4350450903952293, -0.42749997269553786, -0.4255249021621857, -0.42796511810623505, -0.43358968469786313, -0.4411261695006274, -0.4492958058702677, -0.45684823291342536, -0.462594923681821, -0.4654404516301579, -0.4644108060393281, -0.4586780475164014, -0.4475806927540195, -0.4306393309495928, -0.40756709975857175, -0.37827478319243873, -0.34287043405406603, -0.3016535657767979, -0.25510409929633365, -0.20386638627596482, -0.1487287571962092, -0.09059915829689169, -0.030477542207752107, 0.030574239222617133, 0.09146422700165002, 0.15110297559635746, 0.20843612422133956, 0.26247604204932046, 0.31233169419054696, 0.3572359208286477, 0.3965693882290112, 0.4298805557813067, 0.45690110564775777, 0.4775563983819309, 0.49197064611341795, 0.5004666313258225, 0.5035599404430962, 0.501947823813139, 0.49649293363450886, 0.4882023253646378, 0.4782022327740114, 0.467709238898057, 0.45799856182530896, 0.4503702530661401, 0.44611416513522406, 0.4464745824126221, 0.4526154243176601, 0.46558692189169976, 0.48629463816834245, 0.5154716499103488, 0.5536546346628556, 0.6011645143867147, 0.6580921974479329, 0.7242898371273415, 0.7993678901150174, 0.8826981159859542, 0.9734225119373003, 1.070468029737131, 1.1725667775476694, 1.278281271633054, 1.386034175376199, 1.4941418487039648, 1.6008509328249259, 1.7043771155972591, 1.8029451638882144, 1.8948292724781806, 1.9783927653748759, 2.0521261952398326, 2.1146829198158064, 2.1649112900280945, 2.201882661505479, 2.2249145377923583, 2.2335882671844316, 2.227760843174066, 2.207570497837507, 2.1734359247526114, 2.1260491196219933, 2.06636197900143, 1.9955669466860622, 1.91507213974855, 1.826471518475835, 1.7315107832840568, 1.632049784200456, 1.5300223121809335, 1.4273942043366648, 1.3261207355375868, 1.2281042858580795, 1.1351532665160102, 1.0489432564997105, 0.9709812487255498, 0.902573829629091, 0.8448000214008959, 0.7984894039521321, 0.7642060068789032, 0.7422383232887744, 0.7325956507413707, 0.7350108133175838, 0.7489491666590639, 0.7736236384204171, 0.808015413587192, 0.8508997410077495, 0.900876217493258, 0.9564028018575756, 1.0158327257997855, 1.0774534036197563, 1.139526399935705, 1.2003274948296587, 1.2581858896006337, 1.3115216233942661, 1.358880320665349, 1.398964460424664, 1.4306604487079928, 1.4530608833914034, 1.465481522650223, 1.4674726019549522, 1.458824286175615, 1.439566189593628, 1.4099610437599177, 1.3704927375376068, 1.3218490917520196, 1.2648998592293772, 1.2006705564775837, 1.1303128330148553, 1.0550721659489741, 0.9762537288739571, 0.8951873240104927, 0.8131922838421004, 0.7315432429260625, 0.6514376522950059, 0.5739658586867665, 0.5000845000690545, 0.4305938793969041, 0.3661198725573428, 0.30710080672801676, 0.25377961495650025, 0.20620143497030544, 0.1642166785505637, 0.12748945583443466, 0.09551110024549762, 0.06761840789336368, 0.0430160835653226, 0.020802776927534305, 1.9040217631105167e-16], [-0.0, -0.020832544703979678, -0.04281471799674584, -0.06695303249886644, -0.0941854897873894, -0.12535158325253723, -0.16116496506734865, -0.20218952053413025, -0.24881950536362193, -0.30126429678322786, -0.3595381903999203, -0.4234555444641619, -0.4926314348833479, -0.5664878415117148, -0.6442652425107296, -0.7250393525691059, -0.8077426060700778, -0.8911898613171391, -0.9741076898601821, -1.0551665186647676, -1.1330148148095145, -1.20631444459822, -1.2737763029476155, -1.334195295628903, -1.386483766803756, -1.4297024971269403, -1.463088452736573, -1.4860785414107103, -1.4983287272014005, -1.499727966650344, -1.4904065555061043, -1.4707386116079915, -1.4413385639033809, -1.403051665854558, -1.3569387000923454, -1.3042551863940028, -1.2464255432859224, -1.1850127813456968, -1.1216844204034724, -1.0581754204500882, -0.996248994683228, -0.9376562307609808, -0.8840954814975953, -0.8371724979942956, -0.7983622661897579, -0.7689734722675337, -0.7501164640791617, -0.7426754961016336, -0.7472859463443815, -0.7643170774344861, -0.7938607836438023, -0.8357266240379602, -0.8894432926621872, -0.9542665233633936, -1.0291932732165734, -1.1129818783230008, -1.2041777326442593, -1.3011439080255947, -1.4020960148834116, -1.5051405010870955, -1.6083155038492187, -1.7096333079742552, -1.8071234251098123, -1.8988752936430606, -1.9830796079569164, -2.058067318683731, -2.1223454015634204, -2.1746285701591854, -2.213866205107116, -2.239263887394193, -2.2502990525641864, -2.24673042358096, -2.2286010288929816, -2.196234765409316, -2.1502266198801223, -2.091426812827071, -2.020919273025533, -1.9399949841068154, -1.8501208648879977, -1.7529049486491768, -1.6500587112705776, -1.5433574618918229, -1.4345997510574913, -1.3255667692162083, -1.2179827025725534, -1.1134769838644119, -1.0135493234466921, -0.9195383324576824, -0.8325944567050522, -0.753657829590467, -0.6834415276704803, -0.6224205764519086, -0.5708269101395118, -0.5286503408770796, -0.4956454442326914, -0.4713441219648517, -0.4550734640728827, -0.445978403213437, -0.4430485389266331, -0.44514840959433893, -0.45105040907613814, -0.4594694844949125, -0.46909871311783724, -0.47864484059348555, -0.4868628702831948, -0.4925888238071206, -0.4947698453826661, -0.49249089568489723, -0.4849973729091005, -0.47171310710143627, -0.45225329587326674, -0.42643208221846546, -0.3942646149410527, -0.35596357562722, -0.3119302995290997, -0.26274075753906717, -0.2091267990901774, -0.15195317797045207, -0.09219099160389937, -0.030888256590983994, 0.03086158310972871, 0.09195236589336019, 0.15129825940780578, 0.2078662553227375, 0.2607072368859622, 0.3089847809062008, 0.35200091408373785, 0.38921812198406464, 0.4202770054381995, 0.4450090913229457, 0.4634444296946501, 0.4758137439647334, 0.48254504181142543, 0.4842547382549705, 0.48173348514565656, 0.4759270396068392, 0.4679126342290027, 0.4588714307136592, 0.4500577431852433, 0.44276580484995476, 0.43829491983055197, 0.4379138890744448, 0.44282562397319625, 0.45413286305624306, 0.4728058857167399, 0.49965307285829114, 0.5352950986511779, 0.5801434518315488, 0.634383881247544, 0.6979652411862204, 0.7705940803290756, 0.8517351772251616, 0.9406180784208422, 1.0362495464778685, 1.1374316777422995, 1.2427853075617068, 1.350778187232739, 1.4597572956305953, 1.5679845422711913, 1.6736750301611154, 1.7750369784410962, 1.8703123582753427, 1.9578172718966906, 2.035981104835177, 2.1033835052007337, 2.158788290941142, 2.2011734551615407, 2.2297565292327257, 2.2440146713868043, 2.2436989721995815, 2.22884260479835, 2.199762593502635, 2.1570551263588627, 2.1015844909737633, 2.034465865433543, 1.9570423431981647, 1.870856709090762, 1.7776186094830757, 1.679167870428967, 1.5774348101129683, 1.4743984642931152, 1.3720436936570357, 1.2723181689472756, 1.1770902326866033, 1.088108615272596, 1.0069649386288038, 0.9350598735876411, 0.8735737293772563, 0.8234421471387467, 0.7853374469143367, 0.7596560420158283, 0.746512189417014, 0.7457381933614133, 0.7568910254330006, 0.7792651716552463, 0.8119113694805286, 0.8536607583985623, 0.903153840704984, 0.958873536807509, 1.0191815250118124, 1.0823569812870772, 1.1466367818317784, 1.2102562015754499, 1.2714891357250413, 1.3286868891757215, 1.380314619550495, 1.4249845827345045, 1.4614854134085067, 1.488806775137309, 1.5061588324597446, 1.5129861281972825, 1.5089755895771901, 1.4940585332516096, 1.4684066882408406, 1.4324224035399058, 1.3867233499433638, 1.3321221600358266, 1.2696015729531402, 1.2002857584295643, 1.1254085851711608, 1.0462796695349645, 0.9642490901405146, 0.880671681222658, 0.7968718216426763, 0.7141096174769345, 0.6335493345440324, 0.5562308742214094, 0.4830450030839201, 0.4147129464065269, 0.35177083998654696, 0.2945594070075331, 0.2432190900369424, 0.19769072619185704, 0.15772170962130688, 0.12287744338178776, 0.09255774611647774, 0.06601775114034256, 0.04239271980930091, 0.02072609033126682, 1.9196017496292266e-16], [-0.0, -0.021422836501935733, -0.04449234184807285, -0.07019238696580545, -0.09942106417747588, -0.1329617997118059, -0.1714575906241621, -0.21538906837061553, -0.2650569925321341, -0.3205696638071727, -0.3818356182717323, -0.44856182825688956, -0.5202574924687083, -0.5962433527843625, -0.6756663311770574, -0.7575191411005248, -0.8406643969333518, -0.9238626260699213, -1.0058034839841348, -1.0851393857544775, -1.1605207003611135, -1.230631608294847, -1.294225699867337, -1.350160391730468, -1.3974292625670626, -1.4351914551878326, -1.4627973602711812, -1.4798098850781225, -1.4860207165234665, -1.4814611093928023, -1.466406864279936, -1.4413773026831613, -1.4071281951093284, -1.3646387483139577, -1.3150929062209928, -1.259855361921589, -1.2004428118824977, -1.1384911047536026, -1.0757190429057535, -1.013889682386496, -0.9547700441294285, -0.9000901942698013, -0.8515026731250712, -0.8105432501888888, -0.7785939563436968, -0.7568492949950474, -0.7462864621210097, -0.7476403130133153, -0.7613837029717873, -0.7877137030629716, -0.8265440533193505, -0.8775040678027953, -0.9399440523820161, -1.0129471406185275, -1.0953472996097655, -1.1857531097495564, -1.282576783748376, -1.384067764297969, -1.48835012954868, -1.5934629437912724, -1.6974026196464838, -1.7981663094068452, -1.893795318141096, -1.9824175303766933, -2.062287865643511, -2.1318258253200164, -2.189649262920718, -2.2346036004979255, -2.265785822989074, -2.282562707456471, -2.2845828821821317, -2.2717824581267303, -2.2443841287369484, -2.2028897897467297, -2.148066884671962, -2.0809288303952282, -2.0027100169636958, -1.914836003089792, -1.8188896407695065, -1.7165739562194826, -1.6096726877329035, -1.500009432322188, -1.3894063809568207, -1.279643626196148, -1.1724200060297076, -1.0693164043309702, -0.9717623626405805, -0.8810067717047263, -0.7980933064907816, -0.7238411479229689, -0.6588314013466982, -0.6033994790712293, -0.5576335658117799, -0.5213791351469071, -0.49424933596295284, -0.47564092396577834, -0.46475527825267016, -0.4606239199799545, -0.46213784235062905, -0.4680798711142727, -0.47715920470308193, -0.48804723470565803, -0.4994137217433137, -0.509962399530786, -0.5184651009586131, -0.5237935438294603, -0.5249479792494477, -0.5210819909148088, -0.5115228364462807, -0.49578683987215827, -0.47358947433710497, -0.4448499128118342, -0.4096899684791122, -0.36842749192880214, -0.3215644356293708, -0.2697699337332121, -0.2138588736451153, -0.1547665516985518, -0.09352010582136945, -0.03120750069799139, 0.031055096430969015, 0.0921566701242772, 0.15102454357636497, 0.20665650485428463, 0.25815100699242727, 0.3047346261849367, 0.3457860330864988, 0.38085582220397984, 0.40968165126276057, 0.43219826356334795, 0.44854209864666467, 0.45905033671717926, 0.4642543666888155, 0.464867812764946, 0.4617693964664166, 0.4559810463785766, 0.4486417931599889, 0.44097809935116045, 0.4342713693790286, 0.4298234624112728, 0.4289210873750535, 0.43279999403270203, 0.44260988556810893, 0.45938096632328057, 0.4839930033604952, 0.5171477232176063, 0.5593452869387061, 0.6108654890932026, 0.6717542124180305, 0.7418155417270313, 0.8206098019787084, 0.9074576393041556, 1.0014501139871737, 1.1014646245753668, 1.2061863362100544, 1.3141346475356341, 1.4236941026534058, 1.5331490407260762, 1.6407211788837284, 1.7446092464825131, 1.8430297325031628, 1.9342577744033889, 2.016667206951728, 2.088768803783054, 2.1492457823472995, 2.1969857037086995, 2.2311079808622045, 2.2509863109060526, 2.2562654651019254, 2.2468720037002434, 2.2230186261896936, 2.1852020188547097, 2.1341942165128054, 2.071027650278161, 1.9969742043781116, 1.9135187487424639, 1.8223277467806236, 1.7252136562120526, 1.624095942123261, 1.5209596031084587, 1.4178121714096599, 1.316640184932815, 1.2193661419718322, 1.1278069381023372, 1.0436347492865368, 0.9683412666242366, 0.903206107824145, 0.8492701303176586, 0.8073142534417119, 0.7778442651487559, 0.7610819454838624, 0.7569626880976403, 0.7651396460229186, 0.7849942726126478, 0.8156529766992161, 0.8560094663846005, 0.9047522219186378, 0.9603964181146605, 1.0213195135860629, 1.0857996402448538, 1.1520558639858154, 1.2182893477622379, 1.2827244322531721, 1.3436486573537127, 1.3994507795240905, 1.4486558947591588, 1.489956853173499, 1.5222412469980777, 1.5446133667315654, 1.5564106474455968, 1.5572142656227093, 1.5468536929550836, 1.5254051636163102, 1.4931841619099941, 1.4507321841722096, 1.3987981687265192, 1.3383151171113519, 1.2703725455389945, 1.1961855047699705, 1.117060986880112, 1.0343625968204926, 0.9494744038075088, 0.8637649015754146, 0.778551997099096, 0.6950699148591936, 0.6144388489599498, 0.5376381198614769, 0.4654834981092054, 0.3986092466587042, 0.33745530903552184, 0.2822599358042111, 0.23305790007180974, 0.18968430761250357, 0.15178386234591854, 0.11882530699371534, 0.09012062533697399, 0.06484846996642614, 0.0420811708490542, 0.020814588163810818, 1.9511555178739186e-16], [-0.0, -0.02218963880608415, -0.046518226964157354, -0.07393750000883288, -0.1052965595567347, -0.1413143762933223, -0.18255585920376796, -0.22941214516344952, -0.282085653869676, -0.3405803298216375, -0.40469735875583884, -0.4740365040148381, -0.5480030623582842, -0.6258202924123404, -0.7065470260043988, -0.7891000366719115, -0.8722806141232039, -0.9548046815623611, -1.0353356974292336, -1.112519506698795, -1.1850202514088473, -1.251556416996917, -1.310936081222562, -1.3620904462447345, -1.4041047715390396, -1.4362458849160809, -1.457985529514986, -1.4690189043421453, -1.469277872269478, -1.4589384395434857, -1.4384222515796714, -1.4083919976491237, -1.3697407683428036, -1.3235755606673765, -1.2711952725271574, -1.2140636675141672, -1.1537779188816355, -1.0920334551040536, -1.0305859256688459, -0.9712111822623366, -0.9156642253505088, -0.8656380978900754, -0.8227237156825096, -0.7883716074385922, -0.7638564972863647, -0.7502455991545125, -0.7483714076871968, -0.7588096661185177, -0.781863070360885, -0.8175511333688176, -0.8656064879047439, -0.9254777527020783, -0.9963389304208183, -1.0771051495400121, -1.1664544102436618, -1.2628548501480867, -1.3645969129161946, -1.4698296846577883, -1.5766005624187323, -1.68289733848107, -1.7866917256082784, -1.8859833132131938, -1.978842933567632, -2.063454430882647, -2.138153864037243, -2.2014652349972845, -2.2521319180512855, -2.2891430678679576, -2.3117544045395637, -2.31950290828223, -2.312215102035225, -2.2900087532843374, -2.2532879832959747, -2.2027319287660316, -2.1392772538429536, -2.0640949558587054, -1.9785620423655823, -1.8842287769793935, -1.7827822941750264, -1.6760074661021254, -1.5657459657068333, -1.453854508518197, -1.3421632695133079, -1.232435461234368, -1.1263290251133793, -1.0253613306744018, -0.9308776984053014, -0.8440244636249913, -0.7657271831022884, -0.6966744564090674, -0.6373076932585973, -0.5878170098985145, -0.5481432856820445, -0.517986259000857, -0.49681839358954305, -0.48390410546461715, -0.47832381090656023, -0.47900214012022163, -0.4847395623477986, -0.49424658866375815, -0.5061796603704257, -0.5191777952214044, -0.5318990514455146, -0.5430558809583442, -0.551448477872105, -0.555995285506189, -0.5557599030621101, -0.549973729939894, -0.5380537988524294, -0.5196153755485436, -0.4944790398602801, -0.46267210646879336, -0.42442439059546755, -0.38015847005564934, -0.3304747370667953, -0.2761316672973287, -0.21802185649570902, -0.1571444835550738, -0.09457495031533257, -0.03143252048103656, 0.03115316907176413, 0.09207582289010827, 0.15028552046388194, 0.20482017972420133, 0.2548346024401454, 0.2996263161008552, 0.338657509753251, 0.37157246226998386, 0.39820997809544256, 0.4186104747137443, 0.4330175046360515, 0.44187363911129474, 0.445810787370304, 0.4456351703052196, 0.44230730738463786, 0.4369175067575587, 0.43065746756818574, 0.4247887074507371, 0.42060861433550745, 0.419414987854425, 0.4224699800639997, 0.43096436672633914, 0.4459830783972541, 0.4684728950451859, 0.49921315943577793, 0.5387902942105751, 0.5875768171588153, 0.6457154408293547, 0.7131087190089893, 0.7894145667440756, 0.8740478358567004, 0.9661879778857944, 1.0647926747886995, 1.1686171683386521, 1.2762388756713254, 1.3860867444533327, 1.4964746800246589, 1.6056382716496216, 1.7117739583559797, 1.8130797089525117, 1.9077962473865127, 1.9942478347768502, 2.070881623797005, 2.1363046295521366, 2.1893174130639133, 2.228943647736738, 2.2544548339659736, 2.2653895400913036, 2.26156667647205, 2.2430924504540775, 2.2103607999884716, 2.16404725900228, 2.1050963645270504, 2.0347028702336036, 1.9542871796253551, 1.8654655510740465, 1.7700157527429397, 1.6698389551509367, 1.5669187399992763, 1.4632781736820821, 1.3609359409197554, 1.261862557033866, 1.167937675953529, 1.0809094851359795, 1.002357128826446, 0.933657028687599, 0.8759538775630238, 0.830136970279239, 0.7968224076679704, 0.7763415695229431, 0.7687361024217527, 0.7737595128972874, 0.7908852991246863, 0.8193213989309064, 0.8580305823146939, 0.9057562764205027, 0.961053183441158, 1.0223219403140795, 1.087846976013724, 1.1558366499588364, 1.2244647052629791, 1.2919120444211798, 1.3564078331215432, 1.4162689601774416, 1.4699369274780487, 1.516011312156, 1.5532790321252488, 1.5807387534989992, 1.597619901455557, 1.6033958717973267, 1.5977911853570568, 1.5807824779377435, 1.5525933708890904, 1.513683417946672, 1.464731468868203, 1.406613926120331, 1.340378494061668, 1.2672141277140736, 1.1884179776889654, 1.105360196971066, 1.0194475224017705, 0.9320865677436045, 0.8446477656196911, 0.7584308724717536, 0.6746329046196828, 0.5943193057587199, 0.5183990585605164, 0.44760434771051877, 0.382475261413487, 0.3233498861990398, 0.2703600091205677, 0.22343249573361496, 0.1822962652532777, 0.14649463974073282, 0.11540270570730483, 0.08824919764410952, 0.06414229693489532, 0.04209863931260488, 0.02107474200061104, 1.999076828119418e-16], [-0.0, -0.023133074688004362, -0.04888787902788743, -0.07817464007496097, -0.11178467484690131, -0.15036455680567615, -0.19439426743686036, -0.24416993212157856, -0.29979162074284377, -0.3611565622184292, -0.4279579817261844, -0.4996896233378557, -0.5756558728014656, -0.6549872490595273, -0.7366608924681485, -0.8195255461628258, -0.9023304079482677, -0.9837571265112812, -1.062454130321813, -1.1370724125003482, -1.2063018518851563, -1.2689071306752384, -1.3237623129195932, -1.369883175741419, -1.4064564359035305, -1.4328650869354194, -1.448709154799311, -1.4538212907113557, -1.4482767455419108, -1.4323974080982997, -1.4067497361387997, -1.3721365605485805, -1.329582895963761, -1.2803160414550676, -1.2257403989288629, -1.167407571068289, -1.1069824215568658, -1.046205884957261, -0.9868553993129212, -0.9307038991167594, -0.879478348084343, -0.8348188090744041, -0.7982390420006273, -0.7710895897614646, -0.7545242577653258, -0.7494708158179554, -0.7566066537917747, -0.7763400069476555, -0.8087972358145632, -0.8538165023225216, -0.910948031906368, -0.9794609942497278, -1.0583568770481633, -1.1463890715009484, -1.2420882389960977, -1.3437928892835653, -1.449684474743971, -1.5578261962344098, -1.666204626105112, -1.77277318553741, -1.875496468037714, -1.9723943798502674, -2.06158507174807, -2.1413256650430355, -2.210049827037046, -2.2664013262403593, -2.3092627936824766, -2.33777903119172, -2.351374337828123, -2.349763468541, -2.3329559911014437, -2.301253964725598, -2.255243022721466, -2.195777098090738, -2.123957181488431, -2.0411046416323892, -1.9487297657509, -1.848496288877583, -1.7421827730684354, -1.6316417687171507, -1.518757738393879, -1.4054047479073288, -1.2934049290586198, -1.1844886938895467, -1.0802576318014596, -0.982150949990108, -0.8914162260157401, -0.8090851313213733, -0.7359546588894564, -0.6725742501312362, -0.6192390689786753, -0.5759895186558022, -0.5426169425295734, -0.5186752985950603, -0.5034984512872367, -0.4962225880264674, -0.4958131445452723, -0.5010955156302349, -0.5107887390616859, -0.5235412723943831, -0.5379679364237584, -0.5526870767934636, -0.566356996703901, -0.5777107389644903, -0.5855883439872489, -0.588965780463811, -0.5869798355779352, -0.5789483593607473, -0.5643853804385986, -0.5430107448278868, -0.5147540721821837, -0.47975297137534634, -0.43834560577762505, -0.3910578442979374, -0.33858537354660156, -0.28177127580680356, -0.22157969363228608, -0.15906630189020773, -0.09534638942778706, -0.03156141321585436, 0.031155073709376827, 0.09171120388411375, 0.14908937825597102, 0.20237677341795254, 0.2507929505281066, 0.2937138184555375, 0.33069129819182647, 0.3614681469234313, 0.3859875255593115, 0.40439702977759706, 0.4170470483486057, 0.424483459972175, 0.427434827400091, 0.4267943914592409, 0.4235973040965659, 0.4189936652620818, 0.4142180401273836, 0.4105562279484732, 0.40931012938711064, 0.41176161334944356, 0.4191363159595028, 0.43256831230061266, 0.4530665857607529, 0.48148418053576475, 0.5184908609930958, 0.5645500186615522, 0.6199004656028138, 0.6845436343327108, 0.7582365722087738, 0.8404909755468926, 0.9305783592025033, 1.0275413046583948, 1.1302105775970699, 1.2372277582887594, 1.347072888583649, 1.4580965113525761, 1.5685553650890698, 1.6766509009199118, 1.7805697138947678, 1.8785249270672086, 1.9687975369289707, 2.0497767230295407, 2.119998143320241, 2.178179279518998, 2.223250962616722, 2.2543842959869136, 2.271012300330476, 2.2728457283195507, 2.2598826343098226, 2.2324114325359203, 2.191007332190762, 2.136522195942548, 2.0700680259053064, 1.9929944340046548, 1.9068605983318012, 1.8134023399151817, 1.71449507210822, 1.6121134746056505, 1.508288823511333, 1.4050649659366488, 1.304453960906122, 1.2083924170629758, 1.1186995415806116, 1.037037874182568, 0.9648776162364767, 0.903465379074616, 0.853798070097059, 0.8166025124092111, 0.7923212567302012, 0.7811048964249501, 0.7828110413677555, 0.797009947720858, 0.8229966424722476, 0.859809227574002, 0.9062529024991998, 0.9609291095357777, 1.0222690864159663, 1.0885710088303997, 1.1580398234484561, 1.2288288122155848, 1.2990818923332161, 1.3669756442770395, 1.4307600727056586, 1.4887971417793435, 1.5395961862805982, 1.5818453814662419, 1.614438555716359, 1.6364967482317032, 1.647384046304558, 1.646717379745004, 1.6343701003212951, 1.6104693278356783, 1.5753871978937062, 1.529726295740748, 1.4742997020497566, 1.4101062067670278, 1.3383013628637774, 1.2601651502735305, 1.1770670990282806, 1.0904297777453262, 1.0016915878082293, 0.9122698140513483, 0.8235248693127432, 0.7367266332767225, 0.6530237265828609, 0.573416480791172, 0.4987342655420174, 0.42961771868124954, 0.36650629618704067, 0.3096314197157182, 0.25901535400783077, 0.2144757979500647, 0.1756360255275421, 0.1419402699511175, 0.11267390951174347, 0.08698789059449999, 0.06392671487821777, 0.04245922678000121, 0.021511365963175853, 2.0635977570917994e-16], [-0.0, -0.024251456895742988, -0.05159319827170661, -0.08288478477801614, -0.1188513340978279, -0.1600596133193921, -0.20689850790758005, -0.259564405150737, -0.3180519024562773, -0.3821501126574749, -0.4514446930723956, -0.5253255761058269, -0.603000230480187, -0.6835121374928531, -0.7657640296989804, -0.8485453135952895, -0.9305629864391816, -1.010475263129446, -1.086927054521022, -1.158586385578218, -1.2241808117808424, -1.2825328860039589, -1.3325937459171064, -1.373473933413689, -1.4044706217136935, -1.4250905110412941, -1.4350677580896916, -1.4343764252945208, -1.4232370702721335, -1.4021172403237914, -1.3717257880826457, -1.3330010784354571, -1.28709330995311, -1.2353413223956675, -1.1792444017119759, -1.1204297218250054, -1.0606161751672287, -1.0015754385593456, -0.9450911952062934, -0.8929174854134783, -0.8467371867498074, -0.8081216280322676, -0.7784923205129158, -0.7590857444554239, -0.7509220609351438, -0.7547785287982034, -0.771168297419818, -0.800325119840256, -0.8421943910766552, -0.8964307663010014, -0.9624024567892268, -1.0392021419036286, -1.125664276766167, -1.2203884215890741, -1.321768073611015, -1.4280243497927194, -1.537243751110277, -1.6474191403253613, -1.7564929869401813, -1.8624018775837423, -1.9631212586931703, -2.056709371827368, -2.141349360451393, -2.215388570115295, -2.2773741305770523, -2.326083996964818, -2.360552735381897, -2.3800914637887, -2.38430149849031, -2.3730814067152983, -2.3466273229297507, -2.3054265468608017, -2.25024460080153, -2.1821060787508455, -2.1022697665416876, -2.012198646771771, -1.9135255218131988, -1.8080150895580058, -1.697523387420082, -1.5839555785324901, -1.4692230886780868, -1.3552011124844765, -1.243687492620887, -1.136363936583716, -1.0347604731776507, -0.9402239665900315, -0.8538914021504581, -0.7766685370762387, -0.709214374752053, -0.6519317757417149, -0.6049643663984663, -0.5681997504095411, -0.5412788737332209, -0.5236112429897873, -0.5143955551593529, -0.512645165915975, -0.5172177082868693, -0.5268480753895876, -0.5401839031437292, -0.5558226329475046, -0.5723492016731822, -0.5883733977065824, -0.6025659372716403, -0.6136923544766638, -0.6206438603388968, -0.6224644088701343, -0.6183733099981658, -0.607782847048851, -0.5903104877112443, -0.5657854185167601, -0.534249280303304, -0.49595113217390724, -0.4513368203044503, -0.40103307184947823, -0.3458267695112889, -0.28663998566732274, -0.2245014631919612, -0.16051532054060297, -0.09582782901684361, -0.031593158654927754, 0.031060985392293315, 0.09106691229518368, 0.14744877909717388, 0.19935185174716483, 0.24606840409150546, 0.287059552709456, 0.32197243097362516, 0.35065222663503903, 0.3731487405115594, 0.38971726612555235, 0.400813737790848, 0.4070842439504073, 0.40934914973051234, 0.40858221397047545, 0.40588521781825043, 0.4024587409953654, 0.39956982499048493, 0.3985173470955031, 0.4005959931679073, 0.4070597586213748, 0.41908592530403765, 0.4377404560986918, 0.4639457193497369, 0.49845140226552787, 0.5418093975227567, 0.5943533522247062, 0.6561834554587753, 0.7271569127322066, 0.8068844156926407, 0.8947327672200084, 0.9898336688850273, 1.0910985237111566, 1.1972389559879617, 1.3067926053385288, 1.4181536179593606, 1.5296071372988171, 1.6393669924603231, 1.7456156979414779, 1.846545815111616, 1.940401685721228, 2.0255205317925675, 2.100371924931463, 2.163594661287822, 2.2140301353332736, 2.250751384986861, 2.273087080517424, 2.2806398476870813, 2.2732984489260737, 2.2512434917161785, 2.21494648727622, 2.16516224134245, 2.102914718448844, 2.0294766777405013, 1.9463435281675021, 1.855201990241167, 1.7578942769752093, 1.656378615105944, 1.5526870165248505, 1.4488812768804853, 1.3470082218643908, 1.2490552407105724, 1.1569071404344233, 1.0723053234511444, 0.9968102361915869, 0.9317679585111398, 0.8782817049599438, 0.837188891756151, 0.8090442904364306, 0.7941096438894841, 0.7923499663511168, 0.8034365897101877, 0.8267568580225266, 0.8614302143606787, 0.9063302728775202, 0.9601123279041615, 1.0212456244561237, 1.0880496037670448, 1.1587332460739221, 1.2314365630301647, 1.3042732454791441, 1.37537344996477, 1.4429257097720898, 1.5052169833553597, 1.5606699039918417, 1.6078763680793418, 1.6456266938013964, 1.6729336945369482, 1.6890511395650325, 1.6934862151050853, 1.686005748039711, 1.6666361090777386, 1.6356568678022878, 1.5935884251594288, 1.5411739956985204, 1.4793564486622008, 1.4092506404845353, 1.3321119783709299, 1.2493020427965493, 1.1622521638419845, 1.072425890685862, 0.9812813142619553, 0.890234199624644, 0.8006228571158016, 0.7136756307508397, 0.6304818096828938, 0.551966676047221, 0.47887129231440223, 0.41173750630882505, 0.35089851546178624, 0.29647518713544996, 0.2483781826423102, 0.20631578266914488, 0.16980716498122053, 0.13820074523562506, 0.11069706200088263, 0.0863755709291173, 0.06422461337735835, 0.04317374412913415, 0.02212754324871162, 2.144783963361557e-16], [-0.0, -0.02554127922068466, -0.05462251061437802, -0.0880437393259272, -0.1264559371300837, -0.17033926970952776, -0.21998610051228992, -0.27548920180720476, -0.3367355082730256, -0.4034056043818565, -0.47497898761925983, -0.5507449990024363, -0.6298191642322765, -0.7111645469045536, -0.7936175831172014, -0.8759177479085516, -0.9567403012821295, -1.0347312777498643, -1.1085438205198153, -1.1768749213047036, -1.2385016103051047, -1.2923156487040783, -1.337355807869741, -1.3728368746665631, -1.3981745995062973, -1.4130059011526777, -1.4172037574493137, -1.410886341237269, -1.3944201025576328, -1.3684166482851987, -1.3337234248891603, -1.2914083652221247, -1.24273881223119, -1.189155177466712, -1.1322399266044056, -1.0736826045184025, -1.015241715712431, -0.9587043595141344, -0.9058445812272665, -0.8583814388168822, -0.817937798648881, -0.7860008628949458, -0.7638853956382524, -0.7527005552757643, -0.7533211589013316, -0.766364101919798, -0.792170535644921, -0.8307942699820802, -0.8819967207776153, -0.9452485656151197, -1.0197381115493351, -1.104386217401028, -1.1978674557213511, -1.2986370492249868, -1.4049629770686092, -1.514962521232981, -1.626642415523808, -1.7379416719858647, -1.8467760939855862, -1.9510834434760436, -2.0488682130500306, -2.1382449617383084, -2.2174792069303675, -2.2850249224784154, -2.33955777359287, -2.3800033205903612, -2.405559543442392, -2.415713174473463, -2.4102494741711555, -2.389255241300211, -2.35311500955106, -2.302500544879025, -2.2383539165627306, -2.161864566966962, -2.0744409463470257, -1.9776774063536058, -1.8733171561115625, -1.7632121751999685, -1.6492810463878598, -1.5334657159576208, -1.4176882098316568, -1.3038083290713856, -1.1935833188190568, -1.0886304511918536, -0.9903933863948606, -0.900113079330039, -0.818803883686131, -0.7472353747883542, -0.6859202696306896, -0.6351086710637329, -0.5947887068285805, -0.5646934768840797, -0.5443140681581826, -0.5329182482700182, -0.5295743125480481, -0.5331794351765969, -0.5424917685549344, -0.5561654475442231, -0.5727875893157037, -0.5909163365680962, -0.6091189729465799, -0.6260091449630436, -0.6402822543713549, -0.6507481379735098, -0.6563602268220523, -0.6562404717947677, -0.6496994351062512, -0.6362510746095605, -0.6156218864888547, -0.5877542186286544, -0.5528037178520405, -0.5111310255335327, -0.46328798399302956, -0.4099987568364095, -0.3521363964819698, -0.2906955082280605, -0.22676175945926655, -0.1614790624662094, -0.09601531786732986, -0.03152764130857968, 0.03087199190676124, 0.0901497616287223, 0.1453807901877127, 0.19577687378851885, 0.24071040927862053, 0.279733866614273, 0.31259427311420807, 0.33924230517607534, 0.35983572325403995, 0.37473703300919625, 0.3845054059214054, 0.38988304248040095, 0.391776306554857, 0.39123209697551276, 0.38941004826573317, 0.38755126359981557, 0.38694437662222547, 0.38888981231463865, 0.39466316874580615, 0.40547866992307063, 0.4224536443063471, 0.4465749636703657, 0.47866833334054765, 0.5193712584106777, 0.5691104229771387, 0.6280841128283798, 0.6962501890233064, 0.773319983407742, 0.8587583407246611, 0.9517898791989244, 1.0514113861158616, 1.1564101108332636, 1.2653875687131846, 1.3767883293595493, 1.4889331348145576, 1.6000555812164738, 1.7083415036899718, 1.8119701313119414, 1.9091560287464653, 1.9981908148890333, 2.077483647328228, 2.1455994847389546, 2.2012941869672504, 2.2435455834528657, 2.271579733085884, 2.2848917103972015, 2.2832603814469845, 2.2667567747928747, 2.2357458050440537, 2.1908812650373894, 2.1330941637433645, 2.0635746466899283, 1.9837478900783856, 1.895244505077669, 1.7998661214622422, 1.6995469365490885, 1.5963121134239258, 1.4922339893144, 1.389387108775557, 1.2898031257702467, 1.1954266230210686, 1.1080728760627734, 1.0293885437345682, 0.9608161975262831, 0.9035635109147064, 0.8585778188187085, 0.8265266292680149, 0.8077845274409431, 0.8024267598405987, 0.8102296272605649, 0.8306776532160778, 0.8629773336284143, 0.9060771176623086, 0.9586931225159739, 1.019339950218831, 1.0863658553648134, 1.1579914120729802, 1.232350748739557, 1.3075343622263549, 1.3816324903577804, 1.4527780137144708, 1.519187874845629, 1.5792020446889956, 1.6313191310980122, 1.6742278112677147, 1.706833376327145, 1.7282787997521103, 1.7379598784621877, 1.7355341430787612, 1.720923388166992, 1.6943098305352349, 1.6561260599288772, 1.6070390978734352, 1.5479290232642255, 1.4798627540583567, 1.404063689898157, 1.3218780178694465, 1.2347385605147596, 1.1441270998366606, 1.0515361420543325, 0.9584310946222485, 0.8662138093944041, 0.776188404340601, 0.6895302120055987, 0.6072586176265894, 0.530214445691041, 0.4590424333944672, 0.3941791960151285, 0.3358469460522601, 0.2840530787061796, 0.2385955846893743, 0.19907410127686964, 0.1649062677177893, 0.13534891528583107, 0.10952349876301845, 0.08644506813270271, 0.06505398941607038, 0.04424955417366562, 0.02292456994578141, 2.242531641306249e-16], [-0.0, -0.026997226770318048, -0.057960636488907175, -0.09362231031602426, -0.13455168115565408, -0.18113620882030315, -0.23356711630571675, -0.29183058512585114, -0.3557046656531908, -0.42476200964202476, -0.4983783803522815, -0.575746744786564, -0.6558966063322976, -0.7377180982791366, -0.8199902327660961, -0.9014125889147988, -0.9806396310599408, -1.0563167754832214, -1.127117273772226, -1.1917789541855845, -1.249139859945389, -1.2981718453245403, -1.3380112362655256, -1.3679857309726309, -1.3876368058019, -1.3967370006390145, -1.3953015831315572, -1.3835942295426513, -1.3621265081939222, -1.331651105791493, -1.2931488935423459, -1.2478100849673257, -1.19700988683021, -1.1422791848858753, -1.0852709336826416, -1.027723031220137, -0.9714185520407975, -0.9181442839554574, -0.8696485622265895, -0.8275994193772404, -0.7935440681788214, -0.7688707097320518, -0.7547736084464138, -0.7522223023045417, -0.761935721806589, -0.7843618766995372, -0.8196636387613107, -0.8677110046960465, -0.9280800691065805, -1.0000587772937823, -1.0826593651971115, -1.174637233104603, -1.2745158447537306, -1.3806170979136356, -1.4910964800522388, -1.6039822065010232, -1.7172174414916916, -1.828704626941299, -1.9363508917687795, -2.0381134871264854, -2.132044190912337, -2.216331648355863, -2.289340663787842, -2.349647530740049, -2.3960705815311605, -2.427695251190622, -2.443893081186435, -2.444334232774068, -2.4289932343550675, -2.398147848260506, -2.3523711059343952, -2.292516722605175, -2.219698259256801, -2.1352625472380877, -2.0407580256019346, -1.9378987599840882, -1.8285250116500422, -1.714561303862239, -1.5979729880762465, -1.480722343365182, -1.3647252481986512, -1.2518094441889942, -1.1436753672062607, -1.0418604535034057, -0.9477077389117912, -0.862339460024168, -0.7866362403164352, -0.7212223045173427, -0.6664570146950161, -0.6224328652127057, -0.5889799147875447, -0.5656764762950461, -0.5518657325866314, -0.5466778031777887, -0.5490566557399906, -0.5577911410921305, -0.5715493336422806, -0.5889152833177679, -0.6084272317576225, -0.6286163161757656, -0.6480447794876713, -0.6653427250666296, -0.679242498283972, -0.6886098436190146, -0.6924710738592856, -0.6900355944866261, -0.6807132490301891, -0.6641260868357771, -0.6401142999053987, -0.6087362265218994, -0.5702624724708063, -0.5251643519398862, -0.47409699580284465, -0.41787761131054324, -0.35745950079327393, -0.2939025547170494, -0.22834102363380407, -0.16194944198645825, -0.09590762266691581, -0.031365663536938614, 0.03059009473714133, 0.08896924615119711, 0.1429067681500749, 0.19168894933177957, 0.2347750956017639, 0.2718144242690542, 0.3026576807717344, 0.3273631499801893, 0.3461968798755799, 0.35962708614318395, 0.3683128580349428, 0.3730874348922361, 0.3749364651948386, 0.3749717922928479, 0.3744014297151249, 0.3744964910976925, 0.3765559227188264, 0.38186994822389403, 0.3916831737650152, 0.4071583164354297, 0.4293415091131078, 0.45913010082214034, 0.4972438142612526, 0.5442000426133307, 0.6002939680705724, 0.6655840671275706, 0.7398834354979086, 0.822757221763699, 0.9135263071328985, 1.0112772127240337, 1.114878059504012, 1.2230002532710014, 1.3341454217202384, 1.4466769963003747, 1.5588557116402137, 1.6688781928287197, 1.7749177183682103, 1.8751661863019486, 1.9678762744112333, 2.0514027734660365, 2.124242085671468, 2.185068918434419, 2.2327692655212252, 2.2664688521350205, 2.2855563253982867, 2.289700594661244, 2.2788618640003637, 2.2532960488792404, 2.213552426578949, 2.160464531826089, 2.09513447110404, 2.018910987465275, 1.9333617583947047, 1.840240548711782, 1.7414499652224826, 1.6390006667766972, 1.5349679699226735, 1.4314468543443593, 1.3305064121389063, 1.2341447997483026, 1.1442457406240287, 1.0625375907239814, 0.990555918581972, 0.9296104684144691, 0.8807572705598924, 0.8447765410180517, 0.8221568739548528, 0.8130860811195599, 0.8174488738410246, 0.8348314204806285, 0.8645326488864438, 0.9055820034890715, 0.9567632140914397, 1.0166434918361054, 1.0836074407142373, 1.1558948633824773, 1.2316415506152418, 1.3089220765817475, 1.3857935788887448, 1.4603394839733301, 1.5307121453532828, 1.5951733942117554, 1.6521320579601948, 1.700177581344868, 1.7381089843392425, 1.764958508988978, 1.7800094405968463, 1.7828077338289605, 1.773167227879551, 1.751168392939708, 1.7171507089618336, 1.6716989331749537, 1.6156236611555987, 1.5499367238486816, 1.475822086391385, 1.394603020907788, 1.3077064120323814, 1.2166251187019275, 1.122879357189735, 1.0279780874909683, 0.9333813776554672, 0.8404646887744922, 0.7504859679356062, 0.6645563590257878, 0.5836152437947508, 0.5084102105927524, 0.4394824186077642, 0.3771576845432329, 0.32154347007426315, 0.27253179585865656, 0.22980795521445352, 0.1928647516590002, 0.1610218430878704, 0.13344964501347728, 0.10919712925898131, 0.08722275572524446, 0.06642769579219056, 0.04569044855803512, 0.02390191688956869, 2.3565662112874196e-16], [-0.0, -0.028612205205775034, -0.061588996965975785, -0.09958653354585015, -0.14308595059427662, -0.19237665861277914, -0.2475449869750185, -0.30846849495558337, -0.37481612263867375, -0.44605420235266785, -0.5214581982750532, -0.6001298919554167, -0.681019588518671, -0.762952785872484, -0.8446606307262154, -0.9248133836613168, -1.0020560334802628, -1.0750451407196198, -1.142485953118033, -1.203168822975414, -1.2560039681119617, -1.3000536543038896, -1.334560936793628, -1.3589741803103894, -1.372966679000058, -1.376450817251194, -1.3695863466700229, -1.3527825000821232, -1.3266938168112097, -1.2922097107940567, -1.250437970416249, -1.202682532368068, -1.1504160174838827, -1.0952476507862678, -1.0388873074281653, -0.9831065278917464, -0.9296974270771433, -0.8804304807126391, -0.8370122073086906, -0.8010437737208298, -0.7739815369564665, -0.7571004944580879, -0.7514615506384672, -0.7578834204470153, -0.776919883284399, -0.8088429752384717, -0.853632567417524, -0.9109726265077609, -0.9802542942695213, -1.060585759397276, -1.1508087319895097, -1.249521171797433, -1.355105770341811, -1.4657635476099322, -1.5795517997917436, -1.6944255284402412, -1.8082813961582436, -1.9190031915263117, -2.024507748039934, -2.122790249265278, -2.211967865578151, -2.29032070641581, -2.356329135020823, -2.408706578663534, -2.4464270742075587, -2.468746914031648, -2.4752198976955233, -2.465705846918767, -2.4403722017244736, -2.399688680080705, -2.344415148049213, -2.275583008317069, -2.1944705681335686, -2.10257298938544, -2.0015675503851855, -1.8932750578556399, -1.7796183359470397, -1.6625787848074167, -1.544152042687462, -1.4263038018399292, -1.3109268192319332, -1.1998001286162903, -1.0945514017136704, -0.9966233246462709, -0.9072447534003624, -0.8274072915497844, -0.7578477977595895, -0.6990371830896666, -0.6511757024977319, -0.6141947850571325, -0.587765287212205, -0.5713118968459809, -0.5640332668862938, -0.5649273192869642, -0.5728210368660173, -0.5864039546700474, -0.6042644768280266, -0.6249280813189892, -0.6468964352105936, -0.6686864276419138, -0.6888681374224299, -0.7061007862782778, -0.7191657865628173, -0.726996072141012, -0.7287010010864317, -0.7235862362302831, -0.7111681414763248, -0.691182374790196, -0.663586509260565, -0.628556667805325, -0.586478311065695, -0.5379314679123285, -0.4836708400071558, -0.4246013424515931, -0.3617497584271151, -0.29623328399238497, -0.22922581738318087, -0.16192290331500134, -0.09550627551780706, -0.031108949232382995, 0.030218200526483014, 0.08753747906281767, 0.14005219747810824, 0.1871305348478068, 0.2283247919232406, 0.26338551130859333, 0.29227007274581723, 0.31514551599662577, 0.3323854941944773, 0.34456141363871434, 0.3524279679351031, 0.35690342129565245, 0.3590451339628519, 0.3600209486031415, 0.3610771669103163, 0.363503937746482, 0.3685989495574442, 0.3776303686791907, 0.3917999902136777, 0.4122075687033773, 0.4398172717965815, 0.47542715200817676, 0.5196424606862255, 0.5728535361123952, 0.6352188865471994, 0.7066539617110104, 0.7868259658116392, 0.875154915264788, 0.9708209884280824, 1.0727780568599972, 1.1797731317575468, 1.2903713092171636, 1.4029856575609456, 1.5159113627041578, 1.6273633366197273, 1.7355164021927008, 1.838547097495004, 1.9346760955612003, 2.022210213350566, 2.099582986373487, 2.165392813453605, 2.2184377286801515, 2.257745933557588, 2.282601319882105, 2.292563330630494, 2.287480639322001, 2.2674982746826164, 2.2330579734483758, 2.1848917059902244, 2.1240084831789887, 2.0516747145329273, 1.969388543246695, 1.8788487293773894, 1.7819187846856375, 1.6805871781500197, 1.5769245271481565, 1.4730387633631687, 1.3710293127982898, 1.2729413546158594, 1.1807212232209208, 1.0961739920729605, 1.0209242267488354, 0.9563808200253354, 0.9037067250137734, 0.8637942860118111, 0.8372467335710552, 0.8243662635545851, 0.8251489632494926, 0.8392866847218527, 0.8661758005206026, 0.9049326135692598, 0.9544150355998935, 1.0132500006069212, 1.0798659451148394, 1.1525295688226278, 1.2293859902603543, 1.3085013348448615, 1.3879067389920543, 1.4656427249929145, 1.5398028978394906, 1.608575937119935, 1.670284903887243, 1.7234229528340088, 1.7666846323842487, 1.7989920671191406, 1.8195154454848217, 1.8276873777794782, 1.8232108414500718, 1.8060605889722348, 1.776478054122442, 1.7349599513127427, 1.6822409159290794, 1.6192706775255967, 1.5471863887507282, 1.4672808478150148, 1.3809674483608345, 1.2897427654409293, 1.1951477381679347, 1.0987284372491004, 1.0019974084619738, 0.9063965611694721, 0.8132625248465136, 0.7237953275261714, 0.6390311598717244, 0.559819879567026, 0.4868077856816285, 0.42042605479461126, 0.3608850834527977, 0.3081748287234136, 0.26207108404061374, 0.22214747513935917, 0.18779281445873658, 0.15823331566365662, 0.1325590463145947, 0.10975388931152476, 0.08872819524129522, 0.06835324037973489, 0.04749656052006175, 0.025057210121704566, 2.4864427753583164e-16], [-0.0, -0.030377388799908728, -0.06548575637427535, -0.10589795389799313, -0.15200077155191968, -0.20398105177699297, -0.2618173921160997, -0.32527767643161015, -0.3939225213255426, -0.46711457019570823, -0.5440334144515505, -0.6236957738695831, -0.7049804296402031, -0.7866572778689618, -0.8674197613553046, -0.945919846194386, -1.0208046394808337, -1.0907536969601943, -1.154516046125715, -1.210945951643536, -1.259036476136519, -1.2979499396727256, -1.32704445458843, -1.3458958067490179, -1.3543140677011547, -1.3523544516061006, -1.3403220731683216, -1.3187704144582317, -1.2884934658037466, -1.2505116648754693, -1.2060519147472075, -1.1565221121578655, -1.1034807576592205, -1.0486023462730159, -0.993639347495417, -0.9403816741796918, -0.89061460868134, -0.8460761998817572, -0.8084151651174256, -0.779150326044255, -0.7596325771017077, -0.7510103301773232, -0.7541993005897945, -0.7698573994700708, -0.7983653784229974, -0.8398137368724943, -0.8939962540137236, -0.9604103494251265, -1.038264312978225, -1.126491279713297, -1.223769662858547, -1.3285496021387442, -1.4390848387725654, -1.5534692966750605, -1.6696775346054842, -1.7856081391580052, -1.8991290559242244, -2.0081238076587002, -2.110537525060022, -2.2044217184297934, -2.2879767469467645, -2.3595909959162435, -2.4178758498343615, -2.461695648564956, -2.490191932949325, -2.5028014218613657, -2.4992673117808053, -2.4796436487569977, -2.4442926873091566, -2.3938753173483107, -2.329334804560208, -2.2518742478617018, -2.1629283056951407, -2.064129877463897, -1.9572725440826144, -1.8442696695800915, -1.7271111415991995, -1.607818780679885, -1.4884014751677184, -1.3708110998605547, -1.2569002521182175, -1.1483827897753836, -1.0467980820886986, -0.9534797899698072, -0.8695298772958537, -0.7957984240114084, -0.7328696673089242, -0.6810545429883161, -0.6403898389736544, -0.6106439108675688, -0.591328749353677, -0.5817180351567928, -0.5808706729261037, -0.587659164354039, -0.6008020662819473, -0.6188996842555564, -0.6404720782765555, -0.6639984071085947, -0.687956611610032, -0.7108624367432759, -0.7313068160880074, -0.7479906911768989, -0.7597564094868596, -0.765614937594425, -0.7647682374539594, -0.7566262811313333, -0.7408183193804979, -0.7171981686319348, -0.6858434354941191, -0.6470487538485348, -0.601313263112347, -0.5493227033858336, -0.49192664029487654, -0.43011145594014816, -0.3649698493757049, -0.29766767778244024, -0.22940903578599436, -0.16140051354532198, -0.09481559324167105, -0.03076013797152436, 0.02976010304503177, 0.08586910280691963, 0.13684648437966093, 0.18214907066101166, 0.22142747285731562, 0.2545372638606871, 0.28154442385088163, 0.30272489473772923, 0.31855823372529096, 0.32971551042032865, 0.3370417426137882, 0.3415333093068401, 0.3443109120844159, 0.34658877418201256, 0.3496408675245977, 0.3547650390507012, 0.36324596667802383, 0.3763179107771085, 0.3951282380436961, 0.42070268085900575, 0.45391325688338685, 0.49544971164226775, 0.545795262728099, 0.6052073200102059, 0.6737037344755302, 0.751054992020925, 0.8367826210555007, 0.9301639278089732, 1.0302430146344226, 1.1358478782955994, 1.2456132311956984, 1.3580085425948383, 1.4713706627421346, 1.5839402738951769, 1.693901311425341, 1.7994224181772187, 1.8986994380215538, 1.989997921607684, 2.071694609581196, 2.1423168762587426, 2.2005791595895317, 2.245415470204122, 2.2760071618798934, 2.2918052557022577, 2.2925467379260964, 2.2782643939549905, 2.2492898944995954, 2.2062500111121057, 2.150056002990575, 2.081886381181001, 2.0031634160569043, 1.915523905311032, 1.8207848589378064, 1.7209048813962327, 1.6179421362779904, 1.5140098627712806, 1.4112304739339279, 1.311689302760865, 1.2173890723506033, 1.1302061508686092, 1.0518496108336945, 0.9838240465041208, 0.9273970144025971, 0.8835718524464687, 0.853066505403653, 0.8362988415842926, 0.8333787912783596, 0.8441074752192157, 0.8679833252414448, 0.9042150333501633, 0.9517410036640913, 1.0092548280660893, 1.0752361646204347, 1.1479862713297382, 1.2256673396618842, 1.3063446850816742, 1.3880307876583013, 1.4687301362072493, 1.5464838152766176, 1.6194127858907739, 1.6857588479724128, 1.743922333808124, 1.7924956662340814, 1.8302920202685036, 1.8563684500722712, 1.8700429813025052, 1.8709053186966567, 1.8588209763688026, 1.8339287999103515, 1.7966320109707345, 1.7475830625649236, 1.687662743037582, 1.6179541047355317, 1.539711916623497, 1.4543284453223817, 1.3632964538069032, 1.2681703692362887, 1.1705266096380864, 1.071924072551071, 0.9738657770091842, 0.8777626137902967, 0.7849000986531097, 0.6964089409241812, 0.6132401374057231, 0.5361451817804795, 0.4656618455491502, 0.40210584145773204, 0.34556852803334365, 0.295920658099499, 0.2528220189160002, 0.21573666079558093, 0.1839532684831298, 0.156610098825603, 0.13272379259201014, 0.11122127062038722, 0.09097384721436524, 0.07083263881123561, 0.04966431475785986, 0.026386230323861566, 2.631548349074569e-16], [-0.0, -0.032282286969046274, -0.06962600022266754, -0.11251395478632942, -0.16123332671111024, -0.215864752465379, -0.27627721559977736, -0.34212887431706746, -0.4128738285152488, -0.48777466963881955, -0.5659205052092694, -0.6462500060596059, -0.7275788917279641, -0.8086311515505387, -0.8880731987472186, -0.9645500747861662, -1.0367227636120286, -1.1033056414342273, -1.1631030786081076, -1.2150442259942575, -1.2582150587137257, -1.2918868144730522, -1.3155400500597936, -1.3288836460948907, -1.3318682140541764, -1.3246934978772493, -1.3078095117410888, -1.2819113120806471, -1.2479274617921878, -1.2070024037685674, -1.1604731155069143, -1.1098405626226686, -1.0567366030269718, -1.0028871118985758, -0.9500721974081276, -0.9000844558862823, -0.8546862707415053, -0.8155671904705001, -0.7843024267129399, -0.7623134932594081, -0.7508319616389404, -0.7508672394275409, -0.7631791853693194, -0.788256262986506, -0.8262998042796325, -0.8772148105320782, -0.9406075616450743, -1.015790142628944, -1.1017918298368263, -1.1973771143078775, -1.301069979233662, -1.411183897006578, -1.5258568722740937, -1.6430907343267007, -1.7607937780226313, -1.8768257698686035, -1.9890442768772678, -2.0953512418764637, -2.1937387209077355, -2.2823327164423115, -2.3594340839429213, -2.4235555577595624, -2.4734540338139768, -2.508157358783163, -2.5269850058108783, -2.5295621619887574, -2.515826909422559, -2.4860303458238007, -2.440729658248585, -2.380774330764544, -2.3072858293992033, -2.221631261759246, -2.1253916504730426, -2.0203255856648523, -1.9083291289732276, -1.791392927596041, -1.6715575594237044, -1.550868168031207, -1.43132945826977, -1.3148621091966362, -1.2032616215088876, -1.0981605525360114, -1.0009950048278915, -0.9129761266425864, -0.8350672568902762, -0.7679672064621059, -0.7121000158626705, -0.6676113694425739, -0.6343716832431938, -0.6119857205514923, -0.5998084307326219, -0.5969665566590688, -0.6023854177704588, -0.6148201528566622, -0.6328906020494968, -0.6551189237646267, -0.6799689814614184, -0.7058864985180912, -0.7313389680790559, -0.7548543186204741, -0.7750573747676172, -0.7907032155333036, -0.8007066169878467, -0.8041668712249458, -0.8003873956667362, -0.7888896831397192, -0.769421290287192, -0.7419577160367955, -0.706698179118464, -0.6640554600617521, -0.6146401247534514, -0.5592395896936458, -0.4987926199597674, -0.4343599662932958, -0.36709194477499657, -0.29819383882900524, -0.2288900568959789, -0.1603880087150098, -0.09384266803263619, -0.03032276961707917, 0.02922045577612833, 0.08398117222593396, 0.13332270781061797, 0.17679656265888788, 0.21415614084513332, 0.2453648287709991, 0.27059819013674236, 0.2902402011045402, 0.3048736048987879, 0.3152646189262299, 0.32234237562534007, 0.32717361690443947, 0.33093328767185826, 0.3348717833932032, 0.34027969702918953, 0.34845097978651246, 0.3606454760612947, 0.37805181455642844, 0.401751634207162, 0.4326860952760184, 0.4716255734265724, 0.5191433590143811, 0.5755940870804799, 0.6410975079708598, 0.715528076982437, 0.7985106972059332, 0.8894227963770549, 0.9874027598733368, 1.0913645819605713, 1.2000184399974623, 1.3118967454912338, 1.4253850854464314, 1.5387573409006055, 1.6502141600925824, 1.757923874142353, 1.8600648757291904, 1.9548684377848058, 2.040660930828202, 2.1159044047985303, 2.179234533996431, 2.2294949812967415, 2.2657673188042815, 2.287395744665694, 2.294005957363729, 2.2855176865700617, 2.262150530179477, 2.2244229068304566, 2.1731440981422563, 2.1093995210375227, 2.0345295338075293, 1.9501022360124585, 1.8578808680531846, 1.7597865477224912, 1.657857195006233, 1.5542035900500952, 1.4509635802197338, 1.3502554988010695, 1.254131878947237, 1.164534541440461, 1.0832521038003162, 1.0118809019709125, 0.9517902356140495, 0.9040927458646685, 0.8696206127485233, 0.8489081212762292, 0.8421809938742886, 0.8493527259751593, 0.8700279951790976, 0.9035130464695977, 0.9488327905961497, 1.0047541939518245, 1.0698153899242109, 1.1423598073827594, 1.2205744949328887, 1.3025317226396658, 1.3862328684281855, 1.46965354607683, 1.5507889068116478, 1.6276980475373262, 1.6985464856185981, 1.7616457121356366, 1.8154889113424952, 1.8587820317407346, 1.8904695112874006, 1.909754092861691, 1.9161103128903794, 1.9092914023335972, 1.8893295011878366, 1.8565292512680778, 1.8114549932505717, 1.7549119488238631, 1.687921913506507, 1.6116941167034398, 1.5275920196946529, 1.4370969167105845, 1.3417692767739158, 1.2432088128520629, 1.1430142889349195, 1.0427440744139576, 0.9438784287079606, 0.8477844482002757, 0.755684533573619, 0.6686291404748613, 0.587474462561776, 0.5128655662872913, 0.44522535456440276, 0.3847495853332205, 0.33140801484338783, 0.28495157811378136, 0.24492536450216953, 0.2106869984982172, 0.18142989845761803, 0.15621076246983898, 0.13398052399052876, 0.11361793293564827, 0.09396485279500832, 0.07386232259483282, 0.05218641524862939, 0.027882931393530333, 2.7911058610218833e-16], [-0.0, -0.03431482873161094, -0.07398194684347316, -0.11938813410410382, -0.17071652570818688, -0.2279388430439266, -0.2908135615181588, -0.3588900811667121, -0.43151880893141886, -0.5078669067694453, -0.5869393111043989, -0.6676044903111101, -0.7486242814814436, -0.8286870388478765, -0.9064432367318044, -0.9805426020375292, -1.0496718068914093, -1.1125917322028482, -1.1681733182570948, -1.2154310488655962, -1.2535531703941412, -1.2819278248455004, -1.3001643751939975, -1.3081093189226545, -1.3058563192932684, -1.293750029978061, -1.2723835436701665, -1.242589455311264, -1.205424691635779, -1.1621494168054523, -1.1142004750342784, -1.06315997148475, -1.0107197188140924, -0.9586423853729851, -0.9087202694464883, -0.8627326898104591, -0.8224030245446993, -0.7893564463804356, -0.765079393375067, -0.7508817785503912, -0.7478628820869793, -0.7568817861397729, -0.7785331073147085, -0.8131286578451568, -0.8606855265255445, -0.9209209178935335, -0.9932539267139792, -1.0768142584456313, -1.1704577391314777, -1.2727882941405355, -1.382185918424333, -1.4968400152852708, -1.614787349668575, -1.7339537489115562, -1.8521985915041994, -1.967361055019978, -2.077307049690003, -2.1799757452376842, -2.2734246060533043, -2.3558718834118553, -2.425735572426234, -2.4816679243618647, -2.5225847098129948, -2.547688552511057, -2.556485794183352, -2.5487965044859635, -2.5247574128617973, -2.4848177072613016, -2.4297278139208736, -2.3605214387061073, -2.278491309852486, -2.1851592104068107, -2.082241022689682, -1.971607623420713, -1.8552425639686734, -1.7351975432089097, -1.6135467289517498, -1.4923410067148852, -1.3735632312462818, -1.2590855268038272, -1.1506296275420345, -1.049731170844476, -0.9577087560553788, -0.875638461322054, -0.8043343751507032, -0.7443355501868463, -0.6958996283577032, -0.6590032227771414, -0.6333489767588026, -0.6183790579777202, -0.6132946902565792, -0.617081180445581, -0.6285377669608223, -0.6463115029341793, -0.6689342933612878, -0.6948621343632769, -0.7225155553943641, -0.7503202430232921, -0.7767468282585869, -0.800348848105862, -0.8197979453389214, -0.8339154469240448, -0.8416995591727799, -0.8423475340034662, -0.8352722926950056, -0.8201131378616394, -0.7967403374062442, -0.7652535220534021, -0.7259739967399629, -0.6794312216542505, -0.6263438671554604, -0.5675959844457515, -0.5042089572593731, -0.4373100058886138, -0.36809810093778417, -0.2978082081414162, -0.22767482581794296, -0.1588957920692775, -0.09259732931673709, -0.02980125945201037, 0.028604735330060194, 0.0818930115690318, 0.12951732996812604, 0.17112911248679735, 0.20658814988274066, 0.23596746337943247, 0.2595521767247084, 0.2778324113238508, 0.29149037340836464, 0.30138195437174026, 0.308513309599789, 0.3140130136772691, 0.3191005073862939, 0.32505165142205855, 0.333162280684664, 0.34471070932413694, 0.36092016894687196, 0.38292216966715387, 0.411721755764349, 0.44816558497471115, 0.49291369391972967, 0.5464157234628609, 0.6088922690647101, 0.6803218951504839, 0.760434212229373, 0.8487092644924218, 0.9443833176181546, 1.0464609754709513, 1.1537333943083692, 1.2648022080265984, 1.3781086317595428, 1.4919670774856975, 1.6046024975628783, 1.7141905732900982, 1.8188997882111573, 1.9169343719215997, 2.006577071038604, 2.0862307005463996, 2.1544574511099466, 2.2100149756876823, 2.2518883507731773, 2.2793171021556304, 2.2918165999494002, 2.2891932600359928, 2.271553135782549, 2.2393036413841263, 2.193148312585462, 2.1340746778573423, 2.063335479239484, 1.9824236429458086, 1.893041551510594, 1.7970653080080319, 1.696504805288223, 1.5934605162207627, 1.4900780020774558, 1.3885011934052016, 1.2908255296130935, 1.1990520492160346, 1.1150435020750193, 1.0404835085296023, 0.976839719142407, 0.9253318345865507, 0.8869052302862517, 0.8622107975584741, 0.8515914654280266, 0.8550757085897049, 0.872378181029529, 0.9029074456306445, 0.9457806017932183, 0.9998444497830521, 1.0637026761574309, 1.1357484029441198, 1.2142013177013458, 1.2971484951958334, 1.38258793676285, 1.4684737924819993, 1.5527621955550008, 1.6334566285284466, 1.7086517574462976, 1.7765747121826645, 1.8356228580020904, 1.8843971931263086, 1.9217306174964597, 1.9467104462459608, 1.9586946844451567, 1.9573217338905056, 1.942513364267053, 1.9144709459189726, 1.8736651056496596, 1.8208191263985134, 1.75688656239005, 1.6830236797301097, 1.6005574550555437, 1.5109499687477492, 1.4157601118870031, 1.3166035855771538, 1.2151122061124853, 1.1128935389086714, 1.0114918680290927, 0.9123514669935486, 0.8167830714678254, 0.7259343671039664, 0.6407651984869883, 0.5620280805927685, 0.49025445554741437, 0.42574698831912094, 0.3685780390446802, 0.3185942909319978, 0.2754273550888783, 0.2385100211722437, 0.20709767926088937, 0.18029430742822825, 0.15708230440797805, 0.1363553503817285, 0.11695340367531955, 0.09769888889980306, 0.07743310410104642, 0.05505187146653707, 0.02953947812674057, 2.9641798927082e-16], [-0.0, -0.03646146435173875, -0.07852319080564008, -0.12647072309751414, -0.18037962544759006, -0.24011096306989071, -0.3053128195028547, -0.3754278266115248, -0.4497065258384988, -0.5272262264564651, -0.6069148820828829, -0.6875793742332624, -0.7679374745901328, -0.8466526589424265, -0.9223708679373956, -0.9937582548937343, -1.0595389303856386, -1.1185317079479964, -1.1696848752658047, -1.2121080601522856, -1.2451003294191707, -1.2681737497278363, -1.2810717504503444, -1.2837817567296208, -1.2765417031355826, -1.2598401910388815, -1.2344102122650162, -1.2012165237723844, -1.161436918964276, -1.1164377967671386, -1.067744575879977, -1.0170076349387631, -0.9659645763753808, -0.916399709510986, -0.8701017244101468, -0.8288205802706032, -0.7942246592563071, -0.7678592379399156, -0.7511073037873771, -0.7451536939173324, -0.7509534588594646, -0.7692052569803597, -0.8003304679658675, -0.844458579073017, -0.9014192490550217, -0.9707412953379602, -1.0516586840715167, -1.1431234341435528, -1.2438251792645965, -1.3522169708878637, -1.4665467529949305, -1.584893801378731, -1.7052092984031484, -1.825360112315026, -1.9431747705512386, -2.0564905610983955, -2.1632006662109333, -2.261300229432553, -2.3489302800078358, -2.424418487877442, -2.486315796347701, -2.5334280764311092, -2.5648420644229297, -2.579944979657462, -2.578437369287203, -2.5603388877041557, -2.5259868859647514, -2.476027857207949, -2.4114019534206177, -2.333320952888442, -2.243240212291607, -2.1428252789112934, -2.0339139633787426, -1.9184747788045482, -1.7985627354351894, -1.676273539204621, -1.5536972762810688, -1.4328726731812933, -1.3157430031082498, -1.2041146643850789, -1.0996193873625824, -1.003680933729857, -0.9174870390793985, -0.8419672186932371, -0.7777769110832882, -0.7252882774458344, -0.6845878117489622, -0.655480749700452, -0.637502099446432, -0.6299339565968131, -0.631828614995113, -0.64203684624765, -0.6592405987757906, -0.6819892640230182, -0.7087385759238156, -0.737891151769802, -0.7678376495479133, -0.7969975094112, -0.8238582652720084, -0.8470124560362093, -0.8651912335562036, -0.8772938542042894, -0.882412350739818, -0.879850808054452, -0.8691388071983791, -0.8500387532445827, -0.8225469602148229, -0.7868885264909765, -0.7435061928335539, -0.6930435283353663, -0.6363229335063496, -0.5743190806096988, -0.5081285260742999, -0.4389363254301679, -0.3679805553716334, -0.29651569840887826, -0.22577587187179987, -0.15693888414910723, -0.09109207698280254, -0.02920086402998714, 0.027919195995775324, 0.07962604664241897, 0.125469868958688, 0.1652064007523034, 0.19880447754477842, 0.22644758383189476, 0.24852935971103118, 0.2656431659396591, 0.27856596603277906, 0.2882369331401899, 0.29573132837568966, 0.302230322462113, 0.30898754081411467, 0.3172932007335363, 0.32843677596173004, 0.34366916669160213, 0.3641653711555708, 0.3909886475634825, 0.4250571225925639, 0.4671137455894542, 0.5177004075075315, 0.5771369423284674, 0.6455056087960751, 0.7226415146861767, 0.8081292979100202, 0.9013062221778758, 1.001271683634705, 1.106902962848911, 1.2168768978430784, 1.3296970024820658, 1.443725414285606, 1.5572189301475408, 1.6683682807028175, 1.7753397069302985, 1.8763178382526633, 1.9695488315702891, 2.053382716416208, 2.126313903182594, 2.1870188489424773, 2.2343899379284826, 2.267564719769639, 2.28594975607883, 2.289238452344404, 2.2774223942548524, 2.2507958621244684, 2.2099533602276966, 2.1557801656085847, 2.089436069206813, 2.012332646810312, 1.9261045543664395, 1.8325754876996923, 1.7337195771127154, 1.631619099473075, 1.5284194814395682, 1.426282635203262, 1.3273397108218574, 1.2336443658379874, 1.1471276429553265, 1.0695555103154992, 1.0024900572320274, 0.9472552525775515, 0.9049080654577066, 0.876215620946694, 0.8616389205860663, 0.8613235015367283, 0.8750972435141403, 0.9024753629356151, 0.9426724631940013, 0.9946213427899167, 1.0569981032673421, 1.1282529503835144, 1.2066459483038816, 1.2902868710790645, 1.377178201019498, 1.4652602521061129, 1.552457349963396, 1.6367239792629895, 1.716089815173748, 1.7887025874296654, 1.852867782910362, 1.9070842738573721, 1.950075061936229, 1.9808124507186071, 1.998537097749522, 2.002770548738484, 1.993321016817948, 1.9702823352804495, 1.9340261786540416, 1.8851878103043322, 1.8246457709477477, 1.7534960676959899, 1.673021553977568, 1.5846573037169294, 1.4899528757591765, 1.390532434484338, 1.288053738203266, 1.1841670272174978, 1.0804748379402613, 0.9784937384396495, 0.8796189250372388, 0.7850925406479917, 0.6959764754279704, 0.6131302915761927, 0.5371947798453978, 0.4685815088660633, 0.4074685734880396, 0.35380258890802724, 0.3073068173983804, 0.2674951580087568, 0.23369158060747078, 0.2050544478014324, 0.1806050450738002, 0.15925953398614437, 0.13986345813731144, 0.12122786887044412, 0.10216609902200184, 0.08153019925610563, 0.05824606303967589, 0.031346302768166474, 3.1496841126988625e-16], [-0.0, -0.03870728323795299, -0.08321697579513994, -0.1337090441076261, -0.19014889423498163, -0.25228619209770614, -0.31965976861438006, -0.39160849454274843, -0.46728785350868574, -0.5456917921502922, -0.6256792873138577, -0.7060049453530853, -0.7853528409893593, -0.8623727156430614, -0.9357175898962822, -1.0040818034894272, -1.066238480080472, -1.1210754233689169, -1.167628485928269, -1.2051115113849822, -1.2329420329940628, -1.2507620151752563, -1.2584530466389996, -1.256145531328608, -1.2442215731196495, -1.2233114083243601, -1.1942834026054139, -1.1582277918473882, -1.1164345057849374, -1.0703655647466728, -1.0216226799285262, -0.9719108126237419, -0.9229985546391456, -0.8766762779954003, -0.8347130647342098, -0.7988134655986078, -0.7705751484874885, -0.7514484835233334, -0.7426990715732983, -0.7453741580319986, -0.7602737851351552, -0.7879274261373702, -0.8285767159989169, -0.8821647488987263, -0.9483322564292677, -1.0264208155457686, -1.1154830662614998, -1.2142997498404198, -1.3214032129871558, -1.435106866329867, -1.5535399402000645, -1.6746867509144172, -1.7964295796601681, -1.9165941764270453, -2.0329968354398096, -2.1434919478742653, -2.2460189233135184, -2.3386473838035045, -2.419619573225333, -2.487388989096315, -2.5406543322953725, -2.5783879804464673, -2.5998583201155463, -2.604645418440523, -2.5926496727859294, -2.5640932436532466, -2.519514247332182, -2.459753856482497, -2.3859366248163347, -2.2994445122255915, -2.2018852351801788, -2.095055700411224, -1.9809013945670386, -1.8614726959229695, -1.7388791440977802, -1.6152427484163934, -1.4926514340180437, -1.3731137166422105, -1.2585156624861245, -1.1505811295203663, -1.0508362026978693, -0.9605786297091085, -0.8808529389664784, -0.8124317804556389, -0.7558038764727651, -0.7111688068779431, -0.6784386863496374, -0.6572466233447336, -0.6469616861821126, -0.646709944908677, -0.6554010122142794, -0.6717593761855607, -0.6943597053009049, -0.7216652144871122, -0.7520681124790312, -0.783931106766739, -0.8156289240872261, -0.8455888120859472, -0.8723290211588219, -0.8944943236687719, -0.9108877091792179, -0.9204974969506716, -0.9225192280731652, -0.9163718361683874, -0.9017077441232982, -0.8784166910524139, -0.8466232546716674, -0.8066781954469625, -0.7591439062017334, -0.7047744003806189, -0.6444904101234459, -0.579350288253636, -0.5105175131582241, -0.43922567972131593, -0.36674192088055835, -0.2943297414933903, -0.2232122581254701, -0.15453682484080802, -0.08934198645617696, -0.028527638026408595, 0.02717081583687879, 0.07720361366667144, 0.12122253677769601, 0.15909112829362243, 0.19088895254057822, 0.21690977151801294, 0.23765367415306876, 0.2538133522643575, 0.26625487058775943, 0.27599342295159146, 0.2841646990489024, 0.29199260286732265, 0.30075416172215264, 0.3117425414851128, 0.3262291370300621, 0.34542573573072627, 0.3704477552638299, 0.40227953485130485, 0.4417426119163218, 0.4894678450583388, 0.5458721510029425, 0.61114051004343, 0.6852137642561332, 0.7677825886676938, 0.8582878611607117, 0.9559274960703033, 1.0596696431630224, 1.1682719920853406, 1.280306766473602, 1.3941908456488539, 1.5082203188652894, 1.620608660803599, 1.729527620356058, 1.833149840212488, 1.9296921742552149, 2.017458644643584, 2.0948819814250133, 2.160562714613446, 2.21330484134467, 2.252147167732398, 2.276389524585742, 2.2856131758229576, 2.2796948753407222, 2.258814178952905, 2.223453779127875, 2.1743927976986672, 2.1126931414018224, 2.039679192862743, 1.956911271371407, 1.8661534495086591, 1.7693364496550812, 1.6685164652401534, 1.5658308522837918, 1.4634517148497237, 1.3635384615293227, 1.2681904376622006, 1.1794007389698535, 1.0990122865739764, 1.0286771915905755, 0.9698203608716448, 0.9236081958542846, 0.8909231162830695, 0.8723445027101951, 0.8681364994976276, 0.8782429572448366, 0.902289624103772, 0.9395935234406377, 0.9891792849440666, 1.0498020317022287, 1.1199762709741723, 1.1980100951183474, 1.2820438748351524, 1.3700925225332206, 1.4600903217523473, 1.5499372611274416, 1.6375457797150632, 1.7208868253493799, 1.7980341491205936, 1.8672058064948946, 1.9268019078034915, 1.9754377559944287, 2.011971625279245, 2.0355265677300856, 2.0455057826741854, 2.041601242228087, 2.0237954315923505, 1.992356230709077, 1.9478251304313186, 1.8909991373711073, 1.822906873133227, 1.7447795119989307, 1.6580173229264057, 1.5641526840285083, 1.4648105180091155, 1.3616671534727451, 1.25640864825107, 1.1506896162256082, 1.0460935785242689, 0.944095814031525, 0.8460296141079012, 0.7530567540910025, 0.666142881926332, 0.58603839502107, 0.5132652334160163, 0.44810986425504157, 0.3906225731680282, 0.34062301659147715, 0.2977118292980027, 0.26128792750593627, 0.2305710037536185, 0.20462857886020439, 0.18240686202679843, 0.16276457530801025, 0.14450882566184278, 0.12643205837189955, 0.10734910104135272, 0.08613330816862366, 0.061750842476372365, 0.033292179986283, 3.3463903405064364e-16], [-0.0, -0.041036146987973275, -0.08802849433158214, -0.14104800268388815, -0.19994831310569483, -0.26436796739497365, -0.33373870852313486, -0.4072996545933023, -0.48411698575922135, -0.5631086386202218, -0.6430733704249557, -0.722723439343147, -0.8007200500659994, -0.8757106385603042, -0.9463670178764967, -1.011423379855294, -1.0697131461255753, -1.1202036860293996, -1.1620279684943153, -1.1945122882117267, -1.2171993019828262, -1.2298657264109423, -1.232534180400195, -1.225478801883656, -1.2092244242190184, -1.184539259866576, -1.1524212032509915, -1.1140780269919934, -1.0709019018974555, -1.0244388173161685, -0.9763536109585489, -0.9283914327561469, -0.8823365628070755, -0.8399695764967562, -0.8030238985972709, -0.7731428112391036, -0.7518379774558107, -0.7404505125146907, -0.7401155801071541, -0.751731410960381, -0.7759335394326545, -0.8130749316146905, -0.8632125393253477, -0.9261006615377694, -1.0011913319224177, -1.087641782321706, -1.1843288612081768, -1.2898701177098102, -1.402651099748245, -1.5208582632134122, -1.6425167516262347, -1.765532185812709, -1.8877355036939958, -2.0069298138552307, -2.1209381749960614, -2.2276511879858303, -2.3250732887022507, -2.4113666581234154, -2.4848917206102668, -2.544243280659553, -2.5882814507151175, -2.6161566454234673, -2.6273280580315985, -2.621575189043945, -2.5990021620290964, -2.5600347325895036, -2.5054100698178403, -2.43615956084825, -2.353585054206771, -2.259229112563008, -2.1548399864274317, -2.0423321439114934, -1.923743294886132, -1.8011889282534557, -1.6768154366643684, -1.5527529325582945, -1.4310688621970142, -1.3137235003979162, -1.2025283585824398, -1.0991084638254431, -1.0048693687084234, -0.9209696333947269, -0.8482993854070102, -0.7874654124721683, -0.7387830832254841, -0.7022752235020734, -0.67767790651093, -0.6644529475554288, -0.6618067322516098, -0.6687148553644452, -0.6839519091424108, -0.706125638747677, -0.7337145809917354, -0.7651082235336849, -0.7986486668614332, -0.8326727420303331, -0.8655535339202245, -0.8957402826801847, -0.9217956844019938, -0.9424296846074871, -0.9565289529623521, -0.9631813422994207, -0.9616947666184332, -0.9516100778818288, -0.9327076764702873, -0.9050077511812203, -0.8687642075900158, -0.8244525043494333, -0.7727517715407546, -0.7145217296379662, -0.6507750583893294, -0.5826459786947272, -0.5113559045283402, -0.4381770937918715, -0.364395274910127, -0.2912722488275914, -0.22000946329315318, -0.15171352803623253, -0.08736458638950992, -0.02778838247187368, 0.02636723483095039, 0.07465074666344196, 0.11681984612619464, 0.15284842104527233, 0.18292744555864746, 0.20745974773183504, 0.22704878059057795, 0.24248168100464954, 0.254707050784075, 0.26480803334521347, 0.2739713838301559, 0.2834533374415476, 0.2945431672507918, 0.30852538662562645, 0.32664159104488455, 0.3500529483741927, 0.3798043352519496, 0.41679108031214385, 0.4617292134225326, 0.5151300354363996, 0.577279717219847, 0.6482245125326961, 0.7277620297852342, 0.8154388562321614, 0.9105546685710061, 1.0121728001682695, 1.1191370713379025, 1.2300945293486465, 1.343523593152922, 1.457766958030713, 1.5710684909603967, 1.681613241721389, 1.7875696102020806, 1.8871326493087397, 1.97856744684665, 2.0602515197544222, 2.1307151704533225, 2.1886787975078286, 2.2330862203188695, 2.263133168599452, 2.27829019974131, 2.2783194381658047, 2.263284677191814, 2.2335545422881555, 2.1897985809484846, 2.1329763147668386, 2.0643194594306626, 1.985307684112077, 1.8976384390534673, 1.8031915251390547, 1.7039892083441452, 1.6021527919691516, 1.4998566477713375, 1.3992807713095838, 1.30256296541124, 1.2117517676737533, 1.1287612230000326, 1.0553285606648921, 0.9929757683040359, 0.9429759641172124, 0.9063253556826779, 0.8837214418250084, 0.8755479661641685, 0.8818669708911, 0.9024181308548533, 0.9366253753047863, 0.9836106318086751, 1.0422143581649204, 1.1110223676432174, 1.1883983045185889, 1.2725209942050293, 1.3614257785568147, 1.4530488548308589, 1.5452735686024603, 1.6359775682221593, 1.723079712189506, 1.8045856314447575, 1.8786308857292882, 1.9435207158749384, 1.9977654805622518, 2.0401109745610104, 2.06956295302573, 2.085405329891505, 2.0872116742430724, 2.074849792857293, 2.0484793558887455, 2.008542691721259, 1.955749042188304, 1.8910527266192716, 1.8156258086491652, 1.7308259898870464, 1.6381605662121734, 1.5392473729585405, 1.4357737123922332, 1.329454299098036, 1.2219892752115986, 1.1150233375446017, 1.0101069828883513, 0.9086608171240558, 0.8119437898109733, 0.7210261108378355, 0.6367674822021683, 0.559801139173419, 0.49052404452098086, 0.4290934209559884, 0.37542964444592697, 0.329225358704578, 0.28996051301654296, 0.2569228755927974, 0.22923343662676632, 0.20587599257915673, 0.18573009902301282, 0.16760649621945786, 0.1502840515287889, 0.1325472272677282, 0.11322307255899573, 0.09121675330084372, 0.06554467518333726, 0.03536431963222056, 3.5529391579828295e-16], [-0.0, -0.04343083630279722, -0.09292121138835485, -0.14843060917915302, -0.2097003072884646, -0.276259027223939, -0.347434606342318, -0.4223713940782921, -0.5000529247262722, -0.5793292801061245, -0.6589484313303521, -0.7375907427771321, -0.8139057359765413, -0.8865501486325649, -0.9542262860529456, -1.0157196498487828, -1.0699348422611017, -1.1159287835863427, -1.152940343976566, -1.1804155778309675, -1.1980278569374414, -1.2056923247998717, -1.2035742360674535, -1.1920908981483624, -1.171907093123627, -1.143924022955713, -1.109261985582839, -1.0692371496759963, -1.025332947583314, -0.9791667454704623, -0.9324525733579818, -0.8869608025145079, -0.8444757408111688, -0.8067521760309728, -0.7754719311985256, -0.7522015038154355, -0.7383518421718781, -0.7351412670286144, -0.7435624769501552, -0.7643544820676739, -0.7979801962939721, -0.8446102847673854, -0.9041137147951768, -0.9760552984116806, -1.059700346769185, -1.154026385045974, -1.257741705589229, -1.3693103708075567, -1.4869831199756598, -1.6088334894882053, -1.7327983277701853, -1.8567217771911984, -1.9784017086406587, -2.095637532059347, -2.206278269754183, -2.3082697696784886, -2.3996999533131382, -2.47884103694441, -2.5441877349567856, -2.594490547568284, -2.628783350968865, -2.6464046422817997, -2.647011941892969, -2.6305890178376243, -2.5974457671582027, -2.5482107633117526, -2.4838166525771417, -2.4054787517638916, -2.314667360242161, -2.2130744474952153, -2.1025755094501686, -1.9851874995740175, -1.8630238314113496, -1.738247515710028, -1.6130235359502831, -1.4894715800135157, -1.3696202326086675, -1.2553636932898646, -1.1484220194745387, -1.0503058044620288, -0.9622860892981616, -0.8853701772037121, -0.8202838734161736, -0.7674605152990939, -0.7270369913573843, -0.6988567774606407, -0.6824798483139188, -0.6771991562099287, -0.6820632114180389, -0.6959041530693092, -0.7173705696290664, -0.7449642171588836, -0.7770796942335669, -0.8120460667317558, -0.8481693953051541, -0.8837751040659525, -0.9172491411791432, -0.9470769202134011, -0.9718790942533184, -0.9904433012498969, -1.0017511266516408, -1.0049996552613545, -0.999617125298416, -0.985272350237404, -0.9618777342844668, -0.929585871301582, -0.8887798804710375, -0.8400577909029372, -0.7842114377439394, -0.7222004703839007, -0.655122195631681, -0.5841780821959134, -0.5106378348915079, -0.4358020056689184, -0.36096414239215396, -0.28737348446079847, -0.2161991967147167, -0.14849709006088566, -0.0851797100408456, -0.026990584843986445, 0.02551668563892458, 0.07199394543347351, 0.11230818994388107, 0.14654520445535277, 0.17500703159391406, 0.19820332705294777, 0.2168368228598399, 0.23178327193015677, 0.24406639271489644, 0.2548284646980921, 0.2652973409848685, 0.27675074028371677, 0.29047875476762264, 0.3077455606815748, 0.32975134383062776, 0.3575954515453569, 0.39224175634041575, 0.4344871648670052, 0.4849341301565161, 0.543967927409904, 0.6117393361140935, 0.6881532369707737, 0.7728634843393389, 0.8652742573040346, 0.9645479290079233, 1.0696193286407416, 1.1792161075648346, 1.2918847646037601, 1.40602173944113, 1.519908851070729, 1.6317522436488234, 1.7397239078450424, 1.8420047742886299, 1.9368283288208294, 2.022523678242466, 2.0975570006993305, 2.160570346732124, 2.210416814630725, 2.2461912057350424, 2.2672553697683897, 2.2732575746671557, 2.2641453766765625, 2.240171621285975, 2.201893370107253, 2.150163719037489, 2.086116644825864, 2.011145186269895, 1.926873428544898, 1.8351229106273252, 1.7378742126746456, 1.6372245991886845, 1.5353426918703412, 1.4344212208343878, 1.336628952425259, 1.2440629150081146, 1.1587020401983115, 1.0823633060966174, 1.0166614119358546, 0.9629729314823439, 0.922405787547479, 0.895774764589013, 0.8835836336565087, 0.8860143073251052, 0.9029232755709903, 0.9338454008224953, 0.9780049758720485, 1.034333776199623, 1.1014956727211647, 1.1779172160559959, 1.2618234628637597, 1.3512781920379588, 1.444227556526251, 1.5385461377328526, 1.632084315730797, 1.7227158411398094, 1.8083844941304508, 1.887148742554885, 1.9572233639782641, 2.017017074046754, 2.0651653042256473, 2.100557392959704, 2.1223575927365568, 2.130019447938843, 2.123293260979492, 2.102226533012394, 2.0671574363367418, 2.0187015442663463, 1.9577322065755014, 1.8853551106857336, 1.802877706810794, 1.7117742959722335, 1.6136476802136177, 1.510188352064568, 1.4031322534912878, 1.2942181619840873, 1.1851457624841697, 1.077535438605599, 0.9728907657815102, 0.8725646139081532, 0.777729669727973, 0.6893540720849411, 0.6081827192912905, 0.5347246605656637, 0.46924682656629796, 0.41177419141081684, 0.36209629434232177, 0.3197798874976105, 0.2841873211143637, 0.25450013286483597, 0.22974717743968065, 0.2088365192835867, 0.19059021832112552, 0.17378106791311007, 0.15717029789002238, 0.13954523444868608, 0.11975591346211852, 0.09674967418129667, 0.06960281559674988, 0.03754847644786938, 3.767851968994969e-16], [-0.0, -0.04587321033816182, -0.09785720871197155, -0.1557985245933822, -0.21932650038156043, -0.28786237001574416, -0.3606342472363573, -0.43669763646758714, -0.5149609341555476, -0.5942152567288679, -0.6731678165080099, -0.7504779718090767, -0.8247950046053345, -0.8947966303063215, -0.9592272207672952, -1.01693472419121, -1.0669052941185864, -1.1082946935512492, -1.1404556181203258, -1.1629601821781437, -1.1756169313004843, -1.178481880965719, -1.1718632307426966, -1.156319562442531, -1.1326514953964981, -1.1018869381913392, -1.065260239657179, -1.024185698554142, -0.9802260372945291, -0.9350565764815423, -0.8904259607083531, -0.8481143790442003, -0.8098902935471428, -0.7774667341647682, -0.7524582373088591, -0.7363394976570771, -0.7304067684454549, -0.7357429854296029, -0.753187505211948, -0.7833112417662703, -0.8263978583075293, -0.882431528218547, -0.9510916220405471, -1.0317545113817905, -1.1235025090587398, -1.225139792059282, -1.3352149842467718, -1.4520499132787443, -1.573773904996157, -1.6983628422795118, -1.8236820974365349, -1.9475323505064672, -2.0676972328440266, -2.1819916878100893, -2.288309919550547, -2.3846718072407262, -2.469266695693577, -2.5404935330936866, -2.5969964113979356, -2.6376946725973567, -2.661806871962451, -2.6688680344961844, -2.658739799574783, -2.6316132173096682, -2.588004134418217, -2.528741283110149, -2.4549473594086404, -2.3680135432285176, -2.269568067399083, -2.161439582888625, -2.0456161893690283, -1.9242011010059386, -1.7993659945477836, -1.6733031385685968, -1.5481774278731681, -1.4260794450303562, -1.3089806418602052, -1.1986916782271737, -1.096824875092759, -1.0047616354756435, -0.9236255633325288, -0.8542618694818573, -0.7972234990367022, -0.7527642502162409, -0.7208389839290245, -0.7011108513636028, -0.692965297214615, -0.6955304332748393, -0.707703224921548, -0.7281807952318023, -0.7554960314250739, -0.7880565789554039, -0.824186232244287, -0.8621676795686954, -0.9002855341856092, -0.9368685849256932, -0.9703302271048618, -0.9992060879061749, -1.022187937962841, -1.0381530807120414, -1.0461885306256409, -1.045609427609429, -1.0359712842405762, -1.0170758213055062, -0.9889703113017569, -0.9519405150453757, -0.9064974591238185, -0.8533584575770651, -0.7934229259821088, -0.7277436664422173, -0.6574944145951191, -0.5839345318556024, -0.508371795418899, -0.43212428336811154, -0.3564823714655881, -0.2826718514226147, -0.21181914784695233, -0.14491955352514674, -0.08280932169516533, -0.02614235158273242, 0.024627917673096803, 0.06926092640646553, 0.10773539785060003, 0.14024955376832898, 0.16721513230460097, 0.1892453602350255, 0.20713719012808898, 0.22184826344671904, 0.23446919946069103, 0.2461919334902657, 0.25827493329942475, 0.27200620670998776, 0.28866507454936324, 0.30948371929054286, 0.3356095302313965, 0.3680692504766614, 0.407735889670696, 0.45529930037008665, 0.5112412267539264, 0.5758155242407821, 0.6490341202393783, 0.7306591428909216, 0.8202014898334388, 0.9169259465953687, 1.0198627982674764, 1.1278257127664792, 1.239435513441094, 1.3531493070213643, 1.4672942938044131, 1.5801054640253174, 1.689766280707352, 1.7944513675740392, 1.8923701629485614, 1.9818104684825841, 2.0611808159323477, 2.129050596265543, 2.1841869427066016, 2.2255874318258266, 2.2525077627393117, 2.264483691615503, 2.2613466341560073, 2.243232499248041, 2.210583478910235, 2.1641426890192235, 2.1049417279675757, 2.0342813921303993, 1.9537059535895251, 1.8649715628821302, 1.7700094837257905, 1.6708849941637343, 1.5697528962149725, 1.4688106612314458, 1.370250298634711, 1.2762100700062202, 1.18872717775851, 1.1096925376002706, 1.040808697178297, 0.9835518907408445, 0.9391391231601292, 0.9085010585039089, 0.892261351416355, 0.8907229071770685, 0.903861392154061, 0.9313261444403227, 0.9724484589434487, 1.0262570463508736, 1.091500295469436, 1.1666748075656566, 1.250059523417601, 1.3397546324166683, 1.4337243414068614, 1.5298424917143052, 1.6259399481431804, 1.7198526451349407, 1.8094691637035512, 1.8927767284060546, 1.9679045560514565, 2.0331635560032786, 2.0870814740723875, 2.128432685822451, 2.156261977786163, 2.1699018033239175, 2.168982659978952, 2.1534364032386937, 2.1234924834591054, 2.0796672641188887, 2.022746746335054, 1.9537631826053437, 1.8739662081849289, 1.7847892478130432, 1.6878120655439457, 1.5847204135542652, 1.4772637998913758, 1.3672124336917797, 1.2563144185661042, 1.1462542504079702, 1.0386136352870985, 0.9348355774312148, 0.8361925983057412, 0.7437598377608236, 0.6583936599461608, 0.5807162434584395, 0.5111064806125966, 0.4496973487205771, 0.3963797509014696, 0.35081265939215955, 0.31243923470691964, 0.2805084433054513, 0.2541015584388925, 0.23216280699454606, 0.21353332248449075, 0.19698748336728944, 0.1812706586532197, 0.16513735062092777, 0.14738871823365982, 0.126908484601079, 0.10269627704915678, 0.07389751785669987, 0.03982907570372562, 3.9895443921830614e-16], [-0.0, -0.048344376921091774, -0.10279754639776688, -0.16309262514499542, -0.22874848353353594, -0.29908221953880004, -0.3732273768179477, -0.4501574325236587, -0.5287139417728706, -0.6076386025568852, -0.6856084004459065, -0.7612729093775858, -0.8332927652607722, -0.9003782946177143, -0.9613272719467286, -1.0150607971767116, -1.0606563281091523, -1.0973769710565804, -1.1246962243181653, -1.1423174814294987, -1.1501877315028435, -1.1485050391960792, -1.1377195432947722, -1.118527876655673, -1.0918610772439021, -1.058866226013811, -1.0208822082639708, -0.9794101467889517, -0.9360791938238808, -0.8926084909186791, -0.8507662083782305, -0.8123266561362767, -0.779026513817108, -0.7525212578038449, -0.734342866538526, -0.7258598618504413, -0.7282406943355437, -0.7424214058357355, -0.7690784036650578, -0.8086070617571907, -0.8611067262492673, -0.9263725505111221, -1.0038944209913216, -1.0928630644789583, -1.1921832536548969, -1.3004938553906473, -1.416194299385784, -1.5374768875254456, -1.6623642206668272, -1.7887508929800238, -1.9144484976115406, -2.0372329039535457, -2.1548927082748555, -2.2652777273776104, -2.3663464001157273, -2.456210984208937, -2.533179485298081, -2.5957933304417713, -2.642859897447755, -2.6734791321727456, -2.68706362529143, -2.6833516746499355, -2.662413025428582, -2.624647153907231, -2.5707741374355764, -2.501818328961875, -2.4190852248951806, -2.324132076027191, -2.218732938813397, -2.1048389949302537, -1.9845350775252313, -1.8599934302923073, -1.7334257883309163, -1.6070349061859868, -1.482966667673547, -1.3632638938917114, -1.249822920693707, -1.1443539460116128, -1.0483460525490502, -0.9630376948788208, -0.8893933047826885, -0.8280865181075814, -0.7794903642081789, -0.7436745892033021, -0.7204101109763132, -0.7091804313579827, -0.7091996634763049, -0.7194366739406796, -0.7386446942129484, -0.7653956267410368, -0.7981181623121507, -0.8351387382485532, -0.8747243045897084, -0.915125828742159, -0.9546214590523651, -0.9915582845245535, -1.0243916709578278, -1.0517212219542567, -1.0723225047714708, -1.0851737935014487, -1.08947721267689, -1.084673809818406, -1.0704522419584082, -1.0467509248610967, -1.0137536603811372, -0.9718789229784096, -0.9217631466809209, -0.8642385047519171, -0.8003058121997697, -0.7311033026342019, -0.6578721328034739, -0.5819195479224425, -0.5045806966564199, -0.42718011500186687, -0.3509939025825991, -0.277213592996756, -0.20691267240046388, -0.1410166287364008, -0.08027731975825338, -0.025252333678365217, 0.023710115207355834, 0.06648035883851429, 0.10315027395834728, 0.13403002678058387, 0.15963864720807258, 0.18068867756406645, 0.19806529610760717, 0.21280046077099615, 0.22604274988734824, 0.2390236908238929, 0.2530214614870833, 0.2693229212077822, 0.28918497470273813, 0.313796294407489, 0.3442404218936914, 0.3814612383868185, 0.42623173831108657, 0.4791269596697649, 0.5405018228891534, 0.6104745080388779, 0.68891586211022, 0.7754451767280026, 0.8694325160642645, 0.9700076088282845, 1.0760751511822697, 1.1863362034670895, 1.2993152068416844, 1.4133920002961833, 1.5268380876763805, 1.6378562916774067, 1.7446228401040837, 1.845330861413966, 1.9382342234388217, 2.0216906323816826, 2.094202919218002, 2.154457477333774, 2.201358877791294, 2.2340597755607816, 2.2519853293231926, 2.2548514864069507, 2.242676629947656, 2.21578624391649, 2.1748104193825233, 2.1206741981536936, 2.054580923546266, 1.9779889381989086, 1.8925821313880244, 1.8002349892095775, 1.702972936541292, 1.6029288765335312, 1.502296928596009, 1.4032844370781918, 1.3080633682965674, 1.2187222320846027, 1.137219655135463, 1.065340697247566, 1.0046569390141729, 0.956491282011587, 0.9218882922409974, 0.9015907871306523, 0.8960232189672631, 0.9052822467752345, 0.9291347183058688, 0.9670231080759694, 1.0180782805778381, 1.0811392741689752, 1.1547796349588895, 1.2373396752789274, 1.3269638918033586, 1.4216426574663004, 1.5192572019121497, 1.6176268197213324, 1.7145571958744161, 1.8078887150307252, 1.895543625717019, 1.9755709622900415, 2.046188185727243, 2.105818587440932, 2.15312360631873, 2.187029335426891, 2.206746638138815, 2.2117844503205877, 2.2019560117436425, 2.177377941995309, 2.1384622495865537, 2.085901533452819, 2.020647799430202, 1.9438854665705927, 1.8569992756237337, 1.761537931323511, 1.6591744083875506, 1.5516639260182459, 1.4408006454078712, 1.3283741681567849, 1.2161269101216543, 1.1057133951970548, 0.9986624577348311, 0.8963432621964792, 0.799935946290726, 0.710407571896161, 0.6284939296137602, 0.554687591348143, 0.4892324447069839, 0.43212477728325116, 0.38312081221263566, 0.34175043296164836, 0.30733667919426294, 0.279020450689535, 0.25578972625398966, 0.2365124926271171, 0.21997248729369392, 0.20490679114306307, 0.1900442637197316, 0.17414379643385255, 0.15603136793669456, 0.13463492064785323, 0.1090161372284474, 0.07839827907974505, 0.04218935357197897, 4.216340856778974e-16], [-0.0, -0.05082487193504389, -0.10770263807634396, -0.17025357981845007, -0.23788859171717486, -0.30982498604172537, -0.3851078233642302, -0.46263621044695163, -0.5411938757476997, -0.6194832194597802, -0.6961619420294552, -0.7698812849338578, -0.8393248719653897, -0.9032471195463154, -0.960510191232334, -1.0101185044365262, -1.0512498557351555, -1.0832823134830112, -1.105816130840811, -1.1186900561168969, -1.1219915574744623, -1.1160606320624107, -1.101487031672562, -1.0791009040543622, -1.0499570168437986, -1.01531289547098, -0.9766013632623528, -0.9353981172911079, -0.8933851036737954, -0.8523105676552035, -0.8139467441137147, -0.7800462207283598, -0.7522980472341286, -0.7322846788399314, -0.7214408295383655, -0.7210152719115794, -0.732036555013243, -0.7552835225070611, -0.7912614016001537, -0.8401841021133859, -0.9019632174591331, -0.9762040589407803, -1.0622088855621674, -1.1589873175810104, -1.2652737476252025, -1.3795513926016172, -1.5000824670641897, -1.6249438081822447, -1.7520671476823058, -1.8792831104666106, -2.0043679259141016, -2.125091768484359, -2.2392676009163544, -2.3447993771499687, -2.4397284735405016, -2.5222772557500317, -2.590888753977767, -2.644261509377996, -2.6813787674406706, -2.7015313270490076, -2.704333503661813, -2.68973182796361, -2.658006273427761, -2.6097639833643984, -2.5459256458708555, -2.4677048393438246, -2.3765808376153243, -2.274265518296313, -2.162665156803207, -2.043838008437178, -1.919948678886245, -1.793220357263943, -1.665886033521943, -1.5401398426506017, -1.4180896710516608, -1.3017121260484856, -1.192810908579421, -1.0929795432370746, -1.003569311117107, -0.9256631021300493, -0.8600557577016398, -0.8072413157465068, -0.7674074013715796, -0.7404368330987965, -0.7259163397620172, -0.7231521119162831, -0.7311917477945925, -0.7488520015599898, -0.7747516045384173, -0.8073483116061508, -0.8449792278048828, -0.8859033968922086, -0.9283455856376842, -0.9705401763424851, -1.0107740857314873, -1.0474276608066266, -1.079012560563361, -1.10420571512014, -1.1218785586559166, -1.131120856907042, -1.1312585906772772, -1.1218655102978243, -1.102768138361885, -1.0740441652607728, -1.0360143498637717, -0.9892282019040646, -0.9344438791473183, -0.8726028773186947, -0.8048002204362887, -0.7322509704203577, -0.6562539648621707, -0.578153758423993, -0.49930178487386817, -0.42101777223831693, -0.3445524326410147, -0.271052411408202, -0.2015284179393367, -0.13682737527175895, -0.07760931840827454, -0.024329646057877102, 0.022772810340654846, 0.06368158900239348, 0.0986021207389807, 0.12795498589995635, 0.15236308269428944, 0.17263304370716073, 0.189731388302032, 0.20475603707934756, 0.21890393712654235, 0.23343565031433222, 0.24963783872436665, 0.2687846393304249, 0.2920989527940523, 0.32071467780594404, 0.3556409025942357, 0.3977290194815668, 0.44764365780833854, 0.505838236879769, 0.5725358261520923, 0.6477158674867888, 0.7311071672650493, 0.8221874081348781, 0.920189265109636, 1.0241130427826564, 1.1327455837817872, 1.2446850374501357, 1.358370926165694, 1.4721188085331463, 1.584158717400642, 1.6926764493623674, 1.7958567037030817, 1.8919270146648166, 1.9792013929013157, 2.0561225908198733, 2.121301932314508, 2.1735556996204637, 2.211937147462354, 2.235763315492257, 2.244635931802416, 2.2384558401067993, 2.217430537621603, 2.182074575972434, 2.13320274957489, 2.0719161706575218, 1.9995815031321578, 1.917803794608986, 1.8283935028841605, 1.733328456318828, 1.6347116131380417, 1.5347255896902245, 1.4355850095062732, 1.3394877815342585, 1.2485664457702033, 1.1648407268797323, 1.090172411206902, 1.026223610366376, 0.9744193966499852, 0.9359156936154872, 0.9115731819200134, 0.9019378386950353, 0.9072285719697158, 0.9273322436406278, 0.9618061993393922, 1.009888245522529, 1.0705138375275736, 1.142340071498484, 1.2237759121326062, 1.3130179410489105, 1.4080907807916774, 1.5068912402071029, 1.6072351407999372, 1.7069057227630098, 1.80370249512365, 1.895489387663093, 1.9802410830594852, 2.056086455527678, 2.121348115862228, 2.1745771603866673, 2.2145823404377434, 2.240453006710124, 2.2515753356448847, 2.247641509287421, 2.228651691617524, 2.1949088190429755, 2.147006396257108, 2.08580965673597, 2.012430605680874, 1.9281976083293069, 1.8346203147332154, 1.7333508202361418, 1.6261420463689447, 1.5148043876937005, 1.401161704837051, 1.2870077517985414, 1.1740641064934145, 1.0639406279606292, 0.9580993929561025, 0.8578229706020404, 0.764187778795607, 0.678043133128785, 0.5999964515115688, 0.5304049192554717, 0.4693737540591103, 0.4167610423010534, 0.37218895150548564, 0.33506096297587484, 0.30458461741315657, 0.2797991286203426, 0.2596070995734771, 0.24280947420881802, 0.22814277973365754, 0.2143176600436247, 0.20005767223972237, 0.18413731595511862, 0.16541828923471225, 0.14288301440776643, 0.11566455145898434, 0.08307211292779616, 0.04461151087734342, 4.446490257965823e-16], [-0.0, -0.053294846070557046, -0.11253263590053943, -0.17722243496677328, -0.24667067906534323, -0.3200002133370844, -0.3961745880282651, -0.4740269717272567, -0.5522929208747923, -0.6296461417864726, -0.7047363008732069, -0.7762278822673765, -0.8428390611240805, -0.9033795562905182, -0.9567864479822134, -1.002156994064985, -1.0387775513538378, -1.0661478042151857, -1.0839996193257921, -1.0923099798054818, -1.0913076007546414, -1.0814729877766684, -1.063531866358923, -1.038442078855845, -1.0073742130244314, -0.9716863873982844, -0.9328937701828717, -0.892633545982845, -0.8526261650387913, -0.8146338096860893, -0.7804170898831324, -0.7516910318859971, -0.7300814500835253, -0.7170827909138809, -0.7140185095951936, -0.7220049857259547, -0.7419199039125383, -0.7743759223569342, -0.8197003282661826, -0.8779212370266531, -0.9487607357705611, -1.0316352050618864, -1.1256628790271699, -1.2296785286053424, -1.3422549790060982, -1.461731005221934, -1.5862449926603122, -1.7137736075245054, -1.8421745970032892, -1.9692327357255583, -2.092707854880104, -2.2103838359024244, -2.3201174230729986, -2.4198857094792454, -2.507831178611832, -2.5823032387609457, -2.6418952680504026, -2.685476292464723, -2.7122165450680886, -2.7216062987415053, -2.713467523683108, -2.68795809076954, -2.645568418538279, -2.587110640727854, -2.5137005486495623, -2.426732733849635, -2.327849517395085, -2.2189043987728154, -2.1019208862730694, -1.9790476787135176, -1.8525112528426626, -1.7245669697095793, -1.5974498452987007, -1.473326135060518, -1.354246858558432, -1.2421043399151088, -1.1385927633590334, -1.0451736428571636, -0.9630469830691655, -0.8931287686937607, -0.8360352641645084, -0.7920744394207355, -0.7612446642243829, -0.7432406374764672, -0.7374663435287871, -0.7430546588615077, -0.7588930738276058, -0.783654849319026, -0.8158348007058479, -0.853788794322406, -0.8957759576952141, -0.9400025456248543, -0.984666371522817, -1.028000707783881, -1.0683165804916301, -1.1040424317823179, -1.133760196448324, -1.1562369359400684, -1.17045129034348, -1.175614144174645, -1.1711830515126216, -1.1568701263027588, -1.132643270566167, -1.0987207825512337, -1.0555595543129825, -1.003837229614596, -0.9444288443794644, -0.8783786094093534, -0.8068676153052792, -0.7311783395017427, -0.6526569125838877, -0.5726741537062259, -0.4925864116964288, -0.41369724868587443, -0.3372209769039334, -0.26424900731452744, -0.19571989241704005, -0.132393846747184, -0.07483240992794245, -0.0233837815658374, 0.02182579168376933, 0.06089435515793653, 0.0941402538068797, 0.12209191649232232, 0.14547168790945506, 0.1651741350135248, 0.18223939989256382, 0.1978223015250419, 0.21315800147222394, 0.22952514040565195, 0.24820742110764746, 0.27045465743467134, 0.2974443265526399, 0.33024465304702555, 0.36978021845299053, 0.4168010291795215, 0.471855891196802, 0.5352708333045121, 0.6071331949419118, 0.6872818524685759, 0.7753039031795831, 0.8705379628857738, 0.9720840647803619, 1.078819978744836, 1.1894236054565284, 1.3024009427985312, 1.4161189771010474, 1.5288427223341183, 1.638775519817265, 1.7441016221399188, 1.8430300200917522, 1.9338384321858346, 2.0149163638856264, 2.0848061583221082, 2.1422410018382574, 2.1861789151848265, 2.215831853028074, 2.2306891484225235, 2.2305346723025776, 2.2154572276204734, 2.1858538598625215, 2.1424259363505187, 2.0861680218006207, 2.018349752769749, 1.940491084562439, 1.8543314466856613, 1.7617934930128873, 1.6649422667387634, 1.5659407146490252, 1.467002577349741, 1.3703437495906916, 1.2781332459787658, 1.19244492115139, 1.1152110794804195, 1.04817906790001, 0.9928718774659527, 0.9505536863808258, 0.9222011616902567, 0.9084812014604983, 0.9097356472639403, 0.9259733319129326, 0.9568696535970167, 1.0017736891169393, 1.0597226801085715, 1.1294635513578115, 1.2094809537721336, 1.298031170341217, 1.39318108523171, 1.4928512973689638, 1.5948623633344878, 1.696983082477564, 1.7969796915256695, 1.892664817756633, 1.9819450493701858, 2.062866018790217, 2.133653958290343, 2.192752775961582, 2.238855811421029, 2.2709315620260124, 2.2882428184563777, 2.2903588096981666, 2.27716012773076, 2.2488363773951865, 2.20587667269923, 2.149053272884506, 2.079398815730314, 1.9981777577916051, 1.9068527678584024, 1.80704693757027, 1.700502768985287, 1.5890389706962178, 1.474506140115706, 1.3587424287666106, 1.2435302794296896, 1.1305552891089359, 1.0213681909334618, 0.9173508629230541, 0.8196871642031687, 0.7293392725107716, 0.6470300539080552, 0.5732318401348366, 0.5081618249064512, 0.4517841218325655, 0.40381835772774866, 0.3637545101393728, 0.33087354105745226, 0.30427323390911154, 0.2828985116847357, 0.26557540360348314, 0.25104773883571957, 0.23801558064721687, 0.22517437450413436, 0.21125377013022686, 0.19505509052845796, 0.1754864601906527, 0.15159466908517938, 0.12259293686679137, 0.08788385083802187, 0.04707687871893102, 4.678182516238676e-16], [-0.0, -0.055734257050528015, -0.11724782139805347, -0.18394119994047797, -0.2550208852029298, -0.32952150188516877, -0.4063328914946498, -0.48423141989954255, -0.5619146808678058, -0.6380386779759757, -0.7112564999965387, -0.7802574627393721, -0.8438056744326641, -0.900776992524103, -0.9501933770347123, -0.991253708410246, -1.0233602246491291, -1.0461398411959222, -1.0594597449766443, -1.06343679783243, -1.0584404408894759, -1.04508895617724, -1.0242391109444215, -0.9969693793773295, -0.9645571015405109, -0.9284500961729169, -0.8902333885211924, -0.8515918430104745, -0.8142695999675078, -0.780027303018925, -0.7505981669297046, -0.7276439728637415, -0.7127120883228971, -0.7071945920039241, -0.7122905398338406, -0.7289723385036839, -0.7579570985659004, -0.7996837228464788, -0.8542963503563694, -0.921634624358077, -1.001231089445537, -1.0923158504329546, -1.1938284497387495, -1.3044367441201652, -1.4225623903906457, -1.5464123873586144, -1.6740159716759546, -1.8032660322813732, -1.9319640949708676, -2.0578678381447877, -2.1787400352351067, -2.2923977803649542, -2.396760842440728, -2.4898980094551195, -2.5700703289309157, -2.635770221127899, -2.68575553718337, -2.7190777524649237, -2.73510362323113, -2.7335297888859125, -2.7143899689366684, -2.6780545791743, -2.6252227713234015, -2.5569070800939793, -2.4744110368339007, -2.379300275573411, -2.2733678111218767, -2.158594306286751, -2.037104262904832, -1.9111191663597404, -1.7829086833186647, -1.6547410558765097, -1.5288338511226118, -1.4073062129958276, -1.292133723506667, -1.185106913995454, -1.0877943757295736, -1.0015113050979676, -0.9272941847660167, -0.8658821517227727, -0.8177054398978857, -0.782881112971014, -0.7612161263736206, -0.75221758062877, -0.7551098554234204, -0.7688581493845842, -0.7921977984471741, -0.8236686096564468, -0.8616533305372335, -0.9044192795970822, -0.9501620933691267, -0.9970505012929082, -1.043271022679291, -1.0870714903386445, -1.1268023428204084, -1.1609546905976207, -1.1881942492704716, -1.2073903426948072, -1.217639308058357, -1.218281780048964, -1.208913488714315, -1.1893893714315567, -1.159820969417536, -1.1205672491510492, -1.0722191546918645, -1.01557835402984, -0.9516307873621969, -0.8815157539771098, -0.8064913840226561, -0.7278974291533634, -0.6471163697169218, -0.5655338742221191, -0.48449965841123555, -0.40528977610829414, -0.3290713325624214, -0.256870544347685, -0.18954497974406845, -0.12776070222443903, -0.07197491005599826, -0.02242452039689152, 0.02087900968938332, 0.058148496202599924, 0.08981351259864742, 0.11650674857612162, 0.1390446065399292, 0.1584025500529687, 0.17568585649101962, 0.19209654738826396, 0.20889737151116278, 0.22737379493181314, 0.24879500725422776, 0.2743749822558262, 0.30523463376734294, 0.3423660835204939, 0.38660000750800017, 0.43857695234616134, 0.4987234150542284, 0.5672333609969553, 0.6440557184279047, 0.728888237519537, 0.8211779407340173, 0.9201282239073892, 1.024712497689857, 1.133694091271458, 1.245651978848269, 1.3590117381249065, 1.4720810131302944, 1.5830886342258077, 1.6902264494564558, 1.7916928458750327, 1.885736889122033, 1.9707019857132366, 2.045067975857433, 2.1074905952087364, 2.1568373010844795, 2.1922185410229456, 2.2130136471581303, 2.2188906662124626, 2.209819578895241, 2.1860785206417344, 2.1482527840749226, 2.097226558194967, 2.034167535815843, 1.9605046948329592, 1.8778997262321582, 1.7882127382076818, 1.6934630074739834, 1.5957856723198167, 1.4973853640907602, 1.4004878520480823, 1.3072908289684195, 1.2199149900850457, 1.1403565553576898, 1.0704423546064306, 1.011788537453669, 0.9657638866484284, 0.9334586061969624, 0.9156593273732908, 0.9128309292363631, 0.9251056092851262, 0.9522794682454522, 0.9938166948726875, 1.0488612563992552, 1.1162558222402392, 1.1945674771190895, 1.2821196190573, 1.3770292915896023, 1.4772490716642903, 1.5806125280647219, 1.6848821824182971, 1.7877988479330804, 1.8871311912759052, 1.9807243611672223, 2.0665465533219307, 2.142732434633029, 2.207622428631286, 2.259796967280763, 2.29810493852665, 2.3216857016168304, 2.329984199548158, 2.3227588661619745, 2.300082200290983, 2.262334056643399, 2.210187878451119, 2.1445902660137355, 2.0667344340083127, 1.9780282549390513, 1.8800577128628324, 1.7745466974835116, 1.6633141513171046, 1.5482296399314714, 1.4311684459282643, 1.3139672906936044, 1.1983817640078585, 1.0860464910596184, 0.9784389906002339, 0.8768480788712563, 0.7823475540810184, 0.6957757586514021, 0.617721464688261, 0.5485163659811356, 0.4882342913930278, 0.4366970839899772, 0.393486921956499, 0.3579646954564496, 0.32929390217049714, 0.3064693870425601, 0.28835013220678535, 0.2736952041045069, 0.2612018888765951, 0.24954499608842265, 0.23741628594286826, 0.2235629769342072, 0.2068243192938917, 0.18616527381163236, 0.16070641426653684, 0.12974927274564263, 0.09279646797166102, 0.04956609432271983, 4.909565874815401e-16], [-0.0, -0.0581230653712635, -0.12180899817176649, -0.19035342767092991, -0.262868384560535, -0.3383073981366598, -0.4154951659253733, -0.4931610100415807, -0.5699752340758651, -0.644587416432478, -0.7156656227909461, -0.7819354931133775, -0.8422181580949477, -0.8954659662094685, -0.9407950549144855, -0.9775138768711408, -1.0051468922957676, -1.0234527593052167, -1.032436492340255, -1.032355211001156, -1.0237172640990844, -1.0072746823453032, -0.9840090836351781, -0.9551113230471158, -0.9219553412305942, -0.8860668157221742, -0.849087356082349, -0.8127351021231254, -0.778762681871289, -0.748913559778644, -0.7248778541220492, -0.70824872423674, -0.7004804225631834, -0.7028490735072374, -0.7164171815423354, -0.7420027862096624, -0.7801540737164245, -0.8311301262914936, -0.8948883444467967, -0.9710789173664699, -1.0590465467111774, -1.157839453345309, -1.2662255191868461, -1.382715241906704, -1.5055910128687329, -1.6329420726378068, -1.7627043574559262, -1.892704327793694, -2.0207057694724617, -2.144458481438286, -2.2617477139782918, -2.370443198290136, -2.468546613460348, -2.5542363700052615, -2.6259086494197104, -2.682213725236697, -2.722086700865109, -2.744771930298504, -2.7498405365136076, -2.737200605399465, -2.7070998064214735, -2.660120370718132, -2.5971665385897382, -2.5194447669606914, -2.428437159037495, -2.3258687388709802, -2.213669338964985, -2.0939309959249552, -1.9688618543357905, -1.8407376600556602, -1.7118519789644375, -1.5844663046036722, -1.4607612174573334, -1.342789729903065, -1.232433894854588, -1.1313656742268554, -1.0410129576288525, -0.9625314947497214, -0.8967833598925463, -0.8443224076079855, -0.80538700831653, -0.7799001763677738, -0.7674770245003152, -0.7674393025125242, -0.7788366084424755, -0.800473701822972, -0.8309432044892293, -0.8686628484679957, -0.9119163257082216, -0.9588967133363805, -1.0077513926547506, -1.0566273515317415, -1.1037157587748243, -1.1472947254614214, -1.1857692212844062, -1.2177071923390839, -1.2418710284068342, -1.2572436500721644, -1.2630486258336404, -1.258763883194046, -1.2441287416600153, -1.219144165521559, -1.184066305952018, -1.139393571070128, -1.085847624911424, -1.0243488677189163, -0.9559870868135931, -0.8819880861480708, -0.8036772005425223, -0.7224406751415741, -0.6396859399945223, -0.5568018326634883, -0.47511981788261104, -0.3958772226798488, -0.3201834488558067, -0.24899004376623465, -0.18306540706381288, -0.12297478806785403, -0.06906608888850382, -0.02146183588982898, 0.019942479585925633, 0.05547365698461408, 0.08566977200211627, 0.11126318892849597, 0.13315805340741615, 0.15240286388443086, 0.17015884947370366, 0.18766499284940913, 0.20620062623796173, 0.2270465943606105, 0.2514460185587998, 0.28056571027125654, 0.31545926913140726, 0.35703286150111574, 0.40601461020513785, 0.46292843717874815, 0.5280730898929149, 0.6015069525325554, 0.6830390972120549, 0.7722268726581037, 0.8683801617249437, 0.9705722689957816, 1.07765722984008, 1.188293166915964, 1.3009711634018408, 1.4140489781748045, 1.525788800380808, 1.6343981326184949, 1.7380728060601733, 1.8350410694825727, 1.923607658993295, 2.0021967471839024, 2.069392689811529, 2.123977534520084, 2.1649643284985576, 2.1916253586286945, 2.203514576282091, 2.20048359662194, 2.182690815702558, 2.150603354097696, 2.10499170917894, 2.0469171752549875, 1.9777122672180842, 1.8989545547783615, 1.8124344765697842, 1.7201178523700766, 1.6241039436985465, 1.5265800248584105, 1.4297735152827764, 1.335902787598615, 1.2471278025282715, 1.1655017306503528, 1.0929247018690775, 1.0311007766097553, 0.9814991593654527, 0.9453205770140769, 0.9234696236667357, 0.9165337336082952, 0.9247692875433846, 0.9480951886564059, 0.9860940680281424, 1.0380210980242741, 1.1028202117806862, 1.1791473512451445, 1.2654001996655675, 1.3597537009895533, 1.4602005320834675, 1.564595577304151, 1.6707033615785405, 1.776247330018368, 1.8789598208508447, 1.9766315650555546, 2.067159560852273, 2.1485922136845175, 2.219170701510332, 2.277365619313646, 2.3219080734451336, 2.3518145327998603, 2.366404896567942, 2.365313403587624, 2.3484921821175266, 2.316207416854968, 2.269028287892508, 2.2078090096686633, 2.1336644625941426, 2.0479400619080796, 1.9521766437485162, 1.848071264129294, 1.73743489971733, 1.6221481077770286, 1.5041157447853033, 1.3852218580696642, 1.267285852108001, 1.1520209912611694, 1.0409962347681339, 0.9356023095437306, 0.8370228140058378, 0.7462110146887923, 0.6638728501100449, 0.5904564969700389, 0.5261486862962725, 0.4708777858000567, 0.42432349379400197, 0.3859328237957552, 0.35494190156893124, 0.3304029517460677, 0.3112157229342629, 0.29616249149939466, 0.28394569774191486, 0.2732272060372146, 0.2626681442236482, 0.2509682679380298, 0.2369038129066604, 0.21936284190886396, 0.19737716208639838, 0.17014998068900455, 0.13707858084900407, 0.09777143066292959, 0.052059285367366454, 5.138764760463572e-16], [-0.0, -0.06044143155310596, -0.1261778823891616, -0.19640478415747814, -0.2701461107927795, -0.346282240697375, -0.42358198155992494, -0.5007379076220282, -0.5764040709905911, -0.6492350843602732, -0.7179255339095421, -0.7812486691746771, -0.8380933317269005, -0.8874981261380742, -0.9286819040085379, -0.9610697230889357, -0.9843135564936151, -0.9983071588645445, -1.0031946438110546, -0.9993724863340259, -0.9874848312502787, -0.9684121596648435, -0.9432535359955486, -0.9133028236423291, -0.8800194139328219, -0.8449941565044656, -0.8099113061568496, -0.776507408191085, -0.7465281285995943, -0.7216840949937434, -0.7036068472861595, -0.693806002962097, -0.6936287200409351, -0.7042224919911731, -0.7265022340420784, -0.7611225213024416, -0.8084557182276797, -0.8685765991937303, -0.9412539046387899, -1.0259491102127953, -1.1218225117193523, -1.2277465506328662, -1.3423261280043979, -1.463925482995901, -1.5907010503426258, -1.72063956274663, -1.8516005332307095, -1.9813621420918597, -2.1076694660453548, -2.2282839256338147, -2.341032792554447, -2.4438575921328836, -2.534860257957285, -2.6123459452032547, -2.674861485268408, -2.7212285651817463, -2.7505708384347356, -2.762334316425674, -2.756300548166918, -2.7325922664339166, -2.6916713569957205, -2.634329189622417, -2.561669530789827, -2.475084433989107, -2.376223670019375, -2.266958412548826, -2.149340029860172, -2.025554948758862, -1.897876648332342, -1.7686159073914944, -1.6400704684168046, -1.5144752917504005, -1.3939545563902098, -1.2804765185149527, -1.1758122669423188, -1.081499317893873, -0.998810872113552, -0.9287314185161489, -0.8719392135559627, -0.8287959982241944, -0.7993441391211734, -0.7833112007163999, -0.7801217771025909, -0.7889162376460955, -0.8085758761828686, -0.8377538018208418, -0.8749107746678361, -0.9183550751683159, -0.9662854039582949, -1.0168357424218202, -1.068121064017025, -1.1182827738361005, -1.1655327689903776, -1.208195054800681, -1.244743920281873, -1.2738377692510237, -1.2943478181744459, -1.3053810056726862, -1.30629660803242, -1.2967162163564152, -1.2765269000574384, -1.2458775540241864, -1.2051685986326055, -1.1550353685490677, -1.0963256838122497, -1.0300722410677992, -0.957460590479115, -0.8797935715901711, -0.7984531666172286, -0.7148607902099078, -0.6304370691840754, -0.5465621732817695, -0.4645377385256488, -0.3855513787555165, -0.31064470967468155, -0.2406857150411637, -0.17634616894666658, -0.11808469439436965, -0.06613589002604282, -0.02050579763625605, 0.01902618290587944, 0.05289899331197486, 0.08175546000346538, 0.10642207059409882, 0.12788352457178767, 0.14725273614149423, 0.165737086969941, 0.18460182596565372, 0.20513158969692658, 0.2285910686347846, 0.25618586977275176, 0.2890246246444444, 0.32808336333474725, 0.3741731204387458, 0.4279116594034154, 0.4897000992567062, 0.5597051049321938, 0.6378471622956026, 0.7237953050728061, 0.8169684970194682, 0.9165437029696677, 1.0214705111172893, 1.1304920003298649, 1.2421713847201545, 1.3549238171896156, 1.467052598025259, 1.5767889173280247, 1.6823341640766267, 1.7819037624601175, 1.8737714496298274, 1.9563128894757682, 2.028047525004057, 2.087677607276435, 2.1341234008840813, 2.1665536531152885, 2.1844105242608545, 2.1874283072246645, 2.1756454125990685, 2.1494092570194896, 2.109373863977513, 2.056490163145152, 1.9919891522981847, 1.9173582607389836, 1.8343114203944426, 1.7447535063667559, 1.6507399487865866, 1.554432438878578, 1.4580517511800448, 1.3638287783721879, 1.2739549233080105, 1.1905330133146779, 1.1155298941520353, 1.0507318252560123, 0.9977037349069181, 0.9577533052304551, 0.9319007445870664, 0.9208549716398174, 0.9249967844325377, 0.9443694228159666, 0.9786767575332309, 1.0272891584683599, 1.0892569123674452, 1.1633308811914675, 1.2479899205089307, 1.34147441716114, 1.4418251607252015, 1.5469266375725603, 1.6545537326216597, 1.7624207447193203, 1.8682315688618152, 1.9697298734399884, 2.064748103941318, 2.1512541759496293, 2.227394779045486, 2.2915342978524693, 2.342288464889707, 2.378551989390946, 2.3995195536348897, 2.4046997299643516, 2.3939215435736574, 2.3673335840889695, 2.3253957485878383, 2.2688638756018658, 2.1987676994943373, 2.116382713259439, 2.0231966713911302, 1.9208715895370532, 1.8112022011686097, 1.6960719109843856, 1.5774073383401304, 1.4571325704288767, 1.337124243658252, 1.2191685428133658, 1.104921151961681, 0.9958711101197377, 0.893309420555511, 0.7983031379090973, 0.7116755152480367, 0.6339926373261664, 0.5655568006155377, 0.5064067292947492, 0.4563245436024955, 0.4148492271254978, 0.38129617692617523, 0.35478226898071935, 0.33425573495700206, 0.3185300282960812, 0.3063207607870086, 0.29628471771978704, 0.2870599120461771, 0.27730561691202577, 0.2657413219187123, 0.25118359131599705, 0.23257986114071624, 0.2090382955610613, 0.1798529282174474, 0.14452343946316937, 0.10276906190569435, 0.05453626092757246, 5.363898026253207e-16], [-0.0, -0.06266991286827096, -0.13031748700477427, -0.2020436008934985, -0.27679144864584915, -0.35337695428452426, -0.43052289796710813, -0.5068958462035661, -0.581144903095905, -0.6519412497440669, -0.7180174155098008, -0.7782052284350124, -0.8314714227170804, -0.8769499380151323, -0.9139700271005184, -0.9420793929465843, -0.9610617011749919, -0.9709479557234, -0.9720213811225175, -0.9648156199729033, -0.9501062249476203, -0.9288955966240398, -0.9023916873360074, -0.8719809527748246, -0.8391961831684808, -0.8056799807260256, -0.7731447662139025, -0.7433302920597119, -0.7179597098165684, -0.6986952843249193, -0.6870948642781041, -0.6845702086067554, -0.6923482303069712, -0.7114361548946355, -0.7425915010850567, -0.7862976787131234, -0.8427458660409228, -0.9118236786730377, -0.9931109789709744, -1.0858830021239352, -1.1891207971319075, -1.3015288022641147, -1.4215591994757575, -1.5474425251226533, -1.6772238592439634, -1.8088037765348168, -1.9399831223650859, -2.068510579808464, -2.192131921072031, -2.3086397907987566, -2.415922850638966, -2.512013124754383, -2.595130424336379, -2.6637227949037943, -2.7165020215395472, -2.752473342141168, -2.7709586544310354, -2.7716126556185934, -2.7544315205193484, -2.719753900564102, -2.6682542081863145, -2.600928334130586, -2.519072124829234, -2.424253118779121, -2.3182762006395103, -2.2031439756803137, -2.0810127917438095, -1.9541454380216334, -1.8248616272227136, -1.6954874182546533, -1.5683047591567383, -1.4455023241849339, -1.3291287848353797, -1.2210495930710266, -1.122908267625947, -1.0360930631752017, -0.9617097701247868, -0.9005612430569316, -0.8531340921497675, -0.8195927982057686, -0.7997813325359383, -0.7932321822564378, -0.7991825039847292, -0.8165969588127102, -0.8441966229321824, -0.8804932252471159, -0.9238278391926186, -0.9724130537839519, -1.0243775710847067, -1.0778121256495217, -1.1308155972501366, -1.1815401918412902, -1.2282345970810404, -1.269284076918826, -1.3032465532717303, -1.3288838294680394, -1.3451872372219849, -1.3513971331870163, -1.3470158289706546, -1.3318137059059323, -1.3058284386577264, -1.2693574255673046, -1.2229436941588996, -1.167355713193972, -1.1035616940047468, -1.0326990998105972, -0.9560401989518647, -0.8749545935743773, -0.7908697269196633, -0.7052304182804784, -0.6194584937764395, -0.534913572971867, -0.45285603626262205, -0.3744131368431685, -0.3005491355233024, -0.23204022890263845, -0.1694549141925335, -0.11314029054896041, -0.06321464080044707, -0.019566472890052887, 0.018139968619152725, 0.05045287970924991, 0.07811508638384126, 0.10204072664021516, 0.12328704932966787, 0.1430220825068906, 0.16248903281832694, 0.18296836439311545, 0.20573856835715412, 0.2320366708794679, 0.2630195376197676, 0.2997270152911731, 0.34304790717955735, 0.39368970994087893, 0.45215294554695484, 0.5187108071894081, 0.5933947041484361, 0.6759861414303141, 0.7660152091102214, 0.8627657878182966, 0.9652874049093128, 1.072413504884679, 1.1827857318991164, 1.2948836658700418, 1.4070593107741607, 1.5175755077951776, 1.6246473402928088, 1.7264855148115341, 1.8213406446863365, 1.9075473317581533, 1.9835669381502408, 2.0480279641612147, 2.0997629995954994, 2.137841293094696, 2.16159608542246, 2.170645975755354, 2.16490973186241, 2.1446141121650295, 2.110294436218161, 2.0627878160129502, 2.003219139350132, 1.9329800739686822, 1.8537015327582007, 1.767220201991577, 1.675539882083374, 1.5807885202421972, 1.485171923306025, 1.3909252243025285, 1.3002632357125297, 1.2153308545189363, 1.1381546880479088, 1.0705970451993698, 1.0143133854608202, 0.9707142393251532, 0.9409325102682221, 0.9257969427695898, 0.9258123960135289, 0.9411474023913, 0.9716293176323819, 1.0167471895043618, 1.075662288909879, 1.147226065326554, 1.2300051123055695, 1.3223125624522871, 1.422245179001261, 1.5277252764687317, 1.636546489185448, 1.746422316535282, 1.8550363096230715, 1.9600927274063473, 2.0593664819157333, 2.1507512122312393, 2.2323043748515428, 2.302288312783163, 2.3592063652246558, 2.401833201659294, 2.429238705483026, 2.440804889497797, 2.436235494822225, 2.4155581018526138, 2.3791187625008954, 2.3275693426170236, 2.261847937876612, 2.1831528912235934, 2.092911091189467, 1.9927413643944756, 1.8844138890337692, 1.7698066464364335, 1.6508599927098935, 1.529530470529395, 1.4077449914525342, 1.28735650157045, 1.1701021983785103, 1.057565295665565, 0.9511412378316584, 0.8520091477993018, 0.7611091565682014, 0.6791261109255518, 0.6064799926869969, 0.5433232122104064, 0.48954476507605155, 0.4447810681144469, 0.4084331237005504, 0.37968950358877684, 0.3575544994572997, 0.34088066033609427, 0.32840483034986584, 0.31878671634068506, 0.3106489559944567, 0.30261762450088997, 0.2933621122860963, 0.2816333280470238, 0.26629922958194363, 0.2463767584787297, 0.22105935168650975, 0.1897393208638449, 0.15202452615257733, 0.1077489212079862, 0.05697670710005489, 5.583097389795766e-16], [-0.0, -0.06478965750891556, -0.13419249570529493, -0.2072214044162032, -0.28274688592305464, -0.3595297829479074, -0.4362572306884942, -0.5115808745169638, -0.5841563339137102, -0.6526828582606127, -0.7159421121794391, -0.7728350474032438, -0.8224158642575436, -0.8639221375752112, -0.8968002774985984, -0.9207256127555727, -0.9356165197101662, -0.9416421713893782, -0.9392236429947741, -0.9290282800477273, -0.9119574080266232, -0.8891276337848131, -0.8618461548655199, -0.8315806488626764, -0.7999244572603199, -0.7685579030997621, -0.7392066861821046, -0.7135983806304278, -0.6934181154022069, -0.6802645472780919, -0.675607237143961, -0.6807465139024851, -0.6967768566633746, -0.7245547462115909, -0.764671833032622, -0.8174341438784263, -0.8828479050236792, -0.9606124014932866, -1.0501201215233766, -1.150464258518787, -1.2604534631421336, -1.378633560338997, -1.5033157744618995, -1.6326108444496785, -1.7644682642470626, -1.8967197549615236, -2.027125967861738, -2.1534253339163074, -2.273383918258624, -2.3848451082113407, -2.4857779621032083, -2.5743230731582014, -2.6488348576282514, -2.7079192577891185, -2.7504659564822656, -2.7756743280165233, -2.7830724973502248, -2.7725290419976183, -2.74425704510215, -2.698810389369156, -2.6370723656467057, -2.560236852409531, -2.4697824987983417, -2.3674405099049367, -2.255156784634058, -2.1350492900304685, -2.0093616681916475, -1.8804141600723814, -1.7505529924975793, -1.622099409043815, -1.4972995313190258, -1.3782762144490335, -1.2669840098575225, -1.1651682709745772, -1.0743293352544896, -0.9956925913582176, -0.9301850966343969, -0.8784192506574594, -0.8406838594725143, -0.816942746558125, -0.8068408847308963, -0.8097178427320689, -0.8246281654678619, -0.8503681420857973, -0.8855082652687205, -0.9284305519746573, -0.9773697835597891, -1.0304576344889105, -1.0857685957706846, -1.1413665633243177, -1.195350953486352, -1.2459012279056938, -1.291318757562328, -1.3300650293128802, -1.3607952963012695, -1.382386893264272, -1.393961576165962, -1.3949013992089825, -1.3848578072225715, -1.3637537935719295, -1.331779148755472, -1.2893789983790296, -1.2372359968883988, -1.176246701128602, -1.10749279156222, -1.0322079352592382, -0.9517411904493708, -0.8675179349088975, -0.7809993577272314, -0.6936415846878219, -0.6068555108968355, -0.5219683903797488, -0.44018818180429475, -0.362571573610452, -0.28999651260019566, -0.22313994001250353, -0.16246130135337672, -0.10819224428013169, -0.06033275652255927, -0.01865382728656752, 0.01729345489127717, 0.04816262296046348, 0.07479078740571955, 0.09817239478092779, 0.11942849209810925, 0.13977231852909106, 0.1604721429300855, 0.18281233924283113, 0.2080537399771576, 0.2373943294946023, 0.2719313331172067, 0.31262572529090316, 0.36027012093266103, 0.4154609301415395, 0.4785755497397262, 0.5497552382896936, 0.6288941774759154, 0.7156350656426718, 0.8093714227827856, 0.9092566145566877, 1.0142194303070762, 1.1229858808711644, 1.2341067205512446, 1.3459900479710154, 1.4569382065178067, 1.5651880900649717, 1.668953866630699, 1.7664710639630166, 1.8560409185463946, 1.9360738743535466, 2.0051311302890094, 2.0619631754691103, 2.1055443183488496, 2.1351023076673608, 2.1501422580393768, 2.150464227996207, 2.1361739500955794, 2.1076863776697903, 2.0657218868263802, 2.0112951511809047, 1.9456968860849877, 1.8704688343921332, 1.787372532746439, 1.6983525518488922, 1.6054950423175698, 1.51098253616966, 1.4170460496542878, 1.325915603749837, 1.2397703223143306, 1.1606892835108584, 1.0906042872755322, 1.0312556605083216, 0.984152153295483, 0.9505358854352757, 0.931353185088516, 0.9272320233395969, 0.9384665931686642, 0.9650094125627106, 1.00647115332808, 1.0621282139369594, 1.130937870900298, 1.2115606631805897, 1.3023894924181132, 1.4015847624207212, 1.5071147383341157, 1.6168001826413203, 1.7283622246273493, 1.8394723446207315, 1.9478033060029056, 2.0510798478128436, 2.1471279592306614, 2.2339215940631014, 2.3096257476422632, 2.3726349086826093, 2.4216060123840273, 2.4554851556085437, 2.4735274869759274, 2.475309850476612, 2.4607359366138297, 2.4300338758551856, 2.383746390866686, 2.3227138021738183, 2.2480503521935242, 2.1611144708581502, 2.063473748461803, 1.956865504453574, 1.8431539417163993, 1.724284951995508, 1.6022396877823522, 1.478988037981501, 1.356443138637262, 1.2364180161175957, 1.1205853993760333, 1.010441651834013, 0.9072756642641684, 0.8121434205968975, 0.7258488021009619, 0.6489310356028813, 0.5816590223308516, 0.5240326098403888, 0.47579069466024504, 0.4364258721561204, 0.40520518691235985, 0.3811963857371335, 0.36329893995558304, 0.35027898731781976, 0.340807249479916, 0.3334989109266716, 0.3269544010932126, 0.31980000435293454, 0.31072723283719217, 0.298529934415221, 0.2821381715899168, 0.2606479949017701, 0.23334634441410523, 0.19973044215790695, 0.15952118374138136, 0.11267019497508353, 0.05936038531830274, 5.794525877546376e-16], [-0.0, -0.06678259417549484, -0.1377696226555108, -0.21189341737723294, -0.28796061858074495, -0.3646869546261853, -0.4407347248573425, -0.5147519845380502, -0.5854123845017203, -0.6514545986016786, -0.7117202798525157, -0.7651895211435653, -0.8110128577330438, -0.8485389348795848, -0.877337072794691, -0.89721408988968, -0.908224890823075, -0.910676484482698, -0.9051252647802505, -0.8923675597788274, -0.873423627869756, -0.8495154490970711, -0.8220388210163748, -0.7925304175851756, -0.7626306027266397, -0.7340429039928433, -0.7084911432591026, -0.6876752882411828, -0.6732271290857049, -0.6666668972403645, -0.6693619288475812, -0.6824884323012114, -0.7069973503285492, -0.7435852126428611, -0.7926707581157394, -0.8543779683755569, -0.9285260010822963, -1.0146263446138415, -1.111887340605867, -1.2192260410246472, -1.3352871866477019, -1.4584689184198831, -1.5869546664820253, -1.7187505078679708, -1.8517271467571481, -1.9836655541725938, -2.1123052100577704, -2.2353938221167517, -2.3507373544065366, -2.4562491855075144, -2.549997231555334, -2.6302479131790237, -2.695505916443833, -2.7445487945596785, -2.7764555770726904, -2.790628693619624, -2.786808676700651, -2.7650812785028624, -2.7258768164454414, -2.6699617464538106, -2.5984226475221535, -2.51264298140235, -2.414273162875923, -2.3051946348488865, -2.1874787845952928, -2.0633416594106215, -1.9350955387613629, -1.805098493338303, -1.675703107470542, -1.5492055590339058, -1.4277962398877178, -1.3135130602964797, -1.2081985137362317, -1.1134614856178622, -1.0306446730819432, -0.9607983460055903, -0.9046610250875091, -0.8626474851386018, -0.834844314622026, -0.8210130804028596, -0.8206009640426731, -0.832758557274529, -0.8563643338805215, -0.8900551572170694, -0.9322620409289046, -0.981250258389345, -1.0351627970378507, -1.0920660794282067, -1.149996825201779, -1.2070089084462083, -1.2612190733860758, -1.3108504077752903, -1.3542725367274757, -1.390037588371951, -1.4169110943782033, -1.433897120204404, -1.4402570685564073, -1.4355217612424804, -1.4194965753102016, -1.3922595847749235, -1.354152835005219, -1.305767048533075, -1.2479202244283953, -1.1816307443594058, -1.1080857333106402, -1.0286055383173927, -0.9446052816615078, -0.8575545134832991, -0.7689360310428865, -0.6802049469155554, -0.5927490759185783, -0.5078516709209618, -0.4266574719431814, -0.35014294282585806, -0.2790914575587663, -0.214074066991064, -0.15543632944551664, -0.10329152948397624, -0.057520441769554634, -0.017777625892624847, 0.01649593248456799, 0.04605418443023227, 0.07182189128517127, 0.09486565920084192, 0.11636091168733638, 0.13755568401751328, 0.15973220752144082, 0.18416731120032315, 0.21209270116650988, 0.24465618431365313, 0.2828848811605539, 0.327651424504576, 0.3796440665531953, 0.4393415194099572, 0.5069932346101466, 0.5826056898093334, 0.6659350981689417, 0.7564867922825806, 0.853521363756633, 0.956067466092341, 1.062941016685124, 1.1727703678968935, 1.2840268614637664, 1.39506003892339, 1.5041366568855659, 1.6094825529936554, 1.7093263289830036, 1.801943763404188, 1.8857018397768346, 1.9591012769348064, 2.020816477185819, 2.0697318640131543, 2.104973663089428, 2.125936286399181, 2.13230260672432, 2.124057555541637, 2.101494637959841, 2.0652151297550008, 2.016119899640512, 1.9553939802486733, 1.8844841894587567, 1.8050702752780072, 1.7190302182184118, 1.628400471022151, 1.5353320430413147, 1.4420434423876412, 1.3507715704795022, 1.2637217187641763, 1.1830178447653, 1.1106543034637384, 1.0484501803279276, 0.998007314733776, 0.9606730184060727, 0.9375083848777969, 0.9292629554109566, 0.9363563575018599, 0.9588673676191339, 0.9965306741819213, 1.0487414342436503, 1.114567532340091, 1.192769266988572, 1.2818260138399102, 1.379969248779896, 1.4852211633840413, 1.5954379727169017, 1.7083569047518095, 1.8216457743530727, 1.9329539848981678, 2.0399637686607406, 2.1404404737810876, 2.232280731071497, 2.313557387389338, 2.3825601725230166, 2.4378311714841607, 2.478194301188563, 2.5027781366038737, 2.511031592946258, 2.502732143451825, 2.477986432385669, 2.437223325866974, 2.3811796243059504, 2.3108788353401746, 2.227603570855278, 2.13286228197237, 2.0283511781387613, 1.9159122874774022, 1.7974887026722954, 1.6750781178239493, 1.5506857954791993, 1.4262781086801877, 1.3037377803416328, 1.1848218922048823, 1.0711236593613684, 0.9640388658636745, 0.8647377348203066, 0.7741428657040411, 0.6929137159486783, 0.6214379371853588, 0.5598297028637222, 0.5079349878632389, 0.4653435864272143, 0.4314074866919687, 0.40526506241738913, 0.3858703991652502, 0.37202694666606434, 0.3624245845580262, 0.3556791076371836, 0.3503730811976875, 0.3450969882943388, 0.3384895894821727, 0.3292764417451445, 0.31630557619568356, 0.29857941231706275, 0.2752820880051333, 0.2458015068365735, 0.20974554372148066, 0.1669520038250069, 0.11749209345275068, 0.06166733132442137, 5.996396084766755e-16], [-0.0, -0.06863161510404027, -0.14101795425385466, -0.21601902580357096, -0.2923871024459921, -0.3688032697915923, -0.4439161283133596, -0.5163816134088495, -0.5849028671504801, -0.6482690914580702, -0.7053923360573648, -0.7553412251164203, -0.797370702631906, -0.8309469765762104, -0.8557669630202628, -0.8717716708846964, -0.8791531221494854, -0.8783545674000212, -0.8700639283576768, -0.8552005732115864, -0.8348957027448931, -0.810466791084649, -0.7833866802027494, -0.7552480681148663, -0.7277242534795658, -0.7025271008500507, -0.6813632685596418, -0.6658897931030143, -0.6576701485232713, -0.6581318960224728, -0.6685270077678412, -0.6898958903523145, -0.7230360489519695, -0.7684762249178286, -0.8264567099581865, -0.8969163923574259, -0.9794869284432527, -1.0734942597301569, -1.177967517077018, -1.2916551722112601, -1.413048118557633, -1.5404091918793195, -1.671808481042362, -1.805163634231879, -1.938284239793559, -2.0689192567020367, -2.1948063900885093, -2.313722254311394, -2.4235321410919464, -2.5222382139409003, -2.6080249824476214, -2.679300970261233, -2.734735577347542, -2.7732902482880304, -2.7942431913268604, -2.7972070443608814, -2.782139050440175, -2.7493434825681646, -2.6994662413571757, -2.6334817349405286, -2.5526723339448703, -2.4586008708238047, -2.3530768181498622, -2.238116930534405, -2.1159012660434335, -1.9887256121131187, -1.8589514253941115, -1.7289544526250678, -1.601073229166889, -1.4775586525208861, -1.3605258000164557, -1.2519091035999186, -1.1534219116896278, -1.06652136043804, -0.9923793471172636, -0.9318602499145481, -0.8855058748393072, -0.8535279357221891, -0.8358081917147446, -0.8319061827237161, -0.8410743213362062, -0.8622799244522652, -0.894233603312113, -0.9354232808855445, -0.9841529743080891, -1.0385853703686916, -1.0967871366045834, -1.1567758513659796, -1.2165674046490795, -1.2742227182490862, -1.3278926588426043, -1.375860070258514, -1.4165779300449097, -1.4487027384481101, -1.4711223724556919, -1.4829777804582334, -1.4836780507458056, -1.4729085555076766, -1.450632047021474, -1.417082759921348, -1.3727537483989463, -1.3183778555577355, -1.2549028697251958, -1.1834615654219705, -1.1053374513597167, -1.0219271512207013, -0.9347004225303812, -0.8451588727386226, -0.7547944583934874, -0.6650488524203136, -0.5772747360990612, -0.49270001714599815, -0.4123958948034738, -0.3372495891096711, -0.2679424272246912, -0.2049338380103534, -0.14845165061203058, -0.09848892752803792, -0.054807391775556775, -0.016947335609744152, 0.015756270807911775, 0.044151914077248285, 0.06924450905059422, 0.09216393554825278, 0.11412998489957416, 0.13641465544604117, 0.16030280660577842, 0.18705222568890406, 0.21785417922069095, 0.253795510605314, 0.2958233087702458, 0.3447131088802131, 0.4010414978748458, 0.4651638866660107, 0.5371980801004175, 0.617014128523387, 0.7042307846638252, 0.798218720619714, 0.898110486207344, 1.0028170162163108, 1.1110503245698564, 1.2213518623124757, 1.3321258678155332, 1.4416769053822858, 1.5482506759198547, 1.6500770934151423, 1.7454145559331986, 1.832594301461009, 1.9100637281972728, 1.976427576200333, 2.0304859123151666, 2.071267931977962, 2.098060688148434, 2.110431976925485, 2.1082467484721916, 2.091676567324758, 2.0612018141857464, 2.017606497783031, 1.9619657259717267, 1.8956260655144725, 1.8201791954424578, 1.7374294252305715, 1.6493558020874894, 1.5580696676556354, 1.4657686399431185, 1.3746880884722248, 1.287051237101033, 1.2050190680594706, 1.1306412114116018, 1.0658089860849282, 1.0122117121717427, 0.9712973404835068, 0.9442383460741507, 0.931903710018698, 0.934837671088662, 0.9532457695520635, 0.9869885330063025, 1.0355829731080004, 1.0982118766944746, 1.1737406896043425, 1.2607416110056269, 1.3575243446216667, 1.4621727950799925, 1.5725868565451835, 1.6865283202640764, 1.8016698305775145, 1.9156457476898776, 2.026103731756408, 2.1307558476945547, 2.2274280038948167, 2.3141065803359773, 2.3889811714379703, 2.4504824645778833, 2.497314394187109, 2.528479850805406, 2.5432993809576083, 2.54142248339375, 2.522831285929244, 2.487836570457528, 2.4370662971959494, 2.3714469583822875, 2.292178262094014, 2.2007018044664193, 2.098664529514463, 1.9878778966090584, 1.8702737735157742, 1.7478581454392264, 1.6226637760249618, 1.4967029737192397, 1.371921605936858, 1.2501554645017432, 1.1330900198611642, 1.0222245103530736, 0.9188411986710081, 0.8239804935268745, 0.7384224837549394, 0.6626752685295505, 0.5969702950940677, 0.5412647387356548, 0.49525078310586684, 0.45837148678537043, 0.42984275850817455, 0.4086808127548511, 0.39373434322644474, 0.3837205373324906, 0.37726396307707805, 0.3729372928441391, 0.36930278817880485, 0.36495345668130225, 0.3585528068304288, 0.348872168497521, 0.33482461497884247, 0.31549461479009727, 0.2901626558477542, 0.2583242180759704, 0.21970261951743505, 0.17425542189473847, 0.12217425017477138, 0.06387805274994278, 6.186988061787375e-16], [-0.0, -0.07032075061075688, -0.14390926927766115, -0.21956220754846448, -0.2959875455773556, -0.37184260769917743, -0.44577365775308325, -0.516456013333872, -0.5826336025892626, -0.6431568992411011, -0.697018210908172, -0.7433833615791873, -0.7816188995929855, -0.8113140754708802, -0.8322969665871222, -0.8446442746334317, -0.848684483393481, -0.8449942344322037, -0.8343879526419874, -0.8179009277786614, -0.796766227766868, -0.7723859803654991, -0.746297707681823, -0.7201365292463724, -0.6955941605585824, -0.6743757223294194, -0.6581554387920622, -0.6485323397603214, -0.646987089588689, -0.6548410465226884, -0.6732186085198011, -0.703013827558657, -0.7448621754929199, -0.7991182230258643, -0.8658398523271096, -0.9447794666229349, -1.0353824906131377, -1.13679327796152, -1.2478683607457197, -1.367196795109987, -1.4931271819085523, -1.623800775205454, -1.7571899392310437, -1.8911410795782506, -2.0234210604229954, -2.151766029235208, -2.273931506093698, -2.3877425579780027, -2.4911428702542806, -2.582241548269648, -2.6593565310796548, -2.721053575717727, -2.7661798722617736, -2.79389147482301, -2.8036738784678215, -2.7953552334835337, -2.769111862402453, -2.725465927582439, -2.665275283474265, -2.58971573345422, -2.500256091744177, -2.398626622083311, -2.286781582288851, -2.1668567438150386, -2.0411228744843823, -1.9119362678300893, -1.7816874716425826, -1.652749409684862, -1.5274261031414587, -1.40790318190689, -1.2962013307291582, -1.194133742627048, -1.1032685536973756, -1.0248971118465098, -0.9600087901152516, -0.9092728966067322, -0.8730280614700128, -0.851279301146137, -0.8437027755634671, -0.8496580696897503, -0.8682076513100966, -0.8981429864803564, -0.938016636949626, -0.9861795237658367, -1.0408224216589816, -1.10002065251215, -1.1617808755745418, -1.2240888287006928, -1.2849568597965317, -1.3424701010968576, -1.3948301804652319, -1.4403954324770756, -1.4777166658353877, -1.5055676602710044, -1.5229697025314086, -1.5292096239134332, -1.5238509671976175, -1.5067380846430294, -1.477993146550815, -1.4380062173603543, -1.387418728881918, -1.3271008438018206, -1.2581233529642686, -1.1817248834195737, -1.0992753075413209, -1.0122363338764424, -0.922120325602009, -0.8304484309542421, -0.7387091208742577, -0.6483182121792966, -0.5605814103138957, -0.47666033534264557, -0.39754290014899957, -0.32401879324537086, -0.25666068316594415, -0.19581161056430763, -0.1415788717155007, -0.09383452725628699, -0.052222497002117015, -0.016172029943419902, 0.015082827597656882, 0.04247829896489208, 0.06709115514328182, 0.0901050046422856, 0.11277350074826666, 0.13638145290585507, 0.1622048849828246, 0.19147111243029155, 0.2253199121088411, 0.2647668327431893, 0.31066964121945745, 0.36369882155523886, 0.4243129413053747, 0.49273957696590653, 0.5689623486898439, 0.652714458873946, 0.7434789628277089, 0.8404958269780994, 0.9427756552479694, 1.049119791781831, 1.1581463424386924, 1.2683215026253007, 1.3779954390361786, 1.4854418512668148, 1.5889002391865603, 1.686619825979371, 1.7769040368671098, 1.8581544110572377, 1.9289128300585618, 1.9879009791392503, 2.0340560196159285, 2.0665615364348486, 2.084872936061848, 2.0887366013667377, 2.0782022597681102, 2.0536281847423665, 2.015679024879258, 1.9653162347060824, 1.9037812630665953, 1.8325718334438754, 1.7534118218378163, 1.6682153973992682, 1.5790462350149665, 1.4880727338369562, 1.397520278232822, 1.309621655216205, 1.226566793128853, 1.1504530088725033, 1.0832369447080412, 1.0266893406374655, 0.9823537254523409, 0.9515100201511705, 0.9351439337289535, 0.9339228960563599, 0.9481791189586001, 0.9779002083923272, 1.0227275718826525, 1.081962680462348, 1.154581057747727, 1.2392536850305569, 1.3343753348356027, 1.4380991805844037, 1.5483768808298222, 1.6630032066127949, 1.7796641730020673, 1.895987553419168, 2.009594599921576, 2.118151765551894, 2.219421226799944, 2.311309035097687, 2.3919097852948674, 2.459546774779374, 2.5128067371898597, 2.5505683667996557, 2.57202400037796, 2.576693988952325, 2.5644334683400865, 2.5354314202609194, 2.4902021008091357, 2.4295690955314515, 2.354642435870851, 2.2667893760253115, 2.1675995783405106, 2.0588455855990513, 1.942439566845778, 1.8203874071077233, 1.6947412685466803, 1.5675517798988643, 1.4408210118776827, 1.31645736861417, 1.196233469959732, 1.0817480180343302, 0.97439253587094, 0.8753237390779103, 0.7854421563311244, 0.7053774548793639, 0.6354807571111779, 0.5758240578546607, 0.5262066738729888, 0.4861684814241211, 0.45500952914320386, 0.4318154560683862, 0.415488002264307, 0.4047797757176456, 0.39833233702975707, 0.39471658540976856, 0.3924743774664888, 0.3901602855437035, 0.3863824053906191, 0.3798411536598015, 0.3693650532381305, 0.35394258723005967, 0.33274930838195865, 0.3051695171378107, 0.2708119651168438, 0.22951919794038522, 0.18137031800976405, 0.12667711981423566, 0.06597372326275038, 6.364666640263556e-16], [-0.0, -0.07183533331270517, -0.146418334008587, -0.22249191731641552, -0.29873033588525655, -0.3737783445908897, -0.446291352547272, -0.5149754849391459, -0.5786264776284851, -0.6361663554820607, -0.6866769003357923, -0.7294289950895367, -0.7639070346032472, -0.789827719235626, -0.8071526898919119, -0.8160946207377856, -0.8171165533377579, -0.8109244296702224, -0.7984529568800106, -0.7808451093250205, -0.7594257390896894, -0.735669920478127, -0.7111667931423946, -0.6875797888991231, -0.666604225855514, -0.6499233276594605, -0.6391637735680841, -0.6358519053087964, -0.6413717087878623, -0.6569256526873556, -0.6834994026874417, -0.7218313409445029, -0.772387707680351, -0.8353440480215973, -0.9105734958260057, -0.9976422608467922, -1.095812510274102, -1.2040526547690928, -1.3210548670326774, -1.4452594822290517, -1.5748857586416594, -1.7079683180211545, -1.8423984421481792, -1.9759692787480716, -2.106423909154785, -2.2315051545688624, -2.34900594931483, -2.4568190894376527, -2.552985173850128, -2.6357375929062523, -2.7035434848739706, -2.7551396727707855, -2.7895627102127674, -2.806172302520139, -2.804667525000022, -2.785095430321024, -2.747851817081784, -2.693674117679482, -2.623626550881323, -2.539077868534217, -2.4416722021341672, -2.3332936792244445, -2.2160256277996324, -2.092105315453403, -1.963875275792845, -1.8337323550810176, -1.704075665212354, -1.5772546536906045, -1.4555184966857229, -1.3409679876256668, -1.235511031976082, -1.1408227704065148, -1.05831123962137, -0.989089345528079, -0.9339537704343017, -0.8933712683672105, -0.8674726245016122, -0.8560543704332982, -0.8585881611471019, -0.8742375365474857, -0.9018816148058522, -0.9401451008080455, -0.9874338446387833, -1.0419750559069936, -1.1018611729073424, -1.165096303683655, -1.2296441009458097, -1.2934759057651226, -1.3546179966099985, -1.4111968104515087, -1.4614810605302753, -1.5039197594119127, -1.5371752640045389, -1.5601505885150757, -1.5720103786078985, -1.5721951015873488, -1.5604281791978727, -1.5367159673193864, -1.5013406659926452, -1.4548464193737758, -1.3980190340079475, -1.331859901041517, -1.2575548497694407, -1.1764387827435827, -1.0899570435312562, -0.9996245446503604, -0.9069837333716768, -0.8135624957846994, -0.720833094275187, -0.6301732005652568, -0.5428300266208775, -0.4598884706092316, -0.38224408689350137, -0.31058156056593805, -0.245359221527535, -0.18679997433450338, -0.13488885198795206, -0.089377228812747, -0.04979355394535569, -0.01546029713099802, 0.014483363178378738, 0.041053728934290275, 0.06539040182292559, 0.08872059995283017, 0.1123209308801983, 0.13747764718730326, 0.16544645173824404, 0.19741293326766216, 0.23445469875044844, 0.2775062273904488, 0.3273274030812691, 0.3844765895249108, 0.449288997159732, 0.5218609565291268, 0.602040562090849, 0.6894249875081813, 0.7833646022770115, 0.8829738444389318, 0.987148629526558, 1.094589906193729, 1.2038328084957939, 1.313280707575248, 1.4212433353216558, 1.525978042738973, 1.6257331690914174, 1.7187924366603402, 1.8035192517469931, 1.878399786345032, 1.9420837369309067, 1.9934217066236999, 2.031498233399086, 2.0556595882887607, 2.065535591118679, 2.0610548343360495, 2.042452864357017, 2.0102730407421063, 1.9653599721758834, 1.908845610289462, 1.8421282633235083, 1.7668449670068458, 1.684837815471757, 1.5981150064278322, 1.5088074883968783, 1.4191222102284227, 1.3312930615431373, 1.2475306549482112, 1.169972135236546, 1.1006322064056742, 1.041356544002148, 0.9937787085168381, 0.9592815965282666, 0.9389643618903665, 0.9336156119882992, 0.9436935370065713, 0.9693134668233916, 1.0102431745214944, 1.0659060618520284, 1.1353921747682898, 1.2174768109148217, 1.3106463002480397, 1.4131303691777304, 1.5229403419141412, 1.6379122938989104, 1.7557541546681494, 1.874095664101213, 1.9905400190158027, 2.102716008099821, 2.20832942315723, 2.30521255381419, 2.3913706206935346, 2.465024077428389, 2.524645812885925, 2.5689924091186063, 2.5971287547980704, 2.608445474671291, 2.602668808964226, 2.5798627583941927, 2.5404234960899763, 2.485066232719096, 2.4148049009687576, 2.330925195838365, 2.2349516638363727, 2.1286096733353745, 2.013783216666654, 1.8924695891871781, 1.7667320592760176, 1.638651684404428, 1.5102794411470355, 1.383589821039144, 1.2604370000231078, 1.142514618047087, 1.0313201090304918, 0.928124402357649, 0.8339476783284341, 0.7495417050846377, 0.6753791173415795, 0.6116498219781167, 0.5582645365590144, 0.5148652886479302, 0.48084253075416045, 0.45535836223937526, 0.43737519954380893, 0.42568910337973803, 0.4189668593502338, 0.41578581953073024, 0.4146754490604522, 0.41415948525047575, 0.4127976079685583, 0.40922553925340166, 0.40219253668826394, 0.390595317785458, 0.37350754960518734, 0.3502041565542402, 0.3201798367391756, 0.2831613298758897, 0.23911314369534656, 0.18823661686633966, 0.1309623703367164, 0.06793637126423786, 6.527898018164599e-16], [-0.0, -0.07316215028350286, -0.1485231691758851, -0.22478242408095164, -0.3005913992828364, -0.3745936791018228, -0.4454653120089373, -0.5119544709906665, -0.5729193418223719, -0.6273632147320135, -0.6744658251284618, -0.7136100838797946, -0.7444034546838644, -0.7666933724410693, -0.7805762487935081, -0.7863997753076762, -0.7847584070134755, -0.776482084829825, -0.7626184303692627, -0.7444088162981273, -0.7232588755379229, -0.700704159062969, -0.6783717811499239, -0.6579389993651912, -0.6410897615470366, -0.6294703113426046, -0.6246449759260266, -0.628053263460033, -0.6409693734787202, -0.6644651711788526, -0.6993775978217217, -0.7462813859434955, -0.8054678223455904, -0.8769301569433455, -0.9603560950304717, -1.0551276383042443, -1.1603283603275718, -1.2747580194089478, -1.3969542306749931, -1.5252207438811698, -1.6576617086044303, -1.7922211579912393, -1.926726809951241, -2.0589371739056705, -2.186590864709597, -2.3074569653655734, -2.4193852481791107, -2.520355060933626, -2.608521710632494, -2.6822592318030893, -2.740198508015223, -2.781259822195758, -2.8046790409611737, -2.8100267874168043, -2.797220122078177, -2.7665264287520075, -2.7185593870703193, -2.654267101406718, -2.5749126425436, -2.482047439158006, -2.3774781265506517, -2.2632276159058846, -2.1414912849434193, -2.014589306754463, -1.8849162250845555, -1.7548889491102644, -1.6268943772879059, -1.5032378672524194, -1.3860937468492187, -1.2774590107453054, -1.179111268943755, -1.092571909847745, -1.0190753138389648, -0.9595448067653977, -0.9145758798735272, -0.884427027564052, -0.8690183711888914, -0.8679380504220404, -0.8804561780896846, -0.9055459742653044, -0.9419115253093338, -0.9880214574943763, -1.042147676686799, -1.1024082085883387, -1.1668130810838233, -1.233312123503203, -1.299843518647853, -1.3643819331237812, -1.4249850700318039, -1.4798375348378356, -1.527290979040199, -1.5658995851544268, -1.5944500780220545, -1.6119855884375898, -1.6178228520202482, -1.611562395190321, -1.5930915368112186, -1.5625802141115137, -1.520469820417505, -1.467455415555148, -1.4044618332190724, -1.3326143591097144, -1.2532047855179858, -1.1676537590477947, -1.0774704255957726, -0.9842104384348197, -0.889433429800147, -0.7946610529627112, -0.7013366803063248, -0.6107877940145243, -0.5241920309224851, -0.44254774385130763, -0.36664982087523845, -0.2970713645739058, -0.23415167895062963, -0.17799084628484188, -0.12845100393634182, -0.0851642564031906, -0.04754698518430789, -0.014820152589762764, 0.01396496020841356, 0.03989628193692059, 0.06416657110477784, 0.08803605337107294, 0.11279308100959635, 0.13971387154681086, 0.17002240798586069, 0.20485158058173034, 0.24520661994469453, 0.2919318140632961, 0.34568141907739897, 0.4068955673647379, 0.475781849392998, 0.5523031010233482, 0.6361717691678612, 0.726851059896946, 0.8235628985154327, 0.9253025551800329, 1.0308596167605837, 1.138844820226135, 1.2477221090586006, 1.3558451359706307, 1.461497316056819, 1.562934437493399, 1.6584287645276485, 1.7463135216593124, 1.8250266298478461, 1.8931525758241707, 1.9494613339821734, 1.9929433260072933, 2.022839494819358, 2.0386656843713045, 2.0402306525698592, 2.0276471977613366, 2.0013360461059806, 1.9620223236498204, 1.910724618647189, 1.8487368222039458, 1.7776031140846162, 1.699086631124015, 1.615132513863886, 1.5278261688567778, 1.4393477059956192, 1.3519236091766609, 1.2677767720853483, 1.1890760770306497, 1.1178867123375311, 1.0561224123334185, 1.005500763641294, 0.9675026532395969, 0.9433368391737618, 0.9339105061634345, 0.9398065284941979, 0.9612680048887011, 0.9981904583369973, 1.0501219122954297, 1.116270867649066, 1.1955220169231973, 1.2864593479991808, 1.3873961135259247, 1.4964109786101172, 1.6113895122019777, 1.7300700604546386, 1.8500929363183247, 1.9690517812661927, 2.084545904238024, 2.1942323808580175, 2.2958767032558565, 2.3874008072005326, 2.4669273678370596, 2.532819346498089, 2.5837138865990337, 2.618549793673327, 2.636587989796715, 2.6374245021786873, 2.620995725409286, 2.5875758823414854, 2.537766795327249, 2.4724802629493086, 2.392913513029451, 2.300518366274231, 2.196964892470916, 2.084100469101493, 1.9639052575208311, 1.838445191929979, 1.7098236293772577, 1.580132833718226, 1.451406462341962, 1.3255741917189134, 1.2044195573446357, 1.0895419970271412, 0.9823239759189938, 0.8839039400425281, 0.7951556956260267, 0.7166746481229523, 0.6487711614266595, 0.591471118857165, 0.54452358745105, 0.5074153104140948, 0.47939158368920265, 0.45948291563571286, 0.4465367276905634, 0.4392532320636224, 0.4362245229963487, 0.4359758433096115, 0.43700793968512563, 0.4378393995009254, 0.4370478695158166, 0.4333090920076995, 0.425432756155865, 0.4123942498853515, 0.3933615077991988, 0.367716281375351, 0.3350693049602404, 0.2952689914941368, 0.2484034612737819, 0.1947958810938998, 0.13499326539564152, 0.06974906116926105, 6.675265429218629e-16], [-0.0, -0.07428958152193181, -0.1502052858367831, -0.22641359719427884, -0.3015544843448075, -0.37428186106627154, -0.44330381309642325, -0.5074215088155964, -0.565565743412172, -0.6168301256635808, -0.660500001397178, -0.6960763160317386, -0.7232937476242712, -0.7421325883175449, -0.7528240123178227, -0.7558485384958759, -0.7519276711137577, -0.7420088786084517, -0.7272442433530457, -0.70896328048736, -0.6886405770732507, -0.6678590400894284, -0.648269659632862, -0.6315487891149404, -0.6193540147629318, -0.6132797305118318, -0.6148135502147112, -0.6252946765236408, -0.6458753050194327, -0.6774860741229307, -0.7208064776119458, -0.7762410394482852, -0.8439019129291292, -0.9235984112756069, -1.0148338084535673, -1.1168095714249195, -1.2284370025294036, -1.3483560878054004, -1.4749611683031292, -1.6064328812607451, -1.7407756606374496, -1.8758599458538394, -2.0094681271993657, -2.1393431592572565, -2.26323870232775, -2.3789696080293603, -2.4844615501773624, -2.5777986161252633, -2.6572677167376133, -2.7213987440583787, -2.7689995028771657, -2.7991845634572505, -2.81139732476449, -2.8054247371951204, -2.7814043071771044, -2.7398231889073816, -2.6815093564415897, -2.6076150378006386, -2.519592777111363, -2.419164666564707, -2.308285452870357, -2.1891003689411694, -2.0638986671934676, -1.935063933039813, -1.8050223333911968, -1.6761900034238724, -1.5509207943306726, -1.4314555948051852, -1.319874399858971, -1.218052233218543, -1.127619935654217, -1.0499307134672082, -0.986033201908749, -0.9366516409476928, -0.9021735893997102, -0.8826454221800072, -0.8777756687771975, -0.8869460635305674, -0.9092299945027428, -0.9434178621531124, -0.9880486959041838, -1.041447230009742, -1.101765513426118, -1.1670280247043874, -1.2351791847376206, -1.3041321093572575, -1.3718174214418486, -1.4362309488413003, -1.4954791697751348, -1.5478213304716564, -1.5917072490296162, -1.6258099325170594, -1.6490522683013835, -1.6606272021460495, -1.6600109809015329, -1.646969212516958, -1.6215556762324141, -1.584103996687082, -1.5352124727949048, -1.4757225212001024, -1.4066913507454464, -1.329359624799125, -1.24511498903609, -1.155452440399557, -1.0619325860913291, -0.9661388877987381, -0.8696350048768796, -0.7739233404813008, -0.6804058570105429, -0.5903481626895714, -0.5048477813971728, -0.4248074052344891, -0.3509137967402688, -0.2836228584717064, -0.22315122569002566, -0.1694745672372145, -0.12233260469744617, -0.08124068504189659, -0.045507571590754595, -0.014258956605640222, 0.013533949761442114, 0.03902153132864041, 0.06343946757823217, 0.08807000319774762, 0.11420182734634081, 0.14308964163941942, 0.1759145052597254, 0.21374602706611884, 0.2575074285341458, 0.3079444289699985, 0.36559880750153706, 0.43078737729588723, 0.5035869692711983, 0.583825868733378, 0.6710819827476946, 0.7646878428219973, 0.863742371001623, 0.9671291622122307, 1.0735408660688484, 1.1815090916945539, 1.289439113416544, 1.3956485272419425, 1.498408901034558, 1.5959893780714267, 1.6867011363194964, 1.768941575859526, 1.841237105234565, 1.9022834242477542, 1.9509822553036242, 1.9864735565070197, 2.008162355468244, 2.0157394705578304, 2.0091955330999363, 1.988827886101663, 1.9552401086081144, 1.9093340953792826, 1.852294804847712, 1.7855679697029216, 1.7108312394627117, 1.6299593886841688, 1.5449843739456472, 1.4580511536600635, 1.3713702938752197, 1.2871684677259827, 1.2076380139767648, 1.1348867496346642, 1.0708892321222576, 1.017440637886821, 0.9761143672174291, 0.9482244007749757, 0.9347933239126469, 0.9365268028988136, 0.9537951458300411, 0.9866224139980534, 1.0346833707999523, 1.0973083692947372, 1.1734960907337124, 1.2619338594227614, 1.3610250786648408, 1.468923162682684, 1.5835711844747684, 1.7027463232892148, 1.8241080811311396, 1.9452491482318024, 2.063747734879735, 2.177220152960898, 2.283372425796315, 2.380049729503702, 2.4652825225268287, 2.53732830085078, 2.5947080227596597, 2.636236376180602, 2.661045210520976, 2.6685996197926514, 2.6587063406874094, 2.631514313791103, 2.587507443788563, 2.527489780733476, 2.4525635246960142, 2.3641004259681724, 2.2637073083769663, 2.153186580365848, 2.0344927140477695, 1.9096857636390516, 1.7808830593846345, 1.6502102497736006, 1.5197528727031608, 1.3915096151756379, 1.2673483717180944, 1.1489661353063234, 1.0378536531275377, 0.9352656556178104, 0.842197323998547, 0.7593675026208386, 0.687208991796597, 0.6258660787232795, 0.5751992830404925, 0.534797114002682, 0.5039944626752683, 0.48189708926594726, 0.46741151672673814, 0.4592795107787281, 0.4561162167364766, 0.4564509376228784, 0.45876947814623537, 0.46155694658443314, 0.46333990222371185, 0.462726759763861, 0.4584454133544236, 0.44937712030703914, 0.4345857860237483, 0.413341914674597, 0.38514063149900984, 0.34971333868624493, 0.3070327336375263, 0.25731109178621747, 0.20099189165341225, 0.1387350329954964, 0.07139606537088874, 6.80548373138949e-16], [-0.0, -0.07520772324784195, -0.15144988762618244, -0.2273711380090368, -0.3016113702032806, -0.37284632091488695, -0.4398273067724614, -0.5014190412383585, -0.5566345064894269, -0.6046659319330617, -0.644911030071707, -0.676993761454704, -0.7007790404192358, -0.7163809487013478, -0.7241641908810872, -0.7247386998062284, -0.7189474772215604, -0.7078479303409696, -0.69268713459647, -0.6748716119847974, -0.6559323592631428, -0.6374859870292752, -0.6211929362119823, -0.6087138199775164, -0.6016649944048639, -0.6015744890257011, -0.6098394276798292, -0.6276860410282333, -0.6561333151289308, -0.6959612370473248, -0.7476844905386385, -0.8115323250164623, -0.8874351724710459, -0.975018423359903, -1.073603597781148, -1.1822169667614046, -1.2996054947269737, -1.4242597927286118, -1.5544435972599235, -1.6882291258925564, -1.8235375125281565, -1.9581833955500523, -2.0899226248003013, -2.2165019708221263, -2.335709664297827, -2.4454255665200217, -2.543669773803687, -2.6286484900047613, -2.698796061066024, -2.752812152367982, -2.789693161558023, -2.8087570937829187, -2.809661279622334, -2.7924124848050256, -2.757369140892487, -2.705235613162256, -2.6370486113652536, -2.5541560362560016, -2.4581887352392013, -2.351025809742183, -2.2347542708818753, -2.111623974892899, -1.9839988823297332, -1.8543057725082734, -1.7249816048805888, -1.5984207505786965, -1.4769233194580393, -1.3626457805790506, -1.2575550178685608, -1.1633868790875994, -1.081610167257166, -1.0133968920344323, -0.9595994474201647, -0.920735215317367, -0.8969789159379146, -0.8881628402360299, -0.8937849109761422, -0.9130243323212917, -0.9447644075080477, -0.9876219346425785, -1.0399824360259995, -1.1000403404382493, -1.1658431237568188, -1.2353383238928357, -1.30642228341328, -1.3769894388426918, -1.4449809702593972, -1.5084316484633893, -1.5655137690214445, -1.6145771415179835, -1.6541842063210992, -1.6831394774636883, -1.700512655645181, -1.7056549162194812, -1.6982080493145806, -1.6781063086197243, -1.6455710074020584, -1.6010980804452246, -1.5454390043647594, -1.4795756318442648, -1.4046896437230496, -1.3221274528958045, -1.2333615024691529, -1.1399489849139588, -1.043489067020915, -0.9455797359341281, -0.8477753837200701, -0.7515462218525806, -0.6582405633920108, -0.5690509309286218, -0.48498484462040303, -0.40684101955584634, -0.33519155841704557, -0.270370567663965, -0.21246945722149332, -0.16133900920126235, -0.11659812495529205, -0.0776489862043646, -0.043698199505360906, -0.013783338131838598, 0.013195844532606525, 0.03844237720679009, 0.06322415504293438, 0.08883416764207282, 0.11654994112864707, 0.14759328598186006, 0.18309143560854016, 0.2240406260508588, 0.2712731056117814, 0.32542847609228825, 0.386930156950935, 0.45596763279013075, 0.5324849964358838, 0.61617613823703, 0.7064867611382758, 0.8026232248932768, 0.9035680459279994, 1.0081017063125328, 1.1148302604344953, 1.222218075472802, 1.3286249055280144, 1.432346382754255, 1.5316569150489003, 1.6248539112176095, 1.7103022128459535, 1.786477598506398, 1.8520082408419074, 1.9057130402141713, 1.946635828999224, 1.9740745365867758, 1.9876045243815215, 1.987095439719172, 1.9727210941869755, 1.9449620415383961, 1.9046007090393076, 1.8527091192718168, 1.7906294226213977, 1.7199476393439, 1.6424611798122632, 1.5601408680528062, 1.4750883330892095, 1.3894897514247802, 1.305567019218443, 1.2255275019306977, 1.1515135506552916, 1.0855529869127785, 1.029511740977066, 0.9850497831694959, 0.9535814140324272, 0.9362408796211057, 0.9338541547080117, 0.946917592446541, 0.975583977473535, 1.0196563444558209, 1.0785897399511393, 1.1515009166346533, 1.2371857600336478, 1.3341440635166937, 1.4406110918937516, 1.5545952118769255, 1.6739207227815962, 1.7962748967476263, 1.9192581374559425, 2.040436092250547, 2.15739250655215, 2.2677815925818368, 2.3693786971029613, 2.460128094814822, 2.5381868041547184, 2.6019634188582637, 2.650151069316552, 2.6817537695905855, 2.696105565419592, 2.6928820717835253, 2.6721041713109, 2.6341338325927612, 2.579662195685558, 2.5096902561685983, 2.4255026545822598, 2.3286352406462885, 2.220837227401894, 2.104028875815481, 1.9802557524106892, 1.851640678724844, 1.7203345400202943, 1.588467140609027, 1.4580992839683844, 1.3311772178523904, 1.2094905188642924, 1.0946343991605476, 0.9879773024543875, 0.890634520209392, 0.8034484052979325, 0.7269755933062533, 0.6614814652816083, 0.6069419044438649, 0.56305221774087, 0.5292429156297345, 0.5047018745176935, 0.48840225007635096, 0.47913537000557316, 0.4755477152004553, 0.4761810015922582, 0.4795143035391003, 0.48400711524539775, 0.4881422303233165, 0.49046733160443756, 0.48963422328518985, 0.48443470436463515, 0.4738321743554514, 0.4569881770381026, 0.43328322263662294, 0.40233137978128586, 0.36398829214098377, 0.3183524464990945, 0.26575969494740426, 0.2067712093237601, 0.1421552165761716, 0.0728630250817275, 6.917412759595503e-16], [-0.0, -0.07590849469238507, -0.15224603714898405, -0.2276467543887334, -0.3007619951979526, -0.3703006978806261, -0.4350682924993012, -0.4940030873191048, -0.5462091529826385, -0.5909848071754893, -0.6278459149500609, -0.6565433526333379, -0.677074133011126, -0.6896858524850269, -0.6948742930295044, -0.6933741886911564, -0.6861433436010844, -0.6743404615307176, -0.6592972115262395, -0.6424852059299795, -0.6254787022745198, -0.6099139556626305, -0.5974462403658947, -0.589705626100799, -0.588252634018479, -0.5945349087947569, -0.6098460259564068, -0.6352875080676865, -0.6717350506751958, -0.7198098606979276, -0.7798558886216193, -0.8519235943625912, -0.9357607284657788, -1.0308104392779642, -1.1362168371018038, -1.2508379625240496, -1.3732659226715656, -1.5018537806313907, -1.6347486141145675, -1.769930003864023, -1.9052530741937845, -2.0384950908658026, -2.1674045282168044, -2.289751450412491, -2.403378012656794, -2.5062478781612403, -2.596493366009281, -2.672459193337181, -2.732741751386327, -2.7762229571642707, -2.8020978482425485, -2.809895234592832, -2.799490884784316, -2.771112900375441, -2.7253391176472554, -2.663086565438128, -2.5855931971340924, -2.4943922992335272, -2.391280153843775, -2.2782776937129112, -2.1575870320179975, -2.0315438716162046, -1.9025668968292468, -1.7731053226751847, -1.6455858200351967, -1.522360049488142, -1.405654021122736, -1.2975204529321516, -1.199795227511377, -1.1140589475066136, -1.0416044670445592, -0.9834111322206769, -0.9401263021809517, -0.9120545473468301, -0.899154737188547, -0.9010450411484241, -0.9170156774623445, -0.9460490603292318, -0.9868468206215587, -1.0378630133729074, -1.0973426805461444, -1.1633648135734942, -1.2338886598474363, -1.3068022431210333, -1.379971921393324, -1.4512917883663559, -1.5187317363083175, -1.5803830387627817, -1.6345003799183289, -1.6795393518220938, -1.7141885585745757, -1.7373956051922619, -1.7483864044778754, -1.7466774040883166, -1.7320805138125035, -1.7047006954276789, -1.664926359853051, -1.6134128941343326, -1.5510598096653412, -1.4789821588089915, -1.398477005881461, -1.3109858569021882, -1.2180540476961998, -1.1212881595574375, -1.0223125740786527, -0.9227262929452145, -0.8240611342034241, -0.7277423741885878, -0.6350528350752606, -0.5471013237037844, -0.46479621038248026, -0.3888247997653255, -0.3196389931519659, -0.25744757654157724, -0.20221529568918567, -0.15366870265437058, -0.11130858237807563, -0.07442859712833479, -0.042139625539468234, -0.013399125506304193, 0.01295527988631239, 0.03816890362909478, 0.06353077945255349, 0.09033318645339747, 0.11983100346322706, 0.15320198816689737, 0.19150905307492724, 0.23566555998911473, 0.28640457783588613, 0.34425294760388575, 0.4095108751522763, 0.48223763094730926, 0.5622437789046754, 0.6490901884171575, 0.7420939085709503, 0.8403408059203481, 0.9427046914897588, 1.0478724933524435, 1.154374872491842, 1.2606215357167867, 1.364940373847251, 1.4656194494285568, 1.5609507785494836, 1.6492747980106186, 1.7290243835345105, 1.7987672876575878, 1.8572458974128148, 1.903413271205604, 1.936464500012036, 1.9558625481323886, 1.9613578605468445, 1.9530011742291495, 1.9311491358949309, 1.8964625045345116, 1.8498968993685585, 1.7926862380630353, 1.7263191915833942, 1.6525091564492351, 1.5731584080280197, 1.4903172458155955, 1.406139069701754, 1.3228324317919975, 1.2426111887792823, 1.167643933076219, 1.1000039055412552, 1.0416205879749847, 0.9942341396608105, 0.9593537798324896, 0.9382211285277036, 0.9317794039580756, 0.9406492380326883, 0.9651117163050291, 1.0050990781307854, 1.060193331360598, 1.1296328478565891, 1.2123268160895382, 1.306877239672971, 1.411607990489434, 1.524600256457815, 1.6437335710925074, 1.7667314785467616, 1.891210777070403, 2.014733198449056, 2.1348583231076073, 2.2491965015645157, 2.355460553516246, 2.451515045989525, 2.535422010976458, 2.6054820493116395, 2.6602698791406643, 2.6986635214265315, 2.7198664682583367, 2.7234223485093465, 2.7092217855083245, 2.677501328435003, 2.628834528558386, 2.5641154185842274, 2.4845348337054247, 2.3915501820707052, 2.286849426198283, 2.1723101716411173, 2.0499548717105824, 1.9219032445923525, 1.7903230596667472, 1.657380481870088, 1.5251911658029667, 1.395773265023001, 1.2710034672906352, 1.152577084902776, 1.0419731227491298, 0.9404251180684376, 0.848898398316375, 0.7680742407954125, 0.6983412438172655, 0.6397940385161391, 0.5922392875087676, 0.5552087359542066, 0.5279789066844438, 0.5095968682598462, 0.49891135707029843, 0.4946084055875451, 0.49525052173690276, 0.49931838170477394, 0.5052539423232425, 0.5115038508004451, 0.516562029623856, 0.5190103428692694, 0.5175563061081997, 0.5110668841392835, 0.49859752674278185, 0.47941571984245046, 0.4530184745991231, 0.41914333635259066, 0.3777726649168713, 0.32913111321206406, 0.27367640813371463, 0.21208371143634902, 0.1452240048405428, 0.0741370983527616, 7.010069300183297e-16], [-0.0, -0.07638572721680471, -0.15258678465400125, -0.22723827606919136, -0.2990145046150325, -0.3666687662794963, -0.42907107161840013, -0.4852427756481356, -0.5343871747013492, -0.5759152322573988, -0.6094657206461319, -0.6349192089434808, -0.6524054857167904, -0.6623041745439325, -0.6652384761511717, -0.6620621491461274, -0.6538400171586022, -0.6418224592895836, -0.6274144988168336, -0.6121402480941017, -0.597603591861862, -0.5854460935754936, -0.5773031872103598, -0.5747597682908406, -0.5793063212421741, -0.5922967149069339, -0.6149087642434478, -0.6481085945873774, -0.6926197568623975, -0.7488979298853281, -0.8171119121487005, -0.8971314534459468, -0.9885223101596607, -1.090548731060764, -1.202183397433126, -1.3221246567731368, -1.4488207077931328, -1.5805002204934293, -1.715208712994263, -1.8508498606856287, -1.985230786723436, -2.1161102791609014, -2.2412488016845145, -2.358459114030849, -2.465656296028041, -2.5609059764603903, -2.64246960449949, -2.7088456664617633, -2.7588058426186595, -2.7914252155148516, -2.806105779941235, -2.8025926620193746, -2.7809826269754883, -2.741724637939795, -2.6856124170593945, -2.6137691507609873, -2.527624668501077, -2.4288856042236113, -2.3194992176190223, -2.2016117040463796, -2.0775219539355128, -1.9496318314067305, -1.8203941250714073, -1.692259379477098, -1.5676228420823142, -1.4487727573480575, -1.337841206602078, -1.2367586305790723, -1.1472130824834117, -1.0706151452441426, -1.0080693101347789, -0.9603524584547924, -0.9278999173221399, -0.9107993789797814, -0.9087927848133776, -0.9212860851072169, -0.9473665980687367, -0.9858275113950499, -1.0351989010201743, -1.0937844887596813, -1.1597032270590804, -1.230934688168724, -1.3053671494654135, -1.3808472083468077, -1.4552297304904256, -1.5264269349386168, -1.5924554483639473, -1.6514802181866963, -1.7018542584575285, -1.7421533114236112, -1.7712046386972917, -1.7881093056377668, -1.7922574871775356, -1.7833364987554987, -1.7613314378776146, -1.7265185055847354, -1.679451258200099, -1.6209402136662783, -1.5520263992624441, -1.473949574510615, -1.3881119910217627, -1.2960386567692588, -1.1993351532391245, -1.0996441081476886, -0.9986014526630064, -0.8977935897435754, -0.7987165694592212, -0.7027383088371821, -0.6110648094238853, -0.524711217560119, -0.44447844311975354, -0.3709359054682541, -0.3044108144057047, -0.2449842229654792, -0.1924939124820809, -0.14654399279361002, -0.10652092630128618, -0.07161551827624449, -0.040850261487843556, -0.013111284827699988, 0.01281596338373893, 0.03820826329000127, 0.06436444018270981, 0.0925645326069183, 0.12402941174259965, 0.1598819408892394, 0.20111072487130568, 0.24853743316909083, 0.30278858921997837, 0.3642726039268743, 0.43316269683301784, 0.5093861970652181, 0.5926205518259917, 0.6822961970744498, 0.7776062674478564, 0.8775229449295905, 0.9808200727584091, 1.0861014969844378, 1.1918344470779514, 1.2963871329332988, 1.3980696219104387, 1.4951769691427363, 1.5860335095558598, 1.6690371825950836, 1.7427027515716527, 1.8057027991301688, 1.8569054282084223, 1.8954076729011302, 1.9205637240613445, 1.9320071978513307, 1.9296668187846264, 1.9137750485743397, 1.8848693643936372, 1.8437860707165175, 1.7916467132784828, 1.729837347311035, 1.6599810905021435, 1.5839045596810062, 1.5035989448137523, 1.4211766106590016, 1.3388242319326622, 1.258753559152784, 1.1831509771523308, 1.1141270548839826, 1.0536672926144304, 1.003585250648995, 0.9654791928004663, 0.9406932990927708, 0.930284397529799, 0.9349950366646677, 0.9552335722557297, 0.9910617760797545, 1.0421902969928352, 1.1079821179077913, 1.187463962027117, 1.279345412068164, 1.3820453219634627, 1.493724926108962, 1.612326890922976, 1.7356194111829264, 1.8612443328005752, 1.9867681873296115, 2.109734953924861, 2.227719323387003, 2.33837922733117, 2.4395064136896774, 2.5290738972480633, 2.6052791895517022, 2.6665823144507894, 2.7117377412750474, 2.7398195140655925, 2.7502390188549546, 2.7427550076748686, 2.7174756834656333, 2.6748528398293674, 2.6156682389816988, 2.5410125956959457, 2.45225771001254, 2.3510224527547012, 2.2391334515424424, 2.1185814475633746, 1.9914743918965352, 1.859988422346643, 1.726317905836612, 1.5926257464244726, 1.460995144674995, 1.3333839508677008, 1.211582683514198, 1.0971771877258882, 0.9915167875893819, 0.8956886459177574, 0.8104988870953336, 0.7364608681745752, 0.6737908041806249, 0.6224107701993513, 0.5819589198311729, 0.5518065815264004, 0.5310817255875216, 0.518698139396551, 0.5133895105227417, 0.5137475001691718, 0.5182627957844157, 0.5253680638622188, 0.5334816835930435, 0.5410511300433031, 0.5465948921368549, 0.5487418553992496, 0.5462671509973025, 0.5381235691920221, 0.5234677544260498, 0.5016805378310004, 0.47238091742563404, 0.4354333627482425, 0.39094829489572214, 0.33927577050810087, 0.2809925746419809, 0.21688309825487004, 0.14791453685552883, 0.07520709369811895, 7.082637558517263e-16], [-0.0, -0.07663523477398763, -0.15246925751476625, -0.2261497094422779, -0.29638521668618356, -0.3619842601911236, -0.4218913816272525, -0.4752197443909984, -0.5212791622516683, -0.5595988245834578, -0.5899440834873527, -0.6123268210156845, -0.6270090803066674, -0.634499818537044, -0.635544817809482, -0.6311099679006879, -0.6223583077038835, -0.6106213758198944, -0.597365570926524, -0.5841543554591285, -0.5726072483670577, -0.5643566413844519, -0.5610035360691346, -0.564073334163359, -0.5749728206444101, -0.5949494569024235, -0.6250540512667067, -0.6661077967682946, -0.7186745634233025, -0.7830392069319699, -0.8591925105692393, -0.9468232157503236, -1.045317423255935, -1.1537654656769747, -1.2709761667741226, -1.3954982197273833, -1.5256482382385954, -1.6595448665802883, -1.795148181149, -1.9303034807265662, -2.0627884488834836, -2.1903625826518422, -2.3108177190307218, -2.4220284566867893, -2.5220012653032247, -2.608921099615599, -2.6811943887317113, -2.7374873526266343, -2.7767587048116393, -2.798285930535486, -2.801684480351344, -2.7869193858361205, -2.7543089836344437, -2.7045206214598188, -2.6385584106594955, -2.5577432797850963, -2.463685767678808, -2.358252168392882, -2.243524799563999, -2.1217573067720363, -1.9953260354809608, -1.866678596478392, -1.7382808179935265, -1.6125633162379835, -1.491868925038892, -1.378402204302752, -1.2741821967774725, -1.1809995242012896, -1.1003788093625833, -1.0335472824038097, -0.9814102810251553, -0.944534188715434, -0.9231371768076333, -0.9170879293812242, -0.9259123393733646, -0.9488079743667035, -0.9846659260188695, -1.0320994824757528, -1.0894789026070093, -1.1549714284041237, -1.2265855508278236, -1.3022184476882064, -1.3797054420904487, -1.4568702882243947, -1.531575078760925, -1.6017685850643177, -1.6655318873328349, -1.7211202254230549, -1.7670001005975247, -1.801880781228069, -1.8247395084853248, -1.8348398576534022, -1.8317428829289868, -1.8153108540947693, -1.7857035778009671, -1.7433674797635579, -1.6890178024420264, -1.6236144412829412, -1.5483320972511083, -1.4645255603140628, -1.373691054444488, -1.2774246667357856, -1.1773789491673803, -1.075218819841976, -0.9725779002748688, -0.8710164063872358, -0.7719816638008168, -0.6767722441120231, -0.5865066199719432, -0.5020971155675128, -0.42422978859856564, -0.35335072366357173, -0.28965904907963136, -0.23310681383473197, -0.18340568304781593, -0.1400402335110994, -0.10228746008180775, -0.06924194319470027, -0.03984598163690896, -0.012923866652429252, 0.012780633341988881, 0.03856459094960259, 0.06572511114327233, 0.09551849524188162, 0.12912047795981688, 0.16758861067891961, 0.2118278092073493, 0.26256000319709366, 0.32029871913276875, 0.38532930203, 0.4576953358872018, 0.5371916631786244, 0.6233642332903518, 0.7155168330873027, 0.8127245742248279, 0.913853835902209, 1.0175881929549775, 1.122459701783755, 1.2268847746247304, 1.329203749704826, 1.427723164046527, 1.5207596596947328, 1.6066844049157039, 1.6839668907843004, 1.7512169711468772, 1.8072240501232255, 1.850992385275622, 1.8817715648138083, 1.8990813315496184, 1.9027300619850507, 1.8928263625962847, 1.8697834132901823, 1.834315866022723, 1.787429290283561, 1.730402342018312, 1.6647620139922472, 1.5922524990819198, 1.5147983591893912, 1.4344628373746053, 1.3534022757586075, 1.2738177036128713, 1.1979047362313522, 1.127802973725245, 1.0655461085066955, 1.0130139403710092, 0.971887458905148, 0.9436080853263294, 0.9293420713732041, 0.9299509337813048, 0.9459686620328547, 0.9775862778751737, 1.0246441514056757, 1.0866322945393931, 1.1626986628802467, 1.2516653060304788, 1.3520520188493255, 1.4621069666863076, 1.579843590548736, 1.703082947597456, 1.8295005119785979, 1.9566763539790029, 2.0821475344550104, 2.2034614984088705, 2.3182292277703422, 2.424176919463903, 2.519194990553582, 2.601383276781195, 2.6690913825677924, 2.7209532572846284, 2.755915211460484, 2.7732567441783593, 2.772603725372377, 2.753933659849195, 2.7175729491550555, 2.66418625827014, 2.594758281883526, 2.5105683851137037, 2.4131587616139516, 2.3042969039635683, 2.1859333134208745, 2.060155485320306, 1.9291392900213773, 1.7950989253828902, 1.6602366439448883, 1.5266934557682335, 1.3965019763496325, 1.2715425290620674, 1.1535035247290528, 1.0438470294497457, 0.9437802984765202, 0.8542339021670344, 0.7758469035981023, 0.7089593705011726, 0.6536123211726866, 0.6095550194801134, 0.5762593526079375, 0.5529408512616012, 0.5385857499686146, 0.531983338877473, 0.5317627316462932, 0.5364330697321195, 0.5444261041685282, 0.5541400436530607, 0.5639835336799792, 0.5724186360646415, 0.5780017113120041, 0.5794211669695523, 0.5755311217725482, 0.5653801457868123, 0.5482343680410331, 0.5235943919571607, 0.49120562143975344, 0.451061772639829, 0.4034015237966945, 0.3486984336877027, 0.28764443357224606, 0.22112736369370495, 0.1502031792022841, 0.07606358789859576, 7.134478006290146e-16], [-0.0, -0.07665486491786405, -0.15189470944551425, -0.22439123095888078, -0.2928985068667083, -0.35629059792267165, -0.41359591461223166, -0.46402741367983497, -0.5070077991496708, -0.5421890308255973, -0.5694655899883083, -0.5889811131375189, -0.6011281760854352, -0.6065411881627714, -0.6060825352623932, -0.600822286387531, -0.5920119468309002, -0.5810528978098263, -0.5694603033315621, -0.5588233866631284, -0.550763077911847, -0.5468881083254572, -0.5487506740568, -0.5578028110424085, -0.5753546127567392, -0.6025353840838023, -0.6402587582720143, -0.6891927114784611, -0.7497352929954235, -0.8219967517180333, -0.9057885841236044, -1.0006198598072362, -1.1057010016272728, -1.2199550131833787, -1.34203596124778, -1.470354339494325, -1.603108766934165, -1.738323314187531, -1.8738896071110287, -2.007612733967403, -2.137259882384105, -2.260610558340389, -2.3755071932560528, -2.4799049281510426, -2.5719193763101855, -2.64987120770074, -2.7123264686054496, -2.7581316469037134, -2.786442614848573, -2.7967467241329045, -2.7888774890651096, -2.763021468883966, -2.7197171453809084, -2.6598457825635897, -2.58461444644544, -2.495531550516545, -2.394375471465786, -2.2831569459104344, -2.164076108185888, -2.0394751580040116, -1.9117877518547532, -1.7834862908305362, -1.6570283281686076, -1.5348033409932467, -1.4190811019790726, -1.311962848162759, -1.2153363768452812, -1.1308361040970598, -1.059809002114162, -1.00328719049311, -0.9619677968463873, -0.9362005279734283, -0.9259832082880471, -0.9309653518877647, -0.9504596431755711, -0.9834610129760432, -1.0286728171996273, -1.0845394576716152, -1.1492846338143365, -1.2209542831004059, -1.2974631607277727, -1.3766439273738675, -1.4562975600945585, -1.5342438766861421, -1.608370968649797, -1.6766823720834783, -1.7373408684492888, -1.788707896597876, -1.8293776713919496, -1.8582052398729172, -1.874327859745393, -1.877179253157496, -1.8664964671274114, -1.842319256063684, -1.8049820870706497, -1.755099050527132, -1.6935421322765727, -1.621413465379328, -1.5400123247754882, -1.4507977538241212, -1.355347814457606, -1.2553165301285212, -1.152389640979229, -1.0482403125608453, -0.9444859325085281, -0.8426470941053844, -0.7441098026115135, -0.6500918512603208, -0.5616142012394504, -0.4794780666733785, -0.40424825501929096, -0.3362431492149845, -0.27553154454821815, -0.2219363749488394, -0.17504518475387745, -0.13422702748087667, -0.09865530717716123, -0.06733592468351504, -0.0391399545275226, -0.012839961590836717, 0.012851026884654485, 0.03923894661538049, 0.0676076127415483, 0.09917823431310833, 0.13507061828548453, 0.1762671110821317, 0.22358025539566523, 0.2776250443351678, 0.33879653669377047, 0.40725345899202553, 0.48290826553365745, 0.5654239608888414, 0.6542178142097629, 0.7484719160077278, 0.8471503500038363, 0.9490225799161829, 1.052692487948593, 1.1566323524457305, 1.2592209204832805, 1.358784620439565, 1.4536408726955103, 1.5421423957898015, 1.622721372221565, 1.6939323335598628, 1.7544926487884915, 1.803319552366769, 1.8395627280940656, 1.8626315696206417, 1.8722163658109046, 1.8683028060278724, 1.851179363167008, 1.8214372869165394, 1.7799631219476413, 1.727923851030547, 1.6667449468344442, 1.5980817938301377, 1.5237851088455443, 1.4458611412482665, 1.3664275676232744, 1.2876661078066038, 1.2117729763891736, 1.140908344088993, 1.0771460151345715, 1.022424529140308, 0.9785008687431547, 0.9469078980934021, 0.9289165734524781, 0.9255038576309288, 0.9373271374204908, 0.9647057907274691, 1.0076103814853703, 1.0656597797018619, 1.1381263155697634, 1.2239488850300335, 1.3217537341844239, 1.4298824661521399, 1.5464266408355, 1.6692681798349152, 1.7961246493012704, 1.9245983762445473, 2.0522282616003427, 2.1765430884474353, 2.295115087759344, 2.4056125178410994, 2.5058500373034316, 2.593835704479566, 2.667813517296656, 2.726300514789955, 2.768117592071001, 2.792413331437097, 2.7986803197485326, 2.7867636021116895, 2.756861109896035, 2.709516092593468, 2.645601773331333, 2.5662986323411827, 2.4730648968782907, 2.367600975754043, 2.251808717920385, 2.127746494023846, 1.9975811946604254, 1.8635383069548022, 1.72785127046859, 1.5927113234266137, 1.4602190306760383, 1.3323386362296916, 1.2108563069716132, 1.0973432320819256, 0.9931244175621778, 0.8992538700701993, 0.8164967027512648, 0.7453185219218512, 0.6858822716619047, 0.6380525281256472, 0.6014070512901968, 0.5752552234866075, 0.5586628358080066, 0.5504825295113714, 0.5493890636061353, 0.5539184652794926, 0.562510029430389, 0.5735500695491473, 0.5854162860032884, 0.5965216102896075, 0.6053564050877697, 0.6105279493819574, 0.6107962141818359, 0.6051050354808173, 0.5926079144284487, 0.572687817102102, 0.5449705041054744, 0.5093310894808338, 0.46589370480069114, 0.41502432333174216, 0.35731697630791, 0.2935737641309728, 0.2247792254218678, 0.15206977223130408, 0.07669902671666334, 7.165134511644309e-16], [-0.0, -0.07644452976551071, -0.15086852879596005, -0.22197911898388314, -0.28858661126214114, -0.34964050868627733, -0.4042617243114531, -0.4517701372919218, -0.49170673088752226, -0.5238496958998683, -0.5482240389499752, -0.5651044030114666, -0.5750109834834465, -0.5786986023767955, -0.577139181358568, -0.5714980269358438, -0.5631045035833258, -0.5534178189947807, -0.5439887760830385, -0.5364184555275379, -0.5323148777617336, -0.5332487520940605, -0.5407094516101648, -0.5560623547505325, -0.5805086678538798, -0.615048788082191, -0.6604501842862247, -0.7172206664961887, -0.7855877854260335, -0.8654849548220024, -0.9565447253148727, -1.0580994626965061, -1.169189500578084, -1.28857865173265, -1.4147767786888545, -1.5460689468990605, -1.6805505174759867, -1.8161673852392446, -1.9507604354336976, -2.0821131823133636, -2.2080014676227706, -2.3262440390347106, -2.4347527993338067, -2.531581517378163, -2.6149718217074267, -2.683395356447085, -2.7355910655212576, -2.7705966830843813, -2.787773642837284, -2.786824773259898, -2.767804316038046, -2.731119986956262, -2.6775269878485863, -2.608114070235318, -2.524281941343553, -2.427714486674309, -2.3203434556570617, -2.2043074140096057, -2.081905904354901, -1.955549872060472, -1.8277095033342468, -1.7008606851253918, -1.5774313298075524, -1.4597488111427734, -1.3499897315482559, -1.2501331848597206, -1.1619185949678807, -1.086809100946494, -1.025961326273925, -0.9802022167261931, -0.9500134622261134, -0.9355238365056792, -0.9365095993053144, -0.9524029136078512, -0.9823080397716438, -1.0250248840267953, -1.0790793051133307, -1.142759424084223, -1.2141570423109331, -1.2912131548904233, -1.371766453786116, -1.453603649350013, -1.5345104019047695, -1.6123216476408158, -1.6849701253032905, -1.75053196137533, -1.8072682503638715, -1.8536616713369596, -1.8884473093962209, -1.9106369980797113, -1.9195366620838268, -1.9147563150829385, -1.8962125504397551, -1.864123548686476, -1.818996810199423, -1.7616099999201476, -1.6929854588873428, -1.6143590906018295, -1.5271444650898882, -1.4328930966634892, -1.3332519400523888, -1.229919211670636, -1.1245996768141202, -1.0189605488049003, -0.9145891224609545, -0.812953212457322, -0.7153653885389278, -0.6229518961976158, -0.5366270260024582, -0.45707355048726145, -0.3847296880348987, -0.31978288261067545, -0.2621705108166634, -0.21158744805957824, -0.1675002481928162, -0.12916752029253226, -0.09566592656859625, -0.06592108082170223, -0.03874250098360649, -0.01286166529000978, 0.013027857846328634, 0.04022928917075141, 0.07000163517724153, 0.10351990667232298, 0.14183763232080918, 0.18585268089445503, 0.23627732057668777, 0.29361333438342685, 0.3581328803004312, 0.42986563640512704, 0.5085926087814127, 0.5938468075540347, 0.6849208182252242, 0.7808811161976718, 0.8805887964557684, 0.982726222312965, 1.0858289411868465, 1.18832207550623, 1.2885602766593913, 1.384870232443687, 1.4755946462933178, 1.5591365615330084, 1.6340028872425425, 1.6988459945236707, 1.7525022928176763, 1.7940267644924492, 1.8227225305703891, 1.8381646389154647, 1.84021740555294, 1.82904479664341, 1.8051135091150936, 1.7691885878673752, 1.7223216023422812, 1.6658315905331202, 1.6012791595547, 1.530434304225721, 1.4552386644050528, 1.377763084088732, 1.3001614569338067, 1.224621940853903, 1.1533166961311991, 1.0883513452577223, 1.0317153672888373, 0.9852346244173494, 0.9505271740425447, 0.9289634468230672, 0.921631771776529, 0.9293101057909934, 0.9524446799150945, 0.9911361119948815, 1.0451333585693332, 1.1138356927128887, 1.1963027032528146, 1.2912721191518726, 1.397185075507356, 1.5122182591512225, 1.634322206603212, 1.7612648791711583, 1.8906795129302674, 2.02011563825691, 2.147092087066999, 2.269150757790084, 2.3839098895795954, 2.489115608772646, 2.5826905518921843, 2.6627784395222753, 2.727783572472819, 2.776404343410699, 2.8076600005942933, 2.820910062002426, 2.8158659540475193, 2.7925946349120094, 2.7515141538113865, 2.693381289503229, 2.6192715994522406, 2.5305523906509, 2.4288492898226814, 2.316007240559105, 2.1940468842443948, 2.0651173872907265, 1.9314468567191159, 1.7952915375968133, 1.658885008097121, 1.524388580517084, 1.3938440797390454, 1.2691301053459623, 1.1519227915860906, 1.0436619629761998, 0.9455234454762351, 0.8583981373279761, 0.782878273728175, 0.719251139744584, 0.6675003007578032, 0.627314233820735, 0.5981020612780724, 0.5790159142817614, 0.5689792927585072, 0.5667206438924134, 0.5708112568188636, 0.5797064700151106, 0.5917891122656961, 0.6054140498807038, 0.6189526931684127, 0.6308363244134514, 0.6395971474664476, 0.643906024476453, 0.6426059565706904, 0.6347404800414292, 0.6195762848875359, 0.5966195149192492, 0.5656253741874823, 0.5266008390371513, 0.47980045418187633, 0.42571537032027673, 0.365055955432873, 0.2987284776023144, 0.22780650980598888, 0.15349784279014247, 0.07710780742936263, 7.174339672743204e-16], [-0.0, -0.07600621652334698, -0.14940020569176737, -0.2189356245750217, -0.2834893509153016, -0.3420955649437893, -0.3939755274526465, -0.4385622418319183, -0.47551932003632424, -0.5047535223412334, -0.5264206044923636, -0.5409242793105261, -0.5489082785937236, -0.5512416807386948, -0.5489978453323687, -0.5434274635796671, -0.5359263885777341, -0.5279990481658171, -0.5212183618298247, -0.5171831788722113, -0.5174743252956745, -0.5236103897531219, -0.5370043933287671, -0.5589224733904802, -0.5904456685702134, -0.6324358210842175, -0.6855065157887686, -0.7499998549242689, -0.825969726370242, -0.9131720648784297, -1.0110624340708885, -1.1188010762257834, -1.2352653915024068, -1.3590696228811106, -1.4885913423254469, -1.6220041620223886, -1.757315936313855, -1.8924115790690899, -2.0250995013099073, -2.153160577926388, -2.2743984827593704, -2.3866901899797317, -2.4880354276710572, -2.576603887207256, -2.6507790390629653, -2.7091974810297, -2.75078284666261, -2.7747734277225575, -2.780742811379801, -2.7686129974588987, -2.7386596390433686, -2.6915092369981215, -2.6281283108507565, -2.549804760322059, -2.4581218189293983, -2.3549251789323034, -2.2422840310986905, -2.122446909324611, -1.9977933554511247, -1.8707825206181952, -1.7438998936999184, -1.619603392956648, -1.5002700728944771, -1.3881446840478902, -1.2852912793395923, -1.1935489878953474, -1.1144929774761994, -1.0494015024696097, -0.9992297886886605, -0.9645913426212114, -0.9457470952439464, -0.9426026034011065, -0.954713339608955, -0.9812979086672241, -1.021258841324871, -1.0732104360344703, -1.1355129538887205, -1.20631232318343, -1.2835843822847919, -1.3651825856663926, -1.4488880206034958, -1.5324605328939473, -1.613689740245218, -1.6904447220291554, -1.7607212136291615, -1.8226852015344386, -1.874711909919119, -1.915419288275054, -1.9436952497457878, -1.9587180676190912, -1.9599695090281446, -1.94724046600793, -1.9206290301481854, -1.8805311435588465, -1.8276241411009249, -1.7628436723330958, -1.6873546521074116, -1.6025170322746292, -1.5098473100192515, -1.4109767879419124, -1.30760767473853, -1.2014681614369969, -1.0942676255814354, -0.9876531041563432, -0.8831681357996989, -0.7822150050604962, -0.6860213278950428, -0.5956118006904424, -0.5117857978570826, -0.43510134895150016, -0.36586585930079735, -0.30413376244078655, -0.24971111280433522, -0.2021669475563192, -0.16085107180426214, -0.12491775602921278, -0.09335468265095259, -0.06501634399434894, -0.03866097995043742, -0.012990053194526804, 0.013310804792280065, 0.0415304808300773, 0.07289181301803264, 0.10851286255255269, 0.1493710695036017, 0.196271262949315, 0.24981839617462237, 0.310395755487999, 0.3781492496879981, 0.45297822989371694, 0.5345331203171031, 0.622219963876611, 0.7152118068016065, 0.812466668107232, 0.9127516675498434, 1.0146727237779625, 1.1167090869917686, 1.217251841275861, 1.314645404182899, 1.4072309678901627, 1.4933907694923525, 1.571592049235492, 1.6404295555428108, 1.6986654846180578, 1.745265799595065, 1.77943195828678, 1.800627187548665, 1.8085965734604166, 1.8033803867356848, 1.7853202282989642, 1.7550577567391197, 1.713525942987393, 1.6619329835204504, 1.6017391870345052, 1.5346273262997707, 1.4624671123711643, 1.387274598356724, 1.3111674507602549, 1.2363171347158548, 1.1648991424675075, 1.0990424500841802, 1.0407794141802984, 0.9919973175840149, 0.9543927404414168, 0.9294298718766117, 0.9183037884710363, 0.9219096115876981, 0.9408183186833607, 0.9752598275217786, 1.0251138004040097, 1.0899084323357067, 1.168827296911125, 1.2607241312404585, 1.364145251175809, 1.477359105042133, 1.5983923025278872, 1.7250712995312725, 1.855068783408261, 1.9859536895676266, 2.1152436924886824, 2.2404589541556548, 2.359175882085279, 2.469079648331767, 2.5680142501111534, 2.6540289512858815, 2.725420030461466, 2.780766873759324, 2.818961585701271, 2.8392314467660893, 2.841153717269354, 2.824662470098224, 2.790047325041376, 2.7379441503526882, 2.6693179880765943, 2.585438643897796, 2.487849555381397, 2.3783307102432425, 2.258856524917179, 2.1315497098249137, 1.9986322386202988, 1.8623746021143497, 1.7250445621082244, 1.5888566252005074, 1.4559234317565728, 1.32821020132548, 1.2074932942729009, 1.0953238423530323, 0.9929972710788176, 0.9015293873376489, 0.8216395404825023, 0.7537411882328259, 0.6979400145517786, 0.6540395598022866, 0.6215541385567386, 0.5997286420173649, 0.5875646544988649, 0.583852160952305, 0.5872059888080231, 0.5961060157482866, 0.6089400880952376, 0.6240485344017557, 0.6397691269747728, 0.6544813411475922, 0.6666487881314086, 0.6748587514758232, 0.6778578381101122, 0.6745828605115692, 0.6641861940328359, 0.6460549995506146, 0.6198238626464937, 0.5853805724014352, 0.5428649412185009, 0.49266074736736737, 0.4353810596098617, 0.3718473738307942, 0.3030631507584381, 0.2301824876013856, 0.15447478113189198, 0.07728634227113072, 7.162018293862331e-16], [-0.0, -0.07534397739993655, -0.14750325821435195, -0.21528878229318166, -0.2776537794926993, -0.33372562486222607, -0.3828329061252835, -0.4245269628263038, -0.45859729968512586, -0.4850804354054816, -0.5042619184069613, -0.5166714183861296, -0.5230709827699805, -0.5244367254395584, -0.5219343870508043, -0.5168893674960098, -0.5107519774297502, -0.5050587835923184, -0.5013910286275893, -0.501331187480556, -0.5064187771550042, -0.518106563162708, -0.5377183036542729, -0.5664091409634575, -0.6051296908210412, -0.6545947932085846, -0.7152577778080844, -0.7872909639645623, -0.870572963275355, -0.9646831860882434, -1.068903775449908, -1.1822290077971764, -1.3033820134988092, -1.4308384868669628, -1.562856879039404, -1.6975144025916258, -1.832748027996329, -1.9663995228489395, -2.0962634783874776, -2.220137186961213, -2.3358711808270036, -2.441419218378552, -2.534886509331465, -2.6145750054528065, -2.679024647362882, -2.7270495492600775, -2.7577682199593374, -2.7706270575987824, -2.765416513407014, -2.7422794932109253, -2.7017117496940473, -2.6445542093043977, -2.571977370506973, -2.4854581000744393, -2.38674933666862, -2.2778433816203507, -2.1609296113890215, -2.038347580888948, -1.9125365984047449, -1.7859829384448322, -1.6611659164963748, -1.5405040778278636, -1.426302750537016, -1.320704181001229, -1.225641408529846, -1.1427969468351504, -1.0735672251060133, -1.0190336037853922, -0.9799406229805241, -0.9566819686071824, -0.949294457103965, -0.9574601483422751, -0.9805165028633157, -1.0174743085069327, -1.0670429175068317, -1.1276621626820764, -1.1975401646374448, -1.2746961046849759, -1.3570069238228488, -1.4422568192958767, -1.5281883491245536, -1.6125539229518067, -1.6931664553270742, -1.767947985099898, -1.8349751211705603, -1.8925202589721306, -1.9390876215880175, -1.9734433115728958, -1.994638711019814, -2.00202673441137, -1.9952706171406756, -1.974345107850715, -1.93953012031902, -1.891397085862247, -1.8307884255744846, -1.758790728747678, -1.6767023754470067, -1.5859964737148646, -1.488280092024407, -1.3852508527307752, -1.2786520103373478, -1.1702271680456944, -1.0616757866436792, -0.9546106113838307, -0.8505180859158459, -0.7507227390664079, -0.6563564224749789, -0.5683331475723914, -0.48733012244680696, -0.4137754265499525, -0.3478425880885815, -0.28945214971142313, -0.23828012727717116, -0.19377308864524564, -0.15516940905730592, -0.12152610107072406, -0.0917504741612596, -0.06463575562672999, -0.038899703402029605, -0.013225165376073022, 0.013698509310208103, 0.043134322480737355, 0.07625785047189634, 0.11411991069471487, 0.15761267923175318, 0.20744017790723135, 0.2640939360368127, 0.3278344980446231, 0.3986792967183344, 0.4763972468871258, 0.5605102399253439, 0.6503015401193296, 0.7448309041283852, 0.8429560690809123, 0.9433600877322775, 1.0445838348206635, 1.145062871222428, 1.2431677352451624, 1.337246636416609, 1.4256694588618921, 1.5068719406007858, 1.5793988829438, 1.6419452610083323, 1.6933941518759659, 1.7328504700121927, 1.7596695985208564, 1.7734801272072651, 1.7742000512848362, 1.7620459443714218, 1.737534792243083, 1.7014783553719839, 1.6549701140705328, 1.5993650354792333, 1.536252582053535, 1.4674235521212176, 1.3948315002184672, 1.32054962432346, 1.2467241252769383, 1.1755251376127882, 1.1090963983158975, 1.049504858931356, 0.9986914559184351, 0.9584242338505912, 0.93025496641865, 0.9154803423347603, 0.9151086789925309, 0.9298329986020274, 0.9600111525677106, 1.0056535137112328, 1.066418576587471, 1.1416166179597624, 1.230221377071199, 1.3308895233653828, 1.4419874924605869, 1.561625094032253, 1.687695132145515, 1.8179181334950787, 1.9498911555111544, 2.081139547406024, 2.2091704653947954, 2.3315269002932717, 2.445840962538138, 2.5498851867211547, 2.641620664571377, 2.719240890820919, 2.7812103087106204, 2.8262966685375455, 2.853596460526442, 2.8625528488137166, 2.8529657124266805, 2.8249935874543035, 2.7791474975474837, 2.7162768527558274, 2.6375477848097035, 2.544414465717882, 2.438584121633355, 2.321976601345272, 2.196679484923564, 2.0648998199423287, 1.9289136479053133, 1.7910145302193177, 1.653462300238556, 1.5184332551928574, 1.3879729596095516, 1.2639527612610435, 1.1480310235337678, 1.0416199568858888, 0.9458587897954862, 0.8615938598671323, 0.7893660325536381, 0.7294056725775014, 0.6816352061362292, 0.6456791249840637, 0.6208811011264419, 0.6063277076433126, 0.600878081337621, 0.6031987204072429, 0.6118024886449039, 0.6250907997385495, 0.641397883433649, 0.65903599133309, 0.6763403849564805, 0.6917129626447162, 0.7036634245361554, 0.7108469450012752, 0.7120974177613033, 0.7064554579523953, 0.6931904845745489, 0.6718163625280609, 0.6421002518256196, 0.6040644883003159, 0.5579815007317036, 0.5043619492155511, 0.4439364442635919, 0.3776313711308187, 0.3065394950701596, 0.23188615680000813, 0.15499198007799092, 0.0772331020742551, 7.128288962184838e-16], [-0.0, -0.07446389894136872, -0.1451951182393137, -0.2110721627771047, -0.27113375771111387, -0.32460819026841053, -0.3709374189917346, -0.40979528823400496, -0.44109933860414435, -0.4650158702475737, -0.48195809110274124, -0.49257736217256914, -0.4977477318293125, -0.49854412666941306, -0.49621473299593655, -0.4921482563944468, -0.4878368831739877, -0.48483588318300097, -0.484720885707006, -0.48904392642424227, -0.4992894019978878, -0.5168310787710049, -0.5428912828735715, -0.578503351247884, -0.6244783477658451, -0.6813769475573356, -0.749487268348479, -0.828809283064665, -0.9190462867400792, -1.0196037168716832, -1.129595444065095, -1.2478574636654967, -1.3729687336779428, -1.5032787242791619, -1.6369410741048722, -1.7719525925246573, -1.9061967092114598, -2.0374903559555686, -2.1636331738182544, -2.282457873721716, -2.3918805421237668, -2.489949676518861, -2.5748927584042156, -2.645159223578042, -2.6994587699973556, -2.736794050021002, -2.7564869241533514, -2.758197604251722, -2.741936181919801, -2.708066218411952, -2.657300261428244, -2.590687347082346, -2.5095927373672247, -2.4156703299359212, -2.3108283533947516, -2.1971891232566563, -2.077043777253958, -1.9528030303415846, -1.8269450864471541, -1.7019619134642259, -1.5803051284288472, -1.4643327502638408, -1.3562580576533718, -1.2581017399943346, -1.171648451163892, -1.098408770946342, -1.0395874499328406, -0.9960586636901161, -0.9683488346474336, -0.9566273995560888, -0.9607057109353361, -0.9800440672502281, -1.0137666733869202, -1.060684145000513, -1.119322992078492, -1.1879613529142208, -1.2646701035942423, -1.347358343597208, -1.4338221581727715, -1.5217954852011952, -1.6090018699465658, -1.6932058765209475, -1.7722629402525756, -1.8441664900412673, -1.907091243005346, -1.9594316733983106, -1.9998347813742727, -2.0272264315975246, -2.0408306933063334, -2.0401817882191207, -2.025128436261885, -1.995830576939957, -1.9527486316208835, -1.8966256544046975, -1.8284628921346597, -1.7494894331943056, -1.661126766144941, -1.564949189529983, -1.4626411103897887, -1.3559523388786845, -1.2466525282024616, -1.1364859219484438, -1.0271275545345102, -0.9201420054605183, -0.8169457355221993, -0.7187739350457829, -0.6266526930577243, -0.5413771552267932, -0.4634961810073607, -0.3933038406770279, -0.33083791520622025, -0.2758853806224352, -0.22799467832065073, -0.1864943981730689, -0.15051783670881852, -0.1190327422127786, -0.09087542611770025, -0.06478830886497976, -0.03945988127874671, -0.01356600161912878, 0.01418858462480287, 0.04502961965243705, 0.0800746962444902, 0.12029764963827173, 0.16649694039043325, 0.219268886490273, 0.2789864771316224, 0.3457843557684244, 0.41955040003163585, 0.4999241548227054, 0.5863021967564641, 0.6778503276151282, 0.7735223161700965, 0.8720847361531522, 0.9721472876727382, 1.0721978440598992, 1.1706413397011755, 1.2658415101118325, 1.3561644160109427, 1.4400226305492105, 1.5159189445093098, 1.5824884489378623, 1.638537888243577, 1.6830812385481149, 1.7153705545379119, 1.734921241098287, 1.7415310408580316, 1.7352921821247058, 1.7165962997700215, 1.6861319202765708, 1.6448744869548566, 1.5940690876926118, 1.5352062308670733, 1.469991190661745, 1.4003076065886282, 1.3281761694209704, 1.2557093532772394, 1.1850632580372904, 1.1183877049528874, 1.0577757792078322, 1.0052140349395686, 0.96253457022683, 0.9313701418809198, 0.9131134233903295, 0.9088814156112003, 0.9194859009962034, 0.945410691160879, 0.9867962577994472, 1.0434321622508969, 1.1147575136233463, 1.199869493822187, 1.297539794765717, 1.4062386232243296, 1.5241657467264738, 1.649287884289689, 1.779381592515082, 1.9120806645837791, 2.044926950179522, 2.175423421022947, 2.301088251591802, 2.4195086590783697, 2.52839325133776, 2.625621666406206, 2.709290351275534, 2.7777534194426483, 2.8296576440746577, 2.8639707835819124, 2.880002595560149, 2.8774180695675127, 2.8562425947872514, 2.8168589707680782, 2.759996363450711, 2.6867114998571497, 2.5983625784898896, 2.496576544200497, 2.3832105318784462, 2.2603084190198115, 2.1300535397911493, 1.9947186999113968, 1.8566146904741267, 1.718038528356492, 1.5812226504603992, 1.4482862587964103, 1.3211899541739847, 1.2016947095379185, 1.0913261220006703, 0.9913447481897522, 0.9027231740339887, 0.826130301390297, 0.7619231541694733, 0.7101463203241918, 0.6705389578357949, 0.6425491073373029, 0.625354875818022, 0.6178918893591071, 0.6188862621379259, 0.6268921976993359, 0.640333229919212, 0.6575460278044554, 0.6768256322734133, 0.69647096564705, 0.714829456344915, 0.7303396520828171, 0.7415707538485055, 0.7472580885233789, 0.7463336479961374, 0.7379509541464653, 0.7215036587976322, 0.6966374518312264, 0.6632550249562847, 0.6215140187109754, 0.5718180615917628, 0.5148011881722193, 0.4513060932010436, 0.38235683666904857, 0.30912675673013806, 0.23290246958273844, 0.15504493489543908, 0.07694863959824139, 7.073463703085915e-16], [-0.0, -0.0733740510387285, -0.14249697797282798, -0.20632456942397936, -0.2639894586136317, -0.3148276863815348, -0.358399630107807, -0.39450472086445826, -0.42318953247018215, -0.4447489983758725, -0.4597206911057986, -0.46887227979107104, -0.4731824595738792, -0.4738158178094691, -0.4720922616983108, -0.46945177617675254, -0.4674154058991604, -0.46754345775412437, -0.47139199792624426, -0.48046876802261523, -0.49618966688515476, -0.5198369377726837, -0.5525201647137933, -0.595141117822561, -0.6483633967598582, -0.712587706508274, -0.7879334630186979, -0.874227271437429, -0.9709986503534376, -1.0774831960036906, -1.1926331950925009, -1.3151355084251561, -1.4434363645726584, -1.5757725278439658, -1.7102081423248032, -1.8446764077307705, -1.9770251169976343, -2.1050649830826402, -2.226619605993291, -2.339575882572238, -2.4419336423382245, -2.5318533032817236, -2.6077003817719944, -2.6680857597482364, -2.7119007085282854, -2.7383457895873913, -2.7469528956335005, -2.7375998567840605, -2.710517212720768, -2.6662869380854093, -2.6058331005436055, -2.530404624196799, -2.4415505206457024, -2.341088131362797, -2.2310650936770138, -2.1137158944767886, -1.991414006973511, -1.866620713312085, -1.741831796825542, -1.6195233403090148, -1.5020978895323558, -1.3918322337465565, -1.2908280173332343, -1.2009663299053501, -1.123867327711552, -1.0608558194237425, -1.0129336072144746, -0.9807592129218182, -0.9646354429818385, -0.9645050589747702, -0.9799546276336821, -1.0102264297039496, -1.0542381158513658, -1.1106096145446345, -1.1776966259343953, -1.2536298813578872, -1.336359213948426, -1.4237013751528638, -1.513390447409672, -1.6031296468200058, -1.690643282667062, -1.773727643690667, -1.8502996139523, -1.9184418830434464, -1.9764437046981072, -2.022836272299114, -2.056421916432449, -2.076296485118074, -2.081864437745917, -2.0728463648283397, -2.049278832947395, -2.0115066430854514, -1.9601677762124106, -1.896171477980956, -1.820670100273529, -1.7350254670811993, -1.6407706621155, -1.5395682425005681, -1.4331659642831882, -1.323351159392846, -1.211904928831744, -1.100557312742985, -0.9909445647930513, -0.8845695969350579, -0.7827665727171801, -0.6866705151494399, -0.5971926616279664, -0.5150021469526331, -0.4405144299200172, -0.3738867035317844, -0.31502034797394873, -0.26357030376864865, -0.21896106446584912, -0.1804088184171366, -0.14694911183410406, -0.11746926443816275, -0.0907446480971399, -0.06547784095103161, -0.04033959710724432, -0.014010526844029397, 0.014777634478889851, 0.04720227853557302, 0.08431276635276039, 0.12699686200516508, 0.17595166513456637, 0.23165983267190596, 0.2943717426964329, 0.36409409902417667, 0.44058530778700195, 0.523357781179655, 0.6116871431755447, 0.7046281319134677, 0.8010368182053097, 0.8995985936595197, 0.9988612294781389, 1.0972721719528487, 1.1932191265112582, 1.2850728917826535, 1.3712313409033094, 1.450163410852643, 1.5204519529955958, 1.5808343194744416, 1.6302396101867391, 1.6678215826294163, 1.692986330015682, 1.705413959271496, 1.705073646698933, 1.6922316116562797, 1.6674517235332453, 1.6315886402608282, 1.5857735630458294, 1.5313928773189054, 1.4700601294096551, 1.4035819577231197, 1.3339187519445697, 1.2631409501497626, 1.193381998199671, 1.1267890855413816, 1.065472834215263, 1.0114571518441153, 0.96663046372093, 0.9326995136171378, 0.9111468681391636, 0.9031931766284884, 0.9097651296856228, 0.9314699270036569, 0.9685769125094079, 1.0210068655217701, 1.088329254855138, 1.1697675729421129, 1.2642126737512345, 1.3702438462506135, 1.4861571691103652, 1.6100005167995588, 1.7396144265161995, 1.87267789343426, 2.006758042043639, 2.1393625268411594, 2.2679934486301274, 2.3902015348577397, 2.503639324705081, 2.6061121222477945, 2.6956255333885193, 2.770428483157501, 2.8290507174204396, 2.8703339244071593, 2.8934557635805347, 2.897946258495438, 2.883696192329543, 2.8509573352653534, 2.8003345272249427, 2.732769832874321, 2.649519173617766, 2.552122018930717, 2.442364882523434, 2.3222395135371343, 2.193896795757611, 2.059597465737653, 1.9216608314142813, 1.7824127146253192, 1.6441338529207064, 1.5090099780094817, 1.3790847406049123, 1.256216575575541, 1.1420404991184134, 1.0379357037285597, 0.9449996702112625, 0.8640293525365981, 0.7955098150462883, 0.7396105167748691, 0.6961892490245875, 0.6648035445059438, 0.6447291939623013, 0.6349853337319139, 0.6343654094015833, 0.641473180449947, 0.6547628119849389, 0.672582005228433, 0.6932170505588817, 0.7149386472901458, 0.7360473238362472, 0.7549173106546563, 0.7700377658121008, 0.7800503278985945, 0.7837820713671234, 0.7802730626051692, 0.7687978579897958, 0.7488804441933089, 0.7203022920477601, 0.6831033740064418, 0.6375761771354365, 0.5842529240326063, 0.5238863885519196, 0.45742485731074556, 0.38598193754651106, 0.31080204320575266, 0.23322250089548455, 0.1546333027520551, 0.07643559224875691, 6.998045711564291e-16], [-0.0, -0.07208441606849679, -0.139433598635254, -0.20108968210245348, -0.25628680853116403, -0.3044746704284098, -0.3453360649982171, -0.3787979720626422, -0.405035836293188, -0.42447091125257186, -0.4377607035503291, -0.4457827355797327, -0.44961202025686603, -0.4504928064813216, -0.44980530547627295, -0.4490282418819694, -0.44969818605042794, -0.45336671252661725, -0.46155649190926307, -0.47571745752684286, -0.4971841937054494, -0.5271356686327473, -0.5665583824539433, -0.6162139215071589, -0.6766118044403421, -0.7479883779141815, -0.8302923718273542, -0.9231775601437429, -1.026002797507895, -1.1378395182662653, -1.2574865978302696, -1.3834922911733858, -1.5141827842711142, -1.6476967259498982, -1.7820249541339725, -1.9150544957342024, -2.04461580681865, -2.1685321321090583, -2.284669802513973, -2.390988257921171, -2.485588580701578, -2.5667593534626905, -2.6330187119325656, -2.683151549132012, -2.716240938186991, -2.7316929755859625, -2.7292544011597992, -2.7090225218178277, -2.6714471489673097, -2.617324450124767, -2.5477828088489223, -2.464260979057919, -2.3684790053441396, -2.262402555524588, -2.1482014710829107, -2.0282034814579357, -1.9048441458656689, -1.7806141786094218, -1.658005378360644, -1.5394564170835712, -1.4272997492499147, -1.3237108766062196, -1.2306611486182475, -1.1498751951569135, -1.0827939780358538, -1.030544314336135, -0.993915570313204, -0.9733440538294645, -0.9689054498557499, -0.9803154521038875, -1.0069385489543596, -1.0478047282713236, -1.1016336781600264, -1.1668658837747654, -1.241699858221004, -1.3241346023356015, -1.4120162671315424, -1.5030878968640593, -1.5950410622996694, -1.6855681544550711, -1.772414099712261, -1.8534262779629511, -1.926601475704393, -1.9901287844891573, -2.0424274598204155, -2.082178883838702, -2.1083519237460586, -2.1202211431454696, -2.117377501220526, -2.0997313605258676, -2.0675078134960203, -2.02123452592559, -1.9617224779841524, -1.8900401553164345, -1.807481900220168, -1.7155312719385076, -1.6158203823641564, -1.5100862660907142, -1.4001254095431581, -1.2877476013267497, -1.174730274115083, -1.062774487245425, -0.9534636493277368, -0.8482260029406921, -0.748301790903647, -0.6547158983254936, -0.5682566198510934, -0.4894610409449309, -0.41860734975147523, -0.35571421641905343, -0.3005471943135657, -0.25263191688737935, -0.21127368966244206, -0.17558291322487427, -0.14450562442449003, -0.11685831286268211, -0.09136606149969557, -0.06670297652855824, -0.04153381463833017, -0.01455568684172418, 0.01546128211836948, 0.04963543115756319, 0.08893821276483058, 0.13416296794557012, 0.1858986709959568, 0.2445093594751505, 0.3101198168482873, 0.3826079126689893, 0.4616038319739932, 0.5464962461618028, 0.6364452965688634, 0.7304020838321186, 0.8271341854578358, 0.9252565651417982, 1.0232670943515767, 1.1195857831404095, 1.2125967162810904, 1.3006916151891281, 1.3823138977182592, 1.4560020880477287, 1.520431438116017, 1.5744526602365916, 1.6171267367783697, 1.647754865522786, 1.6659027162695266, 1.6714183125923627, 1.6644430089425457, 1.6454152037010563, 1.6150666090729564, 1.5744110844212442, 1.524726226133189, 1.4675280897479137, 1.404539594284321, 1.3376533201270713, 1.2688895563968106, 1.2003505778004642, 1.1341722313792666, 1.0724739877786726, 1.0173086577298422, 0.97061299112588, 0.9341603628901918, 0.9095167069999449, 0.8980007885089814, 0.9006498048861072, 0.9181911847918243, 0.9510213075164746, 0.9991917031942864, 1.0624031165440275, 1.140007629579207, 1.2310188460416098, 1.3341299469440262, 1.447739237287188, 1.5699826233748504, 1.6987722926162723, 1.8318407173852604, 1.9667889750923782, 2.10113827130271, 2.2323834740916646, 2.3580474178174393, 2.4757347143436417, 2.583183819980879, 2.678316146799479, 2.759281076526416, 2.8244958322926834, 2.872679285685126, 2.90287892090523, 2.9144903408313683, 2.9072688774497757, 2.8813330571344054, 2.837159865036956, 2.775571947677729, 2.697717083965028, 2.6050404376692473, 2.4992502744002225, 2.382277979262741, 2.2562333438940434, 2.123356200327657, 1.9859655614754548, 1.8464074820227243, 1.7070028779349569, 1.5699965370558926, 1.4375085176501161, 1.3114890671613813, 1.1936781015823987, 1.0855701689924797, 0.9883856819577063, 0.9030490460815014, 0.8301741399686557, 0.7700574195037905, 0.7226787311711981, 0.6877097298168326, 0.6645296104527181, 0.6522476860088874, 0.64973217771714, 0.6556444361138332, 0.6684776821063172, 0.6865992522813156, 0.7082952531802602, 0.731816477515526, 0.7554244124483506, 0.7774361765677894, 0.79626725784097, 0.8104709885637003, 0.8187737835427285, 0.8201052820455359, 0.8136226695216131, 0.7987286082682028, 0.7750823731850754, 0.7426039652992389, 0.701471157372047, 0.6521096080376019, 0.5951763589669333, 0.5315371990207443, 0.46223853597937475, 0.3884745562853016, 0.31155057279012666, 0.2328435567677113, 0.15376092102971722, 0.075698664099753, 6.90272517741743e-16], [-0.0, -0.07060679883360366, -0.13603308313667625, -0.195415651379986, -0.2480968692427071, -0.2936449769989766, -0.3318681044079477, -0.3628215997605388, -0.3868084538261522, -0.40437277939480293, -0.4162864883622551, -0.42352948626001674, -0.4272638742698264, -0.42880280675773, -0.42957479419129685, -0.4310843633426103, -0.4348700858002117, -0.4424610594583101, -0.4553329739008466, -0.4748649082164999, -0.5022979982503899, -0.5386970698317765, -0.5849162660534011, -0.6415696018599162, -0.7090072603361423, -0.7872983050837227, -0.8762203253847322, -0.975256359370489, -1.0835992593935044, -1.200163477738206, -1.323604064335613, -1.4523424859229424, -1.5845987026704986, -1.7184287780355303, -1.8517671545293606, -1.982472605814909, -2.108376777193613, -2.227334154613794, -2.337272258707186, -2.4362408462097407, -2.5224589168928766, -2.594358369528305, -2.6506232244066066, -2.690223430791259, -2.712442403012814, -2.7168975756819504, -2.703553433179029, -2.672726647168423, -2.6250831440450137, -2.5616271173621037, -2.483682193698431, -2.3928651493680335, -2.291052755232919, -2.180342493236434, -2.0630080370501593, -1.941450516763355, -1.8181466907012078, -1.6955952236920766, -1.5762623185277227, -1.4625279647916916, -1.3566340562221688, -1.260635584622911, -1.1763560460758602, -1.105348095589298, -1.0488603617548213, -1.0078111865138422, -0.9827698903148687, -0.973945983790032, -0.9811865579561054, -1.003981890457029, -1.041479110245578, -1.092503572097895, -1.1555874101080414, -1.2290045702440098, -1.310811470257939, -1.3988923043999246, -1.4910079036371848, -1.584846981984334, -1.678078548003551, -1.7684042387312593, -1.8536093416916941, -1.931611308988355, -2.000504634705262, -2.0586010612772485, -2.1044641997115847, -2.136937789565804, -2.155166983881628, -2.1586122178714664, -2.147055403737547, -2.1205983830218376, -2.0796537576609477, -2.02492840676945, -1.9574001735201159, -1.8782883709740497, -1.7890189033097907, -1.6911849260083047, -1.5865040720868644, -1.4767733489484154, -1.3638228599862536, -1.2494695256170862, -1.1354719694944606, -1.0234876975993183, -0.9150336317603373, -0.8114509666683857, -0.713875203014022, -0.6232120719866991, -0.5401199115376883, -0.4649988864650797, -0.3979872667984614, -0.33896479663627055, -0.2875630031260604, -0.24318211727762776, -0.20501410924392993, -0.17207118484611578, -0.1432189513715301, -0.11721334251673912, -0.09274029773997203, -0.0684571225917121, -0.04303441551769392, -0.015197434187661604, 0.01623420911310632, 0.05230958852193452, 0.09391323525663406, 0.14173653329240096, 0.19625451466314542, 0.2577086882608476, 0.3260963789045665, 0.40116688395997385, 0.48242457720577986, 0.5691389084661628, 0.6603610673527925, 0.7549469048588159, 0.8515855419563597, 0.9488329439572022, 1.0451496070386994, 1.1389413924005278, 1.2286024568540428, 1.3125591685009865, 1.3893138641146898, 1.4574873017739618, 1.5158586883709018, 1.5634022162414836, 1.599319125056976, 1.623064412284918, 1.6343674453626091, 1.6332458780339585, 1.620012438397701, 1.595274333015229, 1.5599251955415663, 1.5151296951931315, 1.4623011052924146, 1.4030723105112197, 1.3392608988018107, 1.2728291361542199, 1.2058397554119582, 1.1404086010461862, 1.078655257207098, 1.0226528443395306, 0.9743781986398649, 0.9356636478322218, 0.9081515660759338, 0.8932528309468394, 0.8921102177465153, 0.9055676529621323, 0.9341461122402711, 0.9780267920389677, 1.0370420119648982, 1.1106741208677915, 1.1980624885306046, 1.298018470926482, 1.4090480452496825, 1.5293816259600037, 1.6570103994407557, 1.789728356818777, 1.9251790659133083, 2.0609061075782513, 2.1944060117289474, 2.3231824663241327, 2.4448005400447093, 2.556939657191297, 2.6574440914878332, 2.744369803360381, 2.8160265314631268, 2.871014161656228, 2.9082525325719275, 2.9270039930280793, 2.9268881990612234, 2.907888823053323, 2.8703520398193523, 2.814976849922918, 2.7427974941390607, 2.6551584001788475, 2.553682278982141, 2.440232148800787, 2.316868207039256, 2.185800588974493, 2.0493391461792223, 1.909841443489023, 1.7696602101334709, 1.6310914873625955, 1.4963246914525512, 1.3673957580170488, 1.2461444524595107, 1.1341768242384138, 1.0328336520862016, 0.9431655766937007, 0.8659154504064775, 0.8015082543333937, 0.7500487463880654, 0.7113268137997609, 0.6848303152367023, 0.6697650155272636, 0.6650810445240812, 0.6695051551374394, 0.681577917793305, 0.6996948729000493, 0.7221505721318595, 0.7471843756270161, 0.7730268370490784, 0.7979455026474661, 0.8202889740284429, 0.8385281366228199, 0.851293535413574, 0.8574079842872504, 0.8559136226944856, 0.84609277988668, 0.8274821691017743, 0.7998801075849791, 0.763346638854712, 0.7181966165961249, 0.6649859903667948, 0.6044917073754953, 0.5376858075648976, 0.4657044369965604, 0.3898126333931729, 0.3113658444096507, 0.23176922111215648, 0.15243578420018677, 0.07474458734661857, 6.788373241547722e-16], [-0.0, -0.06895471817307365, -0.132326614965831, -0.1893546472661821, -0.23949516746803906, -0.28243880867114607, -0.31812082681758497, -0.346724604597923, -0.3686782002188982, -0.3846440056228703, -0.39550175888313827, -0.40232532969610196, -0.406353860724398, -0.4089579968447748, -0.4116020653123276, -0.41580317911782994, -0.42308832057771734, -0.43495052025982683, -0.4528052761829635, -0.47794835901256594, -0.5115161206140033, -0.5544493664566272, -0.6074617683391222, -0.6710136847667819, -0.745292124724136, -0.8301974397894805, -0.9253371632560697, -1.0300272372781363, -1.1433006844612719, -1.2639235933622721, -1.3904181027184799, -1.521091891509174, -1.6540735156176682, -1.787352781095357, -1.918825212633341, -2.0463395671555986, -2.167747259236324, -2.280952509462774, -2.3839620003833955, -2.474932828050752, -2.55221757040391, -2.6144053561104768, -2.6603579075572905, -2.6892396473064677, -2.700541095750107, -2.6940949455648893, -2.670084372063257, -2.629043323445082, -2.5718487267682684, -2.499704739496912, -2.414119368006837, -2.3168739587418647, -2.209986240300079, -2.095667751351811, -1.9762766260986582, -1.8542668226081815, -1.7321349669979722, -1.6123660459273874, -1.4973792097049534, -1.3894749477788133, -1.2907848674362716, -1.203225245928839, -1.1284554374225761, -1.0678421013003838, -1.0224300802030661, -0.9929205981483694, -0.9796572749578808, -0.9826202672890755, -1.0014286533403314, -1.0353509824736873, -1.0833237173474337, -1.1439771093762388, -1.2156678729761614, -1.2965178643578181, -1.3844578304674149, -1.477275176423731, -1.5726646082750482, -1.6682804442849628, -1.7617893537427367, -1.8509222782530255, -1.9335243166177243, -2.0076014100662425, -2.071362748280779, -2.123257926275789, -2.162008014966681, -2.1866298608778556, -2.1964530990888447, -2.191129544005588, -2.1706348103955992, -2.1352622076916603, -2.085609139143092, -2.0225564193305194, -1.9472410943877925, -1.8610235048069848, -1.7654494671412402, -1.662208564949979, -1.553089628199078, -1.4399345419143053, -1.3245915577508325, -1.2088692855642906, -1.0944925160630568, -0.9830609709337224, -0.8760119949213474, -0.7745880973493167, -0.6798101212369606, -0.5924566698269823, -0.5130502567468388, -0.4418504713515453, -0.3788542694523741, -0.32380331620789854, -0.2761981270676196, -0.2353185788685917, -0.2002502008627479, -0.16991550867292557, -0.14310951661966004, -0.11853845872141103, -0.09486066857412162, -0.07072851525513572, -0.044830267683113975, -0.015930764096535082, 0.01709020364350328, 0.0552028202228806, 0.099196433422743, 0.14965382739563293, 0.20693128012953965, 0.2711449517113346, 0.3421639850181743, 0.4196105255308645, 0.5028666865117805, 0.5910883043977067, 0.6832251515276289, 0.7780471037708582, 0.8741756035536759, 0.970119618204624, 1.0643151730404017, 1.1551674412863135, 1.241094301278278, 1.320570227296755, 1.392169365016208, 1.4546066563763884, 1.5067759214216583, 1.5477838753133943, 1.5769791555976693, 1.5939755555454114, 1.5986688010118615, 1.5912463672946677, 1.572190004970317, 1.542270825377526, 1.5025369827748651, 1.4542941765830673, 1.399079378874138, 1.338628364838202, 1.274837783011864, 1.2097226435822142, 1.1453702235084409, 1.0838914834646673, 1.0273711612317042, 0.9778177473372817, 0.9371145603487868, 0.9069731208765033, 0.8888899754040757, 0.8841080446168762, 0.8935834677434472, 0.9179587870203112, 0.957543167799365, 1.0123001836313472, 1.0818435159108681, 1.1654407287314947, 1.262025086081203, 1.3702151851361442, 1.4883419909160172, 1.6144826785656976, 1.7465005244166565, 1.8820899398143118, 2.018825616094102, 2.154214648146042, 2.2857504302170066, 2.4109670727935857, 2.52749307470651, 2.63310300038497, 2.725765958103198, 2.80368975000235, 2.8653596668270915, 2.9095710272093664, 2.9354547098790484, 2.9424950937681547, 2.9305400015475116, 2.8998024322961684, 2.8508540641255253, 2.784610702913614, 2.7023100440997627, 2.6054822961100474, 2.4959143820214584, 2.3756085864576013, 2.2467366438061043, 2.111590368550413, 1.9725300063100348, 1.831931533239908, 1.6921341506180576, 1.5553892103493432, 1.423811766078437, 1.2993358747150159, 1.1836746762169543, 1.0782861579020444, 0.9843453664160005, 0.9027236693514713, 0.8339754934004848, 0.7783327811804416, 0.7357072190783556, 0.7057000983013819, 0.6876194854941984, 0.6805042023584983, 0.6831539500292556, 0.6941647675307792, 0.7119688880209075, 0.7348779547773998, 0.7611284834308027, 0.788928409587905, 0.8165035428026073, 0.8421427591907168, 0.8642408054710913, 0.8813376557408263, 0.892153457053569, 0.895618218413107, 0.8908955370763043, 0.8773998125250052, 0.8548065681375777, 0.8230556791664133, 0.7823474885917724, 0.7331319751563796, 0.6760913157839156, 0.6121163531714706, 0.5422776343846571, 0.46779182388366297, 0.3899844111217916, 0.31024972576644155, 0.23000934037892576, 0.15066997939661408, 0.0735820635314906, 6.656034140218279e-16], [-0.0, -0.06714328129962294, -0.12834816586787728, -0.18296236695227253, -0.23056097838353323, -0.27095978101699414, -0.3042218113624581, -0.33065699827583933, -0.350814854484653, -0.36547039119862457, -0.37560360151046956, -0.3823730272126761, -0.38708407974761333, -0.3911529252933053, -0.39606686290755316, -0.40334222015899446, -0.41448086030062115, -0.4309264369721095, -0.45402154552856444, -0.48496690398367426, -0.5247836515568096, -0.5742797799838734, -0.6340216138483631, -0.7043111336268194, -0.7851697919336813, -0.8763293131296899, -0.9772297929960759, -1.0870252328813288, -1.2045964561361704, -1.328571168420306, -1.4573507422479302, -1.5891431344796978, -1.722001187680771, -1.8538654263265801, -1.9826103402929962, -2.1060930539365916, -2.2222032117731256, -2.328912873058854, -2.4243251985242127, -2.506720733425174, -2.5746001415449933, -2.6267223236466575, -2.662136959288083, -2.6802106403519472, -2.680645914995717, -2.6634927283583947, -2.629151927199156, -2.578370685287028, -2.5122299001828288, -2.432123805317138, -2.339732229239597, -2.2369861119864596, -2.1260270523135745, -2.0091618050432265, -1.8888127713928122, -1.767465623841115, -1.6476152784022031, -1.5317114693451976, -1.4221051933604465, -1.3209972716089502, -1.2303902294291202, -1.1520446158786575, -1.087440780632163, -1.0377469965748465, -1.0037946658660442, -0.9860611789546615, -0.9846608141065821, -0.9993438738789243, -1.0295040592991156, -1.0741938870387346, -1.1321477643659186, -1.2018121557443346, -1.2813821080111016, -1.368843252154452, -1.4620182724224482, -1.5586167308909449, -1.6562870601581052, -1.752669490300124, -1.8454486596940753, -1.9324046731241775, -2.011461414329761, -2.0807309926820774, -2.1385533031443793, -2.1835298025670187, -2.2145507505914055, -2.2308153263607116, -2.231844208807323, -2.2174843941276157, -2.187906214562505, -2.1435927130722643, -2.0853217142317946, -2.014141108110879, -1.9313380267161266, -1.8384027377779082, -1.7369882047319025, -1.628866361669149, -1.5158822254139237, -1.3999070120040207, -1.2827914406672523, -1.166320394616814, -1.0521700650693924, -0.9418686339903481, -0.8367614540533811, -0.7379815636766203, -0.6464262338580429, -0.5627400854797837, -0.48730514479989195, -0.42023802533144883, -0.3613942407608236, -0.3103794706087838, -0.26656742259816824, -0.22912376762924241, -0.19703546909859845, -0.16914469189498063, -0.14418636117942615, -0.12082834988546402, -0.09771320902753054, -0.07350031798764746, -0.04690732386310413, -0.016749759876265303, 0.018022217783801007, 0.05829095877108104, 0.10474319535729931, 0.15784742508356253, 0.2178374133284685, 0.28470227014009164, 0.3581833842180271, 0.4377783180495714, 0.5227515864379216, 0.6121520606215506, 0.7048365664440193, 0.7994990820079612, 0.8947047920857127, 0.9889281270416912, 1.0805938064624094, 1.1681198248550597, 1.2499612608122808, 1.3246537634242193, 1.3908555712142374, 1.447386949516148, 1.4932659913021353, 1.5277398125994839, 1.5503102847081238, 1.5607535787283857, 1.5591329501450786, 1.545804358625708, 1.521414696625242, 1.4868925854109218, 1.4434318841174438, 1.3924682417452663, 1.3356491990094563, 1.2747985121915018, 1.2118755204824876, 1.1489305079602852, 1.0880571180236651, 1.0313429590838763, 0.9808195934918875, 0.9384131256462879, 0.905896599291015, 0.8848453782226178, 0.8765966197711967, 0.8822138580057509, 0.9024575958361625, 0.9377626648641093, 0.988222952359911, 1.0535839199762704, 1.1332431530025047, 1.2262589866425158, 1.3313670616638436, 1.4470044705623426, 1.5713409718024685, 1.7023165782307461, 1.8376846706320658, 1.975059652422736, 2.11196804997623, 2.2459018778132025, 2.3743730309687683, 2.494967439699268, 2.605397724999004, 2.7035531271114626, 2.787545542540764, 2.855750596473722, 2.906842794798754, 2.939823940209049, 2.954044156794503, 2.9492150431697555, 2.92541466128016, 2.883084262020502, 2.823016844972006, 2.7463378431401604, 2.654478409854063, 2.5491419594441345, 2.4322647717192964, 2.305971608784514, 2.172527408033385, 2.034286204449531, 1.8936384965280346, 1.7529583017481072, 1.614551148883777, 1.480604225566379, 1.3531398411902578, 1.2339732789821491, 1.1246759990205997, 1.0265450190106093, 0.9405791450641589, 0.8674625544604501, 0.8075560505902508, 0.7608961215307714, 0.7272017426191274, 0.7058886747077101, 0.6960908281389949, 0.6966880923312004, 0.7063398763856733, 0.7235234710806202, 0.7465762302822009, 0.7737404828905364, 0.8032100270153255, 0.8331770275262559, 0.8618781371092139, 0.8876386894059185, 0.9089138699145831, 0.924325854562505, 0.9326960150350797, 0.9330714212487601, 0.924745021430389, 0.9072690452921054, 0.8804613515829925, 0.8444046234081832, 0.7994384985346218, 0.7461449028170293, 0.6853270283248833, 0.6179825593730988, 0.5452718954003766, 0.4684822458486658, 0.3889885757194498, 0.3082124587357636, 0.22757994607920562, 0.14847958124161856, 0.07222168509188005, 6.506915612942926e-16], [-0.0, -0.06518904210514287, -0.12413417521394642, -0.17629750645906078, -0.22137657033929334, -0.2593139315904474, -0.2902999132256655, -0.31476835861845454, -0.3333855184829786, -0.3470323334967551, -0.3567805565424399, -0.3638633207145353, -0.3696409062152366, -0.3755625873016194, -0.3831255462672846, -0.3938319223241053, -0.4091451170964758, -0.4304465038312187, -0.45899368365389087, -0.4958813992912392, -0.5420061553862923, -0.5980355063270227, -0.664382859539423, -0.7411885072338378, -0.8283074459684734, -0.9253043749092875, -1.0314560845034817, -1.1457612619033146, -1.2669575525013363, -1.3935455330410949, -1.5238190755560026, -1.655901417289362, -1.7877861038947718, -1.9173818453475084, -2.042560219364779, -2.161205078416266, -2.2712624656492997, -2.3707898236086584, -2.458003288129244, -2.5313218981094896, -2.589407619184486, -2.63120017404127, -2.65594579200428, -2.663219132690022, -2.652937799553532, -2.6253690351206234, -2.581128376338248, -2.521170241229053, -2.4467706121951363, -2.3595021721275855, -2.261202432264227, -2.1539355610111413, -2.039948776516234, -1.9216242988747076, -1.8014279671714712, -1.6818557094211224, -1.5653791077933623, -1.4543913259507173, -1.3511546592473989, -1.2577509320612563, -1.1760359005191565, -1.1075987249159216, -1.0537274564912746, -1.0153813408187593, -0.9931705783349791, -0.987344005428849, -0.9977849713273332, -1.0240154913349535, -1.0652085605454291, -1.1202083187222769, -1.1875575713419706, -1.2655319983168305, -1.352180224871168, -1.4453687922328624, -1.542830952523733, -1.642218125205722, -1.7411527937389286, -1.8372815921081531, -1.9283273322212038, -2.0121387547754073, -2.0867368471840737, -2.1503566609894484, -2.201483675616211, -2.238883892469633, -2.2616269998300655, -2.269102120847298, -2.2610258399297125, -2.2374423924229885, -2.198716093997348, -2.145516274888942, -2.0787951654277044, -1.9997593486826242, -1.909835549421797, -1.810631662180887, -1.703894031820246, -1.5914620848662275, -1.4752214671574058, -1.3570568715252251, -1.2388057378284525, -1.1222139767671988, -1.0088948093943324, -0.9002917276995609, -0.7976464703141359, -0.7019727741362544, -0.6140365109127113, -0.5343426513925325, -0.4631293228115294, -0.4003690426456111, -0.34577702739850724, -0.2988262943049475, -0.25876910078262877, -0.2246641056000455, -0.19540849107568953, -0.1697741608071145, -0.14644702556326225, -0.12406831359673925, -0.10127679263759577, -0.07675077041890867, -0.04924874923941108, -0.01764764753967196, 0.01902243321922725, 0.06154782660777731, 0.11050611913537788, 0.16624684673173556, 0.2288785948788826, 0.2982628602912843, 0.37401485556681285, 0.4555112569377746, 0.5419047137384915, 0.6321447610816157, 0.7250046089994133, 0.8191131262379633, 0.9129911989430026, 1.0050915271702963, 1.0938408284992727, 1.177683350443471, 1.255124553599231, 1.3247738166223066, 1.3853850325132044, 1.4358940129342548, 1.4754516922583853, 1.503452223946774, 1.519555186202113, 1.5237012585859937, 1.5161208928455974, 1.4973356755614482, 1.4681522630698278, 1.429648955875999, 1.3831551657939938, 1.33022420967069, 1.272600034245527, 1.212178633169021, 1.1509650555039632, 1.0910270216569318, 1.0344462546595623, 0.9832686996699194, 0.9394548407900355, 0.9048313308022723, 0.8810451259533656, 0.8695212649437768, 0.8714253500233541, 0.8876316804688571, 0.9186978572950977, 0.964846525994257, 1.0259547550872554, 1.1015513664124357, 1.1908223428000746, 1.2926242447313807, 1.4055053745043387, 1.5277342390551314, 1.6573346855106579, 1.7921269211252386, 1.9297734854796593, 2.067829121237211, 2.2037933933625897, 2.3351648379048373, 2.459495381937915, 2.574443767041079, 2.6778267300412, 2.7676667461382207, 2.842235219764042, 2.900090115648703, 2.94010715399139, 2.96150384616659, 2.9638558173312988, 2.947105045504086, 2.9115598387037442, 2.8578865678925633, 2.787093368995572, 2.7005062174085386, 2.5997379585454894, 2.4866510437401144, 2.3633148681894403, 2.231958733052366, 2.0949215542697806, 1.9545995137541572, 1.813392892574643, 1.6736533396245854, 1.53763281273072, 1.407435382718133, 1.284973015792082, 1.1719263476458153, 1.0697113365203497, 0.9794525351847571, 0.9019635571439705, 0.8377351344082848, 0.786930977285078, 0.7493914555013482, 0.7246449292530117, 0.7119263732001493, 0.7102027605458523, 0.7182045124595856, 0.7344621741871982, 0.7573473567283715, 0.7851168849181032, 0.8159590214691842, 0.8480405936951394, 0.8795538362049747, 0.9087617790767776, 0.934041056372134, 0.9539210831197054, 0.9671186481528224, 0.9725670928677329, 0.9694393889319398, 0.9571645875720244, 0.9354372852549472, 0.9042199309865804, 0.8637379845292442, 0.8144681179457246, 0.757119830402241, 0.6926110136461606, 0.6220381588139972, 0.5466420303829144, 0.46776974677520194, 0.38683429652443885, 0.305272581792633, 0.22450311583667945, 0.14588450691536672, 0.07067583798832817, 6.342377667793834e-16], [-0.0, -0.06310984484180379, -0.11972320426283867, -0.1694212014868243, -0.21202641836861996, -0.2476087028845321, -0.2764840238791614, -0.299206385979727, -0.31655299908212203, -0.32950307355565783, -0.33921077981478254, -0.3469730649050704, -0.3541931553231519, -0.36234069094689575, -0.3729095267268971, -0.3873743043146451, -0.4071469333654726, -0.43353413084532466, -0.4676971460059488, -0.5106147492244582, -0.5630504858055103, -0.625525092988254, -0.6982948523059026, -0.7813365032208545, -0.8743391812205275, -0.976703668347346, -1.0875490608095217, -1.2057267714489217, -1.3298415990979364, -1.4582794168908406, -1.5892408619246667, -1.7207802535616927, -1.8508488310485487, -1.9773412864627504, -2.0981444792151303, -2.2111871557530405, -2.314489464371379, -2.406211051080799, -2.4846965485030954, -2.5485173252182083, -2.5965084466010233, -2.627799907985004, -2.641841334347785, -2.6384194944177346, -2.617668147427671, -2.5800699235526214, -2.5264501299068756, -2.4579625681802417, -2.3760676428112877, -2.2825032253001734, -2.179248916271161, -2.0684845078780163, -1.9525435911385467, -1.8338633722851538, -1.7149318562694902, -1.5982336218277036, -1.4861954493420586, -1.381133069190198, -1.2852002741635244, -1.2003415854183068, -1.1282495785907363, -1.070327867156248, -1.0276606064967386, -1.0009892276980181, -0.9906969385862942, -0.9968013450966595, -1.0189553532340103, -1.05645631532814, -1.1082631887803704, -1.1730212858013522, -1.2490940133565287, -1.3346008380167278, -1.4274605646414171, -1.5254388943233346, -1.6261991287685276, -1.7273548176263762, -1.8265231038916694, -1.9213775113274767, -2.0096989371119576, -2.089423662057541, -2.158687268514769, -2.2158634604848833, -2.259596908900167, -2.2888293942804165, -2.3028186853211583, -2.3011497712853206, -2.2837382539136875, -2.2508258962987897, -2.2029685170538467, -2.1410166034556792, -2.066089192498038, -1.9795417296690605, -1.882928757838182, -1.777962409440609, -1.6664677712654241, -1.5503362602891626, -1.4314781895275255, -1.3117757138953932, -1.1930373273960313, -1.0769550351698602, -0.9650652483104033, -0.8587143478794003, -0.7590297398435619, -0.6668970779060667, -0.5829441701026984, -0.507531911664333, -0.4407524053999862, -0.38243424630349815, -0.33215476388160897, -0.2892588384489671, -0.25288374078765724, -0.22198929230736542, -0.19539250897802876, -0.17180578018269774, -0.14987754604721423, -0.12823437591788256, -0.10552331797769951, -0.08045338630390665, -0.05183507703264481, -0.018616859036866013, 0.020082334745990017, 0.0649454835461951, 0.11643546287965115, 0.17477923001646356, 0.23995864215778037, 0.31170816543966134, 0.3895195529081782, 0.4726533874664863, 0.5601572061053925, 0.6508897490574657, 0.7435507162507261, 0.8367152676869138, 0.9288723778496428, 1.0184660501973202, 1.1039383188901553, 1.1837729131865162, 1.2565384367860364, 1.3209299204444376, 1.3758076413540834, 1.4202321662589992, 1.4534946655260892, 1.4751416602232938, 1.4849935008377169, 1.48315603122935, 1.4700250609185128, 1.4462834486357574, 1.4128907857421509, 1.3710658550212191, 1.3222622237755794, 1.2681375055321888, 1.2105169875616877, 1.151352467741754, 1.0926772703372538, 1.0365585128233017, 0.9850477723098496, 0.940131348450053, 0.9036813386340539, 0.8774087302175317, 0.86281967368316, 0.8611760308959805, 0.8734611956191289, 0.9003520615121463, 0.9421978688683134, 0.9990064988390721, 1.0704386067856893, 1.1558097990021725, 1.2541008639416278, 1.3639758749724344, 1.4838077913457892, 1.6117110021410206, 1.7455800889400486, 1.883133931026201, 2.021964145751067, 2.159586749605849, 2.2934958451239638, 2.4212180870315057, 2.540366659349463, 2.6486935040028317, 2.744138580722655, 2.8248750067096293, 2.8893490210123276, 2.9363138405277462, 2.964856619001207, 2.974417883878096, 2.9648030043691525, 2.936185433292269, 2.8891016605449464, 2.824438012692515, 2.743409626347044, 2.6475321080654366, 2.5385865659206694, 2.418578853516837, 2.2896940022615966, 2.1542469289217796, 2.0146305901982178, 1.873262812247488, 1.7325330494351843, 1.5947503225444555, 1.4620935523515703, 1.336565440822327, 1.2199509608079948, 1.1137813983302869, 1.019304752268841, 0.9374631379745859, 0.8688776679630377, 0.8138410986924769, 0.7723183420576937, 0.743954748330756, 0.7280918785832403, 0.723790303767549, 0.7298587990523162, 0.7448891498192495, 0.7672956536416708, 0.7953582937779325, 0.8272684768405514, 0.8611761723102849, 0.89523726572291, 0.9276599412075066, 0.9567489424021499, 0.9809466226851314, 0.9988697844984522, 1.0093414209983602, 1.011416608429752, 1.004401951036149, 0.9878681480852232, 0.9616554304609768, 0.9258717977525269, 0.880884171229382, 0.8273027588910136, 0.7659591013710959, 0.6978784275336709, 0.6242470921108233, 0.5463759911112877, 0.4656609508989805, 0.38354116130950033, 0.301456770099537, 0.22080677426153597, 0.14290833285985133, 0.06895858636370435, 6.163919815048678e-16], [-0.0, -0.060924654739736295, -0.11515556877943013, -0.16239644308670356, -0.20259639441442528, -0.2359519095298216, -0.26290182872162354, -0.28411547563860645, -0.30047422994831907, -0.31304701136541807, -0.3230603039103866, -0.33186349374018503, -0.34089041885662735, -0.3516181312481182, -0.3655239489264851, -0.38404192488842526, -0.40851988095126085, -0.4401781460945868, -0.4800711015264433, -0.5290525690594717, -0.587745987113897, -0.656520202016125, -0.7354715641058774, -0.8244128619173656, -0.9228694572371795, -1.0300828034032021, -1.1450213432933116, -1.2663985967044882, -1.3926980639179234, -1.52220439777366, -1.6530401349288848, -1.7832071322272407, -1.9106317299302682, -2.033212563121096, -2.1488698684651673, -2.2555950876368693, -2.3514995523292224, -2.4348610493633553, -2.5041671077690912, -2.558153921843497, -2.5958399234218117, -2.616553140551725, -2.6199516254679014, -2.606036398695838, -2.575156534292053, -2.5280061993116214, -2.4656136539918068, -2.389322413120325, -2.300764958864298, -2.201829576311545, -2.0946210506697556, -1.9814161153510776, -1.864614669331969, -1.7466878870263007, -1.6301244218425217, -1.5173759536694063, -1.4108033495116334, -1.3126246948751819, -1.2248664115318177, -1.1493186059643665, -1.0874956938219584, -1.0406032214877392, -1.0095116593893472, -0.994737776520483, -0.9964340258024894, -1.0143861797707296, -1.0480192602457512, -1.096411608906183, -1.158316752802177, -1.2321925345218743, -1.3162368054231501, -1.408428826222099, -1.5065753860168472, -1.6083605417342035, -1.7113977976366277, -1.813283490879169, -1.9116501254160112, -2.0042184033421853, -2.0888467397896893, -2.163577113805646, -2.226676201535917, -2.2766708571558123, -2.312377148351117, -2.332922313236352, -2.3377591804268976, -2.326672779227512, -2.2997790579819792, -2.257515820834804, -2.200626181754164, -2.1301350150242238, -2.0473190491159126, -1.9536714017928458, -1.850861484831066, -1.7406913136699103, -1.6250493380995528, -1.5058629628167686, -1.3850509501317774, -1.2644768908043185, -1.145904893184102, -1.0309585765212825, -0.9210843631953665, -0.8175199490479367, -0.7212686939634492, -0.6330805198182651, -0.5534397338497221, -0.48256001666418663, -0.4203866300226415, -0.3666057148525903, -0.32066036928225833, -0.2817730244129122, -0.2489734763519392, -0.22113179070672084, -0.19699517384178866, -0.17522780676615132, -0.1544525649872915, -0.13329350283269012, -0.11041796469006598, -0.0845771987198305, -0.054644390479855004, -0.019649103481492004, 0.0211927908217059, 0.06845449216494155, 0.12247961889558985, 0.18337002659296775, 0.25098043159954003, 0.3249199953648554, 0.40456084357741556, 0.48905331263897095, 0.5773475397269687, 0.6682208459739604, 0.760310209409181, 0.8521489891528792, 0.9422069483811814, 1.0289325337112163, 1.1107963052119778, 1.1863343758834566, 1.2541907131176608, 1.3131571775849276, 1.362210226666779, 1.4005432887489435, 1.4275939194688736, 1.4430649788093102, 1.4469392155893464, 1.4394868097697162, 1.4212655989887555, 1.3931138994970422, 1.3561360185763227, 1.3116807409372988, 1.2613132508437768, 1.206781120303791, 1.149975147353582, 1.092885963351433, 1.037557440868397, 0.986038021330197, 0.9403311417648399, 0.9023459712545365, 0.8738496691039963, 0.8564223481850937, 0.8514158690062522, 0.8599175041196577, 0.8827194005526776, 0.9202946327110877, 0.9727804829122445, 1.0399694151296959, 1.1213080238396835, 1.2159040485344248, 1.3225413501836285, 1.439702553441542, 1.5655988724343597, 1.6982064630899727, 1.8353084854929043, 1.9745419195926264, 2.113448060224958, 2.2495255257316003, 2.380284550760284, 2.503301299694898, 2.616270933471892, 2.717058189414296, 2.80374429053452, 2.87466908616554, 2.928467437719687, 2.9640989991368123, 2.9808706978767403, 2.9784513953389955, 2.956878391150453, 2.9165556293362394, 2.8582436612734416, 2.7830416157332754, 2.692361615495769, 2.5878962583768312, 2.4715799437139965, 2.345544969460683, 2.212073446557901, 2.073546173261432, 1.9323896803042968, 1.7910226965553049, 1.651803293305842, 1.5169779433323964, 1.3886336790452876, 1.2686544536781152, 1.1586827026309408, 1.0600869714327998, 0.9739363255964852, 0.9009820896612556, 0.8416472821224746, 0.7960239242004707, 0.7638782081645119, 0.7446633199382625, 0.7375395256670274, 0.7414009573632226, 0.7549083729351967, 0.7765270247415501, 0.8045686517240451, 0.8372365160281143, 0.8726723380674214, 0.9090039457944762, 0.9443924453525948, 0.9770777414174763, 1.0054212857623754, 1.0279450105497852, 1.0433655065279022, 1.050622633018537, 1.0489018930830694, 1.0376500698157471, 1.0165837942171059, 0.9856908971322659, 0.9452245827072309, 0.8956906440646527, 0.8378281188230376, 0.7725839482414318, 0.7010823550031641, 0.6245897871764579, 0.5444763864007192, 0.4621750240962784, 0.3791390083594688, 0.29679959473933637, 0.21652443556593923, 0.13957807491420265, 0.06708554037388882, 5.973166896093752e-16], [-0.0, -0.058653377259265164, -0.11047295370249664, -0.1552874740405732, -0.19317294244805988, -0.2244507001818273, -0.24967857470491753, -0.26963532068013796, -0.2852987490212842, -0.2978181060734589, -0.30848141671757007, -0.3186786388916211, -0.3298615892775268, -0.3435016878384405, -0.3610466302386849, -0.38387713033368004, -0.4132648789852393, -0.4503328402730957, -0.4960189523063078, -0.5510442185796903, -0.6158860691519561, -0.6907577414663548, -0.7755942815901371, -0.8700456017121511, -0.9734768530095579, -1.0849761888800287, -1.2033698066333736, -1.327243970724777, -1.4549735421315564, -1.5847563710148713, -1.7146527575902817, -1.8426290530091458, -1.9666043614122475, -2.0844992189914398, -2.194285068095034, -2.2940333156692074, -2.381962766454177, -2.456484252423453, -2.5162413402984773, -2.5601460871930573, -2.587408928453008, -2.5975619188239905, -2.590474704896607, -2.566362779539362, -2.5257877535326814, -2.469649571358309, -2.3991707923886616, -2.315873250799056, -2.2215475926773562, -2.118216362478369, -2.0080914688866205, -1.8935269984155543, -1.7769684602635678, -1.660899635212336, -1.5477882624652892, -1.4400318297497248, -1.3399047329350726, -1.2495080417909805, -1.1707230490091738, -1.1051696916618774, -1.0541708199850341, -1.0187231505192673, -0.9994755825580619, -0.9967153823782033, -1.0103625531021097, -1.0399725138023717, -1.0847470143288709, -1.1435530171111545, -1.2149490886084022, -1.2972186657261686, -1.3884094006963241, -1.486377645543533, -1.5888370177789206, -1.6934098952458196, -1.7976806223362696, -1.8992491736540094, -1.9957840154469881, -2.0850729298510924, -2.165070621509135, -2.2339420090588487, -2.290100213226607, -2.3322383860851725, -2.3593546791226236, -2.3707698173227936, -2.36613692827405, -2.3454434649080533, -2.3090052531456737, -2.2574528867498094, -2.1917108763609785, -2.1129701334947963, -2.0226545289625903, -1.9223824048727214, -1.8139240366938645, -1.6991561339876655, -1.580014533152336, -1.4584462713506001, -1.3363622369352657, -1.2155915680829863, -1.0978389186900126, -0.9846456302823102, -0.8773557428409413, -0.77708764876812, -0.6847120460085874, -0.6008366823649113, -0.5257982074581338, -0.45966126602434915, -0.40222478090971986, -0.3530351908941729, -0.31140623193910094, -0.276444685042269, -0.24708136373375816, -0.22210648310995015, -0.20020844344601252, -0.1800149775544679, -0.16013555424070336, -0.1392039018356396, -0.11591951653455196, -0.08908705007930508, -0.05765252939813195, -0.020735445660527634, 0.02234414036004266, 0.07204419848928519, 0.1285856071038668, 0.19194371667188245, 0.2618468319015126, 0.3377816646572881, 0.41900562749451886, 0.5045656585334473, 0.5933230969957783, 0.6839839694149575, 0.7751339033639253, 0.8652767621721955, 0.9528759936848546, 1.0363976112314996, 1.1143536775652385, 1.1853451438539502, 1.2481029063899116, 1.3015259833269337, 1.3447157815228679, 1.3770055178182385, 1.3979839775098473, 1.4075129324617712, 1.4057376987768955, 1.3930904853194002, 1.370286365365882, 1.3383118897544557, 1.2984065464437586, 1.2520374537137602, 1.2008678477581913, 1.146720085765056, 1.091534028706529, 1.0373217903320113, 0.9861199371585587, 0.9399402960513386, 0.9007205694063861, 0.8702759718129001, 0.8502530859374363, 0.8420870895368334, 0.846963431005374, 0.8657849294432682, 0.8991451493156174, 0.9473087523835502, 1.0101993642983242, 1.0873953140712824, 1.1781334159342094, 1.2813207694964721, 1.3955543603268388, 1.5191480538916262, 1.6501663958154342, 1.7864644651234323, 1.9257328785755048, 2.065546917080955, 2.203418642635626, 2.3368507987994134, 2.4633912413165517, 2.580686629250447, 2.6865341213943768, 2.7789298674171095, 2.8561131571508422, 2.91660519285416, 2.9592415757368133, 2.983197746454156, 2.9880067860663346, 2.9735691650590135, 2.9401542190372774, 2.888393325987422, 2.8192649567798815, 2.734071963077013, 2.634411650334962, 2.5221393536937597, 2.399326387110949, 2.268213367419446, 2.131160021911673, 1.9905926680025758, 1.8489506045987183, 1.7086326758064851, 1.571945258093676, 1.441052882268959, 1.3179326326999306, 1.204333369801268, 1.1017407004137467, 1.0113484772935049, 0.9340374471082848, 0.8703614901073004, 0.8205417083553616, 0.7844684277011534, 0.7617109862085298, 0.7515349933521847, 0.7529265644891465, 0.7646228683661803, 0.7851481757792378, 0.8128544686018709, 0.8459655633599926, 0.8826236248683247, 0.9209368950170872, 0.9590274407595015, 0.9950777341227973, 1.0273749153273999, 1.054351656798878, 1.0746226392367038, 1.0870157685457509, 1.0905974013232538, 1.0846910031855217, 1.0688888345401923, 1.0430564381521497, 1.0073298874783072, 0.9621059396086449, 0.9080254171017449, 0.8459503145147917, 0.7769352837045195, 0.7021942930596209, 0.6230633761970152, 0.5409604823193213, 0.45734351099324444, 0.373667656832039, 0.291343203414916, 0.21169489044438075, 0.13592393405609351, 0.06507370850497284, 5.771853649180891e-16], [-0.0, -0.056316667795001794, -0.10571801374427091, -0.14815917204232226, -0.18384224682129818, -0.21321052461171397, -0.23693586045195641, -0.25589955956121313, -0.27116724717789714, -0.2839583774304465, -0.2956111739205633, -0.30754391644322765, -0.32121358682841594, -0.3380729597325601, -0.35952726944436525, -0.38689160020324165, -0.4213501346859289, -0.46391835346018767, -0.5154092083255783, -0.5764041962579044, -0.6472301405072027, -0.7279423442361241, -0.8183146234250811, -0.9178365535568311, -1.0257180831175619, -1.140901480746128, -1.2620803965872873, -1.3877256367300992, -1.516117077105278, -1.645380984222879, -1.773531868674125, -1.8985178769903979, -2.0182686313219578, -2.130744356947057, -2.2339850966689943, -2.3261587998200133, -2.4056070922499213, -2.4708875819727694, -2.5208116319804046, -2.5544766353005586, -2.571291955207013, -2.570997842501962, -2.553676808377493, -2.5197571114736848, -2.470008206992829, -2.4055281994760676, -2.3277235343541895, -2.2382813518991416, -2.1391351060925414, -2.032424215786766, -1.920448662295366, -1.8056195725847766, -1.6904069274476818, -1.5772856069271053, -1.468681029001395, -1.3669156510216267, -1.2741575862414118, -1.1923725403736583, -1.1232801965698447, -1.0683160733796568, -1.028599751618014, -1.004910215755217, -0.9976688871004821, -1.006930743756949, -1.0323837305176626, -1.0733564652100491, -1.12883405126254, -1.1974816142434934, -1.2776749974750672, -1.3675378829868026, -1.4649844531393417, -1.5677665788698187, -1.6735244158091156, -1.7798392120117206, -1.8842870825672493, -1.9844924880610344, -2.0781801661106103, -2.1632243076670905, -2.237693841335327, -2.2998927878235658, -2.3483947703015384, -2.3820709118420207, -2.400110514630624, -2.402034093199784, -2.3876985211847868, -2.357294243391704, -2.311334697573428, -2.2506382784971275, -2.176303356039393, -2.089677024782295, -1.992318410863497, -1.8859574890561195, -1.772450466147526, -1.6537328631835457, -1.5317714772430686, -1.4085164220128863, -1.285854435183836, -1.1655645999687878, -1.049277558963865, -0.9384392029526705, -0.8342796975617737, -0.7377885699809626, -0.6496964198468194, -0.5704636468639743, -0.5002764071407885, -0.439049825100511, -0.3864383028529151, -0.3418525887215004, -0.3044830957352634, -0.2733288035882532, -0.2472309377742424, -0.22491050080131592, -0.20500863553407087, -0.1861287321458107, -0.1668791495726342, -0.14591541072361278, -0.12198074826524263, -0.0939439240782072, -0.060833319272267976, -0.021866391041297128, 0.023526284897935238, 0.07568302513527353, 0.1346995827938769, 0.20042453427499726, 0.2724616386920489, 0.350179117817103, 0.432725623245806, 0.5190524822002087, 0.6079416483875286, 0.6980386338138005, 0.7878895652500784, 0.8759813985418705, 0.9607842379731002, 1.0407946486625266, 1.1145788190307726, 1.1808144285677034, 1.2383301035585614, 1.2861413994642472, 1.3234823319474998, 1.3498315870567001, 1.3649326721502686, 1.3688074195242186, 1.3617624206599876, 1.344388146408878, 1.3175506928475291, 1.2823762793660012, 1.240228810105645, 1.192680987515413, 1.1414796330711103, 1.0885060209055633, 1.0357321614110349, 0.9851740804551167, 0.9388432229130271, 0.8986971646067705, 0.866590842982271, 0.8442295131975939, 0.8331246027272061, 0.83455357484033, 0.8495248208412298, 0.8787484849122028, 0.9226139865596503, 0.9811748473838248, 1.054141255014746, 1.1408806118150712, 1.2404261238684349, 1.3514932915503803, 1.4725039713804606, 1.6016174945848025, 1.7367681553931504, 1.8757082258013924, 2.016055517210924, 2.1553443963839953, 2.2910790763351976, 2.4207879442806375, 2.542077660062469, 2.6526857603032954, 2.7505305359179806, 2.833757012769324, 2.900777955715761, 2.9503089328872427, 2.981396616921747, 2.993439659709726, 2.9862016530485107, 2.959815875230779, 2.9147817184204996, 2.8519528889691195, 2.772517667797504, 2.6779717058769417, 2.570084006121641, 2.4508569033782974, 2.3224809947813667, 2.18728609013756, 2.047689343382925, 1.9061417893346693, 1.7650745434427082, 1.6268459252700849, 1.4936907389801126, 1.36767288691208, 1.250642406848502, 1.1441979119653163, 1.04965527750486, 0.9680232632777563, 0.8999865900301379, 0.8458968047410679, 0.8057710795611863, 0.7792988960608201, 0.7658563754726935, 0.7645278313801696, 0.7741339483288964, 0.7932658323521926, 0.8203240412309816, 0.8535615868040918, 0.891129811581779, 0.9311259794362589, 0.9716413867006626, 1.0108087963317403, 1.0468480238708475, 1.0781085590220179, 1.1031081892864052, 1.120566700097086, 1.1294338565095914, 1.1289110213856903, 1.1184659303522042, 1.0978403204362415, 1.0670502927138328, 1.0263794749396287, 0.976365233283999, 0.9177783583945361, 0.8515968156105148, 0.7789742981755483, 0.7012044519972608, 0.6196817476655829, 0.5358600574058344, 0.4512100493879066, 0.36717653800418387, 0.28513692575109917, 0.2063618403209809, 0.13197901028207834, 0.06294133585386008, 5.561808166845126e-16], [-0.0, -0.053935733749469354, -0.10093396395309494, -0.14107642591566924, -0.17468940227017207, -0.20233411647112845, -0.22479046114853116, -0.243034482111907, -0.2582102028658097, -0.2715965237691688, -0.28457006063847445, -0.2985648963218231, -0.31503030277037686, -0.33538754823890987, -0.36098693296571727, -0.3930661962348385, -0.43271140806359526, -0.4808214005737776, -0.5380767088012883, -0.6049138803661109, -0.6815058807834844, -0.7677491695341333, -0.8632578550953726, -0.9673651591244836, -1.0791322353254191, -1.1973642018398938, -1.3206330619643218, -1.4473070112291677, -1.5755854638390203, -1.70353898232945, -1.8291531648321244, -1.9503754378526097, -2.065163621690384, -2.171535082668746, -2.2676152626073396, -2.3516843821522144, -2.4222211506268145, -2.477942380189391, -2.517837494762738, -2.5411970422391064, -2.5476344590220927, -2.5371004956502112, -2.5098898871756234, -2.4666400378830144, -2.408321682285407, -2.3362216784147156, -2.2519182804732774, -2.1572494212319033, -2.0542747056361135, -1.945231971695004, -1.8324894090538593, -1.7184943363640912, -1.6057198229072713, -1.4966103957959145, -1.3935281000475828, -1.298700174230907, -1.2141695692794088, -1.1417494732779994, -1.0829829120921781, -1.0391083768661424, -1.0110322875350717, -0.999308940014949, -1.0041284075692625, -1.0253126783084403, -1.0623201154375086, -1.1142581294789378, -1.1799037570596005, -1.2577316536933651, -1.3459488328599873, -1.4425353248255008, -1.5452897899184168, -1.6518790057223376, -1.759890058645294, -1.8668840097092971, -1.970449773602998, -2.068256949756592, -2.1581063743824545, -2.2379772222823355, -2.306069575228897, -2.360841487676001, -2.401039717592427, -2.4257234469414564, -2.4342804888579326, -2.4264356626381236, -2.4022512087133245, -2.3621193091192785, -2.3067469698468592, -2.237133705182781, -2.1545426362256728, -2.060465771993599, -1.9565843781252845, -1.8447254518141898, -1.7268154095726858, -1.6048321546150772, -1.4807567216782587, -1.3565256982981704, -1.2339855930019301, -1.1148502633710595, -1.0006624320094082, -0.8927602083175286, -0.7922494014632236, -0.6999822584267438, -0.6165430943354089, -0.5422411047038045, -0.47711046514236743, -0.4209176382231229, -0.37317562416541566, -0.3331647164164716, -0.29995915944626067, -0.2724589582438419, -0.24942596077819051, -0.22952322925725394, -0.21135663599516072, -0.19351756704788553, -0.1746255927808838, -0.15336996974531053, -0.12854887248440322, -0.09910531626038284, -0.06415882056988965, -0.02303197642148777, 0.024728785207403105, 0.0793387739601866, 0.14076735356955133, 0.2087371958338257, 0.28273050119289805, 0.36200202973279916, 0.4455986080882782, 0.5323846077866957, 0.6210727334043914, 0.7102593184890614, 0.7984632071200061, 0.8841672023039019, 0.9658609916218384, 1.0420844174891175, 1.1114699452019547, 1.172783197039469, 1.2249604647433485, 1.2671421846614743, 1.2987014579624736, 1.3192668201926563, 1.3287386070422047, 1.3272984229752613, 1.315411392382369, 1.2938210548187747, 1.2635369521517184, 1.2258151413895073, 1.1821320479376127, 1.1341522454707287, 1.0836909061997404, 1.0326718050611958, 0.9830818797122141, 0.936923442149065, 0.896165204857328, 0.8626933228827183, 0.8382636620288821, 0.8244564822209222, 0.8226346743438017, 0.8339066097309683, 0.859094555804267, 0.8987094816777176, 0.9529329269606605, 1.0216064391795403, 1.1042289042652593, 1.1999619048412482, 1.3076430472368206, 1.4258070049927158, 1.5527138388643125, 1.6863839755824543, 1.824639064283635, 1.965147784602963, 2.105475557522831, 2.2431370122379004, 2.375649991972098, 2.500589840632843, 2.615642701461868, 2.718656578749197, 2.8076889637723808, 2.8810499052244043, 2.9373395106045703, 2.9754789958059904, 2.9947345522774826, 2.9947334709776805, 2.9754721457519087, 2.937315771290936, 2.8809897477956645, 2.807563001084301, 2.7184236183595716, 2.615247381550841, 2.4999599476486387, 2.3746935746950677, 2.2417394194719216, 2.1034965353641515, 1.9624187739093248, 1.8209608393875658, 1.6815247613901279, 1.5464080353024245, 1.4177546354720185, 1.297510031665778, 1.1873812381276183, 1.0888027986625384, 1.0029094638319016, 0.9305161512051173, 0.8721056007641873, 0.8278239494179409, 0.7974842557910841, 0.780577813754404, 0.7762929052884149, 0.7835404648275331, 0.8009859625767652, 0.827086667439137, 0.8601333247023033, 0.8982951825336283, 0.9396672270400804, 0.9823184399096677, 1.0243398764996605, 1.063891375972429, 1.0992457582587263, 1.128829434076474, 1.1512584520770521, 1.1653691289033143, 1.1702425504097644, 1.1652223918896039, 1.1499256778312665, 1.1242462831257356, 1.0883511631942029, 1.0426694855375698, 0.9878750150806562, 0.9248622758889322, 0.8547171681179867, 0.7786828575160488, 0.6981218719908922, 0.614475432766796, 0.5292211141982031, 0.4438299647453433, 0.3597242310329319, 0.2782368071160925, 0.20057348261239566, 0.1277789874912232, 0.06070772999554869, 5.344934411386254e-16], [-0.0, -0.05153213097427422, -0.09616416437742488, -0.13410351118057776, -0.16579759397908703, -0.19192050204854597, -0.213353200142544, -0.23115780713106027, -0.24654661661294994, -0.26084667061817773, -0.2754608159012466, -0.2918262670891542, -0.311371769650205, -0.33547449651310957, -0.3654178241070028, -0.4023511162569112, -0.44725259813648166, -0.5008963284583344, -0.5638241780801962, -0.636323599685561, -0.7184118292191853, -0.8098269988971448, -0.9100264678753422, -1.0181924943864182, -1.1332451869025015, -1.2538624863183843, -1.3785067509373459, -1.5054573457164935, -1.632848481089832, -1.7587114086898967, -1.8810199649435488, -1.9977383618033606, -2.106870059164813, -2.206506517516654, -2.2948746230716197, -2.3703816012866827, -2.4316562878206134, -2.477585707374613, -2.507346018597796, -2.5204270147349432, -2.5166495217769977, -2.4961752048564043, -2.459508475395205, -2.4074903816249384, -2.3412845588998197, -2.262355508964346, -2.1724396642761925, -2.0735098700224444, -1.9677340782470059, -1.8574291915308057, -1.7450111143904061, -1.632942165983771, -1.5236770754511897, -1.4196088195677197, -1.3230155703539965, -1.2360099976419756, -1.1604921188290622, -1.0981068064250437, -1.050206955456641, -1.0178231799606987, -1.0016407538817773, -1.0019843404244846, -1.0188108694519313, -1.0517107293509147, -1.0999172425966948, -1.1623241978393049, -1.2375110204733326, -1.3237749829815932, -1.4191696902461628, -1.5215489275263947, -1.628614833482094, -1.7379692604969708, -1.8471671120374702, -1.9537704035931085, -2.055401780893187, -2.1497962468436533, -2.2348498964892363, -2.308664536053041, -2.3695871658069216, -2.4162434345880506, -2.4475643230157953, -2.462805479176599, -2.4615588106093567, -2.443756125395302, -2.4096648083782477, -2.3598757112624584, -2.2952836228263283, -2.217060863159839, -2.126624709343106, -2.0255995053521176, -1.91577443268257, -1.7990580172432582, -1.6774305201230142, -1.5528954031900724, -1.4274310741641967, -1.3029440995737689, -1.1812250283765937, -1.0639078952200003, -0.9524343722735834, -0.8480234148669201, -0.7516471019676902, -0.6640132115084689, -0.5855548967917958, -0.5164276480591286, -0.45651353738767286, -0.40543256005097544, -0.36256070598553275, -0.327054225538935, -0.2978793984695677, -0.27384697809226993, -0.25365036692718435, -0.23590648907277334, -0.21919826003475978, -0.2021175184744766, -0.183307277155763, -0.16150217240002968, -0.1355660420009158, -0.10452563948015701, -0.06759959577673888, -0.02422186530900099, 0.025940961377348, 0.08297893516227585, 0.14673490025958424, 0.216807624754142, 0.292561831482877, 0.3731448703711763, 0.4575095992761015, 0.5444428772934908, 0.6325989265058529, 0.720536689051345, 0.8067601994775038, 0.8897609103463362, 0.9680608540947239, 1.040255497661952, 1.10505514909537, 1.1613238072234058, 1.2081144057955555, 1.244699490769383, 1.2705964815323814, 1.2855868010125038, 1.2897283125272467, 1.2833606690437633, 1.2671033590863794, 1.2418464183710929, 1.2087339627405431, 1.1691408814385784, 1.1246432055877669, 1.076982830484111, 1.0280274178605393, 0.9797264318501331, 0.9340643667464115, 0.8930123031273085, 0.8584789794366829, 0.8322625873480983, 0.8160044905411812, 0.8111460280144529, 0.8188894955936769, 0.8401643044461204, 0.8755991954348732, 0.9255012459279333, 0.9898422446552639, 1.0682528342969992, 1.1600246349772414, 1.2641203692913219, 1.3791918156280543, 1.5036052261231316, 1.6354736632799651, 1.7726955396117263, 1.9129984917841798, 2.0539875884545804, 2.193196762591284, 2.3281422772215925, 2.4563769803430318, 2.5755440814978328, 2.6834291898673786, 2.778009391561567, 2.857498211175718, 2.9203853980601253, 2.965470598800938, 2.9918901212224167, 2.9991361583071887, 2.9870680188366574, 2.9559151009456324, 2.9062715405612307, 2.839082664097145, 2.755623569001621, 2.657470342090824, 2.5464645995127517, 2.4246721894602072, 2.2943370355739345, 2.1578312120413146, 2.0176024279778013, 1.8761201567053454, 1.7358216736428298, 1.5990592640613979, 1.4680498290455135, 1.344828055499156, 1.2312042255289217, 1.128727624292484, 1.0386563663186539, 0.961934301838873, 0.8991754907434125, 0.8506565466867003, 0.8163169621798089, 0.7957673319417968, 0.7883052010910294, 0.7929380816172898, 0.8084130094642691, 0.8332518596425406, 0.8657915018486889, 0.9042277673487588, 0.9466621120737462, 0.9911498030046099, 1.0357484263305077, 1.0785655171549668, 1.117804141565257, 1.151805321797991, 1.179086282440641, 1.1983736078413658, 1.208630535277905, 1.2090777615351573, 1.1992073084760104, 1.1787891717153358, 1.1478706611216767, 1.106768527931227, 1.056054156093553, 0.9965322704969631, 0.9292137775668243, 0.8552835003279404, 0.77606369672263, 0.6929743536339281, 0.607491327116198, 0.5211034498675022, 0.4352697487670033, 0.3513779078480721, 0.2707050756209539, 0.19438205116373503, 0.12336179253809447, 0.05839307618986406, 5.123193964678516e-16], [-0.0, -0.049127556636263926, -0.09145170303299421, -0.12730347129111347, -0.15724729601519438, -0.18206404507284052, -0.20272787870956263, -0.2203775440041229, -0.23628285829676396, -0.2518072627124474, -0.2683674319788744, -0.28739100671277534, -0.31027356715594845, -0.33833599160518596, -0.37278333783512263, -0.4146663517320099, -0.46484664494438277, -0.5239664941319824, -0.5924241005517545, -0.6703550130757945, -0.7576202636593958, -0.8538015956049552, -0.9582039859095047, -1.069865478018537, -1.1875741550715264, -1.309891900891642, -1.4351844211440195, -1.5616568346741966, -1.687393999150338, -1.8104046094757311, -1.9286680052212115, -2.040182547182846, -2.1430143750870645, -2.235345339737964, -2.3155189140970407, -2.3820829287286553, -2.4338280468206586, -2.46982099096623, -2.489431655759579, -2.492353384081861, -2.478615847251691, -2.448590146039171, -2.402985936578304, -2.342840577883243, -2.26950049125438, -2.184595111593698, -2.0900039918646027, -1.9878177901598046, -1.8802940199242366, -1.7698085740761655, -1.6588041398433038, -1.5497367004363143, -1.4450213702257844, -1.3469788305833184, -1.2577836234387672, -1.1794155190927416, -1.1136151048493454, -1.0618446432659514, -1.025255125604424, -1.0046603003860903, -1.000518292328518, -1.012921247367941, -1.0415932493078675, -1.085896557502322, -1.1448460176490622, -1.2171313040308935, -1.3011464661105716, -1.395026079760999, -1.4966871477872052, -1.6038757595409077, -1.714217408604059, -1.8252697833943012, -1.9345767901378188, -2.039722542272691, -2.1383840555610876, -2.228381423823437, -2.3077243153383162, -2.3746537229328637, -2.427678019292501, -2.4656025100969425, -2.4875518377411514, -2.492984763663857, -2.4817010433547497, -2.4538403003604006, -2.409872999329884, -2.3505838085784685, -2.2770478251361945, -2.1906003053283762, -2.0928006974624243, -1.9853919064433865, -1.8702558298914478, -1.7493662889585686, -1.624740532560934, -1.4983905198815584, -1.3722751822068624, -1.2482548316387534, -1.1280488219037823, -1.0131974770102825, -0.9050291892005387, -0.8046334514381815, -0.7128404350298467, -0.6302075538247889, -0.5570132770396158, -0.49325826763786146, -0.43867373700806134, -0.39273672410032895, -0.3546918327705721, -0.3235787992016274, -0.298265115957844, -0.27748281409795517, -0.2598684029228888, -0.2440048908836922, -0.2284647627823094, -0.21185276882987938, -0.19284739082306268, -0.17023988936249884, -0.14296990264444695, -0.11015666018086162, -0.07112499146024287, -0.02542544706905121, 0.027151995354264706, 0.08657099970418371, 0.1525488965198824, 0.22456366460650173, 0.30186768714330103, 0.3835079228724918, 0.46835196470619406, 0.5551193032367757, 0.6424169751285266, 0.7287786597116171, 0.8127061942752922, 0.8927124119504419, 0.9673641674083218, 1.035324405906578, 1.0953921507820295, 1.1465393328824183, 1.1879434614810398, 1.2190152380667347, 1.2394203395337218, 1.2490947426088517, 1.2482531232341412, 1.2373900390336667, 1.2172737855780638, 1.1889330033462466, 1.1536362974020207, 1.1128653112002471, 1.0682818650929229, 1.0216899247474511, 0.974993300896671, 0.930150096144569, 0.8891250040229542, 0.8538406278149365, 0.8261290201838831, 0.8076846484377518, 0.8000199641216524, 0.8044247001127185, 0.8219299347680316, 0.8532778529262853, 0.8988980003165804, 0.9588906744010242, 1.033017924598508, 1.120702452349182, 1.2210345110425633, 1.332786712112229, 1.4544364513516477, 1.5841954834581897, 1.7200459975493203, 1.8597823862436567, 2.00105775982295, 2.141434138487254, 2.278435162735672, 2.409600096775282, 2.5325378642269074, 2.644979850182066, 2.744830229048497, 2.830212633030465, 2.8995120602138353, 2.9514110320516695, 2.9849191449024035, 2.9993953158989832, 2.994562196051874, 2.9705124089224983, 2.9277064669417636, 2.8669624147823454, 2.7894374453263935, 2.6966019239346166, 2.5902064362976627, 2.4722426397760104, 2.3448988438176586, 2.2105113682559043, 2.071512826058888, 1.9303785470774693, 1.7895723998517905, 1.6514932786464414, 1.5184235023904473, 1.3924803216553043, 1.2755716505000227, 1.1693570339386623, 1.075214731591214, 0.9942156469955532, 0.9271046638310328, 0.8742897690890878, 0.835839153493674, 0.8114862858946873, 0.800642765687525, 0.8024185702769504, 0.8156491377795312, 0.838928562861664, 0.8706480397872148, 0.9090385648829719, 0.9522168136540177, 0.9982330380059456, 1.0451197880882044, 1.0909402520781148, 1.1338350259531564, 1.1720661733828932, 1.2040575120168395, 1.2284301646618394, 1.2440325395004883, 1.2499640493903945, 1.2455920426975033, 1.2305615929452378, 1.204797977394732, 1.1685018609090145, 1.1221373864195818, 1.066413552372265, 1.0022594262020144, 0.9307938969633429, 0.8532908058874515, 0.7711404074799802, 0.6858082029981817, 0.598792250558638, 0.5115800902079969, 0.4256064272344667, 0.3422126927353785, 0.26260954764839795, 0.18784331648031374, 0.1187672318898719, 0.056018243791583926, 4.898587196589409e-16]], \"y\": [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0], [0.0, 0.0007676059644469046, 0.0016216519819783383, 0.0025552485258622244, 0.003558552558133107, 0.004619036972158722, 0.00572183685289155, 0.00685016344937142, 0.007985774966332694, 0.009109491771397605, 0.010201742419907482, 0.011243126051624856, 0.012214976234294869, 0.013099911231086895, 0.013882355955363997, 0.014549021540496088, 0.01508932947847656, 0.0154957686437355, 0.015764175184083275, 0.01589392718782014, 0.01588804817672975, 0.015753215775511736, 0.015499674311662706, 0.015141052545666833, 0.01469409015820811, 0.014178278967920776, 0.013615427060782729, 0.013029156024816609, 0.01244434325023413, 0.011886522730513799, 0.01138125894627699, 0.01095350920147513, 0.010626990189446175, 0.010423564583367387, 0.010362663069753609, 0.010460756482916288, 0.01073089157027815, 0.01118230244985592, 0.011820108047312422, 0.012645103763616819, 0.013653653375010342, 0.014837684759504402, 0.016184790537414957, 0.017678432168913592, 0.01929824353176029, 0.021020427569299897, 0.022818237312453422, 0.024662530496314384, 0.026522385163657455, 0.028365762119587988, 0.030160198911797376, 0.031873519189271976, 0.033474540859661894, 0.03493376643314826, 0.03622403931004666, 0.037321150532178, 0.038204381656200735, 0.03885697089338263, 0.03926649145889155, 0.039425133141121775, 0.03932988038775101, 0.03898258265466658, 0.03838991531711428, 0.03756323203735692, 0.03651831205670249, 0.03527500836941264, 0.03385680508123166, 0.03229029439912869, 0.030604585589319732, 0.028830659831944362, 0.027000686154489494, 0.025147314512031515, 0.023302962579502477, 0.021499112917902633, 0.019765636870935112, 0.018130160849040136, 0.016617489582015144, 0.01524909949629392, 0.014042713634019127, 0.013011967521430455, 0.012166173163534515, 0.011510185945596954, 0.011044376718762372, 0.010764708798639342, 0.010662917074565965, 0.01072678397552236, 0.01094050472623202, 0.011285132210285896, 0.011739089887578135, 0.012278739636195878, 0.012878990142071193, 0.01351393057284597, 0.014157473766214079, 0.01478399304871238, 0.015368937080022722, 0.015889407782052598, 0.016324687443580427, 0.0166567024631985, 0.016870412870380613, 0.0169541187039541, 0.016899676479841662, 0.016702621291235186, 0.016362192496111108, 0.01588126339855172, 0.01526617776019211, 0.014526498325423737, 0.013674674750097062, 0.012725640333360103, 0.011696348715948183, 0.010605263181952818, 0.009471812348441818, 0.008315826820113816, 0.007156971805223683, 0.006014190724499322, 0.004905174496516989, 0.0038458704604906104, 0.0028500438195400352, 0.0019289030820290206, 0.001090799281526378, 0.0003410068106704303, -0.00031840843973974197, -0.0008886302332096258, -0.0013740414024723863, -0.0017820828976026666, -0.002123026202666791, -0.0024096651256012252, -0.0026569350824362315, -0.002881469906671531, -0.003101107868939932, -0.0033343599488470984, -0.003599854425307405, -0.003915772517406689, -0.004299290097424863, -0.0047660404032095335, -0.0053296122003268975, -0.006001096996673902, -0.006788697714204293, -0.007697409703626977, -0.00872878318600957, -0.009880774164965102, -0.01114768862537667, -0.012520222475081265, -0.013985597253648526, -0.015527789188356768, -0.017127846783098012, -0.01876428984153295, -0.02041358070904012, -0.022050656622458392, -0.023649510430514074, -0.02518380563271882, -0.02662751071434276, -0.02795553715519694, -0.029144365276627823, -0.03017264227098006, -0.031021737327702983, -0.031676239717442496, -0.032124386997662076, -0.03235841212949532, -0.032374800206478836, -0.03217444764522552, -0.03176271902365503, -0.031149399217060416, -0.0303485410157076, -0.029378210947662433, -0.028260138514662907, -0.027019276415896847, -0.025683281526077434, -0.02428192835602489, -0.022846468407404685, -0.02140895019647222, -0.020001515730555645, -0.01865568985016681, -0.017401679082950823, -0.01626769648674603, -0.015279328391288276, -0.014458957994780298, -0.01382525945537922, -0.013392774470244763, -0.013171581395908152, -0.013167064780297267, -0.013379790801735361, -0.013805491601281698, -0.014435158912863505, -0.015255244803517835, -0.016247964796735702, -0.017391696227097665, -0.018661462423019207, -0.0200294912911337, -0.02146583512967255, -0.02293903707139798, -0.02441682848358611, -0.02586684095896403, -0.02725731623375388, -0.0285577974737518, -0.029739785873480758, -0.030777347403919793, -0.03164765579869724, -0.03233145945561349, -0.03281346181047595, -0.03308260686690567, -0.03313226388644252, -0.03296030770069315, -0.03256909364092287, -0.03196532862812234, -0.03115984246568542, -0.0301672657662358, -0.02900562316548782, -0.02769585247523402, -0.026261262156126827, -0.024726940907166428, -0.02311913423882212, -0.02146460359525017, -0.01978998390211585, -0.01812115533371313, -0.01648264461979694, -0.014897070361882054, -0.013384645623136111, -0.011962749526577334, -0.010645577782242507, -0.009443880011473045, -0.008364789497453567, -0.007411748622157279, -0.006584530810536899, -0.0058793573544177165, -0.005289105092468097, -0.004803598638779124, -0.004409978737992814, -0.004093136432250196, -0.0038362011015066586, -0.003621069124183563, -0.0034289589320761512, -0.0032409776256857275, -0.003038684088252832, -0.0028046336937406313, -0.002522890241183859, -0.00217949165095346, -0.0017628572041792129, -0.0012641256628124055, -0.0006774154348008261, -6.734692708291278e-18], [0.0, 0.0015963423292227816, 0.003360017028019801, 0.005274187330629608, 0.007316386113923138, 0.009459141642869961, 0.011670747032584113, 0.013916153118803955, 0.016157961163513732, 0.0183574891582515, 0.020475883492665697, 0.02247524648146543, 0.024319749722335582, 0.02597670350498246, 0.027417553502241992, 0.028618777723911023, 0.029562659159824384, 0.030237912620302412, 0.0306401479229752, 0.03077215568451945, 0.030644006451473547, 0.030272958634113195, 0.029683175572881117, 0.028905256945956085, 0.02797559449652373, 0.026935566598968452, 0.025830590379823493, 0.024709053855538926, 0.02362115374962185, 0.02261766722455499, 0.021748687642673438, 0.02106235560559333, 0.020603616882970906, 0.020413038416658546, 0.02052571238357521, 0.02097027634703889, 0.021768074867849267, 0.022932484646588838, 0.02446842140701286, 0.02637204240070309, 0.028630653720848075, 0.031222826672766622, 0.03411872238166728, 0.03728061874858134, 0.0406636289181721, 0.04421659571919759, 0.04788314219597184, 0.05160285447475522, 0.05531256989878523, 0.05894774070209586, 0.062443841542043764, 0.06573778802280769, 0.06876933294763118, 0.07148240744736568, 0.073826375338353, 0.07575717103572242, 0.07723829404178593, 0.0782416363786876, 0.07874812325897589, 0.07874815169233432, 0.07824181650453475, 0.07723891827977387, 0.07575875290758495, 0.07382968759481362, 0.07148853326579169, 0.06877972809677627, 0.06575435139675773, 0.062468991047450274, 0.05898449115366953, 0.05536460934817022, 0.05167461527502704, 0.04797986309293873, 0.044344371363296706, 0.040829443405822244, 0.037492360125130804, 0.03438517546235261, 0.031553642053382736, 0.029036291443597657, 0.02686368939817869, 0.025057882551844036, 0.023632047967882357, 0.02259035223909375, 0.021928021684056737, 0.02163162009578917, 0.021679525511296725, 0.022042592711738147, 0.022684983750118168, 0.02356514484391528, 0.024636904559820927, 0.025850665439007967, 0.027154659130476707, 0.02849623376606804, 0.02982314175411924, 0.031084796400591044, 0.03223346677837939, 0.033225382029683705, 0.03402171875638215, 0.03458944826558157, 0.03490202411227506, 0.03493989452495727, 0.03469082880824514, 0.034150051575325274, 0.03332018355269301, 0.03221099259744458, 0.030838963350674875, 0.029226698499762123, 0.027402168824025835, 0.025397832947865774, 0.023249650929984378, 0.02099601839742895, 0.01867664982551958, 0.016331440723154317, 0.013999338879890882, 0.011717254458143216, 0.009519037581695543, 0.007434550210487276, 0.005488856549524191, 0.0037015530821566194, 0.002086255625611037, 0.0006502566737338669, -0.0006056381763900129, -0.001687090607345006, -0.00260602745991432, -0.0033802615669498394, -0.004032945635654915, -0.004591873646769419, -0.005088648245444333, -0.005557736133865597, -0.006035436449857983, -0.006558789452784604, -0.00716445447807869, -0.007887587022233857, -0.008760744957160007, -0.009812853241804345, -0.011068255114486112, -0.01254587564512457, -0.014258520754221921, -0.01621233143373681, -0.01840640901765782, -0.020832623044049422, -0.0234756086331602, -0.02631295549342414, -0.029315585779519936, -0.032448313186880046, -0.03567057099698367, -0.038937292405259685, -0.04219992247935754, -0.04540753761106308, -0.04850804542916745, -0.05144943590752845, -0.054181052890453385, -0.056654854506577416, -0.05882663097395088, -0.06065714911499825, -0.062113194482781485, -0.0631684843129035, -0.06380442750353386, -0.06401071141764166, -0.06378569940969457, -0.06313662750392865, -0.06207959348239433, -0.0606393366601047, -0.058848811708620746, -0.05674856491331412, -0.05438592608960739, -0.05181403392023828, -0.04909071659682755, -0.04627725325259137, -0.04343704466931068, -0.0406342240558741, -0.03793224026968253, -0.0353924466459216, -0.033072728592246456, -0.031026202296501715, -0.029300015301153823, -0.02793427735779495, -0.026961146944427215, -0.026404095180226073, -0.026277364695297206, -0.026585636407778175, -0.027323912239233517, -0.028477616681179086, -0.030022914935135717, -0.03192724021203051, -0.03415001781891496, -0.03664356900234187, -0.039354173271494916, -0.04222326419332461, -0.04518873052688421, -0.04818629212029019, -0.05115091829001047, -0.05401825547914833, -0.05672603087047477, -0.05921539931296695, -0.06143220238962781, -0.0633281106722197, -0.06486162311977717, -0.06599890110996665, -0.06671441865798038, -0.0669914148761926, -0.06682213954828492, -0.06620788771526873, -0.06515882427429841, -0.06369360464915995, -0.061838802479965836, -0.05962815987943019, -0.05710168000204765, -0.05430458536857208, -0.051286168492034545, -0.04809856378862369, -0.044795471469170296, -0.0414308650548925, -0.03805771432362113, -0.03472675486860394, -0.03148533405932476, -0.02837636106975411, -0.025437385839316158, -0.022699828427514997, -0.02018837630138507, -0.017920562755167076, -0.01590653501347633, -0.014149015729815455, -0.012643456683167215, -0.011378378619661483, -0.010335886505430067, -0.009492345067617512, -0.00881919551245442, -0.008283890821434324, -0.007850924125370872, -0.007482922413010904, -0.007141776300881133, -0.006789775811122095, -0.0063907220923008325, -0.005910985773364163, -0.005320484142504575, -0.004593551551523323, -0.0037096803053114622, -0.002654112732042413, -0.001418269054835131, -1.4054791784244343e-17], [0.0, 0.0024833296957056604, 0.00520718842390496, 0.008141938507937587, 0.011249983583189585, 0.014486829490071788, 0.017802344031074783, 0.021142182243926465, 0.024449339452181227, 0.027665790927109385, 0.030734174618447373, 0.03359947214791022, 0.03621064314187798, 0.03852216901303855, 0.040495464460723385, 0.04210011819355521, 0.04331492860609869, 0.04412870525861968, 0.04454081288846129, 0.04456144117623965, 0.04421159043766041, 0.043522770638226314, 0.042536418452099156, 0.04130304432377126, 0.039881128459672725, 0.03833579120044175, 0.03673726913813746, 0.03515923349589955, 0.033676991548858635, 0.03236561512485446, 0.0312980423968571, 0.030543200207931213, 0.030164194024545007, 0.03021661129456738, 0.030746981521204107, 0.031791432810723386, 0.03337458009460517, 0.03550867477531814, 0.03819303933130925, 0.041413803592193925, 0.04514395212623555, 0.04934368464703171, 0.05396108372987566, 0.05893307661792295, 0.06418667067920701, 0.06964043532604343, 0.0752061970955161, 0.08079090926525277, 0.08629865297511927, 0.09163272345289875, 0.09669775268539167, 0.10140181879328243, 0.10565849248743131, 0.10938877230531657, 0.1125228628190365, 0.11500175361165177, 0.11677856145042559, 0.11781960363216779, 0.11810517680337036, 0.11763002251285005, 0.11640346816845472, 0.11444923976197695, 0.11180495051079996, 0.10852127725172303, 0.1046608438249877, 0.10029683762481104, 0.09551139179817546, 0.09039377109318807, 0.0850384039582644, 0.07954280706252684, 0.07400545086026292, 0.06852361609956831, 0.0631912912477587, 0.05809715967363739, 0.05332272311866329, 0.048940604563649966, 0.045013069140342234, 0.04159079635876685, 0.03871193075477717, 0.03640143126000291, 0.03467073232614073, 0.033517722276063644, 0.03292703669128237, 0.0328706570667524, 0.033308797655368046, 0.03419105656418262, 0.035457800919515614, 0.03704175044020806, 0.038869719179685076, 0.04086447162801638, 0.04294664688950207, 0.04503670332689538, 0.047056835919046074, 0.04893281961406379, 0.05059573414539996, 0.051983529055417727, 0.05304239195500346, 0.05372788822869722, 0.054005846340777576, 0.053852969458096964, 0.05325716111463716, 0.052217559924342655, 0.05074428571998971, 0.04885790677200486, 0.046588644740373004, 0.04397534056045951, 0.041064210396747916, 0.03790742596986512, 0.03456155784388973, 0.03108592354736652, 0.027540884612371513, 0.023986137698163643, 0.02047904489460418, 0.01707304707981004, 0.013816201869473431, 0.01074988430298973, 0.007907684051522588, 0.005314527717172674, 0.0029860488537397974, 0.0009282218294878514, -0.0008627312635506179, -0.0024001585951071882, -0.0037065266129115457, -0.004812710285889268, -0.005757044517650248, -0.006584161935966061, -0.007343647882449639, -0.008088548258332693, -0.008873769803881663, -0.009754415300264111, -0.010784098008634857, -0.012013280354192243, -0.013487681403792747, -0.015246796084228895, -0.017322566383052764, -0.01973824103127131, -0.02250745547992713, -0.025633558466973114, -0.029109205264406975, -0.03291623095337429, -0.03702580996561203, -0.041398900831444485, -0.04598696777085252, -0.05073296363872951, -0.05557255196799719, -0.06043553961588615, -0.06524748596762277, -0.06993144992936609, -0.07440983216952916, -0.0786062673421185, -0.08244751941911069, -0.08586533281506839, -0.08879819272124964, -0.091192949964171, -0.09300626872176258, -0.09420585949777274, -0.09477146477460432, -0.09469557061509831, -0.09398382402287955, -0.09265514293929976, -0.09074151317987116, -0.08828747421230781, -0.08534930326510896, -0.08199391464318087, -0.07829749813301277, -0.07434392683114667, -0.0702229704662227, -0.06602835516419236, -0.06185571450663225, -0.057800479555679074, -0.053955757194426156, -0.05041024661531729, -0.04724624306698999, -0.044537776057578984, -0.04234892615439141, -0.04073236038889629, -0.039728121171380394, -0.039362697664548925, -0.03964840190391271, -0.040583064746502494, -0.042150059153229016, -0.04431865054813577, -0.047044666238560656, -0.05027146831247288, -0.053931207236981006, -0.05794632673998371, -0.06223128462646233, -0.06669444910581895, -0.07124012610978422, -0.07577067006060324, -0.08018862867883024, -0.08439887174336919, -0.08831065424828664, -0.09183956612672341, -0.0949093235880237, -0.09745336106789998, -0.09941618772466154, -0.10075447820496128, -0.10143787390697653, -0.10144947802697861, -0.1007860351130334, -0.09945779348427167, -0.0974880565183815, -0.09491243627645705, -0.09177783004054252, -0.08814114691183436, -0.0840678174967518, -0.07963012475156787, -0.07490539814256818, -0.06997411631022543, -0.06491796533135759, -0.05981790040942127, -0.05475225837572815, -0.04979496676858478, -0.045013892517150336, -0.04046936946401034, -0.036212939212857724, -0.03228633420650774, -0.028720725667476594, -0.025536252227140604, -0.022741837901568345, -0.0203353007226745, -0.018303745986667744, -0.016624230921705365, -0.015264680782031788, -0.01418503011598282, -0.013338557385694737, -0.012673376375221009, -0.01213404402808327, -0.011663241598237365, -0.011203484346991366, -0.010698814511709372, -0.010096432920519397, -0.00934822641203682, -0.008412151093116639, -0.007253435356323094, -0.005845571382185906, -0.004171069446503937, -0.0022219555972444543, -2.1943931114862367e-17], [0.0, 0.0034246641548217696, 0.007153331743936164, 0.011140964910712148, 0.015332653515663649, 0.019665180601642983, 0.02406882847961949, 0.028469377503397755, 0.03279024447302175, 0.03695470383369965, 0.04088813251692745, 0.044520218463616645, 0.0477870735979016, 0.05063319426872937, 0.05301321588985652, 0.05489341359610506, 0.05625290706859598, 0.05708453510657652, 0.05739537385314715, 0.05720688160841972, 0.0565546626603093, 0.055487852291993656, 0.054068134841524215, 0.05236841614845591, 0.050471180685954894, 0.048466571917857734, 0.04645024172941552, 0.04452102097164599, 0.042778468073552164, 0.0413203561866997, 0.0402401613402845, 0.03962461454647425, 0.03955137968863178, 0.04008691637119517, 0.04128458277020309, 0.043183027995494914, 0.04580491669197022, 0.04915602073191563, 0.0532247040747043, 0.05798181740828535, 0.0633810092704193, 0.06935945021993888, 0.07583895653852471, 0.08272749014026513, 0.08992100209172343, 0.09730557862891093, 0.10475984101073231, 0.11215754415890689, 0.11937031396167616, 0.1262704594902446, 0.13273379428499266, 0.1386424003675441, 0.1438872697402486, 0.14837076082257844, 0.15200881148152137, 0.15473285594005806, 0.1564913997591367, 0.15725121511745307, 0.15699812756554737, 0.15573737508920432, 0.1534935304474268, 0.1503099881062132, 0.14624802741924636, 0.14138547375922422, 0.13581498883449594, 0.12964203020324705, 0.12298252780850319, 0.11596033201218113, 0.10870449294417307, 0.10134643487416313, 0.09401709166619507, 0.08684407013331483, 0.07994890725541637, 0.07344448478069285, 0.06743266076172762, 0.06200217218048077, 0.05722685612633601, 0.0531642291736294, 0.049854455852766856, 0.04731972763789631, 0.045564063917192844, 0.04457353621374454, 0.0443169067359162, 0.044746662405357046, 0.04580041608113757, 0.04740263799966281, 0.0494666726933765, 0.05189699002453575, 0.05459161363293468, 0.05744466617564766, 0.06034896832464624, 0.06319862763901492, 0.06589155415816352, 0.0683318418474983, 0.07043195880658586, 0.07211469432314711, 0.0733148172911058, 0.07398040804321378, 0.07407383408741344, 0.0735723493679084, 0.07246830626694184, 0.07076897938055496, 0.06849600989512435, 0.06568448891637867, 0.06238170712121939, 0.058645606390482316, 0.05454297643196897, 0.05014744563564311, 0.04553732036318493, 0.04079333044058424, 0.035996340708770204, 0.031225089044280868, 0.026554010278998532, 0.02205120295302484, 0.017776591893782834, 0.01378033432962032, 0.01010151075344435, 0.006767134217361799, 0.00379150335515726, 0.0011759154091472064, -0.0010912538891561078, -0.0030341063295863625, -0.004688425388297966, -0.006100550010759341, -0.0073259481252928565, -0.008427527877541535, -0.009473731482734535, -0.010536462351916609, -0.0116889006134032, -0.013003265207158827, -0.01454858229853204, -0.0163885197971849, -0.01857934627398068, -0.021168069578473954, -0.024190806045629558, -0.027671425451553204, -0.03162050997662079, -0.03603465753240679, -0.04089615110359996, -0.046173006465504936, -0.051819400994675545, -0.05777647653689174, -0.06397349967843598, -0.07032935352593349, -0.0767543264703647, -0.08315215561090884, -0.08942227574241582, -0.09546221923959605, -0.1011701079449743, -0.10644717539645025, -0.11120025648816148, -0.11534418198146969, -0.11880401716863061, -0.12151708739850187, -0.12343473802200822, -0.12452378248953276, -0.12476759968426496, -0.1241668499265734, -0.12273978823129719, -0.12052216311888511, -0.11756669933434029, -0.11394217296796083, -0.10973209744923017, -0.10503304845374668, -0.09995266468624449, -0.09460736955943536, -0.08911986577844826, -0.08361646058985199, -0.07822428381859464, -0.07306846368559251, -0.06826932669956566, -0.06393968761397323, -0.06018229353779218, -0.05708748283092336, -0.054731114482999325, -0.053172817386282795, -0.05245460142062401, -0.052599863752113424, -0.05361281441342697, -0.05547833530935229, -0.05816227651664805, -0.06161218337293785, -0.06575843762702177, -0.07051578610136007, -0.07578522113534654, -0.08145616875844487, -0.08740893328730055, -0.09351734102642428, -0.09965152112339894, -0.1056807584982512, -0.11147635220732058, -0.1169144126508725, -0.12187853268753326, -0.12626227093483058, -0.12997139023290338, -0.13292580031074208, -0.13506116097080698, -0.13633011041862259, -0.13670309250389615, -0.1361687663837689, -0.13473399222740717, -0.13242339680614107, -0.1292785329042091, -0.12535665619506867, -0.12072915232023655, -0.115479655160451, -0.10970190450247158, -0.10349739730493825, -0.09697289140961748, -0.09023782372011603, -0.08340170650525477, -0.07657156554357741, -0.06984948231277273, -0.06333029938592376, -0.05709954370602303, -0.05123161658745625, -0.045788292287296764, -0.04081755897842528, -0.03635282714346573, -0.032412521015575395, -0.029000058955415017, -0.026104218817433925, -0.02369987466911534, -0.021749081926065415, -0.02020247928561165, -0.019000967997746258, -0.018077622199313043, -0.01735977842364706, -0.01677124812144621, -0.016234594193761102, -0.015673411212590964, -0.015014549218661062, -0.014190222730837695, -0.013139949830177662, -0.011812270809471979, -0.010166201786898123, -0.008172385718557083, -0.005813911229499545, -0.0030867784128778596, -3.037580115434353e-17], [0.0, 0.004415469164794989, 0.00918681853690486, 0.01425131203144025, 0.019534902027938568, 0.02495435814114457, 0.030419663555842184, 0.03583661518879555, 0.04110955849134105, 0.046144184026030585, 0.05085031113505788, 0.05514458411519827, 0.05895300832371782, 0.06221325751405295, 0.06487668934393491, 0.0669100132722966, 0.06829656378384444, 0.06903714183401295, 0.06915039834328951, 0.06867274521467445, 0.06765779140916388, 0.06617531378848955, 0.06430978441541736, 0.06215848748746024, 0.05982926977949568, 0.05743797811318171, 0.05510564571082345, 0.05295549611509227, 0.051109838487803025, 0.049686931406733206, 0.04879789367040843, 0.04854374005561317, 0.049012617458488235, 0.05027731244335582, 0.05239309502699404, 0.05539595568782017, 0.05930128329830652, 0.06410302116041312, 0.06977332683429421, 0.07626274927107424, 0.08350092418985759, 0.09139777598641805, 0.09984520203798793, 0.10871920338198177, 0.11788241469045713, 0.1271869765108571, 0.1364776841445614, 0.14559534050261855, 0.1543802349891342, 0.16267566705094172, 0.17033143158520572, 0.17720718395415475, 0.18317560490866763, 0.18812529021136457, 0.19196329606903265, 0.19461727948241428, 0.1960371821060739, 0.1961964169530497, 0.19509252901811394, 0.19274731334490075, 0.1892063869234958, 0.18453822376370316, 0.1788326752300038, 0.17219900993733808, 0.1647635188952976, 0.15666674187528926, 0.14806037991092225, 0.13910396620955925, 0.12996137337443484, 0.12079723857654132, 0.11177339008434317, 0.1030453583163301, 0.09475905233480475, 0.0870476785065189, 0.08002897202186074, 0.07380280423929617, 0.06844921959699268, 0.06402694533687282, 0.06057240577648997, 0.05809926062433351, 0.0565984741651691, 0.056038909354565056, 0.056368428269001083, 0.057515468267688406, 0.059391051929311135, 0.06189117860598316, 0.06489953653550178, 0.06829046708612804, 0.07193210705199762, 0.07568963110561482, 0.07942851463461252, 0.0830177372830093, 0.0863328495736248, 0.08925882895060402, 0.09169265734454606, 0.0935455597785053, 0.0947448524114655, 0.09523535853121542, 0.0949803621051001, 0.09396208029528395, 0.09218164854849573, 0.0896586241728607, 0.08643002640867845, 0.08254894258404034, 0.07808274073154428, 0.07311093876111766, 0.06772278869538259, 0.06201464137049909, 0.05608716221775267, 0.0500424721425045, 0.04398128902632737, 0.038000144961596094, 0.032188752000256636, 0.02662758502270149, 0.02138574441769452, 0.016519153762769512, 0.012069138798858924, 0.008061423930332373, 0.004505571508575921, 0.001394877552862693, -0.0012932743785747543, -0.0035966114284552487, -0.0055667437559691274, -0.007267544028283465, -0.008773177473790703, -0.010165835056615946, -0.011533230160754134, -0.01296592545672377, -0.014554561203199251, -0.016387058992994634, -0.018545875815148574, -0.02110538224849299, -0.024129435651074126, -0.02766921443595596, -0.0317613730450485, -0.03642656920949549, -0.04166840571769522, -0.047472818434167924, -0.053807930986437096, -0.060624384646785504, -0.06785613977975212, -0.07542173311033809, -0.08322596329738474, -0.09116196616875423, -0.0991136307715047, -0.10695829837039114, -0.11456967892186455, -0.12182091355351755, -0.12858770734618666, -0.13475145435941877, -0.14020227642603506, -0.14484189878506784, -0.14858628909267968, -0.1513679916680444, -0.15313809586970148, -0.15386778608866086, -0.15354943077967723, -0.1521971789899357, -0.14984704471534557, -0.14655647182789652, -0.1424033849682406, -0.13748474437442493, -0.13191463481028842, -0.1258219302640745, -0.11934758662427652, -0.11264162384393765, -0.10585986694481118, -0.09916052139286272, -0.09270066274092122, -0.08663272287177536, -0.08110105562166398, -0.07623866300485745, -0.07216415972901652, -0.06897904827085025, -0.06676536960139523, -0.06558378588236069, -0.0654721413109856, -0.06644453601613659, -0.06849093577628808, -0.07157732763508176, -0.07564641854083072, -0.08061886124743901, -0.08639497919921132, -0.09285695028526465, -0.09987139847854058, -0.10729233273384615, -0.11496436434292537, -0.12272612743035324, -0.13041382257936002, -0.13786480081425861, -0.14492110440123446, -0.15143288217829642, -0.15726160035513403, -0.1622829748530446, -0.16638955815605316, -0.16949292214560358, -0.17152538828253944, -0.17244126753745403, -0.17221758438202647, -0.17085427164680658, -0.16837383581836926, -0.16482050507790702, -0.16025888476273223, -0.1547721566595679, -0.14845986932827154, -0.14143537624478045, -0.13382298671070408, -0.12575490100799633, -0.11736800602498844, -0.10880061043360485, -0.10018919939267926, -0.09166528767342244, -0.08335244708358908, -0.07536357918809856, -0.0677984977129721, -0.06074187684635642, -0.054261612123400214, -0.04840762994222154, -0.043211170274713745, -0.03868455509741419, -0.03482144277616922, -0.031597556401652044, -0.028971862196608807, -0.026888162896100933, -0.02527706071804157, -0.024058235448115153, -0.023142975485567492, -0.022436893623374515, -0.02184275501641952, -0.0212633423288466, -0.020604282504270925, -0.019776760979460805, -0.018700052424585535, -0.01730380215496339, -0.015529999089177316, -0.013334589353382506, -0.010688689141137854, -0.007579365989543868, -0.004009968957242072, -3.9314484311946475e-17], [0.0, 0.005449960465010133, 0.011294384140923331, 0.017450882530927487, 0.023824842787335876, 0.030312166708526225, 0.036802288247519944, 0.043181389114940454, 0.04933572672818451, 0.05515498562255843, 0.060535562580564695, 0.06538369717687711, 0.06961836314527975, 0.07317384185931043, 0.07600190713499505, 0.07807356031505233, 0.07938026593606919, 0.07993465092982607, 0.07977064395034804, 0.07894304570714387, 0.07752653576340204, 0.07561413575868509, 0.07331516307323437, 0.07075272221012088, 0.06806079329622526, 0.06538098778520413, 0.06285905041245603, 0.06064119347322315, 0.058870354388047524, 0.05768247015528513, 0.05720286259474661, 0.057542826244221024, 0.05879650642451939, 0.06103814843907766, 0.06431979027645898, 0.0686694607449394, 0.07408993294060835, 0.08055806962693503, 0.08802478281020656, 0.0964156148820707, 0.10563193353416454, 0.11555271760409216, 0.1260368964582534, 0.13692619181525612, 0.14804839840360115, 0.15922102883999503, 0.17025523888455368, 0.1809599420075264, 0.1911460171711769, 0.2006305110186534, 0.2092407353407778, 0.21681816277471813, 0.22322202812945832, 0.22833254942785586, 0.23205369154441646, 0.2343154059906935, 0.23507529269897384, 0.2343196432820948, 0.23206383987247348, 0.22835209891166855, 0.22325656480200845, 0.21687577376614597, 0.20933252321342452, 0.20077119601993532, 0.19135460204902013, 0.18126041065670673, 0.17067725756493862, 0.1598006171108487, 0.14882853630848325, 0.13795733025988652, 0.1273773391519811, 0.11726884535970107, 0.10779824508902958, 0.09911456263863602, 0.09134638689387144, 0.08459929930166472, 0.07895385056540254, 0.07446412994121368, 0.07115695663991198, 0.06903170779542617, 0.0680607821199175, 0.0681906831036975, 0.06934369080769488, 0.0714200772989661, 0.07430080793631834, 0.07785065933516291, 0.08192167520316612, 0.08635687357256783, 0.09099411344353334, 0.0956700256243504, 0.10022391168077843, 0.10450151640211801, 0.10835858301068842, 0.11166410638204427, 0.11430320764829896, 0.11617956351838847, 0.1172173352134728, 0.11736255479016863, 0.11658394048428641, 0.11487312720479387, 0.1122443130783418, 0.10873333761936571, 0.10439622131321033, 0.09930720979590996, 0.09355637806131568, 0.08724686092068705, 0.08049178501507279, 0.07341098481370824, 0.06612759004822566, 0.05876457481195515, 0.05144135903155318, 0.04427055118797881, 0.037354917076742516, 0.030784653161269295, 0.024635034849861757, 0.018964500027596146, 0.013813216655439355, 0.009202170503792158, 0.005132795441033607, 0.001587154496374091, -0.0014713344789067172, -0.0040966489515708365, -0.006358421739098663, -0.008339757837870504, -0.010134666556557708, -0.011845177571389509, -0.013578217870034296, -0.015442332931144826, -0.017544339733848453, -0.019986001195959124, -0.02286081134823581, -0.02625097796918291, -0.03022468459297043, -0.03483370688051727, -0.040111449482345955, -0.04607145894220544, -0.05270645615687925, -0.05998791872119612, -0.06786622947861175, -0.07627139311857142, -0.08511430807634404, -0.09428856666661876, -0.10367274268043038, -0.11313311294263675, -0.12252674788726625, -0.13170489635197494, -0.14051658177299753, -0.14881232098531388, -0.15644787305577487, -0.1632879241014434, -0.1692096149161446, -0.17410582143147216, -0.17788810350245768, -0.18048924510454092, -0.18186531857580893, -0.18199721680624598, -0.18089160999024428, -0.17858129740964582, -0.17512493936302365, -0.1706061694431553, -0.165132102517465, -0.15883126861194352, -0.1518510170708224, -0.14435444851109927, -0.13651694388653848, -0.1285223701263041, -0.12055905006525772, -0.11281559052886486, -0.1054766663196732, -0.09871885937408398, -0.09270665147506273, -0.08758866563509451, -0.08349424567930708, -0.08053045579337578, -0.07877957204043351, -0.07829712633065083, -0.07911055032483631, -0.08121845258422555, -0.08459054728637287, -0.08916823737588196, -0.09486583948421518, -0.10157242271280437, -0.10915421879887535, -0.11745754762826217, -0.12631218985364528, -0.13553512781658178, -0.14493456731365145, -0.15431414620058495, -0.16347723155118205, -0.17223120518238522, -0.18039163786704165, -0.1877862554666229, -0.19425860545349377, -0.19967133972543055, -0.20390903905949243, -0.2068805157744135, -0.2085205438935381, -0.20879098001063043, -0.20768125281660274, -0.2052082144840646, -0.20141536245504557, -0.1963714552596585, -0.1901685604414243, -0.18291958612634943, -0.1747553599204224, -0.16582132935980157, -0.15627396681563505, -0.14627696836364354, -0.1359973405112868, -0.12560147073181838, -0.11525127744173863, -0.10510053239177994, -0.09529144349542297, -0.08595157902324212, -0.07719120502918686, -0.06910109707773032, -0.06175087508267651, -0.055187896658950096, -0.049436730165516134, -0.04449921393777316, -0.04035509343893933, -0.036963213571213606, -0.03426322954008865, -0.03217778680364495, -0.03061510908215032, -0.029471923437760627, -0.028636643305154603, -0.027992724260723113, -0.02742210340830591, -0.026808631626313608, -0.026041408600030583, -0.02501793353156749, -0.023646989598476033, -0.021851187485210682, -0.019569102452243158, -0.016756950201272124, -0.013389758965878863, -0.009462008495003919, -0.004987720565017396, -4.8714918725756224e-17], [0.0, 0.006521523232359227, 0.013461307685477633, 0.020715740022888337, 0.028168639962808554, 0.03569464365281609, 0.04316285958283444, 0.05044069942991049, 0.05739778147079768, 0.06390980206315203, 0.06986227123990627, 0.07515401167335695, 0.07970032606771542, 0.08343574628807784, 0.08631628802495202, 0.08832114726497568, 0.0894537889784637, 0.08974239388873843, 0.0892396455690878, 0.08802185700903922, 0.08618745277720531, 0.08385483955504351, 0.08115971370398033, 0.07825186925523403, 0.07529158290338729, 0.07244566390506255, 0.06988326594282133, 0.0677715647749669, 0.06627140967701131, 0.06553305817683372, 0.06569210234650373, 0.06686569096096777, 0.06914914525655566, 0.07261305697536238, 0.07730094608159611, 0.08322754225605897, 0.09037773933795627, 0.09870625565398747, 0.10813801605081041, 0.11856925384920054, 0.129869313299926, 0.14188311587784216, 0.1544342373284662, 0.16732852718738217, 0.18035818890483193, 0.1933062270644337, 0.2059511587775218, 0.21807187939990502, 0.22945256843222886, 0.23988751993999763, 0.24918578310835648, 0.2571755026047414, 0.26370785516596607, 0.2686604880956194, 0.271940376930977, 0.2734860331374045, 0.2732690079838433, 0.271294655374975, 0.26760213396072374, 0.26226364688569465, 0.2553829356413135, 0.24709306220155217, 0.23755353052812833, 0.22694681421163754, 0.21547437108988046, 0.20335223781156833, 0.19080630719829558, 0.17806739866070323, 0.16536623666754632, 0.15292845423548934, 0.14096973755747222, 0.1296912242420083, 0.11927526128687614, 0.10988162001653132, 0.10164425399359808, 0.09466867264815632, 0.08902998838120595, 0.08477167855948545, 0.08190508652917407, 0.08040966796011381, 0.08023397092649806, 0.08129732057242542, 0.08349216242994133, 0.08668700286194779, 0.09072987107147157, 0.09545221499182854, 0.10067313344119996, 0.10620383942730978, 0.11185224460001429, 0.11742755268362316, 0.1227447503211359, 0.12762888710528147, 0.1319190425644965, 0.1354718863585624, 0.13816474869993395, 0.13989813077831442, 0.14059759940426736, 0.1402150258381929, 0.13872914543766127, 0.13614543192082393, 0.132495297276886, 0.1278346452261377, 0.12224182222148752, 0.11581502489088191, 0.10866923617585385, 0.10093277389564712, 0.09274354477652215, 0.08424510390424804, 0.07558262391701162, 0.06689887995297909, 0.05833035536542066, 0.05000356955023734, 0.0420317229943782, 0.0345117460118316, 0.027521826809620998, 0.02111948179714435, 0.015340216743472723, 0.010196811863458522, 0.005679247569588644, 0.0017552708776610532, -0.0016284142742737985, -0.004544365818237665, -0.007082079910691059, -0.009345187476857435, -0.011448246141126954, -0.01351321337963438, -0.0156656951721007, -0.01803107045665115, -0.020730595148937807, -0.023877590285514075, -0.02757381696799161, -0.031906136263540996, -0.03694354516973753, -0.04273467035227884, -0.0493057898467709, -0.05665943956823648, -0.06477364662827773, -0.0736018154920528, -0.08307327631634591, -0.09309448781574498, -0.10355087013435015, -0.1143092268812238, -0.12522070013158262, -0.13612418819188526, -0.14685014363166532, -0.15722465881238523, -0.16707373815798654, -0.17622765092077286, -0.18452525534561692, -0.19181818500534975, -0.19797479068312213, -0.20288373645791552, -0.20645715648482507, -0.20863328916597754, -0.20937851773537616, -0.20868876043265217, -0.20659016907174624, -0.2031391115385459, -0.19842143116601627, -0.19255099360801153, -0.18566754932804225, -0.1779339567045687, -0.1695328266118106, -0.1606626637710504, -0.15153359282276285, -0.14236276762856973, -0.13336957050909812, -0.12477071375214048, -0.11677535864067819, -0.10958036737463274, -0.10336580058429766, -0.09829076771685982, -0.0944897295471721, -0.09206934161127207, -0.0911059147370625, -0.09164355435555044, -0.09369302426873788, -0.097231363414718, -0.10220226632280979, -0.10851721982540924, -0.11605737062946207, -0.12467608098609019, -0.1342021133544399, -0.14444337003277408, -0.15519110058910904, -0.16622447888443748, -0.17731544281155026, -0.1882336837813067, -0.19875166962235505, -0.20864958399947306, -0.21772006771074726, -0.22577265223682377, -0.23263778356082337, -0.23817034436538242, -0.24225259499411617, -0.2447964677355522, -0.24574516469929142, -0.2450740264205098, -0.2427906559357976, -0.2389343009891017, -0.23357451481265046, -0.22680913314955045, -0.21876162142228273, -0.20957786080957488, -0.19942245511277182, -0.18847465135511346, -0.1769239757978255, -0.16496569326796798, -0.1527962012298029, -0.1406084708156153, -0.12858764505316636, -0.11690689984341261, -0.10572366597866102, -0.09517630083648745, -0.08538128658582465, -0.07643101809860149, -0.06839222861823807, -0.0613050849766126, -0.055182967182244316, -0.050012929949515034, -0.04575682663298305, -0.04235305949891153, -0.03971890471941462, -0.03775334629908093, -0.036340340690485924, -0.03535242343083541, -0.03465456099292392, -0.03410814538783635, -0.03357502601999827, -0.032921472947089865, -0.032021968040233995, -0.03076272550851114, -0.029044850715189332, -0.026787055977543005, -0.0239278638566812, -0.020427242006047116, -0.016267628611204874, -0.01145432343824817, -0.006015236107340801, -5.852348480925823e-17], [0.0, 0.0076228005374259535, 0.01567161206839065, 0.02402043836380985, 0.032530978654174106, 0.041056675986922454, 0.049447014575838937, 0.05755195121816289, 0.06522636213370367, 0.07233438590059955, 0.07875354554460492, 0.08437853822596651, 0.08912458922735338, 0.09293027787279433, 0.09575975632864886, 0.09760429762022188, 0.09848312625637952, 0.09844350316140826, 0.09756005570836791, 0.0959333630507883, 0.09368782617070928, 0.09096887061543679, 0.08793954731350363, 0.08477661270031689, 0.08166618324264976, 0.07879907097410906, 0.07636591554430411, 0.07455223431118257, 0.07353351500846968, 0.07347047541309686, 0.07450461121309374, 0.07675414700449298, 0.08031049617232483, 0.08523532355427228, 0.09155829053179586, 0.09927554588854427, 0.10834900781740481, 0.11870646328533864, 0.13024249104999422, 0.14282019445427757, 0.15627371020219807, 0.17041144013402545, 0.18501993504653805, 0.19986834329136574, 0.21471332263749726, 0.22930430205916075, 0.24338897100461715, 0.25671886754563167, 0.26905493375993206, 0.280172906842031, 0.2898684177752099, 0.2979616758545459, 0.3043016267761642, 0.3087694841768256, 0.31128154912834477, 0.3117912488104719, 0.3102903439992369, 0.3068092746689011, 0.30141663343718694, 0.29421777728873355, 0.28535260848715216, 0.27499257533336635, 0.26333696196654927, 0.25060855328275944, 0.23704877585480127, 0.2229124281149722, 0.20846212270986753, 0.19396257061979102, 0.17967484019375074, 0.1658507246001999, 0.1527273483279739, 0.14052213736430524, 0.12942826867734328, 0.1196107028623364, 0.11120288956428308, 0.10430421891655658, 0.09897827413761205, 0.09525192105103232, 0.09311525011325428, 0.09252236604278784, 0.0933929998458707, 0.09561489842203237, 0.09904692848697562, 0.10352281471799532, 0.10885541721677726, 0.11484144095321981, 0.12126646009994109, 0.127910133321802, 0.13455148230730013, 0.14097410520219006, 0.14697119913528756, 0.15235027163919854, 0.15693742931566862, 0.1605811433550573, 0.16315540520408914, 0.16456220143804234, 0.16473325433469072, 0.16363099332861103, 0.16124874197708405, 0.15761012480582515, 0.15276771793124294, 0.14680098618920437, 0.1398135671701336, 0.13192997862844216, 0.12329183980345147, 0.11405370891252185, 0.10437864816777699, 0.0944336339047233, 0.08438493264521282, 0.07439356407499848, 0.06461096900129208, 0.05517499444896553, 0.04620629931102282, 0.03780527261640018, 0.03004954280794504, 0.022992140785406446, 0.016660362261384173, 0.011055356640399696, 0.006152450628672013, 0.0019021955972531633, -0.0017678911593396786, -0.004950939224112566, -0.007757756728390502, -0.010313360887953623, -0.0127531005302837, -0.015218474480203312, -0.017852757750522388, -0.02079655269502545, -0.02418338448901231, -0.028135459449008225, -0.03275970080665835, -0.03814416970733442, -0.04435496958106339, -0.0514337198716068, -0.05939567071260228, -0.06822851386796949, -0.07789192751523383, -0.08831787369044333, -0.09941164790370854, -0.11105366106137086, -0.12310191488312092, -0.13539511395897133, -0.14775634090889875, -0.15999720621111937, -0.17192237153329812, -0.18333433516108846, -0.19403836063518853, -0.20384742517810073, -0.21258706303830102, -0.22009998054919222, -0.22625032446199903, -0.23092749285740974, -0.23404938848748505, -0.2355650274942262, -0.23545643177734435, -0.23373975046815645, -0.23046557458911215, -0.2257184285825598, -0.21961544249594955, -0.21230422871826557, -0.203960006777412, -0.1947820383450199, -0.184989451791294, -0.17481655096032694, -0.16450771591333063, -0.15431201388572738, -0.14447764635927077, -0.13524636276720706, -0.1268479728081463, -0.11949508759973165, -0.1133782149918222, -0.10866132639419833, -0.10547800164433366, -0.10392824500571074, -0.10407604966996005, -0.10594777051649731, -0.10953134578817188, -0.1147763882340375, -0.12159514563924428, -0.1298643100088884, -0.13942763449992376, -0.15009929799385693, -0.1616679394402437, -0.17390126820909632, -0.18655114305569098, -0.19935900125500366, -0.21206151127290165, -0.22439631720501974, -0.23610774125488376, -0.24695231178545615, -0.25670398892898405, -0.26515896726708904, -0.2721399455092431, -0.27749976614547567, -0.2811243434064362, -0.28293481515257746, -0.28288887310921157, -0.2809812457040684, -0.27724332816231123, -0.27174197497135594, -0.2645774898442412, -0.2558808673973194, -0.2458103584510227, -0.2345474467318818, -0.22229233841599352, -0.20925907708004254, -0.19567040495025798, -0.18175249666637075, -0.1677296939852353, -0.15381936889305717, -0.1402270385100992, -0.12714184806868956, -0.11473252831005089, -0.10314392113341803, -0.09249415256081339, -0.08287251542675313, -0.07433810608400535, -0.06691924028959743, -0.06061365377898495, -0.055389473342121034, -0.05118692497437066, -0.04792072736679116, -0.04548310207887245, -0.04374731662149601, -0.042571663741758116, -0.04180376976232937, -0.04128511714104097, -0.04085566166692754, -0.0403584230086288, -0.03964392871491073, -0.03857439619275049, -0.037027544537359056, -0.03489993816890584, -0.032109776782420274, -0.028599060818500034, -0.024335078137481883, -0.01931117540885742, -0.013546796457471923, -0.007086788962680756, -6.867870746608346e-17], [0.0, 0.008745792019826004, 0.01790828145055134, 0.02733837238351718, 0.03687555697048651, 0.046352635234073465, 0.05560064238359962, 0.06445385165505613, 0.07275471847131758, 0.08035863293948364, 0.08713835233851674, 0.09298799318843234, 0.09782647353516673, 0.10160030995751135, 0.1042856901572793, 0.10588976042138666, 0.10645108728238094, 0.10603927384858276, 0.10475373299434249, 0.10272164134758946, 0.10009511923694062, 0.09704770192734337, 0.09377018607034937, 0.0904659518498389, 0.08734587539377575, 0.08462295728568431, 0.08250680115429318, 0.08119808113184675, 0.08088313831941055, 0.08172884423577668, 0.08387786359747147, 0.0874444398095792, 0.09251081445281692, 0.0991243771220301, 0.10729562456676116, 0.11699698862984086, 0.12816257145102958, 0.1406888043157191, 0.15443602392712563, 0.1692309373217621, 0.18486992468994198, 0.20112310854964585, 0.21773909857014256, 0.23445030432818978, 0.2509786938294653, 0.267041864103762, 0.2823592818755358, 0.2966585474340629, 0.3096815335080384, 0.3211902532288954, 0.33097231709793284, 0.338845848119602, 0.34466373670799566, 0.3483171323178132, 0.3497380866254462, 0.34890128305839885, 0.3458248090581919, 0.3405699501393265, 0.33324000802376774, 0.32397816832210574, 0.3129644658346956, 0.30041191700847386, 0.286561908885283, 0.271678951533496, 0.25604491603698476, 0.23995289225750566, 0.22370080949386417, 0.2075849686184557, 0.19189363614822785, 0.17690084895967867, 0.16286057303190415, 0.15000135083118393, 0.13852155995269566, 0.12858539070604996, 0.12031963283936467, 0.11381134197187714, 0.10910643502972481, 0.10620924157549287, 0.10508301493835352, 0.10565138405048291, 0.10780070443884678, 0.1113832454570114, 0.11622113108919557, 0.12211093399758444, 0.12882880734088215, 0.1361360266312695, 0.14378480481070766, 0.15152423802937523, 0.15910623742842828, 0.16629130360858038, 0.17285400535956388, 0.1785880325009155, 0.18331070412594605, 0.1868668278545286, 0.1891318225223109, 0.19001403563860553, 0.18945620745633387, 0.1874360550999774, 0.18396597235056478, 0.1790918628368752, 0.1728911459771494, 0.16546999551860425, 0.15695988942426709, 0.14751356669042276, 0.13730050102823418, 0.12650201285770096, 0.11530614946045782, 0.1039024682178781, 0.09247685950389227, 0.08120654397545846, 0.07025537376240816, 0.05976955854260666, 0.049873925920172195, 0.04066881120238274, 0.03222765496211344, 0.024595368104006032, 0.017787503999708486, 0.011790256132903713, 0.0065612781349976635, 0.0020313016443008333, -0.0018934933707801976, -0.005328420793497546, -0.008406625943940713, -0.011274917260996407, -0.014089204033868201, -0.017009662522956704, -0.02019576005992845, -0.023801270644231227, -0.027969416056197113, -0.032828263569492935, -0.03848650503899439, -0.04502973262003814, -0.052517313878388525, -0.06097995388925203, -0.07041801447778326, -0.08080064146022291, -0.09206573008856779, -0.10412073740194046, -0.11684432838602442, -0.130088821287912, -0.14368337667204145, -0.15743785535925714, -0.17114725275891182, -0.18459660173250494, -0.1975662234099341, -0.20983719564377956, -0.22119690228698774, -0.23144452338831503, -0.24039632680672315, -0.24789062565210893, -0.25379227327967385, -0.25799657812790894, -0.26043253424346435, -0.2610652795529832, -0.2598977124281802, -0.2569712173946289, -0.25236547245931196, -0.24619733294550264, -0.23861880937376967, -0.2298141792554974, -0.21999629411774013, -0.20940216312340795, -0.19828791279026128, -0.18692323809359965, -0.1755854732658434, -0.164553420553449, -0.1541010818052161, -0.14449144087518018, -0.13597044434293248, -0.12876132398775378, -0.12305939689177765, -0.11902746816907382, -0.11679194738128718, -0.11643977304094828, -0.11801622062271666, -0.1215236486598867, -0.12692121530392528, -0.13412557470770373, -0.14301253931801475, -0.15341967119616548, -0.16514974338592475, -0.17797499165386685, -0.19164205814200463, -0.20587751205359564, -0.22039381883949116, -0.23489561879582044, -0.24908616877992362, -0.26267379707380145, -0.275378221360102, -0.2869365833235496, -0.2971090604608812, -0.3056839260989759, -0.3124819421260634, -0.31735998520155506, -0.32021382582580094, -0.32098000016425715, -0.3196367364275918, -0.3162039203730522, -0.310742107555555, -0.30335061275559755, -0.29416472898872914, -0.28335214912258216, -0.27110868189127285, -0.25765337054886633, -0.24322313614682742, -0.2280670781257478, -0.21244057232545863, -0.1965993104678834, -0.18079342556749803, -0.16526184457674453, -0.1502270029674719, -0.13589004605917432, -0.12242662898595658, -0.10998341157679278, -0.0986753265037712, -0.08858367928295734, -0.07975511758943842, -0.07220148540161843, -0.06590055526886487, -0.06079761005566122, -0.05680782440074219, -0.0538193763658368, -0.05169720182527513, -0.050287288507568584, -0.0494213936279567, -0.04892205906419013, -0.04860779126856752, -0.048298269738359594, -0.047819447959954145, -0.04700841428817892, -0.045717887123549295, -0.04382022882490153, -0.04121087578187019, -0.03781109763700879, -0.033570016392761526, -0.0284658356113176, -0.02250625062001513, -0.01572803204524861, -0.008195796570306385, -7.911206545913124e-17], [0.0, 0.009881961576567316, 0.02015349359512294, 0.03064214572541813, 0.041165593656206124, 0.05153702230488309, 0.06157065703093032, 0.07108729446831889, 0.07991968432358522, 0.08791761703475012, 0.09495257946520541, 0.10092185163566304, 0.1057519316062308, 0.10940119265677538, 0.111861696450047, 0.11316010740823702, 0.11335767654823033, 0.11254928692462633, 0.11086157702029802, 0.10845018229133196, 0.10549615801329283, 0.1022016680077397, 0.09878504320743815, 0.09547533085184974, 0.09250646896015659, 0.09011123124991219, 0.08851509458071069, 0.08793018411904813, 0.08854945065221592, 0.09054122983186094, 0.09404432470479772, 0.09916374088718395, 0.10596718844528782, 0.11448244633141566, 0.124695664530283, 0.13655065640500325, 0.14994920964888536, 0.1647524193417717, 0.18078302149188755, 0.1978286807368737, 0.21564616219281216, 0.2339662953656093, 0.2524996181245064, 0.27094257147992856, 0.28898410173993727, 0.3063125158984349, 0.32262242910684064, 0.3376216399809297, 0.35103777038184647, 0.362624511172907, 0.37216732418182424, 0.37948846298635175, 0.3844511908947401, 0.3869630932324728, 0.3869784023213566, 0.3844992768313341, 0.37957600193443225, 0.372306102292939, 0.36283238574768417, 0.3513399610085282, 0.3380522970685663, 0.3232264148714521, 0.3071473224021933, 0.29012182234324135, 0.2724718363024482, 0.2545274010162606, 0.23661949958409728, 0.2190728945135771, 0.20219912906280849, 0.1862898590652939, 0.17161066922327334, 0.15839551596002036, 0.14684192362458853, 0.13710704252068043, 0.12930465633536006, 0.12350320358650044, 0.11972485325332625, 0.11794564940137144, 0.11809671398200948, 0.12006647170376136, 0.12370383655462672, 0.1288222767937981, 0.13520465458008837, 0.14260871836314254, 0.1507731111667643, 0.15942374630044384, 0.16828039411981285, 0.17706331940245373, 0.1854998087998017, 0.1933304316586846, 0.20031488516997653, 0.20623728609505645, 0.21091078595210425, 0.21418140414058967, 0.2159309935978825, 0.21607927570954696, 0.2145849047786534, 0.21144554680851835, 0.20669698205669437, 0.20041126515985985, 0.19269400000396314, 0.1836808083414378, 0.17353309089725172, 0.16243319687091065, 0.15057913191052844, 0.1381789454616402, 0.12544494561572886, 0.11258789303027716, 0.09981132508722039, 0.08730615722018215, 0.07524570038912293, 0.06378122222324492, 0.05303816468609073, 0.04311311361783265, 0.03407159562647006, 0.025946756039143124, 0.018738948540797266, 0.012416243306468839, 0.006915836480074032, 0.0021463203741795374, -0.002009248643094878, -0.0056895683782931935, -0.009050697570334209, -0.012261169556210073, -0.015496744154061846, -0.018934938632098698, -0.022749484577369975, -0.02710485965769934, -0.03215104162528494, -0.03801862648001732, -0.0448144436283414, -0.0526177883654271, -0.06147737638694081, -0.07140910669294087, -0.08239469864039954, -0.09438124655013014, -0.10728171174054112, -0.12097634773726357, -0.13531503030264125, -0.15012044045114997, -0.16519202636013738, -0.18031064961439555, -0.19524380305870445, -0.20975127213863357, -0.2235910993820011, -0.2365257029285118, -0.24832799498382752, -0.25878734489484984, -0.26771523425771226, -0.2749504580240314, -0.28036373581372503, -0.2838616113311943, -0.2853895345865511, -0.2849340411372134, -0.28252396431164456, -0.27823063982375246, -0.2721670867575333, -0.2644861739917982, -0.25537780612484723, -0.24506518723048168, -0.2338002437279129, -0.22185830870847295, -0.20953218870659643, -0.19712574966497476, -0.18494717132800645, -0.17330202818758536, -0.16248636017289855, -0.15277989738703945, -0.14443960031070688, -0.13769367007830924, -0.13273617284228617, -0.1297224081284, -0.12876513378598345, -0.1299317400691821, -0.13324244303310573, -0.13866954333402806, -0.14613777127020028, -0.15552571310316526, -0.16666828798622105, -0.17936021982275385, -0.19336042469142065, -0.20839721268441802, -0.22417418363999742, -0.24037667978222793, -0.25667864511035776, -0.2727497318265973, -0.2882624883859878, -0.3028994620320872, -0.3163600509867877, -0.32836694773248304, -0.3386720249036363, -0.3470615289432294, -0.3533604635410655, -0.35743606454041577, -0.3592002899936194, -0.3586112728260055, -0.3556737085479929, -0.35043817602571725, -0.34299941485575974, -0.33349360776601517, -0.3220947400761646, -0.3090101300233721, -0.294475243163759, -0.27874792062916354, -0.2621021643535391, -0.24482163216647998, -0.22719300165329565, -0.20949936376600028, -0.1920138052987268, -0.1749933335734052, -0.15867328717208182, -0.14326236354836488, -0.12893837818529952, -0.11584485105129494, -0.10408849491743377, -0.09373765717185732, -0.08482174267512786, -0.07733162054724534, -0.07122099317774919, -0.06640868181770428, -0.0627817604409862, -0.06019944871414166, -0.05849765640444377, -0.05749405584042972, -0.05699354650331767, -0.056793966776142624, -0.05669190252738665, -0.05648844068146248, -0.055994718257739724, -0.05503712347441543, -0.05346201525012615, -0.051139840540901746, -0.04796854508481875, -0.04387619187780613, -0.038822722592598, -0.032800819646696115, -0.025835850152490375, -0.01798489694597926, -0.009334905681965737, -8.974889810989014e-17], [0.0, 0.011022352745888276, 0.022388864193017933, 0.033903951249642, 0.04536434496322424, 0.056565114366306506, 0.06730576103157976, 0.07739622059178955, 0.08666260960566383, 0.09495256242965958, 0.1021400130315736, 0.10812929069973597, 0.11285841600993697, 0.11630150377506579, 0.11847020250847588, 0.11941412460807103, 0.11922024739302234, 0.11801129164559959, 0.11594311075766123, 0.11320114928650522, 0.10999605403721513, 0.10655854309133278, 0.10313365792695457, 0.09997454041903969, 0.09733588964291782, 0.09546726268779046, 0.09460638887517828, 0.0949726677264181, 0.09676101769571027, 0.10013623514983055, 0.10522801150656169, 0.1121267411162571, 0.12088023375407361, 0.13149142393889401, 0.14391714523742916, 0.15806801183811178, 0.1738094226252904, 0.19096367541678033, 0.2093131516281372, 0.22860450507355948, 0.24855376356512898, 0.2688522290523341, 0.2891730418244017, 0.30917825728522336, 0.3285262704327845, 0.34687941377135056, 0.36391154919718227, 0.3793154735657779, 0.3928099612020716, 0.40414627447826945, 0.4131139855745113, 0.4195459683710426, 0.4233224387179075, 0.4243739436246328, 0.42268322466903974, 0.418285907541296, 0.4112699974704565, 0.40177418864950415, 0.38998502399105783, 0.37613296892242404, 0.36048748879871745, 0.3433512432460557, 0.32505353176517976, 0.30594314271737316, 0.286380771946329, 0.26673118741824703, 0.247355322142596, 0.22860247912630988, 0.2108028291809089, 0.19426037511960312, 0.17924654443078525, 0.16599455717828776, 0.15469469703518798, 0.14549059147014265, 0.13847658271075167, 0.13369624480564574, 0.13114207454029375, 0.1307563558055503, 0.13243316896083948, 0.13602148946029552, 0.14132929418455134, 0.1481285701709151, 0.15616109933603073, 0.1651448748471991, 0.17478099045199824, 0.1847608336621278, 0.1947734074503662, 0.20451260319955394, 0.21368425007323727, 0.22201277268514405, 0.22924729974970084, 0.23516708101809747, 0.23958608786994978, 0.24235669398098197, 0.24337235599103646, 0.2425692394631927, 0.23992676201805946, 0.2354670526826004, 0.22925335353292087, 0.22138741596244643, 0.21200596871913444, 0.20127635761335239, 0.18939147693996128, 0.17656412968851942, 0.16302096711764696, 0.14899616791573495, 0.13472502272963516, 0.12043759118768044, 0.1063525956511039, 0.09267170888246425, 0.07957438180892634, 0.06721334286912335, 0.055710882443691025, 0.045156015042587434, 0.03560258878881881, 0.027068386887372193, 0.019535239831745682, 0.012950140736843883, 0.00722733006479467, 0.0022512907914438974, -0.002119428615236148, -0.006047667568119219, -0.009712506095611433, -0.013303655630238317, -0.017015538662142643, -0.021041216316217914, -0.025566327077648266, -0.030763199867254083, -0.0367853004530339, -0.0437621618810319, -0.051794937423617585, -0.06095269878081484, -0.07126958332521541, -0.08274287252851943, -0.09533205989177414, -0.10895894132096144, -0.12350873458383752, -0.13883220791616124, -0.15474877168655604, -0.17105046194088797, -0.1875067212651339, -0.2038698613244986, -0.21988107319357575, -0.23527683665519875, -0.249795568399878, -0.2631843417973975, -0.2752055078322031, -0.28564304798544865, -0.29430849529342695, -0.30104626939259904, -0.30573828485034443, -0.3083077091546332, -0.30872176698184156, -0.30699351028676675, -0.3031824988016641, -0.29739436207703746, -0.28977924159242474, -0.2805291390344734, -0.269874223900258, -0.25807817946524403, -0.24543269021442377, -0.2322511954725675, -0.21886205264440953, -0.20560126871918769, -0.192804970121364, -0.18080178830892382, -0.16990534154156361, -0.16040699187808038, -0.15256905073776916, -0.14661859640458902, -0.14274205289931446, -0.14108066202662164, -0.141726959544278, -0.14472234280365529, -0.15005579144586095, -0.15766377543080165, -0.16743135649085222, -0.17919446072199635, -0.19274327214409587, -0.20782667035734692, -0.2241576105445739, -0.24141932162487362, -0.25927217890002063, -0.27736109152474236, -0.2953232329649749, -0.31279593457964283, -0.32942455876540655, -0.3448701688279823, -0.35881681786764663, -0.370978288362362, -0.38110412756687384, -0.38898484098892133, -0.39445612663236346, -0.3974020559096043, -0.397757132552527, -0.3955071878688311, -0.39068909863770157, -0.3833893421316114, -0.3737414305012447, -0.3619222933913699, -0.34814770251897975, -0.3326668544375407, -0.3157562472886245, -0.29771300353302366, -0.2788478030704272, -0.2594775995063415, -0.23991829641449264, -0.22047756018514142, -0.20144794146480274, -0.1831004684078433, -0.1656788622057566, -0.14939450896383163, -0.13442230237490332, -0.12089744929239155, -0.10891330579269902, -0.09852028525557632, -0.08972585303260887, -0.08249559509158955, -0.07675532129541218, -0.07239413836260263, -0.06926840369769847, -0.06720644976342983, -0.06601395002330783, -0.06547978217029388, -0.06538223274808641, -0.06549537964630797, -0.06559548548940204, -0.06546723571676574, -0.06490966013762256, -0.06374158580211788, -0.061806481921916824, -0.05897657396524767, -0.055156123521542214, -0.05028379258148486, -0.04433403494713824, -0.03731748296146922, -0.029280323979972243, -0.02030268733357287, -0.01049608828421838, -1.0050939830742653e-16], [0.0, 0.012157710372977904, 0.024595700164894176, 0.03709595928976501, 0.04943562434013697, 0.0613936056205253, 0.07275719032157313, 0.08332844415768105, 0.09293023872749066, 0.10141174123563375, 0.10865321680175355, 0.11457001103895446, 0.1191156014708274, 0.12228363014951422, 0.12410885593870342, 0.12466699267800202, 0.1240734281494643, 0.12248084769894774, 0.12007581479341889, 0.11707438800086495, 0.11371687917213566, 0.110261880340729, 0.10697970645706985, 0.10414541703559857, 0.10203159170354383, 0.10090104218778649, 0.1009996462574297, 0.10254948746504794, 0.10574247822569989, 0.1107346329819254, 0.1176411431796537, 0.12653238688487528, 0.1374309835620165, 0.15030997935618656, 0.1650922207894639, 0.1816509457702148, 0.1998115909389109, 0.21935478437194983, 0.24002046327929058, 0.2615130282913968, 0.2835074199334278, 0.3056559795781717, 0.32759593713706925, 0.3489573514943211, 0.36937131762369, 0.3884782467599181, 0.4059360231249459, 0.4214278426163627, 0.43466954551711023, 0.4454162665300166, 0.4534682410135687, 0.45867562582499793, 0.46094221619400966, 0.46022796599981963, 0.4565502470773885, 0.4499838130504391, 0.4406594639531472, 0.42876143881093376, 0.4145235936509914, 0.3982244513668755, 0.38018123676305166, 0.3607430342989964, 0.3402832269486456, 0.31919139168060084, 0.29786483993159957, 0.2766999997776919, 0.2560838401028129, 0.23638553583737135, 0.21794856732259787, 0.20108343619939803, 0.18606116518660618, 0.17310773007300556, 0.16239954966840725, 0.15406013389573042, 0.1481579622853501, 0.14470563553895588, 0.1436603122870156, 0.14492541241822282, 0.14835353816152694, 0.1537505351874585, 0.16088058906874345, 0.16947222815397417, 0.17922508284964495, 0.18981723398203465, 0.2009129697352373, 0.21217076194618542, 0.22325126848236065, 0.23382516911833381, 0.2435806477313966, 0.2522303436060644, 0.25951760891151093, 0.2652219276284916, 0.2691633728899369, 0.27120600431405245, 0.27126013383109826, 0.2692834170598957, 0.2652807567634242, 0.2593030345693406, 0.25144471624274123, 0.24184040362231035, 0.23066043218790566, 0.21810563647885234, 0.20440142565537986, 0.18979132789879036, 0.17453017467982795, 0.1588771038925227, 0.143088564265412, 0.12741150225065037, 0.11207690679725246, 0.09729387719532925, 0.08324436480218818, 0.07007872130082199, 0.0579121646632947, 0.046822249745181316, 0.03684740404066776, 0.02798656125260971, 0.02019989668570936, 0.013410639780555064, 0.007507911098700029, 0.0023505044535716687, -0.0022284896673291487, -0.006416345105254077, -0.01041478979504499, -0.014433683536753178, -0.01868445383556514, -0.02337346632222216, -0.028695508185618158, -0.03482756038667451, -0.04192302724244596, -0.05010658045008327, -0.05946975904959947, -0.07006744759241791, -0.08191533237205882, -0.09498841054716751, -0.1092205999749608, -0.12450546925537893, -0.14069807857678326, -0.15761789318283012, -0.1750527033747172, -0.19276345863024053, -0.21048989932965279, -0.22795684834179447, -0.24488100688539538, -0.26097808509888876, -0.27597008799075107, -0.2895925721596919, -0.3016016880168751, -0.31178082624228004, -0.31994669577970714, -0.32595467362071273, -0.3297032836384382, -0.3311376823972976, -0.33025205368129995, -0.32709083987031407, -0.3217487666024821, -0.31436964669566864, -0.305143979332648, -0.2943053903010946, -0.28212598788213306, -0.26891073608475646, -0.2549909716528651, -0.24071721300933788, -0.22645142750236247, -0.21255893752442534, -0.19940015592288782, -0.18732234635857165, -0.1766516047541765, -0.16768525368342055, -0.16068483257769642, -0.15586985317856145, -0.15341247206046651, -0.15343321071046656, -0.15599782909417495, -0.1611154314535975, -0.16873785393155205, -0.17876035320694866, -0.19102358439468212, -0.20531682576605492, -0.22138237812818448, -0.2389210386878798, -0.25759852359979, -0.277052690784818, -0.2969013955539735, -0.31675079654884003, -0.3362039188782167, -0.3548692753489842, -0.37236934550197964, -0.38834871579722147, -0.40248169265581835, -0.41447921295127277, -0.4240948936328117, -0.43113008303755807, -0.435437800593856, -0.43692547844252955, -0.43555644734877474, -0.4313501394384472, -0.4243810110310806, -0.41477621940718984, -0.40271211699374604, -0.38840965445731906, -0.3721288098788954, -0.35416218392553667, -0.3348279201831335, -0.31446212510967697, -0.293410973046023, -0.2720226881244905, -0.2506395966014703, -0.22959044008172222, -0.20918313238964562, -0.18969813068165636, -0.17138257509840885, -0.1544453312421605, -0.13905304654021672, -0.1253273057057391, -0.11334294268143638, -0.1031275373466478, -0.09466209561102663, -0.08788288204739893, -0.08268434566514442, -0.0789230525017932, -0.07642251408048266, -0.07497877905198116, -0.07436663704594892, -0.07434626934394556, -0.07467017080553856, -0.07509016177140528, -0.07536430756388955, -0.07526356672099038, -0.07457799713340478, -0.07312236159222814, -0.07074099057581373, -0.06731177998731662, -0.06274922448999184, -0.057006412489780035, -0.05007593603729554, -0.04198969727216414, -0.03281762179224826, -0.022665317769504225, -0.011670747032584479, -1.1130967973816564e-16], [0.0, 0.013278607064410187, 0.02675525881357741, 0.040190708946473676, 0.053344318458996724, 0.06598123396369103, 0.07787943112028568, 0.08883643336284318, 0.09867552424388124, 0.10725128452660006, 0.11445430232260598, 0.1202149256636179, 0.12450595138172277, 0.12734417143798063, 0.12879072719714918, 0.12895025285711847, 0.12796882053049502, 0.1260307305522233, 0.1233542206649655, 0.12018619605081587, 0.11679610801443412, 0.11346913182047907, 0.11049881316649603, 0.10817936754251027, 0.10679782690634046, 0.1066262334191204, 0.10791408028986899, 0.11088119504733698, 0.1157112508936988, 0.12254607742327829, 0.1314809232536971, 0.14256080046950623, 0.15577801477089231, 0.17107095648874418, 0.18832419687774563, 0.2073699020885581, 0.2279905447389351, 0.24992286085564966, 0.2728629689418101, 0.2964725388086727, 0.3203858713232105, 0.3442177270247772, 0.36757172223860896, 0.3900490963485359, 0.4112576436673243, 0.43082059812556045, 0.44838525893087555, 0.46363115044403924, 0.4762775196652315, 0.4860899896863711, 0.49288620688856616, 0.4965403430822341, 0.4969863406370078, 0.49421981828000483, 0.48829858693605804, 0.4793417579723517, 0.4675274596902568, 0.4530892110639454, 0.43631103375073843, 0.41752141351144856, 0.39708624964589534, 0.37540095519947053, 0.35288189094220296, 0.32995733196880944, 0.3070581768308874, 0.2846086151219809, 0.26301697024774195, 0.24266692970905332, 0.22390936571572237, 0.20705493456705956, 0.19236762433733962, 0.18005939745313804, 0.17028604830915256, 0.1631443667875461, 0.15867066714033504, 0.15684070893336807, 0.1575710034348172, 0.1607214657742143, 0.16609934120583889, 0.17346430366129942, 0.18253459720258097, 0.19299406665633576, 0.20449990320955588, 0.2166909145675754, 0.2291961178019084, 0.24164344651546815, 0.2536683625708764, 0.2649221663820631, 0.27507980855164377, 0.2838470192141867, 0.2909665894681319, 0.29622366128729183, 0.29944990773955465, 0.3005265135649824, 0.2993858964697055, 0.2960121411176925, 0.2904401499603998, 0.282753546933829, 0.2730814008815145, 0.26159386456645406, 0.24849685159812673, 0.2340258968705251, 0.21843936561263597, 0.2020111914181577, 0.18502333427743983, 0.1677581554285709, 0.15049090664512044, 0.13348252737934413, 0.11697293410095592, 0.10117497245406543, 0.08626918485573881, 0.07239952434277626, 0.05967012039773911, 0.04814317479109372, 0.037838035868560695, 0.028731468943626284, 0.020759109305361425, 0.013818053610618188, 0.007770515875867984, 0.002448446665419817, -0.0023410109116429032, -0.006809376501579402, -0.011180165111137204, -0.01568187665861471, -0.020540831129636877, -0.025974042169904593, -0.03218232116881394, -0.039343798175033536, -0.04760803547960839, -0.057090894666480665, -0.06787029874135879, -0.07998300808936355, -0.0934225030544828, -0.10813803753274377, -0.12403489784153726, -0.14097587002945625, -0.15878388750940575, -0.17724580022340594, -0.19611717725718794, -0.21512802765954142, -0.2339892998764602, -0.2523999993050312, -0.2700547465430618, -0.2866515863955294, -0.3018998499260872, -0.3155278690211807, -0.3272903451524593, -0.3369751812409151, -0.3444095975795174, -0.34946536937477574, -0.35206304422238877, -0.3521750222342179, -0.3498274089875665, -0.34510058130017224, -0.33812843731172854, -0.3290963346988809, -0.31823775326589426, -0.3058297498344452, -0.29218730351649386, -0.27765667734313887, -0.26260794714352126, -0.24742686989695134, -0.23250628098162449, -0.21823722237864315, -0.20500001163651602, -0.19315546405462936, -0.183036478025455, -0.1749401858328276, -0.1691208596119225, -0.16578374493234233, -0.16507997298037427, -0.16710267710641985, -0.17188441117736464, -0.17939593641713092, -0.18954641097816094, -0.20218498315058153, -0.21710375569547893, -0.2340420560980452, -0.2526919163720425, -0.2727046371689091, -0.2936982850571457, -0.3152659495716649, -0.33698456853146036, -0.35842411662810986, -0.37915694372573144, -0.39876704589237694, -0.4168590539852417, -0.43306673159117953, -0.4470607861069063, -0.45855581343464963, -0.46731621775829985, -0.4731609726370714, -0.47596711760053534, -0.47567191486585714, -0.4722736229800271, -0.4658308773296539, -0.45646070074898476, -0.44433520008100835, -0.4296770357120902, -0.41275378004989305, -0.3938713069452821, -0.37336637654232024, -0.35159859843550145, -0.3289419698807785, -0.30577619481964713, -0.2824779934267962, -0.2594126106999779, -0.23692572632106068, -0.21533595680078726, -0.19492812506891538, -0.17594745259227565, -0.15859480530577305, -0.14302309772612448, -0.12933493026178725, -0.11758150367051036, -0.10776282262441145, -0.0998291682188614, -0.0936837878045698, -0.08918672051263245, -0.08615964902264535, -0.08439164318081677, -0.0836456396217241, -0.0836654841089704, -0.08418335031022715, -0.0849273404730344, -0.08562907016195068, -0.08603104092387584, -0.08589361140978675, -0.08500138891686035, -0.08316887922490288, -0.08024525257329711, -0.07611810714623357, -0.07071613790337376, -0.0640106473356088, -0.056015865010330686, -0.04678807382873191, -0.036423571961583565, -0.02505552967325716, -0.012849828920809755, -1.2206290531976526e-16], [0.0, 0.014375572875976851, 0.028849009621042723, 0.04316149755067262, 0.05705689312478482, 0.07028938564097754, 0.08263089964556569, 0.09387803625765556, 0.103858365283629, 0.11243589652791885, 0.11951557966593096, 0.12504670690956818, 0.12902512083943862, 0.1314941604917346, 0.13254431129777525, 0.13231155796004282, 0.1309744729643744, 0.1287501063235424, 0.12588877348938513, 0.1226678673632983, 0.1193848462403223, 0.11634957167853949, 0.11387618812414452, 0.11227474918168678, 0.11184280335576205, 0.11285715468958497, 0.11556601090525725, 0.1201817234633611, 0.12687431059317156, 0.13576593611645682, 0.14692649423670454, 0.16037042394213544, 0.17605484692322376, 0.19387909066359835, 0.2136856244207985, 0.23526240100820212, 0.25834656248261845, 0.28262943389669376, 0.307762697035106, 0.33336560632185874, 0.3590330826058232, 0.38434449796712583, 0.40887294660678075, 0.4321947837451915, 0.45389920659974303, 0.47359764914597446, 0.4909327655640478, 0.5055867859687845, 0.5172890420181816, 0.5258224789621029, 0.5310289941769102, 0.5328134696686659, 0.5311463967547039, 0.5260650244066393, 0.5176729977497098, 0.506138489112483, 0.4916908599336461, 0.47461592688381804, 0.45524993889553966, 0.43397240260067294, 0.41119792119972365, 0.3873672353604269, 0.36293767378816794, 0.33837323516402756, 0.314134531865159, 0.2906688290550861, 0.2684004102824318, 0.24772149271719357, 0.22898390178176498, 0.21249169652837224, 0.19849491412749393, 0.18718457482698458, 0.178689058380946, 0.17307192997428097, 0.17033125889011305, 0.1704004374329664, 0.17315047180331852, 0.17839368159232113, 0.18588871118200226, 0.19534672540738335, 0.2064386341124176, 0.21880316638128314, 0.2320555958237482, 0.24579690380110156, 0.25962315823882104, 0.2731348818951015, 0.2859461857169203, 0.29769345015711673, 0.30804334985161697, 0.3167000345399999, 0.3234113011079315, 0.32797361757887133, 0.3302358891306237, 0.33010188802534174, 0.3275313029231618, 0.32253939756144523, 0.31519530336411866, 0.30561900433957884, 0.29397710479331135, 0.2804775001274081, 0.2653630975901985, 0.2489047566221038, 0.23139363686180028, 0.21313315548309406, 0.19443076400187723, 0.17558975782748315, 0.15690132957069827, 0.13863706953377627, 0.12104210410139622, 0.10432904525874648, 0.08867290263644274, 0.07420708388234341, 0.06102058044190531, 0.04915640472333741, 0.03861131192223834, 0.029336806312605587, 0.02124139842543968, 0.014194047078028304, 0.008028689507791365, 0.002549734681015798, -0.0024616300984232316, -0.007240490231405352, -0.012030800142049977, -0.017077724347295414, -0.022619929477854312, -0.028882034880341606, -0.036067425526230226, -0.04435162181206668, -0.05387638668564992, -0.06474473172951567, -0.07701696084845197, -0.09070786361989552, -0.10578514084421142, -0.1221691131198265, -0.13973373016568078, -0.1583088649561775, -0.17768384337243845, -0.1976121278526793, -0.2178170432610018, -0.23799840565703043, -0.25783989054065215, -0.27701695708393437, -0.2952051293629328, -0.31208842506919543, -0.32736771689419875, -0.34076881188894825, -0.35205003962008874, -0.36100915075238565, -0.3674893435323798, -0.3713842561499717, -0.3726417876173747, -0.371266638027078, -0.36732149014098536, -0.3609267874575789, -0.352259098384529, -0.3415480910585604, -0.32907217783775694, -0.31515292168781406, -0.30014832776688605, -0.2844451717080857, -0.2684505406985908, -0.2525827838413855, -0.2372620839443356, -0.2229008734118176, -0.20989432204254485, -0.1986111241222329, -0.18938480623649318, -0.18250576584970093, -0.17821423416484214, -0.1766943354902271, -0.17806938980158318, -0.18239857601787252, -0.1896750414116779, -0.19982550832846427, -0.21271139382538515, -0.22813142182475457, -0.24582567178691397, -0.2654809736094557, -0.28673752629103133, -0.3091965886430893, -0.33242906470571637, -0.35598478514960374, -0.37940226934648413, -0.40221874136964453, -0.4239801672223812, -0.4442510802295926, -0.46262396677341755, -0.4787279952777177, -0.4922368872841181, -0.5028757502226162, -0.5104267165528328, -0.5147332627231788, -0.5157031131595924, -0.5133096684756216, -0.5075919324604893, -0.498652948287343, -0.4866567899144974, -0.4718241889622788, -0.45442690960242715, -0.43478101341299474, -0.4132391820173579, -0.39018228701776025, -0.3660104137319765, -0.34113355714281846, -0.31596221499707855, -0.29089810399889005, -0.26632522052439656, -0.2426014573683169, -0.22005097297973145, -0.19895748984177766, -0.17955867460183644, -0.162041724873203, -0.14654025700262188, -0.13313255629825638, -0.12184121705946774, -0.1126341650948045, -0.1054270211199262, -0.10008673034390048, -0.0964363524995639, -0.09426087831815595, -0.09331391368558449, -0.09332505205432869, -0.0940077396244328, -0.09506742673668142, -0.09620979310286694, -0.09714883406228554, -0.09761459999556776, -0.09736039120750864, -0.0961692257395452, -0.0938594172958358, -0.09028912425630502, -0.08535975799614443, -0.07901816873883089, -0.07125755917501488, -0.062117109269746854, -0.05168032921363581, -0.04007219050013681, -0.02745511679520339, -0.014023945805484562, -1.3268046304600178e-16], [0.0, 0.015439226634623365, 0.030858895441867058, 0.045982763434863294, 0.06054188271386864, 0.07428267025398869, 0.08697457602738982, 0.09841714213753386, 0.1084462611784768, 0.11693946251338591, 0.12382008007800126, 0.12906018402969024, 0.1326821903576054, 0.13475909664263414, 0.13541332764751007, 0.13481421043115607, 0.13317413430629937, 0.13074348529345237, 0.12780447689641294, 0.1246640282164387, 0.12164586588958101, 0.11908204742195835, 0.11730411966723361, 0.11663413701782444, 0.11737576907803803, 0.11980572700540403, 0.12416573134229521, 0.1306552321543756, 0.13942507492766484, 0.15057228336867706, 0.16413610354304453, 0.18009542332913245, 0.1983676477011332, 0.2188090747142571, 0.24121678012224398, 0.2653319812282451, 0.29084481377954263, 0.3174004203787667, 0.34460621587939766, 0.3720401653857462, 0.3992598845352613, 0.4258123503568423, 0.45124399471447396, 0.47511094157767325, 0.4969891443902535, 0.5164841807756655, 0.5332404687132802, 0.5469496809920562, 0.5573581529000681, 0.5642731013090408, 0.5675675010060722, 0.5671834956426302, 0.5631342552511753, 0.5555042290837171, 0.5444477806598944, 0.5301862304468503, 0.5130033695904362, 0.493239544650713, 0.4712844474729272, 0.44756877531390904, 0.42255495338651033, 0.39672713442094587, 0.37058070712390967, 0.3446115571223919, 0.31930532982390314, 0.2951269444664968, 0.27251060247570336, 0.2518505212431502, 0.2334926068882738, 0.21772725689082434, 0.20478345624373087, 0.19482429964055106, 0.18794403794141015, 0.18416671059431544, 0.1834463877188038, 0.18566900711320838, 0.19065575346316857, 0.1981678904325572, 0.20791292199867673, 0.21955192818408437, 0.2327078929927953, 0.24697481953777028, 0.26192740959603145, 0.2771310725683908, 0.29215202233754234, 0.306567219953419, 0.3199739254243531, 0.33199863300703025, 0.3423051809759669, 0.35060184848819537, 0.3566472782912675, 0.36025509399282546, 0.3612971136646726, 0.35970509686565433, 0.3554709988538861, 0.3486457429060064, 0.33933655834593435, 0.32770296719840136, 0.31395153544979315, 0.298329534904906, 0.2811176878354227, 0.26262218838280105, 0.24316621147552064, 0.2230811314439711, 0.2026976782964003, 0.1823372596285599, 0.162303670394697, 0.14287540142902572, 0.12429874097518151, 0.10678184198880335, 0.09048990217890353, 0.0755415743077136, 0.06200669192743829, 0.0499053613186582, 0.039208434782794455, 0.029839344532982426, 0.02167724113328188, 0.014561346648364067, 0.008296401239058008, 0.0026590536676753254, -0.002594978224775219, -0.007723170922974466, -0.012988091302884253, -0.018649143697279467, -0.02495439024993263, -0.03213266508713773, -0.040386195408267336, -0.049883929688963255, -0.060755755125418934, -0.07308776368016044, -0.08691869919172, -0.10223768765996832, -0.11898331978056442, -0.13704411990931412, -0.15626039977109335, -0.17642745929487577, -0.1973000618655934, -0.21859807792449046, -0.2400131600695458, -0.26121628539021663, -0.28186597741689257, -0.301617001375052, -0.32012931289122126, -0.33707703225857494, -0.3521572140531976, -0.3650981853737833, -0.3756672351890906, -0.3836774520065776, -0.3889935269719319, -0.39153636409238374, -0.39128636794860805, -0.3882853113191851, -0.3826367198005561, -0.37450474691026503, -0.3641115504126655, -0.35173321778180416, -0.3376943248931697, -0.32236124631453394, -0.30613436709119646, -0.2894393739040353, -0.27271782721717086, -0.2564172349266583, -0.24098086159170726, -0.22683751522534976, -0.21439155563154483, -0.20401336433433226, -0.19603050633248842, -0.19071979845560946, -0.18830047835932157, -0.18892864267381337, -0.19269309312478472, -0.1996126962964606, -0.20963532690555456, -0.2226384268722099, -0.23843117402291003, -0.2567582158774506, -0.2773048865927408, -0.2997037896722105, -0.3235425963663936, -0.3483728805857417, -0.37371978633159036, -0.39909230373135435, -0.4239939152258202, -0.4479333646542892, -0.47043529913174653, -0.4910505367795242, -0.5093657224784978, -0.5250121486374536, -0.5376735381449117, -0.5470926117056246, -0.5530762910395898, -0.5554994222249633, -0.55430693899384, -0.5495144231728499, -0.541207057785602, -0.5295370066658077, -0.5147192918341189, -0.49702627545792927, -0.4767808860776555, -0.4543487581489985, -0.4301294791092837, -0.40454715852255435, -0.3780405489075395, -0.3510529572509033, -0.3240221897410353, -0.29737076985575683, -0.2714966616777288, -0.24676471641532238, -0.22349904093421294, -0.20197646314549356, -0.1824212409562038, -0.16500112987662946, -0.14982489008845498, -0.13694127766643693, -0.126339527614325, -0.11795129934480977, -0.11165401912264555, -0.10727551969409871, -0.10459984569177763, -0.10337406521078586, -0.10331590389167544, -0.10412199850508344, -0.10547655288045302, -0.10706017039465801, -0.10855863433479196, -0.1096714103285068, -0.11011965360605168, -0.10965351788934849, -0.10805858182740478, -0.10516123261961137, -0.1008328741799177, -0.09499285818738276, -0.08761006985267743, -0.07870313535473118, -0.06833925377575767, -0.056631692077355265, -0.0437360163112458, -0.029845164969027803, -0.015183500319209979, -1.430731748338501e-16], [0.0, 0.01646040726991909, 0.032767589840943544, 0.04863045721512221, 0.06377035696368007, 0.07792945880661209, 0.0908785842854607, 0.10242426995944692, 0.11241487169990623, 0.12074554227022717, 0.12736194333821835, 0.13226258564510784, 0.13549972642857933, 0.13717879047358242, 0.1374563194025041, 0.1365364920487609, 0.1346662960170025, 0.13212946587411342, 0.1292393359400982, 0.1263307845281585, 0.12375147098038906, 0.12185258632986716, 0.12097935238640871, 0.12146151212425002, 0.12360405622444556, 0.12767842642438462, 0.13391442603741838, 0.14249305186550132, 0.1535404401220383, 0.1671230924331822, 0.1832445171405342, 0.20184338674205066, 0.22279327522637166, 0.24590400019323344, 0.27092455496997336, 0.2975475764148653, 0.32541525572377844, 0.35412656328293424, 0.38324562534287016, 0.4123110608601777, 0.44084606200400517, 0.4683689821818013, 0.49440418150404536, 0.5184928717414422, 0.5402037012418116, 0.5591428250247424, 0.5749632162607965, 0.5873729923156509, 0.5961425510971002, 0.6011103410453449, 0.6021871200904145, 0.5993585944922889, 0.592686366816742, 0.5823071624521505, 0.5684303450626591, 0.5513337722028167, 0.5313580819924816, 0.508899539300435, 0.484401604393801, 0.45834541763518466, 0.4312394198019974, 0.40360834832757053, 0.37598186471482054, 0.34888307718523637, 0.3228172250837372, 0.2982607876040676, 0.27565126912736193, 0.25537789713040954, 0.23777344662047178, 0.2231073779291402, 0.21158044311279284, 0.2033208809345636, 0.19838228230500587, 0.19674316806682268, 0.19830828009970292, 0.20291154589240817, 0.21032063697560568, 0.22024300389770973, 0.23233323567290415, 0.24620156067735005, 0.2614232795634983, 0.27754889953767403, 0.2941147238084349, 0.31065364052770994, 0.326705852328755, 0.34182929067527834, 0.35560946857933207, 0.36766854057295884, 0.3776733597342762, 0.3853423475396807, 0.39045102268351134, 0.39283606901084783, 0.39239785949602096, 0.3891013918497455, 0.38297563088840664, 0.37411129226665074, 0.36265714058006954, 0.34881491123808944, 0.3328329989899648, 0.3149990857352773, 0.2956319055355584, 0.2750723649493511, 0.25367425145096534, 0.23179477141500243, 0.20978516175446565, 0.18798161574324165, 0.16669675394126834, 0.14621185573149417, 0.12677004617509957, 0.10857060723302406, 0.09176455254616875, 0.07645157167638082, 0.06267841383322646, 0.05043874355914633, 0.03967446257023529, 0.030278453921030346, 0.022098667841534782, 0.014943433914047, 0.008587852592444198, 0.0027810912170164823, -0.0027456136531554443, -0.008270463991984528, -0.01407234720028225, -0.02042205796884932, -0.02757373164848988, -0.03575672029829299, -0.04516813127456879, -0.05596623125561479, -0.06826489639901458, -0.08212926245743568, -0.09757269781300353, -0.11455518830746236, -0.13298318630542058, -0.15271093855109413, -0.17354326902234432, -0.19523975511995792, -0.21752019911439566, -0.24007126273092919, -0.2625541019532066, -0.2846128123507736, -0.30588347317415426, -0.32600356168097666, -0.34462149809597853, -0.36140607656191204, -0.3760555385524647, -0.38830605248367484, -0.3979393765143255, -0.40478950045576995, -0.4087480868625216, -0.40976856016022606, -0.4078687253839952, -0.40313183394459573, -0.39570605192992814, -0.3858023258440659, -0.3736906804106147, -0.3596950221356969, -0.3441865597668326, -0.32757598766402124, -0.31030460954633915, -0.29283460730248273, -0.27563868187076435, -0.25918931003695667, -0.24394787193497794, -0.23035390877867884, -0.21881476876825576, -0.2096958912230783, -0.20331196497066445, -0.19991917719715335, -0.1997087438092191, -0.20280188247439943, -0.20924635561673502, -0.21901467356760607, -0.23200400870719337, -0.24803783073698238, -0.2668692321887586, -0.28818587290074893, -0.31161643346171886, -0.33673843148438, -0.3630872219029957, -0.39016597409470416, -0.4174563951937369, -0.44442995107499716, -0.4705593245656803, -0.4953298447916139, -0.5182506223166937, -0.5388651318698466, -0.5567609977992071, -0.5715787566202513, -0.5830193956623728, -0.5908504962634776, -0.5949108434937964, -0.5951134011881535, -0.5914465902306405, -0.5839738486103845, -0.5728314927615273, -0.5582249401151691, -0.5404233916418881, -0.5197531095061336, -0.49658945790686576, -0.471347903945342, -0.4444741992481483, -0.416433981509593, -0.387702047665787, -0.35875155678197984, -0.33004342078651006, -0.30201613493649404, -0.27507628752476254, -0.2495899701578158, -0.2258752864166567, -0.20419612845301235, -0.18475735878508726, -0.16770149905031026, -0.15310698963584957, -0.14098804488512748, -0.13129608894634662, -0.12392271827138844, -0.1187040992580322, -0.11542667448236872, -0.11383401925525617, -0.11363466263545968, -0.11451066421741113, -0.11612672053727914, -0.11813956322684717, -0.12020740536551486, -0.12199919296028709, -0.12320342509145775, -0.12353631881416924, -0.12274911307114052, -0.12063432917755887, -0.11703083328550899, -0.11182757790946907, -0.10496593428861159, -0.09644056419351367, -0.08629881781948494, -0.0746386826821694, -0.061605345974497634, -0.04738646870798312, -0.03220630323939758, -0.016318815635505635, -1.5315252351621846e-16], [0.0, 0.01743030352424802, 0.03455874735733887, 0.051082396906054005, 0.06671635918487216, 0.08120237789224104, 0.09431671085399203, 0.10587707605093302, 0.11574847640222231, 0.12384774233722402, 0.13014666422827403, 0.13467362314150008, 0.1375136671739593, 0.13880702090237076, 0.13874605615370372, 0.13757079239097314, 0.1355630334727895, 0.133039283415819, 0.13034261615243622, 0.1278337023053195, 0.12588121897784046, 0.12485188589071365, 0.12510038242890423, 0.12695940499770964, 0.13073012238240847, 0.13667327858456432, 0.1450011780557312, 0.155870767710417, 0.1693780040695063, 0.18555366299597115, 0.20436071449226642, 0.2256933467930237, 0.24937768344995814, 0.2751741952702069, 0.3027817668711244, 0.331843336299309, 0.3619529866576812, 0.39266433197753897, 0.4235000065813028, 0.45396203873468277, 0.48354286620215964, 0.5117367339861448, 0.5380512034937514, 0.5620184979268844, 0.5832064109602669, 0.6012285147216471, 0.6157534185173656, 0.6265128512933913, 0.6333083679741408, 0.6360165119273915, 0.6345923020889177, 0.6290709528668278, 0.6195677768721941, 0.6062762637699997, 0.5894643720594896, 0.569469113314827, 0.5466895493028812, 0.5215783604466078, 0.49463217838984647, 0.4663809051042837, 0.43737626533571683, 0.408179857618767, 0.37935098114577914, 0.35143452116180407, 0.32494917414145247, 0.30037628581978093, 0.278149560398584, 0.25864587829255814, 0.24217743312969364, 0.22898536702889172, 0.2192350472203171, 0.21301308772937425, 0.2103261780747644, 0.2111017377546982, 0.21519037176635308, 0.2223700595828907, 0.23235196894200977, 0.24478774747804527, 0.25927811058518374, 0.27538251376997713, 0.2926296728623379, 0.3105286764010515, 0.32858042174345364, 0.34628910026491544, 0.3631734575451042, 0.3787775616521644, 0.3926808263357994, 0.4045070557691453, 0.4139323029302749, 0.420691364142383, 0.4245827669309424, 0.42547214633767866, 0.42329394520571995, 0.4180514157112274, 0.40981494152566644, 0.3987187414048674, 0.38495605469101085, 0.3687729462017029, 0.35046090135571867, 0.33034841132908005, 0.3087917718413113, 0.28616533726286303, 0.2628514836774949, 0.23923054004874417, 0.2156709456094152, 0.19251988406304357, 0.17009463136455039, 0.14867483409889537, 0.12849591031425942, 0.10974373473752853, 0.09255073637054323, 0.07699349940060829, 0.06309191910050208, 0.0508099239377808, 0.040057734485391065, 0.030695589953456733, 0.022538835250968822, 0.015364226393488755, 0.008917280684727151, 0.0029204712078719705, -0.002917956554973377, -0.008894784152349433, -0.015302483689334812, -0.022419996993290434, -0.030503878996955114, -0.039780044562878016, -0.050436342467814824, -0.0626161589992776, -0.076413227124994, -0.09186778614758145, -0.1089642019345358, -0.12763012009649494, -0.14773718482722586, -0.16910331551925034, -0.19149649275656228, -0.21463996588668469, -0.2382187570878157, -0.2618873026208024, -0.2852780416624627, -0.30801073753117836, -0.3297022958957384, -0.34997683022865067, -0.3684757167032651, -0.3848673791615483, -0.39885654975543694, -0.41019276228492124, -0.41867785285443937, -0.42417226582485906, -0.4265999915856672, -0.4259519957144347, -0.42228803581802665, -0.4157368018584938, -0.40649435708090553, -0.39482089875820764, -0.38103589980526875, -0.3655117328505162, -0.34866591657869644, -0.33095215911724346, -0.3128504040550888, -0.29485611058090183, -0.2774690195520814, -0.2611816715372563, -0.2464679506439319, -0.23377192903854688, -0.2234972814422063, -0.21599752666092176, -0.21156733466654568, -0.21043511332213055, -0.21275705912697576, -0.21861282205739396, -0.22800289652810155, -0.2408478096185217, -0.2569891349913072, -0.2761923174166107, -0.2981512495652867, -0.32249450080240116, -0.3487930581227442, -0.37656940308972786, -0.4053077165548794, -0.43446497583168764, -0.46348268753782723, -0.4917989840288228, -0.5188608025982855, -0.5441358646288701, -0.5671241766929994, -0.5873687871050157, -0.6044655493353664, -0.6180716675742772, -0.6279128289929078, -0.6337887611784795, -0.6355770909866529, -0.6332354217365804, -0.6268015882778182, -0.6163920929439273, -0.6021987687147071, -0.5844837579828542, -0.5635729351381931, -0.5398479377769368, -0.5137370038286747, -0.4857048394860717, -0.45624176485926443, -0.4258524002337059, -0.3950441653125143, -0.3643158666572193, -0.3341466446537605, -0.3049855408389887, -0.2772419296045023, -0.25127703558253855, -0.22739672999060476, -0.20584576657533768, -0.1868035813716392, -0.17038174119245472, -0.1566230845685508, -0.14550255679209514, -0.13692969882756914, -0.13075270917678689, -0.12676395932721732, -0.12470680812261199, -0.12428352913954108, -0.125164138697828, -0.12699589112088017, -0.12941319280031155, -0.1320476778653712, -0.13453818601067133, -0.13654038733183094, -0.13773580973061378, -0.1378400412914051, -0.13660990255917704, -0.13384941128342107, -0.1294143942240539, -0.12321563622599614, -0.11522049505251522, -0.10545295045125244, -0.09399209659741599, -0.08096912738631915, -0.06656290301238964, -0.050994222889445634, -0.034518963312838116, -0.0174202674965419, -1.6283188284955877e-16], [0.0, 0.018340580423799067, 0.03621724354815391, 0.05331860236640315, 0.06935731028653552, 0.0840787536242466, 0.09726885484471331, 0.10876077431728871, 0.11844032675198854, 0.126249961649759, 0.13219119418285039, 0.13632541299059653, 0.13877303341700403, 0.13971100766669384, 0.13936874612783534, 0.1380225456209266, 0.13598865952716072, 0.13361518063302513, 0.13127293918386365, 0.12934564525833134, 0.12821952547308518, 0.12827271866022377, 0.1298647031425952, 0.13332602934386245, 0.13894862566255176, 0.14697693293681935, 0.157600103724207, 0.17094547747626235, 0.1870735121115626, 0.20597431722938606, 0.22756589512556655, 0.2516941538346864, 0.27813471266479767, 0.3065964761961352, 0.3367269085883915, 0.36811889738010534, 0.4003190558326601, 0.4328372762740647, 0.46515731475246314, 0.49674816042626635, 0.5270759221785073, 0.5556159504834056, 0.5818649049500657, 0.6053524774299619, 0.6256524871354845, 0.6423930777355225, 0.6552657665579416, 0.6640331223608444, 0.6685348800047518, 0.6686923369990943, 0.664510917422777, 0.6560808321474109, 0.6435758095676024, 0.6272499170633248, 0.6074325390629414, 0.5845216217281207, 0.5589753358651383, 0.531302347664568, 0.5020509203536189, 0.47179709799308034, 0.4411322447747132, 0.41065022873302615, 0.38093454739621146, 0.35254569435322564, 0.32600905997131735, 0.3018036467006532, 0.2803518598626768, 0.2620106090139574, 0.24706392353835732, 0.23571724981571146, 0.22809355703201115, 0.22423133541822432, 0.22408452548890972, 0.22752437080074486, 0.23434314098745263, 0.2442596274655573, 0.25692627232345616, 0.27193775252074476, 0.2888408075647343, 0.30714507011577397, 0.32633463619144454, 0.34588009533410996, 0.3652507316587626, 0.3839266043213695, 0.40141022068031007, 0.4172375271283244, 0.43098796094137287, 0.4422933310520653, 0.45084532578522113, 0.4564014805318719, 0.4587894772087441, 0.45790968918079855, 0.4537359290715778, 0.4463144014616623, 0.43576090677313295, 0.42225638556073314, 0.4060409329181215, 0.38740644976287264, 0.3666881304769007, 0.34425501394998637, 0.3204998468331197, 0.29582852323162206, 0.27064937379083615, 0.24536257895276492, 0.22034997606616716, 0.19596551816409896, 0.1725266238994025, 0.15030663382883946, 0.12952855858780984, 0.11036027026003892, 0.09291125029428572, 0.0772309666186947, 0.06330891018616196, 0.051076278125928645, 0.04040924806712081, 0.031133747116144157, 0.023031580449236245, 0.015847749496032196, 0.009298759121973851, 0.003081687837133728, -0.003116224494186718, -0.009607730202672426, -0.01669573396347764, -0.024663724652031815, -0.033766736966208855, -0.04422308719652765, -0.05620710756073217, -0.0698430777707812, -0.08520052161882243, -0.10229100113363351, -0.12106650216001369, -0.14141946402826572, -0.16318446335031495, -0.18614151898163192, -0.21002094291280418, -0.23450962137339124, -0.25925857277183134, -0.28389159521742313, -0.3080147871389804, -0.33122670067945037, -0.353128869722252, -0.3733364430592229, -0.3914886486460634, -0.4072588172440023, -0.4203637029779232, -0.43057185424104927, -0.43771081056690764, -0.44167292903497085, -0.4424196767965853, -0.4399842635937196, -0.43447252877776166, -0.4260620403165248, -0.414999407541523, -0.4015958538368493, -0.38622113900086374, -0.36929596253795305, -0.35128301762264164, -0.33267689995834676, -0.31399310536102243, -0.2957563738857462, -0.2784886560712418, -0.2626969879456055, -0.24886156552257593, -0.23742430649997884, -0.22877817680404558, -0.22325754273260098, -0.22112978613283074, -0.22258839086069884, -0.22774767440971022, -0.23663929989579083, -0.24921066147967666, -0.2653251918206175, -0.2847645943675331, -0.30723295732151834, -0.33236266106800344, -0.3597219478776169, -0.388823982762424, -0.4191371985247491, -0.45009668712629003, -0.4811163742923482, -0.5116016953672444, -0.5409624783154896, -0.5686257347164654, -0.5940480617522631, -0.616727367487192, -0.6362136479560784, -0.6521185673207521, -0.6641236210640802, -0.6719866961668436, -0.675546880624386, -0.6747274165687972, -0.6695367356451493, -0.6600675610637364, -0.6464941067982696, -0.629067449600693, -0.6081091927570291, -0.5840035807647673, -0.5571882603950469, -0.5281439150354543, -0.49738302503517695, -0.46543802637608267, -0.43284915290735104, -0.4001522533093882, -0.36786687276895974, -0.33648488110106517, -0.30645991396737526, -0.27819787230733506, -0.2520486976657397, -0.2282996084636455, -0.2071699452388376, -0.18880773240502466, -0.17328802115640884, -0.16061303384525843, -0.15071408558536434, -0.14345521508874662, -0.1386384149086718, -0.13601031237095884, -0.13527011748418846, -0.1360786238852674, -0.13806802413695374, -0.14085228204714711, -0.14403779257156438, -0.14723405457347202, -0.15006408335720417, -0.1521742984037942, -0.15324363688317505, -0.1529916648985704, -0.15118548548022642, -0.14764527439146832, -0.142248311020631, -0.13493141108488438, -0.12569170956375747, -0.11458578515386493, -0.1017271605062615, -0.08728225448733422, -0.07146490263258533, -0.05452959883215831, -0.03676364416749064, -0.018478416881187936, -1.720277353083025e-16], [0.0, 0.019183500924352698, 0.037729401775357656, 0.05532160480166197, 0.07167437339113232, 0.08654099948706827, 0.09972140402885976, 0.11106846317323003, 0.12049288598301686, 0.1279665067213171, 0.13352389591345787, 0.13726223790070025, 0.1393394676061349, 0.13997070452605687, 0.13942306640173294, 0.13800898748953697, 0.13607820575293278, 0.13400861864415725, 0.1321962375237609, 0.13104449540277885, 0.13095318094857658, 0.13230728309373513, 0.135466034821263, 0.14075244164156153, 0.1484435699819651, 0.15876185341470425, 0.1718676507658088, 0.1878532602534317, 0.2067385586284058, 0.2284683946951371, 0.25291182355193637, 0.27986322246946893, 0.30904528264873427, 0.340113824324369, 0.3726643369686467, 0.4062401028461332, 0.4403417219561106, 0.47443782048801014, 0.5079766942081496, 0.5403986134710355, 0.5711484984359806, 0.5996886620380492, 0.6255113146056146, 0.6481505278476898, 0.6671933671804947, 0.682289919769352, 0.6931619707965724, 0.6996101117296798, 0.7015191010062412, 0.6988613386871664, 0.6916983612631584, 0.6801803098450329, 0.6645433732830657, 0.6451052561658773, 0.6222587689644004, 0.5964636826554846, 0.568237031880721, 0.5381420880484108, 0.5067762558555926, 0.47475817270705545, 0.44271430980168447, 0.41126538576977717, 0.381012908380178, 0.35252615687830297, 0.32632990703629267, 0.30289318324972403, 0.28261929743447456, 0.2658374036625511, 0.25279576117954344, 0.2436568575551732, 0.23849449923060967, 0.23729292972759444, 0.23994798742143747, 0.24627026623148007, 0.25599019503094866, 0.2687649061797918, 0.284186721441523, 0.3017930456793988, 0.3210774260532862, 0.34150150774233495, 0.3625075971381159, 0.3835315304626997, 0.4040155401655665, 0.4234208133594356, 0.4412394459001955, 0.45700551224933056, 0.4703049945511273, 0.4807843438182874, 0.48815748100432665, 0.49221108517286866, 0.492808058965922, 0.4898891070528331, 0.4834724100771176, 0.4736514236470743, 0.46059087797308906, 0.4445210977017721, 0.4257308022513533, 0.4045585835127302, 0.38138328925132897, 0.35661356616018325, 0.3306768356555672, 0.3040079877168279, 0.2770380830693318, 0.25018335169167527, 0.22383476607631742, 0.19834845114805957, 0.17403716968241104, 0.15116309306377426, 0.12993203302706355, 0.11048927151002824, 0.09291708388835919, 0.07723400673479829, 0.0633958559557387, 0.05129845586045519, 0.04078199555413567, 0.031636887131441936, 0.02361096153980975, 0.01641780365422356, 0.009745998922439563, 0.0032690406360510087, -0.0033443699555952867, -0.010419908421906151, -0.018267377364227563, -0.027170898218272673, -0.03737980931026113, -0.049100516539767686, -0.06248951842993198, -0.07764779693489206, -0.09461673009183202, -0.1133756432427616, -0.13384107312386123, -0.15586777470056706, -0.17925145533836348, -0.20373317588923723, -0.22900531468290336, -0.2547189493469337, -0.2804924738853249, -0.30592123547712063, -0.33058794785939843, -0.3540736166425998, -0.3759686970297287, -0.3958841965677031, -0.41346243496663965, -0.42838717971751283, -0.440392890074228, -0.4492728226175671, -0.4548857785893246, -0.4571613058198705, -0.4561032055730783, -0.4517912360774853, -0.4443809488797726, -0.4341016403490037, -0.42125244753246127, -0.4061966639517335, -0.38935439567564634, -0.3711937199975566, -0.35222054722710655, -0.3329674195217126, -0.3139815084875957, -0.2958120947681286, -0.27899782745745905, -0.2640540685473502, -0.251460627530843, -0.2416501837273848, -0.234997679024661, -0.231810941897215, -0.2323227752782589, -0.23668470680581333, -0.2449625609576406, -0.25713396957481904, -0.27308789129463806, -0.29262616258765384, -0.31546705458595453, -0.3412507618829934, -0.36954670315174526, -0.399862469899903, -0.4316542200228157, -0.46433827799767796, -0.49730367443882484, -0.5299253350177371, -0.5615776129997834, -0.5916478512497568, -0.6195496587170652, -0.6447355931508537, -0.6667089559521643, -0.6850344262990997, -0.6993472894639421, -0.7093610478997817, -0.7148732423864312, -0.7157693533460159, -0.7120246983221963, -0.7037042894440435, -0.6909606632997634, -0.6740297438426263, -0.6532248455685051, -0.6289289681084251, -0.6015855735054421, -0.5716880728219934, -0.5397682784986034, -0.5063841023432124, -0.4721067956145485, -0.43750803698464635, -0.403147176016121, -0.36955893414436014, -0.337241852173211, -0.3066477533152903, -0.2781724643466687, -0.25214800517103475, -0.22883641981337807, -0.2084253805222747, -0.19102565228578744, -0.17667045876455037, -0.16531674356749254, -0.1568482741083795, -0.15108049013989208, -0.1477669565804656, -0.14660724147307655, -0.14725600579562118, -0.149333063212698, -0.15243414541314193, -0.15614209295579712, -0.16003818291819474, -0.16371330330187128, -0.1667786901045335, -0.1688759560514926, -0.16968615983734717, -0.16893769084556895, -0.16641277601469437, -0.16195245199272443, -0.15545988603557934, -0.14690197223556972, -0.1363091745174338, -0.12377363327649225, -0.10944559740660102, -0.09352828664126618, -0.07627132951982421, -0.05796295887353021, -0.03892117858195306, -0.019484141676221582, -1.8066086251924099e-16], [0.0, 0.01995204119647586, 0.03908320384362402, 0.05707672732948327, 0.0736527742643193, 0.0885769429308213, 0.10166753138165362, 0.11280135451678318, 0.12191795293846883, 0.12902207403668514, 0.1341843505487387, 0.13754014863089128, 0.1392866050925279, 0.13967792066870602, 0.13901902184720147, 0.1376577466623589, 0.13597574892867395, 0.13437834961557457, 0.13328359258483263, 0.1331107839890076, 0.13426880968947189, 0.1371445326972001, 0.14209157265522038, 0.1494197617458997, 0.15938555628818502, 0.17218366104638078, 0.18794009443885534, 0.20670688811402077, 0.22845857460241834, 0.2530905729358618, 0.28041953532886627, 0.31018566940229175, 0.342057001200434, 0.37563549563498766, 0.4104649041942064, 0.44604016595257373, 0.4818181482030214, 0.5172294784089032, 0.5516911905112835, 0.5846198866575157, 0.6154451007043922, 0.643622542779733, 0.6686469049584135, 0.6900639167274261, 0.707481355190684, 0.7205787385198601, 0.7291154614340286, 0.7329371677633131, 0.7319801965460113, 0.7262739836232726, 0.7159413492257749, 0.7011966524126777, 0.682341844197242, 0.659760501532269, 0.6339099728021772, 0.6053118108919684, 0.574540711164712, 0.5422122077680034, 0.508969411721297, 0.4754690974733011, 0.4423674604908199, 0.4103058765567646, 0.3798969936145537, 0.3517114791925411, 0.32626573086415755, 0.3040108342261304, 0.28532302306849594, 0.2704958604932915, 0.2597343185903471, 0.25315088890261833, 0.250763807417172, 0.2524974273840342, 0.2581847221230004, 0.26757184937380185, 0.2803246599089589, 0.2960369872477846, 0.3142405134970434, 0.33441596961021797, 0.3560053975887227, 0.3784251780825118, 0.40107951005644576, 0.42337402006493835, 0.44472917742405166, 0.46459319819679623, 0.48245413522928643, 0.49785087311905535, 0.5103827754089069, 0.5197177657612011, 0.5255986645117394, 0.527847645836627, 0.5263687276955498, 0.5211482555725792, 0.5122533906076414, 0.4998286617699433, 0.48409068905623914, 0.4653212291347783, 0.44385873530741765, 0.42008865913662047, 0.39443275071564177, 0.3673376376311877, 0.3392629786251934, 0.3106694964313589, 0.28200719505558774, 0.2537040598920981, 0.2261555247148213, 0.19971496813929931, 0.1746854741725331, 0.15131305767850933, 0.12978151685098344, 0.1102090320903292, 0.09264658511342148, 0.07707822484029302, 0.0634231587958877, 0.05153960164812463, 0.041230267264354005, 0.032249348448156114, 0.024310790381237644, 0.017097630701032256, 0.010272151925995605, 0.0034865712814072286, -0.0036060206028898016, -0.01134076681511019, -0.020030490390040373, -0.02995576398959549, -0.0413558711372857, -0.05442090397105486, -0.06928521303395803, -0.08602238961420987, -0.10464192146037114, -0.1250876193372347, -0.14723786594998406, -0.17090769141073062, -0.19585263185164056, -0.2217742812081525, -0.24832740178627677, -0.27512841811852945, -0.3017650818509263, -0.3278070639281267, -0.3528172049632978, -0.37636313604972177, -0.3980289708804273, -0.4174267661972651, -0.4342074514101277, -0.4480709396370695, -0.4587751511530291, -0.46614370585106624, -0.47007207319473715, -0.47053200549496044, -0.46757412226239353, -0.4613285588339274, -0.45200364032603974, -0.43988259104252136, -0.4253183385404673, -0.4087265194145702, -0.3905768393013322, -0.3713829814947809, -0.3516912958521205, -0.3320685314119023, -0.31308890154432334, -0.2953207888543305, -0.2793134079861678, -0.2655837476396159, -0.2546041084014667, -0.24679054051300073, -0.24249246571982344, -0.24198374035399015, -0.2454553834237003, -0.2530101545349563, -0.2646591228831072, -0.280320321386477, -0.299819530435226, -0.32289318490371116, -0.3491933472630808, -0.37829464007325764, -0.40970298404086236, -0.44286594435425136, -0.4771844492129253, -0.5120256113068601, -0.5467363562850582, -0.5806575426377327, -0.6131382453853512, -0.6435498718170479, -0.6712997813547043, -0.69584409334557, -0.7166993859212107, -0.7334530155325598, -0.7457718197345491, -0.7534090044447569, -0.7562090602955309, -0.7541105997792396, -0.7471470565030827, -0.7354452388135632, -0.7192217810798588, -0.6987775857977772, -0.6744903971790294, -0.646805690871068, -0.6162261038453521, -0.5832996623451018, -0.5486070932833402, -0.5127485249712638, -0.47632989605209397, -0.43994939671767996, -0.40418426358772397, -0.36957823912243537, -0.3366299883986082, -0.30578274097155933, -0.27741539400922494, -0.25183527571522024, -0.2292727261875587, -0.2098776073357584, -0.1937178054358006, -0.18077974053444348, -0.170970847446193, -0.1641239447421194, -0.16000336210318555, -0.15831265383527532, -0.15870368826376965, -0.16078687007334547, -0.16414222622773392, -0.1683310665318885, -0.17290791765070657, -0.17743242475585264, -0.18148091802692823, -0.18465735188443635, -0.1866033427895021, -0.18700705623692265, -0.18561072455158567, -0.18221661347774343, -0.17669129639635045, -0.1689681392778232, -0.15904794605193603, -0.1469977617730195, -0.1329478785705701, -0.1170871356999018, -0.09965664887561757, -0.08094214437650021, -0.061265109138696254, -0.04097299830569517, -0.020428765718055908, -1.8865749344801865e-16], [0.0, 0.020639998083506333, 0.0402684817766162, 0.05857233294088259, 0.07528207329074252, 0.09018008624059803, 0.10310740795873044, 0.11396890121300997, 0.122736667532053, 0.12945159891003752, 0.13422301859730348, 0.1372264102191087, 0.13869928429255032, 0.13893527990340188, 0.13827664562445915, 0.13710528652719958, 0.13583260226925759, 0.1348883737566837, 0.1347089819472098, 0.13572526130452245, 0.1383503017373951, 0.14296751625537354, 0.14991928693675324, 0.15949648922825613, 0.1719291743716387, 0.18737866236508538, 0.20593126398152103, 0.22759381081070057, 0.2522911280393285, 0.27986553682521675, 0.3100784228416601, 0.34261385611395895, 0.37708419592054127, 0.413037564566031, 0.4499670265008813, 0.48732126574736745, 0.5245165159881418, 0.56094946495517, 0.5960108287538752, 0.6290992731353291, 0.6596353479726622, 0.6870750985972102, 0.7109230232949292, 0.7307440600403755, 0.7461743071390805, 0.7569302113510383, 0.7628159925885487, 0.7637291155668493, 0.7596636648382622, 0.7507115293435034, 0.7370613547591767, 0.7189952752383602, 0.6968834893309072, 0.6711767966325025, 0.6423972607807605, 0.6111272095917354, 0.5779968233041607, 0.5436705960864674, 0.5088329833236703, 0.4741735670650763, 0.44037208388999094, 0.4080836630432835, 0.377924617914504, 0.350459120896978, 0.3261870706827975, 0.30553343263625665, 0.2888392977343144, 0.27635486452515695, 0.26823450263578175, 0.2645340066766196, 0.26521009715703614, 0.2701221715132021, 0.2790362548627702, 0.29163104794071193, 0.3075059201054757, 0.3261906495372484, 0.3471566718889641, 0.3698295636824483, 0.3936024585074775, 0.4178500732547789, 0.4419430086863938, 0.46526198391481793, 0.4872116679203447, 0.5072337829745863, 0.5248191744464908, 0.5395185684415897, 0.5509517723813733, 0.558815113120028, 0.5628869515305717, 0.5630311605644873, 0.5591985044012252, 0.5514259081991637, 0.5398336598516946, 0.5246206357578513, 0.5060576906879921, 0.4844793961788297, 0.4602743514408479, 0.43387432453895636, 0.4057425087938047, 0.3763611992919437, 0.34621920661529865, 0.3157993291246716, 0.28556620127879967, 0.25595482366198175, 0.22736006094989836, 0.20012736747563215, 0.17454496705359093, 0.15083767512541987, 0.1291625080947905, 0.10960617801636079, 0.09218452178357191, 0.0768438638617314, 0.06346426170380234, 0.05186453452664183, 0.04180893033726193, 0.033015244135552735, 0.02516416313796637, 0.017909583598180595, 0.010889619131014994, 0.0037380029933943974, -0.00390442302260115, -0.01237844233109575, -0.021995723134561992, -0.033028893226960565, -0.04570269813768762, -0.06018648258065676, -0.07658820083521849, -0.09495012203481065, -0.11524635237839566, -0.13738224912110233, -0.16119575203761324, -0.18646060812955076, -0.21289141593153746, -0.24015036811331528, -0.26785552638793486, -0.29559042215601444, -0.3229147408789134, -0.3493758187871141, -0.3745206579511719, -0.3979081505584731, -0.41912119585229274, -0.4377783938079296, -0.45354500825115407, -0.46614290857340146, -0.4753592230762062, -0.48105346770785024, -0.48316295078891813, -0.4817062963571345, -0.4767849749603329, -0.46858277994825187, -0.45736323833969666, -0.44346499690430347, -0.42729527491431957, -0.4093215238237134, -0.39006147969898103, -0.3700718354152322, -0.34993579540557845, -0.3302498052066897, -0.31160977042826343, -0.2945970945123533, -0.2797648713512495, -0.26762456730913203, -0.25863351745510516, -0.2531835430785779, -0.25159097223525767, -0.2540883127641038, -0.26081778869669253, -0.27182690717920094, -0.28706617500387016, -0.30638903276729323, -0.32955402178006576, -0.35622914543553313, -0.3859983341084688, -0.4183698720840675, -0.45278659775073665, -0.4886376454845904, -0.5252714603583568, -0.5620097859378461, -0.5981623017434483, -0.6330415710351563, -0.6659779518202174, -0.6963341245758852, -0.7235188991147452, -0.7469999800810231, -0.7663153953390586, -0.7810833233962797, -0.7910100942156789, -0.7958961813850323, -0.7956400515582549, -0.7902397881991016, -0.7797924596926827, -0.7644912555538155, -0.7446204674463612, -0.720548442745743, -0.6927186861884768, -0.661639328598585, -0.627871219710463, -0.5920149338045229, -0.5546970014760497, -0.5165556977845432, -0.47822672588543874, -0.44032913583230504, -0.4034518105631994, -0.3681408353604965, -0.33488804370770175, -0.3041210020554894, -0.2761946593208252, -0.25138484489896057, -0.22988375262015243, -0.2117974985869144, -0.1971457894143117, -0.18586368534103637, -0.1778053912712964, -0.17274995931668016, -0.17040874005231155, -0.17043437762157737, -0.17243110704843456, -0.17596608154166116, -0.1805814339411286, -0.18580676032755875, -0.19117170557159088, -0.19621833041525005, -0.2005129475377193, -0.20365712973556566, -0.20529761642843386, -0.2051348745837115, -0.20293010606781342, -0.19851053445819894, -0.19177284944315953, -0.18268473495002688, -0.17128445685945254, -0.1576785363257835, -0.1420375840638684, -0.12459041823579503, -0.10561663258551438, -0.08543782111677371, -0.06440769989288067, -0.042901394594110874, -0.021304183595991188, -1.9595039588423992e-16], [0.0, 0.02124208735188127, 0.04127708823094549, 0.059800036561435205, 0.07655638528449761, 0.0913497979746474, 0.10404832885259338, 0.1145888207502926, 0.12297939686312187, 0.12929997165315527, 0.1337007577926208, 0.13639879825247384, 0.13767260422400027, 0.13785502920251513, 0.13732455600014276, 0.13649521550711657, 0.1358053926146338, 0.13570580490947814, 0.13664696277323576, 0.1390664347678939, 0.14337624926007142, 0.14995076192781465, 0.15911530911633903, 0.17113594918170338, 0.18621056840816447, 0.2044615954241944, 0.22593052907127562, 0.25057444035554405, 0.27826456052785736, 0.3087870156944815, 0.34184571493883076, 0.3770673450623778, 0.4140083720719536, 0.4521638987741345, 0.49097818055607634, 0.5298565588231953, 0.5681785347012472, 0.6053116754273032, 0.6406260231208851, 0.673508660930266, 0.7033780852790987, 0.729698035276809, 0.7519904412718625, 0.7698471737773457, 0.7829403011341659, 0.7910305986541412, 0.7939740927788999, 0.7917264700169567, 0.7843452309610088, 0.7719895233129079, 0.7549176432494434, 0.7334822502968829, 0.708123395782466, 0.679359517554325, 0.6477766027192137, 0.6140157644378903, 0.5787595172543274, 0.5427170670732893, 0.5066089559629069, 0.47115141785183084, 0.43704080852095784, 0.4049384718739537, 0.3754563943391452, 0.34914398065165025, 0.32647625764002053, 0.30784377864377377, 0.29354446064498024, 0.28377754009654205, 0.27863978289575136, 0.27812403021588694, 0.2821201062805457, 0.2904180580000697, 0.30271364105393206, 0.3186159138428663, 0.3376567510408275, 0.35930204345416705, 0.38296431163238626, 0.40801642811749755, 0.4338061181476228, 0.4596708916403043, 0.48495305076807155, 0.5090144175902073, 0.5312504349940997, 0.5511033113885775, 0.5680739047352392, 0.5817320739623215, 0.5917252647602619, 0.5977851412316357, 0.5997321237492819, 0.5974777454474505, 0.5910247937378794, 0.5804652577679624, 0.565976156472961, 0.5478133734925179, 0.5263036734529232, 0.5018351177770412, 0.47484613620588123, 0.4458135416744088, 0.4152398003194012, 0.3836398846328544, 0.3515280457325018, 0.31940484023014276, 0.2877447382785499, 0.2569846223181268, 0.22751346127780228, 0.19966341315516123, 0.1737025708279371, 0.1498295226068589, 0.12816985153272292, 0.10877464695495828, 0.09162104978369492, 0.07661480030118302, 0.06359470587727332, 0.0523388966573758, 0.04257269152108478, 0.033977855497127375, 0.026202994398762523, 0.01887480360231688, 0.011609866353015579, 0.004026683285067569, -0.004242390672234273, -0.01353962302938022, -0.02417110409686978, -0.03639696195395585, -0.05042285653241544, -0.06639298404138361, -0.08438478371810881, -0.1044054946811769, -0.12639066260641113, -0.15020464525787644, -0.17564311387092194, -0.2024374953194999, -0.23026124922658783, -0.2587378259836299, -0.2874501072581355, -0.31595109111936504, -0.34377555040897595, -0.3704523662872105, -0.39551721968647807, -0.4185253122065649, -0.4390637850927521, -0.45676351044556257, -0.47130994260382175, -0.48245273939863004, -0.4900138921718558, -0.4938941393788832, -0.49407748037164173, -0.4906336525564339, -0.4837184853910224, -0.4735720973819537, -0.4605149560579464, -0.4449418744892932, -0.42731406995997984, -0.40814945957768484, -0.38801141269412975, -0.3674962198704187, -0.34721957175209933, -0.3278023677622926, -0.3098561932974918, -0.2939688146297706, -0.2806900426946137, -0.27051831029968143, -0.2638882921635941, -0.2611598739322756, -0.26260874547200586, -0.2684188560396984, -0.27867692528903726, -0.29336915554091275, -0.3123802385052422, -0.335494694959156, -0.3624005300960597, -0.39269513172288556, -0.4258932845561268, -0.46143712287057065, -0.4987077969369313, -0.5370385871940112, -0.5757291649557483, -0.6140606705174583, -0.6513112594863758, -0.6867717565139532, -0.7197610526406807, -0.7496408882553527, -0.7758296780823348, -0.7978150572937076, -0.8151648582473948, -0.8275362647371779, -0.834682934095242, -0.8364599259533544, -0.832826328763532, -0.8238455300285724, -0.8096831322606858, -0.790602572607478, -0.7669585584981046, -0.7391884832462805, -0.707802033049248, -0.6733692390926734, -0.6365072644902837, -0.5978662446879917, -0.5581145210555447, -0.5179236201770899, -0.4779533355431944, -0.4388372638599789, -0.40116913515913155, -0.3654902546583969, -0.33227834542965007, -0.30193804511254774, -0.27479326806677856, -0.2510815975325467, -0.23095082173533082, -0.21445767468690918, -0.20156878801994585, -0.19216380589567228, -0.18604056218478696, -0.1829221690430384, -0.18246581991593522, -0.18427306904082358, -0.18790131466859283, -0.19287618534663478, -0.19870450835947837, -0.2048875272922933, -0.21093403194078233, -0.21637306850466212, -0.22076591102595144, -0.2237169960154167, -0.22488355060065085, -0.22398367959321527, -0.22080271771037033, -0.2151976987567928, -0.20709984271418008, -0.19651501315530187, -0.18352214989091897, -0.1682697339465987, -0.15097039253481834, -0.13189379936133247, -0.1113580691834103, -0.08971988392536788, -0.06736361988955962, -0.044689770870207535, -0.022102979650572285, -2.0247989737671387e-16], [0.0, 0.021754031455992157, 0.04210304328881997, 0.06075487832776835, 0.07747454402596088, 0.09209143207469454, 0.10450474999733911, 0.11468701395862586, 0.12268550243959056, 0.12862162348688666, 0.13268820260340836, 0.1351447526272565, 0.13631083977101313, 0.13655771002139058, 0.13629838605796918, 0.13597648556723607, 0.13605404626320938, 0.1369986701938545, 0.1392703193074324, 0.1433081052657344, 0.14951741882239353, 0.158257737652034, 0.16983143645753707, 0.1844738998522977, 0.20234520747408136, 0.22352362279322313, 0.2480010730622387, 0.2756807589008132, 0.30637697932965796, 0.33981720296472423, 0.3756463599288577, 0.4134332732296899, 0.4526790942833979, 0.4928275562869144, 0.5332768125352926, 0.5733925857196925, 0.6125223197631551, 0.6500099987333443, 0.685211278508031, 0.7175085666540044, 0.7463256846940087, 0.7711417546394852, 0.7915039681975415, 0.8070389220383183, 0.8174622353440991, 0.8225862057694182, 0.8223253059613672, 0.8166993738083123, 0.8058344043651657, 0.7899609086114735, 0.769409862440241, 0.7446063271284794, 0.7160608785902932, 0.6843590355877089, 0.6501489254774357, 0.6141274688156121, 0.5770254001772329, 0.5395914709858233, 0.5025762002908142, 0.46671555077681737, 0.4327149095573283, 0.4012337464344783, 0.37287130645911765, 0.34815366918441276, 0.3275224745644301, 0.31132557579577563, 0.2998098335007291, 0.29311621462254656, 0.29127730449101946, 0.2942172830568052, 0.3017543576859834, 0.31360558657838206, 0.3293939702432227, 0.34865763490942075, 0.37086088256472693, 0.3954068386984432, 0.4216513918195884, 0.44891808932532445, 0.47651363300710553, 0.5037436049057004, 0.5299280506476294, 0.5544165528798507, 0.576602441808937, 0.595935812769182, 0.6119350516053776, 0.6241966066804788, 0.6324027905510403, 0.6363274436881685, 0.6358393458292398, 0.6309033163032505, 0.621579001597808, 0.6080174051199971, 0.5904552691473778, 0.5692074710136971, 0.5446576433482464, 0.5172472705189259, 0.4874635492853075, 0.45582633018092594, 0.422874476629641, 0.38915199077633983, 0.35519425820762435, 0.3215147581026589, 0.2885925710576887, 0.2568609942550607, 0.2266975433898517, 0.1984155836063265, 0.17225778858510868, 0.14839157896002123, 0.1269066396503348, 0.1078145617775874, 0.09105059996043115, 0.07647748133196983, 0.06389114997505917, 0.05302828094807548, 0.043575352922561546, 0.035179028809386795, 0.02745756060641874, 0.020012908888467292, 0.01244324952456031, 0.004355530792282806, -0.004622256704472732, -0.014829427005863358, -0.026561875983181105, -0.04006257766543989, -0.05551355679989639, -0.07302955629760322, -0.09265357413102418, -0.11435439564266382, -0.1380261953226519, -0.1634902282339825, -0.1904985767720148, -0.21873986472163728, -0.24784679898489814, -0.2774053512050871, -0.3069653480363028, -0.33605220111037554, -0.36417947680173945, -0.3908619824831956, -0.41562903071097473, -0.438037536081617, -0.45768460155736834, -0.4742192618332645, -0.4873530705711444, -0.49686924559409706, -0.5026301207580376, -0.5045826943486222, -0.5027621104803188, -0.4972929609493925, -0.4883883490519023, -0.47634671268001316, -0.46154646016667306, -0.444438527460118, -0.4255370178981509, -0.4054081347978873, -0.38465766104920684, -0.3639172777905125, -0.3438300450923417, -0.32503539058997133, -0.30815396659419025, -0.2937727419816757, -0.2824306919516899, -0.2746054365851068, -0.2707011583269203, -0.2710380995208328, -0.27584390464366304, -0.285247028793403, -0.29927238531790284, -0.3178393524105048, -0.34076220233393967, -0.3677529590322633, -0.3984266316654313, -0.43230871447487806, -0.46884478875911306, -0.5074120119439882, -0.5473322330185465, -0.5878864340968619, -0.6283301655299931, -0.667909617626862, -0.7058779562496287, -0.7415115427203923, -0.7741256607838843, -0.8030893847645542, -0.8278392432621832, -0.8478913612585751, -0.8628517996659425, -0.8724248542551322, -0.876419124514151, -0.8747512161199128, -0.8674469970643861, -0.854640385687351, -0.836569707514385, -0.8135717154533966, -0.7860734231643546, -0.7545819529431678, -0.7196726460030769, -0.6819757234702758, -0.6421618197607575, -0.6009267354734795, -0.5589757739165052, -0.5170080334825792, -0.47570102713219514, -0.43569599027203837, -0.3975842196026983, -0.36189475853434033, -0.32908371021735955, -0.2995254179773031, -0.2735057060131667, -0.25121732178695244, -0.23275766688013177, -0.2181288465762971, -0.20724001144845222, -0.19991190819252508, -0.19588350323731377, -0.19482049259626852, -0.19632546623574457, -0.1999494560215732, -0.20520456402390408, -0.21157734338791337, -0.21854258770035825, -0.22557717717657244, -0.23217363122021023, -0.23785302690904464, -0.24217696145632447, -0.24475826319866806, -0.24527018947988707, -0.24345389006523901, -0.23912396040299208, -0.2321719589865864, -0.22256781599343292, -0.21035911494537762, -0.19566828397150798, -0.17868778697258386, -0.159673456233922, -0.13893615552013872, -0.11683200521684563, -0.09375143759327845, -0.07010737983045996, -0.046322884351881546, -0.022818539661676046, -2.0819482253951928e-16], [0.0, 0.022172635657690284, 0.04274265563948582, 0.061435455640987034, 0.07804020905827957, 0.09241637259760928, 0.10449823463994462, 0.11429737892364675, 0.12190299038171135, 0.1274799861943162, 0.13126501186744627, 0.1335603979846977, 0.1347262267843747, 0.1351707075274662, 0.13533910447534947, 0.13570150004379647, 0.1367397073489249, 0.13893367009516241, 0.1427477029568654, 0.1486169318691795, 0.15693429078903953, 0.16803841956144963, 0.18220278680455004, 0.1996263327056941, 0.22042589000496987, 0.24463059812902604, 0.2721784764928607, 0.30291526961966475, 0.33659562026122625, 0.37288656853650887, 0.41137331669195015, 0.45156714188147523, 0.49291528479799707, 0.534812591429755, 0.5766146399360325, 0.6176520457811945, 0.6572456068201439, 0.6947219267972066, 0.7294291413071099, 0.7607523650569504, 0.7881284834206602, 0.8110599247198298, 0.8291270720944715, 0.8419990047191659, 0.8494422967388919, 0.8513276477173962, 0.8476341695124282, 0.838451210077296, 0.8239776533855271, 0.8045186950546896, 0.7804801538326468, 0.7523604384234087, 0.7207403457181618, 0.6862709189728887, 0.649659641549385, 0.6116552823546042, 0.5730317420769723, 0.5345712739148165, 0.4970474681128154, 0.46120839587865914, 0.4277603049840575, 0.3973522466354054, 0.3705619913347177, 0.34788356096979733, 0.3297166660140067, 0.31635829141321914, 0.30799662359327445, 0.3047074552809641, 0.30645314585282823, 0.31308415414506957, 0.3243430995542987, 0.33987124731912643, 0.35921725655370496, 0.38184797629758527, 0.4071610268434831, 0.43449886206604793, 0.4631639744010818, 0.49243487833195854, 0.5215824913401808, 0.5498865236627698, 0.5766514900346184, 0.6012219678107547, 0.6229967461628407, 0.6414415399046312, 0.6560999781911636, 0.6666026219335989, 0.6726738131848384, 0.6741362137482366, 0.6709129475003177, 0.6630273199786288, 0.6506001482061301, 0.6338447920365098, 0.6130600340739322, 0.5886210070756006, 0.5609684144158299, 0.5305963295372913, 0.498038893359302, 0.4638562535587932, 0.42862010589413074, 0.39289920493005626, 0.35724520949495603, 0.32217921704044933, 0.2881793210865985, 0.25566949765189345, 0.22501009071960848, 0.1964901243028088, 0.17032162062482065, 0.14663605155308257, 0.12548299504090563, 0.1068310113454597, 0.09057069664107574, 0.0765198157759704, 0.06443036273508064, 0.053997348209572485, 0.04486906976977865, 0.036658582594185765, 0.028956058462919314, 0.02134169853568523, 0.01339885185373156, 0.004726986868391541, -0.005045832284917677, -0.016251299696855064, -0.02917036476457031, -0.04402415545246316, -0.06096657349676902, -0.080078763745341, -0.10136561103095958, -0.12475436519904032, -0.1500954394860196, -0.17716537077768796, -0.20567187380421148, -0.23526086648350497, -0.26552529180038165, -0.2960155141240021, -0.3262510259314527, -0.355733165593351, -0.3839585190956771, -0.41043265903985704, -0.43468386349370836, -0.4562764555529434, -0.47482341188352056, -0.4899979048874131, -0.5015434680813631, -0.5092825071974608, -0.5131229196024651, -0.5130626309051924, -0.5091919089368074, -0.5016933703777205, -0.49083965280018016, -0.4769887833678246, -0.46057733342475604, -0.4421115042686372, -0.4221563421305241, -0.4013233284547339, -0.3802566337731224, -0.3596183587316699, -0.3400731132542803, -0.3222723037133131, -0.3068385078222921, -0.2943503175004989, -0.28532802113834205, -0.28022047870464983, -0.27939351639735366, -0.283120132679506, -0.2915727653970629, -0.30481782125839585, -0.3228126154398023, -0.3454048117656274, -0.37233439419124126, -0.4032381396485332, -0.43765650217915486, -0.47504276015152785, -0.5147742236578452, -0.5561652492584694, -0.5984817653093264, -0.640956974253701, -0.6828078693906556, -0.7232521834614404, -0.7615253754224364, -0.7968972602740626, -0.82868789483243, -0.8562823496750172, -0.8791440237447498, -0.896826192622255, -0.9089815234349321, -0.915369337742637, -0.9158604573458564, -0.910439525497411, -0.8992047560620017, -0.8823651242966815, -0.860235073632106, -0.8332268716428158, -0.801840803876388, -0.7666534450203024, -0.7283042917919367, -0.6874810798575012, -0.6449041371088753, -0.6013101470368521, -0.557435708231557, -0.5140010789364858, -0.4716944890336932, -0.4311573860282725, -0.3929709569419451, -0.3576442351468014, -0.32560406090037003, -0.29718711769240647, -0.27263421464716336, -0.2520869294337884, -0.23558666780735296, -0.22307613647913185, -0.21440316696595615, -0.20932677085138818, -0.2075252529138556, -0.20860615916323172, -0.2121177931858878, -0.2175619973914015, -0.22440786667211332, -0.2321060413259865, -0.24010321433918852, -0.24785648554020118, -0.2548472017560853, -0.26059393772810874, -0.2646642967588648, -0.2666852422328819, -0.26635171044741485, -0.2634333006025525, -0.2577788881723106, -0.2493190619311326, -0.2380663412735106, -0.22411318771323405, -0.2076278811378033, -0.1888483860942264, -0.1680743847178235, -0.14565769959541278, -0.12199137070648008, -0.09749768458666803, -0.07261548015642824, -0.04778707359790216, -0.023445153799816, -2.1305333457443468e-16], [0.0, 0.022495851472507048, 0.04319461645292752, 0.06184401203520992, 0.07826191294968537, 0.0923420028908107, 0.10405730936433585, 0.11346152147769747, 0.12068804788251393, 0.1259468310388868, 0.12951899261234284, 0.13174944164725136, 0.13303763074135846, 0.13382669441116843, 0.134591246938568, 0.13582415312275875, 0.13802261359956386, 0.14167392600114354, 0.1472412936974906, 0.15515005490012215, 0.1657746964677783, 0.1794269990211787, 0.19634563336989816, 0.2166874934233298, 0.24052100855100503, 0.26782162981314395, 0.29846963079882216, 0.33225030631625657, 0.3688565923051299, 0.40789406957497726, 0.44888825383231756, 0.4912940164462275, 0.534506925971542, 0.5778762509691662, 0.62071932138231, 0.6623369097429211, 0.7020292657124406, 0.7391124186218251, 0.7729343532641779, 0.802890664473409, 0.8284393060188172, 0.8491140688425902, 0.8645364522138865, 0.8744256282937191, 0.8786062450154719, 0.8770138630162203, 0.8696978783733071, 0.8568218427480536, 0.8386611547564733, 0.8155981594571001, 0.7881147552267959, 0.7567826674595521, 0.7222516049960316, 0.6852355665867705, 0.6464976097464367, 0.6068334319612696, 0.5670541434393803, 0.5279686307211843, 0.4903659209943039, 0.45499795761849976, 0.4225631881374462, 0.39369134715379395, 0.3689297883271024, 0.34873168310179, 0.33344635947428725, 0.32331200324219356, 0.3184508879813417, 0.3188672398373009, 0.3244477805606753, 0.33496492858570814, 0.3500825748973263, 0.36936428948589833, 0.39228375683183286, 0.4182371864847584, 0.44655739867204813, 0.4765292461020423, 0.5074060026499261, 0.5384263281556427, 0.5688314066281146, 0.5978818530084901, 0.6248739913263454, 0.6491551243746467, 0.6701374414837439, 0.6873102459193025, 0.7002502259835923, 0.7086295429982116, 0.7122215637641093, 0.7109041234781934, 0.7046602659862925, 0.6935764701622603, 0.6778384325933368, 0.657724536109545, 0.6335971895606199, 0.605892275248186, 0.5751069853176131, 0.541786366111525, 0.5065089190746425, 0.46987162757045037, 0.432474790437607, 0.3949070450240774, 0.35773095477419764, 0.32146951943106705, 0.28659394000940713, 0.25351293656863466, 0.22256387535243263, 0.1940059141213048, 0.16801532170475345, 0.14468307128056299, 0.12401474808156354, 0.10593275262116608, 0.09028072162178583, 0.07683003210856977, 0.06528820102138529, 0.05530894453472611, 0.046503619266053765, 0.038453732749992246, 0.030724183828305274, 0.022876875619272635, 0.014484334930033158, 0.0051429725751725225, -0.005514370958983146, -0.017806930971658454, -0.031995883872484365, -0.04827584547673059, -0.06676823271446708, -0.08751667060442175, -0.1104845730491693, -0.1355549693638586, -0.16253258989186267, -0.19114816507241866, -0.22106483440418057, -0.25188650636543203, -0.2831679589148118, -0.3144264240159304, -0.34515435988462784, -0.3748330823676151, -0.4029469028585634, -0.4289974050677473, -0.4525174871866221, -0.4730847996982054, -0.4903342222091314, -0.5039690449146461, -0.5137705511193751, -0.5196057358743923, -0.5214329413072435, -0.519305240494435, -0.5133714574873847, -0.5038747699699925, -0.491148901535136, -0.47561197121086934, -0.45775812713011876, -0.43814714763693813, -0.4173922452418943, -0.39614635536692905, -0.3750872315793074, -0.3549017009945881, -0.3362694569095305, -0.31984677989932775, -0.30625058319763465, -0.29604317302786276, -0.28971809976579194, -0.2876874517211693, -0.29027091049469633, -0.2976868460787547, -0.31004568210554484, -0.3273457080590145, -0.34947145715692607, -0.3761947073900803, -0.40717810036977314, -0.44198130971658456, -0.4800696292629989, -0.5208247928444861, -0.56355778335369, -0.607523340358892, -0.6519358341306575, -0.6959861404012014, -0.7388591254267887, -0.7797513355484912, -0.8178884798344409, -0.8525422986831245, -0.8830464253742615, -0.9088108711341414, -0.9293347967658572, -0.9442172744938371, -0.95316579139998, -0.9560022995241884, -0.9526666760584437, -0.9432175186598237, -0.9278302642446656, -0.9067926831619199, -0.8804978628333782, -0.8494348542805088, -0.8141772099921291, -0.7753696909906237, -0.7337134635327398, -0.6899501406087893, -0.6448450494497195, -0.5991701229972168, -0.5536868203494216, -0.5091294784137776, -0.4661894844708325, -0.42550063740948896, -0.38762603459742323, -0.35304678247891474, -0.3221527830220963, -0.29523579621776735, -0.2724849222556177, -0.25398458717637035, -0.23971505420261832, -0.22955542111022037, -0.22328900344166797, -0.22061094557376418, -0.22113784805295966, -0.2244191515146593, -0.22994997608014728, -0.23718508138079514, -0.2455535871051914, -0.25447407779943054, -0.26336970894531825, -0.27168293423078277, -0.2788894863074002, -0.2845112648611401, -0.2881278159367559, -0.289386124372659, -0.2880084859480088, -0.28379827627424525, -0.27664348829699437, -0.2665179681207479, -0.25348033826462807, -0.23767065690343495, -0.2193049196454169, -0.1986675654872501, -0.17610219938279584, -0.15200078909040216, -0.12679163249034994, -0.10092642242581717, -0.07486675854741327, -0.049070469075909805, -0.023978109509973256, -2.1702366992562102e-16], [0.0, 0.02272282655911415, 0.04346006456362582, 0.06198648140073539, 0.07815304792430981, 0.09189159892424037, 0.10321723062803535, 0.11222836488572446, 0.11910447057097343, 0.12410149393726723, 0.12754510964486107, 0.12982196139856642, 0.13136911415309258, 0.1326619873009639, 0.13420107894588945, 0.13649782423876955, 0.14005995496644988, 0.14537674250370586, 0.15290451146824396, 0.16305280680111042, 0.17617158262217802, 0.19253975741873014, 0.21235544748784174, 0.23572814986639198, 0.26267309824545687, 0.29310796175642256, 0.3268519983616625, 0.36362771332677657, 0.40306501041849846, 0.44470776062954, 0.48802265194962857, 0.5324101255162955, 0.5772171498513082, 0.6217515371707574, 0.6652974651563427, 0.7071318351260479, 0.7465410740775302, 0.7828379742096344, 0.8153781596321771, 0.843575776180957, 0.8669180164434069, 0.884978117902633, 0.8974265069175923, 0.9040398042447033, 0.904707457937588, 0.899435825524899, 0.888349588000637, 0.871690441891334, 0.8498130809352923, 0.8231785441256729, 0.7923450704352094, 0.7579566608975341, 0.72072960438697, 0.6814372730468388, 0.6408935356445946, 0.5999351711363846, 0.559403689563031, 0.5201269824570343, 0.4829012298381605, 0.44847348548466154, 0.41752534661099716, 0.39065808873315966, 0.3683796119712909, 0.3510935021631121, 0.33909045998214044, 0.3325422949918201, 0.3314986205895184, 0.3358863215868391, 0.3455118002975752, 0.36006594106461254, 0.379131668755753, 0.4021939154605214, 0.42865175291314767, 0.45783239742490617, 0.4890067505582088, 0.5214061034640245, 0.5542396065789329, 0.5867120898599605, 0.618041812306999, 0.647477723318437, 0.6743158323288305, 0.6979143068230621, 0.7177069516056578, 0.7332147632993943, 0.7440553024235341, 0.7499496798514144, 0.7507270136147121, 0.7463262744391765, 0.7367955025184117, 0.7222884422741724, 0.7030587046298483, 0.6794516260942504, 0.6518940492493026, 0.62088229870564, 0.5869686690296658, 0.5507467755267589, 0.512836144262593, 0.47386643371513626, 0.43446168660805323, 0.3952250066619601, 0.35672404134192665, 0.31947762855107, 0.2839439332298146, 0.25051035979677444, 0.21948547933739251, 0.19109315761072873, 0.1654690126458971, 0.14265927038964019, 0.12262202507018963, 0.1052308492189567, 0.09028063819574907, 0.07749551710645297, 0.06653858561506004, 0.057023229648240935, 0.04852568953465152, 0.0405985426985287, 0.03278473642060526, 0.024631792949091298, 0.015705805713233132, 0.005604851641113338, -0.006028539554998419, -0.0194961931971938, -0.03503467500760361, -0.05280751312937447, -0.07289946791947478, -0.0953130071996491, -0.11996708713821325, -0.14669827879683822, -0.17526421913810475, -0.20534930450505112, -0.23657248579636167, -0.26849696926416655, -0.3006415764631127, -0.33249347266472795, -0.36352193615136624, -0.39319281216760826, -0.4209832756757921, -0.44639651695279065, -0.46897596375529726, -0.48831866330289736, -0.5040874664676341, -0.5160216848593931, -0.5239459282713859, -0.5277768742988614, -0.5275277727748791, -0.5233105437230825, -0.5153353874191263, -0.5039078873910928, -0.48942365022427564, -0.47236058829344096, -0.4532690114678517, -0.43275974991799254, -0.4114905809865208, -0.39015127738621497, -0.36944763062995817, -0.3500848316460273, -0.33275060926054095, -0.3180985361425519, -0.3067319106522553, -0.2991886118047793, -0.2959273035057136, -0.297315333818446, -0.30361863600784184, -0.31499389140456874, -0.33148316087579244, -0.3530111331612771, -0.37938507596173415, -0.4102975109683423, -0.44533156857858847, -0.48396891345443305, -0.5256000699266996, -0.569536918058818, -0.6150270783832529, -0.6612698572137894, -0.707433386152433, -0.752672559896707, -0.7961473564423452, -0.837041113767216, -0.874578337328355, -0.9080416232088723, -0.9367873022664108, -0.960259440666804, -0.9780018710085852, -0.9896679749141093, -0.9950279913472074, -0.9939736837166605, -0.9865202616087873, -0.9728055182327808, -0.9530862107716443, -0.9277317762014741, -0.8972155381834497, -0.8621036198152103, -0.8230418309163187, -0.7807408458120672, -0.7359600271299032, -0.6894902819831874, -0.6421363583521142, -0.59469900097756, -0.5479573874012853, -0.5026522559064321, -0.45947011827730544, -0.41902892199287173, -0.38186548941217874, -0.3484250166338416, -0.3190528631382406, -0.2939888063355755, -0.2733638741614082, -0.25719980539541437, -0.24541112299851386, -0.23780974205739688, -0.2341119724623014, -0.23394771873372391, -0.23687162686996888, -0.24237588199252336, -0.24990432203974372, -0.25886750273069714, -0.2686583282064116, -0.2786678506411379, -0.28830084094501984, -0.29699074144741267, -0.3042136299053021, -0.3095008518310114, -0.312450014257125, -0.312734077723196, -0.3101083333614987, -0.30441510720201614, -0.29558609280836257, -0.28364227460331554, -0.26869146619822615, -0.2509235491430146, -0.23060355622455778, -0.20806279828561752, -0.1836882831375239, -0.15791071825474978, -0.1311914244899448, -0.10400851514698642, -0.07684271272354827, -0.05016318404030308, -0.024413773108988266, -2.200847561863644e-16], [0.0, 0.022853940323905933, 0.043542621913924585, 0.061872486621815666, 0.0777317914764011, 0.09109414738926297, 0.10201966383809234, 0.11065366255502213, 0.11722298674585754, 0.12202999526804088, 0.12544439190326578, 0.12789309683189412, 0.12984841920059148, 0.13181483495105403, 0.1343147116879637, 0.13787335134161008, 0.1430037409741502, 0.1501914117724018, 0.15987980579662756, 0.1724565394012535, 0.18824093165279507, 0.20747313603517395, 0.23030517498365297, 0.25679413027617415, 0.28689768918168995, 0.32047218783386966, 0.3572732310154294, 0.39695890295279956, 0.4390955184432484, 0.4831657992981855, 0.5285792992985023, 0.5746848431720051, 0.6207846929719479, 0.6661501099772852, 0.7100379429992909, 0.7517078457188091, 0.7904397071258403, 0.8255508707815061, 0.8564127207127633, 0.8824662242654807, 0.9032360449063043, 0.9183428702510619, 0.9275136417411298, 0.9305894214026368, 0.9275306868236665, 0.9184199065215566, 0.903461312761472, 0.8829778560466781, 0.8574053932894974, 0.8272842284308694, 0.7932481883693148, 0.7560114769137333, 0.7163536036174466, 0.6751027314502096, 0.6331178261587939, 0.5912700198934506, 0.55042362149925, 0.5114172152922831, 0.47504528891989256, 0.44204081906089326, 0.4130592215359402, 0.38866404040287944, 0.3693147095807094, 0.35535667147365013, 0.34701408114580656, 0.3443852631866484, 0.34744102300198393, 0.35602584645567364, 0.36986195322377186, 0.3885561015726075, 0.4116089771797575, 0.4384269376624653, 0.46833582913979166, 0.5005965427717947, 0.5344219389587337, 0.5689947357127186, 0.603485936376553, 0.6370733608606398, 0.6689598441456185, 0.6983906759425492, 0.7246698758412459, 0.7471749284856402, 0.7653696425283512, 0.7788148443505644, 0.787176671607769, 0.7902322912308274, 0.7878729300963534, 0.7801041726057262, 0.7670435462465425, 0.7489154822057686, 0.7260438016364485, 0.6988419376901762, 0.6678011574593054, 0.6334770952085884, 0.5964749475695121, 0.5574337117755226, 0.5170098688087061, 0.47586092402485564, 0.4346292181926709, 0.3939264119498929, 0.3543190267267185, 0.3163153957458303, 0.28035434054534847, 0.24679584256828135, 0.2159139268930571, 0.18789191747975148, 0.16282016183880785, 0.14069625934819732, 0.1214277631583703, 0.10483726235155671, 0.0906696903545859, 0.07860164906594604, 0.0682524871660811, 0.05919682691141871, 0.0509781974707483, 0.043123405450247294, 0.0351572553506223, 0.026617224746539287, 0.01706770116413172, 0.006113399890879185, -0.00658839603603644, -0.021317101216694646, -0.03827988661245925, -0.05760477259226121, -0.07933594411879885, -0.10343141788323468, -0.12976312981797863, -0.15811944822520307, -0.1882100543570554, -0.219673070281367, -0.25208425483912367, -0.28496803394825043, -0.3178100828222913, -0.35007113609584467, -0.38120166844703485, -0.4106570639424577, -0.437912877637187, -0.46247978833467523, -0.4839178469894416, -0.5018496409038279, -0.5159720192599341, -0.5260660600255603, -0.5320050010354946, -0.5337599080250408, -0.5314029083466342, -0.5251078796461046, -0.5151485464080565, -0.5018940024151562, -0.48580174217789224, -0.46740834765332956, -0.4473180364970522, -0.4261893331751072, -0.4047201731126494, -0.3836317914354525, -0.363651780714681, -0.3454967256089949, -0.32985483579648167, -0.31736900173393634, -0.3086206904600999, -0.30411508101931745, -0.3042678115250799, -0.30939367305762877, -0.319697540375292, -0.33526777690356124, -0.35607229291960873, -0.38195737269465757, -0.4126493201304056, -0.4477589047448465, -0.4867885223825085, -0.529141919396952, -0.5741362668892396, -0.6210163144120124, -0.6689703017712735, -0.7171472644284229, -0.7646753335882774, -0.8106806072075726, -0.8543061534910752, -0.8947307043287771, -0.9311866026787383, -0.9629765849660087, -0.9894890067409837, -1.0102111564651723, -1.0247403474816859, -1.032792530884819, -1.0342082308482772, -1.028955667573513, -1.017130999830976, -0.9989556874621673, -0.9747710425255283, -0.9450301043433321, -0.9102870369226201, -0.8711843055467149, -0.8284379413521697, -0.7828212471620241, -0.7351473336692995, -0.6862509013972309, -0.6369697000807822, -0.5881261028424386, -0.5405092276571529, -0.4948580232600197, -0.4518457112460704, -0.41206594129119617, -0.37602097306398896, -0.34411214758577996, -0.31663285379730666, -0.29376413432226556, -0.2755730094120273, -0.2620135314201613, -0.2529305155352421, -0.24806582753678433, -0.24706704762853188, -0.24949827245834758, -0.25485276664575557, -0.26256713174237273, -0.27203662559654235, -0.2826312394192625, -0.29371212405942926, -0.30464795145112517, -0.31483080199730634, -0.3236911836481632, -0.33071181321087995, -0.3354398243394736, -0.33749710882187134, -0.3365885471249054, -0.33250793941826734, -0.32514150807204445, -0.3144689053954494, -0.3005617245708805, -0.2835795757188595, -0.2637638511952607, -0.24142936300992945, -0.2169540891901692, -0.19076731364222838, -0.1633364843951701, -0.13515314703805736, -0.10671833288938473, -0.07852779440530425, -0.05105748322482251, -0.024749659003941132, -2.2222670470174246e-16], [0.0, 0.022890824677088983, 0.043448398551969934, 0.0615152922226714, 0.07702097130263315, 0.0899840900691743, 0.10051227804095361, 0.10879941876974483, 0.11512048570639727, 0.11982406399710949, 0.12332274785821548, 0.12608165921928308, 0.12860538318758094, 0.1314236582982643, 0.1350761933866434, 0.1400970073779426, 0.1469987026980851, 0.1562570869801655, 0.16829655115111575, 0.18347659497251, 0.2020798640812634, 0.22430202618508763, 0.25024376920490754, 0.279905151927065, 0.31318247942375266, 0.3498678125672064, 0.3896511549669737, 0.43212529324526006, 0.4767931994170554, 0.523077838940728, 0.5703341663873688, 0.6178630341941532, 0.6649266900446329, 0.7107654963234861, 0.7546154718992326, 0.7957262330514567, 0.833378897294357, 0.8669035115151928, 0.8956955743382525, 0.91923124176807, 0.9370808345214455, 0.948920304334233, 0.9545403639969714, 0.9538530407899841, 0.9468954740241666, 0.9338308430652548, 0.914946380926713, 0.8906484985815944, 0.8614551148524328, 0.8279853543819922, 0.7909468401061615, 0.7511208652720904, 0.709345781926475, 0.6664989866609027, 0.6234779191589536, 0.5811805138809797, 0.5404855594284834, 0.5022334233911169, 0.46720759270365214, 0.4361174609066708, 0.40958276465777776, 0.3881200330800023, 0.37213136599878627, 0.36189580196181526, 0.35756347549693945, 0.35915269683629847, 0.3665500179304296, 0.3795132776828689, 0.3976775486777991, 0.4205638389683594, 0.4475903374102879, 0.4780859311438109, 0.5113056705967278, 0.5464478120898799, 0.5826720318633002, 0.6191183789754906, 0.6549265186840655, 0.6892548129590585, 0.7212987908087027, 0.750308577939737, 0.7756048824933577, 0.796593170502713, 0.8127757103802571, 0.8237612190217182, 0.8292719016808033, 0.8291477421458945, 0.8233479673420105, 0.8119496796174753, 0.7951437189496341, 0.7732278844198842, 0.7465977079171012, 0.7157350315724805, 0.6811946924788875, 0.6435896625390484, 0.6035750267493483, 0.5618312090111981, 0.5190468700632263, 0.4759019069953101, 0.433050977954871, 0.3911079592689029, 0.350631715725804, 0.3121135288832926, 0.27596648391958867, 0.24251706386085423, 0.21199914231555658, 0.18455050359075237, 0.16021195383174688, 0.13892902026228413, 0.12055616938482999, 0.10486341079517851, 0.09154509268525052, 0.08023063967142886, 0.07049693468088072, 0.06188200547675441, 0.05389964403033032, 0.04605456415769058, 0.0378576901920372, 0.028841167266445495, 0.018572692078479777, 0.006668781576378127, -0.0071933746333322085, -0.023265794931044713, -0.04172159061901673, -0.06264907389247217, -0.08604824948310398, -0.11182978835637143, -0.13981651702409537, -0.16974739029367594, -0.2012838502832536, -0.23401841193881076, -0.26748525668568734, -0.30117256272494863, -0.33453625419960786, -0.3670148131909737, -0.3980447692450308, -0.42707646163096363, -0.4535896603123627, -0.47710863292230327, -0.4972162568681204, -0.5135667977776006, -0.5258970073050656, -0.5340352340680715, -0.5379082901821177, -0.5375458712997293, -0.5330823888682253, -0.5247561379867972, -0.5129057911580255, -0.49796427572181634, -0.4804501591428598, -0.4609567299323334, -0.44013902122184484, -0.4186990773796966, -0.3973698102155219, -0.37689782908558717, -0.35802565761904903, -0.3414737680978333, -0.327922872250403, -0.3179969041355724, -0.31224711693669027, -0.3111376911663709, -0.31503321756430963, -0.32418837466863376, -0.3387400696939289, -0.35870225319670224, -0.383963554462144, -0.41428781715104734, -0.4493175451467785, -0.48858019844056066, -0.5314972100059425, -0.5773955286295, -0.6255214312058006, -0.6750562925820706, -0.7251339530180178, -0.7748592838944601, -0.8233275224371387, -0.8696439266624925, -0.9129432929904548, -0.9524088812325401, -0.9872903049074423, -1.016919968748995, -1.0407276692779353, -1.058253017588356, -1.069155395002774, -1.0732212107260564, -1.0703682946568447, -1.0606473265382683, -1.0442402729931926, -1.0214558749812677, -0.9927222981095043, -0.9585771253262615, -0.919654934201523, -0.8766727577242984, -0.8304137769584646, -0.7817096347990071, -0.7314217914790017, -0.6804223636451839, -0.6295748992500235, -0.5797155399680378, -0.5316350113708178, -0.48606185899404836, -0.4436473162665209, -0.4049521488578353, -0.37043577037632563, -0.34044786774997354, -0.315222712458009, -0.29487626759157043, -0.27940613214599264, -0.2686942946783251, -0.26251260020842676, -0.26053076867860053, -0.26232674202303824, -0.2673990814324398, -0.2751810880821493, -0.2850562805950936, -0.2963748317958408, -0.3084705466090725, -0.32067795274412825, -0.3323490763050612, -0.34286948562391295, -0.35167320811972413, -0.358256156266452, -0.36218773899605694, -0.3631203830340056, -0.3607967435324349, -0.35505444353635723, -0.3458282457653822, -0.3331496263012486, -0.31714378637249213, -0.2980242038449724, -0.2760848886166461, -0.2516905643060043, -0.22526505095827373, -0.1972781686629197, -0.16823151885309465, -0.1386435277251332, -0.10903415398926147, -0.07990967060601369, -0.051747927101543315, -0.024984485578600855, -2.2345117074042277e-16], [0.0, 0.02283636954845353, 0.043185966834339125, 0.06093171115614635, 0.07604787060632553, 0.08860099686683996, 0.09874826031785722, 0.1067332235701642, 0.11287915858578418, 0.11758007699384863, 0.12128970340181418, 0.12450867591335521, 0.127770305305817, 0.13162526318337783, 0.1366255989080956, 0.14330850445570228, 0.15218025503643193, 0.16370075112056237, 0.17826907444442125, 0.19621044694906797, 0.21776494799008952, 0.24307830237403544, 0.27219500087756743, 0.3050539571474634, 0.3414868416955175, 0.3812191666632304, 0.42387412580773376, 0.46897912448163426, 0.5159748659893951, 0.5642267953172841, 0.6130386404972936, 0.661667737310237, 0.7093417760412105, 0.7552765707685742, 0.7986944231769966, 0.8388426348776321, 0.8750117151770284, 0.906552835372783, 0.9328940959033369, 0.9535551987011752, 0.9681601532850908, 0.9764476906172055, 0.9782791124514105, 0.9736433645138741, 0.9626591879119986, 0.9455742730573458, 0.9227614124044875, 0.8947117206900124, 0.8620250623302723, 0.8253978934609671, 0.7856087891089429, 0.743501982625326, 0.6999692933821515, 0.6559308586337794, 0.6123151153802078, 0.5700384972958348, 0.5299853198201914, 0.49298832313654334, 0.4598103280593253, 0.4311274341591158, 0.40751415339078995, 0.38943082692723957, 0.377213618941393, 0.37106732003268794, 0.37106112634394567, 0.37712748978115446, 0.3890640618498371, 0.4065386802303393, 0.42909727511494516, 0.4561745032742077, 0.4871068534848038, 0.521147908896466, 0.5574854015459316, 0.5952596527568048, 0.6335829615918612, 0.6715594826011351, 0.7083051243257014, 0.7429670015900489, 0.7747419874832419, 0.802893934751308, 0.8267691704927453, 0.845809911704748, 0.859565301277009, 0.8676998231757633, 0.8699989203336477, 0.8663717075561166, 0.8568507428715314, 0.8415888924350868, 0.820853394581464, 0.7950172961759513, 0.7645484973833286, 0.7299966978196427, 0.691978586390639, 0.6511616577575824, 0.6082470693302041, 0.5639519732336565, 0.5189917673574541, 0.47406270816695095, 0.4298253155152236, 0.38688897658243687, 0.3457981229028056, 0.30702031207698005, 0.2709364952984698, 0.23783369453473263, 0.20790025055243969, 0.18122373654904328, 0.15779156362697272, 0.13749423544992262, 0.12013114188618722, 0.10541871696798705, 0.0930007266950581, 0.08246039858223674, 0.07333405873421214, 0.06512590477533312, 0.05732351509857128, 0.04941367731355065, 0.04089811189784453, 0.03130867104759583, 0.020221607468484847, 0.007270532961073061, -0.007842278510275722, -0.02533654490872457, -0.04534683763416405, -0.06791784290915186, -0.09300215275732275, -0.12046064919522033, -0.1500654774894546, -0.18150553660780813, -0.2143943490349196, -0.24828010960629818, -0.2826576555289972, -0.31698204876787417, -0.35068341878540643, -0.3831826793377709, -0.4139077085345998, -0.4423095673036223, -0.46787832814176755, -0.4901580936876831, -0.5087608030493126, -0.5233784525262621, -0.5337933956828275, -0.5398864347139787, -0.5416424695443758, -0.5391535317602764, -0.5326190957895481, -0.5223436280899746, -0.5087314047753915, -0.49227869736109053, -0.47356349340892767, -0.4532329821134087, -0.4319890926991417, -0.4105724244358053, -0.38974494982581803, -0.37027190598967225, -0.35290331260007324, -0.33835556728440364, -0.3272935708770177, -0.3203138251848305, -0.3179289252347359, -0.3205538367753132, -0.32849430884468456, -0.34193772147106577, -0.3609466112414831, -0.3854550539462009, -0.41526801532614377, -0.45006370978037624, -0.48939893446970784, -0.5327172743536688, -0.579360004084981, -0.6285794470679089, -0.6795544919790633, -0.7314079141300742, -0.7832251045277571, -0.8340737744613556, -0.883024178788278, -0.9291693874168996, -0.9716451321452252, -1.0096487650785053, -1.042456885108304, -1.0694412199068977, -1.0900823918283575, -1.1039812460209704, -1.1108674767345017, -1.1106053518493628, -1.1031964045065707, -1.088779032703002, -1.067625021085253, -1.040133072143182, -1.0068195047973054, -0.9683063452730374, -0.9253070965362208, -0.8786105269413794, -0.8290628648026576, -0.7775488222282759, -0.7249718978854238, -0.6722344237605636, -0.6202178250954086, -0.5697635554337238, -0.5216551503102183, -0.4766018140249919, -0.43522391491212054, -0.3980407165086326, -0.3654606162592443, -0.33777410124012025, -0.31514956339355255, -0.29763204659300824, -0.28514492623757765, -0.27749445077167434, -0.2743770052936458, -0.27538889195449195, -0.2800383617569707, -0.2877595791115191, -0.29792815538158035, -0.3098778517457863, -0.3229180258757574, -0.3363513817819281, -0.3494915780550591, -0.3616802566927977, -0.37230307253782996, -0.3808043315856998, -0.3866998843076514, -0.3895879666989615, -0.38915773581436647, -0.3851953067129258, -0.3775871624790835, -0.36632087667730556, -0.35148315652640216, -0.33325528351089917, -0.31190609436016503, -0.2877827076600575, -0.26129925825464684, -0.23292395162453955, -0.20316479234493884, -0.1725543734878088, -0.14163413662670016, -0.11093852436976843, -0.08097944879127457, -0.052231489732127316, -0.02511821694637622, -2.237715756273737e-16], [0.0, 0.02269471294813116, 0.042766304844330284, 0.06014196641110531, 0.0748439755376095, 0.08698917073221102, 0.09678575495146019, 0.10452750894983594, 0.11058556118124256, 0.115397925484496, 0.1194570766678699, 0.12329588617193335, 0.12747228390569376, 0.1325530469927223, 0.13909714063805087, 0.14763904999459798, 0.15867254440218936, 0.1726353066058388, 0.18989483972873564, 0.21073603435354174, 0.23535073779405774, 0.26382961850748887, 0.2961565618188941, 0.3322057701113885, 0.37174167294478705, 0.414421681888319, 0.4598017529546406, 0.5073446482018111, 0.5564307191157217, 0.6063709695311666, 0.6564220967302618, 0.7058031574680105, 0.7537134623353751, 0.7993512681894378, 0.8419328152294224, 0.8807112432881863, 0.9149949213775213, 0.9441647355243826, 0.9676899022302703, 0.9851419079632662, 0.996206218169331, 1.0006914513348963, 0.998535773391116, 0.9898103337726992, 0.974719635124764, 0.9535988022652946, 0.9269077907584917, 0.8952226495044386, 0.8592240232857032, 0.8196831484734224, 0.7774456564278495, 0.7334135530185533, 0.6885257878052353, 0.6437378616431463, 0.6000009459304363, 0.5582409997848321, 0.5193383727888227, 0.4841083705280147, 0.45328323820692096, 0.42749598468310557, 0.40726642610725455, 0.39298977603661905, 0.3849280486706049, 0.3832044752019265, 0.38780106180438806, 0.3985593432266342, 0.415184310142976, 0.4372514131711523, 0.46421647363141255, 0.4954282624607062, 0.5301434458759746, 0.5675435409234191, 0.6067534772964661, 0.6468613248800525, 0.6869387202668441, 0.7260615106126699, 0.763330129995855, 0.7978892319733776, 0.8289461220533284, 0.8557875648134089, 0.8777945816057657, 0.8944549051666333, 0.9053728157386801, 0.9102761480661596, 0.9090203282329231, 0.9015893720597704, 0.8880938508651623, 0.8687659039974153, 0.8439514488582496, 0.8140998064085512, 0.7797510217326649, 0.7415212136368325, 0.7000863331510746, 0.6561647470859733, 0.6104990886010933, 0.5638378314667154, 0.5169170480177671, 0.4704428026651609, 0.42507461348653036, 0.38141038438515457, 0.33997317036727226, 0.3012000896733294, 0.26543364005654674, 0.23291561386853596, 0.20378373937410646, 0.1780711055753624, 0.15570835654724674, 0.13652857066655502, 0.12027467192806675, 0.10660915649464016, 0.09512585932619906, 0.08536343463202165, 0.07682018126536774, 0.0689698110884002, 0.06127773559680619, 0.05321743426463535, 0.04428646743286018, 0.03402170712042841, 0.022013380602949592, 0.007917553425986738, -0.008533280118806292, -0.027521781181580773, -0.04913975027380647, -0.07338467316383168, -0.1001589240015797, -0.1292716514666348, -0.16044330357069025, -0.19331267765890733, -0.22744631589998798, -0.26235000481597864, -0.2974820817517061, -0.3322682030396296, -0.3661171892104507, -0.39843753294583456, -0.42865413633543575, -0.45622483589086826, -0.4806562769122272, -0.5015187131437752, -0.5184593328583752, -0.531213747965719, -0.5396153275795612, -0.5436021105991451, -0.5432210919452186, -0.5386297426499672, -0.530094693401039, -0.5179875826515868, -0.5027781422431747, -0.48502466384717924, -0.4653620566462381, -0.44448776886102814, -0.4231459014088105, -0.40210988974706124, -0.38216416859021907, -0.36408526269675945, -0.3486227645635631, -0.336480666159436, -0.32829950658473295, -0.3246397808504447, -0.3259670272027662, -0.332638972228382, -0.3448950652711292, -0.3628486776193295, -0.38648217884110575, -0.41564503408465053, -0.45005499379207853, -0.48930237286687134, -0.5328573417072635, -0.5800800785009811, -0.6302335625641766, -0.6824987240115187, -0.7359916072547698, -0.7897821561706803, -0.8429141884846196, -0.8944260969850256, -0.9433717963626858, -0.9888414272343552, -1.0299813334539218, -1.066012845040098, -1.0962494265744427, -1.1201117890875074, -1.1371406113331275, -1.1470065727920271, -1.1495174643768, -1.1446222120852914, -1.1324117220847645, -1.113116531124134, -1.0871013219322119, -1.054856437524543, -1.0169865993054854, -0.9741970997928411, -0.9272778001109436, -0.8770853136588672, -0.8245237993266283, -0.7705248192956605, -0.7160267370657099, -0.6619541404160715, -0.6091977713354795, -0.5585954306309121, -0.5109142993260258, -0.4668350827357742, -0.4269383371660331, -0.39169328468365283, -0.36144935969015574, -0.33643066364266894, -0.31673343286694167, -0.30232655076332154, -0.29305506163290157, -0.2886465706700187, -0.2887203451631347, -0.29279886732070043, -0.3003215309694013, -0.31066012407367244, -0.3231356978139443, -0.33703639182537504, -0.35163576487551523, -0.3662111712152825, -0.38006172525849996, -0.3925254110317345, -0.402994917606507, -0.410931816825914, -0.4158787441576273, -0.4174692963023542, -0.4154354189148542, -0.4096121229367835, -0.399939436948392, -0.386461573879969, -0.3693233615971155, -0.3487640564971181, -0.3251087255794116, -0.29875744381980307, -0.2701726085508597, -0.23986471956042105, -0.20837701159641894, -0.17626935396744856, -0.14410184926502037, -0.11241856948422904, -0.08173186284284166, -0.052507648535498205, -0.025152089929554408, -2.2321318681993174e-16], [0.0, 0.022471215538102336, 0.04220270939932241, 0.059169508651114894, 0.07344466722671224, 0.08519718855616136, 0.0946872333494397, 0.10225873451887726, 0.10832960925727637, 0.11337982152830528, 0.11793760506717724, 0.12256420598265283, 0.12783754394285787, 0.13433522069218035, 0.14261732351334627, 0.15320947871980098, 0.166586606126934, 0.18315780978628246, 0.2032528134443159, 0.22711031185734804, 0.25486856217208526, 0.286558484225158, 0.322099476196221, 0.3612980841190165, 0.40384959200540776, 0.4493425255601377, 0.4972659885046433, 0.5470196782408873, 0.5979263587872315, 0.649246505341236, 0.7001947780757134, 0.7499579342947372, 0.7977137491029799, 0.8426504862785168, 0.8839864438304412, 0.9209890932348208, 0.9529933377519966, 0.9794184334164375, 0.9997831458463933, 1.0137187562508112, 1.0209795799559647, 1.0214507192320028, 1.0151528377551788, 1.002243815101503, 0.9830172144994861, 0.9578975738445608, 0.9274326068152302, 0.8922824759457839, 0.8532063708585675, 0.8110466907838532, 0.7667111893710974, 0.7211534901667803, 0.6753524217526713, 0.6302906513939401, 0.5869331143916023, 0.5462057427024954, 0.5089749906098907, 0.47602863742410906, 0.4480583177851993, 0.4256441898335294, 0.4092421012811594, 0.39917355447279723, 0.39561870529949145, 0.3986125589290977, 0.4080444494922533, 0.42366081295448405, 0.4450711843084085, 0.4717572738332679, 0.5030849043481788, 0.5383185238985373, 0.5766379477982383, 0.6171569318684954, 0.6589431363239486, 0.7010390080769431, 0.7424830890163655, 0.7823312495414836, 0.8196773504738863, 0.8536728523143781, 0.8835449182449374, 0.9086125956029911, 0.928300708814384, 0.9421511537581678, 0.9498313478338303, 0.9511396600158792, 0.946007719179896, 0.9344995751419121, 0.9168077632930423, 0.8932463985546638, 0.8642414957901342, 0.8303187800399652, 0.7920893093830798, 0.7502332844233865, 0.7054824601216234, 0.6586016069377971, 0.610369488281892, 0.5615598296319507, 0.512922751201695, 0.46516712085163464, 0.41894425745578084, 0.37483337785820187, 0.33332913383965224, 0.2948315303618217, 0.2596384541709343, 0.22794097420119977, 0.19982150383266256, 0.17525484172815234, 0.15411203454603128, 0.13616693314403297, 0.12110524575234495, 0.10853582870683351, 0.0980038992672715, 0.08900580719822226, 0.08100496335124717, 0.07344849540781645, 0.06578418391271265, 0.05747722615931197, 0.048026381503811194, 0.03697906911658201, 0.023945017569708578, 0.008608104279135744, -0.009263929320590145, -0.02981214511177696, -0.053081653905251165, -0.07901956760782165, -0.10747571544307165, -0.1382061094423343, -0.1708790724784104, -0.20508387233369446, -0.24034163945007153, -0.2761182857750413, -0.31183908903166235, -0.34690456215464993, -0.38070719269412084, -0.41264861259308766, -0.4421567455313678, -0.46870247735319887, -0.4918154050246606, -0.5110982408746654, -0.5262394810480573, -0.5370239893557219, -0.5433411990047032, -0.5451906937624631, -0.5426849954877155, -0.5360494550190048, -0.5256192164040467, -0.5118332985537567, -0.49522591175892966, -0.4764151972738586, -0.4560896445691236, -0.4349925012102402, -0.4139045431013073, -0.3936256167002591, -0.37495539864062327, -0.3586738411070142, -0.3455217827005133, -0.3361822040731819, -0.33126259527912444, -0.3312788778483567, -0.33664128959308726, -0.3476425949329969, -0.3644489291607202, -0.38709352287347787, -0.4154734842805159, -0.44934974392675525, -0.488350190337024, -0.5319759480429103, -0.5796106732943654, -0.6305326693508928, -0.6839295543985642, -0.7389151525455131, -0.7945482235555793, -0.8498526013432822, -0.9038382759061027, -0.9555229291939943, -1.0039534230192892, -1.0482267368133584, -1.0875098648628139, -1.1210582063345609, -1.1482320163614166, -1.1685105318673168, -1.1815034405661287, -1.1869594243440147, -1.1847715775087455, -1.1749795744773577, -1.1577685385753316, -1.1334646418613392, -1.1025275433694193, -1.065539847992114, -1.023193838596148, -0.9762757981590998, -0.9256482951861646, -0.8722308530452485, -0.8169794610053067, -0.7608654107875092, -0.7048539567253207, -0.6498832998505242, -0.5968443863461681, -0.5465619890996485, -0.49977750810523774, -0.4571338820365081, -0.41916295052195357, -0.38627554582617635, -0.35875452527464774, -0.33675088353018884, -0.32028300851863534, -0.3092390682667663, -0.3033824400408995, -0.30236001982281996, -0.3057131811280445, -0.3128910891463149, -0.32326602069999205, -0.3361502939172239, -0.3508143749249232, -0.3665057031529065, -0.3824677626046483, -0.3979589240056059, -0.41227059210705747, -0.4247442133287178, -0.43478673080756836, -0.4418841159519233, -0.44561265669683375, -0.4456477415136392, -0.44176994334674974, -0.4338682773849837, -0.4219405791618392, -0.40609102308993783, -0.38652487431843036, -0.363540636931588, -0.3375198272248675, -0.30891466045799887, -0.2782339916037909, -0.24602789388899848, -0.21287129228592322, -0.1793470917371006, -0.14602925122804708, -0.11346625459663984, -0.08216541720512233, -0.05257844461526195, -0.0250886257941545, -2.2181305355445957e-16], [0.0, 0.022172419861951464, 0.04151067938049591, 0.05804079162195865, 0.07188886153559929, 0.08327738287772911, 0.09251880156602538, 0.10000651166700929, 0.10620351766505087, 0.11162905819645165, 0.11684354048957563, 0.12243217995141002, 0.12898777452407933, 0.13709306769462395, 0.14730316674473426, 0.16012848363116053, 0.1760186547481824, 0.19534787299707895, 0.21840203162440402, 0.2453680350221016, 0.27632557819933035, 0.3112416352626698, 0.3499678295028452, 0.39224078526937556, 0.43768548652720385, 0.4858215907145997, 0.5360725711710868, 0.5877774888705724, 0.6402051263045253, 0.6925701548274782, 0.7440509531618377, 0.7938086504267827, 0.8410069331443881, 0.8848321330658052, 0.9245131019528693, 0.959340380953034, 0.988684185922485, 1.0120107556850215, 1.0288966471678993, 1.0390406087535584, 1.042272719890619, 1.0385605496486194, 1.0280121579093697, 1.0108758385336067, 0.9875365822769436, 0.9585093165335253, 0.9244290572138341, 0.8860381832922828, 0.8441711149384595, 0.7997367399375008, 0.753698988733452, 0.7070560045165487, 0.6608183901753584, 0.6159870377629519, 0.5735310577810462, 0.5343663247635917, 0.4993351423437537, 0.469187505523491, 0.44456440083951476, 0.4259835374234115, 0.4138278447393174, 0.4083370074354877, 0.4096022358519212, 0.41756439403103524, 0.4320155274462345, 0.45260375202994496, 0.4788413864085955, 0.5101161324734498, 0.5457050373980423, 0.5847909047027889, 0.6264807645523917, 0.669825965539994, 0.7138434129183349, 0.7575374524755755, 0.7999218856317591, 0.8400416001625266, 0.8769933122456945, 0.9099449389738894, 0.9381531554851753, 0.96097873655305, 0.977899337706057, 0.9885194343418031, 0.9925772072882116, 0.9899482381150325, 0.9806459553630137, 0.9648188518183121, 0.9427445710739507, 0.9148210369716175, 0.8815548702611391, 0.8435474012246302, 0.8014786435207918, 0.756089641744214, 0.7081636420291774, 0.6585065605819119, 0.6079272387054883, 0.5572179743893083, 0.507135809874838, 0.45838503208744363, 0.4116013090415204, 0.3673378411617572, 0.3260538530532073, 0.2881056899601036, 0.25374071553517213, 0.2230941353089492, 0.19618879522522992, 0.17293792868348098, 0.15315075060955577, 0.1365407250414837, 0.12273626537088873, 0.11129356540544694, 0.10171120633409877, 0.09344614080437254, 0.08593062174704465, 0.07858962113421976, 0.0708582730789911, 0.06219887683040818, 0.052117008238766534, 0.04017631281674641, 0.026011588965447315, 0.00933981536089272, -0.010031169254642171, -0.03219656394343577, -0.0571512436129066, -0.08478922802041894, -0.11490599849087563, -0.14720360459713666, -0.181298429993718, -0.21673141682947056, -0.2529804834685459, -0.2894748122675662, -0.325610634369189, -0.3607680981513321, -0.39432877815322703, -0.42569336275670555, -0.4542990521231817, -0.4796362030679129, -0.5012637745867566, -0.5188231562323108, -0.5320500007731226, -0.5407837315974401, -0.5449744529302216, -0.544687055689832, -0.5401023821080951, -0.5315153863213704, -0.519330304159835, -0.504052921413932, -0.48628010403269334, -0.4666868241432202, -0.44601098069780626, -0.4250363713130991, -0.40457422099685025, -0.38544371270672695, -0.3684519930399665, -0.3543741430688753, -0.34393360895946945, -0.33778357938264353, -0.33648977699656873, -0.3405150998937646, -0.3502065066044358, -0.3657844860394329, -0.3873353928991656, -0.4148068610432021, -0.44800643376383803, -0.48660347263009196, -0.5301343274562784, -0.5780106709405386, -0.6295308245534761, -0.6838938292282944, -0.7402159471113765, -0.7975492207369951, -0.8549016649740088, -0.9112586262217298, -0.9656048136249998, -1.0169464892806033, -1.0643332989722878, -1.106879232051602, -1.1437822185205975, -1.1743419027118922, -1.1979751754508974, -1.2142290991999312, -1.2227909221515996, -1.2234949460690003, -1.2163260871920398, -1.2014200479317645, -1.1790600974523444, -1.1496705396390556, -1.1138070254160064, -1.072143941002892, -1.0254591726740243, -0.974616610232574, -0.9205468042463718, -0.8642262348331818, -0.8066556814062321, -0.7488382025411974, -0.6917572425415482, -0.6363553762013047, -0.5835141858399937, -0.5340357353639175, -0.4886260656321943, -0.44788108478925415, -0.4122751677291829, -0.38215271195883477, -0.35772282448314086, -0.3390572377425922, -0.32609147397849386, -0.31862919862243894, -0.3163496263377264, -0.3188177700686916, -0.3254972556705667, -0.3357653640494414, -0.3489299107110423, -0.36424753045405306, -0.3809429036571647, -0.39822844093593457, -0.4153239353333438, -0.43147569580403033, -0.44597469240039517, -0.4581732718142093, -0.4675000410276327, -0.4734725657719198, -0.47570758802721563, -0.47392853145766817, -0.4679701338235092, -0.45778011927281137, -0.4434178991285707, -0.42505036544714714, -0.4029449153324971, -0.37745991390011324, -0.34903286814650003, -0.3181666411879685, -0.2854140849617771, -0.2513615083261661, -0.21661142559381621, -0.1817650471970064, -0.14740497901183297, -0.11407858976078737, -0.08228248706539971, -0.052448512626608684, -0.024931626445537272, -2.196197973710879e-16], [0.0, 0.021805994561302524, 0.04070777047140183, 0.05678500757307933, 0.07021860028848213, 0.08128526998033299, 0.09034945304280856, 0.09785267604545049, 0.10430069536040573, 0.11024873777393193, 0.116285229111372, 0.1230144385988072, 0.13103849649907656, 0.14093926072256954, 0.1532605141444205, 0.16849096808448621, 0.18704852895917726, 0.2092662549355123, 0.23538038824387766, 0.265520797650492, 0.29970410571941747, 0.3378297083939664, 0.37967882176939066, 0.42491661452616103, 0.4730974062566047, 0.5236728338076557, 0.5760028117402624, 0.6293690409849086, 0.6829907535701039, 0.7360423225927764, 0.7876723168790403, 0.8370235403230128, 0.8832535677095613, 0.9255552726650709, 0.9631768396820557, 0.9954407610635735, 1.0217613409540238, 1.041660261877566, 1.0547798136103974, 1.0608934387068272, 1.0599133122675684, 1.0518947440480473, 1.0370372670386239, 1.0156823563511417, 0.9883078036665286, 0.9555188536394553, 0.9180362875244873, 0.8766817139424025, 0.8323603953042784, 0.7860419992595802, 0.7387397161255299, 0.6914882243068402, 0.645321015202662, 0.601247606279395, 0.560231175423047, 0.5231671412445298, 0.4908631928829349, 0.4640212395337982, 0.44322170521942383, 0.4289105392937927, 0.421389249166253, 0.4208081902874213, 0.42716327130155607, 0.4402961513060482, 0.459897923338469, 0.4855161955481991, 0.5165654010123638, 0.5523400907805798, 0.592030894334248, 0.6347427689311513, 0.6795151057931584, 0.7253432180759298, 0.7712007040685459, 0.816062159858729, 0.8589257092148825, 0.8988348248162404, 0.9348989340282248, 0.966312333681876, 0.9923709809857792, 1.0124867807091495, 1.026199050806332, 1.0331829181671914, 1.0332544714545602, 1.0263725771705041, 1.0126373462263059, 0.9922853193812251, 0.9656815189716885, 0.9333085894393042, 0.895753318448571, 0.853690892176291, 0.8078672911560163, 0.7590802755995358, 0.708159440377248, 0.6559458390856753, 0.6032716834279082, 0.5509406183558387, 0.49970905525805775, 0.45026901541809383, 0.4032328948023808, 0.359120510028475, 0.3183487254218813, 0.2812238939189938, 0.24793727191536835, 0.21856349182765006, 0.19306209805662827, 0.17128207417075128, 0.1529692134272073, 0.13777611310685983, 0.1252745073502076, 0.11496959488463204, 0.10631596867859715, 0.09873471536957286, 0.09163122425584405, 0.08441322940372363, 0.07650860438894166, 0.0673824374448502, 0.056552935102302436, 0.04360573424522793, 0.02820624505112019, 0.010109699447024856, -0.010831359842093255, -0.03466234738374261, -0.061324785769157716, -0.09065738905643649, -0.1224000522790218, -0.15620064431687614, -0.19162442796451998, -0.22816586202654746, -0.2652624774822876, -0.3023104647861478, -0.3386815636123734, -0.3737408109846343, -0.4068646796637133, -0.43745912652859975, -0.4649770708058221, -0.4889348343993848, -0.508927100960677, -0.5246399861240267, -0.5358618576415436, -0.5424915998371994, -0.5445440804841335, -0.5421526483070918, -0.5355685640761928, -0.5251573458210692, -0.5113920871141352, -0.49484388468139073, -0.4761695858552487, -0.4560971357153781, -0.4354088664179856, -0.41492312560206046, -0.3954746854958597, -0.3778944082790189, -0.3629886655021116, -0.35151901933211266, -0.34418267078886183, -0.341594164985839, -0.34426881602144027, -0.3526082752215831, -0.3668886168362351, -0.38725125623287787, -0.41369694853723943, -0.44608304217587824, -0.48412408366818344, -0.5273957892064333, -0.5753423170314828, -0.6272866943600455, -0.682444175621099, -0.739938236910558, -0.7988188466489741, -0.8580825960323399, -0.9166942264001994, -0.973609055264928, -1.0277957793373074, -1.0782591220398126, -1.1240617950055767, -1.164345257888875, -1.1983487881178305, -1.225426411352172, -1.2450612934277037, -1.2568772542669147, -1.2606471321663968, -1.256297801388608, -1.243911725278546, -1.2237250092681544, -1.1961220011260625, -1.1616265676399937, -1.1208902555950493, -1.0746776185221005, -1.0238490574503247, -0.9693415821886556, -0.9121479480733673, -0.8532946604862935, -0.7938193648755324, -0.7347481528960322, -0.6770733153372812, -0.6217320597408073, -0.5695866853665599, -0.5214066710853663, -0.4778530837853145, -0.4394656571798456, -0.4066528249282042, -0.37968491935900117, -0.3586906696201394, -0.34365705267400404, -0.33443246919517605, -0.33073313610830907, -0.33215251019571496, -0.3381734847987639, -0.3481830359006989, -0.36148893640852636, -0.3773381096382059, -0.3949361559984667, -0.413467561542292, -0.4321160839981704, -0.45008481138701156, -0.4666154003445911, -0.4810060254621966, -0.4926276066868748, -0.5009379281590103, -0.5054933176186761, -0.505957619261559, -0.5021082630520166, -0.4938393082316383, -0.48116141621166364, -0.46419878625821515, -0.4431831644063273, -0.41844510994187706, -0.39040277272109924, -0.35954849683455536, -0.32643362011624494, -0.2916518834078968, -0.25582189721509807, -0.21956913560709182, -0.1835079373772695, -0.14822399236163303, -0.11425777648187228, -0.08208937291911714, -0.05212507951232379, -0.02468615497001428, -2.1669325852068894e-16], [0.0, 0.02138066408543496, 0.03981342273432394, 0.05543378542225215, 0.06847859833678917, 0.07927893062037007, 0.08825027488655536, 0.09588031886281612, 0.1027146090068086, 0.10934048278288937, 0.11636969254624639, 0.12442017947869291, 0.1340974798382655, 0.14597625730288658, 0.16058245409410615, 0.17837653986497548, 0.19973831134825346, 0.22495365811863458, 0.25420366145059614, 0.2875563353479073, 0.32496125281928756, 0.36624722802028764, 0.4111231477821858, 0.45918196623234386, 0.5099077956767046, 0.5626859476855616, 0.6168157023915368, 0.6715255132888053, 0.7259902911037988, 0.779350355207866, 0.8307315959680844, 0.8792663575433417, 0.9241145288124826, 0.9644843209550285, 0.999652213964314, 1.0289815710090193, 1.0519394487029425, 1.0681111723143135, 1.0772122967698399, 1.0790976357387578, 1.0737671106315574, 1.0613682473256947, 1.0421952289829384, 1.0166844964795099, 0.9854069716920791, 0.9490570611132655, 0.9084386759856341, 0.8644485784023583, 0.8180574288157088, 0.7702889674871656, 0.7221978091873185, 0.6748463657435859, 0.6292814339532805, 0.5865109963456364, 0.547481779023217, 0.5130580943989449, 0.48400246745090575, 0.46095850283808343, 0.4444363978477806, 0.43480144394403436, 0.43226578916151415, 0.43688365645158517, 0.4485501312093601, 0.4670035465821184, 0.49183140983753465, 0.5224797291288706, 0.5582655194737763, 0.5983921916196829, 0.6419674595256549, 0.6880233430948118, 0.7355377939722161, 0.7834574348571404, 0.8307208777611861, 0.876282074566828, 0.9191331543790584, 0.9583262164660596, 0.9929935746809299, 1.0223659884595298, 1.0457884658179066, 1.0627332839729522, 1.0728099417881671, 1.0757718335054072, 1.07151951330473, 1.0601005031642508, 1.0417056802299551, 1.0166623623957112, 0.9854242900148363, 0.9485587756800307, 0.9067313610141114, 0.8606883777826394, 0.811237858960847, 0.7592292825024938, 0.7055326555883111, 0.6510174594987923, 0.596531974697244, 0.5428834922826821, 0.4908198920554756, 0.44101302971840906, 0.3940443271903281, 0.3503929018841448, 0.31042650457675464, 0.2743954628546811, 0.24242974989192714, 0.21453921845172277, 0.19061695950952015, 0.17044566579048964, 0.15370680478163498, 0.13999233530933602, 0.12881863832518986, 0.11964227769498213, 0.11187716189793277, 0.10491264372439943, 0.0981320731390396, 0.0909313089821686, 0.08273669833100539, 0.07302204803295463, 0.06132414073814788, 0.0472563869766265, 0.03052025443904962, 0.010914174359922363, -0.011660308728641763, -0.03719530529573777, -0.0655763521755775, -0.0965851934375643, -0.12990549846652363, -0.16513136805367587, -0.20177840618255033, -0.2392970677231246, -0.27708793213890703, -0.31451850209761034, -0.350941084865677, -0.3857112846131308, -0.41820661602857, -0.44784474441296657, -0.4741008648396111, -0.4965237528724397, -0.5147500512479868, -0.5285164000668487, -0.5376690713448864, -0.5421708309215302, -0.5421048201674277, -0.5376753249452644, -0.5292053779822079, -0.517131221240198, -0.5019937350042435, -0.48442701823541473, -0.46514437829400473, -0.4449220555719112, -0.4245810681726593, -0.40496761202593884, -0.3869324914337582, -0.37131008299252083, -0.35889735138272616, -0.35043343823574363, -0.3465803350634262, -0.3479051282807584, -0.3548642691904232, -0.3677902752613479, -0.38688121223499045, -0.4121932409041626, -0.44363643942344155, -0.4809740335054211, -0.5238250847512264, -0.5716706036677155, -0.6238629706916161, -0.6796384678192918, -0.7381326472184465, -0.7983981933559725, -0.8594248734421753, -0.9201611188961162, -0.9795367393762447, -1.0364862417239586, -1.0899722096719555, -1.139008196800219, -1.1826805950840271, -1.2201689642505513, -1.250764342503372, -1.273885106141995, -1.2890900030646781, -1.2960880517083588, -1.2947450710361472, -1.2850866869336173, -1.2672977438827449, -1.2417181360173235, -1.2088351565540407, -1.169272547075596, -1.1237765062120564, -1.0731989890283418, -1.0184786921387068, -0.9606201736905332, -0.9006716005829183, -0.8397016465709417, -0.7787760835084716, -0.7189346134663084, -0.661168481715554, -0.6063993898003952, -0.5554601946706214, -0.5090778349384169, -0.4678588698875861, -0.4322779522741162, -0.4026694838155043, -0.3792226243558079, -0.3619797439362056, -0.3508383234100783, -0.34555622587173135, -0.3457601800640094, -0.3509572400772271, -0.3605489149261441, -0.3738475987141853, -0.39009487858810615, -0.40848125484038683, -0.4281667763528324, -0.4483020758238206, -0.46804928330493273, -0.4866023035929214, -0.5032059627616013, -0.517173561041474, -0.5279024125276834, -0.5348870057038134, -0.537729481142484, -0.5361471923987159, -0.5299771912851965, -0.5191775575132239, -0.5038255731157253, -0.48411282211937556, -0.46033737359488824, -0.4328932795451439, -0.40225768625910924, -0.3689759170921536, -0.3336449346564393, -0.2968956298801439, -0.2593744133497421, -0.2217246001042457, -0.1845680822302207, -0.14848777415420755, -0.1140112937050369, -0.08159630839335429, -0.05161793179694953, -0.02435850059004337, -2.1310400095194143e-16], [0.0, 0.02090612457373407, 0.03884876278114237, 0.05402085484805808, 0.06671575136217166, 0.07731835023092874, 0.08629361660585508, 0.09417278804876533, 0.10153762831024492, 0.10900314493584963, 0.11719922718586187, 0.12675169039089282, 0.13826323010100067, 0.15229479376476235, 0.1693478690645131, 0.1898481666291156, 0.21413114116261678, 0.24242974989192667, 0.27486479176422035, 0.31143810639156383, 0.3520288399500313, 0.3963929078844547, 0.444165703281911, 0.49486801718581197, 0.5479150550007432, 0.6026283535512752, 0.6582503283117793, 0.7139611117156371, 0.7688972830210145, 0.8221720394962564, 0.8728963189914228, 0.920200356312397, 0.9632551409412566, 1.0012932419658567, 1.0336284776800206, 1.0596739319508919, 1.0789578565548221, 1.0911370473799187, 1.0960073415147733, 1.093510950360746, 1.0837404193652846, 1.0669390859367174, 1.0434979915872913, 1.0139492902903806, 0.9789562803190225, 0.9393002693577392, 0.8958645604132814, 0.8496159170722859, 0.8015839292064824, 0.752838752756202, 0.7044677384217078, 0.6575514929272143, 0.6131399322644879, 0.5722288885624671, 0.535737820888198, 0.504489155617454, 0.47918974460285946, 0.4604148801081824, 0.44859524555606317, 0.4440071120011158, 0.4467660135661273, 0.45682405272638427, 0.47397090029619626, 0.49783846735322274, 0.5279091392601812, 0.5635273775266403, 0.603914415547314, 0.64818570119334, 0.6953706745918181, 0.7444344147720444, 0.7943006455046429, 0.8438755596548683, 0.8920719034531029, 0.9378327576723368, 0.9801544618811227, 1.0181081504648952, 1.0508594044055728, 1.077685569993303, 1.0979903535391577, 1.1113153683262236, 1.1173483848163004, 1.1159281156733105, 1.1070454514871728, 1.090841149108482, 1.067600060122023, 1.037742070097253, 1.001809997823615, 0.960454775851338, 0.9144182975607495, 0.8645143701282836, 0.8116082558426567, 0.7565953152239302, 0.700379283586309, 0.6438507176564467, 0.5878661405347326, 0.5332283919196746, 0.48066865667985814, 0.43083059943747154, 0.3842569769911012, 0.3413790355788701, 0.3025089278122247, 0.2678353064209162, 0.23742217070004315, 0.21121095878391052, 0.18902579666597835, 0.17058173529836612, 0.15549573212746387, 0.14330006492451164, 0.1334578054562004, 0.12537992990702415, 0.11844360326385875, 0.11201114707936893, 0.1054491848194939, 0.09814745672968725, 0.08953680685751653, 0.07910586825229474, 0.06641600781380388, 0.051114138867023415, 0.0329430661034747, 0.011749092607852334, -0.012513309376895177, -0.039779885331692674, -0.06987808434422922, -0.10253160427566921, -0.13736787644387932, -0.17392829305843438, -0.21168090865423525, -0.25003528162154975, -0.28835906527939886, -0.32599591123180116, -0.36228421217837764, -0.3965761878381743, -0.42825680680165557, -0.45676203924555764, -0.48159595049753295, -0.5023461730658944, -0.5186973342808575, -0.5304420671541075, -0.5374892922036136, -0.5398695263156625, -0.5377370495233529, -0.531368840001879, -0.5211602696282979, -0.5076176350700138, -0.4913476804763618, -0.47304434540955675, -0.4534730437072301, -0.4334528436949478, -0.4138369759183043, -0.39549213991607873, -0.37927711534000796, -0.36602120406036154, -0.35650303820504065, -0.35143028411162447, -0.35142075400444267, -0.35698540624836494, -0.36851367200210694, -0.38626149202213445, -0.4103423835553973, -0.4407217852510989, -0.4772148495707431, -0.519487769197061, -0.5670626384674748, -0.6193257649836487, -0.6755392623864234, -0.734855674908248, -0.7963353097066241, -0.8589658859869195, -0.921684052202344, -0.9833982756077227, -1.0430125733164242, -1.09945053164998, -1.1516790515488777, -1.198731262375378, -1.239728064496065, -1.2738977921638346, -1.3005935316848913, -1.319307684612454, -1.329683430433743, -1.3315228163439883, -1.3247912814574505, -1.3096185072545714, -1.2862955731544712, -1.2552684837163444, -1.217128219981846, -1.1725975497829244, -1.1225149084558859, -1.0678157304630511, -1.0095116722540096, -0.9486682158517077, -0.8863811799395966, -0.8237526897606354, -0.761867168336828, -0.7017679091256882, -0.6444347743273108, -0.5907635340538492, -0.5415473202036762, -0.49746061617927206, -0.45904614086186984, -0.4267049140616552, -0.40068971276026255, -0.3811020447743855, -0.36789268103216105, -0.36086570156774667, -0.359685925716528, -0.3638895159058416, -0.3728974688647434, -0.38603163986185585, -0.4025328863779915, -0.42158086885911084, -0.4423150090432606, -0.46385608169073467, -0.4853279039370948, -0.5058785881765948, -0.5247008392815876, -0.5410508046568866, -0.5542650253852073, -0.5637750875114278, -0.5691196330380037, -0.5699534589207447, -0.5660535075223656, -0.5573216317023952, -0.5437840999890048, -0.5255878900239287, -0.5029938996217559, -0.4763672823087565, -0.4461651861683591, -0.412922239427344, -0.37723418186307006, -0.3397400864193607, -0.3011036492699798, -0.2619940481362419, -0.22306687743096285, -0.18494566456848094, -0.1482044546807207, -0.1133519214663017, -0.08081742073913382, -0.05093935149301236, -0.023956128283113613, -2.0893268024778127e-16], [0.0, 0.02039294675687974, 0.03783638260468888, 0.05258167991574526, 0.0649786098155444, 0.07546472596708281, 0.08455223073303332, 0.09281267077342581, 0.10085986654481195, 0.1093315272651091, 0.1188700384911216, 0.1301029326070934, 0.14362356263889794, 0.15997249661363944, 0.17962013323735415, 0.20295101035656235, 0.23025023621904275, 0.2616924209781289, 0.29733342349683817, 0.3371051578556642, 0.38081362681342923, 0.42814026774292496, 0.47864661230913097, 0.531782176491695, 0.5868954146036304, 0.643247491814707, 0.7000285563496818, 0.7563761268563286, 0.8113951540966959, 0.8641792705482808, 0.9138327078852896, 0.9594923415240943, 1.0003493140237967, 1.035669695362907, 1.0648136578584062, 1.0872526763096944, 1.1025843090671257, 1.110544172065986, 1.111014784074039, 1.1040310358687409, 1.0897821169754378, 1.0686098189832782, 1.0410032222195411, 1.0075898605506879, 0.9691235451250076, 0.9264691098561362, 0.8805844173440339, 0.8325000318615767, 0.783297024314946, 0.734083421263492, 0.6859698449793894, 0.6400449132592311, 0.5973509757108061, 0.5588607573071381, 0.5254554602468217, 0.4979048420445537, 0.4768497420864228, 0.4627874717181388, 0.4560604156700657, 0.4568481168884813, 0.4651630344739985, 0.4808500774251287, 0.5035899273613033, 0.5329060735313416, 0.5681753953851565, 0.6086420439382245, 0.6534342951322091, 0.7015839782855695, 0.7520480222349016, 0.8037316123551453, 0.8555124145063701, 0.9062652979771959, 0.9548869792475145, 1.000320012106745, 1.0415755672268097, 1.077754475250429, 1.1080660510364935, 1.1318442718177084, 1.1485609473028706, 1.1578355935807043, 1.159441803230677, 1.153309989332884, 1.1395264689951288, 1.118328940420842, 1.0900984942587122, 1.0553483828819992, 1.0147098483185, 0.9689153789152369, 0.9187798247933101, 0.8651798512816975, 0.8090322466385997, 0.7512716245993327, 0.6928280730756465, 0.634605297451748, 0.5774597904951158, 0.5221815313792534, 0.4694766744780983, 0.4199526355195504, 0.3741059197366369, 0.33231296542998345, 0.29482419865769166, 0.2617614125587109, 0.23311850016201965, 0.20876548456147018, 0.18845570717357424, 0.17183595552206837, 0.1584592385864227, 0.14779985203888168, 0.13927031930743244, 0.13223974873510108, 0.12605311328303753, 0.12005093807092651, 0.11358887306923154, 0.10605663362800032, 0.09689581008525691, 0.0856160789519265, 0.0718093913087276, 0.055161767964228975, 0.03546239423294341, 0.012609778282987896, -0.013385185935319401, -0.042399329094772426, -0.0742004851192846, -0.10845385005323119, -0.1447312525806603, -0.18252309129996003, -0.2212526238025817, -0.2602922305753502, -0.2989812243250534, -0.33664473385030735, -0.3726131621232869, -0.406241701554923, -0.43692938594291186, -0.4641371684512907, -0.4874045379170496, -0.5063642212672679, -0.5207545669871869, -0.5304292622386623, -0.5353641029569927, -0.5356606103895075, -0.5315463672301992, -0.5233720297569361, -0.5116050571044328, -0.4968202828791761, -0.47968753562604927, -0.4609565911397584, -0.4414398093426725, -0.42199286965475274, -0.4034940698998843, -0.3868226935139441, -0.3728369771120719, -0.3623522246123238, -0.35611961470240544, -0.35480623541413303, -0.35897685321358275, -0.3690778849325207, -0.3854239899849541, -0.40818763885270154, -0.43739194327190956, -0.47290695562317364, -0.5144495616224928, -0.5615870035692608, -0.6137439832608436, -0.6702132063974862, -0.7301691460257795, -0.792684723383329, -0.8567505323694498, -0.9212961705641977, -0.9852131868245699, -1.047379114321572, -1.1066820294787354, -1.1620450623526748, -1.2124502829502903, -1.2569614008562426, -1.2947447420570384, -1.3250880063691777, -1.3474163604624807, -1.3613054838743224, -1.366491257127755, -1.3628758603592424, -1.35053013580612, -1.3296921560369896, -1.300762029778468, -1.26429306641195, -1.220979506515258, -1.171641107108854, -1.117204944560248, -1.0586848636006083, -0.9971590560276407, -0.9337462960763715, -0.869581390090615, -0.8057904152908147, -0.7434663257087911, -0.6836454926867961, -0.6272857229991752, -0.5752462602669255, -0.5282702258343361, -0.4869698948944874, -0.45181513388396627, -0.4231252477417902, -0.40106440245388786, -0.38564070143104123, -0.3767089058310888, -0.37397670110581765, -0.3770143269808334, -0.3852673078421501, -0.39807194706214766, -0.41467318393422165, -0.43424435716882975, -0.45590837564856784, -0.47875976637527634, -0.5018870519856244, -0.5243949062523477, -0.545425545677887, -0.5641788383388454, -0.5799306469359276, -0.5920489706122889, -0.6000075082999271, -0.6033963336546638, -0.6019294463379982, -0.5954490446112038, -0.5839264479024142, -0.567459683087988, -0.5462678325612987, -0.5206823236350994, -0.49113541540277306, -0.45814620896075375, -0.42230456813448297, -0.38425338903565126, -0.3446696966459892, -0.3042450741949885, -0.26366594570822977, -0.22359423340838358, -0.1846488996457118, -0.14738885804702168, -0.11229770125535891, -0.07977064395034841, -0.05010402103942172, -0.023487613495028595, -2.0426928051054333e-16], [0.0, 0.01985246688010141, 0.03680009742378555, 0.05115306622391169, 0.0633168248252045, 0.07377974840110432, 0.08309839515670903, 0.09188076911518828, 0.1007680298865027, 0.11041513463773125, 0.12147092671657464, 0.13455820146778252, 0.15025428230092508, 0.1690726289329714, 0.19144597520005247, 0.21771145650645543, 0.24809813777488104, 0.2827172928998012, 0.32155571767455254, 0.36447228168444823, 0.41119784264438003, 0.46133856116400257, 0.5143825670916238, 0.5697098426018194, 0.6266051042170889, 0.6842733880850564, 0.7418579720408142, 0.7984602060672634, 0.8531607713050608, 0.905041848080814, 0.953209646549223, 0.9968167401967469, 1.0350836430103532, 1.0673190856091954, 1.0929384737569108, 1.111480053765758, 1.1226183623951267, 1.1261746026603017, 1.1221236599581472, 1.1105975533090415, 1.0918852023462549, 1.0664284798534232, 1.0348146099692186, 0.9977650614242947, 0.9561211711494613, 0.910826814172796, 0.862908508912832, 0.813453410959462, 0.7635857016215887, 0.7144419185817578, 0.6671458039001192, 0.622783258642191, 0.582377993195871, 0.5468684478711805, 0.5170865299696203, 0.49373867183940356, 0.477389660494825, 0.4684496244711482, 0.4671644892788014, 0.47361013091234516, 0.48769036934758947, 0.5091388529499902, 0.5375247924308137, 0.5722624116681047, 0.6126238945774518, 0.6577555244152409, 0.7066966364360581, 0.7584009385378382, 0.8117596990194815, 0.8656262571880153, 0.9188412823302287, 0.9702581902284477, 1.0187681243324247, 1.0633239209300898, 1.1029625038697104, 1.1368251939130485, 1.1641754696561262, 1.1844137798525165, 1.1970890793561875, 1.2019068409786693, 1.1987333813543957, 1.1875964283169098, 1.1686819481104946, 1.1423273407692112, 1.1090111989849434, 1.069339907633163, 1.0240314358358127, 0.9738967392012454, 0.9198192451021571, 0.8627329372083911, 0.8035995859525135, 0.7433856884635949, 0.683039684388043, 0.6234700029018664, 0.5655244714293125, 0.509971578779925, 0.4574840355821676, 0.40862501430620873, 0.363837381374564, 0.32343615662599773, 0.28760435267555706, 0.2563922605842404, 0.22972016087862038, 0.20738435253297763, 0.18906630920526105, 0.1743446938827294, 0.16270989208873904, 0.15358066169219287, 0.1463224456830911, 0.1402668543048193, 0.13473179564421886, 0.12904171983237325, 0.12254744172492815, 0.11464502028965218, 0.10479319956716772, 0.09252895529134811, 0.07748074204626634, 0.059379096894133315, 0.03806432517362526, 0.013491070862490186, -0.014270344428853637, -0.045035845190424965, -0.07851273449984417, -0.11430789737214768, -0.1519388567042968, -0.19084738875340534, -0.23041533777904144, -0.2699822113684146, -0.3088640905304674, -0.3463733531040676, -0.38183868629119777, -0.4146248547906693, -0.4441516953271348, -0.46991182625609423, -0.49148659194859445, -0.5085598050589735, -0.5209289044823071, -0.528513211456696, -0.5313590392486374, -0.5296414913549713, -0.5236628671733544, -0.5138476805287892, -0.5007343831260141, -0.48496396974568173, -0.46726572267950395, -0.4484404274668565, -0.42934145856200445, -0.4108541904327266, -0.3938742353112723, -0.3792850422065277, -0.3679354119657714, -0.3606174895967305, -0.35804578751832355, -0.36083777204115847, -0.3694965106702596, -0.38439583058903193, -0.40576838005435983, -0.43369691582254194, -0.46810906279964537, -0.5087757087427326, -0.5553131090687536, -0.6071886868073384, -0.6637304226742777, -0.7241396423615469, -0.7875069246051749, -0.8528307764693607, -0.9190386534847247, -0.9850098435094605, -1.0495996859100767, -1.1116645630675521, -1.1700870801800982, -1.223800842397908, -1.271814245685365, -1.3132327193086795, -1.3472788929905166, -1.3733102097221117, -1.3908335648261638, -1.3995166216829669, -1.3991955328783712, -1.3898788805060618, -1.371747738895534, -1.3451518549658037, -1.3106020334886053, -1.2687589045449703, -1.2204183361874623, -1.1664938346937646, -1.1079963458881608, -1.0460119320914427, -0.9816778488583399, -0.9161575825776489, -0.8506154333587048, -0.7861912368554349, -0.7239758135800405, -0.6649877149769139, -0.6101518025557344, -0.5602801505482029, -0.5160557049969341, -0.4780190643350514, -0.4465586700493013, -0.4219046128249049, -0.4041261716962965, -0.39313311333507306, -0.38868068791403404, -0.39037816921627017, -0.3977007019816427, -0.41000414096537835, -0.426542495734574, -0.4464875345549367, -0.46895005128409384, -0.493002262170494, -0.5177007757302121, -0.5421095689790657, -0.5653224074321078, -0.5864841642966058, -0.6048105256843229, -0.6196056126296839, -0.6302771060875962, -0.6363485264827298, -0.6374683931294588, -0.6334160690730143, -0.6241041815952418, -0.6095775956530706, -0.5900090046917854, -0.5656912884160692, -0.5370268680831114, -0.5045143646850628, -0.46873293215272904, -0.4303246947830874, -0.38997576406016266, -0.3483963437729118, -0.30630045301432746, -0.2643858037811228, -0.22331436333198054, -0.18369411139725642, -0.1460624692963723, -0.11087183286840595, -0.07847758501769297, -0.049128898055488764, -0.0229625625549281, -1.992122277649548e-16], [0.0, 0.01929666679859876, 0.0357646851569261, 0.04977274589761116, 0.06178057227754399, 0.07232486603059685, 0.08200302727872599, 0.09145508084031795, 0.10134428917593416, 0.1123369676540115, 0.1250820400812779, 0.14019088094473475, 0.15821798532024545, 0.17964298803541418, 0.20485452089933853, 0.23413635143470368, 0.26765618969235344, 0.3054574828088516, 0.34745444165262673, 0.3934304620765583, 0.44304001700344525, 0.49581400698036887, 0.5511684681747973, 0.6084164502816214, 0.6667827946486463, 0.7254214671865672, 0.7834350332298817, 0.8398958041748473, 0.8938681399090197, 0.9444313579491579, 0.990702680690605, 1.0318596467753802, 1.0671614214911374, 1.0959684641463932, 1.1177600470045403, 1.1321491697363664, 1.1388944742858664, 1.1379088360652476, 1.129264386776926, 1.113193809966637, 1.0900878405428225, 1.060488991741958, 1.0250816251091381, 0.9846785687289924, 0.9402045739699022, 0.8926769792908236, 0.8431840192631986, 0.7928612761493942, 0.7428668186761593, 0.6943556068593023, 0.6484537620065546, 0.6062333068234389, 0.5686879717007501, 0.5367106399603598, 0.5110729676219318, 0.49240766301227656, 0.48119384947735044, 0.4777458620713298, 0.48220574813881056, 0.49453965413762097, 0.5145381889965456, 0.5418207600009458, 0.5758437829422237, 0.6159125763461885, 0.6611966622456917, 0.7107481153075926, 0.7635225301223364, 0.8184021148632015, 0.8742203698132629, 0.9297877726415419, 0.9839178696644302, 1.0354531641905502, 1.083290199597262, 1.1264032558456119, 1.1638661131729928, 1.1948713848324417, 1.218746980777874, 1.2349693346384762, 1.2431731054427457, 1.2431571513924191, 1.2348866634361368, 1.2184914392295079, 1.1942603710149675, 1.1626323117354105, 1.1241835700915657, 1.079612365158285, 1.029720642647134, 0.9753937162117454, 0.9175782468622765, 0.8572591104006343, 0.7954357259427387, 0.7330984275322532, 0.6712054553990099, 0.6106611237585368, 0.5522956887217234, 0.4968473937588512, 0.44494711242815954, 0.39710594020994594, 0.3537060110052654, 0.31499473109138404, 0.28108253615913636, 0.25194418767995214, 0.22742353550282868, 0.20724158649847035, 0.19100763642260846, 0.1782331460214128, 0.16834797464050408, 0.16071852690371566, 0.15466732182165352, 0.1494934601061835, 0.14449344531993455, 0.13898180825614181, 0.13231099175022262, 0.12388997474428609, 0.11320114928650547, 0.09981501134403398, 0.08340228462688638, 0.06374316456825024, 0.04073344545044328, 0.014387375474056286, -0.015162829739362511, -0.047670797320240925, -0.08278302621967557, -0.12004894622201605, -0.1589337386314027, -0.19883357791275444, -0.23909288982832919, -0.2790231682045262, -0.31792285075300253, -0.3550977254242562, -0.38988132333869285, -0.42165475282785647, -0.44986544158499314, -0.4740442800754381, -0.49382069855466654, -0.5089352613175887, -0.5192494238838484, -0.5247521701643266, -0.5255633254724239, -0.5219334255680295, -0.5142401096389426, -0.5029810940314481, -0.4887638714025887, -0.47229236456711615, -0.45435084351505395, -0.4357854858751305, -0.4174840236696149, -0.4003539709490637, -0.38529996647941955, -0.3732007920481027, -0.3648866394557858, -0.3611171975069964, -0.36256111430014254, -0.3697773601955375, -0.383198973704685, -0.403119617221627, -0.4296833033386663, -0.4628775770576802, -0.5025303563610587, -0.5483105453672673, -0.5997324428273783, -0.6561638762672504, -0.7168379009212208, -0.7808678149856552, -0.8472651608098792, -0.9149603074670649, -0.9828251455505415, -1.0496973716309077, -1.1144057989234508, -1.1757961033839193, -1.2327564013730776, -1.284242056556132, -1.3292991298234937, -1.3670859163675804, -1.3968920579094721, -1.4181547743907656, -1.430471826873926, -1.4336109003000586, -1.4275151792735932, -1.4123049801286052, -1.3882753959935255, -1.3558900061384735, -1.3157707942630594, -1.2686845102919253, -1.215525794504515, -1.157297459387274, -1.0950883916017733, -1.0300495922868074, -0.9633689172063241, -0.8962451079752073, -0.8298617210321528, -0.765361561823191, -0.7038222178107102, -0.6462332557891696, -0.5934756072777533, -0.5463036115121693, -0.5053301201184361, -0.4710149925394773, -0.4436572285521294, -0.42339089579565625, -0.41018491830751974, -0.4038466988848168, -0.40402945594434714, -0.4102430666948088, -0.42186812503019305, -0.43817284663453643, -0.4583323871965782, -0.4814500839766454, -0.5065800875820408, -0.5327508207201808, -0.5589886846088313, -0.5843414319803191, -0.6079006382161101, -0.6288227287289373, -0.6463480605655159, -0.6598176082998295, -0.6686868672895415, -0.6725366596731505, -0.6710806082621953, -0.6641691287183802, -0.6517898789562203, -0.6340646943553284, -0.6112431258589089, -0.5836927831649756, -0.5518867648622504, -0.5163885295423172, -0.47783462484290923, -0.4369157434886348, -0.39435661541289957, -0.35089527199150666, -0.307262231646814, -0.26416015528902215, -0.22224450529823628, -0.18210571341794682, -0.14425332176886804, -0.1091025082644954, -0.07696334437377789, -0.048033061050361626, -0.022391519570019596, -1.9386738893974302e-16], [0.0, 0.018738044529636785, 0.034755610372814806, 0.048478945043960185, 0.06041996157530632, 0.07116054102562398, 0.08133480028321591, 0.09160979729250576, 0.10266518757791795, 0.115172374542572, 0.12977371074404184, 0.14706230780562038, 0.16756299877881872, 0.1917149689608859, 0.21985653007161882, 0.25221245932348874, 0.2888842606049414, 0.32984363134244804, 0.37492933745340246, 0.42384761218145683, 0.476176104691174, 0.5313713133491303, 0.5887793489231298, 0.6476497867520397, 0.707152286454354, 0.7663955849941163, 0.8244484057590964, 0.8803617743432182, 0.9331921923017835, 0.9820250942925713, 1.025998002420565, 1.0643227946071676, 1.0963065213814982, 1.1213702372541805, 1.1390653580413959, 1.149087113081655, 1.151284729842615, 1.1456680662876786, 1.1324104916644857, 1.1118479070040368, 1.084473890357668, 1.0509310463452486, 1.0119987326126405, 0.9685774250033787, 0.9216700664319114, 0.8723608195412951, 0.8217917083699685, 0.7711376878152283, 0.7215807203225445, 0.6742834659229843, 0.6303632038003517, 0.5908666006685374, 0.5567459234184611, 0.5288372611599362, 0.5078412757005482, 0.49430694077331444, 0.4886186603608536, 0.49098707695629484, 0.5014437934756357, 0.5198401399063145, 0.5458500198920346, 0.5789767756448594, 0.6185639141962636, 0.663809446368779, 0.7137835041972442, 0.7674488249353641, 0.8236836221336863, 0.8813063082099893, 0.9391014898088584, 0.9958466281032741, 1.0503387417236427, 1.101420530545453, 1.1480053140942996, 1.1891002084380649, 1.2238270093753996, 1.251440306403921, 1.271342419956719, 1.2830948320512705, 1.2864258658862906, 1.2812344609473536, 1.267589984604607, 1.245728116688843, 1.216042937776419, 1.1790754425949335, 1.135498784868065, 1.0861006369839699, 1.0317631152286193, 0.9734407773483794, 0.9121372425526226, 0.8488810137109005, 0.7847010967543944, 0.7206030128295255, 0.6575457846089633, 0.5964204497414953, 0.5380306124696638, 0.48307549004910355, 0.4321358451583263, 0.3856631206560219, 0.3439720107177526, 0.30723661464032853, 0.27549022864551675, 0.2486287391254284, 0.22641749024880062, 0.2085014119501293, 0.1944181132167352, 0.18361357228793945, 0.1754599917018694, 0.1692753336412752, 0.16434401102922375, 0.15993818328277695, 0.15533909318298542, 0.1498578832435076, 0.14285534617755885, 0.13376009413462586, 0.12208467451793861, 0.10743921528704121, 0.0895422482836631, 0.06822843361630188, 0.04345298960089302, 0.0152927191090462, -0.016056387772877483, -0.050284905382340324, -0.08697892137219256, -0.12563194221703844, -0.1656594372844352, -0.20641563415721043, -0.24721211853862485, -0.2873377441387103, -0.326079322652577, -0.36274254220640045, -0.3966725550300885, -0.42727368182773884, -0.4540277012079278, -0.47651022709838936, -0.4944047244517642, -0.5075137725755041, -0.5157672546196597, -0.5192272294035375, -0.5180893259134136, -0.5126805893495701, -0.503453798318979, -0.4909783633785389, -0.4759280053501429, -0.45906549542576236, -0.44122481594222185, -0.42329116887985985, -0.40617931688827125, -0.3908107874844772, -0.37809050381659337, -0.3688834241765041, -0.3639917767611183, -0.36413346586629325, -0.36992220095714995, -0.3818498614595371, -0.40027155857196667, -0.4253937921414065, -0.45726602720947046, -0.49577593300337447, -0.540648438916386, -0.5914486695560487, -0.6475887265056215, -0.7083381903686471, -0.7728381252684124, -0.8401182815117836, -0.9091171127415053, -0.9787041535635903, -1.047704244098161, -1.1149230406513246, -1.1791732179313794, -1.2393007487931578, -1.2942106428976992, -1.342891536064069, -1.3844385472416192, -1.4180738593572955, -1.4431645328576443, -1.4592371253077665, -1.4659887653726287, -1.4632944130767407, -1.4512101283903251, -1.4299722647354915, -1.3999926006473598, -1.3618495192131865, -1.3162754387031825, -1.2641407867191945, -1.2064348920598085, -1.1442442413437193, -1.0787286094791797, -1.0110956228128984, -0.9425743500352749, -0.874388537789745, -0.8077301149145832, -0.7437335811821586, -0.6834518735094004, -0.6278342654724428, -0.577706805495095, -0.5337557365478811, -0.49651426713875135, -0.46635298160124516, -0.4434740892055649, -0.42790961860857746, -0.4195235689041428, -0.4180179333703805, -0.4229424192645284, -0.4337075989538568, -0.4496011464382265, -0.46980674088942115, -0.4934251569564631, -0.5194970117530643, -0.54702660184113, -0.5750062410114154, -0.6024405017477742, -0.628369770091389, -0.6518925449772841, -0.6721859484193401, -0.6885239612497493, -0.7002929592311853, -0.7070041947219544, -0.7083029479023332, -0.7039741568737552, -0.6939444255745082, -0.6782804001664747, -0.6571835960400165, -0.630981846572497, -0.6001176290405893, -0.565133600531278, -0.5266557453992388, -0.48537459407950617, -0.4420250194489841, -0.39736515030319386, -0.3521549610686152, -0.30713510214659345, -0.26300652618158715, -0.2204114423251844, -0.17991609384239068, -0.14199580513163287, -0.10702268367239431, -0.075256292124344, -0.04683752757294884, -0.021785860740657765, -1.8834696688469665e-16], [0.0, 0.018189476666292146, 0.033798735767955376, 0.04730993852561034, 0.059284435807022154, 0.07034550480902858, 0.08115927186281155, 0.09241433028802011, 0.10480059729789842, 0.11898797511110246, 0.13560538810610318, 0.15522075987499737, 0.17832247157827896, 0.20530280661845682, 0.23644383723732304, 0.2719061474270951, 0.31172071505591536, 0.355784196130084, 0.4038577676516881, 0.45556959474976577, 0.5104208949465887, 0.5677954799038162, 0.6269725651086812, 0.6871425529788471, 0.7474254169385638, 0.8068912451283462, 0.8645824443136528, 0.9195370587468898, 0.970812626399564, 1.0175099769719276, 1.0587963729045844, 1.0939274063904454, 1.1222670918738322, 1.1433056341173287, 1.156674405654687, 1.1621577330393302, 1.1597011671549533, 1.1494159971311868, 1.131579858044071, 1.1066333773567203, 1.075172901641212, 1.0379394411397862, 0.9958040628021183, 0.9497500502738665, 0.9008522297325321, 0.8502539314715247, 0.7991421169520059, 0.7487212481770236, 0.7001865095056591, 0.654697010567963, 0.6133496022766072, 0.5771539259439159, 0.5470092884650235, 0.5236839150514465, 0.5077970760814086, 0.49980451759185957, 0.4999875473890406, 0.508446042575606, 0.5250955515716708, 0.5496685666955408, 0.5817199444245307, 0.6206363519829695, 0.6656495232983333, 0.7158530169529782, 0.7702220857369053, 0.8276361937942696, 0.8869036549403018, 0.9467878160190064, 1.0060341733766482, 1.0633977895021507, 1.117670371131225, 1.1677063797503826, 1.2124475702169268, 1.250945392507849, 1.2823807444455435, 1.3060806283118738, 1.321531339946732, 1.3283879033665729, 1.3264795550542507, 1.3158111776245982, 1.296560680215958, 1.2690724203040784, 1.2338468563007445, 1.1915267099746076, 1.1428800002325534, 1.088780383124012, 1.0301852953052588, 0.9681124481272203, 0.9036152557995841, 0.8377578028867443, 0.7715899632172666, 0.7061232740195987, 0.642308145987714, 0.5810129526531862, 0.5230054918673868, 0.4689372496781259, 0.41933082401116334, 0.3745707841845125, 0.3348981544451924, 0.30040861763293986, 0.2710544410530159, 0.24665003303326435, 0.22688094778640752, 0.2113160703607127, 0.1994226347743146, 0.19058365884142597, 0.1841173204317122, 0.17929775340271292, 0.1753767083451249, 0.17160550438006222, 0.16725669398694135, 0.16164487329338934, 0.15414609512821256, 0.14421538076711693, 0.13140187768592582, 0.11536127345543319, 0.09586514855774167, 0.0728070315222176, 0.04620500631743683, 0.01620081219347379, -0.016944532145858424, -0.05285845737588805, -0.09106771514257081, -0.13101210001054908, -0.17206065472177626, -0.2135299264824022, -0.2547037878262438, -0.29485429388158607, -0.33326301966194566, -0.36924230703835753, -0.40215585170010243, -0.43143807567392656, -0.45661176048221525, -0.4773034590526484, -0.49325625997873407, -0.5043395442909865, -0.5105554508705248, -0.5120418501198962, -0.5090717144076223, -0.5020488658915633, -0.49150017528625606, -0.47806437662932477, -0.4624777508131103, -0.4455570123611662, -0.4281798075724299, -0.4112632958538168, -0.39574133818444024, -0.38254085585757447, -0.3725579479051551, -0.3666343662456068, -0.36553494329351705, -0.369926547585367, -0.38035910933612754, -0.3972492105347087, -0.4208666743413919, -0.4513245176109857, -0.48857255005387545, -0.5323948158220628, -0.5824109803157469, -0.6380816690301048, -0.6987176686628506, -0.763492805862259, -0.8314602282559402, -0.9015717280092485, -0.9726996722130407, -1.0436610387839826, -1.1132430029156322, -1.1802294787918441, -1.2434279952875884, -1.3016962734056516, -1.353967877533474, -1.399276332178504, -1.4367771302047234, -1.4657671069354192, -1.4857007156515936, -1.496202812529969, -1.4970776411773694, -1.4883137966409574, -1.4700850439297226, -1.442746964360631, -1.4068295020540553, -1.363025580239746, -1.3121760503288746, -1.2552513236907683, -1.1933301146296054, -1.1275757912784885, -1.059210887360344, -0.989490370645828, -0.9196742924338395, -0.851000455808747, -0.7846577384784341, -0.7217606887328654, -0.6633259809243764, -0.6102512706617936, -0.5632969307783338, -0.5230710785415058, -0.4900182242640223, -0.464411783426405, -0.4463506008001313, -0.4357595381637089, -0.43239407940880775, -0.4358488105333142, -0.4455695395659036, -0.4608687351162802, -0.48094388409613076, -0.504898301101463, -0.5317638656280499, -0.560525120056224, -0.5901441322115502, -0.6195855119555893, -0.647840971991316, -0.6739528388121687, -0.6970359500423141, -0.71629741850864, -0.7310538001129577, -0.7407452704857653, -0.7449464927761715, -0.7433739438109249, -0.735889556101185, -0.7225006265224698, -0.7033560366026828, -0.6787389218727727, -0.6490560163570649, -0.6148239807997481, -0.5766530975921739, -0.5352287797415661, -0.49129139401816374, -0.44561493834017524, -0.39898513953426096, -0.35217754922227806, -0.3059362124749994, -0.26095346615250703, -0.21785139199772857, -0.17716540439681566, -0.13933039543394726, -0.10466979191834891, -0.07338780218404574, -0.045565046617636634, -0.021157677189233382, -1.8276830316432254e-16], [0.0, 0.017664074162931743, 0.032920024389761146, 0.0463035970926227, 0.05842217021430568, 0.06993602213500377, 0.08153803568638836, 0.09393237967312014, 0.10781273805523818, 0.12384067009375932, 0.14262468295860578, 0.1647005815714129, 0.190513629210503, 0.2204030074119573, 0.25458900607678975, 0.29316330587635225, 0.336082636756337, 0.38316601053469707, 0.434095634422795, 0.4884215180624531, 0.5455696917355219, 0.604853860159925, 0.6654902270915637, 0.7266151430625665, 0.7873051541071171, 0.8465989651541851, 0.9035207795455178, 0.9571044372155538, 1.0064177494663171, 1.050586418648461, 1.0888169367106464, 1.1204178774144709, 1.1448190325637024, 1.1615878920297757, 1.1704430294881452, 1.171264029111611, 1.1640976712149482, 1.149160184990063, 1.1268354718045033, 1.097669300716937, 1.0623595764739175, 1.0217428768598977, 0.9767775484882465, 0.9285237356597683, 0.8781207936521748, 0.8267626038269916, 0.7756713615984056, 0.726070448251797, 0.6791570228140135, 0.6360749800093936, 0.5978889145091633, 0.5655597103056047, 0.5399223376070956, 0.5216663890172085, 0.51131982314127, 0.5092363086883228, 0.5155864774187318, 0.5303533019795253, 0.5533317170103477, 0.5841325012647851, 0.6221903373213987, 0.6667758662167717, 0.7170114594338299, 0.7718903424313099, 0.8302986244508721, 0.891039720617919, 0.9528605960288727, 1.014479218955947, 1.0746125825273396, 1.1320046419210417, 1.1854535175299987, 1.233837333615655, 1.27613809618333, 1.3114630623331853, 1.3390631149616055, 1.358347729886984, 1.3688962054463434, 1.3704649153127197, 1.3629904414888678, 1.3465885437797254, 1.321549022099994, 1.2883266262865194, 1.2475282622572177, 1.1998968310946359, 1.14629211680096, 1.0876692071556544, 1.0250549886521252, 0.9595232995439685, 0.8921693535778337, 0.8240840603727949, 0.7563288663450577, 0.6899117226741381, 0.625764754543854, 0.5647241596168263, 0.5075128046081052, 0.4547259184207117, 0.4068202003787676, 0.3641065746608007, 0.3267467292965776, 0.29475348237249827, 0.26799492178911916, 0.24620217043477738, 0.22898053833620258, 0.21582373946560476, 0.20613077550434056, 0.19922502384963167, 0.19437501410375782, 0.19081633750320953, 0.18777410819251916, 0.1844853845298342, 0.1802209629618561, 0.174305976279422, 0.1661387617423124, 0.1552075117625525, 0.14110427934067304, 0.12353598073245162, 0.1023321170886616, 0.07744902303710419, 0.0489705411711981, 0.017105114860639894, -0.017820614665244733, -0.055371529765098515, -0.0950168125261748, -0.13614543192082362, -0.17808392729111427, -0.22011601309616508, -0.26150348164804077, -0.30150784575241985, -0.3394121426524531, -0.3745423149813998, -0.40628759372183915, -0.4341193322290431, -0.45760777861406116, -0.47643632525123614, -0.4904128375940789, -0.4994777382695438, -0.5037086047275451, -0.503321127487228, -0.49866636901572486, -0.4902243581607936, -0.4785941494464477, -0.4644805680490894, -0.4486779475875333, -0.4320512467958927, -0.4155150006964823, -0.40001062027449913, -0.38648260037643684, -0.3758542274228347, -0.36900339569889606, -0.366739142984993, -0.3697795030114129, -0.37873124394696905, -0.3940720195123919, -0.41613540335838695, -0.4450992094103793, -0.48097742260369064, -0.5236159777212459, -0.572692531021312, -0.6277202722871704, -0.6880557262306721, -0.7529103942701038, -0.8213659929979386, -0.8923929565002566, -0.9648717882987645, -1.0376167770829212, -1.1094015303711535, -1.1789857332915858, -1.2451425069894717, -1.3066857235876093, -1.3624966326130525, -1.4115491674428242, -1.4529333293124527, -1.4858760900957733, -1.5097593123634745, -1.5241342547858465, -1.5287323110850193, -1.5234717195247378, -1.5084600751994532, -1.4839925768361946, -1.4505460410355573, -1.408768817390942, -1.3594668352927914, -1.3035861050779163, -1.2421920802889648, -1.1764463621203491, -1.1075812898397661, -1.036873010567565, -0.9656136570703158, -0.8950832823315427, -0.8265222041247389, -0.761104401538432, -0.6999125786816268, -0.6439154693009923, -0.5939479007998076, -0.5506940685299772, -0.5146743929015783, -0.4862362447486914, -0.46554873064788765, -0.4526016318088829, -0.4472084901503406, -0.4490137356862002, -0.4575036528107953, -0.47202089183933604, -0.49178214845396395, -0.5158985595552058, -0.5433983012154749, -0.5732508244832403, -0.6043921288815309, -0.6357504524214064, -0.6662717512792915, -0.6949443520559947, -0.7208221844518282, -0.7430460415895518, -0.7608623680706961, -0.7736391408059692, -0.7808784830646299, -0.7822257361329406, -0.7774748033425517, -0.7665696757553362, -0.7496021451027653, -0.7268058052676711, -0.6985465362765658, -0.6653097521349104, -0.6276847737159013, -0.5863467583276725, -0.5420366767964201, -0.49553987545970274, -0.4476637932302985, -0.3992154220790663, -0.3509791024744984, -0.30369523346296123, -0.2580404505103521, -0.21460978365527758, -0.17390125499857884, -0.13630330945136424, -0.1020853976501948, -0.07139194693761164, -0.044239867412493014, -0.020519647537537572, -1.7725260152674147e-16], [0.0, 0.01717503309098846, 0.03214523595619006, 0.045496932042012765, 0.0578794759190432, 0.06998517230337893, 0.08252790571436458, 0.09622105282698566, 0.11175526940568964, 0.1297767483618177, 0.15086653482651174, 0.17552145842776293, 0.20413720283638603, 0.2369939790970327, 0.27424520362178034, 0.3159095056360111, 0.36186630423480504, 0.4118551041559347, 0.4654785641902389, 0.5222092952265438, 0.5814002487088329, 0.6422984631970139, 0.704061849124137, 0.7657786119538925, 0.8264888437953614, 0.8852077549202545, 0.9409499710591389, 0.9927542910124778, 1.039708282831632, 1.0809720960621554, 1.1158008823682928, 1.143565246956662, 1.163769197890432, 1.176065118570316, 1.1802653589540946, 1.1763501217867562, 1.1644714092507717, 1.1449528908388134, 1.1182856525575302, 1.0851198883467732, 1.0462526943580757, 1.0026122230131898, 0.9552385441728983, 0.9052616430428716, 0.8538770565778817, 0.802319710315318, 0.7518365642628823, 0.7036587085017589, 0.6589735657227532, 0.6188978585456993, 0.5844519841298155, 0.5565364076051281, 0.5359106399678965, 0.5231753063786481, 0.5187577387128338, 0.5229014434799171, 0.5356597048482323, 0.5568934847055438, 0.5862736798235083, 0.6232876927539485, 0.6672501705818016, 0.7173176665879671, 0.7725068866461021, 0.8317160970592596, 0.8937491956055922, 0.9573418846283093, 1.021189335600953, 1.0839746999206805, 1.1443978015644578, 1.2012033441396646, 1.2532079778328644, 1.2993256004762062, 1.3385903106923984, 1.3701764887615633, 1.3934155510509079, 1.4078090048304392, 1.413037520071858, 1.408965831187182, 1.3956433822440286, 1.3733007315310535, 1.3423418329357988, 1.3033324099565875, 1.2569847309022548, 1.2041391786831412, 1.1457430835069122, 1.0828273499550347, 1.0164814598146972, 0.9478274674915348, 0.8779936250040391, 0.808088278013724, 0.739174663017519, 0.6722472090526098, 0.6082099057523538, 0.5478572444215962, 0.49185817138304133, 0.4407434148963454, 0.39489646043833726, 0.35454835623483444, 0.31977643398383937, 0.2905069311341323, 0.26652140334501334, 0.24746672128842032, 0.23286835711332937, 0.22214658487828207, 0.21463514807519454, 0.20960188777081346, 0.20627077834259752, 0.20384478541566606, 0.2015289431919671, 0.19855304630121454, 0.19419336460915929, 0.187792817720762, 0.17877908846637303, 0.1666802103540175, 0.151137231377493, 0.13191363396271524, 0.10890127623898498, 0.08212271106326151, 0.051729833984928204, 0.017998907209779813, -0.01867789882754514, -0.05780421384177635, -0.09879410877570981, -0.14098927569354947, -0.1836782860860003, -0.226117412475825, -0.26755245670543704, -0.3072410010425879, -0.344474485957674, -0.37859952143121944, -0.4090378568825376, -0.43530446782641863, -0.4570232643474258, -0.4739399862619956, -0.48593192092450843, -0.49301416024630446, -0.495342201615509, -0.493210790818465, -0.4870490014219571, -0.47741164195302527, -0.46496717716670033, -0.4504824403219671, -0.43480449739741484, -0.4188400994364496, -0.4035332237987456, -0.38984125735424635, -0.37871041323762, -0.371050996673091, -0.3677131439347956, -0.36946365146088067, -0.37696448961329204, -0.3907535580787699, -0.4112281883230241, -0.4386318340751253, -0.47304431509096795, -0.5143758942655398, -0.562365375614977, -0.616582312999655, -0.6764333191093741, -0.7411723636535306, -0.8099148513767661, -0.8816551768869821, -0.9552873666603711, -1.029628341131169, -1.1034432634139923, -1.1754723876062119, -1.2444587801272808, -1.3091762631764057, -1.3684569207649397, -1.4212175151532314, -1.46648418474916, -1.5034148330725443, -1.5313186713443485, -1.5496724433557507, -1.558132938918721, -1.556545489521418, -1.544948234693272, -1.523572047724229, -1.49283611234753, -1.453339245282136, -1.4058471606266911, -1.3512759685416897, -1.290672290103019, -1.2251904504824014, -1.1560672817562325, -1.0845951229849227, -1.0120936473740503, -0.9398811733080988, -0.8692461271910078, -0.8014193210766734, -0.7375476871632795, -0.6786700748838627, -0.6256956654564869, -0.5793854946197302, -0.5403374984557713, -0.5089754115621187, -0.4855417534798316, -0.4700950405133308, -0.4625112583069311, -0.46248952826793177, -0.4695618006460982, -0.48310631124183806, -0.502364449654165, -0.5264606068573305, -0.554424500650553, -0.5852154208254908, -0.6177477930954203, -0.6509174329374391, -0.6836278481533323, -0.7148159524094678, -0.7434765711340663, -0.7686851554068602, -0.7896181679737851, -0.8055706670093907, -0.8159706861646092, -0.8203900919300209, -0.8185516893338388, -0.8103324422173487, -0.7957627724011589, -0.7750220005204684, -0.7484300877098076, -0.7164359292567248, -0.6796025365361856, -0.6385895198719888, -0.5941333505634263, -0.5470259335517004, -0.4980920617804025, -0.4481663482711279, -0.39807024169994465, -0.34858972561592516, -0.3004542805688216, -0.25431765287053354, -0.2107409244331419, -0.17017831637721917, -0.13296608647221725, -0.09931479881186688, -0.06930515552255152, -0.04288748700558094, -0.01988490159520463, -1.7192358596351585e-16], [0.0, 0.016735482034390122, 0.031499620718039655, 0.044925642644827325, 0.05770021586897871, 0.0705421560209126, 0.084180143173051, 0.0993300468892612, 0.11667246825640147, 0.13683110344257296, 0.16035251354721963, 0.18768785068743465, 0.21917704126621357, 0.2550358654132501, 0.295346298225916, 0.3400503955048907, 0.3889479162561462, 0.44169777859044884, 0.49782334719945437, 0.5567214518044666, 0.6176749393529829, 0.6798684707222643, 0.742407187610248, 0.8043377993145027, 0.8646715741581847, 0.9224086680841942, 0.9765631847565335, 1.0261883383843406, 1.070401083048015, 1.1084055807969018, 1.139514905045802, 1.1631704152713374, 1.1789582927666902, 1.1866227939645873, 1.186075855967372, 1.1774027765269448, 1.160863785653839, 1.1368914259743859, 1.1060837614392212, 1.069193536488033, 1.0271135077612439, 0.9808582654428234, 0.9315429489613943, 0.8803593398875894, 0.8285498814938936, 0.777380227917639, 0.7281109648388098, 0.6819691670567862, 0.6401204657092585, 0.6036422889028404, 0.5734989144005549, 0.5505189323157164, 0.535375660457686, 0.5285709863856007, 0.5304230300020872, 0.541057930598473, 0.5604059648239684, 0.5882020994581665, 0.6239909776115974, 0.6671362316226398, 0.7168339130244968, 0.7721297320277967, 0.8319397083866671, 0.8950737544933774, 0.9602616420499261, 1.026180747383136, 1.0914849287682156, 1.1548338630125543, 1.2149221586528998, 1.2705075696641854, 1.3204376563934337, 1.3636742789455232, 1.3993153615031872, 1.426613432745378, 1.444990525992105, 1.45404911101936, 1.4535788254846869, 1.4435588752266653, 1.4241560768671546, 1.39571862060421, 1.3587657332839147, 1.3139735192880713, 1.2621573471002057, 1.2042512304223312, 1.1412847224505476, 1.0743578987011908, 1.0046150462557322, 0.9332177044624053, 0.8613177133753943, 0.7900309213030533, 0.7204121819488009, 0.653432235330672, 0.5899570159064379, 0.5307298674150003, 0.4763570684986782, 0.42729698810447897, 0.3838530971191136, 0.34617096499689975, 0.31423926973891975, 0.2878947489848163, 0.2668309216936101, 0.25061031636189246, 0.23867985527794164, 0.23038896707831252, 0.22500993376434672, 0.22175992497325855, 0.21982413298345174, 0.21837939761416045, 0.21661770142594994, 0.213768922620671, 0.20912225556180883, 0.2020457462844044, 0.19200344175971798, 0.17856971569668795, 0.1614404086578165, 0.14044050432520463, 0.11552815473120594, 0.08679496285357166, 0.05446252873927546, 0.018875362783495917, -0.019509635521231115, -0.06013684553648055, -0.10236837023045524, -0.14550281528663256, -0.18879589894437576, -0.2314823406888023, -0.2727984427984976, -0.3120047596737641, -0.3484082462996972, -0.38138328925132864, -0.4103910510329474, -0.43499660058439144, -0.45488335843803207, -0.4698644528820041, -0.4798906618794376, -0.485054702444902, -0.48559172250481036, -0.4818759476218985, -0.4744135338939333, -0.46383177634891276, -0.45086491677751644, -0.4363368837733625, -0.4211413785386687, -0.40621979070019326, -0.3925374871598213, -0.38105906236229736, -0.3727231691181849, -0.3684175644547518, -0.3689550044457722, -0.37505060555307274, -0.387301258054001, -0.4061676303741685, -0.43195924270826364, -0.4648230156509657, -0.5047356164398934, -0.5514998338618671, -0.6047451151354519, -0.6639322965580057, -0.728362456895156, -0.797189720932709, -0.869437742818205, -0.9440195072163842, -1.0197600031669147, -1.0954212529362624, -1.1697291179148672, -1.2414012572413113, -1.3091755835128482, -1.3718385444737713, -1.428252560378662, -1.4773819638247252, -1.5183168218547811, -1.5502940682762967, -1.5727154362757176, -1.5851617560399656, -1.5874032674280967, -1.5794056917016595, -1.5613319066437676, -1.5335391736385044, -1.496571970909979, -1.451150591564585, -1.398155765798805, -1.338609661176494, -1.2736537009423796, -1.204523715828679, -1.1325230078931245, -1.0589939540680224, -0.9852888111104089, -0.9127404017034899, -0.8426333631402921, -0.7761766252938661, -0.7144777538188563, -0.6585197485024127, -0.6091408265284483, -0.5670176476224131, -0.5326523543969129, -0.5063637087786249, -0.4882825064337773, -0.47835134804975393, -0.4763287416982182, -0.48179740685910044, -0.49417655055528664, -0.5127377918746076, -0.5366243252277646, -0.5648728370900948, -0.5964376275254617, -0.6302163380130573, -0.6650766521734678, -0.6998833167313523, -0.7335248268825421, -0.7649391331789285, -0.7931377557329129, -0.8172277352133911, -0.8364309076273402, -0.8501000597846258, -0.8577316028548126, -0.8589744905106297, -0.8536352035720979, -0.8416787224251043, -0.8232255093023972, -0.7985446222672683, -0.768043178946321, -0.732252478326922, -0.6918111710301709, -0.6474459403625012, -0.5999502163688751, -0.5501614915909161, -0.4989378391460952, -0.44713425032795595, -0.39557940980605555, -0.3450535116957803, -0.296267689683698, -0.2498455898273507, -0.20630755675571935, -0.16605783426697449, -0.12937510153858175, -0.0964065783667571, -0.06716583927246011, -0.04153437932811139, -0.01926687663500203, -1.6690610814058382e-16], [0.0, 0.016358327846219604, 0.03100761436653275, 0.04462367159202027, 0.057925239877494955, 0.07165163619713977, 0.08653973559163712, 0.10330090386153659, 0.12259850203432779, 0.14502656963362068, 0.17109026467544355, 0.20118859432972505, 0.23559991241074987, 0.2744705897431835, 0.31780718274675757, 0.36547233631793663, 0.4171845615038015, 0.4725219289668421, 0.5309296183360952, 0.5917311637760274, 0.6541431400012865, 0.7172929429568554, 0.7802392377547525, 0.8419945752898531, 0.9015496200703026, 0.9578983867101386, 1.0100638524186991, 1.0571232984868577, 1.098232735625135, 1.1326497860610671, 1.1597544291564221, 1.1790670661676743, 1.1902634224785031, 1.1931858806666358, 1.1878509233045111, 1.1744524583442406, 1.1533608999984866, 1.1251179817396864, 1.0904273828438906, 1.0501413532129726, 1.0052436204619526, 0.9568289559935466, 0.906079860692242, 0.8542409038613613, 0.8025913092698607, 0.7524164281534429, 0.704978769558052, 0.6614892727324592, 0.6230795039780274, 0.5907754414638625, 0.5654734764388168, 0.5479192088410072, 0.5386895507218414, 0.5381785737155327, 0.5465874488584327, 0.5639187305227247, 0.5899751334169475, 0.6243628450183949, 0.6664993080311068, 0.7156253011302719, 0.7708210439480426, 0.8310259564683401, 0.8950616160617718, 0.9616573794228171, 1.029478073518274, 1.0971531108532553, 1.1633063510920014, 1.2265860141383733, 1.285693949587539, 1.3394135839990498, 1.3866359002951494, 1.4263828519407329, 1.4578276772178573, 1.4803116543236845, 1.4933569243408207, 1.4966751042324224, 1.4901715135677713, 1.4739449441984738, 1.4482830089986527, 1.4136532114419353, 1.370689979635568, 1.3201780039873379, 1.263032304622837, 1.2002755308935311, 1.1330130589825333, 1.062406503199856, 0.989646290887154, 0.9159239691272286, 0.8424049132767021, 0.7702020927196089, 0.7003515185892929, 0.6337899523355917, 0.5713353941080547, 0.5136707975129535, 0.46133137421735615, 0.41469576021351223, 0.3739812176247017, 0.3392429441839059, 0.31037745949250256, 0.2871299354370882, 0.2691052402399073, 0.2557823739726524, 0.24653189024393013, 0.24063582622911844, 0.2373096030311138, 0.23572531201256836, 0.2350357713469459, 0.23439872134315598, 0.23300052745835073, 0.2300787762746901, 0.2249431816264665, 0.21699426468277708, 0.2057393319088433, 0.19080534689986606, 0.1719483742604777, 0.14905936389403107, 0.12216613997371495, 0.0914315580546611, 0.05714789373541775, 0.01972762445356498, -0.020309140084749894, -0.06235023606791785, -0.10570961114079414, -0.1496475885926264, -0.19339268637542137, -0.2361644060890799, -0.2771963810030029, -0.3157592617878985, -0.35118272418069496, -0.3828760041725446, -0.41034640296928976, -0.43321525501397845, -0.4512309165078687, -0.4642784075143217, -0.47238542598222094, -0.47572454474152515, -0.4746115003719316, -0.46949958336299497, -0.46097023963608436, -0.449720091743579, -0.4365446814132409, -0.4223193211984813, -0.40797751963896195, -0.3944875095737559, -0.38282746140614915, -0.37396000084420433, -0.3688066729415192, -0.3682230005290345, -0.37297477515093236, -0.3837161925906734, -0.4009704035925514, -0.42511299443203665, -0.4563588429094051, -0.49475271481037036, -0.5401638758578451, -0.5922848968740905, -0.6506347276719272, -0.7145660106135501, -0.7832765003970494, -0.8558243550355629, -0.9311469667007132, -1.0080829125031727, -1.085396526586646, -1.1618045280847058, -1.2360040862109747, -1.3067016653699641, -1.372641970671005, -1.432636308194383, -1.4855896849862906, -1.5305260008261738, -1.566610726691424, -1.5931705225248445, -1.6097093180098654, -1.6159204628658108, -1.6116946456897325, -1.597123380351566, -1.5724979639690548, -1.5383039179961469, -1.4952110313383744, -1.444059229047549, -1.3858405894980959, -1.3216779245892005, -1.2528004192190045, -1.1805168960511914, -1.106187327743279, -1.0311932599670688, -0.9569078337285725, -0.8846661040829406, -0.8157363441411368, -0.7512929984919114, -0.69239190943388, -0.6399483837363115, -0.5947185983980742, -0.5572847627569998, -0.5280443633109031, -0.5072037189808543, -0.49477597069547835, -0.49058352264544675, -0.49426484595557274, -0.5052854514512838, -0.5229527391937463, -0.546434340931825, -0.5747794897895327, -0.6069428813522125, -0.641810433519974, -0.6782263104169811, -0.7150205492687678, -0.7510366190864672, -0.7851582464225553, -0.8163348661754166, -0.8436050938060469, -0.8661176683892718, -0.8831493822931322, -0.8941195912759893, -0.8986009864397809, -0.8963264045730523, -0.8871915535724161, -0.8712536323394834, -0.8487259272475148, -0.8199685673997589, -0.7854757159710357, -0.745859562578257, -0.7018315596972389, -0.6541814127086052, -0.603754386582717, -0.5514275312017288, -0.49808545092888634, -0.4445962517206405, -0.3917882906852346, -0.3404283287744681, -0.29120164790208475, -0.24469464024095477, -0.2013803111441631, -0.16160705976273285, -0.12559101497186742, -0.0934121108711044, -0.0650139882652187, -0.040207708647364934, -0.018679167827785722, -1.6232471968196082e-16], [0.0, 0.01605610152116577, 0.03069253750587646, 0.04462277366222587, 0.058591845472092674, 0.07335312064310957, 0.08964473678824879, 0.10816634798326429, 0.12955680696232597, 0.15437338671800008, 0.1830731067415779, 0.21599667603369346, 0.2533554986611542, 0.2952221096967116, 0.3415243218102414, 0.39204326778318804, 0.4464154241834615, 0.5041385988854985, 0.5645817626371196, 0.6269985050505563, 0.6905438007565231, 0.754293684408572, 0.817267355975296, 0.8784511722838173, 0.9368239287616659, 0.991382798114443, 1.0411692712545173, 1.0852944407497975, 1.1229629785716624, 1.1534951877548487, 1.176346551098935, 1.191124258208094, 1.1976002635826541, 1.1957205114092857, 1.18561005512243, 1.167573899463328, 1.1420934971955186, 1.109818939273408, 1.0715569834696008, 1.0282551696178213, 0.9809823671622057, 0.9309061901946696, 0.8792677943777923, 0.8273546371084342, 0.7764718352929818, 0.7279127928351241, 0.6829297914125588, 0.6427052427696197, 0.6083242884217078, 0.5807494036154704, 0.5607976172884399, 0.5491208996916304, 0.546190195716075, 0.5522834965719776, 0.5674782473704044, 0.5916482856563947, 0.624465398526911, 0.6654054762480258, 0.7137591309325094, 0.7686465425138959, 0.8290361935458836, 0.8937670617199787, 0.9615737566863359, 1.0311140177871165, 1.100997933371219, 1.1698182018131915, 1.2361807301898067, 1.2987348593565466, 1.3562025140790042, 1.4074056036577756, 1.4512910414736435, 1.4869528100102452, 1.5136505697514684, 1.5308243941335324, 1.5381053063990926, 1.5353213954548568, 1.5224993941938916, 1.4998617126057432, 1.4678190267007118, 1.426958630165774, 1.3780288561687446, 1.3219199693908479, 1.2596420109494246, 1.1923001493773113, 1.121068147559857, 1.0471605971430884, 0.9718045974409689, 0.8962115647087693, 0.8215498496482985, 0.748918816420516, 0.6793249959222061, 0.613660870688711, 0.5526867799325313, 0.497016352666187, 0.4471057866214469, 0.40324719303543577, 0.36556612477537354, 0.3340233002832892, 0.30842043105926875, 0.2884099584740543, 0.27350840914050084, 0.26311298927025834, 0.256520959590534, 0.25295126543630975, 0.25156784320546505, 0.2515039857660691, 0.2518871265615998, 0.2518633955999909, 0.2506213103567253, 0.2474139905800112, 0.24157932736332718, 0.23255759256778194, 0.21990604329582492, 0.20331015587927556, 0.18259121271089224, 0.15771006095618065, 0.12876696229748696, 0.09599755484384487, 0.05976504960105057, 0.020548881870475082, -0.021069869849961242, -0.06442590078897575, -0.10878946211069744, -0.15338797611297073, -0.19742890403599805, -0.2401232529156268, -0.2807090904726849, -0.3184744357810269, -0.35277890844496457, -0.38307354987492664, -0.4089182762120985, -0.42999648237069965, -0.44612638904052876, -0.4572688075072988, -0.46353108871911547, -0.46516712085163464, -0.46257334123886007, -0.45628083137958153, -0.4469436652045865, -0.43532377833080255, -0.42227271716372267, -0.4087107091233318, -0.39560356686049497, -0.38393799826659003, -0.374695938838738, -0.3688285523777677, -0.3672305592787591, -0.37071554843916277, -0.3799929090830653, -0.3956469830201689, -0.41811898686364857, -0.4476921887426768, -0.48448074663474794, -0.5284225274944925, -0.57927613002028, -0.6366222315417485, -0.6998692736497435, -0.7682633944365673, -0.8409024102089859, -0.9167535488812295, -0.9946745434507912, -1.0734376093421596, -1.1517557560870613, -1.2283108236334659, -1.3017825880578648, -1.3708782517564317, -1.4343616200824894, -1.491081270244779, -1.5399970390318032, -1.5802041931132473, -1.610954698417576, -1.6316750721383133, -1.641980380670242, -1.6416840372970316, -1.630803152553061, -1.609559295461112, -1.5783746327468982, -1.5378635230027808, -1.4888197509424808, -1.432199690721921, -1.369101784269135, -1.3007428083062593, -1.2284314801215883, -1.1535400153006539, -1.0774742990159172, -1.0016433649311574, -0.9274288915142891, -0.8561554241966146, -0.7890620134111657, -0.7272759235487402, -0.6717890171549392, -0.6234373535057169, -0.5828844626479798, -0.5506086669937221, -0.5268947247957537, -0.5118299657074263, -0.5053049806878934, -0.5070188193986015, -0.5164885406114277, -0.5330628576387932, -0.5559395239207109, -0.5841860160153186, -0.6167629944651402, -0.6525499592009005, -0.6903724668255677, -0.7290302434606861, -0.7673255096141206, -0.8040908331152846, -0.838215842517391, -0.8686721660287029, -0.894536009147145, -0.9150078464952766, -0.9294287782973495, -0.9372931876096299, -0.9382574286506936, -0.9321443770137808, -0.9189437766637527, -0.8988084238263012, -0.8720463315453655, -0.8391091182386122, -0.8005769565513042, -0.757140502896025, -0.7095803011963218, -0.6587442147307033, -0.6055234861263261, -0.5508280563640944, -0.4955617883995285, -0.44059823935108045, -0.38675760724481817, -0.33478544452570286, -0.28533368184053, -0.23894444322884675, -0.1960370594296118, -0.1568986014275417, -0.12167816378138466, -0.0903850290526953, -0.06289074328328277, -0.038935030524830584, -0.018135374489707333, -1.5830222531772736e-16], [0.0, 0.015840805951609662, 0.03057630318771933, 0.04495210270706526, 0.0597332710276579, 0.07568039422984446, 0.09352567607046033, 0.1139497139226587, 0.1375595797773457, 0.16486880089416237, 0.19627978672594645, 0.23206918666030274, 0.27237658848149465, 0.3171968821292888, 0.36637651946347016, 0.41961380069578896, 0.47646321444574297, 0.5363437536289296, 0.5985510262427753, 0.6622728811841552, 0.7266081770250477, 0.7905882385299072, 0.8532004737425415, 0.9134135655453056, 0.9702036072206137, 1.022580522884253, 1.0696141014809437, 1.110458977693855, 1.1443779145599928, 1.1707627803222151, 1.1891526651978626, 1.1992486510292768, 1.2009248265732322, 1.1942352315399858, 1.179416511196336, 1.1568861679763511, 1.1272364045210042, 1.0912236612276267, 1.0497540580427382, 1.0038650522319374, 0.9547037186721593, 0.903502144471047, 0.8515505032929617, 0.8001684348130935, 0.750675399712605, 0.7043607094191913, 0.6624539416371196, 0.6260964472628694, 0.5963146316365795, 0.5739956537486223, 0.5598661319289827, 0.5544743750079949, 0.5581765756203335, 0.5711273092162142, 0.5932745806979306, 0.6243595528817922, 0.6639209798122543, 0.7113042560307871, 0.7656748829516423, 0.8260360481985858, 0.8912499156768892, 0.9600621356839169, 1.0311290076556676, 1.1030466650741415, 1.1743816041566244, 1.2437018463767162, 1.3096080103921632, 1.3707635719216804, 1.4259236104402035, 1.4739613787428436, 1.5138920845432016, 1.5448933410132089, 1.566321823873484, 1.577725764323742, 1.5788530075132432, 1.5696544729313713, 1.5502829634371766, 1.5210873809465943, 1.4826025163398548, 1.4355346862690328, 1.3807435876794605, 1.3192208296271521, 1.2520656792302465, 1.1804586224752567, 1.1056333895809978, 1.0288481275462422, 0.9513564186114484, 0.8743788423064378, 0.7990757606146814, 0.726521971062745, 0.6576838221504412, 0.5933993207689103, 0.5343616837583782, 0.48110669749422025, 0.43400415258103925, 0.3932535178082414, 0.3588839110519989, 0.3307583174542212, 0.30858189964219596, 0.29191414359504064, 0.2801844895219214, 0.272711012120877, 0.2687216409295353, 0.26737735096607, 0.26779670796466565, 0.2690811223405206, 0.2703401522858695, 0.27071619939880504, 0.2694079598597629, 0.26569202985929696, 0.258942114806091, 0.24864535648894298, 0.2344153691685731, 0.21600166256981496, 0.1932952247135061, 0.16633013805421337, 0.13528120592148796, 0.10045767017230858, 0.06229320261719021, 0.021332449607182353, -0.02178550128802119, -0.06634628358637615, -0.1115815258399579, -0.15669166476559998, -0.20086968469795768, -0.2433251458309954, -0.28330785540612125, -0.3201305442807981, -0.35318993597147713, -0.3819856356971381, -0.40613632214505635, -0.4253927932562451, -0.43964749756399085, -0.4489402724993209, -0.45346010834139894, -0.45354285868975613, -0.44966492289234666, -0.4424330301394629, -0.4325703562922374, -0.4208993003886842, -0.40832133572626106, -0.3957944282182857, -0.384308580373596, -0.37486011106637646, -0.3684253179011463, -0.36593418946882816, -0.36824483856766244, -0.37611931437832546, -0.390201421907452, -0.41099713143428046, -0.4388581002958769, -0.47396875558380236, -0.5163373009917336, -0.565790916234115, -0.6219753154757549, -0.6843587245799586, -0.7522402283283538, -0.8247623307747491, -0.9009274672440915, -0.9796181077744225, -1.0596200014823671, -1.1396480316659683, -1.2183740844394308, -1.2944562810106799, -1.3665688867021077, -1.4334321894315316, -1.4938416371595755, -1.5466955378947755, -1.5910206569269632, -1.6259950933116194, -1.650967880131111, -1.6654748292166603, -1.6692502289938995, -1.6622341017885545, -1.644574831930381, -1.616627085773779, -1.5789450566436705, -1.5322711789923182, -1.477520564006815, -1.4157615109076616, -1.3481925417401703, -1.2761164903022169, -1.2009122459551835, -1.1240048087232624, -1.0468343519451677, -0.9708250118356475, -0.897354129084993, -0.8277226559411528, -0.7631274133760492, -0.7046358376501204, -0.6531637949745877, -0.6094569685206144, -0.5740762355682728, -0.5473873562475907, -0.5295551914606573, -0.5205425587315774, -0.5201137235722381, -0.5278424131921938, -0.5431241317226176, -0.5651924541890213, -0.5931388827324261, -0.6259357653153813, -0.6624617063676133, -0.7015288422254491, -0.7419113131465835, -0.7823742390991364, -0.8217024989848992, -0.8587286225934798, -0.8923591311048459, -0.9215987046541683, -0.9455716132388149, -0.9635399186061748, -0.9749180379032395, -0.9792833526972465, -0.9763826471588218, -0.9661342642253233, -0.9486259758085376, -0.9241086699042679, -0.8929860611460526, -0.8558007293484751, -0.8132168804821973, -0.7660003040947952, -0.7149960684829992, -0.6611045482876855, -0.6052564173289583, -0.5483872615136623, -0.4914124720255826, -0.43520306766080646, -0.3805630674272595, -0.32820899112890556, -0.27875200773312525, -0.23268318036873062, -0.19036217464114122, -0.1520097056785959, -0.11770390126355151, -0.08738065604913524, -0.060837947809477586, -0.03774398356342412, -0.017648943855770153, -1.5495823325931208e-16], [0.0, 0.0157237673285404, 0.030679135941943433, 0.045637821883813164, 0.061378227347421384, 0.07866100756378727, 0.09820504419723329, 0.12066447336124073, 0.1466073900040534, 0.17649680804853488, 0.21067439836434818, 0.24934745583980575, 0.2925794642842036, 0.3402845357045115, 0.39222590098337695, 0.4480185246461287, 0.5071358098748371, 0.5689202538982024, 0.632597811039087, 0.6972956236430893, 0.7620626923067714, 0.825892978535182, 0.8877503671876229, 0.9465948645106078, 1.0014093715472105, 1.0512263532055397, 1.095153720807762, 1.1323992606419013, 1.162292972589743, 1.1843067305724915, 1.1980707392042957, 1.2033863371594193, 1.2002347854895177, 1.1887817763278739, 1.1693775017014492, 1.1425522309717335, 1.1090074560560539, 1.0696027733049844, 1.0253387770080216, 0.9773363393316518, 0.9268127425736293, 0.8750552096682397, 0.8233924458908094, 0.7731648569951542, 0.725694145244685, 0.6822530040296189, 0.6440356334799552, 0.612129783597693, 0.587490998286881, 0.5709196840266005, 0.5630415619866693, 0.5642919836839878, 0.5749044997142909, 0.5949039708589955, 0.6241044033891304, 0.6621115782779802, 0.7083304300172125, 0.761977017583424, 0.8220948205796677, 0.8875749903492423, 0.9571800914437446, 1.029570785526515, 1.1033348396372296, 1.1770177854431751, 1.249154517004101, 1.3183010926301784, 1.3830660021464016, 1.4421401743887587, 1.4943250307093605, 1.5385579378945735, 1.5739344770291237, 1.5997270219186304, 1.615399209820897, 1.62061598624685, 1.615249012049692, 1.5993773323202147, 1.5732833200262895, 1.5374440201057464, 1.4925181290943743, 1.4393289486822365, 1.3788437463325534, 1.3121500399732136, 1.24042939475798, 1.1649293762892947, 1.0869343451565732, 1.0077358012268203, 0.928602992299983, 0.850754490411673, 0.7753314105644165, 0.7033729017526799, 0.6357944799772616, 0.5733696990566483, 0.5167155693078171, 0.46628203874700674, 0.42234574874749226, 0.38500816865698734, 0.3541981044038616, 0.3296784673351639, 0.31105708413363803, 0.2978012292679912, 0.2892554704981621, 0.2846623377262942, 0.28318525792428034, 0.2839331456293499, 0.28598600086871667, 0.28842084524859823, 0.29033732280360225, 0.29088230510512647, 0.2892728697011529, 0.2848170664166734, 0.2769319461992246, 0.2651584004963341, 0.2491724437219291, 0.2287926650478358, 0.20398367615895754, 0.17485548618532235, 0.14165884111733545, 0.10477666993313409, 0.06471188076161556, 0.02207184511240712, -0.022450005871874627, -0.06809497421941636, -0.11406171595635813, -0.15953008124175336, -0.20368553304948095, -0.24574348804370924, -0.28497292455538936, -0.3207186206577106, -0.35242141981048913, -0.3796359715360037, -0.40204545884942067, -0.41947290108266067, -0.4318887083784466, -0.4394142602865311, -0.44232138314503666, -0.44102770669873026, -0.43608798702302193, -0.4281815875928796, -0.41809641060717584, -0.40670966390763913, -0.3949659326465181, -0.38385309711911336, -0.3743766970333587, -0.36753338641773536, -0.36428415122105223, -0.36552797268319553, -0.3720766134242615, -0.3846311800082631, -0.40376107601076816, -0.42988590429538515, -0.4632608076109879, -0.503965654447751, -0.5518983843403424, -0.6067727257537752, -0.6681203928158734, -0.7352977571047601, -0.8074968801802015, -0.8837606843012629, -0.9630019354871835, -1.0440256173237608, -1.1255541880836375, -1.2062551399647148, -1.2847702194122412, -1.359745623092043, -1.429862456261897, -1.4938667297758923, -1.5505981790577106, -1.5990172129646056, -1.6382293419759273, -1.667506492601367, -1.6863046869448763, -1.6942776512496887, -1.6912860129395004, -1.677401849844169, -1.6529084654278916, -1.61829537724739, -1.574248619797864, -1.521636574580778, -1.4614916469285857, -1.3949882082458969, -1.3234173114572738, -1.2481587644154466, -1.1706512089438195, -1.0923609005314598, -1.0147499143150027, -0.9392445161287138, -0.8672044327663544, -0.7998937332978463, -0.7384539938732446, -0.6838803628979948, -0.6370010731436837, -0.5984608639941343, -0.5687086826635178, -0.5479899301736653, -0.5363434086652328, -0.5336030139134442, -0.5394041034774287, -0.5531943595009665, -0.5742488585162236, -0.6016889612746513, -0.6345045460500822, -0.6715790311941481, -0.7117165688425612, -0.7536707430992128, -0.7961740739105297, -0.8379676129243627, -0.8778299202200164, -0.9146047307806128, -0.9472266564085734, -0.9747443214974487, -0.9963403983165099, -1.01134808752961, -1.0192636805348216, -1.019754939591269, -1.012665137103707, -0.9980127042292914, -0.9759865484420711, -0.9469372071158125, -0.9113641068988766, -0.869899294112872, -0.8232880872533277, -0.7723671767935624, -0.7180407580773188, -0.6612553286580434, -0.602973810907498, -0.5441496733829123, -0.48570172004056844, -0.4284901950730149, -0.37329481350807814, -0.3207952747302041, -0.2715547491406086, -0.22600674898301204, -0.18444570495185655, -0.1470214728492514, -0.11373789174163763, -0.0844554093979563, -0.0588976849475417, -0.03666197535990981, -0.017233014136308004, -1.524077193334442e-16], [0.0, 0.015715491921897022, 0.031019305636535405, 0.046702741842701276, 0.06355047346974442, 0.08231582865409935, 0.10369686284112682, 0.12831386649724247, 0.1566889185882794, 0.18922804393387382, 0.2262064660904319, 0.26775736821696633, 0.3138644844310213, 0.36435874573080324, 0.41891910012515493, 0.4770775188097447, 0.5382280917784051, 0.6016400099055066, 0.666474128972434, 0.7318027169163008, 0.796631901148837, 0.8599262602838098, 0.9206349458831213, 0.9777186764036181, 1.0301769185369323, 1.0770745613124342, 1.1175673959794745, 1.1509257396643777, 1.176555582541387, 1.1940166957764935, 1.2030372094143946, 1.2035242539353794, 1.1955703543453609, 1.1794553690450322, 1.1556438748092164, 1.1247780113032342, 1.087665910897048, 1.0452659493251317, 0.9986671572526618, 0.9490662294432884, 0.8977416545665939, 0.8460255625697602, 0.7952739461069706, 0.7468359562603952, 0.702022999575068, 0.6620783725590854, 0.6281481609974555, 0.6012541048607549, 0.5822690858646852, 0.5718958348831373, 0.5706493818632707, 0.5788436834279415, 0.5965827650897122, 0.6237566083209826, 0.6600419002152944, 0.7049076478705127, 0.7576255437389148, 0.8172848548454016, 0.8828115007361298, 0.9529908849210431, 1.0264939548570888, 1.1019058883734947, 1.1777567417483925, 1.2525533479358786, 1.3248117238520358, 1.3930892338760534, 1.4560157630902386, 1.5123231781088735, 1.560872395029105, 1.6006774320517678, 1.6309258972408998, 1.650995447928736, 1.6604658553190172, 1.6591264135187616, 1.6469785439513025, 1.6242335611399572, 1.591305681392984, 1.548800469148275, 1.497499023893159, 1.4383383110316954, 1.3723881303932486, 1.3008252940789724, 1.224905649151023, 1.145934628758788, 1.065237046533206, 0.9841268627470329, 0.9038776465529433, 0.8256944367305812, 0.7506876643918619, 0.6798497460261023, 0.6140348855226715, 0.5539425411586002, 0.5001049200668178, 0.4528787607555216, 0.4124415563832885, 0.37879226040147274, 0.35175640462276575, 0.330995450535007, 0.31602009046130775, 0.30620711854892296, 0.3008194049330982, 0.2990284318971389, 0.29993879025878445, 0.30261398902652703, 0.3061029026712872, 0.30946616881805583, 0.31180185501797963, 0.3122697363172032, 0.31011356496800296, 0.3046807687895482, 0.29543908395164015, 0.2819897095453907, 0.2640766631334735, 0.24159211619903082, 0.21457759350053945, 0.1832210281225408, 0.1478497717566597, 0.10891976472499867, 0.06700116981206848, 0.02276086558352492, -0.023057723776652942, -0.06965691604147918, -0.11620857488459484, -0.16187878962664476, -0.2058527671531842, -0.24735926635031197, -0.2856939165824859, -0.3202407898405948, -0.3504916405151653, -0.3760622861882009, -0.3967056758949922, -0.4123212771473107, -0.42296050749658565, -0.4288280381698213, -0.4302789037663972, -0.42781146047362884, -0.42205634300173067, -0.4137616747279892, -0.4037748837313965, -0.39302156699765817, -0.3824819237968638, -0.37316534506742416, -0.3660837968851795, -0.36222467142302617, -0.3625237972773398, -0.3678393021362682, -0.37892700440837224, -0.39641797697115055, -0.42079887641856123, -0.45239556627490723, -0.4913604841695149, -0.5376641128443029, -0.5910908153008431, -0.651239187831215, -0.7175269737438252, -0.7892004680319045, -0.8653482318261796, -0.9449188279888379, -1.026742188317698, -1.1095541310536332, -1.1920234670173964, -1.2727810657628658, -1.35045020131415, -1.4236774616751535, -1.491163488280203, -1.551692811385265, -1.604162065133587, -1.6476059012787299, -1.6812199724921821, -1.7043804235890698, -1.7166594102596975, -1.717836258039255, -1.707903977030887, -1.6870709578266871, -1.6557577884770345, -1.6145892484581232, -1.5643816505536052, -1.5061258125970776, -1.440966045410381, -1.370175638471757, -1.2951294085350864, -1.217273946554964, -1.1380962531413257, -1.0590914910349856, -0.9817306038301156, -0.9074285528702545, -0.837513908850119, -0.7732005015491609, -0.715561781120516, -0.6655084786898143, -0.6237700742947797, -0.5908804883732399, -0.5671683113344471, -0.552751776715303, -0.5475385696960231, -0.5512304471080677, -0.5633325303330248, -0.5831670214610589, -0.609890988453062, -0.6425177693719405, -0.67994146133194, -0.7209638886964237, -0.7643233889392704, -0.8087247148061198, -0.852869328897657, -0.8954853620493198, -0.9353565199628241, -0.9713492530776848, -1.0024375518484214, -1.027724792198962, -1.0464621323653212, -1.058063050677405, -1.0621137118474189, -1.0583789545676208, -1.0468038030430167, -1.0275105167556495, -1.000791303497922, -0.9670969277735678, -0.9270215473950689, -0.881284203017314, -0.8307074661763395, -0.776193819167123, -0.7187003931439172, -0.6592127278792277, -0.5987182367943465, -0.5381800637197599, -0.47851200333636207, -0.42055512580144405, -0.36505669851300954, -0.31265193555084186, -0.26384902966180973, -0.21901783466944377, -0.17838247010420982, -0.1420180171169456, -0.10985136796354572, -0.08166618324264975, -0.057111804368834375, -0.03571586617310518, -0.01690025863584555, -1.50759621388702e-16], [0.0, 0.01582552992859333, 0.03161287935934787, 0.04816599129908692, 0.06626844202651479, 0.08665866338760865, 0.11000634340047011, 0.13689064385950622, 0.1677808273121538, 0.20301982419089076, 0.24281119556775246, 0.28720985985358055, 0.33611685498480337, 0.3892783036663716, 0.4462886406938211, 0.5065980510016871, 0.5695239576704311, 0.6342662934401164, 0.6999261900069293, 0.7655276290420204, 0.8300415197744664, 0.8924116021467945, 0.9515815236786543, 1.0065224035863138, 1.056260180321483, 1.0999020390026537, 1.136661233263815, 1.16587965144386, 1.1870475289555222, 1.199819775861474, 1.2040284695194228, 1.1996911546660454, 1.1870146952243217, 1.1663945309338861, 1.1384093049355473, 1.1038109428943286, 1.0635103772837053, 1.0185592192692927, 0.9701277825135635, 0.9194799556305018, 0.8679455006357328, 0.8168904215357103, 0.767686098488397, 0.7216779174367841, 0.680154141867493, 0.6443157719167475, 0.6152481164202381, 0.5938947661147991, 0.5810346019199274, 0.5772624023446313, 0.5829735302543975, 0.5983530835138117, 0.6233697887075152, 0.6577748047895199, 0.7011054868481511, 0.7526940420396321, 0.8116808930151742, 0.8770324516902236, 0.9475629007241155, 1.0219594841683055, 1.098810724743033, 1.1766369151667002, 1.2539221765992121, 1.3291473398964389, 1.400822885918465, 1.4675211800614951, 1.5279072535143763, 1.5807674190474539, 1.6250350615556326, 1.6598130118126204, 1.6843919942761183, 1.6982647342957369, 1.7011354144026478, 1.6929242809500176, 1.6737673184983308, 1.6440110271637034, 1.6042024547959215, 1.5550747484844325, 1.4975285957654665, 1.432610022452421, 1.3614850988981158, 1.28541217767528, 1.2057123414251099, 1.1237387786491781, 1.0408458265983718, 0.9583584236706659, 0.8775426988418559, 0.7995783930416548, 0.7255337579096295, 0.6563435122940954, 0.5927903578470428, 0.5354904641153265, 0.4848832329194762, 0.44122554406716724, 0.40459057226029815, 0.37487115121835085, 0.3517875483864831, 0.3348994049188134, 0.3236214936148416, 0.3172428546570782, 0.3149487876339633, 0.31584511042640306, 0.3189840427415638, 0.32339103566606564, 0.3280918494431791, 0.3321391801830078, 0.33463815237665917, 0.33477002744869494, 0.33181352826097293, 0.3251632441822627, 0.3143446593943188, 0.2990254365169167, 0.2790226861199273, 0.25430605774380277, 0.22499659700275024, 0.19136142343478799, 0.15380439220140138, 0.11285300678255188, 0.06914194682929334, 0.023393662873855272, -0.023603434556367715, -0.07101860163541582, -0.11800356690212921, -0.16371784835896858, -0.20735390093599643, -0.2481614172046848, -0.2854701255796956, -0.31871046846499984, -0.3474315969246578, -0.37131618712790504, -0.3901916653054438, -0.40403752020716793, -0.4129884827463993, -0.41733345911265823, -0.4175102134431899, -0.4140959063882965, -0.40779370379746516, -0.3994157725583361, -0.3898630757282577, -0.38010246408736037, -0.3711416339415652, -0.3640025795469361, -0.3596942113983309, -0.35918483770009413, -0.3633752149078595, -0.3730728640283832, -0.38896832256265507, -0.41161395819068336, -0.44140591056420714, -0.4785696533364251, -0.5231495816209214, -0.5750029325612502, -0.6337982410022086, -0.6990184209869076, -0.7699684497081883, -0.8457875164430896, -0.9254653877261848, -1.0078626343385984, -1.0917342682396156, -1.175756250783523, -1.258554259624, -1.3387340424768202, -1.41491264289454, -1.4857497575120204, -1.5499784765314997, -1.606434669770576, -1.6540843091861017, -1.6920480647572052, -1.7196225728785852, -1.7362978534942042, -1.7417704422391784, -1.7359519046799605, -1.7189725089079202, -1.6911799475992977, -1.6531331184124713, -1.6055910893845782, -1.5494974909432397, -1.485960685461916, -1.4162301662918872, -1.3416697284343997, -1.2637280302701177, -1.1839072281535945, -1.1037304116849034, -1.024708595967433, -0.9483080374558799, -0.8759186318445152, -0.8088241260459481, -0.7481748323154176, -0.6949634720657505, -0.6500047013778096, -0.6139187814925051, -0.5871197578456582, -0.5698084029174226, -0.5619700639616015, -0.5633774393475994, -0.5735981896530794, -0.5920071746553912, -0.6178029977837911, -0.6500284380749811, -0.6875942586821224, -0.7293058027202406, -0.7738917235706618, -0.8200341492329452, -0.8663995500245087, -0.9116695665791198, -0.9545710609355125, -0.9939046773379056, -1.0285712405492629, -1.0575953769370956, -1.080145815861915, -1.0955519141492698, -1.1033160425094235, -1.103121577273055, -1.0948363511224555, -1.078511529863577, -1.0543759958830448, -1.0228264299450402, -0.9844133886554661, -0.939823772643771, -0.8898601678785336, -0.8354176173969664, -0.7774584412626674, -0.7169857673032749, -0.6550164630503551, -0.5925541696616633, -0.5305631312434304, -0.4699434881435662, -0.41150866112907447, -0.35596539598517124, -0.3038969664647721, -0.2557499495142782, -0.21182489245240138, -0.17227108968460061, -0.13708557919170022, -0.10611635916139425, -0.0790697155198746, -0.055521444542536845, -0.034931653873867506, -0.01666273271673751, -1.5011548028462236e-16], [0.0, 0.01606234801083481, 0.032473494337788976, 0.05004272409203558, 0.06954491896377542, 0.0916959498985329, 0.11712964005061045, 0.14637692262216523, 0.17984776197188534, 0.21781633548175902, 0.260409889889464, 0.30760159123882325, 0.35920758465596203, 0.41488837142214974, 0.47415449903212664, 0.5363764479251647, 0.6007984891903332, 0.6665561835506956, 0.732697095965237, 0.7982042146963287, 0.8620214908595387, 0.9230808561726673, 0.9803300343619298, 1.032760436575879, 1.0794344238848954, 1.119511230743805, 1.1522708719534291, 1.177135401512769, 1.1936869537149404, 1.2016820734102842, 1.201061931674737, 1.191958122994066, 1.1746938480503923, 1.1497803996147005, 1.1179089851042971, 1.0799380351821162, 1.0368762604792108, 0.9898618253074047, 0.940138105430955, 0.8890265841260744, 0.8378975146851827, 0.7881390363513664, 0.7411254728997316, 0.6981855676251388, 0.6605714146938771, 0.6294288344650079, 0.6057699097375949, 0.5904483516361536, 0.5841382991464222, 0.5873170767019992, 0.6002523416136774, 0.6229939497642388, 0.6553707563662986, 0.6969924514099699, 0.7472564095605871, 0.8053594146237569, 0.8703140021924759, 0.9409690535714772, 1.0160341722355513, 1.0941072834088021, 1.1737048200658327, 1.2532937966423452, 1.331325026516893, 1.406266711992093, 1.4766376267294048, 1.541039120589047, 1.5981852053487866, 1.6469300261218605, 1.686292086328657, 1.7154746722546035, 1.733882014633563, 1.741130827094935, 1.7370569721990508, 1.7217171224491687, 1.6953854032602835, 1.6585451244672613, 1.6118758236529585, 1.5562359555312686, 1.4926416641357618, 1.4222421661578892, 1.34629235223806, 1.2661232764527364, 1.183111251148197, 1.0986462935429155, 1.0141006814880573, 0.9307983682235534, 0.8499859801364714, 0.772806078110155, 0.7002733031699748, 0.6332539523122385, 0.5724494425396519, 0.5183840224310998, 0.47139698351964804, 0.4316395110161617, 0.3990761978070076, 0.37349113004801177, 0.35449833994156926, 0.34155631421003174, 0.3339861480097604, 0.330992845997423, 0.33168919712164247, 0.33512158930128366, 0.34029708592794283, 0.3462110591488917, 0.3518746657698266, 0.35634146053836896, 0.3587324682526571, 0.35825907986355504, 0.35424319735819926, 0.3461341261846101, 0.3335218004026186, 0.31614602241696993, 0.2939015036016526, 0.2668386017061938, 0.235159762864995, 0.19921178747457868, 0.1594741473407411, 0.11654368359393176, 0.07111610834700713, 0.02396481556390186, -0.024082423962200773, -0.07216825400968946, -0.11943134278011683, -0.16503212202225898, -0.20817796270486022, -0.24814710876514173, -0.2843107221505644, -0.3161524407050696, -0.34328491421207397, -0.36546286148946994, -0.38259228088233815, -0.3947355455619789, -0.4021122212163055, -0.4050955543261464, -0.4042046914694843, -0.4000928011417093, -0.39353137661141546, -0.38539109863218834, -0.3766197278501857, -0.3682175761632324, -0.36121117206519304, -0.3566257854536065, -0.3554575111746346, -0.358645626827539, -0.3670459385892002, -0.3814058090356059, -0.402341523570395, -0.43031859799968225, -0.4656355603158067, -0.508411656556145, -0.5585788357184872, -0.615878264469403, -0.6798615113426786, -0.7498964250324519, -0.825177615088327, -0.9047413287021772, -0.9874844071883218, -1.072186902943639, -1.1575378447018647, -1.2421635580979395, -1.324657881969146, -1.4036135701276422, -1.4776541348428063, -1.5454653728477763, -1.6058258177647837, -1.6576353844050782, -1.6999415099621011, -1.7319621537574603, -1.7531050895729923, -1.7629830109734062, -1.761424068311132, -1.7484775639300634, -1.7244146468325758, -1.6897239669556097, -1.64510236932342, -1.5914408267794558, -1.529805923859384, -1.4614173108724022, -1.387621643807927, -1.3098636099208705, -1.2296547087126994, -1.1485405118102472, -1.0680671616354795, -0.9897478868691963, -0.9150303120982153, -0.845265319716979, -0.7816781846053383, -0.7253426472460482, -0.6771585201228242, -0.6378333371872592, -0.6078684589829902, -0.5875499390458417, -0.5769443430751555, -0.5758995938821445, -0.5840507951582795, -0.6008308685957646, -0.6254857247189403, -0.657093580725807, -0.6945879412900644, -0.7367836729909963, -0.7824055318760431, -0.8301184483234801, -0.8785588351724892, -0.926366164913454, -0.972214060025703, -1.0148401573002834, -1.053074041724227, -1.085862597320139, -1.1122921899011688, -1.131607178300748, -1.1432243442105552, -1.1467429339587176, -1.1419501158002874, -1.1288217708221646, -1.1075186515332727, -1.0783780567372834, -1.041901281531292, -0.998737204514072, -0.9496624679768281, -0.8955587886859143, -0.8373880048492585, -0.7761655173342622, -0.7129328189130245, -0.6487298234100806, -0.5845677067193077, -0.5214029537917745, -0.46011327037547883, -0.4014759664477074, -0.346149351269202, -0.2946575995328348, -0.2473794562382829, -0.20454104704116677, -0.16621295346662412, -0.13231160126881109, -0.10260489817575237, -0.07672194711989144, -0.054166555604315936, -0.03433416375844196, -0.016531725372861288, -1.5056814338436878e-16], [0.0, 0.016433212063026816, 0.03361215470067645, 0.05234386645400184, 0.0733867818627306, 0.09742653112967131, 0.12505370090181042, 0.15674416035443833, 0.19284249081574362, 0.23354897731059446, 0.2789105286474373, 0.32881579133621286, 0.3829946142659009, 0.4410219084249645, 0.5023258318644769, 0.5662001174694535, 0.6318202527733846, 0.6982631197743205, 0.76452961106494, 0.8295696589126729, 0.8923090482612437, 0.9516773346658969, 1.006636155224014, 1.0562072054999476, 1.0994991587001401, 1.135732824906773, 1.1642638875420999, 1.1846026104817535, 1.1964299810102226, 1.199609839371233, 1.194196642917935, 1.1804386194242695, 1.1587761773542, 1.129835558001708, 1.094417832510904, 1.0534834629302827, 1.008132757758172, 0.9595826561211263, 0.9091403681997343, 0.8581744804304116, 0.8080842003266079, 0.760267465794633, 0.7160886762831901, 0.6768468171484111, 0.6437447438376097, 0.6178603689584218, 0.6001204535318886, 0.591277644704638, 0.5918913273198506, 0.6023127678148599, 0.6226749280693182, 0.6528872165124106, 0.6926353266872342, 0.7413861924123929, 0.7983979666226333, 0.862734810887448, 0.9332861674290901, 1.0087900780019041, 1.087860016878892, 1.1690146207931578, 1.2507096290650592, 1.3313712940135893, 1.4094304864024845, 1.4833567039725826, 1.5516911934704296, 1.6130784179408908, 1.666295140885376, 1.71027645622197, 1.7441381664157947, 1.7671949988805646, 1.7789742506395134, 1.7792245608335175, 1.7679196272981608, 1.7452568042515781, 1.7116506401932619, 1.6677215354356112, 1.6142798143458754, 1.5523056155554995, 1.482925101473345, 1.4073835740469374, 1.3270161547901669, 1.2432167419351625, 1.1574059948711393, 1.0709991149377844, 0.9853741917339184, 0.9018418654359787, 0.8216170187098669, 0.7457931576071738, 0.6753200707499663, 0.6109852719042589, 0.5533996348424752, 0.502987523613194, 0.45998160861734766, 0.4244224420446366, 0.3961627481588667, 0.37487626756646336, 0.36007088283962285, 0.3511056484548845, 0.3472112535208443, 0.3475133635241082, 0.3510582193294703, 0.35683981957819383, 0.3638279776869734, 0.37099652767869373, 0.3773509544436086, 0.3819547436458538, 0.383953783809613, 0.38259820715375936, 0.37726112508926546, 0.3674537971646236, 0.35283686651953744, 0.333227398182332, 0.308601566195454, 0.2790929487936851, 0.24498650482188208, 0.20670841637941817, 0.16481208949054882, 0.11996070372542149, 0.07290679063301769, 0.024469397350732464, -0.024490546104157157, -0.07309599114513968, -0.12047997269761608, -0.16581154393246048, -0.2083207453615317, -0.24732193477475836, -0.2822348465871054, -0.31260280751068775, -0.33810760860203437, -0.3585806198131239, -0.37400983002632887, -0.38454260073367486, -0.390484032373969, -0.3922909560660805, -0.39056167719620605, -0.38602170815150144, -0.37950583263070814, -0.37193694073258843, -0.36430215995943066, -0.35762688017824423, -0.35294732858264133, -0.35128239229047054, -0.3536054103016534, -0.36081666246935884, -0.3737172707013096, -0.39298519706158996, -0.419153975495278, -0.4525947496935326, -0.4935021107090166, -0.5418841362447108, -0.5975569313203929, -0.6601438597850051, -0.7290795406099159, -0.8036185649259062, -0.882848772280997, -0.9657088105169204, -1.051009595831503, -1.1374591907056013, -1.2236905299048642, -1.3082913509186467, -1.3898356268391925, -1.4669157583024834, -1.5381747577806728, -1.6023376548633317, -1.6582413653597154, -1.7048622998014702, -1.7413410374709326, -1.7670034592308403, -1.7813778145829648, -1.7842072935593811, -1.7754577799516247, -1.7553205764432858, -1.724210011660198, -1.6827559610829381, -1.6317914352083545, -1.5723355063380817, -1.5055719570325978, -1.4328241358715912, -1.3555265971977808, -1.2751941787659644, -1.1933892327827043, -1.1116877701987895, -1.0316453042204767, -0.9547631861985181, -0.8824562151597309, -0.816022271556677, -0.7566146770778864, -0.7052179167773445, -0.6626272789526312, -0.629432874103581, -0.6060083892390582, -0.5925048203361142, -0.5888493066654618, -0.5947490688866295, -0.6097003312559859, -0.6330019899422811, -0.6637736771860193, -0.7009777675964728, -0.7434447807587193, -0.7899015557463606, -0.8390015099908408, -0.8893562487507277, -0.9395677632396674, -0.9882604459506709, -1.0341121610370732, -1.0758836354923484, -1.1124454825707828, -1.1428022312298707, -1.166112812766038, -1.181707046302396, -1.1890977660962252, -1.187988343227564, -1.1782754693718416, -1.160047188181734, -1.1335762773784437, -1.0993091990658375, -1.0578509442028061, -1.0099461969254933, -0.9564573330489772, -0.8983398424269251, -0.8366158250727178, -0.772346254592419, -0.7066027285112851, -0.6404394328952379, -0.5748660381371576, -0.5108222142139771, -0.4491544078935643, -0.3905954624803914, -0.33574758433560126, -0.2850690715501615, -0.2388651210589904, -0.19728292368240732, -0.16031114478193542, -0.12778377425513607, -0.09938821635441955, -0.07467738016182161, -0.053085428256424615, -0.03394674678213868, -0.016517617141548094, -1.5220054590144853e-16], [0.0, 0.016944081643460306, 0.035037054641874864, 0.05507590779524772, 0.07779480047562612, 0.10384150903814413, 0.13375622006001625, 0.16795324784313595, 0.20670617823034318, 0.25013685240670236, 0.29820850521615305, 0.35072326512422186, 0.4073241100126386, 0.4675012573573943, 0.5306028519443104, 0.5958497020392981, 0.6623537087020097, 0.7291395354121537, 0.7951689788529626, 0.8593674287743976, 0.9206517472148514, 0.9779588564894108, 1.0302743023320524, 1.0766600540399844, 1.1162808175802421, 1.1484281700846477, 1.172541874222339, 1.1882277974007458, 1.1952719419951914, 1.193650186860506, 1.1835334449275174, 1.1652880541584438, 1.139471336750295, 1.1068223813220999, 1.068248221925763, 1.024805703118718, 0.9776794291518311, 0.9281562948374237, 0.877597183373819, 0.8274064901051219, 0.7790001890209337, 0.7337731992719705, 0.6930668310417707, 0.658137093172157, 0.6301246288593704, 0.610027010859137, 0.5986740747671837, 0.5967068993263214, 0.604560958016347, 0.6224538684467893, 0.650378057657081, 0.688098544962424, 0.7351559222963374, 0.7908744880544808, 0.8543753672599435, 0.9245943314534387, 1.0003039189792395, 1.080139353044462, 1.162627663601542, 1.246219341976249, 1.3293217961244017, 1.410333830944722, 1.4876803532680432, 1.5598464955929725, 1.6254103664826571, 1.6830736684390113, 1.7316894752258922, 1.7702865287708542, 1.7980894992699334, 1.8145347489105967, 1.8192812473490827, 1.812216403098503, 1.7934566964705656, 1.7633431237025776, 1.7224315853699956, 1.6714784721267413, 1.611421814314362, 1.5433584662821902, 1.468517888838691, 1.388233171875356, 1.3039100019812166, 1.2169943253029112, 1.1289394829358959, 1.0411736041446236, 0.9550680315607486, 0.8719075225275983, 0.7928629227388173, 0.7189669434948776, 0.6510935939202682, 0.5899417263649578, 0.536023049294123, 0.48965484985024754, 0.4509575507484844, 0.41985710616403277, 0.396092121768395, 0.3792254680296503, 0.3686600461776487, 0.3636582655518693, 0.363364701870674, 0.36683133046715316, 0.37304466856461627, 0.3809541176591816, 0.3895007720571916, 0.39764595314950213, 0.4043987411973664, 0.40884180689310656, 0.4101548929244527, 0.40763535995949696, 0.4007152902215921, 0.3889747331199058, 0.3721507789104938, 0.35014225550118105, 0.32300995750984834, 0.29097243265084544, 0.2543974655230016, 0.2137895099980435, 0.1697734258534661, 0.12307497042309767, 0.07449857945266626, 0.024903040943974546, -0.0248242802035064, -0.0737939718509164, -0.1211411444463203, -0.166051326005672, -0.20778498472179482, -0.24570001708752476, -0.2792715918638444, -0.3081088083769996, -0.3319677097703871, -0.3507602858942033, -0.364559204113899, -0.3735981168405633, -0.37826750923913965, -0.3791061664537809, -0.3767884538693835, -0.37210771350964195, -0.36595618187175877, -0.359301926715018, -0.35316338020040755, -0.3485821112732051, -0.3465945295994851, -0.34820324542070913, -0.354348823521096, -0.3658826647083956, -0.383541724853852, -0.40792574015013916, -0.4394775688075856, -0.4784671853281259, -0.5249797755760781, -0.5789082812572782, -0.6399506335720786, -0.7076118004076943, -0.7812106523352296, -0.8598915328289628, -0.9426403005079914, -1.0283044987423435, -1.11561720347528, -1.2032240062068784, -1.2897125081216427, -1.3736436353690524, -1.4535840361989651, -1.5281387892826745, -1.5959836399441871, -1.6558959875515717, -1.7067838728702154, -1.7477122581845719, -1.7779259544220551, -1.7968686269007343, -1.80419740281496, -1.7997927069627147, -1.7837630650026204, -1.756444732969568, -1.7183961349709822, -1.6703872149300787, -1.6133839299155333, -1.5485282290282658, -1.4771139701612113, -1.400559324557905, -1.3203763035828153, -1.238138111412699, -1.1554450797670082, -1.0738899750325945, -0.995023483363917, -0.9203206751809458, -0.8511492270425692, -0.7887401367165975, -0.734161607428213, -0.6882967012100321, -0.6518252708581203, -0.6252105774291669, -0.6086908880009825, -0.6022762293016624, -0.6057503496998241, -0.6186778179416226, -0.6404160649436026, -0.6701320578745288, -0.7068231865283542, -0.7493418432526827, -0.7964230918392174, -0.846714749871892, -0.8988091547612059, -0.9512758473547395, -1.002694389445471, -1.0516865330799487, -1.096946980204185, -1.1372720103135117, -1.1715853103764091, -1.1989604139355268, -1.2186392431131956, -1.2300463460786362, -1.232798530893129, -1.2267097118307564, -1.2117909034059782, -1.1882454174647743, -1.1564594368341374, -1.1169882522528802, -1.0705385548308604, -1.017947271507421, -0.9601575135686944, -0.8981922762226492, -0.8331265788746723, -0.7660587698591207, -0.6980817351675233, -0.6302547478346447, -0.5635766732291594, -0.49896120613866285, -0.4372147592791636, -0.3790175511582619, -0.32490835592376066, -0.2752732811182901, -0.23033883360066904, -0.1901694219720752, -0.15466932849882806, -0.12358906767492647, -0.09653593514676924, -0.07298844259560183, -0.05231423406988443, -0.03379098970558927, -0.016629746025206955, -1.5508458470450386e-16], [0.0, 0.01759951738810651, 0.03675343027048783, 0.05824073784591546, 0.08276350242292617, 0.11092418301115346, 0.14320569227732646, 0.17995472130227302, 0.22136879214457258, 0.2674874018602915, 0.31818751578088683, 0.3731835551880642, 0.43203190789407436, 0.49413987259014763, 0.5587788321445578, 0.6251013402492777, 0.6921617027447864, 0.7589395422206971, 0.8243657544637448, 0.8873502000570826, 0.9468104256112151, 1.001700678002922, 1.0510404624475969, 1.093941901602475, 1.1296351780896314, 1.1574913862635405, 1.177042179695619, 1.18799567724239, 1.1902481808426661, 1.183891360139906, 1.1692146701396224, 1.1467028856455126, 1.1170287572625308, 1.081040915307191, 1.039747267002145, 0.9942942458862781, 0.9459423776053879, 0.8960387205241472, 0.8459868205455321, 0.7972148850923162, 0.7511429297259653, 0.7091496810989593, 0.6725400310546916, 0.6425138283725066, 0.6201367670513132, 0.6063140837567378, 0.6017677132089079, 0.6070174703805751, 0.6223667343266464, 0.6478930025458047, 0.6834435695479247, 0.7286364615653251, 0.7828666340633782, 0.8453173129294014, 0.914976237016991, 0.9906564421049565, 1.0710211171710537, 1.1546119658512615, 1.2398804214551593, 1.3252209950071905, 1.409005984171178, 1.489620737858015, 1.5654986576265515, 1.6351551230038828, 1.697219553429896, 1.7504648640493123, 1.7938336349464794, 1.8264603921209117, 1.8476894916127142, 1.8570882034326435, 1.8544547067616064, 1.8398208294565297, 1.8134494902678213, 1.7758269282818566, 1.727649927878624, 1.6698083659289156, 1.6033635181708565, 1.529522661030948, 1.4496105911898682, 1.3650387558674089, 1.2772727404239645, 1.187798895179344, 1.0980908995173657, 1.0095770580325654, 0.923609100819481, 0.8414332186172208, 0.7641640044745126, 0.6927618983987006, 0.6280146419965541, 0.5705231486540087, 0.5206920838759113, 0.47872533278400276, 0.44462641037957873, 0.4182037480310203, 0.39908066977203677, 0.38670975735708335, 0.38039119644242164, 0.37929460036443585, 0.3824837251194862, 0.38894342133080495, 0.39760811785774164, 0.40739109848169586, 0.4172138185631332, 0.42603451300900613, 0.4328753701494776, 0.4368475875566102, 0.43717368435278886, 0.4332065186343652, 0.4244445463714175, 0.4105429572935852, 0.3913204313083887, 0.36676137317733737, 0.33701360060113966, 0.30238157856608905, 0.26331540780338114, 0.22039588460767656, 0.17431605029051628, 0.1258597386611631, 0.0758777068619552, 0.025261996700504635, -0.025080781237820565, -0.0742565210807652, -0.12141032430761152, -0.16575211295230205, -0.20658046312133643, -0.24330401465176693, -0.2754598753872534, -0.302728516197309, -0.3249447435452014, -0.3421044378326636, -0.35436685535190304, -0.36205240668653954, -0.36563594191374504, -0.3657356899949034, -0.3630981133350837, -0.3585790457593301, -0.35312158036809593, -0.3477312603910092, -0.34344919903996873, -0.3413238115943594, -0.34238188304769074, -0.34759971654821714, -0.35787511097257196, -0.3740009001474157, -0.39664075181979563, -0.42630787227861827, -0.4633471938001484, -0.5079215384984178, -0.5600021557505849, -0.6193639235056095, -0.685585389106315, -0.7580537055948757, -0.8359743977954509, -0.9183857717975574, -1.0041776648042133, -1.0921141225714088, -1.1808594915967108, -1.2690073253270824, -1.355111430166156, -1.4377183198335, -1.5154003071291926, -1.5867884414167541, -1.65060449872563, -1.705691249383682, -1.7510402651341064, -1.785816582913483, -1.809379614561731, -1.8212997789761245, -1.8213704335102507, -1.8096147923296948, -1.7862876382797672, -1.751871758707917, -1.7070691615979703, -1.652787253244653, -1.590120279476886, -1.520326446175498, -1.444801238744233, -1.3650475517389427, -1.282643316796977, -1.199207377451546, -1.1163644018818537, -1.0357096480964427, -0.9587743998966997, -0.8869928761227409, -0.8216713805284686, -0.7639604060242744, -0.7148303362727015, -0.6750513014525408, -0.6451776455248988, -0.6255373519701366, -0.6162266564119636, -0.6171099506971112, -0.6278249568766268, -0.6477930242110185, -0.6762342808468879, -0.7121872571401122, -0.7545324925123333, -0.8020195447671291, -0.8532967422020524, -0.9069429565189108, -0.9615006299410613, -1.015509264138744, -1.0675385721231183, -1.1162205073011182, -1.1602794160113803, -1.19855961024146, -1.2300497245655044, -1.2539033039312553, -1.2694551646845964, -1.2762331777470484, -1.2739652374940946, -1.262581299763307, -1.2422104945697938, -1.213173440493435, -1.1759700053231221, -1.1312628684942667, -1.079857342405617, -1.0226779993581256, -0.9607427264317296, -0.8951348902704136, -0.8269743360468972, -0.7573879688266016, -0.6874806706067519, -0.6183072924035808, -0.5508464283053578, -0.48597662827080856, -0.42445563994129715, -0.36690318856833143, -0.3137877104163353, -0.26541735107710623, -0.22193542867070806, -0.18332044573681275, -0.1493906156837817, -0.11981275294347293, -0.09411526342708769, -0.07170486633234507, -0.051886582476702886, -0.03388644054155227, -0.016876283018268573, -1.5928009826931165e-16], [0.0, 0.01840260258950482, 0.038763442130230766, 0.06183553250324113, 0.08828110629297058, 0.1186500741353602, 0.15336157074376852, 0.19268909294919037, 0.23674964210939203, 0.28549717954637704, 0.33872059188494924, 0.39604624611452977, 0.456945094844103, 0.5207441735892294, 0.5866422170284151, 0.6537290129112993, 0.7210080134471216, 0.7874216370700121, 0.8518786206931088, 0.9132827257996288, 0.9705620624497902, 1.0226982745453808, 1.0687548280632293, 1.1079036615413729, 1.1394494944928653, 1.1628511437755755, 1.1777392689542625, 1.1839300536268753, 1.1814344284467393, 1.1704625507276092, 1.151423372376172, 1.1249192495650853, 1.0917356710211175, 1.0528263039880514, 1.0092936747879648, 0.9623659115029942, 0.9133700768622675, 0.8637027074173913, 0.8147982483030081, 0.7680961294459271, 0.7250072675549688, 0.6868807975863525, 0.6549718370989644, 0.6304110669371304, 0.6141768724389958, 0.6070707317755876, 0.6096964634430512, 0.622443855143326, 0.645477093459284, 0.6787283003463727, 0.7218963612749647, 0.7744511038128243, 0.8356427576059031, 0.9045165002163873, 0.9799317711992755, 1.0605859221272553, 1.1450416658143179, 1.231757696299616, 1.319121774481794, 1.4054855145212684, 1.4892000647217496, 1.5686518545815262, 1.6422975776142965, 1.708697597435368, 1.7665470020592764, 1.8147035874481774, 1.852212124719221, 1.8783243542735253, 1.8925142522807687, 1.8944882279482862, 1.8841900310646216, 1.8618002754819338, 1.8277306124135269, 1.7826127145490724, 1.7272823549373453, 1.6627589803668432, 1.5902212847801078, 1.5109793815276762, 1.4264442517532752, 1.3380952080200796, 1.2474461559679513, 1.1560114613105639, 1.0652722342894099, 0.9766438287343145, 0.8914453185597498, 0.8108716617509956, 0.7359691920148429, 0.6676149930560367, 0.6065006120370731, 0.553120459650916, 0.5077651271082507, 0.4705197281297682, 0.44126724977536047, 0.4196967727155694, 0.4053163024031421, 0.39746984047297956, 0.39535822334508636, 0.39806316493635596, 0.40457386480103946, 0.4138154837494412, 0.4246787474623893, 0.4360499158030543, 0.44684035193687244, 0.4560149410330508, 0.462618642785285, 0.46580051433379793, 0.4648346090296652, 0.4591372400788808, 0.4482801942955425, 0.43199958752687584, 0.4102001670835435, 0.38295498483051105, 0.3505004844704716, 0.3132271649525483, 0.27166609587364365, 0.2264716673342367, 0.17840105327820696, 0.12829095145560174, 0.07703223268218878, 0.02554318528238138, -0.0252579238429574, -0.07448023307538162, -0.12128687837987397, -0.16492007844273626, -0.2047240363038572, -0.24016503779188572, -0.27084819967656243, -0.2965304071769807, -0.31712907911544386, -0.33272650708975043, -0.3435696298190607, -0.3500652223958979, -0.35277059954728585, -0.35238004914658283, -0.34970732415208106, -0.34566462503433065, -0.3412385979453426, -0.33746395399864704, -0.3353953800138089, -0.33607845925350643, -0.34052035078594217, -0.34966098733156326, -0.3643455434642956, -0.3852988989780376, -0.4131027767213129, -0.44817617133208015, -0.490759606592746, -0.5409036664934576, -0.5984621408130445, -0.663090012670172, -0.7342463958635578, -0.8112024068732709, -0.8930538331883108, -0.9787383392255071, -1.0670568365151294, -1.1566985389157391, -1.2462691290424992, -1.334321381231195, -1.4193875212627263, -1.500012555400942, -1.5747877722845878, -1.642383611636339, -1.7015811039049398, -1.7513011146494142, -1.7906306760337627, -1.8188457540866412, -1.835429882813846, -1.840088192852092, -1.8327564707886912, -1.8136050029159547, -1.7830370811838145, -1.7416821764413626, -1.690383911613618, -1.6301830921302167, -1.5622961696615736, -1.4880896251207758, -1.4090508552660015, -1.326756231678122, -1.24283706932104, -1.1589442926385318, -1.0767126189535874, -0.9977250910304114, -0.9234787827334573, -0.8553524739611669, -0.7945770441176252, -0.7422092684567383, -0.6991096202738873, -0.6659245861149716, -0.6430738932605331, -0.6307429313566817, -0.6288805260689109, -0.6372020950529949, -0.6551980884783828, -0.6821474909214419, -0.7171360417186464, -0.7590787197403022, -0.8067459387061684, -0.8587928130275868, -0.9137907837987352, -0.9702608416544933, -1.0267075490145758, -1.081653049532109, -1.133670257667454, -1.181414446035322, -1.2236524918628247, -1.2592891054198545, -1.2873894410758453, -1.3071975837354777, -1.3181505074980981, -1.319887216868314, -1.312252900888942, -1.2952980541868615, -1.2692726430499766, -1.2346155162168047, -1.1919393760568753, -1.1420117333928281, -1.0857323657223004, -1.0241078816785343, -0.9582240622015028, -0.889216699443652, -0.818241686701969, -0.7464451259055143, -0.6749342131254057, -0.6047496374247238, -0.5368401848182581, -0.4720401783131831, -0.4110503085283059, -0.35442231920690037, -0.30254791035181317, -0.25565211130873944, -0.21379125970800447, -0.1768556026976962, -0.14457641738429933, -0.11653743086126614, -0.0921902095923181, -0.07087308601396637, -0.051833099597667, -0.03425035254737362, -0.017264118740909922, -1.6483396539325373e-16], [0.0, 0.019354879975317565, 0.041066090044411835, 0.06585269020662393, 0.09432952365059122, 0.1269870360174507, 0.1641745274235019, 0.20608729759464028, 0.2527580435251474, 0.3040527587693358, 0.3596712665969465, 0.41915239875049465, 0.48188371048672307, 0.5471155040337825, 0.6139788195595633, 0.681506948098337, 0.7486599272886273, 0.8143514006267984, 0.8774771562954522, 0.9369446141543039, 0.9917025004261146, 1.040769939753802, 1.0832642039490832, 1.1184263857117482, 1.1456443132013021, 1.1644720864506561, 1.1746456976456126, 1.176094292273471, 1.1689467347357152, 1.1535332575949409, 1.13038209532637, 1.1002111282517832, 1.0639146871464522, 1.0225457907184252, 0.9772942037251848, 0.9294608100217268, 0.8804288896510232, 0.831632969801533, 0.7845259840203573, 0.7405455208338418, 0.7010799706761368, 0.6674353880146248, 0.6408038735303583, 0.6222342493971131, 0.6126057498287311, 0.6126053803270993, 0.6227095141014077, 0.6431701949848599, 0.6740065052424733, 0.7150012366317677, 0.7657029768639844, 0.8254335942903146, 0.8933009743597059, 0.9682167353192138, 1.0489185308373088, 1.133996436656621, 1.2219228197341685, 1.3110850040229607, 1.3998199791581607, 1.4864503485023113, 1.56932068250383, 1.6468334328853567, 1.7174835730667635, 1.7798911602072305, 1.8328310635955671, 1.8752591716275135, 1.9063344736382462, 1.9254365113588612, 1.9321778053347287, 1.9264109815844566, 1.908230450165969, 1.8779686170700867, 1.8361867408211647, 1.7836606721657198, 1.721361836185958, 1.6504339281497216, 1.5721658946891464, 1.4879618580652187, 1.3993087112518778, 1.3077421636892674, 1.2148120505802253, 1.1220477317771453, 1.0309243993573802, 0.9428310861388126, 0.8590411213571748, 0.7806857156976911, 0.7087312774714908, 0.6439609669783045, 0.5869608893765497, 0.5381112103566414, 0.4975823564730866, 0.4653363361781398, 0.441133091533445, 0.4245416673743032, 0.41495586740409557, 0.4116139581906838, 0.4136218849843052, 0.4199793800490921, 0.429608276820407, 0.44138229329164114, 0.4541575167823593, 0.46680281036280874, 0.4782293689416144, 0.4874186801077593, 0.4934481905165111, 0.49551404171943103, 0.4929503182264965, 0.48524434322687215, 0.4720476614173333, 0.4531824611457229, 0.4286433067086907, 0.3985941731432449, 0.363360897147534, 0.3234192757947375, 0.27937915648764844, 0.23196496432393812, 0.18199320411740966, 0.13034755145840796, 0.07795220845944872, 0.02574424368336963, -0.025354338906373074, -0.07446405093069955, -0.12077415255746685, -0.163566961518548, -0.2022395824278214, -0.23632246767846446, -0.26549430339515884, -0.2895928091994297, -0.308621146503938, -0.3227497440034744, -0.33231346809308543, -0.3378041871025872, -0.33985889842178507, -0.33924370375364565, -0.33683402692290254, -0.33359156810665014, -0.3305385755043705, -0.32873008809609705, -0.32922485937899204, -0.3330557103632577, -0.3412000796324536, -0.3545515383869353, -0.37389301903415556, -0.39987246749558036, -0.43298157287433464, -0.4735381548334944, -0.5216727007575993, -0.5773194436730783, -0.6402122604757488, -0.7098855510071992, -0.7856801348841667, -0.8667540777852815, -0.9520982352531082, -1.040556183060102, -1.1308480917904975, -1.2215980022993944, -1.3113638706669355, -1.3986696783947674, -1.4820388477490996, -1.5600281647760816, -1.6312613945841343, -1.6944617755079565, -1.748482600752424, -1.7923351375799252, -1.8252131940887788, -1.8465137207115572, -1.8558529258943535, -1.8530774907761922, -1.8382705835225768, -1.8117524974668295, -1.7740758653731217, -1.7260155318325117, -1.6685532938724599, -1.6028578431715046, -1.5302603588079189, -1.4522263044047703, -1.3703240752925911, -1.2861912176435424, -1.2014990005630393, -1.1179161624042766, -1.0370726731044912, -0.9605243546190035, -0.8897191815352986, -0.8259660441670553, -0.7704066978226235, -0.723991545941736, -0.6874598132502582, -0.6613245602283798, -0.6458628745802855, -0.6411114518525085, -0.6468676488860907, -0.6626959635345933, -0.6879397652078887, -0.7217379764453192, -0.7630462889024551, -0.8106623906861785, -0.863254588468315, -0.9193931295028422, -0.9775834674437608, -1.0363006731660827, -1.0940241686293863, -1.1492719587091216, -1.200633552878016, -1.2468008051779416, -1.2865959561292182, -1.3189962326696887, -1.343154450068307, -1.3584151608097828, -1.364326007169037, -1.3606440537999938, -1.3473370011770391, -1.3245793070592762, -1.2927433681687464, -1.2523860348959235, -1.2042308450959873, -1.1491464661348372, -1.088121924759976, -1.0222392799044087, -0.9526444523526271, -0.8805169658978754, -0.8070393762442409, -0.7333671659785524, -0.6605998664669203, -0.5897541310177323, -0.5217394290705613, -0.4573369599416053, -0.39718229861742543, -0.34175218744365565, -0.291355778819077, -0.24613051794213014, -0.2060427342093986, -0.17089288808239078, -0.1403253001976578, -0.11384207422552688, -0.09082081739056946, -0.07053566536203093, -0.052181033850437826, -0.0348974498281778, -0.017798762569482696, -1.7177933406592033e-16], [0.0, 0.020456304560240515, 0.04365716159622423, 0.07027982011487062, 0.10088443070505276, 0.1358954518937437, 0.17558681418955063, 0.22007125158027147, 0.2692941020427069, 0.3230317625261685, 0.3808948628252325, 0.44233609982832284, 0.5066625519325318, 0.5730521760394276, 0.6405740794735619, 0.708212059196756, 0.7748908133780587, 0.8395041579578054, 0.9009445251796581, 0.9581329836039103, 1.0100490008510097, 1.055759171768337, 1.0944441558845148, 1.125423108438088, 1.1481749479822025, 1.1623558791549227, 1.1678126798218174, 1.1645913652195945, 1.1529409554081211, 1.1333121934627683, 1.1063511874072183, 1.0728880757785735, 1.0339209417717614, 0.9905953210071259, 0.9441797600983709, 0.8960379845531915, 0.8475983225629574, 0.8003211037026077, 0.7556648066203236, 0.715051766028623, 0.6798342657574465, 0.6512618408262549, 0.6304505874665481, 0.6183552363088178, 0.6157446815563523, 0.6231815793827761, 0.6410065339180684, 0.6693272813163834, 0.7080131641399111, 0.7566950625179644, 0.8147708183106174, 0.8814160569968271, 0.9556001824294583, 1.036107195121934, 1.1215608684004081, 1.2104537114215659, 1.301179056303097, 1.3920655306944796, 1.481413118896594, 1.5675299755542595, 1.648769136962264, 1.7235642766174886, 1.7904636737881603, 1.848161606023793, 1.8955264376739132, 1.9316247551329164, 1.955740993766942, 1.967392109009762, 1.9663369623169658, 1.9525802186598473, 1.9263706829516658, 1.8881941350453293, 1.8387608535037012, 1.7789881440464874, 1.7099783063679377, 1.6329925800416354, 1.5494217038938916, 1.460753801278272, 1.368540364249062, 1.2743611512715576, 1.1797888348495091, 1.0863542368125254, 0.9955129700086491, 0.9086142663096011, 0.8268727131661957, 0.7513435459181402, 0.6829020525598437, 0.6222275439638894, 0.5697922282580892, 0.5258552059897522, 0.49046167592535866, 0.4634473129694495, 0.4444476529190378, 0.4329121967284894, 0.42812283264956424, 0.4292160708386307, 0.4352084943264871, 0.445024754833866, 0.4575273836106957, 0.47154764767334945, 0.48591666144140855, 0.4994959632780316, 0.5112067857636755, 0.5200572871347852, 0.525167068170847, 0.5257883724340192, 0.5213234562590879, 0.5113377159922202, 0.49556827110858853, 0.473927820178, 0.4465037091949198, 0.413552275444911, 0.3754886517201471, 0.33287233225432333, 0.2863889102852973, 0.23682849494076383, 0.18506139972003965, 0.13201176408995743, 0.07862982188918276, 0.025863564037886626, -0.025369442362935948, -0.07420932144321427, -0.11987950980893602, -0.1617100421754159, -0.19915787288732403, -0.23182368193358924, -0.259464705386945, -0.2820032334197357, -0.2995305315568641, -0.3123060597752643, -0.3207519864350338, -0.32544311672959286, -0.32709247525944585, -0.3265328964218406, -0.32469508166572897, -0.32258267660318085, -0.3212450010934601, -0.3217481296672079, -0.32514506637416035, -0.33244578609501685, -0.34458792280181677, -0.3624088739150952, -0.3866200590193821, -0.4177840214809298, -0.45629499415555846, -0.5023634670168947, -0.556005197216406, -0.6170349932000728, -0.685065486740391, -0.7595109830118817, -0.8395963522143979, -0.9243707998810552, -1.0127262300472446, -1.1034197989770884, -1.19510015006289, -1.2863367255236813, -1.375651470029239, -1.4615521774095128, -1.542566685815481, -1.61727710026783, -1.6843532151801532, -1.7425843233935505, -1.7909086322287615, -1.828439560273864, -1.8544882598272672, -1.8685817974085526, -1.8704765264296475, -1.8601662995288746, -1.8378852904606149, -1.8041053238279292, -1.7595277422166864, -1.7050699712343549, -1.6418470703750858, -1.5711486784077393, -1.494411873157791, -1.4131905644015819, -1.3291221226870265, -1.2438920141719547, -1.1591972603744167, -1.0767095708543455, -0.9980390055702487, -0.9246990117548348, -0.8580736479108573, -0.799387755723169, -0.749680770572865, -0.7097847746317377, -0.680307295322215, -0.6616192387163334, -0.6538482249769999, -0.6568774642009381, -0.6703501791424683, -0.693679449492064, -0.7260632238607235, -0.7665041235042305, -0.8138335490739941, -0.8667395010338265, -0.9237974382651635, -0.9835034298678585, -1.0443088039100683, -1.104655465098777, -1.1630110417614772, -1.2179030313816677, -1.267951142944899, -1.3118970827619758, -1.3486310969993895, -1.377214667177011, -1.3968988523002677, -1.4071378806390684, -1.4075977127195771, -1.3981594219072409, -1.3789173669315993, -1.3501722586658738, -1.3124193482642126, -1.2663320823007471, -1.212741679932065, -1.1526131846377852, -1.0870186264019268, -1.017107997258841, -0.9440787923280805, -0.8691448986376024, -0.793505624494641, -0.7183156527121858, -0.6446566719367773, -0.5735113924393549, -0.5057405872828036, -0.44206371846161574, -0.3830436125081304, -0.3290755436048803, -0.28038096714178684, -0.23700602583104868, -0.1988248270005363, -0.16554736664977734, -0.13673185637658358, -0.1118010963787705, -0.09006243424718799, -0.07073075779636062, -0.052953893025413125, -0.03583971740050264, -0.01848425552582099, -1.8013499053311108e-16], [0.0, 0.021705213273331376, 0.046529215190566416, 0.07509978279390774, 0.10791540961847756, 0.14532851680387734, 0.1875327218744153, 0.23455451911555228, 0.286249610776895, 0.3423040073383463, 0.4022398908509021, 0.46542611105572973, 0.5310930627477723, 0.5983515777620492, 0.6662153589492167, 0.733626389273979, 0.799482669124724, 0.8626675711210077, 0.9220800557975314, 0.9766649647323703, 1.0254426006991324, 1.0675368174868813, 1.10220087487485, 1.1288403661016742, 1.1470325947837179, 1.1565418639194711, 1.1573302392668068, 1.1495634605432488, 1.1336117938294394, 1.110045744280904, 1.0796266766499354, 1.0432925189912527, 1.0021388490811138, 0.9573957804140578, 0.9104011722113076, 0.8625707829728568, 0.8153660673279044, 0.770260379245676, 0.7287043894359407, 0.6920915498265786, 0.6617244426708812, 0.6387828359294548, 0.6242942304186218, 0.6191076286480113, 0.6238711815946577, 0.6390142796387615, 0.6647345496832594, 0.700990104614788, 0.7474972665484775, 0.8037338547668803, 0.8689479960956711, 0.942172282906691, 1.0222429752431461, 1.107823821872356, 1.1974339633707458, 1.2894792813739113, 1.382286474312725, 1.474139073365993, 1.5633145646322208, 1.6481217558376313, 1.7269375189443517, 1.7982420539839883, 1.8606518539878116, 1.9129496051815578, 1.9541103293429603, 1.9833231646147498, 2.0000082849484633, 2.003828574194324, 1.99469579582703, 1.9727711303615698, 1.9384600864747554, 1.8924019254456983, 1.8354538685121444, 1.768670479950907, 1.6932787321400777, 1.6106493598013283, 1.5222651966152245, 1.4296872563837557, 1.3345193712349532, 1.2383722298377673, 1.1428276685237981, 1.049404057404131, 0.9595235923429747, 0.8744822528245577, 0.7954231166267379, 0.7233136365423175, 0.6589273843199198, 0.6028306550340999, 0.5553742040299109, 0.5166902614311699, 0.4866948391076783, 0.4650952151845332, 0.45140235485175495, 0.4449479065066388, 0.44490530207573215, 0.4503143924162272, 0.46010896537590756, 0.4731464274162545, 0.4882388812760251, 0.5041848031166074, 0.5198005136043126, 0.5339506486064054, 0.545576866261083, 0.5537240772856714, 0.5575635531985543, 0.5564123508947888, 0.5497485895845906, 0.5372222249873766, 0.5186610831034009, 0.49407203888212353, 0.46363735055882505, 0.42770628516962267, 0.38678229163332206, 0.34150609176152, 0.29263516375817006, 0.2410201845778673, 0.18757907462414297, 0.13326934875261395, 0.07905951988675029, 0.02590032470164425, -0.025303455787126, -0.07371982434905257, -0.11861432386608414, -0.15937205571208057, -0.19551636551038995, -0.2267236883710791, -0.25283414558533346, -0.27385759520132025, -0.28997495712625754, -0.3015347563991096, -0.3090449529406668, -0.3131602492518502, -0.31466518607109367, -0.3144534469051671, -0.3135038927912051, -0.3128539360673888, -0.3135709340861165, -0.31672233883779927, -0.3233453749342194, -0.33441703536010553, -0.3508251813610803, -0.37334150981726305, -0.4025971089775203, -0.4390612625111757, -0.48302408394740454, -0.5345834706207957, -0.5936367605088153, -0.6598773594413933, -0.7327964829531357, -0.8116900295913304, -0.8956704739579671, -0.9836835413550893, -1.0745293047781157, -1.166887232195233, -1.2593446103965729, -1.3504276837579337, -1.4386347742692756, -1.522470594965755, -1.6004809338706745, -1.6712868706441955, -1.7336176937627485, -1.7863417121575018, -1.828494201236233, -1.8593017880285154, -1.8782026622898116, -1.8848620978074737, -1.8791828785206406, -1.8613103447234047, -1.8316319026351071, -1.7907709728759893, -1.7395754866544888, -1.6791011694982676, -1.6105899779393247, -1.5354441716184202, -1.4551966089358037, -1.3714779460496298, -1.2859814944578174, -1.2004265497360156, -1.1165210418290565, -1.0359243746679758, -0.9602113193719716, -0.8908378009686461, -0.8291093740098913, -0.7761531187543375, -0.7328936082776465, -0.7000334999384923, -0.6780391944312313, -0.6671318848812385, -0.6672841900284165, -0.6782224326268314, -0.6994344900006897, -0.7301830115044483, -0.7695236706519515, -0.8163280009894827, -0.8693102572677057, -0.927057649717614, -0.9880632215149561, -1.0507605796893504, -1.11355964921954, -1.174882599800159, -1.2331990952137868, -1.2870600363316507, -1.335129009925896, -1.376210715642414, -1.4092757211265854, -1.4334809884579065, -1.4481857213981113, -1.4529621998355509, -1.4476013923063347, -1.4321132664984453, -1.4067218480019357, -1.371855206034098, -1.328130668274245, -1.276335682253057, -1.2174048451274941, -1.1523937145833265, -1.082450088832704, -1.0087835013978688, -0.9326337152172274, -0.8552390196728193, -0.7778051330089174, -0.7014754913847586, -0.6273036650757102, -0.5562285831871803, -0.48905317221299177, -0.42642692281208566, -0.36883279562104754, -0.3165787634029812, -0.2697941662377515, -0.22843093183969204, -0.19226958759697846, -0.16092986772979934, -0.1338856011677179, -0.11048345631587415, -0.08996502056676282, -0.0714916076884074, -0.05417111720573247, -0.0370862183176295, -0.01932309804499445, -1.899048771147814e-16], [0.0, 0.023098311882311554, 0.0496715982673261, 0.08029078354581906, 0.11538615866212096, 0.15523260264843092, 0.19993913324214144, 0.24944307983183284, 0.30350905165611647, 0.3617327492567243, 0.42354954082961255, 0.4882476005301835, 0.5549852861337717, 0.6228123217717987, 0.6906942506013012, 0.7575395347957803, 0.8222286084096507, 0.8836441343180382, 0.9407016809824799, 0.9923800191828012, 1.0377502435309147, 1.0760029484799682, 1.1064727330912225, 1.1286593719566254, 1.1422450698647686, 1.147107313079335, 1.1433269381279327, 1.1311911571075415, 1.1111914037750126, 1.0840159939965548, 1.0505377242604432, 1.0117966596659707, 0.9689784848955595, 0.9233889050951163, 0.8764246854780156, 0.8295420062584564, 0.7842228809827437, 0.7419404396345606, 0.7041239116613727, 0.6721241574032438, 0.6471805889065027, 0.630390292891332, 0.6226801203454909, 0.6247824399645574, 0.6372151680513113, 0.6602665875534228, 0.6939853560717049, 0.7381759796456054, 0.7923998989086759, 0.8559821999767636, 0.9280238274617827, 1.0074190445933942, 1.0928777588210175, 1.1829522135620416, 1.2760674408473756, 1.3705547780945382, 1.464687677363118, 1.5567189790633753, 1.6449187855898906, 1.727612054646153, 1.803215037511664, 1.8702697140604034, 1.927475423332402, 1.9737169547520135, 2.00808844906814, 2.0299125577208756, 2.0387544221907, 2.0344301582122055, 2.0170096605306487, 1.9868136789610022, 1.9444052525871527, 1.8905757227026556, 1.8263256732924964, 1.7528412673751674, 1.671466555469435, 1.5836724262103998, 1.4910229464558973, 1.3951398972439413, 1.297666351283376, 1.200230156367128, 1.1044081867822582, 1.0116922015618839, 0.9234571049039825, 0.8409323413912175, 0.7651770783746683, 0.6970597320524381, 0.6372422847808314, 0.5861697217199483, 0.5440647880076209, 0.5109281364245709, 0.4865438032079066, 0.47048981955775737, 0.4621536416693007, 0.46075196587518935, 0.46535439055016753, 0.4749102953722536, 0.4882782335648455, 0.5042570756685772, 0.5216181055689519, 0.5391372518122747, 0.5556266400515524, 0.569964675637985, 0.581123908267125, 0.5881959920659517, 0.5904131329708052, 0.5871655086778101, 0.5780142524587666, 0.5626997080276303, 0.541144785474702, 0.513453374947717, 0.4799039020507382, 0.44093823364186996, 0.3971462616976903, 0.3492466031825221, 0.2980639526434735, 0.24450370906892707, 0.1895245672741185, 0.1341098149944347, 0.07923810870682625, 0.025854513174857117, -0.025157418463252465, -0.0730017753505924, -0.11699392891234037, -0.1565810461165323, -0.1913589215650138, -0.2210846699085013, -0.24568492784041931, -0.26525933179136146, -0.2800791604585384, -0.29058115734493234, -0.29735667435550095, -0.30113640000880226, -0.3027710518599638, -0.3032085193430954, -0.3034680377100429, -0.3046120536522829, -0.307716506491098, -0.3138402938702031, -0.32399471650302886, -0.339113702018483, -0.3600255931228779, -0.3874272504699709, -0.4218611666260286, -0.46369621563503277, -0.5131125746834732, -0.5700912523946683, -0.6344085448631681, -0.7056356184757783, -0.7831432908849346, -0.8661119513766412, -0.9535464325517125, -1.0442955199454018, -1.1370756680835905, -1.230498383479324, -1.3231006399322045, -1.4133776116123278, -1.4998169468243736, -1.5809337616652062, -1.6553055091549331, -1.7216058764867046, -1.778636880944262, -1.8253583734022725, -1.8609142162706727, -1.8846544789024702, -1.8961530860344766, -1.89522046154444, -1.8819108281042793, -1.8565239503164472, -1.81960124154784, -1.7719162896891452, -1.7144599911689204, -1.648420612460912, -1.575159220858162, -1.496181038443335, -1.4131033722081032, -1.3276208567303074, -1.2414688116514743, -1.1563855627838373, -1.0740746018611083, -0.9961674650755663, -0.9241881944756716, -0.8595202094127241, -0.8033763584108181, -0.7567728464691152, -0.7205076407199781, -0.6951438508019786, -0.6809984618574507, -0.678136670615192, -0.6863719416742184, -0.705271765111039, -0.7341689612006348, -0.772178246661443, -0.8182176525990216, -0.8710342702454199, -0.9292336994335716, -0.9913124889500904, -1.0556927895380177, -1.1207583910056649, -1.1848912858007508, -1.2465078931948361, -1.3040940910416419, -1.3562382355575633, -1.4016614028488918, -1.4392441576185044, -1.4680492428144745, -1.487339686717552, -1.4965919385367163, -1.4955037671387539, -1.4839967870094346, -1.4622136077219905, -1.4305097348046107, -1.389440477705451, -1.33974324140531, -1.2823156891585825, -1.2181903621385486, -1.1485064250294998, -1.0744792728301937, -0.9973687817229685, -0.9184470146998165, -0.8389662000941388, -0.7601277881264339, -0.6830533574269393, -0.608758091141755, -0.5381274720316436, -0.4718977597487167, -0.41064071343541486, -0.35475291148466087, -0.30444990055823695, -0.2597652808173836, -0.22055470694040435, -0.1865046581023522, -0.15714570785838558, -0.13186990988200903, -0.10995181065347763, -0.09057250810489222, -0.07284609821603578, -0.05584779154607741, -0.038642940178910165, -0.020316193585118176, -2.0107776575631545e-16], [0.0, 0.024630679548970996, 0.053070500851106664, 0.08582651792757452, 0.12325476965804633, 0.16554770301340427, 0.21272616481307727, 0.26463619019787155, 0.3209506910056294, 0.38117601941677376, 0.4446632548414754, 0.5106239382830718, 0.5781498614771311, 0.6462364109475153, 0.7138088724721653, 0.7797510217326646, 0.8429352641809282, 0.9022535430173847, 0.9566482097963821, 1.0051420482201123, 1.0468666583042363, 1.0810884449324636, 1.1072315109918285, 1.1248968294370256, 1.1338771589594003, 1.1341672722140825, 1.1259691812135457, 1.1096921686640104, 1.085947563620031, 1.0555383316373412, 1.0194436803274982, 0.9787990075923525, 0.9348716386752186, 0.889032906521954, 0.8427272250665878, 0.7974388845328623, 0.7546573596486327, 0.7158419642116536, 0.6823867076046477, 0.6555862100187541, 0.6366035132103914, 0.62644058301192, 0.625912239477955, 0.6356241719030531, 0.655955600874092, 0.6870470403122123, 0.7287934917580291, 0.7808432738912311, 0.8426025555990428, 0.9132455241032321, 0.991729984065933, 1.0768180525391877, 1.1671014913139128, 1.2610311056867902, 1.3569495396639695, 1.4531267145944606, 1.5477970932207588, 1.6391979057565504, 1.7256074499784497, 1.8053825740700056, 1.876994469177862, 1.9390619379022376, 1.9903813643017723, 2.029952689008932, 2.0570007878322287, 2.0709917614608426, 2.071643764927331, 2.058932135378243, 2.03308871228808, 1.9945953822286357, 1.944172017316044, 1.8827591091705076, 1.8114955254150409, 1.7316919303730902, 1.6448005129257213, 1.5523817500120092, 1.456069001945891, 1.3575317839636034, 1.2584385860717833, 1.1604201197081816, 1.065033854847472, 0.9737306754002839, 0.8878244249944094, 0.8084650409121488, 0.736615882960387, 0.6730357586505678, 0.6182660288948071, 0.5726230523975321, 0.5361960951667708, 0.5088506973482985, 0.4902373562152354, 0.4798052549134404, 0.4768206446472016, 0.48038937638012985, 0.4894829795504508, 0.5029676021563823, 0.5196350608658505, 0.5382352031176614, 0.5575087566044573, 0.5762198356550433, 0.5931872889417056, 0.6073141081862913, 0.6176141721802084, 0.6232356730395224, 0.6234806603130945, 0.6178202410768809, 0.6059050878682144, 0.5875710283515116, 0.5628396178701984, 0.5319137253118803, 0.49516829073325314, 0.45313653673277976, 0.4064920315148209, 0.3560271070456505, 0.30262822801394684, 0.24724898416382954, 0.19088143804645358, 0.13452660085441, 0.07916482975574171, 0.02572694052575634, -0.024933190707152632, -0.07206380260999075, -0.11503752534322984, -0.1533701594386795, -0.18673544885975127, -0.21497544469775906, -0.23810617083902125, -0.2563184253366899, -0.26997367803578926, -0.27959515301440924, -0.285854310370782, -0.28955306260650276, -0.2916021732613393, -0.2929963866821615, -0.29478692527292555, -0.29805206203312945, -0.3038665298069174, -0.31327056303850664, -0.32723938204762965, -0.3466539234919123, -0.37227359387780923, -0.4047117763376962, -0.44441475552643267, -0.4916446429959574, -0.5464667878032441, -0.6087420467994991, -0.6781241687640628, -0.754062419267161, -0.8358094420353972, -0.9224342209184963, -1.0128398776032488, -1.1057859172179527, -1.19991442000434, -1.293779575172653, -1.3858798654783524, -1.4746921401909046, -1.5587067617818973, -1.6364629792006535, -1.7065836689010807, -1.7678085941909205, -1.8190253638299578, -1.859297321424164, -1.8878876668633464, -1.904279198171629, -1.9081891645907871, -1.8995788370219122, -1.8786575273149897, -1.8458809202701174, -1.8019437183716578, -1.7477667358926525, -1.6844787127398642, -1.613393245984404, -1.5359813553104025, -1.4538403047096802, -1.368659394045534, -1.2821835083542645, -1.1961752681170439, -1.1123766588452586, -1.032471032303849, -0.9580463641903986, -0.8905606242600576, -0.8313100654274219, -0.7814011694807943, -0.7417269003833057, -0.7129478138145122, -0.6954784561151733, -0.6894793599477805, -0.694854810840366, -0.7112564215826044, -0.7380924135304323, -0.7745423686029751, -0.8195770864111266, -0.8719830606804319, -0.9303909808365378, -0.9933075709276915, -1.059150001222574, -1.1262820496843169, -1.1930511524629646, -1.2578254654540562, -1.3190300632098553, -1.3751814269067175, -1.4249194189920353, -1.467036007378565, -1.5005000849714472, -1.5244778288206149, -1.5383481548252693, -1.5417129458958796, -1.5344018607721115, -1.5164716640967162, -1.4882001525563802, -1.4500748836084356, -1.4027770392741925, -1.3471608746017816, -1.284229305816427, -1.2151062843128608, -1.1410066772923964, -1.0632044322094638, -0.9829998389308359, -0.9016867197779469, -0.8205203730826987, -0.7406870707221676, -0.6632758650040212, -0.5892533964438088, -0.5194423130636926, -0.4545038159298887, -0.3949247371828482, -0.3410094385599281, -0.2928766933638962, -0.25046158615624975, -0.21352233540143448, -0.181651818110003, -0.15429345540233025, -0.13076100685938954, -0.11026172233153342, -0.09192221502669708, -0.0748163513192347, -0.05799440251635462, -0.04051267303890915, -0.02146280887520191, -2.1362709262396706e-16], [0.0, 0.026295791157511326, 0.05670904423297732, 0.09167636842672015, 0.13147407038648493, 0.1762079537363035, 0.22580789144775812, 0.2800273303420706, 0.33844775833771823, 0.40048803542653844, 0.4654183620609731, 0.5323785368992467, 0.6004000427792597, 0.6684313982560652, 0.7353661246346147, 0.8000726073990124, 0.8614250781126758, 0.9183349096161506, 0.9697814045663312, 1.0148412654150847, 1.0527159626667966, 1.0827562670135882, 1.1044832785510454, 1.1176053710787395, 1.1220305694069688, 1.1178739901597938, 1.105460098998568, 1.0853196664513367, 1.0581814374059573, 1.0249586624956297, 0.986730769747039, 0.9447205787136307, 0.9002675737692857, 0.8547978554072091, 0.8097914756905933, 0.7667479342145427, 0.7271506622613944, 0.6924313539269578, 0.6639350130253528, 0.6428865732269238, 0.6303599163581427, 0.6272500608296862, 0.6342492200012482, 0.6518273406582029, 0.6802176268201322, 0.7194074363608908, 0.7691348102508938, 0.8288907597411371, 0.8979272987750664, 0.9752710707115106, 1.059742283451695, 1.1499785385942234, 1.2444630214468368, 1.3415564125219044, 1.4395317901481772, 1.5366117202877698, 1.6310066753726287, 1.720953890316088, 1.8047557516553372, 1.8808168253573956, 1.947678659958917, 2.004051553664937, 2.048842545549743, 2.08117898035118, 2.1004271013579943, 2.1062052440049697, 2.0983913311387536, 2.077124506374471, 2.0428008812328438, 1.9960635114406324, 1.9377868544967332, 1.8690560910297873, 1.791141813435342, 1.7054706938503674, 1.613592837075855, 1.5171466003406084, 1.417821718983745, 1.3173216138628583, 1.2173257717162467, 1.1194530834920051, 1.0252269980071882, 0.9360432999455047, 0.8531412533791941, 0.7775787664228837, 0.7102121314414821, 0.6516807809676138, 0.6023973749810498, 0.562543403553986, 0.5320703533323565, 0.5107063502543868, 0.49796805765857305, 0.4931774817826518, 0.4954832187229724, 0.5038855710948399, 0.5172648714872843, 0.5344122755488474, 0.5540622319587563, 0.5749258009469036, 0.5957239782431244, 0.6152201876590594, 0.6322511327058143, 0.6457552449799305, 0.6547980332608628, 0.6585937206388829, 0.6565226553920206, 0.6481440922420171, 0.6332040612225567, 0.6116381686310953, 0.5835693051910307, 0.5493003673262926, 0.5093022250508417, 0.4641972911909655, 0.4147391584436516, 0.36178887032577195, 0.3062884768932515, 0.2492325940868661, 0.19163873499788286, 0.1345172110162018, 0.07884140999855395, 0.025519247063354587, -0.024633448307747805, -0.07091689667985832, -0.11276804215830988, -0.14977737877049813, -0.18170147406214235, -0.20847084649234432, -0.23019297435998126, -0.24715034096007787, -0.2597935502331243, -0.26872967604598375, -0.27470613315863907, -0.2785904757123277, -0.28134663672438975, -0.2840082168483531, -0.2876495101303811, -0.2933550166234282, -0.30218823489988067, -0.3151605505980252, -0.33320103951629865, -0.35712798532019024, -0.38762287306088966, -0.42520756134631504, -0.4702252595685258, -0.5228258439471217, -0.5829559395759928, -0.6503540777939818, -0.7245511119600965, -0.804875943237386, -0.8904664745514626, -0.9802855788201273, -1.0731417401540986, -1.1677139072003315, -1.2625799891453349, -1.356248329858936, -1.4471914166494777, -1.5338810191369903, -1.6148239124058825, -1.6885973179636473, -1.7538831966875006, -1.809500549940089, -1.8544349279043046, -1.8878644069337924, -1.9091813788550906, -1.9180095927466823, -1.9142160014070964, -1.897917087803912, -1.8694794782771427, -1.8295147859511154, -1.7788687663517948, -1.7186050042438223, -1.6499834828374704, -1.5744345105297286, -1.4935285931903306, -1.4089429389071373, -1.3224253646301947, -1.2357564382620632, -1.1507107338469955, -1.0690181005142176, -0.9923258471491292, -0.9221627243494072, -0.8599055435519194, -0.8067492112930862, -0.7636808758876866, -0.731458786337136, -0.7105963513762436, -0.7013517629599886, -0.7037234161866155, -0.717451219870815, -0.7420237520739403, -0.7766910762706483, -0.8204828998530728, -0.8722316305986615, -0.9305997716136342, -0.9941109938969719, -1.0611841404966293, -1.13016934929692, -1.19938543438091, -1.267157639762685, -1.3318548746740773, -1.3919255565822093, -1.4459312262403332, -1.4925771573491515, -1.5307392603490702, -1.5594866735396455, -1.5780995427865814, -1.5860816108345837, -1.5831673657195835, -1.5693236317805916, -1.5447456229942815, -1.5098476134314527, -1.4652485102366035, -1.4117527374507846, -1.3503269512218683, -1.2820732057354445, -1.208199272152644, -1.129986877955869, -1.0487586798244166, -0.9658448084192628, -0.8825498276909843, -0.8001209345026451, -0.7197181869697611, -0.6423874929636754, -0.5690370151896819, -0.500417558071488, -0.4371073966836991, -0.3795018918478079, -0.32780811119288045, -0.28204454662648826, -0.24204588753233985, -0.20747267941502032, -0.1778255729116997, -0.15246375122325395, -0.13062701801634796, -0.11146093537062385, -0.09404432470479814, -0.07741838472527025, -0.060616640765256115, -0.04269492040144216, -0.022760551419523524, -2.275109573175121e-16], [0.0, 0.02808555736260695, 0.060567404190281185, 0.0978056506880359, 0.13999202890289034, 0.1871422243193449, 0.2390931466326732, 0.2955052268143841, 0.35586969631291776, 0.41952067391995534, 0.48565175978720887, 0.5533367175035888, 0.6215537170559556, 0.689212516654699, 0.75518388223398, 0.8183304819698924, 0.8775384509894347, 0.931748799677357, 0.9799878382236472, 1.0213958103619578, 1.0552529701698707, 1.081002396358619, 1.0982689172014812, 1.1068736142071138, 1.1068434814966137, 1.0984159378985627, 1.0820380170561565, 1.058360194154415, 1.0282249429002182, 0.9926502497503806, 0.9528084407440199, 0.9100007964329797, 0.8656285392936273, 0.8211608728935634, 0.7781008305682757, 0.7379497514284167, 0.7021712416141408, 0.6721554977765088, 0.6491848672547429, 0.6344014953225586, 0.6287778647221651, 0.6330909675381662, 0.6479007658300724, 0.6735334973454324, 0.7100702684904026, 0.7573412513068959, 0.8149256675448789, 0.882157604282872, 0.9581375653255979, 1.0417495242260728, 1.1316831116315003, 1.226460445005776, 1.3244669956998614, 1.4239857896079005, 1.5232341556968219, 1.6204021735555225, 1.713691928343081, 1.8013566601919282, 1.881738895784923, 1.9533066724799226, 2.0146870094679605, 2.064695844962061, 2.102363741763617, 2.126956763721013, 2.137992040147784, 2.135247661419702, 2.118766683652941, 2.088855160301616, 2.0460742602979485, 1.991226672543498, 1.9253376317379665, 1.8496310274203114, 1.7655011736183066, 1.674480917861246, 1.5782068530599551, 1.4783824618621348, 1.3767400689723304, 1.2750025015053286, 1.174845360164729, 1.0778607848869144, 0.9855235580843258, 0.8991603278037201, 0.8199226535259857, 0.7487644809732567, 0.6864245415652088, 0.6334140498368611, 0.590009941232821, 0.5562537564706029, 0.5319561404856864, 0.516706787242029, 0.5098895297788747, 0.5107021510067179, 0.5181803779943355, 0.5312254235557843, 0.5486343562529338, 0.5691325154691242, 0.5914071435196304, 0.614141382887041, 0.6360477841271076, 0.6559004887742365, 0.6725652911456114, 0.685026842242873, 0.6924123364345104, 0.6940111152746045, 0.689289730278435, 0.6779021249969255, 0.6596947233035576, 0.634706342226774, 0.6031629806104112, 0.5654676660140485, 0.5221856682754286, 0.4740255058828668, 0.42181627779409736, 0.3664819459228878, 0.30901326988218353, 0.25043815381908824, 0.19179120385702533, 0.1340833128215977, 0.07827208613410537, 0.025233899102957244, -0.02426166805379025, -0.06957433413433346, -0.11021195702731613, -0.14584520311261207, -0.1763176481653024, -0.20165103119110336, -0.22204550910122106, -0.23787489063429915, -0.24967695914213575, -0.25813912244393594, -0.2640797506548908, -0.2684256765884248, -0.27218643512134283, -0.27642590519805516, -0.2822320886968868, -0.29068581236970575, -0.30282917114149177, -0.319634542363688, -0.34197499081940824, -0.37059685357464067, -0.4060952428774707, -0.448893135454968, -0.49922462945026497, -0.557122848021902, -0.6224128538177585, -0.6947098139811917, -0.7734225241415729, -0.8577622652518706, -0.9467568325213535, -1.0392694444180326, -1.1340221150744194, -1.229622958554376, -1.3245967912253092, -1.4174183115172418, -1.5065470668535679, -1.5904633672937207, -1.6677042757481404, -1.7368987963154234, -1.7968013956279134, -1.846323026816299, -1.8845588810275866, -1.9108121660540447, -1.9246133037738875, -1.9257340455512437, -1.914196124895105, -1.8902741966177388, -1.8544929482988395, -1.8076184097202201, -1.7506436256676432, -1.6847689936799817, -1.6113776976212433, -1.5320067871828316, -1.448314559659203, -1.3620449909623988, -1.2749900356132162, -1.1889506685667863, -1.1056975738773922, -1.0269323955726373, -0.9542504544157313, -0.8891058007516879, -0.8327794191577068, -0.7863513264634981, -0.7506772126693598, -0.7263701666027738, -0.7137879074348668, -0.7130258123629252, -0.7239158930367694, -0.7460317320165943, -0.7786992491349638, -0.8210130295346421, -0.8718578137220615, -0.9299346284033353, -0.9937909281012302, -1.0618540242166077, -1.1324670025450039, -1.2039262741002827, -1.2745198687648835, -1.3425655675997092, -1.4064479778930614, -1.4646536849557261, -1.515803665494346, -1.5586822178218789, -1.5922617524162233, -1.6157228902053795, -1.6284694328487022, -1.6301378962922386, -1.6206014328515272, -1.59996810470245, -1.5685736095409912, -1.5269686939088694, -1.4759016179616822, -1.416296154134305, -1.3492257083342087, -1.2758842433830817, -1.1975547582258397, -1.115576131163406, -1.031309169748141, -0.9461027232234619, -0.861260705234548, -0.7780108452605735, -0.6974759376209045, -0.6206482882935481, -0.5483679739304426, -0.4813054265634263, -0.41994874414142913, -0.3645960041031583, -0.31535272778499407, -0.27213451086085083, -0.23467470255403752, -0.2025368873857242, -0.1751318009725678, -0.15173819892631268, -0.1315270980589015, -0.1135887243558696, -0.09696143466361795, -0.08066183042247906, -0.06371525326987149, -0.045185844632141654, -0.024205364691567546, -2.42672288485038e-16], [0.0, 0.029990382108294744, 0.06462296776515718, 0.10417590712613148, 0.1487522160016776, 0.1982747744748158, 0.25248639051908434, 0.31095494090701703, 0.37308346895420014, 0.43812498881474315, 0.5052016224288615, 0.5733275809661309, 0.6414354006195246, 0.7084047554900593, 0.7730931002924544, 0.834367344513451, 0.8911357287976587, 0.9423790645450545, 0.98718050927533, 1.0247530830066467, 1.054464183938725, 1.0758564338391583, 1.0886642729434108, 1.0928258286920587, 1.0884896996596711, 1.0760164226760354, 1.0559745242531127, 1.0291311936930012, 0.9964377512599724, 0.9590102171490766, 0.9181054123542522, 0.8750931377761941, 0.8314250801056008, 0.7886011795800826, 0.7481342634351171, 0.7115137979815502, 0.6801696404580005, 0.6554366783553631, 0.638521228557586, 0.6304700316951816, 0.632142619408359, 0.6441877551232713, 0.6670245542982893, 0.7008287801755306, 0.7455246885360803, 0.8007826627818962, 0.8660227420731201, 0.940424003620355, 1.022939619032006, 1.112317267306932, 1.2071244570121153, 1.3057781905901609, 1.4065782975462766, 1.5077436730875005, 1.607450586857399, 1.7038721745105396, 1.7952181942968544, 1.8797741223489228, 1.9559386742164675, 2.0222588760563656, 2.0774618659080732, 2.120482682289819, 2.1504873920815446, 2.166891020018271, 2.1693698654213645, 2.157867925047199, 2.1325972808916887, 2.0940324550504443, 2.0428988768134415, 1.9801557465915078, 1.9069737136428164, 1.824707906678457, 1.734866965318849, 1.6390788134149081, 1.539053990198382, 1.4365474102892646, 1.3333194574588658, 1.231097328940745, 1.1315375367541696, 1.03619044025773, 0.9464676308237716, 0.8636129164730739, 0.7886775633724755, 0.7225003445504866, 0.6656928266824352, 0.6186301963059108, 0.5814477905580197, 0.5540433578476534, 0.536084934234816, 0.5270240851232908, 0.526114132527085, 0.5324328688140014, 0.5449091513757979, 0.562352681712234, 0.5834861991446381, 0.606979265548661, 0.6314827843842921, 0.6556633856554506, 0.6782368184677567, 0.6979995242482501, 0.7138576155904083, 0.7248525567289782, 0.7301829299946466, 0.7292217759835239, 0.7215291109653587, 0.7068593503070625, 0.6851634982339191, 0.6565860987673509, 0.6214570767749705, 0.5802787283717843, 0.5337082431476221, 0.48253625377430276, 0.4276620086353495, 0.3700658477201127, 0.310779729023992, 0.2508566004330146, 0.19133943936651682, 0.1332307886433075, 0.07746360199361282, 0.024874176764777683, -0.023822104409073907, -0.06805157545571465, -0.10739907554809856, -0.141620273043075, -0.1706491898016052, -0.19460071636013254, -0.21376803922423485, -0.22861503449637272, -0.23976381375554442, -0.24797773523344588, -0.2541403126482035, -0.2592305625259941, -0.2642954256966314, -0.27041997746527974, -0.2786962017136354, -0.2901911452972698, -0.30591528950011626, -0.32679197442063745, -0.3536286899692175, -0.3870910041602165, -0.42767983661537556, -0.47571270418634337, -0.5313094683415968, -0.5943830028469215, -0.6646350780504079, -0.7415576277977028, -0.8244394298944341, -0.9123780944706689, -1.0042971200019104, -1.0989676474749377, -1.1950344225026703, -1.2910453661309798, -1.385484060400474, -1.4768043768346018, -1.563466416916926, -1.643972894827657, -1.7169050752646724, -1.7809573835812003, -1.834969831695555, -1.8779574506906163, -1.9091359886186277, -1.9279432181559952, -1.9340553013475654, -1.9273977752635711, -1.9081508501381492, -1.876748847358518, -1.8338737452161369, -1.780442942180978, -1.7175914871440598, -1.646649160166566, -1.5691129124827112, -1.4866152877485144, -1.4008895450196968, -1.3137322852475928, -1.2269644451903008, -1.1423915640030298, -1.061764247361075, -0.9867397512770524, -0.9188455828435592, -0.8594459685503489, -0.8097119737092447, -0.7705959704917063, -0.7428110492277312, -0.7268158504282439, -0.7228051663239977, -0.7307065236919775, -0.750182817698206, -0.7806409228791399, -0.8212460657045988, -0.8709416068568883, -0.9284737537330094, -0.9924206078247463, -1.0612248503586532, -1.1332292853287629, -1.206714393853864, -1.279937009193476, -1.351169198810526, -1.4187364390900252, -1.4810541896825444, -1.5366620173668242, -1.5842544827160312, -1.6227080851051736, -1.651103660649436, -1.6687437410424844, -1.6751645061493852, -1.6701420965024634, -1.6536931902506429, -1.626069889205439, -1.5877490969566168, -1.5394167051958554, -1.4819470291206842, -1.4163780460424997, -1.3438830903315144, -1.2657397401972201, -1.1832966955420265, -1.0979394897217667, -1.0110559004866968, -0.9240019261749993, -0.8380691724414282, -0.7544544530176744, -0.6742323463299328, -0.5983313698485918, -0.5275143378724704, -0.4623633585131225, -0.4032698047406636, -0.3504294655457909, -0.3038429498203913, -0.26332128082789297, -0.22849648651736407, -0.19883686376635612, -0.17366647610845196, -0.15218833758301198, -0.13351064271111912, -0.11667532656556644, -0.10068818135620557, -0.08454971832054758, -0.06728594691622032, -0.047978247754829444, -0.025791541259195017, -2.590391758059263e-16], [0.0, 0.03199923717468105, 0.06885052224549709, 0.1107452452203791, 0.15769432139381334, 0.20952596932520093, 0.26588863695674225, 0.3262590113481597, 0.3899549144509713, 0.45615275918639603, 0.5239091200859467, 0.5921858639568685, 0.6598781912204117, 0.7258448601646188, 0.7889398063693559, 0.8480443295529944, 0.9020990011100718, 0.9501344481827015, 0.9913001942197125, 1.024890781069562, 1.0503684626413072, 1.067381843466373, 1.0757799350544093, 1.075621216299571, 1.067177408548753, 1.0509318081996226, 1.0275721565583789, 0.9979781647377858, 0.9632039471606292, 0.9244557473468862, 0.883065460833091, 0.8404605692435871, 0.7981311939416982, 0.7575950549315641, 0.720361178777297, 0.6878932367453492, 0.6615734101585381, 0.6426676736109717, 0.632293358315062, 0.6313898080638605, 0.6406928702548571, 0.6607138757994425, 0.6917236566628339, 0.7337420307809167, 0.786533054070518, 0.84960620135332, 0.9222234956162236, 1.003412461614809, 1.0919846389051824, 1.1865592544210288, 1.2855915290142819, 1.3874049790436853, 1.4902269759206759, 1.5922267459324173, 1.6915549316553131, 1.7863837963678997, 1.8749471350729472, 1.9555789605069793, 2.026750059760485, 2.087101566212338, 2.135474761220431, 2.17093640872391, 2.192799031451969, 2.200635657238659, 2.1942886951018754, 2.1738727400687057, 2.1397712498303005, 2.0926271816826802, 2.033327821320757, 1.9629841724235317, 1.8829054042636009, 1.7945689706827253, 1.6995871148873067, 1.5996705581926336, 1.4965902350721494, 1.3921379801156915, 1.288087093752918, 1.1861537123798533, 1.0879598849145482, 0.994999212428535, 0.9086058415140923, 0.8299275171173204, 0.7599032988209296, 0.6992464285348846, 0.6484327101311647, 0.6076946258991455, 0.5770212741555065, 0.5561640703856615, 0.5446480144185146, 0.541788191780232, 0.5467110518289541, 0.5583798916093252, 0.5756238753508393, 0.5971698375659227, 0.6216760547532199, 0.6477671282735327, 0.6740691000228018, 0.6992439235248531, 0.7220224359065623, 0.7412350202571056, 0.7558392119419665, 0.7649435848764129, 0.7678273524429167, 0.7639552301424337, 0.7529872303433984, 0.7347831905114683, 0.7094019717572657, 0.6770954010132467, 0.6382971642102094, 0.5936069861008305, 0.5437705516548826, 0.4896557312418417, 0.432225764440302, 0.37251013296078056, 0.31157390995932877, 0.2504864095502063, 0.19028997570414605, 0.13196974358445185, 0.07642517890835, 0.02444415284412918, -0.02331975749722221, -0.06636613801938065, -0.10436227167491587, -0.13715294671265588, -0.16476527182380607, -0.18740836132639577, -0.2054678875755022, -0.21949563202646818, -0.23019429740180317, -0.2383979678907356, -0.2450487190775208, -0.25116998142679, -0.2578373480434037, -0.26614758684363093, -0.27718666743441595, -0.2919976425910148, -0.311549232458811, -0.33670594622708516, -0.3682005413180554, -0.40660956492693745, -0.45233264837750675, -0.5055761330454173, -0.566341499809109, -0.6344189547588066, -0.709386395187684, -0.7906138449088839, -0.8772733100546967, -0.9683538691660836, -1.0626816780131325, -1.158944443548341, -1.255719805858953, -1.3515069648707903, -1.444760802455641, -1.5339276827062232, -1.6174820652180197, -1.693963039514835, -1.7620098840098322, -1.8203957702975038, -1.8680587727680367, -1.9041294036259055, -1.9279539729627069, -1.9391131706783864, -1.9374353794252026, -1.9230043526434948, -1.896161026132082, -1.857499372173568, -1.8078563485814196, -1.7482961376429154, -1.6800890083029005, -1.6046852656700406, -1.523684871813871, -1.4388034279039568, -1.3518352974031522, -1.2646147210463192, -1.1789758249506244, -1.0967124521476932, -1.0195387543674153, -0.9490514648510606, -0.886694734695255, -0.8337283556400533, -0.79120011274846, -0.7599229130032545, -0.7404572228319478, -0.7330992217068814, -0.7378749433137035, -0.7545405336368862, -0.7825886101324684, -0.821260561476532, -0.8695644867099804, -0.9262983393632394, -0.9900777195713774, -1.0593676482508727, -1.1325175647368428, -1.2077987151065102, -1.2834430445179053, -1.35768267454983, -1.428789036487697, -1.4951107439598574, -1.555109322937398, -1.6073919729713684, -1.6507406092383377, -1.6841365285967733, -1.7067801520835835, -1.718105418383845, -1.717788534757248, -1.7057509304349243, -1.682156399187948, -1.6474025591207806, -1.6021068952817208, -1.5470877810323462, -1.4833409940882714, -1.4120123498074213, -1.3343671650682605, -1.2517573387578826, -1.1655868877399935, -1.0772768089535487, -0.9882301482873993, -0.899798144910946, -0.8132482861878618, -0.7297350540685492, -0.6502740703680523, -0.5757202574882988, -0.5067505252637442, -0.44385137639442557, -0.38731169538035987, -0.3372208522123761, -0.29347211568070414, -0.2557712354690896, -0.22364992062082223, -0.19648381779673693, -0.17351447910535997, -0.1538747090148696, -0.1366165954582438, -0.12074146381798644, -0.1052309456719285, -0.08907832814857261, -0.07131934510739282, -0.051061588215703925, -0.027511753887495063, -2.7652536647843334e-16], [0.0, 0.034099753119031524, 0.07322247462777758, 0.11746871727652884, 0.16675471854037383, 0.22081304608500102, 0.27919843004662365, 0.3412986394965145, 0.4063501282907089, 0.4734580502156679, 0.5416201281178088, 0.6097537594841389, 0.6767256543329319, 0.7413832324969292, 0.8025869582097593, 0.8592427616206388, 0.9103336902206245, 0.954949948380125, 0.9923165199373294, 1.0218176261646634, 1.0430173480793854, 1.0556758360734373, 1.059760638895974, 1.0554528054273418, 1.043147543418652, 1.023449356180008, 0.9971617176674582, 0.9652714850549864, 0.9289283822074852, 0.8894200141177577, 0.8481429881435755, 0.806570819851755, 0.7662193868546324, 0.7286107610217917, 0.695236296135311, 0.6675198731998636, 0.6467822085219569, 0.6342071101877649, 0.6308105271039994, 0.6374131722740395, 0.6546174199380834, 0.6827890765743169, 0.7220445109400342, 0.7722435011096422, 0.832988019934667, 0.9036270378394036, 0.9832672768584475, 1.0707897058708036, 1.1648714276215313, 1.2640124767709908, 1.3665669281070087, 1.47077760815848, 1.5748136143769684, 1.6768097760126313, 1.7749071415451716, 1.867293550274011, 1.952243341120774, 2.0281552699915464, 2.0935877477664095, 2.1472905731597973, 2.18823241683149, 2.2156234132390438, 2.2289323323818313, 2.2278979319870245, 2.2125342287087153, 2.1831295711974845, 2.140239544940446, 2.0846738849956608, 2.017477714595715, 1.9399075616274604, 1.8534027279561929, 1.759552695473567, 1.6600613449767778, 1.5567088373099087, 1.4513120588605437, 1.3456845642574242, 1.2415969572485583, 1.1407386360997072, 1.0446817928455168, 0.9548484973030139, 0.8724816183975042, 0.798620239018935, 0.7340801087261996, 0.6794395539293062, 0.635031130796442, 0.6009391653787435, 0.5770031817945276, 0.5628270763056772, 0.5577937562671893, 0.5610848316420954, 0.571704826259004, 0.5885092691861707, 0.6102359360961213, 0.6355384384808849, 0.663021306769333, 0.691275683009563, 0.7189147304911403, 0.7446078816243473, 0.7671130811436628, 0.7853062382967236, 0.7982071776371041, 0.8050014714000078, 0.8050576448152051, 0.7979393663426949, 0.7834123646449903, 0.7614459498532322, 0.7322091549190702, 0.6960616500907976, 0.6535397163624413, 0.6053376887871226, 0.5522853946903055, 0.4953222122119033, 0.4354684587453545, 0.3737948846351985, 0.31139109331418563, 0.24933373378239004, 0.18865531436181393, 0.13031446795404958, 0.07516845908658068, 0.023948662889955487, -0.022760332653828437, -0.06453744529976306, -0.10113719173765584, -0.13249683026433637, -0.15873835724004162, -0.18016529614976648, -0.1972543542532978, -0.21064215616585152, -0.22110739285216705, -0.2295488451577575, -0.23695985007115422, -0.2443998726288808, -0.2529639243181155, -0.26375062799811483, -0.2778297682184029, -0.2962101833367162, -0.3198088515450377, -0.34942199685808395, -0.3856989939125086, -0.42911978320633737, -0.4799764228205455, -0.5383593008159727, -0.604148416908092, -0.6770100155582193, -0.7563987184290022, -0.8415651655808457, -0.9315690352974335, -1.025297175515585, -1.1214864489344647, -1.218750772285159, -1.3156117210236469, -1.4105319766358568, -1.5019508172098652, -1.5883207949033826, -1.668144707899824, -1.7400119603706092, -1.8026334122691923, -1.8548738513430423, -1.8957812718815716, -1.9246122172022282, -1.9408525339892782, -1.9442329941507193, -1.9347393612484458, -1.9126166108375986, -1.8783671540011362, -1.8327430575674961, -1.7767323994240383, -1.7115400394341322, -1.6385632222416928, -1.5593625543645018, -1.4756290113292938, -1.3891477283895448, -1.3017594081716966, -1.2153202384359394, -1.131661251520896, -1.052548072998298, -0.979642000175382, -0.9144633214888899, -0.8583577362324053, -0.8124666616847009, -0.7777021233067893, -0.754726815462265, -0.7439397977141804, -0.7454681581353706, -0.7591648334852239, -0.7846126299974399, -0.821134341442992, -0.8678087166563119, -0.9234918903512302, -0.9868437621659572, -1.0563586925884159, -1.1303997835395678, -1.2072359283674183, -1.2850807528235288, -1.3621325267642745, -1.4366141068222982, -1.506811973562905, -1.5711134525497392, -1.6280412566124067, -1.6762845552166747, -1.7147258644585366, -1.7424631556460637, -1.7588266990963204, -1.763390289713307, -1.755976638908966, -1.7366568600728363, -1.705744118569499, -1.6637816586084915, -1.6115255548175509, -1.549922662638589, -1.4800843556726342, -1.403256737051913, -1.3207880934195741, -1.2340944221936598, -1.1446239040098112, -1.0538212116268915, -0.9630925437347075, -0.8737722471701198, -0.7870918447225788, -0.7041522192191144, -0.625899619647037, -0.5531060538817384, -0.48635451771897187, -0.426029384283199, -0.3723121446771028, -0.3251825533150744, -0.28442509320819853, -0.2496405410143995, -0.2202622823354867, -0.19557690777394715, -0.17474851265738145, -0.15684603078394374, -0.140872857342479, -0.12579796018196363, -0.1105876432267352, -0.09423711191783202, -0.0758009984268644, -0.054422033809319204, -0.02935710446885032, -2.9503092252800394e-16], [0.0, 0.0362783257932035, 0.07770909949364906, 0.12429873795958077, 0.17586707251101266, 0.2320509244302092, 0.2923128601190183, 0.35595490460437335, 0.4221368620103826, 0.48989877039206553, 0.5581869090373576, 0.6258826817773517, 0.6918336224181492, 0.7548857101100601, 0.8139161448106473, 0.8678657169689622, 0.9157699116081577, 0.9567879150066546, 0.9902287415159734, 1.015573767511361, 1.0324950473474561, 1.0408688903181877, 1.0407842954190745, 1.0325459692547603, 1.0166717885235386, 0.9938847087473017, 0.9650992617921347, 0.9314029227110241, 0.8940327580693562, 0.8543478898710284, 0.8137984184068258, 0.7738915410270252, 0.7361556796072812, 0.7021034853815211, 0.6731946243982753, 0.6507992591846874, 0.6361631318932642, 0.6303751214389265, 0.6343380926444234, 0.6487437804767742, 0.6740523588614965, 0.7104772335559477, 0.7579754748096706, 0.8162441710450623, 0.884722842834021, 0.9626019104942908, 1.0488370622567984, 1.142169226753112, 1.2411497170592638, 1.3441699870688124, 1.4494953276725995, 1.5553017328945482, 1.6597150871831952, 1.7608517664499976, 1.856859708644033, 1.9459589955906522, 2.0264809968746267, 2.0969051585255585, 2.155892573411772, 2.2023155452718886, 2.235282452401829, 2.25415732789234, 2.2585736982895908, 2.2484423585942195, 2.2239529053164895, 2.1855689973709014, 2.134017463322631, 2.0702715192749435, 1.9955285009690866, 1.911182643074416, 1.8187935550386698, 1.7200511434288988, 1.6167378129953103, 1.5106888407548942, 1.4037518577389234, 1.2977463907317368, 1.194424410957835, 1.0954328084263507, 1.002278660253547, 0.9162980900345475, 0.8386294250148123, 0.7701912506750251, 0.7116658410550641, 0.663488310711247, 0.6258416939028153, 0.5986580119024565, 0.5816252437870348, 0.5741999732674533, 0.5756253475643036, 0.5849538573707957, 0.6010743326641936, 0.6227424503091786, 0.6486139684299348, 0.6772798413537707, 0.7073023289944084, 0.7372511967644969, 0.7657391068494286, 0.7914553287430828, 0.8131969455912004, 0.8298968018256367, 0.8406475250160477, 0.8447210585714188, 0.8415832592483596, 0.8309032413882419, 0.8125572851739018, 0.786627265552857, 0.753393698309436, 0.7133236365687181, 0.6670537813494305, 0.6153692903873086, 0.5591788773108315, 0.4994868856779135, 0.4373630970765361, 0.3739110876045448, 0.3102359812180665, 0.24741246084630517, 0.18645388853323705, 0.12828335445874686, 0.07370742233583959, 0.02339326672584209, -0.022150191898134615, -0.06258665368951179, -0.09776192489058447, -0.12770826730650744, -0.1526434911922829, -0.17296480840621223, -0.18923759978426163, -0.2021793839582038, -0.21263940089000583, -0.2215743390196651, -0.23002083717823085, -0.23906547869126335, -0.24981306317992413, -0.26335398970258905, -0.28073161181470624, -0.30291043013605584, -0.3307459709304017, -0.3649571604059442, -0.4061019448653859, -0.45455682792466595, -0.510500899720144, -0.5739048217157164, -0.6445251071650229, -0.7219039045531822, -0.8053743527464995, -0.8940714355802275, -0.9869481237440494, -1.0827964565916472, -1.180273089306434, -1.2779287149079404, -1.3742406688177249, -1.4676479387079866, -1.5565877363065346, -1.6395327424383668, -1.715028113046726, -1.7817273329148762, -1.8384260254062141, -1.8840928702956043, -1.9178968466701087, -1.939230102396892, -1.947725853765788, -1.94327083614988, -1.926011956046746, -1.8963569335132948, -1.8549688684047598, -1.802754810441101, -1.7408485583583309, -1.6705880536924973, -1.5934878666395156, -1.5112073916857462, -1.4255154763437474, -1.338252294741827, -1.2512893468111812, -1.1664885116705384, -1.0856611093230264, -1.010527927296558, -0.9426811482855014, -0.8835490716604852, -0.8343644569331676, -0.7961372324511881, -0.7696322098044628, -0.7553523261379295, -0.7535278056582219, -0.7641114912728533, -0.7867804509215667, -0.820943814309818, -0.8657566480526842, -0.9201395342738897, -0.9828033829515941, -1.052278885030239, -1.126949904512586, -1.205090016039082, -1.2849013220620065, -1.3645546323641384, -1.4422300595733144, -1.5161570781549587, -1.5846531112318045, -1.6461597490255824, -1.6992757637276736, -1.74278616664549, -1.775686652509558, -1.797202890395681, -1.806804247971383, -1.8042116725645878, -1.78939959549416, -1.7625918716709978, -1.7242519110915815, -1.6750672989510715, -1.6159293332666338, -1.5479080298938885, -1.4722232516932856, -1.39021270876785, -1.3032976479772236, -1.2129471006362404, -1.120641586243743, -1.0278371766165053, -0.9359308088387611, -0.8462276974537389, -0.7599116373397468, -0.6780189102704842, -0.6014164122779947, -0.5307845080688659, -0.46660499570964303, -0.4091544327129203, -0.3585029368588137, -0.3145184350499038, -0.2768761947440166, -0.2450733385216627, -0.21844791648172182, -0.19620199656869428, -0.17742813247826825, -0.161138484967157, -0.14629580728873118, -0.13184546069581282, -0.11674760259132415, -0.1000086885218307, -0.08071144980067202, -0.058042550565803104, -0.03131719043329235, -3.1444303346169504e-16], [0.0, 0.038520237442652226, 0.08227881290524247, 0.13118553546043812, 0.18496298472153164, 0.24315305222235864, 0.30512860853270213, 0.37010999629024993, 0.43718592257304606, 0.5053382080641587, 0.5734697482269143, 0.6404349558244112, 0.7050718867813005, 0.7662352043341414, 0.8228291108753147, 0.8738393735508482, 0.9183635886534288, 0.9556388707259017, 0.9850662140742994, 1.0062308555727202, 1.018918066225211, 1.0231239124922669, 1.019060654071839, 1.007156579517607, 0.9880502214194189, 0.9625790353529888, 0.9317627678578074, 0.8967818747819949, 0.8589514790149603, 0.8196914726900992, 0.7804934704399183, 0.7428854046408803, 0.7083946186322203, 0.6785103579450381, 0.6546465814665967, 0.6381060135696427, 0.6300463345020744, 0.6314493602692998, 0.6430939959162617, 0.6655336591235272, 0.6990787664580163, 0.7437847549892533, 0.799445980199656, 0.8655956903917804, 0.9415121315633834, 1.0262306885621473, 1.1185618218796676, 1.2171144182971798, 1.3203240412275847, 1.426485446273402, 1.5337886222111001, 1.640357529926866, 1.7442906439461843, 1.8437023548144986, 1.9367642668687464, 2.021745425503951, 2.0970505309297556, 2.1612552411009993, 2.2131377339071383, 2.251705786197784, 2.2762187326927745, 2.286203788720758, 2.2814663541171796, 2.26209405825122, 2.2284544545750773, 2.181186423689717, 2.1211854930376175, 2.0495834253408636, 1.9677225633042899, 1.8771255416123198, 1.7794610858720408, 1.6765067092670962, 1.5701091890920322, 1.4621437553234706, 1.3544729507686333, 1.2489061264839239, 1.1471605170175212, 1.050824798112489, 0.9613259658812099, 0.8799002927295524, 0.8075690135630773, 0.7451192785795021, 0.6930907791500148, 0.6517683141286956, 0.6211804188409473, 0.6011040315641124, 0.5910750261528508, 0.5904042981659973, 0.5981989588804797, 0.613388070178698, 0.634752246422677, 0.6609563596699567, 0.6905845141019769, 0.7221764060030792, 0.754264158201677, 0.78540871316849, 0.8142348869990028, 0.8394642267625004, 0.8599448751010832, 0.8746777269087952, 0.8828382613298188, 0.8837935456722442, 0.8771140332594298, 0.8625799115587766, 0.8401818967470409, 0.810116512670461, 0.7727760323731697, 0.7287333954807952, 0.6787225413545771, 0.6236147129096266, 0.5643913864516459, 0.5021145663303925, 0.4378952475671733, 0.3728608933015579, 0.3081227958543576, 0.2447441899023249, 0.1837099637478834, 0.12589877054558105, 0.07205827676068245, 0.0227842017430429, -0.021496297767544043, -0.06053645857969372, -0.09427664321858699, -0.12284579255346528, -0.14655755620107913, -0.1659011972464646, -0.1815275046497797, -0.19423007766239028, -0.2049224683281054, -0.2146117775977254, -0.22436939494625358, -0.23529964823956442, -0.24850718797714197, -0.2650639664543063, -0.2859766868816949, -0.31215558966278906, -0.34438541301413006, -0.3832993136276462, -0.4293564613708694, -0.4828239318592527, -0.5437634143421403, -0.6120231323583828, -0.6872352440227314, -0.768818850855585, -0.8559886022123067, -0.9477687401550213, -1.0430122906069779, -1.1404249743313568, -1.2385932890181865, -1.3360161046356704, -1.431139020977124, -1.522390661392501, -1.6082200219651073, -1.687133962311928, -1.7577339136472807, -1.8187508920933242, -1.869077940219341, -1.9077991766533622, -1.9342147110004708, -1.947860777375355, -1.948524552299901, -1.9362532488069886, -1.9113572152636062, -1.8744069113463337, -1.8262237812513098, -1.7678651919812238, -1.7006037487961507, -1.6259014370964318, -1.5453791667443089, -1.4607824079993066, -1.3739437050407528, -1.286742931078845, -1.2010662063701611, -1.1187644356173483, -1.041612433351584, -0.9712695946389269, -0.9092430340611944, -0.8568540592076919, -0.8152087672338729, -0.7851734562688469, -0.767355429926408, -0.7620896456461885, -0.7694315191583169, -0.7891560513902349, -0.8207632941662378, -0.8634900207350067, -0.9163273201517672, -0.9780436944118936, -1.0472131073840105, -1.1222473181722201, -1.201431731366865, -1.2829639151402081, -1.364993877266384, -1.4456651503462246, -1.5231557217070004, -1.5957178509694692, -1.661715848902715, -1.7196609441273891, -1.7682424381395612, -1.806354442157745, -1.8331175991248891, -1.8478953180970386, -1.8503041831508342, -1.8402183415088245, -1.8177678222974378, -1.7833308846051867, -1.7375206376799845, -1.6811663136597126, -1.615289700805211, -1.5410773596896294, -1.4598493434124151, -1.373025223268942, -1.282088281493445, -1.1885487712835476, -1.093907160426981, -0.9996182681631857, -0.9070571756685943, -0.8174877395585475, -0.7320344663938984, -0.6516584162145282, -0.5771376969002988, -0.5090529913885325, -0.44777842949359326, -0.3934779785717046, -0.3461073860204687, -0.3054215651509001, -0.2709871778725208, -0.24220003635017037, -0.21830682460928882, -0.19843053301023122, -0.181598906273254, -0.16677513160508534, -0.15288993928827874, -0.13887425517550012, -0.12369153367612475, -0.10636891126999941, -0.08602635400986952, -0.06190302700405978, -0.03338018809839708, -3.3463697705270413e-16], [0.0, 0.040809791225373926, 0.086898469621559, 0.1380776317595751, 0.19397266795436305, 0.2540322778032197, 0.3175430102936421, 0.3836484510738671, 0.4513725572510557, 0.5196465305207926, 0.5873385253303472, 0.6532854125424813, 0.7163257626538585, 0.7753331774924339, 0.8292490863973011, 0.8771141325403468, 0.9180973070821083, 0.9515220425019181, 0.9768885503977471, 0.9938917814949264, 1.0024344942486254, 1.0026350405755207, 0.9948296098647964, 0.9795688121887096, 0.9576086250639629, 0.9298958716139339, 0.8975485379460876, 0.8618313704672149, 0.8241273163586608, 0.7859054794241535, 0.7486863562342381, 0.714005191553064, 0.6833743455343552, 0.6582455967100633, 0.6399733135070209, 0.6297794126188727, 0.6287209853112375, 0.6376614134935455, 0.6572457175449792, 0.6878807793416155, 0.7297209690716899, 0.7826595760293135, 0.8463263047680686, 0.9200909521625307, 1.0030732316361464, 1.0941585617284904, 1.1920194909562032, 1.295142293143659, 1.4018581404585457, 1.5103781484199628, 1.6188314909493569, 1.7253057064968016, 1.827888260318347, 1.9247083945108494, 2.0139782872849197, 2.094032556458667, 2.1633651789896846, 2.2206629576626757, 2.2648347463966645, 2.2950357450930006, 2.3106862911086408, 2.3114847044931324, 2.297413884915858, 2.2687415063124057, 2.226013807095636, 2.1700431256175987, 2.1018894787418834, 2.0228366222918086, 1.9343631623568147, 1.8381094028090683, 1.7358407140872527, 1.6294082889369923, 1.5207082104187506, 1.4116397946818322, 1.3040641848860517, 1.199764162931405, 1.1004061126104114, 1.0075050122791909, 0.9223932585532911, 0.846194026789463, 0.7797997615992074, 0.7238562641457669, 0.6787527056347866, 0.6446177516114587, 0.6213218329935485, 0.6084854508575939, 0.6054932565115662, 0.6115135098954506, 0.62552239123603, 0.6463325262645535, 0.6726249869668027, 0.7029839501463465, 0.7359331369493355, 0.7699731193150005, 0.8036185649259069, 0.8354345009140527, 0.8640707080384988, 0.88829341042792, 0.9070134998745754, 0.9193106261659917, 0.9244525936783853, 0.9219096266648292, 0.9113631982538885, 0.892709257781982, 0.8660558341974393, 0.8317151362980053, 0.7901904099079433, 0.7421579442758806, 0.6884447416765126, 0.6300024723921962, 0.5678784292424844, 0.5031842693391296, 0.4370633839567494, 0.3706577690230788, 0.3050752779895704, 0.2413581255478207, 0.18045347518218582, 0.1231868868233044, 0.07023932435489715, 0.022128328387404562, -0.020806150045051493, -0.058410881588010936, -0.09072321508513075, -0.11796955517769915, -0.14055849835662465, -0.15906880462547104, -0.17423251725194314, -0.1869136704976355, -0.19808314148143985, -0.20879030448981517, -0.22013223148966177, -0.23322124913846712, -0.24915170850759993, -0.26896684784132735, -0.29362663031742275, -0.3239774178705811, -0.3607242991697756, -0.4044068258431176, -0.45537882758671155, -0.5137928759366034, -0.5795898507247779, -0.6524939354591723, -0.7320132312484086, -0.8174460368466177, -0.9078926984774812, -1.0022727909179527, -1.099347254454742, -1.1977449842177321, -1.29599325228143, -1.392551241752261, -1.4858458884044103, -1.5743091614379965, -1.6564158722725597, -1.7307210800927315, -1.7958961657103343, -1.8507626712070722, -1.894323051210038, -1.9257875514052354, -1.9445965193569703, -1.9504375597255994, -1.9432570679760206, -1.9232658106815073, -1.8909383632860162, -1.8470063642040817, -1.79244569378533, -1.728457834277793, -1.6564458088608909, -1.577985230589478, -1.4947911124177118, -1.4086811943801685, -1.3215366308967151, -1.235260947874317, -1.151738224135071, -1.0727914735692552, -1.0001422027243623, -0.935372093300206, -0.8798877108099719, -0.8348890706340482, -0.8013428025195419, -0.7799605464412291, -0.7711830892566555, -0.7751706157549635, -0.7917993028136427, -0.8206643349609086, -0.8610892673499225, -0.9121415116870183, -0.9726535756761795, -1.041249550568309, -1.116376217735864, -1.1963380368289165, -1.279335187627582, -1.363503767368598, -1.446957196775931, -1.527827862416953, -1.6043080209245697, -1.6746890120806601, -1.737397872180503, -1.7910305053612952, -1.8343806570158923, -1.8664640378688042, -1.8865370671686195, -1.8941098357792465, -1.8889530314593743, -1.871098715814429, -1.8408349916629794, -1.798694747211508, -1.7454388058563348, -1.682033944144008, -1.6096263621589622, -1.5295112974097915, -1.4430995625684926, -1.3518818570352715, -1.2573917506007157, -1.161168263335486, -1.0647189686910394, -0.9694845266520555, -0.8768055112210612, -0.7878923326728111, -0.7037989715512394, -0.6254011404411587, -0.5533793737055153, -0.4882074175787873, -0.43014615648125837, -0.3792431696111546, -0.3353378683515868, -0.2980720234008845, -0.2669053543489916, -0.24113572708626796, -0.21992338912420875, -0.2023185725030946, -0.1872917109538674, -0.173765454424991, -0.16064762154271636, -0.14686421007822426, -0.13139158752562083, -0.11328700836186584, -0.09171665081050386, -0.06598043276517594, -0.03553295222892004, -3.554772193663964e-16], [0.0, 0.04313045783401879, 0.09153368066347617, 0.14492234709900031, 0.2028256446849838, 0.26460173971895595, 0.32945512321257486, 0.3964583796804283, 0.4645778089383416, 0.5327022290653538, 0.5996742037364303, 0.664322871441398, 0.7254975093612375, 0.7821009420416631, 0.8331219050962113, 0.8776654970260996, 0.9149808973285359, 0.9444855952858555, 0.9657854595588901, 0.9786900818306129, 0.98322294570152, 0.9796261018907639, 0.9683591693074746, 0.9500926252625196, 0.9256954933928216, 0.8962176811217403, 0.8628673560771528, 0.8269838793647412, 0.790006929699042, 0.7534425531822071, 0.7188269564190839, 0.6876889235361054, 0.6615117788937178, 0.6416958357460566, 0.6295222662694097, 0.626119300292674, 0.632431609336258, 0.6491936603816982, 0.6769077318686605, 0.7158271749578473, 0.7659453787557851, 0.8269907619925859, 0.8984279688984782, 0.9794652972789969, 1.069068235712695, 1.1659788380995877, 1.2687405211321843, 1.3757277371605796, 1.4851798546662835, 1.5952384741233365, 1.7039873210021568, 1.8094937922055003, 1.9098511889584076, 2.0032206492037843, 2.087871796410315, 2.162221149323797, 2.224867387947571, 2.2746226437155492, 2.3105390746774384, 2.331930097308849, 2.3383857726076474, 2.329781982385309, 2.3062831787517997, 2.2683386421505936, 2.2166723372236663, 2.1522666075326895, 2.0763400960441905, 1.9903204147591222, 1.8958122106187383, 1.7945613828492284, 1.688416296604174, 1.5792869069639575, 1.4691027543960542, 1.3597708165547666, 1.2531342012599826, 1.1509326416826577, 1.0547657078032475, 0.9660595792887933, 0.886038135782096, 0.815699013433905, 0.7557951539966977, 0.7068222379691104, 0.6690122494644086, 0.6423332712194706, 0.6264954571360614, 0.620962980662364, 0.6249716138342596, 0.63755145741109, 0.6575542205364051, 0.6836843416944721, 0.714533153996818, 0.7486152291493332, 0.7844059874488755, 0.8203796369269292, 0.8550465038191937, 0.8869888388368699, 0.9148942286150136, 0.9375858080228777, 0.9540485550181093, 0.9634510532037528, 0.9651622255656297, 0.9587626730266483, 0.9440503901631618, 0.921040774190274, 0.8899609885225319, 0.8512388852096127, 0.8054868277519827, 0.7534808837887575, 0.6961359727264215, 0.6344776536658574, 0.569611321498037, 0.5026896417367664, 0.4348790960016334, 0.367326529055544, 0.30112658450152957, 0.23729088978861224, 0.1767198027720141, 0.12017746297528215, 0.06827080268767724, 0.0214330683503421, -0.02008771599117083, -0.05623504104191287, -0.0871447956252881, -0.11314071779116137, -0.13472453251193783, -0.15256103392301074, -0.1674585026281739, -0.18034497124103985, -0.19224096094937043, -0.20422940567672399, -0.21742355597810625, -0.23293371020386014, -0.2518336542655281, -0.2751277026478504, -0.30371922180656447, -0.3383814830200503, -0.3797316359397896, -0.42820851787386227, -0.48405491911743603, -0.547304813760433, -0.6177759411111187, -0.6950679882723837, -0.7785664828562817, -0.86745235986382, -0.9607170220256621, -1.0571825720307735, -1.155526761611821, -1.2543120797768479, -1.3520182936845826, -1.4470776635228682, -1.5379119796246583, -1.6229705178341434, -1.700767979189776, -1.7699214731444608, -1.8291856200450494, -1.8774848881143935, -1.9139423418170705, -1.9379040607917202, -1.948958589530406, -1.9469508952423151, -1.9319904420117608, -1.9044531302669734, -1.8649769982751385, -1.8144517332541403, -1.754002190040664, -1.6849662613815988, -1.6088675822217828, -1.5273836774339047, -1.4423102751331245, -1.3555226032466179, -1.2689345629913857, -1.1844567274529347, -1.1039541451794437, -1.0292049367936438, -0.9618606568422373, -0.9034093537978372, -0.8551421992275416, -0.8181244741258391, -0.7931715982763872, -0.7808307697269025, -0.7813686489112419, -0.7947653788498392, -0.8207150826794413, -0.8586328261556992, -0.9076678794715187, -0.9667229634667753, -1.0344790236979995, -1.1094249453290908, -1.1898915055612105, -1.2740887611575014, -1.360145988930477, -1.446153238764176, -1.5302035232300693, -1.6104346559568192, -1.6850697628820692, -1.7524555260155015, -1.8110972774673468, -1.859690140781619, -1.897145515077837, -1.9226123127006698, -1.9354924901479678, -1.9354505518027696, -1.9224168529849406, -1.8965846794430872, -1.8584012309246225, -1.808552783198296, -1.747944442266797, -1.6776750330939694, -1.5990077798516886, -1.5133375326858276, -1.4221553749473466, -1.3270115028484184, -1.2294773052215122, -1.1311075836742388, -1.0334038427106982, -0.9377795456776233, -0.8455281766065148, -0.757794871623354, -0.6755522885564778, -0.5995812721218284, -0.5304567474311072, -0.4685391397088384, -0.4139714764230399, -0.3666821830979015, -0.32639343952726313, -0.2926348225683553, -0.2647618286834464, -0.24197874723432736, -0.22336524726535079, -0.20790594882588578, -0.1945221770531849, -0.18210504505606076, -0.1695489813817361, -0.15578481023370233, -0.13981150778872486, -0.12072579551420226, -0.0977487903287938, -0.07024901025820886, -0.03776113089419611, -3.768186435540968e-16], [0.0, 0.045465032762772584, 0.09614914801097968, 0.15166632347326767, 0.21145146143059884, 0.27477576447319885, 0.34076679216347794, 0.4084326718198186, 0.47668982702033935, 0.5443934940058932, 0.6103702213242999, 0.6734514937233499, 0.7325075888737455, 0.7864807658398445, 0.8344168975986005, 0.8754946960386355, 0.9090517358823812, 0.9346065624438145, 0.9518762651252246, 0.9607890116631796, 0.9614911645421222, 0.9543487375510032, 0.9399430937507987, 0.9190609325602933, 0.8926787595798159, 0.8619421744893477, 0.8281404463074139, 0.7926769680962353, 0.7570362917335612, 0.7227485348788073, 0.6913520243956269, 0.6643550913875496, 0.6431979613155986, 0.6292156876137047, 0.6236030585956093, 0.6273823656375555, 0.6413748565830595, 0.6661766135619005, 0.7021394909749726, 0.7493576297671516, 0.8076599311956768, 0.8766087303405965, 0.9555047600907123, 1.043398343936645, 1.1391066043540217, 1.241236326592996, 1.348211978927675, 1.4583082632875606, 1.5696864578393872, 1.6804337182997764, 1.7886044298974253, 1.892262648842097, 1.989524642237757, 2.0786005293729053, 2.1578340454211906, 2.225739490386443, 2.281034990643652, 2.322671286118482, 2.3498553609495834, 2.3620683568575087, 2.3590773434611085, 2.340940665160936, 2.308006736418732, 2.260906312603427, 2.200538418271195, 2.128050265039363, 2.0448116334491173, 1.9523843239354528, 1.8524873980632819, 1.7469590297351534, 1.6377158647479026, 1.5267108439797608, 1.415890479268111, 1.307152580900341, 1.2023054213824456, 1.1030292821596521, 1.0108412692092532, 0.9270642014339335, 0.852800274599014, 0.7889100856920663, 0.7359974709569218, 0.6944004687178925, 0.6641885689688681, 0.6451662592261374, 0.6368827240792765, 0.6386474079495487, 0.6495510103989911, 0.6684913543460597, 0.6942034528727377, 0.725293002730674, 0.7602724545191727, 0.7975987526789003, 0.8357118042539342, 0.8730727245898393, 0.9082009209436939, 0.9397091109850022, 0.9663354313912488, 0.9869718706658763, 1.00068835789621, 1.0067519529315017, 1.0046407105065895, 0.9940519279504965, 0.974904629843238, 0.9473362897022635, 0.9116939348094072, 0.8685199219714467, 0.8185328058001353, 0.7626038436622842, 0.7017297897361935, 0.6370027219291476, 0.5695777175035794, 0.500639244354186, 0.43136716373165673, 0.36290324613795205, 0.29631908501699755, 0.23258625320591636, 0.17254948593510058, 0.11690359304985909, 0.06617470415229511, 0.02070633605722843, -0.019349354767221865, -0.05403490802160528, -0.08358539856542917, -0.10842083728285835, -0.12913333482376219, -0.14646936639103791, -0.16130760430954436, -0.1746329018011203, -0.18750711323335204, -0.20103752050884985, -0.21634370005662157, -0.23452370840962616, -0.2566204854690337, -0.28358937269542467, -0.31626761863706937, -0.3553466969905759, -0.4013481939382624, -0.45460393350390405, -0.515240904292214, -0.5831714308455067, -0.6580889009563271, -0.7394692199108671, -0.8265780173162031, -0.918483485527803, -1.0140745844249865, -1.1120842090122431, -1.2111167875422928, -1.3096796618209903, -1.4062175010128952, -1.4991489181812823, -1.5869043970808323, -1.6679645969848333, -1.740898086637632, -1.8043975652723476, -1.857313658934305, -1.8986854334299692, -1.927766839840283, -1.94404840291933, -1.947273574574032, -1.9374493012788891, -1.9148504926409475, -1.8800182250172115, -1.83375166550984, -1.7770938541093104, -1.7113116314756902, -1.6378701431561722, -1.5584024843973912, -1.4746751698270952, -1.388550216174367, -1.3019447112891356, -1.216788806885764, -1.1349831140597604, -1.058356498649954, -0.9886252674576732, -0.9273547062977366, -0.8759238775386059, -0.8354945094593014, -0.8069847142163883, -0.791048157780808, -0.7880591766164273, -0.7981041952476389, -0.8209796496160112, -0.8561964668819039, -0.9029909968352007, -0.9603421371199192, -1.026994247768232, -1.1014853136447809, -1.1821796896452956, -1.2673046558746943, -1.3549899211531522, -1.4433091452069813, -1.5303225044256825, -1.6141193041843025, -1.6928596429401372, -1.7648141595229332, -1.8284009445672316, -1.8822187686333571, -1.9250758714388851, -1.9560136664889978, -1.9743248405279876, -1.9795654645403107, -1.9715608791195587, -1.9504052682984223, -1.9164549886728572, -1.870315871110334, -1.8128248568202057, -1.7450264645534146, -1.6681447078998244, -1.5835511880980537, -1.4927301758937923, -1.3972415636655668, -1.2986826146794597, -1.1986494588827796, -1.0986992836224119, -1.0003141431821563, -0.9048672637632389, -0.81359265173499, -0.7275587244419656, -0.6476465768399067, -0.57453337644625, -0.5086812465925503, -0.4503318571035039, -0.39950679584835125, -0.3560136477758648, -0.31945756373658696, -0.28925796322666586, -0.264669886608052, -0.24480939657447265, -0.2286823285202122, -0.21521560751023633, -0.2032902877672917, -0.19177543049686152, -0.1795619184302288, -0.16559531107498607, -0.1489068731373822, -0.12864195916329346, -0.10408500882074906, -0.07468049758121606, -0.040049294538062365, -3.9850789546107064e-16], [0.0, 0.04779580263408041, 0.1007090130060258, 0.1582560617046988, 0.2197804116085305, 0.2844707627503359, 0.3513836969716701, 0.41947016529032377, 0.4876051193000303, 0.5546195041228591, 0.6193337665860784, 0.6805919900393997, 0.7372957476658136, 0.7884367697996231, 0.8331275475946532, 0.8706290447466803, 0.9003747596620137, 0.9219904707360106, 0.9353091050235147, 0.9403802928708309, 0.9374743049862122, 0.9270802106063758, 0.9098982423101065, 0.8868265009516246, 0.8589422794181245, 0.8274784227998175, 0.7937952715900776, 0.7593488504403381, 0.725656064832208, 0.6942577492458323, 0.666680470905694, 0.6443980313914068, 0.6287936232821516, 0.6211235901081721, 0.6224837053504914, 0.633778830788035, 0.655696737437656, 0.6886867755045046, 0.7329439654897856, 0.7883989536596193, 0.8547141346014518, 0.9312860950143754, 1.0172543798356533, 1.111516428054483, 1.2127483748871355, 1.3194312730986977, 1.4298821527084968, 1.5422892184136947, 1.6547503807829158, 1.7653142331794889, 1.8720225235742753, 1.972953130483202, 2.0662625362368354, 2.150226799094961, 2.2232800581983154, 2.284049661248483, 2.3313870827966996, 2.364393899231304, 2.3824422026127188, 2.385188966606276, 2.3725840207286413, 2.3448714404827693, 2.302584317032032, 2.2465330270628163, 2.177787277589765, 2.0976523479229003, 2.007640088257957, 1.9094353580381822, 1.8048586943682237, 1.6958260887457342, 1.5843068170913945, 1.472280311902509, 1.361693085290353, 1.2544167072341579, 1.152207814739931, 1.056671075468286, 0.9692259551049471, 0.8910780431453375, 0.8231955792012575, 0.7662916942009254, 0.7208127410998824, 0.6869329413954735, 0.6645554204929544, 0.6533195505719457, 0.6526143678348274, 0.6615976855983774, 0.6792203891673548, 0.7042552761035159, 0.7353296993428164, 0.7709611831791446, 0.8095951155184441, 0.8496435755868992, 0.8895243354678085, 0.927699076878871, 0.9627098913281222, 0.9932131814589514, 1.0180101527012775, 1.0360731754415053, 1.0465674064752515, 1.0488671817523965, 1.0425668272421482, 1.0274856777339803, 1.0036672409496281, 0.9713725927663985, 0.9310682349238681, 0.8834087856641929, 0.829215002870061, 0.7694477551986889, 0.705178656586305, 0.6375581608432284, 0.567781973871916, 0.4970566798339884, 0.42656549343691313, 0.3574350430539331, 0.2907040588647893, 0.22729478742218964, 0.1679878803810461, 0.11340141246911799, 0.06397457450036673, 0.01995646412377038, -0.018599736805056017, -0.05183705044205743, -0.0800894537854084, -0.10387123398401747, -0.12386123118714305, -0.14088238596573086, -0.1558771316688456, -0.1698792816399524, -0.1839831542168142, -0.19931075250030925, -0.21697786910215733, -0.2380600170933532, -0.2635590963562984, -0.29437168925553, -0.33125984133123293, -0.3748251225103904, -0.42548668360084735, -0.4834639235801702, -0.548764267878979, -0.6211764293595766, -0.7002693852133076, -0.7853971580085038, -0.875709341248684, -0.9701671627612574, -1.0675647367295986, -1.1665550207997164, -1.2656798718348474, -1.3634034856738155, -1.4581484154307132, -1.5483332917836634, -1.632411319182725, -1.708908595270764, -1.7764612977990555, -1.8338508040880468, -1.880035852198511, -1.9141809194235033, -1.935680080914813, -1.9441757171276057, -1.9395715607454602, -1.9220397088713759, -1.8920213712435394, -1.8502212765116781, -1.797595812481505, -1.7353351289200158, -1.6648395792542547, -1.5876910166459752, -1.5056195870447973, -1.4204667737640977, -1.334145542105201, -1.2485985062335845, -1.1657550920371575, -1.0874886977653333, -1.0155748581267972, -0.9516513970746396, -0.8971815101886977, -0.8534206504201729, -0.8213880025988185, -0.8018432246445272, -0.7952690094697287, -0.8018598841088284, -0.8215175150005484, -0.8538526341632239, -0.8981935439888178, -0.9536010023554704, -1.0188891385140186, -1.0926519074168006, -1.17329445929575, -1.2590686855367437, -1.3481121040430384, -1.4384891696977198, -1.5282340400900694, -1.6153937946882644, -1.6980710978682851, -1.7744653128009613, -1.8429111137130771, -1.9019137074452295, -1.9501798599402254, -1.9866440272021153, -2.010489010789749, -2.0211606920694267, -2.018376543936612, -2.002127769967877, -1.9726750752609867, -1.9305382267759723, -1.8764797100405552, -1.8114829299854698, -1.7367255329932683, -1.6535485418348903, -1.5634220922587123, -1.4679086372521517, -1.3686245405764554, -1.267201013781614, -1.1652453598122334, -1.0643034713774806, -0.9658244939301859, -0.8711285024130152, -0.7813779594666943, -0.697553622652286, -0.6204354519719611, -0.5505889395318153, -0.48835714384770096, -0.43385856556307756, -0.3869908528899505, -0.3474401776236245, -0.31469597981094, -0.28807064463613236, -0.2667235521820611, -0.24968883248362056, -0.235906067398582, -0.22425310952338118, -0.21358013842700263, -0.20274404707658025, -0.1906422471272802, -0.1762450008063969, -0.15862542891321946, -0.13698640788674593, -0.11068365232453294, -0.079244380627897, -0.04238107801364402, -4.203848327372583e-16], [0.0, 0.0501047188903241, 0.10517721486040862, 0.16463846648027397, 0.22774425924349906, 0.2936061144955236, 0.3612163725519603, 0.42947676654470135, 0.4972297310087285, 0.5632916159872811, 0.626486925364666, 0.6856826685798882, 0.7398219086098019, 0.7879556063313066, 0.8292719016808032, 0.8631220344468296, 0.8890421905222055, 0.9067706609494309, 0.9162598185933117, 0.9176825478379864, 0.9114329030689672, 0.8981209183501837, 0.8785616399630132, 0.8537586015882822, 0.8248821051540121, 0.7932428051264895, 0.7602612168802458, 0.7274338776241721, 0.6962969784352137, 0.6683883559444037, 0.6452087803149343, 0.6281835010727814, 0.6186250133960803, 0.6176979845315597, 0.6263872335729831, 0.6454695889810066, 0.6754903585787533, 0.7167450384752052, 0.7692667630686827, 0.8328198609875682, 0.9068997348858734, 0.9907391300239478, 1.0833207012835846, 1.1833956345103789, 1.2895079296329537, 1.4000238135434444, 1.513165623686852, 1.6270493918489612, 1.7397252645257897, 1.849219823827372, 1.9535793229352607, 2.0509128239666468, 2.139434224386148, 2.217502180937147, 2.2836569869237686, 2.336653528457582, 2.3754895363218935, 2.3994284602102023, 2.408016418604335, 2.4010928174079877, 2.3787943802505174, 2.341552489486102, 2.2900838955410783, 2.2253750095510556, 2.1486601463553625, 2.0613942281814333, 1.9652205902755921, 1.8619346451412324, 1.7534442591339208, 1.6417277715879457, 1.5287906405701774, 1.4166217294867083, 1.3071502544013693, 1.2022043929590067, 1.10347251273951, 1.0124679107902246, 0.9304978686464983, 0.8586377205266061, 0.7977105092194484, 0.7482726675149802, 0.7106060162286469, 0.6847162165558437, 0.6703376584284854, 0.666944611561369, 0.6737683157663227, 0.689819545544337, 0.7139160543898938, 0.744714189804516, 0.7807438734852502, 0.8204460648472887, 0.8622117717730385, 0.9044216415177593, 0.9454851577314004, 0.9838784866675795, 1.0181800563385046, 1.0471030155491825, 1.0695238037610038, 1.0845061654353518, 1.0913200612739689, 1.0894550605936097, 1.078627940617727, 1.058784366173743, 1.0300946734401637, 0.9929439302302175, 0.9479165891049789, 0.8957761847895778, 0.8374406505545379, 0.7739539363599973, 0.7064547019658853, 0.6361429286567543, 0.5642453419910048, 0.4919805638821074, 0.4205249147510061, 0.35097976544135084, 0.28434129463913316, 0.22147344183738488, 0.16308476013228834, 0.1097097695290597, 0.061695292622023536, 0.01919212352128265, -0.017847758938671205, -0.04966836780116307, -0.0767013552264483, -0.09955235580680756, -0.1189823902178811, -0.1358848229702713, -0.15125848492050548, -0.16617767251258023, -0.1817598188676602, -0.1991316946937942, -0.21939503793331283, -0.24359252903710846, -0.27267502326420123, -0.3074709225540251, -0.3486585179979046, -0.39674206100684806, -0.4520322287364897, -0.5146315394839812, -0.5844251493513615, -0.6610773255813254, -0.7440337480135527, -0.8325296416904416, -0.925603594486244, -1.022116767494833, -1.1207770664724401, -1.2201677134154907, -1.3187795416358183, -1.4150462384197788, -1.5073816790652126, -1.5942184368522225, -1.67404651687212, -1.7454513486054093, -1.8071500831099583, -1.8580252754647908, -1.8971550909297037, -1.9238392527694896, -1.937620048955373, -1.9382978316020454, -1.9259405741969746, -1.900887194232782, -1.863744499279077, -1.815377769140398, -1.756895141743934, -1.6896261219690945, -1.615094677032686, -1.5349875157096569, -1.4511182682891166, -1.3653883867686099, -1.2797456678189474, -1.196141362428408, -1.1164868743088787, -1.0426110631348262, -0.9762191581007491, -0.9188542523365111, -0.8718622902257283, -0.8363613790197835, -0.8132161552649712, -0.803017817895362, -0.806070306259642, -0.8223829560849135, -0.8516698129597936, -0.8933556250705968, -0.9465883784846209, -1.0102580830956045, -1.0830213692009225, -1.16333131716836, -1.2494718191115217, -1.3395956649243645, -1.431765458006088, -1.5239964006390698, -1.6142999468323993, -1.7007273025121081, -1.7814117596310535, -1.8546088818882203, -1.9187336144929272, -1.9723934674082777, -2.0144170188420083, -2.043877101006254, -2.0601081604892775, -2.0627174277550204, -2.051589680807401, -2.026885543223581, -1.9890334127638511, -1.9387152697820562, -1.8768467609467652, -1.8045520897700384, -1.7231343678192632, -1.634042186291682, -1.538833254310231, -1.439136015780042, -1.336610199382551, -1.232907275299867, -1.1296317871659864, -1.028304498742345, -0.9303282427126898, -0.8369572851582456, -0.7492709256161458, -0.6681519415377021, -0.5942703602718066, -0.5280729045834683, -0.46977831263541947, -0.41937858396112493, -0.37664605298882503, -0.3411460448929843, -0.3122547286197105, -0.28918165234486937, -0.270996330601586, -0.2566581527354587, -0.24504880167235135, -0.23500631219823645, -0.2253598605095212, -0.21496436258907056, -0.20273396830679688, -0.1876735707511889, -0.16890750530274268, -0.14570468893276062, -0.11749954519667319, -0.0839081719584972, -0.04473933418560194, -4.4228406291887707e-16], [0.0, 0.05237357706344086, 0.10951785553221177, 0.17076139360012874, 0.23527695579734423, 0.3021050332875734, 0.3701811901334405, 0.4383665102864555, 0.5054803376156735, 0.5703344394772893, 0.6317676847348651, 0.6886803107965594, 0.7400668615868166, 0.7850469092644643, 0.8228927261931951, 0.8530531488454821, 0.8751729701165796, 0.8891073085849289, 0.8949305297852059, 0.892939432398685, 0.8836505579617137, 0.8677916325928331, 0.8462872995764058, 0.8202394486313943, 0.7909025876306296, 0.759654831880025, 0.7279652015381123, 0.6973580164132936, 0.6693752566924062, 0.6455378160800724, 0.6273066088435861, 0.6160445034101402, 0.6129800420920342, 0.6191738694631687, 0.6354887317159328, 0.662563827408058, 0.7007941883234682, 0.7503156501741136, 0.8109958394505805, 0.8824314581411434, 0.9639519958189541, 1.0546298424787022, 1.1532966193252883, 1.2585653923251419, 1.3688582884874307, 1.482438901130268, 1.5974487511212987, 1.7119469692277343, 1.8239522828096073, 1.9314863301964893, 2.0326172897185484, 2.12550279845832, 2.208431148690494, 2.2798597874152167, 2.3384502054951, 2.383098386224647, 2.412960086694177, 2.4274703465620076, 2.4263567548858305, 2.4096461531895113, 2.377664608374317, 2.3310306486477246, 2.270641915459764, 2.1976555406203957, 2.1134627065243046, 2.0196579851158565, 1.9180041745419372, 1.8103934583717327, 1.6988057982447948, 1.58526553476556, 1.471797211858271, 1.3603816556728134, 1.2529133301328519, 1.151159957595541, 1.0567253357030133, 0.971016201787398, 0.8952138961261947, 0.8302514574134853, 0.7767966509288543, 0.7352412853274943, 0.7056970213005873, 0.687997718316907, 0.6817082081081356, 0.6861392293600977, 0.7003681109895417, 0.723264655007727, 0.7535215476138838, 0.7896885217869892, 0.8302094087916599, 0.8734611517340055, 0.9177938131100777, 0.9615705911220658, 1.0032068667395022, 1.041207334792793, 1.074200326947552, 1.10096851078794, 1.120475245465611, 1.1318859879897107, 1.1345842723571624, 1.128181923112787, 1.1125233120726346, 1.0876836181441862, 1.0539612016427824, 1.0118643524456465, 0.9620928120498868, 0.9055145996031582, 0.8431387880248461, 0.7760849755560494, 0.7055502780196704, 0.6327747257756147, 0.5590059853945739, 0.48546433859164745, 0.41330883969415155, 0.343605538200183, 0.2772985957379465, 0.21518504844784128, 0.15789386849482073, 0.10586986456859547, 0.0593628337495234, 0.018422239254438796, -0.01710245616499803, -0.047555819341486893, -0.07346500388622129, -0.09552314410590032, -0.11456802945164879, -0.1315566271076718, -0.1475361296169494, -0.16361229643941497, -0.18091593069735507, -0.200568383229492, -0.22364700413592264, -0.2511514665108306, -0.2839718678810727, -0.3228594724451908, -0.36840089257339687, -0.42099642277921945, -0.4808431356226523, -0.5479232293361693, -0.6219979843658522, -0.7026075438067285, -0.7890765844478503, -0.8805257945503713, -0.9758889253477308, -1.0739350393385938, -1.1732954433751084, -1.2724946717510555, -1.3699847770877822, -1.464182097542037, -1.5535056000151939, -1.6364158524179064, -1.7114536548785133, -1.777277360736281, -1.8326979432905517, -1.8767109130424013, -1.908524261434683, -1.9275816991765948, -1.9335805679163103, -1.926483930619522, -1.9065264854424506, -1.874214096748977, -1.8303168915667383, -1.7758560264088485, -1.712084384151605, -1.6404616097380131, -1.5626240331884875, -1.4803501552841114, -1.395522482194123, -1.3100865874865941, -1.226008351083476, -1.145230373007621, -1.0696285839876232, -1.0009700744931358, -0.9408731385332424, -0.8907704791335669, -0.8518764499804454, -0.8251591140128473, -0.8113177870100551, -0.8107666051882927, -0.8236245136070368, -0.8497119202455838, -0.8885541026320509, -0.9393912937297009, -1.0011952153036714, -1.0726916740581542, -1.1523886921681796, -1.2386095129223744, -1.3295297072215129, -1.423217510430402, -1.5176764438847352, -1.610889223022719, -1.7008619258929982, -1.7856673923460895, -1.863486845597511, -1.9326487735009232, -1.991664175639145, -2.0392573725133145, -2.074391682448074, -2.0962893976276833, -2.104445629828811, -2.0986357454919813, -2.0789162651080586, -2.0456192596744587, -1.9993404333296687, -1.9409212323786889, -1.8714254630864955, -1.7921110303797805, -1.7043975238097422, -1.6098304730310649, -1.510043170342875, -1.4067170107287186, -1.3015413290940054, -1.1961737193877462, -1.0922018009695709, -0.991107354504258, -0.8942336839823415, -0.8027569748836648, -0.7176623132421833, -0.6397249091148574, -0.5694969337768256, -0.5073002362458664, -0.45322505509712896, -0.4071346897206237, -0.3686759450006859, -0.33729501861134453, -0.3122583643353281, -0.2926779414055756, -0.2775401518993473, -0.2657376783566458, -0.25610336425887253, -0.24744523248956107, -0.23858171255091254, -0.22837614668898568, -0.2157696681518824, -0.19981159093891118, -0.1796865183861106, -0.15473746601788513, -0.12448440001574929, -0.08863771370639403, -0.04710629756707001, -4.640365548799258e-16], [0.0, 0.05458419976227162, 0.11369556713851763, 0.17657419362191393, 0.2423153424127919, 0.3098954005948259, 0.37820128874637166, 0.4460625462318613, 0.5122852389843069, 0.5756867869699309, 0.635130781999988, 0.6895608638223737, 0.7380327435872598, 0.7797435083358512, 0.8140574070190808, 0.8405274060607718, 0.8589119084631093, 0.8691861522691879, 0.8715479388041567, 0.8664174851431646, 0.854431345089077, 0.8364304948217747, 0.8134428294818555, 0.7866604614901146, 0.7574123467277473, 0.7271328873816312, 0.6973272671744292, 0.6695343631184022, 0.6452881455787204, 0.6260785235444368, 0.6133126133792871, 0.6082774063452431, 0.612104782850037, 0.6257397702627479, 0.6499128674588003, 0.6851171647510482, 0.7315908748119139, 0.7893057613332811, 0.8579618106446891, 0.9369883407759418, 1.0255515862029325, 1.1225686385949194, 1.2267274681770626, 1.3365126006762993, 1.4502358849323753, 1.5660716595962885, 1.6820955170532261, 1.7963257715461043, 1.9067666687227873, 2.011452327245715, 2.1084903808802884, 2.196104292214486, 2.2726733368406102, 2.3367693088219617, 2.387189073346307, 2.422982188839736, 2.443472936160518, 2.448276224026745, 2.4373069843691773, 2.4107828253354757, 2.369219869463639, 2.313421866207073, 2.2444628276007967, 2.1636635895260974, 2.0725628450230724, 1.9728833269168695, 1.8664939314871087, 1.7553686702446412, 1.6415434107785478, 1.5270714183176388, 1.413978735902842, 1.3042204422766546, 1.1996388027640974, 1.1019242801604654, 1.012580301166433, 0.9328925810008507, 0.8639036967782451, 0.8063934718315882, 0.7608655915578222, 0.7275407200502813, 0.7063562294777737, 0.6969724947348133, 0.6987855482275569, 0.7109457376305162, 0.732381886759909, 0.7618303298329615, 0.7978680754685282, 0.8389492615830337, 0.8834439881296715, 0.9296785631771937, 0.9759761703215861, 1.0206969624676498, 1.0622766085992326, 1.0992623656586613, 1.1303458158703934, 1.1543914990019026, 1.170460776872459, 1.1778303911556696, 1.1760053120424423, 1.1647256211956643, 1.143967323968487, 1.1139371392747646, 1.0750614669535064, 1.0279698781776725, 0.9734736107905737, 0.9125396750216935, 0.8462612827748, 0.7758254029332419, 0.7024783136968391, 0.6274900691797958, 0.5521188202510767, 0.47757592836913926, 0.4049927860357675, 0.3353902091531237, 0.26965119628001866, 0.2084977593639849, 0.15247242229564048, 0.10192486035680617, 0.057004018456582, 0.017655902409355793, -0.01637291094382652, -0.04552614846408879, -0.07042335073012328, -0.09184040804262279, -0.11068564334891082, -0.12797207990240897, -0.14478663203784528, -0.16225703913076833, -0.1815174235322002, -0.20367339146668118, -0.22976761056154923, -0.26074678843572696, -0.2974309438182789, -0.34048580578868176, -0.3903990993078615, -0.44746137816138987, -0.5117519521792682, -0.5831303269824413, -0.6612334347513438, -0.7454787871181731, -0.835073529951727, -0.9290292283364506, -1.0261820622608773, -1.1252179731551917, -1.2247021720054259, -1.3231123046071278, -1.4188744715402095, -1.5104012221602778, -1.5961305853364565, -1.6745651663087, -1.7443103298014333, -1.8041105047283326, -1.8528826851600368, -1.889746264806944, -1.9140484266163846, -1.9253844131771318, -1.9236121249489162, -1.9088606289416734, -1.8815323070494583, -1.8422985272085193, -1.792088878118886, -1.7320741655674994, -1.663643521540229, -1.5883761225268782, -1.5080081471121816, -1.4243957217892518, -1.3394747049715743, -1.2552182398914837, -1.1735930654278266, -1.0965156084219485, -1.025808890821578, -0.9631612697448979, -0.9100879886064265, -0.8678964537216525, -0.8376560648246729, -0.8201733217542914, -0.8159728057498142, -0.8252844953425236, -0.8480377270882856, -0.8838619539956059, -0.9320942932854123, -0.9917936939931695, -1.0617613978089804, -1.1405672172676267, -1.2265810175778167, -1.3180086653668794, -1.4129316023993657, -1.509349117455608, -1.605222327078739, -1.6985188373183957, -1.7872570448303813, -1.8695490470420684, -1.943641167254176, -2.00795116060486, -2.0611012492719185, -2.1019462380846647, -2.1295960823154387, -2.1434324148440007, -2.1431186867992986, -2.1286037305686616, -2.1001187129225274, -2.058167605038532, -2.0035114515290626, -1.9371468683874173, -1.8602793364670085, -1.7742919793743606, -1.680710619530967, -1.581165991117147, -1.4773540516258514, -1.3709953733448652, -1.263794611353032, -1.1574010352646014, -1.0533710782998664, -0.9531338002158722, -0.8579600816906315, -0.7689362689513363, -0.6869428712923455, -0.6126387835883812, -0.5464513642695467, -0.4885725500538763, -0.4389610357750572, -0.3973503947298988, -0.3632628659242458, -0.3360283931348394, -0.3148083703491708, -0.2986234321314258, -0.2863845286615542, -0.27692644604131017, -0.26904287489455786, -0.2615220957037066, -0.25318233853593486, -0.24290588803961147, -0.2296710414479648, -0.21258108683512664, -0.19088954948341436, -0.16402105386503213, -0.1315872648651055, -0.09339750151250895, -0.04946375633905382, -4.854713071472521e-16], [0.0, 0.056718621464030616, 0.11767587801724162, 0.18202824608241866, 0.24879982996478, 0.31691056076119356, 0.385207446604952, 0.4524980418730439, 0.5175852433968797, 0.5793024849566577, 0.6365483883588122, 0.6883199405517371, 0.7337433012760032, 0.7721014038187226, 0.80285759111398, 0.8256746287235806, 0.8404285526699254, 0.8472169407663173, 0.8463613377280051, 0.8384037133978682, 0.8240969861399478, 0.8043897959996235, 0.7804058607561192, 0.7534183887497662, 0.7248201517890193, 0.6960899362431727, 0.6687561876777451, 0.6443587415949436, 0.6244095880013045, 0.6103536491844764, 0.6035305573702943, 0.6051384015844846, 0.6162003714085984, 0.6375351603505239, 0.6697319047823658, 0.7131303279141702, 0.7678066346470246, 0.8335655653908991, 0.9099388684059481, 0.9961902945700034, 1.0913270595134272, 1.1941175597090832, 1.3031149752671198, 1.4166862466651142, 1.5330457790498329, 1.650293109396172, 1.7664536716509232, 1.8795217155300137, 1.9875043778786516, 2.0884658728899477, 2.1805707598626407, 2.26212526480329, 2.33161567466306, 2.3877428893536625, 2.429452305333311, 2.455958313365142, 2.466762819404189, 2.4616673384084704, 2.4407783627818085, 2.404505866453133, 2.353554968408879, 2.2889109418632825, 2.211817913226876, 2.1237517447737577, 2.0263877327719215, 1.9215638754770892, 1.8112405698215024, 1.6974576793231675, 1.5822899766751373, 1.4678020011831971, 1.356003382832651, 1.2488056710243878, 1.1479816672919945, 1.0551281985720269, 0.9716331824121827, 0.8986477299801505, 0.8370639094867861, 0.7874986547016402, 0.7502841540120364, 0.7254648986272016, 0.712801407905858, 0.7117804893250258, 0.7216317342348482, 0.7413498020764572, 0.7697219087933146, 0.8053598130663611, 0.8467354897025675, 0.8922195955132519, 0.940121771334794, 0.9887317859167437, 1.036360514088324, 1.081379753159793, 1.1222599175521337, 1.1576047112017775, 1.1861819588027718, 1.206949878330642, 1.2190781959568293, 1.2219636374030816, 1.2152394736463628, 1.1987789500484167, 1.1726925826570869, 1.1373194597378526, 1.0932128366893898, 1.041120454635916, 0.9819601436372413, 0.9167913873748804, 0.8467836244939473, 0.7731821400859591, 0.6972724571730836, 0.6203441711379275, 0.5436551790593525, 0.46839724069322375, 0.3956637688150906, 0.3264206848544368, 0.2614810928023516, 0.20148442240129807, 0.14688057423841205, 0.09791946758349507, 0.05464624999576297, 0.01690227947512772, -0.015668160979881728, -0.043605606293646536, -0.06761794438324414, -0.08855821418841779, -0.10739826152137921, -0.12519895639734618, -0.14307776629420046, -0.16217455024945399, -0.18361648703215686, -0.2084830755805917, -0.23777214681584538, -0.272367802773787, -0.3130111522973343, -0.36027464344399257, -0.4145407030018512, -0.4759852853044798, -0.5445668085917098, -0.6200208205793755, -0.7018605890989462, -0.7893836623069318, -0.881684289849072, -0.9776714453514515, -1.0760920455098297, -1.1755588255288814, -1.274582208161492, -1.371605397231876, -1.4650418390163593, -1.553314128456417, -1.6348933936233674, -1.7083381723086524, -1.7723317996480559, -1.8257173552612946, -1.8675292718471224, -1.8970207832702546, -1.9136864870952937, -1.9172794119286332, -1.9078221110215525, -1.8856114471704448, -1.8512168865106897, -1.8054722765958746, -1.7494612433032364, -1.684496497686809, -1.612093494044198, -1.5339390204551069, -1.4518554294164576, -1.3677613257965744, -1.283629619422861, -1.2014439179438126, -1.123154280437699, -1.0506333724240604, -0.9856340579214348, -0.9297494340544321, -0.8843762591334223, -0.8506826473976338, -0.8295808045862023, -0.8217054605631083, -0.8273985212199597, -0.8467003150597019, -0.8793476537859265, -0.9247787646771362, -0.9821449894395675, -1.050328983571791, -1.127968995947367, -1.2134886640814382, -1.3051316299006437, -1.4010001669570515, -1.4990969156788256, -1.5973687507183032, -1.6937517554904271, -1.7862162547642295, -1.8728108572414037, -1.951704486375636, -2.0212254285806797, -2.079896502170035, -2.126465546023181, -2.1599305417140546, -2.1795588138346735, -2.1848998972723948, -2.175791813710177, -2.1523606588452258, -2.1150135628575266, -2.0644252455634273, -2.001518540577199, -1.9274394059472062, -1.843527068651514, -1.7512800638816377, -1.6523190244740378, -1.5483471489045135, -1.4411093262115529, -1.3323509219054614, -1.2237772297971805, -1.1170145708056884, -1.0135739718494172, -0.9148182871640944, -0.8219335326472015, -0.73590509345544, -0.6574993388801239, -0.5872510396871178, -0.5254568351305294, -0.47217484345048494, -0.4272303546883131, -0.3902273919726833, -0.3605657808567239, -0.3374632294675179, -0.3199817985636169, -0.3070580331452896, -0.29753593867701233, -0.2902019174359276, -0.28382073563662225, -0.2771715708734426, -0.26908319254124596, -0.2584673551098624, -0.24434953469825, -0.2258962119969146, -0.20243799734589682, -0.1734880043096836, -0.1387550035747704, -0.09815102623154388, -0.05179323099789313, -5.064170558417859e-16], [0.0, 0.05875927316336373, 0.12142557353803689, 0.1870774785381216, 0.254675049497862, 0.3230900679273443, 0.39113888259310703, 0.45761699090217284, 0.5213344310726827, 0.58115103823136, 0.6360106185024874, 0.6849731203491096, 0.7272439312875651, 0.7621994994176114, 0.7894085712220044, 0.8086484474984477, 0.8199157853346135, 0.8234316125677558, 0.8196403687102368, 0.8092029391652383, 0.7929838038580677, 0.772032573279483, 0.7475603305441171, 0.7209113337248971, 0.6935307549910619, 0.6669292388389989, 0.6426451482543133, 0.6222054327476549, 0.607086094164241, 0.5986732438503404, 0.5982257376451282, 0.6068403433461134, 0.6254203394796297, 0.6546483657023299, 0.6949642458405182, 0.746548386838385, 0.8093112235936747, 0.8828890340625388, 0.9666462946793571, 1.0596845868517324, 1.1608579049762582, 1.2687940590314601, 1.3819217142311317, 1.4985024701943293, 1.6166672560849107, 1.734456209331821, 1.8498611165822914, 1.9608694286995536, 2.065508818589683, 2.1618912325406483, 2.2482553930807643, 2.3230067439897737, 2.3847538852776897, 2.4323406263343386, 2.4648728871248906, 2.481739797817665, 2.482628483669653, 2.4675321710587528, 2.436751408623786, 2.390888360714641, 2.330834294797283, 2.2577505461022707, 2.1730433977184234, 2.078333458746527, 1.9754202535294187, 1.866242848194942, 1.7528374340387198, 1.637292858374252, 1.5217051406723285, 1.4081320339697585, 1.2985486881323, 1.1948054427175419, 1.098588723632766, 1.0113859408574641, 0.9344551861081808, 0.868800411897759, 0.8151526398771042, 0.7739575999342171, 0.7453700458608024, 0.7292548323021559, 0.7251946751292632, 0.7325043572909985, 0.7502509885289539, 0.7772797838128621, 0.812244695469356, 0.8536431208769649, 0.8998538140117914, 0.9491770572909664, 0.9998761017731617, 1.0502188599527111, 1.0985188366334961, 1.143174309575678, 1.1827048220421723, 1.2157841227021107, 1.2412687826826683, 1.258221832487877, 1.2659308901579156, 1.2639203931751835, 1.2519576966813728, 1.2300529557870103, 1.1984528662446579, 1.1576284916101833, 1.1082575523977747, 1.0512016899782493, 0.9874793416717961, 0.9182349705859221, 0.8447054816085079, 0.7681847214321283, 0.6899870039465156, 0.611410621757319, 0.5337022995418104, 0.45802351562071764, 0.3854195653037427, 0.31679216463735344, 0.25287629808303796, 0.19422190082312965, 0.14118083871362905, 0.09389950963331868, 0.05231724265967052, 0.016170519877632003, -0.014997106453042272, -0.04181967732369919, -0.06508848845045884, -0.08572729798796515, -0.10476374533004691, -0.12329774545181263, -0.14246770327421723, -0.16341545093604498, -0.18725084614211362, -0.21501698100474406, -0.24765693769757444, -0.2859829900990366, -0.33064909032544415, -0.38212739713235383, -0.4406895016354575, -0.5063928872027681, -0.5790730276644203, -0.6583413845005486, -0.7435894130024824, -0.833998533345115, -0.9285558689376135, -1.0260754052090328, -1.1252240809059983, -1.2245521946059392, -1.3225273947701932, -1.4175714251958802, -1.508098721652376, -1.5925559017800188, -1.669461160405205, -1.7374425771151005, -1.7952743624534946, -1.8419101130449862, -1.8765122133160816, -1.8984766106629596, -1.9074522997736802, -1.9033549777111294, -1.8863744712363082, -1.8569756882803157, -1.8158930027689206, -1.764118142298771, -1.7028818075093959, -1.6336294064555907, -1.5579914330379807, -1.4777491519808206, -1.3947963706371738, -1.3110981771139978, -1.2286476023567925, -1.1494212189444253, -1.0753347200108063, -1.0081995271231539, -0.9496814559177756, -0.9012624232592209, -0.8642061106993849, -0.8395284077093517, -0.8279733467297096, -0.8299951132204172, -0.8457465707062635, -0.8750745867787963, -0.9175222848694488, -0.9723381822671886, -1.0384920113136449, -1.1146968619473199, -1.1994371336490903, -1.291001647014934, -1.387521143000291, -1.4870092943114919, -1.587406270975039, -1.686623842790357, -1.7825909665923632, -1.8732987968442933, -1.9568440742516313, -2.031469888413759, -2.095602875972555, -2.147886003648922, -2.1872061938026066, -2.212716176034301, -2.2238500887709045, -2.220332506280359, -2.202180725430443, -2.169700308840013, -2.123474042896021, -2.0643446264692202, -1.9933915552162615, -1.9119028034780599, -1.8213420276461734, -1.7233121185254852, -1.6195160131823363, -1.5117157370571006, -1.401690683327899, -1.2911961478239957, -1.1819231240065964, -1.0754603240855238, -0.9732593302562804, -0.8766036959401761, -0.7865827129486342, -0.704070439318197, -0.6297104472423599, -0.5639066044718771, -0.5068200494374229, -0.45837236400610737, -0.4182547921258667, -0.38594320152396133, -0.3607183428697326, -0.3416908299334103, -0.3278301485147709, -0.31799690413557197, -0.31097744109090897, -0.3055199103252931, -0.3003708320666896, -0.2943111919497654, -0.2861911266108706, -0.27496229595066535, -0.2597071033443097, -0.23966401036880539, -0.2142482969173949, -0.1830677382109211, -0.14593280411698356, -0.10286112993985912, -0.054076157792696054, -5.267040044605034e-16], [0.0, 0.06068916492045286, 0.12491304779147933, 0.19167886478932714, 0.2598904658946378, 0.32838037654703417, 0.3959439787430066, 0.4613749178980982, 0.5235007880272631, 0.5812181383146405, 0.6335258592096876, 0.6795560454462715, 0.7186014958708864, 0.7501390941357722, 0.773848418065111, 0.7896250462452187, 0.7975881650995995, 0.7980822250084397, 0.7916725462700718, 0.7791349310495955, 0.7614394920033941, 0.7397290581072236, 0.7152926595605222, 0.6895347229069173, 0.6639407214127127, 0.6400401213715601, 0.6193675398960221, 0.6034230819701272, 0.5936328526884886, 0.5913106439121913, 0.5976217728627843, 0.6135500039098716, 0.6398684150545569, 0.6771149790270229, 0.7255735177054213, 0.7852605604216263, 0.8559184947705073, 0.9370152462564016, 1.0277505642306235, 1.1270688300062999, 1.2336781427659018, 1.3460752838633194, 1.4625760142055662, 1.5813500262016218, 1.7004597546032223, 1.8179021523611762, 1.931652460845555, 2.0397089503698544, 2.140137578286899, 2.23111550875035, 2.31097246069635, 2.378228898201581, 2.431630149004514, 2.4701756309320406, 2.493142480000007, 2.5001030053042115, 2.4909355413114267, 2.465828424271206, 2.425276982408961, 2.3700735953691034, 2.3012910430215086, 2.2202595232192617, 2.1285378685196776, 2.027879629593718, 1.9201948147016208, 1.8075081772480626, 1.6919150245578916, 1.5755355786692895, 1.460468952736653, 1.3487478137907982, 1.2422947839680123, 1.1428815883721282, 1.0520918895748042, 0.9712886580807055, 0.9015868171274306, 0.8438317716922527, 0.7985842887011926, 0.7661120416932553, 0.7463879723568041, 0.7390954573683745, 0.7436401058399653, 0.759167854404547, 0.7845888774007195, 0.818606692394696, 0.8597517197287929, 0.9064184518462431, 0.9569053062833748, 1.0094561773887696, 1.0623026673993905, 1.113705968244657, 1.161997381507413, 1.2056165048643883, 1.2431461779654231, 1.273343367410386, 1.2951652770245956, 1.307790093308376, 1.3106319136170212, 1.3033495528459278, 1.2858490794295636, 1.2582800894297483, 1.2210258844405164, 1.1746878710606676, 1.120064642998706, 1.0581263379216745, 0.9899849766962944, 0.9168615898488317, 0.8400510125047764, 0.7608852828996266, 0.6806966094862019, 0.6007808770108406, 0.5223626426171475, 0.44656252960665965, 0.3743678600901228, 0.30660728012556243, 0.24393002431553668, 0.18679034395599337, 0.13543748682915707, 0.08991147107533926, 0.05004474396676618, 0.015469662690159586, -0.014368417675340521, -0.04019281006885833, -0.06287241324236464, -0.08339450351357566, -0.10283413064940918, -0.12232093742231534, -0.14300429074925522, -0.1660176579418685, -0.19244318329287702, -0.22327741742665566, -0.2593991245965827, -0.3015400420794676, -0.35025939225889985, -0.4059228537341198, -0.4686865851909484, -0.5384867676433124, -0.6150349902084181, -0.6978196553409712, -0.786113425173086, -0.8789865751705099, -0.9753259686419685, -1.0738592195838819, -1.1731834756053934, -1.2717981307052042, -1.368140672571006, -1.4606247835365334, -1.5476797505699373, -1.627790199348864, -1.6995351516903987, -1.7616254148247557, -1.812938345085211, -1.852549086768079, -1.8797574678279538, -1.8941098357792465, -1.8954152372173674, -1.8837554798329337, -1.8594887633616322, -1.8232467219744921, -1.775924881333287, -1.7186666949545122, -1.6528414826579754, -1.5800167448104525, -1.5019254660682773, -1.4204291478954978, -1.3374774171554238, -1.255065145838996, -1.1751880822935254, -1.0997980354903836, -1.030758669850361, -0.9698029584803234, -0.9184933075436242, -0.8781853046943078, -0.8499959614646474, -0.8347772151910726, -0.8330953330051902, -0.8452167215758066, -0.8711004950271787, -0.910397993447393, -0.9624592795257094, -1.026346475127292, -1.1008536370598208, -1.1845327158642365, -1.2757249969540758, -1.3725972933495674, -1.4731820467674066, -1.5754204016666058, -1.6772072472491049, -1.7764371770531382, -1.871050295743935, -1.959076808468487, -2.038679359532487, -2.1081921433869053, -2.166155890578209, -2.2113479324470395, -2.242806668458886, -2.2598498961571654, -2.2620866124969505, -2.2494220530920925, -2.222055898819929, -2.1804737432862127, -2.125432075846478, -2.057937189274077, -1.9792185649989922, -1.89069741862139, -1.7939512009881682, -1.690674942797817, -1.5826404012532531, -1.4716540140479508, -1.3595146878729985, -1.2479724452129066, -1.1386889246238325, -1.033200676749191, -0.9328861224150076, -0.838936942217667, -0.7523345515423138, -0.6738321838587661, -0.6039429617413349, -0.5429341829556452, -0.4908278919638721, -0.44740764924751825, -0.4122312558761309, -0.38464904262128796, -0.3638271953084576, -0.3487754644252639, -0.3383785003190182, -0.33142996824382787, -0.3266685321874894, -0.3228147544020589, -0.31860793987376174, -0.3128419619811551, -0.3043991370686798, -0.29228127075583793, -0.2756370760690785, -0.2537852609273414, -0.22623269763268097, -0.1926872168718894, -0.15306471001393473, -0.10749037259707325, -0.05629407505042415, -5.461655573554045e-16], [0.0, 0.062492064358746, 0.12810864235706015, 0.19579289683717777, 0.2644009479654487, 0.3327354677063274, 0.3995809153808323, 0.4637394709247685, 0.5240667024476263, 0.5795060093911754, 0.62912091190168, 0.6721243102454664, 0.7079039138958434, 0.736043136411774, 0.7563368670040372, 0.7688016598688181, 0.7736800246964058, 0.7714386526588858, 0.762760567849702, 0.7485313506682671, 0.7298197330651875, 0.7078530120098462, 0.6839878633017225, 0.659677259470683, 0.6364342998976247, 0.6157938457588285, 0.5992729147715774, 0.5883308293591818, 0.5843301257144072, 0.5884992198916579, 0.6018977906984871, 0.6253857786084941, 0.6595968166074266, 0.7049168048092496, 0.7614682183571447, 0.8291006005334031, 0.9073875435054608, 0.9956303013997279, 1.092868018299711, 1.197894391306312, 1.3092804299900787, 1.425402822339712, 1.5444772774216318, 1.6645960898924548, 1.783769064371984, 1.8999668511741583, 2.0111656811892935, 2.115392448436891, 2.2107690749892974, 2.2955551050030034, 2.3681875122511125, 2.4273167679622087, 2.471838301462576, 2.5009185930417637, 2.5140152640434326, 2.5108906703910843, 2.49161865917191, 2.456584309799628, 2.4064766477255586, 2.3422744856189652, 2.2652257103306184, 2.176820489810652, 2.078759018679075, 1.9729145508272299, 1.8612925791065158, 1.745987113122695, 1.6291350741935522, 1.5128698699990974, 1.3992752293139994, 1.2903403690452244, 1.1879175318257031, 1.0936828734903665, 1.0091015973477462, 0.9353981282962535, 0.8735319970804537, 0.8241799663606806, 0.7877247791859131, 0.7642507506232992, 0.7535462586256078, 0.7551130247410494, 0.7681819130324584, 0.7917348205327611, 0.82453208849519, 0.8651447340976214, 0.9119906902656584, 0.9633741495844632, 1.0175270390649314, 1.0726516074468213, 1.1269630867928178, 1.1787313957628252, 1.2263208829344396, 1.2682271640049092, 1.3031101852194387, 1.329822744900757, 1.3474338229697576, 1.3552462018583444, 1.3528080078576268, 1.3399179560578507, 1.316624240759374, 1.2832171725991404, 1.2402158196699857, 1.1883490587278784, 1.1285315804904446, 1.0618355166143723, 0.9894584621497142, 0.9126887534962019, 0.8328689260254992, 0.7513583160354969, 0.6694957876146017, 0.5885635559790396, 0.5097530451938864, 0.43413366080516513, 0.3626252782966168, 0.29597514849745693, 0.2347398036671901, 0.17927241597076016, 0.12971591679653174, 0.08600203450478022, 0.04785625355801216, 0.014808543500846807, -0.013790444155502641, -0.038748155617172, -0.061004466563010694, -0.08160225768311803, -0.10165502415078231, -0.12231238734491746, -0.14472443304451685, -0.17000583252839802, -0.19920071069881914, -0.23324920829017814, -0.27295664383106083, -0.31896611631964394, -0.3717353031573176, -0.4315181019198455, -0.49835164168028434, -0.5720490529126353, -0.6521982379306187, -0.7381667300490315, -0.8291125730665848, -0.9240009972065414, -1.0216265172409371, -1.1206399369721287, -1.219579615142519, -1.3169062344759275, -1.4110402208201642, -1.500400885697799, -1.5834463148968636, -1.6587129993900616, -1.7248542036010506, -1.780676089955013, -1.8251706672466332, -1.8575447025034886, -1.8772438299994876, -1.883971204617049, -1.8777001771118234, -1.8586806128196145, -1.827438629435737, -1.7847696899075167, -1.7317251492611132, -1.6695925153167932, -1.599869838746715, -1.5242347939417593, -1.4445091450503942, -1.3626194080214198, -1.2805546166110862, -1.2003221756618507, -1.1239028366160724, -1.0532058568648937, -0.990025405434683, -0.9359992525985922, -0.8925707308202615, -0.8609548801645188, -0.8421095947131586, -0.8367124699200884, -0.8451439170410211, -0.867476963014461, -0.9034739960352663, -0.9525905523886923, -1.0139860729043138, -1.0865413917128681, -1.1688825598768637, -1.2594104558152526, -1.356335496920787, -1.4577166457218134, -1.5615038023122298, -1.6655825950314094, -1.7678205254524513, -1.8661133929803417, -1.958430919503192, -2.0428605156775967, -2.117648177023449, -2.181235568893234, -2.2322924528088066, -2.269743720318927, -2.2927904316231764, -2.300924401507944, -2.2939360310798085, -2.271915246535747, -2.235245571791826, -2.1845915261523077, -2.120879697326121, -2.045273990109154, -1.959145688301782, -1.8640390885947404, -1.76163356730857, -1.653703021561886, -1.5420736837554823, -1.428581340856117, -1.3150289971228672, -1.2031460005463077, -1.094549609903821, -0.9907099121274157, -0.8929189103750519, -0.8022644940778463, -0.7196098760737758, -0.6455789419212509, -0.5805478061365846, -0.5246427131901692, -0.47774426155381794, -0.43949777089993003, -0.4093294596523545, -0.3864679562798779, -0.3699705365715653, -0.358753363880817, -0.3516249128106139, -0.34732168140046366, -0.3445452443982432, -0.3419996719124922, -0.3384283342895918, -0.33264913546923225, -0.3235872627409184, -0.3103046095463392, -0.2920251179632411, -0.2681553964495394, -0.23830009353283724, -0.20227164620756283, -0.16009416933437545, -0.11200140557426015, -0.05842881044232306, -5.646400386019638e-16], [0.0, 0.06415266919313417, 0.1309849684632714, 0.1993840253673602, 0.2681672885702888, 0.336117404088277, 0.40201821149324973, 0.4646908948345665, 0.5230293171776443, 0.5760335867313078, 0.6228409460767765, 0.6627531429440193, 0.695259529638653, 0.7200552463890117, 0.7370539688493584, 0.7463948386265339, 0.7484433445110038, 0.7437860773458334, 0.7332194392479694, 0.7177325442249881, 0.6984846981569639, 0.6767779878157326, 0.654025637475595, 0.6317169044480538, 0.6113793786632943, 0.594539623807166, 0.5826831466194481, 0.5772147054605583, 0.5794199684647685, 0.590429505453565, 0.6111860468507708, 0.642415868308413, 0.6846050633968723, 0.7379813508597073, 0.802501930398253, 0.8778477549703617, 0.9634244317395603, 1.0583698019266634, 1.1615680858849768, 1.271670317791855, 1.3871206384321175, 1.5061878685109902, 1.6270016524083404, 1.747592346577977, 1.865933730803134, 1.979987546658575, 2.0877488176765597, 2.18729088115534, 2.276809062951504, 2.35466195399006, 2.4194092999978567, 2.4698455928813425, 2.505028551398099, 2.5243017979319853, 2.5273111744006758, 2.5140142903067972, 2.4846830560533197, 2.439899120992655, 2.3805423042227765, 2.3077722727820866, 2.2230038825711036, 2.1278767481308747, 2.0242197446633603, 1.9140112660462787, 1.799336163145853, 1.682340365021883, 1.5651842397523912, 1.4499957802729309, 1.3388247031457328, 1.2335985245035124, 1.1360816281506803, 1.0478382671758801, 0.9702003442545465, 0.90424069947055, 0.8507525008243703, 0.8102351849071325, 0.7828872371287782, 0.7686059362703087, 0.7669940210137193, 0.7773730705742969, 0.7988032316581385, 0.8301087735880167, 0.8699088162372522, 0.9166524547077873, 0.9686574033963734, 1.0241512026399313, 1.0813139754023489, 1.1383216907568365, 1.193388885906913, 1.2448098192153738, 1.2909970725797966, 1.330516691288851, 1.3621190414125457, 1.3847646764723283, 1.3976446337720694, 1.4001947231014853, 1.3921035229713767, 1.3733139582836387, 1.344018494408728, 1.3046481420215155, 1.2558556207656726, 1.1984931740599822, 1.1335856585541952, 1.0622996466476513, 0.9859093762744466, 0.9057604564914284, 0.8232322884775701, 0.7397001881485689, 0.6564981981070176, 0.574883553113531, 0.49600371533303317, 0.4208668245491039, 0.35031631619215736, 0.28501034877092096, 0.2254065549792335, 0.1717524906200976, 0.124082006113508, 0.08221761052966522, 0.04577874174517669, 0.01419570242180189, -0.013271126043316744, -0.037507316910714524, -0.05951632804261776, -0.08038808478630406, -0.10126505993413339, -0.12330676098462857, -0.1476535776696854, -0.1753909610108514, -0.20751489854161506, -0.24489961892951576, -0.28826840382277685, -0.3381683067073737, -0.39494947983939965, -0.4587496933844905, -0.529484498681802, -0.6068433433741366, -0.6902917936322119, -0.7790798616891734, -0.87225627934894, -0.9686884040165826, -1.0670872970188452, -1.1660373782591276, -1.2640299400341344, -1.3594996992225057, -1.4508634836981327, -1.5365600878791374, -1.6150902953992181, -1.6850560549844704, -1.7451978091177245, -1.7944290137212213, -1.8318669500074467, -1.8568590153501303, -1.8690037864550035, -1.8681662726846893, -1.8544869170786087, -1.8283840539889706, -1.7905496916117638, -1.7419386511045807, -1.6837512574193592, -1.6174099363961414, -1.5445302241131045, -1.4668868342064243, -1.3863755533805742, -1.3049718415143867, -1.2246870979650608, -1.147523617728626, -1.0754292984444633, -1.0102531708540423, -0.9537028108904635, -0.9073046513780867, -0.8723681462863109, -0.8499546521457524, -0.8408517817116891, -0.8455538568832209, -0.864248944351577, -0.8968128019333067, -0.942809899817747, -1.00150151300113, -1.0718607130772173, -1.1525939233972726, -1.2421685453977818, -1.3388460194259484, -1.4407195541890403, -1.5457556481578023, -1.651838436561493, -1.756815831199775, -1.8585463787719765, -1.954945747785854, -2.0440317647184427, -2.123966956683423, -2.1930976194966156, -2.249988515197361, -2.2934524096754654, -2.3225737864456257, -2.3367262137208926, -2.335582995297809, -2.319120897617676, -2.28761691174603, -2.2416381758458974, -2.1820253469347035, -2.1098698663302704, -2.026485707421667, -1.9333763237464023, -1.8321976266892135, -1.7247179127617576, -1.6127757282136506, -1.4982367020684095, -1.382950396582975, -1.268708216237646, -1.1572033829524986, -1.0499939272048047, -0.948469563604489, -0.8538232173540349, -0.7670278474742659, -0.6888190767664871, -0.6196839906281401, -0.5598563107548001, -0.5093179893535962, -0.4678071087681273, -0.4348318143780278, -0.40968985919137285, -0.3914932004020834, -0.3791969647541116, -0.3716319938818583, -0.36754009547485145, -0.3656110632231729, -0.3645204895524385, -0.3629673810655378, -0.3597105976607499, -0.3536031721498246, -0.34362362689153664, -0.328903485925635, -0.30875028322224096, -0.28266548733160163, -0.25035689687108315, -0.21174520650157463, -0.1669645956309538, -0.11635734816261367, -0.06046266722221511, -5.819723779827007e-16], [0.0, 0.06565677192051401, 0.13351720900621417, 0.20242106385631836, 0.2711566688757497, 0.3384968071410374, 0.40323516383192315, 0.46422237929721705, 0.5204007334036048, 0.5708365243253961, 0.6147492625448419, 0.6515368811121112, 0.6807962641546964, 0.7023385146991824, 0.716198517086206, 0.7226384952496797, 0.7221454222212573, 0.7154222945292372, 0.7033734436945766, 0.687084211780564, 0.667795465010486, 0.6468735550992282, 0.6257764586999794, 0.6060169281624352, 0.5891235689943632, 0.5766008188849525, 0.5698888383211687, 0.5703243327467202, 0.5791033105454975, 0.5972467401840225, 0.6255700045584822, 0.6646569625083318, 0.7148393186987574, 0.776181876276567, 0.8484741049612297, 0.9312283040163568, 1.0236844786213848, 1.1248218834929753, 1.2333770232569647, 1.3478677391118676, 1.4666228597217437, 1.5878167547989075, 1.7095080059633818, 1.829681304295155, 1.9462916001711, 2.0573094706228927, 2.160766634112879, 2.2548005332353953, 2.337696922707759, 2.4079294427689337, 2.464195225767733, 2.5054456746956726, 2.5309116645263465, 2.540122547765604, 2.532918491441158, 2.509455830334198, 2.4702052867549145, 2.415943076566505, 2.3477350903471943, 2.2669145034283438, 2.17505332504411, 2.073928541161848, 1.9654836342168587, 1.8517863728171458, 1.7349838528408206, 1.6172558360736724, 1.5007674720590323, 1.3876225022049196, 1.2798180321042882, 1.1792019188097105, 1.087433755440955, 1.0059503475841725, 0.935936466632271, 0.8783015372069085, 0.8336627722383311, 0.8023351136828333, 0.7843281730423664, 0.7793501978271853, 0.7868189219782014, 0.8058789941453925, 0.8354255216018993, 0.8741331232568147, 0.9204897562131072, 0.972834469718126, 1.0293981508309322, 1.0883462598179192, 1.1478225117440246, 1.2059924448958346, 1.2610858268634524, 1.3114368849853852, 1.3555214084564573, 1.3919898531355883, 1.4196956848219582, 1.4377183198335015, 1.4453801600117073, 1.442257369311698, 1.4281841971536111, 1.4032508157578918, 1.36779480071945, 1.3223865420596388, 1.2678090230062937, 1.2050325420734427, 1.1351850772261545, 1.0595190959887606, 0.9793756997119788, 0.8961470518046906, 0.8112380770807525, 0.7260284316010528, 0.6418357292673337, 0.5598809733434045, 0.4812570790630311, 0.4069012891518326, 0.3375721796206757, 0.27383183126058397, 0.21603360599915666, 0.164315820137926, 0.118601452220523, 0.07860386579998803, 0.04383837067480622, 0.013639294219126463, -0.012817908907107245, -0.03649011148649608, -0.05843625127644776, -0.07978416677192687, -0.10169542273789457, -0.12532907028004464, -0.15180531521029397, -0.18217007246207018, -0.21736136320144078, -0.25817846557775986, -0.30525466089603925, -0.3590343260985292, -0.4197550130898406, -0.4874350283952481, -0.5618668860955434, -0.6426168564676412, -0.7290306760668532, -0.8202453260639249, -0.9152066285091736, -1.0126922588103526, -1.1113396309155685, -1.2096779830893198, -1.3061638800353368, -1.3992192543255628, -1.4872710390319779, -1.5687913959800868, -1.6423375214166576, -1.7065900137576853, -1.7603888164688348, -1.8027658024051596, -1.8329731428538651, -1.8505067032447151, -1.8551238256317453, -1.8468549927329965, -1.8260090162495053, -1.7931715497417042, -1.7491968896440553, -1.6951931930195976, -1.6325014033154723, -1.5626683316484737, -1.487414487145604, -1.408597381953762, -1.3281711514161942, -1.248143424710704, -1.17053045356573, -1.0973115546743208, -1.030383943868321, -0.971519036379056, -0.9223212576221823, -0.8841903535739859, -0.8582881102513724, -0.8455102899625642, -0.8464644703042805, -0.8614543332787101, -0.8904707997433325, -0.9331902423780764, -0.9889798423927914, -1.0569099853875992, -1.1357734242520023, -1.2241107758249936, -1.3202417671635056, -1.422301510355707, -1.5282809652038272, -1.636070649699596, -1.743506581442186, -1.8484173808662552, -1.9486714406205439, -2.0422230652980966, -2.127156511954222, -2.201726913799167, -2.2643971458304146, -2.3138697900898384, -2.349113477257183, -2.369383017497341, -2.3742328835207895, -2.3635237690142903, -2.337422112028931, -2.2963926415029254, -2.2411841717284293, -2.172809030180358, -2.092516654800806, -2.0017620339153583, -1.9021697821287802, -1.7954947459102888, -1.6835801107291002, -1.568314035687154, -1.4515858703629794, -1.3352430113996594, -1.2210494332547046, -1.110646879133869, -1.005519625731384, -0.906963640863535, -0.8160608388221213, -0.7336590071835907, -0.6603578341927306, -0.5965013113298526, -0.5421766251370366, -0.49721948983279296, -0.4612257117369844, -0.43356862205096836, -0.4134218699239363, -0.39978693656418623, -0.3915246166590673, -0.38738961836219893, -0.386067359911515, -0.3862119913272849, -0.3864846447827263, -0.3855909176970596, -0.3823166182924874, -0.3755608535713433, -0.36436561308263815, -0.3479410965533026, -0.3256861470223722, -0.29720328062885204, -0.2623079463625115, -0.22103180027299027, -0.173619935005123, -0.12052216311888639, -0.062378607465133434, -5.98015746042168e-16], [0.0, 0.06699141487619259, 0.13568339708518173, 0.2048775517521984, 0.27334306140777476, 0.33985325079587936, 0.40322217931209486, 0.4623402768731759, 0.5162080621861307, 0.5639670302610487, 0.6049268674055606, 0.6385882450651742, 0.6646605563990291, 0.6830740885805179, 0.6939862662421968, 0.6977817536607908, 0.6950663613675067, 0.6866548628840831, 0.6735529851845938, 0.6569339882724121, 0.6381103910933874, 0.618501529275779, 0.5995977416243001, 0.582922074044965, 0.569990459272329, 0.5622713765916182, 0.5611460164692376, 0.5678699700254304, 0.5835374326424508, 0.6090488553814761, 0.6450828985873596, 0.6920734409911963, 0.7501922772223916, 0.8193379998471795, 0.8991314122066244, 0.9889176591134999, 1.0877750978045686, 1.1945307654975434, 1.3077821365785642, 1.425924705896388, 1.5471847887548396, 1.6696567966109397, 1.7913441334924107, 1.9102027646067854, 2.0241864378878263, 2.1312924931177304, 2.2296071729763414, 2.3173493564677825, 2.39291166757828, 2.454897969996628, 2.5021563409203678, 2.5338067214189146, 2.549262565022107, 2.548245947153382, 2.530795752320191, 2.4972687198684644, 2.4483332986214728, 2.384956431733537, 2.308383561432774, 2.220112304903903, 2.1218604034349084, 2.0155286834430113, 1.9031598867799113, 1.7868943258999257, 1.6689233946681, 1.551442015961456, 1.4366011315562692, 1.3264613375155827, 1.2229487394644083, 1.1278140474848297, 1.0425958512314297, 0.9685889142093935, 0.9068182044734031, 0.8580192402842942, 0.8226251769049129, 0.800760898461138, 0.7922442106099239, 0.7965940597562247, 0.8130455368956847, 0.8405712629178589, 0.8779086013091489, 0.9235920073087277, 0.9759897030067244, 1.0333437685127405, 1.0938126625418345, 1.1555151333826021, 1.2165744544400647, 1.2751619179641578, 1.3295385461143665, 1.3780940294591748, 1.4193819780272505, 1.452150667183669, 1.4753685774257823, 1.488244160722985, 1.490239412900841, 1.481076988106279, 1.4607407536700359, 1.4294698476544927, 1.3877464629556915, 1.3362777370030656, 1.2759722710226067, 1.2079119339163091, 1.1333197198328595, 1.05352452266424, 0.9699237627044115, 0.8839448488120956, 0.7970064824929638, 0.710480807848864, 0.6256573834649863, 0.5437098997880213, 0.46566648977383424, 0.39238438351743726, 0.3245295417175935, 0.26256177113866047, 0.20672568107189607, 0.15704768683572018, 0.11333910847513076, 0.07520525402975417, 0.04206022106319614, 0.01314700152675522, -0.012437662768207786, -0.035714350283858304, -0.057788737761863135, -0.07981695429563049, -0.1029694432860715, -0.1283943037997115, -0.1571810976126348, -0.19032609766459382, -0.228699918015745, -0.2730184055767767, -0.32381759136471655, -0.3814333958871412, -0.4459866620639535, -0.5173739529024586, -0.5952644033726479, -0.6791027603059787, -0.7681185845846054, -0.8613414304263433, -0.9576216612340065, -1.055656414199578, -1.154020090371708, -1.251198626657652, -1.3456267043101042, -1.4357269674647117, -1.5199502673454097, -1.5968159143693212, -1.6649509124776938, -1.7231271678749622, -1.770295707613633, -1.8056170111214482, -1.8284866482222437, -1.8385555282738775, -1.835744194037975, -1.8202507376572954, -1.7925520711231593, -1.753398446055546, -1.7038012834873737, -1.6450145395426612, -1.5785099933341518, -1.5059469950963145, -1.4291373517395345, -1.3500061501872767, -1.2705494229542549, -1.1927896428199944, -1.1187300920584782, -1.0503091849935398, -0.9893558297746792, -0.9375468959666327, -0.8963678092248739, -0.8670772240370328, -0.8506766319108017, -0.8478856477212953, -0.8591235839554837, -0.8844977745207975, -0.9237989502070904, -0.9765038006791483, -1.0417846870956806, -1.1185262992556446, -1.2053488857086967, -1.3006375285642762, -1.4025767906128905, -1.509189934345095, -1.6183818036389155, -1.7279843719336851, -1.8358038977331745, -1.9396685908107358, -2.0374756814270913, -2.1272368004748397, -2.207120620335267, -2.2754917733350113, -2.3309451553650518, -2.3723348342412076, -2.39879691299019, -2.409765844232334, -2.404983849622437, -2.384503264038134, -2.348681793816984, -2.298170847693978, -2.2338972640485006, -2.1570389146156814, -2.068994809146612, -1.971350454116314, -1.8658393283718775, -1.7543014269483685, -1.6386398890527436, -1.5207767659063334, -1.4026089978461829, -1.2859656575581087, -1.1725674779421347, -1.0639896199231305, -0.9616285491560959, -0.8666737832462916, -0.7800851455327422, -0.7025760208387835, -0.6346029564101042, -0.5763617913530953, -0.5277903342503986, -0.4885774453461927, -0.4581782208228456, -0.4358348261761996, -0.42060238726467847, -0.41137922467479204, -0.4069406126353298, -0.40597516037906417, -0.4071228536169862, -0.4090137580976795, -0.4103063768982442, -0.4097246683223027, -0.406092771613376, -0.39836655204870924, -0.3856611636793369, -0.36727393478837106, -0.3427020053120631, -0.311654283834627, -0.27405744080395283, -0.2300558105320273, -0.1800052333833123, -0.12446102728857285, -0.064160430353987, -6.126331205960254e-16], [0.0, 0.0681450339508187, 0.13746466794264584, 0.20673207258992998, 0.274707567179257, 0.3401755669349202, 0.4019809963637845, 0.4590641878055755, 0.5104933220849006, 0.555493530199834, 0.5934718597371962, 0.6240374150518544, 0.6470161035412179, 0.6624595584870174, 0.6706479584479003, 0.6720866203016902, 0.667496403792694, 0.6577981257775776, 0.6440913382281644, 0.62762797149212, 0.6097814795891501, 0.5920122439860944, 0.5758300932896956, 0.562754876023665, 0.5542760800476433, 0.5518125237405677, 0.5566731499388049, 0.5700199335598973, 0.5928338682729976, 0.6258849275520539, 0.6697068026351647, 0.7245771065527702, 0.7905036022351457, 0.867216866971835, 0.9541696487483516, 1.0505430060866472, 1.1552591560099654, 1.267000788770626, 1.3842364471356903, 1.5052514163170032, 1.628183431838005, 1.7510623902176436, 1.8718531443919022, 1.9885003848815765, 2.0989745509075943, 2.2013176844182247, 2.2936881351639817, 2.3744030467246744, 2.441977601292896, 2.495160073939439, 2.532961843301307, 2.5546816228396985, 2.559923312191894, 2.5486070184155705, 2.5209729584553466, 2.4775781230273757, 2.419285754212707, 2.34724786018529, 2.2628811565069045, 2.167836980253292, 2.063965867069377, 1.9532776085797108, 1.8378977152988039, 1.7200212956697079, 1.6018654230272646, 1.4856210976486874, 1.3734059197645956, 1.2672185712565225, 1.1688961592183342, 1.0800754047107743, 1.0021585666113546, 0.9362848757530255, 0.8833081213707313, 0.843780883501693, 0.8179457450479555, 0.8057336496239044, 0.8067694001743249, 0.8203841228401809, 0.8456343548278001, 0.8813272581375589, 0.926051316742321, 0.9782117466692769, 1.0360697395240408, 1.097784572918019, 1.161457558090918, 1.2251767572403562, 1.2870613915305331, 1.3453048756550257, 1.3982154557249797, 1.4442534930522855, 1.4820645253951747, 1.5105073471570183, 1.5286764780934545, 1.535918533058952, 1.5318421596220302, 1.516321372135065, 1.489492276021177, 1.4517433405223958, 1.403699537851734, 1.3462008176474707, 1.2802755241070796, 1.207109485766572, 1.128011611577583, 1.0443769091863049, 0.9576479001426038, 0.8692754407611119, 0.7806799657386911, 0.6932141542666893, 0.6081279757689427, 0.5265370056857923, 0.4493948126511116, 0.3774701092721895, 0.3113292323197449, 0.25132437769586596, 0.19758786464767408, 0.15003254616928016, 0.10835832238195277, 0.07206455496188224, 0.04046802741714956, 0.012725952080303434, -0.0121366062768423, -0.0351956349698973, -0.057594246312159494, -0.08050683301864979, -0.10510227059855916, -0.13250715684986625, -0.16377007876591715, -0.1998278719195088, -0.24147478732935995, -0.28933540718616674, -0.3438420554648127, -0.4052173347682106, -0.47346228961805087, -0.5483505521270166, -0.6294286721883712, -0.7160226748795357, -0.8072507267195035, -0.9020416338162126, -0.9991587428035111, -1.0972286736565806, -1.1947741855953429, -1.2902503666000082, -1.3820832464085715, -1.4687098645835626, -1.5486187811096774, -1.6203899981986638, -1.6827332690859622, -1.7345238025109901, -1.7748344295418774, -1.8029633810700376, -1.8184569277009104, -1.8211262563985744, -1.8110580971133845, -1.788618764331614, -1.75445143930605, -1.7094666846926916, -1.6548263503310494, -1.5919211928283428, -1.5223426883728197, -1.4478496639083815, -1.3703305028169275, -1.2917617942973336, -1.214164387858551, -1.1395578834258102, -1.0699146317264792, -1.0071143377200957, -0.9529003513502374, -0.9088386949636199, -0.8762808161537653, -0.8563309699661579, -0.8498190273699203, -0.857279380227476, -0.8789364697348776, -0.9146973089283421, -0.9641512041506578, -1.0265767093705784, -1.100955675109393, -1.1859940846429267, -1.2801492082348696, -1.3816624553647825, -1.4885971689191297, -1.5988804874310556, -1.7103483045591326, -1.8207922814459563, -1.928007819184369, -2.0298418765152713, -2.1242395226158344, -2.2092881462837353, -2.283258300199108, -2.3446402408369353, -2.392175328992053, -2.424881580203405, -2.442072795572082, -2.4433708580977456, -2.428710943923614, -2.398339567762068, -2.3528055531200605, -2.2929441865736413, -2.219854977144901, -2.1348735928768394, -2.0395386833174167, -1.9355544155086568, -1.824749649368087, -1.7090347536970052, -1.5903571146716002, -1.470656413399711, -1.3518207474296893, -1.2356446431019739, -1.1237899521118806, -1.0177505480050288, -0.9188216385491516, -0.8280743905551139, -0.7463364277721877, -0.6741786133782376, -0.6119083700623236, -0.5595696267191173, -0.5169493154309107, -0.4835901798180447, -0.4588095000288752, -0.44172319447475594, -0.4312746274786727, -0.42626733852109344, -0.4254008155136842, -0.42730836378069953, -0.4305960758822676, -0.43388188616861895, -0.435833698469433, -0.43520560541293285, -0.43087127270952624, -0.4218536398806704, -0.40735018833930586, -0.38675314587665033, -0.35966413045884477, -0.325902882372223, -0.28550988846069303, -0.23874286154378888, -0.1860671980480864, -0.12814069337503187, -0.06579294360227878, -6.256987676951095e-16], [0.0, 0.06910758937254162, 0.13884548145965306, 0.20796852335356608, 0.2752386828435935, 0.33946205871755697, 0.3995247920488096, 0.4544269096024267, 0.5033131827495576, 0.5455001611416959, 0.580498637963631, 0.6080309204039609, 0.6280424121172192, 0.6407071605503337, 0.6464271773869464, 0.6458255011068925, 0.6397331327058806, 0.6291701348749207, 0.6153213373672389, 0.5995072330146402, 0.5831507762899829, 0.567740906194847, 0.5547937047631835, 0.545812169299876, 0.5422456188685315, 0.5454497723646633, 0.5566485262554621, 0.5768984248832911, 0.6070567559128872, 0.6477541194773251, 0.6993722138651708, 0.7620274557563372, 0.8355609121045826, 0.9195348672353147, 1.0132361863550203, 1.1156864694585782, 1.225658821707472, 1.341700901896983, 1.4621637537189283, 1.5852357790656668, 1.7089810822433367, 1.8313813019344112, 1.9503799568920333, 2.063928263963838, 2.1700313448591886, 2.2667937222002985, 2.3524630162972895, 2.4254707915637193, 2.484469564691261, 2.5283650741444017, 2.5563430201336548, 2.567889613346687, 2.5628054162449665, 2.54121211914624, 2.5035520607665407, 2.450580475319917, 2.3833506214733826, 2.3031921182101684, 2.211682974828036, 2.110615952936269, 2.001960033740161, 1.8878178808113026, 1.7703802840839173, 1.6518786426624392, 1.534536590423841, 1.4205218882230117, 1.31189969928468, 1.2105883302765617, 1.11831846044949, 1.03659679658085, 0.9666749843480036, 0.9095244798170429, 0.8658179410714332, 0.8359175431439853, 0.8198704531931814, 0.8174115313455005, 0.8279731499983607, 0.8507018548548725, 0.8844814286708903, 0.9279617675825654, 0.9795928436137529, 1.037662908831554, 1.1003399994678256, 1.1657157244766698, 1.2318502741965096, 1.2968175621547948, 1.3587494170705872, 1.4158777725944505, 1.4665738584430663, 1.509383476873512, 1.5430575508411186, 1.5665772520952033, 1.5791731558118858, 1.580338019665857, 1.5698329457135667, 1.5476868490903684, 1.5141893241863849, 1.469877162516892, 1.4155149328860313, 1.3520701797884216, 1.2806839267159378, 1.2026372839225914, 1.1193150524870918, 1.0321672859577153, 0.9426698157998876, 0.8522847662415709, 0.7624220775140671, 0.6744030241557404, 0.5894266578668508, 0.5085400238789585, 0.43261289801931024, 0.3623176712254604, 0.29811487227862593, 0.24024467144280712, 0.1887245512864291, 0.1433531701951841, 0.10372028303505672, 0.06922242617234897, 0.03908392458321728, 0.012382640870182338, -0.011920236864633216, -0.03494717605269752, -0.05786894127118153, -0.08186784908802143, -0.10810062530166235, -0.13766186484166934, -0.17154908000823826, -0.21063028280596482, -0.25561498286664086, -0.30702939546762925, -0.36519654662056966, -0.4302218368327032, -0.5019844850847399, -0.5801351233523986, -0.6640996534356649, -0.7530893159521568, -0.8461167601895689, -0.9420177471749493, -1.0394779707684199, -1.1370643465741022, -1.233259999421509, -1.3265020801518164, -1.415221464018688, -1.4978833282205464, -1.5730275763696797, -1.6393080738982062, -1.6955296806801818, -1.7406821150395773, -1.7739697557017933, -1.7948365834035116, -1.802985579502433, -1.7983920322095406, -1.7813103487405562, -1.75227413012329, -1.7120894307004635, -1.6618212924507962, -1.6027738109535892, -1.5364641510078265, -1.4645910815770247, -1.3889987380842486, -1.3116364416673767, -1.2345155067698932, -1.1596640478174516, -1.089080850693501, -1.0246894038554692, -0.9682931864373242, -0.9215332864312288, -0.8858493715558518, -0.8624449598731478, -0.8522578384002233, -0.8559363582434178, -0.8738221970411157, -0.9059400270695686, -0.9519943639368672, -1.0113737003330017, -1.083161855964513, -1.1661563028008124, -1.2588930582872926, -1.359677582296768, -1.4666209701223676, -1.5776806072619465, -1.6907043451937551, -1.803477173394513, -1.9137693035493395, -2.019384548691842, -2.118207873695076, -2.2082510142564145, -2.287695108764909, -2.354929360043199, -2.4085848401321637, -2.4475626686730356, -2.471055931160141, -2.4785648540611036, -2.469904915840092, -2.445207742309753, -2.4049148073387583, -2.3497641315416926, -2.2807703379927693, -2.1991985811850348, -2.1065330095848904, -2.0044405497179745, -1.8947309076880055, -1.7793137697854549, -1.6601542453482905, -1.5392276308541761, -1.418474583549424, -1.2997577756064331, -1.1848210563564652, -1.0752520817213294, -0.9724492783324994, -0.877593897315573, -0.7916277821794137, -0.7152373299697661, -0.6488439684715359, -0.5926013086831371, -0.5463989651214021, -0.5098728708945651, -0.48242175401661597, -0.46322929010424535, -0.4512913081369732, -0.4454473037820251, -0.44441541188558215, -0.4468299086211044, -0.4512802564246698, -0.45635067260051415, -0.46065919608110134, -0.4628952463605836, -0.4618547135255737, -0.4564716873849494, -0.4458460251499014, -0.4292660685776653, -0.4062259501095641, -0.3764370700226821, -0.3398334793462968, -0.2965710623889408, -0.24702057414312453, -0.19175474749192745, -0.13152983899239332, -0.0672621261619947, -6.37099620849548e-16], [0.0, 0.06987068208679013, 0.13981381265310747, 0.20857633189453428, 0.2749324945441483, 0.3377206188299656, 0.395878172951309, 0.4484742509058654, 0.49473855598635746, 0.5340860994822489, 0.5661369318248365, 0.5907303508429971, 0.6079331737425449, 0.6180418123069996, 0.621578050784791, 0.619278588938201, 0.6120785746616678, 0.6010895073320072, 0.5875720406554102, 0.5729043484742734, 0.5585468353575241, 0.5460040727917008, 0.5367849188676406, 0.5323618325148535, 0.5341304211636309, 0.5433702624360909, 0.5612080159558707, 0.5885837911518716, 0.6262216621876006, 0.6746051236625987, 0.7339581628660026, 0.8042324889877661, 0.8851013101265472, 0.9759598888517823, 1.075932940428027, 1.1838887687116662, 1.29845986737317, 1.4180695526382567, 1.5409640421976276, 1.6652492570897455, 1.7889315026659578, 1.9099610842364452, 2.0262778352111, 2.13585748247686, 2.2367577467717132, 2.3271630756636985, 2.4054269334988603, 2.470110625760202, 2.5200177134460198, 2.5542231744767716, 2.572096591346224, 2.5733187843017093, 2.557891463882858, 2.5261396419215765, 2.4787067120933317, 2.416542285626982, 2.3408830405768035, 2.2532270099239464, 2.155301890634756, 2.049028098832473, 1.9364774219450007, 1.8198282240059018, 1.7013182426378683, 1.5831960736281812, 1.4676724700162842, 1.3568725865015343, 1.2527902766559278, 1.1572455004692777, 1.071845824392179, 0.9979528971254342, 0.9366546643595977, 0.8887439474367901, 0.8547038578737285, 0.8347003555949141, 0.8285820875894524, 0.8358874697046627, 0.8558588016694619, 0.8874630384068771, 0.9294186833110767, 0.9802281252505404, 1.0382146140991175, 1.1015629626524865, 1.1683629784228726, 1.236654569024866, 1.3044734310648038, 1.3698962253797224, 1.431084161231954, 1.4863239580843408, 1.5340652246440059, 1.5729533891389418, 1.601857429882454, 1.6198917881757842, 1.6264319931548568, 1.6211236866038943, 1.6038849010786744, 1.574901612784014, 1.5346167573535332, 1.4837130578486895, 1.4230901659391568, 1.3538367556046944, 1.2771983304049115, 1.1945416074156985, 1.1073164208441069, 1.0170161441789534, 0.9251376601890321, 0.8331419124584871, 0.7424160504162319, 0.6542381325936251, 0.5697452813888909, 0.48990608878985337, 0.41549795872780537, 0.3470899409208082, 0.2850314665532198, 0.22944724160834162, 0.18023839304763292, 0.13708980038660354, 0.09948338467434382, 0.06671697250349364, 0.037928208365123395, 0.012122858066466591, -0.011793267650553338, -0.03497963384513695, -0.058624482460733686, -0.08390749712388186, -0.11196263713971072, -0.14384214245075222, -0.18048268187139432, -0.22267456245149786, -0.27103483972534487, -0.32598506882825773, -0.3877343175226183, -0.45626792706169983, -0.531342358937749, -0.6124863086391826, -0.6990081055406789, -0.7900092550628275, -0.8844038193874585, -0.9809431803513031, -1.0782455865395089, -1.1748297596655741, -1.2691517262971845, -1.3596439526663302, -1.4447557949706356, -1.522994236943323, -1.5929638716383883, -1.653405095798434, -1.703229522642971, -1.7415516815804066, -1.7677161597224251, -1.7813194480842256, -1.7822258823637838, -1.7705772111034062, -1.746795479340195, -1.7115790797244654, -1.6658919914813324, -1.6109463963426545, -1.5481790254988796, -1.4792217486125991, -1.4058670610849497, -1.3300292554440845, -1.2537021736787195, -1.1789145267724572, -1.1076838333349435, -1.0419700693865706, -0.9836301349720351, -0.9343742299451363, -0.8957251912367235, -0.8689817781024968, -0.8551868017955684, -0.8551008839685041, -0.8691824965750292, -0.8975747882875915, -0.9400995420514576, -0.9962584392516409, -1.0652416321878808, -1.1459434523655117, -1.236984911760865, -1.3367424918626656, -1.4433825648876535, -1.5549006567896706, -1.6691646458180849, -1.783960896261078, -1.8970422569303387, -2.0061768096136934, -2.1091962352211264, -2.204042675098793, -2.2888130017399213, -2.3617994759757774, -2.4215258551381833, -2.4667781265041717, -2.496629169869355, -2.510456799177604, -2.50795479218399, -2.4891366852558034, -2.4543322835142365, -2.4041770103609412, -2.3395943907806322, -2.261772125515427, -2.1721323643149173, -2.0722969223143934, -1.964048300899841, -1.8492874703601787, -1.7299894439138321, -1.6081577196226116, -1.4857786871930276, -1.3647770902892256, -1.2469736019810478, -1.1340455122191198, -1.0274914432942293, -0.9286009042220689, -0.8384293705592399, -0.7577794354392514, -0.6871884241508095, -0.6269227022056136, -0.5769787396111332, -0.5370908261395544, -0.506745167938249, -0.4851999389350495, -0.47151071503165626, -0.464560588635858, -0.4630941488610235, -0.4657544214619644, -0.4711217944932952, -0.47775391240062715, -0.4842255037939369, -0.4891671168673508, -0.49130177102534467, -0.48947859281085476, -0.48270258714125097, -0.4701597989962504, -0.45123724339164784, -0.42553711957651474, -0.3928849753900615, -0.3533316457934078, -0.3071489517396543, -0.2548193076529078, -0.19701954374904118, -0.13459939925158015, -0.06855528044706213, -6.467365433000001e-16], [0.0, 0.07042765441011148, 0.14036130794568624, 0.20855061974657674, 0.2737927958875502, 0.33496875071344334, 0.3910770490709671, 0.4412647105824799, 0.4848540374378349, 0.5213647291507355, 0.5505306687682474, 0.5723109020863756, 0.5868944810551068, 0.5946990009775608, 0.5963628243193254, 0.5927311478198561, 0.5848362299904206, 0.5738722489268243, 0.5611654017782536, 0.5481399835954408, 0.5362812914029561, 0.527096286425523, 0.5220730111932256, 0.5226397970815179, 0.5301253106573005, 0.5457204735996929, 0.5704432512013127, 0.6051072394454728, 0.6502948919420887, 0.7063361177310067, 0.7732928518093157, 0.8509500553693113, 0.938813445705081, 1.0361140904282307, 1.141819831111916, 1.2546533319561204, 1.3731163837445626, 1.4955199363586742, 1.6200191883436204, 1.7446529331077676, 1.8673862515181823, 1.9861555527026729, 2.0989149010212884, 2.2036825290731548, 2.29858642527215, 2.381907900312565, 2.4521220794407865, 2.5079343358774384, 2.548311773384246, 2.5725089806306234, 2.5800874139306074, 2.5709279148581565, 2.5452360315761333, 2.503539983490853, 2.4466812839166514, 2.3757982105403985, 2.292302484345674, 2.1978496801220184, 2.094304041780191, 1.9836985097540865, 1.8681908825189517, 1.7500171268900078, 1.631442920022483, 1.5147145482464777, 1.402010303008429, 1.2953935018883949, 1.196768223223904, 1.1078387772654743, 1.0300738466257096, 0.9646761162724338, 0.9125580812125084, 0.8743245715501817, 0.85026237341377, 0.8403371542674318, 0.8441977265124132, 0.8611875082952466, 0.8903628693438801, 0.9305178866106527, 0.9802148834741452, 1.0378199909002113, 1.1015428525553532, 1.1694795012017196, 1.239657363041678, 1.310081301686503, 1.3787795951281527, 1.4438487478669813, 1.5034960758946674, 1.556079063594835, 1.6001405772131, 1.634439127178258, 1.6579734985019872, 1.6700012115494491, 1.6700504310694406, 1.6579251056103137, 1.6337032882313758, 1.597728758550347, 1.5505962314480466, 1.4931305950895064, 1.4263607664303568, 1.3514888824759017, 1.2698556570566941, 1.182902823057647, 1.092133646704553, 0.9990725420798559, 0.9052248295459507, 0.812037670889845, 0.7208631771177052, 0.63292462292221, 0.5492866165448232, 0.47082996726686055, 0.3982318678234436, 0.33195186883652883, 0.2722239704793055, 0.21905499687470734, 0.17222925524732666, 0.13131931873259747, 0.09570261312788976, 0.06458333775801503, 0.037019112816202716, 0.011951623511855256, -0.011759571810122006, -0.03530098411188073, -0.05986785936747061, -0.08662657339603258, -0.1166777690142381, -0.15102122999433723, -0.19052344204769198, -0.23588872233698968, -0.28763470758172927, -0.3460728789626408, -0.41129467256911745, -0.4831635803324129, -0.5613134918733746, -0.6451533663670816, -0.7338781594637903, -0.8264857676559229, -0.9217995953638355, -1.0184962024150799, -1.115137355265868, -1.2102056876848946, -1.3021430787007793, -1.389390779928176, -1.4704302729036838, -1.54382381114868, -1.6082536020610803, -1.662558610494697, -1.7057680184262773, -1.7371304522036666, -1.7561381886653595, -1.7625456715021868, -1.7563818066653805, -1.7379556570415573, -1.707855318288281, -1.666939925664023, -1.6163249117386198, -1.557360802817943, -1.4916060035850813, -1.4207941708221468, -1.3467969143502312, -1.271582683069283, -1.197172793180321, -1.1255956318168951, -1.0588401204527318, -0.9988095472538464, -0.9472768753193032, -0.9058426044834287, -0.8758962086789849, -0.8585820900825478, -0.8547708872968299, -0.865036850161327, -0.889641851425807, -0.9285264489141585, -0.9813082447467087, -1.0472876147369357, -1.1254607054544816, -1.214539422929868, -1.3129779697985289, -1.4190053309228337, -1.530662965018118, -1.6458468350235254, -1.7623528059494373, -1.8779243582415197, -1.990301509298466, -2.097269807018, -2.196708257824981, -2.2866350775866118, -2.3652502065045646, -2.430973607198863, -2.4824784668482227, -2.5187185469361655, -2.538949064867224, -2.5427406470203784, -2.529986058899228, -2.5008995908621103, -2.4560091532511854, -2.3961413083111625, -2.322399633868635, -2.2361369712566512, -2.138922253594369, -2.032502736792715, -1.9187625615109947, -1.7996786571989116, -1.6772750573559212, -1.553576726873029, -1.4305640070882557, -1.3101287619488646, -1.194033260059526, -1.0838727536827297, -0.9810426188404872, -0.8867108030074096, -0.801796191454472, -0.7269533535031599, -0.6625639695319088, -0.6087350725461269, -0.5653040686391202, -0.531850332945554, -0.5077130158793752, -0.492014542555824, -0.4836891500681751, -0.48151568612169066, -0.4841537913849381, -0.4901825092619829, -0.4981403125115684, -0.5065655075227727, -0.5140359747385066, -0.519207227678454, -0.5208478225735786, -0.5178712244687024, -0.5093633318548711, -0.4946049779798496, -0.47308885997916417, -0.4445304934778191, -0.40887294660678103, -0.36628526948944357, -0.3171546990722871, -0.26207288055253264, -0.20181650151149508, -0.13732287928104323, -0.06966117240343107, -6.54525459273059e-16], [0.0, 0.07077367379341427, 0.1404834053288134, 0.20789230824126276, 0.271831128257831, 0.33123349184422596, 0.3851683911835909, 0.4328690244026737, 0.4737572036144324, 0.5074626573452486, 0.5338366853850742, 0.5529597697237937, 0.5651429013413357, 0.5709225452599771, 0.5710493313334392, 0.5664707215618054, 0.5583080621457138, 0.5478285760320363, 0.5364129856033579, 0.5255195720088182, 0.5166455744309204, 0.5112869068362624, 0.5108972195334747, 0.5168473568345896, 0.5303862596062155, 0.5526043324855393, 0.5844002406677584, 0.6264520217384255, 0.6791932959353153, 0.7427952359587736, 0.8171548179949027, 0.9018897223957139, 0.9963400892484493, 1.0995771648941408, 1.2104187045120285, 1.3274508274143546, 1.4490558598861527, 1.573445549292215, 1.6986988965372272, 1.822803735233816, 1.9437010880997558, 2.0593312566517987, 2.167680551098929, 2.266827544750528, 2.354987741879559, 2.4305555797819562, 2.4921427440449335, 2.5386118594194937, 2.5691047252056944, 2.5830643911501414, 2.580250514460482, 2.560747597162788, 2.5249658718166463, 2.4736347784568076, 2.407789152292452, 2.3287484158596747, 2.23808923674038, 2.1376122685438936, 2.0293037347706013, 1.9152927389711105, 1.7978052872527308, 1.679116088157395, 1.5614992483098713, 1.447179008706744, 1.3382816654384007, 1.236789790035272, 1.1444998092072571, 1.0629839228585798, 0.9935572348901511, 0.9372508460017092, 0.8947915145421594, 0.8665883339293485, 0.8527267071196305, 0.8529697241572822, 0.8667668722307053, 0.893269833211918, 0.9313549556050955, 0.9796518302638657, 1.0365772559777127, 1.1003737555404394, 1.169151698221668, 1.2409340031736713, 1.3137023421505702, 1.3854437303024263, 1.4541963913831055, 1.5180938084594373, 1.5754059224401566, 1.6245765171166562, 1.664255928965678, 1.6933283401805395, 1.7109330512423375, 1.7164792813551328, 1.7096542074479952, 1.6904241211405935, 1.6590287538808683, 1.6159689891522206, 1.5619883430355912, 1.4980487464867906, 1.4253013007045021, 1.3450527975311313, 1.2587288970003585, 1.167834931489398, 1.073915358592889, 0.9785129115705026, 0.8831284964432284, 0.7891828585989241, 0.6979809898514702, 0.6106801706570845, 0.528262443609472, 0.45151219595211994, 0.38099939369287394, 0.3170688614304306, 0.25983584398088333, 0.20918792233619546, 0.16479319153993402, 0.12611444590355678, 0.09242896170934468, 0.06285332307642413, 0.0363726066522316, 0.011873128514125543, -0.011822135042708844, -0.035916409981321666, -0.06160127162177887, -0.09001909619676512, -0.12222682897376966, -0.15916204732317782, -0.20161223822404395, -0.2501881271378382, -0.3053017910254285, -0.3671501651592596, -0.4357044143962775, -0.5107054882343215, -0.5916660190965022, -0.6778785589143922, -0.7684299843684844, -0.8622217402645829, -0.9579954375567341, -1.0543631813580547, -1.1498418785059459, -1.242890667082638, -1.331950524488983, -1.4154850484508432, -1.4920213683377026, -1.5601901333980925, -1.618763540316731, -1.6666904045601456, -1.7031273473298565, -1.7274652609790901, -1.7393503282701055, -1.738699002112307, -1.7257064992112956, -1.7008485197656271, -1.664876072056942, -1.6188034513667697, -1.5638895928914205, -1.501613183984375, -1.4336420780081043, -1.3617976964047696, -1.2880152336828838, -1.2143005886437799, -1.142685031591798, -1.075178679282906, -1.0137238853638117, -0.9601496630733423, -0.916128238719205, -0.8831347892780568, -0.8624113464306569, -0.8549357541122461, -0.861396449504182, -0.8821737011335669, -0.9173277856738726, -0.9665944208361024, -1.0293875993943962, -1.1048097930950858, -1.1916693192483474, -1.2885044914879098, -1.3936140136879371, -1.5050929263157318, -1.6208732812335418, -1.7387686073993172, -1.8565211388332137, -1.9718507098403166, -2.0825041824354757, -2.186304258181039, -2.281196541534633, -2.3652937639459126, -2.43691614630585, -2.494626970266452, -2.5372625441371124, -2.563955883709047, -2.5741535791668704, -2.5676254825307887, -2.544467021844206, -2.5050941243866354, -2.450230907256438, -2.380890465442374, -2.2983492508087013, -2.2041156862894686, -2.099893794369346, -1.9875427343658827, -1.8690332363480697, -1.7464019885017752, -1.621705077761283, -1.4969715995855986, -1.3741585415517772, -1.255108007320984, -1.1415077835244025, -1.0348561638692904, -0.9364318345299081, -0.8472694954505694, -0.7681417468039148, -0.6995476121592721, -0.6417079038623079, -0.5945674658451467, -0.5578041588076059, -0.53084428665807, -0.5128840053844416, -0.5029161100330436, -0.4997614657851145, -0.502104238414111, -0.5085299903801573, -0.5175656436225105, -0.5277202702995947, -0.5375256592153509, -0.5455756187176066, -0.5505630160527037, -0.5513136174503728, -0.5468158809086643, -0.5362459624815118, -0.5189873240468827, -0.49464447280182955, -0.4630505164683724, -0.42426837949555113, -0.3785856903169049, -0.3265035137967925, -0.2687192622225743, -0.20610426854864364, -0.13967664327535484, -0.07057015787584807, -6.603983414639129e-16], [0.0, 0.07090579870206083, 0.14017941691051156, 0.2066081664160749, 0.2690667425001651, 0.32655123916883455, 0.3782098733697953, 0.42336958309207573, 0.4615577705752038, 0.4925185870380032, 0.5162232962166271, 0.5328744070202814, 0.5429034269055376, 0.5469622530586266, 0.5459083839722798, 0.5407842953171149, 0.5327914770448525, 0.5232597695320615, 0.5136127616889231, 0.5053301201184355, 0.49990780288890907, 0.49881717208755644, 0.5034640544612567, 0.5151488081636175, 0.5350284356167312, 0.5640817381317061, 0.6030784382444486, 0.6525531023779966, 0.7127845817004478, 0.7837815557079804, 0.8652746143956253, 0.9567151545440239, 1.0572811976069187, 1.165890065091364, 1.281217676437971, 1.401724068481689, 1.5256845787408821, 1.6512259909637583, 1.7763668141626314, 1.8990607589901676, 2.017242390476233, 2.1288738760154766, 2.2319917136347, 2.324752318889491, 2.4054753694865068, 2.472683854469905, 2.525139848449632, 2.5618751291476696, 2.582215876159562, 2.585800827395416, 2.5725924238290583, 2.5428806392097436, 2.497279365244347, 2.4367154002084677, 2.3624102656678705, 2.2758552476756506, 2.1787802212630565, 2.0731169662932665, 1.9609578151478502, 1.844510585026064, 1.7260508371085155, 1.6078725692780513, 1.4922384869231866, 1.3813310066452127, 1.2772051301954734, 1.1817442811106587, 1.0966201253876313, 1.0232573018840376, 0.9628038702859042, 0.9161081473292758, 0.8837024488521042, 0.8657940899256029, 0.8622638218081847, 0.8726717070136593, 0.8962702567149112, 0.932024482327105, 0.9786383496227054, 1.0345869730930832, 1.0981537541362747, 1.1674715522551584, 1.2405668865428836, 1.3154060975037043, 1.3899423582880372, 1.4621624106427635, 1.5301319145522592, 1.5920383412577015, 1.646230406010974, 1.6912531278269674, 1.7258777163318628, 1.7491256177162937, 1.7602861994773977, 1.7589277133766146, 1.7449013438643801, 1.718338320951291, 1.6796402478733314, 1.6294629606605986, 1.5686943947527692, 1.4984270792147696, 1.4199260083195808, 1.334592750119647, 1.243926739450734, 1.149484766483413, 1.0528397099457862, 0.9555395756177567, 0.8590678854373319, 0.7648064210271321, 0.6740012587636016, 0.5877329434191843, 0.5068915362382397, 0.4321571439136548, 0.3639863906184148, 0.30260513968853653, 0.2480076087015721, 0.19996185567671007, 0.15802144914064611, 0.12154297502932973, 0.08970888286536675, 0.061555036163633906, 0.03600221104166949, 0.01189068559640771, -0.011983016689732201, -0.03682822143528791, -0.0638220573429406, -0.09407229471719833, -0.12858207065448732, -0.16821745438928107, -0.21367873309918403, -0.26547620261119514, -0.3239111313293597, -0.38906243225097087, -0.4607794305233739, -0.5386809563391257, -0.6221608290579821, -0.7103996324253699, -0.8023825168316454, -0.8969226068801105, -0.9926894451079871, -1.0882417692848927, -1.1820638047030976, -1.2726041572461562, -1.358316320244043, -1.4376997600914507, -1.5093405236015702, -1.5719503147214864, -1.624403019511132, -1.66576771548343, -1.69533728316665, -1.712651842111888, -1.7175163579911492, -1.7100119088703065, -1.6905002537207363, -1.6596215109327246, -1.618284924940912, -1.5676528708455684, -1.5091184158463544, -1.4442769181915662, -1.3748922951446658, -1.3028587274068237, -1.2301586850940096, -1.1588182567805358, -1.0908608358376177, -1.02826026544645, -0.9728945640091151, -0.9265013456359119, -0.890636016048034, -0.8666337633664611, -0.8555762772840282, -0.8582640210813316, -0.8751947514628783, -0.9065488343802048, -0.952181744426482, -1.0116239649293866, -1.0840883296805621, -1.1684846696118765, -1.263441452991915, -1.3673339401363194, -1.4783182172959182, -1.594370333129014, -1.7133296384335448, -1.8329453286145885, -1.9509251111704597, -2.0649848691870956, -2.172898167693118, -2.272544453338748, -2.3619548291351227, -2.4393543441617114, -2.503199821797228, -2.552212357108279, -2.5854037419215863, -2.6020962216845396, -2.6019351479267048, -2.584894260071747, -2.551273506366222, -2.501689491495859, -2.43705881371859, -2.3585747227911917, -2.2676776875101807, -2.1660206045069805, -2.055429504579298, -1.9378607163027708, -1.8153555264727208, -1.6899934311831177, -1.5638450987992203, -1.4389261661230384, -1.3171529617641764, -1.2003011968631558, -1.0899685842739126, -0.9875422451179252, -0.8941716388636294, -0.8107476128520854, -0.737888012999075, -0.6759301331082193, -0.6249301099238491, -0.5846691989704383, -0.5546666966355155, -0.5341991110523167, -0.5223250321480188, -0.5179150134891229, -0.5196856586556486, -0.5262370057369581, -0.5360922275676675, -0.5477386143331844, -0.5596687803649042, -0.5704210388534041, -0.5786179167037477, -0.5830018360465626, -0.5824670675636358, -0.5760871617435426, -0.5631371848514646, -0.5431102236891271, -0.515727773635254, -0.4809437841693741, -0.4389423010405449, -0.39012881026848795, -0.3351155520582269, -0.2747012283537015, -0.20984567222110842, -0.14164017689371597, -0.07127429385754776, -6.643040434379734e-16], [0.0, 0.07082302580373738, 0.13945257272913583, 0.20471079981393123, 0.2655264818287347, 0.32096747783389, 0.37026940363595395, 0.41285972691893785, 0.4483766220524917, 0.4766820569889065, 0.49786873383245644, 0.5122606638285684, 0.52040732265215, 0.523071498795818, 0.5212111123420171, 0.5159554392768849, 0.5085763237581361, 0.5004550936356489, 0.4930460096490514, 0.4878371731396944, 0.48630988837837286, 0.48989752186545354, 0.49994492097096443, 0.5176694474686983, 0.5441246479714319, 0.5801675237544687, 0.6264302783738532, 0.6832973148729812, 0.750888127823453, 0.8290465920630087, 0.9173369933022929, 1.0150469796399024, 1.1211974415625239, 1.2345591554670952, 1.3536758564142406, 1.4768932439265376, 1.6023932742259175, 1.7282329571308448, 1.8523867593052024, 1.9727916206119716, 2.0873935193926285, 2.19419447739554, 2.2912988770065965, 2.3769579729203776, 2.4496115172784636, 2.507925480765013, 2.5508249407029067, 2.5775213187306103, 2.58753328248425, 2.580700774680966, 2.557191795491512, 2.517501736157742, 2.4624452392683835, 2.3931407396308595, 2.3109880149127267, 2.2176392428943035, 2.1149642181761004, 2.0050105217048966, 1.8899595580812627, 1.7720794753106588, 1.6536760570164497, 1.537042726297712, 1.4244108221796017, 1.3179013034321883, 1.2194790005713148, 1.1309104759291382, 1.0537264652792804, 0.9891897647316852, 0.9382692961572642, 0.9016209364478546, 0.8795755340771007, 0.8721343646525264, 0.8789720996300997, 0.8994471834277049, 0.9326193381819463, 0.9772737466252662, 1.031951306117137, 1.0949842045604643, 1.1645359452126212, 1.2386448452379133, 1.315269954690259, 1.3923382903118633, 1.467792253298478, 1.5396361025590282, 1.6059803848506746, 1.6650832796883097, 1.7153878986419786, 1.7555546834619424, 1.784488172757179, 1.801357549549003, 1.8056105383555277, 1.7969803866320626, 1.7754858372597206, 1.741424172070271, 1.6953575768248261, 1.6380932414132594, 1.5706577612818065, 1.4942665434844176, 1.4102890399232624, 1.320210728389894, 1.2255928365681268, 1.1280308534297563, 1.0291128952965727, 0.9303789897694505, 0.8332823099236402, 0.7391533344920117, 0.6491678287032886, 0.5643194371153616, 0.48539755684397295, 0.4129710201795419, 0.34737796326298187, 0.28872209612620386, 0.23687542308687495, 0.19148729543114193, 0.15199951474614182, 0.11766704930793942, 0.08758378152540608, 0.060712575227577434, 0.03591884081698029, 0.012006686783172828, -0.012243319968183971, -0.03803580340515774, -0.06652267042768105, -0.09876666701752622, -0.13570738173981334, -0.1781306165179538, -0.2266419575931797, -0.281645271094155, -0.3433267204216114, -0.41164475991083943, -0.48632640457782583, -0.5668699130919573, -0.6525538545639158, -0.742452363507883, -0.8354562256450463, -0.9302992841643378, -1.025589515537737, -1.1198439995832965, -1.2115269033616953, -1.2990895153841018, -1.381011307655417, -1.4558409698303056, -1.5222363531302754, -1.5790022819042169, -1.6251252373850373, -1.6598039902118957, -1.682475353925226, -1.6928343485801325, -1.690848199005826, -1.6767637427406104, -1.651107984585073, -1.6146817040393775, -1.5685461944287584, -1.514003383990009, -1.4525697553229742, -1.3859446362598173, -1.3159735784519684, -1.2446076662249785, -1.1738597043225627, -1.1057583163638647, -1.0423010440432112, -0.9854075687942954, -0.9368741819575256, -0.898330606241699, -0.8712002209508498, -0.8566646672139563, -0.8556337091106291, -0.8687211045284299, -0.8962270987540293, -0.9381279975953739, -0.9940731090424711, -1.0633891671782278, -1.1450921735155266, -1.2379064135153803, -1.3402902340637377, -1.4504680053535348, -1.5664675419025875, -1.6861621259762238, -1.8073161656947765, -1.9276334323095996, -2.0448067586798495, -2.156568045408707, -2.2607374132776727, -2.355270360746366, -2.4383018328757142, -2.508186181923276, -2.5635320982473653, -2.603231710638496, -2.6264831948290293, -2.6328063843050833, -2.622051044864337, -2.594397649546307, -2.5503506693348132, -2.490724573039172, -2.4166229026673633, -2.3294109542076344, -2.23068274406434, -2.1222230748097943, -2.005965627197324, -1.8839480958115418, -1.7582654511556204, -1.6310224498551371, -1.5042865261137606, -1.3800421813818695, -1.2601479458711091, -1.1462969162092704, -1.0399817799627966, -0.9424651223345245, -0.8547556759815313, -0.7775910249646677, -0.7114271120852074, -0.6564347293185352, -0.6125029979361628, -0.5792496725110623, -0.5560379355948586, -0.5419991915729577, -0.5360612229435886, -0.5369809435944329, -0.5433808747116589, -0.5537883823978944, -0.5666766539823416, -0.5805063538477153, -0.5937668901955209, -0.6050162416739832, -0.6129183366805153, -0.6162770472434027, -0.6140659518777137, -0.6054531353087088, -0.5898204245505635, -0.5667766071595413, -0.5361643348246196, -0.498060579820832, -0.4527706790665573, -0.4008161663647413, -0.3429167536787891, -0.2799669729505196, -0.2130081272098224, -0.14319632009434916, -0.07176743336097166, -6.662089672192136e-16], [0.0, 0.07052631784795943, 0.1383100251168258, 0.2022185798921409, 0.2612445866441439, 0.31453641537656296, 0.3614245467490537, 0.4014429233131523, 0.43434471623642246, 0.46011206146312256, 0.47895947551715434, 0.4913308251424531, 0.4978898925475418, 0.49950474493094404, 0.4972262789809951, 0.4922614640541494, 0.4859419478483482, 0.47968881202971897, 0.47497436927798603, 0.4732819749130068, 0.4760648835323206, 0.4847052124174159, 0.500474077992553, 0.524493949152686, 0.5577042123004959, 0.6008308685957654, 0.6543611860091529, 0.7185240096661162, 0.7932762965791571, 0.8782962885746963, 0.9729835737808883, 1.0764661164974596, 1.1876141618470215, 1.305060749619695, 1.4272284054536784, 1.5523614210958652, 1.678562992875244, 1.8038363622808846, 1.926128997826296, 2.0433787758616138, 2.153561061754854, 2.2547355633724955, 2.3450918268590337, 2.422992270476385, 2.48701170516518, 2.5359723693084044, 2.568973608049237, 2.5854154519790007, 2.585015493071359, 2.5678186139359727, 2.5341992959616464, 2.4848564085946925, 2.4208005615497905, 2.3433342797985333, 2.2540254333772136, 2.154674516190963, 2.0472765160991298, 1.9339782490205302, 1.8170321393996602, 1.6987475154385154, 1.58144054790988, 1.4673839946411733, 1.358757918071402, 1.2576025204997454, 1.1657741913136312, 1.084905783830724, 1.0163720382829837, 0.9612609443777278, 0.9203516947959076, 0.8940997233987036, 0.8826291526561557, 0.8857327980146463, 0.9028796968940883, 0.933229951136376, 0.9756564983671169, 1.0287732640961877, 1.0909689964393656, 1.1604459527221056, 1.2352624951267488, 1.3133785636567359, 1.3927029311323165, 1.4711411081929928, 1.5466427571910137, 1.6172474925663283, 1.6811279912587953, 1.7366294087327154, 1.782304192414733, 1.8169415023405586, 1.839590585597615, 1.8495776033108602, 1.8465155726476847, 1.830307257535789, 1.801141016241988, 1.7594797873243309, 1.7060435634574114, 1.6417858610961817, 1.567864838987957, 1.4856098466088445, 1.3964842915625337, 1.302045800216392, 1.2039047063139563, 1.1036819365669004, 1.0029673695231056, 0.9032797242339555, 0.8060289889829239, 0.7124823288291949, 0.6237343158327839, 0.5406822100116121, 0.46400688530546835, 0.3941598465007407, 0.33135662397600235, 0.27557666729906904, 0.22656969034072988, 0.18386825392702041, 0.1468062113393483, 0.11454249124493163, 0.08608955569836013, 0.060345751147358274, 0.03613067091458649, 0.012222570912860943, -0.012603171690209731, -0.03953559320661376, -0.06969070734833933, -0.10407610695531379, -0.14355855907528095, -0.18883547129649933, -0.24041100698873563, -0.2985775067952923, -0.36340273638008624, -0.43472332954062826, -0.5121446351657938, -0.5950470102098812, -0.6825984330816007, -0.7737731468595529, -0.8673758837294407, -0.9620710750084371, -1.056416318822131, -1.1488992633087571, -1.237976970072539, -1.322116752898076, -1.3998374422914528, -1.4697500084209902, -1.53059648401982, -1.581286164637357, -1.6209281254680776, -1.648859180371971, -1.664666517542592, -1.6682043749210642, -1.6596042637425474, -1.6392784069577606, -1.6079162267848328, -1.5664738881667801, -1.5161570781549645, -1.4583973708974485, -1.394822689752509, -1.3272225280238936, -1.2575087241647436, -1.18767270263862, -1.1197401850401694, -1.0557244451823904, -0.9975792248669311, -0.947152442824654, -0.906141817372624, -0.8760534838918141, -0.8581646221769742, -0.8534910175944269, -0.8627603659738877, -0.8863919979937562, -0.9244835477332397, -0.9768049257188802, -1.042799783178583, -1.1215944755583303, -1.2120143540097061, -1.3126070378978842, -1.4216721537010233, -1.537296870074464, -1.6573964191448092, -1.7797586737019393, -1.9020917518236935, -2.02207354700505, -2.1374020348777285, -2.245845188253014, -2.3452893409829967, -2.4337848778047504, -2.5095881910192954, -2.5711989340101087, -2.6173917140499423, -2.647241499836112, -2.660142169486183, -2.6558177886509533, -2.634326381959365, -2.5960561399683715, -2.5417141837878354, -2.472308186203754, -2.3891213171356394, -2.2936811385317646, -2.1877232155177526, -2.073150333345025, -1.9519883104820583, -1.8263394746419064, -1.6983349188353132, -1.5700866775155575, -1.4436409580501133, -1.320933530309683, -1.20374831798177, -1.0936801508249614, -0.9921025296309727, -0.9001411278672062, -0.81865360904339, -0.7482161804074626, -0.6891171355799119, -0.6413574653616464, -0.6046584415010512, -0.5784759070010485, -0.5620208428159404, -0.5542856285653306, -0.5540752779178421, -0.5600428109228962, -0.5707278286768627, -0.5845972826416017, -0.6000873834318641, -0.6156455730552712, -0.6297714908593615, -0.6410558965722317, -0.648216572903476, -0.6501303136417114, -0.6458602088771006, -0.6346775641743638, -0.6160779320216396, -0.5897908880786612, -0.555783347726966, -0.5142563860535068, -0.46563569243546976, -0.41055595509106696, -0.34983962717422196, -0.28447067028066036, -0.21556399996347003, -0.14433146778696063, -0.07204530281365563, -6.660975580198431e-16], [0.0, 0.0700186118213945, 0.13676281330870207, 0.19915551438356313, 0.256262422772931, 0.3073205245502755, 0.35176184456564125, 0.38923183528057614, 0.4196018817637003, 0.44297556318184156, 0.45968847318004763, 0.4703015689798794, 0.47558818759884564, 0.47651503303185394, 0.4742175963398006, 0.4699706173423369, 0.46515432827349046, 0.4612173329665949, 0.4596370669843064, 0.4618788522279668, 0.46935460216775654, 0.4833822497878816, 0.5051469591628505, 0.5356651434744657, 0.5757522481222693, 0.6259951689047263, 0.6867300642029012, 0.7580261893953151, 0.8396762345815297, 0.9311934867201738, 1.0318159684498935, 1.1405175323443908, 1.2560257154666983, 1.3768459891637708, 1.501291877321952, 1.6275202668349311, 1.7535711005707688, 1.877410529027586, 1.9969765050297397, 2.1102257385837007, 2.215180888127338, 2.3099768509614482, 2.3929050300656116, 2.462454496501658, 2.5173490352451737, 2.5565791559477424, 2.579428266588449, 2.5854923444257567, 2.574692591815527, 2.5472807306066945, 2.5038367639261496, 2.4452592139559113, 2.37274802440426, 2.2877804923807386, 2.1920807619997666, 2.087583567157859, 1.9763930497554827, 1.8607375987631605, 1.742921752039371, 1.6252762743238103, 1.510107569593695, 1.3996476028769569, 1.296005495240324, 1.2011219162807472, 1.1167273319993327, 1.0443050740444308, 0.9850600812139868, 0.9398940286130866, 0.9093874072763153, 0.8937889511074674, 0.8930126327093477, 0.9066422693462034, 0.9339435992945564, 0.9738835116001937, 1.0251559430794077, 1.0862137993884475, 1.1553061159409277, 1.2305195527858943, 1.3098232181976146, 1.3911157410468955, 1.4722734637898898, 1.5511986072366104, 1.6258662655823721, 1.6943691252461057, 1.754958862922304, 1.8060832653237922, 1.84641822315675, 1.8748938821528207, 1.8907143812168026, 1.8933707682531944, 1.8826468540109387, 1.8586179391134892, 1.8216425249854589, 1.7723472913044802, 1.7116057866540018, 1.64051143119107, 1.5603455666387205, 1.4725414064286477, 1.3786448344985782, 1.2802730727820715, 1.1790722831144342, 1.0766751880621988, 0.9746597866839058, 0.8745102057460657, 0.7775806654229352, 0.6850634526226169, 0.5979616870318544, 0.5170675375347533, 0.44294640309419325, 0.3759274161441069, 0.31610046198852876, 0.2633197388085094, 0.21721371391261654, 0.17720116709882372, 0.14251285558163723, 0.11221819082047457, 0.08525618939193302, 0.06046985100402898, 0.03664302959459326, 0.01253880037550402, -0.013061711741414678, -0.04132108773978544, -0.07330898350782386, -0.1099680992080627, -0.15208366815399463, -0.2002572929038422, -0.2548858435248607, -0.31614600175704777, -0.38398488843224254, -0.4581170536859451, -0.5380279442283167, -0.62298379340159, -0.7120477122136247, -0.8041015972504727, -0.8978733184558344, -0.9919685101128629, -1.0849061655356973, -1.175157133118442, -1.261184531144988, -1.3414850432169314, -1.4146300267754537, -1.4793053647889691, -1.5343490153887671, -1.578785265518331, -1.6118547713096438, -1.6330395680659853, -1.6420823539773277, -1.6389994910513266, -1.624087320781025, -1.5979215569865985, -1.5613496899798287, -1.5154765104448529, -1.4616430338726494, -1.4013992727301217, -1.3364714596297746, -1.2687244666805435, -1.2001202903746298, -1.1326735746622414, -1.0684052246586162, -1.0092952176655243, -0.9572357454501907, -0.9139858212504244, -0.8811284566914963, -0.8600314583208853, -0.8518128120768891, -0.8573115186330209, -0.8770646157241875, -0.9112909783179263, -0.9598823273580516, -1.022401706664844, -1.0980895095879482, -1.185876956512467, -1.2844067457198063, -1.3920604277664952, -1.5069918916811773, -1.627166203855611, -1.750402911131609, -1.8744228114360646, -1.9968971110456324, -2.1154978292434303, -2.2279482801997874, -2.332072459134863, -2.42584218528142, -2.5074209072474307, -2.575203155792346, -2.6278487328427573, -2.66431085125331, -2.683857584301015, -2.6860861436613765, -2.6709296757565837, -2.6386564447159073, -2.589861451400281, -2.5254507176034364, -2.4466186382801784, -2.3548189682467178, -2.251730159280882, -2.139215895304215, -2.0192817841760617, -1.894029251912017, -1.765607746778204, -1.6361663952647914, -1.5078062586300631, -1.3825343174417815, -1.2622202629223194, -1.1485570991989968, -1.0430264616811624, -0.9468694362329944, -0.8610635246169198, -0.7863062473315346, -0.7230057093123491, -0.6712782811250207, -0.6309533725505131, -0.6015851011922835, -0.5824704902339826, -0.5726736708959345, -0.5710554203782827, -0.5763072386845296, -0.5869890607979056, -0.6015696168257486, -0.6184683939448111, -0.6360981216559501, -0.6529066967098316, -0.6674174861375612, -0.6782669954729017, -0.6842389631854139, -0.68429403962668, -0.6775943269146627, -0.6635221921175561, -0.6416929163806051, -0.6119609034468205, -0.5744193382763679, -0.5293933559359731, -0.4774269483256655, -0.4192639974098595, -0.3558239743612101, -0.2881729806118373, -0.21749092580010942, -0.14503573601086972, -0.0721055610618618, -6.639726198458997e-16], [0.0, 0.06930480716877524, 0.13482578841097395, 0.19555105957644625, 0.2506281354561326, 0.2993899989390592, 0.3413760402421116, 0.3763472895668206, 0.4042955146768391, 0.42544591423015105, 0.4402533042075228, 0.44939186423621025, 0.45373867872067647, 0.45435147019520217, 0.45244107507875453, 0.449339351152575, 0.446463328045921, 0.4452765136825304, 0.4472483483926558, 0.4538128521876769, 0.4663275381044239, 0.4860336647923326, 0.5140188745557964, 0.5511832094764169, 0.5982094192934274, 0.6555383723210456, 0.7233502573253111, 0.8015521229959314, 0.8897721459110715, 0.9873608515538419, 1.0933993401203852, 1.2067143938538658, 1.325900169803357, 1.4493460155548186, 1.5752697897745296, 1.701755928250359, 1.8267973730669842, 1.9483403807206028, 2.064331146960293, 2.172763133946267, 2.2717239603139947, 2.3594407176317773, 2.4343226075536193, 2.494999852025146, 2.540357912849778, 2.5695661647758534, 2.582100295439782, 2.577757852882719, 2.5566665233814687, 2.519284895065157, 2.46639564202439, 2.3990912449899455, 2.3187525437352625, 2.2270205887637267, 2.1257624213583908, 2.0170315577418174, 1.9030240813201804, 1.7860313536209036, 1.668390436955803, 1.552433378022057, 1.440436530203541, 1.3345710925429377, 1.2368560152023937, 1.1491143653935887, 1.0729341655906994, 1.0096346093405566, 0.9602384317472251, 0.9254510648586433, 0.905647046301306, 0.9008639765412564, 0.9108041403122704, 0.9348437254258, 0.972049391801177, 1.0212017695157931, 1.0808253012011533, 1.1492236951659076, 1.2245201248146962, 1.3047012004053136, 1.3876636535745346, 1.471262615400506, 1.5533603364541806, 1.631874193045127, 1.7048228477196326, 1.770369483361298, 1.8268611076417227, 1.872863026097983, 1.9071877052088595, 1.9289173884127178, 1.937419984515587, 1.9323579154773292, 1.9136897849709724, 1.8816649060595227, 1.836810901446419, 1.7799147587066664, 1.7119978815340338, 1.6342858224498258, 1.548173509076339, 1.4551868818979772, 1.3569419438546328, 1.255102279162552, 1.1513361291006292, 1.0472741154659302, 0.9444686780065656, 0.8443562410800426, 0.7482230484226868, 0.6571755052416369, 0.5721157464250171, 0.49372301159168314, 0.42244125548991357, 0.35847325977213407, 0.3017813435394707, 0.25209459953213664, 0.20892241474684825, 0.1715738728315331, 0.13918248490800567, 0.11073555929850143, 0.08510740240574415, 0.061095445687679856, 0.037458319717397714, 0.012954847576491662, -0.013617092489192744, -0.043382880570224866, -0.07735565867678515, -0.11640398080456205, -0.16122348378746398, -0.21231334865737234, -0.2699581978086077, -0.33421593215345186, -0.4049118582265399, -0.48163929175398074, -0.563766655686275, -0.6504509213715965, -0.7406570757112249, -0.8331831390015039, -0.9266901117470399, -1.019736097758619, -1.11081373867308, -1.1983900045301725, -1.28094731855183, -1.3570249535312893, -1.425259623348701, -1.4844242065101705, -1.5334635789989546, -1.571526600194358, -1.597993386563631, -1.612497121057254, -1.614939778868592, -1.6055012991919397, -1.5846418941523532, -1.5530973561886081, -1.5118673996265455, -1.4621972466455018, -1.405552837966817, -1.34359021012995, -1.2781197301217166, -1.2110660106456368, -1.1444244421171281, -1.0802153676845971, -1.0204369928971901, -0.9670181603702874, -0.9217721308970417, -0.8863524955572889, -0.8622122988138216, -0.8505673813744459, -0.8523648554105013, -0.8682575058516352, -0.8985847727795623, -0.9433608147705551, -1.0022699851492738, -1.0746698765960576, -1.1596019086954632, -1.2558092522379358, -1.361761707805497, -1.4756869886981976, -1.5956077036910554, -1.7193831972404974, -1.8447552869669663, -1.969396843420298, -2.090962087619166, -2.2071374393595793, -2.315691734863389, -2.4145246463522025, -2.5017121782553695, -2.575548183973931, -2.6345809417452215, -2.677643945880618, -2.7038802076143456, -2.7127595146402514, -2.7040882663514507, -2.678011678741011, -2.6350083345583024, -2.5758772362218436, -2.5017176967386234, -2.4139025731514527, -2.314045503721003, -2.203962950352934, -2.0856319683135833, -1.961144723140539, -1.8326608475080284, -1.7023587769297337, -1.572387221511184, -1.4448179211219578, -1.32160079366141, -1.204522521539628, -1.0951695317477257, -0.9948962122249868, -0.9047990744815655, -0.8256974229306391, -0.7581209288552524, -0.7023043354296022, -0.6581893439901435, -0.6254335551755369, -0.603426165990906, -0.5913099595569921, -0.5880089723195395, -0.5922610875453292, -0.6026546873386321, -0.6176684010069527, -0.635712917661578, -0.6551737871162896, -0.6744541164528444, -0.6920160803818428, -0.7064202013853409, -0.716361419549726, -0.7207010603024644, -0.7184939186667996, -0.7090098083085397, -0.6917490692565216, -0.666451686027269, -0.6330998339691366, -0.5919138417554183, -0.5433417277992074, -0.4880426336476989, -0.4268646339727001, -0.3608175466646593, -0.2910414941397051, -0.21877207507634777, -0.1453030916976161, -0.07194783925349059, -6.598554475674729e-16], [0.0, 0.06839173407783541, 0.13251749925874046, 0.19143987609534655, 0.24439623220675902, 0.29082212645243316, 0.330369213757019, 0.36291715462453383, 0.38857918922117685, 0.4077012006885435, 0.42085426189882924, 0.4288208298838406, 0.432574918347905, 0.4332567367915712, 0.4321424308073797, 0.4306096883394417, 0.4301000877965937, 0.432079153022542, 0.43799514495219566, 0.4492376586245897, 0.4670971060323001, 0.4927261496947582, 0.5271041091646883, 0.5710052939090571, 0.6249721228000062, 0.6892937750741459, 0.7639909828965401, 0.8488074249148497, 0.943208017133017, 1.0463842261118708, 1.1572663541704729, 1.2745425712810647, 1.3966842980872434, 1.5219773831874504, 1.6485583695579895, 1.7744550134718096, 1.8976301078232969, 2.0160275732272552, 2.1276197168921462, 2.230454522724738, 2.322701827396284, 2.4026972564935227, 2.4689828420009396, 2.5203433161374735, 2.555837175264448, 2.574821728837193, 2.576971489274457, 2.5622894157623337, 2.531110694581374, 2.4840989164234557, 2.4222346930140075, 2.3467969367367574, 2.2593372034384136, 2.161647665850808, 2.0557234390094163, 1.9437201158944237, 1.8279074879126096, 1.7106205179134926, 1.5942087008984456, 1.4809849877697834, 1.3731754593786272, 1.2728709214578637, 1.1819815461619034, 1.102195613960943, 1.0349433123001617, 0.9813664271011725, 0.9422946227839872, 0.9182288494431438, 0.9093322459486155, 0.9154287291992868, 0.93600927688381, 0.97024572835262, 1.017011750022058, 1.0749104424470575, 1.1423079099207438, 1.2173719739722746, 1.298115092807251, 1.382440452437458, 1.4681901242803848, 1.553194140048788, 1.6353193188077797, 1.7125166934707856, 1.7828664243600236, 1.8446191547080717, 1.8962328554006251, 1.9364043215173636, 1.9640946184193442, 1.9785479268748483, 1.9793034012259378, 1.9661998277840989, 1.9393730482079117, 1.8992462901632483, 1.8465137207115574, 1.7821177023479973, 1.7072203833763773, 1.6231703896447147, 1.5314655002719757, 1.4337122830694993, 1.3315837336618632, 1.2267760042250555, 1.1209653223285878, 1.0157661873194166, 0.9126918914354284, 0.8131183464780544, 0.7182521061503911, 0.6291033614271516, 0.5464645544596248, 0.4708951088990633, 0.4027126149008247, 0.34199063949765746, 0.2885631617454657, 0.24203546137637552, 0.20180112394769759, 0.16706466882785437, 0.13686916275345704, 0.11012805473546357, 0.0856603609738409, 0.06222824384449371, 0.038575969065562654, 0.013469191326821122, -0.014266488188768951, -0.04570872869237693, -0.08180441051965688, -0.12333926687181829, -0.17091200790638464, -0.22491364155674598, -0.28551256033241695, -0.35264581347990304, -0.42601682306257094, -0.5050996348199079, -0.589149624341103, -0.6772204104529954, -0.7681865650576303, -0.8607715560931102, -0.9535802217164874, -1.0451349527553697, -1.1339146600456036, -1.2183955260517272, -1.2970924881614647, -1.3686003756314484, -1.4316336240497778, -1.4850635203992106, -1.527951987694322, -1.559580999399381, -1.57947681844538, -1.5874283811003915, -1.5834992891263688, -1.568033031046956, -1.5416512210611648, -1.505244818007291, -1.4599584624873723, -1.4071682434266297, -1.3484533716395986, -1.285562393241141, -1.2203747160768834, -1.1548583442167533, -1.0910248158702052, -1.030882416283863, -0.9763887873043077, -0.9294040780057773, -0.8916457754447507, -0.8646463212539396, -0.8497145591623356, -0.8479019720365839, -0.8599745567341915, -0.8863910535842213, -0.9272880978366461, -0.9824726965667927, -1.051422260266067, -1.1332922379366002, -1.2269312223358473, -1.3309032125374989, -1.4435165485770989, -1.562858871856579, -1.6868373191400596, -1.8132230309639545, -1.939698950227746, -2.0639098062138506, -2.183513125291594, -2.296230083429006, -2.399895018022663, -2.492502447417731, -2.5722505050883, -2.637579780362619, -2.687206666746802, -2.7201504496659776, -2.7357535146197733, -2.7336942207038195, -2.7139921591856626, -2.6770056980849533, -2.623421897079296, -2.5542390580759884, -2.470742351054164, -2.3744731180596834, -2.2671926065674457, -2.150841013225502, -2.027492827133068, -1.8993095456869296, -1.768490893663419, -1.6372257062388826, -1.5076436384234624, -1.3817688369187404, -1.2614766564333453, -1.1484544223987625, -1.0441671378592114, -0.9498289066916052, -0.8663807013947367, -0.794474945066122, -0.7344672078103798, -0.6864151419028204, -0.6500846019249534, -0.6249627201997153, -0.6102775385225073, -0.605023638576839, -0.6079930694321604, -0.6178107446668935, -0.6329733770038367, -0.6518909374165123, -0.6729295703969033, -0.6944548687573411, -0.7148744105888877, -0.7326784877431206, -0.7464780086871159, -0.7550386373793703, -0.7573103318755787, -0.7524515690683806, -0.7398476821541532, -0.7191228915308034, -0.6901457739488422, -0.6530280847060462, -0.6081170191951687, -0.5559811688543785, -0.49739058827709476, -0.43329154083948757, -0.36477662591247045, -0.29305110813137597, -0.2193963653551854, -0.14513144445016934, -0.07157376106929307, -6.537857729509137e-16], [0.0, 0.06728810203619852, 0.12986004010787744, 0.18686153036703065, 0.23762709841885224, 0.28170058668063247, 0.3188498371445671, 0.34907513943539087, 0.37261119631561135, 0.3899225276335086, 0.4016924048525674, 0.4088055774053858, 0.4123252148879401, 0.41346464141448647, 0.41355457641173116, 0.4140067162221167, 0.416274590034266, 0.42181269931029625, 0.43203500006832524, 0.4482738107742456, 0.4717402245405235, 0.5034870728501367, 0.544375429837463, 0.5950455626525684, 0.6558931266355554, 0.7270512765454239, 0.8083792200581591, 0.8994575807518934, 0.9995907687699871, 1.107816382492048, 1.2229214881993353, 1.343465451292641, 1.4678088264428806, 1.5941476592921056, 1.7205524128655796, 1.8450106112229658, 1.965472194127553, 2.079896502170033, 2.186299763770969, 2.2828019350789304, 2.367671751573737, 2.439368886074114, 2.4965821710390976, 2.538262932069386, 2.563652592244077, 2.5723038406666956, 2.5640948101150514, 2.5392358743216454, 2.4982688511300366, 2.442058579297965, 2.371777019620414, 2.288880210855067, 2.195078583248145, 2.0923012930582163, 1.9826553864190952, 1.8683807266103956, 1.7518017222230153, 1.6352769722684415, 1.5211479960441685, 1.4116882392467203, 1.3090535428202392, 1.2152352274459695, 1.1320168852193602, 1.0609358824111867, 1.003250465394115, 0.9599132285559384, 0.9315515515591296, 0.9184554473318646, 0.9205730857314453, 0.9375140752039394, 0.9685604004204235, 1.0126847322856094, 1.0685756523035206, 1.1346691702820766, 1.2091857667152783, 1.290172062468535, 1.375546111712148, 1.4631452319573335, 1.5507752295005504, 1.6362598508709028, 1.7174892916145843, 1.7924666228499373, 1.8593510527018453, 1.9164970225124376, 1.9624882445239238, 1.9961659158502976, 2.0166504897877555, 2.0233565462105756, 2.0160004739611326, 1.9946008555222141, 1.959471623464257, 1.9112082347621433, 1.850667278722256, 1.7789400927795669, 1.697321103930227, 1.607271738552775, 1.5103808468028785, 1.4083226671474338, 1.3028134100417055, 1.1955675660055174, 1.0882550418582797, 0.9824601997566974, 0.8796438177611852, 0.781108909420988, 0.6879712354270642, 0.6011352154242862, 0.5212758057964753, 0.4488267532621088, 0.3839754684050331, 0.32666459200906395, 0.2766001545964601, 0.23326606023952115, 0.19594446378843272, 0.16374146021172675, 0.13561736955905315, 0.11042078452246885, 0.08692545261229773, 0.0638689939515345, 0.03999241039894131, 0.014079323256836317, -0.015006114349909866, -0.048283648464290785, -0.08662465470597273, -0.13072403761824736, -0.18107705960547643, -0.23796173167009269, -0.3014272533949243, -0.3712888322013976, -0.44712904583528273, -0.5283057414975006, -0.6139662943716839, -0.7030678818323823, -0.7944032715760999, -0.8866314763216196, -0.9783124982871886, -1.0679452766792412, -1.1540078637438045, -1.234998791804857, -1.3094785567971878, -1.3761101340922721, -1.4336974602307972, -1.481220859141006, -1.5178684624824161, -1.5430627691986787, -1.5564816068655838, -1.5580728940983355, -1.5480627557680031, -1.5269567073002426, -1.495533796810463, -1.4548337699817597, -1.406137498026823, -1.3509410794124566, -1.2909241870019046, -1.2279133798458506, -1.163841229311433, -1.100702219280707, -1.040506466975515, -0.9852323723447701, -0.9367793382779378, -0.8969217102474837, -0.8672650620861186, -0.8492059049229261, -0.8438958199744505, -0.852210914712003, -0.8747273783210244, -0.9117037693064242, -0.9630705090390027, -1.0284268838418895, -1.1070456790478704, -1.1978853856865137, -1.299609738548009, -1.410614167767607, -1.5290585791052107, -1.652905724853164, -1.7799642915526197, -1.907935715772696, -2.034463647935212, -2.1571849188035808, -2.2737808254156264, -2.3820275438719944, -2.4798444957427694, -2.5653395424698813, -2.6368499568751105, -2.6929782209211224, -2.7326218217860427, -2.754996361108928, -2.759651451467942, -2.7464790458869186, -2.7157140262464603, -2.6679270605177003, -2.604009922260518, -2.5251536443697926, -2.4328200482750306, -2.3287073455949443, -2.214710647846294, -2.092878337859522, -1.9653653512231755, -1.8343844851034228, -1.7021568935353517, -1.5708629418022015, -1.4425945775453763, -1.319310333219826, -1.2027940045550662, -1.0946179545882249, -0.9961118750059543, -0.908337698925129, -0.8320712052977749, -0.7677906886792425, -0.7156728932858094, -0.6755962314230698, -0.6471511279123412, -0.6296571584836783, -0.6221864855162081, -0.6235929430306661, -0.6325459881820656, -0.6475686219439336, -0.6670782899942651, -0.6894297082076779, -0.7129585172003686, -0.7360246579696207, -0.7570543760357544, -0.7745798041561356, -0.7872751424842978, -0.7939885481875776, -0.7937689616057878, -0.7858872300798934, -0.7698510401829901, -0.7454133304430004, -0.7125740256665226, -0.6715751063809055, -0.6228891983528562, -0.5672020332943092, -0.5053892885463335, -0.43848845679922177, -0.36766652316359083, -0.29418433298687235, -0.21935861705607623, -0.1445226991623389, -0.07098694297531533, -6.458215240931518e-16], [0.0, 0.06600442907623458, 0.12687886151054661, 0.18186014453583327, 0.2303864503352222, 0.27211467891775754, 0.3069317587212382, 0.3349595251214347, 0.35655302435809244, 0.3722922618578627, 0.38296758519415247, 0.3895590586278258, 0.39321034408584954, 0.3951977485400672, 0.3968952263461962, 0.3997362339060529, 0.4051734202298947, 0.4146371983709155, 0.4294942776712515, 0.45100724435071665, 0.4802962579242461, 0.5183038836831864, 0.5657640081338953, 0.6231756866255963, 0.6907826528017935, 0.7685590809135974, 0.856202037858308, 0.9531308958686017, 1.0584938031948663, 1.171181133213942, 1.2898456565723824, 1.412929010625379, 1.538693879830664, 1.6652611539347362, 1.7906512014472866, 1.912828287313746, 2.0297470786320777, 2.1394001229076887, 2.2398651512559806, 2.32935105502994, 2.40624140875917, 2.4691344645249473, 2.516878621762066, 2.5486024801106604, 2.5637387088628665, 2.5620411117281687, 2.5435944265650035, 2.508816572487603, 2.4584532371507333, 2.3935648806404894, 2.3155064147697235, 2.225899993229136, 2.1266015146508024, 2.0196615931122106, 1.9072818852000195, 1.7917677761523911, 1.6754785170119915, 1.560775967939553, 1.44997313829075, 1.3452837208578414, 1.2487737956333418, 1.16231682808412, 1.0875530094426247, 1.0258538838030673, 0.9782930813490097, 0.9456238318848432, 0.9282637715306774, 0.9262873818946871, 0.9394262194852339, 0.9670769079864203, 1.008316681800508, 1.061926090438447, 1.1264183042598583, 1.2000743068275477, 1.2809831215079983, 1.3670861032405692, 1.4562242334212112, 1.546187288821156, 1.6347637159684947, 1.7197900313632588, 1.7991985854776025, 1.8710625742113998, 1.9336372541378184, 1.9853964156321158, 2.025063288362729, 2.051635193619477, 2.064401414062796, 2.0629539198155316, 2.0471907662055187, 2.01731215853412, 1.9738093585432497, 1.9174467813593625, 1.8492377963250406, 1.7704148962479884, 1.6823950335089348, 1.5867410349144184, 1.4851200974132535, 1.3792604316548784, 1.2709071583276368, 1.1617785724209748, 1.0535238728469483, 0.9476834097668424, 0.8456524307145005, 0.7486492110543328, 0.657688336927387, 0.5735597726322688, 0.49681419283192807, 0.4277548969233367, 0.36643645248600937, 0.31267004124590075, 0.2660353088313737, 0.22589835309582304, 0.19143532912645195, 0.16166100618732485, 0.13546148634201557, 0.11163018951129688, 0.08890612786954669, 0.06601343581031374, 0.041701091622181934, 0.014781764245698647, -0.015831256922515545, -0.0510900398936544, -0.09178180960716407, -0.13850338291679024, -0.19164093176482191, -0.2513556283463555, -0.3175755728328335, -0.3899942405637584, -0.46807551567578115, -0.5510652062276307, -0.6380087663588355, -0.7277747881935889, -0.8190836742075618, -0.9105407634855416, -1.0006730662155328, -1.087968662941484, -1.170917751051386, -1.2480542726360269, -1.3179970364984945, -1.3794892533321346, -1.431435436830178, -1.472934683968116, -1.503309433462682, -1.5221289103755555, -1.5292265943262, -1.5247111956185937, -1.5089707841417324, -1.4826698861944814, -1.4467395401800287, -1.4023604790357231, -1.3509397808947172, -1.2940814954718751, -1.2335519078648693, -1.1712402399814756, -1.1091157091480617, -1.0491819605907902, -0.9934299629250349, -0.9437905016607535, -0.9020874238078912, -0.8699927764078439, -0.8489849433865745, -0.8403108193812622, -0.8449529676713132, -0.8636025942223711, -0.8966390338914856, -0.9441162913251036, -1.0057570117304053, -1.0809540795833366, -1.1687798607698745, -1.2680029200979932, -1.3771118660549797, -1.4943458025282303, -1.6177307071777896, -1.7451209121756956, -1.8742447386489498, -2.002753234443243, -2.128270888272719, -2.248447143831917, -2.36100751625376, -2.4638031209413724, -2.5548574611178787, -2.632409384557993, -2.694951210341059, -2.7412611409040832, -2.7704292103953705, -2.781876174032065, -2.775364911106831, -2.751004092381303, -2.709244046510295, -2.6508649453852486, -2.57695761036147, -2.488897415815944, -2.3883119291348507, -2.277043073110504, -2.157104724284089, -2.030636765929891, -1.8998566946173983, -1.7670099327031712, -1.6343200244496587, -1.5039398901881649, -1.3779052811881232, -1.25809151851263, -1.1461745136585622, -1.0435969593636516, -0.9515404483637319, -0.8709041293682115, -0.8022903467928713, -0.74599753789077, -0.7020204821421706, -0.6700578175259135, -0.6495265610470684, -0.6395832010047431, -0.6391507701233335, -0.6469511657189863, -0.6615418590185502, -0.6813560336021945, -0.7047451151637423, -0.7300226032242202, -0.7555080912881027, -0.7795703657069218, -0.8006685050244758, -0.8173899599437139, -0.8284846777318902, -0.8328944416941491, -0.8297767235485684, -0.8185224908774198, -0.7987675696356367, -0.7703973289655209, -0.7335446280626932, -0.688581138205552, -0.6361023229273044, -0.5769065213986492, -0.5119687303250995, -0.4424098142727141, -0.3694619899448431, -0.2944315236465138, -0.21865965065207055, -0.14348276870745952, -0.07019297437767816, -6.360383996543962e-16], [0.0, 0.0645529523283376, 0.12360254611616858, 0.17648399814629379, 0.2227447306591163, 0.2621584884188979, 0.29473312637499477, 0.32071184204031195, 0.34056779769929524, 0.3549922501849313, 0.3648764758482459, 0.37128794117067954, 0.3754413210996816, 0.3786651037593026, 0.38236463821398003, 0.3879825784212629, 0.3969577489130095, 0.4106835042111161, 0.4304666732789158, 0.45748817187959495, 0.4927663297001851, 0.5371239163383663, 0.5911597622463903, 0.6552257596245189, 0.7294098967809285, 0.8135258308672394, 0.9071093418351052, 1.009421838960525, 1.1194609146137893, 1.2359777625180688, 1.3575011039711513, 1.4823670997540108, 1.6087545718780458, 1.7347247217978001, 1.8582644137148758, 1.9773319961219045, 2.089904564229932, 2.1940255222217804, 2.2878512885502507, 2.369696000235247, 2.438073113086008, 2.491732863062516, 2.5296946479951403, 2.5512735063662215, 2.5561000079999006, 2.5441330269699782, 2.5156650360493162, 2.4713197404770555, 2.412042052360376, 2.339080591172275, 2.253963076049924, 2.1584651475232794, 2.0545733156919397, 1.9444428748040297, 1.8303517471564963, 1.7146513192011492, 1.5997154072346045, 1.4878885372256163, 1.3814347420102882, 1.2824880687824782, 1.1930059507505193, 1.1147265299547982, 1.0491309251563203, 0.997411321670733, 0.9604456218768934, 0.9387792392334761, 0.9326144487844282, 0.9418075274584405, 0.965873732342378, 1.0039999790384881, 1.055064899725721, 1.1176657860715125, 1.1901517599169797, 1.2706623686171086, 1.3571706755892223, 1.4475298130518017, 1.5395218856045574, 1.6309080620692507, 1.7194786700732427, 1.803102113709623, 1.8797714690395428, 1.9476476743003004, 2.005098319856449, 2.0507311549511065, 2.0834215613683655, 2.102333394881326, 2.1069327600789656, 2.096994458749009, 2.0726010321172397, 2.034134498454149, 1.9822610653872204, 1.917909266325326, 1.8422421285360298, 1.7566241227474448, 1.662583767204138, 1.5617728599080862, 1.4559233888959886, 1.3468032200374949, 1.2361716838410064, 1.125736176670619, 1.0171108578554497, 0.9117784633494115, 0.8110561704830771, 0.7160663391737992, 0.6277128255315261, 0.5466634174215866, 0.47333878194500456, 0.4079081460181184, 0.350291757545755, 0.30017000046993797, 0.2569988666295791, 0.22003132517197427, 0.18834398028945604, 0.1608682740770078, 0.1364253766748766, 0.11376381344023273, 0.09159881098794392, 0.06865230223789427, 0.04369251612970895, 0.015572090753763226, -0.016736311055682997, -0.05410783815413301, -0.0972376031022511, -0.1466179002307815, -0.20252110785580354, -0.2649887444577323, -0.33382698819044737, -0.4086088005486361, -0.4886826226655924, -0.5731874409122402, -0.6610738515820439, -0.7511305967157168, -0.8420158985576992, -0.9322927924288842, -1.0204675502123162, -1.1050302019439224, -1.1844961033696257, -1.257447464337414, -1.3225737474347945, -1.3787098685649486, -1.4248711806893197, -1.4602842975760861, -1.4844129142523717, -1.4969779025218917, -1.497971100386096, -1.4876623700264553, -1.4665996663075311, -1.4356020323891268, -1.395745616642964, -1.3483429812231786, -1.294916142934658, -1.2371639472093465, -1.176924522010874, -1.1161336866582927, -1.0567802976413596, -1.000859596760469, -0.9503256842167939, -0.9070442690951209, -0.8727468511930492, -0.8489874612255199, -0.8371030316461333, -0.8381783889401844, -0.8530167521825786, -0.8821164944541902, -0.9256547764617066, -0.9834784989731974, -1.0551028464178953, -1.1397175124480168, -1.2362005138542995, -1.3431393164735108, -1.4588588201007187, -1.5814555832524422, -1.7088375169987484, -1.838768143721526, -1.9689144048460019, -2.096896914093219, -2.2203414917771553, -2.336930782640589, -2.4444547555217655, -2.5408589078972357, -2.6242890514733164, -2.693131635222905, -2.746048667645442, -2.7820064280084127, -2.800297303799452, -2.8005542549906584, -2.7827575810160874, -2.747233849322045, -2.6946470305153865, -2.625982069978253, -2.5425213048447297, -2.445814304097103, -2.3376418641412404, -2.219975028819226, -2.0949301181147195, -1.9647208410314765, -1.8316086330991588, -1.6978523961519312, -1.5656588265868967, -1.4371344980977805, -1.3142408164582429, -1.1987528885537548, -1.092223247448787, -0.9959512523544659, -0.9109588400094129, -0.8379731457534758, -0.777416342395049, -0.7294028670686159, -0.6937440250525072, -0.6699597794433895, -0.6572973610997938, -0.6547561686613191, -0.6611182777573665, -0.6749837454203742, -0.6948097834497852, -0.7189527857471232, -0.7457121315810429, -0.7733746508237757, -0.800258629228427, -0.8247562518940883, -0.8453734305990038, -0.8607660343933767, -0.8697716408064973, -0.8714360447090835, -0.8650339002159352, -0.8500830244908055, -0.8263520570276384, -0.7938613397592577, -0.7528770578457373, -0.7038988538193296, -0.6476412945587019, -0.5850097271386844, -0.5170712020215739, -0.44502126675156584, -0.37014753716459314, -0.29379103353861113, -0.2173063240829408, -0.1420215463406075, -0.06919937777100103, -6.245292612340705e-16], [0.0, 0.06294752070166254, 0.12006255151493045, 0.17078508543100954, 0.21477645271956614, 0.2519299991381634, 0.2823752606698736, 0.30647550568680654, 0.32481868862990504, 0.33820203158627643, 0.34761061716045727, 0.35419053353129043, 0.3592172565537051, 0.36406008053388483, 0.37014351563543624, 0.3789066530322733, 0.3917615567596029, 0.4100517722100472, 0.43501204453246056, 0.4677303156655944, 0.5091130169253553, 0.559854596196808, 0.6204121167498846, 0.6909856409999499, 0.771504970217566, 0.8616231537750249, 0.9607170129044792, 1.0678947483262409, 1.1820105228622493, 1.3016857337305874, 1.4253365190381708, 1.5512068833207944, 1.6774066818407487, 1.8019535764080794, 1.922817969963494, 2.037969845745739, 2.1454263816674146, 2.243299182998674, 2.3298399773827625, 2.4034836456522286, 2.4628875192452617, 2.506965958911743, 2.5349193378625, 2.5462566829558444, 2.540811376787572, 2.51874948803849, 2.480570473138939, 2.4271001749510885, 2.359476229286682, 2.2791261731419064, 2.1877387250566755, 2.087228873661632, 1.979697561191838, 1.867386880812971, 1.7526318167675579, 1.6378096418842334, 1.5252881457810168, 1.4173738976678405, 1.3162617492375448, 1.2239867556619424, 1.1423796368253456, 1.0730268179742606, 1.017235980942813, 0.9760079266487747, 0.9500153998131862, 0.9395893614786959, 0.9447130179111388, 0.9650237301722427, 0.9998227415330385, 1.0480924745088218, 1.1085209701439407, 1.1795328736092852, 1.2593262162852503, 1.3459141090135682, 1.437170347383473, 1.530877840507226, 1.6247787118719554, 1.7166248860092066, 1.8042279686930252, 1.8855072512433566, 1.9585347206487396, 2.021576035309322, 2.073126529258437, 2.11194143315741, 2.1370596450368073, 2.1478205440742326, 2.1438735126708766, 2.125180011455331, 2.0920082341679715, 2.044920550164408, 1.9847541170710075, 1.912595210636552, 1.829747969022978, 1.7376983809993922, 1.638074458535427, 1.5326036214538008, 1.4230683830165993, 1.3112614591542386, 1.1989414297519896, 1.087790057939837, 0.979372323341952, 0.8751001490704943, 0.7762007018835171, 0.6836900229555203, 0.5983526062533215, 0.5207273861462622, 0.4511004295507374, 0.3895044548237266, 0.3357251241493613, 0.289313882728928, 0.249606951052521, 0.21574992009648383, 0.18672725737926896, 0.16139590797395093, 0.13852207191385726, 0.11682016049865712, 0.0949928807721259, 0.07177137121189144, 0.04595431307742262, 0.016444970840784504, -0.01771482908344059, -0.057314690920707685, -0.10295041856362555, -0.15500424104752925, -0.21363103188065224, -0.2787509031870051, -0.3500483892903936, -0.42697826237552844, -0.5087778495699415, -0.5944855505962798, -0.6829650923713817, -0.7729349057150295, -0.8630018735289956, -0.9516985828830342, -1.0375231183944296, -1.1189803635607292, -1.1946237321415096, -1.2630962344696621, -1.323169794205412, -1.3737817693278664, -1.4140676961958611, -1.443389365735754, -1.461357454027365, -1.4678480629793365, -1.463012677118472, -1.4472812060412785, -1.4213579547288964, -1.3862105414114652, -1.3430519605565439, -1.2933161624012268, -1.2386276858919165, -1.1807660347822921, -1.1216256231146038, -1.063172232917791, -1.007397020729567, -0.9562691780810095, -0.9116883925846179, -0.875438269620762, -0.8491418593980175, -0.8342203906527322, -0.8318562414355617, -0.8429610809686856, -0.8681499967453568, -0.907722280763311, -0.9616493914262637, -1.0295704370319338, -1.1107953470436067, -1.2043157128994135, -1.308823095457981, -1.4227344158314086, -1.5442238747389967, -1.671260686841677, -1.801651774689256, -1.9330884454240047, -2.063195975232, -2.1895849541478194, -2.3099031989968295, -2.4218870261282253, -2.523410688573505, -2.612532824068975, -2.6875388300109857, -2.7469781771899937, -2.789695793755965, -2.8148567913991887, -2.8219639637727063, -2.8108676588905754, -2.781767808432741, -2.735208083162913, -2.6720623304890236, -2.593513633023412, -2.501026501389746, -2.396312876242778, -2.2812927595969033, -2.1580504205913296, -2.0287872227401533, -1.8957721960830312, -1.7612915266523088, -1.6275981561661994, -1.496862676406568, -1.371126665616785, -1.2522595494367617, -1.1419199780333833, -1.0415225964793202, -0.9522109499529475, -0.8748371123587276, -0.8099484603059794, -0.7577818381694315, -0.7182651785491692, -0.6910264603311643, -0.675409708211603, -0.6704975673734365, -0.6751398291661722, -0.6879871419986824, -0.7075290196590124, -0.7321351598790127, -0.7600990115525691, -0.7896824813553001, -0.8191606506941004, -0.8468653823352924, -0.8712267324150212, -0.8908111468256404, -0.9043555095277017, -0.9107962218644101, -0.9092926235899095, -0.8992442147050943, -0.8803012985533494, -0.8523688368748709, -0.8156034823487754, -0.7704039291563534, -0.7173948928697323, -0.6574051932135494, -0.5914405628898748, -0.5206519389475069, -0.4463001067801332, -0.36971765791733247, -0.2922692890607606, -0.21531150967353693, -0.1401528378790477, -0.06801554918177338, -6.114033491549012e-16], [0.0, 0.06120347070194756, 0.1162929225949672, 0.1648186325228528, 0.20655949966411274, 0.24153016179030923, 0.2699814890904767, 0.292394425211759, 0.3094673190726178, 0.3220970614561955, 0.33135450305785286, 0.3384547814059569, 0.34472331905893916, 0.3515583712581879, 0.36039109481909865, 0.37264417905984554, 0.3896901222029562, 0.4128102518032788, 0.4431555749122357, 0.4817105031390125, 0.5292604304673294, 0.5863640492576344, 0.6533311745680827, 0.7302067116002803, 0.816761249061502, 0.912488596302675, 1.0166104083404204, 1.128087864630858, 1.2456401891829423, 1.3677696257411585, 1.4927923166921038, 1.6188743822085885, 1.7440723607770952, 1.866377057089983, 1.983759751257735, 2.094219656775966, 2.1958314754052966, 2.286791886156236, 2.3654638232824987, 2.430417444231578, 2.4804667618353435, 2.5147010139226986, 2.532509965641959, 2.533602482155214, 2.5180178685667083, 2.4861296461064497, 2.438641614516131, 2.376576235860586, 2.3012555600830242, 2.214275093001759, 2.1174711786841303, 2.0128826260223245, 1.9027074499898178, 1.7892557180091042, 1.6748995881470579, 1.5620216960881002, 1.4529630902671964, 1.3499719281053482, 1.2551541306167515, 1.170427148102783, 1.0974779172741258, 1.0377259916924053, 0.9922927052779145, 0.9619770857542633, 0.9472390747642745, 0.948190437888085, 0.9645935651443849, 0.9958681752024663, 1.0411057490333726, 1.0990913356417007, 1.1683321982935777, 1.2470926085196223, 1.333433951028555, 1.4252591790026932, 1.5203605590404754, 1.616469570664939, 1.7113077785958777, 1.802637477971543, 1.8883109237836075, 1.966316995619924, 2.0348242163541004, 2.0922191369578576, 2.13713921678651, 2.168499466566603, 2.1855122764605426, 2.1877000201412042, 2.1749002036012097, 2.147263110050246, 2.105242075211668, 2.0495767061113477, 1.981269526664301, 1.901556690836943, 1.811873545048187, 1.7138159423437276, 1.6090983088107664, 1.4995095353472596, 1.3868678135443595, 1.2729755520424275, 1.159575498937526, 1.048309157011427, 0.9406785127953554, 0.838012009485842, 0.741435579866168, 0.6518494215693965, 0.569911046662036, 0.4960249744501207, 0.43033926474143885, 0.3727489128752397, 0.322905952089486, 0.28023593765798877, 0.24396032499582668, 0.21312410467106915, 0.18662792471216044, 0.16326381807693008, 0.1417535634569743, 0.12078864295914933, 0.09907072223053465, 0.07535156819879693, 0.048471337016064535, 0.017394209550566687, -0.018759577292287256, -0.060686159836393506, -0.10887567667140303, -0.16359570045599578, -0.22488092380803848, -0.2925293872836226, -0.3661053666313944, -0.444948862529373, -0.5281914632837754, -0.6147781838789462, -0.7034947275610818, -0.792999472816529, -0.8818593628226966, -0.9685887694224993, -1.0516903220991682, -1.129696636418114, -1.2012118474264977, -1.2649518523521972, -1.3197821937166203, -1.3647525680636563, -1.3991270256167783, -1.422409030359345, -1.4343606757335328, -1.4350154952712644, -1.4246844664383183, -1.403954975844263, -1.3736826905183568, -1.3349764587720074, -1.2891765407916957, -1.2378266391080397, -1.1826403581970524, -1.1254628666810196, -1.0682286612628547, -1.012916435456618, -0.9615021357086698, -0.915911340579359, -0.8779721238670313, -0.8493695591857597, -0.8316029915432974, -0.825947141602961, -0.8334180219409579, -0.8547445337764124, -0.8903464800112822, -0.9403195791719776, -1.0044278986597757, -1.082103948634785, -1.1724564941962423, -1.2742859577677252, -1.3861071002969643, -1.5061784935297962, -1.6325381305469744, -1.763044372020153, -1.8954212949373046, -2.027307402094149, -2.156306567129229, -2.2800400333715944, -2.3961982566844755, -2.502591383545141, -2.5971971858045326, -2.6782053322110633, -2.7440569624548923, -2.793478640122645, -2.8255098938678582, -2.8395237080716673, -2.835239491598667, -2.81272823187432, -2.772409727078032, -2.7150419772455034, -2.6417030009334987, -2.553765523302136, -2.452865149662798, -2.340862791644401, -2.2198022474413355, -2.0918639498805467, -1.9593159835834446, -1.8244635332121577, -1.6895979572487687, -1.5569466852267166, -1.428625110793619, -1.3065915991244965, -1.192606646408767, -1.0881971234469183, -0.9946264074674734, -0.9128710593052671, -0.8436045407263643, -0.7871882929723207, -0.7436703168279142, -0.7127912111579736, -0.693997445430958, -0.6864614667129061, -0.6891080772700311, -0.7006463692833328, -0.7196063719022209, -0.7443794561317282, -0.7732614575033676, -0.8044974171616429, -0.8363268102886781, -0.8670281273823498, -0.8949616987871462, -0.9186097053360117, -0.936612396596026, -0.9477996409707246, -0.9512170561514762, -0.9461461109520092, -0.9321177467768152, -0.908919234878937, -0.8765941599089955, -0.8354355966457746, -0.7859727207861756, -0.7289512618841721, -0.6653083627660906, -0.5961425510971023, -0.5226796516944165, -0.44623556960682564, -0.3681769513827293, -0.2898807834110207, -0.21269401047665493, -0.137894254146841, -0.06665267941550491, -5.967853287909973e-16], [0.0, 0.05933748657657987, 0.11232997621343613, 0.1586425793477552, 0.19817438564987142, 0.23106192658269287, 0.25767595320446324, 0.2786115987134404, 0.2946721683452041, 0.3068469663457403, 0.3162837266086895, 0.324256356191014, 0.33212882567102453, 0.3413161439962478, 0.3532434354230707, 0.3693041903066077, 0.3908187884354288, 0.4189943925817963, 0.4548872809158403, 0.49936863057694647, 0.5530946823603512, 0.6164821101687366, 0.6896892912096598, 0.7726040270425937, 0.8648381051090845, 0.9657289193037191, 1.074348190723387, 1.1895176503967155, 1.3098313690307202, 1.433684249049775, 1.5593060357100221, 1.6848000608461176, 1.808185808471204, 1.9274442891678676, 2.0405651325984757, 2.145594256541829, 2.24068094798471, 2.3241231976244285, 2.394410163623842, 2.4502607028453185, 2.4906569966238843, 2.5148724113138714, 2.522492868642813, 2.5134311540763203, 2.48793375922299, 2.44658003270512, 2.3902735985364405, 2.3202261873686725, 2.237934209430566, 2.1451485740853693, 2.043838425348027, 1.936149611385708, 1.8243588353085742, 1.7108245412486303, 1.5979356711791302, 1.488059482119009, 1.383489638935367, 1.2863957942426771, 1.19877583395749, 1.1224119056758446, 1.058831258668174, 1.0092728110666092, 0.9746602244933381, 0.9555821122308702, 0.952279837810218, 0.9646431807058492, 0.9922139590589375, 1.0341975105455423, 1.089481746254691, 1.1566633132695876, 1.2340802339036663, 1.3198502373003211, 1.411913866045711, 1.5080813297805697, 1.6060819921895888, 1.703615319238969, 1.798402086501131, 1.8882346425260148, 1.9710250534523817, 2.0448500106445, 2.107991466641636, 2.1589720730106943, 2.196584624082898, 2.219914859781106, 2.2283571450952193, 2.221622719164814, 2.199740389040986, 2.163049727528349, 2.1121870165118852, 2.0480643523786406, 1.9718424942547124, 1.8848981847816304, 1.7887868034233319, 1.6852013206682175, 1.5759286053620107, 1.4628041947823243, 1.3476666666118922, 1.2323127530464697, 1.1184543099554094, 1.007678199074497, 0.9014100601139274, 0.800882844519354, 0.7071108561364465, 0.6208698994305779, 0.5426839768805558, 0.472818807728881, 0.4112822647131667, 0.3578316481512052, 0.3119875422676579, 0.2730538313174667, 0.24014329707792081, 0.21220807855422705, 0.18807415279022557, 0.16647889553820466, 0.1461107047090581, 0.1256496198721653, 0.10380784881884614, 0.07936911786919816, 0.05122579601183064, 0.018412803243403407, -0.019862600931990562, -0.06419594416334509, -0.11496624931620443, -0.1723228440314362, -0.23617863235953448, -0.30621002022623584, -0.3818635126327291, -0.4623688260253765, -0.5467581886149375, -0.6338913389190965, -0.7224855825776948, -0.8111501333737126, -0.8984238498090971, -0.9828153864686412, -1.0628447121305649, -1.137084905900637, -1.2042031296419415, -1.2629996900351876, -1.3124441464201966, -1.3517074901257082, -1.3801895156068307, -1.3975406210604042, -1.4036774133868923, -1.3987916460189294, -1.3833521844280625, -1.3580998689154393, -1.3240353232303097, -1.2823999361710872, -1.234650417133733, -1.1824274912186945, -1.1275194508457622, -1.0718214150341046, -1.0172912611780958, -0.9659032843874719, -0.9196007039379701, -0.8802481734059469, -0.8495854596250663, -0.8291834353968931, -0.8204034823139705, -0.8243613242218204, -0.8418962105402485, -0.8735462443034943, -0.9195305053571322, -0.9797384581630468, -1.0537269600238008, -1.1407250034756695, -1.2396461405624934, -1.3491083512427477, -1.467460937846778, -1.5928178567172593, -1.7230967411337184, -1.8560627302092907, -1.9893761000949606, -2.1206425994615654, -2.247465323194348, -2.367496918228897, -2.4784909044930235, -2.578350912299387, -2.6651766848412346, -2.7373057695526772, -2.793349923198177, -2.8322253802080413, -2.8531762789561332, -2.8557907028565754, -2.840008968396693, -2.8061239762618784, -2.754773630068566, -2.6869255153230895, -2.60385421449424, -2.5071118080732817, -2.3984922719752553, -2.27999062472031, -2.153757800064899, -2.0220523191844255, -1.8871899087817925, -1.751492255896183, -1.617236105682622, -1.4866038947066078, -1.3616370697475622, -1.2441931718352435, -1.1359076690389895, -1.0381614018086254, -0.9520543644217809, -0.8783863888158325, -0.8176451266788132, -0.7700015463623926, -0.7353129773924659, -0.7131335516212017, -0.7027317109098173, -0.7031142810526174, -0.7130564546165143, -0.7311368853093962, -0.7557769768091547, -0.7852833525745929, -0.8178924223278384, -0.8518159173142917, -0.8852862510983645, -0.9166005758265241, -0.9441624451585734, -0.9665200633103735, -0.9824001930751248, -0.9907369118796211, -0.9906945409095723, -0.9816842246381535, -0.9633738028488892, -0.9356907902885226, -0.8988184560490068, -0.8531851712019481, -0.7994473646567082, -0.7384665893806959, -0.671281349941942, -0.5990744740863202, -0.5231369224548686, -0.4448290188061494, -0.3655401460451612, -0.2866479894235742, -0.20947841659273925, -0.13526706458703888, -0.0651236568193224, -5.808141763773391e-16], [0.0, 0.05736744614557171, 0.1082119612821843, 0.1523170313423562, 0.18970348642891552, 0.22062925037096734, 0.24558240085144004, 0.26526770965157204, 0.2805870033634145, 0.29261384721444894, 0.30256320430118805, 0.3117568557292656, 0.3215854805053922, 0.33346838461786776, 0.3488119342431662, 0.36896778672124136, 0.39519202381847884, 0.42860627450981176, 0.47016186943311616, 0.5206079973710784, 0.580464737342507, 0.6500017205106471, 0.7292230370857323, 0.8178588481564714, 0.9153639947868372, 1.0209237209341764, 1.1334664471691411, 1.2516833532986242, 1.3740543542930392, 1.498879889763135, 1.624317796754555, 1.7484244026344926, 1.869198862710934, 1.984629678816547, 2.092742272687774, 2.1916464532157574, 2.2795826104965657, 2.3549654923135717, 2.4164244697792046, 2.4628392771766063, 2.4933703147272097, 2.5074827295893876, 2.5049636368160377, 2.4859320047186495, 2.450840904145735, 2.4004720043159504, 2.3359223845749733, 2.2585839171977318, 2.17011565657716, 2.0724098403994273, 1.967552264513107, 1.8577779313078753, 1.7454229881148289, 1.6328740645356274, 1.5225161834033645, 1.416680457627807, 1.3175927935248217, 1.2273248001338584, 1.1477480539687264, 1.0804927908164312, 1.0269119924679548, 0.9880517091411705, 0.9646283109196265, 0.9570131973613665, 0.9652253175178465, 0.9889316672457912, 1.0274557414018644, 1.079793729884251, 1.1446380631116593, 1.2204077388636096, 1.305284702660314, 1.3972554119073155, 1.4941565933010137, 1.593724106395957, 1.6936437560882884, 1.7916028547363776, 1.8853413216931583, 1.9727011244228467, 2.051672910657261, 2.1204387540425125, 2.1774100345884286, 2.2212595974785554, 2.250947476377281, 2.265739626736477, 2.265219286804242, 2.249290764812754, 2.2181756357066984, 2.1724015152131364, 2.112783758512364, 2.0404006008452042, 1.9565624139238644, 1.8627758911840673, 1.760704093346432, 1.6521233805872113, 1.5388783265853245, 1.4228357511942327, 1.3058390215482132, 1.1896637558266807, 1.0759760201523778, 0.9662940383744023, 0.861954338638635, 0.7640831421509405, 0.6735736614272081, 0.591069821115398, 0.5169567480799597, 0.45135820306623975, 0.39414094831077534, 0.3449258684127794, 0.3031054900823385, 0.26786738433912183, 0.2382227864102111, 0.21303963767474263, 0.19107914379142055, 0.17103485636372315, 0.15157322429559092, 0.1313745268710768, 0.10917309437580973, 0.08379574388434524, 0.054197407078702, 0.01949300236249427, -0.02101529684281611, -0.06781612443177505, -0.12117290149995509, -0.1811141657766376, -0.24743051657879664, -0.3196782683535741, -0.3971897304749871, -0.47908985751691285, -0.5643188471434718, -0.651660106286532, -0.7397728644006585, -0.8272285889158066, -0.9125502557097478, -0.994253449122761, -1.0708882137623463, -1.1410805554694163, -1.2035724920256023, -1.2572595854551742, -1.3012249463904064, -1.3347687855136758, -1.3574326954978075, -1.3690179764701202, -1.3695974656208196, -1.359520493501548, -1.3394107617871702, -1.3101571155098357, -1.2728973625657245, -1.228995470140675, -1.1800126371629927, -1.1276728997075205, -1.0738240684618872, -1.0203949203223113, -0.9693496667812745, -0.9226407974212777, -0.8821614455703594, -0.8496984437031234, -0.826887227879941, -0.815169713515228, -0.8157561998730745, -0.8295922694182467, -0.8573315326718741, -0.8993149323067442, -0.9555571651755425, -1.0257406115597287, -1.1092169812820072, -1.2050167008273915, -1.3118658788048716, -1.4282105035321064, -1.5522473507462393, -1.6819609157567075, -1.8151655367930923, -1.9495517485038583, -2.082735799691032, -2.212311190023821, -2.3359010286385176, -2.451209994509591, -2.5560746848669202, -2.6485111736173623, -2.7267586658664253, -2.7893182256923996, -2.8349856701043037, -2.86287785981402, -2.8724517737322195, -2.8635159251607885, -2.8362338593442127, -2.7911196599402994, -2.729025581507836, -2.6511221116768553, -2.558870945732629, -2.453991523558933, -2.3384219301951648, -2.214275093001763, -2.083791317419504, -1.9492882869300283, -1.8131097090808899, -1.6775738170069563, -1.5449229341420514, -1.4172752788727412, -1.2965801265584136, -1.184577360142125, -1.0827623296767894, -0.9923568082652497, -0.9142866804708748, -0.8491668329571324, -0.7972935400802179, -0.7586444537638128, -0.7328861217530376, -0.7193887758351263, -0.7172479563099655, -0.7253123751897008, -0.7422172723042071, -0.766422389297866, -0.7962535795507597, -0.8299469899144784, -0.8656946947685907, -0.9016906355603883, -0.9361757202696094, -0.9674809670122274, -0.9940676334251275, -1.0145633570323283, -1.0277934393128363, -1.0328065349061264, -1.0288941540184824, -1.0156035469054794, -0.9927437102305094, -0.9603844318195666, -0.9188484683946846, -0.8686971257939036, -0.8107096785819783, -0.7458572216275692, -0.6752716862737933, -0.6002108746626742, -0.5220204645778412, -0.4420940113909769, -0.36183202150431315, -0.2826011919081815, -0.20569490264796825, -0.1322960133541784, -0.06344295246763862, -5.636419149508749e-16], [0.0, 0.05531225383177577, 0.10397869763732347, 0.14590368647568489, 0.18123024707205315, 0.21033608829665051, 0.23382297566984217, 0.2524997387780711, 0.26735934748171697, 0.2795506488215669, 0.29034549761442335, 0.3011021362734098, 0.3132257802616842, 0.32812744219935824, 0.3471820780103343, 0.3716871612945874, 0.4028227867101339, 0.4416143696237754, 0.4888989484240168, 0.5452960091547773, 0.6111836416481264, 0.6866807048314345, 0.771635529614405, 0.8656215244314441, 0.9679398751910492, 1.077629352391286, 1.1934830579744775, 1.3140717676299598, 1.437773355152714, 1.562807628385535, 1.6872757651802337, 1.8092034162866333, 1.9265864432148632, 2.037438185457801, 2.139837104925927, 2.231973637286584, 2.3121950906613176, 2.3790474716501695, 2.431313186038192, 2.468043655222234, 2.488586007145576, 2.4926031395143293, 2.480086609931503, 2.451361978512398, 2.40708640937371, 2.3482385237008856, 2.2761006843329734, 2.1922340753692495, 2.0984471156874296, 1.9967579081533673, 1.8893515726808847, 1.7785334375524535, 1.6666791664100604, 1.5561829755119574, 1.4494051452957188, 1.348620050741447, 1.2559659259502414, 1.1733975399257095, 1.1026428936729866, 1.0451649550110942, 1.0021293291893234, 0.9743786233695954, 0.96241410467917, 0.9663850786973914, 0.9860862321160323, 1.0209629943575713, 1.0701247827435807, 1.13236580900022, 1.2061929460086886, 1.2898599870991894, 1.3814074798875204, 1.4787071863031447, 1.579510113203148, 1.6814969763871415, 1.7823299068709488, 1.8797041832099137, 1.9713987780447186, 2.0553245407083662, 2.1295688998009688, 2.192436058529203, 2.2424817690865653, 2.27854190758253, 2.299754224649389, 2.3055728150535053, 2.295775028250272, 2.270460726438539, 2.230043982740128, 2.1752374950770674, 2.1070301666529567, 2.026658467373301, 1.9355723380734873, 1.835396527475195, 1.727888357265007, 1.6148929910516787, 1.4982973363070797, 1.3799837335013732, 1.261784582979071, 1.1454390278795525, 1.0325527514824275, 0.9245618613407987, 0.8227017226856934, 0.7279814726634676, 0.6411647983446485, 0.5627573988908184, 0.4930013798996171, 0.4318766501171322, 0.37910921189028784, 0.3341860614237141, 0.2963762475047816, 0.2647574820593509, 0.23824755658192007, 0.21563969862254817, 0.19564090509112111, 0.17691221657164127, 0.15810985091211982, 0.13792609618460103, 0.11512887311108287, 0.08859891493168477, 0.0573635774573489, 0.02062638203050617, -0.022208492990437072, -0.07151742368291165, -0.1274447568362154, -0.18989677052102377, -0.2585423472816913, -0.3328203527642822, -0.4119535371560676, -0.4949686059090947, -0.5807219441936206, -0.6679303304973216, -0.7552058425493486, -0.8410940466799286, -0.9241144726971654, -1.0028023126663392, -1.0757502452714718, -1.1416492787055783, -1.1993275245534447, -1.247785862468074, -1.28622952946826, -1.3140947665969662, -1.3310697770476019, -1.3371093906892384, -1.3324429867102712, -1.3175753949543199, -1.293280673233343, -1.2605888380573194, -1.2207658053077555, -1.1752869709118494, -1.1258050251815879, -1.0741127440426121, -1.0221016321068654, -0.9717174030927169, -0.92491336963795, -0.8836028748472861, -0.8496119303770806, -0.8246332295836538, -0.810182679057909, -0.807559538264594, -0.8178111762317504, -0.8417033482027703, -0.8796967664075596, -0.9319305907356008, -0.9982133006988324, -1.0780212336559507, -1.1705048901362476, -1.2745029197537143, -1.3885635152316609, -1.5109727620292026, -1.639789321401054, -1.7728846696091085, -1.9079879792664316, -2.0427346138127747, -2.174717115747151, -2.3015375057289176, -2.4208596745978106, -2.530460644654798, -2.6282795003674435, -2.7124628414720044, -2.781405691983539, -2.833786904959725, -2.868598232424835, -2.885166379508883, -2.8831675279622426, -2.8626339927325, -2.8239528618989347, -2.7678566604133605, -2.6954062671709984, -2.607966498335725, -2.5071749431157553, -2.3949047971229582, -2.2732225792011054, -2.144341736770839, -2.0105732394411784, -1.8742743286085901, -1.7377966303918422, -1.6034348496193367, -1.4733772434965489, -1.3496590255606147, -1.234119774811362, -1.1283658234057907, -1.0337384715590494, -0.9512887334184251, -0.8817591562680501, -0.8255730814789732, -0.7828315334428184, -0.7533177368117507, -0.7365090772905014, -0.7315961415350307, -0.737508301811976, -0.7529451551169506, -0.7764129882376615, -0.8062653231325364, -0.8407465037999151, -0.8780372187611846, -0.916300813944471, -0.9537292400144283, -0.9885874962159346, -1.0192554790393458, -1.0442662172255617, -1.0623395728953777, -1.0724106093757648, -1.073651966515049, -1.0654897403625379, -1.0476125320791507, -1.0199735065990778, -0.9827854804501739, -0.9365092357619155, -0.8818354293841002, -0.8196606278977471, -0.751058147072102, -0.6772445043174345, -0.5995424016639793, -0.5193412420563512, -0.4380562411826668, -0.35708722920301006, -0.2777782408348029, -0.20137896823098417, -0.129009099596472, -0.061626488865485725, -5.454322126788771e-16], [0.0, 0.053191662542790466, 0.0996711972958141, 0.13946524333197263, 0.17283837484229878, 0.2002853801639731, 0.22251701634698465, 0.24043960587036392, 0.25512900382722326, 0.2677996122544059, 0.27976924950894216, 0.29242079334033594, 0.30716160373860574, 0.3253817935012099, 0.34841244914699687, 0.3774849113837716, 0.4136922025855359, 0.4579536391455731, 0.5109835903324623, 0.5732652442493674, 0.645030118169605, 0.7262439079446491, 0.8165991128937815, 0.9155147025275626, 1.022142913872587, 1.1353830874922268, 1.2539022710630794, 1.3761621460693485, 1.5004516701781514, 1.6249246792712908, 1.7476415626961646, 1.8666140163785687, 1.9798517938033784, 2.0854103167077804, 2.181437977184144, 2.2662219616017216, 2.3382314544586262, 2.3961571363796423, 2.4389459736869967, 2.465830405321322, 2.4763511637828364, 2.4703731170389247, 2.4480936843584065, 2.410043556743099, 2.3570796376948957, 2.2903703079525735, 2.2113733039497623, 2.1218066795118524, 2.0236134893017645, 1.9189209865766006, 1.8099952631242437, 1.699192372461398, 1.588907065680378, 1.4815203305280005, 1.37934695684479, 1.284584354547509, 1.1992638237852897, 1.1252054213485507, 1.063977484180533, 1.0168617619331155, 0.9848249785510937, 0.9684974910581519, 0.9681595457356742, 0.9837354518125492, 1.0147958049961838, 1.0605677022375013, 1.1199526996776972, 1.1915520823765415, 1.2736988416246466, 1.3644955975894402, 1.4618575655662827, 1.5635595465761267, 1.6672858303015161, 1.770681832607694, 1.8714062527144908, 1.9671825273255275, 2.055848380820102, 2.135402321379736, 2.204046011357783, 2.2602215443287013, 2.3026427884709157, 2.330320103075144, 2.342577898378047, 2.33906468455397, 2.3197554392168436, 2.284946309666576, 2.235241851761109, 2.1715351871492174, 2.0949816302542157, 2.006966491711061, 1.909067902147598, 1.8030156159405166, 1.6906468460813064, 1.5738602463768534, 1.4545691943622163, 1.3346555366950934, 1.215924938322581, 1.1000649279694368, 0.9886066568013613, 0.8828912864430766, 0.7840417994724589, 0.6929408832134335, 0.6102153797299574, 0.5362276253804182, 0.47107382640790735, 0.4145894372731949, 0.3663613303032696, 0.3257463731988511, 0.29189586932855016, 0.26378516857554757, 0.24024762746647707, 0.22001198961259305, 0.2017421738011414, 0.18407839945454169, 0.1656785490332565, 0.14525866500956977, 0.12163150528886442, 0.09374213469789096, 0.06069961000046848, 0.02180391978854293, -0.023432534125096702, -0.07526948370979172, -0.1337297819890671, -0.19859707389925563, -0.2694202192451044, -0.3455243596427527, -0.4260283473918554, -0.509868087359777, -0.5958251874329739, -0.6825601728516583, -0.7686493983690151, -0.852624692767979, -0.9330146953791815, -1.0083867958104018, -1.0773885673940018, -1.1387875924619815, -1.1915086133341883, -1.2346670060116458, -1.267597662473274, -1.2898784799993819, -1.3013477893116359, -1.3021152042211446, -1.2925655401624825, -1.273355623357995, -1.2454039920488384, -1.209873671750362, -1.1681483833124633, -1.1218027112466895, -1.0725669160701912, -1.0222872143620987, -0.9728824702784016, -0.9262983393632418, -0.8844599771284383, -0.8492244691778804, -0.8223341554331172, -0.8053720077812613, -0.7997201784455399, -0.8065227665168647, -0.8266537540179943, -0.8606909428897558, -0.9088965832778191, -0.9712052248714179, -1.0472191506576993, -1.1362115705104612, -1.2371375649772232, -1.348652582046428, -1.4691381061708466, -1.5967339439052644, -1.7293764084949697, -1.86484154062339, -2.0007923778814836, -2.1348291844483045, -2.264541477486846, -2.3875606397404256, -2.5016118899554742, -2.6045643945376793, -2.6944783450220413, -2.769647895537108, -2.828638950803803, -2.87032091600882, -2.8938916622095188, -2.898895121311995, -2.885231099223468, -2.853157080272843, -2.803281985935037, -2.73655204166732, -2.6542290926321197, -2.55786188769714, -2.4492510170335637, -2.3304083378515195, -2.2035118517069714, -2.0708571022721274, -1.934806241947268, -1.7977359673077857, -1.661985545913143, -1.529806149957372, -1.4033126758400638, -1.2844391639303836, -1.1748988412275516, -1.0761496935868313, -0.9893663365752722, -0.9154187982656098, -0.8548586572310545, -0.807912798871709, -0.7744848674305443, -0.7541643042181914, -0.7462426792533562, -0.749736848235005, -0.7634183037818213, -0.7858479431787432, -0.8154153480232278, -0.8503815672304681, -0.8889243163280075, -0.9291844547024293, -0.9693125796302311, -1.0075145820005977, -1.0420950433686613, -1.07149741640329, -1.0943400192657209, -1.1094469866821934, -1.1158734535776307, -1.1129243977254868, -1.1001667321212658, -1.07743441154964, -1.0448264967053689, -1.0026982987444923, -0.9516459027755497, -0.8924845361478718, -0.8262214022672819, -0.7540237392011391, -0.6771829810721113, -0.5970759962335516, -0.5151244470938618, -0.432753360471617, -0.3513500134537662, -0.2722242275352027, -0.1965711236900657, -0.12543732401688423, -0.05969149344006156, -5.263588573108712e-16], [0.0, 0.051026086179067516, 0.09533127189854657, 0.13306479622958847, 0.1646110254126837, 0.19057804190484726, 0.21177987792037148, 0.2292128552935833, 0.24402664847096792, 0.2574908267859053, 0.27095775233022495, 0.2858228076418679, 0.30348300056422406, 0.3252950401087145, 0.35253399574559297, 0.38635364273673106, 0.42774955810025805, 0.4775259664619601, 0.5362672439917975, 0.6043148740838916, 0.6817505132464556, 0.7683856731791415, 0.8637583590238547, 0.9671368284216467, 1.0775304556757017, 1.1937075045252343, 1.3142194363145259, 1.4374312121405517, 1.5615568921232421, 1.6846996961970115, 1.8048955722952638, 1.9201592225197237, 2.0285314683096862, 2.128126793574673, 2.217179891368554, 2.2940900553955252, 2.3574623021576975, 2.406144181874416, 2.43925733472685, 2.456222971159084, 2.4567805979569566, 2.4409994721645796, 2.409282438686061, 2.3623619904160105, 2.301288577470811, 2.2274113799513255, 2.1423519420430264, 2.047971239639577, 1.946330914762469, 1.8396495538642894, 1.7302550100866372, 1.620533868643028, 1.512879227241468, 1.4096380080250153, 1.3130590327541092, 1.2252430784637787, 1.1480960869119368, 1.0832866288242406, 1.0322086249654443, 0.995950202810438, 0.9752694230301464, 0.9705774476514668, 0.9819295455363903, 1.0090241450343012, 1.0512099528085428, 1.1075009665635411, 1.1765990223515688, 1.256923338863982, 1.346646355939108, 1.4437350164549472, 1.5459965134040417, 1.6511274203475212, 1.7567650461065718, 1.860539805319344, 1.9601273765253742, 2.053299429175332, 2.137971740110631, 2.21224858760219, 2.274462405274335, 2.323207796806952, 2.357369152254322, 2.3761412646672646, 2.379042517548892, 2.365920395267851, 2.336949255418988, 2.2926204896617284, 2.2337253831748654, 2.16133115804362, 2.0767508483583814, 1.9815078005955176, 1.8772957184302237, 1.7659352734684484, 1.6493283800299463, 1.5294112812596465, 1.4081076143669806, 1.2872826142828095, 1.1686995777912876, 1.0539796452635835, 0.9445658662006339, 0.8416924002350695, 0.746359569982981, 0.6593153296179092, 0.5810435471294387, 0.5117593231189699, 0.45141138908922607, 0.39969144802567175, 0.3560501441687675, 0.31971918164212904, 0.28973895721479337, 0.2649909347878676, 0.24423387163423915, 0.22614291190170194, 0.20935049374923323, 0.19248797441726082, 0.17422686354736447, 0.15331856946968606, 0.12863160555817124, 0.0991852730018447, 0.06417893066701491, 0.02301607971290704, -0.02467737271498437, -0.0790411535341354, -0.13997528517559277, -0.20714151282320967, -0.2799714648476173, -0.357681337643862, -0.439292725142831, -0.5236590519293348, -0.6094969212667695, -0.6954215591590382, -0.7799854261969623, -0.8617189831392702, -0.9391725361767743, -1.0109580551843538, -1.0757898538536932, -1.132523044586271, -1.180188732862166, -1.2180249942366685, -1.2455027802336454, -1.2623460246593114, -1.2685453661498483, -1.264365062505162, -1.2503428435691009, -1.2272826278187936, -1.1962402089585558, -1.158502198136312, -1.1155586804070257, -1.0690702064016777, -1.0208298877213906, -0.9727214936246272, -0.9266745538237247, -0.8846175549045782, -0.848430373884161, -0.8198971202384796, -0.8006605565796037, -0.7921792379638544, -0.7956884512242041, -0.8121659500947266, -0.8423033712628454, -0.886484083499776, -0.9447680698936266, -1.0168842756360663, -1.1022306748750668, -1.1998821242148054, -1.3086058820723019, -1.4268844869111343, -1.5529455079426497, -1.684797513632636, -1.8202714504284017, -1.9570664903074353, -2.0927992943615012, -2.2250555534392533, -2.351442608031135, -2.469641919579183, -2.5774601650107023, -2.6728777555839605, -2.7540936394220474, -2.819565333013214, -2.8680432384098467, -2.8985984371735842, -2.910643306039312, -2.903944469072818, -2.8786277826527384, -2.835175238505179, -2.7744138616673553, -2.697496869995911, -2.6058775450543314, -2.5012764364615547, -2.3856426788799054, -2.2611103389568474, -2.129950825371376, -1.9945224858784372, -1.8572185787187425, -1.7204148404605064, -1.5864178774643158, -1.4574155836405671, -1.3354307336530127, -1.2222788195766658, -1.119531092283578, -1.0284836391709318, -0.9501331804865887, -0.8851601011497288, -0.8339190576990435, -0.7964373152018256, -0.77242078117691, -0.7612675174390625, -0.7620883308289734, -0.7737338744558554, -0.7948275364823246, -0.8238032573841555, -0.858947302315676, -0.8984429254539172, -0.9404168001162286, -0.9829860535166688, -1.0243047390145428, -1.0626086016642573, -1.0962570441289845, -1.1237712782013956, -1.1438677502457029, -1.1554860541844356, -1.157810690002012, -1.1502861854576354, -1.13262526975104, -1.1048099659490234, -1.067085649576329, -1.0199482993643543, -0.9641253382572832, -0.9005506240904615, -0.8303342958506025, -0.7547283094509522, -0.6750886033244877, -0.592834916220907, -0.5094093353681428, -0.42623468126911396, -0.3446738351893193, -0.26599108690323436, -0.19131652427044338, -0.12161440416111167, -0.05765633825407502, -5.066041218302564e-16], [0.0, 0.04883640464639346, 0.09100113029620994, 0.1267652235064782, 0.1566299907203431, 0.1813119724631828, 0.20172178727088247, 0.21893739900955825, 0.2341725081060094, 0.24874089627461113, 0.2640176623062399, 0.2813983706141156, 0.3022571923445965, 0.32790514944556454, 0.3595495743201091, 0.39825587147028196, 0.44491261346206784, 0.5002009229268944, 0.5645689871345669, 0.6382124245252689, 0.7210610766279408, 0.8127726376502432, 0.9127333617201436, 1.020065908597072, 1.1336442071377826, 1.2521150364532914, 1.3739258520378046, 1.4973582225401572, 1.6205660963677093, 1.7416179896782704, 1.8585420817814637, 1.969373123247627, 2.0722000082082235, 2.1652128368603467, 2.246748297790536, 2.315332232420521, 2.369718304937488, 2.40892178908638, 2.432247596081962, 2.4393118029334797, 2.4300560943996414, 2.404754700866722, 2.3640135945456286, 2.308761893111475, 2.2402356086858926, 2.1599540662524768, 2.0696894946192077, 1.971430460486173, 1.8673399679076608, 1.7597091776999485, 1.6509078108575894, 1.5433323840744277, 1.4393534819151275, 1.3412632976184191, 1.2512246722138218, 1.1712228296084417, 1.1030209442870211, 1.0481205897162196, 1.007728001578576, 0.9827269533325868, 0.9736588856093086, 0.9807107593954942, 1.0037109199832701, 1.0421330687326817, 1.0951082474125216, 1.161444549931101, 1.239654093258887, 1.3279866077253613, 1.4244688508084715, 1.5269489118105408, 1.6331443607362297, 1.74069310600817, 1.8472057645001883, 1.950318315188174, 2.0477438052537953, 2.1373219047368845, 2.217065162100572, 2.285200896919495, 2.3402077752236474, 2.3808462451015453, 2.4061821617080152, 2.415603098079981, 2.4088270170062414, 2.3859031652139415, 2.3472052397467187, 2.293417062984088, 2.225511182714144, 2.1447209826206324, 2.05250704235984, 1.9505186213443626, 1.8405512531554673, 1.724501525463869, 1.6043201813614023, 1.4819647106759535, 1.3593526034470704, 1.2383164122909252, 1.1205617166112687, 1.007629000951348, 0.9008603543276983, 0.8013717698501447, 0.7100316775663917, 0.6274461819888602, 0.5539513032499465, 0.4896123416391501, 0.43423030390949263, 0.3873551507541107, 0.3483054527311461, 0.3161938809601032, 0.28995781314254493, 0.2683942085033403, 0.2501978002574374, 0.23400157377695208, 0.2184184447397819, 0.20208302549049456, 0.18369237024231802, 0.1620446204853348, 0.13607453021791993, 0.10488493487197019, 0.06777333589075996, 0.02425290207601944, -0.02593266424596567, -0.08280078722070748, -0.14612842369389004, -0.21545725922773193, -0.2901055598283572, -0.36918637106538366, -0.45163158983973267, -0.5362212796768528, -0.6216174620178974, -0.7064014970779339, -0.7891140714763454, -0.8682967384925135, -0.9425339123046647, -1.0104942011018063, -1.070969975984098, -1.1229141128359088, -1.1654729119071006, -1.1980142930238324, -1.220150480875524, -1.2317545318047516, -1.232970207558869, -1.2242148687088792, -1.2061752367272294, -1.17979605463185, -1.1462618571141026, -1.1069722376273783, -1.063511167576186, -1.0176110772815712, -0.9711125458942829, -0.9259205643865814, -0.883958429184843, -0.8471203914962205, -0.817224227161956, -0.7959649028515554, -0.7848704962236299, -0.7852614806724865, -0.7982144105225281, -0.8245309417843053, -0.864712999253873, -0.9189447558180064, -0.9870819278349517, -1.0686487153367346, -1.1628425318206, -1.2685464800674489, -1.3843493423637194, -1.5085726703325004, -1.6393043858099745, -1.7744381441207997, -1.9117175686687864, -2.0487843444956195, -2.183229061385369, -2.312643626629822, -2.434674025492891, -2.5470721948007213, -2.6477457922938594, -2.734804691035563, -2.806603103178396, -2.861776338957038, -2.8992713324537323, -2.918370212436308, -2.9187063608418184, -2.9002725792855704, -2.863421170997084, -2.808855937276099, -2.7376162792633165, -2.651053782872273, -2.55080184258507, -2.438739044156299, -2.316947173110111, -2.187664841697752, -2.0532378286694946, -1.9160673013579648, -1.7785571363761303, -1.643061572603736, -1.5118344176939829, -1.386980987434337, -1.2704138870168982, -1.1638136463871351, -1.0685951007668864, -0.9858802652003071, -0.9164782920774566, -0.8608729270038732, -0.8192176953915667, -0.7913388642545154, -0.7767460355209467, -0.7746500433433057, -0.7839876528966924, -0.8034523962820497, -0.8315307363334533, -0.8665426248813337, -0.9066854213414312, -0.9500800627894505, -0.9948183297021036, -1.0390100333643717, -1.0808289619117617, -1.118556461723492, -1.1506215983214503, -1.1756369342901807, -1.1924290786035188, -1.2000632991327058, -1.1978616445245285, -1.1854141891639927, -1.1625831913450313, -1.1295001356213972, -1.0865558110540519, -1.034383753178372, -0.973837544576135, -0.9059626227804097, -0.8319633810309865, -0.7531664637332656, -0.6709812514714708, -0.5868585977953019, -0.5022489200915222, -0.4185607587094183, -0.3371209018834903, -0.25913712935616057, -0.18566455611949315, -0.11757646121444382, -0.055540367522827, -4.863570375660247e-16], [0.0, 0.04664376333502752, 0.08672297034970054, 0.12062857519358562, 0.14897489675885242, 0.17258108630306981, 0.19244674463235095, 0.2097223300972825, 0.22567513607050219, 0.2416517341782522, 0.2590378743447374, 0.27921690224647194, 0.303527797266725, 0.33322394836982483, 0.3694337710713956, 0.4131242261721469, 0.46506823116962126, 0.5258168599708337, 0.5956771080499654, 0.6746958614663163, 0.7626505526290985, 0.8590468172454175, 0.9631232897251486, 1.0738634928769508, 1.1900145965645754, 1.310112643655631, 1.4325136745280778, 1.5554300278228796, 1.6769709589360025, 1.795186602395857, 1.9081142127269604, 2.013825553024255, 2.1104742629753726, 2.196342029500413, 2.2698824038431407, 2.329761158431163, 2.3748921539954972, 2.404467790482532, 2.417983241738115, 2.4152538207435774, 2.396424985775011, 2.3619746742553187, 2.3127078359630864, 2.2497432261242865, 2.1744927071060545, 2.08863349032734, 1.9940739230923674, 1.8929135840658087, 1.7873985921090298, 1.679873152687124, 1.5727284610624392, 1.4683501496355666, 1.369065506359001, 1.2770917011120033, 1.1944862369924985, 1.1231007940917737, 1.0645395556317352, 1.0201230022189427, 0.9908580319106176, 0.9774151148895623, 0.9801130254140323, 0.9989115143757457, 1.033412097619368, 1.0828669427232807, 1.1461956448923252, 1.222009495637128, 1.3086426705554288, 1.4041895990964042, 1.5065476336442403, 1.6134640111287708, 1.722586000657333, 1.8315130577640943, 1.937849761531164, 2.039258296090822, 2.133509253183949, 2.2185295771068994, 2.2924465463862504, 2.353626786041737, 2.4007094278498284, 2.43263268053285, 2.4486532336929807, 2.4483580945850494, 2.431668641154834, 2.398836863622458, 2.350433955622949, 2.2873315998998054, 2.210676468279761, 2.121858616873121, 2.0224746012210426, 1.9142862589653886, 1.7991762065886163, 1.6791011694982703, 1.556044309504876, 1.4319677295514193, 1.3087663221044759, 1.1882240853458341, 1.0719739613561545, 0.961462154692141, 0.8579177705957132, 0.7623284725841543, 0.6754227028993662, 0.5976588401971987, 0.5292214912011639, 0.4700249312990267, 0.4197235277895694, 0.3777288032326261, 0.343232629526242, 0.3152358900943156, 0.2925818117325789, 0.2739930526033959, 0.25811154143773346, 0.24353999744560106, 0.22888402235158026, 0.21279364626502137, 0.19400322795641747, 0.17136865701532336, 0.143900879079707, 0.11079486394707154, 0.07145325737455632, 0.025504097657460586, -0.027187865931415776, -0.08651654802395954, -0.15213671532821066, -0.22347292981292932, -0.29973501188185303, -0.37993961775194796, -0.46293736481047437, -0.5474447926880194, -0.6320803198663533, -0.7154032491037321, -0.7959547925325318, -0.8723000310855166, -0.9430696944000007, -1.0070006473000614, -1.062973997416614, -1.110049794807527, -1.1474973772173143, -1.1748205218334302, -1.1917766934015035, -1.1983898261511379, -1.194956239481576, -1.182043460706159, -1.1604819080202982, -1.1313495687321613, -1.0959499871115828, -1.0557840484591403, -1.0125162068289428, -0.967935949187442, -0.9239154149652927, -0.882364193740278, -0.8451824025073594, -0.8142131955969877, -0.7911958834151998, -0.7777208301250816, -0.7751872652189656, -0.7847650804179597, -0.8073615929592867, -0.8435941412416003, -0.8937692417605304, -0.95786888059776, -1.0355443422120019, -1.126117797079567, -1.2285916822792171, -1.341665720007507, -1.4637612328934348, -1.593052236437355, -1.7275026223325918, -1.8649085959553515, -2.002945400657856, -2.1392172539160854, -2.2713093385515686, -2.396840638220706, -2.5135163815194677, -2.619178864046096, -2.7118554525268497, -2.78980263883845, -2.851545102941364, -2.895908860182821, -2.9220477073287547, -2.9294623396788912, -2.918011684878448, -2.8879161833577913, -2.839752936229837, -2.7744428343141214, -2.6932299720483392, -2.5976538327725316, -2.4895149027882524, -2.3708345265557638, -2.243809950639759, -2.110765616274726, -1.974101846988073, -1.8362421365142994, -1.6995802718629416, -1.5664285261870998, -1.438968126090238, -1.3192031389911427, -1.2089188396322903, -1.1096455029325094, -1.0226284359358397, -0.9488049079298807, -0.888788468700705, -0.8428609645318593, -0.8109723743869274, -0.7927483993410488, -0.7875055513960868, -0.7942733079063599, -0.8118227293542132, -0.8387007852537193, -0.8732694992413934, -0.9137489131662779, -0.9582627838873405, -1.0048858675654129, -1.0516916158638367, -1.0967991073009034, -1.1384180649566746, -1.1748908680340597, -1.2047305479132548, -1.226653867162246, -1.23960870970687, -1.2427951587154455, -1.235679801953989, -1.2180029782938178, -1.189778859322608, -1.1512884420905625, -1.1030657083485023, -1.045877377715164, -0.9806968427472479, -0.9086730188756054, -0.8310949680082742, -0.749353258166264, -0.6648991002543849, -0.5792023550476854, -0.49370952743908647, -0.4098028603954437, -0.3287616080761286, -0.25172650706237987, -0.17966837819980952, -0.1133616813949771, -0.05336371464901254, -4.658115920408005e-16], [0.0, 0.04446936909140338, 0.08253856908962462, 0.1147154663234348, 0.1417224195332687, 0.16447438151067087, 0.18405148250039738, 0.20166681915709217, 0.21863029957447427, 0.23630949995872155, 0.25608856921200435, 0.2793262719515567, 0.3073142869030276, 0.3412368754628035, 0.3821330045293673, 0.4308619491838956, 0.4880733158814577, 0.5541823175883864, 0.6293510014747385, 0.7134759805961927, 0.8061830571963243, 0.906828950920573, 1.0145101647216517, 1.128078839079946, 1.2461652659387215, 1.3672065619758331, 1.4894808408369833, 1.6111460797911266, 1.7302827515999004, 1.8449391904050674, 1.9531785837568998, 2.0531264335332824, 2.143017307759236, 2.221239713844996, 2.286377961406749, 2.337249948782353, 2.372939900064331, 2.392825196736142, 2.3965965869930113, 2.384271213188543, 2.356198069743675, 2.3130556860881906, 2.25584201731508, 2.185856714598399, 2.1046761333992006, 2.0141216154794472, 1.9162217463667057, 1.8131694390655824, 1.7072748237965563, 1.600915029150677, 1.496482019640664, 1.3963297062026312, 1.3027215684402802, 1.217780019706744, 1.143438708623677, 1.0813988842098328, 1.0330908580097296, 0.9996414777269148, 0.9818483857427036, 0.9801616759541397, 0.994673387471265, 1.0251150881189013, 1.0708636089005492, 1.1309547972633849, 1.2041049668532695, 1.2887395390894634, 1.383028201751415, 1.484925755985957, 1.5922176894413698, 1.702569402852315, 1.8135779329990214, 1.9228249585723043, 2.0279298484301616, 2.126601514650797, 2.2166878655541598, 2.29622171563149, 2.3634620985324912, 2.41693004368297, 2.455438013898914, 2.4781123571353625, 2.484408296411587, 2.474117163771348, 2.447365772392887, 2.404608011030684, 2.3466089321872845, 2.2744217851954334, 2.1893586133468923, 2.092955186244334, 1.9869311709868285, 1.8731465554303985, 1.7535554209653041, 1.6301582190284172, 1.504953733612096, 1.379891910744737, 1.2568287054344855, 1.1374840377427984, 1.0234038640447756, 0.9159272593577271, 0.8161592747015253, 0.7249501831523919, 0.6428815633740269, 0.570259494118936, 0.5071149519021488, 0.4532113213122976, 0.4080587478216272, 0.3709348909794102, 0.3409114758154031, 0.3168858961280327, 0.2976169986672925, 0.2817640751314303, 0.2679280118953822, 0.254693497360068, 0.2406711649580913, 0.22453855666693667, 0.20507882713857664, 0.18121617131292206, 0.15204704701007135, 0.11686637621170937, 0.07518804167289503, 0.026759145759970838, -0.028432337837478287, -0.09015671578656659, -0.15794854842649242, -0.23111928452474326, -0.3087762229562945, -0.38984730100668014, -0.47311105597253944, -0.557230970351958, -0.6407932946555244, -0.7223473486959968, -0.8004472345189031, -0.8736938536668273, -0.9407761092914351, -1.0005101900928646, -1.0518758778086121, -1.0940488919146527, -1.1264283825753763, -1.148658803279639, -1.160645535039002, -1.1625637910040323, -1.1548604999575416, -1.1382490451279086, -1.1136969166716502, -1.0824065174356516, -1.045789537666472, -1.0054354807487003, -0.9630750746197025, -0.9205394383554228, -0.8797159871154867, -0.8425021482615896, -0.8107580246996463, -0.786259176675295, -0.7706506994004723, -0.7654037507528085, -0.7717756313439846, -0.79077443968941, -0.823129219909562, -0.8692663908759432, -0.9292930970858456, -1.002987956419199, -1.0897995023233722, -1.1888524322305989, -1.2989615846909746, -1.4186533794525986, -1.5461942721728161, -1.6796256031030645, -1.8168040612132275, -1.9554468457192664, -2.093180489315621, -2.2275922145230864, -2.356282628772415, -2.4769185268188, -2.587284561783585, -2.6853325687796543, -2.769227377192553, -2.837388028035233, -2.8885234194503036, -2.9216615338337193, -2.9361715510479436, -2.931778320123938, -2.9085688426460568, -2.8669906102819347, -2.807841832061173, -2.732253779327273, -2.641665663111163, -2.5377926354615368, -2.4225876687223398, -2.298198210928853, -2.1669186379075533, -2.0311396203514844, -1.8932955947514938, -1.7558115689059717, -1.6210505048275248, -1.4912625039623713, -1.3685369722202265, -1.2547588665872342, -1.1515700229598693, -1.0603364388389984, -0.9821222377868072, -0.9176708787058963, -0.8673939960948154, -0.8313680718266507, -0.8093389492534508, -0.8007340112174951, -0.8046816594885788, -0.8200375587456404, -0.8454169477352425, -0.8792321775705403, -0.9197345157369323, -0.9650591571655408, -1.01327231304053, -1.0624192054774524, -1.1105717828029653, -1.1558749861139348, -1.196590442600175, -1.2311365335703468, -1.2581238833300856, -1.276385436497005, -1.2850004328977398, -1.2833117472829416, -1.2709362317197406, -1.2477678773753806, -1.2139737949939082, -1.169983195108113, -1.1164697253712703, -1.0543276889311037, -0.9846428203487787, -0.9086584303932004, -0.827737844770748, -0.743324151673198, -0.656898336735531, -0.5699369200433373, -0.4838702173656251, -0.4000423266789309, -0.31967389187905954, -0.24382861963831795, -0.17338442462110573, -0.10900995530434957, -0.051147110603532074, -4.451648696675859e-16], [0.0, 0.04233428475072377, 0.07848887540873555, 0.10908448208095471, 0.1349455272379212, 0.15707505311931644, 0.17662449276066297, 0.19485910514622473, 0.213119989871696, 0.23278368822505666, 0.25522044341956507, 0.28175223113968934, 0.3136116815779498, 0.35190299545176396, 0.39756590952035126, 0.4513436930106925, 0.5137560569307774, 0.5850777359594306, 0.6653233604945905, 0.7542390780582827, 0.8513012125535743, 0.9557220711193507, 1.066462826015201, 1.1822532176712852, 1.301617649320257, 1.422907077923348, 1.5443359546021065, 1.6640233343365258, 1.7800371626918303, 1.8904406596646093, 1.9933396596679913, 2.086929733820921, 2.1695419169845764, 2.2396858875928607, 2.296089502717518, 2.3377336727391276, 2.3638816675230396, 2.3741020765448657, 2.3682847958171154, 2.3466495810814822, 2.309746885485202, 2.258450886480712, 2.193944796399938, 2.117698739394046, 2.031440659559531, 1.9371208965965827, 1.836871222023549, 1.732959266917704, 1.6277393879376565, 1.5236011091166484, 1.42291634032009, 1.3279866077253624, 1.2409915363056885, 1.1639397989138176, 1.098623691732234, 1.0465784128751354, 1.0090470117756634, 0.986951844295621, 0.9808732154592196, 0.9910357220430239, 1.0173026250665995, 1.0591783919466038, 1.1158193543249837, 1.1860522350697538, 1.2684001113548864, 1.361115204589837, 1.4622177265683276, 1.5695398684583342, 1.6807738986200482, 1.793523239634059, 1.9053553266496641, 2.0138550098563766, 2.1166772544606682, 2.2115979122041156, 2.296561388639578, 2.3697241088173158, 2.4294927887607645, 2.474556648526316, 2.5039128515615094, 2.516884620819165, 2.5131316605639538, 2.4926526996270733, 2.455780162432692, 2.4031671637602927, 2.335767207275548, 2.2548071418607387, 2.1617540894624523, 2.0582771996698312, 1.9462052061178705, 1.8274808551952628, 1.704113346154332, 1.5781299619677045, 1.4515280812539495, 1.3262287431306228, 1.2040328895053811, 1.086581334357405, 0.975319408946077, 0.8714671081999995, 0.7759954199409409, 0.6896093587273466, 0.6127380540001501, 0.5455320622148463, 0.48786788927125607, 0.4393595274028486, 0.39937663431827114, 0.36706881620220216, 0.3413953243209254, 0.3211593412140217, 0.3050459201014539, 0.29166255296671867, 0.2795812809528821, 0.26738122672605347, 0.2536904231162858, 0.23722583571492623, 0.2168305285447472, 0.19150700007456845, 0.1604458197033593, 0.12304881975021738, 0.07894624176391635, 0.028007394943963478, -0.029655445401037584, -0.09368999446658315, -0.16351368544396055, -0.2383299066111007, -0.3171503163687984, -0.3988226452327814, -0.48206324954427215, -0.565493556171916, -0.6476794339450029, -0.7271724486287718, -0.8025519059563837, -0.8724665629281728, -0.9356748919329659, -0.9910828151736814, -1.0377778876055275, -1.0750589936353672, -1.1024607340363268, -1.1197718121435585, -1.1270468791138106, -1.124611463091854, -1.113059782403218, -1.0932454239936056, -1.0662650507154592, -1.0334354801351548, -0.9962646487876894, -0.9564171349137384, -0.9156750556451962, -0.8758952777247514, -0.838963981003764, -0.8067496885789116, -0.7810559245504383, -0.7635746787434645, -0.7558418467719878, -0.7591957737147728, -0.7747399613103689, -0.8033109035661427, -0.8454518962800638, -0.9013935250707119, -0.9710413775169674, -1.053971351796235, -1.1494327510115283, -1.2563591637018063, -1.3733869414709143, -1.4988808989131253, -1.6309666836377443, -1.767569099584295, -1.9064555190493548, -2.0452833915840563, -2.181650754338314, -2.3131485711153124, -2.4374136783086184, -2.5521810962837064, -2.655334475172554, -2.7449534842751775, -2.8193570233733274, -2.877141230618582, -2.9172113829479964, -2.938806928281214, -2.941519050597486, -2.9253003454566606, -2.8904663703318936, -2.8376890267257657, -2.7679819247640927, -2.6826780710934433, -2.5834004028266015, -2.4720258595644014, -2.3506438380606944, -2.2215100061898956, -2.086996561325243, -1.9495401004219772, -1.8115883230507839, -1.6755468130610345, -1.5437271389152156, -1.41829747720539, -1.3012368993519776, -1.194294369618124, -1.0989533856388964, -1.0164030535670756, -0.9475162321187295, -0.8928352071588262, -0.8525651752547242, -0.8265756253504, -0.8144095170258355, -0.815299966378068, -0.8281939709789855, -0.8517825380132541, -0.8845364286508565, -0.9247466006250996, -0.9705683230311536, -1.0200678551159912, -1.0712705262416011, -1.122209028524494, -1.1709707374225518, -1.2157429085616398, -1.2548546604506576, -1.2868147408067032, -1.31034418672246, -1.3244031229766415, -1.328211095005565, -1.3212604995661335, -1.3033228527277636, -1.274447817089392, -1.2349550934542637, -1.1854194620175715, -1.1266494299362833, -1.0596601016715785, -0.9856410317525409, -0.9059199430503747, -0.8219232942228065, -0.7351347552146547, -0.6470526977478085, -0.5591478274523005, -0.4728220752424623, -0.38936982801383535, -0.30994251372870724, -0.23551746516145994, -0.1668718723264199, -0.10456249883609177, -0.04891168557590666, -4.246151540548214e-16], [0.0, 0.04025922431950193, 0.07461360944651997, 0.10379160089803362, 0.1287127564672834, 0.15045966084470141, 0.17024513217856993, 0.18937559124529987, 0.2092115658743992, 0.23112638040695668, 0.2564641302772448, 0.286498063987692, 0.32239048819826904, 0.3651552764954536, 0.41562399948684237, 0.4744166047282592, 0.5419174618355296, 0.6182574537744775, 0.703302643108841, 0.7966498757190379, 0.8976295083466512, 1.0053152646870958, 1.1185410422083792, 1.2359243130109783, 1.3558955913728086, 1.4767332824585602, 1.5966030850243966, 1.7136009994230934, 1.8257988939216443, 1.931291509820769, 2.02824374101355, 2.1149370076530505, 2.1898135570136392, 2.2515175671950995, 2.298932000073618, 2.331210247188073, 2.3478017337390975, 2.3484707886418446, 2.3333082491464725, 2.3027354430092277, 2.2575003752950806, 2.1986661361059854, 2.127591735206834, 2.045905754992537, 1.9554733899277326, 1.8583576041257968, 1.7567752850633092, 1.6530493969130993, 1.5495582384938758, 1.448682985832423, 1.3527547459186493, 1.2640023652036068, 1.1845022232710556, 1.1161311991676088, 1.0605239261011767, 1.019035351316861, 0.992709494305464, 0.9822551510732646, 0.9880291285197805, 1.0100274149997646, 1.0478845052060055, 1.1008809041662324, 1.1679586411002167, 1.2477444338500452, 1.3385799631980992, 1.438558548032719, 1.5455673611004208, 1.6573341946655868, 1.771477678942078, 1.8855597762384504, 1.9971393222881348, 2.1038253644416494, 2.203329054772982, 2.2935128944526064, 2.372436192986901, 2.4383957004318657, 2.4899604901057053, 2.5260003106890587, 2.5457067864195784, 2.54860701841557, 2.5345693247098082, 2.5038010468019403, 2.4568385417780303, 2.394529666613556, 2.318009240585483, 2.228668138396387, 2.1281168166047832, 2.018144205626894, 1.900673005800497, 1.7777125062414167, 1.651310097585097, 1.523502672990349, 1.3962691055125418, 1.2714849543848183, 1.1508804888587116, 1.0360030277310812, 0.928184477859274, 0.8285148187774116, 0.7378221264328757, 0.6566595609610196, 0.5852995655450078, 0.5237353402373551, 0.4716894707440809, 0.4286294121922419, 0.3937893563116548, 0.3661978515374892, 0.3447104032327211, 0.32804615906559276, 0.3148276855740854, 0.3036227685381046, 0.29298712374651664, 0.2815068871866273, 0.2678397649784202, 0.25075376318002635, 0.22916248484415322, 0.20215607465834032, 0.16902700776183835, 0.1292900559212427, 0.08269591767971948, 0.029238165463117714, -0.030846662300370743, -0.09708581665986661, -0.16878375479974217, -0.24504185726217517, -0.324783920191698, -0.4067867455827559, -0.4897150183377797, -0.5721595454880557, -0.6526778430872863, -0.7298359923589955, -0.8022506503137051, -0.8686300922062704, -0.9278131841172036, -0.9788052331294165, -1.0208097388364705, -1.0532551713806944, -1.0758160253632247, -1.0884275427036318, -1.0912936572675445, -1.0848878858320714, -1.0699470694183577, -1.047458051684348, -1.0186375623466903, -0.9849057489222788, -0.9478539650209581, -0.9092075738062121, -0.8707846572499096, -0.8344516320720242, -0.8020768589431155, -0.7754833904110119, -0.7564020335309709, -0.7464259044720998, -0.74696762430901, -0.7592202483841364, -0.7841229373568475, -0.8223322683395087, -0.8741999519935454, -0.939757569327658, -1.0187087739064402, -1.110429225343523, -1.2139743327231365, -1.3280946965637814, -1.4512589497830688, -1.5816835164822136, -1.7173686367288215, -1.856139850102265, -1.9956939944338112, -2.133648662316921, -2.2675939694289617, -2.3951454277205557, -2.513996684647369, -2.621970887681606, -2.7170694614528648, -2.797517142399005, -2.8618022014022575, -2.908710896500192, -2.9373553327102595, -2.947194061031593, -2.9380449200351735, -2.910089806967337, -2.863871256515667, -2.800280899673857, -2.720540067769476, -2.626172993002334, -2.5189732322520397, -2.4009641011893907, -2.274354046975374, -2.1414880066293267, -2.0047958916205904, -1.8667394051323598, -1.7297584351877742, -1.596218273554142, -1.4683588869277036, -1.3482474139612832, -1.2377349805662616, -1.1384188186256163, -1.0516105424596172, -0.9783112863285487, -0.9191942386676227, -0.8745949287584327, -0.8445094335773509, -0.8286004812408305, -0.8262112374824936, -0.836386377596427, -0.8578998727593901, -0.8892887608284212, -0.9288920314555206, -0.9748936370577613, -1.0253685476711036, -1.0783307012217476, -1.131781662821054, -1.183758798169463, -1.2323817871523943, -1.2758963536068313, -1.3127141646959484, -1.3414479563359112, -1.360941067027896, -1.3702907080524713, -1.3688644595923207, -1.3563096558825978, -1.3325555035788006, -1.2978079616327205, -1.2525375934667375, -1.1974607785728237, -1.1335148364366232, -1.0618277667729699, -0.9836834427061859, -0.9004832044544999, -0.8137048875502446, -0.7248603795312811, -0.6354528309285915, -0.5469346495098859, -0.4606673811016942, -0.37788452660743616, -0.29965826447584337, -0.22687094293059726, -0.1601920794416121, -0.10006145944323012, -0.04667876589314745, -4.0436001113043494e-16], [0.0, 0.03826435089587519, 0.07095087276669022, 0.09888964142321793, 0.12308752993775146, 0.1446973598767792, 0.16498281560643255, 0.18528005529345262, 0.20695704035172113, 0.2313716670908166, 0.25982981860980425, 0.29354446064498, 0.33359688194314485, 0.38090112833588224, 0.4361726012908948, 0.49990168825036385, 0.5723331661031982, 0.6534519738168133, 0.7429757892047755, 0.8403546720600377, 0.9447778557707819, 1.055187586580536, 1.1702997284591856, 1.2886306766842879, 1.408529959110368, 1.5282177548854043, 1.6458264298515861, 1.75944507937559, 1.8671659856823974, 1.9671318400929863, 2.0575825523980704, 2.136900470738104, 2.2036528658763053, 2.2566305929876287, 2.294881930667379, 2.317740708730754, 2.3248479708383574, 2.3161665717848776, 2.2919882786842214, 2.25293312613469, 2.1999409633202793, 2.1342553212830175, 2.0573999166015584, 1.971148288794551, 1.8774872384567882, 1.7785748872268359, 1.676694315349201, 1.5742038444755493, 1.4734851196471732, 1.376890202938758, 1.2866889205249485, 1.2050177041765109, 1.1338311373597385, 1.074857355896959, 1.0295583649660713, 0.9990962201790644, 0.9843058833260343, 0.9856754064142743, 1.0033339246716515, 1.0370477544146244, 1.0862246995906921, 1.1499264760609598, 1.2268889700259755, 1.3155498611021503, 1.4140829659472787, 1.5204384992560158, 1.6323883092631177, 1.747575027992246, 1.8635639851997496, 1.977896671488371, 2.0881445019228733, 2.1919616274694573, 2.287135567763537, 2.3716344944085272, 2.443650077820511, 2.5016349204717465, 2.5443337325263293, 2.570807559011526, 2.580450537050952, 2.572998843128844, 2.548531679398302, 2.5074643400497427, 2.450533589014445, 2.3787757641381373, 2.293498195933782, 2.1962446869002417, 2.0887559363438863, 1.9729259123074359, 1.8507552637950455, 1.7243029308107192, 1.5956371453023563, 1.4667870221440302, 1.3396959157446755, 1.2161776654251262, 1.0978767727541259, 0.9862334486542231, 0.882454339981385, 0.7874895977088782, 0.7020167855422595, 0.6264319528777201, 0.5608480138894784, 0.5051003897620346, 0.4587596882950414, 0.42115101886740475, 0.3913793754457874, 0.368360370071199, 0.35085546778180143, 0.3375107644796231, 0.32689826451557663, 0.3175585568189405, 0.30804375862766237, 0.2969595949687722, 0.2830055099529824, 0.26501176191965065, 0.24197253702954818, 0.21307422291836908, 0.1777181127465841, 0.13553695712028602, 0.08640494316208361, 0.030440852363280736, -0.031995672632037286, -0.10031464200731299, -0.17371272600108217, -0.2511962980885296, -0.3316098987950093, -0.4136693625520307, -0.4959987271171221, -0.5771699446981712, -0.6557443386140893, -0.730314701020105, -0.7995469071820748, -0.8622199305428817, -0.9172631802037937, -0.9637901475421334, -1.0011274399024976, -1.0288383943721535, -1.0467406007186817, -1.0549168162345923, -1.0537189226570074, -1.043764752316507, -1.0259277927767991, -1.0013199618782418, -0.971267823694062, -0.9372827859415354, -0.901025976560175, -0.8642686374873826, -0.8288489935539679, -0.7966266508160779, -0.7694356490443351, -0.7490373356575567, -0.7370742419588708, -0.7350261266685485, -0.744169306744436, -0.7655403223575138, -0.7999048833684207, -0.8477329211122799, -0.9091804247272333, -0.9840785791685921, -1.071930546389819, -1.1719160462427174, -1.2829037039903708, -1.4034709416020197, -1.5319310048856747, -1.6663665425836254, -1.804668991162154, -1.9445828741989626, -2.0837540016132556, -2.2197804545818256, -2.350265169337238, -2.472868888992267, -2.585362238220634, -2.6856756914598816, -2.7719462509602875, -2.842559725423824, -2.8961876013912673, -2.9318176255124713, -2.94877736333738, -2.946750165726859, -2.925783153393102, -2.8862870190848122, -2.8290276409409554, -2.7551096948326945, -2.6659526433710696, -2.563259660061718, -2.4489802144408923, -2.3252671938638425, -2.1944295662993207, -2.0588816928948694, -1.921090476693667, -1.7835215828385718, -1.6485859847308615, -1.5185880794866813, -1.39567657496428, -1.2817992806619052, -1.1786628376593375, -1.0876983009103853, -1.0100333436050684, -0.9464716915554928, -0.8974802196054148, -0.8631839562495026, -0.8433690515388927, -0.8374935716316741, -0.8447057957145656, -0.8638695120594359, -0.8935956440483306, -0.9322793881362629, -0.9781419175264983, -1.0292756008954136, -1.0836916073181104, -1.1393687184518009, -1.1943021481747609, -1.2465511786711676, -1.294284460078767, -1.335821887233831, -1.369672060013902, -1.3945644508975388, -1.4094755416400855, -1.413648346896996, -1.406604912270865, -1.3881515533424365, -1.358376786272036, -1.3176420849142265, -1.2665657794662801, -1.2060005829765705, -1.1370053903079615, -1.060812135453271, -0.9787886139362383, -0.8923982744225952, -0.8031580552242334, -0.7125953853693318, -0.6222054852903514, -0.5334100886276598, -0.44751866456318423, -0.36569315060572705, -0.28891711065481557, -0.21797011492200064, -0.15340799991554277, -0.09554951172872632, -0.04446966826030092, -3.845943725452794e-16], [0.0, 0.036369079392308594, 0.06753677332659992, 0.09442773906511236, 0.11812752278625817, 0.1398492027425286, 0.16089630537735802, 0.18262298316546755, 0.20639251639687195, 0.2335352474007009, 0.2653070736007427, 0.30284961482378103, 0.3471531306846346, 0.39902319660966584, 0.45905205379216824, 0.5275954314135858, 0.6047555017280035, 0.690370473534217, 0.7840111610311551, 0.8849846872938237, 0.9923452990822028, 1.1049120869960338, 1.22129322671807, 1.3399161877487982, 1.4590631999132624, 1.5769111289798248, 1.6915747945137711, 1.8011526686274961, 1.9037738260281099, 1.9976449754986705, 2.081096391781921, 2.152625585143783, 2.2109375933224666, 2.2549808560368514, 2.2839777339535705, 2.2974488595579863, 2.295230653704731, 2.2774855051806218, 2.2447042874031595, 2.1977010720712817, 2.1376000896211518, 2.0658151760411054, 1.9840221302868706, 1.8941245816459746, 1.798214127590795, 1.6985256459303153, 1.5973888068524318, 1.497176907696285, 1.4002542235606632, 1.3089231083533763, 1.225372092535822, 1.151626205266987, 1.0895007002938957, 1.0405592878955983, 1.0060778712953378, 0.9870146577016083, 0.983987364614907, 0.9972580748585601, 1.026726113010695, 1.071929125917751, 1.1320523553739539, 1.205945896586845, 1.2921495464457322, 1.3889246654794039, 1.4942923111123931, 1.6060767514463221, 1.7219533419083766, 1.8394996447980532, 1.9562485965002918, 2.069742480728175, 2.177586449714512, 2.277500349157948, 2.3673676465705005, 2.4452803353632073, 2.5095787867297625, 2.558885645672154, 2.5921330132828775, 2.6085823210598473, 2.60783648055208, 2.5898440786521837, 2.5548955807747893, 2.5036116962844304, 2.4369242481613522, 2.356050067437626, 2.2624585980491494, 2.1578340454211924, 2.044033028762863, 1.9230387996421823, 1.796913165500259, 1.6677473045525661, 1.5376126769326255, 1.4085132256014496, 1.2823400198557975, 1.160829425324709, 1.0455257889509428, 0.9377495080664827, 0.8385712123337786, 0.7487926295951896, 0.6689345355335595, 0.5992320068039348, 0.539637012473137, 0.489828193827875, 0.44922750249933946, 0.41702319589293485, 0.3921985313579277, 0.3735653602921707, 0.35980170391963834, 0.34949229674497806, 0.34117101402199623, 0.3333640576573103, 0.3246327617931923, 0.3136148951396953, 0.29906338149179384, 0.2798814315932347, 0.25515317672985777, 0.22416901464759467, 0.1864450185153855, 0.14173591611369477, 0.09004131524069371, 0.031605028197450084, -0.033092471352158793, -0.10334824643213278, -0.17825736315072174, -0.25673907500766047, -0.3375680249476759, -0.4194096332094905, -0.5008587285284822, -0.5804803938712797, -0.6568519378211655, -0.7286048705414441, -0.7944657597662144, -0.853294867627577, -0.904121522722658, -0.94617526233891, -0.9789118851985372, -1.0020336828302974, -1.0155032645416755, -1.0195505532746942, -1.0146727033181429, -1.0016268715596046, -0.9814159571506764, -0.9552676055157396, -0.9246069469920293, -0.8910237036381121, -0.8562344457514689, -0.8220409086279502, -0.7902853867793453, -0.7628043044532425, -0.7413811157444539, -0.7276997133969197, -0.7232995218263494, -0.7295334169359514, -0.7475295536701773, -0.7781580933904344, -0.8220037091779001, -0.8793446108171209, -0.9501386757968378, -1.0340171019686912, -1.1302858157050706, -1.237934680953179, -1.355654364126932, -1.4818605220043861, -1.6147247993426508, -1.7522119542503325, -1.892122276652044, -2.032138332239, -2.1698749544409495, -2.3029313229323334, -2.4289439111239313, -2.5456390584276694, -2.650883926536487, -2.7427346325105035, -2.8194804143458647, -2.879682775441021, -2.9222086707996207, -2.946256937120325, -2.951377327757153, -2.937481688044705, -2.9048469924377835, -2.85411015779906, -2.786254742293505, -2.7025898319695267, -2.604721602539054, -2.4945182176024994, -2.374068882375082, -2.2456380100251874, -2.111615572682193, -1.974464798228371, -1.8366684350070668, -1.7006748380970227, -1.5688451320822967, -1.4434026762908516, -1.3263860000270817, -1.2196062888486636, -1.1246103905868903, -1.0426501743644192, -0.9746589206703784, -0.921235249434606, -0.8826349102114367, -0.8587705685301285, -0.8492195298555726, -0.8532391521461894, -0.8697895143515305, -0.897562735839364, -0.9350181848740101, -0.9804226766878676, -1.0318946467167711, -1.0874511949630186, -1.145056835332171, -1.2026727506014177, -1.258305350141928, -1.3100529536226524, -1.3561494789234307, -1.395004094921462, -1.425235907551317, -1.445702877816472, -1.4555243199375896, -1.4540964927783093, -1.4411009739354959, -1.4165056889890986, -1.3805586537875083, -1.333774670660815, -1.2769153955399928, -1.2109633577293568, -1.1370906634400733, -1.056623244443947, -0.9710016211343094, -0.8817392322345451, -0.7903794393543789, -0.6984523422194368, -0.607432539062943, -0.5186989364696117, -0.43349765472515184, -0.3529089899770934, -0.277819285445508, -0.20889843333579283, -0.1465835803381533, -0.09106944644289366, -0.04230549340876137, -3.6550863886177547e-16], [0.0, 0.03459188608033418, 0.06440506909359281, 0.09045085751478413, 0.11388408402462659, 0.13596751953581848, 0.1580331043781812, 0.18144103220955285, 0.20753778030849349, 0.2376142099866117, 0.2728648621423763, 0.31434954539931265, 0.3629582584910821, 0.4193804059464409, 0.4840791587375985, 0.5572716820611628, 0.6389158040561751, 0.7287035357421465, 0.8260616778813751, 0.930159569218046, 1.0399238471804961, 1.1540599112721717, 1.2710796055862927, 1.3893344745556273, 1.5070537993095332, 1.6223864945914723, 1.7334458413513427, 1.8383559505706213, 1.9352988016805848, 2.0225606754926884, 2.0985768075586795, 2.1619731232670625, 2.2116039799804543, 2.2465849326295815, 2.266319655230455, 2.2705202889831413, 2.2592206445885057, 2.232781858354463, 2.1918902843471186, 2.1375475937904165, 2.071053243481185, 1.993979662465453, 1.9081406859834416, 1.815553933282737, 1.7183979771613487, 1.6189652842687225, 1.5196120129862165, 1.4227058374215167, 1.3305730196142596, 1.2454459760823775, 1.1694125786842757, 1.1043683935157576, 1.0519729960278357, 1.0136114072868982, 0.990361577530138, 0.9829687017527475, 0.9918269914137744, 1.0169693503541144, 1.0580652159516204, 1.1144266329377661, 1.185022431873745, 1.2685001917839576, 1.3632154815548458, 1.4672677019245735, 1.5785416934164616, 1.6947541392093546, 1.8135036790014267, 1.9323235631471989, 2.0487356178250224, 2.1603042631279044, 2.2646893274385764, 2.3596964331843053, 2.4433237902583245, 2.513804322514432, 2.569642167576768, 2.609642727918114, 2.6329356083501447, 2.6389899478665924, 2.6276218379377596, 2.598993710350433, 2.5536057708400697, 2.4922797453444328, 2.4161353890642405, 2.326560380176944, 2.2251743758409908, 2.1137881442748823, 1.9943587999147734, 1.868942256234769, 1.7396440706821243, 1.6085698869505407, 1.4777766808255033, 1.3492259871603036, 1.2247402279881539, 1.1059631768661482, 0.9943254844758078, 0.8910160580876484, 0.796959936094977, 0.7128031322618619, 0.6389047468052267, 0.57533645739875, 0.5218893172557593, 0.47808760426560676, 0.44320928929098585, 0.4163125275573261, 0.3962674286543895, 0.3817922316967309, 0.37149290583289374, 0.36390511516043345, 0.3575374331662769, 0.3509146663559408, 0.3426201503312939, 0.33133591406576085, 0.3158796686243904, 0.2952376634981466, 0.26859256481984023, 0.23534564215067133, 0.1951327008862826, 0.14783336179596135, 0.0935734635934538, 0.032720544311149784, -0.03412746195580379, -0.10615999924032381, -0.1823776521656705, -0.26162125749445936, -0.3426055854785507, -0.42395669160209226, -0.5042519422233434, -0.5820616460459624, -0.6559911791216069, -0.7247224753491197, -0.7870537676206936, -0.8419365065729206, -0.8885084533106348, -0.9261220377678574, -0.9543671931833148, -0.9730880165341445, -0.9823927612053911, -0.9826568377560891, -0.9745186771198149, -0.9588684934632088, -0.9368301666166621, -0.9097366418801033, -0.8790994135989956, -0.8465728139306902, -0.8139139657401027, -0.7829393750675395, -0.7554792311096072, -0.7333305477499886, -0.718210318627446, -0.7117098664902426, -0.7152515468408035, -0.7300489160385945, -0.7570713962448613, -0.79701436570032, -0.8502754753198234, -0.9169378445526876, -0.9967606244968633, -1.0891772384004312, -1.1933014232951207, -1.3079410061644456, -1.4316191584427633, -1.5626026884514606, -1.6989367571616583, -1.838485242748861, -1.9789758377490423, -2.118048842770833, -2.2533085256662533, -2.382375847208404, -2.502941315400286, -2.6128167215647236, -2.709984532628786, -2.792643765060091, -2.859251245548979, -2.908557269867207, -2.9396348018208056, -2.95190150570739, -2.9451340745227617, -2.9194744982467964, -2.8754281074547823, -2.813853422608745, -2.7359440339398424, -2.6432029261053813, -2.5374098411872112, -2.420582438729582, -2.2949321583779656, -2.162815815709382, -2.0266840620056223, -1.8890279115908137, -1.752324584179904, -1.618983923421515, -1.4912966361635924, -1.3713855503610355, -1.2611610141550769, -1.1622814563603734, -1.076120001931216, -1.003737888072443, -0.9458652611576759, -0.902889755590214, -0.8748530675884189, -0.8614555442132193, -0.8620686154995021, -0.8757547100115478, -0.9012941160923669, -0.9372180868525399, -0.9818473405326984, -1.0333349828149299, -1.0897127769588437, -1.1489396136972554, -1.2089509873793527, -1.2677082689218593, -1.3232465800171742, -1.3737201163087347, -1.4174438387093602, -1.4529305498439158, -1.4789224942301442, -1.4944167631735772, -1.4986839448375824, -1.4912796325361635, -1.4720485856456718, -1.4411215230945371, -1.3989047145259579, -1.346062714315211, -1.2834947541761748, -1.2123054668720765, -1.1337707526683698, -1.0492997181946093, -0.9603937114147614, -0.8686035441455237, -0.775486033375923, -0.6825610035975629, -0.5912698742469459, -0.5029369097126323, -0.41873413540935034, -0.3396508240910917, -0.2664683344239172, -0.1997409419954249, -0.1397831450220608, -0.08666375704975535, -0.04020692124942943, -3.4728682187385985e-16], [0.0, 0.032950126910679146, 0.0615868339784887, 0.08699934030184955, 0.11040171917148184, 0.13309538301462692, 0.1564289592359359, 0.18175663053256633, 0.21039605542475864, 0.24358699831108832, 0.28245178295805295, 0.3279586393244979, 0.3808889420813104, 0.44180924188877924, 0.5110488698612221, 0.5886837546941671, 0.6745269341817285, 0.7681260722661457, 0.8687681136215231, 0.975491024584845, 1.0871023866237592, 1.202204431080477, 1.3192249361410362, 1.4364532531020617, 1.552080592955407, 1.664243589558917, 1.7710700651570788, 1.8707258601068668, 1.961461553040091, 2.041657891340254, 2.109868774987105, 2.16486068904802, 2.2056475601692895, 2.2315201184436635, 2.242068975454357, 2.237200778983901, 2.2171469711819993, 2.182464855842292, 2.134030867455672, 2.0730261252873854, 2.0009145451681802, 1.9194139653156694, 1.8304609157642802, 1.736169819580609, 1.6387875540292833, 1.5406444177371679, 1.4441026427245973, 1.3515036555866486, 1.2651153284417782, 1.1870804665588757, 1.119367755603755, 1.0637263377328199, 1.0216451035575396, 0.9943176782618683, 0.9826139474835927, 0.9870588151674508, 1.007818715172331, 1.0446962150973926, 1.0971328590323075, 1.164220200394894, 1.244718781450572, 1.3370846272458805, 1.4395026431289597, 1.549926141117766, 1.6661215750989726, 1.7857174417276866, 1.9062562059381185, 2.0252480395402572, 2.140225120163764, 2.2487952268000924, 2.34869338762688, 2.4378303851720413, 2.514337001950274, 2.576602994543298, 2.623309913103946, 2.6534570332603256, 2.666379834686889, 2.6617606410809214, 2.639631225506096, 2.6003673783997634, 2.544675628255764, 2.4735724923797573, 2.3883568125993255, 2.2905758940773984, 2.181986310464297, 2.064510362025177, 1.940189272131533, 1.811134279257162, 1.679476824690734, 1.5473190496009184, 1.4166857986320236, 1.289479281373915, 1.16743746907055, 1.0520972037318936, 0.9447628729640621, 0.8464813594835595, 0.7580238130845194, 0.679874618845809, 0.6122277529674511, 0.5549905313832019, 0.5077945708635101, 0.4700136023251028, 0.44078760597964733, 0.41905258200645046, 0.4035751324838728, 0.39299091376435175, 0.3858459261901855, 0.38063954227084956, 0.3758681367590811, 0.3700681733472627, 0.36185762310535674, 0.3499746387138411, 0.3333124847118465, 0.31094982540196503, 0.28217559611742155, 0.24650782708654864, 0.2037059484604376, 0.1537762761444782, 0.09697055654392046, 0.03377762966505513, -0.03509155039457657, -0.10872512523678245, -0.1860371972977817, -0.26579962760036935, -0.34667791417112137, -0.42727019179535547, -0.506148310989642, -0.5818998979753045, -0.6531702694787906, -0.718703077099781, -0.7773785857826757, -0.8282485488809077, -0.8705667269862674, -0.9038142070024842, -0.927718809146794, -0.9422680193844671, -0.9477150494855204, -0.9445778023078911, -0.9336307016487841, -0.9158895294916267, -0.8925895940844721, -0.8651577254549407, -0.8351787563136078, -0.804357291726475, -0.7744756967428358, -0.7473493341262928, -0.7247801617970786, -0.708509849528685, -0.7001735955090155, -0.7012558149521935, -0.7130488351416555, -0.7366156649410931, -0.772757813482557, -0.8219890146611792, -0.8845155740846948, -0.9602238966452075, -1.0486755797697196, -1.1491102739054355, -1.2604563224140883, -1.3813490024499846, -1.5101560012834483, -1.6450095835324074, -1.7838447383175462, -1.9244424455966747, -2.064477071593945, -2.2015667975557554, -2.333325906696238, -2.4574177031560036, -2.571606815410604, -2.673809645422603, -2.7621417637850967, -2.8349611192652207, -2.8909060269163653, -2.9289270199994935, -2.948311794425589, -2.9487026368388887, -2.9301059048715996, -2.892893316212269, -2.8377949973728294, -2.7658844386914767, -2.678555694410667, -2.5774933509427194, -2.4646359581950823, -2.34213377389549, -2.212301805462469, -2.077569244840761, -1.9404264761750303, -1.8033708921886353, -1.6688527813242273, -1.5392225434754585, -1.416680457627805, -1.3032301608032804, -1.200636905963305, -1.1103915492386303, -1.0336810769215325, -0.9713663235232175, -0.9239673577824581, -0.8916568280954769, -0.8742613669704522, -0.8712709604929197, -0.881855998156304, -0.9048915354192116, -0.93898813045633, -0.9825284619251594, -1.0337087999212822, -1.0905842908852215, -1.1511169317198626, -1.2132250508000149, -1.2748330852334662, -1.3339204452675513, -1.388568287991156, -1.4370030825878095, -1.4776359367679384, -1.5090967663929948, -1.530262524831279, -1.5402788618435415, -1.538574749915758, -1.5248697947082936, -1.4991741311905273, -1.4617809934508044, -1.4132522294591696, -1.3543972076479638, -1.2862457256992272, -1.2100156793331867, -1.1270763765359606, -1.038908487404795, -0.9470616990620256, -0.8531111969735877, -0.7586141172720112, -0.6650671088148621, -0.5738661089257413, -0.4862693740099306, -0.4033647171547222, -0.32604179171834, -0.2549701256852281, -0.19058345965080242, -0.1330707755680347, -0.0823742280585077, -0.03819400961675005, -3.3010474504090837e-16], [0.0, 0.031459866475203664, 0.05911014953272174, 0.08410850703458353, 0.10771763946223206, 0.13126616420025256, 0.15610747892522828, 0.18357771652462715, 0.21495391979144313, 0.25141356102243556, 0.2939964996427712, 0.3435704108669897, 0.4008006316733518, 0.46612525917534786, 0.539736203598002, 0.6215667468339799, 0.7112859917577559, 0.8083004112789411, 0.9117625239494972, 1.0205865393920348, 1.1334706365178682, 1.2489253650107042, 1.3653075002337194, 1.4808585376464811, 1.5937468886663955, 1.7021127388587423, 1.804114453999748, 1.8979753719012402, 1.9820297991981723, 2.0547670431463656, 2.1148723486859335, 2.161263679692497, 2.193123378848593, 2.2099238606350147, 2.211446633663071, 2.1977941084961885, 2.169393821334757, 2.1269948881898313, 2.0716566939191496, 2.0047300110663775, 1.9278309301243894, 1.8428081610148188, 1.7517044308183105, 1.656712850992856, 1.5601292547833563, 1.4643016090609489, 1.371577681826165, 1.2842521951059243, 1.2045147117088078, 1.1343994927452254, 1.0757385211818902, 1.0301188159367316, 0.9988450628010297, 0.9829084651469601, 0.9829625719069318, 0.999306676208849, 1.0318771992922755, 1.0802472852507787, 1.14363463733864, 1.2209174307822537, 1.310657945011628, 1.4111333746491865, 1.5203731079301233, 1.6362016076343082, 1.7562858968208213, 1.8781865428989881, 1.9994109514839182, 2.1174677280541605, 2.229920841938158, 2.3344423341540264, 2.4288623479168003, 2.5112153272705027, 2.5797813236416465, 2.633121469813676, 2.670106822934074, 2.6899399391900625, 2.6921687187655277, 2.6766922463018044, 2.6437585447531142, 2.5939543545369452, 2.528187240488174, 2.447660511682027, 2.3538416092500056, 2.2484247707446428, 2.1332889127004506, 2.010451782584671, 1.8820215147134578, 1.7501467799590815, 1.6169667449210727, 1.4845620521371656, 1.354907999068084, 1.229831030936701, 1.1109695726825368, 0.999740110619206, 0.8973092977798991, 0.8045727018645958, 0.7221406450734872, 0.6503314051880186, 0.5891718615531414, 0.5384054827655697, 0.4975073695440711, 0.4657058910125675, 0.44201028981688767, 0.4252434851539109, 0.4140791765304253, 0.4070822479923872, 0.40275139519160297, 0.39956284785673907, 0.39601403918583256, 0.3906660818328569, 0.3821839472431492, 0.36937331009875746, 0.3512131108624421, 0.32688300450016394, 0.29578499946164827, 0.25755874443046123, 0.21209008730807857, 0.15951270712299928, 0.10020280057937857, 0.03476698618514037, -0.03597623426944635, -0.11102094915890963, -0.18920358285550587, -0.269237113654816, -0.3497488463066402, -0.4293207280064204, -0.5065311289668071, -0.5799969686077697, -0.6484150570130202, -0.7106015389142254, -0.7655283736660066, -0.8123558583267894, -0.8504603002338162, -0.8794560678789588, -0.899211391393464, -0.9098574429644894, -0.9117903990430751, -0.9056663659517562, -0.8923892339361201, -0.8730917072048424, -0.849109934459373, -0.8219523313502167, -0.793263338978396, -0.7647829971029247, -0.7383033236806237, -0.7156225808478762, -0.6984985691567982, -0.6886021251666319, -0.6874720014369289, -0.6964722823752251, -0.7167534347968878, -0.7492180097220716, -0.794491903820609, -0.8529019576232648, -0.9244605163322243, -1.0088574114742217, -1.105459641849226, -1.2133188446502818, -1.331186456884091, -1.4575362780131358, -1.5905939617475748, -1.7283727926733554, -1.8687149461908394, -2.009337291972175, -2.1478806852811747, -2.28196159994811, -2.409224893844594, -2.5273964639765634, -2.6343345447062605, -2.7280784292853264, -2.806893451247241, -2.869311146951444, -2.914163631680089, -2.940611356496175, -2.9481635683297367, -2.9366909677121984, -2.9064302430599724, -2.857980352938437, -2.7922906236374363, -2.710640923894169, -2.614614366975981, -2.5060631679983683, -2.3870684469783314, -2.259894911753194, -2.1269414760369076, -1.9906889635990264, -1.8536461175154078, -1.718295172016681, -1.5870382527298903, -1.4621458488945491, -1.345708549006139, -1.2395931505987874, -1.145404147526997, -1.0644514667944465, -0.9977251749422292, -0.945877704989554, -0.9092139730689822, -0.8876895636765065, -0.8809169685249001, -0.8881796710907619, -0.908453681792945, -0.9404359518947413, -0.9825789319852299, -1.0331303971998906, -1.0901775396569002, -1.1516942318341503, -1.2155902950934205, -1.2797615668964761, -1.3421395493620545, -1.4007394408538727, -1.4537054007002195, -1.499351973631349, -1.5362007030969835, -1.563011088665659, -1.578805189008141, -1.5828853348314698, -1.5748445914576739, -1.5545697941321106, -1.5222371660094307, -1.478300714433712, -1.4234737809767368, -1.3587042902527948, -1.2851443975851355, -1.2041153723230362, -1.1170686686309736, -1.025544226072583, -0.9311271060906341, -0.8354036060120119, -0.739917998665288, -0.6461310229994864, -0.555381199878847, -0.46884996885660923, -0.38753153823821657, -0.31220821479519195, -0.24343183431142654, -0.18151175343916096, -0.12650969120431899, -0.07824152930639858, -0.036285998656672744, -3.1412832045472506e-16], [0.0, 0.030135719370387802, 0.05699982559539229, 0.08180829852056289, 0.10586138235861013, 0.13050318318698503, 0.15707987291922296, 0.18689762157186324, 0.2211813888550528, 0.26103568628892637, 0.30740837266510085, 0.36105846992837815, 0.42252888533343164, 0.49212480156345617, 0.5698983524914044, 0.6556400420312648, 0.7488771910912532, 0.8488795173396003, 0.9546717688675747, 1.0650531505147627, 1.1786231052146132, 1.2938128466893928, 1.4089218883863455, 1.5221586805564908, 1.6316843562346872, 1.7356585004450649, 1.8322857974775841, 1.9198623801383925, 1.996820703337786, 2.0617717923819954, 2.113543773278629, 2.1512156769275563, 2.1741456192351607, 2.1819925923042054, 2.174731254680768, 2.152659277453264, 2.1163969836602115, 2.0668792065333266, 2.0053394829473037, 1.9332868873545348, 1.852475993777046, 1.764870624587509, 1.6726022005805514, 1.5779236433302672, 1.483159894633795, 1.390656206090678, 1.302725412325477, 1.2215954324689884, 1.1493582454341202, 1.087921555160185, 1.0389643030031193, 1.0038970971973644, 0.9838285158829979, 0.9795381032995445, 0.9914567216959218, 1.0196547480924814, 1.0638384194598156, 1.1233544366556032, 1.1972027412821942, 1.2840571852665854, 1.3822936251521145, 1.4900247964001618, 1.605141161733347, 1.7253567856342973, 1.848259167999224, 1.9713618765276641, 2.092158751974131, 2.208178424474958, 2.3170378736502877, 2.4164937901805303, 2.504490551432414, 2.5792037070975855, 2.639077980642304, 2.68285892594179, 2.7096175324987697, 2.718767243337082, 2.7100730328281424, 2.6836523828599934, 2.6399681902158307, 2.5798138310365624, 2.5042907950890725, 2.414779478695875, 2.3129038863218336, 2.2004911330545314, 2.0795267601246796, 1.9521069703152536, 1.8203889573538568, 1.6865405416041812, 1.5526903327208494, 1.4208796182979924, 1.2930171265571515, 1.1708377321400691, 1.0558660691417519, 0.9493858873217812, 0.852415839220018, 0.7656922214191423, 0.6896590165770682, 0.6244653985269119, 0.5699706753205885, 0.5257564592513688, 0.4911456732579148, 0.4652278341494387, 0.446889898985461, 0.4348518255009849, 0.42770588402205134, 0.4239586696445222, 0.42207470170264133, 0.4205204642080214, 0.41780773675503546, 0.41253509039425446, 0.4034264764690429, 0.3893659169757629, 0.3694274105522365, 0.3428992960047546, 0.30930246207827594, 0.2684019542109653, 0.22021170216779634, 0.1649922723172695, 0.10324173033437385, 0.035679879664692576, -0.03677368638296556, -0.11302711990756456, -0.19184869637872956, -0.27190316412555576, -0.3517910900708142, -0.4300901473410603, -0.5053972383352299, -0.5763703231621978, -0.6417688286815763, -0.7004915475913929, -0.7516109992634489, -0.7944033127867488, -0.8283728057276429, -0.8532705666246899, -0.8691065018356865, -0.8761544742140666, -0.8749503380179495, -0.8662828569950392, -0.8511776761398009, -0.8308746975526401, -0.8067993825941966, -0.7805286617679772, -0.7537522764345332, -0.7282304989206079, -0.7057492766965812, -0.6880739194928488, -0.6769024935906606, -0.6738201038277448, -0.6802552305986675, -0.6974392465367677, -0.726370166602773, -0.7677815876485216, -0.8221176515148281, -0.8895147223141375, -0.9697903072339334, -1.0624395749213815, -1.166639640574977, -1.2812615968253303, -1.4048900790227175, -1.5358499673717672, -1.6722396510765338, -1.8119701156842178, -1.9528089682261638, -2.092428389212032, -2.2284558991864114, -2.35852675296584, -2.480336728741946, -2.5916940631640712, -2.6905692977712823, -2.775141846451092, -2.8438421669437814, -2.8953885200552043, -2.92881742578204, -2.9435070729720527, -2.9391931048779663, -2.9159763830037364, -2.874322521618052, -2.8150531806063688, -2.739329300200219, -2.6486266527944022, -2.5447042698723594, -2.4295664715567433, -2.3054193783582306, -2.1746229156115064, -2.0396394276782774, -1.9029800986766015, -1.7671504273336527, -1.6345960243335893, -1.5076499907575696, -1.3884830961502381, -1.2790579054011724, -1.181087906718983, -1.096002570894923, -1.0249191278091692, -0.9686216832740467, -0.9275481218355095, -0.9017850534196178, -0.8910708683146695, -0.8948067706537486, -0.9120754700542292, -0.9416670290263344, -0.9821111946127288, -1.0317153905707452, -1.0886074149381628, -1.1507817801964244, -1.2161485520322082, -1.2825834898137625, -1.3479782685539574, -1.4102895688086152, -1.4675858573932559, -1.518090746998134, -1.5602219150341519, -1.5926246789794403, -1.6141994641408972, -1.6241225565880195, -1.621859705106673, -1.6071723170607568, -1.580116179507069, -1.5410328241246487, -1.4905338378278368, -1.4294785957738438, -1.3589460555124067, -1.2802013962485315, -1.194658412017558, -1.1038386689407174, -1.0093285121667697, -0.9127350557920497, -0.8156423078665459, -0.7195685721411605, -0.6259262288290471, -0.5359849294044111, -0.45083914710561324, -0.37138090775862603, -0.29827838779629895, -0.2319609114393562, -0.1726107108748573, -0.1201616361933805, -0.07430482032547978, -0.03450112285696434, -2.995119200007167e-16], [0.0, 0.028990705596795053, 0.05527715278241179, 0.08012297446581064, 0.10485450734970225, 0.13081945889377586, 0.15934481177732746, 0.19169509742984814, 0.22903216266703352, 0.2723775170634699, 0.3225782843084941, 0.38027769003040973, 0.44589090370399614, 0.5195869161538428, 0.6012769802457621, 0.6906099744868995, 0.7869748716545661, 0.8895103117169972, 0.9971210948075135, 1.1085012305016768, 1.2221630086669861, 1.336471399042305, 1.4496829454802018, 1.559988200054819, 1.6655566450990051, 1.764582980201424, 1.8553336081329792, 1.9361921397526254, 2.0057027536101746, 2.0626102909249986, 2.105896039849805, 2.134808262696088, 2.1488866437054357, 2.1479799799950268, 2.1322566009502744, 2.102207177600618, 2.0586397690668568, 2.0026671434401893, 1.93568660074748, 1.8593527112657966, 1.7755435587696005, 1.6863212409435417, 1.5938875241185801, 1.5005356730649915, 1.4085995756980614, 1.3204013547140312, 1.238198701527582, 1.164133181288135, 1.100180740804495, 1.0481056042484271, 1.009418665617194, 0.9853413839065802, 0.9767760592420291, 0.9842832189083499, 1.0080666749141507, 1.0479666334776883, 1.1034610460243717, 1.1736751955790483, 1.2573993165789696, 1.3531138548935964, 1.4590217928724367, 1.573087295984396, 1.6930797871601084, 1.8166224259658188, 1.9412438653625033, 2.064432081572508, 2.1836890243607128, 2.2965848169980076, 2.400810247734471, 2.494226337440455, 2.5749098401076322, 2.6411936323568317, 2.6917010725217803, 2.7253735562066255, 2.7414906598533673, 2.7396824427635313, 2.719933666809989, 2.6825798871279187, 2.628295561643038, 2.5580745176296245, 2.473203294951024, 2.3752280538073585, 2.2659158856193837, 2.147211495468599, 2.0211903301703567, 1.8900093050578743, 1.755856333040791, 1.6208998803201298, 1.4872397638732238, 1.3568603667925447, 1.2315873798313555, 1.113049082842435, 1.0026430606239585, 0.901509107037837, 0.8105089126966734, 0.7302129590168056, 0.6608948593346096, 0.6025332006380005, 0.5548207519457493, 0.517180722144317, 0.4887895757178088, 0.4686057536037269, 0.45540350235989097, 0.4478108914843414, 0.4443509991140632, 0.4434851728650326, 0.44365722703179095, 0.443337420804268, 0.441065074919995, 0.4354887258535748, 0.4254027861299557, 0.40977977481653866, 0.3877973012342789, 0.35885912437629025, 0.32260976687000237, 0.2789423315814303, 0.22799934683310355, 0.17016664817333088, 0.10606048607797391, 0.03650822528689615, -0.03747683179182485, -0.11472581225993563, -0.19394900991100017, -0.27377405772592733, -0.35278651089108565, -0.4295717517493522, -0.5027570922251129, -0.5710529422486639, -0.633291934741167, -0.6884649482737484, -0.7357530463305656, -0.7745544552446416, -0.8045058287567823, -0.8254971926167678, -0.8376801240499853, -0.841468894195237, -0.8375344824187229, -0.8267915551695093, -0.8103786841251477, -0.7896322541798718, -0.766054676899256, -0.7412776752125046, -0.7170215365123712, -0.6950513406201659, -0.6771312534349067, -0.6649780343239529, -0.6602149339047566, -0.664327158003343, -0.6786200431784662, -0.7041810299321768, -0.7418464329699567, -0.7921738956976406, -0.8554212812564455, -0.9315325980815864, -1.0201313879949934, -1.1205218233766843, -1.2316975714662532, -1.3523582929727933, -1.4809334536364056, -1.6156129458563933, -1.754383847487417, -1.8950724906362406, -2.0353908786195976, -2.172986377543297, -2.3054935230477507, -2.4305867248207518, -2.546032623002267, -2.6497408523734713, -2.7398120022660173, -2.814581621733238, -2.872659209252836, -2.9129612419450153, -2.9347374382158224, -2.9375896065229297, -2.921482607769353, -2.886747145421815, -2.8340742912931143, -2.764501851309171, -2.6793928697226987, -2.5804067574092917, -2.469463705529781, -2.348703205685783, -2.220437637840722, -2.0871020043150184, -1.9512009792445466, -1.8152545058065597, -1.6817432067444016, -1.5530548764693624, -1.4314332952358675, -1.31893054827573, -1.2173639467681336, -1.1282785352377147, -1.052916034180684, -0.9921909107567358, -0.9466740980829703, -0.9165846992514665, -0.901789820182496, -0.9018124805187714, -0.9158473587256365, -0.9427839410971803, -0.9812364690196662, -1.0295799188712955, -1.0859911082156355, -1.1484939038685156, -1.2150074148151553, -1.283395988022439, -1.3515197894413713, -1.4172847467146767, -1.4786906543412575, -1.5338762956075818, -1.581160517059223, -1.6190782985485748, -1.6464109922195238, -1.662210053873276, -1.6658137562164912, -1.6568565513509264, -1.6352709350664612, -1.6012818534189377, -1.5553938780249406, -1.4983715558620034, -1.4312135076733816, -1.3551210021750395, -1.2714618673711944, -1.1817307121070264, -1.087506517790434, -0.9904087198967803, -0.892052930011301, -0.7940074510604331, -0.6977517110661706, -0.6046376849890379, -0.5158552914800023, -0.43240264378834486, -0.35506190444060554, -0.284381344933923, -0.22066404836176287, -0.16396351876861165, -0.11408628053718305, -0.07060136882835971, -0.032856432642624465, -2.86396857429828e-16], [0.0, 0.028036121486305535, 0.05395968938509014, 0.07907086691239305, 0.10471037026396803, 0.1322175604720771, 0.16288841180106498, 0.19793448823670975, 0.23844403538322562, 0.2853462423727391, 0.3393796485258239, 0.4010655644740418, 0.47068724989752014, 0.5482754431432717, 0.6336006754639728, 0.7261726285408592, 0.8252466127124352, 0.9298370594932167, 1.038737740175993, 1.150548247165017, 1.2637061106248606, 1.3765237742184437, 1.4872295239410154, 1.5940113566573686, 1.6950626926859464, 1.7886287817908073, 1.8730526257071782, 1.9468192435897005, 2.008597139549691, 2.0572758930174766, 2.0919988815864667, 2.1121902601403697, 2.117575456673727, 2.1081946009630546, 2.0844084733219246, 2.046896742878968, 1.996648453667826, 1.9349449076518932, 1.8633352819042606, 1.7836054978614795, 1.6977410293787396, 1.6078844890282993, 1.5162889648859852, 1.4252681896100148, 1.3371447071672093, 1.254197257974839, 1.178608629063246, 1.112415211412077, 1.057459471903534, 1.0153464831463799, 0.9874055622577735, 0.9746579517396737, 0.9777913346828839, 0.9971418160722405, 1.0326838258330746, 1.084028211722834, 1.1504285957877294, 1.2307958715997094, 1.3237205256470752, 1.4275022797937518, 1.540186377191129, 1.6596056756751727, 1.7834275743696395, 1.9092046843119295, 2.0344280652184485, 2.1565817901661455, 2.2731975694468667, 2.3819081648822635, 2.4804983564508727, 2.5669522834119296, 2.6394960707178052, 2.696634766205335, 2.7371827520227456, 2.760286951594755, 2.765442327280108, 2.752499349472336, 2.7216633106917594, 2.673485553499713, 2.608846874065516, 2.5289335492263043, 2.4352066093723166, 2.32936513822843, 2.2133045197443924, 2.08907066849728, 1.9588113704680372, 1.8247259236351943, 1.689014301080773, 1.5538270624988857, 1.4212172131530538, 1.2930951532013495, 1.171187776378493, 1.0570026674543518, 0.951798215471566, 0.8565603078533666, 0.7719861028930122, 0.6984751990962164, 0.6361283338283672, 0.5847535553647137, 0.5438796264456099, 0.5127762384235063, 0.4904804474924056, 0.4758285924584489, 0.4674928207898972, 0.46402123953379804, 0.46388062279289605, 0.4655005498711536, 0.4673178192841869, 0.4678199842368319, 0.4655868848035567, 0.4593291100863098, 0.4479224085358623, 0.4304371742024006, 0.40616226810912937, 0.3746225838542192, 0.33558993111729846, 0.2890869857881634, 0.23538423650074156, 0.1749900398500286, 0.10863407586770231, 0.03724466689088886, -0.038079417566583326, -0.11610190397819022, -0.19548581644157403, -0.27483314651020885, -0.3527263256658127, -0.42777038695499936, -0.498634682969483, -0.5640930370883186, -0.6230612434954448, -0.6746308979811391, -0.7180986342736856, -0.7529899573066849, -0.7790770024830137, -0.796389705191855, -0.8052200336684723, -0.8061191165080426, -0.7998872792633265, -0.7875571879506466, -0.7703704763248335, -0.749748403928972, -0.72725724886211, -0.7045692789442244, -0.683420263923866, -0.6655645865144582, -0.6527290788956474, -0.6465667520648618, -0.6486115969587675, -0.6602356182003147, -0.682609214018254, -0.7166659404174054, -0.7630725958390179, -0.82220543679229, -0.8941331883127664, -0.9786073491895335, -1.0750601147176262, -1.1826100536305546, -1.3000754854377026, -1.4259953143370272, -1.5586568909016918, -1.6961302974403143, -1.836308291666045, -1.9769510001027797, -2.1157343310935524, -2.2503009804146203, -2.378312832793301, -2.4975035218683703, -2.6057299003976957, -2.7010211921500082, -2.781624646511445, -2.8460465952485765, -2.893087916244323, -2.921873038842112, -2.9318717765732303, -2.922913441851533, -2.8951928796095596, -2.8492682483939906, -2.7860505734806904, -2.706785292340514, -2.6130262035198664, -2.506602411047922, -2.3895790234337246, -2.2642125151028827, -2.1329017851194094, -1.9981360501523864, -1.8624407833946555, -1.728322956709677, -1.5982168585726606, -1.4744317450263007, -1.3591025352823982, -1.254144688900111, -1.1612142995056132, -1.0816743132961082, -1.0165676322100134, -0.9665976952865268, -0.9321169514614207, -0.9131234472687915, -0.9092655582835938, -0.9198546984044201, -0.9438856509925108, -0.9800639850824763, -1.0268398527583036, -1.082447314397417, -1.1449482104345696, -1.2122794946641573, -1.2823028673547583, -1.3528554983970429, -1.4218006124387002, -1.4870767198336745, -1.546744318860283, -1.5990289649203722, -1.6423596994935357, -1.6754019530001807, -1.6970841783428816, -1.7066176321462687, -1.703508894571655, -1.6875649016863397, -1.6588904521407755, -1.6178783376672494, -1.5651924299890132, -1.5017442305739734, -1.4286635499771796, -1.347264126332879, -1.2590051143665164, -1.1654494741173362, -1.0682203600166338, -0.9689566543419751, -0.869268803355873, -0.7706960993608063, -0.6746665079187082, -0.5824600677735493, -0.4951767934547983, -0.41370988964762523, -0.3387249452947731, -0.2706456176508041, -0.20964614616120777, -0.15565085741795054, -0.10834064008410323, -0.06716618720825843, -0.031367627363189175, -2.749099969365357e-16], [0.0, 0.027281427490450743, 0.053061084893357764, 0.07866419200261046, 0.10543397850464106, 0.13468956203697446, 0.16768434410944308, 0.2055660456498208, 0.2493394631621487, 0.2998329578985898, 0.35766959575867857, 0.4232437372163853, 0.49670373740807955, 0.5779412600911282, 0.6665875394394536, 0.762016744854471, 0.8633564206459803, 0.9695047892064246, 1.079154527796516, 1.1908224598020798, 1.3028844456076933, 1.4136146200264823, 1.521228006059298, 1.6239254416417195, 1.7199396893882608, 1.807581560916558, 1.885284878184093, 1.951649114720488, 2.005478609274689, 2.0458173220740665, 2.071978207764798, 2.0835664066658457, 2.0804956041223934, 2.0629970728690052, 2.031621091357794, 1.987230617591737, 1.930987288525138, 1.864330004840854, 1.78894654518487, 1.70673882815569, 1.619782600170305, 1.5302824687687024, 1.4405233204291736, 1.352819256536234, 1.2694612483703476, 1.1926647501428067, 1.1245185171619991, 1.066935853911693, 1.0216094646165164, 0.9899709979716532, 0.9731562700363499, 0.971977017409772, 0.9868998798967988, 1.018033141624969, 1.0651215761167474, 1.1275495486070648, 1.2043523325976346, 1.2942354020343354, 1.3956012703462566, 1.5065832675289161, 1.6250854808791582, 1.7488279379324014, 1.875395985199312, 2.0022927164932844, 2.126993232412419, 2.2469994696437667, 2.3598943262311014, 2.4633938270822613, 2.5553961223312047, 2.6340261885162444, 2.69767520698302, 2.7450337229003323, 2.7751178386208655, 2.7872878631398947, 2.781259020984848, 2.757104014562534, 2.7152474291348265, 2.65645216442122, 2.581798266585537, 2.492654714433076, 2.3906448796478825, 2.277606528814442, 2.1555473612221854, 2.026597178012459, 1.8929578526763944, 1.7568523185018412, 1.6204738042648208, 1.4859365349729887, 1.35522907024627, 1.2301713801479113, 1.1123766588452582, 1.0032187529247831, 0.9038059366444654, 0.8149616045228795, 0.7372122765059201, 0.6707831269051613, 0.6156010599634016, 0.5713051669664986, 0.53726421695802, 0.5126006598606333, 0.49622046145158755, 0.4868479481099787, 0.48306471902854653, 0.4833515876015415, 0.4861324442904442, 0.48981889209021423, 0.49285449372050816, 0.4937574870674629, 0.49116087168416867, 0.48384884308172815, 0.47078865117638713, 0.45115708202921606, 0.42436090477330723, 0.39005078472280613, 0.34812833504546853, 0.2987461586991728, 0.24230091503179252, 0.17941962689077942, 0.11093961968770097, 0.037882649167659925, -0.03857607453970631, -0.11714312647922046, -0.19644541904908513, -0.27507102938647177, -0.3516112047738653, -0.42470241727848773, -0.49306733621677074, -0.5555536134775135, -0.6111694315892385, -0.659114846311195, -0.6988080624135475, -0.7299059105091587, -0.7523179410616553, -0.7662137152938397, -0.7720230475378319, -0.7704291351984339, -0.7623546963604052, -0.748941416513947, -0.73152318030848, -0.7115937272500931, -0.6907695176894935, -0.6707487235446293, -0.6532673636839065, -0.6400536840400864, -0.6327819352398969, -0.6330267244097587, -0.64221911216279, -0.6616055906315252, -0.692211014566489, -0.734806466473169, -0.7898829206909859, -0.8576314330382674, -0.9379304255273162, -1.0303404635401134, -1.134106739976953, -1.248169291752588, -1.371180783289543, -1.5015315040667019, -1.6373810474784363, -1.776695970716457, -1.917292584281902, -2.056883888848878, -2.1931295698216267, -2.3236878787704907, -2.446268178068992, -2.5586829018654162, -2.6588976936565274, -2.7450785180923942, -2.8156346113901107, -2.8692562293044994, -2.9049462717451195, -2.922045005956891, -2.9202472722522415, -2.899611733673831, -2.8605619193765075, -2.803879006367701, -2.7306864807974223, -2.6424270134563566, -2.5408320698101026, -2.427884948242963, -2.305778096980311, -2.176865696580861, -2.0436126076143797, -1.9085408694210213, -1.7741749935859967, -1.6429873235593366, -1.5173447290365252, -1.3994578703762064, -1.2913342052942753, -1.1947358188968646, -1.111143041042358, -1.0417246749309355, -0.9873155011486622, -0.9484015460558735, -0.925113416701604, -0.9172278109356576, -0.9241771158072675, -0.9450668144582958, -0.9787002362409827, -1.023610011227472, -1.0780954328433132, -1.1402647948589073, -1.2080816547237512, -1.279413886962393, -1.3520843301581202, -1.4239218003243796, -1.4928112428699154, -1.556741824822255, -1.6138518276650322, -1.6624692875262441, -1.7011474413061352, -1.7286941718077002, -1.7441947986304494, -1.7470277306405397, -1.7368726759978201, -1.71371129249705, -1.6778203497065856, -1.6297576603662087, -1.5703412171177953, -1.5006221374636488, -1.4218521707561633, -1.335446652303145, -1.2429438981074497, -1.1459621167058285, -1.046154970030524, -0.9451669418797305, -0.8445896698630427, -0.7459203647361422, -0.6505233807370365, -0.5595959134749279, -0.47413869036152295, -0.3949323853832349, -0.32252033860070606, -0.25719799499077933, -0.19900930133382616, -0.1477501182641035, -0.1029785219484135, -0.06403169076779626, -0.0300489013834574, -2.6516250255193145e-16], [0.0, 0.0267341539905712, 0.0525909419830553, 0.0789089220583691, 0.10702192878764188, 0.13821710132312182, 0.1736940671999282, 0.2145263841092456, 0.26162628492425294, 0.3157136873621495, 0.3772903209529756, 0.4466196931889628, 0.5237134671357632, 0.60832465816426, 0.6999478819562153, 0.7978267039747537, 0.9009679567656835, 1.0081627104149595, 1.118013407815002, 1.2289665144939748, 1.3393498867547262, 1.4474139354795672, 1.551375559423522, 1.6494637438154414, 1.7399656696520576, 1.8212721575573876, 1.891921278120344, 1.9506389981111194, 1.9963757980696, 2.028338289898731, 2.0460149810455817, 2.0491954717527494, 2.0379825302989376, 2.012796664237116, 1.9743729891251156, 1.9237503856022604, 1.8622531262156854, 1.7914653404202516, 1.713198865022189, 1.629455193556725, 1.5423823875346594, 1.454227941419308, 1.367288698359538, 1.2838589924437678, 1.2061782435375594, 1.1363792513058235, 1.0764384252124042, 1.0281291472955805, 0.9929793952405652, 0.9722346563362784, 0.9668270406217638, 0.9773513568336083, 1.0040487511500173, 1.0467983301497885, 1.1051170001974264, 1.1781675602269974, 1.2647748883775738, 1.363449869918743, 1.4724205291000436, 1.5896696554699425, 1.7129780600358435, 1.839972462162169, 1.9681768976088985, 2.095066454291697, 2.218122087238666, 2.334885239165215, 2.443010998691493, 2.540318564337153, 2.624837848152245, 2.6948511465612355, 2.74892892540601, 2.785958908342367, 2.805167819186193, 2.8061353055657055, 2.7887997589873113, 2.7534559405741, 2.7007445175443285, 2.631633808185441, 2.5473942179526725, 2.449566021884603, 2.339921304594796, 2.220421004894696, 2.09316812435868, 1.9603582451730293, 1.8242285603819262, 1.6870066478210735, 1.550860217009541, 1.4178490261964027, 1.2898801055136786, 1.1686673333731183, 1.055696299141214, 0.9521952486330506, 0.8591127535291615, 0.7771025753472287, 0.7065160133646535, 0.6474018384168129, 0.5995137254621712, 0.5623249119106023, 0.5350496305671888, 0.5166707000598435, 0.5059725058917443, 0.5015784754714898, 0.5019920438027142, 0.5056400255548209, 0.5109172559345913, 0.5162313383867763, 0.5200463421973871, 0.5209243273459171, 0.5175636365103832, 0.5088329833236706, 0.4938004794975459, 0.47175687835264557, 0.4422324651659808, 0.40500719167416077, 0.36011382880425685, 0.30783409375747367, 0.24868789032730673, 0.1834159801637152, 0.1129565730715695, 0.03841648204422645, -0.038962370404954524, -0.11784018750176702, -0.19681927076436578, -0.27448565419217685, -0.3494512807034713, -0.4203955864519687, -0.48610537280501404, -0.5455118887075882, -0.5977241168167711, -0.642057353400201, -0.6780562921250722, -0.7055119625020175, -0.724472031352735, -0.7352441462729963, -0.7383921793630069, -0.7347254129714644, -0.7252808922122835, -0.7112993469345543, -0.6941952541473917, -0.6755217663471758, -0.656931367831553, -0.640133236418212, -0.626848379051321, -0.6187636742105703, -0.6174859901364669, -0.6244975546550596, -0.6411137295622448, -0.6684442905874219, -0.70735923410236, -0.7584600258769435, -0.8220570778652551, -0.8981540893798199, -0.9864397227385692, -1.0862869046302013, -1.196759857443819, -1.3166287742644045, -1.4443918618634108, -1.5783042925097448, -1.7164134323541118, -1.8565995558122461, -1.9966211157491331, -2.1341635218506907, -2.266890287324562, -2.3924953393448156, -2.5087552531181583, -2.6135801640583582, -2.705062137524421, -2.781519830373362, -2.841538361932198, -2.8840034219315465, -2.9081287768357105, -2.9134764906275095, -2.8999693477243267, -2.8678951501555363, -2.817902753942257, -2.7509899060992042, -2.6684831390424177, -2.572010168675235, -2.4634654214189644, -2.3449694795878435, -2.218823379776932, -2.0874588217920502, -1.953385443106937, -1.8191363835099303, -1.6872134048046268, -1.5600328401841752, -1.4398736269772963, -1.3288286253903239, -1.2287603459028529, -1.1412621010832429, -1.0676254663996425, -1.0088147823303724, -0.9654492604576193, -0.9377930734135854, -0.9257536170116366, -0.928887937318222, -0.9464171205792149, -0.9772482545572628, -1.0200033905740569, -1.073054770737389, -1.134565438459996, -1.2025342259782779, -1.2748440131402508, -1.349312079620105, -1.423741329621599, -1.4959711550256083, -1.5639267200493494, -1.6256654973011868, -1.6794199603890028, -1.7236354400244274, -1.7570022762630493, -1.7784815459482382, -1.7873238078949831, -1.7830804847573567, -1.7656076854551892, -1.735062460877225, -1.6918916736275866, -1.636813845168958, -1.5707945163144656, -1.4950158153649524, -1.4108410683772958, -1.319775404641964, -1.223423404549277, -1.1234449043561416, -1.0215101113238803, -0.9192551923911805, -0.818239479815067, -0.7199053886354428, -0.6255420646942201, -0.5362536802554662, -0.4529331696533345, -0.3762420530355325, -0.30659683585910313, -0.24416229941680553, -0.18885181770742007, -0.1403346529781079, -0.09805000089884644, -0.06122738117091291, -0.028912804855846266, -2.5724874122318156e-16], [0.0, 0.026399826105570016, 0.05255471841132148, 0.07980471934335819, 0.10946242811055305, 0.1427715417940938, 0.18086718078457992, 0.2247390717805102, 0.27519858884945847, 0.332850554551019, 0.3980705813043677, 0.47098859111769054, 0.5514789930589178, 0.6391578264374264, 0.7333869979079788, 0.8332855571396247, 0.937747772953486, 1.0454675945496557, 1.1549689151098514, 1.2646409019307994, 1.3727775222158634, 1.4776202801837417, 1.5774030921629552, 1.6703981641413035, 1.7549617024752122, 1.8295782840714834, 1.8929027375364418, 1.9437984410091977, 1.9813710243938882, 2.0049965715214397, 2.0143435487969428, 2.009387837931935, 1.9904204177235727, 1.9580474194117936, 1.9131824674950724, 1.8570314083855175, 1.7910697182163353, 1.7170130637887058, 1.63678166251507, 1.5524592439935936, 1.4662475536102075, 1.3804174538484228, 1.297257768879608, 1.2190230802157898, 1.1478817141202282, 1.0858651641947796, 1.0348201649469442, 0.9963645747804629, 0.9718481410818863, 0.9623191079238497, 0.9684974910581515, 0.9907556885991152, 1.0291069228777334, 1.0832018235711607, 1.1523332688826802, 1.2354494049670872, 1.3311745687527565, 1.4378376505586172, 1.5535072550456277, 1.6760328564181077, 1.8030910003702776, 1.932235484557928, 2.0609503543116676, 2.186704483214795, 2.30700647068091, 2.419458581693641, 2.521808477576365, 2.611997540455987, 2.6882046766466416, 2.748884593479919, 2.7927996774651564, 2.819044755809077, 2.8270641944823685, 2.8166609700036687, 2.787997544419695, 2.741588568896141, 2.67828563611614, 2.5992544905645905, 2.50594528416191, 2.400056628268667, 2.2834943378524164, 2.158325886097798, 2.026731685011717, 1.8909543773137734, 1.753247365476947, 1.6158238142840662, 1.4808073435245868, 1.350185578051605, 1.2257676446598336, 1.109146601137094, 1.0016676550371955, 0.9044028814530313, 0.8181329840664873, 0.7433364661533606, 0.6801863924662707, 0.6285547336385728, 0.588024096655441, 0.5579064626934567, 0.5372683817490715, 0.5249619162036923, 0.5196604866800937, 0.5198986566337542, 0.5241147999431836, 0.5306955305419633, 0.5380207364210977, 0.5445080529571428, 0.5486556325880787, 0.5490821187271319, 0.5445628101169026, 0.5340611055394621, 0.5167544452365862, 0.4920541113162445, 0.4596184111012398, 0.41935894069723606, 0.3714398066173409, 0.3162698665187583, 0.25448823134242393, 0.1869434458113265, 0.11466692791963495, 0.03884139659444194, -0.03923485361983889, -0.11818686449481867, -0.19660406367692196, -0.27308234721373803, -0.3462660631025164, -0.4148887657015187, -0.4778116416677001, -0.534058567175009, -0.582846842045165, -0.6236127569299763, -0.6560312820424439, -0.6800293168115732, -0.6957921054324775, -0.7037625994241888, -0.7046337305475889, -0.6993337411717075, -0.6890048997608239, -0.6749761020130673, -0.6587300189262095, -0.6418655976082152, -0.6260568452989422, -0.6130089286276404, -0.6044126959746754, -0.6018987789503663, -0.6069924481541747, -0.621070387962115, -0.645320515275713, -0.6807058988541965, -0.7279337406584759, -0.7874302608512768, -0.8593221866313329, -0.9434253853867395, -1.0392410086511001, -1.1459593293187949, -1.2624712650645649, -1.3873873906061749, -1.5190640550666443, -1.6556360428663728, -1.7950550517368, -1.9351331137144248, -2.073589958051826, -2.2081032120679307, -2.3363602596644575, -2.4561105295176926, -2.5652169670713056, -2.661705456931047, -2.743811004871625, -2.8100195604430556, -2.8591044604225044, -2.8901565977320085, -2.9026075669459708, -2.8962452026099124, -2.8712211062866855, -2.828049948177844, -2.7676005247195117, -2.6910787499639888, -2.600002951045133, -2.4961720218939316, -2.3816271601347574, -2.2586080655849305, -2.12950461125355, -1.996805105956782, -1.863042348994082, -1.730738729781558, -1.602351647636916, -1.4802205185186232, -1.3665165966517332, -1.2631967705842093, -1.1719623969917465, -1.0942241138472368, -1.0310734303785964, -0.9832617280872303, -0.9511871289843572, -0.9348894984802708, -0.9340536556450695, -0.9480206676031047, -0.9758069124057277, -1.016130410533861, -1.0674437536906047, -1.1279728049131024, -1.1957602099999678, -1.2687126500416488, -1.3446506810894259, -1.4213599516834603, -1.4966425633557667, -1.568367343870777, -1.6345178376582632, -1.693236881683976, -1.742866726230669, -1.7819837763884832, -1.8094271685286223, -1.8243205531646718, -1.8260866274453955, -1.8144541427699363, -1.7894573011209713, -1.751427642989358, -1.700978715511545, -1.6389839870544085, -1.5665486395691146, -1.4849760185256842, -1.395729648485116, -1.300391827230423, -1.2006198903160137, -1.098101289012545, -0.9945086467270056, -0.8914559515976801, -0.7904570063712528, -0.692887191865967, -0.5999495090160609, -0.5126457490455089, -0.4317535047016126, -0.35780958118600464, -0.2911001973853672, -0.23165819049963404, -0.17926725469744667, -0.1334730616224814, -0.09360093205877325, -0.058779558355424706, -0.027970120602576153, -2.5124535087658795e-16], [0.0, 0.026281908277714323, 0.05295366985326224, 0.08134493223987314, 0.11273539782232518, 0.14831423666498675, 0.18914189743652005, 0.23611535132413877, 0.2899377159789246, 0.3510930942652949, 0.4198273287086642, 0.4961352204183323, 0.5797545947424524, 0.6701674191895256, 0.7666079966884148, 0.8680780736679949, 0.9733685223641628, 1.0810870847696563, 1.1896915060981332, 1.2975272425994495, 1.402868805691199, 1.50396370481584, 1.599077877767296, 1.6865414513858723, 1.7647936587321873, 1.8324257516313933, 1.888220789600812, 1.931189256676051, 1.9605995548597785, 1.9760025444906422, 1.9772494448106976, 1.9645025689014213, 1.9382385420098034, 1.899243836789458, 1.8486026485794596, 1.7876773238409394, 1.7180817405528352, 1.641648216114479, 1.560388681706046, 1.4764510080311162, 1.3920714922442117, 1.3095246164998897, 1.2310712623910922, 1.158906610672492, 1.0951089708938229, 1.0415907704385914, 1.0000528872623677, 0.9719434363818306, 0.9584220186264141, 0.960330313750574, 0.9781697517527048, 1.0120868297352599, 1.0618664609017177, 1.1269335517067476, 1.2063628073901924, 1.298896569900409, 1.402970300330671, 1.5167451351345307, 1.6381467760154416, 1.764909821638588, 1.894626518895447, 2.0247988055501964, 2.152892437298706, 2.27639194249934, 2.3928551283043817, 2.499965873104118, 2.5955839818154534, 2.6777909515787655, 2.7449305941286393, 2.7956435850561423, 2.8288951563461704, 2.843995313375046, 2.8406111369586218, 2.8187709206641753, 2.778860088807548, 2.7216090365868526, 2.6480732258767574, 2.5596060536476632, 2.457825180324925, 2.3445731585352014, 2.2218733349000654, 2.0918821056510035, 1.9568386882725397, 1.8190136242099677, 1.6806572506908095, 1.5439493724271833, 1.4109513266588922, 1.2835615686740716, 1.1634758113279515, 1.052152633563707, 0.9507853325255539, 0.8602806350797129, 0.7812447114082317, 0.7139767501433342, 0.6584701658361857, 0.6144213200980883, 0.5812454522175576, 0.5580993380390359, 0.5439100317609366, 0.5374088981153287, 0.5371700157409419, 0.5416519295478952, 0.5492416529933523, 0.55829977228154, 0.5672054847066981, 0.5744004130812755, 0.5784300771032425, 0.5779819695553979, 0.5719192786333458, 0.5593094150478775, 0.5394466408255273, 0.5118682524025459, 0.4763639397048471, 0.4329781211313582, 0.38200523718805235, 0.3239781683221061, 0.25965012065333726, 0.1899704922876347, 0.11605538845387026, 0.039153591901703234, -0.03939108765734146, -0.11818006775240684, -0.19580176633240423, -0.2708737697795473, -0.3420842610186845, -0.4082315915377204, -0.46826092837598327, -0.5212969818809083, -0.5666719203996889, -0.6039477015356057, -0.6329321930495652, -0.6536886163107601, -0.6665380173657751, -0.6720546508580504, -0.6710543456376743, -0.6645761033123798, -0.6538573575843929, -0.6403034885156225, -0.6254523376376517, -0.61093460320395, -0.5984311064556944, -0.5896280066663102, -0.5861711026845045, -0.5896203901223027, -0.6014060453568233, -0.6227869799891119, -0.6548130529266363, -0.6982919431488822, -0.7537615764920698, -0.8214688671072654, -0.9013553818428348, -0.9930503674125659, -1.0958713999774297, -1.2088327291378262, -1.330661197945597, -1.4598194321200064, -1.5945358098722309, -1.7328405531350275, -1.8726071258202206, -2.011597988873319, -2.1475136487808837, -2.278043848674546, -2.400919691502307, -2.5139654544560988, -2.6151488537844223, -2.7026285493679088, -2.7747977383328695, -2.8303227751313704, -2.8681758698366946, -2.8876610541520114, -2.8884327624906274, -2.8705065496407984, -2.8342616527545843, -2.780435299173774, -2.71010885821199, -2.624686129660434, -2.5258642497298514, -2.415597871796047, -2.2960574403689424, -2.1695825182209014, -2.0386312451332067, -1.9057270993534194, -1.7734041973391672, -1.6441524021220522, -1.520363514811667, -1.404279797277811, -1.2979460175499884, -1.2031661243462641, -1.121465545474689, -1.0540599693771473, -1.0018313131249468, -0.965311407544178, -0.944673745069637, -0.9397334429213414, -0.9499553779803074, -0.9744702550963121, -1.012098182231264, -1.061379148407933, -1.1206096382017108, -1.1878844734093632, -1.2611428520042398, -1.3382174594321368, -1.4168854599748315, -1.4949201378815398, -1.5701419500910971, -1.6404677747433503, -1.7039571916657081, -1.758854711249624, -1.8036269745378593, -1.8369940772198101, -1.8579543202994508, -1.8658018566856955, -1.8601368816885313, -1.8408682019221552, -1.8082082067719505, -1.7626604546618847, -1.7050002681987304, -1.6362489033714773, -1.5576420141271639, -1.470593270988988, -1.3766541075659204, -1.2774706590220477, -1.1747390196537526, -1.0701599811706344, -0.9653944183167875, -0.8620204640645834, -0.7614935634608138, -0.6651104147214083, -0.573977700453555, -0.48898638365933167, -0.41079219572942477, -0.3398027807322268, -0.27617178608898624, -0.21980000862357485, -0.17034352157818217, -0.12722852713812446, -0.08967250489027649, -0.056711063852684616, -0.027229758370786658, -2.472104830677019e-16], [0.0, 0.026381769213302823, 0.05378483429113204, 0.08351665392825176, 0.11681265980530947, 0.15479689224477444, 0.19844562736306048, 0.24855498329475217, 0.30571339086518784, 0.370279689015338, 0.44236746049081915, 0.5218360624467642, 0.6082886337515604, 0.7010771802606794, 0.799314655739392, 0.9018937740852941, 1.007512112649841, 1.1147029012450915, 1.2218707410492082, 1.327331365927142, 1.4293544490339771, 1.5262083727924882, 1.6162058226397198, 1.6977490358511966, 1.7693735370931347, 1.8297892222050995, 1.8779177104218945, 1.9129249714252203, 1.9342483452043129, 1.94161720699298, 1.9350666832583263, 1.9149439940724489, 1.8819071780326355, 1.8369161437427268, 1.7812161820784205, 1.7163142613128644, 1.6439486080043497, 1.5660522458372412, 1.4847113181286193, 1.402119153615726, 1.3205271460499415, 1.2421936032301253, 1.1693317782319521, 1.1040583232381505, 1.048343403779186, 1.0039636783322337, 0.9724592858214836, 0.9550958930677448, 0.9528327377970812, 0.9662974632261608, 0.9957683808595075, 1.041164622815926, 1.1020444580002025, 1.1776118522964159, 1.2667311564065338, 1.3679496107824995, 1.4795271700386048, 1.5994729738503264, 1.72558763193023, 1.8555103511168352, 1.9867698163307854, 2.1168376469868346, 2.243183188606258, 2.363328367363242, 2.4749013339035897, 2.5756876520267804, 2.6636778470056552, 2.7371102159819563, 2.794507916873286, 2.8347094897683447, 2.8568921225061272, 2.860587146175039, 2.84568743237491, 2.8124465577134097, 2.7614697974326012, 2.693697204492393, 2.610379218140985, 2.513045422414796, 2.403467235851447, 2.28361545507792, 2.155613693443875, 2.021688848667439, 1.884119798343992, 1.745185557624355, 1.607114138611856, 1.4720333260164924, 1.3419245290442476, 1.2185807868217367, 1.103569895983347, 0.9982034971390882, 0.9035128051239161, 0.8202315000153751, 0.7487861160977177, 0.6892940787339157, 0.641569349141872, 0.6051354490754974, 0.5792454560423046, 0.5629083894298287, 0.5549212529593687, 0.553905863043561, 0.5583494792160169, 0.5666481645825493, 0.5771517433363683, 0.5882091902202569, 0.5982132841227736, 0.6056433847411148, 0.6091052466725619, 0.6073668679357405, 0.5993894776197579, 0.5843528973376678, 0.5616746600906695, 0.5310224342310194, 0.49231947527046743, 0.4457430098727862, 0.3917156398913766, 0.33089003512013826, 0.26412735694592426, 0.19247001693916466, 0.11710952050887631, 0.03935027239182075, -0.039429675252411304, -0.11781987263155229, -0.194419609001581, -0.2678798023086054, -0.3369435140565825, -0.4004839968359665, -0.4575392452093218, -0.5073421104088901, -0.5493451532969232, -0.5832395453991699, -0.6089674811324358, -0.6267277317407476, -0.6369741487057218, -0.6404071070273049, -0.6379580621626705, -0.6307675739210074, -0.620157321688602, -0.6075967936564866, -0.594665474210743, -0.5830114747081333, -0.5743076503885216, -0.5702063176469526, -0.5722937294276896, -0.5820454809317155, -0.6007840026967223, -0.6296392537021561, -0.6695136544919051, -0.7210522011226417, -0.7846185774320227, -0.8602779386806986, -0.94778687759209, -1.0465909081771603, -1.155829617818962, -1.274349448475441, -1.4007238782381182, -1.5332805895689197, -1.670135034932099, -1.809229648625819, -1.9483778094532294, -2.0853115360785175, -2.2177317985919807, -2.343360258462715, -2.4599912065303555, -2.56554245611215, -2.658103966074567, -2.7359830164896417, -2.7977448361729396, -2.8422476851773513, -2.868671523719386, -2.8765395489559062, -2.8657320488893334, -2.8364922043921728, -2.789423661495109, -2.7254798920274506, -2.6459455566619705, -2.5524102756195988, -2.4467353940671055, -2.3310144971535642, -2.2075285795763, -2.078696902878858, -1.9470246772249453, -1.8150487806318272, -1.6852827757186795, -1.5601625007810282, -1.4419934980311533, -1.3329014974915343, -1.2347871013796807, -1.1492857126829383, -1.0777336254671248, -1.0211410463799147, -0.9801726504222169, -0.9551360934352939, -0.9459787133024548, -0.9522924562412151, -0.9733268685370485, -1.008009802419794, -1.0549753021714654, -1.1125979674152247, -1.1790329389680263, -1.2522605223047858, -1.3301343577133082, -1.4104319671467576, -1.4909064574670232, -1.56933813937192, -1.6435848312257695, -1.7116296569335088, -1.7716252158414776, -1.821933098630584, -1.861157843841821, -1.8881745719860143, -1.9021496945593828, -1.9025542696941027, -1.889169760260715, -1.8620861394196604, -1.8216924781888306, -1.7686603348510443, -1.7039204423849457, -1.6286333532125363, -1.5441548464025283, -1.451997027476074, -1.3537861520816383, -1.251218279592646, -1.1460139093504067, -1.039872769746414, -0.9344299182647956, -0.8312142693785631, -0.7316105979315966, -0.6368259701611584, -0.5478614352950376, -0.46548967075584197, -0.39023911699871994, -0.32238496789768745, -0.26194720370263175, -0.20869567045143464, -0.16216202697824383, -0.1216582029330625, -0.08630084301176724, -0.05504105813868435, -0.02669866754523367, -2.451832280263886e-16], [0.0, 0.02669866754523276, 0.05504105813868367, 0.08630084301176683, 0.12165820293306212, 0.16216202697824228, 0.20869567045143347, 0.261947203702631, 0.322384967897685, 0.3902391169987184, 0.46548967075584163, 0.5478614352950345, 0.6368259701611545, 0.7316105979315941, 0.8312142693785607, 0.9344299182647925, 1.0398727697464123, 1.1460139093504067, 1.2512182795926432, 1.3537861520816354, 1.4519970274760723, 1.544154846402526, 1.6286333532125346, 1.7039204423849454, 1.7686603348510426, 1.82169247818883, 1.8620861394196615, 1.889169760260716, 1.9025542696941022, 1.902149694559385, 1.8881745719860175, 1.8611578438418233, 1.8219330986305842, 1.7716252158414811, 1.7116296569335165, 1.643584831225769, 1.5693381393719228, 1.4909064574670299, 1.4104319671467616, 1.3301343577133093, 1.2522605223047893, 1.1790329389680323, 1.1125979674152238, 1.0549753021714678, 1.008009802419796, 0.9733268685370501, 0.9522924562412155, 0.945978713302455, 0.9551360934352934, 0.9801726504222168, 1.0211410463799138, 1.0777336254671224, 1.1492857126829352, 1.2347871013796745, 1.33290149749153, 1.441993498031146, 1.5601625007810231, 1.6852827757186777, 1.8150487806318212, 1.947024677224943, 2.0786969028788524, 2.207528579576295, 2.331014497153559, 2.446735394067101, 2.5524102756195974, 2.645945556661966, 2.7254798920274452, 2.789423661495106, 2.836492204392171, 2.865732048889332, 2.876539548955906, 2.868671523719387, 2.8422476851773517, 2.797744836172942, 2.735983016489644, 2.6581039660745676, 2.5655424561121545, 2.4599912065303573, 2.3433602584627145, 2.217731798591989, 2.0853115360785233, 1.9483778094532345, 1.8092296486258248, 1.670135034932105, 1.5332805895689217, 1.40072387823812, 1.2743494484754483, 1.1558296178189635, 1.0465909081771643, 0.9477868775920916, 0.8602779386807011, 0.7846185774320251, 0.7210522011226437, 0.6695136544919075, 0.6296392537021572, 0.6007840026967225, 0.5820454809317158, 0.5722937294276892, 0.5702063176469521, 0.5743076503885209, 0.5830114747081329, 0.5946654742107421, 0.6075967936564861, 0.6201573216886003, 0.630767573921005, 0.63795806216267, 0.6404071070273041, 0.6369741487057224, 0.6267277317407463, 0.6089674811324358, 0.583239545399169, 0.5493451532969227, 0.5073421104088909, 0.45753924520932165, 0.4004839968359682, 0.3369435140565829, 0.2678798023086061, 0.19441960900158298, 0.11781987263155302, 0.03942967525241338, -0.039350272391818694, -0.11710952050887563, -0.19247001693916277, -0.2641273569459236, -0.330890035120138, -0.39171563989137503, -0.44574300987278637, -0.4923194752704673, -0.5310224342310199, -0.5616746600906704, -0.584352897337668, -0.5993894776197592, -0.60736686793574, -0.6091052466725627, -0.6056433847411152, -0.5982132841227747, -0.5882091902202585, -0.5771517433363699, -0.5666481645825511, -0.5583494792160172, -0.5539058630435616, -0.5549212529593688, -0.562908389429829, -0.579245456042304, -0.6051354490754967, -0.6415693491418699, -0.6892940787339137, -0.7487861160977157, -0.8202315000153725, -0.9035128051239133, -0.9982034971390865, -1.1035698959833429, -1.218580786821735, -1.3419245290442428, -1.4720333260164904, -1.6071141386118508, -1.745185557624349, -1.8841197983439835, -2.0216888486674347, -2.155613693443869, -2.283615455077915, -2.403467235851446, -2.513045422414793, -2.6103792181409813, -2.6936972044923913, -2.7614697974325995, -2.8124465577134083, -2.84568743237491, -2.860587146175039, -2.8568921225061277, -2.8347094897683474, -2.7945079168732883, -2.7371102159819594, -2.6636778470056584, -2.575687652026785, -2.4749013339035946, -2.3633283673632466, -2.24318318860626, -2.1168376469868404, -1.9867698163307945, -1.8555103511168407, -1.7255876319302355, -1.5994729738503317, -1.4795271700386097, -1.3679496107825013, -1.2667311564065376, -1.1776118522964216, -1.1020444580002056, -1.0411646228159297, -0.9957683808595089, -0.9662974632261612, -0.9528327377970812, -0.9550958930677441, -0.9724592858214831, -1.0039636783322317, -1.048343403779182, -1.1040583232381478, -1.169331778231951, -1.2421936032301217, -1.320527146049935, -1.402119153615722, -1.4847113181286153, -1.5660522458372346, -1.6439486080043457, -1.7163142613128635, -1.7812161820784171, -1.836916143742726, -1.8819071780326329, -1.9149439940724464, -1.9350666832583234, -1.9416172069929778, -1.9342483452043135, -1.9129249714252212, -1.877917710421895, -1.8297892222051, -1.7693735370931367, -1.6977490358511975, -1.616205822639722, -1.5262083727924909, -1.4293544490339793, -1.3273313659271433, -1.2218707410492116, -1.1147029012450924, -1.0075121126498436, -0.9018937740852986, -0.7993146557393952, -0.7010771802606824, -0.6082886337515625, -0.5218360624467672, -0.44236746049082, -0.37027968901533986, -0.3057133908651904, -0.24855498329475303, -0.19844562736306176, -0.1547968922447755, -0.11681265980530951, -0.08351665392825221, -0.053784834291132705, -0.026381769213303704, -2.451832280263885e-16], [0.0, 0.02722975837078571, 0.0567110638526839, 0.08967250489027606, 0.1272285271381245, 0.17034352157818114, 0.2198000086235736, 0.27617178608898546, 0.33980278073222425, 0.41079219572942316, 0.4889863836593312, 0.5739777004535519, 0.6651104147214068, 0.7614935634608114, 0.8620204640645808, 0.9653944183167844, 1.0701599811706328, 1.1747390196537526, 1.277470659022045, 1.3766541075659193, 1.4705932709889864, 1.5576420141271619, 1.636248903371476, 1.70500026819873, 1.7626604546618834, 1.80820820677195, 1.8408682019221545, 1.8601368816885306, 1.8658018566856953, 1.8579543202994533, 1.8369940772198134, 1.8036269745378612, 1.7588547112496244, 1.7039571916657068, 1.640467774743352, 1.5701419500910967, 1.4949201378815427, 1.4168854599748382, 1.3382174594321405, 1.261142852004241, 1.1878844734093663, 1.1206096382017117, 1.0613791484079322, 1.012098182231266, 0.9744702550963138, 0.9499553779803086, 0.9397334429213414, 0.9446737450696367, 0.9653114075441777, 1.001831313124947, 1.0540599693771464, 1.121465545474686, 1.2031661243462604, 1.2979460175499817, 1.4042797972778065, 1.5203635148116654, 1.6441524021220466, 1.7734041973391648, 1.9057270993534137, 2.0386312451332045, 2.1695825182208957, 2.296057440368937, 2.4155978717960487, 2.5258642497298465, 2.6246861296604327, 2.7101088582119863, 2.7804352991737735, 2.8342616527545816, 2.8705065496407967, 2.8884327624906265, 2.887661054152012, 2.868175869836694, 2.8303227751313713, 2.774797738332871, 2.702628549367912, 2.6151488537844227, 2.513965454456103, 2.4009196915023083, 2.2780438486745456, 2.147513648780889, 2.0115979888733215, 1.8726071258202257, 1.7328405531350333, 1.5945358098722366, 1.4598194321200086, 1.330661197945596, 1.2088327291378307, 1.0958713999774292, 0.9930503674125698, 0.9013553818428346, 0.8214688671072677, 0.753761576492071, 0.6982919431488837, 0.6548130529266377, 0.6227869799891127, 0.6014060453568235, 0.5896203901223026, 0.5861711026845037, 0.5896280066663103, 0.5984311064556934, 0.6109346032039507, 0.6254523376376506, 0.6403034885156219, 0.653857357584391, 0.6645761033123787, 0.6710543456376752, 0.6720546508580496, 0.6665380173657768, 0.6536886163107588, 0.6329321930495662, 0.6039477015356048, 0.566671920399689, 0.5212969818809092, 0.46826092837598327, 0.4082315915377224, 0.342084261018685, 0.27087376977954813, 0.19580176633240623, 0.1181800677524076, 0.039391087657343525, -0.039153591901701194, -0.11605538845386953, -0.18997049228763288, -0.2596501206533365, -0.3239781683221058, -0.38200523718805035, -0.4329781211313585, -0.4763639397048464, -0.5118682524025459, -0.5394466408255282, -0.5593094150478767, -0.5719192786333472, -0.5779819695553963, -0.5784300771032433, -0.5744004130812747, -0.567205484706699, -0.5582997722815415, -0.5492416529933526, -0.5416519295478959, -0.5371700157409415, -0.5374088981153289, -0.5439100317609362, -0.5580993380390359, -0.5812454522175567, -0.6144213200980877, -0.658470165836184, -0.7139767501433318, -0.7812447114082293, -0.8602806350797114, -0.9507853325255506, -1.0521526335637073, -1.1634758113279469, -1.283561568674072, -1.4109513266588871, -1.543949372427184, -1.6806572506908077, -1.8190136242099622, -1.9568386882725342, -2.091882105650999, -2.221873334900063, -2.3445731585351965, -2.4578251803249254, -2.5596060536476624, -2.6480732258767548, -2.721609036586852, -2.778860088807546, -2.8187709206641745, -2.840611136958622, -2.843995313375045, -2.8288951563461717, -2.795643585056144, -2.744930594128642, -2.6777909515787686, -2.595583981815454, -2.4999658731041223, -2.3928551283043835, -2.276391942499345, -2.152892437298705, -2.024798805550202, -1.8946265188954525, -1.76490982163859, -1.6381467760154467, -1.5167451351345327, -1.4029703003306755, -1.2988965699004102, -1.206362807390196, -1.1269335517067522, -1.0618664609017199, -1.0120868297352619, -0.9781697517527055, -0.9603303137505741, -0.9584220186264143, -0.9719434363818296, -1.000052887262367, -1.041590770438589, -1.09510897089382, -1.1589066106724888, -1.2310712623910933, -1.3095246164998884, -1.392071492244208, -1.476451008031115, -1.5603886817060417, -1.641648216114472, -1.7180817405528321, -1.7876773238409398, -1.8486026485794578, -1.8992438367894595, -1.9382385420098034, -1.9645025689014197, -1.9772494448106959, -1.9760025444906408, -1.9605995548597792, -1.9311892566760522, -1.8882207896008127, -1.8324257516313942, -1.76479365873219, -1.6865414513858727, -1.5990778777672983, -1.5039637048158423, -1.4028688056912013, -1.2975272425994504, -1.1896915060981361, -1.0810870847696565, -0.9733685223641648, -0.8680780736679983, -0.7666079966884171, -0.6701674191895279, -0.5797545947424538, -0.49613522041833513, -0.41982732870866446, -0.3510930942652963, -0.2899377159789268, -0.23611535132413944, -0.18914189743652104, -0.14831423666498764, -0.11273539782232518, -0.0813449322398735, -0.05295366985326285, -0.026281908277715184, -2.472104830677017e-16], [0.0, 0.027970120602575168, 0.05877955835542394, 0.09360093205877276, 0.13347306162248096, 0.17926725469744487, 0.2316581904996327, 0.29110019738536635, 0.357809581186002, 0.43175350470161095, 0.5126457490455084, 0.5999495090160579, 0.6928871918659634, 0.7904570063712506, 0.8914559515976775, 0.9945086467270026, 1.0981012890125432, 1.2006198903160135, 1.3003918272304205, 1.3957296484851138, 1.4849760185256833, 1.5665486395691128, 1.6389839870544074, 1.7009787155115446, 1.751427642989357, 1.789457301120971, 1.8144541427699379, 1.8260866274453977, 1.8243205531646713, 1.809427168528625, 1.7819837763884867, 1.7428667262306714, 1.6932368816839765, 1.634517837658267, 1.5683673438707846, 1.4966425633557663, 1.4213599516834632, 1.344650681089432, 1.2687126500416523, 1.195760209999969, 1.1279728049131053, 1.0674437536906094, 1.0161304105338602, 0.9758069124057294, 0.9480206676031057, 0.9340536556450703, 0.9348894984802708, 0.9511871289843562, 0.983261728087228, 1.031073430378597, 1.0942241138472357, 1.171962396991743, 1.2631967705842053, 1.3665165966517256, 1.4802205185186184, 1.6023516476369075, 1.7307387297815522, 1.8630423489940797, 1.9968051059567762, 2.1295046112535476, 2.258608065584925, 2.381627160134752, 2.4961720218939267, 2.6000029510451284, 2.691078749963987, 2.7676005247195086, 2.8280499481778403, 2.8712211062866837, 2.896245202609912, 2.9026075669459708, 2.8901565977320094, 2.859104460422505, 2.810019560443057, 2.743811004871629, 2.6617054569310508, 2.565216967071307, 2.456110529517697, 2.3363602596644593, 2.2081032120679325, 2.0735899580518344, 1.9351331137144303, 1.7950550517368056, 1.6556360428663783, 1.5190640550666499, 1.3873873906061769, 1.2624712650645666, 1.1459593293188015, 1.0392410086511017, 0.9434253853867428, 0.8593221866313341, 0.7874302608512788, 0.7279337406584777, 0.6807058988541976, 0.6453205152757141, 0.6210703879621154, 0.6069924481541746, 0.6018987789503658, 0.6044126959746745, 0.6130089286276393, 0.626056845298941, 0.6418655976082145, 0.6587300189262082, 0.6749761020130669, 0.689004899760822, 0.699333741171705, 0.7046337305475886, 0.7037625994241882, 0.6957921054324783, 0.680029316811572, 0.6560312820424441, 0.6236127569299756, 0.5828468420451646, 0.53405856717501, 0.4778116416677002, 0.4148887657015205, 0.34626606310251684, 0.27308234721373875, 0.19660406367692398, 0.11818686449481942, 0.03923485361984097, -0.038841396594439935, -0.11466692791963431, -0.18694344581132472, -0.2544882313424234, -0.31626986651875816, -0.37143980661733933, -0.41935894069723634, -0.4596184111012399, -0.4920541113162454, -0.5167544452365872, -0.5340611055394623, -0.5445628101169039, -0.5490821187271314, -0.5486556325880795, -0.5445080529571431, -0.5380207364210985, -0.5306955305419647, -0.5241147999431847, -0.5198986566337556, -0.5196604866800939, -0.5249619162036924, -0.5372683817490713, -0.5579064626934561, -0.5880240966554394, -0.6285547336385715, -0.6801863924662676, -0.743336466153358, -0.8181329840664846, -0.9044028814530278, -1.001667655037192, -1.1091466011370923, -1.225767644659829, -1.3501855780516032, -1.4808073435245817, -1.615823814284064, -1.7532473654769418, -1.8909543773137678, -2.0267316850117094, -2.1583258860977934, -2.283494337852412, -2.400056628268662, -2.5059452841619083, -2.599254490564588, -2.678285636116138, -2.74158856889614, -2.7879975444196945, -2.8166609700036687, -2.827064194482369, -2.8190447558090774, -2.792799677465158, -2.748884593479923, -2.6882046766466448, -2.6119975404559908, -2.521808477576369, -2.4194585816936454, -2.3070064706809155, -2.1867044832148, -2.06095035431167, -1.9322354845579337, -1.8030910003702867, -1.6760328564181128, -1.5535072550456328, -1.4378376505586221, -1.331174568752761, -1.2354494049670885, -1.1523332688826833, -1.083201823571165, -1.0291069228777352, -0.9907556885991169, -0.9684974910581522, -0.9623191079238496, -0.9718481410818856, -0.9963645747804615, -1.0348201649469433, -1.0858651641947765, -1.147881714120223, -1.2190230802157864, -1.2972577688796065, -1.3804174538484189, -1.4662475536102006, -1.5524592439935907, -1.636781662515066, -1.717013063788699, -1.7910697182163309, -1.8570314083855166, -1.9131824674950695, -1.9580474194117927, -1.990420417723571, -2.009387837931933, -2.0143435487969406, -2.0049965715214384, -1.9813710243938891, -1.9437984410091993, -1.8929027375364424, -1.8295782840714845, -1.754961702475215, -1.6703981641413046, -1.577403092162958, -1.4776202801837444, -1.3727775222158662, -1.2646409019308007, -1.154968915109855, -1.0454675945496563, -0.9377477729534887, -0.8332855571396293, -0.7333869979079817, -0.6391578264374292, -0.5514789930589197, -0.4709885911176932, -0.3980705813043684, -0.3328505545510206, -0.27519858884946075, -0.22473907178051097, -0.18086718078458097, -0.14277154179409465, -0.1094624281105531, -0.07980471934335857, -0.05255471841132206, -0.026399826105570855, -2.512453508765876e-16], [0.0, 0.02891280485584524, 0.06122738117091213, 0.09805000089884594, 0.140334652978108, 0.188851817707419, 0.24416229941680412, 0.30659683585910236, 0.37624205303552977, 0.4529331696533329, 0.5362536802554658, 0.6255420646942169, 0.7199053886354411, 0.8182394798150647, 0.9192551923911783, 1.0215101113238776, 1.12344490435614, 1.2234234045492767, 1.3197754046419619, 1.4108410683772952, 1.4950158153649515, 1.570794516314464, 1.6368138451689571, 1.6918916736275869, 1.7350624608772243, 1.7656076854551892, 1.7830804847573567, 1.7873238078949834, 1.7784815459482384, 1.757002276263052, 1.7236354400244318, 1.6794199603890057, 1.6256654973011877, 1.5639267200493479, 1.4959711550256107, 1.4237413296215988, 1.3493120796201092, 1.2748440131402572, 1.2025342259782812, 1.134565438459997, 1.0730547707373919, 1.0200033905740578, 0.9772482545572624, 0.9464171205792163, 0.9288879373182224, 0.9257536170116372, 0.9377930734135856, 0.9654492604576177, 1.0088147823303717, 1.0676254663996434, 1.1412621010832416, 1.2287603459028493, 1.3288286253903197, 1.4398736269772885, 1.5600328401841703, 1.687213404804625, 1.819136383509925, 1.9533854431069348, 2.087458821792045, 2.2188233797769303, 2.3449694795878386, 2.46346542141896, 2.572010168675236, 2.6684831390424146, 2.7509899060992034, 2.8179027539422545, 2.867895150155536, 2.8999693477243254, 2.913476490627509, 2.908128776835711, 2.8840034219315487, 2.841538361932198, 2.7815198303733637, 2.7050621375244224, 2.6135801640583622, 2.50875525311816, 2.392495339344821, 2.266890287324564, 2.1341635218506902, 1.9966211157491391, 1.8565995558122494, 1.7164134323541171, 1.5783042925097506, 1.4443918618634166, 1.3166287742644065, 1.1967598574438183, 1.0862869046302057, 0.9864397227385687, 0.8981540893798232, 0.8220570778652548, 0.7584600258769454, 0.7073592341023608, 0.6684442905874226, 0.6411137295622455, 0.6244975546550598, 0.6174859901364669, 0.6187636742105698, 0.6268483790513196, 0.6401332364182122, 0.6569313678315517, 0.6755217663471766, 0.6941952541473904, 0.711299346934554, 0.7252808922122816, 0.7347254129714634, 0.738392179363008, 0.7352441462729958, 0.7244720313527367, 0.7055119625020163, 0.6780562921250735, 0.6420573534002003, 0.5977241168167713, 0.5455118887075895, 0.4861053728050142, 0.4203955864519707, 0.34945128070347187, 0.27448565419217763, 0.19681927076436787, 0.11784018750176778, 0.03896237040495659, -0.03841648204422446, -0.11295657307156885, -0.18341598016371344, -0.24868789032730593, -0.30783409375747356, -0.3601138288042551, -0.40500719167416116, -0.4422324651659804, -0.4717568783526455, -0.49380047949754685, -0.5088329833236699, -0.5175636365103845, -0.5209243273459158, -0.520046342197388, -0.5162313383867757, -0.510917255934592, -0.5056400255548221, -0.5019920438027146, -0.50157847547149, -0.505972505891744, -0.5166707000598434, -0.5350496305671882, -0.5623249119106016, -0.5995137254621697, -0.6474018384168121, -0.7065160133646512, -0.7771025753472258, -0.8591127535291585, -0.9521952486330489, -1.0556962991412107, -1.168667333373119, -1.289880105513674, -1.4178490261964036, -1.550860217009536, -1.6870066478210743, -1.8242285603819244, -1.9603582451730235, -2.0931681243586753, -2.220421004894692, -2.3399213045947937, -2.4495660218845994, -2.547394217952673, -2.6316338081854402, -2.7007445175443268, -2.7534559405741, -2.788799758987311, -2.8061353055657046, -2.8051678191861944, -2.7859589083423666, -2.7489289254060116, -2.6948511465612386, -2.624837848152249, -2.540318564337158, -2.443010998691495, -2.3348852391652204, -2.2181220872386684, -2.0950664542917026, -1.9681768976088971, -1.8399724621621747, -1.712978060035849, -1.5896696554699445, -1.4724205291000485, -1.3634498699187447, -1.2647748883775782, -1.178167560226999, -1.105117000197429, -1.046798330149792, -1.0040487511500187, -0.9773513568336091, -0.9668270406217642, -0.9722346563362789, -0.992979395240565, -1.0281291472955787, -1.0764384252124033, -1.13637925130582, -1.206178243537556, -1.2838589924437642, -1.3672886983595396, -1.4542279414193067, -1.5423823875346556, -1.6294551935567239, -1.7131988650221852, -1.7914653404202452, -1.8622531262156832, -1.9237503856022609, -1.9743729891251147, -2.0127966642371176, -2.037982530298938, -2.0491954717527485, -2.046014981045581, -2.0283382898987306, -1.9963757980696013, -1.9506389981111214, -1.891921278120345, -1.8212721575573887, -1.739965669652061, -1.6494637438154425, -1.5513755594235248, -1.4474139354795694, -1.3393498867547289, -1.2289665144939759, -1.118013407815005, -1.00816271041496, -0.9009679567656856, -0.7978267039747569, -0.6999478819562176, -0.6083246581642623, -0.5237134671357647, -0.4466196931889655, -0.37729032095297593, -0.3157136873621508, -0.2616262849242549, -0.2145263841092461, -0.17369406719992908, -0.13821710132312265, -0.10702192878764193, -0.07890892205836941, -0.05259094198305586, -0.02673415399057204, -2.5724874122318116e-16], [0.0, 0.030048901383456318, 0.06403169076779543, 0.10297852194841298, 0.14775011826410356, 0.19900930133382497, 0.25719799499077795, 0.32252033860070517, 0.39493238538323205, 0.47413869036152123, 0.5595959134749275, 0.6505233807370332, 0.7459203647361404, 0.8445896698630405, 0.9451669418797279, 1.046154970030521, 1.145962116705827, 1.2429438981074497, 1.3354466523031427, 1.4218521707561624, 1.5006221374636484, 1.5703412171177937, 1.629757660366208, 1.6778203497065853, 1.7137112924970492, 1.7368726759978197, 1.7470277306405393, 1.7441947986304494, 1.7286941718077002, 1.7011474413061383, 1.6624692875262488, 1.6138518276650353, 1.556741824822256, 1.4928112428699136, 1.4239218003243816, 1.3520843301581187, 1.279413886962397, 1.208081654723757, 1.1402647948589106, 1.0780954328433143, 1.023610011227474, 0.9787002362409832, 0.9450668144582952, 0.9241771158072681, 0.9172278109356576, 0.9251134167016037, 0.9484015460558732, 0.9873155011486604, 1.0417246749309346, 1.1111430410423588, 1.194735818896863, 1.291334205294271, 1.3994578703762015, 1.517344729036517, 1.6429873235593313, 1.7741749935859947, 1.9085408694210153, 2.043612607614377, 2.176865696580855, 2.3057780969803088, 2.4278849482429576, 2.5408320698100977, 2.642427013456358, 2.7306864807974187, 2.8038790063677004, 2.8605619193765057, 2.8996117336738307, 2.9202472722522406, 2.922045005956891, 2.904946271745121, 2.869256229304501, 2.8156346113901103, 2.7450785180923964, 2.6588976936565296, 2.5586829018654202, 2.4462681780689937, 2.323687878770496, 2.1931295698216284, 2.056883888848877, 1.9172925842819077, 1.7766959707164598, 1.6373810474784414, 1.5015315040667072, 1.3711807832895484, 1.2481692917525897, 1.1341067399769524, 1.030340463540117, 0.9379304255273156, 0.8576314330382703, 0.789882920690986, 0.7348064664731704, 0.6922110145664898, 0.6616055906315258, 0.6422191121627903, 0.6330267244097585, 0.6327819352398967, 0.6400536840400857, 0.6532673636839049, 0.6707487235446292, 0.6907695176894921, 0.711593727250094, 0.7315231803084784, 0.7489414165139463, 0.7623546963604033, 0.7704291351984328, 0.7720230475378329, 0.7662137152938391, 0.7523179410616571, 0.7299059105091574, 0.6988080624135488, 0.6591148463111945, 0.6111694315892389, 0.5555536134775149, 0.49306733621677096, 0.42470241727848973, 0.3516112047738659, 0.27507102938647254, 0.19644541904908724, 0.11714312647922122, 0.038576074539708356, -0.03788264916765797, -0.1109396196877003, -0.17941962689077776, -0.24230091503179174, -0.2987461586991727, -0.3481283350454667, -0.3900507847228065, -0.42436090477330685, -0.4511570820292161, -0.47078865117638813, -0.48384884308172754, -0.4911608716841699, -0.49375748706746153, -0.49285449372050893, -0.48981889209021356, -0.4861324442904449, -0.4833515876015425, -0.4830647190285467, -0.48684794810997895, -0.49622046145158727, -0.5126006598606327, -0.5372642169580194, -0.5713051669664976, -0.6156010599633998, -0.6707831269051604, -0.7372122765059176, -0.8149616045228762, -0.9038059366444623, -1.0032187529247814, -1.1123766588452546, -1.2301713801479117, -1.355229070246265, -1.4859365349729896, -1.6204738042648155, -1.7568523185018419, -1.8929578526763924, -2.026597178012454, -2.1555473612221805, -2.277606528814438, -2.3906448796478807, -2.492654714433072, -2.581798266585537, -2.6564521644212187, -2.7152474291348248, -2.757104014562534, -2.7812590209848476, -2.787287863139895, -2.7751178386208677, -2.745033722900331, -2.6976752069830225, -2.634026188516248, -2.5553961223312087, -2.4633938270822657, -2.3598943262311027, -2.2469994696437716, -2.1269932324124214, -2.0022927164932893, -1.8753959851993107, -1.7488279379324068, -1.6250854808791635, -1.506583267528918, -1.395601270346261, -1.294235402034337, -1.2043523325976382, -1.127549548607066, -1.0651215761167496, -1.0180331416249717, -0.9868998798967998, -0.9719770174097722, -0.9731562700363496, -0.9899709979716538, -1.0216094646165157, -1.0669358539116907, -1.124518517161998, -1.192664750142803, -1.269461248370344, -1.35281925653623, -1.440523320429175, -1.530282468768701, -1.619782600170301, -1.7067388281556886, -1.7889465451848663, -1.8643300048408478, -1.9309872885251353, -1.9872306175917376, -2.0316210913577932, -2.0629970728690066, -2.0804956041223934, -2.0835664066658452, -2.0719782077647975, -2.045817322074066, -2.00547860927469, -1.95164911472049, -1.8852848781840936, -1.8075815609165595, -1.719939689388264, -1.6239254416417204, -1.5212280060593009, -1.4136146200264847, -1.302884445607696, -1.1908224598020807, -1.0791545277965189, -0.9695047892064246, -0.8633564206459822, -0.7620167448544741, -0.6665875394394557, -0.5779412600911303, -0.4967037374080808, -0.4232437372163877, -0.3576695957586788, -0.29983295789859093, -0.24933946316215044, -0.20556604564982126, -0.16768434410944386, -0.13468956203697519, -0.1054339785046411, -0.07866419200261078, -0.05306108489335832, -0.02728142749045158, -2.651625025519308e-16], [0.0, 0.03136762736318803, 0.06716618720825755, 0.10834064008410266, 0.15565085741794998, 0.20964614616120567, 0.2706456176508026, 0.3387249452947722, 0.4137098896476224, 0.4951767934547967, 0.5824600677735491, 0.6746665079187051, 0.770696099360803, 0.8692688033558711, 0.9689566543419725, 1.0682203600166311, 1.165449474117335, 1.2590051143665164, 1.347264126332877, 1.4286635499771785, 1.5017442305739732, 1.565192429989012, 1.6178783376672492, 1.6588904521407757, 1.6875649016863392, 1.7035088945716554, 1.7066176321462718, 1.6970841783428852, 1.6754019530001811, 1.6423596994935394, 1.5990289649203768, 1.546744318860286, 1.4870767198336752, 1.4218006124387041, 1.3528554983970507, 1.282302867354757, 1.2122794946641613, 1.1449482104345747, 1.08244731439742, 1.0268398527583047, 0.9800639850824784, 0.9438856509925136, 0.9198546984044197, 0.9092655582835945, 0.9131234472687912, 0.9321169514614202, 0.9665976952865264, 1.0165676322100112, 1.0816743132961038, 1.161214299505614, 1.2541446889001095, 1.359102535282394, 1.4744317450262958, 1.5982168585726524, 1.7283229567096718, 1.8624407833946466, 1.998136050152381, 2.132901785119407, 2.2642125151028774, 2.3895790234337233, 2.5066024110479175, 2.6130262035198624, 2.7067852923405105, 2.7860505734806877, 2.8492682483939906, 2.8951928796095583, 2.922913441851532, 2.9318717765732307, 2.921873038842113, 2.893087916244325, 2.8460465952485796, 2.781624646511445, 2.7010211921500114, 2.6057299003977015, 2.4975035218683743, 2.3783128327933025, 2.2503009804146257, 2.115734331093554, 1.976951000102782, 1.8363082916660542, 1.69613029744032, 1.5586568909016971, 1.4259953143370327, 1.3000754854377077, 1.1826100536305564, 1.0750601147176277, 0.9786073491895391, 0.8941331883127678, 0.8222054367922924, 0.763072595839019, 0.7166659404174064, 0.6826092140182548, 0.6602356182003151, 0.648611596958767, 0.6465667520648612, 0.6527290788956471, 0.6655645865144573, 0.6834202639238645, 0.7045692789442229, 0.7272572488621084, 0.7497484039289716, 0.7703704763248321, 0.7875571879506462, 0.7998872792633245, 0.80611911650804, 0.8052200336684722, 0.7963897051918547, 0.7790770024830146, 0.752989957306684, 0.7180986342736864, 0.6746308979811388, 0.6230612434954448, 0.5640930370883199, 0.4986346829694834, 0.4277703869550013, 0.35272632566581347, 0.2748331465102096, 0.19548581644157617, 0.11610190397819098, 0.038079417566585366, -0.03724466689088697, -0.10863407586770177, -0.17499003985002703, -0.23538423650074114, -0.28908698578816344, -0.3355899311172971, -0.37462258385421965, -0.4061622681091299, -0.4304371742024015, -0.44792240853586324, -0.4593291100863102, -0.4655868848035581, -0.4678199842368316, -0.4673178192841876, -0.4655005498711539, -0.46388062279289655, -0.46402123953379887, -0.46749282078989784, -0.47582859245844933, -0.4904804474924055, -0.5127762384235056, -0.5438796264456089, -0.5847535553647125, -0.6361283338283643, -0.6984751990962144, -0.771986102893008, -0.8565603078533635, -0.9517982154715627, -1.057002667454348, -1.1711877763784893, -1.2930951532013475, -1.421217213153049, -1.553827062498884, -1.689014301080768, -1.8247259236351923, -1.9588113704680328, -2.0890706684972753, -2.2133045197443857, -2.329365138228427, -2.435206609372313, -2.528933549226301, -2.6088468740655157, -2.673485553499712, -2.7216633106917585, -2.752499349472336, -2.765442327280109, -2.760286951594756, -2.7371827520227483, -2.696634766205336, -2.639496070717809, -2.5669522834119354, -2.480498356450877, -2.381908164882269, -2.2731975694468716, -2.1565817901661513, -2.0344280652184543, -1.9092046843119352, -1.7834275743696417, -1.6596056756751782, -1.5401863771911375, -1.4275022797937564, -1.3237205256470796, -1.2307958715997132, -1.150428595787733, -1.084028211722835, -1.0326838258330762, -0.997141816072242, -0.9777913346828844, -0.9746579517396734, -0.9874055622577729, -1.015346483146379, -1.0574594719035317, -1.1124152114120747, -1.178608629063245, -1.254197257974835, -1.337144707167203, -1.425268189610011, -1.5162889648859839, -1.6078844890282966, -1.697741029378733, -1.7836054978614766, -1.8633352819042566, -1.934944907651887, -1.9966484536678222, -2.0468967428789675, -2.0844084733219224, -2.108194600963055, -2.1175754566737264, -2.1121902601403697, -2.0919988815864667, -2.0572758930174766, -2.0085971395496927, -1.946819243589703, -1.873052625707179, -1.78862878179081, -1.6950626926859511, -1.5940113566573704, -1.4872295239410196, -1.376523774218447, -1.2637061106248642, -1.1505482471650188, -1.038737740175997, -0.9298370594932177, -0.8252466127124378, -0.7261726285408637, -0.6336006754639757, -0.5482754431432745, -0.4706872498975219, -0.4010655644740441, -0.3393796485258246, -0.2853462423727405, -0.23844403538322737, -0.19793448823671028, -0.16288841180106578, -0.13221756047207783, -0.10471037026396808, -0.07907086691239336, -0.053959689385090666, -0.02803612148630637, -2.7490999693653496e-16], [0.0, 0.03285643264262326, 0.07060136882835878, 0.11408628053718245, 0.16396351876861168, 0.2206640483617615, 0.2843813449339214, 0.35506190444060465, 0.4324026437883419, 0.5158552914800004, 0.6046376849890374, 0.6977517110661674, 0.7940074510604314, 0.8920529300112991, 0.9904087198967778, 1.0875065177904313, 1.1817307121070253, 1.2714618673711942, 1.3551210021750375, 1.4312135076733807, 1.4983715558620032, 1.5553938780249392, 1.6012818534189377, 1.6352709350664614, 1.6568565513509266, 1.6658137562164912, 1.6622100538732754, 1.646410992219524, 1.6190782985485748, 1.5811605170592262, 1.5338762956075864, 1.4786906543412601, 1.4172847467146774, 1.3515197894413697, 1.2833959880224426, 1.2150074148151537, 1.1484939038685191, 1.0859911082156406, 1.0295799188712984, 0.9812364690196668, 0.942783941097182, 0.9158473587256366, 0.9018124805187708, 0.9017898201824956, 0.9165846992514657, 0.9466740980829691, 0.9921909107567353, 1.0529160341806814, 1.1282785352377134, 1.2173639467681345, 1.3189305482757283, 1.4314332952358626, 1.5530548764693572, 1.6817432067443925, 1.8152545058065541, 1.9512009792445448, 2.087102004315012, 2.22043763784072, 2.3487032056857773, 2.4694637055297792, 2.580406757409287, 2.6793928697226947, 2.7645018513091717, 2.834074291293112, 2.8867471454218148, 2.9214826077693523, 2.93758960652293, 2.934737438215823, 2.9129612419450157, 2.872659209252838, 2.8145816217332404, 2.7398120022660173, 2.649740852373474, 2.5460326230022687, 2.4305867248207567, 2.3054935230477525, 2.1729863775433027, 2.0353908786195998, 1.8950724906362397, 1.754383847487423, 1.6156129458563957, 1.4809334536364105, 1.3523582929727984, 1.231697571466258, 1.1205218233766858, 1.0201313879949927, 0.9315325980815895, 0.8554212812564452, 0.7921738956976427, 0.7418464329699567, 0.7041810299321775, 0.6786200431784667, 0.6643271580033426, 0.6602149339047562, 0.6649780343239522, 0.6771312534349063, 0.6950513406201646, 0.7170215365123692, 0.7412776752125044, 0.7660546768992543, 0.7896322541798727, 0.8103786841251461, 0.8267915551695089, 0.837534482418721, 0.8414688941952362, 0.8376801240499863, 0.8254971926167674, 0.8045058287567843, 0.7745544552446407, 0.735753046330567, 0.6884649482737482, 0.6332919347411672, 0.5710529422486654, 0.5027570922251133, 0.4295717517493542, 0.3527865108910864, 0.27377405772592805, 0.1939490099110023, 0.11472581225993639, 0.03747683179182685, -0.03650822528689427, -0.1060604860779733, -0.17016664817332938, -0.22799934683310283, -0.2789423315814303, -0.3226097668700007, -0.3588591243762907, -0.3877973012342787, -0.4097797748165387, -0.4254027861299567, -0.4354887258535742, -0.44106507491999625, -0.44333742080426675, -0.44365722703179156, -0.443485172865032, -0.44435099911406367, -0.44781089148434206, -0.45540350235989097, -0.4686057536037265, -0.4887895757178086, -0.5171807221443161, -0.5548207519457485, -0.602533200637999, -0.6608948593346073, -0.7302129590168046, -0.8105089126966701, -0.9015091070378333, -1.002643060623955, -1.1130490828424333, -1.2315873798313515, -1.3568603667925452, -1.4872397638732187, -1.6208998803201304, -1.755856333040786, -1.8900093050578748, -2.0211903301703544, -2.147211495468594, -2.2659158856193793, -2.3752280538073554, -2.4732032949510216, -2.5580745176296213, -2.628295561643038, -2.6825798871279183, -2.7199336668099883, -2.739682442763532, -2.741490659853368, -2.725373556206626, -2.6917010725217834, -2.6411936323568304, -2.5749098401076354, -2.4942263374404594, -2.4008102477344755, -2.2965848169980125, -2.183689024360714, -2.064432081572513, -1.9412438653625053, -1.8166224259658241, -1.693079787160107, -1.5730872959844011, -1.4590217928724416, -1.3531138548935981, -1.2573993165789734, -1.1736751955790496, -1.1034610460243746, -1.047966633477689, -1.008066674914152, -0.9842832189083507, -0.9767760592420288, -0.9853413839065794, -1.0094186656171937, -1.0481056042484276, -1.1001807408044941, -1.1641331812881317, -1.2381987015275804, -1.320401354714027, -1.4085995756980572, -1.5005356730649873, -1.5938875241185815, -1.6863212409435404, -1.7755435587695967, -1.859352711265795, -1.9356866007474762, -2.002667143440183, -2.0586397690668545, -2.1022071776006186, -2.1322566009502735, -2.147979979995028, -2.148886643705436, -2.1348082626960885, -2.1058960398498057, -2.062610290924999, -2.005702753610176, -1.936192139752628, -1.8553336081329799, -1.7645829802014255, -1.6655566450990087, -1.5599882000548204, -1.449682945480205, -1.3364713990423072, -1.2221630086669888, -1.1085012305016775, -0.9971210948075165, -0.8895103117169972, -0.786974871654568, -0.6906099744869025, -0.601276980245764, -0.5195869161538448, -0.4458909037039973, -0.38027769003041184, -0.3225782843084944, -0.2723775170634709, -0.22903216266703497, -0.19169509742984844, -0.15934481177732807, -0.1308194588937765, -0.1048545073497023, -0.08012297446581093, -0.055277152782412346, -0.02899070559679592, -2.863968574298271e-16], [0.0, 0.03450112285696307, 0.07430482032547882, 0.12016163619337988, 0.1726107108748567, 0.2319609114393539, 0.2982783877962974, 0.37138090775862526, 0.45083914710561035, 0.5359849294044093, 0.6259262288290466, 0.7195685721411574, 0.8156423078665428, 0.912735055792048, 1.0093285121667672, 1.103838668940715, 1.1946584120175567, 1.2802013962485315, 1.358946055512405, 1.4294785957738436, 1.4905338378278372, 1.5410328241246471, 1.5801161795070695, 1.6071723170607572, 1.6218597051066734, 1.62412255658802, 1.6141994641409008, 1.5926246789794454, 1.5602219150341523, 1.5180907469981375, 1.4675858573932612, 1.4102895688086183, 1.3479782685539583, 1.2825834898137662, 1.2161485520322166, 1.150781780196423, 1.0886074149381662, 1.0317153905707495, 0.9821111946127311, 0.9416670290263349, 0.9120754700542304, 0.8948067706537499, 0.8910708683146695, 0.9017850534196172, 0.927548121835508, 0.9686216832740451, 1.0249191278091683, 1.0960025708949197, 1.1810879067189772, 1.2790579054011733, 1.3884830961502361, 1.5076499907575647, 1.6345960243335844, 1.7671504273336438, 1.902980098676596, 2.0396394276782686, 2.1746229156115016, 2.305419378358229, 2.429566471556738, 2.544704269872358, 2.6486266527943987, 2.739329300200216, 2.8150531806063657, 2.874322521618051, 2.915976383003736, 2.9391931048779663, 2.9435070729720536, 2.9288174257820407, 2.895388520055206, 2.843842166943784, 2.775141846451095, 2.690569297771282, 2.5916940631640752, 2.480336728741954, 2.3585267529658447, 2.228455899186413, 2.0924283892120377, 1.952808968226166, 1.8119701156842205, 1.672239651076543, 1.535849967371773, 1.4048900790227223, 1.2812615968253351, 1.166639640574982, 1.062439574921383, 0.9697903072339348, 0.8895147223141417, 0.822117651514829, 0.7677815876485233, 0.7263701666027735, 0.6974392465367683, 0.6802552305986675, 0.6738201038277442, 0.6769024935906591, 0.6880739194928479, 0.7057492766965807, 0.7282304989206065, 0.7537522764345314, 0.7805286617679755, 0.8067993825941949, 0.8308746975526393, 0.8511776761397996, 0.8662828569950387, 0.8749503380179476, 0.8761544742140646, 0.8691065018356862, 0.8532705666246897, 0.828372805727644, 0.7944033127867479, 0.7516109992634498, 0.7004915475913926, 0.6417688286815765, 0.5763703231621996, 0.5053972383352304, 0.4300901473410624, 0.35179109007081505, 0.2719031641255566, 0.19184869637873173, 0.11302711990756534, 0.036773686382967546, -0.035679879664690786, -0.10324173033437338, -0.1649922723172681, -0.22021170216779595, -0.26840195421096535, -0.3093024620782748, -0.3428992960047551, -0.36942741055223705, -0.38936591697576384, -0.40342647646904384, -0.41253509039425484, -0.4178077367550367, -0.42052046420802114, -0.4220747017026419, -0.4239586696445224, -0.4277058840220517, -0.43485182550098556, -0.44688989898546116, -0.46522783414943825, -0.49114567325791475, -0.5257564592513677, -0.569970675320587, -0.6244653985269101, -0.6896590165770644, -0.7656922214191398, -0.8524158392200127, -0.9493858873217774, -1.0558660691417483, -1.170837732140065, -1.2930171265571475, -1.4208796182979904, -1.5526903327208443, -1.6865405416041797, -1.8203889573538523, -1.952106970315252, -2.0795267601246756, -2.2004911330545265, -2.312903886321828, -2.414779478695872, -2.5042907950890694, -2.57981383103656, -2.6399681902158303, -2.6836523828599934, -2.710073032828143, -2.7187672433370835, -2.709617532498772, -2.6828589259417917, -2.639077980642308, -2.579203707097587, -2.5044905514324185, -2.416493790180538, -2.317037873650293, -2.2081784244749634, -2.0921587519741367, -1.9713618765276697, -1.8482591679992295, -1.7253567856343028, -1.605141161733349, -1.490024796400167, -1.3822936251521223, -1.2840571852665896, -1.197202741282198, -1.123354436655606, -1.063838419459818, -1.019654748092482, -0.9914567216959229, -0.9795381032995447, -0.9838285158829974, -1.0038970971973622, -1.0389643030031175, -1.0879215551601842, -1.1493582454341171, -1.2215954324689848, -1.3027254123254757, -1.3906562060906738, -1.483159894633788, -1.577923643330263, -1.67260220058055, -1.7648706245875063, -1.8524759937770394, -1.9332868873545324, -2.0053394829472997, -2.0668792065333212, -2.1163969836602083, -2.152659277453264, -2.1747312546807667, -2.1819925923042054, -2.1741456192351607, -2.1512156769275568, -2.113543773278631, -2.061771792381996, -1.9968207033377876, -1.9198623801383956, -1.8322857974775852, -1.7356585004450678, -1.6316843562346925, -1.5221586805564928, -1.4089218883863501, -1.2938128466893961, -1.178623105214617, -1.0650531505147642, -0.9546717688675782, -0.8488795173396014, -0.748877191091256, -0.6556400420312692, -0.5698983524914071, -0.49212480156345856, -0.4225288853334332, -0.36105846992838014, -0.3074083726651014, -0.2610356862889276, -0.2211813888550542, -0.18689762157186365, -0.15707987291922343, -0.13050318318698567, -0.10586138235861017, -0.08180829852056314, -0.056999825595392815, -0.030135719370388662, -2.9951192000071565e-16], [0.0, 0.036285998656671405, 0.07824152930639755, 0.12650969120431832, 0.18151175343916104, 0.2434318343114251, 0.3122082147951903, 0.3875315382382157, 0.4688499688566061, 0.5553811998788452, 0.6461310229994859, 0.7399179986652847, 0.8354036060120102, 0.9311271060906322, 1.0255442260725807, 1.1170686686309714, 1.2041153723230351, 1.2851443975851355, 1.3587042902527933, 1.423473780976736, 1.4783007144337121, 1.5222371660094294, 1.5545697941321113, 1.5748445914576743, 1.5828853348314704, 1.5788051890081412, 1.5630110886656583, 1.5362007030969842, 1.4993519736313494, 1.4537054007002232, 1.4007394408538778, 1.3421395493620574, 1.2797615668964768, 1.2155902950934192, 1.1516942318341534, 1.090177539656899, 1.0331303971998937, 0.982578931985234, 0.9404359518947432, 0.9084536817929453, 0.8881796710907627, 0.8809169685248999, 0.8876895636765064, 0.9092139730689811, 0.945877704989552, 0.9977251749422272, 1.0644514667944454, 1.1454041475269936, 1.239593150598786, 1.34570854900614, 1.4621458488945471, 1.5870382527298852, 1.7182951720166757, 1.8536461175153987, 1.9906889635990206, 2.1269414760369054, 2.259894911753188, 2.3870684469783296, 2.5060631679983634, 2.61461436697598, 2.7106409238941653, 2.792290623637433, 2.8579803529384376, 2.9064302430599707, 2.936690967712198, 2.9481635683297363, 2.9406113564961758, 2.91416363168009, 2.869311146951446, 2.806893451247243, 2.72807842928533, 2.63433454470626, 2.5273964639765674, 2.409224893844596, 2.281961599948115, 2.1478806852811765, 2.00933729197218, 1.8687149461908414, 1.7283727926733543, 1.5905939617475804, 1.4575362780131382, 1.3311864568840956, 1.2133188446502865, 1.1054596418492304, 1.008857411474223, 0.9244605163322238, 0.8529019576232673, 0.7944919038206089, 0.7492180097220729, 0.7167534347968881, 0.696472282375225, 0.687472001436929, 0.6886021251666309, 0.6984985691567974, 0.715622580847875, 0.7383033236806231, 0.7647829971029232, 0.7932633389783939, 0.8219523313502165, 0.8491099344593711, 0.8730917072048435, 0.8923892339361186, 0.9056663659517558, 0.9117903990430732, 0.9098574429644887, 0.8992113913934651, 0.8794560678789586, 0.8504603002338184, 0.8123558583267887, 0.765528373666008, 0.7106015389142253, 0.6484150570130206, 0.5799969686077714, 0.5065311289668077, 0.4293207280064223, 0.34974884630664105, 0.2692371136548167, 0.189203582855508, 0.11102094915891036, 0.035976234269448286, -0.034766986185138606, -0.100202800579378, -0.15951270712299795, -0.21209008730807785, -0.2575587444304614, -0.2957849994616467, -0.3268830045001645, -0.351213110862442, -0.36937331009875757, -0.38218394724315013, -0.39066608183285645, -0.3960140391858336, -0.39956284785673796, -0.40275139519160336, -0.40708224799238674, -0.4140791765304254, -0.42524348515391125, -0.44201028981688745, -0.46570589101256665, -0.49750736954407104, -0.5384054827655682, -0.5891718615531403, -0.6503314051880166, -0.7221406450734843, -0.8045727018645944, -0.8973092977798952, -0.999740110619202, -1.1109695726825328, -1.2298310309366989, -1.3549079990680797, -1.4845620521371659, -1.6169667449210678, -1.750146779959082, -1.882021514713453, -2.0104517825846715, -2.133288912700449, -2.2484247707446383, -2.3538416092500016, -2.447660511682024, -2.528187240488172, -2.5939543545369435, -2.6437585447531142, -2.6766922463018044, -2.692168718765528, -2.689939939190063, -2.6701068229340756, -2.6331214698136765, -2.57978132364165, -2.5112153272705013, -2.4288623479168048, -2.3344423341540304, -2.229920841938163, -2.117467728054166, -1.99941095148392, -1.8781865428989932, -1.756285896820823, -1.6362016076343133, -1.520373107930122, -1.411133374649191, -1.3106579450116322, -1.220917430782255, -1.143634637338643, -1.0802472852507796, -1.0318771992922775, -0.9993066762088493, -0.9829625719069318, -0.9829084651469593, -0.9988450628010285, -1.0301188159367296, -1.0757385211818893, -1.1343994927452263, -1.2045147117088069, -1.2842521951059205, -1.3715776818261631, -1.464301609060944, -1.5601292547833503, -1.6567128509928535, -1.751704430818312, -1.8428081610148177, -1.9278309301243859, -2.0047300110663766, -2.0716566939191465, -2.126994888189826, -2.1693938213347552, -2.197794108496189, -2.2114466336630705, -2.2099238606350156, -2.1931233788485938, -2.1612636796924978, -2.1148723486859358, -2.054767043146366, -1.9820297991981743, -1.8979753719012433, -1.804114453999749, -1.702112738858744, -1.5937468886663997, -1.480858537646482, -1.365307500233723, -1.2489253650107066, -1.133470636517871, -1.0205865393920353, -0.9117625239495001, -0.8083004112789414, -0.7112859917577579, -0.6215667468339827, -0.5397362035980037, -0.46612525917534964, -0.40080063167335284, -0.3435704108669916, -0.2939964996427714, -0.2514135610224364, -0.21495391979144432, -0.18357771652462734, -0.15610747892522867, -0.13126616420025314, -0.10771763946223213, -0.08410850703458381, -0.059110149532722304, -0.031459866475204566, -3.141283204547239e-16], [0.0, 0.03819400961674868, 0.0823742280585067, 0.13307077556803415, 0.19058345965080195, 0.25497012568522587, 0.3260417917183386, 0.40336471715472155, 0.48626937400992787, 0.5738661089257399, 0.6650671088148621, 0.758614117272009, 0.8531111969735851, 0.9470616990620243, 1.0389084874047927, 1.1270763765359584, 1.2100156793331858, 1.2862457256992272, 1.3543972076479622, 1.4132522294591696, 1.4617809934508048, 1.4991741311905258, 1.5248697947082943, 1.538574749915758, 1.5402788618435421, 1.5302625248312791, 1.5090967663929977, 1.4776359367679424, 1.4370030825878073, 1.3885682879911572, 1.333920445267555, 1.274833085233468, 1.2132250508000155, 1.151116931719866, 1.0905842908852266, 1.0337087999212808, 0.9825284619251603, 0.9389881304563319, 0.9048915354192121, 0.8818559981563034, 0.8712709604929201, 0.874261366970452, 0.891656828095477, 0.9239673577824573, 0.9713663235232151, 1.0336810769215314, 1.110391549238631, 1.200636905963301, 1.303230160803276, 1.4166804576278058, 1.5392225434754594, 1.6688527813242218, 1.8033708921886333, 1.9404264761750247, 2.0775692448407588, 2.2123018054624635, 2.342133773895485, 2.464635958195083, 2.5774933509427145, 2.6785556944106657, 2.765884438691473, 2.8377949973728285, 2.8928933162122674, 2.9301059048715996, 2.948702636838889, 2.9483117944255897, 2.928927019999495, 2.890906026916367, 2.834961119265222, 2.7621417637851, 2.6738096454226046, 2.571606815410603, 2.4574177031560054, 2.33332590669624, 2.2015667975557602, 2.0644770715939433, 1.9244424455966807, 1.7838447383175453, 1.6450095835324094, 1.5101560012834538, 1.381349002449987, 1.2604563224140901, 1.1491102739054397, 1.0486755797697234, 0.9602238966452068, 0.8845155740846958, 0.8219890146611815, 0.7727578134825578, 0.7366156649410939, 0.7130488351416558, 0.7012558149521932, 0.7001735955090155, 0.7085098495286838, 0.7247801617970774, 0.7473493341262915, 0.7744756967428367, 0.8043572917264732, 0.835178756313607, 0.8651577254549407, 0.8925895940844705, 0.915889529491626, 0.9336307016487829, 0.9445778023078922, 0.9477150494855188, 0.9422680193844665, 0.9277188091467939, 0.9038142070024844, 0.8705667269862686, 0.8282485488809078, 0.7773785857826774, 0.718703077099781, 0.6531702694787911, 0.5818998979753064, 0.5061483109896426, 0.42727019179535747, 0.34667791417112215, 0.2657996276003702, 0.18603719729778387, 0.1087251252367831, 0.03509155039457847, -0.03377762966505342, -0.09697055654392003, -0.15377627614447673, -0.20370594846043721, -0.24650782708654834, -0.28217559611742055, -0.310949825401965, -0.33331248471184644, -0.34997463871384193, -0.3618576231053569, -0.37006817334726294, -0.3758681367590813, -0.38063954227084906, -0.38584592619018515, -0.39299091376435186, -0.4035751324838727, -0.4190525820064504, -0.4407876059796471, -0.47001360232510164, -0.5077945708635098, -0.5549905313832009, -0.6122277529674488, -0.679874618845808, -0.7580238130845163, -0.8464813594835582, -0.9447628729640583, -1.0520972037318894, -1.1674374690705485, -1.2894792813739104, -1.4166857986320218, -1.5473190496009162, -1.6794768246907315, -1.8111342792571599, -1.9401892721315281, -2.064510362025175, -2.181986310464297, -2.290575894077394, -2.3883568125993233, -2.4735724923797573, -2.544675628255762, -2.6003673783997616, -2.6396312255060956, -2.661760641080921, -2.66637983468689, -2.653457033260328, -2.6233099131039443, -2.576602994543301, -2.5143370019502784, -2.4378303851720426, -2.3486933876268776, -2.2487952268001004, -2.1402251201637688, -2.0252480395402555, -1.9062562059381238, -1.7857174417276922, -1.6661215750989775, -1.5499261411177645, -1.4395026431289613, -1.3370846272458845, -1.2447187814505736, -1.1642202003948932, -1.0971328590323102, -1.0446962150973944, -1.007818715172331, -0.9870588151674508, -0.9826139474835922, -0.994317678261868, -1.0216451035575402, -1.063726337732816, -1.119367755603752, -1.1870804665588743, -1.2651153284417744, -1.3515036555866442, -1.4441026427245958, -1.5406444177371694, -1.638787554029276, -1.7361698195806048, -1.8304609157642784, -1.9194139653156663, -2.000914545168174, -2.073026125287383, -2.1340308674556736, -2.1824648558422877, -2.2171469711819967, -2.237200778983901, -2.2420689754543566, -2.2315201184436635, -2.20564756016929, -2.1648606890480218, -2.1098687749871075, -2.0416578913402548, -1.9614615530400927, -1.8707258601068704, -1.77107006515708, -1.66424358955892, -1.5520805929554093, -1.4364532531020602, -1.3192249361410406, -1.2022044310804803, -1.0871023866237597, -0.9754910245848467, -0.8687681136215267, -0.7681260722661466, -0.6745269341817283, -0.588683754694171, -0.5110488698612243, -0.44180924188877957, -0.3808889420813118, -0.32795863932449965, -0.2824517829580534, -0.24358699831108865, -0.21039605542475967, -0.18175663053256647, -0.15642895923593628, -0.13309538301462745, -0.11040171917148188, -0.08699934030184976, -0.061586833978489436, -0.03295012691068006, -3.3010474504090713e-16], [0.0, 0.04020692124942794, 0.08666375704975421, 0.1397831450220601, 0.19974094199542425, 0.26646833442391477, 0.33965082409109, 0.41873413540934956, 0.5029369097126293, 0.5912698742469442, 0.6825610035975626, 0.77548603337592, 0.8686035441455209, 0.96039371141476, 1.0492997181946069, 1.1337707526683678, 1.2123054668720759, 1.283494754176175, 1.3460627143152102, 1.3989047145259585, 1.4411215230945384, 1.4720485856456709, 1.4912796325361648, 1.498683944837583, 1.4944167631735787, 1.4789224942301444, 1.4529305498439196, 1.4174438387093662, 1.3737201163087356, 1.323246580017178, 1.2677082689218644, 1.2089509873793558, 1.148939613697256, 1.089712776958847, 1.0333349828149367, 0.9818473405326975, 0.9372180868525423, 0.9012941160923699, 0.8757547100115491, 0.8620686154995024, 0.8614555442132195, 0.8748530675884183, 0.9028897555902139, 0.945865261157674, 1.0037378880724406, 1.0761200019312132, 1.1622814563603723, 1.2611610141550726, 1.3713855503610282, 1.4912966361635935, 1.6189839234215133, 1.7523245841798984, 1.889027911590808, 2.0266840620056135, 2.1628158157093766, 2.294932158377957, 2.420582438729577, 2.537409841187209, 2.6432029261053773, 2.735944033939842, 2.8138534226087417, 2.8754281074547805, 2.919474498246795, 2.945134074522761, 2.951901505707391, 2.939634801820807, 2.90855726986721, 2.8592512455489816, 2.792643765060094, 2.7099845326287904, 2.612816721564728, 2.5029413154002853, 2.382375847208409, 2.2533085256662586, 2.1180488427708393, 1.9789758377490443, 1.8384852427488667, 1.6989367571616605, 1.5626026884514628, 1.4316191584427718, 1.3079410061644507, 1.193301423295125, 1.0891772384004352, 0.996760624496867, 0.9169378445526889, 0.8502754753198244, 0.7970143657003226, 0.7570713962448619, 0.7300489160385949, 0.7152515468408038, 0.7117098664902419, 0.7182103186274451, 0.7333305477499873, 0.7554792311096046, 0.782939375067538, 0.8139139657401019, 0.8465728139306883, 0.8790994135989931, 0.9097366418801014, 0.9368301666166603, 0.9588684934632082, 0.9745186771198137, 0.9826568377560888, 0.9823927612053892, 0.9730880165341428, 0.9543671931833149, 0.9261220377678576, 0.8885084533106362, 0.8419365065729204, 0.787053767620695, 0.7247224753491202, 0.6559911791216073, 0.5820616460459646, 0.5042519422233441, 0.42395669160209426, 0.3426055854785517, 0.2616212574944602, 0.18237765216567267, 0.10615999924032456, 0.03412746195580565, -0.03272054431114817, -0.09357346359345342, -0.14783336179596016, -0.19513270088628226, -0.2353456421506715, -0.2685925648198393, -0.2952376634981472, -0.315879668624391, -0.33133591406576174, -0.3426201503312947, -0.35091466635594104, -0.35753743316627773, -0.36390511516043317, -0.37149290583289385, -0.3817922316967309, -0.3962674286543893, -0.416312527557326, -0.44320928929098524, -0.4780876042656051, -0.5218893172557587, -0.5753364573987481, -0.6389047468052244, -0.7128031322618597, -0.7969599360949721, -0.8910160580876453, -0.9943254844758018, -1.105963176866144, -1.2247402279881499, -1.349225987160299, -1.4777766808254995, -1.6085698869505387, -1.7396440706821201, -1.8689422562347675, -1.9943587999147692, -2.113788144274881, -2.225174375840988, -2.3265603801769403, -2.4161353890642365, -2.4922797453444314, -2.5536057708400675, -2.5989937103504315, -2.62762183793776, -2.6389899478665937, -2.632935608350145, -2.6096427279181165, -2.569642167576771, -2.5138043225144355, -2.443323790258329, -2.359696433184307, -2.264689327438581, -2.1603042631279132, -2.0487356178250287, -1.9323235631472042, -1.8135036790014316, -1.69475413920936, -1.5785416934164667, -1.4672677019245781, -1.3632154815548476, -1.2685001917839613, -1.1850224318737506, -1.114426632937769, -1.058065215951623, -1.0169693503541157, -0.9918269914137751, -0.9829687017527476, -0.9903615775301373, -1.013611407286896, -1.0519729960278337, -1.1043683935157533, -1.1694125786842728, -1.2454459760823764, -1.330573019614256, -1.4227058374215125, -1.5196120129862147, -1.6189652842687174, -1.7183979771613414, -1.815553933282733, -1.9081406859834407, -1.9939796624654502, -2.0710532434811793, -2.1375475937904143, -2.191890284347116, -2.2327818583544596, -2.2592206445885035, -2.2705202889831417, -2.266319655230455, -2.246584932629582, -2.2116039799804548, -2.1619731232670643, -2.098576807558683, -2.02256067549269, -1.935298801680587, -1.8383559505706253, -1.7334458413513445, -1.6223864945914759, -1.5070537993095392, -1.3893344745556295, -1.2710796055862974, -1.1540599112721752, -1.0399238471805003, -0.9301595692180477, -0.8260616778813787, -0.7287035357421474, -0.6389158040561775, -0.5572716820611665, -0.4840791587376005, -0.4193804059464429, -0.3629582584910833, -0.3143495453993142, -0.27286486214237676, -0.23761420998661248, -0.20753778030849435, -0.1814410322095529, -0.15803310437818138, -0.135967519535819, -0.11388408402462663, -0.09045085751478434, -0.06440506909359334, -0.03459188608033514, -3.4728682187385857e-16], [0.0, 0.04230549340875981, 0.09106944644289246, 0.14658358033815255, 0.2088984333357929, 0.2778192854455064, 0.35290898997709175, 0.4334976547251509, 0.5186989364696087, 0.6074325390629414, 0.6984523422194363, 0.7903794393543758, 0.8817392322345433, 0.971001621134308, 1.0566232444439445, 1.1370906634400717, 1.2109633577293561, 1.2769153955399928, 1.3337746706608138, 1.3805586537875074, 1.4165056889890997, 1.4411009739354952, 1.4540964927783107, 1.4555243199375902, 1.445702877816473, 1.4252359075513172, 1.3950040949214617, 1.3561494789234316, 1.3100529536226528, 1.2583053501419315, 1.2026727506014228, 1.145056835332174, 1.0874511949630192, 1.03189464671677, 0.9804226766878701, 0.9350181848740091, 0.8975627358393661, 0.8697895143515327, 0.8532391521461902, 0.8492195298555724, 0.858770568530128, 0.8826349102114363, 0.9212352494346063, 0.974658920670376, 1.042650174364416, 1.124610390586887, 1.2196062888486625, 1.3263860000270775, 1.4434026762908498, 1.5688451320822978, 1.7006748380970202, 1.8366684350070612, 1.9744647982283652, 2.111615572682184, 2.245638010025182, 2.3740688823750804, 2.4945182176024945, 2.6047216025390516, 2.7025898319695223, 2.786254742293504, 2.8541101577990573, 2.9048469924377818, 2.9374816880447057, 2.9513773277571533, 2.9462569371203253, 2.9222086707996215, 2.879682775441023, 2.819480414345868, 2.7427346325105066, 2.650883926536491, 2.545639058427674, 2.428943911123931, 2.302931322932338, 2.1698749544409517, 2.032138332239006, 1.892122276652046, 1.7522119542503383, 1.614724799342653, 1.4818605220043848, 1.355654364126937, 1.237934680953181, 1.1302858157050748, 1.0340171019686948, 0.950138675796841, 0.879344610817122, 0.8220037091779, 0.7781580933904358, 0.7475295536701775, 0.7295334169359515, 0.7232995218263498, 0.7276997133969186, 0.7413811157444538, 0.7628043044532407, 0.7902853867793436, 0.8220409086279483, 0.8562344457514681, 0.8910237036381101, 0.9246069469920266, 0.9552676055157395, 0.9814159571506745, 1.0016268715596055, 1.0146727033181415, 1.019550553274694, 1.0155032645416737, 1.002033682830297, 0.9789118851985381, 0.9461752623389105, 0.90412152272266, 0.8532948676275768, 0.7944657597662161, 0.7286048705414444, 0.656851937821166, 0.5804803938712817, 0.5008587285284831, 0.41940963320949237, 0.33756802494767696, 0.2567390750076611, 0.17825736315072388, 0.1033482464321335, 0.0330924713521606, -0.03160502819744849, -0.09004131524069324, -0.14173591611369363, -0.18644501851538486, -0.22416901464759484, -0.2551531767298564, -0.27988143159323525, -0.29906338149179373, -0.3136148951396954, -0.324632761793193, -0.33336405765730986, -0.3411710140219969, -0.34949229674497717, -0.35980170391963834, -0.37356536029217036, -0.3921985313579273, -0.4170231958929345, -0.449227502499339, -0.4898281938278737, -0.5396370124731371, -0.5992320068039324, -0.6689345355335581, -0.7487926295951868, -0.8385712123337752, -0.9377495080664812, -1.0455257889509386, -1.1608294253247045, -1.2823400198557933, -1.4085132256014476, -1.5376126769326215, -1.6677473045525661, -1.7969131655002544, -1.9230387996421827, -2.044033028762858, -2.1578340454211924, -2.262458598049148, -2.3560500674376224, -2.43692424816135, -2.503611696284429, -2.554895580774788, -2.589844078652183, -2.6078364805520793, -2.6085823210598473, -2.5921330132828793, -2.558885645672155, -2.509578786729765, -2.445280335363208, -2.367367646570505, -2.2775003491579464, -2.1775864497145165, -2.0697424807281792, -1.9562485965002974, -1.8394996447980585, -1.7219533419083781, -1.606076751446327, -1.494292311112395, -1.388924665479408, -1.2921495464457309, -1.2059458965868486, -1.1320523553739563, -1.071929125917752, -1.0267261130106968, -0.9972580748585607, -0.9839873646149073, -0.9870146577016083, -1.0060778712953364, -1.0405592878955952, -1.0895007002938932, -1.1516262052669837, -1.225372092535821, -1.3089231083533777, -1.4002542235606619, -1.4971769076962804, -1.5973888068524298, -1.6985256459303117, -1.7982141275907886, -1.8941245816459717, -1.984022130286872, -2.0658151760411037, -2.1376000896211487, -2.1977010720712804, -2.244704287403157, -2.277485505180618, -2.2952306537047296, -2.297448859557987, -2.2839777339535714, -2.254980856036852, -2.210937593322468, -2.1526255851437854, -2.0810963917819247, -1.9976449754986723, -1.9037738260281116, -1.8011526686275, -1.6915747945137718, -1.5769111289798263, -1.459063199913267, -1.3399161877487995, -1.221293226718074, -1.1049120869960358, -0.9923452990822059, -0.8849846872938244, -0.7840111610311578, -0.6903704735342171, -0.6047555017280051, -0.5275954314135882, -0.4590520537921698, -0.39902319660966723, -0.34715313068463544, -0.3028496148237824, -0.26530707360074285, -0.23353524740070142, -0.20639251639687264, -0.18262298316546757, -0.1608963053773582, -0.13984920274252918, -0.11812752278625827, -0.09442773906511263, -0.06753677332660053, -0.036369079392309635, -3.655086388617741e-16], [0.0, 0.04446966826029928, 0.09554951172872507, 0.153407999915542, 0.21797011492200005, 0.28891711065481307, 0.36569315060572544, 0.44751866456318345, 0.5334100886276568, 0.6222054852903498, 0.7125953853693313, 0.8031580552242308, 0.8923982744225929, 0.9787886139362373, 1.0608121354532687, 1.1370053903079602, 1.20600058297657, 1.2665657794662804, 1.3176420849142256, 1.3583767862720368, 1.3881515533424382, 1.4066049122708641, 1.413648346896998, 1.4094755416400866, 1.3945644508975403, 1.3696720600139027, 1.335821887233835, 1.2942844600787728, 1.2465511786711683, 1.1943021481747649, 1.1393687184518058, 1.083691607318113, 1.0292756008954143, 0.978141917526501, 0.9322793881362686, 0.8935956440483295, 0.8638695120594375, 0.8447057957145674, 0.8374935716316746, 0.8433690515388926, 0.8631839562495016, 0.8974802196054126, 0.9464716915554933, 1.0100333436050657, 1.087698300910382, 1.1786628376593342, 1.2817992806619036, 1.395676574964275, 1.5185880794866733, 1.6485859847308628, 1.7835215828385698, 1.9210904766936616, 2.0588816928948637, 2.194429566299312, 2.325267193863837, 2.448980214440885, 2.5632596600617137, 2.665952643371068, 2.755109694832691, 2.829027640940955, 2.88628701908481, 2.925783153393101, 2.9467501657268587, 2.948777363337381, 2.931817625512472, 2.896187601391269, 2.842559725423828, 2.7719462509602915, 2.685675691459885, 2.5853622382206383, 2.4728688889922723, 2.3502651693372396, 2.219780454581831, 2.0837540016132614, 1.9445828741989684, 1.8046689911621563, 1.6663665425836314, 1.531931004885677, 1.4034709416020217, 1.2829037039903783, 1.1719160462427218, 1.0719305463898225, 0.9840785791685952, 0.909180424727236, 0.847732921112281, 0.7999048833684215, 0.765540322357515, 0.7441693067444363, 0.7350261266685484, 0.7370742419588707, 0.7490373356575553, 0.7694356490443337, 0.7966266508160759, 0.8288489935539645, 0.8642686374873806, 0.9010259765601745, 0.9372827859415334, 0.9712678236940594, 1.00131996187824, 1.0259277927767978, 1.0437647523165066, 1.0537189226570065, 1.0549168162345923, 1.0467406007186801, 1.0288383943721522, 1.0011274399024979, 0.9637901475421342, 0.9172631802037953, 0.8622199305428817, 0.7995469071820765, 0.7303147010201054, 0.65574433861409, 0.5771699446981734, 0.4959987271171232, 0.4136693625520328, 0.3316098987950104, 0.2511962980885305, 0.1737127260010843, 0.10031464200731371, 0.03199567263203903, -0.030440852363279248, -0.0864049431620833, -0.135536957120285, -0.17771811274658386, -0.21307422291836928, -0.24197253702954738, -0.26501176191965115, -0.28300550995298296, -0.29695959496877294, -0.3080437586276631, -0.31755855681894063, -0.32689826451557724, -0.33751076447962264, -0.3508554677818014, -0.3683603700711989, -0.39137937544578666, -0.4211510188674042, -0.45875968829504044, -0.5051003897620322, -0.5608480138894776, -0.6264319528777177, -0.7020167855422568, -0.7874895977088753, -0.8824543399813795, -0.9862334486542197, -1.0978767727541194, -1.2161776654251217, -1.3396959157446715, -1.4667870221440253, -1.5956371453023526, -1.7243029308107174, -1.8507552637950415, -1.9729259123074345, -2.0887559363438823, -2.1962446869002403, -2.29349819593378, -2.3787757641381346, -2.4505335890144426, -2.507464340049742, -2.5485316793983013, -2.572998843128844, -2.5804505370509525, -2.570807559011528, -2.544333732526332, -2.50163492047175, -2.4436500778205144, -2.371634494408531, -2.2871355677635425, -2.191961627469459, -2.088144501922878, -1.9778966714883799, -1.8635639851997554, -1.7475750279922513, -1.6323883092631224, -1.5204384992560205, -1.4140829659472833, -1.3155498611021545, -1.2268889700259769, -1.149926476060963, -1.0862246995906963, -1.0370477544146262, -1.003333924671653, -0.985675406414275, -0.9843058833260341, -0.9990962201790642, -1.0295583649660698, -1.0748573558969554, -1.1338311373597354, -1.2050177041765053, -1.286688920524945, -1.3768902029387566, -1.4734851196471692, -1.5742038444755448, -1.6766943153491995, -1.778574887226831, -1.8774872384567807, -1.971148288794547, -2.057399916601557, -2.1342553212830153, -2.1999409633202736, -2.252933126134688, -2.2919882786842196, -2.3161665717848754, -2.324847970838356, -2.317740708730755, -2.2948819306673798, -2.2566305929876296, -2.2036528658763066, -2.1369004707381074, -2.0575825523980753, -1.9671318400929885, -1.8671659856823997, -1.7594450793755942, -1.6458264298515877, -1.5282177548854083, -1.4085299591103746, -1.2886306766842903, -1.1702997284591905, -1.0551875865805393, -0.9447778557707858, -0.8403546720600391, -0.7429757892047789, -0.6534519738168142, -0.5723331661032004, -0.499901688250367, -0.43617260129089674, -0.38090112833588385, -0.3335968819431458, -0.29354446064498135, -0.2598298186098045, -0.23137166709081705, -0.20695704035172166, -0.18528005529345257, -0.16498281560643258, -0.1446973598767797, -0.1230875299377515, -0.09888964142321814, -0.07095087276669082, -0.03826435089587624, -3.84594372545278e-16], [0.0, 0.04667876589314573, 0.10006145944322882, 0.16019207944161132, 0.22687094293059656, 0.29965826447584076, 0.37788452660743443, 0.4606673811016934, 0.5469346495098829, 0.6354528309285897, 0.7248603795312806, 0.8137048875502418, 0.9004832044544978, 0.9836834427061848, 1.0618277667729674, 1.1335148364366217, 1.1974607785728233, 1.2525375934667375, 1.2978079616327198, 1.332555503578802, 1.356309655882599, 1.3688644595923203, 1.3702907080524729, 1.3609410670278967, 1.3414479563359127, 1.312714164695949, 1.2758963536068355, 1.2323817871524, 1.1837587981694635, 1.1317816628210575, 1.0783307012217522, 1.025368547671106, 0.9748936370577619, 0.9288920314555232, 0.8892887608284263, 0.8578998727593893, 0.8363863775964283, 0.8262112374824945, 0.8286004812408304, 0.8445094335773506, 0.874594928758431, 0.9191942386676197, 0.9783112863285491, 1.051610542459614, 1.1384188186256128, 1.2377349805662576, 1.3482474139612812, 1.4683588869276982, 1.5962182735541335, 1.7297584351877753, 1.8667394051323571, 2.004795891620585, 2.141488006629321, 2.274354046975365, 2.400964101189386, 2.5189732322520326, 2.62617299300233, 2.720540067769475, 2.800280899673854, 2.863871256515666, 2.9100898069673353, 2.9380449200351726, 2.947194061031593, 2.937355332710261, 2.908710896500193, 2.8618022014022597, 2.79751714239901, 2.717069461452868, 2.62197088768161, 2.5139966846473736, 2.3951454277205615, 2.2675939694289635, 2.1336486623169257, 1.9956939944338172, 1.8561398501022708, 1.7173686367288232, 1.5816835164822192, 1.4512589497830706, 1.3280946965637832, 1.2139743327231434, 1.110429225343527, 1.0187087739064433, 0.9397575693276607, 0.8741999519935477, 0.8223322683395092, 0.7841229373568479, 0.7592202483841369, 0.7469676243090101, 0.7464259044720992, 0.7564020335309707, 0.77548339041101, 0.802076858943114, 0.8344516320720219, 0.8707846572499058, 0.90920757380621, 0.9478539650209574, 0.9849057489222766, 1.0186375623466877, 1.0474580516843461, 1.069947069418356, 1.0848878858320707, 1.0912936572675436, 1.0884275427036314, 1.0758160253632232, 1.0532551713806935, 1.0208097388364707, 0.9788052331294174, 0.927813184117205, 0.8686300922062705, 0.8022506503137069, 0.7298359923589961, 0.652677843087287, 0.5721595454880579, 0.48971501833778064, 0.406786745582758, 0.32478392019169905, 0.24504185726217595, 0.16878375479974425, 0.0970858166598673, 0.030846662300372432, -0.029238165463116295, -0.08269591767971918, -0.12929005592124168, -0.16902700776183804, -0.20215607465834054, -0.22916248484415247, -0.2507537631800268, -0.2678397649784207, -0.281506887186628, -0.29298712374651725, -0.30362276853810466, -0.31482768557408575, -0.3280461590655923, -0.3447104032327208, -0.36619785153748896, -0.39378935631165385, -0.42862941219224115, -0.4716894707440797, -0.5237353402373522, -0.5852995655450071, -0.6566595609610169, -0.7378221264328726, -0.8285148187774085, -0.9281844778592684, -1.0360030277310777, -1.1508804888587052, -1.2714849543848135, -1.3962691055125374, -1.5235026729903443, -1.651310097585093, -1.7777125062414147, -1.9006730058004928, -2.0181442056268923, -2.1281168166047797, -2.228668138396386, -2.3180092405854804, -2.394529666613553, -2.4568385417780285, -2.5038010468019394, -2.534569324709808, -2.54860701841557, -2.545706786419579, -2.5260003106890605, -2.4899604901057075, -2.4383957004318693, -2.372436192986905, -2.2935128944526104, -2.203329054772987, -2.103825364441651, -1.99713932228814, -1.8855597762384586, -1.771477678942083, -1.657334194665592, -1.5455673611004255, -1.4385585480327234, -1.3385799631981037, -1.247744433850049, -1.1679586411002179, -1.100880904166235, -1.0478845052060086, -1.010027414999766, -0.9880291285197811, -0.9822551510732647, -0.9927094943054632, -1.0190353513168606, -1.0605239261011743, -1.1161311991676042, -1.184502223271052, -1.2640023652036008, -1.352754745918645, -1.4486829858324215, -1.5495582384938709, -1.6530493969130926, -1.7567752850633074, -1.8583576041257912, -1.955473389927725, -2.045905754992533, -2.1275917352068325, -2.198666136105983, -2.2575003752950753, -2.302735443009226, -2.3333082491464703, -2.3484707886418423, -2.3478017337390966, -2.331210247188074, -2.298932000073619, -2.2515175671951004, -2.1898135570136414, -2.1149370076530536, -2.0282437410135556, -1.9312915098207715, -1.8257988939216463, -1.7136009994230978, -1.5966030850243982, -1.4767332824585642, -1.3558955913728148, -1.2359243130109807, -1.1185410422083837, -1.0053152646870989, -0.897629508346655, -0.7966498757190394, -0.7033026431088443, -0.6182574537744782, -0.5419174618355316, -0.47441660472826214, -0.41562399948684386, -0.36515527649545504, -0.3223904881982699, -0.28649806398769306, -0.25646413027724496, -0.231126380406957, -0.20921156587439954, -0.18937559124529968, -0.17024513217856987, -0.15045966084470186, -0.12871275646728345, -0.10379160089803383, -0.07461360944652057, -0.04025922431950303, -4.0436001113043336e-16], [0.0, 0.04891168557590492, 0.1045624988360905, 0.16687187232641923, 0.23551746516145944, 0.3099425137287049, 0.3893698280138339, 0.4728220752424618, 0.5591478274522979, 0.647052697747807, 0.7351347552146543, 0.8219232942228044, 0.9059199430503728, 0.98564103175254, 1.0596601016715763, 1.1266494299362821, 1.185419462017571, 1.2349550934542635, 1.2744478170893907, 1.3033228527277645, 1.3212604995661343, 1.328211095005564, 1.3244031229766426, 1.3103441867224597, 1.286814740806705, 1.2548546604506583, 1.215742908561643, 1.1709707374225564, 1.1222090285244921, 1.0712705262416022, 1.0200678551159936, 0.9705683230311559, 0.9247466006251002, 0.8845364286508586, 0.8517825380132569, 0.8281939709789848, 0.8152999663780682, 0.8144095170258354, 0.8265756253503996, 0.8525651752547242, 0.8928352071588245, 0.9475162321187273, 1.0164030535670763, 1.0989533856388947, 1.19429436961812, 1.3012368993519763, 1.4182974772053913, 1.5437271389152105, 1.6755468130610287, 1.811588323050785, 1.9495401004219781, 2.086996561325237, 2.221510006189893, 2.350643838060689, 2.4720258595643996, 2.5834004028265976, 2.682678071093439, 2.7679819247640935, 2.837689026725763, 2.8904663703318927, 2.9253003454566597, 2.941519050597486, 2.9388069282812146, 2.917211382947997, 2.8771412306185815, 2.81935702337333, 2.7449534842751806, 2.6553344751725576, 2.552181096283708, 2.4374136783086233, 2.3131485711153146, 2.1816507543383157, 2.0452833915840576, 1.9064555190493573, 1.7675690995843005, 1.6309666836377432, 1.4988808989131304, 1.3733869414709132, 1.2563591637018081, 1.149432751011532, 1.0539713517962368, 0.9710413775169686, 0.9013935250707146, 0.8454518962800659, 0.8033109035661425, 0.7747399613103692, 0.759195773714773, 0.7558418467719877, 0.7635746787434645, 0.7810559245504378, 0.806749688578911, 0.8389639810037638, 0.8758952777247491, 0.915675055645194, 0.9564171349137361, 0.9962646487876906, 1.0334354801351529, 1.0662650507154583, 1.0932454239936056, 1.1130597824032162, 1.1246114630918531, 1.1270468791138095, 1.1197718121435594, 1.1024607340363255, 1.0750589936353674, 1.0377778876055277, 0.9910828151736821, 0.9356748919329674, 0.8724665629281733, 0.8025519059563857, 0.7271724486287725, 0.6476794339450035, 0.5654935561719183, 0.48206324954427304, 0.3988226452327833, 0.31715031636879926, 0.23832990661110148, 0.16351368544396255, 0.09368999446658369, 0.029655445401039204, -0.028007394943962077, -0.07894624176391607, -0.12304881975021621, -0.16044581970335903, -0.19150700007456828, -0.21683052854474644, -0.23722583571492617, -0.25369042311628576, -0.267381226726054, -0.27958128095288215, -0.2916625529667186, -0.3050459201014539, -0.3211593412140211, -0.3413953243209248, -0.36706881620220194, -0.39937663431827, -0.43935952740284806, -0.48786788927125535, -0.5455320622148441, -0.6127380540001494, -0.6896093587273452, -0.7759954199409377, -0.8714671081999982, -0.9753194089460732, -1.0865813343574033, -1.2040328895053767, -1.326228743130618, -1.4515280812539475, -1.5781299619676998, -1.7041133461543305, -1.8274808551952608, -1.9462052061178703, -2.05827719966983, -2.1617540894624487, -2.2548071418607374, -2.3357672072755475, -2.4031671637602905, -2.4557801624326907, -2.4926526996270724, -2.513131660563954, -2.516884620819166, -2.50391285156151, -2.4745566485263146, -2.429492788760767, -2.3697241088173198, -2.2965613886395766, -2.21159791220412, -2.1166772544606736, -2.0138550098563788, -1.9053553266496623, -1.7935232396340672, -1.6807738986200533, -1.5695398684583328, -1.462217726568332, -1.3611152045898411, -1.26840011135489, -1.1860522350697529, -1.1158193543249848, -1.059178391946606, -1.0173026250666002, -0.9910357220430239, -0.9808732154592197, -0.9869518442956202, -1.009047011775664, -1.0465784128751345, -1.0986236917322312, -1.1639397989138165, -1.2409915363056898, -1.327986607725356, -1.4229163403200855, -1.5236011091166466, -1.6277393879376536, -1.7329592669176976, -1.8368712220235472, -1.9371208965965845, -2.0314406595595234, -2.117698739394042, -2.193944796399937, -2.25845088648071, -2.3097468854851977, -2.346649581081481, -2.3682847958171167, -2.374102076544864, -2.3638816675230387, -2.3377336727391285, -2.2960895027175194, -2.2396858875928616, -2.169541916984579, -2.0869297338209223, -1.993339659667997, -1.890440659664612, -1.7800371626918328, -1.6640233343365305, -1.5443359546021083, -1.422907077923352, -1.3016176493202594, -1.1822532176712837, -1.0664628260152056, -0.9557220711193537, -0.8513012125535746, -0.754239078058284, -0.6653233604945935, -0.5850777359594312, -0.5137560569307772, -0.4513436930106951, -0.3975659095203527, -0.35190299545176423, -0.3136116815779505, -0.2817522311396902, -0.25522044341956523, -0.23278368822505713, -0.21311998987169617, -0.19485910514622445, -0.1766244927606634, -0.15707505311931685, -0.13494552723792122, -0.1090844820809549, -0.07848887540873649, -0.04233428475072494, -4.246151540548198e-16], [0.0, 0.051147110603530214, 0.10900995530434819, 0.17338442462110493, 0.2438286196383173, 0.31967389187905704, 0.4000423266789293, 0.48387021736562436, 0.5699369200433345, 0.6568983367355296, 0.7433241516731977, 0.8277378447707455, 0.9086584303931988, 0.9846428203487781, 1.0543276889311015, 1.1164697253712694, 1.1699831951081128, 1.2139737949939085, 1.2477678773753806, 1.2709362317197426, 1.2833117472829438, 1.2850004328977394, 1.276385436497007, 1.258123883330087, 1.2311365335703486, 1.1965904426001757, 1.155874986113939, 1.110571782802971, 1.062419205477453, 1.0132723130405334, 0.9650591571655448, 0.9197345157369345, 0.879232177570541, 0.8454169477352443, 0.8200375587456438, 0.8046816594885783, 0.8007340112174959, 0.8093389492534505, 0.8313680718266497, 0.8673939960948146, 0.917670878705894, 0.982122237786803, 1.060336438838999, 1.1515700229598653, 1.2547588665872298, 1.368536972220222, 1.49126250396237, 1.6210505048275194, 1.755811568905963, 1.893295594751495, 2.0311396203514818, 2.1669186379075485, 2.298198210928848, 2.4225876687223327, 2.5377926354615323, 2.6416656631111572, 2.73225377932727, 2.8078418320611718, 2.866990610281933, 2.9085688426460563, 2.931778320123938, 2.936171551047944, 2.9216615338337206, 2.8885234194503058, 2.8373880280352344, 2.7692273771925566, 2.685332568779661, 2.5872845617835893, 2.476918526818805, 2.35628262877242, 2.2275922145230918, 2.0931804893156234, 1.9554468457192717, 1.8168040612132335, 1.6796256031030703, 1.5461942721728181, 1.4186533794526037, 1.2989615846909766, 1.1888524322306004, 1.0897995023233782, 1.0029879564192024, 0.9292930970858482, 0.8692663908759455, 0.8231292199095637, 0.7907744396894103, 0.771775631343985, 0.7654037507528079, 0.7706506994004722, 0.7862591766752937, 0.8107580246996459, 0.8425021482615874, 0.8797159871154846, 0.9205394383554202, 0.9630750746196985, 1.0054354807486978, 1.0457895376664714, 1.0824065174356496, 1.1136969166716475, 1.138249045127907, 1.1548604999575403, 1.1625637910040318, 1.1606455350390017, 1.1486588032796392, 1.1264283825753751, 1.0940488919146527, 1.0518758778086124, 1.000510190092866, 0.9407761092914368, 0.8736938536668276, 0.8004472345189053, 0.7223473486959976, 0.6407932946555254, 0.5572309703519605, 0.4731110559725406, 0.3898473010066822, 0.3087762229562956, 0.2311192845247441, 0.15794854842649445, 0.09015671578656725, 0.028432337837479855, -0.026759145759969558, -0.07518804167289478, -0.11686637621170848, -0.15204704701007118, -0.1812161713129223, -0.20507882713857595, -0.22453855666693714, -0.24067116495809165, -0.25469349736006847, -0.2679280118953827, -0.28176407513143015, -0.29761699866729274, -0.31688589612803214, -0.3409114758154024, -0.37093489097940985, -0.4080587478216259, -0.45321132131229636, -0.5071149519021473, -0.5702594941189325, -0.6428815633740261, -0.724950183152389, -0.8161592747015219, -0.9159272593577239, -1.0234038640447698, -1.1374840377427946, -1.2568287054344789, -1.3798919107447327, -1.5049537336120922, -1.630158219028413, -1.7535554209653006, -1.8731465554303965, -1.986931170986825, -2.0929551862443327, -2.189358613346889, -2.274421785195432, -2.346608932187283, -2.404608011030682, -2.4473657723928866, -2.474117163771349, -2.484408296411588, -2.4781123571353634, -2.4554380138989145, -2.416930043682974, -2.363462098532494, -2.296221715631495, -2.216687865554164, -2.1266015146508015, -2.027929848430167, -1.922824958572306, -1.8135779329990265, -1.7025694028523237, -1.592217689441375, -1.4849257559859617, -1.3830282017514195, -1.2887395390894676, -1.2041049668532733, -1.130954797263388, -1.07086360890055, -1.025115088118903, -0.9946733874712664, -0.98016167595414, -0.9818483857427035, -0.999641477726914, -1.0330908580097282, -1.0813988842098319, -1.1434387086236741, -1.2177800197067383, -1.3027215684402762, -1.396329706202624, -1.4964820196406596, -1.6009150291506755, -1.7072748237965534, -1.8131694390655764, -1.916221746366704, -2.0141216154794424, -2.1046761333991935, -2.1858567145983954, -2.255842017315079, -2.313055686088189, -2.3561980697436717, -2.3842712131885424, -2.396596586993011, -2.3928251967361414, -2.372939900064331, -2.3372499487823544, -2.2863779614067514, -2.2212397138449966, -2.143017307759239, -2.053126433533287, -1.9531785837569065, -1.8449391904050707, -1.7302827515999024, -1.6111460797911312, -1.4894808408369853, -1.3672065619758373, -1.2461652659387281, -1.1280788390799483, -1.0145101647216563, -0.906828950920576, -0.8061830571963279, -0.7134759805961941, -0.6293510014747414, -0.5541823175883872, -0.4880733158814594, -0.43086194918389803, -0.3821330045293687, -0.3412368754628045, -0.30731428690302826, -0.2793262719515575, -0.2560885692120045, -0.23630949995872172, -0.2186302995744743, -0.20166681915709184, -0.18405148250039716, -0.16447438151067134, -0.14172241953326875, -0.11471546632343503, -0.08253856908962527, -0.04446936909140461, -4.451648696675842e-16], [0.0, 0.05336371464901065, 0.11336168139497572, 0.17966837819980874, 0.2517265070623794, 0.3287616080761262, 0.4098028603954423, 0.4937095274390859, 0.5792023550476828, 0.6648991002543836, 0.7493532581662634, 0.8310949680082719, 0.9086730188756039, 0.9806968427472473, 1.0458773777151618, 1.1030657083485014, 1.1512884420905622, 1.1897788593226077, 1.2180029782938169, 1.2356798019539903, 1.2427951587154469, 1.2396087097068687, 1.2266538671622471, 1.2047305479132546, 1.1748908680340617, 1.1384180649566753, 1.0967991073009065, 1.0516916158638412, 1.0048858675654113, 0.9582627838873415, 0.9137489131662797, 0.8732694992413955, 0.8387007852537194, 0.8118227293542148, 0.7942733079063614, 0.7875055513960861, 0.7927483993410487, 0.8109723743869265, 0.8428609645318585, 0.8887884687007054, 0.9488049079298779, 1.0226284359358366, 1.10964550293251, 1.2089188396322885, 1.319203138991138, 1.4389681260902365, 1.5664285261871012, 1.699580271862936, 1.8362421365142938, 1.974101846988074, 2.1107656162747266, 2.2438099506397533, 2.3708345265557615, 2.4895149027882475, 2.59765383277253, 2.6932299720483357, 2.7744428343141183, 2.839752936229837, 2.8879161833577895, 2.918011684878448, 2.9294623396788912, 2.9220477073287547, 2.8959088601828222, 2.851545102941365, 2.78980263883845, 2.7118554525268532, 2.6191788640461007, 2.513516381519472, 2.3968406382207084, 2.2713093385515744, 2.139217253916088, 2.002945400657859, 1.8649085959553535, 1.727502622332594, 1.59305223643736, 1.4637612328934335, 1.3416657200075117, 1.2285916822792164, 1.1261177970795686, 1.0355443422120054, 0.9578688805977614, 0.8937692417605314, 0.8435941412416018, 0.8073615929592879, 0.7847650804179599, 0.7751872652189655, 0.7777208301250809, 0.7911958834151994, 0.8142131955969873, 0.8451824025073589, 0.8823641937402772, 0.9239154149652922, 0.9679359491874391, 1.0125162068289404, 1.055784048459138, 1.095949987111584, 1.1313495687321593, 1.160481908020298, 1.182043460706159, 1.1949562394815747, 1.1983898261511374, 1.191776693401503, 1.1748205218334313, 1.1474973772173136, 1.1100497948075274, 1.0629739974166141, 1.0070006473000626, 0.9430696944000023, 0.8723000310855171, 0.7959547925325338, 0.715403249103733, 0.6320803198663539, 0.5474447926880217, 0.46293736481047515, 0.37993961775194995, 0.2997350118818538, 0.22347292981293013, 0.1521367153282126, 0.08651654802396003, 0.027187865931417275, -0.02550409765745932, -0.07145325737455609, -0.1107948639470705, -0.14390087907970678, -0.17136865701532325, -0.1940032279564168, -0.21279364626502129, -0.2288840223515801, -0.2435399974456015, -0.2581115414377334, -0.27399305260339557, -0.2925818117325788, -0.315235890094315, -0.34323262952624134, -0.3777288032326257, -0.4197235277895678, -0.47002493129902617, -0.5292214912011631, -0.597658840197196, -0.6754227028993652, -0.7623284725841526, -0.8579177705957097, -0.9614621546921395, -1.0719739613561503, -1.1882240853458323, -1.3087663221044714, -1.4319677295514148, -1.5560443095048744, -1.6791011694982658, -1.7991762065886128, -1.9142862589653866, -2.0224746012210417, -2.1218586168731197, -2.210676468279759, -2.2873315998998045, -2.3504339556229485, -2.398836863622457, -2.431668641154833, -2.448358094585048, -2.4486532336929816, -2.4326326805328513, -2.4007094278498284, -2.3536267860417355, -2.2924465463862536, -2.218529577106904, -2.1335092531839472, -2.0392582960908263, -1.9378497615311692, -1.8315130577640963, -1.7225860006573313, -1.6134640111287786, -1.5065476336442452, -1.4041895990964028, -1.3086426705554328, -1.2220094956371312, -1.146195644892328, -1.08286694272328, -1.0334120976193686, -0.998911514375747, -0.9801130254140323, -0.9774151148895623, -0.9908580319106168, -1.020123002218941, -1.0645395556317359, -1.1231007940917728, -1.1944862369924947, -1.277091701112002, -1.3690655063590023, -1.468350149635559, -1.5727284610624344, -1.679873152687122, -1.7873985921090267, -1.8929135840658025, -1.9940739230923654, -2.088633490327341, -2.174492707106048, -2.2497432261242833, -2.312707835963085, -2.361974674255317, -2.3964249857750075, -2.4152538207435765, -2.417983241738116, -2.4044677904825313, -2.3748921539954977, -2.3297611584311637, -2.269882403843143, -2.1963420295004137, -2.110474262975376, -2.013825553024257, -1.9081142127269677, -1.79518660239586, -1.6769709589360045, -1.555430027822884, -1.4325136745280798, -1.310112643655635, -1.1900145965645779, -1.0738634928769493, -0.963123289725153, -0.8590468172454202, -0.7626505526290988, -0.6746958614663174, -0.5956771080499679, -0.5258168599708344, -0.4650682311696212, -0.41312422617214895, -0.3694337710713968, -0.3332239483698251, -0.30352779726672546, -0.2792169022464725, -0.25903787434473746, -0.24165173417825275, -0.22567513607050207, -0.20972233009728206, -0.1924467446323514, -0.17258108630307029, -0.14897489675885248, -0.12062857519358583, -0.08672297034970157, -0.046643763335028815, -4.658115920407988e-16], [0.0, 0.05554036752282504, 0.11757646121444242, 0.18566455611949234, 0.2591371293561601, 0.33712090188348803, 0.4185607587094168, 0.5022489200915217, 0.5868585977952995, 0.6709812514714695, 0.7531664637332651, 0.8319633810309844, 0.9059626227804086, 0.9738375445761347, 1.0343837531783697, 1.0865558110540516, 1.1295001356213967, 1.1625831913450306, 1.185414189163992, 1.19786164452453, 1.2000632991327072, 1.1924290786035177, 1.1756369342901818, 1.1506215983214503, 1.1185564617234938, 1.0808289619117624, 1.0390100333643748, 0.9948183297021078, 0.950080062789449, 0.9066854213414319, 0.8665426248813355, 0.831530736333455, 0.8034523962820499, 0.7839876528966935, 0.7746500433433067, 0.7767460355209463, 0.7913388642545153, 0.8192176953915654, 0.8608729270038725, 0.9164782920774569, 0.985880265200304, 1.0685951007668828, 1.163813646387136, 1.270413887016896, 1.3869809874343324, 1.511834417693981, 1.6430615726037372, 1.7785571363761246, 1.9160673013579592, 2.053237828669496, 2.187664841697753, 2.316947173110106, 2.4387390441562973, 2.5508018425850656, 2.6510537828722716, 2.7376162792633134, 2.8088559372760966, 2.863421170997084, 2.900272579285569, 2.9187063608418184, 2.918370212436308, 2.8992713324537327, 2.8617763389570396, 2.8066031031783973, 2.734804691035563, 2.647745792293864, 2.5470721948007267, 2.434674025492896, 2.312643626629824, 2.1832290613853744, 2.048784344495622, 1.9117175686687886, 1.7744381441208017, 1.6393043858099765, 1.5085726703325057, 1.384349342363718, 1.2685464800674535, 1.162842531820599, 1.0686487153367359, 0.987081927834955, 0.9189447558180076, 0.864712999253874, 0.8245309417843065, 0.798214410522529, 0.7852614806724867, 0.7848704962236298, 0.7959649028515545, 0.8172242271619553, 0.8471203914962201, 0.8839584291848425, 0.9259205643865805, 0.9711125458942822, 1.0176110772815683, 1.0635111675761837, 1.1069722376273758, 1.1462618571141039, 1.179796054631848, 1.2061752367272287, 1.2242148687088792, 1.232970207558868, 1.2317545318047514, 1.2201504808755235, 1.1980142930238333, 1.1654729119070997, 1.12291411283591, 1.0709699759840985, 1.0104942011018077, 0.9425339123046664, 0.8682967384925142, 0.7891140714763475, 0.7064014970779349, 0.621617462017898, 0.5362212796768553, 0.4516315898397335, 0.3691863710653856, 0.290105559828358, 0.21545725922773268, 0.14612842369389192, 0.08280078722070794, 0.0259326642459671, -0.024252902076018237, -0.06777333589075975, -0.10488493487196919, -0.13607453021791974, -0.1620446204853347, -0.1836923702423174, -0.20208302549049453, -0.21841844473978173, -0.23400157377695238, -0.2501978002574373, -0.26839420850333984, -0.28995781314254476, -0.3161938809601026, -0.34830545273114527, -0.3873551507541101, -0.43423030390949086, -0.4896123416391494, -0.5539513032499457, -0.6274461819888574, -0.7100316775663906, -0.8013717698501428, -0.9008603543276946, -1.0076290009513464, -1.1205617166112647, -1.2383164122909236, -1.3593526034470658, -1.4819647106759493, -1.6043201813614005, -1.724501525463865, -1.8405512531554642, -1.9505186213443606, -2.052507042359839, -2.144720982620631, -2.2255111827141416, -2.293417062984087, -2.347205239746718, -2.3859031652139406, -2.40882701700624, -2.41560309807998, -2.406182161708016, -2.3808462451015475, -2.3402077752236488, -2.2852008969194944, -2.2170651621005755, -2.1373219047368894, -2.0477438052537935, -1.9503183151881787, -1.8472057645001931, -1.7406931060081716, -1.633144360736228, -1.5269489118105484, -1.4244688508084764, -1.3279866077253601, -1.2396540932588906, -1.1614445499311041, -1.095108247412524, -1.042133068732681, -1.0037109199832706, -0.9807107593954951, -0.9736588856093086, -0.9827269533325868, -1.0077280015785746, -1.0481205897162176, -1.1030209442870222, -1.1712228296084404, -1.2512246722138178, -1.3412632976184176, -1.4393534819151288, -1.54333238407442, -1.650907810857586, -1.759709177699947, -1.8673399679076579, -1.9714304604861672, -2.069689494619206, -2.159954066252477, -2.240235608685886, -2.308761893111472, -2.3640135945456278, -2.404754700866721, -2.430056094399639, -2.4393118029334793, -2.432247596081963, -2.4089217890863805, -2.369718304937488, -2.315332232420522, -2.2467482977905386, -2.165212836860348, -2.0722000082082266, -1.9693731232476288, -1.8585420817814715, -1.7416179896782737, -1.6205660963677115, -1.4973582225401618, -1.3739258520378062, -1.2521150364532951, -1.133644207137785, -1.0200659085970705, -0.912733361720148, -0.8127726376502459, -0.7210610766279409, -0.63821242452527, -0.5645689871345693, -0.5002009229268951, -0.4449126134620679, -0.3982558714702837, -0.3595495743201102, -0.32790514944556476, -0.30225719234459697, -0.28139837061411604, -0.2640176623062399, -0.2487408962746117, -0.23417250810600915, -0.21893739900955778, -0.20172178727088294, -0.1813119724631833, -0.15662999072034314, -0.12676522350647845, -0.09100113029621104, -0.04883640464639483, -4.863570375660231e-16], [0.0, 0.057656338254072945, 0.12161440416111013, 0.19131652427044252, 0.2659910869032338, 0.3446738351893168, 0.42623468126911246, 0.5094093353681423, 0.5928349162209046, 0.6750886033244863, 0.7547283094509517, 0.8303342958506006, 0.9005506240904607, 0.964125338257283, 1.0199482993643527, 1.0670856495763288, 1.1048099659490238, 1.1326252697510402, 1.1502861854576354, 1.1578106900020142, 1.155486054184438, 1.1438677502457026, 1.123771278201398, 1.0962570441289856, 1.0626086016642595, 1.0243047390145434, 0.9829860535166716, 0.9404168001162346, 0.898442925453918, 0.8589473023156787, 0.8238032573841585, 0.794827536482326, 0.7737338744558556, 0.7620883308289743, 0.7612675174390632, 0.7724207811769098, 0.7964373152018249, 0.833919057699041, 0.8851601011497267, 0.9501331804865875, 1.0284836391709282, 1.119531092283572, 1.222278819576667, 1.335430733653008, 1.4574155836405622, 1.586417877464311, 1.7204148404605046, 1.857218578718737, 1.9945224858784287, 2.129950825371377, 2.2611103389568457, 2.385642678879901, 2.501276436461551, 2.6058775450543257, 2.6974968699959083, 2.7744138616673513, 2.8351752385051765, 2.8786277826527384, 2.9039444690728176, 2.9106433060393124, 2.8985984371735856, 2.8680432384098484, 2.8195653330132164, 2.754093639422051, 2.6728777555839622, 2.5774601650107076, 2.4696419195791917, 2.35144260803114, 2.2250555534392586, 2.092799294361507, 1.9570664903074413, 1.8202714504284043, 1.6847975136326414, 1.5529455079426553, 1.4268844869111394, 1.3086058820723034, 1.1998821242148099, 1.102230674875068, 1.0168842756360676, 0.9447680698936309, 0.8864840834997783, 0.8423033712628466, 0.8121659500947275, 0.7956884512242043, 0.7921792379638544, 0.8006605565796036, 0.8198971202384774, 0.8484303738841605, 0.8846175549045763, 0.9266745538237243, 0.9727214936246246, 1.020829887721388, 1.0690702064016746, 1.1155586804070212, 1.1585021981363095, 1.196240208958555, 1.2272826278187918, 1.2503428435690986, 1.2643650625051608, 1.2685453661498474, 1.2623460246593112, 1.2455027802336456, 1.2180249942366688, 1.1801887328621656, 1.1325230445862717, 1.0757898538536939, 1.0109580551843556, 0.9391725361767763, 0.8617189831392711, 0.7799854261969648, 0.6954215591590395, 0.6094969212667707, 0.5236590519293373, 0.43929272514283235, 0.357681337643864, 0.27997146484761853, 0.2071415128232104, 0.13997528517559465, 0.07904115353413599, 0.024677372714985744, -0.02301607971290595, -0.06417893066701472, -0.09918527300184399, -0.12863160555817107, -0.15331856946968622, -0.17422686354736386, -0.1924879744172611, -0.2093504937492333, -0.22614291190170213, -0.24423387163423926, -0.2649909347878671, -0.28973895721479315, -0.3197191816421283, -0.35605014416876635, -0.39969144802567114, -0.45141138908922424, -0.5117593231189682, -0.5810435471294365, -0.6593153296179048, -0.74635956998298, -0.8416924002350661, -0.9445658662006301, -1.05397964526358, -1.1686995777912816, -1.2872826142828062, -1.4081076143669744, -1.5294112812596423, -1.6493283800299428, -1.7659352734684448, -1.8772957184302212, -1.9815078005955165, -2.0767508483583783, -2.1613311580436187, -2.233725383174864, -2.2926204896617284, -2.3369492554189875, -2.3659203952678505, -2.379042517548893, -2.3761412646672664, -2.357369152254323, -2.323207796806954, -2.2744624052743365, -2.212248587602194, -2.137971740110635, -2.0532994291753375, -1.9601273765253795, -1.8605398053193491, -1.7567650461065774, -1.6511274203475235, -1.5459965134040463, -1.4437350164549545, -1.346646355939112, -1.2569233388639862, -1.176599022351572, -1.1075009665635438, -1.051209952808545, -1.009024145034303, -0.9819295455363907, -0.9705774476514669, -0.9752694230301457, -0.9959502028104369, -1.0322086249654423, -1.0832866288242384, -1.1480960869119337, -1.2252430784637778, -1.313059032754105, -1.4096380080250084, -1.5128792272414633, -1.62053386864302, -1.7302550100866343, -1.8396495538642879, -1.9463309147624666, -2.0479712396395713, -2.142351942043025, -2.2274113799513215, -2.3012885774708054, -2.3623619904160083, -2.4092824386860605, -2.440999472164579, -2.4567805979569552, -2.4562229711590837, -2.4392573347268502, -2.406144181874417, -2.3574623021576984, -2.2940900553955275, -2.2171798913685574, -2.128126793574675, -2.0285314683096902, -1.920159222519729, -1.8048955722952715, -1.6846996961970153, -1.5615568921232448, -1.4374312121405568, -1.3142194363145274, -1.1937075045252383, -1.0775304556757082, -0.967136828421649, -0.8637583590238589, -0.7683856731791441, -0.6817505132464587, -0.6043148740838927, -0.5362672439917997, -0.47752596646196055, -0.4277495581002593, -0.3863536427367326, -0.3525339957455939, -0.32529504010871474, -0.3034830005642244, -0.28582280764186824, -0.27095775233022495, -0.2574908267859052, -0.2440266484709676, -0.22921285529358276, -0.21177987792037112, -0.1905780419048478, -0.16461102541268374, -0.13306479622958875, -0.09533127189854734, -0.05102608617906895, -5.06604121830255e-16], [0.0, 0.05969149344005948, 0.12543732401688276, 0.19657112369006496, 0.2722242275352023, 0.35135001345376393, 0.4327533604716156, 0.5151244470938614, 0.5970759962335493, 0.6771829810721101, 0.7540237392011386, 0.82622140226728, 0.892484536147871, 0.9516459027755495, 1.0026982987444903, 1.0448264967053689, 1.0774344115496404, 1.1001667321212656, 1.1129243977254863, 1.115873453577633, 1.1094469866821952, 1.09434001926572, 1.0714974164032913, 1.0420950433686613, 1.0075145820006, 0.9693125796302319, 0.929184454702432, 0.8889243163280114, 0.8503815672304669, 0.8154153480232286, 0.7858479431787444, 0.7634183037818223, 0.749736848235005, 0.7462426792533566, 0.754164304218191, 0.7744848674305443, 0.8079127988717086, 0.8548586572310524, 0.9154187982656087, 0.9893663365752726, 1.0761496935868275, 1.1748988412275476, 1.2844391639303847, 1.4033126758400618, 1.5298061499573667, 1.6619855459131414, 1.7977359673077875, 1.9348062419472625, 2.070857102272122, 2.2035118517069727, 2.330408337851521, 2.4492510170335597, 2.557861887697139, 2.6542290926321166, 2.7365520416673195, 2.803281985935035, 2.8531570802728417, 2.885231099223468, 2.8988951213119956, 2.893891662209519, 2.870320916008821, 2.8286389508038043, 2.7696478955371107, 2.694478345022043, 2.6045643945376784, 2.5016118899554787, 2.387560639740428, 2.2645414774868513, 2.1348291844483063, 2.00079237788149, 1.8648415406233927, 1.729376408494972, 1.5967339439052664, 1.4691381061708488, 1.3486525820464328, 1.237137564977222, 1.136211570510465, 1.0472191506576987, 0.971205224871419, 0.9088965832778217, 0.8606909428897569, 0.826653754017995, 0.8065227665168653, 0.7997201784455398, 0.8053720077812621, 0.8223341554331168, 0.8492244691778789, 0.8844599771284376, 0.9262983393632414, 0.9728824702784011, 1.0222872143620976, 1.072566916070191, 1.1218027112466866, 1.168148383312461, 1.2098736717503602, 1.24540399204884, 1.2733556233579935, 1.292565540162482, 1.3021152042211452, 1.3013477893116352, 1.2898784799993819, 1.2675976624732743, 1.2346670060116467, 1.1915086133341881, 1.1387875924619828, 1.0773885673940025, 1.0083867958104036, 0.9330146953791835, 0.8526246927679797, 0.7686493983690172, 0.6825601728516594, 0.5958251874329747, 0.5098680873597797, 0.42602834739185624, 0.3455243596427546, 0.2694202192451053, 0.19859707389925632, 0.13372978198906885, 0.07526948370979214, 0.023432534125098006, -0.02180391978854186, -0.06069961000046831, -0.09374213469789008, -0.12163150528886427, -0.1452586650095696, -0.16567854903325585, -0.18407839945454163, -0.20174217380114115, -0.22001198961259316, -0.24024762746647696, -0.2637851685755469, -0.29189586932855, -0.3257463731988504, -0.36636133030326873, -0.4145894372731943, -0.47107382640790535, -0.5362276253804175, -0.6102153797299565, -0.6929408832134304, -0.7840417994724578, -0.8828912864430747, -0.9886066568013574, -1.1000649279694352, -1.2159249383225768, -1.3346555366950916, -1.454569194362212, -1.5738602463768492, -1.6906468460813064, -1.8030156159405133, -1.9090679021475951, -2.0069664917110597, -2.0949816302542152, -2.1715351871492166, -2.2352418517611077, -2.284946309666575, -2.319755439216843, -2.33906468455397, -2.342577898378046, -2.330320103075143, -2.3026427884709184, -2.260221544328704, -2.204046011357785, -2.1354023213797353, -2.055848380820106, -1.9671825273255328, -1.8714062527144895, -1.7706818326076992, -1.6672858303015217, -1.563559546576128, -1.4618575655662813, -1.3644955975894468, -1.2736988416246506, -1.1915520823765404, -1.1199526996777, -1.0605677022375035, -1.0147958049961856, -0.9837354518125492, -0.9681595457356743, -0.9684974910581515, -0.9848249785510934, -1.0168617619331162, -1.063977484180531, -1.125205421348548, -1.199263823785291, -1.2845843545475075, -1.3793469568447854, -1.481520330527999, -1.5889070656803799, -1.69919237246139, -1.8099952631242409, -1.9189209865765988, -2.0236134893017614, -2.121806679511847, -2.211373303949761, -2.290370307952575, -2.3570796376948904, -2.4100435567430973, -2.4480936843584056, -2.470373117038924, -2.4763511637828355, -2.465830405321322, -2.4389459736869976, -2.3961571363796446, -2.338231454458628, -2.266221961601724, -2.1814379771841477, -2.0854103167077818, -1.9798517938033826, -1.8666140163785705, -1.7476415626961728, -1.6249246792712944, -1.5004516701781536, -1.3761621460693538, -1.2539022710630814, -1.135383087492231, -1.0221429138725893, -0.9155147025275613, -0.8165991128937855, -0.7262439079446514, -0.6450301181696051, -0.5732652442493684, -0.5109835903324643, -0.45795363914557347, -0.4136922025855361, -0.37748491138377277, -0.34841244914699776, -0.3253817935012101, -0.3071616037386059, -0.29242079334033616, -0.2797692495089421, -0.26779961225440657, -0.25512900382722287, -0.2404396058703633, -0.2225170163469852, -0.20028538016397365, -0.17283837484229883, -0.1394652433319729, -0.09967119729581529, -0.053191662542791986, -5.263588573108698e-16], [0.0, 0.061626488865483546, 0.12900909959647042, 0.20137896823098325, 0.2777782408348025, 0.35708722920300767, 0.43805624118266534, 0.5193412420563507, 0.599542401663977, 0.6772445043174334, 0.7510581470721016, 0.8196606278977454, 0.8818354293840999, 0.9365092357619158, 0.9827854804501724, 1.019973506599078, 1.0476125320791512, 1.0654897403625379, 1.0736519665150492, 1.0724106093757673, 1.0623395728953804, 1.0442662172255617, 1.0192554790393482, 0.9885874962159356, 0.9537292400144304, 0.9163008139444716, 0.8780372187611873, 0.8407465037999204, 0.8062653231325367, 0.7764129882376637, 0.7529451551169527, 0.7375083018119768, 0.7315961415350307, 0.7365090772905016, 0.7533177368117497, 0.7828315334428182, 0.8255730814789718, 0.8817591562680464, 0.9512887334184223, 1.0337384715590479, 1.1283658234057867, 1.2341197748113553, 1.3496590255606158, 1.473377243496544, 1.603434849619331, 1.7377966303918373, 1.8742743286085883, 2.0105732394411735, 2.144341736770831, 2.2732225792011063, 2.394904797122956, 2.5071749431157513, 2.607966498335722, 2.695406267170993, 2.767856660413359, 2.8239528618989325, 2.862633992732499, 2.8831675279622426, 2.885166379508883, 2.8685982324248354, 2.833786904959727, 2.781405691983542, 2.712462841472008, 2.6282795003674475, 2.5304606446548004, 2.420859674597816, 2.3015375057289233, 2.1747171157471565, 2.04273461381278, 1.9079879792664378, 1.7728846696091143, 1.639789321401056, 1.5109727620292077, 1.3885635152316658, 1.2745029197537188, 1.170504890136249, 1.0780212336559543, 0.9982133006988335, 0.9319305907356019, 0.8796967664075623, 0.8417033482027717, 0.8178111762317507, 0.8075595382645943, 0.8101826790579085, 0.8246332295836535, 0.8496119303770803, 0.8836028748472826, 0.9249133696379493, 0.9717174030927146, 1.0221016321068648, 1.0741127440426093, 1.1258050251815852, 1.1752869709118465, 1.220765805307751, 1.2605888380573176, 1.2932806732333426, 1.3175753949543183, 1.3324429867102694, 1.3371093906892375, 1.3310697770476014, 1.3140947665969662, 1.2862295294682606, 1.2477858624680744, 1.199327524553445, 1.1416492787055799, 1.0757502452714727, 1.0028023126663412, 0.9241144726971674, 0.8410940466799298, 0.7552058425493514, 0.6679303304973232, 0.580721944193622, 0.49496860590909725, 0.41195353715606897, 0.33282035276428396, 0.25854234728169245, 0.1898967705210245, 0.1274447568362171, 0.07151742368291218, 0.02220849299043831, -0.0206263820305052, -0.057363577457348734, -0.08859891493168412, -0.1151288731110827, -0.13792609618460114, -0.15810985091211924, -0.1769122165716414, -0.19564090509112095, -0.2156396986225482, -0.2382475565819199, -0.26475748205935007, -0.29637624750478103, -0.3341860614237132, -0.37910921189028635, -0.43187665011713167, -0.49300137989961496, -0.5627573988908166, -0.6411647983446462, -0.7279814726634629, -0.8227017226856924, -0.9245618613407951, -1.0325527514824235, -1.145439027879549, -1.2617845829790648, -1.37998373350137, -1.498297336307074, -1.614892991051675, -1.7278883572650041, -1.8353965274751922, -1.9355723380734853, -2.0266584673732995, -2.1070301666529545, -2.1752374950770665, -2.2300439827401273, -2.2704607264385395, -2.2957750282502727, -2.3055728150535053, -2.2997542246493916, -2.2785419075825333, -2.242481769086568, -2.192436058529206, -2.12956889980097, -2.0553245407083707, -1.971398778044723, -1.879704183209919, -1.7823299068709537, -1.6814969763871463, -1.579510113203153, -1.4787071863031467, -1.3814074798875249, -1.2898599870991958, -1.2061929460086922, -1.132365809000223, -1.0701247827435836, -1.0209629943575735, -0.9860862321160336, -0.9663850786973919, -0.9624141046791701, -0.9743786233695947, -1.002129329189321, -1.0451649550110922, -1.1026428936729842, -1.1733975399257064, -1.255965925950238, -1.3486200507414459, -1.4494051452957142, -1.5561829755119496, -1.6666791664100555, -1.7785334375524453, -1.889351572680882, -1.9967579081533662, -2.0984471156874265, -2.192234075369244, -2.276100684332972, -2.348238523700882, -2.4070864093737057, -2.4513619785123963, -2.480086609931503, -2.4926031395143293, -2.4885860071455754, -2.4680436552222345, -2.431313186038193, -2.379047471650172, -2.31219509066132, -2.2319736372865857, -2.139837104925931, -2.0374381854578028, -1.9265864432148674, -1.8092034162866388, -1.6872757651802421, -1.5628076283855388, -1.4377733551527168, -1.314071767629965, -1.1934830579744793, -1.07762935239129, -0.9679398751910555, -0.8656215244314464, -0.7716355296144085, -0.6866807048314366, -0.6111836416481291, -0.5452960091547782, -0.4888989484240186, -0.4416143696237758, -0.4028227867101347, -0.3716871612945881, -0.34718207801033496, -0.3281274421993581, -0.3132257802616843, -0.3011021362734099, -0.29034549761442324, -0.2795506488215666, -0.2673593474817165, -0.2524997387780704, -0.23382297566984175, -0.21033608829665112, -0.1812302470720532, -0.1459036864756852, -0.10397869763732434, -0.05531225383177737, -5.454322126788757e-16], [0.0, 0.06344295246763644, 0.1322960133541769, 0.20569490264796744, 0.28260119190818117, 0.361832021504311, 0.4420940113909756, 0.5220204645778409, 0.6002108746626721, 0.6752716862737922, 0.7458572216275688, 0.8107096785819766, 0.8686971257939032, 0.9188484683946847, 0.9603844318195648, 0.9927437102305097, 1.0156035469054796, 1.028894154018482, 1.0328065349061262, 1.0277934393128383, 1.0145633570323298, 0.9940676334251266, 0.9674809670122289, 0.9361757202696096, 0.9016906355603903, 0.8656946947685913, 0.8299469899144809, 0.7962535795507629, 0.7664223892978651, 0.7422172723042079, 0.7253123751897016, 0.717247956309966, 0.7193887758351258, 0.7328861217530374, 0.7586444537638115, 0.797293540080218, 0.8491668329571317, 0.9142866804708721, 0.9923568082652484, 1.0827623296767903, 1.184577360142121, 1.2965801265584094, 1.4172752788727425, 1.5449229341420492, 1.677573817006951, 1.813109709080888, 1.9492882869300296, 2.083791317419499, 2.2142750930017585, 2.338421930195166, 2.4539915235589334, 2.558870945732625, 2.6511221116768544, 2.7290255815078335, 2.7911196599402994, 2.836233859344212, 2.8635159251607885, 2.8724517737322195, 2.862877859814021, 2.834985670104305, 2.7893182256924023, 2.7267586658664267, 2.648511173617366, 2.556074684866922, 2.4512099945095907, 2.335901028638523, 2.2123111900238235, 2.0827357996910374, 1.949551748503861, 1.8151655367930983, 1.6819609157567101, 1.552247350746241, 1.428210503532108, 1.3118658788048736, 1.205016700827396, 1.1092169812820067, 1.0257406115597318, 0.9555571651755423, 0.8993149323067449, 0.8573315326718756, 0.8295922694182474, 0.8157561998730747, 0.8151697135152276, 0.8268872278799401, 0.849698443703124, 0.8821614455703591, 0.9226407974212755, 0.9693496667812738, 1.0203949203223106, 1.0738240684618865, 1.1276728997075194, 1.1800126371629922, 1.2289954701406718, 1.2728973625657223, 1.3101571155098335, 1.3394107617871718, 1.3595204935015464, 1.3695974656208192, 1.369017976470121, 1.3574326954978075, 1.334768785513676, 1.3012249463904073, 1.2572595854551751, 1.2035724920256026, 1.1410805554694181, 1.070888213762347, 0.9942534491227635, 0.9125502557097498, 0.8272285889158075, 0.7397728644006607, 0.6516601062865335, 0.5643188471434727, 0.4790898575169154, 0.397189730474988, 0.3196782683535759, 0.24743051657879747, 0.18111416577663833, 0.12117290149995674, 0.06781612443177543, 0.021015296842817284, -0.019493002362493312, -0.05419740707870183, -0.08379574388434445, -0.10917309437580955, -0.1313745268710767, -0.15157322429559036, -0.17103485636372304, -0.19107914379142013, -0.21303963767474254, -0.23822278641021088, -0.2678673843391209, -0.30310549008233817, -0.34492586841277845, -0.39414094831077434, -0.4513582030662391, -0.5169567480799574, -0.5910698211153971, -0.6735736614272071, -0.7640831421509372, -0.8619543386386339, -0.9662940383744002, -1.0759760201523743, -1.1896637558266796, -1.3058390215482092, -1.4228357511942311, -1.5388783265853185, -1.6521233805872073, -1.760704093346432, -1.8627758911840642, -1.9565624139238629, -2.0404006008452034, -2.1127837585123634, -2.1724015152131355, -2.218175635706698, -2.2492907648127543, -2.2652192868042413, -2.2657396267364778, -2.2509474763772808, -2.221259597478554, -2.1774100345884313, -2.120438754042515, -2.051672910657263, -1.9727011244228456, -1.885341321693163, -1.791602854736383, -1.6936437560882867, -1.5937241063959617, -1.4941565933010186, -1.3972554119073173, -1.3052847026603127, -1.2204077388636156, -1.1446380631116628, -1.0797937298842504, -1.0274557414018664, -0.988931667245793, -0.9652253175178472, -0.9570131973613665, -0.9646283109196266, -0.9880517091411694, -1.0269119924679542, -1.0804927908164321, -1.147748053968723, -1.2273248001338546, -1.317592793524823, -1.4166804576278054, -1.5225161834033598, -1.632874064535626, -1.7454229881148307, -1.8577779313078668, -1.967552264513104, -2.072409840399426, -2.1701156565771575, -2.258583917197727, -2.3359223845749724, -2.4004720043159513, -2.450840904145731, -2.4859320047186486, -2.5049636368160377, -2.5074827295893876, -2.49337031472721, -2.4628392771766072, -2.416424469779206, -2.3549654923135748, -2.279582610496568, -2.1916464532157596, -2.0927422726877785, -1.9846296788165487, -1.8691988627109384, -1.7484244026344942, -1.6243177967545637, -1.4988798897631392, -1.3740543542930412, -1.2516833532986293, -1.133466447169143, -1.0209237209341804, -0.9153639947868395, -0.81785884815647, -0.7292230370857359, -0.6500017205106493, -0.5804647373425075, -0.5206079973710793, -0.4701618694331178, -0.428606274509812, -0.395192023818479, -0.36896778672124186, -0.3488119342431668, -0.33346838461786804, -0.32158548050539215, -0.31175685572926565, -0.30256320430118794, -0.2926138472144498, -0.2805870033634141, -0.26526770965157137, -0.24558240085144062, -0.22062925037096795, -0.1897034864289156, -0.15231703134235652, -0.10821196128218559, -0.057367446145573375, -5.636419149508736e-16], [0.0, 0.06512365681932017, 0.13526706458703733, 0.20947841659273841, 0.28664798942357395, 0.36554014604515916, 0.4448290188061482, 0.5231369224548683, 0.5990744740863183, 0.6712813499419409, 0.7384665893806954, 0.7994473646567064, 0.853185171201948, 0.8988184560490069, 0.935690790288521, 0.9633738028488898, 0.981684224638154, 0.9906945409095718, 0.9907369118796208, 0.9824001930751268, 0.9665200633103752, 0.9441624451585726, 0.9166005758265257, 0.8852862510983653, 0.8518159173142937, 0.8178924223278391, 0.7852833525745951, 0.7557769768091576, 0.7311368853093954, 0.713056454616515, 0.7031142810526178, 0.7027317109098176, 0.7131335516212014, 0.7353129773924652, 0.7700015463623906, 0.8176451266788133, 0.8783863888158319, 0.9520543644217778, 1.0381614018086238, 1.1359076690389902, 1.2441931718352386, 1.3616370697475575, 1.4866038947066087, 1.6172361056826199, 1.7514922558961776, 1.8871899087817907, 2.022052319184427, 2.1537578000648936, 2.279990624720305, 2.3984922719752557, 2.507111808073282, 2.6038542144942367, 2.6869255153230887, 2.7547736300685637, 2.806123976261879, 2.8400089683966927, 2.8557907028565754, 2.8531762789561337, 2.832225380208043, 2.7933499231981784, 2.7373057695526803, 2.6651766848412364, 2.578350912299391, 2.4784909044930257, 2.367496918228899, 2.2474653231943535, 2.120642599461568, 1.9893761000949663, 1.856062730209293, 1.7230967411337241, 1.5928178567172615, 1.4674609378467804, 1.3491083512427495, 1.2396461405624957, 1.1407250034756733, 1.0537269600238002, 0.9797384581630496, 0.9195305053571319, 0.873546244303495, 0.8418962105402494, 0.8243613242218208, 0.8204034823139704, 0.8291834353968922, 0.8495854596250653, 0.8802481734059479, 0.9196007039379694, 0.9659032843874693, 1.0172912611780949, 1.071821415034104, 1.1275194508457616, 1.1824274912186936, 1.2346504171337327, 1.2823999361710843, 1.3240353232303077, 1.3580998689154375, 1.383352184428064, 1.3987916460189282, 1.4036774133868921, 1.3975406210604053, 1.380189515606831, 1.3517074901257085, 1.3124441464201972, 1.2629996900351887, 1.204203129641942, 1.1370849059006387, 1.062844712130566, 0.9828153864686436, 0.8984238498090992, 0.8111501333737136, 0.722485582577697, 0.6338913389190981, 0.5467581886149384, 0.462368826025379, 0.38186351263272994, 0.3062100202262376, 0.23617863235953532, 0.17232284403143688, 0.11496624931620601, 0.06419594416334545, 0.019862600931991672, -0.018412803243402505, -0.05122579601183048, -0.07936911786919743, -0.103807848818846, -0.12564961987216516, -0.14611070470905752, -0.16647889553820452, -0.18807415279022507, -0.21220807855422677, -0.2401432970779206, -0.2730538313174656, -0.3119875422676575, -0.35783164815120416, -0.4112822647131656, -0.47281880772888024, -0.542683976880553, -0.620869899430577, -0.7071108561364454, -0.8008828445193505, -0.9014100601139262, -1.007678199074495, -1.1184543099554052, -1.2323127530464684, -1.3476666666118884, -1.462804194782323, -1.5759286053620052, -1.6852013206682137, -1.7887868034233319, -1.8848981847816277, -1.9718424942547108, -2.0480643523786397, -2.1121870165118843, -2.1630497275283487, -2.199740389040986, -2.221622719164814, -2.228357145095219, -2.219914859781107, -2.196584624082898, -2.158972073010693, -2.107991466641639, -2.044850010644503, -1.971025053452383, -1.8882346425260133, -1.7984020865011356, -1.7036153192389742, -1.6060819921895872, -1.508081329780574, -1.4119138660457156, -1.3198502373003227, -1.2340802339036652, -1.156663313269593, -1.089481746254694, -1.0341975105455417, -0.992213959058939, -0.9646431807058503, -0.9522798378102184, -0.9555821122308702, -0.9746602244933378, -1.0092728110666076, -1.0588312586681734, -1.1224119056758453, -1.198775833957487, -1.2863957942426736, -1.3834896389353686, -1.4880594821190074, -1.5979356711791255, -1.710824541248629, -1.8243588353085762, -1.9361496113857, -2.043838425348024, -2.145148574085368, -2.2379342094305636, -2.3202261873686676, -2.390273598536439, -2.4465800327051213, -2.487933759222987, -2.5134311540763195, -2.5224928686428134, -2.5148724113138714, -2.490656996623885, -2.4502607028453194, -2.394410163623843, -2.324123197624432, -2.2406809479847127, -2.145594256541832, -2.04056513259848, -1.9274442891678691, -1.8081858084712088, -1.6848000608461193, -1.5593060357100315, -1.4336842490497788, -1.3098313690307224, -1.1895176503967204, -1.0743481907233885, -0.9657289193037228, -0.8648381051090865, -0.7726040270425925, -0.689689291209663, -0.6164821101687386, -0.5530946823603513, -0.4993686305769472, -0.4548872809158417, -0.41899439258179644, -0.39081878843542905, -0.36930419030660794, -0.3532434354230712, -0.34131614399624804, -0.33212882567102453, -0.3242563561910139, -0.31628372660868936, -0.30684696634574116, -0.29467216834520354, -0.2786115987134397, -0.25767595320446385, -0.23106192658269353, -0.1981743856498715, -0.15864257934775555, -0.11232997621343745, -0.05933748657658161, -5.808141763773378e-16], [0.0, 0.06665267941550264, 0.13789425414683942, 0.21269401047665407, 0.28988078341102036, 0.3681769513827273, 0.4462355696068245, 0.5226796516944163, 0.5961425510971003, 0.6653083627660897, 0.7289512618841715, 0.7859727207861741, 0.8354355966457749, 0.8765941599089958, 0.9089192348789352, 0.9321177467768157, 0.9461461109520095, 0.9512170561514757, 0.9477996409707246, 0.936612396596028, 0.9186097053360135, 0.8949616987871454, 0.8670281273823521, 0.8363268102886788, 0.8044974171616446, 0.773261457503368, 0.7443794561317303, 0.7196063719022233, 0.7006463692833321, 0.6891080772700315, 0.6864614667129061, 0.6939974454309579, 0.7127912111579733, 0.7436703168279132, 0.7871882929723181, 0.8436045407263644, 0.9128710593052662, 0.9946264074674699, 1.0881971234469165, 1.192606646408768, 1.3065915991244919, 1.4286251107936143, 1.5569466852267178, 1.6895979572487665, 1.8244635332121526, 1.9593159835834428, 2.0918639498805485, 2.2198022474413306, 2.3408627916443963, 2.452865149662799, 2.553765523302137, 2.6417030009334956, 2.7150419772455026, 2.7724097270780304, 2.8127282318743196, 2.835239491598667, 2.839523708071668, 2.825509893867858, 2.7934786401226464, 2.7440569624548936, 2.6782053322110664, 2.597197185804534, 2.5025913835451457, 2.3961982566844777, 2.2800400333715967, 2.1563065671292345, 2.0273074020941517, 1.8954212949373104, 1.7630443720201554, 1.6325381305469802, 1.5061784935297982, 1.386107100296966, 1.2742859577677268, 1.172456494196244, 1.0821039486347885, 1.004427898659775, 0.9403195791719804, 0.8903464800112822, 0.8547445337764128, 0.8334180219409585, 0.8259471416029615, 0.8316029915432973, 0.8493695591857587, 0.8779721238670298, 0.9159113405793602, 0.9615021357086693, 1.0129164354566156, 1.0682286612628538, 1.1254628666810191, 1.1826403581970515, 1.2378266391080386, 1.2891765407916953, 1.3349764587720048, 1.3736826905183552, 1.4039549758442613, 1.42468446643832, 1.4350154952712635, 1.4343606757335325, 1.4224090303593464, 1.3991270256167787, 1.3647525680636565, 1.3197821937166216, 1.2649518523521979, 1.2012118474264983, 1.1296966364181162, 1.0516903220991691, 0.9685887694225017, 0.8818593628226987, 0.7929994728165299, 0.703494727561084, 0.6147781838789478, 0.5281914632837763, 0.44494886252937554, 0.3661053666313953, 0.2925293872836242, 0.2248809238080392, 0.16359570045599642, 0.10887567667140455, 0.060686159836393846, 0.018759577292288304, -0.017394209550565833, -0.04847133701606438, -0.07535156819879622, -0.09907072223053448, -0.12078864295914915, -0.14175356345697376, -0.16326381807692994, -0.18662792471215983, -0.2131241046710688, -0.2439603249958264, -0.28023593765798754, -0.3229059520894856, -0.37274891287523865, -0.43033926474143763, -0.49602497445011984, -0.5699110466620333, -0.6518494215693955, -0.7414355798661668, -0.8380120094858384, -0.9406785127953541, -1.048309157011425, -1.1595754989375222, -1.2729755520424264, -1.3868678135443555, -1.49950953534726, -1.609098308810761, -1.7138159423437245, -1.811873545048187, -1.9015566908369406, -1.9812695266643001, -2.049576706111347, -2.1052420752116667, -2.147263110050246, -2.1749002036012097, -2.1877000201412047, -2.1855122764605412, -2.1684994665666046, -2.1371392167865104, -2.092219136957856, -2.0348242163541035, -1.9663169956199278, -1.8883109237836093, -1.802637477971542, -1.7113077785958821, -1.6164695706649441, -1.5203605590404738, -1.4252591790026976, -1.3334339510285598, -1.247092608519624, -1.1683321982935768, -1.0990913356417054, -1.041105749033375, -0.9958681752024658, -0.964593565144386, -0.9481904378880854, -0.9472390747642745, -0.9619770857542638, -0.9922927052779141, -1.037725991692403, -1.0974779172741251, -1.1704271481027841, -1.255154130616748, -1.3499719281053442, -1.4529630902671982, -1.5620216960880984, -1.674899588147053, -1.7892557180091027, -1.9027074499898196, -2.012882626022317, -2.1174711786841276, -2.2142750930017576, -2.3012555600830225, -2.376576235860582, -2.43864161451613, -2.4861296461064506, -2.518017868566706, -2.533602482155214, -2.5325099656419594, -2.5147010139226995, -2.4804667618353453, -2.43041744423158, -2.3654638232825, -2.2867918861562404, -2.195831475405299, -2.094219656775968, -1.9837597512577396, -1.8663770570899847, -1.7440723607771, -1.6188743822085905, -1.4927923166921127, -1.3677696257411622, -1.2456401891829447, -1.1280878646308625, -1.0166104083404224, -0.9124885963026785, -0.816761249061504, -0.7302067116002793, -0.6533311745680858, -0.5863640492576361, -0.5292604304673296, -0.4817105031390132, -0.4431555749122367, -0.41281025180327885, -0.38969012220295646, -0.3726441790598454, -0.36039109481909903, -0.3515583712581882, -0.34472331905893905, -0.33845478140595686, -0.3313545030578528, -0.3220970614561964, -0.3094673190726172, -0.2923944252117583, -0.26998148909047737, -0.24153016179030995, -0.20655949966411286, -0.1648186325228532, -0.11629292259496855, -0.061203470701949376, -5.967853287909961e-16], [0.0, 0.06801554918177107, 0.1401528378790461, 0.21531150967353604, 0.2922692890607604, 0.3697176579173304, 0.44630010678013204, 0.5206519389475066, 0.5914405628898729, 0.6574051932135483, 0.7173948928697318, 0.7704039291563516, 0.8156034823487758, 0.8523688368748712, 0.8803012985533477, 0.8992442147050951, 0.9092926235899098, 0.9107962218644096, 0.9043555095277016, 0.8908111468256426, 0.8712267324150228, 0.8468653823352907, 0.8191606506941026, 0.7896824813553008, 0.7600990115525706, 0.7321351598790132, 0.7075290196590139, 0.6879871419986843, 0.6751398291661714, 0.6704975673734366, 0.6754097082116024, 0.6910264603311637, 0.7182651785491685, 0.7577818381694301, 0.8099484603059762, 0.874837112358728, 0.9522109499529464, 1.0415225964793164, 1.1419199780333815, 1.2522595494367628, 1.37112666561678, 1.496862676406563, 1.6275981561662005, 1.7612915266523061, 1.8957721960830252, 2.028787222740151, 2.158050420591331, 2.2812927595968984, 2.396312876242774, 2.501026501389747, 2.5935136330234125, 2.6720623304890214, 2.735208083162912, 2.7817678084327393, 2.8108676588905754, 2.8219639637727068, 2.814856791399189, 2.789695793755964, 2.7469781771899955, 2.687538830010987, 2.6125328240689787, 2.523410688573507, 2.42188702612823, 2.3099031989968317, 2.1895849541478216, 2.0631959752320053, 1.9330884454240072, 1.8016517746892617, 1.671260686841679, 1.5442238747390018, 1.4227344158314104, 1.308823095457983, 1.2043157128994146, 1.1107953470436083, 1.029570437031937, 0.9616493914262633, 0.9077222807633128, 0.8681499967453564, 0.8429610809686857, 0.8318562414355619, 0.8342203906527323, 0.8491418593980171, 0.8754382696207604, 0.9116883925846162, 0.9562691780810106, 1.0073970207295662, 1.0631722329177882, 1.121625623114603, 1.1807660347822913, 1.2386276858919159, 1.2933161624012255, 1.3430519605565434, 1.386210541411462, 1.4213579547288944, 1.4472812060412765, 1.463012677118473, 1.4678480629793358, 1.461357454027365, 1.443389365735755, 1.4140676961958614, 1.3737817693278664, 1.3231697942054133, 1.263096234469663, 1.1946237321415103, 1.1189803635607312, 1.0375231183944302, 0.9516985828830368, 0.8630018735289976, 0.7729349057150303, 0.6829650923713837, 0.5944855505962813, 0.5087778495699423, 0.4269782623755309, 0.3500483892903944, 0.2787509031870067, 0.21363103188065294, 0.15500424104752983, 0.10295041856362697, 0.057314690920708, 0.017714829083441578, -0.016444970840783692, -0.04595431307742246, -0.07177137121189076, -0.09499288077212571, -0.11682016049865693, -0.13852207191385665, -0.1613959079739507, -0.18672725737926824, -0.21574992009648336, -0.24960695105252065, -0.2893138827289266, -0.3357251241493608, -0.3895044548237255, -0.45110042955073626, -0.5207273861462614, -0.5983526062533188, -0.6836900229555192, -0.776200701883516, -0.8751001490704906, -0.9793723233419506, -1.0877900579398347, -1.1989414297519858, -1.311261459154237, -1.4230683830165969, -1.5326036214538008, -1.6380744585354223, -1.7376983809993887, -1.8297479690229776, -1.9125952106365496, -1.9847541170710066, -2.044920550164407, -2.0920082341679698, -2.125180011455331, -2.1438735126708766, -2.1478205440742326, -2.1370596450368065, -2.111941433157411, -2.073126529258437, -2.021576035309321, -1.9585347206487431, -1.88550725124336, -1.804227968693027, -1.716624886009205, -1.6247787118719599, -1.5308778405072307, -1.4371703473834714, -1.3459141090135724, -1.2593262162852543, -1.1795328736092863, -1.1085209701439396, -1.0480924745088258, -0.9998227415330405, -0.9650237301722424, -0.9447130179111394, -0.9395893614786959, -0.9500153998131853, -0.976007926648775, -1.0172359809428122, -1.0730268179742577, -1.1423796368253443, -1.2239867556619435, -1.3162617492375408, -1.417373897667836, -1.5252881457810181, -1.6378096418842316, -1.7526318167675528, -1.8673868808129692, -1.97969756119184, -2.087228873661624, -2.1877387250566733, -2.2791261731419055, -2.3594762292866798, -2.427100174951084, -2.480570473138937, -2.5187494880384906, -2.54081137678757, -2.5462566829558444, -2.5349193378625, -2.5069659589117435, -2.4628875192452644, -2.40348364565223, -2.3298399773827625, -2.2432991829986784, -2.1454263816674177, -2.0379698457457414, -1.9228179699634982, -1.8019535764080814, -1.6774066818407536, -1.5512068833207957, -1.4253365190381795, -1.3016857337305914, -1.1820105228622513, -1.067894748326245, -0.9607170129044805, -0.8616231537750281, -0.7715049702175677, -0.6909856409999487, -0.6204121167498873, -0.5598545961968096, -0.5091130169253554, -0.4677303156655949, -0.4350120445324614, -0.4100517722100472, -0.39176155675960317, -0.37890665303227283, -0.37014351563543657, -0.364060080533885, -0.35921725655370484, -0.35419053353129026, -0.347610617160457, -0.33820203158627726, -0.3248186886299045, -0.30647550568680576, -0.2823752606698743, -0.2519299991381641, -0.21477645271956616, -0.17078508543100998, -0.12006255151493185, -0.0629475207016644, -6.114033491548998e-16], [0.0, 0.06919937777099866, 0.14202154634060588, 0.21730632408293987, 0.29379103353861086, 0.37014753716459126, 0.4450212667515648, 0.5170712020215738, 0.5850097271386828, 0.6476412945587012, 0.7038988538193294, 0.7528770578457364, 0.7938613397592584, 0.8263520570276394, 0.8500830244908044, 0.8650339002159362, 0.8714360447090848, 0.8697716408064975, 0.8607660343933774, 0.8453734305990067, 0.8247562518940907, 0.8002586292284273, 0.7733746508237777, 0.7457121315810435, 0.7189527857471247, 0.6948097834497857, 0.6749837454203756, 0.6611182777573689, 0.6547561686613191, 0.6572973610997944, 0.6699597794433888, 0.6937440250525061, 0.729402867068615, 0.7774163423950472, 0.8379731457534707, 0.9109588400094132, 0.9959512523544627, 1.092223247448781, 1.1987528885537506, 1.3142408164582413, 1.4371344980977756, 1.5656588265868892, 1.6978523961519323, 1.8316086330991537, 1.9647208410314714, 2.094930118114715, 2.2199750288192246, 2.337641864141236, 2.4458143040970977, 2.54252130484473, 2.625982069978252, 2.6946470305153847, 2.7472338493220434, 2.7827575810160865, 2.800554254990659, 2.800297303799453, 2.782006428008415, 2.7460486676454425, 2.6931316352229078, 2.6242890514733173, 2.5408589078972397, 2.4444547555217704, 2.3369307826405907, 2.2203414917771607, 2.096896914093225, 1.9689144048460077, 1.838768143721532, 1.708837516998754, 1.5814555832524477, 1.458858820100724, 1.3431393164735157, 1.236200513854301, 1.1397175124480203, 1.0551028464178986, 0.9834784989732, 0.9256547764617074, 0.8821164944541917, 0.8530167521825788, 0.8381783889401846, 0.8371030316461323, 0.8489874612255193, 0.8727468511930477, 0.9070442690951193, 0.9503256842167918, 1.000859596760468, 1.0567802976413587, 1.1161336866582876, 1.1769245220108728, 1.2371639472093439, 1.2949161429346574, 1.348342981223175, 1.3957456166429616, 1.4356020323891239, 1.4665996663075276, 1.4876623700264544, 1.4979711003860956, 1.4969779025218914, 1.4844129142523708, 1.4602842975760866, 1.4248711806893204, 1.378709868564949, 1.3225737474347963, 1.257447464337415, 1.1844961033696269, 1.1050302019439253, 1.0204675502123173, 0.9322927924288869, 0.8420158985577014, 0.7511305967157184, 0.6610738515820468, 0.5731874409122419, 0.48868262266559404, 0.4086088005486386, 0.33382698819044876, 0.26498874445773385, 0.20252110785580457, 0.1466179002307821, 0.09723760310225246, 0.05410783815413343, 0.016736311055683933, -0.015572090753762487, -0.0436925161297088, -0.0686523022378937, -0.09159881098794376, -0.11376381344023266, -0.13642537667487595, -0.16086827407700754, -0.1883439802894551, -0.22003132517197374, -0.25699886662957827, -0.30017000046993647, -0.3502917575457538, -0.4079081460181173, -0.4733387819450023, -0.5466634174215856, -0.6277128255315231, -0.7160663391737968, -0.8110561704830744, -0.9117784633494064, -1.0171108578554489, -1.1257361766706155, -1.2361716838410026, -1.3468032200374918, -1.4559233888959837, -1.5617728599080838, -1.6625837672041341, -1.756624122747442, -1.8422421285360282, -1.9179092663253245, -1.9822610653872201, -2.034134498454148, -2.0726010321172397, -2.096994458749009, -2.106932760078966, -2.102333394881326, -2.083421561368368, -2.0507311549511082, -2.005098319856454, -1.9476476743003046, -1.8797714690395464, -1.803102113709627, -1.7194786700732443, -1.6309080620692555, -1.5395218856045618, -1.4475298130518064, -1.3571706755892265, -1.2706623686171128, -1.1901517599169837, -1.1176657860715138, -1.0550648997257235, -1.0039999790384913, -0.9658737323423795, -0.9418075274584414, -0.9326144487844283, -0.9387792392334756, -0.9604456218768925, -0.9974113216707313, -1.0491309251563197, -1.1147265299547953, -1.1930059507505135, -1.2824880687824742, -1.381434742010284, -1.4878885372256119, -1.5997154072345998, -1.7146513192011474, -1.8303517471564914, -1.9444428748040212, -2.054573315691935, -2.158465147523272, -2.2539630760499216, -2.339080591172274, -2.4120420523603743, -2.471319740477052, -2.5156650360493154, -2.5441330269699765, -2.5561000079998997, -2.551273506366222, -2.529694647995141, -2.4917328630625173, -2.4380731130860105, -2.369696000235249, -2.287851288550254, -2.1940255222217857, -2.089904564229936, -1.9773319961219062, -1.8582644137148805, -1.7347247217978023, -1.6087545718780512, -1.4823670997540168, -1.3575011039711602, -1.2359777625180728, -1.1194609146137915, -1.0094218389605292, -0.9071093418351066, -0.8135258308672425, -0.729409896780933, -0.6552257596245205, -0.5911597622463928, -0.5371239163383678, -0.4927663297001863, -0.4574881718795955, -0.4304666732789164, -0.41068350421111616, -0.3969577489130092, -0.38798257842126227, -0.38236463821398026, -0.37866510375930146, -0.37544132109968137, -0.3712879411706793, -0.36487647584824573, -0.35499225018493086, -0.3405677976992947, -0.3207118420403112, -0.29473312637499444, -0.2621584884188987, -0.22274473065911637, -0.17648399814629426, -0.12360254611616973, -0.06455295232833955, -6.245292612340693e-16], [0.0, 0.07019297437767578, 0.1434827687074579, 0.21865965065206952, 0.2944315236465136, 0.36946198994484125, 0.44240981427271314, 0.5119687303250994, 0.5769065213986477, 0.6361023229273036, 0.6885811382055524, 0.7335446280626918, 0.7703973289655215, 0.7987675696356372, 0.8185224908774204, 0.8297767235485694, 0.8328944416941494, 0.8284846777318926, 0.8173899599437139, 0.800668505024478, 0.7795703657069227, 0.7555080912881044, 0.7300226032242221, 0.7047451151637432, 0.6813560336021959, 0.6615418590185504, 0.6469511657189876, 0.6391507701233347, 0.6395832010047434, 0.6495265610470683, 0.6700578175259125, 0.7020204821421693, 0.7459975378907692, 0.8022903467928691, 0.8709041293682073, 0.9515404483637286, 1.0435969593636505, 1.146174513658558, 1.258091518512628, 1.3779052811881243, 1.50393989018816, 1.634320024449654, 1.7670099327031663, 1.89985669461739, 2.0306367659298856, 2.1571047242840877, 2.277043073110505, 2.3883119291348467, 2.4888974158159405, 2.5769576103614678, 2.6508649453852464, 2.709244046510294, 2.751004092381303, 2.7753649111068315, 2.7818761740320657, 2.7704292103953723, 2.7412611409040855, 2.6949512103410616, 2.6324093845579957, 2.5548574611178805, 2.463803120941377, 2.3610075162537623, 2.248447143831922, 2.1282708882727217, 2.002753234443249, 1.8742447386489556, 1.7451209121757012, 1.6177307071777949, 1.4943458025282326, 1.3771118660549846, 1.2680029200979952, 1.1687798607698783, 1.080954079583338, 1.0057570117304084, 0.9441162913251059, 0.8966390338914852, 0.8636025942223722, 0.8449529676713133, 0.8403108193812617, 0.8489849433865729, 0.8699927764078428, 0.9020874238078906, 0.9437905016607514, 0.9934299629250325, 1.049181960590791, 1.1091157091480586, 1.1712402399814703, 1.2335519078648658, 1.2940814954718747, 1.3509397808947143, 1.4023604790357225, 1.4467395401800263, 1.4826698861944785, 1.508970784141729, 1.5247111956185928, 1.5292265943262013, 1.5221289103755555, 1.5033094334626822, 1.4729346839681168, 1.431435436830179, 1.3794892533321348, 1.3179970364984965, 1.2480542726360278, 1.170917751051387, 1.087968662941487, 1.0006730662155343, 0.9105407634855444, 0.8190836742075646, 0.7277747881935899, 0.6380087663588384, 0.5510652062276324, 0.46807551567578265, 0.38999424056376075, 0.3175755728328343, 0.25135562834635744, 0.19164093176482255, 0.1385033829167911, 0.09178180960716535, 0.051090039893654786, 0.015831256922516426, -0.014781764245697937, -0.041701091622181774, -0.06601343581031317, -0.08890612786954656, -0.11163018951129669, -0.1354614863420149, -0.16166100618732462, -0.19143532912645086, -0.22589835309582235, -0.26603530883137283, -0.31267004124589903, -0.36643645248600876, -0.4277548969233345, -0.49681419283192574, -0.5735597726322667, -0.657688336927384, -0.7486492110543304, -0.8456524307144992, -0.9476834097668372, -1.0535238728469456, -1.1617785724209713, -1.2709071583276328, -1.3792604316548758, -1.4851200974132501, -1.5867410349144184, -1.68239503350893, -1.770414896247986, -1.8492377963250402, -1.917446781359361, -1.9738093585432497, -2.01731215853412, -2.0471907662055173, -2.0629539198155333, -2.0644014140627975, -2.051635193619479, -2.0250632883627278, -1.9853964156321207, -1.9336372541378215, -1.8710625742113984, -1.799198585477606, -1.7197900313632626, -1.6347637159684993, -1.546187288821155, -1.456224233421218, -1.367086103240574, -1.2809831215079999, -1.2000743068275515, -1.1264183042598621, -1.06192609043845, -1.0083166818005072, -0.9670769079864242, -0.9394262194852351, -0.9262873818946871, -0.928263771530677, -0.9456238318848418, -0.978293081349008, -1.0258538838030677, -1.0875530094426218, -1.1623168280841167, -1.2487737956333378, -1.3452837208578428, -1.4499731382907426, -1.5607759679395483, -1.6754785170119897, -1.791767776152386, -1.9072818852000133, -2.019661593112206, -2.126601514650803, -2.225899993229129, -2.3155064147697204, -2.3935648806404886, -2.4584532371507306, -2.508816572487599, -2.5435944265650017, -2.562041111728169, -2.563738708862866, -2.5486024801106617, -2.516878621762066, -2.469134464524949, -2.406241408759174, -2.3293510550299437, -2.239865151255983, -2.139400122907696, -2.0297470786320826, -1.912828287313749, -1.7906512014472928, -1.6652611539347384, -1.5386938798306693, -1.4129290106253816, -1.2898456565723924, -1.171181133213948, -1.0584938031948705, -0.9531308958686068, -0.8562020378583102, -0.7685590809136001, -0.6907826528017953, -0.6231756866255962, -0.5657640081338976, -0.5183038836831879, -0.48029625792424646, -0.451007244350717, -0.42949427767125187, -0.41463719837091517, -0.40517342022989494, -0.399736233906052, -0.396895226346196, -0.395197748540067, -0.3932103440858488, -0.3895590586278248, -0.3829675851941519, -0.3722922618578633, -0.3565530243580916, -0.3349595251214336, -0.30693175872123873, -0.2721146789177582, -0.23038645033522215, -0.18186014453583366, -0.12687886151054803, -0.06600442907623655, -6.360383996543952e-16], [0.0, 0.07098694297531295, 0.14452269916233726, 0.21935861705607534, 0.2941843329868723, 0.3676665231635891, 0.4384884567992209, 0.5053892885463334, 0.567202033294308, 0.6228891983528553, 0.6715751063809048, 0.7125740256665213, 0.7454133304430013, 0.7698510401829908, 0.785887230079892, 0.7937689616057889, 0.7939885481875781, 0.7872751424842971, 0.7745798041561357, 0.7570543760357565, 0.7360246579696215, 0.7129585172003674, 0.6894297082076798, 0.6670782899942657, 0.6475686219439346, 0.6325459881820659, 0.623592943030667, 0.6221864855162087, 0.629657158483678, 0.6471511279123412, 0.6755962314230683, 0.7156728932858077, 0.7677906886792415, 0.8320712052977727, 0.9083376989251241, 0.9961118750059549, 1.0946179545882233, 1.2027940045550618, 1.3193103332198242, 1.4425945775453775, 1.5708629418021962, 1.7021568935353466, 1.8343844851034241, 1.9653653512231735, 2.092878337859517, 2.2147106478462932, 2.328707345594946, 2.432820048275027, 2.52515364436979, 2.604009922260518, 2.667927060517701, 2.7157140262464594, 2.746479045886918, 2.7596514514679424, 2.7549963611089288, 2.732621821786045, 2.6929782209211246, 2.63684995687511, 2.565339542469885, 2.479844495742771, 2.382027543871999, 2.273780825415628, 2.157184918803583, 2.0344636479352145, 1.9079357157726986, 1.7799642915526253, 1.6529057248531664, 1.529058579105216, 1.4106141677676092, 1.2996097385480136, 1.1978853856865155, 1.1070456790478722, 1.028426883841891, 0.9630705090390038, 0.911703769306426, 0.8747273783210242, 0.8522109147120038, 0.8438958199744507, 0.8492059049229259, 0.8672650620861178, 0.8969217102474831, 0.936779338277937, 0.9852323723447679, 1.0405064669755126, 1.1007022192807083, 1.163841229311432, 1.2279133798458477, 1.2909241870019035, 1.3509410794124561, 1.4061374980268226, 1.4548337699817586, 1.4955337968104627, 1.5269567073002401, 1.548062755768002, 1.5580728940983344, 1.5564816068655851, 1.5430627691986787, 1.5178684624824166, 1.4812208591410077, 1.4336974602307984, 1.3761101340922728, 1.30947855679719, 1.2349987918048575, 1.1540078637438058, 1.0679452766792439, 0.9783124982871896, 0.8866314763216226, 0.794403271576102, 0.7030678818323832, 0.6139662943716859, 0.5283057414975024, 0.4471290458352835, 0.37128883220139985, 0.30142725339492504, 0.2379617316700941, 0.18107705960547704, 0.13072403761824786, 0.08662465470597396, 0.04828364846429106, 0.0150061143499107, -0.014079323256835618, -0.03999241039894114, -0.06386899395153388, -0.08692545261229753, -0.11042078452246863, -0.13561736955905254, -0.16374146021172648, -0.19594446378843172, -0.2332660602395204, -0.2766001545964597, -0.32666459200906217, -0.38397546840503244, -0.44882675326210747, -0.5212758057964737, -0.6011352154242852, -0.6879712354270612, -0.781108909420987, -0.8796438177611839, -0.9824601997566941, -1.0882550418582786, -1.1955675660055154, -1.302813410041702, -1.4083226671474316, -1.5103808468028765, -1.607271738552775, -1.6973211039302238, -1.7789400927795647, -1.8506672787222553, -1.9112082347621422, -1.9594716234642575, -1.9946008555222132, -2.0160004739611317, -2.0233565462105756, -2.0166504897877573, -1.9961659158502987, -1.9624882445239225, -1.9164970225124403, -1.8593510527018464, -1.792466622849936, -1.7174892916145883, -1.6362598508709068, -1.550775229500552, -1.4631452319573324, -1.3755461117121521, -1.2901720624685398, -1.2091857667152772, -1.13466917028208, -1.0685756523035235, -1.01268473228561, -0.9685604004204228, -0.9375140752039414, -0.920573085731446, -0.9184554473318647, -0.9315515515591286, -0.959913228555937, -1.0032504653941128, -1.0609358824111876, -1.132016885219359, -1.215235227445966, -1.3090535428202377, -1.4116882392467216, -1.521147996044164, -1.6352769722684384, -1.7518017222230156, -1.868380726610394, -1.9826553864190903, -2.092301293058215, -2.1950785832481463, -2.2888802108550603, -2.3717770196204118, -2.442058579297964, -2.4982688511300353, -2.5392358743216437, -2.564094810115051, -2.5723038406666965, -2.5636525922440776, -2.5382629320693875, -2.4965821710390985, -2.4393688860741154, -2.3676717515737415, -2.2828019350789326, -2.1862997637709696, -2.0798965021700395, -1.9654721941275568, -1.845010611222968, -1.7205524128655845, -1.5941476592921073, -1.4678088264428852, -1.3434654512926425, -1.222921488199344, -1.1078163824920517, -0.9995907687699891, -0.8994575807518975, -0.8083792200581604, -0.7270512765454266, -0.655893126635557, -0.5950455626525679, -0.5443754298374648, -0.5034870728501378, -0.47174022454052367, -0.4482738107742459, -0.43203500006832546, -0.4218126993102961, -0.4162745900342665, -0.41400671622211555, -0.41355457641173127, -0.41346464141448674, -0.4123252148879398, -0.4088055774053856, -0.4016924048525672, -0.38992252763350965, -0.37261119631561085, -0.3490751394353902, -0.3188498371445679, -0.28170058668063347, -0.23762709841885235, -0.18686153036703115, -0.129860040107879, -0.06728810203620057, -6.458215240931509e-16], [0.0, 0.07157376106929068, 0.14513144445016776, 0.21939636535518456, 0.2930511081313759, 0.3647766259124689, 0.4332915408394868, 0.49739058827709476, 0.5559811688543773, 0.608117019195168, 0.6530280847060459, 0.6901457739488411, 0.7191228915308044, 0.739847682154154, 0.7524515690683793, 0.7573103318755801, 0.7550386373793708, 0.7464780086871156, 0.7326784877431208, 0.7148744105888897, 0.694454868757342, 0.6729295703969022, 0.6518909374165142, 0.6329733770038374, 0.6178107446668943, 0.6079930694321605, 0.6050236385768398, 0.6102775385225074, 0.6249627201997151, 0.6500846019249532, 0.6864151419028186, 0.734467207810378, 0.7944749450661209, 0.866380701394734, 0.9498289066916, 1.0441671378592121, 1.1484544223987614, 1.2614766564333408, 1.3817688369187386, 1.5076436384234637, 1.6372257062388775, 1.7684908936634143, 1.899309545686931, 2.027492827133066, 2.150841013225498, 2.267192606567445, 2.374473118059685, 2.470742351054161, 2.554239058075986, 2.6234218970792966, 2.677005698084954, 2.7139921591856626, 2.73369422070382, 2.7357535146197742, 2.7201504496659785, 2.6872066667468046, 2.637579780362622, 2.5722505050882996, 2.4925024474177353, 2.399895018022665, 2.2962300834290112, 2.1835131252915962, 2.0639098062138523, 1.9396989502277482, 1.8132230309639574, 1.6868373191400654, 1.5628588718565817, 1.443516548577104, 1.330903212537501, 1.226931222335852, 1.133292237936602, 1.0514222602660686, 0.9824726965667937, 0.9272880978366471, 0.8863910535842229, 0.8599745567341919, 0.847901972036584, 0.8497145591623362, 0.8646463212539395, 0.8916457754447493, 0.9294040780057771, 0.9763887873043071, 1.0308824162838608, 1.091024815870203, 1.1548583442167548, 1.2203747160768825, 1.2855623932411382, 1.3484533716395979, 1.4071682434266293, 1.4599584624873718, 1.5052448180072902, 1.5416512210611653, 1.568033031046954, 1.583499289126368, 1.587428381100391, 1.5794768184453813, 1.5595809993993812, 1.5279519876943226, 1.4850635203992124, 1.4316336240497798, 1.3686003756314493, 1.2970924881614672, 1.2183955260517276, 1.1339146600456054, 1.0451349527553728, 0.9535802217164885, 0.8607715560931132, 0.7681865650576325, 0.6772204104529966, 0.589149624341105, 0.5050996348199098, 0.4260168230625719, 0.35264581347990537, 0.2855125603324177, 0.2249136415567473, 0.17091200790638522, 0.1233392668718188, 0.08180441051965803, 0.04570872869237718, 0.014266488188769742, -0.013469191326820446, -0.03857596906556249, -0.06222824384449309, -0.08566036097384068, -0.11012805473546333, -0.1368691627534564, -0.16706466882785412, -0.20180112394769653, -0.24203546137637472, -0.2885631617454652, -0.34199063949765557, -0.4027126149008241, -0.47089510889906194, -0.5464645544596234, -0.6291033614271506, -0.718252106150388, -0.8131183464780534, -0.9126918914354273, -1.0157661873194133, -1.1209653223285871, -1.2267760042250548, -1.3315837336618601, -1.433712283069497, -1.5314655002719744, -1.6231703896447145, -1.7072203833763744, -1.7821177023479957, -1.8465137207115576, -1.8992462901632472, -1.9393730482079126, -1.9661998277840989, -1.979303401225937, -1.9785479268748491, -1.9640946184193464, -1.9364043215173647, -1.896232855400624, -1.8446191547080744, -1.782866424360025, -1.7125166934707847, -1.6353193188077841, -1.553194140048792, -1.4681901242803868, -1.3824404524374574, -1.298115092807255, -1.2173719739722786, -1.142307909920743, -1.0749104424470606, -1.0170117500220608, -0.9702457283526209, -0.9360092768838096, -0.915428729199288, -0.9093322459486156, -0.9182288494431441, -0.9422946227839861, -0.9813664271011706, -1.0349433123001595, -1.1021956139609437, -1.1819815461619025, -1.2728709214578597, -1.3731754593786258, -1.480984987769785, -1.5942087008984396, -1.7106205179134897, -1.82790748791261, -1.9437201158944226, -2.055723439009412, -2.1616476658508077, -2.2593372034384154, -2.346796936736751, -2.4222346930140066, -2.4840989164234553, -2.5311106945813733, -2.562289415762332, -2.576971489274457, -2.5748217288371937, -2.5558371752644495, -2.5203433161374753, -2.468982842000941, -2.4026972564935254, -2.322701827396289, -2.230454522724741, -2.1276197168921467, -2.0160275732272623, -1.897630107823301, -1.7744550134718124, -1.6485583695579946, -1.5219773831874523, -1.3966842980872485, -1.2745425712810663, -1.1572663541704813, -1.0463842261118743, -0.9432080171330189, -0.8488074249148535, -0.7639909828965414, -0.6892937750741485, -0.6249721228000076, -0.5710052939090566, -0.52710410916469, -0.4927261496947591, -0.4670971060323003, -0.44923765862458986, -0.4379951449521956, -0.4320791530225418, -0.4301000877965944, -0.43060968833944024, -0.43214243080737985, -0.43325673679157156, -0.4325749183479049, -0.42882082988384035, -0.4208542618988291, -0.40770120068854465, -0.38857918922117646, -0.36291715462453317, -0.3303692137570198, -0.29082212645243427, -0.24439623220675916, -0.19143987609534713, -0.13251749925874198, -0.06839173407783752, -6.53785772950913e-16], [0.0, 0.0719478392534882, 0.14530309169761446, 0.21877207507634688, 0.291041494139705, 0.3608175466646578, 0.42686463397269925, 0.4880426336476988, 0.5433417277992063, 0.5919138417554176, 0.6330998339691359, 0.6664516860272679, 0.6917490692565225, 0.7090098083085404, 0.718493918666798, 0.7207010603024653, 0.7163614195497263, 0.7064202013853403, 0.6920160803818429, 0.6744541164528461, 0.6551737871162903, 0.6357129176615768, 0.6176684010069541, 0.6026546873386325, 0.5922610875453298, 0.5880089723195395, 0.5913099595569924, 0.6034261659909054, 0.6254335551755366, 0.6581893439901432, 0.7023043354296, 0.7581209288552497, 0.8256974229306377, 0.9047990744815625, 0.994896212224981, 1.0951695317477264, 1.2045225215396262, 1.3216007936614051, 1.4448179211219558, 1.572387221511185, 1.7023587769297281, 1.8326608475080237, 1.96114472314054, 2.0856319683135816, 2.203962950352929, 2.314045503721002, 2.4139025731514536, 2.5017176967386203, 2.575877236221842, 2.635008334558303, 2.6780116787410106, 2.7040882663514507, 2.712759514640252, 2.7038802076143464, 2.677643945880619, 2.6345809417452237, 2.5755481839739334, 2.5017121782553677, 2.414524646352206, 2.3156917348633907, 2.2071374393595837, 2.0909620876191677, 1.9693968434203, 1.8447552869669688, 1.7193831972404994, 1.5956077036910603, 1.4756869886982, 1.3617617078055015, 1.2558092522379376, 1.159601908695467, 1.074669876596059, 1.0022699851492745, 0.943360814770556, 0.898584772779563, 0.8682575058516361, 0.8523648554105013, 0.8505673813744455, 0.862212298813822, 0.8863524955572883, 0.9217721308970399, 0.967018160370287, 1.020436992897189, 1.0802153676845943, 1.1444244421171248, 1.2110660106456381, 1.2781197301217155, 1.3435902101299466, 1.4055528379668163, 1.462197246645501, 1.5118673996265448, 1.5530973561886074, 1.584641894152353, 1.6055012991919377, 1.614939778868591, 1.6124971210572536, 1.5979933865636318, 1.5715266001943582, 1.533463578998955, 1.484424206510172, 1.4252596233487025, 1.3570249535312902, 1.2809473185518323, 1.198390004530173, 1.1108137386730814, 1.0197360977586218, 0.9266901117470411, 0.8331831390015066, 0.7406570757112267, 0.6504509213715975, 0.5637666556862769, 0.48163929175398235, 0.40491185822654063, 0.334215932153454, 0.26995819780860836, 0.21231334865737356, 0.16122348378746448, 0.1164039808045625, 0.07735565867678619, 0.043382880570225095, 0.01361709248919349, -0.012954847576491008, -0.03745831971739752, -0.061095445687679224, -0.08510740240574391, -0.11073555929850117, -0.13918248490800497, -0.17157387283153272, -0.20892241474684703, -0.2520945995321357, -0.30178134353947017, -0.358473259772132, -0.4224412554899129, -0.49372301159168164, -0.5721157464250154, -0.6571755052416357, -0.7482230484226835, -0.8443562410800415, -0.9444686780065641, -1.0472741154659266, -1.1513361291006279, -1.255102279162551, -1.3569419438546297, -1.4551868818979747, -1.548173509076337, -1.6342858224498253, -1.711997881534031, -1.7799147587066646, -1.836810901446418, -1.8816649060595219, -1.913689784970973, -1.9323579154773287, -1.9374199845155853, -1.9289173884127175, -1.9071877052088615, -1.872863026097984, -1.8268611076417212, -1.7703694833613006, -1.7048228477196328, -1.6318741930451255, -1.5533603364541844, -1.47126261540051, -1.3876636535745361, -1.304701200405312, -1.2245201248147, -1.1492236951659114, -1.080825301201152, -1.0212017695157958, -0.9720493918011791, -0.9348437254258005, -0.9108041403122703, -0.9008639765412566, -0.9056470463013054, -0.9254510648586436, -0.9602384317472232, -1.0096346093405544, -1.0729341655906965, -1.1491143653935891, -1.2368560152023922, -1.3345710925429333, -1.4404365302035391, -1.5524333780220583, -1.6683904369557965, -1.7860313536209003, -1.9030240813201802, -2.017031557741815, -2.125762421358386, -2.2270205887637258, -2.3187525437352643, -2.3990912449899393, -2.466395642024388, -2.519284895065156, -2.5566665233814683, -2.577757852882718, -2.5821002954397816, -2.5695661647758534, -2.54035791284978, -2.494999852025148, -2.43432260755362, -2.3594407176317795, -2.271723960314, -2.17276313394627, -2.0643311469602925, -1.9483403807206094, -1.826797373066988, -1.7017559282503607, -1.5752697897745345, -1.4493460155548206, -1.3259001698033617, -1.206714393853867, -1.093399340120393, -0.9873608515538451, -0.8897721459110732, -0.8015521229959347, -0.7233502573253121, -0.6555383723210477, -0.5982094192934286, -0.5511832094764165, -0.5140188745557974, -0.48603366479233323, -0.466327538104424, -0.45381285218767703, -0.4472483483926555, -0.44527651368253, -0.4464633280459216, -0.44933935115257334, -0.45244107507875453, -0.4543514701952024, -0.4537386787206761, -0.44939186423621, -0.44025330420752257, -0.42544591423015216, -0.4042955146768387, -0.37634728956681995, -0.3413760402421124, -0.29938999893906026, -0.2506281354561327, -0.19555105957644683, -0.1348257884109755, -0.0693048071687774, -6.598554475674721e-16], [0.0, 0.0721055610618594, 0.1450357360108681, 0.21749092580010856, 0.2881729806118373, 0.35582397436120866, 0.4192639974098587, 0.47742694832566535, 0.529393355935972, 0.5744193382763672, 0.6119609034468199, 0.6416929163806039, 0.663522192117557, 0.6775943269146635, 0.6842940396266787, 0.684238963185415, 0.678266995472902, 0.6674174861375607, 0.6529066967098316, 0.6360981216559519, 0.6184683939448119, 0.6015696168257476, 0.5869890607979068, 0.5763072386845298, 0.571055420378283, 0.5726736708959345, 0.5824704902339827, 0.6015851011922825, 0.6309533725505126, 0.6712782811250202, 0.7230057093123468, 0.7863062473315321, 0.8610635246169182, 0.9468694362329912, 1.0430264616811564, 1.1485570991989973, 1.262220262922318, 1.3825343174417764, 1.507806258630061, 1.636166395264792, 1.765607746778199, 1.894029251912012, 2.0192817841760626, 2.139215895304212, 2.251730159280877, 2.354818968246717, 2.4466186382801793, 2.525450717603434, 2.589861451400279, 2.638656444715907, 2.6709296757565837, 2.6860861436613765, 2.6838575843010153, 2.664310851253312, 2.6278487328427578, 2.5752031557923494, 2.507420907247434, 2.4258421852814185, 2.332072459134867, 2.2279482801997896, 2.115497829243435, 1.9968971110456344, 1.8744228114360666, 1.750402911131611, 1.6271662038556132, 1.5069918916811824, 1.3920604277664972, 1.2844067457198105, 1.1858769565124685, 1.0980895095879517, 1.0224017066648454, 0.9598823273580523, 0.9112909783179266, 0.8770646157241878, 0.8573115186330211, 0.8518128120768891, 0.8600314583208846, 0.8811284566914968, 0.9139858212504239, 0.9572357454501887, 1.0092952176655237, 1.068405224658615, 1.1326735746622383, 1.2001202903746269, 1.2687244666805448, 1.3364714596297735, 1.4013992727301186, 1.4616430338726487, 1.5154765104448524, 1.5613496899798278, 1.5979215569865977, 1.624087320781025, 1.6389994910513246, 1.642082353977327, 1.6330395680659855, 1.6118547713096447, 1.5787852655183316, 1.5343490153887673, 1.4793053647889705, 1.4146300267754555, 1.341485043216932, 1.2611845311449907, 1.1751571331184423, 1.0849061655356993, 0.9919685101128659, 0.8978733184558354, 0.8041015972504757, 0.7120477122136265, 0.6229837934015908, 0.5380279442283186, 0.45811705368594663, 0.38398488843224327, 0.3161460017570498, 0.2548858435248613, 0.20025729290384342, 0.1520836681539951, 0.10996809920806314, 0.07330898350782483, 0.041321087739785684, 0.013061711741415393, -0.01253880037550338, -0.036643029594593056, -0.06046985100402834, -0.08525618939193276, -0.11221819082047425, -0.14251285558163646, -0.1772011670988234, -0.21721371391261518, -0.26331973880850845, -0.31610046198852815, -0.37592741614410474, -0.4429464030941924, -0.5170675375347518, -0.5979616870318527, -0.6850634526226157, -0.7775806654229319, -0.8745102057460646, -0.9746597866839048, -1.0766751880621952, -1.1790722831144331, -1.2802730727820708, -1.3786448344985751, -1.4725414064286457, -1.5603455666387185, -1.6405114311910696, -1.7116057866539993, -1.7723472913044787, -1.8216425249854582, -1.8586179391134885, -1.8826468540109393, -1.8933707682531937, -1.8907143812168008, -1.8748938821528212, -1.846418223156752, -1.806083265323793, -1.7549588629223025, -1.6943691252461084, -1.6258662655823728, -1.5511986072366089, -1.4722734637898933, -1.391115741046899, -1.3098232181976162, -1.2305195527858932, -1.155306115940931, -1.0862137993884506, -1.0251559430794066, -0.9738835116001959, -0.9339435992945583, -0.9066422693462036, -0.8930126327093474, -0.8937889511074671, -0.9093874072763144, -0.9398940286130869, -0.9850600812139846, -1.0443050740444282, -1.1167273319993294, -1.2011219162807478, -1.2960054952403226, -1.3996476028769524, -1.5101075695936932, -1.6252762743238116, -1.7429217520393643, -1.8607375987631574, -1.976393049755483, -2.087583567157857, -2.1920807619997613, -2.287780492380737, -2.3727480244042614, -2.445259213955906, -2.5038367639261483, -2.5472807306066936, -2.574692591815526, -2.585492344425756, -2.5794282665884487, -2.5565791559477424, -2.517349035245176, -2.4624544965016604, -2.3929050300656125, -2.3099768509614504, -2.215180888127344, -2.1102257385837033, -1.9969765050297394, -1.877410529027593, -1.753571100570773, -1.6275202668349336, -1.5012918773219568, -1.3768459891637728, -1.2560257154667027, -1.1405175323443917, -1.0318159684499013, -0.9311934867201767, -0.8396762345815311, -0.7580261893953182, -0.6867300642029021, -0.6259951689047282, -0.5757522481222704, -0.5356651434744656, -0.5051469591628511, -0.48338224978788186, -0.46935460216775665, -0.46187885222796676, -0.45963706698430595, -0.4612173329665944, -0.46515432827349107, -0.46997061734233514, -0.47421759633980054, -0.47651503303185416, -0.4755881875988453, -0.4703015689798791, -0.45968847318004746, -0.44297556318184256, -0.4196018817637, -0.3892318352805754, -0.3517618445656421, -0.3073205245502766, -0.2562624227729311, -0.19915551438356374, -0.13676281330870363, -0.07001861182139667, -6.639726198458992e-16], [0.0, 0.07204530281365329, 0.14433146778695904, 0.21556399996346925, 0.2844706702806604, 0.3498396271742207, 0.4105559550910663, 0.4656356924354699, 0.514256386053506, 0.5557833477269655, 0.5897908880786621, 0.6160779320216385, 0.6346775641743652, 0.6458602088771014, 0.6501303136417125, 0.6482165729034771, 0.6410558965722324, 0.6297714908593637, 0.6156455730552712, 0.6000873834318659, 0.5845972826416024, 0.570727828676864, 0.5600428109228974, 0.5540752779178425, 0.5542856285653308, 0.5620208428159402, 0.5784759070010483, 0.60465844150105, 0.6413574653616451, 0.6891171355799115, 0.7482161804074602, 0.8186536090433872, 0.9001411278672049, 0.9921025296309696, 1.0936801508249554, 1.2037483179817658, 1.3209335303096814, 1.4436409580501088, 1.5700866775155558, 1.698334918835314, 1.8263394746419017, 1.9519883104820543, 2.0731503333450214, 2.1877232155177464, 2.293681138531761, 2.3891213171356394, 2.472308186203755, 2.541714183787834, 2.5960561399683706, 2.6343263819593656, 2.6558177886509533, 2.6601421694861846, 2.647241499836113, 2.617391714049945, 2.5711989340101105, 2.5095881910192994, 2.4337848778047544, 2.3452893409830016, 2.2458451882530195, 2.1374020348777307, 2.0220735470050553, 1.902091751823696, 1.779758673701945, 1.6573964191448116, 1.5372968700744694, 1.4216721537010284, 1.3126070378978894, 1.2120143540097106, 1.1215944755583316, 1.0427997831785862, 0.9768049257188817, 0.9244835477332416, 0.8863919979937568, 0.8627603659738886, 0.8534910175944269, 0.8581646221769746, 0.8760534838918131, 0.9061418173726247, 0.9471524428246518, 0.9975792248669271, 1.055724445182388, 1.1197401850401687, 1.1876727026386171, 1.257508724164741, 1.3272225280238954, 1.3948226897525053, 1.4583973708974431, 1.5161570781549614, 1.5664738881667803, 1.6079162267848308, 1.6392784069577602, 1.659604263742546, 1.668204374921063, 1.6646665175425908, 1.6488591803719717, 1.6209281254680794, 1.5812861646373584, 1.5305964840198212, 1.4697500084209922, 1.3998374422914555, 1.3221167528980775, 1.2379769700725418, 1.1488992633087578, 1.056416318822133, 0.9620710750084415, 0.8673758837294432, 0.7737731468595559, 0.6825984330816037, 0.5950470102098823, 0.5121446351657967, 0.43472332954063003, 0.3634027363800878, 0.2985775067952944, 0.2404110069887363, 0.18883547129650083, 0.14355855907528145, 0.1040761069553144, 0.06969070734834025, 0.039535593206614046, 0.012603171690210418, -0.012222570912860326, -0.03613067091458628, -0.06034575114735762, -0.08608955569835983, -0.11454249124493134, -0.1468062113393473, -0.18386825392702005, -0.22656969034072802, -0.275576667299068, -0.33135662397600113, -0.3941598465007386, -0.46400688530546763, -0.5406822100116095, -0.6237343158327812, -0.7124823288291928, -0.8060289889829209, -0.9032797242339533, -1.0029673695231045, -1.1036819365668946, -1.203904706313954, -1.3020458002163902, -1.396484291562531, -1.4856098466088432, -1.5678648389879548, -1.6417858610961815, -1.7060435634574103, -1.7594797873243297, -1.801141016241988, -1.8303072575357897, -1.8465155726476867, -1.849577603310862, -1.8395905855976133, -1.8169415023405615, -1.7823041924147354, -1.7366294087327188, -1.6811279912587946, -1.6172474925663345, -1.5466427571910175, -1.4711411081929917, -1.3927029311323202, -1.3133785636567394, -1.235262495126753, -1.1604459527221047, -1.090968996439371, -1.0287732640961909, -0.9756564983671177, -0.933229951136378, -0.90287969689409, -0.8857327980146472, -0.8826291526561557, -0.8940997233987025, -0.9203516947959065, -0.9612609443777274, -1.0163720382829813, -1.084905783830719, -1.165774191313628, -1.2576025204997467, -1.3587579180713978, -1.467383994641169, -1.5814405479098772, -1.698747515438517, -1.8170321393996522, -1.9339782490205257, -2.0472765160991284, -2.1546745161909584, -2.2540254333772087, -2.34333427979853, -2.420800561549791, -2.484856408594688, -2.534199295961645, -2.567818613935973, -2.585015493071359, -2.5854154519790007, -2.5689736080492374, -2.5359723693084053, -2.487011705165184, -2.422992270476389, -2.345091826859035, -2.2547355633724995, -2.153561061754861, -2.043378775861618, -1.9261289978262985, -1.803836362280895, -1.6785629928752501, -1.552361421095869, -1.4272284054536848, -1.305060749619697, -1.1876141618470262, -1.076466116497462, -0.972983573780897, -0.878296288574701, -0.7932762965791601, -0.7185240096661198, -0.6543611860091545, -0.6008308685957671, -0.5577042123004969, -0.5244939491526861, -0.5004740779925534, -0.48470521241741604, -0.4760648835323206, -0.4732819749130064, -0.4749743692779852, -0.4796888120297182, -0.4859419478483485, -0.49226146405414767, -0.4972262789809947, -0.4995047449309439, -0.49788989254754107, -0.4913308251424521, -0.47895947551715384, -0.4601120614631234, -0.43434471623642196, -0.40144292331315146, -0.3614245467490544, -0.314536415376564, -0.2612445866441439, -0.20221857989214154, -0.13831002511682736, -0.07052631784796165, -6.660975580198429e-16], [0.0, 0.07176743336096932, 0.14319632009434757, 0.21300812720982157, 0.2799669729505197, 0.34291675367878793, 0.40081616636474066, 0.4527706790665574, 0.4980605798208313, 0.536164334824619, 0.5667766071595406, 0.5898204245505626, 0.60545313530871, 0.6140659518777145, 0.6162770472434016, 0.6129183366805165, 0.6050162416739835, 0.5937668901955203, 0.5805063538477154, 0.566676653982343, 0.553788382397895, 0.543380874711658, 0.5369809435944337, 0.5360612229435888, 0.5419991915729577, 0.5560379355948584, 0.5792496725110616, 0.6125029979361608, 0.6564347293185352, 0.7114271120852068, 0.7775910249646647, 0.8547556759815281, 0.942465122334523, 1.0399817799627928, 1.1462969162092638, 1.2601479458711096, 1.380042181381868, 1.5042865261137557, 1.631022449855135, 1.7582654511556213, 1.8839480958115369, 2.00596562719732, 2.122223074809795, 2.2306827440643384, 2.3294109542076304, 2.416622902667363, 2.4907245730391727, 2.550350669334812, 2.594397649546306, 2.622051044864337, 2.6328063843050833, 2.6264831948290306, 2.6032317106384975, 2.563532098247368, 2.5081861819232776, 2.4383018328757182, 2.35527036074637, 2.2607374132776745, 2.156568045408712, 2.0448067586798517, 1.9276334323096052, 1.8073161656947785, 1.686162125976226, 1.5664675419025897, 1.450468005353537, 1.3402902340637426, 1.2379064135153823, 1.1450921735155302, 1.0633891671782292, 0.9940731090424737, 0.9381279975953751, 0.8962270987540302, 0.86872110452843, 0.8556337091106294, 0.8566646672139558, 0.8712002209508504, 0.8983306062416976, 0.9368741819575265, 0.9854075687942945, 1.0423010440432086, 1.105758316363864, 1.1738597043225616, 1.2446076662249754, 1.3159735784519653, 1.385944636259819, 1.4525697553229735, 1.5140033839900064, 1.5685461944287575, 1.6146817040393775, 1.6511079845850727, 1.6767637427406097, 1.6908481990058266, 1.6928343485801312, 1.6824753539252264, 1.6598039902118962, 1.6251252373850382, 1.5790022819042182, 1.522236353130276, 1.4558409698303076, 1.3810113076554191, 1.2990895153841029, 1.2115269033616982, 1.119843999583297, 1.0255895155377392, 0.930299284164341, 0.8354562256450476, 0.742452363507886, 0.6525538545639178, 0.5668699130919583, 0.4863264045778276, 0.4116447599108411, 0.3433267204216121, 0.2816452710941569, 0.2266419575931803, 0.17813061651795484, 0.13570738173981378, 0.09876666701752661, 0.06652267042768194, 0.03803580340515797, 0.012243319968184632, -0.012006686783172207, -0.03591884081698005, -0.06071257522757678, -0.08758378152540577, -0.11766704930793909, -0.15199951474614096, -0.19148729543114149, -0.2368754230868734, -0.28872209612620264, -0.3473779632629812, -0.4129710201795396, -0.4853975568439722, -0.5643194371153599, -0.6491678287032869, -0.7391533344920107, -0.8332823099236372, -0.9303789897694497, -1.0291128952965716, -1.128030853429752, -1.2255928365681261, -1.320210728389893, -1.41028903992326, -1.4942665434844162, -1.5706577612818051, -1.638093241413259, -1.6953575768248248, -1.7414241720702703, -1.77548583725972, -1.7969803866320628, -1.8056105383555294, -1.801357549549003, -1.7844881727571773, -1.7555546834619433, -1.715387898641981, -1.6650832796883106, -1.605980384850673, -1.5396361025590315, -1.467792253298479, -1.3923382903118622, -1.3152699546902624, -1.2386448452379166, -1.1645359452126225, -1.0949842045604636, -1.03195130611714, -0.9772737466252691, -0.9326193381819456, -0.8994471834277062, -0.8789720996301008, -0.8721343646525264, -0.8795755340771005, -0.9016209364478529, -0.9382692961572625, -0.9891897647316857, -1.0537264652792773, -1.1309104759291349, -1.2194790005713108, -1.3179013034321891, -1.4244108221796001, -1.5370427262977073, -1.653676057016448, -1.7720794753106603, -1.8899595580812563, -2.0050105217048935, -2.114964218176101, -2.2176392428943017, -2.310988014912722, -2.3931407396308586, -2.462445239268385, -2.5175017361577385, -2.5571917954915113, -2.5807007746809663, -2.5875332824842503, -2.5775213187306107, -2.550824940702907, -2.5079254807650133, -2.449611517278467, -2.376957972920381, -2.2912988770065983, -2.1941944773955435, -2.087393519392635, -1.9727916206119747, -1.8523867593052024, -1.7282329571308528, -1.6023932742259217, -1.4768932439265396, -1.3536758564142455, -1.2345591554670972, -1.1211974415625283, -1.0150469796399035, -0.9173369933022996, -0.8290465920630115, -0.7508881278234545, -0.6832973148729838, -0.6264302783738539, -0.58016752375447, -0.5441246479714327, -0.5176694474686984, -0.4999449209709644, -0.4898975218654537, -0.4863098883783729, -0.4878371731396944, -0.49304600964905065, -0.5004550936356483, -0.508576323758137, -0.5159554392768829, -0.5212111123420171, -0.5230714987958184, -0.5204073226521497, -0.5122606638285683, -0.4978687338324563, -0.47668205698890764, -0.4483766220524917, -0.41285972691893735, -0.37026940363595495, -0.32096747783389123, -0.2655264818287348, -0.20471079981393192, -0.13945257272913741, -0.07082302580373964, -6.662089672192134e-16], [0.0, 0.07127429385754543, 0.14164017689371441, 0.20984567222110775, 0.2747012283537016, 0.33511555205822585, 0.3901288102684874, 0.43894230104054494, 0.48094378416937345, 0.5157277736352536, 0.5431102236891282, 0.5631371848514638, 0.5760871617435438, 0.5824670675636365, 0.5830018360465639, 0.578617916703749, 0.5704210388534046, 0.559668780364906, 0.5477386143331844, 0.5360922275676688, 0.5262370057369585, 0.5196856586556493, 0.5179150134891236, 0.5223250321480188, 0.5341991110523163, 0.5546666966355152, 0.5846691989704376, 0.6249301099238467, 0.6759301331082173, 0.7378880129990742, 0.8107476128520822, 0.8941716388636257, 0.9875422451179234, 1.0899685842739086, 1.200301196863149, 1.317152961764172, 1.4389261661230368, 1.5638450987992156, 1.689993431183116, 1.8153555264727215, 1.9378607163027664, 2.055429504579294, 2.166020604506977, 2.2676776875101763, 2.358574722791188, 2.4370588137185893, 2.50168949149586, 2.551273506366221, 2.584894260071747, 2.601935147926705, 2.6020962216845405, 2.5854037419215876, 2.55221235710828, 2.503199821797231, 2.4393543441617127, 2.361954829135127, 2.272544453338753, 2.1728981676931194, 2.064984869187101, 1.950925111170462, 1.8329453286145938, 1.7133296384335468, 1.594370333129016, 1.47831821729592, 1.3673339401363214, 1.2634414529919196, 1.1684846696118782, 1.0840883296805657, 1.0116239649293877, 0.9521817444264844, 0.9065488343802056, 0.8751947514628787, 0.8582640210813317, 0.8555762772840282, 0.8666337633664603, 0.8906360160480347, 0.92650134563591, 0.9728945640091161, 1.0282602654464494, 1.0908608358376148, 1.1588182567805352, 1.2301586850940087, 1.3028587274068206, 1.3748922951446627, 1.4442769181915682, 1.5091184158463538, 1.5676528708455655, 1.6182849249409113, 1.6596215109327241, 1.6905002537207363, 1.710011908870306, 1.71751635799115, 1.7126518421118873, 1.6953372831666507, 1.665767715483431, 1.6244030195111328, 1.5719503147214882, 1.5093405236015713, 1.4376997600914527, 1.3583163202440456, 1.2726041572461573, 1.1820638047031007, 1.088241769284893, 0.9926894451079893, 0.8969226068801136, 0.8023825168316467, 0.710399632425373, 0.6221608290579838, 0.5386809563391266, 0.46077943052337555, 0.3890624322509725, 0.32391113132936045, 0.2654762026111969, 0.21367873309918461, 0.16821745438928204, 0.12858207065448776, 0.09407229471719869, 0.06382205734294139, 0.03682822143528817, 0.011983016689732843, -0.011890685596407087, -0.03600221104166923, -0.061555036163633184, -0.08970888286536645, -0.12154297502932937, -0.15802144914064523, -0.1999618556767096, -0.24800760870157051, -0.30260513968853536, -0.3639863906184135, -0.43215714391365245, -0.5068915362382389, -0.5877329434191825, -0.6740012587635987, -0.764806421027131, -0.8590678854373289, -0.9555395756177543, -1.0528397099457865, -1.1494847664834087, -1.2439267394507334, -1.3345927501196455, -1.4199260083195784, -1.4984270792147687, -1.568694394752768, -1.6294629606605981, -1.6796402478733308, -1.7183383209512908, -1.7449013438643801, -1.7589277133766152, -1.7602861994774, -1.7491256177162942, -1.725877716331861, -1.6912531278269685, -1.6462304060109771, -1.5920383412577033, -1.5301319145522578, -1.4621624106427693, -1.3899423582880381, -1.315406097503703, -1.2405668865428872, -1.1674715522551617, -1.0981537541362758, -1.0345869730930823, -0.9786383496227096, -0.9320244823271074, -0.8962702567149117, -0.8726717070136603, -0.8622638218081853, -0.8657940899256029, -0.8837024488521046, -0.9161081473292734, -0.962803870285902, -1.023257301884037, -1.0966201253876278, -1.1817442811106527, -1.2772051301954692, -1.3813310066452138, -1.492238486923185, -1.6078725692780464, -1.726050837108514, -1.8445105850260652, -1.9609578151478426, -2.0731169662932616, -2.178780221263055, -2.2758552476756484, -2.362410265667867, -2.436715400208466, -2.4972793652443475, -2.542880639209741, -2.5725924238290574, -2.5858008273954165, -2.582215876159563, -2.561875129147671, -2.525139848449633, -2.4726838544699055, -2.4054753694865108, -2.324752318889495, -2.2319917136347023, -2.1288738760154806, -2.01724239047624, -1.8990607589901722, -1.776366814162633, -1.6512259909637672, -1.5256845787408866, -1.4017240684816912, -1.2812176764379755, -1.1658900650913657, -1.057281197606923, -0.956715154544026, -0.8652746143956324, -0.7837815557079838, -0.7127845817004497, -0.6525531023779989, -0.6030784382444494, -0.5640817381317071, -0.5350284356167319, -0.5151488081636176, -0.5034640544612562, -0.4988171720875565, -0.49990780288890924, -0.5053301201184348, -0.5136127616889223, -0.5232597695320611, -0.5327914770448535, -0.5407842953171128, -0.5459083839722794, -0.5469622530586264, -0.5429034269055374, -0.532874407020281, -0.5162232962166265, -0.4925185870380044, -0.46155777057520386, -0.42336958309207534, -0.37820987336979606, -0.3265512391688357, -0.26906674250016527, -0.20660816641607566, -0.14017941691051314, -0.07090579870206312, -6.643040434379734e-16], [0.0, 0.07057015787584578, 0.13967664327535328, 0.20610426854864297, 0.26871926222257425, 0.3265035137967913, 0.37858569031690414, 0.42426837949555096, 0.46305051646837153, 0.49464447280182877, 0.5189873240468834, 0.536245962481511, 0.5468158809086652, 0.551313617450373, 0.5505630160527043, 0.5455756187176065, 0.5375256592153501, 0.5277202702995965, 0.5175656436225095, 0.5085299903801584, 0.5021042384141113, 0.49976146578511477, 0.5029161100330435, 0.5128840053844415, 0.5308442866580695, 0.5578041588076057, 0.5945674658451456, 0.6417079038623059, 0.6995476121592696, 0.7681417468039139, 0.8472694954505657, 0.9364318345299063, 1.034856163869291, 1.1415077835244007, 1.2551080073209793, 1.3741585415517725, 1.4969715995855992, 1.6217050777612778, 1.746401988501773, 1.8690332363480704, 1.9875427343658805, 2.0998937943693425, 2.2041156862894673, 2.2983492508086982, 2.3808904654423713, 2.450230907256438, 2.505094124386636, 2.5444670218442056, 2.5676254825307887, 2.5741535791668704, 2.563955883709048, 2.537262544137113, 2.4946269702664505, 2.436916146305853, 2.3652937639459117, 2.2811965415346376, 2.1863042581810403, 2.0825041824354806, 1.971850709840318, 1.8565211388332126, 1.7387686073993223, 1.6208732812335407, 1.5050929263157367, 1.3936140136879362, 1.288504491487914, 1.1916693192483485, 1.1048097930950893, 1.0293875993943975, 0.9665944208361021, 0.9173277856738744, 0.8821737011335666, 0.8613964495041826, 0.8549357541122461, 0.862411346430656, 0.8831347892780563, 0.9161282387192057, 0.9601496630733416, 1.0137238853638129, 1.0751786792829028, 1.142685031591795, 1.2143005886437763, 1.288015233682885, 1.3617976964047662, 1.4336420780081036, 1.5016131839843763, 1.563889592891417, 1.6188034513667668, 1.6648760720569389, 1.700848519765629, 1.7257064992112938, 1.7386990021123079, 1.7393503282701046, 1.7274652609790906, 1.703127347329857, 1.6666904045601467, 1.6187635403167315, 1.560190133398094, 1.4920213683377028, 1.4154850484508457, 1.3319505244889853, 1.2428906670826398, 1.1498418785059488, 1.0543631813580547, 0.957995437556735, 0.8622217402645862, 0.7684299843684868, 0.6778785589143939, 0.5916660190965051, 0.5107054882343214, 0.4357044143962798, 0.36715016515926036, 0.30530179102542976, 0.2501881271378399, 0.2016122382240441, 0.15916204732317904, 0.12222682897376984, 0.09001909619676557, 0.06160127162177955, 0.0359164099813219, 0.011822135042709465, -0.011873128514124913, -0.03637260665223135, -0.06285332307642341, -0.09242896170934421, -0.1261144459035566, -0.16479319153993274, -0.20918792233619538, -0.2598358439808816, -0.31706886143042934, -0.38099939369287317, -0.45151219595211745, -0.5282624436094722, -0.6106801706570816, -0.6979809898514682, -0.7891828585989219, -0.8831284964432254, -0.9785129115705014, -1.073915358592889, -1.1678349314893952, -1.2587288970003567, -1.3450527975311295, -1.4253013007045, -1.4980487464867902, -1.5619883430355896, -1.61596898915222, -1.6590287538808681, -1.6904241211405933, -1.7096542074479955, -1.7164792813551342, -1.7109330512423366, -1.6933283401805417, -1.6642559289656762, -1.624576517116659, -1.5754059224401595, -1.5180938084594409, -1.4541963913831042, -1.385443730302427, -1.3137023421505738, -1.2409340031736698, -1.1691516982216714, -1.1003737555404423, -1.0365772559777156, -0.9796518302638648, -0.931354955605096, -0.8932698332119177, -0.8667668722307057, -0.8529697241572828, -0.8527267071196305, -0.8665883339293476, -0.8947915145421597, -0.9372508460017069, -0.9935572348901516, -1.0629839228585787, -1.1444998092072534, -1.2367897900352705, -1.3382816654383962, -1.4471790087067453, -1.5614992483098682, -1.6791160881573948, -1.7978052872527275, -1.915292738971112, -2.029303734770599, -2.1376122685438887, -2.238089236740379, -2.3287484158596707, -2.4077891522924517, -2.473634778456805, -2.5249658718166463, -2.560747597162788, -2.580250514460482, -2.5830643911501414, -2.5691047252056953, -2.5386118594194946, -2.492142744044933, -2.4305555797819562, -2.3549877418795613, -2.2668275447505324, -2.1676805510989308, -2.0593312566518027, -1.9437010880997585, -1.8228037352338153, -1.6986988965372294, -1.5734455492922197, -1.4490558598861532, -1.3274508274143582, -1.2104187045120343, -1.0995771648941424, -0.9963400892484491, -0.9018897223957155, -0.817154817994906, -0.7427952359587745, -0.6791932959353174, -0.6264520217384276, -0.5844002406677591, -0.5526043324855396, -0.5303862596062161, -0.5168473568345898, -0.5108972195334748, -0.5112869068362619, -0.51664557443092, -0.5255195720088174, -0.5364129856033585, -0.547828576032035, -0.558308062145714, -0.5664707215618056, -0.5710493313334387, -0.5709225452599769, -0.5651429013413349, -0.5529597697237946, -0.5338366853850737, -0.5074626573452494, -0.4737572036144334, -0.43286902440267394, -0.38516839118359164, -0.3312334918442272, -0.27183112825783096, -0.2078923082412635, -0.14048340532881493, -0.07077367379341658, -6.603983414639129e-16], [0.0, 0.06966117240342884, 0.13732287928104173, 0.2018165015114945, 0.2620728805525328, 0.3171546990722863, 0.36628526948944307, 0.4088729466067812, 0.4445304934778187, 0.4730888599791639, 0.4946049779798506, 0.5093633318548704, 0.5178712244687038, 0.5208478225735795, 0.5192072276784556, 0.5140359747385077, 0.5065655075227731, 0.49814031251157004, 0.4901825092619829, 0.4841537913849391, 0.481515686121691, 0.48368915006817537, 0.49201454255582416, 0.5077130158793752, 0.531850332945553, 0.5653040686391196, 0.6087350725461255, 0.6625639695319055, 0.7269533535031575, 0.8017961914544711, 0.8867108030074059, 0.9810426188404834, 1.083872753682728, 1.1940332600595223, 1.3101287619488575, 1.430564007088251, 1.5535767268730272, 1.6772750573559168, 1.7996786571989098, 1.9187625615109953, 2.03250273679271, 2.1389222535943655, 2.236136971256648, 2.322399633868631, 2.39614130831116, 2.456009153251185, 2.5008995908621108, 2.529986058899228, 2.542740647020379, 2.5389490648672255, 2.5187185469361673, 2.4824784668482254, 2.4309736071988635, 2.3652502065045686, 2.2866350775866136, 2.1967082578249824, 2.0972698070180043, 1.990301509298468, 1.8779243582415248, 1.7623528059494393, 1.6458468350235305, 1.5306629650181198, 1.4190053309228357, 1.3129779697985307, 1.2145394229298696, 1.1254607054544854, 1.047287614736937, 0.9813082447467113, 0.9285264489141595, 0.8896418514258085, 0.8650368501613274, 0.8547708872968302, 0.8585820900825477, 0.8758962086789849, 0.905842604483427, 0.9472768753193039, 0.998809547253844, 1.058840120452733, 1.1255956318168943, 1.197172793180318, 1.271582683069282, 1.34679691435023, 1.4207941708221437, 1.4916060035850782, 1.557360802817945, 1.6163249117386187, 1.666939925664021, 1.7078553182882803, 1.7379556570415575, 1.7563818066653807, 1.7625456715021866, 1.75613818866536, 1.7371304522036664, 1.7057680184262782, 1.662558610494698, 1.608253602061081, 1.543823811148682, 1.470430272903685, 1.389390779928178, 1.3021430787007824, 1.2102056876848954, 1.1151373552658714, 1.0184962024150803, 0.9217995953638378, 0.8264857676559263, 0.7338781594637916, 0.6451533663670846, 0.5613134918733764, 0.48316358033241374, 0.41129467256911906, 0.3460728789626423, 0.28763470758172993, 0.23588872233699124, 0.19052344204769245, 0.1510212299943381, 0.11667776901423847, 0.08662657339603289, 0.05986785936747133, 0.03530098411188095, 0.011759571810122622, -0.011951623511854616, -0.037019112816202425, -0.06458333775801421, -0.09570261312788941, -0.13131931873259706, -0.17222925524732569, -0.21905499687470684, -0.27222397047930375, -0.33195186883652755, -0.3982318678234421, -0.4708299672668581, -0.5492866165448224, -0.6329246229222084, -0.7208631771177022, -0.8120376708898441, -0.9052248295459476, -0.999072542079855, -1.092133646704553, -1.1829028230576437, -1.2698556570566935, -1.3514888824759004, -1.426360766430355, -1.4931305950895057, -1.5505962314480453, -1.5977287585503466, -1.6337032882313764, -1.6579251056103135, -1.6700504310694408, -1.6700012115494507, -1.6579734985019898, -1.6344391271782583, -1.6001405772130983, -1.556079063594836, -1.5034960758946707, -1.4438487478669826, -1.3787795951281514, -1.3100813016865087, -1.239657363041679, -1.1694795012017183, -1.1015428525553563, -1.037819990900214, -0.9802148834741463, -0.930517886610652, -0.890362869343883, -0.8611875082952479, -0.8441977265124133, -0.8403371542674319, -0.8502623734137696, -0.8743245715501813, -0.9125580812125087, -0.96467611627243, -1.0300738466257071, -1.1078387772654732, -1.1967682232238999, -1.2953935018883878, -1.4020103030084243, -1.5147145482464788, -1.6314429200224814, -1.750017126890003, -1.8681908825189502, -1.9836985097540878, -2.0943040417801835, -2.1978496801220144, -2.2923024843456727, -2.3757982105403967, -2.4466812839166487, -2.5035399834908523, -2.545236031576134, -2.5709279148581548, -2.5800874139306074, -2.572508980630624, -2.5483117733842477, -2.5079343358774406, -2.452122079440788, -2.381907900312565, -2.2985864252721555, -2.2036825290731588, -2.09891490102129, -1.9861555527026773, -1.86738625151819, -1.7446529331077727, -1.620019188343621, -1.495519936358683, -1.3731163837445668, -1.2546533319561224, -1.1418198311119205, -1.0361140904282322, -0.9388134457050848, -0.8509500553693131, -0.7732928518093218, -0.7063361177310092, -0.6502948919420901, -0.6051072394454745, -0.5704432512013132, -0.5457204735996933, -0.5301253106573012, -0.5226397970815181, -0.5220730111932245, -0.5270962864255228, -0.5362812914029562, -0.5481399835954401, -0.5611654017782526, -0.5738722489268236, -0.5848362299904214, -0.5927311478198539, -0.596362824319325, -0.5946990009775606, -0.5868944810551066, -0.5723109020863754, -0.5505306687682471, -0.5213647291507368, -0.48485403743783523, -0.44126471058247957, -0.3910770490709679, -0.3349687507134446, -0.2737927958875503, -0.20855061974657751, -0.1403613079456878, -0.0704276544101138, -6.545254592730593e-16], [0.0, 0.06855528044705994, 0.13459939925157874, 0.1970195437490407, 0.254819307652908, 0.30714895173965345, 0.3533316457934074, 0.3928849753900616, 0.42553711957651436, 0.45123724339164745, 0.47015979899625143, 0.4827025871412503, 0.4894785928108562, 0.491301771025346, 0.48916711686735237, 0.4842255037939379, 0.47775391240062753, 0.4711217944932968, 0.4657544214619642, 0.4630941488610244, 0.4645605886358582, 0.4715107150316562, 0.48519993893504926, 0.5067451679382488, 0.5370908261395532, 0.5769787396111326, 0.626922702205612, 0.6871884241508058, 0.7577794354392487, 0.838429370559239, 0.9286009042220649, 1.0274914432942253, 1.134045512219118, 1.2469736019810438, 1.364777090289219, 1.485778687193023, 1.6081577196226102, 1.7299894439138277, 1.849287470360177, 1.9640483008998417, 2.07229692231439, 2.1721323643149146, 2.261772125515425, 2.3395943907806287, 2.4041770103609394, 2.454332283514237, 2.489136685255804, 2.50795479218399, 2.5104567991776046, 2.496629169869357, 2.466778126504174, 2.421525855138186, 2.3617994759757783, 2.2888130017399257, 2.2040426750987945, 2.1091962352211318, 2.0061768096136983, 1.8970422569303438, 1.7839608962610831, 1.6691646458180869, 1.5549006567896755, 1.4433825648876555, 1.33674249186267, 1.236984911760867, 1.1459434523655152, 1.0652416321878841, 0.9962584392516437, 0.9400995420514597, 0.8975747882875922, 0.8691824965750302, 0.8551008839685045, 0.8551868017955678, 0.8689817781024962, 0.895725191236722, 0.9343742299451343, 0.983630134972036, 1.0419700693865679, 1.1076838333349444, 1.1789145267724535, 1.2537021736787137, 1.3300292554440811, 1.4058670610849489, 1.479221748612596, 1.5481790254988772, 1.610946396342656, 1.6658919914813295, 1.7115790797244612, 1.7467954793401927, 1.7705772111034066, 1.7822258823637827, 1.7813194480842252, 1.7677161597224254, 1.7415516815804066, 1.703229522642972, 1.6534050957984359, 1.5929638716383892, 1.5229942369433254, 1.4447557949706369, 1.3596439526663329, 1.2691517262971874, 1.1748297596655763, 1.0782455865395124, 0.9809431803513032, 0.8844038193874609, 0.7900092550628318, 0.6990081055406812, 0.6124863086391854, 0.5313423589377516, 0.4562679270617007, 0.3877343175226205, 0.3259850688282592, 0.271034839725346, 0.22267456245149936, 0.18048268187139474, 0.1438421424507533, 0.11196263713971105, 0.0839074971238822, 0.05862448246073433, 0.03497963384513718, 0.011793267650553952, -0.012122858066465927, -0.03792820836512307, -0.06671697250349277, -0.09948338467434328, -0.1370898003866031, -0.1802383930476315, -0.22944724160834104, -0.2850314665532174, -0.3470899409208068, -0.4154979587278039, -0.4899060887898508, -0.5697452813888901, -0.6542381325936224, -0.7424160504162292, -0.833141912458485, -0.9251376601890293, -1.0170161441789525, -1.1073164208441066, -1.1945416074156945, -1.2771983304049106, -1.353836755604693, -1.423090165939155, -1.4837130578486892, -1.534616757353532, -1.5749016127840134, -1.603884901078676, -1.621123686603895, -1.6264319931548568, -1.6198917881757857, -1.6018574298824568, -1.5729533891389442, -1.5340652246440043, -1.4863239580843441, -1.4310841612319571, -1.3698962253797262, -1.3044734310648027, -1.2366545690248716, -1.1683629784228757, -1.1015629626524859, -1.0382146140991204, -0.9802281252505429, -0.9294186833110791, -0.8874630384068766, -0.8558588016694643, -0.8358874697046638, -0.8285820875894524, -0.8347003555949136, -0.8547038578737278, -0.8887439474367886, -0.936654664359598, -0.9979528971254282, -1.0718458243921756, -1.1572455004692763, -1.2527902766559238, -1.3568725865015272, -1.4676724700162795, -1.5831960736281807, -1.7013182426378652, -1.8198282240058956, -1.9364774219449978, -2.0490280988324745, -2.1553018906347488, -2.2532270099239433, -2.3408830405768026, -2.4165422856269787, -2.478706712093328, -2.526139641921575, -2.5578914638828585, -2.5733187843017085, -2.572096591346225, -2.554223174476772, -2.520017713446022, -2.470110625760205, -2.4054269334988625, -2.327163075663699, -2.23675774677172, -2.1358574824768652, -2.0262778352111015, -1.90996108423645, -1.7889315026659656, -1.6652492570897504, -1.5409640421976296, -1.418069552638267, -1.2984598673731755, -1.1838887687116693, -1.0759329404280322, -0.9759598888517838, -0.8851013101265506, -0.8042324889877679, -0.733958162866008, -0.6746051236626014, -0.6262216621876021, -0.5885837911518733, -0.5612080159558709, -0.5433702624360909, -0.5341304211636312, -0.5323618325148538, -0.5367849188676389, -0.5460040727917002, -0.5585468353575237, -0.5729043484742726, -0.5875720406554086, -0.6010895073320058, -0.612078574661668, -0.6192785889381988, -0.6215780507847907, -0.6180418123069995, -0.6079331737425442, -0.5907303508429965, -0.5661369318248362, -0.5340860994822498, -0.4947385559863577, -0.44847425090586485, -0.39587817295130984, -0.33772061882996707, -0.2749324945441484, -0.20857633189453512, -0.139813812653109, -0.06987068208679245, -6.467365433000005e-16], [0.0, 0.06726212616199256, 0.1315298389923919, 0.19175474749192703, 0.24702057414312478, 0.29657106238894015, 0.3398334793462965, 0.3764370700226823, 0.40622595010956386, 0.42926606857766497, 0.4458460251499024, 0.45647168738494875, 0.46185471352557456, 0.46289524636058493, 0.4606591960811028, 0.45635067260051504, 0.45128025642467007, 0.4468299086211058, 0.444415411885582, 0.4454473037820257, 0.4512913081369734, 0.46322929010424513, 0.48242175401661547, 0.509872870894565, 0.5463989651214006, 0.5926013086831363, 0.648843968471534, 0.7152373299697621, 0.7916277821794108, 0.8775938973155719, 0.9724492783324953, 1.0752520817213254, 1.184821056356463, 1.299757775606429, 1.4184745835494168, 1.539227630854172, 1.6601542453482891, 1.7793137697854506, 1.8947309076880041, 2.004440549717975, 2.1065330095848873, 2.1991985811850325, 2.280770337992768, 2.3497641315416895, 2.404914807338757, 2.445207742309753, 2.4699049158400923, 2.478564854061104, 2.4710559311601425, 2.447562668673038, 2.4085848401321663, 2.3549293600432026, 2.2876951087649102, 2.208251014256419, 2.1182078736950776, 2.0193845486918436, 1.9137693035493446, 1.803477173394515, 1.69070434519376, 1.5776806072619485, 1.4666209701223725, 1.3596775822967697, 1.2588930582872944, 1.166156302800814, 1.0831618559645144, 1.0113737003330048, 0.9519943639368684, 0.9059400270695702, 0.8738221970411163, 0.8559363582434185, 0.8522578384002234, 0.8624449598731476, 0.8858493715558514, 0.9215332864312282, 0.968293186437322, 1.0246894038554701, 1.0890808506934981, 1.159664047817453, 1.234515506769892, 1.3116364416673734, 1.3889987380842477, 1.4645910815770236, 1.5364641510078234, 1.6027738109535863, 1.6618212924507978, 1.712089430700463, 1.7522741301232883, 1.7813103487405557, 1.798392032209541, 1.8029855795024332, 1.7948365834035116, 1.7739697557017944, 1.7406821150395773, 1.6955296806801836, 1.6393080738982082, 1.5730275763696804, 1.497883328220549, 1.415221464018689, 1.3265020801518186, 1.233259999421512, 1.1370643465741035, 1.0394779707684232, 0.9420177471749492, 0.8461167601895713, 0.7530893159521599, 0.664099653435666, 0.5801351233524014, 0.5019844850847415, 0.43022183683270393, 0.36519654662057094, 0.30702939546763064, 0.2556149828666414, 0.21063028280596613, 0.17154908000823868, 0.1376618648416701, 0.10810062530166266, 0.0818678490880217, 0.05786894127118217, 0.034947176052697745, 0.011920236864633829, -0.012382640870181667, -0.03908392458321694, -0.06922242617234806, -0.10372028303505632, -0.14335317019518365, -0.188724551286428, -0.24024467144280653, -0.29811487227862404, -0.362317671225459, -0.43261289801930874, -0.5085400238789559, -0.58942665786685, -0.6744030241557386, -0.7624220775140643, -0.8522847662415699, -0.9426698157998847, -1.0321672859577145, -1.1193150524870914, -1.2026372839225885, -1.2806839267159373, -1.35207017978842, -1.41551493288603, -1.469877162516892, -1.5141893241863835, -1.5476868490903677, -1.5698329457135678, -1.5803380196658576, -1.5791731558118864, -1.5665772520952053, -1.5430575508411217, -1.5093834768735128, -1.4665738584430648, -1.4158777725944518, -1.3587494170705903, -1.296817562154796, -1.2318502741965085, -1.1657157244766754, -1.1003399994678265, -1.0376629088315532, -0.9795928436137555, -0.9279617675825677, -0.8844814286708911, -0.850701854854872, -0.8279731499983622, -0.8174115313455013, -0.8198704531931813, -0.8359175431439845, -0.865817941071432, -0.9095244798170422, -0.9666749843480043, -1.0365967965808451, -1.1183184604494865, -1.2105883302765603, -1.3118996992846759, -1.4205218882230044, -1.5345365904238362, -1.6518786426624406, -1.7703802840839158, -1.8878178808112982, -2.0019600337401595, -2.1106159529362705, -2.211682974828029, -2.303192118210165, -2.383350621473382, -2.4505804753199154, -2.5035520607665385, -2.5412121191462393, -2.562805416244968, -2.5678896133466864, -2.556343020133656, -2.5283650741444026, -2.4844695646912633, -2.4254707915637232, -2.3524630162972917, -2.2667937222002985, -2.1700313448591952, -2.0639282639638425, -1.9503799568920352, -1.831381301934416, -1.7089810822433447, -1.5852357790656715, -1.4621637537189294, -1.3417009018969919, -1.2256588217074764, -1.11568646945858, -1.0132361863550243, -0.9195348672353162, -0.8355609121045857, -0.7620274557563388, -0.6993722138651756, -0.6477541194773269, -0.6070567559128882, -0.576898424883292, -0.5566485262554624, -0.5454497723646632, -0.542245618868532, -0.5458121692998765, -0.5547937047631816, -0.5677409061948464, -0.5831507762899829, -0.5995072330146393, -0.6153213373672377, -0.62917013487492, -0.6397331327058816, -0.6458255011068904, -0.6464271773869463, -0.6407071605503335, -0.6280424121172191, -0.6080309204039608, -0.5804986379636305, -0.5455001611416971, -0.5033131827495583, -0.4544269096024265, -0.3995247920488105, -0.33946205871755847, -0.27523868284359365, -0.20796852335356691, -0.1388454814596546, -0.06910758937254394, -6.370996208495486e-16], [0.0, 0.06579294360227668, 0.12814069337503048, 0.18606719804808597, 0.23874286154378901, 0.28550988846069225, 0.3259028823722226, 0.3596641304588447, 0.38675314587664983, 0.4073501883393053, 0.42185363988067104, 0.43087127270952574, 0.43520560541293374, 0.4358336984694333, 0.4338818861686195, 0.4305960758822677, 0.4273083637806991, 0.4254008155136853, 0.4262673385210928, 0.4312746274786731, 0.44172319447475594, 0.4588095000288747, 0.4835901798180443, 0.5169493154309109, 0.5595696267191164, 0.6119083700623239, 0.6741786133782355, 0.7463364277721849, 0.828074390555111, 0.9188216385491507, 1.017750548005025, 1.1237899521118788, 1.2356446431019745, 1.3518207474296877, 1.4706564133997069, 1.590357114671596, 1.7090347536970063, 1.8247496493680833, 1.9355544155086557, 2.039538683317417, 2.1348735928768376, 2.219854977144899, 2.292944186573641, 2.3528055531200587, 2.398339567762067, 2.428710943923615, 2.443370858097746, 2.442072795572082, 2.4248815802034063, 2.392175328992054, 2.344640240836939, 2.2832583001991096, 2.209288146283734, 2.124239522615839, 2.029841876515271, 1.9280078191843741, 1.820792281445958, 1.7103483045591379, 1.5988804874310574, 1.4885971689191289, 1.3816624553647874, 1.2801492082348689, 1.1859940846429309, 1.1009556751093925, 1.026576709370582, 0.9641512041506589, 0.914697308928344, 0.8789364697348784, 0.8572793802274763, 0.8498190273699204, 0.8563309699661584, 0.8762808161537641, 0.9088386949636207, 0.9529003513502357, 1.007114337720095, 1.06991463172648, 1.1395578834258095, 1.2141643878585526, 1.29176179429733, 1.3703305028169241, 1.4478496639083782, 1.5223426883728213, 1.59192119282834, 1.6548263503310494, 1.7094666846926936, 1.7544514393060477, 1.7886187643316125, 1.8110580971133834, 1.8211262563985764, 1.81845692770091, 1.802963381070039, 1.7748344295418783, 1.734523802510991, 1.6827332690859642, 1.620389998198666, 1.548618781109678, 1.4687098645835654, 1.382083246408572, 1.2902503666000114, 1.1947741855953453, 1.0972286736565833, 0.9991587428035149, 0.9020416338162125, 0.8072507267195048, 0.7160226748795391, 0.6294286721883736, 0.5483505521270182, 0.4734622896180534, 0.40521733476821054, 0.3438420554648148, 0.28933540718616735, 0.24147478732936095, 0.19982787191951001, 0.16377007876591734, 0.13250715684986714, 0.10510227059855938, 0.08050683301865005, 0.05759424631216011, 0.03519563496989751, 0.012136606276842921, -0.012725952080302739, -0.040468027417149284, -0.07206455496188142, -0.10835832238195214, -0.15003254616928002, -0.1975878646476726, -0.2513243776958659, -0.311329232319743, -0.3774701092721881, -0.44939481265111086, -0.5265370056857899, -0.6081279757689427, -0.6932141542666869, -0.7806799657386894, -0.8692754407611102, -0.9576479001426015, -1.0443769091863044, -1.1280116115775827, -1.20710948576657, -1.2802755241070791, -1.3462008176474698, -1.4036995378517332, -1.4517433405223952, -1.4894922760211768, -1.5163213721350646, -1.531842159622031, -1.5359185330589533, -1.5286764780934552, -1.5105073471570207, -1.4820645253951739, -1.4442534930522886, -1.3982154557249784, -1.3453048756550294, -1.2870613915305364, -1.22517675724036, -1.161457558090917, -1.0977845729180196, -1.0360697395240437, -0.9782117466692761, -0.9260513167423234, -0.8813272581375607, -0.8456343548278019, -0.8203841228401806, -0.806769400174325, -0.8057336496239046, -0.8179457450479555, -0.8437808835016919, -0.8833081213707319, -0.9362848757530235, -1.002158566611355, -1.0800754047107712, -1.1688961592183351, -1.2672185712565212, -1.3734059197645911, -1.4856210976486857, -1.60186542302726, -1.7200212956697079, -1.8378977152988012, -1.953277608579711, -2.063965867069374, -2.167836980253294, -2.2628811565069036, -2.3472478601852873, -2.419285754212707, -2.4775781230273735, -2.5209729584553475, -2.54860701841557, -2.5599233121918945, -2.554681622839699, -2.532961843301308, -2.4951600739394406, -2.441977601292899, -2.3744030467246766, -2.2936881351639813, -2.201317684418225, -2.098974550907598, -1.9885003848815828, -1.8718531443919049, -1.7510623902176485, -1.6281834318380075, -1.505251416317003, -1.3842364471356927, -1.267000788770631, -1.155259156009966, -1.05054300608665, -0.9541696487483565, -0.8672168669718364, -0.7905036022351456, -0.7245771065527715, -0.6697068026351669, -0.6258849275520546, -0.5928338682729986, -0.5700199335598981, -0.556673149938805, -0.5518125237405682, -0.5542760800476436, -0.5627548760236657, -0.5758300932896955, -0.5920122439860933, -0.6097814795891497, -0.6276279714921191, -0.6440913382281652, -0.6577981257775763, -0.6674964037926944, -0.6720866203016904, -0.6706479584479, -0.6624595584870174, -0.6470161035412176, -0.6240374150518557, -0.593471859737196, -0.5554935301998352, -0.510493322084902, -0.4590641878055758, -0.4019809963637855, -0.34017556693492174, -0.27470756717925715, -0.20673207258993087, -0.1374646679426474, -0.06814503395082099, -6.256987676951096e-16], [0.0, 0.064160430353985, 0.12446102728857157, 0.180005233383312, 0.23005581053202764, 0.2740574408039523, 0.31165428383462684, 0.34270200531206324, 0.3672739347883709, 0.3856611636793367, 0.3983665520487103, 0.4060927716133755, 0.40972466832230353, 0.41030637689824523, 0.40901375809768076, 0.40712285361698697, 0.40597516037906434, 0.40694061263533077, 0.4113792246747918, 0.4206023872646787, 0.4358348261761996, 0.45817822082284504, 0.48857744534619185, 0.5277903342503981, 0.5763617913530933, 0.6346029564101033, 0.7025760208387813, 0.7800851455327377, 0.8666737832462884, 0.9616285491560949, 1.0639896199231262, 1.1725674779421305, 1.2859656575581069, 1.4026089978461789, 1.520776765906327, 1.63863988905274, 1.7543014269483674, 1.865839328371874, 1.971350454116313, 2.0689948091466124, 2.157038914615679, 2.2338972640484993, 2.2981708476939766, 2.348681793816983, 2.384503264038134, 2.404983849622438, 2.4097658442323344, 2.3987969129901914, 2.3723348342412103, 2.3309451553650544, 2.2754917733350144, 2.207120620335271, 2.127236800474842, 2.037475681427096, 1.9396685908107378, 1.8358038977331796, 1.7279843719336903, 1.6183818036389206, 1.5091899343450996, 1.4025767906128925, 1.3006375285642808, 1.2053488857086985, 1.1185262992556482, 1.041784687095682, 0.976503800679151, 0.9237989502070925, 0.8844977745207991, 0.8591235839554848, 0.8478856477212956, 0.8506766319108013, 0.8670772240370328, 0.8963678092248725, 0.9375468959666319, 0.989355829774677, 1.050309184993537, 1.1187300920584795, 1.1927896428199911, 1.2705494229542564, 1.350006150187273, 1.4291373517395285, 1.5059469950963116, 1.578509993334151, 1.6450145395426585, 1.7038012834873715, 1.753398446055548, 1.7925520711231568, 1.8202507376572923, 1.8357441940379735, 1.8385555282738784, 1.8284866482222437, 1.8056170111214487, 1.7702957076136343, 1.7231271678749631, 1.6649509124776962, 1.5968159143693237, 1.5199502673454104, 1.435726967464715, 1.3456267043101058, 1.2511986266576556, 1.1540200903717115, 1.0556564141995806, 0.95762166123401, 0.8613414304263433, 0.7681185845846078, 0.6791027603059829, 0.5952644033726502, 0.5173739529024612, 0.4459866620639559, 0.3814333958871419, 0.3238175913647184, 0.2730184055767777, 0.22869991801574585, 0.190326097664595, 0.15718109761263516, 0.1283943037997123, 0.10296944328607176, 0.07981695429563072, 0.05778873776186371, 0.035714350283858526, 0.012437662768208412, -0.013147001526754475, -0.04206022106319576, -0.07520525402975317, -0.11333910847513012, -0.1570476868357197, -0.2067256810718945, -0.2625617711386599, -0.32452954171759096, -0.3923843835174359, -0.4656664897738327, -0.5437098997880189, -0.6256573834649858, -0.7104808078488614, -0.7970064824929621, -0.883944848812094, -0.9699237627044089, -1.0535245226642396, -1.1333197198328593, -1.207911933916307, -1.2759722710226065, -1.3362777370030645, -1.3877464629556908, -1.4294698476544934, -1.4607407536700359, -1.4810769881062784, -1.4902394129008443, -1.4882441607229866, -1.475368577425783, -1.4521506671836713, -1.419381978027254, -1.378094029459178, -1.3295385461143652, -1.2751619179641616, -1.2165744544400683, -1.1555151333826055, -1.0938126625418336, -1.0333437685127456, -0.9759897030067272, -0.9235920073087269, -0.8779086013091509, -0.8405712629178604, -0.8130455368956861, -0.7965940597562248, -0.7922442106099241, -0.8007608984611378, -0.8226251769049124, -0.8580192402842929, -0.9068182044734013, -0.9685889142093911, -1.0425958512314302, -1.1278140474848217, -1.2229487394644045, -1.3264613375155812, -1.4366011315562648, -1.5514420159614486, -1.6689233946680953, -1.786894325899926, -1.9031598867799084, -2.015528683443006, -2.1218604034349062, -2.2201123049039047, -2.308383561432769, -2.384956431733535, -2.4483332986214723, -2.4972687198684627, -2.530795752320189, -2.548245947153382, -2.549262565022108, -2.5338067214189164, -2.50215634092037, -2.454897969996629, -2.3929116675782836, -2.3173493564677883, -2.229607172976345, -2.131292493117731, -2.0241864378878347, -1.9102027646067918, -1.791344133492413, -1.6696567966109448, -1.5471847887548478, -1.425924705896393, -1.3077821365785665, -1.1945307654975528, -1.0877750978045737, -0.9889176591135028, -0.8991314122066287, -0.8193379998471807, -0.7501922772223942, -0.6920734409911976, -0.6450828985873628, -0.6090488553814773, -0.5835374326424515, -0.5678699700254309, -0.5611460164692375, -0.5622713765916176, -0.5699904592723293, -0.5829220740449657, -0.5995977416242977, -0.6185015292757778, -0.6381103910933871, -0.6569339882724112, -0.673552985184592, -0.6866548628840817, -0.6950663613675071, -0.6977817536607889, -0.6939862662421967, -0.6830740885805179, -0.664660556399029, -0.6385882450651743, -0.6049268674055605, -0.5639670302610498, -0.5162080621861315, -0.46234027687317586, -0.40322217931209586, -0.33985325079588097, -0.273343061407775, -0.20487755175219935, -0.1356833970851833, -0.0669914148761949, -6.126331205960263e-16], [0.0, 0.062378607465131485, 0.12052216311888517, 0.17361993500512274, 0.22103180027299058, 0.26230794636251104, 0.29720328062885193, 0.3256861470223724, 0.3479410965533025, 0.36436561308263793, 0.37556085357134433, 0.382316618292487, 0.38559091769706044, 0.3864846447827274, 0.386211991327286, 0.3860673599115156, 0.3873896183621991, 0.391524616659068, 0.399786936564186, 0.4134218699239363, 0.4335686220509684, 0.46122571173698346, 0.497219489832792, 0.5421766251370361, 0.5965013113298505, 0.6603578341927298, 0.7336590071835883, 0.8160608388221164, 0.9069636408635318, 1.005519625731383, 1.1106468791338646, 1.2210494332547002, 1.3352430113996576, 1.4515858703629756, 1.5683140356871477, 1.6835801107290966, 1.7954947459102877, 1.9021697821287764, 2.001762033915358, 2.0925166548008063, 2.172809030180356, 2.241184171728428, 2.296392641502925, 2.3374221120289307, 2.3635237690142903, 2.374232883520791, 2.3693830174973414, 2.3491134772571853, 2.313869790089841, 2.264397145830418, 2.201726913799171, 2.127156511954226, 2.042223065298099, 1.9486714406205488, 1.8484173808662576, 1.7435065814421884, 1.636070649699601, 1.5282809652038292, 1.422301510355712, 1.3202417671635074, 1.2241107758249978, 1.135773424252004, 1.0569099853876007, 0.9889798423927926, 0.9331902423780775, 0.8904707997433342, 0.8614543332787107, 0.8464644703042808, 0.845510289962564, 0.8582881102513716, 0.8841903535739856, 0.922321257622182, 0.9715190363790553, 1.0303839438683204, 1.0973115546743177, 1.1705304535657313, 1.2481434247107006, 1.3281711514161958, 1.408597381953761, 1.487414487145601, 1.5626683316484735, 1.6325014033154719, 1.6951931930195951, 1.7491968896440535, 1.7931715497417062, 1.826009016249505, 1.8468549927329954, 1.855123825631746, 1.8505067032447162, 1.832973142853866, 1.8027658024051598, 1.7603888164688364, 1.7065900137576866, 1.64233752141666, 1.5687913959800899, 1.4872710390319783, 1.3992192543255662, 1.3061638800353383, 1.2096779830893223, 1.1113396309155723, 1.012692258810354, 0.9152066285091771, 0.820245326063925, 0.7290306760668556, 0.6426168564676443, 0.5618668860955446, 0.48743502839525066, 0.41975501308984203, 0.35903432609852987, 0.3052546608960404, 0.25817846557776086, 0.21736136320144125, 0.1821700724620712, 0.1518053152102943, 0.1253290702800453, 0.10169542273789482, 0.07978416677192707, 0.05843625127644831, 0.03649011148649629, 0.01281790890710789, -0.013639294219125712, -0.04383837067480583, -0.07860386579998696, -0.11860145222052257, -0.16431582013792545, -0.2160336059991555, -0.2738318312605834, -0.33757217962067365, -0.40690128915183127, -0.4812570790630297, -0.5598809733434021, -0.6418357292673331, -0.7260284316010512, -0.8112380770807511, -0.8961470518046899, -0.9793756997119766, -1.0595190959887602, -1.1351850772261542, -1.205032542073441, -1.2678090230062937, -1.322386542059638, -1.3677948007194496, -1.4032508157578925, -1.4281841971536104, -1.4422573693116971, -1.4453801600117098, -1.437718319833503, -1.419695684821959, -1.3919898531355908, -1.3555214084564606, -1.3114368849853861, -1.2610858268634508, -1.2059924448958357, -1.147822511744028, -1.0883462598179208, -1.0293981508309313, -0.9728344697181307, -0.9204897562131078, -0.874133123256814, -0.8354255216019012, -0.8058789941453941, -0.7868189219782018, -0.7793501978271853, -0.7843281730423662, -0.8023351136828328, -0.8336627722383307, -0.8783015372069067, -0.9359364666322689, -1.0059503475841716, -1.0874337554409559, -1.1792019188097045, -1.2798180321042842, -1.387622502204918, -1.5007674720590276, -1.617255836073665, -1.7349838528408161, -1.8517863728171475, -1.9654836342168573, -2.073928541161844, -2.175053325044109, -2.266914503428345, -2.34773509034719, -2.4159430765665033, -2.4702052867549145, -2.5094558303341974, -2.5329184914411575, -2.540122547765604, -2.5309116645263474, -2.505445674695675, -2.4641952257677358, -2.4079294427689355, -2.3376969227077624, -2.254800533235401, -2.160766634112882, -2.0573094706228923, -1.9462916001711077, -1.82968130429516, -1.7095080059633843, -1.5878167547989128, -1.4666228597217517, -1.3478677391118723, -1.2333770232569654, -1.124821883492983, -1.0236844786213883, -0.9312283040163584, -0.848474104961233, -0.7761818762765681, -0.7148393186987596, -0.6646569625083331, -0.6255700045584848, -0.5972467401840231, -0.5791033105454977, -0.5703243327467205, -0.5698888383211687, -0.5766008188849517, -0.5891235689943636, -0.6060169281624359, -0.6257764586999769, -0.6468735550992276, -0.6677954650104861, -0.6870842117805631, -0.7033734436945754, -0.7154222945292367, -0.7221454222212583, -0.7226384952496779, -0.716198517086206, -0.7023385146991824, -0.6807962641546966, -0.6515368811121117, -0.6147492625448419, -0.5708365243253974, -0.5204007334036059, -0.46422237929721716, -0.40323516383192415, -0.33849680714103914, -0.2711566688757499, -0.20242106385631928, -0.1335172090062157, -0.06565677192051629, -5.98015746042169e-16], [0.0, 0.060462667222213204, 0.11635734816261238, 0.16696459563095348, 0.21174520650157475, 0.2503568968710826, 0.2826654873316012, 0.30875028322224085, 0.3289034859256346, 0.3436236268915362, 0.3536031721498256, 0.35971059766074953, 0.3629673810655385, 0.3645204895524387, 0.3656110632231732, 0.36754009547485134, 0.371631993881858, 0.3791969647541121, 0.3914932004020829, 0.40968985919137263, 0.4348318143780277, 0.46780710876812603, 0.5093179893535955, 0.5598563107548005, 0.6196839906281388, 0.6888190767664873, 0.7670278474742632, 0.8538232173540314, 0.9484695636044854, 1.0499939272048033, 1.1572033829524941, 1.268708216237644, 1.3829503965829752, 1.4982367020684078, 1.6127757282136466, 1.7247179127617536, 1.8321976266892144, 1.9333763237463986, 2.026485707421666, 2.109869866330271, 2.1820253469347026, 2.241638175845896, 2.28761691174603, 2.3191208976176756, 2.335582995297809, 2.336726213720892, 2.3225737864456257, 2.2934524096754663, 2.249988515197364, 2.193097619496617, 2.123966956683427, 2.044031764718444, 1.9549457477858532, 1.858546378771981, 1.7568158311997741, 1.6518384365614984, 1.5457556481578043, 1.440719554189045, 1.3388460194259497, 1.2421685453977809, 1.1525939233972764, 1.0718607130772166, 1.0015015130011329, 0.9428098998177469, 0.8968128019333085, 0.8642489443515775, 0.8455538568832217, 0.8408517817116893, 0.8499546521457526, 0.8723681462863097, 0.9073046513780875, 0.9537028108904613, 1.0102531708540434, 1.0754292984444604, 1.1475236177286252, 1.2246870979650621, 1.304971841514386, 1.3863755533805757, 1.46688683420642, 1.5445302241131011, 1.6174099363961383, 1.6837512574193612, 1.7419386511045782, 1.7905496916117642, 1.828384053988972, 1.8544869170786071, 1.8681662726846886, 1.8690037864550026, 1.856859015350132, 1.8318669500074474, 1.794429013721222, 1.7451978091177256, 1.6850560549844713, 1.6150902953992206, 1.5365600878791406, 1.450863483698133, 1.3594996992225088, 1.2640299400341344, 1.1660373782591311, 1.0670872970188472, 0.9686884040165854, 0.8722562793489433, 0.7790798616891734, 0.690291793632213, 0.6068433433741395, 0.529484498681804, 0.45874969338449195, 0.3949494798394017, 0.3381683067073737, 0.2882684038227784, 0.24489961892951623, 0.20751489854161567, 0.1753909610108523, 0.14765357766968557, 0.12330676098462921, 0.10126505993413362, 0.0803880847863042, 0.05951632804261836, 0.03750731691071473, 0.013271126043317403, -0.014195702421801105, -0.04577874174517634, -0.08221761052966427, -0.1240820061135073, -0.1717524906200974, -0.2254065549792318, -0.2850103487709208, -0.3503163161921553, -0.42086682454910257, -0.49600371533303245, -0.5748835531135286, -0.6564981981070176, -0.7397001881485663, -0.8232322884775685, -0.905760456491427, -0.9859093762744444, -1.0622996466476509, -1.1335856585541952, -1.1984931740599807, -1.2558556207656724, -1.3046481420215146, -1.344018494408728, -1.373313958283638, -1.3921035229713772, -1.4001947231014844, -1.3976446337720705, -1.3847646764723298, -1.3621190414125464, -1.3305166912888535, -1.2909970725797957, -1.244809819215377, -1.1933888859069115, -1.1383216907568399, -1.0813139754023515, -1.0241512026399346, -0.9686574033963724, -0.9166524547077878, -0.8699088162372544, -0.830108773588016, -0.7988032316581398, -0.777373070574298, -0.7669940210137199, -0.7686059362703087, -0.782887237128778, -0.810235184907133, -0.8507525008243697, -0.9042406994705477, -0.9702003442545474, -1.0478382671758768, -1.1360816281506811, -1.2335985245035082, -1.338824703145734, -1.449995780272929, -1.5651842397523865, -1.6823403650218811, -1.7993361631458482, -1.9140112660462782, -2.0242197446633576, -2.127876748130875, -2.2230038825711014, -2.3077722727820875, -2.380542304222776, -2.4398991209926537, -2.4846830560533197, -2.5140142903067964, -2.527311174400676, -2.5243017979319857, -2.5050285513980994, -2.469845592881343, -2.4194092999978594, -2.3546619539900613, -2.2768090629515076, -2.1872908811553424, -2.087748817676559, -1.9799875466585757, -1.865933730803138, -1.7475923465779837, -1.6270016524083422, -1.5061878685109953, -1.38712063843212, -1.2716703177918545, -1.161568085884979, -1.0583698019266679, -0.9634244317395608, -0.877847754970364, -0.8025019303982567, -0.7379813508597083, -0.6846050633968725, -0.6424158683084139, -0.611186046850772, -0.5904295054535651, -0.5794199684647685, -0.5772147054605579, -0.5826831466194474, -0.5945396238071667, -0.6113793786632944, -0.6317169044480544, -0.6540256374755946, -0.6767779878157313, -0.6984846981569632, -0.717732544224987, -0.7332194392479703, -0.7437860773458319, -0.7484433445110041, -0.7463948386265342, -0.7370539688493584, -0.7200552463890119, -0.6952595296386529, -0.6627531429440208, -0.6228409460767764, -0.5760335867313089, -0.5230293171776459, -0.4646908948345669, -0.40201821149325084, -0.33611740408827867, -0.26816728857028893, -0.1993840253673611, -0.1309849684632729, -0.06415266919313634, -5.819723779827008e-16], [0.0, 0.058428810442321254, 0.11200140557425901, 0.1600941693343753, 0.20227164620756308, 0.2383000935328369, 0.26815539644953923, 0.2920251179632413, 0.3103046095463392, 0.3235872627409183, 0.3326491354692332, 0.33842833428959135, 0.3419996719124928, 0.344545244398244, 0.34732168140046427, 0.3516249128106142, 0.358753363880817, 0.3699705365715657, 0.3864679562798775, 0.40932945965235396, 0.43949777089992975, 0.4777442615538166, 0.5246427131901678, 0.580547806136584, 0.6455789419212483, 0.7196098760737746, 0.8022644940778434, 0.8929189103750464, 0.9907099121274118, 1.0945496099038197, 1.203146000546303, 1.3150289971228628, 1.428581340856115, 1.5420736837554785, 1.6537030215618798, 1.761633567308566, 1.8640390885947393, 1.9591456883017786, 2.0452739901091532, 2.120879697326121, 2.1845915261523063, 2.235245571791825, 2.271915246535747, 2.293936031079809, 2.300924401507945, 2.292790431623177, 2.269743720318927, 2.232292452808809, 2.181235568893237, 2.1176481770234528, 2.042860515677598, 1.9584309195031961, 1.8661133929803433, 1.7678205254524564, 1.6655825950314112, 1.561503802312232, 1.457716645721818, 1.3563354969207886, 1.2594104558152566, 1.168882559876865, 1.0865413917128715, 1.013986072904315, 0.9525905523886931, 0.9034739960352673, 0.8674769630144618, 0.8451439170410218, 0.8367124699200887, 0.842109594713158, 0.8609548801645187, 0.89257073082026, 0.9359992525985915, 0.990025405434682, 1.0532058568648925, 1.1239028366160713, 1.2003221756618472, 1.2805546166110875, 1.362619408021416, 1.444509145050396, 1.5242347939417582, 1.5998698387467118, 1.6695925153167928, 1.7317251492611125, 1.7847696899075143, 1.8274386294357359, 1.858680612819616, 1.8777001771118234, 1.8839712046170487, 1.8772438299994878, 1.8575447025034897, 1.825170667246634, 1.7806760899550134, 1.7248542036010523, 1.6587129993900631, 1.5834463148968665, 1.5004008856978024, 1.4110402208201644, 1.3169062344759312, 1.2195796151425202, 1.120639936972131, 1.0216265172409407, 0.9240009972065428, 0.8291125730665884, 0.7381667300490314, 0.652198237930621, 0.572049052912638, 0.49835164168028534, 0.4315181019198477, 0.37173530315731884, 0.31896611631964444, 0.27295664383106183, 0.23324920829017892, 0.19920071069881945, 0.17000583252839882, 0.14472443304451713, 0.12231238734491802, 0.10165502415078252, 0.0816022576831182, 0.06100446656301121, 0.03874815561717221, 0.013790444155503331, -0.014808543500845987, -0.047856253558011694, -0.08600203450477903, -0.12971591679653124, -0.17927241597075963, -0.23473980366718875, -0.29597514849745626, -0.36262527829661473, -0.43413366080516386, -0.5097530451938852, -0.5885635559790374, -0.6694957876146003, -0.751358316035495, -0.8328689260254974, -0.9126887534962012, -0.9894584621497122, -1.0618355166143718, -1.128531580490444, -1.1883490587278773, -1.2402158196699855, -1.2832171725991393, -1.316624240759374, -1.3399179560578518, -1.3528080078576261, -1.3552462018583433, -1.3474338229697604, -1.3298227449007585, -1.3031101852194393, -1.2682271640049116, -1.226320882934443, -1.178731395762826, -1.1269630867928164, -1.0726516074468224, -1.017527039064934, -0.9633741495844643, -0.9119906902656575, -0.8651447340976252, -0.8245320884951904, -0.7917348205327605, -0.7681819130324595, -0.7551130247410499, -0.7535462586256078, -0.7642507506232992, -0.7877247791859115, -0.8241799663606794, -0.873531997080453, -0.9353981282962508, -1.0091015973477433, -1.0936828734903652, -1.187917531825704, -1.2903403690452173, -1.399275229313995, -1.512869869999096, -1.6291350741935475, -1.7459871131226872, -1.861292579106511, -1.972914550827231, -2.0787590186790736, -2.176820489810648, -2.265225710330617, -2.3422744856189666, -2.406476647725555, -2.4565843097996263, -2.49161865917191, -2.510890670391084, -2.514015264043433, -2.5009185930417646, -2.471838301462577, -2.427316767962212, -2.3681875122511156, -2.2955551050030047, -2.2107690749893014, -2.1153924484368973, -2.011165681189296, -1.8999668511741574, -1.7837690643719917, -1.6645960898924597, -1.5444772774216335, -1.4254028223397166, -1.3092804299900862, -1.1978943913063165, -1.0928680182997117, -0.9956303013997346, -0.9073875435054638, -0.8291006005334044, -0.7614682183571473, -0.7049168048092503, -0.6595968166074283, -0.6253857786084948, -0.6018977906984883, -0.5884992198916575, -0.5843301257144071, -0.5883308293591814, -0.5992729147715772, -0.6157938457588272, -0.6364342998976247, -0.6596772594706838, -0.6839878633017192, -0.7078530120098455, -0.7298197330651875, -0.7485313506682661, -0.7627605678497009, -0.771438652658885, -0.7736800246964068, -0.7688016598688165, -0.7563368670040373, -0.7360431364117742, -0.7079039138958437, -0.6721243102454669, -0.6291209119016798, -0.5795060093911766, -0.5240667024476275, -0.4637394709247687, -0.39958091538083335, -0.33273546770632917, -0.2644009479654489, -0.1957928968371787, -0.1281086423570616, -0.06249206435874819, -5.646400386019649e-16], [0.0, 0.05629407505042242, 0.10749037259707217, 0.15306471001393465, 0.1926872168718897, 0.22623269763268072, 0.2537852609273413, 0.2756370760690787, 0.292281270755838, 0.30439913706867966, 0.312841961981156, 0.3186079398737614, 0.3228147544020595, 0.32666853218749015, 0.33142996824382837, 0.33837850031901845, 0.34877546442526386, 0.3638271953084579, 0.38464904262128763, 0.41223125587613024, 0.44740764924751797, 0.49082789196387056, 0.5429341829556437, 0.6039429617413343, 0.6738321838587634, 0.7523345515423125, 0.8389369422176641, 0.9328861224150021, 1.0332006767491875, 1.1386889246238314, 1.2479724452129024, 1.3595146878729945, 1.4716540140479488, 1.58264040125325, 1.6906749427978114, 1.7939512009881653, 1.8906974186213898, 1.9792185649989893, 2.0579371892740763, 2.1254320758464784, 2.180473743286212, 2.222055898819929, 2.2494220530920934, 2.262086612496952, 2.2598498961571662, 2.242806668458887, 2.211347932447039, 2.1661558905782123, 2.1081921433869093, 2.0386793595324915, 1.9590768084684913, 1.8710502957439394, 1.7764371770531402, 1.67720724724911, 1.575420401666608, 1.4731820467674115, 1.3725972933495718, 1.2757249969540803, 1.1845327158642407, 1.1008536370598223, 1.0263464751272953, 0.9624592795257106, 0.9103979934473954, 0.8711004950271795, 0.8452167215758075, 0.8330953330051907, 0.8347772151910725, 0.8499959614646466, 0.8781853046943076, 0.9184933075436224, 0.9698029584803229, 1.0307586698503584, 1.099798035490383, 1.1751880822935223, 1.2550651458389928, 1.3374774171554251, 1.4204291478954945, 1.5019254660682788, 1.5800167448104492, 1.65284148265797, 1.7186666949545097, 1.7759248813332866, 1.8232467219744906, 1.8594887633616313, 1.8837554798329352, 1.895415237217367, 1.8941098357792454, 1.879757467827954, 1.8525490867680803, 1.8129383450852123, 1.7616254148247565, 1.699535151690401, 1.627790199348866, 1.5476797505699416, 1.460624783536537, 1.3681406725710061, 1.2717981307052078, 1.1731834756053952, 1.0738592195838856, 0.9753259686419722, 0.8789865751705126, 0.7861134251730894, 0.6978196553409711, 0.6150349902084206, 0.5384867676433163, 0.46868658519095036, 0.4059228537341219, 0.35025939225890174, 0.30154004207946816, 0.25939912459658404, 0.2232774174266563, 0.19244318329287755, 0.16601765794186926, 0.14300429074925544, 0.12232093742231583, 0.10283413064940936, 0.08339450351357573, 0.06287241324236517, 0.04019281006885856, 0.014368417675341236, -0.015469662690158698, -0.05004474396676571, -0.08991147107533805, -0.13543748682915635, -0.1867903439559928, -0.24393002431553493, -0.30660728012556177, -0.37436786009012024, -0.4465625296066584, -0.522362642617146, -0.6007808770108383, -0.6806966094862006, -0.7608852828996245, -0.840051012504775, -0.9168615898488306, -0.9899849766962927, -1.0581263379216743, -1.120064642998706, -1.1746878710606672, -1.2210258844405169, -1.2582800894297477, -1.2858490794295638, -1.3033495528459291, -1.3106319136170221, -1.3077900933083753, -1.2951652770246007, -1.273343367410388, -1.2431461779654243, -1.2056165048643912, -1.1619973815074165, -1.1137059682446602, -1.0623026673993892, -1.0094561773887727, -0.9569053062833777, -0.906418451846246, -0.8597517197287924, -0.8186066923946993, -0.7845888774007211, -0.7591678544045466, -0.7436401058399662, -0.7390954573683746, -0.7463879723568042, -0.7661120416932558, -0.7985842887011905, -0.843831771692251, -0.9015868171274299, -0.9712886580807025, -1.0520918895748013, -1.1428815883721244, -1.2422947839680136, -1.3487478137907885, -1.4604689527366472, -1.5755355786692882, -1.6919150245578867, -1.8075081772480552, -1.9201948147016166, -2.027879629593718, -2.1285378685196754, -2.220259523219258, -2.3012910430215068, -2.3700735953691043, -2.425276982408959, -2.4658284242712054, -2.4909355413114276, -2.500103005304212, -2.493142480000008, -2.4701756309320424, -2.431630149004515, -2.3782288982015856, -2.3109724606963535, -2.231115508750352, -2.1401375782869034, -2.0397089503698616, -1.9316524608455599, -1.8179021523611771, -1.7004597546032316, -1.5813500262016282, -1.4625760142055684, -1.346075283863324, -1.2336781427659094, -1.127068830006304, -1.0277505642306253, -0.9370152462564092, -0.855918494770511, -0.7852605604216283, -0.7255735177054243, -0.6771149790270239, -0.6398684150545582, -0.6135500039098721, -0.5976217728627845, -0.5913106439121906, -0.5936328526884882, -0.6034230819701263, -0.6193675398960213, -0.6400401213715586, -0.6639407214127129, -0.6895347229069182, -0.7152926595605191, -0.7397290581072222, -0.7614394920033936, -0.7791349310495947, -0.7916725462700702, -0.7980822250084385, -0.7975881650996, -0.7896250462452172, -0.7738484180651115, -0.7501390941357725, -0.7186014958708866, -0.6795560454462722, -0.6335258592096878, -0.5812181383146418, -0.5235007880272646, -0.4613749178980985, -0.39594397874300774, -0.328380376547036, -0.25989046589463805, -0.1916788647893281, -0.12491304779148078, -0.06068916492045503, -5.461655573554057e-16], [0.0, 0.05407615779269436, 0.10286112993985799, 0.14593280411698337, 0.1830677382109212, 0.21424829691739444, 0.23966401036880502, 0.25970710334430935, 0.2749622959506647, 0.2861911266108698, 0.2943111919497662, 0.30037083206668924, 0.3055199103252934, 0.31097744109090897, 0.3179969041355718, 0.32783014851477055, 0.34169082993341016, 0.3607183428697325, 0.385943201523961, 0.4182547921258659, 0.4583723640061069, 0.506820049437421, 0.5639066044718761, 0.6297104472423601, 0.7040704393181955, 0.7865827129486347, 0.876603695940173, 0.9732593302562764, 1.07546032408552, 1.1819231240065948, 1.2911961478239908, 1.4016906833278964, 1.5117157370571008, 1.619516013182335, 1.7233121185254818, 1.8213420276461703, 1.9119028034780603, 1.9933915552162589, 2.064344626469219, 2.123474042896021, 2.169700308840012, 2.202180725430443, 2.2203325062803594, 2.223850088770905, 2.212716176034302, 2.1872061938026057, 2.147886003648921, 2.0956028759725553, 2.0314698884137625, 1.9568440742516329, 1.8732987968442973, 1.7825909665923645, 1.686623842790356, 1.5874062709750434, 1.4870092943114908, 1.3875211430002954, 1.2910016470149352, 1.199437133649094, 1.114696861947321, 1.038492011313644, 0.9723381822671912, 0.9175222848694484, 0.8750745867787978, 0.8457465707062631, 0.8299951132204177, 0.8279733467297097, 0.8395284077093508, 0.8642061106993845, 0.9012624232592216, 0.9496814559177732, 1.008199527123155, 1.075334720010803, 1.1494212189444264, 1.2286476023567885, 1.3110981771139965, 1.3947963706371749, 1.4777491519808195, 1.5579914330379818, 1.6336294064555867, 1.7028818075093928, 1.7641181422987682, 1.815893002768922, 1.8569756882803141, 1.8863744712363084, 1.9033549777111303, 1.907452299773679, 1.8984766106629596, 1.8765122133160814, 1.8419101130449875, 1.7952743624534957, 1.7374425771151005, 1.6694611604052074, 1.59255590178002, 1.508098721652379, 1.4175714251958833, 1.3225273947701928, 1.2245521946059426, 1.1252240809059981, 1.0260754052090364, 0.9285558689376152, 0.8339985333451176, 0.7435894130024855, 0.6583413845005485, 0.5790730276644211, 0.5063928872027704, 0.4406895016354592, 0.382127397132355, 0.33064909032544576, 0.28598299009903655, 0.2476569376975756, 0.2150169810047443, 0.18725084614211399, 0.16341545093604554, 0.14246770327421746, 0.12329774545181305, 0.10476374533004719, 0.08572729798796518, 0.06508848845045946, 0.04181967732369941, 0.014997106453043012, -0.016170519877631104, -0.052317242659670124, -0.0938995096333176, -0.14118083871362824, -0.1942219008231294, -0.2528762980830361, -0.3167921646373532, -0.38541956530374055, -0.45802351562071636, -0.5337022995418096, -0.6114106217573165, -0.6899870039465155, -0.768184721432126, -0.8447054816085061, -0.9182349705859211, -0.9874793416717942, -1.0512016899782488, -1.108257552397774, -1.1576284916101824, -1.1984528662446583, -1.2300529557870095, -1.251957696681373, -1.2639203931751826, -1.2659308901579165, -1.2582218324878762, -1.24126878268267, -1.2157841227021124, -1.1827048220421732, -1.1431743095756806, -1.098518836633495, -1.0502188599527138, -0.9998761017731603, -0.9491770572909691, -0.8998538140117939, -0.8536431208769674, -0.8122446954693551, -0.7772797838128622, -0.7502509885289551, -0.732504357290998, -0.7251946751292635, -0.7292548323021555, -0.7453700458608016, -0.7739575999342174, -0.8151526398771032, -0.8688004118977595, -0.9344551861081796, -1.0113859408574608, -1.0985887236327667, -1.1948054427175379, -1.298548688132301, -1.408132033969755, -1.521705140672328, -1.6372928583742503, -1.752837434038715, -1.86624284819494, -1.975420253529414, -2.0783334587465263, -2.173043397718421, -2.25775054610227, -2.3308342947972807, -2.3908883607146416, -2.436751408623786, -2.467532171058752, -2.482628483669653, -2.481739797817665, -2.4648728871248906, -2.43234062633434, -2.38475388527769, -2.323006743989775, -2.248255393080768, -2.1618912325406496, -2.0655088185896866, -1.9608694286995554, -1.8498611165822902, -1.734456209331821, -1.6166672560849138, -1.498502470194335, -1.3819217142311335, -1.2687940590314644, -1.16085790497626, -1.0596845868517317, -0.9666462946793587, -0.8828890340625418, -0.8093112235936748, -0.7465483868383864, -0.6949642458405203, -0.6546483657023304, -0.62542033947963, -0.6068403433461138, -0.5982257376451283, -0.5986732438503403, -0.6070860941642401, -0.6222054327476534, -0.6426451482543122, -0.6669292388389999, -0.6935307549910619, -0.7209113337248979, -0.7475603305441166, -0.7720325732794815, -0.792983803858067, -0.8092029391652372, -0.8196403687102377, -0.8234316125677544, -0.8199157853346138, -0.8086484474984482, -0.7894085712220048, -0.7621994994176116, -0.7272439312875654, -0.6849731203491111, -0.6360106185024875, -0.5811510382313609, -0.5213344310726844, -0.4576169909021731, -0.3911388825931081, -0.32309006792734607, -0.25467504949786224, -0.18707747853812254, -0.12142557353803829, -0.05875927316336571, -5.267040044605034e-16], [0.0, 0.05179323099789152, 0.09815102623154283, 0.13875500357477022, 0.17348800430968375, 0.20243799734589646, 0.22589621199691431, 0.24434953469824966, 0.2584673551098619, 0.2690831925412453, 0.2771715708734433, 0.28382073563662186, 0.290201917435928, 0.29753593867701245, 0.30705803314528946, 0.3199817985636167, 0.3374632294675177, 0.36056578085672364, 0.3902273919726829, 0.42723035468831205, 0.4721748434504844, 0.5254568351305273, 0.5872510396871168, 0.6574993388801244, 0.7359050934554383, 0.8219335326472018, 0.9148182871640914, 1.0135739718494132, 1.1170145708056844, 1.2237772297971792, 1.332350921905457, 1.4411093262115509, 1.5483471489045135, 1.6523190244740364, 1.7512800638816342, 1.843527068651511, 1.927439405947207, 2.0015185405771967, 2.064425245563426, 2.1150135628575266, 2.1523606588452253, 2.175791813710177, 2.1848998972723956, 2.179558813834675, 2.1599305417140564, 2.1264655460231805, 2.079896502170034, 2.021225428580681, 1.9517044863756399, 1.8728108572414053, 1.786216254764234, 1.6937517554904291, 1.5973687507183019, 1.49909691567883, 1.4010001669570504, 1.3051316299006481, 1.2134886640814397, 1.1279689959473707, 1.050328983571792, 0.9821449894395669, 0.9247787646771385, 0.8793476537859262, 0.846700315059703, 0.8273985212199598, 0.8217054605631086, 0.8295808045862024, 0.8506826473976327, 0.8843762591334218, 0.9297494340544331, 0.9856340579214322, 1.0506333724240615, 1.1231542804376955, 1.2014439179438139, 1.2836296194228571, 1.3677613257965733, 1.4518554294164587, 1.533939020455106, 1.6120934940441995, 1.6844964976868055, 1.7494612433032337, 1.8054722765958724, 1.8512168865106917, 1.8856114471704435, 1.9078221110215536, 1.9172794119286343, 1.9136864870952932, 1.897020783270255, 1.8675292718471228, 1.8257173552612957, 1.7723317996480572, 1.7083381723086528, 1.6348933936233698, 1.553314128456418, 1.4650418390163626, 1.3716053972318796, 1.2745822081614921, 1.1755588255288854, 1.0760920455098295, 0.977671445351455, 0.881684289849074, 0.7893836623069345, 0.7018605890989493, 0.6200208205793755, 0.5445668085917108, 0.47598528530448214, 0.4145407030018528, 0.3602746434439936, 0.3130111522973357, 0.272367802773787, 0.23777214681584644, 0.20848307558059198, 0.18361648703215716, 0.1621745502494545, 0.14307776629420071, 0.12519895639734657, 0.10739826152137949, 0.08855821418841782, 0.0676179443832448, 0.04360560629364678, 0.015668160979882505, -0.016902279475126784, -0.05464624999576257, -0.09791946758349393, -0.14688057423841122, -0.2014844224012978, -0.26148109280234977, -0.3264206848544366, -0.3956637688150884, -0.4683972406932224, -0.5436551790593517, -0.6203441711379253, -0.6972724571730835, -0.7731821400859571, -0.8467836244939457, -0.9167913873748796, -0.9819601436372397, -1.0411204546359158, -1.0932128366893892, -1.1373194597378522, -1.1726925826570875, -1.1987789500484158, -1.2152394736463636, -1.2219636374030804, -1.2190781959568306, -1.2069498783306412, -1.1861819588027738, -1.1576047112017798, -1.1222599175521348, -1.0813797531597957, -1.036360514088323, -0.9887317859167466, -0.9401217713347926, -0.8922195955132547, -0.8467354897025697, -0.8053598130663633, -0.7697219087933139, -0.7413498020764573, -0.721631734234849, -0.7117804893250256, -0.7128014079058578, -0.7254648986272011, -0.7502841540120356, -0.7874986547016405, -0.8370639094867853, -0.8986477299801514, -0.9716331824121812, -1.0551281985720231, -1.1479816672919956, -1.2488056710243838, -1.3560033828326519, -1.467802001183194, -1.5822899766751373, -1.6974576793231657, -1.8112405698214973, -1.9215638754770874, -2.0263877327719175, -2.1237517447737573, -2.211817913226874, -2.288910941863283, -2.3535549684088775, -2.4045058664531336, -2.440778362781809, -2.4616673384084704, -2.46676281940419, -2.4559583133651426, -2.4294523053333115, -2.387742889353665, -2.3316156746630603, -2.262125264803292, -2.1805707598626447, -2.088465872889949, -1.9875043778786563, -1.879521715530016, -1.7664536716509223, -1.6502931093961721, -1.5330457790498364, -1.4166862466651207, -1.3031149752671216, -1.1941175597090874, -1.0913270595134292, -0.996190294570003, -0.9099388684059496, -0.8335655653909021, -0.7678066346470247, -0.7131303279141715, -0.6697319047823677, -0.6375351603505244, -0.6162003714085988, -0.6051384015844852, -0.6035305573702943, -0.6103536491844761, -0.6244095880013036, -0.6443587415949419, -0.6687561876777441, -0.696089936243174, -0.7248201517890195, -0.7534183887497671, -0.7804058607561188, -0.804389795999622, -0.8240969861399471, -0.8384037133978672, -0.8463613377280063, -0.847216940766316, -0.8404285526699259, -0.8256746287235815, -0.8028575911139807, -0.7721014038187226, -0.7337433012760035, -0.6883199405517387, -0.6365483883588123, -0.5793024849566588, -0.5175852433968815, -0.4524980418730442, -0.38520744660495315, -0.3169105607611954, -0.2487998299647802, -0.1820282460824196, -0.11767587801724298, -0.05671862146403255, -5.064170558417859e-16], [0.0, 0.04946375633905234, 0.09339750151250803, 0.1315872648651055, 0.16402105386503243, 0.19088954948341427, 0.2125810868351269, 0.22967104144796505, 0.2429058880396116, 0.2531823385359348, 0.2615220957037073, 0.26904287489455747, 0.2769264460413105, 0.28638452866155456, 0.2986234321314257, 0.31480837034917053, 0.33602839313483923, 0.36326286592424545, 0.3973503947298982, 0.4389610357750561, 0.4885725500538758, 0.5464513642695445, 0.6126387835883791, 0.6869428712923449, 0.7689362689513333, 0.8579600816906304, 0.9531338002158694, 1.0533710782998609, 1.1574010352645978, 1.263794611353031, 1.3709953733448612, 1.477354051625848, 1.5811659911171456, 1.6807106195309645, 1.7742919793743568, 1.8602793364670065, 1.9371468683874171, 2.0035114515290613, 2.058167605038532, 2.100118712922528, 2.1286037305686616, 2.1431186867993004, 2.1434324148440025, 2.129596082315442, 2.1019462380846665, 2.06110124927192, 2.00795116060486, 1.9436411672541796, 1.8695490470420728, 1.787257044830386, 1.6985188373184004, 1.6052223270787442, 1.50934911745561, 1.4129316023993705, 1.3180086653668817, 1.226581017577821, 1.1405672172676307, 1.061761397808984, 0.9917936939931725, 0.9320942932854135, 0.8838619539956081, 0.8480377270882864, 0.8252844953425247, 0.8159728057498146, 0.820173321754291, 0.8376560648246721, 0.8678964537216515, 0.9100879886064246, 0.9631612697448974, 1.0258088908215754, 1.0965156084219476, 1.1735930654278235, 1.2552182398914826, 1.339474704971571, 1.4243957217892487, 1.5080081471121833, 1.5883761225268755, 1.6636435215402308, 1.7320741655674965, 1.7920888781188824, 1.8422985272085175, 1.8815323070494587, 1.908860628941673, 1.9236121249489164, 1.9253844131771338, 1.9140484266163853, 1.889746264806945, 1.8528826851600384, 1.8041105047283348, 1.7443103298014353, 1.6745651663087011, 1.5961305853364596, 1.5104012221602807, 1.4188744715402144, 1.323112304607132, 1.224702172005426, 1.1252179731551957, 1.026182062260879, 0.9290292283364542, 0.8350735299517306, 0.7454787871181758, 0.661233434751347, 0.5831303269824413, 0.5117519521792703, 0.44746137816139314, 0.3903990993078631, 0.3404858057886834, 0.29743094381828034, 0.2607467884357274, 0.2297676105615502, 0.2036733914666815, 0.1815174235322004, 0.16225703913076883, 0.14478663203784548, 0.12797207990240933, 0.11068564334891103, 0.0918404080426228, 0.07042335073012383, 0.045526148464089033, 0.016372910943827333, -0.017655902409354784, -0.057004018456581484, -0.10192486035680483, -0.15247242229563968, -0.20849775936398432, -0.2696511962800169, -0.3353902091531231, -0.404992786035765, -0.47757592836913826, -0.5521188202510762, -0.6274900691797939, -0.7024783136968384, -0.7758254029332402, -0.8462612827747988, -0.9125396750216931, -0.9734736107905727, -1.0279698781776727, -1.0750614669535061, -1.1139371392747657, -1.1439673239684884, -1.1647256211956638, -1.1760053120424432, -1.1778303911556718, -1.1704607768724606, -1.154391499001902, -1.1303458158703992, -1.0992623656586635, -1.062276608599234, -1.0206969624676525, -0.9759761703215895, -0.9296785631771967, -0.8834439881296706, -0.8389492615830365, -0.7978680754685303, -0.7618303298329636, -0.7323818867599086, -0.710945737630518, -0.6987855482275577, -0.6969724947348134, -0.7063562294777733, -0.7275407200502806, -0.7608655915578211, -0.8063934718315887, -0.8639036967782413, -0.9328925810008483, -1.0125803011664318, -1.1019242801604623, -1.1996388027640938, -1.3042204422766508, -1.413978735902842, -1.5270714183176304, -1.6415434107785425, -1.7553686702446398, -1.8664939314871047, -1.9728833269168635, -2.0725628450230698, -2.1636635895260974, -2.2444628276007954, -2.31342186620707, -2.3692198694636386, -2.410782825335477, -2.4373069843691773, -2.4482762240267464, -2.4434729361605187, -2.4229821888397383, -2.3871890733463097, -2.336769308821965, -2.2726733368406116, -2.196104292214492, -2.1084903808802933, -2.0114523272457174, -1.9067666687227924, -1.7963257715461123, -1.682095517053231, -1.5660716595962891, -1.4502358849323846, -1.3365126006763055, -1.2267274681770646, -1.1225686385949238, -1.025551586202939, -0.9369883407759453, -0.8579618106446909, -0.7893057613332867, -0.7315908748119165, -0.6851171647510496, -0.649912867458802, -0.6257397702627483, -0.6121047828500373, -0.6082774063452436, -0.6133126133792856, -0.6260785235444348, -0.6452881455787194, -0.6695343631184005, -0.6973272671744281, -0.7271328873816294, -0.7574123467277476, -0.7866604614901157, -0.8134428294818523, -0.8364304948217736, -0.8544313450890769, -0.8664174851431641, -0.8715479388041556, -0.8691861522691872, -0.8589119084631099, -0.8405274060607713, -0.8140574070190819, -0.7797435083358516, -0.7380327435872606, -0.6895608638223752, -0.6351307819999883, -0.575686786969932, -0.512285238984309, -0.4460625462318619, -0.3782012887463728, -0.3098954005948278, -0.24231534241279223, -0.17657419362191495, -0.11369556713851899, -0.05458419976227364, -4.854713071472535e-16], [0.0, 0.04710629756706851, 0.08863771370639299, 0.12448440001574902, 0.1547374660178851, 0.17968651838611027, 0.19981159093891093, 0.2157696681518821, 0.22837614668898515, 0.23858171255091196, 0.2474452324895612, 0.25610336425887176, 0.2657376783566456, 0.277540151899347, 0.2926779414055751, 0.3122583643353277, 0.3372950186113444, 0.3686759450006858, 0.40713468972062344, 0.45322505509712824, 0.5073002362458666, 0.5694969337768244, 0.6397249091148574, 0.7176623132421838, 0.8027569748836629, 0.8942336839823417, 0.9911073545042566, 1.0922018009695666, 1.1961737193877444, 1.3015413290940059, 1.4067170107287144, 1.5100431703428745, 1.6098304730310646, 1.7043975238097406, 1.7921110303797774, 1.8714254630864942, 1.9409212323786889, 1.9993404333296676, 2.0456192596744582, 2.078916265108058, 2.0986357454919804, 2.104445629828812, 2.0962893976276837, 2.0743916824480757, 2.039257372513315, 1.9916641756391442, 1.9326487735009203, 1.8634868455975095, 1.7856673923460935, 1.7008619258929998, 1.6108892230227232, 1.5176764438847368, 1.4232175104304003, 1.3295297072215142, 1.2386095129223733, 1.1523886921681812, 1.0726916740581531, 1.0011952153036743, 0.9393912937297002, 0.8885541026320504, 0.8497119202455845, 0.8236245136070364, 0.8107666051882929, 0.8113177870100551, 0.8251591140128463, 0.8518764499804459, 0.890770479133565, 0.9408731385332433, 1.0009700744931365, 1.069628583987622, 1.1452303730076223, 1.2260083510834745, 1.310086587486595, 1.395522482194119, 1.4803501552841127, 1.5626240331884886, 1.6404616097380147, 1.7120843841516062, 1.7758560264088477, 1.8303168915667363, 1.8742140967489744, 1.906526485442452, 1.9264839306195223, 1.9335805679163118, 1.9275816991765957, 1.9085242614346827, 1.8767109130424025, 1.8326979432905526, 1.777277360736282, 1.7114536548785144, 1.6364158524179062, 1.5535056000151968, 1.4641820975420368, 1.3699847770877855, 1.2724946717510575, 1.173295443375108, 1.0739350393385956, 0.9758889253477303, 0.8805257945503745, 0.7890765844478504, 0.7026075438067296, 0.6219979843658537, 0.5479232293361691, 0.4808431356226521, 0.42099642277922145, 0.36840089257339753, 0.3228594724451911, 0.2839718678810734, 0.25115146651083065, 0.22364700413592337, 0.20056838322949214, 0.18091593069735512, 0.1636122964394154, 0.14753612961694965, 0.13155662710767232, 0.11456802945164911, 0.09552314410590047, 0.07346500388622212, 0.047555819341487136, 0.01710245616499891, -0.01842223925443777, -0.059362833749523065, -0.10586986456859424, -0.15789386849482015, -0.21518504844784095, -0.277298595737945, -0.34360553820018275, -0.4133088396941494, -0.48546433859164634, -0.5590059853945731, -0.6327747257756132, -0.7055502780196702, -0.7760849755560474, -0.8431387880248444, -0.9055145996031576, -0.9620928120498855, -1.011864352445646, -1.0539612016427817, -1.0876836181441858, -1.1125233120726354, -1.1281819231127868, -1.1345842723571606, -1.1318859879897099, -1.1204752454656124, -1.1009685107879388, -1.0742003269475537, -1.0412073347927948, -1.0032068667395029, -0.9615705911220643, -0.9177938131100768, -0.8734611517340081, -0.8302094087916587, -0.7896885217869882, -0.7535215476138853, -0.7232646550077284, -0.700368110989541, -0.6861392293600976, -0.6817082081081357, -0.6879977183169069, -0.705697021300587, -0.7352412853274929, -0.7767966509288526, -0.8302514574134859, -0.8952138961261934, -0.9710162017873988, -1.0567253357030117, -1.1511599575955418, -1.252913330132853, -1.3603816556728103, -1.4717972118582705, -1.5852655347655569, -1.6988057982447946, -1.8103934583717312, -1.9180041745419378, -2.0196579851158547, -2.113462706524301, -2.1976555406203953, -2.2706419154597657, -2.3310306486477246, -2.3776646083743156, -2.4096461531895117, -2.4263567548858305, -2.4274703465620076, -2.4129600866941776, -2.3830983862246464, -2.3384502054951, -2.2798597874152193, -2.2084311486904946, -2.1255027984583217, -2.032617289718552, -1.9314863301964909, -1.8239522828096062, -1.711946969227736, -1.5974487511212976, -1.4824389011302683, -1.368858288487434, -1.2585653923251476, -1.1532966193252896, -1.0546298424787015, -0.9639519958189556, -0.8824314581411429, -0.8109958394505817, -0.750315650174116, -0.7007941883234684, -0.6625638274080589, -0.6354887317159331, -0.6191738694631688, -0.6129800420920348, -0.6160445034101403, -0.6273066088435856, -0.645537816080072, -0.6693752566924046, -0.6973580164132942, -0.727965201538114, -0.7596548318800261, -0.7909025876306296, -0.8202394486313952, -0.8462872995764055, -0.8677916325928319, -0.883650557961713, -0.8929394323986868, -0.8949305297852068, -0.8891073085849277, -0.87517297011658, -0.8530531488454827, -0.8228927261931961, -0.7850469092644646, -0.7400668615868178, -0.6886803107965611, -0.6317676847348653, -0.5703344394772903, -0.5054803376156753, -0.4383665102864558, -0.37018119013344153, -0.30210503328757476, -0.23527695579734403, -0.1707613936001296, -0.10951785553221303, -0.05237357706344265, -4.640365548799258e-16], [0.0, 0.04473933418560056, 0.0839081719584963, 0.11749954519667308, 0.14570468893276076, 0.16890750530274243, 0.1876735707511887, 0.20273396830679663, 0.21496436258907017, 0.22535986050952067, 0.2350063121982369, 0.2450488016723509, 0.2566581527354587, 0.2709963306015859, 0.2891816523448687, 0.31225472861970993, 0.3411460448929843, 0.3766460529888243, 0.41937858396112476, 0.4697783126354179, 0.5280729045834678, 0.594270360271804, 0.6681519415377009, 0.7492709256161464, 0.8369572851582439, 0.9303282427126902, 1.028304498742342, 1.1296317871659824, 1.2329072752998635, 1.33661019938255, 1.4391360157800377, 1.5388332543102292, 1.6340421862916819, 1.723134367819262, 1.804552089770036, 1.8768467609467634, 1.9387152697820562, 1.9890334127638496, 2.0268855432235804, 2.0515896808074006, 2.06271742775502, 2.0601081604892784, 2.0438771010062546, 2.0144170188420105, 1.9723934674082808, 1.9187336144929263, 1.8546088818882196, 1.7814117596310548, 1.700727302512112, 1.6142999468324009, 1.523996400639074, 1.4317654580060895, 1.3395956649243634, 1.249471819111526, 1.1633313171683592, 1.0830213692009263, 1.0102580830956056, 0.9465883784846235, 0.8933556250705976, 0.8516698129597934, 0.8223829560849145, 0.8060703062596422, 0.8030178178953618, 0.8132161552649714, 0.8363613790197821, 0.8718622902257278, 0.9188542523365092, 0.9762191581007482, 1.042611063134827, 1.1164868743088756, 1.1961413624284094, 1.2797456678189438, 1.3653883867686114, 1.4511182682891128, 1.534987515709656, 1.6150946770326873, 1.6896261219690938, 1.7568951417439354, 1.8153777691403947, 1.8637444992790753, 1.9008871942327812, 1.9259405741969757, 1.938297831602045, 1.9376200489553743, 1.9238392527694905, 1.8971550909297041, 1.8580252754647923, 1.8071500831099598, 1.74545134860541, 1.6740465168721221, 1.5942184368522225, 1.5073816790652157, 1.4150462384197804, 1.318779541635822, 1.2201677134154947, 1.1207770664724397, 1.0221167674948368, 0.925603594486244, 0.832529641690445, 0.7440337480135544, 0.6610773255813278, 0.5844251493513642, 0.5146315394839811, 0.4520322287364905, 0.3967420610068499, 0.34865851799790576, 0.30747092255402597, 0.27267502326420223, 0.24359252903710854, 0.2193950379333135, 0.1991316946937943, 0.18175981886766016, 0.16617767251258053, 0.15125848492050575, 0.13588482297027157, 0.11898239021788144, 0.0995523558068075, 0.07670135522644903, 0.04966836780116334, 0.017847758938672093, -0.019192123521281586, -0.061695292622023085, -0.10970976952905843, -0.16308476013228754, -0.22147344183738457, -0.2843412946391313, -0.35097976544135057, -0.42052491475100406, -0.4919805638821064, -0.5642453419910043, -0.636142928656752, -0.7064547019658852, -0.7739539363599957, -0.8374406505545364, -0.8957761847895772, -0.947916589104978, -0.9929439302302175, -1.0300946734401633, -1.058784366173743, -1.0786279406177284, -1.0894550605936095, -1.0913200612739702, -1.0845061654353507, -1.0695238037610053, -1.0471030155491816, -1.0181800563385066, -0.9838784866675816, -0.9454851577314014, -0.9044216415177617, -0.8622117717730378, -0.8204460648472909, -0.7807438734852491, -0.744714189804518, -0.7139160543898952, -0.6898195455443383, -0.6737683157663223, -0.6669446115613686, -0.670337658428485, -0.6847162165558438, -0.7106060162286457, -0.7482726675149783, -0.7977105092194465, -0.8586377205266066, -0.9304978686464972, -1.0124679107902255, -1.1034725127395089, -1.202204392959003, -1.3071502544013691, -1.4166217294867054, -1.5287906405701772, -1.6417277715879428, -1.7534442591339203, -1.861934645141231, -1.9652205902755882, -2.061394228181432, -2.148660146355359, -2.225375009551055, -2.290083895541077, -2.3415524894861024, -2.3787943802505165, -2.401092817407988, -2.4080164186043356, -2.3994284602102027, -2.375489536321895, -2.336653528457584, -2.283656986923769, -2.2175021809371507, -2.139434224386149, -2.050912823966648, -1.953579322935265, -1.8492198238273743, -1.7397252645257943, -1.627049391848963, -1.5131656236868511, -1.400023813543445, -1.289507929632957, -1.1833956345103847, -1.0833207012835862, -0.9907391300239512, -0.9068997348858749, -0.832819860987568, -0.7692667630686837, -0.7167450384752072, -0.6754903585787536, -0.6454695889810074, -0.6263872335729835, -0.6176979845315597, -0.618625013396081, -0.6281835010727814, -0.6452087803149337, -0.6683883559444032, -0.696296978435212, -0.7274338776241698, -0.7602612168802447, -0.7932428051264906, -0.8248821051540122, -0.8537586015882832, -0.8785616399630128, -0.8981209183501824, -0.9114329030689667, -0.9176825478379858, -0.9162598185933128, -0.90677066094943, -0.889042190522206, -0.8631220344468303, -0.8292719016808044, -0.7879556063313069, -0.7398219086098027, -0.68568266857989, -0.6264869253646665, -0.5632916159872821, -0.4972297310087305, -0.42947676654470157, -0.36121637255196143, -0.2936061144955254, -0.22774425924349934, -0.1646384664802749, -0.10517721486040985, -0.05010471889032582, -4.422840629188771e-16], [0.0, 0.042381078013642756, 0.07924438062789622, 0.11068365232453298, 0.1369864078867461, 0.15862542891321957, 0.17624500080639707, 0.19064224712728037, 0.20274404707658022, 0.2135801384270025, 0.22425310952338154, 0.23590606739858155, 0.24968883248362053, 0.26672355218206106, 0.2880706446361315, 0.31469597981093933, 0.3474401776236241, 0.3869908528899496, 0.43385856556307667, 0.4883571438476994, 0.5505889395318146, 0.6204354519719587, 0.6975536226522835, 0.7813779594666935, 0.8711285024130119, 0.9658244939301845, 1.0643034713774777, 1.1652453598122279, 1.267201013781611, 1.3686245405764546, 1.4679086372521482, 1.563422092258709, 1.653548541834889, 1.7367255329932667, 1.8114829299854671, 1.8764797100405541, 1.9305382267759723, 1.972675075260986, 2.0021277699678772, 2.018376543936612, 2.0211606920694276, 2.010489010789751, 1.9866440272021177, 1.95017985994023, 1.9019137074452324, 1.842911113713081, 1.7744653128009629, 1.6980710978682918, 1.615393794688269, 1.5282340400900742, 1.438489169697724, 1.3481121040430453, 1.259068685536748, 1.1732944592957566, 1.0926519074168044, 1.0188891385140217, 0.9536010023554747, 0.8981935439888201, 0.8538526341632269, 0.8215175150005498, 0.8018598841088296, 0.7952690094697289, 0.8018432246445267, 0.8213880025988176, 0.8534206504201715, 0.8971815101886942, 0.9516513970746375, 1.0155748581267927, 1.08748869776533, 1.1657550920371518, 1.248598506233581, 1.3341455421051975, 1.420466773764094, 1.5056195870447941, 1.5876910166459695, 1.6648395792542539, 1.7353351289200107, 1.7975958124815044, 1.8502212765116761, 1.8920213712435365, 1.922039708871375, 1.9395715607454593, 1.9441757171276048, 1.9356800809148136, 1.9141809194235044, 1.880035852198512, 1.8338508040880492, 1.7764612977990573, 1.7089085952707668, 1.6324113191827276, 1.548333291783666, 1.4581484154307172, 1.3634034856738202, 1.265679871834853, 1.166555020799722, 1.0675647367296002, 0.9701671627612627, 0.8757093412486872, 0.7853971580085073, 0.7002693852133123, 0.6211764293595791, 0.5487642678789829, 0.48346392358017115, 0.4254866836008496, 0.37482512251039274, 0.33125984133123404, 0.2943716892555316, 0.26355909635629926, 0.23806001709335356, 0.2169778691021579, 0.1993107525003091, 0.18398315421681413, 0.1698792816399524, 0.15587713166884545, 0.14088238596573113, 0.12386123118714297, 0.10387123398401744, 0.08008945378540885, 0.0518370504420577, 0.018599736805056902, -0.01995646412376924, -0.06397457450036616, -0.11340141246911652, -0.16798788038104528, -0.22729478742218875, -0.2907040588647875, -0.3574350430539325, -0.42656549343691047, -0.4970566798339875, -0.5677819738719155, -0.6375581608432266, -0.7051786565863043, -0.7694477551986877, -0.8292150028700599, -0.8834087856641929, -0.9310682349238677, -0.9713725927663988, -1.0036672409496274, -1.027485677733982, -1.0425668272421502, -1.0488671817523965, -1.0465674064752526, -1.0360731754415091, -1.0180101527012793, -0.9932131814589509, -0.962709891328128, -0.9276990768788752, -0.8895243354678094, -0.8496435755869015, -0.8095951155184483, -0.7709611831791471, -0.7353296993428171, -0.7042552761035178, -0.6792203891673573, -0.6615976855983785, -0.6526143678348274, -0.6533195505719457, -0.6645554204929539, -0.6869329413954732, -0.720812741099881, -0.7662916942009224, -0.8231955792012555, -0.8910780431453382, -0.9692259551049419, -1.0566710754682829, -1.1522078147399297, -1.254416707234154, -1.3616930852903466, -1.472280311902505, -1.584306817091393, -1.6958260887457242, -1.8048586943682174, -1.9094353580381813, -2.0076400882579533, -2.097652347922895, -2.1777872775897626, -2.2465330270628154, -2.302584317032031, -2.3448714404827675, -2.3725840207286413, -2.3851889666062767, -2.3824422026127205, -2.3643938992313056, -2.3313870827967014, -2.2840496612484857, -2.2232800581983203, -2.1502267990949644, -2.066262536236837, -1.9729531304832097, -1.8720225235742802, -1.7653142331794924, -1.6547503807829211, -1.5422892184137027, -1.4298821527085015, -1.3194312730986995, -1.212748374887145, -1.1115164280544896, -1.0172543798356557, -0.9312860950143789, -0.8547141346014574, -0.7883989536596218, -0.7329439654897868, -0.6886867755045077, -0.6556967374376572, -0.6337788307880355, -0.6224837053504915, -0.621123590108172, -0.6287936232821507, -0.6443980313914068, -0.6666804709056908, -0.6942577492458292, -0.7256560648322065, -0.7593488504403352, -0.7937952715900755, -0.8274784227998147, -0.8589422794181238, -0.886826500951625, -0.9098982423101035, -0.9270802106063748, -0.937474304986212, -0.9403802928708299, -0.9353091050235135, -0.9219904707360096, -0.9003747596620142, -0.87062904474668, -0.8331275475946543, -0.7884367697996237, -0.7372957476658146, -0.6805919900394016, -0.6193337665860791, -0.5546195041228603, -0.4876051193000327, -0.4194701652903247, -0.35138369697167143, -0.28447076275033784, -0.21978041160853087, -0.1582560617046998, -0.10070901300602704, -0.04779580263408223, -4.2038483273725974e-16], [0.0, 0.040049294538061185, 0.07468049758121535, 0.10408500882074903, 0.1286419591632936, 0.14890687313738232, 0.1655953110749863, 0.17956191843022898, 0.1917754304968615, 0.20329028776729155, 0.21521560751023666, 0.22868232852021184, 0.2448093965744725, 0.26466988660805185, 0.2892579632266648, 0.3194575637365862, 0.3560136477758645, 0.3995067958483503, 0.45033185710350293, 0.5086812465925487, 0.5745333764462495, 0.6476465768399042, 0.727558724441963, 0.8135926517349893, 0.9048672637632355, 1.0003141431821552, 1.0986992836224092, 1.1986494588827743, 1.2986826146794566, 1.3972415636655662, 1.4927301758937892, 1.5835511880980513, 1.6681447078998233, 1.7450264645534135, 1.812824856820204, 1.8703158711103336, 1.9164549886728581, 1.9504052682984223, 1.9715608791195591, 1.979565464540311, 1.9743248405279894, 1.9560136664890004, 1.9250758714388883, 1.8822187686333625, 1.8284009445672376, 1.7648141595229379, 1.69285964294014, 1.6141193041843094, 1.5303225044256872, 1.443309145206986, 1.3549899211531566, 1.2673046558747012, 1.1821796896452998, 1.1014853136447869, 1.0269942477682354, 0.9603421371199223, 0.9029909968352049, 0.8561964668819062, 0.8209796496160136, 0.7981041952476401, 0.7880591766164278, 0.7910481577808077, 0.8069847142163876, 0.8354945094593001, 0.8759238775386042, 0.927354706297733, 0.9886252674576711, 1.0583564986499492, 1.1349831140597573, 1.2167888068857584, 1.301944711289132, 1.3885502161743635, 1.4746751698270915, 1.5584024843973883, 1.6378701431561669, 1.7113116314756893, 1.777093854109306, 1.8337516655098394, 1.8800182250172095, 1.9148504926409455, 1.937449301278889, 1.9472735745740322, 1.9440484029193306, 1.9277668398402843, 1.8986854334299705, 1.8573136589343064, 1.8043975652723507, 1.7408980866376345, 1.6679645969848365, 1.5869043970808354, 1.4991489181812852, 1.4062175010128992, 1.3096796618209954, 1.2111167875422986, 1.112084209012249, 1.0140745844249883, 0.9184834855278083, 0.8265780173162063, 0.7394692199108706, 0.6580889009563317, 0.583171430845509, 0.5152409042922176, 0.45460393350390504, 0.40134819393826454, 0.3553466969905782, 0.3162676186370703, 0.28358937269542595, 0.2566204854690345, 0.2345237084096264, 0.216343700056622, 0.20103752050884963, 0.18750711323335187, 0.17463290180112023, 0.1613076043095442, 0.14646936639103825, 0.1291333348237621, 0.10842083728285834, 0.08358539856542965, 0.054034908021605585, 0.019349354767222795, -0.020706336057227256, -0.06617470415229454, -0.11690359304985763, -0.17254948593509983, -0.23258625320591556, -0.29631908501699583, -0.3629032461379516, -0.4313671637316543, -0.5006392443541855, -0.5695777175035791, -0.6370027219291461, -0.7017297897361932, -0.762603843662283, -0.8185328058001343, -0.8685199219714468, -0.9116939348094072, -0.9473362897022639, -0.9749046298432374, -0.9940519279504989, -1.0046407105065913, -1.0067519529315017, -1.0006883578962114, -0.9869718706658802, -0.9663354313912508, -0.9397091109850015, -0.9082009209436996, -0.8730727245898434, -0.8357118042539352, -0.7975987526789028, -0.7602724545191768, -0.725293002730676, -0.6942034528727383, -0.6684913543460614, -0.6495510103989931, -0.6386474079495496, -0.6368827240792764, -0.6451662592261372, -0.6641885689688675, -0.6944004687178922, -0.7359974709569201, -0.7889100856920631, -0.8528002745990116, -0.9270642014339344, -1.0108412692092479, -1.103029282159649, -1.2023054213824442, -1.3071525809003373, -1.415890479268105, -1.5267108439797572, -1.6377158647479015, -1.7469590297351443, -1.8524873980632761, -1.9523843239354521, -2.0448116334491147, -2.128050265039359, -2.2005384182711922, -2.260906312603427, -2.3080067364187316, -2.340940665160935, -2.359077343461109, -2.3620683568575096, -2.3498553609495856, -2.3226712861184846, -2.281034990643654, -2.2257394903864465, -2.157834045421196, -2.0786005293729097, -1.9895246422377593, -1.8922626488421053, -1.7886044298974304, -1.6804337182997804, -1.5696864578393923, -1.4583082632875686, -1.3482119789276796, -1.2412363265929982, -1.1391066043540308, -1.0433983439366512, -0.9555047600907145, -0.8766087303405997, -0.8076599311956819, -0.7493576297671538, -0.7021394909749737, -0.6661766135619028, -0.6413748565830603, -0.6273823656375557, -0.6236030585956089, -0.6292156876137044, -0.6431979613155975, -0.6643550913875498, -0.6913520243956234, -0.7227485348788042, -0.7570362917335597, -0.7926769680962322, -0.8281404463074119, -0.8619421744893452, -0.8926787595798156, -0.9190609325602938, -0.9399430937507958, -0.9543487375510022, -0.961491164542122, -0.9607890116631789, -0.9518762651252237, -0.9346065624438137, -0.9090517358823823, -0.8754946960386355, -0.834416897598602, -0.786480765839845, -0.7325075888737468, -0.673451493723352, -0.6103702213243009, -0.5443934940058944, -0.47668982702034207, -0.4084326718198197, -0.34076679216347927, -0.27477576447320085, -0.21145146143059923, -0.15166632347326867, -0.09614914801098084, -0.045465032762774325, -3.985078954610722e-16], [0.0, 0.03776113089419496, 0.07024901025820812, 0.09774879032879372, 0.12072579551420239, 0.1398115077887247, 0.15578481023370214, 0.16954898138173594, 0.18210504505606034, 0.1945221770531845, 0.20790594882588598, 0.22336524726535023, 0.24197874723432705, 0.2647618286834462, 0.29263482256835427, 0.32639343952726246, 0.3666821830979016, 0.4139714764230387, 0.46853913970883837, 0.5304567474311053, 0.5995812721218277, 0.675552288556475, 0.7577948716233527, 0.8455281766065156, 0.9377795456776213, 1.0334038427106986, 1.131107583674236, 1.2294773052215087, 1.327011502848415, 1.4221553749473457, 1.513337532685824, 1.599007779851687, 1.6776750330939687, 1.7479444422667962, 1.8085527831982944, 1.8584012309246218, 1.896584679443087, 1.9224168529849401, 1.9354505518027696, 1.9354924901479673, 1.9226123127006696, 1.8971455150778391, 1.8596901407816202, 1.8110972774673497, 1.7524555260155046, 1.6850697628820683, 1.6104346559568183, 1.5302035232300708, 1.4461532387641802, 1.3601459889304788, 1.2740887611575051, 1.1898915055612118, 1.1094249453290899, 1.0344790236980028, 0.9667229634667748, 0.9076678794715213, 0.8586328261557001, 0.8207150826794427, 0.7947653788498397, 0.781368648911242, 0.7808307697269022, 0.7931715982763874, 0.8181244741258379, 0.8551421992275422, 0.903409353797835, 0.9618606568422365, 1.0292049367936411, 1.1039541451794426, 1.1844567274529358, 1.2689345629913822, 1.3555226032466194, 1.4423102751331207, 1.527383677433906, 1.6088675822217793, 1.684966261381598, 1.754002190040665, 1.8144517332541399, 1.8649769982751396, 1.9044531302669712, 1.9319904420117597, 1.946950895242315, 1.9489585895304073, 1.9379040607917208, 1.9139423418170722, 1.877484888114394, 1.829185620045051, 1.7699214731444632, 1.7007679791897783, 1.6229705178341438, 1.5379119796246612, 1.4470776635228682, 1.3520182936845864, 1.2543120797768494, 1.1555267616118248, 1.0571825720307773, 0.9607170220256621, 0.8674523598638236, 0.7785664828562814, 0.6950679882723868, 0.6177759411111201, 0.547304813760435, 0.4840549191174382, 0.42820851787386227, 0.3797316359397902, 0.33838148302005155, 0.3037192218065652, 0.2751277026478511, 0.25183365426552873, 0.23293371020386028, 0.21742355597810656, 0.20422940567672404, 0.19224096094937018, 0.18034497124103996, 0.16745850262817433, 0.15256103392301096, 0.13472453251193825, 0.11314071779116135, 0.08714479562528893, 0.05623504104191317, 0.020087715991171824, -0.021433068350340923, -0.06827080268767677, -0.1201774629752808, -0.1767198027720133, -0.2372908897886119, -0.3011265845015277, -0.3673265290555437, -0.4348790960016315, -0.5026896417367658, -0.5696113214980365, -0.6344776536658557, -0.696135972726421, -0.7534808837887564, -0.8054868277519814, -0.851238885209613, -0.8899609885225314, -0.9210407741902742, -0.9440503901631612, -0.9587626730266487, -0.9651622255656312, -0.9634510532037527, -0.9540485550181106, -0.9375858080228768, -0.9148942286150153, -0.886988838836869, -0.8550465038191957, -0.8203796369269312, -0.7844059874488762, -0.7486152291493351, -0.7145331539968173, -0.6836843416944739, -0.6575542205364043, -0.6375514574110912, -0.6249716138342604, -0.6209629806623644, -0.6264954571360613, -0.6423332712194703, -0.6690122494644075, -0.7068222379691108, -0.7557951539966956, -0.8156990134339023, -0.8860381357820932, -0.9660595792887942, -1.0547657078032457, -1.150932641682659, -1.253134201259981, -1.3597708165547622, -1.469102754396054, -1.5792869069639544, -1.6884162966041738, -1.7945613828492255, -1.8958122106187383, -1.9903204147591207, -2.0763400960441873, -2.1522666075326886, -2.216672337223664, -2.2683386421505936, -2.3062831787517992, -2.329781982385309, -2.3383857726076474, -2.3319300973088493, -2.310539074677439, -2.2746226437155515, -2.2248673879475724, -2.1622211493238, -2.0878717964103153, -2.0032206492037883, -1.9098511889584082, -1.8094937922055023, -1.7039873210021617, -1.5952384741233383, -1.4851798546662884, -1.3757277371605816, -1.2687405211321836, -1.165978838099588, -1.069068235712698, -0.9794652972790014, -0.8984279688984794, -0.8269907619925886, -0.7659453787557863, -0.7158271749578473, -0.6769077318686612, -0.649193660381699, -0.6324316093362582, -0.6261193002926742, -0.6295222662694089, -0.6416958357460564, -0.6615117788937187, -0.6876889235361052, -0.7188269564190828, -0.7534425531822064, -0.7900069296990402, -0.8269838793647386, -0.8628673560771514, -0.8962176811217416, -0.9256954933928218, -0.9500926252625206, -0.9683591693074742, -0.9796261018907629, -0.9832229457015197, -0.9786900818306123, -0.9657854595588912, -0.944485595285855, -0.9149808973285366, -0.8776654970261006, -0.8331219050962129, -0.7821009420416638, -0.7254975093612387, -0.6643228714413997, -0.5996742037364311, -0.5327022290653548, -0.4645778089383436, -0.3964583796804285, -0.32945512321257603, -0.26460173971895773, -0.20282564468498407, -0.1449223470990012, -0.09153368066347725, -0.043130457834020294, -3.768186435540968e-16], [0.0, 0.03553295222891896, 0.06598043276517529, 0.0917166508105038, 0.11328700836186595, 0.1313915875256206, 0.1468642100782241, 0.16064762154271614, 0.17376545442499058, 0.187291710953867, 0.20231857250309465, 0.21992338912420822, 0.2411357270862674, 0.2669053543489913, 0.2980720234008834, 0.3353378683515862, 0.37924316961115473, 0.4301461564812571, 0.4882074175787871, 0.5533793737055132, 0.625401140441158, 0.7037989715512366, 0.7878923326728099, 0.876805511221062, 0.9694845266520535, 1.0647189686910397, 1.1611682633354832, 1.2573917506007122, 1.3518818570352682, 1.443099562568492, 1.529511297409788, 1.6096263621589608, 1.6820339441440073, 1.7454388058563346, 1.7986947472115067, 1.8408349916629787, 1.8710987158144288, 1.8889530314593743, 1.8941098357792465, 1.886537067168619, 1.8664640378688044, 1.834380657015895, 1.7910305053612965, 1.7373978721805061, 1.6746890120806632, 1.604308020924569, 1.5278278624169521, 1.4469571967759323, 1.3635037673686021, 1.2793351876275836, 1.19633803682892, 1.1163762177358656, 1.0412495505683084, 0.9726535756761825, 0.9121415116870177, 0.8610892673499247, 0.8206643349609095, 0.7917993028136439, 0.7751706157549635, 0.7711830892566556, 0.7799605464412286, 0.8013428025195424, 0.8348890706340466, 0.8798877108099727, 0.9353720933002035, 1.0001422027243612, 1.0727914735692519, 1.15173822413507, 1.2352609478743186, 1.3215366308967114, 1.40868119438017, 1.4947911124177082, 1.5779852305894795, 1.6564458088608875, 1.7284578342777925, 1.792445693785331, 1.8470063642040817, 1.8909383632860173, 1.9232658106815055, 1.94325706797602, 1.9504375597255994, 1.9445965193569714, 1.9257875514052363, 1.8943230512100395, 1.850762671207073, 1.7958961657103358, 1.730721080092734, 1.6564158722725622, 1.5743091614379972, 1.4858458884044137, 1.3925512417522605, 1.2959932522814335, 1.197744984217734, 1.099347254454746, 1.0022727909179565, 0.9078926984774811, 0.8174460368466211, 0.7320132312484083, 0.6524939354591752, 0.5795898507247793, 0.5137928759366052, 0.45537882758671355, 0.40440682584311755, 0.36072429916977616, 0.32397741787058226, 0.29362663031742336, 0.26896684784132796, 0.24915170850760032, 0.2332212491384674, 0.220132231489662, 0.2087903044898152, 0.19808314148143952, 0.18691367049763563, 0.1742325172519435, 0.1590688046254712, 0.1405584983566251, 0.11796955517769912, 0.09072321508513162, 0.05841088158801125, 0.02080615004505253, -0.022128328387403348, -0.07023932435489666, -0.12318688682330303, -0.18045347518218505, -0.24135812554782035, -0.3050752779895686, -0.37065776902307845, -0.43706338395674754, -0.503184269339129, -0.567878429242484, -0.6300024723921949, -0.6884447416765123, -0.7421579442758794, -0.7901904099079422, -0.8317151362980055, -0.8660558341974389, -0.8927092577819822, -0.9113631982538876, -0.9219096266648298, -0.924452593678387, -0.9193106261659916, -0.9070134998745768, -0.8882934104279191, -0.8640707080385007, -0.8354345009140518, -0.8036185649259087, -0.7699731193150023, -0.7359331369493363, -0.7029839501463483, -0.6726249869668023, -0.6463325262645551, -0.6255223912360295, -0.6115135098954515, -0.6054932565115666, -0.608485450857594, -0.6213218329935484, -0.6446177516114581, -0.6787527056347853, -0.7238562641457672, -0.7797997615992048, -0.8461940267894601, -0.9223932585532882, -1.0075050122791918, -1.1004061126104099, -1.1997641629314064, -1.30406418488605, -1.4116397946818278, -1.5207082104187504, -1.6294082889369896, -1.735840714087252, -1.8381094028090654, -1.9343631623568147, -2.0228366222918073, -2.1018894787418807, -2.1700431256175987, -2.226013807095634, -2.268741506312406, -2.2974138849158576, -2.3114847044931324, -2.310686291108641, -2.2950357450930006, -2.2648347463966654, -2.220662957662678, -2.1633651789896864, -2.0940325564586706, -2.01397828728492, -1.9247083945108538, -1.827888260318348, -1.7253057064968034, -1.6188314909493615, -1.5103781484199648, -1.4018581404585502, -1.295142293143661, -1.1920194909562023, -1.0941585617284906, -1.003073231636149, -0.9200909521625348, -0.8463263047680698, -0.7826595760293159, -0.7297209690716907, -0.6878807793416155, -0.6572457175449796, -0.637661413493546, -0.6287209853112378, -0.6297794126188725, -0.6399733135070198, -0.6582455967100631, -0.683374345534356, -0.7140051915530639, -0.7486863562342368, -0.7859054794241528, -0.8241273163586588, -0.8618313704672123, -0.8975485379460862, -0.9298958716139354, -0.9576086250639632, -0.9795688121887105, -0.9948296098647964, -1.0026350405755198, -1.0024344942486254, -0.9938917814949262, -0.9768885503977484, -0.9515220425019174, -0.9180973070821088, -0.8771141325403478, -0.8292490863973029, -0.7753331774924346, -0.7163257626538597, -0.6532854125424831, -0.5873385253303481, -0.5196465305207936, -0.4513725572510576, -0.3836484510738673, -0.3175430102936433, -0.25403227780322146, -0.1939726679543633, -0.138077631759576, -0.08689846962156005, -0.04080979122537535, -3.554772193663964e-16], [0.0, 0.033380188098396116, 0.06190302700405919, 0.0860263540098695, 0.10636891126999953, 0.12369153367612479, 0.1388742551755002, 0.15288993928827882, 0.16677513160508511, 0.18159890627325379, 0.19843053301023125, 0.21830682460928838, 0.24220003635016982, 0.2709871778725202, 0.3054215651508984, 0.3461073860204675, 0.39347797857170413, 0.447778429493592, 0.5090529913885314, 0.5771376969002969, 0.6516584162145277, 0.7320344663938957, 0.817487739558545, 0.9070571756685938, 0.9996182681631826, 1.0939071604269799, 1.1885487712835452, 1.2820882814934405, 1.3730252232689397, 1.4598493434124151, 1.5410773596896268, 1.6152897008052092, 1.6811663136597121, 1.7375206376799843, 1.7833308846051863, 1.8177678222974385, 1.8402183415088254, 1.8503041831508356, 1.8478953180970394, 1.833117599124889, 1.8063544421577478, 1.7682424381395647, 1.7196609441273933, 1.661715848902721, 1.5957178509694754, 1.523155721707005, 1.4456651503462268, 1.3649938772663912, 1.2829639151402126, 1.201431731366869, 1.122247318172224, 1.0472131073840163, 0.9780436944118972, 0.9163273201517719, 0.8634900207350091, 0.82076329416624, 0.789156051390237, 0.7694315191583175, 0.762089645646189, 0.7673554299264079, 0.7851734562688456, 0.8152087672338717, 0.85685405920769, 0.9092430340611927, 0.9712695946389246, 1.0416124333515788, 1.1187644356173452, 1.2010662063701554, 1.2867429310788414, 1.373943705040747, 1.4607824079993035, 1.5453791667443058, 1.6259014370964284, 1.7006037487961483, 1.7678651919812192, 1.8262237812513096, 1.874406911346331, 1.911357215263607, 1.936253248806988, 1.9485245522999006, 1.947860777375356, 1.9342147110004717, 1.907799176653364, 1.869077940219344, 1.8187508920933257, 1.757733913647283, 1.6871339623119326, 1.60822002196511, 1.522390661392505, 1.4311390209771278, 1.3360161046356738, 1.2385932890181908, 1.1404249743313621, 1.0430122906069836, 0.9477687401550268, 0.8559886022123083, 0.7688188508555901, 0.6872352440227343, 0.6120231323583857, 0.5437634143421438, 0.4828239318592546, 0.42935646137087213, 0.3832993136276469, 0.34438541301413145, 0.31215558966279044, 0.2859766868816955, 0.26506396645430685, 0.24850718797714233, 0.23529964823956437, 0.22436939494625377, 0.21461177759772482, 0.20492246832810512, 0.19423007766239006, 0.18152750464977946, 0.16590119724646493, 0.14655755620107905, 0.12284579255346531, 0.09427664321858757, 0.06053645857969406, 0.021496297767545088, -0.022784201743041625, -0.07205827676068187, -0.1258987705455795, -0.18370996374788268, -0.2447441899023239, -0.3081227958543559, -0.3728608933015575, -0.4378952475671713, -0.5021145663303921, -0.5643913864516457, -0.6236147129096253, -0.6787225413545772, -0.7287333954807945, -0.7727760323731688, -0.8101165126704617, -0.8401818967470416, -0.8625799115587771, -0.8771140332594293, -0.8837935456722474, -0.8828382613298209, -0.8746777269087955, -0.859944875101085, -0.8394642267625043, -0.8142348869990049, -0.7854087131684893, -0.7542641582016821, -0.7221764060030826, -0.6905845141019777, -0.6609563596699587, -0.6347522464226801, -0.6133880701786995, -0.59819895888048, -0.5904042981659982, -0.5910750261528511, -0.6011040315641124, -0.6211804188409477, -0.6517683141286937, -0.6930907791500133, -0.7451192785795017, -0.8075690135630749, -0.8799002927295478, -0.961325965881207, -1.05082479811249, -1.1471605170175154, -1.2489061264839205, -1.354472950768632, -1.4621437553234669, -1.5701091890920265, -1.6765067092670927, -1.7794610858720397, -1.8771255416123123, -1.9677225633042852, -2.0495834253408636, -2.121185493037615, -2.1811864236897143, -2.2284544545750764, -2.2620940582512206, -2.28146635411718, -2.2862037887207594, -2.2762187326927763, -2.2517057861977854, -2.2131377339071423, -2.161255241101003, -2.0970505309297582, -2.021745425503955, -1.936764266868753, -1.8437023548145037, -1.7442906439461865, -1.640357529926875, -1.533788622211105, -1.4264854462734056, -1.3203240412275894, -1.2171144182971871, -1.1185618218796718, -1.0262306885621488, -0.941512131563391, -0.8655956903917854, -0.7994459801996577, -0.7437847549892557, -0.6990787664580193, -0.6655336591235285, -0.6430939959162623, -0.6314493602692999, -0.6300463345020736, -0.6381060135696421, -0.654646581466595, -0.6785103579450374, -0.7083946186322182, -0.7428854046408804, -0.7804934704399139, -0.8196914726900953, -0.8589514790149585, -0.8967818747819916, -0.9317627678578055, -0.9625790353529863, -0.9880502214194186, -1.0071565795176074, -1.0190606540718365, -1.0231239124922666, -1.0189180662252113, -1.0062308555727197, -0.9850662140742992, -0.9556388707259014, -0.9183635886534297, -0.873839373550849, -0.8228291108753167, -0.7662352043341423, -0.7050718867813021, -0.6404349558244138, -0.5734697482269153, -0.5053382080641601, -0.437185922573049, -0.37010999629025115, -0.3051286085327034, -0.24315305222236056, -0.18496298472153205, -0.13118553546043904, -0.0822788129052435, -0.03852023744265374, -3.3463697705270556e-16], [0.0, 0.03131719043329137, 0.058042550565802424, 0.08071144980067183, 0.10000868852183063, 0.11674760259132393, 0.13184546069581263, 0.1462958072887311, 0.16113848496715658, 0.17742813247826797, 0.1962019965686942, 0.21844791648172138, 0.24507333852166224, 0.2768761947440166, 0.3145184350499024, 0.35850293685881296, 0.4091544327129204, 0.46660499570964264, 0.5307845080688659, 0.6014164122779938, 0.6780189102704849, 0.7599116373397453, 0.8462276974537392, 0.9359308088387618, 1.0278371766165035, 1.1206415862437435, 1.2129471006362396, 1.3032976479772207, 1.3902127087678486, 1.4722232516932863, 1.5479080298938863, 1.6159293332666327, 1.675067298951071, 1.7242519110915817, 1.7625918716709974, 1.78939959549416, 1.8042116725645876, 1.8068042479713828, 1.7972028903956803, 1.7756866525095576, 1.7427861666454907, 1.6992757637276767, 1.6461597490255837, 1.5846531112318083, 1.5161570781549623, 1.4422300595733162, 1.3645546323641378, 1.284901322062008, 1.2050900160390858, 1.1269499045125873, 1.0522788850302425, 0.9828033829515972, 0.9201395342738907, 0.8657566480526866, 0.8209438143098189, 0.7867804509215672, 0.7641114912728535, 0.7535278056582223, 0.7553523261379295, 0.7696322098044627, 0.796137232451187, 0.834364456933167, 0.8835490716604847, 0.9426811482855008, 1.010527927296555, 1.0856611093230257, 1.1664885116705352, 1.2512893468111803, 1.338252294741826, 1.4255154763437439, 1.5112073916857454, 1.5934878666395147, 1.6705880536924962, 1.740848558358328, 1.8027548104411006, 1.8549688684047594, 1.896356933513295, 1.9260119560467461, 1.9432708361498805, 1.9477258537657882, 1.9392301023968932, 1.91789684667011, 1.8840928702956061, 1.8384260254062161, 1.7817273329148773, 1.7150281130467278, 1.63953274243837, 1.5565877363065364, 1.4676479387079886, 1.374240668817727, 1.2779287149079417, 1.180273089306438, 1.0827964565916488, 0.9869481237440534, 0.894071435580231, 0.805374352746501, 0.7219039045531855, 0.6445251071650241, 0.573904821715719, 0.5105008997201455, 0.45455682792466673, 0.4061019448653877, 0.3649571604059448, 0.3307459709304021, 0.3029104301360567, 0.28073161181470646, 0.2633539897025896, 0.24981306317992458, 0.23906547869126338, 0.23002083717823094, 0.22157433901966508, 0.21263940089000544, 0.20217938395820392, 0.18923759978426172, 0.17296480840621287, 0.1526434911922831, 0.1277082673065077, 0.09776192489058542, 0.06258665368951213, 0.02215019189813573, -0.023393266725840814, -0.07370742233583918, -0.12828335445874547, -0.18645388853323666, -0.2474124608463046, -0.3102359812180649, -0.3739110876045443, -0.4373630970765344, -0.49948688567791305, -0.5591788773108312, -0.6153692903873071, -0.6670537813494305, -0.7133236365687174, -0.7533936983094353, -0.7866272655528564, -0.8125572851739027, -0.8309032413882425, -0.8415832592483592, -0.8447210585714199, -0.8406475250160496, -0.829896801825637, -0.8131969455911991, -0.7914553287430837, -0.7657391068494304, -0.7372511967644962, -0.7073023289944103, -0.6772798413537736, -0.6486139684299355, -0.622742450309178, -0.6010743326641943, -0.5849538573707969, -0.5756253475643038, -0.5741999732674533, -0.5816252437870347, -0.598658011902456, -0.6258416939028155, -0.6634883107112464, -0.7116658410550621, -0.7701912506750244, -0.8386294250148129, -0.9162980900345427, -1.0022786602535438, -1.0954328084263518, -1.1944244109578337, -1.2977463907317381, -1.403751857738922, -1.5106888407548955, -1.6167378129953094, -1.720051143428895, -1.8187935550386687, -1.911182643074413, -1.995528500969086, -2.0702715192749426, -2.1340174633226314, -2.1855689973709014, -2.223952905316489, -2.2484423585942195, -2.2585736982895916, -2.2541573278923415, -2.2352824524018313, -2.2023155452718894, -2.1558925734117733, -2.096905158525562, -2.0264809968746293, -1.9459589955906518, -1.8568597086440348, -1.760851766450002, -1.6597150871831974, -1.5553017328945513, -1.4494953276726044, -1.3441699870688155, -1.2411497170592634, -1.1421692267531136, -1.0488370622567977, -0.962601910494292, -0.8847228428340242, -0.8162441710450666, -0.7579754748096722, -0.7104772335559478, -0.6740523588614976, -0.6487437804767745, -0.6343380926444239, -0.6303751214389265, -0.6361631318932642, -0.6507992591846865, -0.6731946243982752, -0.7021034853815225, -0.7361556796072818, -0.773891541027025, -0.8137984184068242, -0.8543478898710277, -0.8940327580693543, -0.9314029227110242, -0.9650992617921359, -0.9938847087473024, -1.0166717885235386, -1.0325459692547603, -1.040784295419075, -1.0408688903181873, -1.0324950473474561, -1.0155737675113619, -0.9902287415159744, -0.9567879150066543, -0.9157699116081583, -0.8678657169689635, -0.8139161448106492, -0.7548857101100611, -0.6918336224181503, -0.6258826817773537, -0.5581869090373586, -0.48989877039206675, -0.42213686201038464, -0.35595490460437373, -0.2923128601190195, -0.23205092443021036, -0.17586707251101247, -0.12429873795958164, -0.07770909949365003, -0.036278325793204794, -3.144430334616951e-16], [0.0, 0.029357104468849406, 0.054422033809318565, 0.0758009984268642, 0.09423711191783193, 0.11058764322673498, 0.12579796018196346, 0.1408728573424789, 0.15684603078394335, 0.1747485126573812, 0.195576907773947, 0.22026228233548625, 0.24964054101439903, 0.28442509320819864, 0.32518255331507284, 0.372312144677102, 0.4260293842831992, 0.4863545177189715, 0.5531060538817383, 0.6258996196470361, 0.704152219219115, 0.7870918447225772, 0.8737722471701201, 0.9630925437347083, 1.05382121162689, 1.1446239040098114, 1.234094422193659, 1.3207880934195715, 1.4032567370519118, 1.4800843556726349, 1.5499226626385865, 1.6115255548175504, 1.6637816586084913, 1.7057441185694993, 1.7366568600728363, 1.7559766389089664, 1.7633902897133071, 1.758826699096321, 1.742463155646063, 1.7147258644585357, 1.6762845552166754, 1.6280412566124098, 1.5711134525497408, 1.5068119735629086, 1.4366141068223022, 1.3621325267642763, 1.2850807528235282, 1.2072359283674197, 1.1303997835395716, 1.0563586925884174, 0.9868437621659604, 0.9234918903512331, 0.8678087166563129, 0.8211343414429941, 0.7846126299974407, 0.7591648334852245, 0.7454681581353708, 0.7439397977141805, 0.7547268154622648, 0.7777021233067892, 0.8124666616846995, 0.8583577362324047, 0.9144633214888891, 0.9796420001753813, 1.052548072998295, 1.131661251520895, 1.215320238435936, 1.3017594081716954, 1.389147728389544, 1.4756290113292905, 1.5593625543645013, 1.6385632222416922, 1.7115400394341316, 1.7767323994240363, 1.8327430575674963, 1.8783671540011357, 1.9126166108375995, 1.9347393612484456, 1.9442329941507195, 1.9408525339892786, 1.9246122172022295, 1.8957812718815727, 1.8548738513430445, 1.802633412269194, 1.7400119603706108, 1.6681447078998255, 1.588320794903386, 1.5019508172098672, 1.4105319766358588, 1.3156117210236487, 1.2187507722851605, 1.1214864489344687, 1.0252971755155869, 0.9315690352974373, 0.8415651655808493, 0.7563987184290036, 0.6770100155582223, 0.6041484169080931, 0.5383593008159752, 0.47997642282054664, 0.42911978320633803, 0.38569899391251017, 0.34942199685808445, 0.319808851545038, 0.2962101833367169, 0.27782976821840316, 0.2637506279981153, 0.2529639243181158, 0.2443998726288808, 0.23695985007115422, 0.2295488451577575, 0.22110739285216666, 0.2106421561658516, 0.1972543542532979, 0.18016529614976717, 0.15873835724004184, 0.13249683026433662, 0.10113719173765681, 0.06453744529976344, 0.02276033265382959, -0.023948662889954186, -0.07516845908658028, -0.13031446795404816, -0.18865531436181354, -0.24933373378238946, -0.311391093314184, -0.3737948846351981, -0.435468458745353, -0.495322212211903, -0.5522853946903052, -0.6053376887871212, -0.6535397163624413, -0.696061650090797, -0.7322091549190693, -0.7614459498532318, -0.7834123646449913, -0.7979393663426955, -0.8050576448152045, -0.805001471400009, -0.7982071776371064, -0.7853062382967239, -0.7671130811436618, -0.7446078816243482, -0.7189147304911421, -0.6912756830095622, -0.6630213067693349, -0.6355384384808878, -0.6102359360961219, -0.5885092691861702, -0.5717048262590045, -0.5610848316420962, -0.5577937562671893, -0.5628270763056771, -0.577003181794527, -0.6009391653787428, -0.6350311307964424, -0.6794395539293054, -0.7340801087261976, -0.7986202390189341, -0.8724816183975044, -0.9548484973030085, -1.0446817928455134, -1.1407386360997083, -1.2415969572485568, -1.3456845642574258, -1.4513120588605424, -1.5567088373099096, -1.6600613449767767, -1.7595526954735636, -1.8534027279561918, -1.939907561627458, -2.017477714595715, -2.0846738849956608, -2.1402395449404468, -2.183129571197485, -2.212534228708715, -2.2278979319870253, -2.2289323323818317, -2.215623413239044, -2.188232416831492, -2.1472905731597978, -2.0935877477664113, -2.02815526999155, -1.9522433411207758, -1.8672935502740104, -1.7749071415451736, -1.6768097760126364, -1.5748136143769704, -1.4707776081584831, -1.3665669281070134, -1.2640124767709942, -1.1648714276215313, -1.0707897058708051, -0.9832672768584471, -0.9036270378394049, -0.83298801993467, -0.7722435011096459, -0.7220445109400355, -0.682789076574317, -0.6546174199380843, -0.6374131722740398, -0.6308105271039999, -0.6342071101877645, -0.6467822085219567, -0.6675198731998625, -0.695236296135311, -0.7286107610217935, -0.7662193868546331, -0.806570819851755, -0.8481429881435738, -0.8894200141177571, -0.9289283822074831, -0.9652714850549866, -0.9971617176674595, -1.0234493561800089, -1.043147543418652, -1.0554528054273422, -1.0597606388959744, -1.0556758360734368, -1.0430173480793854, -1.0218176261646645, -0.9923165199373306, -0.9549499483801248, -0.9103336902206252, -0.8592427616206403, -0.8025869582097614, -0.7413832324969301, -0.676725654332933, -0.6097537594841408, -0.5416201281178099, -0.47345805021566895, -0.406350128290711, -0.3412986394965149, -0.2791984300466248, -0.22081304608500207, -0.16675471854037363, -0.11746871727652969, -0.07322247462777849, -0.034099753119032745, -2.95030922528004e-16], [0.0, 0.027511753887494262, 0.05106158821570343, 0.07131934510739277, 0.08907832814857267, 0.1052309456719284, 0.12074146381798634, 0.13661659545824378, 0.15387470901486913, 0.17351447910535964, 0.1964838177967366, 0.22364992062082156, 0.2557712354690887, 0.2934721156807031, 0.3372208522123738, 0.38731169538035826, 0.44385137639442496, 0.5067505252637428, 0.5757202574882976, 0.6502740703680502, 0.7297350540685485, 0.8132482861878589, 0.8997981449109433, 0.9882301482873986, 1.0772768089535456, 1.1655868877399926, 1.2517573387578809, 1.3343671650682571, 1.4120123498074193, 1.4833409940882711, 1.5470877810323442, 1.6021068952817195, 1.64740255912078, 1.6821563991879482, 1.7057509304349252, 1.7177885347572488, 1.7181054183838458, 1.7067801520835848, 1.6841365285967738, 1.650740609238337, 1.6073919729713733, 1.5551093229374016, 1.4951107439598612, 1.4287890364877032, 1.3576826745498363, 1.2834430445179092, 1.207798715106512, 1.1325175647368488, 1.059367648250876, 0.9900777195713809, 0.9262983393632422, 0.8695644867099847, 0.8212605614765344, 0.7825886101324712, 0.7545405336368874, 0.7378749433137044, 0.7330992217068815, 0.7404572228319474, 0.7599229130032529, 0.7912001127484587, 0.8337283556400501, 0.8866947346952526, 0.949051464851058, 1.0195387543674124, 1.09671245214769, 1.1789758249506184, 1.264614721046316, 1.351835297403146, 1.4388034279039537, 1.5236848718138654, 1.6046852656700372, 1.6800890083028976, 1.7482961376429125, 1.8078563485814176, 1.8574993721735642, 1.896161026132082, 1.923004352643493, 1.9374353794252028, 1.9391131706783864, 1.927953972962708, 1.9041294036259073, 1.8680587727680382, 1.8203957702975067, 1.762009884009836, 1.6939630395148366, 1.6174820652180224, 1.533927682706228, 1.4447608024556446, 1.3515069648707942, 1.2557198058589567, 1.1589444435483442, 1.0626816780131363, 0.9683538691660887, 0.8772733100547019, 0.7906138449088889, 0.7093863951876852, 0.6344189547588107, 0.5663414998091112, 0.5055761330454195, 0.4523326483775094, 0.4066095649269388, 0.3682005413180572, 0.3367059462270856, 0.3115492324588115, 0.29199764259101524, 0.277186667434416, 0.2661475868436308, 0.2578373480434037, 0.25116998142678953, 0.24504871907752077, 0.23839796789073467, 0.2301942974018027, 0.21949563202646782, 0.20546788757550183, 0.18740836132639607, 0.164765271823806, 0.1371529467126559, 0.10436227167491655, 0.06636613801938104, 0.02331975749722336, -0.024444152844127827, -0.0764251789083494, -0.1319697435844504, -0.19028997570414538, -0.25048640955020546, -0.31157390995932727, -0.37251013296078006, -0.4322257644403004, -0.48965573124184136, -0.5437705516548824, -0.5936069861008297, -0.63829716421021, -0.6770954010132464, -0.7094019717572649, -0.7347831905114692, -0.7529872303433996, -0.7639552301424343, -0.767827352442916, -0.7649435848764163, -0.7558392119419685, -0.741235020257106, -0.722022435906564, -0.6992439235248565, -0.6740691000228035, -0.6477671282735321, -0.6216760547532239, -0.5971698375659252, -0.5756238753508398, -0.5583798916093264, -0.5467110518289557, -0.5417881917802324, -0.5446480144185144, -0.5561640703856613, -0.5770212741555055, -0.6076946258991445, -0.648432710131165, -0.6992464285348813, -0.759903298820927, -0.8299275171173194, -0.9086058415140891, -0.9949992124285296, -1.087959884914545, -1.1861537123798545, -1.2880870937529119, -1.3921379801156886, -1.496590235072148, -1.59967055819263, -1.6995871148873014, -1.7945689706827226, -1.8829054042635998, -1.9629841724235266, -2.0333278213207535, -2.09262718168268, -2.1397712498302996, -2.1738727400687052, -2.1942886951018754, -2.2006356572386596, -2.1927990314519707, -2.1709364087239127, -2.1354747612204332, -2.0871015662123393, -2.02675005976049, -1.955578960506983, -1.874947135072949, -1.786383796367904, -1.6915549316553202, -1.5922267459324224, -1.4902269759206777, -1.3874049790436935, -1.2855915290142863, -1.1865592544210317, -1.0919846389051866, -1.0034124616148148, -0.9222234956162266, -0.8496062013533213, -0.7865330540705233, -0.7337420307809198, -0.691723656662835, -0.6607138757994439, -0.6406928702548579, -0.6313898080638606, -0.6322933583150621, -0.6426676736109695, -0.6615734101585359, -0.6878932367453477, -0.720361178777294, -0.7575950549315629, -0.7981311939416954, -0.8404605692435871, -0.883065460833086, -0.9244557473468822, -0.9632039471606273, -0.9979781647377828, -1.027572156558377, -1.0509318081996204, -1.0671774085487529, -1.0756212162995713, -1.0757799350544077, -1.0673818434663733, -1.0503684626413072, -1.0248907810695622, -0.9913001942197132, -0.9501344481827015, -0.9020990011100722, -0.848044329552996, -0.7889398063693582, -0.7258448601646197, -0.6598781912204132, -0.5921858639568712, -0.5239091200859479, -0.45615275918639714, -0.38995491445097424, -0.32625901134816093, -0.2658886369567434, -0.20952596932520265, -0.15769432139381367, -0.1107452452203799, -0.06885052224549795, -0.031999237174682324, -2.7652536647843447e-16], [0.0, 0.025791541259194205, 0.047978247754828895, 0.06728594691622014, 0.08454971832054753, 0.10068818135620528, 0.11667532656556624, 0.13351064271111907, 0.15218833758301153, 0.1736664761084517, 0.198836863766356, 0.2284964865173637, 0.2633212808278924, 0.3038429498203914, 0.35042946554578913, 0.40326980474066276, 0.46236335851312277, 0.5275143378724698, 0.5983313698485917, 0.6742323463299317, 0.7544544530176749, 0.8380691724414269, 0.9240019261749997, 1.0110559004866975, 1.0979394897217651, 1.183296695542027, 1.2657397401972197, 1.3438830903315118, 1.4163780460424988, 1.4819470291206847, 1.5394167051958536, 1.5877490969566166, 1.6260698892054388, 1.6536931902506435, 1.6701420965024643, 1.6751645061493852, 1.6687437410424844, 1.6511036606494367, 1.6227080851051725, 1.5842544827160323, 1.5366620173668268, 1.481054189682548, 1.4187364390900268, 1.3511691988105299, 1.2799370091934799, 1.2067143938538658, 1.1332292853287627, 1.0612248503586543, 0.9924206078247496, 0.9284737537330108, 0.8709416068568908, 0.8212460657046012, 0.7806409228791407, 0.7501828176982075, 0.730706523691978, 0.7228051663239982, 0.7268158504282438, 0.7428110492277303, 0.7705959704917059, 0.8097119737092442, 0.8594459685503467, 0.9188455828435586, 0.9867397512770515, 1.0617642473610744, 1.1423915640030267, 1.2269644451903, 1.3137322852475897, 1.4008895450196956, 1.4866152877485133, 1.5691129124827083, 1.6466491601665654, 1.7175914871440592, 1.7804429421809773, 1.833873745216135, 1.8767488473585185, 1.9081508501381492, 1.9273977752635718, 1.934055301347566, 1.9279432181559955, 1.9091359886186294, 1.8779574506906185, 1.8349698316955563, 1.7809573835812027, 1.7169050752646746, 1.6439728948276586, 1.5634664169169274, 1.4768043768346055, 1.3854840604004757, 1.2910453661309818, 1.1950344225026721, 1.0989676474749392, 1.0042971200019142, 0.9123780944706704, 0.8244394298944376, 0.7415576277977062, 0.6646350780504091, 0.5943830028469242, 0.5313094683415976, 0.47571270418634537, 0.4276798366153766, 0.387091004160217, 0.35362868996921865, 0.3267919744206378, 0.3059152895001165, 0.29019114529727025, 0.2786962017136355, 0.27041997746528007, 0.2642954256966317, 0.259230562525994, 0.25414031264820347, 0.24797773523344588, 0.2397638137555439, 0.2286150344963728, 0.21376803922423493, 0.19460071636013326, 0.17064918980160543, 0.14162027304307528, 0.10739907554809965, 0.06805157545571505, 0.023822104409075118, -0.024874176764776344, -0.0774636019936124, -0.13323078864330606, -0.19133943936651643, -0.25085660043301405, -0.31077972902399054, -0.3700658477201122, -0.4276620086353482, -0.48253625377430265, -0.5337082431476219, -0.5802787283717831, -0.6214570767749705, -0.6565860987673506, -0.6851634982339186, -0.7068593503070619, -0.7215291109653601, -0.7292217759835244, -0.7301829299946461, -0.7248525567289794, -0.7138576155904102, -0.6979995242482503, -0.6782368184677557, -0.6556633856554512, -0.6314827843842937, -0.6069792655486606, -0.5834861991446396, -0.5623526817122363, -0.5449091513757983, -0.532432868814001, -0.5261141325270854, -0.5270240851232911, -0.5360849342348158, -0.5540433578476534, -0.5814477905580181, -0.6186301963059095, -0.6656928266824358, -0.7225003445504856, -0.7886775633724729, -0.8636129164730729, -0.9464676308237723, -1.0361904402577244, -1.1315375367541662, -1.2310973289407463, -1.3333194574588645, -1.4365474102892661, -1.539053990198381, -1.6390788134149092, -1.7348669653188482, -1.8247079066784542, -1.9069737136428155, -1.9801557465915056, -2.042898876813441, -2.0940324550504443, -2.1325972808916887, -2.1578679250471993, -2.169369865421365, -2.1668910200182716, -2.150487392081545, -2.12048268228982, -2.077461865908076, -2.0222588760563665, -1.9559386742164693, -1.8797741223489268, -1.7952181942968564, -1.7038721745105387, -1.6074505868574007, -1.507743673087505, -1.4065782975462786, -1.3057781905901642, -1.20712445701212, -1.1123172673069348, -1.0229396190320057, -0.9404240036203566, -0.8660227420731198, -0.8007826627818975, -0.7455246885360828, -0.7008287801755332, -0.6670245542982902, -0.6441877551232718, -0.6321426194083595, -0.6304700316951822, -0.638521228557586, -0.6554366783553623, -0.6801696404580002, -0.7115137979815487, -0.7481342634351171, -0.7886011795800845, -0.8314250801056015, -0.875093137776194, -0.9181054123542507, -0.9590102171490762, -0.9964377512599706, -1.0291311936930014, -1.055974524253114, -1.076016422676036, -1.0884896996596711, -1.0928258286920591, -1.0886642729434113, -1.0758564338391585, -1.0544641839387252, -1.0247530830066478, -0.9871805092753312, -0.9423790645450546, -0.8911357287976595, -0.8343673445134525, -0.7730931002924567, -0.7084047554900603, -0.6414354006195255, -0.5733275809661329, -0.5052016224288627, -0.43812498881474415, -0.3730834689542021, -0.31095494090701736, -0.25248639051908545, -0.1982747744748168, -0.14875221600167737, -0.10417590712613226, -0.06462296776515798, -0.029990382108295813, -2.5903917580592635e-16], [0.0, 0.024205364691566793, 0.04518584463214115, 0.0637152532698713, 0.08066183042247901, 0.09696143466361766, 0.11358872435586936, 0.13152709805890148, 0.15173819892631218, 0.17513180097256764, 0.20253688738572398, 0.23467470255403722, 0.2721345108608503, 0.31535272778499435, 0.36459600410315657, 0.41994874414142824, 0.48130542656342656, 0.5483679739304421, 0.6206482882935481, 0.6974759376209037, 0.7780108452605741, 0.8612607052345469, 0.9461027232234623, 1.0313091697481418, 1.115576131163405, 1.19755475822584, 1.2758842433830813, 1.3492257083342065, 1.4162961541343044, 1.4759016179616828, 1.526968693908868, 1.5685736095409906, 1.5999681047024499, 1.6206014328515277, 1.6301378962922397, 1.6284694328487028, 1.6157228902053795, 1.5922617524162241, 1.5586822178218782, 1.5158036654943472, 1.4646536849557292, 1.4064479778930652, 1.342565567599711, 1.2745198687648873, 1.2039262741002865, 1.1324670025450057, 1.0618540242166072, 0.9937909281012316, 0.9299346284033386, 0.8718578137220628, 0.8210130295346446, 0.778699249134966, 0.746031732016595, 0.7239158930367706, 0.7130258123629256, 0.7137879074348671, 0.7263701666027738, 0.7506772126693588, 0.7863513264634978, 0.8327794191577064, 0.8891058007516857, 0.9542504544157309, 1.0269323955726366, 1.1056975738773918, 1.1889506685667834, 1.2749900356132156, 1.3620449909623955, 1.4483145596592024, 1.532006787182831, 1.6113776976212406, 1.6847689936799812, 1.750643625667643, 1.80761840972022, 1.8544929482988384, 1.8902741966177392, 1.9141961248951054, 1.9257340455512446, 1.9246133037738884, 1.9108121660540462, 1.8845588810275886, 1.8463230268163013, 1.796801395627915, 1.7368987963154265, 1.6677042757481428, 1.5904633672937223, 1.50654706685357, 1.4174183115172458, 1.3245967912253114, 1.2296229585543783, 1.1340221150744219, 1.0392694444180344, 0.9467568325213574, 0.8577622652518724, 0.7734225241415763, 0.6947098139811949, 0.6224128538177597, 0.5571228480219045, 0.49922462945026597, 0.44889313545496984, 0.4060952428774716, 0.3705968535746412, 0.34197499081940924, 0.31963454236368827, 0.30282917114149194, 0.290685812369706, 0.28223208869688704, 0.2764259051980555, 0.27218643512134316, 0.2684256765884248, 0.2640797506548907, 0.25813912244393594, 0.24967695914213534, 0.23787489063429929, 0.22204550910122117, 0.20165103119110414, 0.17631764816530268, 0.14584520311261243, 0.11021195702731727, 0.06957433413433387, 0.024261668053791517, -0.025233899102955894, -0.07827208613410493, -0.1340833128215963, -0.19179120385702492, -0.2504381538190878, -0.3090132698821822, -0.36648194592288746, -0.4218162777940962, -0.4740255058828669, -0.5221856682754286, -0.5654676660140474, -0.6031629806104114, -0.634706342226774, -0.659694723303557, -0.677902124996925, -0.6892897302784367, -0.6940111152746052, -0.69241233643451, -0.6850268422428744, -0.6725652911456135, -0.6559004887742369, -0.6360477841271067, -0.6141413828870418, -0.5914071435196321, -0.5691325154691238, -0.5486343562529351, -0.5312254235557864, -0.518180377994336, -0.5107021510067177, -0.5098895297788749, -0.516706787242029, -0.5319561404856863, -0.5562537564706032, -0.5900099412328191, -0.6334140498368598, -0.6864245415652094, -0.7487644809732557, -0.819922653525983, -0.8991603278037194, -0.9855235580843266, -1.0778607848869086, -1.1748453601647257, -1.2750025015053301, -1.3767400689723293, -1.4783824618621366, -1.5782068530599542, -1.6744809178612474, -1.7655011736183062, -1.8496310274203092, -1.925337631737966, -1.9912266725434962, -2.0460742602979485, -2.088855160301616, -2.1187666836529413, -2.1352476614197022, -2.1379920401477848, -2.1269567637210143, -2.1023637417636176, -2.0646958449620634, -2.014687009467964, -1.9533066724799235, -1.881738895784925, -1.8013566601919326, -1.7136919283430836, -1.6204021735555223, -1.5232341556968239, -1.4239857896079056, -1.3244669956998636, -1.2264604450057794, -1.1316831116315045, -1.0417495242260757, -0.9581375653255977, -0.8821576042828737, -0.8149256675448787, -0.7573412513068968, -0.7100702684904046, -0.6735334973454348, -0.647900765830073, -0.6330909675381667, -0.6287778647221656, -0.6344014953225593, -0.6491848672547429, -0.672155497776508, -0.7021712416141405, -0.737949751428415, -0.7781008305682756, -0.8211608728935659, -0.865628539293628, -0.9100007964329797, -0.9528084407440186, -0.9926502497503802, -1.0282249429002164, -1.0583601941544154, -1.082038017056158, -1.0984159378985638, -1.1068434814966142, -1.1068736142071143, -1.098268917201482, -1.0810023963586197, -1.0552529701698712, -1.0213958103619591, -0.9799878382236488, -0.9317487996773575, -0.8775384509894356, -0.8183304819698943, -0.7551838822339829, -0.6892125166547002, -0.6215537170559565, -0.5533367175035908, -0.4856517597872102, -0.41952067391995645, -0.3558696963129198, -0.2955052268143845, -0.2390931466326744, -0.18714222431934585, -0.13999202890289011, -0.09780565068803666, -0.06056740419028196, -0.028085557362607958, -2.426722884850381e-16], [0.0, 0.022760551419522858, 0.042694920401441745, 0.06061664076525602, 0.0774183847252703, 0.09404432470479786, 0.11146093537062365, 0.1306270180163479, 0.1524637512232533, 0.17782557291169934, 0.20747267941501976, 0.24204588753233908, 0.28204454662648715, 0.32780811119287934, 0.37950189184780525, 0.4371073966836973, 0.5004175580714875, 0.5690370151896804, 0.6423874929636743, 0.7197181869697591, 0.8001209345026444, 0.882549827690982, 0.9658448084192608, 1.0487586798244164, 1.1299868779558666, 1.2081992721526433, 1.2820732057354436, 1.3503269512218659, 1.4117527374507837, 1.465248510236604, 1.5098476134314518, 1.5447456229942813, 1.5693236317805916, 1.5831673657195846, 1.5860816108345859, 1.5780995427865832, 1.5594866735396464, 1.5307392603490726, 1.4925771573491544, 1.4459312262403345, 1.3919255565822148, 1.331854874674081, 1.267157639762689, 1.199385434380916, 1.1301693492969258, 1.0611841404966331, 0.9941109938969735, 0.9305997716136393, 0.8722316305986643, 0.8204828998530751, 0.7766910762706501, 0.742023752073943, 0.7174512198708163, 0.7037234161866166, 0.7013517629599889, 0.7105963513762432, 0.7314587863371346, 0.7636808758876854, 0.8067492112930831, 0.8599055435519175, 0.922162724349403, 0.9923258471491264, 1.0690181005142145, 1.1507107338469926, 1.2357564382620603, 1.3224253646301891, 1.4089429389071344, 1.4935285931903253, 1.574434510529726, 1.6499834828374658, 1.7186050042438203, 1.7788687663517928, 1.8295147859511134, 1.8694794782771418, 1.8979170878039102, 1.9142160014070968, 1.918009592746682, 1.9091813788550915, 1.8878644069337938, 1.8544349279043075, 1.8095005499400916, 1.753883196687503, 1.688597317963652, 1.6148239124058876, 1.5338810191369925, 1.4471914166494813, 1.3562483298589418, 1.2625799891453389, 1.1677139072003353, 1.0731417401541024, 0.9802855788201308, 0.8904664745514662, 0.8048759432373908, 0.7245511119601012, 0.6503540777939862, 0.582955939575994, 0.5228258439471251, 0.4702252595685274, 0.4252075613463167, 0.38762287306089155, 0.35712798532019097, 0.33320103951629954, 0.3151605505980255, 0.30218823489988045, 0.29335501662342806, 0.28764951013038065, 0.2840082168483526, 0.2813466367243896, 0.27859047571232715, 0.274706133158639, 0.2687296760459827, 0.2597935502331238, 0.24715034096007757, 0.230192974359981, 0.2084708464923448, 0.18170147406214232, 0.14977737877049827, 0.11276804215831072, 0.07091689667985875, 0.02463344830774904, -0.025519247063353182, -0.0788414099985534, -0.13451721101620037, -0.19163873499788234, -0.24923259408686552, -0.3062884768932502, -0.36178887032577167, -0.41473915844365067, -0.4641972911909656, -0.5093022250508416, -0.5493003673262923, -0.5835693051910319, -0.6116381686310955, -0.6332040612225563, -0.6481440922420184, -0.6565226553920224, -0.6585937206388834, -0.6547980332608625, -0.6457552449799343, -0.6322511327058165, -0.6152201876590597, -0.595723978243126, -0.5749258009469066, -0.5540622319587577, -0.5344122755488471, -0.5172648714872874, -0.5038855710948416, -0.49548321872297285, -0.4931774817826523, -0.49796805765857344, -0.5107063502543866, -0.5320703533323563, -0.5625434035539851, -0.6023973749810476, -0.6516807809676122, -0.7102121314414828, -0.7775787664228795, -0.8531412533791911, -0.936043299945504, -1.025226998007185, -1.1194530834919996, -1.2173257717162438, -1.3173216138628596, -1.417821718983739, -1.5171466003406056, -1.613592837075854, -1.7054706938503648, -1.791141813435338, -1.8690560910297858, -1.9377868544967327, -1.9960635114406289, -2.0428008812328424, -2.077124506374471, -2.0983913311387536, -2.1062052440049714, -2.100427101357996, -2.081178980351182, -2.0488425455497454, -2.004051553664942, -1.9476786599589206, -1.8808168253573965, -1.8047557516553436, -1.7209538903160926, -1.6310066753726309, -1.5366117202877745, -1.4395317901481846, -1.341556412521909, -1.2444630214468388, -1.1499785385942312, -1.0597422834516992, -0.9752710707115133, -0.8979272987750696, -0.8288907597411417, -0.7691348102508964, -0.7194074363608918, -0.6802176268201352, -0.6518273406582045, -0.6342492200012486, -0.6272500608296864, -0.6303599163581418, -0.642886573226923, -0.6639350130253527, -0.6924313539269542, -0.7271506622613912, -0.766747934214541, -0.80979147569059, -0.8547978554072079, -0.9002675737692829, -0.9447205787136308, -0.9867307697470342, -1.024958662495626, -1.0581814374059557, -1.0853196664513345, -1.1054600989985666, -1.1178739901597923, -1.1220305694069692, -1.1176053710787401, -1.1044832785510446, -1.082756267013589, -1.052715962666797, -1.0148412654150856, -0.9697814045663328, -0.9183349096161513, -0.8614250781126767, -0.8000726073990151, -0.7353661246346174, -0.6684313982560665, -0.6004000427792617, -0.5323785368992497, -0.4654183620609745, -0.4004880354265395, -0.3384477583377212, -0.2800273303420719, -0.2258078914477592, -0.17620795373630502, -0.13147407038648526, -0.09167636842672085, -0.05670904423297804, -0.026295791157512377, -2.275109573175131e-16], [0.0, 0.02146280887520123, 0.04051267303890868, 0.05799440251635442, 0.07481635131923464, 0.09192221502669667, 0.11026172233153315, 0.13076100685938946, 0.1542934554023296, 0.18165181811000283, 0.21352233540143417, 0.2504615861562493, 0.29287669336389544, 0.3410094385599281, 0.3949247371828461, 0.4545038159298876, 0.5194423130636927, 0.589253396443808, 0.6632758650040209, 0.7406870707221666, 0.820520373082699, 0.9016867197779452, 0.9829998389308356, 1.0632044322094638, 1.1410066772923948, 1.2151062843128604, 1.2842293058164262, 1.3471608746017794, 1.4027770392741916, 1.4500748836084354, 1.4882001525563786, 1.5164716640967146, 1.5344018607721104, 1.5417129458958796, 1.5383481548252704, 1.5244778288206149, 1.5005000849714467, 1.4670360073785673, 1.424919418992036, 1.3751814269067184, 1.3190300632098582, 1.2578254654540593, 1.1930511524629657, 1.12628204968432, 1.0591500012225772, 0.9933075709276926, 0.9303909808365372, 0.8719830606804327, 0.8195770864111288, 0.7745423686029758, 0.738092413530434, 0.7112564215826053, 0.6948548108403662, 0.6894793599477805, 0.6954784561151732, 0.7129478138145119, 0.7417269003833049, 0.7814011694807924, 0.831310065427421, 0.8905606242600567, 0.9580463641903955, 1.0324710323038477, 1.1123766588452573, 1.1961752681170426, 1.2821835083542608, 1.368659394045533, 1.4538403047096766, 1.5359813553104014, 1.6133932459844027, 1.684478712739861, 1.7477667358926516, 1.8019437183716567, 1.8458809202701165, 1.8786575273149884, 1.8995788370219124, 1.9081891645907871, 1.9042791981716294, 1.8878876668633466, 1.8592973214241642, 1.8190253638299596, 1.7678085941909225, 1.706583668901082, 1.636462979200656, 1.5587067617818993, 1.474692140190906, 1.3858798654783537, 1.2937795751726566, 1.1999144200043412, 1.1057859172179545, 1.0128398776032501, 0.9224342209184972, 0.8358094420354003, 0.7540624192671622, 0.6781241687640656, 0.6087420467995016, 0.546466787803245, 0.4916446429959592, 0.4444147555264333, 0.4047117763376975, 0.3722735938778098, 0.3466539234919126, 0.3272393820476301, 0.3132705630385067, 0.30386652980691736, 0.2980520620331293, 0.29478692527292555, 0.2929963866821617, 0.2916021732613395, 0.2895530626065026, 0.2858543103707818, 0.2795951530144092, 0.2699736780357887, 0.2563184253366901, 0.23810617083902127, 0.21497544469775984, 0.18673544885975152, 0.15337015943867977, 0.11503752534323096, 0.07206380260999116, 0.024933190707153934, -0.02572694052575496, -0.07916482975574123, -0.13452660085440854, -0.19088143804645308, -0.24724898416382896, -0.30262822801394546, -0.3560271070456501, -0.40649203151481966, -0.45313653673277965, -0.49516829073325297, -0.5319137253118789, -0.5628396178701983, -0.5875710283515115, -0.6059050878682138, -0.6178202410768803, -0.6234806603130959, -0.6232356730395228, -0.6176141721802075, -0.6073141081862923, -0.5931872889417072, -0.5762198356550433, -0.5575087566044562, -0.5382352031176618, -0.5196350608658515, -0.5029676021563817, -0.4894829795504516, -0.4803893763801311, -0.4768206446472016, -0.47980525491343995, -0.49023735621523534, -0.5088506973482978, -0.5361960951667702, -0.5726230523975323, -0.6182660288948042, -0.6730357586505656, -0.7366158829603875, -0.8084650409121474, -0.8878244249944062, -0.9737306754002826, -1.0650338548474725, -1.1604201197081754, -1.2584385860717797, -1.3575317839636045, -1.456069001945889, -1.5523817500120098, -1.6448005129257197, -1.7316919303730904, -1.8114955254150396, -1.882759109170505, -1.944172017316043, -1.994595382228634, -2.0330887122880794, -2.058932135378242, -2.0716437649273307, -2.070991761460843, -2.0570007878322296, -2.0299526890089323, -1.9903813643017718, -1.9390619379022385, -1.8769944691778648, -1.8053825740700056, -1.7256074499784513, -1.6391979057565542, -1.5477970932207603, -1.4531267145944597, -1.356949539663971, -1.261031105686794, -1.1671014913139142, -1.0768180525391904, -0.9917299840659363, -0.913245524103234, -0.8426025555990423, -0.780843273891232, -0.7287934917580284, -0.6870470403122129, -0.655955600874093, -0.6356241719030539, -0.6259122394779548, -0.6264405830119204, -0.636603513210391, -0.6555862100187546, -0.6823867076046474, -0.7158419642116519, -0.7546573596486321, -0.7974388845328599, -0.8427272250665873, -0.889032906521956, -0.9348716386752188, -0.9787990075923522, -1.0194436803274964, -1.0555383316373403, -1.085947563620029, -1.1096921686640104, -1.1259691812135464, -1.1341672722140832, -1.1338771589594006, -1.1248968294370258, -1.1072315109918287, -1.0810884449324638, -1.0468666583042363, -1.0051420482201128, -0.9566482097963833, -0.9022535430173851, -0.8429352641809287, -0.7797510217326662, -0.7138088724721678, -0.6462364109475162, -0.5781498614771317, -0.5106239382830735, -0.4446632548414767, -0.3811760194167746, -0.3209506910056311, -0.26463619019787177, -0.2127261648130782, -0.16554770301340502, -0.12325476965804608, -0.08582651792757516, -0.05307050085110732, -0.02463067954897187, -2.1362709262396706e-16], [0.0, 0.020316193585117534, 0.03864294017890972, 0.05584779154607721, 0.07284609821603574, 0.09057250810489179, 0.10995181065347732, 0.13186990988200897, 0.15714570785838494, 0.18650465810235198, 0.22055470694040397, 0.25976528081738315, 0.3044499005582362, 0.3547529114846609, 0.41064071343541264, 0.4718977597487155, 0.5381274720316437, 0.6087580911417544, 0.6830533574269388, 0.7601277881264327, 0.8389662000941392, 0.9184470146998148, 0.9973687817229682, 1.0744792728301937, 1.1485064250294983, 1.2181903621385481, 1.2823156891585819, 1.339743241405308, 1.38944047770545, 1.4305097348046103, 1.4622136077219894, 1.4839967870094333, 1.4955037671387525, 1.4965919385367163, 1.4873396867175528, 1.4680492428144747, 1.439244157618504, 1.4016614028488938, 1.356238235557564, 1.3040940910416428, 1.246507893194839, 1.184891285800754, 1.120758391005666, 1.0556927895380206, 0.9913124889500933, 0.9292336994335728, 0.8710342702454192, 0.8182176525990223, 0.772178246661445, 0.7341689612006355, 0.7052717651110401, 0.6863719416742191, 0.6781366706151921, 0.6809984618574504, 0.6951438508019784, 0.7205076407199776, 0.7567728464691145, 0.8033763584108158, 0.8595202094127231, 0.9241881944756705, 0.9961674650755631, 1.074074601861107, 1.1563855627838362, 1.2414688116514732, 1.3276208567303036, 1.413103372208102, 1.4961810384433314, 1.575159220858161, 1.6484206124609107, 1.7144599911689178, 1.7719162896891443, 1.8196012415478395, 1.8565239503164468, 1.8819108281042787, 1.89522046154444, 1.8961530860344764, 1.8846544789024708, 1.8609142162706729, 1.8253583734022731, 1.7786368809442643, 1.721605876486707, 1.6553055091549342, 1.580933761665209, 1.4998169468243754, 1.4133776116123293, 1.3231006399322056, 1.2304983834793273, 1.137075668083592, 1.0442955199454036, 0.953546432551714, 0.8661119513766424, 0.7831432908849377, 0.7056356184757794, 0.6344085448631707, 0.5700912523946704, 0.5131125746834739, 0.46369621563503444, 0.4218611666260292, 0.38742725046997195, 0.36002559312287846, 0.33911370201848323, 0.32399471650302913, 0.31384029387020324, 0.3077165064910979, 0.3046120536522826, 0.30346803771004277, 0.3032085193430956, 0.30277105185996395, 0.3011364000088021, 0.29735667435550067, 0.2905811573449322, 0.2800791604585378, 0.2652593317913616, 0.24568492784041945, 0.22108466990850217, 0.19135892156501405, 0.15658104611653262, 0.11699392891234152, 0.07300177535059281, 0.025157418463253776, -0.02585451317485573, -0.07923810870682575, -0.13410981499443325, -0.18952456727411804, -0.24450370906892654, -0.29806395264347213, -0.3492466031825217, -0.3971462616976892, -0.44093823364186996, -0.479903902050738, -0.5134533749477156, -0.5411447854747019, -0.5626997080276303, -0.578014252458766, -0.5871655086778095, -0.5904131329708069, -0.5881959920659522, -0.5811239082671242, -0.5699646756379861, -0.5556266400515539, -0.5391372518122747, -0.5216181055689509, -0.5042570756685775, -0.48827823356484645, -0.47491029537225304, -0.46535439055016803, -0.46075196587519013, -0.46215364166930073, -0.4704898195577571, -0.4865438032079065, -0.5109281364245699, -0.5440647880076203, -0.5861697217199484, -0.637242284780828, -0.6970597320524357, -0.7651770783746688, -0.8409323413912161, -0.923457104903979, -1.0116922015618826, -1.1044081867822584, -1.2002301563671218, -1.2976663512833722, -1.395139897243942, -1.4910229464558953, -1.5836724262104007, -1.6714665554694335, -1.7528412673751674, -1.8263256732924955, -1.8905757227026538, -1.9444052525871518, -1.986813678961001, -2.0170096605306482, -2.0344301582122055, -2.0387544221906997, -2.0299125577208756, -2.0080884490681408, -1.973716954752014, -1.9274754233324014, -1.8702697140604045, -1.8032150375116671, -1.7276120546461533, -1.644918785589892, -1.5567189790633793, -1.4646876773631192, -1.370554778094537, -1.2760674408473769, -1.1829522135620456, -1.0928777588210188, -1.0074190445933962, -0.9280238274617858, -0.8559821999767656, -0.7923998989086755, -0.7381759796456063, -0.6939853560717045, -0.660266587553423, -0.6372151680513121, -0.6247824399645576, -0.6226801203454907, -0.6303902928913324, -0.6471805889065019, -0.6721241574032444, -0.7041239116613722, -0.7419404396345588, -0.784222880982743, -0.8295420062584543, -0.876424685478015, -0.9233889050951182, -0.9689784848955598, -1.0117966596659704, -1.0505377242604417, -1.084015993996554, -1.1111914037750108, -1.1311911571075417, -1.1433269381279336, -1.1471073130793357, -1.142245069864769, -1.1286593719566256, -1.1064727330912227, -1.076002948479969, -1.037750243530915, -0.9923800191828017, -0.940701680982481, -0.8836441343180387, -0.8222286084096512, -0.7575395347957818, -0.690694250601304, -0.6228123217717996, -0.5549852861337723, -0.4882476005301851, -0.4235495408296138, -0.3617327492567251, -0.3035090516561182, -0.24944307983183306, -0.19993913324214233, -0.1552326026484316, -0.11538615866212072, -0.08029078354581966, -0.049671598267326714, -0.023098311882312372, -2.0107776575631545e-16], [0.0, 0.01932309804499384, 0.03708621831762916, 0.0541711172057323, 0.0714916076884074, 0.08996502056676234, 0.11048345631587367, 0.13388560116771794, 0.16092986772979873, 0.19226958759697765, 0.22843093183969168, 0.2697941662377511, 0.31657876340298047, 0.3688327956210462, 0.42642692281208355, 0.48905317221299077, 0.5562285831871786, 0.6273036650757098, 0.7014754913847584, 0.7778051330089164, 0.8552390196728178, 0.9326337152172262, 1.0087835013978688, 1.0824500888327027, 1.1523937145833236, 1.2174048451274941, 1.276335682253057, 1.328130668274244, 1.3718552060340976, 1.406721848001936, 1.432113266498445, 1.447601392306335, 1.4529621998355502, 1.448185721398112, 1.4334809884579083, 1.4092757211265863, 1.376210715642415, 1.3351290099258986, 1.287060036331652, 1.2331990952137881, 1.1748825998001622, 1.1135596492195432, 1.050760579689352, 0.9880632215149592, 0.9270576497176171, 0.869310257267707, 0.8163280009894823, 0.7695236706519523, 0.73018301150445, 0.6994344900006904, 0.6782224326268323, 0.667284190028417, 0.6671318848812386, 0.6780391944312307, 0.7000334999384921, 0.7328936082776464, 0.7761531187543369, 0.829109374009889, 0.8908378009686451, 0.9602113193719707, 1.035924374667973, 1.1165210418290554, 1.2004265497360147, 1.2859814944578165, 1.371477946049627, 1.4551966089358033, 1.5354441716184175, 1.6105899779393242, 1.6791011694982672, 1.7395754866544868, 1.7907709728759893, 1.8316319026351073, 1.8613103447234047, 1.8791828785206401, 1.8848620978074746, 1.878202662289812, 1.859301788028517, 1.8284942012362346, 1.7863417121575027, 1.7336176937627512, 1.6712868706441986, 1.6004809338706762, 1.5224705949657589, 1.4386347742692778, 1.3504276837579356, 1.2593446103965749, 1.1668872321952373, 1.0745293047781175, 0.9836835413550913, 0.895670473957969, 0.8116900295913319, 0.7327964829531388, 0.6598773594413945, 0.5936367605088179, 0.534583470620798, 0.48302408394740537, 0.4390612625111773, 0.4025971089775208, 0.37334150981726405, 0.3508251813610809, 0.33441703536010575, 0.32334537493421955, 0.31672233883779927, 0.3135709340861165, 0.3128539360673886, 0.313503892791205, 0.3144534469051674, 0.314665186071094, 0.3131602492518501, 0.30904495294066664, 0.3015347563991096, 0.28997495712625704, 0.27385759520132047, 0.2528341455853336, 0.22672368837108003, 0.1955163655103903, 0.15937205571208096, 0.11861432386608539, 0.07371982434905296, 0.025303455787127324, -0.02590032470164287, -0.07905951988674983, -0.13326934875261254, -0.18757907462414256, -0.24102018457786692, -0.29263516375816895, -0.3415060917615198, -0.3867822916333212, -0.4277062851696229, -0.4636373505588254, -0.4940720388821222, -0.5186610831034012, -0.5372222249873769, -0.549748589584591, -0.5564123508947882, -0.5575635531985562, -0.5537240772856731, -0.5455768662610825, -0.5339506486064065, -0.5198005136043141, -0.5041848031166087, -0.48823888127602433, -0.473146427416255, -0.4601089653759085, -0.4503143924162269, -0.44490530207573264, -0.44494790650663923, -0.45140235485175517, -0.465095215184533, -0.48669483910767813, -0.5166902614311689, -0.5553742040299103, -0.6028306550341004, -0.6589273843199165, -0.7233136365423153, -0.7954231166267386, -0.8744822528245546, -0.9595235923429715, -1.04940405740413, -1.1428276685237977, -1.2383722298377615, -1.3345193712349501, -1.4296872563837557, -1.522265196615222, -1.6106493598013287, -1.693278732140076, -1.7686704799509072, -1.8354538685121444, -1.892401925445697, -1.9384600864747554, -1.9727711303615694, -1.9946957958270306, -2.0038285741943245, -2.0000082849484637, -1.9833231646147513, -1.9541103293429631, -1.912949605181559, -1.8606518539878114, -1.7982420539839898, -1.7269375189443554, -1.648121755837633, -1.5633145646322242, -1.4741390733659985, -1.3822864743127279, -1.2894792813739107, -1.1974339633707476, -1.1078238218723602, -1.0222429752431479, -0.9421722829066943, -0.8689479960956751, -0.8037338547668831, -0.7474972665484778, -0.7009901046147892, -0.6647345496832593, -0.6390142796387617, -0.6238711815946582, -0.6191076286480112, -0.6242942304186214, -0.638782835929455, -0.6617244426708802, -0.6920915498265788, -0.7287043894359404, -0.7702603792456744, -0.8153660673279037, -0.8625707829728547, -0.9104011722113073, -0.9573957804140591, -1.0021388490811138, -1.0432925189912519, -1.0796266766499334, -1.1100457442809035, -1.1336117938294383, -1.1495634605432496, -1.1573302392668081, -1.1565418639194716, -1.1470325947837183, -1.1288403661016748, -1.1022008748748509, -1.0675368174868827, -1.0254426006991328, -0.9766649647323713, -0.9220800557975332, -0.8626675711210086, -0.799482669124725, -0.7336263892739809, -0.6662153589492196, -0.5983515777620505, -0.5310930627477732, -0.46542611105573156, -0.4022398908509036, -0.34230400733834737, -0.2862496107768968, -0.23455451911555264, -0.18753272187441633, -0.1453285168038781, -0.10791540961847744, -0.07509978279390833, -0.04652921519056702, -0.021705213273332156, -1.8990487711478142e-16], [0.0, 0.018484255525820423, 0.03583971740050231, 0.05295389302541296, 0.07073075779636064, 0.0900624342471874, 0.11180109637876982, 0.13673185637658344, 0.16554736664977646, 0.19882482700053505, 0.23700602583104788, 0.2803809671417859, 0.32907554360487895, 0.3830436125081277, 0.4420637184616128, 0.5057405872828017, 0.5735113924393523, 0.644656671936776, 0.7183156527121846, 0.7935056244946395, 0.8691448986376, 0.9440787923280786, 1.0171079972588397, 1.0870186264019253, 1.1526131846377823, 1.2127416799320647, 1.266332082300747, 1.3124193482642121, 1.3501722586658742, 1.3789173669316, 1.3981594219072409, 1.4075977127195798, 1.4071378806390689, 1.39689885230027, 1.3772146671770147, 1.3486310969993927, 1.311897082761979, 1.2679511429449037, 1.217903031381671, 1.1630110417614787, 1.1046554650987823, 1.0443088039100719, 0.983503429867862, 0.9237974382651686, 0.8667395010338311, 0.8138335490739972, 0.7665041235042316, 0.7260632238607266, 0.6936794494920657, 0.6703501791424695, 0.6568774642009386, 0.6538482249770005, 0.6616192387163332, 0.6803072953222139, 0.7097847746317367, 0.7496807705728634, 0.7993877557231658, 0.8580736479108548, 0.9246990117548303, 0.9980390055702459, 1.0767095708543404, 1.1591972603744136, 1.2438920141719516, 1.3291221226870238, 1.4131905644015792, 1.494411873157786, 1.5711486784077366, 1.6418470703750816, 1.7050699712343533, 1.7595277422166837, 1.8041053238279283, 1.8378852904606142, 1.8601662995288741, 1.8704765264296481, 1.868581797408553, 1.8544882598272678, 1.8284395602738663, 1.790908632228763, 1.7425843233935527, 1.6843532151801577, 1.6172771002678332, 1.5425666858154843, 1.4615521774095186, 1.375651470029245, 1.2863367255236833, 1.1951001500628937, 1.1034197989770942, 1.0127262300472482, 0.9243707998810591, 0.8395963522144013, 0.7595109830118848, 0.6850654867403941, 0.6170349932000765, 0.5560051972164095, 0.5023634670168978, 0.45629499415555935, 0.4177840214809317, 0.3866200590193831, 0.3624088739150961, 0.3445879228018173, 0.33244578609501685, 0.32514506637416024, 0.3217481296672079, 0.32124500109345905, 0.32258267660318, 0.3246950816657283, 0.3265328964218396, 0.3270924752594455, 0.32544311672959214, 0.3207519864350338, 0.3123060597752632, 0.2995305315568637, 0.2820032334197356, 0.2594647053869448, 0.23182368193358993, 0.19915787288732414, 0.16171004217541612, 0.11987950980893705, 0.0742093214432147, 0.025369442362937256, -0.025863564037885235, -0.07862982188918227, -0.1320117640899561, -0.18506139972003924, -0.23682849494076347, -0.28638891028529617, -0.33287233225432317, -0.37548865172014684, -0.4135522754449114, -0.4465037091949203, -0.47392782017799995, -0.49556827110859014, -0.5113377159922206, -0.5213234562590886, -0.5257883724340205, -0.5251670681708489, -0.5200572871347867, -0.5112067857636751, -0.49949596327803475, -0.4859166614414102, -0.4715476476733507, -0.4575273836106969, -0.44502475483386805, -0.435208494326488, -0.4292160708386305, -0.4281228326495654, -0.4329121967284896, -0.4444476529190379, -0.463447312969449, -0.4904616759253576, -0.5258552059897511, -0.5697922282580887, -0.6222275439638876, -0.6829020525598402, -0.7513435459181379, -0.8268727131661967, -0.9086142663095944, -0.995512970008646, -1.0863542368125243, -1.1797888348495047, -1.2743611512715525, -1.3685403642490592, -1.4607538012782724, -1.5494217038938858, -1.632992580041633, -1.7099783063679364, -1.7789881440464848, -1.8387608535036994, -1.8881941350453288, -1.926370682951666, -1.9525802186598473, -1.9663369623169669, -1.9673921090097635, -1.955740993766944, -1.9316247551329202, -1.895526437673917, -1.8481616060237949, -1.7904636737881638, -1.7235642766174946, -1.6487691369622683, -1.5675299755542615, -1.4814131188966018, -1.3920655306944851, -1.3011790563031003, -1.21045371142157, -1.1215608684004146, -1.036107195121938, -0.9556001824294601, -0.8814160569968339, -0.8147708183106213, -0.7566950625179669, -0.7080131641399138, -0.6693272813163862, -0.6410065339180693, -0.6231815793827764, -0.6157446815563523, -0.6183552363088173, -0.6304505874665474, -0.6512618408262537, -0.679834265757443, -0.7150517660286209, -0.7556648066203236, -0.8003211037026027, -0.8475983225629533, -0.8960379845531895, -0.9441797600983672, -0.9905953210071238, -1.0339209417717583, -1.0728880757785728, -1.1063511874072136, -1.1333121934627655, -1.1529409554081202, -1.1645913652195934, -1.1678126798218165, -1.162355879154922, -1.1481749479822034, -1.1254231084380886, -1.0944441558845153, -1.0557591717683386, -1.0100490008510103, -0.9581329836039119, -0.9009445251796605, -0.8395041579578066, -0.7748908133780598, -0.7082120591967593, -0.640574079473565, -0.5730521760394289, -0.5066625519325342, -0.44233609982832606, -0.38089486282523405, -0.3230317625261695, -0.26929410204270965, -0.22007125158027271, -0.17558681418955163, -0.135895451893745, -0.10088443070505307, -0.07027982011487119, -0.04365716159622479, -0.020456304560241324, -1.8013499053311168e-16], [0.0, 0.017798762569482127, 0.03489744982817743, 0.052181033850437625, 0.07053566536203093, 0.0908208173905689, 0.11384207422552622, 0.14032530019765785, 0.17089288808239006, 0.2060427342093976, 0.24613051794212978, 0.29135577881907654, 0.3417521874436548, 0.39718229861742405, 0.457336959941603, 0.5217394290705601, 0.5897541310177306, 0.6605998664669197, 0.7333671659785521, 0.80703937624424, 0.8805169658978741, 0.9526444523526256, 1.0222392799044087, 1.0881219247599752, 1.149146466134835, 1.204230845095987, 1.2523860348959233, 1.2927433681687455, 1.3245793070592757, 1.3473370011770387, 1.3606440537999938, 1.3643260071690375, 1.3584151608097819, 1.3431544500683077, 1.3189962326696907, 1.2865959561292188, 1.2468008051779427, 1.2006335528780185, 1.1492719587091225, 1.0940241686293875, 1.0363006731660855, 0.9775834674437638, 0.9193931295028432, 0.8632545884683177, 0.8106623906861808, 0.763046288902456, 0.7217379764453189, 0.6879397652078891, 0.6626959635345944, 0.646867648886091, 0.6411114518525086, 0.6458628745802854, 0.6613245602283796, 0.6874598132502572, 0.7239915459417353, 0.7704066978226229, 0.8259660441670545, 0.8897191815352958, 0.9605243546190024, 1.0370726731044901, 1.117916162404273, 1.2014990005630382, 1.286191217643541, 1.37032407529259, 1.452226304404767, 1.530260358807918, 1.6028578431715017, 1.6685532938724592, 1.726015531832511, 1.7740758653731201, 1.8117524974668295, 1.8382705835225768, 1.853077490776192, 1.8558529258943537, 1.846513720711558, 1.825213194088779, 1.7923351375799261, 1.7484826007524248, 1.6944617755079578, 1.6312613945841372, 1.5600281647760847, 1.4820388477491009, 1.3986696783947712, 1.3113638706669377, 1.221598002299396, 1.130848091790499, 1.0405561830601056, 0.9520982352531095, 0.8667540777852831, 0.7856801348841682, 0.7098855510072002, 0.6402122604757514, 0.5773194436730793, 0.5216727007576013, 0.4735381548334962, 0.4329815728743352, 0.3998724674955813, 0.37389301903415584, 0.3545515383869357, 0.341200079632454, 0.33305571036325776, 0.3292248593789918, 0.32873008809609694, 0.33053857550437027, 0.3335915681066497, 0.3368340269229025, 0.33924370375364593, 0.33985889842178535, 0.33780418710258714, 0.33231346809308526, 0.3227497440034744, 0.3086211465039375, 0.28959280919943, 0.26549430339515906, 0.23632246767846543, 0.20223958242782172, 0.16356696151854855, 0.12077415255746811, 0.07446405093069995, 0.025354338906374403, -0.025744243683368268, -0.07795220845944825, -0.1303475514584066, -0.18199320411740919, -0.23196496432393773, -0.27937915648764744, -0.3234192757947372, -0.36336089714753333, -0.3985941731432452, -0.42864330670869116, -0.45318246114572175, -0.4720476614173335, -0.4852443432268725, -0.49295031822649693, -0.4955140417194305, -0.49344819051651284, -0.4874186801077607, -0.47822936894161383, -0.46680281036280974, -0.4541575167823607, -0.4413822932916421, -0.42960827682040625, -0.4199793800490924, -0.4136218849843057, -0.41161395819068364, -0.4149558674040957, -0.42454166737430293, -0.44113309153344454, -0.46533633617813974, -0.4975823564730862, -0.5381112103566399, -0.5869608893765488, -0.643960966978305, -0.7087312774714868, -0.7806857156976885, -0.8590411213571755, -0.9428310861388102, -1.030924399357377, -1.122047731777144, -1.214812050580225, -1.3077421636892619, -1.3993087112518747, -1.4879618580652185, -1.5721658946891446, -1.6504339281497216, -1.7213618361859564, -1.7836606721657193, -1.8361867408211647, -1.8779686170700858, -1.9082304501659686, -1.9264109815844563, -1.9321778053347292, -1.9254365113588623, -1.906334473638246, -1.8752591716275149, -1.8328310635955702, -1.7798911602072318, -1.717483573066763, -1.646833432885358, -1.5693206825038337, -1.4864503485023126, -1.3998199791581634, -1.311085004022966, -1.2219228197341714, -1.1339964366566204, -1.0489185308373101, -0.9682167353192171, -0.8933009743597072, -0.8254335942903173, -0.7657029768639876, -0.7150012366317696, -0.6740065052424736, -0.6431701949848608, -0.6227095141014078, -0.6126053803270994, -0.6126057498287308, -0.6222342493971119, -0.6408038735303572, -0.667435388014625, -0.7010799706761353, -0.740545520833842, -0.7845259840203569, -0.8316329698015308, -0.8804288896510224, -0.9294608100217243, -0.9772942037251844, -1.0225457907184263, -1.063914687146452, -1.1002111282517824, -1.1303820953263681, -1.1535332575949404, -1.168946734735714, -1.1760942922734716, -1.1746456976456134, -1.1644720864506564, -1.1456443132013028, -1.1184263857117487, -1.0832642039490838, -1.040769939753803, -0.9917025004261153, -0.9369446141543044, -0.8774771562954536, -0.8143514006267994, -0.7486599272886282, -0.6815069480983389, -0.6139788195595662, -0.5471155040337837, -0.4818837104867239, -0.4191523987504963, -0.3596712665969478, -0.30405275876933674, -0.252758043525149, -0.20608729759464056, -0.16417452742350275, -0.12698703601745137, -0.09432952365059111, -0.06585269020662443, -0.04106609004441236, -0.019354879975318248, -1.7177933406592038e-16], [0.0, 0.017264118740909374, 0.034250352547373256, 0.0518330995976668, 0.07087308601396637, 0.0921902095923175, 0.11653743086126579, 0.1445764173842994, 0.1768556026976955, 0.21379125970800433, 0.25565211130873905, 0.3025479103518128, 0.3544223192068996, 0.411050308528306, 0.4720401783131809, 0.536840184818257, 0.6047496374247241, 0.6749342131254055, 0.7464451259055138, 0.8182416867019682, 0.8892166994436526, 0.9582240622015017, 1.0241078816785343, 1.0857323657223008, 1.1420117333928268, 1.1919393760568753, 1.2346155162168047, 1.269272643049976, 1.2952980541868615, 1.312252900888942, 1.3198872168683145, 1.3181505074980973, 1.3071975837354766, 1.287389441075846, 1.2592891054198567, 1.2236524918628255, 1.1814144460353233, 1.1336702576674569, 1.0816530495321102, 1.0267075490145772, 0.9702608416544963, 0.9137907837987383, 0.8587928130275879, 0.8067459387061707, 0.7590787197403044, 0.7171360417186473, 0.6821474909214418, 0.6551980884783833, 0.6372020950529957, 0.628880526068911, 0.6307429313566818, 0.6430738932605325, 0.6659245861149714, 0.699109620273886, 0.7422092684567378, 0.7945770441176246, 0.8553524739611661, 0.9234787827334544, 0.9977250910304105, 1.0767126189535865, 1.1589442926385285, 1.242837069321039, 1.3267562316781212, 1.409050855266001, 1.488089625120773, 1.5622961696615734, 1.6301830921302147, 1.690383911613618, 1.7416821764413626, 1.7830370811838139, 1.813605002915955, 1.8327564707886916, 1.8400881928520922, 1.835429882813847, 1.8188457540866423, 1.7906306760337634, 1.751301114649416, 1.701581103904941, 1.6423836116363404, 1.574787772284591, 1.5000125554009458, 1.419387521262728, 1.334321381231199, 1.2462691290425012, 1.1566985389157411, 1.0670568365151314, 0.9787383392255109, 0.8930538331883123, 0.8112024068732727, 0.7342463958635594, 0.6630900126701731, 0.5984621408130469, 0.5409036664934586, 0.4907596065927479, 0.44817617133208176, 0.41310277672131346, 0.3852988989780385, 0.3643455434642958, 0.34966098733156364, 0.34052035078594245, 0.3360784592535064, 0.3353953800138088, 0.337463953998647, 0.34123859794534245, 0.34566462503433026, 0.3497073241520809, 0.35238004914658316, 0.35277059954728623, 0.3500652223958978, 0.34356962981906064, 0.33272650708975043, 0.31712907911544347, 0.29653040717698115, 0.2708481996765627, 0.24016503779188644, 0.20472403630385758, 0.16492007844273682, 0.12128687837987523, 0.07448023307538211, 0.02525792384295873, -0.025543185282380046, -0.07703223268218833, -0.12829095145560043, -0.17840105327820652, -0.22647166733423635, -0.2716660958736427, -0.3132271649525481, -0.35050048447047105, -0.38295498483051144, -0.4102001670835436, -0.43199958752687473, -0.4482801942955429, -0.45913724007888124, -0.464834609029665, -0.4658005143337975, -0.46261864278528675, -0.4560149410330513, -0.44684035193687194, -0.4360499158030553, -0.42467874746239065, -0.4138154837494414, -0.40457386480103885, -0.39806316493635624, -0.3953582233450867, -0.3974698404729795, -0.405316302403142, -0.4196967727155688, -0.44126724977536036, -0.47051972812976833, -0.5077651271082504, -0.5531204596509145, -0.6065006120370723, -0.6676149930560371, -0.7359691920148388, -0.8108716617509931, -0.8914453185597506, -0.9766438287343132, -1.0652722342894068, -1.1560114613105628, -1.247446155967952, -1.3380952080200743, -1.4264442517532727, -1.5109793815276773, -1.590221284780107, -1.6627589803668446, -1.7272823549373448, -1.7826127145490729, -1.827730612413527, -1.8618002754819338, -1.8841900310646218, -1.8944882279482869, -1.8925142522807692, -1.878324354273526, -1.852212124719221, -1.8147035874481787, -1.7665470020592795, -1.7086975974353693, -1.642297577614296, -1.5686518545815282, -1.4892000647217538, -1.4054855145212688, -1.319121774481796, -1.2317576962996204, -1.1450416658143197, -1.0605859221272549, -0.979931771199277, -0.9045165002163907, -0.8356427576059045, -0.7744511038128262, -0.721896361274967, -0.6787283003463739, -0.645477093459284, -0.6224438551433267, -0.6096964634430514, -0.6070707317755878, -0.6141768724389953, -0.630411066937129, -0.6549718370989637, -0.6868807975863533, -0.7250072675549679, -0.7680961294459283, -0.8147982483030077, -0.8637027074173892, -0.9133700768622668, -0.962365911502992, -1.0092936747879646, -1.0528263039880537, -1.0917356710211183, -1.124919249565086, -1.1514233723761715, -1.170462550727609, -1.1814344284467384, -1.1839300536268762, -1.1777392689542636, -1.1628511437755764, -1.1394494944928664, -1.1079036615413735, -1.0687548280632304, -1.0226982745453823, -0.9705620624497908, -0.9132827257996294, -0.8518786206931103, -0.7874216370700131, -0.7210080134471223, -0.6537290129113011, -0.5866422170284181, -0.5207441735892306, -0.45694509484410345, -0.3960462461145313, -0.3387205918849506, -0.2854971795463778, -0.23674964210939353, -0.1926890929491906, -0.15336157074376933, -0.11865007413536077, -0.08828110629297045, -0.06183553250324158, -0.03876344213023126, -0.01840260258950546, -1.6483396539325375e-16], [0.0, 0.016876283018268032, 0.03388644054155189, 0.051886582476702636, 0.07170486633234505, 0.09411526342708693, 0.11981275294347196, 0.14939061568378156, 0.1833204457368117, 0.22193542867070665, 0.26541735107710546, 0.31378771041633435, 0.36690318856833004, 0.4244556399412944, 0.4859766282708057, 0.5508464283053561, 0.6183072924035787, 0.687480670606751, 0.7573879688266008, 0.8269743360468961, 0.8951348902704123, 0.9607427264317284, 1.0226779993581248, 1.0798573424056166, 1.1312628684942656, 1.1759700053231221, 1.2131734404934353, 1.2422104945697943, 1.262581299763308, 1.2739652374940955, 1.2762331777470495, 1.2694551646846006, 1.2539033039312564, 1.230049724565507, 1.1985596102414644, 1.1602794160113834, 1.116220507301122, 1.0675385721231234, 1.0155092641387473, 0.961500629941063, 0.9069429565189155, 0.8532967422020555, 0.8020195447671323, 0.7545324925123372, 0.7121872571401158, 0.67623428084689, 0.6477930242110195, 0.6278249568766285, 0.617109950697112, 0.6162266564119641, 0.6255373519701363, 0.6451776455248975, 0.6750513014525399, 0.7148303362726991, 0.7639604060242726, 0.8216713805284666, 0.8869928761227367, 0.9587743998966971, 1.035709648096438, 1.116364401881851, 1.1992073774515408, 1.2826433167969744, 1.3650475517389402, 1.4448012387442302, 1.5203264461754955, 1.5901202794768823, 1.6527872532446517, 1.7070691615979676, 1.751871758707916, 1.7862876382797659, 1.809614792329695, 1.8213704335102514, 1.821299778976125, 1.8093796145617325, 1.7858165829134856, 1.7510402651341077, 1.7056912493836858, 1.6506044987256319, 1.5867884414167572, 1.5154003071291977, 1.4377183198335042, 1.3551114301661602, 1.2690073253270884, 1.180859491596717, 1.0921141225714106, 1.004177664804217, 0.9183857717975631, 0.8359743977954543, 0.7580537055948792, 0.6855853891063179, 0.619363923505612, 0.5600021557505873, 0.5079215384984205, 0.46334719380015094, 0.4263078722786203, 0.3966407518197962, 0.37400090014741666, 0.3578751109725724, 0.34759971654821753, 0.3423818830476905, 0.3413238115943591, 0.343449199039968, 0.34773126039100927, 0.3531215803680945, 0.35857904575932903, 0.36309811333508296, 0.3657356899949024, 0.3656359419137449, 0.3620524066865389, 0.3543668553519031, 0.34210443783266264, 0.32494474354520114, 0.30272851619730917, 0.27545987538725347, 0.2433040146517678, 0.20658046312133693, 0.16575211295230244, 0.1214103243076127, 0.07425652108076568, 0.02508078123782188, -0.025261996700503317, -0.07587770686195477, -0.1258597386611619, -0.17431605029051603, -0.2203958846076765, -0.26331540780338036, -0.30238157856608894, -0.3370136006011399, -0.366761373177338, -0.39132043130838945, -0.41054295729358536, -0.4244445463714193, -0.4332065186343659, -0.43717368435278964, -0.43684758755661146, -0.43287537014947947, -0.42603451300900763, -0.41721381856313294, -0.40739109848169847, -0.39760811785774297, -0.3889434213308058, -0.382483725119487, -0.3792946003644371, -0.38039119644242203, -0.38670975735708346, -0.3990806697720364, -0.41820374803101956, -0.4446264103795782, -0.47872533278400164, -0.5206920838759093, -0.5705231486540071, -0.6280146419965533, -0.6927618983986987, -0.7641640044745086, -0.8414332186172184, -0.9236091008194813, -1.0095770580325598, -1.0980908995173628, -1.1877988951793432, -1.277272740423961, -1.3650387558674042, -1.4496105911898667, -1.5295226610309485, -1.603363518170853, -1.6698083659289138, -1.7276499278786237, -1.775826928281856, -1.8134494902678215, -1.8398208294565308, -1.8544547067616073, -1.857088203432646, -1.8476894916127171, -1.826460392120914, -1.7938336349464827, -1.750464864049318, -1.6972195534299006, -1.6351551230038845, -1.5654986576265557, -1.4896207378580217, -1.4090059841711826, -1.3252209950071925, -1.239880421455167, -1.154611965851267, -1.0710211171710569, -0.9906564421049605, -0.9149762370169965, -0.8453173129294045, -0.7828666340633799, -0.7286364615653301, -0.6834435695479275, -0.6478930025458064, -0.6223667343266479, -0.607017470380576, -0.601767713208908, -0.606314083756738, -0.6201367670513113, -0.6425138283725048, -0.6725400310546904, -0.7091496810989572, -0.7511429297259608, -0.7972148850923136, -0.845986820545532, -0.8960387205241418, -0.9459423776053841, -0.9942942458862764, -1.039747267002142, -1.0810409153071894, -1.1170287572625284, -1.1467028856455126, -1.169214670139619, -1.183891360139904, -1.1902481808426661, -1.1879956772423896, -1.1770421796956194, -1.157491386263541, -1.1296351780896332, -1.0939419016024756, -1.0510404624475984, -1.0017006780029243, -0.9468104256112164, -0.8873502000570845, -0.8243657544637479, -0.7589395422206988, -0.6921617027447877, -0.6251013402492813, -0.558778832144561, -0.494139872590149, -0.43203190789407675, -0.3731835551880673, -0.31818751578088833, -0.2674874018602925, -0.22136879214457508, -0.17995472130227413, -0.14320569227732732, -0.11092418301115455, -0.08276350242292642, -0.058240737845915914, -0.036753430270488295, -0.017599517388107163, -1.592800982693119e-16], [0.0, 0.016629746025206414, 0.03379098970558886, 0.052314234069884204, 0.07298844259560186, 0.09653593514676855, 0.12358906767492558, 0.1546693284988281, 0.19016942197207437, 0.23033883360066795, 0.2752732811182897, 0.32490835592376005, 0.379017551158261, 0.43721475927916215, 0.4989612061386607, 0.5635766732291584, 0.6302547478346432, 0.6980817351675229, 0.7660587698591204, 0.8331265788746715, 0.8981922762226482, 0.9601575135686932, 1.0179472715074207, 1.0705385548308601, 1.116988252252879, 1.156459436834137, 1.1882454174647743, 1.2117909034059777, 1.2267097118307562, 1.2327985308931289, 1.2300463460786366, 1.218639243113197, 1.1989604139355272, 1.1715853103764098, 1.1372720103135137, 1.096946980204186, 1.0516865330799499, 1.0026943894454734, 0.9512758473547404, 0.8988091547612068, 0.8467147498718945, 0.7964230918392201, 0.7493418432526837, 0.7068231865283561, 0.6701320578745305, 0.6404160649436033, 0.6186778179416225, 0.6057503496998242, 0.6022762293016625, 0.6086908880009823, 0.625210577429166, 0.6518252708581193, 0.6882967012100314, 0.7341616074282111, 0.7887401367165968, 0.8511492270425683, 0.9203206751809447, 0.9950234833639138, 1.0738899750325936, 1.155445079767007, 1.2381381114126955, 1.320376303582814, 1.400559324557904, 1.4771139701612102, 1.5485282290282631, 1.6133839299155326, 1.6703872149300767, 1.718396134970982, 1.7564447329695678, 1.78376306500262, 1.799792706962715, 1.80419740281496, 1.7968686269007346, 1.7779259544220565, 1.747712258184573, 1.7067838728702163, 1.655895987551573, 1.595983639944188, 1.5281387892826757, 1.4535840361989687, 1.373643635369056, 1.2897125081216443, 1.203224006206882, 1.1156172034752818, 1.0283044987423449, 0.9426403005079927, 0.859891532828966, 0.7812106523352309, 0.7076118004076958, 0.6399506335720799, 0.5789082812572791, 0.5249797755760801, 0.47846718532812665, 0.439477568807587, 0.4079257401501402, 0.38354172485385235, 0.36588266470839603, 0.3543488235210962, 0.3482032454207091, 0.3465945295994853, 0.34858211127320504, 0.35316338020040705, 0.35930192671501776, 0.3659561818717585, 0.37210771350964134, 0.3767884538693833, 0.37910616645378126, 0.37826750923914, 0.37359811684056327, 0.364559204113899, 0.3507602858942034, 0.33196770977038675, 0.3081088083770001, 0.27927159186384465, 0.2457000170875256, 0.2077849847217952, 0.1660513260056725, 0.12114114444632157, 0.07379397185091685, 0.024824280203507704, -0.02490304094397324, -0.0744985794526658, -0.12307497042309644, -0.16977342585346566, -0.21378950999804316, -0.25439746552300074, -0.2909724326508453, -0.3230099575098479, -0.3501422555011815, -0.3721507789104944, -0.3889747331199047, -0.40071529022159236, -0.4076353599594974, -0.4101548929244533, -0.4088418068931062, -0.40439874119736796, -0.3976459531495034, -0.38950077205719114, -0.3809541176591823, -0.3730446685646172, -0.3668313304671537, -0.36336470187067343, -0.3636582655518694, -0.3686600461776487, -0.3792254680296502, -0.39609212176839437, -0.4198571061640315, -0.4509575507484834, -0.4896548498502477, -0.5360230492941225, -0.5899417263649558, -0.6510935939202671, -0.7189669434948781, -0.7928629227388129, -0.8719075225275954, -0.9550680315607486, -1.0411736041446213, -1.1289394829358927, -1.2169943253029103, -1.3039100019812164, -1.3882331718753513, -1.4685178888386887, -1.5433584662821902, -1.6114218143143604, -1.6714784721267415, -1.7224315853699947, -1.7633431237025774, -1.7934566964705658, -1.812216403098503, -1.8192812473490827, -1.8145347489105974, -1.798089499269934, -1.7702865287708556, -1.7316894752258924, -1.683073668439013, -1.6254103664826611, -1.5598464955929738, -1.4876803532680423, -1.4103338309447235, -1.3293217961244053, -1.2462193419762508, -1.1626276636015447, -1.080139353044467, -1.000303918979242, -0.9245943314534381, -0.8543753672599446, -0.7908744880544833, -0.7351559222963384, -0.688098544962426, -0.6503780576570829, -0.6224538684467903, -0.6045609580163472, -0.5967068993263216, -0.598674074767184, -0.6100270108591368, -0.6301246288593695, -0.6581370931721546, -0.6930668310417689, -0.7337731992719707, -0.7790001890209318, -0.8274064901051221, -0.8775971833738184, -0.9281562948374215, -0.9776794291518304, -1.024805703118716, -1.0682482219257625, -1.1068223813221008, -1.1394713367502949, -1.1652880541584432, -1.1835334449275163, -1.1936501868605058, -1.1952719419951912, -1.188227797400747, -1.17254187422234, -1.1484281700846484, -1.1162808175802432, -1.0766600540399849, -1.0302743023320535, -0.9779588564894127, -0.9206517472148522, -0.8593674287743981, -0.7951689788529641, -0.7291395354121548, -0.6623537087020106, -0.5958497020393, -0.5306028519443133, -0.46750125735739545, -0.4073241100126393, -0.3507232651242233, -0.29820850521615433, -0.2501368524067031, -0.20670617823034457, -0.16795324784313623, -0.13375622006001697, -0.10384150903814465, -0.07779480047562605, -0.055075907795248104, -0.03503705464187529, -0.01694408164346088, -1.5508458470450388e-16], [0.0, 0.01651761714154755, 0.03394674678213825, 0.053085428256424365, 0.07467738016182165, 0.09938821635441879, 0.12778377425513512, 0.1603111447819355, 0.19728292368240646, 0.23886512105898933, 0.285069071550161, 0.33574758433560076, 0.39059546248039045, 0.44915440789356287, 0.5108222142139749, 0.5748660381371565, 0.6404394328952364, 0.7066027285112849, 0.7723462545924185, 0.836615825072717, 0.8983398424269242, 0.956457333048976, 1.009946196925493, 1.057850944202806, 1.0993091990658364, 1.1335762773784432, 1.160047188181734, 1.1782754693718416, 1.1879883432275637, 1.1890977660962248, 1.1817070463023969, 1.1661128127660394, 1.1428022312298711, 1.1124454825707835, 1.0758836354923507, 1.0341121610370738, 0.988260445950672, 0.93956776323967, 0.8893562487507286, 0.8390015099908416, 0.7899015557463629, 0.7434447807587217, 0.7009777675964737, 0.663773677186021, 0.6330019899422824, 0.6097003312559863, 0.5947490688866295, 0.5888493066654619, 0.5925048203361137, 0.6060083892390579, 0.6294328741035798, 0.6626272789526299, 0.7052179167773439, 0.7566146770778842, 0.8160222715566763, 0.8824562151597302, 0.9547631861985171, 1.0316453042204734, 1.1116877701987882, 1.1933892327827031, 1.275194178765961, 1.3555265971977797, 1.43282413587159, 1.5055719570325972, 1.572335506338079, 1.631791435208354, 1.6827559610829366, 1.724210011660198, 1.7553205764432858, 1.7754577799516242, 1.7842072935593816, 1.7813778145829655, 1.7670034592308406, 1.741341037470934, 1.7048622998014713, 1.6582413653597163, 1.6023376548633332, 1.5381747577806737, 1.4669157583024848, 1.389835626839196, 1.3082913509186505, 1.2236905299048655, 1.137459190705605, 1.051009595831505, 0.9657088105169219, 0.8828487722809982, 0.8036185649259094, 0.729079540609917, 0.6601438597850064, 0.5975569313203939, 0.5418841362447115, 0.4935021107090183, 0.4525947496935332, 0.41915397549527916, 0.3929851970615908, 0.37371727070130983, 0.36081666246935906, 0.3536054103016535, 0.35128239229047037, 0.35294732858264144, 0.3576268801782441, 0.3643021599594301, 0.3719369407325882, 0.37950583263070786, 0.3860217081515009, 0.39056167719620594, 0.3922909560660808, 0.3904840323739694, 0.38454260073367474, 0.3740098300263289, 0.35858061981312395, 0.3381076086020341, 0.31260280751068864, 0.28223484658710574, 0.24732193477475925, 0.2083207453615321, 0.165811543932461, 0.12047997269761734, 0.07309599114514012, 0.02449054610415845, -0.02446939735073118, -0.07290679063301722, -0.11996070372542034, -0.16481208949054837, -0.20670841637941784, -0.24498650482188136, -0.279092948793685, -0.3086015661954536, -0.33322739818233243, -0.35283686651953805, -0.36745379716462256, -0.37726112508926574, -0.38259820715375986, -0.38395378380961354, -0.38195474364585336, -0.37735095444361005, -0.37099652767869484, -0.36382797768697295, -0.35683981957819444, -0.3510582193294711, -0.3475133635241086, -0.34721125352084387, -0.3511056484548845, -0.3600708828396226, -0.37487626756646336, -0.3961627481588659, -0.4244224420446349, -0.4599816086173465, -0.502987523613194, -0.5533996348424746, -0.6109852719042567, -0.675320070749965, -0.7457931576071742, -0.8216170187098623, -0.901841865435976, -0.9853741917339183, -1.070999114937782, -1.157405994871136, -1.2432167419351616, -1.3270161547901662, -1.4073835740469327, -1.482925101473343, -1.5523056155554995, -1.614279814345874, -1.6677215354356116, -1.711650640193261, -1.7452568042515781, -1.7679196272981612, -1.7792245608335178, -1.7789742506395139, -1.767194998880566, -1.7441381664157956, -1.7102764562219717, -1.666295140885376, -1.6130784179408924, -1.5516911934704336, -1.4833567039725841, -1.409430486402484, -1.3313712940135907, -1.250709629065063, -1.1690146207931595, -1.087860016878895, -1.0087900780019086, -0.9332861674290925, -0.8627348108874473, -0.7983979666226344, -0.7413861924123953, -0.6926353266872349, -0.6528872165124121, -0.6226749280693198, -0.6023127678148603, -0.5918913273198508, -0.5912776447046378, -0.6001204535318888, -0.6178603689584213, -0.6437447438376085, -0.6768468171484082, -0.716088676283188, -0.7602674657946331, -0.8080842003266058, -0.8581744804304118, -0.909140368199734, -0.9595826561211243, -1.0081327577581713, -1.0534834629302805, -1.0944178325109035, -1.1298355580017092, -1.1587761773542, -1.1804386194242693, -1.194196642917934, -1.199609839371233, -1.1964299810102224, -1.1846026104817546, -1.1642638875421005, -1.1357328249067737, -1.0994991587001415, -1.056207205499948, -1.006636155224015, -0.9516773346658991, -0.8923090482612446, -0.8295696589126732, -0.7645296110649415, -0.6982631197743218, -0.6318202527733855, -0.5662001174694554, -0.5023258318644797, -0.44102190842496575, -0.3829946142659016, -0.3288157913362143, -0.2789105286474385, -0.2335489773105952, -0.1928424908157449, -0.15674416035443858, -0.1250537009018111, -0.09742653112967181, -0.07338678186273054, -0.052343866454002165, -0.03361215470067685, -0.016433212063027367, -1.5220054590144855e-16], [0.0, 0.016531725372860746, 0.03433416375844152, 0.05416655560431569, 0.0767219471198915, 0.10260489817575161, 0.13231160126881011, 0.1662129534666242, 0.20454104704116588, 0.24737945623828178, 0.2946575995328344, 0.3461493512692016, 0.40147596644770656, 0.46011327037547767, 0.5214029537917724, 0.5845677067193067, 0.6487298234100793, 0.7129328189130244, 0.7761655173342618, 0.837388004849258, 0.8955587886859139, 0.9496624679768273, 0.9987372045140718, 1.0419012815312922, 1.078378056737283, 1.1075186515332724, 1.128821770822165, 1.1419501158002878, 1.1467429339587178, 1.143224344210555, 1.131607178300749, 1.1122921899011693, 1.0858625973201397, 1.053074041724228, 1.0148401573002859, 0.972214060025704, 0.9263661649134554, 0.8785588351724918, 0.8301184483234811, 0.7824055318760441, 0.7367836729909986, 0.6945879412900666, 0.6570935807258079, 0.6254857247189416, 0.6008308685957658, 0.5840507951582801, 0.5758995938821447, 0.5769443430751555, 0.5875499390458413, 0.6078684589829901, 0.637833337187258, 0.6771585201228227, 0.7253426472460478, 0.7816781846053362, 0.8452653197169784, 0.9150303120982144, 0.9897478868691955, 1.0680671616354767, 1.1485405118102463, 1.2296547087126988, 1.3098636099208676, 1.3876216438079265, 1.4614173108724018, 1.5298059238593835, 1.5914408267794538, 1.64510236932342, 1.6897239669556086, 1.7244146468325763, 1.7484775639300638, 1.7614240683111322, 1.7629830109734073, 1.753105089572993, 1.731962153757461, 1.699941509962103, 1.6576353844050797, 1.6058258177647848, 1.5454653728477783, 1.477654134842808, 1.403613570127644, 1.3246578819691497, 1.2421635580979435, 1.1575378447018665, 1.0721869029436428, 0.9874844071883238, 0.9047413287021786, 0.8251776150883287, 0.749896425032455, 0.6798615113426799, 0.6158782644694043, 0.5585788357184883, 0.5084116565561456, 0.46563556031580833, 0.43031859799968286, 0.402341523570396, 0.38140580903560656, 0.3670459385892005, 0.358645626827539, 0.35545751117463464, 0.35662578545360607, 0.36121117206519326, 0.3682175761632323, 0.3766197278501852, 0.3853910986321882, 0.3935313766114153, 0.40009280114170875, 0.4042046914694842, 0.4050955543261469, 0.40211222121630597, 0.3947355455619788, 0.3825922808823383, 0.36546286148947, 0.34328491421207374, 0.31615244070507054, 0.28431072215056474, 0.24814710876514268, 0.2081779627048607, 0.1650321220222595, 0.11943134278011812, 0.07216825400968993, 0.024082423962202046, -0.023964815563900618, -0.0711161083470067, -0.11654368359393065, -0.15947414734074072, -0.1992117874745784, -0.23515976286499435, -0.2668386017061937, -0.29390150360165235, -0.3161460224169705, -0.33352180040261925, -0.3461341261846091, -0.3542431973581996, -0.3582590798635556, -0.3587324682526577, -0.35634146053836857, -0.351874665769828, -0.3462110591488928, -0.34029708592794244, -0.3351215893012843, -0.33168919712164324, -0.33099284599742335, -0.3339861480097601, -0.34155631421003174, -0.35449833994156893, -0.37349113004801193, -0.39907619780700665, -0.43163951101615994, -0.4713969835196468, -0.5183840224310999, -0.5724494425396514, -0.6332539523122362, -0.7002733031699738, -0.7728060781101558, -0.849985980136467, -0.9307983682235507, -1.0141006814880573, -1.098646293542913, -1.183111251148194, -1.2661232764527355, -1.3462923522380599, -1.4222421661578852, -1.4926416641357603, -1.5562359555312688, -1.6118758236529576, -1.6585451244672618, -1.6953854032602833, -1.721717122449169, -1.7370569721990514, -1.7411308270949362, -1.7338820146335636, -1.7154746722546053, -1.686292086328658, -1.6469300261218625, -1.5981852053487868, -1.5410391205890495, -1.4766376267294092, -1.4062667119920944, -1.3313250265168926, -1.253293796642347, -1.1737048200658367, -1.0941072834088037, -1.0160341722355541, -0.9409690535714818, -0.8703140021924782, -0.8053594146237564, -0.7472564095605881, -0.696992451409972, -0.6553707563662994, -0.6229939497642402, -0.6002523416136786, -0.5873170767019996, -0.5841382991464226, -0.5904483516361534, -0.6057699097375954, -0.6294288344650074, -0.6605714146938758, -0.6981855676251358, -0.7411254728997296, -0.7881390363513668, -0.8378975146851807, -0.8890265841260746, -0.9401381054309547, -0.9898618253074029, -1.0368762604792103, -1.0799380351821144, -1.1179089851042974, -1.1497803996147018, -1.174693848050393, -1.1919581229940661, -1.2010619316747368, -1.2016820734102844, -1.1936869537149408, -1.1771354015127704, -1.1522708719534303, -1.119511230743806, -1.0794344238848972, -1.0327604365758796, -0.9803300343619311, -0.9230808561726698, -0.86202149085954, -0.7982042146963292, -0.7326970959652387, -0.666556183550697, -0.6007984891903342, -0.5363764479251666, -0.4741544990321295, -0.41488837142215096, -0.35920758465596275, -0.30760159123882463, -0.26040988988946523, -0.21781633548175974, -0.17984776197188657, -0.14637692262216545, -0.11712964005061108, -0.0916959498985334, -0.06954491896377538, -0.05004272409203588, -0.032473494337789365, -0.016062348010835347, -1.5056814338436888e-16], [0.0, 0.016662732716736958, 0.03493165387386705, 0.05552144454253658, 0.07906971551987464, 0.10611635916139342, 0.1370855791916992, 0.1722710896846007, 0.2118248924524005, 0.255749949514277, 0.3038969664647716, 0.35596539598517063, 0.4115086611290737, 0.4699434881435648, 0.5305631312434282, 0.5925541696616623, 0.6550164630503538, 0.7169857673032748, 0.7774584412626668, 0.8354176173969657, 0.8898601678785332, 0.9398237726437703, 0.9844133886554658, 1.0228264299450405, 1.0543759958830445, 1.0785115298635766, 1.0948363511224557, 1.1031215772730554, 1.1033160425094235, 1.0955519141492696, 1.0801458158619175, 1.0575953769370958, 1.0285712405492633, 0.9939046773379064, 0.9545710609355149, 0.9116695665791205, 0.8663995500245097, 0.8200341492329475, 0.7738917235706626, 0.7293058027202414, 0.6875942586821243, 0.6500284380749829, 0.6178029977837919, 0.5920071746553925, 0.5735981896530801, 0.5633774393475995, 0.5619700639616017, 0.5698084029174225, 0.5871197578456574, 0.6139187814925046, 0.650004701377808, 0.6949634720657487, 0.7481748323154168, 0.8088241260459456, 0.8759186318445145, 0.948308037455879, 1.0247085959674316, 1.1037304116849003, 1.1839072281535936, 1.263728030270117, 1.3416697284343966, 1.4162301662918864, 1.4859606854619152, 1.549497490943239, 1.6055910893845762, 1.653133118412471, 1.6911799475992968, 1.7189725089079204, 1.7359519046799605, 1.7417704422391787, 1.736297853494205, 1.7196225728785859, 1.6920480647572058, 1.6540843091861035, 1.6064346697705774, 1.5499784765315006, 1.4857497575120222, 1.4149126428945413, 1.3387340424768215, 1.2585542596240034, 1.1757562507835266, 1.0917342682396172, 1.007862634338602, 0.9254653877261865, 0.8457875164430909, 0.7699684497081897, 0.6990184209869105, 0.6337982410022095, 0.5750029325612513, 0.5231495816209222, 0.4785696533364257, 0.4414059105642084, 0.4116139581906837, 0.38896832256265584, 0.37307286402838363, 0.3633752149078595, 0.359184837700094, 0.3596942113983308, 0.36400257954693566, 0.3711416339415653, 0.38010246408736015, 0.389863075728257, 0.3994157725583359, 0.40779370379746493, 0.414095906388296, 0.4175102134431898, 0.41733345911265857, 0.41298848274639977, 0.4040375202071679, 0.3901916653054441, 0.3713161871279051, 0.3474315969246575, 0.31871046846500084, 0.2854701255796959, 0.2481614172046858, 0.20735390093599684, 0.16371784835896908, 0.11800356690213046, 0.07101860163541628, 0.023603434556368964, -0.023393662873854058, -0.0691419468292929, -0.1128530067825508, -0.15380439220140096, -0.1913614234347877, -0.22499659700274963, -0.25430605774380266, -0.279022686119927, -0.2990254365169172, -0.31434465939431944, -0.3251632441822618, -0.33181352826097316, -0.3347700274486954, -0.3346381523766597, -0.33213918018300737, -0.3280918494431803, -0.32339103566606653, -0.31898404274156344, -0.3158451104264035, -0.3149487876339639, -0.3172428546570783, -0.32362149361484127, -0.3348994049188133, -0.3517875483864826, -0.3748711512183509, -0.40459057226029704, -0.4412255440671652, -0.4848832329194747, -0.5354904641153269, -0.5927903578470421, -0.656343512294093, -0.7255337579096283, -0.7995783930416555, -0.8775426988418513, -0.9583584236706633, -1.0408458265983718, -1.1237387786491755, -1.2057123414251067, -1.2854121776752792, -1.3614850988981153, -1.432610022452417, -1.4975285957654645, -1.5550747484844325, -1.6042024547959206, -1.6440110271637038, -1.6737673184983306, -1.6929242809500173, -1.7011354144026485, -1.698264734295738, -1.6843919942761185, -1.6598130118126222, -1.6250350615556335, -1.5807674190474559, -1.5279072535143763, -1.4675211800614971, -1.400822885918469, -1.3291473398964404, -1.2539221765992117, -1.1766369151667018, -1.0988107247430365, -1.0219594841683068, -0.947562900724118, -0.8770324516902275, -0.811680893015176, -0.7526940420396315, -0.7011054868481519, -0.6577748047895217, -0.6233697887075159, -0.5983530835138126, -0.582973530254398, -0.5772624023446312, -0.5810346019199276, -0.5938947661147986, -0.6152481164202386, -0.6443157719167469, -0.6801541418674915, -0.721677917436781, -0.7676860984883946, -0.8168904215357105, -0.8679455006357306, -0.9194799556305018, -0.9701277825135631, -1.0185592192692905, -1.0635103772837047, -1.1038109428943266, -1.1384093049355473, -1.166394530933887, -1.1870146952243221, -1.1996911546660454, -1.2040284695194226, -1.199819775861474, -1.1870475289555225, -1.1658796514438612, -1.1366612332638157, -1.0999020390026546, -1.0562601803214848, -1.0065224035863143, -0.9515815236786556, -0.8924116021467968, -0.8300415197744676, -0.7655276290420208, -0.6999261900069308, -0.6342662934401179, -0.569523957670432, -0.5065980510016889, -0.44628864069382373, -0.38927830366637267, -0.33611685498480404, -0.2872098598535819, -0.24281119556775357, -0.20301982419089143, -0.16778082731215493, -0.13689064385950642, -0.11000634340047066, -0.08665866338760912, -0.06626844202651476, -0.04816599129908719, -0.03161287935934822, -0.015825529928593842, -1.5011548028462238e-16], [0.0, 0.016900258635844993, 0.03571586617310471, 0.0571118043688341, 0.08166618324264982, 0.10985136796354489, 0.14201801711694456, 0.17838247010420993, 0.21901783466944286, 0.26384902966180857, 0.3126519355508415, 0.365056698513009, 0.42055512580144316, 0.478512003336361, 0.5381800637197579, 0.5987182367943457, 0.6592127278792266, 0.7187003931439173, 0.7761938191671225, 0.8307074661763392, 0.8812842030173138, 0.9270215473950683, 0.9670969277735675, 1.0007913034979223, 1.02751051675565, 1.0468038030430162, 1.058378954567621, 1.0621137118474195, 1.0580630506774051, 1.046462132365321, 1.0277247921989647, 1.002437551848422, 0.9713492530776854, 0.9353565199628251, 0.8954853620493224, 0.852869328897658, 0.8087247148061208, 0.7643233889392728, 0.7209638886964247, 0.6799414613319409, 0.6425177693719424, 0.6098909884530638, 0.5831670214610597, 0.5633325303330257, 0.5512304471080683, 0.5475385696960234, 0.5527517767153033, 0.567168311334447, 0.5908804883732389, 0.6237700742947794, 0.6655084786898126, 0.7155617811205142, 0.7732005015491602, 0.8375139088501165, 0.9074285528702537, 0.9817306038301149, 1.059091491034985, 1.1380962531413228, 1.2172739465549631, 1.2951294085350855, 1.3701756384717543, 1.4409660454103803, 1.5061258125970771, 1.564381650553605, 1.6145892484581221, 1.6557577884770347, 1.687070957826687, 1.7079039770308877, 1.7178362580392557, 1.7166594102596981, 1.704380423589071, 1.6812199724921832, 1.647605901278731, 1.6041620651335895, 1.5516928113852668, 1.491163488280204, 1.4236774616751555, 1.3504502013141515, 1.2727810657628673, 1.1920234670174004, 1.1095541310536372, 1.0267421883176997, 0.9449188279888417, 0.8653482318261814, 0.7892004680319058, 0.7175269737438266, 0.6512391878312178, 0.5910908153008441, 0.537664112844304, 0.49136048416951583, 0.45239556627490785, 0.42079887641856234, 0.39641797697115094, 0.37892700440837285, 0.36783930213626853, 0.3625237972773399, 0.362224671423026, 0.3660837968851795, 0.37316534506742366, 0.382481923796864, 0.393021566997658, 0.40377488373139586, 0.41376167472798897, 0.42205634300173056, 0.42781146047362845, 0.43027890376639716, 0.4288280381698218, 0.42296050749658626, 0.4123212771473108, 0.39670567589499256, 0.3760622861882011, 0.3504916405151651, 0.32024078984059584, 0.2856939165824863, 0.24735926635031302, 0.2058527671531847, 0.1618787896266453, 0.1162085748845961, 0.06965691604147965, 0.023057723776654167, -0.022760865583523752, -0.06700116981206808, -0.1089197647249977, -0.14784977175665928, -0.18322102812254057, -0.2145775935005389, -0.24159211619903076, -0.26407666313347333, -0.28198970954539126, -0.2954390839516408, -0.30468076878954736, -0.31011356496800324, -0.31226973631720367, -0.31180185501798025, -0.30946616881805544, -0.30610290267128837, -0.3026139890265279, -0.29993879025878417, -0.29902843189713924, -0.30081940493309867, -0.306207118548923, -0.3160200904613075, -0.330995450535007, -0.3517564046227651, -0.378792260401473, -0.41244155638328733, -0.4528787607555192, -0.5001049200668163, -0.5539425411586005, -0.6140348855226708, -0.6798497460261, -0.7506876643918607, -0.8256944367305817, -0.903877646552939, -0.9841268627470303, -1.065237046533206, -1.145934628758786, -1.2249056491510204, -1.3008252940789717, -1.372388130393248, -1.438338311031692, -1.4974990238931578, -1.5488004691482753, -1.5913056813929836, -1.6242335611399579, -1.6469785439513027, -1.6591264135187618, -1.660465855319018, -1.6509954479287379, -1.6309258972409004, -1.60067743205177, -1.5608723950291061, -1.5123231781088757, -1.4560157630902393, -1.3930892338760557, -1.3248117238520405, -1.2525533479358797, -1.177756741748392, -1.1019058883734962, -1.0264939548570926, -0.9529908849210446, -0.8828115007361319, -0.8172848548454053, -0.7576255437389169, -0.7049076478705125, -0.6600419002152954, -0.6237566083209841, -0.5965827650897129, -0.5788436834279421, -0.5706493818632711, -0.5718958348831371, -0.5822690858646855, -0.6012541048607544, -0.6281481609974561, -0.662078372559085, -0.7020229995750664, -0.746835956260392, -0.7952739461069686, -0.8460255625697605, -0.8977416545665918, -0.9490662294432891, -0.9986671572526613, -1.04526594932513, -1.0876659108970472, -1.1247780113032326, -1.1556438748092166, -1.1794553690450338, -1.1955703543453615, -1.2035242539353799, -1.203037209414395, -1.1940166957764937, -1.1765555825413876, -1.1509257396643793, -1.1175673959794752, -1.077074561312435, -1.0301769185369343, -0.9777186764036186, -0.9206349458831229, -0.8599262602838125, -0.7966319011488382, -0.7318027169163014, -0.6664741289724355, -0.6016400099055081, -0.5382280917784061, -0.4770775188097466, -0.41891910012515765, -0.3643587457308044, -0.3138644844310219, -0.2677573682169676, -0.22620646609043296, -0.18922804393387446, -0.15668891858828043, -0.12831386649724266, -0.10369686284112732, -0.08231582865409978, -0.06355047346974445, -0.046702741842701505, -0.03101930563653576, -0.015715491921897525, -1.5075962138870204e-16], [0.0, 0.017233014136307435, 0.03666197535990932, 0.058897684947541405, 0.08445540939795637, 0.11373789174163673, 0.14702147284925032, 0.18444570495185664, 0.2260067489830111, 0.27155474914060745, 0.3207952747302037, 0.3732948135080775, 0.428490195073014, 0.48570172004056733, 0.5441496733829103, 0.602973810907497, 0.6612553286580424, 0.7180407580773188, 0.7723671767935618, 0.8232880872533276, 0.8698992941128719, 0.9113641068988759, 0.9469372071158123, 0.9759865484420717, 0.9980127042292919, 1.0126651371037065, 1.0197549395912695, 1.0192636805348223, 1.0113480875296101, 0.9963403983165108, 0.9747443214974515, 0.9472266564085741, 0.9146047307806136, 0.8778299202200173, 0.837967612924365, 0.7961740739105306, 0.7536707430992139, 0.7117165688425633, 0.671579031194149, 0.6345045460500829, 0.6016889612746529, 0.574248858516225, 0.5531943595009671, 0.5394041034774294, 0.5336030139134446, 0.536343408665233, 0.5479899301736655, 0.5687086826635176, 0.5984608639941332, 0.6370010731436833, 0.6838803628979929, 0.7384539938732424, 0.7998937332978455, 0.867204432766352, 0.9392445161287131, 1.014749914315002, 1.092360900531459, 1.1706512089438168, 1.2481587644154457, 1.3234173114572734, 1.3949882082458942, 1.4614916469285852, 1.5216365745807776, 1.5742486197978638, 1.6182953772473891, 1.6529084654278918, 1.6774018498441687, 1.691286012939501, 1.6942776512496893, 1.6863046869448772, 1.6675064926013685, 1.6382293419759286, 1.5990172129646067, 1.5505981790577132, 1.493866729775894, 1.4298624562618985, 1.3597456230920446, 1.2847702194122428, 1.2062551399647166, 1.1255541880836413, 1.0440256173237645, 0.9630019354871852, 0.8837606843012664, 0.8074968801802034, 0.7352977571047616, 0.6681203928158747, 0.6067727257537777, 0.5518983843403434, 0.5039656544477521, 0.4632608076109888, 0.42988590429538565, 0.4037610760107691, 0.3846311800082634, 0.3720766134242618, 0.36552797268319565, 0.3642841512210521, 0.3675333864177351, 0.3743766970333585, 0.3838530971191128, 0.3949659326465182, 0.4067096639076389, 0.4180964106071751, 0.4281815875928795, 0.4360879870230218, 0.44102770669872976, 0.44232138314503655, 0.4394142602865316, 0.4318887083784473, 0.41947290108266067, 0.4020454588494211, 0.3796359715360039, 0.3524214198104891, 0.3207186206577116, 0.28497292455538975, 0.24574348804371032, 0.20368553304948142, 0.15953008124175386, 0.11406171595635937, 0.06809497421941685, 0.02245000587187582, -0.02207184511240599, -0.06471188076161515, -0.10477666993313316, -0.14165884111733507, -0.17485548618532215, -0.20398367615895707, -0.22879266504783577, -0.24917244372192895, -0.2651584004963347, -0.27693194619922534, -0.2848170664166727, -0.2892728697011532, -0.2908823051051269, -0.2903373228036028, -0.2884208452485979, -0.2859860008687177, -0.2839331456293507, -0.2831852579242802, -0.2846623377262944, -0.2892554704981624, -0.29780122926799113, -0.31105708413363786, -0.3296784673351638, -0.3541981044038608, -0.3850081686569875, -0.42234574874749087, -0.46628203874700425, -0.5167155693078155, -0.5733696990566485, -0.635794479977261, -0.7033729017526775, -0.7753314105644156, -0.8507544904116737, -0.9286029922999787, -1.0077358012268176, -1.086934345156573, -1.1649293762892927, -1.2404293947579776, -1.312150039973213, -1.3788437463325531, -1.4393289486822338, -1.4925181290943732, -1.5374440201057469, -1.573283320026289, -1.5993773323202152, -1.6152490120496923, -1.6206159862468505, -1.615399209820898, -1.5997270219186321, -1.5739344770291246, -1.5385579378945762, -1.4943250307093616, -1.442140174388761, -1.3830660021464023, -1.3183010926301808, -1.2491545170041054, -1.1770177854431765, -1.103334839637229, -1.0295707855265166, -0.957180091443748, -0.8875749903492436, -0.8220948205796698, -0.7619770175834274, -0.7083304300172143, -0.66211157827798, -0.624104403389131, -0.5949039708589967, -0.5749044997142915, -0.5642919836839881, -0.5630415619866693, -0.5709196840266001, -0.5874909982868813, -0.6121297835976923, -0.6440356334799558, -0.6822530040296182, -0.7256941452446835, -0.7731648569951507, -0.8233924458908072, -0.87505520966824, -0.9268127425736273, -0.9773363393316522, -1.0253387770080213, -1.0696027733049824, -1.1090074560560537, -1.1425522309717324, -1.1693775017014498, -1.1887817763278754, -1.2002347854895183, -1.2033863371594196, -1.1980707392042964, -1.1843067305724917, -1.1622929725897442, -1.1323992606419029, -1.0951537208077629, -1.0512263532055408, -1.0014093715472128, -0.9465948645106084, -0.8877503671876246, -0.8258929785351847, -0.7620626923067727, -0.6972956236430897, -0.6325978110390885, -0.5689202538982041, -0.5071358098748381, -0.4480185246461305, -0.3922259009833795, -0.34028453570451256, -0.29257946428420417, -0.2493474558398069, -0.21067439836434917, -0.17649680804853543, -0.14660739000405437, -0.12066447336124092, -0.09820504419723373, -0.07866100756378772, -0.06137822734742141, -0.045637821883813365, -0.030679135941943773, -0.0157237673285409, -1.5240771933344432e-16], [0.0, 0.017648943855769556, 0.03774398356342359, 0.06083794780947726, 0.08738065604913528, 0.11770390126355057, 0.15200970567859476, 0.19036217464114127, 0.2326831803687296, 0.2787520077331241, 0.3282089911289051, 0.3805630674272587, 0.4352030676608056, 0.4914124720255813, 0.5483872615136602, 0.6052564173289573, 0.6611045482876845, 0.714996068482999, 0.7660003040947945, 0.8132168804821968, 0.855800729348475, 0.8929860611460518, 0.9241086699042672, 0.948625975808538, 0.9661342642253238, 0.9763826471588208, 0.9792833526972468, 0.97491803790324, 0.9635399186061752, 0.9455716132388154, 0.9215987046541709, 0.8923591311048461, 0.8587286225934802, 0.8217024989849, 0.7823742390991386, 0.741911313146584, 0.7015288422254499, 0.662461706367615, 0.6259357653153818, 0.5931388827324267, 0.5651924541890224, 0.5431241317226188, 0.5278424131921939, 0.5201137235722382, 0.5205425587315772, 0.5295551914606573, 0.5473873562475909, 0.5740762355682724, 0.6094569685206127, 0.653163794974587, 0.704635837650118, 0.7631274133760466, 0.8277226559411516, 0.89735412908499, 0.9708250118356464, 1.0468343519451664, 1.1240048087232608, 1.2009122459551804, 1.2761164903022153, 1.3481925417401694, 1.4157615109076584, 1.477520564006814, 1.5322711789923171, 1.5789450566436702, 1.6166270857737777, 1.6445748319303808, 1.6622341017885542, 1.6692502289938995, 1.6654748292166606, 1.6509678801311116, 1.62599509331162, 1.5910206569269638, 1.5466955378947762, 1.4938416371595775, 1.4334321894315325, 1.3665688867021089, 1.2944562810106814, 1.218374084439432, 1.1396480316659694, 1.0596200014823705, 0.9796181077744255, 0.9009274672440927, 0.8247623307747521, 0.7522402283283552, 0.6843587245799596, 0.6219753154757558, 0.5657909162341171, 0.5163373009917344, 0.47396875558380314, 0.43885810029587735, 0.41099713143428074, 0.39020142190745255, 0.3761193143783256, 0.36824483856766244, 0.36593418946882805, 0.3684253179011461, 0.3748601110663759, 0.3843085803735957, 0.39579442821828487, 0.408321335726261, 0.4208993003886839, 0.43257035629223656, 0.44243303013946256, 0.4496649228923464, 0.4535428586897555, 0.4534601083413987, 0.4489402724993212, 0.43964749756399135, 0.425392793256245, 0.4061363221450566, 0.3819856356971383, 0.3531899359714771, 0.3201305442807991, 0.2833078554061215, 0.24332514583099643, 0.2008696846979581, 0.1566916647656004, 0.11158152583995908, 0.06634628358637659, 0.021785501288022337, -0.021332449607181253, -0.062293202617189784, -0.10045767017230767, -0.1352812059214875, -0.16633013805421315, -0.19329522471350566, -0.2160016625698149, -0.23441536916857297, -0.2486453564889435, -0.25894211480609153, -0.2656920298592961, -0.26940795985976307, -0.2707161993988054, -0.2703401522858699, -0.2690811223405203, -0.2677967079646665, -0.26737735096607057, -0.26872164092953504, -0.272711012120877, -0.2801844895219214, -0.2919141435950403, -0.3085818996421958, -0.3307583174542209, -0.3588839110519978, -0.3932535178082415, -0.4340041525810375, -0.4811066974942174, -0.5343616837583762, -0.5933993207689106, -0.6576838221504403, -0.7265219710627424, -0.7990757606146801, -0.874378842306438, -0.9513564186114439, -1.0288481275462393, -1.1056333895809973, -1.1804586224752545, -1.2520656792302438, -1.319220829627151, -1.3807435876794596, -1.4355346862690301, -1.4826025163398537, -1.5210873809465941, -1.550282963437176, -1.5696544729313713, -1.5788530075132432, -1.5777257643237417, -1.5663218238734844, -1.5448933410132104, -1.513892084543202, -1.4739613787428454, -1.4259236104402042, -1.3707635719216822, -1.309608010392163, -1.2437018463767184, -1.1743816041566282, -1.1030466650741426, -1.0311290076556667, -0.9600621356839181, -0.8912499156768923, -0.8260360481985869, -0.7656748829516441, -0.7113042560307901, -0.6639209798122555, -0.6243595528817919, -0.5932745806979312, -0.5711273092162149, -0.5581765756203335, -0.5544743750079947, -0.559866131928982, -0.5739956537486213, -0.5963146316365796, -0.6260964472628684, -0.6624539416371202, -0.7043607094191906, -0.7506753997126031, -0.8001684348130896, -0.851550503292959, -0.9035021444710473, -0.9547037186721572, -1.0038650522319377, -1.0497540580427374, -1.0912236612276247, -1.1272364045210037, -1.1568861679763498, -1.1794165111963362, -1.1942352315399865, -1.2009248265732324, -1.199248651029277, -1.189152665197863, -1.170762780322215, -1.1443779145599933, -1.110458977693856, -1.069614101480944, -1.0225805228842537, -0.9702036072206156, -0.913413565545306, -0.8532004737425427, -0.7905882385299097, -0.7266081770250487, -0.6622728811841551, -0.5985510262427767, -0.5363437536289309, -0.4764632144457437, -0.4196138006957905, -0.3663765194634725, -0.31719688212928965, -0.27237658848149504, -0.23206918666030374, -0.19627978672594731, -0.16486880089416284, -0.13755957977734654, -0.1139497139226588, -0.0935256760704607, -0.07568039422984484, -0.059733271027657915, -0.04495210270706543, -0.030576303187719648, -0.01584080595161015, -1.5495823325931208e-16], [0.0, 0.018135374489706722, 0.038935030524830036, 0.06289074328328245, 0.09038502905269537, 0.1216781637813837, 0.15689860142754053, 0.19603705942961186, 0.23894444322884578, 0.2853336818405288, 0.3347854445257024, 0.38675760724481745, 0.4405982393510796, 0.4955617883995275, 0.5508280563640925, 0.6055234861263252, 0.6587442147307027, 0.7095803011963217, 0.7571405028960243, 0.8005769565513038, 0.8391091182386125, 0.8720463315453649, 0.8988084238263006, 0.9189437766637535, 0.9321443770137815, 0.938257428650693, 0.9372931876096304, 0.9294287782973506, 0.9150078464952769, 0.8945360091471458, 0.8686721660287056, 0.8382158425173915, 0.8040908331152853, 0.7673255096141214, 0.7290302434606882, 0.6903724668255683, 0.6525499592009013, 0.6167629944651418, 0.5841860160153192, 0.5559395239207114, 0.5330628576387941, 0.5164885406114285, 0.5070188193986018, 0.5053049806878935, 0.5118299657074262, 0.5268947247957535, 0.5506086669937226, 0.5828844626479791, 0.6234373535057153, 0.6717890171549386, 0.7272759235487379, 0.7890620134111631, 0.8561554241966136, 0.9274288915142861, 1.0016433649311565, 1.077474299015916, 1.1535400153006528, 1.2284314801215854, 1.3007428083062582, 1.3691017842691344, 1.4321996907219188, 1.48881975094248, 1.5378635230027804, 1.5783746327468982, 1.6095592954611109, 1.6308031525530609, 1.6416840372970318, 1.6419803806702424, 1.6316750721383138, 1.6109546984175773, 1.5802041931132484, 1.5399970390318045, 1.49108127024478, 1.4343616200824918, 1.3708782517564333, 1.3017825880578657, 1.2283108236334677, 1.1517557560870624, 1.073437609342161, 0.9946745434507948, 0.9167535488812328, 0.8409024102089873, 0.7682633944365703, 0.6998692736497448, 0.6366222315417496, 0.5792761300202809, 0.5284225274944944, 0.48448074663474866, 0.44769218874267747, 0.41811898686364907, 0.3956469830201691, 0.37999290908306566, 0.37071554843916293, 0.36723055927875903, 0.36882855237776735, 0.3746959388387378, 0.3839379982665894, 0.3956035668604948, 0.4087107091233311, 0.4222727171637227, 0.4353237783308022, 0.4469436652045858, 0.45628083137958136, 0.46257334123885985, 0.4651671208516342, 0.4635310887191154, 0.45726880750729937, 0.44612638904052937, 0.4299964823706997, 0.4089182762120989, 0.3830735498749269, 0.35277890844496457, 0.31847443578102796, 0.2807090904726852, 0.24012325291562786, 0.1974289040359985, 0.15338797611297117, 0.10878946211069865, 0.06442590078897623, 0.02106986984996236, -0.02054888187047403, -0.05976504960105018, -0.09599755484384404, -0.12876696229748658, -0.15771006095618045, -0.18259121271089185, -0.20331015587927556, -0.2199060432958248, -0.23255759256778247, -0.2415793273633278, -0.24741399058001046, -0.2506213103567255, -0.25186339559999127, -0.25188712656160017, -0.2515039857660688, -0.25156784320546577, -0.2529512654363102, -0.25652095959053384, -0.26311298927025834, -0.2735084091405008, -0.28840995847405376, -0.30842043105926864, -0.33402330028328886, -0.36556612477537237, -0.40324719303543605, -0.4471057866214452, -0.49701635266618405, -0.5526867799325295, -0.6136608706887112, -0.6793249959222054, -0.7489188164205136, -0.8215498496482974, -0.8962115647087701, -0.9718045974409646, -1.047160597143086, -1.1210681475598565, -1.1923001493773095, -1.2596420109494224, -1.321919969390847, -1.378028856168744, -1.426958630165772, -1.4678190267007114, -1.4998617126057432, -1.5224993941938914, -1.535321395454857, -1.5381053063990933, -1.5308243941335324, -1.5136505697514693, -1.4869528100102472, -1.4512910414736446, -1.407405603657778, -1.3562025140790053, -1.2987348593565486, -1.2361807301898065, -1.1698182018131935, -1.100997933371223, -1.0311140177871176, -0.9615737566863354, -0.8937670617199799, -0.8290361935458864, -0.7686465425138969, -0.7137591309325112, -0.6654054762480285, -0.6244653985269122, -0.5916482856563946, -0.5674782473704048, -0.5522834965719782, -0.5461901957160752, -0.54912089969163, -0.560797617288439, -0.5807494036154695, -0.6083242884217079, -0.6427052427696186, -0.6829297914125595, -0.7279127928351233, -0.7764718352929797, -0.8273546371084304, -0.8792677943777899, -0.9309061901946699, -0.9809823671622037, -1.0282551696178215, -1.0715569834696008, -1.1098189392734064, -1.142093497195518, -1.1675738994633267, -1.1856100551224302, -1.1957205114092866, -1.1976002635826544, -1.1911242582080948, -1.176346551098936, -1.1534951877548492, -1.1229629785716633, -1.0852944407497989, -1.0411692712545175, -0.9913827981144439, -0.9368239287616681, -0.8784511722838179, -0.8172673559752975, -0.7542936844085748, -0.6905438007565243, -0.6269985050505564, -0.5645817626371209, -0.5041385988854998, -0.44641542418346225, -0.39204326778318965, -0.34152432181024356, -0.29522210969671253, -0.25335549866115464, -0.2159966760336944, -0.18307310674157867, -0.15437338671800058, -0.12955680696232671, -0.10816634798326441, -0.0896447367882491, -0.07335312064310995, -0.05859184547209271, -0.044622773662226015, -0.030692537505876784, -0.016056101521166266, -1.5830222531772738e-16], [0.0, 0.01867916782778503, 0.04020770864736438, 0.06501398826521841, 0.0934121108711045, 0.1255910149718665, 0.1616070597627318, 0.2013803111441625, 0.24469464024095303, 0.29120164790208375, 0.3404283287744678, 0.3917882906852331, 0.4445962517206399, 0.4980854509288857, 0.5514275312017274, 0.6037543865827156, 0.6541814127086047, 0.7018315596972392, 0.7458595625782565, 0.7854757159710357, 0.8199685673997593, 0.8487259272475147, 0.871253632339484, 0.8871915535724174, 0.8963264045730538, 0.8986009864397821, 0.8941195912759903, 0.8831493822931336, 0.8661176683892725, 0.8436050938060482, 0.8163348661754198, 0.785158246422556, 0.7510366190864681, 0.7150205492687688, 0.6782263104169832, 0.6418104335199749, 0.6069428813522134, 0.5747794897895346, 0.5464343409318256, 0.5229527391937469, 0.5052854514512849, 0.4942648459555735, 0.49058352264544697, 0.49477597069547846, 0.507203718980854, 0.5280443633109032, 0.5572847627570005, 0.5947185983980738, 0.6399483837363099, 0.6923919094338793, 0.7512929984919092, 0.8157363441411346, 0.8846661040829399, 0.95690783372857, 1.0311932599670683, 1.1061873277432785, 1.180516896051191, 1.2528004192190023, 1.3216779245892003, 1.3858405894980956, 1.4440592290475476, 1.4952110313383744, 1.5383039179961473, 1.5724979639690553, 1.5971233803515663, 1.6116946456897336, 1.615920462865812, 1.6097093180098667, 1.5931705225248454, 1.5666107266914264, 1.5305260008261756, 1.4855896849862922, 1.4326363081943847, 1.372641970671008, 1.3067016653699661, 1.2360040862109767, 1.1618045280847078, 1.085396526586648, 1.0080829125031743, 0.931146966700717, 0.8558243550355663, 0.7832765003970511, 0.7145660106135532, 0.6506347276719288, 0.5922848968740917, 0.5401638758578461, 0.49475271481037225, 0.456358842909406, 0.4251129944320375, 0.400970403592552, 0.38371619259067374, 0.3729747751509327, 0.3682230005290346, 0.36880667294151914, 0.3739600008442041, 0.38282746140614915, 0.3944875095737553, 0.407977519638962, 0.4223193211984806, 0.4365446814132411, 0.44972009174357885, 0.46097023963608386, 0.469499583362995, 0.47461150037193156, 0.475724544741525, 0.4723854259822211, 0.4642784075143224, 0.45123091650786884, 0.4332152550139786, 0.4103464029692905, 0.38287600417254497, 0.3511827241806951, 0.31575926178789976, 0.27719638100300337, 0.23616440608908112, 0.19339268637542187, 0.14964758859262686, 0.10570961114079536, 0.06235023606791833, 0.020309140084750977, -0.019727624453563988, -0.05714789373541746, -0.09143155805466037, -0.12216613997371464, -0.149059363894031, -0.17194837426047746, -0.19080534689986609, -0.20573933190884336, -0.21699426468277813, -0.2249431816264672, -0.23007877627468995, -0.233000527458351, -0.23439872134315642, -0.23503577134694634, -0.2357253120125682, -0.23730960303111442, -0.24063582622911886, -0.24653189024393024, -0.2557823739726523, -0.26910524023990723, -0.28712993543708776, -0.3103774594925022, -0.33924294418390566, -0.3739812176247006, -0.4146957602135119, -0.46133137421735454, -0.5136707975129505, -0.571335394108053, -0.6337899523355909, -0.7003515185892925, -0.7702020927196069, -0.8424049132767012, -0.9159239691272293, -0.9896462908871503, -1.062406503199854, -1.133013058982533, -1.2002755308935291, -1.2630323046228356, -1.3201780039873379, -1.3706899796355676, -1.4136532114419342, -1.4482830089986531, -1.4739449441984744, -1.4901715135677718, -1.4966751042324231, -1.4933569243408222, -1.4803116543236854, -1.4578276772178587, -1.4263828519407358, -1.3866359002951507, -1.339413583999053, -1.2856939495875408, -1.226586014138377, -1.163306351092003, -1.0971531108532588, -1.0294780735182796, -0.9616573794228187, -0.8950616160617716, -0.8310259564683415, -0.7708210439480456, -0.7156253011302732, -0.6664993080311092, -0.6243628450183978, -0.5899751334169492, -0.5639187305227252, -0.5465874488584332, -0.5381785737155332, -0.5386895507218418, -0.5479192088410068, -0.5654734764388156, -0.5907754414638615, -0.6230795039780274, -0.6614892727324577, -0.7049787695580524, -0.7524164281534426, -0.8025913092698588, -0.8542409038613576, -0.9060798606922399, -0.9568289559935462, -1.005243620461951, -1.0501413532129726, -1.0904273828438902, -1.1251179817396846, -1.153360899998487, -1.17445245834424, -1.1878509233045118, -1.1931858806666369, -1.190263422478504, -1.1790670661676752, -1.1597544291564237, -1.132649786061068, -1.0982327356251367, -1.0571232984868597, -1.0100638524186998, -0.9578983867101399, -0.9015496200703051, -0.8419945752898541, -0.7802392377547547, -0.7172929429568584, -0.654143140001288, -0.5917311637760282, -0.530929618336097, -0.4725219289668439, -0.41718456150380245, -0.3654723363179385, -0.3178071827467601, -0.2744705897431846, -0.2355999124107504, -0.2011885943297261, -0.17109026467544447, -0.14502656963362123, -0.12259850203432855, -0.10330090386153674, -0.08653973559163744, -0.07165163619714017, -0.057925239877495024, -0.04462367159202038, -0.03100761436653307, -0.0163583278462201, -1.6232471968196038e-16], [0.0, 0.01926687663500131, 0.04153437932811081, 0.0671658392724598, 0.0964065783667572, 0.1293751015385808, 0.16605783426697343, 0.2063075567557188, 0.24984558982734903, 0.29626768968369693, 0.3450535116957801, 0.39557940980605405, 0.4471342503279553, 0.4989378391460945, 0.5501614915909147, 0.5999502163688739, 0.647445940362501, 0.6918111710301712, 0.7322524783269214, 0.768043178946321, 0.798544622267269, 0.8232255093023972, 0.8416787224251053, 0.8536352035720991, 0.8589744905106313, 0.8577316028548141, 0.8501000597846267, 0.8364309076273416, 0.8172277352133919, 0.7931377557329142, 0.7649391331789316, 0.7335248268825428, 0.6998833167313531, 0.6650766521734688, 0.6302163380130593, 0.5964376275254625, 0.5648728370900958, 0.5366243252277663, 0.5127377918746082, 0.4941765505552873, 0.48179740685910105, 0.47632874169821887, 0.47835134804975415, 0.488282506433777, 0.5063637087786244, 0.5326523543969129, 0.5670176476224138, 0.6091408265284478, 0.6585197485024109, 0.7144777538188556, 0.7761766252938639, 0.8426333631402897, 0.9127404017034894, 0.9852888111104064, 1.0589939540680222, 1.1325230078931243, 1.2045237158286783, 1.2736537009423776, 1.3386096611764935, 1.3981557657988049, 1.451150591564584, 1.4965719709099794, 1.5335391736385047, 1.5613319066437683, 1.57940569170166, 1.5874032674280978, 1.5851617560399667, 1.572715436275719, 1.550294068276298, 1.5183168218547836, 1.4773819638247268, 1.4282525603786633, 1.371838544473773, 1.3091755835128516, 1.2414012572413136, 1.1697291179148688, 1.0954212529362641, 1.0197600031669165, 0.944019507216386, 0.8694377428182086, 0.7971897209327125, 0.7283624568951576, 0.6639322965580087, 0.6047451151354534, 0.5514998338618683, 0.5047356164398943, 0.4648230156509674, 0.4319592427082643, 0.40616763037416914, 0.3873012580540015, 0.375050605553073, 0.3689550044457724, 0.368417564454752, 0.37272316911818465, 0.3810590623622969, 0.39253748715982123, 0.40621979070019254, 0.42114137853866856, 0.43633688377336177, 0.4508649167775168, 0.4638317763489127, 0.4744135338939328, 0.4818759476218985, 0.48559172250481036, 0.48505470244490195, 0.4798906618794378, 0.4698644528820048, 0.45488335843803246, 0.4349966005843917, 0.41039105103294815, 0.3813832892513291, 0.3484082462996975, 0.3120047596737653, 0.27279844279849813, 0.23148234068880355, 0.18879589894437632, 0.14550281528663303, 0.1023683702304564, 0.06013684553648103, 0.019509635521232162, -0.018875362783494967, -0.05446252873927519, -0.08679496285357097, -0.11552815473120563, -0.14044050432520455, -0.16144040865781625, -0.17856971569668803, -0.19200344175971804, -0.20204574628440536, -0.20912225556180947, -0.21376892262067088, -0.21661770142595022, -0.2183793976141608, -0.21982413298345208, -0.22175992497325842, -0.22500993376434716, -0.23038896707831286, -0.23867985527794167, -0.2506103163618921, -0.26683092169361, -0.28789474898481565, -0.31423926973891936, -0.3461709649968996, -0.3838530971191123, -0.4272969881044785, -0.47635706849867665, -0.5307298674149973, -0.5899570159064362, -0.6534322353306717, -0.7204121819488004, -0.7900309213030514, -0.8613177133753934, -0.9332177044624062, -1.0046150462557288, -1.0743578987011893, -1.1412847224505478, -1.20425123042233, -1.2621573471002043, -1.3139735192880715, -1.358765733283915, -1.3957186206042094, -1.4241560768671555, -1.443558875226666, -1.4535788254846875, -1.4540491110193612, -1.444990525992106, -1.426613432745379, -1.3993153615031892, -1.3636742789455256, -1.320437656393435, -1.2705075696641883, -1.2149221586529015, -1.1548338630125572, -1.091484928768216, -1.0261807473831386, -0.9602616420499305, -0.8950737544933789, -0.8319397083866669, -0.772129732027798, -0.7168339130244994, -0.6671362316226411, -0.623990977611599, -0.5882020994581687, -0.5604059648239695, -0.5410579305984735, -0.5304230300020876, -0.5285709863856008, -0.5353756604576861, -0.5505189323157158, -0.5734989144005536, -0.6036422889028393, -0.640120465709259, -0.6819691670567853, -0.7281109648388101, -0.7773802279176387, -0.8285498814938919, -0.880359339887586, -0.9315429489613922, -0.9808582654428242, -1.0271135077612426, -1.0691935364880338, -1.1060837614392207, -1.1368914259743845, -1.160863785653839, -1.1774027765269446, -1.186075855967373, -1.1866227939645886, -1.1789582927666915, -1.163170415271339, -1.139514905045804, -1.1084055807969027, -1.070401083048017, -1.0261883383843426, -0.9765631847565343, -0.9224086680841957, -0.8646715741581875, -0.8043377993145036, -0.7424071876102502, -0.6798684707222674, -0.6176749393529843, -0.5567214518044672, -0.49782334719945587, -0.44169777859045045, -0.38894791625614716, -0.3400503955048924, -0.29534629822591824, -0.25503586541325096, -0.21917704126621407, -0.18768785068743563, -0.16035251354722035, -0.13683110344257338, -0.11667246825640212, -0.09933004688926136, -0.08418014317305127, -0.07054215602091299, -0.05770021586897881, -0.04492564264482742, -0.03149962071803999, -0.01673548203439063, -1.6690610814058328e-16], [0.0, 0.01988490159520388, 0.04288748700558034, 0.06930515552255116, 0.09931479881186693, 0.13296608647221622, 0.17017831637721803, 0.21074092443314127, 0.2543176528705318, 0.3004542805688205, 0.3485897256159248, 0.3980702416999431, 0.4481663482711272, 0.4980920617804017, 0.5470259335516988, 0.594133350563425, 0.6385895198719883, 0.6796025365361857, 0.7164359292567241, 0.7484300877098075, 0.7750220005204689, 0.7957627724011584, 0.8103324422173493, 0.81855168933384, 0.8203900919300223, 0.8159706861646095, 0.8055706670093912, 0.7896181679737864, 0.7686851554068606, 0.7434765711340672, 0.7148159524094707, 0.6836278481533327, 0.6509174329374396, 0.6177477930954209, 0.5852154208254926, 0.5544245006505536, 0.5264606068573311, 0.5023644496541662, 0.48310631124183845, 0.46956180064609837, 0.4624895282679321, 0.46251125830693124, 0.47009504051333073, 0.48554175347983075, 0.5089754115621177, 0.5403374984557707, 0.5793854946197309, 0.6256956654564862, 0.6786700748838606, 0.7375476871632787, 0.8014193210766708, 0.8692461271910052, 0.9398811733080977, 1.0120936473740472, 1.0845951229849218, 1.1560672817562314, 1.2251904504824003, 1.2906722901030165, 1.351275968541689, 1.4058471606266905, 1.4533392452821345, 1.4928361123475296, 1.5235720477242287, 1.5449482346932721, 1.5565454895214177, 1.5581329389187217, 1.5496724433557518, 1.5313186713443494, 1.5034148330725452, 1.4664841847491623, 1.4212175151532322, 1.3684569207649409, 1.3091762631764068, 1.2444587801272837, 1.1754723876062132, 1.1034432634139937, 1.0296283411311706, 0.9552873666603722, 0.8816551768869834, 0.8099148513767692, 0.7411723636535335, 0.6764333191093752, 0.6165823129996575, 0.5623653756149782, 0.5143758942655404, 0.4730443150909686, 0.43863183407512657, 0.41122818832302466, 0.3907535580787703, 0.37696448961329226, 0.36946365146088084, 0.3677131439347955, 0.3710509966730909, 0.3787104132376195, 0.3898412573542457, 0.4035332237987454, 0.41884009943644873, 0.4348044973974146, 0.45048244032196627, 0.46496717716670044, 0.47741164195302493, 0.4870490014219565, 0.49321079081846486, 0.4953422016155089, 0.49301416024630434, 0.4859319209245085, 0.4739399862619962, 0.4570232643474261, 0.43530446782641874, 0.40903785688253824, 0.37859952143121967, 0.3444744859576742, 0.3072410010425889, 0.2675524567054374, 0.22611741247582615, 0.18367828608600073, 0.14098927569354985, 0.09879410877571089, 0.0578042138417768, 0.018677898827546138, -0.017998907209778904, -0.05172983398492793, -0.08212271106326083, -0.10890127623898464, -0.1319136339627151, -0.15113723137749277, -0.16668021035401748, -0.17877908846637303, -0.18779281772076284, -0.1941933646091598, -0.19855304630121434, -0.20152894319196724, -0.20384478541566628, -0.20627077834259772, -0.20960188777081323, -0.21463514807519474, -0.2221465848782822, -0.23286835711332932, -0.24746672128841984, -0.2665214033450129, -0.29050693113413145, -0.3197764339838388, -0.35454835623483394, -0.39489646043833576, -0.4407434148963448, -0.49185817138303944, -0.5478572444215931, -0.6082099057523525, -0.6722472090526094, -0.7391746630175184, -0.8080882780137217, -0.8779936250040381, -0.9478274674915353, -1.0164814598146936, -1.0828273499550325, -1.145743083506912, -1.2041391786831397, -1.2569847309022533, -1.3033324099565873, -1.3423418329357986, -1.3733007315310528, -1.3956433822440286, -1.408965831187182, -1.4130375200718583, -1.4078090048304395, -1.3934155510509088, -1.3701764887615635, -1.3385903106923993, -1.2993256004762086, -1.2532079778328655, -1.2012033441396672, -1.144397801564459, -1.0839746999206825, -1.0211893356009532, -0.9573418846283112, -0.893749195605596, -0.8317160970592606, -0.7725068866461017, -0.7173176665879681, -0.6672501705818037, -0.6232876927539492, -0.5862736798235096, -0.5568934847055454, -0.5356597048482331, -0.5229014434799172, -0.5187577387128339, -0.5231753063786475, -0.5359106399678962, -0.5565364076051271, -0.5844519841298137, -0.6188978585456977, -0.6589735657227533, -0.7036587085017578, -0.7518365642628823, -0.8023197103153172, -0.8538770565778796, -0.9052616430428679, -0.955238544172896, -1.00261222301319, -1.0462526943580739, -1.0851198883467736, -1.1182856525575293, -1.144952890838812, -1.1644714092507715, -1.1763501217867556, -1.180265358954095, -1.1760651185703168, -1.163769197890433, -1.1435652469566628, -1.1158008823682943, -1.080972096062156, -1.0397082828316337, -0.9927542910124793, -0.9409499710591392, -0.8852077549202556, -0.8264888437953637, -0.7657786119538931, -0.7040618491241386, -0.6422984631970167, -0.581400248708834, -0.522209295226544, -0.4654785641902401, -0.411855104155936, -0.3618663042348057, -0.3159095056360126, -0.2742452036217823, -0.23699397909703343, -0.20413720283638642, -0.1755214584277637, -0.15086653482651227, -0.12977674836181805, -0.11175526940569015, -0.09622105282698575, -0.08252790571436475, -0.06998517230337929, -0.057879475919043286, -0.04549693204201283, -0.032145235956190385, -0.017175033090988966, -1.7192358596351521e-16], [0.0, 0.0205196475375368, 0.0442398674124924, 0.07139194693761128, 0.10208539765019486, 0.13630330945136324, 0.17390125499857767, 0.214609783655277, 0.2580404505103504, 0.3036952334629602, 0.3509791024744981, 0.39921542207906485, 0.4476637932302977, 0.4955398754597021, 0.5420366767964185, 0.5863467583276714, 0.627684773715901, 0.6653097521349104, 0.6985465362765654, 0.7268058052676709, 0.749602145102766, 0.7665696757553359, 0.7774748033425524, 0.7822257361329418, 0.7808784830646316, 0.7736391408059696, 0.7608623680706966, 0.743046041589553, 0.7208221844518286, 0.6949443520559957, 0.6662717512792943, 0.6357504524214068, 0.6043921288815315, 0.573250824483241, 0.5433983012154765, 0.5158985595552062, 0.4917821484539644, 0.4720208918393371, 0.4575036528107955, 0.44901373568620034, 0.44720849015034064, 0.4526016318088827, 0.4655487306478875, 0.48623624474869054, 0.5146743929015771, 0.5506940685299768, 0.5939479007998081, 0.6439154693009916, 0.6999125786816247, 0.7611044015384311, 0.8265222041247362, 0.89508328233154, 0.9656136570703147, 1.036873010567562, 1.1075812898397652, 1.1764463621203483, 1.242192080288964, 1.3035861050779138, 1.3594668352927908, 1.4087688173909416, 1.450546041035556, 1.4839925768361943, 1.5084600751994532, 1.523471719524738, 1.5287323110850195, 1.524134254785847, 1.5097593123634756, 1.4858760900957741, 1.4529333293124538, 1.4115491674428264, 1.3624966326130539, 1.3066857235876106, 1.2451425069894728, 1.178985733291589, 1.1094015303711549, 1.0376167770829223, 0.9648717882987663, 0.8923929565002579, 0.8213659929979398, 0.7529103942701068, 0.6880557262306748, 0.6277202722871715, 0.5726925310213142, 0.5236159777212469, 0.4809774226036914, 0.44509920941037995, 0.41613540335838795, 0.3940720195123923, 0.3787312439469694, 0.36977950301141305, 0.366739142984993, 0.3690033956988958, 0.37585422742283453, 0.3864826003764362, 0.4000106202744984, 0.41551500069648195, 0.4320512467958918, 0.44867794758753315, 0.4644805680490885, 0.4785941494464478, 0.4902243581607934, 0.49866636901572425, 0.503321127487228, 0.5037086047275451, 0.49947773826954367, 0.4904128375940795, 0.4764363252512368, 0.45760777861406154, 0.43411933222904325, 0.4062875937218398, 0.3745423149814001, 0.3394121426524534, 0.3015078457524209, 0.26150348164804116, 0.22011601309616624, 0.17808392729111472, 0.136145431920824, 0.09501681252617586, 0.05537152976509896, 0.017820614665245687, -0.017105114860639033, -0.04897054117119783, -0.07744902303710355, -0.10233211708866129, -0.12353598073245152, -0.14110427934067285, -0.1552075117625525, -0.1661387617423124, -0.1743059762794228, -0.18022096296185658, -0.18448538452983396, -0.1877741081925193, -0.19081633750320967, -0.19437501410375793, -0.1992250238496315, -0.20613077550434056, -0.21582373946560474, -0.22898053833620252, -0.2462021704347768, -0.2679949217891185, -0.2947534823724973, -0.32674672929657694, -0.36410657466080026, -0.4068202003787659, -0.4547259184207111, -0.5075128046081033, -0.564724159616823, -0.6257647545438527, -0.6899117226741377, -0.7563288663450571, -0.8240840603727927, -0.8921693535778327, -0.9595232995439691, -1.0250549886521219, -1.0876692071556526, -1.1462921168009599, -1.1998968310946347, -1.2475282622572164, -1.288326626286519, -1.3215490220999937, -1.3465885437797247, -1.362990441488868, -1.3704649153127197, -1.3688962054463438, -1.3583477298869844, -1.3390631149616066, -1.3114630623331853, -1.276138096183331, -1.2338373336156574, -1.18545351753, -1.1320046419210443, -1.0746125825273405, -1.014479218955949, -0.952860596028873, -0.891039720617921, -0.8302986244508758, -0.7718903424313108, -0.7170114594338294, -0.6667758662167727, -0.6221903373214007, -0.5841325012647857, -0.5533317170103486, -0.5303533019795267, -0.5155864774187321, -0.5092363086883229, -0.5113198231412699, -0.5216663890172077, -0.5399223376070953, -0.5655597103056036, -0.5978889145091613, -0.6360749800093918, -0.6791570228140138, -0.7260704482517959, -0.7756713615984057, -0.826762603826991, -0.8781207936521728, -0.9285237356597644, -0.9767775484882443, -1.021742876859898, -1.062359576473916, -1.0976693007169376, -1.1268354718045026, -1.1491601849900617, -1.1640976712149482, -1.1712640291116103, -1.1704430294881458, -1.1615878920297764, -1.144819032563703, -1.1204178774144717, -1.0888169367106482, -1.050586418648462, -1.0064177494663191, -0.9571044372155553, -0.903520779545518, -0.8465989651541864, -0.7873051541071195, -0.726615143062567, -0.6654902270915652, -0.6048538601599277, -0.5455696917355232, -0.4884215180624534, -0.43409563442279603, -0.3831660105346984, -0.33608263675633765, -0.29316330587635364, -0.2545890060767916, -0.22040300741195798, -0.19051362921050333, -0.16470058157141362, -0.1426246829586062, -0.12384067009375962, -0.10781273805523862, -0.09393237967312022, -0.08153803568638852, -0.06993602213500412, -0.05842217021430579, -0.04630359709262275, -0.03292002438976147, -0.017664074162932256, -1.772526015267408e-16], [0.0, 0.021157677189232595, 0.04556504661763603, 0.07338780218404542, 0.10466979191834905, 0.13933039543394635, 0.17716540439681472, 0.21785139199772816, 0.2609534661525056, 0.3059362124749986, 0.35217754922227795, 0.3989851395342598, 0.4456149383401748, 0.4912913940181636, 0.5352287797415652, 0.5766530975921734, 0.6148239807997483, 0.6490560163570656, 0.6787389218727728, 0.7033560366026832, 0.7225006265224709, 0.7358895561011852, 0.7433739438109261, 0.7449464927761733, 0.7407452704857664, 0.7310538001129585, 0.7162974185086409, 0.6970359500423159, 0.6739528388121696, 0.6478409719913171, 0.6195855119555922, 0.590144132211551, 0.5605251200562248, 0.5317638656280509, 0.5048983011014646, 0.4809438840961314, 0.4608687351162809, 0.4455695395659046, 0.4358488105333147, 0.4323940794088082, 0.43575953816370905, 0.44635060080013117, 0.4644117834264051, 0.4900182242640216, 0.5230710785415047, 0.5632969307783338, 0.6102512706617947, 0.6633259809243762, 0.7217606887328634, 0.7846577384784337, 0.851000455808745, 0.9196742924338375, 0.9894903706458279, 1.059210887360342, 1.1275757912784887, 1.1933301146296056, 1.2552513236907685, 1.3121760503288735, 1.3630255802397464, 1.4068295020540562, 1.442746964360631, 1.4700850439297235, 1.4883137966409585, 1.497077641177371, 1.4962028125299704, 1.4857007156515951, 1.4657671069354214, 1.4367771302047252, 1.399276332178506, 1.3539678775334774, 1.301696273405654, 1.2434279952875904, 1.180229478791846, 1.113243002915636, 1.0436610387839849, 0.9726996722130424, 0.9015717280092506, 0.8314602282559419, 0.7634928058622608, 0.6987176686628538, 0.6380816690301078, 0.5824109803157482, 0.5323948158220653, 0.4885725500538766, 0.45132451761098674, 0.4208666743413928, 0.39724921053470974, 0.38035910933612804, 0.3699265475853676, 0.36553494329351743, 0.366634366245607, 0.37255794790515473, 0.3825408558575745, 0.3957413381844398, 0.41126329585381627, 0.42817980757242985, 0.44555701236116557, 0.4624777508131104, 0.4780643766293242, 0.4915001752862565, 0.5020488658915634, 0.5090717144076222, 0.5120418501198966, 0.5105554508705249, 0.5043395442909867, 0.4932562599787349, 0.4773034590526494, 0.45661176048221586, 0.43143807567392706, 0.40215585170010354, 0.3692423070383581, 0.3332630196619462, 0.29485429388158735, 0.2547037878262444, 0.21352992648240351, 0.17206065472177684, 0.1310121000105495, 0.09106771514257188, 0.05285845737588851, 0.01694453214585934, -0.016200812193472986, -0.04620500631743662, -0.07280703152221706, -0.09586514855774145, -0.11536127345543319, -0.13140187768592576, -0.144215380767117, -0.15414609512821265, -0.16164487329339017, -0.16725669398694187, -0.17160550438006217, -0.1753767083451251, -0.17929775340271317, -0.18411732043171236, -0.19058365884142603, -0.19942263477431454, -0.2113160703607127, -0.2268809477864075, -0.24665003303326383, -0.27105444105301546, -0.300408617632939, -0.33489815444519194, -0.37457078418451223, -0.4193308240111619, -0.4689372496781256, -0.5230054918673852, -0.5810129526531833, -0.6423081459877126, -0.7061232740195982, -0.7715899632172663, -0.8377578028867428, -0.9036152557995838, -0.9681124481272214, -1.0301852953052566, -1.0887803831240113, -1.1428800002325537, -1.1915267099746065, -1.2338468563007443, -1.269072420304079, -1.2965606802159582, -1.315811177624599, -1.3264795550542523, -1.3283879033665744, -1.321531339946734, -1.306080628311875, -1.2823807444455462, -1.2509453925078504, -1.2124475702169288, -1.167706379750386, -1.1176703711312266, -1.0633977895021545, -1.0060341733766502, -0.94678781601901, -0.8869036549403033, -0.8276361937942728, -0.7702220857369101, -0.7158530169529796, -0.6656495232983332, -0.6206363519829707, -0.5817199444245328, -0.5496685666955418, -0.5250955515716721, -0.5084460425756073, -0.4999875473890412, -0.49980451759186, -0.5077970760814088, -0.5236839150514458, -0.5470092884650235, -0.5771539259439148, -0.6133496022766048, -0.6546970105679617, -0.7001865095056591, -0.7487212481770219, -0.7991421169520064, -0.8502539314715245, -0.9008522297325308, -0.9497500502738636, -0.9958040628021169, -1.0379394411397866, -1.0751729016412115, -1.106633377356721, -1.1315798580440712, -1.1494159971311864, -1.1597011671549542, -1.162157733039331, -1.1566744056546885, -1.14330563411733, -1.1222670918738338, -1.0939274063904474, -1.0587963729045873, -1.0175099769719291, -0.9708126263995667, -0.9195370587468923, -0.8645824443136537, -0.8068912451283479, -0.7474254169385668, -0.6871425529788483, -0.6269725651086833, -0.5677954799038193, -0.5104208949465903, -0.4555695947497665, -0.4038577676516896, -0.3557841961300857, -0.3117207150559162, -0.27190614742709657, -0.23644383723732498, -0.20530280661845762, -0.1783224715782794, -0.1552207598749981, -0.13560538810610365, -0.11898797511110283, -0.10480059729789888, -0.09241433028802025, -0.08115927186281172, -0.07034550480902897, -0.059284435807022286, -0.04730993852561039, -0.03379873576795571, -0.018189476666292684, -1.8276830316432197e-16], [0.0, 0.021785860740656946, 0.046837527572948186, 0.07525629212434362, 0.10702268367239437, 0.14199580513163185, 0.17991609384238963, 0.22041144232518387, 0.26300652618158554, 0.3071351021465925, 0.352154961068615, 0.39736515030319247, 0.44202501944898337, 0.4853745940795057, 0.5266557453992377, 0.5651336005312774, 0.6001176290405892, 0.6309818465724973, 0.6571835960400162, 0.6782804001664747, 0.693944425574509, 0.7039741568737549, 0.7083029479023341, 0.707004194721955, 0.7002929592311862, 0.6885239612497498, 0.6721859484193407, 0.6518925449772854, 0.6283697700913893, 0.6024405017477749, 0.5750062410114178, 0.5470266018411304, 0.5194970117530646, 0.49342515695646355, 0.46980674088942237, 0.44960114643822685, 0.4337075989538572, 0.4229424192645289, 0.4180179333703805, 0.4195235689041428, 0.42790961860857707, 0.4434740892055643, 0.46635298160124483, 0.4965142671387501, 0.5337557365478798, 0.5777068054950947, 0.6278342654724435, 0.6834518735093996, 0.7437335811821562, 0.8077301149145824, 0.8743885377897423, 0.9425743500352723, 1.0110956228128976, 1.0787286094791773, 1.1442442413437184, 1.206434892059808, 1.2641407867191936, 1.3162754387031805, 1.361849519213186, 1.3999926006473598, 1.4299722647354909, 1.4512101283903251, 1.463294413076741, 1.4659887653726293, 1.4592371253077674, 1.4431645328576452, 1.418073859357297, 1.38443854724162, 1.34289153606407, 1.2942106428977016, 1.239300748793159, 1.1791732179313807, 1.1149230406513257, 1.0477042440981639, 0.9787041535635917, 0.9091171127415063, 0.840118281511785, 0.7728381252684136, 0.708338190368648, 0.6475887265056242, 0.591448669556051, 0.5406484389163869, 0.4957759330033762, 0.45726602720947135, 0.42539379214140705, 0.4002715585719671, 0.38184986145953775, 0.3699222009571501, 0.36413346586629336, 0.3639917767611183, 0.36888342417650394, 0.37809050381659287, 0.3908107874844771, 0.4061793168882705, 0.42329116887985896, 0.4412248159422216, 0.45906549542576147, 0.4759280053501427, 0.49097836337853806, 0.5034537983189791, 0.5126805893495698, 0.5180893259134132, 0.5192272294035375, 0.5157672546196597, 0.5075137725755042, 0.4944047244517648, 0.47651022709839, 0.4540277012079283, 0.427273681827739, 0.3966725550300894, 0.3627425422064008, 0.32607932265257733, 0.2873377441387114, 0.2472121185386253, 0.20641563415721156, 0.1656594372844356, 0.12563194221703874, 0.08697892137219354, 0.05028490538234074, 0.01605638777287834, -0.015292719109045432, -0.0434529896008928, -0.06822843361630136, -0.08954224828366282, -0.10743921528704113, -0.12208467451793845, -0.1337600941346259, -0.14285534617755888, -0.14985788324350827, -0.1553390931829858, -0.15993818328277676, -0.16434401102922386, -0.16927533364127528, -0.17545999170186935, -0.18361357228793934, -0.1944181132167349, -0.20850141195012908, -0.22641749024880048, -0.24862873912542763, -0.27549022864551603, -0.30723661464032737, -0.34397201071775185, -0.3856631206560213, -0.43213584515832465, -0.48307549004910283, -0.5380306124696617, -0.596420449741492, -0.6575457846089615, -0.7206030128295247, -0.7847010967543938, -0.8488810137108985, -0.9121372425526216, -0.9734407773483797, -1.0317631152286166, -1.0861006369839685, -1.1354987848680647, -1.1790754425949324, -1.2160429377764181, -1.2457281166888428, -1.2675899846046066, -1.2812344609473538, -1.2864258658862915, -1.283094832051271, -1.2713424199567203, -1.251440306403922, -1.2238270093754013, -1.189100208438066, -1.1480053140943005, -1.1014205305454556, -1.0503387417236438, -0.9958466281032768, -0.9391014898088597, -0.8813063082099921, -0.8236836221336873, -0.7674488249353667, -0.713783504197248, -0.6638094463687797, -0.6185639141962632, -0.57897677564486, -0.5458500198920361, -0.5198401399063151, -0.5014437934756365, -0.49098707695629534, -0.48861866036085355, -0.49430694077331455, -0.5078412757005479, -0.528837261159935, -0.5567459234184609, -0.5908666006685359, -0.6303632038003488, -0.6742834659229823, -0.721580720322544, -0.7711376878152262, -0.8217917083699684, -0.8723608195412943, -0.9216700664319093, -0.9685774250033753, -1.0119987326126385, -1.050931046345248, -1.0844738903576667, -1.111847907004037, -1.1324104916644855, -1.1456680662876777, -1.151284729842615, -1.1490871130816547, -1.1390653580413965, -1.1213702372541812, -1.0963065213814993, -1.0643227946071687, -1.0259980024205675, -0.9820250942925722, -0.9331921923017856, -0.8803617743432198, -0.8244484057590968, -0.7663955849941174, -0.7071522864543565, -0.6476497867520404, -0.5887793489231314, -0.5313713133491328, -0.4761761046911751, -0.4238476121814573, -0.3749293374534036, -0.3298436313424493, -0.28888426060494193, -0.25221245932348996, -0.2198565300716204, -0.19171496896088652, -0.16756299877881903, -0.14706230780562093, -0.12977371074404215, -0.11517237454257223, -0.10266518757791827, -0.09160979729250582, -0.08133480028321598, -0.07116054102562429, -0.060419961575306415, -0.048478945043960185, -0.03475561037281513, -0.01873804452963733, -1.88346966884696e-16], [0.0, 0.022391519570018757, 0.048033061050360974, 0.07696334437377751, 0.10910250826449547, 0.14425332176886707, 0.18210571341794582, 0.2222445052982358, 0.26416015528902065, 0.3072622316468131, 0.35089527199150644, 0.39435661541289835, 0.4369157434886343, 0.4778346248429089, 0.5163885295423162, 0.55188676486225, 0.5836927831649757, 0.6112431258589093, 0.6340646943553283, 0.6517898789562203, 0.6641691287183811, 0.6710806082621952, 0.6725366596731515, 0.6686868672895421, 0.6598176082998305, 0.6463480605655162, 0.628822728728938, 0.6079006382161115, 0.5843414319803196, 0.558988684608832, 0.5327508207201831, 0.5065800875820412, 0.48145008397664585, 0.45833238719657876, 0.4381728466345375, 0.4218681250301935, 0.41024306669480914, 0.4040294559443475, 0.4038466988848169, 0.4101849183075197, 0.42339089579565575, 0.44365722855212875, 0.47101499253947693, 0.5053301201184348, 0.5463036115121677, 0.5934756072777528, 0.6462332557891702, 0.7038222178107095, 0.7653615618231887, 0.829861721032152, 0.8962451079752047, 0.9633689172063217, 1.0300495922868065, 1.095088391601771, 1.1572974593872736, 1.2155257945045146, 1.268684510291925, 1.315770794263058, 1.3558900061384733, 1.3882753959935255, 1.412304980128605, 1.4275151792735936, 1.4336109003000592, 1.4304718268739267, 1.4181547743907668, 1.396892057909473, 1.3670859163675821, 1.3292991298234946, 1.2842420565561332, 1.2327564013730805, 1.1757961033839206, 1.1144057989234522, 1.0496973716309093, 0.9828251455505445, 0.9149603074670665, 0.8472651608098806, 0.7808678149856566, 0.7168379009212219, 0.6561638762672514, 0.5997324428273806, 0.5483105453672694, 0.5025303563610596, 0.46287757705768184, 0.4296833033386671, 0.4031196172216274, 0.38319897370468536, 0.369777360195538, 0.36256111430014265, 0.3611171975069966, 0.3648866394557859, 0.3732007920481026, 0.3852999664794189, 0.4003539709490636, 0.417484023669614, 0.4357854858751297, 0.4543508435150537, 0.4722923645671153, 0.4887638714025885, 0.5029810940314473, 0.514240109638943, 0.5219334255680295, 0.5255633254724236, 0.5247521701643266, 0.5192494238838485, 0.5089352613175888, 0.4938206985546672, 0.4740442800754389, 0.4498654415849938, 0.4216547528278568, 0.3898813233386938, 0.3550977254242566, 0.317922850753003, 0.27902316820452727, 0.23909288982832966, 0.1988335779127556, 0.15893373863140314, 0.1200489462220164, 0.0827830262196765, 0.047670797320241334, 0.015162829739363325, -0.014387375474055568, -0.04073344545044308, -0.06374316456824977, -0.08340228462688612, -0.09981501134403392, -0.11320114928650535, -0.12388997474428612, -0.13231099175022265, -0.13898180825614243, -0.1444934453199349, -0.1494934601061833, -0.15466732182165366, -0.16071852690371569, -0.168347974640504, -0.17823314602141274, -0.19100763642260807, -0.20724158649847008, -0.22742353550282854, -0.2519441876799513, -0.28108253615913553, -0.3149947310913828, -0.3537060110052647, -0.3971059402099454, -0.4449471124281578, -0.4968473937588506, -0.5522956887217214, -0.6106611237585337, -0.671205455399008, -0.7330984275322522, -0.7954357259427381, -0.8572591104006324, -0.9175782468622756, -0.9753937162117458, -1.0297206426471317, -1.0796123651582838, -1.1241835700915654, -1.1626323117354096, -1.1942603710149668, -1.2184914392295079, -1.2348866634361368, -1.24315715139242, -1.2431731054427468, -1.234969334638477, -1.2187469807778752, -1.1948713848324428, -1.163866113172995, -1.1264032558456127, -1.083290199597263, -1.035453164190553, -0.983917869664431, -0.9297877726415447, -0.874220369813264, -0.8184021148632042, -0.7635225301223375, -0.7107481153075951, -0.6611966622456953, -0.6159125763461893, -0.5758437829422235, -0.5418207600009466, -0.5145381889965469, -0.49453965413762135, -0.4822057481388111, -0.47774586207133, -0.4811938494773502, -0.49240766301227673, -0.5110729676219316, -0.5367106399603583, -0.5686879717007498, -0.6062333068234373, -0.6484537620065517, -0.6943556068593005, -0.7428668186761589, -0.7928612761493922, -0.8431840192631987, -0.8926769792908229, -0.9402045739699003, -0.9846785687289893, -1.0250816251091364, -1.0604889917419578, -1.0900878405428214, -1.1131938099666372, -1.1292643867769259, -1.1379088360652474, -1.1388944742858667, -1.1321491697363666, -1.1177600470045412, -1.0959684641463938, -1.0671614214911385, -1.031859646775382, -0.9907026806906074, -0.9444313579491591, -0.8938681399090221, -0.8398958041748492, -0.7834350332298823, -0.7254214671865683, -0.6667827946486488, -0.6084164502816223, -0.5511684681747991, -0.49581400698037154, -0.4430400170034464, -0.39343046207655874, -0.3474544416526279, -0.3054574828088529, -0.26765618969235405, -0.23413635143470476, -0.20485452089933998, -0.17964298803541476, -0.1582179853202457, -0.14019088094473525, -0.1250820400812781, -0.11233696765401173, -0.10134428917593441, -0.09145508084031796, -0.08200302727872606, -0.07232486603059717, -0.06178057227754411, -0.04977274589761116, -0.03576468515692643, -0.01929666679859932, -1.9386738893974233e-16], [0.0, 0.02296256255492725, 0.04912889805548811, 0.07847758501769264, 0.11087183286840605, 0.14606246929637134, 0.1836941113972555, 0.22331436333198013, 0.2643858037811215, 0.30630045301432673, 0.3483963437729117, 0.3899757640601617, 0.4303246947830871, 0.4687329321527289, 0.5045143646850621, 0.5370268680831113, 0.5656912884160695, 0.590009004691786, 0.609577595653071, 0.6241041815952423, 0.6334160690730155, 0.6374683931294589, 0.6363485264827302, 0.630277106087597, 0.6196056126296852, 0.6048105256843237, 0.5864841642966065, 0.5653224074321094, 0.5421095689790665, 0.5177007757302131, 0.4930022621704965, 0.4689500512840944, 0.4464875345549373, 0.4265424957345746, 0.4100041409653794, 0.39770070198164315, 0.39037816921627067, 0.38868068791403426, 0.3931331133350732, 0.4041261716962966, 0.4219046128249044, 0.44655867004930055, 0.47801906433505126, 0.5160557049969328, 0.5602801505482012, 0.6101518025557341, 0.664987714976915, 0.72397581358004, 0.7861912368554329, 0.8506154333587045, 0.916157582577647, 0.981677848858338, 1.0460119320914425, 1.1079963458881592, 1.1664938346937646, 1.2204183361874623, 1.2687589045449705, 1.3106020334886046, 1.3451518549658041, 1.3717477388955346, 1.3898788805060622, 1.399195532878372, 1.399516621682968, 1.3908335648261654, 1.3733102097221137, 1.3472788929905182, 1.3132327193086821, 1.2718142456853665, 1.2238008423979096, 1.1700870801801015, 1.111664563067554, 1.0495996859100785, 0.9850098435094622, 0.919038653484728, 0.8528307764693625, 0.7875069246051762, 0.7241396423615485, 0.6637304226742791, 0.6071886868073396, 0.5553131090687561, 0.5087757087427346, 0.46810906279964637, 0.43369691582254355, 0.4057683800543606, 0.3843958305890325, 0.3694965106702602, 0.36083777204115874, 0.3580457875183238, 0.3606174895967307, 0.36793541196577156, 0.3792850422065276, 0.3938742353112717, 0.4108541904327266, 0.4293414585620036, 0.4484404274668557, 0.4672657226795039, 0.484963969745681, 0.5007343831260141, 0.5138476805287887, 0.5236628671733548, 0.5296414913549715, 0.5313590392486374, 0.5285132114566963, 0.5209289044823073, 0.5085598050589739, 0.4914865919485952, 0.4699118262560953, 0.44415169532713566, 0.4146248547906698, 0.38183868629119905, 0.3463733531040681, 0.308864090530468, 0.26998221136841577, 0.23041533777904197, 0.19084738875340654, 0.1519388567042973, 0.11430789737214801, 0.07851273449984511, 0.045035845190425375, 0.014270344428854411, -0.013491070862489518, -0.03806432517362509, -0.059379096894132906, -0.07748074204626614, -0.0925289552913481, -0.10479319956716764, -0.11464502028965225, -0.12254744172492821, -0.12904171983237384, -0.13473179564421922, -0.14026685430481917, -0.1463224456830912, -0.15358066169219287, -0.16270989208873896, -0.17434469388272944, -0.18906630920526055, -0.20738435253297735, -0.22972016087862027, -0.25639226058423953, -0.2876043526755563, -0.32343615662599656, -0.36383738137456345, -0.4086250143062084, -0.45748403558216605, -0.5099715787799247, -0.5655244714293108, -0.6234700029018635, -0.6830396843880415, -0.7433856884635941, -0.8035995859525131, -0.8627329372083897, -0.9198192451021565, -0.9738967392012462, -1.0240314358358111, -1.0693399076331624, -1.1090111989849438, -1.142327340769211, -1.1686819481104946, -1.1875964283169103, -1.1987333813543959, -1.2019068409786706, -1.1970890793561892, -1.1844137798525178, -1.1641754696561282, -1.1368251939130498, -1.1029625038697133, -1.063323920930091, -1.0187681243324263, -0.9702581902284507, -0.9188412823302299, -0.8656262571880182, -0.811759699019483, -0.758400938537841, -0.7066966364360592, -0.6577555244152433, -0.6126238945774553, -0.5722624116681055, -0.5375247924308137, -0.5091388529499908, -0.48769036934759064, -0.4736101309123456, -0.4671644892788018, -0.4684496244711482, -0.4773896604948249, -0.4937386718394038, -0.5170865299696203, -0.5468684478711789, -0.5823779931958708, -0.6227832586421898, -0.6671458039001162, -0.7144419185817561, -0.7635857016215886, -0.8134534109594602, -0.8629085089128324, -0.9108268141727957, -0.9561211711494597, -0.9977650614242922, -1.0348146099692177, -1.0664284798534238, -1.0918852023462544, -1.110597553309042, -1.1221236599581477, -1.1261746026603021, -1.1226183623951274, -1.111480053765759, -1.092938473756912, -1.0673190856091963, -1.0350836430103547, -0.9968167401967489, -0.9532096465492264, -0.9050418480808154, -0.8531607713050637, -0.7984602060672655, -0.7418579720408147, -0.6842733880850578, -0.6266051042170917, -0.5697098426018207, -0.5143825670916258, -0.46133856116400523, -0.4111978426443813, -0.3644722816844488, -0.32155571767455365, -0.28271729289980246, -0.24809813777488163, -0.21771145650645649, -0.19144597520005385, -0.16907262893297192, -0.15025428230092544, -0.13455820146778302, -0.1214709267165748, -0.11041513463773149, -0.10076802988650294, -0.09188076911518833, -0.0830983951567091, -0.0737797484011047, -0.06331682482520466, -0.051153066223911706, -0.0368000974237859, -0.019852466880102, -1.9921222776495417e-16], [0.0, 0.023487613495027718, 0.05010402103942105, 0.07977064395034804, 0.11229770125535897, 0.14738885804702068, 0.18464889964571082, 0.2235942334083831, 0.2636659457082284, 0.3042450741949876, 0.3446696966459889, 0.3842533890356501, 0.4223045681344824, 0.4581462089607534, 0.4911354154027723, 0.5206823236350991, 0.5462678325612988, 0.5674596830879881, 0.5839264479024142, 0.595449044611204, 0.6019294463379992, 0.6033963336546637, 0.6000075082999272, 0.5920489706122892, 0.5799306469359286, 0.5641788383388457, 0.5454255456778875, 0.524394906252349, 0.5018870519856248, 0.4787597663752769, 0.4559083756485698, 0.43424435716883, 0.4146731839342219, 0.398071947062148, 0.3852673078421508, 0.3770143269808335, 0.3739767011058177, 0.3767089058310886, 0.38564070143104107, 0.4010644024538876, 0.4231252477417892, 0.4518151338839651, 0.48696989489448694, 0.5282702258343344, 0.5752462602669234, 0.6272857229991744, 0.6836454926867966, 0.7434663257087901, 0.8057904152908124, 0.8695813900906142, 0.933746296076369, 0.9971590560276384, 1.0586848636006074, 1.1172049445602454, 1.1716411071088535, 1.2209795065152573, 1.2642930664119494, 1.3007620297784668, 1.3296921560369892, 1.35053013580612, 1.3628758603592421, 1.3664912571277552, 1.3613054838743228, 1.3474163604624811, 1.3250880063691786, 1.2947447420570393, 1.2569614008562444, 1.2124502829502912, 1.162045062352676, 1.1066820294787378, 1.0473791143215732, 0.985213186824571, 0.9212961705641985, 0.8567505323694523, 0.7926847233833301, 0.7301691460257806, 0.6702132063974874, 0.6137439832608443, 0.5615870035692616, 0.5144495616224947, 0.47290695562317525, 0.43739194327191017, 0.4081876388527026, 0.3854239899849547, 0.36907788493252097, 0.35897685321358286, 0.354806235414133, 0.35611961470240544, 0.3623522246123238, 0.37283697711207175, 0.3868226935139438, 0.40349406989988335, 0.42199286965475236, 0.4414398093426716, 0.4609565911397574, 0.47968753562604893, 0.4968202828791752, 0.5116050571044325, 0.5233720297569352, 0.5315463672301993, 0.5356606103895073, 0.5353641029569923, 0.5304292622386623, 0.5207545669871869, 0.5063642212672682, 0.48740453791704996, 0.46413716845129144, 0.4369293859429126, 0.4062417015549233, 0.37261316212328777, 0.33664473385030763, 0.2989812243250538, 0.26029223057535117, 0.22125262380258207, 0.18252309129996114, 0.1447312525806607, 0.10845385005323145, 0.07420048511928544, 0.04239932909477279, 0.01338518593532012, -0.01260977828298727, -0.03546239423294322, -0.05516176796422856, -0.07180939130872735, -0.08561607895192644, -0.0968958100852568, -0.10605663362800032, -0.11358887306923153, -0.12005093807092697, -0.12605311328303775, -0.1322397487351009, -0.13927031930743242, -0.1477998520388815, -0.15845923858642244, -0.17183595552206835, -0.18845570717357346, -0.20876548456146965, -0.23311850016201938, -0.2617614125587097, -0.29482419865769066, -0.332312965429982, -0.37410591973663615, -0.41995263551954976, -0.4694766744780965, -0.5221815313792527, -0.5774597904951138, -0.6346052974517449, -0.6928280730756446, -0.7512716245993317, -0.8090322466385991, -0.8651798512816958, -0.9187798247933092, -0.968915378915237, -1.014709848318498, -1.0553483828819983, -1.0900984942587117, -1.1183289404208414, -1.1395264689951285, -1.1533099893328838, -1.1594418032306768, -1.1578355935807054, -1.148560947302872, -1.1318442718177089, -1.108066051036495, -1.0777544752504298, -1.0415755672268117, -1.0003200121067457, -0.9548869792475155, -0.9062652979771982, -0.8555124145063708, -0.8037316123551477, -0.7520480222349026, -0.7015839782855718, -0.6534342951322097, -0.6086420439382264, -0.5681753953851593, -0.5329060735313421, -0.503589927361303, -0.48085007742512914, -0.46516303447399904, -0.45684811688848137, -0.4560604156700656, -0.46278747171813805, -0.4768497420864221, -0.4979048420445537, -0.5254554602468212, -0.5588607573071361, -0.5973509757108055, -0.6400449132592293, -0.6859698449793862, -0.7340834212634899, -0.7832970243149454, -0.8325000318615746, -0.880584417344034, -0.9264691098561353, -0.969123545125006, -1.007589860550685, -1.0410032222195393, -1.0686098189832782, -1.089782116975437, -1.104031035868741, -1.1110147840740388, -1.110544172065986, -1.1025843090671257, -1.0872526763096948, -1.0648136578584069, -1.0356696953629074, -1.0003493140237978, -0.959492341524096, -0.9138327078852923, -0.8641792705482818, -0.8113951540966983, -0.7563761268563302, -0.700028556349682, -0.6432474918147081, -0.5868954146036325, -0.5317821764916957, -0.47864661230913247, -0.42814026774292724, -0.38081362681343023, -0.3371051578556644, -0.29733342349683906, -0.26169242097812984, -0.23025023621904314, -0.2029510103565632, -0.17962013323735523, -0.1599724966136398, -0.1436235626388982, -0.13010293260709377, -0.11887003849112165, -0.10933152726510925, -0.10085986654481208, -0.09281267077342578, -0.08455223073303329, -0.07546472596708312, -0.06497860981554453, -0.05258167991574523, -0.037836382604689224, -0.020392946756880335, -2.0426928051054264e-16], [0.0, 0.02395612828311273, 0.05093935149301169, 0.08081742073913344, 0.11335192146630177, 0.14820445468071974, 0.1849456645684801, 0.2230668774309625, 0.26199404813624066, 0.3011036492699791, 0.33974008641936054, 0.3772341818630692, 0.41292223942734363, 0.4461651861683591, 0.47636728230875586, 0.502993899621756, 0.5255878900239291, 0.5437840999890052, 0.5573216317023956, 0.5660535075223659, 0.569953458920746, 0.5691196330380037, 0.5637750875114282, 0.5542650253852079, 0.5410508046568877, 0.5247008392815882, 0.5058785881765955, 0.4853279039370961, 0.4638560816907351, 0.4423150090432613, 0.42158086885911267, 0.40253288637799184, 0.3860316398618562, 0.37289746886474373, 0.36388951590584223, 0.3596859257165282, 0.36086570156774683, 0.36789268103216094, 0.38110204477438536, 0.40068971276026233, 0.42670491406165423, 0.45904614086186873, 0.49746061617927184, 0.5415473202036746, 0.5907635340538473, 0.6444347743273103, 0.7017679091256892, 0.7618671683368273, 0.8237526897606332, 0.8863811799395961, 0.9486682158517055, 1.0095116722540076, 1.0678157304630504, 1.1225149084558843, 1.1725975497829244, 1.217128219981846, 1.2552684837163444, 1.2862955731544705, 1.3096185072545716, 1.324791281457451, 1.3315228163439887, 1.3296834304337437, 1.3193076846124547, 1.3005935316848924, 1.2738977921638364, 1.2397280644960664, 1.1987312623753805, 1.1516790515488788, 1.0994505316499816, 1.043012573316427, 0.983398275607724, 0.9216840522023453, 0.8589658859869209, 0.796335309706627, 0.7348556749082494, 0.6755392623864245, 0.6193257649836499, 0.567062638467476, 0.519487769197062, 0.477214849570745, 0.4407217852511004, 0.410342383555398, 0.3862614920221354, 0.36851367200210744, 0.3569854062483652, 0.35142075400444284, 0.35143028411162436, 0.35650303820504065, 0.3660212040603616, 0.37927711534000796, 0.3954921399160787, 0.41383697591830354, 0.4334528436949477, 0.4534730437072292, 0.473044345409556, 0.4913476804763617, 0.5076176350700131, 0.5211602696282978, 0.5313688400018783, 0.5377370495233532, 0.5398695263156625, 0.5374892922036142, 0.5304420671541076, 0.5186973342808578, 0.5023461730658948, 0.48159595049753356, 0.4567620392455585, 0.42825680680165645, 0.39657618783817467, 0.36228421217837875, 0.32599591123180166, 0.2883590652793995, 0.2500352816215508, 0.21168090865423575, 0.17392829305843555, 0.1373678764438798, 0.10253160427566951, 0.06987808434423004, 0.03977988533169304, 0.012513309376895853, -0.011749092607851756, -0.03294306610347455, -0.05111413886702306, -0.06641600781380369, -0.07910586825229472, -0.08953680685751644, -0.09814745672968726, -0.10544918481949389, -0.11201114707936935, -0.11844360326385896, -0.12537992990702398, -0.13345780545620042, -0.14330006492451144, -0.15549573212746354, -0.17058173529836618, -0.18902579666597752, -0.21121095878391002, -0.2374221707000429, -0.26783530642091513, -0.3025089278122238, -0.3413790355788688, -0.3842569769911005, -0.4308305994374706, -0.48066865667985603, -0.5332283919196742, -0.5878661405347305, -0.6438507176564435, -0.7003792835863074, -0.7565953152239295, -0.8116082558426562, -0.8645143701282818, -0.9144182975607487, -0.960454775851338, -1.0018099978236135, -1.0377420700972526, -1.0676000601220232, -1.0908411491084817, -1.107045451487173, -1.1159281156733114, -1.1173483848163004, -1.1113153683262256, -1.0979903535391597, -1.0776855699933043, -1.0508594044055748, -1.0181081504648968, -0.9801544618811251, -0.9378327576723379, -0.8920719034531049, -0.8438755596548717, -0.7943006455046446, -0.7444344147720476, -0.6953706745918199, -0.6481857011933423, -0.6039144155473148, -0.5635273775266422, -0.5279091392601838, -0.4978384673532237, -0.4739709002961965, -0.4568240527263849, -0.4467660135661279, -0.44400711200111603, -0.44859524555606306, -0.4604148801081815, -0.47918974460285874, -0.5044891556174541, -0.5357378208881971, -0.5722288885624652, -0.6131399322644869, -0.6575514929272126, -0.7044677384217047, -0.7528387527562003, -0.801583929206482, -0.8496159170722841, -0.8958645604132818, -0.9393002693577381, -0.9789562803190204, -1.013949290290378, -1.04349799158729, -1.0669390859367176, -1.0837404193652844, -1.0935109503607463, -1.0960073415147737, -1.0911370473799191, -1.0789578565548226, -1.0596739319508928, -1.0336284776800222, -1.0012932419658573, -0.963255140941258, -0.9202003563123992, -0.872896318991426, -0.8221720394962577, -0.7688972830210172, -0.7139611117156394, -0.65825032831178, -0.6026283535512763, -0.5479150550007454, -0.49486801718581286, -0.44416570328191285, -0.39639290788445714, -0.3520288399500325, -0.3114381063915642, -0.27486479176422146, -0.24242974989192773, -0.21413114116261733, -0.1898481666291164, -0.16934786906451407, -0.15229479376476274, -0.13826323010100092, -0.12675169039089315, -0.11719922718586184, -0.10900314493584976, -0.10153762831024506, -0.0941727880487653, -0.08629361660585506, -0.07731835023092905, -0.06671575136217178, -0.05402085484805807, -0.03884876278114272, -0.02090612457373468, -2.089326802477806e-16], [0.0, 0.024358500590042482, 0.05161793179694887, 0.08159630839335395, 0.11401129370503697, 0.14848777415420664, 0.18456808223021998, 0.22172460010424538, 0.259374413349741, 0.29689562988014334, 0.3336449346564392, 0.3689759170921528, 0.40225768625910896, 0.432893279545144, 0.4603373735948878, 0.4841128221193758, 0.5038255731157258, 0.5191775575132245, 0.5299771912851969, 0.5361471923987163, 0.5377294811424846, 0.5348870057038136, 0.527902412527684, 0.5171735610414747, 0.5032059627616026, 0.48660230359292195, 0.4680492833049334, 0.44830207582382187, 0.42816677635283296, 0.40848125484038744, 0.3900948785881079, 0.3738475987141856, 0.36054891492614455, 0.35095724007722756, 0.3457601800640099, 0.34555622587173146, 0.3508383234100785, 0.36197974393620536, 0.37922262435580784, 0.40266948381550416, 0.43227795227411503, 0.4678588698875849, 0.5090778349384164, 0.5554601946706198, 0.6063993898003935, 0.6611684817155538, 0.7189346134663094, 0.778776083508471, 0.8397016465709397, 0.9006716005829182, 0.9606201736905314, 1.0184786921387052, 1.0731989890283415, 1.1237765062120553, 1.169272547075596, 1.2088351565540412, 1.2417181360173235, 1.2672977438827446, 1.285086686933618, 1.2947450710361479, 1.29608805170836, 1.289090003064679, 1.273885106141996, 1.2507643425033732, 1.2201689642505533, 1.1826805950840285, 1.1390081968002217, 1.089972209671957, 1.0364862417239604, 0.9795367393762477, 0.920161118896118, 0.8594248734421769, 0.798398193355974, 0.7381326472184493, 0.6796384678192933, 0.6238629706916173, 0.5716706036677168, 0.5238250847512275, 0.48097403350542195, 0.4436364394234432, 0.412193240904164, 0.38688121223499106, 0.3677902752613487, 0.3548642691904237, 0.34790512828075865, 0.34658033506342645, 0.3504334382357435, 0.3588973513827262, 0.371310082992521, 0.38693249143375824, 0.4049676120259388, 0.42458106817265845, 0.44492205557191117, 0.46514437829400396, 0.484427018235414, 0.5019937350042434, 0.5171312212401973, 0.529205377982208, 0.537675324945264, 0.5421048201674282, 0.5421708309215297, 0.5376690713448871, 0.5285164000668491, 0.5147500512479871, 0.4965237528724403, 0.4741008648396118, 0.4478447444129675, 0.418206616028571, 0.3857112846131313, 0.3509410848656782, 0.31451850209761084, 0.27708793213890764, 0.23929706772312562, 0.20177840618255086, 0.16513136805367698, 0.12990549846652408, 0.09658519343756458, 0.0655763521755783, 0.03719530529573813, 0.011660308728642396, -0.010914174359921829, -0.030520254439049477, -0.04725638697662619, -0.061324140738147695, -0.07302204803295459, -0.08273669833100532, -0.09093130898216864, -0.09813207313903959, -0.10491264372439978, -0.11187716189793291, -0.11964227769498195, -0.12881863832518986, -0.13999233530933577, -0.15370680478163465, -0.17044566579048973, -0.19061695950951926, -0.21453921845172227, -0.24242974989192687, -0.27439546285468, -0.31042650457675375, -0.3503929018841435, -0.39404432719032756, -0.4410130297184087, -0.49081989205547405, -0.5428834922826817, -0.5965319746972423, -0.6510174594987896, -0.70553265558831, -0.7592292825024933, -0.8112378589608471, -0.8606883777826383, -0.9067313610141112, -0.948558775680031, -0.9854242900148356, -1.0166623623957112, -1.0417056802299556, -1.060100503164251, -1.0715195133047304, -1.0757718335054078, -1.0728099417881676, -1.0627332839729544, -1.0457884658179086, -1.0223659884595306, -0.9929935746809321, -0.9583262164660611, -0.9191331543790611, -0.876282074566829, -0.8307208777611873, -0.7834574348571431, -0.7355377939722172, -0.6880233430948143, -0.641967459525656, -0.5983921916196853, -0.5582655194737772, -0.5224797291288723, -0.4918314098375369, -0.46700354658211907, -0.4485501312093602, -0.4368836564515856, -0.43226578916151454, -0.43480144394403464, -0.4444363978477804, -0.4609585028380823, -0.48400246745090497, -0.5130580943989451, -0.5474817790232168, -0.5865109963456344, -0.6292814339532803, -0.6748463657435843, -0.7221978091873154, -0.7702889674871637, -0.8180574288157085, -0.8644485784023567, -0.9084386759856348, -0.9490570611132655, -0.9854069716920784, -1.0166844964795083, -1.0421952289829375, -1.0613682473256951, -1.0737671106315576, -1.0790976357387583, -1.0772122967698403, -1.0681111723143144, -1.0519394487029434, -1.0289815710090209, -0.9996522139643157, -0.9644843209550292, -0.924114528812484, -0.8792663575433437, -0.8307315959680878, -0.7793503552078676, -0.7259902911038015, -0.6715255132888073, -0.6168157023915372, -0.5626859476855629, -0.509907795676707, -0.4591819662323447, -0.4111231477821874, -0.3662472280202898, -0.3249612528192886, -0.28755633534790775, -0.254203661450597, -0.22495365811863544, -0.19973831134825393, -0.17837653986497617, -0.16058245409410696, -0.14597625730288682, -0.13409747983826578, -0.12442017947869324, -0.11636969254624628, -0.10934048278288949, -0.10271460900680869, -0.09588031886281614, -0.08825027488655536, -0.07927893062037043, -0.06847859833678933, -0.05543378542225216, -0.039813422734324325, -0.021380664085435593, -2.1310400095194086e-16], [0.0, 0.024686154970013377, 0.052125079512323105, 0.08208937291911678, 0.1142577764818723, 0.1482239923616321, 0.18350793737726873, 0.21956913560709151, 0.2558218972150969, 0.2916518834078962, 0.32643362011624477, 0.35954849683455453, 0.39040277272109875, 0.418445109941877, 0.44318316440632677, 0.4641987862582153, 0.481161416211664, 0.49383930823163863, 0.502108263052017, 0.5059576192615591, 0.5054933176186764, 0.5009379281590104, 0.49262760668687505, 0.4810060254621972, 0.466615400344592, 0.4500848113870119, 0.43211608399817086, 0.4134675615422929, 0.394936155998467, 0.3773381096382063, 0.3614889364085277, 0.34818303590069893, 0.33817348479876397, 0.33215251019571507, 0.3307331361083092, 0.33443246919517594, 0.34365705267400387, 0.3586906696201387, 0.37968491935900084, 0.40665282492820376, 0.43946565717984415, 0.477853083785313, 0.5214066710853656, 0.5695866853665579, 0.6217320597408051, 0.6770733153372805, 0.734748152896033, 0.7938193648755317, 0.8532946604862913, 0.9121479480733664, 0.9693415821886534, 1.0238490574503225, 1.0746776185220996, 1.1208902555950477, 1.1616265676399935, 1.1961220011260623, 1.223725009268154, 1.2439117252785454, 1.256297801388608, 1.260647132166397, 1.256877254266915, 1.2450612934277039, 1.2254264113521725, 1.1983487881178314, 1.1643452578888769, 1.1240617950055776, 1.0782591220398148, 1.0277957793373085, 0.973609055264929, 0.9166942264002019, 0.8580825960323409, 0.798818846648975, 0.739938236910559, 0.6824441756211014, 0.6272866943600464, 0.5753423170314834, 0.5273957892064343, 0.4841240836681841, 0.4460830421758788, 0.41369694853724076, 0.38725125623287887, 0.36688861683623536, 0.35260827522158356, 0.34426881602144055, 0.34159416498583905, 0.34418267078886183, 0.35151901933211205, 0.36298866550211145, 0.37789440827901866, 0.3954746854958594, 0.41492312560206007, 0.43540886641798454, 0.45609713571537774, 0.4761695858552477, 0.4948438846813898, 0.5113920871141349, 0.5251573458210684, 0.5355685640761927, 0.5421526483070911, 0.5445440804841336, 0.5424915998371987, 0.535861857641544, 0.5246399861240267, 0.5089271009606771, 0.4889348343993853, 0.46497707080582257, 0.43745912652860053, 0.4068646796637141, 0.3737408109846346, 0.33868156361237445, 0.3023104647861482, 0.26526247748228815, 0.22816586202654834, 0.19162442796452034, 0.1562006443168772, 0.12240005227902216, 0.09065738905643668, 0.06132478576915842, 0.03466234738374292, 0.010831359842093836, -0.010109699447024357, -0.028206245051120047, -0.043605734245227616, -0.05655293510230224, -0.06738243744485016, -0.07650860438894155, -0.0844132294037236, -0.09163122425584397, -0.09873471536957307, -0.1063159686785972, -0.11496959488463178, -0.1252745073502075, -0.13777611310685947, -0.15296921342720676, -0.17128207417075125, -0.19306209805662716, -0.21856349182764934, -0.247937271915368, -0.2812238939189926, -0.31834872542188014, -0.3591205100284735, -0.40323289480237995, -0.4502690154180928, -0.4997090552580556, -0.5509406183558381, -0.6032716834279059, -0.6559458390856722, -0.7081594403772465, -0.759080275599535, -0.8078672911560156, -0.8536908921762896, -0.8957533184485702, -0.9333085894393041, -0.9656815189716876, -0.992285319381225, -1.0126373462263059, -1.0263725771705041, -1.0332544714545606, -1.0331829181671919, -1.026199050806332, -1.0124867807091518, -0.9923709809857815, -0.9663123336818764, -0.9348989340282264, -0.8988348248162414, -0.8589257092148848, -0.8160621598587295, -0.7712007040685476, -0.7253432180759327, -0.6795151057931598, -0.634742768931154, -0.5920308943342493, -0.5523400907805813, -0.5165654010123645, -0.4855161955482005, -0.4598979233384707, -0.44029615130604866, -0.4271632713015562, -0.42080819028742134, -0.4213892491662528, -0.4289105392937926, -0.4432217052194232, -0.4640212395337966, -0.49086319288293373, -0.5231671412445298, -0.5602311754230459, -0.6012476062793927, -0.6453210152026607, -0.6914882243068381, -0.7387397161255265, -0.7860419992595781, -0.832360395304278, -0.8766817139424006, -0.9180362875244875, -0.9555188536394541, -0.9883078036665267, -1.0156823563511392, -1.0370372670386228, -1.0518947440480473, -1.0599133122675684, -1.0608934387068274, -1.0547798136103979, -1.0416602618775666, -1.0217613409540238, -0.9954407610635744, -0.9631768396820568, -0.925555272665071, -0.8832535677095624, -0.8370235403230147, -0.7876723168790434, -0.7360423225927776, -0.6829907535701063, -0.6293690409849103, -0.5760028117402627, -0.5236728338076566, -0.4730974062566067, -0.42491661452616164, -0.37967882176939216, -0.3378297083939685, -0.29970410571941836, -0.26552079765049225, -0.23538038824387847, -0.20926625493551304, -0.1870485289591776, -0.16849096808448671, -0.15326051414442105, -0.14093926072256965, -0.13103849649907676, -0.12301443859880741, -0.11628522911137179, -0.11024873777393196, -0.10430069536040577, -0.09785267604545038, -0.0903494530428085, -0.08128526998033331, -0.07021860028848224, -0.0567850075730793, -0.0407077704714022, -0.02180599456130316, -2.166932585206883e-16], [0.0, 0.02493162644553637, 0.05244851262660801, 0.08228248706539935, 0.11407858976078741, 0.1474049790118321, 0.18176504719700567, 0.21661142559381596, 0.25136150832616505, 0.2854140849617766, 0.3181666411879684, 0.3490328681464992, 0.3774599139001129, 0.40294491533249716, 0.42505036544714675, 0.44341789912857116, 0.4577801192728119, 0.4679701338235095, 0.473928531457668, 0.47570758802721586, 0.4734725657719202, 0.46750004102763276, 0.45817327181420964, 0.4459746924003956, 0.4314756958040314, 0.41532393533334416, 0.398228440935935, 0.3809429036571657, 0.36424753045405334, 0.3489299107110427, 0.3357653640494425, 0.32549725567056675, 0.31881777006869166, 0.31634962633772656, 0.31862919862243894, 0.32609147397849375, 0.33905723774259217, 0.3577228244831402, 0.3821527119588343, 0.4122751677291825, 0.44788108478925265, 0.4886260656321928, 0.5340357353639169, 0.5835141858399917, 0.6363553762013027, 0.6917572425415477, 0.748838202541198, 0.8066556814062313, 0.8642262348331797, 0.9205468042463711, 0.974616610232572, 1.0254591726740228, 1.0721439410028915, 1.1138070254160053, 1.1496705396390554, 1.1790600974523442, 1.2014200479317647, 1.2163260871920396, 1.2234949460690003, 1.2227909221516, 1.214229099199932, 1.197975175450898, 1.1743419027118929, 1.1437822185205984, 1.106879232051604, 1.064333298972289, 1.0169464892806057, 0.9656048136250008, 0.911258626221731, 0.8549016649740113, 0.7975492207369962, 0.7402159471113776, 0.6838938292282954, 0.6295308245534783, 0.5780106709405396, 0.5301343274562792, 0.48660347263009285, 0.4480064337638386, 0.41480686104320263, 0.3873353928991667, 0.3657844860394338, 0.35020650660443614, 0.3405150998937648, 0.33648977699656907, 0.3377835793826436, 0.34393360895946945, 0.3543741430688748, 0.36845199303996634, 0.38544371270672684, 0.40457422099685003, 0.42503637131309874, 0.4460109806978053, 0.46668682414322005, 0.48628010403269245, 0.5040529214139311, 0.5193303041598348, 0.5315153863213697, 0.540102382108095, 0.5446870556898316, 0.5449744529302221, 0.5407837315974396, 0.5320500007731233, 0.518823156232311, 0.5012637745867569, 0.4796362030679135, 0.4542990521231821, 0.42569336275670644, 0.39432877815322803, 0.36076809815133243, 0.32561063436919013, 0.2894748122675666, 0.2529804834685465, 0.21673141682947153, 0.18129842999371845, 0.14720360459713766, 0.114905998490876, 0.08478922802041913, 0.05715124361290728, 0.03219656394343607, 0.010031169254642711, -0.009339815360892262, -0.026011588965447183, -0.040176312816746135, -0.05211700823876636, -0.06219887683040814, -0.070858273078991, -0.07858962113421974, -0.08593062174704454, -0.09344614080437268, -0.1017112063340988, -0.1112935654054467, -0.12273626537088865, -0.1365407250414833, -0.15315075060955521, -0.17293792868348107, -0.19618879522522872, -0.2230941353089485, -0.2537407155351717, -0.2881056899601024, -0.3260538530532063, -0.3673378411617558, -0.4116013090415197, -0.45838503208744275, -0.5071358098748359, -0.5572179743893078, -0.6079272387054862, -0.6585065605819092, -0.7081636420291761, -0.7560896417442133, -0.8014786435207911, -0.843547401224629, -0.8815548702611384, -0.9148210369716174, -0.9427445710739502, -0.964818851818312, -0.9806459553630136, -0.9899482381150326, -0.9925772072882122, -0.9885194343418038, -0.9778993377060572, -0.9609787365530525, -0.9381531554851777, -0.9099449389738903, -0.8769933122456963, -0.8400416001625275, -0.7999218856317613, -0.7575374524755762, -0.7138434129183365, -0.6698259655399968, -0.6264807645523931, -0.5847909047027915, -0.5457050373980435, -0.5101161324734513, -0.4788413864085961, -0.4526037520299462, -0.43201552744623584, -0.4175643940310357, -0.4096022358519213, -0.4083370074354878, -0.41382784473931694, -0.42598353742341133, -0.44456440083951404, -0.4691875055234892, -0.4993351423437524, -0.5343663247635917, -0.5735310577810451, -0.6159870377629496, -0.6608183901753572, -0.7070560045165468, -0.7536989887334488, -0.799736739937499, -0.8441711149384591, -0.8860381832922811, -0.9244290572138341, -0.9585093165335243, -0.9875365822769424, -1.0108758385336045, -1.0280121579093688, -1.0385605496486199, -1.0422727198906192, -1.0390406087535589, -1.0288966471678997, -1.0120107556850224, -0.9886841859224856, -0.9593403809530351, -0.9245131019528705, -0.8848321330658054, -0.8410069331443892, -0.7938086504267847, -0.7440509531618408, -0.6925701548274794, -0.6402051263045277, -0.5877774888705741, -0.5360725711710873, -0.4858215907146005, -0.4376854865272058, -0.3922407852693761, -0.3499678295028466, -0.3112416352626717, -0.27632557819933123, -0.24536803502210186, -0.21840203162440477, -0.19534787299707962, -0.17601865474818268, -0.16012848363116097, -0.14730316674473468, -0.137093067694624, -0.12898777452407956, -0.12243217995141022, -0.11684354048957538, -0.11162905819645166, -0.1062035176650509, -0.10000651166700918, -0.09251880156602531, -0.08327738287772944, -0.0718888615355994, -0.058040791621958646, -0.04151067938049628, -0.022172419861952113, -2.1961979737108725e-16], [0.0, 0.025088625794153607, 0.052578444615261316, 0.08216541720512201, 0.1134662545966399, 0.1460292512280463, 0.1793470917371, 0.2128712922859231, 0.24602789388899768, 0.2782339916037906, 0.30891466045799887, 0.33751982722486695, 0.3635406369315877, 0.38652487431843063, 0.40609102308993766, 0.42194057916183975, 0.43386827738498446, 0.44176994334675035, 0.44564774151363923, 0.4456126566968342, 0.4418841159519239, 0.4347867308075685, 0.42474421332871837, 0.41227059210705813, 0.39795892400560695, 0.3824677626046488, 0.36650570315290704, 0.3508143749249242, 0.3361502939172242, 0.32326602069999255, 0.312891089146316, 0.3057131811280447, 0.3023600198228202, 0.3033824400408997, 0.3092390682667661, 0.3202830085186353, 0.33675088353018884, 0.358754525274647, 0.3862755458261761, 0.4191629505219533, 0.45713388203650684, 0.49977750810523636, 0.546561989099648, 0.5968443863461664, 0.6498832998505223, 0.7048539567253204, 0.7608654107875104, 0.8169794610053062, 0.872230853045247, 0.9256482951861645, 0.9762757981590985, 1.023193838596147, 1.065539847992114, 1.1025275433694186, 1.1334646418613397, 1.1577685385753322, 1.1749795744773583, 1.1847715775087462, 1.1869594243440154, 1.1815034405661295, 1.1685105318673183, 1.1482320163614177, 1.121058206334562, 1.087509864862815, 1.048226736813361, 1.0039534230192908, 0.9555229291939973, 0.903838275906104, 0.8498526013432838, 0.7945482235555823, 0.7389151525455147, 0.6839295543985655, 0.630532669350894, 0.5796106732943679, 0.5319759480429114, 0.4883501903370249, 0.44934974392675614, 0.4154734842805167, 0.38709352287347853, 0.36444892916072125, 0.34764259493299765, 0.3366412895930876, 0.33127887784835697, 0.3312625952791247, 0.336182204073182, 0.34552178270051337, 0.3586738411070137, 0.37495539864062316, 0.3936256167002591, 0.41390454310130725, 0.43499250121024, 0.4560896445691229, 0.47641519727385856, 0.49522591175892905, 0.5118332985537561, 0.5256192164040469, 0.5360494550190045, 0.5426849954877158, 0.545190693762463, 0.543341199004704, 0.5370239893557217, 0.5262394810480582, 0.5110982408746658, 0.491815405024661, 0.46870247735319975, 0.44215674553136847, 0.4126486125930886, 0.380707192694122, 0.34690456215465043, 0.31183908903166363, 0.2761182857750417, 0.24034163945007225, 0.20508387233369546, 0.17087907247841083, 0.13820610944233533, 0.10747571544307204, 0.07901956760782186, 0.053081653905251824, 0.029812145111777256, 0.009263929320590648, -0.008608104279135328, -0.02394501756970847, -0.036979069116581754, -0.048026381503811055, -0.057477226159311945, -0.06578418391271255, -0.07344849540781646, -0.08100496335124709, -0.08900580719822238, -0.09800389926727149, -0.10853582870683333, -0.12110524575234491, -0.13616693314403253, -0.15411203454603076, -0.17525484172815248, -0.19982150383266142, -0.22794097420119913, -0.259638454170934, -0.2948315303618205, -0.333329133839651, -0.3748333778582006, -0.41894425745578023, -0.46516712085163403, -0.5129227512016932, -0.5615598296319505, -0.6103694882818902, -0.6586016069377947, -0.7054824601216225, -0.7502332844233863, -0.7920893093830796, -0.8303187800399646, -0.8642414957901341, -0.8932463985546643, -0.9168077632930423, -0.9344995751419127, -0.9460077191798968, -0.9511396600158799, -0.9498313478338315, -0.9421511537581689, -0.9283007088143846, -0.9086125956029943, -0.8835449182449402, -0.8536728523143793, -0.8196773504738886, -0.7823312495414848, -0.7424830890163681, -0.7010390080769442, -0.6589431363239505, -0.6171569318684983, -0.5766379477982398, -0.5383185238985398, -0.50308490434818, -0.4717572738332695, -0.44507118430840903, -0.4236608129544852, -0.4080444494922546, -0.3986125589290981, -0.3956187052994917, -0.39917355447279734, -0.40924210128115884, -0.42564418983352936, -0.4480583177851985, -0.4760286374241071, -0.5089749906098896, -0.5462057427024957, -0.5869331143916016, -0.6302906513939379, -0.6753524217526704, -0.7211534901667788, -0.7667111893710944, -0.8110466907838516, -0.8532063708585674, -0.8922824759457828, -0.9274326068152309, -0.9578975738445603, -0.9830172144994852, -1.0022438151015012, -1.0151528377551786, -1.0214507192320035, -1.0209795799559656, -1.013718756250812, -0.9997831458463944, -0.9794184334164391, -0.9529933377519978, -0.9209890932348228, -0.8839864438304429, -0.8426504862785175, -0.7977137491029813, -0.7499579342947396, -0.7001947780757168, -0.6492465053412374, -0.5979263587872342, -0.5470196782408893, -0.49726598850464393, -0.44934252556013876, -0.4038495920054098, -0.36129808411901726, -0.3220994761962224, -0.28655848422515984, -0.25486856217208614, -0.22711031185734837, -0.20325281344431662, -0.18315780978628307, -0.16658660612693424, -0.15320947871980137, -0.1426173235133467, -0.13433522069218043, -0.1278375439428581, -0.12256420598265305, -0.11793760506717699, -0.11337982152830535, -0.1083296092572764, -0.10225873451887725, -0.0946872333494397, -0.08519718855616175, -0.07344466722671239, -0.05916950865111493, -0.042202709399322816, -0.022471215538103013, -2.2181305355445907e-16], [0.0, 0.025152089929553537, 0.052507648535497595, 0.08173186284284138, 0.11241856948422915, 0.1441018492650197, 0.17626935396744808, 0.20837701159641897, 0.23986471956042044, 0.27017260855085956, 0.29875744381980324, 0.32510872557941134, 0.34876405649711817, 0.3693233615971161, 0.38646157387996904, 0.39993943694839285, 0.40961212293678445, 0.41543541891485497, 0.4174692963023544, 0.41587874415762793, 0.41093181682591484, 0.4029949176065075, 0.39252541103173516, 0.38006172525850074, 0.3662111712152837, 0.3516357648755159, 0.3370363918253757, 0.3231356978139453, 0.3106601240736729, 0.3003215309694018, 0.2927988673207014, 0.28872034516313505, 0.288646570670019, 0.2930550616329018, 0.3023265507633214, 0.3167334328669417, 0.336430663642669, 0.361449359690155, 0.3916932846836528, 0.426938337166033, 0.46683508273577284, 0.5109142993260246, 0.5585954306309119, 0.6091977713354781, 0.66195414041607, 0.7160267370657101, 0.7705248192956619, 0.8245237993266284, 0.8770853136588662, 0.927277800110944, 0.9741970997928405, 1.0169865993054847, 1.0548564375245437, 1.087101321932212, 1.113116531124135, 1.1324117220847656, 1.1446222120852925, 1.1495174643768011, 1.1470065727920282, 1.137140611333129, 1.1201117890875094, 1.0962494265744442, 1.0660128450400999, 1.0299813334539238, 0.9888414272343582, 0.9433717963626878, 0.8944260969850288, 0.8429141884846214, 0.7897821561706819, 0.7359916072547729, 0.6824987240115203, 0.6302335625641783, 0.5800800785009824, 0.5328573417072661, 0.4893023728668726, 0.4500549937920795, 0.41564503408465153, 0.38648217884110664, 0.3628486776193302, 0.34489506527113023, 0.3326389722283827, 0.32596702720276666, 0.32463978085044487, 0.32829950658473345, 0.33648066615943617, 0.34862276456356334, 0.364085262696759, 0.3821641685902192, 0.40210988974706147, 0.42314590140881064, 0.4444877688610282, 0.4653620566462375, 0.48502466384717946, 0.5027781422431743, 0.5179875826515866, 0.5300946934010393, 0.5386297426499672, 0.5432210919452191, 0.5436021105991453, 0.5396153275795622, 0.531213747965719, 0.5184593328583763, 0.5015187131437758, 0.48065627691222784, 0.4562248358908694, 0.4286541363354364, 0.3984375329458357, 0.36611718921045205, 0.33226820303963034, 0.29748208175170754, 0.26235000481597925, 0.22744631589998884, 0.19331267765890836, 0.16044330357069078, 0.12927165146663583, 0.10015892400158012, 0.07338467316383193, 0.049139750273807105, 0.027521781181581065, 0.008533280118806759, -0.007917553425986355, -0.0220133806029495, -0.03402170712042819, -0.04428646743286008, -0.053217434264635335, -0.06127773559680611, -0.06896981108840024, -0.07682018126536769, -0.08536343463202171, -0.09512585932619906, -0.10660915649463998, -0.12027467192806675, -0.1365285706665546, -0.15570835654724624, -0.17807110557536263, -0.20378373937410527, -0.23291561386853538, -0.26543364005654657, -0.3012000896733284, -0.3399731703672712, -0.38141038438515346, -0.42507461348653, -0.4704428026651604, -0.5169170480177657, -0.5638378314667154, -0.6104990886010919, -0.6561647470859716, -0.7000863331510743, -0.7415212136368325, -0.779751021732665, -0.814099806408551, -0.8439514488582499, -0.868765903997416, -0.888093850865163, -0.9015893720597717, -0.9090203282329241, -0.9102761480661611, -0.9053728157386822, -0.894454905166635, -0.8777945816057667, -0.8557875648134124, -0.8289461220533315, -0.7978892319733791, -0.7633301299958577, -0.7260615106126714, -0.6869387202668468, -0.646861324880054, -0.6067534772964681, -0.5675435409234221, -0.5301434458759764, -0.4954282624607087, -0.46421647363141405, -0.4372514131711539, -0.41518431014297674, -0.39855934322663533, -0.387801061804389, -0.38320447520192696, -0.38492804867060537, -0.39298977603661917, -0.4072664261072541, -0.4274959846831056, -0.45328323820692024, -0.4841083705280129, -0.5193383727888217, -0.5582409997848327, -0.6000009459304356, -0.6437378616431444, -0.6885257878052348, -0.733413553018552, -0.7774456564278472, -0.8196831484734215, -0.8592240232857038, -0.8952226495044382, -0.9269077907584928, -0.9535988022652948, -0.9747196351247637, -0.9898103337726988, -0.9985357733911165, -1.0006914513348975, -0.9962062181693324, -0.9851419079632676, -0.9676899022302718, -0.9441647355243848, -0.9149949213775228, -0.8807112432881888, -0.8419328152294249, -0.7993512681894387, -0.7537134623353768, -0.7058031574680131, -0.6564220967302655, -0.6063709695311684, -0.5564307191157247, -0.5073446482018132, -0.4598017529546413, -0.4144216818883202, -0.3717416729447891, -0.33220577011138935, -0.29615656181889555, -0.2638296185074907, -0.23535073779405863, -0.21073603435354216, -0.18989483972873633, -0.17263530660583934, -0.1586725444021897, -0.14763904999459834, -0.13909714063805123, -0.13255304699272236, -0.127472283905694, -0.1232958861719336, -0.11945707666786967, -0.11539792548449611, -0.11058556118124263, -0.10452750894983595, -0.09678575495146022, -0.08698917073221143, -0.0748439755376097, -0.06014196641110536, -0.042766304844330714, -0.022694712948131857, -2.232131868199314e-16], [0.0, 0.025118216946375324, 0.052231489732126664, 0.08097944879127424, 0.11093852436976846, 0.1416341366266994, 0.17255437348780828, 0.2031647923449387, 0.23292395162453883, 0.2612992582546465, 0.2877827076600574, 0.3119060943601645, 0.3332552835108989, 0.35148315652640244, 0.36632087667730534, 0.37758716247908414, 0.38519530671292596, 0.38915773581436697, 0.38958796669896156, 0.3866998843076517, 0.3808043315857003, 0.37230307253783007, 0.36168025669279796, 0.34949157805505954, 0.3363513817819289, 0.3229180258757577, 0.30987785174578664, 0.297928155381581, 0.2877595791115193, 0.280038361756971, 0.27538889195449245, 0.27437700529364567, 0.27749445077167423, 0.28514492623757753, 0.2976320465930078, 0.31514956339355227, 0.33777410124012003, 0.36546061625924325, 0.3980407165086321, 0.43522391491212004, 0.4766018140249902, 0.5216551503102166, 0.5697635554337233, 0.6202178250954067, 0.6722344237605618, 0.7249718978854235, 0.7775488222282768, 0.8290628648026568, 0.8786105269413778, 0.9253070965362202, 0.9683063452730358, 1.006819504797304, 1.040133072143182, 1.0676250210852527, 1.0887790327030022, 1.103196404506571, 1.1106053518493633, 1.110867476734502, 1.1039812460209708, 1.0900823918283582, 1.069441219906899, 1.042456885108305, 1.0096487650785062, 0.9716451321452263, 0.9291693874169018, 0.8830241787882791, 0.8340737744613579, 0.7832251045277583, 0.7314079141300752, 0.6795544919790656, 0.6285794470679099, 0.5793600040849819, 0.5327172743536697, 0.4893989344697096, 0.450063709780377, 0.41526801532614427, 0.38545505394620155, 0.36094661124148353, 0.3419377214710661, 0.3284943088446851, 0.32055383677531346, 0.3179289252347359, 0.32031382518483026, 0.3272935708770177, 0.3383555672844036, 0.3529033126000731, 0.37027190598967147, 0.3897449498258178, 0.4105724244358052, 0.43198909269914154, 0.45323298211340834, 0.4735634934089267, 0.4922786973610903, 0.5087314047753907, 0.522343628089974, 0.5326190957895481, 0.5391535317602761, 0.5416424695443759, 0.5398864347139786, 0.5337933956828279, 0.523378452526262, 0.5087608030493133, 0.4901580936876834, 0.46787832814176783, 0.4423095673036231, 0.4139077085346001, 0.3831826793377717, 0.3506834187854074, 0.31698204876787456, 0.2826576555289983, 0.24828010960629854, 0.21439434903492022, 0.18150553660780894, 0.15006547748945495, 0.1204606491952212, 0.09300215275732307, 0.06791784290915201, 0.04534683763416459, 0.025336544908724813, 0.007842278510276145, -0.0072705329610727055, -0.020221607468484754, -0.031308671047595604, -0.0408981118978444, -0.0494136773135506, -0.05732351509857116, -0.06512590477533307, -0.07333405873421195, -0.08246039858223668, -0.09300072669505798, -0.10541871696798677, -0.12013114188618708, -0.13749423544992204, -0.15779156362697203, -0.1812237365490434, -0.20790025055243835, -0.23783369453473188, -0.2709364952984694, -0.30702031207697844, -0.3457981229028042, -0.38688897658243554, -0.42982531551522296, -0.47406270816695, -0.5189917673574523, -0.5639519732336561, -0.6082470693302026, -0.6511616577575802, -0.6919785863906381, -0.7299966978196422, -0.7645484973833283, -0.7950172961759506, -0.8208533945814637, -0.8415888924350869, -0.8568507428715316, -0.8663717075561173, -0.8699989203336478, -0.867699823175764, -0.8595653012770103, -0.845809911704749, -0.8267691704927457, -0.8028939347513108, -0.7747419874832441, -0.7429670015900497, -0.7083051243257033, -0.671559482601136, -0.6335829615918631, -0.5952596527568056, -0.557485401545933, -0.5211479088964681, -0.48710685348480487, -0.4561745032742096, -0.429097275114946, -0.40653868023034034, -0.38906406184983744, -0.377127489781155, -0.37106112634394595, -0.3710673200326879, -0.3772136189413931, -0.3894308269272392, -0.4075141533907889, -0.43112743415911553, -0.45981032805932415, -0.49298832313654106, -0.5299853198201898, -0.5700384972958348, -0.6123151153802066, -0.655930858633777, -0.6999692933821504, -0.7435019826253241, -0.7856087891089402, -0.8253978934609655, -0.862025062330272, -0.8947117206900113, -0.9227614124044877, -0.9455742730573451, -0.9626591879119979, -0.9736433645138729, -0.9782791124514102, -0.9764476906172057, -0.9681601532850914, -0.9535551987011758, -0.9328940959033379, -0.9065528353727846, -0.8750117151770291, -0.8388426348776338, -0.7986944231769979, -0.7552765707685744, -0.7093417760412116, -0.6616677373102392, -0.6130386404972967, -0.5642267953172854, -0.5159748659893976, -0.4689791244816358, -0.42387412580773415, -0.3812191666632312, -0.34148684169551907, -0.3050539571474639, -0.2721950008775686, -0.24307830237403683, -0.21776494799009014, -0.1962104469490682, -0.1782690744444217, -0.1637007511205627, -0.15218025503643204, -0.14330850445570245, -0.1366255989080957, -0.1316252631833777, -0.12777030530581715, -0.12450867591335532, -0.12128970340181379, -0.11758007699384866, -0.11287915858578418, -0.10673322357016411, -0.09874826031785719, -0.08860099686684032, -0.07604787060632567, -0.06093171115614637, -0.043185966834339534, -0.022836369548454215, -2.237715756273732e-16], [0.0, 0.024984485578599988, 0.051747927101542704, 0.0799096706060134, 0.10903415398926151, 0.13864352772513253, 0.16823151885309426, 0.19727816866291975, 0.22526505095827318, 0.2516905643060041, 0.2760848886166462, 0.29802420384497214, 0.317143786372492, 0.33314962630124906, 0.34582824576538224, 0.35505444353635807, 0.36079674353243574, 0.3631203830340062, 0.36218773899605766, 0.3582561562664525, 0.3516732081197253, 0.3428694856239133, 0.3323490763050623, 0.32067795274412936, 0.30847054660907397, 0.29637483179584184, 0.285056280595094, 0.27518108808214997, 0.2673990814324401, 0.26232674202303885, 0.2605307686786011, 0.26251260020842687, 0.268694294678325, 0.27940613214599264, 0.29487626759157004, 0.31522271245800887, 0.3404478677499729, 0.3704357703763239, 0.4049521488578342, 0.4436473162665197, 0.48606185899404586, 0.5316350113708164, 0.5797155399680375, 0.6295748992500219, 0.680422363645181, 0.7314217914790002, 0.7817096347990071, 0.8304137769584633, 0.8766727577242972, 0.919654934201523, 0.9585771253262608, 0.9927222981095031, 1.0214558749812674, 1.0442402729931919, 1.060647326538269, 1.0703682946568454, 1.0732212107260573, 1.069155395002775, 1.0582530175883575, 1.0407276692779368, 1.0169199687489974, 0.9872903049074443, 0.9524088812325414, 0.9129432929904574, 0.869643926662495, 0.8233275224371412, 0.7748592838944627, 0.7251339530180205, 0.6750562925820731, 0.6255214312058044, 0.5773955286295024, 0.5314972100059436, 0.48858019844056255, 0.44931754514678035, 0.414287817151049, 0.38396355446214525, 0.3587022531967033, 0.3387400696939298, 0.3241883746686342, 0.3150332175643102, 0.31113769116637113, 0.3122471169366902, 0.31799690413557186, 0.3279228722504027, 0.3414737680978327, 0.3580256576190489, 0.37689782908558644, 0.39736981021552187, 0.41869907737969575, 0.4401390212218448, 0.46095672993233244, 0.4804501591428591, 0.4979642757218156, 0.512905791158025, 0.5247561379867962, 0.5330823888682249, 0.5375458712997281, 0.5379082901821175, 0.5340352340680719, 0.5258970073050659, 0.5135667977776007, 0.4972162568681211, 0.47710863292230377, 0.45358966031236325, 0.42707646163096474, 0.3980447692450313, 0.36701481319097484, 0.3345362541996091, 0.3011725627249494, 0.2674852566856885, 0.23401841193881148, 0.20128385028325427, 0.16974739029367697, 0.139816517024096, 0.11182978835637233, 0.08604824948310448, 0.06264907389247233, 0.04172159061901732, 0.02326579493104495, 0.0071933746333326136, -0.006668781576377803, -0.018572692078479693, -0.028841167266445294, -0.037857690192037094, -0.04605456415769061, -0.0538996440303302, -0.06188200547675443, -0.07049693468088056, -0.08023063967142878, -0.09154509268525038, -0.10486341079517827, -0.12055616938482974, -0.13892902026228354, -0.16021195383174622, -0.18455050359075253, -0.21199914231555486, -0.24251706386085356, -0.27596648391958845, -0.3121135288832912, -0.35063171572580276, -0.3911079592689017, -0.43305097795487046, -0.4759019069953096, -0.5190468700632248, -0.5618312090111979, -0.6035750267493469, -0.6435896625390466, -0.6811946924788871, -0.7157350315724803, -0.7465977079171016, -0.7732278844198841, -0.7951437189496343, -0.8119496796174758, -0.8233479673420117, -0.8291477421458957, -0.829271901680804, -0.8237612190217192, -0.8127757103802589, -0.7965931705027144, -0.7756048824933583, -0.7503085779397405, -0.7212987908087056, -0.6892548129590595, -0.6549265186840676, -0.6191183789754917, -0.5826720318633024, -0.5464478120898809, -0.5113056705967293, -0.47808593114381326, -0.44759033741028914, -0.42056383896836125, -0.39767754867780003, -0.37951327768286997, -0.3665500179304299, -0.3591526968362989, -0.3575634754969397, -0.3618958019618153, -0.37213136599878655, -0.388120033080002, -0.4095827646577767, -0.4361174609066707, -0.4672075927036512, -0.5022334233911147, -0.5404855594284823, -0.5811805138809794, -0.6234779191589527, -0.6664989866609, -0.7093457819264742, -0.7511208652720891, -0.7909468401061591, -0.827985354381991, -0.8614551148524329, -0.8906484985815938, -0.9149463809267133, -0.9338308430652548, -0.9468954740241665, -0.9538530407899838, -0.954540363996972, -0.9489203043342341, -0.9370808345214467, -0.919231241768071, -0.895695574338254, -0.866903511515195, -0.8333788972943583, -0.7957262330514593, -0.7546154718992345, -0.7107654963234868, -0.6649266900446346, -0.6178630341941556, -0.570334166387372, -0.5230778389407297, -0.47679319941705806, -0.4321252932452617, -0.3896511549669742, -0.3498678125672075, -0.3131824794237545, -0.2799051519270656, -0.2502437692049086, -0.22430202618508904, -0.20207986408126405, -0.1834765949725103, -0.16829655115111625, -0.15625708698016572, -0.1469987026980853, -0.14009700737794273, -0.13507619338664345, -0.13142365829826422, -0.12860538318758108, -0.12608165921928322, -0.12332274785821508, -0.11982406399710953, -0.11512048570639727, -0.10879941876974479, -0.10051227804095358, -0.08998409006917467, -0.07702097130263329, -0.06151529222267146, -0.04344839855197037, -0.02289082467708968, -2.2345117074042243e-16], [0.0, 0.024749659003940286, 0.051057483224821926, 0.07852779440530398, 0.1067183328893848, 0.13515314703805678, 0.1633364843951698, 0.19076731364222846, 0.21695408919016876, 0.2414293630099294, 0.26376385119526086, 0.28357957571885933, 0.30056172457088054, 0.31446890539544997, 0.3251415080720446, 0.3325079394182679, 0.3365885471249057, 0.3374971088218719, 0.3354398243394739, 0.33071181321088045, 0.32369118364816385, 0.3148308019973067, 0.30464795145112566, 0.2937121240594298, 0.2826312394192634, 0.27203662559654274, 0.26256713174237317, 0.2548527666457562, 0.24949827245834785, 0.24706704762853224, 0.24806582753678452, 0.25293051553524215, 0.2620135314201613, 0.27557300941202734, 0.29376413432226506, 0.31663285379730655, 0.34411214758577985, 0.3760209730639879, 0.41206594129119584, 0.4518457112460702, 0.4948580232600183, 0.5405092276571516, 0.5881261028424384, 0.6369697000807809, 0.6862509013972296, 0.7351473336692997, 0.7828212471620253, 0.8284379413521699, 0.8711843055467141, 0.9102870369226205, 0.9450301043433319, 0.9747710425255282, 0.9989556874621679, 1.0171309998309763, 1.0289556675735139, 1.0342082308482783, 1.03279253088482, 1.0247403474816874, 1.0102111564651735, 0.989489006740985, 0.9629765849660108, 0.9311866026787399, 0.8947307043287785, 0.8543061534910767, 0.8106806072075754, 0.7646753335882791, 0.7171472644284257, 0.6689703017712749, 0.6210163144120137, 0.5741362668892421, 0.5291419193969533, 0.4867885223825097, 0.4477589047448474, 0.41264932013040734, 0.38195737269465846, 0.35607229291960935, 0.33526777690356196, 0.3196975403752925, 0.3093936730576292, 0.30426781152508026, 0.30411508101931767, 0.30862069046009993, 0.3173690017339362, 0.3298548357964818, 0.345496725608995, 0.363651780714681, 0.3836317914354518, 0.4047201731126494, 0.4261893331751074, 0.4473180364970523, 0.46740834765332956, 0.4858017421778916, 0.5018940024151565, 0.5151485464080563, 0.5251078796461045, 0.5314029083466345, 0.5337599080250405, 0.532005001035495, 0.5260660600255608, 0.5159720192599351, 0.5018496409038283, 0.4839178469894427, 0.46247978833467596, 0.43791287763718756, 0.41065706394245877, 0.3812016684470354, 0.3500711360958457, 0.3178100828222925, 0.284968033948251, 0.25208425483912494, 0.21967307028136754, 0.18821005435705612, 0.15811944822520388, 0.12976312981797902, 0.10343141788323555, 0.07933594411879918, 0.05760477259226138, 0.03827988661245973, 0.02131710121669487, 0.006588396036036801, -0.006113399890878888, -0.017067701164131647, -0.026617224746539107, -0.03515725535062222, -0.04312340545024727, -0.050978197470748166, -0.05919682691141869, -0.0682524871660809, -0.0786016490659459, -0.09066969035458576, -0.10483726235155648, -0.1214277631583702, -0.14069625934819677, -0.16282016183880724, -0.1878919174797517, -0.21591392689305586, -0.24679584256828074, -0.2803543405453483, -0.316315395745829, -0.35431902672671745, -0.3939264119498918, -0.4346292181926705, -0.47586092402485525, -0.5170098688087049, -0.5574337117755226, -0.596474947569511, -0.6334770952085872, -0.6678011574593051, -0.6988419376901763, -0.7260438016364489, -0.7489154822057689, -0.7670435462465427, -0.7801041726057267, -0.7878729300963547, -0.7902322912308289, -0.78717667160777, -0.7788148443505657, -0.765369642528353, -0.7471749284856417, -0.7246698758412468, -0.6983906759425527, -0.6689598441456212, -0.6370733608606408, -0.6034859363765551, -0.5689947357127197, -0.5344219389587359, -0.5005965427717957, -0.468335829139793, -0.4384269376624675, -0.41160897717975864, -0.38855610157260917, -0.36986195322377263, -0.35602584645567453, -0.3474410230019842, -0.3443852631866487, -0.34701408114580656, -0.3553566714736501, -0.36931470958070967, -0.3886640404028792, -0.4130592215359391, -0.44204081906089315, -0.4750452889198917, -0.5114172152922809, -0.5504236214992487, -0.5912700198934511, -0.6331178261587932, -0.6751027314502078, -0.716353603617446, -0.756011476913732, -0.7932481883693129, -0.8272842284308688, -0.8574053932894979, -0.8829778560466778, -0.9034613127614728, -0.9184199065215567, -0.927530686823667, -0.9305894214026371, -0.9275136417411307, -0.9183428702510629, -0.9032360449063057, -0.8824662242654819, -0.856412720712765, -0.8255508707815085, -0.7904397071258418, -0.7517078457188117, -0.7100379429992929, -0.6661501099772856, -0.6207846929719494, -0.5746848431720075, -0.5285792992985057, -0.483165799298187, -0.4390955184432509, -0.3969589029528011, -0.35727323101542996, -0.3204721878338705, -0.28689768918169145, -0.25679413027617476, -0.230305174983654, -0.20747313603517517, -0.1882409316527956, -0.17245653940125383, -0.15987980579662797, -0.15019141177240194, -0.14300374097415036, -0.13787335134161022, -0.13431471168796366, -0.1318148349510539, -0.1298484192005917, -0.12789309683189426, -0.12544439190326545, -0.12202999526804094, -0.11722298674585761, -0.11065366255502211, -0.10201966383809238, -0.09109414738926341, -0.07773179147640126, -0.06187248662181575, -0.04354262191392504, -0.02285394032390664, -2.2222670470174216e-16], [0.0, 0.02441377310898743, 0.05016318404030248, 0.07684271272354797, 0.10400851514698642, 0.13119142448994417, 0.15791071825474945, 0.18368828313752392, 0.20806279828561702, 0.23060355622455758, 0.2509235491430147, 0.2686914661982258, 0.28364227460331537, 0.295586092808363, 0.3044151072020162, 0.31010833336149946, 0.31273407772319667, 0.3124500142571254, 0.30950085183101195, 0.3042136299053023, 0.29699074144741366, 0.2883008409450199, 0.27866785064113875, 0.2686583282064125, 0.25886750273069825, 0.2499043220397444, 0.2423758819925236, 0.23687162686996924, 0.2339477187337239, 0.2341119724623016, 0.23780974205739674, 0.24541112299851364, 0.257199805395414, 0.27336387416140806, 0.29398880633557467, 0.3190528631382403, 0.3484250166338406, 0.38186548941217663, 0.41902892199287034, 0.45947011827730405, 0.5026522559064295, 0.5479573874012836, 0.5946990009775596, 0.6421363583521126, 0.6894902819831847, 0.7359600271299017, 0.7807408458120668, 0.8230418309163173, 0.862103619815209, 0.8972155381834492, 0.9277317762014734, 0.9530862107716433, 0.9728055182327806, 0.9865202616087869, 0.9939736837166607, 0.9950279913472081, 0.98966797491411, 0.9780018710085859, 0.9602594406668052, 0.9367873022664122, 0.9080416232088748, 0.8745783373283568, 0.8370411137672169, 0.7961473564423475, 0.752672559896709, 0.7074333861524351, 0.6612698572137915, 0.615027078383255, 0.5695369180588201, 0.5256000699267026, 0.4839689134544349, 0.44533156857858924, 0.4102975109683437, 0.3793850759617355, 0.35301113316127813, 0.33148316087579316, 0.3149938914045694, 0.3036186360078423, 0.29731533381844616, 0.2959273035057136, 0.2991886118047792, 0.30673191065225486, 0.3180985361425509, 0.33275060926054034, 0.35008483164602644, 0.36944763062995795, 0.3901512773862141, 0.41149058098652064, 0.43275974991799165, 0.4532690114678516, 0.47236058829343985, 0.48942365022427486, 0.5039078873910919, 0.5153353874191258, 0.5233105437230814, 0.5275277727748785, 0.5277768742988604, 0.5239459282713856, 0.5160216848593933, 0.5040874664676345, 0.48831866330289747, 0.468975963755298, 0.4463965169527911, 0.4209832756757925, 0.3931928121676092, 0.3635219361513665, 0.33249347266472895, 0.3006415764631137, 0.2684969692641672, 0.23657248579636278, 0.20534930450505173, 0.17526421913810533, 0.14669827879683917, 0.11996708713821379, 0.09531300719964984, 0.07289946791947517, 0.05280751312937458, 0.035034675007604106, 0.019496193197193996, 0.0060285395549987564, -0.005604851641113062, -0.015705805713233056, -0.024631792949091104, -0.03278473642060516, -0.04059854269852868, -0.048525689534651334, -0.05702322964824088, -0.06653858561505978, -0.07749551710645274, -0.09028063819574883, -0.1052308492189564, -0.12262202507018923, -0.14265927038963952, -0.16546901264589634, -0.19109315761072887, -0.21948547933739068, -0.25051035979677366, -0.28394393322981426, -0.3194776285510685, -0.35672404134192554, -0.39522500666195887, -0.4344616866080526, -0.4738664337151357, -0.5128361442625917, -0.5507467755267587, -0.5869686690296646, -0.6208822987056387, -0.6518940492493023, -0.67945162609425, -0.7030587046298484, -0.7222884422741725, -0.7367955025184116, -0.7463262744391767, -0.7507270136147131, -0.7499496798514156, -0.7440553024235346, -0.7332147632993951, -0.7177069516056593, -0.6979143068230631, -0.6743158323288307, -0.64747772331844, -0.6180418123070013, -0.5867120898599612, -0.5542396065789345, -0.5214061034640253, -0.4890067505582106, -0.4578323974249068, -0.4286517529131487, -0.40219391546052313, -0.3791316687557537, -0.3600659410646137, -0.3455118002975757, -0.33588632158683956, -0.33149862058951846, -0.33254229499182, -0.3390904599821399, -0.3510935021631118, -0.368379611971291, -0.390658088733159, -0.41752534661099566, -0.44847348548466126, -0.4829012298381592, -0.5201269824570317, -0.5594036895630295, -0.5999351711363842, -0.6408935356445935, -0.6814372730468361, -0.720729604386969, -0.7579566608975327, -0.7923450704352072, -0.8231785441256718, -0.8498130809352924, -0.8716904418913334, -0.888349588000637, -0.8994358255248986, -0.9047074579375879, -0.9040398042447032, -0.8974265069175926, -0.8849781179026334, -0.866918016443408, -0.8435757761809578, -0.8153781596321784, -0.7828379742096365, -0.7465410740775313, -0.70713183512605, -0.6652974651563441, -0.6217515371707576, -0.5772171498513096, -0.5324101255162973, -0.4880226519496314, -0.4447077606295413, -0.40306501041850074, -0.3636277133267778, -0.3268519983616627, -0.29310796175642334, -0.2626730982454582, -0.2357281498663924, -0.21235544748784252, -0.1925397574187311, -0.1761715826221784, -0.1630528068011106, -0.15290451146824421, -0.14537674250370583, -0.1400599549664499, -0.1364978242387695, -0.13420107894588926, -0.13266198730096365, -0.1313691141530927, -0.12982196139856644, -0.12754510964486057, -0.12410149393726722, -0.11910447057097336, -0.11222836488572438, -0.10321723062803531, -0.09189159892424073, -0.07815304792430992, -0.06198648140073544, -0.04346006456362624, -0.022722826559114843, -2.2008475618636407e-16], [0.0, 0.023978109509972444, 0.04907046907590925, 0.07486675854741298, 0.1009264224258172, 0.1267916324903494, 0.1520007890904019, 0.17610219938279587, 0.19866756548724976, 0.21930491964541682, 0.23767065690343503, 0.2534803382646279, 0.26651796812074785, 0.27664348829699487, 0.28379827627424536, 0.28800848594800965, 0.2893861243726597, 0.28812781593675635, 0.28451126486114076, 0.2788894863074005, 0.2716829342307837, 0.2633697089453184, 0.2544740777994313, 0.2455535871051922, 0.23718508138079616, 0.2299499760801479, 0.22441915151465952, 0.22113784805295994, 0.22061094557376426, 0.22328900344166816, 0.22955542111022, 0.23971505420261793, 0.25398458717636985, 0.27248492225561755, 0.2952357962177666, 0.322152783022096, 0.3530467824789138, 0.3876260345974212, 0.42550063740948757, 0.4661894844708311, 0.5091294784137752, 0.5536868203494201, 0.5991701229972165, 0.644845049449718, 0.689950140608787, 0.7337134635327387, 0.7753696909906236, 0.8141772099921282, 0.8494348542805079, 0.8804978628333783, 0.9067926831619193, 0.9278302642446651, 0.9432175186598237, 0.9526666760584439, 0.956002299524189, 0.9531657913999807, 0.9442172744938381, 0.9293347967658584, 0.9088108711341428, 0.8830464253742631, 0.8525422986831271, 0.8178884798344428, 0.7797513355484922, 0.7388591254267909, 0.6959861404012037, 0.6519358341306597, 0.6075233403588942, 0.563557783353692, 0.5208247928444881, 0.4800696292630018, 0.4419813097165864, 0.40717810036977387, 0.3761947073900816, 0.3494714571569272, 0.32734570805901547, 0.31004568210554556, 0.2976868460787553, 0.2902709104946965, 0.28768745172116944, 0.2897180997657918, 0.2960431730278624, 0.30625058319763415, 0.3198467798993267, 0.33626945690952986, 0.35490170099458723, 0.3750872315793073, 0.39614635536692827, 0.4173922452418941, 0.43814714763693724, 0.45775812713011876, 0.4756119712108683, 0.4911489015351353, 0.5038747699699917, 0.5133714574873843, 0.5193052404944348, 0.5214329413072432, 0.5196057358743916, 0.513770551119375, 0.5039690449146464, 0.4903342222091319, 0.47308479969820566, 0.452517487186623, 0.4289974050677478, 0.402946902858564, 0.37483308236761614, 0.3451543598846281, 0.31442642401593146, 0.28316795891481283, 0.2518865063654327, 0.22106483440418165, 0.19114816507241933, 0.16253258989186328, 0.13555496936385947, 0.11048457304916981, 0.08751667060442246, 0.06676823271446745, 0.048275845476730715, 0.03199588387248482, 0.01780693097165863, 0.005514370958983455, -0.00514297257517227, -0.014484334930033087, -0.022876875619272454, -0.030724183828305197, -0.03845373274999222, -0.04650361926605357, -0.055308944534726005, -0.065288201021385, -0.0768300321085695, -0.09028072162178558, -0.10593275262116576, -0.12401474808156315, -0.14468307128056232, -0.1680153217047527, -0.19400591412130494, -0.222563875352431, -0.2535129365686339, -0.28659394000940686, -0.3214695194310657, -0.3577309547741966, -0.3949070450240763, -0.43247479043760645, -0.4698716275704499, -0.5065089190746412, -0.5417863661115248, -0.5751069853176121, -0.6058922752481849, -0.6335971895606197, -0.6577245361095448, -0.677838432593337, -0.6935764701622606, -0.7046602659862927, -0.7109041234781935, -0.7122215637641106, -0.7086295429982128, -0.700250225983593, -0.6873102459193036, -0.6701374414837455, -0.6491551243746478, -0.6248739913263458, -0.5978818530084931, -0.5688314066281169, -0.5384263281556435, -0.5074060026499277, -0.47652924610204306, -0.4465573986720497, -0.418237186484759, -0.39228375683183386, -0.3693642894858999, -0.3500825748973269, -0.33496492858570903, -0.3244477805606757, -0.31886723983730125, -0.31845088798134175, -0.3233120032421934, -0.3334463594742866, -0.34873168310178965, -0.3689297883271025, -0.39369134715379334, -0.42256318813744476, -0.45499795761849937, -0.49036592099430265, -0.5279686307211819, -0.567054143439379, -0.6068334319612692, -0.6464976097464358, -0.6852355665867681, -0.7222516049960309, -0.7567826674595509, -0.788114755226794, -0.8155981594570992, -0.8386611547564734, -0.8568218427480532, -0.8696978783733071, -0.8770138630162204, -0.8786062450154721, -0.8744256282937196, -0.8645364522138871, -0.849114068842591, -0.8284393060188187, -0.8028906644734098, -0.7729343532641794, -0.7391124186218273, -0.7020292657124417, -0.6623369097429234, -0.6207193213823116, -0.5778762509691665, -0.5345069259715434, -0.4912940164462294, -0.44888825383232034, -0.40789406957497854, -0.368856592305132, -0.33225030631625785, -0.2984696307988225, -0.26782162981314467, -0.2405210085510062, -0.21668749342333019, -0.19634563336989885, -0.1794269990211795, -0.1657746964677786, -0.15515005490012235, -0.1472412936974908, -0.14167392600114342, -0.13802261359956386, -0.13582415312275867, -0.1345912469385678, -0.13382669441116815, -0.1330376307413586, -0.1317494416472514, -0.12951899261234237, -0.12594683103888685, -0.1206880478825139, -0.11346152147769742, -0.10405730936433584, -0.0923420028908111, -0.0782619129496855, -0.061844012035210005, -0.04319461645292795, -0.022495851472507742, -2.1702366992562073e-16], [0.0, 0.02344515379981522, 0.04778707359790165, 0.072615480156428, 0.0974976845866681, 0.12199137070647963, 0.14565769959541267, 0.16807438471782368, 0.1888483860942262, 0.20762788113780337, 0.2241131877132342, 0.2380663412735106, 0.24931906193113265, 0.2577788881723112, 0.2634333006025528, 0.2663517104474159, 0.26668524223288276, 0.2646642967588653, 0.2605939377281095, 0.25484720175608566, 0.2478564855402022, 0.2401032143391888, 0.2321060413259873, 0.2244078666721142, 0.21756199739140247, 0.2121177931858884, 0.20860615916323208, 0.2075252529138559, 0.20932677085138826, 0.21440316696595635, 0.22307613647913135, 0.23558666780735266, 0.252086929433788, 0.2726342146471633, 0.29718711769240574, 0.3256040609003698, 0.3576442351468006, 0.39297095694194323, 0.43115738602827147, 0.4716944890336922, 0.5140010789364836, 0.5574357082315559, 0.6013101470368521, 0.6449041371088743, 0.6874810798574994, 0.7283042917919361, 0.7666534450203029, 0.8018408038763877, 0.8332268716428156, 0.8602350736321065, 0.8823651242966817, 0.899204756062002, 0.9104395254974118, 0.9158604573458574, 0.9153693377426383, 0.9089815234349334, 0.8968261926222567, 0.8791440237447515, 0.856282349675019, 0.8286878948324321, 0.7968972602740656, 0.7615253754224388, 0.7232521834614418, 0.6828078693906581, 0.6409569742537036, 0.598481765309329, 0.5561652492584719, 0.5147742236578474, 0.47504276015153, 0.43765650217915775, 0.40323813964853494, 0.3723343941912421, 0.3454048117656287, 0.32281261543980344, 0.3048178212583968, 0.29157276539706356, 0.2831201326795065, 0.2793935163973538, 0.2802204787046501, 0.285328021138342, 0.2943503175004986, 0.30683850782229166, 0.322272303713312, 0.34007311325427986, 0.35961835873166925, 0.38025663377312247, 0.40132332845473323, 0.42215634213052416, 0.44211150426863666, 0.46057733342475626, 0.4769887833678241, 0.4908396528001799, 0.5016933703777202, 0.5091919089368074, 0.5130626309051926, 0.5131229196024653, 0.5092825071974606, 0.5015434680813633, 0.48999790488741385, 0.47482341188352145, 0.456276455552944, 0.43468386349370935, 0.4104326590398578, 0.38395851909567796, 0.3557331655933522, 0.32625102593145316, 0.29601551412400334, 0.2655252918003828, 0.23526086648350578, 0.20567187380421267, 0.1771653707776887, 0.1500954394860203, 0.12475436519904125, 0.10136561103096012, 0.0800787637453417, 0.060966573496769406, 0.044024155452463284, 0.029170364764570744, 0.016251299696855234, 0.005045832284917963, -0.00472698686839131, -0.013398851853731499, -0.02134169853568506, -0.028956058462919262, -0.03665858259418574, -0.044869069769778475, -0.053997348209572416, -0.06443036273508039, -0.07651981577597013, -0.09057069664107553, -0.10683101134545943, -0.1254829950409053, -0.14663605155308196, -0.17032162062481998, -0.19649012430280907, -0.22501009071960704, -0.2556694976518929, -0.28817932108659833, -0.3221792170404481, -0.3572452094949552, -0.3928992049300555, -0.42862010589413047, -0.463856253558793, -0.49803889335930124, -0.5305963295372914, -0.5609684144158296, -0.5886210070756001, -0.6130600340739324, -0.63384479203651, -0.6506001482061308, -0.6630273199786296, -0.6709129475003184, -0.6741362137482372, -0.6726738131848402, -0.6666026219336008, -0.6560999781911645, -0.6414415399046326, -0.6229967461628427, -0.6012219678107562, -0.5766514900346192, -0.549886523662773, -0.5215824913401832, -0.4924348783319596, -0.46316397440108353, -0.4344988620660489, -0.4071610268434848, -0.38184797629758604, -0.35921725655370607, -0.33987124731912793, -0.3243430995542994, -0.3130841541450705, -0.30645314585282873, -0.3047074552809645, -0.30799662359327473, -0.31635829141321903, -0.32971666601400595, -0.34788356096979706, -0.370561991334718, -0.397352246635405, -0.42776030498405615, -0.4612083958786591, -0.4970474681128144, -0.5345712739148144, -0.5730317420769713, -0.6116552823546042, -0.6496596415493845, -0.6862709189728868, -0.7207403457181616, -0.7523604384234082, -0.7804801538326457, -0.8045186950546893, -0.8239776533855278, -0.8384512100772962, -0.8476341695124288, -0.8513276477173967, -0.8494422967388928, -0.8419990047191671, -0.8291270720944727, -0.8110599247198309, -0.788128483420662, -0.7607523650569518, -0.7294291413071117, -0.6947219267972093, -0.6572456068201455, -0.6176520457811971, -0.5766146399360342, -0.5348125914297555, -0.4929152847979986, -0.45156714188147734, -0.41137331669195304, -0.3728865685365103, -0.33659562026122847, -0.3029152696196661, -0.27217847649286114, -0.24463059812902682, -0.22042589000497106, -0.19962633270569458, -0.1822027868045507, -0.16803841956145035, -0.15693429078903984, -0.14861693186917976, -0.14274770295686567, -0.13893367009516228, -0.13673970734892493, -0.13570150004379636, -0.13533910447534928, -0.13517070752746602, -0.13472622678437493, -0.13356039798469782, -0.1312650118674459, -0.1274799861943163, -0.1219029903817114, -0.11429737892364678, -0.1044982346399447, -0.09241637259760974, -0.07804020905827974, -0.06143545564098716, -0.04274265563948629, -0.022172635657690988, -2.1305333457443458e-16], [0.0, 0.022818539661675283, 0.046322884351881026, 0.0701073798304597, 0.0937514375932784, 0.11683200521684506, 0.1389361555201384, 0.15967345623392193, 0.17868778697258347, 0.1956682839715077, 0.2103591149453774, 0.22256781599343253, 0.2321719589865859, 0.23912396040299244, 0.2434538900652387, 0.2452701894798874, 0.2447582631986682, 0.24217696145632422, 0.2378530269090446, 0.2321736312202099, 0.2255771771765727, 0.2185425877003579, 0.21157734338791387, 0.20520456402390425, 0.1999494560215735, 0.19632546623574462, 0.19482049259626835, 0.19588350323731366, 0.19991190819252494, 0.2072400114484521, 0.2181288465762965, 0.23275766688013116, 0.25121732178695205, 0.2735057060131668, 0.2995254179773026, 0.3290837102173596, 0.3618947585343399, 0.3975842196026968, 0.43569599027203765, 0.4757010271321954, 0.5170080334825775, 0.5589757739165055, 0.6009267354734797, 0.6421618197607567, 0.6819757234702742, 0.7196726460030765, 0.7545819529431681, 0.7860734231643536, 0.8135717154533965, 0.8365697075143851, 0.8546403856873509, 0.8674469970643858, 0.8747512161199127, 0.8764191245141512, 0.8724248542551323, 0.8628517996659423, 0.8478913612585758, 0.8278392432621828, 0.8030893847645553, 0.7741256607838848, 0.7415115427203938, 0.7058779562496292, 0.6679096176268615, 0.6283301655299938, 0.5878864340968616, 0.5473322330185482, 0.5074120119439879, 0.4688447887591146, 0.43230871447487873, 0.3984266316654327, 0.3677529590322638, 0.3407622023339394, 0.31783935241050515, 0.29927238531790273, 0.28524702879340347, 0.275843904643663, 0.2710380995208328, 0.27070115832692043, 0.27460543658510694, 0.28243069195168985, 0.2937727419816761, 0.30815396659419003, 0.3250353905899705, 0.34383004509234083, 0.36391727779051297, 0.3846576610492073, 0.405408134797887, 0.42553701789815146, 0.4444385274601178, 0.46154646016667356, 0.4763467126800129, 0.4883883490519028, 0.49729296094939157, 0.5027621104803184, 0.5045826943486219, 0.5026301207580379, 0.4968692455940971, 0.4873530705711443, 0.4742192618332651, 0.4576846015573687, 0.43803753608161716, 0.4156290307109754, 0.3908619824831957, 0.3641794768017399, 0.33605220111037637, 0.30696534803630293, 0.2774053512050879, 0.24784679898489853, 0.21873986472163784, 0.19049857677201515, 0.163490228233983, 0.1380261953226519, 0.11435439564266454, 0.09265357413102424, 0.0730295562976035, 0.05551355679989669, 0.040062577665439976, 0.026561875983181472, 0.014829427005863437, 0.004622256704472987, -0.0043555307922825744, -0.01244324952456024, -0.02001290888846711, -0.027457560606418664, -0.03517902880938672, -0.04357535292256136, -0.05302828094807533, -0.06389114997505897, -0.07647748133196969, -0.09105059996043079, -0.107814561777587, -0.12690663965033486, -0.14839157896002106, -0.17225778858510785, -0.19841558360632636, -0.22669754338985088, -0.2568609942550599, -0.28859257105768826, -0.32151475810265845, -0.35519425820762424, -0.3891519907763387, -0.4228744766296403, -0.45582633018092605, -0.4874635492853062, -0.5172472705189256, -0.544657643348246, -0.5692074710136965, -0.5904552691473776, -0.6080174051199967, -0.6215790015978078, -0.6309033163032501, -0.63583934582924, -0.6363274436881684, -0.6324027905510405, -0.6241966066804788, -0.6119350516053779, -0.5959358127691813, -0.5766024418089385, -0.5544165528798517, -0.5299280506476295, -0.503743604905701, -0.47651363300710553, -0.44891808932532484, -0.4216513918195879, -0.395406838698442, -0.370860882564728, -0.34865763490942114, -0.3293939702432222, -0.31360558657838206, -0.3017543576859837, -0.2942172830568052, -0.29127730449101924, -0.29311621462254644, -0.2998098335007289, -0.3113255757957757, -0.32752247456442984, -0.3481536691844121, -0.3728713064591176, -0.401233746434479, -0.43271490955732644, -0.46671555077681687, -0.5025762002908147, -0.5395914709858226, -0.5770254001772314, -0.6141274688156115, -0.6501489254774365, -0.6843590355877066, -0.7160608785902922, -0.7446063271284799, -0.7694098624402408, -0.7899609086114739, -0.8058344043651656, -0.8166993738083127, -0.8223253059613675, -0.822586205769418, -0.8174622353440992, -0.8070389220383186, -0.7915039681975417, -0.7711417546394856, -0.7463256846940091, -0.717508566654004, -0.6852112785080321, -0.650009998733345, -0.6125223197631545, -0.5733925857196928, -0.5332768125352937, -0.4928275562869145, -0.45267909428339737, -0.4134332732296914, -0.3756463599288586, -0.33981720296472384, -0.3063769793296584, -0.2756807589008141, -0.2480010730622388, -0.22352362279322274, -0.20234520747408222, -0.1844738998522979, -0.1698314364575371, -0.15825773765203424, -0.14951741882239356, -0.14330810526573448, -0.13927031930743264, -0.13699867019385448, -0.13605404626320922, -0.1359764855672363, -0.1362983860579693, -0.13655771002139022, -0.1363108397710132, -0.13514475262725703, -0.13268820260340836, -0.12862162348688663, -0.12268550243959096, -0.11468701395862615, -0.1045047499973391, -0.09209143207469489, -0.07747454402596093, -0.060754878327768574, -0.04210304328882039, -0.02175403145599287, -2.0819482253951928e-16], [0.0, 0.022102979650571553, 0.044689770870207056, 0.0673636198895594, 0.08971988392536792, 0.11135806918340987, 0.13189379936133236, 0.1509703925348185, 0.16826973394659858, 0.18352214989091906, 0.196515013155302, 0.20709984271418005, 0.2151976987567931, 0.22080271771037088, 0.22398367959321588, 0.22488355060065177, 0.2237169960154174, 0.2207659110259523, 0.2163730685046627, 0.21093403194078306, 0.20488752729229412, 0.19870450835947892, 0.1928761853466354, 0.18790131466859344, 0.1842730690408242, 0.1824658199159356, 0.18292216904303868, 0.18604056218478698, 0.1921638058956722, 0.20156878801994568, 0.21445767468690824, 0.23095082173533027, 0.25108159753254605, 0.2747932680667779, 0.30193804511254624, 0.3322783454296491, 0.36549025465839596, 0.4011691351591296, 0.4388372638599777, 0.47795333554319325, 0.5179236201770877, 0.5581145210555428, 0.5978662446879907, 0.6365072644902818, 0.6733692390926719, 0.7078020330492474, 0.7391884832462808, 0.7669585584981042, 0.7906025726074775, 0.809683132260686, 0.8238455300285724, 0.8328263287635326, 0.8364599259533552, 0.8346829340952431, 0.8275362647371791, 0.8151648582473963, 0.797815057293709, 0.7758296780823372, 0.7496408882553544, 0.7197610526406826, 0.686771756513956, 0.6513112594863778, 0.6140606705174603, 0.5757291649557504, 0.5370385871940143, 0.49870779693693335, 0.4614371228705735, 0.4258932845561285, 0.39269513172288717, 0.36240053009606193, 0.33549469495915735, 0.3123802385052434, 0.2933691555409136, 0.27867692528903826, 0.2684188560396989, 0.26260874547200613, 0.26115987393227574, 0.26388829216359405, 0.2705183102996812, 0.2806900426946129, 0.2939688146297697, 0.30985619329749126, 0.3278023677622913, 0.3472195717520987, 0.3674962198704179, 0.388011412694129, 0.40814945957768345, 0.4273140699599791, 0.4449418744892926, 0.4605149560579459, 0.4735720973819532, 0.4837184853910216, 0.4906336525564336, 0.49407748037164134, 0.49389413937888343, 0.49001389217185576, 0.48245273939863004, 0.4713099426038221, 0.4567635104455632, 0.43906378509275296, 0.4185253122065656, 0.395517219686479, 0.3704523662872113, 0.3437755504089767, 0.31595109111936637, 0.28745010725813613, 0.25873782598363104, 0.23026124922658922, 0.2024374953195006, 0.1756431138709232, 0.15020464525787708, 0.12639066260641194, 0.10440549468117764, 0.08438478371810926, 0.06639298404138431, 0.05042285653241576, 0.036396961953956024, 0.024171104096870125, 0.013539623029380353, 0.004242390672234509, -0.004026683285067372, -0.01160986635301552, -0.018874803602316713, -0.02620299439876247, -0.0339778554971273, -0.04257269152108452, -0.052338896657375664, -0.06359470587727291, -0.07661480030118265, -0.09162104978369463, -0.10877464695495795, -0.12816985153272253, -0.14982952260685795, -0.1737025708279364, -0.19966341315516126, -0.22751346127780092, -0.2569846223181263, -0.28774473827854974, -0.31940484023014176, -0.351528045732501, -0.3836398846328537, -0.4152398003194009, -0.4458135416744086, -0.47484613620588056, -0.5018351177770412, -0.5263036734529227, -0.5478133734925177, -0.5659761564729612, -0.5804652577679624, -0.59102479373788, -0.5974777454474511, -0.5997321237492823, -0.5977851412316362, -0.5917252647602638, -0.5817320739623232, -0.56807390473524, -0.5511033113885787, -0.5312504349941015, -0.5090144175902085, -0.48495305076807227, -0.45967089164030706, -0.4338061181476249, -0.4080164281174983, -0.3829643116323877, -0.3593020434541678, -0.3376567510408287, -0.31861591384286686, -0.30271364105393284, -0.2904180580000706, -0.2821201062805461, -0.2781240302158873, -0.2786397828957516, -0.28377754009654194, -0.2935444606449802, -0.3078437786437733, -0.3264762576400194, -0.34914398065164975, -0.3754563943391454, -0.4049384718739531, -0.43704080852095634, -0.47115141785183023, -0.5066089559629057, -0.5427170670732873, -0.5787595172543264, -0.6140157644378902, -0.6477766027192131, -0.6793595175543232, -0.7081233957824656, -0.7334822502968821, -0.7549176432494425, -0.7719895233129074, -0.7843452309610094, -0.7917264700169572, -0.7939740927789004, -0.7910305986541416, -0.7829403011341669, -0.769847173777347, -0.7519904412718637, -0.72969803527681, -0.7033780852791007, -0.673508660930267, -0.6406260231208868, -0.6053116754273057, -0.5681785347012486, -0.5298565588231975, -0.49097818055607784, -0.45216389877413504, -0.414008372071955, -0.3770673450623796, -0.34184571493883315, -0.3087870156944828, -0.27826456052785925, -0.25057444035554505, -0.22593052907127592, -0.20446159542419504, -0.18621056840816538, -0.17113594918170372, -0.15911530911633942, -0.149950761927815, -0.1433762492600715, -0.13906643476789407, -0.13664696277323587, -0.1357058049094778, -0.13580539261463373, -0.13649521550711638, -0.13732455600014237, -0.13785502920251486, -0.13767260422400043, -0.13639879825247392, -0.13370075779262036, -0.12929997165315532, -0.12297939686312194, -0.11458882075029259, -0.10404832885259345, -0.09134979797464782, -0.07655638528449772, -0.059800036561435344, -0.04127708823094593, -0.021242087351881947, -2.0247989737671382e-16], [0.0, 0.0213041835959905, 0.042901394594110444, 0.06440769989288048, 0.08543782111677378, 0.10561663258551404, 0.12459041823579503, 0.14203758406386865, 0.1576785363257835, 0.1712844568594527, 0.1826847349500271, 0.19177284944315967, 0.19851053445819936, 0.20293010606781403, 0.20513487458371218, 0.20529761642843478, 0.2036571297355664, 0.20051294753772017, 0.19621833041525066, 0.1911717055715916, 0.18580676032755952, 0.1805814339411292, 0.17596608154166177, 0.17243110704843514, 0.1704343776215779, 0.17040874005231185, 0.17274995931668038, 0.17780539127129638, 0.18586368534103628, 0.19714578941431157, 0.21179749858691338, 0.22988375262015198, 0.25138484489896, 0.2761946593208246, 0.30412100205548803, 0.33488804370770087, 0.36814083536049574, 0.4034518105631976, 0.4403291358323041, 0.47822672588543785, 0.5165556977845415, 0.5546970014760481, 0.5920149338045224, 0.6278712197104617, 0.6616393285985839, 0.6927186861884768, 0.7205484427457436, 0.7446204674463612, 0.7644912555538155, 0.7797924596926832, 0.7902397881991022, 0.795640051558256, 0.7958961813850334, 0.7910100942156806, 0.7810833233962813, 0.7663153953390603, 0.7469999800810249, 0.7235188991147479, 0.6963341245758873, 0.6659779518202197, 0.6330415710351596, 0.5981623017434506, 0.5620097859378483, 0.525271460358359, 0.48863764548459343, 0.4527865977507387, 0.4183698720840704, 0.3859983341084705, 0.35622914543553474, 0.32955402178006793, 0.3063890327672945, 0.28706617500387116, 0.2718269071792017, 0.26081778869669336, 0.2540883127641043, 0.25159097223525784, 0.25318354307857793, 0.25863351745510504, 0.26762456730913176, 0.2797648713512488, 0.2945970945123524, 0.3116097704282628, 0.3302498052066885, 0.349935795405578, 0.3700718354152316, 0.3900614796989804, 0.4093215238237122, 0.427295274914319, 0.44346499690430324, 0.45736323833969633, 0.46858277994825165, 0.47678497496033245, 0.48170629635713463, 0.4831629507889181, 0.4810534677078508, 0.4753592230762066, 0.46614290857340185, 0.4535450082511547, 0.43777839380793054, 0.41912119585229374, 0.397908150558474, 0.37452065795117306, 0.349375818787115, 0.3229147408789143, 0.2955904221560159, 0.2678555263879355, 0.24015036811331647, 0.21289141593153887, 0.18646060812955154, 0.16119575203761455, 0.137382249121103, 0.11524635237839645, 0.09495012203481137, 0.07658820083521893, 0.060186482580657424, 0.04570269813768791, 0.03302889322696073, 0.021995723134562314, 0.012378442331095875, 0.003904423022601368, -0.003738002993394215, -0.01088961913101494, -0.01790958359818043, -0.025164163137966333, -0.033015244135552665, -0.04180893033726166, -0.0518645345266417, -0.06346426170380191, -0.07684386386173106, -0.09218452178357164, -0.10960617801636052, -0.12916250809479016, -0.15083767512541915, -0.1745449670535903, -0.20012736747563223, -0.22736006094989714, -0.25595482366198136, -0.28556620127879967, -0.31579932912467074, -0.3462192066152982, -0.37636119929194317, -0.4057425087938046, -0.4338743245389564, -0.46027435144084755, -0.48447939617882996, -0.5060576906879921, -0.5246206357578515, -0.5398336598516952, -0.5514259081991643, -0.5591985044012261, -0.5630311605644884, -0.5628869515305724, -0.5588151131200286, -0.5509517723813754, -0.5395185684415916, -0.5248191744464918, -0.5072337829745879, -0.48721166792034665, -0.4652619839148193, -0.4419430086863946, -0.4178500732547818, -0.3936024585074796, -0.36982956368244907, -0.3471566718889655, -0.3261906495372492, -0.30750592010547695, -0.2916310479407125, -0.279036254862771, -0.27012217151320295, -0.2652100971570365, -0.26453400667661986, -0.26823450263578186, -0.2763548645251569, -0.28883929773431444, -0.3055334326362562, -0.32618707068279634, -0.3504591208969777, -0.3779246179145043, -0.40808366304328314, -0.44037208388998955, -0.47417356706507585, -0.5088329833236694, -0.5436705960864656, -0.5779968233041599, -0.6111272095917356, -0.6423972607807604, -0.6711767966325013, -0.6968834893309073, -0.7189952752383597, -0.7370613547591762, -0.7507115293435033, -0.7596636648382631, -0.7637291155668502, -0.7628159925885497, -0.7569302113510392, -0.746174307139082, -0.7307440600403775, -0.7109230232949308, -0.6870750985972114, -0.6596353479726642, -0.6290992731353304, -0.5960108287538771, -0.5609494649551725, -0.5245165159881432, -0.4873212657473698, -0.44996702650088294, -0.4130375645660316, -0.3770841959205425, -0.3426138561139607, -0.3100784228416624, -0.2798655368252179, -0.2522911280393302, -0.22759381081070157, -0.20593126398152137, -0.18737866236508594, -0.17192917437163946, -0.15949648922825643, -0.1499192869367536, -0.14296751625537388, -0.13835030173739524, -0.13572526130452264, -0.13470898194720993, -0.13488837375668342, -0.13583260226925756, -0.13710528652719942, -0.13827664562445885, -0.1389352799034017, -0.13869928429255052, -0.13722641021910884, -0.13422301859730315, -0.12945159891003766, -0.12273666753205316, -0.11396890121301, -0.10310740795873057, -0.0901800862405985, -0.07528207329074268, -0.05857233294088277, -0.040268481776616655, -0.02063999808350701, -1.9595039588424004e-16], [0.0, 0.02042876571805524, 0.040972998305694716, 0.06126510913869602, 0.08094214437650016, 0.09965664887561712, 0.11708713569990163, 0.13294787857057014, 0.14699776177301924, 0.15904794605193587, 0.16896813927782325, 0.17669129639635017, 0.18221661347774334, 0.1856107245515861, 0.1870070562369228, 0.18660334278950247, 0.18465735188443652, 0.18148091802692848, 0.17743242475585266, 0.1729079176507067, 0.16833106653188867, 0.16414222622773394, 0.1607868700733458, 0.15870368826376977, 0.15831265383527543, 0.16000336210318558, 0.16412394474211936, 0.17097084744619273, 0.1807797405344433, 0.19371780543580047, 0.20987760733575767, 0.22927272618755795, 0.25183527571521985, 0.2774153940092246, 0.3057827409715582, 0.3366299883986078, 0.3695782391224349, 0.40418426358772264, 0.4399493967176795, 0.47632989605209425, 0.5127485249712623, 0.5486070932833399, 0.5832996623451014, 0.616226103845351, 0.6468056908710669, 0.6744903971790291, 0.6987775857977776, 0.7192217810798582, 0.7354452388135632, 0.7471470565030828, 0.7541105997792397, 0.7562090602955311, 0.7534090044447571, 0.7457718197345499, 0.7334530155325601, 0.7166993859212112, 0.6958440933455713, 0.6712997813547048, 0.6435498718170493, 0.6131382453853519, 0.5806575426377343, 0.5467363562850588, 0.5120256113068608, 0.47718444921292597, 0.44286594435425203, 0.40970298404086375, 0.37829464007325825, 0.34919334726308204, 0.3228931849037116, 0.29981953043522697, 0.28032032138647733, 0.2646591228831075, 0.25301015453495646, 0.24545538342370052, 0.24198374035399026, 0.24249246571982364, 0.2467905405130005, 0.2546041084014669, 0.26558374763961573, 0.27931340798616716, 0.29532078885433044, 0.3130889015443231, 0.3320685314119015, 0.35169129585211967, 0.3713829814947814, 0.39057683930133197, 0.40872651941456944, 0.4253183385404671, 0.4398825910425213, 0.4520036403260396, 0.46132855883392726, 0.46757412226239364, 0.4705320054949601, 0.47007207319473676, 0.4661437058510663, 0.45877515115302936, 0.44807093963706984, 0.4342074514101279, 0.41742676619726565, 0.39802897088042793, 0.376363136049722, 0.35281720496329866, 0.3278070639281268, 0.30176508185092693, 0.27512841811853067, 0.24832740178627713, 0.2217742812081534, 0.19585263185164115, 0.17090769141073117, 0.14723786594998464, 0.12508761933723522, 0.10464192146037136, 0.08602238961421046, 0.06928521303395808, 0.05442090397105518, 0.04135587113728593, 0.029955763989595617, 0.020030490390040644, 0.011340766815110256, 0.003606020602889998, -0.0034865712814070478, -0.010272151925995543, -0.017097630701032072, -0.02431079038123757, -0.03224934844815607, -0.04123026726435379, -0.05153960164812444, -0.06342315879588743, -0.07707822484029285, -0.09264658511342112, -0.11020903209032883, -0.12978151685098352, -0.15131305767850906, -0.17468547417253236, -0.1997149681392992, -0.22615552471482056, -0.2537040598920975, -0.28200719505558747, -0.31066949643135855, -0.33926297862519333, -0.36733763763118693, -0.3944327507156412, -0.42008865913662063, -0.44385873530741693, -0.4653212291347781, -0.48409068905623887, -0.499828661769943, -0.5122533906076416, -0.5211482555725792, -0.5263687276955495, -0.5278476458366269, -0.5255986645117398, -0.5197177657612011, -0.5103827754089074, -0.4978508731190554, -0.48245413522928676, -0.46459319819679573, -0.4447291774240531, -0.4233740200649392, -0.4010795100564461, -0.37842517808251247, -0.35600539758872285, -0.3344159696102184, -0.314240513497043, -0.2960369872477839, -0.2803246599089596, -0.2675718493738021, -0.25818472212300025, -0.25249742738403425, -0.2507638074171721, -0.25315088890261833, -0.25973431859034735, -0.270495860493291, -0.28532302306849566, -0.3040108342261306, -0.3262657308641573, -0.3517114791925403, -0.3798969936145537, -0.4103058765567654, -0.4423674604908181, -0.47546909747330024, -0.5089694117212975, -0.5422122077680032, -0.5745407111647106, -0.6053118108919682, -0.6339099728021781, -0.6597605015322674, -0.6823418441972415, -0.7011966524126777, -0.715941349225775, -0.7262739836232728, -0.7319801965460114, -0.7329371677633135, -0.7291154614340287, -0.7205787385198603, -0.7074813551906843, -0.6900639167274267, -0.6686469049584138, -0.6436225427797334, -0.6154451007043926, -0.5846198866575151, -0.5516911905112849, -0.517229478408904, -0.48181814820302094, -0.44604016595257406, -0.41046490419420745, -0.37563549563498794, -0.34205700120043364, -0.31018566940229303, -0.280419535328867, -0.2530905729358616, -0.22845857460241878, -0.2067068881140214, -0.18794009443885548, -0.1721836610463807, -0.15938555628818554, -0.14941976174589983, -0.1420915726552205, -0.13714453269720026, -0.13426880968947175, -0.13311078398900766, -0.133283592584833, -0.13437834961557454, -0.13597574892867376, -0.1376577466623591, -0.13901902184720158, -0.13967792066870566, -0.13928660509252797, -0.13754014863089178, -0.13418435054873873, -0.12902207403668514, -0.12191795293846923, -0.11280135451678343, -0.10166753138165367, -0.08857694293082168, -0.07365277426431939, -0.05707672732948348, -0.039083203843624424, -0.019952041196476516, -1.8865749344801872e-16], [0.0, 0.019484141676220954, 0.03892117858195265, 0.05796295887353002, 0.07627132951982421, 0.09352828664126586, 0.10944559740660104, 0.12377363327649242, 0.13630917451743377, 0.1469019722355698, 0.15545988603557967, 0.16195245199272446, 0.16641277601469467, 0.1689376908455694, 0.1696861598373477, 0.16887595605149336, 0.16677869010453403, 0.16371330330187192, 0.16003818291819513, 0.1561420929557976, 0.15243414541314243, 0.1493330632126983, 0.1472560057956215, 0.14660724147307683, 0.1477669565804658, 0.15108049013989208, 0.15684827410837943, 0.1653167435674921, 0.17667045876455, 0.19102565228578705, 0.2084253805222733, 0.22883641981337738, 0.2521480051710339, 0.27817246434666787, 0.3066477533152887, 0.33724185217320996, 0.3695589341443592, 0.40314717601611916, 0.43750803698464535, 0.4721067956145475, 0.5063841023432106, 0.5397682784986019, 0.5716880728219925, 0.6015855735054405, 0.6289289681084238, 0.6532248455685049, 0.6740297438426264, 0.6909606632997632, 0.7037042894440434, 0.7120246983221965, 0.7157693533460163, 0.7148732423864321, 0.7093610478997826, 0.6993472894639435, 0.6850344262991009, 0.6667089559521657, 0.6447355931508552, 0.6195496587170676, 0.5916478512497583, 0.5615776129997849, 0.5299253350177396, 0.49730367443882645, 0.46433827799767957, 0.43165422002281734, 0.39986246989990537, 0.36954670315174676, 0.34125076188299547, 0.3154670545859557, 0.2926261625876548, 0.2730878912946394, 0.25713396957481977, 0.2449625609576411, 0.23668470680581366, 0.23232277527825906, 0.23181094189721496, 0.23499767902466076, 0.24165018372738453, 0.2514606275308426, 0.26405406854734964, 0.278997827457458, 0.2958120947681273, 0.31398150848759493, 0.3329674195217112, 0.3522205472271059, 0.37119371999755585, 0.3893543956756455, 0.4061966639517322, 0.42125244753246066, 0.43410164034900334, 0.44438094887977225, 0.4517912360774849, 0.4561032055730778, 0.45716130581987047, 0.4548857785893245, 0.4492728226175675, 0.4403928900742282, 0.4283871797175132, 0.4134624349666401, 0.39588419656770385, 0.3759686970297295, 0.35407361664260056, 0.3305879478593993, 0.3059212354771213, 0.28049247388532556, 0.2547189493469349, 0.22900531468290378, 0.20373317588923812, 0.1792514553383646, 0.15586777470056765, 0.13384107312386223, 0.1133756432427621, 0.09461673009183263, 0.07764779693489261, 0.06248951842993229, 0.04910051653976819, 0.03737980931026134, 0.027170898218272788, 0.01826737736422781, 0.010419908421906243, 0.003344369955595469, -0.0032690406360508417, -0.009745998922439507, -0.016417803654223382, -0.023610961539809683, -0.031636887131441825, -0.04078199555413534, -0.051298455860455006, -0.0633958559557382, -0.07723400673479786, -0.09291708388835887, -0.1104892715100279, -0.1299320330270633, -0.15116309306377346, -0.17403716968241034, -0.1983484511480596, -0.22383476607631614, -0.2501833516916747, -0.27703808306933164, -0.304007987716827, -0.3306768356555667, -0.3566135661601826, -0.3813832892513287, -0.40455858351273016, -0.4257308022513529, -0.44452109770177217, -0.46059087797308895, -0.47365142364707447, -0.483472410077118, -0.4898891070528332, -0.49280805896592256, -0.49221108517286954, -0.4881574810043272, -0.4807843438182875, -0.47030499455112895, -0.457005512249332, -0.441239445900196, -0.42342081335943677, -0.40401554016556807, -0.38353153046270066, -0.3625075971381163, -0.3415015077423372, -0.32107742605328765, -0.3017930456793992, -0.28418672144152396, -0.26876490617979226, -0.2559901950309494, -0.24627026623148032, -0.23994798742143778, -0.2372929297275947, -0.23849449923060964, -0.2436568575551729, -0.2527957611795433, -0.2658374036625506, -0.2826192974344744, -0.30289318324972325, -0.3263299070362912, -0.3525261568783024, -0.3810129083801781, -0.4112653857697765, -0.4427143098016829, -0.4747581727070548, -0.5067762558555914, -0.538142088048409, -0.56823703188072, -0.5964636826554843, -0.6222587689643999, -0.645105256165876, -0.6645433732830655, -0.6801803098450323, -0.6916983612631579, -0.6988613386871663, -0.7015191010062416, -0.6996101117296802, -0.6931619707965728, -0.6822899197693527, -0.6671933671804958, -0.6481505278476916, -0.6255113146056158, -0.5996886620380499, -0.5711484984359825, -0.5403986134710362, -0.5079766942081513, -0.4744378204880124, -0.44034172195611165, -0.40624010284613504, -0.37266433696864787, -0.3401138243243693, -0.3090452826487353, -0.27986322246947015, -0.25291182355193814, -0.22846839469513805, -0.20673855862840704, -0.18785326025343235, -0.171867650765809, -0.1587618534147046, -0.1484435699819656, -0.14075244164156164, -0.13546603482126307, -0.13230728309373505, -0.13095318094857644, -0.13104449540277893, -0.1321962375237609, -0.13400861864415675, -0.1360782057529326, -0.1380089874895367, -0.13942306640173252, -0.13997070452605656, -0.139339467606135, -0.13726223790070033, -0.1335238959134575, -0.12796650672131715, -0.12049288598301695, -0.11106846317323002, -0.09972140402885986, -0.08654099948706866, -0.07167437339113242, -0.05532160480166212, -0.03772940177535808, -0.019183500924353322, -1.80660862519241e-16], [0.0, 0.018478416881187357, 0.03676364416749029, 0.05452959883215817, 0.07146490263258537, 0.08728225448733398, 0.10172716050626159, 0.11458578515386517, 0.12569170956375758, 0.1349314110848846, 0.14224831102063146, 0.1476452743914685, 0.1511854854802268, 0.15299166489857094, 0.15324363688317563, 0.15217429840379498, 0.15006408335720473, 0.14723405457347266, 0.14403779257156488, 0.14085228204714761, 0.13806802413695424, 0.13607862388526773, 0.13527011748418877, 0.13601031237095917, 0.1386384149086719, 0.14345521508874665, 0.1507140855853643, 0.16061303384525802, 0.17328802115640854, 0.18880773240502435, 0.20716994523883622, 0.2282996084636449, 0.25204869766573906, 0.2781978723073344, 0.3064599139673738, 0.3364848811010644, 0.367866872768959, 0.40015225330938664, 0.4328491529073502, 0.4654380263760821, 0.4973830250351755, 0.5281439150354533, 0.5571882603950467, 0.5840035807647666, 0.6081091927570286, 0.6290674496006933, 0.6464941067982701, 0.6600675610637369, 0.6695367356451496, 0.674727416568798, 0.6755468806243871, 0.671986696166845, 0.6641236210640815, 0.6521185673207539, 0.6362136479560799, 0.6167273674871938, 0.5940480617522649, 0.5686257347164678, 0.5409624783154914, 0.5116016953672462, 0.48111637429235093, 0.4500966871262919, 0.4191371985247509, 0.38882398276242575, 0.35972194787761924, 0.3323626610680049, 0.30723295732152034, 0.2847645943675343, 0.2653251918206185, 0.2492106614796779, 0.23663929989579158, 0.22774767440971078, 0.22258839086069923, 0.2211297861328309, 0.22325754273260107, 0.22877817680404544, 0.23742430649997862, 0.24886156552257557, 0.262696987945605, 0.2784886560712408, 0.29575637388574516, 0.3139931053610218, 0.33267689995834565, 0.35128301762264125, 0.3692959625379525, 0.3862211390008633, 0.4015958538368483, 0.4149994075415227, 0.4260620403165247, 0.43447252877776105, 0.43998426359371945, 0.44241967679658517, 0.4416729290349711, 0.43771081056690797, 0.43057185424105, 0.42036370297792364, 0.40725881724400326, 0.3914886486460641, 0.3733364430592241, 0.35312886972225305, 0.33122670067945137, 0.30801478713898145, 0.28389159521742396, 0.2592585727718322, 0.23450962137339262, 0.2100209429128047, 0.18614151898163292, 0.16318446335031614, 0.14141946402826636, 0.12106650216001472, 0.10229100113363401, 0.08520052161882304, 0.06984307777078175, 0.05620710756073249, 0.04422308719652813, 0.03376673696620906, 0.02466372465203194, 0.01669573396347787, 0.009607730202672514, 0.003116224494186888, -0.0030816878371335704, -0.009298759121973805, -0.01584774949603203, -0.023031580449236196, -0.031133747116144053, -0.040409248067120485, -0.05107627812592847, -0.06330891018616146, -0.07723096661869433, -0.09291125029428546, -0.11036027026003864, -0.12952855858780965, -0.15030663382883877, -0.17252662389940193, -0.19596551816409902, -0.22034997606616613, -0.24536257895276464, -0.27064937379083615, -0.2958285232316214, -0.3204998468331195, -0.34425501394998603, -0.3666881304769007, -0.3874064497628728, -0.40604093291812143, -0.4222563855607334, -0.43576090677313317, -0.4463144014616629, -0.4537359290715785, -0.45790968918079894, -0.458789477208745, -0.4564014805318731, -0.4508453257852219, -0.44229333105206575, -0.43098796094137504, -0.41723752712832624, -0.4014102206803108, -0.3839266043213708, -0.36525073165876426, -0.345880095334111, -0.32633463619144515, -0.3071450701157761, -0.28884080756473574, -0.27193775252074537, -0.25692627232345705, -0.2442596274655578, -0.23434314098745335, -0.2275243708007452, -0.22408452548891009, -0.22423133541822454, -0.22809355703201123, -0.2357172498157112, -0.24706392353835718, -0.262010609013957, -0.2803518598626768, -0.3018036467006527, -0.3260090599713161, -0.3525456943532253, -0.3809345473962118, -0.41065022873302576, -0.44113224477471197, -0.47179709799307995, -0.5020509203536182, -0.5313023476645665, -0.5589753358651378, -0.584521621728121, -0.6074325390629414, -0.6272499170633242, -0.6435758095676027, -0.656080832147411, -0.6645109174227771, -0.6686923369990947, -0.6685348800047528, -0.6640331223608453, -0.6552657665579423, -0.6423930777355235, -0.6256524871354859, -0.6053524774299641, -0.5818649049500674, -0.5556159504834067, -0.5270759221785093, -0.49674816042626746, -0.4651573147524649, -0.43283727627406715, -0.4003190558326614, -0.36811889738010733, -0.33672690858839277, -0.3065964761961357, -0.2781347126647988, -0.25169415383468774, -0.2275658951255683, -0.20597431722938697, -0.1870735121115638, -0.170945477476263, -0.15760010372420724, -0.14697693293681974, -0.1389486256625522, -0.13332602934386265, -0.12986470314259532, -0.12827271866022374, -0.1282195254730851, -0.12934564525833145, -0.13127293918386373, -0.13361518063302472, -0.13598865952716063, -0.13802254562092636, -0.139368746127835, -0.13971100766669362, -0.13877303341700423, -0.1363254129905967, -0.1321911941828501, -0.12624996164975918, -0.11844032675198873, -0.10876077431728878, -0.09726885484471348, -0.08407875362424705, -0.06935731028653565, -0.053318602366403345, -0.03621724354815433, -0.018340580423799678, -1.7202773530830264e-16], [0.0, 0.017420267496541336, 0.034518963312837735, 0.050994222889445426, 0.06656290301238955, 0.08096912738631878, 0.09399209659741589, 0.10545295045125246, 0.11522049505251507, 0.123215636225996, 0.12941439422405393, 0.13384941128342084, 0.13660990255917696, 0.13784004129140542, 0.13773580973061392, 0.1365403873318312, 0.1345381860106714, 0.13204767786537136, 0.12941319280031152, 0.12699589112088022, 0.12516413869782805, 0.12428352913954102, 0.12470680812261209, 0.1267639593272173, 0.13075270917678672, 0.136929698827569, 0.145502556792095, 0.1566230845685503, 0.17038174119245447, 0.18680358137163902, 0.2058457665753368, 0.22739672999060387, 0.25127703558253806, 0.2772419296045019, 0.3049855408389876, 0.33414664465376, 0.36431586665721893, 0.39504416531251313, 0.4258524002337053, 0.4562417648592647, 0.48570483948607046, 0.5137370038286743, 0.5398479377769365, 0.5635729351381921, 0.5844837579828535, 0.602198768714707, 0.6163920929439274, 0.626801588277818, 0.6332354217365803, 0.6355770909866532, 0.6337887611784794, 0.6279128289929081, 0.6180716675742776, 0.6044655493353671, 0.5873687871050162, 0.5671241766929996, 0.5441358646288711, 0.5188608025982858, 0.49179898402882405, 0.46348268753782773, 0.4344649758316889, 0.4053077165548799, 0.37656940308972825, 0.34879305812274464, 0.3224945008024016, 0.29815124956528766, 0.2761923174166111, 0.256989134991308, 0.24084780961852195, 0.22800289652810204, 0.2186128220573941, 0.21275705912697584, 0.21043511332213055, 0.21156733466654565, 0.21599752666092142, 0.22349728144220643, 0.23377192903854638, 0.24646795064393215, 0.26118167153725597, 0.2774690195520807, 0.29485611058090166, 0.31285040405508846, 0.33095215911724263, 0.3486659165786957, 0.3655117328505165, 0.3810358998052685, 0.39482089875820703, 0.4064943570809054, 0.4157368018584938, 0.42228803581802665, 0.42595199571443415, 0.42659999158566725, 0.42417226582485884, 0.41867785285443926, 0.41019276228492146, 0.39885654975543705, 0.38486737916154873, 0.3684757167032654, 0.3499768302286511, 0.32970229589573896, 0.3080107375311786, 0.2852780416624634, 0.26188730262080245, 0.23821875708781617, 0.21463996588668574, 0.19149649275656258, 0.16910331551925106, 0.1477371848272263, 0.1276301200964954, 0.10896420193453621, 0.09186778614758181, 0.07641322712499415, 0.06261615899927803, 0.05043634246781484, 0.03978004456287824, 0.03050387899695526, 0.022419996993290513, 0.015302483689335, 0.008894784152349487, 0.0029179565549735317, -0.0029204712078718166, -0.00891728068472709, -0.015364226393488568, -0.022538835250968746, -0.030695589953456687, -0.04005773448539084, -0.05080992393778058, -0.06309191910050178, -0.07699349940060814, -0.09255073637054287, -0.10974373473752815, -0.12849591031425955, -0.14867483409889506, -0.17009463136454964, -0.19251988406304343, -0.21567094560941455, -0.23923054004874358, -0.2628514836774946, -0.2861653372628627, -0.3087917718413112, -0.33034841132907944, -0.3504609013557182, -0.36877294620170287, -0.38495605469101046, -0.39871874140486724, -0.4098149415256661, -0.4180514157112272, -0.4232939452057203, -0.42547214633767855, -0.42458276693094193, -0.42069136414238284, -0.4139323029302751, -0.40450705576914525, -0.3926808263357998, -0.3787775616521643, -0.36317345754510444, -0.34628910026491494, -0.32858042174345486, -0.31052867640105203, -0.29262967286233804, -0.2753825137699775, -0.2592781105851838, -0.2447877474780455, -0.23235196894200955, -0.22237005958289027, -0.2151903717663534, -0.2111017377546982, -0.2103261780747644, -0.21301308772937422, -0.21923504722031684, -0.2289853670288916, -0.24217743312969392, -0.25864587829255736, -0.27814956039858363, -0.30037628581978115, -0.32494917414145197, -0.35143452116180324, -0.3793509811457791, -0.40817985761876774, -0.4373762653357152, -0.4663809051042828, -0.4946321783898468, -0.5215783604466074, -0.5466895493028802, -0.5694691133148266, -0.5894643720594901, -0.6062762637699984, -0.6195677768721938, -0.6290709528668279, -0.6345923020889178, -0.6360165119273916, -0.6333083679741409, -0.6265128512933914, -0.6157534185173655, -0.6012285147216474, -0.5832064109602672, -0.562018497926885, -0.5380512034937515, -0.5117367339861453, -0.4835428662021599, -0.45396203873468205, -0.4235000065813041, -0.3926643319775396, -0.3619529866576807, -0.33184333629930923, -0.3027817668711252, -0.2751741952702071, -0.24937768344995784, -0.2256933467930246, -0.20436071449226684, -0.18555366299597106, -0.1693780040695066, -0.15587076771041738, -0.1450011780557313, -0.13667327858456435, -0.1307301223824086, -0.1269594049977096, -0.12510038242890437, -0.1248518858907137, -0.12588121897784016, -0.1278337023053195, -0.13034261615243659, -0.13303928341581892, -0.13556303347278928, -0.13757079239097336, -0.1387460561537038, -0.1388070209023704, -0.13751366717395938, -0.13467362314150053, -0.13014666422827403, -0.12384774233722404, -0.1157484764022227, -0.10587707605093319, -0.09431671085399213, -0.08120237789224138, -0.06671635918487219, -0.05108239690605419, -0.03455874735733923, -0.017430303524248594, -1.6283188284955877e-16], [0.0, 0.016318815635505118, 0.03220630323939725, 0.047386468707982944, 0.061605345974497586, 0.07463868268216912, 0.08629881781948491, 0.09644056419351377, 0.10496593428861156, 0.11182757790946903, 0.11703083328550912, 0.12063432917755877, 0.12274911307114054, 0.12353631881416964, 0.12320342509145794, 0.12199919296028741, 0.12020740536551502, 0.11813956322684739, 0.1161267205372792, 0.11451066421741123, 0.11363466263545982, 0.11383401925525617, 0.1154266744823688, 0.11870409925803226, 0.12392271827138832, 0.1312960889463466, 0.14098804488512742, 0.15310698963584912, 0.1677014990503101, 0.18475735878508714, 0.2041961284530116, 0.22587528641665594, 0.24958997015781553, 0.2750762875247623, 0.30201613493649315, 0.33004342078650983, 0.35875155678197973, 0.38770204766578603, 0.4164339815095928, 0.44447419924814874, 0.47134790394534126, 0.49658945790686576, 0.5197531095061337, 0.5404233916418879, 0.5582249401151689, 0.5728314927615276, 0.5839738486103849, 0.5914465902306407, 0.5951134011881538, 0.5949108434937969, 0.590850496263478, 0.5830193956623737, 0.5715787566202518, 0.5567609977992083, 0.5388651318698473, 0.5182506223166944, 0.4953298447916153, 0.470559324565681, 0.44442995107499855, 0.4174563951937375, 0.3901659740947056, 0.36308722190299636, 0.3367384314843806, 0.31161643346171947, 0.28818587290074954, 0.2668692321887596, 0.24803783073698288, 0.23200400870719415, 0.21901467356760637, 0.20924635561673552, 0.2028018824743997, 0.19970874380921927, 0.19991917719715338, 0.20331196497066456, 0.20969589122307802, 0.21881476876825603, 0.23035390877867842, 0.24394787193497833, 0.25918931003695656, 0.27563868187076374, 0.29283460730248273, 0.3103046095463391, 0.3275759876640207, 0.34418655976683205, 0.3596950221356975, 0.37369068041061465, 0.3858023258440656, 0.3957060519299283, 0.40313183394459645, 0.4078687253839955, 0.409768560160226, 0.40874808686252206, 0.40478950045577, 0.39793937651432587, 0.3883060524836754, 0.3760555385524651, 0.36140607656191276, 0.34462149809597903, 0.32600356168097727, 0.3058834731741551, 0.28461281235077396, 0.2625541019532075, 0.2400712627309293, 0.21752019911439632, 0.19523975511995906, 0.1735432690223447, 0.1527109385510949, 0.13298318630542105, 0.11455518830746284, 0.09757269781300394, 0.08212926245743606, 0.06826489639901477, 0.0559662312556152, 0.04516813127456885, 0.03575672029829322, 0.027573731648490023, 0.020422057968849407, 0.014072347200282425, 0.008270463991984585, 0.0027456136531555904, -0.0027810912170163375, -0.008587852592444146, -0.01494343391404682, -0.02209866784153472, -0.030278453921030322, -0.039674462570235096, -0.05043874355914613, -0.06267841383322621, -0.07645157167638071, -0.09176455254616846, -0.10857060723302374, -0.1267700461750998, -0.14621185573149398, -0.1666967539412678, -0.18798161574324163, -0.2097851617544652, -0.2317947714150021, -0.2536742514509652, -0.2750723649493509, -0.2956319055355585, -0.31499908573527696, -0.33283299898996466, -0.34881491123808955, -0.3626571405800695, -0.37411129226665085, -0.38297563088840664, -0.3891013918497456, -0.3923978594960216, -0.39283606901084805, -0.3904510226835111, -0.38534234753968083, -0.3776733597342767, -0.36766854057295906, -0.3556094685793328, -0.3418292906752785, -0.3267058523287555, -0.31065364052770966, -0.2941147238084362, -0.27754889953767475, -0.26142327956349865, -0.2462015606773506, -0.23233323567290434, -0.22024300389771007, -0.21032063697560563, -0.20291154589240798, -0.19830828009970322, -0.19674316806682277, -0.19838228230500599, -0.2033208809345637, -0.2115804431127927, -0.2231073779291403, -0.23777344662047226, -0.25537789713040887, -0.27565126912736176, -0.298260787604068, -0.322817225083737, -0.3488830771852358, -0.37598186471482076, -0.40360834832757153, -0.43123941980199626, -0.4583454176351841, -0.4844016043938016, -0.508899539300435, -0.5313580819924811, -0.5513337722028168, -0.56843034506266, -0.58230716245215, -0.5926863668167422, -0.5993585944922892, -0.602187120090415, -0.6011103410453453, -0.5961425510971008, -0.5873729923156513, -0.5749632162607966, -0.5591428250247432, -0.5402037012418123, -0.5184928717414432, -0.49440418150404586, -0.46836898218180206, -0.44084606200400567, -0.4123110608601774, -0.38324562534287154, -0.354126563282935, -0.3254152557237783, -0.2975475764148658, -0.2709245549699744, -0.2459040001932337, -0.2227932752263715, -0.20184338674205166, -0.18324451714053477, -0.16712309243318227, -0.15354044012203863, -0.14249305186550176, -0.13391442603741857, -0.12767842642438476, -0.12360405622444572, -0.12146151212425005, -0.12097935238640892, -0.12185258632986724, -0.1237514709803888, -0.12633078452815852, -0.12923933594009862, -0.13212946587411345, -0.13466629601700236, -0.13653649204876117, -0.13745631940250427, -0.13717879047358214, -0.13549972642857946, -0.13226258564510837, -0.12736194333821843, -0.12074554227022727, -0.11241487169990662, -0.10242426995944715, -0.09087858428546083, -0.07792945880661248, -0.06377035696368014, -0.04863045721512243, -0.03276758984094392, -0.01646040726991964, -1.5315252351621855e-16], [0.0, 0.015183500319209519, 0.029845164969027543, 0.043736016311245705, 0.0566316920773553, 0.06833925377575754, 0.07870313535473134, 0.08761006985267766, 0.09499285818738294, 0.10083287417991792, 0.10516123261961176, 0.10805858182740499, 0.10965351788934884, 0.11011965360605211, 0.10967141032850727, 0.10855863433479256, 0.1070601703946584, 0.10547655288045349, 0.10412199850508375, 0.10331590389167575, 0.10337406521078617, 0.10459984569177778, 0.10727551969409883, 0.11165401912264564, 0.11795129934480958, 0.12633952761432485, 0.13694127766643677, 0.1498248900884544, 0.16500112987662907, 0.18242124095620346, 0.20197646314549217, 0.22349904093421233, 0.24676471641532177, 0.2714966616777283, 0.29737076985575567, 0.32402218974103475, 0.3510529572509028, 0.37804054890753847, 0.4045471585225539, 0.4301294791092835, 0.45434875814899783, 0.4767808860776551, 0.49702627545792954, 0.5147192918341189, 0.5295370066658078, 0.5412070577856026, 0.5495144231728506, 0.5543069389938406, 0.5554994222249643, 0.5530762910395908, 0.5470926117056261, 0.5376735381449134, 0.5250121486374549, 0.5093657224784999, 0.49105053677952576, 0.4704352991317482, 0.44793336465429084, 0.42399391522582247, 0.399092303731356, 0.37371978633159203, 0.34837288058574395, 0.3235425963663951, 0.2997037896722119, 0.27730488659274205, 0.25675821587745234, 0.2384311740229111, 0.2226384268722112, 0.20963532690555534, 0.19961269629646125, 0.19269309312478536, 0.18892864267381368, 0.18830047835932173, 0.19071979845560946, 0.19603050633248806, 0.20401336433433212, 0.21439155563154458, 0.2268375152253495, 0.2409808615917069, 0.25641723492665786, 0.2727178272171699, 0.28943937390403435, 0.30613436709119607, 0.3223612463145331, 0.3376943248931695, 0.35173321778180383, 0.3641115504126653, 0.37450474691026453, 0.3826367198005565, 0.3882853113191853, 0.391286367948608, 0.39153636409238396, 0.38899352697193224, 0.38367745200657805, 0.3756672351890913, 0.3650981853737842, 0.3521572140531983, 0.3370770322585761, 0.3201293128912221, 0.3016170013750532, 0.2818659774168936, 0.2612162853902177, 0.24001316006954684, 0.21859807792449132, 0.19730006186559418, 0.17642745929487694, 0.15626039977109385, 0.13704411990931495, 0.1189833197805654, 0.10223768765996882, 0.0869186991917208, 0.07308776368016084, 0.06075575512541938, 0.049883929688963644, 0.04038619540826757, 0.03213266508713806, 0.02495439024993277, 0.018649143697279557, 0.01298809130288442, 0.0077231709229745255, 0.0025949782247753567, -0.002659053667675183, -0.00829640123905796, -0.014561346648363897, -0.021677241133281826, -0.02983934453298231, -0.03920843478279412, -0.04990536131865804, -0.06200669192743785, -0.07554157430771327, -0.09048990217890332, -0.10678184198880313, -0.1242987409751814, -0.1428754014290252, -0.16230367039469662, -0.18233725962856, -0.20269767829639965, -0.223081131443971, -0.24316621147552073, -0.2626221883828007, -0.2811176878354227, -0.29832953490490594, -0.31395153544979326, -0.32770296719840175, -0.3393365583459346, -0.34864574290600686, -0.3554709988538867, -0.35970509686565527, -0.36129711366467343, -0.360255093992826, -0.35664727829126835, -0.3506018484881966, -0.3423051809759677, -0.3319986330070306, -0.319973925424355, -0.3065672199534205, -0.292152022337543, -0.27713107256839187, -0.2619274095960328, -0.24697481953777112, -0.23270789299279573, -0.2195519281840859, -0.20791292199867775, -0.19816789043255761, -0.19065575346316918, -0.18566900711320874, -0.18344638771880414, -0.18416671059431566, -0.18794403794141026, -0.19482429964055092, -0.20478345624373084, -0.21772725689082384, -0.23349260688827359, -0.2518505212431498, -0.2725106024757033, -0.2951269444664963, -0.31930532982390186, -0.34461155712239155, -0.3705807071239101, -0.39672713442094565, -0.42255495338650945, -0.447568775313909, -0.47128444747292686, -0.49323954465071224, -0.5130033695904361, -0.5301862304468508, -0.5444477806598947, -0.5555042290837171, -0.5631342552511759, -0.5671834956426307, -0.567567501006073, -0.5642731013090416, -0.5573581529000692, -0.5469496809920573, -0.5332404687132811, -0.5164841807756667, -0.4969891443902553, -0.47511094157767564, -0.4512439947144758, -0.4258123503568434, -0.3992598845352633, -0.37204016538574725, -0.34460621587939916, -0.3174004203787688, -0.29084481377954385, -0.2653319812282468, -0.2412167801222451, -0.2188090747142575, -0.19836764770113405, -0.18009542332913342, -0.16413610354304575, -0.15057228336867767, -0.13942507492766557, -0.13065523215437602, -0.12416573134229542, -0.1198057270054042, -0.11737576907803816, -0.11663413701782452, -0.11730411966723356, -0.11908204742195815, -0.12164586588958085, -0.12466402821643885, -0.12780447689641292, -0.13074348529345192, -0.13317413430629935, -0.13481421043115588, -0.13541332764750985, -0.134759096642634, -0.13268219035760567, -0.12906018402969047, -0.12382008007800112, -0.11693946251338608, -0.10844626117847704, -0.09841714213753396, -0.08697457602739006, -0.07428267025398914, -0.06054188271386876, -0.045982763434863516, -0.03085889544186744, -0.015439226634623894, -1.4307317483385038e-16], [0.0, 0.014023945805484151, 0.02745511679520318, 0.04007219050013675, 0.051680329213635884, 0.06211710926974681, 0.07125755917501508, 0.07901816873883119, 0.0853597579961447, 0.09028912425630532, 0.09385941729583622, 0.09616922573954546, 0.09736039120750903, 0.09761459999556824, 0.09714883406228608, 0.09620979310286754, 0.09506742673668186, 0.09400773962443329, 0.09332505205432899, 0.09331391368558485, 0.09426087831815627, 0.09643635249956406, 0.10008673034390064, 0.1054270211199263, 0.11263416509480437, 0.12184121705946768, 0.13313255629825627, 0.14654025700262138, 0.16204172487320276, 0.17955867460183622, 0.19895748984177647, 0.22005097297973109, 0.2426014573683166, 0.26632522052439633, 0.2908981039988892, 0.3159622149970784, 0.3411335571428184, 0.36601041373197596, 0.3901822870177603, 0.413239182017358, 0.4347810134129945, 0.45442690960242726, 0.47182418896227935, 0.4866567899144978, 0.4986529482873437, 0.5075919324604904, 0.5133096684756228, 0.5157031131595936, 0.5147332627231803, 0.5104267165528342, 0.5028757502226181, 0.4922368872841202, 0.4787279952777195, 0.4626239667734198, 0.4442510802295946, 0.42398016722238313, 0.40221874136964647, 0.3794022693464867, 0.3559847851496056, 0.3324290647057181, 0.30919658864309163, 0.286737526291033, 0.2654809736094572, 0.2458256717869153, 0.2281314218247562, 0.21271139382538623, 0.1998255083284655, 0.1896750414116787, 0.1823985760178732, 0.17806938980158374, 0.17669433549022748, 0.1782142341648424, 0.18250576584970105, 0.18938480623649298, 0.19861112412223286, 0.2098943220425447, 0.22290087341181752, 0.23726208394433537, 0.2525827838413853, 0.2684505406985902, 0.28444517170808503, 0.30014832776688594, 0.3151529216878135, 0.3290721778377571, 0.3415480910585605, 0.3522590983845292, 0.3609267874575788, 0.36732149014098603, 0.37126663802707865, 0.37264178761737515, 0.3713842561499722, 0.36748934353238044, 0.3610091507523865, 0.35205003962008974, 0.3407688118889493, 0.3273677168941998, 0.31208842506919693, 0.2952051293629338, 0.27701695708393576, 0.25783989054065337, 0.23799840565703165, 0.21781704326100298, 0.19761212785268026, 0.1776838433724393, 0.1583088649561787, 0.1397337301656813, 0.12216911311982737, 0.10578514084421241, 0.09070786361989608, 0.07701696084845275, 0.06474473172951607, 0.05387638668565036, 0.04435162181206707, 0.03606742552623045, 0.028882034880341908, 0.022619929477854447, 0.017077724347295504, 0.012030800142050133, 0.007240490231405412, 0.002461630098423364, -0.002549734681015663, -0.008028689507791327, -0.014194047078028148, -0.021241398425439647, -0.029336806312605497, -0.03861131192223804, -0.0491564047233373, -0.06102058044190493, -0.07420708388234315, -0.08867290263644262, -0.10432904525874634, -0.12104210410139613, -0.13863706953377578, -0.15690132957069805, -0.17558975782748332, -0.1944307640018767, -0.2131331554830942, -0.23139363686180062, -0.24890475662210373, -0.2653630975901987, -0.28047750012740835, -0.29397710479331174, -0.3056190043395794, -0.3151953033641193, -0.3225393975614459, -0.32753130292316274, -0.330101888025343, -0.3302358891306248, -0.327973617578872, -0.3234113011079328, -0.3167000345400016, -0.3080433498516183, -0.29769345015711757, -0.2859461857169226, -0.2731348818951034, -0.2596231582388218, -0.2457969038011027, -0.23205559582374985, -0.2188031663812843, -0.20643863411241822, -0.19534672540738499, -0.18588871118200342, -0.17839368159232166, -0.17315047180331913, -0.17040043743296687, -0.1703312588901134, -0.17307192997428134, -0.17868905838094618, -0.1871845748269844, -0.19849491412749387, -0.21249169652837172, -0.22898390178176478, -0.24772149271719332, -0.26840041028243206, -0.2906688290550859, -0.31413453186515805, -0.3383732351640273, -0.3629376737881684, -0.3873672353604267, -0.4111979211997229, -0.4339724026006733, -0.45524993889553983, -0.4746159268838179, -0.49169085993364636, -0.5061384891124838, -0.5176729977497104, -0.5260650244066399, -0.5311463967547049, -0.532813469668667, -0.5310289941769114, -0.5258224789621043, -0.5172890420181829, -0.5055867859687861, -0.49093276556404913, -0.47359764914597596, -0.45389920659974525, -0.43219478374519416, -0.4088729466067828, -0.38434449796712733, -0.3590330826058253, -0.33336560632186, -0.3077626970351077, -0.2826294338966959, -0.2583465624826197, -0.2352624010082039, -0.2136856244207997, -0.19387909066359887, -0.17605484692322462, -0.16037042394213644, -0.14692649423670567, -0.13576593611645743, -0.1268743105931722, -0.12018172346336155, -0.11556601090525756, -0.11285715468958527, -0.1118428033557622, -0.11227474918168691, -0.1138761881241445, -0.11634957167853935, -0.11938484624032221, -0.12266786736329852, -0.1258887734893852, -0.12875010632354209, -0.13097447296437448, -0.1323115579600428, -0.13254431129777514, -0.1314941604917346, -0.12902512083943898, -0.1250467069095685, -0.11951557966593093, -0.11243589652791916, -0.10385836528362938, -0.09387803625765574, -0.08263089964556598, -0.07028938564097804, -0.05705689312478498, -0.04316149755067288, -0.028849009621043108, -0.014375572875977361, -1.3268046304600217e-16], [0.0, 0.012849828920809356, 0.025055529673256905, 0.03642357196158343, 0.04678807382873185, 0.05601586501033057, 0.06401064733560882, 0.07071613790337383, 0.07611810714623357, 0.08024525257329711, 0.08316887922490297, 0.0850013889168603, 0.0858936114097868, 0.0860310409238761, 0.08562907016195082, 0.0849273404730346, 0.08418335031022725, 0.08366548410897054, 0.08364563962172411, 0.0843916431808168, 0.08615964902264543, 0.08918672051263242, 0.09368378780456973, 0.09982916821886138, 0.10776282262441118, 0.11758150367051026, 0.12933493026178713, 0.143023097726124, 0.15859480530577286, 0.1759474525922755, 0.19492812506891466, 0.21533595680078657, 0.2369257263210604, 0.25941261069997773, 0.2824779934267955, 0.30577619481964685, 0.32894196988077845, 0.3515985984355008, 0.3733663765423201, 0.3938713069452825, 0.41275378004989266, 0.4296770357120902, 0.44433520008100846, 0.4564607007489847, 0.46583087732965384, 0.47227362298002745, 0.47567191486585747, 0.4759671176005357, 0.4731609726370718, 0.4673162177583003, 0.45855581343465013, 0.44706078610690725, 0.43306673159118, 0.41685905398524276, 0.3987670458923775, 0.379156943725732, 0.35842411662811097, 0.3369845685314609, 0.3152659495716661, 0.29369828505714624, 0.2727046371689101, 0.252691916372043, 0.23404205609804563, 0.21710375569547932, 0.20218498315058187, 0.18954641097816158, 0.1793959364171312, 0.171884411177365, 0.16710267710642002, 0.16507997298037438, 0.1657837449323424, 0.16912085961192258, 0.1749401858328276, 0.18303647802545497, 0.19315546405462897, 0.20500001163651632, 0.21823722237864265, 0.2325062809816249, 0.24742686989695126, 0.26260794714352076, 0.27765667734313887, 0.2921873035164938, 0.3058297498344448, 0.31823775326589393, 0.3290963346988814, 0.33812843731172854, 0.34510058130017174, 0.34982740898756665, 0.3521750222342185, 0.35206304422238904, 0.3494653693747758, 0.34440959757951783, 0.33697518124091524, 0.3272903451524598, 0.3155278690211813, 0.3018998499260874, 0.2866515863955301, 0.27005474654306233, 0.2523999993050317, 0.23398929987646097, 0.21512802765954175, 0.19611717725718872, 0.17724580022340605, 0.1587838875094063, 0.14097587002945713, 0.12403489784153755, 0.10813803753274437, 0.09342250305448316, 0.07998300808936391, 0.0678702987413591, 0.05709089466648093, 0.04760803547960852, 0.03934379817503379, 0.032182321168813983, 0.025974042169904742, 0.02054083112963696, 0.01568187665861476, 0.011180165111137324, 0.006809376501579451, 0.0023410109116430234, -0.002448446665419688, -0.0077705158758679315, -0.01381805361061801, -0.020759109305361356, -0.02873146894362627, -0.0378380358685605, -0.048143174791093535, -0.05967012039773887, -0.07239952434277618, -0.08626918485573858, -0.10117497245406513, -0.11697293410095601, -0.13348252737934385, -0.15049090664512, -0.1677581554285708, -0.18502333427743944, -0.20201119141815754, -0.21843936561263594, -0.23402589687052486, -0.24849685159812676, -0.26159386456645395, -0.2730814008815144, -0.2827535469338291, -0.29044014996039996, -0.29601214111769264, -0.29938589646970554, -0.3005265135649828, -0.29944990773955515, -0.296223661287292, -0.2909665894681319, -0.283847019214187, -0.2750798085516445, -0.26492216638206345, -0.2536683625708771, -0.24164344651546854, -0.22919611780190874, -0.2166909145675752, -0.204499903209557, -0.19299406665633642, -0.18253459720258122, -0.17346430366129995, -0.1660993412058391, -0.16072146577421445, -0.15757100343481723, -0.1568407089333681, -0.15867066714033504, -0.1631443667875461, -0.17028604830915275, -0.180059397453138, -0.19236762433733917, -0.20705493456705937, -0.2239093657157227, -0.24266692970905263, -0.2630169702477418, -0.28460861512198127, -0.30705817683088715, -0.32995733196880866, -0.3528818909422029, -0.375400955199471, -0.3970862496458941, -0.4175214135114482, -0.436311033750739, -0.45308921106394556, -0.4675274596902565, -0.4793417579723518, -0.4882985869360585, -0.4942198182800048, -0.496986340637008, -0.4965403430822344, -0.4928862068885666, -0.4860899896863715, -0.47627751966523213, -0.46363115044403963, -0.44838525893087544, -0.4308205981255612, -0.41125764366732487, -0.3900490963485369, -0.36757172223860923, -0.34421772702477793, -0.32038587132321095, -0.29647253880867236, -0.27286296894181117, -0.24992286085565024, -0.22799054473893493, -0.20736990208855843, -0.18832419687774637, -0.17107095648874437, -0.15577801477089226, -0.14256080046950687, -0.13148092325369745, -0.12254607742327835, -0.11571125089369898, -0.11088119504733718, -0.1079140802898691, -0.1066262334191206, -0.10679782690634039, -0.10817936754251019, -0.11049881316649621, -0.11346913182047912, -0.11679610801443381, -0.1201861960508159, -0.1233542206649659, -0.1260307305522233, -0.12796882053049488, -0.12895025285711875, -0.12879072719714935, -0.12734417143798046, -0.12450595138172288, -0.12021492566361834, -0.11445430232260603, -0.1072512845266002, -0.09867552424388161, -0.08883643336284335, -0.07787943112028586, -0.06598123396369138, -0.05334431845899678, -0.04019070894647387, -0.02675525881357773, -0.013278607064410634, -1.2206290531976533e-16], [0.0, 0.011670747032584139, 0.022665317769504045, 0.032817621792248196, 0.041989697272164214, 0.05007593603729556, 0.057006412489780195, 0.06274922448999207, 0.06731177998731681, 0.07074099057581391, 0.07312236159222843, 0.07457799713340496, 0.07526356672099065, 0.07536430756388988, 0.07509016177140562, 0.07467017080553892, 0.07434626934394584, 0.0743666370459492, 0.07497877905198132, 0.07642251408048281, 0.07892305250179335, 0.0826843456651444, 0.08788288204739891, 0.09466209561102659, 0.10312753734664745, 0.11334294268143619, 0.12532730570573888, 0.13905304654021608, 0.15444533124216012, 0.17138257509840854, 0.18969813068165503, 0.20918313238964512, 0.2295904400817218, 0.2506395966014699, 0.2720226881244897, 0.2934109730460227, 0.31446212510967686, 0.3348279201831329, 0.35416218392553656, 0.3721288098788954, 0.38840965445731884, 0.40271211699374604, 0.4147762194071903, 0.4243810110310809, 0.4313501394384477, 0.4355564473487755, 0.4369254784425303, 0.43543780059385695, 0.43113008303755934, 0.42409489363281283, 0.41447921295127427, 0.40248169265582007, 0.3883487157972228, 0.3723693455019815, 0.35486927534898555, 0.33620391887821804, 0.3167507965488413, 0.2969013955539754, 0.2770526907848193, 0.25759852359979124, 0.23892103868788145, 0.22138237812818556, 0.20531682576605592, 0.191023584394683, 0.17876035320694975, 0.16873785393155266, 0.1611154314535982, 0.15599782909417534, 0.15343321071046684, 0.15341247206046665, 0.15586985317856156, 0.1606848325776964, 0.1676852536834204, 0.17665160475417604, 0.18732234635857142, 0.1994001559228875, 0.21255893752442506, 0.22645142750236216, 0.24071721300933754, 0.25499097165286444, 0.2689107360847558, 0.28212598788213283, 0.29430539030109404, 0.305143979332648, 0.31436964669566864, 0.3217487666024818, 0.327090839870314, 0.33025205368130034, 0.3311376823972979, 0.3297032836384385, 0.3259546736207132, 0.31994669577970775, 0.31178082624228065, 0.301601688016876, 0.2895925721596927, 0.27597008799075184, 0.26097808509889003, 0.24488100688539619, 0.22795684834179564, 0.21048989932965373, 0.1927634586302415, 0.17505270337471812, 0.15761789318283081, 0.14069807857678393, 0.1245054692553799, 0.10922059997496116, 0.09498841054716815, 0.08191533237205953, 0.0700674475924183, 0.05946975904960003, 0.05010658045008355, 0.04192302724244625, 0.03482756038667476, 0.028695508185618293, 0.02337346632222236, 0.018684453835565225, 0.01443368353675324, 0.010414789795045107, 0.0064163451052541174, 0.0022284896673292645, -0.0023505044535715395, -0.007507911098699985, -0.013410639780554902, -0.02019989668570931, -0.027986561252609603, -0.036847404040667456, -0.04682224974518118, -0.05791216466329432, -0.07007872130082173, -0.08324436480218803, -0.09729387719532909, -0.11207690679725232, -0.12741150225064993, -0.14308856426541175, -0.15887710389252277, -0.17453017467982748, -0.1897913278987904, -0.20440142565538003, -0.21810563647885223, -0.23066043218790588, -0.2418404036223105, -0.25144471624274134, -0.25930303456934106, -0.2652807567634247, -0.26928341705989617, -0.27126013383109904, -0.2712060043140536, -0.2691633728899377, -0.26522192762849206, -0.2595176089115118, -0.25223034360606567, -0.24358064773139743, -0.23382516911833437, -0.22325126848236243, -0.2121707619461868, -0.20091296973523778, -0.18981723398203545, -0.17922508284964606, -0.16947222815397486, -0.16088058906874378, -0.1537505351874595, -0.1483535381615276, -0.14492541241822307, -0.14366031228701584, -0.1447056355389561, -0.1481579622853502, -0.15406013389573053, -0.16239954966840717, -0.1731077300730051, -0.1860611651866059, -0.20108343619939728, -0.21794856732259751, -0.23638553583737096, -0.2560838401028129, -0.27669999977769144, -0.29786483993159857, -0.31919139168060046, -0.34028322694864577, -0.3607430342989962, -0.38018123676305093, -0.39822445136687556, -0.41452359365099145, -0.42876143881093354, -0.4406594639531475, -0.4499838130504397, -0.456550247077389, -0.4602279659998201, -0.4609422161940104, -0.4586756258249987, -0.4534682410135698, -0.44541626653001765, -0.4346695455171112, -0.42142784261636396, -0.4059360231249467, -0.38847824675991915, -0.36937131762369174, -0.3489573514943233, -0.3275959371370708, -0.3056559795781726, -0.2835074199334295, -0.2615130282913976, -0.2400204632792918, -0.2193547843719514, -0.1998115909389118, -0.181650945770216, -0.1650922207894647, -0.1503099793561869, -0.13743098356201705, -0.1265323868848759, -0.11764114317965435, -0.1107346329819257, -0.10574247822570018, -0.10254948746504818, -0.1009996462574299, -0.10090104218778659, -0.1020315917035438, -0.10414541703559856, -0.10697970645706971, -0.11026188034072866, -0.11371687917213545, -0.11707438800086509, -0.1200758147934189, -0.12248084769894735, -0.1240734281494643, -0.12466699267800194, -0.12410885593870329, -0.12228363014951418, -0.11911560147082767, -0.11457001103895471, -0.10865321680175351, -0.10141174123563398, -0.09293023872749097, -0.08332844415768119, -0.07275719032157336, -0.06139360562052569, -0.04943562434013706, -0.03709595928976523, -0.0245957001648945, -0.012157710372978333, -1.1130967973816593e-16], [0.0, 0.010496088284218085, 0.020302687333572735, 0.029280323979972222, 0.037317482961469334, 0.044334034947138314, 0.05028379258148508, 0.05515612352154247, 0.058976573965247914, 0.06180648192191706, 0.06374158580211821, 0.06490966013762278, 0.06546723571676603, 0.06559548548940239, 0.06549537964630833, 0.0653822327480868, 0.06547978217029418, 0.06601395002330813, 0.06720644976343, 0.06926840369769864, 0.07239413836260278, 0.07675532129541224, 0.08249559509158957, 0.0897258530326089, 0.09852028525557606, 0.10891330579269894, 0.12089744929239146, 0.13442230237490282, 0.14939450896383144, 0.1656788622057565, 0.18310046840784228, 0.20144794146480255, 0.22047756018514128, 0.2399182964144926, 0.25947759950634103, 0.2788478030704273, 0.2977130035330238, 0.31575624728862434, 0.332666854437541, 0.3481477025189802, 0.3619222933913702, 0.3737414305012452, 0.38338934213161224, 0.3906890986377024, 0.3955071878688322, 0.39775713255252815, 0.3974020559096055, 0.3944561266323648, 0.38898484098892305, 0.38110412756687534, 0.3709782883623639, 0.35881681786764863, 0.344870168827984, 0.32942455876540866, 0.3127959345796445, 0.29532323296497653, 0.2773610915247439, 0.2592721789000226, 0.241419321624875, 0.22415761054457523, 0.2078266703573486, 0.19274327214409698, 0.17919446072199738, 0.1674313564908531, 0.15766377543080268, 0.15005579144586162, 0.14472234280365595, 0.1417269595442785, 0.14108066202662195, 0.1427420528993146, 0.14661859640458919, 0.15256905073776927, 0.1604069918780804, 0.1699053415415633, 0.18080178830892377, 0.19280497012136386, 0.20560126871918769, 0.21886205264440947, 0.23225119547256748, 0.24543269021442335, 0.2580781794652437, 0.2698742239002581, 0.2805291390344733, 0.2897792415924252, 0.29739436207703773, 0.3031824988016642, 0.30699351028676714, 0.3087217669818424, 0.3083077091546339, 0.30573828485034504, 0.3010462693925998, 0.2943084952934279, 0.28564304798544954, 0.27520550783220427, 0.26318434179739864, 0.249795568399879, 0.23527683665520024, 0.21988107319357672, 0.2038698613244999, 0.18750672126513496, 0.1710504619408891, 0.154748771686557, 0.13883220791616208, 0.12350873458383824, 0.10895894132096243, 0.09533205989177457, 0.08274287252852007, 0.07126958332521612, 0.06095269878081523, 0.05179493742361811, 0.04376216188103218, 0.03678530045303419, 0.03076319986725433, 0.025566327077648412, 0.0210412163162181, 0.017015538662142726, 0.01330365563023839, 0.009712506095611547, 0.0060476675681192605, 0.00211942861523626, -0.002251290791443775, -0.0072273300647946355, -0.01295014073684374, -0.019535239831745658, -0.027068386887372124, -0.03560258878881856, -0.045156015042587365, -0.055710882443690726, -0.06721334286912314, -0.07957438180892625, -0.09267170888246412, -0.10635259565110391, -0.12043759118768019, -0.13472502272963502, -0.1489961679157352, -0.16302096711764677, -0.17656412968851964, -0.1893914769399616, -0.2012763576133526, -0.2120059687191349, -0.22138741596244685, -0.2292533535329213, -0.2354670526826011, -0.2399267620180602, -0.24256923946319345, -0.24337235599103751, -0.2423566939809834, -0.23958608786995095, -0.2351670810180983, -0.22924729974970195, -0.22201277268514547, -0.21368425007323835, -0.2045126031995547, -0.19477340745036797, -0.1847608336621292, -0.17478099045199905, -0.16514487484720017, -0.15616109933603184, -0.14812857017091594, -0.14132929418455187, -0.13602148946029644, -0.13243316896084018, -0.1307563558055507, -0.13114207454029406, -0.13369624480564604, -0.13847658271075172, -0.14549059147014282, -0.15469469703518804, -0.1659945571782874, -0.17924654443078514, -0.1942603751196026, -0.21080282918090876, -0.22860247912630946, -0.24735532214259612, -0.26673118741824664, -0.28638077194632816, -0.30594314271737316, -0.3250535317651803, -0.3433512432460558, -0.3604874887987173, -0.3761329689224246, -0.38998502399105817, -0.40177418864950426, -0.41126999747045706, -0.418285907541297, -0.4226832246690406, -0.4243739436246339, -0.42332243871790864, -0.41954596837104385, -0.41311398557451284, -0.40414627447827095, -0.392809961202073, -0.37931547356577955, -0.3639115491971835, -0.346879413771352, -0.3285262704327864, -0.30917825728522563, -0.2891730418244034, -0.26885222905233525, -0.24855376356513068, -0.22860450507356053, -0.20931315162813852, -0.19096367541678197, -0.17380942262529137, -0.158068011838113, -0.14391714523743, -0.13149142393889446, -0.1208802337540742, -0.11212674111625774, -0.10522801150656232, -0.10013623514983089, -0.0967610176957106, -0.09497266772641838, -0.09460638887517855, -0.09546726268779063, -0.09733588964291787, -0.09997454041903982, -0.10313365792695453, -0.10655854309133259, -0.10999605403721503, -0.11320114928650546, -0.11594311075766137, -0.1180112916455994, -0.11922024739302242, -0.11941412460807113, -0.1184702025084759, -0.1163015037750659, -0.11285841600993732, -0.10812929069973636, -0.10214001303157372, -0.09495256242965992, -0.08666260960566424, -0.07739622059178977, -0.06730576103158008, -0.05656511436630692, -0.045364344963224376, -0.03390395124964225, -0.022388864193018256, -0.011022352745888682, -1.0050939830742693e-16], [0.0, 0.009334905681965452, 0.017984896945979083, 0.025835850152490306, 0.0328008196466961, 0.03882272259259793, 0.04387619187780617, 0.0479685450848188, 0.05113984054090177, 0.05346201525012615, 0.05503712347441551, 0.05599471825773968, 0.0564884406814625, 0.056691902527386824, 0.05679396677614269, 0.05699354650331777, 0.05749405584042977, 0.05849765640444385, 0.060199448714141665, 0.0627817604409862, 0.06640868181770428, 0.0712209931777491, 0.07733162054724516, 0.0848217426751278, 0.09373765717185702, 0.10408849491743365, 0.11584485105129484, 0.12893837818529905, 0.14326236354836472, 0.1586732871720817, 0.17499333357340463, 0.19201380529872625, 0.20949936376600006, 0.22719300165329553, 0.24482163216647945, 0.262102164353539, 0.2787479206291635, 0.29447524316375856, 0.30901013002337197, 0.3220947400761648, 0.33349360776601494, 0.34299941485575985, 0.3504381760257175, 0.355673708547993, 0.35861127282600574, 0.3592002899936197, 0.35743606454041593, 0.35336046354106593, 0.3470615289432297, 0.3386720249036367, 0.3283669477324834, 0.3163600509867885, 0.3028994620320877, 0.2882624883859886, 0.27274973182659773, 0.25667864511035815, 0.24037667978222876, 0.2241741836399978, 0.20839721268441883, 0.193360424691421, 0.17936021982275455, 0.16666828798622133, 0.15552571310316546, 0.14613777127020047, 0.1386695433340283, 0.13324244303310598, 0.1299317400691823, 0.12876513378598356, 0.12972240812840005, 0.1327361728422861, 0.13769367007830924, 0.14443960031070685, 0.15277989738703937, 0.1624863601728985, 0.17330202818758497, 0.1849471713280067, 0.19712574966497431, 0.2095321887065968, 0.2218583087084729, 0.23380024372791247, 0.2450651872304817, 0.2553778061248472, 0.2644861739917979, 0.2721670867575331, 0.27823063982375285, 0.28252396431164467, 0.2849340411372132, 0.28538953458655125, 0.28386161133119475, 0.28036373581372526, 0.27495045802403156, 0.26771523425771265, 0.2587873448948501, 0.24832799498382813, 0.23652570292851233, 0.22359109938200128, 0.20975127213863418, 0.19524380305870495, 0.180310649614396, 0.165192026360138, 0.15012044045115028, 0.13531503030264183, 0.12097634773726362, 0.10728171174054155, 0.0943812465501308, 0.08239469864039974, 0.07140910669294126, 0.06147737638694103, 0.052617788365427326, 0.0448144436283416, 0.03801862648001748, 0.03215104162528501, 0.02710485965769949, 0.022749484577370017, 0.0189349386320988, 0.015496744154061883, 0.01226116955621011, 0.009050697570334294, 0.005689568378293238, 0.002009248643094979, -0.0021463203741794237, -0.006915836480073984, -0.012416243306468672, -0.01873894854079721, -0.02594675603914311, -0.034071595626469886, -0.043113113617832495, -0.05303816468609053, -0.0637812222232448, -0.0752457003891227, -0.08730615722018187, -0.09981132508722045, -0.11258789303027696, -0.1254449456157285, -0.13817894546164014, -0.15057913191052816, -0.16243319687091057, -0.1735330908972517, -0.18368080834143766, -0.19269400000396322, -0.20041126515985988, -0.2066969820566944, -0.21144554680851838, -0.21458490477865375, -0.2160792757095472, -0.21593099359788256, -0.21418140414059006, -0.21091078595210486, -0.20623728609505673, -0.2003148851699765, -0.19333043165868488, -0.1854998087998023, -0.177063319402454, -0.1682803941198134, -0.1594237463004441, -0.1507731111667647, -0.14260871836314254, -0.13520465458008904, -0.12882227679379848, -0.12370383655462691, -0.1200664717037616, -0.11809671398200956, -0.11794564940137152, -0.1197248532533263, -0.12350320358650059, -0.1293046563353598, -0.13710704252068026, -0.14684192362458875, -0.1583955159600203, -0.17161066922327287, -0.1862898590652938, -0.20219912906280876, -0.21907289451357628, -0.2366194995840969, -0.25452740101626065, -0.27247183630244787, -0.2901218223432408, -0.3071473224021932, -0.3232264148714525, -0.3380522970685656, -0.3513399610085281, -0.3628323857476844, -0.37230610229293903, -0.37957600193443214, -0.3844992768313343, -0.3869784023213569, -0.38696309323247313, -0.38445119089474045, -0.37948846298635197, -0.37216732418182474, -0.3626245111729073, -0.35103777038184697, -0.3376216399809299, -0.3226224291068403, -0.30631251589843556, -0.2889841017399376, -0.27094257147992934, -0.2524996181245066, -0.2339662953656099, -0.21564616219281244, -0.1978286807368734, -0.1807830214918883, -0.1647524193417721, -0.14994920964888525, -0.1365506564050035, -0.12469566453028344, -0.11448244633141579, -0.10596718844528784, -0.09916374088718426, -0.09404432470479794, -0.09054122983186103, -0.08854945065221605, -0.08793018411904817, -0.08851509458071073, -0.09011123124991241, -0.0925064689601564, -0.09547533085184962, -0.0987850432074383, -0.1022016680077397, -0.10549615801329253, -0.10845018229133198, -0.11086157702029836, -0.11254928692462633, -0.11335767654823017, -0.11316010740823722, -0.11186169645004714, -0.1094011926567753, -0.10575193160623093, -0.1009218516356634, -0.0949525794652055, -0.08791761703475026, -0.0799196843235855, -0.071087294468319, -0.06157065703093049, -0.051537022304883384, -0.041165593656206166, -0.030642145725418284, -0.020153493595123195, -0.009881961576567648, -8.974889810989019e-17], [0.0, 0.008195796570306146, 0.015728032045248475, 0.0225062506200151, 0.028465835611317623, 0.03357001639276151, 0.03781109763700888, 0.041210875781870285, 0.04382022882490161, 0.04571788712354936, 0.04700841428817903, 0.04781944795995417, 0.04829826973835968, 0.04860779126856772, 0.04892205906419025, 0.04942139362795685, 0.05028728850756867, 0.051697201825275235, 0.053819376365836835, 0.05680782440074225, 0.0607976100556613, 0.06590055526886486, 0.07220148540161836, 0.0797551175894385, 0.08858367928295716, 0.0986753265037712, 0.10998341157679284, 0.12242662898595628, 0.13589004605917432, 0.150227002967472, 0.1652618445767442, 0.18079342556749778, 0.19659931046788348, 0.21244057232545877, 0.22806707812574764, 0.24322313614682758, 0.2576533705488666, 0.2711086818912729, 0.2833521491225825, 0.2941647289887297, 0.3033506127555978, 0.3107421075555554, 0.3162039203730528, 0.3196367364275924, 0.32098000016425776, 0.32021382582580166, 0.3173599852015555, 0.31248194212606434, 0.3056839260989766, 0.2971090604608819, 0.2869365833235503, 0.27537822136010304, 0.2626737970738021, 0.2490861687799247, 0.2348956187958211, 0.22039381883949183, 0.20587751205359664, 0.19164205814200524, 0.17797499165386774, 0.16514974338592525, 0.15341967119616626, 0.14301253931801514, 0.13412557470770411, 0.1269212153039256, 0.121523648659887, 0.11801622062271698, 0.11643977304094852, 0.11679194738128731, 0.11902746816907397, 0.12305939689177768, 0.12876132398775395, 0.13597044434293262, 0.1444914408751803, 0.15410108180521626, 0.16455342055344882, 0.17558547326584387, 0.1869232380935995, 0.19828791279026184, 0.20940216312340815, 0.21999629411774005, 0.22981417925549782, 0.23861880937377, 0.24619733294550272, 0.2523654724593122, 0.2569712173946296, 0.2598977124281806, 0.2610652795529834, 0.2604325342434648, 0.2579965781279096, 0.2537922732796744, 0.24789062565210945, 0.2403963268067238, 0.23144452338831561, 0.2211969022869886, 0.20983719564378034, 0.1975662234099345, 0.18459660173250572, 0.17114725275891252, 0.15743785535925772, 0.14368337667204217, 0.13008882128791244, 0.11684432838602511, 0.10412073740194062, 0.09206573008856828, 0.08080064146022357, 0.07041801447778351, 0.06097995388925245, 0.052517313878388795, 0.04502973262003838, 0.0384865050389946, 0.0328282635694931, 0.027969416056197217, 0.023801270644231383, 0.02019576005992851, 0.017009662522956815, 0.014089204033868244, 0.011274917260996456, 0.008406625943940801, 0.005328420793497594, 0.0018934933707802951, -0.002031301644300728, -0.006561278134997628, -0.011790256132903573, -0.01778750399970845, -0.024595368104006043, -0.032227654962113314, -0.04066881120238266, -0.04987392592017208, -0.05976955854260662, -0.07025537376240805, -0.08120654397545829, -0.09247685950389242, -0.10390246821787803, -0.11530614946045765, -0.12650201285770107, -0.13730050102823416, -0.14751356669042287, -0.15695988942426728, -0.16546999551860433, -0.17289114597714972, -0.17909186283687545, -0.18396597235056508, -0.1874360550999776, -0.18945620745633446, -0.19001403563860605, -0.1891318225223112, -0.18686682785452916, -0.18331070412594688, -0.17858803250091607, -0.17285400535956408, -0.1662913036085808, -0.15910623742842894, -0.15152423802937565, -0.1437848048107083, -0.1361360266312699, -0.12882880734088262, -0.1221109339975846, -0.11622113108919625, -0.11138324545701185, -0.10780070443884705, -0.1056513840504832, -0.1050830149383537, -0.10620924157549301, -0.10910643502972499, -0.11381134197187745, -0.12031963283936453, -0.12858539070604993, -0.13852155995269602, -0.15000135083118404, -0.16286057303190388, -0.1769008489596787, -0.19189363614822835, -0.20758496861845524, -0.22370080949386412, -0.23995289225750602, -0.25604491603698476, -0.2716789515334958, -0.28656190888528327, -0.3004119170084745, -0.3129644658346954, -0.323978168322106, -0.33324000802376846, -0.340569950139327, -0.3458248090581923, -0.3489012830583994, -0.34973808662544686, -0.3483171323178139, -0.34466373670799644, -0.3388458481196027, -0.3309723170979337, -0.32119025322889605, -0.3096815335080393, -0.29665854743406356, -0.28235928187553583, -0.267041864103763, -0.2509786938294659, -0.23445030432819078, -0.21773909857014306, -0.2011231085496466, -0.18486992468994246, -0.16923093732176203, -0.15443602392712646, -0.1406888043157196, -0.12816257145102966, -0.11699698862984122, -0.10729562456676167, -0.09912437712203033, -0.09251081445281704, -0.08744443980957954, -0.08387786359747172, -0.08172884423577685, -0.08088313831941071, -0.08119808113184686, -0.08250680115429332, -0.08462295728568466, -0.08734587539377565, -0.09046595184983888, -0.09377018607034962, -0.0970477019273435, -0.10009511923694046, -0.1027216413475896, -0.10475373299434294, -0.10603927384858289, -0.10645108728238097, -0.10588976042138698, -0.10428569015727956, -0.1016003099575114, -0.09782647353516698, -0.09298799318843279, -0.08713835233851691, -0.08035863293948389, -0.07275471847131795, -0.0644538516550563, -0.055600642383599845, -0.046352635234073784, -0.03687555697048659, -0.02733837238351735, -0.01790828145055159, -0.00874579201982631, -7.911206545913137e-17], [0.0, 0.007086788962680569, 0.013546796457471847, 0.019311175408857455, 0.024335078137481973, 0.02859906081850012, 0.03210977678242046, 0.03489993816890605, 0.03702754453735926, 0.03857439619275067, 0.03964392871491097, 0.04035842300862898, 0.040855661666927744, 0.04128511714104119, 0.04180376976232957, 0.04257166374175833, 0.04374731662149619, 0.04548310207887262, 0.04792072736679125, 0.05118692497437075, 0.05538947334212112, 0.060613653778984956, 0.06691924028959745, 0.07433810608400537, 0.0828725154267529, 0.09249415256081335, 0.103143921133418, 0.11473252831005055, 0.1271418480686895, 0.14022703851009924, 0.15381936889305659, 0.1677296939852353, 0.18175249666637086, 0.19567040495025817, 0.20925907708004252, 0.22229233841599383, 0.23454744673188227, 0.24581035845102292, 0.25588086739731997, 0.2645774898442419, 0.2717419749713566, 0.27724332816231206, 0.28098124570406935, 0.2828888731092126, 0.2829348151525786, 0.28112434340643744, 0.2774997661454767, 0.2721399455092443, 0.26515896726709065, 0.2567039889289854, 0.24695231178545776, 0.23610774125488546, 0.22439631720502104, 0.21206151127290332, 0.19935900125500494, 0.1865511430556922, 0.17390126820909746, 0.1616679394402451, 0.1500992979938579, 0.13942763449992468, 0.12986431000888946, 0.121595145639245, 0.11477638823403816, 0.10953134578817246, 0.10594777051649784, 0.10407604966996045, 0.10392824500571105, 0.10547800164433392, 0.10866132639419852, 0.11337821499182216, 0.11949508759973175, 0.12684797280814636, 0.13524636276720708, 0.14447764635927055, 0.15431201388572746, 0.1645077159133307, 0.17481655096032706, 0.18498945179129414, 0.1947820383450201, 0.20396000677741197, 0.21230422871826565, 0.21961544249594994, 0.22571842858255975, 0.23046557458911276, 0.23373975046815706, 0.23545643177734485, 0.23556502749422684, 0.2340493884874859, 0.2309274928574106, 0.22625032446199989, 0.22009998054919308, 0.21258706303830208, 0.20384742517810164, 0.19403836063518964, 0.18333433516108946, 0.17192237153329898, 0.15999720621112068, 0.14775634090889958, 0.1353951139589724, 0.12310191488312176, 0.11105366106137175, 0.0994116479037093, 0.08831787369044394, 0.07789192751523437, 0.06822851386797017, 0.059395670712602586, 0.05143371987160724, 0.04435496958106386, 0.03814416970733468, 0.032759700806658666, 0.0281354594490084, 0.024183384489012475, 0.02079655269502561, 0.017852757750522478, 0.015218474480203423, 0.012753100530283754, 0.01031336088795368, 0.007757756728390592, 0.0049509392241126, 0.0017678911593397718, -0.0019021955972530597, -0.006152450628671989, -0.011055356640399581, -0.016660362261384162, -0.022992140785406404, -0.030049542807944866, -0.03780527261640016, -0.04620629931102264, -0.05517499444896543, -0.06461096900129208, -0.07439356407499846, -0.08438493264521293, -0.09443363390472324, -0.10437864816777703, -0.11405370891252214, -0.12329183980345157, -0.13192997862844252, -0.13981356717013402, -0.14680098618920476, -0.15276771793124355, -0.15761012480582567, -0.16124874197708453, -0.16363099332861172, -0.16473325433469155, -0.164562201438043, -0.16315540520409008, -0.16058114335505852, -0.15693742931566965, -0.15235027163919923, -0.14697119913528844, -0.14097410520219117, -0.13455148230730093, -0.1279101333218026, -0.12126646009994232, -0.11484144095322076, -0.10885541721677786, -0.103522814717996, -0.09904692848697631, -0.09561489842203287, -0.09339299984587106, -0.09252236604278825, -0.09311525011325458, -0.0952519210510326, -0.09897827413761216, -0.10430421891655677, -0.11120288956428306, -0.11961070286233658, -0.12942826867734336, -0.14052213736430502, -0.1527273483279739, -0.16585072460019956, -0.17967484019375077, -0.1939625706197909, -0.20846212270986778, -0.22291242811497214, -0.23704877585480097, -0.25060855328275966, -0.26333696196655, -0.27499257533336685, -0.2853526084871525, -0.29421777728873433, -0.3014166334371876, -0.3068092746689018, -0.31029034399923777, -0.311791248810473, -0.3112815491283458, -0.3087694841768268, -0.3043016267761654, -0.29796167585454725, -0.28986841777521155, -0.2801729068420325, -0.2690549337599333, -0.2567188675456331, -0.2433889710046182, -0.22930430205916197, -0.21471332263749884, -0.19986834329136766, -0.1850199350465394, -0.17041144013402632, -0.15627371020219935, -0.14282019445427832, -0.13024249104999513, -0.11870646328533974, -0.10834900781740547, -0.09927554588854508, -0.09155829053179641, -0.08523532355427259, -0.08031049617232522, -0.07675414700449336, -0.07450461121309404, -0.07347047541309705, -0.07353351500846979, -0.0745522343111828, -0.07636591554430433, -0.07879907097410921, -0.08166618324264978, -0.084776612700317, -0.08793954731350362, -0.09096887061543667, -0.09368782617070928, -0.09593336305078856, -0.0975600557083681, -0.09844350316140824, -0.09848312625637973, -0.09760429762022205, -0.09575975632864904, -0.09293027787279452, -0.08912458922735372, -0.08437853822596691, -0.07875354554460512, -0.07233438590059989, -0.06522636213370407, -0.0575519512181631, -0.04944701457583924, -0.0410566759869228, -0.03253097865417424, -0.024020438363810064, -0.01567161206839089, -0.007622800537426246, -6.867870746608381e-17], [0.0, 0.00601523610734062, 0.011454323438248058, 0.01626762861120483, 0.02042724200604711, 0.023927863856681164, 0.026787055977543033, 0.029044850715189363, 0.030762725508511155, 0.032021968040233995, 0.03292147294708991, 0.03357502601999825, 0.03410814538783636, 0.034654560992924, 0.035352423430835424, 0.036340340690485945, 0.037753346299080934, 0.039718904719414645, 0.04235305949891149, 0.04575682663298303, 0.05001292994951502, 0.05518296718224424, 0.061305084976612426, 0.06839222861823802, 0.07643101809860121, 0.08538128658582457, 0.09517630083648737, 0.10572366597866065, 0.11690689984341249, 0.1285876450531663, 0.1406084708156149, 0.1527962012298025, 0.16496569326796784, 0.17692397579782546, 0.18847465135511318, 0.19942245511277173, 0.2095778608095749, 0.21876162142228256, 0.22680913314955045, 0.2335745148126506, 0.23893430098910168, 0.24279065593579768, 0.24507402642051, 0.24574516469929159, 0.24479646773555241, 0.24225259499411642, 0.23817034436538248, 0.23263778356082385, 0.22577265223682397, 0.21772006771074748, 0.20864958399947328, 0.1987516696223557, 0.18823368378130698, 0.17731544281155087, 0.16622447888443778, 0.15519110058910932, 0.14444337003277463, 0.13420211335444013, 0.12467608098609063, 0.11605737062946227, 0.10851721982540961, 0.10220226632280996, 0.09723136341471812, 0.09369302426873799, 0.09164355435555052, 0.09110591473706253, 0.09206934161127212, 0.09448972954717198, 0.09829076771685981, 0.10336580058429747, 0.10958036737463271, 0.11677535864067813, 0.1247707137521404, 0.1333695705090981, 0.14236276762856936, 0.15153359282276307, 0.1606626637710501, 0.16953282661181085, 0.17793395670456866, 0.18566754932804203, 0.19255099360801162, 0.1984214311660163, 0.20313911153854586, 0.20659016907174618, 0.2086887604326524, 0.2093785177353763, 0.20863328916597756, 0.2064571564848252, 0.20288373645791577, 0.19797479068312235, 0.19181818500534997, 0.18452525534561723, 0.1762276509207732, 0.16707373815798707, 0.15722465881238565, 0.14685014363166538, 0.13612418819188574, 0.125220700131583, 0.11430922688122408, 0.10355087013435059, 0.09309448781574516, 0.0830732763163463, 0.07360181549205283, 0.06477364662827799, 0.056659439568236894, 0.049305789846771024, 0.042734670352279076, 0.03694354516973766, 0.03190613626354112, 0.027573816967991716, 0.023877590285514148, 0.020730595148937842, 0.01803107045665123, 0.01566569517210073, 0.013513213379634445, 0.011448246141126965, 0.00934518747685746, 0.007082079910691119, 0.0045443658182377, 0.0016284142742738798, -0.00175527087766096, -0.005679247569588604, -0.010196811863458388, -0.015340216743472673, -0.021119481797144332, -0.02752182680962086, -0.03451174601183148, -0.042031722994378046, -0.05000356955023725, -0.05833035536542051, -0.06689887995297888, -0.07558262391701166, -0.08424510390424791, -0.09274354477652194, -0.10093277389564709, -0.10866923617585374, -0.11581502489088193, -0.12224182222148754, -0.1278346452261376, -0.1324952972768861, -0.13614543192082404, -0.1387291454376613, -0.14021502583819284, -0.14059759940426766, -0.13989813077831464, -0.138164748699934, -0.13547188635856267, -0.13191904256449696, -0.1276288871052817, -0.12274475032113585, -0.11742755268362332, -0.11185224460001465, -0.10620383942730993, -0.1006731334412003, -0.09545221499182868, -0.09072987107147179, -0.08668700286194779, -0.08349216242994162, -0.08129732057242559, -0.08023397092649813, -0.08040966796011381, -0.08190508652917411, -0.08477167855948542, -0.08902998838120595, -0.0946686726481565, -0.10164425399359774, -0.10988162001653114, -0.11927526128687636, -0.1296912242420082, -0.14096973755747183, -0.15292845423548918, -0.16536623666754652, -0.17806739866070265, -0.1908063071982953, -0.20335223781156844, -0.21547437108988024, -0.2269468142116372, -0.23755353052812836, -0.24709306220155244, -0.2553829356413131, -0.26226364688569465, -0.26760213396072385, -0.27129465537497516, -0.2732690079838434, -0.27348603313740466, -0.27194037693097717, -0.26866048809561976, -0.2637078551659665, -0.2571755026047416, -0.24918578310835693, -0.23988751993999785, -0.22945256843222933, -0.2180718793999052, -0.2059511587775215, -0.1933062270644343, -0.18035818890483227, -0.1673285271873828, -0.15443423732846634, -0.14188311587784255, -0.12986931329992613, -0.11856925384920043, -0.10813801605081085, -0.09870625565398768, -0.09037773933795627, -0.08322754225605912, -0.07730094608159635, -0.07261305697536247, -0.06914914525655572, -0.06686569096096787, -0.06569210234650381, -0.06553305817683379, -0.06627140967701135, -0.06777156477496683, -0.06988326594282135, -0.07244566390506274, -0.0752915829033871, -0.0782518692552339, -0.08115971370398044, -0.08385483955504351, -0.08618745277720509, -0.08802185700903924, -0.08923964556908803, -0.0897423938887384, -0.08945378897846364, -0.08832114726497584, -0.08631628802495216, -0.08343574628807782, -0.07970032606771553, -0.0751540116733572, -0.06986227123990633, -0.06390980206315215, -0.0573977814707979, -0.05044069942991054, -0.04316285958283458, -0.035694643652816306, -0.028168639962808578, -0.02071574002288844, -0.013461307685477809, -0.006521523232359448, -5.852348480925827e-17], [0.0, 0.004987720565017255, 0.009462008495003844, 0.013389758965878854, 0.01675695020127215, 0.019569102452243164, 0.021851187485210748, 0.023646989598476106, 0.02501793353156755, 0.026041408600030635, 0.02680863162631369, 0.027422103408305937, 0.027992724260723165, 0.028636643305154724, 0.029471923437760672, 0.030615109082150378, 0.032177786803645005, 0.03426322954008873, 0.036963213571213634, 0.04035509343893938, 0.044499213937773216, 0.049436730165516155, 0.05518789665895003, 0.06175087508267658, 0.0691010970777302, 0.07719120502918692, 0.08595157902324221, 0.09529144349542283, 0.10510053239178002, 0.11525127744173881, 0.12560147073181824, 0.13599734051128673, 0.14627696836364368, 0.1562739668156353, 0.16582132935980165, 0.1747553599204227, 0.18291958612634981, 0.19016856044142452, 0.19637145525965885, 0.20141536245504602, 0.20520821448406498, 0.20768125281660324, 0.20879098001063096, 0.2085205438935387, 0.20688051577441416, 0.20390903905949298, 0.19967133972543094, 0.19425860545349455, 0.18778625546662345, 0.1803916378670422, 0.17223120518238574, 0.16347723155118285, 0.15431414620058548, 0.1449345673136522, 0.13553512781658228, 0.12631218985364576, 0.11745754762826284, 0.10915421879887575, 0.10157242271280492, 0.09486583948421551, 0.0891682373758824, 0.08459054728637314, 0.0812184525842258, 0.07911055032483655, 0.07829712633065103, 0.07877957204043363, 0.08053045579337596, 0.08349424567930712, 0.08758866563509465, 0.09270665147506273, 0.09871885937408413, 0.10547666631967335, 0.112815590528865, 0.12055905006525787, 0.12852237012630408, 0.13651694388653896, 0.14435444851109927, 0.1518510170708229, 0.1588312686119438, 0.16513210251746513, 0.17060616944315568, 0.1751249393630242, 0.17858129740964612, 0.18089160999024465, 0.18199721680624653, 0.18186531857580937, 0.1804892451045413, 0.17788810350245818, 0.17410582143147268, 0.1692096149161451, 0.1632879241014439, 0.1564478730557754, 0.14881232098531444, 0.14051658177299828, 0.13170489635197558, 0.12252674788726653, 0.11313311294263736, 0.10367274268043092, 0.0942885666666192, 0.08511430807634458, 0.07627139311857173, 0.06786622947861219, 0.05998791872119624, 0.05270645615687957, 0.04607145894220587, 0.04011144948234612, 0.03483370688051752, 0.0302246845929706, 0.026250977969183055, 0.02286081134823594, 0.019986001195959214, 0.017544339733848523, 0.015442332931144918, 0.013578217870034354, 0.011845177571389587, 0.010134666556557734, 0.008339757837870542, 0.006358421739098727, 0.004096648951570876, 0.0014713344789067933, -0.0015871544963740097, -0.005132795441033581, -0.009202170503792044, -0.01381321665543934, -0.01896450002759617, -0.02463503484986168, -0.03078465316126926, -0.037354917076742454, -0.044270551187978825, -0.05144135903155316, -0.058764574811955086, -0.0661275900482258, -0.07341098481370825, -0.08049178501507277, -0.0872468609206872, -0.09355637806131577, -0.09930720979591016, -0.10439622131321057, -0.10873333761936586, -0.11224431307834208, -0.1148731272047942, -0.11658394048428669, -0.11736255479016881, -0.11721733521347331, -0.11617956351838887, -0.11430320764829921, -0.11166410638204473, -0.10835858301068903, -0.1045015164021184, -0.10022391168077857, -0.09567002562435072, -0.09099411344353382, -0.08635687357256812, -0.08192167520316654, -0.07785065933516318, -0.07430080793631863, -0.07142007729896624, -0.06934369080769522, -0.06819068310369773, -0.06806078211991766, -0.06903170779542626, -0.0711569566399121, -0.07446412994121378, -0.0789538505654027, -0.08459929930166507, -0.09134638689387128, -0.09911456263863605, -0.10779824508902992, -0.11726884535970121, -0.127377339151981, -0.13795733025988666, -0.14882853630848372, -0.1598006171108485, -0.17067725756493868, -0.18126041065670712, -0.1913546020490203, -0.20077119601993546, -0.20933252321342494, -0.21687577376614658, -0.22325656480200862, -0.228352098911669, -0.23206383987247406, -0.23431964328209537, -0.2350752926989744, -0.2343154059906941, -0.23205369154441702, -0.22833254942785672, -0.2232220281294591, -0.21681816277471871, -0.20924073534077856, -0.20063051101865395, -0.19114601717117766, -0.18095994200752688, -0.17025523888455377, -0.1592210288399958, -0.14804839840360168, -0.1369261918152569, -0.12603689645825372, -0.1155527176040927, -0.10563193353416486, -0.09641561488207079, -0.0880247828102071, -0.08055806962693535, -0.07408993294060852, -0.06866946074493967, -0.06431979027645927, -0.06103814843907784, -0.05879650642451956, -0.057542826244221176, -0.05720286259474677, -0.05768247015528532, -0.058870354388047656, -0.06064119347322318, -0.06285905041245614, -0.06538098778520442, -0.06806079329622519, -0.07075272221012091, -0.07331516307323462, -0.07561413575868522, -0.077526535763402, -0.07894304570714404, -0.07977064395034839, -0.07993465092982621, -0.07938026593606928, -0.07807356031505261, -0.07600190713499533, -0.07317384185931054, -0.06961836314527997, -0.06538369717687745, -0.06053556258056487, -0.05515498562255865, -0.049335726728184794, -0.04318138911494057, -0.03680228824752015, -0.030312166708526465, -0.023824842787335945, -0.017450882530927612, -0.011294384140923503, -0.005449960465010328, -4.8714918725756347e-17], [0.0, 0.004009968957241977, 0.007579365989543841, 0.010688689141137898, 0.013334589353382583, 0.015529999089177397, 0.017303802154963528, 0.01870005242458568, 0.019776760979460947, 0.020604282504271054, 0.02126334232884676, 0.02184275501641963, 0.02243689362337464, 0.023142975485567638, 0.02405823544811526, 0.025277060718041686, 0.026888162896101044, 0.028971862196608928, 0.031597556401652106, 0.0348214427761693, 0.038684555097414274, 0.04321117027471379, 0.0484076299422216, 0.054261612123400305, 0.06074187684635634, 0.06779849771297218, 0.0753635791880987, 0.083352447083589, 0.0916652876734226, 0.10018919939267949, 0.10880061043360471, 0.11736800602498869, 0.12575490100799666, 0.1338229867107045, 0.1414353762447808, 0.1484598693282721, 0.15477215665956853, 0.1602588847627328, 0.16482050507790771, 0.1683738358183701, 0.17085427164680742, 0.1722175843820274, 0.172441267537455, 0.17152538828254046, 0.16949292214560466, 0.16638955815605422, 0.16228297485304552, 0.15726160035513506, 0.15143288217829767, 0.1449211044012355, 0.13786480081425984, 0.13041382257936127, 0.12272612743035421, 0.11496436434292652, 0.10729233273384706, 0.09987139847854141, 0.09285695028526542, 0.08639497919921221, 0.08061886124743964, 0.0756464185408313, 0.07157732763508237, 0.06849093577628854, 0.06644453601613699, 0.06547214131098594, 0.06558378588236097, 0.0667653696013955, 0.06897904827085038, 0.07216415972901673, 0.07623866300485765, 0.081101055621664, 0.08663272287177554, 0.09270066274092138, 0.0991605213928629, 0.10585986694481121, 0.1126416238439379, 0.11934758662427682, 0.12582193026407484, 0.13191463481028878, 0.13748474437442532, 0.14240338496824093, 0.14655647182789694, 0.14984704471534616, 0.15219717898993615, 0.15354943077967795, 0.15386778608866158, 0.15313809586970215, 0.1513679916680452, 0.14858628909268048, 0.14484189878506867, 0.14020227642603594, 0.1347514543594196, 0.12858770734618757, 0.12182091355351836, 0.1145696789218655, 0.10695829837039196, 0.09911363077150544, 0.09116196616875523, 0.0832259632973854, 0.07542173311033887, 0.06785613977975273, 0.06062438464678612, 0.053807930986437595, 0.04747281843416835, 0.04166840571769559, 0.03642656920949591, 0.03176137304504871, 0.02766921443595623, 0.02412943565107439, 0.021105382248493152, 0.01854587581514876, 0.01638705899299475, 0.014554561203199338, 0.012965925456723868, 0.011533230160754191, 0.010165835056616012, 0.008773177473790745, 0.007267544028283514, 0.005566743755969198, 0.003596611428455278, 0.0012932743785748246, -0.0013948775528626197, -0.004505571508575905, -0.008061423930332297, -0.01206913879885894, -0.016519153762769523, -0.02138574441769445, -0.02662758502270153, -0.03218875200025659, -0.03800014496159613, -0.043981289026327475, -0.05004247214250458, -0.056087162217752874, -0.06201464137049922, -0.06772278869538277, -0.07311093876111796, -0.07808274073154456, -0.08254894258404075, -0.08643002640867886, -0.08965862417286118, -0.09218164854849631, -0.09396208029528448, -0.09498036210510058, -0.09523535853121602, -0.09474485241146618, -0.09354555977850589, -0.09169265734454679, -0.08925882895060493, -0.08633284957362553, -0.08301773728300983, -0.07942851463461316, -0.07568963110561557, -0.07193210705199818, -0.06829046708612843, -0.06489953653550252, -0.06189117860598374, -0.05939105192931151, -0.0575154682676888, -0.05636842826900146, -0.05603890935456537, -0.05659847416516936, -0.05809926062433366, -0.06057240577649012, -0.06402694533687306, -0.06844921959699277, -0.07380280423929637, -0.08002897202186082, -0.08704767850651912, -0.09475905233480493, -0.10304535831633008, -0.11177339008434337, -0.12079723857654132, -0.1299613733744351, -0.13910396620955945, -0.14806037991092272, -0.1566667418752896, -0.1647635188952978, -0.17219900993733864, -0.17883267523000457, -0.18453822376370385, -0.18920638692349648, -0.19274731334490164, -0.19509252901811486, -0.19619641695305068, -0.19603718210607493, -0.19461727948241533, -0.19196329606903373, -0.1881252902113658, -0.1831756049086688, -0.17720718395415602, -0.1703314315852071, -0.16267566705094302, -0.15438023498913525, -0.14559534050261977, -0.13647768414456224, -0.12718697651085806, -0.11788241469045832, -0.10871920338198311, -0.09984520203798891, -0.09139777598641874, -0.08350092418985847, -0.07626274927107482, -0.06977332683429484, -0.0641030211604138, -0.059301283298306966, -0.05539595568782064, -0.0523930950269944, -0.0502773124433561, -0.04901261745848849, -0.048543740055613384, -0.048797893670408585, -0.04968693140673335, -0.05110983848780309, -0.052955496115092426, -0.05510564571082369, -0.05743797811318188, -0.05982926977949577, -0.06215848748746043, -0.06430978441541747, -0.06617531378848962, -0.06765779140916403, -0.06867274521467479, -0.06915039834328979, -0.06903714183401308, -0.06829656378384472, -0.06691001327229688, -0.0648766893439352, -0.06221325751405323, -0.058953008323718185, -0.055144584115198646, -0.05085031113505813, -0.0461441840260309, -0.0411095584913414, -0.035836615188795766, -0.030419663555842438, -0.02495435814114483, -0.019534902027938672, -0.014251312031440413, -0.009186818536905023, -0.0044154691647951706, -3.931448431194677e-17], [0.0, 0.0030867784128777677, 0.0058139112294994895, 0.008172385718557062, 0.010166201786898114, 0.011812270809471963, 0.013139949830177676, 0.01419022273083771, 0.015014549218661064, 0.015673411212590957, 0.016234594193761113, 0.01677124812144619, 0.017359778423647058, 0.01807762219931306, 0.019000967997746233, 0.020202479285611634, 0.02174908192606541, 0.02369987466911534, 0.026104218817433883, 0.02900005895541499, 0.03241252101557536, 0.03635282714346566, 0.04081755897842514, 0.045788292287296715, 0.05123161658745606, 0.05709954370602295, 0.06333029938592369, 0.06984948231277248, 0.07657156554357733, 0.08340170650525473, 0.09023782372011578, 0.09697289140961728, 0.10349739730493819, 0.10970190450247154, 0.11547965516045086, 0.1207291523202365, 0.12535665619506867, 0.12927853290420901, 0.13242339680614104, 0.13473399222740717, 0.13616876638376893, 0.13670309250389617, 0.13633011041862267, 0.13506116097080711, 0.13292580031074228, 0.12997139023290352, 0.12626227093483058, 0.12187853268753356, 0.1169144126508726, 0.11147635220732073, 0.10568075849825131, 0.09965152112339926, 0.09351734102642442, 0.08740893328730087, 0.081456168758445, 0.07578522113534666, 0.0705157861013603, 0.06575843762702185, 0.06161218337293803, 0.05816227651664813, 0.055478335309352415, 0.05361281441342702, 0.052599863752113445, 0.05245460142062404, 0.0531728173862828, 0.05473111448299926, 0.057087482830923346, 0.060182293537792045, 0.0639396876139732, 0.0682693266995655, 0.07306846368559247, 0.07822428381859459, 0.08361646058985192, 0.08911986577844822, 0.09460736955943513, 0.0999526646862446, 0.10503304845374652, 0.10973209744923029, 0.11394217296796079, 0.11756669933434004, 0.12052216311888513, 0.12273978823129732, 0.12416684992657336, 0.12476759968426497, 0.12452378248953289, 0.12343473802200827, 0.12151708739850196, 0.11880401716863068, 0.11534418198146977, 0.11120025648816162, 0.1064471753964504, 0.10117010794497444, 0.09546221923959626, 0.08942227574241617, 0.0831521556109091, 0.0767543264703647, 0.07032935352593374, 0.0639734996784362, 0.05777647653689189, 0.051819400994675774, 0.046173006465505026, 0.04089615110360016, 0.03603465753240678, 0.031620509976620914, 0.0276714254515534, 0.024190806045629606, 0.021168069578474058, 0.018579346273980737, 0.01638851979718494, 0.014548582298532084, 0.013003265207158844, 0.011688900613403214, 0.010536462351916638, 0.009473731482734556, 0.00842752787754157, 0.007325948125292856, 0.006100550010759352, 0.0046884253882980035, 0.0030341063295863855, 0.001091253889156162, -0.0011759154091471437, -0.00379150335515723, -0.006767134217361704, -0.010101510753444317, -0.013780334329620307, -0.01777659189378274, -0.022051202953024776, -0.026554010278998435, -0.031225089044280823, -0.03599634070877012, -0.04079333044058413, -0.04553732036318493, -0.05014744563564304, -0.054542976431968856, -0.058645606390482316, -0.06238170712121933, -0.0656844889163787, -0.06849600989512436, -0.07076897938055492, -0.07246830626694187, -0.0735723493679085, -0.0740738340874135, -0.07398040804321375, -0.07331481729110602, -0.07211469432314724, -0.07043195880658587, -0.06833184184749845, -0.06589155415816378, -0.06319862763901503, -0.0603489683246462, -0.057444666175647724, -0.05459161363293485, -0.05189699002453582, -0.04946667269337663, -0.04740263799966285, -0.04580041608113764, -0.044746662405357046, -0.04431690673591625, -0.044573536213744554, -0.04556406391719282, -0.04731972763789624, -0.049854455852766835, -0.05316422917362933, -0.057226856126336004, -0.06200217218048091, -0.06743266076172734, -0.0734444847806927, -0.07994890725541647, -0.08684407013331476, -0.0940170916661948, -0.10134643487416302, -0.10870449294417317, -0.1159603320121808, -0.12298252780850302, -0.12964203020324705, -0.13581498883449586, -0.14138547375922403, -0.14624802741924633, -0.1503099881062133, -0.15349353044742667, -0.1557373750892043, -0.15699812756554743, -0.15725121511745313, -0.15649139975913684, -0.15473285594005817, -0.1520088114815214, -0.14837076082257875, -0.14388726974024885, -0.13864240036754422, -0.1327337942849929, -0.12627045949024476, -0.11937031396167642, -0.11215754415890697, -0.10475984101073216, -0.09730557862891125, -0.0899210020917236, -0.08272749014026547, -0.0758389565385248, -0.0693594502199391, -0.06338100927041941, -0.05798181740828529, -0.053224704074704525, -0.04915602073191574, -0.045804916691970225, -0.04318302799549497, -0.04128458277020316, -0.0400869163711952, -0.03955137968863182, -0.03962461454647421, -0.0402401613402845, -0.04132035618669973, -0.04277846807355215, -0.044521020971645925, -0.04645024172941551, -0.04846657191785786, -0.05047118068595474, -0.052368416148455825, -0.05406813484152428, -0.05548785229199366, -0.05655466266030917, -0.05720688160841972, -0.05739537385314728, -0.0570845351065765, -0.05625290706859595, -0.05489341359610514, -0.0530132158898566, -0.050633194268729365, -0.04778707359790168, -0.04452021846361678, -0.04088813251692749, -0.036954703833699726, -0.032790244473021875, -0.02846937750339777, -0.024068828479619584, -0.0196651806016431, -0.015332653515663661, -0.011140964910712208, -0.007153331743936261, -0.0034246641548218854, -3.0375801154343544e-17], [0.0, 0.0022219555972443966, 0.004171069446503912, 0.005845571382185912, 0.007253435356323115, 0.008412151093116658, 0.009348226412036868, 0.010096432920519444, 0.010698814511709412, 0.011203484346991402, 0.011663241598237417, 0.0121340440280833, 0.012673376375221045, 0.013338557385694795, 0.014185030115982846, 0.015264680782031815, 0.01662423092170541, 0.01830374598666781, 0.02033530072267454, 0.022741837901568397, 0.025536252227140673, 0.028720725667476642, 0.03228633420650775, 0.036212939212857814, 0.04046936946401033, 0.045013892517150454, 0.049794966768584914, 0.05475225837572817, 0.059817900409421414, 0.0649179653313578, 0.0699741163102255, 0.0749053981425683, 0.07963012475156811, 0.08406781749675207, 0.08814114691183457, 0.09177783004054282, 0.09491243627645742, 0.09748805651838181, 0.09945779348427203, 0.10078603511303379, 0.10144947802697901, 0.10143787390697695, 0.1007544782049617, 0.09941618772466203, 0.09745336106790048, 0.09490932358802415, 0.09183956612672374, 0.08831065424828718, 0.08439887174336957, 0.08018862867883064, 0.07577067006060362, 0.07124012610978471, 0.0666944491058193, 0.062231284626462775, 0.057946326739984025, 0.053931207236981284, 0.050271468312473234, 0.047044666238560885, 0.04431865054813605, 0.04215005915322921, 0.040583064746502716, 0.03964840190391288, 0.039362697664549084, 0.039728121171380554, 0.040732360388896445, 0.0423489261543915, 0.04453777605757913, 0.04724624306699005, 0.050410246615317435, 0.053955757194426204, 0.057800479555679254, 0.06185571450663244, 0.06602835516419255, 0.07022297046622293, 0.07434392683114677, 0.07829749813301314, 0.08199391464318104, 0.08534930326510937, 0.0882874742123081, 0.09074151317987134, 0.09265514293930013, 0.09398382402287998, 0.09469557061509866, 0.09477146477460471, 0.09420585949777316, 0.09300626872176296, 0.09119294996417142, 0.08879819272125004, 0.08586533281506878, 0.08244751941911108, 0.0786062673421189, 0.07440983216952954, 0.06993144992936651, 0.06524748596762328, 0.06043553961588657, 0.05557255196799741, 0.050732963638729894, 0.04598696777085284, 0.04139890083144474, 0.037025809965612326, 0.03291623095337447, 0.02910920526440722, 0.025633558466973207, 0.022507455479927302, 0.019738241031271513, 0.01732256638305286, 0.01524679608422902, 0.013487681403792836, 0.012013280354192312, 0.010784098008634927, 0.009754415300264154, 0.008873769803881704, 0.008088548258332738, 0.00734364788244968, 0.006584161935966113, 0.005757044517650267, 0.004812710285889296, 0.003706526612911588, 0.002400158595107215, 0.000862731263550664, -0.0009282218294878052, -0.002986048853739785, -0.005314527717172621, -0.007907684051522592, -0.010749884302989758, -0.013816201869473412, -0.01707304707981006, -0.020479044894604184, -0.023986137698163695, -0.02754088461237156, -0.03108592354736655, -0.03456155784388986, -0.0379074259698652, -0.041064210396748006, -0.04397534056045966, -0.04658864474037314, -0.04885790677200508, -0.050744285719989915, -0.05221755992434282, -0.053257161114637394, -0.05385296945809724, -0.05400584634077779, -0.05372788822869738, -0.05304239195500383, -0.05198352905541802, -0.05059573414540017, -0.04893281961406409, -0.047056835919046434, -0.045036703326895626, -0.0429466468895022, -0.040864471628016576, -0.038869719179685326, -0.03704175044020824, -0.035457800919515836, -0.03419105656418278, -0.033308797655368205, -0.03287065706675252, -0.032927036691282496, -0.033517722276063755, -0.03467073232614082, -0.03640143126000298, -0.03871193075477729, -0.04159079635876693, -0.045013069140342386, -0.04894060456365025, -0.05332272311866326, -0.05809715967363748, -0.06319129124775902, -0.06852361609956852, -0.07400545086026297, -0.07954280706252707, -0.08503840395826477, -0.09039377109318816, -0.09551139179817568, -0.10029683762481141, -0.10466084382498801, -0.10852127725172331, -0.11180495051080036, -0.11444923976197743, -0.11640346816845508, -0.1176300225128505, -0.11810517680337083, -0.11781960363216827, -0.11677856145042613, -0.1150017536116523, -0.11252286281903694, -0.10938877230531727, -0.10565849248743191, -0.10140181879328289, -0.09669775268539223, -0.09163272345289916, -0.08629865297511975, -0.08079090926525313, -0.07520619709551626, -0.06964043532604391, -0.06418667067920737, -0.0589330766179234, -0.05396108372987592, -0.049343684647032024, -0.04514395212623579, -0.041413803592194036, -0.03819303933130954, -0.03550867477531834, -0.033374580094605304, -0.03179143281072354, -0.03074698152120425, -0.030216611294567507, -0.030164194024545163, -0.030543200207931283, -0.03129804239685721, -0.03236561512485461, -0.03367699154885873, -0.03515923349589962, -0.03673726913813758, -0.03833579120044198, -0.039881128459672746, -0.04130304432377135, -0.042536418452099344, -0.04352277063822649, -0.04421159043766047, -0.04456144117623981, -0.044540812888461546, -0.044128705258619824, -0.04331492860609884, -0.042100118193555434, -0.04049546446072361, -0.0385221690130387, -0.03621064314187818, -0.03359947214791044, -0.030734174618447515, -0.02766579092710955, -0.024449339452181414, -0.021142182243926555, -0.017802344031074925, -0.014486829490071932, -0.011249983583189635, -0.008141938507937662, -0.005207188423905051, -0.0024833296957057537, -2.1943931114862457e-17], [0.0, 0.0014182690548351041, 0.0026541127320424164, 0.0037096803053114926, 0.004593551551523369, 0.005320484142504626, 0.0059109857733642334, 0.006390722092300907, 0.006789775811122167, 0.007141776300881208, 0.007482922413010988, 0.007850924125370945, 0.008283890821434405, 0.008819195512454516, 0.00949234506761759, 0.010335886505430155, 0.011378378619661596, 0.012643456683167341, 0.01414901572981558, 0.015906535013476483, 0.017920562755167253, 0.020188376301385248, 0.022699828427515164, 0.025437385839316404, 0.02837636106975431, 0.031485334059325056, 0.03472675486860427, 0.03805771432362142, 0.04143086505489289, 0.044795471469170754, 0.04809856378862409, 0.05128616849203499, 0.054304585368572626, 0.05710168000204824, 0.05962815987943077, 0.06183880247996648, 0.06369360464916063, 0.0651588242742991, 0.06620788771526945, 0.06682213954828564, 0.06699141487619337, 0.06671441865798113, 0.0659989011099674, 0.06486162311977794, 0.06332811067222048, 0.061432202389628536, 0.059215399312967563, 0.05672603087047552, 0.054018255479148965, 0.051150918290011074, 0.04818629212029077, 0.04518873052688485, 0.04222326419332512, 0.03935417327149548, 0.03664356900234232, 0.03415001781891538, 0.03192724021203095, 0.030022914935136074, 0.028477616681179457, 0.027323912239233836, 0.026585636407778494, 0.026277364695297498, 0.026404095180226368, 0.026961146944427496, 0.02793427735779524, 0.029300015301154083, 0.031026202296502034, 0.033072728592246727, 0.035392446645921956, 0.03793224026968284, 0.04063422405587451, 0.043437044669311115, 0.04627725325259183, 0.049090716596828066, 0.05181403392023872, 0.054385926089608023, 0.05674856491331465, 0.058848811708621426, 0.06063933666010534, 0.0620795934823949, 0.06313662750392934, 0.0637856994096953, 0.06401071141764235, 0.06380442750353459, 0.06316848431290423, 0.06211319448278219, 0.06065714911499898, 0.058826630973951556, 0.05665485450657807, 0.05418105289045402, 0.0514494359075291, 0.04850804542916805, 0.045407537611063684, 0.04219992247935817, 0.03893729240526023, 0.035670570996984056, 0.032448313186880524, 0.029315585779520356, 0.026312955493424488, 0.02347560863316056, 0.020832623044049682, 0.01840640901765811, 0.016212331433736987, 0.014258520754222131, 0.012545875645124785, 0.011068255114486251, 0.00981285324180449, 0.008760744957160123, 0.007887587022233956, 0.007164454478078787, 0.006558789452784676, 0.006035436449858053, 0.005557736133865667, 0.0050886482454443995, 0.004591873646769487, 0.004032945635654955, 0.003380261566949882, 0.002606027459914368, 0.0016870906073450367, 0.0006056381763900495, -0.0006502566737338392, -0.002086255625611043, -0.003701553082156609, -0.005488856549524232, -0.007434550210487347, -0.009519037581695599, -0.011717254458143311, -0.013999338879890983, -0.016331440723154473, -0.01867664982551975, -0.02099601839742912, -0.023249650929984624, -0.025397832947866007, -0.027402168824026088, -0.029226698499762425, -0.030838963350675184, -0.03221099259744495, -0.03332018355269339, -0.03415005157532562, -0.03469082880824553, -0.0349398945249577, -0.03490202411227546, -0.03458944826558192, -0.03402171875638263, -0.033225382029684114, -0.03223346677837975, -0.031084796400591454, -0.029823141754119684, -0.028496233766068406, -0.027154659130476978, -0.025850665439008273, -0.02463690455982126, -0.023565144843915562, -0.022684983750118463, -0.0220425927117384, -0.02167952551129698, -0.021631620095789394, -0.02192802168405696, -0.022590352239093975, -0.02363204796788258, -0.02505788255184425, -0.026863689398178958, -0.029036291443597918, -0.03155364205338306, -0.034385175462353056, -0.037492360125131054, -0.0408294434058226, -0.04434437136329723, -0.04797986309293921, -0.051674615275027466, -0.055364609348170765, -0.058984491153670215, -0.06246899104745079, -0.06575435139675835, -0.06877972809677702, -0.0714885332657924, -0.07382968759481436, -0.07575875290758576, -0.07723891827977473, -0.07824181650453557, -0.07874815169233518, -0.07874812325897677, -0.07824163637868851, -0.07723829404178685, -0.07575717103572328, -0.0738263753383538, -0.07148240744736667, -0.06876933294763204, -0.06573778802280845, -0.062443841542044555, -0.05894774070209655, -0.05531256989878595, -0.05160285447475581, -0.047883142195972256, -0.04421659571919821, -0.04066362891817261, -0.03728061874858188, -0.03411872238166769, -0.03122282667276704, -0.028630653720848425, -0.026372042400703347, -0.02446842140701321, -0.022932484646589122, -0.021768074867849506, -0.02097027634703913, -0.02052571238357544, -0.02041303841665878, -0.020603616882971156, -0.021062355605593514, -0.021748687642673663, -0.022617667224555254, -0.023621153749622086, -0.02470905385553914, -0.025830590379823756, -0.0269355665989688, -0.027975594496523946, -0.02890525694595635, -0.029683175572881457, -0.030272958634113514, -0.030644006451473804, -0.03077215568451978, -0.03064014792297559, -0.03023791262030273, -0.029562659159824693, -0.028618777723911377, -0.027417553502242335, -0.025976703504982747, -0.024319749722335884, -0.02247524648146574, -0.02047588349266594, -0.018357489158251746, -0.016157961163513968, -0.013916153118804115, -0.011670747032584288, -0.009459141642870122, -0.007316386113923223, -0.005274187330629694, -0.0033600170280198836, -0.0015963423292228531, -1.4054791784244497e-17], [0.0, 0.0006774154348008294, 0.0012641256628124367, 0.001762857204179269, 0.002179491650953533, 0.002522890241183943, 0.0028046336937407306, 0.003038684088252938, 0.0032409776256858373, 0.0034289589320762657, 0.003621069124183686, 0.003836201101506779, 0.0040931364322503265, 0.004409978737992953, 0.004803598638779262, 0.005289105092468249, 0.005879357354417894, 0.0065845308105370965, 0.0074117486221574914, 0.00836478949745381, 0.009443880011473322, 0.010645577782242809, 0.011962749526577679, 0.013384645623136505, 0.014897070361882453, 0.016482644619797426, 0.01812115533371367, 0.0197899839021164, 0.021464603595250813, 0.023119134238822826, 0.02472694090716712, 0.026261262156127632, 0.027695852475234883, 0.02900562316548874, 0.03016726576623674, 0.03115984246568642, 0.03196532862812338, 0.03256909364092393, 0.032960307700694226, 0.033132263886443615, 0.03308260686690678, 0.03281346181047708, 0.032331459455614595, 0.03164765579869835, 0.03077734740392088, 0.0297397858734818, 0.028557797473752755, 0.02725731623375484, 0.025866840958964982, 0.02441682848358698, 0.02293903707139884, 0.021465835129673358, 0.020029491291134422, 0.018661462423019914, 0.01739169622709829, 0.016247964796736285, 0.015255244803518371, 0.01443515891286403, 0.013805491601282173, 0.013379790801735814, 0.013167064780297706, 0.013171581395908577, 0.013392774470245188, 0.01382525945537965, 0.01445895799478072, 0.01527932839128874, 0.01626769648674649, 0.017401679082951337, 0.018655689850167363, 0.0200015157305562, 0.02140895019647286, 0.022846468407405365, 0.024281928356025616, 0.025683281526078166, 0.02701927641589767, 0.028260138514663764, 0.029378210947663345, 0.030348541015708542, 0.031149399217061363, 0.03176271902365602, 0.032174447645226534, 0.03237480020647988, 0.03235841212949635, 0.03212438699766314, 0.031676239717443544, 0.031021737327704014, 0.030172642270981084, 0.02914436527662879, 0.0279555371551979, 0.026627510714343695, 0.025183805632719682, 0.023649510430514928, 0.022050656622459166, 0.020413580709040875, 0.018764289841533624, 0.017127846783098626, 0.01552778918835739, 0.013985597253649031, 0.012520222475081751, 0.011147688625377083, 0.00988077416496548, 0.008728783186009894, 0.007697409703627258, 0.006788697714204537, 0.006001096996674133, 0.0053296122003270805, 0.004766040403209706, 0.004299290097425018, 0.003915772517406819, 0.0035998544253075288, 0.0033343599488472055, 0.0031011078689400264, 0.002881469906671628, 0.0026569350824363143, 0.0024096651256013037, 0.002123026202666858, 0.0017820828976027275, 0.0013740414024724413, 0.0008886302332096567, 0.00031840843973976815, -0.00034100681067042194, -0.001090799281526405, -0.0019289030820290572, -0.0028500438195401185, -0.00384587046049072, -0.004905174496517112, -0.006014190724499502, -0.007156971805223879, -0.008315826820114064, -0.009471812348442113, -0.010605263181953133, -0.011696348715948554, -0.012725640333360494, -0.013674674750097489, -0.014526498325424207, -0.01526617776019261, -0.015881263398552253, -0.016362192496111653, -0.01670262129123575, -0.016899676479842255, -0.01695411870395468, -0.01687041287038117, -0.01665670246319908, -0.01632468744358101, -0.015889407782053142, -0.015368937080023284, -0.014783993048712956, -0.014157473766214597, -0.013513930572846434, -0.012878990142071653, -0.012278739636196336, -0.011739089887578547, -0.01128513221028627, -0.010940504726232422, -0.010726783975522734, -0.010662917074566316, -0.010764708798639687, -0.011044376718762712, -0.01151018594559731, -0.012166173163534891, -0.013011967521430804, -0.01404271363401952, -0.015249099496294384, -0.016617489582015612, -0.018130160849040695, -0.01976563687093567, -0.021499112917903282, -0.023302962579503168, -0.025147314512032216, -0.0270006861544903, -0.028830659831945184, -0.030604585589320665, -0.032290294399129664, -0.03385680508123272, -0.035275008369413725, -0.036518312056703583, -0.037563232037358105, -0.03838991531711552, -0.038982582654667836, -0.03932988038775228, -0.039425133141123066, -0.03926649145889285, -0.03885697089338395, -0.038204381656202026, -0.03732115053217924, -0.0362240393100479, -0.034933766433149493, -0.03347454085966306, -0.031873519189273114, -0.030160198911798494, -0.02836576211958902, -0.026522385163658378, -0.02466253049631529, -0.022818237312454203, -0.021020427569300653, -0.019298243531761034, -0.017678432168914304, -0.016184790537415564, -0.014837684759504923, -0.013653653375010852, -0.012645103763617256, -0.011820108047312839, -0.011182302449856315, -0.010730891570278511, -0.010460756482916634, -0.010362663069753947, -0.01042356458336773, -0.01062699018944651, -0.010953509201475461, -0.011381258946277313, -0.011886522730514146, -0.012444343250234474, -0.013029156024817008, -0.013615427060783166, -0.01417827896792121, -0.014694090158208543, -0.0151410525456673, -0.01549967431166317, -0.015753215775512197, -0.015888048176730233, -0.015893927187820657, -0.01576417518408378, -0.015495768643735973, -0.015089329478477045, -0.014549021540496565, -0.013882355955364464, -0.013099911231087327, -0.012214976234295285, -0.011243126051625254, -0.010201742419907829, -0.009109491771397924, -0.007985774966332994, -0.006850163449371655, -0.0057218368528917625, -0.004619036972158901, -0.003558552558133225, -0.0025552485258623285, -0.0016216519819784133, -0.0007676059644469579, -6.734692708291519e-18], [0.0, 6.016390498453092e-18, 1.1199603539593065e-17, 1.559017886370091e-17, 1.9257239773958414e-17, 2.229641500382736e-17, 2.4827004775959874e-17, 2.698846538686041e-17, 2.893630461065196e-17, 3.083749582828554e-17, 3.286553165683235e-17, 3.519524764745359e-17, 3.7997553087756365e-17, 4.143420891556367e-17, 4.5652792145524936e-17, 5.078198203627164e-17, 5.692729558255246e-17, 6.416738898991927e-17, 7.255102784784558e-17, 8.209481210556537e-17, 9.278172308596529e-17, 1.0456053911645112e-16, 1.1734614442743105e-16, 1.3102073331736546e-16, 1.454358887758467e-16, 1.6041549236559918e-16, 1.7575940075401702e-16, 1.9124780439503423e-16, 2.066461659959913e-16, 2.217106210156068e-16, 2.361937099212067e-16, 2.498503026083766e-16, 2.624435694977139e-16, 2.7375085152990506e-16, 2.835692826514096e-16, 2.9172102339711007e-16, 2.980579727213974e-16, 3.0246583710537373e-16, 3.0486745089220635e-16, 3.0522525941599246e-16, 3.035428963652688e-16, 2.9986580847706206e-16, 2.9428090356267246e-16, 2.869152214617249e-16, 2.779336512278022e-16, 2.675357410846177e-16, 2.5595166988421765e-16, 2.4343746940073696e-16, 2.302696052956126e-16, 2.1673904053459176e-16, 2.0314491802714803e-16, 1.8978800897105129e-16, 1.7696407957465293e-16, 1.6495733133931058e-16, 1.540340688464246e-16, 1.4443674403216401e-16, 1.363785173635895e-16, 1.3003846435674104e-16, 1.2555754078808754e-16, 1.230354021098244e-16, 1.2252815241884954e-16, 1.240470763377493e-16, 1.2755838387783712e-16, 1.3298397433503484e-16, 1.4020320110305183e-16, 1.4905559556234778e-16, 1.5934448549442017e-16, 1.7084142233063876e-16, 1.8329131248625824e-16, 1.9641813151518024e-16, 2.099310862489631e-16, 2.2353107978142134e-16, 2.369173273747041e-16, 2.4979396825429533e-16, 2.6187651889906223e-16, 2.7289801779647934e-16, 2.8261471960935865e-16, 2.908112080873077e-16, 2.973048115686948e-16, 3.0194922219599e-16, 3.0463723958028173e-16, 3.0530258111440633e-16, 3.039207239185041e-16, 3.005087669455144e-16, 2.9512432549809744e-16, 2.8786349373032164e-16, 2.7885793305584824e-16, 2.6827116521316107e-16, 2.562941675400706e-16, 2.4314038432789546e-16, 2.2904028156632382e-16, 2.1423558263093948e-16, 1.989733292645714e-16, 1.8349991540456888e-16, 1.680552409438985e-16, 1.5286712840866177e-16, 1.3814613790264096e-16, 1.2408090471248164e-16, 1.108341099689364e-16, 9.853917807906564e-17, 8.729777570621087e-17, 7.71781663590011e-17, 6.821445268091434e-17, 6.040671586156754e-17, 5.372203878969302e-17, 4.8096377207708497e-17, 4.343722176861894e-17, 3.962697407142171e-17, 3.652694195550878e-17, 3.398184401034608e-17, 3.1824700783905044e-17, 2.9881980859701285e-17, 2.797886404593146e-17, 2.5944481523801593e-17, 2.3616993989538237e-17, 2.0848373559498374e-17, 1.750876336479307e-17, 1.3490300129525488e-17, 8.710299313116926e-18, 3.1137192370004017e-18, -3.3251604201064076e-18, -1.0601889768671503e-17, -1.868185178365348e-17, -2.7501117306515213e-17, -3.6968129682605824e-17, -4.6966175019344706e-17, -5.735657344518147e-17, -6.798250778538264e-17, -7.867338923090749e-17, -8.924964529027302e-17, -9.952780394664636e-17, -1.0932573978542221e-16, -1.1846794312264457e-16, -1.267906719772626e-16, -1.3414684912663473e-16, -1.4041057241109954e-16, -1.4548111576707823e-16, -1.4928631094102754e-16, -1.517852151608098e-16, -1.5296998783677172e-16, -1.5286691918943775e-16, -1.5153657505993984e-16, -1.4907304451941572e-16, -1.4560229969486302e-16, -1.4127969989935888e-16, -1.3628669412435056e-16, -1.3082679666732126e-16, -1.2512092960630662e-16, -1.1940224251332203e-16, -1.1391053379700493e-16, -1.0888640902185886e-16, -1.0456531918355286e-16, -1.0117162602509316e-16, -9.89128419429748e-17, -9.797418883155621e-17, -9.851361341481103e-17, -1.0065738637370627e-16, -1.0449639913695013e-16, -1.1008325588476567e-16, -1.174302395137461e-16, -1.2650820948214049e-16, -1.372464671066015e-16, -1.4953360055967288e-16, -1.632192980934366e-16, -1.7811709447110303e-16, -1.9400799280407658e-16, -2.1064488252849912e-16, -2.2775765464239205e-16, -2.450588980476149e-16, -2.6225004632832853e-16, -2.79027832910902e-16, -2.9509090457410017e-16, -3.1014643891449566e-16, -3.2391661073347125e-16, -3.3614475542071383e-16, -3.4660108419471615e-16, -3.550878163630021e-16, -3.614436073370263e-16, -3.655471676518383e-16, -3.673199872993254e-16, -3.667281008242596e-16, -3.6378285134144313e-16, -3.585406353583237e-16, -3.511016344538965e-16, -3.416075638840738e-16, -3.3023849147211226e-16, -3.172088021342805e-16, -3.0276240355172945e-16, -2.871672863405625e-16, -2.7070956716134294e-16, -2.536871551825705e-16, -2.364031908821141e-16, -2.1915941113209424e-16, -2.022495957507732e-16, -1.8595324819525748e-16, -1.7052965687908454e-16, -1.5621247388679593e-16, -1.4320493486734258e-16, -1.3167582794392606e-16, -1.217563009755319e-16, -1.1353757590352572e-16, -1.07069616724223e-16, -1.023607743928061e-16, -9.937840825729028e-17, -9.805046002597119e-17, -9.826793336660629e-17, -9.988821058090013e-17, -1.027391179221826e-16, -1.0662363351093301e-16, -1.113251168785435e-16, -1.1661292729356846e-16, -1.2224828947971194e-16, -1.2799026032077797e-16, -1.33601648776847e-16, -1.3885474352946894e-16, -1.435367087622247e-16, -1.4745451780807485e-16, -1.5043930691291777e-16, -1.5235004675344262e-16, -1.5307644721352108e-16, -1.5254103081329106e-16, -1.507003315954054e-16, -1.4754519866356639e-16, -1.4310020637599505e-16, -1.3742219584823176e-16, -1.3059799434800529e-16, -1.2274137982135599e-16, -1.1398937665820492e-16, -1.044979854171933e-16, -9.443746317135435e-17, -8.398728206307215e-17, -7.333090130008761e-17, -6.265049199807375e-17, -5.212175488092305e-17, -4.19089678785978e-17, -3.2160394195314494e-17, -2.300417162688395e-17, -1.4544791037752306e-17, -6.860256295321934e-18, -5.999039130647426e-32]], \"z\": [[2.0, 2.130332796838008, 2.256753911784933, 2.376789638294702, 2.488075604138452, 2.588407808013885, 2.675789958185559, 2.7484760201951044, 2.805006995826015, 2.8442410940625464, 2.865376613357637, 2.867967029244015, 2.8519279679163567, 2.817535940324214, 2.7654189078139355, 2.696538944653189, 2.6121674501337298, 2.5138535388224583, 2.403386397651281, 2.2827525390293038, 2.154088996640754, 2.0196336022438546, 1.8816735454341926, 1.7424934524981004, 1.6043242244022853, 1.4692938476366197, 1.3393813357838407, 1.2163748757950643, 1.1018351431545763, 0.9970646172067862, 0.9030835752431645, 0.8206132753387548, 0.7500666576036418, 0.6915467059718643, 0.6448524225548543, 0.6094921786570255, 0.5847040254418049, 0.5694823774212108, 0.5626103276043474, 0.562696718068872, 0.568216977215646, 0.5775566477621683, 0.589056469720342, 0.6010578515962625, 0.6119475615298626, 0.6202004980084016, 0.6244194563522353, 0.6233708908814289, 0.616015781348306, 0.6015348430632947, 0.5793474697981014, 0.5491239632035355, 0.5107907779410832, 0.4645286935439924, 0.4107640075879514, 0.35015302541788323, 0.28356029487838363, 0.21203119585578453, 0.13675963988628234, 0.05905176094738821, -0.019713418345185477, -0.09812528316559538, -0.17478377313093832, -0.2483412449370153, -0.3175429240306221, -0.3812648546229005, -0.43854832164009483, -0.4886298089205054, -0.5309656728128324, -0.5652508464155105, -0.5914310435863067, -0.6097080996627086, -0.6205382633289118, -0.6246234367591293, -0.6228955444384521, -0.6164943902707143, -0.606739533182977, -0.5950968690939954, -0.5831407478136716, -0.5725125735862396, -0.564876934495972, -0.5618763763227153, -0.5650859788187031, -0.5759689056289827, -0.5958340827741818, -0.6257971150739303, -0.6667454761620001, -0.7193089075868944, -0.7838358383252534, -0.860376490885721, -0.9486731776038657, -1.0481581147228927, -1.157958896762308, -1.2769115840757097, -1.4035811670905025, -1.536288986213304, -1.6731465113714492, -1.8120947240139385, -1.9509482011513046, -2.0874428792756796, -2.2192863788470563, -2.3442096999359485, -2.4600190583883133, -2.5646466206285163, -2.656198914305576, -2.733001741033373, -2.793640495355376, -2.8369948989436145, -2.8622672884173284, -2.8690037459293434, -2.8571075301766835, -2.8268444476640338, -2.778839995460327, -2.714068302683439, -2.633833093751007, -2.5397410872713246, -2.433668425658943, -2.3177208977183823, -2.194188865460708, -2.0654979336576758, -1.9341565029841026, -1.8027014225470428, -1.673643003315771, -1.5494106693307361, -1.432300508206476, -1.3244259367287958, -1.2276726223996803, -1.143658699438247, -1.0737011905070444, -1.0187893964125891, -0.9795658488710625, -0.9563152402204208, -0.9489615531250435, -0.9570734175169213, -0.9798775260235782, -1.0162797477220724, -1.0648933978872752, -1.1240739528948953, -1.191959348678073, -1.2665148717614474, -1.3455815470181587, -1.426926848416447, -1.5082965099775545, -1.5874661950782214, -1.662291793481848, -1.7307571567074012, -1.791018152441967, -1.8414420158585025, -1.880641097439626, -1.9075002501526428, -1.9211972599688287, -1.9212158987340744, -1.9073513629076277, -1.8797080510947568, -1.8386898229007402, -1.7849830667268025, -1.7195330801350512, -1.643514428987137, -1.558296096711596, -1.4654023592217986, -1.3664704211642016, -1.2632059229044617, -1.1573374731997923, -1.0505713788099913, -0.9445477290492286, -0.8407989508968838, -0.7407118799175634, -0.645494295734913, -0.5561467506582967, -0.47344037936217304, -0.39790121986060634, -0.3298014054193769, -0.2691574078403067, -0.21573532928103656, -0.16906305707992222, -0.1284489185605246, -0.09300630497914189, -0.06168357988930772, -0.03329845111287882, -0.006575870661041266, 0.019811563763794626, 0.04720179634599987, 0.07690121672611482, 0.11014341376919395, 0.14804989189739776, 0.19159381192176567, 0.24156774056072752, 0.29855628972809545, 0.3629144008106004, 0.43475188370873713, 0.5139246590543266, 0.60003297881744, 0.6924267198491046, 0.7902176613420437, 0.8922984753753752, 0.9973679842477005, 1.1039620736499134, 1.210489501072855, 1.3152717080029064, 1.4165856357825461, 1.5127084613030342, 1.601963112132467, 1.682763392766697, 1.7536575552108429, 1.8133691781075414, 1.8608342784386231, 1.8952336670319472, 1.9160196716095936, 1.922936486185448, 1.916033559958485, 1.895671608663898, 1.8625210124541185, 1.8175525523118523, 1.762020627093329, 1.6974392808435306, 1.6255515503499745, 1.5482928115106325, 1.4677489557673422, 1.3861103607672236, 1.3056227292110403, 1.2285359537427785, 1.1570522215788412, 1.0932745989052495, 1.0391573311513418, 0.9964590610873105, 0.9667001030453637, 0.9511248199133455, 0.9506700320705619, 0.9659402469434338, 0.9971903377389502, 1.0443161240403631, 1.1068531195884053, 1.1839835182767917, 1.2745512928931142, 1.3770850872253881, 1.489828395561497, 1.61077634889063, 1.7377182685412587, 1.868285009436098, 1.9999999999999987], [2.0918833918127375, 2.220837794218755, 2.344259914887943, 2.4597370308582525, 2.5649977042183587, 2.657960734972634, 2.736779746720657, 2.7998823772730286, 2.8460031757078474, 2.8742094582391693, 2.883919543933573, 2.8749129736538097, 2.84733250717748, 2.801677889559804, 2.738791573701678, 2.659836776976977, 2.5662684310239836, 2.45979775101499, 2.342351299835696, 2.216025550032304, 2.083038049057366, 1.9456763688167729, 1.8062460670136273, 1.6670189042397519, 1.5301825468628176, 1.3977929419250008, 1.2717304776725906, 1.153660943846501, 1.0450021820120727, 0.9468971711194766, 0.8601941308079342, 0.7854340487687614, 0.7228458531603885, 0.6723492612351014, 0.6335651457058452, 0.6058330756495923, 0.5882355134769512, 0.5796279880157202, 0.5786744200266037, 0.5838866540094944, 0.5936671519486121, 0.6063537330539815, 0.6202652002862374, 0.6337466804926718, 0.64521352059225, 0.6531926269444629, 0.6563602076137602, 0.653574975795335, 0.6439059946500445, 0.6266544860748317, 0.6013690848754866, 0.5678541913642802, 0.5261712552189497, 0.4766330069535959, 0.4197908359212798, 0.3564156907769306, 0.28747304530691586, 0.2140926252644645, 0.13753372648628756, 0.05914706771198671, -0.019665789665915007, -0.09749436046273734, -0.17296136462471862, -0.24476393257263826, -0.31171277735275166, -0.372768276523337, -0.42707248643245793, -0.47397621644282223, -0.5130604180851722, -0.5441512908558708, -0.5673286687122783, -0.5829274251605023, -0.5915318157803515, -0.5939628605148796, -0.5912590494212142, -0.5846508302376766, -0.5755294996345505, -0.5654112682216883, -0.5558973985031683, -0.5486314216890218, -0.5452545208449177, -0.5473602221573614, -0.5564495616693248, -0.5738878909713407, -0.6008644520243276, -0.6383557892880606, -0.6870939780981391, -0.7475405339230612, -0.819866730521655, -0.9039408994523177, -0.9993231126826086, -1.1052674684198744, -1.220732012221685, -1.3443961356102592, -1.474685107524109, -1.6098012146463725, -1.7477608194289307, -1.886436493670522, -2.0236032545983598, -2.1569878228507164, -2.284319740295273, -2.403383132338803, -2.512067875688849, -2.608418939090664, -2.6906827013106405, -2.7573491167528177, -2.807188693035342, -2.8392833643872937, -2.853050486987476, -2.848259343926195, -2.8250397244187306, -2.7838823299415156, -2.7256309545263067, -2.651466582795429, -2.5628837426642175, -2.4616596352554474, -2.349816737929789, -2.229579733197622, -2.103327752803413, -1.9735430391224216, -1.8427572124169354, -1.7134963903483176, -1.588226434012619, -1.4692995919764495, -1.3589037804013322, -1.2590156741729583, -1.1713586925401287, -1.0973668453503873, -1.0381552654154858, -0.9944980922846803, -0.9668141966626702, -0.9551610471810107, -0.9592368267939514, -0.9783907094641843, -1.0116410138213918, -1.0577007638377283, -1.1150100118046549, -1.1817741202526957, -1.2560070607663636, -1.3355786722516485, -1.4182647318766854, -1.5017986307467535, -1.583923414814642, -1.6624429502590161, -1.7352710015317103, -1.8004770686805165, -1.8563279168743896, -1.901323843084283, -1.9342288597682933, -1.954094129777405, -1.9602741566687676, -1.9524354159397732, -1.9305573008601167, -1.8949254469030181, -1.8461176865406583, -1.7849830667268023, -1.7126145302849034, -1.6303160154963268, -1.5395648616864643, -1.441970519277953, -1.3392306479367173, -1.2330857440368235, -1.12527346736373, -1.017483836136462, -0.9113164291702436, -0.8082406751691188, -0.7095602232934435, -0.6163822785229086, -0.5295926527807725, -0.44983713169350487, -0.37750959108457866, -0.3127471210567257, -0.2554322332753898, -0.20520204344309292, -0.16146414059516978, -0.1234186823087993, -0.0900860945557176, -0.06033961078971068, -0.032941760576841804, -0.006583816780878787, 0.0200728654406756, 0.04835473288687367, 0.07953427652001971, 0.11478975684083488, 0.15516749923759224, 0.2015477797705843, 0.2546152292469411, 0.3148345669097035, 0.3824323375506611, 0.45738517083040464, 0.5394149129662515, 0.6279908029900343, 0.7223386829824179, 0.82145704868419, 0.9241395683043047, 1.0290035277196263, 1.1345235039036579, 1.2390694293153024, 1.3409480916799654, 1.4384470191441758, 1.5298796326271675, 1.6136305071199197, 1.6881995727835926, 1.7522441053363136, 1.804617403012155, 1.8444031232201934, 1.8709443541126192, 1.8838666221172171, 1.8830941830301022, 1.8688591079053616, 1.841702851690574, 1.8024701779773369, 1.7522955027736227, 1.69258190915661, 1.6249732683309532, 1.551320076419011, 1.473639775902057, 1.3940724720125741, 1.3148330739878562, 1.2381609859065619, 1.1662685394207637, 1.1012893993143662, 1.045228181423282, 0.9999125007424896, 0.9669486159660428, 0.9476817564420484, 0.9431621104686054, 0.9541173225648276, 0.9809321949808277, 1.023636118942719, 1.0818985780778492, 1.1550328745784189, 1.2420080326082963, 1.3414686380162626, 1.4517621833579633, 1.5709733071896912, 1.6969641509808426, 1.8274199098483423, 1.9598985282465429, 2.091883391812736], [2.1829894085530297, 2.3094685569379836, 2.428829939403708, 2.538742241419929, 2.6370461969756547, 2.721801043522426, 2.7913259774585035, 2.844235656054852, 2.879468934248715, 2.8963101866331558, 2.894402742298232, 2.8737541486032225, 2.834733174882783, 2.77805866376104, 2.704780531376074, 2.6162534036922818, 2.5141035496845547, 2.400189929307395, 2.276560311015218, 2.1454035268815415, 2.0089990203625434, 1.8696649004027999, 1.7297057445260262, 1.5913613921625183, 1.4567579378563213, 1.3278620730311892, 1.2064398362587938, 1.0940207177302674, 0.9918679267723209, 0.9009554752131078, 0.8219525580982149, 0.7552155309596845, 0.7007875940894032, 0.6584061037503197, 0.6275172426959509, 0.6072976023973184, 0.5966820614349793, 0.5943971927312728, 0.5989993003926866, 0.6089160781199926, 0.6224907980583378, 0.6380278835881509, 0.6538386931928818, 0.6682863457474187, 0.6798284501784133, 0.6870566635477483, 0.6887320895856365, 0.6838156422639579, 0.671492633255929, 0.6511909946393347, 0.62259271508014, 0.5856382447399439, 0.5405238067955586, 0.4876917371178798, 0.42781415368673154, 0.36177042917200497, 0.2906190994531743, 0.21556498366231455, 0.13792241402250993, 0.059075573225947434, -0.019562989147715384, -0.09659454348462022, -0.1706759351124881, -0.2405597839486633, -0.30513204592780224, -0.3634459217044302, -0.41475119261385907, -0.4585181820755601, -0.49445567954971936, -0.5225223203003114, -0.5429310836307727, -0.5561467506582961, -0.5628763455670633, -0.5640527669995951, -0.5608119941780267, -0.5544644209778413, -0.5464610262177475, -0.5383552259294035, -0.5317613698127228, -0.5283109364734655, -0.5296075479853862, -0.537181962084659, -0.5524482088584856, -0.5766620178318785, -0.6108826313244948, -0.6559390220096871, -0.7124014286279744, -0.7805589963091454, -0.8604041600566134, -0.9516242452759796, -1.053600581845209, -1.1654152425106175, -1.2858653269527132, -1.4134845244038454, -1.5465715049072388, -1.6832245167454407, -1.8213814095535736, -1.9588641631352728, -2.093426884533214, -2.222806143450172, -2.3447724510357224, -2.45718165104181, -2.558024986385399, -2.6454766284761893, -2.7179375107629595, -2.774074390577994, -2.8128531725650086, -2.8335656601525474, -2.8358490554779285, -2.819697699156186, -2.7854667251782947, -2.7338674985445492, -2.665954899309792, -2.583106711756814, -2.4869955666616175, -2.379554063445153, -2.2629338630472775, -2.13945968759543, -2.011579285815753, -1.8818105206369133, -1.7526868051747038, -1.6267021535462982, -1.5062571227548192, -1.393606900962124, -1.2908127463365513, -1.1996979005677773, -1.121808994037991, -1.0583838281415754, -1.0103262675658762, -0.9781888052116776, -0.9621631789969062, -0.9620792275274342, -0.9774119752232351, -1.0072967417426861, -1.0505518802176632, -1.1057085685244135, -1.1710469119454991, -1.2446374681422903, -1.3243871799139029, -1.408088600779961, -1.493471225385283, -1.5782536928019295, -1.6601956169957468, -1.7371478152869253, -1.8070997520747962, -1.8682230901892278, -1.9189103440445812, -1.957807754721301, -1.9838416540106059, -1.9962377486425904, -1.9945329332734698, -1.978579426912216, -1.9485412176930432, -1.9048829905289129, -1.8483518965188237, -1.7799526974766566, -1.700916979304661, -1.6126672702145666, -1.5167770205258477, -1.4149274970102697, -1.308862714186609, -1.2003435659548072, -1.0911023325624138, -0.9827987199211321, -0.8769785412796217, -0.7750360764762715, -0.678181043400779, -0.5874109924864116, -0.5034897912118406, -0.42693270538606537, -0.35799841149892564, -0.296688094021943, -0.24275159781077066, -0.19570042333939783, -0.15482717599723836, -0.11923091455811669, -0.08784769237483862, -0.05948545168347185, -0.032862319970965, -0.006647270472054828, 0.020497951299412273, 0.04987676500377052, 0.08271668982181998, 0.1201303823907042, 0.16307983038008178, 0.21234467206267044, 0.2684955055514235, 0.3318729224040923, 0.40257285229324985, 0.4804386421456262, 0.5650601186959985, 0.6557797021899248, 0.7517054555917129, 0.8517307727540591, 0.9545602351716648, 1.0587410045880712, 1.162698971985586, 1.2647787561088055, 1.3632865399176661, 1.456534653938841, 1.542886763455366, 1.6208024932314187, 1.6888803296800317, 1.7458976759776408, 1.790846999806345, 1.8229671046406726, 1.841768671589063, 1.8470533569238434, 1.8389258872029461, 1.8177987654453964, 1.784389383936371, 1.7397095273992635, 1.6850474398139712, 1.621942814369544, 1.5521552442745188, 1.4776268379561324, 1.400439851405387, 1.3227703193151579, 1.2468387719556968, 1.1748592037561367, 1.1089875102752245, 1.0512706313103235, 1.0035976286999644, 0.967653888058279, 0.9448795651190741, 0.9364333011658393, 0.9431621104686051, 0.9655781986547369, 1.0038433079814901, 1.0577610074984842, 1.1267771574087866, 1.2099885821478111, 1.3061597905457445, 1.4137473887072767, 1.5309316466393121, 1.6556545076953069, 1.7856631747916096, 1.9185582728835868, 2.0518454766619594, 2.1829894085530284], [2.272547252093312, 2.395475228637213, 2.5097484846564537, 2.613136850148115, 2.7036115195592982, 2.779388615764862, 2.838967164604605, 2.8811606077319922, 2.905121135987933, 2.9103562970815986, 2.896737515849748, 2.8645003582765565, 2.8142365670847402, 2.746878092266002, 2.6636735296453704, 2.5661575598587927, 2.456114144616453, 2.335534382844167, 2.2065700527260295, 2.0714839638497002, 1.932598314242087, 1.7922422884202986, 1.6527001437345248, 1.5161610130539875, 1.3846716028000066, 1.2600928877501059, 1.1440617999131628, 1.0379587807468165, 0.9428819172781738, 0.8596282170239027, 0.7886823981236395, 0.730213384246224, 0.684078503243902, 0.649835198939191, 0.6267598815213422, 0.6138733683412121, 0.6099722076980576, 0.6136650374128337, 0.6234130110175856, 0.6375732301464483, 0.6544440544558867, 0.6723111217184403, 0.689492901498106, 0.7043846261630713, 0.7154994923206189, 0.7215061027449428, 0.7212612214979381, 0.7138370405649155, 0.6985423017202573, 0.6749367787914514, 0.6428387988967282, 0.6023256621915927, 0.553727003589968, 0.49761132217552156, 0.4347660799854183, 0.3661719370932371, 0.29297184027547574, 0.21643581423103922, 0.13792241402250996, 0.05883788236497389, -0.01940588652948835, -0.09543344509005072, -0.1679468203620889, -0.23576436806484827, -0.29785640572144384, -0.3533766615063617, -0.4016886839054525, -0.44238648778430645, -0.4753088617132238, -0.500546925626953, -0.5184447029516129, -0.5295926527807719, -0.5348142909338, -0.5351462091388869, -0.5318119745736964, -0.5261905531730526, -0.5197800453713085, -0.5141576485779327, -0.510936863466734, -0.511723038439619, -0.5180683963881052, -0.5314277087905385, -0.5531157736415983, -0.5842678158420489, -0.6258038623445265, -0.6783980511334811, -0.7424537152682716, -0.8180849436123362, -0.9051051619328666, -1.003023105674078, -1.1110463731417166, -1.2280925596091357, -1.3528077836396069, -1.4835922314244223, -1.6186321677890647, -1.7559376981503274, -1.893385418239226, -2.0287649615506247, -2.159828351451066, -2.2843409882986463, -2.400133053780376, -2.505150096232634, -2.597501572525641, -2.6755061639640956, -2.7377327546416232, -2.7830360591240675, -2.8105860098843487, -2.819890160604493, -2.8108085257829933, -2.783560456058362, -2.738723337935936, -2.677223101578724, -2.600316716241639, -2.509567045009775, -2.4068106140519805, -2.2941190221311487, -2.1737548694478646, -2.048123217277387, -1.9197196980450977, -1.7910764768169762, -1.6647073176600016, -1.5430530306591737, -1.4284285670071482, -1.3229729907050733, -1.2286034869718656, -1.1469744711195502, -1.0794427397640904, -1.0270394617774137, -0.9904496428727886, -0.9699995191422555, -0.9656521455878322, -0.9770112503234488, -1.0033332284328342, -1.0435469562392217, -1.0962809216753113, -1.1598969940306996, -1.23253000077763, -1.3121321441945437, -1.3965211793703465, -1.4834311905399176, -1.570564746577542, -1.655645190160678, -1.7364678191768514, -1.8109487531994768, -1.877170341378631, -1.9334220592361473, -1.9782359582998112, -2.0104158713178464, -2.0290597334772293, -2.0335745526623934, -2.023683745030586, -1.9994267414882763, -1.961150961332185, -1.9094964366475267, -1.8453735504078292, -1.7699345181764892, -1.6845393937688193, -1.5907175095130888, -1.4901253686775806, -1.3845020886242398, -1.2756235463750492, -1.1652564023009913, -1.0551131720588778, -0.9468094819423772, -0.8418245794469894, -0.7414660807485353, -0.6468398223007028, -0.5588255478149473, -0.47805900797205364, -0.40492088225078654, -0.33953275451185116, -0.28176019095053595, -0.2312227853605332, -0.18731085697556063, -0.1492083150098872, -0.11592104571863401, -0.08631003633184367, -0.05912832914314143, -0.03306080139872141, -0.006765694887628913, 0.021083224921286194, 0.05175501561625411, 0.086421531974924, 0.12612010630998943, 0.1717199434230302, 0.2238931422035835, 0.28309113605574215, 0.3495272040138354, 0.42316554716995763, 0.5037172548552601, 0.5906433061985055, 0.6831645697552597, 0.7802785814920987, 0.8807827041470035, 0.9833031033702487, 1.0863288223423666, 1.1882501006861794, 1.2873999689150883, 1.3820980593356542, 1.4706955105914312, 1.5516198075750296, 1.6234183922191003, 1.6847999039446249, 1.7346719607989902, 1.7721744723324122, 1.7967075811171533, 1.8079534589375748, 1.8058913329112012, 1.7908052824730591, 1.76328452618087, 1.7242161032731298, 1.674770044223307, 1.6163773124756327, 1.550700981438585, 1.4796012821082765, 1.4050953131053054, 1.3293123425052082, 1.2544457461515057, 1.1827027172337097, 1.1162529444811402, 1.0571774897326933, 1.007419098977778, 0.9687351540493762, 0.9426544155592067, 0.9304386227029291, 0.9330499042383571, 0.9511248199133447, 0.9849556961424637, 1.0344797475620395, 1.0992762914073757, 1.178572168944247, 1.2712552921428029, 1.3758960391879835, 1.490776034028802, 1.613923667585484, 1.7431555558033864, 1.8761229864447255, 2.0103622858551344, 2.1433479418922845, 2.2725472520933105], [2.3597992225518465, 2.4781301539554037, 2.5863309431372823, 2.682291444989025, 2.7641304992190805, 2.830236234780097, 2.879300242157822, 2.9103448305045294, 2.9227427516910347, 2.9162289531341665, 2.8909041113473775, 2.847229893927362, 2.786016094360144, 2.708399976818907, 2.6158183523453395, 2.50997307898397, 2.3927908324270595, 2.266378126805352, 2.1329726742242108, 1.9948922538890148, 1.8544823152414904, 1.714063563200774, 1.5758807668672508, 1.442053996149978, 1.3145334247078873, 1.1950587440551341, 1.0851241150495652, 0.9859494422513438, 0.898458597336374, 0.8232650438569397, 0.7606651314925121, 0.7106391381031758, 0.672859947093388, 0.6467090605347959, 0.6312994698002663, 0.62550473952582, 0.6279935116149408, 0.6372685073755978, 0.6517090008620842, 0.6696156576152085, 0.689256582133122, 0.7089133957369257, 0.7269261744659349, 0.7417361139526547, 0.7519248538610134, 0.7562494866918889, 0.7536723921750873, 0.7433851760837439, 0.7248261476077067, 0.697690938452165, 0.6619360452947056, 0.6177752606164428, 0.5656691405827825, 0.5063078379482703, 0.44058779837507034, 0.3695829757919084, 0.2945113625218362, 0.21669774934997169, 0.13753372648628756, 0.05843600610130626, -0.019195810970473848, -0.09402088869684994, -0.16479710991924795, -0.23041825630952067, -0.289947411942087, -0.3426456864267993, -0.38799547504176396, -0.42571761500244015, -0.45578195531861637, -0.4784110286187119, -0.4940766925355581, -0.50348979121184, -0.5075830695609833, -0.5074877494926232, -0.5045043438967347, -0.5000684365390099, -0.49571229026647595, -0.4930232586211977, -0.49360006421208524, -0.49900806871095765, -0.5107346924971131, -0.5301461458616972, -0.5584466081185209, -0.5966409365090232, -0.6455019047180588, -0.7055428631102285, -0.7769965820752393, -0.8598008893377637, -0.9535915454471077, -1.0577026230293955, -1.1711744691832457, -1.292769141250966, -1.4209930188069884, -1.5541261137464966, -1.6902574303537843, -1.827325572443257, -1.9631636589902222, -2.0955474965315113, -2.222245868894784, -2.3410717447638856, -2.4499331727790556, -2.5468826331589915, -2.630163644327469, -2.6982534820956348, -2.7499009562259698, -2.7841583026199377, -2.800406386215544, -2.79837256665754, -2.7781407521148576, -2.74015335206162, -2.685205032899347, -2.614428376274251, -2.52927173405222, -2.4314697614120715, -2.3230072858184894, -2.2060773304227497, -2.0830342517713545, -1.9563430701126086, -1.828526163170924, -1.7021085587309501, -1.5795630961483749, -1.4632567311182267, -1.355399231569055, -1.2579954560482818, -1.172802320791511, -1.1012914498990338, -1.0446183674005323, -1.0035989337808309, -0.9786935565754018, -0.9699995191422552, -0.977251578199313, -0.9998307838993826, -1.0367812808910952, -1.0868346597357414, -1.1484412498109775, -1.2198075817562606, -1.2989391035481128, -1.383687112908365, -1.4717987728592852, -1.560969009129239, -1.64889304937896, -1.7333183557352918, -1.8120947240139385, -1.8832213746666242, -1.9448899405504005, -1.9955223630402679, -2.0338028380983335, -2.058703104402068, -2.0695005327544607, -2.065788655579711, -2.047479962881758, -2.014800981953123, -1.968279847640381, -1.9087267534170878, -1.8372078463634915, -1.7550132871564572, -1.6636203354619536, -1.5646524382998077, -1.4598353911763098, -1.3509517068424644, -1.2397943629026187, -1.1281211063570091, -1.0176104704362627, -0.9098206074388134, -0.8061519620967998, -0.7078147053403633, -0.6158017209057859, -0.5308677903054976, -0.4535154589951811, -0.38398789227185653, -0.32226884793727106, -0.26808970865744164, -0.22094333489485332, -0.18010432387934147, -0.14465509573963287, -0.1135170787784661, -0.08548613569265383, -0.05927126458701042, -0.03353552561741835, -0.006938088103457627, 0.02182373462661697, 0.05397359387422474, 0.09061745833825625, 0.13270825282395243, 0.18101473910039848, 0.23609548491018906, 0.29827863512123237, 0.367648048527861, 0.44403619866382665, 0.5270240613620905, 0.615948030130977, 0.7099137173146427, 0.8078163191089712, 0.9083670503772899, 1.0101249952288003, 1.111533575560681, 1.2109607158946143, 1.3067416820375939, 1.3972234959673442, 1.4808097818468042, 1.5560048794811583, 1.62145607239382, 1.6759928178255068, 1.7186619344304679, 1.7487577986222003, 1.7658467201012138, 1.7697848081587442, 1.760728799428466, 1.7391394909312778, 1.7057776052439344, 1.6616921028839813, 1.6082011458625873, 1.5468661011094762, 1.4794591485076263, 1.4079252211831947, 1.3343391513876575, 1.2608590201123808, 1.1896768093278043, 1.122967529866739, 1.0628380435546738, 1.0112768140112618, 0.9701058061233075, 0.9409357097825108, 0.9251255900950053, 0.9237479656250493, 0.9375601907286132, 0.9669828706777547, 1.012085872630844, 1.0725823155804766, 1.1478307325816446, 1.2368454034491303, 1.338314660473335, 1.4506267783154885, 1.5719028767855594, 1.700036096144956, 1.8327361530522597, 1.9675782550000736, 2.102055245271456, 2.233631771676332, 2.359799222551845], [2.444007128776587, 2.556734034822584, 2.6579293925934877, 2.7456209467774944, 2.8180911180019272, 2.873913706702452, 2.9119839740311284, 2.9315414126417965, 2.9321846945152994, 2.913878469463248, 2.8769518820328566, 2.822088871499008, 2.750310514678155, 2.6629498596879833, 2.561619875930654, 2.448175307199781, 2.3246693569916226, 2.193306254410603, 2.0563908426350803, 1.916276397523896, 1.775311920060191, 1.635790152135859, 1.4998975406136668, 1.3696673203473053, 1.2469368043045117, 1.1333098602302203, 1.0301254211515538, 0.9384327247820163, 0.8589738083354108, 0.7921736046117341, 0.7381377969584899, 0.6966583995103579, 0.6672268396993492, 0.6490541370826299, 0.6410976005616964, 0.642093309287665, 0.650593504799759, 0.6650079065829881, 0.6836478730480163, 0.7047722670905237, 0.7266338513530456, 0.7475250338426926, 0.7658218096683111, 0.7800247986277283, 0.7887963597583008, 0.790992870638835, 0.7856913884469334, 0.7722100582232699, 0.7501217976884933, 0.7192609631343712, 0.6797228829279425, 0.6318563294207975, 0.5762491818911644, 0.5137077079774701, 0.4452300544837539, 0.3719746863371155, 0.2952246411374097, 0.21634857292947876, 0.13675963988628237, 0.05787334448998626, -0.018934539804961417, -0.09236882517129338, -0.16125345175957181, -0.2245666792072737, -0.28147197825596565, -0.33134378537073783, -0.373787416766028, -0.4086525899364469, -0.4360401668300213, -0.45630190898088524, -0.47003321677737847, -0.47805900797205314, -0.4814130699036955, -0.4813113911450073, -0.4791201370595123, -0.47631907600283, -0.47446138500222007, -0.47513086256165316, -0.47989764921546224, -0.4902736016849757, -0.5076684827658666, -0.5333481159004273, -0.5683956110173489, -0.6136766976330579, -0.6698101040931461, -0.7371438005474388, -0.8157377807648647, -0.9053538977079099, -1.0054530938544672, -1.1152001838823422, -1.233476159069011, -1.358897794288932, -1.4898441545111702, -1.6244894228086777, -1.7608413104692993, -1.8967841659043307, -2.0301257763147946, -2.158646757612553, -2.2801513564225466, -2.392518444975234, -2.4937514764902216, -2.5820261856742976, -2.655734865883684, -2.7135261302661364, -2.7543391670244204, -2.7774316263778087, -2.782400425781164, -2.7691949268933036, -2.7381221186210905, -2.6898436309077107, -2.6253645991464487, -2.5460145944221444, -2.4534210254390785, -2.3494755993223637, -2.236294596039437, -2.116173860871128, -1.9915395474948394, -1.8648957476770982, -1.7387702197638129, -1.615659475224285, -1.4979744992820119, -1.3879883677258114, -1.2877869776644966, -1.199224036337615, -1.1238813509116896, -1.0630353359375562, -1.0176305068957208, -0.9882605616256377, -0.9751574704834813, -0.9781888052116768, -0.9968633403826525, -1.0303447646752262, -1.0774731469388041, -1.1367936186727554, -1.2065915646458163, -1.2849334610190892, -1.3697123691970474, -1.4586969868694417, -1.5495830778763036, -1.6400460515163962, -1.7277934409038755, -1.810616039397502, -1.8864364936705222, -1.9533542206070214, -2.009685611137644, -2.0539986049306984, -2.0851408624927523, -2.1022609221318502, -2.104821904380744, -2.0926075115068143, -2.065720260056054, -2.0245720752755005, -1.9698675630136064, -1.9025804527060108, -1.8239238699370484, -1.735315244782925, -1.6383367890833218, -1.534692578871767, -1.4261633549380668, -1.314560203076537, -1.2016782948743847, -1.0892518595304603, -0.978911517520462, -0.8721450390263977, -0.770262495713879, -0.6743666561151298, -0.5853293355987301, -0.503774255237622, -0.43006679381164975, -0.36431083801678293, -0.30635275223681313, -0.2557923056088235, -0.21200021521617518, -0.17414179458172788, -0.14120604048185695, -0.11203935238573415, -0.0853829610294959, -0.05991304871654462, -0.03428247624535049, -0.0071629915949262424, 0.022713215368213045, 0.05651372960170185, 0.09526896947610465, 0.13983908323191474, 0.190885579234813, 0.24884846284156614, 0.3139295096333784, 0.3860821454018047, 0.46500823161914123, 0.5501618755366195, 0.6407602010784264, 0.7358008349755939, 0.8340856867211235, 0.9342504353937515, 1.0347989854051518, 1.1341420206255066, 1.230638675529556, 1.3226402558310812, 1.4085348817744934, 1.48679189639338, 1.556004879481158, 1.6149321358692603, 1.6625335832564974, 1.698003048939771, 1.7207950943314634, 1.7306456184417482, 1.7275856433096721, 1.7119478519451805, 1.6843656285530837, 1.6457645372078948, 1.5973463641046506, 1.5405660353200064, 1.4771019020178413, 1.4088200537205606, 1.3377334734084876, 1.2659569819488483, 1.1956590303098298, 1.1290114833578597, 1.06813859657039, 1.0150664152090938, 0.9716738235978255, 0.9396464400889186, 0.9204344917772584, 0.9152157134609858, 0.9248641998718707, 0.949926001571972, 0.9906020964765182, 1.0467391945502418, 1.117828647069757, 1.2030135384778204, 1.3011038429905861, 1.41059933453862, 1.5297197520591945, 1.656441547177511, 1.7885403822057973, 1.9236384070535184, 2.059255227501694, 2.1928613872043523, 2.32193312396023, 2.444007128776586], [2.524458533776361, 2.630621846837956, 2.7239380777440023, 2.8025895592714662, 2.8650368446554793, 2.910051500355182, 2.9367418410633195, 2.9445710214673495, 2.9333670813519057, 2.9033247322243043, 2.8549988700796414, 2.7892899954176813, 2.7074219133998416, 2.610912269430571, 2.5015366440368725, 2.3812870816193317, 2.252326056817644, 2.116936986765778, 1.9774724749075572, 1.8363015204732738, 1.6957569460664352, 1.558084283702286, 1.4253933174506794, 1.299613409678604, 1.182453639586311, 1.075368659774211, 0.9795310320566982, 0.8958106412701834, 0.8247616094573028, 0.7666169469333376, 0.7212909859654656, 0.6883894518426217, 0.667226839699349, 0.6568505881739387, 0.6560713771856861, 0.6634987308201482, 0.677580981083555, 0.6966485471654891, 0.7189594102641848, 0.7427456177476853, 0.7662596335046504, 0.7878193641054009, 0.8058507324309474, 0.8189267405901136, 0.8258020603880434, 0.8254423098360295, 0.8170473151162555, 0.8000678154371856, 0.7742152393165216, 0.7394643606687112, 0.6960488271014259, 0.6444497363908154, 0.5853776155781214, 0.5197483260141949, 0.4486535727241446, 0.3733268337753846, 0.2951056414623462, 0.21539123916008207, 0.13560670334540853, 0.05715465790285293, -0.018624283505237843, -0.09049123171837455, -0.15734582683461504, -0.21825914374826116, -0.2725018106672418, -0.31956657753528, -0.35918471568047705, -0.3913357904203966, -0.4162505207113131, -0.4344066198700999, -0.44651769436178523, -0.4535154589951806, -0.4565257020010972, -0.45683859793259707, -0.45587411593835675, -0.4551434019013571, -0.45620712185322077, -0.46063183816636455, -0.46994554710814995, -0.4855935349051042, -0.508895708716168, -0.541006528791293, -0.582878609271583, -0.6352309689662735, -0.6985228021034893, -0.7729335052148056, -0.8583495432656411, -0.9543585696589919, -1.0602510349878007, -1.1750293328501593, -1.2974243423107434, -1.4259190403947755, -1.5587786789886011, -1.6940868531765385, -1.8297866365702624, -1.9637258274024951, -2.093705240399673, -2.2175288964922633, -2.333054907407335, -2.4382458265690055, -2.531217242236469, -2.610283423421635, -2.6739988930888106, -2.7211948949611244, -2.751009837765307, -2.762912941122544, -2.7567204671542744, -2.7326040973472203, -2.6910912010496877, -2.6330569356030042, -2.559708313824894, -2.472560567574462, -2.373406321719919, -2.2642782664547116, -2.147406173308294, -2.0251692375104757, -1.9000448432183248, -1.7745549356990455, -1.6512112437200144, -1.5324606246621033, -1.4206318035096634, -1.3178847448955502, -1.2261638355564002, -1.1471559643781966, -1.0822544708745754, -1.0325297932703204, -0.9987074877616725, -0.9811541148809596, -0.9798713014854621, -0.9944980922846791, -1.0243215077553565, -1.0682950305658825, -1.1250645549759186, -1.1930011576509698, -1.2702398882030075, -1.3547236374108242, -1.444251023871776, -1.5365271486017091, -1.6292160040031578, -1.7199932901400241, -1.8065983881371535, -1.8868842677659248, -1.958864163135273, -2.0207539354085386, -2.071009152446818, -2.108356049440245, -2.1318156885659705, -2.140720805659063, -2.1347250135690192, -2.1138042207868897, -2.0782503153855507, -2.028657353584431, -1.9659006746613539, -1.8911095349995448, -1.8056340095801355, -1.7110070454078379, -1.6089026648762221, -1.5010914051967186, -1.3893941406261976, -1.2756354659156617, -1.1615978214735836, -1.0489775132380326, -0.9393437239646192, -0.8341015290622882, -0.7344598214239952, -0.6414049187046951, -0.5556804765481449, -0.477774166177959, -0.4079113987395542, -0.34605619626853246, -0.2919191247822187, -0.24497202339911123, -0.20446908916378823, -0.16947371477865278, -0.13889032980475552, -0.11150036877439953, -0.08600138524670727, -0.06104825174759755, -0.0352953337422065, -0.007438502576726941, 0.023744141736505887, 0.05935393210100645, 0.10033671149941022, 0.14745226748188747, 0.20124895205213053, 0.262044180033627, 0.329911346111706, 0.404673533834589, 0.48590421314714644, 0.5729349410009501, 0.6648698968470026, 0.7606069060086474, 0.8588644335915319, 0.9582138740467834, 1.0571163207773033, 1.1539628798611568, 1.2471174951481148, 1.3349611811670705, 1.4159365173147132, 1.4885912428351566, 1.5516198075750296, 1.6039017781005338, 1.6445360714524233, 1.6728700878464033, 1.6885229365917696, 1.6914020933874754, 1.6817129884203206, 1.6599611993506846, 1.6269471069996508, 1.5837530597845593, 1.5317232810019896, 1.4724369362359908, 1.4076749518937035, 1.3393813357838413, 1.269619892732457, 1.2005273488856145, 1.1342639945146167, 1.0729630243507513, 1.0186797949307245, 0.973342229037112, 0.9387035777118399, 0.9162987008942826, 0.9074049496148501, 0.9130086276977426, 0.9337778815965637, 0.9700427164131055, 1.0217826679715558, 1.088622479116411, 1.169835937591283, 1.264357837587518, 1.3708038320928175, 1.4874977532868785, 1.6125057980712516, 1.7436768097989566, 1.8786877394592865, 2.015093243604573, 2.150378275277921, 2.282012450602823, 2.4075049293468385, 2.524458533776359], [2.600472782260193, 2.6991684656772525, 2.783798535243183, 2.8527153022306497, 2.904570497089063, 2.938343873651447, 2.9533643804962404, 2.9493234205945593, 2.9262799086731803, 2.8846570308099984, 2.825230807902708, 2.7491107590166894, 2.657713147499331, 2.552727467607527, 2.4360769879937894, 2.309874306898299, 2.1763729889603134, 2.03791644243264, 1.8968852561435834, 1.7556442463860404, 1.6164904643392461, 1.4816033847093086, 1.3529984368197936, 1.2324849519278878, 1.1216294873057668, 1.0217253514616564, 0.9337689991909636, 0.858443793829068, 0.796111451385756, 0.7468112917102291, 0.7102672301577094, 0.6859022541389779, 0.6728599470933878, 0.6700324523045555, 0.6760941147462852, 0.6895399045710413, 0.7087276142049959, 0.7319227349862193, 0.7573448609270874, 0.7832144378569968, 0.8077986765400619, 0.8294554782576353, 0.8466742799539768, 0.858112811807479, 0.8626288707776429, 0.8593063464393148, 0.8474748868547121, 0.8267227584936819, 0.7969026310732116, 0.7581302011699025, 0.7107757529398744, 0.6554489356049484, 0.5929772109639986, 0.5243785856964427, 0.450829388582769, 0.3736279783275342, 0.2941553702877448, 0.21383384751866902, 0.13408467122851167, 0.05628602675364282, -0.018267666979991368, -0.08840399362832582, -0.15310729541946316, -0.21154901453665878, -0.2631128008527632, -0.30741370342796115, -0.3443109172440924, -0.3739137244141365, -0.3965804463235733, -0.41291040533996437, -0.4237290772493095, -0.4300667938116493, -0.4331315242473068, -0.4342764207600349, -0.4349629523908976, -0.43672057001959136, -0.44110394014586685, -0.4496488537425993, -0.4638279571773535, -0.48500746385405535, -0.5144059874611514, -0.5530565908957661, -0.6017730701623608, -0.6611213916197726, -0.7313970763312766, -0.8126091800158174, -0.9044713547847697, -1.006400303491437, -1.117521753468769, -1.2366838882595805, -1.362477988341334, -1.493265849498981, -1.6272133749689737, -1.7623295790959717, -1.8965100999997435, -2.027584200190028, -2.153364140208665, -2.2716957436312475, -2.3805089338686893, -2.4778670152050415, -2.562013492686132, -2.6314152773831134, -2.6848012040081266, -2.721194894961125, -2.7399411360807013, -2.7407250815011834, -2.723583774405172, -2.6889096529947905, -2.637445902245035, -2.570273707286052, -2.4887916588183128, -2.394687750036662, -2.289904583495272, -2.176598570797409, -2.0570940539038367, -1.9338334006344844, -1.809324225541815, -1.6860849583274673, -1.566590023597751, -1.4532159069680708, -1.3481893630355322, -1.2535389709988385, -1.1710511649117894, -1.102231759619874, -1.0482738629216604, -1.010032912592207, -0.9880094073030258, -0.9823397173019607, -0.9927951684380348, -1.0187893964125876, -1.059393771796489, -1.1133605051492252, -1.1791528601550867, -1.2549817354564274, -1.3388477268640624, -1.4285876544587774, -1.5219244368246243, -1.6165191197183615, -1.7100238206505047, -1.800134335184829, -1.8846411655655548, -1.961477777116797, -2.0287649615506247, -2.0848502869852354, -2.128341739569228, -2.158134807991333, -2.1734324261688087, -2.1737573669657695, -2.1589568664842407, -2.129199449667807, -2.0849641189322456, -2.0270222535768117, -1.9564127442541215, -1.874411049452136, -1.7824930057876285, -1.6822943473974947, -1.57556698885054, -1.4641331984086585, -1.3498388324320396, -1.2345068162498631, -1.1198920416418072, -1.0076388066737085, -0.8992418512068473, -0.7960119428556657, -0.699046846052536, -0.6092083643229078, -0.52710598651786, -0.453087495645128, -0.38723671844663515, -0.3293784095566148, -0.2790900805930445, -0.23572040651203247, -0.19841367347196895, -0.16613957853758057, -0.1377275556685279, -0.11190468798970701, -0.0873361761955702, -0.06266726934884131, -0.036565528875239735, -0.007762290101283549, 0.024907791627920235, 0.062470171973788166, 0.10577780901747633, 0.15548339459011068, 0.21201717872883688, 0.2755709947477966, 0.3460889309877451, 0.4232649222673732, 0.5065473537885756, 0.5951505873163245, 0.6880731385007418, 0.7841220598279885, 0.8819429203091621, 0.9800546248018012, 1.076888186589297, 1.1708284598294572, 1.260257756479567, 1.343600217441937, 1.419365781402055, 1.4861925978870232, 1.5428867634553658, 1.5884583209056575, 1.6221525495071145, 1.6434756873740086, 1.6522143624609145, 1.6484481629182526, 1.6325549469086678, 1.6052086722501555, 1.567369712945499, 1.5202678181334421, 1.4653780545538306, 1.4043902516175601, 1.3391726341511658, 1.2717304776725915, 1.2041607508693688, 1.138603816500918, 1.0771933425111395, 1.0220056276318958, 0.9750095687899779, 0.938018490534153, 0.9126450195527068, 0.9002601209779585, 0.9019573191179145, 0.9185230057495505, 0.9504135970182497, 0.9977401387415402, 1.0602607834186506, 1.1373813747895203, 1.2281641819336748, 1.3313446293816567, 1.4453556773084155, 1.5683593212985683, 1.6982845089412846, 1.8328706148537124, 1.9697154804709147, 2.1063269134044162, 2.2401764561109174, 2.3687541771292007, 2.4896232116409043, 2.6004727822601916], [2.671406759289071, 2.7617939559273954, 2.8370043185334204, 2.8955740891874533, 2.9363576027139078, 2.958551460310716, 2.9617109581245025, 2.9457584025763235, 2.9109831371669674, 2.858033302421526, 2.7878995467782746, 2.701891096817298, 2.6016047756296152, 2.488887723971196, 2.3657947261123606, 2.2345411674254723, 2.097452750742858, 1.956913170973451, 1.8153109906800358, 1.6749869722988073, 1.538183105182528, 1.4069945181704095, 1.2833253921702035, 1.1688498842237007, 1.0649789473144147, 0.9728337819547545, 0.8932264900599493, 0.8266483228967132, 0.7732657274223999, 0.7329242037477571, 0.7051597954976613, 0.6892178492174693, 0.6840785032439016, 0.6884882049390739, 0.700996411823339, 0.7199965104266466, 0.7437698895538618, 0.7705320344544629, 0.7984794667545018, 0.825836342887984, 0.8508995413585696, 0.8720811159331121, 0.8879470665524891, 0.8972514803854267, 0.8989652194468821, 0.8922984753753764, 0.8767166726367628, 0.8519493745130019, 0.8179920273581403, 0.775100563180916, 0.7237790639866846, 0.6647608688606504, 0.5989836720329753, 0.5275593129320857, 0.4517390936728953, 0.37287557217438366, 0.2923818673377452, 0.21168957424325385, 0.13220642061602805, 0.05527480005493831, -0.017867707366396385, -0.08612476987987508, -0.14857371740784572, -0.2044930623019647, -0.25338438408413566, -0.29498798186296754, -0.3292918605221165, -0.3565337904796542, -0.3771963613969323, -0.39199513309255174, -0.4018601674526897, -0.4079113987395538, -0.41142846197210753, -0.41381574585570213, -0.4165635643231557, -0.4212064458516793, -0.4292796196316703, -0.4422748303084392, -0.4615966370021287, -0.48852034695812113, -0.524152699549205, -0.5693963532357277, -0.6249191380007052, -0.691128920902356, -0.7681547955407627, -0.8558351507882097, -0.9537130039264408, -1.0610388025878692, -1.1767807131037273, -1.2996422246728374, -1.4280867138782543, -1.5603684371217483, -1.694569253957241, -1.828640236225512, -1.9604471900644178, -2.0878190135369046, -2.2085977344534253, -2.320689022991932, -2.4221119532695545, -2.5110467976986888, -2.5858796776249453, -2.6452429625119467, -2.688050406203153, -2.7135261302661364, -2.721226708195499, -2.711055766846245, -2.683270698949039, -2.6384812686071966, -2.5776400857097967, -2.50202512047815, -2.4132146211182124, -2.3130549810829653, -2.2036222732554855, -2.0871783222512312, -1.966122319222926, -1.8429390927530633, -1.7201452319424015, -1.6002343116040516, -1.4856224932107942, -1.3785957683125227, -1.2812600736866075, -1.1954954403996372, -1.1229152438630856, -1.0648315011633376, -1.022227018372627, -0.9957350276937071, -0.9856267761213967, -0.9918073381556682, -1.0138197295786635, -1.0508572021705398, -1.1017834052818818, -1.1651599141179196, -1.239280450939255, -1.3222109683543628, -1.4118346272685072, -1.5059005891548736, -1.6020754558343908, -1.6979961319469727, -1.791322857123554, -1.8797911571454948, -1.9612614959772758, -2.0337654726070618, -2.0955474965315117, -2.1451009911988432, -2.181198312874526, -2.202913729761474, -2.209638978869358, -2.2010911017941006, -2.177312450685709, -2.138662947546813, -2.0858048688801034, -2.0196806089385984, -1.941484043976491, -1.852626272807666, -1.754696641923036, -1.649420073169707, -1.538611795910018, -1.4241306416607928, -1.3078320861618968, -1.1915222210662408, -1.076913805148513, -0.9655854840010012, -0.8589451792369818, -0.7581985355415727, -0.6643231793956977, -0.5780493903889449, -0.49984761862363564, -0.4299231040426824, -0.3682176700835702, -0.3144185795033973, -0.2679741591883398, -0.22811572781285633, -0.1938851996975771, -0.1641675941598244, -0.13772755566852782, -0.11324888930813853, -0.0893760409406575, -0.06475640389875552, -0.038082315218854884, -0.008131614779622792, 0.026194320037817142, 0.0658360844206086, 0.11154622788317546, 0.1638645175871223, 0.22309915519456897, 0.2893144640106397, 0.36232539457300367, 0.44169901914131693, 0.5267630032324749, 0.6166208600622202, 0.7101736161156668, 0.8061473475915769, 0.9031258924332488, 0.9995879050243651, 1.093947303909492, 1.1845960700921139, 1.269948286967012, 1.348484274499587, 1.4187936609105802, 1.4796162551706398, 1.529879632627167, 1.5687324229207442, 1.595572392144887, 1.6100685374517019, 1.612176558905862, 1.6021472367227245, 1.5805274180501692, 1.5481535017986654, 1.5061374981034046, 1.4558459261263121, 1.3988719953974829, 1.3370016872080628, 1.272174509395983, 1.2064398362587945, 1.1419098617799843, 1.0807102858994513, 1.0249299178401121, 0.9765704158360203, 0.937497388022303, 0.9093940545121258, 0.8937186163140847, 0.8916663939835784, 0.9041376897055373, 0.9317121934828061, 0.9746306004567142, 1.0327839358311512, 1.105710900549574, 1.1926033592485228, 1.2923198967559644, 1.4034071752897894, 1.5241286362917614, 1.6524999131180333, 1.7863301579600235, 1.9232683423903576, 2.060853469361201, 2.1965675383228347, 2.327890036756696, 2.4523526925259933, 2.567593213015272, 2.67140675928907], [2.7366603313193396, 2.817968477602511, 2.883105282612188, 2.9308033154104005, 2.9601292282325993, 2.970503295005814, 2.961710958124503, 2.933906129078267, 2.8876061844420775, 2.8236787958484277, 2.7433209260680425, 2.648030508528853, 2.5395715000060397, 2.4199331516405547, 2.2912844781311894, 2.1559250156494265, 2.0162330430924142, 1.8746124967191546, 1.7334398337155112, 1.595012095248185, 1.461497384289231, 1.3348889088574047, 1.2169636489870561, 1.1092465880340172, 1.012981308815243, 0.9291075960552215, 0.8582465126365991, 0.8006932325448222, 0.7564177227297721, 0.7250731740940631, 0.7060118931936857, 0.6983081856434076, 0.7007875940894028, 0.7120617020588823, 0.7305675837151576, 0.7546108717196534, 0.7824113336238909, 0.8121497934258121, 0.8420152103675067, 0.8702507322374515, 0.8951975751404452, 0.9153356449487748, 0.929319905775712, 0.9360116154773371, 0.9345036844436333, 0.9241395683043059, 0.9045252737226325, 0.875534234908448, 0.837305002335676, 0.7902318697599623, 0.7349487463463349, 0.6723067529888805, 0.6033461814064531, 0.5292635973294145, 0.4513749914778147, 0.3710759810124563, 0.2898001372498235, 0.20897656085604127, 0.1299878423580574, 0.054129533242195764, -0.017427788503767708, -0.0836728437372947, -0.1437834489212085, -0.19715098359293934, -0.24339886716938067, -0.282394540067442, -0.3142546135306179, -0.33934303072254535, -0.3582622640612679, -0.37183775579534367, -0.3810959858445999, -0.38723671844663476, -0.3916001329030953, -0.3956296797878505, -0.40083161888400226, -0.4087322859083026, -0.42083419941274713, -0.4385721554389216, -0.46327046456084203, -0.49610246363664334, -0.5380533833856259, -0.5898875740279548, -0.6521209865789889, -0.7249996795377318, -0.8084849727943776, -0.9022457062592731, -1.0056578840568156, -1.11781180052173, -1.237526556279179, -1.3633716860749014, -1.493695439415174, -1.6266590850075218, -1.7602764547382797, -1.89245780639993, -2.021056970050475, -2.143920653665646, -2.258938721933157, -2.364094229261214, -2.4575119852402176, -2.5375044580760275, -2.6026138783287527, -2.651649490334846, -2.6837190099530397, -2.698253482095635, -2.695024886637983, -2.674156012985227, -2.6361223076461084, -2.5817455911354616, -2.5121797357143, -2.42888858910653, -2.333616616662535, -2.22835291087797, -2.115289378388378, -1.9967740565820025, -1.8752606313061424, -1.753255320841032, -1.6332623570598903, -1.5177293308479376, -1.4089936745044431, -1.3092315288344825, -1.2204101875366304, -1.1442452276318125, -1.0821633240841138, -1.0352716121189394, -1.0043343053186917, -0.9897571051509291, -0.9915797523547356, -1.009476877085512, -1.0427671076063763, -1.0904302014109757, -1.1511317727307204, -1.2232550110325906, -1.3049386207023448, -1.3941200666128843, -1.4885830872119712, -1.5860083390870823, -1.6840259670115034, -1.78026885289532, -1.8724252867855096, -1.9582898232631119, -2.0358111367059384, -2.103135767622316, -2.1586467576125536, -2.20099629982796, -2.229131681834678, -2.2423139648098003, -2.2401290228481203, -2.222490754378753, -2.189636469625081, -2.1421146489495704, -2.0807654521041212, -2.006694533305562, -1.9212408773881262, -1.825939514134271, -1.7224800878026505, -1.6126623539602207, -1.4983497437093483, -1.381422174684572, -1.2637292978974837, -1.147045349490799, -1.0330267273223082, -0.923173335359067, -0.8187946361343396, -0.7209812256566484, -0.6305825993860358, -0.548191615921884, -0.4741359909924094, -0.40847697260558585, -0.35101516340572836, -0.3013032730405305, -0.25866540629319995, -0.22222232632453423, -0.19092198077790173, -0.16357444552555334, -0.13889032980475538, -0.11552160017828214, -0.09210372130317643, -0.06729798037370377, -0.03983286007423132, -0.008543351957844596, 0.027592842353688137, 0.06942319229907491, 0.11759316466266448, 0.17252472837986627, 0.23440112291377513, 0.3031583118532018, 0.3784833690384669, 0.45981986365534255, 0.546380127936863, 0.6371641110157972, 0.730984349650575, 0.8264964253983763, 0.9222341324342178, 1.0166484543248822, 1.108149344886021, 1.19514923043639, 1.2761071003375115, 1.3495720310072514, 1.414224996238534, 1.4689178535212166, 1.512708461303034, 1.5448909741688168, 1.5650204795246838, 1.5729312776847337, 1.5687482638620014, 1.5528910415879131, 1.526070578281693, 1.489278400555993, 1.4437685147188248, 1.3910324221207877, 1.3327677748877433, 1.270841380756076, 1.2072474120805807, 1.1440617999131635, 1.0833938961548486, 1.027336562547224, 0.977915892723721, 0.9370417914145853, 0.90646062265145, 0.8877110966524819, 0.8820844939316673, 0.8905902267302211, 0.9139276144559181, 0.9524646044011112, 1.0062240051045492, 1.0748776213010611, 1.157748490806986, 1.2538212295166626, 1.3617602956799635, 1.4799357935648594, 1.606456254164685, 1.7392076612644294, 1.8758978390956593, 2.0141051867284943, 2.151330637503723, 2.2850516418386695, 2.412776920632145, 2.5321007155241846, 2.640755271976487, 2.7366603313193387], [2.7956814236040453, 2.867216768829965, 2.9217113924624534, 2.9581049257042378, 2.9756842549364655, 2.974098259806954, 2.9533643804962404, 2.913866875697397, 2.856346830096755, 2.7818841657619044, 2.6918721010752757, 2.5879846791004706, 2.4721381502107573, 2.3464471374998213, 2.2131766344644688, 2.0746909797884014, 1.9334010214880402, 1.7917107206154228, 1.6519644522850516, 1.5163962388830663, 1.3870820975587967, 1.2658966028532426, 1.1544746576467133, 1.0541793342154013, 0.9660764953591554, 0.8909167370820923, 0.8291250133585346, 0.7807981145825837, 0.7457099790513815, 0.7233246260126486, 0.7128163141136956, 0.7130963550572054, 0.7228458531603882, 0.7405535012112181, 0.7645574449264282, 0.7930901352903462, 0.8243250223127977, 0.856423906827118, 0.8875837596749873, 0.9160818400737631, 0.9403179964748052, 0.9588531124162536, 0.9704427646823934, 0.9740652888011715, 0.9689435942726853, 0.9545602351716658, 0.9306654167635994, 0.8972778010888036, 0.8546781594982881, 0.803396103206388, 0.7441902994517241, 0.6780227463953624, 0.6060278302810747, 0.5294770198712305, 0.4497401624668557, 0.36824443019730624, 0.2864320226287699, 0.20571776067793962, 0.1274477066305803, 0.052859915790890104, -0.016951632304748724, -0.08106895960526013, -0.13877701779856957, -0.18958489571778941, -0.23324073210009494, -0.2697399242575722, -0.2993263981835766, -0.32248688674926246, -0.33993834534781653, -0.3526088139815918, -0.3616122067973436, -0.3682176700835698, -0.3738142936766152, -0.3798720849047027, -0.3879002154506391, -0.39940362722720385, -0.41583913156574565, -0.4385721554389215, -0.46883527851493073, -0.507689665751575, -0.555990432895027, -0.614356888272162, -0.6831484759492624, -0.7624471055811513, -0.852046396542942, -0.9514481921287067, -1.059866517984665, -1.1762389720404243, -1.299245345674052, -1.4273330923844016, -1.5587490854457648, -1.6915769442783277, -1.8237790646606342, -1.9532423640977692, -2.0778266537929944, -2.195414475314481, -2.3039611951142254, -2.401544134752975, -2.4864095294915107, -2.557016152558038, -2.612074515887289, -2.650580658727443, -2.6718436608300418, -2.675506163964096, -2.661557350674992, -2.630338008533123, -2.582537497221694, -2.519182630084184, -2.4416186764406524, -2.3514828813212545, -2.2506710805874834, -2.141298157263734, -2.025653235155618, -1.9061506347856818, -1.7852777211486444, -1.6655408501911364, -1.5494106693307361, -1.439268045530252, -1.3373518819598893, -1.2457100413876108, -1.1661545221573173, -1.100221932686366, -1.0491401852566578, -1.0138021825239973, -0.9947471042088358, -0.9921497208936257, -1.0058179711303552, -1.0351988417965885, -1.0793923946042212, -1.137173588653335, -1.2070213646239967, -1.2871542850850086, -1.3755718716174996, -1.4701006467214872, -1.5684437799942588, -1.6682331564418063, -1.7670826319483741, -1.8626412181153496, -1.9526449463821638, -2.034966199301273, -2.107659364056881, -2.1690017580763143, -2.2175288964922637, -2.252063313268669, -2.2717363084581836, -2.276002169318993, -2.2646445985361328, -2.2377752739754064, -2.1958246565254496, -2.1395253509202985, -2.0698885043505855, -1.9881738947538248, -1.8958545108385008, -1.794576555486224, -1.6861159100524872, -1.572332176706606, -1.4551214674289354, -1.336369130436416, -1.2179035971842571, -1.1014524959830803, -0.9886021127007315, -0.8807611867171327, -0.779129913661897, -0.6846748884835441, -0.5981105665982184, -0.5198876512045137, -0.45018863562858535, -0.3889305453102813, -0.33577473940382724, -0.2901434515954343, -0.25124257816937673, -0.21809006289045182, -0.18954908688587516, -0.16436515094061607, -0.14120604048185678, -0.118703592437763, -0.0954961398729706, -0.07027049588663149, -0.041802353039761965, -0.008994018153108007, 0.02909152644390238, 0.07320114705335047, 0.12386745953451882, 0.18139075766624582, 0.24582746212535223, 0.31698541305832223, 0.3944261506085901, 0.47747414526508564, 0.5652327581498905, 0.6566065349780615, 0.7503292708827969, 0.8449971308420786, 0.9391059759550838, 1.0310919327362833, 1.1193741538257258, 1.2023986563504134, 1.2786820902430558, 1.3468542840526603, 1.4056984403563866, 1.4541879062577894, 1.4915185253624115, 1.5171356840946957, 1.5307552946521703, 1.532378106095534, 1.5222969003569302, 1.5010963072133419, 1.4696451571096816, 1.4290814785199382, 1.3807904326134803, 1.326375657689201, 1.267624664642626, 1.2064690783920633, 1.1449406548280943, 1.0851241150495659, 1.0291079255419266, 0.9789342122956813, 0.9365490270885402, 0.9037541844171026, 0.8821618577567527, 0.8731530645903641, 0.8778410823453102, 0.8970407240798207, 0.9312442661756769, 0.9806046637175233, 1.0449265164622554, 1.1236650635245848, 1.2159332926300301, 1.3205170547100689, 1.4358978815086356, 1.5602830174666644, 1.6916420020263099, 1.8277489789527344, 1.9662297692359465, 2.104612627060881, 2.24038150711461, 2.3710306083966644, 2.4941189262879266, 2.6073235417628178, 2.708490404399528, 2.795681423604044], [2.8479706909951092, 2.909122166780869, 2.9524960229254216, 2.9772479360917603, 2.9828910802608624, 2.969305939685177, 2.9367418410633195, 2.885810183585182, 2.8174695424137797, 2.733003013644773, 2.6339883521402725, 2.522261623420161, 2.399875242896975, 2.2690514064814264, 2.1321320228138214, 1.9915263365446012, 1.8496574823144267, 1.7089092292015735, 1.5715741649835888, 1.4398045289223806, 1.315566831990266, 1.200601306286093, 1.0963871032925054, 1.0041140166533744, 0.9246613428926598, 0.85858431698384, 0.8061083732872769, 0.7671312907106018, 0.7412330887440567, 0.7276933530115097, 0.7255154897776724, 0.733457242853899, 0.7500666576036413, 0.7737225488825664, 0.802678425850716, 0.8351087491568517, 0.8691563468481138, 0.902979795624741, 0.9347995841297985, 0.9629419144858109, 0.9858790661799373, 1.0022653408688953, 1.0109677252778773, 1.011090549061127, 1.0019935717126474, 0.9833031033702498, 0.9549159443209869, 0.916996112645107, 0.8699645140749374, 0.814481888148353, 0.7514255355817299, 0.6818604891893608, 0.6070059306939006, 0.5281977749062551, 0.4468484380332197, 0.3644048759301212, 0.2823060192483677, 0.20194074463307957, 0.12460750413127565, 0.05147668923916784, -0.01644326726624628, -0.0783351475217994, -0.13359678071266246, -0.18185881120363265, -0.22299592129557325, -0.25713119820938857, -0.28463351393792297, -0.30610796916531163, -0.3223796339005619, -0.3344709932002359, -0.34357367189817145, -0.351015163405728, -0.35822142054070716, -0.3666762775893632, -0.37787875954763916, -0.3932993944820914, -0.41433667662494567, -0.4422748303084392, -0.4782439980202363, -0.5231839203297547, -0.5778120925219515, -0.6425972744973523, -0.7177390995113543, -0.8031543768631335, -0.8984705174297742, -1.0030263331016764, -1.1158802761372721, -1.2358259968343073, -1.3614149124019952, -1.4909853011610925, -1.6226972686874972, -1.7545727804690685, -1.8845398229091033, -2.0104796444555806, -2.130275944078939, -2.241864817451041, -2.3432842435006163, -2.4327218963204795, -2.508560099722779, -2.5694168033802605, -2.614181549025822, -2.6420455104887868, -2.6525248296613957, -2.6454766284761893, -2.6211072508050033, -2.579972473635471, -2.52296961941939, -2.4513216964139195, -2.3665538863795534, -2.27046288443667, -2.1650797696615367, -2.0526272428485584, -1.93547220588977, -1.816074772018232, -1.6969348848880959, -1.5805377849163251, -1.4692995919764495, -1.365514273628918, -1.2713032375603406, -1.1885687264995095, -1.1189521050287454, -1.063798012559305, -1.0241252180783393, -1.000604853467912, -0.9935465271027065, -1.0028926323099425, -1.0282209706745467, -1.06875561282812, -1.1233857240710647, -1.1906918936899233, -1.268979329723965, -1.3563171195019392, -1.4505826144200662, -1.5495098785908477, -1.6507410480170557, -1.7518793820570708, -1.8505427536760681, -1.9444163201233793, -2.0313031412935185, -2.1091715684222403, -2.1761983095150206, -2.230806187885116, -2.271695743631248, -2.2978699814791734, -2.308651738324995, -2.303693325834818, -2.2829782930696507, -2.2468153466319505, -2.19582465652545, -2.1309169600919957, -2.0532660495193675, -1.9642753862662188, -1.8655397244760874, -1.7588027416855885, -1.6459117660712905, -1.5287707529580417, -1.4092926978471294, -1.2893526780573998, -1.1707426901866163, -1.055129396714761, -0.9440158136258487, -0.8387078640444253, -0.7402865933202625, -0.649586692063549, -0.567181809123393, -0.49337696058603314, -0.4282081579948436, -0.3714491937765461, -0.3226253389612935, -0.2810335323074107, -0.24576847530166573, -0.2157538983291322, -0.1897781333250655, -0.16653302067940293, -0.14465509573963264, -0.12276794499219804, -0.09952459525385267, -0.07364880161122073, -0.04397413131375269, -0.009479800525472315, 0.030677692762894386, 0.07713798547667006, 0.13031602912497176, 0.19038759482657422, 0.25728150082909274, 0.330678784092971, 0.41001885613709904, 0.4945125007594744, 0.5831613920890429, 0.6747836402444951, 0.7680447130250312, 0.8614929395829652, 0.9535986795650638, 1.0427961418954597, 1.127526763765692, 1.2062830144105487, 1.2776514711038482, 1.3403540270048437, 1.3932861317852112, 1.435551035399584, 1.4664891012519132, 1.485701375011819, 1.4930667364965404, 1.4887521208662668, 1.473215467945384, 1.447201240489204, 1.411728539130045, 1.3680720288903438, 1.3177360748598896, 1.2624226583161626, 1.2039938048523977, 1.144429398922824, 1.0857813809990084, 1.0301254211515543, 0.9795112338172853, 0.9359127409302646, 0.9011793033365626, 0.8769892230615853, 0.8648066718845369, 0.8658431258646027, 0.8810242827372, 0.9109633119059167, 0.9559411381553904, 1.0158942937967042, 1.09041069377066, 1.1787334986639417, 1.2797730362663609, 1.3921265579674003, 1.51410541671823, 1.6437690731234624, 1.778965169902736, 1.917374766569902, 2.056561699376234, 2.1940249294872216, 2.327252667540975, 2.453777017033812, 2.5712278635485166, 2.677384752093196, 2.770225540413599, 2.8479706909951084], [2.893085742629241, 2.9433301328261496, 2.9751987220971703, 2.988070388042778, 2.981688731202419, 2.9561668798372644, 2.9119839740311284, 2.8499734250526885, 2.7713032408391243, 2.6774488961629186, 2.570159401971717, 2.451417388279004, 2.3233941549599058, 2.1884007614917538, 2.048836317266916, 1.9071346964322993, 1.7657109338073658, 1.6269085605630709, 1.4929491100187129, 1.3658849658905399, 1.247556639091375, 1.1395554469113727, 1.0431924329191864, 0.9594742105893268, 0.8890862423461935, 0.832383882665083, 0.7893913236129775, 0.7598083884431421, 0.7430249283256136, 0.7381423936833643, 0.744001979413056, 0.7592185867093213, 0.7822197070960178, 0.8112882199204624, 0.8446080057394607, 0.8803112168322197, 0.9165260139378647, 0.9514235759326731, 0.9832632164916485, 1.0104344980396431, 1.031495316989517, 1.0452050432097328, 1.050551928057772, 1.046774145801283, 1.033373998999092, 1.0101249952288014, 0.9770716859581712, 0.9345223437389544, 0.8830347365887515, 0.8233954338288734, 0.756593241364711, 0.6837875123302397, 0.6062722074728428, 0.5254366854257567, 0.44272428347413545, 0.35958980257741957, 0.2774570349642528, 0.19767746798631977, 0.12149126425849387, 0.049991556309573686, -0.015906994386523897, -0.07549453677420268, -0.1282865648133179, -0.1740380962215518, -0.2127511104910513, -0.2446750374507721, -0.270300269242981, -0.29034485102499763, -0.30573468436375517, -0.3175777476225437, -0.3271329953148604, -0.3357747394038269, -0.34495343625795666, -0.3561539003428907, -0.3708520372267022, -0.39047123224418584, -0.41633954603901496, -0.4496488537425993, -0.49141702105225005, -0.5424541389662211, -0.6033337411515423, -0.67436980625714, -0.7556002049374938, -0.8467770914483836, -0.9473645663850184, -1.0565437547661756, -1.173225256774152, -1.2960687417101864, -1.42350927379644, -1.5537897859157705, -1.6849989585732628, -1.81511362029963, -1.9420446659743484, -2.063685394181372, -2.177961096178917, -2.282878689161832, -2.3765751763090996, -2.4573637359927685, -2.523776292086619, -2.5746014954253797, -2.6089171512905556, -2.626116256835177, -2.6259259625006592, -2.6084189390906634, -2.574016813176797, -2.5234855235081692, -2.4579226454401732, -2.378736924330942, -2.287620447622125, -2.186514064288383, -2.0775668251056354, -1.9630903636924415, -1.8455092629058052, -1.7273085508384582, -1.61097954289485, -1.4989652894131489, -1.393606900962124, -1.297092005428184, -1.2114065427247696, -1.1382910255508711, -1.0792022899591602, -1.0352816300969154, -1.0073300604908877, -0.9957912803263581, -1.0007427314258888, -1.0218949495080745, -1.0585992114736935, -1.1098632847125673, -1.1743748925324087, -1.2505323274428217, -1.3364814756095802, -1.4301583654076753, -1.5293362242831872, -1.6316759241862637, -1.734778619152951, -1.8362393310138219, -1.9337002217986328, -2.024902304552766, -2.1077343875973846, -2.1802781196249366, -2.240848102587555, -2.2880261636057146, -2.3206890229919326, -2.338028759318659, -2.3395656501940163, -2.3251531546427606, -2.2949749950968283, -2.24953448924303, -2.189636469625082, -2.1163623073464115, -2.031038721100084, -1.9352012000387473, -1.8305529951111092, -1.7189207353849525, -1.6022078011097243, -1.482346632071209, -1.361251167092347, -1.2407705980098371, -1.1226455795183157, -1.0084679660670928, -0.8996450503633642, -0.7973691574801014, -0.7025933071763294, -0.6160134984159666, -0.5380579982452189, -0.4688838365052987, -0.408380522878245, -0.3561808181487576, -0.31167821195604245, -0.2740505892159222, -0.24228941107738747, -0.21523359764989047, -0.19160718225895257, -0.17005971358295147, -0.1492083150098869, -0.12768027157983616, -0.1041550048904035, -0.07740431555234066, -0.04632982066926468, -0.00999658913624829, 0.032337921625857025, 0.08120040013453268, 0.1368843156172771, 0.19943912254735985, 0.26866633267455153, 0.34412257284187403, 0.42512956427944293, 0.5107907779410825, 0.6000143453983956, 0.6915416402793102, 0.7839807954204254, 0.8758442896146498, 0.9655896284335944, 1.0516620588967096, 1.1325381999367299, 1.2067694411899157, 1.2730239624241664, 1.330126254979826, 1.3770930842721536, 1.4131649173073408, 1.4378319492254574, 1.4508539953992161, 1.452273667314058, 1.4424224175729552, 1.4219192177551656, 1.391661818067781, 1.3528107251384585, 1.3067662192181673, 1.25513890985707, 1.1997144953154308, 1.1424135413841765, 1.0852472261099428, 1.0302701048197944, 0.9795310320566987, 0.9350234314356746, 0.8986361295661632, 0.8721059653357133, 0.8569733510323839, 0.8545418977605925, 0.8658431258646023, 0.8916071637916064, 0.9322401988154569, 0.9878092836826483, 1.0580349283994435, 1.1422917203079095, 1.2396170228391021, 1.3487276085970015, 1.4680438904874298, 1.5957212301715604, 1.7296876307265254, 1.8676869642795448, 2.007326749396559, 2.1461293805118697, 2.2815856254694604, 2.4112091494559635, 2.5325907956898646, 2.6434513559124935, 2.7416915969728666, 2.8254383728325534, 2.89308574262924], [2.9306448847548214, 2.9695512520937815, 2.989627414869619, 2.99048071871657, 2.9720873801782397, 2.9347922426550213, 2.879300242157822, 2.8066597952934202, 2.718238513174599, 2.615691826288762, 2.5009252723709667, 2.3760513479636725, 2.2433419510115846, 2.105177543482249, 1.9639942371844166, 1.822230050914498, 1.6822716017534747, 1.546402477462322, 1.41675449093367, 1.295262942739777, 1.1836269158690125, 1.083275500322958, 0.9953406975089779, 0.9206375889823021, 0.8596521751682958, 0.8125371016559897, 0.7791152981404319, 0.7588913628470382, 0.7510703380223754, 0.7545833444158839, 0.7681193789522992, 0.7901624339973147, 0.8190329722893913, 0.8529326917492654, 0.8899914413734528, 0.9283151049855662, 0.9660332547634523, 1.0013453914484487, 1.032564632500712, 1.0581577819877552, 1.076780814780106, 1.087308930126526, 1.0888604727545033, 1.0808141796462059, 1.062819383517371, 1.0347989854051527, 0.9969451940753137, 0.9497082145245814, 0.8937782470429202, 0.8300613276180665, 0.7596496956713295, 0.6837875123302398, 0.6038328682483654, 0.5212171114961478, 0.4374025910033739, 0.3538399478386107, 0.27192609437765936, 0.19296399998724667, 0.11812535181167338, 0.048417081898722326, -0.01534735077681028, -0.07257116021478564, -0.12289129692994448, -0.16618891755920928, -0.2025929754217656, -0.2324768267382182, -0.2564479298347376, -0.2753308954406804, -0.2901443205424036, -0.30207200175038346, -0.31242927261079634, -0.32262533896129314, -0.33412259397922717, -0.34839397723822046, -0.36687949773829187, -0.3909430680457779, -0.4218307946264016, -0.4606318381663647, -0.5082428978752599, -0.5653372868914363, -0.6323394540877144, -0.709405673555603, -0.7964114701434298, -0.8929461814320053, -0.9983148776297017, -1.1115476755180134, -1.2314162954102164, -1.3564575257862592, -1.4850030834619707, -1.6152151922880575, -1.745127054614792, -1.8726872608700023, -1.995807076862798, -2.112409468556587, -2.220478672128383, -2.3181090945331895, -2.4035523371837964, -2.4752611726556544, -2.531929370710227, -2.572526363852594, -2.5963258618684972, -2.602927666460591, -2.592272097800138, -2.564646620628516, -2.520684444201373, -2.4613550633099317, -2.387946902118003, -2.3020424138520568, -2.2054861727780426, -2.100346665882128, -1.9888726460307857, -1.8734450423089466, -1.756525533410064, -1.640602973644715, -1.5281389162574057, -1.4215135039055395, -1.3229729907050733, -1.234580124278458, -1.1581685505950488, -1.0953023106426412, -1.0472413783710466, -1.0149140467986395, -0.9988968071273889, -0.9994021881062797, -1.0162748340334895, -1.048995904285879, -1.0966956798643233, -1.1581740679443548, -1.2319285085502083, -1.3161886127643756, -1.408956703581581, -1.5080532924483099, -1.611166410031005, -1.7159036215814387, -1.8198454975226999, -1.9205992799705727, -2.015851486506568, -2.1034182235549133, -2.1812920423644986, -2.247684259310107, -2.3010617767707258, -2.3401775783511796, -2.364094229261214, -2.37219988535455, -2.3642164983821305, -2.3402000958804217, -2.3005332070899467, -2.24590969663173, -2.1773124506857098, -2.095984531631828, -2.0033945723491446, -1.9011973168431142, -1.7911903263056692, -1.6752679564044335, -1.555373770487633, -1.433452583115966, -1.311403328253815, -1.1910339166745723, -1.0740191884997994, -0.9618629808578931, -0.8558652196484777, -0.7570948111876733, -0.6663689574872819, -0.5842393519510986, -0.5109855345824004, -0.44661550187529875, -0.39087348104398323, -0.34325459579374573, -0.30302597603617, -0.2692537011793403, -0.240834819954174, -0.21653356283191186, -0.1950207591059015, -0.17491539223345098, -0.154827175997238, -0.13339901169489288, -0.10934819342181366, -0.08150526436266001, -0.0488494909083887, -0.010540011719939254, 0.03405816674534751, 0.08535402116066924, 0.14351674833552633, 0.2084687608082218, 0.2798856368326208, 0.35720303876883164, 0.4396304316070641, 0.526171255218949, 0.6156490344669031, 0.7067387548191305, 0.7980026916007552, 0.8879297620218042, 0.9749773737072815, 1.057614674070329, 1.1343660633211319, 1.2038538212978498, 1.2648387150214122, 1.316257499557059, 1.3572562983266123, 1.3872189486699547, 1.4057895217566971, 1.412888369857028, 1.4087212149290813, 1.3937809664698908, 1.368842139274702, 1.3349479285946346, 1.2933901865019064, 1.2456827243944304, 1.1935285379464857, 1.1387817081217588, 1.0834048711322903, 1.029423267915655, 0.978876476806067, 0.9337689991909639, 0.8960209053362026, 0.8674197552033763, 0.8495749866813145, 0.8438759116641509, 0.8514543800188714, 0.8731530645903633, 0.909500189546001, 0.9606913727172863, 1.0265790838257896, 1.106670038688148, 1.2001306591130658, 1.305800533885435, 1.4222136227377347, 1.5476267572840536, 1.680054815155235, 1.8173117803999406, 1.9570567586292384, 2.0968438929542565, 2.2341750295306086, 2.366553911897922, 2.4915406430318323, 2.6068051441337543, 2.7101783599529576, 2.7997000113949677, 2.873661776110035, 2.9306448847548205], [2.9603303500337628, 2.987563682049569, 2.9956600279728542, 2.98445853562495, 2.9541682589626497, 2.9053628672411427, 2.8389671646046053, 2.756235747214782, 2.6587243110283096, 2.548254296778832, 2.4268717154032426, 2.296801133278759, 2.1603959089214495, 2.020085858536208, 1.8783235849553006, 1.7375307317120683, 1.6000454206586567, 1.4680720977917772, 1.343634948684378, 1.2285359537427778, 1.1243185367101687, 1.0322376203359536, 0.9532367443966078, 0.8879327272248677, 0.8366081668863593, 0.7992118867046678, 0.7753672366950924, 0.764387972373792, 0.7653012500277182, 0.776877107326256, 0.7976636442820523, 0.8260269857675722, 0.8601949963020334, 0.8983036332929655, 0.9384447683509891, 0.9787142790011073, 1.0172592156652098, 1.0523228810229253, 1.0822867198684076, 1.105708005752914, 1.1213524237484749, 1.128220783683732, 1.1255692517451228, 1.1129226565062764, 1.0900806039902704, 1.0571163207773042, 1.0143683298008788, 0.9624252456634572, 0.9021041504775074, 0.8344231730381243, 0.7605690395150904, 0.6818604891893608, 0.5997085509341207, 0.5155747526222518, 0.4309283845473312, 0.347203958086624, 0.26575999174872916, 0.18784021870800097, 0.11453824393320705, 0.04676658677258736, -0.014769071275285229, -0.06958975093208396, -0.11745662347022211, -0.15837768281988232, -0.1926074585070106, -0.22063976845410815, -0.2431936927728413, -0.2611931272704953, -0.27574044396915554, -0.28808494121026346, -0.299586903933566, -0.3116782119560422, -0.32582052753120866, -0.34346216073622315, -0.3659947505640744, -0.39471090994247776, -0.4307639639392381, -0.4751308625616534, -0.5285792739575471, -0.5916397623192103, -0.6645838298737935, -0.7474084571014853, -0.8398276133582123, -0.9412710354209862, -1.0508903884754162, -1.1675727372980709, -1.2899610695268593, -1.4164814326230049, -1.5453760759425508, -1.6747418335447308, -1.8025728459112993, -1.9268066031285904, -2.0453722012505677, -2.1562396398641157, -2.2574689539953834, -2.347257968393733, -2.4239874871364013, -2.4862627858962876, -2.5329503568591365, -2.5632089652140175, -2.5765142087657815, -2.5726759253325553, -2.5518479624837447, -2.514530006711136, -2.461561359853437, -2.394106744848389, -2.3136344159057685, -2.2218870352405777, -2.1208459549786713, -2.0126897043996115, -1.8997476253265326, -1.7844497186819475, -1.669273860019677, -1.5566916088547822, -1.4491138741629273, -1.3488377055462246, -1.2579954560482818, -1.1785075089812147, -1.112039678675062, -1.059966285755558, -1.0233397740389176, -1.0028675816356176, -0.9988968071273887, -1.0114070268939037, -1.0400114263090914, -1.0839662103026138, -1.1421880624850038, -1.2132792314364624, -1.2955596424896445, -1.387105267770957, -1.4857918404159096, -1.5893428742932225, -1.6953808512635125, -1.8014803663429413, -1.905221978842093, -2.0042455055858373, -2.096301510926573, -2.1792997969262045, -2.2513537745503114, -2.3108197010343883, -2.3563298971339446, -2.3868192075539794, -2.401544134752976, -2.4000942563979706, -2.382395725559031, -2.348706845616112, -2.2996059040604244, -2.2359716361837787, -2.158956866484242, -2.06995603815184, -1.9705674852741017, -1.8625514249180872, -1.7477847440496725, -1.6282137270073145, -1.50580591129672, -1.3825022718712827, -1.260170916604511, -1.1405634288818067, -1.0252749184027774, -0.9157087403510282, -0.8130467186596364, -0.7182255643611246, -0.6319200186431942, -0.5545330763260029, -0.4861934634279541, -0.4267603568835392, -0.375835149988003, -0.332779888401816, -0.2967418330327398, -0.26668345204107125, -0.2414170084311376, -0.2196427955815154, -0.19998998346112598, -0.18105897539229854, -0.16146414059516936, -0.13987578220823532, -0.11506022412316275, -0.08591695215954293, -0.051511824480737975, -0.011105470675585656, 0.03582387406923515, 0.08956370704166366, 0.15015721389771303, 0.21740011478351529, 0.2908444929133302, 0.3698095152131235, 0.45339877422065344, 0.5405238067955578, 0.6299331827502683, 0.7202464093981765, 0.8099917699793544, 0.8976471082391254, 0.9816824908131065, 1.0606036255983604, 1.1329948893675479, 1.1975608221979708, 1.25316497979248, 1.2988650966831023, 1.333943602133934, 1.3579326441227821, 1.370632912281382, 1.3721257047569835, 1.3627778527964967, 1.3432392962439128, 1.31443328860559, 1.2775393972380344, 1.2339696478653546, 1.1853383384259388, 1.1334262107535116, 1.0801398156872064, 1.0274670341487984, 0.9774298202869136, 0.9320353103067046, 0.8932264900599498, 0.8628336345385155, 0.8425277224945839, 0.8337769896481667, 0.8378077152206004, 0.8555702404565865, 0.8877110966524808, 0.9345519769058147, 0.9960761238058916, 1.0719225285320688, 1.1613881496221365, 1.2634381665914194, 1.376724089351108, 1.4996093537561292, 1.630201851292514, 1.7663926713789089, 1.9059001821870911, 2.0463184440513253, 2.185168841701526, 2.3199537404006416, 2.4482109186208336, 2.5675675074825177, 2.675792175395263, 2.7708443350214136, 2.850919217924381, 2.914487758432978, 2.960330350033762], [2.9818909859969787, 2.9972150293853685, 2.993245522770234, 2.9700547891619404, 2.9280829714296277, 2.8681277394285747, 2.7913259774585035, 2.6991278910806598, 2.5932641514808963, 2.4757068596486134, 2.3486252576701094, 2.214337236901628, 2.0752577897390942, 1.9338456208127006, 1.7925491730638379, 1.653753333392342, 1.5197280612227453, 1.3925801320083508, 1.2742091076852362, 1.1662685394207628, 1.070133277339875, 0.9868736105099536, 0.917236792077662, 0.8616363232466102, 0.8201491802379817, 0.7925209751593343, 0.7781788495728043, 0.7762517132195628, 0.7855972643865158, 0.8048350670922163, 0.832384817548693, 0.8665088116832225, 0.9053575297847689, 0.9470171858555174, 0.9895580496004597, 1.0310823390607848, 1.0697705018338972, 1.1039247520267255, 1.1320088072361034, 1.1526828729253449, 1.1648330479138678, 1.1675944710874329, 1.160367692148458, 1.1428279241380075, 1.1149270181567474, 1.0768881865892979, 1.0291936855225692, 0.9725658453176244, 0.9079420059819421, 0.8364440669030357, 0.7593434948310673, 0.6780227463953625, 0.5939341491208618, 0.5085573457133385, 0.42335643882223695, 0.3397379767975807, 0.2590108950958961, 0.18234947365674256, 0.11076028917893146, 0.045054034866793456, -0.014177048388206093, -0.06657553299773229, -0.11202852423083769, -0.15067047858408947, -0.1828790417383831, -0.2092640094678555, -0.23064969490044646, -0.24805115843057526, -0.2626449179576492, -0.27573490286357016, -0.28871454153341675, -0.30302597603616965, -0.32011747615277925, -0.34140017623617813, -0.3682052810654965, -0.4017428802868716, -0.44306347532283247, -0.49302325862119795, -0.552254094355141, -0.6211390344054191, -0.6997940664998828, -0.7880566361495339, -0.885481314364216, -0.9913428032833338, -1.104646286309717, -1.2241449427320608, -1.3483642638432423, -1.4756326328074587, -1.6041174684027049, -1.7318660873646474, -1.8568503150739009, -1.977013772950605, -2.090320695756863, -2.1948050850213185, -2.2886189872570295, -2.370078698080586, -2.4377077355513057, -2.4902754970883643, -2.5268306125285274, -2.546728128918303, -2.549649807532532, -2.5356169768700814, -2.504995563028387, -2.4584931065702915, -2.397147768180071, -2.322309519327936, -2.2356139040636087, -2.1389489392702785, -2.034415888766727, -1.9242847974002029, -1.8109458009975663, -1.6968573335201713, -1.5844924313733595, -1.4762843845851081, -1.3745730042267728, -1.2815527644754972, -1.199224036337615, -1.1293485592350174, -1.0734101980948048, -1.0325819096499, -1.0076996953510222, -0.9992441531542162, -1.0073300604908868, -1.0317042303208357, -1.071751685941112, -1.1265100029451336, -1.1946914731932252, -1.2747125605703766, -1.3647299461641738, -1.4626823054710576, -1.5663368260866513, -1.67333936429605, -1.7812670557004129, -1.887682140486171, -1.9901857394458702, -2.0864703229405617, -2.1743696514480035, -2.251905032219115, -2.317326830197236, -2.3691502903916795, -2.406184870369829, -2.427556441925481, -2.4327218963204804, -2.421475873447548, -2.393949527236606, -2.35060143289772, -2.2922009314115, -2.2198043883875904, -2.13472501356902, -2.0384970397393154, -1.9328351918860363, -1.819590485996818, -1.7007034792102547, -1.5781561472665764, -1.4539235900554526, -1.3299267610255683, -1.207987381529919, -1.0897861377964229, -0.9768251678093042, -0.8703957303062182, -0.771551811290799, -0.6810902684171427, -0.5995379442550103, -0.5271460000747111, -0.46389153692238716, -0.409486385041206, -0.36339276079596033, -0.3248453167373634, -0.29287894963916783, -0.26636158727187575, -0.24403105093031988, -0.22453499038269573, -0.20647281343798124, -0.18843848556596726, -0.16906305707992175, -0.14705578671054859, -0.12124277062999403, -0.09060205406791633, -0.05429429683957075, -0.011688181964549633, 0.03762010491456818, 0.09379384193005814, 0.15674953096033625, 0.2261576211771256, 0.301450184035298, 0.38183534567953537, 0.46631810571145393, 0.5537270035899672, 0.6427459398903631, 0.7319503231464259, 0.8198465975280205, 0.9049141151204655, 0.9856482514262541, 1.0606036255983604, 1.1284362788280888, 1.1879436855102785, 1.2381015218198315, 1.2780961939564215, 1.3073522316530244, 1.3255537790544965, 1.3326595616242203, 1.328910870691145, 1.3148322825495544, 1.2912250122955, 1.2591529892447766, 1.2199219261509144, 1.175051833873768, 1.126243602124132, 1.0753404211628135, 1.0242849549575286, 0.9750732898467406, 0.9297067713179614, 0.8901429027861613, 0.8582465126365997, 0.835742398370973, 0.8241706293002751, 0.8248456324398455, 0.8388201013895351, 0.8668546570319865, 0.9093940545121243, 0.9665505764139211, 1.0380950810752811, 1.1234559917411278, 1.22172632122268, 1.3316786325827297, 1.4517876438636066, 1.5802599987458017, 1.7150705498518435, 1.854004341510605, 1.9947033381221488, 2.1347168262957616, 2.2715543266044707, 2.402739786412699, 2.5258657904111006, 2.638646521132212, 2.7389682279729346, 2.824936019517114, 2.8949158788969123, 2.947570913516962, 2.981890985996978], [2.9951443799079214, 2.9984236393354355, 2.982404327068349, 2.9473913415403885, 2.8940522109154307, 2.8234018852476996, 2.736779746720657, 2.635819385195549, 2.5224118571031915, 2.3986632990443164, 2.266847899610916, 2.129357340710969, 1.9886479004782418, 1.847186461747021, 1.7073966918479953, 1.571606650654809, 1.441999044650589, 1.3205652763030744, 1.2090643419666485, 1.1089875102752238, 1.0215295695715143, 0.9475672708955344, 0.8876454164389236, 0.8419708565244445, 0.8104144656979845, 0.7925209751593341, 0.7875263492563519, 0.7943822127683914, 0.8117866676332413, 0.8382206867230236, 0.8719891419148754, 0.9112654171787838, 0.9541384772680542, 0.9986612107391083, 1.04289884363347, 1.0849762276796766, 1.1231228440268992, 1.155714429281044, 1.181310223245167, 1.1986849548723986, 1.206854821520639, 1.2050968731253962, 1.1929613834122226, 1.1702769704449465, 1.137148414109823, 1.093947303909493, 1.0412958320224293, 0.9800442194253349, 0.9112424226569972, 0.8361069115362386, 0.7559834302818527, 0.6723067529888805, 0.5865585168608761, 0.5002242612072699, 0.4147508159152704, 0.3315051695515813, 0.2517359048308443, 0.1765382190211955, 0.10682345075561187, 0.043293915145402206, -0.013576290897090991, -0.06355400805940455, -0.10665292338759955, -0.1431325112872156, -0.17349003192390444, -0.19844579384807357, -0.21892206411577728, -0.2360161759241146, -0.2509685365837354, -0.265126373623173, -0.2799041705160543, -0.2967418330327395, -0.3170616902392608, -0.3422254690600145, -0.3734923871542396, -0.41197948542784285, -0.45862526934528725, -0.5141576485779329, -0.5790670593744984, -0.653585525959639, -0.7376722694313119, -0.8310063087114898, -0.9329863221923931, -1.0427378552051993, -1.1591277719121051, -1.280785665362794, -1.4061317609076993, -1.533410680419834, -1.6607302820814343, -1.786104656711469, -1.907500250152644, -2.0228839949603494, -2.130272275778735, -2.227779522911102, -2.313665228536377, -2.3863782098941013, -2.4445970029184347, -2.4872653568794276, -2.5136219135246516, -2.5232232902981764, -2.5159599431594626, -2.492064356546529, -2.452111291934408, -2.3970100177381606, -2.3279886373143173, -2.2465708237650928, -2.1545454554263923, -2.0539298197629874, -1.9469272116124172, -1.8358798904007947, -1.7232184766609928, -1.6114089580380933, -1.502898536721493, -1.400061582337699, -1.305146955938731, -1.220227941741599, -1.1471559643781966, -1.0875191819993968, -1.042606931740025, -1.0133808665390927, -1.000453464450276, -1.0040744171990084, -1.024125218078338, -1.0601220748614946, -1.111227075970434, -1.176267342476397, -1.2537617093763322, -1.3419543015827258, -1.4388542075047897, -1.542280309926735, -1.64991021356801, -1.7593321141425229, -1.8680983871882193, -1.973779637995128, -2.074017947472783, -2.1665780728727704, -2.249395416275812, -2.320619656288824, -2.378653047401351, -2.4221825242011255, -2.4502049008451716, -2.4620446260290927, -2.4573637359927694, -2.43616383834775, -2.3987801530245094, -2.3458678286595323, -2.2783809385625733, -2.197544735475283, -2.1048219043807457, -2.0018736937561834, -1.8905169244610693, -1.7726779690626266, -1.6503448605924727, -1.5255187269581394, -1.4001657546785502, -1.2761708631912672, -1.155294219350089, -1.0391316422779902, -0.9290798435331626, -0.826307319292813, -0.731731563234965, -0.6460031047633266, -0.5694967013251099, -0.5023098302551025, -0.44426843945567335, -0.39493973196664683, -0.35365158171066496, -0.3195180108671038, -0.29147000759693853, -0.26829082999334664, -0.2486548314693101, -0.23116875705369136, -0.21441440136134896, -0.19699148875912142, -0.1775596351794852, -0.154878279114754, -0.12784352580122546, -0.09552093200560255, -0.057173367009648195, -0.012283215585646684, 0.03943166235559136, 0.098008636970539, 0.1632379255379886, 0.2346671875221459, 0.3116129812525024, 0.39317878620057084, 0.47827912268898937, 0.5656691405827818, 0.6539789041639434, 0.7417514756574874, 0.827483797946331, 0.90966930049925, 0.98684110341741, 1.057614674070329, 1.1207287996107131, 1.175083776562955, 1.2197757847742081, 1.2541265056921205, 1.2777071619108842, 1.290356293315179, 1.2921907415149088, 1.283609484710645, 1.2652901454081615, 1.2381781790035873, 1.2034689375394743, 1.1625829852108742, 1.1171352158941312, 1.0688984836987963, 1.0197626012384482, 0.9716896833291111, 0.9266669130113523, 0.8866578795980015, 0.8535536829685912, 0.829125013358535, 0.8149764009504765, 0.8125037849355533, 0.8228564783798186, 0.8469045049258562, 0.8852121584745869, 0.9380184905341509, 1.0052252654389495, 1.0863927451331608, 1.18074347703506, 1.2871740652547037, 1.4042747118655468, 1.5303561257851095, 1.6634832167553064, 1.8015148253687059, 1.9421485911762755, 2.0829699333220164, 2.2215040150480347, 2.355269487370934, 2.481832760156405, 2.598861531914149, 2.704176323361822, 2.7957988038744723, 2.8719957733124604, 2.931317762652019, 2.9726313428996782, 2.995144379907921], [2.9999784020568754, 2.9911792865126894, 2.9632281622885337, 2.916659935782501, 2.8523638930531026, 2.7715637056635662, 2.675789958185559, 2.566845848166663, 2.4467668703666585, 2.317775438351261, 2.182231514679518, 2.042580413082396, 1.9012989999934593, 1.760841557038581, 1.6235865698307954, 1.4917856816072261, 1.3675159935951686, 1.2526368089423086, 1.1487518057249368, 1.0571774897326927, 0.9789186227662349, 0.9146511509121554, 0.8647129739085463, 0.8291027058055651, 0.807486383356385, 0.7992118867046678, 0.8033306516686214, 0.8186260787899506, 0.8436478855655872, 0.8767515087694364, 0.916141546875301, 0.9599181411191696, 1.0061251298625504, 1.052798776124035, 1.0980158631955172, 1.1399399781728046, 1.1768648572870528, 1.2072537486812132, 1.2297738556070168, 1.2433250531646245, 1.2470622213490055, 1.2404107025063504, 1.2230745681595119, 1.1950375640745017, 1.1565567887844372, 1.1081493448860218, 1.0505723796647866, 0.9847970975576349, 0.9119774774841459, 0.8334145594247007, 0.7505172735339793, 0.6647608688606504, 0.5776440553405945, 0.4906460007697313, 0.4051843232903132, 0.3225751896233147, 0.2439965706631867, 0.17045562064519934, 0.10276103609774921, 0.04150111901771984, -0.012971881482160618, -0.06055073958533456, -0.10137530095612854, -0.13582755554356116, -0.1645198643351806, -0.1882766485942041, -0.2081100214820856, -0.2251900011490098, -0.24081008731746004, -0.2563491064468598, -0.27323033060702384, -0.2928789496391676, -0.3166790231222405, -0.3459310568569931, -0.3818113375203501, -0.4253341190537824, -0.4773176861873804, -0.5383552259294038, -0.6087913191985512, -0.6887047249811173, -0.7778979719311987, -0.8758941011225314, -0.9819407229802568, -1.0950213657907975, -1.2138739072612308, -1.3370156990465965, -1.4627748215549767, -1.589326747032467, -1.714735546957428, -1.83699865874529, -1.9540941297774062, -2.064029186323108, -2.1648889328709022, -2.254883974867815, -2.3323957752986484, -2.3960186025887213, -2.444597002918435, -2.4772578324177497, -2.493436011418087, -2.492893310924424, -2.4757296471440076, -2.442386539237619, -2.393642574065671, -2.3306009149676776, -2.254669084798162, -2.1675314417964704, -2.071114945753482, -1.967548976941325, -1.8591201173135437, -1.748222928918278, -1.6373078651777675, -1.5288275241581224, -1.4251824973344915, -1.3286680815107785, -1.2414231050829632, -1.1653820730946578, -1.102231759619874, -1.0533732727337755, -1.019890489182722, -1.0025256059364247, -1.001662387729057, -1.0173175075504555, -1.0491401852566562, -1.096420132691845, -1.1581036167345908, -1.2328172592885163, -1.318899010106629, -1.41443555891731, -1.5173053017189397, -1.6252258460017863, -1.735804934184504, -1.846593586256777, -1.9551402133709193, -2.059044435081325, -2.156009344508417, -2.243891007568867, -2.320744053490009, -2.384862312321978, -2.4348135786146807, -2.469467725767339, -2.4880175591828584, -2.4899919742212164, -2.4752611726556553, -2.444033884269141, -2.3968467336426915, -2.3345460813353847, -2.258262848906763, -2.169381004183103, -2.0695005327544624, -1.9603958502817145, -1.84397071469085, -1.7222107752369322, -1.597134944897367, -1.4707468024765173, -1.344987220778999, -1.221689377588879, -1.1025372380609901, -0.9890285022800148, -0.8824428926227347, -0.7838165152182195, -0.693922871809555, -0.6132609266813102, -0.5420504523624973, -0.4802346921023458, -0.4274901913119339, -0.38324346892730776, -0.34669402751511275, -0.31684304220933307, -0.29252692719328266, -0.2724548579390681, -0.2552492307724638, -0.239487970926652, -0.22374755780378797, -0.2066456226944689, -0.18688198999839203, -0.16327707759539378, -0.1348066442612327, -0.10063197003943113, -0.060124676754537344, -0.012885537285186542, 0.04124321979661454, 0.10217243308984726, 0.16956750287651118, 0.2428568190366747, 0.32124690270176776, 0.4037438661364567, 0.48918062953720787, 0.5762491818911636, 0.6635370396102809, 0.7495669447460452, 0.8328387570628747, 0.9118724333554289, 0.9852509547189571, 1.0516620588967094, 1.1099376604772742, 1.1590898960048692, 1.198342812683506, 1.2271588262993223, 1.2452592036120793, 1.252637973561228, 1.249568836483922, 1.2366048170399897, 1.2145705902706068, 1.1845475965817907, 1.147852245764431, 1.1060076878044338, 1.0607097947221198, 1.0137881488007718, 0.9671629644862263, 0.9227989805995621, 0.8826574434947958, 0.8486473582308305, 0.8225772122104624, 0.8061083732872772, 0.8007113320119248, 0.8076258961830519, 0.8278263566115364, 0.8619925281174117, 0.9104874320153188, 0.9733422290371095, 1.050248838611252, 1.1405604958866584, 1.243300306365396, 1.3571776641882551, 1.4806122087590377, 1.611764810205917, 1.7485749017013477, 1.8888033201557477, 2.0300796801380216, 2.1699531924502136, 2.30594575141965, 2.4356060558592896, 2.55656349928391, 2.6665805661259125, 2.763602502391911, 2.845803090711619, 2.911625449595562, 2.9598168927810913, 2.989457024008576, 2.9999784020568754], [2.99635215442904, 2.9755432614201176, 2.935879267462139, 2.878120573487107, 2.803370719875939, 2.7130517751325014, 2.60887261306241, 2.492790827328148, 2.3669691820888357, 2.233727625473088, 2.0954919957817877, 1.9547406260906552, 1.8139500995086772, 1.6755414236527293, 1.5418278785690165, 1.4149657477671378, 1.296909068372378, 1.1893694354979074, 1.09378177030844, 1.0112768140112611, 0.942660944815683, 0.8884037358295905, 0.8486334833273862, 0.8231407414679582, 0.8113897061147656, 0.8125371016559896, 0.8254580452596761, 0.8487781972072231, 0.8809113578624806, 0.9201015450415457, 0.9644684831048123, 1.0120553594442345, 1.0608776569630791, 1.1089718537096134, 1.1544427933603694, 1.1955085723396148, 1.2305418598636386, 1.2581066642632999, 1.2769896800618281, 1.2862254923705945, 1.2851150746023636, 1.2732371882540423, 1.250452475220992, 1.2169002192002703, 1.1729879385484532, 1.1193741538257265, 1.0569448446589014, 0.986784268214823, 0.9101409515669345, 0.8283897890855887, 0.7429912707469982, 0.6554489356049484, 0.5672661849383184, 0.4799036008182364, 0.3947378978038594, 0.31302358868383606, 0.23585837086207032, 0.1641531400634221, 0.09860741507161262, 0.039690814350236046, -0.01236893372056366, -0.05759113658580744, -0.09624030801034625, -0.12881741458424764, -0.15604443064905918, -0.17884260927668558, -0.19830504177255745, -0.21566422844275812, -0.2322555152363666, -0.2494773609867009, -0.2687494855119025, -0.2914700075969383, -0.3189727123386872, -0.35248558867755403, -0.3930917500793629, -0.44169379492117394, -0.49898257954421266, -0.5654112682216885, -0.6411753931388069, -0.7261995071545134, -0.8201308463540559, -0.9223402423469034, -1.031930340345023, -1.1477509928820158, -1.2684215152791314, -1.3923593122541225, -1.5178142198607203, -1.642907757419506, -1.7656763540521736, -1.8841175071791059, -1.9962377486425906, -2.1001012401015413, -2.193877794450149, -2.2758891249629993, -2.3446521586425666, -2.3989183140799235, -2.4377077355513057, -2.460337591888732, -2.4664436880748797, -2.4559947961470203, -2.4292992859948734, -2.3870038217572547, -2.3300840812327395, -2.259827649318743, -2.177809427223368, -2.0858600823592526, -1.9860282349094462, -1.88053723182334, -1.7717374936210382, -1.6620555305120228, -1.553940809196033, -1.4498117081794089, -1.3520018260724773, -1.2627079034272701, -1.1839405842730815, -1.117479179401465, -1.0648315011633376, -1.027199721281741, -1.0054530618062374, -1.000107968258656, -1.0113162371493822, -1.0388613816716175, -1.082163324084112, -1.1402913058175836, -1.2119847114868416, -1.2956813154961317, -1.3895522843449721, -1.491543108338937, -1.5994194970500475, -1.7108171569277333, -1.823294279731914, -1.9343855090984596, -2.0416561210121316, -2.1427551529786513, -2.2354662462323205, -2.3177550246168206, -2.387811921334136, -2.4440894783784044, -2.485333280330229, -2.510605840888272, -2.51930293318293, -2.511162039289828, -2.486262785896288, -2.44501942706199, -2.388165626694005, -2.3167319780307887, -2.232016870586096, -2.135551472422016, -2.0290597334772316, -1.914414430640641, -1.793590364572435, -1.6686158798161665, -1.541523912089481, -1.414303769087403, -1.2888548237221609, -1.1669432422397537, -1.0501627855971347, -0.9399006130388091, -0.8373088847861835, -0.7432828095122169, -0.6584456156526559, -0.5831407478136721, -0.5174314050529655, -0.46110735127432745, -0.41369874406270873, -0.3744965516011213, -0.34257896226612683, -0.3168430422093329, -0.29604076641015353, -0.27881844154837504, -0.26375845723767655, -0.2494222476877253, -0.23439332003849378, -0.21731920903037122, -0.19695125019646054, -0.17218112451682208, -0.142073214876997, -0.10589192647486477, -0.06312325665831353, -0.013490051149037422, 0.04303945064194758, 0.10625000268867434, 0.17568471188745366, 0.25065722773224847, 0.33027044104823394, 0.4134412001301822, 0.49893039457518523, 0.5853776155781206, 0.6713394800783935, 0.7553306080070699, 0.8358661695003792, 0.9115048741881095, 0.9808912587084349, 1.0427961418954594, 1.0961541593478867, 1.1400973593028567, 1.1739839381901434, 1.1974213145487047, 1.2102828811666861, 1.2127179338454968, 1.2051544471344544, 1.1882945484375271, 1.1631027275242145, 1.1307870040255137, 1.0927734562989033, 1.0506746865482655, 1.0062529549536436, 0.9613788558010075, 0.9179865276346785, 0.8780264842372691, 0.8434172213236939, 0.8159967934271716, 0.7974755654714009, 0.7893913236129777, 0.7930678804935548, 0.8095782321888862, 0.8397132197162627, 0.8839565194605924, 0.9424666374028362, 1.015066415209091, 1.101240376128392, 1.2001400496532129, 1.310597220648713, 1.431144855899366, 1.560045273496372, 1.695324942817979, 1.8348151394248546, 1.976197534048576, 2.117053671593955, 2.2549171977741413, 2.3873276201105815, 2.5118843483474134, 2.62629974792615, 2.728449959373747, 2.816422285857232, 2.888558029590536, 2.9434897633724306, 2.980172153747234, 2.9979056039677654, 2.99635215442904], [2.9842963167202434, 2.951647851905386, 2.900589026614912, 2.832099315098488, 2.7474871957986804, 2.648361131063748, 2.536593862371396, 2.4142808616665765, 2.283693916821419, 2.147230942938814, 2.007363198497679, 1.866581144081653, 1.7273402102478244, 1.592007739316661, 1.4628123335869632, 1.3417967805362465, 1.2307756355196002, 1.1312984265780237, 1.0446193070910068, 0.971673823597825, 0.9130632920821069, 0.8690470906565287, 0.8395429844618119, 0.8241354044277398, 0.8220914100963161, 0.832383882665083, 0.853721322266976, 0.8845834674544095, 0.9232618186863761, 0.9679040346163744, 1.0165610828547205, 1.0672359676945884, 1.1179328274145692, 1.166705193840862, 1.2117022367653552, 1.2512118747283814, 1.283699720025738, 1.307842937350273, 1.3225582293693088, 1.3270233153619562, 1.3206914369230773, 1.303298603444892, 1.274863475114279, 1.2356799678669244, 1.1863028484396876, 1.127526763765693, 1.0603593130673499, 0.9859889190339345, 0.9057483827456603, 0.8210751123497061, 0.7334690953100426, 0.6444497363908155, 0.555512707133691, 0.4680879469173664, 0.3834999209425863, 0.3029311775992421, 0.22739015828039008, 0.15768409911349057, 0.09439772919061817, 0.037878317139609936, -0.011772548823200203, -0.05470023864143481, -0.09129138891418483, -0.12216139737391582, -0.14813543686970235, -0.1702234921370957, -0.18959007955233934, -0.20751945015291579, -0.22537719589124905, -0.24456927531878947, -0.26649954520780067, -0.2925269271932825, -0.32392335223992347, -0.36183361021653576, -0.4072381874365837, -0.4609201027693418, -0.5234366546145091, -0.5950968690939958, -0.6759452972757701, -0.7657526496560577, -0.8640135834716726, -0.9699517770127288, -1.0825322395032255, -1.2004806199732339, -1.3223090985189014, -1.4463482729743664, -1.5707842976096522, -1.6937003919873928, -1.8131217210866721, -1.927062555233644, -2.033574552662394, -2.1307949703978926, -2.216993601629905, -2.2906172601219117, -2.3503306840189655, -2.3950528114963574, -2.4239874871364018, -2.436647788183746, -2.4328733107646787, -2.4128399240977503, -2.37706168157736, -2.3263847669562847, -2.2619735470455273, -2.185288994644014, -2.0980599320724105, -2.002247722110989, -1.900005194970202, -1.793630743145994, -1.6855186370724273, -1.578106710363738, -1.4738226317334182, -1.3750300196601966, -1.2839756645289586, -1.2027391010410815, -1.1331857216462737, -1.0769245408189714, -1.0352716121189394, -1.0092199677322444, -0.9994167967791868, -1.006148407814534, -1.029333336776739, -1.0685237686387155, -1.1229152438630832, -1.1913644242621346, -1.2724145017841086, -1.3643276527374173, -1.4651237734203344, -1.5726245850879343, -1.6845020702485145, -1.7983301014836324, -1.9116380507575281, -2.0219651232740317, -2.126914146384317, -2.224203561134164, -2.3117164113012505, -2.387545201008556, -2.450031595297675, -2.497800065832667, -2.5297847330110574, -2.545248822494792, -2.5437963344245538, -2.5253757129048826, -2.490275497088365, -2.4391121285883064, -2.372810278271482, -2.292576234120674, -2.1998650564536075, -2.0963423533387577, -1.9838416540106085, -1.8643184584499555, -1.7398021146651934, -1.6123467198675552, -1.483982256670648, -1.3566671603940323, -1.2322434689873358, -1.1123956342218528, -0.9986139735260767, -0.8921636187279772, -0.7940596741531777, -0.7050491356667892, -0.6255999484049964, -0.5558973985031687, -0.49584784767699924, -0.4450896337296728, -0.40301077959242754, -0.3687729828666921, -0.3413412012778021, -0.3195180108671035, -0.3019817965777461, -0.2873277420243784, -0.2741105189585838, -0.260887538860201, -0.2462616200996984, -0.22892194439657365, -0.2076822252760229, -0.1815150876129564, -0.1495817591729483, -0.11125629970030229, -0.06614373737811796, -0.014091642716365505, 0.04480515796583522, 0.11020684768309287, 0.18153779821451477, 0.2580024186215775, 0.33860725307429224, 0.42218874434806664, 0.5074459303788812, 0.5929772109639977, 0.6773202133912765, 0.7589937022412859, 0.836540421979703, 0.9085697327141701, 0.9737989003868774, 1.0310919327362833, 1.079494910879211, 1.118266851911637, 1.1469052483948505, 1.1651655632460551, 1.1730741100895588, 1.1709339157680037, 1.1593233392981428, 1.1390874056362803, 1.1113219985772926, 1.0773512402747278, 1.0386985606252068, 0.9970521236714649, 0.9542254260951448, 0.9121140110337564, 0.8726493455921603, 0.8377509898212431, 0.8092782365340166, 0.7889824237398131, 0.7784611140414441, 0.779115298140432, 0.7921107134539138, 0.818344275307005, 0.8584164994532649, 0.9126106536498161, 0.980879216088805, 1.0628380435546707, 1.1577684665090404, 1.2646273364479037, 1.3820648575379733, 1.508449844475625, 1.6419018664060003, 1.7803295670880068, 1.9214742984905344, 2.0629580724513246, 2.2023347262201787, 2.3371431153621094, 2.4649610936859885, 2.5834590159645354, 2.690451505863598, 2.7839462685945557, 2.8621887944884428, 2.9237018943814763, 2.967319128129748, 2.9922113308318132, 2.997905603967766, 2.9842963167202434], [2.96391288677283, 2.9196952239457854, 2.8576560111534373, 2.778985521287467, 2.685186120722606, 2.578039085578977, 2.45956521704987, 2.33198018101761, 2.1976456209910586, 2.059017191822874, 1.9185907323309515, 1.7788478361658069, 1.64220209106547, 1.5109472367992822, 1.3872084421501252, 1.2728978224866614, 1.1696752138044895, 1.0789150891955508, 1.0016803527577247, 0.9387035777118394, 0.8903760741007226, 0.8567449813701158, 0.8375183870457237, 0.8320782793861798, 0.839500954042777, 0.85858431698384, 0.8878813625777604, 0.9257389607431493, 0.9703409639749017, 1.0197545468012468, 1.0719786191589706, 1.1249931129549233, 1.176807928657242, 1.225510346335636, 1.2693097526090744, 1.3065786101948633, 1.3358886982221736, 1.3560417765658959, 1.3660939729823136, 1.3653733540949773, 1.3534903161874257, 1.33034061490344, 1.296101039734172, 1.2512179249028104, 1.1963888682953947, 1.1325381999367308, 1.060786896942332, 0.9824177790289396, 0.8988369341402109, 0.8115324146921674, 0.7220313091361424, 0.6318563294207978, 0.5424830616674488, 0.4552990048457669, 0.37156547107598253, 0.2923833427341765, 0.2186635778284968, 0.15110322880911564, 0.09016759430222367, 0.03607896193240777, -0.011187772476169184, -0.05190250405697233, -0.08657041376260924, -0.11591581683004726, -0.14085979666334394, -0.16249221880663034, -0.18203886734537983, -0.2008245747893691, -0.2202333229762421, -0.2416663740688101, -0.2664995452078006, -0.2960407664101534, -0.33148905817219476, -0.3738960329816908, -0.42413096433063446, -0.4828503793338868, -0.5504730188575799, -0.627160874930058, -0.7128068624868812, -0.8070295150021863, -0.9091749154708687, -1.01832588999227, -1.133318305490366, -1.2527641305588322, -1.3750807436419232, -1.498525810169351, -1.6212369039747827, -1.7412749220637538, -1.856670238786538, -1.9654704683695075, -2.0657886555797114, -2.155850694364783, -2.234040784221408, -2.29894377365655, -2.349383308533598, -2.38445479873904, -2.4035523371837972, -2.406388847761895, -2.393008900070298, -2.3637938045219533, -2.3194587876626254, -2.2610422394687606, -2.189887217443627, -2.107615581691166, -2.0160953161613238, -1.9174017594544048, -1.8137736197795042, -1.7075647791291317, -1.601192998208592, -1.4970867134791528, -1.3976311688251455, -1.3051151455244583, -1.2216795448127826, -1.1492690375565924, -1.089587926307201, -1.0440612679407688, -1.0138021825239973, -0.9995861289362459, -1.0018327636351405, -1.020595819752086, -1.0555612537954495, -1.1060537112356243, -1.1710511649117865, -1.249207386332607, -1.338881724255685, -1.4381754919364897, -1.544974108338649, -1.6569940031812194, -1.771833184244778, -1.887024280558482, -2.0000888189824573, -2.1085914656173403, -2.21019296801313, -2.3027005691590428, -2.3841147288151316, -2.4526710802713847, -2.5068766687841713, -2.5455396588105845, -2.5677918572529737, -2.57310357528638, -2.561290537649834, -2.532512740955837, -2.4872653568794285, -2.4263619672662595, -2.3509106015711514, -2.2622832181291197, -2.1620794254057194, -2.0520853738231026, -1.9342288597682962, -1.810531768303078, -1.6830610379028026, -1.5538793579463495, -1.4249968070836074, -1.2983246081868138, -1.175632114252511, -1.0585080509820828, -0.9483269281240411, -0.8462213959206247, -0.7530611686161635, -0.6694389678636032, -0.5956637592743258, -0.5317613698127232, -0.4774823868966704, -0.43231705660690956, -0.3955167229168676, -0.3661211867054577, -0.34299121656819304, -0.324845316737363, -0.3102997538924956, -0.29791076683454876, -0.2862178328086653, -0.2737868428926565, -0.259252046798417, -0.2413556644015806, -0.21898412633208442, -0.191199997332337, -0.1572687514666878, -0.11667970469084991, -0.06916056428027795, -0.014685222250287904, 0.0465254030853257, 0.11400949137395727, 0.18707724209881585, 0.2648302480660013, 0.34618680557775183, 0.42991249060771786, 0.5146551916620727, 0.5989836720329744, 0.6814286398387902, 0.7605252360139027, 0.8348558100197686, 0.9030918415586466, 0.9640338843150138, 1.016648454324882, 1.0601008598516877, 1.093783069802157, 1.1173358412665422, 1.1306644706432878, 1.133947693421171, 1.1276394310291689, 1.1124632648860955, 1.0893997033308338, 1.0596664918277794, 1.024692396070724, 0.9860850568299097, 0.9455936703204565, 0.9050673845834919, 0.8664104173783461, 0.8315349914340608, 0.802313246259112, 0.7805293203851517, 0.7678328029604514, 0.7656947287838268, 0.7753672366950923, 0.7978479289592796, 0.8338498608459496, 0.883777957612637, 0.9477125037436983, 1.025400180275652, 1.1162529444811369, 1.2193548565293242, 1.3334767646436174, 1.4570985684856186, 1.58843859473277, 1.7254894436713766, 1.866059505429644, 2.007819203198974, 2.1483509019495157, 2.285201327704437, 2.415935276743671, 2.5381893578298764, 2.649724504634708, 2.7484760201951026, 2.8325999698999653, 2.9005148229129434, 2.950937352085529, 2.982911936658756, 2.9958325671489043, 2.9894570240085776, 2.9639128867728304], [2.9353743176277622, 2.8799557112325815, 2.807443453815929, 2.7192285587839518, 2.616994589934415, 2.5026805950040796, 2.378438374293113, 2.246585086381021, 2.109552302117777, 1.9698327003768865, 1.8299256525153742, 1.6922829658278584, 1.5592560489753347, 1.4330457246321853, 1.3156558473912097, 1.2088517899806157, 1.1141247404430112, 1.0326626100884748, 0.9653281902923516, 0.9126450195527065, 0.8747912350017366, 0.8516014893816831, 0.8425768200894028, 0.8469021660269382, 0.8634710453344526, 0.8909167370820925, 0.9276491567934059, 0.9718964829771464, 1.02175048285536, 1.0752144028004542, 1.1302522345837078, 1.1848381436409305, 1.2370048506932974, 1.2848897929941951, 1.3267779552397916, 1.3611403511032807, 1.3866672520816217, 1.4022953979201815, 1.4072285788097285, 1.400951149888386, 1.3832342190351705, 1.3541344349760969, 1.313985489673879, 1.2633826321603994, 1.2031606658236198, 1.1343660633211325, 1.0582239787307814, 0.9761010616602394, 0.8894650797332551, 0.7998424316532754, 0.7087746810719863, 0.6177752606164432, 0.528287485236218, 0.4416449748404261, 0.35903551905031983, 0.28146932354454746, 0.20975246032583625, 0.1444662062909501, 0.08595279926174279, 0.03430797208789997, -0.0106195521519808, -0.04922160293299386, -0.0821173241416674, -0.1101335133902005, -0.13427906523839453, -0.15571419935610634, -0.17571529182391216, -0.19563624402715926, -0.21686741598383577, -0.24079321709491552, -0.2687494855119025, -0.301981796577746, -0.3416058208397932, -0.388570803418117, -0.4436271602249229, -0.5072990845515095, -0.5798629323978344, -0.6613320097313742, -0.7514482232504056, -0.8496808822340762, -0.9552327570471953, -1.067053314400184, -1.1838588652072357, -1.3041591824806977, -1.4262899786510135, -1.5484504782638024, -1.6687451870761978, -1.7852288455964225, -1.8959534669861011, -1.999016298261788, -2.0926075115068143, -2.1750564292396093, -2.244875115345996, -2.3007982194946206, -2.341818047411763, -2.3672139397915535, -2.3765751763091005, -2.3698167749514747, -2.3471877269450623, -2.309271389784863, -2.256977950798795, -2.1915290666450584, -2.1144349753949054, -2.027464562681399, -1.9326090372301277, -1.8320400296268107, -1.7280630674836996, -1.6230674967736294, -1.5194740100921036, -1.4196810056938773, -1.3260110347244487, -1.2406585972442234, -1.1656405202860645, -1.1027500939063613, -1.0535160553326588, -1.0191673989262073, -1.000604853467912, -0.9983797115293215, -1.0126805222012591, -1.0433279724287914, -1.0897780881592674, -1.1511336891654815, -1.226163835556397, -1.3133308143956464, -1.4108240361227, -1.516600046957196, -1.6284277191338188, -1.743937559164126, -1.8606739782966502, -1.9761493012627351, -2.08789825088309, -2.1935316380732943, -2.2907880093834945, -2.377582056845095, -2.4520486762471836, -2.5125816679969466, -2.55786620674924, -2.5869043587531526, -2.5990330955864716, -2.5939344354499996, -2.5716375339832678, -2.5325127409558372, -2.47725783241775, -2.4068768152301487, -2.322651877767614, -2.2261092226791606, -2.1189796609792895, -2.003154967948264, -1.880641097439629, -1.753509419937405, -1.6238471894703017, -1.4937084543911852, -1.365066606923086, -1.2397697168577269, -1.1194997171956729, -1.005736405859061, -0.8997271005502763, -0.8024626366107952, -0.7146602340840197, -0.6367535842360589, -0.5688903219669695, -0.5109368634667343, -0.4624904028206459, -0.4228976816881534, -0.39127997714660395, -0.3665635985128937, -0.3475150482613024, -0.33277988840181544, -0.32092426467160085, -0.31047797880011874, -0.29997796543412736, -0.2880110258359756, -0.27325469524654333, -0.2545151741478272, -0.23076133416754224, -0.20115391495626628, -0.16506915632500682, -0.12211625698616885, -0.07214821364407147, -0.015265767799349832, 0.04818563194828834, 0.11762576167492698, 0.19225617733846875, 0.271082949538792, 0.35294497211464665, 0.4365470925207441, 0.520497184812076, 0.6033461814064522, 0.6836300002741046, 0.7599122518561772, 0.8308265862000526, 0.8951175461594891, 0.951678826947532, 0.9995879050243648, 1.0381360887129176, 1.066853156850101, 1.0855258873698335, 1.0942099315957448, 1.0932346583514427, 1.08320077056086, 1.0649706813322632, 1.0396518219666337, 1.0085732362371589, 0.9732559890638666, 0.9353780789630025, 0.8967346882958054, 0.8591947296941406, 0.8246547479182134, 0.7949913112010145, 0.7720130728971737, 0.7574137017167515, 0.7527268664511928, 0.7592844190946837, 0.7781788495728039, 0.8102309875703577, 0.8559638045357024, 0.9155830247821606, 0.988965092206676, 1.0756528624603903, 1.1748592037561327, 1.2854784974615125, 1.4061058369230965, 1.5350635343438912, 1.6704343656483038, 1.810100816565025, 1.951789443771282, 2.093119336584826, 2.2316535605648973, 2.364952387100609, 2.4906270645796806, 2.6063928682914193, 2.7101201783383067, 2.7998823772730272, 2.8739994309608803, 2.931076115587536, 2.9700339784063314, 2.990136266743473, 2.9910052254006354, 2.9726313428996813, 2.935374317627763], [2.8989220584938575, 2.8327655280256647, 2.7503761755589045, 2.6533339985310564, 2.5434895346415973, 2.4229232262694254, 2.293899703901161, 2.1588180588991577, 2.0201592695419235, 1.8804320097549287, 1.7421181057475936, 1.6076189110419188, 1.4792038450270133, 1.3589622848591414, 1.2487599166397954, 1.1502005414342713, 1.0645941975766806, 0.9929323061595277, 0.9358703754388858, 0.8937186163140846, 0.8664406295761462, 0.8536601309609096, 0.8546754869603326, 0.8684816475611487, 0.8937988861524245, 0.9291075960552214, 0.9726882513797157, 1.0226655206317843, 1.0770554275349493, 1.1338143871363713, 1.1908889079733271, 1.2462647437128214, 1.2980143003228912, 1.3443411568283004, 1.3836206376585924, 1.4144354804360788, 1.4356057720608733, 1.446212474846469, 1.4456140294726307, 1.4334556984906341, 1.40967149858895, 1.3744787571782218, 1.3283655143941042, 1.2720711707116994, 1.2065609485530002, 1.1329948893675486, 1.052692241880502, 0.9670922092151206, 0.8777121096538878, 0.7861040657793167, 0.6938113681896895, 0.6023256621915929, 0.5130460788401785, 0.427241376173708, 0.3460160739296032, 0.27028145757134936, 0.20073219785880758, 0.13782918377278455, 0.08178900314243451, 0.032580330981553135, -0.010072695251700316, -0.046680216906129876, -0.07796979520459857, -0.1048634079579988, -0.12844891856052404, -0.1499467788971639, -0.17067285329829857, -0.19199835349228103, -0.21530795201027614, -0.2419571917002129, -0.27323033060702373, -0.31029975389249564, -0.35418804785266345, -0.40573376632751307, -0.465561828480054, -0.5340593713129038, -0.6113577432676343, -0.6973211702349101, -0.7915424561688689, -0.8933459014849819, -1.0017974380195058, -1.115721794176569, -1.2337263226487662, -1.3542309503430454, -1.4755035502455531, -1.5956998919744707, -1.7129072053411165, -1.8251902925029353, -1.93063905179893, -2.027416232009936, -2.1138042207868897, -2.188249685814636, -2.2494049316597633, -2.2961649081851876, -2.3276989061858715, -2.343476100122171, -2.3432842435006176, -2.3272409860375123, -2.2957974592479298, -2.249733964186829, -2.190147787138638, -2.1184333613823347, -2.0362551810096248, -1.9455140515042864, -1.8483074269765523, -1.7468847314891711, -1.6435986881396776, -1.540853781323672, -1.441053052340693, -1.3465444743222577, -1.2595681681743003, -1.182205706384864, -1.1163327064542472, -1.063575841403731, -1.0252752930737994, -1.002453547171754, -0.9957912803263581, -1.0056109223486434, -1.031868295531407, -1.0741525415465893, -1.131694349966181, -1.2033823054160777, -1.2877869776644935, -1.3831921952336563, -1.487632772872491, -1.598937810576546, -1.7147785504953266, -1.8327196712106306, -1.9502728190855343, -2.0649511255917017, -2.174323438931325, -2.27606700834705, -2.368017399975745, -2.448214492922238, -2.5149435016616692, -2.566770093503233, -2.602568814628668, -2.6215442015811155, -2.6232441329984284, -2.607565164482595, -2.574749783153805, -2.5253757129048835, -2.4603375918887327, -2.3808215256833307, -2.2882731884514667, -2.1843602961412225, -2.070930406684232, -1.949965109089204, -1.8235317437426473, -1.693733848223018, -1.562661545320002, -1.432343082273784, -1.3046986928011666, -1.181497887283806, -1.0643211832961217, -0.9545271708499705, -0.8532256673377295, -0.7612575597033141, -0.6791817598395088, -0.6072695179199498, -0.5455061518776665, -0.4936000642120855, -0.4509987344181597, -0.41691120114753255, -0.390336387068002, -0.3700964752849157, -0.3548744226939494, -0.343254595793745, -0.3337654407462244, -0.3249230536211313, -0.3152744998864276, -0.30343974466594165, -0.28815109670193556, -0.2682891382281142, -0.24291420827486107, -0.2112926258374467, -0.1729169787930805, -0.12751996089377277, -0.0750814086039541, -0.015828367685506373, 0.04977179826728035, 0.12102506330287478, 0.1970307877978511, 0.27670762235610996, 0.3588245755379695, 0.4420364183527696, 0.52492248392331, 0.6060278302810738, 0.6839056701918099, 0.757159935891462, 0.8244868395773143, 0.8847143126641839, 0.9368382576604884, 0.9800546248018008, 1.0137864293659078, 1.0377049523049675, 1.0517445133088585, 1.0561103679996355, 1.0512794555799223, 1.0379939055393628, 1.017247397384151, 0.9902646511311938, 0.9584745038676895, 0.9234771945326733, 0.8870066310024085, 0.8508885466943817, 0.8169955648450682, 0.787200274511647, 0.763327480963997, 0.7471068229130552, 0.7401269491226873, 0.7437924172704198, 0.7592844190946834, 0.7875263492563516, 0.8291551230079001, 0.8844990124059748, 0.9535626157016239, 1.036019403473344, 1.131212102212139, 1.2381609859065577, 1.3555799533820303, 1.481900078469827, 1.61530013622208, 1.7537434358967712, 1.895020134585183, 2.03679406804131, 2.1766530209208943, 2.312161270110701, 2.4409131743584362, 2.560586552546621, 2.668994592509673, 2.7641350623464436, 2.8442356560548507, 2.9077943936032553, 2.9536141101470506, 2.980830207243889, 2.9889309972823366, 2.977770147082594, 2.9475709135169663, 2.8989220584938584], [2.854864511978224, 2.7785239246287654, 2.6869369913796555, 2.581859338326148, 2.4652928408733454, 2.3394417628051287, 2.2066644412797154, 2.069421647339548, 1.9302228287698984, 1.7915714902539344, 1.655910983606633, 1.5255719680223971, 1.402722757089944, 1.2893236969037678, 1.1870866197407925, 1.0974402929503224, 1.021502636010972, 0.9600603137581153, 0.913556134640801, 0.8820844939316673, 0.8653949077245439, 0.8629034890684887, 0.8737120274620757, 0.8966341518102052, 0.9302278892398694, 0.9728337819547548, 1.0226175952160672, 1.077616544675253, 1.1357878931559084, 1.1950587174247227, 1.2533756256325446, 1.3087532163381337, 1.3593201099950682, 1.4033614523978686, 1.4393568850506067, 1.4660130972827812, 1.4822902161359715, 1.4874214490012598, 1.4809255666887993, 1.4626119967120703, 1.432578483500734, 1.3912014593380737, 1.3391194523786791, 1.2772100315889576, 1.2065609485530004, 1.1284362788280895, 1.044238487388386, 0.955467440661821, 0.8636774593472603, 0.770433549862266, 0.6772679668872126, 0.5856382447399437, 0.49688779167425573, 0.41221006980803593, 0.33261728611092006, 0.25891439922328235, 0.1916791059295972, 0.13124831346840962, 0.07771143354360742, 0.03091065523889344, -0.009551828432159676, -0.04429984725215792, -0.07416291692298856, -0.10015008801014848, -0.12341868230879877, -0.14523875241667322, -0.16695421308019517, -0.1899416813848238, -0.21556812482644502, -0.2451484501328368, -0.27990417051605426, -0.32092426467160085, -0.36912928787675403, -0.42523971527733617, -0.4897493918770388, -0.5629048354829002, -0.6446909911154568, -0.7348238718575252, -0.8327503458889334, -0.9376551469333942, -1.0484750001160157, -1.163919571959778, -1.28249877655972, -1.4025558043320263, -1.5223050893404568, -1.639874299880761, -1.7533493281114767, -1.8608211708597022, -1.9604335374821018, -2.0504299933233248, -2.129199449667807, -2.195318843169221, -2.2475919088669305, -2.285083039638526, -2.307145339179678, -2.313442112595991, -2.3039611951142267, -2.2790216914599846, -2.2392728818979792, -2.185685241289403, -2.1195337101077123, -2.0423735464232977, -1.9560092707250452, -1.8624573865674152, -1.7639037151702563, -1.662656317396943, -1.5610950886172563, -1.461619198014091, -1.366593601742825, -1.2782958875143549, -1.1988647058914548, -1.130251010853285, -1.0741732697343875, -1.0320777119514255, -1.005104569158423, -0.9940611194263556, -0.9994021881062797, -1.0212185820785205, -1.0592337463806438, -1.112808737302468, -1.1809554086739784, -1.2623575130511646, -1.355399231569051, -1.458200469952116, -1.5686580978358056, -1.6844921680560594, -1.8032960353156575, -1.922589202478456, -2.039871659874422, -2.1526784499282754, -2.258633186928434, -2.35549928985841, -2.441227744198776, -2.5140002950197173, -2.572267086375352, -2.6147778981899203, -2.6406062881316332, -2.649166118549442, -2.6402201331567197, -2.613880440248575, -2.570600954125154, -2.5111620392898284, -2.436647788183747, -2.3484165381655253, -2.248065392890858, -2.1373896533254215, -2.018338180954416, -1.8929658075205567, -1.763383969651902, -1.631710781545375, -1.500021763688232, -1.3703024204104062, -1.244403804588111, -1.124002125511548, -1.0105633479192173, -0.9053135992554309, -0.8092160516535173, -0.7229547787943285, -0.6469259098289326, -0.5812362174580014, -0.525709089666829, -0.479897649215462, -0.4431046064039355, -0.41440826331933434, -0.39269393588010626, -0.3766899272853872, -0.3650070762282793, -0.3561808181487568, -0.3487146399560773, -0.3411237794281299, -0.3319780205623386, -0.3199424654396782, -0.3038152208675825, -0.2825610226735329, -0.25533992983985476, -0.22153035189400488, -0.18074582274164872, -0.13284509863339955, -0.07793533300327934, -0.016368262059141287, 0.0512704823574946, 0.12417863662782673, 0.2013606781119408, 0.28165667924072746, 0.3637758717422082, 0.4463340259233072, 0.5278936489628229, 0.6070059306938999, 0.6822533172996603, 0.7522915739582556, 0.8158902072767497, 0.871970157135618, 0.9196377343854855, 0.9582138740467829, 0.9872578909470799, 1.0065850631669218, 1.0162775247944185, 1.0166881194032305, 1.008437045107001, 0.9924013064990982, 0.969697173618992, 0.9416560286377318, 0.909794152665152, 0.8757771636040395, 0.8413799572862022, 0.8084431246197475, 0.7788269140662362, 0.7543638789520088, 0.7368113910548602, 0.7278052144518286, 0.7288153163522496, 0.7411050449010858, 0.7656947287838257, 0.8033306516686215, 0.8544602285228365, 0.9192140636858556, 0.9973954058458877, 1.0884773367780667, 1.191607843221758, 1.3056227292110356, 1.4290661342525222, 1.560218235703038, 1.6971295361608227, 1.8376609730460858, 1.97952894187497, 2.120354200653375, 2.257713523438273, 2.3891928989340183, 2.51244102684507, 2.6252218517192656, 2.7254648915701476, 2.811312166298397, 2.881160607731991, 2.9336989371507416, 2.967938124958956, 2.983234697616886, 2.9793063254003775, 2.956239306946293, 2.9144877584329834, 2.854864511978225], [2.803574424860651, 2.717689809551228, 2.617662625482897, 2.5054092861372137, 2.383066088043347, 2.2529424955678925, 2.11747063622496, 1.9791521857963246, 1.8405038827873368, 1.7040029420787268, 1.5720336373549726, 1.4468362910339048, 1.3304598497761617, 1.2247191347319886, 1.1311577406934525, 1.0510174201052287, 0.9852146298558856, 0.9343247448147, 0.8985742564725578, 0.8778410823453104, 0.8716629167269886, 0.879253360712163, 0.8995253838478544, 0.931121495849007, 0.972449848746355, 1.0217253514616564, 1.0770147634603189, 1.1362846445785229, 1.1974509764823393, 1.258429238917892, 1.317183721654401, 1.371774880762101, 1.420403604818805, 1.461451341295391, 1.493515143541958, 1.5154368316657267, 1.526325612785089, 1.5255736738159291, 1.5128644388747314, 1.4881733690763659, 1.45176137031264, 1.4041610598282717, 1.346156320446042, 1.2787557377037917, 1.2031606658236198, 1.1207287996107138, 1.0329342378428046, 0.9413251068025694, 0.8474798683057183, 0.7529634635577718, 0.659284441825549, 0.5678541913642801, 0.4799493301595818, 0.3966782273970071, 0.3189525154022371, 0.24746431895762386, 0.18266977779249705, 0.12477927251847813, 0.07375458854918888, 0.029313071072240737, -0.009061358462347116, -0.04210063297548017, -0.07072889720973186, -0.09603343036620997, -0.11923091455811617, -0.14162995194906552, -0.16459083254855103, -0.1894836280814713, -0.21764573325258796, -0.25033999290238634, -0.2887145415334167, -0.33376544074622455, -0.38630313126047294, -0.4469236211129283, -0.5159852126845416, -0.5935914313818992, -0.6795806615810426, -0.7735228247733259, -0.8747232550167846, -0.9822337423126573, -1.0948705300395507, -1.2112388727400223, -1.3297635899102236, -1.4487248943156479, -1.5662986337370435, -1.680599966502638, -1.7897293967283712, -1.891820027312669, -1.985084849204578, -2.0678628753673975, -2.1386629475468126, -2.1962040930333147, -2.2394513859607277, -2.2676463714771433, -2.2803312388706503, -2.277366078338019, -2.2589387219331587, -2.2255668482704967, -2.1780922183972535, -2.117667102270675, -2.045733146750935, -1.9639931222199585, -1.8743761612538616, -1.7789972648397214, -1.680111995406237, -1.5800673978471367, -1.4812502867017, -1.3860341072737503, -1.296725618943844, -1.2155126591974024, -1.1444142266354547, -1.0852340708834511, -1.0395188980385008, -1.0085221939776772, -0.9931745370382122, -0.9940611194263553, -1.0114070268939042, -1.045070642855091, -1.0945453506517784, -1.1589695107882019, -1.2371444934351088, -1.3275603551275632, -1.4284285670071442, -1.5377210346052694, -1.6532145000990761, -1.7725392908176656, -1.8932312756186127, -2.01278581606665, -2.128712453926294, -2.238589061411501, -2.340114196255759, -2.431156449562271, -2.509799649412397, -2.5743828854833724, -2.6235344469223305, -2.656198914305577, -2.671656813020148, -2.66953641574152, -2.649817471418278, -2.612826832657264, -2.559226147868264, -2.489991974221217, -2.4063888477618964, -2.309936013534557, -2.202368667230466, -2.085594687124437, -1.9616479378177734, -1.8326393031260697, -1.7007066525533836, -1.5679649631143266, -1.4364578054724264, -1.3081113608741357, -1.1846920643219547, -1.0677688717026794, -0.9586810266779499, -0.8585120601605274, -0.768070594760906, -0.6878783527425346, -0.6181655831393188, -0.558873936352327, -0.5096666274390353, -0.4699455471081497, -0.43887480667310774, -0.41541004419017735, -0.39833267765316316, -0.38628817092681317, -0.37782728203031285, -0.37144919377654523, -0.36564538531125323, -0.3589430907498751, -0.3499472081185131, -0.3373795676718732, -0.3201145421649457, -0.29721008088357276, -0.2679333716353803, -0.23178047733087762, -0.18848945260831432, -0.13804661713011931, -0.08068584135021341, -0.01688088316954863, 0.0526690046733656, 0.12705980099244552, 0.2052092154493826, 0.28588824893192655, 0.3677569705209875, 0.44940355552762046, 0.529385542529913, 0.6062722074728422, 0.6786869212508215, 0.7453483546014723, 0.8051094206976429, 0.8569929008963597, 0.9002227813327551, 0.9342504353937511, 0.9587749168957581, 0.973756777779982, 0.979424988598343, 0.976276715868429, 0.9650698931116949, 0.9468087074588338, 0.9227223064465613, 0.8942372054281948, 0.8629440404288302, 0.8305594601241316, 0.7988840801203317, 0.7697575295494303, 0.7450117014147479, 0.7264233720043721, 0.7156673795929027, 0.7142715478551531, 0.7235745049372485, 0.7446874857294858, 0.7784611140414425, 0.8254580452596761, 0.8859322114718193, 0.9598152533327768, 1.0467105499757676, 1.145895074267601, 1.2563291101909169, 1.376673676794424, 1.5053153137299422, 1.640397701573166, 1.7798594204084053, 1.921476996758846, 2.062912255684043, 2.201762885074183, 2.33561503560537, 2.462096724597788, 2.5789307865617506, 2.683986118218807, 2.775326001189689, 2.8512523505468503, 2.910344830504528, 2.951493897442987, 2.9739269723762516, 2.977227106448722, 2.961343680176932, 2.9265948656421013, 2.873661776110042, 2.8035744248606527], [2.745485734487182, 2.6507778669343587, 2.543139170351125, 2.424630643999815, 2.297504951688574, 2.1641572474999076, 2.0270729086883144, 1.8887733947615404, 1.7517614944755373, 1.6184672347720879, 1.4911957072968336, 1.3720780195320648, 1.2630264999808793, 1.1656951821736747, 1.0814464631226224, 1.0113246814098484, 0.9560371920640037, 0.9159433338880207, 0.8910514944028372, 0.8810242827372005, 0.8851916263910132, 0.902571418579426, 0.9318971634419684, 0.9716519011412853, 1.0201075477888017, 1.0753686597742111, 1.1354195314541249, 1.1981734616687945, 1.2615229799264371, 1.3233898083285591, 1.3817733506730585, 1.4347965451860687, 1.4807479907872967, 1.5181193567748203, 1.5456372097589184, 1.5622885364275412, 1.5673394026263299, 1.5603463642044675, 1.54116042871923, 1.5099235548066663, 1.4670578631218834, 1.413247914564382, 1.3494165835081235, 1.2766952116830297, 1.196388868295395, 1.1099376604772746, 1.0188751323101448, 0.9247848581812941, 0.8292563754789668, 0.7338416117012738, 0.6400129417643584, 0.5491239632035354, 0.4623740013453121, 0.3807772553556578, 0.30513737194712903, 0.23602808963464164, 0.1737804364403144, 0.11847679193670085, 0.06995194485832446, 0.02780109476655996, -0.008605434940147441, -0.040101180424033114, -0.06769678942551428, -0.09254826381265978, -0.11592104571863353, -0.13915090957929763, -0.16360270697210577, -0.19062806892044143, -0.2215231997812914, -0.2574878972078314, -0.29958690393356574, -0.3487146399560769, -0.4055642795175411, -0.47060202817884095, -0.5440473239866864, -0.6258595365227523, -0.7157315722644968, -0.8130906183291687, -0.9171060737482429, -1.026704532533818, -1.1405915006127414, -1.2572793538204734, -1.3751208809917594, -1.4923476089008973, -1.6071119781424121, -1.7175323342719069, -1.8217396193491326, -1.9179245975091004, -2.0043844257143415, -2.0795673880715926, -2.14211464894957, -2.190897945792487, -2.22505223544857, -2.244002425803867, -2.2474834646809216, -2.2355532169226695, -2.208597734453427, -2.1673287086310244, -2.1127730848435355, -2.0462550113653024, -1.9693704832294405, -1.8839552226286238, -1.7920465056416044, -1.695839796717157, -1.5976411835498825, -1.4998167124710589, -1.4047398055473987, -1.3147379931729546, -1.2320402186938513, -1.1587259638926959, -1.0966774060999291, -1.0475357501579048, -1.0126627830324149, -0.9931085778235378, -0.9895861301833035, -1.002453547171753, -1.0317042303208366, -1.0769653054510049, -1.137504356193993, -1.2122443209721145, -1.299786219166642, -1.398439186096685, -1.5062571227548147, -1.6210811092326876, -1.7405865942369467, -1.8623342603610262, -1.9838233785750687, -2.102546407809823, -2.216043567922558, -2.3219561173932353, -2.418077100703817, -2.5023983936522836, -2.573152966269361, -2.6288514002744474, -2.668311838233635, -2.6906827013106414, -2.6954576878031338, -2.682482751225439, -2.6519549499585655, -2.6044132557056483, -2.5407216003912274, -2.462044626029093, -2.369816774951476, -2.2657055144414393, -2.151569626447382, -2.029413606389819, -1.9013393023838663, -1.7694959854309762, -1.6360300709115532, -1.5030357113991115, -1.3725074505221067, -1.2462960681704252, -1.1260686603452172, -1.013273884630259, -0.909113167487037, -0.8145185157639406, -0.7301374058437393, -0.6563250439845943, -0.5931441051486579, -0.5403718696201266, -0.49751449168402845, -0.46382795717735353, -0.43834512124540526, -0.4199080682405833, -0.4072049060802131, -0.39881000072473255, -0.39322657535775596, -0.3889305453102802, -0.38441443504479816, -0.37823022814925483, -0.3690300350970756, -0.3556035255872635, -0.33691116096032264, -0.31211237519700286, -0.2805879874452501, -0.24195628144863482, -0.1960823537803729, -0.14308050918373602, -0.08330966309952204, -0.017361894010170662, 0.0539555330832625, 0.1296441804424647, 0.20854383944281887, 0.28936653043531274, 0.3707341899771714, 0.45121903755627896, 0.5293855425299131, 0.6038328682483646, 0.6732366553696794, 0.7363890205987129, 0.7922356901728143, 0.8399092583114789, 0.8787576577904902, 0.9083670503772896, 0.9285784860611092, 0.9394978382934903, 0.9414986938528128, 0.9352180561555034, 0.9215449053237427, 0.9016018424373364, 0.8767202244995076, 0.8484093662041979, 0.8183205403081608, 0.7882066463256336, 0.7598785338552221, 0.7351590591231545, 0.7158360188911917, 0.7036151430007372, 0.700074334482867, 0.7066203240664909, 0.7244488545137494, 0.7545094306851383, 0.7974755654713986, 0.853721322266976, 0.9233048046378658, 1.0059590769100777, 1.1010908196565679, 1.2077868359009631, 1.3248283319143512, 1.4507127054892464, 1.5836823892527665, 1.7217601215173275, 1.862789856708397, 2.004482385547259, 2.144464615446198, 2.2803313669956857, 2.409698475378414, 2.5302559477475404, 2.6398199200543155, 2.736382179759525, 2.818156073818507, 2.883617703059922, 2.9315414126417956, 2.9610287210636086, 2.9715299840398033, 2.962858260679147, 2.9351950337187787, 2.889087628557714, 2.825438372832561, 2.7454857344871844], [2.6810898974638095, 2.5783542020906958, 2.4639971281369997, 2.340206835779186, 2.209333317739443, 2.0738371819756125, 1.9362360643501777, 1.799049919704219, 1.6647464645960062, 1.5356880391231809, 1.4140811189000884, 1.3019296423222853, 1.2009932243573038, 1.1127512085761122, 1.0383733669311608, 0.9786978953947139, 0.9342171769619866, 0.9050715960322006, 0.891051494402837, 0.8916071637916071, 0.9058665777110496, 0.932660381349179, 0.9705534863406536, 1.0178824621180491, 1.0727977806679556, 1.1333098602302203, 1.197337768431799, 1.262759388548475, 1.3274618253461525, 1.3893908298445174, 1.4465980551998792, 1.4972850178113812, 1.5398427270891035, 1.5728860617826315, 1.5952821074357884, 1.6061718249453012, 1.6049845904386857, 1.5914453274713656, 1.565574139344129, 1.5276785374896211, 1.4783385466775565, 1.4183851446434885, 1.3488726582641328, 1.2710458865092065, 1.1863028484396876, 1.096154159347887, 1.0021801171850302, 0.9059866327858789, 0.8091611598625446, 0.7132297738122146, 0.6196165123146116, 0.5296060264634747, 0.44431050046614234, 0.36464168310272954, 0.2912887381106497, 0.22470246692936094, 0.16508628972336165, 0.11239419356070467, 0.06633567455735474, 0.026387518325574247, -0.008187915184866211, -0.0383184058711646, -0.06509224657423472, -0.08972407443559685, -0.11351707877846563, -0.13782259912759717, -0.16399819634036805, -0.1933653214143711, -0.22716771929114885, -0.2665316885442841, -0.31242927261079595, -0.3656453853112526, -0.4267497746179347, -0.49607460643669504, -0.5736983076236071, -0.6594361481344835, -0.7528378701029639, -0.8531924910869406, -0.9595402242583961, -1.070691274588343, -1.185251091735563, -1.3016514918976352, -1.4181869065973696, -1.5330548801828796, -1.6443998231946446, -1.7503589386451517, -1.8491091750055986, -1.9389140249726822, -2.018168983860961, -2.08544450596208, -2.139525350920298, -2.1794452938534543, -2.2045162806594796, -2.2143512410981, -2.2088799236439245, -2.188357284078051, -2.1533641402086663, -2.104799993555977, -2.0438681106639343, -1.972053147176684, -1.8910917822311186, -1.8029370044973996, -1.7097168500293474, -1.613688532009222, -1.5171890199879678, -1.4225832183808393, -1.3322109584463064, -1.2483340530988554, -1.1730846687494403, -1.108416242738786, -1.0560581193877656, -1.017474993528669, -0.9938321396016115, -0.9859672696564115, -0.9943697081394627, -1.019167398926206, -1.060122074861496, -1.116632726588201, -1.187747310381229, -1.2721824388529237, -1.3683506085231856, -1.474394338975494, -1.5882264340126147, -1.707575429882159, -1.8300351727966875, -1.953117370611118, -2.07430589400062, -2.1911115624846964, -2.301126141121025, -2.4020742948558502, -2.4918622988223613, -2.568622383044098, -2.6307516970413567, -2.676945011110526, -2.7062204233167715, -2.71793751076296, -2.711807546309907, -2.6878955931447224, -2.646614484741912, -2.5887108920619255, -2.515243868539102, -2.427556441925482, -2.327240986037514, -2.216099250923029, -2.0960980534134586, -1.9693217284868114, -1.8379225129984338, -1.704070075475653, -1.5699014178735873, -1.4374723572500616, -1.3087117477780192, -1.1853795276472865, -1.0690295731829351, -0.9609782165441816, -0.8622791368649457, -0.773705171358572, -0.6957374168452196, -0.628561807790635, -0.572073168883099, -0.5258865531182357, -0.48935549496920006, -0.4615966370021289, -0.4415200314992317, -0.42786428015170674, -0.41923555809403396, -0.41414947633286214, -0.4110746712207987, -0.4084769726055847, -0.4048629945028745, -0.3988220137163409, -0.3890650521467097, -0.37446015625544976, -0.35406297025814754, -0.3271418254605665, -0.2931967134934338, -0.2519716723398362, -0.2034602868780818, -0.14790418578961395, -0.08578459953191313, -0.017807225011635827, 0.05511918297467686, 0.1319099099582921, 0.21133633766433066, 0.29206209591542703, 0.3726823414869534, 0.4517651122098053, 0.5278936489628232, 0.5997085509341199, 0.6659486313718618, 0.7254893719697857, 0.7773779332879336, 0.8208637647276799, 0.8554239684169372, 0.8807827041470031, 0.8969240739120348, 0.9040980908378493, 0.9028195141732188, 0.8938595151048797, 0.878230322835112, 0.8571631819690276, 0.8320801262072822, 0.8045602352229096, 0.776301187306529, 0.7490770461781481, 0.7246933230624875, 0.7049404320567128, 0.6915467059718637, 0.6861321598793163, 0.6901641799423175, 0.7049162759013123, 0.7314309676886874, 0.7704877816692376, 0.8225772122104593, 0.8878813625777606, 0.9662618189714998, 1.0572551367899763, 1.1600761331994356, 1.273628989368393, 1.3965259739800295, 1.5271134116097023, 1.6635043399005662, 1.8036171326458803, 1.9452192160432487, 2.0859748762618064, 2.2234960512949824, 2.3553949215081844, 2.4793370633337877, 2.593093910513028, 2.6945932777007706, 2.781966741951298, 2.853592747661333, 2.9081343983098624, 2.9445710214673486, 2.9622227390902185, 2.960767439555588, 2.940249727245348, 2.9010816154073518, 2.8440349238910847, 2.770225540413607, 2.6810898974638118], [2.610931731711199, 2.5010315519968986, 2.380906076329836, 2.252852125095082, 2.1192971581172833, 1.982746447619638, 1.8457286240177904, 1.7107408618236806, 1.5801949796762738, 1.4563657045852083, 1.341342296477322, 1.2369846464182646, 1.1448848524875879, 1.066335143913358, 1.0023028700036456, 0.9534130994333022, 0.919939191751267, 0.9018015110690173, 0.8985742564725578, 0.9095001895460018, 0.933512851243408, 0.9692656827809791, 1.0151673025600023, 1.069422047313868, 1.1300747641710576, 1.1950587440551348, 1.262245618090188, 1.3294959990506967, 1.3947096402715677, 1.455873904957939, 1.5111093889010523, 1.5587116178832716, 1.5971878455144402, 1.6252881052122423, 1.642029818273649, 1.6467154247407318, 1.6389426808986223, 1.6186074523149445, 1.5858990197102119, 1.541288101937512, 1.485507981292211, 1.4195292867744993, 1.3445291465677631, 1.2618555580296407, 1.1729879385484532, 1.079494910879211, 0.9829904398500001, 0.8850894721094629, 0.7873642360737553, 0.691302335366099, 0.598267716498943, 0.5094655117208858, 0.4259116529133377, 0.34840802488091177, 0.27752377960163416, 0.21358327073477099, 0.15666089405701045, 0.10658293892515766, 0.06293637292940692, 0.025084301245624982, -0.007812331602562947, -0.03676739239630657, -0.06293730426698409, -0.08758475615511141, -0.11203935238573368, -0.13765625870145295, -0.16577395463432132, -0.19767222716854077, -0.2345315365929327, -0.277394852344676, -0.3271329953148599, -0.3844144350447976, -0.4496803776865586, -0.5231258463479562, -0.6046873028565121, -0.6940371928892678, -0.7905856190259389, -0.8934891630568061, -1.0016666944322559, -1.1138218207342236, -1.228471463058421, -1.3439798786047532, -1.4585973086628319, -1.5705023062262993, -1.6778466968516565, -1.7788020516951675, -1.8716065048720496, -1.954610729649248, -2.0263219000449326, -2.08544450596208, -2.1309169600919953, -2.1619430318340043, -2.178017265063598, -2.178943679799768, -2.164847219185133, -2.136177578752434, -2.093705240399675, -2.0385097242694545, -1.9719602631198663, -1.8956892910525827, -1.8115593169879325, -1.7216239186128373, -1.628083740558164, -1.533238507589217, -1.4394361664292397, -1.3490203458850358, -1.2642773722645753, -1.187384094432606, -1.1203577597408285, -1.0650091387420437, -1.0229000240449864, -0.9953061285994748, -0.9831862835104792, -0.987158688174872, -1.0074847996725864, -1.0440612679407686, -1.0964201326918466, -1.1637373019341462, -1.2448491350858666, -1.3382767608310497, -1.4422575757450453, -1.5547831988005374, -1.6736430033157697, -1.7964722154618622, -1.9208034603277433, -2.044120555375399, -2.163913298870965, -2.277731978806536, -2.383240336452133, -2.478265757764126, -2.560845534447125, -2.629268132820765, -2.68210853040233, -2.7182568242813288, -2.7369394783881056, -2.737732754641624, -2.7205680613391054, -2.6857291464073936, -2.6338412585206377, -2.5658525908279213, -2.4830085054521605, -2.3868192075539802, -2.2790216914599846, -2.1615369144157808, -2.0364232627377334, -1.9058274578943564, -1.7719341043961012, -1.636915106063882, -1.5028801717677438, -1.3718295963110316, -1.2456104377532633, -1.1258771208025926, -1.0140573793229823, -0.9113243124605159, -0.8185751719033795, -0.736417326306338, -0.6651616672384465, -0.6048235337018643, -0.5551310439981553, -0.5155405391789406, -0.4852586660987457, -0.4632704645608422, -0.448372676257177, -0.4392113667705531, -0.4343228489346573, -0.4321768188463661, -0.43122056665208425, -0.429923104042682, -0.42681805961938835, -0.42054423162734755, -0.40988275395722784, -0.39378992404825736, -0.37142485799047936, -0.3421712757241302, -0.3056528742520505, -0.2617419152655263, -0.2105608312488819, -0.1524768364609288, -0.08808971156524728, -0.018213108472157177, 0.05615010934296973, 0.1338378204429696, 0.21356308431534407, 0.29395213966855044, 0.37358494280701215, 0.45103715944952893, 0.5249224839233103, 0.5939341491208611, 0.6568845092382583, 0.7127416246742383, 0.7606618533894582, 0.8000175536388657, 0.8304191267828105, 0.8517307727540574, 0.8640794910991001, 0.8678570332951006, 0.863714692922179, 0.8525510046887999, 0.8354926066137289, 0.813868697230191, 0.7891796870013107, 0.7630607959743886, 0.7372414841643008, 0.713501713805267, 0.6936261305469235, 0.679357311609172, 0.6723492612351011, 0.6741223365884563, 0.6860207603630631, 0.7091738203781854, 0.7444617726251606, 0.7924873546021719, 0.8535536829685879, 0.9276491567934061, 1.01443981869319, 1.1132694450941585, 1.2231674481606425, 1.3428644802576444, 1.4708154418925232, 1.6052294106103018, 1.7441058358510164, 1.8852761876039599, 2.0264501087332776, 2.165265005555275, 2.2993379215209866, 2.426318476973858, 2.543941625505567, 2.650078975294753, 2.7427874521102, 2.8203541387707323, 2.881336212422179, 2.9245950139609262, 2.949323420594559, 2.955065849590013, 2.941730394920047, 2.9095927845706524, 2.859292040198063, 2.7918179179102744, 2.7084904043995373, 2.610931731711202], [2.5356048070585513, 2.4194641012616596, 2.2945690028270547, 2.16330557232835, 2.028158219474326, 1.8916557132636644, 1.7563163215914508, 1.6245933557098993, 1.4988223835387466, 1.3811713340021283, 1.2735946433809258, 1.1777924958732968, 1.0951760865870779, 1.0268396890959675, 0.9735401450661701, 0.9356842143409483, 0.9133240346475895, 0.9061607453969901, 0.9135561346408008, 0.9345519769058159, 0.9678965470039225, 1.0120776254606247, 1.0653611590268162, 1.1258346085160567, 1.191453909099539, 1.2600928877501056, 1.329593930650045, 1.3978186712519503, 1.4626974777584285, 1.5222765567694285, 1.574761556701755, 1.618556648569279, 1.6522981804124637, 1.6748821420640414, 1.6854848354852316, 1.6835763186133759, 1.6689263731946373, 1.6416029348680246, 1.6019631121324684, 1.5506371050767116, 1.4885055103048002, 1.4166706609972557, 1.336422796493427, 1.2492019805819412, 1.1565567887844372, 1.0601008598516874, 0.9614684536587375, 0.8622701755874418, 0.7640500159510729, 0.6682448124144599, 0.5761471747903937, 0.488872816844178, 0.4073331212627684, 0.3322136247845759, 0.26395895419778337, 0.20276457448217225, 0.1485755321011331, 0.10109219387389923, 0.059782799604454984, 0.023902469332920978, -0.007481861800297443, -0.03546126227529794, -0.061250194290804236, -0.08614840857190885, -0.11150036877439908, -0.13865329561614, -0.168914958135259, -0.20351234781137315, -0.24355235046010446, -0.2899854813276178, -0.3435736718981709, -0.40486299450287394, -0.4741620854452359, -0.5515268821821493, -0.6367521287630508, -0.7293699302913283, -0.8286554559964826, -0.9336397061594484, -1.0431290752697064, -1.155731267034271, -1.2698869506824833, -1.3839063966364717, -1.4960101969007569, -1.604373064861675, -1.7071696234274267, -1.8026210318148956, -1.889041271357658, -1.9648819103143949, -2.0287741969061033, -2.0795673880715926, -2.1163623073464106, -2.1385392367906864, -2.145779382323807, -2.138079305899559, -2.115757887909295, -2.0794555648644573, -2.0301257763147964, -1.9690187464463105, -1.8976579151402255, -1.8178095157708465, -1.73144596814469, -1.6407039104761119, -1.547837830273584, -1.4551703670677865, -1.3650404471983828, -1.2797504701725422, -1.2015137958816013, -1.132403781404693, -1.0743055851774335, -1.0288718956442198, -0.9974836525624006, -0.9812167139991483, -0.980815283518853, -0.996672753439129, -1.0288204451736582, -1.0769245408189698, -1.1402913058175856, -1.21788050546635, -1.3083267230320337, -1.4099680990345362, -1.520881834446232, -1.6389256394413207, -1.761784167836527, -1.8870193589395392, -2.0121235160444724, -2.1345738865313524, -2.251887473993076, -2.3616748088570616, -2.4616914306662836, -2.5498858918648204, -2.624443178189453, -2.683822552496654, -2.726788964302814, -2.752437323153618, -2.760209106341203, -2.7499009562259706, -2.721665114969402, -2.676001740133179, -2.6137433385685265, -2.5360317435755757, -2.444288236888792, -2.3401775783511805, -2.225566848270499, -2.1024801269762907, -1.9730501301524814, -1.8394679848731585, -1.7039323683737402, -1.5685992386248646, -1.4355333626635383, -1.3066627960432615, -1.1837373860843168, -1.0682922649234021, -0.9616171684006156, -0.8647322668764571, -0.778371027922183, -0.7029704526493274, -0.6386688417007804, -0.5853110582587673, -0.542461068536754, -0.5094213597617927, -0.48525866609874546, -0.4688352785149311, -0.4588450790437306, -0.45385332660971006, -0.45233913329449266, -0.4527395087901125, -0.45349381826014235, -0.45308749564512657, -0.45009388060867356, -0.4432131020893293, -0.431307013351193, -0.4134292903833371, -0.3888499347307567, -0.35707357003756035, -0.31785108496460396, -0.27118434954946835, -0.21732391307436244, -0.1567597745038532, -0.09020549690864714, -0.018576110433994292, 0.05703959008456577, 0.13541160090140714, 0.21520524011157716, 0.2950206710692768, 0.37343435752174814, 0.4490413380852043, 0.5204971848120767, 0.5865585168608756, 0.6461209755436825, 0.698253630422613, 0.7422288760774421, 0.7775469934238661, 0.8039546851631574, 0.8214570486841893, 0.8303226176552495, 0.8310812814113258, 0.8245150745826106, 0.811642013597698, 0.7936933370778634, 0.7720846791526994, 0.7483818640099505, 0.7242621524933919, 0.7014718936447812, 0.6817816326168907, 0.6669397988152771, 0.6586261425560124, 0.6584061037503194, 0.6676872816677062, 0.6876791309496636, 0.7193569367442744, 0.7634310228168982, 0.8203220231420084, 0.8901429027861573, 0.972688251379716, 1.0674311961244916, 1.1735280954276013, 1.2898309834664632, 1.4149075449863697, 1.5470682131369247, 1.684399805791598, 1.8248049519757832, 1.9660464138354676, 2.105795284668928, 2.2416819430546404, 2.3713485695832524, 2.4925019880201913, 2.602965578063882, 2.700729022658626, 2.783994698758986, 2.8512195954702415, 2.9011517458351066, 2.9328602857561914, 2.9457584025763235, 2.939618603086692, 2.9145799121451597, 2.871146804262514, 2.8101798668071827, 2.7328783901143447, 2.6407552719764973, 2.535604807058554], [2.4557464233742476, 2.3343419474278906, 2.2057163583384574, 2.072324781835671, 1.936687578472329, 1.8013356477393687, 1.6687556256092106, 1.5413362482467885, 1.421317125168265, 1.3107411057749132, 1.211411335412255, 1.1248539830657447, 1.0522874853087634, 0.9945989935435934, 0.9523285377869863, 0.9256612345079442, 0.914427672873444, 0.9181124179211275, 0.9358703754388858, 0.9665505764139223, 1.0087267633676602, 1.0607340009804227, 1.1207103930024067, 1.1866428699298701, 1.2564159201129275, 1.3278620730311899, 1.3988129089116546, 1.4671493644290514, 1.530850129936751, 1.5880369887971204, 1.6370160324594587, 1.676313793829614, 1.7047074734122287, 1.7212485843447072, 1.7252795099613072, 1.7164426467213263, 1.694681991722131, 1.6602372229426339, 1.6136305071199213, 1.5556464501101896, 1.4873057732634805, 1.4098334525793759, 1.3246221914309184, 1.2331922091571244, 1.1371484141098231, 1.0381360887129178, 0.9377962443532287, 0.8377218047942415, 0.7394157483465402, 0.6442522820351163, 0.5534420369814769, 0.4680021653503089, 0.38873208829907957, 0.3161954947665854, 0.2507090264601674, 0.19233790923737681, 0.14089860967654444, 0.09596841259465352, 0.056901635239836205, 0.022852021420228748, -0.007199301702136158, -0.034411065959993055, -0.060045190359519614, -0.08542718383649786, -0.11190468798970658, -0.14080527448819571, -0.1733946325322428, -0.21083627327954507, -0.2541538407253831, -0.3041970530745896, -0.3616122067973431, -0.42681805961938774, -0.49998777156822916, -0.5810374283245019, -0.6696215024065545, -0.7651354293939977, -0.8667252929670262, -0.9733044286318908, -1.0835765762669216, -1.1960650406085458, -1.309147160841728, -1.4210932495832873, -1.5301090413471266, -1.6343805941442586, -1.7321205176943486, -1.8216143596543115, -1.9012659684486342, -1.9696406681319325, -2.0255051269033504, -2.0678628753673975, -2.095984531631827, -2.1094319154199046, -2.108075379515895, -2.0921038504920078, -2.0620272477721797, -2.0186711363186176, -1.9631636589902242, -1.8969149852039549, -1.8215896982111164, -1.73907271947136, -1.651429530884309, -1.5608615999727808, -1.4696580358883036, -1.3801446022399784, -1.2946312837445257, -1.2153596457368623, -1.1444512375544267, -1.083858272342208, -1.0353177672949008, -1.0003102508742105, -0.9800240389437901, -0.9753259525507418, -0.9867391993595527, -1.0144289721518847, -1.058196135427249, -1.1174791794014642, -1.1913644242621368, -1.2786042611828512, -1.3776430251017697, -1.4866499123014811, -1.603558187820262, -1.7261097777751344, -1.851904213438722, -1.9784507905083186, -2.1032227309527287, -2.2237120879668, -2.337484118036666, -2.442229858309496, -2.5358156920068993, -2.6163287584149715, -2.682117165205023, -2.7318240869951564, -2.7644149820538853, -2.779197325240088, -2.775832435593954, -2.7543391670244213, -2.715089425630665, -2.6587956725808595, -2.5864907623827835, -2.49950064816673, -2.399410653842157, -2.2880261636057155, -2.1673287086310244, -2.039428535749789, -1.9065148210360334, -1.7708047405929708, -1.634492630389236, -1.499700456310407, -1.3684307750407707, -1.2425232970653197, -1.123616066786174, -1.0131121539478891, -0.9121526083297041, -0.8215962695807877, -0.7420068501720196, -0.6736475260735562, -0.6164830815244066, -0.5701894658330854, -0.5341704362245263, -0.5075807858936209, -0.4893554949691996, -0.4782439980202369, -0.47284863859250365, -0.4716662820633783, -0.4731319852553969, -0.47566357650245694, -0.4777059842576074, -0.4777741661779585, -0.47449353349273166, -0.4666368362004004, -0.4531565713995476, -0.43321209733458266, -0.4061907764448224, -0.3717226282476002, -0.3296881432487145, -0.28021908792487, -0.22369231362195152, -0.1607167643244925, -0.09211405506070407, -0.01889315973628982, 0.05778009978989659, 0.13661793643878284, 0.21624891167190985, 0.2952586498584401, 0.37223185965081534, 0.4457945336686928, 0.5146551916620734, 0.5776440553405937, 0.6337490946537434, 0.6821479642021705, 0.722234952680962, 0.753642195190144, 0.7762545447093727, 0.7902176613420419, 0.795939052004972, 0.7940819746886734, 0.785552305663696, 0.7714786504077344, 0.753186154962174, 0.7321646394369662, 0.710031825276928, 0.6884925588603497, 0.6692950426696844, 0.6541851688533681, 0.6448601063097006, 0.6429223199683848, 0.6498351989391908, 0.6668814385935898, 0.6951252611365349, 0.7353794712272107, 0.7881782298235975, 0.853756293397569, 0.9320353103067003, 1.0226175952160677, 1.124787620233472, 1.2375212723411422, 1.359502735442627, 1.489148666627116, 1.624639154763734, 1.7639547797853574, 1.9049189372356845, 2.045244458677553, 2.182583447757682, 2.31457916688961, 2.438918752813991, 2.553385512195352, 2.6559095516614444, 2.7446155302845403, 2.8178663856939905, 2.8743019763193693, 2.9128716995208115, 2.932860285756192, 2.9339061290782666, 2.916011690275633, 2.8795456966009345, 2.8252370567113423, 2.754160606445109, 2.66771499557889, 2.567593213015283, 2.4557464233742508], [2.3720322187205896, 2.2463852624352394, 2.1150998764426996, 1.980679492273892, 1.8456591181251076, 1.7125503996713842, 1.583787339180749, 1.4616739322377572, 1.3483349341221746, 1.2456708915044077, 1.1553184714949947, 1.0786169917689117, 1.0165819056267742, 0.9698858281296893, 0.938847507962038, 0.9234289588791279, 0.9232407691500375, 0.9375554120836824, 0.9653281902923516, 1.0052252654389509, 1.0556580582282997, 1.1148231543862126, 1.1807467249215269, 1.251332366147695, 1.3244111892024024, 1.3977929419250013, 1.469316928996979, 1.5369015095452252, 1.598590994529678, 1.6525988380291234, 1.6973461151387814, 1.7314944020799676, 1.75397231817948, 1.7639951509714888, 1.7610771607485116, 1.745036345056606, 1.7159916322938102, 1.6743526620295484, 1.6208024932314202, 1.5562737557122088, 1.4819189204865086, 1.399075507397947, 1.309227169838901, 1.2139616936659483, 1.114927018156748, 1.0137864293659078, 0.9121740895359968, 0.8116520500550366, 0.7136698503112244, 0.6195277318918214, 0.5303443988122484, 0.4470301323949942, 0.3702659271782076, 0.30048915545518, 0.23788609677310726, 0.18239148930647608, 0.1336950770208034, 0.09125494459558044, 0.05431725578981702, 0.021941844772222788, -0.006967041894369439, -0.03362568858643865, -0.059332487351659385, -0.08542718383649785, -0.1132488893081381, -0.14409398860258102, -0.17917507775279856, -0.2195820398494817, -0.2662463139838953, -0.31990933125780224, -0.3810959858445993, -0.45009388060867284, -0.5269389390646817, -0.6114078122009752, -0.7030173340124382, -0.8010310978907942, -0.9044730418900014, -1.0121477489735253, -1.122666993262762, -1.234481899481369, -1.3459199343927606, -1.455225819842027, -1.5606053503480217, -1.6602710167977577, -1.7524882837965152, -1.835621343065315, -1.9081771696758494, -1.9688467418573625, -2.016542347848169, -2.0504299933233248, -2.069956038151839, -2.074867328831669, -2.0652242495648716, -2.0414062867339946, -2.004109884302739, -1.9543385568856815, -1.8933854182392282, -1.822808470989822, -1.7443991838690196, -1.660145051079623, -1.5721869804738628, -1.4827724891787588, -1.3942057938395822, -1.3087959650257819, -1.2288043694510067, -1.156392648089903, -1.0935724723476012, -1.0421582842189139, -1.0037241606747105, -0.9795658488710624, -0.9706688994209336, -0.9776836827617088, -1.0009079120239626, -1.0402771186680473, -1.0953633388011625, -1.1653820730946571, -1.2492073863326096, -1.345394818632475, -1.4522115940135805, -1.5676734377927295, -1.6895871565061062, -1.815597996540402, -1.9432406837567644, -2.069992958883934, -2.1933303644715125, -2.3107810101621014, -2.419979044660193, -2.5187155949938864, -2.6049859956814285, -2.677032220697817, -2.7333795474659066, -2.7728666216134683, -2.7946682505194, -2.7983104288140432, -2.7836772857112435, -2.751009837765308, -2.7008966266302306, -2.6342565148677632, -2.552314099089873, -2.456568374199053, -2.348755440972173, -2.2308061878851175, -2.1047999935559765, -1.9729155857292302, -1.8373802542110929, -1.7004186471708844, -1.5642023820477775, -1.4308016739959522, -1.302140127154997, -1.179953748562022, -1.0657551334253048, -0.9608036365841974, -0.8660821916714166, -0.7822812706298904, -0.7097902960516341, -0.6486966318066345, -0.5987920882795907, -0.5595866919393405, -0.5303292895623883, -0.5100343896622195, -0.49751449168402784, -0.49141702105225066, -0.4902648784530292, -0.49249952746796366, -0.4965254878809056, -0.5007550739972917, -0.5036522187640108, -0.5037742552376214, -0.4998105861671947, -0.49061725857061794, -0.4752465709541623, -0.4529709734033619, -0.423300671764953, -0.3859945126930184, -0.3410639022349672, -0.2887696924168095, -0.22961215334128157, -0.16431432799840573, -0.09379923875581901, -0.019161573998479862, 0.0583653734117705, 0.13744662091057727, 0.21668526906267496, 0.2946640626277973, 0.3699876228703384, 0.4413242156345542, 0.5074459303788821, 0.5672661849383175, 0.6198735382791111, 0.6645608872370327, 0.7008492408393059, 0.7285054043478016, 0.747553061144155, 0.7582769100805171, 0.7612196946724141, 0.7571721440043986, 0.7471560288213431, 0.7324007153456255, 0.7143137693570687, 0.6944463196830152, 0.6744540294835192, 0.6560546420233271, 0.6409831619584547, 0.6309458010856847, 0.6275738572199661, 0.632378705291441, 0.6467090605347958, 0.671711625163163, 0.7082961532928835, 0.7571058659349879, 0.8184940210757403, 0.8925072963133116, 0.9788764768060622, 1.077014763460319, 1.1860238297180852, 1.3047075646008428, 1.4315932495405808, 1.5649597316963035, 1.7028719815055366, 1.8432212615125463, 1.9837699910634299, 2.122200270833319, 2.25616493539277, 2.3833399335601597, 2.5014767968872107, 2.6084539473347093, 2.702325616324199, 2.78136719845911, 2.844115943116628, 2.8894059939312347, 2.916396917367774, 2.924595013960928, 2.9138668756973973, 2.8844448363214674, 2.8369241536040386, 2.77225195915582, 2.6917082074035097, 2.5968790461084525, 2.489623211640916, 2.3720322187205927], [2.2851704531500565, 2.156338199639598, 2.023486213581045, 1.889145064262672, 1.7558429803980473, 1.6260511324341476, 1.5021303324578383, 1.386280386923851, 1.2804932727615432, 1.186511214647948, 1.105790622640194, 1.0394727078516457, 0.9883614329021784, 0.9529092774164925, 0.9332111112038799, 0.9290062735164356, 0.9396887606948989, 0.9643252313559844, 1.0016803527577245, 1.0502488386112538, 1.108293371594667, 1.1738874669645614, 1.2449622202493906, 1.3193557947591974, 1.3948644456232573, 1.4692938476366202, 1.540509494992663, 1.6064849718895835, 1.665346953169663, 1.7154158820063656, 1.7552413849405823, 1.7836316204050326, 1.79967591183489, 1.802760186647683, 1.7925749235225643, 1.7691154979925026, 1.7326750057077167, 1.6838298291267844, 1.6234183922191017, 1.5525137145935168, 1.4723905271859568, 1.3844878425372305, 1.2903679805663706, 1.191673132971376, 1.090080603990271, 0.9872578909470798, 0.8848187642309523, 0.7842814732916197, 0.6870301437926564, 0.594280342866774, 0.5070496767534203, 0.426134150866989, 0.3520908699792682, 0.28522748958813327, 0.22559865292419717, 0.17300946590289162, 0.12702587927981335, 0.08699166794882073, 0.05205152627398961, 0.021179639895204844, -0.006787047400069755, -0.03311177480260231, -0.05911811505717184, -0.08614840857190885, -0.11552160017828167, -0.14849161394972804, -0.18620738861467898, -0.22967565437849696, -0.27972746243996754, -0.33698938289393876, -0.40186016745268915, -0.47449353349273093, -0.5547875688620308, -0.6423810866212187, -0.7366570797335299, -0.8367532421832599, -0.9415793397284685, -1.0498410351174583, -1.1600696036408273, -1.2706568196428496, -1.3798941570314693, -1.4860153304231372, -1.5872411113295575, -1.6818252881309737, -1.7681006012161833, -1.844523476630017, -1.909716403149567, -1.9625068484662234, -2.001961688907069, -2.027416232009936, -2.038497039739314, -2.035137909069169, -2.0175885324204805, -1.986415538955821, -1.9424958046038308, -1.8870021092984746, -1.8213814095535759, -1.7473261784477434, -1.6667394387943757, -1.5816942743854074, -1.4943887447474873, -1.4070972473070915, -1.3221194642376812, -1.2417280971816549, -1.1681166297997638, -1.1033483647146276, -1.049307957637679, -1.0076566178037927, -0.9797920615251381, -0.9668141966626701, -0.9694973827074436, -0.9882699571675788, -1.0232015477915268, -1.0739985059716706, -1.1400076039365037, -1.2202279417415982, -1.3133308143956488, -1.417687099476126, -1.5314015459318095, -1.652353179819062, -1.7782408965001322, -1.906633184912489, -2.0350208309215434, -2.160871375898624, -2.2816840652470898, -2.395044010636348, -2.498674309455045, -2.590484914967696, -2.6686171296208654, -2.731482699953817, -2.7777966220216843, -2.8066029179367624, -2.817292813358382, -2.809614928370472, -2.783677285711243, -2.7399411360807018, -2.679206795469959, -2.602591879372237, -2.5115024987263705, -2.407598148137386, -2.2927511643014635, -2.169001758076316, -2.038509724269454, -1.9035040065692377, -1.7662313393967446, -1.6289052028073174, -1.4936563106570335, -1.362485806556932, -1.2372222678841913, -1.1194835172267468, -1.0106441156803132, -0.9118092665590961, -0.8237956949977836, -0.7471198927051295, -0.6819939321870416, -0.6283288657044679, -0.5857455357744491, -0.5535924408424828, -0.5309701263892405, -0.5167614124694375, -0.5096666274390345, -0.5082428978752606, -0.5109464493551491, -0.5161768041401927, -0.5223217215531273, -0.5278017158517789, -0.5311130048946234, -0.5308677903054971, -0.5258308449103398, -0.5149514839754659, -0.497390120622967, -0.47253874955714037, -0.4400348632344249, -0.3997684767733053, -0.35188211785474915, -0.2967638210420925, -0.23503334770956935, -0.16752202850899547, -0.09524679057737705, -0.019379082314447457, 0.058790459270507175, 0.13789064327117512, 0.2165106205028926, 0.29324193985437363, 0.36672063443900876, 0.4356682048961992, 0.4989303945751861, 0.5555127071336902, 0.6046116999054755, 0.6456411941565678, 0.678252673351799, 0.7023492895218928, 0.7180930620060346, 0.7259050281086409, 0.7264582871312962, 0.7206640632279778, 0.709651093932152, 0.6947388254249636, 0.6774050582347214, 0.6592488339436974, 0.6419494808812712, 0.6272228414370891, 0.6167757828331797, 0.6122601448810874, 0.6152273010354897, 0.6270845022763883, 0.6490541370826298, 0.6821369758123624, 0.72708037571117, 0.7843523057370728, 0.8541219112612823, 0.9362471808695403, 1.0302701048197889, 1.135419531454125, 1.2506217385363922, 1.3745185457720446, 1.5054926073897281, 1.6416993442785515, 1.7811048082473397, 1.9215286206692646, 2.0606909978631274, 2.196262769309029, 2.325917214892795, 2.447382495865662, 2.5584934324422157, 2.657241389558233, 2.74182107114159, 2.8106730914392584, 2.8625212878930437, 2.8964038614821965, 2.911697574437828, 2.9081343983098655, 2.8858101835851824, 2.845185111092812, 2.7870758806946947, 2.7126397894972962, 2.623351045238309, 2.520969845889185, 2.407504929346851, 2.2851704531500596], [2.195896016504772, 2.064962597938978, 1.931650462796958, 1.7984959204827866, 1.6679990504585847, 1.5425696689698514, 1.424475460667571, 1.3157934758143937, 1.218366112240183, 1.133762592841799, 1.0632468168607723, 1.0077523096688776, 0.9678648251041356, 0.9438129707050131, 0.9354670339795849, 0.9423459918142717, 0.9636324900567573, 0.998195390953508, 1.0446193070910066, 1.101240376128394, 1.1661873848979318, 1.2374272279041498, 1.3128135868376811, 1.3901376467773718, 1.46717962294571, 1.5417598601491975, 1.6117882855753798, 1.675311043883817, 1.730553220239196, 1.7759566601117625, 1.8102120216844304, 1.832284344345418, 1.8414315812950226, 1.83721572163009, 1.8195063129574962, 1.7884763849992382, 1.7445909630754557, 1.688588543112232, 1.6214560723938214, 1.544398138403416, 1.4588012078807944, 1.3661938762429409, 1.2682041808884523, 1.1665150983825718, 1.0628193835173712, 0.958774916895758, 0.8559617068686016, 0.7558416419687362, 0.6597220127625878, 0.5687237192956996, 0.4837549546945921, 0.4054910102255597, 0.3343606859104716, 0.2705396177646631, 0.21395065224853083, 0.16427121519003177, 0.1209474408843094, 0.08321465190396064, 0.05012361578931219, 0.02057185538733613, -0.006660841054107317, -0.03287367255164393, -0.05940388716267295, -0.08758475615511137, -0.11870359243776256, -0.15396094462925175, -0.19443206858583562, -0.24103172032026268, -0.29448322947737204, -0.355292703017346, -0.42372907724930886, -0.499810586167194, -0.5832980489505427, -0.6736952036680708, -0.7702561320988706, -0.8719996367662257, -0.9777302504119229, -1.0860653848065058, -1.1954679643924446, -1.3042837448990832, -1.4107823914608197, -1.5132012881346897, -1.6097909737010112, -1.6988610492550082, -1.7788253826833285, -1.8482454442701983, -1.9058706462580886, -1.9506746263254389, -1.9818865090525153, -1.9990162982617883, -2.001873693756182, -1.9905797850013638, -1.9655712478051708, -1.927596853767287, -1.877706291670396, -1.817231490373675, -1.747760819428933, -1.671106721928752, -1.5892674995719513, -1.504384118458927, -1.4186930319835287, -1.3344761211474498, -1.2540089300504695, -1.1795084232181159, -1.1130815105297627, -1.056675574251203, -1.0120321912490269, -0.9806451728068986, -0.9637239462343871, -0.9621631789969061, -0.976519400364833, -1.0069952110965348, -1.0534314924156665, -1.1153078358670643, -1.1917512201484668, -1.2815527644754963, -1.3831921952336592, -1.4948694783052363, -1.6145428980293668, -1.7399727094449158, -1.8687693570457162, -1.998445144003874, -2.1264681533570537, -2.2503171690214923, -2.367536320990393, -2.475788186276085, -2.5729041148710436, -2.656930617307957, -2.7261707456386657, -2.7792195204893426, -2.8149926003226584, -2.832747551632295, -2.832097256531482, -2.8130151827277823, -2.775832435593954, -2.7212267081954993, -2.6502034379362263, -2.564069663238986, -2.46440124589881, -2.353004280253491, -2.2318716453528875, -2.1031357676223172, -1.9690187464463098, -1.8317810516386035, -1.6936700286075694, -1.5568694436017882, -1.423451267903431, -1.2953308371451635, -1.1742264316934508, -1.0616242085796825, -0.9587492776993415, -0.8665435584132027, -0.7856508812055216, -0.7164096169744537, -0.6588529283945349, -0.6127165482848, -0.5774538037468072, -0.5522574266192215, -0.5360875249355452, -0.5277049406583135, -0.525709089666828, -0.528579273957548, -0.5347183758505141, -0.5424977916053288, -0.5503024384622658, -0.5565746752370849, -0.5598560119726329, -0.5588255478149468, -0.5523341665588986, -0.5394336338566567, -0.5193998759556934, -0.4917498735551374, -0.4562517720210985, -0.412927986519552, -0.36205126310861857, -0.30413383985516457, -0.2399100309693407, -0.1703127272584411, -0.09644446358194315, -0.019543844465415895, 0.05905176094738815, 0.1379462468904833, 0.215726443598408, 0.29100431334035, 0.3624585345572847, 0.4288743538638483, 0.48918062953720887, 0.542483061667448, 0.588092701591538, 0.6255489541254954, 0.6546364274044489, 0.6753951432796215, 0.6881237922185214, 0.6933758961963391, 0.6919489266191325, 0.6848666072428746, 0.6733548097164613, 0.6588116172766774, 0.6427722859926097, 0.6268699688754117, 0.6127931826598351, 0.6022410871811334, 0.5968777106752234, 0.5982862893464231, 0.6079248952084725, 0.627084502276388, 0.6568505881739387, 0.6980692873571712, 0.7513190053697782, 0.8168882734235855, 0.8947604723074498, 0.9846058878503857, 1.0857813809990025, 1.1973377684317994, 1.3180348191489033, 1.4463635833642097, 1.5805755869828246, 1.7187182525263434, 1.8586757498741486, 1.9982143415625615, 2.1350311711100995, 2.2668053518539146, 2.391250150409921, 2.506165024749421, 2.609486272941887, 2.6993350750281437, 2.7740617666939644, 2.832285268109305, 2.872926702477916, 2.8952363738462012, 2.898813429298639, 2.8836177030599264, 2.849973425052689, 2.7985646696303292, 2.730422616818316, 2.646904893665895, 2.549667452473394, 2.4406296211042475, 2.3219331239602425, 2.195896016504775], [2.1049642109158984, 1.9730315362716981, 1.8403695960982234, 1.7094989937098195, 1.582870527703839, 1.4628123002351965, 1.351479719164523, 1.2508095500730625, 1.1624790764489656, 1.0878713032954639, 1.028046994004915, 0.983724166142877, 0.9552654928094383, 0.9426738668661561, 0.9455961901616533, 0.9633352537195453, 0.9948693824505503, 1.0388793339996365, 1.0937817703084398, 1.1577684665090424, 1.2288502885882087, 1.3049048620753592, 1.3837267714219676, 1.463079075704991, 1.5407449020466208, 1.6145778842056318, 1.6825502499227787, 1.7427974258147017, 1.7936581212126963, 1.8337089699675286, 1.861792948908975, 1.8770409498409795, 1.878886054701589, 1.867070246501451, 1.8416434773120947, 1.8029552042118338, 1.7516386900056644, 1.6885885431122323, 1.6149321358692617, 1.5319956885888144, 1.4412659343615803, 1.3443483837480423, 1.2429232865796558, 1.1387004382562982, 1.0333739989990924, 0.9285784860611088, 0.8258470612121978, 0.7265731699285483, 0.631976496366603, 0.543074081778514, 0.46065731652536357, 0.3852753607816605, 0.3172253803520396, 0.25654980602673394, 0.20304064210260475, 0.15625066672303087, 0.11551118817364227, 0.07995585172585898, 0.04854983533087458, 0.020123633380578845, -0.00658949061927799, -0.03291339628634913, -0.06018738590683675, -0.08972407443559684, -0.12276794499219756, -0.16045570762870304, -0.2037795331520024, -0.25355416021823307, -0.3103887746299117, -0.37466443725743304, -0.44651769436178457, -0.525830844910339, -0.6122291677675289, -0.7050852317415156, -0.8035302279217047, -0.9064720811923442, -1.0126199208775086, -1.1205143236505934, -1.228562589367715, -1.3350781762460453, -1.4383233092404537, -1.5365536874726584, -1.6280641554227906, -1.7112341699219826, -1.7845718916937192, -1.8467557564554133, -1.896672435844941, -1.9334501813884613, -1.9564866533902006, -1.9654704683695081, -1.9603958502817131, -1.9415699385206484, -1.9096124854848777, -1.865447863860847, -1.8102894940994412, -1.7456169911189525, -1.6731465113714514, -1.5947949525246965, -1.512638813864021, -1.4288686622025648, -1.3457402621646746, -1.2655235182885778, -1.190450437217538, -1.1226633497316196, -1.0641646336537025, -1.016769149626629, -0.9820605430327698, -0.9613524782757237, -0.9556557583287222, -0.9656521455878321, -0.9916755429462218, -1.0337010204270634, -1.0913419868856549, -1.1638556127306283, -1.2501564130296459, -1.3488377055462233, -1.458200469952116, -1.5762889572694874, -1.700932236845616, -1.8297907258013668, -1.9604066264020465, -2.0902571030952593, -2.2168089653351064, -2.3375735863680354, -2.4501607827692458, -2.552330404818244, -2.642040443165001, -2.7174905413058497, -2.7771599141000096, -2.819838807201506, -2.844652787561031, -2.8510793272684194, -2.8389563277503673, -2.808482424195479, -2.7602091063412026, -2.695024886637984, -2.6141319355579364, -2.519015781847997, -2.4114088385196726, -2.293248659373673, -2.1666319524050466, -2.0337654726070626, -1.896914985203954, -1.7583535295910482, -1.6203102233672106, -1.484920824673729, -1.35418122021681, -1.2299049271898401, -1.1136855918628898, -1.0068653385536193, -0.9105096732943908, -0.8253894805203981, -0.7519704726800386, -0.6904102662671029, -0.6405630680376222, -0.6019917668176552, -0.5739870440016707, -0.5555929440939862, -0.545638189693952, -0.5427723870283666, -0.5455061518776643, -0.5522540943551415, -0.5613795366840537, -0.571239802399034, -0.5802309090818513, -0.5868305198968973, -0.5896380611518001, -0.587410992486411, -0.5790963210188342, -0.5638565781478962, -0.5410896244626983, -0.5104418105951972, -0.47181419573840355, -0.425361706524559, -0.37148530242613714, -0.31081739516189566, -0.24420094417349358, -0.1726628136725167, -0.09738212491394548, -0.019654466489032248, 0.05914706771198664, 0.13761296133672152, 0.21433937284067708, 0.28797011441857256, 0.35723738251878784, 0.4210001415914878, 0.4782791226889906, 0.5282874852362172, 0.5704563015379668, 0.6044541565863207, 0.6302003071244436, 0.6478710098950875, 0.657898805365267, 0.6609647255191898, 0.6579835779415195, 0.6500826387252565, 0.6385742591629922, 0.6249230513389484, 0.6107084615554099, 0.5975836643282391, 0.5872318102955397, 0.5813207362008385, 0.5814572921790226, 0.5891424596227569, 0.6057284213965872, 0.6323787052914405, 0.6700324523045555, 0.7193737652324667, 0.7808069724936912, 0.8544384999852043, 0.9400658835986334, 1.0371742807122255, 1.1449406548280878, 1.2622456180901882, 1.3876927263888699, 1.5196348358490583, 1.6562069523370773, 1.7953648416244494, 1.9349285211185503, 2.072629628292996, 2.206161559299365, 2.3332311962987617, 2.451610995746182, 2.559190193417682, 2.654023895881075, 2.7343788721177553, 2.7987749321078685, 2.846020879675001, 2.875244152355352, 2.8859134084969447, 2.8778534876482262, 2.8512523505468557, 2.806659795293421, 2.744977941964782, 2.6674436742231915, 2.575603418625732, 2.4712808256457612, 2.356538086409687, 2.233631771676345, 2.104964210915902], [2.013144360605829, 1.8813227930187426, 1.7504158909221754, 1.6229072382158376, 1.5011776379574115, 1.3874538096602989, 1.2837606849527599, 1.19187840311719, 1.1133049949998575, 1.0492256070845498, 1.0004889605020841, 0.9675915662407331, 0.950670032070562, 0.9495016032338484, 0.9635128825052898, 0.9917964805787882, 1.0331351596317717, 1.086032855926506, 1.1487518057249368, 1.2193548565293264, 1.295751926144991, 1.375749478159124, 1.4571018163720866, 1.5375629640469544, 1.6149378873761284, 1.687131846371874, 1.7521967097963278, 1.8083731523531663, 1.854127760072635, 1.8881842008990657, 1.9095477686292615, 1.9175227757566304, 1.9117224502612273, 1.8920711784720277, 1.8587991261587393, 1.8124294582680103, 1.75375855953938, 1.6838298291267844, 1.603901778100535, 1.5154112954873162, 1.419933062977089, 1.3191361878042396, 1.2147391854455682, 1.1084644772034997, 1.0019935717126471, 0.8969240739120339, 0.7947296107910264, 0.6967236816886507, 0.6040283342284019, 0.5175484378552057, 0.4379521787164469, 0.36565823607727244, 0.3008299257428104, 0.2433764145121106, 0.1929609261090891, 0.14901567797125934, 0.11076311430567662, 0.07724283833864637, 0.047343499793498924, 0.019838766035932928, -0.006573599752546872, -0.033230609925947084, -0.06146198253575047, -0.0925482638126598, -0.1276802715798357, -0.16792095431419282, -0.21417069853317358, -0.2671370285644026, -0.3273095297882552, -0.3949406919767195, -0.47003321677737825, -0.5523341665588982, -0.6413361549563176, -0.7362855969999017, -0.8361978532946711, -0.9398789229828117, -1.045953168725331, -1.1528963980387774, -1.259073483063859, -1.3627795788599015, -1.4622839017435483, -1.5558749565715635, -1.6419060571088206, -1.7188399679321533, -1.7852915101808027, -1.8400670166186668, -1.8821995929324566, -1.9109792402536074, -1.9259770161925927, -1.9270625552336436, -1.9144144306406383, -1.8885230151054575, -1.8501856819104598, -1.800494377813846, -1.7408157885048636, -1.6727645026039313, -1.5981697561906554, -1.519036502336203, -1.437501695026549, -1.355786800547383, -1.2761476487350951, -1.2008228089520712, -1.1319817193488002, -1.0716738117665512, -1.0217798580850943, -0.9839667172510917, -0.9596465866951427, -0.9499417591360458, -0.9556557583287224, -0.9772515781993129, -1.0148375826271385, -1.0681614419277121, -1.136612291263582, -1.2192311004019776, -1.3147290482196143, -1.4215135039055387, -1.5377210346052694, -1.6612566907341069, -1.7898386694825499, -1.9210473278269231, -2.0523774118040317, -2.1812922914673454, -2.305278942706683, -2.4219023991635225, -2.528858410249003, -2.6240230844582095, -2.705498369715003, -2.771652322600672, -2.8211532435668536, -2.852996902544285, -2.8665262451313773, -2.8614431497280317, -2.8378119961687616, -2.7960550019618413, -2.7369394783881047, -2.6615573506749923, -2.5712974695677513, -2.4678114114229524, -2.3529736163347232, -2.2288368450903016, -2.097584042781576, -1.9614777771167982, -1.8228084709898211, -1.6838426704894267, -1.5467725808236927, -1.4136680638963923, -1.286432223545653, -1.1667616094947464, -1.0561119512925181, -0.9556701919676486, -0.8663334313473969, -0.788695215002088, -0.7230394209180191, -0.6693418068549013, -0.627279091611179, -0.5962452578072646, -0.57537458689521, -0.5635707732796013, -0.559541317718879, -0.5618362741652088, -0.5688903219669671, -0.5790670593744991, -0.5907043663708034, -0.6021596661040854, -0.6118539250076545, -0.6183132716944679, -0.6202071828195382, -0.616382278522908, -0.6058908883534027, -0.5880136876889722, -0.5622758610568895, -0.5284564184317627, -0.48659046923961463, -0.4369644418907615, -0.38010441956572705, -0.31675794106004745, -0.24786978425466052, -0.174552404956733, -0.09805184153421867, -0.019710012472919695, 0.05907557322594736, 0.13689360635648806, 0.21236114347596702, 0.2841650137849103, 0.35110135163236195, 0.4121121874780636, 0.4663181057114552, 0.5130460788401777, 0.5518517116697769, 0.5825352730717298, 0.6051510531468224, 0.6200097559915366, 0.6276738185120128, 0.6289457292473439, 0.6248496033177656, 0.6166064457887077, 0.6056037014678054, 0.5933598402143607, 0.581484859386907, 0.5716376956908527, 0.5654816245652396, 0.5646387841320643, 0.5706449910628738, 0.5849060166471811, 0.6086564627621983, 0.6429223199683839, 0.6884882049390739, 0.7458701639150378, 0.8152947955375835, 0.896685293513547, 0.9896548408543776, 1.0935076070639798, 1.2072474120805743, 1.3295939306500455, 1.4590061228404794, 1.5937123952749486, 1.7317468278780057, 1.8709906467461224, 2.009217989031044, 2.1441448938615264, 2.2734803671599737, 2.394978309941535, 2.5064890708364396, 2.6060093849493478, 2.69172949281621, 2.76207629444619, 2.8157514828210655, 2.851763716647065, 2.869454030850731, 2.868513841939971, 2.8489950800774344, 2.8113121662984035, 2.756235747214783, 2.6848782960604924, 2.5986718832619715, 2.499338607119932, 2.388854351088726, 2.2694066942408724, 2.143347941892298, 2.013144360605833], [1.9212133030571439, 1.790612265646713, 1.6625503963191206, 1.5394532594355383, 1.4236115400330118, 1.3171317641755291, 1.2218912917049258, 1.139498619116673, 1.0712599028734429, 1.0181524642863793, 0.9808058697858663, 0.9594909990577029, 0.954117322564828, 0.9642384140688329, 0.9890655276858713, 1.0274888775339195, 1.0781060758100058, 1.1392570166014013, 1.2090643419666476, 1.285478497461515, 1.3663262794412103, 1.449361698645819, 1.5323179356051704, 1.612959144403545, 1.689130872705636, 1.7588079072969558, 1.820138424630112, 1.8714834231793398, 1.9114505363114327, 1.9389214678023694, 1.953072453461153, 1.9533873275268874, 1.939662957208864, 1.9120069983442989, 1.8708281149451673, 1.8168189906913041, 1.7509326366210956, 1.6743526620295486, 1.5884583209056584, 1.494785270569084, 1.3949830794724678, 1.2907705949978663, 1.183890327735235, 1.0760630251366132, 0.9689435942726858, 0.864079491099101, 0.7628726233164578, 0.6665457174266004, 0.5761139804463609, 0.4923627460238513, 0.41583163700789744, 0.34680560586424486, 0.2853130350478069, 0.2311308960740344, 0.1837967832264132, 0.14262746021342687, 0.10674339013386337, 0.07509856506323118, 0.04651481532170449, 0.019719663460038023, -0.006613302897837206, -0.03382262969950598, -0.06321689338517185, -0.09603343036620993, -0.13339901169489235, -0.1762935253206991, -0.22551765076816843, -0.28166540814624463, -0.34510233770703275, -0.415949920885169, -0.49407669253555736, -0.5790963210188333, -0.6703727522342281, -0.7670323302348171, -0.8679826253248456, -0.9719375251393125, -1.077447979595131, -1.1829376409686778, -1.2867425095138691, -1.38715358633951, -1.4824614515152355, -1.5710016287518527, -1.6511995700073057, -1.7216140947926912, -1.7809781498465476, -1.8282358145256674, -1.8625745643207123, -1.8834519172510964, -1.890615722796154, -1.8841175071791063, -1.864318458449954, -1.8318878157318903, -1.7877936147310922, -1.7332859315100337, -1.6698729538732078, -1.599290389847576, -1.5234648911627475, -1.4444723221329596, -1.3644918370848345, -1.2857568391129044, -1.2105039766954218, -1.1409213904163207, -1.0790974482548217, -1.026971203887124, -0.9862857782045782, -0.9585458005457589, -0.9449799544491928, -0.9465095552351954, -0.9637239462343873, -0.9968633403826523, -1.0458095580709394, -1.1100849248390667, -1.188859398289364, -1.2809657971977182, -1.384922812005215, -1.4989652894131478, -1.6210811092326876, -1.7490538132256466, -1.8805100072894407, -2.0129704433743654, -2.1439035987899158, -2.2707805102326133, -2.391129589430099, -2.502590147492481, -2.602963385890103, -2.690259672684919, -2.7627410117473987, -2.8189577280141846, -2.857778530564699, -2.8784132740268706, -2.8804279136848, -2.8637513363834404, -2.8286739433496617, -2.775838057642439, -2.7062204233167706, -2.621107250805004, -2.522062438930764, -2.410889764107891, -2.289589967765887, -2.1603137904988934, -2.025312093042427, -1.8868842677659263, -1.7473261784477427, -1.6088788699182865, -1.4736792627090964, -1.3437139918681964, -1.220777465058569, -1.1064351051002597, -1.00199260903393, -0.9084719029279561, -0.8265943028552092, -0.7567712119489018, -0.6991024957088194, -0.6533824874380629, -0.6191133875668413, -0.5955256393201811, -0.5816046931866755, -0.5761234181311479, -0.5776792822559987, -0.5847353129571552, -0.595663759274323, -0.6087913191985519, -0.6224447635819766, -0.6349957866821405, -0.6449039412153651, -0.6507565723034822, -0.651304748373853, -0.6454942957349123, -0.6324911743982738, -0.6117005824019506, -0.582779340589799, -0.5456412853308338, -0.5004555785645715, -0.4476380282266639, -0.3878356928961925, -0.3219052178431939, -0.2508855111655858, -0.17596551431377566, -0.098447947337105, -0.019710012472919695, 0.05883788236497381, 0.1357942680184276, 0.20980849221986222, 0.27962120431255166, 0.34410235549589197, 0.40228568763722045, 0.4533987742206547, 0.49688779167425484, 0.5324363352359263, 0.5599777472546642, 0.5797005934951528, 0.592047100384354, 0.5977045487244995, 0.5975898025780221, 0.5928273311664821, 0.5847212521736217, 0.5747220824683495, 0.5643890229515444, 0.5553487243852769, 0.5492515775986094, 0.5477266418822847, 0.5523363678379821, 0.5645322842868418, 0.5856128026442815, 0.6166842467503988, 0.6586261425560113, 0.7120617020588823, 0.7773343118822731, 0.8544906919125858, 0.9432712270184713, 1.043107799057039, 1.1531292614735913, 1.2721745093959762, 1.3988129089116552, 1.5313716649000706, 1.6679695319686596, 1.8065561120763498, 1.944955839358966, 2.0809156310967225, 2.2121550867604145, 2.3364180471153184, 2.4515242842599254, 2.5554200823328173, 2.646226487798136, 2.722284057335243, 2.782193009287324, 2.8248477895325452, 2.849465192026049, 2.8556053250120432, 2.8431848823817463, 2.8124823617728896, 2.7641350623464507, 2.6991278910806615, 2.61877420211721, 2.5246890844057797, 2.418755693964053, 2.3030853940754463, 2.179972615602957, 2.0518454766619727, 1.9212133030571474], [1.8299488166159816, 1.701667406264156, 1.5775164941329887, 1.459843115792757, 1.3508284782181388, 1.2524411201067749, 1.1663949824841173, 1.0941133547462762, 1.0366995205747327, 0.9949147677497809, 0.9691642497104203, 0.9594909990577026, 0.9655781986547375, 0.9867596192829639, 1.022037938762466, 1.0701104707557045, 1.1294016566848146, 1.1981015155408077, 1.274209107685236, 1.355579953382033, 1.4399762575127242, 1.52511873084022, 1.6087387667168287, 1.6886297309717855, 1.7626961518065472, 1.828999655071663, 1.8858005767726633, 1.9315942968443114, 1.9651414733032577, 1.9854915104405626, 1.9919987648758282, 1.984331174814881, 1.9624711862124988, 1.9267090400610831, 1.8776286729830667, 1.8160866640511277, 1.7431848298374446, 1.6602372229426339, 1.5687324229207449, 1.470292119338308, 1.3666270719981617, 1.2594915910796411, 1.1506377087441535, 1.0417702130019466, 0.9345036844436332, 0.8303226176552483, 0.7305456233179777, 0.6362945963757388, 0.5484696030848653, 0.46773008863399995, 0.39448284119222893, 0.3288769719250924, 0.2708059881837807, 0.2199168533396518, 0.17562574625018565, 0.13714006066246628, 0.10348602434364199, 0.07354117342181817, 0.04607079296110665, 0.01976733331458074, -0.006708264148573962, -0.03468444685184956, -0.06543727111520868, -0.10015008801014852, -0.13987578220823477, -0.1855025849088753, -0.2377243895065245, -0.29701638229833005, -0.36361666317991553, -0.43751437639943336, -0.5184447029516127, -0.6058908883534025, -0.6990932968490814, -0.797065300170039, -0.8986156304580794, -1.0023766573809192, -1.1068378931353855, -1.2103838899312904, -1.3113355762336028, -1.4079939835522302, -1.4986852473540018, -1.5818057255219853, -1.655866066793762, -1.7195330801350492, -1.7716683036711989, -1.8113622474998008, -1.8379633866321883, -1.851101105989783, -1.850701945744183, -1.8369986587452898, -1.8105317683030753, -1.7721434998143673, -1.7229641490678445, -1.6643911388173036, -1.5980611986874513, -1.5258162770912211, -1.4496639532501951, -1.371733258620157, -1.294226936474402, -1.2193712630617835, -1.14936462121521, -1.086326055787841, -1.0322450487994634, -0.9889337303841588, -0.9579826899891973, -0.9407214719690531, -0.9381847326404473, -0.9510849045712643, -0.9797920615251385, -1.0243215077553562, -1.084329432350392, -1.1591167775251052, -1.2476412737954772, -1.3485373996476893, -1.4601438333817813, -1.5805377849163238, -1.707575429882159, -1.8389375213591763, -1.9721791297191937, -2.1047823612904786, -2.234210834401726, -2.357964648566427, -2.4736345701862126, -2.578954176492426, -2.671848748065739, -2.750479777989578, -2.813284070608003, -2.8590065324106497, -2.886725908592412, -2.895872887645482, -2.8862401788147602, -2.8579843589310743, -2.8116194813549327, -2.748002635734486, -2.6683118382336346, -2.5740168131767973, -2.4668433942852706, -2.3487324227964357, -2.2217941471614844, -2.0882592316483266, -1.950427556585823, -1.8106160393975033, -1.6711067219287514, -1.5340963555519667, -1.4016486715697751, -1.2756504516930782, -1.1577724137214753, -1.0494358035316118, -0.9517854392119149, -0.8656697903172867, -0.7916284988270319, -0.7298875628724458, -0.6803622142712918, -0.6426673310805286, -0.6161350414558471, -0.5998389996544364, -0.5926246533576859, -0.593144677593045, -0.5998986279178042, -0.6112757671740925, -0.6255999484049933, -0.6411753931388076, -0.6563321901944731, -0.6694703556945947, -0.6791013396125631, -0.6838859367200264, -0.6826676583383461, -0.6745007432834726, -0.658672128696741, -0.6347168604391173, -0.6024265943466476, -0.5618510195422033, -0.5132922186143513, -0.45729216216201146, -0.39461371234671644, -0.3262156772205804, -0.2532226104919709, -0.1768901861990449, -0.09856709108827215, -0.019654466489032255, 0.058436006101306184, 0.13432424722233627, 0.2067030156570772, 0.2743771286857301, 0.33629960878377424, 0.3916037787041536, 0.4396304316070655, 0.47994933015958097, 0.5123744351066032, 0.5369724260109328, 0.554064250574552, 0.5642196197932224, 0.568244549586379, 0.5671622308395656, 0.5621876844003124, 0.5546968210461966, 0.5461906746354525, 0.5382557057739872, 0.5325211800793699, 0.5306147067404036, 0.5341170774343938, 0.5445175713273467, 0.5631708881162832, 0.5912568378846981, 0.6297438546760349, 0.6793573116091705, 0.7405535012112182, 0.8135000082046802, 0.89806304659902, 0.9938021624221506, 1.0999725219924845, 1.2155348177656489, 1.339172634151159, 1.4693169289969794, 1.6041771073360387, 1.7417779969520248, 1.8800018845362052, 2.016634640463844, 2.149414852820157, 2.2760848099827773, 2.3944421179133513, 2.5023907147238553, 2.597990051736522, 2.6795012470754993, 2.745429083996245, 2.7945588201306832, 2.825986893371403, 2.839144752370343, 2.833815201157293, 2.810140824281617, 2.768624246853643, 2.7101201783383146, 2.6358193851955507, 2.5472249306821384, 2.4461212056105364, 2.33453644706758, 2.214699598793149, 2.088992503270599, 1.9598985282465562, 1.8299488166159854], [1.7401230401352867, 1.6152407286294577, 1.4960336096545552, 1.3847503451267138, 1.2834442301504583, 1.1939291895757096, 1.1177412811787082, 1.0561065898796413, 1.009916244576726, 0.979709118902633, 0.965662593649478, 0.9675915662407331, 0.9849556961424645, 1.0168746792891674, 1.0621511542171802, 1.1193006622789967, 1.186587918430481, 1.262068501656257, 1.3436349486843777, 1.429066134252522, 1.5160787482180502, 1.6023796359695124, 1.6857177548950335, 1.763934516347977, 1.8350113291289993, 1.8971132357476939, 1.9486276347043918, 1.988197208156393, 2.014746321425733, 2.0275003251797425, 2.025997368664361, 2.010092518670304, 1.9799541693339195, 1.9360529176967072, 1.8791432644741486, 1.810238674162239, 1.730580689139739, 1.641602934868025, 1.5448909741688175, 1.4421390649376786, 1.335104945208643, 1.2255638105766233, 1.1152626606759697, 1.0058761735078354, 0.8989652194468821, 0.7959390520049723, 0.6980221118437079, 0.6062262567089448, 0.5213290860856167, 0.4438588691135742, 0.37408641174248214, 0.31202401861573975, 0.25743152133171604, 0.20982916218490794, 0.16851694585066224, 0.1325999052016553, 0.10101857572357258, 0.07258383965242139, 0.04601518934179849, 0.019981372291020785, -0.006857680089605444, -0.03580877001989223, -0.0681043303255324, -0.10486340795799885, -0.14705578671054803, -0.19547022026745844, -0.25068764021490303, -0.31306007483293724, -0.3826958666355741, -0.4594516134678331, -0.5429310836307726, -0.6324911743982735, -0.7272547999972396, -0.8261304142898414, -0.9278376996093523, -1.030938790875004, -1.1338742573784564, -1.2350029372408222, -1.3326446147501199, -1.4251244513072547, -1.5108180286056996, -1.5881958393343754, -1.6558660667937617, -1.7126145302849014, -1.757440737166154, -1.7895890735534832, -1.808574281566816, -1.8142005089718483, -1.8065733736517322, -1.7861046567114685, -1.7535094199374026, -1.709795531300162, -1.6562457715358958, -1.5943928808570897, -1.5259880828916594, -1.4529637885762, -1.3773913317830477, -1.3014347171899192, -1.2273014660496462, -1.1571917244072283, -1.0932468489076967, -1.0374987063022585, -0.9918209134830703, -0.9578832054956437, -0.9371100503725478, -0.9306445334063344, -0.9393184119202818, -0.9636290976184995, -1.0037241606747114, -1.0593937717964887, -1.1300713098986501, -1.2148421683249366, -1.312460596516038, -1.4213742214186653, -1.5397557084705666, -1.665540850191135, -1.7964722154618622, -1.9301473582910451, -2.0640704745153022, -2.195706311204325, -2.322535078561697, -2.4421070892072105, -2.5520958555038984, -2.6503484119229, -2.734931695440923, -2.8041739110313997, -2.856699929147859, -2.891459904782582, -2.9077504697330414, -2.905228027168338, -2.8839138661281782, -2.8441910086097675, -2.7867928986502823, -2.712784236502995, -2.6235344469223296, -2.520684444201374, -2.4061075137358725, -2.2818652667226003, -2.150159737841786, -2.013282782711537, -1.8735639904758252, -1.7333183557352934, -1.5947949525246958, -1.46012782130148, -1.3312902188009814, -1.2100532917200228, -1.0979501207787954, -0.9962459446725517, -0.9059152172021707, -0.8276259793765037, -0.7617318457871504, -0.7082717156088966, -0.6669771278664721, -0.6372869928537467, -0.6183692514340126, -0.6091488458297853, -0.6083412335586059, -0.6144905441080374, -0.6260113689856283, -0.6412330925636531, -0.6584456156526527, -0.6759452972757709, -0.6920799432449157, -0.7052917026876824, -0.714156794734309, -0.7174210755299284, -0.7140305683028392, -0.7031562134967608, -0.6842122485284222, -0.6568677936732934, -0.621051397670169, -0.5769484793794546, -0.5249917856054872, -0.4658451653551656, -0.4003811328056589, -0.3296528507553691, -0.2548613093159652, -0.17731859746997247, -0.09840826477767205, -0.0195438444654159, 0.05787334448998618, 0.13249598100934107, 0.20307098752457725, 0.2684771541572197, 0.3277591262639764, 0.3801568344620559, 0.4251295642794444, 0.4623740013453113, 0.4918357440350152, 0.5137139447682845, 0.528458919446706, 0.5367627472960212, 0.5395430660211613, 0.5379204450575149, 0.5331898882954965, 0.5267871726799805, 0.5202508665899893, 0.515180988370472, 0.5131953578235952, 0.5158847594769761, 0.5247680742951946, 0.5412485451566837, 0.5665723205788398, 0.6017903712763419, 0.6477247963465156, 0.704940432056711, 0.7737225488825665, 0.8540612747262071, 0.9456432177595238, 1.0478505851455602, 1.159767908373099, 1.2801962966950848, 1.4076749518936964, 1.5405094949926634, 1.676806483160537, 1.8145133372125737, 1.9514627607879693, 2.0854206149683816, 2.2141361197893157, 2.3353931891416213, 2.447061669658929, 2.547147248314276, 2.6338388178432663, 2.7055521432609506, 2.76096875540042, 2.7990691066209403, 2.8191591570037113, 2.8208897132694846, 2.804268013594436, 2.7696612353237176, 2.7177917948179346, 2.6497245046347175, 2.566845848166665, 2.4708358209680332, 2.363632966683221, 2.2473933993688995, 2.124444749064952, 1.9972360901631017, 1.8682850094361112, 1.7401230401352905], [1.652495940330713, 1.5320634415439252, 1.4187911249579335, 1.314810266257109, 1.2220288970603428, 1.1420910099915766, 1.0763418201177937, 1.0257998789457965, 0.9911366735139356, 0.9726641644148165, 0.9703305271978327, 0.9837241661428768, 1.0120858726308453, 1.0543288070525707, 1.1090657980958298, 1.174643280824693, 1.249181039395558, 1.330616785299821, 1.4167544909336698, 1.5053153137299418, 1.5939898900490523, 1.6804907518153445, 1.762603623066409, 1.8382363879720336, 1.9054645855498547, 1.962572377610782, 2.0080880530856264, 2.0408132708727758, 2.0598454012172924, 2.064592498438009, 2.054780621254158, 2.0304534064669975, 1.9919639926247794, 1.9399595778182206, 1.875359075289038, 1.799324497665343, 1.7132268512617206, 1.6186074523149445, 1.517135684094696, 1.4105642949468271, 1.3006833905604764, 1.189274297864364, 1.078064472444732, 0.9686845864706375, 0.8626288707776433, 0.7612196946724143, 0.6655772525177772, 0.5765950901858782, 0.494922050503653, 0.42095104878156686, 0.3548149116812914, 0.2963893295472323, 0.2453027885331962, 0.20095316904170418, 0.16253052569599172, 0.12904540560063615, 0.09936192000551418, 0.0722346632319285, 0.04634847489556026, 0.020359969522763734, -0.007060286594459046, -0.03718608692087033, -0.07119550648836562, -0.11013351339020055, -0.1548782791147534, -0.20611210069090846, -0.26429772792637324, -0.3296607488513697, -0.40217852937933585, -0.481576033138057, -0.567328668712278, -0.6586721286967406, -0.7546190026188443, -0.8539817685766565, -0.9554016008505076, -1.0573822770476937, -1.1583283324487528, -1.2565864946167884, -1.3504893409551217, -1.438400058095751, -1.518757146450793, -1.5901179069346107, -1.6511995700073057, -1.7009169793046592, -1.7384158219820927, -1.763100503590773, -1.77465589425217, -1.773062321945775, -1.7586033542071091, -1.7318660873646472, -1.6937338482230155, -1.6453714022156822, -1.5882029497995762, -1.5238833745663074, -1.4542633776589202, -1.3813492893214772, -1.3072584858426504, -1.2341714553131975, -1.1642816455744809, -1.0997442901828187, -1.042625441520185, -0.9948524434308497, -0.9581670487825489, -0.9340823307126583, -0.9238444513307631, -0.9284002403177095, -0.948371400848993, -0.9840360048274097, -1.0353177672949017, -1.1017834052818816, -1.1826481937332194, -1.276789635216368, -1.3827689656497524, -1.4988600300394261, -1.6230848847835357, -1.7532553208410306, -1.8870193589395392, -2.0219116475278875, -2.155406599319483, -2.2849730353560767, -2.4081290681970575, -2.5224959490322543, -2.6258496274052323, -2.716168826245901, -2.7916785177355012, -2.8508877951479783, -2.8926212695578206, -2.9160432749143967, -2.9206743366856145, -2.906399543881828, -2.8734686572830515, -2.8224879834048004, -2.7544042393595483, -2.670480823541973, -2.572267086375351, -2.461561359853438, -2.340368650315319, -2.210854022284502, -2.075292799324578, -1.9360187783737608, -1.795371695262885, -1.6556451901606795, -1.5190365023362034, -1.3875990744377287, -1.2631991687507025, -1.1474774936054555, -1.0418167098987199, -0.9473155387977127, -0.8647700258394118, -0.7946623379611867, -0.7371572829486718, -0.6921065500073862, -0.6590604803821656, -0.6372869928537465, -0.6257971150739308, -0.6233764123348304, -0.6286214644091018, -0.6399804219862935, -0.6557965798538868, -0.674353836597197, -0.6939228718095516, -0.7128068624868821, -0.7293855805664552, -0.7421567628564975, -0.7497737215674984, -0.7510782662840331, -0.745128133857154, -0.7312182681300241, -0.7088954529225058, -0.6779659751859061, -0.6384961762964264, -0.5908059335006861, -0.5354552959071197, -0.4732246755288344, -0.40508915928614964, -0.3321876584041168, -0.255787743503998, -0.17724712357334804, -0.09797281214776213, -0.01937908231444747, 0.05715465790285285, 0.13032493733890385, 0.19894313642387484, 0.26197119718130063, 0.3185531642832285, 0.36804170123901675, 0.4100188561371006, 0.4443105004661416, 0.4709940286414916, 0.4903990808026147, 0.5031012327995007, 0.5099087804584536, 0.5118429255673776, 0.5101118439716452, 0.5060792773287335, 0.5012284353294116, 0.49712212084592217, 0.4953600932916615, 0.497534762819271, 0.5051863578275526, 0.5197587292617166, 0.5425569467666483, 0.5747078040167125, 0.6171242843602418, 0.6704749448588397, 0.7351590591231524, 0.8112882199204626, 0.8986749447778997, 0.9968286556158062, 1.1049592210752703, 1.2219880621723822, 1.3465666328905037, 1.4771019020178342, 1.6117882855753802, 1.7486453149889225, 1.8855601788585852, 2.020334149482138, 2.15073180240226, 2.274531860798933, 2.3895784485119154, 2.493831517133666, 2.5854152245044513, 2.662663083870036, 2.724158773984595, 2.7687715988959076, 2.7956857096934584, 2.8044223461687268, 2.7948545206147672, 2.7672137449005083, 2.722088591147855, 2.6604150712119323, 2.583459015964545, 2.4927908273281503, 2.390253159409543, 2.2779222554515117, 2.158063820484222, 2.033084441760341, 1.905479677055604, 1.7777800120553646, 1.6524959403307165], [1.5678088821183216, 1.452839262494453, 1.346442546416279, 1.2506146038994266, 1.1671020804564898, 1.0973651558107012, 1.0425468574754189, 1.0034496304331852, 0.980519691055406, 0.9738395077891767, 0.9831285575254005, 1.0077523096688776, 1.046739194550243, 1.09880512370411, 1.162384951282083, 1.235670102797076, 1.3166514534529714, 1.4031664169734235, 1.4929491100187127, 1.583682389252766, 1.6730505194906466, 1.7587912229919775, 1.8387458819949734, 1.9109067183880353, 1.9734598546393296, 2.024823266700166, 2.0636787698707173, 2.0889973292938393, 2.1000571540553334, 2.096454213645198, 2.078105003303738, 2.045241575880795, 1.9983990475455298, 1.938395968313211, 1.8663081213806063, 1.7834364734323251, 1.691270137524538, 1.5914453274713662, 1.4857013750118198, 1.3758349462076227, 1.263653629981917, 1.150930078641601, 1.0393578575552493, 0.9305101095460723, 0.8258020603880436, 0.7264582871312963, 0.6334855435315496, 0.5476517898835799, 0.46947191180931735, 0.39920043816389383, 0.33683138661962786, 0.2821051812638672, 0.23452240435601088, 0.19336396882846474, 0.15771713360956857, 0.12650663453446287, 0.0985300732464868, 0.07249659835086095, 0.04706782987579371, 0.020899921905911837, -0.007314369520423216, -0.03880474483055859, -0.0746846468545976, -0.11591581683004733, -0.16327707759539317, -0.2173381910553372, -0.27843950514026117, -0.3466779551395408, -0.4218998192683831, -0.5037004528082809, -0.5914310435863065, -0.6842122485284219, -0.7809543911772737, -0.8803837279703366, -0.9810741311042376, -1.0814833920401536, -1.1799932258055852, -1.2749519553971174, -1.3647187803900829, -1.4477084862770075, -1.5224354323598215, -1.5875556667610482, -1.6419060571088204, -1.6845393937688173, -1.7147545175103442, -1.73212064289977, -1.736495189593177, -1.728034592589045, -1.7071977354814964, -1.6747418335447317, -1.6317107815453724, -1.5794161698452334, -1.5194113569205032, -1.4534591622740916, -1.3834939064513017, -1.3115786703966779, -1.2398587710411337, -1.1705125506224419, -1.1057006512469203, -1.0475149916773538, -0.9979286790656213, -0.9587480738551603, -0.9315681816218129, -0.9177324722058856, -0.9182981258344893, -0.9340075804382632, -0.9652671070437193, -1.0121329745287768, -1.0743055851774328, -1.1511317727307202, -1.2416152596255485, -1.3444350745979488, -1.457971540578849, -1.5803392605063118, -1.7094263597821984, -1.842939092753062, -1.9784507905083186, -2.1134540216589452, -2.245414759185825, -2.371827296865757, -2.4902686394237716, -2.598451101911063, -2.6942718956059664, -2.77585854897218, -2.841609111154632, -2.8902262097414138, -2.920744181043428, -2.9325486563706766, -2.9253881676875957, -2.8993775262244386, -2.8549929234727203, -2.7930589007301383, -2.7147275261963664, -2.621450302867582, -2.5149435016616706, -2.3971477681800732, -2.270182984555321, -2.136299476743042, -1.9978267397873917, -1.8571209070740553, -1.7165122131469215, -1.5782536928019308, -1.4444723221329587, -1.3171237409788126, -1.1979516025139152, -1.088452476917297, -0.9898470951379527, -0.903058559282057, -0.8286979720609787, -0.7670577533939276, -0.7181127222333262, -0.6815288306837244, -0.6566792502384131, -0.6426673310805281, -0.6383557892880614, -0.642401327518892, -0.6532937659792697, -0.6693986553266621, -0.6890022641606729, -0.7103577827928929, -0.7317315632349614, -0.7514482232504065, -0.7679334795863576, -0.7797536411103819, -0.7856507847942794, -0.7845727539185081, -0.7756972555248922, -0.7584494895028409, -0.7325129108005399, -0.6978329048143227, -0.6546133395043894, -0.6033061415734626, -0.5445942234873047, -0.47936825868768207, -0.40869795975375733, -0.3337986545471017, -0.2559940750036223, -0.17667636921067936, -0.09726441732483597, -0.019161573998479873, 0.056286026753642734, 0.12782948422288498, 0.1943543858431559, 0.2549143010979683, 0.3087596094456328, 0.3553608785442634, 0.39442615060859165, 0.42591165291333694, 0.4500256192692454, 0.4672250884131693, 0.4782057281364557, 0.48388491599152367, 0.4853784839477235, 0.4839717009306784, 0.48108521953649375, 0.47823684747793616, 0.4770001170581223, 0.47896071427897957, 0.4856718907866341, 0.49861001511116915, 0.5191314236596977, 0.5484317064875618, 0.5875085085586687, 0.6371288452930326, 0.6978018236620337, 0.769757529549428, 0.8529326917492658, 0.9469635665232045, 1.0511863082019282, 1.1646449053093633, 1.2861065727342504, 1.4140843032747723, 1.546866101109469, 1.6825502499227791, 1.8190858137964847, 1.9543174334606717, 2.086033367505699, 2.2120156405661437, 2.330091100550682, 2.438182156280276, 2.534355966264328, 2.6168708788993555, 2.684218983483115, 2.7351637187309157, 2.768771598895908, 2.78443725441725, 2.7819011409545964, 2.7612594439171096, 2.722965890955909, 2.6678253778506242, 2.596979509080608, 2.5118843483474245, 2.4142808616665787, 2.3061587117875213, 2.1897142233169684, 2.067303479073007, 1.9413916264201228, 1.8144995647232465, 1.6891492493361353, 1.567808882118325], [1.4867783563319206, 1.3782384638851501, 1.2795999757421603, 1.1927064824060805, 1.1191284860620354, 1.0601300279981332, 1.0166423139279328, 0.9892449375578269, 0.9781551216769757, 0.9832252050889175, 1.003948407504436, 1.0394727078516457, 1.0886224791164125, 1.1499273394791498, 1.2216575096127922, 1.3018648136673083, 1.3884283303690845, 1.4791035939640231, 1.5715741649835884, 1.663504339900566, 1.752591747842414, 1.8366185920818898, 1.9135003337154248, 1.9813306837169629, 2.038421865652717, 2.083339232325302, 2.1149294624405757, 2.1323417244818055, 2.13504137031482, 2.122815906273066, 2.0957731799865593, 2.054331912306733, 1.999204890619646, 1.931375318025633, 1.852066977914522, 1.7627090213376093, 1.6648963116619344, 1.5603463642044684, 1.4508539953992163, 1.3382448447256086, 1.224328952003616, 1.1108555623539154, 0.999470291484429, 0.8916757160830695, 0.788796359758301, 0.6919489266191327, 0.6020184952647124, 0.5196412292196002, 0.4451939896922829, 0.3787910572686439, 0.320287985317151, 0.26929242412377247, 0.22518157572847863, 0.18712576961314595, 0.15411749306652867, 0.1250050711551623, 0.09853007324648677, 0.07336742891958557, 0.04816716821385423, 0.021596661198972435, -0.00761777921097046, -0.040651049170589974, -0.07854223171787598, -0.12216139737391589, -0.1721811245168214, -0.22905351355639772, -0.2929933260221102, -0.36396772043187897, -0.44169288526626915, -0.5256376898766807, -0.6150342912549747, -0.7088954529225053, -0.8060381563684244, -0.9051129199473882, -1.004638089147643, -1.1030382295136685, -1.1986856426476782, -1.2899439394731416, -1.375212545558489, -1.4529709823364996, -1.5218217663695508, -1.5805307965249829, -1.6280641554227904, -1.6636203354619519, -1.6866570090936022, -1.6969115951204665, -1.6944150244191682, -1.679498275867296, -1.6527914322706214, -1.6152151922880584, -1.567964963114324, -1.5124878452997526, -1.4504530009029843, -1.3837160646837543, -1.314278411018771, -1.2442422228094707, -1.1757624194644374, -1.1109965862573195, -1.0520541047871776, -1.0009457123902168, -0.959534716379887, -0.9294910568792145, -0.912249350453167, -0.908971957176688, -0.9205179983071657, -0.9474191131332244, -0.9898625851846595, -1.047682293644903, -1.1203577597408299, -1.2070213646239965, -1.3064736195152866, -1.417206175442601, -1.5374320734898745, -1.6651225616598002, -1.798049645518103, -1.933833400634483, -2.069992958883934, -2.2039999907756727, -2.3333334443527027, -2.4555342693789926, -2.568258854300681, -2.669329932880185, -2.7567837767556926, -2.828912578037564, -2.8843010402841385, -2.9218563340234094, -2.9408307310477486, -2.9408364061555314, -2.9218520815956754, -2.8842213836430495, -2.8286429777655857, -2.7561527439420193, -2.6680984421080143, -2.5661074948712908, -2.452048676247185, -2.3279886373143195, -2.196144318947586, -2.058832395289818, -1.918416957147703, -1.7772566805053103, -1.6376527310309579, -1.5017986307467548, -1.3717332586201576, -1.2492980741362465, -1.1360995440258432, -1.033477620005854, -0.9424809629538888, -0.863849440198799, -0.7980042417646276, -0.7450457729513819, -0.7047592892425272, -0.6766280499298618, -0.6598535837197501, -0.653382487438062, -0.6559390220096879, -0.6660626319906405, -0.6821493994334819, -0.7024963525631809, -0.7253474867910074, -0.7489403214739532, -0.771551811290795, -0.7915424561688696, -0.8073975076357915, -0.8177642508465265, -0.821484448225197, -0.8176211599115373, -0.8054793047040593, -0.7846194891601287, -0.7548648077818552, -0.7163004993439986, -0.6692665288002191, -0.6143433461810798, -0.5523312488833017, -0.4842239373381817, -0.41117700212352526, -0.33447220942797, -0.2554785581569852, -0.17561116322214393, -0.09628907364964784, -0.018893159736289838, 0.055274800054938227, 0.12503073432385137, 0.18934355868876654, 0.24736617044136955, 0.2984613196567496, 0.3422216518759311, 0.37848336903846846, 0.4073331212627676, 0.4291079181498792, 0.44438803006191413, 0.45398303269236456, 0.4589113275645548, 0.4603736423135976, 0.45972117337329077, 0.45841917595763954, 0.45800692836259, 0.4600550964839451, 0.4661215974996772, 0.4777071069910913, 0.4962113701630353, 0.5228914647783897, 0.5588231211938258, 0.6048661344518985, 0.6616348064370562, 0.7294742349958685, 0.808443124619745, 0.8983036332929657, 0.9985185963713056, 1.1082562851798927, 1.226402669951138, 1.3515809684453943, 1.4821780778043456, 1.6163773124756255, 1.7521967097963276, 1.887532021088623, 2.020203383531887, 2.1480045697449355, 2.268753640457911, 2.3803437827354204, 2.480793103085556, 2.5682921618737478, 2.641248082428961, 2.698324144017621, 2.738473870687564, 2.760968755400422, 2.765418907813935, 2.7517860809483934, 2.7203887127273183, 2.671898808627391, 2.6073306867709034, 2.5280218019845107, 2.4356060558593007, 2.331980181017612, 2.2192639551820226, 2.0997551501460396, 1.9758802486931166, 1.8501420657535486, 1.7250654860853303, 1.603142577636906, 1.4867783563319241], [1.410089917886394, 1.3088922022294973, 1.2188289313300875, 1.1415758306886286, 1.0785139921938558, 1.0307006525842546, 0.9988473536356874, 0.9833059784491442, 0.9840629707055664, 1.0007418490678068, 1.0326139317830274, 1.0786169917689115, 1.1373813747895218, 1.2072629372991677, 1.286382000423341, 1.3726673762279789, 1.4639044052857797, 1.5577858533923155, 1.651964452285052, 1.7441058358510169, 1.8319406203196826, 1.9133144043252948, 1.986234521739435, 2.0489124653449267, 2.0998010105811993, 2.137625202938224, 2.1614065267448574, 2.1704797432398224, 2.164502067695658, 2.143454544473179, 2.1076356705329435, 2.0576475073852247, 1.9943747040500732, 1.9189570248337995, 1.8327561314086995, 1.7373175050051965, 1.6343285081749999, 1.52557367381593, 1.4128883698570283, 1.2981120197690366, 1.1830420611958905, 1.0693897975430262, 0.9587392410905604, 0.85250996262309, 0.7519248538610136, 0.6579835779415197, 0.5714423331846046, 0.49280039021207916, 0.42229368635954456, 0.3598955786935414, 0.30532467243485395, 0.2580594598501921, 0.21735933028756146, 0.18229134938392674, 0.15176205865472212, 0.12455341936838851, 0.09936192000551414, 0.07483978731743565, 0.04963718900994558, 0.02244429267224809, -0.0079679486828243, -0.042709379370785575, -0.08273562416468042, -0.12881741458424772, -0.1815150876129559, -0.2411589512644874, -0.30783605866158104, -0.38138376549030345, -0.4613902690781873, -0.5472021453909446, -0.637938717562414, -0.7325129108005395, -0.8296580781882459, -0.9279601243535986, -1.0258941132328645, -1.1218644257895374, -1.2142474366701332, -1.3014356078756282, -1.3818818544585325, -1.4541430231762569, -1.5169213403719455, -1.5691027298074018, -1.609790973701011, -1.6383367890833191, -1.654361014367339, -1.6577712447293518, -1.6487714159690074, -1.6278640109829283, -1.5958447465187804, -1.5537897859157712, -1.5030357113991084, -1.4451526724903057, -1.381911300642939, -1.3152441399600212, -1.247202485773057, -1.1799096433765341, -1.1155117152508296, -1.0561270942076395, -1.0037958802536415, -0.9604304494970162, -0.9277683837607696, -0.9073289201055801, -0.9003740013301683, -0.9078749035463908, -0.9304852876231693, -0.9685213707672066, -1.0219497463971605, -1.0903831988498158, -1.1730846687494394, -1.268979329723965, -1.3766745423290236, -1.4944872613078797, -1.6204782923181005, -1.752492628407251, -1.8882049488914296, -2.0251692375104744, -2.160871375898624, -2.292783495006824, -2.418418822959945, -2.5353857540304836, -2.641439880318953, -2.7345327749565835, -2.812856392052936, -2.8748820523489393, -2.9193931120852663, -2.945510562829746, -2.9527109782684797, -2.940836406155532, -2.910095995298289, -2.8610593439621335, -2.794641752625816, -2.712081755827099, -2.6149114902457806, -2.504920624751655, -2.384114728815133, -2.2546690847981643, -2.1188790541060323, -1.979108184488178, -1.8377352940999803, -1.6971017861632718, -1.559460435818018, -1.4269268484164481, -1.3014347171899197, -1.1846959097429823, -1.0781662896896715, -0.9830180350370037, -0.9001190522582244, -0.8300199084377116, -0.7729485177977365, -0.7288126279486286, -0.6972099600618749, -0.6774456705686049, -0.6685566245285219, -0.6693418068549002, -0.678398051133482, -0.6941601404073827, -0.7149442330553926, -0.7389934922003504, -0.7645247507150369, -0.7897750269043389, -0.8130467186596324, -0.8327503458889343, -0.8474437811797821, -0.8558670051065661, -0.8569715428527078, -0.8499438797938453, -0.8342223117820686, -0.8095068570627271, -0.7757620367036406, -0.733212514568531, -0.6823317715718289, -0.6238241675781652, -0.5586009133592168, -0.48775063024173027, -0.4125053125752257, -0.33420262446764254, -0.2542455544698833, -0.1740605177324159, -0.0950550329710379, -0.018576110433994323, 0.05412953324219568, 0.12195236633239763, 0.18395304882585803, 0.2393906658124273, 0.2877454231082221, 0.328735185037202, 0.36232539457300533, 0.3887320882990789, 0.4084178985002307, 0.4220811175963877, 0.43063808143157906, 0.4351993030363167, 0.4370399529400445, 0.43756543173610674, 0.4382729115773499, 0.44070983225323146, 0.4464304216651575, 0.45695136769147393, 0.4737077971076588, 0.4980107166048116, 0.5310070409684908, 0.5736432748148569, 0.62663382832693, 0.6904348362719601, 0.7652242159285304, 0.850888546694377, 0.9470171858555175, 1.052903855440771, 1.1675557487200074, 1.2897100163660178, 1.4178573062905953, 1.550271852333919, 1.6850474398139645, 1.8201384246301122, 1.9534048509793838, 2.082660604120893, 2.20572345178662, 2.3204657729242397, 2.424864746922268, 2.517050781036108, 2.5953529883907653, 2.658340592920598, 2.7048592294327745, 2.7340612244711253, 2.745429083996248, 2.738791573701678, 2.7143319531849905, 2.672588111925476, 2.614444548539572, 2.541116330369387, 2.4541253633293927, 2.355269487370946, 2.246585086381024, 2.130304058554256, 2.008806130404695, 1.8845676112430478, 1.7601077723347545, 1.6379340939165155, 1.520487652318715, 1.4100899178863973], [1.3383923856729054, 1.245387178280643, 1.1646435637149992, 1.0976552371974846, 1.0456022158483447, 1.0093260154020114, 0.9893125300150665, 0.9856829993886064, 0.9981932550650635, 1.0262412409914115, 1.0688826070544788, 1.1248539830657445, 1.1926033592485246, 1.2703268320619512, 1.3560108252333056, 1.4474787687612993, 1.5424411164559486, 1.6385475077394074, 1.733439833715512, 1.8248049519757836, 1.9104258095555202, 1.9882297784453622, 2.056333081923723, 2.1130802908182473, 2.157077994084301, 2.187221894662865, 2.202716745788437, 2.2030887206715466, 2.1881899953668897, 2.1581955160272743, 2.11359211290503, 2.055160309681581, 1.9839493534008739, 1.9012461531174554, 1.8085389603628355, 1.7074767481530504, 1.5998253445133226, 1.4874214490012603, 1.3721257047569835, 1.2557760131973514, 1.1401422633375047, 1.0268836033427076, 0.9175093094909856, 0.8133442091631102, 0.7154994923206192, 0.6248496033177657, 0.5420157454582952, 0.4673563585046395, 0.4009647487398035, 0.342673866737633, 0.29206804437069783, 0.24850132440385475, 0.21112184776929596, 0.17890160952354636, 0.15067075841511893, 0.1251555003526324, 0.1010185757235725, 0.0769012167261156, 0.05146545522294077, 0.023435644979917285, -0.008361915343799358, -0.04496232102624671, -0.08722934619737917, -0.1358275555435612, -0.19119999733233647, -0.2535520866988223, -0.32284212682413016, -0.3987787426927688, -0.48082532192392086, -0.5682113742993946, -0.6599505406976928, -0.7548648077818547, -0.851614321410006, -0.9487320435012128, -1.0446623677776798, -1.1378027027283153, -1.2265469480537277, -1.3093297358898521, -1.384670281719022, -1.4512146928004208, -1.507775614188414, -1.5533681532239951, -1.5872411113295573, -1.6089026648762195, -1.6181397720610446, -1.6150307368019448, -1.5999505298241516, -1.5735686471816348, -1.5368394729561035, -1.4909853011610932, -1.4374723572500585, -1.3779803374483763, -1.3143661499400425, -1.2486226915699545, -1.1828336233939403, -1.1191252148306952, -1.0596164066217124, -1.0063682952048716, -0.9613342640629614, -0.926311980455194, -0.9028984387566561, -0.8924491652398427, -0.8960426050800547, -0.9144505928851285, -0.9481156660046371, -0.9971358186917456, -1.0612571187777582, -1.1398744211631016, -1.2320402186938504, -1.3364814756095802, -1.4516240964934757, -1.5756244992372748, -1.7064075884733974, -1.8417102704485757, -1.9791295152399, -2.1161738608711267, -2.2503171690214923, -2.3790533857316096, -2.499951034202961, -2.6107061711268695, -2.7091925728836794, -2.7935079825916707, -2.8620153417991334, -2.913378049352206, -2.9465884317512345, -2.960988770681061, -2.956284410438261, -2.9325486563706775, -2.890219370605202, -2.830087368518332, -2.753276913803823, -2.6612187968871788, -2.5556166562897897, -2.4384073611172608, -2.311716411301252, -2.1778094272233703, -2.0390408891341507, -1.8978013472371213, -1.7564643540224762, -1.617334370724577, -1.4825968697080203, -1.3542717949693934, -1.234171455313198, -1.1238638113426003, -1.0246419810521805, -0.9375006329328053, -0.8631197639844285, -0.8018561771455313, -0.7537427829229105, -0.7184956581379726, -0.6955286054323473, -0.6839747751593721, -0.6827147410013156, -0.6904102662671014, -0.7055428631102297, -0.7264561351336454, -0.751400807712729, -0.778581291921696, -0.8062025985520502, -0.8325164189981935, -0.8558652196484734, -0.8747232550167855, -0.8877334906230022, -0.8937395373477683, -0.89181183179817, -0.8812674487290304, -0.8616830979126814, -0.8329010348165173, -0.7950277975531144, -0.748425867186346, -0.6936985299532813, -0.6316683937255788, -0.5633501727165281, -0.4899184999805172, -0.41267165300136993, -0.3329921804768723, -0.25230549571144995, -0.17203755190401354, -0.09357273583155695, -0.0182131084721572, 0.05285991579089002, 0.11862042463470883, 0.17822846240710416, 0.23105526358925943, 0.2767025811338493, 0.31501557964022747, 0.34608893098774673, 0.37026592717820694, 0.38813060724887644, 0.40049307759004127, 0.40836838320547636, 0.4129494568641318, 0.41557482939777945, 0.4176919236189642, 0.4208168729085705, 0.4264919004099713, 0.43624136351596215, 0.4515276091481234, 0.4737077971076586, 0.503992831151387, 0.5434094907830925, 0.592766782144825, 0.6526274256435869, 0.7232852735131791, 0.8047493054442781, 0.8967346882958004, 0.9986612107391085, 1.1096592198302626, 1.2285829985274095, 1.354031335756432, 1.4843748584612977, 1.6177895227181873, 1.7522955027736156, 1.885800576772663, 2.016146989520095, 2.141160678879298, 2.2587016857705846, 2.366714529924457, 2.463277325608237, 2.5466484337696844, 2.6153094989778833, 2.668003800001057, 2.703768949948803, 2.721963113065336, 2.722284057335247, 2.704780531376074, 2.669855636533452, 2.6182620562243852, 2.5510891997311447, 2.4697425120635708, 2.375915390424795, 2.271554326604483, 2.158818058899161, 2.0400316628845037, 1.917636633954848, 1.7941381129550686, 1.672050477027046, 1.5538425592219545, 1.4418837714515342, 1.3383923856729085], [1.272292353257484, 1.1882606732775454, 1.1175023056260776, 1.0613162900278785, 1.0206716055461333, 0.9961869555540986, 0.9881185119884569, 0.9963558897034507, 1.0204264261557594, 1.0595076444654508, 1.1124475839142318, 1.177792495873296, 1.2538212295166646, 1.3385854746810697, 1.4299548926773915, 1.5256660530338968, 1.6233740077648242, 1.7207052768644573, 1.8153109906800358, 1.904918937235685, 1.9873832953340385, 2.060730896477443, 2.1232029487291704, 2.17329127129715, 2.209768226963455, 2.231709697044476, 2.2385106164251183, 2.2298927700721753, 2.2059047427415055, 2.1669141056456382, 2.11359211290503, 2.046891362013845, 1.9680170418560652, 1.8783925448655814, 1.779620353002373, 1.6734392170872372, 1.56167873305434, 1.44621247484647, 1.328910870691145, 1.2115950067834103, 1.0959925101307204, 0.9836966013901651, 0.8761293205637943, 0.7745098157001076, 0.6798284501784134, 0.5928273311664822, 0.5139876943336318, 0.44352440211908145, 0.3813876292967765, 0.32727162487697936, 0.28063025819679766, 0.24069888393574226, 0.20652190009827973, 0.1769852287650984, 0.15085282524156524, 0.12680622023032245, 0.1034860243436419, 0.07953427652002053, 0.05363649889337801, 0.024562330832865107, -0.008796346057671838, -0.04739081323110045, -0.09198537889414322, -0.14313251128721566, -0.20115391495626572, -0.2661280683256705, -0.33788457238277936, -0.41600548266082565, -0.4998336144619332, -0.5884876290186807, -0.6808835306766229, -0.7757620367036403, -0.8717211262807353, -0.9672529375548417, -1.0607840648559081, -1.1507182152949473, -1.2354801173665642, -1.3135595356206797, -1.3835542359835562, -1.4442107662090553, -1.494461964800957, -1.5334601884126353, -1.5606053503480215, -1.5755669888505373, -1.5782997302749286, -1.5690516753756119, -1.5483654127730893, -1.5170715478101067, -1.4762748228971219, -1.427333092384402, -1.3718295963110312, -1.3115391485242462, -1.2483890113337706, -1.1844153671134834, -1.1217164135843907, -1.0624032009427185, -1.0085493931810041, -0.9621411712046918, -0.925028500702211, -0.8988789629516273, -0.8851352923560598, -0.884977681741333, -0.8992918072750814, -0.9286433918855628, -0.9732599724726246, -1.0330203657292143, -1.107452144169324, -1.1957372424489565, -1.2967256189438428, -1.4089567035815809, -1.5306881748653518, -1.6599314314828841, -1.7944929612268414, -1.93202066616066, -2.07005408158837, -2.2060773304227483, -2.3375735863680354, -2.4620797806369277, -2.57724027868089, -2.680858275856639, -2.7709437135573216, -2.8457565988422666, -2.903844719034754, -2.94407487549308, -2.965656914571646, -2.9681600049349637, -2.951520794703938, -2.916043274914398, -2.862390372755593, -2.7915674942388793, -2.704898426553844, -2.603994190770641, -2.4907156013665284, -2.367130436276051, -2.2354662462323214, -2.0980599320724127, -1.9573052910347863, -1.8155997761715545, -1.6752917258437663, -1.5386293026190048, -1.4077123332514159, -1.284448165034539, -1.1705125506224423, -1.067316446014406, -0.9759794579844693, -0.8973105115119195, -0.831796128853666, -0.7795965242332236, -0.740549526347884, -0.7141821497524944, -0.6997294503749324, -0.6961601245228723, -0.7022081490661505, -0.716409616974452, -0.7371438005474401, -0.7626773774399398, -0.7912106842871021, -0.8209248210278917, -0.8500284168499047, -0.8768028862377027, -0.89964505036336, -0.9171060737482439, -0.9279257667922602, -0.9310614288098558, -0.9257105504516945, -0.9113268551498243, -0.8876293324190849, -0.8546040970917166, -0.8124990932756334, -0.7618118453501764, -0.7032706360251524, -0.6378096589205607, -0.5665388460720086, -0.49070920539558005, -0.41167461608668293, -0.33085111835955316, -0.2496747956566682, -0.16955938094324755, -0.0918547231357521, -0.017807225011635872, 0.051476689239167754, 0.11506309896526827, 0.17221823202401249, 0.22243048504648646, 0.26542622117367737, 0.30117890975485806, 0.32991134611170764, 0.35209086997926753, 0.36841768405990694, 0.37980655463002805, 0.3873623497382027, 0.392350032814787, 0.39615987634504907, 0.40026878789339926, 0.40619874593738686, 0.4154734229698909, 0.4295741260789024, 0.4498962093211811, 0.4777071069910909, 0.5141071024067599, 0.5599938838845906, 0.6160318496582329, 0.6826270088063326, 0.7599081885966597, 0.8477151034005014, 0.9455936703204512, 1.0527987761240352, 1.1683045134749503, 1.2908217164535827, 1.418822440654609, 1.550570856366602, 1.6841598589136064, 1.8175525523118456, 1.9486276347043914, 2.0752276098275595, 2.195208670703057, 2.306491051864402, 2.4071086260465413, 2.495256530995755, 2.569335651751069, 2.6279928525251113, 2.670155948565787, 2.6950625298234985, 2.702281891967147, 2.691729492816215, 2.6636735296453713, 2.6187334207584123, 2.5578701686380976, 2.482368777121651, 2.3938130866533416, 2.2940535750319087, 2.1851688417015387, 2.0694216473395515, 1.9492105134888567, 1.8270179959911317, 1.7053568283045093, 1.5867151843951068, 1.4735023344370166, 1.3679959594361621, 1.272292353257487], [1.2123490568249704, 1.1379960033025693, 1.077803993438417, 1.0328664331164263, 1.0039330855316084, 0.9913946354323221, 0.9952754014886634, 1.0152343519120761, 1.0505743812896016, 1.1002596106633153, 1.1629402829446758, 1.236984646418264, 1.320517054710071, 1.411461366152577, 1.5075886024849487, 1.6065677292406755, 1.7060183503293826, 1.8035640688638526, 1.8968852561435827, 1.9837699910634297, 2.0621619825018915, 2.1302043661558554, 2.1862783728236432, 2.229035994641002, 2.2574259260059018, 2.270712223143948, 2.2684853063124035, 2.250665117054808, 2.217496435040702, 2.169536550114892, 2.1076356705329435, 2.0329106234210275, 1.9467125639807696, 1.8505895519453648, 1.7462449738314005, 1.6354928847227317, 1.5202114113925336, 1.4022953979201822, 1.2836094847106447, 1.1659427918336092, 1.0509663284656585, 0.9401941732642605, 0.834949367739969, 0.7363353387755424, 0.6452135205922503, 0.5621876844003125, 0.4875953098059665, 0.4215061501905103, 0.3637279593196997, 0.3138191630473155, 0.2711080827598422, 0.2347181506228593, 0.20359840491330958, 0.17655842055697155, 0.15230671876632304, 0.12949161316433416, 0.10674339013386319, 0.08271668982182079, 0.05613195200939686, 0.02581481795894445, -0.009267565344020238, -0.04997430984238847, -0.09696348406622861, -0.15067047858408955, -0.2112926258374459, -0.27878049764977186, -0.35283612944131787, -0.4329182393791552, -0.5182543279360023, -0.6078593632587678, -0.7005605849316964, -0.7950277975531138, -0.8898083801327945, -0.9833661113699911, -1.0741228076151164, -1.1605016924087839, -1.2409713659539507, -1.3140892210483823, -1.3785431595040738, -1.4331904997904366, -1.4770930317078876, -1.5095472657640834, -1.530109041347126, -1.5386117959100158, -1.535177953790327, -1.5202230641157826, -1.4944524982486038, -1.4588507038942562, -1.4146632006871507, -1.3633716860749023, -1.3066627960432586, -1.2463912282411957, -1.1845380812717257, -1.1231653896096554, -1.06436793559525, -1.0102234956171008, -0.9627427249704997, -0.9238199036891438, -0.8951857533579675, -0.8783634927279783, -0.8746292288154457, -0.8849776817413327, -0.9100941181943971, -0.9503332230458346, -1.0057054748164844, -1.0758714123737332, -1.1601439917535576, -1.2574990379610869, -1.3665936017428242, -1.4857918404159094, -1.6131978595647218, -1.7466947832485886, -1.8839891684658527, -2.0226597487298603, -2.160209384961697, -2.2941190221311474, -2.4219023991635225, -2.5411602388520063, -2.649632654411666, -2.7452485496695873, -2.8261708597470694, -2.8908365767721245, -2.937990628300375, -2.9667128217319365, -2.9764372325532538, -2.966963593704645, -2.9384604334101856, -2.8914599047825837, -2.8268444476640346, -2.7458256166906216, -2.649915594769529, -2.5408920835396622, -2.4207574177687095, -2.291692885265357, -2.1560093445084183, -2.016095316161326, -1.8743637799536383, -1.7331989337793279, -1.5949041667292758, -1.4616524623371774, -1.3354403835122668, -1.2180466981166869, -1.1109965862573197, -1.0155322300570504, -0.9325904274517334, -0.8627876973878045, -0.8064131589932497, -0.7634292764370348, -0.7334803689932988, -0.7159085970250201, -0.7097769538405115, -0.7138986250895566, -0.7268719256699303, -0.7471198927051277, -0.7729335052148073, -0.8025174192260558, -0.8340370532085177, -0.8656658341020331, -0.8956314193543915, -0.9222597450701655, -0.9440158136258444, -0.9595402242583969, -0.967680564843952, -0.9675169194027108, -0.9583809003141268, -0.9398677828758705, -0.91184149841655, -0.8744324261607289, -0.8280281088035337, -0.773257197627532, -0.7109671054386467, -0.6421960052806073, -0.5681399558061796, -0.49011605676130904, -0.40952263721462717, -0.32779755247003955, -0.24637571121840676, -0.16664697129783118, -0.08991553004843948, -0.017361894010170707, 0.0499915563095736, 0.11131048590894761, 0.1659732069452842, 0.213589299713337, 0.25401174633558055, 0.28734223986948876, 0.31392950963338, 0.33436068591047097, 0.34944590918370033, 0.36019656606134826, 0.3677977015782298, 0.3735753113370854, 0.3789593530700459, 0.38544343217170896, 0.3945422066327532, 0.40774762123805125, 0.42648511719965526, 0.4520709705913999, 0.4856718907866335, 0.5282679590593498, 0.580619908802823, 0.643241644356354, 0.7163787677666448, 0.799993735088738, 0.8937580997042457, 0.9970521236714595, 1.1089718537096138, 1.2283435706533017, 1.3537453347815305, 1.4835351689948004, 1.615885251910199, 1.7488213378430426, 1.880266484260409, 2.0080880530856264, 2.1301468631196943, 2.2443473091243464, 2.348687230405982, 2.4413063089587617, 2.5205318045364873, 2.584920490850055, 2.6332957421221557, 2.6647788304640714, 2.6788136293108207, 2.675184073212904, 2.6540238958810813, 2.615818352345341, 2.5613978229383956, 2.491923391863234, 2.408864686582712, 2.313970451436128, 2.2092325051518493, 2.0968438929542694, 1.9791521857963281, 1.858608998388242, 1.737716891196121, 1.6189748871335035, 1.5048238696292637, 1.3975931342177486, 1.2994493405968646, 1.2123490568249728], [1.1590696437878338, 1.0950184302087247, 1.0458844928368154, 1.0125463651263056, 0.9955282712583591, 0.9949896002334618, 1.010722647991985, 1.042158665681596, 1.0883820551240533, 1.1481523595104968, 1.2199335130638074, 1.3019296423222853, 1.3921265579674027, 1.4883379434579087, 1.5882551383413541, 1.6894993325925007, 1.789674935614536, 1.8864228608632496, 1.9774724749075572, 2.0606909978631287, 2.134129209527897, 2.196062410490016, 2.2450257075773488, 2.2798428352655424, 2.2996478855123876, 2.303899493941635, 2.292387216010145, 2.2652300181643783, 2.2228670013023266, 2.166040662368157, 2.0957731799865598, 2.013336377277979, 1.9202161652981988, 1.8180724002579076, 1.7086951936602357, 1.593958794202249, 1.4757742118333395, 1.356041776565896, 1.2366048170399881, 1.119205606744284, 1.0054446602137848, 0.8967443691920087, 0.7943178520545402, 0.6991437517383442, 0.6119475615298628, 0.5331898882954965, 0.46306188339109333, 0.4014878870936134, 0.34813514760766995, 0.3024302951630288, 0.26358207997286104, 0.2306097241753456, 0.20237609630654707, 0.17762479588973953, 0.15502013839227866, 0.13318895951529172, 0.11076311430567651, 0.0864215319749249, 0.05893070190843055, 0.027182509750311785, -0.009771586474452894, -0.05269095330973373, -0.1021215446912612, -0.15837768281988224, -0.22153035189400383, -0.2914023293937558, -0.3675703010613746, -0.44937392327281167, -0.5359316147746698, -0.6261626833821751, -0.7188152266799468, -0.8124990932756329, -0.9057230566140194, -0.9969352402048914, -1.0845657442557122, -1.1670703614263682, -1.24297423536802, -1.3109143107945556, -1.369679448255129, -1.418247129985193, -1.455815763942704, -1.4818316994246674, -1.4960101969007564, -1.4983497437093456, -1.4891392723491232, -1.4689580151689134, -1.4386679139034446, -1.3993986901188438, -1.3525258685296635, -1.299642224672838, -1.2425232970653195, -1.1830877574845846, -1.1233535675151092, -1.0653909615840835, -1.011273383500788, -0.9630275627724808, -0.9225839471310144, -0.8917287079219803, -0.8720585051767593, -0.8649391399456953, -0.8714691341864146, -0.892449165239842, -0.9283581453995239, -0.9793365805795672, -1.0451776694046298, -1.1253264193803696, -1.2188868646565638, -1.3246372749619295, -1.4410530523406917, -1.5663368260866541, -1.698455081322971, -1.835180497317589, -1.9741390317796939, -2.112860670502988, -2.2488326706976016, -2.3795540634451515, -2.502590147492481, -2.6156257039160304, -2.7165156891386846, -2.803332221712326, -2.8744067648055887, -2.9283665193690336, -2.964164179752409, -2.9811003607998083, -2.9788381793277843, -2.9574096591704953, -2.917213823123429, -2.8590065324106515, -2.7838823299415165, -2.693248732856052, -2.5887935980877894, -2.4724463475754446, -2.3463339833860095, -2.2127329439026115, -2.0740179474727847, -1.9326090372301301, -1.7909180786059153, -1.6512959684738862, -1.5159817918048983, -1.387055108780297, -1.2663924738887966, -1.1556291806729684, -1.05612709420764, -0.9689492813701579, -0.8948419802860403, -0.834224269189702, -0.7871856058141237, -0.7534912159890833, -0.7325951191292049, -0.7236603934303975, -0.7255861094032191, -0.7370402011178677, -0.7564974041021009, -0.7822812706298882, -0.812609180015819, -0.8456391957106585, -0.8795175840167483, -0.9124258019279741, -0.942625784028729, -0.9685024099003955, -0.988602112700727, -1.001666694432257, -1.0066615411973092, -1.0027975791796204, -0.9895464754421293, -0.9666487627436894, -0.9341147500246081, -0.8922182653872092, -0.8414834616384896, -0.7826650911590654, -0.7167228225798339, -0.6447903223306679, -0.5681399558061797, -0.48814407238355295, -0.4062339231002419, -0.32385731735751094, -0.24243615414386607, -0.16332496327124502, -0.08777156302063265, -0.01688088316954868, 0.04841708189872224, 0.10739433427028015, 0.15954622290899148, 0.20460650801841157, 0.2425557282417978, 0.2736226344725142, 0.2982786351212339, 0.317225380352039, 0.33137579242053544, 0.3418290212609138, 0.3498399645020951, 0.3567841350703868, 0.36411878378300216, 0.37334128567184893, 0.3859458745918308, 0.4033798589930687, 0.4270004712911317, 0.45803349349434286, 0.49753476281927017, 0.546355593854015, 0.605113060033599, 0.6741659590634694, 0.7535971473708737, 0.8432027711271739, 0.9424887497720873, 1.0506746865482597, 1.1667051938408624, 1.2892684337736047, 1.4168214912269368, 1.547622021812405, 1.6797654557506883, 1.8112268941351, 1.9399067103766425, 2.063678769870717, 2.180440107662404, 2.288160859026634, 2.3849332226308753, 2.4690182507890555, 2.538889305979088, 2.593271096275646, 2.6311733029234414, 2.6519179385482237, 2.655159721461818, 2.6408989166111687, 2.6094862729418904, 2.5616198759306554, 2.4983339281756125, 2.420979665472567, 2.331198805981262, 2.2308901112350714, 2.122169805417776, 2.007326749396565, 1.888773394761537, 1.7689936473980634, 1.6504888473255919, 1.5357231197526318, 1.4270693703086779, 1.3267571847473107, 1.2368238503467166, 1.1590696437878325], [1.1129048820895788, 1.0596915637119604, 1.0220138572401023, 1.0005280030276498, 0.9955282712583589, 1.0069414349285597, 1.0343295608030443, 1.0769010391341294, 1.133529577630307, 1.2027806966800314, 1.2829450857550864, 1.3720780195320643, 1.4680438904874324, 1.5685647959660125, 1.6712720248512345, 1.7737592241980362, 1.8736359910537355, 1.9685806299882997, 2.0563908426350803, 2.135031171110101, 2.202676101105874, 2.2577478406237543, 2.298947923954796, 2.3252819443087276, 2.336076888599832, 2.330990730109178, 2.310014124546562, 2.2734642477468054, 2.221971004105598, 2.1564560191976776, 2.0781050033037385, 1.9883342305645184, 1.8887520173309635, 1.7811161996206653, 1.6672887006205956, 1.5491883427259827, 1.4287430931930902, 1.3078429373502731, 1.1882945484375258, 1.07177886925011, 0.9598126392872997, 0.8537147941771245, 0.7545785345161773, 0.663249712244233, 0.5803120180579371, 0.5060792773287335, 0.440594978977985, 0.38363897639255884, 0.3347411164035997, 0.2932013761999418, 0.25811592322498766, 0.22840836374003126, 0.2028653155619064, 0.18017533274554673, 0.15897012736156005, 0.1378669780599976, 0.11551118817364214, 0.0906174583382572, 0.06200906989988433, 0.02865383491552456, -0.010304145202134178, -0.05551775960010729, -0.10741592124230416, -0.16618891755920923, -0.23178047733087656, -0.30388677714962337, -0.3819624294837543, -0.4652333118097718, -0.5527159171322167, -0.6432427350183116, -0.7354930133918645, -0.8280281088035332, -0.9193305103599055, -1.0078455230894978, -1.0920245228082328, -1.1703686484354545, -1.24147178042722, -1.3040616660366107, -1.3570380932447632, -1.3995070844638295, -1.4308101768187746, -1.4505479756270547, -1.4585973086628317, -1.4551214674289326, -1.4405731940290536, -1.4156902540467944, -1.3814836225639837, -1.3392184974227523, -1.2903885363721768, -1.2366838882595812, -1.1799537485620215, -1.1221643122621672, -1.0653531187366105, -1.0115808808410913, -0.9628819612372839, -0.9212147013571313, -0.888412821095124, -0.8661390899408233, -0.8558424231434006, -0.858719480703905, -0.8756817442994879, -0.9073289201055789, -0.953929366955739, -1.015408082957857, -1.0913426036094738, -1.180966975011202, -1.28318377159213, -1.3965839335860581, -1.5194740100921023, -1.649910213568013, -1.785738525464692, -1.9246399445086122, -2.064179842531451, -2.2018602908654605, -2.3351741456962642, -2.4616596352554465, -2.578954176492426, -2.684846164298552, -2.7773235221232326, -2.8546178778362123, -2.9152433311490897, -2.9580289063361316, -2.982143933301906, -2.9871157676057445, -2.9728394417990835, -2.939579031941879, -2.8879607197808945, -2.818957728014187, -2.7338674985445506, -2.634281666963723, -2.522049556258571, -2.3992360647762956, -2.2680749541502943, -2.130918649021525, -1.990185739445872, -1.8483074269765547, -1.70767417538463, -1.570583816403228, -1.4391923200752765, -1.3154683693151417, -1.2011527809409552, -1.0977236931452068, -1.006368295204872, -0.9279617127786441, -0.8630534854317788, -0.8118618864452661, -0.7742761431167503, -0.7498664233777829, -0.7379012663700325, -0.737371955263309, -0.7470231644532699, -0.7653890644029238, -0.7908339394094442, -0.8215962695807852, -0.8558351507882114, -0.8916778771518614, -0.9272674908409806, -0.9608091140187803, -0.9906139172825795, -1.015139646858885, -1.033026727322304, -1.0431290752697073, -1.0445388991532891, -1.0366049177941912, -1.0189436009675352, -0.9914432155450678, -0.9542606454558938, -0.9078111385231171, -0.852751313406901, -0.7899559309083793, -0.7204890914772077, -0.6455706609745574, -0.5665388460720088, -0.4848099361424808, -0.4018362977530949, -0.3190637491939961, -0.23788945486856672, -0.15962146255461984, -0.08544096098354294, -0.01636826205914134, 0.04676658677258728, 0.10334777646420779, 0.15299165510832474, 0.1955581084442088, 0.23115508998930986, 0.26013616763378505, 0.2830911360557436, 0.3008299257428102, 0.31436021513504964, 0.3248593179691453, 0.3336410690914316, 0.3421185649640014, 0.35176372641552023, 0.3640647380294915, 0.38048247867357055, 0.40240708947997106, 0.4311158282245175, 0.4677333323881789, 0.5131953578235939, 0.5682169772156446, 0.6332661144342286, 0.7085431600837454, 0.7939672632860587, 0.889169728714771, 0.9934947702535819, 1.106007687804428, 1.2255103463356363, 1.3505636509250465, 1.4795165329639866, 1.6105407953329538, 1.7416710124574575, 1.8708485485447115, 1.995968647360094, 2.1149294624405752, 2.225681839848897, 2.3262786379518885, 2.4149223710433607, 2.490009995969736, 2.5501737225544883, 2.5943168181272487, 2.6216434917250044, 2.631682081783474, 2.624300929040409, 2.599716490101004, 2.558493432442219, 2.5015366440368743, 2.4300752855564944, 2.3456392054937627, 2.2500282238114124, 2.145274963322555, 2.0336020656657587, 1.917374766569908, 1.7990499197042156, 1.6811226469391063, 1.5660718531018294, 1.4563058737857912, 1.3541095246819141, 1.2615937902118557, 1.1806493286716016, 1.1129048820895777], [1.0742453465039652, 1.032314285088428, 1.0063940430270113, 0.9969130276021828, 1.0039330855316082, 1.0271490215878287, 1.0658964147572103, 1.1191675360691637, 1.1856349803384731, 1.2636824417198604, 1.3514418946004834, 1.4468362910339048, 1.5476267572840563, 1.651463168201605, 1.7559369015891488, 1.8586345272462637, 1.957191168125154, 2.0493422843353915, 2.1329726742242108, 2.206161559299366, 2.267222719515251, 2.314738769905162, 2.347588815605352, 2.364968886346621, 2.3664047294178046, 2.351756727529674, 2.3212169002991696, 2.275298140493791, 2.214816023992244, 2.1408637110217765, 2.0547806212541584, 1.9581157127554414, 1.852586321008557, 1.7400336162138996, 1.622375812380248, 1.5015603085722826, 1.3795159600173064, 1.2581066642633005, 1.139087405636279, 1.0240638310111314, 0.9144563332319667, 0.8114694978953376, 0.7160676277335011, 0.6289569001095672, 0.5505745411894921, 0.48108521953649386, 0.4203846767443662, 0.36811042794860144, 0.32365918527234333, 0.2862104869886157, 0.254755858675773, 0.22813269382232607, 0.20506192366311288, 0.18418845242846188, 0.16412326698009674, 0.14348609064473608, 0.12094744088430923, 0.09526896947610568, 0.06534101159757315, 0.030216345377902843, -0.010860735839242339, -0.05843081265314816, -0.11280182089800295, -0.17403809622155178, -0.24195628144863368, -0.31612821684008324, -0.39589075078949165, -0.4803622273865581, -0.568465232215715, -0.6589550132015243, -0.7504528434450819, -0.8414834616384891, -0.9305156161543199, -1.0160046540936474, -1.0964360386309884, -1.1703686484354547, -1.2364767125802187, -1.2935892632500567, -1.3407260460566424, -1.3771289124914239, -1.4022878289183243, -1.4159607688306206, -1.4181869065973693, -1.4092926978471267, -1.3898906098291057, -1.3608704501124556, -1.3233834292111406, -1.278819277468039, -1.2287769141622056, -1.1750293328501602, -1.1194835172267465, -1.0641363324886959, -1.0110274449783982, -0.9621904050131035, -0.9196030821344542, -0.8851386670991597, -0.8605184500517031, -0.8472675494932276, -0.8466747026497538, -0.8597571361342212, -0.8872314185668807, -0.9294910568792131, -0.986591438757567, -1.058242548948042, -1.1438097011977721, -1.2423223349879544, -1.352490731632899, -1.4727303125452784, -1.6011929982085906, -1.7358049341845072, -1.8743097345562367, -2.0143162574175646, -2.153349814718233, -2.2889056327562236, -2.4185033220092333, -2.5397410872713233, -2.6503484119229, -2.7482359835821186, -2.8315416915824048, -2.8986716181834136, -2.9483350629475478, -2.9795727804572936, -2.9917777720979046, -2.984708149086164, -2.958491772001104, -2.913622567193601, -2.850948617874041, -2.7716523226006746, -2.677223101578725, -2.569423307073985, -2.450248154077772, -2.321880627262725, -2.1866424368615123, -2.0469421865781805, -1.9052219788420948, -1.7639037151702588, -1.6253363513793304, -1.491745338896536, -1.365185425218875, -1.2474979001509563, -1.140273261992379, -1.0448201421604182, -0.9621411712046922, -0.89291629765988, -0.8374938879398739, -0.7958897450316091, -0.7677939907971479, -0.7525855659888623, -0.7493539183090655, -0.7569272765060964, -0.7739067518045623, -0.798705370733326, -0.8295910289658007, -0.8647322668764545, -0.9022457062592751, -0.9402439554719312, -0.9768827878624028, -1.010406425660465, -1.0391898177937375, -1.0617768838173742, -1.0769138051485088, -1.0835765762669225, -1.0809921791238841, -1.0686529098637485, -1.0463235639060486, -1.014041368989688, -0.9721087413189365, -0.9210791228058676, -0.8617363329840458, -0.7950680330720522, -0.7222340477916406, -0.6445304191942413, -0.5633501727165284, -0.48014185633940587, -0.3963669670735711, -0.31345740373527264, -0.23277408052578255, -0.1555678024398714, -0.08294344188501365, -0.01582836768550643, 0.04505403486679338, 0.09920504820085821, 0.1463649581528534, 0.18652065454557396, 0.21990628613658045, 0.24699694096545283, 0.2684955055514249, 0.2853130350478064, 0.29854313681071476, 0.30943102755476937, 0.3193380653314973, 0.32970267837727524, 0.3419987103436564, 0.35769227303537693, 0.3781982416796556, 0.40483754276902223, 0.43879637021793577, 0.48108842224663884, 0.5325211800793686, 0.5936671519486104, 0.6648408844250802, 0.7460824007406893, 0.8371475660638716, 0.9375057065900521, 1.0463446271349686, 1.1625829852108684, 1.284889792994195, 1.4117106368341241, 1.541300031569755, 1.6717591682613937, 1.8010781730081833, 1.927181874896466, 2.0479779858555665, 2.1614065267448566, 2.2654892941527622, 2.3583781522419116, 2.438400953877624, 2.5041039448377056, 2.554289582992204, 2.5880488091248046, 2.604786935041871, 2.60424246467488, 2.586498331394241, 2.551985215645946, 2.501476796887215, 2.436076987993791, 2.3571993940849865, 2.26653942631019, 2.166039679928423, 2.057849350591217, 1.9442786090514594, 1.8277489789527404, 1.7107408618236775, 1.5957394254373356, 1.4851801144950922, 1.3813950550705745, 1.2865616060576814, 1.2026542624159253, 1.1314010374441468, 1.0742453465039643], [1.0434181141956866, 1.0131182185036423, 0.9991572008938314, 1.0017320231778002, 1.0206716055461331, 1.055441394884094, 1.105156139985866, 1.168600562796822, 1.2442574279636767, 1.3303423383085928, 1.424844425602007, 1.525571968022397, 1.630201851292517, 1.736331702423632, 1.8415334653866002, 1.9434071582668826, 2.0396335522216194, 2.128024543763683, 2.2065700527260295, 2.273480367159975, 2.3272229711566053, 2.3665530292838297, 2.3905368585753988, 2.3985678918910365, 2.39037482070948, 2.3660217964682255, 2.325900762715787, 2.2707161808428498, 2.201462595331688, 2.1193956558232214, 2.025997368664362, 1.922936486185448, 1.8120250544870298, 1.6951722272833138, 1.57433651229702, 1.45147764646202, 1.3285092961281875, 1.2072537486812138, 1.0893997033308327, 0.9764641828421502, 0.8697594769209762, 0.7703658946694066, 0.6791109514042771, 0.59655544804268, 0.5229867234351969, 0.4584191759576397, 0.4026019649923994, 0.3550336203083255, 0.3149831123659023, 0.28151677361519173, 0.25353031399175, 0.2297850467144758, 0.20894733631165385, 0.18963020213001025, 0.1704359593548936, 0.14999875703436286, 0.12702587927981315, 0.10033671149941129, 0.06889833726701373, 0.03185682159189086, -0.011436649377127303, -0.06140546672185608, -0.11823367651012298, -0.18185881120363256, -0.25197167233983503, -0.3280230803460394, -0.4092374250777027, -0.49463267253147847, -0.5830463136929116, -0.673166584948496, -0.7635681499079486, -0.8527513134069004, -0.9391837429409234, -1.0213436032769962, -1.0977629683038848, -1.1670703614263682, -1.2280312923612955, -1.279585703701284, -1.320881313991263, -1.351301943529101, -1.3704900322111009, -1.3783627024557519, -1.3751208809917592, -1.3612511670923444, -1.3375203173457426, -1.3049624037134249, -1.2648588877713172, -1.218712034986479, -1.1682122641032238, -1.1152001838823429, -1.0616242085796823, -1.0094947611310148, -0.9608361660231142, -0.9176373998750704, -0.8818029050934253, -0.8551046795729798, -0.839136833002126, -0.8352737483508492, -0.8446329067596353, -0.8680433272021593, -0.9060204415180039, -0.9587480738551587, -1.0260680248978091, -1.1074775795850287, -1.2021350667822954, -1.3088734052016069, -1.4262213765351688, -1.552432179016966, -1.6855186370724278, -1.8232942797319172, -1.9634193560897615, -2.1034507338582413, -2.240894530025466, -2.3732602531944145, -2.498115197098019, -2.613137815076467, -2.716168826245901, -2.805258855211371, -2.8787114872685753, -2.935120728176048, -2.9734019891757697, -2.992815870808741, -2.992984189504829, -2.973897874783204, -2.9359165577127317, -2.8797598683628656, -2.8064906565331675, -2.7174905413058528, -2.614428376274253, -2.499222384260248, -2.373996863898348, -2.2410344970398337, -2.1027253874645617, -1.9615140354446328, -1.8198454975227016, -1.6801119954062391, -1.544601221839391, -1.4154475451483353, -1.2945872390546809, -1.1837187622138574, -1.0842689853216698, -0.9973661156990637, -0.923819903689144, -0.8641095360840012, -0.8183794335709569, -0.7864429764925662, -0.7677939907971476, -0.7616256386454056, -0.7668561803285151, -0.7821609102921613, -0.8060094241431427, -0.836707249081719, -0.8724407702557405, -0.9113243124605132, -0.9514481921287088, -0.9909265396718789, -1.0279437072170354, -1.0607981211535, -1.087942511463033, -1.1080195486476043, -1.1198920416418032, -1.1226669932627629, -1.115712969865246, -1.0986704148735025, -1.0714547173816356, -1.034252032473628, -0.9875080346463796, -0.9319099650845972, -0.8683625030385337, -0.7979581469525266, -0.7219429284031105, -0.6416783979058955, -0.5586009133592171, -0.4741793270417923, -0.3898722040741198, -0.3070857132008217, -0.22713330949718688, -0.15119827872587263, -0.08030013586675859, -0.015265767799349891, 0.04329391514540214, 0.0950011988359453, 0.13972219689743537, 0.177570607271984, 0.20890448665434544, 0.23431611827069945, 0.2546152292469424, 0.27080598818378054, 0.2840583770874642, 0.2956746803360727, 0.3070519631062842, 0.31964151932898494, 0.3349063520220988, 0.35427780462692854, 0.37911248928868374, 0.41065065612560414, 0.44997711641063726, 0.4979857729662731, 0.5553487243852754, 0.6224907980583361, 0.6995702331642846, 0.7864660820716433, 0.8827727308035024, 0.9878017605079134, 1.1005911867121976, 1.2199219261509084, 1.3443411568283008, 1.47219206033072, 1.6016492706886847, 1.7307592054611203, 1.8574843259425624, 1.979750267758306, 2.0954947033248947, 2.2027167457884365, 2.29952568149751, 2.384187825480613, 2.4551703316987075, 2.5111808562079565, 2.551202065250483, 2.57452009946078, 2.5807462469712608, 2.5698312387997504, 2.542071755605271, 2.498108921426532, 2.4389187528139953, 2.3657947261123624, 2.2803228167796554, 2.1843495478468, 2.0799437554187916, 1.9693529332853037, 1.8549551524371601, 1.7392076612644354, 1.6245933557098962, 1.5135663635830037, 1.4084980122179218, 1.3116244430308448, 1.2249971003933224, 1.150437256435114, 1.0894956394932427, 1.0434181141956858], [1.0206839974995527, 1.0022657713672298, 1.0003645577997182, 1.0149442188713114, 1.0456022158483447, 1.091579188536824, 1.1517765814483494, 1.2247818935422874, 1.3089009480720482, 1.4021964135571412, 1.5025316601323597, 1.6076189110419181, 1.7150705498518461, 1.8224523724291255, 1.9273375305809757, 2.0273599024414057, 2.120265643468071, 2.2039617207542825, 2.2765603110152175, 2.3364180471153198, 2.3821692267506287, 2.4127522466791937, 2.4274286929871978, 2.4257946981513445, 2.407784364655941, 2.373665247986595, 2.324026084200897, 2.259757134245989, 2.1820236941728948, 2.0922334830633984, 1.9919987648758288, 1.8830941830301025, 1.7674113844353372, 1.6469115804792704, 1.5235772345876468, 1.3993640783793113, 1.2761546409830133, 1.1557144292810444, 1.0396518219666322, 0.9293826393057628, 0.8261002259842776, 0.7307517395822154, 0.6440211757333376, 0.5663194869898821, 0.49778197021688264, 0.43827291157735, 0.387397293510275, 0.34451918918169067, 0.30878630118703293, 0.27915994701873864, 0.2544496578355109, 0.23335144276331468, 0.21448868115835337, 0.19645454218529687, 0.17785479625193404, 0.1573498771242065, 0.13369507702080324, 0.10577780901747748, 0.07265095032333439, 0.03356138438639433, -0.012027013326654717, -0.06441655488676344, -0.123665532122243, -0.18958489571778936, -0.26174191526552515, -0.3394707317397444, -0.4218895334444704, -0.507923912821157, -0.5963357990164952, -0.685757213931438, -0.7747279713530448, -0.8617363329840452, -0.9452615544447293, -1.0238172007135509, -1.0959940854014465, -1.1605016924087839, -1.216206971847099, -1.2621694638407586, -1.2976717924617427, -1.322244685421119, -1.335685810445914, -1.338071873157299, -1.3297635899102231, -1.3114033282538125, -1.2839053929512008, -1.2484391222209186, -1.2064051423477515, -1.159405304448304, -1.109206990540547, -1.057702623029396, -1.006865338553619, -0.9587018906084029, -0.915203922802533, -0.8782988040109239, -0.8498012367167396, -0.8313668399035977, -0.8244488681019243, -0.8302591594986097, -0.8497343099901992, -0.8835079489817396, -0.9318898495165611, -0.9948524434308476, -1.0720251355943593, -1.1626966242305228, -1.2658252413776694, -1.3800571334834488, -1.5037519116795686, -1.635015219145264, -1.7717374936210386, -1.9116380507575315, -2.052313482344529, -2.191289255826144, -2.326073320547217, -2.4542104739202246, -2.573336218474585, -2.6812288491412475, -2.77585854897218, -2.8554323398891817, -2.9184338313656637, -2.963656831850168, -2.990232032294951, -2.997646134853533, -2.985752978685507, -2.954776404509171, -2.905304795462247, -2.838277429204827, -2.7549629702286746, -2.6569306173079603, -2.546014594422146, -2.4242728300957954, -2.2939408061393176, -2.157381668952598, -2.0170337821702384, -1.8753569564361503, -1.7347786191529524, -1.5976411835498845, -1.4661518424937825, -1.3423359490188809, -1.2279950541836868, -1.1246705558711825, -1.0336137724516856, -0.9557630962981988, -0.8917287079219806, -0.841785146289148, -0.805871839258378, -0.7836015047646897, -0.7742761431167496, -0.776910158242059, -0.7902599753718332, -0.8128593686613245, -0.8430595783344016, -0.879073186361229, -0.9190206350782217, -0.9609782165441786, -1.0030263331016784, -1.043296832155242, -1.080018250421809, -1.1115578639515122, -1.136459528441178, -1.153476407480067, -1.1615978214735796, -1.1600696036408282, -1.1484075177763657, -1.1264034711479942, -1.0941244404639154, -1.0519042146383835, -1.0003282404484133, -0.9402120315326157, -0.8725737631733276, -0.7986018208785823, -0.7196181963133773, -0.6370387265001741, -0.552331248883302, -0.46697279394557323, -0.38240695738863006, -0.3000025849757876, -0.2210148652581596, -0.14654985956047595, -0.07753340649380182, -0.014685222250287963, 0.041501119017719766, 0.0907717948373597, 0.13311957210817518, 0.16878368807331612, 0.19824277174459562, 0.22220098504766028, 0.24156774056072877, 0.2574315213317158, 0.27102848358698517, 0.28370666123534355, 0.2968867084001422, 0.3120202097774054, 0.33054665601157646, 0.3538502207519465, 0.38321748655218074, 0.41979724798025636, 0.4645634726304865, 0.5182824253138553, 0.5814848593869052, 0.6544440544558849, 0.7371603346462988, 0.8293525398587231, 0.930456747965631, 1.0396323630929851, 1.1557754985443978, 1.2775393972380287, 1.4033614523978681, 1.5314962212038958, 1.6600536684494878, 1.787041739919602, 1.9104122496826899, 2.0281089747391516, 2.1381167868367275, 2.2385106164251174, 2.3275030386445636, 2.403489296153384, 2.465088627982014, 2.511180856207956, 2.5409372911265393, 2.553845148140744, 2.5497248226127858, 2.528739538700244, 2.4913970706079294, 2.4385434252711597, 2.371348569583257, 2.2912844781311916, 2.2000959642715525, 2.0997649336667363, 1.9924688607627214, 1.8805344311403092, 1.766387412685143, 1.652499913118039, 1.5413362482467856, 1.4352986826631335, 1.3366743115546311, 1.24758432861602, 1.1699368712650142, 1.1053845517684837, 1.0552876734479624, 1.0206839974995523], [1.0062353373301178, 0.9998487602927527, 1.0100058989589125, 1.0364378335285624, 1.0785139921938558, 1.1352566604591785, 1.2053633091138967, 1.2872362088251115, 1.3790186272319451, 1.4786367494745625, 1.5838463290335407, 1.692282965827858, 1.8015148253687086, 1.909096558379791, 2.012623155953948, 2.1097824815650665, 2.198405257886126, 2.2765113524278853, 2.342351299835696, 2.394442117913352, 2.431596616111531, 2.4529455558067044, 2.45795219722788, 2.4464189540263126, 2.418486068637492, 2.3746224150262365, 2.3156087253830373, 2.2425137191964426, 2.15666378241587, 2.0596069970148787, 1.953072453461154, 1.8389258872029461, 1.7191227626900325, 1.5956599827119229, 1.4705274257103844, 1.3456605086917937, 1.2228949386550638, 1.1039247520267257, 0.9902646511311923, 0.8832175315649283, 0.7838479574408315, 0.6929621863114114, 0.6110951761011629, 0.5385048268636083, 0.47517352515205713, 0.42081687290857067, 0.37489930069892424, 0.3366560914138625, 0.30512117956239737, 0.2791599470187386, 0.2575061121421295, 0.23880170864445696, 0.2216390759183213, 0.20460373558940484, 0.18631701095400702, 0.16547725711188718, 0.14089860967654425, 0.11154622788317665, 0.0765671019620019, 0.03531561238884828, -0.012626832941668841, -0.06743860197946222, -0.12905143177794182, -0.19715098359293926, -0.27118434954946713, -0.3503743187102861, -0.4337400333278672, -0.520123498348388, -0.6082212531270673, -0.6966203777318298, -0.7838378906410683, -0.868362503038533, -0.9486976296301742, -1.0234045186496827, -1.0911443554734572, -1.1507182152949473, -1.201103790139745, -1.2414878929386386, -1.271293844522649, -1.2902029757196303, -1.2981696230879878, -1.2954291595829355, -1.2824987765597198, -1.2601709166045085, -1.2294994431668882, -1.1917788181734394, -1.1485167380773484, -1.1014008476304684, -1.0522603047887058, -1.0030231056740786, -0.9556701919676485, -0.9121874515895176, -0.8745167847431266, -0.8445074397425931, -0.8238688255997839, -0.8141259809561111, -0.8165788221805335, -0.8322662086273266, -0.8619357521617033, -0.906020163774886, -0.9646207756648439, -1.037498706302256, -1.124073952894895, -1.2234325047799204, -1.334341377286685, -1.4552712732812116, -1.5844263936558096, -1.7197807430414354, -1.8591201173135439, -2.0000888189824604, -2.1402400287873733, -2.27708866967804, -2.4081655351718285, -2.531071419435922, -2.6435299822601857, -2.7434381085059334, -2.828912578037564, -2.898331947231416, -2.9503726548680413, -2.9840385008559553, -2.998682802524622, -2.9940227063721316, -2.97014531895563, -2.9275055145551474, -2.8669154746102685, -2.78952620992578, -2.6968015065032422, -2.5904849149676994, -2.472560567574464, -2.34520875172392, -2.2107572912751037, -2.0716298837799734, -1.9302926107352258, -1.7891998774276676, -1.6507410480170572, -1.5171890199879683, -1.3906519305905185, -1.2730291076948026, -1.1659722706232085, -1.0708528556682086, -0.988736189405052, -0.9203630643275357, -0.8661390899408236, -0.8261320027148864, -0.8000769249097728, -0.787389369984578, -0.7871856058141227, -0.7983098108267107, -0.8193672967426152, -0.8487629287645717, -0.884743753308495, -0.9254447475716661, -0.9689365366992168, -1.0132738846302558, -1.0565437547661776, -1.096911756549784, -1.1326658432772116, -1.1622562036613848, -1.1843303928103373, -1.197762874719576, -1.201678294874381, -1.1954679643924457, -1.1787992121874633, -1.1516174444817908, -1.1141409370374455, -1.0668485700351373, -1.0104608939827429, -0.945915082911045, -0.8743344842220702, -0.796993609077539, -0.7152795198078735, -0.6306506586966446, -0.5445942234873051, -0.45858322758173614, -0.3740343863821238, -0.29226794553010604, -0.21447051261559044, -0.14166187267325434, -0.07466666154859786, -0.014091642716365564, 0.03969081435023597, 0.08655261887675662, 0.12661294497851178, 0.1602342382621173, 0.18801134433994846, 0.21075404080556256, 0.22946342715112525, 0.24530278853319595, 0.25956369510438587, 0.27362822510976453, 0.28892830386771556, 0.3069032294500248, 0.32895650731312337, 0.356413138963497, 0.39047850333576495, 0.43219993402700846, 0.4824320317034622, 0.5418066604261849, 0.610708461555408, 0.6892565821331199, 0.7772931596028702, 0.8743789352627067, 0.9797961891878023, 1.0925590039937831, 1.2114306783822824, 1.3349479285946286, 1.4614513412953907, 1.589121379417227, 1.7160190972188165, 1.8401305959271854, 1.9594141500435682, 2.0718488592953803, 2.1754836342778434, 2.268485306312403, 2.34918466449256, 2.416119265084317, 2.468071929452908, 2.5041039448377056, 2.523582105254324, 2.526198874608386, 2.5119851172538734, 2.481315018753411, 2.43490300716785, 2.373792678230998, 2.299337921520989, 2.2131766344644705, 2.11719759203596, 2.0135012078809384, 1.9043550731518433, 1.7921452888752105, 1.679324712951069, 1.5683593212985736, 1.4616739322377543, 1.3615985626748364, 1.2703166735134264, 1.189816520172532, 1.1218467531262206, 1.0678773146840963, 1.0290665541803306, 1.0062353373301176], [1.000194375890509, 1.0058876342876115, 1.0279996542624508, 1.066031021443582, 1.1191284860620347, 1.1861042794744132, 1.2654629550181868, 1.3554351168771017, 1.4540172381490624, 1.5590166262293488, 1.6681004734113387, 1.7788478361658062, 1.8888033201557504, 1.9955312112555452, 2.096668786522677, 2.189977563321836, 2.2733912989792286, 2.3450596360714493, 2.4033863976512806, 2.4470616696589302, 2.4750869611591706, 2.486792903083464, 2.4818491286395266, 2.460266168978657, 2.4223893913958725, 2.36888519952087, 2.3007199009267065, 2.2191318227882655, 2.1255974163895694, 2.021792232513286, 1.9095477686292623, 1.790805282473059, 1.6675677328419318, 1.541851045689996, 1.4156359110536472, 1.290821293900167, 1.1691807903263243, 1.0523228810229255, 0.9416560286377303, 0.8383594373210838, 0.7433601446018853, 0.6573169515776333, 0.5806115213638263, 0.5133467922748044, 0.4553526659164069, 0.40619874593738714, 0.36521372523293727, 0.3315108523700492, 0.30401875607942663, 0.28151677361519156, 0.2626738179251104, 0.24608973264227466, 0.23033802501629763, 0.21400883647858346, 0.19575100929553718, 0.1743121356850277, 0.1485755321011329, 0.11759316466266574, 0.08061365976807428, 0.037104664036554734, -0.01323103347680519, -0.07044604011405627, -0.13434580832898477, -0.20449306230196465, -0.2802190879248687, -0.36064159197796436, -0.4446886641364675, -0.5311282150992359, -0.6186021197046233, -0.7056641690682827, -0.7908208337325568, -0.8725737631733269, -0.949462897746348, -1.020109048562393, -1.0832548094296353, -1.1378027027283153, -1.1828495269907457, -1.217715966443274, -1.241970639549704, -1.2554479017877487, -1.2582588740586382, -1.250795338385548, -1.2337263226487658, -1.2079873815299162, -1.1747627669469534, -1.1354608633823091, -1.0916834370550372, -1.0451894084849673, -0.9978540015778307, -0.9516242452759802, -0.9084719029279558, -0.8703449772764824, -0.8391189834440171, -0.8165491973025543, -0.8042250716751578, -0.8035279681987937, -0.8155932793876849, -0.8412779151931703, -0.8811340035521613, -0.9353895080575553, -1.0039363015167249, -1.086326055787838, -1.1817741202526955, -1.2891713682004746, -1.4071037969956466, -1.5338794789374197, -1.667562279840754, -1.806011596016482, -1.9469272116124177, -2.087898250883093, -2.226455097048172, -2.3601230735480643, -2.4864766366164255, -2.603192811362469, -2.7081026174501543, -2.799239274686288, -2.8748820523489393, -2.9335947271476654, -2.974257740876397, -2.9960932970508116, -2.9986828025246224, -2.98197624120911, -2.9462932581790597, -2.8923159289903637, -2.8210733861825714, -2.7339186679010035, -2.6324983376583497, -2.518715594993891, -2.3946877500366637, -2.26269906702455, -2.125150089482425, -1.9845046404276439, -1.843235742720692, -1.7037717262941199, -1.56844377999426, -1.439436166429243, -1.3187402495484002, -1.2081133884154054, -1.1090436291877976, -1.0227209837014395, -0.9500159208416816, -0.8914655200762428, -0.8472675494932278, -0.8172825380389828, -0.8010437181227591, -0.7977745250984422, -0.8064131589932484, -0.8256435456550417, -0.8539318833308512, -0.8895678302368832, -0.9307092820828374, -0.9754296083218192, -1.0217661640038092, -1.067768871702676, -1.1115476755180156, -1.1513177063340965, -1.1854410633243786, -1.2124642093879114, -1.231150095396134, -1.240504266813431, -1.2397943629026151, -1.2285625893677157, -1.2066309256114227, -1.174099013251035, -1.1313348584836458, -1.078958662654835, -1.01782026841539, -0.9489708688245636, -0.8736297696879536, -0.7931471177489579, -0.7089636060531094, -0.6225682404395585, -0.5354552959071203, -0.44908160747804104, -0.3648253267939476, -0.28394723341345185, -0.20755561975418893, -0.136575672645113, -0.07172415499060003, -0.013490051149037485, 0.037878317139609874, 0.08237936709196166, 0.12025736451824447, 0.1519945900524605, 0.17829676694602095, 0.20007213187249573, 0.21840469698684142, 0.23452240435601068, 0.24976100893810493, 0.2655246400895024, 0.28324408121256783, 0.3043338703158729, 0.330149359304279, 0.36194487581377677, 0.4008341081517996, 0.4477537819296255, 0.5034316175341915, 0.5683594526293735, 0.6427722859926075, 0.7266338513530435, 0.8196291661745553, 0.9211643246038003, 1.0303736204709246, 1.146133899878708, 1.2670858582201674, 1.3916618180677756, 1.5181193567748201, 1.6445800000565465, 1.7690720641446345, 1.8895766177390603, 2.004075448774531, 2.110599862211123, 2.207279105210198, 2.2923872160101446, 2.3643871226757773, 2.4219708770211303, 2.464094996030986, 2.4900099959697357, 2.4992833403596273, 2.491815178847872, 2.467846425879272, 2.4279589118578406, 2.3730675306255904, 2.3044045009260534, 2.2234960512949877, 2.132132022813823, 2.032329057813933, 1.9262882006443338, 1.8163478751012891, 1.7049333186301139, 1.5945036430710098, 1.4874977532868838, 1.386280386923848, 1.293089539982898, 1.2099865137393095, 1.1388097595000437, 1.0811336101374216, 1.0382328733799033, 1.0110541242245428, 1.000194375890509], [1.0026122224480716, 1.0203313017451878, 1.054193588398198, 1.103473410855538, 1.1671020804564889, 1.2436918517168492, 1.3315670489614697, 1.4288016240757804, 1.5332622586377826, 1.642655993691846, 1.7545812650788817, 1.8665811440816527, 1.9761975340485787, 2.0810250547809326, 2.1787633582214685, 2.267266661031364, 2.3445893509081617, 2.409026622186899, 2.459149219915756, 2.493831517133667, 2.5122723138948384, 2.5140079246354117, 2.4989173083689096, 2.4672191893039437, 2.419461309054273, 2.356502140909792, 2.2794855770240736, 2.1898092664454984, 2.0890874316082666, 1.97910911957768, 1.8617929489089762, 1.7391394909312778, 1.6131824737724665, 1.4859400173695168, 1.3593670976701249, 1.2353103985765954, 1.1154666419975845, 1.0013453914484491, 0.8942372054281934, 0.7951878763500514, 0.7049793326850002, 0.6241176101963817, 0.5528281170344165, 0.4910582315802319, 0.4384870859481066, 0.3945422066327534, 0.3584225114635292, 0.3291270031008087, 0.30548835773963895, 0.28621048698861534, 0.2699090540551163, 0.25515385477587776, 0.24051193140659421, 0.2245902734434535, 0.20607697538162234, 0.18377976577307117, 0.1566608940570102, 0.12386745953452015, 0.08475638803142387, 0.038913403143018985, -0.013834503122132646, -0.07341342500304564, -0.13950386895401737, -0.2115490145366587, -0.28876969241680817, -0.3701856857649405, -0.45464279549931846, -0.5408449581902972, -0.6273905719205214, -0.7128120733737277, -0.7956177217691388, -0.8743344842220695, -0.9475508842786995, -1.0139586716198372, -1.0723921963995715, -1.1218644257895376, -1.16159862172649, -1.1910548056097343, -1.2099502651258813, -1.2182735072777884, -1.2162912263544736, -1.204548031889501, -1.1838588652072353, -1.1552942193500864, -1.120158461340845, -1.079961733229226, -1.0363860747248286, -0.9912465612229381, -0.9464483828522184, -0.9039408994523184, -0.8656697903172864, -0.8335284739359208, -0.8093100003218834, -0.7946606160730993, -0.7910361699899631, -0.7996624656152277, -0.8215005778613691, -0.8572180360807503, -0.9071666382675023, -0.9713675038873358, -1.0495037999330183, -1.1409213904163178, -1.24463746814229, -1.359357033960472, -1.4834968975084457, -1.615216689461603, -1.7524562030178583, -1.8929782260343282, -2.0344158887667274, -2.174323438931328, -2.310229268636674, -2.4396899588059795, -2.5603440775266093, -2.6699644700888645, -2.766507810331334, -2.8481602445661096, -2.913378049352206, -2.960922340563248, -2.9898870107549746, -2.99971923140407, -2.990232032294952, -2.9616086579108343, -2.9143985955831457, -2.8495053676321658, -2.768166374991035, -2.671925268098727, -2.5625974975999415, -2.4422298583095006, -2.313054981082967, -2.1774418452663005, -2.0378434764261506, -1.8967430578789932, -1.7565997186237219, -1.6197952638507755, -1.4885830872119727, -1.3650404471983835, -1.2510252047294501, -1.148138007540491, -1.0576907719445017, -0.980682157387635, -0.9177805577547415, -0.8693149498449748, -0.8352737483508494, -0.8153116227370241, -0.808764039389276, -0.8146691069946828, -0.8317961288536643, -0.8586801069617478, -0.8936613030933506, -0.9349288451473751, -0.9805672754843595, -1.0286048740713347, -1.0770625544393229, -1.1240021255115444, -1.167572737298073, -1.2060543825540315, -1.2378974083206522, -1.2617570986832647, -1.2765225203285357, -1.2813389722438167, -1.2756235463750458, -1.2590734830638592, -1.2316671891586828, -1.1936579732109132, -1.1455607364467435, -1.0881320356340347, -1.0223441001084994, -0.9493535359415839, -0.8704655817748238, -0.7870948899500356, -0.7007238905374336, -0.612859852644707, -0.5249917856054879, -0.4385483216400975, -0.35485769143536444, -0.2751108456154971, -0.20032868979658722, -0.1313342910298217, -0.06873078175678839, -0.012885537285186602, 0.036078961932407706, 0.07828734708149213, 0.11410660181400009, 0.1441344545966827, 0.1691812292834622, 0.1902456320316525, 0.20848511192919963, 0.2251815757284784, 0.24170336024887526, 0.25946446617074265, 0.27988213153050145, 0.3043338703158728, 0.33411511991742643, 0.37039863030589276, 0.4141966878975766, 0.466327199096655, 0.5273845641241258, 0.5977161532861068, 0.6774050582347191, 0.7662596335046477, 0.8638101725884965, 0.9693128823175476, 1.081761133859794, 1.1999037828856567, 1.3222701700523671, 1.447201240489198, 1.5728860617826312, 1.6974028780959332, 1.8187637171200126, 1.9349614696361208, 2.0440182910788467, 2.144034132466684, 2.2332341955620896, 2.3100141245465617, 2.3729817935187953, 2.420994624678954, 2.453191474372579, 2.469018250789055, 2.4682465749887745, 2.450984962484135, 2.4176821817909957, 2.369122634821783, 2.306413797093571, 2.230965948734835, 2.1444646154462035, 2.048836317266918, 1.9462083878084397, 1.8388637734624804, 1.7291918473302783, 1.6196363731371592, 1.5126418276781226, 1.4105993345386252, 1.315793475814391, 1.2303512319199787, 1.1561942526836788, 1.0949955868746675, 1.0481418939112102, 1.016702033243601, 1.0014027768887426, 1.0026122224480716], [1.01346842092684, 1.0430575627029564, 1.0883660888304754, 1.148448222207131, 1.222028897060342, 1.3075321602666419, 1.4031163203965415, 1.5067150165715233, 1.6160832399659906, 1.7288472249660751, 1.8425570374056581, 1.9547406260906544, 2.0629580724513277, 2.1648547723533222, 2.2582123138255343, 2.340995873953312, 2.4113970459361194, 2.4678711211263047, 2.5091679879197986, 2.534355966264329, 2.542838069407827, 2.5343603690652796, 2.5090123318920794, 2.467219189303944, 2.409726594514276, 2.33757800547225, 2.252085405663997, 2.1547941322634094, 2.0474427190641675, 1.931918776657825, 1.8102120216844315, 1.6843656285530832, 1.5564271093829745, 1.4283999303501052, 1.3021970451829699, 1.1795974700144838, 1.0622069396696352, 0.9514235759326735, 0.8484093662041964, 0.754068099593, 0.6690302407265093, 0.593645043618615, 0.5279800232856944, 0.4718277160890557, 0.42471947568545015, 0.385945874591831, 0.3545831161322487, 0.32952471204966294, 0.30951755104798645, 0.29320137619994135, 0.2791506071605054, 0.265917388470454, 0.252074719237404, 0.2362585227391374, 0.21720754686662117, 0.19380004694132127, 0.16508628972336142, 0.13031602912497314, 0.08896023739633682, 0.04072652695693658, -0.014432136251378609, -0.0763156512275125, -0.14448197412610275, -0.21825914374826114, -0.29676382104209115, -0.37892585271902496, -0.46351821096079465, -0.5491915195781452, -0.6345122554921949, -0.7180036161432773, -0.7981879709074078, -0.8736297696879529, -0.9429777657263613, -1.0050054227940266, -1.0586484190048893, -1.1030382295136691, -1.1375308666216575, -1.1617299759229847, -1.1755036281081903, -1.1789943043889088, -1.1726217452656487, -1.1570785132348962, -1.1333183054903655, -1.1025372380609877, -1.0661485034827214, -1.0257509754689276, -0.9830924917943782, -0.940028686741634, -0.8984783634075951, -0.8603764908857214, -0.8276259793765035, -0.8020494258457522, -0.7853420328626568, -0.7790268833561255, -0.784413704620503, -0.80256217710643, -0.8342507391834161, -0.8799517106543706, -0.9398134084381323, -1.0136497611392792, -1.1009377492575947, -1.2008228089520676, -1.3121321441945435, -1.4333956995682073, -1.562874358626472, -1.698594755247219, -1.8383899221821067, -1.9799448560521746, -2.1208459549786705, -2.2586331869284337, -2.3908537761529973, -2.515116153598079, -2.6291429059268827, -2.730821477167764, -2.8182514265432967, -2.889787124603224, -2.94407487549308, -2.9800835835027817, -2.9971282338082763, -2.994885626870348, -2.973401989175771, -2.9330922754484448, -2.8747311744459494, -2.799436027201644, -2.708642058291035, -2.6040705027336113, -2.487690379065402, -2.361674808857069, -2.228352910877972, -2.0901584011245795, -1.9495761055594274, -1.8090876388349524, -1.671117518411424, -1.5379809689696884, -1.4118346272685085, -1.294631283744529, -1.1880796960542443, -1.0936103839314306, -1.012348167303032, -0.9450920442201958, -0.8923028259026156, -0.8540987574811348, -0.83025915949861, -0.820235931644314, -0.8231725712979236, -0.837930179865572, -0.8631197639844265, -0.8971399904889601, -0.9382194271611557, -0.9844621987838108, -1.0338959123278846, -1.0845206580098896, -1.1343578755207713, -1.1814978872838005, -1.2241449427320619, -1.2606586881601398, -1.2895910738505965, -1.3097178313987186, -1.3200637963613577, -1.3199215109248772, -1.308862714186606, -1.28674250951387, -1.2536961847105956, -1.2101288467096347, -1.1566982135618873, -1.0942910780863335, -1.0239941153988907, -0.9470598467251373, -0.8648686909442367, -0.7788881302666156, -0.6906300849826226, -0.6016076326659296, -0.513292218614352, -0.42707248643246054, -0.34421581101191434, -0.2658335419755236, -0.19285086584044972, -0.12598207228759803, -0.06571186713923782, -0.012283215585646743, 0.03430797208789991, 0.0743111791862968, 0.10821269510150841, 0.13672033219749163, 0.16074185292572524, 0.18135767791822832, 0.19978859615645095, 0.2173593302875612, 0.23545892039073538, 0.2554989751670978, 0.27887089843712637, 0.3069032294500245, 0.34082023702325137, 0.38170287985147416, 0.4304531891018102, 0.4877630460142966, 0.554088218706282, 0.6296283914247703, 0.7143137693570661, 0.8077986765400592, 0.9094623875382983, 1.0184172498182198, 1.1335239677380262, 1.2534137354732409, 1.3765167296295964, 1.5010963072133363, 1.6252881052122417, 1.747143108084552, 1.8646736422750474, 1.9759011752344384, 2.078904742436278, 2.17186880100652, 2.253129313524328, 2.321216900299169, 2.374895962217149, 2.413198767594362, 2.4354536132048183, 2.441306308958764, 2.4307343942211004, 2.404053667623496, 2.361916797193611, 2.305303969172683, 2.235505727318631, 2.1540983450402043, 2.062912255684049, 1.9639942371844192, 1.8595642018577738, 1.7519675765493414, 1.6436243692723052, 1.536976103152525, 1.434431854773525, 1.3383146604733394, 1.25080955007306, 1.1739144329616986, 1.1093949972163402, 1.0587446900229527, 1.023150729295782, 1.003466954925559, 1.0001941669386758, 1.0134684209268405], [1.0326711229751988, 1.0738741427094647, 1.1302280407423932, 1.2005749482429935, 1.283444230150458, 1.377085087225391, 1.4795054301106476, 1.5885161118076052, 1.7017794791547294, 1.816861103233481, 1.9312834755482935, 2.042580413082396, 2.14835090194952, 2.2463111266286733, 2.334343479219401, 2.4105414195835113, 2.47324916073234, 2.5210952818012013, 2.5530195202523442, 2.568292161873748, 2.5665256275753348, 2.547678045483606, 2.5120487907419795, 2.460266168978657, 2.3932676078658983, 2.3122728999573128, 2.2187512046949016, 2.1143826641217087, 2.001015611869843, 1.8806204554086965, 1.7552413849405828, 1.626947106999649, 1.4977818157382858, 1.369717599805131, 1.2446094381059682, 1.1241538647998548, 1.009852284524461, 0.9029797956247413, 0.8045602352229083, 0.715347998968205, 0.6358170143115299, 0.5661570635465748, 0.5062774662346643, 0.4558179446642387, 0.41416631534117415, 0.38048247867357066, 0.35372802226094435, 0.3327006144189391, 0.31607224720585, 0.3024302951630285, 0.29032028952015604, 0.27828926936039305, 0.26492856209145715, 0.24891486569665056, 0.2290485540791296, 0.20428820307686563, 0.17378043644031432, 0.13688431561727865, 0.09318964139492253, 0.042528695630393895, -0.015018876617837584, -0.07912816464032552, -0.1492380068228668, -0.22456667920727363, -0.3041338398551634, -0.38678814707281567, -0.4712398204899207, -0.5560972835765767, -0.6399069177540291, -0.7211948745759014, -0.7985098356766032, -0.870465581774823, -0.9357822327416458, -0.9933250506214186, -1.0421397558214769, -1.0814833920401539, -1.1108498857752178, -1.1299895787118108, -1.1389221626330819, -1.1379426129515922, -1.1276198943628393, -1.1087883960297533, -1.0825322395032253, -1.0501627855971314, -1.0131898420558456, -0.9732872376427141, -0.9322535760908989, -0.8919691114355197, -0.8543497913151441, -0.8212995941857825, -0.7946623379611866, -0.7761741599972509, -0.7674178609166711, -0.769780267604763, -0.7844137046205027, -0.8122025698010505, -0.8537358912195273, -0.9092866017400336, -0.9787981076155765, -1.0618785527840962, -1.1578029950050401, -1.2655235182885742, -1.3836871129083648, -1.510660964409764, -1.6445646111099563, -1.7833082601287162, -1.9246363991839215, -2.066175709027221, -2.2054861727780417, -2.340114196255759, -2.46764649978055, -2.5857635181856784, -2.6922910525971524, -2.785248954781169, -2.8628956916786383, -2.9237677325561386, -2.9667128217319365, -2.990916343180437, -2.9959201460125806, -2.9816333779312325, -2.9483350629475495, -2.896668355321382, -2.8276265991000042, -2.7425315169754767, -2.643004038736914, -2.5309284538252763, -2.4084107301733906, -2.2777319788065404, -2.1412981572637357, -2.001587192033035, -1.86109475878123, -1.7222799878051633, -1.5875123601787309, -1.4590210276069433, -1.3388477268640635, -1.2288043694510093, -1.1304362710093425, -1.044991845957988, -0.9733994342164176, -0.916251752661228, -0.8737982784255781, -0.8459456788575271, -0.8322662086273268, -0.8320138028792217, -0.8441474111488197, -0.8673609445088665, -0.9001190522582222, -0.9406978082187423, -0.9872292736418713, -1.0377488165603284, -1.0902440082142335, -1.1427038873031823, -1.1931673829053773, -1.239769716857721, -1.280785665362795, -1.3146686460182635, -1.340084708112178, -1.3559406380330215, -1.3614055445967104, -1.355925457120573, -1.3392306479367146, -1.311335576233603, -1.2725315369965577, -1.2233722827042448, -1.1646530617329172, -1.0973836817255864, -1.022756354410566, -0.9421092068239011, -0.8568864494252415, -0.7685962715992207, -0.6787675875511691, -0.5889067793759348, -0.5004555785645722, -0.4147511926138616, -0.3329897206474856, -0.25619381268035335, -0.18518541366019928, -0.1205642986109079, -0.06269295252168727, -0.011688181964549692, 0.03258033098155308, 0.07048450358600551, 0.10262550949858032, 0.12981494968531315, 0.1530500388156579, 0.1734834656458678, 0.19238872612725103, 0.2111218477692957, 0.23108052015052633, 0.253661716926864, 0.2802189374220008, 0.31202020977740497, 0.3502079822969382, 0.3957619853841341, 0.449466074408162, 0.5118799657177958, 0.5833166562793537, 0.6638261750702587, 0.7531861549621716, 0.8508995413585667, 0.9561995726276228, 1.0680619819367816, 1.1852241851080612, 1.3062110392290396, 1.4293665865109833, 1.5528910415879082, 1.674882142064041, 1.7933798651689836, 1.9064134208684527, 2.0120493660992222, 2.108439647682042, 2.1938683739394547, 2.26679613739631, 2.3259007627157864, 2.3701134340374783, 2.3986492622459545, 2.411031482859655, 2.4071086260465435, 2.387064168080354, 2.3514183542571243, 2.301022072474936, 2.2370428497002073, 2.1609432356573337, 2.074452024552398, 1.9795289418749757, 1.8783235849553033, 1.7731295489820131, 1.6663347910517796, 1.5603693805114662, 1.45765185196448, 1.3605354161184007, 1.271255292142807, 1.1918784031171883, 1.1242566239651843, 1.0699846902154524, 1.0303637679359834, 1.0063715528524146, 0.9986396131772893, 1.0074385197614217, 1.0326711229751993], [1.0600578650444963, 1.1125203195531947, 1.1794252730780268, 1.2594125732732473, 1.350828478218138, 1.451762183357966, 1.560088091669138, 1.6735128355029087, 1.7896259472424687, 1.9059529912571842, 2.0200099136909273, 2.129357340710968, 2.2316535605649, 2.324704959990393, 2.406512750294092, 2.4753149111362105, 2.529622398417243, 2.5682488037280695, 2.5903328131068144, 2.5953529883907662, 2.58313458093652, 2.5538482803215734, 2.508000995102726, 2.446418954026313, 2.3702235995839622, 2.2808009170083308, 2.179764996540884, 2.068916761327272, 1.9501989043606625, 1.8256481628408172, 1.697346115138783, 1.5673697129454982, 1.4377427585599358, 1.3103895048050653, 1.1870914936536803, 1.0694486609213414, 0.9588456206353418, 0.8564239068271183, 0.7630607959743888, 0.6793551640479996, 0.6056206523646911, 0.5418862307301245, 0.48790405933449815, 0.44316436721653907, 0.4069168894271509, 0.3781982416796558, 0.35586446433070196, 0.33862784063748086, 0.3250969905176998, 0.3138191630473149, 0.3033236005669659, 0.2921648257350251, 0.27896471064177814, 0.262452223927512, 0.24149981674001292, 0.21515549963285277, 0.18266977779249677, 0.14351674833552783, 0.09740881735552555, 0.044304662000922784, -0.015589760132506287, -0.08182717010533548, -0.15373172885556557, -0.2304182563095206, -0.31081739516189427, -0.3937060502583505, -0.4777422957760117, -0.5615038242972707, -0.6435289174221762, -0.7223588491811987, -0.7965805929551324, -0.864868690944236, -0.9260251627896195, -0.9790163763360231, -1.023005877610123, -1.0573822770476946, -1.0817814123584155, -1.096102152099315, -1.1005153644517776, -1.0954657488515, -1.0816664096682556, -1.0600862365171553, -1.0319303403450226, -0.9986139735260745, -0.9617305312999586, -0.9230143867127071, -0.8842994478461136, -0.8474744410588905, -0.8144360142631738, -0.7870408175810806, -0.7670577533939273, -0.7561215928481866, -0.7556891310893712, -0.7669989993724097, -0.7910361699899624, -0.8285020816145654, -0.8797911807663451, -0.9449745228849646, -1.0237909076040155, -1.1156458414206885, -1.2196184314645144, -1.3344761211474458, -1.4586969868694417, -1.5904991293816422, -1.7278765184576272, -1.8686404895214996, -2.010465949800882, -2.150941232923392, -2.287620447622124, -2.418077100703817, -2.5399577383283307, -2.6510343438960686, -2.749254255641727, -2.832786421839756, -2.9000628950525518, -2.9498145771051716, -2.9811003607998083, -2.9933289695474605, -2.986272968337305, -2.960074604609459, -2.9152433311490915, -2.852645060375938, -2.7734833955678004, -2.679273274859761, -2.5718076436756423, -2.453117936204642, -2.325429292627985, -2.1911115624847053, -2.0526272428485606, -1.91247757049951, -1.7731480283235677, -1.6370545367982479, -1.5064915813960573, -1.3835834765962498, -1.2702398882030086, -1.1681166297997665, -1.0785826190545722, -1.0026937284515582, -0.9411740965910746, -0.8944052846277014, -0.8624234721686876, -0.8449246927086173, -0.8412779151931705, -0.8505455903215524, -0.8715111023056026, -0.9027124033381112, -0.9424809629538862, -0.9889850413029632, -1.0402761970570624, -1.0943378695780686, -1.149134832754403, -1.2026623055031809, -1.252993521549061, -1.298324608186808, -1.3370156990465978, -1.3676273074451384, -1.3889511121109135, -1.4000344527259885, -1.400197995137168, -1.389046201154117, -1.3664704211641991, -1.33264461475012, -1.2880138904131357, -1.2332762357335059, -1.1693579793446967, -1.0973836817255866, -1.0186412891615804, -0.9345435008916299, -0.8465863905930943, -0.756306387729296, -0.6652367603391847, -0.5748647477407576, -0.48659046923961546, -0.40168868390545504, -0.3212743981464251, -0.24627321420185064, -0.1773971864499375, -0.11512680681662658, -0.059699579287875636, -0.011105470675585715, 0.030910655238893414, 0.06683969568778718, 0.09739231512364689, 0.1234767297209215, 0.14617086318121694, 0.16668961461351686, 0.18634810809052635, 0.20652190009827948, 0.22860520277552898, 0.2539682354861224, 0.28391484346531803, 0.31964151932898444, 0.36219893116546875, 0.41245700050924866, 0.47107448620351144, 0.5384739181534303, 0.6148225910354538, 0.7000201754982571, 0.7936933370778607, 0.8951975751404423, 1.0036263101217964, 1.1178270617750121, 1.2364243787363336, 1.3578490050722267, 1.4803726069924779, 1.6021472367227196, 1.7212485843447063, 1.8357219654619246, 1.943629915485853, 2.043100212178514, 2.132373128153063, 2.2098467249235543, 2.2741190396637703, 2.3240260842008964, 2.3586746713323032, 2.377469204032709, 2.380131705610954, 2.3667145299244603, 2.3376053664406893, 2.2935243409538644, 2.235513204561268, 2.1649167963636007, 2.083357154529047, 1.9927008311831338, 1.8950201345851887, 1.7925491730638412, 1.6876357054566327, 1.5826899090843816, 1.48013125592599, 1.3823347386327083, 1.2915777090223086, 1.2099885821478147, 1.1394986191166712, 1.0817979324649718, 1.0382967607116098, 1.0100929360571285, 0.9979463240064826, 1.0022608494943792, 1.023074544853993, 1.060057865044497], [1.0953969429041845, 1.1586691290904556, 1.2355415549898157, 1.324463304365809, 1.4236115400330105, 1.530931646639315, 1.6441825392911598, 1.7609860769135177, 1.8788794233582093, 1.9953691313499675, 2.1079856860177038, 2.214337236901627, 2.3121612701107037, 2.3993730251346297, 2.4741095423593467, 2.5347683355625366, 2.580039815890837, 2.6089327467741983, 2.620792179141203, 2.6153094989778842, 2.592524410230313, 2.5528188706003903, 2.4969031911570765, 2.4257946981513445, 2.340789532406065, 2.243428323842284, 2.1354566221643876, 2.018781085991296, 1.8954225288769757, 1.7674669894245574, 1.6370160324594603, 1.5061374981034037, 1.3768178954396326, 1.2509175878798742, 1.130129839663339, 1.0159446891581434, 0.9096184874595582, 0.8121497934258123, 0.7242621524933907, 0.64639411050275, 0.5786966297720709, 0.521037887397567, 0.47301524992163174, 0.43397403873697343, 0.40303253136701545, 0.3791124892886841, 0.3609743670748603, 0.34725624368937913, 0.336515427571375, 0.32727162487697864, 0.3180505264054142, 0.3074266641086608, 0.29406441272020156, 0.276756065255364, 0.2544559915328994, 0.2263099943629113, 0.19167910592959694, 0.15015721389771464, 0.10158206914032052, 0.04603940058939471, -0.01613995686252288, -0.08438983281499447, -0.15792512130237, -0.23576436806484824, -0.316757941060046, -0.3996210336842932, -0.4829706229357441, -0.5653653999592432, -0.6453476107404702, -0.7214856922073042, -0.7924165650094109, -0.8568864494252408, -0.9137891050972011, -0.9622004577970427, -1.0014086656386725, -1.0309387908750047, -1.050571378809989, -1.0603543990488724, -1.0606081724561656, -1.0519230855799198, -1.0351500784566001, -1.0113840770045575, -0.9819407229802565, -0.9483269281240398, -0.912205940269658, -0.8753577537464994, -0.8396358206844642, -0.806921120657201, -0.7790747208667341, -0.7578900058239645, -0.7450457729513817, -0.7420613781905304, -0.7502550737424051, -0.7707066094468497, -0.8042250716751567, -0.8513228113014192, -0.912196168284151, -0.9867135381273094, -1.0744111489560735, -1.174496731457221, -1.2858610720717665, -1.4070972473070877, -1.536527148601709, -1.672234727481007, -1.8121052242342555, -1.9538694941516317, -2.0951524171964624, -2.2335242730516907, -2.3665538863795526, -2.491862298822361, -2.6071757059970255, -2.710376410008356, -2.7995505805867062, -2.873031689861261, -2.929438585306143, -2.9677072901591073, -2.9871157676057445, -2.987301050693062, -2.9682683202709796, -2.9303917038827865, -2.874406764805591, -2.801394847608113, -2.7127596398512996, -2.610196494207477, -2.4956552268261754, -2.371297262060439, -2.2394481269403483, -2.1025464078098315, -1.9630903636924453, -1.8235834442447423, -1.6864799833224615, -1.5541323316946813, -1.4287406545142247, -1.3123065517550392, -1.2065915646458174, -1.113081510529765, -1.0329574455495152, -0.9670738926263616, -0.9159447953654444, -0.8797374711248193, -0.8582746431400365, -0.8510444370392264, -0.8572180360807503, -0.8756745066638143, -0.9050321355588741, -0.9436854670148932, -0.9898470951379498, -1.0415931578995083, -1.0969113964306294, -1.1537505888416628, -1.2100701429243819, -1.263888637260419, -1.3133301352472606, -1.3566671603940266, -1.3923593122541238, -1.4190866182010253, -1.4357768539566738, -1.4416262218526383, -1.4361129462973738, -1.4190035265436778, -1.390351573061417, -1.3504893409551222, -1.3000122572445805, -1.2397569138732005, -1.1707731606652303, -1.0942910780863337, -1.0116837349660284, -0.9244267382240314, -0.8340556576063446, -0.7421224566356174, -0.6501520802676517, -0.559600339702123, -0.47181419573840455, -0.38799547504176646, -0.3091689604383356, -0.2361556792922656, -0.1695520761360762, -0.10971560054582681, -0.0567570727298778, -0.01054001171993931, 0.029313071072240716, 0.06340759221575512, 0.09255738716916755, 0.11775929651329263, 0.1401625269611322, 0.16103360387516177, 0.18171784840827845, 0.20359840491330938, 0.22805391057082977, 0.2564159375591606, 0.2899273475295351, 0.3297026783772745, 0.37669163477544865, 0.4316466778442786, 0.49509560754615206, 0.5673199064496939, 0.6483394685099476, 0.737904175087173, 0.8354926066137262, 0.9403179964748022, 1.0513413483607752, 1.1672914542385247, 1.2866913718163961, 1.4078907524453224, 1.5291032570603194, 1.6484481629182481, 1.7639951509714884, 1.8738111756348783, 1.9760082577421387, 2.0687910092638147, 2.1505026957745317, 2.2196686698792067, 2.2750360652598745, 2.3156087253830373, 2.340676451210208, 2.349837785831191, 2.343015707556543, 2.320465772924243, 2.28277643314434, 2.230861437263588, 2.165944428118257, 2.089536028211504, 2.003403897288216, 1.9095364170211329, 1.8101008165650307, 1.7073966918479984, 1.6038059878842426, 1.501740604198332, 1.4035888463580355, 1.311661980017379, 1.2281421468909834, 1.1550328745784222, 1.0941133547462751, 1.0468975782039192, 1.014599302927367, 0.9981036947967393, 0.9979463240064822, 1.014300026578958, 1.0469699543687245, 1.0953969429041854], [1.1383893719644553, 1.211930131509987, 1.2981021173398788, 1.3951767828998438, 1.5011776379574104, 1.6139236675854867, 1.7310772958966585, 1.8501957728350045, 1.9687847827063516, 2.08435302250538, 2.194466477685247, 2.296801133278758, 2.389192898934018, 2.4696835964425774, 2.536561955966396, 2.588398689988861, 2.624074858987152, 2.642802906371722, 2.644139918335839, 2.6279928525251117, 2.5946156732519405, 2.544598525592111, 2.4788492713482237, 2.3985678918910365, 2.3052144318595986, 2.2004713095086497, 2.086200950462405, 1.9643998086137755, 1.8371499183419682, 1.7065691742143003, 1.5747615567017565, 1.4437685147188242, 1.3155226782881908, 1.1918050083580958, 1.0742063975031453, 0.9640946173222008, 0.8625873688193092, 0.7705320344544632, 0.68849255886035, 0.6167437037604968, 0.5552727359480628, 0.5037884199674791, 0.4617370040609613, 0.42832471356314983, 0.40254610458764883, 0.383217486552181, 0.36901449840394623, 0.3585128233804178, 0.35023095322249986, 0.3426738667376323, 0.3343764705788977, 0.32394566242259826, 0.3100999180144509, 0.2917053727100111, 0.2678074633563053, 0.23765731519415845, 0.20073219785880736, 0.1567495309603379, 0.10567408915079006, 0.04771823472237301, -0.016664811894584564, -0.08679447148316069, -0.1617827061656484, -0.24055978394866329, -0.32190521784319254, -0.4044830539142996, -0.48688056795550133, -0.5676493398850104, -0.6453476107404703, -0.7185827909573249, -0.7860529814001039, -0.8465863905930936, -0.8991775822493479, -0.9430195652846071, -0.9775308420932546, -1.00237665738092, -1.0174838361364598, -1.0230487617273332, -1.019538219548739, -1.0076830137714086, -0.9884644499388046, -0.9630939597994146, -0.9329863221923926, -0.8997271005502753, -0.8650350694151933, -0.830720535423857, -0.7986405691022594, -0.770652249671636, -0.7485650836691269, -0.7340937879727922, -0.7288126279486284, -0.7341124718026061, -0.7511616634598679, -0.7808717297691405, -0.8238688255997827, -0.8804716851619628, -0.9506766929151198, -1.0341505165109977, -1.1302305615239914, -1.2379333177336511, -1.355970474112122, -1.4827724891787548, -1.6165191197183613, -1.755176238562155, -1.896538115475047, -2.0382741980733776, -2.177979315535431, -2.313226139523378, -2.441618676440651, -2.560845534447125, -2.668731708363677, -2.7632876557906383, -2.8427544977637074, -2.905644265667029, -2.9507742308072142, -2.9772944912689634, -2.984708149086164, -2.9728835855384146, -2.9420585292834422, -2.8928358065230277, -2.826170859747072, -2.743351317008912, -2.6459690824016757, -2.5358855958405426, -2.41519107209442, -2.2861586713202047, -2.151194672679118, -2.0127858160666587, -1.8734450423089504, -1.7356568978018985, -1.6018238746563591, -1.4742149318723654, -1.3549173875573495, -1.245793288120645, -1.1484412498109784, -1.0641646336537047, -0.9939467601076512, -0.9384336984116388, -0.8979249818442855, -0.8723724084920771, -0.8613868923105735, -0.8642531360431022, -0.8799517106543708, -0.9071879499027877, -0.9444269077988712, -0.9899334848799841, -1.0418167098987168, -1.0980770695365265, -1.1566557123481525, -1.2154843158615791, -1.272534398426589, -1.3258648801029995, -1.3736667489454601, -1.4143037690873974, -1.4463482729743675, -1.468611209231326, -1.4801657666845538, -1.4803640602256696, -1.4688465413388123, -1.445543980760615, -1.4106720582769736, -1.3647187803900833, -1.3084251258781752, -1.2427594876537271, -1.1688866326201697, -1.0881320356340352, -1.0019425558807333, -0.9118445112111613, -0.8194002661362818, -0.726164480793539, -0.6336411705558712, -0.5432426990592616, -0.4562517720210995, -0.37378741676603044, -0.2967758250040007, -0.2259268068751702, -0.16171645590182354, -0.10437646105215832, -0.05389032778467385, -0.009996589136248344, 0.02780109476655994, 0.06021723031832727, 0.088161631313467, 0.1127110221345312, 0.13507586339862873, 0.15656328584102316, 0.17853712117263548, 0.20237609630654682, 0.229431307717943, 0.2609841144788426, 0.29820558110957945, 0.3421185649640005, 0.39356347829631444, 0.4531686640355417, 0.5213262088798438, 0.5981738804926415, 0.6835837207528409, 0.7771576580577787, 0.8782303228351093, 0.9858790661799343, 1.0989409965297565, 1.216036668184185, 1.335599882840718, 1.4559129055214013, 1.5751462533640637, 1.6914020933874714, 1.8027601866476823, 1.9073252437342167, 2.003274512210452, 2.088904401586564, 2.162674966200648, 2.2232511107076074, 2.2695394557331214, 2.300719900926706, 2.316271046757713, 2.315988781942747, 2.2999975068351453, 2.2687536404579145, 2.22304124577737, 2.1639597997068063, 2.092904326474842, 2.01153830065267, 1.9217599046703622, 1.8256623906425398, 1.7254894436713821, 1.6235865698307985, 1.5223496336088922, 1.424171744142946, 1.3313897352283823, 1.2462314996361656, 1.170765423284981, 1.1068531195884082, 1.0561065898796402, 1.019850833971669, 0.9990928080788001, 0.9944974785610722, 1.0063715528524138, 1.0346552875450998, 1.0789225823283255, 1.1383893719644567], [1.1886714168211636, 1.2718527146304417, 1.366577669461758, 1.4709547408487404, 1.5828705277038384, 1.7000360961449599, 1.8200371925244263, 1.9403871688720264, 2.0585813852641732, 2.172151820738579, 2.2787206220630454, 2.3760513479636725, 2.4620967245977887, 2.5350418146650746, 2.5933416154360853, 2.6357522373487248, 2.6613549713155087, 2.6695727256440245, 2.6601784982521637, 2.6332957421221566, 2.589390676969932, 2.529256793135253, 2.453991980007243, 2.364968886346621, 2.263799279393102, 2.1522933097869608, 2.032414706705982, 1.9062330194091326, 1.7758740854094222, 1.6434699402833002, 1.511109388901053, 1.3807904326134783, 1.254375692379112, 1.1335518854112303, 1.0197943047994207, 0.9143371204836704, 0.8181501692601147, 0.7319227349862194, 0.6560546420233275, 0.5906547996792408, 0.5355471476338503, 0.4902837667397923, 0.4541647408159325, 0.4262641875423878, 0.405461724479715, 0.3904785033357652, 0.3799168351687151, 0.37230234395275047, 0.3661275279177199, 0.35989557869354083, 0.35216330821213493, 0.34158206247616996, 0.32693555889358783, 0.30717366838574817, 0.28144127271699465, 0.24910145865764063, 0.20975246032583617, 0.16323792553799044, 0.1096502570459855, 0.04932696070341159, -0.017159884717620488, -0.08902074177859004, -0.16527184653188037, -0.24476393257263823, -0.3262156772205791, -0.40825097605713484, -0.48943905093114615, -0.5683363209093062, -0.6435289174221763, -0.7136747052894136, -0.7775436809241006, -0.8340556576063438, -0.882314214341142, -0.9216359778288241, -0.9515744241659012, -0.9719375251393129, -0.9827987199211293, -0.9845008627074299, -0.9776529761154602, -0.9631198244523274, -0.9420045056576163, -0.9156244411448098, -0.8854813143642156, -0.8532256673377266, -0.8206170056490554, -0.7894803828103614, -0.7616605314784483, -0.7389746791625847, -0.7231652280068119, -0.7158534907984963, -0.7184956581379724, -0.7323421250293763, -0.7584012300825137, -0.7974083588215858, -0.8498012367167381, -0.9157020905333207, -0.9949071920082377, -1.0868841197334258, -1.190776887818872, -1.3054188980247008, -1.4293534803194532, -1.5608615999727753, -1.6979961319469725, -1.8386219399098809, -1.980460851713785, -2.121140499297994, -2.258245891778243, -2.3893725184825985, -2.5121797357142985, -2.624443178189453, -2.724104953793856, -2.809320428160986, -2.878500482483419, -2.930348232108386, -2.963889322340339, -2.9784950683750924, -2.973897874783204, -2.9501985523627026, -2.9078653420665126, -2.8477246524160837, -2.7709437135573247, -2.6790055431121975, -2.573676801558025, -2.4569692835852077, -2.331095942639853, -2.1984224749872534, -2.0614155940024883, -1.9225892024784648, -1.784449718681951, -1.6494418295411002, -1.5198959313119011, -1.3979784746968327, -1.2856463587692954, -1.1846064180010092, -1.096280921675312, -1.0217798580850963, -0.9618806107803548, -0.9170154548102823, -0.8872671118040447, -0.8723724084920768, -0.8717338886440068, -0.8844390381496668, -0.9092866017400336, -0.9448193020486753, -0.9893621214261057, -1.0410651777747786, -1.097950120778792, -1.157958896762307, -1.2190036808623577, -1.2790167553723988, -1.3359991233940782, -1.3880666869719047, -1.4334928875891442, -1.470746802476512, -1.4985258101693524, -1.5157820800857909, -1.5217423000066637, -1.5159202282033746, -1.498121839235312, -1.4684430195525613, -1.4272599563108204, -1.3752125455584894, -1.3131813196384132, -1.2422585539422217, -1.1637143560904395, -1.0789586626548358, -0.9895001666886906, -0.8969032711870707, -0.8027442074263831, -0.7085674718997514, -0.6158437209712764, -0.5259302188539289, -0.4400348632344259, -0.35918471568047944, -0.28419984337715254, -0.21567313783983055, -0.15395661864001994, -0.09915455987172572, -0.051123598411717056, -0.009479800525472365, 0.02638751832557423, 0.05729560190081107, 0.08424223764018676, 0.10837461727025167, 0.13095390796918685, 0.15331648142451176, 0.17683283677530653, 0.20286531556190612, 0.23272574081372477, 0.2676341174013044, 0.30867950660342064, 0.3567841350703858, 0.4126717182972833, 0.4768408733410499, 0.5495443674478211, 0.6307748017002877, 0.7202571654419528, 0.8174485221817391, 0.9215449053237399, 1.0314953169895136, 1.146022540066144, 1.2636502970445518, 1.3827361236746798, 1.50150917515517, 1.6181120513202876, 1.7306456184417445, 1.8372157216300893, 1.9359806255785312, 2.025197994039871, 2.103270220746298, 2.1687869565155924, 2.2205637383382735, 2.257675714887351, 2.2794855770240736, 2.285664938740058, 2.2762085702571175, 2.2514410568908163, 2.2120156405661477, 2.1589051910553834, 2.093385446410581, 2.017010851941949, 1.93158350975662, 1.8391159217973594, 1.74178836426394, 1.641901866406006, 1.5418278785690196, 1.4439558002471653, 1.3506395965746005, 1.264144759687658, 1.1865968689607238, 1.1199329712492678, 1.0658569397065758, 1.0257998789457956, 1.000886527463216, 0.9919084681290972, 0.9993047975713127, 1.0231507292957807, 1.063154417674174, 1.1186620950415285, 1.1886714168211643], [1.2458176686219353, 1.3379299062833419, 1.4403888771989604, 1.5511560623983327, 1.667999050458584, 1.788540382205801, 1.9103095881941787, 2.0307972050020364, 2.147509511140606, 2.258022708487099, 2.3600352909642264, 2.4514173882790034, 2.5302559477475413, 2.5948947197010277, 2.643968139156213, 2.6764283452037385, 2.6915647462561663, 2.6890157198065796, 2.6687722252465433, 2.631173302923442, 2.576893627217172, 2.506923471228616, 2.4225416210669315, 2.325281944308728, 2.2168944659370147, 2.0993019323556568, 1.9745529468558496, 1.8447728357348114, 1.7121134513535785, 1.5787031357033419, 1.4465980551998796, 1.3177360748598874, 1.1938942688825163, 1.0766510668192493, 0.9673539124781914, 0.8670931695813309, 0.7766828475983083, 0.6966485471654894, 0.6272228414370893, 0.5683481221928744, 0.5196867522325029, 0.48063818319173846, 0.45036252496008694, 0.4278098936572218, 0.411754723579594, 0.40083410815179993, 0.3935891386667731, 0.38850813982250565, 0.3840706594418309, 0.3787910572686434, 0.3712605546101123, 0.36018665234435987, 0.34442889821756056, 0.3230300835016748, 0.29524207141840697, 0.2605456021211228, 0.21866357782849669, 0.16956750287651304, 0.11347693264627678, 0.05085196798275403, -0.017620986791524757, -0.0910498084471844, -0.1683630226947136, -0.2483412449370153, -0.3296528507553677, -0.41089292178646597, -0.4906244259389776, -0.5674205308618022, -0.6399069177540293, -0.7068029598292547, -0.7669606561139303, -0.8194002661362813, -0.8633416730958478, -0.8982306102557545, -0.9237590148976917, -0.9398789229828122, -0.9468094819423744, -0.945036834657996, -0.9353068102690638, -0.9186105423693887, -0.8961633177650203, -0.8693771346487629, -0.8398276133582129, -0.8092160516535145, -0.7793275458901092, -0.7519862062585045, -0.7290085756649854, -0.712156415710818, -0.7030900481522583, -0.7033234354689996, -0.7141821497524943, -0.736765315805634, -0.7719125236007731, -0.8201765892394922, -0.8818029050934234, -0.9567159622441105, -1.044513455526648, -1.1444681976491047, -1.2555378785227362, -1.3763825137835282, -1.505389237255057, -1.640703910476106, -1.7802688528953199, -1.9218658431311662, -2.0631634086264192, -2.2017673114196925, -2.335273054368838, -2.461319177106727, -2.577640085709796, -2.682117165205023, -2.77282695957454, -2.848085269035079, -2.9064861075398696, -2.946934582450565, -2.968672900296498, -2.9712988640519105, -2.954776404509171, -2.9194378768116884, -2.86597804845664, -2.795439902338729, -2.709192572883683, -2.6089019202819363, -2.496494422728914, -2.37411522515319, -2.2440813213111404, -2.108830960983644, -1.97087046254156, -1.832719671210639, -1.6968573335201746, -1.5656676579525974, -1.4413893007625993, -1.3260679550931787, -1.221513632399108, -1.129263610004718, -1.0505518802176637, -0.9862857782045796, -0.937030291701033, -0.9030003698550255, -0.8840613556480043, -0.8797374711248185, -0.8892280918692866, -0.9114313614928742, -0.9449745228849649, -0.9882501848339418, -1.0394576041998753, -1.0966479484400313, -1.1577724137214718, -1.2207320122216836, -1.2834278099468377, -1.3438103941871036, -1.399927377535509, -1.4499678024343845, -1.49230239497375, -1.5255187269581343, -1.5484504782638036, -1.5602001438519286, -1.5601546976375023, -1.5479939045153122, -1.5236911577194454, -1.4875069066894036, -1.4399749260394819, -1.381881854458533, -1.3142405989738806, -1.238258350864559, -1.1553000908759634, -1.066848570035138, -0.9744618356327106, -0.879729427803352, -0.7842283992702865, -0.6894803086122335, -0.5969103059907909, -0.5078093705026484, -0.423300671764954, -0.3443109172440947, -0.27154741405305083, -0.20548142286612378, -0.14633821608526662, -0.09409407665145272, -0.04848029239346199, -0.008994018153108053, 0.025084301245624958, 0.05466742526167066, 0.08083236599334857, 0.10478676986785147, 0.12783153428094576, 0.15132066006018702, 0.17661941423349048, 0.20506192366311257, 0.23790933746343676, 0.2763096842926613, 0.3212605098618755, 0.3735753113370843, 0.4338546904213698, 0.5024630281582819, 0.5795113448597364, 0.6648468515271302, 0.7580495286402903, 0.8584358885167419, 0.9650698931116921, 1.0767808147801028, 1.1921876478069782, 1.3097295079740539, 1.4277013003914336, 1.544293796272975, 1.6576371408360353, 1.7658467201012105, 1.8670702465014501, 1.9595348836707103, 2.0415932206536276, 2.111766925412318, 2.168786956515592, 2.211629289157501, 2.2395452153385227, 2.252085405663997, 2.2491170686804933, 2.2308337093659207, 2.197757167262138, 2.150731802402264, 2.090910889023224, 2.0197354683390683, 1.9389060976563146, 1.850348109234291, 1.756171154161142, 1.6586239501019393, 1.5600452734963772, 1.4628123335869658, 1.3692877351029287, 1.281766276735401, 1.202422842657636, 1.1332626239515453, 1.0760748563300209, 1.0323911811657083, 1.0034496304331848, 0.9901651052930716, 0.9931070658451838, 1.0124849797332973, 1.0481418939112082, 1.09955630142928, 1.1658522782484455, 1.2458176686219362], [1.3093446442175627, 1.4096026635270336, 1.518911264334077, 1.6351022080767998, 1.7558429803980464, 1.8786877394592902, 2.001130737589825, 2.120660971408367, 2.2348167881503014, 2.3412391791835696, 2.4377225254945794, 2.522261623420161, 2.593093910513029, 2.6487359288900834, 2.688013203827341, 2.7100828752753, 2.7144485954430473, 2.700967392330717, 2.6698483924999006, 2.6216434917250044, 2.5572302546895473, 2.477787509881473, 2.384764278795374, 2.2798428352655433, 2.1648968274378433, 2.0419455082466786, 1.913105207583085, 1.7805392385557461, 1.6464074599905645, 1.5128167169484854, 1.381773350673059, 1.2551389098570678, 1.1345901080093401, 1.0215839592553537, 0.917328889988043, 0.8227624698179469, 0.7385362361393257, 0.6650079065829887, 0.6022410871811339, 0.5500123958868184, 0.5078257358660263, 0.4749332753248104, 0.4503625249600869, 0.43294875453447995, 0.4213718602672864, 0.41419668789757697, 0.4099157350237387, 0.40699310262341903, 0.40390854078277955, 0.3992004381638932, 0.3915066384267006, 0.37960202877821064, 0.3624319344198619, 0.3391404656108006, 0.3090930984585957, 0.27189292295236994, 0.22739015828039, 0.17568471188745557, 0.11712174054449513, 0.05228035430874343, -0.018044216984101077, -0.0928645046667643, -0.1710300819050373, -0.25126145536043953, -0.33218765840411546, -0.412386539045929, -0.4904266641700412, -0.5649097177407002, -0.6345122554921953, -0.6980256926529416, -0.7543934441483604, -0.8027442074263824, -0.8424204747975734, -0.873001482566115, -0.8943199452376513, -0.9064720811923448, -0.9098206074388107, -0.9049905611140053, -0.8928579897344688, -0.874531736189694, -0.8513287234539615, -0.8247433134513753, -0.7964114701434305, -0.7680705947609037, -0.7415160176516092, -0.7185552234682235, -0.700960951983232, -0.6904243539605404, -0.6885093892111581, -0.6966096319223045, -0.71590859702502, -0.7473446219358949, -0.7915812323575515, -0.8489837914907825, -0.9196030821344519, -1.0031663043806704, -1.0990757920338943, -1.206415562901775, -1.323965626349546, -1.4502237807094145, -1.583434448008686, -1.7216239186128315, -1.862641218115349, -2.004203667136466, -2.1439460851581345, -2.279472495123875, -2.4084091186565146, -2.5284574141075695, -2.637445902245035, -2.733379547465906, -2.814485515489868, -2.8792542103178307, -2.926474601881441, -2.9552629886642614, -2.965084493441589, -2.9557667614443095, -2.9275055145551474, -2.880861808119897, -2.816751033911981, -2.736423908935738, -2.641439880318957, -2.5336335568895207, -2.4150749437646635, -2.288024403370715, -2.1548833911792875, -2.018142114058468, -1.8803253310806316, -1.7439375591641342, -1.6114089580380966, -1.4850431504362747, -1.3669681846275556, -1.2590917685971315, -1.163061800332269, -1.0802330893303267, -1.0116410138213927, -0.9579826899891986, -0.9196060478139946, -0.8965070175064879, -0.8883348355238653, -0.8944052846277003, -0.9137214931109096, -0.945001738803075, -0.9867135381273097, -1.0371131533375249, -1.094289525667449, -1.1562115414844243, -1.2207774650585652, -1.2858653269527116, -1.3493830423172866, -1.4093170488018654, -1.4637782988929795, -1.5110445150430527, -1.5495977160551984, -1.5781561472665713, -1.5956998919744723, -1.6014896036108746, -1.5950779733113047, -1.5763137313463798, -1.5453381687865877, -1.502574353059457, -1.448709393065464, -1.3846702817190226, -1.3115940019020698, -1.2307927219488883, -1.1437150254679542, -1.0519042146383843, -0.956954793798449, -0.8604682795462838, -0.7640094937834916, -0.6690644769694374, -0.5770011108726176, -0.4890334645822494, -0.4061907764448234, -0.3292918605221187, -0.25892558230906715, -0.1954378884745311, -0.13892570337054327, -0.08923782536927759, -0.0459827732949327, -0.008543351957844638, 0.02390246933292095, 0.052354935964536664, 0.07796086543006923, 0.10197783473987435, 0.12573515902819812, 0.1505927072999106, 0.17789865919846587, 0.20894733631165355, 0.24493824209381818, 0.28693741593127375, 0.33584214990440847, 0.39235003281478575, 0.456933177139, 0.5298183534633265, 0.6109736069264732, 0.7001017650138559, 0.7966410698539563, 0.8997729853965979, 1.0084370451069982, 1.1213524237484715, 1.2370457420508227, 1.3538844499971467, 1.4701149872489832, 1.583904791619901, 1.693387121768697, 1.7967075811171502, 1.8920711784720274, 1.977788738328871, 2.052321481015646, 2.1143226296183473, 2.162674966200648, 2.1965233526482426, 2.215301349316964, 2.2187512046949016, 2.2069366480978245, 2.180248091124653, 2.139400027947602, 2.085420614968384, 2.0196336022438564, 1.943632977633742, 1.8592508651820006, 1.7685193873335394, 1.6736273520288483, 1.5768727567326686, 1.4806122087590428, 1.3872084421501283, 1.2989771637949814, 1.218134484076719, 1.1467461794858758, 1.0866799964554297, 1.0395621380254765, 1.00673897942649, 0.9892449375578266, 0.9877772755442921, 1.0026784605480104, 1.033926514741835, 1.081133610137419, 1.1435529624018115, 1.2200938816453444, 1.3093446442175638], [1.3787148766482227, 1.4862646024029431, 1.601480495940159, 1.7220829555056376, 1.845659118125107, 1.9697154804709185, 2.09173225269044, 2.209218179963403, 2.319764557222763, 2.4210971838300157, 2.5111250564961027, 2.58798467910047, 2.650078975294754, 2.6961099212390778, 2.7251041682717343, 2.7364310950101554, 2.7298129111569716, 2.70532662665869, 2.6633978951503003, 2.6047869350418718, 2.5305669204164203, 2.442095412510994, 2.3409795666026305, 2.229035994641004, 2.1082462874464913, 1.9807092987620656, 1.8485913645673555, 1.7140756731701063, 1.5793120137396124, 1.4463681129353418, 1.3171837216544013, 1.1935285379464837, 1.076964949796009, 0.9688164553676846, 0.8701424716558231, 0.7817200789733877, 0.7040330724776485, 0.6372685073755983, 0.581320736200839, 0.5358027493026327, 0.5000644481000521, 0.4732173092410623, 0.4541647408159325, 0.44163729308577965, 0.43423176921461026, 0.4304531891018106, 0.42875849384656295, 0.42760084120565384, 0.4254733344876777, 0.42095104878156625, 0.4127302686313541, 0.39966392890753366, 0.3807923536677535, 0.3553685135904513, 0.3228771678811396, 0.28304741768242847, 0.23585837086207023, 0.18153779821451674, 0.1205538440165272, 0.05360003488670974, -0.0184259945764064, -0.0944494772861527, -0.17325045963507413, -0.2534998575413185, -0.33379865454710034, -0.41271919115763933, -0.48884743877839043, -0.5608251241611606, -0.6273905719205217, -0.6874171634125446, -0.7399483693273478, -0.7842283992702859, -0.8197276222508724, -0.8461620445964707, -0.8635062830364346, -0.871999636766226, -0.8721450390263948, -0.8647008516707854, -0.8506656507417083, -0.8312563325594111, -0.8078800436801966, -0.7821005998770116, -0.7556002049374944, -0.7301374058437369, -0.7075023235723645, -0.6894702756816165, -0.6777549560212296, -0.6739623569880293, -0.679546610155976, -0.695768881974447, -0.7236603934303973, -0.7639905377031069, -0.8172409501765745, -0.8835862436090031, -0.9628819612372814, -1.0546601260295054, -1.1581325794733865, -1.2722021127498968, -1.395481201588778, -1.5263179682706118, -1.6628288147815038, -1.8029370044973936, -1.944416320123379, -2.084938796676405, -2.2221254233108945, -2.353598629394407, -2.477035320442953, -2.5902192096197, -2.691091201049687, -2.777796622021684, -2.8487281713060844, -2.9025635486618837, -2.938296853801108, -2.955262988664262, -2.953154461321378, -2.932030169168708, -2.8923159289903637, -2.8347967172843327, -2.76060078125106, -2.6711759742163417, -2.5682588543006855, -2.4538372573485736, -2.3301072103000435, -2.199425185546602, -2.064256807095734, -1.9271232028938852, -1.7905462524040021, -1.6569940031812276, -1.5288275241581257, -1.4082504268087248, -1.2972622192252128, -1.197616564053518, -1.1107853915178187, -1.0379296763693042, -0.9798775260235787, -0.9371100503725488, -0.9097552961070838, -0.8975903344638136, -0.9000513958581063, -0.9162517526612265, -0.9450068671109815, -0.9848661494974561, -1.0341505165109977, -1.0909948047351392, -1.153393982961484, -1.2192520219579683, -1.2864322235456491, -1.3528077836396055, -1.4163113668627672, -1.4749825032765433, -1.5270116797789344, -1.5707800881717116, -1.604894106490712, -1.6282137270073096, -1.6398742998807623, -1.6393011318493749, -1.626216660312908, -1.6006401101467183, -1.5628797289277268, -1.513517881248333, -1.4533894598453356, -1.3835542359835569, -1.3052639198318075, -1.2199248297940724, -1.1290571747620655, -1.034252032473629, -0.9371271586818505, -0.8392827844458903, -0.7422585520555753, -0.6474927041453303, -0.5562845764164698, -0.469761353753013, -0.38884993473075846, -0.31425461353062006, -0.24644113455319952, -0.18562750751075655, -0.13178179370761675, -0.0846268921085263, -0.04365217125784301, -0.00813161477962283, 0.02285202142022873, 0.05037769871527616, 0.07565203014448292, 0.09997157674856065, 0.12468251849420287, 0.15113878195343683, 0.1806597486789641, 0.21448868115835307, 0.2537529869910804, 0.29942739689837544, 0.3523010594579923, 0.41294945686413037, 0.4817119240094084, 0.5586754108256772, 0.6436649686741106, 0.7362412696393366, 0.8357052871814115, 0.941110082276454, 1.051279455579918, 1.1648330479138644, 1.280217303021855, 1.3957415523239776, 1.5096183452640977, 1.6200070342511317, 1.725059533102532, 1.8229671046406704, 1.9120069983442984, 1.990587753682642, 2.0572920091886706, 2.1109157109503323, 2.1505026957745312, 2.1753737318688815, 2.185149230899692, 2.179764996540884, 2.159480542437038, 2.124879692753887, 2.076863366752717, 2.0166346404638458, 1.9456763688167749, 1.8657218358027396, 1.7787190738301428, 1.6867896520695647, 1.5921828733180134, 1.4972264362448688, 1.4042747118655516, 1.315655847391212, 1.2336189455724844, 1.1602825723581622, 1.097585819936788, 1.0472430965798727, 1.0107037304546838, 0.9891173637233884, 0.9833059784491441, 0.9937432403370576, 1.020541673907285, 1.0634479975083484, 1.1218467531262175, 1.1947721689312245, 1.2809279967228817, 1.3787148766482238], [1.4533414623571634, 1.567267128218257, 1.6873979989548165, 1.8113624082023614, 1.9366875784723283, 2.0608534693612044, 2.1813476036806185, 2.2957195966101756, 2.4016341217923345, 2.496921087570969, 2.5796218653415, 2.6480305085288527, 2.700729022658627, 2.7366158913357634, 2.7549272261463402, 2.755250086546643, 2.7375277043345667, 2.702056541695507, 2.649475307324205, 2.580746246971261, 2.4971292082710375, 2.4001491504117904, 2.2915579229666596, 2.173291271297151, 2.047422135165947, 1.9161113899437585, 1.7815572341134207, 1.6459444514161612, 1.5113947704370403, 1.3799195089221983, 1.253375625632545, 1.1334262107535096, 1.0215063291566895, 0.9187949921166995, 0.8261938759327203, 0.7443132342460917, 0.6734652689907138, 0.6136650374128341, 0.5646387841320647, 0.5258394024803579, 0.49646855294110337, 0.4755048027900464, 0.461737004060961, 0.4538020003433687, 0.45022564977269597, 0.44946607440816233, 0.4499579968691592, 0.4501570047756964, 0.44858259264360145, 0.44385886911357353, 0.43475188370873913, 0.4202026199791217, 0.39935481850621385, 0.37157693081144355, 0.3364776602213614, 0.29391471423841564, 0.2439965706631866, 0.18707724209881785, 0.12374420591395506, 0.05479984462180109, -0.0187630895572535, -0.09579131671978129, -0.17500537048449555, -0.2550375135843134, -0.3344722094279686, -0.411888063734205, -0.48590011072544625, -0.5552013076331659, -0.6186021197046238, -0.6750671250658514, -0.7237476435203491, -0.7640094937834908, -0.7954551072569228, -0.8179393701370294, -0.831578725819605, -0.8367532421832602, -0.8341015290622853, -0.8245085755015273, -0.809086759570912, -0.7891504609755952, -0.7661848739353636, -0.741809770578559, -0.7177390995113548, -0.6957374168452176, -0.6775742348956576, -0.6649774347180472, -0.6595869210056499, -0.6629097007368107, -0.6762775401532232, -0.700808298750429, -0.7373719552633091, -0.7865622311275163, -0.8486745842339386, -0.9236911931914454, -1.0112733835007854, -1.1107617661582467, -1.2211841706998856, -1.3412712632130015, -1.4694795501127413, -1.6040212852073403, -1.7429006253042514, -1.8839552226286178, -2.0249023045527657, -2.1633881760220133, -2.2970399905073733, -2.423518573592902, -2.5405710510073285, -2.6460820309055557, -2.73812211862109, -2.814992600322658, -2.8752652186600054, -2.917816076517251, -2.9418528416979988, -2.9469345824505657, -2.932983737406003, -2.900289909536687, -2.8495053676321658, -2.7816323358181547, -2.698002347019669, -2.6002481252332923, -2.490268639423776, -2.370188134461449, -2.242310087808504, -2.109067161155247, -1.9729683109708234, -1.8365442886648742, -1.7022927981427718, -1.5726245850879421, -1.449811708179412, -1.335939188260941, -1.2328611485651826, -1.142162449510624, -1.065126688029673, -1.0027112771378135, -0.955530150304134, -0.9238444513307638, -0.9075613783972576, -0.9062411553753372, -0.9191119092484958, -0.9450920442201939, -0.9828195254486679, -1.0306873226226911, -1.0868841197334258, -1.1494392758742353, -1.216270925628201, -1.2852360388697146, -1.3541812202168058, -1.4209930188069868, -1.483646539672213, -1.5402511981523255, -1.5890925371776472, -1.628669131841038, -1.6577237337953046, -1.6752679564044288, -1.6805999665026394, -1.6733148259286197, -1.6533073112598622, -1.6207672287438653, -1.5761674286064222, -1.520244904055551, -1.4539755308963846, -1.3785431595040747, -1.2953039081218025, -1.2057466216855175, -1.1114505508080221, -1.0140413689896894, -0.9151466810481088, -0.8163521813772665, -0.7191595968959695, -0.6249474970993428, -0.5349359738781851, -0.4501560887932839, -0.3714248579904804, -0.2993263981835786, -0.23419969486273962, -0.17613328023700162, -0.12496692780489138, -0.0803002874510559, -0.04150820423003616, -0.007762290101283585, 0.021941844772222763, 0.04875244183572797, 0.07392539392786555, 0.09878496974435896, 0.12468251849420281, 0.15295426398209527, 0.18487932260857287, 0.22163907591832094, 0.2642789954246751, 0.3136739563032041, 0.37049798870006223, 0.4351993030363152, 0.5079812916215604, 0.588790056482081, 0.6773088463892539, 0.7729596088411285, 0.8749116796673054, 0.9820974486114565, 1.0932346583514383, 1.2068548215206356, 1.3213370797789061, 1.4349466849283028, 1.545877158152498, 1.6522950828575564, 1.752386411905726, 1.8444031232201914, 1.926709040061083, 1.9978236442705093, 2.0564627522551673, 2.1015749934818535, 2.1323731281530627, 2.148359362181523, 2.149343960652506, 2.1354566221643876, 2.107150251826156, 2.065196955958327, 2.010676272129352, 1.944955839358968, 1.8696649004028019, 1.7866612063611456, 1.6979920589966295, 1.6058503739858272, 1.5125267751725784, 1.4203588325502376, 1.3316786325827343, 1.2487599166397976, 1.173766040536532, 1.1086999949311578, 1.0553576828974742, 1.0152855783432224, 0.9897437888042709, 0.9796754208991235, 0.9856829993886063, 1.0080125249095913, 1.046545575054792, 1.1007996629300096, 1.1699368712650107, 1.252780583353325, 1.347839939339751, 1.4533414623571645], [1.532593026660372, 1.651924922950517, 1.775936872424431, 1.9021852215977433, 2.028158219474325, 2.151330637503727, 2.2692186041395757, 2.379433380221514, 2.4797328282963567, 2.568069385870074, 2.6426334380327794, 2.701891096817297, 2.744615530284541, 2.7699111403439596, 2.7772300608864517, 2.7663806327006726, 2.737527704334567, 2.691184803839687, 2.6281984204146642, 2.549724822612786, 2.457200016428886, 2.352303607942123, 2.23691747735617, 2.1130802908182487, 1.9829389704477465, 1.848698309331247, 1.712569955298211, 1.576721994259678, 1.4432303406940918, 1.3140330901673418, 1.1908889079733276, 1.0753404211628115, 0.9686834511173024, 0.8719427737164721, 0.7858549278255184, 0.7108584144692421, 0.6470914431281104, 0.5943971927312731, 0.5523363678379826, 0.5202066498425765, 0.49706847328938575, 0.48177640274123557, 0.47301524992163135, 0.46933995737925477, 0.46921818647470875, 0.4710744862035119, 0.4733348867030717, 0.4744707579829637, 0.4730408004694932, 0.46773008863399923, 0.45738517083040675, 0.4410443353726454, 0.4179622820830985, 0.38762858672969536, 0.3497795091597697, 0.30440287037396, 0.25173590483084424, 0.1922561773384708, 0.12666583433147124, 0.05586963258073852, -0.019052649950567185, -0.09687867039885231, -0.17627996711340924, -0.2558614142235033, -0.33420262446764115, -0.4099001884897179, -0.48160961574021777, -0.548085848189349, -0.608221253127068, -0.6610800645257315, -0.705928332198604, -0.7422585520555747, -0.7698082862760117, -0.7885722357846233, -0.7988073951686017, -0.8010310978907945, -0.7960119428556629, -0.7847537774498355, -0.768473092456048, -0.7485703561649699, -0.726595974222783, -0.7042117042036901, -0.6831484759492629, -0.6651616672384456, -0.6519849567943083, -0.6452839210952042, -0.6466105567338543, -0.6573598956801538, -0.6787298370143939, -0.7116852465039645, -0.7569272765060963, -0.8148687354689447, -0.8856161917616365, -0.9689593342169456, -1.064367935595247, -1.1709965795051234, -1.2876971207204448, -1.4130386580240244, -1.5453346124082887, -1.682676326297163, -1.8229724358269992, -1.9639931222199525, -2.1034182235549133, -2.2388880879252775, -2.36805597560986, -2.488640773352305, -2.598478769318821, -2.695573253218841, -2.778140752114857, -2.8446527875610306, -2.893872142122866, -2.9248827505964283, -2.9371124803054034, -2.930348232108387, -2.904742975147144, -2.860814519507365, -2.799436027201644, -2.7218184584457235, -2.6294853422975195, -2.5242404436842056, -2.408129068197062, -2.283393897659431, -2.1524263796749743, -2.017714799970473, -1.8817902447902883, -1.747171709973239, -1.6163116324551345, -1.4915431083389443, -1.3750300196601994, -1.2687212205922465, -1.1743098348470664, -1.0931985918707556, -1.02647198316014, -0.9748758552298602, -0.9388048764789577, -0.9182981258344898, -0.9130428562210999, -0.9223862903816062, -0.9453551151267701, -0.9806821573876326, -1.0268395559240098, -1.0820775903198239, -1.1444681976491047, -1.211952100082552, -1.2823883862804981, -1.3536053375784813, -1.423451267903427, -1.4898441545111687, -1.5508188747141425, -1.6045709307361407, -1.6494956389436164, -1.6842218785464984, -1.7076396354163, -1.7189207353849485, -1.717532334271908, -1.7032429146053265, -1.6761207269864966, -1.6365248026068635, -1.5850888478706397, -1.5226985078241497, -1.4504626477923193, -1.3696794482551296, -1.2817982329780786, -1.188378051679535, -1.0910441136115636, -0.9914432155450692, -0.891199325684285, -0.7918704736185892, -0.6949080559177211, -0.6016195984849066, -0.5131359220955904, -0.430383539116105, -0.3540629702581493, -0.2846335139379249, -0.22230483135678344, -0.16703553211218913, -0.1185387625116662, -0.07629461643007952, -0.039569011142723536, -0.007438502576726971, 0.021179639895204817, 0.0474929157345302, 0.07279556490392153, 0.09842805295947062, 0.125735159028198, 0.1560237935864085, 0.19052168148246876, 0.23033802501629727, 0.27642721260018077, 0.329556561806553, 0.39027898337502587, 0.4589113275645532, 0.535519029238433, 0.6199075069032522, 0.7116205976424047, 0.8099461288543462, 0.9139285434901129, 1.0223883127354172, 1.1339476934211667, 1.247062221349002, 1.360057180403702, 1.4711681546477673, 1.578584659949848, 1.6804957659374564, 1.7751365604180502, 1.8608342784386218, 1.936052917696707, 1.9994351911838224, 2.0498407261040374, 2.086379503909417, 2.108439647682042, 2.1157087973778648, 2.1081884673637665, 2.0862009504624055, 2.050388514203474, 2.0017048236980095, 1.941398716848024, 1.8709906467461246, 1.7922422884203013, 1.7071199780093778, 1.617752807756343, 1.526386336000356, 1.4353329842276492, 1.346920280359019, 1.2634381665914238, 1.187086619740795, 1.1199248313474761, 1.0638231637421207, 1.0204190375157374, 0.9910778168107033, 0.9768596436650818, 0.9784930340625169, 0.996355889703451, 1.030464404657485, 1.0804701592199244, 1.1456654990155302, 1.2249971003933182, 1.3170874282329952, 1.4202636041834136, 1.5325930266603733], [1.6157990654621017, 1.7395217433481989, 1.866348037415153, 1.993782993592667, 2.1192971581172824, 2.2403815071146136, 2.354601825641346, 2.459651274307148, 2.553399926337737, 2.6339401319287465, 2.69962666815191, 2.749110759016689, 2.7813671984591104, 2.7957139753907874, 2.7918239804180196, 2.7697285640151517, 2.7298129111569716, 2.6728033929130084, 2.599747246512835, 2.511985117253874, 2.4111171639211157, 2.2989635800416393, 2.1775205126661112, 2.0489124653449275, 1.9153423500443707, 1.7790404020912804, 1.642213191717603, 1.5069939550117202, 1.375395426431148, 1.2492662855873837, 1.1302522345837083, 1.0197626012384464, 0.9189432211286857, 0.8286561911355387, 0.7494669130887861, 0.6816386625566299, 0.6251347293909278, 0.5796279880157204, 0.544517571327347, 0.5189521470254534, 0.5018591335472856, 0.4919790485211115, 0.48790405933449765, 0.4881197060459086, 0.49104869386592875, 0.4950956075461526, 0.4986913842821422, 0.5003363954732234, 0.49864103045968056, 0.4923627460238506, 0.48043864214562837, 0.4620127447448917, 0.43645731683657346, 0.4033876770726812, 0.36267017503519045, 0.3144231515422101, 0.2590108950958961, 0.19703078779785316, 0.12929401097061166, 0.05680034787330485, -0.01929222594439245, -0.09770233881920765, -0.17706346585757307, -0.2559645888866612, -0.33299218047687085, -0.40677238374826996, -0.47601225335175107, -0.5395389458363868, -0.5963357990164958, -0.6455743186535713, -0.6866411947992244, -0.7191595968959689, -0.7430041430189567, -0.758309100784654, -0.7654695513699279, -0.765135429393998, -0.75819853554157, -0.7457728010964785, -0.7291682593988018, -0.70985934417694, -0.6894482845482051, -0.6696244974072558, -0.6521209865789891, -0.6386688417007786, -0.6309509861403341, -0.6305563508497533, -0.6389356491194539, -0.6573598956801537, -0.6868827531983654, -0.7283077013351831, -0.7821609102921613, -0.8486705648918246, -0.9277532300437161, -1.01900767772836, -1.1217164135843876, -1.2348549522926568, -1.3571086998804371, -1.4868971125477475, -1.6224046203235925, -1.761617634300648, -1.9023668025998166, -2.042373546423292, -2.1792997969262045, -2.310799768967396, -2.4345725512492877, -2.54841426539452, -2.650268549876974, -2.738274158423754, -2.810808525782993, -2.866526245131377, -2.904391518702442, -2.9237037836389996, -2.9241158752257412, -2.9056442656670307, -2.8686711041726025, -2.813937978743208, -2.7425315169754767, -2.6558611376356986, -2.555629451948859, -2.443795988948853, -2.322535078561702, -2.1941888654607062, -2.0612165427431055, -1.9261409843053188, -1.7914940162525619, -1.6597615992762635, -1.533330194909729, -1.4144355589173176, -1.305115145524461, -1.207165218225595, -1.122103648679691, -1.0511392475259447, -0.9951483132038698, -0.954658910910458, -0.929843207932884, -0.9205179983071655, -0.9261533537958242, -0.9458891443347104, -0.9785589840960129, -1.022720983701437, -1.076694529159894, -1.1386021676697746, -1.206415562901775, -1.278004390579911, -1.3511869812827646, -1.4237814828797322, -1.493656310657029, -1.5587786789885993, -1.6172600636382723, -1.6673975269853192, -1.7077099475031867, -1.7369683269130602, -1.754219500238781, -1.7588027416855847, -1.7503589386451528, -1.7288321927066759, -1.6944638956725755, -1.6477795155304484, -1.5895685074764154, -1.520857933955978, -1.442880531113797, -1.3570380932447637, -1.264861158523739, -1.1679660657377424, -1.0680105108653901, -0.9666487627436909, -0.8654876980530587, -0.7660447874955959, -0.669709108131453, -0.5777063728802941, -0.4910688593714025, -0.41061098943892627, -0.33691116096032436, -0.2703002692429831, -0.2108571799630784, -0.15841123420223305, -0.11255168301509988, -0.07264376883502147, -0.03785099844691868, -0.007162991594926267, 0.020571855387336104, 0.04660977657244103, 0.07227210193744686, 0.0989038460714025, 0.1278315342809456, 0.160321401156946, 0.19753908839138204, 0.24051193140659385, 0.29009485910316174, 0.346940839378903, 0.4114766873169311, 0.48388491599152206, 0.5640921551388187, 0.651764494377821, 0.7463099294917167, 0.846887906983087, 0.9524257783265604, 1.061641795706023, 1.173074110089555, 1.2851150746023614, 1.3960500153239082, 1.5040995114581421, 1.607464130390629, 1.7043704929510208, 1.793117502088531, 1.8721215552876314, 1.9399595778182201, 1.9954087600064607, 2.0374819560730204, 2.0654578029508435, 2.0789047424362774, 2.077698276010694, 2.06203094512977, 2.032414706705982, 1.9896755595542595, 1.9349404681423736, 1.8696168203748635, 1.7953648416244516, 1.7140635632007766, 1.6277711055321096, 1.5386801804834511, 1.4490698398323962, 1.3612545948852082, 1.2775321030540747, 1.2001306591130696, 1.131157740693455, 1.0725508389984812, 1.0260317570899082, 0.9930654805414242, 0.9748246205990171, 0.9721603007351357, 0.9855802067412419, 1.0152343519120766, 1.0609089265184792, 1.1220284090695956, 1.1976659204896036, 1.2865616060576768, 1.387148638563374, 1.4975862542772103, 1.615799065462103], [1.7022556180229278, 1.8293164806727251, 1.9578665745596422, 2.0853807655875904, 2.2093333177394423, 2.3272526675409786, 2.4367748874956776, 2.5356945991841027, 2.6220121589323044, 2.69397602942848, 2.7501193671823545, 2.789289995417681, 2.8106730914392584, 2.813806092815833, 2.7985855135779834, 2.7652655554762036, 2.7144485954430477, 2.647067823969593, 2.5643624954242297, 2.4678464258792725, 2.3592705325326717, 2.240580347483015, 2.1138695540951935, 1.9813306837169646, 1.8452041719522518, 1.7077270056396716, 1.571082193428287, 1.4373502644366227, 1.3084639417185222, 1.1861670516563834, 1.071978619158971, 0.9671629644862245, 0.8727064640442539, 0.7893014684499363, 0.7173376907929612, 0.6569011908315241, 0.6077808915129093, 0.5694823774212109, 0.5412485451566842, 0.522086507690491, 0.5108000025612228, 0.5060264211296264, 0.5062774662346641, 0.5099823611716772, 0.5155324759754089, 0.5213262088798444, 0.5258129621629059, 0.5275350822489734, 0.5251666930842104, 0.5175484378552049, 0.5037172548552623, 0.4829304458642579, 0.4546834464035258, 0.4187208728050297, 0.37504059698122477, 0.3238907816302536, 0.26575999174872905, 0.20136067811194272, 0.13160650026774567, 0.05758411622697148, -0.019479790617412167, -0.09825535337329688, -0.17734923796307417, -0.2553461646694498, -0.33085111835955183, -0.4025311121533217, -0.469155379778688, -0.5296329112357028, -0.5830463136929123, -0.6286810730758793, -0.6660494092321382, -0.6949080559177204, -0.7152694526667251, -0.7274060049534457, -0.731847247667667, -0.7293699302913288, -0.7209812256566458, -0.7078954431404987, -0.6915047970724775, -0.6733449376898567, -0.6550560911757976, -0.6383407736096433, -0.6249191380007055, -0.6164830815244058, -0.6146502798434481, -0.6209193258902727, -0.6366271313538018, -0.6629097007368101, -0.7006673113449846, -0.7505350297544658, -0.8128593686613244, -0.8876817406237358, -0.9747292006690836, -1.0734127920924492, -1.182833623393937, -1.301796613790821, -1.4288316548110713, -1.5622217508375684, -1.7000375267171128, -1.8401773300307367, -1.9804120133534457, -2.1184333613823294, -2.251905032219115, -2.3785148137863454, -2.496026957096653, -2.6023333389290553, -2.6955022277031215, -2.7738234775398807, -2.835849055477928, -2.8804279136848, -2.906734349712797, -2.9142891502389134, -2.902972983619017, -2.8730316898612624, -2.82507330883353, -2.7600568839909574, -2.679273274859761, -2.5843184021681607, -2.477059530226209, -2.359595357515829, -2.2342108344017313, -2.1033277528034118, -1.9694522535062629, -1.8351204700779349, -1.7028435723105824, -1.5750534856639709, -1.4540505460177182, -1.3419543015827324, -1.2406585972442261, -1.151791972795418, -1.0766842780216008, -1.0163402575614184, -0.9714206905828143, -0.94223148867682, -0.9287209644370138, -0.9304852876231687, -0.9467819503793804, -0.976550872455044, -1.0184425963998225, -1.0708528556682055, -1.1319626495231123, -1.1997828311705, -1.2722021127498968, -1.3470373150997024, -1.4220846433895624, -1.4951707528291502, -1.564202382047773, -1.6272133749689723, -1.6824079839213242, -1.728199445466234, -1.7632429434636692, -1.786462218119502, -1.797069241528721, -1.794576555486221, -1.7788020516951684, -1.74986616336065, -1.7081816258106362, -1.6544361475504714, -1.5895685074764156, -1.51473875453883, -1.4312933289988656, -1.3407260460566428, -1.2446359800727813, -1.1446833584977372, -1.0425446172715584, -0.939867782875872, -0.8382293301588346, -0.7390936199991435, -0.6437759480380915, -0.5534101369949785, -0.4689214830417276, -0.3910057244791972, -0.32011454216494745, -0.25644792983473963, -0.19995359299253668, -0.1503333519699908, -0.10705634271691775, -0.06937863248856328, -0.036368701307437724, -0.006938088103457647, 0.02012363338057882, 0.04611049610639676, 0.07235943376200764, 0.10020832365512881, 0.13095390796918663, 0.16581072698897148, 0.20587217289745047, 0.2520747192374036, 0.30516630045952226, 0.36567971016551665, 0.43391175835835866, 0.5099087804584519, 0.5934589277481136, 0.684091494376301, 0.7810833544926431, 0.8834723990680364, 0.9900776801497344, 1.0995257952949387, 1.2102828811666824, 1.3206914369230751, 1.4290110688691573, 1.5334621411792024, 1.6322712360868021, 1.723717272904278, 1.8061771100141675, 1.878169458297526, 1.9383959683132108, 1.9857784161681662, 2.019491002948986, 2.0389868976634187, 2.0440182910788463, 2.0346493842907347, 2.0112619074751326, 1.9745529468558498, 1.925525046947769, 1.8654687459506363, 1.7959378900357126, 1.7187182525263456, 1.635790152135862, 1.5492859162962718, 1.461443167385455, 1.3745550180256416, 1.2909183438399465, 1.212781356013913, 1.142291720307913, 1.0814464631226246, 1.032044868901796, 0.9956455073756045, 0.9735284354441628, 0.9666634991027699, 0.9756855185820976, 1.000876978247455, 1.0421586656815964, 1.0990885160613275, 1.1708687230047545, 1.2563609802561007, 1.3541095246819095, 1.4623714648020067, 1.5791537050124493, 1.7022556180229291], [1.7912312227861493, 1.9205494308137483, 2.0497181956210455, 2.176203578982973, 2.297504951688573, 2.4112091494559666, 2.5150425684155473, 2.6069199939139205, 2.684989035544919, 2.747669147509871, 2.793684344042108, 2.822088871499008, 2.8322852681093056, 2.8240344251189047, 2.7974574547361803, 2.753029366155603, 2.6915647462561663, 2.614195831568181, 2.5223435381548396, 2.4176821817909957, 2.3020987682259673, 2.1776478588324104, 2.0465031175553134, 1.910906718388037, 1.7731178368959368, 1.6353614635800797, 1.4997787608629343, 1.3683801396707804, 1.2430021572037258, 1.125269236446126, 1.0165610828547207, 0.9179865276346768, 0.8303643637513125, 0.7542115644217999, 0.6897390886973049, 0.6368552894985526, 0.5951767508152037, 0.5640461974043155, 0.5425569467666489, 0.5295832137281483, 0.5238154365335501, 0.5237996734380037, 0.5279800232856937, 0.534742954801232, 0.5424623889274651, 0.5495443674478216, 0.5544701595238373, 0.5558367051125447, 0.55239336923428, 0.5430740817785134, 0.5270240613620929, 0.5036204655139064, 0.47248646948040146, 0.43349844815249494, 0.3867861156305293, 0.3327256602033941, 0.2719260943776593, 0.20520921544938456, 0.13358373751700614, 0.058214306606807174, -0.019613757087618595, -0.0985330353077505, -0.17713486566858663, -0.2540113737205869, -0.3277975524700382, -0.3972122567817638, -0.46109700727422737, -0.5184515539225503, -0.5684652322157157, -0.6105432522945234, -0.6443271913211325, -0.6697091081314525, -0.6868388632497878, -0.6961244024655409, -0.6982249439654062, -0.6940371928892682, -0.6846748884835416, -0.6714421631699035, -0.6558013554112672, -0.6393360651055583, -0.6237103676241365, -0.610625207270227, -0.601773070162361, -0.5987920882795901, -0.6032207492550756, -0.6164543798087229, -0.6397045345418119, -0.6739623569880284, -0.7199668878547477, -0.7781791785054053, -0.8487629287645716, -0.9315722104652285, -1.0261466656693792, -1.1317143854230973, -1.2472024857730535, -1.3712552072518944, -1.5022591768586266, -1.6383752923687676, -1.7775765220714699, -1.9176907629128848, -2.05644777028905, -2.191529066645053, -2.3206196562888235, -2.441460322461551, -2.5518992610700524, -2.6499418141951514, -2.7337971054143826, -2.8019204472412476, -2.853050486987476, -2.88624017881476, -2.900880813743441, -2.8967185024549047, -2.8738626839154913, -2.8327864218397583, -2.774318446206723, -2.6996270936936906, -2.610196494207477, -2.507795535958623, -2.3944403142206383, -2.2723509248282756, -2.143903598789921, -2.0115792858157517, -1.8779098793752051, -1.745423332025938, -1.6165889358348824, -1.4937640381083792, -1.3791434274831784, -1.2747125605703828, -1.1822057063848663, -1.1030699670147333, -1.0384359913010632, -0.9890960371789991, -0.9554898617212196, -0.9376987301445164, -0.9354476406791429, -0.9481156660046364, -0.9747541187101251, -1.0141120626481186, -1.0646685186305684, -1.1246705558711791, -1.192176323706283, -1.265101964724218, -1.3412712632130015, -1.4184668238627343, -1.49448154629791, -1.5671691618989505, -1.634492630389232, -1.6945692539572395, -1.7457114546779329, -1.7864622744353544, -1.8156247925502704, -1.8322848114499757, -1.8358263310850778, -1.8259395141342682, -1.8026210318148965, -1.7661668696575359, -1.7171578591963668, -1.656438380547882, -1.5850888478706402, -1.5043927405995352, -1.4157990744206859, -1.3208813139912636, -1.221293811786898, -1.118726912198314, -1.0148618858133203, -0.9113268551498261, -0.8096548401285497, -0.7112449902017942, -0.6173279819069147, -0.5289364479787217, -0.4468811699321168, -0.37173361364996066, -0.3038152208675841, -0.2431936927728432, -0.18968631972485836, -0.14287022795443066, -0.10209923468271224, -0.06652683192168704, -0.03513466062882777, -0.006765694887628927, 0.019838766035932907, 0.045999298475067125, 0.07305682151085001, 0.10233044924000839, 0.13507586339862843, 0.17244532890199765, 0.21545043333498903, 0.2649285620914567, 0.3215140254554824, 0.38561463484010344, 0.4573943856463128, 0.5367627472960196, 0.6233708908814268, 0.7166150058505709, 0.8156466737345217, 0.919390083751484, 1.0265656968325305, 1.1357197957229372, 1.245259203612076, 1.3534903161874234, 1.4586614756114105, 1.559007622676767, 1.652796097698835, 1.738372423284305, 1.8142048940023678, 1.8789268194721347, 1.931375318025633, 1.970625636735591, 1.9960200783363617, 2.007190743884097, 2.0040754487745303, 1.9869263353217825, 1.956310883431664, 1.9131052075830854, 1.8584797187490925, 1.7938774193288516, 1.7209852829213366, 1.6416993442785537, 1.5580842837022886, 1.4723284305177538, 1.3866952285433103, 1.3034722996909194, 1.2249193076032234, 1.1532158598585402, 1.0904106937706632, 1.0383733669311626, 0.9987496198935991, 0.9729214960217274, 0.9619731944660899, 0.9666634991027695, 0.9874054722678026, 1.0242539309723444, 1.0769010391341296, 1.1446801566820357, 1.2265778898690158, 1.3212540915495794, 1.427069370308673, 1.5421194878001978, 1.664275858846218, 1.7912312227861507], [1.88197310587355, 2.0124487217296947, 2.141125794321851, 2.265483031679697, 2.383066088043347, 2.4915406430318363, 2.5887426884038454, 2.6727248594273307, 2.741797743302077, 2.79456521809754, 2.8299530193135602, 2.847229893927362, 2.8460208796750015, 2.826312435980345, 2.7884493477808654, 2.7331235197519392, 2.6613549713155087, 2.5744655276392328, 2.4740458740969595, 2.36191679719361, 2.2400855699975564, 2.1106985514210863, 1.9759911535832595, 1.8382363879720343, 1.6996932278894397, 1.5625560211441103, 1.428906153326218, 1.3006670991790488, 1.179563909205549, 1.0670880630298667, 0.9644684831048126, 0.8726493455921591, 0.792275153578358, 0.7236833555175698, 0.6669046034640561, 0.6216705559538663, 0.5874289440315524, 0.5633654405078764, 0.5484317064875623, 0.5413788396130487, 0.5407953190033107, 0.5451484356892262, 0.5528281170344164, 0.5621920011081714, 0.5716105934725992, 0.5795113448597377, 0.5844205235077334, 0.5850018195278812, 0.580090708909448, 0.5687237192956995, 0.5501618755366219, 0.5239077567652611, 0.48971576443601045, 0.4475953781407082, 0.39780735858042343, 0.3408530401910748, 0.2774570349642527, 0.20854383944282087, 0.13520899439655434, 0.058685587317034126, -0.01969299193805328, -0.09853303530775052, -0.17642216266072644, -0.2519715089754995, -0.32385731735750967, -0.3908608175568491, -0.451905313316212, -0.5060894732394208, -0.5527159171322171, -0.5913143104807712, -0.6216583208591495, -0.6437759480380904, -0.6579529104195998, -0.6647289498330738, -0.6648871001667325, -0.6594361481344839, -0.6495866920635467, -0.6367213724285417, -0.6223600016876158, -0.6081204568752971, -0.5956763128985704, -0.5867122846216742, -0.5828786092715832, -0.5857455357744484, -0.5967590933759159, -0.6171992880693651, -0.648141822459973, -0.6904243539605394, -0.744618199577225, -0.8110062655804483, -0.8895678302368849, -0.9799706411807791, -1.081570610024032, -1.1934191998589576, -1.3142784110187677, -1.4426430815448243, -1.5767700359602481, -1.7147134437201235, -1.8543655913991703, -1.9935021342296808, -2.129830776496381, -2.261042239468756, -2.3848623123219777, -2.4991037475064526, -2.601716758195365, -2.6908369019489746, -2.7648291910166902, -2.8223273544501577, -2.862267288417329, -2.883913866128178, -2.88688043435743, -2.871140495918034, -2.837031262423217, -2.78524895478117, -2.7168359253968415, -2.6331598712221114, -2.5358855958405426, -2.426939957082208, -2.3084707998851752, -2.182800818265286, -2.0523774118040334, -1.9197196980450963, -1.7873639102584744, -1.6578084485256657, -1.5334598600807114, -1.416581002119704, -1.3092425874247673, -1.213279231436466, -1.130251010853287, -1.0614114110994035, -1.0076823863312807, -0.9696370848112721, -0.9474906086400372, -0.9410989845018269, -0.9499663259344077, -0.9732599724726236, -1.009833201586431, -1.0582549302482704, -1.1168456585687119, -1.183718762213854, -1.25682611677882, -1.3340069389038194, -1.4130386580240273, -1.4916885909026525, -1.567765179449233, -1.6391675709687537, -1.703932368373736, -1.7602764547382808, -1.8066348999003508, -1.8416930839953733, -1.8644123206166612, -1.8740484270299476, -1.8701628663924208, -1.8526262728076637, -1.8216143596543124, -1.7775964002459088, -1.7213166528335324, -1.6537692747255017, -1.5761674286064224, -1.4899074240976444, -1.3965288557842197, -1.2976717924617431, -1.1950321389722387, -1.0903163301205916, -0.9851965249253907, -0.8812674487290311, -0.7800059810779646, -0.6827345101132812, -0.590588971499234, -0.5044923643150708, -0.42513439106483214, -0.352957707729561, -0.2881510967019365, -0.2306496949004483, -0.18014222593788187, -0.13608500356182632, -0.09772229828956959, -0.06411249465764302, -0.03415931695363961, -0.006647270472054833, 0.019719663460038, 0.04627712446073069, 0.07435836496804714, 0.10525226868332047, 0.14016252696113185, 0.1801690751616491, 0.2261928332864842, 0.27896471064177825, 0.3389997249401472, 0.40657695491926005, 0.48172589552792733, 0.5642196197932207, 0.6535749757953341, 0.7490598651765028, 0.8497074658964874, 0.9543370811680719, 1.061581123242797, 1.1699175793684256, 1.277707161910881, 1.383234219035168, 1.4847503796926658, 1.5805198296179037, 1.6688650656098836, 1.748211954887356, 1.8171329353679793, 1.874387231193211, 1.9189570248337993, 1.9500786210794454, 1.9672677568780856, 1.9703383514617752, 1.9594141500435678, 1.9349328876930416, 1.8976427835283942, 1.848591364567356, 1.7891068087731474, 1.7207721832956857, 1.6453931320043647, 1.5649597316963058, 1.4816033847093113, 1.397549743349901, 1.31506876534345, 1.2364230767906377, 1.1638158678865063, 1.0993395656391263, 1.044926516462258, 1.0023028700036472, 0.9729467848467718, 0.9580519784470628, 0.9584975201746861, 0.9748246205990162, 1.00722100568073, 1.055513285317667, 1.1191675360691646, 1.1972981224705, 1.2886845849020228, 1.3917962292840287, 1.5048238696292584, 1.6257180031969907, 1.7522325438388688, 1.8819731058735507], [1.9737135498930385, 2.1042368438345114, 2.23131602101464, 2.352463779108535, 2.4652928408733454, 2.5675675074825186, 2.6572517110957827, 2.7325524567850468, 2.7919576548299183, 2.834267479213599, 2.858618543592151, 2.8645003582765565, 2.8517637166470653, 2.8206208523974547, 2.7716374053730948, 2.705716428733287, 2.6240748589871523, 2.528213048532157, 2.419878123343462, 2.3010220724749346, 2.1737555975657434, 2.0402988466846486, 1.9029302253012632, 1.7639345163479776, 1.6255515503499718, 1.4899266453196123, 1.3590639851481219, 1.2347840259244902, 1.118685914008191, 1.0121157704619872, 0.9161415468753011, 0.8315349914340597, 0.7587610854790193, 0.6979751241987493, 0.6490274251710114, 0.6114754599144238, 0.584603021113268, 0.5674458662432836, 0.5588231211938265, 0.5573735890126243, 0.5615959924813255, 0.5698920876942234, 0.580611521363826, 0.5920972687399024, 0.6027304826106451, 0.6109736069264744, 0.6154106604825963, 0.6147836754296644, 0.6080243800828737, 0.5942803428667738, 0.5729349410009524, 0.5436206799542306, 0.5062255636386829, 0.4608923963630358, 0.4080110811283812, 0.34820416028091844, 0.28230601924836757, 0.21133633766433266, 0.13646852049775213, 0.05899397110958685, -0.019716824806027357, -0.0982553533732969, -0.17521715872944182, -0.24924382861298064, -0.3190637491939948, -0.3835305305284793, -0.4416580637948157, -0.4926512579827986, -0.5359316147746703, -0.5711569331835631, -0.5982345867480794, -0.6173279819069136, -0.6288559824081483, -0.6334852667919196, -0.6321157695157291, -0.6258595365227526, -0.6160134984159643, -0.6040268245174221, -0.591463664886411, -0.5799622111699274, -0.5711911077876319, -0.5668043198103145, -0.568395611017349, -0.5774538037468065, -0.5953199807386392, -0.6231477484112397, -0.6618676118345804, -0.7121564157108168, -0.7744126852603969, -0.8487385589685136, -0.934928845147377, -1.0324675601459947, -1.1405321220841813, -1.2580051847481513, -1.3834939064512979, -1.515356262949711, -1.651733836531388, -1.79059034958779, -1.9297550644262513, -2.0669700454747475, -2.1999401785367367, -2.3263847669562803, -2.4440894783784044, -2.5509573994612227, -2.645057969904234, -2.72467261124289, -2.7883359390236695, -2.8348715474973933, -2.8634214814567387, -2.873468657283051, -2.864851661099613, -2.837771532137785, -2.7927903296344265, -2.730821477167765, -2.6531120745410743, -2.5612175593550965, -2.4569692835852077, -2.342435740323779, -2.219878328212747, -2.091702672250268, -1.9604066264020483, -1.8285261631709224, -1.6985804060273233, -1.5730170811377173, -1.4541596546452922, -1.3441573811081309, -1.244939418579875, -1.1581740679443577, -1.085234070883453, -1.0271687552831872, -0.9846836525264633, -0.9581280320005463, -0.9474906086400368, -0.9524034840582559, -0.972154185555768, -1.005705474816483, -1.0517224140936965, -1.108606006620723, -1.1745325739999475, -1.2474979001509525, -1.3253650622369595, -1.4059147864478876, -1.4868971125477506, -1.5660831269370665, -1.6413155301458437, -1.7105568409181717, -1.7719341043960974, -1.8237790646606353, -1.864662879673822, -1.893424596505182, -1.9091927630987917, -1.9113997257733562, -1.8997883448245916, -1.874411049452134, -1.8356213430653159, -1.7840580561250683, -1.7206228214460868, -1.6464514119263718, -1.562879728927727, -1.4714053573654442, -1.3736457078590047, -1.2712938445226494, -1.1660731472643595, -1.0596919786448842, -0.9537995169846123, -0.849943879793846, -0.7495335957709088, -0.6538033912962952, -0.5637851409426382, -0.4802846940128963, -0.40386513402962215, -0.33483685937828056, -0.2732546952465442, -0.21892206411577902, -0.17140205898379737, -0.13003508486088836, -0.09396256439996242, -0.06215604708218508, -0.033450922130713455, -0.00658381678087879, 0.019767333314580717, 0.04694162352983102, 0.07625305248699603, 0.10894906207043605, 0.14617086318121653, 0.1889166193795335, 0.23800848718735418, 0.2940644127202017, 0.3574754619835057, 0.4283893196895588, 0.50670043241947, 0.5920471003843523, 0.683815642263957, 0.7811515741627304, 0.8829775612641628, 0.988017723905956, 1.0948277130284416, 1.2018298175070894, 1.3073522316530215, 1.4096714985889476, 1.507057057179032, 1.5978167589975063, 1.6803421890801296, 1.7531526208236305, 1.814936461556094, 1.8645891004317812, 1.9012461531174552, 1.9243112062498111, 1.9334772962242686, 1.9287415083122428, 1.9104122496826894, 1.8791089294987542, 1.835753966438123, 1.7815572341134212, 1.7179932432299299, 1.646771541228475, 1.5698009810873925, 1.4891486666271183, 1.406994518170412, 1.325582516323895, 1.2471697700758888, 1.1739746160906523, 1.10812498743942, 1.0516082911840676, 1.0062240051045517, 0.9735401450661711, 0.9548546674217261, 0.9511627574988261, 0.9631308183472177, 0.9910778168107021, 1.0349644704415757, 1.0943905730006416, 1.1686005627968226, 1.256497241626249, 1.3566633573601954, 1.467390575053534, 1.586715184395101, 1.7124597297233681, 1.8422796066345104, 1.9737135498930392], [2.0656763891751853, 2.195137228080592, 2.319525825570047, 2.436409924787001, 2.5434895346415964, 2.6386465211322125, 2.7199900191587014, 2.7858966174411255, 2.8350443945792985, 2.8664400317635295, 2.8794383935711862, 2.8737541486032225, 2.8494651920260496, 2.8070078277428157, 2.7471638641531295, 2.6710399694915146, 2.580039815890838, 2.4758297111496854, 2.3602985695769076, 2.2355132045612676, 2.1036700325119573, 1.9670443579813979, 1.8279384612230363, 1.6886297309717873, 1.5513200764190096, 1.4180878134912283, 1.2908431526753743, 1.1712883205192692, 1.0608832269986288, 0.9608174492128586, 0.871989141914876, 0.7949913112010135, 0.7301057036347052, 0.6773043737354026, 0.636258802836045, 0.6063562565060523, 0.5867228906469837, 0.5762529523624019, 0.5736432748148576, 0.5774321391092481, 0.5860414738575581, 0.5978212869604028, 0.611095176101162, 0.6242057455999727, 0.6355587679975843, 0.6436649686741113, 0.6471783798664215, 0.6449303048405215, 0.6359580512562993, 0.6195277318918206, 0.5951505873163269, 0.5625924548304368, 0.5218761867163948, 0.4732770040283474, 0.4173109551644099, 0.3547168266705452, 0.2864320226287698, 0.21356308431534607, 0.13735165965984128, 0.059136848918035105, -0.01968505405469327, -0.09770233881920767, -0.17353004875326197, -0.24585141004318656, -0.31345740373527137, -0.37528341324190717, -0.4304419550779229, -0.47825060153461657, -0.5182543279360033, -0.550241660936151, -0.5742541643778624, -0.5905889714992334, -0.5997942523929204, -0.6026576890385341, -0.6001882122988996, -0.5935914313818995, -0.5842393519510964, -0.5736351301063244, -0.5633737419977427, -0.5550995594898676, -0.5504619082062414, -0.5510697432269084, -0.558446608118521, -0.57398704400167, -0.5989155868873629, -0.6342494341681449, -0.6807657762765341, -0.7389746791625832, -0.8090982700732241, -0.8910568263934808, -0.9844621987838108, -1.0886188196713027, -1.2025323607774092, -1.3249259134330236, -1.4542633776589164, -1.5887795650487793, -1.726516350897708, -1.8653640570134358, -2.0031071120967785, -2.137472924874343, -2.2661828191439883, -2.3870038217572502, -2.4978000658326667, -2.59658257296628, -2.68155620993348, -2.7511626766654387, -2.804118471710257, -2.8394468968334623, -2.856503301110315, -2.8549929234727203, -2.834980867359886, -2.7968939276473654, -2.7415141838597634, -2.669964470088868, -2.5836860262530323, -2.4844088226053076, -2.37411522515319, -2.2549978295957063, -2.129412431602254, -1.9998272183208912, -1.8687693570457213, -1.7387702197638113, -1.6123105153025405, -1.4917666031987262, -1.3793592351503596, -1.2771059116794803, -1.1867779548544448, -1.1098632847125713, -1.0475357501579061, -1.0006317079292673, -0.969634369581645, -0.9546662505415049, -0.9554898617212189, -0.9715165876322105, -1.0018235002107065, -1.0451776694046282, -1.1000673545390238, -1.1647392988752434, -1.2372412075160988, -1.3154683693151377, -1.3972132895878988, -1.4802171344275283, -1.5622217508375686, -1.6410210205272138, -1.7145103291389354, -1.7807329862194199, -1.83792251299843, -1.8845398229091017, -1.9193044510315034, -1.9412191399601715, -1.9495872571898811, -1.944022698791177, -1.9244521214283714, -1.8911095349995435, -1.8445234766300178, -1.785497168762345, -1.7150822351615302, -1.6345467045811446, -1.5453381687865886, -1.44904307625977, -1.3473432324312309, -1.2419706395497048, -1.1346618428372026, -1.0271129536423536, -0.9209364948854725, -0.8176211599115393, -0.7184954943759918, -0.6246964041075082, -0.537143262772508, -0.4565182449170502, -0.3832533463654533, -0.3175243791729484, -0.25925204679841835, -0.20811002148208715, -0.16353976463000705, -0.12477165690144608, -0.09085184206389571, -0.06067404162710423, -0.03301546950080355, -0.006575870661041264, 0.019981372291020757, 0.047987173719554244, 0.07872485415393052, 0.11338955285648199, 0.15305003881565746, 0.19861395337325854, 0.2507974292589531, 0.3100999180144504, 0.3767849234898047, 0.45086718667483533, 0.5321067004377317, 0.6200097559915348, 0.7138370405649133, 0.8126186224295664, 0.9151754797758478, 1.0201470584869095, 1.126024184995624, 1.2311865181638229, 1.3339436021339313, 1.4325784835007314, 1.525392783485088, 1.6107520709660734, 1.6871303664515571, 1.7531526208236303, 1.8076340557290769, 1.8496153238077917, 1.8783925448655814, 1.8935413962360346, 1.8949345789623997, 1.8827521425513316, 1.8574843259425617, 1.819926756685873, 1.771168039558443, 1.7125699552982114, 1.6457406750631913, 1.5725015720447808, 1.4948483739730165, 1.4149075449863746, 1.334888908857407, 1.2570356247459178, 1.1835726989652364, 1.1166552598267365, 1.0583178363109578, 1.0104258646739026, 0.9746306004567161, 0.9523285377869869, 0.9446263351186545, 0.9523121191036475, 0.975833889184553, 1.0152855783432206, 1.0704011442844013, 1.140556874575297, 1.224781893542288, 1.3217766628133178, 1.4299390760677926, 1.547397566486054, 1.67205047702704, 1.8016107931218388, 1.9336552083351302, 2.0656763891751866], [2.1570835764860057, 2.2843808160843233, 2.405008913126143, 2.5166112463365935, 2.6169945899344143, 2.7041763233618226, 2.7764268181169807, 2.8323060256579096, 2.8706934292349673, 2.890810681394513, 2.892236423898755, 2.8749129736538097, 2.839144752370343, 2.7855885343649702, 2.7152357813540937, 2.6293875205630823, 2.529622398417245, 2.4177587022298015, 2.2958112827822172, 2.165944428118257, 2.030421830430631, 1.8915548514337972, 1.7516503256068414, 1.612959144403547, 1.4776268379561308, 1.3476473146836656, 1.2248208350209708, 1.1107171853632458, 1.0066448850649772, 0.9136271062930036, 0.8323848175486935, 0.7633274809639964, 0.7065514455425258, 0.6618459880300698, 0.6287067647819778, 0.6063562565060521, 0.5937706175771921, 0.5897121869314117, 0.5927667821448258, 0.6013847854925051, 0.6139249432978601, 0.6286997398238656, 0.6440211757333366, 0.6582457794448954, 0.6698177074840761, 0.6773088463892546, 0.6794549123781649, 0.6751866536341316, 0.6636553909314675, 0.6442522820351156, 0.6166208600622225, 0.5806625715936018, 0.5365352223159217, 0.4846444217516954, 0.4256282995459241, 0.36033593925528373, 0.28980013724982345, 0.21520524011157918, 0.1378509401258855, 0.059113011931466466, -0.01959794847898374, -0.09687867039885235, -0.17137510644601137, -0.24182295466230452, -0.30708571320082045, -0.36618924004124026, -0.4183518805206253, -0.4630093399647978, -0.4998336144619342, -0.5287454464060155, -0.5499199389730145, -0.5637851409426377, -0.5710135957604264, -0.5725070318303491, -0.5693745500976828, -0.5629048354829006, -0.554533076326001, -0.5458034166823652, -0.5383278864800841, -0.5337428511188076, -0.5336640925629274, -0.5396416765093275, -0.5531157736415983, -0.5753745868952094, -0.6075154913670383, -0.6504104200550076, -0.7046764287631394, -0.7706522496716341, -0.8483814982727871, -0.9376030361637002, -1.0377488165603284, -1.147949354692384, -1.2670467760289432, -1.3936152062669307, -1.5259880828916557, -1.6622917934818477, -1.8004848851481947, -1.9384019465967566, -2.0738011428952783, -2.20441428616583, -2.327998255603463, -2.442386539237615, -2.5455396588105845, -2.6355932584081434, -2.710902686656817, -2.770082980276254, -2.8120432617082467, -2.8360146929326118, -2.8415712783143006, -2.8286429777655853, -2.7975207735699734, -2.748853525478092, -2.683636644495203, -2.6031928113624727, -2.5091451563168783, -2.4033834976419937, -2.288024403370715, -2.1653659891888544, -2.0378384924753044, -1.9079517643915138, -1.7782408965001373, -1.6512112437200146, -1.529284120397223, -1.4147444305183166, -1.309691446992411, -1.2159938796062548, -1.1352502685499515, -1.0687556128281233, -1.0174749935286702, -0.9820247844664063, -0.9626618612404169, -0.9592810286717653, -0.9714206905828131, -0.9982765897186784, -1.0387232540717246, -1.091342603609472, -1.1544590028499144, -1.2261798939587576, -1.3044410157016444, -1.3870551087802927, -1.4717629303165614, -1.5562853513566373, -1.6383752923687678, -1.7158682631835434, -1.7867303153080079, -1.8491022849281868, -1.9013393023838625, -1.942044665974346, -1.9700973215541153, -1.9846723508954391, -1.9852540471912026, -1.9716413409696185, -1.9439455294932066, -1.90258045270601, -1.848245444270199, -1.7819015626136212, -1.7047417698469738, -1.618155871900901, -1.5236911577194467, -1.4230097757978228, -1.317843960345023, -1.209950265125882, -1.1010639795399968, -0.992854888406696, -0.8868854946656145, -0.78457275391851, -0.6871542732759156, -0.5956598068295971, -0.51088873933375, -0.43339409194132233, -0.363473413122903, -0.301166738530087, -0.24626162009969962, -0.19830504177255892, -0.15662186144447213, -0.12033925066576467, -0.08841644939995026, -0.05967901672916556, -0.03285664319020344, -0.006623499340311741, 0.020359969522763702, 0.0494049292021785, 0.08175285740824534, 0.11853617248006364, 0.16074185292572474, 0.20917903330914436, 0.26445145926429386, 0.32693555889358733, 0.39676474267707146, 0.4738203829490435, 0.5577297510588102, 0.6478710098950857, 0.7433851760837417, 0.8431947845096741, 0.9460288124712117, 1.0504532562016913, 1.1549066028749377, 1.2577393103670116, 1.3572562983266099, 1.4517613703126373, 1.5396024300692737, 1.6192163269310553, 1.6891721666719188, 1.748211954887356, 1.7952874995446007, 1.829592586247193, 1.8505895519453646, 1.858029517554331, 1.8519656939212927, 1.8327593450238042, 1.801078173008185, 1.7578870772166337, 1.7044314290562212, 1.6422131917176035, 1.5729603936942818, 1.4985906332914414, 1.4211694436338655, 1.3428644802576466, 1.265896602853245, 1.1924890063365414, 1.1248156120110915, 1.064949955690187, 1.01481580553766, 0.9761407080721679, 0.9504135970182509, 0.9388475079620381, 0.942348324257214, 0.9614903391422581, 0.9964992589592037, 1.04724309657987, 1.1132312169132192, 1.193621602239822, 1.2872362088251124, 1.3925840925891895, 1.5078917952869069, 1.6311403082304925, 1.7601077723347482, 1.892416935054735, 2.0255862700024103, 2.1570835764860075], [2.2471617656586265, 2.3712125667080097, 2.4870420580806663, 2.59238920428549, 2.685186120722605, 2.7636025023919117, 2.8260846271134916, 2.8713880368413887, 2.898603151832364, 2.9071732413828264, 2.8969043574471094, 2.867967029244015, 2.8208897132694846, 2.756544189178236, 2.676123283004089, 2.5811114805138735, 2.4732491607323404, 2.3544913287853997, 2.226961854586502, 2.0929043264748404, 1.9546307042565636, 1.8144690024266314, 1.6747112506007669, 1.537562964046955, 1.4050953131053026, 1.279201107391526, 1.1615556108677072, 1.0535830796685914, 0.9564297691231247, 0.8709439933573977, 0.7976636442820527, 0.7368113910548597, 0.6882975908843646, 0.6517307520208179, 0.6264352046680837, 0.6114754599144238, 0.6056865749449312, 0.6077096987354857, 0.6160318496582337, 0.6290288779352969, 0.6450104940333529, 0.6622662006007278, 0.6791109514042769, 0.6939293761850519, 0.705217454939718, 0.711620597642406, 0.7119671839474797, 0.7052967394085463, 0.6908820670815371, 0.6682448124144597, 0.6371641110157996, 0.5976781488790879, 0.5500786483628021, 0.4948984760353252, 0.4328927457758149, 0.3650139577999896, 0.29238186733774507, 0.2162489116719119, 0.13796213775721514, 0.058922661821573664, -0.019456245031484985, -0.09579131671978132, -0.16877056359473175, -0.23719254502575363, -0.30000258497578625, -0.35632495174691653, -0.40549012762449893, -0.4470564212429724, -0.48082532192392147, -0.5068501572952296, -0.5254377890918234, -0.537143262772507, -0.5427575098891733, -0.5432883833706738, -0.5399354804376423, -0.5340593713129042, -0.5271460000747092, -0.520767153135105, -0.5165379976044935, -0.5160727734735875, -0.5209397779791303, -0.5326168062732618, -0.5524482088584856, -0.5816046931866748, -0.6210469350942663, -0.6714939768182953, -0.7333972743546668, -0.8069211206571989, -0.8919300159726545, -0.9879833862821156, -1.0943378695780708, -1.209957202035587, -1.3335295466926493, -1.4634919207502386, -1.5980611986874476, -1.73527100153171, -1.873013632011946, -2.009086084741856, -2.1412390533317827, -2.267227775141371, -2.3848635013509085, -2.4920643565465253, -2.586904358753152, -2.6676594077354396, -2.7328491156017325, -2.781273447745253, -2.812043261708247, -2.824603973792934, -2.818751744738366, -2.7946417526258154, -2.752788309074225, -2.6940567691708464, -2.6196473817136536, -2.5310714194359236, -2.4301201142224, -2.31882709537872, -2.199425185546602, -2.074298545031936, -1.945931267794593, -1.816853618376496, -1.6895871565061076, -1.5665900235977512, -1.4502036621821415, -1.342602205530296, -1.2457457111842976, -1.1613383203333034, -1.0907923072090764, -1.03519884179659, -0.9953061285994756, -0.9715054078868299, -0.9638251180784423, -0.9719333232801357, -0.9951483132038681, -1.0324570885909703, -1.0825412585238285, -1.14380970119777, -1.2144371810691572, -1.2924079766346734, -1.375563457771075, -1.461652462337173, -1.5483832607282855, -1.633475865698734, -1.7147134437201235, -1.7899916133644191, -1.857364474890154, -1.9150863018399356, -1.96164793781777, -1.9958070768627976, -2.0166117605730007, -2.023416595483669, -2.0158913759199373, -1.994021986098272, -1.9581036459660004, -1.908726753417087, -1.846755756455414, -1.7733016581339454, -1.6896889105180921, -1.597417587747052, -1.4981218392353128, -1.3935257094817137, -1.285397468790803, -1.175503628108191, -1.0655638104994425, -0.9572076216717559, -0.8519346031951518, -0.7510782662840338, -0.6557750933832512, -0.5669392622147431, -0.4852436957749635, -0.4111078758836862, -0.3446926814877253, -0.285902330491452, -0.23439332003849445, -0.18959007955234072, -0.15070687801852917, -0.11677536631628474, -0.08667699093209086, -0.059179390749259556, -0.032975786941370586, -0.006726299858511377, 0.02089992190591183, 0.051182895124779186, 0.08531144397222183, 0.12434537821029366, 0.1691812292834616, 0.22052247383018025, 0.27885505793101234, 0.3444288982175607, 0.4172458812340103, 0.4970547140852635, 0.5833528016798888, 0.6753951432796197, 0.7722100582232688, 0.8726213722359847, 0.9752765261943593, 1.07867991290392, 1.1812306083416804, 1.281263545479341, 1.3770930842721518, 1.4670578631218807, 1.5495657768915483, 1.623137915456869, 1.686450315187425, 1.7383724232843047, 1.7780012504548663, 1.8046902891701395, 1.8180724002579076, 1.818076016767656, 1.8049341773120378, 1.7791860774187427, 1.741671012457459, 1.6935147748526214, 1.636108756854968, 1.5710821934282875, 1.5002681532370357, 1.4256640449553915, 1.3493875471607055, 1.2736289893683974, 1.2006013062860952, 1.1324887546951867, 1.0713956207569717, 1.0192961539509158, 0.9779869419847612, 0.9490428893179239, 0.9337778815965645, 0.9332111112038799, 0.9480399078401046, 0.9786197657199392, 1.0249520892916892, 1.0866799964554268, 1.1630923265327606, 1.2531358043861116, 1.3554351168771026, 1.468320468057232, 1.5898619997389372, 1.7179102987976689, 1.8501420657535423, 1.9841098944710565, 2.1172950132553647, 2.247161765658627], [2.3351488544517998, 2.4548978440495572, 2.564931222906877, 2.6631026828195252, 2.74748719579868, 2.8164222858572323, 2.8685433186137073, 2.9028119994921378, 2.9185374334890217, 2.9153892770668257, 2.893402701386167, 2.8529750812066212, 2.7948545206147677, 2.7201205204856085, 2.630157278537765, 2.526620286487863, 2.411397045936121, 2.2865628614246343, 2.154332782307023, 2.017010851941947, 1.8769378812130633, 1.736438992124245, 1.597772175594692, 1.4630790757049916, 1.3343391513876548, 1.2133282775007654, 1.1015827326397631, 1.0003693838229628, 0.9106627217765383, 0.833129228855805, 0.7681193789522995, 0.7156673795929023, 0.6754985755305934, 0.6470442451814817, 0.6294633409208192, 0.6216705559538661, 0.6223699483588375, 0.6300932206807949, 0.6432416443563546, 0.660130534906463, 0.6790351282384408, 0.6982366818438203, 0.7160676277335009, 0.7309546364450074, 0.7414585124824653, 0.746309929491718, 0.7444401260449188, 0.7350058172131452, 0.7174077297060669, 0.6913023353660988, 0.656606534978064, 0.6134952272034228, 0.5623918813442088, 0.503952412939985, 0.43904283335177763, 0.3687113041509471, 0.2941553702877448, 0.216685269062677, 0.13768431177155158, 0.058567409036420805, -0.01926114258748439, -0.09444947728615274, -0.1657384558105142, -0.2319993564943435, -0.29226794553010477, -0.3457740047015473, -0.3919655126390547, -0.43052681428030504, -0.46139026907818786, -0.48474103765740306, -0.5010148448005839, -0.510888739333749, -0.5152650540516566, -0.5152489466470662, -0.5121200711694329, -0.5072990845515098, -0.5023098302551008, -0.4987381575831922, -0.49818842769089566, -0.5022388234068886, -0.5123966179140471, -0.5300545660996993, -0.5564495616693246, -0.5926246533576853, -0.6393954359320666, -0.6973217280273722, -0.7666853217010786, -0.8474744410588883, -0.9393753830071531, -1.0417716361893565, -1.153750588841665, -1.2741177472535177, -1.401418198444916, -1.5339648682588392, -1.6698729538732027, -1.807099752074796, -1.9434889654708618, -2.076818451655083, -2.204850288167995, -2.3253819612608044, -2.436297450675485, -2.5356169768700787, -2.6215442015811155, -2.692509726814761, -2.7472098200484782, -2.7846394026539043, -2.804118471710258, -2.8053112792617596, -2.7882377639625218, -2.7532769138038224, -2.7011619307639463, -2.6329672640798023, -2.550087773633719, -2.454210473920226, -2.347279487584956, -2.231455001240849, -2.109067161155247, -1.9825659689110067, -1.8544683342694122, -1.7273035118135063, -1.6035581878202636, -1.4856224932107944, -1.3757381971181173, -1.2759502841027914, -1.1880630375867354, -1.1136016446239982, -1.053780205302223, -1.0094768770855134, -0.9812167139991488, -0.9691625768764746, -0.973114298416492, -0.9925160902289994, -1.026471983160138, -1.073768901761772, -1.1329067934214805, -1.2021350667822932, -1.2794944466685778, -1.3628632273549988, -1.450006805681205, -1.538629302619, -1.6264260381566868, -1.7111356107733782, -1.7905903495877906, -1.8627639539861074, -1.9258152109329818, -1.97812678231348, -2.0183381809544128, -2.0453722012505677, -2.0584542348860366, -2.057124079883672, -2.041240037711492, -2.01097528379199, -1.9668066867747722, -1.9094964366475267, -1.840067016618668, -1.7597702144067173, -1.6700510111763047, -1.572507307387721, -1.468846541338813, -1.3608403258541695, -1.2502782697693247, -1.1389221626330825, -1.0284616832096356, -0.9204727454446859, -0.8163795208313857, -0.7174210755299292, -0.6246234367591313, -0.538777759066585, -0.46042510076917037, -0.3898481482166188, -0.3270700449479333, -0.27186029885627466, -0.2237475578037886, -0.1820388673453811, -0.14584485778852274, -0.11411015592727894, -0.0856481832660697, -0.059179390749259535, -0.03337189274425693, -0.006883402476738426, 0.02159666119897243, 0.05330602909111218, 0.08937050659325003, 0.13076802153799827, 0.17829676694602034, 0.23254830429659207, 0.29388636429668435, 0.362431934419862, 0.43805505946060713, 0.5203736071284284, 0.6087590696981503, 0.702349289521891, 0.8000678154371843, 0.900649423360648, 1.002671172052449, 1.1045882183051878, 1.2047734883978547, 1.3015601978269231, 1.3932861317852097, 1.4783385466775538, 1.5551985295293294, 1.6224836581300468, 1.6789878400932863, 1.7237172729042778, 1.75592155794929, 1.7751191172783214, 1.7811161996206653, 1.774018918571829, 1.7542379370471535, 1.7224855938222656, 1.67976545575069, 1.6273544684006347, 1.566778063677867, 1.4997787608629347, 1.4282789629393353, 1.3543387989736115, 1.2801099918793775, 1.2077868359009674, 1.139555446911375, 1.0775424991011635, 1.0237646825017082, 0.9800801064302185, 0.9481428345031703, 0.929361668219735, 0.9248641998718712, 0.9354670339795843, 0.9616529324947434, 1.0035554761366898, 1.0609516563623445, 1.133262623951542, 1.2195626255932346, 1.3185959639335245, 1.4288016240757813, 1.5483450252098854, 1.6751561844022784, 1.8069734248035163, 1.9413916264201163, 2.075913907442604, 2.2080055406273953, 2.3351488544518], [2.4203004322797246, 2.5347286327946383, 2.6380174300250983, 2.7281534139120867, 2.803370719875938, 2.8621887944884437, 2.903443672874759, 2.9263120526666264, 2.93032762116176, 2.915389277066826, 2.8817610813107217, 2.8300639682059585, 2.761259443917109, 2.676625689006126, 2.5777266611527607, 2.466374958644056, 2.3445893509081634, 2.2145480057193576, 2.078538540760292, 1.9389060976563126, 1.7980006777394806, 1.6581249897227788, 1.5214840399784972, 1.3901376467773723, 1.2659569819488456, 1.150586138960054, 1.0454095980249827, 0.9515263097726847, 0.8697309529555953, 0.8005027428072853, 0.7440019794130563, 0.7000743344828669, 0.6682626849427259, 0.6478261174805908, 0.6377655541372383, 0.6368552894985521, 0.6436795889305168, 0.6566733780430225, 0.6741659590634702, 0.6944266223143671, 0.7157109821114269, 0.7363068570049982, 0.754578534516177, 0.7690083097688418, 0.7782342643662418, 0.7810833544926445, 0.7765990028861638, 0.7640625348061901, 0.7430079596962543, 0.7132297738122145, 0.6747836402444977, 0.6279799869266732, 0.5733707457373178, 0.511729632062508, 0.44402652974997353, 0.37139669708495887, 0.2951056414623462, 0.21651062050289466, 0.13701981270245123, 0.05805025917532399, -0.019014291801943067, -0.09286450466676435, -0.1623044360972575, -0.22628732579299443, -0.28394723341345063, -0.33462566469149435, -0.3778924599270274, -0.41356036703143245, -0.4416928852662697, -0.46260514064916186, -0.4768577352595079, -0.485243695774963, -0.4887688268647408, -0.4886259479821979, -0.48616365324207994, -0.4828503793338871, -0.48023469210234426, -0.4799028052972302, -0.48343442240403456, -0.4923580423962082, -0.5081068913676524, -0.5319766336999349, -0.5650859788187029, -0.6083412335586053, -0.6624057572605595, -0.727675159219819, -0.8042589388588122, -0.8919691114355172, -0.990316190101899, -1.0985127129517476, -1.2154843158615816, -1.339888163100654, -1.4701383625719537, -1.6044378157674395, -1.7408157885048599, -1.8771703413786307, -2.0113146323134283, -2.141026000863109, -2.2640966675727907, -2.378384833794492, -2.481864949091779, -2.572675925332552, -2.649166118549442, -2.7099339707017993, -2.7538633019391434, -2.7801523675005684, -2.788335939023671, -2.7782998342648653, -2.7502874980718652, -2.7048984265538434, -2.643078421160844, -2.566101855061348, -2.4755463260158375, -2.373260253194416, -2.2613241455917104, -2.142006422681108, -2.017714799970473, -1.8909443599295144, -1.7642235097048342, -1.6400590791259526, -1.5208818344462365, -1.4089936745044433, -1.306517736735596, -1.2153525716514189, -1.1371314477200654, -1.0731877263559322, -1.024527101959689, -0.9918073381556689, -0.9753259525507421, -0.9750161128458307, -0.9904508115855033, -1.0208551899961615, -1.0651266880296704, -1.1218625125978503, -1.1893937435487822, -1.265825241377667, -1.3490803857424583, -1.436949562817277, -1.5271412350227187, -1.6173343707245724, -1.7052309853899645, -1.7886075499958025, -1.8653640570134389, -1.9335695981170906, -1.9915033992352604, -2.0376903753578732, -2.0709304066842273, -2.0903206957568634, -2.0952707382265983, -2.085509623524614, -2.061085571416709, -2.0223578014808306, -1.9699810202561094, -1.9048829905289137, -1.8282358145256679, -1.741421713568917, -1.6459942173362943, -1.543635783066778, -1.4361129462973745, -1.3252301580509838, -1.212783487595929, -1.1005153644517782, -0.9900714984563505, -0.8829610534010867, -0.7805210596599705, -0.6838859367200271, -0.5939628605148816, -0.5114135564449803, -0.43664293086066186, -0.36979477585631915, -0.3107545989829868, -0.25915944556627984, -0.2144144013613495, -0.17571529182391335, -0.14207693564568763, -0.11236616838465968, -0.08533873058028199, -0.059679016729165514, -0.03404160936453013, -0.00709347803575295, 0.02244429267224809, 0.055756368427093306, 0.0938957037648092, 0.13774976399434602, 0.1880113443399478, 0.24515478074088395, 0.3094182067077131, 0.3807923536677536, 0.45901622229280525, 0.5435797736914734, 0.633733606589693, 0.7285054043478, 0.8267227584936807, 0.9270418078883133, 1.0279809789453038, 1.1279589764181588, 1.2253360596249112, 1.3184575485465575, 1.4056984403563855, 1.4855079812922083, 1.5564530323464525, 1.6172590902636288, 1.666847877305608, 1.7043704929510208, 1.7292352262176436, 1.741129256067051, 1.7400336162138998, 1.7262309659536519, 1.7003058862595906, 1.6631376059828609, 1.615885251910201, 1.5599659039911373, 1.4970259185616928, 1.4289061533262197, 1.357601883926579, 1.2852183392021495, 1.2139228972560132, 1.145895074267605, 1.0832755003229604, 1.0281151097402612, 0.9823257765361859, 0.9476335986355838, 0.9255359777467944, 0.9172635568139458, 0.9237479656250493, 0.9455961901616523, 0.9830722258725887, 1.0360865029988464, 1.104193387543762, 1.1865968689607196, 1.2821643498114883, 1.389448258311229, 1.5067150165715244, 1.6319807200821128, 1.76305272187862, 1.8975761719005015, 2.033084441760334, 2.167052270477849, 2.2969504000099517, 2.420300432279725], [2.501896078262448, 2.610029528346626, 2.705682337051223, 2.7869910389423413, 2.852363893053102, 2.900514822912944, 2.9304904171070087, 2.9416893752811033, 2.933873964527746, 2.9071732413828264, 2.8620779905945035, 2.799427528625409, 2.720388712727318, 2.6264276806957403, 2.519275017597278, 2.4008851997173344, 2.273391298979231, 2.1390560399359315, 2.000220383527081, 1.8592508651819988, 1.718486938296695, 1.5801895671200399, 1.4464922759002705, 1.3193557947591978, 1.200527348885612, 1.0915055186525875, 0.99351145716084, 0.9074670920259656, 0.8339807639463577, 0.7733405700474622, 0.7255154897776726, 0.6901641799423176, 0.6666511380294127, 0.6540697539246931, 0.6512716038367361, 0.6569011908315234, 0.6694352074580104, 0.6872252906632259, 0.7085431600837464, 0.7316269797403816, 0.7547277613325324, 0.7761546351754471, 0.7943178520545398, 0.807768444860752, 0.8152335710888927, 0.8156466737345233, 0.8081717358210803, 0.7922210592085295, 0.767466167522146, 0.7338416117012736, 0.6915416402793126, 0.6410098804271522, 0.5829223553813709, 0.5181643346098859, 0.4478016706437254, 0.373047416962649, 0.2952246411374097, 0.21572644359841, 0.13597426251272796, 0.05737558756012109, -0.018717781144207944, -0.09104980844718445, -0.15849755781564748, -0.2201047792861632, -0.2751108456154959, -0.3229742517179242, -0.3633900338824898, -0.39630062331748495, -0.4218998192683837, -0.4406297459758035, -0.4531708405465291, -0.46042510076916987, -0.463492998400106, -0.4636446299918181, -0.462285829696662, -0.460920102769342, -0.46110735127432606, -0.4644204518806522, -0.47240080730490064, -0.48651402632000124, -0.5081068913676523, -0.538366747512325, -0.5782843923095137, -0.6286214644091013, -0.6898832213490175, -0.7622974666326631, -0.8458002360244572, -0.9400286867416313, -1.0443214549778927, -1.1577265613842485, -1.2790167553724014, -1.406712002097477, -1.5391086353890184, -1.6743145302507445, -1.8102894940994363, -1.9448899405504003, -2.075916796706692, -2.201165507445387, -2.3184769403671113, -2.4257879644567235, -2.5211804749436597, -2.6029276664605883, -2.6695364157415193, -2.7197847224087095, -2.752753269806197, -2.7678503046330487, -2.7648291910166916, -2.7437981678497447, -2.705222023488522, -2.649915594769529, -2.5790291930392484, -2.4940262537327205, -2.3966536932372455, -2.288905632756225, -2.172981309331162, -2.0512381351500557, -1.9261409843053188, -1.8002088783586931, -1.6759603061529247, -1.5558584476929276, -1.4422575757450466, -1.3373518819598893, -1.2431279174520296, -1.1613217522442938, -1.093381845881367, -1.0404384855651596, -1.0032804916729323, -0.9823397173019611, -0.9776836827617084, -0.9890164922318416, -1.0156879828392051, -1.0567108609740021, -1.110785391517816, -1.1763310273889254, -1.2515242037470198, -1.3343413772866823, -1.4226062697582378, -1.5140401790990485, -1.6063141536196595, -1.697101786163267, -1.7841313769148799, -1.8652362357037329, -1.9384019465967597, -2.001809497968102, -2.053873287999708, -2.0932731460231264, -2.118979660979285, -2.130272275778735, -2.126749786316767, -2.108333071862689, -2.075260074840236, -2.0280732379144975, -1.967599790112357, -1.8949254469030192, -1.8113622474998015, -1.7184113922404236, -1.6177220603597697, -1.5110472809444913, -1.4001979951371686, -1.2869964842055561, -1.1732303450943844, -1.060608172456166, -0.9507180545743564, -0.8449899114298816, -0.7446625984885555, -0.6507565723034828, -0.5640527669995969, -0.48507816788655084, -0.41409839396841874, -0.35111741940720986, -0.2958843796485728, -0.24790722558750258, -0.20647281343798168, -0.1706728532982997, -0.13943498991635644, -0.1115581586122009, -0.08575125098447846, -0.060674041627104144, -0.03497927069653245, -0.007354749201265406, 0.02343564497991729, 0.058513182153148956, 0.0988487502711529, 0.14523153687888182, 0.19824277174459495, 0.2582352466678416, 0.32531917874906235, 0.39935481850621396, 0.4799520288080098, 0.5664768791043651, 0.6580651164713076, 0.7536421951901425, 0.8519493745130003, 0.9515752343031859, 1.0509918144537922, 1.1485944600538078, 1.2427443533655995, 1.3318126384050175, 1.4142249962385334, 1.4885055103047975, 1.5533186716814147, 1.6075084140659088, 1.6501331364029697, 1.6804957659374562, 1.69816803370208, 1.7030082751427635, 1.695172227283314, 1.67511646661657, 1.6435943145035432, 1.6016442247329203, 1.550570856366604, 1.4919192193727067, 1.4274424562173347, 1.3590639851481237, 1.288834876268958, 1.2188874560080363, 1.1513862360611278, 1.0884773367780702, 1.0322376203359556, 0.9846247646926217, 0.9474294947561922, 0.922231142705167, 0.9103576359535115, 0.9128509105975066, 0.9304386227029282, 0.9635128825052882, 1.0121165710593227, 1.0759376190986978, 1.1543114382230397, 1.2462314996361612, 1.3503678602730311, 1.4650932450477616, 1.5885161118076054, 1.7185199568497118, 1.8528079676872757, 1.9889519998499725, 2.1244447490649456, 2.2567539117849322, 2.38337707764465, 2.5018960782624484], [2.5792454563125053, 2.680163451055105, 2.767353468253092, 2.839117764978203, 2.8940522109154303, 2.931076115587536, 2.94945472361546, 2.948813868227932, 2.9291464599173653, 2.8908106813945134, 2.834519957091673, 2.7613249606069723, 2.672588111925476, 2.5699511934196146, 2.455296875225466, 2.3307050827026705, 2.1984052578861277, 2.0607256602653865, 1.9200409176569533, 1.778719073830141, 1.6390693851007694, 1.5032920932574276, 1.3734313476182736, 1.2513323661476954, 1.1386038165009156, 1.036586265360453, 0.9463273918032225, 0.8685644915019661, 0.8037146175249886, 0.7518725148489072, 0.7128163141136958, 0.6860207603630636, 0.6706775692067741, 0.665722330524194, 0.6698672227272979, 0.6816386625566292, 0.6994188997540255, 0.7214904755357399, 0.7460824007406902, 0.7714168753273289, 0.7957553662942529, 0.8174428861205197, 0.8349493677399686, 0.8469071134386994, 0.8521434017731676, 0.8497074658964876, 0.8388912052422142, 0.8192431565618418, 0.7905754256780698, 0.7529634635577716, 0.7067387548191328, 0.6524746689097515, 0.5909658993366264, 0.5232020800868318, 0.4503363166328015, 0.37364949794689284, 0.29451136252183624, 0.2143393728406791, 0.13455650703010366, 0.0565491022179691, -0.018374119228616065, -0.08902074177859011, -0.15435002887857865, -0.2135040241149318, -0.2658335419755225, -0.31091834200691776, -0.3485809315922013, -0.3788936083804056, -0.40217852937933646, -0.4190007754202441, -0.43015456250936246, -0.43664293086066136, -0.439651413604006, -0.4405163459303004, -0.44068861772521145, -0.4416937949211742, -0.4450896337296716, -0.45242208504920733, -0.46518093177000036, -0.48475621819871956, -0.5123966179140467, -0.5491708442824573, -0.5959331375912739, -0.653293765979269, -0.7215953564175573, -0.8008957298784193, -0.8909577550263411, -0.9912465612229352, -1.1009342686566221, -1.2189122055345483, -1.3438103941871062, -1.4740239043279413, -1.607745497178674, -1.7430038230846518, -1.877706291670391, -2.0096856111376438, -2.136748895107074, -2.2567281639627934, -2.367531024835763, -2.4671903013119363, -2.5539114010919426, -2.6261162568351746, -2.6824827512254386, -2.7219786401185355, -2.7438891150237805, -2.7478372950699526, -2.7337971054143844, -2.7020981797264505, -2.653422614519828, -2.5887935980877894, -2.5095561318516744, -2.417350252295743, -2.3140773426705743, -2.2018602908654623, -2.0829983991736643, -1.959918079433323, -1.8351204700779349, -1.7111271874309057, -1.5904254702552878, -1.4754139929575756, -1.3683506085231896, -1.2713032375603408, -1.1861050458227775, -1.1143149510628256, -1.057184373499116, -1.0156309956479705, -0.9902201303791799, -0.9811541148809596, -0.9882699571675779, -1.0110452654896585, -1.048612294288841, -1.0997797479611735, -1.1630618003322657, -1.2367136178525804, -1.3187725222085624, -1.4071037969956437, -1.4994500364663004, -1.5934828547026676, -1.6868557227545429, -1.7772566805053052, -1.8624596797162982, -1.940373354541205, -2.009086084741856, -2.0669063131074954, -2.1123971997446813, -2.144404838917921, -2.1620794254057154, -2.1648889328709022, -2.1526250521652686, -2.1254013281972277, -2.083643625269074, -2.028073237914497, -1.9596831426280505, -1.8797080510947586, -1.7895890735534838, -1.6909339281519657, -1.58547373548805, -1.4750175144952817, -1.3614055445967113, -1.246462778499554, -1.131953479748256, -1.0195382195487395, -0.9107342995065321, -0.8068805725742846, -0.7091075161247895, -0.6183132716944688, -0.5351462091388888, -0.4599944026954002, -0.39298222707606845, -0.33397409775645054, -0.28258519572911134, -0.2381988377926509, -0.19998998346112637, -0.16695421308019623, -0.1379413726568934, -0.11169296273820623, -0.08688225436937197, -0.06215604708218497, -0.03617694370109855, -0.0076650055009890115, 0.024562330832865114, 0.061553146377684276, 0.10418774109755835, 0.15315004100746152, 0.20890448665434475, 0.27167903541674454, 0.3414547510019904, 0.4179622820830985, 0.5006853526095417, 0.588871203494252, 0.6815477437592617, 0.7775469934238645, 0.8755342349084464, 0.974042138716294, 1.0715089964969904, 1.1663200836829146, 1.25685108757753, 1.3415124772988538, 1.4187936609105798, 1.4873057732634778, 1.5458219656437573, 1.5933141246697504, 1.6289850316569132, 1.6522950828575562, 1.6629828229093455, 1.6610786952540189, 1.6469115804792707, 1.621107872354549, 1.5845830273383468, 1.5385257119038913, 1.4843748584612995, 1.4237901202886911, 1.3586163842231014, 1.2908431526753747, 1.2225597399686816, 1.1559073386781613, 1.0930290967465923, 1.0360194034733472, 0.9868736105099555, 0.947439411956954, 0.9193710754963333, 0.9040876549108814, 0.9027362247631708, 0.9161610625541543, 0.9448795651190729, 0.9890655276858695, 1.04854023975195, 1.1227716659612033, 1.2108817870127553, 1.3116619800173743, 1.4235961244169189, 1.5448909333255845, 1.6735128355029099, 1.8072305744101773, 1.9436625518339916, 2.0803278277994437, 2.2146995987931426, 2.3442599148879415, 2.466554364730183, 2.579245456312506], [2.6516941556906004, 2.7445370361980004, 2.822509057954231, 2.884092576329796, 2.9280829714296273, 2.953614110147051, 2.960176145785604, 2.9476252550729125, 2.9161851041588425, 2.86644003176353, 2.7993201342358156, 2.7160786291176913, 2.6182620562243852, 2.507674043816007, 2.386333518072231, 2.2564283631468744, 2.120265643468073, 1.9802195771646378, 1.8386784977127912, 1.6979920589966275, 1.560419926588594, 1.4280831555603237, 1.3029193836462198, 1.1866428699298706, 1.080710285899449, 0.986293020817747, 0.9042566004960886, 0.8351476418047469, 0.7791885789858002, 0.736280206673006, 0.7060118931936857, 0.6876791309496644, 0.6803079130450684, 0.6826852612082105, 0.6933950834584954, 0.7108584144692414, 0.7333769902139619, 0.75917903369137, 0.7864660820716441, 0.8134596685534101, 0.8384466848934091, 0.8598222925540744, 0.8761293205637941, 0.8860931846560649, 0.8886514825495883, 0.8829775612641628, 0.8684975105375441, 0.8449002076948793, 0.812140219382968, 0.7704335498622659, 0.7202464093981789, 0.6622773550760324, 0.5974333255814779, 0.5268002468870048, 0.4516090234651937, 0.3731978461601191, 0.2929718402754758, 0.21236114347596902, 0.13277854110750303, 0.05557779558885152, -0.017986213590482126, -0.08679447148316075, -0.14989693925763684, -0.20654090565492464, -0.25619381268035224, -0.2985599340099914, -0.33359044476273303, -0.3614865934433263, -0.3826958666355747, -0.39790121986060484, -0.4080036292751864, -0.4140983939684183, -0.41744578307225577, -0.4194367715464736, -0.42155473951385686, -0.42533411905378254, -0.43231705660690845, -0.4440092164156126, -0.4618358792133898, -0.48709948988448676, -0.5209397779791296, -0.5642975164627472, -0.6178828982927519, -0.6821493994334811, -0.7572738634535948, -0.843143390184115, -0.9393494428196977, -1.0451894084849644, -1.159675661116775, -1.2815519871663155, -1.4093170488018678, -1.541254380640194, -1.6754682490316453, -1.809924551769527, -1.942495804603826, -2.0710091524468175, -2.1932962604352686, -2.307243885198803, -2.4108439012269147, -2.5022415618555636, -2.5797808090905, -2.642045510488786, -2.687895593144722, -2.7164971622946927, -2.7273458323524276, -2.720282657928173, -2.6955022277031233, -2.6535526706639656, -2.5953275176051567, -2.5220495562585707, -2.4352470111326885, -2.3367225644188574, -2.2285159076078416, -2.11286067050299, -1.9921367112568804, -1.8688188645250705, -1.745423332025938, -1.6244529585613265, -1.5083426654285719, -1.3994063114084878, -1.2997862191666458, -1.2114065427247698, -1.135931561144967, -1.0747298669158296, -1.028845277569209, -0.9989751391945823, -0.9854565146448576, -0.9882605616256368, -1.0069952110965337, -1.040916059229386, -1.0889451913611257, -1.1496974686848698, -1.2215136323991045, -1.3024994199500592, -1.3905697477290142, -1.4834968975084428, -1.578961552828095, -1.6746054686443068, -1.768084524307012, -1.8571209070740506, -1.939553200908557, -2.0133832124829194, -2.0768184516550834, -2.128309295022546, -2.166579995694445, -2.1906528567830126, -2.199865056453604, -2.193877794450149, -2.1726776193143333, -2.136569987356166, -2.086165294072996, -2.0223578014808306, -1.946298056223231, -1.8593595491586197, -1.7631005035907739, -1.6592217930834259, -1.549522078142083, -1.4358513118469645, -1.3200637963613588, -1.2039719744249604, -1.089302112516366, -0.9776529761154608, -0.8704585139136063, -0.7689554590856864, -0.6741566246543281, -0.5868305198968979, -0.507487749492625, -0.4363744808755787, -0.37347308251069505, -0.31850985116264824, -0.2709695643385106, -0.23011641953556491, -0.19502075910590175, -0.164590832548552, -0.13760872054518308, -0.11276944025877009, -0.08872217193454146, -0.06411249465764286, -0.037624495522656606, -0.008021622026235527, 0.025814817958944455, 0.06485054162776017, 0.10986750596571328, 0.16143828225199344, 0.21990628613657973, 0.2853724064513934, 0.35768840922380785, 0.43645731683657346, 0.5210407803961039, 0.6105732807432482, 0.7039828148006892, 0.8000175536388644, 0.897277801088802, 0.9942524409499128, 1.0893589404306823, 1.180985880508641, 1.2675369129059004, 1.3474750002017968, 1.419365781402055, 1.4819189204865062, 1.534026339758857, 1.5747963121864346, 1.603582485603218, 1.6200070342511312, 1.6239772766442357, 1.6156952596200274, 1.5956599827119233, 1.5646621203142135, 1.5237712869563305, 1.4743160786757594, 1.417857306290597, 1.35615500974611, 1.2911300022922165, 1.2248208350209713, 1.1593371926686913, 1.0968108275039639, 1.0393452071179141, 0.988965092206679, 0.9475672708955358, 0.9168736564439656, 0.8983879056801274, 0.8933566373694886, 0.9027362247631704, 0.9271660073004748, 0.966948615966041, 1.022037938762464, 1.0920350712314328, 1.1761924063572582, 1.2734258231637725, 1.3823347386327034, 1.501229597992326, 1.6281661985930007, 1.7609860769135188, 1.8973620407969352, 2.034847803424719, 2.170930574896429, 2.30308539407544, 2.428829939403707, 2.5457785437796554, 2.651694155690601], [2.718629227616585, 2.802605654115625, 2.870682464907581, 2.9215349657417526, 2.9541682589626497, 2.9679381249589563, 2.9625639755343838, 2.9381335920211904, 2.8950995561869735, 2.8342674792135987, 2.756776328456394, 2.6640713385961647, 2.5578701686380962, 2.4401231247512962, 2.312968407345364, 2.178683455707987, 2.0396335522216202, 1.8982189085261336, 1.756821486584237, 1.617752807756341, 1.4832039727684667, 1.3551990556740772, 1.2355529471063402, 1.125834608516057, 1.0273365625472222, 0.9410512886312539, 0.867655021171146, 0.8074992646040428, 0.7606101497129928, 0.7266955635025262, 0.7051597954976613, 0.6951252611365356, 0.6954606924776435, 0.7048150319073423, 0.7216561296820654, 0.7443132342460914, 0.7710221780263187, 0.7999721028738533, 0.829352539858725, 0.8573996583633519, 0.8824405292566104, 0.9029343055207827, 0.9175093094909854, 0.9249951266184508, 0.9244489385346922, 0.9151754797758498, 0.8967401689672664, 0.8689751423451088, 0.8319781007239166, 0.7861040657793162, 0.7319503231464282, 0.6703350037652619, 0.6022699167633501, 0.5289283928910865, 0.4516090234651937, 0.37169628278081857, 0.2906190994531743, 0.2098084922198642, 0.13065540714117002, 0.054469885366371935, -0.017557346087034038, -0.0843898328149945, -0.14517596410606115, -0.1992743350391602, -0.24627321420184958, -0.28600358545104265, -0.31854539969593487, -0.3442268497293787, -0.36361666317991576, -0.3775095910845765, -0.38690544776257374, -0.3929822270760673, -0.3970639764873165, -0.40058424957824074, -0.40504607633044487, -0.411979485427843, -0.4228976816881524, -0.4392530226553747, -0.4623939502933518, -0.4935240162384985, -0.5336640925629266, -0.5836187855616517, -0.6439479695060343, -0.7149442330553918, -0.7966168861428963, -0.8886830132262817, -0.9905658838283065, -1.1014008476304675, -1.220048653597355, -1.3451159453821238, -1.474982503276546, -1.607834630782496, -1.7417039258223617, -1.8745105366587205, -2.004109884302737, -2.1283417395692275, -2.245080476392626, -2.3522852852931333, -2.448049123006997, -2.5306451965625305, -2.598569832041624, -2.6505806587274425, -2.685729146407393, -2.7033866647199685, -2.703263385449459, -2.685419517906543, -2.650268549876976, -2.598572357636051, -2.531428243552738, -2.4502481540777716, -2.356730519668832, -2.2528253368259477, -2.1406932765066666, -2.022659748729862, -1.9011649765759664, -1.7787112310062865, -1.6578084485256623, -1.5409194949467275, -1.4304063493445043, -1.3284784624254358, -1.2371444934351123, -1.158168550595049, -1.0930319538027327, -1.042901407527643, -1.0086043196668004, -0.9906118322874508, -0.9890299468146385, -1.0035989337808298, -1.0337010204270634, -1.078376153019298, -1.1363454394959862, -1.2060416966397427, -1.2856463587692941, -1.3731318560272023, -1.4663084432918603, -1.5628743586264722, -1.6604681154358292, -1.7567216869016185, -1.8493133258594812, -1.9360187783737592, -2.0147596944171546, -2.0836481130933544, -2.1410260008631097, -2.185498946701087, -2.2159632648772702, -2.2316259204597944, -2.2320168705860945, -2.2169936016299054, -2.1867378339719896, -2.1417445574291434, -2.082803746792851, -2.01097528379199, -1.927557774785703, -1.8340520986287834, -1.7321206428997695, -1.623543286047388, -1.5101712556113263, -1.3938800367968531, -1.2765225203285369, -1.1598835634115534, -1.0456370932654586, -0.9353068102690627, -0.8302314491666963, -0.7315354345855103, -0.64010562443447, -0.5565746752370856, -0.48131139114500804, -0.4144182376538185, -0.3557360164633093, -0.30485551414963785, -0.26113575897446806, -0.22372835173203545, -0.19160718225895274, -0.16360270697210666, -0.13843984796861739, -0.11477848368695691, -0.0912554371448134, -0.06652683192168699, -0.03930967921777155, -0.008421581639830547, 0.027182509750311796, 0.06837747044747265, 0.11583999149471037, 0.17002613834107685, 0.23115508998930956, 0.2991995076565138, 0.37388280932014395, 0.4546834464035258, 0.5408460960376862, 0.6313995014575263, 0.7251805187425945, 0.8208637647276785, 0.9169961126451054, 1.0120351527018796, 1.1043906276519968, 1.1924677712534926, 1.2747114224330411, 1.3496497614720158, 1.4159365173147138, 1.472390527185954, 1.5180315903592811, 1.5521116456889756, 1.5741404152762812, 1.5839047916199005, 1.5814813994783656, 1.5672419326424911, 1.5418510456899963, 1.506256767099819, 1.4616735881987528, 1.4095585676008262, 1.351580968445396, 1.2895861113853904, 1.2255542757537523, 1.1615556108677092, 1.0997021257276738, 1.0420979057114532, 0.9907887571735894, 0.9477125037437008, 0.9146511509121567, 0.8931860982764586, 0.8846575124192116, 0.8901288793452294, 0.9103576359535106, 0.9457726380241196, 0.9964590610873083, 1.062151154217178, 1.1422330795418185, 1.2357478766499517, 1.3414143958287545, 1.4576518519644748, 1.5826114666832576, 1.714214494423361, 1.8501957728350058, 1.9881518030194003, 2.1255922539692027, 2.2599937009022764, 2.38885435108872, 2.509748484656453, 2.6203793423889583, 2.7186292276165847], [2.7794843710934973, 2.853878018024044, 2.9114661202915983, 2.951128153656772, 2.9720873801782397, 2.973926972376252, 2.9565980107416183, 2.9204191828372092, 2.866068209278921, 2.79456521809754, 2.7072484796015934, 2.6057430942537736, 2.4919233918632337, 2.367869947567909, 2.2358222450797047, 2.0981281174829127, 1.9571911681251564, 1.815417417112286, 1.6751624316261622, 1.5386801804834493, 1.4080748055503272, 1.2852564260641606, 1.171901988535422, 1.0694220473138683, 0.9789342122956798, 0.9012438343273886, 0.8368323197518899, 0.7858532776820066, 0.7481365116250501, 0.723199675755791, 0.7102672301577093, 0.7082961532928841, 0.7160077081337892, 0.7319244147476391, 0.7544112601586851, 0.7817200789733866, 0.8120359678675588, 0.8435245552588292, 0.8743789352627078, 0.9028650925602898, 0.9273646915531024, 0.9464141778825381, 0.9587392410905601, 0.9632838112935236, 0.9592329070523097, 0.946028812471213, 0.923380234861115, 0.8912642756713569, 0.8499212322480276, 0.7998424316532751, 0.7417514756574896, 0.6765794436234018, 0.6054347531322618, 0.5295685130208854, 0.4503363166328015, 0.36915751171464534, 0.287473045306916, 0.2067030156570791, 0.1282050678051889, 0.05323474497234763, -0.017091145131415755, -0.08182717010533555, -0.14022704500989983, -0.19176579074320912, -0.2361556792922646, -0.27335552872069263, -0.3035730842810326, -0.32726040248050614, -0.34510233770703336, -0.35799841149892425, -0.36703851813415717, -0.37347308251069467, -0.3786784331557694, -0.3841182808923167, -0.39130229893576246, -0.40174288028687166, -0.4169112011475318, -0.4381937433199073, -0.4668504234760193, -0.5039754428606685, -0.5504619082062405, -0.6069711848996207, -0.673907828934074, -0.7514008077127282, -0.8392915647105894, -0.9371293131870626, -1.0441737637855308, -1.1594053044483008, -1.2815424632628856, -1.4090663003324406, -1.5402511981523277, -1.6732013557107366, -1.8058921437531879, -1.9362153510945788, -2.0620272477721757, -2.181198312874526, -2.2916634250795167, -2.3914712936195213, -2.4788319171641957, -2.5521608978304244, -2.610119506309016, -2.651649490334846, -2.676001740133179, -2.682758068136412, -2.6718455227131064, -2.6435428329454025, -2.598478769318824, -2.5376223989698037, -2.462265409135808, -2.3739968638983475, -2.274670942507009, -2.166368378026379, -2.051352468566369, -1.9320206661606618, -1.8108528571715121, -1.6903575302307094, -1.5730170811377173, -1.4612335274886117, -1.3572758985037408, -1.263230527706041, -1.1809554086739813, -1.112039678675062, -1.0577691738864836, -1.0190988560672352, -0.9966327474548827, -0.9906118322874505, -1.00091019403537, -1.0270394617774121, -1.0681614419277106, -1.123108617515046, -1.1904120111453385, -1.26833573416124, -1.3549173875573453, -1.448013343713255, -1.5453478252604793, -1.6445646111099532, -1.7432801418877013, -1.8391367691101335, -1.9298548949943648, -2.0132827827115327, -2.087442879275682, -2.1505735835181077, -2.2011655074453875, -2.2379914178113047, -2.2601292024896855, -2.2669773792890395, -2.25826284890676, -2.2340407842214085, -2.1946867403599146, -2.1408812592118225, -2.0735874236397476, -1.9940219860982715, -1.9036208495765041, -1.8039998119884875, -1.6969115951204672, -1.5842002633580865, -1.4677541936608403, -1.34945878532409, -1.231150095396135, -1.1145705533667454, -1.001327847817048, -0.8928579897344694, -0.7903934444365154, -0.694937089413782, -0.6072426023353291, -0.5278017158517796, -0.4568385979325987, -0.39431143278308917, -0.3399210925387882, -0.2931266085872075, -0.25316697808021127, -0.21908868032631407, -0.18977813332506557, -0.16399819634036888, -0.14042772321310454, -0.11770309560626149, -0.09446061743019331, -0.06937863248856307, -0.0412182373698284, -0.008861500502459272, 0.028653834915524572, 0.07210409342305346, 0.12205466775439312, 0.17884095212614892, 0.24255572824179705, 0.31304335549907586, 0.389900939338134, 0.4724864694804014, 0.5599337376019529, 0.6511736663858686, 0.7449615134175583, 0.8399092583114778, 0.9345223437389527, 1.027239824184004, 1.116476883285126, 1.2006686139261527, 1.27831391656185, 1.3480183616450736, 1.4085348817744943, 1.4588012078807917, 1.4979730402626574, 1.525452047720871, 1.5409079139137567, 1.5442937962729748, 1.5358547257621613, 1.516128651393021, 1.485940017369517, 1.4463859484282828, 1.3988153056966321, 1.3448010565258925, 1.2861065727342524, 1.2246466282094337, 1.162444004927578, 1.1015827326397647, 1.044159078797126, 0.992231469376874, 0.9477705564521909, 0.9126106536498183, 0.8884037358295913, 0.8765771449152724, 0.8782960610536477, 0.8944316891315669, 0.9255359777467932, 0.9718235342095705, 1.03316122876352, 1.109065798095827, 1.1987095668179442, 1.3009342106114492, 1.4142722909177756, 1.5369761031525195, 1.6670532030548724, 1.8023078132966428, 1.940387168872027, 2.078831738606334, 2.2151281643535046, 2.3467636914694534, 2.4712808256457555, 2.586330943137281, 2.6897256040446114, 2.7794843710934978], [2.833744724070259, 2.897920340523585, 2.9445149759269227, 2.9726217683140232, 2.981688731202419, 2.9715299840398037, 2.9423287261690847, 2.8946318994385267, 2.8293366817663608, 2.747669147509871, 2.651155615684333, 2.5415873794314825, 2.4209796654725646, 2.291525806839753, 2.155547722717059, 2.0154438830847425, 1.873635991053736, 1.7325156410085523, 1.5943922053946498, 1.461443167385453, 1.3356680516851713, 1.21884701302647, 1.1125050238453629, 1.0178824621180496, 0.9359127409302632, 0.8672074469826404, 0.8120492702397556, 0.7703928158829179, 0.7418731973445812, 0.7258221202250452, 0.7212909859654653, 0.7270803757111707, 0.7417751229634235, 0.7637840520831366, 0.7913833516626596, 0.8227624698179467, 0.8560713645166772, 0.8894679173914147, 0.9211643246038024, 0.949471312997574, 0.9728390930414413, 0.9898940502442934, 0.9994702914844287, 1.000635299083108, 0.9927090999888591, 0.97527652619436, 0.9481923212068629, 0.9115790315197357, 0.8658178069432475, 0.8115324146921672, 0.7495669447460472, 0.6809578438636108, 0.6069010587404274, 0.5287151915704454, 0.4478016706437254, 0.3656030121136261, 0.28356029487838375, 0.20307098752457917, 0.12544825407913324, 0.051882824253419446, -0.016591554994670108, -0.07912816464032556, -0.13509205206411745, -0.1840787984494695, -0.22592680687516922, -0.26072277210219114, -0.2888001710814861, -0.31073079551783883, -0.3273095297882554, -0.33953275451184917, -0.3485709236044813, -0.355736016463309, -0.36244470309375254, -0.3701781750347201, -0.3804396859056988, -0.3947109099424778, -0.4144082633193336, -0.4408403403917181, -0.47516759498169053, -0.518365345952449, -0.5711911077876307, -0.6341571426111732, -0.7075090026091235, -0.7912106842871013, -0.8849368520654793, -0.9880724124465962, -1.09971953576909, -1.2187120349864782, -1.3436368246573305, -1.4728620030765307, -1.6045709307361429, -1.7368015233532426, -1.867489841454929, -1.9945169444252269, -2.1157578879092935, -2.229131681834678, -2.332650993671032, -2.4244703788156543, -2.502931847330568, -2.5666066330905535, -2.6143321164220894, -2.6452429625119476, -2.65879567258086, -2.654785899805667, -2.633358053478863, -2.5950068987489305, -2.5405710510073316, -2.471218458895702, -2.3884241632300713, -2.2939408061393176, -2.189762540802389, -2.078083153013815, -1.9612493474492865, -1.841710270448577, -1.721964434440366, -1.604505274487406, -1.4917666031987231, -1.3860692355299866, -1.2895700296123014, -1.2042145343030473, -1.1316943499661833, -1.0734101980948048, -1.0304415604709019, -1.0035235928907351, -0.9930318458515667, -0.9989751391945818, -1.0209967440396912, -1.0583838281415734, -1.1100849248390667, -1.1747349958253253, -1.2506874786476343, -1.3360525455035561, -1.4287406545142232, -1.5265103517381335, -1.6270191846977005, -1.7278765184576272, -1.8266970049670597, -1.9211534463811173, -2.0090278135913056, -2.0882592316483253, -2.1569878228507187, -2.2135934039932756, -2.2567281639627943, -2.285342598294493, -2.298704144714175, -2.2964081439323345, -2.278380938562572, -2.2448751153459963, -2.1964570871331444, -2.1339873965977696, -2.0585942988779946, -1.971641340969619, -1.8746897978144834, -1.7694569451815185, -1.6577712447293511, -1.541525584790393, -1.4226297598286655, -1.3029633813169805, -1.1843303928103384, -1.0684163128598785, -0.9567492524377833, -0.8506656507417072, -0.7512815472699834, -0.6594700621315943, -0.5758455943945507, -0.5007550739972922, -0.43427642076003553, -0.37622417893102994, -0.3261621121498653, -0.2834223663238055, -0.24713064114802008, -0.21623665903796846, -0.18954908688587516, -0.16577395463432218, -0.14355552795455245, -0.12151853247644498, -0.09831059551510628, -0.07264376883502138, -0.04333402271322834, -0.009337656701478304, 0.030216345377902857, 0.07599888163781303, 0.1284589557714325, 0.18780814629383924, 0.25401174633558027, 0.32678682476191895, 0.4056072786495395, 0.48971576443601, 0.5781422150040141, 0.6697284771450721, 0.7631584426596283, 0.8569929008963586, 0.9497082145245797, 1.0397378169953546, 1.12551545213832, 1.2055190256866872, 1.2783139165618502, 1.342594603101723, 1.3972234959673453, 1.441265934361578, 1.4740203938794, 1.4950430705445368, 1.5041661435150508, 1.5015091751551692, 1.4874832778015672, 1.4627878573600106, 1.4283999303501054, 1.3855561985174207, 1.3357282489636333, 1.2805914232977609, 1.2219880621723838, 1.1618859776313601, 1.1023331312626068, 1.045409598024984, 0.9931779711875954, 0.9476334111164363, 0.9106545583977796, 0.8839565194605941, 0.8690470906565291, 0.8671873156214798, 0.8793573723405775, 0.9062286630106643, 0.9481428345031685, 1.0050982934869332, 1.076744602048215, 1.1623849512820799, 1.2609867164215514, 1.3711999023592842, 1.4913830976698093, 1.6196363731371535, 1.7538403918071455, 1.8917008458724962, 2.0307972050020364, 2.1686346542695323, 2.302698020260312, 2.4305064332138917, 2.549667452473389, 2.6579293925934864, 2.753230627993466, 2.833744724070259], [2.8809512194075952, 2.934360003636522, 2.9695494235400997, 2.985833964007534, 2.9828910802608624, 2.9607674395555876, 2.9198768464211904, 2.8609899139115753, 2.7852157389932564, 2.693976029428481, 2.588972307715663, 2.472146980507485, 2.3456392054937623, 2.211736608543504, 2.0728239990412485, 1.9313302985515273, 1.789674935614538, 1.6502149667542578, 1.5151941605525692, 1.3866952285433085, 1.2665963050751337, 1.1565326702459107, 1.0578645782348737, 0.9716519011412856, 0.8986361295661621, 0.8392300898355869, 0.7935155484480757, 0.761248681709537, 0.741873197344581, 0.7345407098434087, 0.7381377969584894, 0.751319005369779, 0.7725449329771995, 0.8001243969653259, 0.8322596035697998, 0.8670931695813294, 0.9027558085917744, 0.9374134876383563, 0.9693128823175489, 0.9968240099607502, 1.0184789997076347, 1.0330060632110019, 1.039357857555249, 1.0367335794987598, 1.0245942936039447, 1.0026711720524493, 0.9709665065264261, 0.9297475378632363, 0.8795333325943723, 0.8210751123497059, 0.7553306080070719, 0.683433161238608, 0.606656427978891, 0.5263756480253701, 0.4440265297499736, 0.36106285665281523, 0.2789139518067428, 0.19894313642387673, 0.12240828985459791, 0.05042556107062061, -0.01606280243542112, -0.07631565122751258, -0.12981442963264653, -0.17627839359115072, -0.2156731378398296, -0.24821219443291817, -0.2743516456277831, -0.29477787679601336, -0.3103887746299123, -0.32226884793726984, -0.33165890837994905, -0.33992109253878783, -0.3485001310034373, -0.35888187160897617, -0.3725501398618768, -0.3909430680457779, -0.4154100441901769, -0.4471704224619804, -0.4872750977758633, -0.5365719804221779, -0.5956763128985689, -0.6649466531922835, -0.7444672093971824, -0.8340370532085171, -0.9331665684218156, -1.0410813093331237, -1.156733257413255, -1.2788192774680358, -1.4058063913852736, -1.5359633131012844, -1.6673975269853214, -1.7980970475123539, -1.9259758745317528, -2.0489220587893158, -2.1648472191851296, -2.271736308458183, -2.3676964087897945, -2.4510033536885167, -2.520145017191563, -2.573860184885847, -2.6111720217930583, -2.631415277383115, -2.6342565148677637, -2.6197068169293614, -2.5881265991522295, -2.5402223512831985, -2.4770353204429565, -2.3999223447949087, -2.3105292361894363, -2.2107572912751032, -2.102723678054884, -1.9887165947413818, -1.871146226332211, -1.7524926284072526, -1.6352517446613168, -1.5218808127085535, -1.4147444305183166, -1.3160625429930517, -1.2278615649582625, -1.1519297842256946, -1.0897780881592696, -1.042606931740025, -1.0112803175313683, -0.996307391772505, -0.9978320801138433, -1.0156309956479694, -1.0491196555252982, -1.097366845350385, -1.159116777525103, -1.2328185054284275, -1.3166618842728355, -1.4086192158005284, -1.5064915813960527, -1.607958759893646, -1.7106315449459608, -1.8121052242342526, -1.910012960265691, -2.002077820511888, -2.086162242932819, -2.160313790498889, -2.2228061434501747, -2.272174398320834, -2.3072438851988033, -2.327151875737111, -2.33136173008416, -2.3196692168032245, -2.2922009314114993, -2.2494049316597637, -2.192033896356887, -2.1211212947842073, -2.0379512211275435, -1.9440226987911775, -1.8410093892890018, -1.730715746491895, -1.6150307368019456, -1.4958802974355032, -1.3751797272440613, -1.254787196932835, -1.1364595284411794, -1.0218113276506806, -0.9122784622166242, -0.8090867595709126, -0.7132266620154648, -0.6254344198387676, -0.5461802335066223, -0.47566357650245755, -0.41381574585570347, -0.3603095024498051, -0.31457548249664263, -0.2758248896402001, -0.24307781831981448, -0.2151964172576522, -0.19092198077790157, -0.16891495813525972, -0.14779679954950062, -0.1261925139750801, -0.10277279884281897, -0.07629461643007929, -0.0456391347465624, -0.009846021739980807, 0.03185682159189088, 0.08002888342104275, 0.13499867237122992, 0.19685185432378743, 0.26542622117367665, 0.3403136394760886, 0.4208689445165861, 0.5062255636386824, 0.5953174762856186, 0.6869069516399653, 0.7796173522132122, 0.871970157135617, 0.9624252456634554, 1.0494233924613414, 1.1314298638290823, 1.206977969856766, 1.2747114224330418, 1.3334243732935198, 1.3820980593356558, 1.4199330629770868, 1.4463763014366082, 1.4611419878671035, 1.4642259560835766, 1.4559129055214026, 1.43677629993466, 1.407670837797964, 1.3697175998051325, 1.3242821645772542, 1.2729461630469363, 1.2174729104687314, 1.1597679083731007, 1.1018351431545785, 1.045730219950525, 0.9935114571608412, 0.9471901261386733, 0.9086810506838754, 0.8797547811490769, 0.8619925281174128, 0.8567449813701159, 0.8650960525998523, 0.8878324671062653, 0.9254199932453132, 0.9779869419847588, 1.0453153963357216, 1.1268404458817036, 1.2216575096127884, 1.3285376354862621, 1.445950472345682, 1.5720944237666954, 1.7049333186301079, 1.8422387740515815, 1.9816372866445213, 2.120660971408368, 2.2568007767062013, 2.387560941082841, 2.5105134246464114, 2.6233510452383046, 2.7239380777440014, 2.8103571329965633, 2.8809512194075957], [2.9207044687937698, 2.962888711323785, 2.9863576603761066, 2.9906529595831515, 2.975684254936466, 2.941730394920047, 2.8894323245601963, 2.819777852677085, 2.7340786641004207, 2.633940131928748, 2.5212246546192656, 2.398009394678813, 2.2665394263101897, 2.1291774054017747, 1.9883509541874838, 1.8464990028702495, 1.7060183503293849, 1.5692116952950694, 1.4382383483968029, 1.315068765343448, 1.2014439439518532, 1.0988406052599646, 1.0084429345989028, 0.9311214958490075, 0.8674197552033756, 0.8175484639875903, 0.7813879580498114, 0.7584982386747376, 0.7481365116250497, 0.7492816813975035, 0.7606651314925115, 0.780806972493692, 0.808056811658903, 0.8406379936323101, 0.8766941842922588, 0.9143371204836691, 0.9516943285710262, 0.9869556247797495, 1.0184172498182211, 1.04452255820617, 1.0638982772889929, 1.0753854696445564, 1.0780644724447317, 1.071273244753507, 1.0546187247313696, 1.0279809789453043, 0.9915101109065658, 0.9456160809168495, 0.8909517696480477, 0.8283897890855885, 0.7589937022412878, 0.6839844534433072, 0.6047029305345916, 0.5225696759827059, 0.43904283335177763, 0.35557545710185473, 0.27357332625687336, 0.1943543858431577, 0.11911089460452197, 0.048875284529896715, -0.015509360939583277, -0.07341342500304572, -0.12443882878940839, -0.16843057112307713, -0.2054814228661229, -0.23592964086105686, -0.26034974898329427, -0.27953661522619455, -0.29448322947737254, -0.30635275223681196, -0.31644555576213407, -0.3261621121498654, -0.3369626942746986, -0.3503249424537023, -0.3677004099338872, -0.39047123224418584, -0.419908068240583, -0.4571304341719853, -0.5030704969061925, -0.5584413099036452, -0.6237103676241349, -0.6990792234510229, -0.7844697661450482, -0.8795175840167474, -0.9835726685550278, -1.0957075245921917, -1.2147325668339128, -1.3392184974227492, -1.4675251807801466, -1.597836364770231, -1.7281994454662364, -1.8565693403171437, -1.9808554246785974, -2.098970402300731, -2.2088799236439214, -2.3086517383249947, -2.396503170365673, -2.470845737264376, -2.53032579554111, -2.5738601848858473, -2.6006659582524443, -2.610283423421637, -2.6025918793722385, -2.5778176044220964, -2.536533838304276, -2.479652692610051, -2.4084091186565186, -2.324337254054568, -2.2292396543445236, -2.125150089482425, -2.014290742428872, -1.8990247847308932, -1.7818054183919096, -1.6651225616598015, -1.551448416427825, -1.4431831852287964, -1.342602205530296, -1.2518057381750598, -1.1726725860759957, -1.10681863011875, -1.055561253795451, -1.019890489182722, -1.0004475578537135, -0.9975113050393726, -1.0109928380877224, -1.0404384855651578, -1.0850409959352598, -1.1436586994382443, -1.214842168324934, -1.296867733550023, -1.3877770546956008, -1.4854217981846523, -1.5875123601787262, -1.6916694777909724, -1.7954775076025449, -1.8965381154750436, -1.9925231171008695, -2.0812252346786018, -2.160605590842949, -2.228836845090298, -2.284340988298648, -2.325820944780576, -2.352285285293134, -2.363065524733079, -2.357825660649683, -2.336563798699465, -2.299605904060424, -2.247591908866931, -2.1814545902266262, -2.102391806814456, -2.011832840167261, -1.9113997257733555, -1.8028645754967398, -1.6881039839911187, -1.5690516753756127, -1.4476505810791669, -1.3258055446540784, -1.2053378244915154, -1.0879425114630341, -0.9751498970030126, -0.8682917201620991, -0.7684730924560486, -0.6765507502222446, -0.5931181194704027, -0.5184975020483844, -0.4527395087901138, -0.3956296797878517, -0.3467020487039188, -0.30525923170899477, -0.27039845662703194, -0.24104279831064435, -0.21597675590154178, -0.1938851996975769, -0.17339463253224352, -0.15311565492105855, -0.13168549610368818, -0.10780947515400888, -0.08030028745105562, -0.0481140711789535, -0.010382294619703242, 0.03356138438639434, 0.08416000313405989, 0.1416184885920964, 0.20589556235373568, 0.2767025811338486, 0.3535093566681494, 0.43555681634005616, 0.5218761867163947, 0.6113142109644293, 0.7025637522029734, 0.7941989922557452, 0.8847143126641828, 0.9725658453176226, 1.0562146062307494, 1.1341700797582068, 1.2050331031085302, 1.2675369129059018, 1.3205852565142178, 1.3632865399176681, 1.3949830794724656, 1.415274644465442, 1.424035618188437, 1.421425263678146, 1.4078907524453237, 1.3841627961393632, 1.3512439076331122, 1.3103895048050656, 1.263082252661734, 1.2110002128026147, 1.1559795292187909, 1.099972521992486, 1.0450021820120745, 0.993114157234142, 0.9463273918032236, 0.9065846216292104, 0.8757039426745943, 0.8553326508039149, 0.846904504925857, 0.851601489381683, 0.8703210488818606, 0.9036496422139687, 0.9518433124975524, 1.014815805537657, 1.0921345878673876, 1.1830249267565263, 1.2863820004233366, 1.400790812669649, 1.5245534969235386, 1.655723414867362, 1.7921452888752045, 1.9315004594736684, 2.0713562326270827, 2.2092181799634036, 2.3425841806249026, 2.468998948110024, 2.586107770415917, 2.6917082074035052, 2.783798535243182, 2.8606218029715405, 2.92070446879377], [2.9526681417504257, 2.9832650978089528, 2.994797481145495, 2.9870379841576846, 2.9601292282325993, 2.9145799121451597, 2.851252735017348, 2.7713443884217686, 2.676358099881236, 2.5680693858700736, 2.4484858321965004, 2.3198018594692167, 2.184349547846798, 2.044546685631609, 1.9028432683397158, 1.7616677071889715, 1.6233740077648249, 1.4901911509619297, 1.3641758499210919, 1.2471697700758873, 1.1407621867722124, 1.0462589190443705, 0.9646582224061591, 0.8966341518102054, 0.8425277224945832, 0.8023460058043725, 0.7757691039475297, 0.7621647567711847, 0.7606101497129925, 0.769920319597617, 0.7886823981236386, 0.8152947955375842, 0.8480103124455783, 0.8849820787236752, 0.9243111571702476, 0.9640946173222004, 1.002472882430475, 1.0376751799173052, 1.0680619819367838, 1.0921634064318375, 1.1087126581447206, 1.1166737205896293, 1.1152626606759692, 1.103962073649917, 1.0825283730975863, 1.0509918144537929, 1.0096493261581392, 0.9590504056257442, 0.8999765129598977, 0.8334145594247007, 0.7605252360139046, 0.6826070562961938, 0.6010570938798758, 0.5173294756881558, 0.4328927457758148, 0.3491872393440221, 0.26758360233758804, 0.1893435586887683, 0.11558396578480946, 0.04724511067229044, -0.014935912872646487, -0.0704460401140563, -0.11901072955002397, -0.1606017271745088, -0.19543788847453025, -0.22397902734774391, -0.2469129435295625, -0.2651359587780126, -0.27972746243996793, -0.2919191247822171, -0.30305957759830365, -0.3145754824966419, -0.3279300048430111, -0.34457978306160664, -0.36593152703144893, -0.3932993944820912, -0.4278642801517066, -0.47063610931570937, -0.5224201561485365, -0.5837883099734532, -0.6550560911757959, -0.7362660763978385, -0.8271782331212709, -0.9272674908409798, -1.0357286940489687, -1.151488895724064, -1.2732267636283776, -1.3993986901188429, -1.5282710239555986, -1.6579576840683758, -1.7864622744353564, -1.9117236997114693, -2.0316641860679403, -2.1442385433262316, -2.2474834646809203, -2.339565650194016, -2.418827560160527, -2.4838296539993996, -2.5333880483875144, -2.5666066330905544, -2.582902811851848, -2.5820261856743, -2.564069663238987, -2.529472663976767, -2.4790162690377664, -2.4138103694499446, -2.3352730543688422, -2.245102670744987, -2.1452431643416965, -2.03784347642615, -1.9252119165761092, -1.809766556281045, -1.6939827872907345, -1.5803392605063131, -1.4712634638181852, -1.369078209587696, -1.2759502841027892, -1.1938424627213067, -1.1244700167001433, -1.069262732758989, -1.0293333367767403, -1.0054530618062374, -0.9980349314866899, -1.007125147040324, -1.0324027738054344, -1.0731877263559315, -1.1284568544751166, -1.1968677403722643, -1.2767896352163677, -1.3663407947375967, -1.4634313233941723, -1.5658105080553923, -1.6711175184114222, -1.7769342748771693, -1.8808392374301426, -1.9804608517137856, -2.073529402209498, -2.1579260659427955, -2.231728032912377, -2.2932486593736714, -2.3410717447638874, -2.3740791693141143, -2.3914712936195217, -2.3927796995607804, -2.377872039583096, -2.3469489538133295, -2.3005332070899467, -2.2394513859607286, -2.164808674459414, -2.07795739263193, -1.9804601293187731, -1.874048427029947, -1.7605780788231051, -1.6419821724719883, -1.5202230641157815, -1.3972444809459545, -1.2749249399855, -1.1550336280599716, -1.0391898177937386, -0.9288267977346915, -0.8251611740162165, -0.7291682593988008, -0.641564106700133, -0.562794571550909, -0.4930316084545527, -0.4321768188463666, -0.3798720849047033, -0.3355169429095046, -0.29829217948423703, -0.2671889773630813, -0.24104279831064424, -0.21857107295160252, -0.1984136734719686, -0.17917507775279948, -0.1594670941459733, -0.13795100574785857, -0.11337801188796132, -0.08462689210852618, -0.05073789292826211, -0.010941938229416916, 0.0353156123888483, 0.08835728963473931, 0.14826239779330233, 0.21486275652142597, 0.2877454231082218, 0.3662623345995265, 0.4495466280779853, 0.5365352223159214, 0.6259970794264587, 0.7165664152165498, 0.8067799955142, 0.8951175461594881, 0.980044219425333, 1.06005400156203, 1.1337129164589714, 1.1997008798947315, 1.256851087577532, 1.3041858775015358, 1.3409480916799679, 1.3666270719981595, 1.3809785570575377, 1.384037898186843, 1.3761261795240425, 1.357849005072228, 1.3300879004656667, 1.2939844642281266, 1.2509175878798748, 1.2024742417189414, 1.1504144890005972, 1.0966315413793857, 1.0431077990570408, 0.9918679267723226, 0.9449300988130783, 0.9042566004960895, 0.8717049986015574, 0.8489810883446632, 0.8375947896361542, 0.8388201013895356, 0.853660130960909, 0.8828180986346207, 0.9266750772049235, 0.9852750675298196, 1.0583178363109544, 1.145159756535648, 1.2448226985407151, 1.356010825233301, 1.4771349533978058, 1.6063439589366513, 1.7415625318645482, 1.880534431140303, 2.020870253823362, 2.160098620938882, 2.2957195966101756, 2.4252590996110492, 2.546323038951292, 2.6566499081503667, 2.754160606445105, 2.83700431853342, 2.9035993760653844, 2.9526681417504257], [2.9765718111406216, 2.995316769641939, 2.9947974811454956, 2.975019622059029, 2.936357602713908, 2.879545696600934, 2.8056610943966396, 2.716099290169622, 2.6125423884278547, 2.4969210875709704, 2.371371243799755, 2.2381860460158878, 2.099764933666736, 1.9585604634180986, 1.8170243752128865, 1.6775541226557562, 1.5424411164559506, 1.413821883317106, 1.2936332673762072, 1.1835726989652349, 1.0850644286607627, 0.9992324764579992, 0.9268808801346017, 0.868481647561149, 0.8241706293002747, 0.7937513349613545, 0.7767065241894965, 0.772217215596663, 0.779188578985799, 0.7962820122254843, 0.8219525580982139, 0.8544906919125865, 0.8920674106414049, 0.9327814812136206, 0.9747076610662898, 1.015944689158142, 1.0546618606269096, 1.0891430426636968, 1.1178270617750135, 1.1393434915040344, 1.1525429923340391, 1.1565214987600783, 1.1506377087441533, 1.1345235039036607, 1.1080871104481547, 1.0715089964969908, 1.0252306863120284, 0.9699368515237821, 0.9065312091177611, 0.8361069115362386, 0.7599122518561788, 0.679312623200412, 0.5957497634426027, 0.5106993816074299, 0.4256282995459244, 0.3419522505922507, 0.26099545582362504, 0.18395304882585972, 0.11185734280922864, 0.04554883150629919, -0.014347309864745285, -0.06743860197946232, -0.11357605609030169, -0.1528580973078434, -0.1856275075107557, -0.21246146149101633, -0.2341549107209501, -0.2516977435213904, -0.26624631398389575, -0.2790900805930435, -0.29161422532094816, -0.3052592317089945, -0.3214784833483056, -0.3416950000808606, -0.36725845670434526, -0.3994036272272036, -0.43921136677055245, -0.4875731837700488, -0.5451603686298818, -0.6123985335413632, -0.6894482845482031, -0.7761925944295572, -0.8722312773694251, -0.9768827878624018, -1.0891933813270889, -1.2079534870876008, -1.3317209604228426, -1.458850703894253, -1.5875299835905567, -1.715818617429243, -1.841693083995373, -1.9630934948572225, -2.077972293587202, -2.184343492908674, -2.280331238870648, -2.3642164983821305, -2.4344807037347884, -2.4898452540827196, -2.5293058676860123, -2.5521608978304258, -2.558032866847735, -2.546882633158995, -2.5190157818479983, -2.475081015665876, -2.4160605160156923, -2.343252437650814, -2.258245891778247, -2.1628889552950312, -2.059250414495223, -1.9495761055594272, -1.8362408476719383, -1.7216970743943318, -1.608421352228005, -1.4988600300394275, -1.395375287815588, -1.3001928474120599, -1.2153525716514189, -1.142663112170812, -1.0836616723795363, -1.0395798320323166, -1.011316237149383, -0.9994167967791868, -1.0040628503410884, -1.025067580321716, -1.0618807495227012, -1.1136016446239956, -1.1789999133357205, -1.2565437955887786, -1.3444350745979456, -1.4406499154565833, -1.5429846210214044, -1.6491052205509364, -1.7565997186237168, -1.8630317723861263, -1.9659945355677786, -2.0631634086264166, -2.1523464657637947, -2.231531390564452, -2.298927841097923, -2.353004280253488, -2.3925184449752357, -2.416540785504793, -2.4244703788156547, -2.416043004855356, -2.391331265447531, -2.3507368190332185, -2.2949749950968292, -2.2250522354485702, -2.1422369810350053, -2.048024778437312, -1.9440985159121749, -1.8322848114499766, -1.7145076621648194, -1.592740523330319, -1.4689580151689143, -1.3450884554520135, -1.2229683861775589, -1.1043002039029226, -0.9906139172825805, -0.8832339442269743, -0.7832517277161707, -0.6915047970724779, -0.6085627342849635, -0.534720327017247, -0.46999800570837913, -0.4141494763328632, -0.3666762775893643, -0.3268488161229011, -0.2937332702368186, -0.26622360549522717, -0.24307781831981426, -0.22295741931164903, -0.2044690891637878, -0.18620738861467961, -0.16679738117434312, -0.1449360338608253, -0.11943129670411544, -0.08923782536927728, -0.053488401275196176, -0.011520217730942028, 0.03710466403655475, 0.09258523197999148, 0.15487418949660164, 0.22367757030649807, 0.29846131965674894, 0.37846467730613215, 0.4627200195926086, 0.5500786483628015, 0.6392418579604443, 0.7287964718153227, 0.8172539210080413, 0.903091841558646, 0.984797097557633, 1.0609090954333342, 1.1300622417397566, 1.1910264132366182, 1.2427443533656017, 1.2843649824227255, 1.3152717080029093, 1.335104945208641, 1.343778199631523, 1.3414872266727096, 1.3287119543712798, 1.3062110392290411, 1.2750091110001394, 1.2363769483844071, 1.1918050083580962, 1.1429709029468897, 1.0917015742796017, 1.0399310577829084, 0.9896548408543788, 0.9428819172781754, 0.9015857036251115, 0.8676550211711476, 0.8428463544497375, 0.8287385751339432, 0.8266912679777475, 0.8378077152206004, 0.8629034890684876, 0.9024814711622451, 0.9567139664799776, 1.0254324105665005, 1.1081249874394161, 1.2039422854194066, 1.3117109241211642, 1.4299548926773866, 1.5569241516940537, 1.6906298740657828, 1.828885536985814, 1.9693529332852973, 2.109592048200171, 2.2471136508184135, 2.3794333802215144, 2.5041260664391927, 2.6188790168085787, 2.7215430194438452, 2.810179866807179, 2.8831052826121866, 2.9389262425621494, 2.9765718111406216], [2.9922132411047833, 2.998941764225594, 2.9863576603761066, 2.9546995540689083, 2.904570497089063, 2.8369241536040386, 2.7530431286081756, 2.6545099564505454, 2.543171439536106, 2.4210971838300153, 2.290533313741616, 2.153852461032211, 2.0135012078809362, 1.871946221110381, 1.7316203414763405, 1.594869888257586, 1.4639044052857801, 1.3407500109223551, 1.2272074229313563, 1.1248156120110904, 1.0348218978546457, 0.9581591424848361, 0.8954305211942902, 0.8469021660269384, 0.8125037849355533, 0.7918371662630007, 0.7841922877762769, 0.7885705668007206, 0.8037146175249877, 0.828143727432674, 0.8601941308079333, 0.898063046599021, 0.9398553632595819, 0.9836317965276052, 1.0274573187527505, 1.069448660921341, 1.1078197207890101, 1.1409237716106195, 1.1672914542385269, 1.1856636485538175, 1.1950184553962548, 1.194591673921256, 1.1838903277352348, 1.1626989719855894, 1.1310786982996304, 1.089358940430683, 1.0381223660106866, 0.9781833143524924, 0.9105604024261087, 0.8364440669030357, 0.7571599358914636, 0.6741290265506998, 0.5888258416398654, 0.502735487336602, 0.41731095516440997, 0.3339317021252497, 0.2538646254156627, 0.1782284624071058, 0.10796255459446905, 0.04380079832124235, -0.013748531763672371, -0.06441655488676348, -0.10818078820692817, -0.14526519613578476, -0.17613328023700084, -0.20147438710978, -0.22218358928809373, -0.2393356628382608, -0.25415384072538344, -0.26797415918833833, -0.28220633178941473, -0.2982921794842368, -0.3176627125817741, -0.3416950000808605, -0.3716699725271007, -0.40873228590830224, -0.45385332660971006, -0.5077983622210066, -0.5710987418625763, -0.6440299251697165, -0.7265959742227809, -0.8185209811366754, -0.9192477297484432, -1.0279437072170345, -1.1435143949419684, -1.2646235826893557, -1.3897202698435, -1.5170715478101058, -1.644800702071525, -1.770929635174237, -1.893424596505182, -2.010244114042372, -2.1193879596921104, -2.218945945026895, -2.307145339179677, -2.3823957255590305, -2.4433301684106916, -2.488841642815541, -2.5181137905325457, -2.530645196562532, -2.526266534228616, -2.505150096232636, -2.467811411422954, -2.4151028374466357, -2.348199213396424, -2.2685758492434953, -2.1779793155354383, -2.0783916729395253, -1.9719889423809691, -1.8610947587812299, -1.7481302712191564, -1.6355614467394104, -1.52584500166133, -1.4213742214186667, -1.3244259367287958, -1.237109900036876, -1.161321752244292, -1.0987006869881535, -1.050592810173113, -1.0180210587105418, -1.0016623877290574, -1.0018327636351405, -1.018480315495736, -1.0511868037789476, -1.099177368226018, -1.1613383203333025, -1.2362425553681164, -1.3221819786569318, -1.4172061754426006, -1.5191664069204391, -1.625763890681105, -1.7346012247122853, -1.84323574272069, -1.9492335465293555, -2.05022294966001, -2.143946085158135, -2.228307479740963, -2.3014184741904815, -2.361636474614077, -2.4075981481373847, -2.4382458265690072, -2.4528465488655447, -2.451003353688517, -2.4326586225272466, -2.398089467101807, -2.347895347305342, -2.282978293069651, -2.20451628065948, -2.113930476693576, -2.01284720769135, -1.9030556356506982, -1.786462218119503, -1.6650431020939063, -1.540795643199942, -1.4156902540467933, -1.2916237681738933, -1.1703754591860787, -1.0535667797458739, -0.94262578402873, -0.8387570726515308, -0.7429179541418942, -0.6558013554112662, -0.5778258395206601, -0.5091329066819124, -0.4495915685119206, -0.39881000072473344, -0.35615390034289135, -0.3207710046190952, -0.29162107440190194, -0.2675105085063075, -0.24713064114801975, -0.22909868450663098, -0.21200021521617468, -0.19443206858583664, -0.17504449846091527, -0.15258148394399249, -0.12591811607378403, -0.09409407665145259, -0.05634232567452144, -0.012112240618021216, 0.038913403143019, 0.09680805986440984, 0.1613979249523155, 0.2322654263955815, 0.3087596094456326, 0.3900131474470451, 0.47496553803068475, 0.5623918813442083, 0.6509364897466577, 0.7391504501863029, 0.8255321545880857, 0.9085697327141696, 0.9867842682148212, 1.0587726533635764, 1.123248941960636, 1.1790830930473586, 1.225336059624914, 1.2612902650192104, 1.2864746227110961, 1.3006833905604747, 1.303988304044576, 1.2967436015814444, 1.279583734019831, 1.2534137354732424, 1.219392419225096, 1.1789087457536898, 1.1335518854112319, 1.0850756615171588, 1.035358206466065, 0.9863577901778463, 0.9400658835986346, 0.8984585973363753, 0.8634476848670942, 0.8368323197518904, 0.8202528463619609, 0.8151476638640384, 0.8227143345558245, 0.8438759116641501, 0.8792533607121615, 0.9291448054353719, 0.9935121674431122, 1.0719755923140992, 1.163815867886502, 1.2679848477249092, 1.3831236988421964, 1.5075886024849443, 1.6394833548357832, 1.7766981453291295, 1.9169536380937227, 2.0578493505912108, 2.1969152160765972, 2.331665135738145, 2.4596512743071486, 2.578517830882256, 2.6860530252772556, 2.7802380792103425, 2.85929204019806, 2.921711392462453, 2.966303521185682, 2.9922132411047833], [2.999460098067586, 2.9941094124654115, 2.9695494235401, 2.9262496971574565, 2.86503684465548, 2.7870758806946947, 2.6938440094524263, 2.587097460897299, 2.4688321628243313, 2.341239179183571, 2.2066559674899557, 2.0675146048085393, 1.9262882006443331, 1.78543675439177, 1.6473537239012548, 1.5143145500325117, 1.3884283303690863, 1.2715937548835419, 1.1654603092885845, 1.0713956207569706, 0.9904596688994897, 0.9233864161161925, 0.8705732298533095, 0.8320782793861801, 0.807625896183052, 0.7966196944426709, 0.7981630617605802, 0.811086453632194, 0.8339807639463562, 0.8652359006909398, 0.9030835752431634, 0.9456432177595249, 0.990969862596664, 1.0371028079880424, 1.0821138442561058, 1.124153864799853, 1.1614967233655946, 1.1925792783601321, 1.2160366681841863, 1.2307319880924357, 1.235779685693495, 1.2305621551643486, 1.2147391854455678, 1.1882501006861823, 1.1513086174149763, 1.1043906276519972, 1.0482152958103108, 0.9837200253047775, 0.9120300040863211, 0.8344231730381244, 0.7522915739582574, 0.6671001219203183, 0.5803439079832261, 0.49350517102490754, 0.40801108112838136, 0.3251934514123901, 0.24625144116568987, 0.17221823202401407, 0.10393255281123931, 0.04201580026885952, -0.013144644503113041, -0.06140546672185617, -0.10287057230758373, -0.1378872630380759, -0.16703553211218838, -0.191110759825008, -0.21110026202739993, -0.22815430552510832, -0.2435523504601048, -0.258665406293199, -0.27491549204010074, -0.2937332702368184, -0.31651497569075726, -0.34457978306160636, -0.3791287510796212, -0.4212064458516788, -0.47166628206337763, -0.5311405305068896, -0.6000158254718194, -0.6784148689719697, -0.7661848739353614, -0.8628931192138368, -0.9678298097960041, -1.0800182504218079, -1.1982321545378862, -1.3210197278770188, -1.4467339914876651, -1.5735686471816317, -1.6995986432048584, -1.8228244731552063, -1.941219139960173, -2.0527766416927142, -2.1555607891066164, -2.2477531472781855, -2.32769890618587, -2.393949527236606, -2.4453010837126503, -2.480827311203324, -2.4999065069643063, -2.5022415618555653, -2.4878725715428835, -2.4571816510418145, -2.4108897641078926, -2.350045571847215, -2.2760064985077095, -2.19041240195747, -2.0951524171964704, -1.992325708922667, -1.8841970195392863, -1.7731480283235674, -1.6616256425650444, -1.5520884197030578, -1.4469523688827413, -1.3485373996476904, -1.259015674172961, -1.1803630777422975, -1.1143149510628256, -1.0623271291836012, -1.025543207618971, -1.004768809771426, -1.000453464450276, -1.0126805222012591, -1.0411653486714478, -1.085261836962483, -1.1439770836442429, -1.2159938796062513, -1.2997004819181188, -1.393226960846351, -1.4944872613078766, -1.6012259840822627, -1.711068782293894, -1.8215751856568498, -1.9302926107352205, -2.0348102912908588, -2.1328118692098115, -2.222125423310892, -2.3007697795900053, -2.366996040469144, -2.419323390045313, -2.4565683741990503, -2.4778670152050433, -2.482689296209787, -2.4708457372643764, -2.4424859769322964, -2.3980894671018067, -2.3384485787663, -2.264644598536135, -2.1780172650635983, -2.0801286472706977, -1.9727222985605881, -1.8576787298734772, -1.7369683269130616, -1.6126028911715415, -1.486587009272095, -1.3608704501124562, -1.2373027545590136, -1.1175911189719785, -1.0032625833143298, -0.8956314193543927, -0.7957724774679101, -0.7045010952690725, -0.6223600016876162, -0.5496134704455322, -0.48624879169938157, -0.43198494455787734, -0.3862881709268139, -0.34839397723822146, -0.3173349294336501, -0.29197346211203024, -0.271038798614518, -0.2531669780802108, -0.23694291065404463, -0.22094333489485274, -0.20377953315200306, -0.18413867166158218, -0.16082267203004974, -0.13278358856978034, -0.09915455987172539, -0.05927552063440405, -0.012712998109136378, 0.04072652695693658, 0.10099004625324079, 0.16777841040646366, 0.2405536676401134, 0.31855316428322783, 0.4008100397391313, 0.48617958076506734, 0.5733707457373173, 0.6609820329083066, 0.7475407509872428, 0.8315446586523029, 0.9115048741881093, 0.9859889190339327, 1.053662750619418, 1.113330660720794, 1.163971965220167, 1.204773488397858, 1.2351569478416533, 1.254800472176927, 1.263653629981915, 1.2619455108184945, 1.2501855742280414, 1.2291571654446436, 1.1999037828856582, 1.1637083675197937, 1.1220660633348891, 1.0766510668192508, 1.0292783373701397, 0.981861075947354, 0.9363649926503188, 0.8947604723074509, 0.858973808335412, 0.8308387074353695, 0.8120492702397565, 0.8041156256403288, 0.8083233397942498, 0.8256976360267182, 0.8569733510323828, 0.9025714185794244, 0.962582517580755, 1.036758350662803, 1.1245108363940015, 1.2249193076032192, 1.3367456143954615, 1.4584568383150227, 1.588255138341348, 1.7241140746059493, 1.8638205962054661, 2.0050217392016316, 2.1452749633225494, 2.282100963938222, 2.413037731875673, 2.5356945991841027, 2.647805004950394, 2.747276741849093, 2.832238500684417, 2.901081615407349, 2.952496022925421, 2.985499587770468, 2.999460098067586], [2.9982510703398844, 2.9808605982439467, 2.9445149759269227, 2.88991074998785, 2.8180911180019272, 2.730422616818316, 2.628564588265357, 2.51443214372676, 2.390153502212413, 2.2580227084870987, 2.1204488453489954, 1.9799029346768413, 1.838863773462478, 1.6997639724966855, 1.5649374562033942, 1.436569642593624, 1.3166514534529719, 1.2069382084203122, 1.108914334970193, 1.0237646825017073, 0.9523530663263893, 0.8952084903519828, 0.8525193100444569, 0.8241354044277398, 0.8095782321888869, 0.808058457147846, 0.8185006470726522, 0.8395743814999355, 0.8697309529555943, 0.90724471543012, 0.9502580272962872, 0.9968286556158071, 1.0449784568586848, 1.0927421266420685, 1.138214818638242, 1.1795974700144833, 1.2152387366257493, 1.2436725339507535, 1.263650297044554, 1.2741672115737361, 1.2744818247727778, 1.2641286159412108, 1.2429232865796556, 1.2109607158946174, 1.1686057135243348, 1.1164768832851266, 1.0554240849576941, 0.9865001413005908, 0.9109275806033503, 0.8300613276180666, 0.7453483546014741, 0.658285377023056, 0.5703757234695381, 0.4830865253251084, 0.3978073585804233, 0.3158114280088054, 0.23822031405746658, 0.16597320694528575, 0.09980143309822215, 0.0402089392403947, -0.012540757242553692, -0.0584308126531482, -0.0976903352216765, -0.13078671866727615, -0.15841123420223235, -0.18145826061312442, -0.20099869890275715, -0.2182482709244242, -0.23453153659293294, -0.25124257816937556, -0.26980338987642793, -0.2916210744019017, -0.3180449830487101, -0.3503249424537019, -0.3895716877202167, -0.43672057001959086, -0.49249952746796294, -0.5574022033215481, -0.6316669678451522, -0.7152624527641909, -0.8078800436801944, -0.9089336002942879, -1.0175664911312707, -1.1326658432772103, -1.2528837231085928, -1.3766647857427639, -1.5022797634712246, -1.6278640109829277, -1.751460191612218, -1.8710640775601588, -1.9846723508954403, -2.0903312333781385, -2.186184743325481, -2.270521377696092, -2.341818047411763, -2.398780153024509, -2.44037677480536, -2.465870064118034, -2.47483805883917, -2.467190301311938, -2.4431758090883178, -2.403383132338806, -2.3487324227964375, -2.2804596327733346, -2.200093154385084, -2.1094233939261273, -2.01046594980089, -1.9054192202453175, -1.7966174053637143, -1.6864799833224613, -1.5774588300118075, -1.4719842128659761, -1.3724109212648563, -1.280965797197719, -1.1996979005677773, -1.1304324843231668, -1.0747298669158283, -1.033850175515403, -1.0087247956897927, -0.9999352052377035, -1.0076996953510213, -1.0318682955314067, -1.071926024222462, -1.1270043896724662, -1.1959008699128348, -1.2771059116794792, -1.3688368102120758, -1.4690776694594923, -1.5756244992372743, -1.6861343857868825, -1.798177577875836, -1.9092912643188737, -2.0170337821702367, -2.1190379886860335, -2.2130625545858926, -2.2970399905073737, -2.369120301464633, -2.4277092735155335, -2.4715005299834547, -2.499500648166729, -2.5110467976986905, -2.5058165443909948, -2.4838296539994, -2.4454419242053103, -2.391331265447531, -2.322476437352643, -2.240129022848122, -2.145779382323808, -2.0411174715387848, -1.9279895259330009, -1.8083517077366638, -1.6842218785465, -1.5576306973115863, -1.4305732511194855, -1.3049624037134235, -1.1825849949630958, -1.0650619449386558, -0.9538132108730102, -0.8500284168499056, -0.75464382780211, -0.6683261751075903, -0.5914636648864102, -0.5241643164681979, -0.46626159203758705, -0.41732709385198863, -0.3766899272853877, -0.3434621607362239, -0.31656966131747644, -0.29478745200771866, -0.276778624888974, -0.26113575897446745, -0.24642373205113002, -0.2312227853605325, -0.21417069853317464, -0.1940029599559059, -0.16958987393861016, -0.13996962918812658, -0.10437646105215818, -0.06226316999819758, -0.013317407524066816, 0.04252869563039386, 0.10509580964926438, 0.17396166406490232, 0.24847217176869313, 0.32775912626397585, 0.41076400758795, 0.49626727191981124, 0.5829223553813703, 0.6692934976045831, 0.7538963884767125, 0.83524056469562, 0.9118724333554289, 0.9824177790289378, 1.045622619290332, 1.1003913111675934, 1.1458208767343259, 1.1812306083416837, 1.206186130578837, 1.220517234046638, 1.2243289520036142, 1.218005521008553, 1.2022070465916574, 1.1778588802341454, 1.1461338998787096, 1.1084280681589798, 1.066329815942875, 1.0215839592553553, 0.9760510011166933, 0.9316627926553848, 0.8903756268894073, 0.8541219112612833, 0.824761609457304, 0.8040346580347405, 0.7935155484480761, 0.7945712204743219, 0.8083233397942494, 0.8356159323100252, 0.8769892230615837, 0.9326603813491768, 1.0025117094229063, 1.0860866338598902, 1.1825936708688223, 1.290918343839942, 1.4096428382304282, 1.5370729900910685, 1.6712720248512283, 1.810100296819459, 1.9512601313370204, 2.0923447443228973, 2.230890111235065, 2.364428581811146, 2.4905429902461544, 2.606919993913921, 2.7114013877981855, 2.8020321861778457, 2.877104336769937, 2.9351950337187764, 2.9751987220971703, 2.9963520349068817, 2.9982510703398844], [2.988596386843346, 2.959307412524669, 2.9114661202915983, 2.845990156496706, 2.7641304992190805, 2.6674436742231897, 2.5577571584894843, 2.4371287864036266, 2.3078011147716326, 2.172151820738579, 2.032641298581213, 1.8917586850111692, 1.7519675765493392, 1.6156527059273345, 1.4850688173012676, 1.3622929230378282, 1.2491810393955585, 1.1473303867127176, 1.0580479045062638, 0.9823257765361842, 0.9208244892365497, 0.8738637631948313, 0.8414215060988068, 0.8231407414679582, 0.8183442753070062, 0.826056677269941, 0.8450329785378903, 0.8737933296432484, 0.910662721776538, 0.9538147580683145, 1.0013183697562535, 1.0511863082019304, 1.1014242088990203, 1.1500790186767913, 1.1952856022699019, 1.2353103985765952, 1.268591078818751, 1.2937712663202239, 1.3097295079740572, 1.315601837352405, 1.3107974350245752, 1.2950070688046744, 1.268204180888452, 1.2306386755295589, 1.1828236453675949, 1.1255154521383206, 1.0596877438346348, 0.9865001413005909, 0.9072624589787149, 0.8233954338288736, 0.7363890205987145, 0.6477593685894613, 0.5590056234504425, 0.4715676966943161, 0.38678611563052945, 0.3058650080779045, 0.22983919106045472, 0.1595462229089928, 0.09560414659754261, 0.03839550209776264, -0.011941979141480787, -0.055517759600107325, -0.09268390409903758, -0.12402363684179539, -0.15033335196999015, -0.1725985539852671, -0.19196436370920916, -0.20970136857146165, -0.22716771929114904, -0.24576847530166462, -0.2669132759959536, -0.2919734621120301, -0.32223979010104803, -0.35888187160897567, -0.40291043047942554, -0.4551434019013564, -0.5161768041401931, -0.5863611950294273, -0.6657843859957872, -0.7542609293137762, -0.8513287234539593, -0.9562529010745324, -1.0680369789240365, -1.1854410633243795, -1.3070067236538627, -1.431087973917365, -1.5558876434284488, -1.6794982758672954, -1.7999465751264594, -1.9152403195071528, -2.023416595483669, -2.1225901602593384, -2.2110007298385157, -2.287058006748538, -2.349383308533598, -2.396846733642691, -2.4285989035704523, -2.4440964466382438, -2.4431205365718784, -2.4257879644567244, -2.3925544017008065, -2.3442096999359516, -2.281865266722602, -2.206933748757552, -2.1211014422710046, -2.026294028805366, -1.9246363991839233, -1.8184074751273325, -1.7099910630204056, -1.601823874656359, -1.4963419228795596, -1.3959265440655755, -1.3028513131849215, -1.2192311004019787, -1.1469744711195504, -1.0877405551936605, -1.042901407527643, -1.013510753897561, -1.000279865760917, -1.0035611395909616, -1.0233397740389165, -1.059233746380645, -1.1105020929142526, -1.176061301024246, -1.2545094283041807, -1.3441573811081295, -1.4430666156280754, -1.549092373178652, -1.659931431482884, -1.7731732485343874, -1.8863532975991184, -1.9970073429808974, -2.10272538746456, -2.2012040342814494, -2.290296048676112, -2.3680559756098605, -2.4327807690208236, -2.483044511905026, -2.5177264522142004, -2.536031743575575, -2.5375044580760293, -2.5220326264243536, -2.4898452540827205, -2.441501455694776, -2.3778720395830955, -2.300114054608208, -2.20963897886936, -2.108075379515895, -1.997227001697292, -1.8790273493068277, -1.755491898168273, -1.6286691318410393, -1.5005916101493042, -1.3732282704826058, -1.248439122220917, -1.1279334263923892, -1.0132323576681548, -0.9056370264888645, -0.8062025985520511, -0.7157190906412345, -0.6346992498513565, -0.563373741997742, -0.5016936889471793, -0.44934040844997847, -0.40574202844397944, -0.370096475284916, -0.3414001762361788, -0.3184816747851249, -0.30003923646110453, -0.28468142580209244, -0.2709695643385099, -0.25746093665874725, -0.24275159781076996, -0.22551765076816954, -0.20455390700127518, -0.17880891517432224, -0.14741544077347102, -0.10971560054582666, -0.06527999690035756, -0.013920355285663839, 0.04430466200092278, 0.10909061343627115, 0.17989537280372625, 0.2559539446532289, 0.3362996087837737, 0.4197908359212784, 0.505143265063015, 0.5909658993366258, 0.6758005650831762, 0.7581635910855922, 0.8365886036804946, 0.9096693004992504, 0.9761010616602376, 1.034720282525563, 1.0845403660533763, 1.1247833940118863, 1.1549066028749395, 1.174622919454247, 1.1839149600281524, 1.183042061195889, 1.1725400868116151, 1.1532139387266285, 1.1261228850939564, 1.0925590039937847, 1.054019217489864, 1.0121715574515235, 0.9688164553676861, 0.925843980107168, 0.8851880567817896, 0.8487787837398745, 0.8184940210757411, 0.796111451385755, 0.783262311052107, 0.7813879580498116, 0.7917003808505373, 0.8151476638640377, 0.8523853101311084, 0.9037541844171006, 0.9692656827809795, 1.0485945619306765, 1.1410796774372243, 1.245732688676122, 1.361254594885209, 1.4860597757297962, 1.6183070259520933, 1.755936901589149, 1.8967145391271771, 2.0382769726897383, 2.178183861320084, 2.313970451436129, 2.4432015407944916, 2.5635251812922446, 2.6727248594273303, 2.768768925249048, 2.8498561024273705, 2.9144560021915984, 2.961343680176932, 2.9896274148696187, 2.9987690459813585, 2.988596386843346], [2.970577730569146, 2.9296322050116927, 2.870682464907581, 2.794859504779255, 2.7036115195592996, 2.598671883261971, 2.4820207830214427, 2.355841410311021, 2.2224717389646202, 2.0843530225053826, 1.9439762187656375, 1.8038275960494266, 1.666334791051779, 1.5338145740596802, 1.4084235320209628, 1.2921128060231641, 1.1865879184304826, 1.0932745989052501, 1.013291370915844, 0.9474294947561916, 0.8961406836589944, 0.8595328206950855, 0.8373737104595536, 0.8291027058055649, 0.8338498608459508, 0.850462081722436, 0.8775355806260806, 0.9134537902765891, 0.9564297691231224, 1.0045520249716162, 1.055832609020779, 1.1082562851798938, 1.159829562113415, 1.2086283880403579, 1.252843350496738, 1.2908212939001653, 1.3211023649874372, 1.342451617522759, 1.353884449997148, 1.3546853097449703, 1.3444192699531554, 1.322936268070853, 1.2903679805663704, 1.2471174951481174, 1.193842122807675, 1.131429863829083, 1.0609701999577064, 0.9837200253047778, 0.9010656477998457, 0.8144818881483533, 0.7254893719697872, 0.6356111514139555, 0.5463298041171302, 0.45904613963507734, 0.3750405969812251, 0.29543834283310966, 0.22117898026771085, 0.15299165510832616, 0.0913762042522905, 0.036590831339779695, -0.011353376133579585, -0.052690953309733765, -0.08789363561240052, -0.11765523629420666, -0.14287022795443002, -0.16460659706857173, -0.18407369101057675, -0.20258590912764513, -0.22152319978129154, -0.24228941107738658, -0.26626960206989786, -0.29478745200771833, -0.3290639068819365, -0.3701781750347195, -0.41903212755765323, -0.47631907600282924, -0.5424977916053281, -0.6177724994565854, -0.7020794311278622, -0.7950803538621042, -0.896163317765018, -1.0044506788577416, -1.118814270009418, -1.2378974083206509, -1.3601432510981457, -1.483828847602091, -1.6071040844370577, -1.7280345925890426, -1.8446475770027129, -1.9549794479993394, -2.0571240798836716, -2.14928049721757, -2.2297987941704562, -2.297223127070829, -2.3503306840189655, -2.388165626694005, -2.410067116128122, -2.4156906734205075, -2.4050222847531555, -2.378384833794495, -2.336436629393295, -2.280161987847664, -2.2108540222845043, -2.1300899820494923, -2.0396996677941144, -1.9417276186405754, -1.8383899221821152, -1.7320266323056732, -1.6250508905644518, -1.519895931311901, -1.4189612069084683, -1.3245588955963936, -1.238862050403374, -1.1638556127306292, -1.1012914498990354, -1.052648483392533, -1.0190988560672352, -1.001480945040657, -1.0002798657609167, -1.0156159357858163, -1.047241378371045, -1.0945453506517782, -1.1565671837498173, -1.2320175273492802, -1.319306903893614, -1.4165810021196996, -1.5217618804229271, -1.632594111403299, -1.7466947832485848, -1.8616061841603992, -1.974849934974914, -2.083981303925462, -2.186642436861508, -2.2806132661508105, -2.363858921171913, -2.4345725512492855, -2.4912125858963616, -2.5325335944813663, -2.5576100645180104, -2.56585259082792, -2.55701615255804, -2.5312003469180007, -2.488841642815542, -2.430697909547375, -2.3578256606496826, -2.2715506264101055, -2.1734324261688123, -2.065224249564872, -1.9488285709817434, -1.8262500108519644, -1.6995465190765908, -1.5707800881717127, -1.4419682061725694, -1.3150372318465435, -1.1917788181734401, -1.0738104258471195, -0.9625408589219399, -0.859141622481755, -0.7645247507150379, -0.6793275868753086, -0.6039048185043955, -0.5383278864800844, -0.4823916995593787, -0.4356284018066301, -0.3973277632295034, -0.36656359851289383, -0.342225469060015, -0.32305479333746306, -0.3076843829992523, -0.29468034008209015, -0.28258519572911056, -0.26996114473152377, -0.25543223327538894, -0.2377243895065252, -0.21570224701132812, -0.18840179847666805, -0.1550580283905335, -0.11512680681662622, -0.06830047762016198, -0.014516740183027359, 0.0460394005893947, 0.11294065976655368, 0.18552933476197114, 0.2629356871095767, 0.3441023554958915, 0.42781415368673015, 0.5127324652762544, 0.5974333255814772, 0.6804481826087351, 0.760306256348879, 0.8355773705871196, 0.904914115120466, 0.9670922092151188, 1.021047979027505, 1.065911931546444, 1.1010375036762492, 1.1260241849956283, 1.1407343535165206, 1.1453033219223858, 1.1401422633375031, 1.1259338663743306, 1.1036207544951262, 1.0743868899537676, 1.0396323630929867, 1.0009421390094044, 0.960049491234563, 0.9187949921167008, 0.8790820484582405, 0.842830065622117, 0.8119263913175517, 0.7881782298235982, 0.7732657274224005, 0.7686974099425364, 0.7757691039475296, 0.7955273953712622, 0.8287385751339421, 0.8758638929653714, 0.9370417914145827, 1.0120776254606219, 1.100441193319121, 1.2012722153615043, 1.3133937051545195, 1.4353329842276439, 1.5653499050232618, 1.7014716691958935, 1.8415334653865938, 1.9832240058457882, 2.124134918410206, 2.261812852420751, 2.3938130866533363, 2.51775338601009, 2.6313668426528767, 2.732552456785046, 2.8194222619770404, 2.8903438786256284, 2.943977484958112, 2.9793063254003767, 2.9956600279728542, 2.9927301719865, 2.970577730569146], [2.944347547502898, 2.892086041388761, 2.822509057954231, 2.7369513832859087, 2.6370461969756547, 2.5246890844057774, 2.401996225868788, 2.271257743433638, 2.1348872999226796, 1.995369131349968, 1.855203752598908, 1.7168536045934897, 1.5826899090843791, 1.4549419645214945, 1.3356500541583325, 1.226623047096442, 1.129401656684815, 1.0452281814232816, 0.975023394725668, 0.9193710754963325, 0.8785104857584577, 0.8523369091111186, 0.8404101693094536, 0.8419708565244445, 0.8559638045357039, 0.881068189740091, 0.9157334666159643, 0.9582202179564393, 1.0066448850649767, 1.0590272559031553, 1.1133395299577158, 1.16755574872001, 1.219700380784951, 1.2678948805740602, 1.3104010987235761, 1.3456605086917932, 1.3723283258891958, 1.3893017297590826, 1.395741552323979, 1.3910869648895208, 1.3750628736209691, 1.3476799200758507, 1.309227169838901, 1.2602577564795696, 1.2015679245395148, 1.1341700797582075, 1.0592606031677898, 0.9781833143524926, 0.8923895748934045, 0.8033961032063883, 0.7127416246742398, 0.6219435049109745, 0.5324555086370335, 0.44562779218618076, 0.36267017503519067, 0.2846196465805103, 0.21231295098133102, 0.14636495815285464, 0.08715337636787204, 0.034810195297681194, -0.010779928066642798, -0.04997430984238851, -0.08336005760078291, -0.11173539657487663, -0.13608500356182573, -0.15755000543495398, -0.17739343946846045, -0.19696209259965028, -0.21764573325258807, -0.24083481995417305, -0.2678778138709412, -0.30003923646110436, -0.33845959827546107, -0.38411828089231587, -0.4378003821024693, -0.5000684365390091, -0.5712398023990344, -0.6513703627537912, -0.7402450307358686, -0.8373753756064956, -0.9420045056576138, -1.0531191586341264, -1.1694687655278526, -1.2895910738505971, -1.4118437463747109, -1.534441195140058, -1.655495772230414, -1.7730623219457744, -1.8851850065376712, -1.989945252027518, -2.085509623524614, -2.17017643192465, -2.242419896190836, -2.3009307371452694, -2.344652158642567, -2.3728102782714817, -2.384938199785859, -2.380893070160005, -2.360865631833042, -2.3253819612608058, -2.2752972739130812, -2.211781868700122, -2.1362994767430448, -2.050578465687695, -1.9565765268012103, -1.8564396335284767, -1.7524562030178632, -1.647007512798379, -1.5425155202906964, -1.441389300762599, -1.34597135797081, -1.2584850700587096, -1.1809845110388104, -1.115307835867065, -1.0630353359375562, -1.025453163726565, -1.0035235928907351, -0.9978625265711686, -1.0087247956897918, -1.0359976047916042, -1.0792022899591582, -1.1375043561939948, -1.2097315652159957, -1.2943996536523843, -1.3897450807164566, -1.4937640381083777, -1.6042568070464542, -1.7188764216430859, -1.8351804973175851, -1.9506850100131623, -2.062918768405849, -2.169477308086811, -2.2680749541502925, -2.356593846259413, -2.4331287968844095, -2.4960269570966536, -2.543921392479781, -2.5757578212118926, -2.590813933487254, -2.588710892061925, -2.5694168033802622, -2.533242142808119, -2.480827311203325, -2.413122688652176, -2.3313617300841596, -2.237027812285991, -2.131815688565973, -2.017588532420481, -1.896331652016526, -1.770104030733756, -1.6409888936842985, -1.5110445150430538, -1.3822564659064105, -1.2564924577298984, -1.1354608633823076, -1.0206738984028363, -0.9134163217175687, -0.8147203710089916, -0.7253474867910084, -0.6457772050935314, -0.5762034158905384, -0.516537997604493, -0.46642165186926693, -0.4252415818884983, -0.3921554866997735, -0.3661211867054577, -0.34593105685699366, -0.3302503263221786, -0.31765821022298213, -0.30669077238959813, -0.2958843796485719, -0.2838185988527553, -0.2691574078403058, -0.25068764021490425, -0.22735365998489826, -0.19828736371208167, -0.1628327322897634, -0.12056429861090777, -0.07129905752393817, -0.01510151653005844, 0.04771823472237299, 0.11661337550599193, 0.19081588407207425, 0.26935833043728136, 0.3511013516323615, 0.4347660799854168, 0.5189706644915731, 0.6022699167633493, 0.6831970292339229, 0.760306256348879, 0.832215420905053, 0.8976471082391262, 0.9554674406618194, 1.0047213826705392, 1.044663612632188, 1.0747841067047925, 1.0948277130284436, 1.1048071453682315, 1.105008991659678, 1.0959925101307189, 1.0785811694111547, 1.0538470746769208, 1.0230886047432695, 0.9878017605079146, 0.949645888819182, 0.910404593557693, 0.8719427737164732, 0.8361608332716763, 0.8049471869487874, 0.7801302375382295, 0.7634310228168997, 0.7564177227297715, 0.7604631803601086, 0.776706524189496, 0.806019885761907, 0.8489810883446616, 0.9058530413778565, 0.9765704158360173, 1.060734000980423, 1.1576129576258247, 1.2661549915244572, 1.3850042774876488, 1.5125267751725793, 1.6468423957378098, 1.7858633093081955, 1.9273375305809757, 2.0688967877408726, 2.208107571426465, 2.3425241785176367, 2.4697425120635716, 2.5874533751123217, 2.693494003174237, 2.785896617441125, 2.862932847832547, 2.9231529698650536, 2.9654190199666504, 2.9889309972823366, 2.9932455227702337, 2.9782865045289246, 2.9443475475028986], [2.9101277568626367, 2.846986579189957, 2.767353468253092, 2.672755720928226, 2.5649977042183587, 2.446121205610534, 2.3183605309965607, 2.1840934018678118, 2.0457888016325225, 1.9059529912571846, 1.7670749553147995, 1.6315725499672664, 1.50174060419833, 1.3797021752797372, 1.2673640802664732, 1.1663777192526354, 1.0781060758100067, 1.0035976286999642, 0.9435677403307645, 0.8983879056801266, 0.8680830549869348, 0.8523369091111185, 0.8505051928326232, 0.8616363232466102, 0.8844990124059768, 0.9176160597996548, 0.9593034651073241, 1.0077138684475848, 1.0608832269986284, 1.1167795657589215, 1.1733525979937558, 1.228582998527412, 1.280530130695813, 1.3273770749326697, 1.3674718823552363, 1.3993640783793106, 1.4218355667147835, 1.433925229879752, 1.4349466849283044, 1.424498828311595, 1.402468987274598, 1.3690286823270732, 1.3246221914309182, 1.2699482869670147, 1.205935686784497, 1.133712916458972, 1.054573417427329, 0.9699368515237823, 0.8813076437621481, 0.7902318697599626, 0.6982536304226145, 0.606872063554614, 0.5175001198281053, 0.4314261796389171, 0.3497795091597699, 0.2735004503859206, 0.20331611382100256, 0.1397221968974365, 0.08297138997904108, 0.03306865895813032, -0.010226486570804948, -0.04739081323110049, -0.07912152618563105, -0.10631420220658891, -0.13003508486088777, -0.15148848104277934, -0.17198012703375487, -0.19287749902011067, -0.21556812482644502, -0.2414170084311368, -0.27172430519952234, -0.3076843829992525, -0.3503473724808337, -0.4005842495782398, -0.4590564061876905, -0.5261905531730517, -0.6021596661040859, -0.6868705317943441, -0.779958286576988, -0.8807881595242774, -0.9884644499388011, -1.1018465830420403, -1.219571905525828, -1.3400847081121785, -1.4616707998987768, -1.5824968131687402, -1.700653291232298, -1.814200508971848, -1.9212158987340726, -2.0198419050673992, -2.1083330718626887, -2.1851011753174387, -2.248757255665448, -2.2981494689129165, -2.332395775298649, -2.350910601571151, -2.353424756546885, -2.339998040326416, -2.311024163076357, -2.267227775141372, -2.2096536018734074, -2.139647869243679, -2.058832395289821, -1.9690719030799606, -1.8724352786787426, -1.771151648416381, -1.6675622798407583, -1.5640694168280813, -1.4630832387793364, -1.3669681846275556, -1.2779899032168898, -1.1982640819153196, -1.1297083652641473, -1.0739985059716715, -1.0325297932703204, -1.006384680906153, -0.996307391772505, -1.0026861119467023, -1.0255432076189697, -1.0645337084657231, -1.1189521050287432, -1.187747310381231, -1.2695454425884267, -1.3626798989167932, -1.465228019923148, -1.5750534856639693, -1.6898534510900407, -1.8072093165101926, -1.9246399445086086, -2.039656078917333, -2.1498146957094852, -2.252772020582355, -2.3463339833860077, -2.428502944517935, -2.4975196213200888, -2.5518992610700524, -2.59046124841638, -2.6123514955792793, -2.617057139365529, -2.604413255705648, -2.574601495425381, -2.5281407395775553, -2.4658700641180347, -2.3889244873308297, -2.2987041447141747, -2.1968376908651055, -2.085140862492755, -1.9655712478051712, -1.8401803924912181, -1.7110644293503496, -1.5803144459998493, -1.449967802434386, -1.3219615776933573, -1.1980892634135165, -1.0799617332292244, -0.9689734031262714, -0.8662743618688968, -0.77274909595888, -0.6890022641606737, -0.6153517967075016, -0.5518294084109295, -0.49818842769089533, -0.4539186597068313, -0.4182678258921801, -0.39026895865471284, -0.36877298286669175, -0.35248558867755464, -0.34000739627420473, -0.3298763350407718, -0.3206111090325123, -0.3107545989829858, -0.2989160586900066, -0.283811000317989, -0.2642977279263745, -0.23940956969590477, -0.20838197452540108, -0.17067377495807945, -0.12598207228759792, -0.07425036726882733, -0.01566973685424688, 0.04932696070341155, 0.12007768781750745, 0.19571029413468025, 0.27516753616751116, 0.35723738251878745, 0.44058779837506895, 0.5238050847207925, 0.6054347531322611, 0.6840238484724233, 0.7581635910855922, 0.8265311982499051, 0.8879297620218053, 0.9413251068025679, 0.985878623847715, 1.0209751797035962, 1.046245318715692, 1.0615811232427994, 1.0671452554475696, 1.0633728775074434, 1.0509663284656572, 1.030882621165735, 1.0043140071261218, 0.9726620361680817, 0.9375057065900535, 0.9005644564076357, 0.863656882719832, 0.8286561911355397, 0.7974434674500251, 0.7718599270575756, 0.7536593322508048, 0.744461772625161, 0.7457099790513809, 0.7586292876131225, 0.7841922877762763, 0.8230890808058611, 0.8757039426745921, 0.9420990336027498, 1.0220056276318927, 1.114823154386213, 1.2196261558542356, 1.3351790682799531, 1.4599585478294177, 1.5921828733180141, 1.7298477845262221, 1.870767954825997, 2.0126231559539485, 2.153008054310222, 2.2894844850959384, 2.41963498526967, 2.541116330369388, 2.651711814653777, 2.749381038965454, 2.8323060256579096, 2.8989325635704657, 2.948005796387478, 2.9785992021286347, 2.990136266743473, 2.982404327068349, 2.9555602435711563, 2.9101277568626376], [2.868207873561811, 2.7947153802732227, 2.705682337051223, 2.6028156420586215, 2.488075604138452, 2.3636329666832188, 2.2318212942289612, 2.095085835385502, 1.9559300577072118, 1.8168611032334807, 1.680335436417069, 1.548705948483008, 1.4241717441429436, 1.3087317689977853, 1.2041433405842639, 1.111886525226625, 1.033135159631772, 0.9687351540493762, 0.919190536801159, 0.8846575124192115, 0.8649466121272188, 0.8595328206950852, 0.867573372562006, 0.8879327272248675, 0.9192140636858577, 0.9597964803823238, 1.0078769541972745, 1.0615160030707396, 1.1186859140081906, 1.1773203438643185, 1.2353640754170916, 1.2908217164535851, 1.3418041646359795, 1.3865717248359126, 1.423572856737371, 1.4514776464620196, 1.4692052338045345, 1.4759445828813837, 1.4711681546477688, 1.454638220527602, 1.4264057427911236, 1.3868019346354503, 1.3364227964934268, 1.2761071003375142, 1.2069084562975947, 1.1300622417397572, 1.0469482984486642, 0.9590504056257445, 0.8679136125580779, 0.7751005631809165, 0.6821479642021717, 0.5905243385586536, 0.5015901670470595, 0.41656145406173856, 0.3364776602213615, 0.2621748276806398, 0.19426458610021685, 0.13311957210817627, 0.07886562658301746, 0.031380956506613836, -0.009697734011555952, -0.04496232102624674, -0.07521390126067425, -0.10143751894681763, -0.12477165690144551, -0.1464733071312764, -0.16787955277920946, -0.19036668589900874, -0.21530795201027614, -0.24403105093031918, -0.27777653299844457, -0.3176582102229819, -0.3646266535489978, -0.4194367715464725, -0.4826203642310959, -0.5544644209778404, -0.634995786682141, -0.7239726590841509, -0.8208832065363522, -0.9249514138189964, -1.0351500784565968, -1.1502206960215815, -1.2686997947670333, -1.388951112110914, -1.5092028522505316, -1.627589129414202, -1.7421945883979433, -1.8511011059897824, -1.9524354159397714, -2.044416467905878, -2.1254013281972273, -2.19392845731331, -2.2487572556654474, -2.288902853161554, -2.3136652285363777, -2.3226518777676137, -2.3157934044009973, -2.2933515743773443, -2.255919559862303, -2.2044142861658313, -2.1400609884438277, -2.0643702757547397, -1.979108184488181, -1.8862598766280885, -1.7879877964601767, -1.6865852382515871, -1.5844263936558143, -1.483914038216602, -1.3874260790754755, -1.2972622192252126, -1.2155919965158817, -1.1444054279762241, -1.0854674324753566, -1.0402771186680477, -1.010032912592207, -0.995604362924545, -0.997511305039373, -1.015910891452283, -1.0505928101731112, -1.1009828184583577, -1.1661545221573146, -1.2448491350858688, -1.3355027633984515, -1.436280581370409, -1.5451171016915808, -1.659761599276262, -1.7778276262121553, -1.8968454597429532, -2.0143162574175606, -2.127766655370115, -2.2348025380199816, -2.3331607304530952, -2.420757417768708, -2.49573217741587, -2.5564866189670488, -2.6017167581953635, -2.630438405465408, -2.642005018539552, -2.6361176527559183, -2.612826832657264, -2.5725263638525955, -2.5159392974060513, -2.4440964466382447, -2.3583080333163258, -2.260129202489685, -2.1513202887609073, -2.0338028380983366, -1.9096124854848784, -1.7808498574701368, -1.6496307084451727, -1.5180365093061527, -1.388066686971906, -1.261593663571438, -1.140321766349059, -1.0257509754689262, -0.9191463496022054, -0.8215138216882242, -0.7335828933105623, -0.6557965798538875, -0.5883087744398181, -0.5309890111982093, -0.4834344224040343, -0.44498850404343465, -0.41476613494906495, -0.39168413997524654, -0.3744965516011209, -0.3618336102165364, -0.3522434539666231, -0.34423538658789865, -0.33632357766380916, -0.3270700449479322, -0.31512579290137605, -0.2992690346852511, -0.27843950514026256, -0.2517679776928311, -0.21860022594128248, -0.17851481762639557, -0.13133429102982155, -0.07712943743890477, -0.016216593754527425, 0.05085196798275399, 0.12330428705132561, 0.200171156025914, 0.28031415579109287, 0.36245853455728444, 0.4452300544837525, 0.5271948245811728, 0.6069010587404267, 0.6829216450593384, 0.7538963884767128, 0.8185727937174783, 0.8758442896146511, 0.9247848581812925, 0.9646791208251188, 0.9950470476223832, 1.0156625907692847, 1.026565696832533, 1.0280673203854604, 1.0207472398319672, 1.0054446602137834, 0.9832417729400672, 0.9554406240081775, 0.923533815816633, 0.8891697287147723, 0.8541130929025647, 0.820201865508249, 0.7893014684499371, 0.7632575174279458, 0.7438482191393164, 0.7327376312922302, 0.7314309676886881, 0.7412330887440564, 0.7632112472640633, 0.7981630617605795, 0.8465905673891536, 0.9086810506838728, 0.9842952121443299, 1.0729630243507475, 1.173887466964562, 1.2859561282860483, 1.4077604707048896, 1.5376223691355406, 1.6736273520288487, 1.8136638082389822, 1.9554672740284262, 2.096668786522677, 2.2348461861778777, 2.36757717390551, 2.4924928803586917, 2.607330686770904, 2.7099850491586612, 2.798555120414563, 2.871388036841388, 2.9271168353055965, 2.9646920920344892, 2.983406521138876, 2.982911936658756, 2.963228162288534, 2.924743663564649, 2.8682078735618113], [2.818942558782108, 2.7357146826343803, 2.638017430025098, 2.5277228713925783, 2.406930692510258, 2.2779222554515095, 2.143110676668496, 2.0049880882755318, 1.866071313781901, 1.7288472249660758, 1.5957190514856718, 1.4689548890868362, 1.3506395965745985, 1.2426311874272593, 1.1465227111771275, 1.0636104851774169, 0.9948693824505507, 0.9409357097825108, 0.9020980263095226, 0.8782960610536479, 0.8691276929051597, 0.8738637631948308, 0.8914703039736523, 0.9206375889823017, 0.9598152533327791, 1.0072525860431105, 1.0610429801883607, 1.1191714314212475, 1.1795639092055485, 1.2401373878415605, 1.2988493170682087, 1.3537453347815331, 1.4030040765514997, 1.4449780167597228, 1.4782293822407278, 1.5015603085722822, 1.5140365583398505, 1.5150042860236101, 1.5040995114581432, 1.4812501486411638, 1.446670624387372, 1.4008493072439652, 1.3445291465677631, 1.2786820902430582, 1.2044780030085434, 1.1232489419606364, 1.0364497581887604, 0.9456160809168499, 0.8523208008460484, 0.758130201169903, 0.6645608872370339, 0.5730386390739894, 0.4848602556937596, 0.4011593777593931, 0.32287716788113974, 0.2507385983576576, 0.18523494783935482, 0.1266129449785128, 0.07487082279601061, 0.029761366669565657, -0.009198143874810317, -0.0427093793707856, -0.07167024310099813, -0.09714660574266475, -0.12033925066576416, -0.14254691434112848, -0.16512640941854864, -0.1894508958515048, -0.21686741598383566, -0.24865483146930945, -0.2859832926818646, -0.3298763350407716, -0.3811766323006682, -0.4405163459302993, -0.5082928944848256, -0.5846508302376756, -0.6694703556945952, -0.7623628438374359, -0.8626735472723679, -0.9694914973752187, -1.081666409668252, -1.1978322306874072, -1.3164367890778652, -1.4357768539566738, -1.5540377607585798, -1.6693366424765004, -1.779768205555677, -1.8834519172510955, -1.9785794269122141, -2.063461028621224, -2.1365699873561654, -2.1965835951121875, -2.242419896190836, -2.273269120444581, -2.288618987257031, -2.288273188451466, -2.272362521615731, -2.2413483225224855, -2.196018032069188, -2.1374729248743445, -2.0671082186249734, -1.9865859707377216, -1.8978013472371242, -1.8028430135487303, -1.703948544058003, -1.6034558731308262, -1.503751911679573, -1.407219527737717, -1.3161841349854635, -1.2328611485651824, -1.1593055523938507, -1.0973647768250672, -1.0486360109830817, -1.014428972151885, -0.995735027693707, -0.9932034161500146, -1.007125147040324, -1.0374249774690125, -1.083661672379534, -1.1450365588055584, -1.2204101875366271, -1.308326723032036, -1.4070454988659893, -1.5145790059349853, -1.6287364282397718, -1.7471717099732371, -1.8674350310824965, -1.9870264890088012, -2.1034507338582378, -2.214271284024227, -2.3171632597339546, -2.409963312837219, -2.490715601366527, -2.5577127552213277, -2.6095309023423243, -2.645057969904233, -2.663514638788362, -2.6644675078700937, -2.6478342130901598, -2.613880440248575, -2.5632089652140193, -2.496741046015593, -2.415690673420508, -2.3215323556637304, -2.2159632648772694, -2.1008607037920575, -1.9782359582998146, -1.8501856819104605, -1.7188420101269335, -1.5863226250961584, -1.4546819831287245, -1.325864880103001, -1.2016634634109167, -1.0836787057017818, -0.9732872376427127, -0.8716142972504507, -0.7795133955998547, -0.6975531268613523, -0.626011368985629, -0.5648769344959724, -0.5138585434431847, -0.47240080730490047, -0.4397067380369306, -0.4147661349490648, -0.39638905758702603, -0.3832434689273071, -0.37389603298169133, -0.3668549768144764, -0.3606138807907291, -0.35369524368889493, -0.3446926814877241, -0.33231065980044716, -0.3154007289765048, -0.29299332602211164, -0.2643243262517799, -0.228855666928936, -0.1862895215256254, -0.13657567264511286, -0.07991190979773755, -0.016737460574068122, 0.05228035430874338, 0.12626587471787548, 0.20416072883561273, 0.28475464657713895, 0.36672063443900854, 0.4486535727241432, 0.5291112053396209, 0.6066564279788902, 0.6798997441342955, 0.7475407509872434, 0.8084075390113363, 0.8614929395829668, 0.9059866327858773, 0.941302230991206, 0.9670985801185694, 0.9832946665828391, 0.9900776801497368, 0.9879039571954967, 0.9774927108163046, 0.9598126392872985, 0.9360616878678706, 0.9076404162597238, 0.8761195906638697, 0.8432027711271752, 0.8106847978587038, 0.7804071910321735, 0.7542115644218007, 0.7338922118119441, 0.7211490549184412, 0.7175421417197931, 0.7244488545137497, 0.7430249283256133, 0.7741702938609237, 0.8185006470726511, 0.876325512300746, 0.9476334111164334, 1.0320845782381465, 1.129011483357856, 1.2374272279041503, 1.356041693339835, 1.4832851272912926, 1.6173386703344876, 1.7561711541611427, 1.897581345388297, 2.0392446723481528, 2.1787633582214685, 2.313718795716062, 2.4417249383705046, 2.560481453023674, 2.667825377850625, 2.7617800606941216, 2.840600212540978, 2.9028119994921373, 2.9472472113455317, 2.9730706831942793, 2.979800304903209, 2.967319128129748, 2.9358792674621395, 2.8860974867209186, 2.818942558782109], [2.7627486193793755, 2.6704836588735756, 2.5649312229068784, 2.4481127277497987, 2.322249492004644, 2.189714223316968, 2.0529792102817392, 1.9145624282481493, 1.7769728154917455, 1.6426559936918481, 1.5139416934264798, 1.3929941018290117, 1.2817662767354003, 1.1819596713991014, 1.0949896886434813, 1.0219580362489848, 0.9636324900567581, 0.9204344917772588, 0.892434819229064, 0.8793573723405782, 0.8805909234854147, 0.895208490351982, 0.9219938082143342, 0.9594742105893255, 1.0059590769100804, 1.0595828766539923, 1.118351734442795, 1.180192362485884, 1.2430021572037226, 1.304699237073561, 1.3632712090753376, 1.4168214912269383, 1.4636120874942924, 1.502101807045276, 1.5309790399271863, 1.5491883427259816, 1.5559502470287563, 1.5507738765431296, 1.5334621411792029, 1.5041094636984045, 1.4630921819950746, 1.4110519530238408, 1.3488726582641328, 1.2776514711038502, 1.1986648896519612, 1.1133306607207947, 1.0231666190488606, 0.9297475378632372, 0.8346611308689716, 0.7394643606687118, 0.6456411941565693, 0.5545629020306309, 0.4674519283886259, 0.38535025926691824, 0.3090930984585961, 0.23928851809199955, 0.17630359386406141, 0.12025736451824558, 0.07102077646572821, 0.028223591909879955, -0.008731942919192041, -0.040651049170589995, -0.06852053265815726, -0.09347776566149785, -0.11677536631628424, -0.13974252173205337, -0.16374398979041518, -0.19013787687580047, -0.22023332297624193, -0.25524923077246287, -0.29627515134925947, -0.3442353865878979, -0.3998572884266551, -0.4636446299918167, -0.5358567957259798, -0.6164943902707132, -0.7052917026876814, -0.8017162877194298, -0.9049757435920618, -1.014031580931441, -1.1276198943628368, -1.244278371911779, -1.3623790118852157, -1.4801657666845522, -1.5957962018089167, -1.7073861495041627, -1.8130562529020886, -1.910979240253606, -1.9994267414882743, -2.076814461612022, -2.141744557429143, -2.1930441250468298, -2.2297987941704576, -2.251380539215126, -2.2574689539953865, -2.2480653928908576, -2.2234995531121493, -2.184428255804273, -2.1318263737278937, -2.0669700454747515, -1.9914125058610195, -1.9069530446108707, -1.8155997761715574, -1.719527058250102, -1.6210285315757393, -1.5224668650994895, -1.4262213765351759, -1.3346347556547422, -1.2499601455936489, -1.1743098348470664, -1.1096067796379785, -1.0575401136567248, -1.0195257112795564, -0.9966727534391296, -0.9897571051509292, -0.9992021536787157, -1.025067580321716, -1.0670463510939534, -1.1244700167001407, -1.1963222149294421, -1.281260073686604, -1.3776430251017695, -1.4835683650755274, -1.5969127325082613, -1.7153785422269465, -1.836544288664869, -1.9579175465080478, -2.0769894319927658, -2.1912892558261374, -2.298438096577464, -2.3962000518770497, -2.482529983134192, -2.555616656289786, -2.6139202941995427, -2.656203692805747, -2.6815562099334795, -2.689410108484163, -2.6795489207467766, -2.6521076929660214, -2.6075651644825957, -2.5467281289183044, -2.470708411300253, -2.3808930701600057, -2.2789085932471687, -2.1665799956944443, -2.0458858468806143, -1.9189103440445872, -1.7877936147310929, -1.6546814649090051, -1.521675794335674, -1.3907868754272783, -1.2638886372604203, -1.1426780138238781, -1.02863930739604, -0.9230143867127077, -0.8267793887424024, -0.7406284262139056, -0.6649646247390655, -0.5998986279178049, -0.5452545208449189, -0.5005829366546889, -0.4651809317700005, -0.43811804781776065, -0.4182678258921797, -0.404343905758056, -0.394939731966646, -0.388570803418117, -0.38371834472268235, -0.3788732481769532, -0.37257913495242895, -0.363473413122901, -0.35032526763701277, -0.33206960175837114, -0.30783605866158176, -0.2769723829821299, -0.23906153181696577, -0.19393210914268788, -0.14166187267325403, -0.08257424337008683, -0.01722793054388073, 0.05360003488670969, 0.12893739444536442, 0.2076452589725038, 0.2884514399642546, 0.3699876228703382, 0.4508293885827676, 0.5295380135477477, 0.6047029305345908, 0.6749837123465467, 0.7391504501863042, 0.796121436786124, 0.8449971308420804, 0.8850894721094615, 0.9159457334121354, 0.937366233874063, 0.9494153934416257, 0.9524257783265658, 0.946994966104398, 0.9339752433488256, 0.9144563332319655, 0.8897415308180874, 0.8613177952681533, 0.8308205065097661, 0.799993735088739, 0.7706469943036546, 0.7446095402449685, 0.7236833555175711, 0.7095959943754837, 0.7039544795957474, 0.7082014242513137, 0.7235745049372485, 0.7510703380223744, 0.791413708910469, 0.8450329785378886, 0.9120423444514703, 0.9922314693768706, 1.0850628122221113, 1.1896768093278, 1.3049048620753545, 1.4292898954211608, 1.561114065269144, 1.6984330154460787, 1.8391159217973534, 1.9808904156367646, 2.1213913550856858, 2.2582123138255286, 2.3889585849578197, 2.511300454851304, 2.623025489174691, 2.7220885911478514, 2.8066586400250593, 2.8751605948396883, 2.926312052666626, 2.9591533795998743, 2.9730706831942797, 2.96781106364282, 2.9434897633724324, 2.9005890266149126, 2.8399486771836586, 2.762748619379375], [2.7001014815090043, 2.599574192969197, 2.487042058080666, 2.3646587489694975, 2.2347484438965624, 2.099755150146037, 1.9621894480592728, 1.8245738973052585, 1.6893883764498052, 1.5590166262293494, 1.435695235693345, 1.3214662493423754, 1.2181344840767174, 1.12723052939308, 1.049980265672916, 0.9872815770072116, 0.9396887606948992, 0.9074049496148499, 0.8902826706643343, 0.8878324671062661, 0.8992393197501046, 0.9233864161161915, 0.9588856426261338, 1.0041140166533744, 1.0572551367899792, 1.116344614276674, 1.1793183589670817, 1.2440625315755591, 1.3084639417185215, 1.3704596691012547, 1.4280847130808634, 1.4795165329639894, 1.523115426266344, 1.5574598025779471, 1.5813755438232304, 1.5939587942022488, 1.5945916910987863, 1.5829507275182262, 1.5590076226767682, 1.5230227655499833, 1.4755314818060308, 1.4173235529750303, 1.3494165835081235, 1.2730239624241684, 1.1895182977973089, 1.1003913111675938, 1.007211262396776, 0.9115790315197363, 0.8150840114259444, 0.719260963134372, 0.6255489541254965, 0.5352534405243311, 0.4495124674580169, 0.36926785088046626, 0.29524207141840714, 0.22792145974393216, 0.1675460874704507, 0.11410660181400113, 0.0673480607262898, 0.0267806424978747, -0.008303075415743943, -0.0388047448305586, -0.06579141790775794, -0.09046203875057261, -0.11411015592727845, -0.13808385573452572, -0.16374398979041516, -0.19242181680156784, -0.22537719589124885, -0.263758457237676, -0.30856503521918405, -0.36061388079072887, -0.4205105751230392, -0.4886259479821965, -0.5650788648772539, -0.6497256901496984, -0.742156762856498, -0.8417000427872542, -0.9474318997726119, -1.0581948352261599, -1.1726217452656456, -1.2891661643228205, -1.406137771195047, -1.5217423000066637, -1.6341248800943458, -1.7414157344501402, -1.8417770984936153, -1.9334501813884608, -2.0148009819531207, -2.084363790792675, -2.1408812592118225, -2.1833399926356174, -2.2110007298385153, -2.223422296775088, -2.2204786721283853, -2.2023686672304654, -2.169617901714533, -2.1230729437437645, -2.0638876753150424, -1.993502134229682, -1.913614270134641, -1.8261452279635206, -1.733198933779331, -1.6370169014149205, -1.5399292998407192, -1.4443034178134575, -1.3524907316329031, -1.2667738219844749, -1.1893143958169838, -1.1221036486796907, -1.0669161523547248, -1.0252683731424668, -0.998382819672831, -0.987158688174872, -0.9921497208936256, -1.0135498234766949, -1.0511868037789476, -1.1045244021024179, -1.1726725860759928, -1.2544058869721826, -1.3481893630355282, -1.4522115940135831, -1.5644239439519416, -1.6825851805070005, -1.80431041216277, -1.9271232028938832, -2.0485096494645036, -2.1659731614885067, -2.2770886696780366, -2.3795550037097084, -2.471244227423188, -2.550246794476508, -2.6149114902457793, -2.6638792531365563, -2.696110117430323, -2.710902686656818, -2.707905727161351, -2.6871216615922466, -2.6489019368099815, -2.5939344354500005, -2.5232232902981777, -2.438061641129622, -2.3399980403264165, -2.2307973623841564, -2.11239719974468, -1.9868608301924562, -1.8563279168743931, -1.7229641490678451, -1.5889110490618663, -1.4562371576049784, -1.3268917677258274, -1.2026623055031822, -1.0851363584050426, -0.9756692296471061, -0.875357753746498, -0.7850209476920658, -0.7051878979670312, -0.6360931004181221, -0.5776792822559992, -0.5296075479853867, -0.49127450847343157, -0.46183587921339, -0.4402358744240696, -0.42524158188849775, -0.4154813828731998, -0.40948638504120505, -0.4057337663275138, -0.40269088596797653, -0.398859006236028, -0.39281548518926346, -0.38325334636545116, -0.3690172046770726, -0.34913462682436447, -0.3228421268241315, -0.28960513960063144, -0.24913147437021368, -0.20137792072803237, -0.14654985956047584, -0.08509391360921084, -0.017683854066080456, 0.05479984462180104, 0.1312962439680213, 0.210595265734862, 0.2913732594075666, 0.37223185965081523, 0.4517390936728939, 0.5284716382149798, 0.6010570938798752, 0.6682151415495459, 0.7287964718153236, 0.7818184330261886, 0.8264964253983783, 0.8622701755874406, 0.888824155531372, 0.9061015579921324, 0.9143114053269646, 0.9139285434901155, 0.9056864556883151, 0.8905630148961841, 0.8697594769209751, 0.844673191279469, 0.8168646713682797, 0.788019814104335, 0.7599081885966606, 0.7343384201727964, 0.7131117774709157, 0.6979751241987503, 0.690574422112241, 0.6924099670590992, 0.7047945055832983, 0.7288153163522489, 0.7653012500277184, 0.814795605318646, 0.8775355806260794, 0.9534388832792801, 1.0420979057114494, 1.1427816942637956, 1.2544457461515013, 1.3757494781591237, 1.5050810215952282, 1.6405888166051557, 1.7802193096150591, 1.921759904670363, 2.0628861865522983, 2.201212324133268, 2.334343479219401, 2.4599289912397717, 2.5757150829951994, 2.6795958379644067, 2.7696612353237176, 2.8442410940625455, 2.901943870837696, 2.941689375281103, 2.9627346084975907, 2.964692092034491, 2.947540231763966, 2.9116254495955616, 2.857656011153438, 2.7866876747641274, 2.700101481509005], [2.6315311683055342, 2.523586211089698, 2.4050089131261436, 2.278066993475516, 2.1451678466476896, 2.0088061304046927, 1.871509512472339, 1.7357838391389162, 1.6040590006427904, 1.478636749474563, 1.3616416787256214, 1.2549764896256952, 1.160282572358161, 1.0789067947157893, 1.0118752423507609, 0.9598744859885594, 0.9232407691500377, 0.9019573191179145, 0.8956597887660501, 0.9036496422139699, 0.9249151078283345, 0.9581591424848357, 1.0018336855961802, 1.0541793342154009, 1.1132694450941596, 1.1770575689258889, 1.2434270485300296, 1.3102415681581896, 1.3753954264311474, 1.436862320912745, 1.4927414775124501, 1.5413000315697576, 1.5810106676960751, 1.6105836496657508, 1.6289925167012187, 1.6354928847227312, 1.629633966447652, 1.6112626082294559, 1.5805198296179053, 1.5378300391038675, 1.4838832817149923, 1.4196110465240144, 1.3461563204460423, 1.2648387150214142, 1.1771156117505566, 1.084540366053377, 0.9887186777696659, 0.8912642756713576, 0.7937550738062034, 0.6976909384521659, 0.6044541565863216, 0.5152736213370643, 0.43119364885910505, 0.353048217052361, 0.2814412727169948, 0.21673359377073403, 0.15903652112543032, 0.1082126951015094, 0.06388374841477427, 0.025444726438517497, -0.007915169777610002, -0.03718608692087035, -0.06350598839552743, -0.08812493942418749, -0.11236616838465922, -0.13758494941343974, -0.16512640941854848, -0.19628339246354018, -0.2322555152363663, -0.27411051895858324, -0.32274896631286265, -0.3788732481769538, -0.44296175623865036, -0.5152489466470648, -0.5957118700104875, -0.6840635780403201, -0.7797536411103824, -0.8819758283801798, -0.9896828175210963, -1.1016076191439417, -1.2162912263544705, -1.3321158368847765, -1.4473428481025277, -1.5601546976375018, -1.6686995176526476, -1.7711374916272227, -1.8656877509802208, -1.9506746263254382, -2.0245720752754983, -2.0860451454222027, -2.133987396597769, -2.1675532992299207, -2.186184743325481, -2.1896309325067573, -2.177961096178919, -2.1515696264473814, -2.1111734305754366, -2.0578014800445894, -1.9927767289618195, -1.9176907629128863, -1.8343717197241949, -1.7448461914904712, -1.651295968473889, -1.5560106163062921, -1.4613369850512423, -1.3696268294061424, -1.2831837715921337, -1.204210860933197, -1.1347599761410938, -1.0766842780216006, -1.0315948525686405, -1.000822588810173, -0.9853862145931682, -0.9859672696564115, -1.0028926323099423, -1.0361250377650675, -1.0852618369624845, -1.149542049223859, -1.227861564958259, -1.3187961607851304, -1.4206318035096592, -1.5314015459318124, -1.6489281607103707, -1.7708715222538993, -1.8947796341854544, -2.018142114058466, -2.1384448897674595, -2.253224834878894, -2.3601230735480607, -2.4569357196808035, -2.541660878689364, -2.6125408319980052, -2.6680984421080134, -2.7071669566330763, -2.7289125498058597, -2.732849115601733, -2.7188450135165536, -2.687121661592246, -2.638244066769741, -2.5731035752863813, -2.4928933109244253, -2.399076941952178, -2.2933515743773447, -2.177605705858376, -2.053873287999707, -1.9242850320778893, -1.791018152441971, -1.6562457715358965, -1.5220872100650433, -1.3905603553821333, -1.2635372415483994, -1.1427038873031838, -1.0295253255971564, -0.9252166232819756, -0.8307205354238558, -0.7466922694066368, -0.6734916537652222, -0.6111828200587905, -0.5595413177188795, -0.5180683963881056, -0.4860120124139393, -0.46239395029335195, -0.44604230008444046, -0.4356284018066294, -0.4297072608362974, -0.42676035688353803, -0.42523971527733684, -0.42361208426625097, -0.42040206641111244, -0.4142330857193417, -0.4038651340296208, -0.38822832867506957, -0.3664514263404147, -0.33788457238278075, -0.30211571726990444, -0.25898029831797714, -0.20856396134637858, -0.1511982787258723, -0.08744960296472284, -0.018101373821361733, 0.05586963258073846, 0.13332246635149295, 0.2129857907305838, 0.2934953849924462, 0.3734343575217481, 0.45137499147781324, 0.5259211013591727, 0.5957497634426019, 0.6596512969150488, 0.7165664152165507, 0.765619537615525, 0.806147347591579, 0.8377218047942403, 0.8601669581704403, 0.8735690657781663, 0.878279697863042, 0.8749116796673081, 0.8643279146376915, 0.8476233125553467, 0.8261002259842766, 0.8012379677981687, 0.774657138103564, 0.7480796266728608, 0.72328527351318, 0.7020662624331027, 0.6861803880359837, 0.677304373735403, 0.6769884261309222, 0.686613189108508, 0.7073502097893266, 0.7401269491226863, 0.7855972643865159, 0.8441181616614126, 0.9157334666159621, 1.0001648953335451, 1.0968108275039599, 1.2047528965030347, 1.3227703193151534, 1.4493616986458195, 1.5827738446387287, 1.721036988940289, 1.8620056037840398, 2.003403897288217, 2.1428749368094433, 2.278032257973357, 2.4065127502940915, 2.5260295728102977, 2.6344238459001414, 2.729713888643685, 2.810140824281617, 2.874209458239169, 2.920723441900486, 2.9488138682279317, 2.957960599221681, 2.948005796387481, 2.919159309676996, 2.87199577331246, 2.8074434538159303, 2.7267650916436734, 2.631531168305535], [2.5576178156470863, 2.4431626059467315, 2.3195258255700475, 2.1890700667025493, 2.05426559264643, 1.9176366339548454, 1.7817065968091406, 1.6489434578191675, 1.52170661320201, 1.4021964135571416, 1.29240754912487, 1.1940873561331304, 1.1086999949311565, 1.0373973080293368, 0.980997004417041, 0.9399686395848961, 0.914427672873444, 0.9041376897055375, 0.908520680681897, 0.9266750772049248, 0.9574010589345354, 0.9992324764579981, 1.050474577246736, 1.109246588034017, 1.1735280954276046, 1.2412080815323787, 1.310135414608424, 1.378169567637932, 1.4432303406940912, 1.5033453960261662, 1.5566944768854885, 1.6016492706886871, 1.6368079918430942, 1.6610238965235091, 1.6734270974236778, 1.6734392170872368, 1.660780599569093, 1.6354699873547305, 1.5978167589975076, 1.548406008125424, 1.4880769217154972, 1.4178950804402664, 1.3391194523786794, 1.2531649797924818, 1.1615617638479392, 1.0659119315464447, 0.9678453208014649, 0.8689751423451094, 0.7708547704734654, 0.6749367787914523, 0.5825352730717307, 0.4947924827801261, 0.41265045808659695, 0.33682858322425585, 0.26780746335630545, 0.20581957458110503, 0.15084688961090148, 0.10262550949858125, 0.060657149180956105, 0.02422714618617944, -0.007571507862018121, -0.035808770019892244, -0.0616835798893077, -0.08648624060019319, -0.11155815861220045, -0.13825002374202952, -0.16787955277920924, -0.20168993318423442, -0.24081008731745976, -0.2862178328086648, -0.338706942154941, -0.3988590062360277, -0.4670208846219753, -0.5432883833706723, -0.627496642040662, -0.7192175398729524, -0.8177642508465269, -0.9222028931270899, -1.031371034954606, -1.1439026408883333, -1.2582588740586353, -1.3727640159328243, -1.4856456290115128, -1.595077973311304, -1.6992275974048772, -1.7962999615204454, -1.8845859154221754, -1.9625068484662234, -2.028657353584429, -2.0818443004796174, -2.121121294784207, -2.1458176073995103, -2.155560789106617, -2.150292336642611, -2.1302759440789423, -2.096098053413458, -2.04866060636712, -1.9891660908253157, -1.9190951654524429, -1.8401773300307382, -1.7543552824638138, -1.6637437618285156, -1.5705838164032306, -1.4771935527519953, -1.385916513753855, -1.2990688976070082, -1.2188868646565674, -1.147475183461462, -1.0867584416425928, -1.0384359913010632, -1.0039417144589848, -0.9844095830571378, -0.9806458532005725, -0.9931085778235369, -1.021894949508074, -1.0667368000155524, -1.1270043896724662, -1.201718422792913, -1.2895700296122976, -1.3889482655148992, -1.4979744992820074, -1.6145428980293697, -1.736366071438444, -1.8610248153477569, -1.9860207977388986, -2.108830960983642, -2.22696237458779, -2.3380062635252115, -2.4396899588059764, -2.5299255686184585, -2.6068542489419704, -2.6688850599528786, -2.7147275261963655, -2.7434171711296123, -2.7543334665111927, -2.7472098200484787, -2.7221354162371227, -2.6795489207467766, -2.6202242532485824, -2.545248822494794, -2.4559947961470217, -2.354084141963739, -2.241348322522487, -2.119783649153534, -1.9915033992352593, -1.8586878721048339, -1.7235336009074216, -1.5882029497995767, -1.454775307834579, -1.3252010431330365, -1.2012593048547024, -1.0845206580098907, -0.9763154099020511, -0.8777083401805602, -0.7894803828103603, -0.7121176318483351, -0.6458078581771399, -0.5904445359049418, -0.5456381896939522, -0.5107346924971137, -0.48483997157418174, -0.4668504234760196, -0.45548819981034894, -0.44934040844997747, -0.44690118228249787, -0.4466155018752974, -0.44692362111292894, -0.44630493681295186, -0.4433201646647805, -0.4366507339506047, -0.42513439106483075, -0.4077961048288481, -0.3838734923466749, -0.35283612944131965, -0.3143982708417658, -0.2685246781530147, -0.21542943384237492, -0.15556780243987112, -0.08962138123871359, -0.018476957403665038, 0.05680034787330479, 0.13499891883753906, 0.21479660903648065, 0.2947998625761726, 0.37358494280701215, 0.4497401624668544, 0.5219079816762576, 0.5888258416398648, 0.6493646324438471, 0.7025637522029743, 0.7476618005393902, 0.7841220598279909, 0.8116520500550354, 0.8302165941865441, 0.840043996837415, 0.8416251155995361, 0.8357052871814141, 0.8232692549247658, 0.8055194256385535, 0.7838479574408306, 0.7598033420195008, 0.7350522903045523, 0.7113378562741545, 0.6904348362719609, 0.674103558142366, 0.6640432236813848, 0.6618459880300701, 0.668952950105263, 0.6866131891085077, 0.715846914455346, 0.75741370171675, 0.8117866676332416, 0.8791332958435008, 0.9593034651073216, 1.0518250574085244, 1.1559073386781573, 1.2704521145265957, 1.3940724720125695, 1.5251187308402199, 1.661711048112311, 1.8017779543333763, 1.9430999488956306, 2.0833571545290472, 2.2201799253857026, 2.3512012252042487, 2.474109542359346, 2.586701088838457, 2.6869300408659367, 2.772955619825103, 2.8431848823817463, 2.896310186633155, 2.9313404243590164, 2.947625255072912, 2.9448717420508834, 2.923152969865058, 2.882908412825282, 2.824936019517114, 2.750376175558906, 2.6606878999907737, 2.5576178156470872], [2.478986763943325, 2.3589837976319044, 2.23131602101464, 2.098420922922664, 1.9628107560953758, 1.8270179959911292, 1.6935404743724713, 1.5647874622676983, 1.4430279525900938, 1.3303423383085933, 1.2285785989563156, 1.1393139984866756, 1.0638231637421196, 1.0030532583743474, 0.9576067957372374, 0.9277324502642945, 0.9133240346475895, 0.9139276144559182, 0.9287565374466467, 0.9567139664799796, 0.996422327222289, 1.0462589190443699, 1.1043967936241839, 1.1688498842237005, 1.2375212723411433, 1.3082534097310554, 1.3788790742393626, 1.4472718284014172, 1.51139477043704, 1.5693464175421243, 1.6194026398862205, 1.6600536684494904, 1.6900353280965408, 1.7083537958383337, 1.7143033493308188, 1.7074767481530502, 1.6877680758528888, 1.6553680595126867, 1.6107520709660748, 1.5546611951310503, 1.4880769217154974, 1.4121901725733381, 1.3283655143941044, 1.238101521819833, 1.1429883466809097, 1.0446636126321884, 0.9447677895374262, 0.8449002076948801, 0.746576848356431, 0.6511909946393357, 0.559977747254665, 0.4739833045535292, 0.39403977892531744, 0.32074617483780443, 0.25445599153289955, 0.19527173971603942, 0.14304648091532765, 0.09739231512364778, 0.05769556151440621, 0.02313820302075664, -0.007274997204282997, -0.03468444685184957, -0.06033961078971066, -0.0855598064121604, -0.11169296273820577, -0.1400734518905255, -0.17198012703375462, -0.2085956971826658, -0.2509685365837351, -0.2999779654341269, -0.3563039510487286, -0.4204020664111123, -0.4924844091600111, -0.5725070318303476, -0.6601642674136285, -0.7548901572231419, -0.8558670051065665, -0.962040897857271, -1.07214385088952, -1.1847220654366613, -1.298169623087985, -1.4107667994787065, -1.5207220550633065, -1.6262166603129073, -1.7254508379822167, -1.816690258248364, -1.8983117047967828, -1.9688467418573625, -2.0270222535768094, -2.0717967970140383, -2.102391806814456, -2.118316810932786, -2.1193879596921112, -2.1057393315045783, -2.077826653792997, -2.036423262737735, -1.9826083158697607, -1.9177474625366064, -1.8434663641554903, -1.7616176343006495, -1.6742419336205714, -1.5835241022318616, -1.4917453388965387, -1.401232538774827, -1.3143059772638863, -1.2332265744469044, -1.160143991753561, -1.097046799073868, -1.0457159070242807, -1.0076823863312807, -0.9841906960873529, -0.9761682173390022, -0.984201841097463, -1.008522193977676, -1.0489959042858787, -1.10512612086753, -1.176061301024246, -1.2606120870791073, -1.3572758985037368, -1.4642686826112856, -1.5795630961483702, -1.700932236845619, -1.825997911845296, -1.9522823221341685, -2.0772619612923426, -2.1984224749872516, -2.313313205949298, -2.419600158177078, -2.5151161535980764, -2.597907023372379, -2.666272772768334, -2.7188027806765747, -2.7544042393595474, -2.772323203408114, -2.772157795087898, -2.753863301939144, -2.7177490970271183, -2.6644675078700932, -2.594994952022953, -2.510605840888274, -2.4128399240977516, -2.3034639006116806, -2.1844282558042734, -2.0578203930341328, -1.9258152109329805, -1.790624331929716, -1.654445212113835, -1.5194113569205037, -1.3875448315223264, -1.2607121902147411, -1.1405848571702535, -1.028604874071336, -0.9259567912842689, -0.8335463219156415, -0.7519862062585035, -0.6815895520961058, -0.6223707286405198, -0.5740537032246977, -0.5360875249355455, -0.5076684827658673, -0.48776830195001775, -0.47516759498169064, -0.4684936570157955, -0.4662615920375858, -0.46691767885602803, -0.4688838365052973, -0.4706020281788416, -0.4705774518069014, -0.4674194035152482, -0.45987876643491427, -0.4468811699321146, -0.42755498089762733, -0.4012534262811572, -0.36757030106137617, -0.32634888435507875, -0.2776838641030408, -0.22191625321204347, -0.15962146255461956, -0.09159087420424424, -0.018807427205930576, 0.05758411622697142, 0.1363114178795243, 0.2160124003102801, 0.29527565568810454, 0.3726823414869535, 0.44684843803321833, 0.5164662319747093, 0.5803439079832253, 0.6374421779721363, 0.6869069516399665, 0.7280971523794173, 0.7606069060086499, 0.7842814732916185, 0.7992264572116813, 0.8058099884233844, 0.8046577728887839, 0.7966410698539589, 0.7828578513899646, 0.7646075720813472, 0.7433601446018844, 0.7207198696269349, 0.6983852029050223, 0.6781053549116298, 0.6616348064370569, 0.6506868844321542, 0.6468875748347399, 0.651730752020818, 0.6665359777985347, 0.6924099670590985, 0.7302127336150795, 0.7805293203851499, 0.8436478855655878, 0.9195447639852014, 1.007876954197272, 1.107982301156574, 1.2188874560080318, 1.3393235032207642, 1.467748955767337, 1.6023796359695122, 1.7412247875550968, 1.882128607681488, 2.022816250094578, 2.1609432356573346, 2.2941471170968137, 2.4201001832538336, 2.536561955966396, 2.641430230844477, 2.73278944172385, 2.808955186895758, 2.868513841939971, 2.910356297081598, 2.9337049937374466, 2.93813359202119, 2.923578774639638, 2.8903438786256337, 2.8390942401999055, 2.770844335021413, 2.686936991379657, 2.5890151427470824, 2.478986763943326], [2.39630326747262, 2.271761976954905, 2.141125794321851, 2.006886494911444, 1.8715770862955328, 1.7377168911961185, 1.6077570704537707, 1.4840278502878959, 1.3686886758783174, 1.2636824417198607, 1.1706948500213121, 1.0911198240772468, 1.0260317570899076, 0.9761652119517616, 0.9419025080609709, 0.9232694417253463, 0.9199391917512668, 0.9312442661756771, 0.9561961545552402, 0.9935121674431144, 1.041648775104555, 1.098840605259963, 1.1631441283778887, 1.2324849519278873, 1.304707564600844, 1.3776263197070004, 1.4490764249555064, 1.5169637140534566, 1.5793120137396117, 1.6343069869527913, 1.680335427079892, 1.716019097218819, 1.7402423491060663, 1.752172915244997, 1.7512754408347926, 1.7373175050051963, 1.710368069037707, 1.6707884780088875, 1.6192163269310567, 1.5565426784081737, 1.4838832817149927, 1.4025445890252843, 1.3139854896738794, 1.2197757847742092, 1.121552499763268, 1.0209751797035966, 0.9196813303347452, 0.8192431565618425, 0.7211267096620955, 0.6266544860748327, 0.5369724260109335, 0.45302214172133104, 0.37551906614239944, 0.304937056345329, 0.24149981674001306, 0.18517932863144543, 0.13570129002599857, 0.09255738716916839, 0.055024041786917305, 0.022187109894180983, -0.00702814641874167, -0.03382262969950601, -0.05948545168347183, -0.0853534749125361, -0.11276944025876963, -0.14303980683168085, -0.17739343946846015, -0.21694225857051383, -0.2626449179576488, -0.3152744998864271, -0.37539111433624656, -0.4433201646647803, -0.5191368969127899, -0.6026576890385326, -0.6934383632364628, -0.7907796236060627, -0.8937395373477685, -1.0011527950238028, -1.1116563088531193, -1.2237205419862467, -1.3356858104459115, -1.4458026667771697, -1.5522753638212465, -1.6533073112598613, -1.7471473789032301, -1.8321358706739457, -1.906748992714944, -1.9696406681319325, -2.019680608938596, -2.0559876414513307, -2.0779573926319297, -2.085283579012107, -2.0779722935872025, -2.0563488556765908, -2.021056970050478, -1.9730501301524812, -1.9135753913499691, -1.8441498290910825, -1.7665301789523562, -1.6826763262971645, -1.594709468377385, -1.5048659073205068, -1.415447545148338, -1.3287702389257854, -1.247111233124178, -1.1726569157737565, -1.1074521441693266, -1.0533523547214376, -1.0119796107009869, -0.9846836525264632, -0.9725089000066068, -0.9761682173390017, -0.996024093017129, -1.032077711951424, -1.0839662103026135, -1.1509682092952274, -1.2320175273492824, -1.325724775032894, -1.4304063493444998, -1.5441201672627765, -1.6647073176599967, -1.7898386694825532, -1.9170653560022144, -2.0438719628112287, -2.1677311833150275, -2.286158671320203, -2.396766816744468, -2.4973161975640794, -2.5857635181856753, -2.6603049300733876, -2.719413742569695, -2.761871667663746, -2.786792898650282, -2.793640495355377, -2.7822347336506175, -2.7527532698061985, -2.705723166131888, -2.642005018539551, -2.56276961439761, -2.469467725767341, -2.3637938045219546, -2.247644488043763, -2.123072943743766, -1.9922401746856353, -1.8573644748901526, -1.7206702599015202, -1.5843375050932582, -1.4504530009029852, -1.3209645813800244, -1.1976394015044747, -1.0820272317779631, -0.9754296083218205, -0.8788755264448509, -0.7931041991452813, -0.7185552234682226, -0.6553663115187665, -0.603378553876664, -0.5621489958794693, -0.5309701263892405, -0.5088957087161687, -0.494772228541383, -0.48727509777586403, -0.48494863964778556, -0.4862487916993802, -0.4895874019383079, -0.49337696058603153, -0.4960746064366959, -0.4962242727878125, -0.49249589249681075, -0.48372066350664866, -0.46892148304172526, -0.44733778784887207, -0.41844418603826616, -0.381962429483756, -0.3378664502118064, -0.2863803653103397, -0.22796953802819767, -0.16332496327124482, -0.09334141905962066, -0.01908998730409189, 0.05821430660680711, 0.1372488591416409, 0.21662287840765398, 0.29491873890321624, 0.37073418997717156, 0.44272428347413406, 0.5096418919194229, 0.5703757234695375, 0.6239848028597188, 0.6697284771450733, 0.7070911189121435, 0.7358008349755966, 0.755841641968735, 0.7674587378278561, 0.7711566757383226, 0.7676904301780316, 0.758049528640293, 0.743435602793561, 0.7252338846776463, 0.7049793326849995, 0.684318214482385, 0.6649660960564202, 0.6486632845846924, 0.6371288452930332, 0.6320143569582212, 0.6348585860483114, 0.6470442451814816, 0.6697579578901447, 0.7039544795957465, 0.7503261259378283, 0.8092782365340144, 0.8809113578624812, 0.9650106667796376, 1.0610429801883576, 1.168161510884142, 1.2852183392021448, 1.4107843794725285, 1.5431764341879024, 1.6804907518153442, 1.8206423407510224, 1.961409146098214, 2.100480071400701, 2.2355057273186314, 2.3641507160303648, 2.4841462157598793, 2.5933416154360853, 2.6897539655217684, 2.7716140571910084, 2.837408017228244, 2.8859134084969447, 2.916228953134166, 2.9277971447088564, 2.920419182837209, 2.8942618451274225, 2.849856102427377, 2.788087479527418, 2.7101783599529568, 2.617662625482899, 2.5123532038711733, 2.3963032674726215], [2.3102668660298233, 2.182235079986984, 2.049718195621046, 1.9152412053496648, 1.7813364613771145, 1.6504888473255894, 1.5250821514676236, 1.4073478847412515, 1.2993177269865697, 1.2027806966800318, 1.1192460250285452, 1.0499125774284606, 0.995645507375604, 0.9569606538012946, 0.9340170067682547, 0.9266173730398255, 0.9342171769619861, 0.9559411381553906, 0.9906073804303702, 1.0367583506628057, 1.0926977663670487, 1.1565326702459091, 1.2262195524723618, 1.2996134096786034, 1.3745185457720457, 1.4487398852502178, 1.520133565405133, 1.586655599705496, 1.6464074599905638, 1.6976775084459605, 1.7389773195144447, 1.7690720641446394, 1.787004280754994, 1.7921105251649414, 1.784030571311413, 1.7627090213376093, 1.7283893729545903, 1.6816007791250362, 1.6231379154568704, 1.5540345397568893, 1.4755314818060312, 1.3890399357975978, 1.2961010397341726, 1.1983428126835072, 1.0974355800597686, 0.9950470476223837, 0.8927981859900289, 0.7922210592085304, 0.6947196740801318, 0.6015348430632957, 0.5137139447682851, 0.43208633520612644, 0.3572450133487044, 0.2895349800429836, 0.22904855407912975, 0.17562772769196675, 0.12887346058157473, 0.08816163131346783, 0.0526651922642604, 0.021381913484677845, -0.006833043974741076, -0.03323060992594709, -0.05912832914314141, -0.08586899175917322, -0.11477848368695637, -0.14712399186040245, -0.18407369101057636, -0.22665900166157513, -0.27574044396915487, -0.33197802056233816, -0.39580694597904265, -0.46741940351524797, -0.5467528557735347, -0.633485266791918, -0.7270374156018033, -0.8265822978959464, -0.9310614288098559, -1.0392076802783217, -1.1495741155714403, -1.2605681257784678, -1.3704900322110982, -1.4775751985369576, -1.5800386000152056, -1.6761207269864957, -1.7641336576139295, -1.842506121926851, -1.9098263959029542, -1.964881910314395, -2.00669453330556, -2.03455058640128, -2.0480247784373113, -2.046997387727231, -2.031664186067941, -2.0025387749335986, -1.960447190064421, -1.9065148210360356, -1.8421458825869375, -1.7689958597710016, -1.6889375247838805, -1.6040212852073417, -1.5164307673790636, -1.4284346610166405, -1.3423359490188835, -1.2604197170511575, -1.184900779276121, -1.117872368308022, -1.0612571187777604, -1.0167615251753548, -0.9858349770054549, -0.9696343695816448, -0.9689951594976622, -0.9844095830571369, -1.0160125873587003, -1.063575841403729, -1.1265100029451336, -1.203875220486764, -1.2943996536523843, -1.3965056038503563, -1.5083426654285672, -1.6278271397760113, -1.7526868051746989, -1.880510007289444, -2.0087979321231435, -2.135018847574024, -2.256663053250851, -2.371297262060437, -2.476617151662783, -2.570496868826094, -2.6510343438960664, -2.7165913741954184, -2.765827561694971, -2.797727338641587, -2.8116194813549322, -2.807188693035343, -2.784479026739242, -2.7438891150237814, -2.6861593683686027, -2.612351495579279, -2.5238208813109964, -2.4221825242011286, -2.3092713897848647, -2.1870981617488825, -2.05780148004459, -1.9235978324306573, -1.7867303153080092, -1.6494174991241832, -1.513803622771184, -1.3819113006429409, -1.2555978564517838, -1.1365163013354889, -1.0260818526862785, -0.9254447475716673, -0.8354699441888541, -0.7567241305283865, -0.6894702756816159, -0.6336697705977529, -0.5889920162781315, -0.554831133080339, -0.5303292895623883, -0.5144059874611522, -0.5057924949600017, -0.5030704969061934, -0.504713931107288, -0.5091329066819108, -0.5147185554138947, -0.5198876512045121, -0.523125846347957, -0.5230284160448676, -0.5183374731654433, -0.5079747119279995, -0.49106885937140027, -0.4669771541839526, -0.43530033001154916, -0.39589075078949343, -0.3488535245930427, -0.29454060543948535, -0.23353807476215013, -0.16664697129783096, -0.09485820540323582, -0.019322247111858638, 0.058685587317034056, 0.13780331144661428, 0.21662287840765396, 0.2937321318990146, 0.3677569705209877, 0.43740259100337264, 0.501492698515315, 0.5590056234504419, 0.6091063625895777, 0.6511736663858699, 0.6848214206860408, 0.7099137173146454, 0.7265731699285471, 0.7351822053161127, 0.7363772414883478, 0.7310358479145257, 0.7202571654419553, 0.7053360391974517, 0.687731482639683, 0.6690302407265084, 0.6509063510603109, 0.6350777105250036, 0.6232607385309966, 0.6171242843602421, 0.6182439537524117, 0.6280580280104118, 0.6478261174805904, 0.6785916309705553, 0.7211490549184397, 0.7760169230231284, 0.8434172213236913, 0.9232618186863769, 1.0151463421156128, 1.1183517344427931, 1.231853543245531, 1.3543387989736067, 1.4842301519323837, 1.6197167566755037, 1.758791222991977, 1.8992917992631975, 2.038948820353696, 2.17543434174247, 2.306413797093572, 2.429598460062389, 2.542797464306224, 2.643968139156212, 2.731263452208221, 2.8030754134522198, 2.8580733870028947, 2.8952363738462012, 2.9138784694632474, 2.9136668603493603, 2.8946318994385267, 2.857168988003971, 2.8020321861778537, 2.73031967108393, 2.6434513559124926, 2.543139170351126, 2.4313506780558596, 2.3102668660298242], [2.2216054665030556, 2.091160544787874, 1.9578665745596426, 1.8242604148569863, 1.6928523578612795, 1.5660718531018272, 1.4462151846394808, 1.3353963128343689, 1.235502015533187, 1.1481523595104972, 1.074667404318313, 1.016040890493457, 0.9729214960217268, 0.9456020631750606, 0.9340170067682545, 0.9377479191938549, 0.9560371920640031, 0.9878092836826488, 1.0316990805298756, 1.0860866338598933, 1.1491374034437576, 1.2188470130264693, 1.2930894192778093, 1.3696673203473049, 1.446363583364211, 1.5209924534169565, 1.5914493200263162, 1.6557578604689815, 1.7121134513535778, 1.7589218387343115, 1.7948321802441225, 1.818763717120017, 1.8299254959415583, 1.8278287353462694, 1.8122916175349824, 1.783436473432325, 1.7416795192176686, 1.6877134859010678, 1.6224836581300481, 1.547157999165133, 1.4630921819950753, 1.37179046836751, 1.2748634751142798, 1.1739839381901445, 1.0708416276241342, 0.9670985801185699, 0.8643458000691953, 0.764062534806191, 0.6675791570808833, 0.5760445891513708, 0.49039908080261524, 0.4113530114045945, 0.33937222729997024, 0.274670254465805, 0.21720754686662133, 0.16669774776370017, 0.12262075910878405, 0.08424223764018753, 0.05063896988078877, 0.020729426118227156, -0.006691340527242322, -0.03291339628634913, -0.059271264587010396, -0.08710199544627512, -0.11770309560626104, -0.1522914529232325, -0.1919643637092087, -0.23766371841242298, -0.2901443205424028, -0.3499472081185126, -0.41737871880314964, -0.49249589249681053, -0.5750986422339199, -0.6647289498330722, -0.760677161322895, -0.8619952732674058, -0.9675169194027109, -1.0758835920715417, -1.1855764692416433, -1.2949530695807208, -1.402287828918322, -1.5058155847621477, -1.6037768741039748, -1.6944638956725742, -1.776265962510043, -1.847713274988888, -1.9075178781373023, -1.9546107296492488, -1.9881738947538228, -2.007666999049987, -2.0128472076913497, -2.0037821555811273, -1.9808554246785983, -1.9447643469080271, -1.896510099999747, -1.8373802542110955, -1.7689241155470221, -1.6929213911643708, -1.6113448706154045, -1.5263179682706132, -1.4400681038575684, -1.354877006249527, -1.2730291076948048, -1.196759249494967, -1.1282009443098213, -1.0693364341115519, -1.0219497463971625, -0.9875838854111179, -0.96750320136933, -0.9626618612404167, -0.9736792023952111, -1.0008225888101716, -1.04399821241515, -1.102750093906359, -1.1762673424763967, -1.2633995371867641, -1.3626798989167932, -1.472355735691008, -1.590425470255283, -1.7146814012856917, -1.8427572124169302, -1.972179129719197, -2.100419541104636, -2.2249518325330255, -2.343305167238025, -2.4531179362046402, -2.552188640738145, -2.6385230303696123, -2.7103764100083536, -2.7662901469512935, -2.805121548231869, -2.8260664384087493, -2.8286739433496613, -2.8128531725650094, -2.7788716866186887, -2.727345832352429, -2.6592232223190586, -2.5757578212118917, -2.4784782766695272, -2.3691502903916826, -2.249733964186831, -2.1223371710450185, -1.9891660908253161, -1.8524741115456902, -1.7145103291389372, -1.577468880196124, -1.4434403137090028, -1.3143661499400443, -1.1919976888092778, -1.0778600187937313, -0.9732220431178878, -0.87907318636123, -0.796107275383414, -0.724713907907625, -0.6649774347180467, -0.6166834918870537, -0.5793328324629885, -0.5521620272579583, -0.534170436224526, -0.5241526995492057, -0.5207358647652448, -0.5224201561485367, -0.527622308084659, -0.5347203270172454, -0.5420985183524083, -0.5481916159218823, -0.5515268821821502, -0.550763106397099, -0.5447255140552407, -0.5324357114742401, -0.5131359220955882, -0.48630692197675945, -0.4516792475955, -0.40923742507770466, -0.3592171518778147, -0.3020955451664347, -0.23857475107334003, -0.16955938094324738, -0.09612840053626907, -0.019502241606158342, 0.05899397110958678, 0.13797008387705192, 0.2160124003102801, 0.29172587390770094, 0.3637758717422085, 0.4309283845473299, 0.49208759762613646, 0.5463298041171293, 0.5929327354989692, 0.6313995014575269, 0.6614764694252553, 0.6831645697552624, 0.6967236816886497, 0.7026699337467978, 0.7017659354250885, 0.6950041404506029, 0.6835837207528433, 0.6688815001499087, 0.6524176532587288, 0.6358170143115297, 0.6207669588443041, 0.6089729155770172, 0.6021126337849402, 0.6017903712763424, 0.609492178657025, 0.6265434365193296, 0.6540697539246926, 0.6929622601682236, 0.7438482191393146, 0.8070677691024195, 0.882657443494793, 0.9703409639749023, 1.0695276194931331, 1.1793183589670786, 1.2985195348259901, 1.4256640449553863, 1.559039436130728, 1.6967223574670052, 1.8366185920818898, 1.9765077530833235, 2.1140916097166293, 2.247044914075599, 2.3730675306255913, 2.4899366316629323, 2.5955577127901726, 2.6880132038273405, 2.7656075018632107, 2.8269073331970893, 2.8707764578402304, 2.8964038614821965, 2.9033247322243043, 2.8914336892586645, 2.8609899139115753, 2.8126140256252574, 2.747276741849102, 2.6662795566691058, 2.5712278635485157, 2.4639971281370014, 2.3466928833235996, 2.221605466503057], [2.131069184452055, 1.9993089031370561, 1.8663480374151538, 1.7347138620902536, 1.6068733913032844, 1.4851801144950896, 1.3718234201964177, 1.2687818774240387, 1.1777814513140041, 1.1002596106633158, 1.0373361431938797, 0.9897913330708198, 0.9580519784470626, 0.9421855388895787, 0.9419025080609709, 0.9565669107303417, 0.9852146298558848, 1.02657908382579, 1.0791236004767089, 1.1410796774372274, 1.2104901814657851, 1.2852564260641588, 1.3631879794620976, 1.4420539961499776, 1.5196348358490595, 1.593772734785866, 1.6624203252642138, 1.723685859948724, 1.7758740854094217, 1.817521823070229, 1.8474274518725398, 1.8646736422750516, 1.8686428617632094, 1.8590253535681722, 1.8358194782661803, 1.7993244976653429, 1.7501260671756969, 1.6890748820716264, 1.6172590902636301, 1.5359712352779804, 1.4466706243873728, 1.3509421250349525, 1.250452475220993, 1.1469052483948514, 1.0419956393278704, 0.9373662338740633, 0.834564892631986, 0.7350058172131461, 0.6399347797193877, 0.550399383421624, 0.46722508841316984, 0.3909975836180323, 0.32205191985369724, 0.26046864191854124, 0.20607697538162248, 0.15846494051770077, 0.11699608629146599, 0.08083236599334931, 0.048962517394742666, 0.02023516813320299, -0.006604234951532787, -0.03287367255164393, -0.0599130487165446, -0.08904205420470844, -0.12151853247644434, -0.15849847096127667, -0.20099869890275662, -0.249863303939654, -0.30573468436375445, -0.36903003509707505, -0.43992392584913703, -0.518337473165443, -0.603934438113876, -0.6961244024655392, -0.7940729929287786, -0.8967189399242441, -1.0027975791796204, -1.1108702355936535, -1.2193587736604274, -1.3265844612090743, -1.4308101768187726, -1.5302848990063551, -1.6232893495470726, -1.7081816258106346, -1.7834416488022196, -1.8477132749888883, -1.8998429705229023, -1.938914024972683, -1.9642753862662168, -1.975564326711407, -1.972722298560588, -1.956003502992867, -1.9259758745317541, -1.8835143694041991, -1.829786636570266, -1.7662313393967473, -1.694529579512608, -1.6165700476996914, -1.5344086854122705, -1.4502237807094156, -1.3662675405007914, -1.2848152740637142, -1.2081133884154076, -1.1383274326194295, -1.0774914344860616, -1.0274597491504092, -0.989862585184661, -0.9660662914641653, -0.9571393789097177, -0.9638251180784422, -0.986521399576786, -1.025268373142465, -1.0797441971348614, -1.1492690375565897, -1.232817259288516, -1.329037556740885, -1.436280581370409, -1.5526334441169016, -1.6759603061529196, -1.8039481254374434, -1.9341565029840975, -2.0640704745153053, -2.191155022675457, -2.3129100439403403, -2.426924493786216, -2.5309284538252754, -2.622841914976488, -2.7008191500857883, -2.763287655790636, -2.8089807742345454, -2.8369632572735553, -2.8466492053576133, -2.8378119961687616, -2.810586009884349, -2.7654601539237276, -2.703263385449461, -2.62514261996758, -2.5325335944813654, -2.4271254194262313, -2.310819701034392, -2.1856852412894043, -2.0539094232182085, -1.9177474625366073, -1.7794707508932712, -1.6413155301458426, -1.5054331209905953, -1.3738428833411418, -1.2483890113337712, -1.1307021646501663, -1.0221668125717758, -0.923895020981076, -0.8367072490817199, -0.7611205460184357, -0.697344352251159, -0.6452839210952038, -0.6045511869909403, -0.5744827234971418, -0.5541642602553685, -0.5424610685367534, -0.5380533833856267, -0.5394759102866082, -0.5451603686298828, -0.5534799553445111, -0.562794571550907, -0.5714956438778142, -0.578049390388943, -0.5810374283245028, -0.5791936958140363, -0.5714367603995506, -0.5568967110204807, -0.534935973878183, -0.5051635526449457, -0.46744236573581377, -0.4218895334444718, -0.3688696510896983, -0.30898126628244854, -0.24303695440105275, -0.1720375519040134, -0.09714125803312508, -0.019628447952120796, 0.059136848918035036, 0.1377477654627269, 0.21479660903648062, 0.2889169387797239, 0.35882457553797004, 0.4233564388222359, 0.48150616066126645, 0.5324555086370328, 0.5756007577917297, 0.6105732807432497, 0.6372537739811641, 0.6557797021899276, 0.6665457174265995, 0.6701969916493588, 0.6676155848596346, 0.6599001523359418, 0.64833946850995, 0.6343804075471414, 0.6195911675110368, 0.6056206523646903, 0.5941550307307423, 0.5868725695902749, 0.585397892882301, 0.5912568378846983, 0.6058330756495919, 0.6303276257044397, 0.6657223305241932, 0.7127482634573533, 0.7718599270575734, 0.8432159599672029, 0.9266669130113491, 1.0217504828553605, 1.1276944086977756, 1.2434270485300263, 1.3675954611700434, 1.4985906332914365, 1.6345793116716563, 1.7735417343342783, 1.9133144043252945, 2.0516369203014646, 2.1862017721865046, 2.314705930553997, 2.4349030071678506, 2.5446547425969213, 2.641980585635267, 2.725104168271734, 2.792495548285797, 2.8429081876005085, 2.8754097560127625, 2.8894059939312347, 2.8846570308099984, 2.8612857341248223, 2.8197778526770843, 2.760973913134357, 2.6860530252772654, 2.5965089446293756, 2.494118926287929, 2.380906076329839, 2.2590960629259182, 2.131069184452056], [2.0394239977911073, 1.907457261486238, 1.7759368724244318, 1.64735915140615, 1.524126982666137, 1.4084980122179198, 1.3025362461282801, 1.2080681667772077, 1.1266443764211678, 1.059507644465451, 1.007568081016946, 0.9713859882944043, 0.9511627574988262, 0.9467399862862993, 0.957606795737237, 0.9829151304651973, 1.0215026360109707, 1.071922528532069, 1.132479707372279, 1.2012722153615079, 1.2762370281686166, 1.3551990556740765, 1.4359221674861067, 1.516161013053987, 1.59371239527495, 1.666464975243112, 1.732446134299767, 1.7898648965313544, 1.8371499183419675, 1.8729816790694362, 1.8963181546020882, 1.9064134208684531, 1.9028288117852892, 1.8854364423238623, 1.854415097156742, 1.810238674162239, 1.7536575552108433, 1.6856734496090695, 1.60750841406591, 1.5205688931799854, 1.4264057427911248, 1.3266712922185016, 1.2230745681595128, 1.1173358412665428, 1.0111416652849223, 0.9061015579921328, 0.8037074236313341, 0.7052967394085472, 0.6120204259373466, 0.5248161959191169, 0.44438803006191463, 0.37119226797645005, 0.3054306286484093, 0.24705029446964527, 0.19575100929553732, 0.1509989592286575, 0.11204702940684855, 0.07796086543006996, 0.04765001835275743, 0.01990332117581294, -0.0065724642001987, -0.033111774802602294, -0.061048251747597544, -0.09167275425949023, -0.1261925139750796, -0.16569253179322538, -0.2111002620273994, -0.2631545442293325, -0.32237963390056096, -0.38906505214670917, -0.46325182446357327, -0.5447255140552405, -0.633016279531912, -0.727406004953444, -0.8269423665722826, -0.9304595199339061, -1.0366049177941907, -1.143871608008823, -1.2506352152457425, -1.3551946847769845, -1.4558157639427025, -1.550776119798582, -1.6384109419727537, -1.717157859196365, -1.7856000069373914, -1.8425061219268515, -1.886866606251107, -1.9179245975091013, -1.9352012000387455, -1.9385141725201482, -1.9279895259330002, -1.9040656589834342, -1.8674898414549301, -1.8193070449477282, -1.7608413104693028, -1.6936700286075719, -1.619591685922458, -1.540587796292052, -1.4587798841153177, -1.3763825137835295, -1.2956534634698662, -1.2188422184167895, -1.1481380075404928, -1.08561862603601, -1.0332012752042659, -0.9925966091287808, -0.9652671070437205, -0.9523907919161104, -0.9548311922543088, -0.9731142984164919, -1.0074131002430706, -1.0575401136567226, -1.1229481143118625, -1.2027391010410782, -1.2956813154961315, -1.4002339518021563, -1.5145790059349853, -1.6366595433886764, -1.7642235097048289, -1.8948720753512898, -2.0261113975193514, -2.1554065993194866, -2.2802367136032444, -2.3981493155259184, -2.506813575554649, -2.6040705027336095, -2.6879792157067848, -2.756858174612507, -2.809320428160984, -2.8443020740206295, -2.8610832935529995, -2.859301499965983, -2.8389563277503673, -2.8004063862155446, -2.744357896289745, -2.671845522713108, -2.5842058986317085, -2.483044511905025, -2.3701967779908206, -2.2476842593101107, -2.1176671022706763, -1.9823938479789764, -1.8441498290910834, -1.7052053919389178, -1.567765179449232, -1.4339196766270281, -1.3056001574217087, -1.184538081271726, -1.0722298718453764, -0.9699078723957234, -0.878518115203853, -0.7987053707333269, -0.7308057596560222, -0.6748470223847075, -0.6305563508497531, -0.5973755006987642, -0.5744827234971416, -0.5608208922753907, -0.5551310439981547, -0.555990432895028, -0.5618540822590139, -0.5710987418625764, -0.5820681054903071, -0.5931181194704007, -0.6026612190058167, -0.6092083643229059, -0.6114078122009762, -0.6080796486442238, -0.5982452229673232, -0.5811507594418315, -0.5562845764164676, -0.523387510560336, -0.48245632132013105, -0.43374003332786876, -0.37772935771755534, -0.315139512471061, -0.2468869324859657, -0.17406051773241582, -0.09788820866105723, -0.019699798386950133, 0.05911301193146639, 0.1371382371180246, 0.21298579073058377, 0.2853290913773237, 0.3529449721146473, 0.4147508159152694, 0.46983791136558267, 0.5175001198281047, 0.5572570658420717, 0.5888712034942535, 0.612358269318119, 0.6279908029900373, 0.6362945963757379, 0.6380381148081137, 0.6342151172109795, 0.626020879194728, 0.6148225910354559, 0.6021246562444919, 0.5895297523201867, 0.5786966297720701, 0.5712957156735011, 0.5689636514923454, 0.5732579300946221, 0.5856128026442815, 0.607297602397318, 0.6393785796128709, 0.6826852612082095, 0.73778224229685, 0.804947186948785, 0.8841556655655197, 0.9750732898467374, 1.07705542753495, 1.1891545923720965, 1.3101354146084208, 1.4384969086836066, 1.5725015720447755, 1.7102106770259087, 1.8495249605878625, 1.9882297784453618, 2.124043674166619, 2.2546692231586047, 2.3778449483612967, 2.4913970706079303, 2.593289852885626, 2.6816733243306476, 2.75492722614634, 2.811700106436264, 2.8509426021937547, 2.8719340817213586, 2.8743019763193693, 2.8580333024215263, 2.823478060290371, 2.771344388421769, 2.702685549250359, 2.6188790168085885, 2.521598125914159, 2.412776920632148, 2.2945690028270564, 2.1693013256013916, 2.0394239977911086], [1.9474452662692847, 1.8163827262871277, 1.687397998954817, 1.5629353431855213, 1.445313204010084, 1.3366743115546293, 1.238939863280488, 1.1537688463592157, 1.0825234336480625, 1.0262412409914117, 0.9856150690637311, 0.9609805737095328, 0.952312119103648, 0.9592268726793344, 0.9809970044170407, 1.0165696605367587, 1.064594197576679, 1.1234559917411282, 1.1913159844083363, 1.2661549915244608, 1.3458216954783584, 1.4280831555603217, 1.5106766192065582, 1.5913613921625176, 1.667969531968661, 1.7384541655408123, 1.8009342971014946, 1.8537350656210285, 1.8954225288769755, 1.9248321912543085, 1.941090650964381, 1.9436299154858563, 1.9321941174012909, 1.9068385518513125, 1.86792114685624, 1.8160866640511277, 1.7522441053363138, 1.6775379661711967, 1.5933141246697515, 1.5010812836549368, 1.4024689872745992, 1.299183312146462, 1.1929613834122237, 1.085525887369834, 0.9785407440772762, 0.8735690657781664, 0.7720344612181492, 0.6751866536341323, 0.5840722637991455, 0.4995114719866453, 0.4220811175963886, 0.3521046264121833, 0.2896489773289232, 0.23452873741040597, 0.1863170109540071, 0.14436296947667074, 0.10781545971564942, 0.07565203014448361, 0.046712577090640854, 0.019736692821478982, -0.006596297068172775, -0.03362568858643863, -0.06266726934884129, -0.09497183869775162, -0.13168549610368768, -0.17381277040909074, -0.22218358928809306, -0.277424989374253, -0.3399383453478156, -0.4098827539572264, -0.4871650500681856, -0.5714367603995503, -0.6620981209499479, -0.7583091007846523, -0.8590071924788212, -0.9629315527217236, -1.068652909863748, -1.1746085027731263, -1.2791411811490259, -1.3805416848467924, -1.4770930317078859, -1.5671158821385438, -1.6490137158664984, -1.7213166528335304, -1.7827227762290674, -1.8321358706739466, -1.8686985712355275, -1.89182002731267, -1.9011973168431122, -1.896829997546055, -1.8790273493068275, -1.8484080412152912, -1.8058921437531887, -1.7526855965576618, -1.690257430353788, -1.6203102233672133, -1.5447444432661284, -1.4656174811707219, -1.3850983206059408, -1.305418898024702, -1.2288232998097088, -1.1575160012126744, -1.0936103839314326, -1.0390787700994117, -0.9957051812534838, -0.9650419719870005, -0.9483714008489936, -0.9466730876813642, -0.960598169706675, -0.9904508115855032, -1.036177551152826, -1.0973647768250645, -1.173244439256841, -1.2627079034272666, -1.3643276527374169, -1.4763863686516236, -1.5969127325082646, -1.7237231346842494, -1.8544683342694068, -1.9866839932674025, -2.11784391600486, -2.2454147591858282, -2.3669109424728236, -2.4799484844809343, -2.582296514761341, -2.6719252680987258, -2.7470494518898922, -2.806165988444324, -2.848085269035077, -2.871955212130286, -2.877277590648837, -2.8639162780962444, -2.8320972565314824, -2.7824004257811645, -2.7157434483652065, -2.6333580534788656, -2.5367594014980237, -2.427709273515532, -2.308173994430343, -2.180278119624941, -2.0462550113653037, -1.9083954994550132, -1.768995859771002, -1.6303063532248412, -1.4944815462979115, -1.3635335832049413, -1.2392895002921682, -1.1233535675151096, -1.0170755124510507, -0.9215253325469036, -0.837475234942378, -0.7653890644029245, -0.705419393106397, -0.6574122558990989, -0.6209193258902727, -0.5952171425635924, -0.5793328324629881, -0.5720756051989752, -0.5720731688830978, -0.5778120925219525, -0.5876810512213366, -0.6000158254718206, -0.6131448898355281, -0.6254344198387654, -0.6353315688682492, -0.6414049187046932, -0.6423810866212197, -0.6371765766556753, -0.6249240900342675, -0.6049926565135659, -0.5770011108726155, -0.540824612792531, -0.4965940894903162, -0.4446886641364692, -0.38572131463425113, -0.32051818218287825, -0.25009211277134563, -0.17561116322214385, -0.09836293287975417, -0.01971568925368125, 0.058922661821573595, 0.13614665572855597, 0.210595265734862, 0.28099268651304427, 0.3461868055777525, 0.4051843232903121, 0.4571815684080697, 0.501590167047059, 0.5380568555845048, 0.5664768791043666, 0.5870005826709137, 0.6000329788174429, 0.6062262567089439, 0.6064653818731972, 0.6018471155493148, 0.5936529550082825, 0.5833166562793557, 0.5723871444938742, 0.5624877408616384, 0.555272735948062, 0.5523824138219229, 0.5553976788342152, 0.565795455000483, 0.5849060166471811, 0.6138733683412119, 0.6536197230789544, 0.7048150319073408, 0.7678523978977269, 0.8428300656221142, 0.9295405174625799, 1.0274670341487948, 1.135787893155909, 1.2533881895511614, 1.3788790742393588, 1.5106240190374445, 1.6467715412284696, 1.7852936566190056, 1.9240291837508499, 2.0607308964774425, 2.193115420776658, 2.3189146970158325, 2.4359277828361177, 2.5420717556052717, 2.635430487488365, 2.7143001103457824, 2.777230060886451, 2.823058697062498, 2.850942602193755, 2.8603788407432864, 2.8512195954702415, 2.823678795848428, 2.778330537784118, 2.716099290169621, 2.638242079907508, 2.546323038951303, 2.442180879947319, 2.3278900367566986, 2.20571635833846, 2.0780683754603686, 1.947445266269286], [1.8559111715761123, 1.7268558293192071, 1.6014804959401596, 1.4821567010481218, 1.3710988555661976, 1.2703166735134246, 1.1815723258296256, 1.1063433129915214, 1.0457919061355023, 1.000741849067807, 0.9716628397492099, 0.9586631238320967, 0.9614903391422587, 0.9795405533594188, 1.0118752423507607, 1.057245768391772, 1.1141247404430101, 1.1807434770350604, 1.2551346500574363, 1.335179068279957, 1.4186554656221493, 1.5032920932574252, 1.5868188781351222, 1.667018904239751, 1.7417779969520262, 1.8091312445535686, 1.8673053728208473, 1.914755996685666, 1.950198904360662, 1.9726346808291373, 1.981366145380407, 1.976008257742142, 1.9564903348377514, 1.923050610619355, 1.8762233600726594, 1.8168189906913041, 1.7458976759776408, 1.6647372616292402, 1.5747963121864355, 1.4776732806976598, 1.3750628736209705, 1.2687107455686955, 1.160367692148459, 1.051744513308859, 0.9444686942504336, 0.8400439968374153, 0.7398139729866257, 0.6449303048405225, 0.5563267474031608, 0.4746993010391959, 0.4004930775900421, 0.333896149010122, 0.2748404858066806, 0.2230099087796139, 0.1778547962519341, 0.1386131147378619, 0.10433717821226318, 0.07392539392786623, 0.04615812478566746, 0.01973669282147898, -0.006675531918607454, -0.03441106595999303, -0.0647564038987555, -0.09891139577229227, -0.13795100574785776, -0.18279048591573258, -0.23415491072094943, -0.2925539049510393, -0.3582622640612669, -0.4313070133511923, -0.5114612859535012, -0.5982452229673229, -0.6909339168299039, -0.7885722357846219, -0.8899961877117262, -0.9938603101965491, -1.098670414873502, -1.2028208718482545, -1.3046354979996384, -1.40241101432826, -1.4944619648009558, -1.579165944243017, -1.6550079669633557, -1.7206228214460848, -1.7748342993510013, -1.8166902582483648, -1.8454925752735256, -1.8608211708597036, -1.8625514249180855, -1.8508644687717124, -1.8262500108519637, -1.789501538320115, -1.7417039258223628, -1.6842136718339287, -1.6186321677890685, -1.5467725808236954, -1.4706210930852552, -1.3922933851260824, -1.3139873742527175, -1.237933317733655, -1.1663424629458783, -1.1013554699993449, -1.0449918459579897, -0.9991016130503838, -0.9653203865557151, -0.9450289624239038, -0.9393184119202822, -0.9489615531250433, -0.9743915200279817, -1.015687982839205, -1.0725713920352926, -1.1444054279762212, -1.2302076423014152, -1.3286680815107745, -1.438175491936489, -1.5568505233833787, -1.6825851805070005, -1.813087620624536, -1.9459312677945875, -2.0786071088148446, -2.2085779598247965, -2.333333444352706, -2.450444406087423, -2.557615492821484, -2.6527346915841834, -2.733918667901002, -2.7995528625981136, -2.848325425164182, -2.87925421031783, -2.8917062305019177, -2.885409137479633, -2.8604544966372027, -2.8172928133583826, -2.7567204671542744, -2.6798589013277376, -2.5881265991522318, -2.4832045474020608, -2.3669960404691426, -2.241581809559349, -2.1091715684222443, -1.9720531471766853, -1.8325404371594656, -1.6929213911643712, -1.5554073145107652, -1.4220846433895642, -1.2948703389247562, -1.1754719301177503, -1.0653531187366112, -0.9657057173052975, -0.8774285312057866, -0.801113621535778, -0.7370402011178684, -0.6851762265180317, -0.6451875588081228, -0.6164543798087231, -0.5980943732719167, -0.5889920162781307, -0.5878331790619726, -0.5931441051486566, -0.6033337411515429, -0.6167383093293187, -0.6316669678451523, -0.6464473847222084, -0.6594700621315921, -0.6692302875217735, -0.6743666561151278, -0.6736952036680719, -0.6662383066709038, -0.6512476463126723, -0.6282206889978755, -0.596910305990789, -0.5573273335662676, -0.5097360583302364, -0.45464279549932035, -0.39277790626786857, -0.3250717694382626, -0.2526253779816176, -0.1766763692106793, -0.0985614143075106, -0.019675986108390914, 0.058567409036420735, 0.1347814105215716, 0.20764525897250402, 0.2759444121342829, 0.33860725307429307, 0.39473789780385854, 0.44364421017720834, 0.4848602556937591, 0.5181625694860018, 0.5435797736914749, 0.5613952515430677, 0.5721427655157043, 0.5765950901858774, 0.5757459124520634, 0.5707854278153862, 0.5630702270618748, 0.5540882187062838, 0.5454194651010761, 0.5386939207889813, 0.5355471476338498, 0.5375751402680389, 0.5462894258832446, 0.5630736035159887, 0.5891424596227567, 0.62550473952582, 0.6729305695847766, 0.7319244147476376, 0.8027043231366996, 0.8851880567817865, 0.9789865392744547, 1.0834048711322866, 1.1974509764823398, 1.319851754936801, 1.4490764249555026, 1.5833665642400734, 1.7207721832956806, 1.8591930144681528, 1.9964240643817357, 2.130204366155855, 2.258267781899939, 2.3783946479779456, 2.48846302691602, 2.586498331394241, 2.6707201175675466, 2.739584906307194, 2.791823980418019, 2.8264752213479802, 2.8429081876005102, 2.8408417956460252, 2.820354138770732, 2.781884165761905, 2.7262251350759525, 2.654509956450546, 2.5681887260174476, 2.4689989481100354, 2.3589291125664476, 2.24017645611092, 2.115099876442702, 1.9861690845444229, 1.8559111715761134], [1.7655961335723442, 1.6396340086422074, 1.5189112643340774, 1.4057066488591874, 1.302111824304688, 1.2099865137393082, 1.1309189891016338, 1.0661928081467147, 1.0167605592274498, 0.9832252050889178, 0.9658294352468393, 0.9644532453367178, 0.97861976571994, 1.007509165395954, 1.0499802656729156, 1.1045993157516352, 1.169675213804488, 1.2433003063653965, 1.3233957695299123, 1.4077604707048936, 1.4941221319469156, 1.5801895671200377, 1.6637047463064978, 1.7424934524980997, 1.8145133372125752, 1.8778982522111898, 1.9309978321239853, 1.9724114250361744, 2.0010156118698426, 2.0159847171012464, 2.0168038889425377, 2.003274512210455, 1.9755119071009946, 1.9339354572747722, 1.879251496325395, 1.8124294582680107, 1.7346719607989904, 1.64737963573601, 1.5521116456889767, 1.4505429266054157, 1.344419269953157, 1.2355114041874438, 1.125569251745124, 1.0162775247944202, 0.9092137807637078, 0.8058099884233846, 0.7073185588471393, 0.6147836754296654, 0.5290186163730922, 0.45058960527061964, 0.3798065546300289, 0.31672088772851753, 0.26113044062087826, 0.21259126307981485, 0.1704359593548937, 0.13379804138516022, 0.10164161273214889, 0.07279556490392221, 0.045991352355229845, 0.01990332117581292, -0.00680949838881388, -0.035461262275297896, -0.06729798037370374, -0.10345809504759158, -0.1449360338608247, -0.19254972277750215, -0.24691294352956178, -0.30841329348799934, -0.3771963613969313, -0.453156571399546, -0.535934974969758, -0.6249240900342672, -0.7192797032902891, -0.8179393701370278, -0.9196471713486468, -1.022984121074723, -1.1264034711479936, -1.2282700258255888, -1.3269024723407146, -1.4206176487979887, -1.507775614188413, -1.586824357133883, -1.6563429811866168, -1.715082235161528, -1.7620013163871586, -1.7962999615204465, -1.8174449515917723, -1.8251902925029364, -1.8195904859968162, -1.8010064753701902, -1.7701040307337559, -1.7278445259678963, -1.6754682490316466, -1.6144705742435914, -1.5465715049072426, -1.4736792627090989, -1.3978487524635674, -1.3212358631902026, -1.2460486758398661, -1.1744967314572243, -1.1087395690311437, -1.0508357682837965, -1.0026937284515594, -0.9660253797274301, -0.9423039602233789, -0.9327268995563839, -0.9381847326404473, -0.9592368267939512, -0.9960945452329488, -1.0486122942888407, -1.1162867145282043, -1.1982640819153163, -1.2933557889716847, -1.4000615823376947, -1.5166000469571959, -1.6409456528379456, -1.7708715222538993, -1.90399693722059, -2.0378384924752986, -2.1698637108404015, -2.297545877910823, -2.418418822959948, -2.5301303735455387, -2.630493242512283, -2.717532167173617, -2.789526209925779, -2.845045245218794, -2.882979796860069, -2.9025635486618833, -2.903388026582664, -2.8854091374796336, -2.848945443826477, -2.794668250519401, -2.723583774405172, -2.6370078546832185, -2.536533838304279, -2.4239944346433204, -2.3014184741904806, -2.170983623395155, -2.034966199301278, -1.895689291052584, -1.7554704292441619, -1.616570047699692, -1.4811419555564114, -1.3511869812827664, -1.2285108659035557, -1.114687372419911, -1.0110274449783985, -0.9185550981201477, -0.8379905472657482, -0.769740910687291, -0.713898625089557, -0.6702475262404014, -0.6382763575809075, -0.6171992880693655, -0.6059828501499828, -0.603378553876663, -0.6079602976591189, -0.6181655831393171, -0.632339454087715, -0.6487800190308073, -0.6657843859957873, -0.6816938359740556, -0.6949370894137796, -0.7040705764672357, -0.7078147053403612, -0.7050852317415166, -0.6950189633033977, -0.6769931826048771, -0.6506383372291384, -0.6158437209712745, -0.5727560523962337, -0.5217710408366971, -0.46351821096079665, -0.39883943066004324, -0.3287617488285117, -0.2544652955467871, -0.17724712357334801, -0.09848197370163378, -0.019581024857654155, 0.05805025917532393, 0.13305405208930307, 0.20416072883561268, 0.2702269789266541, 0.33027044104823483, 0.3834999209425855, 0.42934036884935645, 0.46745192838862515, 0.4977425222092237, 0.52037360712843, 0.535758908622467, 0.5445561269098199, 0.5476517898835792, 0.5461396071567334, 0.5412928499429966, 0.5345314390727743, 0.5273845641241275, 0.521449776836775, 0.518349598586856, 0.5196867522325023, 0.5269991712464822, 0.5417159525809303, 0.5651154037363499, 0.5982862893464228, 0.642093309287665, 0.6971477406306401, 0.7637840520831347, 0.8420431549555709, 0.9316627926553814, 1.0320753952820354, 1.1424135413841725, 1.2615229799264376, 1.387982976690746, 1.5201335654051293, 1.6561091094427027, 1.7938774193288467, 1.9312835285661063, 2.0660971090313263, 2.1960624104900157, 2.3189495390795787, 2.4326058487448203, 2.5350062086636194, 2.624300929040409, 2.698860176883959, 2.7573137913995485, 2.7985855135779825, 2.82192077395126, 2.8269073331970924, 2.8134882386717117, 2.7819667419512975, 2.733003013644774, 2.6676026874507492, 2.587097460897298, 2.493118170653591, 2.387560941082853, 2.2725471713954417, 2.1503782752779235, 2.023486213581047, 1.8943809624396064, 1.7655961335723453], [1.6772642583475135, 1.55545520032738, 1.4403888771989608, 1.3342319886542793, 1.2389357717270162, 1.1561942526836777, 1.0874084032461275, 1.0336570232640925, 0.9956750112555812, 0.9738395077891767, 0.9681642087983553, 0.9783019511754066, 1.0035554761366907, 1.0428960816751687, 1.09498968864348, 1.158229670177959, 1.2307756355195987, 1.3105972206487135, 1.395521822866518, 1.4832851272912966, 1.5715832123064941, 1.6581249897227768, 1.740683734484703, 1.817146488106675, 1.8855601788585867, 1.9441733885114663, 1.9914728079840367, 2.026213559659329, 2.047442719064167, 2.0545155391476593, 2.047104062304476, 2.0251979940398726, 1.9890979030823133, 1.9394010010894105, 1.876979936211501, 1.802955204211834, 1.7186619344304683, 1.625611941860978, 1.5254520477208724, 1.4199197564504495, 1.310797435024577, 1.1998661694536656, 1.0888604727545044, 0.9794249885983446, 0.8730742761382269, 0.7711566757383227, 0.6748231447076533, 0.5850018195278822, 0.5023789098545246, 0.4273863636168803, 0.36019656606134903, 0.30072415304970673, 0.24863483495765454, 0.2033609467681201, 0.16412326698009683, 0.1299584871179751, 0.09975156897902558, 0.07227210193744754, 0.046213670769554904, 0.020235168133202967, -0.006997063061833591, -0.03676739239630652, -0.07027049588663148, -0.1085734693903757, -0.15258148394399157, -0.20300791343444385, -0.26034974898329355, -0.3248689773816555, -0.3965804463235723, -0.4752465709541606, -0.5603790586334079, -0.651247646312672, -0.7468956621510341, -0.8461620445964694, -0.9477092826507917, -1.0500565847375418, -1.15161744448179, -1.2507406533466077, -1.3457537154934078, -1.4350075518897691, -1.516921340371945, -1.590026327172613, -1.653007463711852, -1.7047417698469713, -1.744332400180404, -1.771137491627224, -1.7847929957783097, -1.7852288455964238, -1.7726779690626249, -1.7476778385266651, -1.7110644293503492, -1.6639586503832504, -1.6077454971786753, -1.5440463619513758, -1.474685107524113, -1.4016486715697776, -1.327043108332584, -1.2530460941525559, -1.181857017498571, -1.1156458414206916, -1.0565019646136307, -1.0063843156029684, -0.9670738926263626, -0.9401299100316293, -0.926850631638299, -0.9282398644030475, -0.9449799544491919, -0.9774119752232346, -1.0255236279076112, -1.0889451913611257, -1.166953667221862, -1.258485070058706, -1.3621546173719574, -1.476284384585104, -1.5989378105765455, -1.7279602741666586, -1.8610248153477569, -1.9956819505170742, -2.1294124316022485, -2.259681727196852, -2.3839949614174882, -2.4999510342029643, -2.6052946655041636, -2.6979651548133896, -2.776140725564963, -2.838277429204826, -2.8831417136094246, -2.9098359118661556, -2.9178160765172505, -2.9069017670916093, -2.8772775906488377, -2.8294864914587516, -2.7644149820538853, -2.683270698949039, -2.587552847676582, -2.479016269037769, -2.3596300075686227, -2.2315313905644505, -2.096976728538754, -1.9582898232631165, -1.8178095157708478, -1.6778375228506415, -1.5405877962920524, -1.4081385949039924, -1.2823883862804994, -1.1650165953111027, -1.0574500920620995, -0.9608361660231146, -0.8760225704698055, -0.8035450439168125, -0.7436225297270083, -0.6961601245228727, -0.6607595958331688, -0.6367371241071896, -0.6231477484112401, -0.6188158331138258, -0.6223707286405185, -0.6322866764594569, -0.6469259098289307, -0.664583829873794, -0.6835350929626888, -0.7020794311278636, -0.7185860426642783, -0.731535434585508, -0.7395576710947468, -0.7414660807485332, -0.7362855969999028, -0.7232750491746505, -0.7019428800238616, -0.6720559377592168, -0.6336411705558694, -0.5869802353395529, -0.5325972156118021, -0.47123982048992263, -0.40385460457154626, -0.3315569014582493, -0.2555962989316806, -0.17731859746997247, -0.09812528316559678, -0.01943160891662266, 0.05737558756012103, 0.130979194665726, 0.20017115602591395, 0.26388875896226244, 0.3212469027017687, 0.37156547107598176, 0.41439106139470944, 0.44951246745801643, 0.4769694765943085, 0.49705471408526514, 0.5103084489707973, 0.5175064584454916, 0.5196412292195995, 0.5178969487270119, 0.5136189024864902, 0.5082780421013173, 0.5034316175341931, 0.5006808741100943, 0.5016268964270039, 0.5078257358660258, 0.5207439842408562, 0.5417159525809301, 0.571903581107777, 0.6122601448810868, 0.6634987308201483, 0.7260663479911023, 0.8001243969653238, 0.8855360690361286, 0.9818610759473504, 1.0883579297405168, 1.2039938048523935, 1.327461825346153, 1.4572054338472291, 1.5914493200263127, 1.7282362197965406, 1.8654687459506312, 2.000955280542268, 2.1324588522144734, 2.257747840623754, 2.3746472971910295, 2.481089648027121, 2.5751635517003, 2.655159721461818, 2.7196125878022643, 2.767336771232553, 2.79745745473618, 2.809433887558225, 2.803075413452224, 2.7785495932899753, 2.736382179759525, 2.67744889616292, 2.6029591673423775, 2.5144321437267605, 2.4136655446841306, 2.302698020260325, 2.1837658867448826, 2.059255227501697, 1.9316504627969606, 1.803480578193525, 1.6772642583475146], [1.5916628735366516, 1.4750315951844142, 1.3665776694617584, 1.268337428401384, 1.1821051958254787, 1.109394997216339, 1.0514086875082091, 1.009011225806373, 0.9827136554970575, 0.9726641644148165, 0.9786474071630143, 1.000092075030157, 1.0360865029988477, 1.0854019128725796, 1.146522711177127, 1.2176830946042851, 1.2969090683723763, 1.3820648575379737, 1.4709025910186149, 1.5611140652691482, 1.650383350909504, 1.736438992124243, 1.8171045655963602, 1.8903464126033451, 1.9543174334606732, 2.0073959358114566, 2.0482186547399874, 2.0757072101504748, 2.089087431608266, 2.0879011587784664, 2.072010312288594, 2.041593220653629, 1.9971333791079728, 1.9394010010894107, 1.8694278981574342, 1.7884763849992384, 1.6980030489397715, 1.5996183445443213, 1.4950430705445377, 1.3860628561094155, 1.2744818247727798, 1.1620766161828617, 1.050551928057773, 0.9414986938528144, 0.836355936936435, 0.7363772414883478, 0.6426026564761297, 0.555836705112545, 0.47663301181920886, 0.4052858860019553, 0.3418290212609146, 0.28604128458767725, 0.23745938729524624, 0.19539705249729242, 0.1589701273615601, 0.12712693630282512, 0.09868303757829923, 0.07235943376200832, 0.046823199114257204, 0.020729426118227125, -0.007236639055658856, -0.038318405871164536, -0.07364880161122071, -0.11421424041897134, -0.1608226720300491, -0.2140765768612147, -0.27435164562778236, -0.34178173409998536, -0.4162505207113121, -0.4973901206229653, -0.5845867289355824, -0.6769931826048766, -0.7735481499038128, -0.8730014825661135, -0.9739451034582945, -1.074848655891988, -1.1740990132510343, -1.2700426427344083, -1.3610297374103615, -1.4454589785119394, -1.5218217663695504, -1.5887447642437718, -1.6450296345262367, -1.6896889105180901, -1.7219770377571224, -1.7414157344501418, -1.7478129581544988, -1.7412749220637551, -1.7222107752369307, -1.691329742640316, -1.649630708445172, -1.5983844149823125, -1.5391086353890198, -1.473536855660593, -1.4035811670905063, -1.3312902188009839, -1.2588032084815726, -1.188300994315423, -1.121955489705456, -1.061878552784097, -1.0100716034644965, -0.968377191361052, -0.9384336984116395, -0.9216342913544416, -0.9190911429530157, -0.9316058193116983, -0.9596465866951416, -1.003333228432834, -1.0624297846957294, -1.136345439495984, -1.2241435847694195, -1.3245588955963896, -1.4360220582821412, -1.5566916088547775, -1.6844921680560558, -1.8171582042985115, -1.9522823221341685, -2.087366963813558, -2.219878328212742, -2.3473012568227065, -2.4671938119796697, -2.577240278680893, -2.6753013580410983, -2.7594603868153484, -2.828064511833555, -2.8797598683628647, -2.9135199544085713, -2.9286665552969593, -2.9248827505964283, -2.902217724194061, -2.8610832935530004, -2.802242271076333, -2.726788964302815, -2.636122307646108, -2.5319122920457495, -2.4160605160156954, -2.290655818356255, -2.1579260659427937, -2.020187256809132, -1.8797911571454995, -1.7390727194713613, -1.6002985274962844, -1.4656174811707225, -1.3370148740190249, -1.2162709256282025, -1.1049247174080952, -1.0042443423363083, -0.9152039228025334, -0.8384679787843817, -0.7743834457040795, -0.7229794519765564, -0.6839747751593724, -0.6567927074809161, -0.6405828809986679, -0.6342494341681456, -0.6364847493205805, -0.6458078581771383, -0.660606503290524, -0.6791817598395068, -0.6997940664998834, -0.720709487472649, -0.7402450307358687, -0.7568118800303629, -0.768955459085684, -0.7753913345256643, -0.7750360764762694, -0.7670323302348183, -0.7507675050121666, -0.7258856528395945, -0.6922922879960512, -0.6501520802676501, -0.5998795393720084, -0.5421229883180537, -0.47774229577601396, -0.40778099736169426, -0.33343357907140686, -0.25600881933587716, -0.17689018619904495, -0.09749436046273872, -0.019229002411769038, 0.05654910221796904, 0.12857439248352753, 0.1957102941346802, 0.256983376450084, 0.3116129812525034, 0.3590355190503191, 0.39892276571897245, 0.43119364885910466, 0.45601918200706887, 0.473820382949045, 0.48525919499317616, 0.4912226125580422, 0.4928003902120791, 0.4912568828331627, 0.4879977195639531, 0.4845321517656801, 0.48243203170346344, 0.48328847123613766, 0.48866729593680575, 0.5000644481000515, 0.5188625009637325, 0.5462894258832441, 0.5833807045780225, 0.630945801085684, 0.6895399045710415, 0.7594417271620745, 0.840637993632308, 0.9328150956444828, 1.0353582064660611, 1.147357966940243, 1.2676246646426215, 1.3947096402715677, 1.5269334730951871, 1.6624203252642102, 1.799137667310104, 1.934940468142369, 2.0676188158480913, 2.194947843554816, 2.3147387699051616, 2.4248898279971454, 2.5234358509437502, 2.6085953067325676, 2.6788136293108207, 2.73280177553552, 2.7695690468613696, 2.7884493477808645, 2.7891202068781404, 2.7716140571910133, 2.7363214562506615, 2.6839861182188067, 2.6156918262887636, 2.5328414881824814, 2.4371287864036275, 2.330503053277491, 2.215128164353518, 2.093336388456903, 1.9675782550000764, 1.8403695960982258, 1.7142369901897938, 1.5916628735366527], [1.5095162055903253, 1.3990436133049136, 1.2981021173398788, 1.2085804658978678, 1.13210090898833, 1.0699846902154506, 1.023224415773078, 0.9924639303723984, 0.9779861508866767, 0.979709118902633, 0.9971903377389509, 1.0296392625930149, 1.0759376190987, 1.1346670404221488, 1.2041433405842645, 1.2824565861569877, 1.3675159935951682, 1.4570985684856208, 1.5489003185774508, 1.6405888166051614, 1.729855862925896, 1.8144690024266306, 1.8923206848294463, 1.9614739215035253, 2.0202033835318907, 2.067031002752477, 2.1007552768504945, 2.120473637830324, 2.125597416389569, 2.115859118544427, 2.0913119207498205, 2.0523214810156474, 1.9995503514147013, 1.9339354572747727, 1.8566592758224676, 1.769115497992503, 1.672870087846403, 1.5696187613815753, 1.4611419878671044, 1.3492586702796194, 1.2357796856934955, 1.12246246109567, 1.010967725277877, 0.9028195141732195, 0.7993694169232164, 0.701765935425088, 0.6109296940629448, 0.5275350822489737, 0.451998744214675, 0.3844751524670462, 0.32485931796914536, 0.27279650605369127, 0.22769864697782505, 0.1887669584165662, 0.15502013839227868, 0.12532734514089774, 0.09844505878913594, 0.07305682151085072, 0.047814780503725854, 0.021381913484677835, -0.007526199448972553, -0.04010118042403305, -0.07740431555234081, -0.12033268465799858, -0.16958987393860953, -0.22566206715659684, -0.28880017108148587, -0.35900847406804226, -0.4360401668300202, -0.5193998759556923, -0.6083531780314294, -0.7019428800238621, -0.7990116744418487, -0.898230610255754, -0.9981326668552795, -1.0971505823975558, -1.1936579732109123, -1.2860126904245206, -1.37260129603368, -1.4518835048659513, -1.5224354323598215, -1.5829905109496512, -1.6324769896746893, -1.670051011176303, -1.6951243655993307, -1.7073861495041647, -1.7068177065722945, -1.6937003919873925, -1.668615879816165, -1.6324389181001444, -1.586322625096158, -1.5316766074692514, -1.470138362571955, -1.4035385977003794, -1.3338612551173883, -1.2631991687507023, -1.1937063933421768, -1.1275483365209176, -1.0668508864913995, -1.0136497611392816, -0.9698413074490397, -0.9371359530275528, -0.9170154548102822, -0.9106950049992394, -0.9190911429530153, -0.9427962867806976, -0.9820605430327684, -1.0367812808910961, -1.1065007728106497, -1.1904120111453405, -1.2873726145896922, -1.3959265440655737, -1.5143331597267415, -1.64060297364471, -1.7725392908176651, -1.907784788382065, -2.0438719628112323, -2.1782762804096123, -2.3084707998851735, -2.431980998849043, -2.546438529673702, -2.6496326544116684, -2.739558162859091, -2.8144586610285147, -2.87286422725178, -2.9136225671936016, -2.9359229539527627, -2.939312411388092, -2.9237037836389996, -2.889375527012486, -2.8369632572735553, -2.767443281111807, -2.682108530402329, -2.5825374972216935, -2.470556932068995, -2.3481992133964247, -2.2176554198581298, -2.0812252346786, -1.9412648818847549, -1.8001343351848305, -1.6601450510796245, -1.523509458168581, -1.3922933851260828, -1.2683725317640469, -1.1533939829614857, -1.0487436366734766, -0.9555202679610916, -0.874516784743127, -0.8062090519031802, -0.7507524729442027, -0.7079863272148028, -0.6774456705686049, -0.6583804228541416, -0.6497810914118158, -0.650410420055009, -0.6588401117438621, -0.6734916537652204, -0.6926801796024611, -0.7146602340840174, -0.7376722694313141, -0.7599886903615299, -0.7799582865769895, -0.7960479401908039, -0.8068805725742821, -0.8112683977524452, -0.8082406751691168, -0.7970653001700414, -0.7772637321990825, -0.7486189343598274, -0.7111761792595854, -0.6652367603391832, -0.6113448305444841, -0.5502677666078961, -0.4829706229357468, -0.4105853899707695, -0.3343759041261708, -0.2556993666500894, -0.17596551431377563, -0.0965945434846216, -0.018974919485804844, 0.05557779558885145, 0.12585999125735442, 0.19081588407207423, 0.24956925405089297, 0.3014501840352982, 0.34601607392960254, 0.38306635060304595, 0.4126504580865966, 0.4350688874198292, 0.45086718667483694, 0.46082307471317085, 0.4659269624772536, 0.4673563585046394, 0.46644479648741527, 0.46464606797662733, 0.46349466904324005, 0.46456347263048764, 0.4694197158133705, 0.47958044120069454, 0.4964685529411025, 0.521370639615017, 0.5553976788342144, 0.5994496724890706, 0.6541851688533673, 0.7199965104266464, 0.7969915073332421, 0.8849820787236764, 0.9834802328215234, 1.091701574279598, 1.2085763398686824, 1.332767774887739, 1.462697477758429, 1.59657716367029, 1.7324461342997683, 1.8682135936541573, 2.0017048236980046, 2.1307101308092955, 2.2530353979090245, 2.366553029283829, 2.4692520569523024, 2.55928618945616, 2.6350186259848067, 2.6950625298234985, 2.738316153587328, 2.763991732224062, 2.7716374053730943, 2.761151594841606, 2.7327894417238534, 2.6871610967015744, 2.6252218517192647, 2.548254296778834, 2.4578428772653647, 2.35584141031102, 2.24433428874243, 2.125592253969209, 2.0020237510068277, 1.8761229864447284, 1.7504158909221783, 1.627405239566108, 1.5095162055903277], [1.4315192524911562, 1.3281341474005373, 1.2355415549898165, 1.155466672086848, 1.0893459701094137, 1.0382967607116094, 1.0030940397331436, 0.9841551345692778, 0.981532494252663, 0.9949147677497805, 1.0236361189427192, 1.0666935312869428, 1.1227716659612048, 1.1902746590520796, 1.2673640802664727, 1.3520021317871838, 1.441999044650587, 1.5350635343438919, 1.6288551094734989, 1.7210369889402932, 1.8093283749422848, 1.891554851433795, 1.9656957297795632, 2.0299272438963514, 2.0826606041208966, 2.1225740496830228, 2.1486381907194074, 2.1601340984636654, 2.15666378241587, 2.138152881454799, 2.104845587346495, 2.057292009188672, 1.9963283713230915, 1.9230506106193557, 1.8387820975294231, 1.7450363450566067, 1.6434756873740088, 1.535867002421263, 1.4240356181884382, 1.309818579027268, 1.195018455396257, 1.0813588578697395, 0.9704427646823947, 0.8637146929221804, 0.7624276387944763, 0.6676155848596347, 0.580072225062293, 0.5003363954732236, 0.4286845240919935, 0.3651302312348251, 0.30943102755477003, 0.26110187426747816, 0.21943519428526176, 0.18352675812201621, 0.15230671876632307, 0.12457493898774717, 0.0990396460197787, 0.07435836496804783, 0.04918002571071026, 0.022187109894180934, -0.007863294429819635, -0.042100632975480105, -0.08150526436266, -0.12687703730056768, -0.17880891517432118, -0.23766636583019723, -0.3035730842810318, -0.37640345127050767, -0.4557819553186154, -0.5410896244626963, -0.6314773310071572, -0.7258856528395942, -0.8230708028251736, -0.921635977828823, -1.0200673351104106, -1.1167736798642691, -1.2101288467096336, -1.298515682586956, -1.3803704907412189, -1.4542267765517185, -1.5187571464507936, -1.5728122508769489, -1.6154557302127928, -1.645994217336292, -1.6640015694644597, -1.6693366424765026, -1.662154079410645, -1.6429077574195077, -1.6123467198675536, -1.5715036079301679, -1.5216757943356738, -1.464399606081263, -1.4014181984449172, -1.3346438050076506, -1.2661152336086794, -1.1979516025139176, -1.1323034114271284, -1.0713021157448728, -1.0170094177347155, -0.971367503887338, -0.9361514430759721, -0.9129249156155972, -0.9030003698550257, -0.9074046022786704, -0.9268506316382982, -0.9617165903915116, -1.012032191249025, -1.077473146938804, -1.1573637317505705, -1.2506874786476319, -1.3561058104789376, -1.4719842128659717, -1.5964253743513495, -1.7273085508384536, -1.8623342603610222, -1.9990732845069756, -2.135018847574024, -2.267640766349899, -2.3944403142206334, -2.513004524340288, -2.6210586683292507, -2.7165156891386846, -2.797521438312844, -2.862494667166036, -2.910160845955097, -2.9395790319418786, -2.9501611727283827, -2.9416834113797186, -2.914289150238914, -2.8684838263462016, -2.8051215482318708, -2.7253839367669963, -2.630751697041358, -2.5229696194193894, -2.4040058618553455, -2.276006498507713, -2.1412464284785995, -2.0020778205118863, -1.8608773227702642, -1.7199932901400288, -1.5816942743854085, -1.448119985141503, -1.3212358631902033, -1.2027923134155492, -1.0942895256674505, -0.9969486704724916, -0.9116900966535645, -0.8391189834440176, -0.7795187149449501, -0.7328520543598677, -0.6987700040616998, -0.6766280499298618, -0.6655093091623374, -0.6642539343242994, -0.6714939768182964, -0.6856927839016529, -0.7051878979670292, -0.7282363475801655, -0.7530611686161611, -0.7778979719311994, -0.8010403817988451, -0.8208832065363523, -0.8359622683221244, -0.8449899114298792, -0.8468853245856345, -0.8407989508968818, -0.8261304142898427, -0.8025395606637172, -0.76995039073597, -0.7285478452846713, -0.6787675875511677, -0.6212791073055574, -0.556962641971443, -0.48688056795550383, -0.4122440559682971, -0.33437590412617074, -0.25467055898406826, -0.1745524049567331, -0.0954334450900521, -0.01867150979525757, 0.05446988536637187, 0.12285895604986073, 0.1855293347619715, 0.24170911859511518, 0.2908444929133313, 0.3326172861109194, 0.36695596849392026, 0.39403977892531716, 0.414295841804914, 0.4283893196895603, 0.43720682876582095, 0.4418335208492272, 0.4435244021190813, 0.4436706111678518, 0.4437615132636845, 0.4453435805573985, 0.44997711641063814, 0.4591919437883532, 0.474443211121588, 0.49706847328938464, 0.5282471802067736, 0.5689636514923443, 0.6199745341011029, 0.6817816326168886, 0.7546108717196534, 0.8383980003728783, 0.932781481213618, 1.0371028305804968, 1.150414489000593, 1.2714951133892312, 1.3988719953974782, 1.5308501299367507, 1.6655472884361266, 1.8009342971014912, 1.9348795852346163, 2.065196955958323, 2.1896954443521635, 2.3062300682823436, 2.412752246679193, 2.5073586595254023, 2.5883373534780643, 2.6542099562194563, 2.703768949948803, 2.736109067824085, 2.7506520139262265, 2.747163864153129, 2.7257646785623915, 2.6869300408659442, 2.631484433529814, 2.5605865525466203, 2.475706859648615, 2.3785978567766444, 2.271257743433639, 2.1558882778187236, 2.0348478034247326, 1.910600520626944, 1.785663174791612, 1.662550396319123, 1.5437199622245599, 1.431519252491157], [1.3583319037563824, 1.2629031236397317, 1.1794252730780277, 1.1094454136982284, 1.0542021053184731, 1.0145993029273663, 0.9911878714788008, 0.9841551345692776, 0.9933226819254007, 1.0181524642863786, 1.0577610074984847, 1.1109413852315424, 1.1761924063572602, 1.2517543031460319, 1.3356500541583318, 1.4257313447091315, 1.5197280612227433, 1.6153001362220807, 1.710090509995828, 1.8017779543333805, 1.8881285135452948, 1.9670443579813954, 2.03660891436385, 2.0951272336989026, 2.1411606788793014, 2.1735551572925536, 2.1914622852281322, 2.1943530466069783, 2.1820236941728943, 2.154593832187319, 2.112496811135157, 2.0564627522551686, 1.9874946982426809, 1.9068385518513133, 1.815947612296175, 1.7164426467213272, 1.6100685374517023, 1.4986486228170341, 1.384037898186844, 1.2680762633711988, 1.1525429923340413, 1.0391135615879528, 0.9293199057757131, 0.8245150745826119, 0.725843146709527, 0.6342151172109796, 0.5502913176250835, 0.47447075798296406, 0.40688760030320426, 0.3474147890925907, 0.2956746803360733, 0.25105633110582937, 0.21273894176659047, 0.17972078607935202, 0.15085282524156524, 0.12487608353989678, 0.10046176879320243, 0.07625305248699676, 0.05090738414297881, 0.023138203020756584, -0.008245072022124957, -0.04429984725215785, -0.08591695215954293, -0.13379193016196916, -0.1884017984766673, -0.2499879110832301, -0.3185453996959341, -0.3938194963289317, -0.47530886171322284, -0.5622758610568875, -0.6537635470647924, -0.7486189343598261, -0.8455219839407848, -0.9430195652846055, -1.039563531004699, -1.1335519280080086, -1.2233722827042433, -1.3074458382503527, -1.3842715906301526, -1.4524689684304368, -1.5108180286057005, -1.558296096711595, -1.5941098636978, -1.6177220603597677, -1.6288719622910335, -1.6275891294142044, -1.61419995116586, -1.589326747032469, -1.5538793579463481, -1.5090393524279608, -1.4562371576049782, -1.3971226046932717, -1.3335295466926507, -1.267435358703837, -1.2009162645617601, -1.1360995440258452, -1.0751137597485876, -1.0200382004667592, -0.9728527648146023, -0.9353895080575572, -0.9092870418427229, -0.8959489154573063, -0.8965070175064878, -0.9117909214886754, -0.9423039602233777, -0.9882066558140594, -1.0493079576376767, -1.1250645549759184, -1.214588337867108, -1.3166618842728355, -1.429761658497807, -1.552088419703053, -1.6816041648731002, -1.816074772018227, -1.953117370611114, -2.0902513506875104, -2.2249518325330255, -2.354704357645472, -2.477059530226204, -2.5896863376072328, -2.6904229078072905, -2.7773235221232326, -2.8487007888633387, -2.9031619988794546, -2.9396388216723643, -2.957409659170495, -2.9561141489617215, -2.935759495539019, -2.896718502454905, -2.839719375436447, -2.7658275616949735, -2.6764200791271286, -2.573152966269362, -2.457922645440174, -2.332822133573503, -2.2000931543850877, -2.0620752988601976, -1.921153446381116, -1.7797046945915544, -1.6400460515164008, -1.5043841184589282, -1.374767937470976, -1.2530460941525565, -1.1408290572961473, -1.0394576041998764, -0.9499780276566899, -0.873124651496362, -0.8093100003218836, -0.7586227802378699, -0.7208336355923297, -0.6954084567815546, -0.681528830683724, -0.6781190528014792, -0.6838789629360439, -0.6973217280273735, -0.7168155800365251, -0.7406284262139032, -0.7669741859531963, -0.7940596741531751, -0.8201308463540565, -0.8435172458989372, -0.862673547272368, -0.8762171711468935, -0.8829610534010843, -0.8819407797073805, -0.8724354459141197, -0.8539817685766581, -0.8263811454598174, -0.7896995481944872, -0.7442603139159683, -0.6906300849826215, -0.6295983211785182, -0.5621509727336529, -0.48943905093114864, -0.4127429622893831, -0.33343357907140686, -0.252931100516209, -0.17266281367251685, -0.09402088869685128, -0.018321340323403698, 0.05323474497234757, 0.11959667697688572, 0.1798953728037264, 0.23346947038545837, 0.2798856368326219, 0.3189525154022365, 0.35072792051426965, 0.3755190661423991, 0.39387579452813576, 0.40657695491926144, 0.414610261278314, 0.419146129092537, 0.42150615019050974, 0.42312700678771203, 0.4255207482083653, 0.43023245273020694, 0.4387963702179363, 0.4526916867405366, 0.4732990689905769, 0.5018591335472845, 0.5394339440939262, 0.5868725695902735, 0.6447816397972758, 0.7135017138052661, 0.7930901352903463, 0.8833108886132255, 0.9836317965276025, 1.0932292174798597, 1.2110002128026103, 1.3355819662068356, 1.4653780545538264, 1.598590994529678, 1.7332603289278572, 1.867305372820844, 1.9985716175960053, 2.1248796927538836, 2.2440757140329635, 2.354081803692552, 2.452945555806704, 2.538887236615242, 2.6103435570160443, 2.6660069300985536, 2.7048592294327745, 2.726199191190066, 2.7296627520209538, 2.7152357813540933, 2.683258847364981, 2.63442384590015, 2.5697625164997926, 2.4906270645796798, 2.3986632990443177, 2.2957768754484364, 2.184093401867813, 2.065913313781063, 1.9436625518340054, 1.819840179215729, 1.6969641509808453, 1.5775164941329913, 1.4638891734794781, 1.3583319037563832], [1.2905733574739537, 1.2039024260008881, 1.1302280407423928, 1.0709060514028341, 1.0269666476144201, 0.9990928080787997, 0.9876066425810849, 0.9924639303723984, 1.0132569635820583, 1.0492256070845498, 1.0992762914073773, 1.1620084675600606, 1.2357478766499548, 1.3185858270951143, 1.4084235320209624, 1.5030204424186624, 1.6000454206586556, 1.6971295361608218, 1.7919192318965813, 1.8821286076814938, 1.965589593904875, 2.0402988466846477, 2.104460280952142, 2.156522269494117, 2.1952086707030625, 2.219543002341477, 2.228865249159001, 2.2228409744747197, 2.2014625953316878, 2.1650428728591735, 2.114200859300335, 2.049840726104039, 1.9731240690450123, 1.8854364423238625, 1.7883490102005184, 1.6835763186133765, 1.572931277684733, 1.4582785069018487, 1.34148722667271, 1.2243848821904755, 1.1087126581447209, 0.9960839865730676, 0.8879470665524888, 0.7855523056636965, 0.6899254620260785, 0.6018471155493149, 0.5218389317042499, 0.45015700477569676, 0.3867923846867812, 0.33147870669719587, 0.28370666123534377, 0.2427448664095526, 0.20766654274820798, 0.17738124253427645, 0.15067075841511893, 0.12622823097816582, 0.1026993953072261, 0.07872485415393138, 0.05298224156655592, 0.02422714618617942, -0.008668302214701292, -0.0466802169061298, -0.0906020540679165, -0.1410188601195708, -0.1982873637120809, -0.262522457067292, -0.3335904447627328, -0.41110926162126993, -0.4944556795497184, -0.5827793405897976, -0.6750232747318597, -0.7699503907359696, -0.866175270637169, -0.962200457797042, -1.05645630789875, -1.1473433752572344, -1.2332762357335043, -1.312727604256857, -1.3842715906301526, -1.4466249523542298, -1.4986852473540027, -1.5395648616864634, -1.5686199858195427, -1.5854737354880482, -1.5900327564520667, -1.5824968131687414, -1.5633610354623808, -1.533410680419834, -1.4937084543911838, -1.4455746274604693, -1.390560355382133, -1.3304147971802105, -1.2670467760289443, -1.2024818726568371, -1.1388159607576376, -1.0781662896896715, -1.022621288638368, -0.9741903066070154, -0.9347545129958771, -0.9060201637748874, -0.8894753887400064, -0.8863515771957475, -0.8975903344638135, -0.9238168523839054, -0.9653203865557134, -1.0220423651079762, -1.0935724723475988, -1.1791528601550885, -1.277690445098087, -1.3877770546956032, -1.5077169968424098, -1.6355614467394088, -1.769148880180337, -1.906150634785677, -2.044120555375398, -2.180547579225237, -2.312910043940344, -2.4387304569172468, -2.5556294519488576, -2.661377675810722, -2.753944395254162, -2.8315416915824048, -2.892663214045997, -2.936116592140296, -2.9610487573900763, -2.9669635937046452, -2.9537315177800925, -2.9215907828746097, -2.871140495918034, -2.8033255345539807, -2.7194137425696963, -2.6209659645842347, -2.509799649412395, -2.3879469021180038, -2.2576079937757374, -2.1211014422710055, -1.98081185458484, -1.8391367691101321, -1.6984337545140507, -1.5609690091292405, -1.428868662202566, -1.3040739066724731, -1.1883009943154232, -1.0830070005913048, -0.9893621214261068, -0.9082291011187511, -0.8401502136065774, -0.785342032862657, -0.7436980368450806, -0.7147988979027589, -0.6979301255854758, -0.6921065500073859, -0.6961029696344061, -0.7084901406245683, -0.7276751592198216, -0.7519451872099517, -0.779513395599852, -0.808565955079846, -0.8373088847861807, -0.8640135834716751, -0.8870599091705191, -0.9049757435920652, -0.9164720739716627, -0.9204727454446836, -0.9161381781045785, -0.9028825011573073, -0.8803837279703393, -0.8485867759915676, -0.8076993199266839, -0.7581806505588823, -0.7007238905374327, -0.6362320878495138, -0.5657888632685312, -0.49062442593898026, -0.4120778879607934, -0.33155690145824923, -0.2504957078522636, -0.17031272725844107, -0.0923688251712947, -0.017927373662428598, 0.051882824253419384, 0.1161007543955849, 0.1739616640649025, 0.22492002057425958, 0.2686663326745518, 0.3051373719471285, 0.3345195032932774, 0.3572450133487041, 0.37398150842963285, 0.3856146348401048, 0.39322454943665786, 0.3980567328076069, 0.40148788709361316, 0.40498779153613906, 0.4100780979370775, 0.4182891325409467, 0.4311158282245179, 0.4499739397859454, 0.47615769476782066, 0.5108000025612216, 0.554836286191921, 0.6089729155770154, 0.6736611102380561, 0.7490770461781455, 0.8351087491568518, 0.9313501886964571, 1.0371028079880438, 1.1513845388889636, 1.272946163046932, 1.4002946945470267, 1.531723281001985, 1.6653469531696625, 1.7991434021824209, 1.9309978321239867, 2.058750827323574, 2.180248091124649, 2.293390858162844, 2.3961857568049227, 2.4867929030834635, 2.563571042192798, 2.625118617630246, 2.6703097398848916, 2.698324144017621, 2.708670365725865, 2.7012015251617107, 2.676123283004089, 2.633993719815413, 2.5757150829952034, 2.5025175409590683, 2.415935276743673, 2.317775438351264, 2.2100806362596987, 2.0950858353855026, 1.975170625539343, 1.852807967687282, 1.7305106003310446, 1.6107763488906326, 1.496033609654558, 1.388588277927491, 1.290573357473956], [1.228816881606515, 1.1516312270841547, 1.0883660888304758, 1.0401746456449463, 1.0078700212936174, 0.9919084681290973, 0.9923806518569952, 1.009011225806372, 1.0411666861794546, 1.0878713032954626, 1.1478307325816448, 1.2194627276478793, 1.3009342106114514, 1.3902038059651043, 1.485068817301267, 1.5832155241754287, 1.682271601753472, 1.7798594204084028, 1.8736489671605545, 1.9614091460982184, 2.0410562602296403, 2.110698551421084, 2.168675776280004, 2.2135929214975927, 2.2443473091243495, 2.2601485068509386, 2.2605306365121227, 2.245356861306193, 2.214816023992244, 2.1694115998580346, 2.109943314823462, 2.0374819560730217, 1.9533380657558832, 1.8590253535681736, 1.7562197879046944, 1.646715424740733, 1.5323781060955342, 1.4150982041240354, 1.2967436015814453, 1.1791140843404646, 1.063898277288995, 0.9526341825008176, 0.846674279953978, 0.7471560288213444, 0.6549784646094927, 0.5707854278153864, 0.49495578735953366, 0.4276008412056541, 0.36856889186003033, 0.3174568105168665, 0.27362822510976514, 0.23623779893095984, 0.20426091202109645, 0.17652792108383655, 0.15176205865472203, 0.12861994152337292, 0.10573359422900357, 0.08175285740824612, 0.05538704374875443, 0.02544472643851743, -0.009129404288605541, -0.04922160293299378, -0.09552093200560254, -0.14849668407570826, -0.20838197452539986, -0.27516395585141096, -0.3485809315922005, -0.4281264679094411, -0.5130604180851713, -0.6024265943466454, -0.6950766470921593, -0.7896995481944858, -0.8848559267631559, -0.979016376336022, -1.0706027452559705, -1.1580313397275153, -1.239756913873199, -1.314316294476027, -1.380370490741219, -1.4367441713435496, -1.4824614515152372, -1.5167770205258468, -1.5392017524791752, -1.549522078142081, -1.547812549203903, -1.5344411951400607, -1.5100674525319304, -1.4756326328074605, -1.4323430822737826, -1.381646373319041, -1.325201043133036, -1.2648405617792748, -1.2025323607774103, -1.1403328827503967, -1.080339718867209, -1.024641981052182, -0.9752701081551817, -0.9341463280941038, -0.903036990728586, -0.8835079489817408, -0.8768840993179486, -0.8842140986554597, -0.9062411553753368, -0.9433806501471912, -0.9957051812534818, -1.0629374528617979, -1.1444512375544236, -1.2392804509392545, -1.3461361810623043, -1.4634313233941691, -1.5893122880751573, -1.7216970743943267, -1.858318852367115, -1.9967740565819978, -2.1345738865313484, -2.269198023167217, -2.3981493155259184, -2.5190081653431404, -2.629485342297515, -2.727471997788846, -2.811085710142264, -2.8787114872685753, -2.9290367718505492, -2.9610796361774465, -2.974209515363955, -2.9681600049349637, -2.9430334373214464, -2.899297147107046, -2.8377715321377863, -2.759610212061069, -2.6662727727683375, -2.5594907600406214, -2.4412277441987777, -2.3136344159057693, -2.1789997881195324, -2.039699667794118, -1.898143621163225, -1.7567216869016173, -1.6177520914663277, -1.483431190539922, -1.355786800547384, -1.2366359962359716, -1.1275483365209182, -1.0298153440655238, -0.9444269077988722, -0.8720551056687913, -0.8130457616498654, -0.7674178609166719, -0.73487075484921, -0.7147988979027585, -0.7063136760143135, -0.7082717156088959, -0.7193089075868944, -0.7378792456899392, -0.7622974666326647, -0.790784393048917, -0.8215138216882213, -0.8526597697728127, -0.8824428926227319, -0.9091749154708696, -0.9312999809790287, -0.9474318997726121, -0.9563864021029829, -0.9572076216717534, -0.9491881943122891, -0.9318825207616376, -0.9051129199473887, -0.868968582576507, -0.8237974197187161, -0.7701910828663903, -0.7089636060531087, -0.6411242826506942, -0.5678455353759886, -0.49042666417004394, -0.4102544598122974, -0.32876174882851167, -0.24738498551619678, -0.16752202850899567, -0.09049123171837584, -0.01749294294855607, 0.05042556107062055, 0.11240076539291909, 0.16777841040646407, 0.21613310137559172, 0.25728150082909396, 0.2912887381106492, 0.31846784737502565, 0.33937222729996996, 0.3547812981720657, 0.3656797101655179, 0.3732306260401779, 0.37874375783007275, 0.38363897639255856, 0.3894064313822497, 0.39756421425899546, 0.40961466588283285, 0.4270004712911319, 0.4510616962936099, 0.48299490318569976, 0.5238154365335487, 0.5743238957169698, 0.6350777105250016, 0.7063686120354059, 0.788206646325631, 0.8803112168322197, 0.9821094664058264, 1.0927421266420656, 1.2110767744731044, 1.3357282489636289, 1.4650857994452038, 1.5973463641046461, 1.7305532202391956, 1.8626391075876383, 1.9914728079840334, 2.114908071071623, 2.2308337093659176, 2.337223648307108, 2.4321857091238686, 2.514007924635411, 2.5812012400933346, 2.6325375316220803, 2.6670819818606324, 2.684218983483115, 2.6836708932267928, 2.66550912820658, 2.6301572785377654, 2.5783861011854814, 2.511300454851314, 2.4303184298294154, 2.3371431153621116, 2.2337276254730902, 2.1222341681719583, 2.0049880882755327, 1.8844279372976227, 1.7630527218786334, 1.6433675526323712, 1.5278289563270824, 1.4187911249579357, 1.318454355219011, 1.228816881606516], [1.1735849638850242, 1.10653176488535, 1.0541935883981979, 1.0175111980233944, 0.9970737924560595, 0.9931070658451844, 1.0054695090277932, 1.0336570232640916, 1.0768157208351234, 1.1337625928417985, 1.2030135384778222, 1.2828180764563069, 1.3711999023592878, 1.4660023192472622, 1.5649374562033935, 1.6656381032990923, 1.765710933807365, 1.862789856708396, 1.9545882452442935, 2.0389488203537014, 2.1138900303734327, 2.17764785883241, 2.228712108199126, 2.265856346168621, 2.2881608590266382, 2.295028129878593, 2.2861905437817414, 2.261710212510251, 2.221971004105598, 2.16766305177662, 2.099760198457372, 2.0194910029489868, 1.9283040869163857, 1.8278287353462697, 1.7198317731679615, 1.6061718249453016, 1.488752120866266, 1.3694730393844046, 1.2501855742280419, 1.1326468812562438, 1.0184789997076351, 0.909131754374911, 0.805850732430947, 0.709651093932153, 0.6212978218716073, 0.5412928499429968, 0.4698693281568526, 0.40699310262341926, 0.3523713008184876, 0.30546773213826683, 0.2655246400895027, 0.2315901814054007, 0.20255086276227277, 0.17716804121363533, 0.15411749306652864, 0.13203098022204418, 0.10953869486266582, 0.0853114439722228, 0.058101444974927544, 0.026780642497874676, -0.009624477111641484, -0.05190250405697224, -0.1006319700394313, -0.15616213625595862, -0.21860022594128162, -0.28780545463553, -0.3633900338824896, -0.44472714192787355, -0.5309656728128315, -0.6210513976701674, -0.7137540035412687, -0.8076993199266832, -0.9014059055148264, -0.9933250506214185, -1.0818831578149835, -1.1655253964030754, -1.2427594876537253, -1.312198467869718, -1.3726012960336798, -1.4229102212768507, -1.4622839017435494, -1.4901253686775797, -1.5061040552426548, -1.5101712556113245, -1.5025685426047173, -1.483828847602094, -1.454770090201722, -1.4164814326230057, -1.3703024204104048, -1.317795451961568, -1.2607121902147407, -1.2009546861946265, -1.1405321220841824, -1.0815141975618625, -1.0259822743576605, -0.9759794579844691, -0.9334608307125626, -0.9002450551063507, -0.8779685426034485, -0.8680433272021598, -0.8716197015826821, -0.8895545638721137, -0.9223862903816061, -0.9703167961967358, -1.0332012752042634, -1.1105459281278953, -1.201513795881598, -1.304938620702347, -1.4193464638614537, -1.5429846210214075, -1.6738571991099302, -1.8097665562810432, -1.9483596631188758, -2.0871783222512263, -2.223712087966799, -2.3554526596429164, -2.479948484480938, -2.5948582971837926, -2.6980023470196675, -2.7874101156696582, -2.861363411090902, -2.9184338313656633, -2.9575137255187474, -2.9778399323424507, -2.979009749626232, -2.960988770681061, -2.924110418187398, -2.8690672024829063, -2.796893927647366, -2.7089432593674116, -2.6068542489419717, -2.4925145735445744, -2.368017399975747, -2.2356139040636096, -2.097662577595346, -1.9565765268012107, -1.8147700092579007, -1.6746054686443055, -1.538342308826639, -1.4080886007799622, -1.2857568391129053, -1.1730247613997564, -1.0713021157448732, -0.9817041132025112, -0.905032135558875, -0.8417620896772365, -0.79204061155468, -0.7556891310893713, -0.7322156170503322, -0.7208336355923292, -0.7204881794378409, -0.7298875628724453, -0.7475405339230623, -0.7717976330045867, -0.8008957298784226, -0.8330046002970822, -0.8662743618688938, -0.8988825764071152, -0.9290798435331599, -0.9552327570471981, -0.9758631702981116, -0.9896828175210981, -0.995622462263424, -0.9928548884066923, -0.9808112102380924, -0.9591901514385993, -0.9279601243536008, -0.8873541259080543, -0.8378576503618703, -0.780189997146388, -0.7152795198078731, -0.6442335154002978, -0.568303588679341, -0.4888474387783931, -0.40728810487114214, -0.3250717694382626, -0.24362525162658963, -0.1643143279984057, -0.0884039936283271, -0.017021723662207628, 0.04887528452989667, 0.10852801355011496, 0.1613979249523157, 0.2071830541020018, 0.2458274621253525, 0.2775237796016337, 0.30270875703203987, 0.32205191985369697, 0.3364376062224077, 0.3469408393789042, 0.35479764872816183, 0.36137060066745935, 0.3681104279486012, 0.3765147516835917, 0.38808497029263267, 0.4042824426690341, 0.42648511719965526, 0.45594575335125986, 0.493752848367129, 0.5407953190033088, 0.5977318986742467, 0.664966096056418, 0.7426274249238058, 0.8305594601241286, 0.9283151049855664, 1.0351592752830927, 1.1500790186767929, 1.271800900908196, 1.3988153056966275, 1.5294071188356184, 1.661692102883977, 1.7936581212126959, 1.9232102427436666, 2.0482186547399888, 2.1665682331466027, 2.2762085702571144, 2.3752032392265714, 2.4617770847626073, 2.5343603690652787, 2.5916286708648575, 2.6325375316220803, 2.6563509643192402, 2.662663083870036, 2.6514122805425817, 2.6228875349847955, 2.5777266611527607, 2.516906457091529, 2.4417249383705104, 2.353776020261461, 2.254917197774144, 2.1472309429388163, 2.032980692056218, 1.9145624282481486, 1.7944529732599621, 1.6751561844022849, 1.5591483057358912, 1.4488237457654056, 1.3464425464162815, 1.2540807700761152, 1.1735849638850258], [1.1253448913261368, 1.0689856012624193, 1.027999654262451, 1.0031074515603853, 0.9946693020830623, 1.0026784605480108, 1.0267624764390382, 1.066192808146713, 1.1199024605845032, 1.1865112146479466, 1.2643578375875186, 1.3515384990658013, 1.4459504723456842, 1.5453400772199966, 1.6473537239012523, 1.7495908474736122, 1.8496574823144238, 1.9452192160432462, 2.0340522832297627, 2.1140916097166333, 2.1834746976831734, 2.240580347483013, 2.284061342174715, 2.3128703712850114, 2.326278637951891, 2.323886774030411, 2.305627876541113, 2.2717626713357295, 2.2228670013023266, 2.1598120221229262, 2.0837376639744365, 1.996020078336363, 1.8982339313155099, 1.7921105251649432, 1.6794928250607604, 1.5622885364275425, 1.4424224175729552, 1.321789022222276, 1.2022070465916583, 1.085376406502558, 0.9728390930414437, 0.8659447524223697, 0.7658218096683126, 0.6733548097164623, 0.5891684872906539, 0.5136189024864904, 0.4467917968928138, 0.38850813982250576, 0.3383366505118605, 0.2956129045896012, 0.2594644661707432, 0.228841334780213, 0.20255086276227274, 0.17929618721771698, 0.15771713360956854, 0.13643248814327633, 0.1140825043350245, 0.08937050659325087, 0.061102480182421266, 0.028223591909879876, -0.010149332143703147, -0.05470023864143473, -0.10589192647486476, -0.16395036346622036, -0.22885566692893472, -0.30034000061959176, -0.37789245992702664, -0.4607708344624807, -0.5480199571754828, -0.6384961762964242, -0.730897325192028, -0.8237974197187151, -0.9156851865829906, -1.0050054227940257, -1.090202108181094, -1.169762142173339, -1.2422585539422197, -1.3063920422093473, -1.3610297374103624, -1.4052401436316315, -1.4383233092404561, -1.4598353911763087, -1.4696069156054867, -1.4677541936608385, -1.4546835214234914, -1.431087973917368, -1.3979367891794108, -1.3564575257862623, -1.3081113608741346, -1.2545620710756156, -1.1976394015044745, -1.1392976738424099, -1.0815706100240332, -1.0265234497836881, -0.9762035158065749, -0.9325904274517348, -0.8975471817165959, -0.872773307753733, -0.8597612590352088, -0.8597571361342217, -0.8737267347212149, -0.9023277900933873, -0.9458891443347092, -1.0043973985482149, -1.0774914344860589, -1.1644650016624287, -1.2642773722645715, -1.3755718716174987, -1.496701901375024, -1.6257638906811016, -1.7606364417423659, -1.8990247847308879, -2.038509526432713, -2.176598570797404, -2.310781010162098, -2.4385817353970842, -2.557615492821484, -2.665639126001255, -2.7606007812510565, -2.840684925853569, -2.904352125999132, -2.9503726548680413, -2.9778531471365888, -2.986255680945628, -2.975408848022916, -2.9455105628297464, -2.8971225576825863, -2.831156708012918, -2.748853525478094, -2.651753341819854, -2.5416608786893677, -2.420604053940921, -2.2907880093834994, -2.154545455426393, -2.0142845118097332, -1.8724352786787464, -1.7313963973525768, -1.5934828547026663, -1.4608762492894523, -1.3355786722516525, -1.2193712630617843, -1.1137783819949634, -1.0200382004667596, -0.9390803507859486, -0.8715111023056032, -0.8176063457671218, -0.7773124763957684, -0.7502550737424052, -0.73575508711569, -0.7328520543598668, -0.7403337131430571, -0.7567712119489011, -0.7805589963091455, -0.8099583376635782, -0.843143390184117, -0.8782486068962666, -0.9134163217175656, -0.9468433091225689, -0.9768251678093012, -1.0017974380195067, -1.0203724523810487, -1.0313710349546061, -1.0338482996295089, -1.0271129536423502, -1.0107396808576776, -0.9845743582758218, -0.9487320435012134, -0.9035878559700712, -0.8497610559425783, -0.7880927980595066, -0.719618196313377, -0.6455334805823192, -0.567159147840371, -0.4859001107254492, -0.40320391984242065, -0.3205181821828782, -0.2392483152334472, -0.16071676432449275, -0.08612476987987633, -0.016517702531774918, 0.04724511067229039, 0.10451526410020281, 0.1548741894966021, 0.19814560020336694, 0.2344011229137763, 0.2639589541977829, 0.28737556129969144, 0.30543062864840903, 0.319105628515168, 0.3295565618065541, 0.33808156882968665, 0.34608424609081095, 0.3550336203083252, 0.36642182188396744, 0.3817205647313514, 0.4023375759207978, 0.429574126078902, 0.4645847896261264, 0.5083405132278443, 0.5615959924813234, 0.6248622527664909, 0.6983852029050198, 0.7821307829389201, 0.8757771636040363, 0.9787142790011074, 1.0900507899398255, 1.2086283880403548, 1.3330431646066163, 1.4616735881987486, 1.5927144652504985, 1.7242161032731256, 1.8541277600726342, 1.9803443484383156, 2.100755276850491, 2.2132942452008675, 2.3159887819427416, 2.407008306396095, 2.484709527292985, 2.5476780454836048, 2.5947651137245735, 2.625118617630247, 2.638207476524955, 2.633838817843266, 2.61216745013373, 2.5736973434615034, 2.519275017597278, 2.4500749331424485, 2.367577173905521, 2.2735378956759846, 2.169953192450216, 2.059017191822876, 1.9430753327080754, 1.8245738973052594, 1.7060069623362555, 1.5898619997389498, 1.4785653925800188, 1.37442913703722, 1.2795999757421623, 1.196012152158491, 1.1253448913261375], [1.0845047967725794, 1.0393103937494421, 1.0100058989589125, 0.9970852684687642, 1.0006768932512256, 1.0205416739072861, 1.056079405951255, 1.1063433129915203, 1.1700623721123453, 1.2456708915044075, 1.3313446293816589, 1.4250425896047405, 1.5245534969235428, 1.6275458465501196, 1.7316203414763396, 1.8343634784942344, 1.933401021488039, 2.026450108733277, 2.1113687793977247, 2.18620177218651, 2.249221544386006, 2.2989635800416384, 2.33425519864153, 2.3542372369201936, 2.358378152241915, 2.3464802821181894, 2.3186781861596013, 2.2754291894321765, 2.217496435040702, 2.1459249341604543, 2.0620112692666583, 1.9672677568780865, 1.8633820060765358, 1.7521729152449974, 1.6355442293376568, 1.5154368316657274, 1.3937809664698897, 1.2724495810001044, 1.153213938726629, 1.0377025896859535, 0.927364691553103, 0.8234385582220501, 0.7269261744659349, 0.638574259162993, 0.5588622895758721, 0.4879977195639531, 0.42591843992461287, 0.3723023439527507, 0.3265836804324928, 0.2879757041712902, 0.2554989751670983, 0.2280145155417127, 0.20426091202109628, 0.18289435401788992, 0.16253052569599166, 0.14178722653835063, 0.11932657996184613, 0.09389570376481028, 0.0643647592553963, 0.02976136666956563, -0.01069952887371976, -0.05759113658580735, -0.11125629970030247, -0.1717954737800816, -0.23906153181696524, -0.3126615458726247, -0.3919655126390545, -0.4761218086145661, -0.5640789842102654, -0.6546133395043876, -0.7463615717858303, -0.8378576503618699, -0.9275729607883632, -1.0139586716198368, -1.0954892142698371, -1.1707057322519412, -1.238258350864557, -1.2969461424834385, -1.345753715493408, -1.3838834352605718, -1.410782391460821, -1.426163354938066, -1.4300191158841393, -1.4226297598286637, -1.4045626146076313, -1.376664785742765, -1.340048384909008, -1.2960687417101873, -1.2462960681704238, -1.1924812136769003, -1.1365163013354886, -1.0803911709472316, -1.02614666566938, -0.9758258860256747, -0.9314245940364321, -0.8948419802860402, -0.8678330068888933, -0.8519635094499616, -0.8485691818817415, -0.858719480703905, -0.8831873722797516, -0.9224257100454998, -0.9765508724550438, -1.0453341198840866, -1.1282009443098182, -1.2242384937046453, -1.3322109584463024, -1.4505826144200686, -1.5775480315979153, -1.711068782293897, -1.8489158243117383, -1.9887165947413796, -2.128005733671728, -2.2642782664547068, -2.3950440106363478, -2.517881940832504, -2.630493242512286, -2.7307518139550413, -2.81675103391198, -2.8868456993393043, -2.9396881508862154, -2.974257740876397, -2.9898829559934934, -2.986255680945628, -2.963437275810999, -2.921856334023409, -2.8622981853190286, -2.7858864036349917, -2.6940567691708464, -2.5885243119995818, -2.4712442274231896, -2.3443675967653888, -2.2101929680131316, -2.0711149457534828, -1.9295710069282324, -1.7879877964601774, -1.6487281639309612, -1.5140401790990474, -1.386009310772244, -1.2665148717614485, -1.1571917244072292, -1.0593981092006408, -0.9741903066070159, -0.9023046731333526, -0.8441474111488203, -0.7997922424625248, -0.7689859628611297, -0.751161663459868, -0.7454592195269025, -0.7507524729442014, -0.7656823749346123, -0.7886952150020872, -0.8180849436123377, -0.8520385028375885, -0.8886830132262837, -0.926133628077494, -0.9625408589219366, -0.9961361984179218, -1.0252749184027743, -1.0484750001160184, -1.0644512585607453, -1.0721438508895216, -1.0707405063197315, -1.059691978644882, -1.0387203977668162, -1.0078203793969776, -0.9672529375548437, -0.9175324280603865, -0.8594069282632751, -0.7938326243339626, -0.7219429284031103, -0.6450131799030775, -0.5644218953464415, -0.48160961574022043, -0.3980364587795906, -0.3151395124710609, -0.23429120719924174, -0.15675977450385317, -0.08367284373729592, -0.01598514380409358, 0.045548831506299146, 0.10039646671931876, 0.14826239779330252, 0.18909720062916416, 0.22309915519456924, 0.250709026460167, 0.2725979859522263, 0.289648977328923, 0.30293200142455945, 0.3136739563032051, 0.323223811944806, 0.3330140235769958, 0.3445191891816902, 0.35921303273658434, 0.3785248433261264, 0.4037965200908762, 0.43624136351596154, 0.47690571496211576, 0.5266344795221353, 0.5860414738575563, 0.6554854229214571, 0.7350522903045497, 0.8245444697964673, 0.9234771945326701, 1.0310823390607848, 1.1463196033233523, 1.2678948805740617, 1.394285428305037, 1.523771286956326, 1.6544722298922732, 1.7843893839363671, 1.9114505363114322, 2.0335580442839487, 2.1486381907194083, 2.254690784028678, 2.3498377858311867, 2.4323697645554674, 2.5007890178741454, 2.5538482803215725, 2.590584032946633, 2.6103435570160456, 2.612805020594538, 2.5979900517365215, 2.5662684310239845, 2.518354724915808, 2.4552968752254665, 2.378456954272457, 2.2894844850959446, 2.190282906915146, 2.082969933322019, 1.9698327003768894, 1.853278730150255, 1.735783839138917, 1.6198381978011935, 1.5078917952869126, 1.4023005810742124, 1.30527454219631, 1.21882893133009, 1.144739788250071, 1.0845047967725807], [1.0514102059046313, 1.017757208030165, 1.0003645577997182, 0.9994955991425567, 1.0150457390208005, 1.0465455750547936, 1.093172263074707, 1.1537688463592144, 1.2268710798695024, 1.310741105774913, 1.4034071752897916, 1.5027084702061846, 1.6063439589366555, 1.7119241292305587, 1.8170243752128858, 1.9192387815424623, 2.0162330430924125, 2.105795284668927, 2.185883601204479, 2.25466922315861, 2.310574322408034, 2.3523036079421225, 2.3788690148608787, 2.389606960672171, 2.384187825480616, 2.3626175028398215, 2.325231061112501, 2.272678746397377, 2.205904742741506, 2.1261192789373458, 2.034764829464573, 1.9334772962242697, 1.8240431742576642, 1.7083537958383344, 1.588357811005437, 1.4660130972827816, 1.3432392962439117, 1.221872149716982, 1.1036207544951264, 0.9900287728693503, 0.882440529256611, 0.7819727934111617, 0.689492901498106, 0.6056037014678063, 0.5306356328736435, 0.46464606797662744, 0.40742585529750264, 0.3585128233804181, 0.3172118260255368, 0.2826207450547464, 0.2536617169268646, 0.22911671895479774, 0.20766654274820773, 0.18793209949483572, 0.16851694585066218, 0.14804989189739803, 0.1252265544903566, 0.09884875027115406, 0.06786068183669713, 0.031380956506613815, -0.011270412388388463, -0.06055073958533446, -0.1166797046908501, -0.17963109401433416, -0.2491314743702127, -0.3246658445462251, -0.40549012762449876, -0.4906501881964082, -0.5790068872816725, -0.6692665288002172, -0.7600159087988407, -0.8497610559425779, -0.9369686521818877, -1.020109048562393, -1.0976997447712593, -1.1683481834398368, -1.2307927219488863, -1.283940685277992, -1.326902472340715, -1.359020783580511, -1.3798941570314711, -1.3893941406261967, -1.3876755867779436, -1.3751797272440598, -1.3526298677087736, -1.321019727877022, -1.2815946394854423, -1.2358259968343082, -1.1853795276472854, -1.132078111910931, -1.0778600187937308, -1.024733553179088, -0.9747292006690844, -0.9298504306181237, -0.8920243589881061, -0.8630534854317787, -0.8445697015943182, -0.8379917205052275, -0.844487001180239, -0.8649391399456946, -0.8999215729835595, -0.9496782862312421, -1.0141120626481184, -1.0927806170177716, -1.1849007792761175, -1.289360693464048, -1.4047398055473947, -1.5293362242831896, -1.6612008596851509, -1.7981775778758358, -1.9379484632946349, -2.078083153013813, -2.2160911064251723, -2.349475599322359, -2.4757881862760844, -2.5926823603274394, -2.6979651548133923, -2.789645478241236, -2.8659780484566393, -2.925501895095182, -2.967072526991873, -2.9898870107549746, -2.9935013744629817, -2.9778399323424507, -2.9431963179085905, -2.890226209741413, -2.819931931045128, -2.73363929660921, -2.6329672640798027, -2.519791116110337, -2.3962000518770545, -2.264450196943073, -2.1269141463843186, -1.9860282349094471, -1.844238777535449, -1.7039485440580036, -1.5674647196556037, -1.436949562817276, -1.3143749014525459, -1.2014815103132315, -1.0997442901828196, -1.0103440247319895, -0.9341463280941043, -0.8716882191188482, -0.823172571297924, -0.7884704951383764, -0.7671315170230589, -0.7584012300825135, -0.7612459129325999, -0.7743834457040777, -0.7963197036633473, -0.8253894805203972, -0.8598008893377653, -0.8976821112877491, -0.9371293131870666, -0.9762545348933523, -1.0132323576681515, -1.0463442041444486, -1.0740191884997963, -1.0948705300395536, -1.1077266621910282, -1.1116563088531208, -1.1059869575715786, -1.0903163301205898, -1.0645166314390377, -1.0287315429444368, -0.9833661113699935, -0.9290698647891253, -0.8667136588793202, -0.7973609144421733, -0.7222340477916406, -0.6426770153417579, -0.5601149895922718, -0.47601225335175373, -0.39182944074154646, -0.30898126628244843, -0.2287958669010596, -0.15247683646092874, -0.0810689596052613, -0.015428553166985362, 0.0438007983212423, 0.09620646829708214, 0.14161848859209683, 0.18011440893423872, 0.21201717872883716, 0.23788609677310688, 0.258501055964013, 0.2748404858066803, 0.28805356115441816, 0.29942739689837633, 0.3103500814199775, 0.322270513122827, 0.33665609141386205, 0.35494937385964376, 0.37852484332612624, 0.4086469318514105, 0.4464304216651567, 0.4928042887556031, 0.5484799720170338, 0.6139249432978581, 0.6893423232624913, 0.7746571381035613, 0.8695096465132209, 0.9732559890638632, 1.0849762276796766, 1.2034896558105068, 1.3273770749326712, 1.4550095547401285, 1.5845830273383426, 1.7141579141263663, 1.8417028516905705, 1.965141473303257, 2.082401118334227, 2.1914622852281327, 2.2904076161794023, 2.3774692040327055, 2.4510730442924697, 2.50987951673972, 2.5528188706003894, 2.5791208023663783, 2.588337353478066, 2.580358512799904, 2.5554200823328173, 2.514103549684556, 2.4573279029434247, 2.386333518072231, 2.302658440990301, 2.208107571426471, 2.104715428857173, 1.9947033381221515, 1.8804320097549314, 1.764350604273822, 1.6489434578191684, 1.536675706394554, 1.4299390760677977, 1.3309991060340494, 1.2419450404078405, 1.1646435637150017, 1.1006974657505297, 1.0514102059046322], [1.026341113936508, 1.0045083938086998, 0.9991572008938314, 1.0103180510935739, 1.037654272454599, 1.0804701592199257, 1.1377272254534199, 1.208068166777205, 1.289847956482116, 1.3811713340021263, 1.47993579356486, 1.5838790523760338, 1.690629874065786, 1.7977610468082286, 1.9028432683397136, 2.0034986731479942, 2.0974527507428555, 2.1825834477576804, 2.2569663195392, 2.318914697015836, 2.3670139594847415, 2.400149150411789, 2.4175253377595634, 2.41868029867302, 2.403489296153386, 2.372161908005828, 2.3252310611125013, 2.2635346122239963, 2.18818999536689, 2.1005626212589497, 2.002228861778061, 1.8949345789624015, 1.7805502601771084, 1.6610238965235118, 1.53833278851529, 1.4144354804360804, 1.2912250122955, 1.1704846363281123, 1.0538470746769213, 0.9427582981156646, 0.8384466848934113, 0.7418982771234778, 0.6538386931928831, 0.5747220824683505, 0.5047273274723765, 0.44376151326368474, 0.3914704986454185, 0.3472562436893794, 0.31030037742008776, 0.2795933326172421, 0.253968235486123, 0.2321386198798404, 0.21273894176659017, 0.19436680204221354, 0.17562574625018554, 0.15516749923759254, 0.13173251146627574, 0.10418774109755935, 0.07156067083936299, 0.03306865895813023, -0.011857152754847415, -0.06355400805940445, -0.12211625698616883, -0.18739093127613773, -0.2589802983179757, -0.33625133484160724, -0.4183518805206246, -0.5042330565425778, -0.5926773695747669, -0.6823317715718266, -0.7717448143612712, -0.8594069282632741, -0.9437927689627762, -1.0234045186496827, -1.0968149975970418, -1.16270944166678, -1.21992482979407, -1.2674857026460025, -1.3046354979996397, -1.3308625378751415, -1.345919934392764, -1.3498388324320387, -1.3429345737038036, -1.3258055446540766, -1.2993246552655182, -1.264623582689359, -1.2230700980456186, -1.1762389720404274, -1.1258771208025937, -1.0738638033513632, -1.0221668125717756, -0.972795709169657, -0.9277532300437169, -0.8889860567179141, -0.8583361544789148, -0.8374938879398744, -0.8279540839224281, -0.8309761485763097, -0.8475492540266434, -0.8783634927279773, -0.9237877579223713, -0.9838549495241503, -1.0582549302482664, -1.1463354711137346, -1.2471112331241743, -1.3592806376625404, -1.4812502867016955, -1.6111664100310046, -1.7469526448577761, -1.8863532975991146, -2.0269811022775315, -2.1663683780263736, -2.302020402580466, -2.431469761412067, -2.5523304048182407, -2.6623501484853875, -2.7594603868153484, -2.84182185181029, -2.9078653420665104, -2.95632646421298, -2.9862735701026804, -2.9971282338082763, -2.9886777890874487, -2.961079636177448, -2.914857221978684, -2.850887795147979, -2.7703822325429908, -2.6748574211030967, -2.5661018550613504, -2.4461352680914676, -2.31716325973396, -2.1815279918395065, -2.0416561210121364, -1.9000051949702028, -1.75900977290532, -1.6210285315757431, -1.4882935900372014, -1.3628632273549977, -1.2465790808481427, -1.1410287995727846, -1.0475149916773545, -0.9670311483408395, -0.9002450551063509, -0.8474900177975013, -0.8087640393892763, -0.7837368909001884, -0.7717648283324917, -0.7719125236007726, -0.7829816047630093, -0.8035450439168105, -0.8319864936646669, -0.8665435584132016, -0.9053538977079097, -0.946502997432603, -0.9880724124465962, -1.0281872817922104, -1.0650619449386525, -1.097042543854321, -1.1226455795183126, -1.1405915006127423, -1.1498325337748425, -1.1495741155714405, -1.139289452458259, -1.1187269121983114, -1.0879101340645465, -1.0471309310121788, -0.9969352402048927, -0.938102554220813, -0.8716194295433687, -0.7986478174532536, -0.7204890914772081, -0.6385447519076756, -0.5542748689494396, -0.4691553797786912, -0.38463537990959784, -0.30209554516643466, -0.22280878740449334, -0.14790418578961423, -0.07833514752180054, -0.014852639629100337, 0.04201580026885948, 0.09198071811614099, 0.13499867237123037, 0.1712732236010893, 0.20124895205213164, 0.22559865292419687, 0.2452040377416855, 0.2611304406208781, 0.27459618604200065, 0.2869374159312745, 0.2995692948408708, 0.31394460968824045, 0.33151085237004874, 0.3536669177365721, 0.3817205647313511, 0.41684777452407035, 0.46005509648394405, 0.512146001878109, 0.5736921679608342, 0.6450104940333502, 0.7261465090922866, 0.8168646713682768, 0.9166458873471824, 1.0246923960707204, 1.1399399781728041, 1.2610772628875044, 1.3865717248359095, 1.5147017903242694, 1.6435943145035392, 1.771266550056077, 1.8956716086638945, 2.0147463214257324, 2.126460336080943, 2.228865249158998, 2.320142561090995, 2.398649262245953, 2.4629599073971966, 2.5119041141558087, 2.5445985255921095, 2.560472406101688, 2.559286189456162, 2.5411424652792065, 2.506489070836439, 2.4561141446164543, 2.391133192073193, 2.312968407345364, 2.2233206830175645, 2.1241349184102187, 2.017559401086162, 1.905900182187094, 1.7915714902539372, 1.6770433272641267, 1.5647874622676992, 1.4572230804250932, 1.356663357360206, 1.2652642102026543, 1.1849764279138688, 1.1175023056260793, 1.0642578026375917, 1.0263411139365082], [1.0095096167301518, 0.9996760420485171, 1.0063940430270113, 1.0294610614810964, 1.0683112151292948, 1.1220284090695978, 1.189367337944322, 1.2687818774240367, 1.3584601890766845, 1.4563657045852083, 1.560283017466667, 1.6678675962590237, 1.776698145329134, 1.8843303801187792, 1.988350954187483, 2.0864302764998217, 2.176372988960312, 2.256164935392769, 2.3240155424394833, 2.37839464797795, 2.4180629507472364, 2.4420954125109935, 2.449897117353678, 2.4412112773274193, 2.4161192650843186, 2.375032747629613, 2.3186781861596013, 2.248074150424908, 2.1645020676956594, 2.069471182013744, 1.9646786352164414, 1.8519656939212936, 1.7332712335687526, 1.6105836496657515, 1.4858923961940596, 1.3611403511032811, 1.2381781790035862, 1.1187218024498804, 1.0043140071261223, 0.8962910950314436, 0.7957553662942534, 0.703554057900713, 0.6202652002862374, 0.5461906746354533, 0.4813565693594049, 0.42552074820836533, 0.37818735950551824, 0.3386278406374811, 0.30590780859881317, 0.27891908013791816, 0.2564159375591613, 0.23705465166758946, 0.2194351942852614, 0.20214402116473645, 0.1837967832264129, 0.1630798303800821, 0.13878940754960814, 0.10986750596571457, 0.07543342268216716, 0.034810195297681173, -0.012454785884093402, -0.06657553299773218, -0.12751996089377293, -0.19500933383089097, -0.2685246781530136, -0.3473199982683781, -0.43044195507792266, -0.5167554964405482, -0.6049747726233851, -0.6936985299532792, -0.7814490566246731, -0.8667136588793195, -0.9479875760151143, -1.0238172007135509, -1.0928424581086316, -1.15383721323973, -1.205746621685515, -1.2477204111864995, -1.279141181149026, -1.2996469296448816, -1.3091471608417302, -1.307832086161896, -1.296174605877861, -1.2749249399854985, -1.2450979634960129, -1.207953487087604, -1.1649699046927755, -1.1178118005217308, -1.068292264923401, -1.0183308073908788, -0.9699078723957231, -0.9250170565813947, -0.8856161917616372, -0.8535784954195816, -0.8306449979630885, -0.8183794335709568, -0.818126729517378, -0.8309761485763094, -0.8577300323761892, -0.898878962951626, -0.9545840083720356, -1.0246665498876546, -1.1086060066207208, -1.2055455838724753, -1.3143059772638823, -1.4334067719330754, -1.5610950886172517, -1.6953808512635151, -1.8340778882101054, -1.9748499349749173, -2.115260484846904, -2.2528253368259463, -2.3850666214086953, -2.5095670450097707, -2.6240230844582086, -2.7262958842934992, -2.8144586610285147, -2.886839498931731, -2.942058529283442, -2.9790586168896867, -2.997128830705349, -2.9959201460125806, -2.975453009581868, -2.936116592140295, -2.878659749596433, -2.804173911031399, -2.714068302683439, -2.610038098382536, -2.494026253732721, -2.368179929746865, -2.2348025380199834, -2.0963025408325913, -1.955140213370921, -1.8137736197795054, -1.6746050689835716, -1.53992929984072, -1.4118845986576711, -1.2924079766346726, -1.1831954322793061, -1.0856681968281285, -1.0009457123902177, -0.9298259265607556, -0.8727733077537333, -0.8299147969023013, -0.8010437181227591, -0.7856314781817957, -0.7828466968791538, -0.7915812323575506, -0.810482401229735, -0.8379905472657457, -0.8723809877557578, -0.9118092665590949, -0.9543585696589938, -0.9980881144836675, -1.041081309333128, -1.0814924942354676, -1.1175911189719752, -1.1478022866523332, -1.1707426901866134, -1.1852510917355659, -1.1904126385854694, -1.1855764692416448, -1.1703662368034802, -1.1446833584977347, -1.10870298602545, -1.0628628764513322, -1.0078455230894998, -0.9445540757155185, -0.8740827352157163, -0.7976824455853995, -0.7167228225798343, -0.6326513504193534, -0.5469509434812677, -0.46109700727422986, -0.3765151412937325, -0.2945406054394853, -0.21638062211126818, -0.14308050918373594, -0.07549453677420379, -0.014262275679572865, 0.04020893924039467, 0.08775496793519984, 0.12845895577143268, 0.16264844505831627, 0.19088557923481325, 0.2139506522485305, 0.23281943007637398, 0.24863483495765434, 0.26267373157028956, 0.27630968429266195, 0.2909726625403067, 0.3081067541838052, 0.3291270031008081, 0.3553765145264888, 0.38808497029263217, 0.4283296652689214, 0.47700011705812095, 0.5347672146843917, 0.6020577607672097, 0.6790351282384379, 0.7655866003446387, 0.8613177952681502, 0.9655543983715041, 1.0773512402747245, 1.1955085723396144, 1.3185952073397968, 1.444978016759724, 1.5728571117333736, 1.7003058862595866, 1.8253149727794873, 1.9458390547512046, 2.0598454012172915, 2.1653629366049456, 2.260530636512123, 2.3436440476742875, 2.4131987675943605, 2.467929785628914, 2.5068456811121296, 2.5292567931352528, 2.534796618023459, 2.5234358509437533, 2.495488663539936, 2.451610995746181, 2.392790832427061, 2.320330629512523, 2.2358222450797056, 2.1411149136874434, 2.038276972689744, 1.929552203035608, 1.8173117803999432, 1.7040029420787297, 1.5920955581916647, 1.4840278502878967, 1.382152525061236, 1.2886845849020274, 1.2056520405441256, 1.1348506849546849, 1.077803993438418, 1.0357290949503282, 1.0095096167301523], [1.0010581163682697, 1.0033010366321724, 1.0220138572401019, 1.056762671774933, 1.1067571954374327, 1.1708687230047563, 1.2476557018283188, 1.3353963128343658, 1.4321272871180637, 1.5356880391231789, 1.6437690731234633, 1.7539635207686546, 1.8638205962054688, 1.9708997134293262, 2.072823999041246, 2.1673319527065975, 2.2523260568176413, 2.325917214892793, 2.3864640031394675, 2.432605848744824, 2.463289398629502, 2.4777875098814723, 2.4757104737394564, 2.4570092743605665, 2.4219708770211317, 2.3712057331088885, 2.3056278765411133, 2.2264281635028715, 2.1350413703148208, 2.0331080088467814, 1.9224318416880992, 1.8049341773120395, 1.6826060963917138, 1.55745980257795, 1.431480303490336, 1.3065786101948649, 1.1845475965817907, 1.0670215850798452, 0.955440624008178, 0.8510202971814335, 0.7547277613325344, 0.6672645451884551, 0.5890564697203432, 0.5202508665899902, 0.46072108572375664, 0.4100780979370776, 0.3676888192456145, 0.33270061441893917, 0.3040712826816019, 0.2806036920978525, 0.26098411447884323, 0.2438232224645902, 0.22769864697782458, 0.21119795806939612, 0.19296092610908902, 0.17171994342303057, 0.14633753820620696, 0.11583999149471128, 0.07944617213207932, 0.0365908313397796, -0.013058255529420835, -0.0695897509320838, -0.1328450986333993, -0.20242184654561426, -0.27768386410303936, -0.3577781889253198, -0.44165806379481515, -0.5281115623823138, -0.6157950548330974, -0.7032706360251498, -0.7890465333082787, -0.8716194295433679, -0.9495175833730671, -1.0213436032769965, -1.0858157357876947, -1.1418065612259096, -1.1883780516795324, -1.2248120342091293, -1.250635215245744, -1.2656380570605832, -1.269886950682487, -1.2637292978974828, -1.2477912937870566, -1.2229683861775573, -1.1904085747504944, -1.1514888957240674, -1.1077856133533146, -1.061038802587872, -1.0131121539478902, -0.9659489583042795, -0.9215253325469033, -0.881801824435292, -0.848674584233939, -0.8239273107138144, -0.8091851691551474, -0.8058718392583784, -0.8151707822443648, -0.8379917205052267, -0.8749432022371832, -0.9263119804551923, -0.9920497741182818, -1.0717678027152133, -1.164739298875241, -1.2699100109471735, -1.3859165137538507, -1.5111119556372545, -1.6435986881396731, -1.7812670557004122, -1.921839470758756, -2.0629187684058454, -2.2020397274793395, -2.3367225644188525, -2.464527154319718, -2.58310671175681, -2.6902596726849164, -2.783978557891061, -2.862494667166036, -2.9243175499401945, -2.9682683202709783, -2.993506028827239, -2.9995464683831177, -2.986272968337305, -2.953938923565139, -2.9031619988794564, -2.8349101477577343, -2.7504797779895793, -2.6514665827954293, -2.539729729248822, -2.417350252295746, -2.2865846385141175, -2.14981469570949, -2.0094948898028018, -1.8680983871882242, -1.7280630674837005, -1.591738767758958, -1.4613369850512459, -1.338884200159546, -1.2261798939587591, -1.1247602100943566, -1.0358680778294507, -0.960430449497017, -0.8990431324035579, -0.8519635094499619, -0.8191112507549002, -0.8000769249097728, -0.7941382279174855, -0.8002833650405359, -0.8172409501765733, -0.8435156331504128, -0.877428531205784, -0.9171614302378862, -0.9608036365841962, -1.0064003034914368, -1.0520010290081507, -1.095707524592194, -1.1357191860049707, -1.1703754591860753, -1.1981939821453682, -1.2179035971842542, -1.2284714630584221, -1.229123650573498, -1.2193587736604288, -1.1989543869492763, -1.1679660657377404, -1.126719270385286, -1.0757942798846956, -1.016004654093649, -0.9483698464820501, -0.8740827352157162, -0.7944729663214489, -0.7109671054386474, -0.6250466717201774, -0.5382051769113311, -0.4519053133162153, -0.36753742578709064, -0.2863803653103396, -0.2095657562085428, -0.13804661713011965, -0.0725711602147867, -0.013662456064558676, 0.038395502097762615, 0.08356496951296322, 0.12205466775439355, 0.15431304283514838, 0.18101473910039947, 0.20304064210260442, 0.22145201235302592, 0.237459387295246, 0.25238706709908776, 0.2676341174013049, 0.28463291591756845, 0.3048063375087503, 0.32952471204966216, 0.36006370026694945, 0.3975642142589947, 0.44299546209464746, 0.49712212084592067, 0.5604765414778948, 0.6333367646854321, 0.7157109821114237, 0.8073289160007078, 0.9076404162597206, 1.0158213914515666, 1.1307870040255101, 1.251211874728381, 1.3755568613301332, 1.5021018070452732, 1.6289834986327365, 1.7542379370471497, 1.875845908183167, 1.9917807506575733, 2.1000571540553326, 2.1987797863021625, 2.286190543781739, 2.360713242718242, 2.4209946246789533, 2.465940631568887, 2.4947470142412005, 2.5069234712286157, 2.5023106669172583, 2.4810896480271283, 2.4437833594033864, 2.3912501504099204, 2.324669356991624, 2.2455192369792023, 2.155547722717059, 2.0567366310070048, 1.9512601313370335, 1.8414384154247299, 1.7296876307265279, 1.6184672347720908, 1.5102259936220932, 1.4073478847412522, 1.312099171171175, 1.2265778898690247, 1.1526669429886072, 1.0919918979978813, 1.0458844928368165, 1.0153527084651603, 1.0010581163682697], [1.0010581163682695, 1.015352708465159, 1.0458844928368154, 1.0919918979978804, 1.152666942988604, 1.2265778898690192, 1.3120991711711711, 1.4073478847412493, 1.5102259936220868, 1.6184672347720874, 1.7296876307265279, 1.8414384154247248, 1.9512601313370248, 2.056736631007, 2.155547722717058, 2.2455192369791983, 2.3246693569916212, 2.3912501504099204, 2.4437833594033846, 2.481089648027125, 2.502310666917256, 2.506923471228616, 2.4947470142412, 2.4659406315688877, 2.4209946246789547, 2.360713242718243, 2.2861905437817414, 2.198779786302168, 2.1000571540553343, 1.9917807506575762, 1.8758459081831742, 1.7542379370471541, 1.6289834986327385, 1.502101807045277, 1.3755568613301414, 1.251211874728382, 1.1307870040255126, 1.0158213914515728, 0.9076404162597242, 0.8073289160007091, 0.7157109821114275, 0.633336764685436, 0.5604765414778947, 0.4971221208459229, 0.44299546209464913, 0.39756421425899563, 0.3600637002669496, 0.32952471204966294, 0.3048063375087506, 0.2846329159175687, 0.2676341174013054, 0.25238706709908776, 0.23745938729524566, 0.22145201235302595, 0.20304064210260442, 0.18101473910039886, 0.1543130428351493, 0.12205466775439457, 0.0835649695129634, 0.03839550209776262, -0.013662456064557205, -0.07257116021478549, -0.1380466171301193, -0.20956575620854073, -0.2863803653103383, -0.36753742578708937, -0.4519053133162119, -0.5382051769113291, -0.6250466717201761, -0.7109671054386443, -0.7944729663214469, -0.8740827352157157, -0.9483698464820502, -1.0160046540936476, -1.075794279884695, -1.1267192703852862, -1.16796606573774, -1.1989543869492765, -1.219358773660428, -1.2291236505735001, -1.2284714630584233, -1.2179035971842562, -1.19819398214537, -1.1703754591860773, -1.1357191860049716, -1.0957075245921948, -1.0520010290081554, -1.0064003034914377, -0.9608036365841983, -0.917161430237887, -0.8774285312057863, -0.8435156331504143, -0.8172409501765752, -0.8002833650405375, -0.7941382279174858, -0.8000769249097727, -0.8191112507548994, -0.8519635094499606, -0.8990431324035557, -0.9604304494970142, -1.0358680778294496, -1.124760210094353, -1.2261798939587574, -1.3388842001595413, -1.4613369850512379, -1.591738767758956, -1.728063067483695, -1.868098387188222, -2.009494889802797, -2.149814695709485, -2.286584638514112, -2.417350252295741, -2.5397297292488177, -2.651466582795425, -2.7504797779895775, -2.8349101477577316, -2.903161998879456, -2.953938923565137, -2.9862729683373046, -2.9995464683831177, -2.9935060288272397, -2.9682683202709796, -2.924317549940197, -2.862494667166037, -2.7839785578910647, -2.690259672684918, -2.5831067117568143, -2.464527154319726, -2.3367225644188574, -2.202039727479345, -2.062918768405851, -1.9218394707587612, -1.7812670557004144, -1.6435986881396785, -1.5111119556372565, -1.3859165137538558, -1.2699100109471777, -1.1647392988752447, -1.0717678027152187, -0.9920497741182829, -0.9263119804551947, -0.8749432022371848, -0.8379917205052277, -0.8151707822443651, -0.8058718392583777, -0.8091851691551459, -0.8239273107138132, -0.8486745842339373, -0.8818018244352903, -0.9215253325469007, -0.9659489583042787, -1.0131121539478878, -1.0610388025878712, -1.1077856133533122, -1.1514888957240665, -1.1904085747504913, -1.2229683861775555, -1.2477912937870532, -1.263729297897481, -1.2698869506824861, -1.265638057060583, -1.250635215245744, -1.2248120342091284, -1.188378051679533, -1.141806561225909, -1.0858157357876956, -1.0213436032769982, -0.9495175833730671, -0.8716194295433687, -0.7890465333082809, -0.7032706360251533, -0.6157950548330987, -0.5281115623823158, -0.4416580637948182, -0.35777818892532104, -0.2776838641030411, -0.2024218465456163, -0.1328450986333995, -0.06958975093208497, -0.013058255529422264, 0.03659083133977966, 0.07944617213207915, 0.11583999149471055, 0.14633753820620612, 0.17171994342303046, 0.19296092610908896, 0.21119795806939604, 0.22769864697782488, 0.2438232224645905, 0.26098411447884295, 0.28060369209785235, 0.30407128268160144, 0.3327006144189383, 0.3676888192456143, 0.4100780979370765, 0.46072108572375403, 0.5202508665899878, 0.5890564697203422, 0.6672645451884525, 0.7547277613325291, 0.8510202971814305, 0.9554406240081742, 1.0670215850798388, 1.1845475965817873, 1.3065786101948629, 1.4314803034903312, 1.5574598025779485, 1.6826060963917095, 1.8049341773120349, 1.9224318416880921, 2.0331080088467783, 2.135041370314819, 2.226428163502869, 2.305627876541113, 2.3712057331088867, 2.4219708770211303, 2.457009274360567, 2.4757104737394577, 2.477787509881473, 2.463289398629505, 2.4326058487448243, 2.3864640031394706, 2.3259172148927947, 2.2523260568176453, 2.167331952706605, 2.0728239990412494, 1.9708997134293331, 1.8638205962054724, 1.7539635207686595, 1.643769073123465, 1.5356880391231835, 1.4321272871180708, 1.3353963128343695, 1.2476557018283236, 1.1708687230047583, 1.1067571954374327, 1.0567626717749343, 1.022013857240103, 1.003301036632173, 1.0010581163682692], [1.0095096167301518, 1.035729094950326, 1.0778039934384167, 1.134850684954684, 1.2056520405441264, 1.2886845849020259, 1.3821525250612319, 1.4840278502878936, 1.5920955581916583, 1.7040029420787262, 1.817311780399943, 1.9295522030356032, 2.0382769726897427, 2.141114913687439, 2.2358222450797043, 2.320330629512519, 2.3927908324270586, 2.451610995746181, 2.4954886635399345, 2.5234358509437533, 2.534796618023458, 2.5292567931352528, 2.50684568111213, 2.4679297856289146, 2.4131987675943622, 2.343644047674289, 2.2605306365121236, 2.1653629366049483, 2.0598454012172938, 1.9458390547512077, 1.8253149727794946, 1.700305886259591, 1.5728571117333756, 1.4449780167597233, 1.3185952073398002, 1.1955085723396155, 1.0773512402747267, 0.9655543983715102, 0.8613177952681537, 0.7655866003446399, 0.6790351282384413, 0.6020577607672108, 0.5347672146843917, 0.47700011705812295, 0.42832966526892297, 0.3880849702926329, 0.3553765145264888, 0.3291270031008087, 0.3081067541838055, 0.290972662540307, 0.2763096842926624, 0.26267373157028945, 0.24863483495765393, 0.23281943007637398, 0.2139506522485305, 0.1908855792348134, 0.16264844505831721, 0.12845895577143374, 0.08775496793520005, 0.040208939240394675, -0.01426227567957133, -0.07549453677420254, -0.143080509183736, -0.21638062211126605, -0.2945406054394839, -0.37651514129373126, -0.46109700727422726, -0.5469509434812658, -0.6326513504193523, -0.7167228225798313, -0.7976824455853977, -0.8740827352157156, -0.9445540757155187, -1.0078455230894983, -1.062862876451332, -1.1087029860254503, -1.1446833584977345, -1.1703662368034804, -1.1855764692416442, -1.1904126385854703, -1.1852510917355652, -1.1707426901866154, -1.147802286652335, -1.1175911189719772, -1.0814924942354684, -1.0410813093331266, -0.9980881144836697, -0.9543585696589928, -0.911809266559097, -0.8723809877557569, -0.8379905472657478, -0.8104824012297354, -0.7915812323575518, -0.7828466968791543, -0.7856314781817956, -0.801043718122759, -0.8299147969023001, -0.8727733077537315, -0.9298259265607545, -1.0009457123902146, -1.0856681968281294, -1.183195432279302, -1.2924079766346708, -1.4118845986576662, -1.5399292998407146, -1.6746050689835728, -1.8137736197794996, -1.9551402133709217, -2.096302540832586, -2.234802538019981, -2.36817992974686, -2.494026253732719, -2.6100380983825318, -2.7140683026834354, -2.8041739110313992, -2.8786597495964306, -2.936116592140296, -2.9754530095818668, -2.9959201460125806, -2.997128830705349, -2.979058616889688, -2.9420585292834422, -2.8868394989317343, -2.814458661028514, -2.726295884293503, -2.6240230844582078, -2.5095670450097756, -2.3850666214087, -2.252825336825948, -2.115260484846909, -1.9748499349749196, -1.834077888210111, -1.6953808512635142, -1.561095088617257, -1.433406771933074, -1.3143059772638865, -1.2055455838724791, -1.1086060066207222, -1.0246665498876575, -0.9545840083720352, -0.898878962951628, -0.8577300323761899, -0.83097614857631, -0.818126729517378, -0.8183794335709565, -0.8306449979630877, -0.8535784954195801, -0.8856161917616349, -0.9250170565813943, -0.9699078723957201, -1.0183308073908799, -1.0682922649233986, -1.1178118005217321, -1.1649699046927728, -1.2079534870876054, -1.2450979634960124, -1.274924939985497, -1.2961746058778596, -1.3078320861618942, -1.309147160841731, -1.2996469296448812, -1.279141181149027, -1.2477204111864995, -1.205746621685516, -1.1538372132397299, -1.0928424581086325, -1.0238172007135529, -0.9479875760151144, -0.8667136588793201, -0.7814490566246755, -0.6936985299532824, -0.6049747726233864, -0.5167554964405501, -0.4304419550779252, -0.3473199982683794, -0.2685246781530149, -0.19500933383089297, -0.12751996089377288, -0.06657553299773332, -0.012454785884094745, 0.03481019529768117, 0.07543342268216699, 0.10986750596571367, 0.13878940754960734, 0.16307983038008197, 0.18379678322641285, 0.20214402116473626, 0.2194351942852616, 0.23705465166758938, 0.2564159375591608, 0.27891908013791794, 0.3059078085988128, 0.33862784063748, 0.378187359505518, 0.4255207482083641, 0.48135656935940274, 0.5461906746354506, 0.6202652002862377, 0.7035540579007116, 0.7957553662942495, 0.8962910950314422, 1.0043140071261185, 1.1187218024498737, 1.2381781790035837, 1.3611403511032798, 1.485892396194056, 1.6105836496657522, 1.7332712335687506, 1.8519656939212898, 1.9646786352164352, 2.069471182013742, 2.1645020676956577, 2.2480741504249058, 2.318678186159601, 2.375032747629612, 2.416119265084318, 2.4412112773274193, 2.449897117353679, 2.442095412510993, 2.418062950747239, 2.3783946479779496, 2.3240155424394855, 2.2561649353927695, 2.1763729889603147, 2.0864302764998266, 1.9883509541874842, 1.8843303801187845, 1.7766981453291357, 1.6678675962590286, 1.560283017466667, 1.4563657045852112, 1.3584601890766899, 1.2687818774240394, 1.189367337944325, 1.1220284090695989, 1.0683112151292944, 1.0294610614810968, 1.0063940430270115, 0.9996760420485171, 1.0095096167301514], [1.0263411139365073, 1.064257802637589, 1.1175023056260776, 1.1849764279138675, 1.2652642102026506, 1.3566633573601992, 1.4572230804250885, 1.5647874622676958, 1.6770433272641199, 1.7915714902539337, 1.9059001821870938, 2.017559401086157, 2.1241349184102103, 2.2233206830175605, 2.312968407345363, 2.3911331920731893, 2.456114144616452, 2.5064890708364387, 2.541142465279205, 2.5592861894561603, 2.5604724061016877, 2.544598525592111, 2.511904114155809, 2.4629599073971966, 2.3986492622459554, 2.3201425610909965, 2.2288652491590013, 2.126460336080949, 2.014746321425734, 1.895671608663898, 1.7712665500560845, 1.6435943145035439, 1.5147017903242714, 1.386571724835913, 1.2610772628875122, 1.139939978172805, 1.0246923960707228, 0.9166458873471882, 0.8168646713682801, 0.7261465090922878, 0.6450104940333533, 0.5736921679608374, 0.5121460018781088, 0.4600550964839459, 0.41684777452407157, 0.38172056473135163, 0.3536669177365721, 0.331510852370049, 0.3139446096882402, 0.29956929484087125, 0.2869374159312749, 0.2745961860420004, 0.2611304406208776, 0.2452040377416854, 0.2255986529241968, 0.20124895205213095, 0.1712732236010903, 0.13499867237123148, 0.09198071811614122, 0.04201580026885949, -0.014852639629098744, -0.07833514752179926, -0.1479041857896139, -0.22280878740449114, -0.3020955451664332, -0.3846353799095967, -0.46915537977868793, -0.5542748689494378, -0.6385447519076746, -0.7204890914772052, -0.7986478174532518, -0.871619429543368, -0.9381025542208135, -0.9969352402048919, -1.0471309310121786, -1.087910134064547, -1.1187269121983114, -1.1392894524582593, -1.149574115571441, -1.149832533774845, -1.1405915006127436, -1.1226455795183148, -1.0970425438543228, -1.0650619449386545, -1.028187281792211, -0.988072412446597, -0.9465029974326074, -0.9053538977079105, -0.8665435584132034, -0.8319864936646675, -0.8035450439168123, -0.7829816047630103, -0.7719125236007734, -0.7717648283324919, -0.7837368909001877, -0.8087640393892759, -0.8474900177974994, -0.9002450551063488, -0.9670311483408365, -1.047514991677351, -1.1410287995727828, -1.2465790808481383, -1.3628632273549959, -1.4882935900371967, -1.6210285315757345, -1.7590097729053182, -1.9000051949701973, -2.0416561210121342, -2.1815279918395016, -2.317163259733954, -2.4461352680914628, -2.5661018550613464, -2.6748574211030927, -2.7703822325429877, -2.850887795147978, -2.9148572219786817, -2.9610796361774474, -2.9886777890874474, -2.9971282338082763, -2.9862735701026817, -2.9563264642129825, -2.9078653420665126, -2.8418218518102933, -2.7594603868153498, -2.662350148485392, -2.5523304048182425, -2.431469761412072, -2.3020204025804745, -2.1663683780263794, -2.026981102277537, -1.8863532975991204, -1.7469526448577815, -1.6111664100310068, -1.4812502867017006, -1.359280637662542, -1.2471112331241785, -1.1463354711137381, -1.0582549302482696, -0.9838549495241544, -0.923787757922372, -0.878363492727979, -0.847549254026644, -0.8309761485763096, -0.827954083922427, -0.8374938879398732, -0.8583361544789121, -0.8889860567179122, -0.9277532300437143, -0.9727957091696545, -1.0221668125717722, -1.0738638033513623, -1.1258771208025913, -1.1762389720404265, -1.2230700980456162, -1.2646235826893581, -1.2993246552655153, -1.325805544654075, -1.3429345737038008, -1.3498388324320372, -1.3459199343927637, -1.3308625378751413, -1.3046354979996395, -1.2674857026460018, -1.219924829794071, -1.1627094416667798, -1.0968149975970432, -1.0234045186496847, -0.9437927689627765, -0.859406928263275, -0.7717448143612735, -0.6823317715718302, -0.5926773695747684, -0.5042330565425798, -0.4183518805206276, -0.3362513348416085, -0.25898029831797736, -0.18739093127613968, -0.122116256986169, -0.06355400805940553, -0.011857152754848718, 0.03306865895813029, 0.07156067083936284, 0.10418774109755873, 0.13173251146627496, 0.15516749923759243, 0.17562574625018545, 0.19436680204221327, 0.21273894176659025, 0.2321386198798403, 0.2539682354861225, 0.27959333261724184, 0.31030037742008704, 0.3472562436893782, 0.39147049864541816, 0.4437615132636832, 0.5047273274723733, 0.5747220824683477, 0.653838693192882, 0.7418982771234748, 0.8384466848934056, 0.9427582981156621, 1.0538470746769173, 1.1704846363281056, 1.2912250122954962, 1.414435480436078, 1.5383327885152853, 1.6610238965235102, 1.7805502601771048, 1.8949345789623968, 2.002228861778055, 2.1005626212589474, 2.188189995366889, 2.263534612223994, 2.325231061112501, 2.3721619080058276, 2.4034892961533862, 2.4186802986730207, 2.4175253377595656, 2.4001491504117904, 2.367013959484746, 2.3189146970158365, 2.256966319539204, 2.182583447757682, 2.09745275074286, 2.003498673148002, 1.9028432683397165, 1.7977610468082352, 1.690629874065789, 1.5838790523760387, 1.4799357935648616, 1.3811713340021305, 1.2898479564821221, 1.2080681667772084, 1.1377272254534236, 1.080470159219927, 1.037654272454599, 1.0103180510935745, 0.9991572008938313, 1.004508393808699, 1.0263411139365068], [1.051410205904631, 1.1006974657505264, 1.1646435637149994, 1.241945040407839, 1.3309991060340507, 1.4299390760677964, 1.536675706394549, 1.648943457819165, 1.7643506042738148, 1.8804320097549279, 1.9947033381221517, 2.104715428857168, 2.2081075714264693, 2.3026584409902964, 2.3863335180722305, 2.4573279029434216, 2.514103549684554, 2.555420082332817, 2.580358512799903, 2.588337353478067, 2.5791208023663774, 2.5528188706003903, 2.509879516739721, 2.4510730442924706, 2.377469204032708, 2.2904076161794036, 2.1914622852281336, 2.08240111833423, 1.9651414733032593, 1.8417028516905738, 1.714157914126374, 1.5845830273383472, 1.4550095547401307, 1.3273770749326703, 1.2034896558105104, 1.0849762276796777, 0.9732559890638666, 0.8695096465132266, 0.7746571381035643, 0.6893423232624925, 0.6139249432978611, 0.5484799720170348, 0.49280428875560317, 0.44643042166515823, 0.40864693185141143, 0.3785248433261266, 0.35494937385964376, 0.33665609141386227, 0.32227051312282723, 0.31035008141997794, 0.2994273968983768, 0.28805356115441794, 0.27484048580667975, 0.2585010559640129, 0.23788609677310685, 0.2120171787288373, 0.1801144089342398, 0.141618488592098, 0.0962064682970824, 0.04380079832124232, -0.01542855316698371, -0.08106895960525999, -0.15247683646092874, -0.22879586690105744, -0.30898126628244704, -0.39182944074154535, -0.476012253351751, -0.5601149895922701, -0.642677015341757, -0.7222340477916379, -0.7973609144421716, -0.8667136588793194, -0.9290698647891259, -0.9833661113699919, -1.0287315429444368, -1.0645166314390384, -1.09031633012059, -1.1059869575715793, -1.1116563088531197, -1.1077266621910293, -1.0948705300395531, -1.0740191884997987, -1.0463442041444504, -1.0132323576681537, -0.976254534893353, -0.9371293131870654, -0.8976821112877513, -0.8598008893377642, -0.8253894805203987, -0.7963197036633464, -0.7743834457040794, -0.7612459129325998, -0.7584012300825139, -0.7671315170230586, -0.7884704951383756, -0.8231725712979235, -0.8716882191188462, -0.9341463280941016, -1.0103440247319881, -1.0997442901828156, -1.2014815103132324, -1.314374901452541, -1.4369495628172742, -1.5674647196555986, -1.703948544057998, -1.8442387775354503, -1.9860282349094416, -2.1269141463843195, -2.2644501969430677, -2.396200051877052, -2.5197911161103326, -2.632967264079801, -2.7336392966092062, -2.8199319310451254, -2.890226209741413, -2.943196317908589, -2.9778399323424507, -2.9935013744629817, -2.989887010754975, -2.9670725269918745, -2.925501895095184, -2.8659780484566406, -2.7896454782412397, -2.697965154813391, -2.592682360327444, -2.4757881862760835, -2.349475599322364, -2.2160911064251776, -2.078083153013815, -1.93794846329464, -1.7981775778758378, -1.6612008596851562, -1.5293362242831887, -1.4047398055473996, -1.2893606934640474, -1.1849007792761215, -1.092780617017775, -1.0141120626481195, -0.9496782862312442, -0.8999215729835593, -0.8649391399456958, -0.8444870011802393, -0.837991720505227, -0.8445697015943174, -0.8630534854317782, -0.8920243589881043, -0.9298504306181216, -0.9747292006690815, -1.0247335531790873, -1.0778600187937275, -1.1320781119109324, -1.185379527647283, -1.2358259968343095, -1.2815946394854396, -1.3210197278770233, -1.3526298677087727, -1.3751797272440582, -1.3876755867779427, -1.3893941406261952, -1.3798941570314722, -1.3590207835805115, -1.3269024723407157, -1.283940685277992, -1.2307927219488874, -1.1683481834398368, -1.0976997447712606, -1.020109048562395, -0.9369686521818882, -0.8497610559425783, -0.7600159087988432, -0.6692665288002205, -0.579006887281674, -0.4906501881964103, -0.40549012762450126, -0.32466584454622643, -0.249131474370214, -0.17963109401433608, -0.11667970469085005, -0.0605507395853355, -0.01127041238838968, 0.031380956506613815, 0.06786068183669701, 0.09884875027115324, 0.12522655449035586, 0.14804989189739792, 0.16851694585066204, 0.18793209949483536, 0.20766654274820773, 0.22911671895479738, 0.253661716926864, 0.28262074505474627, 0.31721182602553627, 0.3585128233804167, 0.4074258552975023, 0.4646460679766257, 0.530635632873641, 0.6056037014678032, 0.6894929014981064, 0.7819727934111601, 0.8824405292566067, 0.9900287728693489, 1.1036207544951224, 1.2218721497169756, 1.3432392962439095, 1.4660130972827803, 1.5883578110054337, 1.7083537958383346, 1.8240431742576624, 1.9334772962242661, 2.034764829464568, 2.1261192789373444, 2.2059047427415046, 2.2726787463973754, 2.3252310611125004, 2.362617502839821, 2.3841878254806166, 2.3896069606721713, 2.378869014860881, 2.3523036079421225, 2.310574322408037, 2.25466922315861, 2.1858836012044818, 2.1057952846689276, 2.016233043092416, 1.9192387815424667, 1.8170243752128872, 1.7119241292305634, 1.6063439589366573, 1.5027084702061893, 1.4034071752897916, 1.3107411057749156, 1.2268710798695073, 1.1537688463592162, 1.0931722630747096, 1.0465455750547943, 1.0150457390208003, 0.9994955991425567, 1.0003645577997178, 1.0177572080301636, 1.0514102059046302], [1.0845047967725792, 1.1447397882500672, 1.2188289313300877, 1.3052745421963083, 1.4023005810742135, 1.507891795286911, 1.6198381978011887, 1.7357838391389135, 1.853278730150248, 1.969832700376886, 2.082969933322019, 2.190282906915141, 2.289484485095943, 2.378456954272453, 2.4552968752254656, 2.5183547249158047, 2.5662684310239827, 2.5979900517365215, 2.6128050205945375, 2.610343557016046, 2.590584032946633, 2.5538482803215734, 2.5007890178741468, 2.4323697645554683, 2.34983778583119, 2.2546907840286794, 2.1486381907194088, 2.033558044283952, 1.9114505363114345, 1.784389383936371, 1.6544722298922814, 1.5237712869563311, 1.3942854283050392, 1.2678948805740609, 1.1463196033233556, 1.0310823390607848, 0.9234771945326732, 0.8245444697964729, 0.7350522903045527, 0.6554854229214581, 0.5860414738575589, 0.5266344795221362, 0.47690571496211576, 0.4362413635159628, 0.40379652009087696, 0.3785248433261265, 0.3592130327365843, 0.3445191891816904, 0.33301402357699594, 0.3232238119448065, 0.3136739563032055, 0.3029320014245591, 0.28964897732892236, 0.2725979859522262, 0.250709026460167, 0.2230991551945694, 0.1890972006291653, 0.14826239779330377, 0.10039646671931902, 0.04554883150629916, -0.01598514380409187, -0.08367284373729457, -0.15675977450385317, -0.23429120719923954, -0.31513951247105954, -0.39803645877958954, -0.48160961574021766, -0.5644218953464398, -0.6450131799030767, -0.7219429284031077, -0.7938326243339611, -0.8594069282632743, -0.9175324280603873, -0.9672529375548423, -1.0078203793969776, -1.038720397766817, -1.0596919786448826, -1.0707405063197317, -1.0721438508895207, -1.0644512585607464, -1.0484750001160181, -1.0252749184027767, -0.9961361984179237, -0.9625408589219386, -0.9261336280774947, -0.8886830132262825, -0.8520385028375904, -0.8180849436123367, -0.7886952150020885, -0.7656823749346118, -0.7507524729442026, -0.7454592195269024, -0.7511616634598682, -0.7689859628611289, -0.7997922424625233, -0.8441474111488196, -0.9023046731333503, -0.974190306607013, -1.0593981092006393, -1.157191724407225, -1.2665148717614494, -1.3860093107722389, -1.5140401790990452, -1.6487281639309563, -1.7879877964601716, -1.9295710069282335, -2.071114945753477, -2.2101929680131325, -2.344367596765384, -2.4712442274231874, -2.588524311999578, -2.694056769170845, -2.785886403634988, -2.862298185319026, -2.921856334023409, -2.963437275810998, -2.9862556809456287, -2.9898829559934934, -2.9742577408763973, -2.939688150886217, -2.886845699339307, -2.816751033911981, -2.7307518139550453, -2.6304932425122844, -2.5178819408325084, -2.3950440106363464, -2.264278266454712, -2.1280057336717335, -1.9887165947413818, -1.8489158243117436, -1.711068782293899, -1.5775480315979205, -1.4505826144200678, -1.332210958446307, -1.2242384937046444, -1.1282009443098218, -1.0453341198840893, -0.9765508724550448, -0.9224257100455017, -0.8831873722797515, -0.8587194807039055, -0.8485691818817418, -0.8519635094499608, -0.8678330068888919, -0.8948419802860395, -0.9314245940364302, -0.9758258860256723, -1.026146665669377, -1.080391170947231, -1.136516301335485, -1.1924812136769019, -1.2462960681704214, -1.2960687417101888, -1.3400483849090055, -1.3766647857427663, -1.4045626146076309, -1.4226297598286626, -1.4300191158841387, -1.4261633549380646, -1.4107823914608224, -1.383883435260572, -1.3457537154934087, -1.2969461424834388, -1.2382583508645584, -1.1707057322519412, -1.0954892142698387, -1.0139586716198392, -0.9275729607883639, -0.8378576503618702, -0.746361571785833, -0.654613339504391, -0.564078984210267, -0.4761218086145682, -0.39196551263905693, -0.31266154587262596, -0.23906153181696646, -0.17179547378008345, -0.11125629970030244, -0.05759113658580834, -0.010699528873720917, 0.02976136666956563, 0.06436475925539616, 0.0938957037648095, 0.11932657996184541, 0.1417872265383505, 0.16253052569599147, 0.18289435401788948, 0.2042609120210962, 0.22801451554171223, 0.2554989751670976, 0.2879757041712901, 0.3265836804324921, 0.372302343952749, 0.42591843992461237, 0.4879977195639513, 0.5588622895758695, 0.6385742591629898, 0.7269261744659351, 0.8234385582220485, 0.9273646915530985, 1.037702589685952, 1.153213938726625, 1.272449581000098, 1.3937809664698875, 1.5154368316657258, 1.6355442293376536, 1.7521729152449979, 1.8633820060765338, 1.9672677568780834, 2.0620112692666535, 2.145924934160453, 2.2174964350407005, 2.275429189432175, 2.318678186159601, 2.3464802821181894, 2.358378152241916, 2.3542372369201936, 2.3342551986415323, 2.298963580041639, 2.2492215443860095, 2.18620177218651, 2.1113687793977274, 2.026450108733277, 1.933401021488042, 1.8343634784942393, 1.7316203414763411, 1.6275458465501245, 1.5245534969235444, 1.4250425896047447, 1.3313446293816589, 1.24567089150441, 1.1700623721123495, 1.106343312991522, 1.0560794059512573, 1.0205416739072866, 1.0006768932512256, 0.9970852684687642, 1.0100058989589118, 1.03931039374944, 1.084504796772578], [1.1253448913261357, 1.1960121521584866, 1.27959997574216, 1.3744291370372184, 1.4785653925800142, 1.5898619997389416, 1.7060069623362504, 1.824573897305256, 1.9430753327080685, 2.059017191822873, 2.1699531924502162, 2.27353789567598, 2.3675771739055143, 2.4500749331424445, 2.519275017597277, 2.5736973434615007, 2.612167450133729, 2.633838817843266, 2.6382074765249546, 2.625118617630247, 2.594765113724574, 2.547678045483606, 2.4847095272929867, 2.407008306396096, 2.3159887819427447, 2.2132942452008697, 2.1007552768504953, 1.9803443484383232, 1.8541277600726365, 1.7242161032731298, 1.5927144652505065, 1.4616735881987533, 1.3330431646066183, 1.2086283880403585, 1.090050789939833, 0.9787142790011073, 0.8757771636040393, 0.782130782938925, 0.6983852029050225, 0.6248622527664919, 0.5615959924813259, 0.5083405132278465, 0.4645847896261265, 0.42957412607890316, 0.4023375759207984, 0.3817205647313513, 0.3664218218839672, 0.3550336203083251, 0.34608424609080995, 0.3380815688296872, 0.32955656180655457, 0.31910562851516766, 0.3054306286484084, 0.28737556129969144, 0.263958954197783, 0.2344011229137756, 0.19814560020336816, 0.1548741894966034, 0.10451526410020312, 0.04724511067229041, -0.016517702531773155, -0.08612476987987495, -0.16071676432449244, -0.23924831523344497, -0.3205181821828768, -0.4032039198424196, -0.48590011072544614, -0.5671591478403695, -0.6455334805823184, -0.7196181963133745, -0.7880927980595053, -0.8497610559425776, -0.9035878559700722, -0.9487320435012134, -0.9845743582758222, -1.0107396808576783, -1.027112953642351, -1.033848299629509, -1.0313710349546068, -1.0203724523810518, -1.0017974380195083, -0.9768251678093035, -0.9468433091225706, -0.9134163217175675, -0.8782486068962673, -0.8431433901841175, -0.8099583376635814, -0.7805589963091459, -0.7567712119489022, -0.7403337131430574, -0.7328520543598676, -0.7357550871156899, -0.7502550737424051, -0.7773124763957665, -0.8176063457671199, -0.8715111023056024, -0.939080350785946, -1.0200382004667563, -1.1137783819949594, -1.21937126306178, -1.335578672251651, -1.460876249289447, -1.5934828547026643, -1.7313963973525714, -1.8724352786787375, -2.0142845118097314, -2.1545454554263874, -2.290788009383497, -2.4206040539409166, -2.5416608786893637, -2.6517533418198505, -2.7488535254780913, -2.8311567080129154, -2.897122557682585, -2.945510562829746, -2.9754088480229157, -2.986255680945628, -2.977853147136589, -2.9503726548680422, -2.9043521259991345, -2.840684925853574, -2.76060078125106, -2.6656391260012593, -2.5576154928214856, -2.4385817353970896, -2.3107810101620996, -2.1765985707974096, -2.038509526432722, -1.8990247847308934, -1.760636441742371, -1.6257638906811072, -1.4967019013750291, -1.3755718716175007, -1.264277372264576, -1.1644650016624298, -1.077491434486062, -1.004397398548217, -0.945889144334711, -0.9023277900933894, -0.873726734721215, -0.8597571361342217, -0.8597612590352084, -0.8727733077537317, -0.897547181716593, -0.9325904274517325, -0.9762035158065708, -1.0265234497836857, -1.0815706100240299, -1.139297673842407, -1.1976394015044707, -1.2545620710756145, -1.308111360874132, -1.3564575257862614, -1.3979367891794088, -1.4310879739173672, -1.4546835214234892, -1.4677541936608374, -1.4696069156054845, -1.4598353911763078, -1.4383233092404561, -1.4052401436316322, -1.3610297374103626, -1.3063920422093473, -1.2422585539422215, -1.169762142173339, -1.0902021081810958, -1.0050054227940286, -0.9156851865829913, -0.823797419718716, -0.7308973251920308, -0.6384961762964282, -0.5480199571754845, -0.46077083446248285, -0.3778924599270296, -0.30034000061959315, -0.2288556669289363, -0.16395036346622213, -0.10589192647486491, -0.054700238641435674, -0.010149332143704266, 0.02822359190987993, 0.061102480182421134, 0.0893705065932503, 0.11408250433502377, 0.1364324881432762, 0.15771713360956827, 0.1792961872177163, 0.20255086276227252, 0.2288413347802124, 0.25946446617074226, 0.2956129045896007, 0.33833665051185935, 0.38850813982250404, 0.44679179689281323, 0.5136189024864884, 0.5891684872906497, 0.673354809716459, 0.7658218096683114, 0.8659447524223672, 0.9728390930414373, 1.0853764065025553, 1.2022070465916541, 1.3217890222222692, 1.442422417572952, 1.5622885364275403, 1.6794928250607564, 1.7921105251649423, 1.898233931315507, 1.99602007833636, 2.083737663974432, 2.1598120221229253, 2.2228670013023257, 2.2717626713357286, 2.3056278765411125, 2.3238867740304125, 2.3262786379518934, 2.3128703712850127, 2.284061342174719, 2.240580347483015, 2.1834746976831783, 2.114091609716635, 2.0340522832297676, 1.9452192160432478, 1.8496574823144285, 1.7495908474736201, 1.6473537239012555, 1.545340077220003, 1.4459504723456873, 1.3515384990658055, 1.26435783758752, 1.18651121464795, 1.1199024605845076, 1.066192808146715, 1.0267624764390404, 1.0026784605480115, 0.9946693020830623, 1.0031074515603848, 1.0279996542624497, 1.068985601262416, 1.1253448913261341], [1.1735849638850238, 1.25408077007611, 1.3464425464162786, 1.4488237457654038, 1.5591483057358924, 1.6751561844022826, 1.794452973259957, 1.914562428248145, 2.0329806920562112, 2.147230942938813, 2.254917197774144, 2.3537760202614564, 2.4417249383705086, 2.5169064570915256, 2.5777266611527603, 2.6228875349847933, 2.651412280542581, 2.6626630838700356, 2.6563509643192402, 2.6325375316220807, 2.591628670864858, 2.53436036906528, 2.4617770847626095, 2.3752032392265723, 2.2762085702571184, 2.166568233146604, 2.048218654739989, 1.9232102427436701, 1.793658121212698, 1.661692102883981, 1.5294071188356264, 1.3988153056966324, 1.2718009009081979, 1.150079018676792, 1.035159275283097, 0.9283151049855662, 0.8305594601241315, 0.7426274249238105, 0.6649660960564205, 0.5977318986742475, 0.5407953190033109, 0.4937528483671296, 0.4559457533512599, 0.42648511719965604, 0.40428244266903457, 0.3880849702926324, 0.3765147516835915, 0.368110427948601, 0.3613706006674594, 0.3547976487281624, 0.34694083937890463, 0.33643760622240726, 0.32205191985369636, 0.3027087570320398, 0.2775237796016337, 0.2458274621253527, 0.2071830541020031, 0.16139792495231706, 0.1085280135501153, 0.048875284529896694, -0.01702172366220581, -0.08840399362832572, -0.16431432799840567, -0.24362525162658746, -0.32507176943826116, -0.4072881048711412, -0.48884743877839043, -0.5683035886793397, -0.6442335154002972, -0.7152795198078707, -0.7801899971463869, -0.8378576503618695, -0.8873541259080553, -0.9279601243535994, -0.9591901514385998, -0.980811210238093, -0.9928548884066931, -0.9956224622634245, -0.9896828175210971, -0.9758631702981131, -0.9552327570471978, -0.9290798435331621, -0.8988825764071169, -0.8662743618688956, -0.833004600297083, -0.8008957298784216, -0.7717976330045881, -0.7475405339230616, -0.729887562872446, -0.7204881794378405, -0.7208336355923296, -0.7322156170503318, -0.7556891310893705, -0.7920406115546784, -0.8417620896772345, -0.905032135558874, -0.981704113202508, -1.0713021157448697, -1.1730247613997544, -1.2857568391129004, -1.4080886007799631, -1.5383423088266335, -1.6746054686443035, -1.8147700092578956, -1.9565765268012054, -2.0976625775953472, -2.235613904063604, -2.3680173999757472, -2.4925145735445704, -2.60685424894197, -2.7089432593674085, -2.7968939276473646, -2.869067202482904, -2.9241104181873965, -2.9609887706810607, -2.979009749626232, -2.9778399323424507, -2.9575137255187482, -2.918433831365664, -2.8613634110909048, -2.7874101156696613, -2.6980023470196692, -2.5948582971837975, -2.4799484844809365, -2.3554526596429217, -2.223712087966798, -2.0871783222512317, -1.9483596631188813, -1.8097665562810452, -1.6738571991099354, -1.5429846210214093, -1.4193464638614584, -1.3049386207023461, -1.201513795881602, -1.1105459281278944, -1.0332012752042663, -0.9703167961967377, -0.9223862903816067, -0.8895545638721144, -0.8716197015826822, -0.8680433272021597, -0.8779685426034485, -0.9002450551063489, -0.9334608307125607, -0.9759794579844682, -1.025982274357658, -1.0815141975618596, -1.1405321220841789, -1.200954686194626, -1.260712190214737, -1.3177954519615696, -1.3703024204104022, -1.416481432623007, -1.4547700902017198, -1.4838288476020953, -1.5025685426047166, -1.5101712556113236, -1.5061040552426546, -1.4901253686775788, -1.462283901743551, -1.4229102212768518, -1.3726012960336804, -1.3121984678697183, -1.2427594876537271, -1.1655253964030756, -1.0818831578149855, -0.9933250506214207, -0.9014059055148274, -0.8076993199266835, -0.7137540035412714, -0.6210513976701708, -0.5309656728128331, -0.44472714192787566, -0.36339003388249186, -0.2878054546355312, -0.21860022594128276, -0.15616213625596034, -0.10063197003943125, -0.051902504056973144, -0.009624477111642524, 0.026780642497874676, 0.05810144497492741, 0.08531144397222208, 0.1095386948626651, 0.13203098022204401, 0.15411749306652836, 0.17716804121363458, 0.20255086276227244, 0.2315901814054, 0.2655246400895019, 0.3054677321382667, 0.35237130081848683, 0.40699310262341726, 0.46986932815685206, 0.5412928499429948, 0.6212978218716043, 0.7096510939321494, 0.8058507324309472, 0.9091317543749093, 1.0184789997076307, 1.132646881256242, 1.250185574228038, 1.3694730393843983, 1.488752120866264, 1.6061718249453, 1.7198317731679584, 1.8278287353462699, 1.928304086916384, 2.019491002948984, 2.0997601984573686, 2.16766305177662, 2.221971004105597, 2.26171021251025, 2.286190543781741, 2.295028129878593, 2.2881608590266396, 2.265856346168622, 2.2287121081991286, 2.1776478588324104, 2.1138900303734363, 2.0389488203537014, 1.9545882452442966, 1.862789856708396, 1.7657109338073682, 1.665638103299097, 1.5649374562033949, 1.4660023192472669, 1.3711999023592891, 1.2828180764563104, 1.2030135384778224, 1.1337625928418005, 1.0768157208351266, 1.0336570232640927, 1.0054695090277943, 0.9931070658451843, 0.9970737924560595, 1.017511198023394, 1.0541935883981965, 1.1065317648853468, 1.173584963885022], [1.2288168816065133, 1.3184543552190058, 1.418791124957933, 1.5278289563270806, 1.643367552632366, 1.7630527218786247, 1.8844279372976174, 2.0049880882755295, 2.1222341681719517, 2.233727625473087, 2.3371431153621116, 2.4303184298294114, 2.511300454851308, 2.578386101185478, 2.6301572785377645, 2.6655091282065784, 2.683670893226792, 2.6842189834831145, 2.6670819818606333, 2.632537531622081, 2.5812012400933355, 2.514007924635412, 2.4321857091238717, 2.3372236483071087, 2.230833709365921, 2.1149080710716253, 1.9914728079840385, 1.8626391075876467, 1.730553220239198, 1.5973463641046506, 1.4650857994452118, 1.3357282489636335, 1.2110767744731064, 1.0927421266420692, 0.9821094664058345, 0.8803112168322197, 0.7882066463256336, 0.7063686120354101, 0.635077710525004, 0.5743238957169705, 0.5238154365335506, 0.48299490318570104, 0.45106169629361015, 0.4270004712911325, 0.409614665882833, 0.397564214258995, 0.38940643138224934, 0.3836389763925583, 0.3787437578300714, 0.3732306260401785, 0.36567971016551837, 0.35478129817206533, 0.33937222729996935, 0.31846784737502565, 0.29128873811064926, 0.2572815008290933, 0.21613310137559313, 0.16777841040646552, 0.11240076539291946, 0.05042556107062058, -0.017492942948554212, -0.09049123171837443, -0.16752202850899542, -0.24738498551619462, -0.3287617488285102, -0.4102544598122966, -0.4904266641700412, -0.5678455353759871, -0.6411242826506937, -0.7089636060531065, -0.7701910828663893, -0.8237974197187153, -0.8689685825765082, -0.9051129199473894, -0.931882520761638, -0.9491881943122898, -0.9572076216717543, -0.9563864021029835, -0.9474318997726128, -0.9312999809790318, -0.9091749154708713, -0.8824428926227341, -0.8526597697728143, -0.8215138216882232, -0.7907843930489176, -0.7622974666326653, -0.7378792456899418, -0.7193089075868947, -0.7082717156088965, -0.7063136760143135, -0.7147988979027587, -0.734870754849209, -0.7674178609166707, -0.8130457616498625, -0.8720551056687887, -0.944426907798871, -1.0298153440655202, -1.1275483365209142, -1.2366359962359672, -1.355786800547379, -1.48343119053992, -1.6177520914663222, -1.7567216869016151, -1.8981436211632194, -2.0396996677941095, -2.17899978811953, -2.313634415905764, -2.4412277441987755, -2.5594907600406174, -2.666272772768334, -2.759610212061066, -2.837771532137784, -2.8992971471070437, -2.943033437321445, -2.9681600049349632, -2.974209515363956, -2.961079636177447, -2.9290367718505514, -2.878711487268576, -2.811085710142267, -2.7274719977888524, -2.6294853422975195, -2.5190081653431458, -2.39814931552592, -2.2691980231672217, -2.1345738865313506, -1.996774056582003, -1.8583188523671244, -1.721697074394332, -1.5893122880751622, -1.463431323394174, -1.3461361810623087, -1.2392804509392563, -1.1444512375544271, -1.062937452861799, -0.9957051812534841, -0.9433806501471929, -0.9062411553753377, -0.8842140986554603, -0.8768840993179488, -0.88350794898174, -0.9030369907285847, -0.9341463280941019, -0.9752701081551777, -1.0246419810521792, -1.0803397188672041, -1.1403328827503936, -1.2025323607774068, -1.2648405617792717, -1.3252010431330323, -1.38164637331904, -1.4323430822737802, -1.4756326328074598, -1.5100674525319284, -1.5344411951400603, -1.547812549203901, -1.5495220781420804, -1.539201752479174, -1.516777020525846, -1.4824614515152381, -1.436744171343551, -1.3803704907412195, -1.3143162944760274, -1.2397569138732012, -1.1580313397275157, -1.0706027452559728, -0.9790163763360249, -0.8848559267631572, -0.789699548194487, -0.6950766470921622, -0.6024265943466496, -0.513060418085173, -0.42812646790944314, -0.3485809315922033, -0.27516395585141223, -0.20838197452540133, -0.1484966840757099, -0.09552093200560267, -0.04922160293299464, -0.009129404288606549, 0.02544472643851748, 0.05538704374875429, 0.08175285740824555, 0.1057335942290028, 0.12861994152337272, 0.1517620586547217, 0.17652792108383566, 0.20426091202109603, 0.23623779893095878, 0.2736282251097639, 0.31745681051686603, 0.3685688918600288, 0.427600841205652, 0.49495578735953305, 0.5707854278153842, 0.6549784646094884, 0.7471560288213406, 0.8466742799539767, 0.9526341825008151, 1.063898277288989, 1.1791140843404622, 1.2967436015814413, 1.4150982041240294, 1.5323781060955313, 1.646715424740731, 1.7562197879046906, 1.8590253535681727, 1.9533380657558808, 2.0374819560730195, 2.1099433148234588, 2.169411599858034, 2.2148160239922428, 2.245356861306193, 2.260530636512123, 2.26014850685094, 2.244347309124353, 2.213592921497595, 2.1686757762800086, 2.110698551421086, 2.0410562602296456, 1.9614091460982195, 1.8736489671605587, 1.7798594204084048, 1.682271601753477, 1.5832155241754364, 1.4850688173012698, 1.39020380596511, 1.300934210611454, 1.2194627276478827, 1.147830732581646, 1.0878713032954652, 1.0411666861794577, 1.009011225806373, 0.9923806518569954, 0.9919084681290972, 1.0078700212936174, 1.0401746456449452, 1.0883660888304736, 1.1516312270841498, 1.2288168816065115], [1.290573357473953, 1.3885882779274852, 1.4960336096545548, 1.6107763488906306, 1.730510600331046, 1.8528079676872804, 1.9751706255393375, 2.0950858353854995, 2.2100806362596916, 2.3177754383512603, 2.4159352767436726, 2.5025175409590648, 2.5757150829952025, 2.6339937198154098, 2.6761232830040886, 2.7012015251617094, 2.708670365725864, 2.698324144017621, 2.670309739884892, 2.625118617630247, 2.5635710421927995, 2.486792903083465, 2.396185756804926, 2.2933908581628453, 2.1802480911246533, 2.0587508273235757, 1.9309978321239871, 1.7991434021824246, 1.665346953169665, 1.5317232810019894, 1.400294694547035, 1.2729461630469368, 1.1513845388889654, 1.037102807988043, 0.931350188696461, 0.8351087491568517, 0.749077046178148, 0.6736611102380602, 0.6089729155770174, 0.5548362861919216, 0.5108000025612232, 0.47615769476782105, 0.44997393978594563, 0.4311158282245183, 0.4182891325409466, 0.41007809793707695, 0.4049877915361387, 0.4014878870936127, 0.398056732807607, 0.3932245494366585, 0.3856146348401053, 0.37398150842963246, 0.35724501334870346, 0.3345195032932775, 0.30513737194712853, 0.2686663326745521, 0.22492002057426108, 0.173961664064904, 0.11610075439558531, 0.05188282425341942, -0.017927373662426693, -0.0923688251712933, -0.17031272725844104, -0.25049570785226144, -0.33155690145824784, -0.41207788796079264, -0.4906244259389776, -0.56578886326853, -0.6362320878495134, -0.7007238905374306, -0.7581806505588814, -0.807699319926683, -0.8485867759915691, -0.880383727970338, -0.902882501157308, -0.9161381781045792, -0.9204727454446844, -0.9164720739716632, -0.9049757435920642, -0.8870599091705207, -0.864013583471675, -0.8373088847861829, -0.8085659550798476, -0.7795133955998537, -0.7519451872099523, -0.7276751592198207, -0.7084901406245694, -0.6961029696344055, -0.692106550007386, -0.6979301255854756, -0.7147988979027584, -0.7436980368450798, -0.7853420328626556, -0.8401502136065752, -0.9082291011187483, -0.9893621214261056, -1.083007000591301, -1.1883009943154192, -1.304073906672471, -1.4288686622025606, -1.5609690091292416, -1.6984337545140449, -1.83913676911013, -1.980811854584835, -2.121101442271, -2.2576079937757387, -2.387946902117999, -2.509799649412396, -2.6209659645842316, -2.719413742569695, -2.803325534553978, -2.8711404959180338, -2.921590782874608, -2.9537315177800925, -2.9669635937046444, -2.9610487573900772, -2.936116592140295, -2.892663214045999, -2.8315416915824057, -2.7539443952541656, -2.6613776758107264, -2.5556294519488594, -2.438730456917252, -2.312910043940342, -2.1805475792252427, -2.044120555375397, -1.9061506347856825, -1.7691488801803426, -1.6355614467394106, -1.5077169968424147, -1.3877770546956052, -1.277690445098091, -1.1791528601550878, -1.093572472347602, -1.0220423651079757, -0.9653203865557153, -0.9238168523839065, -0.8975903344638136, -0.8863515771957474, -0.8894753887400068, -0.9060201637748864, -0.9347545129958764, -0.9741903066070131, -1.0226212886383654, -1.0781662896896702, -1.1388159607576345, -1.202481872656834, -1.2670467760289406, -1.3304147971802098, -1.390560355382129, -1.4455746274604706, -1.4937084543911816, -1.5334106804198353, -1.563361035462379, -1.5824968131687425, -1.5900327564520664, -1.585473735488048, -1.5686199858195429, -1.539564861686463, -1.4986852473540042, -1.4466249523542314, -1.3842715906301533, -1.3127276042568574, -1.2332762357335068, -1.1473433752572344, -1.0564563078987521, -0.9622004577970442, -0.8661752706371703, -0.7699503907359698, -0.6750232747318626, -0.582779340589801, -0.49445567954972014, -0.41110926162127204, -0.33359044476273503, -0.2625224570672932, -0.19828736371208194, -0.14101886011957238, -0.09060205406791645, -0.046680216906130605, -0.00866830221470223, 0.024227146186179417, 0.052982241566555774, 0.07872485415393071, 0.10269939530722536, 0.1262282309781656, 0.15067075841511846, 0.17738124253427542, 0.20766654274820745, 0.2427448664095516, 0.28370666123534277, 0.33147870669719576, 0.3867923846867803, 0.4501570047756944, 0.5218389317042492, 0.6018471155493127, 0.6899254620260746, 0.7855523056636935, 0.887947066552489, 0.996083986573066, 1.1087126581447164, 1.224384882190474, 1.3414872266727065, 1.4582785069018427, 1.5729312776847313, 1.683576318613375, 1.7883490102005157, 1.8854364423238625, 1.9731240690450107, 2.049840726104037, 2.1142008593003325, 2.1650428728591735, 2.2014625953316873, 2.2228409744747197, 2.228865249159001, 2.2195430023414775, 2.1952086707030647, 2.1565222694941175, 2.1044602809521455, 2.0402988466846486, 1.9655895939048793, 1.8821286076814934, 1.7919192318965844, 1.6971295361608223, 1.600045420658659, 1.5030204424186666, 1.4084235320209635, 1.3185858270951183, 1.2357478766499561, 1.1620084675600637, 1.099276291407377, 1.0492256070845511, 1.0132569635820605, 0.9924639303723988, 0.9876066425810848, 0.9990928080787992, 1.0269666476144204, 1.0709060514028332, 1.1302280407423908, 1.2039024260008835, 1.290573357473951], [1.358331903756382, 1.4638891734794737, 1.5775164941329896, 1.696964150980845, 1.8198401792157253, 1.943662551833998, 2.0659133137810595, 2.184093401867811, 2.295776875448431, 2.3986632990443164, 2.4906270645796815, 2.5697625164997917, 2.6344238459001454, 2.6832588473649794, 2.7152357813540937, 2.7296627520209524, 2.726199191190066, 2.7048592294327745, 2.666006930098555, 2.610343557016046, 2.5388872366152437, 2.452945555806705, 2.354081803692555, 2.2440757140329644, 2.124879692753888, 1.998571617596007, 1.8673053728208484, 1.733260328927865, 1.5985909945296772, 1.465378054553828, 1.3355819662068422, 1.2110002128026138, 1.0932292174798615, 0.9836317965276058, 0.8833108886132309, 0.7930901352903462, 0.713501713805267, 0.6447816397972781, 0.5868725695902743, 0.5394339440939262, 0.5018591335472858, 0.4732990689905773, 0.45269168674053695, 0.43879637021793694, 0.4302324527302067, 0.4255207482083651, 0.42312700678771237, 0.4215061501905093, 0.41914612909253623, 0.41461026127831474, 0.40657695491926277, 0.3938757945281353, 0.37551906614239916, 0.35072792051427043, 0.3189525154022372, 0.27988563683262174, 0.23346947038545998, 0.1798953728037282, 0.11959667697688615, 0.05323474497234761, -0.018321340323401752, -0.09402088869684992, -0.17266281367251668, -0.25293110051620693, -0.3334335790714055, -0.4127429622893824, -0.48943905093114615, -0.5621509727336518, -0.6295983211785177, -0.6906300849826195, -0.7442603139159668, -0.7896995481944862, -0.826381145459818, -0.853981768576657, -0.8724354459141204, -0.8819407797073798, -0.8829610534010854, -0.8762171711468925, -0.8626735472723687, -0.8435172458989386, -0.8201308463540565, -0.7940596741531756, -0.7669741859531979, -0.7406284262139046, -0.7168155800365242, -0.6973217280273737, -0.6838789629360448, -0.6781190528014794, -0.6815288306837237, -0.6954084567815544, -0.7208336355923294, -0.758622780237869, -0.8093100003218818, -0.8731246514963593, -0.9499780276566867, -1.039457604199877, -1.1408290572961433, -1.2530460941525545, -1.3747679374709738, -1.5043841184589228, -1.6400460515163988, -1.779704694591549, -1.921153446381117, -2.0620752988601927, -2.2000931543850824, -2.3328221335735018, -2.4579226454401697, -2.5731529662693604, -2.6764200791271273, -2.7658275616949726, -2.8397193754364447, -2.8967185024549047, -2.9357594955390187, -2.9561141489617215, -2.9574096591704953, -2.939638821672365, -2.9031619988794555, -2.848700788863341, -2.7773235221232317, -2.690422907807295, -2.5896863376072377, -2.477059530226209, -2.3547043576454745, -2.2249518325330273, -2.090251350687512, -1.9531173706111162, -1.816074772018229, -1.6816041648731057, -1.5520884197030578, -1.4297616584978088, -1.3166618842728397, -1.2145883378671092, -1.1250645549759195, -1.0493079576376778, -0.9882066558140603, -0.9423039602233791, -0.9117909214886757, -0.8965070175064879, -0.8959489154573056, -0.9092870418427226, -0.9353895080575568, -0.9728527648146, -1.0200382004667585, -1.075113759748585, -1.1360995440258441, -1.200916264561757, -1.2674353587038336, -1.3335295466926493, -1.3971226046932683, -1.4562371576049766, -1.5090393524279597, -1.5538793579463481, -1.5893267470324681, -1.6141999511658582, -1.627589129414204, -1.6288719622910346, -1.6177220603597677, -1.5941098636978013, -1.5582960967115962, -1.5108180286057018, -1.4524689684304386, -1.384271590630153, -1.307445838250353, -1.223372282704246, -1.1335519280080095, -1.0395635310046998, -0.9430195652846086, -0.8455219839407863, -0.7486189343598272, -0.6537635470647936, -0.5622758610568918, -0.47530886171322456, -0.39381949632893243, -0.31854539969593676, -0.24998791108323135, -0.18840179847666869, -0.1337919301619701, -0.08591695215954305, -0.04429984725215862, -0.008245072022125833, 0.02313820302075654, 0.05090738414297866, 0.07625305248699618, 0.10046176879320151, 0.12487608353989654, 0.15085282524156468, 0.17972078607935102, 0.21273894176659036, 0.2510563311058279, 0.2956746803360718, 0.3474147890925901, 0.4068876003032024, 0.47447075798296157, 0.5502913176250829, 0.6342151172109798, 0.7258431467095223, 0.824515074582608, 0.9293199057757117, 1.03911356158795, 1.1525429923340351, 1.2680762633711966, 1.3840378981868435, 1.4986486228170284, 1.6100685374516999, 1.716442646721325, 1.8159476122961717, 1.9068385518513125, 1.9874946982426793, 2.0564627522551673, 2.112496811135155, 2.1545938321873193, 2.182023694172894, 2.194353046606979, 2.1914622852281322, 2.1735551572925558, 2.141160678879302, 2.0951272336989, 2.036608914363855, 1.9670443579813977, 1.888128513545295, 1.801777954333382, 1.7100905099958328, 1.6153001362220825, 1.519728061222742, 1.4257313447091386, 1.3356500541583345, 1.2517543031460316, 1.1761924063572624, 1.110941385231545, 1.0577610074984853, 1.018152464286378, 0.9933226819254022, 0.9841551345692777, 0.9911878714788007, 1.0145993029273654, 1.0542021053184731, 1.1094454136982266, 1.1794252730780284, 1.2629031236397255, 1.3583319037563781], [1.431519252491154, 1.5437199622245532, 1.6625503963191197, 1.78566317479161, 1.9106005206269383, 2.0348478034247237, 2.1558882778187183, 2.2712577434336354, 2.378597856776638, 2.4757068596486125, 2.5605865525466207, 2.6314844335298115, 2.6869300408659393, 2.7257646785623892, 2.747163864153129, 2.750652013926226, 2.736109067824085, 2.703768949948803, 2.6542099562194577, 2.5883373534780674, 2.507358659525405, 2.4127522466791946, 2.306230068282347, 2.1896954443521652, 2.0651969559583274, 1.9348795852346183, 1.8009342971014966, 1.665547288436136, 1.530850129936753, 1.3988719953974824, 1.2714951133892387, 1.1504144890005974, 1.0371028305804986, 0.9327814812136214, 0.8383980003728851, 0.7546108717196534, 0.6817816326168905, 0.6199745341011059, 0.5689636514923457, 0.5282471802067741, 0.49706847328938575, 0.47444321112158816, 0.45919194378835343, 0.4499771164106382, 0.44534358055739814, 0.4437615132636836, 0.4436706111678512, 0.44352440211908073, 0.4418335208492255, 0.4372068287658217, 0.42838931968956084, 0.4142958418049135, 0.3940397789253165, 0.3669559684939205, 0.3326172861109196, 0.29084449291333075, 0.24170911859511687, 0.1855293347619731, 0.12285895604986118, 0.05446988536637193, -0.01867150979525559, -0.09543344509005067, -0.17455240495673294, -0.25467055898406615, -0.33437590412616935, -0.41224405596829644, -0.4868805679555015, -0.556962641971442, -0.6212791073055572, -0.6787675875511661, -0.7285478452846705, -0.7699503907359692, -0.8025395606637188, -0.8261304142898429, -0.8407989508968828, -0.8468853245856354, -0.8449899114298803, -0.835962268322125, -0.8208832065363529, -0.8010403817988482, -0.7778979719312008, -0.753061168616163, -0.728236347580167, -0.7051878979670304, -0.6856927839016533, -0.6714939768182966, -0.6642539343243005, -0.6655093091623374, -0.6766280499298611, -0.6987700040616993, -0.7328520543598667, -0.779518714944948, -0.8391189834440155, -0.9116900966535598, -0.9969486704724883, -1.094289525667449, -1.2027923134155445, -1.3212358631901986, -1.4481199851414979, -1.581694274385403, -1.719993290140027, -1.8608773227702589, -2.0020778205118845, -2.1412464284785946, -2.276006498507705, -2.4040058618553437, -2.5229696194193845, -2.6307516970413563, -2.7253839367669936, -2.8051215482318685, -2.8684838263462002, -2.914289150238913, -2.941683411379718, -2.950161172728383, -2.9395790319418786, -2.910160845955099, -2.862494667166037, -2.797521438312847, -2.716515689138686, -2.621058668329255, -2.513004524340296, -2.3944403142206383, -2.2676407663499045, -2.135018847574026, -1.999073284506981, -1.8623342603610245, -1.7273085508384587, -1.5964253743513581, -1.4719842128659766, -1.3561058104789419, -1.2506874786476359, -1.1573637317505736, -1.0774731469388052, -1.0120321912490273, -0.961716590391512, -0.9268506316382992, -0.9074046022786705, -0.9030003698550251, -0.9129249156155954, -0.9361514430759714, -0.9713675038873362, -1.0170094177347133, -1.07130211574487, -1.132303411427123, -1.1979516025139139, -1.2661152336086736, -1.3346438050076475, -1.4014181984449132, -1.4643996060812596, -1.52167579433567, -1.5715036079301672, -1.6123467198675518, -1.642907757419507, -1.6621540794106437, -1.6693366424765028, -1.6640015694644585, -1.6459942173362925, -1.6154557302127928, -1.572812250876949, -1.5187571464507952, -1.4542267765517205, -1.3803704907412195, -1.2985156825869568, -1.210128846709636, -1.1167736798642702, -1.020067335110413, -0.9216359778288261, -0.823070802825175, -0.7258856528395952, -0.6314773310071599, -0.5410896244627005, -0.4557819553186171, -0.37640345127050967, -0.30357308428103436, -0.2376663658301984, -0.17880891517432249, -0.12687703730056912, -0.08150526436266012, -0.04210063297548083, -0.007863294429820497, 0.022187109894180965, 0.0491800257107101, 0.07435836496804724, 0.09903964601977784, 0.12457493898774694, 0.15230671876632246, 0.1835267581220148, 0.21943519428526104, 0.2611018742674766, 0.30943102755476837, 0.36513023123482435, 0.42868452409199154, 0.5003363954732212, 0.5800722250622923, 0.6676155848596321, 0.7624276387944715, 0.8637146929221765, 0.9704427646823933, 1.0813588578697368, 1.1950184553962506, 1.3098185790272656, 1.4240356181884346, 1.5358670024212577, 1.6434756873740064, 1.7450363450566049, 1.8387820975294202, 1.923050610619355, 1.99632837132309, 2.0572920091886706, 2.104845587346494, 2.1381528814548, 2.1566637824158694, 2.1601340984636663, 2.148638190719408, 2.1225740496830254, 2.082660604120902, 2.029927243896354, 1.9656957297795683, 1.8915548514337976, 1.809328374942291, 1.7210369889402948, 1.6288551094735033, 1.5350635343438936, 1.4419990446505915, 1.3520021317871904, 1.267364080266475, 1.1902746590520843, 1.1227716659612068, 1.066693531286945, 1.0236361189427199, 0.9949147677497817, 0.9815324942526635, 0.9841551345692773, 1.0030940397331423, 1.0382967607116078, 1.0893459701094137, 1.1554666720868458, 1.235541554989813, 1.3281341474005306, 1.4315192524911515], [1.5095162055903244, 1.6274052395661012, 1.7504158909221748, 1.8761229864447262, 2.002023751006829, 2.125592253969207, 2.244334288742425, 2.355841410311017, 2.457842877265359, 2.5482542967788318, 2.625221851719265, 2.6871610967015713, 2.7327894417238525, 2.7611515948416043, 2.7716374053730943, 2.7639917322240626, 2.7383161535873284, 2.6950625298234985, 2.635018625984809, 2.5592861894561603, 2.4692520569523055, 2.366553029283831, 2.2530353979090285, 2.1307101308092973, 2.0017048236980095, 1.8682135936541593, 1.732446134299769, 1.5965771636702935, 1.4626974777584312, 1.3327677748877431, 1.20857633986869, 1.0917015742796021, 0.9834802328215251, 0.8849820787236757, 0.7969915073332451, 0.7199965104266466, 0.654185168853369, 0.5994496724890731, 0.5553976788342156, 0.5213706396150172, 0.49646855294110337, 0.4795804412006948, 0.46941971581337094, 0.46456347263048753, 0.4634946690432396, 0.4646460679766263, 0.4664447964874148, 0.4673563585046388, 0.4659269624772537, 0.46082307471317163, 0.45086718667483744, 0.4350688874198288, 0.41265045808659595, 0.3830663506030462, 0.3460160739296028, 0.30145018403529855, 0.24956925405089475, 0.1908158840720759, 0.12585999125735492, 0.05557779558885151, -0.018974919485802835, -0.09659454348462017, -0.1759655143137756, -0.2556993666500874, -0.3343759041261694, -0.4105853899707689, -0.4829706229357443, -0.5502677666078953, -0.611344830544484, -0.6652367603391817, -0.7111761792595849, -0.7486189343598265, -0.7772637321990841, -0.7970653001700405, -0.8082406751691178, -0.8112683977524461, -0.8068805725742833, -0.7960479401908046, -0.7799582865769885, -0.7599886903615313, -0.737672269431314, -0.7146602340840192, -0.6926801796024623, -0.6734916537652214, -0.6588401117438626, -0.6504104200550086, -0.6497810914118161, -0.6583804228541413, -0.6774456705686039, -0.7079863272148028, -0.7507524729442013, -0.8062090519031789, -0.8745167847431246, -0.9555202679610881, -1.0487436366734728, -1.1533939829614839, -1.2683725317640422, -1.392293385126078, -1.5235094581685786, -1.6601450510796187, -1.8001343351848316, -1.941264881884749, -2.081225234678598, -2.217655419858125, -2.34819921339642, -2.470556932068996, -2.58253749722169, -2.6821085304023295, -2.7674432811118046, -2.836963257273555, -2.889375527012485, -2.9237037836389996, -2.939312411388092, -2.935922953952764, -2.9136225671936007, -2.8728642272517826, -2.814458661028514, -2.739558162859094, -2.64963265441167, -2.546438529673707, -2.4319809988490477, -2.3084707998851757, -2.178276280409618, -2.043871962811231, -1.9077847883820709, -1.7725392908176638, -1.6406029736447154, -1.5143331597267464, -1.3959265440655755, -1.287372614589696, -1.1904120111453418, -1.1065007728106526, -1.036781280891096, -0.9820605430327702, -0.9427962867806974, -0.919091142953016, -0.910695004999239, -0.917015454810282, -0.9371359530275516, -0.9698413074490405, -1.0136497611392794, -1.0668508864913988, -1.1275483365209142, -1.1937063933421734, -1.263199168750701, -1.333861255117385, -1.403538597700376, -1.4701383625719509, -1.531676607469251, -1.5863226250961544, -1.6324389181001457, -1.6686158798161632, -1.6937003919873939, -1.7068177065722931, -1.707386149504166, -1.6951243655993307, -1.6700510111763036, -1.6324769896746905, -1.5829905109496518, -1.5224354323598235, -1.4518835048659535, -1.3726012960336802, -1.2860126904245215, -1.1936579732109152, -1.0971505823975565, -0.9981326668552819, -0.8982306102557561, -0.7990116744418502, -0.7019428800238623, -0.6083531780314322, -0.5193998759556956, -0.43604016683002195, -0.3590084740680442, -0.28880017108148776, -0.22566206715659795, -0.1695898739386104, -0.12033268465799993, -0.07740431555234076, -0.04010118042403373, -0.00752619944897336, 0.021381913484677828, 0.04781478050372569, 0.07305682151085006, 0.09844505878913508, 0.1253273451408975, 0.15502013839227802, 0.18876695841656466, 0.22769864697782424, 0.2727965060536899, 0.3248593179691442, 0.3844751524670462, 0.4519987442146739, 0.527535082248971, 0.6109296940629441, 0.7017659354250861, 0.7993694169232122, 0.9028195141732162, 1.010967725277877, 1.122462461095668, 1.2357796856934908, 1.3492586702796179, 1.461141987867101, 1.5696187613815702, 1.6728700878464013, 1.7691154979925017, 1.8566592758224654, 1.9339354572747722, 1.9995503514147002, 2.0523214810156465, 2.09131192074982, 2.115859118544428, 2.125597416389569, 2.120473637830325, 2.100755276850494, 2.0670310027524774, 2.0202033835318938, 1.9614739215035266, 1.8923206848294507, 1.8144690024266314, 1.7298558629259009, 1.6405888166051612, 1.5489003185774537, 1.457098568485621, 1.3675159935951708, 1.2824565861569914, 1.2041433405842656, 1.134667040422152, 1.075937619098701, 1.0296392625930166, 0.9971903377389508, 0.9797091189026333, 0.9779861508866766, 0.9924639303723979, 1.0232244157730765, 1.0699846902154497, 1.1321009089883307, 1.2085804658978665, 1.298102117339876, 1.3990436133049078, 1.509516205590322], [1.5916628735366491, 1.7142369901897867, 1.8403695960982223, 1.9675782550000742, 2.0933363884568976, 2.215128164353509, 2.3305030532774866, 2.4371287864036244, 2.5328414881824757, 2.6156918262887614, 2.6839861182188063, 2.7363214562506597, 2.77161405719101, 2.7891202068781396, 2.7884493477808654, 2.76956904686137, 2.7328017755355205, 2.6788136293108207, 2.6085953067325693, 2.5234358509437538, 2.4248898279971485, 2.314738769905164, 2.1949478435548206, 2.067618815848093, 1.934940468142374, 1.799137667310106, 1.6624203252642158, 1.526933473095196, 1.3947096402715697, 1.2676246646426257, 1.14735796694025, 1.0353582064660654, 0.9328150956444845, 0.8406379936323106, 0.7594417271620801, 0.6895399045710415, 0.6309458010856854, 0.5833807045780245, 0.546289425883245, 0.5188625009637328, 0.5000644481000519, 0.48866729593680513, 0.4832884712361382, 0.4824320317034632, 0.4845321517656795, 0.4879977195639519, 0.49125688283316205, 0.49280039021207833, 0.49122261255804034, 0.4852591949931769, 0.47382038294904566, 0.45601918200706854, 0.43119364885910405, 0.3989227657189729, 0.35903551905031944, 0.31161298125250303, 0.25698337645008584, 0.1957102941346819, 0.12857439248352803, 0.05654910221796909, -0.019229002411767004, -0.09749436046273731, -0.1768901861990448, -0.2560088193358751, -0.33343357907140553, -0.4077809973616937, -0.4777422957760119, -0.542122988318053, -0.5998795393720084, -0.6501520802676487, -0.6922922879960509, -0.7258856528395945, -0.7507675050121682, -0.7670323302348186, -0.7750360764762705, -0.7753913345256651, -0.7689554590856852, -0.7568118800303636, -0.7402450307358693, -0.7207094874726518, -0.6997940664998847, -0.6791817598395083, -0.6606065032905248, -0.645807858177139, -0.6364847493205809, -0.6342494341681457, -0.6405828809986679, -0.6567927074809159, -0.6839747751593712, -0.7229794519765558, -0.7743834457040778, -0.838467978784379, -0.9152039228025305, -1.0042443423363026, -1.1049247174080907, -1.216270925628201, -1.3370148740190202, -1.4656174811707174, -1.600298527496279, -1.7390727194713558, -1.8797911571454977, -2.020187256809127, -2.157926065942792, -2.29065581835625, -2.4160605160156883, -2.5319122920457486, -2.6361223076461044, -2.7267889643028136, -2.802242271076331, -2.861083293552999, -2.90221772419406, -2.9248827505964283, -2.92866655529696, -2.913519954408573, -2.879759868362865, -2.828064511833558, -2.7594603868153498, -2.6753013580411023, -2.5772402786808946, -2.4671938119796746, -2.347301256822715, -2.2198783282127477, -2.087366963813564, -1.9522823221341707, -1.817158204298517, -1.6844921680560578, -1.5566916088547826, -1.436022058282149, -1.3245588955963938, -1.2241435847694233, -1.1363454394959873, -1.062429784695732, -1.003333228432835, -0.9596465866951431, -0.9316058193116985, -0.9190911429530155, -0.921634291354441, -0.9384336984116379, -0.9683771913610489, -1.0100716034644954, -1.0618785527840946, -1.121955489705453, -1.1883009943154192, -1.2588032084815663, -1.3312902188009796, -1.4035811670905, -1.4735368556605897, -1.5391086353890158, -1.5983844149823092, -1.6496307084451685, -1.6913297426403153, -1.7222107752369293, -1.741274922063755, -1.7478129581544979, -1.7414157344501415, -1.7219770377571215, -1.689688910518091, -1.6450296345262376, -1.5887447642437726, -1.5218217663695526, -1.4454589785119418, -1.3610297374103624, -1.2700426427344098, -1.1740990132510372, -1.0748486558919894, -0.9739451034582972, -0.8730014825661168, -0.7735481499038144, -0.6769931826048777, -0.5845867289355852, -0.4973901206229694, -0.4162505207113138, -0.34178173409998724, -0.2743516456277847, -0.21407657686121576, -0.1608226720300503, -0.1142142404189726, -0.07364880161122081, -0.03831840587116518, -0.007236639055659641, 0.020729426118227135, 0.04682319911425701, 0.07235943376200768, 0.0986830375782983, 0.12712693630282484, 0.15897012736155935, 0.19539705249729072, 0.23745938729524527, 0.2860412845876753, 0.34182902126091264, 0.4052858860019545, 0.4766330118192067, 0.5558367051125422, 0.642602656476129, 0.7363772414883454, 0.83635593693643, 0.9414986938528102, 1.0505519280577715, 1.162076616182859, 1.2744818247727736, 1.3860628561094133, 1.4950430705445346, 1.5996183445443166, 1.6980030489397695, 1.788476384999237, 1.869427898157432, 1.9394010010894103, 1.997133379107972, 2.0415932206536285, 2.0720103122885942, 2.087901158778468, 2.089087431608266, 2.0757072101504765, 2.0482186547399883, 2.00739593581146, 1.9543174334606792, 1.8903464126033478, 1.8171045655963658, 1.7364389921242454, 1.6503833509095103, 1.5611140652691498, 1.4709025910186193, 1.3820648575379753, 1.29690906837238, 1.217683094604291, 1.1465227111771292, 1.0854019128725831, 1.0360865029988489, 1.0000920750301585, 0.9786474071630145, 0.9726641644148164, 0.9827136554970566, 1.0090112258063717, 1.0514086875082065, 1.1093949972163373, 1.1821051958254785, 1.2683374284013813, 1.3665776694617544, 1.4750315951844062, 1.5916628735366465], [1.677264258347511, 1.8034805781935177, 1.931650462796957, 2.059255227501695, 2.183765886744877, 2.302698020260316, 2.413665544684126, 2.5144321437267583, 2.602959167342372, 2.6774488961629177, 2.736382179759525, 2.7785495932899735, 2.803075413452222, 2.809433887558224, 2.7974574547361803, 2.7673367712325536, 2.719612587802265, 2.655159721461818, 2.575163551700302, 2.4810896480271256, 2.3746472971910326, 2.257747840623756, 2.132458852214478, 2.0009552805422697, 1.8654687459506363, 1.7282362197965428, 1.5914493200263182, 1.4572054338472382, 1.3274618253461552, 1.2039938048523975, 1.088357929740524, 0.9818610759473541, 0.88553606903613, 0.8001243969653263, 0.7260663479911074, 0.6634987308201485, 0.6122601448810879, 0.5719035811077785, 0.5417159525809307, 0.5207439842408564, 0.507825735866026, 0.5016268964270028, 0.5006808741100949, 0.5034316175341926, 0.5082780421013166, 0.5136189024864889, 0.5178969487270112, 0.5196412292195989, 0.5175064584454896, 0.5103084489707981, 0.49705471408526575, 0.4769694765943083, 0.4495124674580159, 0.41439106139470994, 0.3715654710759822, 0.32124690270176837, 0.2638887589622644, 0.2001711560259158, 0.13097919466572655, 0.05737558756012108, -0.01943160891662061, -0.09812528316559536, -0.17731859746997242, -0.2555962989316787, -0.331556901458248, -0.4038546045715458, -0.4712398204899208, -0.5325972156118013, -0.586980235339553, -0.6336411705558682, -0.6720559377592167, -0.7019428800238616, -0.7232750491746521, -0.7362855969999034, -0.7414660807485344, -0.7395576710947476, -0.7315354345855092, -0.7185860426642788, -0.7020794311278642, -0.6835350929626913, -0.6645838298737954, -0.6469259098289323, -0.6322866764594577, -0.6223707286405191, -0.6188158331138258, -0.6231477484112401, -0.6367371241071892, -0.6607595958331683, -0.696160124522871, -0.7436225297270076, -0.8035450439168103, -0.8760225704698027, -0.9608361660231115, -1.0574500920620933, -1.1650165953110982, -1.282388386280498, -1.4081385949039875, -1.5405877962920476, -1.6778375228506361, -1.8178095157708423, -1.9582898232631143, -2.096976728538748, -2.2315313905644483, -2.3596300075686183, -2.479016269037763, -2.587552847676581, -2.683270698949036, -2.764414982053884, -2.8294864914587503, -2.8772775906488364, -2.9069017670916093, -2.9178160765172514, -2.9098359118661565, -2.8831417136094264, -2.838277429204827, -2.776140725564966, -2.697965154813391, -2.605294665504168, -2.499951034202966, -2.3839949614174936, -2.259681727196861, -2.129412431602254, -1.9956819505170798, -1.8610248153477589, -1.7279602741666642, -1.5989378105765475, -1.4762843845851086, -1.3621546173719645, -1.2584850700587098, -1.1669536672218652, -1.0889451913611286, -1.0255236279076132, -0.9774119752232355, -0.944979954449193, -0.9282398644030475, -0.9268506316382984, -0.9401299100316283, -0.9670738926263607, -1.0063843156029646, -1.0565019646136296, -1.115645841420689, -1.1818570174985674, -1.253046094152552, -1.3270431083325775, -1.4016486715697734, -1.4746851075241065, -1.5440463619513722, -1.607745497178671, -1.6639586503832475, -1.7110644293503459, -1.7476778385266645, -1.7726779690626235, -1.7852288455964236, -1.7847929957783093, -1.771137491627224, -1.7443324001804033, -1.7047417698469725, -1.6530074637118535, -1.5900263271726138, -1.5169213403719475, -1.4350075518897718, -1.3457537154934087, -1.2507406533466092, -1.1516174444817933, -1.0500565847375434, -0.9477092826507947, -0.8461620445964727, -0.7468956621510358, -0.6512476463126731, -0.5603790586334106, -0.47524657095416456, -0.396580446323574, -0.3248689773816573, -0.2603497489832958, -0.20300791343444488, -0.15258148394399268, -0.1085734693903769, -0.07027049588663158, -0.03676739239630713, -0.006997063061834347, 0.020235168133202967, 0.04621367076955468, 0.07227210193744686, 0.09975156897902458, 0.12995848711797484, 0.16412326698009594, 0.20336094676811822, 0.24863483495765348, 0.3007241530497046, 0.360196566061347, 0.4273863636168795, 0.5023789098545223, 0.5850018195278787, 0.6748231447076526, 0.77115667573832, 0.873074276138222, 0.9794249885983406, 1.088860472754503, 1.1998661694536632, 1.310797435024571, 1.4199197564504475, 1.525452047720869, 1.625611941860974, 1.718661934430467, 1.8029552042118324, 1.876979936211499, 1.93940100108941, 1.989097903082313, 2.0251979940398726, 2.0471040623044767, 2.054515539147661, 2.047442719064167, 2.0262135596593307, 1.9914728079840378, 1.94417338851147, 1.8855601788585927, 1.8171464881066781, 1.7406837344847084, 1.6581249897227794, 1.5715832123065, 1.4832851272912981, 1.3955218228665225, 1.310597220648715, 1.2307756355196022, 1.1582296701779646, 1.0949896886434816, 1.042896081675172, 1.003555476136692, 0.9783019511754075, 0.9681642087983552, 0.9738395077891762, 0.9956750112555794, 1.0336570232640907, 1.0874084032461242, 1.1561942526836753, 1.2389357717270162, 1.3342319886542766, 1.4403888771989561, 1.5554552003273718, 1.6772642583475081], [1.7655961335723434, 1.8943809624396009, 2.023486213581046, 2.1503782752779235, 2.2725471713954377, 2.387560941082847, 2.4931181706535885, 2.587097460897297, 2.6676026874507457, 2.733003013644773, 2.7819667419512983, 2.813488238671712, 2.826907333197091, 2.82192077395126, 2.7985855135779834, 2.7573137913995502, 2.6988601768839597, 2.6243009290404085, 2.5350062086636207, 2.432605848744824, 2.318949539079581, 2.196062410490017, 2.06609710903133, 1.931283528566107, 1.793877419328852, 1.656109109442705, 1.5201335654051338, 1.3879829766907537, 1.2615229799264371, 1.1424135413841738, 1.0320753952820398, 0.931662792655385, 0.8420431549555724, 0.7637840520831369, 0.6971477406306434, 0.6420933092876651, 0.5982862893464233, 0.5651154037363508, 0.5417159525809307, 0.5269991712464825, 0.5196867522325025, 0.5183495985868555, 0.5214497768367756, 0.5273845641241278, 0.5345314390727735, 0.5412928499429964, 0.5461396071567339, 0.5476517898835784, 0.5445561269098189, 0.5357589086224678, 0.5203736071284315, 0.49774252220922344, 0.46745192838862526, 0.42934036884935767, 0.38349992094258645, 0.33027044104823494, 0.2702269789266561, 0.20416072883561467, 0.13305405208930368, 0.058050259175323984, -0.01958102485765209, -0.09848197370163239, -0.177247123573348, -0.2544652955467851, -0.3287617488285103, -0.3988394306600429, -0.46351821096079454, -0.5217710408366965, -0.5727560523962334, -0.6158437209712734, -0.6506383372291374, -0.6769931826048771, -0.6950189633033984, -0.705085231741516, -0.7078147053403625, -0.7040705764672353, -0.6949370894137809, -0.6816938359740549, -0.6657843859957878, -0.6487800190308083, -0.6323394540877149, -0.6181655831393174, -0.6079602976591196, -0.6033785538766633, -0.6059828501499823, -0.6171992880693653, -0.6382763575809068, -0.670247526240401, -0.7138986250895559, -0.76974091068729, -0.8379905472657473, -0.9185550981201461, -1.0110274449783951, -1.1146873724199065, -1.2285108659035509, -1.3511869812827673, -1.4811419555564065, -1.6165700476996896, -1.7554704292441594, -1.895689291052578, -2.0349661993012758, -2.17098362339515, -2.301418474190481, -2.4239944346433164, -2.536533838304275, -2.6370078546832176, -2.723583774405169, -2.7946682505193996, -2.848945443826477, -2.885409137479633, -2.9033880265826646, -2.9025635486618833, -2.882979796860071, -2.8450452452187953, -2.78952620992578, -2.7175321671736183, -2.6304932425122844, -2.530130373545543, -2.418418822959947, -2.2975458779108284, -2.169863710840407, -2.0378384924753044, -1.9039969372205923, -1.7708715222539013, -1.6409456528379476, -1.5166000469571976, -1.4000615823376963, -1.2933557889716891, -1.1982640819153196, -1.1162867145282054, -1.0486122942888432, -0.9960945452329493, -0.9592368267939515, -0.9381847326404475, -0.9327268995563839, -0.9423039602233779, -0.9660253797274294, -1.0026937284515585, -1.050835768283794, -1.1087395690311428, -1.1744967314572239, -1.2460486758398626, -1.3212358631902015, -1.3978487524635637, -1.4736792627090975, -1.5465715049072393, -1.614470574243588, -1.6754682490316453, -1.7278445259678934, -1.7701040307337548, -1.8010064753701895, -1.8195904859968188, -1.8251902925029364, -1.8174449515917719, -1.7962999615204467, -1.7620013163871595, -1.7150822351615294, -1.6563429811866188, -1.5868243571338836, -1.507775614188416, -1.4206176487979918, -1.3269024723407155, -1.2282700258255888, -1.1264034711479969, -1.0229841210747248, -0.9196471713486476, -0.8179393701370312, -0.7192797032902908, -0.6249240900342683, -0.5359349749697588, -0.45315657139954985, -0.3771963613969329, -0.3084132934879999, -0.24691294352956392, -0.19254972277750312, -0.14493603386082576, -0.10345809504759233, -0.06729798037370383, -0.03546126227529847, -0.006809498388814599, 0.019903321175812897, 0.0459913523552296, 0.07279556490392146, 0.10164161273214803, 0.13379804138515985, 0.17043595935489275, 0.21259126307981355, 0.26113044062087815, 0.31672088772851525, 0.3798065546300267, 0.4505896052706187, 0.5290186163730903, 0.6147836754296618, 0.7073185588471387, 0.8058099884233847, 0.9092137807637029, 1.016277524794416, 1.1255692517451226, 1.2355114041874415, 1.3444192699531514, 1.4505429266054137, 1.5521116456889756, 1.647379635736006, 1.7346719607989893, 1.812429458268009, 1.8792514963253932, 1.9339354572747722, 1.9755119071009948, 2.003274512210454, 2.016803888942539, 2.0159847171012486, 2.001015611869843, 1.9724114250361766, 1.9309978321239865, 1.8778982522111936, 1.814513337212576, 1.7424934524980966, 1.6637047463065036, 1.58018956712004, 1.4941221319469158, 1.407760470704895, 1.323395769529916, 1.243300306365398, 1.1696752138044868, 1.10459931575164, 1.049980265672917, 1.0075091653959538, 0.9786197657199407, 0.9644532453367183, 0.9658294352468392, 0.9832252050889179, 1.0167605592274471, 1.0661928081467122, 1.1309189891016334, 1.2099865137393055, 1.3021118243046879, 1.4057066488591843, 1.5189112643340785, 1.639634008642199, 1.7655961335723387], [1.8559111715761096, 1.9861690845444155, 2.1150998764426987, 2.2401764561109183, 2.358929112566442, 2.4689989481100283, 2.5681887260174436, 2.6545099564505437, 2.726225135075948, 2.7818841657619036, 2.8203541387707323, 2.8408417956460243, 2.8429081876005093, 2.8264752213479807, 2.79182398041802, 2.7395849063071958, 2.670720117567548, 2.5864983313942416, 2.488463026916023, 2.378394647977951, 2.258267781899943, 2.130204366155857, 1.9964240643817408, 1.859193014468155, 1.7207721832956857, 1.5833665642400756, 1.4490764249555086, 1.3198517549368098, 1.1974509764823418, 1.0834048711322901, 0.9789865392744608, 0.8851880567817897, 0.8027043231367009, 0.7319244147476396, 0.6729305695847803, 0.6255047395258201, 0.5891424596227574, 0.5630736035159893, 0.5462894258832446, 0.5375751402680388, 0.5355471476338496, 0.5386939207889795, 0.5454194651010768, 0.5540882187062831, 0.5630702270618739, 0.5707854278153847, 0.5757459124520627, 0.5765950901858767, 0.5721427655157023, 0.5613952515430686, 0.5435797736914757, 0.5181625694860017, 0.4848602556937586, 0.44364421017720923, 0.3947378978038591, 0.33860725307429296, 0.275944412134285, 0.2076452589725059, 0.13478141052157222, 0.05856740903642079, -0.019675986108388846, -0.0985614143075092, -0.1766763692106793, -0.2526253779816157, -0.3250717694382613, -0.3927779062678683, -0.45464279549931874, -0.5097360583302358, -0.557327333566268, -0.596910305990788, -0.6282206889978755, -0.6512476463126724, -0.6662383066709057, -0.6736952036680725, -0.674366656115129, -0.6692302875217743, -0.6594700621315933, -0.646447384722209, -0.6316669678451526, -0.6167383093293208, -0.6033337411515438, -0.5931441051486576, -0.5878331790619731, -0.5889920162781308, -0.5980943732719165, -0.6164543798087229, -0.6451875588081212, -0.6851762265180312, -0.737040201117866, -0.801113621535777, -0.8774285312057839, -0.9657057173052939, -1.0653531187366074, -1.1754719301177434, -1.2948703389247513, -1.4220846433895624, -1.5554073145107599, -1.692921391164366, -1.8325404371594605, -1.9720531471766798, -2.1091715684222425, -2.241581809559344, -2.3669960404691412, -2.483204547402057, -2.588126599152227, -2.6798589013277363, -2.756720467154272, -2.8172928133583817, -2.8604544966372027, -2.885409137479633, -2.8917062305019186, -2.8792542103178316, -2.8483254251641843, -2.7995528625981168, -2.7339186679010035, -2.6527346915841874, -2.5576154928214856, -2.4504444060874278, -2.333333444352708, -2.2085779598248023, -2.078607108814854, -1.9459312677945932, -1.8130876206245417, -1.6825851805070027, -1.556850523383384, -1.438175491936491, -1.3286680815107788, -1.2302076423014212, -1.1444054279762244, -1.0725713920352948, -1.015687982839207, -0.9743915200279829, -0.9489615531250435, -0.939318411920282, -0.9450289624239034, -0.9653203865557136, -0.9991016130503816, -1.0449918459579872, -1.10135546999934, -1.1663424629458772, -1.2379333177336516, -1.313987374252714, -1.3922933851260781, -1.4706210930852486, -1.546772580823691, -1.6186321677890623, -1.6842136718339256, -1.741703925822359, -1.7895015383201125, -1.8262500108519606, -1.8508644687717117, -1.862551424918085, -1.8608211708597033, -1.8454925752735254, -1.8166902582483653, -1.7748342993510013, -1.7206228214460864, -1.6550079669633582, -1.5791659442430188, -1.494461964800959, -1.4024110143282629, -1.3046354979996393, -1.2028208718482567, -1.0986704148735054, -0.993860310196551, -0.8899961877117292, -0.7885722357846252, -0.6909339168299057, -0.598245222967324, -0.5114612859535038, -0.4313070133511961, -0.3582622640612685, -0.29255390495104094, -0.23415491072095146, -0.1827904859157335, -0.13795100574785873, -0.09891139577229333, -0.06475640389875559, -0.03441106595999357, -0.006675531918608163, 0.019736692821478958, 0.0461581247856672, 0.07392539392786546, 0.10433717821226207, 0.1386131147378615, 0.17785479625193307, 0.2230099087796117, 0.27484048580667936, 0.3338961490101195, 0.4004930775900399, 0.47469930103919494, 0.556326747403159, 0.6449303048405188, 0.7398139729866249, 0.8400439968374126, 0.9444686942504286, 1.051744513308855, 1.1603676921484576, 1.268710745568693, 1.3750628736209651, 1.4776732806976582, 1.574796312186433, 1.6647372616292366, 1.74589767597764, 1.8168189906913028, 1.876223360072658, 1.9230506106193548, 1.9564903348377518, 1.976008257742143, 1.9813661453804092, 1.9726346808291397, 1.9501989043606622, 1.9147559966856684, 1.8673053728208489, 1.8091312445535725, 1.7417779969520326, 1.6670189042397539, 1.586818878135128, 1.5032920932574279, 1.418655465622155, 1.3351790682799582, 1.25513465005744, 1.180743477035062, 1.1141247404430132, 1.057245768391776, 1.0118752423507618, 0.9795405533594207, 0.9614903391422591, 0.9586631238320967, 0.9716628397492098, 1.0007418490678057, 1.045791906135499, 1.1063433129915188, 1.1815723258296211, 1.270316673513422, 1.3710988555661976, 1.4821567010481187, 1.6014804959401545, 1.7268558293191982, 1.8559111715761065], [1.947445266269284, 2.0780683754603633, 2.205716358338458, 2.327890036756698, 2.4421808799473155, 2.5463230389512974, 2.638242079907506, 2.71609929016962, 2.7783305377841154, 2.8236787958484277, 2.851219595470242, 2.8603788407432864, 2.850942602193755, 2.823058697062499, 2.7772300608864517, 2.7143001103457847, 2.6354304874883665, 2.542071755605271, 2.4359277828361194, 2.318914697015837, 2.193115420776661, 2.060730896477444, 1.9240291837508534, 1.7852936566190059, 1.646771541228475, 1.5106240190374465, 1.3788790742393635, 1.2533881895511687, 1.1357878931559084, 1.0274670341487961, 0.9295405174625838, 0.8428300656221173, 0.7678523978977279, 0.7048150319073426, 0.6536197230789567, 0.6138733683412121, 0.5849060166471812, 0.5657954550004834, 0.5553976788342154, 0.5523824138219234, 0.5552727359480617, 0.5624877408616374, 0.5723871444938748, 0.583316656279356, 0.5936529550082814, 0.6018471155493145, 0.6064653818731978, 0.6062262567089433, 0.6000329788174419, 0.5870005826709146, 0.5664768791043683, 0.5380568555845047, 0.5015901670470593, 0.4571815684080711, 0.4051843232903132, 0.3461868055777527, 0.28099268651304654, 0.21059526573486403, 0.13614665572855664, 0.058922661821573664, -0.019715689253679183, -0.09836293287975278, -0.17561116322214385, -0.2500921127713437, -0.3205181821828769, -0.38572131463425086, -0.4446886641364675, -0.4965940894903158, -0.5408246127925308, -0.5770011108726146, -0.604992656513565, -0.6249240900342677, -0.637176576655676, -0.6423810866212192, -0.6414049187046943, -0.6353315688682486, -0.6254344198387665, -0.6131448898355274, -0.6000158254718212, -0.5876810512213375, -0.5778120925219523, -0.5720731688830979, -0.5720756051989753, -0.5793328324629878, -0.5952171425635921, -0.6209193258902721, -0.6574122558990974, -0.7054193931063963, -0.765389064402923, -0.8374752349423767, -0.9215253325469025, -1.0170755124510489, -1.1233535675151058, -1.2392895002921633, -1.3635335832049362, -1.4944815462979126, -1.6303063532248363, -1.768995859771, -1.9083954994550105, -2.046255011365298, -2.1802781196249392, -2.308173994430338, -2.427709273515533, -2.53675940149802, -2.633358053478862, -2.7157434483652056, -2.7824004257811623, -2.832097256531481, -2.8639162780962444, -2.877277590648837, -2.8719552121302874, -2.848085269035078, -2.8061659884443264, -2.747049451889893, -2.671925268098727, -2.5822965147613424, -2.4799484844809365, -2.366910942472829, -2.245414759185827, -2.1178439160048654, -1.986683993267408, -1.8544683342694124, -1.7237231346842516, -1.5969127325082664, -1.4763863686516256, -1.3643276527374186, -1.262707903427268, -1.1732444392568442, -1.0973647768250674, -1.0361775511528266, -0.9904508115855046, -0.9605981697066752, -0.9466730876813644, -0.9483714008489936, -0.9650419719870001, -0.9957051812534818, -1.039078770099411, -1.0936103839314315, -1.157516001212671, -1.2288232998097075, -1.305418898024701, -1.385098320605937, -1.4656174811707205, -1.5447444432661244, -1.6203102233672118, -1.6902574303537845, -1.7526855965576587, -1.8058921437531879, -1.8484080412152886, -1.8790273493068246, -1.8968299975460545, -1.9011973168431147, -1.89182002731267, -1.868698571235528, -1.8321358706739468, -1.782722776229068, -1.7213166528335324, -1.6490137158665006, -1.5671158821385445, -1.477093031707889, -1.3805416848467957, -1.2791411811490268, -1.1746085027731263, -1.0686529098637518, -0.9629315527217255, -0.8590071924788217, -0.7583091007846556, -0.6620981209499497, -0.5714367603995514, -0.4871650500681864, -0.40988275395723, -0.3399383453478171, -0.2774249893742534, -0.222183589288095, -0.17381277040909157, -0.13168549610368857, -0.09497183869775233, -0.06266726934884136, -0.03362568858643915, -0.006596297068173467, 0.019736692821478958, 0.04671257709064056, 0.07565203014448277, 0.10781545971564849, 0.14436296947667032, 0.18631701095400596, 0.23452873741040453, 0.2896489773289231, 0.3521046264121807, 0.4220811175963862, 0.49951147198664425, 0.5840722637991436, 0.6751866536341288, 0.7720344612181484, 0.8735690657781664, 0.9785407440772713, 1.0855258873698301, 1.1929613834122221, 1.2991833121464595, 1.402468987274594, 1.5010812836549352, 1.5933141246697504, 1.6775379661711936, 1.7522441053363136, 1.8160866640511264, 1.8679211468562391, 1.9068385518513125, 1.9321941174012918, 1.9436299154858554, 1.941090650964384, 1.9248321912543112, 1.8954225288769757, 1.853735065621031, 1.800934297101496, 1.7384541655408166, 1.6679695319686618, 1.5913613921625145, 1.510676619206564, 1.4280831555603242, 1.3458216954783584, 1.2661549915244619, 1.1913159844083394, 1.1234559917411295, 1.0645941975766784, 1.016569660536762, 0.9809970044170415, 0.9592268726793345, 0.9523121191036479, 0.9609805737095322, 0.9856150690637305, 1.026241240991412, 1.082523433648058, 1.1537688463592124, 1.2389398632804876, 1.3366743115546262, 1.445313204010084, 1.5629353431855177, 1.6873979989548182, 1.8163827262871188, 1.9474452662692792], [2.039423997791107, 2.169301325601386, 2.294569002827055, 2.4127769206321474, 2.521598125914156, 2.6188790168085836, 2.702685549250357, 2.771344388421768, 2.823478060290369, 2.858033302421526, 2.8743019763193693, 2.871934081721359, 2.8509426021937556, 2.8117001064362652, 2.7549272261463402, 2.6816733243306508, 2.593289852885627, 2.4913970706079294, 2.377844948361299, 2.2546692231586096, 2.1240436741666224, 1.9882297784453629, 1.8495249605878663, 1.7102106770259093, 1.5725015720447806, 1.4384969086836086, 1.310135414608425, 1.1891545923721036, 1.0770554275349498, 0.9750732898467385, 0.8841556655655234, 0.8049471869487878, 0.737782242296851, 0.6826852612082107, 0.6393785796128726, 0.6072976023973184, 0.5856128026442816, 0.5732579300946221, 0.5689636514923456, 0.5712957156735017, 0.5786966297720696, 0.5895297523201853, 0.6021246562444926, 0.6148225910354563, 0.626020879194727, 0.634215117210979, 0.6380381148081141, 0.6362945963757373, 0.6279908029900363, 0.61235826931812, 0.5888712034942553, 0.5572570658420718, 0.5175001198281051, 0.46983791136558434, 0.4147508159152705, 0.3529449721146476, 0.28532909137732604, 0.21298579073058582, 0.13713823711802528, 0.059113011931466466, -0.019699798386948065, -0.09788820866105585, -0.17406051773241585, -0.2468869324859638, -0.31513951247105965, -0.37772935771755517, -0.43374003332786715, -0.4824563213201307, -0.5233875105603357, -0.5562845764164668, -0.5811507594418307, -0.5982452229673234, -0.6080796486442245, -0.6114078122009756, -0.6092083643229071, -0.6026612190058162, -0.5931181194704018, -0.5820681054903064, -0.5710987418625767, -0.5618540822590146, -0.5559904328950277, -0.5551310439981548, -0.5608208922753904, -0.5744827234971411, -0.597375500698764, -0.6305563508497526, -0.6748470223847058, -0.7308057596560212, -0.7987053707333253, -0.8785181152038518, -0.9699078723957221, -1.0722298718453744, -1.184538081271722, -1.3056001574217038, -1.433919676627023, -1.5677651794492329, -1.7052053919389123, -1.844149829091081, -1.9823938479789738, -2.117667102270671, -2.247684259310109, -2.370196777990816, -2.4830445119050255, -2.5842058986317054, -2.6718455227131055, -2.7443578962897446, -2.800406386215543, -2.8389563277503664, -2.8593014999659836, -2.8610832935529995, -2.8443020740206317, -2.809320428160985, -2.7568581746125096, -2.687979215706786, -2.6040705027336113, -2.506813575554651, -2.39814931552592, -2.2802367136032498, -2.155406599319485, -2.0261113975193568, -1.8948720753512953, -1.7642235097048344, -1.6366595433886786, -1.514579005934987, -1.400233951802158, -1.295681315496133, -1.2027391010410795, -1.1229481143118656, -1.0575401136567248, -1.0074131002430713, -0.9731142984164928, -0.9548311922543088, -0.9523907919161106, -0.9652671070437202, -0.99259660912878, -1.0332012752042636, -1.085618626036009, -1.148138007540492, -1.218842218416786, -1.2956534634698649, -1.3763825137835284, -1.4587798841153137, -1.5405877962920504, -1.6195916859224542, -1.6936700286075703, -1.7608413104692997, -1.8193070449477253, -1.867489841454929, -1.9040656589834322, -1.9279895259329978, -1.9385141725201478, -1.9352012000387477, -1.9179245975091013, -1.886866606251108, -1.842506121926852, -1.785600006937392, -1.7171578591963674, -1.6384109419727557, -1.550776119798583, -1.4558157639427058, -1.355194684776988, -1.2506352152457436, -1.143871608008823, -1.0366049177941943, -0.9304595199339082, -0.826942366572283, -0.7274060049534473, -0.6330162795319138, -0.5447255140552415, -0.46325182446357394, -0.3890650521467126, -0.32237963390056246, -0.263154544229333, -0.21110026202740118, -0.16569253179322616, -0.12619251397508044, -0.0916727542594909, -0.06104825174759759, -0.03311177480260279, -0.006572464200199389, 0.019903321175812914, 0.047650018352757104, 0.07796086543006905, 0.11204702940684762, 0.15099895922865705, 0.1957510092955361, 0.24705029446964372, 0.3054306286484092, 0.37119226797644733, 0.44438803006191263, 0.5248161959191159, 0.6120204259373448, 0.7052967394085435, 0.8037074236313334, 0.9061015579921328, 1.0111416652849177, 1.117335841266539, 1.2230745681595114, 1.3266712922184996, 1.42640574279112, 1.5205688931799841, 1.6075084140659088, 1.685673449609067, 1.7536575552108429, 1.8102386741622376, 1.8544150971567412, 1.8854364423238625, 1.9028288117852898, 1.9064134208684522, 1.8963181546020917, 1.8729816790694391, 1.837149918341968, 1.789864896531357, 1.7324461342997681, 1.6664649752431158, 1.593712395274951, 1.5161610130539842, 1.4359221674861122, 1.355199055674079, 1.2762370281686164, 1.2012722153615087, 1.132479707372282, 1.0719225285320702, 1.0215026360109702, 0.9829151304652, 0.9576067957372376, 0.9467399862862992, 0.9511627574988261, 0.9713859882944031, 1.0075680810169454, 1.0595076444654514, 1.1266443764211629, 1.208068166777204, 1.3025362461282797, 1.4084980122179167, 1.5241269826661368, 1.6473591514061465, 1.775936872424433, 1.9074572614862288, 2.039423997791102], [2.1310691844520524, 2.2590960629259107, 2.3809060763298353, 2.494118926287927, 2.596508944629371, 2.686053025277259, 2.760973913134354, 2.819777852677083, 2.86128573412482, 2.8846570308099975, 2.889405993931235, 2.875409756012763, 2.8429081876005102, 2.7924955482857983, 2.725104168271735, 2.6419805856352703, 2.5446547425969235, 2.4349030071678506, 2.314705930554, 2.186201772186511, 2.0516369203014695, 1.913314404325297, 1.7735417343342836, 1.6345793116716583, 1.4985906332914414, 1.3675954611700452, 1.2434270485300303, 1.1276944086977845, 1.0217504828553623, 0.9266669130113521, 0.8432159599672079, 0.7718599270575758, 0.7127482634573541, 0.6657223305241942, 0.630327625704441, 0.6058330756495923, 0.591256837884698, 0.5853978928823003, 0.5868725695902741, 0.5941550307307419, 0.6056206523646896, 0.6195911675110342, 0.6343804075471423, 0.648339468509949, 0.6599001523359408, 0.6676155848596329, 0.670196991649358, 0.6665457174265988, 0.6557797021899257, 0.637253773981165, 0.6105732807432508, 0.5756007577917299, 0.5324555086370327, 0.4815061606612678, 0.4233564388222368, 0.35882457553797015, 0.2889169387797263, 0.21479660903648262, 0.1377477654627276, 0.059136848918035105, -0.019628447952118742, -0.09714125803312375, -0.17203755190401349, -0.24303695440105105, -0.30898126628244743, -0.36886965108969827, -0.42188953344447083, -0.46744236573581355, -0.5051635526449463, -0.5349359738781823, -0.5568967110204809, -0.5714367603995508, -0.5791936958140381, -0.5810374283245034, -0.5780493903889441, -0.5714956438778149, -0.562794571550908, -0.5534799553445114, -0.5451603686298832, -0.5394759102866097, -0.538053383385627, -0.5424610685367537, -0.5541642602553681, -0.5744827234971409, -0.6045511869909398, -0.6452839210952032, -0.6973443522511559, -0.7611205460184347, -0.8367072490817167, -0.9238950209810748, -1.0221668125717724, -1.1307021646501618, -1.248389011333767, -1.373842883341134, -1.50543312099059, -1.6413155301458406, -1.7794707508932661, -1.9177474625366024, -2.0539094232182036, -2.185685241289399, -2.31081970103439, -2.4271254194262273, -2.532533594481364, -2.625142619967577, -2.703263385449458, -2.765460153923727, -2.8105860098843487, -2.837811996168761, -2.846649205357614, -2.8369632572735566, -2.8089807742345476, -2.763287655790639, -2.7008191500857914, -2.622841914976492, -2.5309284538252768, -2.4269244937862213, -2.312910043940342, -2.1911550226754626, -2.0640704745153076, -1.9341565029841032, -1.8039481254374525, -1.675960306152925, -1.5526334441169067, -1.4362805813704107, -1.3290375567408892, -1.2328172592885174, -1.1492690375565928, -1.0797441971348654, -1.0252683731424668, -0.9865213995767871, -0.9638251180784427, -0.9571393789097172, -0.9660662914641651, -0.9898625851846596, -1.027459749150408, -1.0774914344860589, -1.1383274326194261, -1.2081133884154038, -1.2848152740637078, -1.36626754050079, -1.4502237807094118, -1.5344086854122665, -1.616570047699687, -1.6945295795126012, -1.7662313393967433, -1.8297866365702604, -1.8835143694041965, -1.9259758745317508, -1.9560035029928655, -1.9727222985605857, -1.975564326711407, -1.964275386266217, -1.938914024972683, -1.8998429705229034, -1.847713274988889, -1.7834416488022202, -1.7081816258106373, -1.6232893495470762, -1.5302848990063576, -1.4308101768187762, -1.326584461209078, -1.2193587736604286, -1.1108702355936562, -1.002797579179624, -0.8967189399242462, -0.7940729929287818, -0.6961244024655425, -0.6039344381138778, -0.5183374731654441, -0.4399239258491395, -0.3690300350970783, -0.3057346843637557, -0.24986330393965545, -0.20099869890275832, -0.15849847096127737, -0.12151853247644508, -0.0890420542047093, -0.05991304871654463, -0.032873672551644396, -0.006604234951533474, 0.02023516813320294, 0.048962517394742305, 0.08083236599334835, 0.11699608629146459, 0.1584649405177003, 0.20607697538162117, 0.26046864191853863, 0.3220519198536958, 0.39099758361802944, 0.46722508841316773, 0.550399383421623, 0.6399347797193857, 0.7350058172131424, 0.8345648926319853, 0.9373662338740608, 1.0419956393278658, 1.1469052483948476, 1.2504524752209918, 1.3509421250349505, 1.4466706243873684, 1.535971235277979, 1.6172590902636284, 1.6890748820716242, 1.7501260671756969, 1.799324497665342, 1.83581947826618, 1.8590253535681727, 1.868642861763211, 1.864673642275054, 1.8474274518725438, 1.8175218230702324, 1.7758740854094224, 1.7236858599487268, 1.662420325264215, 1.5937727347858701, 1.5196348358490661, 1.4420539961499805, 1.363187979462103, 1.285256426064161, 1.21049018146579, 1.1410796774372283, 1.0791236004767117, 1.0265790838257909, 0.9852146298558867, 0.9565669107303439, 0.9419025080609711, 0.9421855388895786, 0.958051978447062, 0.989791333070818, 1.0373361431938788, 1.1002596106633131, 1.1777814513139984, 1.2687818774240347, 1.3718234201964117, 1.4851801144950865, 1.6068733913032842, 1.7347138620902498, 1.866348037415148, 1.9993089031370468, 2.1310691844520493], [2.2216054665030547, 2.3466928833235943, 2.4639971281369997, 2.5712278635485157, 2.6662795566691027, 2.747276741849097, 2.8126140256252556, 2.860989913911575, 2.891433689258663, 2.9033247322243043, 2.896403861482197, 2.8707764578402313, 2.8269073331970915, 2.7656075018632125, 2.6880132038273414, 2.5955577127901766, 2.489936631662934, 2.3730675306255904, 2.2470449140756013, 2.1140916097166347, 1.9765077530833273, 1.8366185920818905, 1.6967223574670087, 1.5590394361307283, 1.4256640449553915, 1.2985195348259921, 1.1793183589670824, 1.0695276194931391, 0.970340963974902, 0.8826574434947941, 0.8070677691024225, 0.7438482191393166, 0.6929622601682242, 0.6540697539246932, 0.6265434365193302, 0.6094921786570255, 0.6017903712763422, 0.6021126337849396, 0.608972915577017, 0.6207669588443048, 0.6358170143115289, 0.6524176532587272, 0.6688815001499097, 0.6835837207528437, 0.6950041404506019, 0.7017659354250881, 0.7026699337467983, 0.6967236816886492, 0.6831645697552617, 0.6614764694252562, 0.6313995014575288, 0.5929327354989694, 0.5463298041171296, 0.4920875976261383, 0.4309283845473311, 0.36377587174220893, 0.29172587390770344, 0.21601240031028213, 0.13797008387705267, 0.05899397110958686, -0.019502241606156306, -0.09612840053626774, -0.16955938094324746, -0.23857475107333825, -0.30209554516643333, -0.35921715187781467, -0.4092374250777027, -0.4516792475954998, -0.4863069219767593, -0.5131359220955878, -0.5324357114742394, -0.544725514055241, -0.5507631063970997, -0.5515268821821497, -0.5481916159218835, -0.5420985183524077, -0.5347203270172461, -0.5276223080846584, -0.5224201561485369, -0.5207358647652452, -0.5241526995492054, -0.534170436224526, -0.5521620272579576, -0.5793328324629873, -0.6166834918870537, -0.6649774347180459, -0.7247139079076225, -0.796107275383413, -0.8790731863612281, -0.9732220431178864, -1.0778600187937297, -1.1919976888092758, -1.31436614994004, -1.4434403137089977, -1.577468880196119, -1.714510329138938, -1.852474111545685, -1.9891660908253141, -2.1223371710450163, -2.2497339641868255, -2.369150290391681, -2.4784782766695233, -2.575757821211892, -2.6592232223190564, -2.727345832352427, -2.7788716866186887, -2.8128531725650086, -2.828673943349661, -2.8260664384087497, -2.8051215482318694, -2.7662901469512957, -2.710376410008355, -2.6385230303696168, -2.5521886407381467, -2.453117936204642, -2.3433051672380274, -2.2249518325330273, -2.100419541104641, -1.9721791297191955, -1.8427572124169358, -1.7146814012856972, -1.590425470255288, -1.47235573569101, -1.362679898916795, -1.2633995371867655, -1.1762673424763979, -1.10275009390636, -1.0439982124151523, -1.000822588810173, -0.9736792023952112, -0.9626618612404169, -0.9675032013693298, -0.9875838854111176, -1.0219497463971619, -1.069336434111551, -1.1282009443098184, -1.196759249494966, -1.2730291076948035, -1.354877006249523, -1.440068103857567, -1.5263179682706123, -1.6113448706154005, -1.6929213911643692, -1.7689241155470181, -1.837380254211094, -1.896510099999744, -1.9447643469080247, -1.9808554246785992, -2.003782155581126, -2.0128472076913475, -2.007666999049987, -1.988173894753825, -1.954610729649249, -1.907517878137304, -1.8477132749888887, -1.7762659625100437, -1.694463895672577, -1.6037768741039773, -1.5058155847621482, -1.4022878289183258, -1.2949530695807248, -1.1855764692416444, -1.0758835920715417, -0.9675169194027144, -0.8619952732674079, -0.7606771613228954, -0.6647289498330754, -0.5750986422339218, -0.4924958924968114, -0.41737871880315025, -0.3499472081185157, -0.290144320542404, -0.23766371841242337, -0.19196436370921025, -0.15229145292323312, -0.11770309560626173, -0.08710199544627581, -0.05927126458701042, -0.03291339628634958, -0.006691340527243021, 0.020729426118227142, 0.050638969880788386, 0.08424223764018651, 0.12262075910878302, 0.16669774776369964, 0.21720754686661992, 0.2746702544658033, 0.33937222729997013, 0.41135301140459163, 0.49039908080261313, 0.5760445891513697, 0.6675791570808813, 0.7640625348061874, 0.8643458000691947, 0.9670985801185698, 1.0708416276241297, 1.1739839381901407, 1.2748634751142787, 1.371790468367508, 1.463092181995071, 1.5471579991651319, 1.6224836581300468, 1.6877134859010663, 1.741679519217669, 1.7834364734323243, 1.8122916175349826, 1.8278287353462697, 1.8299254959415598, 1.818763717120016, 1.7948321802441267, 1.7589218387343148, 1.7121134513535783, 1.6557578604689849, 1.5914493200263178, 1.5209924534169608, 1.446363583364212, 1.3696673203473022, 1.2930894192778146, 1.2188470130264715, 1.1491374034437574, 1.0860866338598942, 1.0316990805298782, 0.9878092836826495, 0.9560371920640026, 0.9377479191938561, 0.9340170067682545, 0.9456020631750605, 0.972921496021726, 1.016040890493455, 1.074667404318312, 1.148152359510498, 1.2355020155331808, 1.3353963128343644, 1.4462151846394804, 1.5660718531018234, 1.692852357861279, 1.8242604148569828, 1.957866574559644, 2.091160544787865, 2.2216054665030502], [2.3102668660298207, 2.431350678055853, 2.5431391703511235, 2.6434513559124913, 2.7303196710839264, 2.8020321861778488, 2.8571689880039686, 2.894631899438526, 2.9136668603493585, 2.913878469463248, 2.8952363738462017, 2.8580733870028965, 2.8030754134522233, 2.7312634522082235, 2.6439681391562138, 2.542797464306228, 2.4295984600623917, 2.306413797093572, 2.175434341742473, 2.0389488203537023, 1.8992917992632028, 1.7587912229919798, 1.6197167566755089, 1.4842301519323855, 1.3543387989736115, 1.2318535432455329, 1.1183517344427971, 1.0151463421156208, 0.9232618186863782, 0.8434172213236937, 0.7760169230231321, 0.7211490549184415, 0.6785916309705559, 0.6478261174805908, 0.6280580280104118, 0.6182439537524121, 0.6171242843602412, 0.623260738530995, 0.6350777105250024, 0.6509063510603105, 0.6690302407265075, 0.6877314826396799, 0.7053360391974526, 0.7202571654419543, 0.7310358479145246, 0.736377241488346, 0.7351822053161119, 0.7265731699285468, 0.7099137173146436, 0.6848214206860418, 0.651173666385871, 0.609106362589578, 0.5590056234504419, 0.5014926985153165, 0.43740259100337364, 0.3677569705209881, 0.29373213189901715, 0.21662287840765598, 0.13780331144661503, 0.05868558731703414, -0.019322247111856622, -0.09485820540323456, -0.1666469712978311, -0.23353807476214858, -0.29454060543948435, -0.34885352459304275, -0.39589075078949215, -0.4353003300115491, -0.4669771541839532, -0.4910688593713998, -0.5079747119279998, -0.5183374731654435, -0.5230284160448693, -0.5231258463479577, -0.5198876512045131, -0.5147185554138952, -0.5091329066819116, -0.5047139311072883, -0.5030704969061937, -0.5057924949600023, -0.5144059874611521, -0.530329289562388, -0.5548311330803382, -0.58899201627813, -0.6336697705977521, -0.6894702756816151, -0.7567241305283825, -0.835469944188853, -0.9254447475716634, -1.026081852686277, -1.136516301335485, -1.255597856451779, -1.3819113006429364, -1.5138036227711762, -1.6494174991241781, -1.7867303153080076, -1.923597832430652, -2.0578014800445854, -2.1870981617488776, -2.30927138978486, -2.422182524201127, -2.5238208813109932, -2.612351495579278, -2.6861593683686014, -2.7438891150237796, -2.784479026739242, -2.8071886930353425, -2.811619481354932, -2.797727338641589, -2.765827561694973, -2.716591374195422, -2.65103434389607, -2.570496868826098, -2.4766171516627873, -2.371297262060439, -2.256663053250856, -2.135018847574026, -2.008797932123149, -1.880510007289446, -1.7526868051747042, -1.62782713977602, -1.5083426654285723, -1.396505603850361, -1.2943996536523859, -1.2038752204867673, -1.1265100029451347, -1.0635758414037313, -1.0160125873587027, -0.9844095830571378, -0.9689951594976622, -0.9696343695816441, -0.9858349770054534, -1.0167615251753541, -1.0612571187777582, -1.117872368308021, -1.1849007792761177, -1.2604197170511535, -1.3423359490188793, -1.4284346610166336, -1.516430767379062, -1.6040212852073377, -1.6889375247838763, -1.7689958597709974, -1.842145882586931, -1.906514821036032, -1.960447190064416, -2.0025387749335963, -2.0316641860679385, -2.0469973877272296, -2.0480247784373096, -2.0345505864012803, -2.006694533305561, -1.9648819103143955, -1.909826395902956, -1.842506121926852, -1.764133657613931, -1.6761207269864986, -1.58003860001521, -1.4775751985369603, -1.3704900322111022, -1.2605681257784715, -1.1495741155714416, -1.039207680278324, -0.9310614288098594, -0.8265822978959486, -0.7270374156018062, -0.6334852667919211, -0.5467528557735365, -0.4674194035152489, -0.39580694597904487, -0.3319780205623411, -0.27574044396915603, -0.22665900166157632, -0.18407369101057783, -0.14712399186040304, -0.11477848368695699, -0.08586899175917394, -0.05912832914314143, -0.03323060992594753, -0.006833043974741775, 0.021381913484677773, 0.05266519226425999, 0.08816163131346674, 0.12887346058157317, 0.17562772769196622, 0.2290485540791283, 0.2895349800429806, 0.35724501334870284, 0.4320863352061235, 0.5137139447682829, 0.6015348430632947, 0.6947196740801297, 0.7922210592085267, 0.8927981859900282, 0.9950470476223815, 1.0974355800597646, 1.1983428126835036, 1.2961010397341715, 1.389039935797596, 1.4755314818060274, 1.5540345397568884, 1.623137915456869, 1.681600779125035, 1.728389372954591, 1.7627090213376087, 1.7840305713114133, 1.792110525164942, 1.7870042807549957, 1.769072064144642, 1.7389773195144493, 1.697677508445964, 1.6464074599905647, 1.5866555997054996, 1.5201335654051344, 1.4487398852502218, 1.3745185457720523, 1.2996134096786063, 1.2262195524723667, 1.1565326702459109, 1.092697766367053, 1.0367583506628064, 0.9906073804303723, 0.9559411381553914, 0.9342171769619873, 0.9266173730398259, 0.9340170067682542, 0.9569606538012931, 0.9956455073756026, 1.049912577428458, 1.119246025028544, 1.202780696680028, 1.299317726986563, 1.4073478847412466, 1.525082151467617, 1.6504888473255857, 1.781336461377114, 1.9152412053496612, 2.0497181956210397, 2.1822350799869756, 2.3102668660298176], [2.3963032674726192, 2.5123532038711684, 2.6176626254828976, 2.7101783599529568, 2.788087479527416, 2.849856102427374, 2.8942618451274207, 2.9204191828372084, 2.9277971447088564, 2.9162289531341665, 2.885913408496945, 2.8374080172282454, 2.771614057191011, 2.6897539655217706, 2.593341615436086, 2.4841462157598837, 2.364150716030367, 2.2355057273186305, 2.1004800714007033, 1.961409146098219, 1.8206423407510257, 1.6804907518153451, 1.543176434187906, 1.410784379472529, 1.2852183392021495, 1.1681615108841439, 1.0610429801883614, 0.9650106667796429, 0.8809113578624811, 0.8092782365340153, 0.7503261259378308, 0.7039544795957479, 0.669757957890145, 0.6470442451814817, 0.634858586048311, 0.6320143569582218, 0.6371288452930327, 0.6486632845846916, 0.6649660960564201, 0.6843182144823858, 0.7049793326849985, 0.7252338846776445, 0.7434356027935619, 0.7580495286402934, 0.7676904301780305, 0.7711566757383221, 0.7674587378278566, 0.7558416419687347, 0.735800834975596, 0.7070911189121445, 0.6697284771450751, 0.6239848028597192, 0.5703757234695379, 0.509641891919425, 0.4427242834741354, 0.3707341899771721, 0.2949187389032189, 0.21662287840765598, 0.13724885914164164, 0.0582143066068072, -0.019089987304089905, -0.09334141905961937, -0.16332496327124496, -0.22796953802819597, -0.28638036531033845, -0.33786645021180645, -0.3819624294837543, -0.41844418603826616, -0.447337787848872, -0.46892148304172493, -0.4837206635066481, -0.4924958924968109, -0.49622427278781306, -0.4960746064366955, -0.49337696058603253, -0.4895874019383076, -0.48624879169938073, -0.4849486396477852, -0.48727509777586403, -0.49477222854138286, -0.5088957087161682, -0.5309701263892401, -0.5621489958794681, -0.6033785538766622, -0.6553663115187665, -0.7185552234682219, -0.7931041991452782, -0.8788755264448496, -0.9754296083218182, -1.0820272317779616, -1.1976394015044733, -1.3209645813800222, -1.4504530009029806, -1.5843375050932529, -1.7206702599015147, -1.8573644748901539, -1.9922401746856302, -2.1230729437437637, -2.2476444880437607, -2.36379380452195, -2.4694677257673403, -2.5627696143976073, -2.6420050185395514, -2.7057231661318872, -2.752753269806197, -2.7822347336506175, -2.7936404953553775, -2.7867928986502815, -2.7618716676637467, -2.719413742569696, -2.660304930073391, -2.5857635181856766, -2.497316197564084, -2.39676681674447, -2.2861586713202047, -2.1677311833150297, -2.043871962811231, -1.91706535600222, -1.7898386694825517, -1.664707317660002, -1.5441201672627816, -1.4304063493445043, -1.3257247750328955, -1.2320175273492837, -1.1509682092952283, -1.0839662103026144, -1.0320777119514246, -0.9960240930171302, -0.9761682173390022, -0.9725089000066066, -0.9846836525264622, -1.0119796107009862, -1.053352354721437, -1.1074521441693257, -1.1726569157737552, -1.2471112331241743, -1.3287702389257838, -1.4154475451483366, -1.5048659073205026, -1.5947094683773835, -1.6826763262971633, -1.7665301789523522, -1.8441498290910816, -1.9135753913499656, -1.97305013015248, -2.021056970050473, -2.0563488556765885, -2.0779722935872034, -2.085283579012106, -2.0779573926319284, -2.055987641451331, -2.0196806089385984, -1.9696406681319332, -1.906748992714946, -1.8321358706739466, -1.7471473789032306, -1.6533073112598649, -1.552275363821249, -1.4458026667771702, -1.3356858104459153, -1.2237205419862505, -1.1116563088531204, -1.0011527950238026, -0.8937395373477721, -0.7907796236060649, -0.693438363236463, -0.6026576890385356, -0.5191368969127915, -0.44332016466478114, -0.37539111433624706, -0.31527449988642986, -0.2626449179576499, -0.21694225857051422, -0.17739343946846148, -0.14303980683168135, -0.1127694402587702, -0.08535347491253678, -0.05948545168347185, -0.03382262969950644, -0.0070281464187424035, 0.02218710989418097, 0.05502404178691685, 0.09255738716916723, 0.13570129002599746, 0.18517932863144485, 0.24149981674001153, 0.30493705634532714, 0.37551906614239927, 0.453022141721328, 0.5369724260109312, 0.6266544860748315, 0.7211267096620935, 0.819243156561839, 0.9196813303347446, 1.0209751797035964, 1.121552499763264, 1.219775784774206, 1.3139854896738785, 1.4025445890252828, 1.4838832817149894, 1.556542678408173, 1.6192163269310553, 1.6707884780088869, 1.710368069037708, 1.7373175050051957, 1.7512754408347933, 1.7521729152449976, 1.7402423491060683, 1.716019097218818, 1.6803354270798974, 1.6343069869527953, 1.5793120137396124, 1.5169637140534602, 1.4490764249555077, 1.3776263197070044, 1.304707564600845, 1.2324849519278847, 1.1631441283778932, 1.098840605259965, 1.0416487751045551, 0.9935121674431151, 0.956196154555242, 0.9312442661756775, 0.9199391917512665, 0.9232694417253461, 0.9419025080609703, 0.9761652119517615, 1.0260317570899058, 1.091119824077244, 1.1706948500213108, 1.2636824417198618, 1.3686886758783103, 1.4840278502878912, 1.60775707045377, 1.7377168911961145, 1.8715770862955325, 2.00688649491144, 2.1411257943218525, 2.2717619769548962, 2.396303267472615], [2.478986763943324, 2.589015142747078, 2.686936991379656, 2.7708443350214127, 2.8390942401999038, 2.8903438786256315, 2.9235787746396373, 2.9381335920211904, 2.933704993737447, 2.9103562970815986, 2.868513841939971, 2.80895518689576, 2.732789441723854, 2.6414302308444797, 2.536561955966397, 2.4201001832538385, 2.2941471170968155, 2.1609432356573337, 2.0228162500945803, 1.8821286076814931, 1.7412247875551001, 1.602379635969513, 1.4677489557673407, 1.339323503220766, 1.2188874560080363, 1.1079823011565757, 1.0078769541972752, 0.9195447639852062, 0.8436478855655876, 0.7805293203851507, 0.7302127336150814, 0.6924099670590996, 0.666535977798535, 0.6517307520208175, 0.646887574834739, 0.650686884432155, 0.6616348064370564, 0.6781053549116288, 0.698385202905022, 0.7207198696269358, 0.7433601446018832, 0.7646075720813453, 0.7828578513899656, 0.7966410698539595, 0.8046577728887829, 0.805809988423384, 0.7992264572116818, 0.7842814732916182, 0.7606069060086493, 0.7280971523794181, 0.6869069516399684, 0.6374421779721369, 0.5803439079832259, 0.5164662319747115, 0.4468484380332197, 0.3726823414869541, 0.2952756556881072, 0.21601240031028213, 0.1363114178795251, 0.0575841162269715, -0.018807427205928623, -0.09159087420424297, -0.15962146255461976, -0.22191625321204186, -0.27768386410303986, -0.32634888435507886, -0.36757030106137456, -0.4012534262811573, -0.4275549808976273, -0.44688116993211424, -0.45987876643491377, -0.4674194035152484, -0.47057745180690197, -0.47060202817884134, -0.46888383650529813, -0.46691767885602764, -0.4662615920375862, -0.46849365701579515, -0.47516759498169076, -0.48776830195001725, -0.5076684827658666, -0.5360875249355449, -0.5740537032246961, -0.6223707286405178, -0.681589552096106, -0.7519862062585024, -0.833546321915638, -0.9259567912842674, -1.0286048740713338, -1.1405848571702517, -1.2607121902147393, -1.387544831522324, -1.5194113569204994, -1.65444521211383, -1.7906243319297108, -1.9258152109329816, -2.057820393034128, -2.184428255804271, -2.303463900611679, -2.4128399240977476, -2.5106058408882728, -2.59499495202295, -2.6644675078700932, -2.717749097027117, -2.7538633019391434, -2.772157795087899, -2.772323203408115, -2.754404239359548, -2.718802780676576, -2.666272772768335, -2.5979070233723833, -2.5151161535980777, -2.4196001581770825, -2.3133132059493002, -2.198422474987254, -2.077261961292345, -1.9522823221341707, -1.8259979118453014, -1.7009322368456177, -1.5795630961483753, -1.4642686826112905, -1.357275898503741, -1.2606120870791089, -1.1760613010242473, -1.1051261208675311, -1.0489959042858796, -1.0085221939776765, -0.9842018410974638, -0.9761682173390017, -0.9841906960873527, -1.0076823863312792, -1.0457159070242799, -1.097046799073867, -1.1601439917535599, -1.233226574446903, -1.314305977263882, -1.4012325387748255, -1.4917453388965372, -1.5835241022318574, -1.6742419336205696, -1.7616176343006484, -1.843466364155486, -1.9177474625366056, -1.9826083158697574, -2.0364232627377343, -2.0778266537929926, -2.1057393315045765, -2.1193879596921117, -2.118316810932785, -2.1023918068144547, -2.0717967970140387, -2.0270222535768117, -1.9688467418573632, -1.898311704796785, -1.816690258248365, -1.7254508379822169, -1.6262166603129111, -1.5207220550633092, -1.4107667994787068, -1.2981696230879889, -1.1847220654366653, -1.0721438508895214, -0.9620408978572705, -0.8558670051065702, -0.7548901572231442, -0.6601642674136289, -0.5725070318303505, -0.4924844091600127, -0.4204020664111131, -0.3563039510487291, -0.29997796543412947, -0.250968536583736, -0.20859569718266618, -0.17198012703375584, -0.14007345189052592, -0.11169296273820628, -0.08555980641216109, -0.06033961078971065, -0.03468444685185, -0.007274997204283754, 0.023138203020756625, 0.05769556151440573, 0.09739231512364656, 0.14304648091532648, 0.19527173971603884, 0.25445599153289794, 0.3207461748378025, 0.3940397789253173, 0.4739833045535261, 0.5599777472546625, 0.6511909946393345, 0.746576848356429, 0.8449002076948764, 0.9447677895374257, 1.0446636126321882, 1.142988346680906, 1.2381015218198297, 1.3283655143941036, 1.4121901725733366, 1.4880769217154945, 1.5546611951310496, 1.6107520709660734, 1.6553680595126865, 1.6877680758528901, 1.7074767481530497, 1.7143033493308197, 1.7083537958383344, 1.6900353280965432, 1.6600536684494895, 1.619402639886226, 1.569346417542128, 1.5113947704370405, 1.4472718284014205, 1.378879074239364, 1.3082534097310592, 1.2375212723411442, 1.1688498842236978, 1.104396793624188, 1.0462589190443718, 0.9964223272222889, 0.95671396647998, 0.928756537446648, 0.9139276144559184, 0.9133240346475894, 0.9277324502642934, 0.9576067957372364, 1.003053258374347, 1.0638231637421178, 1.1393139984866723, 1.2285785989563138, 1.3303423383085944, 1.4430279525900858, 1.564787462267693, 1.6935404743724707, 1.8270179959911255, 1.9628107560953756, 2.09842092292266, 2.2313160210146408, 2.358983797631896, 2.47898676394332], [2.557617815647086, 2.6606878999907697, 2.7503761755589045, 2.8249360195171134, 2.88290841282528, 2.923152969865056, 2.944871742050883, 2.9476252550729125, 2.931340424359017, 2.8963101866331558, 2.843184882381746, 2.772955619825104, 2.686930040865941, 2.58670108883846, 2.474109542359347, 2.351201225204253, 2.2201799253857044, 2.083357154529046, 1.943099948895633, 1.8017779543333814, 1.6617110481123145, 1.5251187308402208, 1.3940724720125741, 1.2704521145265975, 1.1559073386781613, 1.051825057408526, 0.9593034651073246, 0.8791332958435052, 0.8117866676332416, 0.7574137017167506, 0.7158469144553474, 0.6866131891085084, 0.6689529501052633, 0.6618459880300693, 0.6640432236813834, 0.6741035581423669, 0.6904348362719603, 0.7113378562741531, 0.735052290304552, 0.7598033420195017, 0.7838479574408295, 0.8055194256385516, 0.8232692549247668, 0.8357052871814147, 0.8416251155995352, 0.8400439968374148, 0.8302165941865446, 0.8116520500550353, 0.7841220598279903, 0.7476618005393912, 0.7025637522029762, 0.6493646324438478, 0.5888258416398654, 0.52190798167626, 0.4497401624668557, 0.3735849428070128, 0.2947998625761753, 0.21479660903648265, 0.13499891883753987, 0.056800347873304874, -0.01847695740366312, -0.08962138123871236, -0.15556780243987134, -0.21542943384237337, -0.2685246781530138, -0.31439827084176597, -0.3528361294413181, -0.383873492346675, -0.40779610482884804, -0.42513439106483053, -0.43665073395060416, -0.4433201646647807, -0.4463049368129524, -0.4469236211129286, -0.4466155018752982, -0.4469011822824975, -0.4493404084499778, -0.45548819981034855, -0.46685042347601957, -0.4848399715741811, -0.5107346924971129, -0.5456381896939516, -0.59044453590494, -0.6458078581771376, -0.7121176318483354, -0.7894803828103591, -0.8777083401805567, -0.9763154099020496, -1.0845206580098885, -1.2012593048547007, -1.3252010431330348, -1.4547753078345769, -1.5882029497995724, -1.7235336009074165, -1.8586878721048286, -1.9915033992352602, -2.1197836491535296, -2.2413483225224846, -2.354084141963737, -2.455994796147018, -2.5452488224947927, -2.6202242532485807, -2.679548920746776, -2.7221354162371227, -2.7472098200484787, -2.754333466511193, -2.743417171129613, -2.714727526196366, -2.6688850599528795, -2.6068542489419713, -2.529925568618463, -2.439689958805978, -2.3380062635252163, -2.2269623745877922, -2.1088309609836435, -1.9860207977389004, -1.8610248153477589, -1.7363660714384492, -1.6145428980293683, -1.4979744992820123, -1.3889482655149037, -1.2895700296123016, -1.2017184227929145, -1.1270043896724673, -1.066736800015553, -1.021894949508075, -0.9931085778235373, -0.9806458532005726, -0.9844095830571369, -1.0039417144589844, -1.0384359913010612, -1.086758441642592, -1.1474751834614612, -1.2188868646565663, -1.2990688976070066, -1.385916513753851, -1.4771935527519937, -1.570583816403229, -1.6637437618285114, -1.7543552824638122, -1.8401773300307374, -1.919095165452439, -1.9891660908253148, -2.0486606063671164, -2.0960980534134594, -2.1302759440789383, -2.15029233664261, -2.1555607891066177, -2.1458176073995103, -2.1211212947842064, -2.081844300479618, -2.028657353584431, -1.962506848466224, -1.8845859154221778, -1.7962999615204467, -1.6992275974048772, -1.595077973311308, -1.4856456290115156, -1.3727640159328245, -1.2582588740586393, -1.1439026408883375, -1.0313710349546075, -0.9222028931270897, -0.8177642508465304, -0.7192175398729546, -0.6274966420406622, -0.5432883833706751, -0.46702088462197683, -0.3988590062360285, -0.33870694215494157, -0.28621783280866714, -0.24081008731746062, -0.2016899331842348, -0.16787955277921038, -0.13825002374202983, -0.1115581586122009, -0.08648624060019391, -0.0616835798893077, -0.035808770019892674, -0.00757150786201891, 0.024227146186179428, 0.0606571491809556, 0.10262550949857996, 0.15084688961090026, 0.2058195745811044, 0.2678074633563038, 0.3368285832242538, 0.4126504580865967, 0.49479248278012306, 0.5825352730717284, 0.6749367787914512, 0.7708547704734635, 0.868975142345106, 0.9678453208014645, 1.0659119315464443, 1.1615617638479359, 1.2531649797924787, 1.3391194523786785, 1.417895080440265, 1.4880769217154948, 1.5484060081254238, 1.5978167589975063, 1.635469987354731, 1.6607805995690943, 1.6734392170872363, 1.6734270974236787, 1.66102389652351, 1.6368079918430969, 1.6016492706886865, 1.5566944768854942, 1.5033453960261698, 1.443230340694092, 1.3781695676379353, 1.3101354146084256, 1.2412080815323825, 1.1735280954276055, 1.1092465880340148, 1.05047457724674, 0.9992324764579994, 0.9574010589345354, 0.9266750772049254, 0.9085206806818977, 0.9041376897055375, 0.9144276728734438, 0.9399686395848942, 0.9809970044170396, 1.0373973080293366, 1.1086999949311542, 1.1940873561331264, 1.2924075491248688, 1.4021964135571428, 1.5217066132020018, 1.648943457819162, 1.7817065968091401, 1.9176366339548414, 2.05426559264643, 2.1890700667025453, 2.3195258255700484, 2.4431626059467235, 2.557617815647082], [2.631531168305534, 2.7267650916436694, 2.807443453815929, 2.87199577331246, 2.9191593096769948, 2.9480057963874793, 2.9579605992216806, 2.948813868227932, 2.9207234419004875, 2.8742094582391693, 2.810140824281617, 2.729713888643687, 2.6344238459001463, 2.5260295728103004, 2.4065127502940924, 2.278032257973362, 2.1428749368094455, 2.0034038972882158, 1.8620056037840422, 1.7210369889402943, 1.582773844638732, 1.449361698645819, 1.3227703193151579, 1.2047528965030363, 1.0968108275039639, 1.0001648953335467, 0.9157334666159647, 0.8441181616614163, 0.785597264386516, 0.7401269491226867, 0.7073502097893277, 0.6866131891085083, 0.6769884261309225, 0.6773043737354021, 0.6861803880359819, 0.7020662624331037, 0.7232852735131793, 0.7480796266728592, 0.7746571381035638, 0.8012379677981698, 0.8261002259842755, 0.8476233125553447, 0.8643279146376925, 0.8749116796673088, 0.878279697863041, 0.873569065778166, 0.8601669581704408, 0.8377218047942402, 0.8061473475915788, 0.7656195376155259, 0.7165664152165526, 0.6596512969150495, 0.5957497634426024, 0.5259211013591751, 0.4513749914778147, 0.3734343575217488, 0.293495384992449, 0.21298579073058574, 0.13332246635149378, 0.05586963258073856, -0.018101373821359856, -0.08744960296472166, -0.15119827872587255, -0.20856396134637709, -0.25898029831797625, -0.3021157172699046, -0.3378845723827793, -0.3664514263404149, -0.38822832867506957, -0.4038651340296206, -0.41423308571934125, -0.42040206641111266, -0.42361208426625135, -0.4252397152773365, -0.4267603568835387, -0.42970726083629723, -0.43562840180662943, -0.44604230008444007, -0.4623939502933518, -0.48601201241393854, -0.5180683963881048, -0.5595413177188787, -0.6111828200587885, -0.6734916537652197, -0.7466922694066371, -0.8307205354238545, -0.9252166232819717, -1.0295253255971548, -1.1427038873031812, -1.2635372415483976, -1.3905603553821315, -1.5220872100650409, -1.6562457715358918, -1.791018152441966, -1.924285032077884, -2.0538732879997075, -2.177605705858372, -2.2933515743773434, -2.3990769419521762, -2.492893310924422, -2.5731035752863805, -2.6382440667697393, -2.687121661592246, -2.7188450135165536, -2.732849115601733, -2.72891254980586, -2.707166956633078, -2.668098442108014, -2.6125408319980066, -2.541660878689365, -2.4569357196808075, -2.3601230735480625, -2.253224834878899, -2.138444889767461, -2.018142114058468, -1.8947796341854564, -1.7708715222539013, -1.6489281607103758, -1.531401545931811, -1.420631803509664, -1.3187961607851346, -1.2278615649582625, -1.1495420492238604, -1.0852618369624853, -1.036125037765068, -1.0028926323099427, -0.9859672696564115, -0.9853862145931679, -1.0008225888101716, -1.0315948525686398, -1.0766842780215982, -1.1347599761410927, -1.204210860933196, -1.2831837715921328, -1.3696268294061407, -1.4613369850512379, -1.5560106163062906, -1.6512959684738875, -1.744846191490467, -1.8343717197241933, -1.9176907629128854, -1.9927767289618157, -2.0578014800445885, -2.1111734305754357, -2.1515696264473827, -2.177961096178916, -2.189630932506756, -2.186184743325482, -2.1675532992299207, -2.133987396597769, -2.086045145422203, -2.0245720752755, -1.9506746263254395, -1.8656877509802239, -1.7711374916272238, -1.6686995176526476, -1.560154697637506, -1.4473428481025303, -1.3321158368847767, -1.2162912263544747, -1.1016076191439457, -0.9896828175210977, -0.8819758283801796, -0.7797536411103858, -0.6840635780403223, -0.5957118700104878, -0.5152489466470674, -0.4429617562386518, -0.3788732481769545, -0.3227489663128632, -0.2741105189585854, -0.23225551523636706, -0.19628339246354062, -0.16512640941854953, -0.13758494941344, -0.11236616838465958, -0.08812493942418823, -0.06350598839552739, -0.03718608692087078, -0.007915169777610824, 0.02544472643851749, 0.06388374841477373, 0.10821269510150802, 0.15903652112542901, 0.21673359377073337, 0.2814412727169931, 0.3530482170523589, 0.4311936488591049, 0.5152736213370612, 0.6044541565863193, 0.6976909384521648, 0.7937550738062015, 0.8912642756713541, 0.9887186777696653, 1.0845403660533763, 1.1771156117505532, 1.2648387150214113, 1.3461563204460414, 1.4196110465240133, 1.4838832817149903, 1.5378300391038675, 1.5805198296179035, 1.6112626082294565, 1.6296339664476538, 1.635492884722731, 1.62899251670122, 1.6105836496657517, 1.5810106676960778, 1.5413000315697567, 1.4927414775124561, 1.4368623209127487, 1.3753954264311483, 1.310241568158193, 1.2434270485300307, 1.1770575689258922, 1.1132694450941603, 1.0541793342153989, 1.0018336855961838, 0.9581591424848369, 0.9249151078283344, 0.90364964221397, 0.8956597887660506, 0.9019573191179145, 0.9232407691500378, 0.9598744859885566, 1.0118752423507593, 1.0789067947157889, 1.1602825723581582, 1.254976489625691, 1.3616416787256194, 1.478636749474564, 1.604059000642782, 1.7357838391389107, 1.8715095124723384, 2.0088061304046883, 2.145167846647689, 2.2780669934755124, 2.405008913126145, 2.52358621108969, 2.63153116830553], [2.7001014815090025, 2.786687674764123, 2.8576560111534364, 2.9116254495955607, 2.947540231763964, 2.96469209203449, 2.962734608497591, 2.9416893752811037, 2.9019438708376977, 2.8442410940625473, 2.7696612353237184, 2.6795958379644107, 2.5757150829952056, 2.459928991239776, 2.3343434792194033, 2.2012123241332735, 2.0628861865523023, 1.921759904670363, 1.780219309615063, 1.6405888166051623, 1.505081021595233, 1.375749478159126, 1.2544457461515057, 1.1427816942637972, 1.0420979057114532, 0.9534388832792814, 0.8775355806260818, 0.8147956053186501, 0.7653012500277191, 0.7288153163522497, 0.704794505583299, 0.692409967059099, 0.6905744221122408, 0.6979751241987491, 0.7131117774709123, 0.7343384201727975, 0.7599081885966585, 0.788019814104332, 0.8168646713682778, 0.8446731912794685, 0.8697594769209741, 0.8905630148961805, 0.9056864556883161, 0.9139285434901149, 0.9143114053269639, 0.906101557992131, 0.8888241555313713, 0.8622701755874407, 0.8264964253983774, 0.7818184330261895, 0.728796471815325, 0.6682151415495468, 0.6010570938798756, 0.5284716382149823, 0.4517390936728953, 0.3722318596508161, 0.29137325940756936, 0.21059526573486406, 0.13129624396802214, 0.054799844621801125, -0.017683854066078628, -0.0850939136092098, -0.1465498595604759, -0.2013779207280312, -0.2491314743702133, -0.2896051396006317, -0.32284212682413066, -0.3491346268243647, -0.3690172046770733, -0.383253346365451, -0.3928154851892638, -0.39885900623602805, -0.40269088596797775, -0.4057337663275141, -0.4094863850412055, -0.4154813828732002, -0.42524158188849764, -0.4402358744240694, -0.4618358792133898, -0.49127450847343, -0.5296075479853853, -0.5776792822559975, -0.6360931004181196, -0.7051878979670284, -0.7850209476920644, -0.8753577537464967, -0.9756692296471001, -1.085136358405041, -1.2026623055031773, -1.3268917677258256, -1.456237157604974, -1.5889110490618614, -1.722964149067841, -1.8563279168743856, -1.9868608301924515, -2.1123971997446787, -2.2307973623841524, -2.3399980403264133, -2.438061641129619, -2.523223290298175, -2.5939344354499996, -2.6489019368099798, -2.687121661592246, -2.7079057271613514, -2.7109026866568198, -2.6961101174303237, -2.663879253136559, -2.6149114902457797, -2.5502467944765117, -2.471244227423192, -2.3795550037097137, -2.277088669678042, -2.1659731614885125, -2.0485096494645094, -1.9271232028938852, -1.804310412162775, -1.6825851805070027, -1.564423943951947, -1.452211594013585, -1.3481893630355324, -1.2544058869721886, -1.172672586075996, -1.1045244021024205, -1.0511868037789482, -1.0135498234766962, -0.9921497208936257, -0.9871586881748715, -0.9983828196728294, -1.025268373142465, -1.0669161523547221, -1.122103648679688, -1.1893143958169805, -1.266773821984474, -1.3524907316328991, -1.444303417813456, -1.5399292998407148, -1.6370169014149156, -1.7331989337793259, -1.826145227963513, -1.9136142701346397, -1.9935021342296784, -2.063887675315039, -2.1230729437437614, -2.169617901714528, -2.202368667230463, -2.2204786721283827, -2.223422296775087, -2.2110007298385144, -2.1833399926356183, -2.1408812592118225, -2.0843637907926755, -2.014800981953124, -1.933450181388462, -1.8417770984936184, -1.7414157344501413, -1.6341248800943486, -1.5217423000066677, -1.4061377711950527, -1.289166164322824, -1.1726217452656498, -1.058194835226164, -0.9474318997726133, -0.8417000427872571, -0.7421567628565013, -0.6497256901497004, -0.5650788648772563, -0.48862594798219905, -0.4205105751230405, -0.36061388079072954, -0.30856503521918555, -0.2637584572376779, -0.22537719589124944, -0.19242181680156847, -0.16374398979041607, -0.13808385573452592, -0.1141101559272788, -0.09046203875057318, -0.06579141790775792, -0.03880474483055905, -0.008303075415744772, 0.02678064249787458, 0.06734806072628921, 0.11410660181399969, 0.16754608747044866, 0.2279214597439315, 0.2952420714184054, 0.36926785088046277, 0.44951246745801515, 0.5352534405243279, 0.625548954125494, 0.7192609631343709, 0.8150840114259426, 0.9115790315197331, 1.0072112623967757, 1.1003913111675923, 1.189518297797306, 1.2730239624241657, 1.3494165835081229, 1.4173235529750292, 1.475531481806029, 1.5230227655499833, 1.5590076226767684, 1.5829507275182273, 1.5945916910987883, 1.5939587942022484, 1.5813755438232322, 1.5574598025779482, 1.523115426266347, 1.4795165329639932, 1.4280847130808694, 1.3704596691012585, 1.3084639417185224, 1.2440625315755625, 1.179318358967083, 1.1163446142766773, 1.057255136789984, 1.0041140166533762, 0.9588856426261367, 0.9233864161161925, 0.8992393197501064, 0.8878324671062662, 0.8902826706643343, 0.9074049496148499, 0.9396887606948978, 0.9872815770072083, 1.0499802656729138, 1.1272305293930758, 1.2181344840767148, 1.3214662493423708, 1.4356952356933432, 1.5590166262293441, 1.6893883764497963, 1.8245738973052528, 1.9621894480592652, 2.099755150146033, 2.2347484438965624, 2.364658748969494, 2.4870420580806605, 2.59957419296919, 2.700101481509], [2.7627486193793738, 2.8399486771836555, 2.900589026614912, 2.94348976337243, 2.967811063642819, 2.9730706831942793, 2.9591533795998752, 2.926312052666627, 2.8751605948396906, 2.80665864002506, 2.7220885911478554, 2.623025489174693, 2.5113004548513094, 2.3889585849578228, 2.2582123138255352, 2.121391355085691, 1.9808904156367666, 1.8391159217973585, 1.698433015446081, 1.5611140652691493, 1.4292898954211626, 1.3049048620753592, 1.1896768093278043, 1.0850628122221129, 0.9922314693768741, 0.9120423444514713, 0.8450329785378906, 0.7914137089104715, 0.7510703380223754, 0.7235745049372486, 0.7082014242513142, 0.703954479595747, 0.7095959943754836, 0.7236833555175696, 0.7446095402449658, 0.7706469943036527, 0.7999937350887383, 0.8308205065097644, 0.861317795268153, 0.8897415308180885, 0.9144563332319644, 0.9339752433488238, 0.9469949661043959, 0.9524257783265638, 0.9494153934416251, 0.9373662338740628, 0.9159457334121358, 0.8850894721094618, 0.8449971308420804, 0.7961214367861239, 0.7391504501863054, 0.6749837123465479, 0.6047029305345916, 0.5295380135477503, 0.450829388582769, 0.3699876228703391, 0.2884514399642574, 0.20764525897250596, 0.12893739444536526, 0.05360003488670978, -0.017227930543878955, -0.08257424337008572, -0.1416618726732543, -0.19393210914268655, -0.23906153181696543, -0.2769723829821302, -0.307836058661581, -0.3320696017583713, -0.35032526763701277, -0.3634734131229008, -0.37257913495242856, -0.3788732481769541, -0.3837183447226828, -0.3885708034181172, -0.39493973196664633, -0.40434390575805584, -0.4182678258921795, -0.4381180478177605, -0.46518093177, -0.500582936654687, -0.5452545208449171, -0.5998986279178039, -0.6649646247390629, -0.7406284262139025, -0.8267793887424026, -0.9230143867127044, -1.0286393073960338, -1.1426780138238741, -1.2638886372604177, -1.390786875427274, -1.5216757943356727, -1.6546814649090003, -1.7877936147310887, -1.91891034404458, -2.04588584688061, -2.166579995694445, -2.278908593247165, -2.380893070160004, -2.470708411300251, -2.546728128918302, -2.607565164482595, -2.6521076929660206, -2.679548920746776, -2.689410108484164, -2.6815562099334818, -2.6562036928057493, -2.613920294199545, -2.5556166562897893, -2.482529983134193, -2.396200051877054, -2.298438096577469, -2.1912892558261423, -2.076989431992771, -1.9579175465080496, -1.8365442886648742, -1.7153785422269485, -1.5969127325082664, -1.4835683650755322, -1.377643025101771, -1.281260073686608, -1.1963222149294475, -1.1244700167001436, -1.0670463510939556, -1.0250675803217173, -0.9992021536787159, -0.9897571051509291, -0.9966727534391294, -1.0195257112795542, -1.0575401136567224, -1.1096067796379756, -1.174309834847063, -1.2499601455936473, -1.334634755654738, -1.4262213765351717, -1.5224668650994848, -1.6210285315757347, -1.7195270582500972, -1.8155997761715557, -1.9069530446108631, -1.9914125058610153, -2.0669700454747484, -2.13182637372789, -2.18442825580427, -2.223499553112147, -2.2480653928908585, -2.257468953995383, -2.251380539215126, -2.2297987941704576, -2.19304412504683, -2.1417445574291434, -2.0768144616120234, -1.999426741488276, -1.9109792402536085, -1.8130562529020922, -1.7073861495041653, -1.5957962018089167, -1.4801657666845582, -1.3623790118852201, -1.2442783719117791, -1.127619894362841, -1.014031580931445, -0.9049757435920648, -0.8017162877194295, -0.705291702687686, -0.6164943902707152, -0.5358567957259812, -0.46364462999181916, -0.39985728842665624, -0.34423538658789904, -0.29627515134925997, -0.25524923077246486, -0.22023332297624248, -0.19013787687580094, -0.163743989790416, -0.1397425217320534, -0.11677536631628452, -0.09347776566149864, -0.0685205326581571, -0.040651049170590446, -0.00873194291919293, 0.028223591909879945, 0.07102077646572746, 0.12025736451824405, 0.1763035938640596, 0.23928851809199841, 0.3090930984585941, 0.38535025926691535, 0.46745192838862526, 0.5545629020306277, 0.6456411941565666, 0.7394643606687108, 0.8346611308689695, 0.9297475378632336, 1.0231666190488597, 1.113330660720794, 1.1986648896519587, 1.277651471103848, 1.3488726582641322, 1.4110519530238403, 1.4630921819950733, 1.5041094636984054, 1.5334621411792024, 1.5507738765431325, 1.5559502470287594, 1.5491883427259823, 1.5309790399271892, 1.5021018070452772, 1.4636120874942955, 1.4168214912269386, 1.3632712090753452, 1.3046992370735673, 1.243002157203726, 1.1801923624858883, 1.1183517344427971, 1.059582876653995, 1.0059590769100812, 0.9594742105893248, 0.9219938082143372, 0.8952084903519832, 0.8805909234854149, 0.879357372340578, 0.8924348192290633, 0.920434491777258, 0.963632490056758, 1.0219580362489806, 1.0949896886434782, 1.1819596713990996, 1.2817662767353963, 1.392994101829004, 1.513941693426476, 1.6426559936918474, 1.7769728154917348, 1.914562428248142, 2.052979210281737, 2.189714223316962, 2.322249492004642, 2.448112727749794, 2.5649312229068775, 2.6704836588735676, 2.7627486193793707], [2.8189425587821075, 2.886097486720916, 2.935879267462139, 2.9673191281297475, 2.979800304903209, 2.9730706831942797, 2.9472472113455326, 2.9028119994921378, 2.840600212540981, 2.761780060694123, 2.667825377850624, 2.560481453023676, 2.441724938370511, 2.3137187957160656, 2.1787633582214694, 2.0392446723481585, 1.8975813453882993, 1.7561711541611413, 1.6173386703344899, 1.4832851272912975, 1.3560416933398367, 1.2374272279041498, 1.1290114833578597, 1.0320845782381478, 0.9476334111164365, 0.876325512300747, 0.8185006470726527, 0.7741702938609255, 0.7430249283256136, 0.7244488545137499, 0.7175421417197931, 0.7211490549184404, 0.7338922118119439, 0.7542115644217988, 0.7804071910321705, 0.8106847978587051, 0.8432027711271743, 0.876119590663868, 0.9076404162597235, 0.9360616878678717, 0.9598126392872973, 0.9774927108163027, 0.987903957195498, 0.9900776801497378, 0.9832946665828387, 0.9670985801185693, 0.9413022309912065, 0.9059866327858779, 0.861492939582967, 0.8084075390113371, 0.7475407509872454, 0.6798997441342968, 0.606656427978891, 0.5291112053396235, 0.44865357272414463, 0.3667206344390095, 0.2847546465771418, 0.20416072883561462, 0.12626587471787634, 0.05228035430874347, -0.016737460574066394, -0.07991190979773648, -0.13657567264511292, -0.18628952152562409, -0.2288556669289353, -0.2643243262517802, -0.2929933260221104, -0.315400728976505, -0.33231065980044716, -0.34469268148772403, -0.35369524368889455, -0.3606138807907292, -0.3668549768144768, -0.37389603298169094, -0.3832434689273073, -0.39638905758702586, -0.41476613494906434, -0.43970673803693044, -0.47240080730490014, -0.5138585434431832, -0.5648769344959712, -0.6260113689856279, -0.6975531268613493, -0.7795133955998513, -0.8716142972504513, -0.9732872376427112, -1.0836787057017774, -1.2016634634109147, -1.3258648801029982, -1.4546819831287225, -1.5863226250961566, -1.7188420101269308, -1.8501856819104565, -1.9782359582998101, -2.1008607037920526, -2.21596326487727, -2.3215323556637273, -2.4156906734205066, -2.496741046015592, -2.5632089652140166, -2.6138804402485745, -2.6478342130901598, -2.664467507870093, -2.6635146387883637, -2.6450579699042347, -2.6095309023423248, -2.557712755221331, -2.490715601366528, -2.409963312837221, -2.317163259733956, -2.2142712840242322, -2.1034507338582396, -1.9870264890088063, -1.8674350310824983, -1.747171709973239, -1.6287364282397738, -1.514579005934987, -1.4070454988659937, -1.308326723032035, -1.2204101875366307, -1.1450365588055615, -1.0836616723795363, -1.0374249774690132, -1.0071251470403244, -0.9932034161500146, -0.9957350276937071, -1.0144289721518844, -1.04863601098308, -1.0973647768250645, -1.1593055523938496, -1.2328611485651788, -1.3161841349854617, -1.4072195277377157, -1.5037519116795715, -1.6034558731308244, -1.7039485440579982, -1.8028430135487288, -1.8978013472371225, -1.9865859707377176, -2.067108218624972, -2.137472924874344, -2.1960180320691856, -2.241348322522483, -2.272362521615731, -2.288273188451467, -2.288618987257029, -2.273269120444581, -2.2424198961908366, -2.196583595112189, -2.1365699873561663, -2.0634610286212243, -1.9785794269122157, -1.8834519172510966, -1.779768205555681, -1.6693366424765022, -1.55403776075858, -1.4357768539566782, -1.316436789077868, -1.1978322306874072, -1.0816664096682564, -0.9694914973752227, -0.8626735472723691, -0.7623628438374357, -0.6694703556945983, -0.5846508302376776, -0.5082928944848258, -0.44051634593030153, -0.3811766323006692, -0.3298763350407721, -0.28598329268186506, -0.24865483146931092, -0.2168674159838361, -0.18945089585150526, -0.1651264094185494, -0.14254691434112854, -0.1203392506657644, -0.0971466057426656, -0.07167024310099808, -0.042709379370786074, -0.009198143874811271, 0.029761366669565647, 0.07487082279600997, 0.12661294497851133, 0.18523494783935313, 0.25073859835765694, 0.3228771678811379, 0.40115937775939076, 0.4848602556937593, 0.5730386390739864, 0.6645608872370314, 0.758130201169902, 0.8523208008460467, 0.9456160809168469, 1.03644975818876, 1.123248941960636, 1.2044780030085411, 1.278682090243056, 1.3445291465677625, 1.4008493072439645, 1.446670624387371, 1.4812501486411642, 1.504099511458142, 1.5150042860236121, 1.5140365583398527, 1.5015603085722822, 1.4782293822407295, 1.4449780167597237, 1.4030040765515026, 1.3537453347815325, 1.298849317068215, 1.2401373878415642, 1.1795639092055492, 1.1191714314212506, 1.0610429801883616, 1.0072525860431134, 0.9598152533327797, 0.9206375889823005, 0.8914703039736543, 0.8738637631948313, 0.8691276929051596, 0.8782960610536477, 0.9020980263095216, 0.9409357097825103, 0.9948693824505512, 1.063610485177412, 1.146522711177125, 1.242631187427259, 1.3506395965745954, 1.4689548890868311, 1.5957190514856698, 1.7288472249660771, 1.8660713137818918, 2.0049880882755264, 2.143110676668495, 2.2779222554515055, 2.4069306925102576, 2.527722871392575, 2.6380174300250987, 2.735714682634374, 2.818942558782105], [2.8682078735618104, 2.9247436635646467, 2.9632281622885337, 2.982911936658756, 2.983406521138876, 2.9646920920344906, 2.927116835305598, 2.8713880368413895, 2.798555120414566, 2.7099850491586626, 2.6073306867709034, 2.492492880358694, 2.367577173905516, 2.2348461861778812, 2.096668786522678, 1.955467274028432, 1.8136638082389844, 1.6736273520288476, 1.5376223691355426, 1.4077604707048945, 1.28595612828605, 1.1738874669645614, 1.0729630243507513, 0.9842952121443311, 0.9086810506838754, 0.8465905673891544, 0.7981630617605806, 0.7632112472640644, 0.7412330887440567, 0.7314309676886879, 0.7327376312922298, 0.7438482191393154, 0.7632575174279455, 0.789301468449935, 0.8202018655082456, 0.8541130929025661, 0.8891697287147714, 0.9235338158166312, 0.9554406240081773, 0.9832417729400684, 1.0054446602137823, 1.0207472398319652, 1.0280673203854616, 1.026565696832534, 1.0156625907692844, 0.9950470476223833, 0.964679120825119, 0.9247848581812932, 0.8758442896146514, 0.818572793717479, 0.7538963884767147, 0.6829216450593396, 0.6069010587404274, 0.5271948245811756, 0.44523005448375397, 0.36245853455728544, 0.2803141557910957, 0.20017115602591584, 0.12330428705132646, 0.050851967982754084, -0.016216593754525756, -0.07712943743890374, -0.1313342910298216, -0.1785148176263943, -0.2186002259412818, -0.25176797769283144, -0.2784395051402614, -0.29926903468525134, -0.31512579290137605, -0.327070044947932, -0.33632357766380877, -0.3442353865878987, -0.3522434539666234, -0.36183361021653593, -0.37449655160112083, -0.39168413997524654, -0.41476613494906417, -0.4449885040434346, -0.48343442240403384, -0.5309890111982074, -0.5883087744398168, -0.6557965798538864, -0.7335828933105591, -0.8215138216882206, -0.9191463496022059, -1.0257509754689247, -1.1403217663490546, -1.2615936635714362, -1.3880666869719032, -1.5180365093061507, -1.6496307084451707, -1.7808498574701344, -1.9096124854848744, -2.033802838098332, -2.1513202887609033, -2.2601292024896855, -2.3583080333163227, -2.4440964466382438, -2.51593929740605, -2.572526363852594, -2.6128268326572637, -2.6361176527559183, -2.6420050185395505, -2.63043840546541, -2.6017167581953657, -2.5564866189670497, -2.4957321774158734, -2.420757417768709, -2.3331607304530975, -2.234802538019983, -2.1277666553701207, -2.014316257417563, -1.8968454597429587, -1.7778276262121573, -1.6597615992762635, -1.5451171016915826, -1.4362805813704107, -1.3355027633984555, -1.2448491350858677, -1.1661545221573177, -1.10098281845836, -1.050592810173113, -1.0159108914522834, -0.997511305039373, -0.9956043629245448, -1.0100329125922065, -1.0402771186680473, -1.0854674324753544, -1.144405427976221, -1.2155919965158801, -1.2972622192252086, -1.3874260790754738, -1.4839140382166007, -1.584426393655813, -1.6865852382515851, -1.7879877964601718, -1.8862598766280867, -1.9791081844881797, -2.0643702757547358, -2.140060988443827, -2.2044142861658336, -2.2559195598623005, -2.293351574377342, -2.3157934044009973, -2.3226518777676146, -2.313665228536377, -2.288902853161555, -2.2487572556654483, -2.1939284573133113, -2.1254013281972286, -2.044416467905879, -1.952435415939773, -1.8511011059897835, -1.7421945883979473, -1.6275891294142035, -1.5092028522505314, -1.3889511121109184, -1.2686997947670362, -1.1502206960215815, -1.035150078456601, -0.9249514138190004, -0.8208832065363535, -0.7239726590841505, -0.634995786682144, -0.5544644209778422, -0.48262036423109606, -0.4194367715464746, -0.3646266535489987, -0.3176582102229824, -0.27777653299844507, -0.2440310509303204, -0.2153079520102764, -0.19036668589900924, -0.16787955277921016, -0.14647330713127638, -0.12477165690144573, -0.10143751894681849, -0.0752139012606742, -0.04496232102624723, -0.009697734011556958, 0.03138095650661383, 0.07886562658301673, 0.13311957210817474, 0.1942645861002151, 0.26217482768063916, 0.3364776602213596, 0.4165614540617361, 0.5015901670470592, 0.5905243385586507, 0.6821479642021694, 0.7751005631809155, 0.8679136125580762, 0.9590504056257418, 1.0469482984486638, 1.1300622417397566, 1.2069084562975927, 1.276107100337512, 1.3364227964934263, 1.38680193463545, 1.4264057427911234, 1.4546382205276025, 1.4711681546477668, 1.4759445828813862, 1.469205233804537, 1.4514776464620198, 1.4235728567373733, 1.3865717248359135, 1.3418041646359826, 1.2908217164535847, 1.2353640754170976, 1.177320343864322, 1.1186859140081913, 1.0615160030707422, 1.0078769541972756, 0.9597964803823263, 0.919214063685858, 0.8879327272248663, 0.8675733725620075, 0.8595328206950852, 0.8649466121272187, 0.8846575124192109, 0.9191905368011575, 0.9687351540493753, 1.0331351596317728, 1.1118865252266195, 1.2041433405842612, 1.308731768997785, 1.4241717441429405, 1.5487059484830024, 1.680335436417067, 1.8168611032334818, 1.9559300577072025, 2.0950858353854964, 2.2318212942289604, 2.3636329666832148, 2.488075604138452, 2.6028156420586184, 2.7056823370512237, 2.794715380273217, 2.8682078735618077], [2.9101277568626367, 2.9555602435711545, 2.982404327068349, 2.990136266743473, 2.978599202128635, 2.9480057963874797, 2.8989325635704675, 2.832306025657911, 2.749381038965458, 2.6517118146537793, 2.5411163303693876, 2.4196349852696724, 2.289484485095945, 2.153008054310226, 2.012623155953949, 1.8707679548260023, 1.7298477845262241, 1.5921828733180128, 1.4599585478294197, 1.3351790682799578, 1.2196261558542372, 1.1148231543862126, 1.0220056276318958, 0.9420990336027506, 0.8757039426745943, 0.8230890808058616, 0.784192287776277, 0.758629287613123, 0.7457099790513815, 0.7444617726251608, 0.7536593322508041, 0.771859927057574, 0.7974434674500247, 0.8286561911355375, 0.8636568827198283, 0.9005644564076372, 0.9375057065900525, 0.9726620361680798, 1.0043140071261216, 1.030882621165736, 1.050966328465656, 1.0633728775074418, 1.0671452554475707, 1.0615811232428005, 1.046245318715692, 1.0209751797035964, 0.9858786238477153, 0.9413251068025686, 0.8879297620218058, 0.8265311982499058, 0.7581635910855941, 0.6840238484724247, 0.6054347531322619, 0.5238050847207952, 0.44058779837507045, 0.35723738251878845, 0.27516753616751394, 0.195710294134682, 0.1200776878175083, 0.049326960703411644, -0.015669736854245272, -0.07425036726882633, -0.125982072287598, -0.17067377495807828, -0.20838197452540044, -0.23940956969590504, -0.2642977279263734, -0.2838110003179892, -0.29891605869000654, -0.3107545989829856, -0.32061110903251183, -0.3298763350407718, -0.340007396274205, -0.35248558867755414, -0.36877298286669163, -0.39026895865471284, -0.4182678258921791, -0.4539186597068313, -0.4981884276908947, -0.5518294084109274, -0.6153517967075002, -0.6890022641606725, -0.7727490959588765, -0.866274361868893, -0.9689734031262719, -1.0799617332292228, -1.1980892634135119, -1.3219615776933555, -1.4499678024343832, -1.5803144459998477, -1.711064429350348, -1.8401803924912157, -1.9655712478051677, -2.085140862492751, -2.1968376908651015, -2.298704144714175, -2.388924487330827, -2.4658700641180338, -2.5281407395775544, -2.5746014954253797, -2.6044132557056483, -2.617057139365529, -2.6123514955792784, -2.590461248416382, -2.551899261070055, -2.4975196213200905, -2.4285029445179385, -2.3463339833860086, -2.252772020582357, -2.1498146957094866, -2.0396560789173384, -1.9246399445086104, -1.807209316510198, -1.689853451090043, -1.5750534856639709, -1.4652280199231498, -1.362679898916795, -1.2695454425884303, -1.18774731038123, -1.1189521050287459, -1.0645337084657254, -1.025543207618971, -1.0026861119467025, -0.996307391772505, -1.0063846809061527, -1.03252979327032, -1.0739985059716706, -1.1297083652641446, -1.1982640819153163, -1.2779899032168882, -1.3669681846275514, -1.4630832387793347, -1.5640694168280798, -1.667562279840757, -1.7711516484163792, -1.872435278678738, -1.9690719030799588, -2.0588323952898193, -2.139647869243675, -2.209653601873406, -2.2672277751413743, -2.311024163076355, -2.3399980403264133, -2.353424756546885, -2.3509106015711514, -2.332395775298649, -2.2981494689129174, -2.248757255665448, -2.1851011753174405, -2.1083330718626905, -2.0198419050674006, -1.921215898734074, -1.8142005089718491, -1.7006532912323025, -1.5824968131687418, -1.4616707998987766, -1.3400847081121832, -1.2195719055258305, -1.1018465830420403, -0.9884644499388053, -0.8807881595242814, -0.7799582865769891, -0.6868705317943438, -0.6021596661040888, -0.5261905531730534, -0.45905640618769067, -0.4005842495782416, -0.3503473724808345, -0.3076843829992529, -0.27172430519952295, -0.2414170084311378, -0.21556812482644516, -0.19287749902011125, -0.1719801270337555, -0.1514884810427793, -0.13003508486088797, -0.10631420220658984, -0.07912152618563097, -0.047390813231100996, -0.01022648657080601, 0.033068658958130305, 0.08297138997904031, 0.13972219689743492, 0.20331611382100068, 0.27350045038591975, 0.349779509159768, 0.4314261796389146, 0.517500119828105, 0.6068720635546111, 0.698253630422612, 0.7902318697599616, 0.8813076437621464, 0.9699368515237796, 1.054573417427329, 1.1337129164589714, 1.2059356867844955, 1.269948286967013, 1.324622191430918, 1.369028682327073, 1.402468987274598, 1.4244988283115958, 1.4349466849283024, 1.4339252298797545, 1.4218355667147862, 1.3993640783793106, 1.3674718823552388, 1.327377074932671, 1.2805301306958163, 1.2285829985274113, 1.1733525979937616, 1.1167795657589248, 1.060883226998629, 1.0077138684475873, 0.959303465107325, 0.917616059799657, 0.8844990124059772, 0.8616363232466093, 0.850505192832624, 0.8523369091111183, 0.8680830549869347, 0.8983879056801259, 0.9435677403307625, 1.0035976286999633, 1.0781060758100074, 1.1663777192526295, 1.26736408026647, 1.379702175279737, 1.5017406041983266, 1.6315725499672609, 1.7670749553147973, 1.905952991257186, 2.0457888016325136, 2.1840934018678064, 2.31836053099656, 2.4461212056105306, 2.5649977042183587, 2.6727557209282233, 2.7673534682530923, 2.8469865791899522, 2.9101277568626345], [2.9443475475028977, 2.9782865045289233, 2.993245522770234, 2.9889309972823366, 2.9654190199666512, 2.9231529698650562, 2.862932847832549, 2.785896617441127, 2.6934940031742407, 2.587453375112324, 2.4697425120635703, 2.342524178517639, 2.2081075714264715, 2.0688967877408766, 1.9273375305809766, 1.785863309308201, 1.6468423957378118, 1.5125267751725777, 1.3850042774876508, 1.2661549915244616, 1.1576129576258265, 1.0607340009804227, 0.9765704158360202, 0.9058530413778574, 0.8489810883446633, 0.8060198857619076, 0.7767065241894965, 0.7604631803601087, 0.7564177227297718, 0.7634310228168992, 0.7801302375382286, 0.8049471869487858, 0.8361608332716758, 0.8719427737164707, 0.910404593557689, 0.9496458888191834, 0.9878017605079138, 1.0230886047432675, 1.0538470746769206, 1.0785811694111558, 1.0959925101307182, 1.1050089916596764, 1.1048071453682327, 1.094827713028445, 1.0747841067047923, 1.0446636126321882, 1.0047213826705395, 0.9554674406618204, 0.8976471082391269, 0.8322154209050536, 0.760306256348881, 0.6831970292339244, 0.6022699167633502, 0.5189706644915761, 0.4347660799854183, 0.3511013516323626, 0.26935833043728413, 0.19081588407207598, 0.11661337550599277, 0.04771823472237309, -0.015101516530056891, -0.07129905752393724, -0.12056429861090785, -0.16283273228976225, -0.19828736371208106, -0.2273536599848986, -0.2506876402149032, -0.26915740784030595, -0.28381859885275523, -0.29588437964857167, -0.30669077238959774, -0.31765821022298213, -0.3302503263221787, -0.3459310568569931, -0.36612118670545724, -0.3921554866997735, -0.4252415818884971, -0.46642165186926693, -0.5165379976044925, -0.576203415890536, -0.6457772050935299, -0.7253474867910069, -0.814720371008988, -0.9134163217175647, -1.0206738984028367, -1.135460863382306, -1.2564924577298937, -1.3822564659064087, -1.5110445150430512, -1.6409888936842965, -1.7701040307337546, -1.8963316520165237, -2.0175885324204774, -2.131815688565969, -2.2370278122859877, -2.3313617300841596, -2.413122688652174, -2.4808273112033237, -2.533242142808118, -2.5694168033802613, -2.588710892061925, -2.590813933487255, -2.5757578212118917, -2.5439213924797843, -2.4960269570966567, -2.433128796884411, -2.3565938462594174, -2.2680749541502934, -2.1694773080868126, -2.0629187684058508, -1.9506850100131674, -1.8351804973175871, -1.7188764216430907, -1.604256807046456, -1.4937640381083797, -1.3897450807164582, -1.2943996536523859, -1.2097315652159988, -1.1375043561939941, -1.0792022899591605, -1.0359976047916057, -1.0087247956897927, -0.9978625265711687, -1.0035235928907347, -1.0254531637265643, -1.0630353359375553, -1.115307835867064, -1.1809845110388073, -1.258485070058706, -1.3459713579708086, -1.4413893007625946, -1.5425155202906944, -1.6470075127983774, -1.7524562030178616, -1.8564396335284745, -1.9565765268012054, -2.050578465687693, -2.1362994767430434, -2.2117818687001187, -2.27529727391308, -2.325381961260808, -2.36086563183304, -2.380893070160003, -2.3849381997858594, -2.3728102782714826, -2.3446521586425675, -2.3009307371452707, -2.2424198961908366, -2.170176431924652, -2.085509623524616, -1.9899452520275192, -1.8851850065376723, -1.773062321945776, -1.6554957722304184, -1.5344411951400596, -1.4118437463747107, -1.2895910738506016, -1.1694687655278553, -1.0531191586341264, -0.9420045056576178, -0.8373753756064993, -0.7402450307358698, -0.6513703627537909, -0.571239802399037, -0.5000684365390107, -0.4378003821024695, -0.3841182808923176, -0.3384595982754618, -0.3000392364611047, -0.26787781387094173, -0.24083481995417394, -0.21764573325258812, -0.19696209259965086, -0.17739343946846103, -0.15755000543495387, -0.1360850035618259, -0.11173539657487762, -0.08336005760078284, -0.04997430984238905, -0.010779928066643915, 0.03481019529768118, 0.08715337636787124, 0.146364958152853, 0.2123129509813291, 0.2846196465805095, 0.3626701750351887, 0.4456277921861782, 0.5324555086370331, 0.6219435049109717, 0.7127416246742374, 0.8033961032063874, 0.892389574893403, 0.9781833143524902, 1.0592606031677896, 1.1341700797582068, 1.2015679245395134, 1.260257756479568, 1.3092271698389009, 1.3476799200758507, 1.3750628736209696, 1.3910869648895219, 1.395741552323977, 1.3893017297590855, 1.3723283258891987, 1.3456605086917934, 1.3104010987235786, 1.2678948805740613, 1.219700380784954, 1.1675557487200092, 1.1133395299577216, 1.0590272559031584, 1.0066448850649774, 0.9582202179564415, 0.915733466615965, 0.8810681897400929, 0.8559638045357042, 0.8419708565244438, 0.8404101693094539, 0.8523369091111179, 0.8785104857584576, 0.9193710754963316, 0.9750233947256657, 1.0452281814232804, 1.1294016566848157, 1.2266230470964357, 1.3356500541583294, 1.4549419645214938, 1.5826899090843756, 1.7168536045934841, 1.8552037525989058, 1.995369131349969, 2.1348872999226707, 2.2712577434336323, 2.4019962258687872, 2.524689084405774, 2.6370461969756547, 2.736951383285906, 2.8225090579542313, 2.8920860413887564, 2.944347547502896], [2.970577730569145, 2.9927301719864996, 2.9956600279728542, 2.9793063254003775, 2.9439774849581135, 2.8903438786256315, 2.8194222619770426, 2.7325524567850477, 2.6313668426528807, 2.517753386010092, 2.393813086653341, 2.261812852420753, 2.124134918410213, 1.9832240058457917, 1.8415334653866011, 1.701471669195899, 1.565349905023264, 1.4353329842276485, 1.3133937051545215, 1.2012722153615085, 1.100441193319122, 1.0120776254606254, 0.9370417914145852, 0.875863892965372, 0.8287385751339436, 0.7955273953712624, 0.7757691039475297, 0.7686974099425359, 0.7732657274223995, 0.7881782298235976, 0.8119263913175505, 0.8428300656221152, 0.87908204845824, 0.918794992116698, 0.9600494912345588, 1.000942139009402, 1.0396323630929856, 1.0743868899537656, 1.1036207544951258, 1.125933866374332, 1.1401422633375025, 1.1453033219223845, 1.1407343535165189, 1.1260241849956274, 1.1010375036762492, 1.0659119315464445, 1.0210479790275053, 0.9670922092151201, 0.9049141151204667, 0.8355773705871202, 0.7603062563488809, 0.6804481826087367, 0.5974333255814781, 0.5127324652762574, 0.42781415368673165, 0.3441023554958926, 0.2629356871095795, 0.18552933476197325, 0.1129406597665545, 0.0460394005893948, -0.01451674018302587, -0.06830047762016109, -0.11512680681662653, -0.15505802839053245, -0.18840179847666785, -0.2157022470113284, -0.23772438950652472, -0.25543223327538916, -0.26996114473152377, -0.2825851957291103, -0.29468034008208976, -0.3076843829992526, -0.32305479333746323, -0.3422254690600145, -0.3665635985128933, -0.39732776322950353, -0.4356284018066287, -0.4823916995593787, -0.5383278864800829, -0.6039048185043917, -0.6793275868753056, -0.7645247507150364, -0.8591416224817511, -0.9625408589219357, -1.07381042584712, -1.1917788181734361, -1.3150372318465364, -1.4419682061725652, -1.57078008817171, -1.6995465190765864, -1.8262500108519628, -1.948828570981739, -2.065224249564869, -2.173432426168807, -2.2715506264101024, -2.357825660649683, -2.4306979095473733, -2.488841642815541, -2.5312003469179998, -2.55701615255804, -2.5658525908279213, -2.5576100645180118, -2.532533594481365, -2.4912125858963647, -2.4345725512492917, -2.3638589211719174, -2.2806132661508145, -2.1866424368615123, -2.0839813039254644, -1.9748499349749193, -1.8616061841604048, -1.7466947832485904, -1.632594111403304, -1.521761880422929, -1.4165810021197038, -1.3193069038936154, -1.2320175273492837, -1.1565671837498201, -1.094545350651779, -1.0472413783710468, -1.015615935785818, -1.000279865760917, -1.0014809450406565, -1.019098856067234, -1.0526484833925323, -1.101291449899033, -1.163855612730628, -1.238862050403368, -1.3245588955963892, -1.4189612069084636, -1.5198959313118963, -1.6250508905644498, -1.7320266323056686, -1.83838992218211, -1.9417276186405705, -2.03969966779411, -2.130089982049488, -2.210854022284503, -2.2801619878476553, -2.3364366293932917, -2.378384833794495, -2.4050222847531537, -2.415690673420506, -2.4100671161281215, -2.3881656266940055, -2.350330684018967, -2.297223127070831, -2.229798794170457, -2.1492804972175725, -2.057124079883674, -1.954979447999342, -1.844647577002714, -1.7280345925890457, -1.6071040844370619, -1.4838288476020947, -1.3601432510981455, -1.2378974083206575, -1.1188142700094226, -1.0044506788577414, -0.8961633177650219, -0.7950803538621077, -0.7020794311278646, -0.617772499456585, -0.5424977916053317, -0.47631907600283063, -0.4190321275576542, -0.37017817503472095, -0.32906390688193704, -0.29478745200771883, -0.26626960206989847, -0.24228941107738713, -0.2215231997812915, -0.20258590912764549, -0.18407369101057733, -0.16460659706857123, -0.14287022795443016, -0.11765523629420768, -0.08789363561240025, -0.05269095330973434, -0.011353376133580754, 0.036590831339779674, 0.09137620425228958, 0.1529916551083243, 0.22117898026770866, 0.29543834283310844, 0.375040596981223, 0.45904613963507424, 0.5463298041171294, 0.6356111514139529, 0.7254893719697849, 0.8144818881483524, 0.9010656477998441, 0.9837200253047755, 1.0609701999577064, 1.1314298638290823, 1.1938421228076743, 1.2471174951481163, 1.2903679805663701, 1.3229362680708536, 1.3444192699531563, 1.354685309744972, 1.353884449997148, 1.3424516175227643, 1.3211023649874414, 1.2908212939001666, 1.2528433504967416, 1.208628388040359, 1.159829562113418, 1.1082562851798945, 1.0558326090207857, 1.0045520249716213, 0.9564297691231249, 0.9134537902765921, 0.8775355806260821, 0.8504620817224375, 0.8338498608459508, 0.8291027058055647, 0.8373737104595533, 0.8595328206950844, 0.8961406836589939, 0.9474294947561899, 1.0132913709158402, 1.0932745989052481, 1.1865879184304822, 1.2921128060231573, 1.4084235320209582, 1.5338145740596782, 1.6663347910517734, 1.8038275960494172, 1.9439762187656335, 2.084353022505382, 2.2224717389646096, 2.3558414103110135, 2.4820207830214405, 2.598671883261966, 2.7036115195592982, 2.794859504779252, 2.8706824649075804, 2.9296322050116888, 2.9705777305691443], [2.988596386843346, 2.9987690459813585, 2.989627414869619, 2.961343680176932, 2.9144560021915997, 2.8498561024273745, 2.768768925249051, 2.6727248594273316, 2.5635251812922495, 2.443201540794494, 2.3139704514361275, 2.178183861320086, 2.0382769726897454, 1.8967145391271807, 1.7559369015891495, 1.6183070259520989, 1.486059775729798, 1.361254594885208, 1.245732688676124, 1.141079677437228, 1.0485945619306778, 0.9692656827809791, 0.9037541844171028, 0.8523853101311089, 0.8151476638640387, 0.7917003808505375, 0.7813879580498111, 0.7832623110521058, 0.7961114513857559, 0.8184940210757407, 0.848778783739873, 0.8851880567817875, 0.9258439801071672, 0.968816455367683, 1.012171557451519, 1.0540192174898655, 1.0925590039937836, 1.1261228850939546, 1.153213938726628, 1.1725400868116163, 1.1830420611958883, 1.183914960028151, 1.174622919454248, 1.1549066028749408, 1.1247833940118865, 1.0845403660533768, 1.0347202825255633, 0.9761010616602391, 0.9096693004992513, 0.8365886036804953, 0.7581635910855941, 0.6758005650831779, 0.5909658993366267, 0.505143265063018, 0.4197908359212799, 0.3362996087837748, 0.2559539446532316, 0.17989537280372805, 0.10909061343627195, 0.04430466200092287, -0.013920355285662414, -0.0652799969003567, -0.10971560054582676, -0.14741544077347002, -0.1788089151743217, -0.2045539070012755, -0.2255176507681686, -0.24275159781077008, -0.2574609366587472, -0.27096956433850955, -0.284681425802092, -0.3000392364611045, -0.3184816747851249, -0.34140017623617813, -0.37009647528491524, -0.4057420284439796, -0.4493404084499769, -0.5016936889471794, -0.5633737419977412, -0.6346992498513536, -0.7157190906412326, -0.8062025985520497, -0.9056370264888606, -1.0132323576681506, -1.1279334263923897, -1.2484391222209155, -1.373228270482601, -1.5005916101493026, -1.6286691318410365, -1.7554918981682712, -1.8790273493068261, -1.9972270016972897, -2.1080753795158924, -2.2096389788693567, -2.300114054608205, -2.3778720395830955, -2.441501455694774, -2.4898452540827196, -2.522032626424353, -2.5375044580760293, -2.5360317435755753, -2.517726452214202, -2.4830445119050246, -2.432780769020827, -2.368055975609864, -2.2902960486761135, -2.201204034281454, -2.1027253874645617, -1.9970073429808997, -1.8863532975991202, -1.773173248534393, -1.659931431482886, -1.5490923731786568, -1.443066615628077, -1.3441573811081309, -1.254509428304182, -1.1760613010242473, -1.110502092914255, -1.0592337463806445, -1.0233397740389178, -1.0035611395909623, -1.0002798657609167, -1.013510753897561, -1.0429014075276422, -1.0877405551936596, -1.1469744711195493, -1.2192311004019774, -1.3028513131849175, -1.3959265440655706, -1.4963419228795578, -1.601823874656354, -1.7099910630204038, -1.8184074751273307, -1.9246363991839217, -2.026294028805364, -2.121101442271, -2.206933748757551, -2.2818652667226007, -2.3442096999359463, -2.392554401700805, -2.425787964456726, -2.443120536571877, -2.4440964466382433, -2.4285989035704527, -2.3968467336426915, -2.3493833085335996, -2.28705800674854, -2.2110007298385157, -2.1225901602593416, -2.0234165954836714, -1.9152403195071543, -1.7999465751264603, -1.679498275867297, -1.5558876434284532, -1.4310879739173665, -1.307006723653862, -1.1854410633243841, -1.068036978924039, -0.9562529010745323, -0.851328723453963, -0.7542609293137795, -0.6657843859957883, -0.586361195029427, -0.5161768041401954, -0.4551434019013576, -0.4029104304794258, -0.35888187160897694, -0.32223979010104836, -0.29197346211203035, -0.2669132759959542, -0.2457684753016651, -0.22716771929114893, -0.20970136857146232, -0.19196436370920966, -0.1725985539852669, -0.15033335196999031, -0.12402363684179649, -0.09268390409903751, -0.055517759600107935, -0.011941979141482028, 0.03839550209776263, 0.09560414659754175, 0.15954622290899104, 0.2298391910604526, 0.3058650080779037, 0.38678611563052745, 0.4715676966943134, 0.5590056234504421, 0.6477593685894588, 0.7363890205987123, 0.8233954338288728, 0.9072624589787135, 0.9865001413005889, 1.0596877438346348, 1.12551545213832, 1.1828236453675944, 1.2306386755295577, 1.268204180888452, 1.2950070688046744, 1.3107974350245761, 1.315601837352406, 1.3097295079740552, 1.2937712663202272, 1.268591078818754, 1.2353103985765954, 1.1952856022699043, 1.1500790186767924, 1.1014242088990234, 1.0511863082019297, 1.0013183697562584, 0.9538147580683173, 0.9106627217765385, 0.8737933296432503, 0.8450329785378907, 0.8260566772699423, 0.8183442753070059, 0.8231407414679581, 0.8414215060988058, 0.8738637631948302, 0.9208244892365494, 0.9823257765361831, 1.0580479045062607, 1.1473303867127163, 1.2491810393955594, 1.3622929230378205, 1.485068817301264, 1.615652705927334, 1.7519675765493352, 1.8917586850111634, 2.032641298581211, 2.1721518207385797, 2.307801114771624, 2.4371287864036217, 2.557757158489484, 2.6674436742231866, 2.76413049921908, 2.845990156496704, 2.9114661202915983, 2.9593074125246663, 2.988596386843345], [2.9982510703398844, 2.9963520349068817, 2.9751987220971707, 2.9351950337187787, 2.8771043367699387, 2.80203218617785, 2.7114013877981886, 2.6069199939139227, 2.490542990246159, 2.364428581811148, 2.2308901112350705, 2.0923447443229, 1.9512601313370275, 1.8101002968194628, 1.6712720248512354, 1.5370729900910736, 1.40964283823043, 1.290918343839946, 1.1825936708688238, 1.086086633859894, 1.0025117094229075, 0.9326603813491793, 0.8769892230615853, 0.8356159323100255, 0.8083233397942501, 0.7945712204743222, 0.7935155484480753, 0.8040346580347386, 0.8247616094573025, 0.8541219112612827, 0.8903756268894056, 0.9316627926553823, 0.9760510011166924, 1.021583959255352, 1.0663298159428705, 1.1084280681589773, 1.1461338998787087, 1.1778588802341436, 1.2022070465916574, 1.218005521008554, 1.224328952003614, 1.2205172340466366, 1.2061861305788357, 1.1812306083416837, 1.1458208767343263, 1.1003913111675936, 1.045622619290332, 0.9824177790289393, 0.91187243335543, 0.8352405646956209, 0.7538963884767146, 0.6692934976045849, 0.5829223553813712, 0.49626727191981423, 0.4107640075879515, 0.327759126263977, 0.24847217176869588, 0.1739616640649041, 0.10509580964926518, 0.04252869563039396, -0.013317407524065458, -0.06226316999819676, -0.10437646105215827, -0.1399696291881256, -0.16958987393860966, -0.19400295995590622, -0.21417069853317372, -0.23122278536053262, -0.24642373205113, -0.26113575897446706, -0.2767786248889735, -0.29478745200771855, -0.31656966131747644, -0.34346216073622315, -0.37668992728538675, -0.4173270938519889, -0.46626159203758516, -0.5241643164681982, -0.5914636648864093, -0.6683261751075872, -0.754643827802108, -0.8500284168499042, -0.9538132108730061, -1.0650619449386514, -1.1825849949630962, -1.304962403713422, -1.4305732511194809, -1.5576306973115845, -1.6842218785464969, -1.8083517077366622, -1.9279895259329993, -2.041117471538783, -2.1457793823238056, -2.240129022848119, -2.3224764373526408, -2.3913312654475307, -2.445441924205309, -2.4838296539994, -2.5058165443909943, -2.5110467976986905, -2.49950064816673, -2.4715005299834565, -2.4277092735155317, -2.3691203014646365, -2.2970399905073777, -2.2130625545858944, -2.119037988686038, -2.017033782170238, -1.9092912643188755, -1.7981775778758375, -1.6861343857868878, -1.5756244992372763, -1.469077669459497, -1.3688368102120776, -1.2771059116794803, -1.1959008699128362, -1.1270043896724673, -1.0719260242224637, -1.0318682955314074, -1.0076996953510222, -0.9999352052377035, -1.0087247956897918, -1.033850175515402, -1.0747298669158274, -1.1304324843231657, -1.1996979005677761, -1.2809657971977177, -1.372410921264852, -1.4719842128659715, -1.5774588300118026, -1.6864799833224564, -1.7966174053637123, -1.905419220245316, -2.010465949800885, -2.109423393926125, -2.2000931543850797, -2.28045963277333, -2.3487324227964392, -2.403383132338801, -2.4431758090883173, -2.4671903013119385, -2.474838058839169, -2.4658700641180338, -2.440376774805361, -2.3987801530245094, -2.341818047411765, -2.270521377696095, -2.186184743325482, -2.0903312333781416, -1.9846723508954431, -1.8710640775601606, -1.751460191612219, -1.6278640109829294, -1.5022797634712293, -1.3766647857427659, -1.2528837231085925, -1.132665843277217, -1.0175664911312732, -0.9089336002942877, -0.8078800436801981, -0.7152624527641942, -0.6316669678451531, -0.5574022033215479, -0.4924995274679659, -0.4367205700195919, -0.38957168772021744, -0.350324942453703, -0.31804498304871026, -0.29162107440190194, -0.26980338987642866, -0.25124257816937584, -0.2345315365929327, -0.21824827092442456, -0.20099869890275762, -0.18145826061312384, -0.15841123420223246, -0.13078671866727729, -0.09769033522167642, -0.05843081265314884, -0.012540757242554995, 0.040208939240394675, 0.0998014330982212, 0.16597320694528378, 0.23822031405746427, 0.3158114280088044, 0.39780735858042143, 0.48308652532510543, 0.5703757234695376, 0.6582853770230537, 0.7453483546014719, 0.8300613276180658, 0.910927580603349, 0.9865001413005892, 1.0554240849576944, 1.116476883285126, 1.1686057135243346, 1.2109607158946165, 1.2429232865796556, 1.2641286159412117, 1.2744818247727794, 1.2741672115737384, 1.2636502970445531, 1.243672533950758, 1.2152387366257522, 1.1795974700144838, 1.1382148186382441, 1.0927421266420696, 1.0449784568586877, 0.9968286556158077, 0.9502580272962928, 0.9072447154301235, 0.8697309529555954, 0.839574381499937, 0.8185006470726529, 0.8080584571478466, 0.8095782321888866, 0.8241354044277397, 0.8525193100444552, 0.8952084903519816, 0.9523530663263892, 1.023764682501705, 1.1089143349701893, 1.206938208420311, 1.3166514534529727, 1.4365696425936163, 1.5649374562033889, 1.6997639724966835, 1.8388637734624742, 1.979902934676834, 2.120448845348991, 2.2580227084870996, 2.390153502212405, 2.5144321437267556, 2.6285645882653554, 2.730422616818312, 2.8180911180019272, 2.8899107499878482, 2.9445149759269222, 2.9808605982439444, 2.998251070339884], [2.999460098067586, 2.9854995877704686, 2.9524960229254216, 2.9010816154073513, 2.8322385006844177, 2.7472767418490966, 2.647805004950395, 2.5356945991841036, 2.4130377318756766, 2.282100963938223, 2.1452749633225534, 2.0050217392016343, 1.8638205962054717, 1.7241140746059513, 1.5882551383413532, 1.4584568383150247, 1.3367456143954604, 1.2249193076032232, 1.1245108363940008, 1.036758350662806, 0.9625825175807559, 0.9025714185794262, 0.8569733510323835, 0.8256976360267183, 0.8083233397942501, 0.8041156256403291, 0.8120492702397554, 0.8308387074353683, 0.8589738083354101, 0.8947604723074501, 0.9363649926503168, 0.9818610759473535, 1.0292783373701413, 1.0766510668192497, 1.1220660633348867, 1.163708367519791, 1.1999037828856594, 1.2291571654446418, 1.2501855742280412, 1.2619455108184958, 1.2636536299819165, 1.2548004721769261, 1.235156947841653, 1.204773488397859, 1.1639719652201679, 1.1133306607207947, 1.053662750619418, 0.9859889190339345, 0.9115048741881105, 0.8315446586523036, 0.7475407509872452, 0.6609820329083081, 0.5733707457373178, 0.4861795807650704, 0.40081003973913243, 0.31855316428322905, 0.24055366764011576, 0.1677784104064656, 0.10099004625324141, 0.0407265269569366, -0.012712998109135083, -0.05927552063440317, -0.09915455987172567, -0.13278358856977918, -0.1608226720300496, -0.18413867166158204, -0.20377953315200253, -0.2209433348948524, -0.23694291065404424, -0.2531669780802103, -0.2710387986145173, -0.2919734621120301, -0.3173349294336501, -0.3483939772382203, -0.38628817092681317, -0.4319849445578776, -0.48624879169938034, -0.5496134704455324, -0.622360001687614, -0.7045010952690692, -0.7957724774679064, -0.8956314193543928, -1.0032625833143258, -1.117591118971976, -1.237302754559014, -1.3608704501124522, -1.4865870092720903, -1.6126028911715373, -1.7369683269130605, -1.8576787298734738, -1.9727222985605883, -2.080128647270694, -2.1780172650635974, -2.2646445985361323, -2.3384485787662976, -2.3980894671018067, -2.442485976932296, -2.4708457372643755, -2.4826892962097875, -2.477867015205043, -2.4565683741990525, -2.419323390045315, -2.3669960404691426, -2.3007697795900066, -2.2221254233108962, -2.1328118692098164, -2.03481029129086, -1.9302926107352254, -1.8215751856568485, -1.7110687822938988, -1.6012259840822647, -1.4944872613078812, -1.3932269608463554, -1.299700481918118, -1.2159938796062546, -1.143977083644242, -1.0852618369624853, -1.041165348671448, -1.0126805222012594, -1.000453464450276, -1.0047688097714256, -1.0255432076189706, -1.0623271291836003, -1.114314951062823, -1.1803630777422984, -1.2590156741729572, -1.3485373996476917, -1.4469523688827368, -1.5520884197030527, -1.6616256425650426, -1.7731480283235623, -1.8841970195392876, -1.992325708922662, -2.095152417196469, -2.190412401957465, -2.2760064985077055, -2.3500455718472137, -2.410889764107894, -2.4571816510418123, -2.4878725715428813, -2.502241561855566, -2.4999065069643054, -2.480827311203325, -2.445301083712651, -2.393949527236606, -2.327698906185873, -2.2477531472781886, -2.1555607891066173, -2.0527766416927182, -1.9412191399601728, -1.8228244731552101, -1.6995986432048595, -1.5735686471816357, -1.4467339914876698, -1.3210197278770226, -1.198232154537886, -1.0800182504218105, -0.9678298097960082, -0.8628931192138367, -0.7661848739353648, -0.6784148689719727, -0.6000158254718215, -0.5311405305068895, -0.4716662820633788, -0.42120644585167866, -0.3791287510796219, -0.3445797830616073, -0.31651497569075726, -0.2937332702368184, -0.2749154920401015, -0.2586654062931994, -0.2435523504601052, -0.22815430552510865, -0.21110026202740043, -0.19111075982500814, -0.16703553211218855, -0.1378872630380771, -0.10287057230758354, -0.06140546672185704, -0.013144644503114396, 0.042015800268859496, 0.10393255281123866, 0.17221823202401207, 0.24625144116568745, 0.3251934514123889, 0.40801108112837997, 0.49350517102490443, 0.5803439079832253, 0.6671001219203169, 0.7522915739582553, 0.8344231730381236, 0.91203000408632, 0.9837200253047758, 1.0482152958103106, 1.1043906276519966, 1.1513086174149751, 1.188250100686182, 1.214739185445568, 1.2305621551643497, 1.2357796856934937, 1.2307319880924346, 1.2160366681841863, 1.1925792783601337, 1.1614967233655946, 1.1241538647998546, 1.0821138442561093, 1.0371028079880436, 0.9909698625966626, 0.9456432177595253, 0.9030835752431651, 0.8652359006909405, 0.8339807639463578, 0.8110864536321956, 0.7981630617605807, 0.7966196944426707, 0.8076258961830517, 0.8320782793861801, 0.8705732298533089, 0.9233864161161902, 0.9904596688994886, 1.071395620756968, 1.165460309288584, 1.2715937548835392, 1.3884283303690859, 1.5143145500325097, 1.6473537239012492, 1.7854367543917677, 1.9262882006443274, 2.0675146048085367, 2.2066559674899517, 2.34123917918357, 2.468832162824328, 2.5870974608972985, 2.6938440094524245, 2.7870758806946907, 2.865036844655479, 2.9262496971574548, 2.9695494235400997, 2.994109412465411, 2.999460098067586], [2.9922132411047837, 2.9663035211856834, 2.921711392462454, 2.8592920401980635, 2.780238079210345, 2.6860530252772614, 2.5785178308822587, 2.4596512743071504, 2.3316651357381506, 2.1969152160765995, 2.0578493505912165, 1.916953638093725, 1.7766981453291368, 1.639483354835787, 1.5075886024849525, 1.3831236988422013, 1.267984847724911, 1.1638158678865056, 1.0719755923141006, 0.993512167443115, 0.9291448054353728, 0.8792533607121632, 0.8438759116641511, 0.8227143345558247, 0.815147663864038, 0.8202528463619606, 0.8368323197518889, 0.8634476848670911, 0.8984585973363731, 0.9400658835986339, 0.9863577901778443, 1.0353582064660622, 1.0850756615171582, 1.1335518854112285, 1.178908745753685, 1.2193924192250933, 1.2534137354732413, 1.2795837340198295, 1.2967436015814446, 1.303988304044577, 1.3006833905604749, 1.2864746227110953, 1.2612902650192095, 1.2253360596249145, 1.1790830930473595, 1.1232489419606362, 1.0587726533635764, 0.986784268214823, 0.9085697327141711, 0.8255321545880868, 0.7391504501863052, 0.6509364897466599, 0.5623918813442091, 0.47496553803068786, 0.3900131474470466, 0.30875960944563335, 0.23226542639558412, 0.1613979249523172, 0.09680805986441061, 0.03891340314301908, -0.012112240618019982, -0.056342325674520695, -0.09409407665145267, -0.12591811607378317, -0.152581483943992, -0.17504449846091547, -0.19443206858583575, -0.21200021521617465, -0.2290986845066309, -0.24713064114801916, -0.26751050850630687, -0.2916210744019017, -0.32077100461909513, -0.3561539003428905, -0.39881000072473205, -0.449591568511921, -0.5091329066819101, -0.5778258395206604, -0.6558013554112652, -0.7429179541418909, -0.8387570726515287, -0.9426257840287284, -1.0535667797458697, -1.170375459186074, -1.2916237681738938, -1.4156902540467915, -1.5407956431999377, -1.6650431020939045, -1.7864622181195002, -1.9030556356506967, -2.0128472076913493, -2.113930476693574, -2.2045162806594782, -2.2829782930696494, -2.3478953473053403, -2.3980894671018063, -2.4326586225272466, -2.451003353688517, -2.452846548865544, -2.4382458265690086, -2.4075981481373856, -2.36163647461408, -2.30141847419048, -2.2283074797409674, -2.1439460851581393, -2.050222949660012, -1.9492335465293604, -1.8432357427206918, -1.734601224712287, -1.625763890681107, -1.5191664069204442, -1.4172061754426024, -1.3221819786569358, -1.2362425553681178, -1.1613383203333034, -1.099177368226019, -1.0511868037789482, -1.0184803154957374, -1.0018327636351405, -1.001662387729057, -1.0180210587105407, -1.0505928101731112, -1.0987006869881515, -1.161321752244291, -1.2371099000368746, -1.3244259367287945, -1.4213742214186649, -1.5258450016613256, -1.6355614467394053, -1.7481302712191509, -1.8610947587812245, -1.971988942380967, -2.0783916729395244, -2.177979315535434, -2.268575849243494, -2.34819921339642, -2.4151028374466343, -2.4678114114229555, -2.5051500962326325, -2.5262665342286157, -2.5306451965625327, -2.518113790532546, -2.4888416428155415, -2.4433301684106925, -2.3823957255590305, -2.307145339179681, -2.218945945026898, -2.1193879596921117, -2.0102441140423766, -1.893424596505185, -1.7709296351742387, -1.6448007020715258, -1.5170715478101078, -1.389720269843505, -1.2646235826893575, -1.143514394941968, -1.027943707217041, -0.9192477297484454, -0.818520981136675, -0.7265959742227842, -0.6440299251697195, -0.571098741862577, -0.5077983622210064, -0.4538533266097123, -0.40873228590830285, -0.37166997252710127, -0.3416950000808613, -0.317662712581774, -0.2982921794842369, -0.2822063317894155, -0.26797415918833833, -0.2541538407253831, -0.2393356628382611, -0.2221835892880942, -0.20147438710977927, -0.17613328023700098, -0.14526519613578603, -0.10818078820692809, -0.06441655488676422, -0.0137485317636738, 0.04380079832124232, 0.10796255459446807, 0.17822846240710377, 0.2538646254156602, 0.33393170212524875, 0.41731095516440814, 0.5027354873365991, 0.5888258416398648, 0.6741290265506978, 0.7571599358914616, 0.8364440669030351, 0.9105604024261077, 0.9781833143524912, 1.038122366010687, 1.089358940430682, 1.1310786982996308, 1.162698971985589, 1.183890327735235, 1.1945916739212574, 1.1950184553962568, 1.18566364855382, 1.167291454238526, 1.1409237716106242, 1.107819720789013, 1.0694486609213414, 1.027457318752753, 0.9836317965276062, 0.9398553632595844, 0.8980630465990216, 0.8601941308079379, 0.8281437274326765, 0.8037146175249886, 0.7885705668007214, 0.7841922877762771, 0.7918371662630007, 0.812503784935553, 0.8469021660269385, 0.8954305211942872, 0.958159142484834, 1.0348218978546455, 1.1248156120110877, 1.2272074229313519, 1.3407500109223536, 1.4639044052857813, 1.5948698882575776, 1.7316203414763347, 1.8719462211103788, 2.0135012078809322, 2.153852461032204, 2.2905333137416126, 2.421097183830016, 2.5431714395360987, 2.654509956450541, 2.7530431286081734, 2.836924153604035, 2.9045704970890625, 2.954699554068907, 2.986357660376106, 2.998941764225594, 2.992213241104784], [2.976571811140622, 2.938926242562151, 2.883105282612188, 2.8101798668071836, 2.721543019443848, 2.618879016808584, 2.504126066439196, 2.379433380221516, 2.247113650818419, 2.109592048200173, 1.969352933285303, 1.8288855369858164, 1.6906298740657901, 1.5569241516940588, 1.4299548926773944, 1.3117109241211689, 1.2039422854194082, 1.1081249874394195, 1.0254324105665016, 0.95671396647998, 0.9024814711622455, 0.8629034890684887, 0.8378077152206006, 0.8266912679777473, 0.8287385751339424, 0.8428463544497373, 0.8676550211711457, 0.901585703625108, 0.9428819172781728, 0.9896548408543778, 1.0399310577829062, 1.091701574279599, 1.142970902946889, 1.1918050083580929, 1.2363769483844025, 1.2750091110001367, 1.30621103922904, 1.3287119543712782, 1.3414872266727096, 1.3437781996315243, 1.3351049452086414, 1.3152717080029086, 1.2843649824227248, 1.2427443533656026, 1.1910264132366195, 1.1300622417397572, 1.0609090954333342, 0.984797097557635, 0.9030918415586475, 0.8172539210080425, 0.7287964718153253, 0.6392418579604464, 0.5500786483628025, 0.4627200195926117, 0.3784646773061336, 0.29846131965675016, 0.2236775703065006, 0.1548741894966035, 0.09258523197999224, 0.03710466403655483, -0.011520217730940854, -0.05348840127519548, -0.08923782536927753, -0.11943129670411465, -0.14493603386082513, -0.16679738117434328, -0.1862073886146791, -0.20446908916378773, -0.22295741931164886, -0.2430778183198136, -0.26622360549522656, -0.29373327023681817, -0.3268488161229009, -0.3666762775893629, -0.41414947633286164, -0.4699980057083795, -0.5347203270172446, -0.6085627342849638, -0.6915047970724755, -0.7832517277161655, -0.8832339442269703, -0.9906139172825789, -1.1043002039029184, -1.2229683861775544, -1.3450884554520137, -1.4689580151689106, -1.5927405233303125, -1.7145076621648159, -1.832284811449974, -1.9440985159121722, -2.0480247784373105, -2.1422369810350026, -2.225052235448569, -2.294974995096827, -2.350736819033217, -2.3913312654475307, -2.4160430048553563, -2.4244703788156547, -2.4165407855047945, -2.3925184449752375, -2.353004280253491, -2.298927841097926, -2.23153139056445, -2.152346465763799, -2.063163408626424, -1.9659945355677837, -1.863031772386131, -1.7565997186237217, -1.6491052205509384, -1.542984621021409, -1.440649915456588, -1.34443507459795, -1.2565437955887824, -1.1789999133357216, -1.1136016446239982, -1.0618807495227018, -1.0250675803217173, -1.0040628503410887, -0.9994167967791868, -1.0113162371493822, -1.0395798320323142, -1.0836616723795338, -1.1426631121708093, -1.2153525716514153, -1.3001928474120583, -1.3953752878155836, -1.4988600300394257, -1.608421352227997, -1.7216970743943265, -1.836240847671933, -1.9495761055594218, -2.0592504144952213, -2.162888955295027, -2.258245891778243, -2.343252437650809, -2.4160605160156887, -2.475081015665875, -2.5190157818479992, -2.5468826331589907, -2.5580328668477335, -2.5521608978304267, -2.5293058676860127, -2.4898452540827205, -2.4344807037347898, -2.3642164983821305, -2.2803312388706534, -2.1843434929086776, -2.077972293587203, -1.9630934948572265, -1.8416930839953767, -1.715818617429247, -1.5875299835905574, -1.458850703894257, -1.331720960422847, -1.2079534870876047, -1.0891933813270884, -0.9768827878624079, -0.872231277369429, -0.7761925944295571, -0.6894482845482062, -0.6123985335413659, -0.5451603686298835, -0.4875731837700487, -0.4392113667705544, -0.39940362722720407, -0.3672584567043457, -0.3416950000808611, -0.3214784833483053, -0.3052592317089942, -0.29161422532094894, -0.2790900805930428, -0.26624631398389526, -0.25169774352139074, -0.23415491072095063, -0.21246146149101558, -0.18562750751075588, -0.15285809730784458, -0.11357605609030151, -0.06743860197946304, -0.014347309864746766, 0.04554883150629916, 0.11185734280922767, 0.18395304882585767, 0.26099545582362255, 0.3419522505922496, 0.4256282995459224, 0.5106993816074268, 0.5957497634426019, 0.6793126232004102, 0.7599122518561771, 0.836106911536238, 0.9065312091177603, 0.9699368515237811, 1.0252306863120293, 1.0715089964969904, 1.1080871104481558, 1.134523503903661, 1.1506377087441533, 1.1565214987600796, 1.1525429923340413, 1.1393434915040368, 1.1178270617750135, 1.0891430426637025, 1.0546618606269138, 1.0159446891581434, 0.9747076610662931, 0.9327814812136215, 0.8920674106414072, 0.8544906919125871, 0.821952558098218, 0.7962820122254871, 0.7791885789858, 0.7722172155966638, 0.7767065241894964, 0.793751334961354, 0.8241706293002741, 0.8684816475611492, 0.9268808801345979, 0.9992324764579962, 1.0850644286607611, 1.183572698965232, 1.2936332673762014, 1.4138218833171028, 1.5424411164559502, 1.6775541226557478, 1.8170243752128807, 1.9585604634180969, 2.0997649336667306, 2.238186046015879, 2.3713712437997514, 2.4969210875709695, 2.6125423884278467, 2.7160992901696166, 2.8056610943966382, 2.879545696600932, 2.9363576027139078, 2.975019622059028, 2.9947974811454947, 2.99531676964194, 2.976571811140623], [2.952668141750426, 2.903599376065387, 2.837004318533421, 2.75416060644511, 2.65664990815037, 2.5463230389512983, 2.4252590996110532, 2.2957195966101778, 2.1600986209388884, 2.0208702538233645, 1.8805344311403085, 1.7415625318645505, 1.6063439589366566, 1.4771349533978106, 1.3560108252333085, 1.2448226985407191, 1.1451597565356493, 1.0583178363109575, 0.9852750675298207, 0.9266750772049253, 0.8828180986346211, 0.8536601309609096, 0.8388201013895353, 0.8375947896361541, 0.8489810883446621, 0.8717049986015569, 0.9042566004960872, 0.9449300988130743, 0.9918679267723199, 1.0431077990570397, 1.0966315413793835, 1.1504144890005943, 1.2024742417189405, 1.2509175878798713, 1.293984464228122, 1.3300879004656643, 1.3578490050722272, 1.3761261795240414, 1.384037898186843, 1.380978557057539, 1.3666270719981601, 1.3409480916799676, 1.3041858775015354, 1.256851087577533, 1.199700879894733, 1.133712916458972, 1.06005400156203, 0.9800442194253352, 0.8951175461594898, 0.8067799955142013, 0.7165664152165524, 0.6259970794264609, 0.5365352223159223, 0.44954662807798834, 0.36626233459952795, 0.2877454231082226, 0.21486275652142847, 0.14826239779330389, 0.08835728963474004, 0.03531561238884838, -0.010941938229415802, -0.050737892928261454, -0.08462689210852625, -0.11337801188796054, -0.13795100574785815, -0.15946709414597343, -0.17917507775279864, -0.19841367347196845, -0.21857107295160236, -0.24104279831064346, -0.2671889773630806, -0.2982921794842367, -0.3355169429095044, -0.3798720849047022, -0.43217681884636483, -0.493031608454553, -0.5627945715509064, -0.6415641067001333, -0.7291682593987996, -0.8251611740162128, -0.9288267977346891, -1.0391898177937369, -1.1550336280599671, -1.2749249399854954, -1.3972444809459548, -1.5202230641157797, -1.641982172471984, -1.7605780788231034, -1.8740484270299442, -1.9804601293187716, -2.0779573926319292, -2.164808674459412, -2.2394513859607272, -2.3005332070899454, -2.346948953813329, -2.377872039583095, -2.3927796995607813, -2.391471293619522, -2.3740791693141143, -2.3410717447638896, -2.2932486593736727, -2.2317280329123808, -2.1579260659427937, -2.0735294022095028, -1.9804608517137898, -1.8808392374301441, -1.776934274877174, -1.6711175184114238, -1.5658105080553943, -1.4634313233941738, -1.3663407947376014, -1.2767896352163692, -1.1968677403722676, -1.1284568544751177, -1.0731877263559322, -1.032402773805435, -1.0071251470403244, -0.99803493148669, -1.0054530618062374, -1.029333336776739, -1.069262732758987, -1.1244700167001407, -1.1938424627213033, -1.2759502841027877, -1.3690782095876943, -1.4712634638181836, -1.5803392605063113, -1.6939827872907296, -1.8097665562810397, -1.925211916576104, -2.037843476426145, -2.1452431643416943, -2.245102670744986, -2.3352730543688383, -2.413810369449943, -2.4790162690377633, -2.529472663976766, -2.5640696632389877, -2.5820261856742976, -2.582902811851848, -2.5666066330905553, -2.5333880483875153, -2.483829653999401, -2.4188275601605285, -2.339565650194016, -2.247483464680925, -2.1442385433262356, -2.031664186067942, -1.911723699711474, -1.7864622744353602, -1.6579576840683778, -1.528271023955599, -1.3993986901188447, -1.2732267636283823, -1.1514888957240659, -1.0357286940489683, -0.9272674908409857, -0.827178233121273, -0.7362660763978384, -0.6550560911757988, -0.5837883099734557, -0.5224201561485371, -0.47063610931570926, -0.42786428015170813, -0.39329939448209156, -0.3659315270314494, -0.344579783061607, -0.32793000484301066, -0.3145754824966419, -0.3030595775983046, -0.29191912478221677, -0.27972746243996743, -0.26513595877801294, -0.24691294352956306, -0.22397902734774316, -0.19543788847453045, -0.1606017271745102, -0.1190107295500239, -0.07044604011405711, -0.014935912872648041, 0.047245110672290404, 0.11558396578480849, 0.18934355868876618, 0.26758360233758555, 0.3491872393440212, 0.43289274577581305, 0.517329475688153, 0.6010570938798752, 0.6826070562961922, 0.7605252360139028, 0.8334145594247, 0.8999765129598969, 0.9590504056257436, 1.0096493261581398, 1.0509918144537922, 1.0825283730975872, 1.1039620736499167, 1.1152626606759695, 1.1166737205896307, 1.1087126581447229, 1.09216340643184, 1.0680619819367831, 1.03767517991731, 1.002472882430478, 0.9640946173222007, 0.9243111571702499, 0.8849820787236761, 0.8480103124455804, 0.8152947955375847, 0.788682398123642, 0.7699203195976188, 0.7606101497129928, 0.7621647567711846, 0.7757691039475296, 0.8023460058043717, 0.8425277224945823, 0.8966341518102058, 0.9646582224061547, 1.046258919044368, 1.140762186772212, 1.2471697700758841, 1.3641758499210872, 1.490191150961928, 1.623374007764826, 1.7616677071889626, 1.9028432683397103, 2.0445466856316066, 2.184349547846794, 2.3198018594692096, 2.4484858321964964, 2.5680693858700745, 2.6763580998812295, 2.771344388421765, 2.8512527350173467, 2.914579912145158, 2.9601292282325993, 2.987037984157684, 2.9947974811454947, 2.9832650978089545, 2.9526681417504275], [2.92070446879377, 2.8606218029715422, 2.7837985352431827, 2.6917082074035092, 2.5861077704159188, 2.468998948110029, 2.342584180624905, 2.209218179963404, 2.0713562326270867, 1.931500459473669, 1.7921452888752083, 1.6557234148673645, 1.5245534969235437, 1.4007908126696509, 1.286382000423341, 1.183024926756528, 1.092134587867387, 1.0148158055376595, 0.951843312497552, 0.90364964221397, 0.8703210488818607, 0.8516014893816831, 0.8469045049258569, 0.8553326508039153, 0.875703942674594, 0.9065846216292114, 0.9463273918032209, 0.9931141572341395, 1.0450021820120716, 1.099972521992485, 1.1559795292187884, 1.211000212802614, 1.2630822526617358, 1.3103895048050644, 1.3512439076331098, 1.384162796139361, 1.4078907524453246, 1.421425263678145, 1.4240356181884375, 1.4152746444654432, 1.3949830794724674, 1.363286539917668, 1.320585256514218, 1.2675369129059035, 1.2050331031085317, 1.1341700797582075, 1.0562146062307494, 0.9725658453176245, 0.8847143126641845, 0.7941989922557461, 0.702563752202976, 0.611314210964431, 0.521876186716395, 0.4355568163400592, 0.35350935666815037, 0.27670258113384977, 0.20589556235373774, 0.14161848859209814, 0.08416000313406043, 0.03356138438639436, -0.010382294619702187, -0.048114071178952784, -0.08030028745105586, -0.10780947515400792, -0.13168549610368802, -0.1531156549210584, -0.17339463253224288, -0.19388519969757648, -0.21597675590154153, -0.24104279831064335, -0.2703984566270314, -0.30525923170899405, -0.346702048703919, -0.3956296797878499, -0.45273950879011277, -0.5184975020483849, -0.593118119470401, -0.676550750222245, -0.7684730924560458, -0.8682917201620952, -0.9751498970030084, -1.0879425114630341, -1.205337824491511, -1.3258055446540755, -1.447650581079167, -1.5690516753756092, -1.6881039839911143, -1.802864575496737, -1.9113997257733542, -2.011832840167259, -2.102391806814456, -2.181454590226624, -2.2475919088669305, -2.2996059040604226, -2.3365637986994643, -2.357825660649682, -2.36306552473308, -2.352285285293133, -2.3258209447805784, -2.2843409882986485, -2.228836845090302, -2.160605590842953, -2.0812252346786, -1.9925231171008713, -1.8965381154750485, -1.7954775076025502, -1.691669477790974, -1.5875123601787309, -1.485421798184651, -1.387777054695605, -1.2968677335500245, -1.2148421683249377, -1.1436586994382472, -1.0850409959352594, -1.0404384855651594, -1.0109928380877222, -0.997511305039373, -1.0004475578537133, -1.0198904891827216, -1.0555612537954493, -1.1068186301187473, -1.1726725860759946, -1.2518057381750587, -1.3426022055302915, -1.4431831852287975, -1.5514484164278204, -1.665122561659803, -1.7818054183919043, -1.8990247847308876, -2.0142907424288703, -2.1251500894824202, -2.229239654344525, -2.324337254054564, -2.4084091186565177, -2.4796526926100473, -2.5365338383042735, -2.577817604422096, -2.6025918793722393, -2.6102834234216368, -2.600665958252444, -2.5738601848858487, -2.5303257955411107, -2.4708457372643764, -2.3965031703656754, -2.3086517383249947, -2.208879923643925, -2.098970402300735, -1.980855424678599, -1.8565693403171486, -1.7281994454662353, -1.5978363647702352, -1.4675251807801473, -1.3392184974227535, -1.2147325668339173, -1.0957075245921954, -0.9835726685550273, -0.8795175840167494, -0.7844697661450516, -0.6990792234510228, -0.6237103676241376, -0.5584413099036474, -0.5030704969061938, -0.4571304341719853, -0.41990806824058374, -0.39047123224418584, -0.36770040993388764, -0.35032494245370255, -0.33696269427469877, -0.3261621121498649, -0.316445555762135, -0.3063527522368122, -0.2944832294773731, -0.27953661522619494, -0.2603497489832949, -0.23592964086105697, -0.20548142286612311, -0.16843057112307844, -0.12443882878940822, -0.07341342500304675, -0.01550936093958488, 0.04887528452989668, 0.11911089460452126, 0.1943543858431556, 0.27357332625687075, 0.3555754571018537, 0.4390428333517763, 0.522569675982703, 0.6047029305345908, 0.6839844534433057, 0.7589937022412862, 0.828389789085588, 0.8909517696480472, 0.9456160809168481, 0.9915101109065655, 1.0279809789453036, 1.0546187247313692, 1.0712732447535076, 1.0780644724447321, 1.0753854696445582, 1.063898277288992, 1.0445225582061688, 1.0184172498182213, 0.9869556247797513, 0.9516943285710262, 0.9143371204836704, 0.8766941842922618, 0.840637993632311, 0.808056811658902, 0.7808069724936921, 0.7606651314925122, 0.7492816813975038, 0.7481365116250498, 0.7584982386747372, 0.781387958049811, 0.8175484639875903, 0.8674197552033746, 0.931121495849008, 1.0084429345989014, 1.0988406052599609, 1.2014439439518516, 1.315068765343445, 1.4382383483968022, 1.5692116952950659, 1.7060183503293842, 1.846499002870247, 1.988350954187478, 2.1291774054017725, 2.2665394263101843, 2.3980093946788106, 2.5212246546192625, 2.633940131928747, 2.7340786641004176, 2.8197778526770843, 2.889432324560195, 2.9417303949200457, 2.9756842549364655, 2.9906529595831515, 2.986357660376106, 2.9628887113237865, 2.9207044687937698], [2.8809512194075966, 2.810357132996567, 2.723938077744003, 2.62335104523831, 2.510513424646415, 2.3875609410828478, 2.2568007767062057, 2.1206609714083697, 1.9816372866445269, 1.8422387740515838, 1.7049333186301134, 1.5720944237666976, 1.4459504723456866, 1.3285376354862664, 1.221657509612795, 1.1268404458817072, 1.0453153963357225, 0.9779869419847608, 0.9254199932453139, 0.8878324671062663, 0.8650960525998524, 0.8567449813701158, 0.8619925281174119, 0.8797547811490763, 0.9086810506838734, 0.9471901261386725, 0.9935114571608384, 1.04573021995052, 1.1018351431545754, 1.1597679083730996, 1.217472910468729, 1.2729461630469334, 1.3242821645772536, 1.369717599805129, 1.4076708377979597, 1.436776299934658, 1.455912905521402, 1.464225956083576, 1.461141987867104, 1.4463763014366093, 1.4199330629770879, 1.3820980593356562, 1.33342437329352, 1.2747114224330436, 1.206977969856768, 1.131429863829083, 1.0494233924613412, 0.9624252456634579, 0.8719701571356189, 0.7796173522132137, 0.686906951639968, 0.5953174762856208, 0.5062255636386834, 0.42086894451658907, 0.34031363947608995, 0.26542622117367787, 0.1968518543237898, 0.1349986723712316, 0.08002888342104342, 0.03185682159189095, -0.009846021739979807, -0.04563913474656181, -0.07629461643007948, -0.10277279884281824, -0.12619251397507988, -0.14779679954950065, -0.16891495813525906, -0.19092198077790126, -0.21519641725765196, -0.24307781831981337, -0.27582488964019936, -0.31457548249664175, -0.36030950244980475, -0.4138157458557015, -0.4756635765024555, -0.5461802335066228, -0.6254344198387646, -0.7132266620154651, -0.8090867595709098, -0.9122784622166186, -1.0218113276506766, -1.1364595284411774, -1.2547871969328306, -1.375179727244057, -1.4958802974355034, -1.6150307368019423, -1.7307157464918892, -1.841009389288999, -1.944022698791175, -2.0379512211275412, -2.121121294784207, -2.1920338963568855, -2.2494049316597633, -2.292200931411499, -2.319669216803224, -2.331361730084159, -2.327151875737112, -2.3072438851988037, -2.2721743983208365, -2.2228061434501774, -2.160313790498893, -2.086162242932823, -2.002077820511886, -1.9100129602656957, -1.8121052242342603, -1.710631544945966, -1.607958759893651, -1.506491581396057, -1.4086192158005302, -1.3166618842728397, -1.232818505428431, -1.159116777525106, -1.0973668453503875, -1.049119655525299, -1.0156309956479705, -0.9978320801138435, -0.996307391772505, -1.0112803175313672, -1.0426069317400246, -1.089778088159267, -1.1519297842256897, -1.227861564958259, -1.316062542993048, -1.4147444305183121, -1.5218808127085517, -1.6352517446613117, -1.7524926284072508, -1.8711462263322023, -1.988716594741376, -2.1027236780548786, -2.2107572912750983, -2.3105292361894345, -2.3999223447949047, -2.4770353204429556, -2.5402223512831954, -2.588126599152227, -2.619706816929361, -2.6342565148677646, -2.631415277383114, -2.6111720217930583, -2.5738601848858482, -2.520145017191565, -2.4510033536885185, -2.367696408789797, -2.2717363084581828, -2.164847219185137, -2.0489220587893207, -1.9259758745317543, -1.7980970475123585, -1.6673975269853256, -1.5359633131012886, -1.405806391385274, -1.27881927746804, -1.1567332574132596, -1.0410813093331273, -0.9331665684218151, -0.8340370532085224, -0.7444672093971856, -0.6649466531922833, -0.5956763128985713, -0.5365719804221798, -0.4872750977758643, -0.4471704224619806, -0.4154100441901777, -0.3909430680457777, -0.37255013986187707, -0.3588818716089763, -0.3485001310034365, -0.33992109253878716, -0.33165890837995005, -0.3222688479372687, -0.3103887746299116, -0.29477787679601375, -0.2743516456277837, -0.2482121944329174, -0.21567313783982986, -0.17627839359115208, -0.12981442963264633, -0.07631565122751344, -0.016062802435422786, 0.05042556107062057, 0.12240828985459694, 0.1989431364238746, 0.2789139518067401, 0.36106285665281423, 0.44402652974997175, 0.5263756480253672, 0.6066564279788902, 0.6834331612386068, 0.7553306080070704, 0.8210751123497054, 0.879533332594372, 0.9297475378632363, 0.9709665065264274, 1.0026711720524486, 1.0245942936039467, 1.0367335794987607, 1.0393578575552491, 1.0330060632110039, 1.0184789997076376, 0.9968240099607527, 0.9693128823175491, 0.937413487638362, 0.9027558085917781, 0.8670931695813308, 0.8322596035698024, 0.8001243969653267, 0.7725449329772012, 0.7513190053697791, 0.7381377969584912, 0.7345407098434097, 0.7418731973445809, 0.7612486817095361, 0.7935155484480749, 0.839230089835585, 0.8986361295661609, 0.9716519011412862, 1.0578645782348681, 1.1565326702459064, 1.266596305075132, 1.3866952285433052, 1.5151941605525623, 1.6502149667542545, 1.7896749356145376, 1.9313302985515184, 2.072823999041243, 2.2117366085435024, 2.3456392054937574, 2.4721469805074774, 2.5889723077156597, 2.6939760294284802, 2.78521573899325, 2.860989913911572, 2.91987684642119, 2.9607674395555867, 2.9828910802608624, 2.9858339640075346, 2.9695494235400997, 2.934360003636526, 2.880951219407599], [2.8337447240702605, 2.7532306279934695, 2.6579293925934886, 2.549667452473395, 2.430506433213895, 2.3026980202603187, 2.1686346542695363, 2.030797205002039, 1.8917008458725018, 1.7538403918071477, 1.6196363731371588, 1.4913830976698115, 1.371199902359289, 1.2609867164215556, 1.1623849512820856, 1.076744602048218, 1.0050982934869341, 0.9481428345031702, 0.906228663010665, 0.8793573723405782, 0.8671873156214799, 0.8690470906565283, 0.8839565194605928, 0.910654558397779, 0.9476334111164342, 0.9931779711875945, 1.045409598024981, 1.1023331312626017, 1.161885977631357, 1.2219880621723826, 1.2805914232977582, 1.3357282489636302, 1.3855561985174198, 1.4283999303501023, 1.4627878573600064, 1.4874832778015652, 1.5015091751551686, 1.5041661435150502, 1.4950430705445374, 1.474020393879401, 1.4412659343615795, 1.3972234959673457, 1.3425946031017233, 1.2783139165618524, 1.2055190256866892, 1.1255154521383208, 1.0397378169953544, 0.9497082145245823, 0.8569929008963608, 0.76315844265963, 0.6697284771450748, 0.5781422150040164, 0.48971576443601106, 0.40560727864954244, 0.3267868247619203, 0.254011746335581, 0.1878081462938415, 0.12845895577143385, 0.07599888163781368, 0.030216345377902926, -0.009337656701477353, -0.04333402271322777, -0.07264376883502144, -0.09831059551510558, -0.12151853247644458, -0.1435555279545524, -0.16577395463432132, -0.18954908688587468, -0.2162366590379681, -0.24713064114801886, -0.28342236632380463, -0.32616211214986474, -0.3762241789310296, -0.43427642076003425, -0.50075507399729, -0.5758455943945513, -0.6594700621315912, -0.7512815472699838, -0.850665650741706, -0.9567492524377793, -1.068416312859876, -1.1843303928103366, -1.3029633813169759, -1.422629759828661, -1.5415255847903933, -1.6577712447293493, -1.7694569451815148, -1.874689797814482, -1.9716413409696165, -2.0585942988779933, -2.133987396597769, -2.196457087133143, -2.2448751153459963, -2.278380938562572, -2.296408143932335, -2.2987041447141743, -2.2853425982944953, -2.2567281639627947, -2.213593403993276, -2.1569878228507218, -2.088259231648326, -2.0090278135913096, -1.9211534463811157, -1.826697004967064, -1.7278765184576321, -1.6270191846977025, -1.526510351738138, -1.4287406545142247, -1.3360525455035577, -1.2506874786476359, -1.1747349958253284, -1.1100849248390678, -1.0583838281415754, -1.0209967440396919, -0.9989751391945821, -0.9930318458515667, -1.0035235928907347, -1.0304415604709003, -1.0734101980948039, -1.1316943499661807, -1.204214534303044, -1.2895700296122976, -1.3860692355299822, -1.4917666031987213, -1.604505274487404, -1.7219644344403642, -1.8417102704485753, -1.961249347449281, -2.078083153013809, -2.1897625408023838, -2.293940806139313, -2.3884241632300696, -2.471218458895701, -2.5405710510073316, -2.5950068987489296, -2.633358053478861, -2.6547858998056664, -2.658795672580861, -2.645242962511947, -2.61433211642209, -2.5666066330905553, -2.5029318473305704, -2.4244703788156565, -2.3326509936710336, -2.2291316818346774, -2.1157578879092993, -1.9945169444252313, -1.8674898414549308, -1.7368015233532472, -1.604570930736147, -1.4728620030765327, -1.343636824657331, -1.21871203498648, -1.0997195357690943, -0.9880724124465977, -0.8849368520654789, -0.7912106842871063, -0.7075090026091252, -0.6341571426111731, -0.5711911077876329, -0.5183653459524508, -0.4751675949816909, -0.44084034039171816, -0.4144082633193342, -0.3947109099424775, -0.3804396859056991, -0.37017817503472006, -0.3624447030937516, -0.3557360164633089, -0.3485709236044824, -0.33953275451184867, -0.3273095297882547, -0.3107307955178392, -0.28880017108148676, -0.26072277210219036, -0.22592680687516956, -0.18407879844947111, -0.13509205206411737, -0.0791281646403265, -0.016591554994671836, 0.0518828242534194, 0.12544825407913227, 0.203070987524577, 0.2835602948783811, 0.3656030121136253, 0.4478016706437238, 0.5287151915704427, 0.6069010587404267, 0.6809578438636097, 0.7495669447460459, 0.8115324146921667, 0.8658178069432473, 0.911579031519736, 0.948192321206864, 0.975276526194359, 0.9927090999888608, 1.0006352990831084, 0.9994702914844291, 0.9898940502442954, 0.9728390930414442, 0.9494713129975766, 0.9211643246038017, 0.8894679173914193, 0.8560713645166796, 0.8227624698179468, 0.7913833516626613, 0.7637840520831372, 0.741775122963425, 0.7270803757111708, 0.7212909859654664, 0.7258221202250456, 0.7418731973445806, 0.7703928158829167, 0.8120492702397549, 0.8672074469826382, 0.9359127409302619, 1.01788246211805, 1.112505023845357, 1.2188470130264668, 1.3356680516851709, 1.4614431673854495, 1.5943922053946444, 1.7325156410085505, 1.873635991053737, 2.0154438830847337, 2.1555477227170527, 2.2915258068397506, 2.4209796654725615, 2.5415873794314767, 2.65115561568433, 2.7476691475098716, 2.8293366817663563, 2.894631899438524, 2.9423287261690834, 2.971529984039803, 2.981688731202419, 2.972621768314024, 2.9445149759269222, 2.8979203405235894, 2.833744724070263], [2.779484371093498, 2.689725604044614, 2.5863309431372814, 2.4712808256457603, 2.346763691469455, 2.21512816435351, 2.078831738606336, 1.9403871688720273, 1.8023078132966466, 1.667053203054873, 1.5369761031525246, 1.4142722909177776, 1.3009342106114534, 1.1987095668179457, 1.1090657980958305, 1.0331612287635212, 0.9718235342095701, 0.9255359777467944, 0.8944316891315669, 0.8782960610536479, 0.8765771449152723, 0.8884037358295902, 0.9126106536498177, 0.9477705564521918, 0.9922314693768733, 1.044159078797127, 1.1015827326397614, 1.162444004927575, 1.2246466282094304, 1.286106572734251, 1.34480105652589, 1.3988153056966315, 1.4463859484282844, 1.4859400173695159, 1.5161286513930192, 1.5358547257621593, 1.5442937962729757, 1.5409079139137563, 1.5254520477208717, 1.4979730402626583, 1.4588012078807941, 1.4085348817744947, 1.3480183616450743, 1.2783139165618524, 1.2006686139261549, 1.1164768832851264, 1.0272398241840037, 0.9345223437389547, 0.8399092583114799, 0.7449615134175593, 0.6511736663858715, 0.5599337376019544, 0.47248646948040174, 0.38990093933813696, 0.3130433554990767, 0.24255572824179822, 0.17884095212615075, 0.12205466775439466, 0.07210409342305392, 0.028653834915524586, -0.008861500502458371, -0.04121823736982779, -0.06937863248856324, -0.09446061743019252, -0.11770309560626122, -0.14042772321310434, -0.16399819634036805, -0.1897781333250651, -0.21908868032631387, -0.2531669780802099, -0.29312660858720696, -0.33992109253878705, -0.3943114327830895, -0.45683859793259635, -0.5278017158517783, -0.6072426023353297, -0.6949370894137802, -0.7903934444365157, -0.8928579897344664, -1.0013278478170438, -1.114570553366741, -1.2311500953961352, -1.3494587853240856, -1.4677541936608376, -1.5842002633580863, -1.6969115951204643, -1.803999811988484, -1.903620849576502, -1.99402198609827, -2.0735874236397462, -2.1408812592118225, -2.1946867403599133, -2.2340407842214085, -2.25826284890676, -2.2669773792890404, -2.2601292024896846, -2.237991417811307, -2.2011655074453857, -2.1505735835181112, -2.0874428792756823, -2.013282782711537, -1.9298548949943686, -1.839136769110132, -1.7432801418877033, -1.6445646111099579, -1.5453478252604842, -1.4480133437132563, -1.354917387557349, -1.268335734161239, -1.1904120111453416, -1.123108617515047, -1.0681614419277128, -1.0270394617774137, -1.0009101940353697, -0.9906118322874509, -0.9966327474548827, -1.019098856067234, -1.057769173886483, -1.112039678675061, -1.180955408673978, -1.2632305277060374, -1.3572758985037392, -1.4612335274886101, -1.5730170811377122, -1.6903575302307108, -1.8108528571715068, -1.9320206661606631, -2.0513524685663636, -2.1663683780263736, -2.274670942507007, -2.373996863898343, -2.4622654091358087, -2.5376223989698, -2.5984787693188234, -2.6435428329453994, -2.671845522713105, -2.682758068136412, -2.6760017401331795, -2.6516494903348473, -2.610119506309017, -2.552160897830426, -2.478831917164199, -2.3914712936195217, -2.2916634250795203, -2.1811983128745256, -2.06202724777218, -1.9362153510945834, -1.8058921437531894, -1.6732013557107415, -1.540251198152327, -1.4090663003324453, -1.2815424632628858, -1.1594053044483048, -1.0441737637855348, -0.937129313187066, -0.839291564710589, -0.7514008077127299, -0.6739078289340767, -0.6069711848996205, -0.5504619082062424, -0.5039754428606701, -0.46685042347601985, -0.43819374331990746, -0.4169112011475324, -0.40174288028687183, -0.3913022989357627, -0.38411828089231653, -0.37867843315576966, -0.3734730825106938, -0.36703851813415833, -0.35799841149892436, -0.345102337707034, -0.3272604024805066, -0.3035730842810333, -0.2733555287206928, -0.23615567929226491, -0.1917657907432106, -0.14022704500989966, -0.08182717010533672, -0.017091145131417528, 0.05323474497234758, 0.12820506780518817, 0.20670301565707697, 0.2874730453069133, 0.36915751171464445, 0.4503363166328001, 0.5295685130208827, 0.6054347531322611, 0.6765794436234005, 0.7417514756574883, 0.7998424316532746, 0.8499212322480276, 0.8912642756713557, 0.9233802348611145, 0.9460288124712126, 0.9592329070523097, 0.9632838112935251, 0.9587392410905603, 0.9464141778825401, 0.9273646915531017, 0.9028650925602887, 0.8743789352627082, 0.8435245552588309, 0.8120359678675587, 0.7817200789733877, 0.7544112601586873, 0.7319244147476397, 0.7160077081337886, 0.708296153292884, 0.710267230157709, 0.7231996757557909, 0.7481365116250491, 0.7858532776820046, 0.8368323197518883, 0.901243834327389, 0.9789342122956782, 1.0694220473138691, 1.1719019885354205, 1.2852564260641561, 1.4080748055503252, 1.5386801804834456, 1.6751624316261615, 1.8154174171122825, 1.957191168125156, 2.0981281174829105, 2.2358222450796994, 2.367869947567907, 2.491923391863229, 2.605743094253772, 2.7072484796015908, 2.7945652180975395, 2.86606820927892, 2.920419182837209, 2.956598010741618, 2.9739269723762516, 2.9720873801782397, 2.9511281536567733, 2.9114661202915983, 2.853878018024046, 2.7794843710934978], [2.718629227616586, 2.6203793423889628, 2.509748484656455, 2.388854351088727, 2.25999370090228, 2.12559225396921, 1.988151803019404, 1.850195772835008, 1.7142144944233666, 1.5826114666832594, 1.4576518519644797, 1.3414143958287565, 1.2357478766499554, 1.142233079541822, 1.0621511542171822, 0.9964590610873105, 0.9457726380241201, 0.9103576359535115, 0.8901288793452297, 0.8846575124192111, 0.8931860982764583, 0.9146511509121553, 0.9477125037436988, 0.9907887571735884, 1.0420979057114506, 1.0997021257276727, 1.1615556108677054, 1.2255542757537465, 1.2895861113853868, 1.351580968445395, 1.4095585676008238, 1.4616735881987497, 1.5062567670998182, 1.5418510456899932, 1.5672419326424876, 1.5814813994783639, 1.5839047916198996, 1.574140415276281, 1.5521116456889765, 1.518031590359282, 1.4723905271859563, 1.4159365173147145, 1.3496497614720164, 1.274711422433044, 1.1924677712534948, 1.104390627651998, 1.0120351527018794, 0.9169961126451083, 0.8208637647276809, 0.7251805187425964, 0.6313995014575283, 0.5408460960376884, 0.45468344640352676, 0.37388280932014684, 0.29919950765651504, 0.23115508998931028, 0.1700261383410789, 0.11583999149471161, 0.06837747044747325, 0.02718250975031186, -0.008421581639829688, -0.03930967921777104, -0.06652683192168701, -0.09125543714481275, -0.11477848368695652, -0.1384398479686172, -0.16360270697210577, -0.1916071822589521, -0.2237283517320351, -0.26113575897446656, -0.30485551414963685, -0.35573601646330866, -0.414418237653818, -0.4813113911450065, -0.5565746752370831, -0.6401056244344707, -0.731535434585507, -0.8302314491666967, -0.9353068102690616, -1.0456370932654546, -1.159883563411551, -1.276522520328535, -1.3938800367968487, -1.5101712556113218, -1.623543286047388, -1.732120642899768, -1.83405209862878, -1.9275577747857016, -2.010975283791988, -2.08280374679285, -2.141744557429143, -2.186737833971989, -2.2169936016299063, -2.232016870586095, -2.2316259204597957, -2.2159632648772694, -2.1854989467010895, -2.1410260008631106, -2.0836481130933553, -2.014759694417158, -1.9360187783737608, -1.8493133258594856, -1.7567216869016171, -1.660468115435834, -1.5628743586264766, -1.4663084432918623, -1.3731318560272063, -1.2856463587692952, -1.206041696639744, -1.1363454394959873, -1.0783761530193006, -1.033701020427064, -1.0035989337808309, -0.989029946814639, -0.9906118322874504, -1.0086043196668002, -1.0429014075276422, -1.09303195380273, -1.1581685505950476, -1.2371444934351088, -1.3284784624254315, -1.4304063493444994, -1.5409194949467226, -1.6578084485256603, -1.7787112310062845, -1.9011649765759644, -2.02265974872986, -2.1406932765066617, -2.2528253368259428, -2.3567305196688273, -2.4502481540777676, -2.531428243552734, -2.5985723576360495, -2.6502685498769756, -2.6854195179065425, -2.7032633854494583, -2.703386664719968, -2.6857291464073936, -2.650580658727444, -2.598569832041624, -2.5306451965625323, -2.448049123007, -2.352285285293137, -2.245080476392628, -2.1283417395692266, -2.004109884302744, -1.8745105366587254, -1.7417039258223632, -1.6078346307825009, -1.4749825032765502, -1.3451159453821258, -1.2200486535973551, -1.1014008476304693, -0.9905658838283105, -0.8886830132262832, -0.7966168861428959, -0.7149442330553961, -0.6439479695060356, -0.5836187855616517, -0.5336640925629281, -0.4935240162384997, -0.46239395029335195, -0.43925302265537486, -0.4228976816881523, -0.4119794854278423, -0.40504607633044504, -0.4005842495782404, -0.3970639764873153, -0.39298222707606717, -0.38690544776257496, -0.3775095910845759, -0.36361666317991503, -0.3442268497293792, -0.3185453996959357, -0.2860035854510419, -0.24627321420184994, -0.19927433503916192, -0.1451759641060611, -0.08438983281499553, -0.01755734608703587, 0.054469885366371894, 0.1306554071411691, 0.20980849221986203, 0.29061909945317166, 0.37169628278081773, 0.4516090234651923, 0.5289283928910838, 0.6022699167633493, 0.6703350037652612, 0.7319503231464272, 0.7861040657793159, 0.8319781007239169, 0.8689751423451094, 0.8967401689672675, 0.9151754797758488, 0.9244489385346945, 0.9249951266184515, 0.9175093094909857, 0.9029343055207846, 0.8824405292566134, 0.8573996583633543, 0.8293525398587245, 0.7999721028738572, 0.7710221780263208, 0.7443132342460917, 0.7216561296820667, 0.7048150319073426, 0.6954606924776444, 0.6951252611365353, 0.7051597954976608, 0.7266955635025254, 0.7606101497129918, 0.8074992646040408, 0.8676550211711452, 0.941051288631251, 1.0273365625472204, 1.125834608516058, 1.2355529471063333, 1.3551990556740736, 1.483203972768466, 1.6177528077563372, 1.7568214865842318, 1.8982189085261316, 2.039633552221621, 2.1786834557079784, 2.3129684073453585, 2.4401231247512944, 2.557870168638093, 2.6640713385961594, 2.7567763284563913, 2.834267479213599, 2.8950995561869703, 2.938133592021189, 2.9625639755343833, 2.9679381249589563, 2.95416825896265, 2.9215349657417544, 2.8706824649075804, 2.8026056541156312, 2.7186292276165895], [2.6516941556906026, 2.54577854377966, 2.4288299394037094, 2.303085394075447, 2.1709305748964325, 2.0348478034247264, 1.8973620407969392, 1.7609860769135213, 1.628166198593006, 1.5012295979923278, 1.3823347386327078, 1.2734258231637743, 1.176192406357262, 1.0920350712314357, 1.0220379387624678, 0.9669486159660428, 0.9271660073004752, 0.9027362247631708, 0.8933566373694888, 0.8983879056801264, 0.9168736564439651, 0.9475672708955339, 0.9889650922066767, 1.0393452071179132, 1.0968108275039608, 1.15933719266869, 1.2248208350209675, 1.2911300022922108, 1.3561550097461064, 1.4178573062905957, 1.4743160786757574, 1.5237712869563278, 1.5646621203142128, 1.5956599827119204, 1.6156952596200242, 1.6239772766442346, 1.620007034251131, 1.6035824856032181, 1.5747963121864352, 1.5340263397588576, 1.4819189204865084, 1.4193657814020562, 1.347475000201798, 1.2675369129059035, 1.1809858805086435, 1.0893589404306832, 0.9942524409499125, 0.897277801088805, 0.8000175536388667, 0.7039828148006914, 0.6105732807432511, 0.5210407803961062, 0.43645731683657446, 0.3576884092238107, 0.28537240645139456, 0.21990628613658084, 0.16143828225199539, 0.10986750596571467, 0.06485054162776073, 0.025814817958944518, -0.008021622026234708, -0.037624495522656114, -0.06411249465764299, -0.0887221719345408, -0.1127694402587697, -0.13760872054518286, -0.16459083254855103, -0.19502075910590103, -0.2301164195355645, -0.2709695643385089, -0.31850985116264724, -0.3734730825106936, -0.4363744808755782, -0.5074877494926223, -0.5868305198968954, -0.6741566246543286, -0.768955459085683, -0.8704585139136067, -0.977652976115458, -1.0893021125163602, -1.2039719744249562, -1.3200637963613568, -1.4358513118469605, -1.5495220781420789, -1.6592217930834257, -1.7631005035907714, -1.8593595491586157, -1.9462980562232295, -2.0223578014808283, -2.086165294072995, -2.136569987356166, -2.172677619314333, -2.19387779445015, -2.1998650564536066, -2.1906528567830135, -2.166579995694444, -2.128309295022549, -2.0768184516550843, -2.013383212482923, -1.9395532009085605, -1.857120907074055, -1.7680845243070162, -1.6746054686443053, -1.5789615528280998, -1.4834968975084504, -1.3905697477290189, -1.302499419950063, -1.221513632399108, -1.149697468684871, -1.0889451913611283, -1.040916059229388, -1.0069952110965352, -0.9882605616256376, -0.9854565146448576, -0.9989751391945813, -1.0288452775692085, -1.0747298669158274, -1.1359315611449639, -1.2114065427247684, -1.2997862191666418, -1.3994063114084805, -1.508342665428567, -1.6244529585613214, -1.7454233320259327, -1.8688188645250685, -1.9921367112568749, -2.1128606705029878, -2.2285159076078336, -2.336722564418852, -2.435247011132683, -2.5220495562585667, -2.5953275176051527, -2.6535526706639634, -2.6955022277031233, -2.7202826579281707, -2.727345832352427, -2.716497162294693, -2.6878955931447224, -2.642045510488788, -2.5797808090905012, -2.502241561855566, -2.410843901226918, -2.3072438851988064, -2.1932962604352726, -2.071009152446817, -1.942495804603836, -1.8099245517695322, -1.6754682490316473, -1.541254380640199, -1.409317048801872, -1.28155198716632, -1.1596756611167751, -1.0451894084849682, -0.9393494428197016, -0.8431433901841181, -0.7572738634535945, -0.682149399433485, -0.6178828982927541, -0.5642975164627472, -0.5209397779791309, -0.48709948988448765, -0.46183587921339, -0.4440092164156129, -0.432317056606908, -0.4253341190537816, -0.421554739513857, -0.41943677154647313, -0.4174457830722545, -0.41409839396841724, -0.4080036292751877, -0.3979012198606034, -0.3826958666355736, -0.3614865934433268, -0.3335904447627339, -0.2985599340099907, -0.2561938126803527, -0.20654090565492622, -0.1498969392576367, -0.0867944714831618, -0.017986213590483996, 0.05557779558885147, 0.13277854110750215, 0.2123611434759669, 0.29297184027547307, 0.3731978461601183, 0.4516090234651924, 0.5268002468870023, 0.5974333255814772, 0.6622773550760318, 0.7202464093981779, 0.7704335498622656, 0.8121402193829682, 0.8449002076948803, 0.868497510537546, 0.8829775612641625, 0.8886514825495911, 0.8860931846560663, 0.8761293205637946, 0.8598222925540762, 0.838446684893412, 0.8134596685534126, 0.7864660820716445, 0.7591790336913744, 0.7333769902139647, 0.710858414469242, 0.693395083458497, 0.6826852612082109, 0.6803079130450689, 0.6876791309496639, 0.7060118931936843, 0.7362802066730045, 0.7791885789857985, 0.835147641804744, 0.9042566004960867, 0.9862930208177437, 1.0807102858994475, 1.1866428699298714, 1.3029193836462125, 1.4280831555603186, 1.560419926588592, 1.6979920589966238, 1.8386784977127846, 1.980219577164634, 2.1202656434680724, 2.2564283631468665, 2.386333518072226, 2.5076740438160057, 2.6182620562243812, 2.716078629117686, 2.7993201342358134, 2.8664400317635295, 2.91618510415884, 2.9476252550729116, 2.9601761457856037, 2.953614110147052, 2.928082971429628, 2.8840925763297984, 2.8225090579542313, 2.744537036198008, 2.651694155690606], [2.5792454563125062, 2.4665543647301864, 2.3442599148879424, 2.2146995987931484, 2.080327827799446, 1.9436625518339974, 1.8072305744101793, 1.6735128355029087, 1.5448909333255862, 1.4235961244169175, 1.3116619800173788, 1.210881787012757, 1.1227716659612064, 1.048540239751951, 0.9890655276858714, 0.9448795651190736, 0.9161610625541544, 0.9027362247631706, 0.9040876549108817, 0.9193710754963322, 0.9474394119569534, 0.9868736105099533, 1.0360194034733463, 1.0930290967465932, 1.1559073386781606, 1.2225597399686832, 1.290843152675371, 1.358616384223098, 1.4237901202886876, 1.4843748584612981, 1.5385257119038889, 1.5845830273383463, 1.6211078723545504, 1.6469115804792698, 1.661078695254018, 1.6629828229093442, 1.652295082857557, 1.6289850316569139, 1.593314124669751, 1.5458219656437582, 1.4873057732634805, 1.4187936609105811, 1.3415124772988547, 1.2568510875775332, 1.1663200836829175, 1.0715089964969906, 0.9740421387162937, 0.8755342349084485, 0.7775469934238669, 0.6815477437592627, 0.5888712034942547, 0.5006853526095432, 0.41796228208309877, 0.34145475100199313, 0.2716790354167452, 0.2089044866543458, 0.15315004100746307, 0.10418774109755967, 0.06155314637768466, 0.024562330832865124, -0.007665005500988228, -0.03617694370109803, -0.062156047082185056, -0.08688225436937123, -0.11169296273820582, -0.13794137265689316, -0.16695421308019512, -0.19998998346112576, -0.2381988377926508, -0.28258519572910956, -0.33397409775645004, -0.39298222707606695, -0.4599944026954006, -0.5351462091388859, -0.6183132716944673, -0.7091075161247901, -0.8068805725742825, -0.9107342995065323, -1.0195382195487366, -1.1319534797482518, -1.2464627784995495, -1.3614055445967108, -1.4750175144952777, -1.5854737354880473, -1.6909339281519655, -1.7895890735534814, -1.8797080510947557, -1.9596831426280492, -2.0280732379144957, -2.0836436252690738, -2.125401328197227, -2.1526250521652686, -2.1648889328709027, -2.1620794254057167, -2.1444048389179224, -2.11239719974468, -2.0669063131074985, -2.009086084741855, -1.9403733545412087, -1.8624596797162987, -1.77725668050531, -1.686855722754547, -1.593482854702666, -1.4994500364663021, -1.407103796995648, -1.3187725222085669, -1.2367136178525815, -1.1630618003322688, -1.0997797479611726, -1.0486122942888432, -1.011045265489659, -0.988269957167579, -0.9811541148809595, -0.9902201303791801, -1.0156309956479692, -1.0571843734991164, -1.114314951062823, -1.1861050458227764, -1.2713032375603395, -1.3683506085231854, -1.475413992957571, -1.5904254702552858, -1.7111271874309042, -1.8351204700779293, -1.9599180794333246, -2.0829983991736585, -2.2018602908654636, -2.314077342670569, -2.417350252295738, -2.5095561318516726, -2.588793598087786, -2.6534226145198287, -2.7020981797264483, -2.7337971054143844, -2.747837295069951, -2.74388911502378, -2.721978640118536, -2.6824827512254386, -2.6261162568351772, -2.553911401091945, -2.467190301311938, -2.367531024835767, -2.2567281639627934, -2.1367488951070785, -2.0096856111376433, -1.8777062916703964, -1.743003823084657, -1.6077454971786758, -1.4740239043279464, -1.3438103941871054, -1.2189122055345523, -1.1009342686566221, -0.9912465612229387, -0.8909577550263448, -0.8008957298784221, -0.7215953564175571, -0.6532937659792704, -0.5959331375912758, -0.5491708442824575, -0.5123966179140478, -0.4847562181987202, -0.46518093177000014, -0.4524220850492077, -0.44508963372967186, -0.44169379492117444, -0.4406886177252115, -0.4405163459302999, -0.43965141360400634, -0.4366429308606603, -0.4301545625093638, -0.4190007754202447, -0.4021785293793369, -0.37889360838040614, -0.3485809315922023, -0.31091834200691804, -0.265833541975523, -0.21350402411493347, -0.15435002887857854, -0.08902074177859136, -0.018374119228617973, 0.05654910221796904, 0.13455650703010294, 0.214339372840677, 0.2945113625218335, 0.3736494979468922, 0.4503363166328001, 0.5232020800868294, 0.5909658993366257, 0.6524746689097504, 0.7067387548191321, 0.7529634635577714, 0.7905754256780703, 0.8192431565618409, 0.8388912052422137, 0.849707465896487, 0.8521434017731677, 0.846907113438701, 0.8349493677399691, 0.8174428861205216, 0.7957553662942524, 0.7714168753273279, 0.7460824007406904, 0.7214904755357412, 0.6994188997540254, 0.6816386625566297, 0.6698672227272989, 0.6657223305241942, 0.6706775692067737, 0.6860207603630631, 0.7128163141136944, 0.7518725148489067, 0.8037146175249866, 0.8685644915019626, 0.9463273918032203, 1.0365862653604534, 1.1386038165009138, 1.2513323661476963, 1.3734313476182718, 1.5032920932574223, 1.6390693851007672, 1.778719073830137, 1.9200409176569524, 2.0607256602653834, 2.1984052578861273, 2.3307050827026687, 2.455296875225461, 2.5699511934196124, 2.672588111925472, 2.7613249606069705, 2.834519957091671, 2.8908106813945125, 2.9291464599173644, 2.9488138682279317, 2.9494547236154602, 2.931076115587538, 2.894052210915431, 2.8391177649782056, 2.7673534682530923, 2.680163451055108, 2.579245456312506], [2.501896078262449, 2.3833770776446537, 2.256753911784933, 2.124444749064951, 1.9889519998499745, 1.8528079676872813, 1.718519956849714, 1.5885161118076043, 1.4650932450477638, 1.3503678602730302, 1.2462314996361652, 1.1543114382230413, 1.0759376190987007, 1.0121165710593236, 0.96351288250529, 0.9304386227029289, 0.9128509105975067, 0.9103576359535106, 0.9222311427051675, 0.9474294947561904, 0.984624764692621, 1.0322376203359531, 1.0884773367780693, 1.1513862360611289, 1.2188874560080352, 1.2888348762689594, 1.3590639851481199, 1.4274424562173313, 1.491919219372703, 1.5505708563666027, 1.6016442247329183, 1.643594314503543, 1.6751164666165714, 1.6951722272833132, 1.7030082751427624, 1.698168033702079, 1.680495765937457, 1.6501331364029703, 1.6075084140659095, 1.5533186716814156, 1.4885055103048002, 1.414224996238535, 1.3318126384050186, 1.2427443533656026, 1.1485944600538107, 1.0509918144537926, 0.9515752343031855, 0.8519493745130026, 0.753642195190145, 0.6580651164713086, 0.5664768791043678, 0.4799520288080113, 0.3993548185062141, 0.32531917874906496, 0.2582352466678422, 0.19824277174459595, 0.1452315368788833, 0.09884875027115414, 0.05851318215314933, 0.023435644979917306, -0.007354749201264652, -0.034979270696531936, -0.06067404162710421, -0.08575125098447775, -0.11155815861220045, -0.13943498991635617, -0.17067285329829848, -0.20647281343798102, -0.24790722558750247, -0.2958843796485708, -0.35111741940720925, -0.414098393968417, -0.4850781678865513, -0.5640527669995941, -0.6507565723034813, -0.7446625984885562, -0.8449899114298794, -0.9507180545743569, -1.0606081724561633, -1.1732303450943804, -1.2869964842055521, -1.4001979951371684, -1.5110472809444875, -1.6177220603597673, -1.7184113922404234, -1.8113622474998, -1.8949254469030168, -1.967599790112356, -2.0280732379144952, -2.075260074840236, -2.1083330718626883, -2.1267497863167675, -2.1302722757787356, -2.118979660979287, -2.093273146023128, -2.0538732879997066, -2.0018094979681056, -1.9384019465967581, -1.865236235703737, -1.7841313769148808, -1.6971017861632718, -1.6063141536196637, -1.5140401790990472, -1.4226062697582393, -1.3343413772866863, -1.2515242037470236, -1.1763310273889265, -1.1107853915178187, -1.0567108609740015, -1.015687982839207, -0.9890164922318421, -0.9776836827617088, -0.9823397173019606, -1.0032804916729328, -1.0404384855651576, -1.0933818458813676, -1.161321752244291, -1.2431279174520282, -1.337351881959888, -1.442257575745042, -1.5558584476929227, -1.6759603061529227, -1.8002088783586914, -1.926140984305313, -2.051238135150057, -2.1729813093311567, -2.2889056327562263, -2.3966536932372406, -2.4940262537327156, -2.579029193039247, -2.649915594769526, -2.7052220234885227, -2.7437981678497425, -2.764829191016692, -2.767850304633048, -2.7527532698061976, -2.71978472240871, -2.6695364157415193, -2.6029276664605914, -2.521180474943662, -2.4257879644567257, -2.3184769403671153, -2.2011655074453866, -2.075916796706697, -1.9448899405503994, -1.8102894940994414, -1.6743145302507498, -1.5391086353890204, -1.4067120020974822, -1.2790167553724003, -1.1577265613842525, -1.0443214549778927, -0.9400286867416346, -0.8458002360244606, -0.7622974666326656, -0.6898832213490173, -0.6286214644091025, -0.5782843923095152, -0.5383667475123253, -0.5081068913676531, -0.4865140263200017, -0.4724008073049003, -0.4644204518806525, -0.46110735127432634, -0.4609201027693423, -0.46228582969666193, -0.4636446299918175, -0.46349299840010644, -0.4604251007691687, -0.45317084054653056, -0.44062974597580423, -0.42189981926838416, -0.3963006233174855, -0.36339003388249086, -0.3229742517179245, -0.27511084561549654, -0.22010477928616493, -0.1584975578156474, -0.09104980844718574, -0.018717781144209893, 0.05737558756012103, 0.1359742625127272, 0.21572644359840792, 0.29522464113740704, 0.3730474169626483, 0.447801670643724, 0.5181643346098836, 0.5829223553813702, 0.6410098804271511, 0.691541640279312, 0.7338416117012735, 0.7674661675221465, 0.7922210592085287, 0.8081717358210798, 0.8156466737345227, 0.8152335710888929, 0.8077684448607537, 0.7943178520545403, 0.7761546351754489, 0.7547277613325319, 0.7316269797403807, 0.7085431600837466, 0.6872252906632271, 0.6694352074580103, 0.6569011908315239, 0.651271603836737, 0.6540697539246932, 0.6666511380294123, 0.6901641799423172, 0.7255154897776708, 0.7733405700474614, 0.8339807639463553, 0.9074670920259617, 0.9935114571608378, 1.0915055186525882, 1.20052734888561, 1.3193557947591987, 1.4464922759002683, 1.5801895671200343, 1.718486938296693, 1.8592508651819948, 2.0002203835270804, 2.139056039935928, 2.27339129897923, 2.4008851997173326, 2.519275017597273, 2.626427680695738, 2.7203887127273148, 2.7994275286254076, 2.862077990594502, 2.907173241382826, 2.933873964527746, 2.941689375281103, 2.930490417107009, 2.9005148229129456, 2.852363893053103, 2.786991038942344, 2.7056823370512237, 2.610029528346629, 2.5018960782624484], [2.420300432279727, 2.296950400009957, 2.1670522704778508, 2.0330844417603418, 1.897576171900505, 1.7630527218786276, 1.6319807200821181, 1.5067150165715262, 1.3894482583112338, 1.2821643498114899, 1.1865968689607234, 1.1041933875437628, 1.0360865029988489, 0.98307222587259, 0.945596190161654, 0.9237479656250496, 0.9172635568139454, 0.9255359777467932, 0.9476335986355835, 0.9823257765361838, 1.02811510974026, 1.0832755003229573, 1.1458950742676017, 1.2139228972560119, 1.2852183392021457, 1.357601883926578, 1.4289061533262157, 1.4970259185616868, 1.5599659039911338, 1.6158852519101994, 1.663137605982859, 1.7003058862595883, 1.7262309659536519, 1.7400336162138976, 1.7411292560670493, 1.7292352262176434, 1.7043704929510206, 1.6668478773056092, 1.6172590902636301, 1.5564530323464532, 1.4855079812922112, 1.4056984403563872, 1.3184575485465593, 1.2253360596249154, 1.1279589764181617, 1.027980978945305, 0.9270418078883128, 0.8267227584936837, 0.7285054043478025, 0.633733606589695, 0.5435797736914761, 0.45901622229280753, 0.3807923536677545, 0.3094182067077156, 0.245154780740885, 0.18801134433994876, 0.13774976399434774, 0.09389570376481036, 0.05575636842709375, 0.02244429267224814, -0.00709347803575222, -0.03404160936452966, -0.05967901672916554, -0.08533873058028131, -0.11236616838465913, -0.14207693564568716, -0.17571529182391205, -0.21441440136134843, -0.25915944556627923, -0.3107545989829847, -0.3697947758563178, -0.4366429308606601, -0.5114135564449797, -0.5939628605148785, -0.6838859367200243, -0.7805210596599712, -0.8829610534010832, -0.9900714984563507, -1.1005153644517753, -1.2127834875959234, -1.3252301580509798, -1.436112946297373, -1.5436357830667744, -1.6459942173362905, -1.7414217135689167, -1.8282358145256663, -1.904882990528911, -1.9699810202561088, -2.0223578014808288, -2.0610855714167093, -2.0855096235246147, -2.095270738226599, -2.0903206957568656, -2.070930406684231, -2.0376903753578754, -1.991503399235259, -1.9335695981170942, -1.8653640570134402, -1.7886075499958063, -1.7052309853899685, -1.617334370724577, -1.527141235022723, -1.4369495628172757, -1.3490803857424627, -1.2658252413776734, -1.1893937435487858, -1.1218625125978532, -1.065126688029673, -1.020855189996162, -0.9904508115855045, -0.9750161128458311, -0.9753259525507418, -0.9918073381556681, -1.0245271019596887, -1.0731877263559297, -1.1371314477200645, -1.2153525716514153, -1.3065177367355918, -1.4089936745044416, -1.5208818344462316, -1.6400590791259442, -1.7642235097048287, -1.890944359929509, -2.0177147999704674, -2.142006422681106, -2.2613241455917055, -2.373260253194414, -2.47554632601583, -2.5661018550613437, -2.6430784211608427, -2.7048984265538407, -2.7502874980718626, -2.7782998342648644, -2.788335939023671, -2.7801523675005675, -2.753863301939144, -2.7099339707018, -2.6491661185494415, -2.572675925332558, -2.4818649490917815, -2.378384833794494, -2.2640966675727947, -2.1410260008631137, -2.011314632313433, -1.8771703413786298, -1.7408157885048705, -1.6044378157674446, -1.4701383625719555, -1.339888163100659, -1.2154843158615856, -1.0985127129517513, -0.9903161901018992, -0.8919691114355204, -0.8042589388588153, -0.7276751592198212, -0.6624057572605594, -0.6083412335586077, -0.5650859788187044, -0.5319766336999352, -0.5081068913676529, -0.49235804239620845, -0.4834344224040339, -0.47990280529723056, -0.4802346921023429, -0.4828503793338856, -0.48616365324208, -0.48862594798219733, -0.48876882686473916, -0.48524369577496185, -0.47685773525950886, -0.462605140649161, -0.4416928852662687, -0.41356036703143306, -0.3778924599270286, -0.3346256646914938, -0.2839472334134513, -0.2262873257929962, -0.16230443609725742, -0.09286450466676553, -0.01901429180194505, 0.05805025917532393, 0.13701981270245042, 0.2165106205028926, 0.2951056414623435, 0.3713966970849583, 0.4440265297499725, 0.5117296320625059, 0.5733707457373173, 0.6279799869266733, 0.6747836402444971, 0.7132297738122143, 0.7430079596962549, 0.7640625348061917, 0.7765990028861659, 0.7810833544926441, 0.778234264366245, 0.7690083097688435, 0.7545785345161774, 0.736306857005, 0.7157109821114294, 0.6944266223143689, 0.6741659590634705, 0.6566733780430257, 0.6436795889305187, 0.6368552894985523, 0.6377655541372388, 0.6478261174805907, 0.6682626849427253, 0.7000743344828662, 0.7440019794130525, 0.8005027428072821, 0.8697309529555927, 0.9515263097726804, 1.0454095980249802, 1.1505861389600498, 1.2659569819488437, 1.3901376467773732, 1.5214840399784892, 1.6581249897227734, 1.7980006777394788, 1.938906097656309, 2.0785385407602854, 2.2145480057193545, 2.3445893509081626, 2.4663749586440495, 2.5777266611527567, 2.676625689006124, 2.761259443917107, 2.8300639682059554, 2.8817610813107204, 2.9153892770668253, 2.9303276211617604, 2.9263120526666273, 2.9034436728747597, 2.862188794488446, 2.8033707198759394, 2.72815341391209, 2.6380174300250987, 2.5347286327946477, 2.4203004322797312], [2.335148854451799, 2.2080055406273975, 2.0759139074426027, 1.94139162642012, 1.8069734248035167, 1.6751561844022838, 1.5483450252098874, 1.4288016240757804, 1.3185959639335258, 1.219562625593234, 1.1332626239515433, 1.060951656362344, 1.0035554761366907, 0.961652932494743, 0.9354670339795849, 0.9248641998718714, 0.9293616682197353, 0.9481428345031699, 0.9800801064302193, 1.0237646825017073, 1.0775424991011644, 1.139555446911374, 1.2077868359009687, 1.2801099918793788, 1.3543387989736104, 1.4282789629393369, 1.4997787608629334, 1.5667780636778634, 1.627354468400634, 1.6797654557506911, 1.722485593822264, 1.7542379370471555, 1.7740189185718307, 1.7811161996206646, 1.775119117278321, 1.7559215579492906, 1.7237172729042785, 1.6789878400932883, 1.6224836581300484, 1.55519852952933, 1.4783385466775567, 1.3932861317852117, 1.3015601978269242, 1.2047734883978585, 1.1045882183051903, 1.002671172052449, 0.9006494233606466, 0.8000678154371853, 0.7023492895218936, 0.6087590696981513, 0.5203736071284311, 0.4380550594606086, 0.36243193441986216, 0.2938863642966862, 0.23254830429659257, 0.1782967669460209, 0.13076802153799932, 0.08937050659325113, 0.05330602909111243, 0.021596661198972442, -0.0068834024767377095, -0.03337189274425644, -0.05917939074925952, -0.08564818326606902, -0.11411015592727833, -0.14584485778852255, -0.1820388673453797, -0.22374755780378822, -0.27186029885627455, -0.3270700449479317, -0.38984814821661823, -0.4604251007691694, -0.5387777590665853, -0.6246234367591282, -0.7174210755299288, -0.8163795208313861, -0.9204727454446852, -1.0284616832096358, -1.1389221626330812, -1.2502782697693209, -1.3608403258541655, -1.4688465413388125, -1.5725073073877185, -1.6700510111763032, -1.7597702144067169, -1.8400670166186666, -1.909496436647525, -1.9668066867747718, -2.010975283791988, -2.041240037711492, -2.057124079883671, -2.0584542348860375, -2.045372201250567, -2.018338180954415, -1.9781267823134803, -1.9258152109329802, -1.862763953986108, -1.7905903495877886, -1.711135610773382, -1.6264260381566846, -1.5386293026190019, -1.4500068056812063, -1.3628632273549974, -1.2794944466685765, -1.2021350667822965, -1.1329067934214816, -1.0737689017617709, -1.0264719831601383, -0.992516090228999, -0.9731142984164927, -0.9691625768764746, -0.9812167139991483, -1.0094768770855127, -1.0537802053022234, -1.1136016446239974, -1.1880630375867363, -1.27595028410279, -1.3757381971181182, -1.4856224932107926, -1.6035581878202616, -1.727303511813501, -1.8544683342694135, -1.982565968911005, -2.1090671611552447, -2.2314550012408505, -2.3472794875849545, -2.4542104739202273, -2.550087773633715, -2.6329672640797988, -2.701161930763945, -2.7532769138038233, -2.788237763962522, -2.8053112792617587, -2.8041184717102583, -2.7846394026539043, -2.74720982004848, -2.6925097268147615, -2.621544201581115, -2.5356169768700823, -2.4362974506754886, -2.3253819612608075, -2.204850288167995, -2.076818451655082, -1.943488965470867, -1.8070997520747951, -1.669872953873208, -1.5339648682588443, -1.4014181984449179, -1.2741177472535175, -1.1537505888416644, -1.0417716361893605, -0.9393753830071532, -0.8474744410588878, -0.7666853217010814, -0.6973217280273741, -0.6393954359320664, -0.5926246533576862, -0.5564495616693257, -0.5300545660996996, -0.5123966179140478, -0.5022388234068885, -0.49818842769089483, -0.49873815758319273, -0.502309830255101, -0.5072990845515103, -0.5121200711694329, -0.5152489466470677, -0.5152650540516571, -0.5108887393337483, -0.501014844800585, -0.484741037657404, -0.4613902690781884, -0.43052681428030576, -0.39196551263905705, -0.3457740047015477, -0.2922679455301055, -0.2319993564943453, -0.16573845581051438, -0.09444947728615408, -0.0192611425874864, 0.058567409036420735, 0.13768431177155085, 0.21668526906267496, 0.29415537028774214, 0.3687113041509464, 0.4390428333517763, 0.5039524129399829, 0.5623918813442081, 0.6134952272034218, 0.6566065349780635, 0.6913023353660986, 0.7174077297060655, 0.7350058172131444, 0.7444401260449184, 0.7463099294917178, 0.7414585124824657, 0.730954636445009, 0.7160676277335013, 0.698236681843819, 0.6790351282384404, 0.6601305349064622, 0.6432416443563548, 0.6300932206807958, 0.6223699483588375, 0.6216705559538662, 0.6294633409208187, 0.6470442451814816, 0.6754985755305934, 0.7156673795929014, 0.7681193789522971, 0.8331292288558041, 0.9106627217765352, 1.0003693838229621, 1.1015827326397651, 1.213328277500766, 1.3343391513876526, 1.4630790757049925, 1.5977721755946899, 1.7364389921242396, 1.876937881213061, 2.0170108519419494, 2.154332782307022, 2.2865628614246307, 2.4113970459361207, 2.5266202864878613, 2.6301572785377614, 2.7201205204856076, 2.7948545206147677, 2.8529750812066204, 2.8934027013861665, 2.9153892770668253, 2.918537433489022, 2.9028119994921373, 2.8685433186137077, 2.8164222858572314, 2.747487195798677, 2.6631026828195283, 2.5649312229068775, 2.454897844049561, 2.3351488544518], [2.2471617656586274, 2.1172950132553687, 1.9841098944710571, 1.850142065753548, 1.7179102987976709, 1.5898619997389425, 1.468320468057234, 1.3554351168771017, 1.2531358043861132, 1.16309232653276, 1.0866799964554295, 1.0249520892916901, 0.9786197657199406, 0.9480399078401047, 0.9332111112038799, 0.9337778815965643, 0.9490428893179244, 0.9779869419847592, 1.0192961539509169, 1.0713956207569688, 1.1324887546951856, 1.2006013062860919, 1.2736289893683963, 1.3493875471607069, 1.4256640449553903, 1.5002681532370374, 1.5710821934282833, 1.6361087568549646, 1.6935147748526183, 1.7416710124574581, 1.7791860774187416, 1.804934177312038, 1.8180760167676573, 1.8180724002579072, 1.8046902891701395, 1.7780012504548663, 1.7383724232843054, 1.6864503151874268, 1.6231379154568704, 1.5495657768915487, 1.4670578631218836, 1.377093084272154, 1.281263545479342, 1.181230608341684, 1.0786799129039233, 0.9752765261943593, 0.8726213722359841, 0.7722100582232708, 0.6753951432796222, 0.5833528016798897, 0.4970547140852662, 0.41724588123401163, 0.34442889821756084, 0.27885505793101467, 0.22052247383018078, 0.1691812292834625, 0.12434537821029491, 0.08531144397222287, 0.05118289512477949, 0.020899921905911847, -0.006726299858510679, -0.032975786941370114, -0.059179390749259514, -0.08667699093209019, -0.11677536631628407, -0.15070687801852878, -0.18959007955233922, -0.2343933200384936, -0.2859023304914519, -0.3446926814877229, -0.41110787588368564, -0.4852436957749616, -0.5669392622147437, -0.655775093383248, -0.7510782662840322, -0.8519346031951522, -0.9572076216717536, -1.0655638104994427, -1.1755036281081883, -1.285397468790799, -1.39352570948171, -1.4981218392353122, -1.5974175877470485, -1.68968891051809, -1.773301658133945, -1.8467557564554133, -1.9087267534170858, -1.9581036459660002, -1.9940219860982695, -2.015891375919938, -2.0234165954836683, -2.016611760573002, -1.9958070768627987, -1.9616479378177727, -1.9150863018399387, -1.8573644748901523, -1.7899916133644231, -1.714713443720122, -1.6334758656987383, -1.5483832607282864, -1.4616524623371774, -1.375563457771079, -1.2924079766346723, -1.2144371810691585, -1.1438097011977733, -1.0825412585238314, -1.0324570885909712, -0.9951483132038695, -0.9719333232801355, -0.9638251180784426, -0.9715054078868297, -0.9953061285994743, -1.035198841796588, -1.0907923072090768, -1.1613383203333, -1.2457457111842984, -1.3426022055302915, -1.4502036621821395, -1.5665900235977495, -1.6895871565061023, -1.8168536183764905, -1.9459312677945908, -2.074298545031934, -2.1994251855465965, -2.318827095378721, -2.430120114222395, -2.5310714194359245, -2.61964738171365, -2.694056769170843, -2.7527883090742242, -2.794641752625813, -2.8187517447383663, -2.824603973792934, -2.8120432617082476, -2.781273447745253, -2.7328491156017343, -2.66765940773544, -2.586904358753152, -2.492064356546529, -2.3848635013509125, -2.267227775141374, -2.1412390533317875, -2.0090860847418552, -1.873013632011951, -1.7352710015317092, -1.598061198687453, -1.4634919207502437, -1.3335295466926513, -1.2099572020355918, -1.09433786957807, -0.987983386282119, -0.8919300159726548, -0.8069211206572016, -0.7333972743546694, -0.6714939768182969, -0.6210469350942663, -0.5816046931866756, -0.5524482088584862, -0.5326168062732622, -0.5209397779791303, -0.5160727734735872, -0.5165379976044925, -0.5207671531351056, -0.5271460000747095, -0.5340593713129046, -0.5399354804376423, -0.5432883833706731, -0.542757509889173, -0.5371432627725062, -0.5254377890918245, -0.5068501572952308, -0.4808253219239219, -0.4470564212429732, -0.4054901276245003, -0.3563249517469169, -0.3000025849757871, -0.23719254502575546, -0.16877056359473172, -0.09579131671978268, -0.01945624503148702, 0.058922661821573595, 0.13796213775721441, 0.21624891167190988, 0.2923818673377425, 0.3650139577999892, 0.43289274577581355, 0.4948984760353234, 0.5500786483628014, 0.597678148879087, 0.6371641110157993, 0.6682448124144597, 0.6908820670815378, 0.7052967394085455, 0.7119671839474793, 0.7116205976424058, 0.7052174549397184, 0.6939293761850536, 0.6791109514042774, 0.6622662006007294, 0.6450104940333524, 0.6290288779352962, 0.6160318496582335, 0.6077096987354863, 0.6056865749449312, 0.6114754599144235, 0.6264352046680831, 0.6517307520208174, 0.6882975908843644, 0.7368113910548586, 0.7976636442820499, 0.8709439933573966, 0.9564297691231213, 1.0535830796685863, 1.1615556108677045, 1.2792011073915266, 1.4050953131053003, 1.537562964046956, 1.6747112506007644, 1.8144690024266257, 1.9546307042565614, 2.092904326474837, 2.2269618545865018, 2.354491328785397, 2.47324916073234, 2.5811114805138717, 2.6761232830040855, 2.7565441891782347, 2.8208897132694832, 2.867967029244014, 2.896904357447109, 2.907173241382826, 2.898603151832365, 2.8713880368413878, 2.8260846271134925, 2.763602502391915, 2.685186120722607, 2.5923892042854937, 2.4870420580806667, 2.3712125667080133, 2.247161765658627], [2.1570835764860092, 2.0255862700024156, 1.8924169350547373, 1.7601077723347556, 1.6311403082304945, 1.507891795286915, 1.3925840925891941, 1.287236208825114, 1.1936216022398256, 1.1132312169132204, 1.0472430965798725, 0.9964992589592043, 0.9614903391422591, 0.9423483242572144, 0.9388475079620375, 0.9504135970182499, 0.9761407080721672, 1.0148158055376573, 1.064949955690186, 1.1248156120110886, 1.19248900633654, 1.2658966028532415, 1.3428644802576426, 1.4211694436338642, 1.4985906332914376, 1.5729603936942806, 1.6422131917175993, 1.7044314290562155, 1.7578870772166308, 1.801078173008184, 1.832759345023803, 1.8519656939212914, 1.8580295175543313, 1.8505895519453632, 1.8295925862471922, 1.795287499544601, 1.748211954887356, 1.6891721666719208, 1.6192163269310569, 1.539602430069274, 1.4517613703126409, 1.3572562983266123, 1.2577393103670136, 1.1549066028749424, 1.0504532562016948, 0.946028812471214, 0.8431947845096748, 0.7433851760837459, 0.6478710098950883, 0.5577297510588122, 0.47382038294904605, 0.39676474267707423, 0.3269355588935888, 0.2644514592642966, 0.20917903330914567, 0.16074185292572551, 0.11853617248006523, 0.0817528574082463, 0.04940492920217893, 0.02035996952276376, -0.006623499340311055, -0.032856643190202976, -0.05967901672916549, -0.08841644939994941, -0.12033925066576394, -0.15662186144447118, -0.1983050417725573, -0.2462616200996978, -0.3011667385300857, -0.36347341312289966, -0.43339409194131995, -0.5108887393337481, -0.5956598068295953, -0.6871542732759125, -0.7845727539185058, -0.8868854946656138, -0.992854888406691, -1.1010639795399955, -1.2099502651258796, -1.3178439603450178, -1.423009775797819, -1.5236911577194443, -1.6181558719008973, -1.7047417698469707, -1.7819015626136205, -1.8482454442701983, -1.902580452706009, -1.9439455294932069, -1.9716413409696176, -1.9852540471912037, -1.9846723508954414, -1.9700973215541173, -1.9420446659743513, -1.9013393023838676, -1.8491022849281924, -1.786730315308009, -1.71586826318355, -1.638375292368772, -1.5562853513566415, -1.4717629303165682, -1.387055108780297, -1.304441015701651, -1.226179893958759, -1.15445900284992, -1.0913426036094767, -1.038723254071727, -0.9982765897186815, -0.9714206905828141, -0.959281028671766, -0.9626618612404167, -0.9820247844664045, -1.0174749935286687, -1.0687556128281193, -1.1352502685499488, -1.2159938796062513, -1.3096914469924072, -1.4147444305183121, -1.5292841203972147, -1.6512112437200126, -1.7782408965001282, -1.9079517643915047, -2.0378384924752986, -2.165365989188849, -2.28802440337071, -2.4033834976419883, -2.509145156316874, -2.603192811362471, -2.683636644495195, -2.7488535254780886, -2.7975207735699725, -2.828642977765584, -2.841571278314299, -2.836014692932612, -2.812043261708247, -2.7700829802762543, -2.71090268665682, -2.6355932584081443, -2.545539658810584, -2.4423865392376234, -2.327998255603467, -2.2044142861658327, -2.0738011428952836, -1.9384019465967646, -1.8004848851481998, -1.6622917934818469, -1.5259880828916665, -1.3936152062669385, -1.2670467760289448, -1.1479493546923882, -1.037748816560334, -0.9376030361637034, -0.848381498272789, -0.7706522496716364, -0.7046764287631427, -0.6504104200550089, -0.6075154913670385, -0.5753745868952104, -0.5531157736415986, -0.5396416765093276, -0.5336640925629271, -0.5337428511188064, -0.5383278864800829, -0.5458034166823658, -0.5545330763259988, -0.5629048354828987, -0.5693745500976828, -0.5725070318303485, -0.5710135957604237, -0.5637851409426364, -0.5499199389730152, -0.5287454464060144, -0.4998336144619329, -0.46300933996479865, -0.4183518805206268, -0.36618924004124, -0.3070857132008213, -0.24182295466230633, -0.17137510644601128, -0.09687867039885363, -0.01959794847898579, 0.05911301193146639, 0.13785094012588484, 0.21520524011157727, 0.2898001372498209, 0.3603359392552834, 0.4256282995459236, 0.4846444217516936, 0.5365352223159212, 0.5806625715936026, 0.6166208600622223, 0.6442522820351161, 0.6636553909314684, 0.6751866536341333, 0.6794549123781669, 0.6773088463892549, 0.6698177074840799, 0.6582457794448977, 0.6440211757333377, 0.6286997398238671, 0.6139249432978625, 0.6013847854925064, 0.5927667821448258, 0.5897121869314131, 0.5937706175771928, 0.6063562565060518, 0.6287067647819768, 0.6618459880300691, 0.7065514455425238, 0.763327480963995, 0.8323848175486875, 0.9136271062929989, 1.0066448850649736, 1.1107171853632394, 1.2248208350209666, 1.3476473146836596, 1.4776268379561273, 1.6129591444035465, 1.7516503256068334, 1.8915548514337919, 2.030421830430629, 2.165944428118252, 2.29581128278221, 2.4177587022297984, 2.529622398417244, 2.6293875205630766, 2.71523578135409, 2.7855885343649693, 2.8391447523703417, 2.874912973653809, 2.892236423898755, 2.8908106813945125, 2.870693429234971, 2.8323060256579127, 2.776426818116983, 2.7041763233618266, 2.616994589934417, 2.516611246336598, 2.405008913126145, 2.2843808160843344, 2.157083576486014], [2.065676389175189, 1.9336552083351357, 1.801610793121841, 1.6720504770270452, 1.5473975664860558, 1.4299390760678001, 1.3217766628133223, 1.2247818935422896, 1.1405568745753003, 1.0704011442844024, 1.0152855783432224, 0.9758338891845537, 0.952312119103648, 0.9446263351186541, 0.9523285377869855, 0.9746306004567147, 1.010425864673902, 1.0583178363109549, 1.1166552598267354, 1.1835726989652329, 1.2570356247459167, 1.3348889088574034, 1.4149075449863704, 1.4948483739730152, 1.5725015720447768, 1.64574067506319, 1.7125699552982077, 1.7711680395584373, 1.8199267566858701, 1.8574843259425606, 1.8827521425513307, 1.8949345789623984, 1.893541396236035, 1.8783925448655803, 1.8496153238077917, 1.8076340557290775, 1.7531526208236308, 1.6871303664515593, 1.610752070966075, 1.5253927834850884, 1.4325784835007354, 1.3339436021339341, 1.231186518163825, 1.1260241849956292, 1.0201470584869141, 0.9151754797758503, 0.8126186224295672, 0.7138370405649175, 0.6200097559915374, 0.5321067004377336, 0.4508671866748378, 0.37678492348980747, 0.3100999180144518, 0.25079742925895565, 0.19861395337325977, 0.15305003881565818, 0.11338955285648349, 0.07872485415393145, 0.04798717371955462, 0.019981372291020802, -0.006575870661040576, -0.03301546950080306, -0.060674041627104124, -0.0908518420638948, -0.12477165690144526, -0.16353976463000602, -0.20811002148208546, -0.25925204679841635, -0.31752437917294696, -0.38325334636544983, -0.4565182449170476, -0.537143262772506, -0.6246964041075064, -0.7184954943759886, -0.8176211599115351, -0.9209364948854716, -1.027112953642349, -1.1346618428372015, -1.2419706395497023, -1.3473432324312262, -1.4490430762597666, -1.5453381687865868, -1.6345467045811415, -1.7150822351615276, -1.7854971687623444, -1.8445234766300174, -1.8911095349995433, -1.9244521214283723, -1.9440226987911768, -1.949587257189883, -1.941219139960174, -1.9193044510315056, -1.8845398229091075, -1.8379225129984353, -1.7807329862194259, -1.714510329138937, -1.6410210205272204, -1.5622217508375726, -1.480217134427532, -1.3972132895879057, -1.3154683693151419, -1.237241207516105, -1.1647392988752445, -1.1000673545390287, -1.0451776694046324, -1.0018235002107088, -0.9715165876322125, -0.9554898617212194, -0.9546662505415049, -0.969634369581644, -1.0006317079292648, -1.0475357501579041, -1.109863284712567, -1.1867779548544415, -1.2771059116794763, -1.3793592351503552, -1.4917666031987213, -1.612310515302532, -1.7387702197638093, -1.8687693570457122, -1.9998272183208818, -2.129412431602248, -2.254997829595701, -2.374115225153185, -2.484408822605303, -2.5836860262530283, -2.669964470088867, -2.7415141838597563, -2.7968939276473628, -2.834980867359885, -2.854992923472719, -2.8565033011103136, -2.8394468968334627, -2.8041184717102583, -2.75116267666544, -2.681556209933484, -2.596582572966281, -2.4978000658326662, -2.387003821757259, -2.2661828191439928, -2.137472924874346, -2.0031071120967834, -1.8653640570134435, -1.7265163508977133, -1.5887795650487784, -1.454263377658927, -1.324925913433031, -1.2025323607774108, -1.088618819671307, -0.9844621987838161, -0.8910568263934838, -0.8090982700732259, -0.7389746791625853, -0.680765776276537, -0.6342494341681459, -0.598915586887363, -0.5739870440016707, -0.5584466081185212, -0.5510697432269085, -0.5504619082062411, -0.5550995594898661, -0.5633737419977413, -0.573635130106325, -0.5842393519510942, -0.5935914313818976, -0.6001882122988996, -0.6026576890385335, -0.5997942523929175, -0.5905889714992323, -0.5742541643778633, -0.55024166093615, -0.5182543279360021, -0.4782506015346174, -0.4304419550779245, -0.375283413241907, -0.31345740373527226, -0.24585141004318845, -0.17353004875326195, -0.09770233881920899, -0.01968505405469533, 0.059136848918035036, 0.1373516596598406, 0.21356308431534418, 0.2864320226287673, 0.35471682667054494, 0.41731095516440947, 0.47327700402834566, 0.5218761867163945, 0.5625924548304378, 0.5951505873163269, 0.6195277318918213, 0.6359580512563003, 0.6449303048405234, 0.6471783798664235, 0.6436649686741116, 0.6355587679975879, 0.6242057455999747, 0.611095176101163, 0.597821286960404, 0.5860414738575603, 0.5774321391092493, 0.5736432748148576, 0.5762529523624027, 0.5867228906469839, 0.6063562565060515, 0.6362588028360435, 0.6773043737354016, 0.7301057036347027, 0.7949913112010122, 0.8719891419148693, 0.9608174492128536, 1.060883226998625, 1.1712883205192623, 1.29084315267537, 1.418087813491222, 1.5513200764190058, 1.6886297309717866, 1.8279384612230283, 1.967044357981392, 2.103670032511955, 2.235513204561263, 2.3602985695769014, 2.475829711149682, 2.5800398158908378, 2.671039969491509, 2.7471638641531264, 2.8070078277428148, 2.8494651920260488, 2.8737541486032225, 2.879438393571187, 2.8664400317635295, 2.8350443945793034, 2.785896617441129, 2.7199900191587036, 2.6386465211322174, 2.5434895346415987, 2.4364099247870064, 2.3195258255700484, 2.1951372280806036, 2.0656763891751937], [1.9737135498930394, 1.8422796066345142, 1.7124597297233688, 1.5867151843951062, 1.4673905750535359, 1.3566633573602, 1.2564972416262505, 1.168600562796822, 1.0943905730006427, 1.0349644704415752, 0.9910778168107034, 0.9631308183472179, 0.9511627574988262, 0.954854667421726, 0.9735401450661697, 1.006224005104551, 1.0516082911840685, 1.1081249874394168, 1.1739746160906537, 1.2471697700758853, 1.3255825163238937, 1.406994518170408, 1.4891486666271168, 1.569800981087394, 1.6467715412284738, 1.7179932432299314, 1.7815572341134174, 1.8357539664381204, 1.8791089294987515, 1.9104122496826885, 1.9287415083122421, 1.9334772962242692, 1.9243112062498124, 1.9012461531174552, 1.864589100431782, 1.8149364615560952, 1.7531526208236308, 1.680342189080132, 1.597816758997508, 1.5070570571790325, 1.4096714985889507, 1.3073522316530244, 1.2018298175070905, 1.0948277130284456, 0.9880177239059595, 0.8829775612641628, 0.7811515741627298, 0.683815642263959, 0.5920471003843547, 0.506700432419471, 0.4283893196895612, 0.3574754619835069, 0.29406441272020184, 0.23800848718735615, 0.18891661937953397, 0.1461708631812172, 0.10894906207043714, 0.07625305248699688, 0.04694162352983129, 0.01976733331458074, -0.006583816780878096, -0.03345092213071299, -0.062156047082184945, -0.09396256439996171, -0.1300350848608875, -0.17140205898379687, -0.21892206411577714, -0.2732546952465432, -0.33483685937828045, -0.4038651340296194, -0.48028469401289553, -0.5637851409426361, -0.6538033912962956, -0.7495335957709055, -0.8499438797938443, -0.9537995169846126, -1.059691978644882, -1.1660731472643595, -1.2712938445226472, -1.3736457078590014, -1.471405357365441, -1.5628797289277265, -1.6464514119263693, -1.7206228214460848, -1.7840580561250676, -1.835621343065316, -1.8744110494521335, -1.8997883448245927, -1.9113997257733537, -1.9091927630987935, -1.8934245965051808, -1.8646628796738245, -1.8237790646606364, -1.7719341043961003, -1.710556840918175, -1.6413155301458424, -1.5660831269370705, -1.486897112547749, -1.4059147864478916, -1.3253650622369604, -1.2474979001509563, -1.1745325739999506, -1.1086060066207222, -1.0517224140936974, -1.0057054748164849, -0.9721541855557697, -0.952403484058256, -0.947490608640037, -0.9581280320005463, -0.9846836525264621, -1.0271687552831865, -1.0852340708834503, -1.1581740679443542, -1.2449394185798761, -1.3441573811081262, -1.4541596546452933, -1.5730170811377122, -1.698580406027321, -1.8285261631709204, -1.9604066264020426, -2.0917026722502627, -2.2198783282127454, -2.342435740323778, -2.456969283585203, -2.561217559355098, -2.6531120745410703, -2.730821477167766, -2.792790329634424, -2.8377715321377828, -2.8648516610996126, -2.8734686572830506, -2.8634214814567387, -2.8348715474973947, -2.788335939023671, -2.7246726112428923, -2.645057969904237, -2.5509573994612245, -2.444089478378404, -2.3263847669562847, -2.1999401785367407, -2.06697004547475, -1.9297550644262567, -1.7905903495877895, -1.6517338365313936, -1.51535626294971, -1.383493906451303, -1.258005184748156, -1.1405321220841829, -1.0324675601459985, -0.9349288451473762, -0.8487385589685164, -0.7744126852603971, -0.7121564157108186, -0.6618676118345822, -0.6231477484112404, -0.5953199807386395, -0.5774538037468072, -0.568395611017349, -0.5668043198103152, -0.5711911077876314, -0.5799622111699264, -0.5914636648864093, -0.6040268245174227, -0.6160134984159645, -0.6258595365227531, -0.6321157695157291, -0.633485266791919, -0.6288559824081482, -0.617327981906913, -0.5982345867480806, -0.5711569331835644, -0.5359316147746709, -0.49265125798279946, -0.4416580637948175, -0.3835305305284798, -0.31906374919399577, -0.2492438286129826, -0.17521715872944182, -0.09825535337329828, -0.019716824806029425, 0.05899397110958678, 0.1364685204977514, 0.21133633766433083, 0.2823060192483651, 0.3482041602809183, 0.4080110811283799, 0.46089239636303425, 0.5062255636386823, 0.5436206799542299, 0.5729349410009525, 0.5942803428667738, 0.6080243800828747, 0.614783675429664, 0.6154106604825959, 0.6109736069264742, 0.6027304826106454, 0.5920972687399039, 0.5806115213638264, 0.5698920876942245, 0.561595992481325, 0.5573735890126239, 0.5588231211938263, 0.5674458662432834, 0.5846030211132679, 0.611475459914423, 0.6490274251710096, 0.6979751241987486, 0.7587610854790193, 0.8315349914340583, 0.9161415468752975, 1.0121157704619859, 1.118685914008187, 1.2347840259244844, 1.3590639851481188, 1.489926645319613, 1.6255515503499693, 1.7639345163479785, 1.9029302253012608, 2.0402988466846432, 2.1737555975657417, 2.301022072474931, 2.4198781233434605, 2.528213048532155, 2.6240748589871523, 2.7057164287332856, 2.771637405373093, 2.8206208523974543, 2.851763716647065, 2.8645003582765556, 2.858618543592152, 2.834267479213599, 2.79195765482992, 2.732552456785046, 2.657251711095785, 2.567567507482523, 2.465292840873347, 2.3524637791085397, 2.2313160210146408, 2.1042368438345154, 1.973713549893039], [1.881973105873551, 1.7522325438388726, 1.6257180031969927, 1.5048238696292633, 1.3917962292840305, 1.2886845849020268, 1.1972981224705013, 1.1191675360691637, 1.055513285317668, 1.0072210056807298, 0.9748246205990172, 0.9584975201746864, 0.9580519784470621, 0.9729467848467714, 1.0023028700036454, 1.0449265164622576, 1.0993395656391272, 1.1638158678865025, 1.2364230767906388, 1.315068765343446, 1.3975497433498996, 1.481603384709307, 1.5649597316963044, 1.6453931320043662, 1.7207721832956846, 1.789106808773149, 1.8485913645673522, 1.8976427835283916, 1.934932887693039, 1.9594141500435667, 1.970338351461775, 1.9672677568780863, 1.9500786210794467, 1.9189570248337995, 1.8743872311932122, 1.8171329353679806, 1.7482119548873565, 1.6688650656098865, 1.5805198296179055, 1.4847503796926662, 1.3832342190351712, 1.277707161910884, 1.1699175793684269, 1.0615811232428012, 0.9543370811680754, 0.8497074658964874, 0.7490598651765024, 0.653574975795336, 0.564219619793223, 0.48172589552792827, 0.4065769549192623, 0.33899972494014824, 0.27896471064177836, 0.226192833286486, 0.1801690751616495, 0.14016252696113243, 0.10525226868332149, 0.07435836496804793, 0.046277124460730935, 0.019719663460038023, -0.00664727047205413, -0.03415931695363914, -0.06411249465764286, -0.0977222982895689, -0.13608500356182537, -0.18014222593788132, -0.2306496949004463, -0.28815109670193545, -0.3529577077295609, -0.4251343910648292, -0.50449236431507, -0.590588971499232, -0.6827345101132818, -0.7800059810779613, -0.8812674487290294, -0.9851965249253911, -1.0903163301205894, -1.1950321389722387, -1.2976717924617411, -1.3965288557842166, -1.4899074240976415, -1.5761674286064218, -1.6537692747254993, -1.7213166528335304, -1.7775964002459081, -1.8216143596543128, -1.8526262728076635, -1.8701628663924224, -1.8740484270299451, -1.8644123206166636, -1.841693083995372, -1.8066348999003532, -1.760276454738282, -1.7039323683737395, -1.6391675709687572, -1.5677651794492318, -1.4916885909026565, -1.4130386580240257, -1.3340069389038232, -1.2568261167788208, -1.1837187622138576, -1.116845658568715, -1.0582549302482696, -1.009833201586432, -0.9732599724726252, -0.9499663259344089, -0.941098984501827, -0.9474906086400365, -0.9696370848112725, -1.007682386331279, -1.0614114110994026, -1.130251010853284, -1.2132792314364624, -1.3092425874247684, -1.416581002119699, -1.533459860080713, -1.6578084485256603, -1.7873639102584722, -1.9197196980450941, -2.0523774118040277, -2.1828008182652803, -2.3084707998851735, -2.426939957082207, -2.535885595840538, -2.6331598712221127, -2.716835925396838, -2.7852489547811703, -2.837031262423215, -2.8711404959180324, -2.8868804343574297, -2.8839138661281782, -2.8622672884173284, -2.8223273544501595, -2.7648291910166916, -2.690836901948977, -2.6017167581953684, -2.499103747506454, -2.3848623123219768, -2.261042239468761, -2.1298307764963855, -1.9935021342296835, -1.8543655913991757, -1.7147134437201228, -1.5767700359602534, -1.4426430815448235, -1.3142784110187724, -1.193419199858962, -1.0815706100240337, -0.9799706411807829, -0.8895678302368843, -0.8110062655804507, -0.7446181995772253, -0.6904243539605407, -0.6481418224599742, -0.6171992880693655, -0.5967590933759161, -0.5857455357744488, -0.5828786092715829, -0.5867122846216749, -0.5956763128985695, -0.6081204568752961, -0.6223600016876141, -0.6367213724285424, -0.6495866920635469, -0.6594361481344845, -0.6648871001667326, -0.6647289498330733, -0.6579529104195997, -0.6437759480380897, -0.6216583208591508, -0.5913143104807725, -0.5527159171322178, -0.5060894732394217, -0.45190531331621386, -0.39086081755684965, -0.32385731735751067, -0.2519715089755016, -0.17642216266072644, -0.09853303530775191, -0.019692991938055345, 0.058685587317034056, 0.13520899439655365, 0.2085438394428191, 0.27745703496425034, 0.34085304019107465, 0.39780735858042215, 0.4475953781407068, 0.48971576443600995, 0.5239077567652604, 0.5501618755366219, 0.5687237192956995, 0.5800907089094489, 0.5850018195278808, 0.584420523507733, 0.5795113448597374, 0.5716105934725996, 0.5621920011081727, 0.5528281170344167, 0.5451484356892272, 0.5407953190033101, 0.5413788396130482, 0.548431706487562, 0.5633654405078757, 0.5874289440315523, 0.6216705559538653, 0.6669046034640539, 0.7236833555175691, 0.7922751535783582, 0.8726493455921575, 0.9644684831048087, 1.0670880630298651, 1.1795639092055448, 1.3006670991790426, 1.4289061533262148, 1.5625560211441112, 1.699693227889437, 1.8382363879720351, 1.9759911535832575, 2.110698551421081, 2.2400855699975546, 2.3619167971936066, 2.4740458740969586, 2.5744655276392305, 2.6613549713155087, 2.7331235197519375, 2.788449347780864, 2.826312435980345, 2.8460208796750015, 2.847229893927362, 2.8299530193135616, 2.7945652180975395, 2.741797743302079, 2.6727248594273303, 2.588742688403847, 2.491540643031841, 2.383066088043349, 2.2654830316797017, 2.1411257943218525, 2.0124487217296987, 1.8819731058735505], [1.7912312227861529, 1.6642758588462234, 1.5421194878001998, 1.4270693703086772, 1.321254091549581, 1.226577889869022, 1.1446801566820388, 1.0769010391341307, 1.0242539309723462, 0.987405472267803, 0.96666349910277, 0.9619731944660901, 0.9729214960217262, 0.9987496198935973, 1.0383733669311588, 1.0904106937706606, 1.1532158598585391, 1.2249193076032194, 1.3034722996909178, 1.3866952285433063, 1.4723284305177522, 1.5580842837022844, 1.6416993442785492, 1.7209852829213352, 1.793877419328848, 1.8584797187490913, 1.913105207583082, 1.9563108834316596, 1.9869263353217805, 2.0040754487745303, 2.007190743884097, 1.996020078336361, 1.9706256367355917, 1.9313753180256328, 1.8789268194721365, 1.8142048940023698, 1.7383724232843056, 1.6527960976988378, 1.5590076226767688, 1.4586614756114107, 1.3534903161874279, 1.245259203612079, 1.1357197957229401, 1.026565696832536, 0.919390083751489, 0.8156466737345244, 0.7166150058505717, 0.623370890881431, 0.5367627472960219, 0.45739438564631457, 0.3856146348401056, 0.32151402545548474, 0.2649285620914579, 0.21545043333499111, 0.17244532890199862, 0.13507586339862898, 0.10233044924000954, 0.07305682151085074, 0.045999298475067375, 0.019838766035932917, -0.006765694887628203, -0.035134660628827204, -0.06652683192168685, -0.10209923468271116, -0.14287022795442963, -0.18968631972485703, -0.24319369277284109, -0.3038152208675818, -0.37173361364995905, -0.44688116993211296, -0.5289364479787191, -0.6173279819069127, -0.7112449902017925, -0.8096548401285463, -0.9113268551498221, -1.0148618858133198, -1.1187269121983099, -1.2212938117868974, -1.3208813139912619, -1.4157990744206823, -1.5043927405995325, -1.5850888478706386, -1.65643838054788, -1.7171578591963657, -1.7661668696575357, -1.802621031814897, -1.8259395141342698, -1.835826331085079, -1.8322848114499766, -1.8156247925502729, -1.7864622744353578, -1.7457114546779358, -1.694569253957246, -1.6344926303892378, -1.5671691618989567, -1.4944815462979115, -1.418466823862741, -1.3412712632130057, -1.2651019647242217, -1.1921763237062883, -1.1246705558711825, -1.0646685186305729, -1.0141120626481195, -0.974754118710128, -0.9481156660046384, -0.9354476406791438, -0.9376987301445162, -0.9554898617212186, -0.9890960371789979, -1.038435991301061, -1.1030699670147288, -1.182205706384863, -1.2747125605703764, -1.379143427483174, -1.4937640381083743, -1.6165889358348775, -1.7454233320259327, -1.8779098793751958, -2.0115792858157495, -2.1439035987899118, -2.272350924828267, -2.394440314220633, -2.5077955359586177, -2.6101964942074725, -2.699627093693684, -2.77431844620672, -2.8327864218397574, -2.873862683915487, -2.8967185024549034, -2.900880813743441, -2.8862401788147602, -2.853050486987477, -2.8019204472412493, -2.7337971054143844, -2.6499418141951536, -2.5518992610700577, -2.4414603224615528, -2.3206196562888226, -2.1915290666450638, -2.0564477702890547, -1.9176907629128876, -1.7775765220714754, -1.6383752923687755, -1.5022591768586318, -1.3712552072518935, -1.2472024857730633, -1.131714385423104, -1.0261466656693805, -0.931572210465232, -0.8487629287645755, -0.7781791785054074, -0.7199668878547488, -0.6739623569880295, -0.639704534541813, -0.6164543798087231, -0.6032207492550761, -0.5987920882795892, -0.6017730701623604, -0.6106252072702268, -0.6237103676241355, -0.639336065105556, -0.6558013554112652, -0.6714421631699043, -0.684674888483539, -0.6940371928892661, -0.6982249439654064, -0.6961244024655403, -0.686838863249785, -0.6697091081314513, -0.6443271913211335, -0.610543252294523, -0.5684652322157149, -0.5184515539225513, -0.4610970072742293, -0.397212256781764, -0.32779755247003933, -0.25401137372058885, -0.17713486566858666, -0.09853303530775191, -0.019613757087620663, 0.05821430660680711, 0.1335837375170056, 0.20520921544938284, 0.27192609437765697, 0.332725660203394, 0.3867861156305292, 0.43349844815249367, 0.47248646948040124, 0.5036204655139077, 0.527024061362093, 0.5430740817785139, 0.5523933692342808, 0.5558367051125466, 0.5544701595238392, 0.549544367447822, 0.5424623889274681, 0.5347429548012337, 0.5279800232856944, 0.5237996734380046, 0.5238154365335509, 0.5295832137281488, 0.5425569467666485, 0.5640461974043143, 0.5951767508152026, 0.6368552894985511, 0.6897390886973018, 0.7542115644217984, 0.8303643637513087, 0.9179865276346753, 1.0165610828547123, 1.12526923644612, 1.2430021572037213, 1.3683801396707727, 1.4997787608629296, 1.6353614635800737, 1.773117836895933, 1.9109067183880366, 2.0465031175553063, 2.177647858832406, 2.3020987682259655, 2.4176821817909917, 2.5223435381548347, 2.6141958315681784, 2.691564746256166, 2.7530293661556002, 2.7974574547361795, 2.8240344251189042, 2.8322852681093065, 2.82208887149901, 2.79368434404211, 2.7476691475098716, 2.6849890355449264, 2.6069199939139263, 2.5150425684155504, 2.4112091494559724, 2.297504951688576, 2.176203578982978, 2.049718195621047, 1.92054943081376, 1.7912312227861575], [1.7022556180229278, 1.5791537050124511, 1.4623714648020056, 1.354109524681911, 1.2563609802560998, 1.1708687230047579, 1.0990885160613284, 1.042158665681596, 1.0008769782474554, 0.9756855185820977, 0.96666349910277, 0.9735284354441632, 0.995645507375604, 1.032044868901797, 1.081446463122622, 1.142291720307912, 1.2127813560139138, 1.2909183438399452, 1.3745550180256434, 1.4614431673854535, 1.5492859162962733, 1.6357901521358607, 1.7187182525263471, 1.795937890035714, 1.8654687459506352, 1.9255250469477705, 1.9745529468558487, 2.011261907475131, 2.0346493842907343, 2.044018291078847, 2.0389868976634196, 2.019491002948987, 1.9857784161681675, 1.938395968313211, 1.878169458297528, 1.806177110014169, 1.7237172729042778, 1.6322712360868046, 1.533462141179203, 1.4290110688691575, 1.3206914369230782, 1.2102828811666855, 1.09952579529494, 0.9900776801497384, 0.8834723990680399, 0.7810833544926444, 0.6840914943763006, 0.5934589277481155, 0.5099087804584541, 0.4339117583583595, 0.3656797101655187, 0.30516630045952375, 0.25207471923740415, 0.20587217289745205, 0.16581072698897215, 0.13095390796918693, 0.10020832365512974, 0.07235943376200836, 0.04611049610639699, 0.020123633380578838, -0.006938088103456908, -0.036368701307437176, -0.06937863248856319, -0.10705634271691677, -0.1503333519699897, -0.19995359299253607, -0.25644792983473735, -0.3201145421649463, -0.3910057244791963, -0.4689214830417245, -0.5534101369949767, -0.6437759480380904, -0.7390936199991428, -0.8382293301588312, -0.9398677828758703, -1.0425446172715578, -1.144683358497735, -1.2446359800727804, -1.340726046056642, -1.4312933289988627, -1.5147387545388276, -1.5895685074764148, -1.6544361475504696, -1.7081816258106344, -1.7498661633606496, -1.7788020516951686, -1.7945765554862214, -1.7970692415287213, -1.7864622181195011, -1.7632429434636698, -1.728199445466235, -1.682407983921327, -1.6272133749689734, -1.5642023820477766, -1.4951707528291538, -1.422084643389564, -1.3470373150997061, -1.2722021127498981, -1.1997828311705037, -1.1319626495231132, -1.0708528556682064, -1.018442596399825, -0.9765508724550447, -0.9467819503793807, -0.9304852876231695, -0.9287209644370138, -0.9422314886768198, -0.9714206905828137, -1.0163402575614178, -1.0766842780215982, -1.1517919727954167, -1.2406585972442223, -1.3419543015827282, -1.4540505460177164, -1.5750534856639689, -1.7028435723105806, -1.8351204700779329, -1.9694522535062606, -2.1033277528034096, -2.2342108344017255, -2.3595953575158237, -2.47705953022621, -2.5843184021681593, -2.6792732748597623, -2.7600568839909565, -2.8250733088335274, -2.8730316898612616, -2.9029729836190157, -2.9142891502389126, -2.906734349712797, -2.8804279136848, -2.835849055477929, -2.7738234775398833, -2.695502227703123, -2.602333338929055, -2.4960269570966593, -2.378514813786347, -2.2519050322191143, -2.1184333613823347, -1.9804120133534506, -1.8401773300307396, -1.7000375267171124, -1.5622217508375706, -1.4288316548110762, -1.3017966137908201, -1.1828336233939414, -1.0734127920924554, -0.9747292006690847, -0.8876817406237357, -0.8128593686613252, -0.7505350297544677, -0.7006673113449857, -0.6629097007368103, -0.6366271313538023, -0.6209193258902723, -0.6146502798434487, -0.616483081524406, -0.6249191380007048, -0.6383407736096429, -0.655056091175799, -0.6733449376898542, -0.6915047970724755, -0.7078954431404995, -0.720981225656646, -0.7293699302913295, -0.7318472476676672, -0.7274060049534476, -0.7152694526667245, -0.6949080559177194, -0.6660494092321393, -0.6286810730758805, -0.5830463136929127, -0.5296329112357038, -0.4691553797786906, -0.4025311121533224, -0.330851118359553, -0.2553461646694518, -0.17734923796307422, -0.09825535337329828, -0.01947979061741422, 0.057584116226971405, 0.131606500267745, 0.20136067811194108, 0.26575999174872683, 0.3238907816302528, 0.3750405969812239, 0.4187208728050285, 0.45468344640352565, 0.48293044586425765, 0.5037172548552625, 0.5175484378552055, 0.5251666930842093, 0.527535082248973, 0.5258129621629054, 0.5213262088798446, 0.5155324759754096, 0.5099823611716785, 0.5062774662346646, 0.5060264211296257, 0.5108000025612224, 0.5220865076904908, 0.5412485451566837, 0.5694823774212098, 0.6077808915129088, 0.6569011908315222, 0.7173376907929598, 0.7893014684499373, 0.8727064640442532, 0.9671629644862226, 1.0719786191589664, 1.1861670516563818, 1.3084639417185175, 1.43735026443662, 1.5710821934282877, 1.7077270056396707, 1.845204171952248, 1.981330683716964, 2.1138695540951913, 2.24058034748301, 2.3592705325326695, 2.4678464258792725, 2.564362495424228, 2.647067823969591, 2.714448595443047, 2.7652655554762027, 2.7985855135779825, 2.8138060928158333, 2.810673091439258, 2.789289995417681, 2.750119367182357, 2.6939760294284802, 2.6220121589323075, 2.5356945991841027, 2.4367748874956807, 2.327252667540978, 2.2093333177394383, 2.0853807655875958, 1.957866574559644, 1.8293164806727298, 1.702255618022929], [1.6157990654621017, 1.4975862542772123, 1.387148638563373, 1.2865616060576783, 1.1976659204896027, 1.1220284090695984, 1.0609089265184801, 1.0152343519120763, 0.9855802067412424, 0.9721603007351358, 0.974824620599017, 0.9930654805414246, 1.0260317570899076, 1.0725508389984821, 1.1311577406934519, 1.2001306591130687, 1.2775321030540758, 1.3612545948852066, 1.4490698398323976, 1.5386801804834498, 1.627771105532111, 1.7140635632007755, 1.7953648416244532, 1.8696168203748649, 1.934940468142373, 1.9896755595542608, 2.032414706705981, 2.0620309451297683, 2.077698276010694, 2.0789047424362788, 2.065457802950844, 2.0374819560730217, 1.995408760006462, 1.9399595778182206, 1.8721215552876336, 1.793117502088533, 1.7043704929510208, 1.6074641303906316, 1.5040995114581428, 1.3960500153239082, 1.2851150746023647, 1.1730741100895583, 1.0616417957060242, 0.9524257783265646, 0.8468879069830906, 0.7463099294917179, 0.6517644943778205, 0.5640921551388204, 0.4838849159915242, 0.41147668731693193, 0.3469408393789049, 0.2900948591031632, 0.24051193140659438, 0.1975390883913835, 0.16032140115694662, 0.12783153428094587, 0.09890384607140341, 0.07227210193744754, 0.04660977657244125, 0.02057185538733612, -0.007162991594925501, -0.03785099844691811, -0.07264376883502136, -0.11255168301509884, -0.15841123420223188, -0.2108571799630778, -0.2703002692429808, -0.33691116096032314, -0.4106109894389254, -0.4910688593713993, -0.5777063728802924, -0.669709108131452, -0.7660447874955953, -0.8654876980530555, -0.9666487627436893, -1.0680105108653895, -1.1679660657377404, -1.2648611585237381, -1.357038093244763, -1.4428805311137944, -1.5208579339559758, -1.5895685074764145, -1.6477795155304469, -1.694463895672574, -1.7288321927066757, -1.7503589386451526, -1.7588027416855854, -1.7542195002387817, -1.7369683269130598, -1.7077099475031874, -1.6673975269853203, -1.6172600636382755, -1.558778678988601, -1.4936563106570326, -1.4237814828797357, -1.3511869812827662, -1.2780043905799146, -1.206415562901776, -1.1386021676697777, -1.0766945291598944, -1.0227209837014377, -0.9785589840960149, -0.9458891443347109, -0.9261533537958244, -0.9205179983071657, -0.929843207932884, -0.9546589109104573, -0.9951483132038687, -1.0511392475259438, -1.1221036486796878, -1.2071652182255936, -1.305115145524457, -1.4144355589173125, -1.5333301949097273, -1.6597615992762613, -1.7914940162525599, -1.9261409843053166, -2.061216542743103, -2.1941888654607045, -2.3225350785616965, -2.4437959889488483, -2.5556294519488603, -2.6558611376356973, -2.7425315169754776, -2.813937978743207, -2.8686711041726003, -2.9056442656670303, -2.9241158752257403, -2.923703783638999, -2.904391518702442, -2.866526245131377, -2.8108085257829933, -2.738274158423757, -2.650268549876975, -2.548414265394519, -2.4345725512492944, -2.310799768967398, -2.1792997969262036, -2.0423735464232977, -1.902366802599822, -1.7616176343006507, -1.622404620323592, -1.4868971125477495, -1.357108699880442, -1.2348549522926557, -1.1217164135843918, -1.019007677728366, -0.9277532300437172, -0.8486705648918245, -0.7821609102921621, -0.7283077013351844, -0.6868827531983662, -0.6573598956801538, -0.638935649119454, -0.6305563508497528, -0.6309509861403346, -0.6386688417007789, -0.6521209865789882, -0.6696244974072554, -0.6894482845482064, -0.7098593441769371, -0.7291682593987997, -0.7457728010964794, -0.7581985355415704, -0.7651354293939987, -0.765469551369928, -0.758309100784656, -0.7430041430189559, -0.719159596895968, -0.6866411947992255, -0.6455743186535727, -0.5963357990164962, -0.5395389458363881, -0.47601225335175373, -0.4067723837482706, -0.3329921804768721, -0.25596458888666324, -0.1770634658575731, -0.09770233881920903, -0.01929222594439449, 0.056800347873304784, 0.12929401097061102, 0.1970307877978516, 0.25901089509589387, 0.31442315154220934, 0.36267017503518967, 0.4033876770726802, 0.4364573168365733, 0.4620127447448915, 0.4804386421456286, 0.49236274602385127, 0.4986410304596795, 0.5003363954732231, 0.4986913842821418, 0.49509560754615295, 0.4910486938659295, 0.4881197060459097, 0.4879040593344981, 0.4919790485211109, 0.5018591335472851, 0.5189521470254532, 0.5445175713273466, 0.5796279880157189, 0.6251347293909272, 0.6816386625566278, 0.7494669130887848, 0.82865619113554, 0.9189432211286852, 1.0197626012384444, 1.1302522345837034, 1.2492662855873822, 1.3753954264311432, 1.5069939550117175, 1.642213191717604, 1.77904040209128, 1.9153423500443671, 2.048912465344927, 2.1775205126661095, 2.2989635800416344, 2.411117163921114, 2.5119851172538734, 2.5997472465128335, 2.6728033929130066, 2.7298129111569716, 2.769728564015151, 2.79182398041802, 2.795713975390788, 2.7813671984591095, 2.7491107590166894, 2.699626668151913, 2.633940131928747, 2.5533999263377405, 2.4596512743071486, 2.3546018256413497, 2.2403815071146127, 2.1192971581172784, 1.9937829935926725, 1.8663480374151549, 1.7395217433482035, 1.6157990654621028], [1.5325930266603751, 1.4202636041834182, 1.317087428232997, 1.224997100393322, 1.145665499015531, 1.0804701592199284, 1.0304644046574862, 0.9963558897034513, 0.978493034062517, 0.9768596436650815, 0.9910778168107022, 1.020419037515737, 1.0638231637421183, 1.1199248313474728, 1.1870866197407894, 1.26343816659142, 1.3469202803590177, 1.4353329842276445, 1.5263863360003547, 1.6177528077563383, 1.7071199780093762, 1.792242288420297, 1.8709906467461204, 1.9413987168480227, 2.0017048236980064, 2.0503885142034735, 2.086200950462403, 2.108188467363764, 2.115708797377864, 2.1084396476820415, 2.086379503909418, 2.0498407261040383, 1.9994351911838233, 1.9360529176967076, 1.860834278438625, 1.775136560418053, 1.6804957659374573, 1.5785846599498516, 1.4711681546477693, 1.360057180403702, 1.2470622213490081, 1.1339476934211703, 1.02238831273542, 0.9139285434901185, 0.8099461288543512, 0.7116205976424071, 0.619907506903253, 0.5355190292384366, 0.45891132756455527, 0.3902789833750275, 0.32955656180655485, 0.2764272126001826, 0.23033802501629813, 0.19052168148247034, 0.1560237935864092, 0.12573515902819837, 0.0984280529594715, 0.07279556490392214, 0.047492915734530336, 0.021179639895204803, -0.00743850257672616, -0.039569011142722856, -0.07629461643007926, -0.11853876251166487, -0.1670355321121879, -0.22230483135678186, -0.28463351393792247, -0.3540629702581467, -0.4303835391161034, -0.5131359220955864, -0.6016195984849037, -0.694908055917719, -0.7918704736185876, -0.8911993256842816, -0.9914432155450655, -1.0910441136115632, -1.1883780516795313, -1.2817982329780777, -1.3696794482551284, -1.4504626477923166, -1.5226985078241477, -1.5850888478706393, -1.6365248026068626, -1.6761207269864966, -1.7032429146053265, -1.7175323342719093, -1.718920735384951, -1.7076396354163024, -1.6842218785465004, -1.6494956389436195, -1.6045709307361442, -1.5508188747141454, -1.4898441545111754, -1.423451267903433, -1.3536053375784876, -1.2823883862804994, -1.211952100082558, -1.144468197649108, -1.0820775903198268, -1.0268395559240138, -0.9806821573876351, -0.9453551151267726, -0.9223862903816066, -0.9130428562211006, -0.9182981258344893, -0.938804876478957, -0.9748758552298576, -1.0264719831601377, -1.093198591870753, -1.1743098348470629, -1.26872122059224, -1.375030019660195, -1.4915431083389363, -1.6163116324551294, -1.7471717099732331, -1.881790244790283, -2.0177147999704674, -2.152426379674965, -2.2833938976594292, -2.4081290681970535, -2.5242404436841976, -2.629485342297515, -2.7218184584457226, -2.799436027201641, -2.8608145195073607, -2.9047429751471427, -2.9303482321083867, -2.9371124803054025, -2.9248827505964283, -2.8938721421228664, -2.844652787561033, -2.7781407521148607, -2.6955732532188446, -2.5984787693188225, -2.4886407733523086, -2.3680559756098676, -2.2388880879252793, -2.103418223554912, -1.9639931222199642, -1.822972435827004, -1.6826763262971658, -1.545334612408294, -1.413038658024032, -1.2876971207204495, -1.1709965795051227, -1.064367935595255, -0.9689593342169509, -0.8856161917616375, -0.8148687354689471, -0.7569272765060986, -0.7116852465039657, -0.6787298370143946, -0.6573598956801538, -0.6466105567338538, -0.6452839210952033, -0.6519849567943088, -0.6651616672384434, -0.6831484759492615, -0.7042117042036897, -0.7265959742227817, -0.748570356164967, -0.7684730924560459, -0.7847537774498364, -0.7960119428556602, -0.8010310978907925, -0.7988073951686018, -0.7885722357846231, -0.7698082862760091, -0.7422585520555739, -0.7059283321986052, -0.661080064525732, -0.6082212531270675, -0.5480858481893502, -0.48160961574022004, -0.4099001884897184, -0.33420262446764254, -0.2558614142235053, -0.17627996711340937, -0.09687867039885377, -0.0190526499505692, 0.05586963258073846, 0.12666583433147086, 0.19225617733846928, 0.25173590483084207, 0.3044028703739601, 0.34977950915976996, 0.38762858672969447, 0.4179622820830983, 0.441044335372647, 0.4573851708304071, 0.4677300886339999, 0.47304080046949415, 0.4744707579829653, 0.4733348867030731, 0.47107448620351217, 0.4692181864747109, 0.4693399573792556, 0.4730152499216316, 0.4817764027412358, 0.4970684732893851, 0.520206649842576, 0.5523363678379819, 0.59439719273127, 0.6470914431281077, 0.7108584144692398, 0.7858549278255138, 0.87194277371647, 0.9686834511172977, 1.0753404211628097, 1.1908889079733178, 1.3140330901673352, 1.443230340694087, 1.5767219942596702, 1.7125699552982065, 1.8486983093312412, 1.9829389704477427, 2.1130802908182478, 2.236917477356164, 2.352303607942119, 2.4572000164288843, 2.5497248226127835, 2.628198420414661, 2.691184803839686, 2.7375277043345663, 2.7663806327006726, 2.777230060886452, 2.769911140343961, 2.744615530284543, 2.7018910968173016, 2.642633438032783, 2.5680693858700745, 2.479732828296366, 2.37943338022152, 2.2692186041395788, 2.151330637503733, 2.0281582194743275, 1.9021852215977488, 1.775936872424433, 1.6519249229505282, 1.5325930266603793], [1.4533414623571634, 1.3478399393397524, 1.252780583353324, 1.169936871265012, 1.100799662930009, 1.046545575054794, 1.008012524909592, 0.9856829993886064, 0.9796754208991236, 0.9897437888042713, 1.0152855783432222, 1.0553576828974751, 1.1086999949311567, 1.1737660405365329, 1.248759916639794, 1.331678632582733, 1.420358832550239, 1.5125267751725766, 1.6058503739858287, 1.697992058996628, 1.786661206361147, 1.869664900402801, 1.9449558393589697, 2.0106762721293534, 2.0651969559583265, 2.1071502518261576, 2.135456622164387, 2.149343960652505, 2.1483593621815236, 2.132373128153063, 2.101574993481855, 2.056462752255169, 1.9978236442705102, 1.9267090400610836, 1.844403123220194, 1.7523864119057277, 1.6522950828575567, 1.5458771581525006, 1.4349466849283032, 1.3213370797789077, 1.20685482152064, 1.0932346583514418, 0.982097448611458, 0.8749116796673095, 0.7729596088411319, 0.6773088463892551, 0.5887900564820805, 0.5079812916215619, 0.43519930303631726, 0.37049798870006295, 0.31367395630320577, 0.26427899542467637, 0.22163907591832138, 0.18487932260857412, 0.1529542639820958, 0.12468251849420307, 0.09878496974435981, 0.07392539392786615, 0.0487524418357282, 0.02194184477222277, -0.007762290101282748, -0.041508204230035525, -0.08030028745105577, -0.12496692780489024, -0.1761332802370003, -0.23419969486273892, -0.29932639818357604, -0.3714248579904791, -0.4501560887932829, -0.5349359738781818, -0.6249474970993408, -0.7191595968959685, -0.816352181377266, -0.9151466810481056, -1.0140413689896877, -1.1114505508080217, -1.2057466216855153, -1.2953039081218019, -1.3785431595040738, -1.4539755308963827, -1.5202449040555495, -1.5761674286064216, -1.6207672287438644, -1.6533073112598609, -1.6733148259286195, -1.6805999665026397, -1.6752679564044304, -1.6577237337953052, -1.6286691318410376, -1.589092537177648, -1.5402511981523264, -1.483646539672216, -1.4209930188069881, -1.3541812202168093, -1.2852360388697182, -1.2162709256282023, -1.1494392758742387, -1.086884119733427, -1.0306873226226938, -0.9828195254486684, -0.9450920442201943, -0.9191119092484968, -0.9062411553753376, -0.9075613783972575, -0.9238444513307631, -0.9555301503041334, -1.0027112771378124, -1.065126688029672, -1.1421624495106226, -1.2328611485651788, -1.3359391882609395, -1.4498117081794073, -1.5726245850879368, -1.7022927981427698, -1.836544288664872, -1.9729683109708214, -2.1090671611552447, -2.242310087808502, -2.370188134461447, -2.490268639423771, -2.600248125233288, -2.69800234701967, -2.781632335818154, -2.849505367632166, -2.9002899095366863, -2.932983737406002, -2.9469345824505653, -2.941852841697999, -2.917816076517252, -2.8752652186600054, -2.814992600322658, -2.738122118621091, -2.6460820309055593, -2.5405710510073307, -2.4235185735929012, -2.297039990507381, -2.1633881760220155, -2.0249023045527648, -1.8839552226286236, -1.7429006253042565, -1.6040212852073428, -1.469479550112741, -1.3412712632130035, -1.2211841706998903, -1.110761766158246, -1.0112733835007892, -0.9236911931914502, -0.8486745842339394, -0.7865622311275162, -0.7373719552633096, -0.7008082987504299, -0.6762775401532238, -0.6629097007368109, -0.6595869210056489, -0.664977434718046, -0.6775742348956584, -0.6957374168452176, -0.7177390995113535, -0.7418097705785586, -0.7661848739353653, -0.7891504609755922, -0.8090867595709098, -0.8245085755015283, -0.8341015290622857, -0.8367532421832609, -0.8315787258196053, -0.8179393701370316, -0.7954551072569223, -0.7640094937834901, -0.7237476435203505, -0.6750671250658531, -0.6186021197046243, -0.5552013076331671, -0.485900110725449, -0.4118880637342058, -0.33447220942797, -0.2550375135843155, -0.17500537048449558, -0.09579131671978268, -0.018763089557255485, 0.054799844621801035, 0.12374420591395446, 0.1870772420988164, 0.2439965706631846, 0.29391471423841486, 0.33647766022136055, 0.37157693081144266, 0.39935481850621385, 0.4202026199791217, 0.4347518837087395, 0.44385886911357414, 0.44858259264360045, 0.45015700477569615, 0.4499579968691588, 0.4494660744081626, 0.4502256497726964, 0.4538020003433692, 0.4617370040609612, 0.47550480279004603, 0.4964685529411025, 0.5258394024803579, 0.5646387841320639, 0.6136650374128321, 0.673465268990713, 0.744313234246089, 0.8261938759327188, 0.918794992116701, 1.0215063291566888, 1.1334262107535076, 1.2533756256325397, 1.3799195089221965, 1.5113947704370356, 1.6459444514161585, 1.7815572341134216, 1.9161113899437576, 2.0474221351659434, 2.1732912712971504, 2.291557922966658, 2.400149150411787, 2.497129208271036, 2.580746246971261, 2.6494753073242037, 2.7020565416955065, 2.7375277043345663, 2.755250086546643, 2.754927226146341, 2.736615891335764, 2.7007290226586256, 2.6480305085288536, 2.5796218653415037, 2.4969210875709695, 2.4016341217923385, 2.2957195966101756, 2.181347603680622, 2.060853469361204, 1.936687578472324, 1.811362408202367, 1.6873979989548182, 1.5672671282182613, 1.4533414623571645], [1.3787148766482227, 1.2809279967228833, 1.1947721689312236, 1.1218467531262184, 1.0634479975083477, 1.0205416739072863, 0.9937432403370577, 0.9833059784491442, 0.9891173637233881, 1.0107037304546844, 1.047243096579872, 1.0975858199367892, 1.160282572358161, 1.2336189455724857, 1.3156558473912083, 1.4042747118655503, 1.4972264362448702, 1.5921828733180117, 1.6867896520695664, 1.7787190738301413, 1.865721835802741, 1.945676368816774, 2.0166346404638475, 2.0768633667527183, 2.1248796927538867, 2.159480542437039, 2.1797649965408836, 2.1851492308996914, 2.175373731868882, 2.150502695774532, 2.110915710950334, 2.057292009188672, 1.9905877536826426, 1.912006998344299, 1.8229671046406735, 1.7250595331025338, 1.6200070342511315, 1.5096183452641005, 1.3957415523239778, 1.2802173030218567, 1.164833047913869, 1.0512794555799214, 0.9411100822764552, 0.8357052871814155, 0.7362412696393399, 0.6436649686741117, 0.5586754108256767, 0.4817119240094098, 0.41294945686413226, 0.35230105945799295, 0.299427396898377, 0.25375298699108156, 0.21448868115835346, 0.18065974867896523, 0.15113878195343733, 0.1246825184942031, 0.0999715767485615, 0.0756520301444835, 0.050377698715276385, 0.022852021420228734, -0.008131614779621953, -0.04365217125784234, -0.08462689210852616, -0.13178179370761556, -0.18562750751075519, -0.2464411345531988, -0.3142546135306174, -0.3888499347307571, -0.469761353753012, -0.5562845764164663, -0.6474927041453283, -0.7422585520555742, -0.8392827844458898, -0.9371271586818474, -1.0342520324736275, -1.129057174762065, -1.2199248297940701, -1.3052639198318068, -1.3835542359835562, -1.4533894598453339, -1.5135178812483314, -1.562879728927726, -1.6006401101467178, -1.626216660312907, -1.6393011318493749, -1.6398742998807627, -1.6282137270073114, -1.604894106490713, -1.570780088171711, -1.5270116797789353, -1.4749825032765447, -1.4163113668627705, -1.3528077836396069, -1.2864322235456525, -1.2192520219579717, -1.1533939829614854, -1.090994804735142, -1.0341505165109985, -0.9848661494974583, -0.9450068671109817, -0.9162517526612269, -0.900051395858107, -0.8975903344638135, -0.9097552961070835, -0.9371100503725474, -0.9798775260235782, -1.0379296763693031, -1.1107853915178174, -1.1976165640535166, -1.2972622192252083, -1.408250426808723, -1.5288275241581208, -1.6569940031812223, -1.790546252404, -1.9271232028938827, -2.064256807095732, -2.1994251855466, -2.3301072103000413, -2.453837257348572, -2.5682588543006837, -2.6711759742163377, -2.760600781251061, -2.8347967172843322, -2.892315928990364, -2.932030169168707, -2.9531544613213776, -2.955262988664262, -2.9382968538011083, -2.902563548661885, -2.848728171306085, -2.777796622021684, -2.6910912010496877, -2.5902192096197045, -2.477035320442955, -2.3535986293944062, -2.222125423310903, -2.0849387966764077, -1.944416320123378, -1.8029370044973994, -1.662828814781509, -1.5263179682706145, -1.3954812015887774, -1.2722021127498986, -1.1581325794733905, -1.0546601260295048, -0.9628819612372848, -0.8835862436090074, -0.8172409501765753, -0.763990537703107, -0.7236603934303976, -0.6957688819744472, -0.6795466101559767, -0.6739623569880296, -0.6777549560212281, -0.6894702756816151, -0.7075023235723652, -0.730137405843737, -0.7556002049374928, -0.7821005998770112, -0.8078800436801984, -0.8312563325594079, -0.8506656507417061, -0.8647008516707864, -0.8721450390263954, -0.8719996367662266, -0.863506283036435, -0.8461620445964728, -0.8197276222508718, -0.7842283992702853, -0.7399483693273491, -0.6874171634125463, -0.6273905719205223, -0.5608251241611618, -0.4888474387783931, -0.41271919115764005, -0.3337986545471018, -0.2534998575413206, -0.17325045963507416, -0.09444947728615408, -0.018425994576408356, 0.05360003488670967, 0.12055384401652662, 0.18153779821451538, 0.23585837086206832, 0.2830474176824278, 0.32287716788113885, 0.3553685135904505, 0.3807923536677535, 0.3996639289075337, 0.41273026863135437, 0.42095104878156686, 0.42547333448767677, 0.42760084120565356, 0.42875849384656267, 0.4304531891018107, 0.4342317692146105, 0.44163729308578, 0.4541647408159325, 0.4732173092410619, 0.500064448100051, 0.5358027493026326, 0.581320736200838, 0.637268507375596, 0.7040330724776476, 0.7817200789733847, 0.8701424716558215, 0.9688164553676865, 1.0769649497960083, 1.1935285379464815, 1.317183721654396, 1.44636811293534, 1.5793120137396075, 1.7140756731701037, 1.8485913645673564, 1.980709298762065, 2.108246287446488, 2.229035994641003, 2.3409795666026287, 2.4420954125109904, 2.5305669204164194, 2.6047869350418713, 2.6633978951503, 2.70532662665869, 2.7298129111569716, 2.7364310950101562, 2.7251041682717365, 2.6961099212390787, 2.6500789752947527, 2.587984679100471, 2.5111250564961067, 2.421097183830016, 2.319764557222767, 2.2092181799634036, 2.0917322526904436, 1.9697154804709176, 1.8456591181251027, 1.7220829555056432, 1.601480495940161, 1.4862646024029473, 1.3787148766482238], [1.3093446442175654, 1.220093881645348, 1.1435529624018124, 1.0811336101374212, 1.0339265147418355, 1.002678460548012, 0.9877772755442924, 0.9892449375578265, 1.006738979426489, 1.0395621380254758, 1.086679996455427, 1.1467461794858749, 1.2181344840767157, 1.2989771637949774, 1.387208442150121, 1.4806122087590385, 1.576872756732667, 1.6736273520288432, 1.768519387333538, 1.8592508651819961, 1.9436329776337402, 2.019633602243853, 2.0854206149683803, 2.1394000279476013, 2.1802480911246502, 2.206936648097824, 2.2187512046949, 2.2153013493169627, 2.1965233526482426, 2.162674966200648, 2.1143226296183495, 2.052321481015648, 1.9777887383288724, 1.8920711784720288, 1.7967075811171547, 1.6933871217687002, 1.5839047916199018, 1.4701149872489874, 1.3538844499971503, 1.237045742050824, 1.121352423748478, 1.0084370451070017, 0.8997729853966009, 0.7966410698539617, 0.7001017650138605, 0.6109736069264754, 0.5298183534633272, 0.4569331771390032, 0.3923500328147874, 0.3358421499044096, 0.2869374159312751, 0.2449382420938195, 0.20894733631165413, 0.17789865919846698, 0.15059270729991106, 0.12573515902819826, 0.10197783473987503, 0.0779608654300698, 0.05235493596453672, 0.023902469332920916, -0.0085433519578437, -0.045982773294931896, -0.08923782536927725, -0.13892570337054172, -0.19543788847452973, -0.2589255823090654, -0.329291860522116, -0.4061907764448207, -0.48903346458224767, -0.5770011108726135, -0.6690644769694345, -0.7640094937834897, -0.8604682795462826, -0.956954793798446, -1.0519042146383815, -1.1437150254679538, -1.2307927219488857, -1.3115940019020693, -1.384670281719022, -1.4487093930654626, -1.5025743530594557, -1.5453381687865877, -1.5763137313463804, -1.5950779733113063, -1.601489603610875, -1.5956998919744743, -1.578156147266575, -1.5495977160552015, -1.5110445150430547, -1.4637782988929828, -1.409317048801869, -1.3493830423172897, -1.285865326952718, -1.220777465058571, -1.1562115414844298, -1.0942895256674503, -1.0371131533375295, -0.986713538127312, -0.9450017388030769, -0.9137214931109121, -0.8944052846277013, -0.8883348355238657, -0.8965070175064878, -0.9196060478139928, -0.9579826899891959, -1.0116410138213903, -1.080233089330322, -1.1630618003322655, -1.2590917685971277, -1.3669681846275512, -1.485043150436267, -1.6114089580380915, -1.743937559164125, -1.880325331080626, -2.0181421140584623, -2.1548833911792817, -2.28802440337071, -2.4150749437646546, -2.533633556889519, -2.64143988031895, -2.7364239089357296, -2.8167510339119772, -2.8808618081198967, -2.9275055145551456, -2.9557667614443077, -2.965084493441589, -2.9552629886642614, -2.926474601881444, -2.8792542103178325, -2.814485515489869, -2.7333795474659097, -2.6374459022450405, -2.5284574141075744, -2.408409118656517, -2.27947249512388, -2.1439460851581433, -2.0042036671364682, -1.8626412181153482, -1.7216239186128435, -1.5834344480086913, -1.4502237807094167, -1.3239656263495507, -1.2064155629017816, -1.099075792033898, -1.0031663043806698, -0.9196030821344582, -0.8489837914907863, -0.7915812323575521, -0.7473446219358963, -0.7159085970250204, -0.6966096319223044, -0.6885093892111585, -0.6904243539605394, -0.70096095198323, -0.7185552234682219, -0.74151601765161, -0.7680705947609004, -0.7964114701434287, -0.8247433134513749, -0.8513287234539599, -0.8745317361896909, -0.8928579897344665, -0.9049905611140062, -0.9098206074388081, -0.9064720811923427, -0.8943199452376518, -0.873001482566115, -0.8424204747975712, -0.802744207426382, -0.7543934441483617, -0.6980256926529428, -0.6345122554921954, -0.5649097177407015, -0.49042666417004377, -0.41238653904592987, -0.33218765840411696, -0.2512614553604416, -0.17103008190503752, -0.09286450466676578, -0.018044216984102992, 0.05228035430874336, 0.11712174054449487, 0.17568471188745427, 0.2273901582803881, 0.27189292295237016, 0.30909309845859617, 0.33914046561079986, 0.3624319344198618, 0.37960202877821214, 0.39150663842670086, 0.3992004381638938, 0.4039085407827802, 0.4069931026234202, 0.4099157350237398, 0.4141966878975771, 0.4213718602672873, 0.4329487545344798, 0.4503625249600867, 0.4749332753248098, 0.5078257358660242, 0.5500123958868172, 0.6022410871811328, 0.6650079065829837, 0.738536236139322, 0.8227624698179438, 0.9173288899880374, 1.0215839592553513, 1.1345901080093348, 1.2551389098570656, 1.3817733506730485, 1.512816716948479, 1.6464074599905598, 1.7805392385557386, 1.913105207583081, 2.0419455082466733, 2.16489682743784, 2.279842835265543, 2.3847642787953696, 2.47778750988147, 2.5572302546895465, 2.621643491725003, 2.6698483924998997, 2.7009673923307176, 2.714448595443047, 2.710082875275303, 2.6880132038273437, 2.6487359288900847, 2.5930939105130326, 2.5222616234201674, 2.437722525494584, 2.34123917918357, 2.2348167881503125, 2.120660971408374, 2.001130737589829, 1.8786877394592965, 1.7558429803980493, 1.6351022080768052, 1.5189112643340785, 1.409602663527043, 1.309344644217569], [1.2458176686219353, 1.1658522782484468, 1.0995563014292793, 1.0481418939112088, 1.0124849797332969, 0.9931070658451844, 0.9901651052930717, 1.0034496304331848, 1.0323911811657078, 1.076074856330022, 1.1332626239515446, 1.2024228426576373, 1.2817662767353997, 1.3692877351029298, 1.4628123335869616, 1.5600452734963761, 1.6586239501019409, 1.75617115416114, 1.8503481092342926, 1.9389060976563135, 2.0197354683390696, 2.090910889023223, 2.150731802402266, 2.197757167262139, 2.230833709365921, 2.2491170686804947, 2.2520854056639967, 2.2395452153385227, 2.211629289157502, 2.168786956515593, 2.111766925412321, 2.041593220653629, 1.959534883670711, 1.867070246501451, 1.7658467201012142, 1.6576371408360373, 1.5442937962729748, 1.427701300391438, 1.3097295079740559, 1.19218764780698, 1.0767808147801075, 0.9650698931116957, 0.8584358885167432, 0.7580495286402941, 0.6648468515271334, 0.5795113448597375, 0.5024630281582815, 0.43385469042137115, 0.3735753113370859, 0.32126050986187604, 0.2763096842926626, 0.23790933746343762, 0.20506192366311288, 0.1766194142334914, 0.15132066006018746, 0.12783153428094593, 0.10478676986785233, 0.08083236599334914, 0.0546674252616709, 0.025084301245624965, -0.00899401815310708, -0.04848029239346125, -0.09409407665145259, -0.1463382160852653, -0.20548142286612234, -0.2715474140530501, -0.3443109172440919, -0.4233006717649526, -0.5078093705026473, -0.5969103059907875, -0.6894803086122315, -0.7842283992702854, -0.8797294278033515, -0.9744618356327077, -1.0668485700351364, -1.1553000908759634, -1.238258350864557, -1.3142405989738801, -1.3818818544585325, -1.4399749260394805, -1.4875069066894029, -1.523691157719445, -1.5479939045153122, -1.5601546976375014, -1.560200143851929, -1.548450478263804, -1.525518726958136, -1.4923023949737506, -1.4499678024343847, -1.3999273775355097, -1.343810394187105, -1.2834278099468408, -1.220732012221685, -1.157772413721475, -1.0966479484400344, -1.0394576041998764, -0.9882501848339441, -0.9449745228849655, -0.9114313614928756, -0.8892280918692865, -0.8797374711248187, -0.8840613556480039, -0.903000369855025, -0.9370302917010324, -0.9862857782045773, -1.050551880217663, -1.1292636100047166, -1.2215136323991065, -1.3260679550931773, -1.4413893007625944, -1.5656676579525959, -1.6968573335201695, -1.8327196712106335, -1.9708704625415578, -2.1088309609836413, -2.2440813213111386, -2.3741152251531883, -2.496494422728912, -2.6089019202819346, -2.709192572883682, -2.795439902338726, -2.865978048456641, -2.919437876811688, -2.9547764045091713, -2.97129886405191, -2.968672900296498, -2.9469345824505653, -2.9064861075398714, -2.84808526903508, -2.772826959574541, -2.682117165205022, -2.577640085709797, -2.4613191771067315, -2.33527305436884, -2.2017673114196916, -2.0631634086264277, -1.9218658431311684, -1.7802688528953186, -1.6407039104761116, -1.505389237255062, -1.3763825137835306, -1.2555378785227356, -1.1444681976491065, -1.0445134555266515, -0.9567159622441099, -0.8818029050934262, -0.8201765892394954, -0.7719125236007736, -0.7367653158056343, -0.7141821497524944, -0.7033234354689992, -0.7030900481522587, -0.7121564157108187, -0.7290085756649831, -0.7519862062585025, -0.7793275458901102, -0.8092160516535145, -0.8398276133582111, -0.8693771346487624, -0.8961633177650222, -0.9186105423693856, -0.9353068102690617, -0.9450368346579971, -0.9468094819423748, -0.9398789229828127, -0.9237590148976923, -0.8982306102557565, -0.8633416730958472, -0.8194002661362808, -0.7669606561139318, -0.7068029598292568, -0.63990691775403, -0.5674205308618036, -0.49062442593898026, -0.4108929217864668, -0.32965285075536926, -0.24834124493701734, -0.1683630226947136, -0.09104980844718573, -0.017620986791526634, 0.050851967982753966, 0.11347693264627627, 0.16956750287651184, 0.21866357782849494, 0.26054560212112216, 0.2952420714184064, 0.32303008350167417, 0.34442889821756056, 0.3601866523443599, 0.37126055461011254, 0.37879105726864387, 0.38407065944183005, 0.38850813982250526, 0.39358913866677275, 0.40083410815180004, 0.4117547235795939, 0.4278098936572213, 0.45036252496008655, 0.4806381831917383, 0.5196867522325013, 0.5683481221928746, 0.6272228414370882, 0.6966485471654865, 0.7766828475983074, 0.8670931695813273, 0.9673539124781892, 1.076651066819251, 1.1938942688825154, 1.3177360748598852, 1.4465980551998738, 1.57870313570334, 1.7121134513535734, 1.8447728357348088, 1.9745529468558498, 2.0993019323556563, 2.2168944659370116, 2.3252819443087276, 2.42254162106693, 2.5069234712286135, 2.576893627217171, 2.6311733029234414, 2.6687722252465425, 2.6890157198065805, 2.691564746256166, 2.6764283452037394, 2.643968139156216, 2.594894719701029, 2.5302559477475404, 2.4514173882790042, 2.3600352909642313, 2.2580227084870996, 2.1475095111406106, 2.0307972050020364, 1.9103095881941823, 1.7885403822058004, 1.66799905045858, 1.5511560623983376, 1.440388877198962, 1.3379299062833454, 1.2458176686219362], [1.1886714168211636, 1.1186620950415296, 1.0631544176741736, 1.023150729295781, 0.9993047975713125, 0.9919084681290973, 1.000886527463216, 1.025799878945796, 1.0658569397065751, 1.119932971249269, 1.1865968689607227, 1.2641447596876596, 1.350639596574599, 1.4439558002471669, 1.541827878569015, 1.6419018664060043, 1.7417883642639416, 1.8391159217973574, 1.9315835097566219, 2.017010851941947, 2.0933854464105828, 2.1589051910553825, 2.212015640566149, 2.251441056890817, 2.2762085702571175, 2.285664938740059, 2.2794855770240736, 2.2576757148873514, 2.2205637383382744, 2.1687869565155924, 2.103270220746301, 2.0251979940398726, 1.935980625578532, 1.8372157216300902, 1.7306456184417482, 1.6181120513202893, 1.5015091751551695, 1.3827361236746842, 1.263650297044554, 1.1460225400661452, 1.0314953169895185, 0.9215449053237433, 0.8174485221817406, 0.7202571654419564, 0.6307748017002907, 0.5495443674478221, 0.4768408733410496, 0.41267171829728455, 0.3567841350703872, 0.3086795066034212, 0.2676341174013055, 0.2327257408137255, 0.2028653155619064, 0.1768328367753074, 0.15331648142451218, 0.13095390796918702, 0.10837461727025255, 0.08424223764018733, 0.057295601900811316, 0.02638751832557423, -0.00947980052547134, -0.05112359841171628, -0.09915455987172558, -0.15395661864001853, -0.21567313783982903, -0.2841998433771517, -0.35918471568047655, -0.4400348632344245, -0.5259302188539278, -0.615843720971273, -0.7085674718997493, -0.8027442074263822, -0.8969032711870704, -0.9895001666886879, -1.0789586626548342, -1.1637143560904395, -1.24225855394222, -1.3131813196384128, -1.3752125455584892, -1.4272599563108193, -1.4684430195525608, -1.4981218392353117, -1.5159202282033748, -1.5217423000066626, -1.5157820800857913, -1.498525810169353, -1.470746802476514, -1.433492887589145, -1.3880666869719047, -1.3359991233940793, -1.2790167553724001, -1.219003680862361, -1.157958896762308, -1.0979501207787947, -1.0410651777747812, -0.9893621214261066, -0.9448193020486775, -0.9092866017400341, -0.884439038149668, -0.8717338886440068, -0.8723724084920768, -0.8872671118040439, -0.9170154548102819, -0.9618806107803538, -1.0217798580850934, -1.096280921675311, -1.1846064180010076, -1.2856463587692937, -1.397978474696831, -1.519895931311896, -1.6494418295410982, -1.7844497186819457, -1.922589202478459, -2.0614155940024865, -2.1984224749872516, -2.3310959426398514, -2.456969283585206, -2.573676801558023, -2.6790055431121957, -2.7709437135573234, -2.8477246524160806, -2.907865342066513, -2.9501985523627026, -2.9738978747832046, -2.9784950683750924, -2.9638893223403393, -2.9303482321083862, -2.8785004824834215, -2.8093204281609885, -2.724104953793857, -2.6244431781894524, -2.5121797357143, -2.3893725184826033, -2.258245891778245, -2.1211404992979928, -1.980460851713794, -1.838621939909883, -1.6979961319469714, -1.5608615999727806, -1.4293534803194579, -1.305418898024703, -1.1907768878188714, -1.0868841197334271, -0.9949071920082411, -0.9157020905333202, -0.8498012367167405, -0.7974083588215883, -0.7584012300825141, -0.7323421250293768, -0.7184956581379726, -0.7158534907984955, -0.7231652280068123, -0.7389746791625855, -0.7616605314784453, -0.7894803828103591, -0.8206170056490564, -0.8532256673377266, -0.8854813143642138, -0.9156244411448092, -0.9420045056576182, -0.9631198244523241, -0.9776529761154579, -0.9845008627074309, -0.9827987199211299, -0.9719375251393133, -0.9515744241659018, -0.9216359778288262, -0.8823142143411415, -0.8340556576063437, -0.7775436809241022, -0.7136747052894159, -0.643528917422177, -0.5683363209093076, -0.4894390509311488, -0.4082509760571356, -0.32621567722058065, -0.24476393257264026, -0.16527184653188037, -0.08902074177859134, -0.017159884717622316, 0.04932696070341154, 0.109650257045985, 0.1632379255379893, 0.20975246032583444, 0.24910145865763997, 0.2814412727169941, 0.3071736683857476, 0.32693555889358783, 0.34158206247616996, 0.3521633082121352, 0.3598955786935414, 0.3661275279177192, 0.37230234395275014, 0.37991683516871494, 0.39047850333576517, 0.4054617244797146, 0.42626418754238704, 0.4541647408159321, 0.49028376673979207, 0.5355471476338485, 0.590654799679241, 0.6560546420233262, 0.7319227349862164, 0.8181501692601137, 0.9143371204836669, 1.0197943047994185, 1.133551885411232, 1.2543756923791112, 1.3807904326134761, 1.5111093889010472, 1.6434699402832982, 1.7758740854094175, 1.9062330194091301, 2.0324147067059823, 2.15229330978696, 2.2637992793930994, 2.364968886346621, 2.4539919800072414, 2.529256793135251, 2.589390676969932, 2.6332957421221557, 2.660178498252163, 2.669572725644026, 2.6613549713155087, 2.635752237348726, 2.5933416154360893, 2.5350418146650764, 2.462096724597788, 2.376051347963674, 2.2787206220630503, 2.1721518207385797, 2.0585813852641777, 1.9403871688720267, 1.8200371925244299, 1.700036096144959, 1.5828705277038346, 1.4709547408487453, 1.3665776694617597, 1.271852714630445, 1.1886714168211643], [1.1383893719644558, 1.0789225823283264, 1.0346552875451016, 1.0063715528524142, 0.9944974785610722, 0.9990928080787993, 1.0198508339716668, 1.0561065898796411, 1.1068531195884075, 1.1707654232849778, 1.2462314996361643, 1.3313897352283837, 1.4241717441429442, 1.5223496336088873, 1.6235865698307936, 1.7254894436713806, 1.8256623906425349, 1.9217599046703602, 2.0115383006526715, 2.092904326474841, 2.1639597997068023, 2.2230412457773694, 2.2687536404579163, 2.2999975068351426, 2.3159887819427443, 2.316271046757714, 2.3007199009267065, 2.2695394557331223, 2.2232511107076083, 2.1626749662006484, 2.0889044015865674, 2.003274512210455, 1.9073252437342174, 1.8027601866476834, 1.6914020933874754, 1.5751462533640659, 1.4559129055214026, 1.3355998828407227, 1.216036668184187, 1.098940996529758, 0.9858790661799387, 0.8782303228351126, 0.7771576580577799, 0.6835837207528443, 0.5981738804926444, 0.5213262088798448, 0.45316866403554135, 0.39356347829631555, 0.3421185649640017, 0.29820558110957995, 0.26098411447884357, 0.2294313077179436, 0.20237609630654707, 0.17853712117263623, 0.15656328584102355, 0.1350758633986289, 0.11271102213453212, 0.08816163131346759, 0.06021723031832751, 0.02780109476655994, -0.009996589136247262, -0.053890327784673016, -0.10437646105215816, -0.1617164559018221, -0.22592680687516867, -0.2967758250039999, -0.37378741676602756, -0.45625177202109807, -0.5432426990592606, -0.6336411705558678, -0.726164480793537, -0.8194002661362809, -0.911844511211161, -1.0019425558807307, -1.0881320356340336, -1.1688866326201695, -1.2427594876537253, -1.308425125878175, -1.364718780390083, -1.4106720582769727, -1.4455439807606147, -1.468846541338812, -1.48036406022567, -1.480165766684553, -1.4686112092313264, -1.4463482729743684, -1.4143037690873999, -1.3736667489454613, -1.3258648801029997, -1.2725343984265902, -1.2154843158615805, -1.1566557123481556, -1.0980770695365276, -1.0418167098987194, -0.9899334848799866, -0.9444269077988721, -0.9071879499027896, -0.8799517106543712, -0.8642531360431029, -0.8613868923105732, -0.872372408492077, -0.8979249818442842, -0.9384336984116378, -0.9939467601076503, -1.0641646336537016, -1.1484412498109773, -1.2457932881206433, -1.3549173875573475, -1.4742149318723636, -1.6018238746563538, -1.7356568978018965, -1.8734450423089448, -2.0127858160666525, -2.151194672679116, -2.2861586713202025, -2.415191072094418, -2.535885595840541, -2.645969082401674, -2.743351317008908, -2.8261708597470707, -2.892835806523025, -2.9420585292834427, -2.972883585538414, -2.984708149086164, -2.9772944912689634, -2.9507742308072156, -2.90564426566703, -2.84275449776371, -2.7632876557906414, -2.6687317083636803, -2.5608455344471235, -2.441618676440653, -2.3132261395233833, -2.177979315535436, -2.038274198073376, -1.8965381154750558, -1.7551762385621603, -1.6165191197183604, -1.48277248917876, -1.3559704741121263, -1.237933317733656, -1.130230561523991, -1.034150516510999, -0.9506766929151228, -0.8804716851619625, -0.8238688255997846, -0.7808717297691422, -0.7511616634598683, -0.7341124718026066, -0.7288126279486282, -0.7340937879727912, -0.748565083669127, -0.7706522496716367, -0.7986405691022563, -0.8307205354238547, -0.8650350694151941, -0.8997271005502734, -0.9329863221923909, -0.9630939597994141, -0.9884644499388058, -1.0076830137714055, -1.0195382195487368, -1.0230487617273332, -1.0174838361364598, -1.00237665738092, -0.9775308420932547, -0.943019565284609, -0.8991775822493476, -0.8465863905930935, -0.7860529814001056, -0.7185827909573274, -0.6453476107404711, -0.5676493398850119, -0.48688056795550405, -0.40448305391430056, -0.32190521784319426, -0.2405597839486653, -0.16178270616564838, -0.08679447148316197, -0.016664811894586344, 0.04771823472237298, 0.10567408915078967, 0.15674953096033692, 0.2007321978588059, 0.2376573151941578, 0.26780746335630473, 0.2917053727100106, 0.3100999180144509, 0.32394566242259865, 0.33437647057889824, 0.34267386673763295, 0.3502309532224994, 0.35851282338041757, 0.3690144984039461, 0.3832174865521809, 0.4025461045876482, 0.42832471356314866, 0.4617370040609606, 0.5037884199674786, 0.5552727359480605, 0.6167437037604965, 0.6884925588603485, 0.77053203445446, 0.862587368819308, 0.9640946173221969, 1.074206397503143, 1.1918050083580964, 1.3155226782881888, 1.4437685147188204, 1.5747615567017497, 1.7065691742142988, 1.8371499183419637, 1.9643998086137733, 2.086200950462406, 2.2004713095086483, 2.305214431859595, 2.398567891891036, 2.4788492713482224, 2.544598525592109, 2.59461567325194, 2.6279928525251113, 2.6441399183358394, 2.6428029063717244, 2.6240748589871523, 2.588398689988863, 2.5365619559664006, 2.46968359644258, 2.3891928989340174, 2.2968011332787603, 2.194466477685253, 2.084353022505382, 1.9687847827063572, 1.8501957728350056, 1.7310772958966627, 1.6139236675854867, 1.5011776379574078, 1.395176782899849, 1.2981021173398808, 1.2119301315099906, 1.1383893719644564], [1.0953969429041863, 1.0469699543687263, 1.0143000265789595, 0.9979463240064826, 0.9981036947967393, 1.0145993029273648, 1.046897578203915, 1.0941133547462742, 1.1550328745784193, 1.2281421468909777, 1.3116619800173748, 1.403588846358034, 1.5017406041983274, 1.6038059878842315, 1.7073966918479904, 1.8101008165650259, 1.909536417021125, 2.0034038972882113, 2.0895360282115027, 2.1659444281182534, 2.2308614372635818, 2.2827764331443374, 2.32046577292424, 2.3430157075565394, 2.349837785831188, 2.340676451210208, 2.3156087253830373, 2.275036065259876, 2.2196686698792085, 2.150502695774532, 2.0687910092638178, 1.9760082577421443, 1.87381117563488, 1.7639951509714913, 1.6484481629182541, 1.5291032570603238, 1.4078907524453255, 1.2866913718164026, 1.1672914542385286, 1.0513413483607768, 0.9403179964748084, 0.8354926066137295, 0.7379041750871757, 0.6483394685099522, 0.5673199064496977, 0.49509560754615395, 0.4316466778442791, 0.37669163477545087, 0.3297026783772757, 0.28992734752953575, 0.25641593755916137, 0.2280539105708303, 0.2035984049133095, 0.18171784840827898, 0.161033603875162, 0.1401625269611321, 0.11775929651329317, 0.09255738716916813, 0.06340759221575512, 0.029313071072240654, -0.01054001171993815, -0.05675707272987682, -0.10971560054582644, -0.16955207613607437, -0.23615567929226405, -0.3091689604383338, -0.38799547504176346, -0.47181419573840183, -0.5596003397021213, -0.6501520802676478, -0.7421224566356147, -0.8340556576063433, -0.9244267382240308, -1.011683734966026, -1.094291078086332, -1.1707731606652303, -1.2397569138731994, -1.30001225724458, -1.3504893409551224, -1.3903515730614175, -1.4190035265436776, -1.436112946297375, -1.4416262218526406, -1.4357768539566766, -1.419086618201026, -1.3923593122541267, -1.356667160394031, -1.3133301352472637, -1.2638886372604214, -1.2100701429243852, -1.1537505888416664, -1.0969113964306323, -1.0415931578995135, -0.9898470951379541, -0.943685467014897, -0.9050321355588749, -0.8756745066638167, -0.8572180360807514, -0.8510444370392268, -0.8582746431400361, -0.8797374711248184, -0.915944795365442, -0.9670738926263606, -1.0329574455495107, -1.1130815105297596, -1.2065915646458136, -1.312306551755032, -1.4287406545142196, -1.5541323316946765, -1.6864799833224562, -1.8235834442447336, -1.9630903636924397, -2.102546407809822, -2.239448126940343, -2.3712972620604336, -2.49565522682617, -2.6101964942074725, -2.7127596398512925, -2.80139484760811, -2.8744067648055864, -2.9303917038827816, -2.9682683202709783, -2.987301050693062, -2.9871157676057445, -2.967707290159108, -2.929438585306144, -2.8730316898612616, -2.7995505805867125, -2.7103764100083594, -2.607175705997029, -2.4918622988223658, -2.36655388637956, -2.233524273051696, -2.095152417196468, -1.9538694941516372, -1.8121052242342643, -1.6722347274810123, -1.5365271486017078, -1.4070972473070984, -1.285861072071771, -1.1744967314572254, -1.0744111489560773, -0.9867135381273141, -0.9121961682841535, -0.8513228113014188, -0.8042250716751596, -0.7707066094468508, -0.7502550737424052, -0.7420613781905302, -0.74504577295138, -0.757890005823963, -0.7790747208667343, -0.8069211206571988, -0.8396358206844606, -0.8753577537464968, -0.9122059402696591, -0.9483269281240341, -0.9819407229802546, -1.011384077004557, -1.0351500784565977, -1.0519230855799169, -1.0606081724561633, -1.0603543990488726, -1.0505713788099866, -1.0309387908750027, -1.0014086656386727, -0.962200457797043, -0.9137891050971999, -0.856886449425241, -0.7924165650094126, -0.7214856922073066, -0.6453476107404711, -0.5653653999592447, -0.48297062293574705, -0.3996210336842945, -0.31675794106004784, -0.23576436806485024, -0.1579251213023703, -0.0843898328149959, -0.016139956862524608, 0.04603940058939469, 0.10158206914032047, 0.15015721389771375, 0.1916791059295956, 0.22630999436291155, 0.2544559915328999, 0.27675606525536356, 0.29406441272020156, 0.3074266641086624, 0.3180505264054147, 0.32727162487697925, 0.33651542757137565, 0.34725624368937963, 0.3609743670748607, 0.37911248928868385, 0.4030325313670145, 0.4339740387369719, 0.4730152499216307, 0.5210378873975651, 0.5786966297720664, 0.6463941105027472, 0.7242621524933894, 0.8121497934258055, 0.9096184874595532, 1.0159446891581394, 1.1301298396633324, 1.2509175878798704, 1.376817895439626, 1.5061374981034001, 1.6370160324594487, 1.7674669894245514, 1.8954225288769717, 2.01878108599129, 2.135456622164384, 2.2434283238422794, 2.340789532406062, 2.4257946981513445, 2.4969031911570743, 2.552818870600389, 2.592524410230313, 2.6153094989778847, 2.620792179141205, 2.608932746774201, 2.5800398158908378, 2.5347683355625437, 2.474109542359351, 2.3993730251346324, 2.31216127011071, 2.214337236901636, 2.1079856860177095, 1.995369131349969, 1.8788794233582216, 1.7609860769135257, 1.644182539291164, 1.5309316466393212, 1.4236115400330136, 1.3244633043658138, 1.2355415549898174, 1.1586691290904627, 1.0953969429041885], [1.0600578650444965, 1.0230745448539935, 1.0022608494943799, 0.9979463240064826, 1.0100929360571287, 1.0382967607116085, 1.081797932464968, 1.139498619116672, 1.2099885821478136, 1.2915777090223046, 1.382334738632707, 1.4801312559259918, 1.5826899090843798, 1.6876357054566278, 1.7925491730638363, 1.8950201345851871, 1.9927008311831287, 2.0833571545290446, 2.1649167963636025, 2.235513204561267, 2.2935243409538613, 2.3376053664406884, 2.3667145299244616, 2.3801317056109523, 2.3774692040327077, 2.358674671332304, 2.324026084200897, 2.274119039663772, 2.2098467249235556, 2.1323731281530627, 2.043100212178518, 1.943629915485856, 1.835721965461925, 1.7212485843447078, 1.602147236722724, 1.48037260699248, 1.357849005072228, 1.236424378736338, 1.1178270617750141, 1.003626310121798, 0.8951975751404466, 0.7936933370778639, 0.7000201754982582, 0.6148225910354569, 0.5384739181534327, 0.4710744862035122, 0.4124570005092484, 0.36219893116546975, 0.3196415193289854, 0.2839148434653184, 0.25396823548612313, 0.2286052027755294, 0.20652190009827964, 0.186348108090527, 0.16668961461351722, 0.14617086318121708, 0.12347672972092247, 0.0973923151236475, 0.06683969568778746, 0.030910655238893414, -0.011105470675584513, -0.05969957928787473, -0.1151268068166264, -0.17739718644993588, -0.24627321420184897, -0.3212743981464242, -0.401688683905452, -0.4865904692396139, -0.5748647477407565, -0.6652367603391813, -0.7563063877292941, -0.8465863905930934, -0.9345435008916296, -1.0186412891615781, -1.0973836817255853, -1.1693579793446967, -1.233276235733504, -1.2880138904131353, -1.3326446147501203, -1.3664704211641987, -1.389046201154117, -1.4001979951371677, -1.4000344527259894, -1.388951112110913, -1.367627307445139, -1.3370156990465982, -1.2983246081868105, -1.252993521549062, -1.2026623055031809, -1.1491348327544042, -1.0943378695780697, -1.040276197057065, -0.9889850413029644, -0.9424809629538883, -0.9027124033381131, -0.8715111023056031, -0.8505455903215532, -0.8412779151931704, -0.8449246927086169, -0.8624234721686872, -0.894405284627701, -0.9411740965910723, -1.0026937284515571, -1.0785826190545709, -1.1681166297997627, -1.2702398882030073, -1.3835834765962478, -1.506491581396055, -1.637054536798246, -1.773148028323562, -1.912477570499508, -2.052627242848555, -2.1911115624846995, -2.3254292926279834, -2.4531179362046402, -2.5718076436756405, -2.6792732748597623, -2.773483395567799, -2.852645060375935, -2.9152433311490906, -2.9600746046094573, -2.986272968337305, -2.9933289695474605, -2.981100360799808, -2.9498145771051725, -2.9000628950525544, -2.832786421839757, -2.749254255641731, -2.6510343438960726, -2.5399577383283347, -2.418077100703816, -2.2876204476221256, -2.150941232923398, -2.010465949800887, -1.8686404895214985, -1.727876518457636, -1.5904991293816473, -1.4586969868694406, -1.3344761211474507, -1.2196184314645186, -1.1156458414206925, -1.0237909076040153, -0.9449745228849658, -0.8797911807663473, -0.8285020816145653, -0.7910361699899635, -0.7669989993724101, -0.7556891310893706, -0.7561215928481874, -0.7670577533939269, -0.7870408175810788, -0.8144360142631737, -0.8474744410588915, -0.8842994478461099, -0.9230143867127044, -0.9617305312999597, -0.9986139735260735, -1.0319303403450208, -1.0600862365171548, -1.081666409668257, -1.0954657488514974, -1.1005153644517756, -1.0961021520993153, -1.081781412358416, -1.0573822770476944, -1.0230058776101232, -0.9790163763360249, -0.9260251627896193, -0.8648686909442362, -0.7965805929551341, -0.7223588491812014, -0.643528917422177, -0.5615038242972724, -0.4777422957760143, -0.3937060502583514, -0.31081739516189605, -0.2304182563095226, -0.15373172885556555, -0.08182717010533669, -0.015589760132507957, 0.04430466200092276, 0.09740881735552519, 0.14351674833552702, 0.1826697777924955, 0.21515549963285222, 0.24149981674001242, 0.2624522239275115, 0.2789647106417781, 0.2921648257350254, 0.3033236005669663, 0.3138191630473154, 0.32509699051769936, 0.3386278406374805, 0.35586446433070196, 0.3781982416796556, 0.4069168894271499, 0.4431643672165371, 0.48790405933449693, 0.541886230730124, 0.6056206523646882, 0.6793551640479991, 0.7630607959743873, 0.8564239068271146, 0.9588456206353406, 1.0694486609213374, 1.1870914936536778, 1.3103895048050658, 1.4377427585599336, 1.5673697129454947, 1.697346115138776, 1.8256481628408157, 1.9501989043606582, 2.0689167613272694, 2.1797649965408845, 2.280800917008329, 2.3702235995839596, 2.4464189540263126, 2.508000995102725, 2.5538482803215725, 2.5831345809365205, 2.595352988390765, 2.5903328131068144, 2.5682488037280726, 2.529622398417244, 2.475314911136213, 2.406512750294097, 2.324704959990396, 2.2316535605649, 2.1293573407109703, 2.020009913690933, 1.905952991257186, 1.789625947242474, 1.6735128355029096, 1.560088091669142, 1.451762183357966, 1.3508284782181355, 1.2594125732732515, 1.1794252730780284, 1.1125203195531974, 1.060057865044497], [1.0326711229751988, 1.0074385197614222, 0.9986396131772894, 1.0063715528524144, 1.0303637679359836, 1.0699846902154502, 1.1242566239651834, 1.1918784031171894, 1.271255292142806, 1.360535416118402, 1.4576518519644786, 1.5603693805114678, 1.6663347910517778, 1.7731295489820147, 1.8783235849552984, 1.9795289418749742, 2.0744520245523996, 2.1609432356573324, 2.2370428497002086, 2.301022072474935, 2.3514183542571256, 2.3870641680803537, 2.4071086260465453, 2.4110314828596557, 2.398649262245955, 2.3701134340374796, 2.325900762715787, 2.2667961373963124, 2.1938683739394564, 2.108439647682042, 2.0120493660992267, 1.9064134208684531, 1.7933798651689836, 1.6748821420640425, 1.5528910415879127, 1.4293665865109852, 1.3062110392290411, 1.1852241851080658, 1.0680619819367836, 0.9561995726276242, 0.8508995413585709, 0.7531861549621746, 0.6638261750702599, 0.5833166562793566, 0.511879965717798, 0.44946607440816266, 0.395761985384134, 0.35020798229693917, 0.3120202097774058, 0.28021893742200105, 0.2536617169268646, 0.2310805201505266, 0.21112184776929588, 0.19238872612725158, 0.1734834656458682, 0.153050038815658, 0.12981494968531415, 0.10262550949858096, 0.0704845035860058, 0.03258033098155308, -0.01168818196454843, -0.06269295252168632, -0.12056429861090773, -0.18518541366019764, -0.2561938126803517, -0.3329897206474848, -0.4147511926138586, -0.5004555785645707, -0.5889067793759338, -0.6787675875511658, -0.7685962715992186, -0.8568864494252407, -0.942109206823901, -1.022756354410564, -1.097383681725585, -1.1646530617329172, -1.223372282704243, -1.2725315369965575, -1.311335576233603, -1.3392306479367144, -1.3559254571205732, -1.3614055445967104, -1.3559406380330223, -1.3400847081121774, -1.3146686460182644, -1.2807856653627958, -1.2397697168577237, -1.1931673829053782, -1.1427038873031827, -1.0902440082142344, -1.0377488165603295, -0.9872292736418737, -0.9406978082187432, -0.9001190522582241, -0.867360944508868, -0.8441474111488202, -0.8320138028792222, -0.8322662086273266, -0.8459456788575264, -0.8737982784255773, -0.9162517526612272, -0.9733994342164153, -1.044991845957987, -1.1304362710093412, -1.2288043694510054, -1.338847726864062, -1.4590210276069413, -1.5875123601787287, -1.7222799878051613, -1.8610947587812243, -2.001587192033033, -2.1412981572637304, -2.277731978806535, -2.408410730173389, -2.5309284538252714, -2.6430040387369123, -2.7425315169754776, -2.827626599100003, -2.8966683553213812, -2.948335062947549, -2.9816333779312316, -2.9959201460125806, -2.990916343180437, -2.966712821731936, -2.9237677325561395, -2.862895691678641, -2.78524895478117, -2.692291052597157, -2.5857635181856824, -2.467646499780552, -2.3401141962557577, -2.2054861727780435, -2.0661757090272266, -1.9246363991839242, -1.7833082601287151, -1.644564611109965, -1.510660964409766, -1.3836871129083637, -1.265523518288579, -1.157802995005044, -1.0618785527840977, -0.9787981076155762, -0.9092866017400345, -0.853735891219529, -0.8122025698010505, -0.7844137046205034, -0.7697802676047629, -0.7674178609166709, -0.7761741599972517, -0.7946623379611861, -0.8212995941857806, -0.8543497913151439, -0.8919691114355206, -0.9322535760908947, -0.9732872376427113, -1.0131898420558467, -1.0501627855971314, -1.0825322395032235, -1.1087883960297529, -1.1276198943628415, -1.1379426129515895, -1.13892216263308, -1.1299895787118117, -1.110849885775219, -1.0814833920401543, -1.042139755821478, -0.9933250506214207, -0.9357822327416456, -0.8704655817748234, -0.798509835676605, -0.7211948745759041, -0.6399069177540299, -0.5560972835765782, -0.47123982048992313, -0.38678814707281656, -0.30413383985516507, -0.22456667920727555, -0.14923800682286678, -0.07912816464032671, -0.015018876617839197, 0.04252869563039385, 0.09318964139492211, 0.13688431561727776, 0.17378043644031296, 0.20428820307686507, 0.22904855407912916, 0.24891486569665014, 0.26492856209145715, 0.278289269360393, 0.2903202895201561, 0.30243029516302866, 0.3160722472058494, 0.3327006144189386, 0.35372802226094435, 0.38048247867357043, 0.414166315341173, 0.4558179446642365, 0.5062774662346632, 0.5661570635465747, 0.6358170143115275, 0.7153479989682054, 0.8045602352229068, 0.9029797956247373, 1.0098522845244597, 1.1241538647998504, 1.2446094381059658, 1.3697175998051327, 1.497781815738285, 1.6269471069996468, 1.7552413849405772, 1.8806204554086952, 2.001015611869839, 2.114382664121706, 2.2187512046949016, 2.312272899957312, 2.393267607865896, 2.4602661689786567, 2.5120487907419786, 2.5476780454836057, 2.5665256275753348, 2.5682921618737473, 2.5530195202523442, 2.5210952818012036, 2.47324916073234, 2.4105414195835135, 2.334343479219407, 2.246311126628676, 2.148350901949518, 2.0425804130823977, 1.9312834755482986, 1.8168611032334818, 1.7017794791547336, 1.5885161118076052, 1.479505430110651, 1.3770850872253906, 1.2834442301504552, 1.200574948242997, 1.1302280407423944, 1.0738741427094665, 1.032671122975199], [1.0134684209268408, 1.0001941669386758, 1.0034669549255584, 1.0231507292957807, 1.058744690022952, 1.109394997216336, 1.1739144329616913, 1.250809550073059, 1.3383146604733351, 1.4344318547735178, 1.5369761031525204, 1.6436243692723036, 1.7519675765493363, 1.859564201857762, 1.963994237184411, 2.062912255684044, 2.1540983450401967, 2.235505727318627, 2.305303969172682, 2.361916797193608, 2.4040536676234914, 2.430734394221099, 2.4413063089587625, 2.4354536132048166, 2.4131987675943614, 2.374895962217149, 2.32121690029917, 2.2531293135243313, 2.171868801006523, 2.0789047424362788, 1.9759011752344429, 1.8646736422750547, 1.747143108084554, 1.6252881052122448, 1.501096307213343, 1.3765167296296006, 1.2534137354732444, 1.1335239677380327, 1.0184172498182238, 0.9094623875382998, 0.8077986765400648, 0.714313769357069, 0.6296283914247728, 0.5540882187062858, 0.48776304601429954, 0.4304531891018115, 0.3817028798514745, 0.34082023702325276, 0.3069032294500252, 0.2788708984371266, 0.2554989751670982, 0.2354589203907353, 0.21735933028756105, 0.19978859615645111, 0.18135767791822835, 0.16074185292572504, 0.13672033219749213, 0.10821269510150908, 0.0743111791862968, 0.034307972087899846, -0.012283215585645395, -0.06571186713923671, -0.12598207228759767, -0.1928508658404477, -0.26583354197552195, -0.3442158110119126, -0.4270724864324575, -0.5132922186143495, -0.6016076326659282, -0.6906300849826189, -0.7788881302666133, -0.8648686909442356, -0.9470598467251371, -1.0239941153988887, -1.0942910780863326, -1.1566982135618875, -1.2101288467096343, -1.2536961847105956, -1.286742509513871, -1.3088627141866072, -1.3199215109248779, -1.3200637963613597, -1.3097178313987217, -1.2895910738506002, -1.2606586881601405, -1.224144942732065, -1.1814978872838051, -1.1343578755207744, -1.0845206580098918, -1.0338959123278877, -0.9844621987838139, -0.938219427161158, -0.897139990488964, -0.8631197639844294, -0.837930179865574, -0.8231725712979239, -0.8202359316443144, -0.8302591594986097, -0.854098757481134, -0.892302825902613, -0.9450920442201936, -1.0123481673030275, -1.0936103839314293, -1.1880796960542384, -1.294631283744522, -1.411834627268504, -1.5379809689696802, -1.6711175184114182, -1.809087638834947, -1.9495761055594216, -2.0901584011245706, -2.2283529108779665, -2.3616748088570607, -2.487690379065397, -2.604070502733607, -2.7086420582910335, -2.799436027201641, -2.8747311744459445, -2.933092275448443, -2.973401989175769, -2.9948856268703468, -2.9971282338082763, -2.980083583502783, -2.9440748754930817, -2.8897871246032274, -2.8182514265433003, -2.730821477167765, -2.629142905926892, -2.5151161535980835, -2.3908537761530018, -2.258633186928439, -2.120845954978679, -1.97994485605218, -1.8383899221821127, -1.698594755247224, -1.5628743586264804, -1.4333956995682122, -1.3121321441945428, -1.2008228089520767, -1.100937749257598, -1.0136497611392823, -0.939813408438135, -0.8799517106543734, -0.8342507391834175, -0.8025621771064301, -0.7844137046205029, -0.7790268833561247, -0.7853420328626556, -0.802049425845751, -0.8276259793765, -0.8603764908857191, -0.898478363407595, -0.9400286867416313, -0.9830924917943739, -1.0257509754689247, -1.0661485034827216, -1.1025372380609828, -1.133318305490364, -1.1570785132348957, -1.1726217452656467, -1.1789943043889064, -1.1755036281081885, -1.1617299759229849, -1.1375308666216561, -1.1030382295136674, -1.05864841900489, -1.0050054227940277, -0.9429777657263607, -0.8736297696879536, -0.7981879709074096, -0.7180036161432806, -0.6345122554921963, -0.5491915195781469, -0.4635182109607978, -0.3789258527190266, -0.29676382104209303, -0.218259143748263, -0.14448197412610309, -0.07631565122751387, -0.01443213625138016, 0.040726526956936564, 0.08896023739633686, 0.13031602912497245, 0.16508628972336029, 0.19380004694132155, 0.21720754686662164, 0.23625852273913692, 0.252074719237404, 0.2659173884704551, 0.2791506071605056, 0.2932013761999416, 0.3095175510479865, 0.3295247120496625, 0.3545831161322485, 0.3859458745918306, 0.42471947568544777, 0.47182771608905305, 0.5279800232856927, 0.5936450436186123, 0.6690302407265032, 0.7540680995929965, 0.8484093662041948, 0.9514235759326656, 1.0622069396696299, 1.1795974700144796, 1.3021970451829632, 1.4283999303501014, 1.5564271093829682, 1.6843656285530797, 1.810212021684421, 1.9319187766578199, 2.047442719064164, 2.154794132263404, 2.252085405663995, 2.337578005472247, 2.4097265945142743, 2.4672191893039437, 2.5090123318920794, 2.53436036906528, 2.5428380694078276, 2.5343559662643305, 2.5091679879198026, 2.4678711211263082, 2.4113970459361207, 2.3409958739533203, 2.25821231382554, 2.1648547723533254, 2.0629580724513343, 1.9547406260906637, 1.8425570374056641, 1.7288472249660771, 1.6160832399660021, 1.5067150165715302, 1.4031163203965453, 1.3075321602666472, 1.2220288970603443, 1.1484482222071346, 1.0883660888304765, 1.0430575627029601, 1.0134684209268414], [1.0026122224480716, 1.0014027768887426, 1.0167020332436, 1.0481418939112097, 1.0949955868746681, 1.156194252683676, 1.230351231919973, 1.3157934758143923, 1.4105993345386236, 1.512641827678118, 1.6196363731371575, 1.7291918473302799, 1.8388637734624786, 1.9462083878084346, 2.0488363172669137, 2.144464615446202, 2.230965948734831, 2.3064137970935694, 2.369122634821785, 2.4176821817909953, 2.4509849624841324, 2.468246574988775, 2.469018250789056, 2.4531914743725785, 2.4209946246789547, 2.372981793518796, 2.310014124546562, 2.2332341955620922, 2.144034132466685, 2.0440182910788467, 1.934961469636126, 1.8187637171200168, 1.6974028780959354, 1.5728860617826326, 1.4472012404892027, 1.3222701700523696, 1.1999037828856582, 1.0817611338597988, 0.9693128823175495, 0.8638101725884978, 0.7662596335046515, 0.677405058234722, 0.5977161532861078, 0.5273845641241284, 0.466327199096657, 0.41419668789757713, 0.3703986303058926, 0.33411511991742715, 0.3043338703158733, 0.2798821315305016, 0.2594644661707429, 0.24170336024887537, 0.22518157572847847, 0.2084851119292001, 0.1902456320316529, 0.16918122928346233, 0.1441344545966838, 0.1141066018140008, 0.07828734708149244, 0.036078961932407706, -0.012885537285185213, -0.06873078175678735, -0.13133429102982153, -0.20032868979658544, -0.2751108456154954, -0.35485769143536355, -0.4385483216400944, -0.5249917856054863, -0.612859852644706, -0.7007238905374304, -0.7870948899500336, -0.8704655817748228, -0.9493535359415839, -1.0223441001084979, -1.0881320356340334, -1.1455607364467437, -1.1936579732109118, -1.2316671891586828, -1.2590734830638595, -1.275623546375046, -1.2813389722438173, -1.276522520328536, -1.2617570986832662, -1.2378974083206518, -1.2060543825540322, -1.167572737298074, -1.124002125511547, -1.0770625544393237, -1.028604874071335, -0.9805672754843604, -0.934928845147376, -0.8936613030933527, -0.8586801069617485, -0.8317961288536655, -0.8146691069946835, -0.8087640393892762, -0.8153116227370237, -0.8352737483508492, -0.8693149498449734, -0.9177805577547403, -0.9806821573876341, -1.0576907719444983, -1.1481380075404894, -1.2510252047294486, -1.3650404471983786, -1.4885830872119707, -1.6197952638507733, -1.7565997186237192, -1.8967430578789914, -2.037843476426145, -2.1774418452662987, -2.313054981082962, -2.4422298583094952, -2.5625974975999397, -2.6719252680987227, -2.7681663749910337, -2.849505367632166, -2.9143985955831444, -2.961608657910833, -2.9902320322949514, -2.99971923140407, -2.9898870107549746, -2.960922340563249, -2.9133780493522057, -2.8481602445661105, -2.766507810331338, -2.6699644700888663, -2.5603440775266146, -2.4396899588059844, -2.310229268636679, -2.174323438931327, -2.0344158887667296, -1.892978226034334, -1.7524562030178639, -1.6152166894616016, -1.483496897508454, -1.3593570339604768, -1.2446374681422891, -1.1409213904163218, -1.0495037999330212, -0.9713675038873386, -0.9071666382675021, -0.8572180360807509, -0.8215005778613701, -0.7996624656152278, -0.7910361699899628, -0.7946606160730979, -0.8093100003218818, -0.833528473935922, -0.8656697903172856, -0.9039408994523158, -0.9464483828522182, -0.9912465612229393, -1.0363860747248241, -1.0799617332292228, -1.1201584613408453, -1.1552942193500857, -1.1838588652072337, -1.2045480318895008, -1.2162912263544752, -1.2182735072777862, -1.2099502651258798, -1.1910548056097345, -1.1615986217264906, -1.1218644257895376, -1.0723921963995724, -1.0139586716198392, -0.9475508842786995, -0.8743344842220702, -0.7956177217691406, -0.7128120733737306, -0.6273905719205223, -0.5408449581902989, -0.454642795499321, -0.37018568576494154, -0.28876969241681005, -0.21154901453666056, -0.1395038689540173, -0.07341342500304673, -0.013834503122134132, 0.038913403143018985, 0.0847563880314236, 0.1238674595345195, 0.15666089405700914, 0.18377976577307065, 0.20607697538162192, 0.22459027344345306, 0.2405119314065942, 0.2551538547758779, 0.2699090540551163, 0.2862104869886155, 0.30548835773963856, 0.3291270031008081, 0.3584225114635294, 0.3945422066327529, 0.438487085948105, 0.4910582315802289, 0.5528281170344147, 0.624117610196381, 0.7049793326849968, 0.7951878763500508, 0.8942372054281915, 1.0013453914484447, 1.1154666419975832, 1.2353103985765914, 1.3593670976701222, 1.4859400173695174, 1.613182473772464, 1.7391394909312743, 1.8617929489089704, 1.9791091195776787, 2.089087431608263, 2.1898092664454962, 2.279485577024074, 2.3565021409097913, 2.4194613090542716, 2.4672191893039437, 2.4989173083689096, 2.514007924635412, 2.5122723138948393, 2.4938315171336654, 2.4591492199157563, 2.4090266221869023, 2.3445893509081626, 2.267266661031367, 2.1787633582214747, 2.0810250547809357, 1.976197534048579, 1.8665811440816549, 1.7545812650788877, 1.6426559936918474, 1.533262258637787, 1.4288016240757813, 1.3315670489614733, 1.2436918517168494, 1.1671020804564871, 1.1034734108555408, 1.0541935883981988, 1.020331301745189, 1.0026122224480716], [1.000194375890509, 1.0110541242245423, 1.0382328733799016, 1.0811336101374207, 1.1388097595000446, 1.2099865137393062, 1.2930895399828917, 1.3862803869238496, 1.4874977532868823, 1.5945036430710051, 1.704933318630112, 1.8163478751012911, 1.9262882006443318, 2.032329057813928, 2.1321320228138188, 2.223496051294987, 2.30440450092605, 2.373067530625589, 2.4279589118578424, 2.4678464258792716, 2.49181517884787, 2.4992833403596277, 2.490009995969737, 2.4640949960309855, 2.4219708770211317, 2.3643871226757778, 2.2923872160101455, 2.207279105210201, 2.110599862211125, 2.0040754487745307, 1.8895766177390656, 1.769072064144639, 1.6445800000565485, 1.5181193567748215, 1.3916618180677802, 1.2670858582201694, 1.1461338998787096, 1.030373620470929, 0.921164324603802, 0.8196291661745565, 0.7266338513530471, 0.6427722859926102, 0.5683594526293744, 0.5034316175341939, 0.4477537819296272, 0.4008341081518001, 0.36194487581377666, 0.3301493593042797, 0.30433387031587317, 0.28324408121256794, 0.2655246400895026, 0.24976100893810488, 0.23452240435601074, 0.2184046969868419, 0.20007213187249615, 0.17829676694602106, 0.1519945900524617, 0.12025736451824522, 0.082379367091962, 0.03787831713960988, -0.013490051149036031, -0.07172415499059895, -0.1365756726451128, -0.20755561975418713, -0.28394723341345013, -0.3648253267939467, -0.449081607478038, -0.5354552959071188, -0.6225682404395576, -0.7089636060531064, -0.7931471177489559, -0.8736297696879529, -0.9489708688245636, -1.0178202684153883, -1.078958662654834, -1.1313348584836462, -1.1740990132510338, -1.2066309256114225, -1.2285625893677161, -1.2397943629026158, -1.2405042668134318, -1.2311500953961343, -1.2124642093879132, -1.1854410633243786, -1.1513177063340974, -1.1115476755180163, -1.0677688717026785, -1.02176616400381, -0.9754296083218195, -0.9307092820828382, -0.889567830236884, -0.8539318833308529, -0.8256435456550423, -0.8064131589932493, -0.7977745250984426, -0.801043718122759, -0.8172825380389821, -0.8472675494932272, -0.8914655200762409, -0.9500159208416802, -1.0227209837014384, -1.1090436291877939, -1.2081133884154036, -1.3187402495483984, -1.439436166429238, -1.5684437799942585, -1.7037717262941174, -1.8432357427206894, -1.9845046404276416, -2.12515008948242, -2.262699067024548, -2.394687750036659, -2.5187155949938886, -2.6324983376583484, -2.733918667901, -2.8210733861825705, -2.892315928990364, -2.9462932581790584, -2.981976241209109, -2.9986828025246224, -2.9960932970508116, -2.9742577408763964, -2.9335947271476672, -2.874882052348939, -2.799239274686289, -2.708102617450159, -2.6031928113624705, -2.486476636616431, -2.360123073548069, -2.2264550970481767, -2.0878982508830917, -1.9469272116124199, -1.8060115960164875, -1.6675622798407594, -1.5338794789374184, -1.4071037969956541, -1.2891713682004786, -1.1817741202526946, -1.0863260557878416, -1.0039363015167273, -0.9353895080575576, -0.8811340035521613, -0.8412779151931706, -0.8155932793876852, -0.803527968198794, -0.8042250716751572, -0.8165491973025523, -0.8391189834440153, -0.8703449772764834, -0.908471902927955, -0.9516242452759774, -0.9978540015778304, -1.0451894084849687, -1.0916834370550326, -1.135460863382306, -1.1747627669469536, -1.2079873815299158, -1.2337263226487643, -1.2507953383855477, -1.2582588740586396, -1.2554479017877467, -1.2419706395497028, -1.2177159664432742, -1.1828495269907469, -1.1378027027283153, -1.083254809429636, -1.020109048562395, -0.949462897746348, -0.8725737631733278, -0.7908208337325588, -0.7056641690682858, -0.6186021197046243, -0.5311282150992377, -0.4446886641364699, -0.3606415919779654, -0.28021908792487055, -0.20449306230196646, -0.13434580832898474, -0.07044604011405732, -0.013231033476806616, 0.037104664036554734, 0.08061365976807403, 0.11759316466266513, 0.1485755321011319, 0.17431213568502724, 0.1957510092955368, 0.21400883647858301, 0.23033802501629752, 0.24608973264227466, 0.26267381792511035, 0.2815167736151915, 0.30401875607942624, 0.3315108523700484, 0.3652137252329373, 0.40619874593738653, 0.4553526659164051, 0.513346792274801, 0.5806115213638242, 0.6573169515776326, 0.7433601446018815, 0.8383594373210833, 0.9416560286377285, 1.0523228810229213, 1.1691807903263227, 1.2908212939001626, 1.4156359110536445, 1.5418510456899968, 1.6675677328419298, 1.7908052824730558, 1.9095477686292566, 2.0217922325132847, 2.1255974163895663, 2.2191318227882633, 2.3007199009267065, 2.3688851995208693, 2.422389391395871, 2.4602661689786567, 2.481849128639527, 2.4867929030834657, 2.475086961159172, 2.4470616696589285, 2.4033863976512815, 2.3450596360714537, 2.27339129897923, 2.1899775633218397, 2.096668786522683, 1.9955312112555488, 1.8888033201557504, 1.7788478361658084, 1.6681004734113445, 1.5590166262293506, 1.4540172381490668, 1.3554351168771026, 1.2654629550181902, 1.1861042794744134, 1.1191284860620332, 1.0660310214435842, 1.0279996542624512, 1.0058876342876122, 1.000194375890509], [1.0062353373301178, 1.02906655418033, 1.0678773146840943, 1.1218467531262195, 1.1898165201725328, 1.2703166735134226, 1.3615985626748295, 1.4616739322377559, 1.5683593212985718, 1.679324712951064, 1.7921452888752087, 1.9043550731518453, 2.0135012078809367, 2.117197592035955, 2.2131766344644666, 2.2993379215209875, 2.373792678230994, 2.434903007167849, 2.4813150187534125, 2.5119851172538734, 2.526198874608385, 2.5235821052543246, 2.5041039448377065, 2.4680719294529085, 2.416119265084319, 2.3491846644925602, 2.268485306312404, 2.1754836342778465, 2.0718488592953825, 1.9594141500435676, 1.8401305959271905, 1.716019097218819, 1.5891213794172288, 1.461451341295392, 1.3349479285946335, 1.2114306783822846, 1.0925590039937847, 0.9797961891878065, 0.8743789352627086, 0.7772931596028714, 0.6892565821331234, 0.6107084615554104, 0.5418066604261855, 0.48243203170346427, 0.43219993402700996, 0.3904785033357654, 0.356413138963497, 0.328956507313124, 0.30690322945002496, 0.2889283038677157, 0.27362822510976464, 0.25956369510438576, 0.24530278853319604, 0.2294634271511257, 0.21075404080556298, 0.18801134433994857, 0.16023423826211858, 0.12661294497851258, 0.08655261887675698, 0.039690814350235984, -0.014091642716364051, -0.07466666154859673, -0.1416618726732542, -0.21447051261558858, -0.2922679455301043, -0.3740343863821229, -0.4585832275817331, -0.5445942234873037, -0.6306506586966437, -0.7152795198078706, -0.7969936090775371, -0.8743344842220695, -0.9459150829110452, -1.0104608939827415, -1.0668485700351364, -1.114140937037446, -1.1516174444817897, -1.1787992121874635, -1.1954679643924462, -1.2016782948743816, -1.1977628747195772, -1.1843303928103375, -1.1622562036613864, -1.1326658432772114, -1.0969117565497848, -1.0565437547661787, -1.013273884630258, -0.9689365366992175, -0.9254447475716664, -0.8847437533084955, -0.8487629287645723, -0.8193672967426167, -0.7983098108267113, -0.7871856058141232, -0.7873893699845781, -0.8000769249097727, -0.8261320027148852, -0.8661390899408229, -0.920363064327533, -0.9887361894050506, -1.0708528556682073, -1.1659722706232045, -1.2730291076948008, -1.3906519305905167, -1.5171890199879632, -1.6507410480170552, -1.7891998774276654, -1.9302926107352234, -2.071629883779971, -2.2107572912750983, -2.3452087517239177, -2.472560567574459, -2.5904849149676976, -2.696801506503241, -2.7895262099257763, -2.8669154746102676, -2.927505514555148, -2.9701453189556295, -2.994022706372131, -2.998682802524622, -2.9840385008559562, -2.950372654868041, -2.898331947231419, -2.828912578037563, -2.7434381085059343, -2.64352998226019, -2.5310714194359236, -2.4081655351718334, -2.277088669678045, -2.1402400287873786, -2.0000888189824595, -1.859120117313546, -1.7197807430414414, -1.5844263936558152, -1.4552712732812105, -1.3343413772866923, -1.2234325047799244, -1.1240739528948942, -1.0374987063022592, -0.9646207756648462, -0.906020163774888, -0.8619357521617036, -0.8322662086273268, -0.8165788221805333, -0.8141259809561116, -0.823868825599783, -0.8445074397425905, -0.8745167847431243, -0.9121874515895189, -0.9556701919676474, -1.0030231056740757, -1.0522603047887058, -1.1014008476304697, -1.1485167380773438, -1.1917788181734363, -1.2294994431668884, -1.2601709166045076, -1.2824987765597184, -1.2954291595829353, -1.2981696230879893, -1.2902029757196287, -1.2712938445226476, -1.241487892938639, -1.201103790139746, -1.1507182152949473, -1.0911443554734581, -1.0234045186496847, -0.9486976296301742, -0.8683625030385341, -0.7838378906410703, -0.696620377731833, -0.6082212531270683, -0.5201234983483899, -0.4337400333278696, -0.3503743187102872, -0.27118434954946896, -0.19715098359294098, -0.12905143177794176, -0.06743860197946325, -0.012626832941670205, 0.03531561238884828, 0.07656710196200166, 0.11154622788317609, 0.14089860967654327, 0.1654772571118867, 0.18631701095400663, 0.20460373558940437, 0.2216390759183212, 0.23880170864445685, 0.2575061121421292, 0.2791599470187384, 0.305121179562397, 0.33665609141386155, 0.3748993006989244, 0.42081687290857, 0.4751735251520551, 0.5385048268636048, 0.6110951761011607, 0.6929621863114107, 0.7838479574408276, 0.8832175315649278, 0.9902646511311904, 1.1039247520267212, 1.2228949386550627, 1.3456605086917894, 1.470527425710382, 1.5956599827119236, 1.719122762690031, 1.8389258872029433, 1.9530724534611485, 2.0596069970148774, 2.156663782415867, 2.242513719196441, 2.3156087253830373, 2.3746224150262356, 2.418486068637491, 2.4464189540263126, 2.457952197227881, 2.4529455558067066, 2.431596616111533, 2.394442117913351, 2.342351299835697, 2.2765113524278897, 2.1984052578861273, 2.10978248156507, 2.0126231559539547, 1.9090965583797945, 1.8015148253687086, 1.6922829658278604, 1.5838463290335467, 1.478636749474564, 1.3790186272319493, 1.2872362088251121, 1.2053633091138993, 1.1352566604591785, 1.0785139921938545, 1.0364378335285642, 1.010005898958913, 0.9998487602927529, 1.0062353373301178], [1.0206839974995523, 1.0552876734479617, 1.1053845517684815, 1.1699368712650133, 1.247584328616021, 1.3366743115546271, 1.4352986826631262, 1.541336248246787, 1.6524999131180373, 1.7663874126851375, 1.8805344311403072, 1.9924688607627232, 2.099764933666735, 2.2000959642715476, 2.2912844781311876, 2.3713485695832555, 2.438543425271156, 2.491397070607929, 2.5287395387002456, 2.5497248226127858, 2.5538451481407427, 2.54093729112654, 2.511180856207957, 2.465088627982015, 2.4034892961533867, 2.3275030386445636, 2.2385106164251183, 2.1381167868367315, 2.028108974739154, 1.9104122496826894, 1.7870417399196095, 1.6600536684494902, 1.531496221203898, 1.40336145239787, 1.2775393972380333, 1.1557754985444, 1.0396323630929867, 0.9304567479656352, 0.8293525398587248, 0.7371603346462999, 0.654444054455888, 0.5814848593869074, 0.518282425313856, 0.46456347263048847, 0.41979724798025764, 0.383217486552181, 0.3538502207519465, 0.330546656011577, 0.3120202097774054, 0.2968867084001422, 0.2837066612353436, 0.271028483586985, 0.2574315213317159, 0.2415677405607292, 0.2222009850476607, 0.19824277174459576, 0.16878368807331742, 0.13311957210817602, 0.09077179483736009, 0.04150111901771978, -0.014685222250286387, -0.07753340649380065, -0.1465498595604758, -0.2210148652581577, -0.3000025849757858, -0.3824069573886292, -0.4669727939455703, -0.5523312488833005, -0.6370387265001732, -0.7196181963133744, -0.7986018208785804, -0.8725737631733269, -0.9402120315326158, -1.000328240448412, -1.0519042146383826, -1.0941244404639159, -1.1264034711479933, -1.148407517776366, -1.1600696036408285, -1.1615978214735805, -1.1534764074800683, -1.1364595284411787, -1.111557863951514, -1.080018250421809, -1.043296832155243, -1.003026333101679, -0.960978216544181, -0.9190206350782224, -0.8790731863612291, -0.843059578334402, -0.8128593686613251, -0.7902599753718343, -0.7769101582420592, -0.7742761431167499, -0.7836015047646893, -0.8058718392583776, -0.8417851462891464, -0.8917287079219796, -0.9557630962981961, -1.033613772451684, -1.1246705558711811, -1.2279950541836824, -1.342335949018879, -1.4661518424937807, -1.5976411835498792, -1.7347786191529506, -1.8753569564361476, -2.0170337821702358, -2.1573816689525964, -2.2939408061393127, -2.4242728300957936, -2.5460145944221417, -2.6569306173079594, -2.7549629702286733, -2.838277429204824, -2.905304795462246, -2.9547764045091713, -2.9857529786855066, -2.997646134853533, -2.9902320322949514, -2.9636568318501695, -2.918433831365663, -2.8554323398891848, -2.775858548972179, -2.681228849141249, -2.5733362184745894, -2.4542104739202264, -2.326073320547222, -2.1912892558261494, -2.052313482344535, -1.9116380507575301, -1.7717374936210406, -1.6350152191452694, -1.503751911679574, -1.3800571334834477, -1.2658252413776763, -1.1626966242305266, -1.0720251355943586, -0.9948524434308504, -0.9318898495165632, -0.8835079489817412, -0.8497343099901994, -0.83025915949861, -0.8244488681019239, -0.8313668399035982, -0.8498012367167384, -0.8782988040109209, -0.9152039228025305, -0.9587018906084043, -1.0068653385536181, -1.057702623029393, -1.1092069905405468, -1.1594053044483053, -1.2064051423477467, -1.2484391222209157, -1.2839053929512012, -1.3114033282538116, -1.3297635899102218, -1.338071873157299, -1.3356858104459157, -1.3222446854211176, -1.2976717924617414, -1.2621694638407592, -1.2162069718471002, -1.1605016924087839, -1.0959940854014476, -1.0238172007135529, -0.9452615544447294, -0.8617363329840464, -0.7747279713530468, -0.6857572139314413, -0.5963357990164961, -0.5079239128211588, -0.42188953344447266, -0.33947073173974546, -0.2617419152655269, -0.18958489571779105, -0.12366553212224297, -0.06441655488676443, -0.012027013326656014, 0.03356138438639433, 0.07265095032333417, 0.10577780901747691, 0.1336950770208023, 0.15734987712420606, 0.17785479625193365, 0.19645454218529634, 0.2144886811583533, 0.2333514427633145, 0.25444965783551043, 0.2791599470187383, 0.30878630118703254, 0.3445191891816896, 0.38739729351027524, 0.43827291157734927, 0.4977819702168804, 0.5663194869898782, 0.6440211757333352, 0.7307517395822146, 0.8261002259842735, 0.9293826393057621, 1.0396518219666302, 1.1557144292810397, 1.2761546409830118, 1.3993640783793067, 1.5235772345876442, 1.6469115804792707, 1.7674113844353356, 1.8830941830300993, 1.991998764875824, 2.0922334830633975, 2.182023694172892, 2.259757134245987, 2.3240260842008964, 2.3736652479865947, 2.4077843646559405, 2.4257946981513445, 2.4274286929871987, 2.412752246679196, 2.382169226750631, 2.3364180471153184, 2.276560311015219, 2.2039617207542874, 2.1202656434680724, 2.0273599024414097, 1.9273375305809823, 1.8224523724291288, 1.7150705498518464, 1.6076189110419206, 1.5025316601323653, 1.4021964135571428, 1.3089009480720524, 1.224781893542288, 1.1517765814483518, 1.091579188536824, 1.0456022158483436, 1.0149442188713127, 1.0003645577997182, 1.0022657713672294, 1.0206839974995523], [1.0434181141956862, 1.0894956394932418, 1.150437256435111, 1.224997100393321, 1.311624443030846, 1.4084980122179176, 1.5135663635829961, 1.6245933557098975, 1.7392076612644334, 1.854955152437155, 1.969352933285302, 2.0799437554187934, 2.1843495478467982, 2.2803228167796514, 2.3657947261123584, 2.438918752813994, 2.4981089214265286, 2.5420717556052703, 2.5698312387997513, 2.5807462469712608, 2.5745200994607793, 2.551202065250484, 2.5111808562079565, 2.4551703316987084, 2.3841878254806166, 2.2995256814975105, 2.2027167457884373, 2.0954947033248987, 1.979750267758308, 1.857484325942562, 1.7307592054611278, 1.6016492706886871, 1.4721920603307217, 1.3443411568283024, 1.219921926150913, 1.1005911867121998, 0.9878017605079146, 0.8827727308035063, 0.7864660820716449, 0.6995702331642858, 0.6224907980583391, 0.5553487243852774, 0.4979857729662739, 0.44997711641063887, 0.4106506561256052, 0.3791124892886841, 0.35427780462692865, 0.3349063520220993, 0.3196415193289848, 0.3070519631062842, 0.29567468033607264, 0.2840583770874639, 0.27080598818378054, 0.25461522924694285, 0.2343161182706999, 0.2089044866543456, 0.1775706072719854, 0.13972219689743628, 0.09500119883594568, 0.043293915145402144, -0.015265767799348254, -0.08030013586675738, -0.15119827872587246, -0.22713330949718494, -0.30708571320082, -0.389872204074119, -0.47417932704178933, -0.5586009133592156, -0.6416783979058946, -0.7219429284031077, -0.7979581469525248, -0.8683625030385332, -0.9319099650845973, -0.9875080346463786, -1.034252032473627, -1.071454717381636, -1.0986704148735014, -1.1157129698652464, -1.1226669932627633, -1.1198920416418041, -1.1080195486476057, -1.0879425114630334, -1.060798121153502, -1.0279437072170354, -0.9909265396718797, -0.9514481921287096, -0.9113243124605152, -0.8724407702557411, -0.836707249081719, -0.8060094241431432, -0.7821609102921617, -0.766856180328516, -0.7616256386454058, -0.7677939907971475, -0.7864429764925654, -0.8183794335709564, -0.8641095360839992, -0.923819903689143, -0.9973661156990605, -1.084268985321668, -1.183718762213856, -1.2945872390546762, -1.4154475451483333, -1.544601221839389, -1.6801119954062336, -1.8198454975226994, -1.9615140354446305, -2.1027253874645595, -2.241034497039832, -2.373996863898343, -2.4992223842602463, -2.6144283762742484, -2.717490541305851, -2.8064906565331666, -2.879759868362863, -2.9359165577127313, -2.9738978747832046, -2.9929841895048286, -2.9928158708087413, -2.97340198917577, -2.93512072817605, -2.878711487268575, -2.8052588552113744, -2.7161688262459003, -2.613137815076468, -2.4981151970980235, -2.373260253194416, -2.2408945300254715, -2.1034507338582467, -1.9634193560897673, -1.823294279731916, -1.6855186370724298, -1.552432179016971, -1.4262213765351737, -1.3088734052016056, -1.2021350667823016, -1.107477579585032, -1.0260680248978085, -0.958748073855161, -0.9060204415180055, -0.8680433272021605, -0.8446329067596356, -0.8352737483508494, -0.8391368330021253, -0.8551046795729803, -0.8818029050934237, -0.9176373998750665, -0.9608361660231113, -1.0094947611310163, -1.0616242085796812, -1.1152001838823398, -1.1682122641032238, -1.2187120349864804, -1.2648588877713123, -1.304962403713422, -1.3375203173457428, -1.361251167092344, -1.375120880991758, -1.3783627024557517, -1.3704900322111024, -1.3513019435291, -1.3208813139912623, -1.2795857037012845, -1.228031292361297, -1.1670703614263682, -1.097762968303886, -1.0213436032769982, -0.9391837429409235, -0.8527513134069017, -0.7635681499079505, -0.6731665849484993, -0.5830463136929126, -0.4946326725314803, -0.40923742507770505, -0.3280230803460405, -0.2519716723398369, -0.18185881120363417, -0.11823367651012293, -0.06140546672185701, -0.01143664937712854, 0.03185682159189086, 0.06889833726701351, 0.10033671149941076, 0.1270258792798123, 0.14999875703436247, 0.17043595935489325, 0.1896302021300097, 0.2089473363116537, 0.22978504671447547, 0.2535303139917494, 0.2815167736151913, 0.31498311236590193, 0.3550336203083243, 0.40260196499239964, 0.4584191759576389, 0.5229867234351946, 0.5965554480426759, 0.6791109514042747, 0.7703658946694057, 0.869759476920972, 0.9764641828421496, 1.0893997033308305, 1.2072537486812092, 1.328509296128186, 1.4514776464620158, 1.5743365122970174, 1.6951722272833145, 1.812025054487028, 1.9229364861854452, 2.025997368664357, 2.1193956558232205, 2.201462595331686, 2.2707161808428484, 2.3259007627157864, 2.366021796468225, 2.3903748207094804, 2.398567891891036, 2.3905368585753997, 2.366553029283833, 2.327222971156608, 2.2734803671599737, 2.206570052726031, 2.1280245437636878, 2.039633552221621, 1.9434071582668866, 1.841533465386607, 1.7363317024236353, 1.630201851292517, 1.5255719680223991, 1.424844425602012, 1.3303423383085944, 1.2442574279636802, 1.1686005627968226, 1.1051561399858683, 1.0554413948840937, 1.0206716055461327, 1.0017320231778009, 0.9991572008938313, 1.0131182185036414, 1.0434181141956858], [1.074245346503965, 1.1314010374441459, 1.202654262415922, 1.2865616060576799, 1.3813950550705756, 1.4851801144950874, 1.5957394254373274, 1.7107408618236788, 1.8277489789527386, 1.9442786090514543, 2.057849350591215, 2.1660396799284247, 2.2665394263101883, 2.357199394084982, 2.436076987993787, 2.501476796887214, 2.5519852156459435, 2.5864983313942402, 2.6042424646748814, 2.6047869350418718, 2.588048809124804, 2.554289582992205, 2.5041039448377065, 2.4384009538776255, 2.358378152241915, 2.2654892941527622, 2.161406526744858, 2.0479779858555704, 1.927181874896468, 1.8010781730081848, 1.6717591682614015, 1.5413000315697574, 1.4117106368341263, 1.2848897929941965, 1.1625829852108729, 1.0463446271349706, 0.9375057065900534, 0.8371475660638754, 0.7460824007406909, 0.664840884425081, 0.5936671519486131, 0.5325211800793702, 0.4810884222466395, 0.4387963702179371, 0.404837542769023, 0.3781982416796558, 0.357692273035377, 0.34199871034365686, 0.329702678377275, 0.3193380653314972, 0.3094310275547692, 0.2985431368107144, 0.2853130350478064, 0.2684955055514254, 0.2469969409654533, 0.21990628613658061, 0.18652065454557543, 0.1463649581528544, 0.09920504820085865, 0.0450540348667934, -0.015828367685504732, -0.08294344188501242, -0.15556780243987123, -0.23277408052578058, -0.31345740373527103, -0.3963669670735703, -0.48014185633940293, -0.5633501727165269, -0.6445304191942404, -0.7222340477916379, -0.7950680330720505, -0.8617363329840453, -0.9210791228058679, -0.9721087413189357, -1.0140413689896874, -1.0463235639060493, -1.0686529098637476, -1.0809921791238846, -1.0835765762669232, -1.07691380514851, -1.0617768838173758, -1.039189817793738, -1.0104064256604668, -0.9768827878624028, -0.940243955471932, -0.9022457062592758, -0.8647322668764565, -0.8295910289658013, -0.7987053707333261, -0.7739067518045628, -0.7569272765060967, -0.749353918309066, -0.7525855659888623, -0.7677939907971472, -0.7958897450316078, -0.8374938879398731, -0.8929162976598777, -0.9621411712046909, -1.0448201421604146, -1.1402732619923772, -1.2474979001509547, -1.36518542521887, -1.491745338896534, -1.6253363513793282, -1.7639037151702532, -1.9052219788420928, -2.0469421865781783, -2.18664243686151, -2.3218806272627233, -2.4502481540777676, -2.5694233070739836, -2.677223101578721, -2.771652322600673, -2.85094861787404, -2.913622567193599, -2.9584917720011035, -2.984708149086164, -2.991777772097904, -2.9795727804572945, -2.9483350629475487, -2.898671618183416, -2.831541691582404, -2.748235983582122, -2.6503484119228986, -2.539741087271325, -2.4185033220092387, -2.2889056327562254, -2.153349814718238, -2.01431625741757, -1.8743097345562423, -1.735804934184506, -1.6011929982085926, -1.4727303125452835, -1.3524907316329038, -1.2423223349879535, -1.143809701197778, -1.058242548948045, -0.9865914387575666, -0.9294910568792151, -0.8872314185668818, -0.8597571361342221, -0.8466747026497541, -0.8472675494932275, -0.860518450051702, -0.8851386670991602, -0.9196030821344521, -0.9621904050130994, -1.0110274449783951, -1.0641363324886974, -1.1194835172267454, -1.1750293328501569, -1.2287769141622056, -1.2788192774680405, -1.3233834292111357, -1.3608704501124524, -1.389890609829106, -1.4092926978471263, -1.4181869065973682, -1.4159607688306206, -1.4022878289183263, -1.3771289124914234, -1.3407260460566415, -1.2935892632500572, -1.23647671258022, -1.1703686484354547, -1.0964360386309897, -1.0160046540936494, -0.9305156161543201, -0.8414834616384905, -0.7504528434450839, -0.6589550132015276, -0.5684652322157159, -0.48036222738655987, -0.3958907507894939, -0.3161282168400843, -0.24195628144863546, -0.1740380962215533, -0.11280182089800289, -0.058430812653149054, -0.010860735839243513, 0.030216345377902843, 0.06534101159757294, 0.09526896947610516, 0.1209474408843084, 0.1434860906447357, 0.16412326698009633, 0.18418845242846127, 0.20506192366311268, 0.2281326938223256, 0.25475585867577216, 0.2862104869886151, 0.3236591852723429, 0.36811042794860016, 0.4203846767443665, 0.48108521953649297, 0.5505745411894897, 0.6289569001095626, 0.7160676277334984, 0.8114694978953367, 0.9144563332319623, 1.0240638310111307, 1.139087405636277, 1.2581066642632956, 1.3795159600173053, 1.5015603085722786, 1.6223758123802459, 1.7400336162139003, 1.8525863210085551, 1.9581157127554385, 2.0547806212541544, 2.1408637110217756, 2.2148160239922423, 2.2752981404937898, 2.321216900299169, 2.351756727529674, 2.366404729417805, 2.364968886346621, 2.3475888156053535, 2.3147387699051656, 2.2672227195152534, 2.2061615592993644, 2.132972674224212, 2.0493422843353963, 1.957191168125156, 1.8586345272462677, 1.7559369015891553, 1.651463168201608, 1.5476267572840563, 1.4468362910339068, 1.3514418946004882, 1.2636824417198618, 1.1856349803384765, 1.1191675360691644, 1.0658964147572119, 1.0271490215878287, 1.0039330855316078, 0.9969130276021828, 1.0063940430270106, 1.0323142850884266, 1.0742453465039645], [1.1129048820895784, 1.1806493286716004, 1.2615937902118521, 1.3541095246819124, 1.4563058737857923, 1.5660718531018245, 1.681122646939098, 1.7990499197042171, 1.9173747665699061, 2.033602065665754, 2.145274963322554, 2.250028223811414, 2.3456392054937614, 2.43007528555649, 2.501536644036871, 2.558493432442219, 2.599716490101002, 2.6243009290404085, 2.6316820817834747, 2.6216434917250044, 2.594316818127249, 2.5501737225544896, 2.4900099959697366, 2.4149223710433625, 2.326278637951893, 2.225681839848897, 2.1149294624405766, 1.9959686473600984, 1.870848548544714, 1.741671012457459, 1.6105407953329618, 1.479516532963989, 1.3505636509250487, 1.2255103463356378, 1.1060076878044325, 0.9934947702535838, 0.8891697287147722, 0.7939672632860622, 0.7085431600837468, 0.6332661144342295, 0.568216977215647, 0.5131953578235956, 0.4677333323881793, 0.4311158282245186, 0.40240708947997167, 0.38048247867357066, 0.3640647380294917, 0.35176372641552067, 0.34211856496400095, 0.3336410690914316, 0.3248593179691451, 0.31436021513504925, 0.30082992574281014, 0.28309113605574415, 0.2601361676337856, 0.23115508998931006, 0.19555810844421037, 0.1529916551083258, 0.10334777646420823, 0.0467665867725873, -0.016368262059139587, -0.08544096098354169, -0.15962146255461968, -0.23788945486856475, -0.3190637491939945, -0.401836297753094, -0.48480993614247797, -0.5665388460720072, -0.6455706609745567, -0.7204890914772053, -0.7899559309083777, -0.8527513134069007, -0.9078111385231175, -0.9542606454558931, -0.9914432155450671, -1.018943600967536, -1.0366049177941903, -1.0445388991532893, -1.043129075269708, -1.033026727322305, -1.0151396468588862, -0.99061391728258, -0.9608091140187821, -0.9272674908409807, -0.8916778771518621, -0.8558351507882122, -0.8215962695807871, -0.7908339394094448, -0.7653890644029238, -0.7470231644532701, -0.7373719552633095, -0.7379012663700327, -0.7498664233777828, -0.7742761431167492, -0.8118618864452646, -0.8630534854317781, -0.9279617127786415, -1.0063682952048707, -1.0977236931452028, -1.201152780940953, -1.3154683693151399, -1.4391923200752714, -1.570583816403226, -1.707674175384628, -1.848307426976549, -1.9901857394458697, -2.130918649021522, -2.268074954150292, -2.399236064776294, -2.5220495562585663, -2.6342816669637217, -2.733867498544548, -2.818957728014186, -2.8879607197808936, -2.9395790319418773, -2.9728394417990835, -2.9871157676057445, -2.9821439333019057, -2.958028906336133, -2.9152433311490906, -2.854617877836215, -2.7773235221232317, -2.6848461642985564, -2.5789541764924246, -2.4616596352554483, -2.33517414569627, -2.2018602908654628, -2.064179842531457, -1.9246399445086175, -1.7857385254646974, -1.6499102135680117, -1.519474010092104, -1.396583933586063, -1.2831837715921346, -1.180966975011201, -1.0913426036094789, -1.0154080829578593, -0.9539293669557385, -0.9073289201055804, -0.8756817442994884, -0.8587194807039055, -0.8558424231434014, -0.8661390899408231, -0.8884128210951223, -0.9212147013571322, -0.9628819612372814, -1.0115808808410869, -1.0653531187366072, -1.1221643122621687, -1.1799537485620204, -1.2366838882595779, -1.2903885363721768, -1.3392184974227537, -1.3814836225639793, -1.4156902540467917, -1.4405731940290538, -1.4551214674289326, -1.458597308662831, -1.450547975627055, -1.4308101768187764, -1.3995070844638295, -1.357038093244763, -1.3040616660366111, -1.2414717804272217, -1.1703686484354545, -1.0920245228082344, -1.0078455230894998, -0.9193305103599059, -0.8280281088035347, -0.7354930133918665, -0.643242735018315, -0.5527159171322177, -0.4652333118097736, -0.38196242948375647, -0.3038867771496245, -0.2317804773308783, -0.16618891755921072, -0.1074159212423041, -0.055517759600108144, -0.010304145202135294, 0.02865383491552456, 0.06200906989988413, 0.09061745833825671, 0.1155111881736413, 0.13786697805999726, 0.1589701273615597, 0.180175332745546, 0.20286531556190615, 0.2284083637400307, 0.25811592322498667, 0.293201376199941, 0.33474111640359927, 0.3836389763925574, 0.4405949789779854, 0.5060792773287327, 0.5803120180579344, 0.6632497122442284, 0.7545785345161745, 0.8537147941771236, 0.9598126392872952, 1.0717788692501096, 1.1882945484375236, 1.3078429373502687, 1.428743093193089, 1.549188342725979, 1.6672887006205934, 1.7811161996206655, 1.888752017330962, 1.9883342305645157, 2.0781050033037345, 2.156456019197677, 2.2219710041055967, 2.273464247746804, 2.3100141245465613, 2.3309907301091775, 2.336076888599833, 2.3252819443087276, 2.2989479239547976, 2.2577478406237583, 2.202676101105877, 2.135031171110099, 2.056390842635082, 1.9685806299883046, 1.873635991053737, 1.7737592241980402, 1.671272024851241, 1.5685647959660156, 1.4680438904874322, 1.3720780195320663, 1.2829450857550908, 1.2027806966800325, 1.1335295776303098, 1.0769010391341296, 1.0343295608030456, 1.00694143492856, 0.9955282712583586, 1.0005280030276493, 1.0220138572401014, 1.0596915637119584, 1.1129048820895777], [1.1590696437878334, 1.2368238503467153, 1.3267571847473068, 1.4270693703086763, 1.5357231197526333, 1.6504888473255868, 1.7689936473980545, 1.8887733947615386, 2.0073267493965634, 2.1221698054177707, 2.2308901112350696, 2.3311988059812636, 2.4209796654725655, 2.498333928175609, 2.5616198759306523, 2.60948627294189, 2.6408989166111674, 2.6551597214618177, 2.6519179385482246, 2.631173302923442, 2.5932710962756467, 2.5388893059790894, 2.4690182507890555, 2.384933222630878, 2.2881608590266387, 2.180440107662404, 2.0636787698707186, 1.9399067103766474, 1.8112268941351022, 1.6797654557506898, 1.547622021812413, 1.4168214912269392, 1.2892684337736067, 1.1667051938408637, 1.050674686548264, 0.9424887497720891, 0.8432027711271751, 0.7535971473708768, 0.6741659590634708, 0.6051130600335999, 0.5463555938540171, 0.4975347628192714, 0.4580334934943433, 0.42700047129113267, 0.4033798589930693, 0.38594587459183083, 0.3733412856718491, 0.3641187837830025, 0.3567841350703863, 0.349839964502095, 0.3418290212609135, 0.331375792420535, 0.317225380352039, 0.2982786351212344, 0.2736226344725148, 0.24255572824179797, 0.2046065080184132, 0.15954622290899256, 0.10739433427028061, 0.048417081898722264, -0.01688088316954688, -0.08777156302063134, -0.1633249632712449, -0.24243615414386405, -0.32385731735750933, -0.40623392310024103, -0.4881440723835502, -0.5681399558061783, -0.6447903223306671, -0.7167228225798314, -0.7826650911590637, -0.8414834616384894, -0.8922182653872095, -0.9341147500246075, -0.9666487627436887, -0.9895464754421299, -1.0027975791796198, -1.0066615411973094, -1.0016666944322574, -0.9886021127007284, -0.968502409900397, -0.9426257840287294, -0.912425801927976, -0.8795175840167483, -0.8456391957106593, -0.8126091800158197, -0.7822812706298897, -0.7564974041021014, -0.7370402011178676, -0.7255861094032192, -0.7236603934303975, -0.7325951191292045, -0.7534912159890832, -0.7871856058141222, -0.8342242691896998, -0.8948419802860393, -0.9689492813701548, -1.0561270942076386, -1.1556291806729644, -1.2663924738887946, -1.387055108780295, -1.515981791804893, -1.6512959684738842, -1.7909180786059133, -1.9326090372301243, -2.0740179474727825, -2.2127329439026093, -2.3463339833860073, -2.4724463475754432, -2.5887935980877854, -2.693248732856051, -2.783882329941514, -2.8590065324106506, -2.917213823123428, -2.9574096591704944, -2.9788381793277843, -2.981100360799808, -2.96416417975241, -2.928366519369036, -2.8744067648055895, -2.8033322217123295, -2.7165156891386837, -2.6156257039160353, -2.50259014749248, -2.3795540634451533, -2.248832670697607, -2.1128606705029904, -1.9741390317796996, -1.8351804973175943, -1.6984550813229764, -1.566336826086653, -1.4410530523406933, -1.324637274961934, -1.218886864656568, -1.125326419380369, -1.0451776694046344, -0.9793365805795693, -0.9283581453995238, -0.8924491652398431, -0.8714691341864147, -0.864939139945695, -0.87205850517676, -0.8917287079219799, -0.9225839471310124, -0.9630275627724817, -1.0112733835007857, -1.0653909615840786, -1.1233535675151056, -1.1830877574845864, -1.2425232970653182, -1.2996422246728347, -1.3525258685296635, -1.3993986901188453, -1.4386679139034402, -1.4689580151689108, -1.4891392723491237, -1.4983497437093458, -1.4960101969007562, -1.4818316994246674, -1.4558157639427058, -1.4182471299851933, -1.369679448255129, -1.3109143107945562, -1.2429742353680218, -1.1670703614263682, -1.084565744255714, -0.9969352402048934, -0.9057230566140198, -0.8124990932756345, -0.7188152266799489, -0.6261626833821784, -0.5359316147746708, -0.4493739232728135, -0.3675703010613766, -0.2914023293937568, -0.22153035189400555, -0.15837768281988368, -0.10212154469126115, -0.052690953309734535, -0.009771586474453949, 0.027182509750311782, 0.05893070190843036, 0.08642153197492441, 0.11076311430567569, 0.13318895951529142, 0.15502013839227824, 0.17762479588973876, 0.20237609630654682, 0.23060972417534492, 0.2635820799728598, 0.30243029516302794, 0.34813514760766945, 0.4014878870936118, 0.46306188339109366, 0.5331898882954955, 0.61194756152986, 0.6991437517383394, 0.7943178520545373, 0.8967443691920077, 1.00544466021378, 1.1192056067442833, 1.2366048170399861, 1.3560417765658914, 1.4757742118333381, 1.593958794202245, 1.708695193660233, 1.8180724002579078, 1.920216165298197, 2.0133363772779767, 2.095773179986556, 2.1660406623681565, 2.2228670013023257, 2.2652300181643774, 2.292387216010144, 2.303899493941635, 2.2996478855123885, 2.279842835265543, 2.24502570757735, 2.1960624104900206, 2.1341292095279, 2.060690997863127, 1.977472474907558, 1.8864228608632543, 1.7896749356145376, 1.6894993325925047, 1.5882551383413601, 1.488337943457912, 1.3921265579674027, 1.301929642322287, 1.2199335130638114, 1.148152359510498, 1.088382055124056, 1.0421586656815964, 1.0107226479919857, 0.9949896002334617, 0.9955282712583591, 1.0125463651263047, 1.0458844928368143, 1.0950184302087225, 1.1590696437878325], [1.2123490568249693, 1.2994493405968581, 1.3975931342177443, 1.504823869629262, 1.6189748871335048, 1.7377168911961158, 1.858608998388233, 1.9791521857963228, 2.0968438929542605, 2.2092325051518444, 2.313970451436126, 2.4088646865827075, 2.491923391863233, 2.561397822938392, 2.6158183523453378, 2.654023895881078, 2.675184073212902, 2.67881362931082, 2.664778830464072, 2.6332957421221566, 2.5849204908500565, 2.520531804536489, 2.4413063089587643, 2.348687230405985, 2.2443473091243513, 2.1301468631196983, 2.0080880530856278, 1.8802664842604138, 1.7488213378430446, 1.6158852519102007, 1.4835351689948086, 1.353745334781533, 1.2283435706533037, 1.1089718537096152, 0.9970521236714636, 0.8937580997042474, 0.7999937350887389, 0.7163787677666478, 0.6432416443563551, 0.5806199088028239, 0.5282679590593518, 0.4856718907866345, 0.4520709705914001, 0.42648511719965604, 0.40774762123805147, 0.39454220663275325, 0.38544343217170923, 0.3789593530700463, 0.3735753113370848, 0.36779770157822955, 0.3601965660613479, 0.34944590918369994, 0.33436068591047097, 0.3139295096333806, 0.28734223986948937, 0.2540117463355807, 0.21358929971333876, 0.1659732069452854, 0.11131048590894813, 0.04999155630957363, -0.017361894010168858, -0.08991553004843816, -0.16664697129783107, -0.24637571121840468, -0.327797552470038, -0.40952263721462634, -0.49011605676130626, -0.5681399558061782, -0.6421960052806065, -0.7109671054386445, -0.7732571976275304, -0.8280281088035333, -0.8744324261607294, -0.9118414984165496, -0.9398677828758699, -0.9583809003141277, -0.9675169194027101, -0.9676805648439526, -0.9595402242583976, -0.9440158136258459, -0.922259745070167, -0.8956314193543922, -0.8656658341020349, -0.8340370532085178, -0.8025174192260565, -0.7729335052148079, -0.747119892705129, -0.7268719256699308, -0.7138986250895564, -0.7097769538405116, -0.71590859702502, -0.733480368993298, -0.7634292764370344, -0.806413158993248, -0.8627876973878023, -0.9325904274517324, -1.0155322300570468, -1.1109965862573183, -1.2180466981166824, -1.3354403835122646, -1.4616524623371756, -1.5949041667292703, -1.7331989337793257, -1.8743637799536361, -2.0160953161613206, -2.1560093445084165, -2.2916928852653546, -2.420757417768704, -2.5408920835396605, -2.6499155947695257, -2.7458256166906203, -2.8268444476640324, -2.891459904782583, -2.938460433410185, -2.966963593704644, -2.9764372325532538, -2.966712821731936, -2.9379906283003754, -2.8908365767721267, -2.8261708597470703, -2.7452485496695913, -2.6496326544116675, -2.541160238852011, -2.421902399163521, -2.2941190221311496, -2.1602093849617026, -2.0226597487298625, -1.8839891684658587, -1.7466947832485975, -1.613197859564727, -1.4857918404159112, -1.3665936017428255, -1.257499037961091, -1.1601439917535614, -1.0758714123737325, -1.005705474816488, -0.950333223045836, -0.9100941181943975, -0.8849776817413333, -0.8746292288154454, -0.8783634927279779, -0.8951857533579671, -0.9238199036891432, -0.9627427249704976, -1.0102234956170997, -1.0643679355952471, -1.1231653896096498, -1.184538081271722, -1.246391228241195, -1.3066627960432573, -1.3633716860748988, -1.4146632006871505, -1.4588507038942577, -1.4944524982485994, -1.5202230641157801, -1.5351779537903265, -1.5386117959100154, -1.530109041347126, -1.5095472657640838, -1.477093031707889, -1.4331904997904372, -1.378543159504074, -1.3140892210483828, -1.2409713659539527, -1.1605016924087839, -1.0741228076151184, -0.9833661113699934, -0.889808380132795, -0.7950277975531156, -0.7005605849316984, -0.6078593632587712, -0.5182543279360035, -0.43291823937915735, -0.3528361294413201, -0.2787804976497731, -0.2112926258374478, -0.15067047858409094, -0.09696348406622857, -0.04997430984238924, -0.00926756534402124, 0.025814817958944445, 0.056131952009396725, 0.08271668982182034, 0.10674339013386246, 0.12949161316433394, 0.15230671876632262, 0.1765584205569707, 0.20359840491330933, 0.2347181506228585, 0.2711080827598407, 0.3138191630473145, 0.36372795931969887, 0.4215061501905083, 0.4875953098059665, 0.5621876844003115, 0.6452135205922472, 0.7363353387755373, 0.834949367739966, 0.9401941732642586, 1.0509663284656539, 1.1659427918336078, 1.2836094847106418, 1.4022953979201769, 1.5202114113925325, 1.635492884722728, 1.7462449738313979, 1.8505895519453646, 1.946712563980768, 2.032910623421025, 2.1076356705329404, 2.1695365501148918, 2.2174964350407014, 2.2506651170548073, 2.2684853063124026, 2.270712223143948, 2.2574259260059035, 2.229035994641003, 2.186278372823646, 2.13020436615586, 2.062161982501894, 1.983769991063429, 1.896885256143585, 1.8035640688638586, 1.7060183503293842, 1.6065677292406801, 1.5075886024849563, 1.4114613661525808, 1.320517054710071, 1.236984646418266, 1.1629402829446802, 1.1002596106633167, 1.0505743812896038, 1.0152343519120763, 0.9952754014886639, 0.991394635432322, 1.0039330855316086, 1.0328664331164241, 1.0778039934384152, 1.1379960033025658, 1.2123490568249686], [1.272292353257483, 1.367995959436155, 1.473502334437012, 1.5867151843951048, 1.7053568283045109, 1.8270179959911264, 1.949210513488848, 2.069421647339546, 2.1851688417015303, 2.2940535750319038, 2.3938130866533402, 2.482368777121647, 2.5578701686380962, 2.618733420758409, 2.6636735296453695, 2.6917294928162123, 2.702281891967146, 2.6950625298234985, 2.6701559485657875, 2.6279928525251117, 2.56933565175107, 2.4952565309957566, 2.4071086260465444, 2.3064910518644046, 2.1952086707030634, 2.0752276098275635, 1.9486276347043932, 1.8175525523118508, 1.6841598589136089, 1.5505708563666039, 1.418822440654617, 1.290821716453585, 1.1683045134749521, 1.0527987761240367, 0.945593670320455, 0.847715103400503, 0.7599081885966606, 0.6826270088063355, 0.616031849658234, 0.5599938838845914, 0.5141071024067615, 0.4777071069910917, 0.4498962093211813, 0.42957412607890283, 0.4154734229698909, 0.40619874593738686, 0.4002687878933995, 0.3961598763450494, 0.39235003281478625, 0.38736234973820255, 0.3798065546300277, 0.3684176840599065, 0.3520908699792676, 0.32991134611170836, 0.3011789097548588, 0.26542622117367765, 0.22243048504648824, 0.17221823202401373, 0.1150630989652688, 0.05147668923916778, -0.017807225011633978, -0.09185472313575077, -0.1695593809432474, -0.24967479565666614, -0.33085111835955167, -0.4116746160866821, -0.4907092053955774, -0.5665388460720072, -0.6378096589205601, -0.7032706360251504, -0.761811845350175, -0.8124990932756331, -0.8546040970917173, -0.8876293324190847, -0.9113268551498239, -0.9257105504516951, -0.9310614288098551, -0.9279257667922607, -0.9171060737482445, -0.8996450503633614, -0.8768028862377043, -0.850028416849905, -0.8209248210278933, -0.7912106842871021, -0.7626773774399405, -0.7371438005474406, -0.7164096169744533, -0.7022081490661507, -0.696160124522872, -0.6997294503749324, -0.7141821497524943, -0.7405495263478831, -0.7795965242332231, -0.8317961288536636, -0.8973105115119168, -0.9759794579844681, -1.067316446014402, -1.1705125506224405, -1.2844481650345343, -1.4077123332514137, -1.538629302619003, -1.6752917258437607, -1.8155997761715523, -1.9573052910347841, -2.0980599320724074, -2.23546624623232, -2.367130436276048, -2.490715601366524, -2.60399419077064, -2.7048984265538407, -2.7915674942388784, -2.8623903727555913, -2.916043274914397, -2.9515207947039377, -2.9681600049349632, -2.9656569145716465, -2.9440748754930794, -2.9038447190347547, -2.8457565988422697, -2.7709437135573225, -2.680858275856643, -2.577240278680892, -2.462079780636933, -2.337573586368034, -2.20607733042275, -2.070054081588376, -1.9320206661606623, -1.794492961226847, -1.6599314314828926, -1.5306881748653567, -1.4089567035815829, -1.2967256189438445, -1.1957372424489603, -1.107452144169327, -1.0330203657292136, -0.9732599724726277, -0.928643391885564, -0.8992918072750815, -0.8849776817413328, -0.8851352923560591, -0.8988789629516262, -0.9250285007022105, -0.9621411712046911, -1.0085493931810015, -1.0624032009427173, -1.1217164135843878, -1.1844153671134778, -1.2483890113337668, -1.311539148524247, -1.37182959631103, -1.427333092384399, -1.4762748228971219, -1.517071547810108, -1.548365412773085, -1.5690516753756096, -1.578299730274929, -1.5755669888505377, -1.5606053503480217, -1.5334601884126358, -1.494461964800959, -1.4442107662090564, -1.3835542359835569, -1.3135595356206804, -1.2354801173665662, -1.1507182152949473, -1.0607840648559101, -0.9672529375548437, -0.8717211262807358, -0.7757620367036421, -0.6808835306766248, -0.588487629018684, -0.4998336144619343, -0.4160054826608275, -0.3378845723827812, -0.2661280683256715, -0.20115391495626736, -0.14313251128721696, -0.09198537889414318, -0.04739081323110117, -0.008796346057672787, 0.024562330832865107, 0.05363649889337783, 0.07953427652002001, 0.10348602434364107, 0.12680622023032223, 0.15085282524156476, 0.17698522876509742, 0.2065219000982794, 0.24069888393574135, 0.28063025819679616, 0.3272716248769782, 0.38138762929677594, 0.4435244021190797, 0.5139876943336318, 0.5928273311664812, 0.6798284501784103, 0.7745098157001024, 0.8761293205637914, 0.9836966013901643, 1.0959925101307157, 1.2115950067834096, 1.3289108706911419, 1.4462124748464649, 1.561678733054339, 1.6734392170872336, 1.7796203530023706, 1.8783925448655814, 1.9680170418560639, 2.046891362013843, 2.1135921129050272, 2.166914105645638, 2.2059047427415055, 2.2298927700721745, 2.2385106164251174, 2.2317096970444763, 2.2097682269634573, 2.1732912712971504, 2.1232029487291726, 2.060730896477448, 1.9873832953340413, 1.904918937235684, 1.8153109906800373, 1.7207052768644624, 1.623374007764826, 1.5256660530339012, 1.429954892677398, 1.3385854746810724, 1.2538212295166646, 1.177792495873298, 1.1124475839142351, 1.0595076444654514, 1.0204264261557607, 0.996355889703451, 0.9881185119884568, 0.9961869555540985, 1.020671605546134, 1.0613162900278759, 1.117502305626076, 1.1882606732775416, 1.2722923532574821], [1.3383923856729043, 1.4418837714515267, 1.5538425592219496, 1.672050477027044, 1.79413811295507, 1.9176366339548425, 2.0400316628844943, 2.1588180588991555, 2.271554326604475, 2.3759153904247907, 2.469742512063569, 2.5510891997311416, 2.6182620562243843, 2.669855636533449, 2.704780531376073, 2.7222840573352447, 2.7219631130653354, 2.703768949948803, 2.668003800001058, 2.6153094989778847, 2.546648433769686, 2.4632773256082388, 2.3667145299244607, 2.258701685770588, 2.1411606788793045, 2.016146989520097, 1.8858005767726647, 1.7522955027736207, 1.6177895227181898, 1.4843748584612995, 1.35403133575644, 1.2285829985274117, 1.1096592198302646, 0.9986612107391099, 0.8967346882958043, 0.8047493054442796, 0.72328527351318, 0.6526274256435893, 0.592766782144826, 0.543409490783093, 0.5039928311513886, 0.4737077971076592, 0.4515276091481235, 0.4362413635159624, 0.4264919004099712, 0.42081687290857034, 0.41769192361896446, 0.4155748293977798, 0.41294945686413104, 0.4083683832054762, 0.40049307759004094, 0.388130607248876, 0.37026592717820694, 0.34608893098774746, 0.3150155796402281, 0.27670258113384955, 0.2310552635892613, 0.1782284624071055, 0.11862042463470937, 0.05285991579089005, -0.01821310847215527, -0.09357273583155558, -0.17203755190401343, -0.25230549571144795, -0.33299218047687074, -0.4126716530013692, -0.4899184999805146, -0.5633501727165268, -0.6316683937255783, -0.6936985299532794, -0.7484258671863445, -0.7950277975531141, -0.8329010348165179, -0.8616830979126814, -0.8812674487290301, -0.8918118317981709, -0.8937395373477677, -0.8877334906230027, -0.8747232550167862, -0.855865219648475, -0.8325164189981951, -0.8062025985520506, -0.7785812919216977, -0.751400807712729, -0.7264561351336458, -0.7055428631102302, -0.6904102662671022, -0.6827147410013158, -0.6839747751593718, -0.6955286054323471, -0.7184956581379724, -0.7537427829229091, -0.8018561771455305, -0.8631197639844259, -0.9375006329328022, -1.0246419810521792, -1.123863811342596, -1.2341714553131962, -1.3542717949693885, -1.4825968697080179, -1.617334370724575, -1.7564643540224705, -1.8978013472371191, -2.039040889134149, -2.1778094272233655, -2.31171641130125, -2.4384073611172585, -2.5556166562897853, -2.6612187968871774, -2.7532769138038193, -2.830087368518331, -2.890219370605201, -2.9325486563706766, -2.956284410438261, -2.9609887706810616, -2.9465884317512345, -2.9133780493522057, -2.862015341799134, -2.793507982591674, -2.709192572883681, -2.6107061711268744, -2.499951034202963, -2.3790533857316154, -2.250317169021491, -2.116173860871129, -1.9791295152399058, -1.8417102704485775, -1.706407588473403, -1.575624499237283, -1.4516240964934808, -1.336481475609582, -1.232040218693852, -1.1398744211631051, -1.0612571187777609, -0.9971358186917451, -0.9481156660046394, -0.9144505928851295, -0.8960426050800548, -0.8924491652398423, -0.9028984387566548, -0.9263119804551926, -0.9613342640629611, -1.0063682952048707, -1.0596164066217097, -1.1191252148306938, -1.1828336233939372, -1.2486226915699488, -1.3143661499400399, -1.377980337448377, -1.4374723572500576, -1.4909853011610898, -1.5368394729561037, -1.5735686471816364, -1.5999505298241479, -1.6150307368019428, -1.618139772061045, -1.6089026648762201, -1.5872411113295577, -1.5533681532239956, -1.507775614188416, -1.4512146928004224, -1.3846702817190226, -1.3093297358898526, -1.2265469480537299, -1.1378027027283153, -1.0446623677776818, -0.9487320435012148, -0.8516143214100064, -0.7548648077818566, -0.6599505406976948, -0.5682113742993979, -0.4808253219239218, -0.39877874269277047, -0.322842126824132, -0.2535520866988233, -0.19119999733233806, -0.13582755554356246, -0.08722934619737911, -0.0449623210262474, -0.00836191534380026, 0.023435644979917285, 0.05146545522294059, 0.07690121672611507, 0.10101857572357169, 0.12515550035263218, 0.15067075841511846, 0.17890160952354522, 0.21112184776929557, 0.24850132440385372, 0.2920680443706961, 0.3426738667376317, 0.40096474873980287, 0.46735635850463764, 0.5420157454582952, 0.6248496033177646, 0.7154994923206158, 0.8133442091631049, 0.9175093094909827, 1.0268836033427065, 1.1401422633375, 1.2557760131973508, 1.3721257047569806, 1.4874214490012554, 1.5998253445133215, 1.7074767481530473, 1.8085389603628335, 1.9012461531174554, 1.9839493534008725, 2.0551603096815794, 2.1135921129050277, 2.1581955160272743, 2.18818999536689, 2.203088720671546, 2.202716745788436, 2.1872218946628657, 2.157077994084303, 2.1130802908182478, 2.056333081923725, 1.9882297784453675, 1.910425809555523, 1.8248049519757827, 1.7334398337155132, 1.6385475077394123, 1.5424411164559502, 1.4474787687613035, 1.3560108252333118, 1.2703268320619536, 1.1926033592485248, 1.1248539830657462, 1.0688826070544815, 1.026241240991412, 0.9981932550650645, 0.9856829993886063, 0.9893125300150659, 1.0093260154020112, 1.0456022158483456, 1.0976552371974813, 1.1646435637149977, 1.2453871782806387, 1.3383923856729032], [1.4100899178863928, 1.520487652318707, 1.6379340939165106, 1.7601077723347525, 1.8845676112430494, 2.0088061304046896, 2.130304058554247, 2.246585086381019, 2.355269487370938, 2.4541253633293882, 2.5411163303693862, 2.614444548539569, 2.6725881119254753, 2.7143319531849883, 2.738791573701677, 2.7454290839962465, 2.7340612244711253, 2.7048592294327745, 2.658340592920599, 2.5953529883907662, 2.5170507810361102, 2.4248647469222697, 2.3204657729242433, 2.2057234517866235, 2.0826606041209, 1.9534048509793858, 1.820138424630114, 1.6850474398139694, 1.550271852333921, 1.417857306290597, 1.2897100163660256, 1.1675557487200097, 1.0529038554407728, 0.9470171858555189, 0.8508885466943805, 0.7652242159285317, 0.6904348362719609, 0.6266338283269324, 0.5736432748148578, 0.5310070409684913, 0.4980107166048127, 0.473707797107659, 0.45695136769147393, 0.44643042166515756, 0.4407098322532312, 0.4382729115773497, 0.437565431736107, 0.4370399529400449, 0.4351993030363159, 0.43063808143157883, 0.4220811175963874, 0.40841789850023025, 0.38873208829907896, 0.3623253945730061, 0.3287351850372027, 0.2877454231082224, 0.2393906658124293, 0.18395304882585942, 0.12195236633239818, 0.05412953324219572, -0.018576110433992352, -0.09505503297103653, -0.17406051773241582, -0.25424555446988123, -0.33420262446764115, -0.41250531257522494, -0.48775063024172777, -0.5586009133592155, -0.6238241675781646, -0.6823317715718271, -0.7332125145685295, -0.7757620367036405, -0.8095068570627276, -0.8342223117820688, -0.849943879793845, -0.8569715428527087, -0.8558670051065658, -0.8474437811797828, -0.8327503458889349, -0.8130467186596338, -0.7897750269043404, -0.7645247507150373, -0.7389934922003518, -0.7149442330553925, -0.6941601404073833, -0.6783980511334824, -0.6693418068549007, -0.6685566245285219, -0.6774456705686043, -0.6972099600618744, -0.7288126279486281, -0.7729485177977348, -0.8300199084377106, -0.9001190522582215, -0.9830180350370002, -1.07816628968967, -1.1846959097429781, -1.3014347171899179, -1.426926848416443, -1.5594604358180153, -1.6971017861632696, -1.8377352940999745, -1.9791081844881762, -2.11887905410603, -2.254669084798159, -2.384114728815134, -2.5049206247516533, -2.6149114902457766, -2.712081755827098, -2.7946417526258127, -2.8610593439621326, -2.9100959952982883, -2.9408364061555314, -2.9527109782684797, -2.9455105628297473, -2.9193931120852668, -2.874882052348939, -2.8128563920529364, -2.7345327749565875, -2.6414398803189547, -2.5353857540304885, -2.418418822959947, -2.2927834950068298, -2.1608713758986227, -2.0251692375104766, -1.8882049488914354, -1.7524926284072533, -1.6204782923181058, -1.4944872613078874, -1.376674542329028, -1.2689793297239664, -1.1730846687494407, -1.090383198849819, -1.0219497463971627, -0.9685213707672061, -0.9304852876231707, -0.9078749035463909, -0.9003740013301684, -0.9073289201055792, -0.9277683837607678, -0.9604304494970143, -1.0037958802536409, -1.0561270942076388, -1.1155117152508265, -1.179909643376533, -1.2472024857730537, -1.3152441399600152, -1.3819113006429364, -1.4451526724903063, -1.5030357113991075, -1.5537897859157679, -1.5958447465187808, -1.6278640109829297, -1.6487714159690041, -1.65777124472935, -1.6543610143673395, -1.63833678908332, -1.6097909737010117, -1.5691027298074025, -1.5169213403719475, -1.4541430231762587, -1.3818818544585332, -1.3014356078756288, -1.2142474366701357, -1.1218644257895376, -1.0258941132328665, -0.9279601243536004, -0.8296580781882463, -0.7325129108005415, -0.6379387175624162, -0.5472021453909479, -0.4613902690781882, -0.3813837654903051, -0.3078360586615828, -0.24115895126448836, -0.18151508761295743, -0.1288174145842489, -0.08273562416468036, -0.04270937937078623, -0.007967948682825158, 0.02244429267224808, 0.04963718900994539, 0.07483978731743511, 0.09936192000551328, 0.12455341936838828, 0.15176205865472156, 0.18229134938392547, 0.21735933028756102, 0.2580594598501909, 0.305324672434852, 0.35989557869354, 0.42229368635954395, 0.4928003902120772, 0.5714423331846045, 0.6579835779415185, 0.7519248538610103, 0.8525099626230844, 0.9587392410905573, 1.069389797543025, 1.1830420611958858, 1.2981120197690361, 1.4128883698570254, 1.5255736738159251, 1.6343285081749988, 1.7373175050051934, 1.8327561314086973, 1.9189570248337995, 1.994374704050072, 2.0576475073852234, 2.1076356705329418, 2.1434545444731796, 2.1645020676956594, 2.170479743239822, 2.1614065267448566, 2.1376252029382248, 2.099801010581202, 2.048912465344927, 1.9862345217394375, 1.9133144043253, 1.8319406203196857, 1.744105835851016, 1.6519644522850536, 1.5577858533923206, 1.4639044052857813, 1.3726673762279828, 1.2863820004233468, 1.2072629372991701, 1.137381374789522, 1.078616991768913, 1.0326139317830294, 1.000741849067807, 0.9840629707055669, 0.9833059784491441, 0.9988473536356867, 1.0307006525842544, 1.0785139921938571, 1.1415758306886248, 1.2188289313300855, 1.3088922022294924, 1.410089917886392], [1.4867783563319192, 1.6031425776368975, 1.7250654860853252, 1.8501420657535466, 1.9758802486931182, 2.099755150146034, 2.219263955182014, 2.3319801810176077, 2.435606055859293, 2.5280218019845067, 2.6073306867709025, 2.6718988086273883, 2.7203887127273174, 2.751786080948392, 2.7654189078139346, 2.7609687554004214, 2.738473870687564, 2.6983241440176213, 2.641248082428963, 2.568292161873749, 2.4807931030855586, 2.3803437827354226, 2.268753640457915, 2.1480045697449395, 2.0202033835318916, 1.887532021088625, 1.7521967097963291, 1.6163773124756309, 1.4821780778043478, 1.351580968445396, 1.2264026699511454, 1.1082562851798947, 0.9985185963713074, 0.8983036332929669, 0.8084431246197481, 0.7294742349958697, 0.6616348064370569, 0.6048661344519005, 0.5588231211938267, 0.5228914647783901, 0.4962113701630362, 0.4777071069910913, 0.4661215974996772, 0.460055096483945, 0.4580069283625895, 0.45841917595763937, 0.45972117337329116, 0.46037364231359795, 0.4589113275645539, 0.45398303269236434, 0.44438803006191385, 0.42910791814987886, 0.4073331212627677, 0.3784833690384694, 0.34222165187593195, 0.29846131965674993, 0.2473661704413716, 0.18934355868876798, 0.12503073432385198, 0.055274800054938275, -0.01889315973628784, -0.09628907364964645, -0.17561116322214382, -0.25547855815698317, -0.3344722094279686, -0.41117700212352454, -0.48422393733817926, -0.5523312488833005, -0.6143433461810793, -0.6692665288002175, -0.7163004993439974, -0.754864807781855, -0.7846194891601292, -0.8054793047040595, -0.8176211599115369, -0.8214844482251976, -0.8177642508465262, -0.8073975076357921, -0.7915424561688704, -0.7715518112907964, -0.7489403214739547, -0.7253474867910078, -0.7024963525631822, -0.6821493994334816, -0.666062631990641, -0.6559390220096882, -0.6533824874380624, -0.65985358371975, -0.6766280499298611, -0.7047592892425268, -0.7450457729513814, -0.7980042417646251, -0.863849440198798, -0.9424809629538856, -1.0334776200058502, -1.1360995440258417, -1.249298074136242, -1.3717332586201556, -1.5017986307467495, -1.6376527310309554, -1.777256680505308, -1.9184169571476972, -2.058832395289816, -2.1961443189475838, -2.327988637314314, -2.452048676247186, -2.566107494871289, -2.6680984421080103, -2.756152743942019, -2.8286429777655835, -2.8842213836430495, -2.921852081595675, -2.940836406155531, -2.9408307310477486, -2.9218563340234107, -2.8843010402841394, -2.828912578037563, -2.7567837767556935, -2.6693299328801894, -2.568258854300683, -2.4555342693789974, -2.333333444352705, -2.2039999907756784, -2.0699929588839328, -1.9338334006344853, -1.7980496455181088, -1.665122561659802, -1.5374320734898794, -1.4172061754426084, -1.3064736195152906, -1.2070213646239982, -1.1203577597408305, -1.0476822936449055, -0.9898625851846614, -0.9474191131332244, -0.9205179983071664, -0.9089719571766877, -0.9122493504531667, -0.9294910568792133, -0.959534716379885, -1.0009457123902146, -1.0520541047871768, -1.1109965862573181, -1.1757624194644338, -1.2442422228094694, -1.3142784110187677, -1.3837160646837483, -1.4504530009029806, -1.5124878452997519, -1.5679649631143227, -1.6152151922880553, -1.6527914322706219, -1.6794982758672976, -1.6944150244191651, -1.696911595120465, -1.686657009093602, -1.6636203354619523, -1.6280641554227913, -1.5805307965249837, -1.5218217663695526, -1.4529709823365018, -1.37521254555849, -1.2899439394731425, -1.198685642647681, -1.103038229513669, -1.0046380891476456, -0.9051129199473904, -0.8060381563684249, -0.7088954529225073, -0.6150342912549766, -0.525637689876684, -0.44169288526627015, -0.36396772043188097, -0.2929933260221121, -0.22905351355639886, -0.17218112451682305, -0.12216139737391701, -0.07854223171787594, -0.04065104917059059, -0.007617779210971279, 0.021596661198972425, 0.048167168213854056, 0.07336742891958499, 0.09853007324648591, 0.12500507115516207, 0.1541174930665281, 0.1871257696131446, 0.22518157572847813, 0.26929242412377113, 0.32028798531714864, 0.3787910572686425, 0.4451939896922819, 0.5196412292195977, 0.6020184952647122, 0.6919489266191314, 0.7887963597582975, 0.8916757160830642, 0.9994702914844261, 1.1108555623539136, 1.2243289520036114, 1.3382448447256072, 1.450853995399214, 1.5603463642044637, 1.6648963116619337, 1.7627090213376067, 1.85206697791452, 1.931375318025633, 1.999204890619645, 2.0543319123067323, 2.0957731799865584, 2.1228159062730665, 2.1350413703148217, 2.1323417244818055, 2.114929462440575, 2.083339232325303, 2.03842186565272, 1.981330683716964, 1.9135003337154282, 1.8366185920818956, 1.7525917478424173, 1.6635043399005658, 1.5715741649835906, 1.4791035939640287, 1.3884283303690859, 1.301864813667312, 1.221657509612798, 1.1499273394791523, 1.0886224791164125, 1.0394727078516468, 1.0039484075044378, 0.9832252050889179, 0.9781551216769758, 0.9892449375578268, 1.0166423139279313, 1.0601300279981325, 1.1191284860620365, 1.192706482406076, 1.2795999757421574, 1.3782384638851446, 1.4867783563319181], [1.56780888211832, 1.6891492493361266, 1.8144995647232407, 1.9413916264201205, 2.0673034790730083, 2.1897142233169635, 2.306158711787513, 2.4142808616665743, 2.511884348347417, 2.596979509080604, 2.6678253778506233, 2.7229658909559062, 2.7612594439171088, 2.781901140954595, 2.7844372544172495, 2.768771598895908, 2.7351637187309166, 2.6842189834831154, 2.6168708788993578, 2.534355966264329, 2.4381821562802792, 2.330091100550684, 2.212015640566148, 2.0860333675057006, 1.9543174334606768, 1.8190858137964871, 1.6825502499227811, 1.5468661011094744, 1.4140843032747745, 1.2861065727342522, 1.1646449053093706, 1.05118630820193, 0.9469635665232059, 0.8529326917492668, 0.769757529549431, 0.6978018236620348, 0.6371288452930333, 0.5875085085586703, 0.5484317064875623, 0.5191314236596979, 0.4986100151111697, 0.48567189078663386, 0.4789607142789794, 0.477000117058122, 0.4782368474779356, 0.4810852195364935, 0.48397170093067876, 0.4853784839477238, 0.4838849159915228, 0.47820572813645545, 0.467225088413169, 0.45002561926924506, 0.4259116529133371, 0.3944261506085927, 0.3553608785442642, 0.30875960944563313, 0.2549143010979704, 0.19435438584315742, 0.1278294842228856, 0.05628602675364279, -0.01916157399847785, -0.09726441732483458, -0.17667636921067928, -0.2559940750036203, -0.3337986545471004, -0.4086979597537566, -0.4793682586876798, -0.5445942234873035, -0.6033061415734622, -0.6546133395043879, -0.6978329048143216, -0.7325129108005399, -0.7584494895028415, -0.7756972555248925, -0.7845727539185079, -0.7856507847942801, -0.7797536411103817, -0.7679334795863582, -0.751448223250407, -0.7317315632349628, -0.7103577827928942, -0.6890022641606732, -0.6693986553266631, -0.6532937659792696, -0.6424013275188922, -0.6383557892880616, -0.6426673310805281, -0.6566792502384129, -0.6815288306837234, -0.7181127222333256, -0.7670577533939268, -0.8286979720609763, -0.903058559282056, -0.9898470951379492, -1.088452476917293, -1.1979516025139136, -1.317123740978808, -1.4444723221329567, -1.5782536928019255, -1.7165122131469188, -1.857120907074053, -1.9978267397873861, -2.1362994767430403, -2.270182984555319, -2.3971477681800684, -2.514943501661672, -2.62145030286758, -2.7147275261963633, -2.7930589007301374, -2.854992923472719, -2.899377526224438, -2.9253881676875957, -2.9325486563706766, -2.9207441810434283, -2.890226209741415, -2.841609111154633, -2.775858548972179, -2.6942718956059672, -2.5984511019110674, -2.4902686394237734, -2.371827296865762, -2.2454147591858273, -2.113454021658951, -1.978450790508317, -1.842939092753064, -1.7094263597822037, -1.5803392605063136, -1.457971540578854, -1.3444350745979556, -1.2416152596255523, -1.1511317727307218, -1.0743055851774337, -1.012132974528779, -0.9652671070437208, -0.9340075804382629, -0.9182981258344896, -0.9177324722058849, -0.9315681816218125, -0.9587480738551587, -0.9979286790656189, -1.0475149916773514, -1.1057006512469194, -1.170512550622441, -1.2398587710411302, -1.3115786703966763, -1.383493906451298, -1.4534591622740856, -1.5194113569204994, -1.579416169845233, -1.631710781545371, -1.6747418335447284, -1.707197735481497, -1.7280345925890463, -1.7364951895931746, -1.7321206428997684, -1.7147545175103442, -1.6845393937688182, -1.6419060571088218, -1.587555666761049, -1.5224354323598235, -1.4477084862770102, -1.3647187803900842, -1.2749519553971183, -1.179993225805588, -1.081483392040154, -0.9810741311042402, -0.8803837279703389, -0.7809543911772743, -0.684212248528424, -0.5914310435863084, -0.5037004528082841, -0.4218998192683841, -0.3466779551395427, -0.278439505140263, -0.2173381910553383, -0.16327707759539467, -0.11591581683004837, -0.07468464685459755, -0.03880474483055917, -0.007314369520424, 0.02089992190591183, 0.04706782987579352, 0.07249659835086032, 0.09853007324648587, 0.12650663453446265, 0.157717133609568, 0.1933639688284632, 0.23452240435601035, 0.2821051812638658, 0.33683138661962536, 0.3992004381638922, 0.4694719118093162, 0.5476517898835772, 0.6334855435315495, 0.7264582871312952, 0.82580206038804, 0.9305101095460668, 1.0393578575552462, 1.150930078641599, 1.263653629981912, 1.3758349462076214, 1.485701375011817, 1.591445327471362, 1.6912701375245371, 1.7834364734323227, 1.866308121380604, 1.9383959683132108, 1.9983990475455287, 2.0452415758807945, 2.078105003303738, 2.096454213645199, 2.1000571540553357, 2.0889973292938393, 2.063678769870717, 2.024823266700167, 1.973459854639333, 1.9109067183880366, 1.8387458819949765, 1.7587912229919833, 1.6730505194906498, 1.583682389252766, 1.4929491100187149, 1.4031664169734288, 1.3166514534529727, 1.2356701027970798, 1.1623849512820883, 1.0988051237041123, 1.046739194550243, 1.0077523096688783, 0.983128557525402, 0.9738395077891766, 0.9805196910554055, 1.0034496304331848, 1.0425468574754169, 1.0973651558107003, 1.1671020804564909, 1.2506146038994213, 1.3464425464162761, 1.4528392624944473, 1.567808882118319], [1.6524959403307111, 1.7777800120553555, 1.9054796770555986, 2.0330844417603386, 2.158063820484223, 2.277922255451507, 2.390253159409535, 2.492790827328146, 2.5834590159645385, 2.6604150712119288, 2.7220885911478545, 2.767213744900506, 2.7948545206147672, 2.804422346168726, 2.7956857096934593, 2.7687715988959085, 2.7241587739845965, 2.6626630838700365, 2.5854152245044544, 2.493831517133667, 2.3895784485119185, 2.274531860798935, 2.1507318024022646, 2.0203341494821396, 1.8855601788585903, 1.7486453149889245, 1.6117882855753822, 1.4771019020178393, 1.346566632890506, 1.2219880621723835, 1.1049592210752774, 0.996828655615808, 0.8986749447779012, 0.8112882199204636, 0.7351590591231549, 0.6704749448588408, 0.6171242843602421, 0.5747078040167137, 0.5425569467666489, 0.5197587292617167, 0.505186357827553, 0.49753476281927056, 0.49536009329166136, 0.4971221208459217, 0.5012284353294109, 0.5060792773287331, 0.5101118439716456, 0.511842925567378, 0.5099087804584526, 0.5031012327995005, 0.4903990808026144, 0.47099402864149126, 0.44431050046614173, 0.4100188561371017, 0.3680417012390176, 0.3185531642832289, 0.2619711971813028, 0.19894313642387648, 0.13032493733890452, 0.0571546579028529, -0.019379082314445423, -0.09797281214776073, -0.177247123573348, -0.255787743503996, -0.33218765840411557, -0.40508915928614897, -0.4732246755288323, -0.5354552959071186, -0.5908059335006857, -0.6384961762964252, -0.6779659751859051, -0.7088954529225058, -0.7312182681300249, -0.7451281338571544, -0.751078266284033, -0.7497737215674993, -0.7421567628564972, -0.7293855805664557, -0.7128068624868826, -0.6939228718095528, -0.6743538365971983, -0.6557965798538872, -0.6399804219862945, -0.6286214644091016, -0.6233764123348305, -0.6257971150739309, -0.6372869928537461, -0.6590604803821652, -0.6921065500073852, -0.737157282948671, -0.794662337961186, -0.8647700258394088, -0.9473155387977116, -1.0418167098987159, -1.147477493605451, -1.2631991687507007, -1.3875990744377238, -1.5190365023362014, -1.655645190160674, -1.7953716952628826, -1.9360187783737588, -2.0752927993245724, -2.2108540222845, -2.340368650315317, -2.4615613598534334, -2.572267086375352, -2.6704808235419715, -2.7544042393595456, -2.8224879834048, -2.87346865728305, -2.906399543881828, -2.920674336685615, -2.9160432749143967, -2.8926212695578215, -2.8508877951479805, -2.7916785177355026, -2.7161688262459003, -2.6258496274052336, -2.5224959490322587, -2.4081290681970593, -2.284973035356082, -2.1554065993194853, -2.0219116475278938, -1.8870193589395376, -1.7532553208410326, -1.6230848847835408, -1.498860030039428, -1.3827689656497568, -1.2767896352163743, -1.182648193733223, -1.101783405281883, -1.0353177672949023, -0.9840360048274116, -0.948371400848994, -0.9284002403177095, -0.9238444513307625, -0.9340823307126572, -0.9581670487825484, -0.9948524434308477, -1.042625441520182, -1.0997442901828158, -1.16428164557448, -1.2341714553131962, -1.3072584858426468, -1.3813492893214756, -1.4542633776589167, -1.5238833745663012, -1.588202949799572, -1.6453714022156816, -1.6937338482230142, -1.7318660873646443, -1.7586033542071096, -1.7730623219457762, -1.774655894252168, -1.7631005035907719, -1.7384158219820927, -1.7009169793046603, -1.6511995700073072, -1.5901179069346119, -1.5187571464507952, -1.4384000580957539, -1.350489340955123, -1.2565864946167893, -1.158328332448756, -1.0573822770476942, -0.9554016008505104, -0.8539817685766589, -0.7546190026188448, -0.6586721286967427, -0.5673286687122798, -0.4815760331380602, -0.40217852937933674, -0.32966074885137153, -0.26429772792637496, -0.20611210069090952, -0.15487827911475485, -0.11013351339020157, -0.07119550648836559, -0.037186086920870894, -0.0070602865944598015, 0.020359969522763716, 0.04634847489556004, 0.07223466323192781, 0.0993619200055132, 0.1290454056006359, 0.16253052569599108, 0.2009531690417025, 0.24530278853319565, 0.29638932954723085, 0.35481491168128876, 0.42095104878156525, 0.4949220505036518, 0.5765950901858753, 0.6655772525177771, 0.761219694672413, 0.8626288707776396, 0.9686845864706319, 1.078064472444729, 1.1892742978643622, 1.300683390560472, 1.4105642949468258, 1.5171356840946935, 1.6186074523149405, 1.7132268512617197, 1.7993244976653409, 1.8753590752890363, 1.9399595778182201, 1.9919639926247783, 2.030453406466997, 2.054780621254158, 2.06459249843801, 2.059845401217295, 2.040813270872776, 2.0080880530856264, 1.9625723776107828, 1.905464585549858, 1.8382363879720351, 1.7626036230664126, 1.6804907518153502, 1.5939898900490554, 1.5053153137299415, 1.4167544909336718, 1.330616785299826, 1.2491810393955594, 1.174643280824696, 1.1090657980958347, 1.0543288070525727, 1.012085872630845, 0.9837241661428774, 0.9703305271978333, 0.9726641644148164, 0.9911366735139344, 1.0257998789457956, 1.0763418201177914, 1.1420910099915755, 1.2220288970603443, 1.3148102662571035, 1.41879112495793, 1.532063441543919, 1.65249594033071], [1.740123040135285, 1.868285009436102, 1.9972360901630963, 2.1244447490649496, 2.247393399368901, 2.363632966683216, 2.4708358209680257, 2.5668458481666607, 2.6497245046347113, 2.7177917948179315, 2.769661235323717, 2.804268013594434, 2.8208897132694846, 2.819159157003711, 2.799069106620941, 2.7609687554004223, 2.705552143260952, 2.6338388178432672, 2.5471472483142796, 2.4470616696589307, 2.335393189141625, 2.214136119789318, 2.085420614968384, 1.951462760787971, 1.8145133372125788, 1.6768064831605392, 1.5405094949926652, 1.4076749518937015, 1.2801962966950868, 1.1597679083731007, 1.047850585145567, 0.9456432177595255, 0.8540612747262084, 0.7737225488825675, 0.7049404320567133, 0.6477247963465166, 0.6017903712763425, 0.5665723205788407, 0.5412485451566842, 0.5247680742951947, 0.5158847594769763, 0.5131953578235945, 0.5151809883704718, 0.5202508665899888, 0.5267871726799797, 0.5331898882954961, 0.5379204450575154, 0.5395430660211618, 0.5367627472960202, 0.5284589194467059, 0.5137139447682844, 0.49183574403501495, 0.46237400134531154, 0.42512956427944565, 0.38015683446205684, 0.3277591262639768, 0.26847715415722195, 0.20307098752457894, 0.13249598100934173, 0.05787334448998623, -0.019543844465413844, -0.09840826477767065, -0.17731859746997242, -0.25486130931596324, -0.32965285075536793, -0.4003811328056583, -0.4658451653551636, -0.5249917856054861, -0.5769484793794543, -0.6210513976701678, -0.6568677936732923, -0.6842122485284224, -0.7031562134967615, -0.7140305683028397, -0.7174210755299283, -0.7141567947343098, -0.7052917026876822, -0.6920799432449163, -0.6759452972757715, -0.6584456156526538, -0.6412330925636542, -0.6260113689856286, -0.6144905441080382, -0.6083412335586056, -0.6091488458297853, -0.6183692514340126, -0.6372869928537459, -0.6669771278664717, -0.7082717156088952, -0.7617318457871496, -0.8276259793765026, -0.9059152172021676, -0.9962459446725503, -1.0979501207787912, -1.2100532917200182, -1.3312902188009796, -1.4601278213014748, -1.5947949525246936, -1.7333183557352878, -1.8735639904758223, -2.0132827827115354, -2.150159737841781, -2.281865266722598, -2.406107513735871, -2.52068444420137, -2.62353444692233, -2.7127842365029937, -2.7867928986502797, -2.844191008609767, -2.883913866128178, -2.905228027168338, -2.9077504697330423, -2.8914599047825824, -2.85669992914786, -2.8041739110314023, -2.7349316954409244, -2.6503484119228986, -2.5520958555039, -2.4421070892072154, -2.3225350785616987, -2.1957063112043302, -2.0640704745153045, -1.930147358291051, -1.7964722154618609, -1.665540850191137, -1.5397557084705715, -1.421374221418667, -1.3124605965160423, -1.2148421683249424, -1.130071309898653, -1.0593937717964899, -1.0037241606747118, -0.9636290976185008, -0.9393184119202824, -0.9306445334063344, -0.9371100503725464, -0.9578832054956422, -0.9918209134830697, -1.037498706302256, -1.0932468489076936, -1.1571917244072254, -1.227301466049645, -1.301434717189918, -1.377391331783044, -1.4529637885761986, -1.525988082891656, -1.5943928808570835, -1.6562457715358918, -1.7097955313001614, -1.7535094199374013, -1.7861046567114658, -1.8065733736517327, -1.8142005089718498, -1.8085742815668144, -1.789589073553482, -1.7574407371661542, -1.7126145302849027, -1.6558660667937637, -1.5881958393343762, -1.5108180286057018, -1.425124451307258, -1.3326446147501216, -1.235002937240823, -1.1338742573784597, -1.0309387908750045, -0.9278376996093552, -0.8261304142898436, -0.7272547999972402, -0.6324911743982755, -0.5429310836307742, -0.45945161346783614, -0.382695866635575, -0.313060074832939, -0.2506876402149047, -0.19547022026745942, -0.14705578671054936, -0.1048634079579998, -0.06810433032553237, -0.03580877001989276, -0.006857680089606175, 0.019981372291020764, 0.04601518934179825, 0.07258383965242066, 0.10101857572357155, 0.13259990520165502, 0.1685169458506616, 0.2098291621849061, 0.25743152133171543, 0.31202401861573814, 0.3740864117424792, 0.4438588691135724, 0.5213290860856155, 0.6062262567089418, 0.6980221118437078, 0.795939052004971, 0.8989652194468785, 1.00587617350783, 1.1152626606759668, 1.2255638105766216, 1.3351049452086385, 1.4421390649376773, 1.544890974168815, 1.6416029348680214, 1.7305806891397384, 1.8102386741622372, 1.8791432644741468, 1.936052917696707, 1.979954169333919, 2.0100925186703034, 2.025997368664362, 2.0275003251797434, 2.014746321425736, 1.9881972081563937, 1.9486276347043907, 1.8971132357476947, 1.8350113291290033, 1.7639345163479785, 1.6857177548950373, 1.602379635969518, 1.516078748218053, 1.4290661342525217, 1.3436349486843797, 1.2620685016562614, 1.1865879184304822, 1.1193006622789998, 1.0621511542171844, 1.016874679289169, 0.9849556961424646, 0.9675915662407333, 0.9656625936494779, 0.9797091189026325, 1.009916244576724, 1.0561065898796405, 1.1177412811787053, 1.193929189575709, 1.28344423015046, 1.3847503451267076, 1.4960336096545517, 1.6152407286294514, 1.7401230401352838], [1.8299488166159799, 1.9598985282465469, 2.088992503270594, 2.214699598793147, 2.334536447067581, 2.446121205610532, 2.5472249306821313, 2.635819385195547, 2.7101201783383098, 2.76862424685364, 2.8101408242816164, 2.8338152011572917, 2.839144752370343, 2.8259868933714034, 2.794558820130685, 2.745429083996248, 2.6795012470755015, 2.597990051736523, 2.5023907147238584, 2.394442117913353, 2.2760848099827817, 2.1494148528201595, 2.016634640463846, 1.8800018845362068, 1.7417779969520302, 1.604177107336041, 1.4693169289969812, 1.3391726341511638, 1.2155348177656506, 1.099972521992486, 0.9938021624221568, 0.8980630465990217, 0.8135000082046814, 0.7405535012112191, 0.6793573116091726, 0.6297438546760356, 0.5912568378846983, 0.5631708881162839, 0.544517571327347, 0.5341170774343938, 0.5306147067404036, 0.532521180079369, 0.5382557057739868, 0.5461906746354518, 0.5546968210461956, 0.562187684400312, 0.5671622308395661, 0.5682445495863794, 0.5642196197932214, 0.5540642505745519, 0.5369724260109328, 0.512374435106603, 0.4799493301595812, 0.4396304316070668, 0.3916037787041546, 0.33629960878377463, 0.2743771286857325, 0.20670301565707894, 0.13432424722233693, 0.05843600610130625, -0.019654466489030187, -0.09856709108827076, -0.17689018619904484, -0.2532226104919689, -0.32621567722057926, -0.39461371234671594, -0.45729216216200946, -0.5132922186143503, -0.561851019542203, -0.6024265943466466, -0.6347168604391163, -0.6586721286967411, -0.6745007432834733, -0.6826676583383466, -0.6838859367200263, -0.679101339612564, -0.6694703556945946, -0.6563321901944736, -0.6411753931388081, -0.6255999484049944, -0.6112757671740934, -0.5998986279178045, -0.5931446775930453, -0.5926246533576855, -0.5998389996544364, -0.6161350414558469, -0.6426673310805275, -0.6803622142712914, -0.7298875628724445, -0.7916284988270309, -0.8656697903172856, -0.9517854392119114, -1.0494358035316103, -1.157772413721471, -1.2756504516930736, -1.4016486715697734, -1.5340963555519616, -1.6711067219287492, -1.8106160393974977, -1.95042755658582, -2.088259231648325, -2.2217941471614786, -2.3487324227964335, -2.466843394285269, -2.574016813176794, -2.6683118382336346, -2.7480026357344842, -2.8116194813549304, -2.8579843589310743, -2.88624017881476, -2.895872887645482, -2.8867259085924135, -2.8590065324106506, -2.813284070608004, -2.750479777989581, -2.6718487480657407, -2.5789541764924246, -2.4736345701862144, -2.3579646485664325, -2.234210834401728, -2.1047823612904843, -1.9721791297191957, -1.838937521359182, -1.7075754298821575, -1.5805377849163258, -1.4601438333817862, -1.3485373996476908, -1.2476412737954814, -1.1591167775251103, -1.0843294323503947, -1.024321507755357, -0.979792061525139, -0.9510849045712649, -0.9381847326404475, -0.9407214719690534, -0.9579826899891951, -0.9889337303841567, -1.0322450487994628, -1.086326055787838, -1.1493646212152067, -1.2193712630617801, -1.294226936474401, -1.3717332586201556, -1.4496639532501912, -1.5258162770912198, -1.5980611986874478, -1.6643911388172976, -1.7229641490678407, -1.772143499814367, -1.8105317683030744, -1.8369986587452873, -1.8507019457441838, -1.851101105989784, -1.8379633866321872, -1.8113622474998006, -1.7716683036711993, -1.719533080135051, -1.655866066793764, -1.5818057255219866, -1.4986852473540042, -1.4079939835522342, -1.3113355762336047, -1.2103838899312915, -1.1068378931353888, -1.00237665738092, -0.8986156304580825, -0.7970653001700412, -0.6990932968490821, -0.6058908883534045, -0.5184447029516144, -0.4375143763994363, -0.3636166631799164, -0.29701638229833177, -0.23772438950652608, -0.18550258490887622, -0.13987578220823604, -0.10015008801014941, -0.06543727111520867, -0.03468444685185008, -0.006708264148574673, 0.019767333314580717, 0.04607079296110639, 0.07354117342181735, 0.10348602434364088, 0.13714006066246603, 0.17562574625018493, 0.21991685333964983, 0.27080598818378016, 0.32887697192509074, 0.3944828411922259, 0.46773008863399806, 0.5484696030848639, 0.6362945963757358, 0.7305456233179777, 0.830322617655247, 0.9345036844436296, 1.0417702130019413, 1.1506377087441508, 1.2594915910796394, 1.3666270719981573, 1.470292119338307, 1.5687324229207427, 1.6602372229426305, 1.743184829837444, 1.8160866640511262, 1.877628672983065, 1.9267090400610827, 1.9624711862124984, 1.9843311748148813, 1.9919987648758295, 1.9854915104405644, 1.965141473303261, 1.9315942968443118, 1.8858005767726627, 1.8289996550716643, 1.7626961518065507, 1.6886297309717866, 1.6087387667168322, 1.5251187308402256, 1.439976257512727, 1.3555799533820325, 1.2742091076852378, 1.1981015155408121, 1.1294016566848157, 1.0701104707557072, 1.0220379387624696, 0.9867596192829652, 0.9655781986547376, 0.9594909990577026, 0.9691642497104197, 0.9949147677497803, 1.0366995205747305, 1.0941133547462751, 1.1663949824841136, 1.2524411201067736, 1.3508284782181406, 1.4598431157927503, 1.577516494132985, 1.7016674062641493, 1.8299488166159787], [1.9212133030571417, 2.0518454766619634, 2.1799726156029515, 2.303085394075444, 2.418755693964054, 2.524689084405775, 2.6187742021172036, 2.699127891080658, 2.7641350623464462, 2.812482361772888, 2.8431848823817454, 2.8556053250120423, 2.8494651920260496, 2.824847789532546, 2.782193009287326, 2.7222840573352465, 2.6462264877981387, 2.5554200823328186, 2.4515242842599294, 2.3364180471153206, 2.212155086760419, 2.0809156310967247, 1.944955839358968, 1.8065561120763518, 1.667969531968665, 1.5313716649000728, 1.398812908911657, 1.2721745093959809, 1.1531292614735933, 1.0431077990570405, 0.9432712270184771, 0.8544906919125872, 0.7773343118822742, 0.712061702058883, 0.658626142556013, 0.6166842467503996, 0.5856128026442816, 0.5645322842868423, 0.5523363678379823, 0.5477266418822845, 0.5492515775986091, 0.5553487243852759, 0.564389022951544, 0.5747220824683488, 0.5847212521736206, 0.5928273311664817, 0.5975898025780225, 0.5977045487245001, 0.592047100384353, 0.5797005934951526, 0.5599777472546641, 0.5324363352359262, 0.4968877916742551, 0.4533987742206562, 0.40228568763722145, 0.3441023554958924, 0.2796212043125541, 0.209808492219864, 0.13579426801842825, 0.05883788236497387, -0.019710012472917628, -0.09844794733710362, -0.17596551431377563, -0.25088551116558383, -0.32190521784319287, -0.3878356928961919, -0.447638028226662, -0.5004555785645705, -0.5456412853308336, -0.582779340589798, -0.6117005824019497, -0.632491174398274, -0.645494295734913, -0.6513047483738537, -0.650756572303482, -0.6449039412153659, -0.6349957866821403, -0.6224447635819771, -0.6087913191985524, -0.5956637592743239, -0.5847353129571559, -0.5776792822559988, -0.5761234181311479, -0.581604693186675, -0.5955256393201809, -0.619113387566841, -0.6533824874380615, -0.6991024957088185, -0.7567712119489004, -0.8265943028552082, -0.908471902927955, -1.0019926090339262, -1.1064351051002583, -1.2207774650585643, -1.3437139918681913, -1.4736792627090944, -1.6088788699182812, -1.7473261784477403, -1.8868842677659206, -2.0253120930424244, -2.1603137904988916, -2.2895899677658846, -2.410889764107889, -2.5220624389307633, -2.6211072508050006, -2.706220423316771, -2.7758380576424377, -2.8286739433496604, -2.8637513363834404, -2.8804279136848003, -2.8784132740268715, -2.857778530564701, -2.8189577280141855, -2.7627410117474, -2.6902596726849226, -2.6029633858901047, -2.50259014749248, -2.3911295894301, -2.2707805102326186, -2.143903598789918, -2.012970443374371, -1.880510007289443, -1.749053813225652, -1.6210811092326862, -1.4989652894131493, -1.3849228120052197, -1.2809657971977193, -1.1888593982893676, -1.1100849248390714, -1.0458095580709417, -0.9968633403826531, -0.9637239462343875, -0.9465095552351956, -0.9449799544491921, -0.9585458005457592, -0.9862857782045751, -1.0269712038871215, -1.0790974482548206, -1.1409213904163176, -1.210503976695418, -1.2857568391129008, -1.3644918370848333, -1.444472322132957, -1.5234648911627422, -1.5992903898475745, -1.6698729538732031, -1.7332859315100264, -1.7877936147310884, -1.83188781573189, -1.8643184584499524, -1.8841175071791032, -1.890615722796154, -1.8834519172510966, -1.862574564320711, -1.828235814525667, -1.780978149846548, -1.7216140947926932, -1.651199570007308, -1.5710016287518545, -1.482461451515238, -1.3871535863395144, -1.2867425095138716, -1.1829376409686791, -1.0774479795951346, -0.9719375251393132, -0.8679826253248486, -0.7670323302348192, -0.6703727522342292, -0.5790963210188359, -0.49407669253555947, -0.41594992088517224, -0.3451023377070339, -0.2816654081462462, -0.2255176507681699, -0.17629352532069995, -0.13339901169489352, -0.09603343036621084, -0.06321689338517188, -0.033822629699506494, -0.006613302897837906, 0.019719663460038, 0.046514815321704206, 0.07509856506323027, 0.10674339013386219, 0.1426274602134266, 0.18379678322641224, 0.23113089607403234, 0.2853130350478059, 0.346805605864243, 0.41583163700789433, 0.4923627460238494, 0.5761139804463594, 0.6665457174265973, 0.7628726233164577, 0.8640794910990991, 0.9689435942726815, 1.0760630251366075, 1.1838903277352326, 1.2907705949978643, 1.3949830794724636, 1.4947852705690827, 1.5884583209056564, 1.6743526620295455, 1.750932636621095, 1.8168189906913028, 1.8708281149451662, 1.9120069983442982, 1.9396629572088637, 1.9533873275268883, 1.9530724534611548, 1.938921467802371, 1.9114505363114365, 1.8714834231793414, 1.820138424630112, 1.758807907296957, 1.6891308727056396, 1.6129591444035465, 1.5323179356051748, 1.449361698645825, 1.3663262794412139, 1.2854784974615148, 1.20906434196665, 1.1392570166014058, 1.0781060758100074, 1.0274888775339217, 0.989065527685874, 0.964238414068834, 0.9541173225648278, 0.9594909990577022, 0.9808058697858648, 1.018152464286378, 1.07125990287344, 1.1394986191166712, 1.221891291704922, 1.3171317641755271, 1.4236115400330134, 1.539453259435531, 1.6625503963191164, 1.7906122656467056, 1.9212133030571406], [2.013144360605827, 2.1433479418922885, 2.269406694240867, 2.388854351088724, 2.499338607119933, 2.5986718832619675, 2.6848782960604867, 2.75623574721478, 2.8113121662983995, 2.8489950800774326, 2.8685138419399707, 2.8694540308507315, 2.8517637166470653, 2.815751482821067, 2.7620762944461927, 2.691729492816214, 2.6060093849493513, 2.5064890708364405, 2.394978309941539, 2.273480367159976, 2.144144893861528, 2.0092179890310464, 1.8709906467461248, 1.7317468278780077, 1.5937123952749537, 1.4590061228404814, 1.329593930650047, 1.2072474120805787, 1.0935076070639818, 0.9896548408543787, 0.8966852935135523, 0.8152947955375849, 0.7458701639150389, 0.6884882049390746, 0.6429223199683853, 0.6086564627621988, 0.5849060166471812, 0.570644991062874, 0.5646387841320645, 0.5654816245652394, 0.5716376956908521, 0.5814848593869058, 0.5933598402143602, 0.6056037014678045, 0.6166064457887067, 0.6248496033177653, 0.6289457292473444, 0.6276738185120132, 0.6200097559915356, 0.6051510531468224, 0.5825352730717299, 0.5518517116697769, 0.5130460788401779, 0.4663181057114568, 0.41211218747806466, 0.3511013516323625, 0.28416501378491277, 0.2123611434759689, 0.13689360635648878, 0.05907557322594742, -0.019710012472917628, -0.09805184153421728, -0.174552404956733, -0.24786978425465864, -0.31675794106004646, -0.38010441956572655, -0.4369644418907598, -0.48659046923961374, -0.5284564184317626, -0.5622758610568888, -0.5880136876889714, -0.6058908883534029, -0.6163822785229086, -0.6202071828195388, -0.618313271694468, -0.6118539250076552, -0.6021596661040853, -0.5907043663708038, -0.5790670593744995, -0.5688903219669679, -0.5618362741652092, -0.559541317718879, -0.5635707732796011, -0.5753745868952094, -0.5962452578072642, -0.6272790916111787, -0.6693418068548996, -0.7230394209180182, -0.7886952150020864, -0.8663334313473958, -0.9556701919676475, -1.0561119512925141, -1.1667616094947448, -1.2864322235456482, -1.4136680638963872, -1.5467725808236907, -1.6838426704894212, -1.8228084709898191, -1.9614777771167928, -2.0975840427815733, -2.228836845090297, -2.352973616334721, -2.467811411422951, -2.5712974695677495, -2.661557350674989, -2.7369394783881056, -2.79605500196184, -2.8378119961687607, -2.8614431497280317, -2.866526245131378, -2.852996902544286, -2.821153243566856, -2.7716523226006724, -2.705498369715005, -2.624023084458213, -2.5288584102490046, -2.421902399163521, -2.305278942706685, -2.181292291467351, -2.052377411804034, -1.9210473278269289, -1.7898386694825519, -1.6612566907341124, -1.5377210346052679, -1.4215135039055402, -1.3147290482196188, -1.219231100401979, -1.1366122912635852, -1.068161441927716, -1.01483758262714, -0.9772515781993132, -0.9556557583287224, -0.9499417591360456, -0.9596465866951418, -0.9839667172510922, -1.0217798580850908, -1.0716738117665483, -1.1319817193487989, -1.2008228089520678, -1.2761476487350911, -1.3557868005473794, -1.4375016950265478, -1.5190365023362016, -1.5981697561906516, -1.6727645026039297, -1.74081578850486, -1.8004943778138403, -1.8501856819104565, -1.8885230151054573, -1.9144144306406377, -1.9270625552336418, -1.925977016192594, -1.9109792402536085, -1.8821995929324566, -1.840067016618667, -1.7852915101808033, -1.7188399679321558, -1.6419060571088235, -1.5558749565715648, -1.4622839017435507, -1.362779578859906, -1.2590734830638612, -1.1528963980387785, -1.0459531687253347, -0.9398789229828126, -0.8361978532946742, -0.7362855969999037, -0.6413361549563181, -0.5523341665589002, -0.47003321677737986, -0.39494069197672216, -0.327309529788256, -0.26713702856440413, -0.214170698533175, -0.1679209543141936, -0.12768027157983672, -0.09254826381266062, -0.06146198253575046, -0.03323060992594756, -0.006573599752547563, 0.0198387660359329, 0.04734349979349861, 0.0772428383386454, 0.11076311430567536, 0.14901567797125903, 0.1929609261090883, 0.24337641451210834, 0.3008299257428097, 0.36565823607727055, 0.4379521787164436, 0.5175484378552037, 0.6040283342284004, 0.6967236816886475, 0.7947296107910264, 0.8969240739120327, 1.0019935717126436, 1.1084644772034946, 1.2147391854455656, 1.3191361878042378, 1.419933062977085, 1.5154112954873151, 1.603901778100533, 1.683829829126782, 1.7537585595393799, 1.8124294582680096, 1.8587991261587382, 1.892071178472027, 1.911722450261227, 1.9175227757566309, 1.9095477686292637, 1.8881842008990677, 1.854127760072639, 1.8083731523531676, 1.752196709796327, 1.6871318463718752, 1.6149378873761322, 1.537562964046956, 1.45710181637209, 1.3757494781591293, 1.295751926144994, 1.2193548565293264, 1.1487518057249382, 1.0860328559265096, 1.0331351596317728, 0.9917964805787901, 0.9635128825052915, 0.9495016032338487, 0.9506700320705619, 0.9675915662407324, 1.000488960502082, 1.0492256070845485, 1.113304994999854, 1.1918784031171885, 1.2837606849527556, 1.3874538096602975, 1.5011776379574135, 1.6229072382158307, 1.7504158909221714, 1.8813227930187357, 2.013144360605826], [2.104964210915896, 2.233631771676336, 2.356538086409682, 2.4712808256457595, 2.5756034186257333, 2.6674436742231875, 2.7449779419647773, 2.806659795293419, 2.8512523505468526, 2.8778534876482254, 2.885913408496945, 2.8752441523553527, 2.8460208796750015, 2.79877493210787, 2.734378872117758, 2.6540238958810796, 2.559190193417685, 2.4516109957461834, 2.333231196298766, 2.206161559299367, 2.0726296282929977, 1.934928521118553, 1.7953648416244516, 1.6562069523370793, 1.5196348358490634, 1.3876927263888719, 1.26224561809019, 1.1449406548280923, 1.0371742807122273, 0.9400658835986346, 0.8544384999852092, 0.7808069724936925, 0.7193737652324677, 0.670032452304556, 0.6323787052914416, 0.6057284213965877, 0.5891424596227568, 0.5814572921790224, 0.5813207362008386, 0.5872318102955394, 0.5975836643282384, 0.6107084615554086, 0.6249230513389479, 0.6385742591629912, 0.6500826387252553, 0.6579835779415192, 0.6609647255191904, 0.6578988053652676, 0.6478710098950867, 0.6302003071244435, 0.6044541565863208, 0.5704563015379668, 0.5282874852362175, 0.47827912268899225, 0.42100014159148896, 0.35723738251878834, 0.2879701144185751, 0.214339372840679, 0.13761296133672224, 0.05914706771198671, -0.019654466489030194, -0.09738212491394412, -0.1726628136725167, -0.24420094417349172, -0.3108173951618947, -0.3714853024261367, -0.4253617065245574, -0.4718141957384028, -0.510441810595197, -0.5410896244626976, -0.5638565781478954, -0.5790963210188343, -0.5874109924864117, -0.5896380611518007, -0.5868305198968972, -0.5802309090818519, -0.5712398023990338, -0.5613795366840542, -0.5522540943551418, -0.5455061518776649, -0.5427723870283669, -0.5456381896939518, -0.5555929440939859, -0.57398704400167, -0.6019917668176548, -0.6405630680376216, -0.6904102662671007, -0.7519704726800378, -0.8253894805203964, -0.9105096732943895, -1.006865338553618, -1.1136855918628856, -1.2299049271898388, -1.3541812202168049, -1.4849208246737238, -1.6203102233672086, -1.7583535295910429, -1.896914985203952, -2.0337654726070573, -2.1666319524050435, -2.2932486593736687, -2.4114088385196704, -2.5190157818479957, -2.614131935557935, -2.695024886637982, -2.760209106341203, -2.8084824241954776, -2.8389563277503664, -2.85107932726842, -2.8446527875610323, -2.819838807201507, -2.7771599141000127, -2.71749054130585, -2.642040443165002, -2.5523304048182482, -2.4501607827692475, -2.337573586368034, -2.216808965335108, -2.0902571030952646, -1.9604066264020488, -1.8297907258013724, -1.700932236845618, -1.5762889572694927, -1.458200469952115, -1.348837705546225, -1.2501564130296496, -1.1638556127306294, -1.0913419868856575, -1.0337010204270665, -0.9916755429462232, -0.9656521455878322, -0.955655758328722, -0.9613524782757231, -0.9820605430327684, -1.0167691496266293, -1.064164633653698, -1.1226633497316165, -1.1904504372175368, -1.2655235182885745, -1.3457402621646704, -1.428868662202561, -1.5126388138640197, -1.5947949525246938, -1.6731465113714463, -1.745616991118951, -1.8102894940994365, -1.86544786386084, -1.9096124854848746, -1.9415699385206482, -1.9603958502817116, -1.9654704683695057, -1.9564866533902012, -1.933450181388462, -1.8966724358449414, -1.846755756455414, -1.7845718916937199, -1.7112341699219855, -1.6280641554227937, -1.5365536874726604, -1.4383233092404561, -1.3350781762460506, -1.2285625893677181, -1.1205143236505946, -1.0126199208775122, -0.9064720811923451, -0.8035302279217078, -0.7050852317415175, -0.61222916776753, -0.5258308449103416, -0.44651769436178657, -0.37466443725743603, -0.31038877462991277, -0.25355416021823446, -0.20377953315200376, -0.1604557076287038, -0.12276794499219851, -0.08972407443559764, -0.06018738590683678, -0.032913396286349594, -0.006589490619278679, 0.020123633380578813, 0.04854983533087424, 0.07995585172585792, 0.11551118817364092, 0.15625066672303053, 0.20304064210260367, 0.25654980602673155, 0.3172253803520385, 0.38527536078165847, 0.46065731652536024, 0.543074081778512, 0.6319764963666017, 0.7265731699285451, 0.8258470612121978, 0.9285784860611069, 1.0333739989990884, 1.1387004382562926, 1.2429232865796536, 1.3443483837480406, 1.4412659343615766, 1.5319956885888135, 1.6149321358692599, 1.68858854311223, 1.7516386900056642, 1.802955204211833, 1.841643477312094, 1.8670702465014501, 1.878886054701589, 1.877040949840981, 1.861792948908978, 1.8337089699675309, 1.7936581212127005, 1.7427974258147032, 1.682550249922779, 1.614577884205633, 1.5407449020466248, 1.4630790757049925, 1.3837267714219719, 1.3049048620753647, 1.2288502885882118, 1.1577684665090424, 1.0937817703084416, 1.03887933399964, 0.9948693824505512, 0.9633352537195465, 0.9455961901616544, 0.942673866866156, 0.9552654928094382, 0.9837241661428759, 1.0280469940049124, 1.0878713032954619, 1.1624790764489619, 1.25080955007306, 1.3514797191645185, 1.4628123002351947, 1.5828705277038408, 1.7094989937098115, 1.840369596098219, 1.9730315362716908, 2.1049642109158953], [2.19589601650477, 2.321933123960234, 2.440629621104243, 2.5496674524733924, 2.6469048936658965, 2.7304226168183128, 2.798564669630325, 2.849973425052687, 2.8836177030599237, 2.898813429298638, 2.8952363738462017, 2.8729267024779164, 2.832285268109306, 2.774061766693966, 2.699335075028147, 2.6094862729418926, 2.506165024749425, 2.391250150409922, 2.2668053518539164, 2.1350311711101018, 1.9982143415625633, 1.8586757498741513, 1.7187182525263456, 1.5805755869828266, 1.4463635833642148, 1.3180348191489053, 1.197337768431801, 1.085781380999007, 0.9846058878503873, 0.8947604723074509, 0.8168882734235898, 0.7513190053697794, 0.6980692873571719, 0.6568505881739392, 0.6270845022763889, 0.6079248952084728, 0.5982862893464229, 0.5968777106752232, 0.6022410871811333, 0.6127931826598348, 0.6268699688754109, 0.6427722859926083, 0.6588116172766769, 0.6733548097164603, 0.6848666072428735, 0.6919489266191321, 0.6933758961963395, 0.6881237922185219, 0.6753951432796206, 0.6546364274044489, 0.6255489541254957, 0.5880927015915383, 0.5424830616674483, 0.4891806295372107, 0.4288743538638494, 0.36245853455728533, 0.29100431334035254, 0.21572644359840995, 0.13794624689048401, 0.05905176094738822, -0.01954384446541385, -0.09644446358194182, -0.1703127272584411, -0.23991003096933886, -0.3041338398551638, -0.3620512631086182, -0.41292798651955054, -0.45625177202109773, -0.4917498735551373, -0.5193998759556927, -0.5394336338566559, -0.5523341665588987, -0.5588255478149474, -0.5598560119726336, -0.5565746752370849, -0.5503024384622666, -0.5424977916053286, -0.5347183758505144, -0.5285792739575483, -0.5257090896668283, -0.5277049406583137, -0.5360875249355451, -0.5522574266192208, -0.5774538037468065, -0.6127165482847995, -0.6588529283945342, -0.7164096169744514, -0.7856508812055206, -0.8665435584132009, -0.95874927769934, -1.0616242085796812, -1.1742264316934463, -1.2953308371451617, -1.423451267903426, -1.5568694436017831, -1.6936700286075674, -1.8317810516385984, -1.9690187464463078, -2.1031357676223124, -2.231871645352885, -2.353004280253487, -2.464401245898808, -2.5640696632389846, -2.650203437936225, -2.7212267081954975, -2.775832435593954, -2.813015182727782, -2.832097256531482, -2.832747551632295, -2.81499260032266, -2.7792195204893435, -2.7261707456386692, -2.6569306173079585, -2.5729041148710454, -2.4757881862760893, -2.367536320990395, -2.250317169021491, -2.1264681533570555, -1.9984451440038795, -1.8687693570457182, -1.7399727094449213, -1.6145428980293686, -1.4948694783052416, -1.383192195233658, -1.2815527644754978, -1.1917512201484703, -1.1153078358670652, -1.0534314924156685, -1.0069952110965368, -0.9765194003648339, -0.9621631789969062, -0.9637239462343866, -0.9806451728068973, -1.012032191249025, -1.056675574251204, -1.1130815105297576, -1.1795084232181123, -1.254008930050468, -1.3344761211474458, -1.4186930319835245, -1.504384118458923, -1.5892674995719505, -1.6711067219287496, -1.7477608194289278, -1.817231490373674, -1.8777062916703917, -1.927596853767281, -1.9655712478051677, -1.990579785001364, -2.0018736937561807, -1.9990162982617865, -1.9818865090525162, -1.9506746263254395, -1.9058706462580897, -1.848245444270199, -1.7788253826833291, -1.6988610492550111, -1.6097909737010145, -1.5132012881346917, -1.4107823914608222, -1.304283744899089, -1.195467964392448, -1.086065384806507, -0.9777302504119263, -0.8719996367662264, -0.7702561320988734, -0.6736952036680729, -0.5832980489505439, -0.4998105861671964, -0.4237290772493108, -0.3552927030173488, -0.29448322947737304, -0.241031720320264, -0.1944320685858369, -0.15396094462925242, -0.11870359243776339, -0.08758475615511215, -0.05940388716267297, -0.032873672551644396, -0.006660841054108007, 0.02057185538733609, 0.05012361578931182, 0.0832146519039595, 0.12094744088430796, 0.16427121519003143, 0.2139506522485297, 0.2705396177646606, 0.33436068591047047, 0.4054910102255576, 0.4837549546945887, 0.5687237192956976, 0.6597220127625862, 0.755841641968733, 0.8559617068686014, 0.958774916895756, 1.0628193835173674, 1.1665150983825665, 1.2682041808884503, 1.3661938762429393, 1.458801207880791, 1.544398138403415, 1.6214560723938198, 1.6885885431122303, 1.744590963075456, 1.788476384999238, 1.8195063129574953, 1.837215721630089, 1.8414315812950226, 1.8322843443454195, 1.8102120216844333, 1.775956660111765, 1.7305532202392004, 1.6753110438838186, 1.6117882855753798, 1.5417598601491986, 1.467179622945714, 1.3901376467773732, 1.3128135868376847, 1.2374272279041554, 1.166187384897935, 1.1012403761283938, 1.0446193070910084, 0.9981953909535111, 0.963632490056758, 0.9423459918142726, 0.9354670339795851, 0.9438129707050127, 0.9678648251041355, 1.007752309668876, 1.063246816860769, 1.1337625928417967, 1.2183661122401788, 1.315793475814391, 1.424475460667566, 1.5425696689698496, 1.6679990504585864, 1.7984959204827784, 1.9316504627969535, 2.0649625979389703, 2.1958960165047685], [2.2851704531500543, 2.4075049293468425, 2.520969845889181, 2.6233510452383078, 2.712639789497297, 2.787075880694692, 2.8451851110928077, 2.8858101835851806, 2.9081343983098638, 2.911697574437828, 2.896403861482197, 2.862521287893045, 2.810673091439259, 2.7418210711415925, 2.6572413895582367, 2.5584934324422215, 2.4473824958656665, 2.325917214892797, 2.196262769309031, 2.0606909978631296, 1.9215286206692663, 1.781104808247342, 1.6416993442785537, 1.50549260738973, 1.3745185457720495, 1.250621738536394, 1.1354195314541267, 1.0302701048197926, 0.9362471808695417, 0.8541219112612833, 0.7843523057370768, 0.7270803757111709, 0.6821369758123631, 0.64905413708263, 0.6270845022763886, 0.61522730103549, 0.612260144881087, 0.6167757828331791, 0.627222841437089, 0.6419494808812709, 0.6592488339436966, 0.6774050582347199, 0.694738825424963, 0.709651093932151, 0.7206640632279767, 0.7264582871312959, 0.7259050281086413, 0.7180930620060352, 0.702349289521892, 0.678252673351799, 0.6456411941565682, 0.6046116999054757, 0.5555127071336906, 0.49893039457518806, 0.4356682048962004, 0.36672063443900943, 0.29324193985437624, 0.21651062050289466, 0.13789064327117584, 0.058790459270507245, -0.019379082314445437, -0.09524679057737573, -0.16752202850899547, -0.23503334770956755, -0.29676382104209176, -0.35188211785474877, -0.399768476773304, -0.44003486323442415, -0.4725387495571403, -0.49739012062296656, -0.5149514839754653, -0.5258308449103399, -0.5308677903054977, -0.5311130048946242, -0.5278017158517789, -0.5223217215531278, -0.5161768041401925, -0.5109464493551495, -0.5082428978752609, -0.5096666274390346, -0.5167614124694374, -0.5309701263892401, -0.5535924408424819, -0.5857455357744481, -0.6283288657044673, -0.6819939321870409, -0.7471198927051269, -0.8237956949977823, -0.911809266559094, -1.0106441156803116, -1.1194835172267454, -1.2372222678841867, -1.36248580655693, -1.4936563106570282, -1.6289052028073119, -1.7662313393967428, -1.9035040065692324, -2.038509724269452, -2.1690017580763112, -2.2927511643014613, -2.4075981481373825, -2.5115024987263688, -2.6025918793722362, -2.679206795469958, -2.7399411360807004, -2.7836772857112435, -2.8096149283704714, -2.817292813358383, -2.806602917936763, -2.7777966220216865, -2.7314826999538178, -2.6686171296208694, -2.590484914967697, -2.4986743094550468, -2.3950440106363526, -2.2816840652470916, -2.1608713758986227, -2.035020830921545, -1.9066331849124944, -1.7782408965001344, -1.6523531798190674, -1.5314015459318113, -1.4176870994761306, -1.3133308143956477, -1.2202279417415995, -1.1400076039365066, -1.0739985059716715, -1.0232015477915286, -0.98826995716758, -0.9694973827074436, -0.9668141966626702, -0.9797920615251376, -1.007656617803791, -1.0493079576376767, -1.1033483647146283, -1.1681166297997583, -1.2417280971816511, -1.32211946423768, -1.4070972473070875, -1.4943887447474813, -1.5816942743854034, -1.6667394387943748, -1.7473261784477407, -1.8213814095535708, -1.8870021092984735, -1.9424958046038265, -1.9864155389558154, -2.017588532420478, -2.035137909069169, -2.038497039739313, -2.0274162320099345, -2.0019616889070697, -1.962506848466224, -1.9097164031495684, -1.844523476630018, -1.7681006012161844, -1.6818252881309768, -1.5872411113295615, -1.4860153304231394, -1.3798941570314718, -1.2706568196428554, -1.1600696036408307, -1.0498410351174596, -0.9415793397284721, -0.8367532421832605, -0.7366570797335329, -0.6423810866212207, -0.5547875688620321, -0.4744935334927333, -0.40186016745269093, -0.3369893828939414, -0.27972746243996843, -0.2296756543784982, -0.18620738861468014, -0.14849161394972862, -0.11552160017828245, -0.08614840857190958, -0.05911811505717186, -0.033111774802602766, -0.006787047400070454, 0.0211796398952048, 0.052051526273989214, 0.08699166794881949, 0.12702587927981182, 0.17300946590289126, 0.225598652924196, 0.2852274895881306, 0.35209086997926703, 0.42613415086698686, 0.5070496767534167, 0.5942803428667719, 0.6870301437926548, 0.7842814732916165, 0.8848187642309523, 0.987257890947078, 1.090080603990267, 1.1916731329713706, 1.2903679805663686, 1.384487842537229, 1.4723905271859534, 1.552513714593516, 1.6234183922191003, 1.683829829126783, 1.7326750057077172, 1.7691154979925032, 1.7925749235225639, 1.8027601866476821, 1.7996759118348902, 1.7836316204050346, 1.7552413849405861, 1.7154158820063679, 1.6653469531696674, 1.6064849718895855, 1.540509494992663, 1.4692938476366215, 1.3948644456232613, 1.3193557947591987, 1.2449622202493944, 1.1738874669645665, 1.10829337159467, 1.0502488386112536, 1.0016803527577258, 0.9643252313559867, 0.9396887606948993, 0.929006273516436, 0.9332111112038797, 0.9529092774164917, 0.988361432902178, 1.0394727078516441, 1.1057906226401901, 1.1865112146479457, 1.2804932727615383, 1.3862803869238485, 1.5021303324578332, 1.6260511324341456, 1.755842980398049, 1.8891450642626637, 2.02348621358104, 2.156338199639591, 2.285170453150053], [2.372032218720588, 2.489623211640908, 2.5968790461084486, 2.6917082074035084, 2.772251959155821, 2.8369241536040364, 2.8844448363214643, 2.913866875697396, 2.924595013960927, 2.916396917367774, 2.8894059939312355, 2.8441159431166296, 2.7813671984591113, 2.702325616324202, 2.608453947334713, 2.5014767968872174, 2.3833399335601637, 2.2561649353927717, 2.122200270833321, 1.9837699910634319, 1.8432212615125485, 1.702871981505539, 1.5649597316963058, 1.4315932495405823, 1.3047075646008475, 1.186023829718087, 1.0770147634603207, 0.9788764768060656, 0.8925072963133128, 0.8184940210757411, 0.7571058659349912, 0.7082961532928844, 0.6717116251631635, 0.6467090605347959, 0.632378705291441, 0.6275738572199663, 0.6309458010856842, 0.6409831619584538, 0.656054642023327, 0.6744540294835187, 0.6944463196830141, 0.7143137693570668, 0.7324007153456248, 0.7471560288213422, 0.7571721440043975, 0.7612196946724138, 0.7582769100805176, 0.7475530611441558, 0.7285054043478011, 0.700849240839306, 0.6645608872370332, 0.6198735382791114, 0.567266184938318, 0.5074459303788841, 0.4413242156345555, 0.36998762287033904, 0.2946640626278, 0.216685269062677, 0.13744662091057802, 0.05836537341177058, -0.019161573998477864, -0.09379923875581771, -0.16431432799840576, -0.22961215334127988, -0.28876969241680883, -0.3410639022349668, -0.38599451269301716, -0.4233006717649523, -0.4529709734033618, -0.4752465709541619, -0.49061725857061733, -0.499810586167195, -0.5037742552376221, -0.5036522187640115, -0.5007550739972917, -0.4965254878809061, -0.4924995274679633, -0.49026487845302946, -0.4914170210522509, -0.4975144916840278, -0.510034389662219, -0.530329289562388, -0.5595866919393392, -0.5987920882795897, -0.6486966318066337, -0.7097902960516331, -0.7822812706298875, -0.8660821916714154, -0.9608036365841953, -1.0657551334253033, -1.1799537485620204, -1.3021401271549922, -1.4308016739959504, -1.5642023820477722, -1.7004186471708789, -1.8373802542110913, -1.9729155857292249, -2.1047999935559742, -2.2308061878851126, -2.3487554409721705, -2.4565683741990494, -2.552314099089872, -2.6342565148677624, -2.7008966266302297, -2.7510098377653067, -2.783677285711243, -2.798310428814043, -2.7946682505194014, -2.772866621613469, -2.7333795474659097, -2.677032220697818, -2.604985995681433, -2.5187155949938878, -2.4199790446601948, -2.3107810101621067, -2.1933303644715143, -2.0699929588839328, -1.9432406837567664, -1.8155979965404079, -1.689587156506108, -1.5676734377927344, -1.452211594013582, -1.3453948186324793, -1.2492073863326085, -1.165382073094658, -1.095363338801165, -1.040277118668048, -1.0009079120239641, -0.9776836827617092, -0.9706688994209333, -0.979565848871062, -1.0037241606747098, -1.0421582842189117, -1.0935724723475986, -1.1563926480899036, -1.2288043694510005, -1.3087959650257774, -1.3942057938395807, -1.4827724891787546, -1.5721869804738569, -1.6601450510796192, -1.7443991838690185, -1.8228084709898191, -1.8933854182392236, -1.9543385568856804, -2.0041098843027356, -2.0414062867339897, -2.0652242495648694, -2.074867328831669, -2.069956038151838, -2.050429993323324, -2.0165423478481705, -1.9688467418573632, -1.9081771696758516, -1.8356213430653168, -1.7524882837965163, -1.660271016797761, -1.5606053503480262, -1.4552258198420291, -1.345919934392763, -1.234481899481375, -1.1226669932627653, -1.0121477489735264, -0.9044730418900051, -0.8010310978907951, -0.7030173340124412, -0.6114078122009771, -0.5269389390646828, -0.4500938806086751, -0.381095985844601, -0.3199093312578047, -0.2662463139838962, -0.21958203984948285, -0.17917507775279967, -0.14409398860258155, -0.11324888930813874, -0.08542718383649854, -0.059332487351659406, -0.0336256885864391, -0.006967041894370154, 0.02194184477222274, 0.054317255789816575, 0.09125494459557913, 0.1336950770208018, 0.1823914893064757, 0.23788609677310596, 0.30048915545517724, 0.3702659271782064, 0.447030132394992, 0.5303443988122448, 0.6195277318918194, 0.713669850311223, 0.8116520500550335, 0.9121740895359968, 1.0137864293659062, 1.1149270181567443, 1.2139616936659436, 1.3092271698388995, 1.3990755073979457, 1.4819189204865055, 1.5562737557122082, 1.6208024932314193, 1.6743526620295472, 1.715991632293811, 1.7450363450566069, 1.7610771607485118, 1.7639951509714882, 1.7539723181794802, 1.7314944020799699, 1.6973461151387854, 1.6525988380291257, 1.5985909945296828, 1.5369015095452274, 1.469316928996979, 1.3977929419250024, 1.3244111892024062, 1.2513323661476963, 1.1807467249215302, 1.1148231543862175, 1.0556580582283022, 1.0052252654389509, 0.9653281902923525, 0.9375554120836843, 0.9232407691500378, 0.9234289588791279, 0.9388475079620369, 0.9698858281296879, 1.0165819056267738, 1.0786169917689095, 1.1553184714949902, 1.2456708915044052, 1.3483349341221695, 1.4616739322377545, 1.5837873391807438, 1.712550399671382, 1.8456591181251096, 1.9806794922738835, 2.1150998764426947, 2.2463852624352323, 2.3720322187205864], [2.455746423374246, 2.567593213015275, 2.6677149955788857, 2.754160606445108, 2.825237056711343, 2.8795456966009323, 2.9160116902756306, 2.933906129078266, 2.932860285756192, 2.9128716995208124, 2.87430197631937, 2.8178663856939927, 2.744615530284541, 2.655909551661448, 2.553385512195356, 2.438918752813998, 2.314579166889612, 2.1825834477576844, 2.0452444586775553, 1.904918937235687, 1.7639547797853594, 1.6246391547637362, 1.489148666627118, 1.359502735442629, 1.2375212723411466, 1.1247876202334735, 1.0226175952160688, 0.9320353103067035, 0.8537562933975701, 0.7881782298235983, 0.7353794712272135, 0.6951252611365356, 0.6668814385935902, 0.6498351989391907, 0.6429223199683844, 0.6448601063097006, 0.6541851688533677, 0.6692950426696835, 0.6884925588603494, 0.7100318252769274, 0.7321646394369651, 0.7531861549621722, 0.771478650407734, 0.785552305663695, 0.7940819746886723, 0.7959390520049717, 0.7902176613420425, 0.7762545447093735, 0.7536421951901435, 0.7222349526809622, 0.6821479642021709, 0.633749094653744, 0.5776440553405943, 0.5146551916620756, 0.44579453366869415, 0.372231859650816, 0.29525864985844275, 0.21624891167191193, 0.1366179364387836, 0.05778009978989666, -0.018893159736287857, -0.0921140550607028, -0.16071676432449253, -0.22369231362194988, -0.2802190879248694, -0.32968814324871415, -0.37172262824759905, -0.40619077644482177, -0.43321209733458255, -0.4531565713995473, -0.46663683620039986, -0.4744935334927318, -0.4777741661779591, -0.477705984257608, -0.47566357650245694, -0.47313198525539735, -0.4716662820633781, -0.47284863859250387, -0.47824399802023704, -0.4893554949691994, -0.5075807858936202, -0.5341704362245256, -0.5701894658330838, -0.6164830815244053, -0.6736475260735554, -0.7420068501720186, -0.8215962695807846, -0.9121526083297028, -1.013112153947887, -1.1236160667861723, -1.2425232970653182, -1.3684307750407658, -1.4997004563104053, -1.6344926303892306, -1.7708047405929657, -1.9065148210360316, -2.0394285357497846, -2.1673287086310222, -2.288026163605711, -2.3994106538421547, -2.4995006481667272, -2.5864907623827817, -2.658795672580859, -2.715089425630664, -2.7543391670244204, -2.775832435593954, -2.7791973252400877, -2.764414982053886, -2.7318240869951573, -2.682117165205026, -2.6163287584149724, -2.5358156920069037, -2.4422298583094975, -2.3374841180366674, -2.223712087966805, -2.103222730952731, -1.978450790508317, -1.8519042134387238, -1.7261097777751397, -1.603558187820264, -1.486649912301486, -1.3776430251017715, -1.278604261182855, -1.191364424262136, -1.1174791794014654, -1.0581961354272515, -1.014428972151885, -0.9867391993595532, -0.9753259525507418, -0.9800240389437892, -1.00031025087421, -1.0353177672948999, -1.0838582723422057, -1.1444512375544236, -1.2153596457368634, -1.2946312837445195, -1.3801446022399741, -1.469658035888302, -1.560861599972775, -1.6514295308843028, -1.7390727194713562, -1.8215896982111155, -1.8969149852039522, -1.9631636589902197, -2.0186711363186167, -2.0620272477721766, -2.0921038504920038, -2.1080753795158924, -2.109431915419905, -2.0959845316318266, -2.067862875367397, -2.025505126903352, -1.9696406681319332, -1.9012659684486368, -1.8216143596543135, -1.7321205176943497, -1.6343805941442624, -1.530109041347131, -1.4210932495832898, -1.3091471608417307, -1.196065040608552, -1.0835765762669252, -0.9733044286318921, -0.8667252929670299, -0.7651354293939985, -0.6696215024065574, -0.5810374283245037, -0.49998777156823027, -0.4268180596193898, -0.3616122067973447, -0.30419705307459194, -0.2541538407253839, -0.2108362732795461, -0.17339463253224388, -0.14080527448819616, -0.11190468798970712, -0.0854271838364985, -0.060045190359519635, -0.0344110659599935, -0.007199301702136893, 0.0228520214202287, 0.05690163523983574, 0.09596841259465214, 0.14089860967654272, 0.1923379092373764, 0.25070902646016613, 0.31619549476658254, 0.3887320882990783, 0.4680021653503066, 0.5534420369814733, 0.6442522820351142, 0.7394157483465386, 0.8377218047942384, 0.9377962443532287, 1.038136088712916, 1.1371484141098198, 1.23319220915712, 1.3246221914309169, 1.4098334525793743, 1.4873057732634776, 1.555646450110189, 1.6136305071199204, 1.660237222942633, 1.6946819917221316, 1.7164426467213274, 1.7252795099613072, 1.7212485843447063, 1.704707473412229, 1.6763137938296164, 1.6370160324594627, 1.5880369887971229, 1.5308501299367558, 1.4671493644290534, 1.3988129089116548, 1.327862073031191, 1.2564159201129308, 1.1866428699298714, 1.12071039300241, 1.0607340009804267, 1.0087267633676624, 0.9665505764139223, 0.9358703754388866, 0.9181124179211289, 0.9144276728734438, 0.9256612345079436, 0.9523285377869842, 0.9945989935435914, 1.0522874853087627, 1.1248539830657422, 1.21141133541225, 1.3107411057749103, 1.4213171251682597, 1.5413362482467858, 1.668755625609205, 1.8013356477393667, 1.9366875784723308, 2.0723247818356625, 2.205716358338453, 2.3343419474278835, 2.4557464233742445], [2.535604807058549, 2.64075527197649, 2.7328783901143407, 2.810179866807182, 2.8711468042625143, 2.914579912145158, 2.9396186030866907, 2.9457584025763235, 2.9328602857561923, 2.9011517458351075, 2.851219595470243, 2.7839946987589896, 2.7007290226586274, 2.6029655780638854, 2.4925019880201957, 2.37134856958326, 2.241681943054645, 2.10579528466893, 1.966046413835473, 1.8248049519757856, 1.6843998057916034, 1.547068213136927, 1.4149075449863746, 1.2898309834664674, 1.173528095427608, 1.0674311961244953, 0.9726882513797173, 0.8901429027861602, 0.8203220231420095, 0.7634310228168996, 0.719356936744277, 0.6876791309496644, 0.6676872816677062, 0.6584061037503193, 0.6586261425560119, 0.666939798815277, 0.681781632616889, 0.7014718936447787, 0.7242621524933902, 0.7483818640099484, 0.7720846791526966, 0.7936933370778615, 0.8116420135976975, 0.8245150745826098, 0.8310812814113232, 0.8303226176552478, 0.8214570486841887, 0.8039546851631572, 0.7775469934238656, 0.7422288760774423, 0.6982536304226138, 0.6461209755436826, 0.5865585168608759, 0.5204971848120789, 0.4490413380852056, 0.3734343575217488, 0.2950206710692795, 0.2152052401115793, 0.13541160090140794, 0.05703959008456589, -0.018576110433992373, -0.09020549690864599, -0.15675977450385326, -0.21732391307436114, -0.2711843495494678, -0.3178510849646041, -0.35707357003755924, -0.38884993473075685, -0.41342929038333787, -0.4313070133511936, -0.44321310208932974, -0.4500938806086737, -0.453087495645128, -0.45349381826014284, -0.45273950879011327, -0.45233913329449377, -0.45385332660971034, -0.45884507904373123, -0.4688352785149312, -0.485258666098745, -0.5094213597617918, -0.542461068536753, -0.5853110582587648, -0.6386688417007781, -0.7029704526493252, -0.7783710279221817, -0.8647322668764535, -0.9616171684006142, -1.0682922649233977, -1.183737386084315, -1.3066627960432573, -1.4355333626635332, -1.5685992386248604, -1.703932368373735, -1.8394679848731506, -1.9730501301524774, -2.1024801269762814, -2.2255668482704944, -2.3401775783511765, -2.444288236888788, -2.5360317435755735, -2.6137433385685243, -2.676001740133178, -2.721665114969402, -2.74990095622597, -2.7602091063412026, -2.75243732315362, -2.7267889643028163, -2.6838225524966566, -2.624443178189456, -2.5498858918648244, -2.4616914306662876, -2.3616748088570665, -2.251887473993081, -2.1345738865313577, -2.012123516044478, -1.8870193589395376, -1.761784167836532, -1.6389256394413259, -1.520881834446237, -1.4099680990345407, -1.308326723032035, -1.2178805054663535, -1.1402913058175848, -1.0769245408189718, -1.02882044517366, -0.9966727534391299, -0.9808152835188534, -0.9812167139991474, -0.9974836525623992, -1.028871895644219, -1.0743055851774308, -1.13240378140469, -1.2015137958815978, -1.2797504701725433, -1.3650404471983733, -1.455170367067782, -1.5478378302735825, -1.640703910476106, -1.7314459681446837, -1.8178095157708425, -1.8976579151402244, -1.969018746446308, -2.030125776314792, -2.079455564864456, -2.115757887909292, -2.138079305899555, -2.1457793823238056, -2.1385392367906872, -2.1163623073464106, -2.0795673880715926, -2.0287741969061055, -1.9648819103143955, -1.8890412713576616, -1.8026210318148979, -1.7071696234274278, -1.6043730648616787, -1.4960101969007615, -1.3839063966364742, -1.269886950682486, -1.1557312670342776, -1.0431290752697102, -0.9336397061594495, -0.8286554559964863, -0.7293699302913291, -0.6367521287630535, -0.5515268821821511, -0.4741620854452369, -0.40486299450287594, -0.34357367189817245, -0.28998548132762003, -0.24355235046010515, -0.20351234781137406, -0.16891495813525997, -0.13865329561614034, -0.11150036877439953, -0.0861484085719095, -0.06125019429080426, -0.03546126227529838, -0.007481861800298204, 0.02390246933292092, 0.05978279960445449, 0.10109219387389776, 0.1485755321011313, 0.2027645744821716, 0.263958954197782, 0.3322136247845726, 0.40733312126276705, 0.48887281684417566, 0.57614717479039, 0.6682448124144579, 0.7640500159510714, 0.8622701755874388, 0.961468453658737, 1.0601008598516861, 1.1565567887844341, 1.2492019805819372, 1.3364227964934257, 1.4166706609972544, 1.4885055103047975, 1.550637105076711, 1.6019631121324678, 1.6416029348680246, 1.6689263731946384, 1.6835763186133776, 1.685484835485232, 1.674882142064041, 1.6522981804124648, 1.6185566485692815, 1.5747615567017594, 1.5222765567694319, 1.462697477758434, 1.3978186712519522, 1.329593930650045, 1.2600928877501074, 1.191453909099543, 1.125834608516058, 1.065361159026819, 1.0120776254606292, 0.9678965470039245, 0.9345519769058157, 0.9135561346408013, 0.9061607453969907, 0.9133240346475894, 0.935684214340947, 0.9735401450661674, 1.0268396890959652, 1.0951760865870763, 1.1777924958732937, 1.2735946433809198, 1.381171334002125, 1.4988223835387402, 1.6245933557098964, 1.7563163215914441, 1.8916557132636616, 2.028158219474327, 2.1633055723283414, 2.29456900282705, 2.4194641012616525, 2.535604807058548], [2.6109317317111973, 2.7084904043995306, 2.7918179179102713, 2.859292040198062, 2.909592784570653, 2.941730394920046, 2.955065849590012, 2.9493234205945593, 2.924595013960928, 2.881336212422181, 2.8203541387707336, 2.7427874521102034, 2.650078975294755, 2.543941625505571, 2.4263184769738624, 2.299337921520992, 2.165265005555277, 2.0264501087332794, 1.8852761876039623, 1.7441058358510186, 1.605229410610304, 1.4708154418925254, 1.3428644802576466, 1.223167448160644, 1.1132694450941627, 1.0144398186931913, 0.9276491567934072, 0.8535536829685905, 0.792487354602173, 0.7444617726251611, 0.7091738203781869, 0.6860207603630636, 0.6741223365884565, 0.6723492612351009, 0.6793573116091711, 0.6936261305469233, 0.7135017138052663, 0.7372414841642994, 0.7630607959743883, 0.7891796870013101, 0.8138686972301897, 0.8354926066137269, 0.8525510046887994, 0.8637146929221783, 0.8678570332950997, 0.8640794910990999, 0.8517307727540578, 0.8304191267828114, 0.8000175536388654, 0.7606618533894586, 0.7127416246742393, 0.656884509238259, 0.5939341491208616, 0.5249224839233128, 0.45103715944953027, 0.3735849428070128, 0.29395213966855316, 0.2135630843153462, 0.13383782044297032, 0.05615010934296982, -0.01821310847215529, -0.0880897115652461, -0.15247683646092883, -0.21056083124888036, -0.2617419152655258, -0.30565287425205023, -0.3421712757241293, -0.37142485799047886, -0.39378992404825736, -0.4098827539572276, -0.4205442316273471, -0.42681805961938857, -0.4299231040426825, -0.4312205666520847, -0.43217681884636605, -0.43432284893465767, -0.4392113667705527, -0.4483726762571771, -0.4632704645608422, -0.4852586660987448, -0.5155405391789395, -0.5551310439981544, -0.6048235337018623, -0.6651616672384449, -0.736417326306337, -0.8185751719033783, -0.911324312460512, -1.0140573793229808, -1.1258771208025902, -1.2456104377532613, -1.3718295963110299, -1.5028801717677387, -1.6369151060638802, -1.771934104396096, -1.9058274578943513, -2.0364232627377317, -2.161536914415774, -2.2790216914599823, -2.3868192075539763, -2.4830085054521587, -2.5658525908279195, -2.6338412585206363, -2.685729146407393, -2.720568061339105, -2.737732754641624, -2.736939478388105, -2.718256824281329, -2.682108530402332, -2.6292681328207665, -2.5608455344471284, -2.478265757764128, -2.3832403364521375, -2.2777319788065373, -2.1639132988709666, -2.0441205553754043, -1.9208034603277455, -1.7964722154618609, -1.6736430033157714, -1.5547831988005423, -1.442257575745047, -1.338276760831054, -1.244849135085868, -1.1637373019341493, -1.096420132691846, -1.044061267940769, -1.0074847996725877, -0.987158688174872, -0.9831862835104789, -0.995306128599473, -1.0229000240449846, -1.065009138742043, -1.1203577597408272, -1.1873840944326026, -1.2642773722645717, -1.349020345885037, -1.4394361664292323, -1.5332385075892123, -1.6280837405581623, -1.7216239186128315, -1.811559316987926, -1.8956892910525787, -1.9719602631198652, -2.038509724269452, -2.0937052403996708, -2.1361775787524326, -2.1648472191851305, -2.1789436797997648, -2.178017265063596, -2.1619430318340056, -2.1309169600919953, -2.0854445059620805, -2.0263219000449344, -1.954610729649249, -1.8716065048720536, -1.7788020516951701, -1.6778466968516579, -1.5705023062263033, -1.4585973086628365, -1.3439798786047557, -1.2284714630584237, -1.1138218207342303, -1.0016666944322596, -0.8934891630568073, -0.7905856190259425, -0.6940371928892686, -0.6046873028565147, -0.5231258463479579, -0.4496803776865595, -0.38441443504479944, -0.3271329953148614, -0.2773948523446779, -0.23453153659293324, -0.1976722271685416, -0.16577395463432226, -0.1376562587014532, -0.11203935238573404, -0.08758475615511203, -0.0629373042669841, -0.036767392396307025, -0.007812331602563737, 0.02508430124562492, 0.0629363729294064, 0.10658293892515608, 0.15666089405700853, 0.21358327073477051, 0.2775237796016327, 0.3484080248809087, 0.4259116529133364, 0.5094655117208834, 0.5982677164989394, 0.6913023353660971, 0.7873642360737539, 0.8850894721094599, 0.98299043985, 1.0794949108792096, 1.1729879385484503, 1.2618555580296371, 1.344529146567762, 1.4195292867744982, 1.4855079812922085, 1.5412881019375118, 1.5858990197102116, 1.6186074523149445, 1.6389426808986234, 1.6467154247407338, 1.6420298182736495, 1.625288105212241, 1.5971878455144404, 1.5587116178832745, 1.5111093889010572, 1.4558739049579417, 1.3947096402715726, 1.3294959990506985, 1.2622456180901878, 1.195058744055136, 1.1300747641710607, 1.0694220473138691, 1.015167302560005, 0.9692656827809826, 0.9335128512434094, 0.9095001895460018, 0.898574256472558, 0.9018015110690173, 0.9199391917512665, 0.9534130994333008, 1.002302870003642, 1.066335143913355, 1.144884852487587, 1.2369846464182612, 1.3413422964773165, 1.4563657045852052, 1.5801949796762678, 1.7107408618236777, 1.8457286240177848, 1.9827464476196357, 2.119297158117285, 2.2528521250950746, 2.380906076329832, 2.501031551996892, 2.6109317317111964], [2.6810898974638078, 2.770225540413602, 2.844034923891082, 2.901081615407351, 2.9402497272453485, 2.960767439555587, 2.962222739090219, 2.94457102146735, 2.908134398309865, 2.853592747661335, 2.781966741951299, 2.694593277700774, 2.59309391051303, 2.479337063333792, 2.35539492150819, 2.223496051294991, 2.0859748762618118, 1.9452192160432507, 1.803617132645886, 1.6635043399005685, 1.5271134116097074, 1.3965259739800318, 1.2736289893683974, 1.1600761331994396, 1.057255136789982, 0.9662618189715029, 0.8878813625777616, 0.8225772122104617, 0.7704877816692383, 0.7314309676886881, 0.7049162759013132, 0.6901641799423176, 0.6861321598793158, 0.6915467059718634, 0.7049404320567116, 0.7246933230624872, 0.7490770461781459, 0.7763011873065258, 0.8045602352229076, 0.8320801262072799, 0.8571631819690247, 0.8782303228351102, 0.8938595151048793, 0.9028195141732182, 0.9040980908378471, 0.8969240739120333, 0.8807827041470022, 0.8554239684169374, 0.8208637647276797, 0.7773779332879337, 0.7254893719697867, 0.6659486313718623, 0.5997085509341203, 0.5278936489628256, 0.45176511220980675, 0.37268234148695417, 0.2920620959154298, 0.2113363376643328, 0.13190990995829294, 0.05511918297467699, -0.017807225011634006, -0.08578459953191206, -0.147904185789614, -0.20346028687808063, -0.2519716723398358, -0.293196713493434, -0.32714182546056564, -0.35406297025814776, -0.37446015625545054, -0.38906505214671033, -0.3988220137163413, -0.4048629945028747, -0.4084769726055859, -0.41107467122079905, -0.4141494763328627, -0.41923555809403473, -0.4278642801517068, -0.4415200314992319, -0.4615966370021287, -0.48935549496919895, -0.5258865531182343, -0.5720731688830974, -0.6285618077906316, -0.695737416845217, -0.7737051713585693, -0.8622791368649444, -0.9609782165441776, -1.0690295731829336, -1.1853795276472818, -1.3087117477780172, -1.4374723572500574, -1.569901417873582, -1.7040700754756488, -1.8379225129984285, -1.969321728486804, -2.0960980534134546, -2.216099250923021, -2.3272409860375105, -2.427556441925478, -2.5152438685390988, -2.5887108920619237, -2.6466144847419106, -2.687895593144722, -2.7118075463099074, -2.7179375107629604, -2.706220423316771, -2.676945011110528, -2.63075169704136, -2.5686223830441017, -2.4918622988223653, -2.402074294855855, -2.30112614112103, -2.191111562484702, -2.074305894000626, -1.9531173706111231, -1.830035172796693, -1.7075754298821575, -1.5882264340126195, -1.474394338975499, -1.36835060852319, -1.2721824388529277, -1.1877473103812304, -1.116632726588204, -1.0601220748614952, -1.0191673989262073, -0.9943697081394632, -0.9859672696564115, -0.9938321396016108, -1.0174749935286664, -1.0560581193877632, -1.1084162427387854, -1.1730846687494365, -1.248334053098852, -1.3322109584463024, -1.4225832183808405, -1.5171890199879572, -1.6136885320092171, -1.7097168500293458, -1.8029370044973936, -1.8910917822311126, -1.9720531471766805, -2.043868110663934, -2.1047999935559747, -2.1533641402086627, -2.1883572840780503, -2.2088799236439223, -2.2143512410980977, -2.2045162806594787, -2.179445293853455, -2.139525350920298, -2.085444505962081, -2.0181689838609636, -1.938914024972683, -1.849109175005603, -1.750358938645155, -1.644399823194646, -1.5330548801828838, -1.4181869065973747, -1.3016514918976378, -1.1852510917355654, -1.0706912745883497, -0.9595402242583997, -0.8531924910869418, -0.7528378701029672, -0.6594361481344844, -0.5736983076236096, -0.49607460643669665, -0.4267497746179356, -0.3656453853112544, -0.3124292726107972, -0.26653168854428594, -0.2271677192911494, -0.1933653214143718, -0.16399819634036894, -0.13782259912759737, -0.11351707877846591, -0.08972407443559748, -0.06509224657423475, -0.038318405871165064, -0.008187915184867037, 0.026387518325574188, 0.06633567455735419, 0.11239419356070302, 0.16508628972335965, 0.22470246692936027, 0.2912887381106482, 0.36464168310272616, 0.444310500466141, 0.5296060264634723, 0.619616512314608, 0.7132297738122129, 0.8091611598625431, 0.9059866327858759, 1.00218011718503, 1.0961541593478856, 1.186302848439685, 1.2710458865092031, 1.348872658264132, 1.4183851446434874, 1.4783385466775545, 1.527678537489621, 1.565574139344129, 1.5914453274713665, 1.604984590438687, 1.6061718249453034, 1.5952821074357888, 1.5728860617826308, 1.5398427270891049, 1.497285017811384, 1.4465980551998838, 1.3893908298445206, 1.327461825346158, 1.262759388548477, 1.1973377684317987, 1.1333098602302218, 1.0727977806679592, 1.01788246211805, 0.970553486340656, 0.9326603813491819, 0.9058665777110511, 0.891607163791607, 0.8910514944028369, 0.9050715960322001, 0.9342171769619858, 0.9786978953947116, 1.0383733669311566, 1.1127512085761089, 1.2009932243573027, 1.3019296423222815, 1.4140811189000815, 1.5356880391231773, 1.6647464645959988, 1.7990499197042158, 1.936236064350171, 2.07383718197561, 2.209333317739445, 2.3402068357791777, 2.4639971281369952, 2.578354202090689, 2.681089897463807], [2.7454857344871804, 2.825438372832556, 2.889087628557712, 2.9351950337187778, 2.9628582606791474, 2.9715299840398037, 2.96102872106361, 2.931541412641797, 2.8836177030599255, 2.81815607381851, 2.7363821797595267, 2.6398199200543195, 2.530255947747542, 2.409698475378419, 2.280331366995691, 2.1444646154462066, 2.0044823855472638, 1.862789856708399, 1.721760121517333, 1.5836823892527687, 1.4507127054892512, 1.3248283319143532, 1.2077868359009674, 1.1010908196565712, 1.005959076910083, 0.9233048046378686, 0.8537213222669768, 0.7974755654714004, 0.754509430685139, 0.7244488545137499, 0.706620324066491, 0.7000743344828666, 0.7036151430007362, 0.7158360188911913, 0.7351590591231532, 0.7598785338552219, 0.7882066463256313, 0.8183205403081575, 0.8484093662041957, 0.8767202244995052, 0.9016018424373337, 0.9215449053237407, 0.9352180561555028, 0.941498693852812, 0.9394978382934883, 0.9285784860611077, 0.908367050377289, 0.8787576577904905, 0.8399092583114789, 0.7922356901728147, 0.736389020598714, 0.6732366553696801, 0.6038328682483651, 0.5293855425299157, 0.45121903755628046, 0.37073418997717217, 0.28936653043531557, 0.208543839442821, 0.12964418044246553, 0.05395553308326264, -0.017361894010168886, -0.083309663099521, -0.14308050918373608, -0.19608235378037178, -0.24195628144863443, -0.2805879874452504, -0.3121123751970021, -0.3369111609603228, -0.3556035255872642, -0.36903003509707616, -0.3782302281492552, -0.38441443504479833, -0.3889305453102813, -0.3932265753577562, -0.39881000072473294, -0.40720490608021376, -0.41990806824058313, -0.4383451212454051, -0.46382795717735326, -0.4975144916840271, -0.5403718696201248, -0.5931441051486561, -0.6563250439845906, -0.7301374058437362, -0.8145185157639379, -0.9091131674870355, -1.0132738846302547, -1.1260686603452157, -1.24629606817042, -1.3725074505221049, -1.5030357113991073, -1.636030070911548, -1.769495985430972, -1.9013393023838614, -2.029413606389814, -2.1515696264473783, -2.2657055144414318, -2.369816774951473, -2.4620446260290905, -2.5407216003912243, -2.6044132557056474, -2.6519549499585646, -2.682482751225439, -2.695457687803135, -2.6906827013106427, -2.6683118382336346, -2.62885140027445, -2.5731529662693644, -2.5023983936522876, -2.4180771007038215, -2.32195611739324, -2.216043567922563, -2.1025464078098284, -1.9838233785750745, -1.8623342603610316, -1.740586594236952, -1.6210811092326862, -1.5062571227548194, -1.3984391860966894, -1.299786219166646, -1.212244320972118, -1.1375043561939941, -1.076965305451007, -1.0317042303208364, -1.002453547171754, -0.9895861301833037, -0.9931085778235369, -1.0126627830324133, -1.0475357501579015, -1.0966774060999263, -1.1587259638926948, -1.2320402186938475, -1.3147379931729506, -1.4047398055473945, -1.4998167124710602, -1.5976411835498732, -1.6958397967171521, -1.7920465056416028, -1.8839552226286183, -1.9693704832294345, -2.046255011365299, -2.1127730848435347, -2.167328708631023, -2.2085977344534236, -2.235553216922668, -2.24748346468092, -2.2440024258038647, -2.2250522354485693, -2.1908979457924884, -2.1421146489495704, -2.079567388071594, -2.004384425714344, -1.917924597509101, -1.8217396193491375, -1.7175323342719102, -1.6071119781424137, -1.4923476089009016, -1.3751208809917645, -1.257279353820476, -1.1405915006127436, -1.0267045325338244, -0.9171060737482467, -0.81309061832917, -0.7157315722645, -0.625859536522753, -0.5440473239866888, -0.4706020281788424, -0.4055642795175419, -0.34871463995607843, -0.29958690393356685, -0.257487897207833, -0.22152319978129184, -0.19062806892044204, -0.16360270697210666, -0.13915090957929774, -0.11592104571863371, -0.0925482638126604, -0.0676967894255143, -0.04010118042403359, -0.00860543494014831, 0.02780109476655989, 0.06995194485832386, 0.11847679193669913, 0.1737804364403123, 0.23602808963464092, 0.3051373719471274, 0.38077725535565426, 0.46237400134531076, 0.5491239632035331, 0.6400129417643549, 0.7338416117012719, 0.8292563754789651, 0.9247848581812912, 1.0188751323101444, 1.1099376604772733, 1.1963888682953925, 1.276695211683027, 1.3494165835081229, 1.4132479145643808, 1.4670578631218816, 1.509923554806666, 1.54116042871923, 1.5603463642044686, 1.5673394026263312, 1.5622885364275438, 1.5456372097589193, 1.5181193567748197, 1.4807479907872978, 1.4347965451860714, 1.3817733506730634, 1.3233898083285622, 1.2615229799264422, 1.1981734616687965, 1.1354195314541249, 1.0753686597742125, 1.0201075477888046, 0.9716519011412862, 0.9318971634419704, 0.9025714185794284, 0.8851916263910143, 0.8810242827372002, 0.8910514944028366, 0.9159433338880195, 0.9560371920640026, 1.0113246814098455, 1.0814464631226175, 1.165695182173671, 1.263026499980878, 1.3720780195320605, 1.4911957072968263, 1.6184672347720843, 1.75176149447553, 1.8887733947615373, 2.0270729086883077, 2.164157247499905, 2.2975049516885755, 2.424630643999807, 2.54313917035112, 2.6507778669343525, 2.7454857344871795], [2.803574424860649, 2.8736617761100374, 2.9265948656420995, 2.961343680176931, 2.9772271064487223, 2.973926972376252, 2.951493897442989, 2.9103448305045303, 2.8512523505468543, 2.7753260011896925, 2.683986118218808, 2.578930786561755, 2.4620967245977896, 2.335615035605375, 2.201762885074188, 2.0629122556840525, 1.9214769967588516, 1.7798594204084073, 1.6403977015731712, 1.505315313729944, 1.3766736767944285, 1.2563291101909189, 1.145895074267605, 1.046710549975771, 0.9598152533327816, 0.8859322114718217, 0.825458045259677, 0.7784611140414439, 0.7446874857294862, 0.7235745049372486, 0.7142715478551523, 0.715667379592902, 0.7264233720043708, 0.7450117014147473, 0.7697575295494288, 0.7988840801203312, 0.8305594601241291, 0.8629440404288268, 0.8942372054281926, 0.922722306446559, 0.9468087074588311, 0.9650698931116929, 0.9762767158684288, 0.9794249885983426, 0.9737567777799803, 0.9587749168957569, 0.9342504353937506, 0.9002227813327556, 0.8569929008963599, 0.8051094206976432, 0.7453483546014736, 0.6786869212508225, 0.6062722074728428, 0.5293855425299158, 0.449403555527622, 0.3677569705209883, 0.2858882489319294, 0.20520921544938475, 0.12705980099244635, 0.05266900467336574, -0.016880883169546907, -0.08068584135021245, -0.1380466171301194, -0.18848945260831332, -0.2317804773308773, -0.2679333716353806, -0.29721008088357204, -0.320114542164946, -0.33737956767187394, -0.34994720811851365, -0.35894309074987546, -0.36564538531125335, -0.3714491937765462, -0.37782728203031296, -0.38628817092681345, -0.39833267765316366, -0.4154100441901769, -0.43887480667310735, -0.4699455471081494, -0.5096666274390337, -0.5588739363523249, -0.6181655831393168, -0.6878783527425303, -0.7680705947609029, -0.8585120601605243, -0.9586810266779484, -1.067768871702675, -1.1846920643219527, -1.3081113608741306, -1.4364578054724244, -1.5679649631143227, -1.7007066525533787, -1.8326393031260657, -1.9616479378177685, -2.085594687124432, -2.2023686672304628, -2.30993601353455, -2.4063888477618938, -2.4899919742212147, -2.5592261478682623, -2.6128268326572632, -2.649817471418277, -2.6695364157415207, -2.67165681302015, -2.656198914305578, -2.6235344469223296, -2.5743828854833755, -2.5097996494124, -2.431156449562276, -2.340114196255764, -2.238589061411506, -2.1287124539262994, -2.012785816066655, -1.8932312756186185, -1.7725392908176707, -1.6532145000990812, -1.5377210346052679, -1.4284285670071486, -1.3275603551275674, -1.2371444934351126, -1.158969510788205, -1.0945453506517793, -1.0450706428550929, -1.011407026893904, -0.9940611194263556, -0.9931745370382119, -1.008522193977676, -1.0395188980384993, -1.085234070883447, -1.1444142266354516, -1.215512659197401, -1.2967256189438399, -1.386034107273746, -1.4812502867016955, -1.5800673978471378, -1.6801119954062271, -1.7789972648397168, -1.8743761612538599, -1.9639931222199525, -2.0457331467509294, -2.117667102270672, -2.178092218397253, -2.2255668482704953, -2.2589387219331556, -2.2773660783380185, -2.2803312388706494, -2.267646371477142, -2.2394513859607277, -2.196204093033316, -2.1386629475468135, -2.0678628753673993, -1.985084849204581, -1.8918200273126697, -1.7897293967283765, -1.680599966502642, -1.5662986337370448, -1.4487248943156523, -1.3297635899102287, -1.2112388727400252, -1.0948705300395531, -0.9822337423126637, -0.8747232550167883, -0.773522824773327, -0.6795806615810457, -0.5935914313819, -0.5159852126845439, -0.4469236211129297, -0.3863031312604737, -0.3337654407462259, -0.28871454153341775, -0.2503399929023878, -0.21764573325258837, -0.1894836280814718, -0.16459083254855192, -0.1416299519490656, -0.11923091455811628, -0.09603343036621056, -0.07072889720973187, -0.04210063297548068, -0.009061358462348028, 0.029313071072240668, 0.07375458854918826, 0.12477927251847631, 0.18266977779249483, 0.2474643189576231, 0.3189525154022355, 0.39667822739700354, 0.4799493301595805, 0.5678541913642777, 0.6592844418255456, 0.75296346355777, 0.8474798683057166, 0.9413251068025666, 1.0329342378428044, 1.1207287996107125, 1.2031606658236176, 1.2787557377037893, 1.3461563204460418, 1.4041610598282706, 1.4517613703126384, 1.4881733690763659, 1.5128644388747317, 1.525573673815931, 1.5263256127850906, 1.5154368316657296, 1.493515143541959, 1.46145134129539, 1.4204036048188062, 1.371774880762104, 1.3171837216544058, 1.258429238917895, 1.1974509764823444, 1.1362846445785248, 1.0770147634603189, 1.0217253514616578, 0.9724498487463578, 0.931121495849008, 0.8995253838478561, 0.8792533607121645, 0.871662916726989, 0.8778410823453102, 0.8985742564725572, 0.934324744814698, 0.985214629855884, 1.0510174201052251, 1.131157740693447, 1.2247191347319848, 1.3304598497761604, 1.4468362910339005, 1.572033637354965, 1.704002942078723, 1.8405038827873295, 1.9791521857963217, 2.117470636224953, 2.25294249556789, 2.383066088043349, 2.5054092861372066, 2.6176626254828936, 2.7176898095512225, 2.8035744248606482], [2.8548645119782243, 2.914487758432981, 2.956239306946293, 2.979306325400378, 2.983234697616886, 2.9679381249589563, 2.9336989371507434, 2.8811606077319922, 2.8113121662984004, 2.725464891570149, 2.625221851719265, 2.5124410268450723, 2.389192898934017, 2.2577135234382784, 2.1203542006533778, 1.9795289418749757, 1.837660973046088, 1.6971295361608214, 1.5602182357030403, 1.4290661342525213, 1.3056227292110376, 1.1916078432217576, 1.0884773367780705, 0.9973954058458889, 0.9192140636858582, 0.8544602285228374, 0.8033306516686213, 0.7656947287838265, 0.7411050449010861, 0.7288153163522494, 0.7278052144518282, 0.7368113910548593, 0.7543638789520085, 0.7788269140662369, 0.8084431246197474, 0.8413799572862034, 0.8757771636040386, 0.9097941526651502, 0.9416560286377313, 0.9696971736189932, 0.9924013064990973, 1.0084370451070026, 1.0166881194032316, 1.0162775247944196, 1.0065850631669213, 0.9872578909470798, 0.9582138740467834, 0.9196377343854861, 0.8719701571356192, 0.8158902072767505, 0.7522915739582575, 0.6822533172996615, 0.6070059306939006, 0.5278936489628258, 0.4463340259233087, 0.3637758717422088, 0.28165667924073023, 0.20136067811194264, 0.12417863662782758, 0.05127048235749469, -0.016368262059139604, -0.07793533300327829, -0.1328450986333994, -0.18074582274164744, -0.2215303518940038, -0.2553399298398551, -0.28256102267353117, -0.3038152208675827, -0.31994246543967825, -0.3319780205623385, -0.34112377942812944, -0.3487146399560768, -0.3561808181487572, -0.3650070762282784, -0.37668992728538725, -0.39269393588010615, -0.4144082633193336, -0.44310460640393545, -0.4798976492154621, -0.5257090896668278, -0.581236217458001, -0.6469259098289315, -0.7229547787943253, -0.8092160516535136, -0.9053135992554314, -1.0105633479192178, -1.1240021255115458, -1.2444038045881116, -1.3703024204104033, -1.5000217636882325, -1.6317107815453735, -1.7633839696519018, -1.8929658075205524, -2.0183381809544114, -2.137389653325417, -2.2480653928908585, -2.348416538165522, -2.4366477881837447, -2.5111620392898275, -2.5706009541251524, -2.6138804402485745, -2.640220133156719, -2.6491661185494415, -2.640606288131635, -2.6147778981899226, -2.572267086375351, -2.5140002950197204, -2.4412277441987746, -2.3554992898584146, -2.2586331869284324, -2.1526784499282803, -2.03987165987442, -1.9225892024784614, -1.8032960353156562, -1.684492168056058, -1.5686580978358107, -1.458200469952115, -1.3553992315690555, -1.2623575130511635, -1.1809554086739815, -1.1128087373024673, -1.0592337463806445, -1.0212185820785218, -0.9994021881062797, -0.9940611194263556, -1.0051045691584237, -1.0320777119514237, -1.0741732697343882, -1.130251010853284, -1.198864705891451, -1.2782958875143535, -1.3665936017428262, -1.4616191980140925, -1.5610950886172517, -1.6626563173969426, -1.7639037151702535, -1.8624573865674108, -1.9560092707250434, -2.042373546423298, -2.1195337101077127, -2.1856852412894003, -2.2392728818979784, -2.279021691459987, -2.303961195114224, -2.3134421125959905, -2.3071453391796792, -2.285083039638527, -2.247591908866931, -2.1953188431692223, -2.129199449667807, -2.050429993323325, -1.960433537482105, -1.8608211708597033, -1.7533493281114798, -1.6398742998807618, -1.5223050893404582, -1.4025558043320272, -1.2824987765597256, -1.1639195719597808, -1.048475000116018, -0.9376551469333974, -0.8327503458889338, -0.7348238718575262, -0.6446909911154571, -0.5629048354828986, -0.48974939187704086, -0.42523971527733756, -0.3691292878767535, -0.3209242646716012, -0.2799041705160552, -0.24514845013283776, -0.21556812482644516, -0.1899416813848242, -0.166954213080196, -0.14523875241667356, -0.12341868230879917, -0.10015008801014909, -0.07416291692298856, -0.04429984725215863, -0.009551828432160637, 0.030910655238893366, 0.07771143354360707, 0.13124831346840826, 0.19167910592959492, 0.25891439922328163, 0.33261728611091945, 0.4122100698080323, 0.4968877916742544, 0.5856382447399429, 0.6772679668872106, 0.7704335498622656, 0.8636774593472588, 0.9554674406618194, 1.0442384873883865, 1.1284362788280884, 1.2065609485529984, 1.2772100315889554, 1.3391194523786785, 1.391201459338073, 1.4325784835007314, 1.4626119967120683, 1.4809255666888, 1.4874214490012585, 1.4822902161359697, 1.46601309728278, 1.4393568850506075, 1.403361452397868, 1.359320109995065, 1.3087532163381366, 1.2533756256325446, 1.195058717424721, 1.1357878931559087, 1.0776165446752546, 1.0226175952160672, 0.9728337819547523, 0.9302278892398719, 0.8966341518102058, 0.8737120274620751, 0.8629034890684887, 0.8653949077245437, 0.8820844939316671, 0.9135561346408013, 0.9600603137581151, 1.0215026360109702, 1.0974402929503226, 1.1870866197407905, 1.2893236969037636, 1.4027227570899423, 1.525571968022399, 1.6559109836066317, 1.7915714902539306, 1.930222828769898, 2.0694216473395515, 2.206664441279709, 2.339441762805126, 2.4652928408733468, 2.581859338326147, 2.686936991379652, 2.778523924628765, 2.854864511978225], [2.898922058493856, 2.947570913516963, 2.9777701470825937, 2.9889309972823366, 2.980830207243889, 2.953614110147052, 2.907794393603259, 2.8442356560548534, 2.764135062346449, 2.668994592509677, 2.5605865525466225, 2.440913174358441, 2.312161270110706, 2.176653020920899, 2.036794068041319, 1.895020134585192, 1.7537434358967763, 1.6153001362220851, 1.4819000784698322, 1.355579953382035, 1.238160985906562, 1.131212102212143, 1.0360194034733472, 0.9535626157016266, 0.8844990124059784, 0.8291551230079016, 0.7875263492563526, 0.7592844190946841, 0.7437924172704197, 0.7401269491226864, 0.7471068229130529, 0.7633274809639957, 0.7872002745116452, 0.8169955648450659, 0.8508885466943781, 0.8870066310024062, 0.9234771945326705, 0.9584745038676856, 0.9902646511311916, 1.0172473973841483, 1.0379939055393599, 1.051279455579919, 1.0561103679996335, 1.0517445133088572, 1.0377049523049662, 1.0137864293659067, 0.9800546248018004, 0.9368382576604891, 0.8847143126641839, 0.8244868395773145, 0.7571599358914634, 0.6839056701918114, 0.6060278302810748, 0.524922483923313, 0.4420364183527713, 0.3588245755379705, 0.2767076223561128, 0.1970307877978534, 0.12102506330287563, 0.0497717982672805, -0.01582836768550477, -0.07508140860395321, -0.12751996089377302, -0.17291697879307955, -0.21129262583744687, -0.2429142082748614, -0.26828913822811407, -0.2881510967019358, -0.3034397446659423, -0.31527449988642803, -0.3249230536211315, -0.33376544074622505, -0.34325459579374573, -0.35487442269394964, -0.37009647528491557, -0.39033638706800206, -0.4169112011475318, -0.4509987344181589, -0.49360006421208447, -0.5455061518776636, -0.6072695179199462, -0.6791817598395063, -0.7612575597033091, -0.8532256673377258, -0.9545271708499671, -1.0643211832961181, -1.1814978872837991, -1.3046986928011624, -1.4323430822737786, -1.5626615453199977, -1.6937338482230142, -1.8235317437426404, -1.9499651090892005, -2.0709304066842256, -2.1843602961412185, -2.288273188451464, -2.380821525683326, -2.460337591888731, -2.5253757129048813, -2.5747497831538038, -2.6075651644825957, -2.6232441329984284, -2.6215442015811172, -2.60256881462867, -2.5667700935032376, -2.514943501661671, -2.448214492922242, -2.368017399975752, -2.276067008347055, -2.1743234389313333, -2.0649511255917075, -1.9502728190855432, -1.8327196712106357, -1.7147785504953321, -1.5989378105765542, -1.487632772872496, -1.383192195233658, -1.2877869776644972, -1.203382305416081, -1.1316943499661836, -1.0741525415465927, -1.0318682955314074, -1.0056109223486442, -0.9957912803263581, -1.002453547171753, -1.0252752930737972, -1.0635758414037288, -1.116332706454243, -1.1822057063848586, -1.2595681681742963, -1.346544474322256, -1.4410530523406884, -1.5408537813236645, -1.643598688139673, -1.746884731489171, -1.848307426976543, -1.9455140515042817, -2.0362551810096234, -2.11843336138233, -2.1901477871386326, -2.2497339641868264, -2.2957974592479293, -2.327240986037511, -2.343284243500616, -2.3434761001221704, -2.3276989061858715, -2.296164908185188, -2.2494049316597637, -2.1882496858146374, -2.1138042207868906, -2.0274162320099385, -1.9306390517989331, -1.8251902925029362, -1.7129072053411232, -1.5956998919744751, -1.4755035502455547, -1.3542309503430496, -1.2337263226487716, -1.1157217941765714, -1.0017974380195083, -0.8933459014849885, -0.7915424561688724, -0.6973211702349111, -0.6113577432676371, -0.5340593713129045, -0.46556182848005595, -0.4057337663275143, -0.35418804785266406, -0.31029975389249664, -0.27323033060702456, -0.2419571917002139, -0.2153079520102764, -0.19199835349228137, -0.17067285329829937, -0.14994677889716387, -0.128448918560524, -0.10486340795799942, -0.07796979520459858, -0.04668021690613043, -0.010072695251701331, 0.032580330981553024, 0.08178900314243383, 0.1378291837727826, 0.20073219785880522, 0.2702814575713486, 0.3460160739296016, 0.4272413761737044, 0.5130460788401772, 0.6023256621915904, 0.6938113681896861, 0.7861040657793148, 0.8777121096538864, 0.9670922092151183, 1.0526922418805018, 1.1329948893675477, 1.2065609485529984, 1.272071170711698, 1.3283655143941044, 1.3744787571782209, 1.4096714985889494, 1.4334556984906341, 1.4456140294726316, 1.4462124748464713, 1.435605772060875, 1.414435480436082, 1.3836206376585936, 1.3443411568283006, 1.298014300322893, 1.2462647437128243, 1.190888907973332, 1.1338143871363746, 1.0770554275349544, 1.0226655206317858, 0.9726882513797157, 0.9291075960552229, 0.8937988861524268, 0.8684816475611492, 0.8546754869603332, 0.8536601309609098, 0.8664406295761458, 0.8937186163140843, 0.9358703754388845, 0.9929323061595247, 1.0645941975766784, 1.150200541434267, 1.2487599166397878, 1.3589622848591363, 1.4792038450270115, 1.6076189110419137, 1.7421181057475854, 1.8804320097549245, 2.020159269541916, 2.158818058899154, 2.293899703901155, 2.4229232262694227, 2.543489534641598, 2.65333399853105, 2.7503761755589013, 2.8327655280256603, 2.8989220584938558], [2.935374317627761, 2.972631342899679, 2.9910052254006354, 2.990136266743473, 2.970033978406331, 2.9310761155875373, 2.873999430960884, 2.799882377273031, 2.7101201783383124, 2.606392868291424, 2.4906270645796824, 2.364952387100614, 2.2316535605649026, 2.0931193365848313, 1.9517894437712908, 1.810100816565034, 1.670434365648309, 1.535063534343896, 1.4061058369231014, 1.285478497461517, 1.1748592037561367, 1.075652862460394, 0.9889650922066792, 0.9155830247821629, 0.8559638045357053, 0.8102309875703588, 0.7781788495728044, 0.7592844190946838, 0.7527268664511924, 0.7574137017167503, 0.7720130728971708, 0.7949913112010131, 0.8246547479182114, 0.8591947296941381, 0.8967346882958015, 0.9353780789630002, 0.9732559890638637, 1.008573236237155, 1.0396518219666315, 1.0649706813322606, 1.0832007705608575, 1.0932346583514394, 1.0942099315957432, 1.0855258873698321, 1.0668531568500996, 1.038136088712917, 0.9995879050243643, 0.9516788269475329, 0.8951175461594892, 0.8308265862000529, 0.7599122518561788, 0.6836300002741063, 0.6033461814064532, 0.5204971848120792, 0.4365470925207458, 0.3529449721146477, 0.27108294953879475, 0.19225617733847106, 0.11762576167492783, 0.0481856319482885, -0.01526576779934829, -0.07214821364407063, -0.12211625698616914, -0.165069156325006, -0.20115391495626647, -0.23076133416754255, -0.2545151741478272, -0.27325469524654356, -0.28801102583597615, -0.29997796543412775, -0.31047797880011885, -0.3209242646716013, -0.332779888401816, -0.34751504826130236, -0.3665635985128934, -0.3912799771466038, -0.4228976816881522, -0.46249040282064496, -0.510936863466733, -0.5688903219669662, -0.636753584236055, -0.7146602340840169, -0.8024626366107901, -0.8997271005502724, -1.0057364058590574, -1.119499717195669, -1.23976971685772, -1.3650666069230817, -1.49370845439118, -1.6238471894702975, -1.7535094199374015, -1.8806410974396224, -2.003154967948261, -2.118979660979284, -2.226109222679157, -2.3226518777676115, -2.4068768152301443, -2.4772578324177488, -2.532512740955836, -2.5716375339832664, -2.593934435450001, -2.599033095586472, -2.5869043587531544, -2.557866206749243, -2.5125816679969515, -2.4520486762471854, -2.377582056845099, -2.290788009383502, -2.1935316380732996, -2.0878982508830983, -1.9761493012627407, -1.860673978296659, -1.7439375591641313, -1.628427719133824, -1.5166000469572039, -1.4108240361227042, -1.3133308143956477, -1.2261638355564004, -1.1511336891654844, -1.0897780881592696, -1.043327972428794, -1.0126805222012594, -0.9983797115293216, -1.000604853467912, -1.019167398926206, -1.0535160553326557, -1.1027500939063586, -1.1656405202860591, -1.2406585972442175, -1.3260110347244443, -1.4196810056938758, -1.5194740100920987, -1.6230674967736232, -1.728063067483695, -1.8320400296268105, -1.9326090372301183, -2.0274645626813945, -2.114434975394904, -2.191529066645053, -2.25697795079879, -2.3092713897848607, -2.3471877269450623, -2.369816774951474, -2.376575176309099, -2.367213939791553, -2.341818047411764, -2.300798219494622, -2.2448751153459963, -2.175056429239611, -2.092607511506816, -1.9990162982617912, -1.8959534669861047, -1.785228845596423, -1.6687451870762047, -1.5484504782638069, -1.4262899786510155, -1.3041591824807022, -1.183858865207241, -1.0670533144001868, -0.9552327570471978, -0.8496808822340826, -0.751448223250409, -0.6613320097313751, -0.579862932397837, -0.5072990845515102, -0.4436271602249247, -0.38857080341811806, -0.3416058208397937, -0.3019817965777469, -0.2687494855119032, -0.2407932170949164, -0.2168674159838359, -0.19563624402715946, -0.175715291823913, -0.15571419935610625, -0.13427906523839442, -0.11013351339020115, -0.08211732414166743, -0.049221602932994456, -0.010619552151981869, 0.03430797208789985, 0.08595279926174208, 0.14446620629094808, 0.2097524603258338, 0.2814693235445467, 0.35903551905031816, 0.4416449748404224, 0.5282874852362167, 0.6177752606164407, 0.708774681071983, 0.7998424316532736, 0.8894650797332536, 0.9761010616602371, 1.0582239787307814, 1.1343660633211319, 1.2031606658236182, 1.2633826321603985, 1.3139854896738796, 1.3541344349760962, 1.38323421903517, 1.4009511498883864, 1.4072285788097294, 1.4022953979201838, 1.3866672520816234, 1.361140351103284, 1.326777955239793, 1.2848897929941945, 1.2370048506932987, 1.1848381436409336, 1.1302522345837125, 1.075214402800457, 1.0217504828553645, 0.9718964829771478, 0.9276491567934059, 0.8909167370820933, 0.8634710453344541, 0.8469021660269385, 0.8425768200894032, 0.8516014893816828, 0.8747912350017358, 0.912645019552706, 0.96532819029235, 1.0326626100884715, 1.1141247404430092, 1.2088517899806108, 1.315655847391202, 1.4330457246321804, 1.5592560489753327, 1.6922829658278535, 1.829925652515366, 1.9698327003768825, 2.10955230211777, 2.2465850863810175, 2.378438374293107, 2.5026805950040774, 2.6169945899344165, 2.719228558783946, 2.8074434538159263, 2.879955711232578, 2.935374317627761], [2.96391288677283, 2.9894570240085767, 2.995832567148905, 2.982911936658756, 2.9509373520855275, 2.9005148229129447, 2.832599969899968, 2.7484760201951044, 2.649724504634712, 2.538189357829878, 2.4159352767436726, 2.2852013277044394, 2.1483509019495175, 2.00781920319898, 1.86605950542965, 1.7254894436713821, 1.588438594732772, 1.4570985684856204, 1.3334767646436192, 1.219354856529326, 1.116252944481138, 1.0254001802756534, 0.9477125037437009, 0.8837779576126379, 0.8338498608459511, 0.7978479289592801, 0.7753672366950924, 0.7656947287838265, 0.7678328029604513, 0.7805293203851512, 0.8023132462591108, 0.8315349914340591, 0.8664104173783456, 0.905067384583491, 0.9455936703204542, 0.9860850568299093, 1.024692396070723, 1.0596664918277774, 1.0893997033308338, 1.1124632648860966, 1.1276394310291682, 1.1339476934211712, 1.1306644706432876, 1.1173358412665424, 1.0937830698021571, 1.0601008598516877, 1.0166484543248822, 0.9640338843150148, 0.9030918415586476, 0.8348558100197693, 0.7605252360139046, 0.6814286398387919, 0.5989836720329753, 0.5146551916620757, 0.4299124906077193, 0.3461868055777526, 0.2648302480660041, 0.18707724209881774, 0.1140094913739581, 0.0465254030853258, -0.014685222250286399, -0.06916056428027703, -0.11667970469085, -0.15726875146668673, -0.19119999733233645, -0.21898412633208472, -0.2413556644015796, -0.25925204679841723, -0.2737868428926565, -0.28621783280866503, -0.29791076683454826, -0.31029975389249564, -0.3248453167373631, -0.34299121656819254, -0.36612118670545724, -0.39551672291686785, -0.4323170566069083, -0.4774823868966704, -0.5317613698127225, -0.5956637592743234, -0.6694389678636017, -0.7530611686161622, -0.8462213959206211, -0.948326928124037, -1.0585080509820832, -1.1756321142525092, -1.2983246081868092, -1.4249968070836054, -1.5538793579463466, -1.6830610379028006, -1.8105317683030764, -1.9342288597682937, -2.0520853738231, -2.1620794254057136, -2.2622832181291166, -2.3509106015711514, -2.4263619672662573, -2.487265356879427, -2.532512740955836, -2.561290537649833, -2.57310357528638, -2.5677918572529745, -2.5455396588105836, -2.5068766687841744, -2.4526710802713905, -2.384114728815133, -2.3027005691590468, -2.2101929680131316, -2.1085914656173457, -2.0000888189824595, -1.8870242805584876, -1.77183318424478, -1.6569940031812243, -1.544974108338648, -1.438175491936491, -1.3388817242556892, -1.2492073863326085, -1.1710511649117894, -1.1060537112356235, -1.0555612537954513, -1.0205958197520864, -1.0018327636351405, -0.9995861289362455, -1.013802182523997, -1.0440612679407695, -1.0895879263072004, -1.1492690375565893, -1.2216795448127815, -1.3051151455244565, -1.3976311688251406, -1.4970867134791512, -1.6011929982085935, -1.707564779129132, -1.8137736197794996, -1.9174017594544044, -2.0160953161613206, -2.1076155816911615, -2.1898872174436255, -2.2610422394687615, -2.319458787662626, -2.3637938045219515, -2.3930089000702974, -2.406388847761897, -2.403552337183796, -2.3844547987390396, -2.349383308533599, -2.2989437736565512, -2.2340407842214094, -2.1558506943647853, -2.065788655579711, -1.9654704683695081, -1.8566702387865417, -1.7412749220637542, -1.621236903974786, -1.498525810169352, -1.3750807436419248, -1.2527641305588328, -1.1333183054903715, -1.0183258899922727, -0.9091749154708709, -0.8070295150021892, -0.7128068624868816, -0.627160874930059, -0.5504730188575802, -0.4828503793338855, -0.4241309643306361, -0.37389603298169183, -0.3314890581721945, -0.29604076641015364, -0.2664995452078013, -0.241666374068811, -0.22023332297624248, -0.20082457478936921, -0.18203886734538063, -0.16249221880663076, -0.1408597966633444, -0.11591581683004794, -0.08657041376260925, -0.05190250405697316, -0.01118777247617031, 0.03607896193240765, 0.09016759430222326, 0.1511032288091141, 0.2186635778284943, 0.2923833427341757, 0.37156547107598187, 0.45529900484576336, 0.5424830616674476, 0.6318563294207964, 0.7220313091361404, 0.8115324146921667, 0.8988369341402096, 0.9824177790289378, 1.060786896942332, 1.1325381999367303, 1.196388868295393, 1.2512179249028086, 1.2961010397341712, 1.3303406149034396, 1.3534903161874232, 1.3653733540949746, 1.3660939729823152, 1.3560417765658952, 1.3358886982221716, 1.3065786101948627, 1.2693097526090757, 1.2255103463356358, 1.1768079286572393, 1.1249931129549262, 1.0719786191589709, 1.0197545468012457, 0.9703409639749022, 0.9257389607431504, 0.8878813625777604, 0.8585843169838386, 0.8395009540427782, 0.8320782793861801, 0.8375183870457235, 0.8567449813701155, 0.8903760741007214, 0.9387035777118389, 1.0016803527577258, 1.0789150891955503, 1.1696752138044868, 1.2728978224866612, 1.3872084421501225, 1.5109472367992767, 1.6422020910654678, 1.7788478361658082, 1.91859073233095, 2.0590171918228695, 2.1976456209910578, 2.3319801810176126, 2.4595652170498647, 2.578039085578975, 2.685186120722607, 2.7789855212874657, 2.8576560111534346, 2.9196952239457845, 2.963912886772831], [2.9842963167202425, 2.9979056039677654, 2.992211330831814, 2.9673191281297484, 2.923701894381476, 2.8621887944884454, 2.7839462685945615, 2.6904515058636016, 2.5834590159645425, 2.464961093685994, 2.3371431153621147, 2.2023347262201844, 2.0629580724513303, 1.92147429849054, 1.7803295670880157, 1.641901866406009, 1.5084498444756298, 1.3820648575379775, 1.264627336447908, 1.1577684665090442, 1.062838043554674, 0.9808792160888078, 0.9126106536498185, 0.8584164994532663, 0.8183442753070068, 0.792110713453914, 0.7791152981404316, 0.7784611140414429, 0.7889824237398118, 0.8092782365340149, 0.8377509898212386, 0.8726493455921586, 0.912114011033754, 0.9542254260951418, 0.9970521236714605, 1.0386985606252042, 1.077351240274725, 1.1113219985772889, 1.1390874056362783, 1.1593233392981406, 1.1709339157680017, 1.1730741100895559, 1.1651655632460534, 1.1469052483948496, 1.1182668519116363, 1.0794949108792105, 1.0310919327362829, 0.9737989003868788, 0.9085697327141707, 0.8365404219797036, 0.7589937022412879, 0.6773202133912783, 0.5929772109639989, 0.5074459303788846, 0.42218874434806847, 0.33860725307429335, 0.2580024186215803, 0.18153779821451704, 0.11020684768309368, 0.04480515796583538, -0.014091642716364086, -0.0661437373781172, -0.11125629970030258, -0.14958175917294758, -0.18151508761295662, -0.2076822252760232, -0.22892194439657365, -0.24626162009969854, -0.2608875388602014, -0.27411051895858396, -0.2873277420243783, -0.3019817965777463, -0.3195180108671038, -0.34134120127780143, -0.3687729828666913, -0.403010779592427, -0.4450896337296712, -0.4958478476769979, -0.5558973985031669, -0.6255999484049926, -0.7050491356667845, -0.7940596741531747, -0.8921636187279713, -0.9986139735260725, -1.1123956342218493, -1.2322434689873318, -1.3566671603940252, -1.483982256670644, -1.6123467198675503, -1.7398021146651896, -1.8643184584499521, -1.9838416540106028, -2.096342353338755, -2.1998650564536026, -2.2925762341206712, -2.372810278271481, -2.4391121285883037, -2.4902754970883643, -2.5253757129048826, -2.5437963344245538, -2.5452488224947944, -2.5297847330110588, -2.49780006583267, -2.4500315952976783, -2.387545201008562, -2.3117164113012523, -2.224203561134168, -2.126914146384325, -2.021965123274037, -1.9116380507575368, -1.798330101483638, -1.684502070248523, -1.5726245850879392, -1.4651237734203393, -1.3643276527374242, -1.2724145017841124, -1.191364424262136, -1.122915243863086, -1.0685237686387177, -1.0293333367767403, -1.0061484078145349, -0.9994167967791868, -1.0092199677322438, -1.035271612118939, -1.0769245408189694, -1.1331857216462693, -1.202739101041078, -1.2839756645289522, -1.3750300196601895, -1.4738226317334133, -1.5781067103637365, -1.6855186370724238, -1.7936307431459872, -1.9000051949701973, -2.002247722110989, -2.098059932072401, -2.1852889946440097, -2.261973547045526, -2.3263847669562807, -2.377061681577356, -2.4128399240977485, -2.432873310764679, -2.4366477881837456, -2.4239874871364013, -2.3950528114963574, -2.350330684018967, -2.2906172601219144, -2.2169936016299068, -2.1307949703978943, -2.033574552662396, -1.927062555233648, -1.8131217210866761, -1.6937003919873934, -1.5707842976096595, -1.446348272974371, -1.3223090985189032, -1.2004806199732385, -1.082532239503231, -0.9699517770127315, -0.8640135834716748, -0.7657526496560636, -0.6759452972757731, -0.5950968690939966, -0.5234366546145114, -0.46092010276934225, -0.4072381874365852, -0.3618336102165368, -0.32392335223992375, -0.29252692719328294, -0.26649954520780117, -0.24456927531879005, -0.22537719589124902, -0.20751945015291584, -0.1895900795523402, -0.1702234921370955, -0.14813543686970224, -0.12216139737391653, -0.09129138891418484, -0.05470023864143547, -0.01177254882320139, 0.03787831713960982, 0.09439772919061741, 0.15768409911348846, 0.22739015828038744, 0.30293117759924126, 0.3834999209425846, 0.46808794691736283, 0.5555127071336898, 0.6444497363908133, 0.7334690953100397, 0.8210751123497046, 0.9057483827456588, 0.9859889190339326, 1.0603593130673499, 1.1275267637656925, 1.1863028484396867, 1.2356799678669241, 1.2748634751142804, 1.3032986034448917, 1.3206914369230778, 1.3270233153619564, 1.3225582293693106, 1.3078429373502762, 1.2836997200257398, 1.2512118747283851, 1.2117022367653563, 1.166705193840862, 1.1179328274145712, 1.067235967694591, 1.0165610828547247, 0.9679040346163775, 0.9232618186863801, 0.8845834674544107, 0.853721322266976, 0.8323838826650837, 0.822091410096317, 0.8241354044277397, 0.8395429844618113, 0.8690470906565266, 0.913063292082105, 0.9716738235978242, 1.0446193070910046, 1.1312984265780188, 1.2307756355195973, 1.341796780536241, 1.4628123335869543, 1.5920077393166554, 1.7273402102478221, 1.8665811440816478, 2.0073631984976705, 2.1472309429388092, 2.283693916821412, 2.4142808616665725, 2.5365938623713906, 2.648361131063745, 2.7474871957986813, 2.832099315098483, 2.90058902661491, 2.951647851905384, 2.9842963167202425], [2.99635215442904, 2.997905603967766, 2.980172153747235, 2.9434897633724315, 2.8885580295905355, 2.8164222858572345, 2.7284499593737532, 2.626299747926154, 2.511884348347421, 2.3873276201105864, 2.2549171977741467, 2.1170536715939607, 1.9761975340485816, 1.8348151394248602, 1.6953249428179877, 1.5600452734963806, 1.4311448558993707, 1.3105972206487173, 1.200140049653217, 1.1012403761283955, 1.0150664152090938, 0.9424666374028386, 0.8839565194605942, 0.8397132197162639, 0.8095782321888871, 0.7930678804935547, 0.7893913236129769, 0.7974755654713991, 0.8159967934271701, 0.8434172213236918, 0.8780264842372643, 0.9179865276346761, 0.9613788558010049, 1.0062529549536403, 1.0506746865482608, 1.0927734562989009, 1.1307870040255106, 1.1631027275242105, 1.1882945484375251, 1.2051544471344522, 1.2127179338454948, 1.2102828811666835, 1.1974213145487032, 1.173983938190143, 1.1400973593028563, 1.0961541593478865, 1.0427961418954592, 0.9808912587084364, 0.9115048741881104, 0.83586616950038, 0.7553306080070722, 0.6713394800783955, 0.5853776155781218, 0.4989303945751886, 0.41344120013018404, 0.3302704410482351, 0.2506572277322512, 0.17568471188745588, 0.10625000268867514, 0.04303945064194774, -0.01349005114903607, -0.06312325665831284, -0.10589192647486506, -0.1420732148769963, -0.17218112451682227, -0.1969512501964608, -0.2173192090303711, -0.23439332003849386, -0.2494222476877256, -0.2637584572376765, -0.2788184415483749, -0.29604076641015364, -0.31684304220933307, -0.34257896226612594, -0.37449655160112044, -0.41369874406270807, -0.46110735127432567, -0.5174314050529638, -0.58314074781367, -0.6584456156526516, -0.743282809512212, -0.8373088847861803, -0.9399006130388031, -1.0501627855971303, -1.1669432422397497, -1.288854823722157, -1.414303769087396, -1.541523912089477, -1.6686158798161617, -1.7935903645724287, -1.9144144306406374, -2.0290597334772262, -2.1355514724220135, -2.232016870586092, -2.316731978030786, -2.388165626694004, -2.445019427061989, -2.486262785896288, -2.511162039289829, -2.5193029331829306, -2.5106058408882754, -2.485333280330231, -2.4440894783784075, -2.3878119213341393, -2.317755024616827, -2.235466246232322, -2.1427551529786557, -2.04165612101214, -1.9343855090984652, -1.8232942797319227, -1.7108171569277384, -1.5994194970500557, -1.4915431083389417, -1.3895522843449766, -1.2956813154961382, -1.2119847114868452, -1.1402913058175848, -1.082163324084114, -1.0388613816716192, -1.0113162371493831, -1.0001079682586562, -1.0054530618062374, -1.0271997212817396, -1.064831501163337, -1.1174791794014622, -1.183940584273076, -1.2627079034272661, -1.3520018260724702, -1.4498117081794013, -1.553940809196028, -1.662055530512021, -1.7717374936210346, -1.8805372318233333, -1.9860282349094414, -2.085860082359252, -2.1778094272233592, -2.259827649318739, -2.330084081232738, -2.3870038217572507, -2.42929928599487, -2.455994796147019, -2.4664436880748797, -2.460337591888732, -2.4377077355513057, -2.398918314079924, -2.344652158642569, -2.275889124963003, -2.1938777944501506, -2.100101240101543, -1.9962377486425928, -1.88411750717911, -1.7656763540521776, -1.6429077574195068, -1.517814219860728, -1.3923593122541276, -1.268421515279133, -1.1477509928820204, -1.0319303403450282, -0.9223402423469059, -0.8201308463540579, -0.7261995071545189, -0.6411753931388098, -0.5654112682216894, -0.49898257954421477, -0.4416937949211744, -0.3930917500793642, -0.35248558867755486, -0.3189727123386873, -0.29147000759693853, -0.268749485511903, -0.24947736098670134, -0.23225551523636648, -0.21566422844275812, -0.1983050417725583, -0.17884260927668538, -0.15604443064905904, -0.1288174145842484, -0.09624030801034626, -0.057591136585808125, -0.01236893372056491, 0.03969081435023592, 0.09860741507161183, 0.1641531400634199, 0.23585837086206768, 0.31302358868383523, 0.39473789780385776, 0.4799036008182329, 0.5672661849383173, 0.6554489356049462, 0.7429912707469956, 0.8283897890855876, 0.9101409515669333, 0.9867842682148212, 1.0569448446589014, 1.1193741538257265, 1.1729879385484525, 1.2169002192002705, 1.2504524752209938, 1.2732371882540419, 1.285115074602364, 1.2862254923705947, 1.2769896800618301, 1.2581066642633034, 1.2305418598636406, 1.1955085723396186, 1.1544427933603707, 1.1089718537096134, 1.0608776569630811, 1.0120553594442372, 0.9644684831048164, 0.9201015450415483, 0.8809113578624843, 0.8487781972072239, 0.825458045259676, 0.81253710165599, 0.8113897061147658, 0.8231407414679581, 0.8486334833273852, 0.8884037358295879, 0.942660944815681, 1.0112768140112602, 1.0937817703084376, 1.1893694354979023, 1.296909068372375, 1.4149657477671318, 1.5418278785690074, 1.6755414236527235, 1.8139500995086748, 1.9547406260906497, 2.0954919957817797, 2.2337276254730836, 2.3669691820888286, 2.4927908273281445, 2.608872613062405, 2.7130517751324987, 2.8033707198759394, 2.8781205734871027, 2.935879267462137, 2.975543261420116, 2.9963521544290397], [2.9999784020568754, 2.9894570240085767, 2.959816892781092, 2.9116254495955616, 2.845803090711617, 2.7636025023919126, 2.6665805661259165, 2.556563499283912, 2.4356060558592945, 2.3059457514196517, 2.169953192450216, 2.0300796801380243, 1.8888033201557497, 1.748574901701353, 1.6117648102059223, 1.4806122087590428, 1.357177664188257, 1.2433003063653976, 1.1405604958866602, 1.0502488386112534, 0.9733422290371104, 0.9104874320153198, 0.861992528117413, 0.8278263566115365, 0.807625896183052, 0.8007113320119246, 0.8061083732872769, 0.8225772122104612, 0.84864735823083, 0.8826574434947951, 0.9227989805995602, 0.9671629644862237, 1.0137881488007712, 1.0607097947221187, 1.1060076878044314, 1.1478522457644305, 1.1845475965817898, 1.2145705902706052, 1.2366048170399895, 1.2495688364839235, 1.252637973561228, 1.2452592036120798, 1.2271588262993223, 1.198342812683507, 1.1590898960048701, 1.1099376604772746, 1.0516620588967096, 0.9852509547189586, 0.91187243335543, 0.8328387570628757, 0.7495669447460471, 0.6635370396102828, 0.5762491818911646, 0.4891806295372109, 0.40374386613645824, 0.32124690270176853, 0.24285681903667736, 0.16956750287651293, 0.10217243308984807, 0.04124321979661464, -0.012885537285185227, -0.06012467675453656, -0.10063197003943121, -0.1348066442612318, -0.1632770775953933, -0.18688198999839226, -0.20664562269446804, -0.22374755780378805, -0.23948797092665197, -0.2552492307724633, -0.2724548579390676, -0.2925269271932825, -0.31684304220933307, -0.3466940275151119, -0.38324346892730665, -0.42749019131193416, -0.4802346921023438, -0.5420504523624975, -0.6132609266813093, -0.6939228718095519, -0.7838165152182175, -0.8824428926227331, -0.9890285022800106, -1.1025372380609857, -1.2216893775888795, -1.3449872207789972, -1.4707468024765127, -1.5971349448973655, -1.7222107752369293, -1.8439707146908484, -1.9603958502817114, -2.06950053275446, -2.169381004183101, -2.258262848906759, -2.334546081335383, -2.396846733642691, -2.4440338842691407, -2.4752611726556553, -2.4899919742212164, -2.488017559182859, -2.4694677257673394, -2.434813578614683, -2.3848623123219768, -2.320744053490013, -2.2438910075688736, -2.1560093445084187, -2.0590444350813293, -1.9551402133709208, -1.8465935862567826, -1.7358049341845059, -1.6252258460017912, -1.5173053017189415, -1.4144355589173148, -1.3188990101066278, -1.2328172592885174, -1.158103616734594, -1.096420132691846, -1.049140185256658, -1.0173175075504552, -1.0016623877290574, -1.0025256059364245, -1.0198904891827216, -1.053373272733774, -1.1022317596198732, -1.1653820730946585, -1.241423105082962, -1.3286680815107743, -1.4251824973344898, -1.5288275241581206, -1.6373078651777624, -1.7482229289182762, -1.8591201173135468, -1.9675489769413252, -2.071114945753477, -2.16753144179647, -2.2546690847981594, -2.330600914967673, -2.3936425740656695, -2.44238653923762, -2.475729647144008, -2.492893310924423, -2.4934360114180874, -2.4772578324177505, -2.4445970029184356, -2.396018602588722, -2.3323957752986497, -2.254883974867817, -2.1648889328709044, -2.0640291863231104, -1.9540941297774044, -1.8369986587452907, -1.7147355469574317, -1.589326747032468, -1.4627748215549803, -1.337015699046597, -1.2138739072612323, -1.095021365790798, -0.981940722980262, -0.8758941011225339, -0.7778979719312006, -0.6887047249811197, -0.6087913191985516, -0.5383552259294045, -0.47731768618738074, -0.4253341190537816, -0.38181133752035123, -0.3459310568569938, -0.3166790231222405, -0.29287894963916783, -0.27323033060702423, -0.2563491064468607, -0.24081008731746065, -0.22519000114900972, -0.2081100214820865, -0.18827664859420462, -0.16451986433518107, -0.13582755554356193, -0.10137530095612855, -0.060550739585335515, -0.012971881482161931, 0.04150111901771971, 0.10276103609774873, 0.17045562064519762, 0.243996570663184, 0.32257518962331394, 0.40518432329031223, 0.4906460007697278, 0.5776440553405934, 0.6647608688606491, 0.7505172735339772, 0.8334145594247, 0.9119774774841447, 0.984797097557633, 1.0505723796647863, 1.108149344886022, 1.1565567887844355, 1.1950375640745006, 1.2230745681595114, 1.2404107025063502, 1.2470622213490032, 1.2433250531646214, 1.229773855607019, 1.2072537486812132, 1.1768648572870508, 1.139939978172804, 1.0980158631955186, 1.052798776124035, 1.006125129862548, 0.9599181411191721, 0.9161415468753009, 0.8767515087694356, 0.8436478855655877, 0.8186260787899513, 0.8033306516686215, 0.7992118867046673, 0.8074863833563847, 0.8291027058055647, 0.8647129739085465, 0.9146511509121545, 0.9789186227662323, 1.0571774897326918, 1.1487518057249382, 1.2526368089423079, 1.3675159935951653, 1.491785681607226, 1.6235865698307923, 1.7608415570385751, 1.901298999993457, 2.0425804130823972, 2.1822315146795166, 2.317775438351257, 2.4467668703666576, 2.566845848166665, 2.6757899581855544, 2.7715637056635645, 2.852363893053103, 2.9166599357825, 2.9632281622885324, 2.9911792865126894, 2.9999784020568754], [2.9951443799079214, 2.9726313428996796, 2.9313177626520197, 2.8719957733124595, 2.7957988038744697, 2.704176323361824, 2.598861531914154, 2.4818327601564074, 2.3552694873709394, 2.2215040150480365, 2.0829699333220186, 1.9421485911762781, 1.8015148253687079, 1.663483216755312, 1.5303561257851146, 1.4042747118655516, 1.2871740652547055, 1.1807434770350613, 1.0863927451331623, 1.0052252654389504, 0.9380184905341518, 0.8852121584745876, 0.846904504925857, 0.8228564783798187, 0.8125037849355533, 0.8149764009504764, 0.8291250133585346, 0.8535536829685898, 0.886657879598001, 0.9266669130113513, 0.971689683329109, 1.0197626012384455, 1.0688984836987956, 1.1171352158941301, 1.1625829852108718, 1.2034689375394738, 1.2381781790035864, 1.2652901454081598, 1.283609484710645, 1.29219074151491, 1.290356293315179, 1.2777071619108846, 1.2541265056921207, 1.219775784774209, 1.1750837765629558, 1.1207287996107138, 1.057614674070329, 0.9868411034174118, 0.9096693004992513, 0.8274837979463318, 0.7417514756574893, 0.6539789041639456, 0.5656691405827827, 0.4782791226889925, 0.39317878620057234, 0.31161298125250325, 0.23466718752214855, 0.1632379255379903, 0.09800863697053977, 0.03943166235559145, -0.012283215585645432, -0.05717336700964745, -0.09552093200560263, -0.1278435258012246, -0.15487827911475358, -0.17755963517948542, -0.19699148875912056, -0.21441440136134898, -0.23116875705369122, -0.24865483146930956, -0.26829082999334614, -0.2914700075969383, -0.3195180108671037, -0.35365158171066413, -0.3949397319666455, -0.4442684394556736, -0.5023098302551003, -0.5694967013251101, -0.6460031047633255, -0.7317315632349617, -0.8263073192928109, -0.929079843533161, -1.039131642277986, -1.1552942193500844, -1.2761708631912676, -1.4001657546785482, -1.525518726958135, -1.6503448605924709, -1.7726779690626258, -1.8905169244610678, -2.0018736937561807, -2.104821904380744, -2.197544735475281, -2.27838093856257, -2.345867828659531, -2.398780153024509, -2.43616383834775, -2.45736373599277, -2.4620446260290927, -2.4502049008451725, -2.4221825242011263, -2.378653047401354, -2.320619656288822, -2.2493954162758163, -2.166578072872778, -2.074017947472785, -1.973779637995133, -1.8680983871882206, -1.7593321141425282, -1.6499102135680115, -1.54228030992674, -1.4388542075047914, -1.34195430158273, -1.2537617093763314, -1.176267342476398, -1.1112270759704366, -1.0601220748614952, -1.0241252180783391, -1.0040744171990084, -1.000453464450276, -1.0133808665390924, -1.0426069317400246, -1.0875191819993946, -1.1471559643781957, -1.2202279417416, -1.3051469559387294, -1.4000615823376943, -1.5028985367214915, -1.6114089580380913, -1.7232184766609875, -1.8358798904007931, -1.94692721161242, -2.053929819762988, -2.154545455426388, -2.2465708237650923, -2.327988637314315, -2.397010017738157, -2.4521112919344072, -2.4920643565465292, -2.515959943159463, -2.5232232902981764, -2.513621913524652, -2.487265356879429, -2.444597002918436, -2.3863782098941018, -2.3136652285363786, -2.227779522911104, -2.130272275778738, -2.0228839949603517, -1.9075002501526421, -1.7861046567114698, -1.6607302820814382, -1.5334106804198346, -1.406131760907703, -1.2807856653627945, -1.159127771912107, -1.0427378552051998, -0.9329863221923981, -0.8310063087114923, -0.7376722694313138, -0.6535855259596414, -0.5790670593744989, -0.5141576485779336, -0.4586252693452877, -0.41197948542784224, -0.3734923871542405, -0.34222546906001516, -0.3170616902392608, -0.2967418330327397, -0.2799041705160547, -0.265126373623174, -0.25096853658373613, -0.2360161759241145, -0.21892206411577825, -0.1984457938480741, -0.17349003192390497, -0.1431325112872164, -0.10665292338759957, -0.06355400805940555, -0.013576290897092369, 0.043293915145402075, 0.10682345075561135, 0.17653821902119374, 0.2517359048308416, 0.33150516955158055, 0.41475081591526947, 0.5002242612072665, 0.5865585168608751, 0.6723067529888792, 0.7559834302818508, 0.836106911536238, 0.911242422656996, 0.9800442194253329, 1.0412958320224286, 1.0939473039094931, 1.1371484141098214, 1.1702769704449456, 1.1929613834122221, 1.2050968731253962, 1.206854821520637, 1.198684954872396, 1.181310223245169, 1.1557144292810437, 1.1231228440268974, 1.0849762276796764, 1.0428988436334719, 0.9986612107391081, 0.954138477268052, 0.9112654171787866, 0.8719891419148756, 0.838220686723023, 0.8117866676332416, 0.794382212768392, 0.7875263492563521, 0.7925209751593337, 0.8104144656979838, 0.8419708565244438, 0.8876454164389237, 0.947567270895533, 1.021529569571511, 1.1089875102752227, 1.2090643419666496, 1.3205652763030737, 1.4419990446505855, 1.5716066506548083, 1.7073966918479921, 1.8471864617470148, 1.9886479004782396, 2.1293573407109703, 2.2668478996109136, 2.3986632990443115, 2.5224118571031906, 2.635819385195551, 2.7367797467206527, 2.8234018852476974, 2.894052210915431, 2.947391341540388, 2.982404327068348, 2.9984236393354355, 2.995144379907921], [2.981890985996979, 2.947570913516965, 2.8949158788969154, 2.824936019517115, 2.7389682279729337, 2.638646521132217, 2.525865790411109, 2.402739786412704, 2.27155432660448, 2.134716826295767, 1.9947033381221546, 1.8540043415106109, 1.715070549851849, 1.580259998745807, 1.4517876438636144, 1.331678632582737, 1.2217263212226839, 1.123455991741131, 1.0380950810752843, 0.9665505764139233, 0.909394054512126, 0.8668546570319878, 0.8388201013895358, 0.8248456324398452, 0.8241706293002738, 0.8357423983709715, 0.8582465126365977, 0.8901429027861579, 0.9297067713179591, 0.9750732898467377, 1.0242849549575221, 1.0753404211628106, 1.1262436021241289, 1.1750518338737648, 1.2199219261509096, 1.259152989244774, 1.291225012295497, 1.3148322825495513, 1.3289108706911432, 1.3326595616242185, 1.3255537790544956, 1.3073522316530226, 1.278096193956421, 1.238101521819832, 1.1879436855102794, 1.128436278828089, 1.0606036255983604, 0.9856482514262561, 0.9049141151204672, 0.8198465975280216, 0.7319503231464287, 0.6427459398903655, 0.5537270035899686, 0.46631810571145754, 0.38183534567953725, 0.30145018403529916, 0.22615762117712815, 0.15674953096033836, 0.0937938419300589, 0.03762010491456834, -0.011688181964548466, -0.054294296839570155, -0.09060205406791659, -0.12124277062999346, -0.14705578671054872, -0.16906305707992192, -0.188438485565967, -0.20647281343798118, -0.22453499038269584, -0.2440310509303194, -0.26636158727187514, -0.2928789496391675, -0.324845316737363, -0.3633927607959584, -0.40948638504120455, -0.46389153692238594, -0.5271460000747088, -0.5995379442550082, -0.6810902684171403, -0.7715518112907939, -0.8703957303062126, -0.9768251678093006, -1.0897861377964166, -1.2079873815299143, -1.3299267610255643, -1.4539235900554486, -1.57815614726657, -1.7007034792102529, -1.8195904859968135, -1.932835191886032, -2.0384970397393127, -2.1347250135690166, -2.2198043883875886, -2.292200931411498, -2.3506014328977187, -2.393949527236606, -2.4214758734475494, -2.4327218963204813, -2.427556441925484, -2.406184870369831, -2.3691502903916843, -2.317326830197239, -2.251905032219119, -2.174369651448008, -2.0864703229405688, -1.9901857394458722, -1.8876821404861759, -1.7812670557004209, -1.673339364296055, -1.5663368260866593, -1.4626823054710623, -1.3647299461641809, -1.2747125605703804, -1.1946914731932285, -1.126510002945138, -1.0717516859411143, -1.0317042303208364, -1.0073300604908877, -0.9992441531542162, -1.0076996953510213, -1.0325819096498976, -1.0734101980948039, -1.1293485592350145, -1.1992240363376137, -1.2815527644754932, -1.3745730042267659, -1.4762843845851035, -1.5844924313733515, -1.6968573335201627, -1.8109458009975608, -1.924284797400201, -2.0344158887667234, -2.1389489392702723, -2.2356139040636043, -2.3223095193279355, -2.397147768180064, -2.4584931065702884, -2.5049955630283858, -2.535616976870079, -2.54964980753253, -2.5467281289183035, -2.526830612528528, -2.490275497088365, -2.4377077355513075, -2.3700786980805875, -2.2886189872570335, -2.194805085021324, -2.090320695756866, -1.9770137729506077, -1.8568503150739033, -1.7318660873646523, -1.6041174684027089, -1.4756326328074592, -1.34836426384325, -1.2241449427320656, -1.1046462863097186, -0.991342803283338, -0.8854813143642208, -0.788056636149536, -0.6997940664998845, -0.6211390344054236, -0.5522540943551433, -0.4930232586211985, -0.443063475322834, -0.4017428802868718, -0.3682052810654972, -0.3414001762361788, -0.320117476152779, -0.3030259760361692, -0.288714541533417, -0.2757349028635702, -0.262644917957649, -0.24805115843057512, -0.23064969490044743, -0.2092640094678552, -0.1828790417383829, -0.15067047858409036, -0.1120285242308377, -0.0665755329977331, -0.014177048388207531, 0.04505403486679333, 0.11076028917893065, 0.18234947365674029, 0.2590108950958933, 0.3397379767975799, 0.4233564388222353, 0.5085573457133352, 0.5939341491208608, 0.6780227463953608, 0.7593434948310652, 0.8364440669030351, 0.9079420059819412, 0.9725658453176231, 1.0291936855225694, 1.0768881865892983, 1.1149270181567479, 1.1428279241380093, 1.1603676921484603, 1.1675944710874333, 1.1648330479138693, 1.1526828729253458, 1.1320088072361052, 1.1039247520267292, 1.0697705018338997, 1.0310823390607888, 0.9895580496004613, 0.9470171858555174, 0.9053575297847705, 0.8665088116832248, 0.8323848175486961, 0.8048350670922182, 0.7855972643865178, 0.776251713219563, 0.7781788495728041, 0.7925209751593337, 0.8201491802379802, 0.8616363232466093, 0.9172367920776595, 0.986873610509949, 1.0701332773398717, 1.1662685394207617, 1.2742091076852324, 1.3925801320083442, 1.519728061222742, 1.6537533333923349, 1.792549173063828, 1.9338456208126946, 2.0752577897390925, 2.2143372369016228, 2.3486252576701014, 2.475706859648609, 2.59326415148089, 2.6991278910806566, 2.7913259774585, 2.8681277394285734, 2.928082971429628, 2.970054789161938, 2.9932455227702333, 2.997215029385369, 2.9818909859969795], [2.9603303500337637, 2.9144877584329816, 2.850919217924384, 2.7708443350214145, 2.675792175395262, 2.5675675074825226, 2.4482109186208416, 2.3199537404006474, 2.185168841701535, 2.046318444051331, 1.9059001821870967, 1.7663926713789146, 1.6302018512925194, 1.4996093537561344, 1.3767240893511155, 1.2634381665914263, 1.16138814962214, 1.071922528532072, 0.9960761238058943, 0.9345519769058169, 0.887711096652482, 0.8555702404565872, 0.8378077152206006, 0.8337769896481658, 0.8425277224945821, 0.8628336345385138, 0.8932264900599476, 0.9320353103067008, 0.9774298202869109, 1.0274670341487953, 1.0801398156871997, 1.1334262107535087, 1.185338338425936, 1.233969647865351, 1.2775393972380298, 1.3144332886055878, 1.34323929624391, 1.3627778527964938, 1.3721257047569821, 1.3706329122813803, 1.3579326441227817, 1.3339436021339326, 1.2988650966831017, 1.2531649797924809, 1.1975608221979719, 1.1329948893675483, 1.0606036255983604, 0.9816824908131087, 0.8976471082391274, 0.8099917699793557, 0.7202464093981795, 0.6299331827502709, 0.5405238067955593, 0.453398774220657, 0.3698095152131255, 0.2908444929133314, 0.2174001147835178, 0.15015721389771514, 0.0895637070416644, 0.0358238740692353, -0.01110547067558455, -0.05151182448073742, -0.08591695215954319, -0.11506022412316219, -0.1398757822082354, -0.1614641405951695, -0.1810589753922982, -0.19998998346112587, -0.21964279558151545, -0.24141700843113686, -0.2666834520410705, -0.29674183303273927, -0.33277988840181544, -0.3758351499880009, -0.42676035688353753, -0.4861934634279527, -0.5545330763260005, -0.631920018643192, -0.7182255643611222, -0.8130467186596312, -0.9157087403510226, -1.0252749184027738, -1.1405634288818, -1.2601709166045065, -1.382502271871279, -1.5058059112967164, -1.6282137270073078, -1.747784744049671, -1.862551424918083, -1.9705674852740978, -2.0699560381518376, -2.1589568664842385, -2.2359716361837774, -2.2996059040604226, -2.348706845616111, -2.3823957255590313, -2.4000942563979732, -2.401544134752977, -2.386819207553983, -2.356329897133947, -2.3108197010343936, -2.251353774550315, -2.179299796926209, -2.096301510926578, -2.0042455055858452, -1.9052219788420952, -1.8014803663429464, -1.6953808512635207, -1.5893428742932276, -1.4857918404159172, -1.3871052677709617, -1.2955596424896512, -1.213279231436466, -1.1421880624850067, -1.0839662103026175, -1.040011426309093, -1.011407026893904, -0.9988968071273888, -1.0028675816356172, -1.0233397740389165, -1.059966285755555, -1.112039678675061, -1.1785075089812118, -1.2579954560482802, -1.3488377055462204, -1.4491138741629195, -1.556691608854777, -1.6692738600196686, -1.7844497186819386, -1.8997476253265273, -2.0126897043996093, -2.120845954978666, -2.22188703524057, -2.3136344159057645, -2.3941067448483873, -2.461561359853429, -2.514530006711133, -2.5518479624837442, -2.572675925332553, -2.5765142087657797, -2.563208965214018, -2.5329503568591374, -2.4862627858962885, -2.423987487136404, -2.3472579683937336, -2.257468953995388, -2.1562396398641224, -2.0453722012505713, -1.9268066031285924, -1.802572845911303, -1.674741833544737, -1.545376075942556, -1.4164814326230066, -1.2899610695268682, -1.1675727372980769, -1.0508903884754177, -0.9412710354209902, -0.8398276133582178, -0.7474084571014883, -0.6645838298737952, -0.591639762319215, -0.5285792739575494, -0.47513086256165393, -0.4307639639392394, -0.3947109099424779, -0.36599475056407493, -0.3434621607362238, -0.3258205275312082, -0.31167821195604145, -0.29958690393356596, -0.28808494121026323, -0.2757404439691551, -0.26119312727049515, -0.24319369277284233, -0.22063976845410785, -0.19260745850701042, -0.1583776828198831, -0.11745662347022201, -0.06958975093208475, -0.01476907127528672, 0.046766586772587236, 0.11453824393320622, 0.1878402187079987, 0.26575999174872633, 0.34720395808662313, 0.4309283845473294, 0.5155747526222486, 0.5997085509341196, 0.6818604891893592, 0.7605690395150885, 0.8344231730381239, 0.9021041504775066, 0.9624252456634562, 1.014368329800879, 1.0571163207773047, 1.0900806039902713, 1.1129226565062784, 1.1255692517451252, 1.1282207836837326, 1.1213524237484764, 1.1057080057529152, 1.0822867198684099, 1.052322881022929, 1.0172592156652125, 0.9787142790011113, 0.9384447683509909, 0.8983036332929655, 0.8601949963020348, 0.8260269857675744, 0.7976636442820548, 0.7768771073262575, 0.7653012500277195, 0.7643879723737919, 0.7753672366950923, 0.7992118867046673, 0.8366081668863571, 0.8879327272248663, 0.9532367443966046, 1.0322376203359485, 1.1243185367101647, 1.2285359537427762, 1.343634948684374, 1.4680720977917705, 1.6000454206586527, 1.7375307317120612, 1.8783235849552906, 2.0200858585362016, 2.160395908921447, 2.2968011332787537, 2.4268717154032347, 2.5482542967788286, 2.658724311028304, 2.7562357472147787, 2.8389671646046013, 2.9053628672411413, 2.95416825896265, 2.984458535624949, 2.9956600279728542, 2.9875636820495703, 2.960330350033764], [2.9306448847548214, 2.8736617761100383, 2.799700011394969, 2.7101783599529568, 2.6068051441337503, 2.4915406430318376, 2.366553911897928, 2.2341750295306113, 2.0968438929542623, 1.9570567586292407, 1.8173117803999428, 1.6800548151552372, 1.5476267572840556, 1.4222136227377395, 1.3058005338854395, 1.2001306591130698, 1.1066700386881494, 1.0265790838257907, 0.9606913727172874, 0.9095001895460015, 0.8731530645903639, 0.8514543800188717, 0.8438759116641503, 0.849574986681314, 0.8674197552033751, 0.8960209053362019, 0.933768999190963, 0.9788764768060647, 1.029423267915654, 1.0834048711322892, 1.1387817081217566, 1.1935285379464826, 1.2456827243944297, 1.2933901865019053, 1.3349479285946324, 1.3688421392747017, 1.39378096646989, 1.4087212149290802, 1.4128883698570283, 1.4057895217566985, 1.3872189486699555, 1.3572562983266128, 1.3162574995570593, 1.264838715021414, 1.2038538212978511, 1.1343660633211325, 1.057614674070329, 0.9749773737072839, 0.8879297620218056, 0.7980026916007561, 0.7067387548191326, 0.6156490344669053, 0.5261712552189499, 0.43963043160706716, 0.357203038768833, 0.2798856368326215, 0.2084687608082242, 0.14351674833552783, 0.08535402116066995, 0.03405816674534758, -0.010540011719938182, -0.048849490908388075, -0.08150526436266006, -0.1093481934218129, -0.13339901169489246, -0.1548271759972381, -0.17491539223345012, -0.19502075910590128, -0.21653356283191164, -0.24083481995417305, -0.2692537011793396, -0.30302597603616965, -0.34325459579374545, -0.3908734810439821, -0.4466155018752969, -0.5109855345824007, -0.5842393519510958, -0.6663689574872822, -0.7570948111876723, -0.8558652196484738, -0.9618629808578909, -1.0740191884997976, -1.1910339166745678, -1.3114033282538105, -1.4334525831159661, -1.5553737704876311, -1.6752679564044275, -1.7911903263056679, -1.9011973168431129, -2.0033945723491438, -2.095984531631826, -2.177312450685708, -2.245909696631729, -2.3005332070899454, -2.3402000958804208, -2.36421649838213, -2.3721998853545507, -2.3640942292612164, -2.3401775783511796, -2.301061776770728, -2.247684259310108, -2.181292042364502, -2.103418223554912, -2.0158514865065724, -1.9205992799705804, -1.819845497522702, -1.7159036215814434, -1.6111664100310066, -1.5080532924483148, -1.4089567035815829, -1.31618861276438, -1.2319285085502096, -1.1581740679443577, -1.0966956798643228, -1.0489959042858794, -1.0162748340334908, -0.9994021881062797, -0.9988968071273884, -1.01491404679864, -1.0472413783710448, -1.0953023106426403, -1.1581685505950476, -1.2345801242784542, -1.3229729907050718, -1.4215135039055409, -1.5281389162574042, -1.6406029736447096, -1.7565255334100622, -1.8734450423089448, -1.9888726460307804, -2.1003466658821264, -2.205486172778044, -2.302042413852056, -2.3879469021179993, -2.46135506330993, -2.5206844442013705, -2.5646466206285132, -2.5922720978001377, -2.6029276664605914, -2.5963258618684972, -2.5725263638525955, -2.5319293707102277, -2.4752611726556553, -2.4035523371837995, -2.3181090945331904, -2.2204786721283853, -2.112409468556591, -1.9958070768628013, -1.8726872608700043, -1.7451270546147912, -1.6152151922880595, -1.4850030834619763, -1.3564575257862608, -1.231416295410221, -1.111547675518015, -0.9983148776297031, -0.8929461814320055, -0.796411470143435, -0.7094056735556056, -0.632339454087716, -0.5653372868914386, -0.5082428978752604, -0.4606318381663651, -0.4218307946264022, -0.3909430680457777, -0.36687949773829215, -0.348393977238221, -0.33412259397922733, -0.32262533896129314, -0.3124292726107962, -0.3020720017503842, -0.29014432054240413, -0.2753308954406802, -0.2564479298347387, -0.23247682673821882, -0.20259297542176619, -0.16618891755921014, -0.12289129692994441, -0.07257116021478671, -0.015347350776811836, 0.048417081898722195, 0.11812535181167283, 0.19296399998724476, 0.2719260943776566, 0.3538399478386099, 0.43740259100337264, 0.5212171114961448, 0.6038328682483645, 0.6837875123302383, 0.7596496956713276, 0.8300613276180658, 0.8937782470429194, 0.9497082145245797, 0.9969451940753128, 1.0347989854051534, 1.0628193835173696, 1.0808141796462054, 1.0888604727545028, 1.0873089301265262, 1.0767808147801041, 1.0581577819877528, 1.0325646325007143, 1.0013453914484487, 0.9660332547634507, 0.9283151049855662, 0.8899914413734543, 0.8529326917492654, 0.8190329722893896, 0.7901624339973166, 0.7681193789522991, 0.7545833444158835, 0.7510703380223754, 0.7588913628470377, 0.7791152981404318, 0.81253710165599, 0.8596521751682934, 0.9206375889823005, 0.995340697508978, 1.0832755003229562, 1.183626915869008, 1.2952629427397755, 1.4167544909336716, 1.5464024774623208, 1.6822716017534705, 1.8222300509144973, 1.963994237184413, 2.105177543482243, 2.243341951011582, 2.3760513479636733, 2.5009252723709645, 2.6156918262887587, 2.7182385131745983, 2.806659795293421, 2.879300242157819, 2.93479224265502, 2.9720873801782397, 2.99048071871657, 2.989627414869619, 2.969551252093782, 2.9306448847548205], [2.8930857426292427, 2.8254383728325587, 2.741691596972871, 2.643451355912495, 2.5325907956898663, 2.411209149455972, 2.2815856254694697, 2.1461293805118755, 2.0073267493965683, 1.8676869642795504, 1.729687630726531, 1.595721230171566, 1.4680438904874349, 1.3487276085970061, 1.2396170228391088, 1.142291720307915, 1.0580349283994464, 0.9878092836826505, 0.9322401988154588, 0.8916071637916076, 0.8658431258646028, 0.8545418977605923, 0.856973351032383, 0.8721059653357117, 0.8986361295661602, 0.9350234314356721, 0.9795310320566959, 1.0302701048197898, 1.0852472261099397, 1.142413541384173, 1.1997144953154233, 1.2551389098570669, 1.3067662192181642, 1.352810725138455, 1.391661818067777, 1.4219192177551634, 1.4424224175729525, 1.4522736673140555, 1.450853995399215, 1.437831949225456, 1.413164917307341, 1.377093084272153, 1.3301262549798263, 1.273023962424168, 1.2067694411899175, 1.132538199936731, 1.0516620588967096, 0.9655896284335969, 0.8758442896146522, 0.783980795420427, 0.6915416402793135, 0.6000143453983985, 0.5107907779410841, 0.4251295642794466, 0.3441225728418759, 0.26866633267455275, 0.19943912254736215, 0.13688431561727904, 0.08120040013453336, 0.03233792162585716, -0.009996589136247295, -0.04632982066926418, -0.07740431555234088, -0.10415500489040297, -0.12768027157983616, -0.14920831500988693, -0.170059713582951, -0.19160718225895226, -0.21523359764989025, -0.24228941107738636, -0.2740505892159212, -0.3116782119560416, -0.3561808181487568, -0.4083805228782424, -0.46888383650529675, -0.5380579982452172, -0.6160134984159636, -0.702593307176327, -0.7973691574800986, -0.8996450503633586, -1.0084679660670868, -1.122645579518312, -1.2407705980098307, -1.3612511670923426, -1.4823466320712058, -1.6022078011097192, -1.7189207353849467, -1.8305529951111077, -1.9352012000387433, -2.031038721100081, -2.11636230734641, -2.18963646962508, -2.2495344892430293, -2.294974995096828, -2.3251531546427597, -2.3395656501940176, -2.3380287593186635, -2.3206890229919352, -2.288026163605719, -2.2408481025875577, -2.1802781196249432, -2.1077343875973886, -2.0249023045527705, -1.9337002217986377, -1.8362393310138296, -1.7347786191529528, -1.6316759241862686, -1.5293362242831947, -1.4301583654076802, -1.3364814756095873, -1.2505323274428255, -1.174374892532414, -1.1098632847125698, -1.0585992114736955, -1.0218949495080765, -1.0007427314258897, -0.9957912803263581, -1.0073300604908868, -1.0352816300969139, -1.079202289959158, -1.1382910255508667, -1.2114065427247682, -1.2970920054281803, -1.3936069009621224, -1.4989652894131442, -1.6109795428948417, -1.727308550838453, -1.8455092629057965, -1.9630903636924328, -2.07756682510563, -2.1865140642883816, -2.28762044762212, -2.378736924330935, -2.4579226454401697, -2.523485523508168, -2.5740168131767907, -2.608418939090661, -2.625925962500659, -2.626116256835176, -2.608917151290555, -2.574601495425381, -2.52377629208662, -2.4573637359927702, -2.3765751763091036, -2.2828786891618327, -2.1779610961789224, -2.06368539418138, -1.942044665974352, -1.8151136202996325, -1.6849989585732665, -1.5537897859157772, -1.4235092737964452, -1.2960687417101884, -1.173225256774161, -1.0565437547661813, -0.9473645663850199, -0.8467770914483874, -0.7556002049374987, -0.6743698062571425, -0.6033337411515437, -0.5424541389662249, -0.49141702105225166, -0.4496488537425996, -0.41633954603901574, -0.39047123224418584, -0.3708520372267023, -0.3561539003428911, -0.344953436257956, -0.33577473940382574, -0.3271329953148602, -0.31757774762254326, -0.3057346843637546, -0.2903448510249974, -0.2703002692429821, -0.24467503745077177, -0.21275111049105117, -0.17403809622155275, -0.12828656481331782, -0.07549453677420358, -0.01590699438652551, 0.049991556309573554, 0.12149126425849305, 0.19767746798631744, 0.27745703496424995, 0.35958980257741874, 0.4427242834741338, 0.5254366854257537, 0.606272207472842, 0.6837875123302384, 0.7565932413647095, 0.8233954338288733, 0.8830347365887508, 0.9345223437389538, 0.9770716859581716, 1.010124995228802, 1.033373998999093, 1.0467741458012854, 1.0505519280577746, 1.0452050432097333, 1.0314953169895187, 1.0104344980396442, 0.9832632164916507, 0.9514235759326769, 0.9165260139378669, 0.8803112168322232, 0.8446080057394624, 0.8112882199204624, 0.782219707096019, 0.7592185867093229, 0.7440019794130573, 0.7381423936833651, 0.7430249283256136, 0.7598083884431414, 0.7893913236129774, 0.8323838826650818, 0.8890862423461904, 0.9594742105893248, 1.0431924329191826, 1.1395554469113658, 1.2475566390913704, 1.365884965890538, 1.4929491100187084, 1.6269085605630633, 1.7657109338073618, 1.907134696432292, 2.0488363172669053, 2.1884007614917476, 2.3233941549599035, 2.4514173882789985, 2.5701594019717104, 2.677448896162915, 2.77130324083912, 2.8499734250526862, 2.911983974031126, 2.9561668798372636, 2.981688731202419, 2.988070388042779, 2.9751987220971716, 2.9433301328261523, 2.893085742629243], [2.8479706909951115, 2.770225540413605, 2.677384752093201, 2.5712278635485184, 2.4537770170338136, 2.327252667540984, 2.1940249294872305, 2.0565616993762394, 1.9173747665699112, 1.7789651699027418, 1.6437690731234678, 1.5141054167182353, 1.3921265579674047, 1.2797730362663653, 1.178733498663948, 1.0904106937706652, 1.0158942937967066, 0.9559411381553922, 0.910963311905918, 0.8810242827372007, 0.8658431258646024, 0.8648066718845363, 0.876989223061584, 0.9011793033365608, 0.935912740930261, 0.9795112338172828, 1.0301254211515514, 1.0857813809990033, 1.1444293989228207, 1.203993804852394, 1.262422658316155, 1.3177360748598865, 1.3680720288903407, 1.4117285391300414, 1.4472012404891996, 1.4732154679453822, 1.4887521208662642, 1.4930667364965382, 1.4857013750118184, 1.4664891012519121, 1.4355510353995844, 1.3932861317852108, 1.3403540270048437, 1.2776514711038502, 1.206283014410551, 1.127526763765693, 1.0427961418954599, 0.9535986795650664, 0.8614929395829679, 0.7680447130250327, 0.6747836402444986, 0.5831613920890459, 0.4945125007594761, 0.41001885613710265, 0.3306787840929729, 0.25728150082909396, 0.1903875948265765, 0.13031602912497364, 0.07713798547667071, 0.03067769276289452, -0.00947980052547137, -0.04397413131375221, -0.07364880161122092, -0.09952459525385214, -0.12276794499219798, -0.14465509573963262, -0.16653302067940232, -0.1897781333250651, -0.21575389832913186, -0.24576847530166435, -0.2810335323074096, -0.32262533896129253, -0.3714491937765452, -0.4282081579948407, -0.4933769605860309, -0.5671818091233911, -0.649586692063546, -0.7402865933202599, -0.8387078640444224, -0.944015813625843, -1.055129396714755, -1.1707426901866127, -1.2893526780573934, -1.409292697847125, -1.528770752958038, -1.6459117660712859, -1.7588027416855831, -1.8655397244760863, -1.964275386266215, -2.0532660495193644, -2.130916960091995, -2.1958246565254482, -2.24681534663195, -2.2829782930696507, -2.3036933258348182, -2.308651738324997, -2.2978699814791783, -2.2716957436312506, -2.2308061878851215, -2.1761983095150237, -2.109171568422247, -2.0313031412935225, -1.9444163201233842, -1.8505427536760732, -1.7518793820570786, -1.650741048017058, -1.5495098785908523, -1.4505826144200735, -1.3563171195019434, -1.2689793297239713, -1.1906918936899267, -1.1233857240710694, -1.068755612828122, -1.0282209706745484, -1.0028926323099436, -0.9935465271027065, -1.000604853467912, -1.0241252180783378, -1.0637980125593027, -1.1189521050287428, -1.188568726499504, -1.2713032375603392, -1.3655142736289139, -1.4692995919764478, -1.58053778491632, -1.6969348848880872, -1.8160747720182266, -1.9354722058897613, -2.052627242848548, -2.1650797696615296, -2.2704628844366663, -2.3665538863795486, -2.451321696413913, -2.5229696194193854, -2.5799724736354697, -2.6211072508049975, -2.6454766284761875, -2.652524829661395, -2.6420455104887868, -2.614181549025822, -2.5694168033802627, -2.508560099722781, -2.432721896320482, -2.343284243500621, -2.2418648174510434, -2.130275944078946, -2.0104796444555895, -1.8845398229091082, -1.754572780469072, -1.6226972686875012, -1.4909853011610992, -1.3614149124020005, -1.235825996834309, -1.115880276137281, -1.003026333101682, -0.8984705174297765, -0.803154376863138, -0.7177390995113588, -0.6425972744973545, -0.5778120925219532, -0.5231839203297578, -0.47824399802023776, -0.4422748303084396, -0.4143366766249463, -0.3932993944820912, -0.3778787595476389, -0.3666762775893635, -0.3582214205407063, -0.3510151634057266, -0.3435736718981712, -0.3344709932002354, -0.32237963390056124, -0.3061079691653111, -0.2846335139379239, -0.257131198209388, -0.2229959212955729, -0.1818588112036336, -0.13359678071266237, -0.07833514752180035, -0.016443267266247952, 0.05147668923916771, 0.12460750413127475, 0.20194074463307715, 0.28230601924836474, 0.36440487593012044, 0.4468484380332181, 0.5281977749062522, 0.6070059306938999, 0.6818604891893596, 0.7514255355817288, 0.8144818881483532, 0.8699645140749367, 0.9169961126451067, 0.9549159443209876, 0.9833031033702505, 1.0019935717126487, 1.0110905490611297, 1.0109677252778801, 1.002265340868896, 0.9858790661799391, 0.9629419144858119, 0.9347995841298007, 0.9029797956247446, 0.8691563468481162, 0.8351087491568551, 0.8026784258507174, 0.7737225488825664, 0.7500666576036421, 0.7334572428539, 0.7255154897776731, 0.7276933530115101, 0.7412330887440564, 0.7671312907106009, 0.8061083732872766, 0.8585843169838385, 0.9246613428926563, 1.0041140166533726, 1.096387103292501, 1.2006013062860856, 1.315566831990261, 1.4398045289223789, 1.5715741649835842, 1.7089092292015662, 1.849657482314422, 1.9915263365445943, 2.1321320228138108, 2.2690514064814207, 2.3998752428969725, 2.5222616234201567, 2.6339883521402663, 2.73300301364477, 2.817469542413776, 2.88581018358518, 2.9367418410633177, 2.969305939685176, 2.9828910802608624, 2.9772479360917616, 2.952496022925423, 2.909122166780873, 2.847970690995112], [2.7956814236040453, 2.708490404399532, 2.6073235417628196, 2.4941189262879284, 2.371030608396663, 2.2403815071146154, 2.1046126270608867, 1.966229769235949, 1.8277489789527401, 1.691642002026312, 1.5602830174666666, 1.4358978815086376, 1.3205170547100704, 1.215933292630034, 1.1236650635245882, 1.044926516462258, 0.9806046637175242, 0.9312442661756775, 0.8970407240798213, 0.8778410823453104, 0.8731530645903639, 0.8821618577567525, 0.9037541844171011, 0.9365490270885394, 0.978934212295679, 1.0291079255419258, 1.085124115049565, 1.1449406548280912, 1.2064690783920626, 1.2676246646426246, 1.3263756576891985, 1.3807904326134774, 1.4290814785199375, 1.4696451571096807, 1.5010963072133399, 1.5222969003569302, 1.5323781060955333, 1.5307552946521699, 1.5171356840946961, 1.4915185253624126, 1.454187906257791, 1.4056984403563875, 1.346854284052661, 1.2786820902430582, 1.2023986563504154, 1.1193741538257265, 1.0310919327362833, 0.9391059759550865, 0.8449971308420801, 0.750329270882798, 0.6566065349780635, 0.5652327581498928, 0.4774741452650867, 0.394426150608593, 0.3169854130583235, 0.24582746212535292, 0.181390757666248, 0.12386745953452014, 0.0732011470533511, 0.029091526443902452, -0.008994018153107092, -0.04180235303976142, -0.07027049588663152, -0.09549613987296993, -0.11870359243776261, -0.1412060404818567, -0.16436515094061527, -0.18954908688587468, -0.21809006289045155, -0.25124257816937545, -0.29014345159543337, -0.3357747394038266, -0.38893054531028093, -0.450188635628584, -0.5198876512045115, -0.5981105665982189, -0.6846748884835409, -0.7791299136618973, -0.8807611867171314, -0.9886021127007273, -1.1014524959830778, -1.2179035971842551, -1.3363691304364114, -1.4551214674289308, -1.572332176706606, -1.6861159100524856, -1.7945765554862192, -1.8958545108384994, -1.988173894753823, -2.0698885043505846, -2.1395253509202976, -2.1958246565254482, -2.237775273975407, -2.2646445985361336, -2.2760021693189936, -2.2717363084581828, -2.2520633132686707, -2.217528896492267, -2.1690017580763152, -2.107659364056884, -2.034966199301275, -1.9526449463821678, -1.862641218115348, -1.7670826319483792, -1.6682331564418142, -1.5684437799942605, -1.4701006467214914, -1.3755718716175007, -1.2871542850850126, -1.207021364623998, -1.1371735886533378, -1.0793923946042219, -1.03519884179659, -1.0058179711303552, -0.9921497208936256, -0.9947471042088354, -1.013802182523997, -1.049140185256656, -1.1002219326863667, -1.1661545221573142, -1.2457100413876094, -1.3373518819598875, -1.4392680455302471, -1.5494106693307343, -1.665540850191138, -1.7852777211486426, -1.9061506347856765, -2.025653235155616, -2.14129815726373, -2.2506710805874772, -2.351482881321252, -2.441618676440654, -2.519182630084183, -2.5825374972216903, -2.630338008533122, -2.66155735067499, -2.675506163964094, -2.6718436608300413, -2.6505806587274434, -2.6120745158872896, -2.557016152558041, -2.4864095294915125, -2.4015441347529753, -2.3039611951142307, -2.1954144753144837, -2.0778266537929966, -1.953242364097774, -1.8237790646606393, -1.6915769442783315, -1.5587490854457642, -1.4273330923844036, -1.2992453456740571, -1.1762389720404258, -1.0598665179846691, -0.9514481921287082, -0.8520463965429441, -0.7624471055811521, -0.6831484759492664, -0.614356888272164, -0.5559904328950287, -0.5076896657515766, -0.468835278514931, -0.43857215543892175, -0.41583913156574626, -0.39940362722720407, -0.38790021545063863, -0.37987208490470287, -0.37381429367661545, -0.3682176700835697, -0.3616122067973433, -0.3526088139815927, -0.3399383453478172, -0.3224868867492619, -0.2993263981835776, -0.26973992425757265, -0.23324073210009552, -0.18958489571779047, -0.13877701779856952, -0.08106895960526132, -0.016951632304750455, 0.052859915790889986, 0.1274477066305796, 0.20571776067793754, 0.286432022628767, 0.3682444301973055, 0.4497401624668544, 0.5294770198712279, 0.606027830281074, 0.678022746395361, 0.7441902994517225, 0.8033961032063873, 0.8546781594982875, 0.8972778010888018, 0.9306654167635979, 0.9545602351716668, 0.9689435942726842, 0.9740652888011716, 0.9704427646823932, 0.9588531124162543, 0.9403179964748036, 0.9160818400737607, 0.8875837596749894, 0.856423906827118, 0.8243250223127964, 0.7930901352903462, 0.7645574449264293, 0.7405535012112181, 0.722845853160387, 0.7130963550572061, 0.7128163141136952, 0.7233246260126485, 0.7457099790513811, 0.7807981145825822, 0.8291250133585341, 0.8909167370820933, 0.9660764953591514, 1.0541793342153989, 1.1544746576467135, 1.26589660285324, 1.3870820975587914, 1.516396238883064, 1.6519644522850534, 1.7917107206154215, 1.9334010214880355, 2.0746909797884006, 2.2131766344644648, 2.346447137499816, 2.4721381502107547, 2.587984679100471, 2.691872101075274, 2.7818841657619013, 2.856346830096754, 2.9138668756973978, 2.953364380496239, 2.9740982598069534, 2.9756842549364655, 2.958104925704238, 2.9217113924624556, 2.867216768829966, 2.7956814236040435], [2.73666033131934, 2.6407552719764915, 2.5321007155241864, 2.412776920632147, 2.285051641838668, 2.151330637503729, 2.0141051867285005, 1.8758978390956615, 1.739207661264435, 1.6064562541646872, 1.4799357935648612, 1.3617602956799655, 1.2538212295166642, 1.1577484908069893, 1.074877621301064, 1.006224005104552, 0.9524646044011117, 0.9139276144559182, 0.8905902267302214, 0.8820844939316673, 0.8877110966524817, 0.9064606226514497, 0.9370417914145833, 0.9779158927237205, 1.0273365625472215, 1.0833938961548477, 1.1440617999131621, 1.2072474120805776, 1.2708413807560748, 1.332767774887742, 1.3910324221207855, 1.443768514718822, 1.4892784005559925, 1.526070578281692, 1.5528910415879116, 1.5687482638620014, 1.572931277684733, 1.5650204795246838, 1.5448909741688177, 1.5127084613030348, 1.4689178535212186, 1.414224996238535, 1.349572031007252, 1.2761071003375142, 1.1951492304363922, 1.1081493448860218, 1.016648454324882, 0.9222341324342207, 0.8264964253983779, 0.7309843496505761, 0.6371641110157992, 0.5463801279368652, 0.45981986365534344, 0.3784833690384698, 0.303158311853203, 0.23440112291377582, 0.17252472837986835, 0.11759316466266574, 0.06942319229907552, 0.027592842353688203, -0.008543351957843726, -0.03983286007423079, -0.06729798037370381, -0.09210372130317576, -0.11552160017828172, -0.13889032980475527, -0.16357444552555245, -0.1909219807779011, -0.22222232632453384, -0.25866540629319845, -0.3013032730405296, -0.35101516340572775, -0.40847697260558546, -0.4741359909924079, -0.5481916159218816, -0.6305825993860363, -0.7209812256566451, -0.8187946361343399, -0.9231733353590655, -1.033026727322304, -1.1470453494907966, -1.263729297897482, -1.3814221746845674, -1.498349743709344, -1.612662353960221, -1.7224800878026492, -1.8259395141342667, -1.9212408773881249, -2.00669453330556, -2.08076545210412, -2.14211464894957, -2.1896364696250803, -2.2224907543787533, -2.2401290228481217, -2.242313964809801, -2.229131681834677, -2.2009962998279624, -2.1586467576125568, -2.103135767622317, -2.0358111367059415, -1.9582898232631136, -1.872425286785514, -1.7802688528953183, -1.684025967011508, -1.5860083390870898, -1.488583087211973, -1.3941200666128888, -1.3049386207023461, -1.2232550110325942, -1.1511317727307215, -1.0904302014109786, -1.0427671076063771, -1.0094768770855134, -0.9915797523547354, -0.989757105150929, -1.0043343053186908, -1.035271612118939, -1.0821633240841113, -1.1442452276318134, -1.220410187536627, -1.309231528834481, -1.4089936745044416, -1.517729330847933, -1.6332623570598883, -1.7532553208410333, -1.8752606313061406, -1.9967740565819974, -2.115289378388377, -2.228352910877966, -2.3336166166625283, -2.428888589106527, -2.5121797357143008, -2.5817455911354608, -2.636122307646105, -2.674156012985226, -2.6950248866379822, -2.698253482095634, -2.6837190099530397, -2.6516494903348473, -2.6026138783287536, -2.5375044580760306, -2.4575119852402203, -2.3640942292612137, -2.2589387219331627, -2.1439206536656488, -2.021056970050477, -1.8924578063999347, -1.760276454738285, -1.6266590850075258, -1.4936954394151734, -1.3633716860749034, -1.237526556279184, -1.1178118005217317, -1.0056578840568198, -0.9022457062592746, -0.8084849727943795, -0.7249996795377327, -0.6521209865789926, -0.5898875740279566, -0.5380533833856272, -0.4961024636366447, -0.4632704645608422, -0.4385721554389216, -0.42083419941274774, -0.40873228590830296, -0.4008316188840016, -0.3956296797878505, -0.3916001329030956, -0.38723671844663465, -0.3810959858445995, -0.37183775579534456, -0.35826226406126854, -0.3393430307225448, -0.314254613530619, -0.28239454006744247, -0.24339886716938122, -0.19715098359294042, -0.14378344892120842, -0.08367284373729592, -0.01742778850376949, 0.054129533242195646, 0.12998784235805672, 0.2089765608560392, 0.2898001372498206, 0.3710759810124555, 0.45137499147781324, 0.529263597329412, 0.6033461814064526, 0.6723067529888792, 0.7349487463463334, 0.7902318697599616, 0.8373050023356755, 0.8755342349084464, 0.9045252737226311, 0.924139568304307, 0.9345036844436323, 0.9360116154773372, 0.9293199057757117, 0.9153356449487754, 0.8951975751404438, 0.8702507322374491, 0.8420152103675086, 0.8121497934258121, 0.7824113336238897, 0.7546108717196534, 0.7305675837151586, 0.7120617020588823, 0.7007875940894017, 0.698308185643408, 0.706011893193685, 0.725073174094063, 0.7564177227297715, 0.8006932325448205, 0.8582465126365985, 0.9291075960552228, 1.0129813088152386, 1.1092465880340148, 1.2169636489870561, 1.3348889088574019, 1.4614973842892254, 1.5950120952481828, 1.733439833715513, 1.8746124967191535, 2.01623304309241, 2.1559250156494256, 2.291284478131186, 2.4199331516405493, 2.539571500006037, 2.6480305085288536, 2.743320926068041, 2.8236787958484255, 2.887606184442077, 2.933906129078267, 2.961710958124502, 2.9705032950058143, 2.9601292282325993, 2.9308033154104014, 2.88310528261219, 2.817968477602512, 2.7366603313193383], [2.671406759289074, 2.5675932130152797, 2.4523526925259986, 2.3278900367567013, 2.1965675383228365, 2.06085346936121, 1.923268342390367, 1.786330157960029, 1.6524999131180422, 1.5241286362917663, 1.403407175289794, 1.292319896755969, 1.1926033592485266, 1.105710900549577, 1.032783935831155, 0.9746306004567173, 0.9317121934828074, 0.9041376897055378, 0.8916663939835783, 0.893718616314084, 0.9093940545121244, 0.9374973880223013, 0.976570415836018, 1.0249299178401092, 1.0807102858994462, 1.141909861779981, 1.2064398362587907, 1.272174509395977, 1.3370016872080592, 1.3988719953974789, 1.4558459261263046, 1.5061374981034017, 1.5481535017986625, 1.580527418050166, 1.6021472367227212, 1.6121765589058608, 1.6100685374517, 1.5955723921448859, 1.5687324229207442, 1.5298796326271669, 1.4796162551706415, 1.418793660910581, 1.3484842744995877, 1.2699482869670153, 1.184596070092117, 1.0939473039094936, 0.9995879050243655, 0.9031258924332517, 0.80614734759158, 0.7101736161156686, 0.6166208600622236, 0.526763003232478, 0.44169901914131854, 0.36232539457300716, 0.2893144640106415, 0.22309915519457008, 0.1638645175871243, 0.1115462278831771, 0.06583608442060916, 0.026194320037817253, -0.008131614779621977, -0.03808231521885444, -0.06475640389875564, -0.08937604094065695, -0.11324888930813824, -0.13772755566852765, -0.1641675941598234, -0.1938851996975764, -0.22811572781285566, -0.2679741591883377, -0.3144185795033957, -0.36821767008356876, -0.429923104042681, -0.4998476186236321, -0.5780493903889423, -0.6643231793956956, -0.7581985355415692, -0.8589451792369789, -0.9655854840009983, -1.0769138051485072, -1.191522221066235, -1.3078320861618935, -1.4241306416607853, -1.5386117959100136, -1.6494200731697042, -1.7546966419230325, -1.8526262728076621, -1.9414840439764902, -2.0196806089385957, -2.0858048688801025, -2.138662947546813, -2.177312450685709, -2.201091101794102, -2.20963897886936, -2.2029137297614754, -2.1811983128745287, -2.1451009911988503, -2.095547496531515, -2.033765472607068, -1.9612614959772794, -1.8797911571455028, -1.7913228571235582, -1.6979961319469776, -1.6020754558343955, -1.505900589154881, -1.411834627268509, -1.3222109683543666, -1.2392804509392612, -1.165159914117923, -1.101783405281886, -1.050857202170542, -1.013819729578666, -0.991807338155669, -0.9856267761213969, -0.9957350276937061, -1.0222270183726256, -1.064831501163337, -1.122915243863083, -1.1954954403996336, -1.2812600736866036, -1.3785957683125154, -1.4856224932107924, -1.6002343116040467, -1.7201452319423995, -1.8429390927530578, -1.966122319222917, -2.0871783222512255, -2.203622273255477, -2.3130549810829555, -2.413214621118206, -2.502025120478147, -2.5776400857097927, -2.6384812686071917, -2.6832706989490362, -2.7110557668462443, -2.721226708195496, -2.713526130266136, -2.6880504062031534, -2.645242962511949, -2.5858796776249475, -2.5110467976986923, -2.4221119532695568, -2.3206890229919357, -2.2085977344534315, -2.0878190135369077, -1.9604471900644251, -1.8286402362255223, -1.6945692539572468, -1.5603684371217519, -1.4280867138782585, -1.299642224672844, -1.1767807131037322, -1.0610388025878708, -0.9537130039264486, -0.8558351507882144, -0.7681547955407647, -0.6911289209023596, -0.6249191380007085, -0.5693963532357292, -0.5241526995492061, -0.4885203469581226, -0.4615966370021289, -0.4422748303084392, -0.42927961963167005, -0.42120644585167866, -0.41656356432315483, -0.4138157458557022, -0.41142846197210636, -0.407911398739552, -0.40186016745268943, -0.39199513309255113, -0.3771963613969315, -0.3565337904796537, -0.3292918605221177, -0.29498798186296704, -0.25338438408413555, -0.2044930623019659, -0.14857371740784567, -0.08612476987987615, -0.01786770736639822, 0.0552748000549382, 0.1322064206160272, 0.21168957424325158, 0.29238186733774235, 0.37287557217438294, 0.4517390936728939, 0.5275593129320832, 0.5989836720329748, 0.6647608688606497, 0.7237790639866841, 0.7751005631809167, 0.8179920273581399, 0.8519493745130021, 0.8767166726367634, 0.8922984753753775, 0.898965219446884, 0.8972514803854301, 0.8879470665524921, 0.8720811159331128, 0.8508995413585716, 0.825836342887985, 0.7984794667545038, 0.7705320344544662, 0.7437698895538637, 0.7199965104266489, 0.7009964118233398, 0.6884882049390738, 0.6840785032439018, 0.6892178492174693, 0.7051597954976602, 0.7329242037477564, 0.7732657274223975, 0.8266483228967113, 0.8932264900599485, 0.9728337819547523, 1.0649789473144096, 1.1688498842236978, 1.283325392170198, 1.4069945181704009, 1.5381831051825223, 1.674986972298805, 1.8153109906800307, 1.9569131709734435, 2.097452750742854, 2.2345411674254656, 2.3657947261123513, 2.4888877239711906, 2.6016047756296126, 2.701891096817294, 2.78789954677827, 2.8580333024215236, 2.910983137166965, 2.945758402576323, 2.961710958124503, 2.958551460310716, 2.9363576027139078, 2.8955740891874577, 2.8370043185334235, 2.7617939559274016, 2.671406759289075], [2.6004727822601934, 2.489623211640909, 2.368754177129203, 2.2401764561109196, 2.106326913404415, 1.9697154804709205, 1.8328706148537182, 1.6982845089412868, 1.5683593212985734, 1.4453556773084175, 1.3313446293816584, 1.2281641819336766, 1.1373813747895216, 1.0602607834186533, 0.9977401387415423, 0.9504135970182511, 0.9185230057495506, 0.9019573191179145, 0.9002601209779583, 0.9126450195527065, 0.9380184905341525, 0.9750095687899774, 1.0220056276318932, 1.0771933425111384, 1.1386038165009147, 1.2041607508693677, 1.27173047767259, 1.3391726341511625, 1.4043902516175593, 1.4653780545538295, 1.5202678181334401, 1.5673697129454964, 1.605208672250155, 1.6325549469086669, 1.6484481629182515, 1.6522143624609147, 1.6434756873740084, 1.6221525495071147, 1.5884583209056584, 1.5428867634553667, 1.4861925978870254, 1.4193657814020562, 1.3436002174419381, 1.2602577564795698, 1.1708284598294598, 1.076888186589298, 0.9800546248018008, 0.8819429203091652, 0.78412205982799, 0.6880731385007428, 0.5951505873163264, 0.5065473537885781, 0.42326492226737417, 0.34608893098774784, 0.27557099474779784, 0.21201717872883752, 0.15548339459011257, 0.10577780901747745, 0.062470171973788687, 0.02490779162792029, -0.007762290101282757, -0.03656552887523925, -0.06266726934884133, -0.08733617619556955, -0.11190468798970658, -0.13772755566852757, -0.1661395785375796, -0.19841367347196812, -0.23572040651203202, -0.27909008059304274, -0.3293784095566137, -0.38723671844663443, -0.45308749564512746, -0.5271059865178583, -0.6092083643229051, -0.6990468460525366, -0.7960119428556621, -0.8992418512068475, -1.0076388066737072, -1.119892041641803, -1.2345068162498605, -1.3498388324320378, -1.4641331984086545, -1.575566988850536, -1.6822943473974943, -1.7824930057876274, -1.8744110494521324, -1.9564127442541204, -2.0270222535768094, -2.0849641189322448, -2.129199449667807, -2.1589568664842402, -2.173757366965771, -2.173432426168811, -2.1581348079913343, -2.1283417395692266, -2.084850286985238, -2.0287649615506282, -1.9614777771167977, -1.8846411655655586, -1.8001343351848307, -1.7100238206505092, -1.6165191197183602, -1.5219244368246287, -1.4285876544587843, -1.338847726864064, -1.254981735456431, -1.1791528601550876, -1.1133605051492281, -1.0593937717964896, -1.0187893964125894, -0.992795168438035, -0.982339717301961, -0.9880094073030258, -1.0100329125922065, -1.0482738629216586, -1.1022317596198732, -1.1710511649117858, -1.2535389709988394, -1.348189363035528, -1.453215906968069, -1.5665900235977492, -1.6860849583274622, -1.809324225541813, -1.933833400634486, -2.0570940539038345, -2.176598570797404, -2.2899045834952703, -2.394687750036659, -2.4887916588183066, -2.5702737072860495, -2.6374459022450365, -2.6889096529947905, -2.72358377440517, -2.740725081501183, -2.739941136080701, -2.7211948949611244, -2.684801204008127, -2.6314152773831148, -2.5620134926861335, -2.477867015205046, -2.3805089338686924, -2.271695743631247, -2.153364140208671, -2.0275842001900313, -1.8965100999997462, -1.7623295790959768, -1.6272133749689794, -1.4932658494989846, -1.3624779883413332, -1.2366838882595823, -1.1175217534687738, -1.0064003034914386, -0.9044713547847733, -0.8126091800158186, -0.7313970763312785, -0.6611213916197733, -0.6017730701623636, -0.5530565908957673, -0.5144059874611524, -0.485007463854056, -0.46382795717735364, -0.44964885374259905, -0.4411039401458674, -0.43672057001959197, -0.4349629523908965, -0.43427642076003486, -0.43313152424730716, -0.4300667938116491, -0.42372907724930914, -0.4129104053399654, -0.3965804463235741, -0.37391372441413606, -0.34431091724409363, -0.3074137034279617, -0.26311280085276384, -0.21154901453666006, -0.15310729541946314, -0.08840399362832711, -0.018267666979993245, 0.0562860267536427, 0.13408467122851095, 0.21383384751866694, 0.294155370287742, 0.37362797832753347, 0.4508293885827676, 0.5243785856964405, 0.5929772109639982, 0.655448935604947, 0.7107757529398732, 0.758130201169902, 0.7969026310732116, 0.8267227584936804, 0.8474748868547104, 0.8593063464393165, 0.8626288707776425, 0.8581128118074799, 0.8466742799539766, 0.8294554782576363, 0.8077986765400605, 0.7832144378569952, 0.7573448609270892, 0.7319227349862192, 0.7087276142049952, 0.6895399045710414, 0.6760941147462859, 0.6700324523045555, 0.6728599470933873, 0.6859022541389774, 0.7102672301577083, 0.7468112917102292, 0.7961114513857551, 0.8584437938290653, 0.9337689991909626, 1.0217253514616578, 1.1216294873057613, 1.2324849519278847, 1.3529984368197934, 1.4816033847093055, 1.6164904643392404, 1.7556442463860382, 1.8968852561435845, 2.037916442432638, 2.176372988960309, 2.3098743068982976, 2.436076987993786, 2.552727467607522, 2.657713147499329, 2.7491107590166894, 2.825230807902707, 2.8846570308099966, 2.92627990867318, 2.949323420594559, 2.953364380496241, 2.938343873651448, 2.904570497089063, 2.852715302230651, 2.783798535243186, 2.699168465677254, 2.6004727822601916], [2.5244585337763614, 2.407504929346844, 2.2820124506028248, 2.150378275277923, 2.015093243604572, 1.8786877394592922, 1.7436768097989623, 1.6125057980712536, 1.4874977532868834, 1.3708038320928193, 1.2643578375875195, 1.1698359375912846, 1.088622479116412, 1.0217826679715583, 0.970042716413107, 0.9337778815965645, 0.9130086276977427, 0.9074049496148499, 0.9162987008942823, 0.9387035777118394, 0.9733422290371112, 1.018679794930724, 1.0729630243507482, 1.1342639945146156, 1.200527348885611, 1.2696198927324558, 1.3393813357838398, 1.4076749518937, 1.47243693623599, 1.5317232810019885, 1.5837530597845568, 1.6269471069996482, 1.659961199350684, 1.6817129884203201, 1.6914020933874745, 1.6885229365917702, 1.6728700878464031, 1.644536071452424, 1.603901778100535, 1.5516198075750303, 1.4885912428351593, 1.4159365173147145, 1.3349611811670714, 1.247117495148118, 1.1539628798611599, 1.0571163207773042, 0.9582138740467829, 0.8588644335915349, 0.760606906008649, 0.6648698968470036, 0.572934941000952, 0.48590421314714866, 0.4046735338345898, 0.3299113461117087, 0.2620441800336281, 0.20124895205213114, 0.14745226748188928, 0.10033671149941129, 0.05935393210100695, 0.023744141736505943, -0.0074385025767261794, -0.035295333742206024, -0.06104825174759757, -0.08600138524670661, -0.11150036877439908, -0.13889032980475513, -0.16947371477865178, -0.20446908916378728, -0.2449720233991107, -0.2919191247822168, -0.34605619626853124, -0.4079113987395534, -0.47777416617795837, -0.5556804765481431, -0.6414049187046924, -0.7344598214239959, -0.8341015290622845, -0.9393437239646194, -1.048977513238031, -1.1615978214735796, -1.275635465915659, -1.3893941406261974, -1.5010914051967148, -1.6089026648762186, -1.7110070454078374, -1.8056340095801342, -1.8911095349995417, -1.9659006746613532, -2.028657353584429, -2.0782503153855503, -2.11380422078689, -2.1347250135690183, -2.1407208056590648, -2.1318156885659736, -2.108356049440247, -2.0710091524468166, -2.0207539354085418, -1.9588641631352768, -1.8868842677659259, -1.8065983881371575, -1.7199932901400257, -1.629216004003162, -1.5365271486017076, -1.4442510238717805, -1.3547236374108311, -1.270239888203009, -1.1930011576509734, -1.1250645549759197, -1.068295030565885, -1.024321507755357, -0.9944980922846803, -0.9798713014854625, -0.9811541148809595, -0.9987074877616728, -1.03252979327032, -1.082254470874573, -1.1471559643781957, -1.2261638355563962, -1.3178847448955513, -1.4206318035096588, -1.5324606246621015, -1.6512112437200124, -1.7745549356990384, -1.9000448432183228, -2.025169237510477, -2.1474061733082928, -2.2642782664547063, -2.3734063217199175, -2.472560567574459, -2.559708313824889, -2.633056935603002, -2.691091201049688, -2.7326040973472203, -2.756720467154273, -2.7629129411225435, -2.7510098377653076, -2.721194894961125, -2.6739988930888114, -2.6102834234216368, -2.5312172422364703, -2.4382458265690103, -2.3330549074073383, -2.217528896492263, -2.09370524039968, -1.9637258274024982, -1.8297866365702649, -1.694086853176544, -1.5587786789886067, -1.425919040394779, -1.2974243423107426, -1.1750293328501613, -1.0602510349878054, -0.9543585696589935, -0.8583495432656445, -0.7729335052148069, -0.6985228021034907, -0.6352309689662744, -0.5828786092715854, -0.5410065287912939, -0.5088957087161688, -0.48559353490510465, -0.4699455471081499, -0.4606318381663642, -0.45620712185322143, -0.45514340190135777, -0.4558741159383555, -0.45683859793259707, -0.4565257020010976, -0.4535154589951804, -0.44651769436178484, -0.434406619870101, -0.4162505207113139, -0.39133579042039623, -0.35918471568047833, -0.3195665775352805, -0.2725018106672425, -0.21825914374826252, -0.157345826834615, -0.09049123171837585, -0.018624283505239765, 0.057154657902852825, 0.13560670334540784, 0.21539123916007996, 0.29510564146234347, 0.3733268337753839, 0.4486535727241431, 0.5197483260141927, 0.5853776155781213, 0.6444497363908142, 0.6960488271014249, 0.7394643606687108, 0.7742152393165215, 0.8000678154371842, 0.8170473151162537, 0.8254423098360311, 0.8258020603880429, 0.8189267405901145, 0.8058507324309471, 0.7878193641054019, 0.766259633504649, 0.7427456177476837, 0.7189594102641864, 0.6966485471654891, 0.6775809810835545, 0.6634987308201483, 0.6560713771856866, 0.6568505881739387, 0.6672268396993486, 0.6883894518426209, 0.7212909859654644, 0.7666169469333379, 0.8247616094573016, 0.8958106412701802, 0.9795310320566972, 1.0753686597742123, 1.1824536395863052, 1.299613409678601, 1.4253933174506794, 1.5580842837022828, 1.6957569460664295, 1.8363015204732716, 1.977472474907558, 2.116936986765776, 2.25232605681764, 2.3812870816193303, 2.5015366440368694, 2.6109122694305666, 2.70742191339984, 2.789289995417681, 2.8549988700796405, 2.9033247322243034, 2.9333670813519053, 2.9445710214673486, 2.936741841063321, 2.9100515003551832, 2.8650368446554793, 2.802589559271468, 2.7239380777440068, 2.6306218468379576, 2.524458533776359], [2.4440071287765908, 2.321933123960239, 2.192861387204358, 2.0592552275017, 1.9236384070535206, 1.7885403822058066, 1.6564415471775198, 1.5297197520591994, 1.4105993345386278, 1.3011038429905901, 1.2030135384778242, 1.1178286470697603, 1.046739194550244, 0.99060209647652, 0.9499260015719737, 0.9248641998718716, 0.9152157134609856, 0.9204344917772574, 0.9396464400889171, 0.9716738235978234, 1.0150664152090911, 1.0681385965703871, 1.1290114833578564, 1.195659030309826, 1.2659569819488419, 1.3377334734084836, 1.4088200537205564, 1.4771019020178353, 1.5405660353200028, 1.5973463641046468, 1.6457645372078882, 1.684365628553081, 1.7119478519451785, 1.7275856433096695, 1.730645618441746, 1.720795094331463, 1.69800304893977, 1.6625335832564978, 1.6149321358692612, 1.5560048794811587, 1.486791896393383, 1.4085348817744954, 1.3226402558310828, 1.23063867552956, 1.1341420206255102, 1.0347989854051536, 0.9342504353937521, 0.8340856867211265, 0.7358008349755973, 0.6407602010784283, 0.5501618755366231, 0.46500823161914434, 0.3860821454018063, 0.31392950963338156, 0.24884846284156772, 0.19088557923481397, 0.13983908323191646, 0.09526896947610604, 0.05651372960170231, 0.022713215368213132, -0.007162991594925516, -0.034282476245350066, -0.05991304871654465, -0.08538296102949522, -0.11203935238573358, -0.1412060404818565, -0.17414179458172635, -0.21200021521617415, -0.25579230560882255, -0.3063527522368105, -0.364310838016781, -0.430066793811648, -0.5037742552376203, -0.585329335598726, -0.6743666561151269, -0.7702624957138768, -0.8721450390263941, -0.9789115175204591, -1.0892518595304574, -1.2016782948743792, -1.3145602030765318, -1.4261633549380637, -1.5346925788717607, -1.6383367890833183, -1.735315244782923, -1.8239238699370461, -1.9025804527060082, -1.9698675630136058, -2.0245720752754988, -2.0657202600560547, -2.0926075115068157, -2.104821904380746, -2.1022609221318524, -2.085140862492756, -2.0539986049307006, -2.0096856111376478, -1.9533542206070305, -1.886436493670526, -1.810616039397509, -1.7277934409038795, -1.640046051516404, -1.5495830778763078, -1.4586969868694464, -1.3697123691970516, -1.2849334610190954, -1.2065915646458176, -1.1367936186727585, -1.0774731469388084, -1.0303447646752282, -0.9968633403826549, -0.9781888052116776, -0.9751574704834813, -0.9882605616256367, -1.0176305068957192, -1.0630353359375526, -1.1238813509116867, -1.1992240363376137, -1.2877869776644926, -1.387988367725807, -1.497974499282007, -1.6156594752242766, -1.738770219763809, -1.864895747677091, -1.9915395474948374, -2.1161738608711227, -2.2362945960394285, -2.3494755993223584, -2.453421025439071, -2.5460145944221364, -2.6253645991464434, -2.6898436309077085, -2.738122118621088, -2.769194926893301, -2.782400425781163, -2.7774316263778083, -2.7543391670244213, -2.7135261302661373, -2.6557348658836855, -2.5820261856743025, -2.493751476490226, -2.392518444975239, -2.2801513564225497, -2.1586467576125576, -2.0301257763148017, -1.8967841659043339, -1.7608413104693073, -1.6244894228086881, -1.4898441545111758, -1.3588977942889355, -1.233476159069015, -1.1152001838823484, -1.0054530938544715, -0.9053538977079112, -0.815737780764871, -0.7371438005474424, -0.6698101040931475, -0.6136766976330601, -0.5683956110173509, -0.533348115900428, -0.5076684827658673, -0.4902736016849754, -0.4798976492154612, -0.47513086256165277, -0.4744613850022191, -0.47631907600282897, -0.479120137059511, -0.4813113911450072, -0.4814130699036939, -0.4780590079720511, -0.4700332167773781, -0.4563019089808847, -0.4360401668300205, -0.40865258993644643, -0.37378741676602945, -0.33134378537073744, -0.28147197825596576, -0.22456667920727508, -0.16125345175957176, -0.09236882517129458, -0.018934539804963377, 0.05787334448998616, 0.13675963988628156, 0.21634857292947668, 0.29522464113740704, 0.3719746863371149, 0.4452300544837528, 0.5137077079774682, 0.5762491818911644, 0.6318563294207974, 0.6797228829279429, 0.7192609631343726, 0.7501217976884934, 0.7722100582232709, 0.7856913884469343, 0.7909928706388366, 0.7887963597583033, 0.7800247986277323, 0.7658218096683143, 0.7475250338426936, 0.7266338513530478, 0.7047722670905249, 0.683647873048018, 0.6650079065829906, 0.6505935047997604, 0.6420933092876664, 0.6410976005616966, 0.6490541370826298, 0.6672268396993486, 0.6966583995103566, 0.7381377969584867, 0.792173604611732, 0.8589738083354065, 0.9384327247820129, 1.0301254211515525, 1.1333098602302172, 1.2469368043045055, 1.3696673203473022, 1.4998975406136608, 1.63579015213585, 1.7753119200601855, 1.916276397523894, 2.0563908426350754, 2.193306254410596, 2.324669356991618, 2.448175307199775, 2.561619875930647, 2.6629498596879797, 2.750310514678154, 2.8220888714990053, 2.8769518820328543, 2.913878469463247, 2.9321846945152994, 2.931541412641797, 2.9119839740311306, 2.873913706702453, 2.8180911180019272, 2.7456209467775006, 2.6579293925934917, 2.556734034822592, 2.444007128776592], [2.359799222551847, 2.233631771676338, 2.1020552452714583, 1.9675782550000755, 1.8327361530522581, 1.7000360961449617, 1.5719028767855645, 1.4506267783154905, 1.3383146604733391, 1.2368454034491319, 1.1478307325816457, 1.072582315580478, 1.012085872630845, 0.9669828706777561, 0.9375601907286139, 0.9237479656250496, 0.9251255900950052, 0.9409357097825105, 0.970105806123307, 1.011276814011261, 1.062838043554673, 1.122967529866738, 1.1896768093278007, 1.2608590201123795, 1.3343391513876537, 1.4079252211831936, 1.479459148507625, 1.5468661011094729, 1.608201145862587, 1.6616921028839802, 1.7057776052439326, 1.739139490931276, 1.7607287994284657, 1.7697848081587437, 1.7658467201012136, 1.7487577986222007, 1.718661934430468, 1.675992817825508, 1.6214560723938214, 1.5560048794811587, 1.4808097818468073, 1.3972234959673455, 1.306741682037595, 1.2109607158946176, 1.111533575560684, 1.0101249952288016, 0.9083670503772896, 0.8078163191089744, 0.7099137173146441, 0.6159480301309781, 0.5270240613620923, 0.4440361986638289, 0.36764804852786187, 0.2982786351212348, 0.23609548491019008, 0.18101473910039903, 0.13270825282395404, 0.0906174583382572, 0.05397359387422517, 0.02182373462661702, -0.0069380881034569125, -0.03353552561741789, -0.059271264587010396, -0.08548613569265315, -0.11351707877846559, -0.14465509573963237, -0.18010432387934036, -0.22094333489485218, -0.26808970865744103, -0.3222688479372689, -0.38398789227185515, -0.4535154589951802, -0.530867790305497, -0.615801720905784, -0.7078147053403604, -0.8061519620968004, -0.9098206074388099, -1.017610470436263, -1.1281211063570078, -1.2397943629026131, -1.3509517068424615, -1.4598353911763093, -1.5646524382998037, -1.6636203354619503, -1.7550132871564572, -1.8372078463634904, -1.9087267534170855, -1.9682798476403804, -2.0148009819531207, -2.047479962881758, -2.0657886555797123, -2.0695005327544598, -2.0587031044020705, -2.0338028380983375, -1.9955223630402705, -1.9448899405503992, -1.8832213746666278, -1.812094724013943, -1.733318355735293, -1.6488930493789642, -1.5609690091292405, -1.4717987728592894, -1.3836871129083634, -1.2989391035481168, -1.2198075817562668, -1.1484412498109786, -1.0868346597357441, -1.0367812808910957, -0.9998307838993842, -0.9772515781993131, -0.9699995191422555, -0.9786935565754016, -1.0035989337808295, -1.0446183674005327, -1.1012914498990327, -1.172802320791508, -1.2579954560482802, -1.3553992315690506, -1.463256731118228, -1.5795630961483698, -1.7021085587309481, -1.8285261631709202, -1.9563430701126014, -2.0830342517713523, -2.206077330422751, -2.323007285818487, -2.4314697614120666, -2.5292717340522186, -2.6144283762742484, -2.6852050328993426, -2.740153352061619, -2.778140752114858, -2.7983725666575405, -2.8004063862155433, -2.7841583026199377, -2.749900956225971, -2.698253482095637, -2.6301636443274705, -2.5468826331589933, -2.449933172779057, -2.3410717447638913, -2.2222458688947877, -2.095547496531511, -1.9631636589902297, -1.8273255724432607, -1.6902574303537867, -1.5541261137465017, -1.420993018806994, -1.2927691412509696, -1.1711744691832449, -1.057702623029397, -0.9535915454471118, -0.859800889337765, -0.7769965820752422, -0.7055428631102293, -0.64550190471806, -0.596640936509024, -0.5584466081185223, -0.5301461458616976, -0.5107346924971136, -0.4990080687109577, -0.493600064212085, -0.49302325862119706, -0.4957122902664766, -0.5000684365390108, -0.5045043438967332, -0.5074877494926231, -0.5075830695609836, -0.5034897912118399, -0.49407669253555764, -0.4784110286187131, -0.4557819553186172, -0.4257176150024399, -0.3879954750417655, -0.34264568642679993, -0.2899474119420879, -0.23041825630952212, -0.1647971099192479, -0.09402088869685128, -0.019195810970475836, 0.058436006101306164, 0.13753372648628684, 0.21669774934996963, 0.29451136252183363, 0.36958297579190785, 0.4405877983750689, 0.5063078379482686, 0.5656691405827825, 0.6177752606164418, 0.6619360452947048, 0.6976909384521648, 0.7248261476077069, 0.7433851760837425, 0.753672392175086, 0.7562494866918905, 0.751924853861013, 0.7417361139526557, 0.726926174465935, 0.7089133957369268, 0.6892565821331211, 0.669615657615207, 0.6517090008620858, 0.637268507375598, 0.6279935116149404, 0.6255047395258198, 0.6312994698002662, 0.6467090605347958, 0.6728599470933878, 0.7106391381031738, 0.7606651314925101, 0.8232650438569394, 0.8984585973363722, 0.9859494422513404, 1.085124115049564, 1.1950587440551357, 1.314533424707881, 1.4420539961499748, 1.5758807668672505, 1.714063563200771, 1.8544823152414849, 1.9948922538890128, 2.132972674224212, 2.266378126805351, 2.392790832427056, 2.5099730789839683, 2.6158183523453364, 2.7083999768189035, 2.7860160943601433, 2.847229893927362, 2.890904111347377, 2.916228953134166, 2.9227427516910343, 2.910344830504528, 2.8793002421578247, 2.8302362347800987, 2.76413049921908, 2.682291444989027, 2.5863309431372867, 2.4781301539554055, 2.359799222551845], [2.2725472520933128, 2.1433479418922903, 2.0103622858551367, 1.8761229864447275, 1.743155555803385, 1.6139236675854893, 1.4907760340288072, 1.3758960391879855, 1.271255292142807, 1.1785721689442483, 1.099276291407377, 1.0344797475620406, 0.9849556961424643, 0.9511248199133456, 0.9330499042383573, 0.9304386227029284, 0.9426544155592063, 0.9687351540493755, 1.0074190989777771, 1.0571774897326924, 1.1162529444811393, 1.1827027172337086, 1.254445746151502, 1.329312342505207, 1.4050953131053014, 1.4796012821082754, 1.550700981438584, 1.6163773124756295, 1.6747700442233062, 1.7242161032731287, 1.7632845261808685, 1.7908052824730571, 1.8058913329112012, 1.8079534589375745, 1.7967075811171531, 1.7721744723324129, 1.7346719607989902, 1.6847999039446264, 1.6234183922191017, 1.5516198075750303, 1.4706955105914346, 1.3820980593356558, 1.2873999689150895, 1.1882501006861832, 1.08632882234237, 0.9833031033702498, 0.8807827041470031, 0.7802785814921019, 0.6831645697552612, 0.5906433061985065, 0.5037172548552619, 0.4231655471699598, 0.34952720401383625, 0.2830911360557445, 0.2238931422035845, 0.17171994342303074, 0.126120106309991, 0.08642153197492489, 0.05175501561625452, 0.021083224921286236, -0.006765694887628211, -0.03306080139872095, -0.05912832914314141, -0.08631003633184296, -0.11592104571863349, -0.1492083150098866, -0.18731085697555944, -0.23122278536053195, -0.2817601909505353, -0.3395327545118488, -0.40492088225078515, -0.47805900797205275, -0.5588255478149468, -0.6468398223007009, -0.7414660807485323, -0.8418245794469899, -0.9468094819423736, -1.055113172058878, -1.1652564023009897, -1.275623546375044, -1.3845020886242374, -1.4901253686775802, -1.5907175095130852, -1.6845393937688165, -1.7699345181764887, -1.8453735504078284, -1.909496436647525, -1.9611509613321845, -1.999426741488274, -2.023683745030586, -2.033574552662395, -2.029059733477229, -2.0104158713178495, -1.978235958299816, -1.9334220592361502, -1.8771703413786296, -1.8109487531994803, -1.7364678191768554, -1.6556451901606792, -1.570564746577546, -1.4834311905399191, -1.3965211793703505, -1.3121321441945426, -1.2325300007776339, -1.159896994030705, -1.0962809216753122, -1.0435469562392239, -1.0033332284328347, -0.9770112503234502, -0.9656521455878321, -0.969999519142255, -0.9904496428727884, -1.0270394617774117, -1.0794427397640909, -1.146974471119549, -1.2286034869718618, -1.3229729907050718, -1.4284285670071435, -1.543053030659175, -1.6647073176599962, -1.791076476816974, -1.919719698045094, -2.0481232172773804, -2.1737548694478623, -2.29411902213115, -2.406810614051979, -2.5095670450097707, -2.600316716241638, -2.677223101578721, -2.7387233379359315, -2.783560456058361, -2.8108085257829933, -2.819890160604493, -2.810586009884349, -2.7830360591240675, -2.7377327546416255, -2.675506163964098, -2.5975015725256427, -2.5051500962326356, -2.400133053780378, -2.2843409882986525, -2.159828351451069, -2.028764961550624, -1.893385418239234, -1.7559376981503307, -1.6186321677890672, -1.4835922314244274, -1.3528077836396126, -1.228092559609139, -1.111046373141716, -1.0030231056740793, -0.9051051619328703, -0.8180849436123374, -0.7424537152682744, -0.6783980511334818, -0.6258038623445273, -0.5842678158420497, -0.5531157736415991, -0.5314277087905386, -0.5180683963881054, -0.5117230384396187, -0.5109368634667337, -0.5141576485779319, -0.5197800453713092, -0.5261905531730535, -0.5318119745736948, -0.5351462091388868, -0.5348142909338004, -0.5295926527807717, -0.5184447029516126, -0.5005469256269544, -0.4753088617132247, -0.4423864877843063, -0.4016886839054541, -0.35337666150636227, -0.2978564057214448, -0.23576436806484985, -0.1679468203620889, -0.0954334450900521, -0.019405886529490365, 0.0588378823649738, 0.1379224140225092, 0.21643581423103717, 0.29297184027547324, 0.36617193709323653, 0.4347660799854168, 0.49761132217552007, 0.5537270035899681, 0.6023256621915917, 0.6428387988967276, 0.6749367787914511, 0.6985423017202576, 0.7138370405649143, 0.7212612214979367, 0.7215061027449444, 0.7154994923206187, 0.7043846261630722, 0.6894929014981063, 0.6723111217184413, 0.654444054455886, 0.637573230146447, 0.6234130110175871, 0.6136650374128336, 0.6099722076980573, 0.6138733683412119, 0.6267598815213417, 0.6498351989391908, 0.6840785032439018, 0.7302133842462216, 0.7886823981236374, 0.8596282170239028, 0.9428819172781717, 1.0379587807468125, 1.1440617999131615, 1.2600928877501072, 1.3846716027999997, 1.5161610130539842, 1.6527001437345241, 1.7922422884202955, 1.9325983142420815, 2.071483963849698, 2.2065700527260304, 2.3355343828441653, 2.45611414461645, 2.566157559858792, 2.6636735296453677, 2.7468780922659994, 2.814236567084739, 2.8645003582765556, 2.8967375158497477, 2.9103562970815986, 2.905121135987933, 2.881160607731991, 2.8389671646046084, 2.7793886157648644, 2.7036115195592982, 2.6131368501481176, 2.509748484656459, 2.395475228637215, 2.2725472520933105], [2.1829894085530306, 2.051845476661965, 1.9185582728835893, 1.7856631747916114, 1.6556545076953055, 1.5309316466393175, 1.4137473887072818, 1.306159790545746, 1.2099885821478147, 1.126777157408788, 1.0577610074984851, 1.0038433079814912, 0.9655781986547373, 0.9431621104686055, 0.9364333011658389, 0.9448795651190731, 0.9676538880582785, 1.0035976286999635, 1.0512706313103226, 1.1089875102752236, 1.1748592037561354, 1.2468387719556957, 1.322770319315154, 1.4004398514053857, 1.4776268379561284, 1.5521552442745175, 1.6219428143695427, 1.685047439813968, 1.7397095273992627, 1.78438938393637, 1.8177987654453953, 1.8389258872029444, 1.8470533569238434, 1.8417686715890627, 1.8229671046406728, 1.790846999806346, 1.7458976759776406, 1.6888803296800337, 1.6208024932314202, 1.5428867634553665, 1.4565346539388448, 1.3632865399176677, 1.2647787561088064, 1.1626989719855896, 1.0587410045880745, 0.954560235171666, 0.8517307727540584, 0.7517054555917161, 0.6557797021899261, 0.5650601186959994, 0.48043864214562787, 0.40257285229325196, 0.33187292240409305, 0.2684955055514257, 0.21234467206267138, 0.16307983038008228, 0.12013038239070563, 0.08271668982182084, 0.04987676500377089, 0.02049795129941231, -0.006647270472054136, -0.03286231997096453, -0.05948545168347183, -0.08784769237483787, -0.11923091455811609, -0.15482717599723772, -0.19570042333939655, -0.24275159781076935, -0.2966880940219423, -0.35799841149892314, -0.4269327053860638, -0.5034897912118396, -0.5874109924864109, -0.678181043400777, -0.7750360764762684, -0.8769785412796223, -0.9827987199211285, -1.0911023325624138, -1.2003435659548058, -1.308862714186604, -1.4149274970102672, -1.516777020525847, -1.6126672702145632, -1.7009169793046583, -1.779952697476656, -1.848351896518823, -1.904882990528912, -1.9485412176930426, -1.978579426912214, -1.9945329332734698, -1.9962377486425926, -1.983841654010606, -1.9578077547213044, -1.918910344044586, -1.868223090189231, -1.807099752074795, -1.7371478152869293, -1.6601956169957508, -1.5782536928019306, -1.493471225385287, -1.4080886007799622, -1.3243871799139069, -1.2446374681422891, -1.1710469119455025, -1.1057085685244183, -1.0505518802176639, -1.007296741742688, -0.9774119752232353, -0.962079227527435, -0.9621631789969061, -0.9781888052116768, -1.0103262675658757, -1.058383828141573, -1.1218089940379918, -1.1996979005677757, -1.2908127463365473, -1.3936069009621224, -1.506257122754814, -1.6267021535462998, -1.7526868051746982, -1.8818105206369113, -2.0115792858157495, -2.1394596875954233, -2.2629338630472757, -2.379554063445154, -2.486995566661616, -2.5831067117568094, -2.6659548993097912, -2.7338674985445475, -2.785466725178291, -2.819697699156185, -2.835849055477929, -2.833565660152548, -2.8128531725650094, -2.774074390577994, -2.7179375107629613, -2.645476628476192, -2.558024986385401, -2.457181651041812, -2.3447724510357237, -2.2228061434501787, -2.0934268845332173, -1.958864163135272, -1.8213814095535816, -1.6832245167454438, -1.5465715049072415, -1.4134845244038505, -1.2858653269527187, -1.1654152425106208, -1.0536005818452083, -0.951624245275981, -0.8604041600566168, -0.7805589963091465, -0.7124014286279768, -0.6559390220096878, -0.6108826313244956, -0.5766620178318792, -0.552448208858486, -0.5371819620846588, -0.5296075479853863, -0.5283109364734652, -0.5317613698127226, -0.5383552259294027, -0.5464610262177482, -0.5544644209778423, -0.560811994178025, -0.564052766999595, -0.5628763455670639, -0.5561467506582959, -0.5429310836307726, -0.5225223203003129, -0.4944556795497202, -0.45851818207556, -0.41475119261386073, -0.36344592170443085, -0.3051320459278032, -0.24055978394866495, -0.1706759351124881, -0.09659454348462161, -0.01956298914771742, 0.05907557322594735, 0.1379224140225092, 0.2155649836623126, 0.2906190994531718, 0.36177042917200436, 0.4278141536867301, 0.4876917371178785, 0.5405238067955587, 0.5856382447399429, 0.6225927150801394, 0.6511909946393345, 0.6714926332559292, 0.6838156422639567, 0.6887320895856349, 0.6870566635477501, 0.679828450178413, 0.6682863457474196, 0.653838693192882, 0.6380278835881517, 0.6224907980583371, 0.6089160781199914, 0.5989993003926877, 0.5943971927312727, 0.596682061434979, 0.607297602397318, 0.62751724269595, 0.6584061037503196, 0.700787594089403, 0.7552155309596817, 0.8219525580982124, 0.900955475213108, 0.9918679267723186, 1.094020717730263, 1.2064398362587923, 1.3278620730311905, 1.4567579378563142, 1.5913613921625145, 1.7297057445260253, 1.869664900402796, 2.008999020362537, 2.145403526881539, 2.2765603110152184, 2.400189929307394, 2.5141035496845516, 2.6162534036922804, 2.704780531376072, 2.778058663761038, 2.834733174882782, 2.873754148603222, 2.8944027422982317, 2.896310186633156, 2.879468934248715, 2.8442356560548507, 2.7913259774585075, 2.7218010435224285, 2.6370461969756547, 2.5387422414199317, 2.4288299394037134, 2.309468556937986, 2.1829894085530284], [2.0918833918127415, 1.9598985282465522, 1.827419909848348, 1.696964150980848, 1.570973307189693, 1.451762183357971, 1.34146863801627, 1.2420080326083, 1.1550328745784242, 1.0818985780778518, 1.023636118942721, 0.9809321949808291, 0.9541173225648282, 0.9431621104686052, 0.947681756442047, 0.9669486159660403, 0.9999125007424877, 1.0452281814232791, 1.1012893993143633, 1.1662685394207604, 1.238160985906558, 1.3148330739878524, 1.3940724720125701, 1.4736397759020528, 1.551320076419004, 1.6249732683309492, 1.692581909156606, 1.752295502773617, 1.802470177977334, 1.8417028516905707, 1.8688591079053567, 1.883094183030101, 1.883866622117216, 1.870944354112618, 1.844403123220193, 1.8046174030121553, 1.7522441053363138, 1.688199572783595, 1.6136305071199215, 1.529879632627169, 1.4384470191441803, 1.340948091679969, 1.2390694293153046, 1.134523503903663, 1.0290035277196308, 0.9241395683043072, 0.8214570486841906, 0.7223386829824211, 0.627990802990038, 0.5394149129662537, 0.4573851708304081, 0.38243233755066386, 0.3148345669097049, 0.2546152292469437, 0.20154777977058558, 0.155167499237593, 0.11478975684083623, 0.07953427652002075, 0.048354732886874, 0.020072865440675644, -0.0065838167808781, -0.032941760576841325, -0.0603396107897106, -0.09008609455571673, -0.12341868230879832, -0.16146414059516906, -0.20520204344309084, -0.2554322332753883, -0.31274712105672425, -0.37750959108457527, -0.4498371316935024, -0.5295926527807705, -0.6163822785229067, -0.7095602232934389, -0.8082406751691158, -0.9113164291702415, -1.0174838361364587, -1.1252734673637275, -1.23308574403682, -1.3392306479367126, -1.4419705192779488, -1.539564861686462, -1.6303160154963225, -1.7126145302849007, -1.7849830667268016, -1.846117686540658, -1.8949254469030177, -1.9305573008601165, -1.9524354159397732, -1.9602741566687707, -1.9540941297774077, -1.9342288597682973, -1.9013238430842863, -1.856327916874395, -1.8004770686805198, -1.7352710015317145, -1.6624429502590259, -1.5839234148146462, -1.5017986307467606, -1.4182647318766892, -1.3355786722516554, -1.2560070607663671, -1.1817741202526992, -1.115010011804658, -1.0577007638377327, -1.0116410138213927, -0.9783907094641857, -0.9592368267939524, -0.9551610471810107, -0.9668141966626693, -0.9944980922846791, -1.0381552654154824, -1.0973668453503846, -1.1713586925401251, -1.2590156741729521, -1.3589037804013278, -1.4692995919764478, -1.5882264340126138, -1.7134963903483105, -1.8427572124169298, -1.9735430391224125, -2.1033277528034096, -2.229579733197615, -2.349816737929787, -2.461659635255443, -2.5628837426642104, -2.651466582795425, -2.7256309545263013, -2.78388232994151, -2.8250397244187284, -2.8482593439261943, -2.8530504869874753, -2.8392833643872937, -2.8071886930353434, -2.7573491167528186, -2.690682701310646, -2.6084189390906674, -2.5120678756888513, -2.40338313233881, -2.2843197402952797, -2.156987822850723, -2.0236032545983633, -1.886436493670527, -1.7477608194289387, -1.609801214646376, -1.474685107524117, -1.3443961356102694, -1.2207320122216903, -1.1052674684198776, -0.999323112682612, -0.9039408994523226, -0.8198667305216583, -0.7475405339230621, -0.6870939780981428, -0.6383557892880625, -0.6008644520243281, -0.5738878909713414, -0.5564495616693247, -0.5473602221573609, -0.5452545208449178, -0.5486314216890196, -0.5558973985031659, -0.5654112682216873, -0.5755294996345488, -0.5846508302376754, -0.5912590494212124, -0.5939628605148793, -0.5915318157803497, -0.5829274251605001, -0.567328668712278, -0.5441512908558707, -0.5130604180851717, -0.47397621644282223, -0.42707248643245976, -0.37276827652333694, -0.31171277735275216, -0.24476393257263995, -0.17296136462471862, -0.09749436046273867, -0.01966578966591706, 0.05914706771198664, 0.13753372648628687, 0.21409262526446268, 0.2874730453069136, 0.3564156907769301, 0.419790835921279, 0.47663300695359484, 0.52617125521895, 0.5678541913642806, 0.6013690848754877, 0.6266544860748334, 0.6439059946500449, 0.6535749757953362, 0.6563602076137612, 0.6531926269444646, 0.6452135205922525, 0.6337466804926754, 0.62026520028624, 0.6063537330539823, 0.5936671519486134, 0.583886654009495, 0.5786744200266045, 0.5796279880157208, 0.5882355134769515, 0.6058330756495919, 0.6335651457058442, 0.6723492612351012, 0.7228458531603869, 0.7854340487687583, 0.8601941308079285, 0.9468971711194728, 1.0450021820120663, 1.1536609438464966, 1.271730477672589, 1.3977929419249968, 1.5301825468628103, 1.6670189042397479, 1.806246067013621, 1.9456763688167635, 2.0830380490573606, 2.2160255500323016, 2.3423512998356917, 2.4597977510149844, 2.5662684310239805, 2.659836776976973, 2.7387915737016737, 2.801677889559802, 2.8473325071774798, 2.874912973653809, 2.883919543933574, 2.8742094582391706, 2.846003175707851, 2.799882377273031, 2.7367797467206625, 2.6579607349726366, 2.5649977042183587, 2.459737030858262, 2.344259914887948, 2.220837794218764, 2.091883391812743], [2.000000000000001, 1.8682850094361036, 1.7377182685412609, 1.610776348890632, 1.4898283955614957, 1.3770850872253926, 1.274551292893118, 1.1839835182767928, 1.1068531195884082, 1.044316124040364, 0.9971903377389509, 0.9659402469434345, 0.950670032070562, 0.9511248199133449, 0.9667001030453626, 0.9964590610873088, 1.039157331151341, 1.0932745989052486, 1.1570522215788401, 1.2285359537427774, 1.3056227292110387, 1.3861103607672227, 1.467748955767338, 1.548292811510631, 1.625551550349971, 1.6974392808435292, 1.7620206270933279, 1.8175525523118492, 1.862521012454118, 1.895671608663897, 1.9160335599584843, 1.9229364861854468, 1.916019671609594, 1.895233667031947, 1.860834278438624, 1.8133691781075427, 1.7536575552108433, 1.6827633927666994, 1.6019631121324684, 1.5127084613030346, 1.41658563578255, 1.3152717080029082, 1.2104895010728565, 1.1039620736499174, 0.9973679842477039, 0.8922984753753767, 0.7902176613420431, 0.6924267198491076, 0.6000329788174413, 0.5139246590543276, 0.4347518837087387, 0.3629144008106023, 0.29855628972809617, 0.24156774056072952, 0.19159381192176647, 0.14804989189739814, 0.11014341376919522, 0.0769012167261156, 0.047201796346000184, 0.019811563763794653, -0.006575870661040576, -0.033298451112878345, -0.06168357988930768, -0.09300630497914109, -0.12844891856052393, -0.16906305707992145, -0.21573532928103517, -0.2691574078403051, -0.32980140541937614, -0.3979012198606036, -0.4734403793621714, -0.5561467506582957, -0.6454942957349123, -0.7407118799175612, -0.8407989508968808, -0.9445477290492291, -1.0505713788099877, -1.157337473199792, -1.2632059229044605, -1.3664704211641971, -1.4654023592217962, -1.5582960967115953, -1.6435144289871344, -1.719533080135049, -1.7849830667268016, -1.8386898229007396, -1.8797080510947568, -1.9073513629076275, -1.921215898734072, -1.9211972599688287, -1.9075002501526457, -1.8806410974396262, -1.8414420158585059, -1.7910181524419728, -1.7307571567074045, -1.6622917934818466, -1.5874661950782254, -1.508296509977559, -1.426926848416448, -1.3455815470181622, -1.2665148717614485, -1.1919593486780764, -1.1240739528948942, -1.0648933978872779, -1.0162797477220762, -0.9798775260235788, -0.9570734175169224, -0.9489615531250433, -0.9563152402204204, -0.9795658488710619, -1.0187893964125874, -1.0737011905070435, -1.1436586994382436, -1.2276726223996812, -1.324425936728794, -1.432300508206471, -1.5494106693307343, -1.6736430033157654, -1.8027014225470426, -1.934156502984097, -2.0654979336576735, -2.194188865460704, -2.3177208977183756, -2.4336684256589414, -2.539741087271326, -2.6338330937510053, -2.7140683026834354, -2.7788399954603262, -2.8268444476640324, -2.857107530176681, -2.869003745929343, -2.8622672884173284, -2.8369948989436153, -2.7936404953553784, -2.733001741033374, -2.656198914305579, -2.5646466206285203, -2.460019058388316, -2.3442096999359507, -2.219286378847058, -2.0874428792756863, -1.9509482011513084, -1.8120947240139378, -1.6731465113714574, -1.5362889862133073, -1.4035811670905047, -1.2769115840757146, -1.1579588967623133, -1.0481581147228956, -0.9486731776038649, -0.8603764908857222, -0.7838358383252563, -0.7193089075868953, -0.6667454761620017, -0.6257971150739307, -0.5958340827741821, -0.5759689056289834, -0.5650859788187027, -0.5618763763227146, -0.5648769344959718, -0.5725125735862389, -0.5831407478136712, -0.5950968690939944, -0.6067395331829778, -0.6164943902707154, -0.6228955444384502, -0.6246234367591292, -0.6205382633289123, -0.6097080996627084, -0.5914310435863066, -0.5652508464155122, -0.5309656728128332, -0.4886298089205055, -0.43854832164009677, -0.38126485462290116, -0.31754292403062323, -0.24834124493701706, -0.17478377313093835, -0.09812528316559678, -0.01971341834518755, 0.05905176094738815, 0.13675963988628162, 0.21203119585578264, 0.2835602948783814, 0.3501530254178828, 0.41076400758794995, 0.46452869354399146, 0.5107907779410836, 0.5491239632035346, 0.5793474697981009, 0.6015348430632946, 0.6160157813483064, 0.6233708908814278, 0.6244194563522338, 0.6202004980084033, 0.6119475615298624, 0.6010578515962632, 0.5890564697203421, 0.5775566477621689, 0.5682169772156453, 0.5626967180688711, 0.5626103276043478, 0.5694823774212103, 0.5847040254418048, 0.6094921786570251, 0.644852422554853, 0.691546705971864, 0.7500666576036421, 0.8206132753387513, 0.9030835752431616, 0.9970646172067864, 1.101835143154574, 1.2163748757950597, 1.3393813357838389, 1.4692938476366213, 1.6043242244022777, 1.7424934524980966, 1.881673545434192, 2.019633602243851, 2.1540889966407493, 2.282752539029301, 2.4033863976512815, 2.5138535388224574, 2.6121674501337266, 2.6965389446531876, 2.7654189078139333, 2.8175359403242126, 2.8519279679163563, 2.867967029244014, 2.865376613357637, 2.844241094062548, 2.8050069958260155, 2.748476020195102, 2.6757899581855646, 2.588407808013888, 2.488075604138452, 2.376789638294705, 2.2567539117849393, 2.130332796838011, 1.9999999999999984]]}],\n",
+       "                        {\"scene\": {\"xaxis\": {\"backgroundcolor\": \"rgb(230, 230,230)\", \"gridcolor\": \"rgb(255, 255, 255)\", \"showbackground\": true, \"zerolinecolor\": \"rgb(255, 255, 255)\"}, \"yaxis\": {\"backgroundcolor\": \"rgb(230, 230,230)\", \"gridcolor\": \"rgb(255, 255, 255)\", \"showbackground\": true, \"zerolinecolor\": \"rgb(255, 255, 255)\"}, \"zaxis\": {\"backgroundcolor\": \"rgb(230, 230,230)\", \"gridcolor\": \"rgb(255, 255, 255)\", \"showbackground\": true, \"zerolinecolor\": \"rgb(255, 255, 255)\"}}, \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Parametric Plot\"}},\n",
+       "                        {\"responsive\": true}\n",
+       "                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('284a1e3b-8dc4-43e6-b7b6-ac7793851bb4');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })\n",
+       "                };\n",
+       "                });\n",
+       "            </script>\n",
+       "        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import chart_studio.plotly as py\n",
+    "import plotly.graph_objects as go\n",
+    "\n",
+    "import numpy as np\n",
+    "\n",
+    "s = np.linspace(0, 2 * np.pi, 240)\n",
+    "t = np.linspace(0, np.pi, 240)\n",
+    "tGrid, sGrid = np.meshgrid(s, t)\n",
+    "\n",
+    "r = 2 + np.sin(7 * sGrid + 5 * tGrid)  # r = 2 + sin(7s+5t)\n",
+    "x = r * np.cos(sGrid) * np.sin(tGrid)  # x = r*cos(s)*sin(t)\n",
+    "y = r * np.sin(sGrid) * np.sin(tGrid)  # y = r*sin(s)*sin(t)\n",
+    "z = r * np.cos(tGrid)                  # z = r*cos(t)\n",
+    "\n",
+    "surface = go.Surface(x=x, y=y, z=z)\n",
+    "data = [surface]\n",
+    "\n",
+    "layout = go.Layout(\n",
+    "    title='Parametric Plot',\n",
+    "    scene=dict(\n",
+    "        xaxis=dict(\n",
+    "            gridcolor='rgb(255, 255, 255)',\n",
+    "            zerolinecolor='rgb(255, 255, 255)',\n",
+    "            showbackground=True,\n",
+    "            backgroundcolor='rgb(230, 230,230)'\n",
+    "        ),\n",
+    "        yaxis=dict(\n",
+    "            gridcolor='rgb(255, 255, 255)',\n",
+    "            zerolinecolor='rgb(255, 255, 255)',\n",
+    "            showbackground=True,\n",
+    "            backgroundcolor='rgb(230, 230,230)'\n",
+    "        ),\n",
+    "        zaxis=dict(\n",
+    "            gridcolor='rgb(255, 255, 255)',\n",
+    "            zerolinecolor='rgb(255, 255, 255)',\n",
+    "            showbackground=True,\n",
+    "            backgroundcolor='rgb(230, 230,230)'\n",
+    "        )\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "fig = go.Figure(data=data, layout=layout)\n",
+    "iplot(fig, filename='jupyter-parametric_plot')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/empty.ipynb b/empty.ipynb
new file mode 100644
index 000000000..e69de29bb
diff --git a/iplot_display_dupes.ipynb b/iplot_display_dupes.ipynb
new file mode 100644
index 000000000..bd4da8582
--- /dev/null
+++ b/iplot_display_dupes.ipynb
@@ -0,0 +1,796 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import ipywidgets\n",
+    "import plotly.graph_objs as go\n",
+    "from plotly.offline import iplot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "linkText": "Export to plot.ly",
+        "plotlyServerURL": "https://plot.ly",
+        "showLink": false
+       },
+       "data": [
+        {
+         "orientation": "h",
+         "type": "bar",
+         "uid": "a72b34d2-0024-4ead-ad82-7e7d2af7f6ea",
+         "x": [
+          0,
+          1,
+          2,
+          3,
+          4
+         ],
+         "y": [
+          0,
+          1,
+          2,
+          3,
+          4
+         ]
+        }
+       ],
+       "layout": {
+        "autosize": true,
+        "bargap": 0.1,
+        "hovermode": "y",
+        "margin": {
+         "l": 200,
+         "t": 35
+        },
+        "template": {
+         "data": {
+          "bar": [
+           {
+            "marker": {
+             "line": {
+              "color": "rgb(237,237,237)",
+              "width": 0.5
+             }
+            },
+            "type": "bar"
+           }
+          ],
+          "barpolar": [
+           {
+            "marker": {
+             "line": {
+              "color": "rgb(237,237,237)",
+              "width": 0.5
+             }
+            },
+            "type": "barpolar"
+           }
+          ],
+          "carpet": [
+           {
+            "aaxis": {
+             "endlinecolor": "rgb(51,51,51)",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "rgb(51,51,51)"
+            },
+            "baxis": {
+             "endlinecolor": "rgb(51,51,51)",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "rgb(51,51,51)"
+            },
+            "type": "carpet"
+           }
+          ],
+          "choropleth": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "tickcolor": "rgb(237,237,237)",
+             "ticklen": 6,
+             "ticks": "inside"
+            },
+            "type": "choropleth"
+           }
+          ],
+          "contour": [
+           {
+            "autocolorscale": true,
+            "colorbar": {
+             "outlinewidth": 0,
+             "tickcolor": "rgb(237,237,237)",
+             "ticklen": 6,
+             "ticks": "inside"
+            },
+            "type": "contour"
+           }
+          ],
+          "contourcarpet": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "tickcolor": "rgb(237,237,237)",
+             "ticklen": 6,
+             "ticks": "inside"
+            },
+            "type": "contourcarpet"
+           }
+          ],
+          "heatmap": [
+           {
+            "autocolorscale": true,
+            "colorbar": {
+             "outlinewidth": 0,
+             "tickcolor": "rgb(237,237,237)",
+             "ticklen": 6,
+             "ticks": "inside"
+            },
+            "type": "heatmap"
+           }
+          ],
+          "heatmapgl": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "tickcolor": "rgb(237,237,237)",
+             "ticklen": 6,
+             "ticks": "inside"
+            },
+            "type": "heatmapgl"
+           }
+          ],
+          "histogram": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "tickcolor": "rgb(237,237,237)",
+              "ticklen": 6,
+              "ticks": "inside"
+             }
+            },
+            "type": "histogram"
+           }
+          ],
+          "histogram2d": [
+           {
+            "autocolorscale": true,
+            "colorbar": {
+             "outlinewidth": 0,
+             "tickcolor": "rgb(237,237,237)",
+             "ticklen": 6,
+             "ticks": "inside"
+            },
+            "type": "histogram2d"
+           }
+          ],
+          "histogram2dcontour": [
+           {
+            "autocolorscale": true,
+            "colorbar": {
+             "outlinewidth": 0,
+             "tickcolor": "rgb(237,237,237)",
+             "ticklen": 6,
+             "ticks": "inside"
+            },
+            "type": "histogram2dcontour"
+           }
+          ],
+          "mesh3d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "tickcolor": "rgb(237,237,237)",
+             "ticklen": 6,
+             "ticks": "inside"
+            },
+            "type": "mesh3d"
+           }
+          ],
+          "parcoords": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "tickcolor": "rgb(237,237,237)",
+              "ticklen": 6,
+              "ticks": "inside"
+             }
+            },
+            "type": "parcoords"
+           }
+          ],
+          "scatter": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "tickcolor": "rgb(237,237,237)",
+              "ticklen": 6,
+              "ticks": "inside"
+             }
+            },
+            "type": "scatter"
+           }
+          ],
+          "scatter3d": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "tickcolor": "rgb(237,237,237)",
+              "ticklen": 6,
+              "ticks": "inside"
+             }
+            },
+            "type": "scatter3d"
+           }
+          ],
+          "scattercarpet": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "tickcolor": "rgb(237,237,237)",
+              "ticklen": 6,
+              "ticks": "inside"
+             }
+            },
+            "type": "scattercarpet"
+           }
+          ],
+          "scattergeo": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "tickcolor": "rgb(237,237,237)",
+              "ticklen": 6,
+              "ticks": "inside"
+             }
+            },
+            "type": "scattergeo"
+           }
+          ],
+          "scattergl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "tickcolor": "rgb(237,237,237)",
+              "ticklen": 6,
+              "ticks": "inside"
+             }
+            },
+            "type": "scattergl"
+           }
+          ],
+          "scattermapbox": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "tickcolor": "rgb(237,237,237)",
+              "ticklen": 6,
+              "ticks": "inside"
+             }
+            },
+            "type": "scattermapbox"
+           }
+          ],
+          "scatterpolar": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "tickcolor": "rgb(237,237,237)",
+              "ticklen": 6,
+              "ticks": "inside"
+             }
+            },
+            "type": "scatterpolar"
+           }
+          ],
+          "scatterpolargl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "tickcolor": "rgb(237,237,237)",
+              "ticklen": 6,
+              "ticks": "inside"
+             }
+            },
+            "type": "scatterpolargl"
+           }
+          ],
+          "scatterternary": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "tickcolor": "rgb(237,237,237)",
+              "ticklen": 6,
+              "ticks": "inside"
+             }
+            },
+            "type": "scatterternary"
+           }
+          ],
+          "surface": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "tickcolor": "rgb(237,237,237)",
+             "ticklen": 6,
+             "ticks": "inside"
+            },
+            "type": "surface"
+           }
+          ],
+          "table": [
+           {
+            "cells": {
+             "fill": {
+              "color": "rgb(237,237,237)"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "header": {
+             "fill": {
+              "color": "rgb(217,217,217)"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "type": "table"
+           }
+          ]
+         },
+         "layout": {
+          "annotationdefaults": {
+           "arrowhead": 0,
+           "arrowwidth": 1
+          },
+          "colorscale": {
+           "sequential": [
+            [
+             0,
+             "rgb(20,44,66)"
+            ],
+            [
+             1,
+             "rgb(90,179,244)"
+            ]
+           ],
+           "sequentialminus": [
+            [
+             0,
+             "rgb(20,44,66)"
+            ],
+            [
+             1,
+             "rgb(90,179,244)"
+            ]
+           ]
+          },
+          "colorway": [
+           "#F8766D",
+           "#A3A500",
+           "#00BF7D",
+           "#00B0F6",
+           "#E76BF3"
+          ],
+          "font": {
+           "color": "rgb(51,51,51)"
+          },
+          "geo": {
+           "bgcolor": "white",
+           "lakecolor": "white",
+           "landcolor": "rgb(237,237,237)",
+           "showlakes": true,
+           "showland": true,
+           "subunitcolor": "white"
+          },
+          "hovermode": "closest",
+          "paper_bgcolor": "white",
+          "plot_bgcolor": "rgb(237,237,237)",
+          "polar": {
+           "angularaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "showgrid": true,
+            "tickcolor": "rgb(51,51,51)",
+            "ticks": "outside"
+           },
+           "bgcolor": "rgb(237,237,237)",
+           "radialaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "showgrid": true,
+            "tickcolor": "rgb(51,51,51)",
+            "ticks": "outside"
+           }
+          },
+          "scene": {
+           "xaxis": {
+            "backgroundcolor": "rgb(237,237,237)",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "showgrid": true,
+            "tickcolor": "rgb(51,51,51)",
+            "ticks": "outside",
+            "zerolinecolor": "white"
+           },
+           "yaxis": {
+            "backgroundcolor": "rgb(237,237,237)",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "showgrid": true,
+            "tickcolor": "rgb(51,51,51)",
+            "ticks": "outside",
+            "zerolinecolor": "white"
+           },
+           "zaxis": {
+            "backgroundcolor": "rgb(237,237,237)",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "showgrid": true,
+            "tickcolor": "rgb(51,51,51)",
+            "ticks": "outside",
+            "zerolinecolor": "white"
+           }
+          },
+          "shapedefaults": {
+           "fillcolor": "black",
+           "line": {
+            "width": 0
+           },
+           "opacity": 0.3
+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "showgrid": true,
+            "tickcolor": "rgb(51,51,51)",
+            "ticks": "outside"
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "showgrid": true,
+            "tickcolor": "rgb(51,51,51)",
+            "ticks": "outside"
+           },
+           "bgcolor": "rgb(237,237,237)",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "showgrid": true,
+            "tickcolor": "rgb(51,51,51)",
+            "ticks": "outside"
+           }
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "showgrid": true,
+           "tickcolor": "rgb(51,51,51)",
+           "ticks": "outside",
+           "zerolinecolor": "white"
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "showgrid": true,
+           "tickcolor": "rgb(51,51,51)",
+           "ticks": "outside",
+           "zerolinecolor": "white"
+          }
+         }
+        },
+        "xaxis": {
+         "autorange": true,
+         "range": [
+          -0.033447777295997905,
+          0.6355077686239602
+         ],
+         "title": {
+          "text": "log"
+         },
+         "type": "log"
+        },
+        "yaxis": {
+         "autorange": true,
+         "range": [
+          -0.5,
+          4.5
+         ],
+         "type": "linear"
+        }
+       }
+      },
+      "image/png": "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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "ea5ba89835034a248324a2c62e0948f2",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Checkbox(value=False, description='%')"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data = [go.Bar(x=[i for i in range(5)], y=[i for i in range(5)], orientation=\"h\")]\n",
+    "layout = go.Layout(\n",
+    "    bargap=0.1,\n",
+    "    xaxis=go.layout.XAxis(type=\"log\", title=\"log\"),\n",
+    "    template=\"ggplot2\",\n",
+    "    hovermode=\"y\",\n",
+    "    margin=dict(l=200, t=35),\n",
+    ")\n",
+    "iplot(go.Figure(data, layout))\n",
+    "\n",
+    "c = ipywidgets.Checkbox(description=\"%\", value=False)\n",
+    "display(c)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "plotly                            3.7.1   \n",
+      "ipython                           7.4.0   \n",
+      "ipython-genutils                  0.2.0   \n"
+     ]
+    }
+   ],
+   "source": [
+    "!pip list installed | grep plotly\n",
+    "!pip list installed | grep ipython"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "JupyterLab v0.35.4\n",
+      "Known labextensions:\n",
+      "   app dir: /Users/valery/.local/share/virtualenvs/arche-lm24e12g/share/jupyter/lab\n",
+      "        @jupyter-widgets/jupyterlab-manager v0.38.1 \u001b[32m enabled \u001b[0m \u001b[32mOK\u001b[0m\n",
+      "        @jupyterlab/plotly-extension v0.18.2 \u001b[32m enabled \u001b[0m \u001b[32mOK\u001b[0m\n",
+      "        plotlywidget v0.8.0 \u001b[32m enabled \u001b[0m \u001b[32mOK\u001b[0m\n"
+     ]
+    }
+   ],
+   "source": [
+    "!jupyter labextension list"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Package                           Version \n",
+      "--------------------------------- --------\n",
+      "alabaster                         0.7.12  \n",
+      "appdirs                           1.4.3   \n",
+      "appnope                           0.1.0   \n",
+      "atomicwrites                      1.3.0   \n",
+      "attrs                             19.1.0  \n",
+      "Babel                             2.6.0   \n",
+      "backcall                          0.1.0   \n",
+      "black                             19.3b0  \n",
+      "bleach                            3.1.0   \n",
+      "boto3                             1.9.126 \n",
+      "botocore                          1.12.126\n",
+      "bumpversion                       0.5.3   \n",
+      "certifi                           2019.3.9\n",
+      "chardet                           3.0.4   \n",
+      "Click                             7.0     \n",
+      "codecov                           2.0.15  \n",
+      "colorama                          0.4.1   \n",
+      "colorlover                        0.3.0   \n",
+      "commonmark                        0.8.1   \n",
+      "coverage                          4.5.3   \n",
+      "cufflinks                         0.15    \n",
+      "decorator                         4.4.0   \n",
+      "defusedxml                        0.5.0   \n",
+      "docutils                          0.14    \n",
+      "entrypoints                       0.3     \n",
+      "fastjsonschema                    2.9     \n",
+      "filelock                          3.0.10  \n",
+      "flake8                            3.7.7   \n",
+      "flake8-bugbear                    19.3.0  \n",
+      "flake8-import-order               0.18.1  \n",
+      "future                            0.17.1  \n",
+      "genson                            1.0.2   \n",
+      "idna                              2.8     \n",
+      "imagesize                         1.1.0   \n",
+      "ipykernel                         5.1.0   \n",
+      "ipython                           7.4.0   \n",
+      "ipython-genutils                  0.2.0   \n",
+      "ipywidgets                        7.4.2   \n",
+      "jedi                              0.13.3  \n",
+      "Jinja2                            2.10    \n",
+      "jmespath                          0.9.4   \n",
+      "jsonpointer                       2.0     \n",
+      "jsonschema                        3.0.1   \n",
+      "jupyter-client                    5.2.4   \n",
+      "jupyter-console                   6.0.0   \n",
+      "jupyter-contrib-core              0.3.3   \n",
+      "jupyter-core                      4.4.0   \n",
+      "jupyter-nbextensions-configurator 0.4.1   \n",
+      "jupyterlab                        0.35.4  \n",
+      "jupyterlab-server                 0.2.0   \n",
+      "livereload                        2.6.0   \n",
+      "Markdown                          3.0.1   \n",
+      "MarkupSafe                        1.1.1   \n",
+      "mccabe                            0.6.1   \n",
+      "mistune                           0.8.4   \n",
+      "mkdocs                            1.0.4   \n",
+      "more-itertools                    7.0.0   \n",
+      "msgpack-python                    0.5.6   \n",
+      "nbconvert                         5.4.1   \n",
+      "nbformat                          4.4.0   \n",
+      "nbsphinx                          0.4.2   \n",
+      "nose                              1.3.7   \n",
+      "notebook                          5.7.8   \n",
+      "numpy                             1.16.2  \n",
+      "packaging                         19.0    \n",
+      "pandas                            0.24.2  \n",
+      "pandocfilters                     1.4.2   \n",
+      "parso                             0.3.4   \n",
+      "pbr                               5.1.3   \n",
+      "perfect-jsonschema                2019.2.6\n",
+      "pexpect                           4.6.0   \n",
+      "pickleshare                       0.7.5   \n",
+      "pip                               19.0.3  \n",
+      "plotly                            3.7.1   \n",
+      "pluggy                            0.9.0   \n",
+      "ply                               3.11    \n",
+      "prometheus-client                 0.6.0   \n",
+      "prompt-toolkit                    2.0.9   \n",
+      "ptyprocess                        0.6.0   \n",
+      "pudb                              2018.1  \n",
+      "py                                1.8.0   \n",
+      "pycodestyle                       2.5.0   \n",
+      "pydoc-markdown                    2.0.5   \n",
+      "pyflakes                          2.1.1   \n",
+      "Pygments                          2.3.1   \n",
+      "pypandoc                          1.4     \n",
+      "pyparsing                         2.3.1   \n",
+      "pyrsistent                        0.14.11 \n",
+      "pytest                            4.4.0   \n",
+      "pytest-cov                        2.6.1   \n",
+      "pytest-mock                       1.10.3  \n",
+      "pytest-pudb                       0.7.0   \n",
+      "pytest-pythonpath                 0.7.3   \n",
+      "python-dateutil                   2.8.0   \n",
+      "pytz                              2018.9  \n",
+      "PyYAML                            5.1     \n",
+      "pyzmq                             18.0.1  \n",
+      "recommonmark                      0.5.0   \n",
+      "requests                          2.21.0  \n",
+      "retrying                          1.3.3   \n",
+      "rfc3987                           1.3.8   \n",
+      "s3transfer                        0.2.0   \n",
+      "scrapinghub                       2.1.0   \n",
+      "Send2Trash                        1.5.0   \n",
+      "setuptools                        40.8.0  \n",
+      "six                               1.12.0  \n",
+      "snowballstemmer                   1.2.1   \n",
+      "Sphinx                            2.0.0   \n",
+      "sphinx-rtd-theme                  0.4.3   \n",
+      "sphinxcontrib-apidoc              0.3.0   \n",
+      "sphinxcontrib-applehelp           1.0.1   \n",
+      "sphinxcontrib-devhelp             1.0.1   \n",
+      "sphinxcontrib-htmlhelp            1.0.1   \n",
+      "sphinxcontrib-jsmath              1.0.1   \n",
+      "sphinxcontrib-qthelp              1.0.2   \n",
+      "sphinxcontrib-serializinghtml     1.1.1   \n",
+      "sphinxcontrib-websupport          1.1.0   \n",
+      "strict-rfc3339                    0.7     \n",
+      "terminado                         0.8.2   \n",
+      "testpath                          0.4.2   \n",
+      "toml                              0.10.0  \n",
+      "tornado                           6.0.2   \n",
+      "tox                               3.8.4   \n",
+      "tqdm                              4.31.1  \n",
+      "traitlets                         4.3.2   \n",
+      "urllib3                           1.24.1  \n",
+      "urwid                             2.0.1   \n",
+      "virtualenv                        16.4.3  \n",
+      "wcwidth                           0.1.7   \n",
+      "webcolors                         1.8.1   \n",
+      "webencodings                      0.5.1   \n",
+      "wheel                             0.33.1  \n",
+      "widgetsnbextension                3.4.2   \n"
+     ]
+    }
+   ],
+   "source": [
+    "!pip list installed"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/notebooks/00.00-Preface.ipynb b/notebooks/00.00-Preface.ipynb
index e9e8d99a8..bc61190e9 100644
--- a/notebooks/00.00-Preface.ipynb
+++ b/notebooks/00.00-Preface.ipynb
@@ -11,12 +11,44 @@
     "*The text is released under the [CC-BY-NC-ND license](https://creativecommons.org/licenses/by-nc-nd/3.0/us/legalcode), and code is released under the [MIT license](https://opensource.org/licenses/MIT). If you find this content useful, please consider supporting the work by [buying the book](http://shop.oreilly.com/product/0636920034919.do)!*"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "'{print $1,$2,$3,$4,$5-1}'\n"
+     ]
+    }
+   ],
+   "source": [
+    "import sys\n",
+    "\n",
+    "def eprint(*args, **kwargs):\n",
+    "    print(*args, file=sys.stderr, **kwargs)\n",
+    "\n",
+    "eprint(\"'{print $1,$2,$3,$4,$5-1}'\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<!--NAVIGATION-->\n",
-    "| [Contents](Index.ipynb) | [IPython: Beyond Normal Python](01.00-IPython-Beyond-Normal-Python.ipynb) >"
+    "Let us try to use \\\\$ sign literally and not as a math formula. Here's an actual math formula on the same line as literal dollor signs. $ a = b + c $ The price of this article is \\\\$10.50 and it's totally worth it."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's see if we can create code block in md --   \n",
+    "\n",
+    "            book a = 2 about doing data science\n",
+    "            which immediately begs the question\n",
+    "    what is data science"
    ]
   },
   {
@@ -190,9 +222,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.1"
+   "version": "3.6.8"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/notebooks/02.09-Structured-Data-NumPy.ipynb b/notebooks/02.09-Structured-Data-NumPy.ipynb
index 7b1f5222a..5785e4d91 100644
--- a/notebooks/02.09-Structured-Data-NumPy.ipynb
+++ b/notebooks/02.09-Structured-Data-NumPy.ipynb
@@ -55,9 +55,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "name = ['Alice', 'Bob', 'Cathy', 'Doug']\n",
@@ -78,9 +76,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "x = np.zeros(4, dtype=int)"
@@ -96,9 +92,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -128,9 +122,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -160,9 +152,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -184,9 +174,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -207,9 +195,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -237,9 +223,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -279,9 +263,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -309,9 +291,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -339,9 +319,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -368,9 +346,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -422,9 +398,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -467,9 +441,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -496,9 +468,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -526,9 +496,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -590,9 +558,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.1"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/notebooks/03.00-Introduction-to-Pandas.ipynb b/notebooks/03.00-Introduction-to-Pandas.ipynb
index 644a1bad0..d9429019b 100644
--- a/notebooks/03.00-Introduction-to-Pandas.ipynb
+++ b/notebooks/03.00-Introduction-to-Pandas.ipynb
@@ -60,14 +60,12 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'0.18.1'"
+       "'0.22.0'"
       ]
      },
      "execution_count": 1,
@@ -90,9 +88,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import pandas as pd"
@@ -154,9 +150,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.1"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/notebooks/03.01-Introducing-Pandas-Objects.ipynb b/notebooks/03.01-Introducing-Pandas-Objects.ipynb
index bdee556f5..140b06f25 100644
--- a/notebooks/03.01-Introducing-Pandas-Objects.ipynb
+++ b/notebooks/03.01-Introducing-Pandas-Objects.ipynb
@@ -39,10 +39,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 2,
+   "metadata": {},
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -62,9 +60,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -97,9 +93,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -126,9 +120,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -155,9 +147,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -177,9 +167,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -226,9 +214,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -261,9 +247,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -290,9 +274,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -318,9 +300,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -353,9 +333,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -394,9 +372,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -423,9 +399,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -472,9 +446,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -504,9 +476,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -536,9 +506,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -568,9 +536,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -622,9 +588,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -659,9 +623,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -735,9 +697,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -764,9 +724,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -804,9 +762,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -859,9 +815,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -930,9 +884,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -994,9 +946,7 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1055,9 +1005,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1133,9 +1081,7 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1199,39 +1145,48 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 3,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "array([(0, 0.0), (0, 0.0), (0, 0.0)], \n",
+       "array([(0, 0.), (0, 0.), (0, 0.), ..., (0, 0.), (0, 0.), (0, 0.)],\n",
        "      dtype=[('A', '<i8'), ('B', '<f8')])"
       ]
      },
-     "execution_count": 28,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "A = np.zeros(3, dtype=[('A', 'i8'), ('B', 'f8')])\n",
+    "A = np.zeros(3000000, dtype=[('A', 'i8'), ('B', 'f8')])\n",
     "A"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 4,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -1256,18 +1211,369 @@
        "      <td>0</td>\n",
        "      <td>0.0</td>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999970</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999971</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999972</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999973</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999974</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999975</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999976</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999977</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999978</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999979</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999980</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999981</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999982</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999983</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999984</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999985</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999986</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999987</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999988</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999989</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999990</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999991</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999992</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999993</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999994</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999995</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999996</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999997</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999998</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999999</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
+       "<p>3000000 rows × 2 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "   A    B\n",
-       "0  0  0.0\n",
-       "1  0  0.0\n",
-       "2  0  0.0"
+       "         A    B\n",
+       "0        0  0.0\n",
+       "1        0  0.0\n",
+       "2        0  0.0\n",
+       "3        0  0.0\n",
+       "4        0  0.0\n",
+       "5        0  0.0\n",
+       "6        0  0.0\n",
+       "7        0  0.0\n",
+       "8        0  0.0\n",
+       "9        0  0.0\n",
+       "10       0  0.0\n",
+       "11       0  0.0\n",
+       "12       0  0.0\n",
+       "13       0  0.0\n",
+       "14       0  0.0\n",
+       "15       0  0.0\n",
+       "16       0  0.0\n",
+       "17       0  0.0\n",
+       "18       0  0.0\n",
+       "19       0  0.0\n",
+       "20       0  0.0\n",
+       "21       0  0.0\n",
+       "22       0  0.0\n",
+       "23       0  0.0\n",
+       "24       0  0.0\n",
+       "25       0  0.0\n",
+       "26       0  0.0\n",
+       "27       0  0.0\n",
+       "28       0  0.0\n",
+       "29       0  0.0\n",
+       "...     ..  ...\n",
+       "2999970  0  0.0\n",
+       "2999971  0  0.0\n",
+       "2999972  0  0.0\n",
+       "2999973  0  0.0\n",
+       "2999974  0  0.0\n",
+       "2999975  0  0.0\n",
+       "2999976  0  0.0\n",
+       "2999977  0  0.0\n",
+       "2999978  0  0.0\n",
+       "2999979  0  0.0\n",
+       "2999980  0  0.0\n",
+       "2999981  0  0.0\n",
+       "2999982  0  0.0\n",
+       "2999983  0  0.0\n",
+       "2999984  0  0.0\n",
+       "2999985  0  0.0\n",
+       "2999986  0  0.0\n",
+       "2999987  0  0.0\n",
+       "2999988  0  0.0\n",
+       "2999989  0  0.0\n",
+       "2999990  0  0.0\n",
+       "2999991  0  0.0\n",
+       "2999992  0  0.0\n",
+       "2999993  0  0.0\n",
+       "2999994  0  0.0\n",
+       "2999995  0  0.0\n",
+       "2999996  0  0.0\n",
+       "2999997  0  0.0\n",
+       "2999998  0  0.0\n",
+       "2999999  0  0.0\n",
+       "\n",
+       "[3000000 rows x 2 columns]"
       ]
      },
-     "execution_count": 29,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1291,9 +1597,7 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1324,9 +1628,7 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1346,9 +1648,7 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1375,9 +1675,7 @@
   {
    "cell_type": "code",
    "execution_count": 33,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1401,9 +1699,7 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "ename": "TypeError",
@@ -1442,9 +1738,7 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "indA = pd.Index([1, 3, 5, 7, 9])\n",
@@ -1454,9 +1748,7 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1476,9 +1768,7 @@
   {
    "cell_type": "code",
    "execution_count": 37,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1498,9 +1788,7 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1550,9 +1838,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.1"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/notebooks/03.02-Data-Indexing-and-Selection.ipynb b/notebooks/03.02-Data-Indexing-and-Selection.ipynb
index 7707be226..90a177199 100644
--- a/notebooks/03.02-Data-Indexing-and-Selection.ipynb
+++ b/notebooks/03.02-Data-Indexing-and-Selection.ipynb
@@ -60,9 +60,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -89,9 +87,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -118,9 +114,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -140,9 +134,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -162,9 +154,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -192,9 +182,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -242,9 +230,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -268,9 +254,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -293,9 +277,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -318,9 +300,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -361,9 +341,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -387,9 +365,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -410,9 +386,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -445,9 +419,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -467,9 +439,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -498,9 +468,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -520,9 +488,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -575,9 +541,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -656,9 +620,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -690,9 +652,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -724,9 +684,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -755,9 +713,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -786,9 +742,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -877,9 +831,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -911,9 +863,7 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -986,9 +936,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1015,9 +963,7 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1053,9 +999,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1115,9 +1059,7 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1179,9 +1121,7 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1244,9 +1184,7 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1300,9 +1238,7 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1391,9 +1327,7 @@
   {
    "cell_type": "code",
    "execution_count": 33,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1450,9 +1384,7 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1509,9 +1441,7 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1591,9 +1521,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.1"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/notebooks/03.03-Operations-in-Pandas.ipynb b/notebooks/03.03-Operations-in-Pandas.ipynb
index ac4b1eb37..4be291faf 100644
--- a/notebooks/03.03-Operations-in-Pandas.ipynb
+++ b/notebooks/03.03-Operations-in-Pandas.ipynb
@@ -51,9 +51,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import pandas as pd\n",
@@ -63,9 +61,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -91,14 +87,25 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -163,9 +170,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -196,9 +201,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -285,9 +288,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "area = pd.Series({'Alaska': 1723337, 'Texas': 695662,\n",
@@ -306,9 +307,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -339,9 +338,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -369,9 +366,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -405,9 +400,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -440,9 +433,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -491,9 +482,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -552,9 +541,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -620,9 +607,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -708,9 +693,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -733,9 +716,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -766,9 +747,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -837,9 +816,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -907,9 +884,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -932,9 +907,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1025,9 +998,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.1"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/notebooks/03.04-Missing-Values.ipynb b/notebooks/03.04-Missing-Values.ipynb
index 6cbef56f9..420114184 100644
--- a/notebooks/03.04-Missing-Values.ipynb
+++ b/notebooks/03.04-Missing-Values.ipynb
@@ -101,9 +101,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -132,9 +130,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -166,9 +162,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "ename": "TypeError",
@@ -206,9 +200,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -238,9 +230,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -260,9 +250,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -289,9 +277,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -318,9 +304,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -356,9 +340,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -390,9 +372,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -415,9 +395,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -499,9 +477,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -532,9 +508,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -574,9 +548,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -606,9 +578,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -678,9 +648,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -730,9 +698,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -792,9 +758,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -856,9 +820,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -922,9 +884,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -989,9 +949,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1024,9 +982,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1058,9 +1014,7 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1093,9 +1047,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1130,9 +1082,7 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1193,9 +1143,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1286,9 +1234,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.1"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/notebooks/03.05-Hierarchical-Indexing.ipynb b/notebooks/03.05-Hierarchical-Indexing.ipynb
index 43e3475c4..9dc32bdef 100644
--- a/notebooks/03.05-Hierarchical-Indexing.ipynb
+++ b/notebooks/03.05-Hierarchical-Indexing.ipynb
@@ -2,10 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "<!--BOOK_INFORMATION-->\n",
     "<img align=\"left\" style=\"padding-right:10px;\" src=\"figures/PDSH-cover-small.png\">\n",
@@ -16,10 +13,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "<!--NAVIGATION-->\n",
     "< [Handling Missing Data](03.04-Missing-Values.ipynb) | [Contents](Index.ipynb) | [Combining Datasets: Concat and Append](03.06-Concat-And-Append.ipynb) >"
@@ -34,10 +28,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Up to this point we've been focused primarily on one-dimensional and two-dimensional data, stored in Pandas ``Series`` and ``DataFrame`` objects, respectively.\n",
     "Often it is useful to go beyond this and store higher-dimensional data–that is, data indexed by more than one or two keys.\n",
@@ -53,9 +44,7 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -65,10 +54,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## A Multiply Indexed Series\n",
     "\n",
@@ -78,10 +64,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### The bad way\n",
     "\n",
@@ -92,11 +75,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -128,10 +107,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "With this indexing scheme, you can straightforwardly index or slice the series based on this multiple index:"
    ]
@@ -139,11 +115,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -166,10 +138,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "But the convenience ends there. For example, if you need to select all values from 2010, you'll need to do some messy (and potentially slow) munging to make it happen:"
    ]
@@ -177,11 +146,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -203,20 +168,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This produces the desired result, but is not as clean (or as efficient for large datasets) as the slicing syntax we've grown to love in Pandas."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### The Better Way: Pandas MultiIndex\n",
     "Fortunately, Pandas provides a better way.\n",
@@ -227,11 +186,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -252,10 +207,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Notice that the ``MultiIndex`` contains multiple *levels* of indexing–in this case, the state names and the years, as well as multiple *labels* for each data point which encode these levels.\n",
     "\n",
@@ -265,11 +217,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -295,10 +243,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Here the first two columns of the ``Series`` representation show the multiple index values, while the third column shows the data.\n",
     "Notice that some entries are missing in the first column: in this multi-index representation, any blank entry indicates the same value as the line above it."
@@ -306,10 +251,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Now to access all data for which the second index is 2010, we can simply use the Pandas slicing notation:"
    ]
@@ -317,11 +259,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -343,10 +281,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The result is a singly indexed array with just the keys we're interested in.\n",
     "This syntax is much more convenient (and the operation is much more efficient!) than the home-spun tuple-based multi-indexing solution that we started with.\n",
@@ -355,10 +290,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### MultiIndex as extra dimension\n",
     "\n",
@@ -369,11 +301,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -426,10 +354,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Naturally, the ``stack()`` method provides the opposite operation:"
    ]
@@ -437,11 +362,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -466,10 +387,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Seeing this, you might wonder why would we would bother with hierarchical indexing at all.\n",
     "The reason is simple: just as we were able to use multi-indexing to represent two-dimensional data within a one-dimensional ``Series``, we can also use it to represent data of three or more dimensions in a ``Series`` or ``DataFrame``.\n",
@@ -479,11 +397,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -561,10 +475,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "In addition, all the ufuncs and other functionality discussed in [Operating on Data in Pandas](03.03-Operations-in-Pandas.ipynb) work with hierarchical indices as well.\n",
     "Here we compute the fraction of people under 18 by year, given the above data:"
@@ -573,11 +484,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -630,20 +537,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This allows us to easily and quickly manipulate and explore even high-dimensional data."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Methods of MultiIndex Creation\n",
     "\n",
@@ -653,11 +554,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -721,10 +618,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The work of creating the ``MultiIndex`` is done in the background.\n",
     "\n",
@@ -734,11 +628,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -769,20 +659,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Nevertheless, it is sometimes useful to explicitly create a ``MultiIndex``; we'll see a couple of these methods here."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Explicit MultiIndex constructors\n",
     "\n",
@@ -793,11 +677,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -817,10 +697,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "You can construct it from a list of tuples giving the multiple index values of each point:"
    ]
@@ -828,11 +705,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -852,10 +725,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "You can even construct it from a Cartesian product of single indices:"
    ]
@@ -863,11 +733,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -887,10 +753,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Similarly, you can construct the ``MultiIndex`` directly using its internal encoding by passing ``levels`` (a list of lists containing available index values for each level) and ``labels`` (a list of lists that reference these labels):"
    ]
@@ -898,11 +761,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -923,20 +782,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Any of these objects can be passed as the ``index`` argument when creating a ``Series`` or ``Dataframe``, or be passed to the ``reindex`` method of an existing ``Series`` or ``DataFrame``."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### MultiIndex level names\n",
     "\n",
@@ -947,11 +800,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -978,20 +827,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "With more involved datasets, this can be a useful way to keep track of the meaning of various index values."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### MultiIndex for columns\n",
     "\n",
@@ -1002,11 +845,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1119,10 +958,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Here we see where the multi-indexing for both rows and columns can come in *very* handy.\n",
     "This is fundamentally four-dimensional data, where the dimensions are the subject, the measurement type, the year, and the visit number.\n",
@@ -1132,11 +968,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1204,20 +1036,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "For complicated records containing multiple labeled measurements across multiple times for many subjects (people, countries, cities, etc.) use of hierarchical rows and columns can be extremely convenient!"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Indexing and Slicing a MultiIndex\n",
     "\n",
@@ -1227,10 +1053,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Multiply indexed Series\n",
     "\n",
@@ -1240,11 +1063,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1270,10 +1089,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can access single elements by indexing with multiple terms:"
    ]
@@ -1281,11 +1097,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1304,10 +1116,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The ``MultiIndex`` also supports *partial indexing*, or indexing just one of the levels in the index.\n",
     "The result is another ``Series``, with the lower-level indices maintained:"
@@ -1316,11 +1125,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1342,10 +1147,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Partial slicing is available as well, as long as the ``MultiIndex`` is sorted (see discussion in [Sorted and Unsorted Indices](#Sorted-and-unsorted-indices)):"
    ]
@@ -1353,11 +1155,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1381,10 +1179,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "With sorted indices, partial indexing can be performed on lower levels by passing an empty slice in the first index:"
    ]
@@ -1392,11 +1187,7 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1419,10 +1210,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Other types of indexing and selection (discussed in [Data Indexing and Selection](03.02-Data-Indexing-and-Selection.ipynb)) work as well; for example, selection based on Boolean masks:"
    ]
@@ -1430,11 +1218,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1457,10 +1241,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Selection based on fancy indexing also works:"
    ]
@@ -1468,11 +1249,7 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1496,10 +1273,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Multiply indexed DataFrames\n",
     "\n",
@@ -1510,11 +1284,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1614,10 +1384,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Remember that columns are primary in a ``DataFrame``, and the syntax used for multiply indexed ``Series`` applies to the columns.\n",
     "For example, we can recover Guido's heart rate data with a simple operation:"
@@ -1626,11 +1393,7 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1654,10 +1417,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Also, as with the single-index case, we can use the ``loc``, ``iloc``, and ``ix`` indexers introduced in [Data Indexing and Selection](03.02-Data-Indexing-and-Selection.ipynb). For example:"
    ]
@@ -1665,11 +1425,7 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1730,10 +1486,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "These indexers provide an array-like view of the underlying two-dimensional data, but each individual index in ``loc`` or ``iloc`` can be passed a tuple of multiple indices. For example:"
    ]
@@ -1741,11 +1494,7 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1769,10 +1518,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Working with slices within these index tuples is not especially convenient; trying to create a slice within a tuple will lead to a syntax error:"
    ]
@@ -1780,11 +1526,7 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "ename": "SyntaxError",
@@ -1801,10 +1543,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "You could get around this by building the desired slice explicitly using Python's built-in ``slice()`` function, but a better way in this context is to use an ``IndexSlice`` object, which Pandas provides for precisely this situation.\n",
     "For example:"
@@ -1813,11 +1552,7 @@
   {
    "cell_type": "code",
    "execution_count": 33,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1886,20 +1621,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "There are so many ways to interact with data in multiply indexed ``Series`` and ``DataFrame``s, and as with many tools in this book the best way to become familiar with them is to try them out!"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Rearranging Multi-Indices\n",
     "\n",
@@ -1910,10 +1639,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Sorted and unsorted indices\n",
     "\n",
@@ -1927,11 +1653,7 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1960,10 +1682,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "If we try to take a partial slice of this index, it will result in an error:"
    ]
@@ -1971,11 +1690,7 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1996,10 +1711,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Although it is not entirely clear from the error message, this is the result of the MultiIndex not being sorted.\n",
     "For various reasons, partial slices and other similar operations require the levels in the ``MultiIndex`` to be in sorted (i.e., lexographical) order.\n",
@@ -2010,11 +1722,7 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2041,10 +1749,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "With the index sorted in this way, partial slicing will work as expected:"
    ]
@@ -2052,11 +1757,7 @@
   {
    "cell_type": "code",
    "execution_count": 37,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2080,10 +1781,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Stacking and unstacking indices\n",
     "\n",
@@ -2093,11 +1791,7 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2154,11 +1848,7 @@
   {
    "cell_type": "code",
    "execution_count": 39,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2216,10 +1906,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The opposite of ``unstack()`` is ``stack()``, which here can be used to recover the original series:"
    ]
@@ -2227,11 +1914,7 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2257,10 +1940,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Index setting and resetting\n",
     "\n",
@@ -2272,11 +1952,7 @@
   {
    "cell_type": "code",
    "execution_count": 41,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2354,10 +2030,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Often when working with data in the real world, the raw input data looks like this and it's useful to build a ``MultiIndex`` from the column values.\n",
     "This can be done with the ``set_index`` method of the ``DataFrame``, which returns a multiply indexed ``DataFrame``:"
@@ -2366,11 +2039,7 @@
   {
    "cell_type": "code",
    "execution_count": 42,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2443,20 +2112,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "In practice, I find this type of reindexing to be one of the more useful patterns when encountering real-world datasets."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Data Aggregations on Multi-Indices\n",
     "\n",
@@ -2469,11 +2132,7 @@
   {
    "cell_type": "code",
    "execution_count": 43,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2573,10 +2232,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Perhaps we'd like to average-out the measurements in the two visits each year. We can do this by naming the index level we'd like to explore, in this case the year:"
    ]
@@ -2584,11 +2240,7 @@
   {
    "cell_type": "code",
    "execution_count": 44,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2664,10 +2316,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "By further making use of the ``axis`` keyword, we can take the mean among levels on the columns as well:"
    ]
@@ -2675,11 +2324,7 @@
   {
    "cell_type": "code",
    "execution_count": 45,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2731,10 +2376,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Thus in two lines, we've been able to find the average heart rate and temperature measured among all subjects in all visits each year.\n",
     "This syntax is actually a short cut to the ``GroupBy`` functionality, which we will discuss in [Aggregation and Grouping](03.08-Aggregation-and-Grouping.ipynb).\n",
@@ -2743,10 +2385,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Aside: Panel Data\n",
     "\n",
@@ -2764,10 +2403,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "<!--NAVIGATION-->\n",
     "< [Handling Missing Data](03.04-Missing-Values.ipynb) | [Contents](Index.ipynb) | [Combining Datasets: Concat and Append](03.06-Concat-And-Append.ipynb) >"
@@ -2791,9 +2427,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.1"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/notebooks/05.14-Image-Features.ipynb b/notebooks/05.14-Image-Features.ipynb
index b745b3079..4652d6559 100644
--- a/notebooks/05.14-Image-Features.ipynb
+++ b/notebooks/05.14-Image-Features.ipynb
@@ -47,9 +47,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "%matplotlib inline\n",
@@ -78,16 +76,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 3,
+   "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/skimage/feature/_hog.py:119: skimage_deprecation: Default value of `block_norm`==`L1` is deprecated and will be changed to `L2-Hys` in v0.15\n",
+      "  'be changed to `L2-Hys` in v0.15', skimage_deprecation)\n"
+     ]
+    },
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAqsAAADlCAYAAAB01r7EAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIxrRiEY0oq8t/X+gMq/LscTgkgAAAABJRU5ErkJggg==\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1023a1278>"
+       "<matplotlib.figure.Figure at 0x1c17da06a0>"
       ]
      },
      "metadata": {},
@@ -107,6 +111,193 @@
     "ax[0].set_title('input image')\n",
     "\n",
     "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');\n",
+    "\n",
+    "ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');\n",
+    "\n",
+    "\n",
+    "ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');\n",
+    "\n",
+    "\n",
+    "ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');\n",
+    "ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');\n",
+    "\n",
+    "ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
+    "ax[1].set_title('visualization of HOG features');ax[0].imshow(image, cmap='gray')\n",
+    "ax[0].set_title('input image')\n",
+    "\n",
+    "ax[1].imshow(hog_vis)\n",
     "ax[1].set_title('visualization of HOG features');"
    ]
   },
@@ -141,18 +332,107078 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 4,
+   "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading LFW metadata: https://ndownloader.figshare.com/files/5976012\n",
+      "Downloading LFW metadata: https://ndownloader.figshare.com/files/5976009\n",
+      "Downloading LFW metadata: https://ndownloader.figshare.com/files/5976006\n",
+      "Downloading LFW data (~200MB): https://ndownloader.figshare.com/files/5976015\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:184: DeprecationWarning: `imread` is deprecated!\n",
+      "`imread` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``imageio.imread`` instead.\n",
+      "  img = imread(file_path)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/datasets/lfw.py:193: DeprecationWarning: `imresize` is deprecated!\n",
+      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
+      "Use ``skimage.transform.resize`` instead.\n",
+      "  face = imresize(face, resize)\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
        "(13233, 62, 47)"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -184,10 +107435,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 5,
+   "metadata": {},
    "outputs": [],
    "source": [
     "from skimage import data, transform\n",
@@ -201,18 +107450,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 6,
+   "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/skimage/transform/_warps.py:84: UserWarning: The default mode, 'constant', will be changed to 'reflect' in skimage 0.15.\n",
+      "  warn(\"The default mode, 'constant', will be changed to 'reflect' in \"\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
        "(30000, 62, 47)"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -245,24 +107500,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAdsAAAFVCAYAAACnwEWcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/wB45kixx1m61wAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x11a5d7710>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
-    "fig, ax = plt.subplots(6, 10)\n",
+    "fig, ax = plt.subplots(6, 100)\n",
     "for i, axi in enumerate(ax.flat):\n",
     "    axi.imshow(negative_patches[500 * i], cmap='gray')\n",
     "    axi.axis('off')"
@@ -288,9 +107530,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "from itertools import chain\n",
@@ -304,9 +107544,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -346,9 +107584,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -379,9 +107615,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -405,9 +107639,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -434,9 +107666,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -470,9 +107700,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -505,9 +107733,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -546,9 +107772,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -577,9 +107801,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -682,9 +107904,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.1"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/notebooks/06.00-Figure-Code.ipynb b/notebooks/06.00-Figure-Code.ipynb
index edacd85a9..00ea32328 100644
--- a/notebooks/06.00-Figure-Code.ipynb
+++ b/notebooks/06.00-Figure-Code.ipynb
@@ -2,10 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "<!--BOOK_INFORMATION-->\n",
     "<img align=\"left\" style=\"padding-right:10px;\" src=\"figures/PDSH-cover-small.png\">\n",
@@ -16,10 +13,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "<!--NAVIGATION-->\n",
     "< [Further Machine Learning Resources](05.15-Learning-More.ipynb) | [Contents](Index.ipynb) |"
@@ -34,10 +28,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Many of the figures used throughout this text are created in-place by code that appears in print.\n",
     "In a few cases, however, the required code is long enough (or not immediately relevant enough) that we instead put it here for reference."
@@ -45,12 +36,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 23,
+   "metadata": {},
    "outputs": [],
    "source": [
     "%matplotlib inline\n",
@@ -61,12 +48,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 24,
+   "metadata": {},
    "outputs": [],
    "source": [
     "import os\n",
@@ -76,10 +59,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Broadcasting\n",
     "\n",
@@ -88,18 +68,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 25,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAb4AAAFSCAYAAACNC7oQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x115e7f908>"
+       "<matplotlib.figure.Figure at 0x10dbfacf8>"
       ]
      },
      "metadata": {},
@@ -298,10 +274,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Aggregation and Grouping\n",
     "\n",
@@ -310,28 +283,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Split-Apply-Combine"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 26,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAmAAAAHSCAYAAABLgXczAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11b1c5f28>"
+       "<matplotlib.figure.Figure at 0x10df19470>"
       ]
      },
      "metadata": {},
@@ -449,22 +415,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## What Is Machine Learning?"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 27,
+   "metadata": {},
    "outputs": [],
    "source": [
     "# common plot formatting for below\n",
@@ -478,10 +437,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Classification Example Figures\n",
     "\n",
@@ -492,12 +448,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 28,
+   "metadata": {},
    "outputs": [],
    "source": [
     "from sklearn.datasets.samples_generator import make_blobs\n",
@@ -522,28 +474,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### Classification Example Figure 1"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 29,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeIAAAGACAYAAABx1WHyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeUAAAF5CAYAAAChlDJaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzt3Xl8XFd9///XmU2jXbIsy6u8xI7tJI6zOPtKSQKUEqBAW5YUWiAUWrpAebQs5XJDgX6hwK9AS2oIhKVQytKyhgQIIXuCncTZvMb7Kln7Ntu95/fHyEayZiTZ0sxcad7Px4NHrLkzOh8Ntt5zzj2LsdYiIiIipRcqdQEiIiKSpVAWEREJCIWyiIhIQCiURUREAkKhLCIiEhAKZRERkYBQKIuIiAREpNQFiJQT13X3Am9zHOeXBW7nI8BKx3HeNEEtLUAG8IDnga8DGx3H8SfRxjJgDxB1HCcz5aJFRD1lkTL3CsdxaoGlwL8A/wDcUdqSRMqXesoiJeK67luAtwGPAm8FuoF3OY5z1/D1+4BHgBcDq4H7gD9zHKfTdd3rgW86jrN4xPfbO/z9IsAHAOO67quAFxzHWT9eLY7j9AA/cl33KPCo67qfdhznWdd1Xw78M3AW0APc4TjOR4Zfdv/wf7td1wW4EWgDvgSsByxwN/CXjuN0n/47JFJ+1FMWKa3LgO3AXOCTwB2u65oR1/8U+HNgIdlh5s9N9A0dx/k58HHgO47j1EwUyKe89nHgIHDN8EMDwzU0AC8H3jkc9ADXDv+3YbidRwADfGK43rXAEuAjk21fpNyppyxSWvscx/kSgOu6XwP+g+x93qPD17/hOM6zw9f/CXjKdd03F7imw8AcAMdx7hvx+NOu634buA74v1wvdBxnF7Br+Mt213U/AziFK1VkdlEoi5TWifDFcZzB4WHgmhHXD4z48z4gSrZXXUiLgE4A13UvI3uv+TwgBlQA3833Qtd155HtzV8D1JIdjesqcL0is4aGr0WCbcmIP7cCaeA42WHlqhMXXNcNA80jnntGx7+5rnsJ2VB+cPihbwE/ApY4jlMP3E52iDpfG58Yfvx8x3HqgDeNeL6ITEA9ZZFge5Prul8H9gK3Ad9zHMdzXXcHEB+eiHUP2YldFSNedwy40XXd0CSXN9WRvUf8b2QnkD0zfKkW6HQcJ+G67qXAG4bbA2gHfGAFsGPE83vITv5aBLzvDH9ukbKknrJIsH0DuJPsMHcc+Gs4OVv6XcCXgUNke84HR7zuxBBzh+u6T4zz/X/sum4f2WHyDwKfAf5sxPV3AbcNP+fDwP+cuOA4ziDwMeAh13W7Xde9HHCBi8gG80+BH5z+jyxSvoy1ZzTKJSIFNrwk6puO43y51LWISHGopywiIhIQCmUREZGA0PC1iIhIQKinLCIiEhAKZRERkYAoyjplY8ytwK0A1dXVF69Zs6YYzYqIiATC5s2bj1trmyd6XtHvKW/YsMFu2rSpqG2KiIiUkjFms7V2w0TP0/C1iIhIQCiURUREAkKhLCIiEhAKZRERkYBQKIuIiASEQllERCQgFMoiIiIBoVAWEREJCIWyiIhIQCiURUREAkKhLCIiEhAKZRERkYBQKIuIiASEQllERCQgFMoiIiIBoVAWEREJCIWyiIhIQCiURUREAkKhLCIiEhAKZRERkYBQKIuIiASEQllERCQgFMoiIiIBoVAWEREJCIWyiIhIQCiURUREAkKhLCIiEhAKZRERkYBQKIuIiASEQllERCQgFMoiIiIBoVAWEREJCIWyiIhIQCiURUREAqIooWyMudUYs8kYs6m9vb0YTYqIiMw4RQlla+1Ga+0Ga+2G5ubmYjQpIiIy42j4WkREJCAUyiIiIgGhUBYREQkIhbKIiEhAKJRFREQCQqEsIiISEAplERGRgFAoi4iIBIRCWUREJCAUyiIiIgGhUBYREQkIhbKIiEhAKJRnuIznk0h7WGtLXYqIiExRpNQFyJkZSGX47f4ujvUnAYiFQ6xbUMfKuTUlrkxERM6UQnkGSqQ97t7WRsrzOdE/TmR8njjYQ8qznNNSW9L6RETkzGj4egbacbyftP+7QD7Bs5Znj/aS8f2S1CUiIlOjUJ6BDnYP4ee5hRwCOgfSRa1HRESmh0J5BjLG5L1mgXEui4hIgCmUZ6Dlc6oI5wleY6CpOlbcgkREZFoolGegs5qqqYpFCJ0SzGFj2LC4gZC6yiIiM5JCeQaKhkPcdPY8Vs2tIRY2hAw0VUW59qwmls2pLnV5IiJyhrQkaoaKRUJctLiBixY3lLoUERGZJuopi4iIBIR6yiLTwFpL11CaobRHQ2WU6pj+aeWS9nz2dg5yrD9JPBJiRVM1c6o0MVHkBP3mEJmirqEUD+zuIJnxMWQ3cWmpqeCq5U1EwxqMOqEvkeYXO9rxrCXjWwywu2OQlXOrdRtGZJh+Y4hMQTLj8aud7QykPDK+Je1bfAvH+pPcv/t4qcsLlAf2dJD0fDLDO99Ysh9gdnUMcKQ3UdriRAJCoSwyBS90DODn2F7Nt9AxkKZnSLurAfQMpelPejmveb5le3t/kSsSCSaFssgUtPUl8fKdmmmgYzBV1HqCajDtjVlXP9JAKlO8YkQCTKEsMgUVkXDea4bs0jWBungEL8+Z3wZorIwWtyCRgNJEL5EpWDm3mgM9Q3h5TghZUBsvckWFdawvwdZjffQmM1THwqyZV8ui+soJX1cdi9BSU8Gx/uSYw1RCxrB2no4bFQH1lEWmZG51jBVzqgiPGJs1ZLc8vXLZnFGPz3Rbj/Xxm90dHOlLMpDyaOtP8dDeTp481D2p11+5rInGyhjhUHYXukjIEDaGS1sbaNSyKBFAPWWRKTHGcPHiBhbVV7KjvZ/BtEdTVYw182qoi8+eIdmhtMfTR3rG9HI937KzfYAVc6qpn2AIOhYJcdPqeXQMpugYSBELh1hUH9eyMZERFMoiU2SMYUFdnAV1s2uoeqQD3UPk6/P71rK3a5D1lfWT+l5NVTGa1DMWyUkfUUVkQhnPH9NLPsECKc8vaj0is1VRQtkYc6sxZpMxZlN7e3sxmhSRaTS3piLv/fFIyNBSU1HkikRmp6KEsrV2o7V2g7V2Q3NzczGaFJFp1Fwdo7Zi7BneBqiIhFjcMPEMbBGZmIavRWRCxhh+b2Uz82vjhAxEQ4awgeaaGDeePY+QmT2zzEVKSRO9RGRSYpEQ1501l6G0R38yQ1UsrNOwRKaZ/kVJXsmMz56OAXoSaWrjEVbMqSYezb+DlZSHymiYSv09ECkIhbLkdKwvwf27O7A2e5JP2MCzR/q4avmcSe3gJCIip0/3lGWMtOdz/+4OMr49uV+xNxzOD+3pJJnJfdqPiIhMjXrKQG8izbNHeznamyQUgmWN1axtqaWiTA8TONA9NM5Vy56OQda0aK9iEZHpVvah3DGY4t6d7Xi+xQJ4sL29j31dg7x0zbxxTwGarQZT3smD6E/lWejXMXsiIgVRnl3BER7f30XmRCAP8y0kMh7PH+srWV2lVBuPEMmzUUTYQIOO2RMRKYiyDuWhtEdvIp3zmm9hb+dgkSsKhsX1lYTzrDs1xrC0sarIFYmIlIeyDmXPt5hxNj3Idyj7bBcOGV60ci4V4RCRkMGQ3UoxGs4+rlN9REQKo6zvKVfHwkRCJu8B9S01s/fUn4k0VsV45XkLONw7RF8iQ3VFJNuDnsL5wL61pDI+0XAosOcMW2s5PpBib9cgnm9ZVB9nUX2ldqwSkaIo61A2xrB+YR2bD/SM6RWHQ4Z1C+pKVFkwhEOGJQ1TH6q21rK1rZ+tx/rI+NnThBbVV7JhcUOgNiPxreXhvZ0c6U2cnOh2oHuIqmgvN5w9b9zZ+H3JDM8e6eVwbwJjoLWhknPn12mTDRE5LWUdygBnNdVgLTx9uJeMtVhrqYlFuLS1UROapsmTh3rYdXxg1Aefg91DdA6m+P01LUQCMhz+wvEBDvcmRo2cZHxLfzLDb/d3cfWKppyv6x5K84sdbaNmrO86PsD+7iFeurqFqtj4wexby872fra395PI+NTEwpw3v45W3bsXKTtlH8oAK+fWsKKpmv5khnDIaD/faZRIe+w83j/mLF4LJDI+ezoHWdVcU5LaTrWtrS/nrQwfONQ7RNrzc95P33Sga8wSMgukMj7PHOnhsqVz8rZpreXBPR0c7U3gDX+LnkSGR/d30Z1Ic/6C+qn8SCIywwSjixIAIWOoi0cVyNOsrT+Z936s59sJNioprkTGz3stZAzJHNfTns/xgVTO11hg/wQ/X/tAimN9yZOBfILnW7Ye62Mord3TRMqJQlkKarzZ7cCY83kLIe35pL38gXtCTUX+D2TWkvP+t29hvB/Rn2AG/97OwbwbtRgMh3qC86FFRApP3UIpqPm1FeTLpUjIsLypumBtt/cn2Xywm+6h7Fr0hsooFy9uoLmmIufzz5tfyyP7usYMYYcNrGiqyrmhSixsqIyGGUjl7tHOrY6NW+N4oW2xY4b9x2OtpXMwzWDaoz4eoS6uOREiM416ylJQ0XCI8xfUjdmMJGSgbniZVSEcH0jy613H6RpKY8kOJXcNpfn1ruMcH0jmfM2ShirWzqslZCBszMn/ttTGuXBRQ87XGGO4cFE94Ry95bAxrF84/j3hRfWVeXdPM0BLbe4PEKfqGUrz4+ePcu+udh7d18nPt7Xxix1tJDT8LTKjqKcsBbempZbqigjPHOmhL5khGgpx1txqzp1fW7D1yk8eGrvMDbIbwjxxqIebzp6X83XrFtSxcm41h3qG8HxLS218wln4SxqqsEvhiUPdpDLZjwCVsTCXLmlkbvX4obqoPk5VLEx/MjOqVxw2sKAuTv0kertpz+eXO9tInXJjumMgxa9fOM5LV8+b8DaCiASDQlmKYklDJUsainMOsz+8AUg+HQMpfGvzTkCrjIZZOff0ZoS3NlaxpKGSgZSHMVAVDU8qCEPGcOOqefz2QBcHe4YwGDCwsql6wl72CXs6B3LOGrdk108fH0jlHbIXkWBRKMusY4b/l+92bKH6jMaYcSeL5ROLhLhqeRMZzyfp+cQj4dMaQWjvT42ZvX2CtZauobRCWWSG0D1lmXWMMePei22prQjktpmRcIjqWOS0h/Qro+G8HzRCxhALyOYsIjIx/WuVWemiRQ05J1BFQibvpK2ZakVTdd4PGZbsfetRj1lLW3+S3R0DHO1LYMv04BWRINLw9SzkW4tvLZFQ+X7mqq+MctPqeWw53MOR3gSQnTi1fkE99VPYPtVaS/tAin0nD6yoZFF9vKQ974bKKGtbath6rP/k5DZDtpd8RWvjqF3I+pMZfr2rfdRGKdFwiOvPmlvwbWVTGZ++ZIaKSOiMhvlFyoH+ZcwiA6kMmw92c7gnG0LVFWEuXNjA4iJNsAqa+niUa1fMnbbv51vLg7s7ONafHHVgRXUszA2r5hEb58CKQlu3oJ75tXG2t/czmMrQWBlj9byaUWuVfWv55c72MbuEZXyPX+1s55XnzS/IBznPt2w+2MXezkFCxuBbS108ypXL5mgttcgpyrcrNcsMpT3u3tbG4Z7EyXW5/UmPh/d2srtjoNTlFZ21lkTaIzXO1pmna2d7P0f7EqN24Mr4lr5khk0Hu6atnTPVXFPB1cubuGl1C5e0No4JvMO9ibw7m/nWsr+rMLuHPbqvk72dg3gW0r7Fs9k147/Y0Z5z61KRcqae8iyxra2PtO+PmXHsWcuTh3pYNqcqkJObCuFA1yBPHu452SNsrIyyYUkjc6rG311rItvb+3POcvZttsec8fzAnHiVS/dQOu+Wnhnf0jmYYsU077A2kMpwsGco585knm95oaOfc1rK+4hUkZGC+xtETsuB7ty/+CDbC+oZ3mpyttvfNcgj+7oYSHn4NhuYHYNpfrWznZ7E1N6DRDp/r84YQ3IS+2uXUjwSyjuzO2QoyNnPxwdS+Q8ksfbk/X4RyVIoy4yWzHj0JdJ4fvYs7Cfy7OSV8S3PHumdUls1FeOHVjwy/aE2nVobqvIu3jZQkH3I820hekKuozBFypmGr2eJpY1VbGvry9lbDofMlGYcB9FgyuOx/Z0nj4a0wPLGSpLj7PU81V7ZufPreGx/7gMrVjZVF2zL0OkSi4S4Ymkjj+zrwlqLz4lZ2nDxkkaqCtBTnl8bz3stEjKcVcADSURmIoXyLLFmXg27OwZIZkbfVw4bw4bFDbPqfnLa87lnxzGGhoeTT5y0tKdzkPEGkKe6/3NrQyU9Q2m2tvVhMFgshuxSqwsWTW5LzFJb0lhFY1WMncf76RlKU1sRYVVzTcFmQYdDhstaG3l0X9eoEYxwyNBSU8HCuvyhLVKOFMqzREUkzEvXtPDUoR72dw/i2+wEp/UL61kwy37x7ekcyDmrOt9Wk5DtEbY2Tm1pmDGG8xfWs7K5hkM9Q/i+Zf4kD40IkpqKSFE3UGltrKK6IsJzR3vpGkxTEQlxdnMNy+ZU6aAMkVMolGeRymiYK5bN4QrmYK2dtb/wDvUk8gZw2GQnd428bMgO3Z43f3pm+VZFw6w6zQMryl1TVWxa14yLzFYK5VlqtgYyMO69W2MM6xfUcqw/RVtfkpDJnlC1bmF9QWYXi4hMp6KEsjHmVuBWgNbW1mI0KbPYijnVHOtL5lxzay2snFvD2hbN6hWRmacov7mstRuttRustRuam5uL0aTMYgvr4zRVxQifMhoQNoYLF9drmc0I1lra+5NsOdzD04d76BrMf860iJSehq9lxgkZw/Ur57KjvZ+d7f0kPZ+GeJRz59fNukltU+H5lvteOE7nYOrkqMK2tn4W1ce5YtmcWTUjX2S2UCjLjBQyhjXzalkzr7bUpZyWjG9JeT7xSKjgofjU4R6ODyRHrV33rOVQzxA72vtn3HsnUg4UyiJFkMr4bD7Yzf7uQQwGY2DV3GrOX1hfkHD2rWV3x0DuPadttsesUBYJHoWySIFlj0xsozeZIbt/RnbN1o72AQZSHlctb5r2NtOef3JTlVwS4+x8JiKlo1AWKbBDPQkGUh6nZuSJoeTeRHrad9SKhkMnzy7OZaYvD7PWcnwgRddQdjOSRfXxgpwFLVJsCmWRAjvYPZT3yEQLHO1LTnsoh0x2X+ldx8ceNxkOGdbOm7mbnwylPe7bdZz+VAbf2pPD/1cum8Oi+qnt2iZSavpoKVJg4252gqFQ51isX1hPc03FyfYN2WVjS+orWdU8c0P5gd0d9CSyZ0P7Njt5LuNbHtrTSV8yU+ryRKZEPWWRAmttrGRv1+CY06UALJaFBerdhUOGF61spmMgxeHeIULGsLi+ckafGNY9lKZ7KJ3zBErfWna093Hx4sai1yUyXRTKMuMFfZ/vlpoK5tXEaOtLjTkpaXVzTUGOTBypqTpGU3WsoG0US08ijTHkPBfaAl2D6WKXJDKtFMoyI6UyPluO9LCnM9sDra2IcP6COlobq0pd2hjGGK5dMZftbf1sb+8nmfGoqYhwbksdS6d4clW5megDTFVsZk9gE1Eoy4yT8Xzu3n6MgfTvZjT3JTM8uq+LoYzH6ubgrb8NGcPallrWtgSvtplkbnWMWDhExh+7pCtsTCD/vxc5HZroJTPO7s4BhtK5lxhtOdxLxh971rLMDtlRhyaiYTNmAts582tnzTC9lC/1lGXG2ds1lPc85RDQ3p/SHtizWGNVjJvPWcCezgHaB1JURkOsbKqZ0RPYRE5QKMvMk3+jqvEuySwSi4RYPa+W1aUuRGSaKZRlWhztTbC1rY/+ZIa6eJS1LbXMq6koSFtLGyvpHkrl7C1bm73vKHKmfGvxfUs4ZAI9q19mJ4WyTNkzR3rYeqz/5HKf/pTHsb4k5y+sK8ihByuaqtnW1p+9rzzi8bAxnLegVucpyxkZTHlsPtjN4d4hrM3O5D5/QR3L5lSXujQpI/rtJVPSl8yw9VjfqPW3cGLSVQ9DBTj4IBoO8ZLV82htrCRkshN9qqJhNixp4JyWumlvT2a/ZMbj7u3HONgzhJ89L4SBlMfj+7vZ2d5f6vKkjKinLFOytzP38YAn7O8aZHUBesvxaJgrlzVpqFGmxY72flLe2Fn7nrU8dbiHFU3V426XKjJd1FOWKUl5ft7JVb6F9HiJPQ1CxhAJhxTIMiX7u4fG/XDZOZgqXjFS1hTKMiXzauJE8vQgIiGjSVcyI0z0kU6f+aRYFMoyJYvq41REQmN+qRmgOhampUAzsEWm09LGKsJ5gtcYmFOlD5dSHAplmZKQMdxw9jyaqmOEDURD2aMI59VU8OJVzRpWlhlh1dwaKiLhMR8uw8Zw0aKGk2c2ixSaJnrJlFVFw9x49jz6kxkGUhlqKiJUx/RXS2aOWCQ7o3/L4R72dQ3hWUtDPML5C+tZVKCjNUVy0W9OmTY1FRFqKvRXSmameDTMZUvncNnS4B8HKrOXhq9FRE6hQJZSUSiLiIgEhMYapSistbT3p9jbNYhvLYvqK1lUH9cEGhGRERTKUnC+tTy4u4Nj/Ukywzs0HOgeojoW5oaz5xHTXtUiIoCGr6UIdrT3c3REIANkfEtfMsPmA10lrExEJFgUylJw29v68XLsYejb7PaGGX/snsMiIuVIoSwFl8zkPynKYEhlCrs/tojITKFQloIbbyMRY6Aior+GIiIwzkQv13WXAJ8CFgF3AZ9yHCc9fO3/HMd5VXFKlJnu3Pl1PH6ga8wQdtjAyrk6Ek9E5ITxuihfAe4D3g0sAH7jum7T8LWlBa5LZpGljZWsnltNyGT3Es7+FxbUVbJ+YX2pyxMRCYzxlkQ1O45z+/Cf3+267puA+13XvRnyHqErMoYxhvWLGljVXMuh3iF83zK/Lk59PFrq0kREAmW8nnLUdd34iS8cx/km8DfA3WR7zpNmjLnVGLPJGLOpvb39zCqVGa8qFmbV3BpWz6tVIIuI5DBeKH8ZuGzkA47j/BJ4HfDs6TRird1ord1grd3Q3Nx8+lWKiIiUAWNtcUeiN2zYYDdt2lTUNkVERErJGLPZWrthoudpLYqIiEhAKJRFREQCQqEsIiISEBOeEuW6bgvwcWCh4zgvc133HOAKx3HuKHh1IiIiZWQyPeU7yS6DWjj89Q7gbwtVkIiISLmaTCjPdRznfwAfwHGcDJD/hAERERE5I5MJ5YHh7TUtgOu6lwM9Ba1KRESkDE14Txl4D/Aj4CzXdR8CmoHXFrQqERGRMjRuKLuuGwLiwHXAasAA20+cFiUiIiLTZ8IdvVzXfcRxnCumq0Ht6CUiIuVmOnf0usd13de4rqtDb0VERAposveUq4GM67oJskPY1nGcuoJWJiIiUmYmDGXHcWqLUYiIiEi5m8yOXtfmetxxnPunvxwREZHyNZnh6/eN+HMcuBTYDPxeQSoSEREpU5MZvn7FyK9d110CfLJgFYmIiJSpMzkl6iBw3nQXIiIiUu4mc0/58wxvsUk2xC8AthSyKBERkXI0mXvKI3f6yADfdhznoQLVIyIiUrYmE8oNjuP828gHXNf9m1MfExERkamZzD3lN+d47C3TXIeIiEjZy9tTdl339cAbgOWu6/5oxKVaoKPQhYmIiJSb8YavHwaOAHOBT494vA94upBFiYiIlKMJT4mabjolSkREys1kT4mazJKoy4HPA2uBGBAGBnQghYiIyPSazESvLwCvB3YClcDbyIa0iIiITKNJ7ejlOM4uIOw4juc4zleBFxW2LBERkfIzmXXKg67rxoCnXNf9JNnJX9WFLUtERKaLtZbjzz9Gz57nidU0sODSG4lW6VTeIJpMKN9Ctkf9V8DfAUuA1xSyKBERmR6JrjYe/tifMdR5FD+dIhSJ8vSdt3HhX3yCRZe/rNTlySkmNfvadd1KoNVxnO1TbVCzr0XkTFnfIz3YT6SymlB4Mn0K+c2HXkfv3q1Y3xv1eDgW59qPfY/aRWeVqLLyMtnZ1xPeU3Zd9xXAU8DPh7++4JTNRERECsrPpHn+O5/lrrdfzt3vuoa73nYpz3zt43ipRKlLC7TeAzvoP7hrTCBD9j3dfdfXS1CVjGcyE70+AlwKdAM4jvMUsKxwJYmIjLbp3/6W3Xd9ncxQPzaTxksOse/e/+GRT7yNYu+1MJP0H9mLCYdzXrO+R+/+KQ9+yjSbTChnHMfpKXglIiI59OzbRtszD+Of0iv200l69m2lY+tvS1RZ8FXOmY/183xoMSGqWpYUtyCZ0GRuyjzruu4bgLDruquAvya7BeekGWNuBW4FaG1tPe0iRaR8tW15AOulc17zEkMc3fwr5p5zaZGrmhkazlpHvGEuA8cOAKPDORyNseIlt5SmMMlrMj3ldwPnAkngW0AP8Len04i1dqO1doO1dkNzc/PpVykiZcuEwuT9VWXAhDThKx9jDJf+/ReJ1dYTrqjMPhaOEIpWcPYf/iWNK88vcYVyqvFOifqG4zi3AG93HOeDwAeLV5aISNb8i17Etu9+Djt2rhLhWJyFl91U/KJmkNpFK7jh337FoUd+RueOJ4k3NLPk2ldRs2BZqUuTHPIuiXJd93ngZcCPgOsBM/K64zidZ9KglkSJyOl6auOHOPTwT0fNtg7H4jSvu4pL3vN5jDHjvFqk9KbjQIrbyS6DWgFsZnQo2+HHRUQKbv3bbqN+2Vp2/fgOhjqPUVE/hxUv/VPOevmfKZBlVplw8xDXdb/oOM47p6tB9ZRFRKTcTLanrPOURURECmzadvQSERGR4lAoi4iIBIQW+InItLHWcuSxu3nhrq+R6GqnftlaVt38NhpXri91aSIzgkJZRKaFtZan/vODHH7s53jJIQCGOg7T/vSDnP9WlyXX3FziCkWCT8PXIjItOrdvHhXIAFiLl0rw9B0OmcRA6YoTmSEUyiKzQCYxSN+hF0j2dpWshv33/QAvmecoxVCYY0/+prgFicxAGr4WmcG8dIrnvvkv7P/N/xIKhfG9NE1rL+HCd3yceOO8otaSHujl1EMPTvJ99ZRFJkE9ZZGASvX3cPSJX9O25cFR20uOtPnz72X/b36An0qQSQzgp1Mcf/ZRHnBen/c1hdJ8/lUnDz04lcVnzqoLi1bLUMdRdt/9TXb9+A66dz9btHZFpko9ZZGAsday9TufZfddXycUiQ5+5xOXAAAWYElEQVQ/5rPuTz9A6/WvOfm8/iN7aNvyAH46Ofr1vkeqv5tDj/6c1mtfVbS6l1x9M9u//wW8VBKsf/LxULSCpjWXULt4ZVHq2Prdz/HCT+4ADNb3CIUjNK5az6V//0UieT40iASFQlkkYF746VfYc/c38dPJUYH7zJ3/TLKvm+PPPUr/4d2EwhHIsyOflxjk2OZ7ixrKkcpqrnH/m02few99h3YSCsfwM0kWbHgx69/+0aLUcPjxe9j9szvx06mTj3lehs4dT/LMnR/jwnf8c1HqEDlTCmWRALG+x84fbhw9g3mYl0qw9b8/nTeITxWOV093eROqblnCdR/7LgPHDpDsOU71/KVU1M0pWvv53js/neLQwz9h3ZvfT6QE74vIZCmURQIk2dOBN6KXN8ZkA7misqi95FNVtyyhumVJ0dsdbDuQ95oJh0l0tlGzcHkRKxI5PZroJRIgkXg11vem9D3CFZU0r7uKpnMunaaqZo7xZpxbL0NFfVMRqxE5feopiwRIpLKa5vOuoO3pB8H3J37BsFh9E9bzqKibw4qXvZmlL3pNWZ4zfNbL/5xn7vzomCFsE4nScsF1RKvrsNbSsfW3HHrkZ1gvzfyLb6DlwmsxoXCJqhb5HYWySMCsf6vL/R96HZmh/pPLmkLRCvxMKufwdSRezbpb3s+iK19e7FIDZ8m1r6Jj6285/Ohd2dsA1iccr6KqaQHr334bfibN45/+Szq2bRre6MRy6NGfU92ylKs//A0ilbrfLKWl85RFAig90Mu++77PkcfuJhSNseTaV7Pnl9+id992bCZ98nkmFCY+p4UXf+YuQpFYCSsOlu7dz3HokZ+SSQ4x7/yrmX/R9ZhQmJ0/+jLbf/Dv+Kes4Q5FYiy++hVccKtmZ0thTPY8ZYWyyAyRHuzjydvfT9uWBwhFYviZNA1nrWPDuz9d9N27Zqp7/vI6El1tOa+FohW87MuPE47qw41Mv8mGsoavRWaIaFUtl77nCyR6jjPYdpDKOS1UNi0odVkzyvh7g1syQ/2Eo8VbwiVyKoWyyDQabD9E74EdVNTPpWHFeQWZbBWvn0u8fu60f99yUNW8kIGj+3JeC4WjRKvrilyRyGgKZZFpkB7sZ/Pn38Px5x8nFIlifZ+K+jlc8nefp37pmlKXN6Ol+rs5+OCPGTi2n9rFK1l0xcuJVtWc0fda9cp38MxXP4qXGj07OxSLs+wlb8zukiZSQrqnLDINHv7nt9C548nsDOkRIlW13PDZu4nVNpaospmtbcsD/Pazf4PF4qcShCsqMSbEZf+wkabVF2Wf8/RDbP3OZ+ndt41wLM7iq1/Bmtf9dc733FrL8//1Kfb84ltgyM5mN4b5F76Ii/7qUwplKRhN9BIpkt6DO7n/Q380ZkYvZCcPrX7NX7Lq5reXoLKZLdXXxS/e/Xs5T7uKVNZw03/cz9Hf/pItX/7wqOeYSJR44zyu/8T/5e1RD3Uc4egTv8Z6Hs3rrqJ20YqC/RwioIleIkXTvfs5jMm9OZ6fTnL8+ccUymfgwIM/znc6M76X5oEP/wl9B3eOWbttM2mSPcfZ+6vvsOoVb835+sqmBSy/8Q3TXLHI1GmbTZEpilXX5Z/QZQwVddra8UwMHN2bc/QBwE8l6TuwI+9e4H4qycEHfljI8kQKQqEsMkXN518NeUI5HIuz9MV/XOSKZofaRSsJx878/OOp7iEuUgoKZZEpCkdjXPzuT2cnIY3YPzlcUcmSa199ckKSnJ7FV/0BhM5sSVkoGmPh5S+d5orG52fSYyb6iZwu3VMWmQYtF1zLdR//Pi/87Gt07Xqa+Jx5rLjpTTSff1WpS5uxotV1XP6+23nsU+/EWouXHMREoqO2Gc3FhEJEKmtYftMbi1Jnz97nefYb/0Ln9s1YCw1nreO8W/6ROasuKEr7Mrto9rVIGbC+R/tzj5LsPk7dkrOpX7a2qO2nB3o58ttfkurvpmHFeTStvWTSG6tkEoMcfuxuho4fxvcyvHDX1/BPOQXqBBMKM++Ca1n3lg9RNXfhdP4IOfXs28aDH3kjXnJw1OPhWJwrPvAV5px9YcFrkJlBs69FBICuXVt47F/fhZ9KYrHgW2oWn8Xl77u9KOcLH3zoJzz1pX/CGIOfSROKxKhqXsSVH/zqpNqPxKtove7VQHad8bEn76Pv0Auje8wmRGXTfK7/lx+e8cYiZ+L5b/3rmEAG8FIJnv3GJ7j2o/9TtFpkdijKPWVjzK3GmE3GmE3t7e3FaFJEgGRvJ498/K2kejvJJAbwEoN4qSF6923j0f93K4UeKes9sIMtX/on/FQCLzmE9TJ4yUH6j+zh8c+++7S/nzGGKz/4VZrPvZxQtIJIVS2haAVzVl/ENe63ixrI1lqOP/do3us9e57PucZaZDxF6SlbazcCGyE7fF2MNkUE9t37XXwvM+Zx62XoP7KH7t3P0njWuoK1/8LPvoaf4x6w9TL07N1K36Hdp71xR6ymgcv/YSOJrjYGjh2gcu6CogxV51SAvc2lvGn2tcgs1rnjSfx0MvdFC737txW0/d792/MuTQqFIwwc3XvG3zveOI+mNReXLJCNMTSvu5Lsfp1jNaw8n3AsXtyiZMZTKIvMYpVN8zGh3P/MTShU8I1NquYtztubtL5HZdP8grZfaOe84e8Jxys5NZjDFZWcd8v7p60dL5WkbcuDHNn0qwmOn5SZThO9RGaxZS/+Yw4+8MPc9zZDIeatv7qg7Z/1sjfT9uRvxrZvDJVNC6hbWtxZ4NOtbvEqrrntv3n+vz5F+zMPY61l7tpLOOeN76Nh+bnT0saB+3/I03fednIrVz+TYunv/RHn3fL+vB+4ZOZSKIvMYvXL1rLqlbey84cb8dIpsD6hSAwTDnPJ332OUCRW0PbnnH0hq171Dnb87+1Y38N6GcIVVYQr4lz63i8U5LzpYqtbvIrL/2FjdtKctdMalMefe4ynv/KRMR9q9t/3faLVdax57elPlpNg0zplkTLQvftZ9tzzLYY6jtC48nyW3fD6og4d9x3azYH7/5dkTwdNay5m4RW/T6TizLfQLBcP3XYLHdty/76MxKt56caHC/7BSqaH1imLyEkNK87jwr/4+Gm9ZrD9EG1PP4SfThKqiBOrrqf53MuJVteddvu1i1Zwzuvfe9qvK3c9+7fnvWatZajjKNUtrUWsSApNoSwio1jf46kvfZhDD//05JAzgAlHwIQ4+1Xv4OxXvzOQQ8+ZxCCHH7+HofZDVLUsYeGlN83oGdDRqloyg305r1kvTbSqtsgVSaEplEVklB0/3MjhR342ZinViXDe9eMvUzl3Ia3XvqoU5eXVsW0zj33qHVg/u092OF7Fs3d+jMvf/+WCrsUupGU3/Anbf/Dv+KnR/1+YUIg5qy8mVttYosqkUDR1T0ROsr7H7p/dOe5OVF5yiO3f+3wRq5pYerCfxz75DjJDAye3vfQSg6QHe3n0E2+bsTtrrXjpn1LfuobwiPvvoVicaE0DF9z6zyWsTApFPWUROSk92IeX57CHkYaOH8H3MoTCwfgVcuiRn2J9P+c1389w+PF7WHL1zUWuaurCsQqu+vA3OPz4Pey/7/t4qQQLNryY1utfS6ymvtTlSQEE41+UiBRFz96t7P3Vd0h0HmPO6otovf61VNT9bgg0Eq8GM/EAWjhWMers6FLrO/QCXir3hwkvMcjA0f1Frmj6hCJRFl/5chZf+fJSlyJFoFAWKRPbvv8FXvjxHfiZFNb3aX/uEXb+cCNXfvCrNKw4D/hdABx86Cf4mVTO72MiUZZc+6pATfSqbllKOBbPOUwdrqiiqnlRCaoSOX26pyxSBrp2beGFH9+Bl0qcHOb1U0kyQ/089q/vGjX0e+4t76d6wbJR9zFPCMXiVLe0svZP3lO02idj8VV/kHc7T2MMCy97Sc5r1lq6dz/LoYd/SufOpwp+apbIRNRTFikDe+75VnZHrxy8xCAd2zYx95xLAYhW1XDdx77H0Sd+zeFH72Ko4yheKkmspoHF19zMostfRjhWUczyJxSrqeeS93ye337m3WAtXiqR/VBhDJe974tE4lVjXjN4/DCPffIdDLYfwoRCWN8Sb2zmsvfdTs2CZcX/IURQKIuUhaHjh8HmnggFkOgefc55KBJl4aU3sfDSmwpd2rSZt+4qbvz8rzn40E8YOLqP2kUrWHTly3Ou5bW+x0O33UKi8+ioUYKBY/t56LY3ccPn7iUc1U5ZUnwKZZEy0HDWOjp3bcHmOtvY96hbvKoEVU2/WE09K17yxgmfd+zJ35Dq7xk7Y9taMskhjjx2N4uvfkWBqhTJT/eURcrA8pvemHP5kglHqGtdTV3r2SWoqnR69m3FSwzkvOYlBul64ZkiVySSpVAWKQNVzYu49D1fIFJZQyReTThWSbiikrrW1Vz6918sdXlFF6ttJJRn+81QJEa8YW6RKxLJ0vC1SJloXnclL7n9Idq2PECqt4P6ZeecXApVbhZd/jKe++Ync180hsUzcKMRmR0UyiJlJByNsWDDi0tdRsnFahu54O0f5akvfxibSWN9DxMKYyJRzrvlH4t6rKXISAplESlLi69+BfXLz2HP3d+k98AOahauYPlL3kR96+pSlyZlTKEsImWrdtFZnP/nTqnLEDlJE71EREQCQqEsIiISEBq+FhEJqGRPB+3PPIzF0rzuSuL1Wqo12ymURUQCxlrL1u98lt0/+xomkv01bb0My296I+e84X2BOqFLppeGr0VEAmbfvd9lz93fxM+k8BKDeIlB/HSKvb/8b/b+8tulLk8KSD1lEZGA2fG/X8RLDo153EsOseN/b2f5jW8oQVWjde9+jm3f/Tc6tm0mFI2y+KqbOfvV76SirrHUpc1o6imLiASI9T0SnUfzXk/2dOQ9hrNYjj//OA/d9ibatjyIlxwk3d/D3l9+m9984NWk+rpKWttMp1AWEQkSEyKc4/znE0LRGKFItIgFjWat5amNH8JLJQD7u8e9DMneTnb99Kslq202UCiLiASIMYal17+GUGTsec6hSIzW615d0oleg20Hx5y/fYLNpDn44I+KXNHsonvKIiLAUMdRdv3kKxx74l5MOMKSa17J8pe8iWhVbdFrWfNHf8PxbZsYOLIPLzkIQLiiiqp5iznnT95b9HpG8jNpjMnfn7NepojVzD4KZREpe/2H93D/h/8YLzl0MlR2/N9/su/X3+O6j3+fWE1DUeuJxKu59rbvcHTTrzj4yE/BwqIrXsaCS27I2YMuppoFSwnHYic/LIwSCjPvgmuLX9QsolAWkbK35Q6HzFA/2N/dI/XTSRJd7ez4wX9w3p9+oOg1hSJRFl7+UhZe/tKitz0eEwpzzuvfxzN3fnT4vvLvRGJxzn7VX5SostmhKPeUjTG3GmM2GWM2tbfnvhchIlIK6cE+Onc8NSqQT7BemgO6RzpG6/V/yPlvdaloaCYUrSAUidKwcj1XfeS/qG5pLXV5M1pResrW2o3ARoANGzaM/ZsvIkXXvfs59tzzXwy07adh2Tksf8mbyvIXqpccwoRCWC/P9VSyuAXNEEuuuZnFV/0Bie52wtEYsVqtT54OGr4WKUM7f/xldnz/37PrXa1P184t7Lv3u1z87s8w/+IXlbq8oqqon0u0upZkd+7wnbNyfZErmjlMKETlnJZSlzGraEmUSJnpO7Sb7d/7QvZ+oPWB7IxZL5Vg8xfeSyaRYwLPLGZCIdb+0d8RjlWOuRaOxVnzR39TgqqkXCmURcrM/vu+h/XzjNUaw9HN9xa3oABovf4POecN7yVSWUMkXk24ooqKhmYu/uvPMOfsC0tdnpQRDV+LlJlEV1vetaQ2kyHV21nkioJh+U1vZOnvvY7e/TsxkQh1i1dhQuq3SHHpb5xImZmz6kLCFWOHaoFsGC1bU+SKgiMUidGw4lzqW1crkKUk9LdOpMwsvuaVhMJj9042oTCVTQtoWnNJCaoSEVAoi5SdaFUNV37468Sb5hOOV2XvocYqqWtdzZUf+EpJ91UWKXe6pyxShupbV3Pj5+6lc/tmEp3HqFm4gvpla0tdlkjZUyiLlCljDE1rNpS6DBEZQcPXIiIiAaFQFhERCQiFsoiISEAolEVERAJCoSwiIhIQCmUREZGAUCiLiIgEhEJZREQkIBTKIiIiAaFQFhERCQiFsoiISEAolEVERAJCoSwiIhIQCmUREZGAUCiLiIgEhEJZREQkIBTKIiIiAaFQFhERCQiFsoiISEAolEVERAJCoSwiIhIQCmUREZGAUCiLiIgEhEJZREQkIBTKIiIiAaFQFhERCYiihLIx5lZjzCZjzKb29vZiNCkiIjLjFCWUrbUbrbUbrLUbmpubi9GkiIjIjKPhaxERkYBQKIuIiASEQllERCQgFMoiIiIBoVAWEREJCIWyiIhIQCiURUREAkKhLCIiEhAKZRERkYBQKIuIiASEQllERCQgFMoiIiIBoVAWEREJCIWyiIhIQCiURUREAkKhLCIiEhAKZRERkYBQKIuIiASEQllERCQgFMoiIiIBoVAWEREJCIWyiIhIQCiURUREAkKhLCIiEhAKZRERkYBQKIuIiASEQllERCQgFMoiIiIBoVAWEREJCIWyiIhIQCiURUREAkKhLCIiEhAKZRERkYBQKIuIiAREpBiNGGNuBW4d/jJpjHm2GO2WsbnA8VIXUQb0Phee3uPC03tcHKsn8yRjrS10IaMbNGaTtXZDURstM3qPi0Pvc+HpPS48vcfFMdn3WcPXIiIiAaFQFhERCYhShPLGErRZbvQeF4fe58LTe1x4eo+LY1Lvc9HvKYuIiEhuGr4WEREJCIWyiIhIQCiURUREAkKhLCIiEhAKZRERkYAoyjabIjJ5ruv+NfBO4AnHcd54mq9dBlzpOM63ClAaruteC/x/wPnAnziO871CtCNSrtRTFgmedwG/f7qBPGwZ8IbTfZHruuFJPnU/8BagIKEvUu60TlkkQFzXvR34c2A78BWyGw58HlhHdmTrI47j/HC4R/wNoHr4pX/lOM7Drus+CqwF9gBfA7qADY7j/NXw9/8J8K+O49znum4/8BngJcB7gaHhr2vIHlDwFsdxjuSp807gJ+opi0wv9ZRFAsRxnL8ADgMvchzns8AHgXsdx7kEeBHwKdd1q4E24EbHcS4C/hj43PC3+EfgAcdxLhh+/XiqgWcdx7kMeIxs+L/WcZyLyX4g+Ng0/3giMgHdUxYJtpuAm13X/fvhr+NAK9ng/oLruhcAHnD2GXxvD/j+8J9XA+cBv3BdFyAM5Owli0jhKJRFgs0Ar3EcZ/vIB13X/QhwDFhPdsQrkef1GUaPiMVH/DnhOI43op3nHMe5YjqKFpEzo+FrkWC7G3i367oGwHXdC4cfrweOOI7jA7eQ7dkC9AG1I16/F7jAdd2Q67pLgEvztLMdaHZd94rhdqKu6547rT+JiExIoSwSbB8FosDTrus+O/w1wH8Abx6e2HU2MDD8+NNAxnXdLa7r/h3wENlJX88A/wo8kasRx3FSwGuB/+e67hbgKeDKU5/nuu4lruseBF4H/Kfrus9Nz48pIqDZ1yIiIoGhnrKIiEhAKJRFREQCQqEsIiISEAplERGRgFAoi4iIBIRCWUREJCAUyiIiIgGhUBYREQmI/x9JawsHFvyU5wAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x118eae860>"
+       "<matplotlib.figure.Figure at 0x1a14703470>"
       ]
      },
      "metadata": {},
@@ -565,28 +510,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### Classification Example Figure 2"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 30,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeIAAAGACAYAAABx1WHyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11b2131d0>"
+       "<matplotlib.figure.Figure at 0x1a1487e588>"
       ]
      },
      "metadata": {},
@@ -618,28 +556,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### Classification Example Figure 3"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 31,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAABCIAAAGACAYAAAB4PcMRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3XlwnPW95/tPb09rbe1qyZbk3dgyXsBgwIDZTMBsNltC\ncsIJEHyY2Gdhau6cW3Xv1MxJ1UzNVGpSc5J74wzRkJttgJCwG7ODIWGzsY0NBoxteZFsSZYtS621\nn16e+4dQW+1ubbbUj7r1flVRsZ7n6e5v56dW//rbv9/367AsyxIAAAAAAEAKOO0OAAAAAAAATB0k\nIgAAAAAAQMqQiAAAAAAAAClDIgIAAAAAAKQMiQgAAAAAAJAyJCIAAAAAAEDKuP7lX/7lX+wOAsDw\nfvzjH+uyyy6Tx+OJHfviiy+0ZcsWLVu2bNjb/uxnP9OMGTOUn58/0WGOyb/+679qx44d2rVrlz75\n5BNt375dgUBAM2fOlMPhGPa2+/fv1549ezRr1qwURQsAQPpqb2/XT37yE3311VfasWNH7D+Xy6XK\nysrzuu8nn3xS0WhUFRUVeuyxx7R48WK53e6k1waDQT3xxBNaunTpmB5jqDlPe3u7/sf/+B+6+uqr\nx3R/yeZVI3nhhRd0+vRpVVdXj+mxACSX/K8EgEllpA/m6cjhcOiuu+6KTYBCoZCeffZZvfbaa1qz\nZs2wtz127Jj6+vpSESYAABnB4/HokUceif3c2dmpTZs2afr06SovLx+Xxxh8/8n09vbq2LFj4/JY\n5yMT51VAuiERAaQBy7KGPb9161Z1dHSos7NTHR0dysnJ0b333qu8vLzYNaZp6oknnlBVVZVWr16t\nn/3sZ1q6dKkOHTqkQCCg2tpa3XjjjZKkHTt2aNu2bXI6ncrNzdWaNWsUDof1xBNP6N/+238rSfrD\nH/6gvLw8rVu3TpFIRD/96U/1j//4j/rpT3+qK6+8UvX19erq6tKKFSt0+eWXj/gcPR6P1qxZo5//\n/Oe64YYb5HA49PLLL+vUqVPq7e2V1+vVXXfdpb6+Pu3YsUOWZcnr9erqq69Oel1JScl5/D8OAEBm\ny8/PV0lJiU6dOqXjx49r165dCoVCysrK0t/+7d9q586d+uSTTyRJ2dnZWrNmjUpLS9XZ2annn39e\nXV1dKigoUHd3d+w+f/zjH+uf//mflZ2drb/85S/as2ePnE6nSkpKtHbtWr3wwgsKhUJ67LHH9Hd/\n93c6efKkXnvtNfX29ioajWrFihW66KKLJEnvvPOOPvvsM+Xk5Ki4uHjMz+/UqVPasmWLQqGQOjs7\nVVFRoXvuuUcul0uWZemtt97S8ePHZVmWrrvuOs2fP1+StGvXLm3fvj32vG+55ZaEOcU777yjffv2\nyeVyKScnR2vXro2bcwEYGYkIIEMcPXpUjzzyiAzD0FNPPaVPPvlE1157rSSpr69Pf/jDH7RgwQKt\nXLkydptQKKQHH3xQnZ2d+vnPf65LL71Up0+f1gcffKCHH35Y2dnZ+vTTT/XHP/5RGzZskMvlUmtr\nq4qKinTq1CmdPHlSklRfX6+qqiplZWUpHA4rNzdXDz30kJqamvTrX/9al156qVwu14jPwefzKSsr\nSydPnlR7e7uysrL0wx/+UJK0efNmbdu2TWvWrNHy5cvV29ur66+/Xl988cWQ1wEAgOQaGhrU1tam\n6dOnq76+Xq2trXr00UdlGIaOHDmiPXv26KGHHpLb7dbBgwf19NNPa8OGDdqyZYuqqqp03XXXqa2t\nTY899ljsPgdWGuzbt0979uzRww8/LK/Xq9dff13btm3T2rVr9ctf/lKPPPKIotGo/vSnP+muu+5S\nRUWFgsGgHn/8cZWXl6urq0tfffWVfvSjH8ntduupp54a8/PbuXOnli1bpsWLFysajepXv/qVvv76\nay1cuFCSVFxcrNtuu00nTpzQb37zG/393/+9WltbtXv37rjnPTAHGhAIBPTxxx/r3//7fy+Xy6UP\nP/xQx44d0wUXXHCeIwJMLSQigDSQbAmhZVlyOs/Um50xY4YMw5AkVVRUqLe3N3buueeek9Pp1IoV\nK+LuY+BNMz8/X3l5eert7dWBAwe0aNEiZWdnS5KWLVum1157Te3t7VqwYIH279+v8vJyzZw5UydO\nnFBra6v27dsXe2MffL+VlZWKRCIyTTN2f6Ph8XhUW1uroqIibdu2TW1tbTpy5IiqqqoSrh3tdQAA\nTGUDKxEkKRqNKicnR3fffbd8Pp8kye/3x+YRX3/9tdra2vT444/Hbt/X16fe3l7V19frW9/6lqT+\nD/PJ6jXV19ertrZWXq9XkmLXt7e3x645deqUTp8+rRdeeCF2LBwOq6mpSa2trVqwYEGshsOyZcu0\nbdu2MT3f1atXq76+Xu+//75OnTqlzs5OmaYZO3/JJZdIksrLy1VeXq7GxkYdOXIk6fMevB00Pz8/\nVg9j7ty5mjdvHjWrgHNAIgJIAzk5Oerp6Yn7MN/d3R3383AFl1atWqXDhw/rjTfeiFspkOw2ybaB\nWJalaDSqhQsX6u2331ZnZ6fmzJmjvLw8HThwQAcOHNANN9wwqliG097eLtM0VVxcrO3bt2vnzp1a\nsWKFFi9erOzs7LgJzIDRXgcAwFR2do2Isw0kIaT+9/0lS5Zo9erVsWOdnZ3Kzs5O+HJk8JciQx07\n+8P8wGNkZWXFxdTd3S2v16s33nhjxMcYyTPPPCPLslRbW6v58+crEAjEnR/8PAa+3BnqeWdlZcXd\n7oEHHtDx48dVX1+v1157TTNnztTNN9885hiBqYz2nUAamDdvnj7++ONYkqC3t1e7d+/WvHnzRnX7\n6dOn65ZbbtEXX3yh+vr6Ya+dO3eu9u7dq56eHkn9eyUH9mdWVVWpra1N+/fv1+zZszV79mx9/PHH\nKikpGXLFw0j1LQb09fXp1Vdf1YoVK+RyuVRfX69ly5bpoosuUklJib7++uvYfTmdTkUiEUka9joA\nADB2c+bM0eeff66uri5J/Un/3/3ud5L65wk7duyQJHV0dOjQoUOx2w28/86ePVtfffVVbAXC1q1b\n9dFHH8npdCoajUqSSkpK5Ha7tWfPnth9bdq0SU1NTZo7d66++OIL9fX1ybKs2DVjcfDgQa1atUqL\nFi2SJDU2NsYeW5I+/fRTSVJTU5Pa2tpUVVU17PMe0NLSok2bNqmsrExXXXWVLr/8crW0tIw5PmCq\nY0UEkAZuuukmvf766/rlL38Z+1Zg6dKlY2p/lZOTo1tuuUUvvPCCfvSjHw153ezZs3X55Zfrt7/9\nbex23/3udyX1fwswb948NTU1KScnRzU1Nert7VVtbW3s9md/UzJcZepnn31WbrdbDocj9q3FQAuu\nK664Qps3b9ann34qp9OpyspKnThxIhbj008/rVdeeUUrV67USy+9lPQ6AAAwdnPmzNGVV16p3//+\n93I4HPJ6vfrOd74jSbG5xKZNm+Tz+eLafw6858+bN08nT57U448/LofDobKyMt1+++3yeDyqrKzU\nL37xCz300EO677779Oqrr+qDDz5QNBrV9ddfH2uPeeLECdXV1Sk7O1t+vz/2BcnZQqGQ/ut//a9x\nx374wx/qhhtu0B//+EdlZ2fL4/Fo5syZamtri8V5+vRpPfbYY3I4HLrnnnuUlZU17PMe4Pf7tWjR\nIv3qV7+SYRjyeDyshgDOgcPiq0MAAAAAAJAibM0AAAAAAAApQyICAAAAAACkDIkIAAAAAACQMiQi\nAAAAAABAytiSiKA+JgAAGG/MLwAASA+2dc1obe2042ExSFlZPuNgM8bAfozB5MA42K+sLN/uEMYF\nv0f24rVsP8ZgcmAc7McYTA5DzS/YmgEAAAAAAFKGRAQAAAAAAEgZEhEAAAAAACBlSEQAAAAAAICU\nIREBAAAAAABShkQEAAAAAABIGRIRAAAAAAAgZUhEAAAAAACAlCERAQAAAAAAUoZEBAAAAAAASBkS\nEQAAAAAAIGVIRAAAAAAAgJQhEQEAAAAAAFKGRAQAAAAAAEgZEhEAAAAAACBlSEQAAAAAAICUIREB\nAAAAAABShkQEAAAAAABIGRIRAAAAAAAgZUhEAAAAAACAlCERAQAAAAAAUoZEBAAAAAAASBkSEQAA\nAAAAIGVIRAAAAAAAgJQhEQEAAAAAAFKGRAQAAAAAAEgZEhEAAAAAACBlSEQAAAAAAICUIREBAAAA\nAABShkQEAAAAAABIGRIRAAAAAAAgZUhEAAAAAACAlCERAQAAAAAAUoZEBAAAAAAASBkSEQAAAAAA\nIGUclmVZdgcBAAAAAACmBrddD9za2mnXQ6dUINChhoajqq6ukc9XYHc4ccrK8qfMOExWjIH9GIPJ\ngXGwX1lZvt0hjItM/z3q6enRm+++q2AopPmzZ2nphYvtDikOr2X7MQaTA+NgP8ZgchhqfmFbIiLT\nmaapurpNamlpkmF4ZJoh+f2VWr9+gwzDsDs8AACQZrbt3KkPvzqo+ZdfoxzDq8+O1usvv/mt/u57\n32VuAQBIK9SImCB1dZsUiZiqqPCruLhYFRV+RSL9yQkAAICx6O3t1YdfHdSiVd+Sx/BKkipqZmvO\nqjX68+bNNkcHAMDYkIiYAIFAh1pamuR2xy84cbvdamlpUiDQYVNkAAAgHb313ruat+LqhOMew6s2\nM2JDRAAAnDsSEROgoeGoDMOT9JxheNTY2JjiiAAAQDrrC4ZkZGUnP+l0pTYYAADOE4mICVBdXSPT\nDCU9Z5ohVVVVpTgiAACQzmrnzVVT/ddJzxlRVkQAANILiYgJ4PMVyO+vVDgcjjseDofl91dOuu4Z\nAABgcqtduFBdh7+S2dcbd/zIZzt0+eKFNkUFAMC5oWvGBFm/foPq6japuTmxawYAAMBYrf/ed/XM\ny5t1qjekqMOpLEW14sKFWrLoQrtDAwBgTEhETBDDMLRx46MKBDrU2NioqqoqVkIAAIBz5na79Z21\n6+wOAwCA80YiYoL5fAWqrSUBAQAAAACARI0IAAAAAACQQiQiAAAAAABAypCIAAAAAAAAKUMiAgAA\nAAAApAyJCAAAAAAAkDIkIgAAAAAAQMqQiAAAAAAAAClDIgIAAAAAAKQMiQgAAAAAAJAyJCIAAAAA\nAEDKkIgAAAAAAAApQyICAAAAAACkjNvuAAAAAAAgHVmWpYaGo5Kk6uoaORwOmyMC0gOJCABTRiDQ\noYaGo6qurpHPV2B3OAAAII3t3P2pPty7T9n+ajkcDvX89SOtWDhPl150sd2hAZMeiQgAGc80TdXV\nbVJLS5MMwyPTDMnvr9T69RvsDg0AAKShxmON+vjQcV2w6uYzB+fXaueuj1RWckRlZRfaFxyQBqgR\nASDj1dVtUiRiqqLCr+LiYlVU+BWJ9CcnAAAAxuqdjz7W3OUrE47PXnaZ/rLtExsiAtILiQgAGS0Q\n6FBLS5Pc7vgFYG63Wy0tTero6LApMgAAkK4iDlfSehAOh0Nhp8uGiID0QiICQEZraDgqw/AkPWcY\nHh09ejTFEQEAgHTnsiKyLCv5uWgkxdEA6YdEBICMVl1dI9MMJT1nmiHV1NSkOCIAAJDurllxqeo/\n/Tjh+KHd23XV8otsiAhILxSrBJDRfL4C+f2VCofNuO0Z4XBYfn+lCgoK1NraaWOEAAAg3dRU12jZ\niVZte/cVFdTMk8PhUPvR/bpk3mzNnjXb7vCASY9EBICMt379BtXVbVJzM10zAADA+Lhs+XKtuPhi\nfb3/a1mWpQuu/HbSuhEAEpGIAJDxDMPQxo2PKhDoUGNjo6qqquTzFdgdFgAASHMOh0MXzL/A7jCA\ntEMiAsCU4fMVqLaWBAQAAABgJ4pVAgAAAACAlCERAQAAAAAAUoZEBAAAAAAASBmHZVmW3UEAAAAA\nAICpwbZila2tnXY9NL5RVpbPONiMMbAfYzA5MA72KyvLtzuEccHvkb14LduPMZgcGAf7MQaTw1Dz\nC7ZmAAAAAACAlCERAQAAAAAAUoZEBAAAAAAASBkSEQAAAAAAIGVIRAAAAAAAgJQhEQEAAAAAAFKG\nRAQAAAAAAEgZEhEAAABAGmppaVFra6vdYQDAmLntDgCYCgKBDjU0HFV1dY18vgK7wwEAAGls157d\n+vDzr+QuKpcsKdLRqquWLtLi2kV2hwYAo0IiAphApmmqrm6TWlqaZBgemWZIfn+l1q/fIMMwRnUf\nJDEAAMCAow1H9fGh45q/6ua44+99/K7KS0pVVpY/7O0/37tXu/Z9LUsO5Xs9uvn665WdnT2RIQNA\nAhIRwASqq9ukSMRURYU/diwc7k9ObNz46LC3HY8kBgAAyCzvbtuuOStuSDg+f8UqvfXBO7rwwrlD\n3vaFV19Ru7dI01dcL0kyg3365ZNP64F1t6m4uGTCYgaAs1EjApgggUCHWlqa5HbH5/vcbrdaWpoU\nCHQMe/vBSYzi4mJVVPgVifQnJwAAwNQUklMOhyPhuMPhkGklHh9w4sQJNZkOTZ+3MHbM8GZp8Y1r\n9dJb70xIrAAwFBIRwARpaDgqw/AkPWcYHjU2Ng552/NNYgAAgMzkikaTHrcsS24lPydJf/n4Y81e\ndlnCcYfDoa7o0AkMAJgIJCKACVJdXSPTDCU9Z5ohVVVVDXnb80liAACAzHXZ0sU6sndXwvFDu7fp\n6kuWD3m7qGUlXUkhSZascYsPAEaDRAQwQXy+Avn9lQqHw3HHw+Gw/P7KYQtPnk8SAwAAZK4F8+dr\nXr5HX773mk41H1fr8UZ9+d6rurC8UDNqZgx5uyuWX5w0gSFJeXwiAJBi/NkBJtD69Rvkchlqbm5R\nW1ubmptb5HIZWr9+w7C3O58kBgAAyGyrVl6pDd+5W/NcvVroDWnjffdq5YoVw96manqVcnpOq63p\nWOxYNBrV51tf0beuWjnRIQNAHIdlWbasxWpt7bTjYTFIWVk+45AigUCHGhsbVVVVFZdEGG4M6JqR\nGrwOJgfGwX4jtfxLF/we2YvXsv1GGoO/fPCBDhxvUtThVLbD0s3XXpN2HTOsYbaZTBa8FuzHGEwO\nQ80vaN8JpIDPV6Da2rGtYjAMQxs3PjpkEiMdBAIdamg4qurqmrSLHQCATHT1ypW62u4gzoFlWXpu\nyxYdD3Qr7HDJY0U1q6xQt6y+0e7QAJwDEhHAJHcuSQy7sZoDAACMpyeee065F1ysBQVFsWOnW5v1\n/CuvaN2aNTZGBuBckIjAhOCb8Kmtrm6TIhFTFRX+2LFwuD85sXHjozZGBgBIR29s3aqDzScUcrjk\nsSKaW+nX6muusTsspEhXV6faLY/8g5IQklRUVqEv9+1RKBSSx5O82xiAyYlEBMYV34QjEOhQS0tT\nXBJCktxut5qbmxQIdJCcAgCM2ouvvqq+0hrNveqi2LG25mN68dVXdcfNN9sYGVLly6/2yT9nQdJz\neeXVOn78mGbMmJnaoACcF7pmYFwN/ia8uLhYFRV+RSL9yQlMDQ0NR2UYyb+VMAyPGhsbUxwRACBd\nmaapI+1dKq6YHne8uGK6jrR3KRRK3uoamcXvL1egtTnpub5Am4qKipKeAzB5kYjAuBn4Jtztjl9o\n43a71dLS/004Ml91dY1MM/nE0DRDqqqqSnFEAIB0deDgARXPmJf0XFHNXB08eCDFEcEONdU16m0+\nknA8Go3K1c1KSyAdkYjAuOGbcEj9xTX9/kqFw+G44+FwWH5/JZMFAMCoFRcVqbu9Lem5no7TfBM+\nhdzzrRu1980XdarpmCSp5egh7Xv7JX3nNgpVAumIRATGDd+EY8D69Rvkchlqbm5RW1ubmptb5HIZ\nWr9+g92hAQDSSEVFpcKnjic9FznVJL+/IsURwS5+v1//+IPva7azV527/6LFPpf+4YG/VUFBod2h\nATgHFKvEuDnzTbgZtz2Db8KnHsMwtHHjowoEOtTY2KiqqirGHwBwTtbdcJ3++NoLmrH8avmKihU4\n3aYjO/6i79y02u7QkGIOh0OXLl+uS+0OBMB5c1iWZdnxwK2tnXY8LAYpK8sf93Gga8bYGEZUu3bt\npc2pjSbidYCxYxzsV1aWb3cI42Kq/x5Fo1H19vYqJydHDocj5Y8/Ua/laDSqv3zwvk60nVZ5cZGu\nXnmlnE4W9p7tSMNRfbT7U7X3RuS0oqoq9unmG1bb8rsw1fG+Zj/GYHIYan7BiggbBQIdamg4mlEf\nQvkmfHQGEjYnT7bI5XKRsAEAnJdoNKqnX3xRrX0hObNyZfV1q6ogT2tvvjkjPoQ6nU5dc9XVdocx\nqR2oP6jXd+3V/MuuUck3xzpPt+m3Tz+tB77zHVtjA4CzkYiwwVRYNeDzFai2lgTEUAbanJaVlcWO\nhcP9vxcbNz5qY2QAgHT0h2eeUdGSlSrNzYsd6zx9Ss9sfln33H6bjZEhVd7bsUvzr7gx7lh+UbHa\niip1+MhhzZwx057AACAJ1rTZYOBDaEWFX8XFxaqo8CsS6f8QisxHm1MAwHgKBDrU7clR9qAkhCTl\nF5WouSco0zRtigyp1B1NvvKlZuESbd+9J8XRAMDwSESkGB9CQZtTAMB42vf1fpXPuiDpuZyy6Wpu\nbkpxRLCDY4iyb9FIRB63K8XRAMDw2JqRYqP5EMqWhjMysY4GbU4BAONpWmWFdn9+UAUlZQnn+jpO\nqbh4kQ1RTU5dXV165a231B2xpGhUF9RM1xUrLrM7rHHhc/XXCjm7iOf+7X/VD26+zqaoACA5EhEp\nxofQ0cnkOhq0OQUAjKfp06tkvrVVVu3SuMKU0UhERl+n8vIyoyPK+WprO6XfvPCyaq+9RUWe/i+F\nDjce0ZHnntN9d95pc3Tn7641N+mxJ5/WnCtXK89XKMuydHDXR1roL1J+vs/u8AAgDlszUuzMh9Bw\n3HE+hMY7nzoagUCH9u79bFJvc1m/foNcLkOtra1qa2tTc3OLXC5D69dvsDs0AEAauu+2Ndr39ktq\nOrRf0WhUjV9/of3vvqzv3nG73aFNGi+9+bYWr75Dbs+ZlallVTPUnVuiw0cOD3vbXXt26/mXN+vz\nvXsnOMpzl5eXr0cfekCVvU1q+WSrTu3YqjsuXaIbVq2yOzQASMCKCBusX79BdXWb1Nyc+G0/ztTR\nqKjwxx13u91qbu6vo5EsYZNOqygG2pwaRlSffvolbU4BAOeluLhEf/+D+/XFl1/q4Ocf6KoFF2ju\n9VfYHdak0hV1JG1lWrNwibbtejdpV4nWkyf1xOYtKl+wTGVLr9buIwf19m9+qx/cuVYFBYUpiHps\nXC6Xbrv5RrW2dtodCgAMi0SEDQY+hAYCHWpsbORD6FnOtY7G4FUUAyZ7S8yCggLV1rJ3FwAwPmoX\nLlTtwoV2h5Ex/vTKa6q94Y5YAsM/Y47Ka2brqc2v6JG/+a7N0QFA+rItEVFWxn7FsrJ8zZljb02I\nyTgOF120SH/+cyTpuUgkomXLFqqgID7ujo4OnTzZorKy+EJdbrdbra0tMoyoCgomZ7JnMo7BVMMY\nTA6MA8YDv0f2m6xjUJbnlmVZCasiGvd9pnuuvyoh7sbGRhnlVQnXOxwOyVcstzusoqKiCY/7XEzW\nMZhqGAf7MQaTl22JCJaM2a+sLH+SjoNTpaX+pMUcS0v9Mk1nQtx79+6Vy5W8NZXL5dKnn345KVce\nTN4xmDoYg8mBcbBfpkzW+D2yV6pey+3tp9XWdkpVVTWj3n65euXV+s0LL6r22jVye/pv03rsiLI7\nTyo/ryQh7i++rFd+qT/ZXSmroERff31Ys2dPvsXF/D2dHBgH+zEGk8NQ84vJ99cTGedcWnCOtY4G\n3UgAAMh8HR3temrzFkXyipRbVKbOT/aoItvQ3bfdmrT+w2DFxSV65Nt3a8tbb6k7HJWiUS2YUaXL\nh+iYMW/uPH3w2tsq8VcmnOtsPqqqy5eMy3MCgKmIRAQmzPkUjxxrHQ1aYgIAkPl+99wLuuD6O+R0\nftP4bfY8BdpO6sXXXtXam9eMePvc3Fzde8cdo3qsvLw8FTnC6uo4rbyCM1swOk61qjLHO+kKYQNA\nOqF9JybM+bTgHODz9RdzHE0iYaAlZnNzCy0xAQDIMHu/+ELF8xafSUJ8w1dcqobTE7P8+rt33qno\n4b368r1Xtff9t/TVe6/K3bRfd916y4Q8HgBMFayIwIQ41xac54NuJAAAZK79hw7Kv3RV0nMRp0eR\nSGTIelHnyuFw6K5bb5UkRaPRhCQIAODc8NcUE2I0LTgnylhWUQAAgPQwq2aGTjQeTnrOGQ2NexIi\n4TFIQgDAuOEvKiYExSMBAMB4Wrp4iVq/2i3LsuKOdwXaNS0/16aoAADngq0ZmBAUjwQAAOPt+7ff\nqj9ueVmesmnylVXq5OGvVegI63tDdL4AAExOJCIwYcbaghMAAGA4JSUl2nD/36ip6biaW1p0603X\nKy8vz+6wAABnsSxL0Wh0yPMkIjBhKB4JAAAmQmXlNFVWTrM7DADIaJFIRMFgUMFgn0wzKI/HUHFx\nScJ1R48e1qef7pBp9n1zfVCmGdTChYt1zz3rkt43iQhMuP7ikSQgAAAAACDVgsGgAoH2WFJhIFGQ\nn1+gOXPmJVy/f/8+vfPOa4pGo/J6vTIMr7xer2bPnpc0EVFUVKxly5bL6/XK68365npDLtfQ6QYS\nEQAAAAAApImOjnYdPlwv0wzGrVgoLS3XpZdekXB9c/Nxffzx+3FJBa83S3l5vqT3P2vWHM2c+SO5\n3W45HI4R48nP9yk/P/l9DYVEBACkmUCgQw0NR1VdXcN2JwAAcN6ONx3Xrs8+U1VlpZYuXmJ3OBkl\nHA7HEgYOh0OFhUUJ17S2ntDOnR/HtjUMrFqYNq1Ka9bckXB9KGQqEGiX1+tVfn6+SkpK5fV65fMV\nJo1hxoxZmjFj1qhjHtxsYKKQiACANGGapurqNqmlJbEArGEYdocHAADSTDgc1m+e/pOihX7NqL1E\ne5sa9e7v/qA7b7hW1dOr7A5v0ohEwurq6orb1hAM9snrzdKcOfMTrm9qOqZXX31JphmUZVnyerPk\n9XpVVVWjVatuSLg+Oztbc+bMj1utMLB6IZnS0nJdffX14/48U4lEBACkibq6TYpETFVU+GPHwuH+\n5MTGjY++8+XkAAAgAElEQVTaGBkAAEhHf3zxRU1bcZ2MrGxJUnn1TJVXz9Szb76of/zb749qWX46\n6u3t0ZEjhxJqJuTm5unyy69KuL619YTefPOVs2ogeFVaWpb0/svKyvXtb39fXq9XLtfI2xvy8vI1\nd+4F4/Lc0gWJCABIA4FAh1pamuKSEFL/0rnm5iYFAh1s0wAAAKNmWZZOBSPyf5OEGKxy0SX6ZOcO\nXbr8Ehsii2dZVmx7QyQSSTrf6ewM6JNPPopLKoTDIeXm5uuOO+5JuN40gzp2rCG26sDnK4htc0im\nomKavv/9H446ZrfbI7fbM/onOQWRiACANNDQcFSGkfwNzTA8amxspDsNAAAYtUgkIrmTb+0s8lfq\n+J6/jttjWZalvr7euBoIptlfMyHZ1ob29tPasuX52LUOh0Neb5bKyvy69dbEdpBut0d+f4UMI+ub\nVQteVVaWqLs7kjSegoIi3XDDzeP2/DB2JCIAIA1UV9fINENJz5lmSFVV7OMEAACj53a75QoHk547\ntv8LXV27cMjbhkIhNTQcjiUWTLN/JYLL5dLKldckXB8ItOuZZ56M29bg9XpVUFCUNBGRl5evNWvW\nxlYsjFQ8MTs7W7W18UU2i4vzFYl0Dns72IdEBDIOHQWQiXy+Avn9lQqHzbg343A4LL+/kt91AJhA\nh48cVuOxY1p4wQKVlJTYHQ4wZgPbG0IhUzk5ubHjcyvKdLKpQUWl5Tq1b5eiIVNhM6iek03acbJQ\nu3dt11133Zdwf+FwSPv2fRGXWCgoKFROTl7Sxy8oKNJDD20Ydbxut1tFRcVjf6JIGyQikDHoKIBM\nt379BtXVbVJzc+LvOABg/J06dUpPvfyKsqfNVHFllf70/nYZPe36wb33yuVy2R0epphIJJLQtSEc\njmj27LkJ1waDfXrppWcGXRuU0+mUz1eg++77Qey6m667Tq++/bb2f/2ZnFZEkXBY2U5pzbduUV5e\nnrzerKSxZGfnaM2atRP2XJH5HJZlWXY8cGsry2TsVlaWn1Hj8Itf/KsikcRvi10uY9J2FMi0MUhH\n6TgGgUCHGhsbVVVVlTErIdJxHDJNWVnyAl3pht8je2Xaa/n/+c3vtOCGO+Iq3gd7e9W+5339zd13\n2xjZ0DJtDNLVSOMQjUZ1/HhjLLFwpsBiWFdembi1wTRN/frXm2JbFQa6N2Rn52j16jVJ77+1tWXQ\nigVDLtfQ30FblqXu7i5lZWWPuA0iXfBamByGml9kxm8Zpjw6CmAq8fkKKEwJABPsq337VDh7YULb\nPW92tk6ZUUUiEVZFTDH92xtC8ngSV9pGo1Ht2PFxrLiiFFFnZ7dCoZDuued7Sds3fvLJR/J6zxRX\n9HqzlJOTk/SxPR6PHnnkn0bdTtPpdMrvrxz1c3M4HMrLy4yENNIDiQhkBDoKAACA8XTw8CGVzU/e\nutCdk6+enm7l5/tSHBXO10AbyIGEQTAYVE3NzIQP+JZlafPmZ9XX1xfr8NBfjNGthx/eKKfTGXe9\nw+GQZVnKy8tXSUmpysoKFQxGh9za4HQ6tW7dt0cd92gTEEC6IBGBjEBHAQAAMJ4uXLhQb+37UjUL\nlySci3QHlJubvCgfUqe1tUV9fX2xegkDWxwuvfTypNsQHn98k0Kh0KAVCP3bHKZPr5LbHf+FlsPh\n0EUXXSqPx4i7dqhVMA6HQytWrIz9zLYAYHgkIpAR6CgAAADG04yaGQq++xeF5y6U23PmQ2qg7aSq\nCvMSvhHH6AyUp0v2Df/nn+9WT093XIHFYLBPt9yyNunKgg8+eE+SYtsb+mshZGmoEng/+MHfyeVy\njXp1QVVVzWifFoAxIhGBjEFHAQAA0ktfX59OnTqp0tIyeb1eu8NJ8OC99+h/P/+8el3Zyi4sVm9b\niypzs3XnrbfYHZptBtpADk4UlJX5kxY43Lr1DXV0tMdda5qm7r//4aT1CHp6uiX1f8E0eBXC2asV\nBqxde++YYs+UIoxAJuDViFELBDrU0HBU1dU1k3KFgWH0d8fIxI4CAABkkkgkoieee14dlkvZxWXq\nbftEhc6Ivrtu3aQqAJmVlaUf3nefenp61NHRrrKyKzLqw2wg0KHe3p64FQimGdTChRcqKys74fo/\n//kJnTzZKodDg7oxeHXTTbclTSzMnj1XDoczVohxILEw1GqSwVsbAGS2zPlLigljmqbq6jappSVx\npYFhJFYNthsdBQAAmNz+8MwzKr1olSqzz3zY7evt0f9+9ln97b1j+5Y7FXJycobsZjCZHDy4XwcO\nBNXW1hGrlxAMBnX11dcl/XLmvffeVm9vT1zXBsPwKhqNJr3/2267U263Z9TJmJqaWef1fABkLhIR\nGFFd3SZFImZca8xwuD85sXHjozZGBgAA0k1XV6e63Dmanh3/jXtWdo46nVnq6upSXl5mF4IcaAM5\nkCjw+Qrk8SRuP9i+/UOdPNka17UhGAzqjjvuVnl5RcL1bW0n5XRG5XA4VVBQKMPIUlaWV1lZyTs3\n3HbbnWOKO9kqCQA4FyQiMKxAoEMtLU1xSQipf49dc3OTAoEOtj8AAIBRO3LkiIqmz0h6rnBajRob\nG7RgwcIUR3Vu+vp61dvbm9AOcubM2Um3Krz++stqbDwq0wzK6XR+s1UhS6tXr1FZWXnC9eXlfhUX\nl8bVSxhYuZDMpZdeQbcGAGmBRASG1dBwVIaRvECQYXjU2NjINggAADBq06ZN03vvfazy6YkdCQIt\nx1VZe4UNUfU7frxR7e2nExILF110qUpLyxKuf/fdt3Ty5Im4bQ1er1fTp1cnvf+VK1fFEhDJ2kue\nbcaM2ef9nABgMiIRgWFVV9fINENJz5lmSFVVVSmOCAAApLOiomK5uk4rEg7LNajWQCQclqe3QwUF\nhaO6n4HtDX19QWVleeXxJNat2rt3j5qbjyckFq699kbV1MxMuL6p6bg6Ok7HCisWFhbL6/UqOzv5\nloSbbrptdE/6G8lWSQDAVEQiAsPy+Qrk91cqHDbjChOFw2H5/ZVsywAAAGN2/1136nfPPicVlquk\nskqnjh6UOlp1/crLtX//Vyovr0iakPjgg/dUX79fphmUaZpyOl3yer267robkxZGzMvL07RpVQnF\nGHNycpPGtXz5inF/rgCARCQiMKL16zeorm6TmpsTu2YAAAAMaGlp0aFDjbGVBwP/zZ+/QJWV02PX\nZWdn65G/+Z5efvl5HfvkDWVnZSs3L0f79n0hw/AqP9+XNBFx4YVLVVu7OFYvYaRWn2xtAIDJachE\nRHNzs55//nkFAgEtWLBAN910k7xeryTpscce0yOPPJKyIGEvwzC0ceOjCgQ61NjYqKqqKlZCAADO\nCfOLycWyLIVCphwOZ9KuDfX1B3TsWMM3WxvOJBeWL1+hefMWJFx/6NAh7d9fH1dYMTc3b8huC7fe\num5M8TL/AIDMMGQiYsuWLbrpppvk9/v1zjvv6Le//a0eeOABGUbi/jtMDT5fAYUpAQDnhfnF+LIs\nS5FIOG71QTDYp8LCIhUWFiVcv2fPTu3b90XsOtM05XZ7dOWV16i2dnHC9W63Sz5fQULHhvz85LUO\nLr/8cs2Zs2jcnycAIL1YliXLsoY8P2QiIhQKadas/r12t956q15//XU9+eST+v73vz8ugZWVUaxn\nMmAc7McY2I8xmBwYh6mB+cXw2tvbderUKfX19amvr0+9vb3q6+vT7NmzNXt24jaDN954Q9u2bVNW\nVlbcf5dcconKyhK7Ulx00WItXDgv7lqn0zlkPGVlS8b8HNJ9DDIBYzA5MA72YwzOTyQSSXg/Gum/\nwddddNFFuu225EV9h0xEGIah/fv3a+7cuXI4HPrWt76lZ599Vk8//bRCoeRdFMaC/sb2o8+0/RgD\n+zEGkwPjYL9UTdYycX5hWZai0WjSegVNTcfU0HA4bsWCaQY1f/5CLVqU+CF/7969Onjw61jXhoFV\nCD094aTPbenSy7Rs2eVJ40r+/4VHHo9HkYjU3R1Rd3f3mJ/vcHgt248xmBwYB/sxBlI0GpVpmgnb\n6/pXxMV3Ezrzc1Cm2X8sGo3G3of6/zcrVvx34Ofc3EIVFydeYxjeuGYHZxvyzG233abNmzerp6dH\nS5culSStW7dOr7/+ug4cODD+/y8BAICMNxnnF/1tIMNxk7Hs7JykWxsOHNinzz/fHZuwDXRvWL78\nMq1YsTLh+kgkIofDKZ+vMG4CN1SLykWLliRNUAzF4XCM/okCANLK4DbFA8kB0wzG/XwmiZD4cygU\nksdjnLW9Lj5ZUFhYlJD8HvjZ7fZM2PuMwxpu48YQenp6lJOTc14PPNWzU5MBWUL7MQb2YwwmB8bB\nfpNh+ep4zC+OHj2hQKA9oWtDaWlp0g4Kn332qd5/f6ucTuc3k7D+ydcFF9QmTQh0dLSrszMQ982P\nYRjDbm+YSngt248xmBwYB/tNljGIr+OTuPpg6NUJ/f92uVxx7YcH3n+ysrLiEgdnJxEMwzsp3p+G\nml+cU/vO850kAAAAnG085heNjUe0e/fOhG92pOTf6CxceKFqay+UyzW6KVFBQeGQqxkAAJmnf3vD\n6BMH8YmGPlmWlTRZMPDvrKysb4oCZ8WtWBg4P1Kb4nR1TokIAACAyWjevAVJ20oOZbj9qwCA9DfQ\npjh5IiHxZ9Ps+2brQ//P4XBIhmGclUiIr4eQm5s7ZA0Ft9vNNrokePfFhAkEOtTQcFTV1TX0/QYA\nAOetpaVFf922TVHL0pWXXqJpldPsDgnABEvWpnhwfYSzfx5YnRAOh9TT0yvTDMrtdifdunCmJbFP\nJSXepKsSDMMgkTABRkxEtLe366WXXlJ7e7seeOABPfvss1q7dq0KC1mWiORM01Rd3Sa1tDTJMDwy\nzZD8/kqtX7+BPvEAAEnMLzB2z2x+WScdhmYvu1qStHnXThVu365v37HW5sgAjCQSiXzTvSF+tcFo\ntjkEg0FJSlpoceDf2dk5KiiIL7o4bVqJurrCMgwjY7c3pLMRExGbN2/WypUr9eabbyovL08XXnih\nnnvuOT344IOpiA9pqK5ukyIRUxUV/tixcLg/ObFx46M2RgYAmCyYX2Asdu35VD0Ffs2ZNS92bPaS\n5Wo9dkQfbd+myy9dYWN0QOazLOsc2kCeuS4SCQ+zIqG/UHBeXt4QxRf7uzeMVXFxviIR+4tVIrkR\nExE9PT2aM2eO3nzzTTkcDi1fvlzbt29PRWxIQ4FAh1pamuKSEFL/Htzm5iYFAh1s0wAAML/AmHy2\nv17TLrsh4XjZ9Bn66qO3SEQAIxhoUzxUm8eh6yUMHDPldnsGrUpI7OLQ36Y4eRcHj2fi2kAiPY2Y\niPB4PAoEArGfjx49SmEnDKmh4agMI3nG0jA8amxsVG0tiQgAmOqYX2Asoo6h289ZTpZcY2ro394w\n8uqDwcmFwUkFh0NJtzUMJAtycnJVVFScdEWCYXhtbwOJzDLiO/5NN92kJ554QqdPn9b//J//U729\nvbr33ntTERvSUHV1jUwzlPScaYZUVVWV4ogAAJMR8wuMRa7bqXDIlNsTX2sqGoko2xm1KSpgbPq3\nNwzdneHsAoxnb3uIRqNxKxDiEwn92xvy830JhRgHfibZi8lkxN/Grq4urV+/XqdOnZJlWSotLaXY\nB4bk8xXI769UOGzG/bELh8Py+yvZlgEAkMT8AmOz5vrr9as/P6vFN9wRt7x773uv6qE7brExMkwl\nA9sbhi6qeCZxIEUUCHTFJR5CIVMej3FWe8f4ZEFBQeGQqxbcbrY3IHOMmIh48803NX/+fJWXl6ci\nHmSA9es3qK5uk5qbE7tmAAAgMb/A2OTl5en+227Ry++8qe6oQ5KlXIel733rBhUU0GkFoze4DWSy\n7gwjtYV0Op1JayAMJA5yc/NVXFyqsrJC9fVF484ZhsH2BuAbIyYiioqK9MILL2j69OnyeM7s/V+6\ndOmEBob0ZRiGNm58VIFAhxobG1VVVcVKCABAHOYXGKuy0lI9cO89docBm0Wj0aTFFEfzs2kGFY1G\nldi1IT6p4PMVxtVHGHx+tCu3ysry1dpKxwZgKCMmInJyciRJx44dizvORAEj8fkKKEwJAEiK+QUw\nNVmWpVAoNELrx+SFGE0zqFAoJMMwkhZTHEgwFBUVJy3GOFAnge0NgP1GTESsXbs2FXEAAIAphPkF\nkL4S6yQMl1SIP2+aplwuV9JtDQP/zs/3qbQ0K+mqBMMwhkwkmKap9vZ2FRcXU5gRmORGfIX+7Gc/\nS3r8n/7pn8Y9GABTRyDQoYaGo6qurmHrDjAFMb8A7BONRkeshzBcFwfLUlwS4exEQnZ2jgoLi2QY\niV0dDMMY98K04XBYT/3iv6j7y/eVbXaoN7tUJctW6+6HH2X1AzBJjZiI+MEPfhD7dzQa1ZdffqlI\nJDKhQQHIXKZpqq5uk1paEouZGoYx8h0AyAjML4Bz198G0ky6AuHAAUttbYEkqxTO/BwOhxNWJAyu\nmWAYWcrLyxuyhsJkW23w+5/+B806+qa8XqfklaRWde58Qs/8r6juWf/v7A4PQBIj/hUpLIyvRHzl\nlVfqV7/6lVatWjVhQQHIXHV1mxSJmKqo8MeOhcP9yYn773+QVRLAFMH8AlPZQBvIkQotnp1IGDhv\nmqbcbk/caoOBZEFhYb4cDqd8vgJ5veVJCzN6PJnTBvJka6t08AN5s+O7UeQbDn354Uv6zckmuUI9\nchdN0/X3PiR/xTSbIgUw2IiJiCNHjsT+bVmWWltbFQ6HJzQoAJkpEOhQS0tTXBJCktxutw4e3K//\n8l/+k/Lz81glAUwBzC+Q7iKRSMKKhNF0bRg47nQ6hlhx0P9zTk6uioqKk543DO+QbSCnWreGr7/4\nVNOc3ZISt3sUh9pUcPAtleV6ZJ209PyP/6rV//RTzVmwKPWBAogzYiJi69atcT/n5ORo3bp1ExUP\ngAzW0HBUhuFJeq6oqEjhcFjFxcWSzqyS2Ljx0VSGCCBFmF/AbpZlxSUHTLNPfX2jLb7Yp2g0elZy\nILEeQn6+L2kNhf42kJNre0O6qpk1T1vDhnzexK1dHX1hVfv6v9BwOBxaYrTp3T9u0pz/9ItUhwng\nLCP+BVyzZo3Ky8vjjjU2Nk5YQAAyV3V1jUwzlPTc6dOnNX369NjPbrdbzc1NCgQ62KYBZCDmFzhf\n/dsbQkNuYxipi0MoZMrjMRLqIwzeylBQUJSw9WHgZ7c7c7Y3pLOqmpnqrlgiK7AzbjxCEUs9oai8\n7viVI8GGvYpGo0OuKAGQGkMmIo4ePSrLsvTiiy/qjjvuiB2PRqPavHmz/uEf/iElAQLIHD5fgfz+\nSoXDZlyhq3A4rN7eXmVlZcVdbxgeNTY2qraWRASQKZhfYLBIJDxMImH4Lg6mGZTT6Uza/nHg59zc\nfBUXl8owvMrKil+14PEYfBjNEPf9H/9NT/73/1O+5j3yGyEd7naouS2gq2f4Ei92MObAZDBkIqK+\nvl5HjhxRV1dX3PJJp9Op5cuXpyI2ABlo/foNqqvbpObm/q4ZwaCphoajuvjiixOuNc2QqqqqbIgS\nwERhfpFZotFoXPKgs7NVJ06cHnW9hGg0mrSY4uB/+3yFCfUTBq4f7zaQSE8FhUX6N//5VzpUv1+H\n93+p6+Ys0Jv/faM8ro6Ea7NqLiQBBUwCQyYirr32WknS7t27tXTp0lTFAyDDGYahjRsfVSDQocbG\nRlVVVen3v///FImYcdeFw2H5/ZVsywAyDPOLycWyLIVCobO2LgxXaDF+hUI4HJJhGLHkQX5+rhwO\nV9zqhP6Ci4nFFgfaQLK9AeNl1ux5mjV7niRp9s0P6tCWTZqV3T+/iEQt7YmU69bv/6OdIQL4xog1\nIqZPn65XXnlFptn/IrYsS6dPn9aDDz444cEByFw+X0Fsy8XZqyQGd80AkJmYX4yfcDicNFlgmsFv\nii8m1kcYfI3b7U66rWHg5/x8n0pLs5LWUDAMIy6RMNU6NmDyWr3ue9o3f7E+ee1PUl+nPKXV+t69\nD6qwsMju0IApwbIsWZY15PkRExF//vOfdcEFF+jo0aNatmyZDhw4kFBcCgDOR7JVEqyEADIb84sz\n+ttAmgldG86ujzBU8UXLUlyC4OwuDtnZOSosLEra1cHrHboNJJDuLqhdrAtqF9sdBpC24tsUB2UY\nhoqKihOua2g4ok8//SShzs/ChYt0zz13Jr3vERMRlmXpuuuuUzQaVWVlpZYvX65f//rX5/+sAOAs\ng1dJAMhsmTS/sCzrm0TC2VsXhm//OPBzOBxOWG1wds2EvLy8uFUKg88NLv4LAMDZTDOojo6OhAS3\nz+fT7G+2Mw124MA+vf3264pEwnGr5GbPnqfly1ckXF9YWKQlSy5OWDU33PvTiO9cHo9H4XBYJSUl\nOn78uGpqahQOh8f41AEAAM6YTPOL/jaQ4RHaPyb+PJB4ME1TbrcnbrVBsoKLZ0/QBn72eGgDCQAY\nvUCgQ4cP1yckt8vKynXJJZcnXN/UdEwfffR+wntUbm5e0vufOXO2HnjgkVG/P+Xn+5Sfn6RLzTBG\nTEQsWbJETz75pO666y49/vjjOnjwoPLz88f0IAAAAINNxPyiu7tb7e2nhyy2eHYyYfA5h8MxbBvI\nnJzcb4ounp1k6D/P9gYAQDKRSCT2nuNwSAUFiXVKWltPaOfObQnb8qZNm66bb74j4fpgMKj29jZ5\nvVnKzT3z/uTzFSaNYcaM2ZoxY/aoY3a7PaN/gufIYQ1XQeIbwWBQXq9XgUBAx44d05w5c2QYxnk9\nMIWM7EdBKfsxBvZjDCYHxsF+ZWWp/5JhvOcXP/nJT74poJhYVDGxfsLol49i9Hgt248xmBwYB/uN\n5xhEImF1d3cnJLa9Xq/mzJmfcH1T0zG99trmWJvigfel6uoZWrXqhoTru7o61dR0LOl7lsuV3u9P\nQ80vRnxWkUhE27Zt08mTJ3XLLbfoxIkTmj8/8f9sAACA0ZqI+cU///M/M/EHAIyot7dHR44cjlt9\nYJpB5ebm6bLLrky4vrX1hN54Y0vCqrjS0uRFlktLy3XPPd8bdZvivLx8zZu3YFyeW7oYMRHx8ssv\nKzc3V01NTXI6nWpra9OLL76oO+9MXv0SAABgJMwvAACjFQ6HZZpBRSKRpLUIOjsD2rHj47gVC5FI\nSLm5+br99rsTrjfNoBobj8RWHeTl5cvrLR2yzkFFxTTdf//Do47X4/HI45n47Q3pbMRERFNTkx55\n5BEdOHBAHo9H69at0y9/+ctUxAYAADIU8wsAmDosy0par0dyaM6cxK4N7e2ntWXLC7FaPpZlyevN\nUnm5X7fempiwdrs9Kivzx9XvqawsUU9PJGk8BQVFWr16zXg/TYzBiIkIh8OhSOTMAPb09FDZGQAA\nnBfmFwCQvkKhkBobj8QlFoLBoNxul664YlXC9YFAu/785ycSOgcVFBQlTUTk5eXr5ptvj6vjM9x7\nRHZ2thYtWhJ3rKQkX9Eo2/UmqxETEZdddpl+97vfqaurS6+++qq++uorXXPNNamIDQAAZCjmFwCQ\nOpZlKRIJyzRDysnJSTgfDAb1yScfJXQVcrs9uvPO7yRcHwqF9OWXe+OSCj5fgXJycpM+fkFBkX74\nw42jjtftdqu4uGT0TxBpZ8iuGZ9//rkuvPBC9fT0qLu7W4cOHZJlWZo5c6b8fn+q4wQAABmA+QUA\nnJtIJKK+vr64/0KhkBYsSCxy2NfXpz/84Q9x1zocDhUWFmrjxsSEgGma2r59u7KyspSVlaXs7OzY\n/xYVJbabBM7XkCsitm7dqtraWv3+97/XI488orKysnF9YKpa24+2QvZjDOzHGEwOjIP9UtW+k/lF\nZuO1bD/GYHIYaRyi0aiamhoHbW0IyjT7FA6HtXJl4uow0zT1+OO/SGjvmJ2do5KS6Unv/7LLrk7a\npniouObPX5JwLBxO37+rvBYmh6HmF0OuiHjhhRe0e/duWZYVtx9n4Of/+B//43kFxC+F/Xhx2o8x\nsB9jMDkwDvZLVSKC+UVm47VsP8Zg4liWpXA4nLQbQjQa1c6d22L1EqSIOju7FQqZuvvu7yXUN4hG\no3rxxT/FtYIcSBosWXJx0seWRC2dMeC1MDmMOREx4KmnntJ999037gHxS2E/Xpz2YwzsxxhMDoyD\n/VKViBjA/CIz8Vq2H2MwvEgkElcDIRgMqrp6RsIHfMuy9PLLz6mvry/W4SEYDMrpdOrhh/9eTqcz\n4fpt2z6IJRXKygoVDFryer0qLS0ngWADXguTw1DzixGLVU7EJAEAAExtzC8AnK+TJ098kygIxiUL\nLrnkMrlciR9zfv3rX8o0g3EFFg0jS9OmTZfbHb/KweFwaOnS5TIMY9BWCCPp/Q5cf9llV8Z+5kMw\nMLwRExEAAAAApp7e3l653e6kWxHO1XBbDPbu3aOenu6EFQtr1twhrzcr4fq//nWrJMW2NAxsb4hG\nLblciY99//0Pj9gGcrDq6hmjf2IAxoREBJABAoEONTQcVXV1jXy+ArvDAQAAaWzbu29ozyu/l3Xi\noCIuQ94ZS3X7I/+XSsvKJUnhcDi2+iAY7FNpaXmsEOJgW7e+qUCgPWHFwv33P6y8vMTl2t3d/SsI\n8vLy5fWWxpILye5bktat+/aYntd4JlQAnB8SEUAaM01TdXWb1NLSJMPwyDRD8vsrtX79BhmGYXd4\nAABgEgsEOtTX1ztoBUJQR+r369Qrv9Aid6eUL0khWSfe1xP/+e817ep1OnWqVZZlxa1CuOmm25Mm\nFmbNmi2HwxlXiNEwvHIlW64gacWKK5MeB5B5SEQAaayubpMiEVMVFf7YsXC4PzmxceOjNkYGAABS\nrb7+gA4eDOrUqY5BKxaCuuqqa5OumHzvvbfU29sT17WhYd9uLfCaUuTMdQ6HQwtD9Yq4HFr3ww1y\nuUa3vWHGjNnj+fQAZBASEUCaCgQ61NLSFJeEkCS3263m5iYFAh1s0wAAYBIaaAM5kCzIz/cl3Tbw\nyeH9yV0AABtASURBVCcf6eTJ1rhtDcFgn26//R6Vl/sTrj91qlUOR0SSU/n5BSotPZNgSOa22+5K\nOHZw86/kiQQTjud5nGo4fjChqCMAnAsSEUCaamg4KsNIPhkwDI8aGxtVW0siAgCAidLX1xvr2jC4\nuOKMGbOSblV4/fWXdexYg4LBoByO/iKLhuHVjTfeorJv6i8MVlparqKi4kErFvq7PHi93qTxXHrp\nFefdrcGVUygFjiYcD0ctGfnF53y/ADAYiQggTVVX18g0Q0nPmWZIVVVVKY4IAID0dvx4ozo62uOS\nCsFgUMuWXaLS0rKE67dufVMnT56Iq5dgGF5Nm5b8PfiKK1bJ6XTI680asgDjYDNnpn5rQ/Ulq9X2\nyh4Vn5Xr+DxUpPvvuj/l8QDITCQigDTl8xXI769UOGzGTWbC4bD8/kq2ZQAAMtrA9oZgsE9er1ce\nT2KR5i++2KPm5qaEFQvXXLNaNTUzE65vajqmjo722AqEgoJCGUaWsrOzk8Zw8823jynm/PzEVRKT\nzeq19+lPJ46paftmXeDtUk/I0kFPlVY++O+SrvIAgHNBIgJIY+vXb1Bd3SY1Nyd2zZgqaF0KAOkr\nEonEkgODiyv6/RVJ/6Z/+OF7qq8/ELvW6XTKMLy67rpvacaMWQnX5+TkqaJiWkLXhtzcvKTxLF9+\n2bg/x3R07/p/p/Z7H9KHb78qX1Gx/s01N8rpdNodVkqcbG3VO8//TpHuDvmmzdHqdd+lExkwARyW\nZVl2PPD57F3D+DjfPYQ4f+M1BoFAhxobG1VVVTVlPoyPV+tSXgeTA+Ngv7KyzPimk98je1lWr+rr\nGxOKK86bt1CVldMSrn/77dd0+HB9bFvDQM2EJUsuTnp9R0e7otFo7HqXi+/Uzsbf03P38buv67P/\n/d+0MKtTTodDfeGoPnPW6Dv/9/8rf0Xi7+NwGAf7MQaTw1DzC/56AxnA5yuYcoUpaV0KAOevf3tD\nSJIjadeGQ4cO6NixxoSaCRdfvELz5l2QcP3Bgwe1f399XL2EwsJiZWUl79pw/fU3jSnegoLCMV0P\njFYoFNLOp3+uZdldkvpbk2a5nbrEatCW//UTPfgf/tXeAIEMQyICQNqhdSkAnBGJhGMJgoFkQWFh\noQoKihKu3bNnl/bt+yK2YsE0TTmdLl111bWqrV2ccL3T6VJeXr683tK4rg35+b6ksVxxxRWaO/fC\ncX+OwET761tbNC/aJMkVd9zhcCh45DNFIhG5XK7kNwYwZiQiAKQdWpcCyFSdnQG1t5+O29YQDAZV\nVVWjqqqahOs//PAv2r17R0LXhgsvXJo0EVFTM1N+f0VcvYThPlzNmDErae0FINP0dHfJ505eB8Px\n/7d3//FR1Hcex9+TnUx+koSQsBuyAVsE0kRBRfAH9gSLFcViBa3aSs9qI23Qytm73j36qD3vl/fo\no1evd1Xaa2yL9qxaPRWkFSotaiuKIIIQBcEqZCG7BvJjIYRM9sf9EYXGLC1JNjPZ3dfzP2aSmc/y\n3YXZ93y/84nZBBFAkhFEAEg5tC4FMJLE43HFYrGEX1Kam/erqWlvv64NU6Z8QjU1U/v9/L5972nP\nnl19goLejhCJw9fzzpul88+/SIZhnFKtJSX9wwkA0kVz5+vxtQ+oNq+z3z7TN5kHVgJJRhABIOXQ\nuhRAMsXj8Y8sb+hWXl5ewi/te/a8rcbGbX06PNh2t6ZPn6mZM2f1+/lIJCJJKioqOv4gxg/bQiZS\nWztVtbX9A4qTyZROBsBwKy4uUen5n9XBV3+hspwTz/Lf3V2o6V/4kouVAemJIAJASqJ1KYBEjh3r\nUkdHR7+uDWPGlCdcYrBjx1b94Q8vyDDUJyiYMqUmYRBRXl6uc86Z2a/Lw8kCgaqqCaqqmpD01wkg\n+RbefIdeGHeadr2yVrGuDpmllTrvM1/QlJppbpcGpB2CCAB/UTjcoaamfaqqGj9iZhtYlqWlS5dl\nZOtSACfX1LRXW7e+1ud5CTk5uZISdyuvrq5VdfUZfWZX/TnFxaMTPnsBwKnbsH6N3nn5N4rbncou\nn6BPX1enMWXlbpclSbp43lW6eN5VbpcBpD2CCAAnZdu97TBDof6zDkbKWslMbF0K4OQmTarWpEnV\np/zzppn42QsAhscTDd9T9ubHdPoHHV1jrVv02D9u0IJv/EB+HowKZAwWFgI4qYaG5YpGbfl8XpWW\nlsrn8yoa7Q0nAAAABiJ4IKDOV5/S2NwT27IMQ2eb72v9I1xbAJmEGRFAEozEpQtDFQ53KBRqls/n\n7bPdNE0Fg80KhzvS5rUCADBSRCIRPfv4gzq0a5MUi6pwfI2u+PwS5efnu13akL383CpNyuuW1L/L\ny9GmRucLAuAagghgCFJh6cJgNTXtk2UlnrJsWdkKBAIsiQAAIIlisZh+/E+3q/rQJpVl905cjm7b\nqgcaN+rL//bT1A8jDENxJYohJNEBBsgofOKBIUjnpQtVVeNl2z0J99l2j/x+v8MVAQCQ3l5cu0of\nb9mkvOwTl+ieLEPnRN7Rr3/xPy5Wlhx/dcW12nWsf5gSj8eVP/5MFyoC4BaCCGCQPly68NEnrZum\nqVCod+lCKisqKpbXW6FIJNJneyQSkddbwbIMAACS7EDjRhXn9L8892QZOrLvTRcqSq4xZWXyzrlR\ne7tOXDv1RGPaHPfr8r9e5mJlAJxGEAEM0qksXUh1dXX18ngsBYMhtba2KhgMyeOxVFdX73ZpAACk\nnyzPSXcZnvRYUT3/hjpNXXqf3p1wmf5Y8Um1zrxZX/7Owyob6/3LvwwgbaTHv2iACzJh6YJlWVq6\ndJnC4Q4FAgH5/X5mQgAAMEwmnTdX+3f+Rt68vtuPRWIaPekcd4oaBjXTzlHNtPR5PQAGjhkRwCBl\n0tKFoqJi1dTUptVrAgBgpDn3wosVrr5coa4T28LdMb01eoau+NyX3CsMAJKMGRHAENTV1auhYbmC\nwf5dMwAAAAbCMAwt/pu7tXnDHO3euE6KRVVRO1NfuewqZdFVAkAaIYgAhoClCwAAIJkMw9CMWbM1\nY9Zst0sBgGFDEAEkQe/SBQIIAAAAAPhLmOMFABiUcLhDjY3bU75VLQAAcF88HtdrG1/Sul89pcOH\nw26Xg2HGjAgAwIDYtq2GhuUKhfo/G8WyLLfLAwAAKaZx66t6ccV3VdX1rgpM6bFnfqCS6Vfqmro7\n3S4Nw4QZEQCGhLvimaehYbmiUVs+n1elpaXy+byKRnvDCQAAhqKrq0srf/4jPfydv9Mj/3W3du98\n0+2SMMy6urr0wo/v1lnxvRqTm6VcM0u1OUeUt+UxrXv6EbfLwzBxbUZEefkot06NP8E4uC9Vx8C2\nbd17770KBALyeDyKRqPy+/268847U+6ueKqOgRs6Ojp08GBI5eXlfbabpqmWlpAsK6bi4sE9L4Vx\nQDLwPnIfY+C+VB2DULBZK755k2p73tNYT+/90k3/+ZxaFt6hq268xeXqBi5Vx8Fpj//sYdVmva+P\n3iMvteLas+13Kq+7ddDHZgxGLteCiJaWw26dGh8oLx/FOLgslcfg/vu/r2jU7vOFtLOzU/fc8x0t\nXbrMxcoGJpXHwA2NjY3yeDwJ93k8Hm3d+pZqamoHfFzGwX3pcrHG+8hdfJbdl8pj8L//8c+aFt0r\nw3PiC+nHcnvU+H8/0pkXztOoUUUuVjcwqTwOTjsYCKjSk3iifnfboUH/PTIGI8PJri9YmgFgwMLh\nDoVCzTLNvlmmaZoKhZpZppHGqqrGy7Z7Eu6z7R75/X6HKwIApIuuvTtkGEa/7dU5h/X8r55woSI4\nobRqkg7bsYT7PKMrHK4GTiGIADBgTU37ZFnZCfdZVrYCgYDDFcEpRUXF8norFIlE+myPRCLyeitU\nVEQbWwDA4MRjib+MGoYU7bEdrgZOuXjeVdqVM1HxeLzP9qbuHE299FqXqsJwI4gAMGDcFc9sdXX1\n8ngsBYMhtba2KhgMyeOxVFdX73ZpAIAUluufknD77mN5mnXZQoergVM8Ho9u+OZ/a2f5BdpyOFfb\n2w1tt07XuEXf0PQLZ7tdHoYJ7TsBDNiJu+J2n+UZ3BXPDJZlafHiL2nnzrckGaqurmbMAQBDNvv6\neq29922daR48vkTj/WPSqJlXq3zsWJerw3DqaDsk9dgyDUmebHlyCzTGy42tdEYQAWBQ6urq1dCw\nXMFgsywrW7bdI6+3grviac62e9t0hkInxn3Tpt5xT7VuKQCAkeW006fos9/+iX73y5/IPrhPRk6B\nJl5wmWZdcrnbpWEYtR46pOe+/3VNsw5JhR9sDG/TSz/8e5Xc9VNVjCOQSEcEEQAGxbIsLV26TOFw\nhwKBgPx+P3fFM0BDw3JFo7Z8Pu/xbZFIbziRSt1SAAAjk9c3Tjd87S63y4CDnnv8JzrDPCip74NK\na7LbtP6Jn+rzX/u2O4VhWPGMCABDUlRUrJqaWkKIDEC3FAAAkGyRtmZ5svp3SzEMQ5G2ZhcqghMI\nIgAAp4RuKQAAINmMvKKT7svK50ZXuiKIAACcErqlAACAZJt5+XV651hOv+37jpma9im6paQrgggA\nwCk50S0l0mc73VIAAMBgnT6lRv4Fy/RGT5mO9kTV1RPT9p5SlV5WrzPPmel2eRgmPKwSAHDK6JYC\nAACSbfb8Rbrw0s/opfVrFI1E9MVPXaHc3Fy3y8IwIogAUkg43KGmpn2qqhrP3We4gm4pAJA+bNvW\nc089rPZ3GyUzW5Mv+LRmzJrjdlnIUJZlac5lC9wuAw4hiABSgG33tkcMhfrfhbYsy+3ykIF6u6UQ\nQABAqjp69Kga7qrT1GO7VGr2rtbev/u32r1lgT5/+7dcrg5AuuMZEUAKaGhYrmjUls/nVWlpqXw+\nr6LR3nACAABgoJ556D5Nt99Wrnni64A3VzLfWK23dmx1sTIAmYAgAhjhwuEOhULNMs2+E5hM01Qo\n1KxwuMOlygAAQKrqfG+7PFlGv+1V+TFtf+HXLlQEIJMQRAAjXFPTPllWdsJ9lpWtQCDgcEUAACDl\nxeMn36WYg4UAyEQEEcAIV1U1Xrbdk3CfbffI7/c7XBEAAEh1uf5qxRKEEcFjhqrPm+tCRQAyCUEE\nMMIVFRXL661QJBLpsz0SicjrraBjAQAAGLD5X7xNrxmnKRI7EUa023G1f/wSTTv3fPcKA5AR6JoB\npIC6uno1NCxXMNi/awYG7k/boJaXj3K7HAAAHFdcXKJb7lmhNY89oM6mnZJpqXLaJ3XT/EVul5Zy\nfv+bVdr1wtOKtgXlKRytynMv1eL629wuCxjRCCKAFGBZlpYuXaZwuEOBQEB+v5+ZEIOQqA3qhAnj\ntXhxHW1QAQAZp6CgQItuvsPtMlLauqd/ocNrfqDanKiULan7oNrX79ZD9mFdcePtbpcHjFgszQBS\nSFFRsWpqatM6hAiHO9TYuH1YuoEkaoPa2dlJG1QAANJYKNSsJ1fcrydX3KfggeQ95DsWi2nP+ifk\ny4n22V5iScENq3TkyOGknQtIN8yIADAiJJqt8OHyk2TMVviwDarP5+2z3TRNBYO9bVDTOeABACAT\nPf3g/Wr/w6OanHdMkrT2pUdVMHOhrqm7c8jHbml5X4WHA1KCVZ7+WKu2bXpZs+Z8esjnAdIRMyIA\njAiJZitEo3bSZivQBhUAgMzy+qsvKfrSzzUlv1uGYcgwDE3Ot2Vufkwbf//bIR+/oKBQxzx5Cfcd\njnk0xlsx5HMA6YogAoDrPpytYJp9J2mZpqlQqDkpyzRogwoAQGZ588XVGpcX67fdmxvX7pfWDPn4\nhYWFUtVUxRO0QW0v+4Sqa84c8jmAdEUQAcB1TsxWoA0qAACZJW53nXRfzD6alHMsXPqPes2cpLbu\n3sDjSE9MW2KVWvT1f0nK8YF0RRABwHVOzVaoq6uXx2MpGAyptbVVwWBIBQUFtEEFACAN5fk+rkis\n/2yFaCyuXO/HknKO0jFluu17D6vkun/VgTNvUNYV/6CvfP8JTaquTcrxgXTFwyoBuO7EbAW7z/KM\nZM9WSNQGdeJEv1paeKo1AADp5rLP3ayfbVmv6fGADMM4vn1brEI3Xv/lpJ3HMAxdOGeeNGde0o4J\npDtmRAAYERLNVvB4rGGZrZAJbVABAMh0hYWFuv6uH+qd8Zdqe8ynN2Je7a68RIu+9UMVF5e4XR6Q\n0ZgRAWBESDRbgaAAAAAMRbnXp8V/e4/bZQD4CIIIACNK72wFAggAAAAgXbE0AwAAAADSVCgUUiDQ\nlLDNKOAWZkQAwAgQDneoqWmfSkpK1N7erqqq8SxNAQAAg7J+9RPavuZhdQX/qEiPrWg8Lu/pZ2rq\nlTfrgksud7s8gCACANxk27YaGpYrFDogy7J08OBBhcNhVVSM07hxftXV1cuyLLfLBAAAKWLNEw/q\n2LrlmpETlypzJOWo41hEb763Q+/+8t9VUubTJ6ae7XaZyHAszQAAFzU0LFc0asvn86m0tFSTJ0/W\nWWedpba2VkWjvSEFAADAqYjFYtr74lPy5vRdhlGcayrHNOTN6tTmNY+4VB1wAkEEALgkHO5QKNQs\n0+w7Oc00TeXl5SkSiSgUalY43OFShQAAIJUEg80qPLI/4b7TS3O1t71b0Y4Wh6sC+nNtaUZ5+Si3\nTo0/wTi4jzFwn1tjcODAH2VZ2Qn3jR49WuFwWJaVraNH2zRxot/h6pzHZwHJwPvIfYyB+xiDkcGN\nccjNrdTa7AJJR/vta+uKqjjXVGTM2Ix5j2TK60xFrgURLS2H3To1PlBePopxcBlj4D43x6CwcIxs\nuyfhvra2NlVWVqq9vUP5+aPT/n3CZ8F96XKxxvvIXXyW3ccYjAxujkO0cqriB1+WYRh9tu9t79bH\nKso0+ZMLMuI9wmdhZDjZ9QVLMwDAJUVFxfJ6KxSJRPpsj0Qi6urqkmma8nor6J4BAABO2aLb7tYW\nq1otXTFJUsexHj33TruMMVUqm3+7zp4xy+UKAbpmAICr6urq1dCwXMFg/64ZHo+lurp6t0sEAAAp\nZHRpqZZ+9yFt3vCCmt7eru64R1dOna5pZ58rj8fjdnmAJIIIAHCVZVlaunSZwuEOBQIBFRcXqaMj\nLL/fz0wIAAAwKIZhaMas2Zoxa7bbpQAJEUQAwAhQVFSsmpre4KGy0uViAAAAgGHEMyIAAAAAAIBj\nCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIA\nAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAA\nAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBj\nCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIA\nAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjCCIAAAAAAIBjjHg8Hne7\nCAAAAAAAkBlMt07c0nLYrVPjA+XloxgHlzEG7mMMRgbGwX3l5aPcLiEpeB+5i8+y+xiDkYFxcB9j\nMDKc7PqCpRkAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAA\nAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAx\nBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEA\nAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAA\nAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAx\nBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxBBEAAAAAAMAxRjwej7tdBAAAAAAAyAzMiAAAAAAA\nAI4hiAAAAAAAAI4hiAAAAAAAAI4hiAAAAAAAAI4hiAAAAAAAAI4hiAAAAAAAAI4hiAAAAAAAAI4h\niAAAAAAAAI4hiAAAAAAAAI4hiAAAAAAAAI4hiAAAAAAAAI4hiAAyyMqVK3Xfffdpx44dA/7d559/\nXvv27RuGqnq9/vrrWrly5bAdHwAAJB/XFgAGgyACyCDbtm1TfX29zjjjjAH/7t69exWPx5NeUyQS\n0bp167RmzZqkHxsAAAwvri0ADIbpdgEAnPHoo48qHo+roaFBixcv1u7du7Vx40bF43FVVFRo/vz5\n8ng8evXVV/XGG2+op6dHhmHommuu0f79+3XgwAGtWrVK1113nZ599lnNnj1bEyZMUHt7ux588EHd\ncccdWrlypY4ePaq2tjbNnTtXhYWFWrt2rXp6epSfn68rr7xSJSUlferau3evJOnSSy/V/v373fir\nAQAAg8C1BYDBYkYEkCGuv/56GYahJUuWqLOzU1u2bNEtt9yiJUuWqKCgQBs2bFB3d7d27dqlm266\nSV/96lc1ZcoUbdq0SdOmTdO4ceO0YMECjR079s+eJz8/X/X19Zo4caJWrVqlRYsW6dZbb9UFF1yg\nZ555pt/PT5w4UXPnzpVpkosCAJBKuLYAMFh8OoEM9O6776q1tVUPPPCAJCkajaqiokI5OTlauHCh\nduzYoUOHDmnPnj3y+XwDOnZlZaUk6dChQ2pra9MjjzxyfJ9t28l7EQAAYMTg2gLAQBBEABkoHo+r\ntrZW8+bNkyT19PQoFospHA5rxYoVmjlzpiZNmqTCwkIFg8GTHkOSYrFYn+3Z2dnH948ePVpLliw5\n/ucjR44M10sCAAAu4toCwECwNAPIIB/+B3/aaadp586d6uzsVDwe1+rVq/XKK69o//79GjNmjM4/\n/3yNGzdOe/bsOf47WVlZxy8M8vPz1dLSIkl66623Ep6rrKxMXV1dx5+GvWXLFj355JPD/RIBAICD\nuLYAMBjMiAAyiGEYkiSv16uLL75YDz300PEHSl100UWKRqPavHmzli9fLtM0VVlZqffff19S73rL\n1atX6+qrr9asWbP09NNP6/XXX1d1dXXCc3k8Hl177bVas2aNIpGIcnJydPXVVzv2WgEAwPDj2gLA\nYBjx4eiZAwAAAAAAkABLMwAAAAAAgGMIIgAAAAAAgGMIIgAAAAAAgGMIIgAAAAAAgGMIIgAAAAAA\ngGMIIgAAAAAAgGMIIgAAAAAAgGMIIgAAAAAAgGP+H0wyl2a5Tt26AAAAAElFTkSuQmCC\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11bbbacc0>"
+       "<matplotlib.figure.Figure at 0x1a1487e7b8>"
       ]
      },
      "metadata": {},
@@ -666,10 +597,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Regression Example Figures\n",
     "\n",
@@ -680,12 +608,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 32,
+   "metadata": {},
    "outputs": [],
    "source": [
     "from sklearn.linear_model import LinearRegression\n",
@@ -709,28 +633,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### Regression Example Figure 1"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 33,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeIAAAFkCAYAAAD8ADhmAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11bbc6cc0>"
+       "<matplotlib.figure.Figure at 0x1a14895748>"
       ]
      },
      "metadata": {},
@@ -752,28 +669,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### Regression Example Figure 2"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 34,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAAFBCAYAAAD69Z+AAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRK5CYII=\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWQAAADuCAYAAAAOR30qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzsvWmQJOtZ7/fLrfalu3qfnp6Znuk5s89ZZ86RBAhJBCCuhDC+l4hrA0EY3zD4mw2fcAT6ZEyATQTGEAQfjH0dDtlxERJcLC5COkLSkY509jnrzPS+r1Vda+75vv5QUzXV61T1bD198hdRMT1VmW9mZWX+88nnfRZFSklISEhIyONHfdw7EBISEhJSJxTkkJCQkENCKMghISEhh4RQkENCQkIOCaEgh4SEhBwSQkEOCQkJOSSEghwSEhJySAgFOSQkJOSQEApySEhIyCFB73D5MK0vJCQkpHOUdhYKLeSQkJCQQ0IoyCEhISGHhFCQQ0JCQg4JoSCHhISEHBJCQQ4JCQk5JISCHBISEnJICAU5JCQk5JAQCnJISEjIISEU5JCQkJBDQijIISEhIYeEUJBDQkJCDgmhIIeEhIQcEkJBDgkJCTkkhIIcEhISckgIBTkkJCTkkBAKckhISMghIRTkkJCQkENCKMghISEhh4RQkENCQkIOCaEgh4SEhBwSQkEOCQkJOSSEghwSEhJySAgFOSQkJOSQoD/uHQh5fEgpcV0XIQSapgGgKMqOV+P9kJCQh0soyB9DhBAEQYDv+80X3BVd0zQpFAocP368uc5uQq0oCqqq7vlZ63ohISH3JhTkjwlSSqSU+L5PEARAXSwty8LzPAzDwDCMpqVsmmbzbyllcxwhxJYxG//eS3RVVW3+2xBpIQSGYYRiHhJyB6X1YmuDjhYOefxIKRFC4Pv+FjEtFotMT08TBAGRSKRpKQdBQBAEuK5LIpFA13V0XccwjB1/b39P07QdAtp6fm3/+8033+S55567p+juZpHvJvDbhTwU85BDRFsnY2ghH1GklE23RKsFu76+zszMDLFYjLNnz5JMJvF9f4t41Wo1ZmZmuHDhQlOoPc/b8q9pmjvea1jeUBfFe4m5EKJpnbcj5o2bSyeWueM4BEFAOp3uSMwbf4eEPEpCQT5iNITY8zzeffddnn76aQAWFhaYn5+nq6uLK1eukEgkAJr+41YURUFKiaqqRCIRIpFIx/vRsMp3E/NarYbv+7iuy/j4eFtivpuot2OZVyoVTNMkmUx2LObtWubbl238PySkU0JBPiI0/MOtE3S1Wo3p6WmWlpYYHBzkhRdeaEtcG4J8P7Qj5sVikatXr+54vx0xb9cyd12XIAhYWVlpW8xhq3+8Hct8fX2deDxOKpVq7kco5iGdEgryE05rxATUL2bHcZidnaVWq6FpGp/4xCeaE3RbkAJFLKH4GyhaBqkMgWI8EEG+Hx6kZb6xsYFlWQghOhbzTizzWq3WfG/7JGirmDfYz0LfL4ql8f/ty4VifjQIBfkJpGG1eZ7XnKhrtYir1SonT54kmUxy8uTJPQbxUNxvofpzIBQUKUHpwtd/FkXRH6sg3w/bxdxxHDRN2xLCtxcNMW+IdSeWueM4FAoFlpeXD+xmgZ0RLdvFfHFxEcMw6O/v3/U77BeWGIr54ScU5CeI3SImFEXZEjExOjpKT08PiqIwMzOz92D+RyAWQT2GlAGoCopYRw3eRlGuP5ovdMi4H8t8fHycTCZDKpXqWMw7scwbUTG7PfHsFp7YOkfQ+Hw3f/t2gW4kDSWTyVDMHyGhID8BNCbqVlZWiMfjJJNJADY2NpieniYajXLmzBmy2WzbYypiAtQuZCAJAommAEoOVUyicH1LiFxIexiG0fxtOqETy7xarQIwPz8PPJgJUNgp5pZlMTU1xcWLF5uf7ye6+yUNNXzn+8Wbh9QJBfkQ05rIIaWkUCjQ1dVFsVhkbm6ObDa7JWKiM3TAxheS9bxDd1eEWFQA+mP3IT+pHFRYOrHMp6enSafT9Pb2AvfnZtlPzBvzEqZpNt9rtZJb2c0y3x6yuN+xKZfLxGIx4vH4DkHfT8yPopCHgnwI2S1iQghBuVxmeXmZ4eFhnn/+eaLR6MG3oV1A9b6DIvua21RkHqE+DYSC3CnthNE9jO08iAnQ3cTcNE1c12VhYaFjMd/NQt9PzNfX1+nr69tyPu8X0SKlJJFI3Nf5f1gJBfkQ0bhAWlObXddldnaW9fV1otEoZ8+eZXh4+P43pp1ByjyKdwNF+ihCRainEdoVFHH0LI+jwoMU/v3EvFwuI6Xk/Pnzu667n5hXq9Udn+0n5qVSCQDLstoS88YT41EkFOTHzF4RE6ZpMj09Tblc5uTJk4yNjTE7O/vgrDBFRRovIcRZAm0G3+jD0AfvbH9nmFbI/jwqC1kI8ci203AX7MaDtMxN0yQSiSCEaEvMNU3j+vWjOfEcCvJjYrtbAuonW6lUYnp6Gs/zGB0d5dKlS1smPx64UCpppNILyt0JwUfpQ35UQnZUeJSukf0E+X7YLuaNML525kKEEDiO89D27XETCvIjprXGxOzsLJqmMTw8TD6fZ3p6GsMwGB0dpaura8e6qqp2HP2w3wVsmiYTExOsrq6STqdJJBLNx0TXdVlfX9/hG9zLF3iYeRy+3Sd9O4/KEm9sq12BbYj5USUU5EfE9oiJxizy5uYmCwsLpNNpLl26tG/YVKeC3LB0t19Y1WqVqakpLMtiZGSEZDLZFGPP8/A8r7nc9vTl1ll0TdP2nNBplPNsfW+vSZ0nTeB34ygK8qOyQjvd1lE5Z3YjFOSHzG6pzUIIFhYWmJmZIZFI8OyzzxKLxe45VmPddmkIeONkL5fLTE5O4vs+p0+fJpfL4fs+S0tLxGKxLTeD+fl5RkdH9xy7kaSyvdaE53m4rkutVtvxWSuGYWBZFrdv394h3tuFfNe0748pR034gS0da9rhqIoxhIL8UNirGLzneczOzrK2tsaxY8cYGxvDdd22xBgObiFvbm4yNTUFwOnTp+nu7t4y5kFoTK4cRCwbkzpvv/02g4ODzep0nufhOM4OIW+1yvcLtdot7OpRcdSE8lFayEEQdPydjqooh4L8ANkrtdmyLGZmZigWi5w4cYJPfOITqKrK6uoqtm23PX4nk22NG8Jbb73VDJfLZDIH+l4PmoYfUNd10ul026Le6n9vFW3P87Btm0qlsmsolhBiV3/4fu6WwzppdBQFGQ5uGBw1QkF+ALSmNmez2WZbonK5zPT0NI7jMDo6yoULF3YE9R/EBXGvfVlfX29u9+rVq/T09Oy5fGN/noQwt9b41XafKho3vZGRkV2F3Pd9LMva8Vnr8djLV9769/b5gYfFUbPEQ7YSCvJ9sL0rx+LiIrFYrCnEmqYxOjq6xUXQyoMUZCklKysrzMzMkMlkuHLlCjdv3jxgWvWj4VGG1x00bra14P920TZNs/l3pVLh9u3bW9ZVFKUt10prAkQ7+/OoLORH6fLplKN6szi8R/wQs1tqM9RLMN64cYNsNsuFCxeaxcr34qA+4VaEECwtLTE3N0cul9syQdju+GHtir1ptcr34/333+f06dNbboDbJz0bf7uuu2sLrNbfYDdfuWEY2LZNuVzG9/3mew8jFDG0kB8PoSB3wF4RE/Pz8ywsLCCl5KmnntqzVu12VFXtSAhbBTYIAhYWFlhYWKC/v3/XbiCHXWgP+/7dL6qqEo1GO6650HrDbxXyxr+bm5sUCoXmZ9tDEdvxke8XigiP3ofcKUf1ZhEK8j3YK7XZ8zzm5uZYWVnh2LFjXL9+nfHxcQzDaHvsg4Sx+b7P9PQ0i4uLDA0Ncf369T232a7gHdWT+1HyIC3KhqvDMAzi8fiWz9bX1zlz5syev3nrpOduoYjbP2ulVayr1WrTt76bkIehiA+HUJD3YK+ICdu2mZmZYXNzk5GRkS3tkTRN25J3fy86cVl4nsfCwgJra2tkMpm92zIdYPzHJcgHtZDtoMaGu0gtKJPUsvRGh4mpj9dXflhSzRuhiAe1yhtCPTc31+wM3mmC0H6W+Xar/KAZgUfViAgFeRuNSZxCoYBt2/T396MoypbstlOnTnH+/PkdJ8XDiJpwHIeZmRk2NjYYGBigt7eXU6dOtTV+p2FyTwJWUOVW7Q1QIKLEyPtLbHhLnE++QEzrvDj8g+RJjn5otcoBotEoPT09e05It+7PXr5y27Z3vLebVW5ZFrdu3brnBOhhdqE8KEJBvsP21GbHcSiVSui6zvT0NIqiNCMm9rogHqQgW5bF9PQ0xWKRU6dOcfbsWWzb3jGTvx/tCvLjEuODCMuyM4WqaMS1+oSpQRQzqLDiznAqfulB72LbHLVwtHaLC91vgpBlWdy8eZPBwcEtom7b9g63S8N9eOzYsV1rvRwFPvaCvFvERKPq2uLiIrZtc+7cOdLp9D3HehCC3Nqo9NSpU1tilw+aOr0flmWRz+eJx+MEQdC0Shon/8O++Du9GVT8AjEtjQgEvhegGxoxNUHZLzykPTxcHKXiQqqqNt0d7bYfa1jkR5WPrSDvV2Nifn6eZDJJT08PV69ebXvM+xHkSqXC1NQUtm1z+vTpLWU3Dzr+fhayaZpMTk4229dvn/CxLIvXX3+9uQ+NC6f11XiUFLqHrmmkol0dPVo2xvaEQ8kvoCgqWT2Hruw9MRpVk/jSRQl0zIpNqitOoHjE1cfrrniUYWJHKVPvINs5qv5j+JgJ8l4RE41JjOXlZYaGhrh27Rq2bTM7O9vR+JqmdSzIruvy1ltvIYRoFvzZi04nwXYT8IYQm6bJ6dOn6enpYXl5mUgkssVKefPNN3nmmWfQNG1LckTrq+oVmXbeoCoKCBEQ8TP0mGcxxN3IgP18gp7nMV+aZEG9BYoERUVXDS4nX6TL6N31Ow1FRxk33yYi6pN4nnDxsDiR3L2zReO4PWyeFB98uxzmFO1QkJ9w9oqYaEyY5fP5HRETrut2/GikqmqzdOW9KBQKTE1NNdOb23lkux8LuVarMTU1hWmanDlzhp6eni2fbxeU1s9akyMaYViB9Jku/YCY1MhpY0gpMUUZVcnzfPYXURVtx8x9q5g7jkPNrTCZf5OIiCEDBZB4uCwoX+Ws/zxRI7ZDzA3DoI+TrHpzVJ0ahujmTPIqGX3vG9mj4igJxaO0kMMQurscaUFuWHYbGxv4vk9vb28zYmJ6ehrTNDl16hTnzp3bcTF1GsIG9xZMKSUbGxtMT08TjUY5d+4c7733Xtv+s4MIsm3bvPvuu1iWtUWIty+327r7WX1FbwVbVMnofc3lk1qWsrdO0V8lZxzbMXO/ncXaNN25bvrig1vH9vOciB8jKbt2TOzUY2MhYvWilXTszQi3lRlgpnnjaBVv27YRQrCxsXGgVOV2OWqZbQ+zY0grQRB0XAv5KEdbHHlBbszYmqaJrutMTU0hpWR0dJRcLvfAIib2W0dKyerqKjMzM6RSqXsWot+LTlwWtVqN1dVVgiDgwoULuwrx9n3sZFuedOHOx3bVQ1EgmjRAAV+6be0jCjT2qFa0UFSFRKae9q3pOgnjbmyxL30WrEVWnDU0RWNIHWTQHCSXyzUzFBu/93Zr3Pd9yuXyrrP2jWOyX03m7X7zoyS8e3FYevd93DjSgtyImKhUKiwtLVGtVtsuQ/kgLGQhRLPgT1dXF08//fSOzKtOaOcCqdVqTE5OYlkW2WyWbDZLb+/u/tj9xt1LkAPpk/fWMAMHXwZIKRCBBCkRsv7dU1p77oOkzGKTx5deXdwluMJBVwwy+t34VyEFb5VukPfyJLUkrvC4Yb7LgNtPjrvbUhRlRwGhIAhwHIcTJ07suR/bm262inlrAaHtNSdUVW2KtmmazM7OEolE9hT3J0nIw0m9x8ORFmTXdXn11VeJxWL09PRw5cqVtte9HwtZCMHi4iJzc3P09vby/PPPd5w51SmtQjw2NkYul2Nubu7A4+0myJtenh+VXsYOLAAqfomKXyUV1MXT8wNOxq+S0Nqru2wQZSz2NHPBR9QCB0VCUsa5lHxxS6RFwSuQ9/LkjLviq+saS5VlzgfniLB3Bbd2nigOWgmuVcir1SqpVAohxJ5pyq1CvpsF3knrq4dNOKn3eDjSghyJRLh27Rq1Wo2lpaWO1u208E+DUqnEq6++ysDAwL51Jh4UjQxC27Y5c+bMFjfM/aRObxdkIQU/Ln0HKSVdRr2+ckpLk/dXSak5ImqM05kLdOtDbe+7oij06cMMpUeY82ZQFYUT2VEMdevNq+JXUalP/HiOh6IqKIoKEixhk+HxFN5vFXJN0+jr62tLXBqZbdst8tbWV41XI1GpsT3TNPnwww/v6VrRNO2+hOuwWshHzVe/nSMtyI1JpYO4HzqhUWhocXERXdd58cUXH3ot2f2EuEEniST38iFv+htYgdkUYwBdjRBVEkS1HgYjI3Tpgwe6WKJqnB5joP57qTufJGJqDEH9e7imi6ar6FEdCUTUh3vDexgctApcEAS88cYbnDhxYouYO46zpd7EbkK+lyW+/f+tQn5YLeSjzJEW5Aaqqj4UQXZdt9kjb2RkhGeffZbJycmHKsZBEHDjxg0cx9lTiBt0Eoa3G62CXLdM6n+7VY/AE0S7dNbdNVarRWLcpFt281L2JQaiAzv3WwYs2Wss2MvEtBin4sfbnqTsi/aSMOOU/TKqVAgkVPwiPZEeko+5fkWDR2G5aZqGqqr3rLO9ne0V4FprTVQqlS3i3hBy0zR5880323atHNQiP0gh/NBCfsJ50BZyo+JboVDY0iPPsqyO/c4NK/ZeVkK1WmVychLbtrl48eK+bZlax263/Ob2/d6+bpfRg6FEcYQNsu4+mLfnKfolTugXiCpxfOHz7cK3+ULfF8jod90IQgq+v/kG89YyUTVCQMAH1QmGRY4T7D3Z1kBXdK5nn+d2bYKZYBZd0RhNn6JbbS9c8OPOQSrAvfbaazzzzDO7ulYsy2oKeatF3rq9dqzxRuurTp8UQkF+gmkUP3kQ+e+maTI9PU25XN41fvl+JgL3EuSGEDcs4lqt1pYYw8HLW1qBjadsq8ql6FzP/hSvFr9D2atQtU02WGM4eoqYTCADSVyL4/gOU+YUz2Seaa677Kwxby3Ta9wtzOQKj4+Y5jnZ3kRrXIvzdOYKQ84AESNCIpFg093cskwgBSrKkZ4Ee1S0Fg1qt38hbK3+tl3MG11StseVq6rKzMzMjvT83XzjDXfPUeXICzLcn4UspWxmuVmWxejoKBcvXtz14nuQscvbhbhdET7I/jSyEgvuJq8Uf8iKs0aFCvOlRT4X/wwJrR6q1xcZ4ljkErPeq3i+hhkkmbdrYFVIBlGiXVE0NGpBbcv4S84ahlJv/Cq8AFSFiGYQEFDyq2Rp39JVlZ3tivJumTeK46w6RaKqwZX0Kc6nR1DvLBdIwbK9iScCcpEUKb19gTlMPAnp2Z0K+cTEBLlcju7u7h29C1tDD1v/f+3atUfwTR4PHwtB7rRKWgMhBO+88w6+7zfrTNyrOPhBXBatF1q1WmViYgLP85o+4u20a43dy0Le3NxkfHwc0zRxhcvba+8TKD4xGUXzVT7yb7JaWuOn9E8SiUSwNIcf2W+TFt2oqoKp+EhgyVpnlHq2nSc9BqNbM+/iaoyA+g3RrThoUR0lUZ+Miyj3dwqWPZNvbr6Drmr0RbJ4MuC14i18BFczp6gENq/UbhNZT1BPzlZ4OnuCy5mR+9rudo5S6c1HSePpsDU9fz+CIDhyx6CVIy/IjeSQTtjc3GzWmTh//vw9Eytat3VQC7lSqTA5ObmvEDeWv19BLpVKTExMoKoqFy5cwLZtJivTJGWSnFGPKS4UCuRiOapKDSWlkpAJZmtLdevF9vAcjzgxNpQ80pEsWSusLK3QrXZTLVS5ZdxqPnLGNB3Hdih6JXRfQeoKZd+kV+kmocab+2oHHsv2JnEtQpfR3mTdVG0FiSSj17P6IopObyTL++UZzieP81ZtjkBK+qN1KzyQgndKswxEs/RFH0+43EE5yoIcUufIC3K7SCmbBX8Mw+Ds2bPcvn27rTrIDQ5ysQRBwAcffICUcl8hbt1GuyfxdpdFpVJhYmICIQRjY2Nks1mklNi2jR3YSLUu3n7NR7oSLalhqAaRVIT+eD8blRLJYoquaAp7w6Q30ctgYoh5e56BSA/XT7/ASGQEArY8Yiq+whV5hneqtzBLVdyKT1pPM2YN8WGlHlM7Za8xqWxAUkdRVUaiPfxU9iKpaGKLDxG2PrqXvBpRtV6/2as5aBEdPaITICh4FYqBRbYllE5TVAxFY87Kh4J8CAgTQ7bysRdkKSXr6+tMT08Tj8e5cOFCM6zoYcYvNyziRjr38ePH21qvEz91w0Ku1WpMTEzgui5jY2M72vIoikKXnkURd0qU+gIlACEDQDYz5E7Ej/Fq8W086TWLUEgUBqMDPB+5wlOpp/a8WEYY4aJ/ka/d/A4rokQ+prCozvGloZcYyPTyyvgMA2oOIxnDD3yWvCI/2PyI5/WTW0t+VqvNhAzXdTGTHgt6gR49hax5GIkoMq6BAtIJ6sdKlXimjW+5xHsejgg/Cv/uo+wW8qgIq71t5WMryFLKZp2JTCbDlStXSCS2Nso8yCTdvWh1TYyNjaHrekdWeCcZhJ7nsbGxQaVSYWxsbM+JQSklPUaOUfUUk+Y0htCxpI0TeLzY9QJpvX6DSulJPtvzCb6z8Aq2b2N5LknSvNT9DNTuvU/f3rjBol1gXdZwFUktsPjLlX/mJec8cSNCXI9hJOoujKRMsuFWGBk5RUy7m/yxsbGBoqnUtIBKocjZdIZa+X3KjkkEgemZ2MLnqnqc9eoSomqxIMukggLCDdDKeSqqy0giysRGsOtMfuuMPoAnAhzhE9cMNOXxPV4/qkpnj9KN0Gm1Nwgt5Cea1h+vUaB+aWmJubk5crkczz777J6zwQ9SkBvuAt/3t1ipy8vLHZfUvNfytm0zNTVFoVAgHo/zwgsv7HsSK4qCqqh8tufTnIyP8IH7ERFV5+nkVa5kL29ZdjQxQmbw57jtjpPL9XCmf5SN1XWKFPe14Cq+xWRtmbxXRTVUknoURRU4SsCPS7d5VhtBSolbMtFiBlq0LsKBDIC7grxkFXmlNImrS2TVpVfk+Jljz7NsbzApZsmmM1ztH2MwWj++8cUMr5Ruo+k6wvbRuuJciw9xNjawxfLeXnvC8zwCIZj2K0z5FVBV4rrB1WQ/o8nuHeLdqP18vynL+3GY60s8Cdt6EjjygtxAVVVmZ2dZXFykv7+fF1544Z7FZB6Ey2IvIW7drwfVJ8913aYQnz59muPHjzMzM9PWRSyEQFM0nkqepTfXw4K5wDF9aNd1o2qEnkg3fZEedOXeAiSkZNUuUfFNfAQJT4NqACroSv1xdbaWJ4hDVomgRQwqvkVvJEOyJUSt7Fn8y8YtEpEIcSOCpQrW7TIvr3/Evx1+kWEnTSqVIhm9OyGY1mJ8OvkUMqlTNWucPnaCtN5exb0PSytUN2a5HBlEQWK5DjftKgORHDlV21J7wnEc3n333eb5IqXcte3Vbq92azM/qpKYj9JXHfqQt3LkBdn3fWZmZqhUKuRyuY4K/tyPhdwQ4iAIOHPmzJ7t1B9EnzzP85ienmZjY2NLwkqtVrvn2PtFoTwIX+K8mefvV96i4FaZMtfRXJ+YkUGv+eiaoBT3saWK8CQFZwEDlRHZQ29XFz/dszVpZLK2ji8DlqwKS2aNqBng+hqLXpXP9J5nL0+krqh0R7OkRYS0HscKPBbMEkIKhuIZMsbOJyQpJe8Wl+mNJDHu+DjTcR2pa6zoHpcHR7csX6lUeO6557asv1dcbbVa3ZE40Xqs9xLuRgq0ZVkPpIDQXoQW8uPjyAvy0tISiqKQy+UYGRnpqPraQSxkIUSzR95+Qtzgfvrk+b7P7OwsKysrnDx5kpdeemnLyd3J2K3LNUT6Xuu2tngSQjBT26AUWOQiSUbiPVR8i/974YdEVJ2BWBeGovBB+RZrdpleGcfCpRpAxohzJTOM53sUnRrVQPBbg5+iO7I19M0VPpuuSd63yaKjByquFmHZqfJ+aYmnlXuHJy6YJf5h8QNcIYC6JfjpvtNc7T629bsBduCT0WMEnk9gOxiJOBFVp+rvLMC/W3GmduJqt9Na0rP11WiyYFkW4+PjW/pCwv5NaLe/7vlE84hFstObSmghP8GcPHkS3/cplUoPvCVTK+VyuVlropPY5YO4LHzfZ3p6mqWlJY4fP96spbHbsu3WstiNvdbdLthO4PHdjZssCYGiKgRS0B1JcSzaheU75BL1ScFcNMu5xAmmKssgQSeCgeBMcoCYbxBFI6VG2VBsNtzqDkE+kcix4dRIGFHUoN4XNUCS0AymawWeTu1+zBvfzxcB31j6iLhm0BOtu6s8EfAva1OMJLvpjtx1ZaiKwlA8Q8ExSUuNwPPRkZQ9mytdg811pYTIA4wS2K82c7VaRUrJxYsXt7y/VxPahpBvF/jW47KbcDdqOlcqlS1V4EIePkdekBscJIuuHQu5IcRBEDA2Nobv+211JGnQiSALIahWq7z//vuMjIzw0ksv7XuhHDRDsbFuu9b1W6VZ1twKfdEBatLnw/IyH5RXiWo6gZRoqkF/EAVNpSeaRQSSy9FBVq0SyZjLUKwbd6UEUqLGDO42dtrKYDRLl5GgJByEKzBqAU4CnsoN4Ymdv5Md+NiB33Rl5F0TR/h0R+LN72aoGiBZMItbBBnghdxx/nH5Jhuuje57lGzIxOKcTvbw6uo8N0sbSAnDyTSRXbb/oNnLt7tbE9p2uFfNiYWFheZn97LG9/KNPwxrNrSQjwAHKcG5n1iWy2UmJiaaCR1dXV33XKfTbTQQQrC0tMTs7CyapnH+/Hn6+/vvOXYn1d5g6wXficvio+oiaT2KBD4sryCBbCSOE3hoisLNyippbYB4LIYnAwxV50JqmH6RZE1dpOY7COGhSpWCVWGFGq+uz6NIjTOprb0Az6WHeL04D0IhremcyRynguBCpm61rtpVfrh6mx+uz2EHHl2KwdlYli8kLlFxbaYrm8xXy3QHKoORBKnuLHvdAHqiSb40fImP8kvSu0PjAAAgAElEQVSsBQVO9RzjTLaPH6zMMVst0R9LoioK67bJopnnk4FPVHt4l9SDnmzbqy5zuVxGCMH58+d33Ye92l1ZlrVD4Bu0NrxtfXmeR6FQ2FFc/+PKx0aQD9ojr/Wkgr2FuHWdByXIUkqWl5eZmZmht7eX69evMzU11fZF2e6+7Ob/3O397Z+3vANSUrUtjLKLmorhqZKIqpPWYyzaReadTXqVFMIP+Inup4hoOjFFp0tJ8f2NKdIlD8fzCKIap7qOMWsWuDm9yueHLvCTfacB+MflW0yUN3GDANOzqVZ93l2aZqC7m5/vz5KvmPzHhQluO2V8KTAUjSW7iiIkX5l5B2F7bKo2EVWjZnmsVctcSsVQFDiR2N3XnzZiXMkOUVaS9GR6qAU+s9USg/FU8zjkonEmhGChWuZMtr1+ggfhMIS9tQprJ+xWk7lheefz+R01mRvb2l57ubu7u+0u7Q8TKSWVSqVZo3r766C/05EX5MaBOajLwnXrEzj3EuLWdToV5O1F5KWUrK2tMTk5SS6X2xKi10liyL2s3CAImJ2dZWpqCt/3mZuba+6P67q4rovjOFsadzasmkZMN8DFzDHe3hxHldHGF0CaDkN6hrKqYvsBK3YFC8nP917kXHoQ0zS5aeeZEVVeyIxRqC2z7JdRpE5UjZCLJPBEwDdXbvNc93FKrs0P1mfIGQm6okk+rM6jIpBAbyTD/zv7Hv2ugk2ALwXZO5ETnudSClwqZZsRI8W17hE+KK+gKJKy53KztMa/G7tONtJeBTjL95slPn3HQQYCIxFHUyTVoM1u2wfkMAjyQdmtJnMjJ+Ds2bO7rtNqjTfOycPSLLZQKPCnf/qndHd3b2l22/h+/f39fP7zn+943CMvyA0OYiFrmoZpmrz11lv3FOIGnbpGWq1YKSUbGxtMTk6SyWR47rnndiStHCR1ejtCCBYWFpifn2d4eJjnn3+eSqXSdIMUCgUWFxeJx+Mkk8kdJRBrtRr5fJ5oNEoqlSJetYnZgqViAcfzcGyPHuJUbJvbfpVACnw/Qt72+ebybUYiWTJS5yMrTy6RJa5HUNCJKDpS1VmtluhNZjH0un932S7zT4vjvLe5QrenYHousUDSa8QwVZ2IqhHTo7y/NsvJ7n4UCZrrgxAkfUlBcdECSSSikdIiPJ8aoqxWcaI+6UQX5zL3dv80jmc2Ur/gfCEQfoD0fSBOIKE3mth/gPvkUaZOH4btbLfGW42Ax00QBLiuS6lUahpttm3jui7VapXTp0+HgrwfnQplqVRicnIS13V55pln2n5MOqjLIp/PMzExQSKR4OrVqzvSuFuXP6iF3EgXn56epq+vr9n7r1QqbRlf0zWWpUnFNzkfTXGhdwi9xWKyLIvFxUUymQz9/f1sbGwwsNSLzCW4sTLFm8EqmiuYsPIEqiQmI2gBuMJlQdj8x5tvcF3poRyYUNEpWC6ybBLgg64RmA5uzUJNxhBScrO0zo3iMhFNIyE0/KqN77m4ikT3VHQBiYiBqij4UqAIgeJ5qIpC4PskogaBFGgoSD8AyyGrRSkL6I911g4prhs83zfEj9cWiLoCTQjytTJ9epShRPsp8AfhSbaQH+d2Hgb9/f384R/+YfP/lUqFVCp137/Px0aQ27WQG6UpAYaHh6nVah35rDoVZNM0WVxcpFarcfnyZZLJ/ctOdhI50XpybGxsMDExQSaT4fnnn9+164KUEtN3+cvJHzC7uUotrvLP1gzH41389099lpQe3bF8Yzu6rnMqd4xBI82/SsX47vJNJm79mAQx4mikpcCOaZi+ixnVOXv8LKPzNktRSZcRJ6JHyPsuFd9hQMYol8usmwUGlRjfXLtBXFHwAoeyIyEIEIGkLByiro5meZSDgF49jiohF0lQsUooQNX3UCM6hlB5e32N3sBlLJJE0zWswOd673Bbx7KVq7lBctEE7y7M4nguLwydpFD2mwXxHxaPqpbFoxT+TifwDoO7opVqtco3vvEN/uRP/oRr167xZ3/2Z/zDP/wDruvyy7/8yx2Pd+QFudWHvF/Dz1YhbpSmLJVKlMvljrbXriCXy+VmgH93dzdXr159oOM3CIKA119/nUgksq/l3eAbyx8wZ22S1aNEdR2h6nxUXuXfz7zGfzv2k7uus30SMKFFWaqYOJ5C2fYRjke6FhDEEggp6IrEUFWVZ9ND5JU1SrgkVJW+eApVD0gQZV0P0BNJnsqdolBY4GSyi16rxtLiIo5e9y1KYCSapuZZrNkOl0WCbifC63YJYTloqkJGqlTNgBNaAlNTmC6XyLt5LuR6+VTvcXLoOI6zpZhQOxxPZkgNjOD7Pr3ZXl5Xptte96AcNQu508JCh6n8aGNfvvvd7/L3f//3/Oqv/io//vGPgbpIf/3rXw8FeT/2clk0hFhRlKYQt67zoFoyNdhek1gIwfLyctvjtxvKVqvVGB8fx3Ecnn766X1jo1sF9dXCDBkjRuA5TFoFXFsigb9ZuIGqaPzXoy9tWWc3bmwucbOcJ21EqKoBChIZCAq2TTpi8GLPKQC69Rj/Vf+zzIgq06VJLqe6ODswzH8Yv4ElAmJKnB9vLDJv1q3dk9E0qWQPjhQU1ArRQOLrGiVFIrQ4t0yHmdomXckEw+k+AMq2xaVsjkwkSuA4HNN11oqbnNBSZFzJ3Nxc0ze+V/pyI1FCCEE0Gm1Ocj5qf+ajqmVxmF0Wh02QG3Vjrl+/zptvvgnUa8rc60l3Lz42grzdZVEsFpmcnNxViPda5yDbadCoSew4DmfPnm2mVBeLxY5Tp/ez9G3bZmJiglqtxtmzZzFNc4cYSym5VV5jza4ynMjSK++GMKmKgkSy4VQxAh8tFcFTQZOCVzdmOZfu56X0cHOc7eMCvLaxSFKPMBjLsuhu4vqCQILrSz45eIqzqT48x0EIQVqP8hPZfnrzLvF4nA9KG1R9l8F0N9yZQBNIZipF4kJBdx1KrkNS0fjp/hGCRJxvV9cZSqX5ID9DKhKl5LgMRw0SmsEH1ga92W4MRUGVCrFkgt7AR03GOXni5K4lSbenL1cqlWYNiVqthuu6eJ5HuVwmCAKSySS1Wo133nln30SJSCSCrusHjrM9LJNtD4onWZAb+9HT08PU1BQvv/xy051448YNRkYO1iLsYyfI7QhxgwdhIVuWxeTkJLVajbGxsR19+Q4yCbibgHuex9TUFPl8njNnznDp0qVdT96a7/A/vf8tblfW7/SYk1xN9PNvey4ipeQne0/z/029Q8Vz0DUVR0g8RdAfzZDUDb63NsknMvVi+o39EMCyVaFaXKNPiRBIgSt9VqpljlGPlDDUAA2VnJFGUxQ8drf2JysF4roBUoJfb4g6EEvhBgFZLc54daXexUSB76/Mo6cTdGez1HwPgSSiqUhgtlTEUHUqjscr6ys8m8hyUjPQJFiBz2Bi52Re0bZ5e22VlVqF4VSaZ/oH6Uomm6nMvb29W8S0WCwSBAG5XI7XXnuNixcv7pq6XKlUmiLemvW2V7LEXiL+KIWy0xocB93Oky7Iv/ALv0A+n+eP/uiPiMfjPP3003zuc5/j937v9w407pEX5MaBM02TtbU1bNvm7NmzbaU3HzSZRAjRrElcKpU4dXqUCxcvou1Rb+J+6iE3YomXl5c5efIkTz21d9cOgK/MvMXN8io90WRTEG8UlxiRcf51Xz8/N3CRifVlVjcLCCnA8xn0ovSn0tgyIJB3xQRgoVbmT9/7Ht5mmVpphqgvuXLsBEu1CkJKYrqBhoqhOPRFk7yZX+Snena3HoQQZIwom7UKSIli2shYBF9XUaTCUtXkTLoXTVUgEDimxUSpwOWubpQgIOL4iEiAW7NxyzW0RJy4puMgma+UUfUIqVSMpG7wVHarZfzjpUX+4p03MT2XXDxObzzBm6sr/Mblp2lMZe53XHerQTFbLPHB+hq2HzDW08OF3t4tdS/2KyTUEHHf95vukkZVuO2ZbU+qJf4kR1m08mu/9mv83M/9HNPT04yOjraVRbsXR16QhRC8+eabCCFIpVJbSiTei4NYyEIIVldXWVhYIDbcw9e8Od699QP02xo/M3CR/+bMZ4hrdy/ag4bJCSFYXFxkbm6OY8eO3bOuRYPvrI6TjcS3pEin9ChvbM7zr3mRqKbz705/klKhyKRVoCfRVQ81k1DzXb507NLd7yol/+tHr1ILPHqMKNFoAiE9XltfIK4b2NLCCTziTlAvq5nooha4mL5HjLsWspCSFauKZ1c5me5mPL+KEwTEUPCFYM2yGIpluF1dp1qsIJDkjAh9qkEEnSWzwki2GwOYK9ewHJcM4AgfR0iG0lnSUlComryY6+NKoqtuhd/hw/wG/9tbr+PJgFwsjuX7zJVLaIrKDxbn+ezQ7pEYDet+NwG7sbLC92bnSEYiGKrK92bmmCxs8sVzTzVDCPcqJOQLQdGy0VWVbCzaHHtpaYkgCBgYGNhTxFuTKNop6bn91UhsOow+5MM0qdegVqvxta99jW984xuUy2X6+vr4jd/4DT796U8faLwjL8iqqnLp0iWklHz00Ucdr9uuWHqex8zMDIuLi3R1dXHumcv85hv/O1XfIaYaSCT/tPI+K3aJP7z6KwfaRoNKpcKPfvQj+vr6OqrvDHURVVBQfIFheXgJAwWlbg3fQVEU/lXfOb6y9C41EeB6Hq4bcLl7kJ8eGKNimqxYVQLXZN2uMWDEwDIBMO5cYKOJLiKuIKppJKVHSoUqd9KpjQiecycD0nP5y3d+SG1+kUDTcOMGg0YcKwioeR4Cg88Mn+H15SWWahVOIon5gk3bxNU1spkUEd1g3ayhSJWSXUORdTeK7fr0aDpVy+aZviEqQuV63zCae9cHv2HW+A83P8T0fXrjcVQgraiUhU/FdZgsbvLZoWEqjsM7U1PMVsoMJJK8ODzMzsDBOrbv8+r8IgOpVFN8k5EIS5UK86Uyo917JxctFMu8Mj2Pe+fJrC8Z56fOnCQZiTTD3vaqBrcXUso9K8G1injDneI4DpqmsbS01LaIH4Qn2UL2fR9d1/nzP/9zXn75ZX77t3+by5cv893vfpcvf/nL/M7v/A5f/OIXOx73yAsyQDwex3Gcjt0P7dyNW2sSnzhxggsXLlCpVHh57SMs3yV+px+cgkJUVXivtMCcmedEov7I3Ikg5/N5bt++jaIovPDCC7vGEt+Ln+g7zXdWJ+jT4yBBCknFt/lk9+gWiyqjx/iVrnMEA1kKtTJnBo9zvmuQ/2fqff7T7C1SNRsTyVoM+uNdqH6AVnPB0FBQGEl2YVsWVd/DUHUc4VD2HL504iK6quFRF4qvLoyzYlY5Fo2BpuJHo6xUKnzx+GVOJdL0duXwNJX/ND1JXNNRFB8FiGkqNd8lpij81oXn+buZcSbMSWK6TlzTiVsOqq4jvPrTRMmxSOgGmUiUmusRSMm/zEzzbrXKW2srVByXqmVzOh7HAGIRnU3b4mpfP0Xb5m9v3cKORkjHYry/vs735uc5G4uTNSI8feokrZ7wkm0jkOiqirjjZtAMA0PTWKlW9xTkiu3wnckZsrEo3Xc6pRRqJt+bnOXzF84eOA5ZUZSORHxycpJsNksmk2lLxLfXntiear+XiAdB0LGYHxYBb/jYNzc3+c3f/E2+9KUvAXDmzBnee+89VldXDzbuA9vDQ85BalnsRxAEzM/Ps7i4yPHjx5sug/X1dYIgYM4sEFDfnuEIpKrgGwoaKit2qSNBLpVKjI+PYxgGZ86cYXNzsyMxbn3U+9XRFxivrLNSKWK4Hp6mM5bu5SfvhKI1UFUVDYWLXUPYsW5y6RwvL0/zd/M36dOjJHRJVIFbTol5UeasVOqWqRQIJM/3HudT3cf40docU8uLpIwoPz/6DBdzA1iWxYeFdf5pfoo3fJMuwyDtq6RjcVRFIaEbvL2xwjNn+4nrOktWhYQW4VS6i2p1lcDz8bX6hXmxq5dvTE3wztoqOhooCq7vkxMSP6j7vM3AxxEBn+4boua6jBfyzJTLfJjPU1JVrDuiWTEtliyL4WwWy5NEIhE+eew4bywt4QYBA3cysVYqVWaLJSqyyMWeXv7mw5v0uA7X7hy7hGEgZf24C89DeB6aYeALQSa6tyjOFesx79GWCbVcMsFqpUrJth95wsbDtMQb9Zuhbmi0I+KHiRs3bjRDJb///e8zOjrK6Ogoi4uLSCm5cOHCgcb92AjyQcpv7kZrHYjdfLcN4T/fNcg/r74HgO6D0CSuDoEQnErcLaS+nyA3Yol93+epp54ik8lQKpUoFApt72/DT9u4kLOROP/zc7/EG2szLKwt0xVNYKxWmL49wfLcAtFoFCFEs5Ri4wSTUvL16Q9JKDqKWo/P0FWN0VQX66UCQ66BpQbYnoIeTfIX771Bv6LzmeOjPHuii3K5zFOZ+k3o5uYG/zQ3iaTu4hBSslGtoPsB0XgURWGLxdkdjRMgGIqnEAkLDwsR0fEDQUyJ8MHmJn3xBKuahq5AUvhEA4HQYpiBw/F4kp8ZHuW7t27zv9y8RTQIqPr1zLogHqMrEmXVq6EicXzBQqVENJPlNy5c4VxPL9+8dYvUHZeBZdkslsr0xuO4tRopI0I6Huf92QKr1RoDqSTpaJRzPTlu5fN0qyoKkrVqDQ2F0X1qoXhB0Mz2c6oVVN3AiMUABT8QjzTs7VFY4gsLCyiKQl9fX9si/qlPfarj/XoYfP3rX+fv/u7vGBoa4sMPP+SrX/0q2WyWxcVFfN8/UFIIfEwEeb++ce3SWpN4YGCgWQdiOw2B/XT/eb4y/yNWrBKGVAgEeELhZwYu0h+7G+GxW+iXbdtMTk5SrVYZGxvbEivbadH53cbXVZUxPUN1bYpcLs7olSuUy2W6u+vdlIvFIktLSxQKBSKRCLVarX4jqFVRpaTqBagVC9fQUZJRshiM6UlMTecds4oTWGSMKOtulf/r5rv8fFc/Kanw+vIiqXic7yzM1K1ACVlFYvs+Cgol26ZPSkzf47O9g839HU6mudTdxwfrKwwCMV2nHAi6jAgqoKkK3bEYmyh06RrSrx+fQEh6ojG+dPw0/zg5Sb5cJtA1nMDHEwJVgYplotYgYej4d46V7QYMEWN2o8hab41cLM5CtUZMCMxqFU1KfCnqPmRxV0TXanVBBvj0qZMkDIO3ZmZY3ChSUw2OpVN89cZNfubcKEOZnXUvhjJp3llaQUiJCASqJrE9n6iukY3HqDzCybZHZYk3BLwdEfd9/9C4LL785S/z+7//+/i+30wSsiyLIAio1Wrkcgcrw/qxEOT7oVGTeHp6mt7eXq5du7bvydMQ5Jhm8KfP/pd8ZfZHvDb7ERHd4PNnXuALx57Zsnzrid/arHTo1Ak+SgR8feo1hlYy/NLJS5xIdd133LJpmoyPj2PbNqOjowwPDyOlpFwuoygKmqYRi8WIx+MYhkFfXx/pdJru7m5+QpT4/socvfEICU8hGjUoxTVe7BnkGZHg1UoeXbNIRGKIQKCLemuhf5ydIONLNpbnkJpKybE5GY1haCrHDJ25QBAEAaaUzBaLnElmuJzt3VIr42dHznBrdY2JzU1ifkA6keJ4VxcxXUfI+k1mOBbHClykrqOrHsOpNJ/o7mW8VMK5U9fa9QOyqoovJY4QSKkgpKQrEJSEJKJoKKhomspypcZfv3WDnx89wcTqCobrot950nJdjyvxONLzkHd68yVaHqsNTeOTJ0ZYWytgxxyuDAygqSpl2+Fvb9zk165dJRPb6nbqTyW4ONDHh6vrSNNC8Xz0WIxrx4eYz5dYrZic6qAjyEE5rFEWhy3ConG9TExMUCqV8DyvGXZ4r16aexEK8h40ahLXajWKxeKeBXm20yqYWSPBb419ln/T/XSz0epe22r0yDt58iSXnn+W3/rh11g0y9Q1SfL12Q/4o+u/wIV4d0eZfQ2L2vM8Jicn2dzc5OzZs2SzWfL5/I79aKyzW5H6f3PqEu8WVsnXqqi+h6kGpIxu/vPTlyjOL5Ev2KRjMfRoFNXzUTSNwPMoVSocj6eI5boIVIXq2gqLtkVfLE5Ch3OpLoolC+EL1som5ZLFl4vf4j/rHSAbT1AFvrK8hJQCwwfhSpa9KqbtkChlEJkka9UavarGhWwfK+Uy/arBL11+mspmkbc21oloOlIIYkiSEqJSkpcSISSBL7D84E6rJ5VIVKVo2ShUWClXCGyba4ND3LYtLN/D0DUGkil6FAUpYd00Ses6J7YlGVUdl+lCkf5UshmDnolFWalUub2W54UTWxurKorCtZFjnMp1cWt6jlQyQU3AK7fnAdgsbPJRvsIvZ7Jk4+3Vbz4IhzUO+TCFvTX25W//9m/5q7/6K771rW8xNjbG0tISUkreeustzp071/G4oSBvo7UmcTqdJp1Oc/bs2bYzl3azYPerS7y0tEStVgNo+qP/j9tvsFArk2iJlbUDnz+88S/8+0/8cseTk3Nzc6yurnLy5EnOnTtXL66+rb3Obt9je+nO/niSP772s7w8e4up8QkGcz38wrMvons+RaA/nmK9WiQlQfN8pKJQsC10RSEQgql8gTXfIxIE6FKyYtdQfQ9dCiK+IKXopIwICMGsY/MDz+Z/+OSn+OrkBIlKEttxCICEruKrGo4vUByHtBtDDwRr5TKWbTEciXIcjcXZuXqPQwkl1wUpMIREUUAXkjQKZVFv4BRRVNQgwFdA9yVWpYYQKoqislSq4pgW/8WLLxCXAUUh+T/f/pDXVpbQdJUzJ0/xucE+DG2ruNiej6LU09ED10UGPno8gaFqlG1n199KURT6U0lkf45qIHljfJHBbApVVVAdEzcQfP/WHF945qmOzoFOCC3ke9MQ5D/4gz/g29/+Nr/+67/OX//1XxOJRPjd3/1dUqnOyro2+FgIcusPud9dtlAoMD4+vqUm8euvv96RALYTzSGlZHV1lampKXp7e0kmk4yOjjY///7qDJpSb4ukCpAqRFWNdbtGwbPbspAbtY9LpRLpdHrPxJHWCZztFvJuxyoTifKzw2Pcqgak02mykSg1ry7ul7r7eKdUoGBb9AGu7+OKgJxusGFaoEBMBRQVRUoiaPiKpGDajKgqEbW+XV1RiWsab6+s8j9+/xVe21hHURRU3+cU9WgOFYVABmSTSdak4L977hMsT0xwYvgY65UqP/rwA97bKJKQktHBfjZcF3Sdouth+wGKFEhFJ6ZqxCQkFQUXCRIc20E3FGTgI4SgK5JAk4J/ujXB544P8ffjs/QlE5wc7McNBAXLYVHZ+Ztn41F0RcUNAmJCIO7cBB3f53jX3XmEQs2iULVIRAwGu1JNn/R8oUQsoqOqjacV6E7EWKvUqNouqVj7ERCd8CirvT2p/fMa10XjqdlxHG7fvs0nP/lJPvjggx2t39rlYyHIDRpW33aRKRaLzbCyS5cubbm7HcRnuz2ao3UiLp/PMz4+TjqdbnYE2djY2LJ8dzR+J0VZI+H4OIaGo9f3OWlE7rk/hUKB27dvk8lk6O7u5sSJEweqO7tXh4btF6srBP8yN8NHtSq+obLqlPFRGEl38YWTw7xy8yMUCSigqCpSgKGACOBUKss71XJdhIQk47h4moZUNDxPkLdMeuJx1msmlushHRcnEATSxUPlveV1qlqEv/jxm6SLBU7YLlMbGyRtl3Q2Qc0yeWV1g8+PnWIjkSBtmhRL9aJAJio9Xd30qyq1YoGSlORdgSbB9gNKpSoD8QjRwAffZ3xpGQobrJse2VgE1zJRFBU1LnitVOTa1BQoKraAXCpBJpngheF+fji9QDSQaDJgvVjhRHeG0z3dCCn53q1ZbsytNI9lfybJF7dZv1JKnEoJ4TmgpNgag/LgOawuCzg8VnIjNPDZZ5/Ftm1+8Rd/kT/+4z9mcHAQKWVoIbdDQywbJ0GjJrGiKJw/f550eufMd6f1LPZyWVSrVWZmZtB1nStXruxbnu9XRq/yxvoCfmMcKbGDgM8MnSYdie0pyNVqldu3bwNw+fJlUqkU77zzzq7L79ZpejvbXRZ78Te3P2KiVCQRiyFQySgqOA5Xu/o5lu7ivWicil1GoBAJAqSi0oNGBYknfJIRncDzAIWIkAhFYvkumqKQiyeIKwobloUfCFwh0YWs+9ZVCAKJKX1M12MgovODuTkyukG3rpG3bApViw3F5Zu3Jvm182OYKxtouofUJJtCsFSzOd/XTW8my9RmGU8VBJ6Hrxn0x2PEAh8tFkeTkrF0mqjrcSKrkIzH8ddWEdr/z96bBteVpvd9v/c9210BXKwESHAH9ya72T1szmhGGo08HsuSnCijpaTYTuVLEieqfHClKp9TlcQqp5JPsSuJq/IlW8mbLMuyLcvSSLOpZ+meXtkECBIgFmK/uOvZz/vmw8G5vAAvQIDsGbWafKpQwL04y3u2//uc//M8/0fSNHMsN9t8Y36V+a0GSiu0UlwZ7ud8weCcpVlu1XGDkMnhQc7ogJnpu6y5Id+cW+NYfwnLNDAMk7XtOn9y5z63JgaZHBzg3tYSKpeVaEPdDxivVH5s3jF8eimLT5NlDs4//If/EIDf+q3f4urVq8zNzfHbv/3bz9yI9YUC5AxcgyBgdnaWOI47Aa797Hm7SLuuy507dwjDkNdee+1QF+rWyCT/5eXb/O933yLRmlDF3D52mv/2+pd7qr0FQcD9+/dpNptMTU3tCh4epeXT3uM4zHphkvDNxQVGDZOlZosmAk9APor4vz/4kOH+PrTrkZeCwVyOph8gDROUQgB+kvDzp8/z/scfE0YhQmp8oUiU5ESpjEBTVJrcznbRIDXsnSI/WFtnoq+A1pp2FFFXCZuxjyEFpilZbbv87gfTCMdhxLEJkph+bJZdj7trW4yb4CUheTvPRF8f865HYprIJGG10aLftvhrr55ifnmF97fqFHM5VByxVPe5HzVpewF/8PFDhssFLowN05ezmWu4nBkf5YsXL3H9q8cAACAASURBVGJZFkEQMDQ01NGaeO+9GfoLOQQa3w9QiYtOYr5/p0quWiTv2BS8iPdXVjBUSJTAgIKzk8Osrq52IvrPW8K81156yE+33/u93yOXy1EoFCiXy+Tzea5cucIbb7zxXJPMCwHI3d7gnTt3iOO4I4X5NDuqh5ztKwPJRqPBxMQEhUJhXzDOKI3uC/lrZ2/wiyev8O7cDOMDQ5wZOdY5hgzwkyRhfn6e1dVVzp49y+XLl5+4YfcLKPa6sXtxyE87zihJuzy3whAVJ/QZBt7OMjGalWaTgSQBlRD6IX2OQy0KCJXGMS3MxODtxTXKmJiGIDY05Xyes/0VFrfrLGzXyWlNFMXY0gSdBsMsFKYCJJhaU9CazVabXKGIGwZ4UUjRtIl2jqNkW2y5Ln2GZL7m4UYhyrTQpkM7CTg2Pkg7ShgfrGDEMRdKee4nEj9JMA3Jz186z5XREYpJzN16i42mS9x2qbohRq6IjSCME+Y36mw2XCrFPGdHKry3uMqVY7sLgRzHwXEccvkCpQTKjkXktjCcMtK0ELUWly6fYrgywBfzebYaLWYfLlLbrnLx1AlyjtNpprlfCXO38lsvNbjs7173wUsP+en2ne98h0aj0flpNps0m01arRbNZvNITSe67YUAZM/zmJ6eptFoMDU1xYkTJw490x7VQ86qjN5+++0OSDYaDXzff+o+9t6cBdPibHmIQlc34wwol5aWePjwIcePH+fzn//8vjd2r/Fv+x4GB1MWvRqkdv8v+65gWZzpr7CwXsWUEqEUidZoBUJCrNOKPlNpXKVQWnNpaITTuQJ3trbZjBIGSjaFyCb0fAbtPF+9cIl/OrfMtuvjC0FOa5o6wZEmFpr0ZV1jkdCXJDQkGAK8OEGpVHc51mmnE53EoAU506YZRmxu1iijyKPwlMC0ciilsYVkvFwiiBMKpOXP14YH2bIMfvONG4wUcmitKTsOf/uNG3x/cYU/nX9AyXE4OTLMt6oPsUyLkm1iJSGWyDOzusWlof0bX16ZGOEP3puhZD9+DLdaHmeHB3BMo3OuB8tFzowNsaJChoeGelJr3dYt69mtw+y67q7P3V1SDMPogHQQBCwuLvYEcMMwPjEv9S+zh/z3//7f/7Fs94UB5EyjtFwuH+miHtZDTpKEhYUFHj16hJSS27dvd262p3mbB4H+3rFubm7SbrdptVqHUnrr3ve96hZ/78+/zf3tKgLNFwYG+a8+/0XGdiLF+4HufmPKgn5/69p1/sfZ+8RKYaLpSzQIgdSanNYIITGEwBEGOUy+PnWJ5WqV762s05fLIYXEjxL8MKIWhPy/P/oA1y5waWCIlTAgCH3MSFM0TEwhETsqISZQ0gqBATs6GkGY0GcaCJ3KWNpAXinqbR+hNYkSKPRO+TdstwOuVUosbDf5K1em+PbiKnXPQxsGodHmC6dOMN5X2hU1Hyzk+YUrU9z/8A44Dr7WDIiEdiJItMBBY0mDDd+n1vD4J9/7iIlKH1cmBhnpOo/nxwa5dmKUj5bWIXARfsJQfx8/ffEUQbvZWa7XdTnIuhXhDttKKNOWiKKIWq2GbdtEUYTnebtAPDsPmZDQfp549+f9QPdZmpx+1u2FAOTBwUHiOKZarT6z4Px+prVmeXmZhw8fMj4+zu3bt/ne97636yZ82kP0NMDWWtNsNpmensayLAqFApcuXTrU+LNt1wOf//qP/g1uHO2I32jeX1/nv/vWn/EPfuFv7AvGhwGAs/0D3D5+grdW13CEJpEKf+c8WwjySoFS5GyHKErYbLu0MwlMDfVWE9wWlhYIoOr5NELNUM7iZLGEzOcZSTTT29vYUqL2XsMd6qJi5ygPVtCJou17FB0HlcRsBmnXk5yQWDLN5lA6IY/EkiZ520QHEQM5m1977Qr3lh4xu1ln0U34xodzfLC4zu3Tx/n8DuWUnZPjA2Wma23cyCeOFJ6OcUhLntfqTdrtiDjv4AcxHy6u8/HiGv/pwCAjfSlIGlLyV6+d55XjozxcfkRlYIBzE6MIrQnazSfO/Y+T2zUMo1OlaZomx44dO3B5rfUucf0MtA/qkCKl3AXanuexsrLSmTyy703T3Pc4Py0e8o/LXghAzi7iJ9kjL6vku3//PkNDQwd6q08DuINAPwxD5ufnEUJw8eJF+vv7+e53v3vo8Wfb/tP5Obw4pmilL/wCyJsm8/Uq/+xb32QgjHAcp3MMYRji+z6Li4upvoPvUy6XO7zj3gnk1sRxGnHMUq1OnwmB56FTRzltCaSh1Q6QUvJP3r/LRDGH1pBoRb3tMYxAAokASxqp4FC7TcH1qfshbWlxzCkwYgsajRZJIjCJsSAVFJImfY4DWtMOQpJIUWv5JEmCMkxKuRw5lWAJAyeKMBGEOwUrs2vbnLTTApAzhSI/erjKw2qTTRwcFbFYa3JncZ23l6v8yqtnyIpiTw0PUI01f/xwC4UmZ5sUURSEZqUd0Zd3ODnUT842yTsW28023767wC/f2q0ENlIuIEcq9PX1dUqze9mnqVKtm6c+rGUVoxmAb2xsoLXucOEZiGedUYBdXvjQ0NAzZy/8ZbEXApAz+6S6SGcFJMVisZNL/EmPK45jHjx4wMOHDzl79ixnz559pocxA8/VdquTRufEcZq9EYYkAgYmJricT6PFxWIRz/PY2NhgenqaUqmE67oEQdB5aHzfZ2lpCdM02d7eRmvN1tYWbxSKXLAdPClxLItvLC7SCtIKNRVrEiEQQqO1Yq3ZwrIM6mFErBRaaFSiKZgmwrZZ82OqDQ9XCJSUNFVCFCcYeYFjGtiOjQx8tDCwYwPHNrDRbLdc1ls+A2gq+Rxt36ceawZsh6DdAqkxkGidEOkYIUzKjkXZMfj3H90n/vghjUYTLSX1MKBPKgr5PBLFg41tvjVt8hs73qMhBCXTIgkSLC0JY03RNskbmthNONZXIm8ZKY9tmJRyNvOb209co+5gavfnvf//NAHys1h3QBPSLiYnTpzYd3mtdYdKCcPwhaA3XihAfl4POctbzrqQHJT83f3wHMVD7pb3nJyc5MaNG9i2/cwPYgbIr4yMYhk77Z+CkFgpcqaJKeDG8eOE1e3O8qZpksvlkFJSqVQ6qT2FQhpcjOMYwzBwHIfz588TRREffvghUkrKOw9OkiT8yunT/MnDRZbaPgYCa2csW22XYSeVz3x9bJBvrm+BgpJhUDRNItMkZ2jiSKGlIooUWptEScJi0KZiSppBhE2EjyZOJLGviA2o+RECgbkj9mOgWar7LG7UGTPSgg9LJ9gifUO4PDTMqGXQ2Kqy3nRxtaQgEsJEpVV8AlpBQL9jYRmS2bUt4kRhS8nCZp0fLaxjSUnZsSkJCUlIf7nEYKIYKORBKVQUYEhJECcMDRQOulwH2rPKYv5ltexezO7Hn5QK3V+kvQTkp5iUkna7zXvvvUcYhly4cOGpr00ZwGYz+kEBsmz5JElYW1vj/v37jIyMdOQ9Nzc3nymPeO9Ybk+c4FS+yN3tKoMatCmJlOLnz11krFhiabt26P3sfSgyMfMsmOM4TnpMStG8v4AlzTRNTUpsNG0pCBONtARvHhtjpG+At2dmMUk9oobrkSQCoTRxohAKhIzRhoVAE8Zx2mEaScG0mOobZKPRpNr2iDCQppNWOyYxXhCnnVF2NCUKwqQkJXEUMpgvslRrUw9dzChEIzFlSp3IRCGIcSwBKkYkkqJjQZJy34lSTK9sMVwssOp5aB2Td0wIYuIkYXygjNbpWE3AixLaQcgvTR2+Pfze++Yvu4f8vPYiHPsLAcjdHHIQ9BZ16WVBEPDo0SNarRbXrl1jeHj46SvxWM/isIAcRREfffQR/f39nwgF0m1CCJrNJnNzc/zdi1f5IIn49r0ZbNPg5yZP8TNnz/dcJ7NuMHia7aVdlFKEsSJnSJI41XNApoG7SCum+vvJ5XJ85fRpzDBgZnWVhuuzHcV4kYmNxkDjADbQThIw0vXjJAEjbUFlqphjBQvL9SkbJrYpaLVd3CRNbYuUQaITtFIgE0q2RS0IeLRVp4FDWUbEKuWzpWVimwYGMe04IVYCBeQcE6EEF8eHMQ2JF8VEcUK5aHFyULK+4eIHElNrGl7I3/zSFQq5PN94+wNavk+hZPPV6+eZGh968sTtOe/7neufBCA/z+T/47aXgPwZs8NyyHEcMzc3x8bGBkM7eZ+HBeNsP0mSPDXg4bouMzMzNBoNzp49y+Tkk97TfhkYh3k4XddlZWUFIQQ3btygWCxyHfhrE2kedhRFT9Aqvfa/33e9tC66PxtSMlQs0FYxIomJlUIhiLWg5Nh8cfJYZ/lTlX6SIOR7tQUMJcn2qnd+hIaCjkErQq1RaEIBCTHrLZfJoX7MJOTmudN858EKiUp2QHZnAwqETLnejaaLRJOoVB85NjSm0EgBVhJhylRfWQhBojQFx6aSyzFeKfFTUycRQpC3LHK2SRAnDBYcnL4ckV3Ed9tcOzHCrfOTWJbFqK2oN1oMDw1iGM9PN/wkAPkn1ZXkpT1pLxQgP42yUEqxsLDA0tISJ0+e5Pbt22xvb7OxsXGk/ewF/r2eTxiG3L9/n1qtxoULF8jn8/t6xb0AeT8ltsziOOb+/ftUq1UqlTR6v18+6tOq8Xp5yN16ydnx9loX4MtnT/IH732IY1qgFZGGAdPi11+9Qv8eof+7q5spvbDzgwAbjUnaLdsAtOqS1klAC40WmoWtJq+ULG4cH2N2vcFmq9ZZTqg02wOt00IVrdEi/V4qjSXTjeZsC0MItEpIlKZkWdwc7WO0r0DBsRmvGMzNzrD2aKf1kA0fVetIyyGnEpIoomybXDw2gO/7nXNgmRIh9gfT/a7BTzLt7Se5D3g2LeQXgT9/CcikF/vRo0fMz89z7Ngxbt++3dE/flbeuZcnHscxS0tLPHr0iNOnT3Pp0iWEEFSr1SN5DPtV9mUVfAsLC5w6dYoLFy6wuLh46KKTXt7uUR7OXiXXxwf6+KtTZ5h+tEYzSRgsFDg5OobJbslPAC+KUiBWmn6RpO2ZdgC5g66ZatzOnyrWJKZCA1Njowgh6Ms5bGtBTgrMJCFAkQCmSBufGjseswRsobGAWIPrxVhS4EiNYZiMlcpMHR+nr5hncavNou9wbnSI6xdOp5oZXkCTBh8u18ipkJMnKlwbLVGv1fnX33wbtKYgAkypOx1YBgYGdvHt2VuU7/vEcdyzG81PkkN+WTb9F2svBCDvl4estWZjY4PZ2VmGhoZ6tmf6pFLlNjY2mJmZ2dWh+jD76JbuPGj5ra0tZmZmGBoa2tXvbz850L2eb/eDfphCFniSM95v3f58jqvHhtloB7y9uMad1TpCQF8hz1+9fKqz3mAhz5IfAAYO+gkBIUNrTAGCVO3NEqnIUFla5PI5yk4KbpeODfFwbi71StHkpcbTAgOBSaozbQpAaqwdkaMdnMcxTSQJ5ZxNueDwR+/eJ29ZYFhsemsYScDnrlX5xVsX+fO7S/jaZqLSR9hSbNUC3vMiHqxssxWkBQ4nBwy+ePUENy+nXH2xWNyVi9tqtXBdl3q9zvr6OpBWzbmu2xGtkVLi+34nd3dvIcUnCdKfVg8ZXnLInznrBrLt7W1mZmaemkv8LN2qu/dTrVa5c+cOUkpee+21njoERwX9bkBtt9tMT08jpeTGjRud1LRey/baTvb7IGoEDg40dT9YGa+8l9ZoBiE/fPgIIQ1s00AI2Gi6/P6dBf6bM6fxw4iSbSMRsCPKnxepZysRWBoKQmIL8Rg901EitGCiv0zDC/n+zBKlUp7BYo61tpci9s6PcDQCiUSDABNNAY1It4IUAscykFrQDiPyiaLtpX30ao2QtjLJyYQ/eGuaO/PrVEgYKOcItMCwTZYbPo9W2hQckyRWuH7AYhjx712PkxOjnBof6pkqGQQBtVqNSqWCbduEYUi1Wu2U+bdaLarVKq1WC8/zaDQauyrhgjCh0QpxHJORwdITgL3XIz8ICD/NHvJLQP4MmRBpQ8JM+OcwucRwuA4gey1LlXvw4AFCCK5du4bv+/sG+Z7mIe8FQyklQRDw4MED6vU6Fy9e3Lep4n5Ae9QJ4DDfdeeJdgf8hBCsVBtpRoSZZi0AOKZkveVxf73Kv31/liSKcEwDGaf6mo5tUHBs3DBGKDBE+gBLkQbrdqYKBooOSah459EqnrBA2PSjKVoWXhxgSLCEwDQMchhYBsRRgq00ISB06jXnpEKrBEPqTsUfaGqtENMwyZsmthBYCcytbtM/tuNbq4QkTnD9GK0VfpiQaAPbMpAiouWF/KvvTvNbv3JwC/u9+eoZiBqGgdaaWq3G6dOnd61z594qb313hiTRKBUwVJF89Qvj2FYatA2CgFartQvAu6/LXrDWWhNFEY1GY9f+P2l7Fg75RbAXBpBd12V6eppms8nrr7/OwMDAodY7KoccBAHVapWtrS2uXr1KpVLp1PjvZ4fRy8hMKYXnebz33nucPXu2w0M/y7afRy9g7zIHrSOEIEzijldr6iT9W0iE0Hz77kP8KKZopiJBpTy0/QQVKxqRj0BQEDlMQ6MTjdwBK5OIwVIZY6DCn91ZZNyKaSWaxFAU8wm+HzOQz1EQJmauSD5uEUUSEau0g0m3aUBrgjBGS4VtmcgUp5ECbFOjdVp0IoQkZxu4XkBfnwYVopRG70wRQsUUdjSdFekG1rdbNN2AXvPmYYN6e21jq8UffvMulf4CtpWC5tZ2m2+/s8yv/cKrB64LuwWFMsDOypiXl5ef0KIADvS8uwH8aWN/6SH3thcCkLXWzM7OMjExQRAEhwZjOFqq3Pz8POvr6xSLRY4dO9bxWg9TGBJFUc//dd+EGxsb3Lt3D601169fP1Rd/9OyNDJ9Zdd1O39ndhSvpJui6MVDDpdLLNRc6OxXECuNKSXL1SZ5aQAKqUkbnRITeT6lnE3etsmTI458pkYqOFKilCYOffL5PH84k2Y9CJnSG5FK8PwYpXd0o+OEVrVOYsTEwqKSt9nu5KM/jhJmHrdWmiiMMRQMlnJst6KUd0ZBorDMPJVCDh0FeFGC1KnUqFYaoTRKagyhMUSCUhqFSSln4fm9r3FmUayYW9qg1XYp50EYbba2fUxDU8w/ufz03DqGlB0wBhgcKPBorU6t4THQ12OlLusWFMqs2WwSRRGXL19+Yvm9WhTZ341G4wktCnhcadcLxMMw7GzvIDGhbnsJyJ8RE0Jw/fp1kiThwYMHR1r3KGpvx48f5/bt28zPz++rnvYs+3Bdl7fffhvTNHnttdeYnZ099M35tG1vb2/z8ccfdyaEhYUFkiSh3W4TBEGHn84E9rsfqOztYW9H7l6APFouMtJXYL3lAQoFKAy+MnWcj9ZbhEELG5AkaQeNMMESkrxl79BNEqEM1uttrkwMI4Rge9un4fpIIdK0NjSOUGghQaf+qhfEeJFGCwOFwg0jbKUgBgwoiJRCiYREapVqN2tNHMHWZovhooUhBb4fo6VB0TE4NThAkiS8fvY4c9sh9bqHKeCVM2Pcub8MOkYpjSnZmSTAMk0qffuXTW/V2vw/v/8RTS8ClVCv10A6jA32g44ZKBtMndwNsGEYdxqgRkEbaVgYZhqUjpOj0Wzd1+4gbe1uLYrDbKtbezkD7Ha7TbPZxHVdPvzww13Sppku817v2zAMxsbGnumY/jLZCwHIkILis7Qz2m8drTWbm5vMzs4yODi4S+3teds+ZRaGIbOzs2xvb/PGG290PPuDAnV7bb9lfd/n4cOHaK25efMm9XodwzCoVCoopdjY2OCDDz7g5MmTBEGwi4NvNBpsbW0RhiGu6yKlZHV1FcMwOupc+Xy+c2ye56FUwpunJ9hwQ1ZqTXI5m3PHRum3DQb6B/n3399E6dQLa7o+SawpOimwGlojtUIakjBMdh2T0hrHMgjiGEsolN5Jp0NTzNkEbgAiDSJq0mIVP4iRaAQClMKQAhKJY2hUGJMIhdCSOFbU2wGFvENff5FAaWwDhCH51Z++RlR7xOdeGWFtY5NWo0FkVdjaqNFyXQQJliExDIM4gcunR7DM3kCnteaPv3uPMDYYHSpTqzfx/Rg/EZyasCgVctSqNd694/KVLz9e7+zJYd79aHnnXChA0/ZCSkWbSv/B3vF+9knqRWQcda9Uvs3NzU5BVGaZmFAG3NnvTJP5JSC/tJ7WaDSYnp7GcRxeffXVDvhk9rTCkL22d/msQGV5eZmxsTEmJiZ20SxHAfy9AbwkSXj48CFra2ucPXuWwcFBCoUCjUaj57qZJKfjOPT1PW5dn3GLU1NTWJbFhx9+SKaRm40xCAKCIMB1XdrtdgrqwImcQMqEuFmjbpoM9/VxZrDE/UdVbB0TxQYSkzCIcZH0F9JXcj9MGMvldp3HUt7CaQsKtiBOXBKdECmJYRpcHh/l44UVRCxQQpOzDJqxRHYqRUBKdgpOsvQ3jdihIGzDSAN2SmFKwdd/9jpt1+fm9asYUvCjHz1Kg2+GRErBQDlP3jYYHRik1Q7wwhCkidaS0Ev4R7/zFk6uwO1XT/PG9UmMHU90c7vNdsPFcUq4Xkh1u41pSgwt2Ky1KeX7KJdz3H+4heuFFPIpwJ2cqHDt4jgf3ltFJi5aRphWjl/+2iudbR/V/iKzLLrFhPZaJmj1WbeXgHwE8zyPe/fuEQTBgSJDUspdr2GHBeTuvOixsTFu377dAbNeyx/GMg8/02+enZ1lYGCA69evY9t2zzEdVsuiO8Ut208ul0tLi/P5Dp+YeUndkfws/cr3fQqlfsqOgyUEtmFQlBZuDCoB1w0xtWQbsA0YdEza7XbnHBdsGxXHNN2IiqPTlLlEc/HUEAPFHKYU5AoOtimQSQiuQhgCxzAwlCLWaZpdd5BPAIbQ2DIBDVGY4AYxfYUcOVNimU/mswshOHlsgHLeoe35lPM2pYJFo53gtiPuPVijVCzQaof87r97n5WNBv/hV18BYHZ+g8XlGrFyMaVCihDLsgGN1D5K5XYmO0UcP96vlIKvfukiV6aOcffePH19Ja5MTVIqHo5S6GWf1jzkvWmUn1V7CciHMK0109PTbG1tMTU1xfDw8IE3h2EYu4J0TwNkIQS+7/PDH/6QXC63Ky+6V6DsqJRFGIadbb/xxhv4vn9g1kf3ugdJhu7NPnnamLq3lwbhJH8+u8nHqw/IKxehFJal8YOIWEssmVIScax5ZWqcN8+Os7ow12noqYFq0yfyBEM5E1tKkJKSkCysVul30tS6ZhABBhaKJE1Bpi9nkUQRjSBJC0ZMiZQKEafOs6EVYkd7AyEYHyodmIsNYFsmX7l1nnc+XuDR6jYYBiOVIhuRS6W/mFInhk3OsfjB+wt8+c3zRFHCN797D8c20JHEsQVRCI2mh5Ur0l/OsbXRYmlpi7ar+T/+z2/zU58/x+3Pnemcx+PH+rHkOKVSieJzgDF8uvOQXwR7YQD5WWZXpRSLi4u0221OnjzJ1NTUoW6ioxSTBEHA/Pw89XqdmzdvPuF17weGh/GQoyji4cOHVKtVbt682aE9MsW7bjqjG+T3esiHjYDvN/Hst7335tb4YLFKIedgIklUmmlgip2upToFSdMQ5IXFSH+JjZ288M2Gz3bdw4sFbuAw4OQxkYQRhIGmrWLm1z3GK2UKfkK15SGUZnSgSOR5BFGEjUaS0hP9lomIA6KdoSuRBgSllAz05Xn1/NhTJyCtNcW8za2rk0QXxpFSMLtQo1rdyejQMVqb+H7C6nKd/+F/+bcIIUiSkMmxAe4ttwnClHvWJGmXkc0Wq6tNSkWLkxM5igWHP/7GXXKOxWs3JneN45PwID+tHjK8zLL4TFoGQgfdDFpr1tbWePDgAaOjoxSLxefuVL3Xq1VK8fDhQx49esTExASmaR6Yxtb9oBwl8yPrjbY31e8wHvZBlXrZeXzWhH2tNe8/XEv1h6XAwkBlLM9OTrDQCiHSlk4zSxv83KunAVittlitNinInSKRRLG+1aCvLyJJJGEMytCs1VzqTZdzkyO8cfEE1WqVs2fPMruwyv2FFeI4oN+yicIYZTtErQDLFGn6GumcYAjB5y8OE7TqzLXqxHFMrVZLx7G62uHJ4zhmcWmVOzPLbNfa9JUczp0ZpVxyHp8jHRH4MDO9RRglnD81zOp6g+3tJqWi4NrpAdqej9YJYT/8B3/tDf74G+9hHzcYHiyyVU27rPT3F/jz7z2gXHT49rfusbHZYGjI4EtfusrU1LML4MNP1kPuxRW/6PbCnZH9hHkyy0qqS6USr7/+Oo7jdHp/PW+qWca5ZkL0WVPUrBy2l/XyOg+iLGq1Gnfv3mVgYIA333wT3/dptVo9t7lXv2K/SeQw2ha9xrR3zHsfwiBMkMJAoDBlgmGbxFECaITW5E2BtCzUjucphEADG7V2Ko9pJBgYCC1SFbidVDdBSjskcYIwDWYXqpw9PpwGGqOEdstHxpqiaTE81MfiWp21pocjsopOQTlnMWCV8MKYvv4Kp8YrWJZFFEVMTU0RhiFxHDM0NMT6+jptN+B3//AOUehiSs2j1ZiZB6tcvTBMEvksrfj0FQw2thSuFzI0WEDomP6STb0uWd9oUekv0ldyCIMIyxRcnhrjW98yKOZyCDSCCK0THNtgYanKP/nHP6BYdBjoz9OoN/hn//Rt/uO/mWdycvDA63WQ/aQAOUmSIwfpXnrIn0HbL3e23W4zMzODUuqJkupsncPeqPt5yK1Wi+npaQqFAm+88UYnn/OTSJPzfZ+ZmRnCMOTatWud8R+lCnDveA8qsT5KIv9+lMWJwT6mV5s4TioCJA2BSkAagrxjYxmKMEmr5W5fSl/Pkzj1yqWZbsM0wLYk0U7ebZrOpjGlIN6pr9ZAywtJkoQ/+s5dvLaHaSaYQcL61qMUGCIJhkIgGShZGAbEZPKZBpvVFu+8/4i1zTr54hxf+anzGIZBoVDAcRwerfskSlAZKCNIB2x16wAAIABJREFUQGn8MGarLvi1X7rFjz5e5/78ClEUMDpUZmKsSKICTBOKBYN222NpeQ0pBVLAzWujzMxMU8grlle26S9baJ3gBz6tVkzgRYweK1IqOWitKBRtlFZ897uz/Pqv33rqtdnPPs2UxYtgLwwgZzfZ3lLoTJu4Xq8zNTXF0NCTHR2ydQ7bYXev/oXv+8zOzhLHMa+++uqu9DE4XHlzN3B250Zn1MfKygrnz59nZGTkCc93P073KHTDflkWez/3AvH99v/5KyeY25zGDyMKMvWKc5bJ8ECZ9YaP2vF4pyYqXD45suNhSyzbSD1pIwXynGXihVFauKAFeUtiyiQVpxegNDiWZG3Vo9kOKTlmqhgXJ8RKg1D0l0pEfpM4Sqv0ZN7Ej0LytkXBtvhXf/QBiRYUciYtN+Qf//6PuH29yPj4OAAbVZdCvgQ6ZkcYlJxjsr7VolRw+OtfvkKzOckHd6u8/f5qqk+tPJBpSmGr1eK1VybJ5QxOHR+gMlCiWCyisan+8TTNlkccJ6yu1ZBCoiOfZmubVksDCdJQKGVzb8Znbm7kieIK27YPVRH3k6ISXnLIve2FAeTMMnDN8nFXVlY4c+bMgZoQz+LBZvuYn59nbW2NoaEhRkdHnwDjp21/P2GfrHjj3r17jI2N8eabb/Z8BTyI3tgbyNuPJz7oQYgTxdxKlaYbkLPkrnX3O5aMuhks5fm122d41NasP1qgnLcZKToM9JdRwqDZbjPY14dKdnc2maiUmV/bJklS/Qgt0oIPw5CpyI7ekeeUBlrD8EABx7ZouQGGyM6RJkoSOiNWmnzOIowTQj9BmoJi3uFn3jjPRzMrKKUpFJ1UzjNnYUrNzP113nzjapruZ5u0I4Vla9IywLTbiGPvBsGb10/ywd1NarU2paIm9DWuG/KzX5zi6sVxlFKd1/l8Ps/E+BC/8atv8v4H88zcW+L69au8cfMM//L33qVea1MomiSJh1aaRlMxMVmhVCp1ina6iyziOO5MmlkBz17QbrfbnZTFw5Y0P4u99JB72wsHyEII1tbWWFtbY2Ji4glt4l72LPKYruvy1ltvdcqpq9Xqc22/Gywz8Ze+vr6n9uDbjz7pNeZenw/KnZ5drvL3fvef40eaIdPl+HCZv/HFq+Ss3efzoP0VbIOfmzrFvaLq6AAD5G0ToRwsUxKq3esPlPOcNyVrG1vESF6dHGfq5Dg/+P5bQAJhmqMrhGS4L8fFU+lbj2UaJDp1m8VOZZvYEbEwjTS7o79sEUc+F0+OcOliSktsVV3MnWMSJIDCsg0iXxEEKcidPTXA23ca5CyNkaY24/kRr109uWsyGejP85/97Z/iG9+a5v7cEn19Bb72s5c4fqx3RxeAUtHhlasT9JUivvCFC1iWxU//9BS/8zs/IElinJzC9yPQFl/5uWuMjBys1ZIV8OytiGu1WrRaLdrtNltbW2lqYReAd+eS9/p9GFGhzF4Ccm97oQB5a2uLjY0NKpVKTzH6/ewoim+1Wo2PP/6YIAj4whe+0NnHQZ7qYQE5a82UedxXr1596nielrOc6Q2srq52jtG27U659H7rrm23+KMfzuAFForUE320Wed3v3WH3/jKKz330/07G1v3773L7j2ObivlHaJyHsdx+MKti+RyOeorIyAlJ45PsrS0RLGQJwh8zJ2S5eFKiaWtVlqsYqR983wdkzcMdiQhiCLFYF+hUw0HMDxUpFZvY9kmggSBIghjHNPAcdJHaGy4xM9+/hh//vYdpI5RCC6cHePShWNPHNPocJmv/9KrbG1N0tfXR5IktFqtfSfFbP3uz2fOjPCbv/km3/rmx6xvbDEyUuZLX3qFiYmnC2cJITpiP3tNa01fX9+uHpLdmhTdIJ4JEfUSFdoPtLO/jxKT6XU+Pqv2wgDy1tYWi4uLjI2NMTo6emgwhsMBZndQ7eLFi9y/f3/XPg5LHez3v5WVFZaWlpicnGRqaqrjST7P2LPqvXv37lEul1FKdcTPq9UqzWaTe/fudV5du9sPffOdeySxQrKjTZzWT7BabVJrepTL5QPzkQ9rvQpjDlrWMk0sU+LYZkd4JzPHMfnS587y9ocPiMMAKQU5x0JKgR/GWDLBNB2Ojw3s2ua1SxM8eLiJ2w4p5jRuGOEHEddvjGIYks3NFg8eVFEqz3Ahj2XZjI0NcPr06K4S5ufR9O11/CdPDvEfff11qtUqQgiGhg6vYniU/QjxWJNiv96M3aaU6njg3QDeLay/vb3dKaeXUu5Sg9vP+34R7IUB5OHhYfr7+7l///6RO4Ac5CEnScLc3Bzr6+udKr4kSZ5bAD6zZrPJRx99xOjoaMerX19fP5KWRS9gbLfb3L17F8dxuHXrFtvb2wRBwMjICJBOYPfu3eP48eP09/cTxzHlcrnzkLlBGrzSaHIiQuzwwlooZucfEnrNjnJYFEW4rtsJGJmm2RFd7zW2etPnnTurNFttioUCU6cqnO4Cir2g0b2Np1XTTYz2UXrjHKtra6gkIZ/Psd3w8EKBJSNOnhjH99q7ttNfzvHXv3KFdz5cZmNzi4Fynp/52nWIN/ngg0W+8515lNJUN7dwcgmFgmB5qc7CfI2f++rVfd8EusfWCwh7nZte2/gkMyM+CSpBSrmvqFBm7777LleuXMG27Y4M514KpZsDHxgY2LcJw2fJXhhAzuyT6pGXea1zc3OdPnnZjbwfb3uU/YZhyMzMDM1mkzNnznD8+PFD0R97be+ycRxz7949NjY2uHDhQkdTYm/ALeMSM6pEKdUJNOVyOa6cHWe9WkfEAssAQwJaYEqDG5em6O8vdyQ8m80mkFYI+r7fKSjJZBWzsnQhBLWGy73FJlEisQxNa7PJdr1FZXicMyeePb+226QUmIYkIZ0wBvsLFAoFWq0Wjm3ie6CUZn29ST5vc+yYQ2WgwFd/+iK1Wo1r164B8KMfrfPd7zzAtiX1WgBSYJkGWiUIYH2jyezsBjdvPg7k7uXm9wPrXuB8EOjuB9ZHtb+I0umnyXpqrY/8zP5ltRcOkD+JLtLb29tMT0/T39+/b2PUXt7NYUA0K9deWlri3LlzXLhw4YmA4FHV3mD3BHLs2DFGRkZwHAfP8wCwLIs4TkuFM5763LlzFIvFDueXvTZqrXltaoJ3p+fYCNNOzkpoTEPyM6+eIXues/SpTFIxS72SUmKaJo7j0Gw2OX36dEeTeWZ+E6U1cocCESJVYvuDP3mPr30+rbbLJoeMs9za2qJUKuG6AS23xdpmQt6JGB3p7aE97TpsbDR49KiO72+iFAwO9vHVr16hVHocPNVa02wGKK0wSLNqLNMGkYCEIIrJ53LMPdjk5s1zz0RX7K3s3M87fh4qpNf2Pq15yC855M+Qdech79edYz/LQNzzPKanp0mSZFfxxWHtaQ9O1jl6eHi4k/3Ra6xH1XVOkoQf/vCHnYKUKIqo1Wq7dCzQDapbD5l7oDl56ixDQ0NEUdTh+DKPNrNCPsfXf+Y6S02Dtz+ep8+MuH7uGKfGhzpSiVLKjvednf8MWOI47hxbFuAxDAMviDCFQSIEhkgLPwwpqLcTpqamOl42gB/4HZ743v017j3YQCeChtumVIhZXKxy4nixI6bveV6Hmsl6y+0t/65W2ywt1TENgWObKAWbGw3+9E/v8ou/+LgtktYaxzFIm5JoDAOkVEipMU2NtZOC16h7/F//6NugBRevjfGVr1bgaLfNLnual/y89jSgbNVcqhtNygMFKiNPNuw9rB0V+F8EMIYXCJAzy0TWj2orKyssLCx0eOKj2kE3lOd5uK7LwsLCE52j9yudPmxbqfv37+P7Pq+88gr9/f0dbxXogKXbuMvqw99HK5M3X72CyI2wuVV/KuhbhuTnb1/kZ65PsrKy0nmYMw8486izVkHZj1Kq49VOTU110qWESEEwiFINCykUIFFaUy46nTxaAJcGMSGIGKsk+Pa/WKaUFwhLUsjZ2Lam5Smi2GS4VOp41NnvLCsgayXkeR5BELCxkTYqVVoSxTFogWUZPFquUa02gMdAks/bTJ4cZGHhEbZt4LkKZew0KLVNtrY8HBlRKhRBC955a471ZZ+/83d/fte1PExWyX7f7cc/P6vt54krpfj2v3qPd/5sBiFTvY9zr5zga79xC9s5XMHUXntRQPYo9sIB8lFe9zORnvn5efr7+7l58+Yz82u9HrzugKBt27z22ms918vGcthj6NbLOHnyJIVCgXK5TBzHHY9XCEGSJCwuLjKQf5vRsZMIOYAhGyjdPFRGQy99jf2+y75vNBq0221GRkYYHR3teN0ZUE9ODPHxvU0SpcF47El96XPnsCwrHTdJShVIEyFgeWMjbWdU3BmTeJxit7nZYmK80gkmlkqpjGZWKJHL5VBKUSqVaLVa1GoNhAiQQmAaCYkySGKN1oqVlTXgcYHF2toa589XaDVtqttJul+tsSyJ74VYpHnHWhl47ZAwiPjw3UXe/+FDrrx6/MDz233Nu0H3xw1iWSB2r9195yE//JO7DE8MII30jWn2vUUGhop86Zee3lD1ee1FAe8XDpAPyyFXq1VmZmaoVCqcP3+eMAyfO9jR/YBlgJkVjrz11luH3s5BfHSr1eLu3bsd7WPTNFleXuatt97qJPdLKanX67TbbcrlMmMTlynaCximDwgQOcDrOfbMnnYuuoNWQqQt6avVKsVikYmJiX3L0If6C1y9cIyZ+Soq8TFNk0tnR7hx+XhnW4ZhIBOBMFLpzIJTIBuelGDKZGcMCmkJisUiSZI8EbjspiuUUiilGBkpU683QYA0DBAGcSQolQpcvHiGZrPJ9evXiaKIDz/8kPHxcUwTPC8gny9RqzWo1+uEnmZupo7retQ3qwRBWjDSasA/+J/+Db/5n7/O0Gi+Q9vEcXxgaf5+XnCvvO7nsf0oi/e+M0uxP480ZGdflbE+3vvOLD/1C9d/rIHAnxSv/WmwFwaQuznkgwDZdV2mp6cBeOWVVygWi6yvr3eCX8+7/2azyd27d8nn87sEhjIaoldbG3i6hxzHMQ8ePKBarXLp0qUOPaGU4o033ugsk7WfCoKAiYkJPM9jcaWALTfRSZWWP0EYv9+hdRzHoVAodPaZpTNlAbXuh6WXd5yVeNdqNUZHR8nn8z09Pa0VMTEazcRYP6dODFOr1RkY6O9cr0hF1KIaYRiRNwuEtLCExeTwcUaGN1FxEykFiVIQJwghOXPqGKZpdjy/zFPuplWygKWUkvHxfjY2tmjUU0nNOFZoLL70pfOd48mKJLqPPZ93GB8fpli0KRQM4kiyPO+SJIDQ5PIGOhGYlsbJWXzjX8/y9f/kGq7rdrrCZFRKxtcXi8WOF+95HnEcs7W1RS6X6+Tn7r1Pntf2A78oiDBMA40iIURiIQ2ZdjD55GKK+9pLQP6M2n6AnPGt1WqVCxcu7BIZepZUOdh9c8dxzNzcHEIILl++/IT28X6yoL1uxO6gXlbcMTs7y+TkJLdu3eqkqmX0BKSez9LSUqeXHkAul8P3fUZHR5Hyxq59bGxs0Gw2O8ft+z7tdpvt7W3CMGRtbY16vY7rup0u1VLKTgsnpRTNZrMDICMjI532TXuPKVQ+a+ESURyhI3Cc49jC3il/frzsnDtPoEMUmpZ2saWDbdgY0uBXf/l1/vm/+DcEYUyiJKYlmTo1QqW/gNKKatiiGfmE6nFrrb1efFoibHDmzCjNZoDnaQrFAsfOj5Ir2sidJq5Z6yshBKurq/i+v+t+0VpTGSxRqRSZv7+5kyqiSXYmtMHBEu2mj2UWmJw8vquDi9Zpo88sDaxaraK1JggClFLU63U2Nzc7+bqe5+F5HrZtU6lUdoH1s4oL9fJ2L752iu/+6w+w833oHUqottHg/LXjHa/5pT2/vVCAnAFUN7hqrVlaWmJhYYFTp05x4cKFJ27a50mVk1KytLTE7OwsQ0NDXLt2recN/7RAXa+gXlbcYds2r7/+eic9LVsmO46MfhkdHeXWrVvEcbwrla4X/WEYBo7jdH5HUcTo6Gjn/4uLi6ysrHD58mU8z2N5eRnP8zAMA9d1WVtbIwiCjnfXarU6wbss/7hUKuF5HnVjEz/ysbVDW7XxYpc8hSfG5mkfy7DQpiLQIZrHk5IfNBkZdTCMMgPlIaSMKRbT5rPLXpVNr46KQz5uLnNaPNm9ezdPC5VKgdOn+1lWLnfDTQhgPF/itCwhpeQHKwv8YH6G8YnjvDo5id7xsrPO26Zp8OWvXeVf/uO32Vitg4D+QZuc1Y9OJKBxHLMDwBmlkv2d8eUZkJZK6X5Pnz696/7JJknTNDtl2L0KK/aKC+1X0hxF0a4u45m9+sUpHnz0iJXFDaStUKGkf6D8TPzxs6TpvfSQP6PWDa5ZmtnQ0BBvvvnmvrKDz1pMUq1WmZ2dZXBwkJs3bx5Ie+yXytaLDsgKN95//30uXbrEwMBAh57oBuIgCLh37x5RFHHjxo0numMfZId9ALTWJMQ01DqJVFhRgWq1yvnz53Ecp+Mp12q1DhBnlnmBMjBIdEyEIA4jGmGdoBnh+z6u6z4GEGnhRi5aCRxlgUrfPGZnZ9ko+fiOQoiQiYpN4j4+X43Yo2AXiEOBn0RE8snJtZfnnmjNpt9maHgYoWHVbTCZz/PD2Wn+5MFdTpT62LZgsVXnRH53LpsQAtsx+dmvXeXf/ct3yeVtDEuQBILatseVG5OU+4o4jtMR8dFaE2vN/NY20vW56uSQUuJ5Ho8ePWJycrID4Jll2SKdicAwaW+H2Lk8Y5Nju65lBuSZNsXe0uYMwO/fv9/JPoH0mbFtm+t/5TjHFopsbdQYOzbCheunMHPiyMpwL3OQ97cXEpDDMOSdd95BSvlEmtl+6xzFQ85e7+fn57l+/TrFYhHXdfE8b1/v4LCgv76+zszMDAC3bqVC5N2iLpnXt7S01Cku2auRvNeex2PRWjPb/gEr3jLNWpu+XIXzp1+jUql0umV3L9uIWviEDNh9VAoVKpUKFSo06k1CXPK6xEBuKBULqtcplUpEUcTg4CB9cR8to0kYhyRRghu4aYFG7LHibWOFEQjNg+oig1FaUWgYBnnLYlu5oCMqxgBxotkM2gilGbbtjgTnE4FLoGQ51IkATVGYPFp+xMC504weG6HYDsGyCcKYvZYd87HjFW5+/hzvfn8OkWiCFpy7NMGv/K3bhLHX2W82IXxvYZlH23UM22ap7XPVkdRrNc6dO0d/f/8uZT+lFJZldbjwhel1/vn/9qe06y5aw6lLx/j63/ky5UqqP9F9DwshOhNi9yS+tbXVqUTMQLPb664MDlCtVsnlcjRadTarGz2lPXtRJtnnbirtMPYyqPcZtSiKmJ2dpdVqcenSpUPXxh8WLJVSzM/Ps7q6Si6X49q1ax2vtJene5R9uK7LzMwMlmXx2muv8e677+L7/hOlz41Gg7t371KpVLh169a+GslHtb0eei2q0oi3caMWq/VFIg8G+0fBjp542LJ1m3Gb5WgNUxpsJNuUykUqVJBCMuSMIoRgvb1BqCJyPO66bZomxWIRIQR9xT58w2ezuoUwJKV8gUvnLtD0HxDWq0RRRDFfxBZmR5e6DxOhHdwgxt4MeNtdQbs+AkEr9Bi1SyilCIIA13V3FeNc6RvD63PY3t5G1n0Gh4d5/eIVNu5/xGrtEU6pwGSx1Blr93labrZY81yGTxT51cs/xcbqNqdOn+Ti5TP4vk9Y83ZdC601q40mZWyEsrg7N8/kyQmMwTEWGy75PYVI2XWXUuI2Av6///kPsWyLwdF+tNYsTq/xT//Xb/Bf/Pdf30XNAJ17rTstcW1tDXgM3N0A3p1HDjA4ONgB12ws2fa6leEyIM+EhcIw7Jzn73//+7t0L3pRKFlW0ItiLxQgZ73mCoXCkYRKDgPIWWDt2LFj3L59m/fff/+52zJB+lAsLS3RbDa5ceMGlUqlI/Rz586dTlQ+exC01gwNDWFZFmtra7tu9v1u7qN6yPfaH/FB64e0my5LM3MM5cvoURffazJkjvdcRwiBF/uY0qCYL9GIWrjxbgpnI6gx566BKRnWAf3sTgPTWtNut1lpVGnKEJVEBKHGMkxGagPMbqyQK1qM54fYCmo0iTAMycnBCqOmxaq5wZwI2PYSKnmHEiYJCsdxME0T3/c7lYBBEHQq/HK5HHnDQNg2zWaT5YUFrptFRgoDnBg8TqNaRfEY4IQQ1FyPd6tVCrbNo0YDyzIZHSszMta7ka0Qgo1HNVZ//x5rCw2CVsLI2QHu/vUyTbOFTkLWmh6/OTHRc/2Zdx8SR4q+wccT2cBImaX7G6wtVDl2ancnnO6JOkkSZmZmiKKIz33uc5im2ROwgV2TVff9utf7zu63bu87++15HnNzc1y7do0kSXaBdxiG+L6/SxkuDEM+97nP9Tzuz5q9UIB8/fp1lFIsLCwcab2DKIsssGZZ1i6x+L1tnJ7FQ846ghQKBW7cuNFRXQO4cuVKxyNbXV1lbm6O06dPU6lUOoGZMAxpt9u7bvYsdSsLuEkpabVa5PP5zkPkOM6BID3fvofr+myHbfJlyWThPMvbd1Ex2FIxKnqvWzQL1JImNZo0ojYzzRVK/RVOFFOFuSXv/2/vzMPjust7/znLrJpV+2pbtixZ3tcsBCckIQmFQEhCoIGyQyhLgUB5blrSlsIFWkp7obS9wIUAbQw0NASCk5BAyEY2x4njRdZmydp3afbl7PePyZmMZMmWHcd2rPk8jx8t1ozOnDn6nt/vXb7vDC5RRpKczGhxSqyX7STT6TTDw8M5E3uHQVYzkIGokuGH//cRUjM6pTUaAjDSn4E6gaxoEXa5SYgWTcEy+hMxdL8Lv9NFIpFElKDCk/Pq8Hg86LpOOBzGsqx8GCCbzdLS0kJJSQmTk5PE4/F8E4mkmyQiESYnJ1EUBVmWX6p6yDI5ozI2lMTlckOdi+dVnZZQiPLy8nxzSiGqovGL//gDaiJDwOfAEQhCUuPAPQe58COvxzI0hiOJl3w+jnW6SyezCPYqVdbBFBBMCUGATEpZ8L1MpVK0tbVRU1Mza7L6QqtSu17avonB7NX23K/nCjrkksy2C6D9u9xudz50OFfALcs6Kbvc1zJLSpBPlfkE2S6Ti0QitLS0HLPitrfLc1mMIKfTaTo6OpAkiS1bthCLxfKNC4UrjsKhqTt27Fj0zD9N0xgfH0eSJBKJBG63G8Mwcg0NL20p4/E42Ww2v6WUJIlIJIKmaUykZxiRR3D43CQNixdibSx31SAIAnElTlbMlXDZNwz7o1dys9xZx4tqHxFNZdIco380zttqLqCjb4SjBycRDAtHiYPy1V5EX+5x8XgcTdNYtmwZhmmiTkyjCCaiJGBMmsRmMoimDC/5MmcmFZw+GbHSgSlJjGUSzGQVstkUCYfJ6kCYWFan2ukj7Ho5f5DUdfrGRyGVwidIlAcCLFu2jEAgkBcFu4QvYhiMGCaNgQB1L1W3eL1epqemefrhA0wMp9BTOvF4GukIGJvL2FeZRRdlmqem8jkFXXLSNh4h3hdheipKIOhGtJxgiIhuF+m4QtehUYLL/SwrDcwSYxtBEGhYXc2+3/W+3KkoCLnZgJJIzYr5W/3Hxsbo6+tj7dq1844Wm4/CUkGbueK9kHexaZocOXKEdDrN2rVrj7FgnVvxMvd3LgWKgrwI5pZHjYyM0NfXx7Jly+Ytk4NjV7yLaUUunAjS0tJCaWlpPgNvPyfktoe9vb35m8HcmuYTUei2JggCpaWls1Ygqqny/PA+lKTKCl8jYU+ISCSSvzFsKNvBSHQGWRRxGD4m0zOMCCNIhoSRNpjQJzAyRn66t6qqxLNpDMnC7XFjWSKiy5mbYSca/O7JNqb2jGEY4HRAMq2hRGKU7/CSzWRxOp2sWpVrnR5IRTBNAc00MQzwpMEUco0lL800xTLBmNDJVsm4MDEMixKvkxKPjxlTJapmqXEHCMovv+bRZJKu6SmiokVAM0i73KwIhfLnXDdNemZmSKZSOCcm+NWhDpzpFO2pDBeGAtT5c/Hd0YEZYpEULpeMLDgRLRMNlcyBBFXXlSMHQ/mKm2g0yl37e4mqJtFYGsUA2eHAtHI3X12zcABhNUuV4CKsJXjuuedmhaBso6RwtZeVG+ro3j+EOyxiZHOlaW//6GW4vbNXl4UhCrubc7HMJ8iLQVVVDh48SGlpKZs2bVrU4+3dnJ0kXAosKUE+1Uyt/bhYLEZHRweBQIALLrjguCvShQR5obt9Npulvb2dhoYGLrzwQuDY6gnIxap7enqor69nx44dryj7vNBjn448S0eyGzEDo/o4WxIbGR8eZ9OmTVRWVmJaJkP9kwzJI8ilLq4w1mMKChk1QzgTxspAOBDKj/iJZBO0x4cwsDATApIL4s4MipUlkHXT8/A4fi/oWk6QAUw95+B20QUtuF/6Y/zjxFG649O4ESh3B4krcSzTAgMM0UQQcxOmLcAywGU6ceHAEiBp6rhEgWW+MJdV1DEzPkFaURiORUmqKgnLBEPHkp1oooAhgF6Q3X92eIgXR4aRDZPnDh7EY4mU+3xYCEQyGWp9uUqG4f4pcpZIuffM45AwTJFs2iAVy9JY/rKnc1ZVOTo0SmXAS7B1JZ2H9yFKMg5JwJJETD23Unz/zW/C5RdRVZXS0tL8LsYOQ2UyGbLZLNvesoJQg5OjHUM4HA5Wb6nHUabS1taWF3B7QVFRUcHKlSvPyCSOWCzG4cOHj2m4Oh52W7vL5ZqVPDzfWVKCXMjJlNIoikImk6Grq4u1a9fi95/YdnCxgpzJZOjo6CCZTNLY2Ehtbe2cJgUhX4va19eHLMts3bp1QTPvxXCi1z2aHae0JISOwdDkELGSOGvXrs1PExEFkUtKtzEk1lBZVYWceulmkYrwm6E9KEqWMspQsxolkhOn00R2OQk43aQFjebyBnaUuEm5DHxZN7uyT2J5wDQcYhQsAAAgAElEQVRyXhSoYAB61mR0ZhIPEiOZOC9oUdwIJEyNjGrhEUVwGegaSA5yIYuXBFkPikRTaZxIyJKMV5AIOh2srWnAQ06EptIpEtksKU0naui4BIEIIJo6sgpTydwE5hqgLxYn6PbgEGDaMBmajNCjaoTCATZWlpJRNfqjEwwmkgiahmiBy+nEMkT8phNBVLlwZQNNFTlBnp6e5khXFxe3LKdzOoUmajRubiB2ZArRIWCqAoZmsf3KZirrw8RiMYD8kAC7esfhcOD1enG73VRVVbFl62bGxsbw+Xx4vd5Z+YPJyUkmJycpLS1FURTa2tryzn/2c81NAhfmFWxBX8w1BC+bc42MjLB58+ZF18Hbfzder3fJjG6yWZKCbMeET7RVsxOAw8PDyLLM9u3bFy3iJ6rMKCyRa25uzsdv0+l0vkPO/rmhoSFmZmbYtGkTpaWnZ2pGIXNvEo2eFTw99ixqKkuNv5q1K1rRlNm+zLIoU+4spdJVxkwq1/X3zEwvmqnjFpw8M9NLoxwmioCZUokpSQzSlLpKCDi8rPLXEg6HmUknEWURJWtiGiDJuVWuqYPlhGkHtAbCBGoq6ZjQkLImWtLAxKJO9CLVWIz3ptB0C10DZFBkSJXmuuFmNJUqUcBlCrgReaKnj1g6jTuTwQGkNY2YbqABTkDTTcrdJYiGxfNDo/QkUnRmdRqDQV5IxBGBpGmwLBjAZZqMpVWe7hlEsGAgmiboE3DFQFF0ZEkmmlLBMKheVsGK+tx4r87OTqLRKGvWrKGmpobRWApVUfC8bh1HDg7R/sJRZNHF5tetpm512bzvUSGaZiCI+jE/ZyfLHA4Hw8PDaJrGxRdfvOBw07nVDqqq5q/LwtW4qqoMDg4uKNx2bXR3dzeCILBt27ZFCau9ELGPeymVu9ksSUFeTBnb1NRUvt34oosu4tlnnz2pbdPxqiymp6fp7OykqqoqH54QBIHh4WE6OzvRNG3WoEjLyk0CjsVied+CwlXL6bxwo9EoVrfOReU7CFQH8CsliLxcY3q8cyAAOCVMt4gVB8njZjSeIJqIEtAtVMnEgUql8+UdRtDlofnCGvr2D+eWxfbzyOCpcqOYOoejE1y/sok6b4i9qXFk0yLo8pBSdFpKy7nyry/n3+/7I6ISR5FNYkEZnDJoBkgipiDiRqJ9apLBl4yHyg0DF6BZFjoCiijiNi2cIyrRSALZMhE9LlxrAwxEY2yvrya8opG0olChQCSTJeBxc7j9CA1eBzOxNClVBadEqNyLNZgmlVLQFQtn2IW0uZxsNsvBgwdpbGykvr6eRCJnc9pQFiSbzRKNRlm5rpYVrdUEAoF8G/rca6iQ3v4pfvvofnRLYueF67j84tWz/n+hKopj3ruCUrXjkUgkSKfTlJeXzwqb2BU9kUgkPwjAjv3u3bv3hCtv2wDKruBYKiGKuSwpQV6M41uh29uWLVtOqt24kLlVFoIgoCgKBw8exOFwsHnz5rwXr2VZBINBQqFcmZeiKHR1daHrOps2bcrXZHq9XhRFmVUNYYs3kP8DsC/yuRe9Ld7zhU/spplMJsPGDRvz290Zdfb4qLnYIm2aJheVN3FfMkpSy9JYUk5/OsFMNo3Tgrgk4pIdZIzZtasDAwNctL6CcpeD/c8NIggGXp8Da5UHd1jGcjpQszl/YnQBlyAhuRxETR37nXF5nIRWhwjFJKZSKSSXhNvtwe/QuXrFKjyixFAyhRyLYVomSTWL18xN9fDKudViTHQgjiTwHU4hlIogCZiTGY7+pgfhDbUMeJyUiCALAmuCIR6cSDAVjxN2OohlNKZUFUkQSWrg9cusvaKJybE4laWVOP0Oxmdi9PcNUO6qJjGsEvTrKBmVfY8eRhIlVmysnVWRkjs/JoYxu6RsLo88043TKeNzunh8Tw9b1tXlr7dTqaI4EfZxSJKE1+s9psvVtiPYunVr/no2TfOYlbc9a9H+3PYDX0rx4vlYUoJsM58g25ULk5OTtLS0zJt8OJke/EJBtsMTR44cobW1lYaGBkzTzBvKFHY5FbY822Y+tgXj8RIitsNb4QVvbzkLVzL2tjCbzeatMEdGRkgmk1RVVbFq1apZO4iTKTkKO0q4vnY7JhaiIPLToQPIxBnJTIBlETd0LnTnSrCSyST9/f1UVFSwZs0ajnAAd1k53niKbY2rmDRU+sZGMHVo8oURBIFINosliMxYBh7Dwi97EAUBjySxs34Zz0UOUOJ0sLa0jIRmgprh/vYeQg4nzVXlSIJAMqNjmAKGJaHrFn5ZwucrQUPEPTZFWhRAE7EEQLQwVAuxM8nAcpG3rF+JZRrU1NSwefVqkpkMv9/fyWNt3aQMnRKnG1k3KXNIVDpM9JCDvkwSK6FRnTJ48nedpCeex8gKiA6QPQJGMic+skfknbddw8oNDQAMj8W457f7UVWVKy/dzMaWsnmFSpZEFFPGEj0IZJBeeu+6u7sRRTFvOnU6me84LMuir6+PmZmZY3IcdgiisO3bxr7OPB7PkosXz8eSF2S7ZdSuXCicHj33MScryLYpe2dnJxUVFaxbt45AIDBv9UQsFqOzs3PBlucTCaNtwGP76B4PO9lil9l5PB7q6+vz8WpVVUkrWR5M9zGSiuJ3utnoKGf91DLKSwK4XK68d69tC9mfjPL7oW5cusUbahoJu71cXtXEtzuewiE7EC0Lt8PJmkBlvkU33LiM+0cHyY72MRWdIeR2osyY7Bkb4c2rWwlrFp6SEkRNJ6VpTCbS6JaFqpu4TYHxVApVM5js6KI/GqVG9rCqIoAzXMpDR/tJpDIoholbFHi6ZwCXoSMZMiCQxSKIiaLqrPIHuKy6jt1PDpIVLQzLREDAMl8yTxrPMhZJMBpNUhfOJctCTidBVaPr9y+wpqqcgZkkEdVi87IaKkyFg4MzCEBrbYDlpdU88M1HcIUkRFnCEAyiUwmcPgm3nLMrzWYtfvaN3Vz84QsJl5Xw4uEIim7hdUnc//AhBGMlgRIPoVAYqcDu8o2vb+aBR9tJphSuvXIdAjrt7e0sW7aMpqam077anO861HWdtrY23G43W7ZsWdTfSDFePD9LUpDtFaBtFm83Vhwvfnayjm+GYTAyMkIkEmHjxo14PB5GRkaOae6wQwV2sfx8g1NfjS3c9PQ0MzMz1NfXs2zZsmNCM89O9zHR3UtYDNCWmWBKybIvkeEToQuQdJ1YLEYikcj580Yj/CzaB5aFqJuMzEzxtsqVeL1etvor6TKmKCvxEUskGBwdY31NPQSDfL99P25ZJqtkSWfSTBgmZZpKKqrxx4F+1vv8KKpO1/gYZDKYJjhlD5qSIqNaKKbBeDLNH9u72VxbzUQ6id/poDxgYCGgihKKCRFFRVc1/E4XGKALIoZlYAAZU+PA4BhR04FqmJhG7qYrO0FJgZq0yHhlygGHY7Y/cyqrMj6RYNrUCYZ8hIIybkNkX9cwqmkgITGYiFG+zA0IOF1OLKeFGssgCgICAqIl4SlxY4gG8UyaPX/sx10bBHIdi2lMRgYj3HX3FKIAy5cdYufFdTidTnp7Yjz77FGcLgfXXbeNkFdj//79NDQ0UFtbe9qvG8Mw6T08jKpohEOlOJwyyWSSQ4cOsWLFCqqrqxf1PIX1xbZ/dpEcS0qQC9/43t5edF3PT9c4EYt1fLMrM/r7+wkGg2zatCkfnrCPwY4Tjo6O0t/fz4oVK1izZs1pd2Sbj2QySXt7O5BrJU8p8zvQGZYJksCwQ0HXBNyyh6xoEnULtJQ1cMTIMKgYXLxyGcFsNe79k4QCAfRkmmQqze7pEabGsqwPlVMne+iNRlBSOh2Kyf4jnRiizLBDx+3ysNLtRjVhOJ4kABiCwMHpKeplB38cHcNlgWrBlKaiKQqGIZAVQEHAAWQMg96sQjij0qtPU1FdTTKtkUnrKBiEvG4MTKYVg6QpIDpdYBgoho7DFNBNjb39o1SVezAmExiGhZoR0LMWhgn6miCTE0nu2P08q2rDvO/aMhqqS7n3qXbcokRKURgZj3PjzvU89lwXmmmSVAVkEUxMZiJJTMPIib1bQC4RIAUIIJeImA6T6ckUgsMkmdAIuV0EggEyachkVbwuD8sbQoDF5LTKhg2bSKey/Oxnv6WkxI2qGtz138/xtusa8Xq9DA8PMz4+PstTeb7cgv29xVpn3nvHE7zw1GEE0aJzzzBXv28rfX19JzWB3RbjpVZfvFiWlCBblsXAwABjY2PU1NScUAQLWcwKORKJ0NHRQXl5Oa2trUxOTqJp2qx6YtvLuKOjA5/Px/bt208Y4zsdF609UHVmZobW1lYSqRS7Bl6gbWqIQCDIX266iir3y9UPW8MNPDXVy3MzA+Bw4CgpQbdMyl1eHhw6wq6uF3BrJo8kJ7it+QKaA2Uc0hM4rVzZW0TXCHpLeDE+w1WOAKrDwYQzTUaJk9INTLdM2Otn2FAoF+CC8momxscxBJOsIOA0dJ7rHyJhGKRFyKYlLAFCDhdRU0ExLaaQKRFMDEFkMJYg/NKq8/4DXZiWgEcQMQ0LSRMxVIMMIk7ZTYnDhd8wEVQF0xJIaxYJS6Ek4CRWWoJbz4JlIXgdXPzhC+hIZEhEZrBMnaOjEX7427186QNXMxFNURoMsKyqjGgsjkPXyKQzaIZIxhRwmAI+t8yK1nqeved5rKSCkTFxu5yYppVranEIpLNqTqwliMlu/AmVC7ZU8ubLN6MbJv/nO78nlsi1o4eCXlwuJ5qWG/LqcDhIJCI4nG4uueQSDMNgamqKYDCIx+OZN6GWyWRmlbMVGgYtJN4Oh4PnH20nVO1DEODAs12sfl052y9cfIy6MF58Mt2BS4kldVYSiQSZTIbly5fnE1qL5XgrZEVR8uVqthF8MpkknU6zd+/e/ArUHtMjiiLV1bnSpkQiMav0Z75jmmvreLLYE0Nqamry3X0vjvdzIDpCucPLlJLil4MH+PjqS/KPcUsOPtdyJVE1zWMTPfSnIlxcvpwmfwX39HbicjoJehyMGyqj6SQ3r9rElAO6Bwd5vLcbTYSonosxV66opSoW4WAsgluUMUWVJBZhh5tWb4B1JSGmJyYJOdxoWRVDkKjz+5BiaRwOGUXXiRoG68KlRNMZPE5IGSopC2QTMAX8Bnhfeo9Sqo4guZnWLATDZCKbwilYIMlohsD6qkraD3fhNQUEEdKakCvsEyFd58UMBih1yQRdXq68bC0d971AQpdxiAIuUSYSz7nUXb1tNT9+6Hky8Qx+0aAm5GBLSwPPt/ch4SLgsLhyRzNxQ8fVWA5TUdSshpLVwSGBLBKbSSOJIkbGJLBhJUKohK3r6nn9tpVIkogkiXzofZfw4O/bALjmjesQRYFAwMO27bU88ocO/H4fN9988azrpNAkaKGE2lzseYGFieHCaginT2CwexzLMnGXOJAcAp2dnQuWstnWsMV48eJZUoIcCARoaWmhv7//lCaAzH2MveIeGhqiqamJioqKfLWDx+Nh69at+Z+bmJhg//79VFVVUVdXl7cZnG+lMtcj1jb/LrzgF5OR1jSNrq4uVFWdf2KIAHrAja7Of6MRBYFSVwnXN2yc9f0t5TW8MD1KWldwyzL1viCSIPBobx9/aD9MOpkg5QTT68avWvzLs3socblxyzK6aBLwB8A02VxVQ5nDwxNdPQSzGSZTGVbLDkwkal0lRCSVbFrFNEHEoiczQ6nHzfqyKvrUSaJKBksUKHN4cLtc6Foc04TN9bW0R1JkMxoWMrKpYQkChiTikURCL62AVUPE1F7q7MNCNQR0CyIJBSWVJRwQcUoSr2ttYHcsjaaaeFxO3nRBrtZ3y+pafE6Lg4c7WbO8mZqaapyuUVLRJMMpieYaL2+5pJUnn+vAs6oaMejFHIsiu7yU1FXg9sjM9I2yef0yUh4vUcXg4h0r2bQmjCy//P5WVvh5780X5b+2vSiamrxceeVNuN0u3O5XXkkhimLetH4+gn9Vxt0/+B3hYJg/effrCVWUHNPGbbsL2iWZdvuz7YRYDFEcnyUlyIupQ16IuXXFdnjCHv8kCMK88+zs1miHw8G6devw+XwnjFnb20z7Qo9GoyQSCcbGxvLfs3+XPV5n7hYzmUwyOjpKY2MjNTU1x/whrA5UsDlUz3PZMSpcfm6cI7rH48ralYRdHkbScTaX1hAwIJXJ8OjAUWYyWdyChKxDPGkSEARAIKFplIseKnxeDCzev3Ydb9ywgX958pmcoY5hYJLB4fDgsUS6JyKELANVN5AEEcUS0CwLI5ahb2YYt2AhSqBbDtIalLsstlZXMpPIUBcMcvW2jfzzg3vonUqS1mT8goGAyG1vvxxDN3ihc4S0piIKIIgCWJBFxDQFRMtAlCwmJpN87UcP8WeXN/GpK1YQz2hIgkVjSKSvr49oNEo2m+WyCzahaRovHBxk9+9eRBYNakJV3HD5BtwuGV9aJfrrvZiWiSQLiC43qVAQ3e2ieuMy3vq+11Nd9fK8QrsKZT7S6TSHDh1asNHjVM1/TsTQ0BCjEyN87Is3zbqxO53OBePHdry40Bu5yPFZUoJsY49xOtnH2ELZ2dmJoihs3JhroJhvnp1dezw5Ocnq1aspLS1lcnJyUaGHudtMt9tNIBCgqqrqmJ81DGPWCiWZTNLX15cztvF48gNcgbzDm9PpJJPJcLW3gRtq1+Fze3EJL09SPhGCILCtvJZt5MzSY7EYiVgMp6qRkSTSkoQsiIimSUaWyVgCumWRnYkTEQRCHjePdPdx5fr1XN20kn0jo6iCgNflRDUtRuNJfLqKblmYSFgiZEwAAckAzcq1bhuWiWSZ6IbOJavW8Menn8chmHROpVElN//07mu45Xv3o6ppZEwyGYOnDvQR9rgQTRBMmFElvF4JydRRshZCRsT0SCimgCnJuF1uKupWsampmt8/doieo8M45RRe5zQej4dwOJyvpnng90dRVRXRCb0D4+zdd5hKfwk/+9ovEUwTb0nO6EiJZ5D/2MYHf/xJqipduF3HVvfM9z6Mj49z9OjR09rocSIMw6CjowPLshbdAg0vx4vt1u0ii2PJCvKprJDHx8fp6urKN23Y4Ym5M8Kmp6fp7u6murqaHTt25P/vlbjNFRoOzX0tXq8Xj8fDwMAAExMTrF279hjPi8LGEUVRGB8fR9d1UrEEkcnpWVtMmD+5Y39emJm3wyKKovD1q97EDw4eYO/ICKUeL1urq3liYIC0nsDQcmVghgBRRWcwGier66yvquQfr7mSIwOD1AZDPNveyT37u8laEh4MVAtUU8QlS5iChCYKmKqBigi6SVnAzU2XXshPf78Pj2WiWwLpjEH3yDTXOZ0sKw/RHlVQZAlLsDh0dJwVZQFKg34yZhpD1cnqUCoJlPpKSKbTGIaJboAoCYRdThqqgjy5p5d7HjiIJKg8u2+EWz92JZs3NAKgqjpPP32YQImfmckpNFnE6XGxvKGWQ79rw9ANRFnMJfKwQIJUNMXRvftIrA7hdrsJBoP5c2vHbIF8G/GRI0dQFOW4jR6mafLoPXvpPHSUjdtbuPRt217RqjSTyXDw4METtl3Pvc7s69Tj8RTjxSfJkhTkk60pjsViDA0N4ff7ueCCC2aFLwpXxXbLs2EY88ZsdcvAOHYe5glJagoj6TilZjlO6di3LJFI0N7eTmlpKTt27Fhwjl5h44hdB2q3txZSaDRjr77ntrra044VRUGSJFwuF9pMhI82ruJTa9bmRfyjmzYznc7yhXsfYtrKMKOqeDWLGlMgmVXxOBzU+P2I5WV0jM6wv2cUS7PIWAKSIJE0RRwieC0H4RI/hmDhxGRlwM2OlpXUh0ooC5fy/fQz5N4SE1MwaG3IOdN96i0X87n/u5u0qhMq8bKsMkSp20nXkQSW5KCptozkZAJDMxmaVLAsiWCJG8E0cLhc3PqunVSEfNzTM46qqpR4ZZwukWgi90aapsW3v/U7BgdHmZlOY1omskOi3FFCeWmQ5x87ipLRsSyBcK0XURBQdRHLCcvrV9C4vh7LsvB4PLMSaTMzM0SjUTKZDIlEIu/xcOjQoQXb4/c92sXunzyJOyBz5PkRQuVBNl2y+pj3dzHYLdCtra3zXiPzUawvfuUsKUE+2Riyqqp0dXWRyWSora3NV2YYhnGMJ8Tg4CAjIyP5Kc9zeXSig5+0PYwlCNy85lKuqV6/qGPuiE7wd3seQFQ0wmNtfPOCa/P+C3a7dzQaXbCpZD4OTU7w/af+iCiJfOqSS2kKz15NF9auzvecqqrS0dGBIAisXr2aRCJBMpnE5/PlHesikUheYAzDYEvAw5OZDKom4DIgFk1z667dfPWtOwn5SpiMxLnjsRfwoeEWZURTxIGOU4OqgB9BdlAf9PPGxgANVTkv32xWYXxyikgsDYaFZAqYmoUkwqNPdXOwY5JPv/tyfvKFm/jNMx2IgsCamjK+u+tJQi4XiYxF0JRBdKCKFklVz4VaRCcyGluaa6mrDBKNRvE50wiiA0WTcDllVjfm3uNoNM3Ro1P4/S40LYVlCSxrKCUe1+juHCXryHUG6pqBomi5eXWGiWlYrLmgCRUFl8uVD0FYloUkSfh8PlKpFEePHmX79u0Eg8FjSthsW1i7Pf75pw6RSWURnS5SSYW9T72II6wtWMo2X1WPZVn09/czNTV1UjavxXjx6WFJCbLNiQTZ9pQYGBhg5cqVVFVV5aeEzMzM5DPRTqcTTdMYGhqirKxswekLhmXy/b7H8IkOBODH/X/kDRUtuKQTx9Z+enQ/imUQdjjpT0Z5bmqIy6ob82GRurq6k7IFVQ2Dv3niERxZBQO4/YlH+Nlbb1j0dtSOYxZ6baiqimma896IbC4CYukMn951P4am4hAsYqpOz+gENSUuuvuGUJQsmmoQT+mIgkVN2IXpFlAtkUxaoUFJ0tK4gdLSUmbiaf73j35HPBYlEAzhkxxkMxIOQcDUTGaSGbK6wP+7Zw+3f/hKPnjNNgCefOEoFhYelw9dV8GysCyRoMuPw9R4y5XrGJuaITETZfzIDP/5n4+waVMZ1791J9u3JRgei9K8spK6mtyq0edz4fU6SSQULCRMyyISVWloCOH3e3CGAuiWFyMdwTQtlIyKqVq867brCFYEmJiYmHWeOvcN8Phv9+DwSmy+tHFWiOJEJWw+qYy+F+/CUi2CISeXX3sx5XWB/C6n8Eapqmq+hV8UxfzuKRaL4XK5qKurI51Oo+t6vqpnoWukGC8+fSw5QbbjvQsJsj0VJBgMzgpPVFZW5qc12Bd3f38/iqLg9/uJx+Ps3bsXeLl8KB9vdcgYuk7GJSMJJxdTCzs9KKJA0iGBbuJG5NChQ+i6nneMOxmyuk5G13G43YhYRLNZTMtCOoEgK4qSn/O3mGaW+Qh6PWxZXstjnX2AgM/jYsf6VroHp9g3lMQlu4gmkuiIuASYjCkITi8uF6yuCfKOC5qJRCKMj49z/95+BsamCLmgf3SaiqCHtAlZS0ASIJ0VcLtFYsn0rNj7+uYawgEv8aSCIIp84MYLee7FATp6xtm5fRU3XL2JPXs6+a//6kbXDHq6Z1i+rB6Px0PzKg/NqypnvSanU+Zzn7ua3bv3I8siFZUBPG4nF1y4nFQqzlXXbuTuiEJ2zI9coiI4BN7wwUt4y8femH8O+9hGjk7xr//rLiyniqkIhH3lbNm6+PO8cl0dX/j39zLcM8Hylmoq6xfnnW2aJtFolPb29vwQ1rklmYXiXbjK9vv9VFZWFuPFp4klJ8hwrFcx5Gp2u7u7SSaT+e1/YfWEKIr5ErPR0VGGhoby/ftzVw6GYRwTf73Jv4GfR1/EtCyukRvZ99zzAPnY4HyJM5fLxQeatjKeSdCbiHBV6TKM3mEqm5ryq9OTJeBy8cbljfxhoA+AG1takY7zh2RPte7r68vXWs/lZLanH79iBw2lASKpLNdsaCKVVvmHux7DbamohonP5cIUIJlR8blA0TS21Tfyl++6fNbzHByzODCQRPS4kM0sb7qohRcPH+XoWIKsouAUJFRNZ/tKH88++2z+OJ1OJ3/2ppVMRlWqygNUhSRuuLoFl2vjS1ttONo7ipJV8XgD6IbO8HD0uK+pti7MLR97w6zv6bpOOi1w1Vs2smbtMr7z9fuRnRoev8Qlb9487/O07etGURRCgRJU0+DIwaFFn9f8sawop3aBoaYLMTk5ydGjR9m4ceMJp+EUXtu2babX6y2GKE4TS1aQC93ehoeH6e/vp7GxkTVr1uQrEmB20m6xLc9zx+wANDQ08HYz1wkni1L+d9uJsfk6o+zk2dvMIApu5LRMIJzr7lMUZZZ425OhF8PnLriYtzQ1IwvCMfHjQuw5fy6X65RXxXNxyTI3bl+X/3p/7yhYIDrdiJpOmUeiNOzmUP8EOFxIghPXPLuAt+1sZf+REQYnoqxdUcUVO1pYXRXkhz/fQ8a0uOTC9Vz3lo0EfS+/B4WdaMtfOueFMVhFUUilUsiOJA6HTDye82Fe0ehhcHDwpM53f9c4Lz7XTlPLcjZdtJq/+ad3cKSrj0DYSbjsZTc+O/ba0dGBOww+fwnJGRVREtn2hjWv+HwfD9M06enpIZlMLtqmU5Ik3G43TqeTsrKyYrz4NLOkBTkej9Pe3k4gEMhXJ8xXPaHrOr29vcRiMVpaWk65BtQWYpvCyof5sI2KxsbG2LRpU96g3hbrZDI56+uFjOrnrrodDgetZQuvouxBmAMDAyc1mPJUWF1XTmnAy1Q8hWhZbGuqYkVQxu9yMDQ2SWmghHddtuGYx4V8Hr75qbeg6gYuh0w2m+Xe+w8QnUzjdgn8/uHDXHpx0yxBLuxEm7sSjMVitLe309zczLZtfjZsmGBqSqOiooTSUvcx53tuc07hLmdqOMn/+/KDiC6DB7V93PLXb2X7ZWtArCGZTM76vdlslq6uLpYvX87r39BCy+o1HHy2h8q6MOsvXPkqnPEc9pUngDkAABYcSURBVBToUCjE5s2bFy2qxXjxq8uSE2S7SiKdTtPe3j5veKKwemJiYoLe3l4aGhpYvXr1GVsN2P7I5eXl+Vg2cMKYsWVZs5pF7I+FLa12jet8TmC2Yb3X62XLli2LilG/Eq8Nr8vBNz/6J7zQPUxsapSgbLBlyxYk7wT3P5KmLhjG754/0y8IAi7Hy5dwKqViIqIbMoJgkUopJ/z9trH61NRUvtEnkUgQDvtYs+bYRpz5mDsY4JlD3ShZjRKXg3RW47d3P4nuijJ0ZJTeF4cJl4a45Lqt7H2gjeceOkCoLMhHvtyIpmlU1IW48sbtizt5p4h982lqaqK8fHHhDXslbycWi2byrw5LTpBHRkbo6elBFEV27NixYHjCHuXkdDrZtm3bCWeNnS5s0/hEIsG6detOaDY/F0EQkGUZWZZP+NjCLXw2m2V8fJzp6WlCoRCWZXHw4MEFW7QLP8ZTaWKJFFVVi5/kXYiWTeNMT7BxVT1Op5ORiRTf+c/HccsavQNxLNHJX7xv5wmf5+o3tvLjXftQNYumlRW0rD6+oGazWdra2ggGg2zbtu2Uk1L2+bbHGW25cA2P/M9BlKSJQ3Kw8+rtNDeu4M6/vh9D0OmIDTHSMU33ngG85Q4Gx8f43v/6Ge+4/cpZHaTz5RVOxTazkOHhYYaHh/M3n8VQrC8+cyw5QZZlmR07drBnzx6y2SyyLM+qKS5seW5ubiYcDp+xY5ucnOTIkSM0NDTQ3Nz8ql/49hbeDo34fD5e//rXz7v6mW/VHYvF6BiY4ocPHUS2dMKhAO+/bCUe9/wCMtfVzo5hxuNxNm3ahCRJzMzMMD4dz/0/TgzLpG/4+HP9bNasruabX72RdFqnrjY0a7LGXCYmJujp6aGlpeW0T/Ju3bqcj//923j+8S6aNzZw6Vs2cvCPXZgWCJaErmiMdEzhdDqxsgKCJaGlzLwZFeREcG7N8UJmVPZOZ76bZeEsxY6ODkzTPKkW6GJ98ZllyQlyeXluFHtZWRltbW2ztu+Qaxf1+/3U1NSgaRrRaPSkk2Yni23fCZxUMf4rxa63Hh4epqWl5bg3n4WGWv7rfYcxTHA5ZEbjKo5QHeubqmclKRVFyQ9qVRQFXdfzAu92uwmFQoyMjCCKItlsloYqP+6XtvuCKPInl7We8LVk0irjo1GaW0KUly0c4zcMI2+VOl+iUtcMHr/3RaanIlx9/SVULzu1+PnW1zez9fXN+a+XtdYiiBaJyTQYEq9/2zY6nz/KaO8EgiVw/aeumvV4QRCO67xWyFwzqsIJ0LaQp1Kp/Ap3brff3BunvVMoxovPPEtOkA3DQNd1Vq1aNcsjoq2tDV3XWbt2LUDeqMcWFLv5AXKlavMly052K1mYPFuopOzVwo6h+/3+BdutF4PbKaOaIqYhIiDgcjqO2+Vnmib9/f1MTk6yYcMGHA5HXkzS6TSpVApN07jlhmY6+2YI+hz4xBn27t27YJJyYjTBV/7ql8gOA6fs5ev/9h4CwWOnhcfjcQ4fPkx9fT11dXXzvkc//Npunv3DfizJ4rG72/jWvZ/BH1rc1n4hDMPgx3+/i+REFFl0cu3H38h1n3gjpm7Qe2iIYLmf6uUnV6pWyPEaRuyZjvYU6LlmVPbNsvB79iT0jRs3Ulpael7Eix977DFWrVpFWVnZKU+SPxMIJ5mMOT1zhM4i9uu1hdj+F4vF8Pl8+YvR/leIvc22L2p7yOfcSc+FvsYLiYhdueH3+1m1atUZm6BQODVlseOrjsfgRJS/+cFDTESTvPmiNXzy+osXvBml02na2tooLS2lsbHxmJitqqrMzMwQDodnrQznGiPNPee/+PGLtB8cw1MikklbXPEnq7n0qqb8+XY4HESj0XyL+fGqZD5x9TdJxJPIThEMib/81rtZt6PxlM9POp3mwV/8nv++7T7cZQ6UhEbjmuV87cG/PuXnXAyFLdAbNmw46RZou3LkfBDjD33oQxw+fJiWlhY0TeOnP/3p2TiMRcV6ltwK2RaLuaIxN9u8kHDbF6zb7c6L93zYP2cLtC0k0WiU6elpMpkMLpeLSCTC3r17j1umZsddXympVIrDhw8TCoXYvn37aflja6gM8eO/fudxrTsLQyOtra0L3gRi0Qzth4ZpXiNTV/+ygJxoovazKybpODRNNm0hiyIrVy2jvr4+X1fc39+PLMt4PB46OzvnLVezPzZtquX5R7rJZA08Ppn6lae+a7HbzKvKqhElkcyUgqGbpBOZU37OxaDrOocPH8bpdLJ169ZFJyvPt3hxNpvl05/+NLIs88wzzzA8PMznP/95du/ezbXXXnu2D29elpwgL5aFhHs+5go2kBdrO2lm/9/Q0BCVlZU0NDTM+kOxRdv+mE6niUajswx64FgRma/GeO4x20m78fFxWltbXxUv3YXOUzab5fDhw5SUlBw3NDI6EuUvP3knLo9JNvUkX/rHm2heU7Oo3/2u91/M0SMTHD0ywbaLVnLFmzYgyxKTk5OMjo7S2to6by114arb/vjmD23DV+okMpVg/SUNtHcfgm6OG3Od6/VgmmbeknTbtm0ICDRtfZTuvb2ITokP/O93LfKsnjypVIpDhw6xbNkyamoWd/7sY4ZcvPhUqjfORURRZOfOnVx//fUAVFZW4vP5zukW7yUXsjibLLTqtgV7oXBJYV203bo6N0xSuI23H2Nn12OxGH6/n9ra2ryAFCZvXi1GR0fp6+tbVCXDz//raf5719O4nBaKApdevpZbb/uTU/q9hmHQ3d1NNptl7dq1r7hk0bYjLQyXzP1ol05CLjHs8/koLS3Nn2tZlomNJiirLsVfujhXvpPFrplft27dCVugC1/b+VhfbO/Y0ul0foiEJEl87nOfo7W1lY9+9KNn+pCKIYtzjcWuuk8ULrFX3YU/O99je3t7mZqaYvny5UiSRDKZZGZm5lVLUtrY9pyiKC665bqiMoBDksmkdZxOieqaU4ttJ5NJ2traqK2tpaWl5bSs9AobaI4ndOPj43lBdDqdxyTNFEVhvHs0/x6dyMfkZJLDR44cOakWaPtxdrz4fBs+ap83uyrIfm39/f1cccUVAPzoRz/ixhtvPGPTVxZDUZDPQU41XGJ/ba+0KyoqaGpqmlVNMt/j5yYp5ytTg+MnKW1RmZ6e5siRI7PsORfD5VetpffIBHue6mHthjpuvPmCRT/Wfh2Dg4OMjo7mZxeeKQpDFIu9ARX6mMwdAjA3OWyXwM0XNhFFke7u7pNugT7f4sVAfqUPL6+QbezPV6xYQVVVFbfccgtjY2O8612vXvjoVCiGLJYIpxIuKbygC5OU84VLbBG3LAu32z1vfHtuzPV0oaoqbW1teDweVq9efUa33fbQ0erqahoaGl4VYZtbZ2x/TCQSzMzMzKqRX4yPSeGYrvlyDq81CsV3amqKUCiUv9nYoQqbq666ij179vCRj3yEf/7nfz6Th7mok1wU5CLHMF+oZD7RLrx29u/fT0VFRd6OtFC45xPwuUnKhcT7RIJhjxo603Xc8HIVxfEqR14tRkZGGBwcZMOGDflteeFuZ25pYOHXjY2NLFu27LyJF9vs3r2bL33pS1x77bUMDw/z/e9/f9a1YxgGf/Znf8ab3/xm3vve957pwysKcpFXl7lhEmCWaB+vptumMEk5X0333CRl4UpvenoaVVVZs2YNfr//jMVAC0MUa9euPaNdbKZp0tnZmW9iOtkW6PMpXly4+t27dy+f+cxn+MlPfsKDDz7Iv/7rv/LrX/+aNWvWzPrZTCZzthpDioJc5NzgROGSuZ/PN+fN9nbQNI1YLMbAwABerxe32z2rwwxmJynn27q/krKuMxGiWIhsNsvBgwepqqo6qd9tn187ifhaD1HA7HhxZ2cnAwMD9PX14fP5+Jd/+Rf+4z/+gx07djA2NkZ1dfVZPlqgKMhFXossJlwyMjJCSUnJrIqHwuvYTpYVdlIWfjyZJGXhSvJshijsFug1a9aclOGVfZM6X+LFhUSjUW699VZ27tzJ9u3bufTSS9m8eTOPPvooAAcOHOChhx7iYx/72KLLAF9FimVvRV57FFqgLkRTU9NxV932SvB4LfALJSnt6SH29+zH2hUPlZWVxGIxstnsq5akLMRudZ+YmFi0P7X9OPvYPR7PeREvLlwV9/f3s3PnTv78z/+cD33oQwD81V/9FQ8//DBjY2M8+eST3H777dx2223nghgvmuIKuch5zYlqugs/zvdYXdd58cUXKSsro6Ki4hgBt8X7dCUpCylsgW5ubj7pFujzKV5cyPj4OFVVVbz1rW+lv7+fAwcOALmGnNtvv52JiQmGhob4+7//ey699NKzfLR5iiGLIkVOhvlqug3DIJVK4fV6j0lSzp2UMnfVPV+lw3wexvOJty3GDQ0N1NbWntRrON/ixYV5hbvvvptdu3bxne98h7q6OlatWsV73vMevvzlL896jD1z8hyiKMhFirwanI6abjtJOZ94x+NxkslkvpW5sKNvIeMp24nQsqyTXom/Fshms3lDrw9/+MNUVVXxta99jZGREbZt28a//du/cdNNN80Ka5xjFAW5SJGzzYmSlHNb4JPJJEeOHJlVTlc4mXy+mm47Sbl69Wpqa2vPi3hxYXna2NgY3/jGN3jrW9/K5ZdfzsDAAJ/97GfZuXMnt956K7/+9a955zvfyeTk5DnVBj2HYlKvSJGzzWKSlPCycHu93rwVrC3aJ0pSAueVf/HQ0BD3338/t9xyC3/4wx8YHx+nrKyMX/3qVzQ2NrJixQo+/vGP8+53v5vy8nLe+9730tXVdS6L8aIpCnKRIucAhcJ9vC33QuGS88UyE6C0tJSenh6am5tZuXIlu3fvpr29nZ///OfccccdfPnLX+aqq66ipaWFrq4uNE1j+fLlZ/uwTwtFQS5S5DXEyRhPvZYojLV7vV5mZmbQdZ1LL70UWZbZsGEDU1NT3Hnnndx0000kEgne9KY3cfvtt5/lIz+9FGPIRYoUOasUJuJGR0epqalBURQOHz7MV77yFd7+9rfzvve9D4DBwUF++ctf4vV6z4an8SuhGEMuUqTIuY8txt/5znfYtWsXq1ev5rLLLuMjH/kIN954I7t27WL79u309vbi8Xj4zGc+c5aP+NWjKMhFihQ563z1q1/lySef5OGHH+Zv//Zv+cQnPkFzczPvec97mJqa4sYbb6SyspK77rrrbB/qq0oxZFGkSJEzyny12c899xwbN27kq1/9KocPH+aSSy7hK1/5Ch0dHVRWVvLCCy+wdevWs3XIp4NiHXKRIkXOPezOu/3795NMJlm5ciU1NTV0dnby6U9/mt/85jc4nU4aGhoIh8P51ujXOIsS5HOypaVIkSLnH/v37wdyK+M77riDm2++mUcffZQdO3awf/9+stkslZWV7Nu3jx/+8IfccsstfPvb3z7LR31mKcaQixQp8qqiaRrXX38969evZ+PGjQwODvLggw/y1FNPsWfPHr73ve9RUlJCfX09y5Yt45vf/CY9PT3ce++91NfXn+3DP6MUQxZFihR5VXn++ef5x3/8R+68804eeOABmpub+cUvfsHAwAA9PT3ccccdNDY25kveIpEIoVDofKu1LoYsihQpcvbZtm0bzz//PCtWrGBmZobq6mqeeOIJJicneeSRR2hsbOQPf/gD73znO+nr6zsfxXjRFAW5SJEiryqaptHc3IxpmmzYsIFwOMxnPvMZpqam+NKXvsTtt9/Opz/9aT7/+c+zYsWKJSvGUAxZFClS5Azxq1/9ittuu43du3fT1NTEww8/zMjICB0dHXzwgx+kqanpbB/iq0mx7G2pkclk+PGPf8w999zDTTfdxEc/+lEMw0AUxSW96ihy7vCFL3yBF154gQcffBBZXlI1BcUY8lKjvb2de+65h3/4h3/goosuAnK2jPOJsWmaGIaRHz0EkEgkSCQSZ+x4iyw9/umf/glRFHn/+99/tg/lnKQoyOcJkUiET3ziEzz77LP8z//8D2VlZUQiEe666y7uvfdeenp6Zv28KIpIkjTLP/eZZ57h/vvvX/B32Gbqcz8vUuRk+M1vfpMfTFpkNsWQxXnE3/zN33Dw4EG+/vWvE4lE6O7u5vDhw0SjUVRV5Qtf+AJr167lBz/4Ad///vfx+/3ccMMNfPKTn+TQoUN88YtfpKysjO9+97v5UUAwe6bZ8bAN1RcKkZzD43WKFHm1KYYslhrRaJStW7fS2tpKW1sbP/rRj2hpaeFrX/sayWSSO++8E4AbbriB++67j+9973v09vby1FNPkUwmaWtr48knn+Szn/0s99xzD3/3d3/HvffeiyAIPPLII+zatQuAzs5O9u7dy/DwMPF4PO9NYK+65w7/BEilUnz7298mGAxy7bXXMjIycmZPTpEirwGWVFT9fGdkZISWlhYA9uzZQ3l5Ofv27eNXv/oVo6OjXHXVVQDcd999/OIXvyAcDvPAAw+wfv16PvjBD3L11Vfzjne8gyuuuIIXX3yRxx9/HLfbDcDTTz/N0aNHec973sPXv/51nn76aV73utdRV1fHpz71Ke68807uvvtuampquPXWW9m5c+esYzNNk5tvvhnDMOjq6kJRlDN7cooUeQ1QFOTziOnp6fwoG7/fT2trK5/73Odm/cyuXbt45JFH+NCHPsTWrVt56KGHqKmpIR6PMzExkQ8pJJNJDMPIz3dLp9P5556YmODyyy/nu9/9LgB/8Rd/waZNm3jsscd44IEHeOyxx2hsbJzV9urz+fD7/ZSVlVFWVpYX+iJFirxMUZDPI/r6+qioqADg4x//OF/84hf51re+xdatWxkZGeFP//RPGR4epra2lre//e1kMhmy2SzV1dVks1kymQyrVq0CcsX8lmXlB0dGIhHWrFkDwMDAALfeemv++y+88AK7d+/mwQcfRNd1Dhw4wBVXXEF9fX0+/mx/nJmZwe12FwW5SJF5KAryecSePXsIh8NAbiT8hz/8YX75y1/y8MMP4/F4uO666/jABz7AtddeyxNPPMHFF19MLBajqqoKv99PJBKhvb2d8vJyampqOHz4MLW1tQA8/vjj7NixA8jFg+vq6gAwDAOHw8Fdd92Fz+ejr68PXdfZsGEDcOzst2g0Sjgcxul0nqnTUqTIa4aiIJ9HVFZWzvr6mmuu4Zprrpn1PY/Hw0MPPcTY2BgOh4PNmzdTU1MDwFVXXcU3vvEN2trauPXWW1mxYgWXXXYZ27ZtY3JyEr/fD0B/f3/+MeXl5UxOTmKaJq2trbS2ts57bHYoJB6PU1dXV2xUKVJkHk627K3IEkIQBCdQB3iBANAHjAE/sSzrfQU/tw34P4AOJIBfWpb1kznPJVuWpQuC8O/AfZZlLVzwXKTIEqUoyEVOC4IgVJIT72qgx7Ksrjn/fwlwNxAGIsBTlmXdcMYPtEiRc5iiIBc5owiCECIn3CHLsp4828dTpMi5RFGQixQpUuQcodipV6RIkSLnCEVBLlKkSJFzhKIgFylSpMg5QlGQixQpUuQcoSjIRYoUKXKOUBTkIkWKFDlHKApykSJFipwj/H8IYZNN7nramQAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11b926198>"
+       "<matplotlib.figure.Figure at 0x1a14a26588>"
       ]
      },
      "metadata": {},
@@ -821,28 +731,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### Regression Example Figure 3"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 35,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeIAAAFkCAYAAAD8ADhmAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11bbd3400>"
+       "<matplotlib.figure.Figure at 0x1a14a00ef0>"
       ]
      },
      "metadata": {},
@@ -875,28 +778,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### Regression Example Figure 4"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 36,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAABCIAAAGACAYAAAB4PcMRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRK5CYII=\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x115e829b0>"
+       "<matplotlib.figure.Figure at 0x1a14a41b00>"
       ]
      },
      "metadata": {},
@@ -924,10 +820,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Clustering Example Figures\n",
     "\n",
@@ -938,12 +831,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 37,
+   "metadata": {},
    "outputs": [],
    "source": [
     "from sklearn.datasets.samples_generator import make_blobs\n",
@@ -960,28 +849,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### Clustering Example Figure 1"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 38,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeIAAAGACAYAAABx1WHyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11a705208>"
+       "<matplotlib.figure.Figure at 0x1a149eb0b8>"
       ]
      },
      "metadata": {},
@@ -1001,28 +883,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### Clustering Example Figure 2"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 39,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeIAAAGACAYAAABx1WHyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nv9AAAAAASUVORK5CYII=\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11b365198>"
+       "<matplotlib.figure.Figure at 0x1a14b67748>"
       ]
      },
      "metadata": {},
@@ -1042,10 +917,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Dimensionality Reduction Example Figures\n",
     "\n",
@@ -1056,28 +928,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### Dimensionality Reduction Example Figure 1"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 40,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeIAAAFkCAYAAAD8ADhmAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nA532xVzn6tbEAAAAAElFTkSuQmCC\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x119c48c88>"
+       "<matplotlib.figure.Figure at 0x1a14e7b0b8>"
       ]
      },
      "metadata": {},
@@ -1103,28 +968,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### Dimensionality Reduction Example Figure 2"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 41,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAb4AAAFkCAYAAABfKF6gAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11b8d2908>"
+       "<matplotlib.figure.Figure at 0x1a149f25c0>"
       ]
      },
      "metadata": {},
@@ -1152,20 +1010,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Introducing Scikit-Learn"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Features and Labels Grid\n",
     "\n",
@@ -1174,18 +1026,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 42,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAdAAAAFCCAYAAABB84xIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQAEAMECAAgBg4P8BcxeynoHUQewAAAAASUVORK5CYII=\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x118e76748>"
+       "<matplotlib.figure.Figure at 0x1a14b15940>"
       ]
      },
      "metadata": {},
@@ -1221,32 +1069,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Hyperparameters and Model Validation"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Cross-Validation Figures"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 43,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def draw_rects(N, ax, textprop={}):\n",
@@ -1263,28 +1101,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### 2-Fold Cross-Validation"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 44,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAmYAAAGqCAYAAACh7ojYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nnOjGf5sKAAAAAElFTkSuQmCC\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11bdaa6a0>"
+       "<matplotlib.figure.Figure at 0x1a14ea52e8>"
       ]
      },
      "metadata": {},
@@ -1302,28 +1133,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### 5-Fold Cross-Validation"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 45,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAl0AAAGqCAYAAAAx/fEXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nwACiCwAAwACiCwAAwACiCwAAwID/A+awRviS8pn9AAAAAElFTkSuQmCC\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11bbe4908>"
+       "<matplotlib.figure.Figure at 0x1a1493a828>"
       ]
      },
      "metadata": {},
@@ -1341,22 +1165,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Overfitting and Underfitting"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 46,
+   "metadata": {},
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -1373,12 +1190,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 47,
+   "metadata": {},
    "outputs": [],
    "source": [
     "from sklearn.preprocessing import PolynomialFeatures\n",
@@ -1392,28 +1205,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### Bias-Variance Tradeoff"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 48,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAABCYAAAF9CAYAAADY2mmsAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAGkUEwAAAECaL44a1wDqBaGbAAAAAElFTkSuQmCC\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11b1b8d68>"
+       "<matplotlib.figure.Figure at 0x1a13bfc908>"
       ]
      },
      "metadata": {},
@@ -1444,28 +1250,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### Bias-Variance Tradeoff Metrics"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 49,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAABCYAAAF9CAYAAADY2mmsAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nMAEAAAAAACzz/wHBdPoar16gEwAAAABJRU5ErkJggg==\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11bd77dd8>"
+       "<matplotlib.figure.Figure at 0x10df11630>"
       ]
      },
      "metadata": {},
@@ -1503,28 +1302,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### Validation Curve"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 50,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAecAAAFwCAYAAACCbrOvAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x118d1d2b0>"
+       "<matplotlib.figure.Figure at 0x1a14b1dd30>"
       ]
      },
      "metadata": {},
@@ -1563,28 +1355,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "#### Learning Curve"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 51,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAecAAAFwCAYAAACCbrOvAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nETkYhjMREZGDYTgTERE5mP8Hlp/kNMiE2u4AAAAASUVORK5CYII=\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAEWCAYAAABollyxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzsnXd4VNXWh9+dkAKh9y5FiiBNEGwgGMDesWChKqKoXLtcLxYEuXavDfRTmqCoiA1RAQVURJqgSG8GMNQk9BBIsr8/1hxmMqTMhEymZL3Pc56ZOXXNyeS391l7rbWNtRZFURQlcokKtgGKoihKYFGhVxRFiXBU6BVFUSIcFXpFUZQIR4VeURQlwlGhVxRFiXBU6IOIMaafMcYaY04Pti3+YIz52xgzIUjXNsaYW40xPxhjUowxx40x240xU40x3YJh06lgjGlkjJlgjNlsjMkwxuw2xiw0xjzr53m6un5L3QNlayBw/Q8MyGO9NcY0KH6rIo9SwTZACUuuBQ4U90WNMdHAVNf1JwJvAKlAPeAG4AdjTCVr7f7itq0wGGNOA5YBScAI4G+gBtAR6AUMD5pxxUc/RIfGea3/BjgX2FHcBkUiKvQlHGOMAWKstcd8PcZauzyAJuXHMEQAe1lrP/PaNsUY0xM4fqoXMcbEWWszTvU8PjAQKAskWmtTPNZ/bIx5pBiuH7JYa/cAe4JtR6SgrpswwBhzoctVcdAYc9gY870x5kyvfXoaY2YaY3YYY44YY/4yxjzk6gV77ve3MWayMWaAMWYtcAy43BjTwPWofJcxZoTrPPuMMV8bY+rmco4JHp+dx+xzjDFTjDEHjDHJxpjXjTHxXsc2ctl5xOWmeNkYM6igx3RjTCzwEPBNLiIPgLV2lrX2iGv/ecaYebmcJy/buxhjPjXG7AMWGWMeNcYcM8ZUyeUcq40xX3h8LmOMed4Ys8V1zBZjzBPGmIL+vyoDR4F9uXyXbK9rljLGPOa69lFjzB5jzHfGmOZeh5YxxrxpjNnr2meyMaZiLucaZoxZ63IXJbv+DvEe+zi/h8HGmNHGmJ2u399k1/c93fU7PGSM2WiM6et1jdONMR+47kW6yzU1xhhTyWOfecCFwPmua1nnb5aX68YYc6cx5nfXOdOMMfONMecVcJ9LPCr0IY4x5nLgB+AQcBtwC1AO+NkYU89j10au/QYAlyOujaeBUbmcthvwIPAMcAnwp8e2YcDprvMMRR6fp/ho7gfAJuA6YAwwxHU+57vEArOBNsA9yGN7Q+AJH87dAagIfOWjLf4yBdiCPDE8DkwGooGbPHcyxrQHzkC+K8aYUsD3wB3A/4BLgfcQt8uLBVxzMdKj/9jV0MTls+9U5G85E7gGuBNYDdTy2u9/gEV+JyOA613rPJkM/Af4EPmtjEaeLnL7Ow8DagN9gSeR+zEW+Bxxr1yL/H7GG2NaehxXG9gO/Au42GVLost+h3uA5a7jz3Ut9+R1A4wxLwHvAr8DNyL/Dz8B9fM6RnFhrdUlSAsidBY4PZ99NgI/eK0rD+wFXsvjGIO45Z4A0oAoj21/A0eAml7HNHDZMt9r/cOu9bW9zjEhl+/xjNexM4D1Hp8Hufbr6GXrH671DfK5Dze59rnYx3s7D5iXy/q8bH81l31nAwu91r2GjAvEuT7f7jq+i9d+TyBPS9XzsdEgopntOkcG8DPy5BLvsd9Fru3353Ourq59JnqtfxN5ajCuz51d+/Xx2u9W1/q2Xr+HH732m+5af5vHukpAJvBUPvaVAi5wHdvO6+/0Sz7/Gw1cn08HsoBXAvX/GMmL9uhDGGNME6Ax4n8u5SyIUC8EunjsW8sY844xJgkRmOPASKQXXN3r1L9Za3fmcdlvvD6vdL360mvK7VjP484BtlprFzsrrPwX5+qKKWY+z2XdB8A5rr+D03u/GfjEun34lyCDqb96/Y1mATHId84VKwxG/sb3IffhdOAlYLExprRr156I6P2fD98jt79BHDLI69h7DPgsF3vB4zfl4luvz2tdr997fI80YDcyKA7I05sx5t8u91A68nv82bW5mQ/fw5vuiAfi3UIcW+JRoQ9tHIF+H/lH8VyuAKoAuHzBX7nWjUR6gGfjdtvk8JOTfyRDqtdnR9C8z+HrsZ7uiFqIIHizy4dzb3O9nubDvoUht3vyGXAYcRGACG4NXG4bF9VdNnn/fZzG7CQfvzfW2i3W2jettbcAdYEXgFaIO8U5R6q1Nt2H71HQ3686EIu4Aj3tdf4u3vameX0+ls96z9/IaMR1OBlxD3VEXHrg22/JG8eu7YU4tsSjUTehjROJMQyYk8t255+uMeLDvt1aO9nZaIy5Mo/zBqs29Q6gRS7ra+SyzpulyKDllfjWqzuKuLi8qZzH/ifdE2vtYWPM54hb4ylE8Ddbaxd47JaC+PZvzOO8f/tgq+c1s4wxo4BHcd+rvUBlY0xpH8U+P1KQe9M5j+3Jp3h+h5uBSdbakc4KY0zZUzjfXtdrHWDdqRhWEtEefWizDhGKltbapbksziBqGdfridBCY0wMIlChxG9AfWNMR2eFMcYgA4b5YiX882XgCmNMrvsbY3oYY5x7kQQ0dQ0AO9u7IAPZ/vAB0NgYczFwNTl78wDfIS6LQ3n8jfZ6n9DDnjqu7++NE0njPGXMQvz5d/hpe258h/SoK+Rhb1EJfRlODnXtn8t+GUDpXNZ7MwcZyxh0inaVSLRHHxpcYozx9pnvt9bONsYMAb50CdYnSM+mBnAe4u9+BViDCNsoY0wW8g/2QPGZ7zMTgMeA6caYJ5A46TuQwTyQf+T8GI1E7HzsCpH8GnFV1EUai+s8zjUVEYVxrn0bIpFG/iZTzUF6ue8j4jXZa/sURMB+MMa8jAwsxyJPWVcB11hXyGcuDAMSXfYtR/5urZHefAowHsBaO9cY8xnwiivS6kfE/98FCTed5+uXsdbOM8Z8BEwzxryCuJiykcHXy4DHrLXrfT1fPnwH9DXGrEQCCq5DfrPerAbuMcbchERsHbTWntRjt9ZuMsa8CjxojCmHuCqzEJfQWmvtx0Vgc8SiQh8avJHLulXAmdbama6e6BNI2F5pYCfSO/4YpLdrjLkGibCYhIjfOGArvg3gFQsuO3si33cs4if+EFgE/JcCRNjl1rgReVIZiDQcZREf/8/AhdaVFesSx8FI1ND1iJDehp8Dv9babGPMh67zLLTWbvTaftzV238caVgaIn79TcjAaH6JaB8g/4O3I6KfgPTiZwPPWms9/dE3I41kXyRkcT+wBPlN+MttyODvAOR3lYE8OX6Pb+MlvnAf8hTijBPNBHrjHrtweB4ZnH0P+VvORyKITsJa+7AxZiMSgtkXuc9/4h5IVvLACblSlKBhjJkBnGGtbRxsWxQlEgn7Hr2R4k/OI/KWYNuj5I8x5kGkJ78B8ZffgERl3B1MuxQlkglroTfGjEYeZwHmGmO6qdiHPBnI+EF9JPN0HXCHtfb9oFqlKBFM2LpujDH/RQatdiKDk7sQf6iKvaIoigdhGV5pjOmNiPz/gHdcq7shyTmBqoWiKIoSlgStR2+MGYQrJjYhIaF98+beRfjyxlpLamoqVapUITk5mR07dtC+fXuOHj1KVlYWCQkJgTJbURQlZFi2bNlea221gvYLCddNhw4d7NKlSwt17DPPPMOIESPIysoqYqsURVFCG2PMMmtth4L2C0vXjaIoiuI7KvSKoigRjgq9oihKhBMSQn/8lGf5VBRFUfIiJIR+zx6YMgX++SfYliiKokQeIZMZu2GDLE2aQNeuUKdOsC1SFEWJDEJG6B1U8BVFUYqWkBN6B0/Bv/BCqFs32BYpiqKEJyEr9A6O4DdsCOefD40bQ65z8iiKoii5EvJC77Bliyw1a4rgt2wJUSExlKwoihLahI3QO+zcCZ99Bj/8AOeeC1r5QFEUJX/Ctk+8bx98+y0sXOj+rCiKopxM2Aq9w/HjYC38738wdSps3iyfFUVRFCHsXDd5YS2sXStLtWrQsSO0bg1xccG2rPBkZEgSWaVKsiiKohSGkOjRF/Wg6p498M038PLL8NVXsH17ePby//oLHn0UvvxSPofjd1AUJfiEhNDXqAGJiVC6dNGe99gx+P13eO89GDsWFi2C9PSivUYg2bNHxiFiY+VzZqZ7W3Z2cGxSFCX8CAnXjTHQubO4WxYvhl9/LXpB3rVLRHP2bGjRAtq0kdj8UA3R/OwzeP556cUfPSrrYmLc2z3tzs6W/aKji9dGRVHCg5CSubg4EfwHHoBLLoEKFXw5yuLPLFmZmfDnn/DBB/DqqzBrloRshppbpEIF2L9fBpv/9S8R9vr14cABSEuD6dPdjWFUVO4in5Uli2fv33m/cKE85ezdG/jvoihKcAnpqQSzsmDVKliwQHrkgaR6dRm8bd0aypcP7LV84eBBuOkm2LZNRHn9enHlXHwxzJgBV10Fb7whfvwFC6RExNdfy7FHjkC5cvmf//PPYfRoePddaNtWGjrNOFaU8MLXqQRDwnWTF9HRIrytWsHGjSJof/8dmGvt3g1z5kgiVv364t4544zgif6uXZCcDM2aQdmy4mqKjhZBdhq911+HK66A/v0hKUm2z58PL74I69ZBfDx07w59+4qYe3LttbI4GCNPO9HRKviKEmmEtNA7GCPFzZo0EfFbtEh6soHIirVWRDMpSXz6nqLvmyupaNi6Vdwq11zjtgvcrqe4OHj6aejdW9ZlZcnr8eMi7v36wZo10nj98QeMHw+nnSbnSE+HTz6Rp4DERPc1S+Xya8jOPnkco2NHaThef10aE0VRQpuQdt3kx+HDsGwZLFkibo7ioG5dEf1mzaBKlcBea/x4GasYP1563pmZIsSHDsHll0OZMjBpkuQMeJOV5fbZ79wJl14KnTqJTx6kt9+9OzRtKk8wADNnSsLZf/8r97ZsWahVK3fbZs8Wey69tOi/t6IovhMRrpv8SEiALl2kwNnatdLL37o1sNfcvl2WWbOgalURymbNoF69oo/e2bZNetPt2sln5/wHDsCmTeKuqVxZ1jm97pQUEf/PP5cCcDVqiMCnp8s2Z7/kZInguegi9/UWLoTJk6UBSUqCn36SAnLPPgu33OI+1lro0SNvu50IIGNCN6JJUUoaYf+vGB0tlSwHDIC77xZhKw53wt69EgY6frz4xKdPF3eSEwp5qqSny+IMqjqiuWuXjCecccbJkTbDh8OwYTKu8cwz4r/fsUMGcuvVcz/5bNkiET0tW7qP3bhRXq2Fhx6SMNfmzeE//4EVK9zXHzdOjps/Xz4fPy4Nh4MTAaQiryihQ9j26HOjRg1xJ3TvLv7p338P3OCtJ+np4jf/808RuDp1pG5+48byvjCi162buFr+8x/5Tm3aiI9961YR0saN3fs65//oI7jrLqn747B9O3z3ndwbJyEtKUlezzxTXjMzxQ12/vnw0kvuxuW+++DKK+VeOoO5q1dLg+Fcc/Nm6NlTooH69YP335fvfOWVcNZZecf2W5vT/68DwIoSOCJK6B1iYtyhkikpIvgrVojvOdBkZ4vbZds2mDdPni4aNhRhbtTI7W4piAsukF75lCmS2Xv77dKb/uUXqYFTvbrs57hJnDIP3sI6aZJkCDdqJBm2zmBz+fKyDiA1VRqQO+/MWRuoVi0RYs91q1bJAHWDBvJ53z5x93z4odzfMmUk/HPKFPi//xP3kDMMZIw0EtHRsp8meClK8RCRQu9JlSriU05MFN/2n3+KT//48eK5/tGj0iNes0Y+V6okItmggfTQK1bM/bgyZeD++2UBEXeQ71GunIwReFKunPT8P/lE9qlUSer9vPGGDCLXrCn77d0rjZDnk8bmzdIYNG7sLrcAErefmZlzwPfvv+Xpwmlodu8WV9Ctt4rrqHZtcRddeCG89hp06OAOUZ07F155BX7+WQaWhwyRsYZ16+DsswtuBD2fAvQJQFF8J+KF3iEqyh2imZEhYv/nn8Vf1jgtTZbly+VzxYoi+I7wV6okIuaIGkjP1+lVX3KJLA6O4FWoAP/+Nzz4IPTqJYJ7ww3im8/IcFe/3LFDnnI6dXKfY+VKGdz2jrJZu1aib2rUcB+bmirnjIsT+5KSJMrnvvvcvfzTTpPG9bvv3HavWSOhorVqwQsvSEM2ebJMEzl1qjRQvXrlf++M0acARSkMJUboPYmLk15pmzbiSli5UlwS//xT/Lbs2yfLH3/I5/LlRSjr1s3ZE3fIysq9R2utJJY5oY9//+0OB12xwt0DX7dOGribbnIf+8cfck1H0J3rrFol53AaiTVr5NyOoB85IgO9NWvKdRw30qFD8sSUnS33Oj1dyk3ExMgAduXKsm/z5hIqGh19ckKXN8nJUsUzK0v2bdtWGqHcyM6WxYn80d6/UtIJe6HPyMhg7969VKtWjVhPv4OPlCsH550ny759ImarVonPOxgcOCANz8qV8rlUKemdO8Jfr17u5Q2McT8BlCoFp58u7/v0kcWhSxcpe3DBBe51CxaIaHqeNz1devQtW0rvG8SmuDh34tWhQ7JPs2Zu/z9I47l5s3sMYNMmCd/s2VNE3skJaNtWxi9Klco7Zh/kXJdfLqIdGyuiX7YsDBoEjzxy8mB3VFT+A+BOI6ANgFJSCFuh//3333n44Yf55ZdfyMrKYvbs2Vx00UXs3r2b3r17M2zYMLp37+7XOStWlHlozz1Xwg/XrJEok0DH5+dHZqZc39OGChVE9GvXFoGsVUsianITN++yBjVqwB135Nxn5kz5vp4+8gMH4LffJIrHyZj9/XcZ83CE/sABeXK44gr57PToHb/9ddfJ+uRk2bd1a/d+IA1rtWryOSEh7+8/caKc888/5Yln505J9Nq61f2dDx+WTOZJk6RhqVsXLrtMbKhXL6d9GvqplDTCUuhXrFhB586dqVq1Kn369GH8+PEntlWvXp309HQmTpzot9B7UqECnHOOLAcPioti3TrpXXrWhQ8G+/fLsmqVe13FijmFv1YtEU/vsgaO79/T1+3s70nt2jKOkJDg9rOnpMh1HDdQcrLE37dpI5+dxmTXLhnIdcYBnIxe7yzevXvlfnqOF3jj2J+eLvvXqSNPHk2auPMCUlOlHMSbb8rYQL9+IvbTpsl9evJJt32//CLbGjSQ8M9y5fIu6ObcK20clHAnLIX+ySefpHbt2ixfvpyjR48ybty4HNsTExP55JNPiux65cpB+/ayHD8u4rR+vSzFVX6hIBxf/+rV7nXly4v/vEYNEecaNaRH7uuAZvPmOT/PmCFRRE5CmlNszempO2K5YYNE8Zx9tnw+7zw55rffJDrHaTi+/16emu69N387brtNxhluvFHi8/v0kWs6rqbPPhORf/ZZeOIJd+2fRYvcBeB27JDEtk8+keunpcn9GT4cBg50l43IzHS7fvIa/NXsXyXcCEuh//nnnxk2bBhly5Ylw4k79KB+/foke6ZrFiExMeKTbtZM/tmdzNONG2UwNwRKB53gwAFZ1q93r4uOFrH3FP/q1eUJJrcBXu91nlnHHTq4o4c8qVhRQjWbNHEfM2iQRNvUqSO97jlzJKsY3A1FXpx+uiRyffKJJIW9956I+uDB8vf44gtphJ0B5lKlZOnSxX2O99+XUNPBg2HoUBHoZ56R99WrSwMC0mj06SORQEePiruoWzfJB3CeLlTclXAjLIX+6NGjVMinlOSBAweKxQ5jxMVRuzZ07SruhS1bxDWwaZP0sEONrCzxd+/enXN9bKzE5letKg2B875y5ZwzW3niDP56C9+tt8riyVNPiXC+9Ra8846IcNeukmjlNAh54VQvfeIJeOwxmYhl6FA5R5s2Unqie/eTI5ScQd/t2yWB67rrZNYuZ3D5uedkIPqbb9xCv2mTPLU984y4d7ZulRDSrl1l+99/S8NirTR0HTrI+IjW81dCmbAU+saNG7Ns2bI8t//444+0aNGiGC0SSpeWMEMn1DAtzS36W7a4k55CkWPHxOfu/SBkjPT2PRuAKlWkAShfPvferXcI6J494kIZPVoWayVpa+hQibqpXj13oTx+XFwyO3ZITf2GDeWJ5MIL4e233XWFjh+XwVjvAV3Htk2bxN329NNukT92TJ4uKlWSv82uXfJ0s2SJbL/zTrj+evmbZmRIQ/jyy/JkUbWquH9GjpQZ0V5/XbKFFSVUCUuhv+WWW3j22We58cYbaecq72hcKvHyyy/z3Xff8T/Pgi9BwBgRw8qVxVednS3RIklJ0ivcujU8Jiq31u3/dwqfOURFiZumUiX5npUq5VxiY+U+bNokcfT164swZmZKeYQFC6SHDScPEIP7iWncOIkMckpIzJkjrppOnUSwL7tMetnHjuUs1+AIfXq6XPO009wNivOUcvCgXMOpA7RkiYSe3n57zklnPvxQnkoGDpRs3nr1JNy0d2/p/b/5ZtFPbq8oRUVY1qM/duwYF198MT/99BPNmzdn7dq1tGrVij179rBz50569OjBzJkziQphZ6ozU5Qj/ElJkoAUSZQpI8JsjFTD/OknaeBiYqSg2sCBcPPNBQvkli0SLbNggTQ43bpJ1q8TDrpokbhe2rUT0a1XT55M4uLE/790qUyW8uGHcj2HlBRx9wwdKj31zExpnIYNk966k5sQFSU5ACkpUvzNk5dekn2dpDNFKU4iuh59bGwss2fP5o033mDKlCnEx8ezfv16mjRpwoMPPsjQoUNDWuRBRKRmTVk6dRLhT0kRf/K2bfK6e3doDe76y5Ej7sarVi33YOnhw/K9kpNlkLRCBek9V6jgXsqVkyUuTlw2DRtKLzs3OnUSH/wjj8igaY0aIrq9e4vQV6ok7rRXXpEnitq15d6+8IIMFDslJf76S14bNXKXoYiKksZl5Ur5+7RtK+c87zzxz592moSOBmK2M0UpKsKyR19SyMgQMXSEf/v2yOv1F0SpUhLG6SzlyklD4LwvV07ely7truL555/SO+/Y0T1AO3MmPPywPAV06iTJX/PnS+991CjZZ8IEicr56ivpwTshl3/9JUlhnTqJ0P/2m4SF/vOPuIXi48Xl41nfX1GKg4ju0ZcUPHuz4B7gTU6WAUpnCQdff2HJzHSPEeRHVJSIfkKCe/nzTxkfSEiQezhqlAj+okUyEDt7tgzsOsyfLwOttWvLZ2dwuGJFWV+3rjQMIOMBaWniVjp0SN02SmgTlkL/1ltv8fnnnzNnzpxct/fs2ZPrr7+eu+66q5gtCyyeA7zOpCHWSvbnjh05G4DiqL0fSmRnuzOGPevfe1OnjiwxMeKO2bRJngbKlpUnp9q1ZRwhO1t66vHx7mkrJ0yQQeCrr5ZjqlZ1F4ILgQdjRcmToLlujDGDgEEA9evXb5/kTHvkA2effTYdOnRgzJgxuW6/9957WbJkCYsWLSoSW8MNayWaZPdu99SDu3e768uXVKx1C7I/QzjOcbNmSZhmlSoy4Fuxogyi33abjAHExbmX+PjcP4f40JESZoS868Za+y7wLoiP3p9jN2zYQP/+/fPc3rJlSz788MNTMzCMMUYGN8uXd1exBOmlpqbmbAB27RIXREnokRZUsdJzasPcjuvaVZKoNm6UxQn/TE6WgVpfiInJvyGIjT15iYnJe502HIovhKXr5vjx4xzNZxbuo0eP5ru9pBIV5c549cwny8yUBmDvXhGsvXvd70vSbSxINOPjpf6PZw2gvBqHvDh+XJZDhwpnozelSuXdIMTEuJdSpQr36rzXBiW8CUuhb9q0KbNnz+bBBx/MdfusWbNo7Dl7tpIvpUpJdqpTldLBWvH1ezYAKSnuWbJKohvI2/0TbAHMzJQl0NFY0dE5GwFniY52b/N+XxTbo6LkvXOvnfeer1p6omDCUuidevPDhw9n+PDhJyYcOX78OCNHjmTWrFmMHDkyyFaGP8a4wxqdWaUcrJVeqSP6qanu92lpRddjDTVK6oQlWVmyhGIZD6eKaG6NQH4NREHbnPPm9b6g7f7s6+t25/fn78xpYRlHf/z4cXr27Mn8+fOpXLkyzZs3xxjDmjVrSE1NpXPnzsyePbtQM04pRYMTfuhEwjjLgQPuV6comqIoheOZZ0J8MPZUiImJYdasWbz66qt8+OGHLHfVym3atCmPP/44Q4cOJSavkotKsRAbK6GHnvPQepKdLb1+7wZg/36JGDp4ULZrY6Aop05Y9uiVkoG14nt2RN+zAfB+ryUIlJJIRPfolZKBMe4s1/ywVrKDDx+WhuHw4YLfh0D/RlGKjbAV+oULF/Lmm2+yYcMGUlJS8H4yMcawadOmIFmnFCfGSKVMp9Z8QXg2DI7wp6e7l6NHc352lmPHAvs9FCVQFErojTHXAzOstUEZg580aRL9+/cnJiaGpk2bUl9nfVD8wLNh8J6wPD+ysvJuDDIyZF1Ghnvx/Hz0qDYUSvDwW+iNMWOQ0gWzjDHXBEPsR40aRbNmzZgzZw61nQpUihJgoqPd4aaFITtbxD6/RuH4cdnHc8lvnaL4gl9C7xL5KwADtAS+CIbYJyUl8eKLL6rIK2FFVJS7UFo+Ux77jLU5GwHvBsHJws3MzPma27qCXpXwxmehN8a0AC4CugLrgRuBN4BEYGYgjMuLunXrkhGKmRuKUowY4y53EEisFbeVZyORmelOosrt/ams836fnS2L8977VSkYn4XeWrvaGNPCWptlZILWVOAca22xB7YNHjyYKVOm8MADDxDtPdGooihFijHukgehNi+uU5Iir0YgvwaioG3Z2XJuz9e83gd6u/Pec/GnkfPLdeMt6sEQeYD27dvz2Wef0bFjR4YMGULDhg1zFfwuXboEwTpFUYoLz5IAJZHHHvNtv7AMr0xMTDzx/o477sB4FX2w1mKMIUuzaBRFUcJT6MePHx9sExRFUcKGsBT6vn37BtsERVGU4OJHendYCr2iKEpIYW3ucaze8ay+rMtrccKRPD/7SFgL/dKlS1m0aBFpaWlkew1BG2MYPnx4kCxTFCUkcQTZOwPNyWTLbX1e272FOoQJS6FPT0/nuuuuY9asWScGXp1aN857FXpFiTCsFYF10oiPHvXtvWcNimPHSmTwfVgK/YgRI5g1axZPPPEEiYmJdOvWjYkTJ1K9enVGjx5Slvg0AAAgAElEQVRNeno6kyZNCraZiqLkRna2u1iQZ0W5vN47xYUyMrTsaCEJS6GfNm0aN9xwAyNGjCAlJQWAOnXqcNFFF5GYmMjZZ5/NhAkTGD16dJAtVZQSQFZWzjrQhw653+dWIvToURXsYiYshX7btm0nJgZ3EqWOuSo8lSpVit69ezNmzBgVekUpLJ6zvhw44J7lxVO8nc/p6cG2NqwY/uOPfLV+PV/cdBMNK1UqlmuGpdCXK1eOzMzME++joqJITk4+sb1ChQrs3LkzWOYpSmiTkeEWb8/Fc92hQzptVwAYNmcOzy9YAEC3iROZ27dvsYh9WAp948aNWb9+PSA9+pYtWzJt2jQGDBiAtZbp06dTr169IFupKEHA2pyT8e7bl/N1/35xnSjFzuNz5vDCggXULFuWXYcPcywrq9jEvrBCH1QHW/fu3Rk3bhyvvfYa0dHR3HXXXdx77700btwYYwxbtmzhueeeC6aJihI40tMhNdW97NuXU8i1Jx5yfLRyJS8sWMDQTp2oGB/PiJ9+Ym7fvnSdOJGrpk5l5d13B/T6hRV6U/AugePxxx/n9ttvPxFSec8993D06FEmT55MdHQ0d955J48++mgwTVSUwuP0yj3FPC3N/V575GHHTWeeSba13Nq6Nc/MmwdAs6pVmde3LweKoeS68Z5r1aeDjGkPrLTWFskcNx06dLBLly4tilMpSviQmQkpKbB378lLiCfgKLkQHQ0xMe6lVKmcn13rnpk2jREff0zWrFkn7+e8d+pCR0e733sv0dGYqKhl1toOBZlWqB69tXZZYY5TlBJJRgbs3g179uQU87Q0DTMMBlFREBfnnrUlNvbkz75s8xZ1X2slr1wprx5VeANNWAzGOslPt99+O8YYn5Oh+vTpE0izFCUn2dniWtm9G3btci9pacG2LHIoVUqE15mT0Z/3cXGylMDJisJC6Pv164cxhptvvpnY2NgTn/NzOxljVOiVwHHsGOzcCcnJbkHfs0ddLr4SGyvTVZUuDWXKFPy+dGkR6VJhIVkhR1jctblz5wIQ65oc0/msKMXC8eNuUXeWvXvV7eJJfDwkJORcypZ1vy9TJqdwq2AXK2Fxty+88MJ8PytKkZGdLb3zbdvcor5nT8kU9VKloFw5WcqXF+EuV+5kQU9IUOEOccLur5Oens6nn35Ks2bN6NSpU7DNUcKdI0dg+3YR9u3b4Z9/xC0TyRgjol2+vFvIPQXdeR8fL/sqYU/YCX1cXBx33HEHr7/+ugq94h/WysDo33+LsG/bJi6YSCM6GipUkKVixZyvFSqImGsPvEQRdn/tqKgo6tevz4EDB4JtihLqeAq7s0TK76Z8eahcWZZKlWRxxLxsWe2JKznwS+iNMZcCQ4BGwMXW2m3GmDuALdbaHwJhYG707duXDz74gKFDhxIXF1dcl1XCgbQ02LIl/IU9KkqE21PMnfcVK0rstqL4iM9Cb4y5FRgLvAckAs4vLRp4FCg2oT/vvPOYPn06bdu25Z577qFJkyaUKVPmpP26dOlSXCYpweLYMRH2TZtg40aJYw8nYmOhalWoVk1enaVy5RIZ760EBn969I8Cd1prp7p68Q6/ASOK1qz86dGjx4n3Q4cOxXg9pjpTCWZpcafIw1oJddy4UcR927bwKOIVHw81akD16jmFvVw5dbMoAccfoW8CLMxl/SGgfNGY4xvjx48vzsspwebYMdi8Gdatg/XrZbKLUCUqSgS8enURdmcpX14FXQka/gh9MtAUSPJa3wXYVGQW+UDfvn2L83JKMDh4UER93ToReddEMyFFTAzUquVeatYUkdeIFiXE8OcX+S7wuofbpp4xpjPwAvC0vxc2xgwCBgHUr1/f38OVSGTPHlizRsT9n3+CbU1OYmJEyGvXFlGvXVtE3ddCVooSRHwWemvtC8aYCsBsIB6YC2QAL1lr3/L3wtbad5HGgw4dOhQq7XDp0qUsWrSItLQ0srOzc2wzxjB8+PDCnFYpTvbuhdWrYdUqyUgNFapVg3r1oG5dqFNHPquoK2GKX8+Y1tonjDGjgBZAFLDaWnsoIJblQ3p6Otdddx2zZs06MfDqFDhz3qvQhzApKW5xD4W5fWNjRdAdYa9bV+qxKEqE4JPQG2NigF+APtbadUBQZwkZMWIEs2bN4oknniAxMZFu3boxceJEqlevzujRo0lPT/e5lLFSTBw8KHW4V66EHTuCa0uZMtCggSz168vAqfbWlQjGJ6G31h43xjQkyHPFOkybNo0bbriBESNGkJKSAkCdOnW46KKLSExM5Oyzz2bChAmMHj06yJaWcI4fh7Vr4Y8/JBQyWIXBPIW9QQNxw2gEjBIkrLX5llgPBP64biYCdwKPBMgWn9m2bRsPPvggANGupJJjrkJUpUqVonfv3owZM0aFPhhYC1u3wooV4p4phvkwTyI2Fho2hMaNVdiVkOPpp5/m6aefLtZr+iP0CcCtxpgewDIgRzCztfb+ojQsP8qVK0emK9yuXLlyREVFkZycfGJ7hQoV2BkKvt+SxKFDIu7LlgVnRqVateD000Xc69XTrFJF8cAfoT8D+N31vpHXtmJ9DmncuDHr168HpEffsmVLpk2bxoABA7DWMn36dOrVq1ecJpVMrJUY92XLxEXjFfkUUBIS3MLeuLF8VhQlV/wJr+wWSEP8oXv37owbN47XXnuN6Oho7rrrLu69914aN26MMYYtW7bw3HPPBdvMyCVYvfeqVaF5c2jWTEIedQBVUXzC+DMoYIypgVSvbIH04lcBb1trd5+KER06dLBLl/oeyHPo0CH++ecfGjduTClXFuIrr7zC5MmTiY6OplevXjz66KMn1cBRTpHkZFi0CP76q3jqyxgjUTHNmslSpUrgr6koYYQxZpm1tkOB+/kq9MaY84HvgF24a96cC1RHShbnVgfHJ3wR+oyMDC1JHAyys8Ut89tvMsgaaKKioFEjaNFCeu+5VCVVFEXwVej98dG/BHwEDLbWZrsuEoWULn4ZOK8whvpKrVq16N27NwMGDKB9+/aBvJQCkJ4Ov/8OixfD/v2BvVZUlETJtGyp4q4oAcCfHn060NaVMOW5vjmw3Fpb6FRCX3r0DRs2JCkpCWMMrVq1YuDAgdx6661Urly5sJdVcuPgQVi4EJYuDezcqcZI6OOZZ4q462CqovhNIFw3O4F+1trvvNZfCoyz1tYqlKX47qP/8ccfGT9+PJ9//jlHjhwhLi6Oq6++mgEDBtCjRw/1yZ8KKSmwYIEkNwXS/161KrRtC61aybR34UxWloZxKkElEEL/GnADMgHJr8hg7AXAf4FPrLUPFtZYfwdjDx48yEcffcT48eNZtGgRxhjq1q1Lv3796NevHw0bNiysKSWPHTvgl18kuSlQ2Xplyoiwt2kj8e7h3iA7YaRO1E92tvu9teH//ZSwIRBCHwu8CAzG7ds/DowBHrPWFvo531+h92TdunW8//77TJ48mZ07dxIVFcWFF17IwIEDueWWWwprUuSTnAzz5knN90BgDDRpAmedJa+R2PP94w947jkpYVytGjz4oCRrKYoXAwYM4K677qJTp065bl+8eDFjx45l3Lhxfp23yIXe48RlgMaAATZaa4/4dYJcOBWhd8jOzubbb7/lzTff5PvvvycqKupE9qziwc6dIvBr1wbm/OXLQ7t2IvDh7prJi+xsGDkS/vtfSEyEuDj4/nsZc/j3v6F372BbqIQYUVFRTJ48Oc/O58cff8wtt9zi9/SngYi6AcAl7Cv9PS7QLF68mK+++oqFCyXKMzY2NsgWhRi7d4vAr15d9Od2eu/t28trJCUy5eaHX7MGPv4YnnkGBg2SBu3gQbj8chg6FLp1k0lKFMVHDh8+TExMTMDO77PQu+rQb7PWjvVaPxioY60t9uLvO3fu5IMPPmD8+PGsW7cOay1t27Y9EZGjIJmrP/4oSU5F7YOPjxdxP/tsqFixaM8dbBxfuyPyM2fKrFJt24rIb9sGd90lTzAg4xzLl4vrZvt2FXqFrVu38vfff5/4vHbtWn766aeT9ktNTWXMmDGcfvrpAbPFnx797chgrDfLgGFAsQh9ZmYmX331FePHj+f7778nMzOTihUrcvfddzNw4EDatWtXHGaEPkeOwE8/wZIlRR9FU7UqnHMOtG4tlSIjEWdANT0dhgwRcR85UoQ+KQnOOENEfu1aGDBAcg7uvx8eekgmA/ccoFVKJOPHj+eZZ57BGIMxhlGjRjFq1KiT9rPWEhUVxfjx4wNmiz9CXx3Yk8v6FKBG0ZiTN3/++Sfjx49nypQpJ2rQd+vWjYEDB3Lddddp1qzD8eOS5PTzz3D0aNGeu0kT6NRJiohFemRJdja8+qp831274KuvZOwBoGlT+PJLuOYaWX/VVXLPW7eW7d98AwcOqK++hHPNNdfQoEEDrLUMGDCAQYMGce655+bYxxhD2bJlOfvsswNaiNEfod8KdAY2e63vAmwvMovyoG3btgDUq1eP//znP/Tv358GDRoE+rLhg7Xw55/ipinKTNaoKAmNvOACiSyJRHILiZw/Hx55RFw3AwbIoKvDjTfC++/DnDnw0Udw002yPjsb5s6FN96QdZmZUMrvYTAlQmjTpg1t2rQBICkpieuvv54zzzwzKLb48yt8B3jVFWb5o2tdIjAaeL6oDfOmV69eDBw4kJ49e2pilDfbt4sP2aMm/ykTEyORM+eeG3n+dwdrRZxzC/1s1QqeeAJGjZJoGmd/J6P3X/+SZfVqqeSZni7CP3asNIo9e6rIKyd46qmngnp9f6tXjgb+BcQi4ZUZwP+stY+fihFFEV5ZIjl8WMRl+fKiO2d8PHTsKC6LSC5L4OlD37FDGsqqVaWYWpMmsv6336BfPymyNmPGyT73Rx6Br7+W4+vUkfLNTz0FAwcW61dRQg9nzurbb78dY4zPc1j36dPHr+sEMo4+ASlTbIDV1tpDfp0gF1To/SQ7W3zC8+YVnR8+Ph7OO08EviSNdwwfDi+9JBm7SUkSLXPfffD443Jv334bHn5YGoJLLpFjnJDL7GwJW929G/bsyeneUUo0UVFRGGNIT08nNjb2xOf89NYYE/w4emNMCyDLVdRsiWtKwbHGmFXAC9baYihQrpCUJIN9u09pCgA3cXHinjnnHBH7ksSbb8L48TBmjDRyqanwwguS9NS4Mdxwgwy4fvaZrOvaVe6R4+qJipKGQUMpFS/mzp0LuPN5nM/Bwp8SCAsRN81UY0xdYB0wH2gNfGCtHVZYI7RH7wPp6TB7toTxFQWxsSLu554LpQtdeDT0ycsPf/AgnH++xMZ/9pnbTfX335IEtWOHhKdWqACffAJ9+8Jrr8Hddxf7V1CUvPC1R+9PoK/nnLE3AIuttZch8fUaRxYorIVVq+Ctt4pG5KOjRdz/9S+46KLIFvmsLHfS0/79EiGzZo1si4uTwevzzxeRd0oyN2gg8fCrVolrLCoKunSRnv2QIRJqqSg+sHjxYlJTU4NtBuCf0EcDTuGyRGCm6/0miiGOvkTiiNOnn8pA36ly5plw771w8cUlY3IPpxf/7LMykfgrr8C330q2cEqKxMPPdP2MY2PdiWVNm0LlyjJtIkivf9Ag+M9/ZMBWUXzg3HPP5bvv3FXdDx06xC233MLqQJQhKQB/4r/+Au42xsxAhN5x1dQB9ha1YSUaayWjdc6copn847TTJNyvTp1TP1e4YK1kBz/4oIxpjBolA80NGriLrZ1zDnz4IUyeDLfd5m4YsrPFX9+4sft8iYk62Kr4hbdbPCMjg6lTp3LHHXfQokWLYrXFH6F/DPgCeBiYaK11CptdBSwuasMKYuHChbz55pts2LCBlJSUk26qMYZNmzYVt1mnzr59knW5Zcupn6tKFRH4pk1LRiarZ/ijMeJ+mT4dnnwS+veX3ABwJzL17y9++Mcfl5yBOnUks3jsWHn6ufDC4HwXRSlifBZ6a+1PxphqQHlrbZrHpneAUy5V7A+TJk2if//+xMTE0LRpU+rXr1+clw8M1krizXffQUbGqZ0rNlZE6pxzIrMOvCeOaEdFyfsjR9yFxr7/XtwxV17pFnmQ/bOzJSnq3/+W2PfWrUXco6OlRv9rr0kDqSgRgF+pe64QyjSvdX8XpUG+MGrUKJo1a8acOXOoXbt2cV++6Dl4UBJvimISkNatoUcPKFfu1M8VDjjZp2+9JYXHbrhBShTUqCGDrEeOiMh7lzlwev/XXSeN4v/9nwy0JiRIGYlIraWvlEjCMkc7KSmJF198MTJEfvVqEfn09FM7T82acOml4o8vSSxaJNmr6elw7bVQvTqULSvbnCJjn34qUUaeteV37pTSwhdcIPfu8VNK7laUXJk5cyY7d+4E4MiRIxhj+PTTT1mxYsVJ+xpjeOCBBwJih9+ZsYHA3zj6008/ncGDB/Pwww8H0KoAc/y4uGmWLTu188TGSphkx44lryxuaqr03qtXhxEjJLvVs2zDtm3wwAMyqD1rltwjkKib118XH/5LL0EkuP6UkCPKz//HkMiMDSUGDx7MlClTeOCBB4gORx/07t0wbdqpZ7c2aSKzGkVq0bGC2LJFGspx4yR8EqTX/ssv0LKlTALyxBPy1HT55dJ7b9FCKlOuWSP15VXklQAR7GxYT8JC6L1nZenQoQOfffYZHTt2ZMiQITRs2DBXwe/SpUtxmegb1oowffedDBwWloQEcdO0bBn50TT5kZEh4ZKTJkkm6+LF8MUXkgQWFwd33ilC/803Utpg+XLxwzduLNmwNTT9QwkcF4ZQ1FZYuG6cgkCeeNqd27bCPAYFlPR08cWfarJEu3YSMhnJGa251YfPixdflBIF1kodmv79xZUzdqzM/jRrljsePitLktAqVw6c7YpSjBSJ68YY85WvF7TWXuXrvv4SyCm2ioWdOyUiJC2t4H3zonx5mckogPNKhgS+TtbhxM0/9JBk+yYn50xwctwznhnA0dEq8kqJpKD/qJRisaIA+vbtG2wTCs+KFVLL/FRcNW3aSIncSO7FOzgiP3asJI916ybx7mXK5EyK8nwtXdot8mlp8tS0aJHEz9eqVfzfQVFCjHyF3lrbv7gMiTgyM8UXfypVORMS4IorZCLqSMbTVbN4sUzDl5Eh6198UXrszzyTf1TRL7+IuK9cKf737t2lNo2iKP4NxhpjLgWGAI2Ai62124wxdwBbrLU/BMLA3Ljooovy3W6MoXTp0tSvX5+ePXty9dVXF+/0g/v3i9/4n38Kf47mzaVHGsmzPDkYIwK9caMUb7v6ahH32FiJf3/nHWjbVuLkPWPhPVm9WgqUxcfD55+L0CuKAvhXj/5WYCzwHjAYaGmt3WyMuQu4zlp7cWGN8DeOvkGDBqSnp7Nnzx4AKrrCC/ft2wdAtWrVyM7OJiUlBWMM559/Pt9++y0JxSGaW7eKP/7w4cIdX6qUuGnaty85ETUHD8og6vTpMm3fpEkyEQjIE9H990sPf8kS6dV7PgE4762VSVl0wnilBBGIevSPAndaax8APB3OvwFt/bTvlJg3bx5lypThkUceYdeuXaSmppKamsquXbt4+OGHSUhIYOnSpezdu5eHHnqIX375hREjRgTesBUrYOLEwot8tWoSEtihQ2SKfF5RUOXKycQerVpJj7ytx8+pQwcpa5CUJCGSIKLu4NwnZ9JuRVFOwp8e/RHgDGttkjHmINDG1aNvDPxlrfVrpNAYMwgYBFC/fv32SUlJPh977bXXkpCQwOTJk3Pdftttt3HkyBGmT58OwJVXXsmaNWvYuHGjPyb6Tna2ZF/++mvhz9G+vfTkPYtvRRKeA6m//CIDrTVryvhDQoK4u0aPFjH/6SdJbjp2TNw3//wjMzv99ZccW7t23i4cRSlBBCIzNhloCngrchdk8hG/sNa+C7wL4rrx59i5c+fy/PPP57n9ggsu4HGP2iXdu3dn9uzZ/proGxkZMvhX2IJkcXESNtmyZdHaFUzS0qBSpZwulqgoyWTt108SlxISJHnpmmvg5ZehYUPxwX/9tYRMLlokIp+dLeWDb7tNZngaOlRq16jIKyFMQeOIuWGM4YcfAjPU6Y/Qvwu87hp8BahnjOkMvAA8XdSG5Ye1lrVr1+a5fe3atTkSqqKjoykdiNDEfftk4orCljKoUUMiTCIptvvZZ0Wsv/lGXFEOaWninomJkVmeKlWSuvsvvigivmABnH22zOT0wAPwwQdw++0SvRQbKyUM5s1zFypTlBBm8+bNJwWAHD58mL17ZY6mihUrYq1l//79AFStWpWyTjG+AOCzj95a+wIwHZgNJABzkcHZsdbatwJjXu50796dMWPGMHXq1JO2ffTRR4wdO5YePXqcWLd06VIaFLX/dscOeO+9wot869Zwxx2RJfIgNdxHjcop8gBz54rbZcgQmbO2RQt47DER+t9+k7j5qChxXyUmSp14EJHPzJQngDfegMGDi/87KYqf/P3332zZsuXE8sMPP1C6dGmGDh1KcnIyqamppKWlkZyczP3330+ZMmUC1puHQpRAMMaUAVogjcRqa+0pT2bqb9RNUlISF1xwAcnJydSqVYvTXdmiGzduZMeOHdSqVYsFCxZw2mmncfToUS699FKuuuqqoisBunGjhE8WZpq/6GgRs0gZcHXcM8eP5xxfWLZMRLpVK/n89tsSPXPokAy4Ohmw27fLAPTmzbBunez78cfQu7eEWL7+evF/J0UpYq6++mrKlCnDRx99lOv2m2++maNHj/LFF1/4dd5ARN0AYK09Yq1daq1dXBQiXxhOO+00/vjjDx566CHKly/PokWLWLRoEeXKleOhhx7ijz/+4DRXXfb4+Hjmzp1bdCK/YoW4awoj8uXLSxjh2WeHv8hnZsLs2fDHHyeL/F9/Sa98+PCc+5cpIyGU4P7+detK737/ftiwQdZ16yZzvYZQUShFORXmzZuXb5Gzrl27BrTaZUG1bsb5eiJr7YBTN8d3KleuzAsvvMALTshdoLEWfv5ZZh8qDHXrij8+UmZ+slZ66c7sWDEx4orp2BGuv16+6w8/wNSpcPPN0LWrNHTTp0vlzUqV3JE4hw/La9Wqcu7q1aVOvKJECMYY1qxZk+f2VatWBTSps6AefTWv5XrgWuB013INcB1QNWAWhgLZ2ZJ1WViRb9VKok0iReRBhP3uu+We3HGHCPdHH4lIg/jiS5eG99+XQevWrSUefv58qQMPUtFz2TJpQPv1k3MoSgTSs2dPxowZw6RJk3IEilhrmThxIu+88w49e/YM2PX9iaMfBrQD+ltrD7vWJQDvAyuttaMKa0RBPvpJkyYBcPvtt2OMOfG5IPr06VNYk9xkZUmN85UrC3d8YqLEhIe7qyY3VqyAs86SENHBg+Hpp3POtTpiBLz7Ltx3n/T2U1MldHLiREluOuMMyXZt2FDcYZ7VJxUlgti+fTudO3dm69at1KhRgyZNmmCMYf369ezatYt69erxyy+/ULduXb/O66uP3h+h3wEkWmtXe61vCfxgra3pl4Ue+FqPPj09ndjY2BOf87O9SOrRZ2ZKzLYzSOgPMTEy8XSkFCTLLUHp669hzBip+f7IIzLJR9my7oHWPXvEjXP4MEyZIvV7Dh4U3/7PP0scfffuMKBYvX6KEhT279/P888/z5dffsnmzZsBaNSoEVdffTWPPvroiVIu/hAIoT8IXGutneO1vjsw3Vpb3m8rXRQk9PPnzwfcM7Y4nwvilGZ4OXZMXBFbtvh/bNmycOutkVEi11vgU1NPDgkdMkQiZT75ROav9TxuwgQZlL3hBnjllWIzW1FKAoEQ+glAIvAIUt8G4BzgeWCutbZfoSzF//DKgJOeLj3Q7dv9P7ZqVUkAirR5XD/+GF59Vdw0FStCnz7SWweZWKV1a+mdv/KKlDZwBlqzs2Uwdu5caTi1qqSiFBmBCK+8G/gamICUPNgETAS+Ae4phI2hyeHD4kMujMjXrw8DB4anyG/ZInHr3u6uf/4RQb/3XujUSaJpoqLgnntg4ULZp2ZNqf3+6afikoGc0TSDBkneQM1Ce/cUJew5fPgwTz31FK1bt6Zs2bKULVuW1q1b8/TTT3O4sIUQfaQwCVMJQGPAABudgdlTIWR69I7IFybbtUUL8cn7Mg1eKPLBB1Ki4J13JIEJpI7P229LsbaHHoJzzpH1V18t/vm2beH332Xd0aOS8RoVBU89JaGUI0fKuW66KTjfSVFChNTUVDp37syaNWuoWrUqzZo1A2D9+vXs2bOHM844g59//pnKfmbKF7nrJpD4IvRXXeXflLTGGL788kvfDzhyRER+1y6/rgNIT/fii/OfASnU2bFDJvlYsECSoKpUkfUffyxFxS64AF57DYYNEzfN+efL5zFj4K67ZN+FC8VHX748HDggGcAffSSZsIpSgrn33nsZM2YMb7zxBnfddRfRrnGvrKws3n33Xe677z7uueceXvczEzwgQm+MqYHMMNUCsMBq4G1rbSHU0Y0vQh+Vi4jmF3njV9TNqYh8t27QpUt4hk9aK64a5ylk3jzxp/fp46797gyqvvSS9O4fekhCKTdvlu+ekSETczuZscuXS5TSWWdJ3RtFUahfvz6XXnop77zzTq7bBw0axHfffcfWrVv9Om+R++iNMecDG4FbgHTgKHArsMEYc65f1hWC7OzsHMvu3bux1jJnzpyTtmVnZ/sn8pMmFU7kL7lE0vTDSeSzs93vjRGRX7MGHn5YaurXqiW99NWr3fvs2gXjx4uw9+8vwt+kicwGlZIi1SZBGo527aSxUJFXlBPs2rWLdu3a5bn9rLPOYldhNMhH/PE1vAR8BDS11t5urb0dqU8/FXg5EMblR5GkC6eni8jv3OnvxaWGvOOzDnUyMyXG/cCBk91Lb74pvvaNG+U+lC0rYxXPPivbo6KkONmWLSLiZcrI+l9/lf0vvFCSotLSwqvBU5RipEaNGixfvtnw0WAAABHcSURBVDzP7cuXL6dGjRoBu74/Qt8WeNlae6JL6Hr/CpIxG15kZMDkyf6LfFSURKGcdVZg7AoEkybJrE3ekUSHD4tI9+olg7HvvSe9eicu/ptvZL/YWHl6eeUVqV2zcKEcd/HF4s5JSdHyBYqSD1deeSXvv/8+77zzDtkeT9XZ2dm8++67jBs3zu9xSH/wJ45+J9DPWvud1/pLgXHW2kJnBxUm6iYlJYVq1aoxZ84c/2dzycyUOHl/k6FKlYIbbwwPt8SqVVKOoG5deXKJj5ced3q61KABWLxYnkq+/BKuvNJ97Lp1kq165Ih7pqflyyXpaedOcf80by5lC5o3D873U5QwIiUlhXPPPZdNmzZRrVq1E1E369atY8+ePZx++un8+uuvVHGCIHwkEHH0U4H3jTG3GmMaGmMaGGNuA/4PcemEB1lZEu9dGJEPF9/z0qVSSO3TTyXDt3RpeYJ58EF3khPIZB7x8VKqANyllxs1gssuk+ibCRNkXbt28lQwcyZ89ZWEVarIK4pPVKlShaVLl/L4449TpUoVlixZwpIlS6hatSrDhg1jyZIlfou8P/gT9P0oEjs/znWcAY4BY4DH8zkudLBWeq/+1q5xRN41wUnI06GDCPW4cVJUrXVriYrZt09mc5oxA664Qr5Xu3bitunXzz2bU0yMW8RHjpRz1a0rk3LXrh3Ur6Yo4Ur58uUZNWoUo0YVuv5jofFZ6K21x4ChriqWnglTRwJlnCeveNVJOXLkCMYYPv30U1asWHHS/saYnJONWCu90T//9O/C0dHhJfIOo0bJBCcffSQZuxUrSlnhv/6SgdYrroBmzaBzZwktfeklePRREf/0dPHVX3KJlC749lt3EpWiKGGHv3H0NYHzgOp4uX2stW8X1ojCxtHnx0lx9HPnSi10f3BEvkkT/44LFf71L+mtT5smoZEA//2vzNP6739LTPyWLRKRM22avDZvDtu2if/9mWckGcypMa8oSqE5fPgwL7zwAp9//nmO6pXXXXcdjzzyCAkJCX6fMxBFzW4D3kN68mlIwpSDtdYW+pneF6H3tWKlJyeqVy5bJin7/hAdLan7oe6Td0oC58bu3eK2uegi6bHXri3Cfs894r5auBBq1ID162Vu1gkT5FylSonLRifiVpQiIWxKIBhjkpAiZiOstZl+WVMAAa11s2GDuC88E4UKwhiJMGnRIjA2FQVOdUiHadOk9EC9evIE4oj/22/D0KESStqrlzRgEydKj/7aayWO3mH3brlfnTqFb80eRQlBwqYEgjEmDWhvrd3slyU+EDChT06WjM7jx/077uqrZZAyHPj8c8lqzcqS3n10tFTQfPJJ2X7sGJx3nkTXjBsnTygHDohb59tvZfasTp3yfzJQFOWUCJsSCMAU4HK/rAgmaWkSK++vyF9ySeiKvOeYQ0aGewC1Vy+pU5OUJHHxr74qk4CARNKMGiWZrN98I7Hx5cvLMRkZ0rsHFXlFCSDBLoHgz3/3g8AXxphEYCWQQ0GttSOK0rBT4sgRcVX4W+O5a9fQLmsQHS0NV0yM9NQ3bpQ68H37wv79ktH66acy+cmzz8qTSVycZLD26gVjx0rVyY4dJWTym2+ktLCiKAElnEog3AVcgkTdXAvc4LH0KnrTCklWlqTvp6T4d1ynTlK3JZT59luJkd+yBcqVk3DJ226TuPiWLWXQ+eefJZpmw4acU/c9+6ysmzhRGkJQkVeUYiKcSiDsBkZba18taiOKzEdvrWRt5tNy5kqrVjJpSKgU5bI2d1uefx6ee04yX52QzyNHpMfeuDGMHi3VJ5OSoGFDeb9gATRoIPuOGyf+es1oVZRiJZxKIEQDX/llRXHz22/+i3yDBuLiCBWRh5NtcXoAV1wBBw/KJCEOP/8sYt6vn3sy8qwsOO00cV0NGeLed8AAFXlFCQLhVAJhPFJ/PnR88Z5s2ACzZvl3TPXqkhAVagOR2dmS1HTTTSLYThiltfJ57lyZ7ARkHta4OOnFgwywTpkCbdpIqGWo5wEoSgkhLEogAGWAO4wxFwN/cvJg7P1FaZhf7NkjceT+TItYrhzcemtoTnP3++8wfLiUBH78cfecq82ayYBsaqp732rV4JprZEKQGTPkHsybJ5mtiYmyv6IoQWHHjh0YY6hZsyYAR48e5e23Ty4iUK9ePW644YaA2eGP0J8BOH4R7+f/4E08e+SIJERlZPh+TFyciHyFCoGz61To0EFq0gweLDHxUVHQs6fY27GjVJF0qF1bwimrVpVjQAq3nX9+cGxXFAUQ//uZZ57JyJEjeeyxxwApg/Dwww+fNA1qqVKlaNu2LU0CVG7Fn6Jm3QJiwamQnS09ec8ebkFERUlNeVcLG7I0bQr/938wYoRMvn3HHTKPa5MmUkd+/Xq3W6ZmTXjjDQmxDNXGS1FKGOPHj6dy5co5iyu6eOmllzjLNXlRdnY2vXr1Yty4cYwePTogtoSYc9pPfviB96dN4/3ly/l14EDfjrnsMolQCQcaN5ZwyCFD4K23ZCyhTBl5esntCUZFXlFChh9//JGrrrqK2NjYk7a1adPGXYsLuOmmm/jhhx8CZot/JSFDidWrYcECth84wKJ//vHtmI4dxS0SLjjRNv/9r0zd9+ab8gTzzz+waVNwbVMUJV82bNhA27Ztfdq3efPmbNy4MWC2hGePfu9e8UP7Q6NGUt4gnHCibZyBY2slCapBg/B5KlGUEsrhw4cpW7ZsjnWVKlVi5cqVNGzYMMf68uXLc9jfTH4/CD+hz8iQzFd/Bl+rVJFqlH7WtA8ZnASqW2+V7N169YJtkaIoBVCxYkV2eOa8IPNqtGzZ8qR9d+7cSYUAul7DS/mczFdnjlNfiI+H3r3dE2KHI04ClTEq8ooSJrRq1YpZPub2zJo1i1atWgXMlvAS+t9+g1WrfN/fqStftWrgbFIURcmF66+/nvnz5/PVV/kXFPjiiy+YP38+vXoFrmRY+Aj99u0we7Z/xyQmqi9bUZSgMHDgQJo1a8aNN97Ik08+SZKTve4iKSmJ4cOHc/PNN3PGGWcwYMCAgNkSNB+9MWYQMAikKH++pKdLtIk/s0SdcYYmDSmKEjTi4uKYMWMGl19+OSNHjmTUqFGUL1+e8uXLc+DAAQ4cOIC1lubNmzNjxgzi4uICZkvQevTW2nettR2stR2qVauW347il9+3z/eTV6kSeoXKFEUpcTRq1Ijly5fzv//9jwsuuIDo6Gh27NhBdHQ0nTt35vXXX+f333+ngVNhNkCEftTN0qWwZo3v+8fESG2YUKxhoyhKiSM+Pp777ruP++67L2g2hLaPfudO+P57/465+mqpSqkoiqIAoSz0x47JtHiZmb4fc845cOaZgbNJURQlDAldof/2W/+mA6xTB3r0CJw9iqIoYUpoCv2aNf7PFNWrl9ZeVxRFyYXQE/qDB+Hrr/07xhioVCkw9iiKooQ5oSX0TijlkSO+H1OnTuDsURRFiQBCK7xy6VKZ+9VXatTwL4lKURSlBBI6Pfq9e/2b3DsmRurYqF9eURQlX0JH6D//HI4fL3g/h0sv1WJliqIoPhAaQn/woMya5CvNmrHBq6A/wKFDh9jjTwljRVGUEkBoCP2hQ77vm5DAZ9nZtDzzTKZOnepxikP06NGDS8JtFilFUZQAExqDsdb6vu9VV3H5aafRedw4+vTpQ7t27QDo2bMny5cvZ/r06QEyUlEUJTwJjR69r7RvD82aER8fzzfffEOXLl1YsmQJwAmRv+yyy4JspKIoSmgRPkJfuTJcfPGJj/Hx8cyYMYPExERiYmJU5BVFUfIgNFw3BWEMXHstxMbmWB0fH8/MmTPZt28f+da0VxRFKcGER4/+vPPynBQ7JiZGRV5RFCUfQl/oq1aFrl2DbYWiKErYEtpCb4xMJBITE2xLFEVRwpbQFvpOnfJ02SiKoii+EbpCX7kyJCYG2wpFUZSwJ3SF/qqr1GWjKIpSBISm0HfsCA0aBNsKRVGUiCD0hL5iRejePdhWKIqiRAyhJ/RXXXVSYpSiKIpSeEJL6Nu3h0aNgm2FoihKRBEaQl+livjke/QItiWKoigRR2jUuomLg379gm2FoihKRBIaPXpFURQlYKjQK4qiRDgq9IqiKBGOCr2iKEqEo0KvKIoS4ajQK4qiRDgq9IqiKBGOCr2iKEqEo0KvKIoS4ajQK4qiRDgq9IqiKBGOCr2iKEqEo0KvKIoS4ajQK4qiRDhBK1NsjBkEDHJ9zDDG/BUsW0KMqsDeYBsRIui9cKP3wo3eCzfNfNnJWGsDbUjBRhiz1FrbIdh2hAJ6L9zovXCj98KN3gs3vt4Ldd0oiqJEOCr0iqIoEU6oCP27wTYghNB74UbvhRu9F270Xrjx6V6EhI9eURRFCRyh0qNXFEVRAoQKvaIoSoSjQq8oihLhqNAriqJEOCr0iqIoEY4KvaIoSoSjQq8oihLhqNAriqJEOCr0SsAwxkwwxswI9DHhSkn6rkpw0cxYJQfGmHnAX9bae4vgXBWQ39i+QB4TDIriPoXLd1XCn6DVo1fCF2NMrLX2WEH7WWv3+3vuwhwTrpSk76oEF3XdKCcwxkwALgSGGGOsa2lgjJlnjBljjHnJGLMHWODa/xJjzM/GmDRjTKox5ntjzBme5/N0TbjO87Yx5jljzF5jzG7XOaNO8ZgEY8wkY8whY8wuY8wwY8wM1/fJ67t2Mcb85jpmvzFmkTHmTNc2Y4x51BizyRiTboxZaYy5raD7VIjrnPiuxpiuHufyXOZ5nCtfuwKFMaalMcYE+jpK4FChVzwZCiwExgO1XMs217bbAAN0Bvq41iUArwEdga7AfuBrY0xsPte4FcgEzgPuBf4F3FSAXQUd8zIivNcCFwFtXHbmijGmFPAl8Itr307A/4Cs/2/v/kLvnuM4jj/eWBgu/CdFMxEtRbNcMLlT8udCcSNJuHDHooQU0myypFhJc+GChRphMf8u0FDb0riY/GxDam1is5m1t4vv98fpOL/zO2fm9/M73s/6dPp+/r1f30+n1/mc9+f7+522y8O4BXfgPDyK5RFxZdveb52GidPJRx1znYr5+Anvd/SZTNdBp72HV/FMmf0MJjOrVPmzaIzlqR51GwYYe5TGxC5pr1fg9a55Pu4a8zae7bgeagyOxl7c0KVjB1ZMoPM4JC6b4B5249Ku+mV4o986DROn17121B+Jz/CKv87RBtL1L70nzsJWLB/XU2VmlcrRF4PyeXdFRMzFQ5qd6omab4iH4PQ+82zouv4eJ00Su9+YuZiFteONmbmr328QZ+b2Nv2yOiLWYA1WZuYWzU75CLwVEZ1PKszC2CQ6h4nTk3bXvAKH4sZsnfaf6IqI+fh0GO0TcBvewcqDMFcxhZTRF4Oyq0fda/gOt7ev+7AR/VI3v3ddp8lTiP3GREfdwGTmzRGxDFfgajwSEddq0iVwFTZPouOA42Tm6gmGPICFuCgzO9d8/H4PRNcXOHeSPv04Fi/hS9TjoDOQMvqim72a3WRfIuJ4jXnckZnvtXUXmvr31CaN0S3AN62O2ZiHr/sNzMz1WI/FEfEmbtJ8aP2GMzLz3T7DB1qnPnH+ZvQRcR3uxuWZubWreeOAunrF34OvhhnToekwfKIx+Wsyc/eBzFNML2X0RTdjWNA+RbIT2yfotwPbcGtEbMFpWKLZ1U8ZmbkzIp7TmOg2/ID7NDvgnrv8iJijMfRVmm8iZ+J8PJ2Zv0TEUixt0ygfas4BLsb+zBz/6bYxXeuUmfsHjdND0zw8j3uxOSJOaZv2Zub2IXQdVDJzX0Q8iDVl8jOXMvqim6Uaw9moORSc06tTZu6PiOvxpCY1sAl34eUp0tnJIs1h5SqN6T6Bk7Fngv6/4mxNrvkE/IgXsLhtv7+tW6Qx5Z+xDo91zNFrncaGjNPJfMzWHK4u66j/QPNE06C6DjqZWemaGU79ZWwxckTE4fgWSzLz8enWUxTTTe3oixlPRFygOS9Yi2NwT/v64nTqKor/CmX0xahwJ87RnBGsw8IeB5pF8b+kUjdFURQjTv0LhKIoihGnjL4oimLEKaMviqIYccroi6IoRpwy+qIoihGnjL4oimLEKaMviqIYcf4AQS3o4as2p14AAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11a78a240>"
+       "<matplotlib.figure.Figure at 0x1a13b6aba8>"
       ]
      },
      "metadata": {},
@@ -1622,10 +1407,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Gaussian Naive Bayes\n",
     "\n",
@@ -1636,18 +1418,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 52,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAecAAAFhCAYAAABK5GKRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11bd53978>"
+       "<matplotlib.figure.Figure at 0x10d9e8278>"
       ]
      },
      "metadata": {},
@@ -1689,10 +1467,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Linear Regression\n",
     "\n",
@@ -1703,18 +1478,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 53,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAe0AAAFVCAYAAADCLbfjAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/9BBE/JV7MXFAAAAAElFTkSuQmCC\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11bb9fef0>"
+       "<matplotlib.figure.Figure at 0x10d9aa278>"
       ]
      },
      "metadata": {},
@@ -1782,9 +1553,7 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "source": [
     "## Random Forests"
@@ -1792,10 +1561,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper Code\n",
     "\n",
@@ -1804,12 +1570,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 54,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1908,28 +1670,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Decision Tree Example"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 55,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAk4AAAFFCAYAAAAadmKrAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11bbbfc18>"
+       "<matplotlib.figure.Figure at 0x101bf5b38>"
       ]
      },
      "metadata": {},
@@ -1977,28 +1732,29 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Decision Tree Levels"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 56,
+   "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/matplotlib/contour.py:967: UserWarning: The following kwargs were not used by contour: 'clim'\n",
+      "  s)\n"
+     ]
+    },
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAABHIAAADSCAYAAAAmGOcRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x115d78e10>"
+       "<matplotlib.figure.Figure at 0x10dcb37f0>"
       ]
      },
      "metadata": {},
@@ -2027,28 +1783,29 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Decision Tree Overfitting"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 57,
+   "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/matplotlib/contour.py:967: UserWarning: The following kwargs were not used by contour: 'clim'\n",
+      "  s)\n"
+     ]
+    },
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAABB8AAAFtCAYAAABP6sLFAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n4A+byZI8PwAAAABJRU5ErkJggg==\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x118fc00b8>"
+       "<matplotlib.figure.Figure at 0x10df199b0>"
       ]
      },
      "metadata": {},
@@ -2068,32 +1825,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Principal Component Analysis"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Principal Components Rotation"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 58,
+   "metadata": {},
    "outputs": [],
    "source": [
     "from sklearn.decomposition import PCA"
@@ -2101,12 +1848,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 59,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def draw_vector(v0, v1, ax=None):\n",
@@ -2119,18 +1862,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 60,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAABDYAAAGJCAYAAABxd7NLAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xt8U/X9P/BXLm0TeqEF0gKlLVIoICoTvICAFLBcpEAD\nrcKkqOPxdX73Vfm6+d2Gbk63KQ7nVJw4/bHNB46Bs6SUqyIXRREEQUAKUihyKUV6oWmaNmlu5/dH\nTGhLL0lzOTnJ6/mP5CQ5+ZxPYs/nvM/78/7IBEEQQEREREREREQkQXKxG0BERERERERE1F0MbBAR\nERERERGRZDGwQURERERERESSxcAGEREREREREUkWAxtEREREREREJFkMbBARERERERGRZDGwQUQB\nc/z4cSxZssTv+/3mm2/wu9/9zu/7JSIios6tWLECJSUl3Xrvrl278MILL3T7s//617/ij3/8Y7ff\nL1Uc9xB1TSl2A4gofN100014/fXX/b7f06dP48qVK37fLxEREXXuiSee6PZ7J0+ejMmTJ/uxNZGB\n4x6irjGwQUQBc+DAAfzhD3/ATTfdhNjYWJSVleH777/HoEGD8Oqrr0KtVmPEiBFYtGgRvvzyS5jN\nZjz55JPIyclBcXExPvroI/ztb38DAPfj5557Dm+88QaMRiOefvppvPjiiyIfJRERkbQdOHAAy5cv\nR0pKCi5evAi1Wo1ly5Zh0KBBWLp0KfR6PSoqKpCdnY2amhpkZWXh4Ycfxi233IJHHnkEe/fuRXV1\nNQoLC/Hggw8CAN5++21s2LABSqUSAwcOxLJly/Dxxx+7z+2FhYUYPHgwjh8/Dr1ej9mzZ+Pxxx8H\nAPztb3/Dzp07YbFYYDKZ8Mtf/hL33HNPh+232+1Yvnw5PvnkE0RFReFHP/oRnnvuOQDASy+9hH37\n9kGhUGDkyJFYunQpevTogcmTJ2PWrFn45JNPUF9fj8ceewyHDx9GaWkpoqKi8NZbb0Gj0WDy5MnI\nycnBV199BaPRiIceeggLFiwAALz//vv417/+BYVCgd69e+PZZ59FRkYGli5d2uG4p7y8HC+++CL0\nej0cDgcKCwsxd+5cHDhwAK+++irS0tJw+vRpWK1WPPvss0hPT2817vnNb36DpUuX4sKFC5DJZLjp\nppvw+9//PrA/ECIJ4FQUIgqKEydO4B//+Ae2bt2KqqoqfPjhhwCcg5GkpCTodDq8+uqrePrpp1FX\nV9fhfvr27YsnnngCo0ePZlCDiIjIT06ePInFixdj48aN0Gq1+L//+z/3c83Nzdi0aRN+8YtftHqP\nxWJBr169sHbtWrz++ut45ZVXYLFYsHPnTmzYsAEffPABNm3ahAEDBmDNmjXXfebly5fx/vvvQ6fT\nYevWrfj0009RWVmJ/fv3Y82aNSgpKcH//u//YsWKFZ22fc2aNThx4gQ2bdqEzZs3o6mpCVu3bsVb\nb72FqqoqbNq0CRs3bnQHQFq2v6SkBL/85S/x7LPP4qGHHkJJSQn69u2L4uJi9+vMZjPWr1+P1atX\nY8WKFTh9+jT279+Pf/zjH3jvvfewYcMG5Obm4mc/+5n7Pe2Ne+x2O5YsWYKnnnoK69evx3vvvYe/\n//3vOHbsGADnlJPFixejuLgY8+bNwxtvvHHduOfjjz9GU1MTiouLUVRUBAC4ePGiF980UXhiYIOI\ngmLChAlQKpVQKpXIyspCfX29+7mFCxcCAIYOHYqhQ4fiq6++EquZREREEWno0KEYNWoUAGDevHn4\n9ttv3edq1/b2TJkyBQAwYsQIWK1WmEwm7Nu3D9OnT0dcXBwA4Fe/+hV++tOfXvfe+++/H3K5HPHx\n8Zg+fTo+++wz9O/fHy+99BJKSkrwyiuvYO3atWhqauq07fv27cOcOXMQHR0NAPjLX/6C2bNnY8+e\nPViwYAHkcuclT2FhIfbs2eN+39SpUwEA6enp0Gg0yMrKAgCkpaVBr9e7X/fAAw8AAFJSUnD33Xfj\n888/x2effYYZM2YgMTERAKDValFVVYVLly4BaH/cc+7cOVy4cAFPP/008vLysHDhQjQ3N+PEiRMA\ngP79+2Po0KEAgBtvvLHVWMll9OjROHPmDAoLC/HOO+/gwQcfRFpaWqf9QxQJGNggoqBQqVTuf8tk\nMgiC4H6sUCjc/7bb7ZDL5ZDJZK3eb7VaA99IIiKiCKVUXpuhLggCBEFwn59jY2M7fF9MTEyrx4Ig\nQKlUtjqPNzQ0uC/4W2p5/nc4HFAoFDhx4gTmz5+PxsZGjB8/Hv/1X//VaszQUdtbfl5tbS2qq6vh\ncDhavc5ut8Nms7kfuwIhrn10pO04RaFQXLdv1zG49t/euMdutyMhIQHFxcXYsGEDNmzYgPfffx9z\n584F0Lov246VXAYMGIDt27fj0UcfRWNjIx588EFs3769w7YTRQoGNohIdBs2bAAAlJaW4rvvvsMd\nd9yBpKQklJWVwWKxwGazYdeuXe7XKxSKVgMTIiIi8s2JEydQVlYGwFk7YtSoUe6MC0+5LsTHjh2L\njz/+GI2NjQCAN954A+++++51r9+4cSMEQUB9fT0+/PBDTJo0CQcPHsTNN9+Mhx56CLfffjt27NjR\nbhChpbFjx2Lz5s2wWCxwOBx47rnnsGXLFkyYMAFr166FzWaDw+HAv//9b4wbN86rYwLgXgWmsrIS\nX3zxBe6++25MmDAB27Ztw9WrVwEA69evR1JSEjIyMjrczw033ICYmBhs3LgRgHMqTm5uLkpLSzv9\n/JbjnrVr1+LXv/41xo0bh1/84heYMGGC+3sjimQsHkpEojt8+DDef/99CIKA1157DfHx8Rg/fjzu\nuOMOTJ8+HcnJybjzzjtx6tQpAMCtt96K1157DY8//jjeeOMNkVtPREQkfRqNBq+++ioqKirQp0+f\nVrUoOtI2u9L1eOLEiTh79izmz58PmUyGIUOG4A9/+AM++uijVq9vbm5Gfn4+mpqa8MADD2DMmDEY\nMmQItm/fjpkzZyI6OhpjxoyBXq/vdDrK/PnzUVlZiXnz5gEA7rzzTixatAhWqxV/+tOfkJeXB7vd\njltuuQW//e1v2217ZyoqKjB37lxYLBb85je/wcCBAzFw4EA8+OCD7mKpSUlJePvttzvdT1RUFFau\nXIk//vGPWLVqFex2O5588knceuutOHDgQIfvaznuefnll3HgwAHce++9UKvVSE1NdbeBKJLJhK5y\nu4iIAmjYsGH48ssv0bNnT7GbQkREFJFcq5ht2rQpaJ9ZWFiIwsJCd52LUDV58mS88cYbGDFihNhN\nIaJOcCoKEYmqozmkREREFL68yZgQk1TaSRTpmLFBRERERERERJLFjA0iIiIiIiIikiwGNoiIiIiI\niIhIssJiVRSbzY66uo4rJVPXkpJ6sA99xD70D/aj79iHvmMf+k6jiRe7CT6rrm4I6P7D9XcWrscF\n8NikiscmTTw2aQrksXU2tgiLwIZSqRC7CZLHPvQd+9A/2I++Yx/6jn0YfhwOB37zm9/gu+++g1wu\nx/PPP4/BgweL2qZw/Z2F63EBPDap4rFJE49NmsQ6Nk5FISIiorC3a9cuyGQyrF27FkuWLMFf/vIX\nsZtEREREfhIWGRtEREREnbnnnnswefJkAMClS5fQs2dPkVtERERE/sLABhEREUUEuVyOX//619ix\nYwdWrFghdnOIiIjIT2SCIAhiN8IfAl3gK9xpNPHsQx+xD/2D/eg79qHv2Ie+C+XiobW1tSgoKMDW\nrVuhUqk6fJ3NZg/redBEREThghkbREREFPZKSkpw5coVPPLII4iJiYFcLodc3nmpsUBXrA/XAFq4\nHhfAY5Oir746gKgoASNH3il2UwIiXL83gMcmVYE8trBfFYWIiIioM1OnTsXSpUuxcOFC2Gw2PPPM\nM4iOjha7WUQUQAZDPXJzp8LhcODgwWPIyBgodpOIKEAY2CAiIqKwp1ar8dprr4ndDCIKolWr3obD\n4QAAvPHGq/jzn18XuUVEFChc7pWIiIiIiMKKwVCPv/3tr+7H69atweXLlSK2iIgCiYENIiIiIiIK\nK6tWvQ29Xu+upWOxWLBixV9EbhURBQoDG0REREREFDZaZmtERV2rpfPee+8ya4MoTDGwQURERERE\nYePIka+h1+tx113joVA4l2y+995ZsFgs2Lv3M5FbR0SBwOKhREREREQUNsaNm4AVK97C5Mk5uOOO\nkQCAF198GTk50zBrVp7IrSOiQGBgg4iIiIiIwoZCocD8+Q+02paQkIAHHlgkUouIKNA4FYWIiIiI\niIiIJIuBDSIiIiIiIiKSLAY2iIiIiIiIiEiyGNggIiIiIiIiIsliYIOIiIiIiIiIJIuBDSIiIiIi\nIiKSrKAv92qz2fD000/j0qVLsFqtePTRRzF58mT387t27cLKlSuhVCoxb948FBQUBLuJRERERERE\nRCQRQQ9sbNy4EUlJSVi+fDnq6+uRl5fnDmzYbDa89NJL0Ol0iImJwYIFCzBlyhT06tUr2M0kIiIi\nIiIiIgkI+lSUGTNmYMmSJQAAh8MBpfJabKW8vBwZGRmIi4tDVFQURo8ejYMHDwa7iUREREREREQk\nEUHP2FCr1QAAo9GIJUuW4Mknn3Q/ZzQaER8f734cGxuLhoaGYDeRiIiIiIiIiCQi6IENALh8+TIe\ne+wxLFy4EPfee697e1xcHIxGo/txY2MjEhISPNqnRhPf9YuoU+xD37EP/YP96Dv2oe/Yh0RERETS\nEPTARk1NDRYvXoxnn30WY8aMafVcZmYmzp8/D4PBAJVKhYMHD2Lx4sUe7be6mpkdvtBo4tmHPmIf\n+gf70XfsQ9+xD33HwBAREREFS9ADG2+//TYMBgNWrlyJN998EzKZDPfddx9MJhMKCgqwdOlS/OQn\nP4EgCCgoKEBycnKwm0hEREREREREEhH0wMYzzzyDZ555psPns7OzkZ2dHbwGEREREREREZFkBX1V\nFCIiIiIiIiIif2Fgg4iIiIiIiIgki4ENIiIiIiIiIpIsBjaIiIiIiIiISLIY2CAiIiIiIiIiyWJg\ng4iIiIiIiIgki4ENIiIiIiIiIpIsBjaIiIiIiIiISLIY2CAiIiIiIiIiyWJgg4iIiIiIiIgki4EN\nIiIiIiIiIpIsBjaIiIiIiIiISLIY2CAiIiIiIiIiyWJgg4iIiIiIiIgki4ENIiIiIiIiIpIsBjaI\niIiIiIiISLKUYjeAiIiIiIikx2az4+xZA8xmBVQqOzIzE6BQKMRuFhFFIGZsEBERERGR186eNcBk\n6g1BSITJ1Bvl5Qaxm0REEYqBDSIiIiIi8prZrOj0MRFRsDCwQUREREREXlOp7J0+JiIKFtbYICIi\nIiIij7SsqxEd7UB0dBWs1mh3jQ0pCFRtENYcIRIPAxtEREREROQRV10NAGhuBtTqWgwfLo2AhkvL\nYzCZgPLyWmRlJYXsfomoawxsEBERERGRR8KhrkagjiEc+iZYmN1C/sYaG0RERERE5JFwqKsRqGMI\nh74JFq6oQ/7GwAYREREREXkkMzMBanUtZDI91Opar+pq2Gx2lJXV4dgxA8rK6mC3i3Ph78sxiLHf\ncMTsFvI3TkUhIiIiIiKPKBSKbteNCJUaFL4cgxj7DUcqlR0mU+vHRL5gxgYREREREQUc79KTC7Nb\nyN+YsUFERERhz2az4emnn8alS5dgtVrx6KOPYvLkyWI3iyii8C49uTC7hfyNgQ0iIiIKexs3bkRS\nUhKWL1+O+vp65OXlMbBBFGSZmQkoL69ttRIGEZE/MLBBREREYW/GjBmYPn06AMDhcECp5BCIKNh4\nl14cXFqVIgHP6kRERBT21Go1AMBoNGLJkiV48sknRW4REUmV1AIFoVK0lSiQGNggIiKiiHD58mU8\n9thjWLhwIe69994uX5+U1ANKZWAvVjSa+IDuXyzhelwAj01qZDLnfzWaeMTFxfllnydPXoVKlQ6V\nyvm4ru4qhg9P9Mu+u6Or762iwgGVKtb9WC63Sea7lko7u4PH5l8MbBAREVHYq6mpweLFi/Hss89i\nzJgxHr2nrq4poG3SaOJRXd0Q0M8QQ7geF8BjkyJBcP63uroBJpPgl31WVpogCI3ux3q9CX36iNN3\nnnxvTU31MJmuXfap1fWorg79xTHD9TcJ8Nh82XdHRPtFHz16FIWFhddtf/fdd5Gbm4tFixZh0aJF\nOHfuXPAbR0RERGHl7bffhsFgwMqVK1FYWIhFixbBYrGI3SwikqC2q7mE+uouXFqVIoEoGRurVq1C\nSUkJYmNjr3uutLQUy5cvx4033ihCy4iIiCgcPfPMM3jmmWfEbgYRhQGpre7Coq0UCUTJ2MjIyMCb\nb77Z7nOlpaV4++238eMf/xjvvPNOkFtGRERERETUMVeg4JZbEpCVlRTShUN9ZbPZUVZWh2PHDCgr\nq4PdHtrZKRS5RAls5OTkdPgHYObMmXj++eexevVqHDp0CJ9++mmQW0dERERERESuFVUEIREmU2+U\nlxvEbhJRu0KueOiDDz7orlg8ceJEnDhxAhMnTuzyfeFcVTZY2Ie+Yx/6B/vRd+xD37EPiYgo0pnN\nik4fE4UKUQMbgtC6MrHRaERubi62bdsGlUqF/fv3Iz8/36N9hWtV2WAJ58q8wcI+9A/2o+/Yh75j\nH/qOgSEiIulTqewwmVo/JgpFogY2ZD8sLL1582aYTCYUFBTg5z//OQoLCxETE4OxY8fi7rvvFrOJ\nREREREREEUlqhVIpcokW2EhNTcW6desAALm5ue7ts2fPxuzZs8VqFhEREREREcG7FVVsNjvOnjW0\nCoKEc2FVCi0hV2ODiIiIiIjI33jhHViuQqMAYDIB5eW1XGaWgkaUVVGIiIiIiIiCiSt8BBYLjZKY\nGNggIiIiIqKwxwvvwGpbWJSFRimYGNggIiIiIqKwxwvvwMrMTIBaXQuZTA+1upaFRimoWGODiIiI\niIjCHlf4CCxvCo0S+RsDG0RERERE1KFwKbrJC2+i8MWpKERERERE1CEW3SSiUMeMDSIiIiIi6pCr\nyKbNZkdlpQEWixlAnWQzN4go/DBjg4iIiIiIOuQqsllZaYDZ3BtRUfHM3CCikMLABhERERERdci1\n2oXF0oSYGD0GDIgDwOVSiSh0cCoKEREREZGXwqWgpieuFd2sg8l0bSURLpdKRKGCGRtERERERF6K\nxIKarswNmUwPtbqWy6USUchgYIOIiIiIyEttp2FEwrQMhUKBQYMSoFLZYTYrUF5ugN3OrA0iEh8D\nG0REREREXmo7DSNSpmVEYqYKEYU+BjaIiIiIiLwUqdMyIjFThYhCH4uHEhERERF56VpBzciiUtlh\nMrV+TEQkNmZsEBERERGRRyI1U4WIQhszNoiIiIiIyCOeZKqE21K44XY8ROGIGRtEREREROQ34VZg\nNNyOhygcMbBBRERERER+E24FRsPteIjCEQMbRERERETkN+G2FG64HQ9ROGJgg4iIiIiI/CbcCoyG\n2/EQhSMWDyUiIiIiIr8Jt6Vww+14iMIRMzaIiIiIiIiISLKYsUFERERERBGHy7gShQ8GNoiIiIiI\nKOK4lnEFAJMJKC+vDbkpJwy+EHmGU1GIiIiIiCjiSGEZV1fwRRASYTL1Rnm5QewmEYUkBjaIiIiI\niCjiSGEZVykEX4hCAaeiEBERERGRZPhrekZmZgLKy2tb7SfUqFR2mEytHxPR9RjYICIiIiIiyfBX\nbQwpLOMqheALUShgYIOIiIiIiDrUWYaEGMUtI2l6hhSCL0ShgDU2iIiIiIioQ50VsBSjuKUUamMQ\nUXCJFtg4evQoCgsLr9u+a9cu5OfnY/78+fjggw9EaBkRERERkTTYbHaUldXh2DEDysrqYLf7/yK/\nswwJMbInMjMToFbXQibTQ62u5fQMIhJnKsqqVatQUlKC2NjYVtttNhteeukl6HQ6xMTEYMGCBZgy\nZQp69eolRjOJiIiIiEKav+pNdKazApZiFLfk9AwiakuUjI2MjAy8+eab120vLy9HRkYG4uLiEBUV\nhdGjR+PgwYMitJCIiIiISHxdZWQEI2OiswyJSMmeCEZmDBF1nygZGzk5Obh06dJ1241GI+Lj492P\nY2Nj0dDQEMymEREREREFnKdFN7vKyAhGxkRnGRKRkj0RjMwYIuq+kFoVJS4uDkaj0f24sbERCQme\nRX01mviuX0SdYh/6jn3oH+xH37EPfcc+JKJA8vRCuauMDC4HGhyRtBILkRSJGtgQBKHV48zMTJw/\nfx4GgwEqlQoHDx7E4sWLPdpXdTUzO3yh0cSzD33EPvQP9qPv2Ie+Yx/6joEhCjYxlh31hacXyl1l\nZERKxoTYxKglQkSeEzWwIZPJAACbN2+GyWRCQUEBli5dip/85CcQBAEFBQVITk4Ws4lEREREJAFS\nmyrg6YUyMzJCA78HotAmWmAjNTUV69atAwDk5ua6t2dnZyM7O1ukVhERERGRFEltqoCnF8rMyAgN\nwfgepJZ1RBRKQqrGBhERERFRd0htqgADFtSW1LKOiEKJKMu9EhERRTouHSiOo0ePorCwUOxmUABE\nyrKjFL6klnVEFEqYsUFERCQC3pkLvlWrVqGkpASxsbFiN4UCgBkQJHVSyzoiCiXM2CAiIhIB78wF\nX0ZGBt58802xm0EkaaGQbRboNvi6/+6+n1lHRN3HwAYREZEI2t6J4525wMvJyWEhPqIudHVR7so2\nE4REmEy9UV5uCHobA90GX/ff3fe7so5uuSUBWVlJ/HtF5AVORSEiIhIBlw4MfUlJPaBUBvbCQqOJ\nD+j+xRKuxwWE/7GdPHkVKlU6VCrntrq6qxg+PNH9mooKB1Sqa9O55HJb0PukszbYbHacPl3v/tsq\nkzlfo9HEIy4uzuf9B+P93gr332S44rH5FwMbREREImA9APEIguDR6+rqmgLaDo0mHtXVDQH9DDGE\n63EB0jo2b5cOdR1bZaUJgtDo3q7Xm9Cnz7Vjbmqqh8l07RJCra5HdXVwk8A7a0NZWZ27fhGghMPh\n/P+9uroBJpNn/+/7eozB7CMp/Sa9xWOTpkAeW2cBEwY2iIiIQsx//rMW+/btxYABaUhPz0B6+kBk\nZGQgOTkFcjlnkfpK5rqFSxTGuluguKsClp1lm3kbTOmuztpgNitgtztQUWGExaKAw+Hf/fvz/cHq\nL6JIwMAGERFRiHnttT/jzJnT122Xy+X417/+g3vumSpCq8JDamoq1q1bJ3YziAKuuwWKu7oo7yzb\nLFirPXXWBpXKjm+/NaK5ObHd533dvz/fz9WxiPyHt32IiIhCzD//uQY//nEhbrhhUKvsAofDgebm\nZhFbRkRS0d0Cxb4UsAyF1Z4yMxMgl9dBJtNDpaoN6QytUOgvonDBjA0iIqIQYLFYsHv3ThQXf4AP\nP9yKpiZnfQfXoFwmk+GVV1Zg5sxZYjaTiCRCjALFXU1jCQZnYCYOJlPoF2QOhf4iChcMbBAREYnE\nbrfjiy8+R3FxETZvLoFer3c/N3r07UhJScHWrZshk8mwYsVbuP/+H4vYWiKSkmAVKG5ZJyIqyo6Y\nmGpYLFGirvbUMqgjk3lWMFQM3gSfWI+DqHMMbBAREQWRIAg4fPgrFBcXoaSkGFeufO9+bvjwEZg7\nNx95efNQW1uD6dMnAwD+8pc3GNQgChPhdoHask6ExQKo1bW45RZxsyVaBnVCeSqKJ8En1++lrKwJ\nghCH1NR4mEwK1uMgaoOBDSIioiD49tuT0Ok+QHFxEc6fP+fenpExEHPn5kOrLcCwYcPd2xUKBcaM\nuQsLFizEggULRWgxEQVCuBWMZJ2IwHL9XsxmFQQhHpcu1SI9PYn9TNQGAxtEREQBcv78OWzYsB46\nXRFOnix1b09OTkFe3lxotfkYNeq2du8oDhiQho0bPwxmc4koCMItEOBJnYhwy1IJJtfvIzrajuZm\noLnZ+TgQ9Tj4PZGUMbBBRETkR1euXMHGjTrodEU4dOige3tiYiJyc+dAq83HXXeN52CRKEKFW8FI\nT+pEhFuWSjC5fi8DBsShokIPubwOarU1IPVL+D2RlDGwQUREARfud4H0+jps2bIJOl0R9u7dA4fD\nAQDo0aMHpk+/F1ptASZNmoLo6GiRW0pEYhNjtZJA8qRORLhlqQRTy9/LsGF2ZGb2D9j5k98TSRkD\nG0REFHDheBeosbER27dvQ3FxEXbu/BhWqxUAEBUVhalTp0OrzcfUqTMQGxsrckuJKJQEa7WSUBJu\nWSrBFMzfC78nkjIGNoiIKODC5S6QxWLBJ5/shE5XhA8/3IqmpkYAzqr7EyZMxNy5BZg5cxYSEyPr\nooWIqDNSzlIJ94zDlqT8PRExsEFERAEn5btAdrsd+/btRXFxETZt2gC9Xu9+bvTo26DV5mPOnLlI\nSekrYiuJiEKXlLNUwjHjsCNS/p6IGNggIqKAk9pdIEEQcPjwVyguLsKGDTpcufK9+7nhw2+EVpuP\nvLx5GDjwBhFbSURiiqQ7+ZGsvYzDYH33/I0ReY6BDSIiCjip3AX69tuTKC7+ABs3FqO8vNy9PT19\nIObOzYdWm4/hw28UsYVEFCoi6U5+JGsv4zBY3z1/Y0SeY2CDiIgi2vnz57Bhw3rodEU4ebLUvT05\nOQV5eXOh1eZj1KjbIJPJRGwlEYWacKkdRJ1rL+OwtLSx1WsC9d3zN0bkOQY2iIgo4lRVVWHjRh3W\nr/8Ahw4ddG/v2TMRs2bNwcMPL8KNN466LuWXacFE5CLl2kHkOUG4fluwvnv+xog8x8AGERFFhPp6\nPbZs2QSdrgiff/4pHA4HAEClUmPs2KmYNm0W5s/PRY8ePaDRxKO6uuG6fTAtmIhcpFY7yFu+BHLD\nKQjc3t/9YH33rs9pbJShuloPjaYnysrqJN2fRIHCwAYREXlESgNVV1v1egsOHfoIX3yxFbt374DF\nYgEAREVFISdnGsaMmYHRo++HWh0LAKioqEVWVo8O98u0YCJykUrtoO7yJZB79qwBRmMSKiqMsFii\ncO7cRUyZkhay54zOtPd3P1jfvetzysrqIJcPAsCgOlFHGNggIiKPSCVbwWKxYM2ajfjoow/xxRdb\nYDY750IBuEz1AAAgAElEQVTLZDJMmDARWm0+Zs6chaSkXjh2zABBiHW/t6tABdOCiShS+BLINZsV\nqKgwork5EQBgMNhRXm5odc4QK1ju7eeGwt99BtWJusbABhEReSSUB1Z2ux379u1FcXERNm8uQV1d\nnfu5YcNux+TJM/Hf//1jpKT0bfU+bwes4Z56HioEQUBjYyPi4uJaba+uroZGoxGpVUSRxZcLepXK\nDoslyv04JsZ+3TlDrGC5t58bCn/3QyG4QhTqGNggIpKoQN/tart/udyKs2cNsFgUiI62IyvL6rfP\n6g5BEHDkyGHodB+gpKQY339/2f3coEFDMXHifEyalI9+/W6AWl2LlJTrB67eDljDPfU8FOzfvx9P\nPfUULBYLhg8fjuXLlyMlJQUA8Mgjj6C4uFjkFhJFBl8u6DMzE3Du3EUYDHbExNiRmpoAlUrf6jVi\nBcu9/dxQ+LsfCsEVolDHwAYRkUQF+m5X2/1fvnwaMlkMAEAms0Nor1R8EJw69S2Kiz+ATleEc+e+\nc29PT8+AVpsPrTYfQ4cOQ3m5KyhT2+EgMBQGrNTa8uXL8d577yEjIwOrVq3CwoULsWbNGiQnJ4v2\nmyOKRN7+fWwbDM/O7o9z5xp/eKy/7u+wWFkIwf5cf9yE4LmKqGsMbBARSVSg73a13V9jYw8MHnxt\nYGW16tu+JWAuXDiPDRvWQ6crwokTx93bNZpk5OXNhVabj9Gjb4dMJnM/x0GgNDkcDtxwww0AnBka\n0dHRWLx4MdauXdvq+yUicbW9YLfb7bBYkgE4g+HnzoXmFI9gf65U6lMRSR0DG0REEhXou05t9x8f\n3+z+t81mx5UrtbhwoQGAA5mZamRlJfl1KkxVVRU2btRBpyvCV18dcG/v2TMRubmzodXmY9y4CZKs\nsk8d69OnD9asWYPZs2cjPj4eDz30EKqqqvDwww+jvr5e7OYR0Q/aXrBfvHgeaWnXng+1KR6lpQ1I\nSrIiMzMBgwYl4PRpPcrKzCgrMwbkHOYSyvWpiMIJAxtERBJks9nhcDhw8eJFuAILmZn+HSC2vavl\nTCt2Pq6tvQqrtQ8sFudnnjlTC4XCWfHel7Tb+no9tmzZBJ2uCJ9//ikcDgcAoEePHpg2bQa02gJM\nmjQFMTExfj1WCh3Lli1z19W45557AAC//OUv8e6772LlypUit46IXK6/QJe3eiR2gUvXuchuF354\nHAeTqSfKy2sBAKdPx6C52Vm/p+U5zN9Y+JMoOIIe2BAEAc899xxOnTqF6OhovPDCC0hrEd599913\nUVRUhF69egEAfv/732PgwIHBbiYRUUg7e9aA5maN++6YQlHr9ztN7d1Ny8qKdv+7rOzaKaS5WQGz\nWeZumzdpt01NTfj44w+h0xVh587tsFgsAICoqCjcc89UzJ1bgKlTZ1y3QgaFJ41Gg5dffvm67Q89\n9BAeeuih4DeIiNrV9oJ98GAV5PLQKXDZ8lwEAJWVDcjK6gmzWQG73YELF0ywWJSIinIgJSVwmRRi\nTbkRazldKWEfhZegBzZ27NgBi8WCdevW4ejRo1i2bFmrOzClpaVYvnw5brzxxmA3jYhIMsRObVWp\n7IiOlqP5h9kpMTF2qFQOj9tmtVrxySc7odMV4cMPt6Kx0QgAkMlkGD/+bmi1+cjNnY2kpF6BPRAi\nIuqW6y/YE0PqorDtuae52flYpbLj3Ll6OBx9IQjxsFiAurpyqFTxne6vuxfBYhX+ZG2PrrGPwkvQ\nAxuHDh3ChAkTAAAjR47E8ePHWz1fWlqKt99+G9XV1cjOzsYjjzwS7CYSEYU8sVNbMzMT4HDocebM\nebSdCtNR2xwOB/bt2wudrgibN29AXV2d+zWjRo2GVpuPOXPmom/ffsE8FCKiiGez2XHy5FVUVpo8\nvmgP9ZU6XOciV9FhlaoOanU0MjMT0NgINDWZcPFiPQAB/fqhy0wKqV0Ei30DRArYR+El6IENo9GI\n+PhrEVGlUgmHwwG53Dkvb+bMmXjggQcQFxeH//mf/8Gnn36KiRMnBruZRER+58+Ux0CntnbVVoVC\ngWHDemPYsM7bFhNjQ0NDOX77Wx1KSnT4/vvL7tcNGzYcWm0+8vLm4YYbBvm1/SR9e/fuxbhx41pt\n2759O6ZOnSpSi4jC19mzBqhU6RCERklctHvCdS4CnDU2pk7th4SEngCA2Fjghht644cFmKBWdz2d\nU2oXwWLfAJEC9lF4CXpgIy4uDo2Nje7HLYMaAPDggw+651FPnDgRJ06c8CiwodF0nj5GXWMf+o59\n6B/h2o8nT16FSpUOlcr5uK7uKoYPT+z2/vr27fi9vvahr22tq7uMtWvXYu3atThz5ox7e2pqOqZO\nzcecOVrk5o4NqbTltsL1dxjqtm7dCovFghUrVuCJJ55wb7darXjnnXcY2CAKAGcQu/VjqXNllMjl\nzowNufzaMXXn5kAwLoKldAMkHLCPwkvQAxujRo3C7t27MX36dBw5cgRZWVnu54xGI3Jzc7Ft2zao\nVCrs378f+fn5Hu23urohUE2OCBpNPPvQR+xD/wjnfqysNEEQrgV29XoT+vTx/Fg9HfD4ow+709aL\nFy+guHg9iouLUFr6TYv2JGPOHC1uu20aBg3KcacF799/KWTvCIbz7zBYuhsYMhqN+Prrr9HY2Igv\nv/zSvV2hUODJJ5/0V/OIqIW2F+mhftHuK0+n0bRsc3S0A9HRVbBaowN2EezP6S6hPlUoFLCPwkvQ\nAxs5OTnYu3cv5s+fD8C5rNvmzZthMplQUFCAn//85ygsLERMTAzGjh2Lu+++O9hNJCIKCF/v9gRz\nfq+nba2qqsKmTcXQ6Ypw8OC1i9CEhJ7IzZ0NrTYf48ZNgFKpxLFjBgiCzP2acLgjSP5333334b77\n7sO+ffswduxYsZtDFBEyMxNQV3cVer1JEhft3eVtcKVlm5ubnVNWhg8P3F397kx3sdnsKCur80vA\nKJSCT0TeCnpgQyaT4fnnn2+17QbXBDcAs2fPxuzZs4PdLCKigPM15TGY83s7a2t9vR5bt26GTvcB\nPvvsUzgcztVQYmJUGD8+BwsXzsc990xFTExMq31yLit5o2fPnnjiiSdQX18PQRDc21evXi1iq4ik\nx5OLVYVCgeHDE73KIvRWKNSo8Da4YjYrYLPZUVlpQHOzAiqVMaAX+905T54+Xe+3gFEoBJ+Iuivo\ngQ0iokjla8qjpwMef9y9advWpqYmfPzxh9DpirBz53ZYLJYfXqfEXXdlY+LEhRg79l6o1XFQq2uv\nC2oAnMtK3vnVr36F+++/H0OGDHFPXyIi74XKxaq/gtu+ZBV4G1xRqew4f94As9nZfw4HUF5uCFj/\ndec86c+AUSgEn4i6i4ENIiKJ8HTA46+7N1arFZ9+ugs6XRG2bduCxkYjAGfm3ciRE3D33fMwePBk\nXL1qR1paCqKjewDoeCDEuazkDZVKhYULF4rdDCLJC5WLVX8Ft30J1HgbXMnMTEBZ2feQyaIRHW3H\ngAFxMJsN3Wq3J7pznnQeg7LN4+5hZiVJGQMbREQS4emAx5dBrMPhwP79X0CnK8LmzRtw9epV93O3\n3joKWm0+srJy0Lv3cFy4UAezuTccjgo0NyeiokKPjIwEDoTIL8aPH4/33nsP48ePb5UB1L9/fxFb\nRSQ9oXKx6q/gti/nOG+DK84294DJFOveFmrnuKysnrh69ZJfsiFb9k9UlBV2u4Bjxwyst0GSwMAG\nEVGI8zbt1tu7N4Ig4OjRr6HTFaGkRIfLlyvdzw0dOgxabT7y8uZh0KBMAEBZWR1MJqC52dmGtDQ1\nFIpaWCxNUKutnGJCflFSUgIA+Oc//+neJpPJsHPnTrGaRCRJ/p4GKHaBSV8CNd0JroT6NEp/ZkO2\n3JfzXC/+FCYiTzGwQUQU4rxNu/X07k1Z2SnodB9gw4b1OHu23L09LS0dc+bMxW23TUdq6gio1Q5k\nZFzbh2uQp1IZ4XAAAwb0hEIhh1rt4KCH/GbXrl1iN4EoLPh7GqDYNTuCHWiI1GmUXWXGeBrgEjsQ\nRpGDgQ0iohDTdhDQ1CRDy9qJHaXdut7Xo4dzlZIRI2KvGzxcvHgBxcXrUVxchNLSb9zbNZpkzJmj\nhVabj9tuuwOnT+s7HLi6BnnOwaUBZrMhJO9ikbTV19fj5ZdfxoULF/D6669j+fLlWLp0KRIS+Dsj\nEpPYNTtc5yDXOa+0tJEXzAHQVWaMpwEusQNhFDkY2CAiCjFtBwFVVWeRktLL/XxHabeu96lUsTCZ\nlO7BQ3V1NTZuLEZxcREOHNjvfn1CQk/MnDkLWm0+xowZhwsXmmA2K3D6tB6NjYBcfm3f7Q1cI/Uu\nFgXHb3/7W4wbNw7Hjh1DbGwskpOT8dRTT+Gdd94Ru2lEES1Uana0PVeeOlUFpVLhVWZAV9kEkZxt\n0FVmjKcBLrEDYRQ5GNggorATrIGIJ5/Tnba0PelrND2hVneddtvyfY2N9di+fT0OHtyMzz77FHa7\nc+CpVqsxdeoMaLX5mDIlx12Use1c2urqs0hJ6e3eX6gVS6PwV1FRgfvvvx9r165FdHQ0nnzyScye\nPVvsZhFFvFCpOdH2XHn2rAlpaRkAPM8M6CqbIJKzDbq6eeFpgEvMQFgkB6YiEQMbRBR2gjUQ8eRz\nutOWtoOA2Fh41H6ZrBGffLILe/cW4/PPt8JqbQYAKJVK5ORMg1abj+nTZyIuLu6697YdICYnJ3oU\nTCEKFIVCgYaGBsh+mId17tw5yFumERGRKEIlW6/tuRJo/ffBk8yArrIJmG3QMVeAy2gEamrqkZyc\niLKyuuuCB2IGwiI5MBWJGNggorATrIGIJ5/TnbZ4MwiwWq3Ys2c31q//ANu2bUFjoxGAc/WIu+4a\nj7lzC5CbOxu9evXucB/A9QPEHj0EnvxJVE888QQKCwtx+fJl/OxnP8ORI0fw4osvit0sIvJSoO6a\ntz1XDh6sQnPztec9yQzoKpsgVKbdhJqW32lNzVX06TMQMpm83eCBmIEwBqYiCwMbRBR2gjUQafk5\nNpsdtbVX3dtdA7futKWrQYDD4cCXX+6DTleETZuKcfXqVfdzt946CoWFCzFlyr3o16+/x8cSKqnF\nRC4TJkzAiBEjcOzYMdjtdvz+979Hnz59xG4WEXkpUHfN254r7Xa71+exrs59oXJuDLUpFS2/U4NB\nDrPZ6F49LZSCBwxMRRYGNogo7ARrINLyc2prnXcsBKH1HQt/tUUQBBw7dgQ6XRFKSnSorLzkfi4r\nayi02nxotfkYNCgTGk08qqsbvNq/QqHAoEEJ7oFTeblB9IETRTaDwYBt27ZBr9dDEAScPHkSAPDY\nY4+J3DIi8kaw7pp3JzOgq/eEyrSbUJtS0fI7jImxo7k52v04lIIHoRKYouBgYIOIrhNqdwa8Fayl\n4NoOeATh2vxe10m/O4Mim82OsrI6nD1rwuXL53D69EfYs2cLzp4td78mLS0deXnzoNXmY8SIm9x1\nCHwRagMnimxLlixBfHw8hgwZ4pffN5EUSf18DIhfPFIQBADAmTN63Hyz2uf+E+M7CbUpFS2/09TU\nBNTUnIdM1ivkggehEpii4GBgg4iuI5UL3K4GF8E8Dn8O3L744iTef38L9u3bhIqKY+7tffpoMGeO\nFlptAW6//Y7rLvZc/VFR4UBTU73Xg61QGzhRZKupqcE///lPsZtBJCqpnI8709Vd80AuuXr2rAGC\n4DxXms29UF5uaHXjo7v7DPZ3EmpTKlp+p3FxdowcmSa5gBuFny4DG8eOHcMtt9wSjLYQUYgQ4wK3\n5UW5wXAVcrkMFksUlEqL+99tBx9dDS6CeRy+pjvW1NRg48ZiFBcX4csv97m3q9U98aMfzUBe3mws\nWJCDCxeaYDYrcPq0vsNAjkoVC5NJ6fVgK9QGTi7hcMeSvDd8+HB8++23GDZsmNhNIRJNOAScu7pr\nHsglVzvqv0DsM5BCbUoFMyEoFHUZ2Pjzn/+Muro6zJkzB3PmzIFGowlGu4hIRP6+wPXkwrTlRXl5\neQMEQYGMjASUl9e5/9128NHV4CJYF+rdvfBuaDBgy5ZN0OmK8Nlnn8Bud7YvOjoGt9ySg1GjFuLG\nG6ciLs6MYcOsuHChKaCBnEAPnLrbT+Fwx5K8d/r0aWi1WvTu3RsxMTEQBAEymQw7d+7s1v4EQcBz\nzz2HU6dOITo6Gi+88ALS0tL83Goi/wrVgLM/+bLkalfnlfZWOXHtw253oKLCCItFAZWqyeNzkhjf\nCQMJ0vPNN8eQnp6Onj0TxW5KxOgysLF69WpcunQJJSUlWLx4Mfr16wetVospU6YgKioqGG0koiDz\n9wWuJxemLQcqzc0KAIrr/t32dV0NLoJ1h8N1fHa7A99+a0RZWSWysuLaHSSZTCbs2PERdLoi7Njx\nEZp/WJtOoVDijjumYdKkAmRn34EePeJQXm4CcAWDB6uQmZmI0tLGVvvydyAn0AOn7gYowuGOJXnv\nr3/9q1/3t2PHDlgsFqxbtw5Hjx7FsmXLsHLlSr9+BpG/hdqd+kDwZcnVrs4rmZkJkMmcNTaqqs5B\npeqPsrI6REXZce6cEc3NzotOQbC4p6l0pb3vhJmF1NKhQwcxY8YUxMcn4JFH/hs//enPkJjIwFSg\neVRjIzU1FXl5eVAqlVi3bh1Wr16NV199FU899RRycnIC3UYiCjJ/X+B6cmHacuASE2PHD7W+Wv3b\n9TqXrgZ8nhxHR4MRbwYpruOpqHAOkmQywGRKcA+wrFYr9uzZDZ2uCNu2bYHR6FyxRCaT4a67xuOO\nO3Ixfvx89OzZ54ftegwfnoDhwzvuo7Z90bI/5HIb1Or6kBsAdzdAEQl3LOl6/fv3x9q1a7F//37Y\nbDaMGTMGCxcu7Pb+Dh06hAkTJgAARo4ciePHj/urqUQBEy536js7p/qy5GpX5xWFQuGuR5WcPBAy\nWRxMJiAmphpyeR1kMuc4IzU1AWazZ6uJtfedlJXVMbNQBKEaUBo6dBgmTZqC3bt34pVX/oR33nmL\nAY4g6DKw8cEHH6CkpATV1dXIy8vDv//9b/Tt2xdXrlyBVqtlYIOIuuTJhWnLi/LBg62QyWywWPSt\n/t12QNN29ZOjRw2oqalHcnIievQQPDrBdXS3x5vsAtfxWSzOz4qJscPhcODgwa+watVWbNq0AbW1\nte7X/+hHt0KrLUBe3lz069e/1YCoo/5p2UddBXKcy73K292HmLoboIiEO5Z0veXLl+P8+fOYN28e\nBEGATqdDRUUFnn766W7tz2g0Ij4+3v1YqVTC4XBALg+9/1eIwonNZseuXRdhMKQgOtqOAQOc00xd\n51Rfllz15LxisTgzIx988JYWRbcFyGRCq9XMZDIHFIru/T2w2QQALQt6C1AqA7uak93ugCDIIJfL\nEK5/xuRyGRwOocPnnX3gn+8wEBITk9DY2IiGBgNeeeVPePXVl/Hmm/8P8+YViN20sNRlYOPgwYN4\n/PHHceedd7banpKSgt/97ncBaxgRic9fkXBPLkx9uSh3BSEuXaqD2TwYZrP+h/oc7QcjWh7Xd98Z\nIQgKNDfLodfXo1cv50DEYHCgstIAi0WB6Gg70tNlHfaJ6/hiYhpx/vwhlJZuw549xaiurnB/5pAh\nWZg7twBa7TwMGjTY6/5p2UdS1d0AhdSPm7pn79692LBhgzvwkJ2djVmzZnV7f3FxcWhsvDady5Og\nRlJSDyiVgb37p9HEd/0iCQrX4wJ4bN6w2ez48MPz+O67XoiKUqNv3x5oaDAiObmnXz6rV68eKCur\nd59XsrJSrxunxMbGor6+HnV1VT5/HpEvHA4H6uquuH/7/FviX10GNpYvX97hc9OmTfNrY4gotPir\naGOgL0xdqafOehzXMic6murQ8ri+/74BFosSgmCD1ToQwEWYTL3xzTfHEBf3ox/2C1RVnQGQ2G6f\nyOU12LDhAxQXF6G8/Iz7c1JTB0CrzYdWm4+bbroZdrsDZ88acOyYoVWgqG3mSWlpY0ilVLanO0Ev\nBijIG3a7HTabDdHR0e7Hvvz/MGrUKOzevRvTp0/HkSNHkJWV1eV76uqauv15nnAGcj1Lf5eScD0u\nQPxjC2TqfWfH1t3PLSurw8WLajQ3O2A0RsFovIr+/QX062f2W2Zhnz6umn9yXL16/f+zJ09+h+bm\nehw9Wo3mZgViYuwYODDer+dXu92Ozz6rhNGoQVSUHf36xSI2Vo/MzMAUjvz448swmwcAAOLj1bBa\nTyMnp19APktMvXvHobbW2OHz5eV6mM293I9VqqsB63Nv2O12vPHGq/j3v9+D6YeUouzsyfjf//0F\n7rprAqqrG0T/WxJIgTy2zgImHtXYIKLIJJWija5U1JgYO8xmIDra7t7ekmtg9s03ZkRH1yE1NQFJ\nST1x5UodbDYloqPrkZQUBwCIjU2CSlXrHgRpND0BXOuDqqoKfPJJEXbvXoczZ67N1e/Tpw9mz9ZC\nqy3A7bff0eqOcCCXtAs2KbWVpGnWrFlYtGgRZs6cCQDYsmULcnNzu72/nJwc7N27F/PnzwcALFu2\nzC/tJAomsf72+lL8OSbGjpSURFy5UgubzYKEBCMyM4O3IpFSqUS/fgMRG9u709f5GjQaPjwegnDt\nolom64GUlMBMnUxMtMJkcgYyEhLUsFrrkJLSNyCfJSaNJh5KZccXyH36aFBe3vI7GxISN4T27duL\nv//9HQDAtGkz8NRTv8bIkbeK3Krwx8AGEXVIKkUbXVMcBgwAqqvPIDk5EWp17XVTHVwDs6goA8zm\nRFy6VAuVSoGBA53BDLM5ATExegDOQUNKyrVBm1pdi5qaGmzb9m9s374V33zzhfu5+PgEzJw5C1pt\nPiZMmAilsv0/rR0FitoLuAAylJU1hVxBLBepBL1Iuh599FEMHz4c+/fvdz/Ozs7u9v5kMhmef/55\nP7WOSBxi/e31pfhzamoiLl3So39/BRISjJgyJc0v5zN/Z6/4GjQK5pgpM1ONM2ecN19UKhPS09UB\n+6xQFqqZoHfcMQavv74SN944ggGNIGJgg4g6JJWijQqFAoMGJeDsWQMUil4dDnBcA7EBA+JQUaGH\nxdKEESOiIQgCzGYFqqvPoFevBFy5cha9e8fjypWz6NFDjkOHtuOLL7Zgz55PYLc7ByrR0TEYN+4e\nLFw4Hzk506BSqbpsZ0eDHtdgSi6vw3ffyXD+/GVERQno21cNQUgMyYwIqQS9SNqsVissFguUSiWX\nmCeCeH97fSv+rEdGhgIqlRWZmf4JagD+z17xNWgUzDFTVlYSFAoDzGYZ+vcHkpJCZ3xAznHpggXd\nX8WLuoeBDSLqUKhGwoHr79TY7XZYLMkAgIYGO3buPI++fVsHOVwDM4VCjoyMBKjV1jbHl4STJ2tx\n/nwcPv10Fw4f1uGbb3a4K6orlUpMmZIDrTYf996bi7g47wojdTTocQ2eZDIHADUsFhWA1svchlpG\nhFSCXiRdL730Eo4cOYKZM2fC4XDg9ddfx/Hjx/HTn/5U7KYRiSbYf3td59qmJhmqqs5Co+kJlcoB\nu124rl5Ue1reeDCbFSgvN/gtA9Hf2Su+Bo2COWZq+VnhXKuByBsMbBCRJLW9U3Px4nmk/TBlt7LS\ngObmFKSkxLa6i9PZgNBms2HPnt1YsWI1Dh/e5V7PXiaTYezYcdBq8zFrVh569+58jm5nOhr0uAZT\nNlsU+vWLQ0yMDQBgsbR+TSgJ5aAXhYfdu3djy5Yt7qld8+fPR15eHgMbFNGC/bfXda6VyYCUlF5Q\nq2sByL3KlGh7vj51qgpKpcLnKST+zl4JVNAokAVfiegaBjaISFLa1qPo2zcOly+bcPGiGQ6HAQMG\nxKG5WeEuIApcu4vTdkDocDiwf/8+FBd/gE2bNqCmpsb9XHr6rRg9+j6MG3cHFi26PaDH5BpMqVRG\nOBzOqTIAUFNzDjKZgxkRFJF69+4Ng8GAXr2cFe+tVivTrYmCzJOsiK4yJVo+b7PZ8eWXVejV6wZE\nR9sxYEACysvrugzWdLbUur8CEYEKGrHYNlFwMLBBFGbC/c5A2wKghw+fR69eGUhNtUAms6Oy8hIS\nEqzo02eg+z0t7+IIgoDjx4+hqOg/WL9+PaqqKt3PDRmShfHj78XgwVokJQ1BTIwdgwdb222HP/vZ\nNZhyDtIMMJud6b0jR/pvLjKR1PTs2RNz5szB5MmToVQqsWfPHvTu3RtLly4FwFVNiIKho6wIbzIl\nWu7DmVHZG4IQj+ZmoKJCj4EDuz7PdRQckEKAgMW2iYKDgQ2iMBPudwbaFgBtampG//61SE1NgkKh\ngEwmw4gRsSgvr2sVdCgvPw2drgjFxUU4c+a0e3/JyWnIzs7HjBk5uPfecXA4HD8EFxxQqRzIzGy/\n7zzt5/YCIIKAdoMigZyL3Fl7GDyhUDR16lRMnTrV/fimm24SsTVEkamjrAhvMiVa7kMmMyItrQes\nP9wzsFicRUW7IuXggNjFtnnep0jBwAZRmAm1k7+/T6htC4CqVDVISUmCzWbHhQt1kMmM7s+5cuV7\nFBevx89+VoRjx46499GnTx/cdddMTJq0EDfeeCfkcjlkMj1kMpnHqaie9nN7ARDnv9sPigQ6MBXu\ngS8KH1qtFkajEQaDodX2/v37i9QiosjT0TnRm/NGy30olRaUlQm4cuUCBEHAkCFmZGYO7HIfYgcH\nfNFRcChYAQee9ylSMLBBFGZC7eTf1Qm17Ym9V68ene6v7QAhO7s/zp2rRVmZEYKQhLg4Ff7zn2Ls\n2bMWR48egPDD0iKxsfEYN246pk2bhfvum4Hz55vc7QK87ydP+9nb+cmBDkyFWuCLqCN/+tOf8J//\n/AeJiYkAnNPIZDIZdu7cKXLLiKi75HIZ5PJo9O2rRnS0HQMHqjy6mJfySlwdBYeCFXDgeZ8iBQMb\nRGEm1E7+XZ1Q257Yy8rq0adPVId3MtobIPTv34xNmz7Grl1bcfjwLtjtzlVFVCoVcnKmY8yY6bj5\n5ilJs/QAACAASURBVLmoqrLBYlFg167LSEtT4+LF8wDkGDxYhczMRK+Oy9N+9nZ+cqADU6EW+CLq\nyM6dO7Fnzx7ExsaK3RTqgrcBaopcFksUMjISWjzWe/S+cFyJK1gBB573KVIEPbAhCAKee+45nDp1\nCtHR0XjhhReQ5lqjEcCuXbuwcuVKKJVKzJs3DwUFBcFuIpGkBevk72kKZVcn1I5O7J3dybDZ7Dh5\nsgp79nyKTz/dgP37d8FsNgMA5HIFbr99KqZNm4GHHy5AfHwCvv5ajwMH9Ghs7A2l0g4gBjabCunp\n/X54T63X6Z+e9rO385MDHZgKtcAXUUeGDh0Ki8XCwIYEdBSgJmorKsqK06cNsFicq5dlZXVdXyNc\nBSvgwPM+RYqgBzZ27NgBi8WCdevW4ejRo1i2bBlWrlwJALDZbHjppZeg0+kQExODBQsWYMqUKe6l\n3ogodHiaQtnVCbX9E7u83YCHzWbDJ5/swltvrcbBg7thNje4nx8z5i6MHz8TY8fOQkpKz1aBlupq\nPRob+0IQnAXLDIZK9O8f32bfngVqvJ0T6+385EAHpsLxrheFpzlz5mDq1KnIyspq9f/Y6tWrRWwV\ntYep7pHL+zoRAmQy5wW8TGZ3TxeNRMEKOPC8T5Ei6IGNQ4cOYcKECQCAkSNH4vjx4+7nysvLkZGR\ngbi4OADA6NGjcfDgQUybNi3YzSSiDthsdpSV1WHXrqsATBgwQIX09KQOB7JdnVDbntizslJx9WoT\nVCo7jEYHLlww4NSpr3Hs2Bp8/fVO1NRUu9/bt+/NuPnmGZg2bRoeeGBUh4MpjaYnYmOrUF9vhdGo\nh9UqR23tVQwaFAuFwvm5ngZqWISLKDhefPFFPPPMMywWKgEdBagp/Hl7TrRao5GentjisWdTUXzl\nGruE0sogDDgQ+VfQAxtGoxHx8dfulCqVSjgcDsjl8uuei42NRUNDQ3u7IaIgaXs3xrkcahQcjnRY\nrfG4eLEeCoUBQ4c6urX/tid2hUIBQRBgMp3HX//6HL74YjuuXr3kfj4tLRO33pqH1NQ5SEi4HTJZ\nAxITbSgvN3Q4QIiNBW6/PQ3795+DXq+GUmmDwyFDRcV5DBvmzO4oLW1s9Z6OAjW8M0kUHPHx8cjL\nyxO7GeSBjgLUFP68PSeKVe/h9Ol63pQgCnNBD2zExcWhsfHaBYQrqOF6zmg0up9rbGxEQgLngVFk\nE3v98bZ3Yy5evIjm5p5ISemBK1caYLWaIZOZkJnZ1y+fZ7PZMWXKJBw/fti9TaMZgEmT8jFp0nTc\ndNMwNDb2wt69V2C1NiE2Vo8BA/rCbDZ0uE/noFsPh8OKvn37ISWlP+RyOeTy79wDG08HWyzCRRQc\no0ePxuOPP467774bUVHX6jUw2BF62gtQU2Tw9pwoVr2HULspIfbYjigcBT2wMWrUKOzevRvTp0/H\nkSNHkJWV5X4uMzMT58+fh8FggEqlwsGDB7F48WKP9qvRxHf9IuoU+9B3gejDkyevQqVKh0rlfFxX\ndxXDh3u3gocvKiocUKmuFe+rr1chPj4GZnMsEhNjoVLVY8SIePTt6582nTx5Fc3NzoHRkCGjUVj4\nR0yfPhVyuRzR0dWQyYBLl6rR1FSJmhoDEhJiUVpagylT1J32f9++ifj+ewEmk8a9Ta2Odb+nV68e\nKCurb3XHsb1BhqevExv/f/Yd+1BcJpMJcXFxOHz4cKvtDGwQhQ5vAxViTb9wBlyUbR6Lh9Naifwv\n6IGNnJwc7N27F/PnzwcALFu2DJs3b4bJZEJBQQGWLl2Kn/zkJxAEAQUFBUhOTvZov9XVnLLiC40m\nnn3oo0D1YWWlCYJwLctJrzehT5/AfVftTT1pbr72p0KjEQDUo7z8ewByZGSokJSU2Omxe3NnwmxW\nYOHCpfjd7+bDZmvGgAHpMBguQ6Wyo7HRDoslGY2NzTAaNTAaYwHE4vRpPfr0qUL//p2vnpCcLKCs\n7LK7GntGhtCq3deq+Ms7TaP29HVi4f/PvmMf+s7XwNCyZctgtVrx3XffwW63Y8iQIVAquUo9USjx\nV6Ai0BkMWVk9cfXqpaBkinhyLKGWQeJvzEghMQR9hCCTyfD888+32nbDDTe4/52dnY3s7Owgt4oo\ndAVr6oPrJFRW1gRBiENqajxMJgWio6ugVre8G5MEhUKB4cPbf397J7GzZw1oaEhEZaUBzc1ROHfu\nIqZMSYMg4Lr3qFQO3HZbDuLiEvHdd8cRFVWJW25xLgl97JgBNpsd584ZUVnpgEIhR3KyGgqFA01N\nHfeLq20mkxwqVQ3S0xPRo4eAjIz4kCsmRkROx48fxxNPPIHExEQ4HA7U1NTgzTffxMiRI8VuGtH/\nb+/ew6Ms7/yPf2YmyUzOCUkIJUCoA0FXRIstdUUtIrSyrusJrFoDyLa2V3+uVVHRUnEvXRa1Ra0r\naKu1UnWtFInUxVWhVmzZXqXFpVy6YjQBhMRDCCEhh5nJHH5/xAw5n+bwHPJ+/aOTmXme7/OEzH3P\n9/7e920ZVvmCmegKhmRWigzlWuw+rZWKFBiBJasBk/N6c5SeXi+H45hSUz9TOBzW3r1NqqxsUCg0\n8Jf5ysqGIb1WOtEI+Xxj5PMVqKamY82KtrahdYA63x+J5KmtrUBVVSfWvPD5XKqtbZLP1/F8U1Ox\nqqqa+nzPSSdlqaGhRjNmXCBJ2rXrleh1fPLJUR06dExSvtLSPIpEcnT0aLNSU8PKzvYPGpvTWaDi\n4pOUkRFRWVm+Dh5s6TdmAMb6t3/7Nz300EPavHmzXnrpJT366KO69957jQ4LsJSB2mYzsVMFw1Cu\npWvfLj29PmlrjSSLnX6fsA5qOgGT6zrKUFnZoObmfB0+3KxA4ETlQ1+jL8PNlnc2OmlpIfn9kt/f\n8fjIkUa5XCcNepyBGrGOkQmXPvmkWcGgS5mZjWpt9UQXDu76nurqZhUXn6RLLlmq//mfF/XCC5t0\n8cX3yOFwqLAwW3/5S6WKi0vkcLTrs8/2Kxxu05QpGZozp2TQa+v5mIYXMK/W1tZu1RlnnHGG/P7+\nE5gAektEO9c5cFJd3SbJqSlTPJo6NS+mShCrVzB0rYz55JOjKizMjt6Pvq7F7lu9Wv33CWsisQFY\niM/n0uHDzfL7OxbqbGoKfV7lkNOr1HSkW7BNmJClw4ePyelsUHp6u8aO7b4oaH/H8XhCam4Of550\ncSkn56hOPTVTLpdLXm+Odu58T8HgFKWmtisv7wv67LP9mjw5t1fD13n8008/T2PGFOuzzw6psvJt\nTZt2plwul0pKMjRxYo6mTesY3UhPH7y8sb8GloYXMK/c3Fxt375d8+bNkyRt27ZNeXnJWzgZsINE\ntHPV1U2qqkqVz9exG1pl5TE5nf1vuT4URu2W0lXPaTulpZk6eLBlSNN4ug4mFRbm6MiRAxo3boxh\n12I0M/w+MfqQ2AAsxOMJKRA4se2h2x36vMqhd3WGx6MRb8F28skheb3j5XK5VFnZMKTjeL05+t3v\nDigQKJTbHVBhYakqK4/K5XLK53OpoCBH+fltCgZT5XYfU1FRbp8NX0NDx8rlLpdL5513uV566TH9\n/ve/0bRpZ35+nnS5XMNrLPtrYL3eHFVW1qmqyicpLK83XaFQyJTzj4HR5t5779Vtt92mlStXSpIm\nTpyoBx54wOCoAGtJxBdMn88lv/9ExWUg4JLPF47pmGaoYOjZl9qxo1rFxYNXrErdB31cLqfGjRuj\nGTNG75d5M/w+MfqQ2AAsxOvN0YEDh9TUFJLbHVJJSY48nmN9VmecemrmsDozkUj/5xzKcVwul8aN\nG6Pi4hPPV1X5NHFix8KfDkdETqdLU6eeqLToq+ErK8uOrlx+4YVf10svPaYdO36j66+/TZmZii5e\nOhz9NbAul0sulzMaYyDAAleAWUyePFmPPfaYMjIyFA6HVV9fr9LSUqPDAiwlEV8wPZ6Q3O6IfL6O\nx2lpIVtUPPbsSx0/7lZxcf/Pd0UFKGA8EhuARXSWSBYV5Uo6orFj85SRcezzxENTrwZ1OJ0Zny+g\n55+vVH39GLW1HdPUqeO6rd8x1OP0bNilEyM4JSU5qq09LIcjPGiCpHNqjdf7ZX3hCxP18ceH1Nr6\njr70pXOHFMdwxDL/2CqrzQNW9Ktf/UoVFRWqqKhQTU2Nvve972np0qX65je/aXRogK11bdtSUgJy\nOh0KBFKj7ZzXm6NQqEFVVfvVucaG12v9aWI9+zA9FyXvK1nRea9aWqS6uurP+2YRpl4ABiCxAVjE\niZ09pOLigm5rS8RaavrWW7VqaJim+vqggsHJeu+9gzrttOJ+1+/o78t77zjSFQh0PNeRIMlSWdng\nsVVWNqiqKlV+v0tf+tI/6eOP12nz5k2aPXvgxMZIEg39jbIM5VhsZwYkzsaNG7Vx40ZJUklJiTZv\n3qwrr7ySxAaQYF3btqqqBkUiLpWW5nRr5045pbDXtu9W17MPM2fOeB04MHDfaqC+mZ0wkAMrILEB\nWMRAlQUjKTXt2kh98EFIKSkhBYMdx2xrS1VaWv/rd/R3rp5xhEKhESVcqqvboouSnXHGEr3yyjr9\n13+9pDVrfqy0tLQB3jf8REN/SaGhHItdVYDEaW9v7/b3npqaOsCrAcRL17asY4c0V5/P2cFgX9jL\nytIGfH1Li9R1g7fO+2O3RAADObACEhuARfRVWeDzBfTWW7U6ftyt7Gy/5swZP+AX/07BYEhvvHFI\nDQ2Fqq8/qn37jqm9PUUpKUF5PJOUk9OgCROmyuNpiOnL+8jn9p7oJZSUTFdJyRTV1HyoHTve0Pz5\nF/b7rpHE2l+MQzkWc2qBxJk3b56WLFmiBQsWSJJef/11XXDBBQZHBauy2xfNoRjpNXdt29zuULc1\nuOzWzg33C3vP19fVVau4uCD6fOf9sVsigIEcWIFz8JcAMAOvN0fp6fVyOI4pPb1eXm+O3nqrVo2N\nUxQOT9TRo1/Uc89Vau/eJlVWNigU6r/zUV3dpKamQn36aVgHD+bK7/+iGhulcDisMWPe1j/8wxhl\nZTXI683p1YlJRqdmyhSP3O5jcjiOy+0+pgULLpEkbd68acD3xTPWoRyrr98JgPi47bbbVF5erv37\n9+vQoUNavHixbrrpJqPDgkV1ftGMRPLU1lagqqomo0NKuJFec9e2bcqUdpWV+S3XzgWDIVVWNgza\nJxruF/aez48dm9dnP8CsiYCh3peejOgLAsNFxQZgct1HXKRTT82MjrgcP+6Ovq6urkXt7eM+78AM\nvi2Z2x1Se3uqGhpaFQwWavLkHBUVBVVWlqEzzzwx+hDvreKGMoI0dWqenM4m+XwdC42eeuq39OST\na/Xf/71Vra2tysjI6PPY8Yx1KMdiOzMgsS688EJdeGH/VVrAUJn1i2Yi9XXNQ2mD7dC29ayYqKxs\nVGFh7+lsndUpoVBYhw83y+lsHLC6pffrj6usLKtb36zr67o+NoORVpIkYttgIN5IbABxNtTSz/5e\n1/Pn4XBYfn+RpN6NUHa2X42NHcdrb3cqM/PECt6DbUtWUpKn2tpDikQicrs9GjMmTy7XMdXWHtfe\nvU3dYopnB2cojWrvc+Zr5swz9fbbu7Vt26u65JLL+zx2PGO1Q8cOANDBrF80E6mva7bbFIn+DDWR\n1fmFvbKyVQ5HlsaPn6C2Nle/92Wor09GIqCzv3j4cFitrY1Dmmo00gQffSJYAYkNIM766jT0tbNI\nf52Lnj8/dOiQJk48cfyujdCcOeO1ffsH2r8/qJaW45o8eZJCoY6tXgfqtHU0uMc0a1a2UlI+UkuL\nU05nk1yuoIqLx0arPt5//zOlpLjiOie5c8SotrZJfr9LHk/zkI57+eWL9Pbbu7V586ZoYmM0zpkG\nAAzfaBxx7uua3323pdtr7Fq50nciq/cM/M4v7D6fS5HIiS1r+7svQ319MhIBnf1FjydTbW0pQ0pS\nJSrBR38MZkBiAxjASD6o+8qG95XE6C9r3rsxDXd71LURSktL05QpeSopKYiWRdbWHlZZWdaAnbau\nDe6MGTmqquq4xo8+atT48ScaxerqNk2cWNot7lgbao8npIMHm+TzddyPcFiqqmoa9LiXXHK5Vq36\noX73u9fV2HhMubl5o2bkCQAQm9E44tzXNY+WypWeSZ2yshIdPdra7+uHe1/McB9HUn2RqAQf/TGY\nAYkNYAAj+aDuq7FrbpZqahrk93esbTFhgpSZ2Xej2PP9Xm+6XK56NTdLR440asyYHL3++gEVFeUq\nM1PRrcZcLqdKS3PkcIRVVjb0hqprx6fj3F0bxu6jG/EY2fF6c1RZ+YkcjjSlpYU0YUKWfL7BFzQr\nLh6n2bPP1R/+sENbt76sa64pH5VzpgEAGCmzVK4keoS/Z1JnsGN3vS+pqe0KhSK9puX293qj7mPX\n/mIwGFJ9/dHoz/u7n4lK8NEfgxmwKwowgJFmw3uukH3kSKN8vo6VyX2+AtXVNfa7o0bPn5eV5aus\nLF9ZWVJx8UmqrU1TY+MUHT7sVFtbx7G6Gs6oQc/VsSdPzux27ilTPCM+dn86GtUMTZ2aqdLSHLlc\nziEf97LLFko6sTtKX6t0j3TFbwAA7K7zi+2MGTkqK8s3bLqA2Xap6XpfXC6nAoGxA8bW9fUnndRR\n+Zrsfkdnf9HpbFR9/UEVFk427H6yawrMgIoNWIYR8/dGUmrYdb/3TmPH5snnO6ZAwKW0tJDGjs3r\nN2ve3887kyqBQMd//X5X9NipqZ+purpNklNTpnii62x06nnvSkszdfBgiyorWxWJZKmkJFvHj0tv\nvnlQ48aN6Tb6kIgRiZGOdPzjP/6TVqy4RX/84w59+umn8noLex2nqopySAAAzMzMI/zDjc2oaRid\n/cWiomwdPTpGkciJ8epk308zVLAAJDZgGUY0HCP5oO4rzowMqbT0xHvT0+uHHUtnkiUtLSS/X3K7\nO5IsGRkRSa7oWhh+f+970zOmHTuqVVx8knw+jyKRbNXU1H/+3mIVF2d2u7+JuMcjLYXMy8vX3Lnz\n9Npr/62XX67Qt7/9vV7HMXNnCQAAmGONiv4MNzYz9DuMvJ8sHAqzYCoKLMOIhmMkJZudu3589FGD\nPvigSZWVzb2meIwkk91ZcjhpUlC5uR9qwoRw9Fhd70XHVIzmbiWRPe/V8eNuSR1JEqmj+sPvd0Uf\nd16HGfWcjtIT5ZAAAAxN1+mb7713NOnTKMLho/r002q1tMg000f7myrcHzP0O4YbczyZbVoRRi8q\nNmAZ8c5GJyrD3NeuHwcOtMRc+dC9yiGv23Nd701tbZMikXxFIjnRyguPR93uXXa2X5I0YUKWDh8+\nJqezQWlpIRUWTu52TDP6xjf+QRkZGfrrX3fpo48Oyu12KxQKafz4EkmUQwIAMFRdKzpbWzN19OhH\nSZ1GUVnZIKfzJEm9q3GNqgQYblWpGfodRu76Y4aKFUAisQELiXfDkaipLSPd9SPWc3beG4ejWSUl\nJdHnWloc8niCOnTooCSnJk9OVUlJhvbvPyQprKlT01VWNl6SVFXVYPqEQGZmpr7xjQWqqHhRFRWb\n9PTTv5Df79O771bJ4XCMyi39AAAYCaO/lA50fqtsIRpLv8MO0zjMPK0IowuJDVhGvL+wJqox79z1\no60tM/qzRH/I996y9cQss7q6YyouPkkTJ3Y8rq2t7vbY5aqPNqJm7DB0VV1dpf/4j4d05pmzVFHx\non7zmxdUU3NYeXl5cjgcRocHAIClGP2ltL/zd0yRaZXP5+kySGStL/xDYZXkzUDMULECSCQ2MIol\nsjGP5UN+oOz9UDL7Pc9dVJTb7fnjx90qLj7x2EodhT/9aaeee+5Xys3NVWZmlior90mSJk2abGxg\nAACMQLJH7Hueb/LkTB040NFnyMjwq6QkuV9K++svVVc3KRLJUiSSLb9fOnz4mE4+2X6VAEZXzMQD\nlbIwCxIbGLUSmWGO5UN+oOz9UDL7Pbeb9XhCCgROPO5cX6Pr81axaNFV2rbtNb3yystKSUmN/nzS\npFIDowIAYGSSPWLf83wHDpw4X1FRturqjvf73kQkYQba4r6kpGPXNr/fJaezQV7v+JjOZUZ9DbLZ\nYXoKYAQSG7C1gRoHs2aYB8reDyWz37PT4nbXKT39RAJnzpzx0dEZq5UMpqWl6Yknntb/+3/f0Usv\nbY7+fNKkSQZGBQDAyCR7xD6W8yU6CdO1z/bJJ0dVWJijSZM6jp+e3m7LL/d9DbJVVVl/espoRVLK\nWCQ2YGtmmbs4nA+6gabIDGX6TM9OSiCQqr/7u8zo+Q8caOk1vaWyssEyH8Kpqalav/5JuVwpevHF\njZIkl4uPMgCA9SR7jYtYzpfoJEzXPlthYbaOHDmgcePGWG4QZjj6GmSzw/SU0cos3ztGK+fgLwGs\nyyyNw3D2+B5oL/Kh7FPe137qA53fivuPp6Sk6NFHf6avfOWrcjgcOuec84wOCQCAYRtKu26W8/XV\nv5BODJDs3dukysoGhUIjS8507aO5XC6NGzdGM2bkqKwsf8ABl3id3yz6u88wP7N87xitGOaErcVj\nJCQeZWXD+aDrb4rMUBcVTU0Nye2uUyCQGn3du++29Ht+q34Iu1wubd26TZFIhB1RAACWlOxpsbGc\nb6CFPuMxSj3QDikD9cPsNkrOLiPWZfQuQ6MdiQ2MiFXmkMWjcYhHgxmPD7qhLioaCEjp6fWaMePE\ntcY6vcXMSGoAAJB4Ay30OdDjoRpp4sSqAzT9MesacBgcSSljkdjAiFglOx6PxiEeDWY8PuhiWVR0\noPMPJTarJLIAAEByxWuAZKSJE6sP0MA+SEoZi8QGRsRu2fFOfX2Bj0eDGY8PuuFUXaSkBHotCNrf\n+YcSm1USWQAwmG3btunVV1/V2rVrjQ4FsIVEj1IP1g9jlByARGIDI2TX7HhfX+DN0mAOp+oiEAhr\n3z6PAgGX0tKcCoeP6eSTC0Z8brsmsgCMLqtXr9bOnTt1yimnGB0KYBs9B0jivdvaYP0wRskBSCQ2\nMEJm+bIfb319gY9HgxmPqRwDxdH5XOd5duxoVCiUo+LiDPn9Tn344UGdfPLI47drIgvA6DJz5kzN\nnz9fL7zwgtGhAIOK1zTQZE8njXeVp1GJC6bhAtaS9MSG3+/Xbbfdpvr6emVlZem+++5Tfn73D6vV\nq1fr7bffVmZmpiRp/fr1ysrKSnaoGIBds+OJ+gKfrKkcnecJh1vV3p6tTz89ri98IUtSOKbj2jWR\nBcCeNm3apA0bNnT72Zo1a7RgwQLt2rXLoKiA4YlX3yHZ00ntUuXJNFzAWpKe2Hj++edVVlamG264\nQa+88orWr1+vlStXdnvNu+++q1/84hfKy8tLdngY5RL1BT5ZjXzncSdNStfBg/UKBgPyePzyetNj\nOq5dE1kA7GnhwoVauHBhzMfJz89QSkpiv5QVFWUn9PhGset1Scm7tsOHw/J4MqOPnc7giM49nOPE\n49rGj29Xa+uJ82Vk+E3x72E4MQSDIX3yyVH5fGG53WFNmpSl1NRcU1xHX8waVzxwbdZkxLUlPbGx\ne/dufec735EknXfeeVq/fn235yORiA4ePKhVq1aprq5OCxcu1BVXXJHsMDFKJeoLfLKmcnSeZ+LE\nfDmdTXI4/Corc8nr7T73ldJKABhcQ0NrQo9fVJSturrjCT2HEex6XVJyr621tVFtbSe66unpjaqr\ncybsOPG6tvx8p44e/SjazygpyTH838Nwr62yskGNjS75fB33rbHxM518cvuI7n+i8fdmTVzbyI/d\nn4QmNvoqBS0sLIxOK8nMzFRzc3O351tbW1VeXq7rrrtOwWBQixcv1mmnnaaysrJEhgokVLKmcnQ9\nz7RpYXm94xSJSFVVJxIZoVBIgcBYSZRWAgBgVvHqOyR7Oqkdqjx9PpdKSrJVU1Mvv98lp7NBXu94\no8MyHQbLYCYJTWz0VQr6L//yL2ppaZEktbS0KDu7e9YlPT1d5eXlcrvdcrvdOuuss7Rv375BExt2\nLuVJFu5h7Aa6h+PGJWdqVc/zvPfeUXk8k+TxdDw+cOCAJk+OvbQ1kcwWjxVxD2PHPbSnWbNmadas\nWUaHAQwqXgkCOyQakq2jAtalSZM67lt6ejtf2PvAOiQwk6RPRZk5c6Z27Nih0047TTt27NCXv/zl\nbs/v379fN998s7Zs2aJgMKjdu3fr8ssvH/S4di3l6U+8M6R2LodKlvz8DP35zzWmy1rX1rYpEmmJ\nPm5q8qmh4cTjkZa2Jgr/FmPHPYwd9zB2JIYAexoNo/Qsmj40dlkoFvaQ9MTG1VdfrRUrVuiaa65R\nWlqa1q5dK0l6+umnVVpaqvPPP1+XXnqpFi1apNTUVF122WXyer3JDtP0yJCazwcfNJryd9JzfY8p\nUzxyOmmsAQDA8I2GPmiiq1zskhxK1hpywFAkPbHh8Xj005/+tNfPly5dGv3/ZcuWadmyZUmMynrI\nkJqPWX8nvUcd8izZeAIAAOOZtb9jJXZJDlHZAjNJemID8UGGNHmGmlXv+B2k9HhsPObWAgCAeKEP\nGjsrJ4fsUm0C+yGxYVHJzpBa+UMs1tiHmlUvK8vV0aM1ZK0BAIBtMUofu0QmhxLdZ7dLtQnsh8SG\nRSV7FN7KH2Kxxj7UrDqVEQAAwO7o78QukcmhRPfZrVxtAnsjsYEhsfKHWKyxU3IJAACAeElkcijR\nfXb6xTArEhsYEit/iPWMPTW1XZWVDUMu0aPkEgAAoIOVpyePBonus9MvhlmR2MCQWPlDrGfsoVBk\nWCV6lFwCAACzMSrBYOXpyaNBovvs9IthViQ2MCRGfojF2nD3jH3v3qZuz1tpWg0AAIBkXILBytOT\nRwMSDxitnEYHAAyms+GORPLU1lagqqqmwd80gJ4leVaaVgMAACAZl2CgHwXAjEhswPTi3XB7vTlK\nT6+Xw3FM6en1lppWAwAAIBmXYKAfha6CwZAqKxu0d2+TKisbFAqR6IIxmIoC04v3IkiU6AEA0l9Y\n8QAAFSJJREFUAKszav0z+lHoijVXYBYkNmB6Vl64FAAAIBFIMMAMWHMFZkFiA6ZHww0AAACYT6K3\nlwWGijU2AAAAAADDxporMAsqNgAAAAAAw0ZlNcyCig0AAAAAAGBZVGzAMoLBkKqrm7otIupysUAR\nAAAAAIxmJDZgGWwnBQAAAKMwyAaYF1NRYBlsJwUAAACjdA6yRSJ5amsrUFVVk9EhAfgciQ1YRs/t\no9hOCgAAAMnCIBtgXiQ2YBlsJwUAAACjMMgGmBdrbMAy2E4KAAAAidbfWhpeb46qquq7/RyAOZDY\nAAAAAIDP9bdgPYNsgHmR2EgCq66gbNW4AQAAgJFiLQ3AelhjIwmsuoKyVeMGAAAARoq1NADroWIj\nCaya9bVq3AAAAMBI2WktDSqwMVqQ2EgCjyektrbuj63AqnEDAAAAI2WntTT6Wy8EsBumoiSBVbcp\ntWrcAAAAAKjAxuhBxUYSWDXra9W4AQAAAFCBjdGDxAYAAAAA2JDZ1gthzQ8kCokNAAAAALAhs1Vg\ns+YHEoXEBgAAAEYtRpBHL373yceaH0gUEhsAAAAYtRhBHjq7JAI6r6OyslnhcL4mTMhSW5uT330S\nsOYHEoVdUQAAADBqMYI8dJ1JoEgkT21tBaqqajI6pBHpvA6fL19+f54OH26WxO8+Gdh1EYliWGJj\n27ZtWr58eZ/Pbdy4UVdccYWuuuoqvfnmm8kNDAAAAKNGzxFjRpD7Z5ckUGfcbnfH7zoQ6HjM7z7x\nOtf8mDEjR2Vl+Zas+IE5GTIVZfXq1dq5c6dOOeWUXs8dOXJEzzzzjCoqKuTz+XT11Vdr9uzZSk1N\nNSBSAAAA2JnZdo0wM7tMI+i8jpKSHNXU1MvhaFZ6uo/fPWBhhiQ2Zs6cqfnz5+uFF17o9dzevXt1\n5plnKiUlRVlZWZo8ebLef/99TZ8+3YBIAQAAYIRkredgtl0jzMwuSaCu1zFtWlhe7zhTVw7YZW0T\nIJESmtjYtGmTNmzY0O1na9as0YIFC7Rr164+39Pc3Kzs7Ozo44yMDB0/fjyRYQIAAMBkWNTTfOyS\nBLLadfC3AAwuoYmNhQsXauHChcN6T1ZWlpqbm6OPW1palJMzeDa4qCh70NdgYNzD2HEP44P7GDvu\nYey4h4Cx7LKeA6PtiJVd/haARDLddq8zZszQww8/rEAgIL/fr+rqak2dOnXQ99XVUdURi6KibO5h\njLiH8cF9jB33MHbcw9iRGEKs7LKeA6PtiJVd/haARDJNYuPpp59WaWmpzj//fJWXl+uaa65RJBLR\nLbfcorS0NKPDAwAAQBLZZT0HRtvNwcqVM3b5WwASybDExqxZszRr1qzo46VLl0b/f9GiRVq0aJEB\nUQEAAMAMrLYOQn8YbTeHWCtnjEyMxOtvwcrJHWAwTqMDAAAAAOzK681Renq9HI5jSk+vZ7TdILFW\nznQmRiKRPLW1Faiqqime4SWFHa4B6I9ppqIAAAAAdmOXyhOri7Vyxg5TiuxwDUB/qNgAAAAAYGux\nVs70TIRYcUqRHa4B6A8VGwAAwPaam5t16623qqWlRe3t7brjjjt0xhlnGB0WgCSJtXLGDgt42uEa\ngP6Q2AAAALb3y1/+UmeffbYWL16s/fv3a/ny5dq8ebPRYQGwCDtMKbLDNQD9IbEBAABs77rrrotu\nHx8MBuV2uw2OCAAAxAuJDQAAYCubNm3Shg0buv1szZo1mj59uurq6nT77bdr5cqVBkUHAADizRGJ\nRCJGBxEPdXXHjQ7B0oqKsrmHMeIexgf3MXbcw9hxD2NXVJRtdAi9vP/++7r11lu1YsUKnXPOOYO+\nPhgMKSWFXQMAKwkGQ/rgg8boOhJlZblyufg7BuyOig0AAGB7H374oW666SY9/PDDmjZt2pDe09DQ\nmtCY7JpAs+t1SVybFVRWNqitreDzRyk6erRGs2dPssW19cUuv7e+cG3WlMhrG2jQhMQGAACwvQcf\nfFCBQECrV69WJBJRTk6O1q1bZ3RYAOLM53MN+BiAPZHYAAAAtrd+/XqjQwCQBB5PSG1t3R8DsD+n\n0QEAAAAAQDx4vTlKT6+Xw3FM6en18npzjA4JQBJQsQEAAADAFlwul8rK8o0OA0CSkdgAAAAAEFfB\nYEjV1U3R3Um83hx2JwGQMExFAQAAABBX1dVNamsrUCSSp7a2AlVVNRkdEgAbI7EBAAAAIK7YnQRA\nMjEVBQAAAEBcxbo7CVNZAAwHFRsAAAAA4irW3UmYygJgOKjYAAAAABBXse5OwlQWAMNBxQYAAAAA\nU+k5dWW4U1kAjC4kNgAAAACYSqxTWQCMLkxFAQAAAGAqsU5lATC6ULEBAAAAAAAsi8QGAAAAAACw\nLBIbAAAAAADAskhsAAAAAAAAyyKxAQAAAAAALIvEBgAAAAAAsCwSGwAAAAAAwLJIbAAAAAAAAMsi\nsQEAAAAAACyLxAYAAAAAALCsFKNOvG3bNr366qtau3Ztr+dWr16tt99+W5mZmZKk9evXKysrK9kh\nAgAAAAAAkzMksbF69Wrt3LlTp5xySp/Pv/vuu/rFL36hvLy8JEcGAAAAAACsxJCpKDNnztS//uu/\n9vlcJBLRwYMHtWrVKl199dV68cUXkxscAAAAAACwjIRWbGzatEkbNmzo9rM1a9ZowYIF2rVrV5/v\naW1tVXl5ua677joFg0EtXrxYp512msrKyhIZKgAAAAAAsKCEJjYWLlyohQsXDus96enpKi8vl9vt\nltvt1llnnaV9+/YNmtgoKsqOJVSIexgP3MP44D7GjnsYO+4hAACANRi2eGh/9u/fr5tvvllbtmxR\nMBjU7t27dfnllw/6vrq640mIzr6KirK5hzHiHsYH9zF23MPYcQ9jR2IIAAAki2kSG08//bRKS0t1\n/vnn69JLL9WiRYuUmpqqyy67TF6v1+jwAAAAAACACRmW2Jg1a5ZmzZoVfbx06dLo/y9btkzLli0z\nICoAAAAAAGAlhuyKAgAAAAAAEA8kNgAAAAAAgGWR2AAAAAAAAJZFYgMAAAAAAFgWiQ0AAAAAAGBZ\nJDYAAAAAAIBlkdgAAAAAAACWRWIDAAAAAABYFokNAAAAAABgWSQ2AAAAAACAZZHYAAAAAAAAlkVi\nAwAAAAAAWBaJDQAAAAAAYFkkNgAAAAAAgGWlGB0AAAAAAHQVDIZUXd0kn88ljyckrzdHLpfL6LAA\nmBQVGwAAAABMpbq6SW1tBYpE8tTWVqCqqiajQwJgYiQ2AAAAAJiKz+ca8DEAdEViAwAAAICpeDyh\nAR8DQFessQEAAGyvra1Ny5cvV1NTk9LS0nTfffdp7NixRocFoB9eb46qquq7rbEBAP2hYgMAANje\nxo0bNX36dD377LO6+OKL9cQTTxgdEoABuFwulZXla8aMHJWV5bNwKIABUbEBAABsb8mSJYpEIpKk\n2tpa5ebmGhwRAACIFxIbAADAVjZt2qQNGzZ0+9maNWs0ffp0LVmyRB988IGeeuopg6IDAADx5oh0\nDl8AAACMAtXV1frud7+rbdu2GR0KAACIA9bYAAAAtvfzn/9cW7ZskSRlZGQwXx8AABuhYgMAANhe\nfX29VqxYIb/fr0gkouXLl+tLX/qS0WEBAIA4ILEBAAAAAAAsi6koAAAAAADAskhsAAAAAAAAyyKx\nAQAAAAAALMsWiY22tjZ9//vf17XXXqtly5bps88+Mzoky2lubtb3vvc9lZeX66qrrtKePXuMDsmy\ntm3bpuXLlxsdhqVEIhHdfffduuqqq7R48WIdOnTI6JAs629/+5vKy8uNDsOSgsGgbr/9dn3rW9/S\nlVdeqTfeeMPokCwpHA7rhz/8oa6++mp961vf0ocffmh0SKZWVVWlL3/5ywoEAkaHEjd27peNhv6S\nnfoxdu9f2LHNt3NbPBrax/r6es2ZM0f79+9P+rltkdjYuHGjpk+frmeffVYXX3yxnnjiCaNDspxf\n/vKXOvvss/XMM89ozZo1uueee4wOyZJWr16thx56yOgwLGf79u0KBAL69a9/reXLl2vNmjVGh2RJ\nTz75pH70ox+pvb3d6FAs6be//a3y8/P13HPP6YknntC9995rdEiW9MYbb8jhcOj555/XD37wAz34\n4INGh2Razc3NeuCBB+R2u40OJa7s3C+ze3/Jbv0YO/cv7Nrm27kttnv7GAwGdffdd8vj8Rhy/hRD\nzhpnS5YsUefmLrW1tcrNzTU4Iuu57rrrlJaWJqnjH6XdOlnJMnPmTM2fP18vvPCC0aFYyu7du3Xu\nuedKkk4//XS98847BkdkTaWlpVq3bp1uv/12o0OxpAULFujCCy+U1DGqkpJiiyYy6ebNm6e5c+dK\nkmpqamiTB7Bq1Srdcsst+v73v290KHFl536Z3ftLduvH2Ll/Ydc2385tsd3bx/vvv19XX321fvaz\nnxlyfsv9S9m0aZM2bNjQ7Wdr1qzR9OnTtWTJEn3wwQd66qmnDIrOGga6h3V1dbr99tu1cuVKg6Kz\nhv7u4YIFC7Rr1y6DorKu5uZmZWdnRx+npKQoHA7L6bRFUVnSzJ8/XzU1NUaHYVnp6emSOv49/uAH\nP9DNN99scETW5XQ6dccdd2j79u165JFHjA7HcH21GePHj9dFF12kadOmRZMAVmTnfpmd+0ujpR9j\n5/6FXdt8u7fFdm0fN2/erIKCAs2ePVuPP/64ITE4IlZuTftQXV2t7373u9q2bZvRoVjO+++/r1tv\nvVUrVqzQOeecY3Q4lrVr1y698MILWrt2rdGhWMZ9992nM844I5qhnzNnjt58801jg7KompoaLV++\nXL/+9a+NDsWSPv74Y91www269tprddlllxkdjuXV19dr0aJFeuWVVwwrTTWrb3zjGyouLlYkEtHf\n/vY3nX766XrmmWeMDivu7Ngvs3t/yU79GLv3L+za5o+Gtthu7eO1114rh8MhSdq3b5+++MUv6rHH\nHlNBQUHSYrBcxUZffv7zn6u4uFiXXHKJMjIy5HK5jA7Jcj788EPddNNNevjhhzVt2jSjw8EoM3Pm\nTP3+97/XhRdeqD179qisrMzokCzNZvnqpDly5Ij++Z//WatWrdJZZ51ldDiWtWXLFn366ae6/vrr\n5Xa75XQ6bTE6Gm+vvfZa9P/nzp1r2aqGvti5X0Z/yVpGQ//Cbm2+ndtiO7ePzz77bPT/y8vLdc89\n9yQ1qSHZJLFxxRVXaMWKFdq0aZMikYitFgZKlgcffFCBQECrV69WJBJRTk6O1q1bZ3RYGCXmz5+v\nnTt36qqrrpIk/oZj1Jkxx/D87Gc/U1NTk9avX69169bJ4XDoySefjM6nx9B8/etf15133qlrr71W\nwWBQK1eu5B4OwuFw2OrLiZ37ZfSXrGU09C/s1ubbuS0eLe2jUf8mbTcVBQAAAAAAjB72qH0BAAAA\nAACjEokNAAAAAABgWSQ2AAAAAACAZZHYAAAAAAAAlkViAwAAAAAAWBaJDQAAAAAAYFkkNgAAAABg\niDZu3KhXXnml3+d37typpUuXJi8gACQ2AAAAAGCo/vd//1eBQKDXzyORiJ566indcsstCofDBkQG\njF4pRgcAAM8884xee+01Pfvss/rrX/+qlStXqqKiQhkZGUaHBgAA4uDHP/6xtm/frtTUVF155ZVa\nvHixDhw4oLvuukuNjY3KyMjQj370I02fPl133nmn0tPTtXv3bh0/flw//OEPtWXLFr3//vu64IIL\ntGLFClVUVOj1119XY2Oj6uvrdf755+uOO+6QJD3++ON6+eWX5XK5NHv2bN1+++2qra3VDTfcoKlT\np+q9995TYWGhfvrTnyonJ0d/+MMf9MgjjygUCmnChAm69957lZubq7lz5+qSSy7RH//4R/l8Pt1/\n//1qbGzUG2+8oT//+c8qKirS7Nmzo9dYVVWl/fv3a/Xq1frVr35l1K0GRiUqNgAYrry8XC6XS889\n95zuuusu3X///SQ1AACwiVdffVV79uzR1q1btXHjRlVUVOjIkSO67bbbtGTJEv32t7/VnXfeqRtv\nvFHt7e2SpLq6Om3ZskU33nij7rzzTt1zzz2qqKjQxo0b1dzcLEl655139Oijj2rr1q3as2ePtm/f\nrh07dujNN99URUWFXnrpJR08eFDPP/+8JGnfvn1atmyZXn75ZWVnZ+vll1/W0aNHtXbtWj311FPa\nvHmzZs+erR//+MfR2MeMGaPf/OY3+uY3v6nHH39cf//3f6+5c+fqxhtv7JbUkKQpU6bo3nvvVU5O\nTpLuLIBOVGwAMIXVq1fr4osv1jXXXKMzzjjD6HAAAECc/OUvf9GCBQuUkpKilJQUVVRUqLW1VR99\n9JHmzZsnSTr99NOVl5en/fv3S5LOO+88SdL48eNVVlam/Px8SVJeXp6ampokSXPnztWYMWMkSRdd\ndJH+9Kc/KS0tTRdddJHS0tIkSVdccYW2bNmir33tayooKNDJJ58sSZo6daqOHTumvXv36uOPP9bi\nxYsViUQUDoeVl5cXjf2cc86Jvn7btm2JvlUARojEBgBTqKmpUVZWlv7v//7P6FAAAEAcpaR0/8pR\nU1Oj3NzcXq8Lh8MKhUKSpNTU1OjPXS7XoMcNh8O9ziN1rHsRDAYlSW63O/pzh8OhSCSiUCikM888\nU+vXr5ckBQIBtbS0RF/X+Z7O1wMwJ6aiADBcS0uLVq1apccee0wej0f/+Z//aXRIAAAgTr7yla/o\n9ddfVzAYVFtbm7797W+rvr5eEydOjFZB7NmzR0eOHNHUqVMHPFbX5MJbb72l5uZm+f1+bd26Veed\nd56++tWvauvWrfL7/QoGg9q8ebPOOuusXu/tdPrpp2vPnj06cOCAJGndunV64IEHBozB5XJFp8wA\nMAcqNgAY7ic/+YnOP/98TZ8+XXfddZeuvPJKfe1rX1NJSYnRoQEAgBjNmzdP77zzji677DJJ0tKl\nS1VaWqoHHnhAd999tx555BG53W6tW7euz6qLrhwOR/T/CwoKdP3116uhoUGXXnppdM2Lffv26Yor\nrlAoFNK5556ra6+9Vh9//HG393YqLCzUv//7v+umm25SOBzWuHHj9JOf/KTXubo6++yz9dBDDyk3\nN1df//rXR3RPAMSXI0JNFQAAAAALqaio0K5du7RmzRqjQwFgAkxFAQAAAAAAlkXFBgAAAAAAsCwq\nNgAAAAAAgGWR2AAAAAAAAJZFYgMAAAAAAFgWiQ0AAAAAAGBZJDYAAAAAAIBlkdgAAAAAAACW9f8B\nKZBY2uqjc7wAAAAASUVORK5CYII=\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11ba330f0>"
+       "<matplotlib.figure.Figure at 0x1a1444ea58>"
       ]
      },
      "metadata": {},
@@ -2169,22 +1908,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Digits Pixel Components"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 61,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_pca_components(x, coefficients=None, mean=0, components=None,\n",
@@ -2233,18 +1965,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 62,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA3MAAAChCAYAAABtV+bDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAHopkDAAAAAAf6P1QpRwQf0IzUAAAAAElFTkSuQmCC\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11d01edd8>"
+       "<matplotlib.figure.Figure at 0x1a13889630>"
       ]
      },
      "metadata": {},
@@ -2265,28 +1993,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Digits PCA Components"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 63,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA3QAAACeCAYAAAB6p0jCAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n4oCOiIiIiIjIoP4/QFJA2Z7Z0loAAAAASUVORK5CYII=\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11ce84a58>"
+       "<matplotlib.figure.Figure at 0x1a13b71668>"
       ]
      },
      "metadata": {},
@@ -2305,32 +2026,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Manifold Learning"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### LLE vs MDS Linkages"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 64,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def make_hello(N=1000, rseed=42):\n",
@@ -2357,12 +2068,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 65,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def make_hello_s_curve(X):\n",
@@ -2379,18 +2086,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 66,
+   "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/matplotlib/cbook/deprecation.py:106: MatplotlibDeprecationWarning: The axisbg attribute was deprecated in version 2.0. Use facecolor instead.\n",
+      "  warnings.warn(message, mplDeprecation, stacklevel=1)\n"
+     ]
+    },
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAABI4AAAG+CAYAAAD1KU+TAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nERERUUJsOCIiIiIiIiIiooT+P2wTBDSvVgX3AAAAAElFTkSuQmCC\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAABI4AAAG+CAYAAAD1KU+TAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzs3XecVPW9//HXOWf6bIdlabtSVAQ19kSJFYwtUYPeKNFojNhj1FyTiNFfjIm5XluKNdFEbvQmDzUGjSVGUYgdvSgaKyLI0tm+08spvz82M+7CALuwwALv5+PBg90zp82ZmTPv/Xy/53sMz/M8RERERERERERE1mJu6x0QEREREREREZGBSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjEREREREREREpSYUjke3M9OnTGTduHOPHj6etrW2985100kmMGzeO6dOnr7Ns93977bUXRxxxBD/84Q9ZuHBhyXXlcjnuvfdeTjrpJPbdd1/2339/TjnlFO69916y2exG9/mOO+5g3LhxvPHGG72ab/ny5RtdZ3czZ87s1fpFRESk9wq5YWPfy739ni98X2/o34EHHtirdcycObNX8/U1G7zxxhu9Wv/26sMPP2TixIkkEomSj5977rk9smN3H330Ed/5znfYf//9mThxIjfccAOpVGqT51vbWWedxbhx43jxxRdLPl7qtdmUZc455xwefPDBje6PiHzOt613QEQ2jeu6zJkzh1NPPXWdx5YtW8aCBQvWu+zVV19NdXU1AOl0msbGRmbOnMmzzz7Lfffdx5e+9KXivLZtM23aNN555x2+/vWvc/rpp+M4DvPmzeOXv/wls2fP5oEHHiAQCGz2c/rKV75CQ0MDNTU1m70uERERGZhOP/10DjjggJKP+f3+ftnGQQcdxM0338zYsWP7ZX07Atd1ue6665g2bRplZWXrPP6b3/yGV199lSlTpqzzWGNjI2effTaDBg3isssuo7W1lRkzZtDY2Mh9993X5/k25Gc/+xlPP/00oVCo18+tL8t8//vf59xzz+XYY49lyJAhvd6GyM5MhSOR7dTIkSN54YUXShaOnn/+eWpqatbbI+noo49m5MiRPaadffbZnHrqqVxxxRU8//zzRKNRAJ555hnefPNN7rjjDo455pge8//+97/nlltu4dFHH+WMM87Y7Oe0xx57sMcee2z2ekRERGTg2nfffTn55JO36Dbq6+upr6/fotvY3jzxxBM0Njauk9my2Sz/9V//xUMPPbTeZW+//XYA/vSnPzFo0CAAGhoauPbaa3n11Vf58pe/3Kf5NmT58uXcfffd/Od//mevn1tfltlnn33Ye++9+fWvf81//dd/9XobIjszXaomsp2aPHkyr732GplMZp3HZs2axaRJk/q0vmHDhnHVVVfR1tbGX//61+L0+fPnA5T8oj/zzDPx+/288847fdx7EREREdma/vjHPzJ58mTC4XBx2po1azj++ON5+OGHueCCC0oul8/nmTVrFsccc0yxGAQwZcoUIpEITz/9dJ/m25ChQ4cyYcIE7r//fhYtWtSr57Upy3zta1/jySef3OCwDyLyORWORLZTRx99NOl0mtdee63H9NbWVubPn9+jd1BvHXfccQQCAV5++eXitELPo4cffnid+cPhMG+//TY333xzn7dVytpjHN1xxx3svffeLFmyhAsvvJD99tuPgw46iKuuuor29vYNruu+++5j3Lhx/OIXvyhOa2xs5KqrruLwww9nr7324otf/CIXXXTROmM7JRIJrr/+eg499FD23XdfLrroIt566611rpF3XZf777+f4447jr322ovDDjuMG264YZ1xA958803OPPNMDjzwQPbbbz+mTp3K7NmzN/dwiYiIyHqsPcZR4fePP/6YK6+8koMOOoj99tuP7373uxsdw+npp59m/PjxXHbZZTiOA0BzczM/+9nPmDx5MnvttRcHHHAAZ599Nm+99VaPZfP5PL/+9a858sgj2WefffjWt77Fxx9/zIQJE7jjjjvW2eevf/3r7L333hx88MFMnz6dpqamHvMsWLCAadOmcfDBB7PPPvswZcoUHn300Y0ej7fffpsPP/yQo48+usf0trY2otEoM2bM4Morryy57MKFC8lms+y55549pvt8PsaNG8f777/fp/k2xLIsrr/+ehzH4ac//elG59/UZSZNmoTjODzyyCO9ml9kZ6fCkch26oADDqC6upoXXnihx/QXXniBcDjMIYcc0ud1BoNBGhoa+Pjjj4vTTjrpJPx+PzfddBNf+9rX+PWvf80bb7xBLpcD6JexjTbEdV3OPvtsotEoV111FccccwyPP/74BoPBX/7yF2699VZOP/10rrnmGgBaWlo47bTTmDdvHt/61re47rrr+NrXvsYrr7zCJZdcguu6ADiOw3nnncfDDz/Mcccdx5VXXklHRweXXHLJOtu55ppruOWWW9h///259tprOe6443jooYc4++yzi4OGL168mAsvvBDP8/j+97/PD37wA9LpNJdccgnz5s3r/wMmIiIywKVSKdra2kr+681NNzbHxRdfTGdnJ9///veZOnUqc+bM4Yorrljv/C+//HKx0em2227DsiwymQxnnnkmzzzzDFOmTOG6665j6tSpvP/++1xwwQU9GpB+8IMfcM8993DwwQfzox/9iFAoxNlnn13MHQV33nknV199NQ0NDVx99dWcfvrpzJo1i6lTpxZ7xbS1tTFt2jSampq4+OKLufrqqykrK+Oaa67hySef3ODzfvHFF/H7/ev0IN9111154oknNpgb16xZA0BdXd06j9XW1rJq1ao+zbcxX/jCFzjttNN48803eeyxx7bIMjU1NXzhC19Y76DaItKTxjgS2U5ZlsVRRx3FnDlzcF0X0+yqA8+aNYsjjzxykws6FRUVLF26tPj7brvtxp133smPf/xjFi5cyMKFC7nnnnuIRCJMmjSJSy+9lNGjR/fLcyrFtm1OOOGE4h0+pk6dypo1a3j++edJp9M9ultD1/O/7rrrOPnkk7n++uuL02fOnElHRwd//vOfewyUGY1Guffee/noo4/Yc889efLJJ5k/fz433HAD3/jGN4rbPOOMM+jo6Cgu98YbbzBz5kyuv/56pk6dWpx+xBFHMG3aNB566CG+/e1v88ILL5BKpbjzzjuLg36fcMIJTJ06lY8++mijd48RERHZ0fz85z/n5z//ecnHrr76as4555wttu299tqrR0+fVCrFQw89xJIlSxg1alSPeefPn8/3vvc9DjzwQG6//fbiwN2zZ8+msbGR3//+9xx22GHF+evr67nuuut47bXXOOaYY5g3bx7/+Mc/uOiii/j+978PwBlnnMH3vvc9Zs2aVVxu2bJl3HXXXVxwwQU9ev189atf5ZRTTuG3v/0tP/7xj5k7dy7Nzc3cc8897L333gCccsopTJ06lU8++WSDz/utt95il112WWfw6N4MRp5MJgHWyVzQ1eiYTqf7NF9vXHnllTz//PPcfPPNTJo0icrKyn5fZty4cfz1r38ll8tt8YZQke2dehyJbMcmT55Ma2trcYyhRCLB66+/vk435L6wbRvDMHpMO/LII5kzZw6/+tWvOPnkk6mtrSWVSvHUU09x8skn8+abb27W89iY448/vsfv48ePx7btHoUcgLlz5/Kf//mffPGLX+TGG2/s8TwuuOACXnvttR5Fo0wmUyy4FW4T+/zzz1NZWckpp5xSnM/v9/Od73ynx7aee+45DMPgiCOO6NFSOmHCBGpra/nnP/8JdF13D10hudBFu7q6mmeffZazzjprcw6LiIjIdmnatGnMmDGj5L9jjz12i267VKaArp7J3S1cuJALL7yQESNGcM899xAMBouPnXDCCbz++usceuihxWmFntjweaYoFIe6ZwjDMDj//PN7bGvWrFm4rsukSZN6ZIrBgwczfvz4dTLFbbfdxrx583Ach0AgwMyZM9d7mVnBsmXL1rkxSm8VeketnQ+7P6e+zNcbFRUV/OhHP6KtrY1bb711iyxTX19PPp8v9pQSkfVTjyOR7dihhx5KOBxm9uzZ7L///rz44ouYpskRRxyxyevs6Ogo9ozpLhgMcsIJJ3DCCScA8MEHH3D//ffz1FNPcd111/HMM89s8jY3Zu39KbQKFcYZKLj77rsxTZNPPvmERCKxTktTPp/nV7/6FR988AFLly5l+fLlxXUUwk5jYyMjR47Esqwey44ZM6bH70uXLsXzPI488siS+1wYG+q4445j1qxZ/P3vf+fvf/87tbW1HHHEEUyZMkW9jUREZKe06667MnHixG2y7erq6h6/ry9T3H///ZimSSaTobm5mYaGhh6PG4bBvffey/z581m6dClLly4ln88DPTNFVVUVVVVVPZYtlSmAHj2Yuyv0Ctp///0566yz+N///V9ef/11qqqqOPTQQznxxBPXm0cKOjo6KCsr2+A861PINKVuyJLNZouP93a+3jr55JOZOXMmf/nLX3o06PXXMoXj0d7erjvwiWyECkci27FQKMTEiRN54YUX+MEPfsCsWbOYOHFin7+YCxKJBMuWLSuGj1Qqxe9+9zv23HPPdQbb3nPPPbntttuIxWK89NJLtLe3rxPG+ktvW6gOOeQQvv3tb3PRRRdx66239ugG//7773PWWWcVj9mpp57KhAkTWLp0KT/72c+K8+Xz+ZLHb+0uzK7rEo1GufPOO0vuS6Fl0u/3c/vtt7NgwQJmzZrFSy+9xMyZM3n00Ue58sor13sHExEREel/hZ7GGzNu3Dh+8pOfcM4553D99dfzhz/8ofjYihUrOP3000mlUhx66KGccMIJjB8/Hs/z+O53v1ucL5/Pl7wUrHvvJfi80HTPPfescynZ2q699lrOPvtsnn32WV566SWeffZZnnrqKU4//fQeeabU8157XKXeGj58ONA1IPjampqaimMa9Xa+vrjuuus46aSTuO6664rDFvTXMoXj0dv3hMjOTJ8Ske3c0UcfzeLFi/nkk0946aWX+MpXvrLJ6/rHP/6B53lMnjwZ6Ao2f/jDH3jwwQfXu8yuu+6KYRgbDTpbw8UXX8xRRx3FCSecwF/+8pcedza5+eabCQQCPP3009x2221ceOGFHHbYYcTj8R7rqK+vZ8mSJXie12N6Y2Njj99HjBhBMplkr732YuLEiT3+xePx4vX9K1euZN68eYwbN45LL72URx55hDlz5jBq1KgeIVREREQGjnPOOYcDDzyQc845h1deeYWnnnqq+Nidd95Ja2srM2fO5Pbbb+fSSy9l8uTJ64zhU19fT2tr6zp3W12yZEmP30eMGAHAsGHD1skU+Xy+WGhqaWnh9ddfp6GhgfPPP58HH3yQl19+mQMOOIBHHnlknUzT3aBBg9a5xL+3xowZQygU4oMPPugx3bZtPvnkk+J4S72dr6/bPu+881iwYAEPPPBAvy5TOB6DBw/u836J7GxUOBLZzh111FFYlsVNN91EJpNh0qRJm7SepqYmbr/9durq6jjxxBOBrgG4TzjhBN58803+9re/rbNMR0cHzz77LBMnTiw5EOK2Mn36dMLhMD/96U+L3cYLl+B1v+wtHo8X77xR6KL+la98hfb29h6X3rmuy0MPPdRjG4XjfM899/SYPnv2bC677LLi3U1++9vfcs455/S4fn7o0KHU1dWphUtERGSAu+SSSxg2bBg33ngjsVgM6MoU4XC42MMGusY4KmSF7pnCdV3+/Oc/91jnn/70px6/H3XUUQD87ne/69Fw9dFHH3HxxRfzxz/+Eei60cc555zDe++9V5ynurqaXXbZBcMwNpgrhg8f3uu7mq0tGAxyxBFH8Mwzz9Da2lqc/thjj5FKpfjqV7/ap/n66uKLL6a+vp45c+b06zKrV68mEAgwaNCgTdovkZ2JLlUT2c5VV1dzwAEH8Morr/ClL32pV5eLPf/888X5stksixcv5vHHHyebzXLffff16D00ffp0/vWvf/GjH/2IJ554gsMOO4yysjKWLl3KzJkzyefz/OQnP+nVvs6YMYOnn356nemHHHLIOoNVbo66ujouvfRSbr75ZmbMmMEFF1zA4Ycfzn333cfll1/OoYceSnNzM48++mhxMMzCnUCmTJnCQw89xI9+9CPmz5/PqFGjePbZZ3n33XeBzy+bO+KII5g8eTL3338/y5cvZ+LEiaxYsYI//elPDB8+nGnTpgFw5pln8re//Y0zzzyT008/ncrKSubOncsbb7zBZZdd1m/PWUREZEv51a9+VfIy7uOPP77Hbdx7+z3/zjvvrDOWYHdf/vKXN9oL5LHHHiveHKS78ePH881vfnODy/ZFJBJh+vTpXH755dx666387Gc/4/DDD2f27NlceOGFHHfcccTjcR5//PHiWEWFTPHlL3+Zo446ittuu43PPvuMvffem9dee42XX34Z+DxT7L777px11lk8+OCDdHR0cPTRR9PR0cH//u//Eo1GufzyywH4+te/zowZM7jooov45je/SV1dHe+//z6PP/44U6ZM2eBQBQcffDC33347sViMioqKPh+Hyy+/nJdeeokzzzyTs846izVr1jBjxgyOOuqoHu+B3s7XF8FgkJ/85CfrDCq+ucu8++67HHjggb26s5zIzk6FI5EdwOTJk3nzzTfXGYdofW688cbiz9FolGHDhjFp0iTOP/98Ro8e3WPempoaZs6cyf/8z//wwgsvcNddd5FOpxkyZAjHHHMMF110EUOGDOnVdtfX6hMMBvu1cATw7W9/m8cee4y77rqL448/nu9973s4jsPf//535syZw5AhQ5g4cSLnnnsuX/3qV5k7dy5f+cpX8Pv9/P73v+eWW27hiSeeIJvN8uUvf5mf/vSnTJ8+vTjWkWEY/OY3v+H3v/89jz/+OHPmzKGmpoZjjjmGyy+/vBh4x40bx4wZM7jrrru4//77SSQSjBo1iv/3//4fZ555Zr8+ZxERkS2h+2Va3Y0ZM6ZHMaC33/MPP/wwDz/88Hq398ADD2y0cPTmm2+WvKvr5MmT+7VwBF03ujj00EN55JFHmDJlClOnTiUWi/GXv/yFG264gcGDB7Pvvvty5513MnXqVObOncs555wDdBXdfvWrX/H000/z1FNPsd9++/HLX/6SSy65pMf4iddccw1jxozhoYce4qabbqK8vJwDDzyQyy+/vHhH2CFDhvDAAw9w++2389BDD9HR0cGIESO49NJLN1pUOfzww/nNb37DW2+9Vezh1Bdjx47lj3/8IzfffDM33XQTVVVVfPOb3+SKK67YpPn66vDDD+fYY4/l2Wef7ZdlYrEYCxcu5Ic//OFm7ZfIzsLw1h7IQ0RkJ9bR0UE0Gl2n9enZZ5/lsssu43/+5382ucVMREREdh7xeJxAILDOYNjvv/8+p556Kr/4xS/4j//4j622P1OmTGHs2LG9vr39juyRRx7hhhtuYPbs2RrjSKQXNMCGiEg3DzzwAPvuuy+rV6/uMf3pp5/G5/MxYcKEbbRnIiIisj157rnn2HfffXn77bd7TC9czveFL3xhq+7Pd77zHZ5//vl1BuveGT3++OOcfPLJKhqJ9JJ6HImIdLNw4UKmTJlCQ0MDp512GqFQiFdffZXnnnuOiy++eLO7WouIiMjOoa2tjeOOO45wOMyZZ55JVVUV77zzDjNnzuTEE0/klltu2ar74zgOp556KsceeywXX3zxVt32QDJv3jzOP/98nn766R4DnIvI+qlwJCKylnfffZc777yT999/n3Q6zahRozjjjDM47bTTtvWuiYiIyHZk0aJF3HHHHcybN49YLMaIESOYMmUK06ZN2+AA4VvKe++9x/nnn8+sWbMoLy/f6tsfCM466ywmT55cHIdKRDZOhSMRERERERERESlJYxyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJKhyJiIiIiIiIiEhJvm29AyKbyvM8HMchn8+Ty+UwDAOg+P+Gfl7fY57nAWCa5jqPrb381pq2oekiIiKyc1H+ERGRrU2FI9nuuK6L4zg4jlMMTwWe5xXDz4asb57Ozk4Mw6CioqLkvGsHGM/z+j3UZLNZXNclHA6X3MaGAmCpaX0Nj4ZhFI9jIUAahtGnUKfwKCIi0r+Uf5R/RES2FRWOZLvgeR6u62LbNq7rAl1fpKZp4rpu8Yt9c79cC0HBsqzN3udNVWhFLCsrA9Yf8kopzLs54REgl8vR3t5OXV3dOvNujfBY0NnZSWVl5QbDY2+C1qaEx4LurbCbG/QUHkVEpC+Uf3pH+YeNzqP8IyKbQ4UjGdDWbl3rr4C0PenLc+2v42JZFoZhbNMACRCPx6mpqdkm4bEgFovheV6PVtitER7XXmchRJbah96Er80Jj90fU3gUEdnylH+Uf5R/uij/bHi6yNaiwpEMOBtqXdvSCt2UpW8tfVvatgiPBaZp4nkePt+2PV3G43Gqq6t7NW9vL1kozNvb+fL5PG1tbdTV1W2T8Fj4PZ/PY9s2kUik+FhfwuPGLnfY2HxbKjy2t7cTCAQoLy8vuS4R2bEp/wwMA+k4KP8o/3T/XflHtiUVjmTAUOva5wZSaJGBo7efhS31mSl8LrdViCx8LvL5PNlslmg0usF5t0R47C6ZTOI4TrEldHPD4zXXXMMee+zBFVdcscnrEJHtj/LP55R/pBTlH+Uf2fZUOJJtqtC6lkgk8DyPYDC4Sa1r/VntV2iR7vR++Ny2PhZrdynf0Gd+a/zBVdiH/rqkIZlMksvl+mVdIjKwKf/IQKf3w+e29bFQ/pGBQIUj2SbWbl1LJpMYhlG8k8a2MhBa9wbCPoisz0B5fw6E/ejvIOm67ja/JEBEtizln4G9DyLrM1DenwNhP5R/dk56hWSr2dC1+wPhJCgi0lf9ee5yHGerjGUiIluX8o+I7GiUf3Y+KhzJFtfba/e3dTfQgoGwH9t6HxRkZSDb1p+Pgv7eD8dx1OImsgNR/tn+9kH5Rwaybf35KFD+2TnpFZItoq93BtHdPEQGvoH0GR0o4V4tbiLSnfKPyI5nIH1GlX9kW1HhSPqV53nYtl1sXYOND+I2kGwv+ymyregz8rn+vgWv67r9NtCkiGxdyj8iOzZ9Rj6n/LNzUuFINlv31rW2tjb8fj9lZWWbdGcQGThfTHo9ZKAaSO/N/m5xU3AS2X4o//Qv5R+RDRtI703ln52PCkeyyUq1rtm2jWVZfT6ZDJSwAAPrpCwykAykz8ZAOGforiIiOyflH5Gdy0D6bAyEc4byz85Jr5D0ycau3d+ck9mmnoQKAa773Um6dw/vyz4NhJMxDKwvKBHZOgrnMREZeJR/tg7lH5Gdj/LP9kGFI+mV3l67v6mDPG5KYMlms7S1tZFIJHp0byxs3/O8Pu+L67q4rksymSzu19oBbO1pm/v42tOy2Sz5fJ5UKrXZ25H+oWP5uYFwLAbSHxa6xl9kx6b8o/yzM9Ox/NxAOBbKP7ItqXAk69XXO4N0X25Tt9ebeRKJBK2trXiex6BBg6itre23SnUikSCdTjN48OCSAWztn3s7be2fN7RMLpcjn8+TSCQ2a5ubohDACvuxfPnyzQ6CvQ14peZzXZdsNtvrbXb/X3ZsA+F13hK3o1VwEtn2lH+Uf5R/ZKAaCK+z8s/OSYUjWcfm3BlkU09mG1vOcRza29vp6OggEokwdOhQQqFQ8bH+VHiu2+rEnEqlSCaT1NbWbtXtdg9e+Xye5uZmhg4d2qdQuLFphTDe23UWXve+hNO+WjuMeR6Y5ufT8vk8hmGQTqd7zFfq595O25THC5/LDc23pQ2Uli7P69+7eQyU/VCLm8i2pfyj/KP8o/xTivLPlt0P5Z/tgwpHAnzeuuY4DplMhpaWFoYPH75VrzctdVLOZDK0traSTqeprq5m9OjRW/TEMhBOxttK9y/iwgCf23qgukwmw9ChQ4u/ex54LpgW2BlY845JPmlQNcalanTP90+q2WDBX310LjXwhWCXI22G7OMSrKTb+j4PXivmmix4zI/neQw7yGHsV3MYPlj1cRLXMSjfNYQV3LTWz0KLted5eC44eY9Mu4lhegRrHAxj4620tm2zevXq9W6nrzYl9DmOQy6Xo7m5uV+DYl+X2ZznPZCpxU1k61P+6aL8o/yj/KP8s60o/2wfVDjayZVqXYOuD/CmhohNOaF135bnecRiMdra2jBNk5qaGoYPH75TtSoMhH0YaFbNM1n4Nx9uHmr3cUiuNkmuMjH9Hp89azH+DJuh+7o4eYgvM/g9xEq/AAAgAElEQVTXDD+eC20fm6RaDJa9YlE/0eEL5+VxctA4x6LjU5NQlUd0mMc79/rxhcH0Qz5m4fObZDtNVrztx7BgWXmAQXs6+IIw7ACXiobPX6O2hQaZdoPwII+qMR6l3qqeB0uet/jsOYuWD01CVVBe7zJ0f5dxp9qYG/m+bGxsZOTIkf1yLPvSetr9sWw2i+d5RCKRDS7T/V9vt9OXll3btgHo7Ozs83PfUEArFdY2NF86nca27WKr7IbWs76fPc9j2bJlGIZBIBAgFouxZs0aLMvCsiyCwWDxeItI/1H+WddAyB4DYR8GGuUf5Z/Cz8o/si2pcLQT6l7BL3RzNozPr903TXOzqvibynEcmpqaiMVilJWVMWLECAKBwCavT7ZPiVUGn82ysNMG3rAwDQ3QucTgo0f8lA11sfyw5HkfuTjscmRXS1Y+BYuf8VEzNsf83/lp+8Sk+T2z2LpWPtIj22EQW24w67IgTtYg1QxDv5Qllckxb4afjNfM8s4FBH0RJqT3ActPIGIQHWnjpEwaZ1s0vWsyaILL8ld9HPDdHFWjPT590mLJCz5c16N9oUWg3GPwBJc9z7Cp2d0tPq/V80w++4dFJmbguQapFo/ykV2BsHpXk6H7u6UOxxaxOV28c7kc0Wi0v3epT9ra2vD5fFRUVPR6mY2FwlI/b+zxTCaDZVnFc2fh8bUvR9jQOuPxOPfffz+5XA7DMHjqqaeYO3cujuNg2zY+n4+77rqreC7M5/P8+Mc/ZsWKFeRyOS6++GImT55cfJ6zZ8/mrrvuwufzceqpp3Laaaf1/sCK7OCUf2Qg60v+GXlYnryTx8kYfPykQWRElnf+4KdtAaz4VwrKEtieQ7DCxY6bZD+G986DXDpPvDmNf/fVxO0VzH9pCUt5k0bepIJR/MeoH7F7+25EyiJE6lx8dpTFz1VQ9pbJoD3gkzkG+12Qp3p0V+5a+k8/rgudn1oEys2u/DPVYdA4r1goWPV/JoueMcjGwHUg2az8s6mUf5R/tiUVjnYipVrXuld/1553c7bTF6lUipaWFrLZLEOGDGHMmDHb7JaMO3NX7bVti1a/2AqDuf8dwPJDoMKj+Y1qBleZ2GmDbHvX65NqNkisNMh0GEBX2DD9kE/Ap3/3EV9hUDbSoX2xQWwlBMpdCNtkM9D5nosRTpPp9Mi5SVb9zSKfdwim6shbAbJODsOL0PyRS2x1mkF7ONRV5en8NEqq2SDdYoAJVaM9lr5oEaywaZzjo7zBpWm+hZ0BJ2fg2jD/d34OviqHYXZ1L2/7pKuQFV9p4I96uHlItxqUDfdItWwf77uB1BLc18/q5oTF9clkMkSj0c1qEaurq+O///u/AZg0aRJXXnklxx9//Hrnf+KJJ6iqquKWW26hvb2dKVOmFINTPp/nxhtv5NFHHyUcDvPNb36To446aquPFyIy0Cj/bJzyz+cGYv6JZzuIr8mTWmPS3t5Jamw7YX8YHD+pjjztM3IsmZ/CDXWy3LbJfJYnZ3XiVbSR6MiS/LSdrL+TRKKDjtwaUss7yBInTQrIAw4ZYP6SOSxs/j9GDhvBoN1DBFfXk1hRgbcS6jO11DT4eecpm/ojM7z9ZJjwkCwtH/rIxgK4MZv04ByLb/LY8+wULi6O47FiLrR35mlZnKcqMBzHgcrWPZV/NpHyj/LPtqLC0Q5uY61rpWzOiaXQ9XBjXNels7OT9vZ2fD4f5eXlBINBampqNnnbO4qdNbwlVhm89OMALe+b+Mtg8J4uuXaTOdODOBnIxg3crEE+DZbfw7UNFj0Pg/dJE1vlkh35Ia/9KcmaZZ18tGg+I0L7snv4SKzOEGYsiVvdjNs8lMyQBZix4ZjJavypKoKmC6aJ4Rg0+L+EzwjiYhOuT9D6YSUJmrEXRXCSHuXDXbJxWP22Qc3uBnbWwDC7xhxIrDIIVUM2Br5QVyHr7bt9pJr+/VnzwFfmEarx6PzMxAOsoIedhrKhAyeQbMzO+v4spb+DZG+u8T/uuOM49thji793n3/RokU0NDRQWdnV1e6AAw5g3rx5GwxiIjsq5Z/tz876/dI9/xDOEd61jXhzjr//sIp82qWjo53O9Bq8bBjHSOB6NvmXXcK7r6JlVTvWyDUse66V1tZVZOwUuRTEO7J4ePjjFr6wTXs8ixnsJJFLk8MBLIIMpZIqApRRx0gqGUqeHIHqBJ98+h5lOT9m20pIhCmvDtG5vALfSh/DPJfloRyfrfZjpDPEl5QzqGo4Xspi18qx5B2Lpn+YZFos8k4Ox85SUWZQ1RDEW12LGfBjBVH+2Y4p/+ycVDjaQXmeV+zqt7HWtfUtvznbXp98Pk9bWxuxWIyKigrq6+vx+/0kk0ny+fwmb7M/DYRWhYGwD1tDPgnLXrFIt8HSf1o0f9TVo8iXhGSLieMFCZU7uCbkUgZOysL0gYuDUZNg2VyLf3XMYoX7FssXvcKw9iMpb98XgFb3E9aYg0iFllHeuTuBzihBM4Zn2QSMCGa2AhcT281jk8EwbYJeGWZ1EmP0UnJVWWrDVSTW1OFmDcxwDtu0MRwLO+4n3JDEiDr4Kw0SqyzMAGTaIFTtYYW6ehYlV5vU7tN1zX/7IhOnHYJVHobp4ebAF/aoP9yhdq+t1017RzCQPh/9GSR7E5wK3eQTiQSXXXYZV1xxRfGxRCJBeXl5j3kLt7UW2Vko/2y6gXBuHQj7sDUU8k+qxeOzf8LKD3K0r0qQDKwgtzyJa+bwhSCZbmdRxycsZh4GLqaXxyVO9l8ZwktymKEcgWaXbLuJlwgSLgtiWgG8oIcXzNAWS5HP5XFx8WU9LCJEKcNHCBewMIkSIUWMcLCMYH2KkcNHUuNvoK2jlUQihg8Xn1XBoFADwVwtRx4TZsRBHm80OuTiLu2DwmRSaapqK6ipHsTKhRBrTVE9IY/PCpJeNgi/GyBca9DWauLkwBd2lX82wUD6fCj/7HxUONqBdG9d6+joAKCioqLP3Z43t8Wt1H6lUilaW1uxbZuamhrGjh27zbpjb4haE/pf4X2Z7nBZ/baFk/Oo3iOPvyLP/90aIdZogOWwck4AM2yD3yWT8HASFjlslrhL8bDxE6GcEbheFhybvBPD50RZEHmYquEBDh76RXy4LJm5hHGBL+G5HqvLZjMucCz+xBhyJEjbccxPhuPPlWN6LgYOLh42GVxfHMfIko8uoDpi0tmZxvKtYrdTgrTOj+ILu8RXmHiuib82y7K3sqyZF6F6jE2yxaZspEus0SI61CO21CQ82MMKUhwoMjzIJTLYY7eTHDwPgpUugSgEyjd8/AaSHTWwbKr+Ph6u6/bqTj6rVq3iu9/9LmeccQYnnnhicXpZWRnJZLL4ezKZ7BGkRHZUyj+bbyCcU3c0juPgui7JVpuVb0Eul6dy1xxWNMdrv3ZpWZLBJsGil5Ok/S2sznxIGyuJ00obi4nzEVDqeyaCSZjBwSAVFRFCoQj+Wo+cESAdz+OQIFhpkm7vmreCIBYh/ATJ4uLh4WITIECEWmr8VaTzaWpG+3GDYNsZrHIYu2eE9NJacmacfHuCmLWEipoki+YNYvHcIBUjfXhBj2DCxlhRhjEoxjvzV2CTx/BDZ3OevUceRrAu8O/8Yyv/9IOB8FlV/tk5qXC0AyjVula4jn9TTi697W69sWVd16Wjo4P29naCwSC1tbWEw+F+36ZsO90Hwiv8X7hlaS5ts+xlH8lVBkY0x6o55eTi/x5fwucw+PAmWj4eilHdSSqZJpfbDS9hkTXimG4AP1HATxUNuDg45LDwYbk+cA18bhmemWefj3+BP/Qx/lGf8urbs0iOTGJX1JPJprCW7I7x6Xjy/hSmESLqlYHfwcLA8mWxk0FMTEJUYeTLscva8KXqSSxrxrYNlvoXsrrlDfbe72iyb+1BsNrFzXvkYhYt80NY4Twr3/Yz6pg8R9+RJ9Nq0rkcTL9Nao2PT2dGcF0P0zTJxkyGfynfY8Bske4cx9noH5QtLS2ce+65/OQnP+GQQw7p8djYsWNpbGyko6ODSCTCvHnzmDZt2pbcZZFtSvlHtoVC5rFtu/h/Pp8nk8mQSqVIxNIsfiVNvCmPG0izdK5DKp7D9bLkyFA2vpVlb+fI+dtoSa5gtRMj5cRwSJDHputisiY+LxrVEKEa8OHHj4ODgYXX7JDPm1Bv4fO7hOpdbNsg4IuSbvWTarIIYv27TAQGeQwCBAhgUEGUSoJEMPNRaoIu4Y4hWINrsWIByqst6vZtp7M6S+LjOowhBulMirbEaha8lWFo1ShWfBhn9EQfE6f7yCViuO0RyquGk27xs/iJMEPqIwT8ATpXK//Ihin/bB9UONpObezafcMwcN1tc4LO5/OsWrWKZDJJZWUlu+yyS6+qyAPF9hzg2vIe8+Iea7IuY0KwX4VFxNq08Oy6bjGA27Zd/FcI6blcDtd1yeVyxdBUeNzAZPlDuxD7KEKuzU9qaRjPMCjbJUN4bCvx5jwfPZEn2f4ZnUuWkuu0GJ4djYmF4fnxE8Ulh00SEz9+Qlj4SVvNhJ3BgAF4eFYWs2MwibljaJ3r8EHgU8JVJulMGsdxODh7Pp6ZJxD2EczV4qYC/x5P28PJ23h4mPjAcEhWLiYR+ZTh4QlUjvWRq1/A0uxbtHW2kbMeZfcvfRE3HiHZbJD8bAyrly8gagxmpO8g5v8yTOuSNew5LcWQCZVEIhHsnEu8Mc/qeRYYDjXjcjRMzuO61oBsbe6tHbGla1Nt6h+n61uX4zgbPVf+9re/JRaLcffdd3P33XcD8I1vfIN0Os3pp5/O9OnTmTZtGp7nceqpp1JXV9cv+ycyUCj/bDkD5dy6Kfor/0DX65jNZov/p9NpUqkUuVyOTCZDIpEglUqRz+dxHIdsNlssIBmYfDYrSNtCyHY4tK/K4ZHHPyiFN6SFdDKF83qGTDaHL+ph5cLUMpI8HjFWkqIJkzge5Zj4qKaeIOWUESVFmgStZOnAI4+HR6rDJtORpWYPo7g/Scchtswii4GfEB4+wgzGxoeJi4GJgUeGOAYOXrSZwBCT1YlWfF6asro06SqHZe8micfj5AyDdDxFc1MLK1vbcWkDGjglfBWdCyfgy5ZzwHf8BEeZ+HwGkb1DGM1Rmt8JkjNg8B4OY45z+vcF3waUfz6n/LNz2n6+zQTo/bX7W2OAx7X3K5FI0NzcjOM4DB06lKFDh/ZpP/qjlW9H0JdxGBzAZxi4nseTLQ6/W+GyJgcVPqgLwGEJOG+ERdA0eizX/X20dlGoEIJWr15NNpsll8sB9LjFJnTdttg0TQKBAJFIhGAwiN/vJxgMEl/mY8myCL5whliLhW2lcZMBmj9LklnVSdy/hJTdgZfzg+Mjag/GMXNdYw1ZBuQ9MCFrNWPgJ5wfQiq0lJXW/9FgH4Xj5Ik6w8hbCUw3RM6MEcxWs9ugQ3GHL6GivAIrMYjyRDVmNAvxWhzbhwFggOt1PR870E7AqcapaMZf34LTbNOaXUZZC7Tt8jot8SZWrVrFe++9x4u8iG3bhGIN7NXyXVozLYxmH9rKYoT8UVbN85PPBqk/6yOi0ShVVVXs8a0qxk0Jg2cQqMrjeg6pVBbDMPD5fFiWhWVZAyKMbG8GyjHrr/0o/KG7saLitddey7XXXrvexydNmsSkSZP6ZZ9EBhLln3Up//Qt/xTeP5lMhmw2SyaTIZ1Ok8vlSKfTJJNdhZKWlhbKysqK5+XuhUmfz4fP5yMSiVBRUVFsOCvkpc4VOdoW29hGiuaWOGbQJJeFfMwmYIUZPmwkkaifADVYTojlKz7jMxbRzgJitOGnmgiVQI4w5ZiYBKw81K4mt9rGI8W/75FFlhgBLHLkaFvjYIa6GvTCwSiGZxElCpTjJwT4CFGJjxAWBpAgi4tjdkB5jIxTgefPkIvncOpayDXlaG9vx3VdstksqVSKTC4H2EAYCLCS9+nIrSE7ewyd8QaOvXoIoVAIF5tdT4/RcKyFafqoHOrD59/w+DXSe8o/pSn/bHkqHG0H1v5DHz4PS+v70G6tMOE4Du3t7cWugVVVVTiOUxzVvrc29+TTXyevgXIyLvXadQ9KHyZc/tbqknFhXNjAZ3rF0ITrkLYdOlyDdxyXN5wUY3z5HgUi+PxEXehy3X27ruuSSCSoqqoiGAwWg1L3YofP5yu+z1KpFG1tbSxfvpyVK1ey+oM89oIjcDMGvsQwXPIE3MFk8xnMbDXV3hDC/hZahs4hEg0T7RiBl2zHG7yGoFuLtyyCa7v4vAh+uwLHyJIlgWWXkfE6KGckrmXjM4NYPj++chu/L8qYMWOo+sJgwu8ehbFoHKYTglwFtufgeS42ua6BtbEwMHDxyAfbyNtJcqtMfPkaco7Fiuh7NC9dWvyDwDAMKioqaGhoYJcRY2h+OElD6wFE7WpwHKhtJWG0kX6jBuvI1UQrwsU75kSjUWpqaijPlRMIBAgGg8VjXei1ZZpm8fgO5N5IA+UPlB1xPwqfwe2pd4LIlqb8s+WX7+/1bK7NyT+eY2N1dLA6H+N1y2HkSoehpItFoWw229Uruttz7d4IFggEimNjFQYv9/l8PXpXp9NpEokEHR0d5PN5PM8rNgD5/X6CgQiVgSiWHcRXZuNaGVqzHQwrG0nOzuAs9AgOrsS39ycsXP0Sn8YXkyZLMOowwhtFLJUiR4pKavEIkKUDx8nh7zSAEBZhDPxY2Jj4CAUccAIMHRlixO7VtC8I0rHEIee5ZMnjkCNLCpsYfgzAJU2aIOAngGM5eBmLdC6HzwgxqLaM6qE+AoFAVxEqHC4OWpzN5En/q4HyjvHYTRFi+TUYgxMkw5/x8quL4B817DKqnl122YWamhoCVQFM0yWdyWFkjeLx3NggyAPRjpg7Nofyz85Jr9AA1/2PS+jbnUE2VW9CVyaToa2tjVQqRVVVFaNHj8ayLOLxOKlUapO2uyOeDPvLR0mXJ1tcsq5H0DRozLjsGjaoDRh8mPT4MOmSiXXQmcjR2bQaI1xGlZdlTTZGoOlddgvYVFRUFAtB5eXl+P1+/H4/4XCYSCSC3+8nEAjg9/sxDINQKERDQ0NxHwzDKPZGamlpYcWKFTQ1NbFixQpaWlpIp9NkMhkymQxW+1BGxidhpivANvAwSQVW4neiBJwasFxCXpSq5eeRLm/ErmzCitpYbg05J0MysACfV07EHo6HTdbfSpU3msHuBDDAs1zykVZ8mQpSkaX47TL8gx3sUTE6PijDeWsknd7HuJ5DmT2SsFuHA2ToxEeQEFXkSdJpfUbUrSOS2oVIfFc8M0fGbGdF+YNUVlYyduxYxo8fj+M4RKNRPM/jgw/+RWqXt9hnxHn4P6knFVyOHUpSYw7B9uVZuWYFFelyKisrCYVC5HJdrXamaVJdXV2cbllWMUQVLrsohNBCsCoU52THV7jkZiAXDkW2JuWfrW+g7Ed3G8s/78Xy0NlJrrERM9ZEUzJLddggHDBZHjMIVoQIhUIMHjyYSCTS4/u1e6/fwvdwOp0mm82STCZJJBKk02ny+TyWZRUbf/x+P7W1tViWVSwcRSIRwuEwqfIwcV+UXGeIsD8Dpkf18NW0xJeSiNtkaGXB0hdpXvoZedZgBf89zmI2T9JtIkccP2XE6cQlh4mDQ5RMGjzSXQ1xeNgEKA9HCFhhDL9Dea1H27IMTQtz+KMmRtDG7kiSd2xMQkQJYuDDR4gQEaJVYOXLyCQN6PATpYzyYDV7H57GqkoUM0khDwYCAUaNGkXFCYNo/EeExc8EqG+oZfexu5PL5Plkxb8Ihj5k8eLFNDY2UlVVxciRI6mrqyMajRIMBjEMo3gHwe25iCT9S/ln+6HC0QBXCEl9DUxbosXN8zzi8Titra0YhsGgQYMYNmzYOvu1KdvVH8frtybn8WiTy2A/LE53XcOfdmBF2mF/K8HSTz9lvltNqGMNZs0IfOVVYPlwbYM64gz3OcRiMWKxGKtWrSqGnmg0SjQa7VE0CofDlJWVYZomzc3NZLNZEokEra2ttLS00NraSnt7O4lEojgoZOFOCIWiUnTFvjS8fRk4FqbrxzNtfJaD6VRjYoEJdjBBPu8RsKsId4wh74Ux7BDp+n+xwnwDX3IXRqaPxzBcDB9UuPUYdohceA25QcuwYz7iZiMLK5+gOr0XWbOdtupXsd/qZFTmGMrwCIWDGBhEBtkE7CRtyU+Jtu+BiUWWDpLBpUQrggQ6o7hmFttIYBkh3ECKoc1Hk9r9Cdra2hg+fDjJZJJoNMobb7zB6tWrOeSQQ8g5L1IWqqBq2e5kmgxyHQGGfmMhbnkZnZ2dxGIxKiu7xjuqrKwkHA7T0dFBLBbD7/dTVVVFOBzG5/NjWWaxK7xpmsUxpIBiwC18sW5rA+WzuqPtR+H1VYubSBflHymVf1I5m0angy+G8jidbTR+soLqfBxfqBq7dhS+kWECQYsJNRbHNwSpCFjFXmuF90bh0rJkMkkqlSIejxfHNAKK3/mDBg0qDmpeGD/Itm18Ph/hcLiYmSKRCJZlseg5i9mXmuSyeXK5HH4rSKexgvZMM60sZQ0fk6KJhcwCHKCSaDaCwSqwcxDKEMxUkieAQZosWUzAII0fHxEzQMiowoy61IwOEMhUEYr4KavPkSdFe0sOwwsQDpYTtcoZWzkYLxsmEPRoWpwmyRrAR2VVEF/YRyZmECZCmBBlDCdaFSDxQYz9z64jkUiQz+dJJBLU19czZswY1qxZgxl0GH+aTdhXRev/lbH8rTwBK8LJVx7EkCNH89lnnxXH+Vq0aBHLli2jrq6OmpoaIpEIoVCISCTy72NqYxj06NE+kA2Uz+qOth/KP9sPvULbgU39YPZXcLJtm/b2djo7O4lGowwfPrx4uc3aNuckMhBaurb1yTjheHTYBt0PRXPOI5lI8Pzrr/NOsI5Q9WDscDmdS1fybstKBsfXMGTUeGqHDWZ1PodtRjAMj3ErP2TXle/whYMPZNSoUWQyGWKxWLH1zLbt4mCPheedSCSIxWJ0dnbS1NSEaZqk02mgqyWg0OJmmmZxPCTXdUmlUl1jBuVtdnv3PDzPgGAGjyxWuhI71EEsvBSzYzBRZxjJZAYfYTwMDM/CF6sDyyW46EAY/Ck1yX2xjSw+N4qZ9+OYGUxcrEwV6c4l2GYMf2oIjYNns9R8md3KD2O3mi9Ru7dLQ3Rvkn8dBOVBMB38mWraAh/yWPpcqs0DGBQdQbziI7LRVXyV3xJ2LZyEhWs6mI5H0Bch4g0h7/fjeR5Na5rJZx0++ugjWlpa2G233QiFQnR0dJDZbR7hhXtguT5sO0/bc6PZZbckNaO6CkfxeLw4YKbnecXeXqZp0rK6gxV/LSP2ziACEYMJ30nScFSuR4HIMIzi65NIJGhvby/2Chvol7VtSQPhXAH9ux+F132gB2eRrUn5Z+sZqPnHtW1WJFLMb/dIJNK0rF5B0Mzxkh1nTBDqB1UzZNieVOBjScrDtCxOHGLyjVoTn52lI9U1oHWhB1FhPEfP8wiHwwSDQYYMGUJZWRmBQIBcLsfy5cuprKwsDoxdGMuxrKyMaDRKIBAo9lYqfA/n8zYv/BAy+SQZo40VfEBzdhE51pCraqGto4M4HTh0Apl/P8MkSUwgB5iUZXxksbFpwwUMAoQJYxEmSISwaRAtK8NwAwwZlcFz01hpP1GqqBo5goZBQT5emcfwpQkHyzGz5YzcrZr9zw6z/K0sjcs8UtYqorU2H8/KkDANfG6UsL8BnxshYpQx2B3BsGEpli9fjmO77LHbBGpqq0gmk4wcORKfz0dVVRXRKTn+/s84XipHOBLm5d96HDHSZdTYUVRVVdHU1EQ8HgegqamJtrY2ysvLGTx4MAFfmA//HKLl/yJEwmH2O89h9KR8cfxHv9+/0+abjRkI5wpQ/tlZqXC0g+qPAJBOp2ltbSWbzVJdXc2YMWN6dSLf3lvctsVJ2fE87lhm82Srh+3CGDPMjTUuyeWf8chzLzHbqaaJEF7dENL5PKaZIVVeS9n/Z+/N4y07yzrf77vmted95nPqnJorlcpEBqYQTBgVFIHuNA7Xa+ttb+tVadFu9CpK06h/wL0I9HVoUIS2pWkVlIAYBpE5kIGkUplrrjp15rPnac3ve//YZ62cigkmIUMF9u/z2Tm7dtbee613v2u9v/U8v+f3GBY5LeDi+z6LPz6HH5tU2zV2NU6zc3qCxIAvfvGLXHnllVxxxRXs3r2bIAhotVrDwIfvU6vVWF9fp9ls4vt+VhoQRVGmlNF1PWs1GwTBsHOIEPi+nymNABy9iJ64oEcoJQkTiQ20Bw02BqewqZFnBpsSGvqwoxkKpI6SGrEYMLF+A13WMZWHyxQSiZJbXdSIsSjgagXalePsnj3I5Sd/m1J7H9apccQdguCaY7gvOkZ8+BBhFNLPr/Llwbu4wXsXM9ZVqEDhJcdRooOxtI8kyaELA11XQ98A06V4TUwjSRg79Sq0215KEil85xbcA3ew0L0EsdJFc7sUbn0jqlMFp8/A2US2CyzdPM7c/1bDcRxs287GtVAoYBhG5gfV+9KlBHdWcad9BnWLb/52haXX17ns/xyQqzwcoIOHjclTJVKaOU09GVIV2dN9Hl0ohAUunGvGU20OOSJOI4zw3WHEf548LiT+UyXCa7ZpLjc5Xu9y8swqVmMdVRxnNZdDTU3ygt3T/PysxYluwOlewCu1PpdrA2j6nF4LsjIy27ZxHIe5uTny+TyO46BpGkqpTFnd6XSytTb1qkrLz9JAxvZmFmlSaDAY0G63WV+uc6IZMlCbLPv3s8F9DPAQBGiDAGUo7HiaAruY5QX0adNnnU1OAi0AejiYREgMwCBHAQ0NEwMLG9cqYMkc1UmHsUqR459XiFqeXjzHCgazz4s5eJ3GudtDZBDAeAvr8i7/9H6X/qpLjgPk9syyP3eAQXONzXiFmIS8WUYGIYOgQ7xjnTNnfJa+arP4uXD3HqAAACAASURBVB2c1hcYvybg8tcVaEUTxIUGwcWb3PJul/ZKglVpMz8/iezbnP17j7G39CiVSjiOw8bGBhsbG5nvV7fbZXNzk/o3Jhgc3kl1Tqe5EfCZXxdc+m90rv53gsK4TRAEmdraNM1nfE4+Gkb8559jxH++/zAKHH2P4slKtaWUdDodgiBgc3OTsbEx8vn84744PNczbs80EqX4clPykZWE27sgFPSl4oFY52tfXGHm3EOUzGlmRMBSeQ5hGBgqoeA10apTXFGp8ObpCZxLb+DIkSPsbddZ3VzNSs127NhBt9vl85//PLfffnvWJSQMQ6JoKKVOlTBpJ7DUy2h1dTWT5wdBkKlf4jjOOmyk2SEhBGW1mwMn34yIbDQMBtRQKGwUIT0AAjrUOQ4IxtnPMBgEAgOBAqURJcMGsl2xQoW92JSGfkTUKLMTGRj09DPcmX8/u87+MLnBLvSwghQJIjYIDu8hinymfvFzrC81+Oq3PsPs2g+yQ70QUewRJzGTtZdh9sAza6hAIBEIaaFZkH/Jaa76RYvkI28k+tLrUCToUrHTfx3qyKvQKwOCMKCYfwlxYweaNNEHFfJejri6TrfmUavVMil2oVAgDEMajQarq6uMj48zPj5O6+QsMtenfc4iXnch0Tj76SrtkybP+51F8hUby7LOMybP5XLZuZ12Oun1erTbbZRSmWeVbdvnBZ6eSlwohOVCwFN5zUqNf0fEaYQRvjuM+M9zA4/Gf3qJ4kE/4d4vLfJivYM26BI31zi12CCMNCIVc2CyTEOazMR9rh+conksYlLTmIRhgMh2yFXLWTm+ZVnD79tKcqWd01LFdNrEIg0UmabJ2toa8/PzaJqWJdJSv6MgCLKytrTsbfN0wDfeN2DVW6HNOjF1DIq42BRNm2KlgG3k6K1HdJMN+rQYUKPFOWBja0QcXKrkGcfCIcEixxgmJoqABJ3A9xDVEPOAydLhHEmjQC9uojPAokjvSEJxEHDg9QYyNrHzguW7dJpnNOYmZ0m0iI07LGpHzqCXBxhUyZHHHhQJtSbm884h9gac/FqZMx+rYmLQJqD1uZhzt0jKkxvoQic/lWPt/oDID4k3LOq+TWV/AqFFuVzOzsGJiQkWFhZYXFyk2WxSqVSQUnLkng7d5DbOPGhRql+FGRU5+nc69ZMR176jTqFon1e+1uv1CMPwWVdaj/jPwxjxn+9PjAJHIwDD2u1Go0Gn06FUKmFZ1nnGyE8Ez+WM2zO9H19qSv6hplgPoZeAJyV6FBCjU8uNYc4dpNvaRHN1dg02qZkmiZvHyY/h9zsUlx5kxwv3UKlUaLfbHDp0iLvuuivzNDp69ChSSlqtFmfPnqVQKFAsFpmcnMy6fQkh6Pf7bGxsEIZhRorCMMR13SyjlgaMoig6z9vI8zziQHJV970Ycowea5TZSYFpIgY8qP81hWSBPNPkmWLAJmvcQ5mdQIBFPhsPiwIDNikbOxhTe4hFDxUnSBJKzNPVlrh3/l2I+RVML6DQnkcmgBIkRGiAlCHy2DRHHvjv3HvfPSwuLvJqdQjdkWiWgS0c9JaLkj45s4Tn1DBw6F76j4y9fJHczjHqrQm0O68DpZB6iNA0ROgiEtCrdfRBiLl0CbK6htabRKIgtjD8EvKiW/B9n7GxMcytcrfUP6rf71Ov11lfX8eUB9B7UyQrY1vSfIXMdegsGpy+JcStxKx/ahI8h9nrfHI3DH0YUnl80rOIOyUKs2AVFFIqTv2TonFcYU4MmHnJBqajZ8on27bPk9U/l3Eh3WSNMm4jjPDcxoj/DPFs8p/1pSV46E70uQWSOOZYq04YtSjiE/S6lAcdwp4PEzsIFJRtjR+YcdkzNywdSxMmqTolDIflaYPBgFqtlpWmpetxqVTCdd3M9DlVEqVJsbShxWAwOC/AlCZlyuUytm0ThiGnT53lpv9yisX1h+jQwMNHkmDgMDXlEA20oT+WV8cz6lgVoGXjkkexC4uDOIxh4jIx5uL1fYLAAzRcqmiYKASuYbPvdR6lnTqaITi+FNONYzQsJAk+LXIUYW2auQUrM+5ebPXoaivcUztK0ZxCqUmioIZseZiFPLaoMP5iyeylA4SeEEuHE1/2aXMSjw4V5iiyi6grsHfGFMxJlm6D/O6IeMlgzr0MOdAJa5L5G3oMBn5Wnp92jD148CC9Xi/zPlpY2Et3SWfpwQ41/SRCauj5CbTFSdoPugxyCff+pSLuSnZdB+Ubhob0mqbhOA6yb5N0LIpzAqsISsHiV3VaJwXFecWuVyToF4ZQ6SnHiP+M8GxiFDj6HsXjybhtb6MeRRHVapV9+/ahaVpWl/xkvneEf461QPKHSwmHe4qSAf96QuPuHny5KckLSa/VwhNFpAAdUJpAKIk0bA7NjrOaGFyJyRE/IQxa2FoOx4yonj7MX526DSkl3W6XQqHAysoKYRhm6qKdO3eya9cu1tfX2djYwDRNarUaKysrWQAoJVRAFijaboAdBAGapjHjv4jLotcR4XFG+wqJPqATP4iW2NiygoFLnilCemgY9NngsPVBav5ZXqXeRZmduIxzCTeioSMQW5ojEECXZRa4llC0MDSTMFK0WKSkz9JnBQ2Ng2d/hW+7v0pxMo/YsYzZsxGxhkCgKZ1Y8wlFj9tvv42zi2fJ5/P0nLOMta4giT2UAFPp4OUhdHFkGaVJ4uoqg6RNHJeGQbRBhEKhpMIwdASABt5g6HegNDAKoOw6ql1EEwL/ojtwDpxFSoO1tTVyuRyapmUd7KrVKuPj43Q6HWovuovowz8G3la5nqZQoUGYCM79zRzx8gTWeIhZiDjxdzmcpTLFX6pj2zab3yxz/CNFhNDQbXjBb3Wo3+1y6tMuugkyFoQnIq78jy3CKKDZbGaS/e3k1zTN52ww6UK41oxq/EcY4cLDiP9cWPhO/Ce6/9t0Dn8FNtvQ65D4Xdh7GSSSpeYSB0ougeVyxaUX0dp7DW65CrZD0TT5mf0OU6bKkl3tdjsrn9/epSlNnDiOk5Xep4mwbrebBZjSYIdpmgwGAyYnJzNzbMuyWP6WyembLcycYMdLQo61TnLn6S9w9+HD3Hu2hUQxIEQRABYWCcUpQa5s03+giPRsppJLSVoGDiGgUyGkxA48mhR0C61RoWwa1FlEw6RQcYlagtgd4Igcy18zGfu3MeVqnp0XaUSnDOxBgCIgIsa1Bcrusbo6TPIZhoFyNJxkgmJuGkMX9DEpcTG18Dh6WEJnjImFLtO7yhSLRSzLYsmUBAwwsCmJHUQqIMQjr3Rymk+sFKYtKe8yCZo14gQOvC5h/PkSKY0saba9xF7TNObn5/E8j+RNTb7wq+AwTSFZICEiieqs9k/xhT/Wic5MMT5bxikq7v9kwsSmy85fHzYQeeizIXd9MEbgYdsON7xd0DyS59hNJpoBMoKV2xKu+50Q8dyjNo8LF8K1ZsR/vj8xChx9D+OxTupUgZIa7Y6Pj2dlNU/n9z5d73uq8VTvxyBRvPVEzDdaEEjQBHypIbnKiZCtJsfD4XeKXILAQAodHYGuwUTBpuxYrDY9xmKP5x/7Gif0MoNel31RA9Gpc/j0aXq9HhMTE8zPz2fKEtM0ieOYxcXFzFy52+3SarUQQmDbdtbBK32k/kXpIw00zGpX8YrmH1FJ9iEJiQm5il+izSIxPp/lPwCCHJNIYhQStgJCk94LWOZeZrmGHquYlkGkNNyogk8HlyoKRZ9NhAaGzKFFBokeEOsNZpLn0TLvJ0wiDN3ADHNom7MEpWXa87dSVfspP/CDGIlLpPeINY9v5/6A02dOZybepyc+wXh0CUV/HwBSDxCJSZLEaJqOlJL2smTJfIh6vT4sT9hRorT5BrTYQsYaugCjFCB1k6RnI0pttNDBykGiB2iVOuLl91KrD8vUSqUSpmlSLBazznRRFGW+REV3lkbeQyLBc1B6TLJUAk3ir1vosU2vFlN372XnrgWCb0/S6x0jaJgc+/AkRjFGMxXxQPDN/5KDRCM37aEZAiE0lr5lcGDJYvyATbVaBcgIdkqU005u6XwxDCPLvj5aMOlCOUcvJDxVBC6Vao+6iowwwnePEf95cngm+M8XNkL2Hf0qzVu+wMbiaQg8iGIQGlSrcPYB6Hcp7tjJoTf+JN78Id600+EiW/LNTQ8ZeFzpeEQbNRa31EDpvuu6Ti6Xy7z/NE3LyvJbrRbLy8vDbmdb651pmpk5dhogklLiui4zMzMAbNwDn/1Fm+YJAUaER4Nvvu9DnOaLDNigPK7Rx0GhY+IANiCxmWDMGOfglWUevCNHuZzgJW283iqSEi458kxi4ZLDITF69JMevWjoGZlzHZqtPlY5IEn6dLUOciA49WDErksqVC4uMFcrsPK1AhE58hg4Luz/0YjcRC9TONt7A5bPrdPdGJCokC59erTpscpubmCKvfTaY8xvJbhyuRxXvqbIsb8ooEILDQOpTApTkkpOEHShMheQBAmGowirq5QmNeZ/RNJq6ed5QaXJqVT9lK5zjl4mV46IVAu/peO4OcTZ3eRI6NUaNII1Vpsn2XFJlUK+yso3DbrdLoO64LY/yVOo5LAcjUG3x2ffHpNEDcozDrbh4hg5lr9l0TotqO576ubzhXKOXkgY8Z/vP4x+oe9RPNrJnPqs9HpD47pdu3Y95Sfpk72IXAjRc3h69uNIT3FrG0IFpgahHJpG31vrUGnX6U3uRgoNXSkMTZITCVESgdBx4wGH6z3idoPV+z9La/EUca/HZLnMwLaZnJykWCzSbDYzg+v0Auy6LmEY0uv1KBaL2f5YlpX5FqVt3uM4zgIFhmGgCT1b7PEdbmi+l4LcgSRCYGDjIIkwcVFawmu193Jf7s+5rvP76FgoJL5WQ9c1dkws0DUOYazqOCKHSQ6lx/SjGiG9re0TQrpU5O6toBPoiUuB+S0fJRslwNANjKTIC9q/iXnYpVG6i7v3foDg0v9KtXUVunLY7J+BjTJ71OsxsLio9yOEtR6HZ/4bPRrs6ryeq+JfBiAmxEs2sW2XTqNHd6xDq9UaGk3nHuLiS3TcEy8CkcAVR7Abe0g2q0SFJeJXf4GSdwC1vAtR7mO+8CHKk0W6vk2322V5eTnLdBaLRaIoypRcYRhiru1jzr+MwGpiJOOYURFL2iQqQRcWoGOpItZgivpGC2UE3HTTTcyKK9F6s+RchaXZWAWDwaoOAhKVoJKhbDvw4cydPXzdI1c1s+CQadjEG0VMXcOdDYmTMOuyF4Yhg8EgOxdSYp2S7KfrHHmiuFAI3CjjNsIIFx5G/OfJ4enkP421ZVg+Aa0a3HozR88eHa6rpguaBYUqCAGmBXMXIa5/HS+6eIFBkuD268y1FJomeYmUKENBDLFSGIaB4zjD5JsQmWK62WwShmHWCdY0TRzHYXp6GsdxzlvPUs/ArENsovB9H8/z8JqKm/4vg/rxHjV1jk8mf0iHv9l2hDn8eoHxsoD2DA5VXKroSApGlarrogJFX3TRFSQeFJxp8E2quWnUwEXHwqwkBK0SGhE6Co8+jlcmh0shFyGlj47FIEyI7qhx/DaD0j7Jrld0mXmxRndRJ/RjhBmyfDaCRUUSRTRO5JG6RmlvC31Hj3NHGzT7bQKaQI8cNm7BxPcC6vV6Vg5vXGTivtpm9VYbUzPZ/UoN/2yB5RWd8ixc/R+he1Zj80Gdwrhi7gaftUaMrA35W+pNlCYy02RUWrrW7xqYjsXkAZvmSp9+r86mdwoTh3wwxQT7COOAwdoGg7HTJFqfEyeKyPUS/ahMHG8QdSJsPYcaVDE0i1B5dPrrSBEhu1VO3VVgX9HCKWlZkgyl0TunIzRBaadCe4LL7YVwro74zwjPJkaBo+9RpIuhUirLOkgpGRsbY3p6+mm9+D3ZGv8L5WL4ZBErxRfqkrO+ZK+r8erqcKFa9iUKiGWMnyhiBAiNGEGrMkM+9ol1k7HeJj3dZnb5frTVM8wmXTZzE9Cqs2vjBIPEp9Vqndf1bG1tLfMcSpKEzc3NTGXjui75fB7TNPF9f7hY9/tEUZS1mFVbxCslTvPxD/AK7z0U5TyKhBXu5Nt8YKiEIkZDRw2tpIHh75YIj5ya5GzxZmIVcp33nwGBJg3sqMqe9R9nFzcSGR3GwkNbZtiCrljhg+pq8naJi/QfZiq5nEPRT2DLMiCQJOhYbBr34IZjWMpFiw3spIpQOonwmWu+CvdshXNX/gly+hiNkyYvrv8BhsphkcOiQF+uIYTOvuXXsuncxUR0JYnhYcR5TFxikSNSAzasw6ydPp11A8nn87QuuZnGxZ/B87xhidcum1arNTRQfShgfv5enN3O8Hw6AbmVXPZ76LqeeSvk83mKxWJGmoQQaHMN9JMx5WQWrRgjvRhaAUZiIrUQIg2hdKpiN7G2TP+Fn8KyLFYaxyh3r2eQRJiuwJAFbMvCNA0ah0uYJYkMIWzrPPiBCY79D8llbz3H2MEEFRjc99452sdtFIrxy+DFvx1gF+zMBPSR52EURdlc6Xa7Wend9nbEzwYuBAIHoxr/EUa40DDiP888Hov/HD55lo3/9Xfw2Y9CvQ6WBN0E1wF3DIoTYDuMjU/h79rPa5//fOaLJtfM5nioX8cRkmurGnYk8be6naUl9CnvSRNf24NEaclVilTtkiqvt5fmp/5Hi7cmfPM90F4NiFQfd/9JJl9Y5/BKk4Zap8ESEWe3PnGGEuNMMI7DFC94fYH+kkP9KxNYhoMlCiShRXhY59ThHnm7Q9DRqVBGJgrLjbnx/TMM+gPaDxXwl23Wv1Kl3evSYYVx9qNIGNuloXULhMojlj6mr5CagTBiuvcnnE1MLnqjR363R7IuOfk3OeJBgVhFePQBH4mGfm4f4/MFJgZTjHExBkUq2g4mp6YoVG1e906f6oGHVedBEBD+SJg1SbEsK+uem87Xmf2w/xVqKyjjZIGhtAFLHMdEUUQURQAZd7Btm9JehV10kYMx5mcnCbs6tbBP16vhmxuEkYdJEau2h8lJjfmfOMPsrEM96eHJDnrgkncrhH2JdJskCLp3VcmX5kkCRbNd53P/7xLOn1i84u0uO5+XQwUGt/yeTeOYBAQzlwte+o4IO69l+/5cKdsf8Z8Rni2MAkfPATwZUiGlxPd9Tp48ieu6WZbl6cazcTFLgx5pxindhye7L090rJVSHO0nvP2U5JYO+BIgYb8LH9qXsPbgA2i9cYL8JEpogAAlCaw8SejhDXoki8foNTewphfY+OSfkV8/hSoUsoV6zTRZ3pJka5pGv9/HMAxarVaWbUszPJ7nYdt2pm5RShGGIZZlZRk5tY2A+b4/XMjlTl49+P/IqQl0hoRrnhczpu1FQ6BLHQMn64MGkFgDSvokvrVBqZqnnv8qtxlvprB5OZc33oyvtYjoY2BTDQ8Sa94w6KNCdGWyO/8CDM1iv/pBXL2CSAR9fQUnmUAog4gBX5/+FcbVxexpvolp/xo0aaGbOkqHKOlTrT2fuzZqeP6Ay8+9HZMcOhY2wwCUqQqYuGjSYkf/ZQih0WUJqUVYqoypOXyp+GY8+xTCGxqF67pOo9Gg2+1SqVSyscrn8+RyOXK5HL1ej42NDSzLIoqiTOLtui6+7zMzM8PCwgKO4xDHMcVikWKxmBl4djodoh1fQt5yLeagyvhLO/iLUL9lCpkoNC0CJQlzG5y65P3sPVRgYWEv/pzPQNxO/KVrCQYSX+8xsCTm0n5QELR1SDQqV3SwSxpxT+foHy5wzXuPc+qvi9Tu17EnPXRdo3a3xYMf1znwY/3MyDKVmG+/7qRBorT9cJIkWetiIFMlpcqk75fF/+nIuD1XiOsIIzwTGPGf74wLlf/M1E7z8js/xmf+9uOwsrS1tQB7Dqb2gabAEiAElekZLnnFa+lV5njdrKIy2KTgS6qRP+xmNhA0oyhLvKTlaGkX0TT5lfKaNMkhpcy6xG7f3/TfaVe0OI5pLUd85fcsgiYoDEJi/BOKzRUw4iJz7GY/b8TAxsCizxraWA9NCnJjguteMeRY4b+y2bzX5IGPgW6ZhFoXP2hCp8oYVSL6hPQxozGaiwkqNjl3eEDgdRjIPkm1h2gqBqxi4bL3p7v4mxYb36jQOWUhiZHExKqPZkLjvhj/NT5CCJZv0QnCiESFxCgcxigxTp4JDIo4S2UEGua4Ry4ep+jtQIt1XvV+n/GDEtBwXRcgU6mn6qxSqQRwHgeIoui8v2mwCIbr2HaPo9R4PNtWehz65R5HP2EzqJtMXqcw5izk1yZAKxAaMV7cRJteYuLf+nTdDTY2duCWXa74KbjvoxGd1hrCirEsm8bhIlKtodcFQrrsvaZCvjTOoB3yjXd3eNl7Vjl1U4Hl+yqMzbkIIVi5G+7/eMKhHw/Om/fpHNO0h5VK6fGM8DBG/Of7E6PA0fcYgmAoN+31emiaxp49e57xm7hnqsZfSkm73aZer59HkrYbPT8RpAQ1iiKWlpbOI2CP9fzbfZ3fWnFYTnTCh3cMlOKhvs7132wz/YWbCcfmUC99E+hiWEeURKgwJFo5CaEHzQ1w8kSBD5tLWVvgVF2U3synpCjt8OH7Pr7v4zgOnudliqJarZb51aSZojiOsW07I5lpq1MpJbascn30TnJqAoMciq3WmJgYuoEuLMwwv6U20kgICc0mujLxtQYP7Pt/qLiVLQNEj3J9DlPlQO+TSAGaBKmhLI8Qb+ifpBwOmj/EJZ1/h6aG7S90ZSMMQaINQJecKH0cdzaiurGT6eAaNEwEOlYwDo4aZuFEgBAMg2hyDFuVMMltqaIEDhWUkoBEigihLFwm6FmLJHHIWv6bLOvfIlgNsrKyHTt2ZCapaVv7tBWv4zjMz89nWc3JycksQ2fbNjDcl/QcbDQauK6L53l0u93Mf6FYLFK9yCbcfSuDwYAzrRanV7vstn4LmxLCkIRaB/WSr+FpZzl9OsfExMTwBujSNdh/M3ZSof/AFP7fvhypRSAkIjYQStFeUlizHQxToNYLdBp9eouzGK5E18VwHpgR9eMw3elgWVY2H4QQ2d/UB0spRbvdRimVdaPZrlZLxyAlANvL3FKfg6cK34sEbvu4jTDCCE8cI/7zLPOfIIBj98Hf/zlL3/4ifxm2Hv6Cqd1gFod3HbYAlWBP7qB84CL2XnQ5nV6foH4fS3WfZa/LxMREppi2bTtLyqRIkiRbp6IoQghxXtIjXcvShMh2FVqaQDNNc2ik7Zmc/etJct0cLhZdlgmI8OhQ1SZwjQoiHCcmRhKhoVOq5rGNEnZF44a3C3YcKqCUYvVsnaWvJ2h+DpGP6IsGllnCCipUSwUSw0AT09iySLKoOHNTAT/sIKTFWDSBboToYxq6rhi/ocb1rylw+0cbHD/pISIdSAgHNo6ro9sahUKOSy6RaJqg+/cOhchCYGNRxcAhooOGRoEZTN1EJCZOu8TMJRZBW7Dr5TE7rn04sPZYcyOFpmmZkmv777EdqTn5I4NM6W+VqbxmFPMXDzv4JklC43TE+v0S2Xcp5XJM5Ktc8+aEhZf3OXVquDZ2Oh3MXTGXvAX00KbxkMM9f2IgzQYyTpBSQzDg9NIq5uQA28qh18cRiUHrTIJvbLDWCRkkbRw1x/rRMofQz5sjadl+etzp+ZQqrrd3qE0fz2TQeMR/Rng2MfqFvgeQZlcajQYA4+PjVKtVarXaM06anoka/yRJaDabtFotisUiO3fuzMjAk8X2zMjGxgazs7PZa+lFOn3eCeFDG4p/asJdniBBAGroBa0AtKEgRw1bpK9e+Rr46Lvg2n8Ngx4k4TC4lCvB1z4J+y6H8Tnweqi/+H1qp49nypZULZR6EUVbWbd+v5+RnjiOs/KnKIoyE8JUItzv97PjjKIoaz+bZt5sUeJN/b+npBYwyTMsJLO2vIYkmjLQEpM+64A+LFnT4O753yUZW2e5fQzZjpi0JqkWpnnene/D7E9iyDyGzGOJMpHqo0SCjDQkGsVkJxoGz2u9BaXFJNaAJJaQKLrWGZbKn6Oln6JWuIPx5RewZ+OnEdIg1LoYwkFTFmZUAVNwV/m9nFs6h5SS0/oX2Bm9AkmCQKFhbCmkNBQxnl7HjSfRMLFkkVDvcWb+oxT8wnnjVavV2LVr13kKGsdx6Pf7WUYtDci12+0ssJSWpE1MTNBsNpmYmGDnzp2ZrD5VJaXlhGm3s5WVFR544AEGgwG5l/0xU4s/giEdOrO3U3zeInP1uaz7Sxq0kZak2ztHdO/zERoIQwMpIDRQQFIv4PUNtMkORrHB4spp4kqO/uG99BuA1EBBeWydWq2WEem0DK1QKGDb9nnnVdqNJgxDgiDIFHBpyVqqTNquaHu0YFIapPpuSMKFINX+bq872zHKuI0wwhPHiP9cAPwnDODP3w3/8EF4OIU2RHmOnKkYhBFs3Aco2HM5zO/nih1TtOKQcyceIufmef2kxbhrYhSnyOfz2bqSBhxSz6I0OOR5XjZ+aQIjDSal70uDR9vLsNPOoqZpokUO337rTsI1m1w8VKXp5Mmzg4SYoqkj/BxGRdCNNlCmRtGo8JLfMdFn25SnTQZBj5Mn11GRxpH/vI9wtYiedOh0VjCZxrQEOlUKqoylC+LNEj4tlj7mULQKuPk2iQrRfAd3l0/1ReuUFiSd/Am+/Zk57v9EHj12IR9Q6ExRxiYXuOTzOa7+5YD9lwwDZ9oP5/nWffpwjIcpNizm0LGQmk9hykY1iiAhaCusguIFv/aI3+spwOMpYU+DS+kjjmMWFkLG/yjgrv/h0+/1mXlpSOGqiF7PQNM0pqenMU2TKIqGRtmDAXd9ZMCALirS0dDwiRFI4vUcTtshmokwSqc4sySQExUGd1ewuyVIctTCNcr2aR58MEe5XM4ClWlQKA06wsPrcuqhlc67FNvVcIZhnKdWejq4yoj/jPBsYRQ4eg4jjmOazSbtdpt8Ps/s7GymeEhLnJ4NPF0ZtyiKc0uKTgAAIABJREFUsmxitVpl7969WT11WkP9ZJESkfSi9WiLnpSSXz4W8z83zttrkN9hv2U87Biy5xKorUB5DIQFCPB6cOwu+NQHwMlDMAA1DHP0ej16vV72MWn2LL1Rl1Ke9xunN/3AebLsFGmnECCTE6c3+gfUD1HQppEySBuhDccEjYSYdXUPk/IKIgLSDYRyWG6cot6/hyRSjEWHqK8KdG0BvT+GJm3ScjZdOejKpqbfT6JipuTlCDRCuhi4aNLBCPKILV8jL+6yGt7Pvt6/4vLV/0Qxmcckj0BHJBpd1nEZo6Hfz53F9/BA97NZh7BN9T6u5e2YOEODbloYDM8JnyZRHKJpTWru3ZywP8Wi9g2KmsBxHAqFQtb1LDUVL5VKdDodAAaDQSaz7vf7JEmCpmm0223GxsYwDIN6vZ6VEQZBwOHDh5mfn8eyLEqlEpqm4fs+5XKZUqk09FVYXKRerzMxMcHc3BxKDRgc+Gv6/T7dbpekPY4QgqWlJYrFIlJKpqamsr/tqkU/H6AGFkRbhp+6BF1C4CD9HtHrb2Z1tYu9IyKoH0T1h75MWi7GmfMzRZHv+/R6vfOUbampaLFYzIKYaavdlCCmY+H7fnb+bCdPaZlkGtD0fT+bj6ky7pEm3N8J34sZt+3jMcIII3xnjPjPBcB/Wi14242weOTRPhWMArRXGJz3ugk//TbcmR382gunuW7SIdAMSpaBYMhPNjc3s45maVABHr6pTNen9LU0WJTuZ5oE2l5+vT0JlB6vruuc+gebXLdErijY8DbwaKBjIhCYCMb3KzrHwXZMMKuYmoOQBqWphPyeiFajQ7BUpqCNs3E0wluzif0YDYMKu4CEJIyo7lRIvc/g9BiCgFj0SOKYTtwkGgyI8bApMSEDpsd9Vv9xFu/sLrxNk7JfRqBjBgpjXBJ1NIoX9Tn083XmXigRYrh+XvLjIcf/8CBxAFJGWK4JiYEQYJVtDEMRl2Mmr/LZ9SM9pl8YEBUkm5sPByLSsUn/7XlephZ6tFLIR27/eJ+nSp3tPlQAU6+Bq18zfB6GYcbF0iBhWoKYls9Nj08QVwTNVp0em0R4gCCkiecXKPuK637ZQCmN/MUNVj7aJ+6uYQqXQr7MzoNFDMPPgrFp0tY0zUy5ls67NFm2XWm1PbgUhmE2L7cfb5okS3nRdrXSk8GI/4zwbGL0Cz0H4XkejUYDz/OoVquPKsd+tswWn46MWxAE1Go1fN9nfHz8Uc0tn8rI96PhtKf4T8divtjOvvE7B4yGOwXri8NtOw246U/g9T9P1sbhxJHhA8DvP+bHwMOtKuHhC+wjkZJH27bPk2d7nkcYhlu7pDISlS5aQhooqdAwt9Q5CoEgYoBA8I2FX+Gqld9mT/haFApFzLp2N4PSCXaU93DdyQ9QDPYMg14KTIoIzl8QFQnlZA//k9fxJv6G7REqi9JWiEmhoTMRPo9X1j+Ijp0FfUJ6mOQxKaKEJNCa3D7726xHD2WeQ1JKJiYmONr4EPvqP4lAQyBoWWe5b+KPOFT7eSxVZGnsn7hv7L+xUV8d+kGFM9m4JUmSlZRpmpbV5AOZqst1XVzXzUjAxsYGy8vL53lMlUqlLCOWdilRSmVlamnwpdvt0ul0snbAaeAlzaIPBoMsM2qaJuvr66ytrZHP5xkbGxt6B1RXmdB/Bt0sIMIyQk9gZn1YutYrIK++FVVcY9CKcB68GM3y0Mdbw/PFcznxnkso7B9QvbLF1A8vYZpxJjNPSXuz2aRWq2Um4ZVKhUKhkJG+VGGkaRoiMdBtgRDDMU0DQ9uvUen8SwNJQRCcV0aQtlLePlaPxPnlGdBbESQhuBOKM/+os3K7junCgTfETF/56OfMU4FRxm2EEZ45jPjPBcB/7rkH3vaKf+FdCuIuAFqhzEXXv4rgl96PZpoIKbk8J7luh4GFQk8Soi2OEoYPd/l8LMPc9GY+TaClJf3ptpZlZd5H24Nh2x8pTGEgNIGMwMCmxAJdlkGLyOsT/MTHEm55e56TNxuYwsC1ikxfKTn0co1Bp8BX/v08nVM2rigRywg1WENDABGSgCGzyuOtxlz/7ogvv6NDrDxi2UYPS2ixS44xNHQs8uhnNc7+IURhhBmXMREYtkIGBlEQolsa5WmHn/gLh4mLph4e7a35fu1bE+7+UxuUjlKC0kLCC/9vj2+/zyXsalz8moBrfs1HM3Ug96iqsu3Pt6u5Hmubx/N8+78fuc3jwczMTOZplXpzRlHErtd6tE6WMMUcpeYCCT7J9Fnq4ih+p071koCjKx7GhkHvgSqBOUZup0UUbtBL8tz0dpPKHoNdV+U4+AZFHLdpNBrYtp2prlO1mu/7GcdL59D24xNCICOBZg7nf/radn+k9DzdHjhLg5rpY3sQ97Ew4j8jPFsYBY6eI1BK0el0qNfr6LrO+Pg4c3NzF4Rc8ZF4qjJuacmQUipTYzzW8T5V47D9c2qh4sMrEZ/YhLM+eAqykjQgrVD7Z/AHYNmQxODkYOk43PL3mOGAaHMJ9l8JjXX4xqcg+u4zo2kAI635T+vHHw1pfXaqYPJ9nxPqi7xIvA1DPpxFifGI8VBazMLqjRwI34ACdCzuNz7Kl53fpL/W5vLaWyj5+xFKw+DR690BBAYmOlNcmnVmYytMBQq55amUEOBSISZAiSQbXx2DSHQRyuBU/tM8UPkQteAEURRRKBTOU7J8Ofo9lt372Ge8irZc5Hb+mLjfo7b/VqrV6rDbyoZOPp/Pyq62l06lAZD081zXzXwWUqVR6is1OTnJ5OQk586do1Ao0Gw2s3K3arWK67oMBoNMKRSGIZ7nZSVuSZJkQRIpJc1mE8dxMtlz6i+UZqharRaTk5N4nsfy8vKwc970WTZ/4E/Rz+4nt34pVmcOkgFaZILms+nchX/uHEmSkFusU/G6KK2LIWzs2jhCQPNsROvEBBtne8z86CI0xrFKEn26haZp57U7hmHWr16vo5TKxsbsT7D+vw4RrOcQVkz1NcfJX3Fu2Bp3i3SmWd70mNKA2iPJVEpW0+NOSwtc183Uc0opiE1kCIufL1I/4iAEBC0Ns5BQ3u8ThoI7P2Rw+S90KS4kTyoz+p2ebyeM3y1G7WhHGOHRMeI/Fwj/+cxn4AM/+zg/zYKLr+Cyn/5VPvaT1zNmaXylmXB3z2faFvzomECLI5Jt1/7tCa9Ha9SwPUiUdlIzTfO8srb0s7YHib7T+Cxcn2A44A3AFRUAbGMvZk5huQan/yri7KdtUD5ERfa/QXLtOzsgBA98cBzvuE4Ud+iFq2ho6OTw2KBPHRsXAxuBQEQuZrPMGA6arqGMBCk0oligkCQE2I6N7Ascy8Q0QohtYiJkonCLJiIq8rwfh+e/JaS86/z5kh7ji94aU9kLS1/XKexQXPnvQ5yK4MBr/W1bP36j+CRJMj/HZwupMjsty0xfA7j8csnV1ySc+FLCma/HbBz3Mao5poLdtLQ61/xQC33CGyqKDnt0k00GUUjDWyFqFygwhbdSYu20xeK5hIteY2H0J7BLHrnZNrquUSgUcF03C1T6vp/xxHS++msGD3x4nMGqiW4kLLyxzuQLBkgRZfubJti2B+NSJVfKI1KOlPKq1Kd0e4m/7/tsbm6iImPEf0Z4xjEKHD0HUK/XqdVqFIvFrOzlX8J3m3HbfiF7ou97st8HDystarUapmkyNTX1mAZ83+13fic0I8VvnIz5pzq05DC0wbCDZ/ofsshROs5KgUxg0IHlDciX4Wt/B5/5c/B6RAB3fXn4eBxIF6RHBoHSUqrUp0gIkUmJ0/9vGEbmfbS9ZGi75DhVyPhxjU+4b+T68HdZiG5AQ0eSgBDck/szru39Jtq2S8XF8Y9xi/kOYmyKvb0IdHT+uSLkfAzHaL/xSm7V382Lg98AMbSvjlVAgg8ChBp2nUv9ldjyJxr6LukEeoNbC79HEPWIoohyuYyUEsuyyOVyrK+vg4DG3NfpWbextraG7/uEvaH8PTU87Pf72Ti5rkuxWGQwGGSBoziOh51WWi06nQ6u65LL5bbMv7Wsg0ixWGRqaorZ2Vl0XefgwYP0+33a7TaGYZDL5YYzRYisNh/IPseyrCxQtLGxkXkgpV5Vg8EA0zSzEsU00JWRFd/fajV9BnvmMMbMp5k4+nrK9WtIjBabBz9JKI6jekOvrK5zO8XkpURtCCOBHkGbMwxW1xmrjhN+bQfN28bRMNCEgTHTwihHmKUA6yX30xdrQ5l4b4LkwT0oJWDfCeLiCvJvngeDEDoOwi/QO3Y1zmVLTPzMbZhFmamYUqRzcHtGLh33lGBt96hIzwOlFK1mi+Lii+D4ReDlUD2DqeuaTE6PcfohC3c8wTQlyoSwJeidMyguJOdlTdO/TzaDCkOV3+Li4r98Mj8C2wnYnXfeyc0334xSimKxyFvf+taMOOq6zlVXXcWNN974zz7jyJEjvOc97+Ev//Ivz3v9Ix/5CJ/4xCcYGxsD4J3vfCd79+59wvs4wggXAkb85wLgP3/7cfjILz6+N5em4Id+jKkf+il+9tJZfm6HSUEf7ucrJ3ReOTHc7JFrwXalQdp0IVX8puvAdnXG9oDQY6mJHg/y04obPznga++wWfyKjoxBMwyEJrnmlyJufZeNjCGUw4DVPX+reNF/HnoIrdwbECU6ItSRRIAFROSZocQCCQEJEQqJSY7aXYLrf0Pjjve56Ohg6MSOQLdhqGIXRCEIPUHoCaEvsDEwdIGmFO4UXP97fcz8Yx+PEHDxjTEX3xg/9kbPUWwPXqTQdZ35q03mr4b4P8C3/+sEp76ooU1EXPILDfRdywwGAy666CIWcgFfPtrHp4NIimyyQWAtccbvkdMKtL4+xbkjJSx8bKpM7y5SGs+TqwouvVFgViTVapVcNMfSV2yCMGbuep/8bMTn32Wg2hpJR8Nr6hz9gzEGL4/5gd/1sAoPB4lSJXdabvlIdXeaYIzjOOOS6Tbp8fd6ffx7Z2ncXSRqO8TtiJnrEqarYyzdJ9BKPbyJFpOVBTTDHPGfEf95SjEKHD0HkM/nKZfLT0jC91RItZ9sJPnJfG9al37y5ElyudzjJohPJU56iod6kt7ApLMW8dU6NKXcKknbHizaDjVUGK2egrEZsJxheZrtQqcO//ixoZfRv4BH+72klDiOQz6fP6/daWqQnQYXHMfBNM2sBjzNwm1X0aTjaxgGnudlJCzNzHW1M3wh/3M4RpF9g9eTY4Jz4hakb3Il4bbA0bCUzfDLWK5H3bqX3eHL0Hn4t0o7r6UGjelrConSY05OfIxOfC9Ob4Ewt87+/o3s9V433FpTnLBuYnf4alA6MSE6JlIktI1TfLnyK7S9YclUoVDIauC3Z29SQtnpdFBKZd2/ut1uNobpWG9fxKvVKmEYUigU6HQ6eJ6XSaKLxWJW954aPkspGQwGrKysZNu5rkuhUMhUMqmvUa/Xw3XdrONd+t2apmVlb1JK+v0+jUbjvIxUqiDzfR/P87ISDd/3s4xXGIbU63XiOOaU+wdoO4fzQzUUoimyOSHlIr2Zd7O/8VO4TBPETdpqCWIIvAjHKxKILkbewxiME9+3n7jaJNQE3h37Kb78OKWDPRqfvhJ8bRgsffBKpt50N3U1gdQ1oigPdoSKdPzlIqs3z5J75RFyuVymIAIy9VVKmLbfPKWy8HS+e56H7/v0+/2hQfmZKebOWfT0r2P2pyj1D3H78TvQJ1pcW/k56qs6pmUwfXWCKTSqM4JK5TvfgD0ZnD17ll27dj2h9zySgE1NTXHttddy+PBhfv/3f5+3vOUt57U4TgnQdvzZn/0Zn/70px/1pvL+++/n3e9+N5dddtmTO6gRRriAMOI/zwwelf/87q/DrR/5l99sleDAlfCyN3LZS29AlsaxdZ3/fYdB2RqO4fYOZynvSJGWiKcG2M1mE9d1s25q282KU0VG+ngqSluqBxRv+JhP5MHRvzXwagJ9zwpjhRk0SyFjgSJC0w1M4RC3oTSusfP5DrVbLcJQ4KgKCRERHgYOGjqCEmpLT2ToBqViwrVv8dn3soT6UUV5d8gDHzM59skhv1ICDv6biNOfN5GxjmlLVCzQjOE+vvZP/e8YNPp+h2HDi38j4sW/kb5SASoMBgNarRazP2gwV9G548MhG4tt1lZrxGOnOdH+JjVvicBfpYBD3i2idcuc3ShTKeRwzCqHP+ew+2WKmUsanPu7ECMqkzNKHLupyEveFqLaOjIMObl0F3pOo6ztYPEBjTv/u8blPxufp9JJeWfK77YHjlJ/rrSEPy3bDMMQ3/cJgoCHbl9j7c77INeh1eizsr7M4omvAPAL5c8xbhwiFBb5q/tYqkB1Jj/iPyM8ZRgFjp4DcBznMX1tni48HbX6j4YkSWg0GrTbw+L53bt3PyvmaF9tJrztVMKpAUSqTPhIhdF5ZWlbAZE4hLVFePB2KJThyNeHN9L7r4DNJfirP4DW5uP6/tQ8OPW4SZEGB2zbztQYMBzn7UESx3HI5XIIISgUChiGkd10w/Am3XEcoijK/GKiKMo8d9IFLRE+xwsfzwJMdjKF7pmkAyDQUCImtIclA4fzf8xs8kIWkh9Ax0YhkVsZtrp1PxPhZbDlNRQLn6PVvyCXy1H372fg3AESzuW+xUn3U4ybe0kmVjnV+yb9+P9gofaj+LLHybkP06wcRtM0vGYTo2Nkx7s9iNbv94et6oGNjY3Mjyj1fBoMBllpVRpkSo9T1/VMBq/rOpXKULKelo8ppbLgT6r4Sh/dbjcrn2q325mfT2pYnvpMbQ+MpJ3RSqVSZuydBnfSebBdYZO+17Ztut1u5i+UejmkZDotg0uPs9lskiRJpqwajsUK902/g42lJi9dez9jahcJEZZ0kYZPog9IAjC6BSQJMokxOlVkYlD/zD4an9HR8yH2jI+hG8ieQ3hkL4ZpEPVsdF3A/8/emwdLdp5lnr+z577n3evWXqUq7Zst2aa947GNsXBAOwAvQDC4g4bpMXTT4ZmBiY6ZDro7mCFoTwzdZgkCMKYB2yxjtw3YkjdhLbYlWWtVqdZbdbfc17Of+SPr/ZQlSyXJKpVKcj4RFXXvzTznfGfJPO95vud5XsMkiXWcsoYT7aK2sKmOrxCYuVxOXceapjEajS4gi4QUzWQmHU/kc+I4Du2vLqOZi4TpFI3TIzQvpsouymaJwIVwBGt366zfr3Pth0Lq11ze78+LYXq2DSYzpvPz88rOuGvXrudcx+rqKh//+Mf5tV/7te957ZFHHuETn/gE29vbvOlNb+IjH/nIJR3/DDNcTszqn5ce31P//KsPwJNfeI6lTNh5DXvf/BYqr30LV+/aSapQ5OER1IyYX91lspC6sM25PDQLSTStQhX1reM4eJ5HqVRSdmUhiJ7LdvZiYaXhmg+E561RI8paTBxoJDFkjCpJDLaVUF4NMQx4zUcDNu4zOfM1g8gDQ7MwTAvDgLnrIrYe0ohDDVPTMdNw0y9Ocpzmro+Zu36y34u3ehz88ZD+mkb96pjaNTEP/VHMo39qEWpj3vgbOqv/7JmjBy4HXiwBeyVA6txOp8PK7XDtu+YJRwv8zYcPs33yNayWb+dE/0G2vDXINzk3OMJ2eB82FVKDNAY5CtQ5/pkUmc/myRXXKS9kCAMPZ1Cj+4d5/FGesJNmlGyxMXycLptcXbyB0bdrcLOmshqlU+00cTrd9EZynCTLScgkscj5vk/NTpGtF2lrx9H8AY3NPjY1IMUj/S9xILYp3bcT79ECN3zQo3ggAS4vEf1smNU/r3zMiKNXKS7VjNtLtZwoLyQLZs+ePRw/fvyyFk3DKOGTGzHHxjH/2Eo46UKYxBfmFiVT/6t6RQMJqzYt+INfh2HvRY3F8zxFAE2TR1IoiaRV8oyks0OpVKJYLGJZFq7r0ul08DxvQvo4zgWze2Jfy2YnU1bTNjYhX0SlJJJ531jjy9lf5S3D/3uSOaTFfKn2CxgaaJqBZsLfOx/GGs5zS/+jXMX7QEt4KPsJvmH+e5bt13Fo/AHQIh7O/SHN+GHs8aTVezabVaqe9eSbRHPHJwqhdIoT1l+xufJ5tre3yeVykDw1KykWp+FweEHIcqFQIJ1OMxxOgsbFyicEWyqVYjQaMRgMSJLkgmtNZkIdx1Ek0vRxFiJm+sYPF978pq2FT0mKByp/SYg6aedarVbxPE9J74vFIqlUCt/3sSyLwWCgOorIw5NI9CVQu9froeu6Koym29vGcczi4qLqAuf7vgrr7vcnoaX37fgYC4234wRlGunvcLX/QYrDPbhGm1SUoBHh94A4IiECa4jhlogGDsNBEyILY2wQbPiU3vIA4z+5jWhggR5D2mV8JoOXO8fo9Bl0XVNWQbne5dzIzHI+nyefz6trV65Hx3HI5/Nomka/3+feI9v0HoX2uI2WiUjVfNL+HE6QRzMgvzPEsHS8rs5gYxJ8alwZddOzQjI7ng/e8Y53sLa29oyvvfvd7+anfuqnyOVy/NIv/RJ33nknb37zmy/lUGeY4YrGrP55bjxj/fMjB4HmcyyZg9e9Da65jdrh6/jk23azq1a+wBI/bcGRh91p6/H0vXS6M6csKxMdL3dQbmE14a2/7fKl/zmFboBmJPzop1zMSc8OzBT82KfHdE5ofPM/2Bz9WwvdgJv+pc/tH/NZ+4bBd//IQjfhxn/hP2NIsabBjjdcSAxd/7MB1/9swKlTp1h9gYqOVyteLGFomibVapXBYECj0aBQKPCjf5jisb/MMm4c5kevXeJrv7/NxrEB15Tb3Hfkblo8SZ/j9HmMFiWaPMpccjNGB5we9OItcqyw4q9w8LXzbHx+EZ0cGmksTE6vnUSvDBgM5igU8kpdJCp4x3FUbSckkZCqMnkmn6liscjy8jKWZTE8dopHHu7QjLfoJV1iu8eKfw0Z6lhxlvXK3YydJ1mJX0vQOIA3bqNbieo6eSViVv+8cjAjjl4B+H6/MF+sx/+lWM51XRqNBp7nUavVWFhYuKwBl0mS8MVWxL3dmK92oB9CzoIT44go0SCJQXuWL684mdjODGPyD+AfPvmiSaPpsYmiQoif6W4hEs5Xq9UwTZPRaKSIBiEoRHEkMvcoihRRJMqiKIro9/skScJwOFSk0sLCAqnUpE27hHJalsWZzOf5b+VvYLpl/NQ2RirGHE9uejI7OGKDr9i/wteNf6OInXgQcyK5i+POncoWV8wWld1IlCfi5240GqRSKTzPUyQIoNRE4/FYWbu63a4iy+TmKsWorENUWiJ1d11X+cZLpZJSCZXLk6I3m80qgkUUMdvb2+o8SCirWMOExJKAa9M0qVQqjEYjdQMMgoD19XVVBMh4UqmUOh/TBYPI+aVLXCaTUblLElIptjYhoYTYkv9TqRRhGDIYDBSxJNteX19nOByqTnR+0udI4c8AGAwGtDJHeEPnN8m6S3h0SIjRI4sEnQiXzfYJ6umdWH6JcDONM54nSjS8fsJG4wy5sItpJRhuFsIMSW5MvLaE9eBtZH7ocfRBHuwQfc5T501k2mLvE7ugXMe6rjMej3niiSfo9Xp0Oh2OjY6TLYSU+vsx0yZ6xcPffw/aPbfj6CVSRY04irHjyWzxuKlhZa/smVMh0V4MkiThwx/+sAoyfeMb38ijjz46K5xmeMViVv9cOjxb/XPsbVcBjYsvXN4J19wCS/vgutfDzv38wrV1Dizp6v40nUkkD8lyb5YsP2mIIJM1QhxJ7SFK3ZebNBIcfn/I3ncOGG5q5JcTrMyFr2salPckvPMTHu/8xIXNTna8IfoeUmiGlw+apk2ao9j2eXW4y3U/Vzh/rWWoH5rns79s090o8kPVg3SjU3huwGn3Ye7kTwGXLb6BzTLpuARYNDlFa/MER/7WxqRChT04VIgxMMjSOR5z76fPce07SxT1BciE9Iweo9FIfV5SqZSKpcjlcmoSTVRKtm2rQOyNjQ229bO4hYDotIERmJRrOZb25mk8buGON8nYdZrBURIjprw94tbufqJsoJq6XImY1T+vHMyIo1cpLkUxcqlm3MQmNN0hJJvNXtaCCaDlR7zmWxFbwQWDg0E4CbW27InJHCbVgLyuMSGNHrgLlvdNyCXdgEEHvvDHl3SMvV5PWXh0XVd5OSJflQJsMJjkJolipVKpqL8PBgNFPImNyXVdBoOBKtSkuJPlxCLleZ7qmCU3ronyJqDtH8VKLBijLHOS7SPBdmI3kplTkZ9HUUShUCBJEnK5nMp0CIKAfD7PYDB4qlPW+fWKwkjGLjd9kfmK/c7zPEWgiXUNUERMt9tlYWGBbDZ7QfC1WKS63S6pVEoVtIVCgfF4jG3bamyZTAbP8+j1elQqFeI4plAoKFJJ8o3keAFKNbO0tKQKaCH7giBQFjeZeZJzICTPcDhUWUqizhFrWq/Xo9vt4jgOzWZTHWMJ1J4mrtrttjqGhmEo29doNFJB20LiRJkO3yx9FM3NEDBkrvMGdvfey0JyCz3W0DHxQpfjhT/hQPsDBNoI19oiYED51OtpOY+ix9sU2Y+WGIRBn3whxPunw8THdxI2MmjoFN5wktTbHkfTnuqkJg8Tvu9z6tQpRqORyqSSHKh+v8/6+joYMcvvWyNp9el/YyeF8UGCe25D0yAcghvroCUUVgPctsnxLxgUdyfs+KFJB50rEXL+XgwGgwE/8iM/wuc//3kymQz33HPPMwZLzjDDqxmz+ud78Yz1z4/UnnvBndfBzW9mz+FDNO08dn0Zc26Fcsrkn+dG9HpPkUTPpCaabvDxfEKsL/dxeT5wCuAUruyJh1czLrVdznEcarUavV6PVqtFoVDAtm3qe1J86K8qnD6yhU+L5r0rfOfTHVIP3cbh2rV84eRvc5SvYuADCVnmcbDJ4NBlQMg2x/kKLiN0LGLaLA9u5MkvlbnvWxrJ0CJn1Tjw2iUOvS1LqVTEcRylxvN9n16vRxzHZLNZMpltWBchAAAgAElEQVQMSZKwtbWl6veVlRV6vR673jSktJGw9Z0M7c060Umb5WKJRr+NOSpjGwalxTJrW6f4i/9nnVtedwMH35oiScbPGbj/cmBW/7xyMCOOXsV4uWfckuSpFrqWZTE/P3/Z2e4kSfjURsS/Oxmz/nTCSGCYk39JAtOzXPKehAmx9P/+G9hxEG5+C/TbE9Ko91yy7hcOkWzn83mlHhFCR0KERYUi5MTGxoaa0ZMwbSGCDMNQJMi0JS2KIkXEiI9azo+QVDB5sO/1ehQKhYlM9nxLetu2L/hZCBBR48RxrJh/GX+xWFTZBtlsVpEisjxM/OjZbFYppSRLSKxnQqaIlUzWI9lFYRgqIkn2t9/vK3JESCDpijbdpQUm17C09xWSaDweU61W6Xa7KjdKZlkrlYrqfDFtcet0Our4DYdDJcE3DINyuazWJ+saDAbKwiUklnRwk9dFESUklqiP5KYr5JUcNyHoxuOxCu6WfRPCS9M0CoUCrVZLLa9nE4aNEY9qf8UTlc+yO3gHh92fJgpiHnZ+j571GIv6m/CMzuR7JoQ4iSHSseMKBikgwXCLuCd9NE3H812MUgcdk9ZdOwjn1tB3rqFrJsGxRcKeTVTaxiudUfY6kS+LvNwwDGq1GlacZbAO0VkLfXMJdnQZjdexhnWyh1qMnixg2jqjTQMzE7H1XYNz92mc/SeD2jURsa9RvzaisJJg559dZHg58WIKp7/7u79jNBrx/ve/n49+9KN86EMfwrZtbr/9dt74xjde4pHOMMOVj1n9c5H65zkJozRU6rCyC37ofVCp8bEbSzSMDA8aZWrZiH9eC8klJmAqYl8UpDJR8nQ10QwzXCnQdZ1SqcR4PKbT6aj6KJV22HP1Itvb21j/rMsdb09x/B8dvvsZh7faH6Ju6XSiswwfr2DbJh3/LH1CChxib/46Wv0W25ygyTlitjjLvUCRSmeZolUm8Ifcf+caTS/P/IEC+XwedyOL7lrkF3XKO21FNktmZTqdVvV3kiScOHoay8iS8RdJugGH9i6wPTiFNcyzuA+S9SLFTBljaFItLNI/scXfPXoPj965i0O378AiYOUmi+IOZvXPDC8YM+LoVYoXe5N+MRkBcRzTarVotVpks9mXpUMIwAO9iJ95LOL4tHr4Yvv09GMmSqMognF/suz9/zD59xJCuqP1+30lZR2NRoocEXWKdOmSLBzXdXEcB9M0FSEgxIpkJ0VRRCqVYm5uTnWumu6w1mw26XQ6ZDIZut0uxWJRZdBIWJ8QLdP2MFFJiQpI1EJiF9M0jeFwqIgQabku63QchyAIVK6BEESy/4VCQdm5JBdJZk2ERCqVSoogkvcLuSWKIGnzKZkL4/FYkTlCTNi2TSaTUeMHFPmiaRqdTkcpwaT7WhAESrkEEzWP4zhks1ksy2JhYUHtv+u6NJsTwlGUVaJeEsWU2BOFJDQMQ5E+MAn/DsOQXC6nbGlSZMgNWGZ64zimVCqpbCYhnEQ1JiRXs9lU+Vai3hI12gm+yGbxa0qJVSnUibse6aRMYA4w4hS+2caI06SiKgmT8Uf46K6DZ/UYeefQGjGapuOMDTbu7DG+9gGK3/oxnPWDxHEC2l4aq306i3dDylUzcKPRSIWBR0d3sXDyvWxqGrZXhkKHdtxl0B9g+xrJ3WX8/MMkPROns0xn7n601pgffvO7Ofa3Bu1jGnGkcc9v2VQPxtSvi7jh5wPS1Zf0Y/2cELve88XKygp/8Rd/AcB73vMe9fc77riDO+6445KPb4YZXimY1T/PUv88F2E0vxdKtac6we6/DZZ2YpoWpmnwrp1VPnjeri0PeaImmm7wILksr1S8ksc+wwuDNDzpdrtKfSREr2EYdDodVt+ks+stJuvrJQ4+/jb+6ev38NDJLmV9lcXUPs71juHRZX1wDJMqda6iwC6OMAQ2AI8hTfpBmwwONmWc0xHZRYP1f7IJt9KYiQ66T/nqFtaOHl44VkRRq9Xi5MmTBEHAuWN9Gkc9UmaWZHyEXCnHmdG3CKKAfYXX462lMGtnCXQNbXM37NkmV0pRTso88A9nWXuyxXz6APf+dp3FQynmro9n9c8MLwgz4uhViksRDvlCEYYhrVYLz/MIw5Ddu3e/aOnhC4UbJ/z1Vsz/dTriiekGZd/XsdAgDifd0458e9Ip7TKi2+0qokMsUGLnESLDcRwqlYoiYsTeI+ofuSlKd7a5uTmy2axSMQlRIq9LMPO0VU6II/liL5fLys6WJJPAPSGfhFByXVeRThL+JyqaaRmukBxCfkiXMdd1CYLggvVIMLIopnzfV+sAaDabat+bzabKi5L1h2GIYRhKcdPpdNRxExVUr9fDsiy63S6e51EsFpX9r9lsKkWVkBgS6il2K1GFwWRGq91uq+MnhJrcHMUeB9DpdLBtW2Uh9ft99T5ZXlRScn6CIKDT6VAqlSiXy5RKJXq9HsPhkNFoRBiGinQSgkpIuTiO1fmXc5bL5RgOhyqIUQqn6XXB5HOezts8vve3OHTiX+OEJXxGfCHzESyvwtuj38HVWmhaQhLr+FqfoX0cxy0RGEMKoz2YcZb0A2/Fe2SVMKzRMo+QsrKUvcMsPfQzFJ98IyfLn+V45s/R9IkibTweE7YzHDj9bjrJOSI8Sv5BypsH8Da6ZIkxsGkamxzvfIWdK7so+BW6J3XO8jA37X4rYZDFyiY0HtVxCgn+AIYbOvd93Oa6DwfkVxIM67J+zBWEAJ1hhhleHGb1z9Pqn4sSRgYs7Yfa0sSqr8eQzsD8Lnj92wGd6/MRr9m3Qvl8t1Fp/iD3pkudR/Rq6OQ1w6XFS0nmiQp8OByqidNMJkO9XseyLDY3N9E0jUwmw549e8jn8yTe1zh+VxMn3Mvu8vXU3tCFkcnjX3JxaTFkmwxZRlTJkcciBcTEQIDO+lqPzbVtIE0lU4KRhUmZM18LSGcdFg/nKOz3VH1m2zat9T7j4zaZlIFhTpqDbHbOEDMmwmd9exMTk43OEW5dehup3n5OPRKSWhhxKPMujDhNOzjN1qkec/lVnOZuMuvlWf0zwwvC7CzN8Ix4IYWX7/s0m03VIcS2bebm5l7iEX4v1r2En3wk4DuDqcZoz7cASZILFUfy+/pxuO8f4c/+0/dJPr14SB6CeKClGBW7WqvVUjatJEkYjyczFf1+n/F4TCaTYXl5WSlaGo2GCoAWBZLjOGxtbakAaLEJRVGkwppd11Wh09J2XmTpnU5HzY6YpqlIFVFIAapr2WAwoFgsqnWKFSyVSlEulzEMg83NzQvyd0Q1JMHJku2kaRr1el0plEzTVIW7kB6iNhqNRgBKmSUKqeFwqDzunuep2VKxnJmmqfKbHMehUCiokMFsNquUXGLPEzJuchlNsp/ENiYB3aIqEmJnevyinkqS5IJzb1mW8ryLrFrsbJIFJd1ostmsClaU8yvHRogpIcsApZSKoohSqaRUahLWKOvb2Nig2WxOiMbsSb6x7yMYfpbW6BxRMukat9b8G2qd2wn0IVpoERljHln8zxxe/2VKo8OYcZYIj1RUZTlaJCHBCHPEbohtp0mMmMgesLv1Poq5CsXmDRBatCr30s48gmWZWLqOraWxrAiznyIyR0RRgBmn8COPhJi1c6c5kD5ALd5JqtQn7DmY6YQoCUkSHc2EONDoHIf+WQO3pVHeHXPDvwiwXoYIgBc64zbDDDO8NHjV1D8XI4yMIuzaA7kyWAbkKlBbhOFgkuO4/waWMwavTQf8yuEatWpVNWeYKXJ+sPCDcL6lsYx0q5Uog1KphGmanDlzBs/zlLr+7T/6eh5YfZBee4vVnYsMx2kcx6EcXM3pb/c45d1LEnjo+JTmY4JNk4gsFjEOVdKUMbEZ0+PY6CF8ngQW2MPNlDMZth/VMJI826fGxGFAXO0RWg28xCTwQ0K/S0KGFHkMKgQM6DNiwDrQ4O5zn+Kq9LtY6B2mvFjj5NljaFoa3z2LP+6zHT/GZrDKOHwDVnsnbsue1T8zPC/MiKMZnhXPVTiNx2MajQZBEFCtVlWHkHa7fZlGCIMg5s/WAwZBxNc7Md8+r7C+KMmTJJNOaGEAmRxYDpCcJ4t0VNn13bvhf3nvS7wHF0cURbTbbQqFgvqbpmkqM0CyjISwyGaz6sYn7eolQFkgdjBZVhQyQRCwsLCgVEaidIrjmNFoRJIkKvNHSArDMBiPx4xGI2q1GqlUSgVMh2GorFVCDsnMieQBASpYU27IxWKRtbU1lUcEKAl8kiQqS0HseKPRSIV9y2uFQkEV/5qmKcucdK6THCQJFBfllASHZzIZgiCgXC6rTCWZjZoOApXtDQYDRSxJfpCQaJ7nUS6X8X2fQqFAr9dTuUvS8U3GJDO5SZIQhiGdTueCrCtZv6jLhAgSosnzPEUm2bZNsVi8wH5WqVRIkoRSqYTneYog7HQ6Kl9JSKZ+v0+nM8kwKhaLaj+FvIyiiDgJaQ1PAZDP54miiHsy/4nD8c+y4N1CWz/Nt5yPo0VdOssf5Y1nfh87ypH1dqJjkZAACQV2EDAkjCJCc0CiB9h6jsXTdxAVG+jphNXeu1msrWKXq1iEFEoZ9PVV4sjFLRyh2WpheFmK7CKvz1MsFXFyPu38/Zg4pK45hbU+RzCyCEcJcQDpesRg0yS3mJAuJZz8ksFwS+Pgj4dk5xIyc4lqvfxS41KEQ84wwwyXBq/o+udihFFuGVZ3Q6EKtXmor8DSLrDSsP4kBKchU2D/6iJ/cNgkny+zY8eOy2a3+0EgKWa4cmFZFuVymcFgQKfTUZNnu3bt4qGHHkLXdZUNGscxJ0+exA99pdiee1OLTHmBwiNv5MzoW7TyLrHuY8/bbD3kkWDRZ5M+Z7CYI02OEgtscRaNhHUew+p7VJOD9B4psjRXYBx32Tp7juqeMpmMxfr4cSLNwqSAgY2vbaMlYwIaaCRAhgrLpIwM9atBszys4ll6Gzo5vUzO2k2SeGjamAdOfZWVuX3syt7AyS9lZ/XPDM+JGXE0wzPi2W7e0sK90WigaRq1Wo1MJvOy3OyPjyJu+eaYUXzBAC++UJLAkW+BOwTXhbmVCXE0vzr5mzeGU0/Aw9+AT//nl3T8Yu2azvyRluRCioitqNfrqRwiWU6IIyE95EYmmTalUolWq6UCmEulkrJUTefoiPpEWtb3ej3Vzcq2bQaDgVIRZTIZRVhEUUSxWFSER7vdVuHKruteEOYnHcKmu575vn+BharVaqn8HVEnjUYj1VJe/iYWPiGRXHeiyZeMJMl7EnWOkFYSMigt323bVllFss1yuUy321WB3RIqbRgGmUyGdDrNxsYGtm1fYOkTBZWcR4Gck36/r36XYzhtuet2uxcQUdNdaIbDodoHy7IIggDLstS2xHYn6jBpYy9qKrH9CQaDgco+kmOaTqcVSSfKLniqe56ojKaJOuk2t7q6SrlcVmRXu92mY3+OrvZ5+v0+5mBArTY/IaPaT1Bvvw4dE43JdZAQo6FhkYU4xsiOyVTrJOt5tFSEns+SGD6J5WP399K/5msY992E6xvEXptxPGSrdYowDsmbWdZzdxJpI6J8wMa+uxmVjhMEAc39W2R3L9H95j78XA0Dh7A1kY+nlyNO/GOayNcYbmo8+d9NSrtiSvsSXvcxn3T1pVcbzgqnGWa4MvCKrH/iGH70IkqnVBUOXo9VqVJaWKC0cx8NNya15zDrPuitsyRJSL1a4oa5PP/6hhK2bTM/P/+yZDTNMIPgclsXZfLRdV3VkCSXy7Fz507W19eVtb9SqaDrOidOnCCVSk1qy2BM4eZ1arfbHAoOcOyYztGjRyeTgvNFNjfbOKQJcGlwDBMfjQKQxcDBwqbrbuERUmU3494Gmh6TzWdIDyoYh55Eu9dkMXM148CnE54hZIRu61T9JULHxTATLDtFameLZAf4moaTz2MVQ7aePENinUVLUmT6ZWIfHvP+ls2/OsMe6030N+Z48r+nZvXPDM+KGXE0w7Ni+staOoQ0Gg0cx2FhYeGydwiRcfzRuYCPnw44MkwI1QsxkzTrZ10QwhBIwHSgkAbv7OT3UXeSX/SVT0+6p/31f5mQSBeBPPzLz4ZhKIuUKDwsy1LvmcZ0+3V50J9WvgCqdbw83EuHtCAIlDJEgqmFfAnDkH6/rzqFOY6jukZINk+5XKZSqWDbtsrcOX36NJubm1SrVVUYy41R7G1iKWs0GkopJOMXi5UQQGIxE/XMdAaQ2KPE/iaklmmaF6iGxEYmWU5yPCVLSUK6ZRvSCW36mIi1S1QzopICFJEk606lUmxsbFCv15WiSkihTqdDvV4HUFY1sdaNRiNyuRzValV1jhNFjgSSA0pV5Ps+mqaRTqdVpzTZLzlWcvwkz0pIQcdxVNaRKLbkegiCgGKxqJRIci0JsSQkk2xDtjMajZS1TY6d53lK0abrOrVajVwup1RsYpmU67Pf7yuyTWxxkhcgZJRse233n5Nzd5ILVid/R556NFytiWXaGL0ycWRhZmLiZgnGBXTHh3IX3zjLWvbLuNfdhR0X2OyeYvnkT1AL9k2uFWuT8DVf4fTWERYWFqhWq4SDyefj6NGjZE8V4dGQmDUiT2OYPYrRXWDts7ux/SpJrJFNFbGzCZ2TOsOthLt/0+Ktv+Vf9PvgUkCu/RlmmOHlxyum/hmP4Sd2XGSpPFxzC8wvQWWeXL0MhRpm2sGMB6T1hHLzNLcVdcZezM0mLNYsUo7D4uIiuVzuMu3dDDNcWRAySNRHSZKwa9cuNjY26PV61Go1oihi165dnD17VuVWyqTvYDAgn8+zd+/eSXOXcoB2V46NwSY6BkUq9GihMcbAJGLMZIqvgoHFOqcI22McHKqZOQKjw+pOjT3ZNI7m0R02MZ8sMNxOYxgmRjnCWGmTzaXVc8ni4qKa4D1zxidojHCTLfzAp10Y0G326R316fF5BvyPfJi72FnaT5IUGW5ps/pnhu/BjDia4RkhM2hxHNNut2m32+RyOVZXV1Wb9suJk+OI/+kxl6+2E9xp8juZWF1IeGbeKEkmZFDgg2HAeAQPfhVe+07YeWiybBhCawtMC06feE7SCLhAwSEkhXS4EnWIqHRktkKUJK7rqvyaMAzVjKXjOLiuq7J2UqmUIomEbHh6XlAmk1EKmyiKSKfTqhW9WK7CMCQIAobDIb1ejzNnzig7mu/7imQQUkAUNBI0LV1SRA0zNzfH2tqaIhPEziZEzjS5I+oWITGEEHIch3w+f/4UJcryJr5yIUTS6bQigoQgE/JH7GfTyiBAkTNhGNLr9chkMhPly3lyS/KXhMSSY+N5nspqKhQKaty6rnP69Gll4RKLgnRRk/3MZrMqt0gKh7m5OWXRk2MuY3BdVxFQpmkyHA7V9SI3ULELiq0sm80q9ZJt27TbbXXOPM9TSiiA4XCojpWQhHJdyLkoFoukUinVuU/ITyG2hCyUsU/nXEkmleyL53kqDFxm6YRMS6VS57sAnmOz8iu8a/gZ0tE8Gk8VCoE+wM02SVEGYvSRiWkY6L4NrknsORy55U/pttu0O+2J+i5t07zhL+l0arTbXai0WcjUlL1yx44d6pym/DnsYzcSlzvEhOiuQdHfQz+3jtksEkY+HmNsL4OVNrHSCZl6wvp9JsHYf8l9/zOP/wwzXBl4RdQ/587BL1x38QWvewvsvxGKVTATmF/l9Ss57vGybKaLBCe+S9gfUCoWGHbPsHO+hnf6MSoH9zE3N0fpfBj25cYsHHuGKwWmaVIsFhmPx7Tbk7pj165dPPHEE8RxTKFQUHXW+vq6qtfq9TqpVIrHHntMOQauumYf5UqHe//YpM06Yzo45LBIGNAmYYRHwpgmEUM8fBISRmhEo5ClqwweeqhBGIbs2LGDucUatbmY3pZHMV/GLkG3l6ZSqZDL5Wi1WmQymUk0QdsgPDVmYTkCNAbjDv3BED99krO9LQYcBwL+iT8n8d7GXm5gR31+Vv/M8D2YEUczPCPiOKbZbDIajSiVSi9LhxDBY4OIN9w7ZvisljSNqThIFIuUJHD35+CBu+C9H4E4gXEfDr0Geg3IlyGdm6iV1o7AY/fCg197XmOaJo6ku1exWFRqELF+LS0tsb29rQgikXwLyRBFkSKFDMNQ/yQjJ5VKKRJKlCi6riuyQpQec3NzqgOYzHqI0kSCjqvVKr7vk0qlFIklyh/pjCIhz5Zl0W63FakjljXXdVlfX1dEj5AvQnAEQaCsT6IwEnud7IsU5a1Wa3L2NE2tW7KF+v2+stIJQdbv99U1KLYxscmZpqlULqJ8EVuXqKV0XWc4HKoxCXkiBB88lbck759WJAkhJcHcQggKWSMZU7ZtMxqN1HtzuZzKRhLiaJokEtucEFsS0C1EkEh4xc4mxzWOYzWrJOSgkIwyKy7KKVHBCSEpxKUQkDCxLA4GA0VWTqu/Wq0Wruuq7CuxwYltUK5n2Zder8doNFK5SJJR5TgOutZjS3+EHVGFCBcDCx0TJ6qx3j1OoJmk4go6Ni2OE+FTzNQJ6NM+FeLnspBus7S0pB7igvwQK91hx45VSqUS/X6fPXv2cPvtt/PYY48xNzfHsnUj3VPLWLUqnucyHo3pnE7o5h6gP3yY9HgZJ7LRfZ041EhXYkJXwynExAHwtMLpUj/cTJOiM8www8uHK7r+eeIJ+NXXX3yhXTfCLW/h0P7dHDDG3NlL0DM58kbM457N4vIKW5sbeFFCbFrMjdscLNpcm9N42PfYt28f8/Pzs7yhGa4YEu/lvBYlYkC6+Pq+z9LSEo1GQ036raysEAQB29vb6LrO5uYm+/fvV/b+Xq/HyZMnyeXyrC6u4KxXifCJCLEpEJEwwsfGwaNHQExCgMcAmywd+owfd3Eyacr1nIo4WFpaIp1Jk05PJiB146m4AqnJz549i9ew2B50aXVPops61dwy/VGfVE2j3CyShEsc5j3czM9hxlCo6bP6Z4ZnxOwsvQJwOb8wfd+n0WgwHA6pVCrs3bv3ZWGB192YP12fWMv+vhEyjkEpi54JmjZRFZ14BJb3QLcFv/e/womH4cd+EY58B2oLoBkwt2Py3sY5aG+CoUPjLBx9EHz3WTZwcXQ6HSULlYflTqejbGnS2l0e+iWnxrIsFUw8TRxlMhmlMJGHfpgojSbKjUC1kU+lUrRaLRVWLd3VYKJYGY/H9Pt9lekj5FGr1aLf72NZ1qTV53kiR5RNEnAt5JHYl0TxIsSL67oUi0WCIFCqIMkXEpJGFD4wyVoShYpY0EShI5Y7yTISJZPruhcomoALSDLJe5KOZTJ7IcdTCB1R08g4hZxxHId+v69sXKKwKRQKivhwHEeRaqJEEmWNbCuXy6nOcL1eTylf5EFEcp/E6iUKIiEWRa0jN1Ehq+S4iIJLbGSiAhMy0LIsRVy2221FIo1GowsshEJETXeOE9WcLCN2SVEeyfU6GAyUAkzG2m631bEX4ktyqKbVZpKZ9GDmv7LYvRUdm1AboyUaBjZ5linGO9Ex0DDIUqOnnyYVlMkGq7x29FvEzpi1a3+PlasGquPduXPnqBUWWeq/Bf8xmwWvxKFDdUqlErlcjnyuQPvePK3vZEB30OZ9RpGHa7SpHopIh1Ws7IjuyRF2fwUrkxC4GrqRsPOtEXb+2b52Lt1382zGbYYZvhez+ud8/fP1r8N/uOPiCxbn4bYfxl7Zwwd3F1lxIu4aFzm8u0Q3gMi0aFg5et0Ohe4Ge+cLBLpPqTvguh1Vto4fpVwuc9VVV71sRNmMrJrhSoVt2yprVGpviWfY2tpi3759+L5Pq9VC0zSeeOIJrr32WjY2NlhbWztfi/dI9vRw1ndSYAfbPIHFmCxVfHqY5M9TRiMCGkCMi49GnniUZziKCNxJDS4uh2w2i55YnDk6YnNjk0y1SXFxQlh1Oh1KpRK9Y1ncc3nK5k0UV1J4fpt03iU7l6W36XFD/Q5uKX2A9mMG9cwu0jiQzOqfGb4XM+JoBmCS+SLKmFqtptqIX+4P8lk35jObIb9+zCc8TxLFTAKO0TQu9KOd74Q27MO3vwyZPCnbQvv6Z0h95uP43RbDfB1N09HigLg4B9kCZIsw7EKuCP4Yes3JenJF6Gx9X+OWdu/r6+vEcawIF+m0JVajaVvSYDBQJE2z2VTKHiGOCoWCCpA2DINqtXpB9ytRnIjyBVDnSzKXhMSBiaJE1EoSgFwul5W01rZtkiRhdXVVkQkC2dbGxgapVEopgsIwJJfLkU6nVTaSqHdEuSP2J1EmiRLFdV1GoxGGYeA4jnqvkFwSFC7HUgifdDp9gRonlUqRy+VwXVeNRWxsgMpJ0jRNyYrldwkJl65kYteTQPB0Oq1CxkX5E0WR6rohaiQ57q7rsrW1RTabVeSQHCMhfsrlsgrhFqub5C0JiSfElKiBhBQUEjGdTqubtoSCCwE23SXNsiz6/b7aVyEep62OonwSYk8siELsSW7XNPEjdsRCoUAqlVIB7nIdhmGI3dxJnUN0nDOcs+4miiNFIK6F99PT14g0jzBxcZIyKUo0kiMU2YnPAJM0BhaFeBdaPMlDihMwggw7Hvl5ejf/JrE+KdJaW112P/4vobuAnrgsjvYS3zXgSBQy7tg06ibakTlSe5oMjmeJn6xh73E59IvniLMVWvk1zKNX0y+sc/NHBlhmmtG6RvWqmAN3hDxTffRSzLjNPP4zzHD5cSXXP+HnPge/++HnXnj1AIuv+2EOX38jb7G7+L0u+YW95LJZTDPFqfaIcW6B3mhEZtDHHLs03ZCcDqZj0xpP7pPXX3/9y5LfNMMMrwRIfS5NYMbjMYuLiypbcufOncRxzOnvdgn7ee5be5L5q+dpNBrouk69Xscfn+GE/ih2bFAhC2QpskrRTLMdbtPjLDFNwAYMJk9BHVxcoERvkKEwntT3rVYLz/MxG3Pobh7Lssl1djMaD+gPNhmbGuZiAevsCov7ErrrAc2TITV6mSMAACAASURBVPldJvvfkGOz3eGWN1zLfu991HNzXPOOiFLGYLQezeqfGZ4RM+LoBxgS3jb9hSYkw2AweI6lLy2ODkM+eK7Md0+OiM7/TSch9r1J9hDaM+QYaZP8ot/9NfjqZ8js2EMmmydpbZBNOaSWlznV7OAt7CJZWIXOeXtaEoFhTtrR2il49F6wrImN7fvEeDxWD8VCmAAqfFjawwu5IqoOsQ9JK095OHddV+XC5PN5ms2mepiXB3khaITgEcUJTIgsCXoeDieZTdOZQELehGFIuVwmk8kwGAyUgqbb7SpFj9wgm82msnKJqmU0GqmcG7meFhYWFOEgJI+odLLZLI1GQxEkcRwrEkSUNaIMEqWTkB6imBEyRt4jVjQhtxqNhspJErJECDwhfWR8YteT8ycKKCGtNE0jl8uRyWRot9vk83nVaUPsc8PhUGVCSUGhaRrValW1rxeyz3Vdtre3yefzhGFIt9tVGU2yb7Ivvu8rlZqMUzInXNdVf9c0TZ0vsenB5DMs16NkZ9m2zXA4VOem1Wopu6HImkej0QWEnlj+5JqWDK7xeKzUYbZtq452o9GIg4Of5LXur6GhEScxR6zPcqf1MUWIjWhwp/kx3hT8e/JJnSxzDNhglTegn889ChmTkGCSIpnQx+iJDUkAXorWxoAkPZwElHcPMD6bpmsfJ05iHMr0//4aWD6Do9WIn5gnqmzixk3sAw7pqE7tJovSDpPt7YjX/nSVE8e/SePbG8zfcIC5fQG5pef+3F/qGbdZ4TTDDJcHV3r9w19/Bn7/F55jyRSkDW46dJAfft+Ps7xjJ92zp7Bji+riIsVambY7z9lRSMkc0Rt0IIohjulEOgPP4zV6F72+xGh7nbm5OVZXV1/ivX1uXCn2qBmuDFwp14OMQ+qsSqVCs9nE93327t3Lgw8+OJnkO3aQo596giAcE8cx9RsHLL2pQLfbQdM0du1dZnTbWR6+ew2fkIABKbJ4oY6GTkzv/BZ9YBHwgNb5vzUJCBgM0jipiQpc9x06bo+ATfQgIdYitCfq6DlwIodjpzqYxTPE3pjr9r2ZVLCAs9JBL4zZW9nL4cOHuPYai8VcnnNHOuy+dlb/zPDsmBFHP4BIkoRut0uz2SSVSrG0tKSUDQKxDl2OsdzxnRFfbCVM2HUQS1oMoBtMSKPziqPk/OueO1EJRT68/SexHvgymXGPoNec7Jss+/afhvoyFOtQWZoQT80tGLSgWJusN5OH+/8BmhvPOd7pbldPh7RQlwwZUWw0Gg0A9XAt4dkwyTqCCcEkVi1pd55Op1WujyhjisUigLKCTfuC5aFcFCBbW1uKkJnO+NE0jV6vp7KP1tbWFGHjOA6bm5sqwwhgfn6ebDbL1taWsjRZlqXUOZJflM/nlXJF13VFnMjYAZWT0+v11I1CyAwhI8SiJcdCLFz9fh/HcZTqRxCGofKaCxnWbDZVpo7ruirrJ0kSpdoRwkaIINk3UfZImPh4PGZ+fp56va4ypXK5nDr+STJRxEnnOlFwyTYkvFzGpus6vV5PWfCEEGs2m2q8QnhJ2KJcd5IDJWOUEO/RaKSUTzKuUqlEEAQqjFxmz8XyJ6oxUXeNx2NlTZP3iXJK07QLlEnTx1NCzYUcs8lxm/tvCfFItIgkgYPh+3jY+lOayWO4Iw/dz/AEXyDB4r38IWPajGkR4pGiiIFDRICBTYyPjvkUbxyZBFaXExuP0h9Mws8zjRJzvTzpaI4oCUkIcRlz5Pg9HDi4DzPKYzTz1PZoZNIZvC0Hu9jFdV1WVlaYm5vjm3/URf+bt/PlTxfRdI1b/5XPdT+r+jY+43fXpcSsq8gMM7z0uOLrnz/5A/hv//biC5p5CCNIOxgHruOnfu79lNMOra1zVEol6vU6hm1zj1Fl2yrQ1EecOr0JhZC5+Sqp5jY9yyBe3yJYqHCd7rJQyDA/P6+aVswwwwzfi2myRCaFpXbauXMnRx45zqOfrFBPr3Kqfx8uI/zv5EiW22jZEePRmHyqRGEZ5vebnD5qMuAMj3LyfN3jAjmgDZQxMIiY7s48h41BnPh43qSu9oMIixIBIR4Ra/4TjLkfBl1K7KbMHur93dT35pgv7aF9bkCcHlMplbj11lvJZrOc+YrBXX8QEfg2BSszq39meFbMiKMfIEgWSafTeV4dQi5H4fQfT/j8fWtqO0/fpn7+i6S9PbGZ2c7592igTTqimeksQaZEY+PkU4vpOvqhWwmv+yFIZaDbAMOC2iI4Dqw1JhlHhSr8zX+Z2NWeB4QAuRikBfvTIUHI2WyWUqmkCCIhhiREL5vNKuWREBtzc3NKhSSk1HTLeiFDgiCg2+0qqb3kzQiBJGHPolaZXo/ruqqtvKhKhCDo9/uKdBECQsgdyWwS0mQ4HKrAZunENZ2Nk81mVdc0sYiJgkgUUqJQkgyb8Xis8mriOFZ5RmKpE4uUkDrNZlNlPQmxIVYwUSiJwghgbW1N5fJIlpGobCQ0WkgaIdnkOMr/hmEoJVGxWFQkj2QMia1t2rYnWUPTxyCXy6nzEoYhvu9jWdYFdrZpm51c79M5UlLcCGkk51MUTRKYLSqj6eMpqjSxv0lOlOd56niLaitJkomf33fYOX4PaSNP1zlGnMTEWgiJhoaOnthcO/p5OpzkOj5AiV0Y2CRMOnxYZEhRpMFjDNnCJotNhgiPIdukKOBQADRizee+xd/g7Lk1FUBebu7EicoTVZJmYcd5BmwSJSHnzp3jqtouEjeD3krj2wl21aV8W4PAcNi7dy+DzYj+396IYWlkFxIiD+7/HZsd/yyivPfyzHbOZtxmmOGlwxVf//zFf4U//t8uvkBhB9RqcOYk2Akcvpmlt93BZrdH0J/YzGu1GrVajfuaY765EdL12hT9AZrboZ8tMvRjqu6QnO/SCnz+hwWTuayD6yYsLCy8LF3jZpjhlQiJZohGBke/mNBqJpi1RXy6WGYGQ08zjM+QwqT9aIq+1mb7yRF5qvQJ6BHi0wVSwPp5taHUAHkmtZEGlIjQgZAcFeaXDLSM95RDoD0mIsEgJs88HkNEoRRisJjbTyas4vaGHHEfw0iPWax7LCwcpFQqYQQZHv2DGr3gGPliBtucm9U/MzwrZsTRDwBEgdHv9593h5CXKqCwE8S8/8Ex93YT0gbULEieK/Q6jqFQgSiE6LzNzLZhPJzYy4Z9clpEdL4zmaZpsPda3Hf8DOy6GqzUhIBK4sk6DAN0HSwbvvv1500aXSqIXU2ICyGTUqmUUqCI+mVhYUFJ6XO5HEEQKCuYBB67rotpmsqqlM1mGY1GRFFEoVBQ1jTpWDYd5iykkRAR3W5XhdTpun5BQLYQMaI4AVQ+j9jrPM9TNrper0elUqFSqSgCR8gxwzDUa91ul0qlQiaT4fTp03iep2Y9JfxaMn6q1aqyhwVBoIgNCRGXwEKxcIl6plgsKluYqJyE5JKbv6iEhAwSgkZshdPbEXJNCJfp7m1yjMIwVOHjMjYJGRcrXBzH1Ot1XNdVxxhQZFcmkyEMQ0WkwVPKMt/3ARTZIwoxIYUkn2laDZTNZlUullwLcozknEu3NdkHUVLZtk0mkyGbzSqbmud5lNOL/ET/c2STBYh0kiDANdqkKGNFWUzSgMb1fAiNiRQ7IUZDQ8MCEiJidEzyLONQRMckwmfAFnkWGLKFr/fw4h7/NP8xtqIH0dAgsBkO2hR713Imvo8SqxTZQUJMmir7zbdjmzHRZoXMjjF+T2f5XS1W3tNkq93m4N6DZDIZzqw3iD2LTGVyjM0UuG3ontIuWjjNpNozzHBl44qvfz71O/DJ/+PiC9oluOpGQIeNJ6FUhZU9sLCM/+QjhPvLLBzYz9zcHI7jcM96lz850eHYWKMfajDukWgamBpB8xy95iZRr8lCxkEbDQlsSzWj8H2fM2fOqOMg/6Z/v9hrl+K9Mjn0bO+d/n+GHwxcqec7Glr81XtTjLd0xqFGpNlYqe+iDdIshK9jTIiPS/O4iUcdlyO4HD2vim7QpwOEgM7EZ2EAmfM/J7g0SVEmTRqTkPpOCyef4DhFbDNNu9sgJkVIm5AxHgEGDhZL1KixbB5gOAipVLNEoc389RE7XlNgdfcKN910E+12m1EjpD1YZ5g+QaefsLx4CK8zq39meGbMiKNXMeI45uzZs7iuS6VSYc+ePS8o7PFSz7h1w4TD3xjROq9+HIcJreA8afT0L6AkgUFnElgN53OOzqPXnNjLuk20jZOk7/xzikZCVCpNuliFMaNb34m2fgLqO8B0gGQSiD0aQGsDTj026ax2519e0n18vpjOQQJUd6pptZLY1aQz2rSCRggQWUbUJs1mE8/z1PLdbhfHcZTaqNfrKeJBlCZCoojySQL3ZB2SiSMFnShjhMwSkkcyi0SpI5Y5UUNJK9Ner4fjOORyOVKpFNvb2yrcWvZVQq87nQ7ZbFZJgqMoolKpKLWNqLPiOGZhYUERQYVCAcMwVF6PrEOCsSXvZzwek8lklGddFFr5fF7tj5BphmHQarWUVa/X6yliRY65kFKSITQej5XKSAi96U5z8hmzbRvXdWm324rcKZVKirSSYy75TqIo831fhYnLcRDVVT6fV4owWafkPYnFTtRf06HZQkIKiSnEnQS8d7tdde0EQcBt0UfJxcskekCixRiJg0cfPbZIUwU0EiJ0TDhPFyXETAeWTV5LSFMhYISOjoZBjjo9/TSmadLLHmUz/i7puZADw7dy7cavYERpevoa3XgT5/z6AoYYuoWfamAHJaxeDi2tMd5IkV7wad1TI3X7E+zcs4tCoTC5Zu02ulMnGWcgD8FwIlAsrDz7d+BLEQ456yoywwyXBld8/fPxX6f1ud+9+EK5ObjmNkjl4dyTsHEWyjm47o0QjSj5Q374xn3cft1+VlZWqFQqNLpd7up47KuW2NoYEVkG0TjBNk3sjEWm06aku7jxiLfuWOL222/n7NmzpFIprrnmGra2tlheXr7Akj/dHXP694u9Nv271DrP571itd7e3r7oe58vXgiRNf2zWOBfSoLsmQixGa5cPNO19/gn0wzWQ3Qzxo3bhFGMU7VpB2eJx1Uq7OM09zBimyEtLExaHANsfHwmFtWESZZRjwmBZAJjJuSRTYJFBptUKUupmmXUHNN5uExETEBAhhFDdEImltuIDgY5YIlW2AViTjUDFkpLtB5N8Zr3LHHLLbcyGk2iK+o7cpTyNuVknnp1gXCkzeqfGZ4VM+LoVYjRaESj0SAMQ/L5PEtLSy/4pnSpb2JxkvDvjnmqaHrKkqZNcooMSzYMZ4/BiUfgxjc99TdNmyiEfBfc0WS5f/wzki//OTYB+nkCodVqMdTtiTKp3YDv3AW3vQtKdWichSfuh3u/CMMetDah31ZjfHp2zvOFWMFeyLKiZhF7EDxlcSsUCoxGIwqFAgDlclm9LkHX0nZd1D3TOTbT2UemaSqywnEcUqmUUqpIQSeWqulsHgnAFuLBMAyKxaJqFy9qE8k3knXW63W2traU8gcm3dxEbdTv99W2pQuFKHeEpMhkMqotvNycMpmMInZgQmhJwLbneYpkElJHbFViSROyA1AKIcuyyOfz5HI5RQ4J6TVtP5vOpBKLXb1eV/k/oggSAsb3fdLp9AUzuPJ5kt8l4Fy6m8l7JDDbdV2KxaIap6iXCoUCpfMEaZIk5HI5SqUSnuep9wohJWOV8ybEkmxLrqFpUq7b7aqg8EqlomyA0pFPrgm5RrLZLMXxMlpoEMX+RD1IgBVlOcv9WORIUyUBdJ4qCvSn3Xok/LrHGVJ6Hi3OgRaiJRZpvYQdFdFHJsX4KqJj7yYOIdI9hvE6ulsgh0lCRJoKhuagJaAFDkmkk6ChpX10dPzNNMHAI/6dW9k2Myy9NmbvB7bx9T6Fn7iH8P97K8MNHcOCm3/Zp7z/4oXTpfyefHonwxlmmOGF44qvf1wXfnwPk+DbZ4Fhw1WvhWtfB8cegI1t8HtQn4PVfdBc58bdS7z7mmu5etcKO3bsYGtri3PnzuFU5zFTGRZyKW4a9rnHqLLV71IwTfYlA/alhmwNGuTzFrdfe1DdO/fs2aMaVbzcD3CnTp1iael5pPM+B14I0fX01/r9vooGePpr0wrsi63zhWzzmeD7PqdOnfqev18uIkvTNFXXSA33fNcjP18KXA7b6PPF0/dp3NDRIh3d0OmwRlarkg4WqF9TpfEdm/Swymm+SoiPgUOKCnlCYgJSZPDwiPCIcPHRmSiOJt8NJlUcdBIMfGK8TkT722fRsMmgo2MQYwAGOXLYVEgw2OYkIREbHDmv3g6os5Ncp4oZ5nj8D+v0PmVRuibFWz66hJlOePv/rvPt/3OBYFtHN2f1zwzPjtlZepUgSZ7qEGIYBrVajSAIyOfz3/eH+8V+WcdJwpYX8zunA/5kPaQTqBVPbwW+fSfaw3djFCtk7/8inDlC94O/MVEKiSpH0yf2sv+fvTcPkuw+6Dw/735535l1dvWpPqSWLMmHbFmWJUCWFxB4DTZmGQYwTAQemGB2BsLsBhDh2YUY8ATsErAM5pjhMhhjGNtjg/GJkSwZWbda7vuqrsqqvO93v/0j6/frKkmWddlSS/mN6OjuqsyX78r3fu/7+x7KVpPa8fun4datOi2QVfeKomAELqEzIsoWIQhQRj1UVSFuraE6Q4JTj0wJKKaEhCBphNLluUKEHguFCSDJnGeCGKSNRiOZcWNZFr7vy5p0TdMYDocyvLNYLE737dZFVtykRdBxJpOR4dKj0UgSO51OB9d1ZUubUByJYGpBICSTSembFhXrwk4XRZHMPxAqF9d1ZVW9eJ34I0groSLSdV1avcIwlHX2pmnS6XR2kGHC0tbv9yWBIqx4giCZnkqx3E+i3l6QJsKuJggTkfEjtl0cb5G9JNRGYkAoMqW2K36EzczzPNLpNNlsVu4jQXQJog2QJJYgiAShJogckQUlzqHtuUOCpBHHP5PJYFmWDBJ3XXeHDVBkQol1tyyL5eVleY6J42wYhiTVBNHW7XbpdrtSnWQYhsxeGgwGkoRyHEfaKofDIYZhcMH/AoeV96DG2pYFTeUkn8ahxwq3EuKiI+qdd1YjxsTEBIR4eAwxlRRWVJg2q20tzwxyOEYDjyFqZGM7c/jxiK7eII4jQq1PIirxSeMnuTl8P3vDOwlxUP0EBhl8HPobbSq1EpEfE7csUteBlYlZv8/AcVN4b+hTep3PkR86QzpYJjOvka59ewersxm3GWZ4frhixj+XzsOv/gTPRBodPHiQ8Oa7OJWcmzbB+iGMBqDoUJuDzhpzVx2ldtNt3Lw/zSOPPEK73ebqq6/Gtm0GozG5ZJ5xIkuuMCbT7BOaGkUzwOg1MJ0NlGGbo0ffyJ49e6jX62iaRq1We8WpXl4IgaFpmsxOfKlw/vx5du3atWP9n6vy65l+92xUYWIyTUy8PZflPlt8MyIrjqe5nhsbG0/53XP5/wt97dNh5faQh//UIIw99plvYRR0mHvTOmpS5dwDTZLMcw0/wgYPs8njdDmPxxiDFAmyTDiBRZ4RDiomESEKOWwMNGx0UnjUmeCQoYqDhYJOhINHhE0GH5XUgkNrbQOHAIsMBjBkQMgqACZHCPGJh1nKmUVyFZvh42nu/5DPm/93k2vvynDwNof+OYVkjdn4Z4ZviBlxdIVDWGna7TaJROIpDSHPlxV+oQOIVSfi3Y84PDGMGEdT8eXWrWXnC6MIPvmHpE/dPyUaknmCt74HLZUl1NRpLpGqX37tmcempFEyN1UqMW0mEzYaVVUxdZ3UA3/P4PXfQ3zdrYQxFJ64m0mnRVhdxrr6tYyPP4x11WswM1m01VP49QvyxvhcIS52gjQCJMnwjYKyhY1MIJFIANNMn+2V6KJBS5Adw+GQcrmMpmkyNBmQRIsIMlZVVVqTRAbSdjIrnU4zHo/RdV1aqUT7WGIrK2o8HsvZR0G8iAGBYRgy2FqooEql0g5rmiBxhsOhJEgEKSSsULqu02g0ZOC0aPjq9/s7FDyiVU2QHoJYG41GZLNZBoOBzOsR4dqWZWFZFnEcS7uVIEtSqZQc4AhiRwwSfd+XgwVBoohtAtB1XYZeC2JpPB7LfSoeWmq1GuPxeEeekbCKJZNJ+ZCTSqWwLGuHDVAQR+l0WpI/URTR6XRkYPh29ZIIDRdqIUGSid+LfwM79ofY3iiKZB6WsD2K4yRIUbEdYh8PBoPpa6x/IGH8Cm/03o+GxTE+ymf5RVR0dvFmqlxDAh0NnQAXlx4GKQxSxIRT4kh1WdX+mRX/tulXnQAFjRCfsX4JTTXIe/un1zP0qYdfWSWjz6P7WSI1YPmqMvX6F9nVuQVDmdokg8hBwyJBAX8ASgRWLmLS0MFXMAsBjYcszGsnFAoF0iWTSiVC15/dAObFfNDa3pA4wwwzfHNcKeMfwhA+/t/hr/8z9PtMh947G4vS6TR3fN8PoB+9ma+3u2DUYOKD604t9vkiqj9g775DJOYXGZ4/STO/zP79+9nc3MQ0TfL5PHNzc7y7M+LPjl/kgYmCHsFb8tBsOlysNxk1LnD1ygLR8lXc2/YJG12yliWVzTO8vPHNiIwXG81mk0QiIRuAX2w8G6JL5C3mcrlnTZB9K1RhIrphB8GxD6752TwP/W4KfJM9t8Pe9w6xDZvV+1Nsnr1EdjRPxH5cBrQ5SYIsDgMsLHTSDNnAJGT6BKJtjZUcImJ0QMMgmE6joWBjk6Jq1FD9JC4xHi1K5SGR12Kj6eMzwSRPnjRdInSSHORtU5WTYfHAqc+x0ruWlYU9DB+bJ5udbo+dBfvaZ08YzcY/r07MjtIVgKf7coqGkE6nQzabZWVl5Slfuhf6pX4+M25xHHPfxOSDD0645MRMtgRDETEqMXGsTMkgFAh8+MNfhge/wABg5TD80p9Nm89UbfqaOAZvDL4/DbaeDKE4Nw3I/sTvA1O1UTqd3qHUGK+exVj/XYLAQ1E1hov78ecOECdSBN23oq9cg2NYOIGPtnSI8IsfQ3XPSzuObdvous5gMEDXdYLg8iBPhCkLVYcIDR4OhwA72r6eLUQWjlD2CMvZaDQikUhI8kV4/3O5nFT5AJKQES1o4kYrcnC2k0Cj0YhOpyOVKaY5rQEWditBgIn3iO0Qn+V5HsViUeYYwXR2TqhehLJm+811e6aRyOkRxJNQ1AhiwrIsNjc3SaVSZLNZstmsVOQIUkQcA/HZqqqSy+WkpDqOY2nREnY8cawE+SKWKYgh8dndblfuD7EN4nVhGMpgaNGctl2hpGka3W4XVVVlbsR2ibcg4drttrQ4appGNpul1+tJ0ki8R3yuIEa3B5qLpjgRXC1C0AXpI/KOxP4R+y6RSMjzOZPJSFIokUjIB6319XV5PATZJUgoQdCJbYmiiK/xIe43fl/uqziOCfH4c95OlWsocZA7+U0u5x1pRHio6KjYECmslj7FXPNGYjXCiBIEOAT6mNHiQ9Qu3EUch8RATAB6SCU+iupaxESMlSbXn/8Vnkj8BY61Qd9okxguY1NBRUMlQTxRIBHitnU2WgqaEaOmYtKHRnQ2NjAMg0uXLkny7enw5FlQz/NYW1t7QTObDz74IJ1Oh9FoRLPZ5Etf+pI8H3Vd5/DhwySTyR3r8fDDD/PBD36QP/3TP93x889//vP8zu/8Drqu8853vpN3vetd3+zSM8MML2tc8eOf4w/BX/4W/Ms/AD5TxeXlZScSCa655hr23HgTn7Z2M+gaUDoCmxfggS/AYB2yechXKB+5GntpCTVV4D1H59ldTMl7/EMPPcT+/fvldeOdOYdRs4U3mXA+sjhzfoP66WOsFDIsH3w9xyYKqc6YtUs97thbJZfLvaD9NcMMzwfPRhUmxjFivPlSYWNjg2w2Kyd6BVb+I7zpZ12gj2GkaLWWSSaTvO8TAQ9+4QKd0yMe+H8XCZ02qn8TDVYZscEFzqNiEOEBIxRsYlQCNgANC52UrdJxLGL6OHTIUMPCZOhPUHBxmaAR0XhUpbS3htbUGbFJAOjYVNlHhcMEhOSYI+HPE63N46/vprtaI3VD/LR2yKfDbPwzA8yIoysOIgB5OBySz+fZu3fvMz7kPF+59fMZdMVxzH884fHhzRztJ9vRYjEQi9EvfJ3KX/wn/NOP4YyGDMXL3vfrUFncFpS9tQzNhEEX7dN/RLh2HqwEnPgarJ6SnzAcDslkMvJBfTgcwjVvhGtugYU94Ezg3LEpAVVZJEjn4di908XnipivvR3nk38kyZjtN6jtpBEgiQhgh/1JvE7s9+dqexPLFA/kiqLI2dM4jmWlu7Ciua4rW65GoxGFQkEGOwsCYzKZUCqVWF5ept/vS8WOID/CMCSTychcpXw+D0C/30fXdflzQWQJQqZUKuF5HrlcToZLC9WPZVmEYSgzh9LpNOl0mlQqhaZptFotcrkck8mEjY0NMpkMhUKBXq+HqqqymU28XkioxX6t1Wo0m01p3xLZR5qmSVucZVlSoWSaJpZlyRwnsa+32xSLxeLU5mgYkjR0XVcqurYHayeTSWkLFN893/dlcLY49kIRJFQ8Qtm1/ffbz1+x7oK8yWQyMtdKnHOmadJqTVsAxXkn8rLE+SZUZ5qmye0ejUY4jiPVQqIlbjgc0u/35fuEKikMQwaDwY6sKHHui/Y1YbETBJMgK7dfcyJC6jxMnYcZ0+Q2/hMWGSzyaKhMiaSpimh/80dIxGWM0AaUqaooSPMF9f/ju3grqqITKxFBooMWm6hRBjexhhMNQAtIRlXsjI476pCKqiSpoWKi6B6B4mEEaVQ0FG16fYkDBTydREajsLDA8vIyKysrknDcjqebhXRdl06nQ7lcfsrvnsusaL/fZ2Njg/F4zGg04sEHH5TKsyAIyGazHDhwQK7Lhz70IT7+8Y8/ZfDq+z6/9mu/xkc/+lESiQTvec97uO2226hUKs902ZlhhisGV9T4OKqEMwAAIABJREFUJ4rgs38FX/gYHPsayEKAy+tUrVa58847ueaaa/jNhskgswK6CWcehy//T7j4GGSqcOQN/OBbX0fFsgh0hduP7GNRC+T96XWvex0PP/wwruuSzWYZjUb882qbr2wMWL24ip5M4R5/BDYvkLrtZ1nzVI5GLvq4R1KDS8m5WaPRDC9rvFxslN9oPQzDkCp+oc5KpCwO31zmZPUkbykVeORDN5BppFCbBYa06PIY05GVTYAChECX6bWigItHmOsSOVtjFmJUJoQEgD0dzzAhreVRQ4v5WoagPiQxyuKjM6ZHghRzXEWeAzi0uMC9FNjLfHwUM8iSLYesrKw84zbPxj8zbMeMOLpC4LouzWYTx3EolUrfcj/68xl0fWwz4Pcu+oRst3nEcpwklnfwX/6WxqlHaDUaJJNJ9u3bh5Ivc+qqG6dZRsqW0khhmmc06sGxrxLuvwE+/afTtrUtCBVIFEUyeBmYqpd+4gMQeFOpd74C83vhno9Dpjits93aTs+ZTD9v2/Z2OpdDs78Znkwsie3cTgw8F4j3CfuSoigUi0VM06TdbssH9kKhIEmdXC5Ht9slmUwyGAyk7Wo8HksiBZCBzkJJ1O12JfMvQp1FDo5oWhOqE0EOVatVST6JUGXP82SYt2EYrK2tyYygXC6HZVkYhiGJItM02dhSeQg1kmjzEuSFbdvSjpZMJqUiSuQkCWWOWJ7v+8RxLFVC6XRabodYN2HNE+1lpmmSSCRIJBL4vk8+nyedTjMcDiWZVCgUCMOQXC7H5uamtHLB9PwRuUeVSgXHccjn87RaLak6SyaTkswUJJdYnqZpOI4jiaNcLicVPUL5JcioQqGA53lyfURWkjimIiR8+/fAdV3ZTiNIJrH+4sYtSCdB+gRBIHOUBMklzoMn2znDMJSEJkxDryscxmdMl52zWGf5PGf5PAC/SA8VA4hRUFHQ2RW/FWUr/2hqVVMhDjlY/ze0Ml+j4BzB07oYJFBUhVCdEFljtCgmDCAMIiJjzKlr/gvXKf+K6IEqxDGaFUytIpECUYyejNFtBX8ck9ntE/ixJNKe6SF0+99wWekmlG/PF3fddRcAv/zLv8zBgwf5uZ/7uWd8/a5du/jt3/5tfuEXfmHHz0+fPs2uXbukcuDGG2/k/vvv5+1vf/sLWr8ZZnipccWNfy6dhns+DV/7Apx+FMIx04fCKUzT5LWvfS233nortVqNOJlhvWdA/Qycehwe/ifYOAWpIlz/Rg7MFzkxDLmtFNG4eI7HP3ecta2JItHkqes6p0+fZnFxkbaW5A9Odgm7TcKNSwSbF+CRf4ZcleXdKzQ2G4wVBz90MewEifzMpjbD0+P5kq+vNqiqShyq1B8N0RIq1QMWvV4Xz/MolUqErw+5/q4Up0/n+OO3HcZjwCqf2Xp3zLRdTeFyBmQHyNDfSJEih4dPAhOVmBAfDR1dV3ADn37YJkGR7niMeWCIPVmgd1xDpYiGzoh1ShxCQyVLhWwyie5B6UBM/Czmt2fjnxm2Y0YcXQEYjUasra1RLpefU0PIC5lxg+d2w9j0Iv7DcW/b0ChmR5xRFKCMB2T+/o85/Ve/J0N2ha9+8+Yf3KY0Yuvf8ZQ4CnyYDMAoQ76MMurJdbMsS+au7CCO3voDU8vbZASWDb4H2SJYW5LHWIGrric2E5DMwN2feK67B3jmJjZh19quRnouEIy7CLpOp9Myn2Zzc1Mqe4QHfXsAdL/fl7Y7QU6I+nRA+rVVVWUwGDAYDHbkAAk1knifyPgRFiyR0yOUUMJSJerdO52OzBMSuUWCrJhMJnS7XeI4JplM0m63d+QZCdWXUMcI+16pVMJ1XXq9HoZhSHLDMAyy2axcx0qlQqvVwrZtkskk/X6f0Wgk1UYi7LnVau1YH/E5Qq0VRZHMLRKtYk9urSsUCjiOIwmYVqsliRhFUXBdF8/zpBVMhJCL7er3+zvUQoKkS6fTcrnpdFoeUxGQLYPgt8g0kVEVx7FUg7XbbXmcxLoKgmgymZBKpQiCgH6/L4OvhdVRnK/CrifOLUASUOIcEd/FNHP8OF8izRwKGif5FB/lh4h5KoE6okmeFGypjgC2X9UUVCBCRWdlcgc97RiD7HFywyPokUWkuhAaWM4yoeITKyFeYZXkgS6TwEe9+j4u9RqsnPwx4gBUDPRESBSoW9elGM2MUTUFfXlT5js914fRF/PhNYqiZzUIe9vb3sbq6upTfi5UlwKpVEraZ2eY4UrFFTf+6benKqP7PgtnHwPcHa8tl8vccsstHD16lFQqRbfb5eNPbEJnMm2MXT8HiQzsvh6uvxnwSdgJQndCe6KzsLAgyw6KxaJU2pbLZdLpNJubm/yLlqOTMlEdn1jbhFQNDr2RuUKC3sWzxHaOU07ExPFBL3FzqSDvYTPM8HLDy4W8eqb1GNYVPnxnjm7dRY8slr/D4U2/MZ08TafTnDt3jvX1dQqFAsmCy6HOO/gKv8E068xgSizbJNnLmJMAJJgjR5WCmSeRSdBrTVBJ4dIlRZ4wCMmSR8Ogki+zdHWPUqlAtVpl7R6b1qf2kDILpMIahq2ie68nkU5MVfWxCVpE7brnN8ENs/HPqxUz4ugKQDKZZM+ePc/rvd8uqfZD/Qh1+1t2ONVi+Ke/Jf7dX2DsXyaMhC0olUrR2H8dOKOpDU0ztlRHwHgApx/ZyjyKoduU5AYgA4RFTky73cY1k0QrR6YWt4wFiSQoGrhjuO7N04aSiyfgyBsgDuHRu2FpP+y/Duvi1yUJYhjGTjLqabCdNBJEishZEiSDsFTFcSwzk0Qe0XaljNjvhmFIsiGdTsvMGrFOYRiSzWaxbZtMJkO73ZYqHWFbEm1m2WxWqmKEVUnY8AThs71hS6hHRJMYIPe3sMWJfB0Roi2ycQDy+Ty9Xo9yuSyVTIuLi1y6dAnHcdizZw+tVkuqoITqRtwwPM8jmUzKRjFxLIR6yDAMqtWqJG9yuZxs+RL7rVQqyeBtQSqOx2OpKtF1/SnEh1Bcra6uSoJKhHtHUSQb8KIokmHYpmnKHCZh6RL5QYLoURRlR36V2NbRaCSJoHQ6La2D4jwWZNLm5qZsQzNNU/rrM5kM4/FYHh8x+yPa0QaDAZZlkUqlyOVyzM/PE0URo9FI5ih5nsdgMJAkl/hscV6L9RXrL/aZsBOaprkjEP4u/oAcK6hbt5UDvJ0b+Tfcz+895XtzkX8mSQkFfaogkpY1AAVlmohGTISn9sj7V3Hm9R9gePEY8+feiR8PSfo11CgJqguaT5z1MJMq/nhqMxwc/CzD6BDp+rWghiTnIlLVmKCbYFRXSc0H1G4aEb3xNIaRkd+dZ3vte7EHs4Lkfb5Ip9MyqB6mD9zbB1IzzHAl4koZ/yjE0KrDx/8rPPpVOPs4TyaNXvOa13DHHXewsLCA4zj0ej10XWcDfTpO8SKY3wX7DoFqoB16DVdnTaz+JnGmzC1vuIa8Mb1G1et1vv71r8v7/fr6OsVikVGk8NjxU3hKDjo9QIOlA7B7L8N+kxNfP87elWW+HpqoqTRvLuVYjW0eHMTckJ0RRzPM8Ez4RteGz/xbi9EFDS8YMqBP7zMu+Rt0jvywJ3M8G40G5XKZ6hGVxj0ub47/Dx7gIxgkCRgR4pFhjhiTkBEqPhYWoadRPOJiNy0aT3jY2ICJj0OCPBo+dgYOHNhPKjUdp+/53wqcjQsMHphH0aGQz1GYT+A1kkw2dDKLEStvDbn2J55fKdBs/PPqxYw4ugLwfFndb2c4ZM4Qs3tPUhpNlwRf+hhMhmSLRXbt2iXtQblSmbGVoaUEeKGP78bEikpsmJjH7iMKA9A0lGIV7ZMfIg4cQi4rIUQDmbAy5XI5gnyNTuAQqgqYCWSuwKADwz7oBnQbUD83JbWiGNobcOB63FMPA0i1zTeDUGOYpinVQCIcWoQVj0YjKSVPJBIyoFhRFBmsLR7gBYlhGIbcJrjcfCVmF0VmTaFQYG5ujs3NTWknE1Y0EeAsPh+Q6p/JZEI+n8cwDJrNJr7vy89zHEd+vgjmFtlC2WxWhm4Xi0Vpg0okEpimKe1OlUoF13XlOWjbNoVCgeFwiK7r7N69m8lkQrFYJJVKyZwmsd8EudLtdllaWpJWt8lkwqFDh3BdlwsXLsj2OFEpLIiVAwcOSAufCL1WVZVsNovv+1iWJTOVYJphJFrpKpWKJF1gSmY1Gg1ptdM0jfn5efr9Po0tu6WYORaEoLCECWtZr9djz5499Pt9JpMJi4uLOI5DuVyWGUTdblfuv2w2KxVAYl0ymQyLi4tyfUUzW6FQkComYVNcWFiQBFQQBFSrVbl8QWxtz6QSJJg497dbAtn2fRsOh5LQe/JsTo1rJWkEoJNkf+oWjsV/Ir3/goz8DD9PhavJsICOtaUwiolhG3mkEROjxQnwdc4/2uZQ+zCTsI+OhRFniYEoiqHQxmruId99Dc74OOlkloiLBHf8HUr/HOowz8HvPMChO1Kk0ylcxydwQ8begGPHfEmCvtSKoxcycNq3bx/nz5+XltX777+f9773vS/a+s0ww0uBK2H8k9VhcvEMfP7v4NgDcOY4cHn8kCzX+F/v/C5uvPFGWq0W9Xp9OgGQz+OpJkUnom0G+KV5ovwc0do5DqQC8gtFsgsr+KNlvjNc4+xjD1Eqldi3bx/79u2jUqnw6KOPSqVovV4n0gzi5ipY7rSIJJ2HyEXLVknHDs6wi7t+nlS+SiaXJlEoUzPhgWHMDdkXtMtmmOFVi+YxjTicln/0OEfeX6F/wiSXS5DP5/F9X47T3vZLVT7+0w6ZC1mWwhtRURjRYkgDmxQQ4pPCJyBAQcFl0jfonfMJcRnSwcbHIkuHsxStNFrrCKPzYC5YGHkL2za55f06oxMB2qBA7YDF7ltUVNUlCl2iAHTrm27WM2I2/nl1YkYcvYLx7QqHjKKIFafFfGuDenKZWH3Sl7+9AY/eTTqdJpvNMhwOaTQaUFli8rafIc4WIZlBj0OMKCaMY8z6KfIf/gBqFKLmK/idBtGoT1QqScWECOoV6hxhxTLUNkQRaqdBlC1MySNvAuP+1JY27m9rdvPAMKeKpuiyeujJ+05Yg0Sj1/ZWKkE4APLhU9i9BFkirHki4wamDLnnefIBfTwey2WJmuFqtcquXbtYX1+XJEKxWCSRSNDr9ej1eiwsLJBOp1FVlcXFRVqtFo1GA8dxGI/HslJeZLiI0OlkMil/JprEtstFRe6OyFEQdihBgAnFUKfTwXEcPM+TeUMiQ8lxHOr1Onv37mVjY4PRaCRVSYZh0G636ff7Ut0i8oJSqZRUSBmGIVvgCoUC586dk2SWmFXwfV/uN0EkKopCo9GQVrNkMjk9P7YsdWtra1Sr0zaZdrst1WOTyQTXdZlMJszNzUkisNvtks1maTabknDxfZ9Lly5RKpUol8vyfLQsi6uuuoonnngCXddZWlqS50Amk+HAgQOMRiMajYbMYEqn00RRJBsmSqUSN910E47jSGJOEHe9Xk+qkJrNpjw30+k05XKZfr8vM5YmkwnHjh2j2WwCyH3leZ60CwqFl6qq2La94yZu2zbD4VAGkAvFm1Ba9ft9LMuiNTxOmhoK0/eFTKhHD2NapiSj0un0VlbWJv+NWylzCIs8d/BBqlxNTICGBVsUkopOMqoSKR5v6XyQvnWGhJvFDsryu6lhwrCEqpgU7/5RcoqL2Rqg7f01cvkcFM+TzXUp37CIYeSm1444wEhoDNtDab0TxOuzxctlxu0Tn/gE4/GYd7/73bz//e/nve99L3Ec8853vpNarfairuMMM1wp+HaNf3zfJ3j8q+Q++1G6990LZ09CvI1UP3ATP/X9txK7E86ePUulUmF+fp6BZvE3bY1hosC4ppJWdRJ7DuHWz5MPOvzi4SypJBgFB7uokNaXCIKAU6dOcenSJQ4fPky5XObw4cM8/vjjDIdDTNOkpJuUrnk9nRNfp5u0ptlunkMuaRMMDWwzwaS7hufGRMUygWYSxuxUjM8ww8sML3cbZWF/xHhDIxVWMOMsmh2y+waVdHo6rhTPLK7romR8vuu3XLy/aTE/WODRTzXIuUe5yMP4RDgMiHBIUsVhjEmVwcNFikWL0SQCkqjYGNgkKFB0r2FAh2MfrpFLpsiv2Nz5SymKxQL73l7YUQwD08edJz+mPVfMxj+vXsyIo1c4vtUef8d1+fXPP8A/PXaC3U6HVGUvdy/fRKRvBb2Ne8z/7r9Dq5RQFEXWyjuOw+SH/jWqYpBob+LZWZx0BnvSR5uMIIqo//AvYzxxL4fOfAW7UmTVnVpzUqmUvIm0Wi3p9xeKn37/Inz6T+AnPwCewzQ5NwRVBc+FxqVp9pHvQaEGrTXIleCeyzlH27ddqHAEhK3L93050ycevEVgtKi93652EYSSeK9QeQgSShAuwgbmOI4M6a5UKnS7XVzXZTgcks1mpWWs1+vJv4WSSFi7BMGw3V4m2rIEEQWX85gcxyGTyUgFVK/Xk6SZIFSEqmptbU2SSmEYShJoYWEBQLampVIpTp8+Ta/Xk+oqYfUSzWHCLhUEAalUSuYQ2bZNr9fb0aImCBrf98lms0wmE6rVqmyMa7fbaJrGwsICtVqNtbU1LMuiUqlIK2EqlWJ5eRlFUWQz3OnTp0kmk2QyGfr9PkEQyAa4XC7HcDhkMBiQz+dpNptks1nm5+fRNI1qtUq1WpXnSLPZZHNzk1qtxokTJ+RxX1pawvd9Tp8+La1zgjwSNjfR3FYsFmVweLfbpV6v4/u+JHGEoqvdbmOaJsViEUASk41GA8uypHVN13VyuZxUrIlQeUGYieY70f5mmqa0/62uru6wVAoiSJwPnufxCfWn+PH4nzDjLAoq6/pXOZn7MHpwmWjUNI1BZ8K7+RgH+V4AzvA5/jJzG0v2a7i586vMB294uosRCb+KGRQI1BFsWdkUFCICNC8FeoBrt9ANDWWzxrz2/ZhvOC6vC+L7JRRh4hwVLXoiI+ulGqA+l4HT0tISH/nIRwD43u/9Xvnz22+/ndtvv/1bsn4zzHCl4Vs9/ukPBnzgzz7GF/7+U/SPPQRraxBvWT+sHBy9he87UiWcjFhaWmJpaYlcLodpmvx2O4VayjI/aXLWURlmF0j5Lim3j5lM8jutJNdHNu/bn8UfjxgOhyQSCfbt20ez2eSxxx4jkUhw1VVXcejQIY4dO0an02F+fp5bMx5n7QQGOhEKWuwRazYaEYWkidqNGGjQ6fQolCq0fLir/PJ+MJ9hhpcaz3RNeNvvOvzV25K4fQUjtKm+fsL+H+oRBLaMR0in06TtPH/90x3OfsXgCRzmF4oc/MENyqkExl/uodHrMmaDIQOSVIEIhz4JyujtPRhcIkWZPpuEjJnnOlxcICJK9piYHomLh+l/dh/lN6ZJJBJSWf9yxmz8c+VgRhy9gvFCHoCebrbuD1c9fu2sjxvBXVWNH3WO87OPDjiVXUY9tIvQ90h/+g/I/N6vYlz3ZswooHTuITKGSi+Xk9ap8XiMoqqM5/eg9DYZF6r4ZpJ4MsZr1glru7GDAGX1NO7hN3I2Drmu/ojMghF5MOl0WlrAut0ujuNcDqF++EvwR78C3/NTUKhM846IYeM8NFbBsKbBlQ+3pnlKwx74T+/1fXKT1PafiYd0QZ4IUkyoNgaDAZlMRjZSCavY9iBiMRMglDfbbW8iIFrYgkR9ped5Unkl8nOE+mU0GlHYalwR+0ycC91ud0cOkiCHhCJJNHgJW1EQBDLPZjuh0Ov18H2f5eVlmdUkcpBM05SZP/l8XhKGuq5TLBalXaxWq5FIJLhw4YIkdCqViiTWxDl46NAhzpw5Ix/+k8mkVB4JBZQINxYE33A4lLXzgiwT+TyNRkPa97rdrgyqFqorQR6I9w8GA2nTE81vgkzbvXs3Fy5cYHNzk3a7zdzcnMx8cl2XIAhYXFyU5IyqqtRqNZltIQK4haIqm81Sq9XQ9WlOjwiE7ff79Ho9hsMhQRCwtLREOp3GdV0ymYy0Nwql2mAwkIHfcDkHSRCPIptKEH/VapW5uTmGw6EkEcfjMY1GQ+4joWoSkmtBOgrromHE/PnwTSR6K0yCPm7qIrVcjYySkstRFIU7+S0O8n2yQW0fd/BO76N8be9/oOcfZ777BnZGZU/Drae2NYNQAV8doJgBSmighhaxGhCkmmiGiqKqqHqE2VsklVql3+9LEkx890SwvCBTBXH0XPBik0wvVKo9wwwzXMa3dPxTUfl3dp0f+o3/yhOf+UfoXILx5bbX5Mp+jlx7PTcd2MW1hw6yZ8+eyxXdiWk47aWNNpneOZqxSQcbK3Cxhy3OhibLVoqVjM3X+j4fvTjiJw9VZN5hGIZkMhlyuRwXL17ky1/+MtVqlRtvvJHJZMLdd99N0XV5W9rj3hGMDRvfKBL5I9LuhGRKoev5LJUT7J7LUR032FtJYL5QCcIMM7wK8I2uK9nlmB/72ojmYyp6AspXR0RRgslkItuDTdPk0f+nSusrCiMeZUKPzbUEw8/kqf2rIYu7yjiPpggISVGjwApNjhPiERMzoIlChIZFkSq7eC09WhjEFLNZuuFZknGe3cVridfLpFLPP/j6m2E2/nn1YkYcvcLxQqTa29/7j62AXzntTTuQ4pi/ODfmf55Ypbd0GN0dMx6NCGOY3PYjlD77YYoPfmbaGhXHDLcqG8XDs2EY6J6H1lwlKlSJzOmDdgyEikYceLiKiuJ5RK06/eoevv7Fj0jLlSAzgiCQagHbtqnX6ztziR78Ijz2FbjqerjlHbB2BnwXKotw4Tg8fi/cdCeUFiFXht2H4cEvwfH7n/P+EjafMAyxLEvalcSFVZA1Inha0zSKxaLMSJo+eBuy6QvY8XuhaBItZ5VKBU3TaLVajMdj8vk82WyWtbU1oiiS5JXI1/E8j1qtxmAwkIqLOI4lISTUUJlMhjAMyefzDIdDOVMhQrTL5TKaptFut0mn07TbbWlXE0HPhmHQ7/cBKJVKmKZJvV7H87wd1fLlcpl6vU6pVJKKMUFSiYf8er3O6dOn8TxPEiX9fp/FxUX279/PmTNnJCEklGdRFOF5HvV6Xba6iaDpXq8HwObmptx+YS8UuVOijU0ozWzblsq2+fl5xuMxpVJJhnzbti3DqcXvDhw4QCKRkCodXddptVqSABOqJqG6EoSUruvyAcNxHB577DHOnTvHxsYG7XZbEjaKolAqlbBtm42NDRzHYTAYyGNZKl1W+KVSKdnuJsjKOI6xbZtKpUIul2NpaUmq0IbDIfV6XSrGRMNcFEUoikK1WsW2bfl56rbv99jrMTAfxIkclnJLxHEsA7sBcrkch/vvQIl2DjiW3Fu5e+Jwv/1bHOJHn+6KNP2eqS6KETFmk5y3HyXSiZWAyeLDWL1dKLGCpmrg63ilVSzLknY88T0VAxSxT8Rxf6kHLeIaMsMMM7w4+FaMfyLP5b998sv83ef/nNZX74HIA0eUaKi88Zabuem1r+WGG25gYWFhRxajmOTpdDrk2m0mlUVc1STq9PHWLzBor2IEIT1TY+CYJM0kX1tVeO/Bspw4EarQ0WjE3NwcpVKJTqfDvffeS6FQ4NChQxw/fpzi+jo/vrTMiVaXU/kV0q0LdJkw6MVkdXhdNYM/v8SF/oTehTWeKM/zHSWdOV78h8IZrmy81OfCy6VV7ZvBSMD86y6TNSIaYjKZMB6PSSQSrH0uRxqFkBiHNjWuI94soigb7L/T5PSjE6oc5RT/SMiEPHtIUqTJKSIcEpjoJuAVabGJBswdsImaSVZyr+FQ7jascY3akQieptH25YrZ+OfKwYw4ugLwUoVDCmx6Ef99zceJIK3G1DfqYCWZXHUTKCqaOyLsD5gGY8fEZlIqQ0TYcDKZlBk5w+GQSqVC/v6/4+J3/wzD6i5iKwnuBEyLWDdQnSEoCkoyjbpxXlpmBDEhFC6GYeC6LoVCQaotwjC8HNzruxD401wjf6vhpNuE130nHH497LkGeg04dh90J3D0Zjj10NTe9iygaZq8qYm2Mtu25QOqqEYXD/OC9HJdl2KxKEmaRCIh1Tkip0coO/L5vFR6iNygVqtFrVZjeXmZ8XgsH+wzmYzMB/I8T1ZUDodDSQSJNjbHcdjY2EBRFHlz2z6jKWZItqtlNjY2pCJFEFSDwUASUPl8Xi5HtG5tbm5KQm1zcxPbtqnVajLQejwe47ouyWSSbrcrtzORSMj2vU6nQ7FYRFEUGSYtCDiRdeT7PoPBgMFgQC6Xk7YkcUzS6TSZTEa2j4njt7KyQq/XY3V1SjSIzx4Oh0RRxMWLFymXy5RKJSqVylQxt2Up7Ha77Nq1S6qBfN9nfn4e27bl+tbrdWnjAzh58iSVSkUuU4SkVyoVms3mDmXe6uqqJDTS6TR79uyh1+vRarVQVRXLsiRZJMi2OI4JgoBKpSKPk2ixE0qyXC4nrW3D4ZCHHnqI4XBIt9ul1+sxHo9xHAfXdSXxItRRlmXJczuOYzqdjiRhhPpLqJ5Ec18mk5GNeYwD8HZ+jxQ09g/eRdRLETAGNFRUFPSt4GxlqlCKI9TIIO3tQo2NaRJSbJC4dC1O7QTGuIyuaLCwwfDqz+N5h+Rsn7CUClWi4ziSQAOes+IIXvxwyOezDjPM8ErGy2n8k1FCNv/HH8Lf/BGtziokUpApTYkjqwzf8X3c8dYjvOm6a7BtW04c5HI5GcDfaDTwfZ9ffOsR/q/zsDaCga1jWhmUXA5vOGLJDFDGLbqdTez2Je65ZzpRUyqVJAm+uLgor+cbGxs8/vjjXLhwQaqH0+k03cYmmVyNjKbgdnt4vS5KELKpJLlvohFmdlOZRFxvj8kOm3xZq/L9V8Yz+gwzXBEQY1bXdRmNRqiGjUWWZV7HJo+SZ5kxLZqPdgl6IdpWetECR7HIMWYDHZMFrmXEJWI0XC9iQp0UDhY5mieT7L5KYcl9Cwl63T0aAAAgAElEQVR3nsq1MTe87/m1pT3XbXuxMBv/XDmYHaVXMF5oOGQcx/x13ed9x1y8GNwYgjACTYdkepoRpCqEdhqKVXAnqOtnUUZdzNIubNvGsizK5bLMbxG5P61WC2O8jj7qkeysMSkuEpgW0fxelMkIPQrwy/OozpjM3X8rFTdCpSGCpUWYc6fTkbYkQdoI+1MwGYKqTzOO7BRUl6E4N21Y0zTIFODqN8H9/zgVNqjasyaOhD1NZPTAlIwYjUZSPVMqlWTwtbCIidd0Oh3G4zHLy8syg2YwGEhyzPM8WeuuaRqFQoHJZCJVHFEUycFpsVhE13X6/b5UG0VRRL/flw/IwqLlui6WZVGtVhmPx/L3oglOhHsbhiH92SLAW4RwCpVUp9MhkUhIS1MqlZLNaIJUEEHmQqZ/4sQJGRQtiChd11leXsY0TRqNBoPBQBJHwqKXTqeJ4xjP82i1WpimKZU6Ing9mUyyb98+2WSxvZ2t3W7j+z4HDx5kOBzSbDZxHEcqiAqFglyWICQFeSKOtQikFv8/fvw43W6XfD5PKpXiwoULpNNpWq2WDNBuNBpyUJ/JZIiiSB5r8b3I5XJTC8OlS3Kf2rZNuVymXC7LPKH5+Xmq1SoXL16UjW5iGZubm3J/iuYzwzCwbZtsNott23K5wnq2urrK+vq6tMGJ/WuaJrlcDkAeA0FiicY2EToubJNCyROGoVRuifMziiKKxSIXo09ypP4zT/kuXVf/edTYQEElVgJCfIzY3PEaLU7h00aPM1tliVsdbIGJ1VzBf8dfkF5Rca0NrI2plTSVSklCLYqmM3BxHDMej7EsS6qSDMPY8T3+ZnixZ0GDIHjJVU8zzPBKwYs+/vE8hh/6AHzqD4EQKkuwdBD6DbjxJ0i+8Q725hMU4nOsrq6SyWQoFApomiYnZLrdLplMhmuvvRbLslichEwcODn0GXRarE4mJE2bbCWFHxYojrr8cCVmVynLeDzm4sWLctJsaWmJUqkks9muu+46JpMJjz76KA8//DDlcnmqEg08xpMOYRDQ7nUZjEcoy1eRKpQYaiatfov7Jgq3qTD0ICq9uMdhhhleKXgh93wx0bn3nX3u//UsKcoU2IWOQZ4lLv5Dhy4XMMgyoImFToV9bDCmyXFsMhRYwUBnQJsxXTZYo8ZRiiyRWnsDP/hXZbLLDpnl+AWHX38zzMY/r17MiKMZviEeG8OPnXQJ2TKKxDEOyrSZDDAGLXzPm5IwyQz6sfso/PWvo+k6g8GA9fV1oiii1WpRLBZJp9PSphMEAWvtHlGhCqqKFvpozojYtLCGLSrtC7j3/j3xxZPk1AjSaflwCkjFg1AiTSYThsMhlmXJgGrRRjVuXsS5eALe+gNgJ8BKTMkv3YLlAxDHMB5Mm9bu/sRUmZQpTP84Y2jXn3E/iQdOQcDoui7JmclkQqfTQdM0ScDEcSwlmeVymV6vJ61aCwsLdLtdTp48KS14IrtGZBIVCgVM05Qh19tDuo8cOcKZM2ekomZxcRHf9+n1elLpJDKGGo0Gtm2Ty+VwXZdOpyOVS0KZIax1pVJJDoCFakpY5zKZjCTHXNel1+sxNzdHNpuVBFQURaRSKXbv3o2iKLJhQlEUisWirIgXN9dMJkOn0+HChQtSESJuVJPJRBI5qqpK8ku0ionXKopCt9uVFkIRzi0G8cIKKLZVkCFif4vq1FQqhe/71Ot1Wq2WnOkV4eOKokglnLAliH2p6zq9Xg/LsigUCoRhSKVSYXV1lSeeeIJUKiUJT0HwBUGAZVmybU9kNPV6PcrlMkEQkM/nqVarbGxsMJlM5EOJIFaFfW9xcVGSi0EQyBmd9fV1ut0u7XZbEmNCKScIM6GqAmR2lyB/bNtmMpnIEHfRSieUPaLlT/wsCAI56zbRG0/7PVLiKWEE6paaSJC3MaJlDRR0NzNVIcVPfr9OqnMI83UPMumFkjwrFAoA8nwWKixBHIk2PkEAPxfMPP4zzPDKxPbxD60W/PvvhPZFUBJw9S2w/xD0O9NJs1vu4o175/jZisuwPlWmCjWQYRjkcjkajQbz8/OUy2XG4zGbvQHnLo1xwgilMyDnTfD7A6oZm8NxyFuXcuQdi2Q8vd8uLi4yPz9PLpdjMpkQRRGbm5uyXCGfzxOGoczFExNAZcWH1bMcawf0VtfA0NAUm4ueyeaFS+h2gnSxTCowuFXr02sOacwt0EcnpcK8NbOszfDS46W2ywm8kPXQdZ3SLpMQDwipcBCTNCPaGGRw6WKQQCHGxyMiIs0uRjSpcB0TWvhMsCmhYFPBBhwyLFFRrmL9/pDlW771SiOB2fjn1YkZcfQKxgudcfsvdYOQaX/RdKZegSggVz+FU1rCVMH3HOhsQHOd4P/+16i1GtFWdky1WkVRlB12GqFOUFWVnG2y5k3w0yUiVSXWLVBUbAJsTaUyWEcpZGT2jVATiXax7XYc8Tnj8RhVVaWixnEcAs+D0IeLx6ftaodeC/N7QNGgsTZtVnPGEIYol04SL+yDN3036MaUTHr8Pnjsnm+4r0QOjrBF9ft9mWkkSBLxt1BlCIJAqEHq9brMutk+UxlFkcyRsW2bfr8vH3hFnTog1SWnT58mk8lIJc65c+ewbZtUKiUzFgRJBUiiQJAHpmkyNzcn7WYAnuextrZGuVyWxBhcrnW3LEsGdouA7TAMWV9fx/d9VlZWWFtbkyoxoXppNBokEokd79N1nWazSSqVolwuS7tYuVxmcXFRhmuvra3Jdel0OtRqNXzfp9lsSguW4zj0ej2q1SrXXXcdly5dksqcMAzRdR1VVen1ejQaDWnlK5VKkqgR564gdkQ+lMg/UlWVubk54jhmbW1NntviXLRtm0OHDqFpmsxKWltbo1gsypD3ZrNJPp+XzWfCwri+vo7ruqiqKu0JoilN3GB7vR6nT5+WiqJcLicJue1qJJFJdPHiRdm+J5R56XRahnELYiuRSDAejyXJKBREcRzLxjuxj/v9vvx+ptNp2Zgnzm9B4ArVXFItEBGgPvn2o0zPSQVty6ImBkAKO8KyTR8848m8EbHuoyq6bHkTGVOihVGojVRV3dEyKL5nz9Vf/62oo515/GeY4cXBizX+4SMfgT953/QXC9dQvOO76cYKxUKFSWsDJZFhV8HiP61EJJM5NkKHYrEor/mNRoOvfvWrFAoFeR9OpVJYtkI2rbExDAgTKoHjEToTDNUlGoTsQ+dio05jSyUsyH1BSInJKNEOOhgM6HQ6bG5uStVvKpWaZvH1+5iNJmxcgNw8Yb9L205RTSfpJguklBjF93nDVXOcfOIJPv7oOmahhKEbvCmv8ZbC7IFuhhleDAQDDVM1caIBBkmK7CUmYkiSFPNERCiohIQMWAVgFzejo+PRI2CCRx+LFEUOkCDHPm7HSmrEwXOb+HohmI1/Xr2YEUevYLyQgRNAP1TQgHDbIlTgf2k8wH2VCp1sEdtKEnselS/+Cf5WS5aoMTcMQ4YgF4tF4jgmk8nguq60Yh09/kXuuf2n8e20/IyOYXGV5lCeX8D3XHK5HJqm0e125cNsv9+n3+9Lm5IYWAHyIXV75TileXBGcOB6sJIQeFCsQXNtK+PoqzBoE6safM+PwcKey8qkvddCqw7rZ77hvhKkkVAzCHWDsKZ5nkexWJSElmhLE5YvQQiJtithY8pms5JoEgNHYVkTJAtAMplEVVVarRZRFLG4uEg+n5d2NrEOwrYj1kOEQwuiSyhLNE2TZMV4PJYKMkA+aG8PhoapEiidTpNMJnEcR7ZoDQYDGWwucnTEvhJWKpGJJcgWERDteR6FQkGqVkQ4uMiGEmSL67rous6ePXtYX1+X6y7k+r1ej0wmw4kTJzAMg0QiITOV4jgmlUoxHA7lTK7YLrFcQUgJ9VYURRw9epRkMsmlS5cwTVOSQSJkWhCIuq5Le2EymcS2bTqdDp1OR+YCua7Lrl27GAwGUukkrHDFYlESGyJT6OzZszLIfDQa0Wq1CIKAcrksLYUi90nY3kajEfV6XaqpBFEp1F6JRGJHJpfIDxOqM9u2GQ6H5PN5+R0fDAZMJhNJwgEyq0uovUQmkqIoU9ImWSdWPeJI3dGdpqATxyEqGhCDGkMklEZTRJqDpqpPIY1AAcMn87pV4i2SVpDUQkG2fR0mkwmAVIk93wHLzOM/wwwvT7xo45/kCNDgfb8Bgcfbk23uTq2w1hvh97uk5nbzb/enyWaz8jqZz+fJ5XKsr6+jaRp33nknmqbJ62W32yWdTvNzB9L88HGFgZYBzwfd4nTgc2MxQbGUk8SPaCEVYx2hZE4mk1JlLRoyxQSV67pUq9XpRBsG3c06OENwTkI2z2DQx0y2yIYur1mqklUD1jc2+KRfoL4xIhyoYCV5oGuxYCXYn5w91M3w6saLQZbk9kQYSQWGWSocxKVPnmWGXCRFkSZniFHwGTKmg0WSEV0MNIosMqFDhWsZsMaIFoe4E4skejJm/13fPuIIZuOfVytmR2mGp4WiKLwt63PcVekHMTEKKFB75HOsff5/cOCBfyZ52zuod/rs99v4BZ3Tu3axd+9e2Wi1urrK2tqabJpaWVmh3W7L4OfBYAC1ECUKUSOfSNUBhUAzOGWWGNUOsq95cqpimExY3rULTVXZ3NwkkUiQzWblg34cx7JmXOQhGYYhf8/GBbjtXVMbWr8BqczUghZ40N6AYWe64UffBNfdcjkPqdeE5avgjh+Gv/rNKfn0DBA3FpG9lE6nGQwG8v9PzlkRwZmigj6KIkajEbZtS4uRZVlUKhUuXbokSZ9+v08qlSKdThOGobRuiSYt0bamaZpcvshUEioZkWc0mUwYjUbk83mSySTD4VB+Rj6flzbDjY0NucztQeCe59Fut+UDuFCECeJFkD4i3Hy7mimRSMg/hmHI5Qvk83m5P8W2CaueIEtErtGpU6eoVCp4nsfq6irLy8tShVWpVOQ6+74vCRuxLoZhyBDyVCpFoVAgkUjQ6/UwTZPl5WV6vZ7MWVpcXJTbWqvVZBD8+fPnpXIplUrJkFLLsjhz5gzD4RDP86SCR5Azk8lEtp61Wi0ZRh1FEa7ryjBsQTIOh0N6vR6FQoFarcZkMpHHZTwe0+v1pCJrMpnQbrflskR2lrAkmqZJNpuVhJ9oltue9WSaptxeofbyfV8GjosWwWQyied59Ho9DMMApjlDIispDEMuZb5AIX0LC4PbUNSYKI65cPj3KZ/5bmyvQmj2MdwCSjy9HkBMTISCghqZxNH2ZO0tJSQQvOPDGAsmg4EriTBBzgpiVxBHw+FQKuzEA5dQCD5bfCs8/rMZtxlmeOkhxj/Hei5Dfwzv/xCkcrxF7/Lvv+s7eVerw5987h6M1x/le95wlGvK06w+cS/t9XqcPHkS13WZm5ujXq/Lpk6hFm61WpzbHBOfdlHsHLHrgOsQDDr8i5HnH3IGt+YVeR9tNBpkMhmZMygm6cQkWhiGtFot2u22LCTodrs0Gg3yCQ29VMVPpOGJf4ELZ0l5E9Rek4KlQPMS3cDlCy2De9s6imHjaQPmdu3hZM/hj88G/Pz+JHnLeKkPzQyvQlwprWrPBnvfHrLv7QGnP6Vj6QnsUOeG/7PO3b+/m+GFNbphSI82GgkS1Bj9/+y9eZCk+Vnf+XnffPPOfPPOrLu6q7unZ0ZzSINGCCSEOYTNIWSMlmAdSF4wMou96zW77BG7C4GxIAg7YtcBtvDuctjGuzZLYHlBBLaQLCwkdM0l0XP1WWdW5X3f77F/ZD/PZLWOmenp0Vz5RFTMVHVV5pvv+fy+z/eggkuDHBcAuMt4N1F/hSHrzJgSIwsG/MC/GJG7+I1LUVv2P2/cWgJHr+O63Ymb53l8/GSIMZ7wvbbJZwYWnV6Poj9heOHNlEs/x8XP/h6JRz9GaH+feiymxr7S3Lzzne+k2WzyxBNPaOLU5cuXlelRr9fnsenDKb4VnJtRm9ZcGmYYdCJprJULnGnv8cT2t1Ar7RCYjrlv/xHS0Z4mh9TrdWWACKNFwBaRUc1mM3jk4/MktZWzMBnD1S9BIj1/38o+9Ntw5Ql481+CUR9SBRj2IZ7CGPUIxZNMcqtwdJVQKKT7SRKapAKBgP5MUs3C4TC9Xo96vU4+nwfQ7ex2u1iWpbIiYW/0ej2V04g8Kp/Ps7u7eyp5TVhIIluLx+PqtySx9IZhsLKyQjwep91uK6uo1WoRCoWUpeJ5nqawBYNBZaKMx2PG4zGlUonj42MMw1AAyjRNZXSIjMlxHJWlCbNFSl7XsiydLizKhYrFIvV6XRfx4pnjOI4ye8Snpt/vMxgMGA6HANpEC2upUqlgWRaFQoHBYIBt2wDqfxUIBJSRJOys4+NjksmkehcJy2kwGGi0faFQwHVd9Vo6OTnRZDnLsiiVSirfazQaPProo2oUPxgMlEU0mUxUiif+QgKALvpiDIdDgsEgzWaT8XisoIjIH4vFIsFgkIODAwXW0uk0/X5fmUdyHsh+n0zmCYPiVyTno6TOiUzPdV310nJdV19HWGHRaFSPhfgDhcNhzpw5w3A4pNlsAqjkToDEz5T+O9bX3krcyHNifInidpwvB/4lw+GQe1bewQOf/8cEZs+xEAlN8VwImAGwPPyZd9P26KbkMndM7FyXyeQ5s3WRZZ4CkJkz3UROFwgEVOp6O9Oz5cRtWct6ddad6H++w+/yCcNgenyD9UKB6gNv43++MuWH3BY/+KYzXLx4ka2tLWU3hkIhvc+XSiU2NjbwfV8TKuUadxxnHk4QCDD1TaxOldnJ4fyeNhxw2K3xJ7MsqxsRPtaERw9OiAUs3nMmxXZgqv588ryQEA0Z2kgv0G63icfj3OP5HGztUJnOGLe6hNdKWHtPET5/L6lpmKRVYCcW5AvVPoFKi34wSSSRpHFokltbZzwz2O2MuJic++8tF3hvnHo9gTZ3ol7qM98w4Ht/Y0z1SybjpkHhAY9INs2FvzbhqadW+cN/HeZj/2+dMR4RbHw8oiSIEWebt5OxC3idBAmjgBUIgg/5e1xKb/7GgUbPfZZl//NGrOVRep3Xi7npe55Hq9Xmh5/y+MIkBsSIGgY/u23ykWeHHITSRCNQCSdpvfvv8N/XP0U2m+Xo6Eg9h8LhsMqnCoUCa2trlEol9bFpt9ua/GQYBt7uk/jTCV4sOTepNgwMb+6AMjGCPLX+FgbZbYrOmJkV4Mm7v4OdkwNCnSMymYwyPSqVijZL0qiZpslgcJMhNB7Av/nf4D0fnP+/68xZRR/9rblHE0Bpe+6FdLIHyTSEgmCaGPVjJu0m4VCQCShzRqLkxa9I9uFiLUrpZBErRsrCMKrX62QyGWUj+b6vQMZ0OqXX6+H7Pg899JAyf4QFYtu2GjBHIhG2trYYj8ccHx+rTK/VajEajUin07rQF/Ck1WrR6/VYXV1ldXWVg4MDTX4Rr5hWq6W0e2FpiPH1YDBQw2TbthVYmk6nCn6I6XS5XAbmQFE8HicWi2EYBnt7e8TjcVZXV9UMWhgh4qPUarVOMZKErbO2tka1WsW2bWVdlUolAOLxOOl0mnvvvZdHHnlEZUsCKsgxjEajTCYT1tbWaLVaNJtNisUijuOoqXg2m2V9fX3Okrt5nMVYWiSZhmEQj8c1dnUymSj7J5PJkMlkGAwGpyKVLcvCdV3q9TrlcplIJEIul9M0utlspsBYIBDAtm3dLsMw1Jg6lUpRKpVUysfN81SYReIzlE6nlf0mnkViJp/P56nVaoxGI0KhkLICha0jx3w0GmEYBtFoVBPYJNVQ/JFk0h0KhRQslm0yDIPBcEA1/SVWVlYYVxqUy525vKIV4FzlZ7FmNuJ+7eOBb+IHpvDDf4h5z2X6f3I/0ce+C9fzCCRGjH/gdyimUnp+GIahbCLZz8Lw832fwWBANps9BRi92Cbo5dD4L80hl7WsO1cvpf/xxgZcvcYD9cu0izv0Nu5mZgT5/PEJTw7G/NpbCirLlXv/eDzm8PCQ7e1tdnZ29J4iz7JWq8VsNiOVSpHP5/lLBY94f0Br4kJ2DeoV8GfMfJ/IZokvBmbsFm22CdDt9vn9bpCfOZ+lWEhrzyUeiMK0luRPCXWQocWPbqX5+GGLC+//IIYz5ZlP/nveHmxzLhRm204ziud4ZhZm1Yxx4MYwYjFcfPLTNvSCzGZpZjP0OSpDnWUta1kvrgyDW4Aek1KpRHW3w+TP3sKYx6lzDZcZWTbY5H7ujn0Pf/XXUtzzgyaf/kcjrvzzBD4+sazPD/zL8Tf8Myz7nzduLYGj13G90Ie653masPTPhxk+N4nc/BefgQ//cNcjHs4SdSaEg2FCkSBtN0Y5NG9+MpkMyWSSz3/+85TLZV107u3tqVRKTKtLpRK9Xo9arTaXt3RqbP+H/4Pr7/1v8S0TfB9zNgFninX5EZpvegeB2hGDWBQraOEFI7jFLXKMle0ii3thzYinCsy9fxQ8Or5B4KO/gXv2PvBdeObR50AjgHYVRgM4vgGJ1NxAu1vHO94l2DrGPZkDHIPBQBOlxLhYmrivlsrkOI4CS2JGLcem0+kocCFspZOTE2XbSLVaLR5//HFWVlZU+gUo+GSapgJGAhANh0Nl85TLZWWyJBIJms2mUuc7nQ7lcplms0kwGNRFviyyBcyKRCLKwBGgS5grjuNQqVQwTVOPv2ma9Ho9EomExp2L91Emk1EgQhLPLMtSmZewsCQqXdgq8XicYrFIJBJRqVQikVA2kpgziwTQcRx2d3fVJFo8hwQwkuMo8q1QKKS+VALM5PN5SqUSnU6H6XTK3t6emp8Wi0USiYQysARsE98o2QcCNp49e1aZPd1u95RRuQBfwtRaZAUBKjsTn4xFyZzv+xSLRU5OTqhWq/r5xSQ7cTOVUMzYhdlmGAb5fJ5wOKx+WJLiJiw+YY3JNDsWi2lanwBJpVKJSCSiUseTkxMFhwWgEvacsN6SyaR6YLmuy6jj8Dd6j5BkTe5gzMEjj8naM9TO/wHn7w9imiH8t/85/jc/S6c8Ir1twKyPZaUZDoenFnNyzQmYJOezmKMvJqq9mHum1DJVZFnLenXWS+5/rjwOlz7Hlydh7PPfRG5tHadRJu7PGFpRWvECgHrFdTod9vf3yeVyrK2tnQKNptOpAkaAAj73JC3+97dE+cm/GOFGYmCYhDonREIR3paL8NlulPVomJ4Vwqme4MZTlEdJ7uG5NFcZDEhwiOu6bG5unvIvLBaLTCYTfuahh+iVzhKNRvnhksXJs0/SbDa5ceMGwXiN2ShIwTXxc3kq4TTFiMVmzGU96BDrNWi7UX2eC7NbGNjLWtbLWa8GkPLlZF85I5P/8GNrxGoWeb5Anc/RI8i38FO857vfyzv/XoTtd82H1Hf/eJ1v/ek44xYkN32s8PO//stRy/7njVlL4Oh1Xl/vRrfYMCWTSc6ePctHPjvm1pzrERAzAzr/N80AgVCIsGmoT04ikeDBBx8km82qKXCj0aBarQLz5kpi3HO5HLZtU61WmUwmpK99Ae+PP8zxQ9+H4c0p3MFxD+vgWfpv+W7cZBaj3yDqOswiM3qVMscnxziOw7lz53SBWqvVaDabhEIhjauXaPB+vw+AW74O5a9uch3yXaZ/+ntw/zvmvkdWCJwJ5rDN7OlHMSdjhjeNgqfTqQJAvu8TCAR0ESqgiTA1Fqvdbqufj5hCi7RKAJpQKES9XmdtbU0lPplMRiVTwWBQP5t45Iix9Wg00sQsibkfj8cqOzIMg+PjY5VniaxJWCyWZRGJRFhdXVWALJ1O6z4UUEO8gcLhsHrcSFrXaDQiHA7rZ6xWqwwGA31tkQ4dHx+TSqUUmFhZWVHfImmyi8UilmVxdHSkccPSrPq+T6PR0J8Hg0FWV1c5OjqiXq+r59HGxgatVotOp6MSJWHFCGtKZATyIPQ8j16vRyqV0nQ2AYaEOZdKpRTwExPzarXKlStXmM1mum8Nw2A0GnF4eKgT4MFgQDgc5vj4mMFgoGbg4i0l4JjjOHpOHR8fEwwGWVlZUT24yNUGg4HKwsSfKBKJaHSz+BOJvNAwDGzb1sQxARSHwyHD4VD9jSzLIh6P02w2CQQCXLhwQRlfcm9ZWVlhdXWVa9euKQAlEsBUKsXGxgaVSoVms6n7RAzzY7EY5XKZ2cTlr03+LUnWMDDw9R5k4AVmDHe+gHFmn16vyNmzZ+dS10gfch2sSJ6Q8RxYKfc913XVK0quU2EHCtgq59HtNCxLjf+ylvXqrtvuf/p92HsGNi5CdhUzlcO0LMxIAncyxnTH2LE5UG5ZFtVqlUqlwvb2trJSFwGjYDCo91pAJeCO4/C+lTBDH37t+pCgvYpzPCY6bLPtj/jISZs9M8x6OEwwlSZgRYiF5qmQ4ks4nU4xb3o/TiYT0uk0yWSSk5MTZZjOZjO2trZ4011nSCTm/YeTu58nDJdr167RaDQIOzPekY7ySL3PFk0wx+TsIusZm3vDDrY1B6hk2JJIJE75MC5lJst6I9TLAWB5Dvzuu2NMazNCxHiY9/MMn+DN/BTfGv8v+Ka/PmX7XfNhsYYA5XyiuTu+KS+4lv3PG7eWd/rXQN3ujepr/Z3Il1qtFrZtc/bsWV04hb/G+uk99ow/bAaZeSYB0+C+4ISHsmFGoSLXrl1TWUjspt+Rbds0Gg0ikQj7+/v0+32KxaImggSDQS5cuKCL2vjBYwR6TbpnHsAcj7Ce/DSN73w/RijKNLdBPbdBuFslEAjSO/+tpO0VVv/iP6pMTthGkUhE5TqLQICY9t7qSQTMza/vfydTfPiLz8Bn/wge/p7518Z5vFEfztyP98WPwVOfB56jnkvJ4lN8hUS6JOlNiyXgimVZ6tUk7AcBTlzXJZfLkUqlqFar6lkkxuDSsJbLZcLhsII/rVbrFLspGo2qcbVt22oULF8CxCSTSWX2AJTLZd1/iyCZyM+Ojo6AOUgh0iyhyAuYIhNRQMYFmFQAACAASURBVEEtYbgkEglCoRDdblelb4FAQIGW3d1dqtUqyWSSWCxGJpNR8KPb7bK9vU0oFOLo6AjHcchkMjiOw9NPP00ulyOfz1OtVgmFQrRaLWWapFIpNR+3LIvxeEy5XFYPHEm+WVlZoXQzJbBcLitok06n1VdIWCuNRkPTzkzTVLBGmmoBKSaTCdVqVT+jGFEXi0U9H0TK1e/3lVUFqBmqMKcAlTAKg0Y8jDY3N3EcR1PUhAmUTCYVBCsWiwrujMdjjo6O1AspkUhQLBbVC0h8o8QkfTqdarqh53nEYjFOTk7UU0kkDJFIRF+n1+tRKpWo1+tEIhFlbAnLa3X4MPbsLMZNo+tT4JFvMkxf1WtF/MsELBTG1XQ6Va8oue4Xo6vlnijnslxz4rn1StdS47+sZX1lvSL9TzwOb/1ucFw4vMy77SmfmnnMhkO8mctbzm7w1pW5Z94zzzzDZDLhrrvuIhqN0u12dXhzK2AkJamlg8GAXq/H94cMhoEqjw1Mkvkw90xM/tmzDQbDMYezMXuxOIWgzazb5vcPhzzdc/irqxEdwMgww3Vdkskk1WpV2cQSqpDNZpWtKnL+0WjElfaQy9METF0eNB3eljD5crfJpfaUysmQRDTK+WyC78wEuMea91aSGivejJKeuQggCevzVjnwC/lenkvP9ze3KzNe1murXu8+SwefCtC6bhIgjMOEDR7i57k8T5j1ofSW00qG1+P5vux/Xju1PEqv47rVHPLrNUxSf2czyH/1zPQU5yhowKVZiA+YN6iYce5JR/mWyTH9aZD18+epVqsKBmWzWQUv8vk88XicSCTC8fEx9XqdXC5HqVSi3W6rH4lt27iuy31+h6dDAdpnH6b+pnfiDvtEj69iVPaZlraZJjMkjp7FHXRpb93P1PUIXvq4LqaFHSEyuFAopJK1YDDIdDql3W6fWki6q2fhe94P/Tlbg7/8fnjsTzHufwdmcR2j18AxLIjZGG/+dsyjKwTdqaaUyYJVYnDlxjedzpOfTNM85Xu0+L1I2ESCtCjN8jyP69evk8lkdHErQI8YGEs6mMS/CzgjUeSz2UzTtDKZjJ4D0sj6vs/R0dGpuHvLshgMBjiOcypmXY6pgA+e55HL5fB9n263q6CMmA1LwyzsJJEqCpsoGAwqUCXNNqDG1Pl8nul0queW4zisrq6qN4/E3gtb5/j4mGg0ys7ODs1mE9d1SSQSdLtdkskkjUaD6XTK+fPn2djYYDgccunSJQ4PDykUCsqsymazBINBdnZ2cByHZ555hpOTE5VsiTeSMKwajYZOXsUcNR6Pq+n14jETFtzu7i7FYpFkMqmSNGmCF1P3hJ2WSCRU0iWgjTTsrVaL6XRKMplUVlqv11MWlfgQjcdjptOp+vp4nsfJyQme59HtdtUDqVgskk6nGY1G6hMm58/a2lxCVqlU1FtMQDI55xalcIlEgna7raCunJ+xWEzvS6FQaA4IuTE8vhLU9XF46p5fJJ1pEA4n1dxbjPAjkcgp1p8AcnJuiYwiEAjg+74CR3ItijfI7TQs8np3qlzXXU7clrWsO1Qvqf8xDFjZgv1nIRjiy5UOf/fNJS5NXDYKUX767duYvkej0SAQCHD+/Hkcx6HRaNDtdhXkv/X+IOmiwhgSD7rpdMq9fpcbsRKPdD3+ZLZKwD3iXDJMYTik7AXoWVG2gw3C3pRHWx79wYgfTM+UlXv9+nVs26ZYLGIYhsrYkskk9957L/l8XoMshIFtrO5wMC2S7JwQMEM8Nppy0RxwbEaYzQKshQM4wRCTqcMX2w73nrHZthPaj8xmM00IFUBfmNTw3IJ/0V/u+b4Xtqgkg36t31n82Ys5J54PgJIvx3Go1Wq3DX7dzu8s641Zk56BYUKQKFl2CBHHAIwAfP9vjcice/UBZ8v+541bS+DodV6yEBXT31Qq9VUbJqm/uRHixsjnH+/NcIAgsBqC/anBcTjDB2ZX2cnsUKsZ9JkbEG9ubjKdTtVUV2Qv7Xabk5MTEokEDzzwgMbGSsKVRI+LJOlTuftorN1NZjZgmkzQTWxiDpr4nQZMRnjRJE6rxmw2I+QdMty+D+vZ/6QAyiIL6FawRTxtCoUC/X5fJ2b+hbfgjXow6EIoCtkV+CsfwDdNvLUdTGeGORrguTP8VgXXDGJ4c28dMW4WTx1hNwAKigkQJNOzxWSnRQBJAB6RwclCdjAYqAePTAgB8vk8vu8TjUY1Uj0YDCooIF4+YgosDet4PFYfmEQiQafTodfr0e/3SaVShMNhfQ8BgCRqXUCewWCgxuRCLxX5TyAQYGVlRaPfpcRPR7wgJpMJyWRSDUNjsZiyUiaTCb1eT/evsIMODw/xfV9ZMCLPq9VqwNx0++rVqzp9jcViCn5JQtnly5dVutdoNFSaJUlykUiEcrnM448/ztraGtPplFKppFHL7XZbZWbiB9RsNnUbFxNtxGNKGvV4PK6yvnq9znA41PNVmHpyDoknVKvVUsaSgIWu69JqtSgUCgpiTadT9vf34eY1KcybaDSqQF86nVbJYrPZVImDALz9fl+lD8J4Ezbf9vY2pmmyu7ur54aws2Tf2LZNv99XSaWwsyaTCfl8nnQ6rV8yDXddd86US3wJwzTwXQ8DEx+PUaDG769/OztrW9jeuprKC/goLEe51gW0lOtdPJ1kkiUMMAH4DMNQttIisPRK1XLitqxl3dl6Sf2P58FkQtodcuzkeKrZ4+9emDNzI1aAZ5+9yurqKpubm8xmM30eR6NRHbwIACHPXZHVCyMzlUrpfexf1I/4wsBjMx6i1Z1xlFyhMCkTnE2J2Dkm8SyZwJDm3lUSK9tc9sJsbGxQKpW4fv26MkkX738CkAloJMOk4XBIPB7nkAQbZwt4hw6dzpCWZfKJsYE5ddkfDwnOwsSdPkYyRimZpz+cUB3PpfUSSCHPn+l0SjweV6ZxJBK5bf8j8c27k/VCAKjF7weDwakhx4sFv17s73y1WnyuS72cwNVX+156RxnMPN/fvJ7r5WI+rX+Li2GAiUGYBBg+sZLPTzwxIBT7xmzDK13L/ue1U8uj9DovMaJOpVLs7Oy8IC+PD10Ic6U/4zNtj1RofopMXDjwY7p4lYWpZVlkMhna7Tbr6+scHh5quposRn3fx7ZtHnzwQWAug9rd3dWUJ4mFHzxwF7Y3xvNcrHYFVmy8TImQAV4iiTvq4rpzHyAvECIwGjC5uSjudrunTKOFkSDpY4ZhaBKVZVkaET+LRRklkkwmQ/w3fQskM3OD7DP34I8G+I6Dl0hjOhO8y49Br8XAc5SaLQ2gyI4WvVR8f55YFYlEvmIf35q+JtPKRRNn8S8SrxuRgnmepwweSTeRyaU0hwKseJ6nXjW+76v/gphyS6Mp297v9/UzyUJdGE3hcFgX7GfOnFFKvsiVJpMJqVRKzZ8FOOn3+wrciUmzYRjKVBIWjCzgG42GRtofHR1pOoxt25oQZ9s2tm1TKBTY29sD5g/UTqcDzBPAcrmcMsPq9fopY+lUKqVeELKwqNfrBAIBlYWJabMki8nfCwgj4JgAWJ1OR/eTMKYMw1CJwNNPP63JO+JrJek6wsYRQFH8LyTqXuQAcm5IIp6Yek8mE6bTKYVC4ZSh+HA4JJPJMJvN6Pf7tNttPWdk38fjcZV5CWgp03LDMJSR1ev1NL1PQMFGo0E0GuXMmTO0Wi1tttfX17FtWxPh7rvvPvU729vbO3UMLMvi+PiYv3joZzn7pZ8h5hQZZa/y6eLPYrno+SRS1FarpdsqUyqZUi/e31zXJZPJ6PktckEB5QCdcN3upOtONsqLTMhlLWtZL71eSv/z6fqMQMDFj8SYOC6XWwP8lSgAV69eJZ1Os7KyomxreU6JJF48/2QgtMhoFW81AcF93+dywGYlE8AbdMhPepzE8gyyd5EyrzJqt4nNZkyt0DyJ0wQ7OWcXTadTms2msjlFgi334fX1dSzLotvt0mw2MYy5XDwWixE6mTIdj0mtbvGF4QnHR9cJuDMOvSBxM0A0U2JgWLTHTZzGCVY8SSg5H1acnJyozD0ajTKdTnUwuNjHiK/hK10vFtwwTVO9B1+p2t/fZ3NzU7f5ToFUi9+Lt+bX+hsZyspA8U4yv14osCXgVaPReNkAshd6frwc4Fi86POf/dGQf/9fRhgcG6y81eN7/8/xV4BGL+c23E4t+583Zi2Bo9dhSVR4o9EgFou94IZpsR5OGvx522Dm+pSn4ABVwvyieYF/1K+RiEV1YSpmxblcjnK5TDwe13Q1WZTKQ2VjY0MlWt1ul0wmo4t0p15hliqQCYYI9rpYrROCgzbWqMvZpz7FdOd+Khs7+JMJru+T/k//j7IpgFNSNGFuWJalvjuyHQJehEIhkgdPErn3YeqpIrN0EbpNKF+DVB5iCXzThPEYfzwi/Jn/D98E1zcUeMlkMqeYQouG2AKsvdBFqTCThGYuN2XxDJKoekDZXcLUkSQzAX3E70iieoVJJAylaDRKNpulWq2q7Ew8X/b29lTmtLKyQjweJxQKUS6X9ZhVq1VlICWTSer1uoJy4jsjcjRZ3Mskdjabkc/nWV1d5fLly+zu7mrK2t7engJYwoCJRqPUajWdeNm2zerqKu12mxs3bmhyWzgcVsaSeD9Iek0kEqFWq6mkbmdnh4ODA+r1OslkkvX1darVKteuXdPzQ/yPJL1NAC75fjweK4hiWZamny0ydZrNJrVaTYEi13VZX1/HdV01oRbDcUnBicfjer66rqusLJEDCKNJvCrC4TC2bTOZTOj3+4RCIcLhMJPJBNd11etJvLXi8Tj5fJ58Ps/R0ZFKNwBlJAlACHOgVySJMklelLpduHBBwTnxwBK5m2zf/v4+e3t7NBoNTNNkdXUV0zTJZrMMh8O59C/5DB/d/H5SqRSxWIxutarvJV5Zs9mMRqOh565MuuWcl4mVSEfl3iQm8wIcLcpYF5vGF1N3mqG0TBVZ1rJeet2p/ufTVQ9Mg1pqDZoVvtia8V9/scXPnQmSuflckkHCZDJRH8Jms0mhUNCkSXlvWfzKIEZYwbHYfCBXiEyoeEGKxVU2Ejat9oh8AOK2zT3dPcrTEeVIlrEVxxyO+em7Q/q8f+aZZzTQQHqD9fV1tre3sSyLSqWirOJUKqVAwNsSJk+0DZ5qj2kF4+RWVgjXDxkRYTybMbr+JNbKGZKlEj9xPojfqas8W9i0tVpNexGRyLdaLXq9HrZta6+1uC+WdXv1SjB7xGtSes+XWi8U2Fr8mfQy0v/c+vX1wK8Xyxj7ejWdTjk4OADuPPMrumPwQx9b8PkyDIbDr/w98c1cZC8u/o78/8tdy/7njVtL4Oh1VNK0tFot0un0KTDgxdbfWjN5tDnmD7phxJbNBD7n2fyz3oz/MemobEkmSoZhUCqVdIEpSUylUol0Oq1ggCRo2bbN8fGxLrrvevZP+fJbf5i6H8JL5Ejvfpnzn/09Av4cRCk5DS77MWaBEJH2CYHuMY4ZoFbYYRLPEKgf4dfrKtECdMEo4I0wb3x/LmvzTg6wP/GvGJ1/K92AhXnjEo4VxBz18dpVAn/xaRzTwh90mVQOVcoDaGS7sERkgSryLkCNrmXiJtKkW72PFo+hSJNExiPsDHkwxGIxNcIU/x+AQqHAdDql3+9rwlQymTzluSM+PZFIhGq1qiad0hwspqS1221gLosbj8eawua6rh43y7JIJBKsra2pVEtAj1gspqCRSOssy1LmiqSApdNpAGVJiXeCmIem02m2trYU5JB9O51OSafT9Ho9KpWKsqtEgiVeTdKoJxIJ3e+NRkMlfrPZjP39fT1u1WpVgbZYLKZG4r7vk8lkqFQqtFotZet0Oh2V1YlEU0CaVqtFPB6nUCjMWXWDwSnTdvk7kcXJ9DoajXJycqL7QhhZwh4TOdtoNNKoZWEKiTGrHMfBYKBgnZwbiURCU8fk/iD+GJZlcXBwoMdNAFE5d/P5PM1mk9lsxl133aUTwXPnzqn/krymMLJkn+ZyOaLRKLlcTj+/UJSFoWYYBoPBQD+DNI4ABwcHKs8bDAYKXMv7CDus1WopS20ROJLPEQ6HGQ6HDAYD9X8SwFa24fmavUUPqJfSNLZaLQVF5ZqX77/a/eEXfuEXePbZZwmFQnzoQx9ie3tb//1DH/oQjz32mE7KP/zhDyu7clnLej3Xne5/Pncw4qNjH4JjsCyon/Co5/J7q+f46zc9gmSYI4yieDxOIpHAtm19Zss1LQsjWXAtLlgBfqLg8stlk8PejMlowoNemx/x6myeW8HZfjPPXr7CkTmlF0oTaFd5+6qN43l89MtX+dSNMvecP0+/38c0TVZWVjh79iye53Hjxg39mQwqhO0Unk75sTR8zPMYz0zuza9weVil0uyQCUV487pNs/Y06VkSJ7tFoVCgWCzSaDRUsi3PGQmHiMfjCiA1Gg36/T6JRIJYLKb7aull8sat2wE3Fgd2r2Tt7++zsbHxFdfvS5UsLoJfz/c6rusymUyo1WovK/Nr2f8s62vVEjh6jdTijerWurVhkglbs9m8LT2s6/v80yOPPx9YChoFAcMAx4fHnBjTaV0lYCIHm0wmSlEejUYq0YlG5+wky7Lo9/vk83k1bkylUjQajbnEp9Hg27/0EabFLY73d3EuP04skwGsuY9Kv0emP49wj6Vi9K1VrtzzHXRSW8zGA1xMzFiO0pN/qlIvadREumNZlsp0fH+uz2/cuIyzf4NgKM40noLJEG/Uwxh08JPZuXTtc38EPEfbFQaQSHGEpi7NoaQ+wXM3+0X9rrCU5Aa8+HP576JZdafTUXDOMObyIZE0RaNRAoGA+gYFAgEqlYoyf0QSJg2byJ4mkwmJRIJUKkWv11M2yMbGhsrdZrMZtVoNx3EoFAqk02lc12V1dVVlY2KOXCqVyOfz2iwKW0SAMPGbkYX5/v6+MlLEf0dS1kQGJ1JGuQbk/BoOh/oAhTlTptfrMZlMCIfDRKNRbNtW8CWRSJDJZNSg+vj4WJlJMoEVQGo8HitTTN7DNE1lEgkjSTx+xKDZdV3K5bI+9MSYVORYwjAS6dnig1EWFr7vc3x8rOeNyNnkHBE5wOJ+E7aX3CNETirAnwBwo9FImVYHBwcUCgW2trZotVp67gjIE41GWVtbU0BGStLwMpkM8Xhcry2RNkrM9Gg00utAwKRSqYTv+7q4ketQvImi0agCuyL5W1lZod/vY9s2kUiE4XCooJNt25imqQmGIlmzbVuBso2NDSKRCI1Gg83NzXnsdDisPmzitZbNZvUcEEPx52v+BKCU930xzZ98dbtdfvVXf1XN/H/913+d3/md31EwOJPJ8Ju/+Zu6/z/+8Y8znU753d/9XZ544gl+5Vd+hV//9V/Xf3/yySf5jd/4DWW/LWtZr4d6Jfqfz/UAZwpeAFpduPElOPcgj/YNfmolyfb2tsqMZTtE9izPJ5HPCuNmUbIlrAHxYcxNOvyvNlwZOUynXb5pM0Euc7fePy+cP4d57RrJQpJjJ8zu7i6fcDN84ukynYHLUdugF/H4kXvWOHv2LP1+n263SyqVUqmvPKtFLm6aJvlwgB9eDTIMh+hhsXb/w7RaE6z6LsNxF3vrPN9Mk/39fdrtNpFIhEKhoHJ0YU9ls1kmkwntdhvf90mn0yphF9PwZDKpIJL0j8ta1vPV7VzHL2fdLkv5TtRkMqHVarGysvKSXufFAFtf7XeW/c8bt5bA0Wu4FhumTCbDuXPnvmKSczs33H94Y8ov7/k4PPdaDmDdfKkVy9WFneu6DAYDXZALEyYSibC2tqaa906nw1133UUymVRmiSzUxADaMAzoNtiMWqStCYPtbfWYkUnZaDTS5sPLrTLeeZDwtWfwRgPwwXj7X8Ha/xKjVk39emQxCihKHo1GlXng+z6jfhf/o79J4O6HcUNRzM//MV63hWuFoFWF0XzCKPIbYe6I+e9gMNB9tZjoJv4/AiItgk0CtNm2fcrsGVB/G1lYC6A0Ho+pVCpsbm4CnGpOheUlfyML61qtplIeAQcE5W+1WpRKJU3DkyZPpjuRSESTsRqNhsrCAoEAm5ubSlPvdDocHBzo6y6mc0UiEQUMhN4eCATI5XIMBgMFmQSwEWDCNE329/eVDSXvK9uYyWTUu0gmn/I64iMUi8XY3t5mPB5zeHhIp9MhFApRKpUUtBwOhwqMibmzsJeKxSIA/X6fw8NDBRskZS4UCpFMJpXRZZomnU6HZDJJPp+n3W6rr5Cko2UyGXq9nibdVSoVLl++rEwjWVwIk2ZlZYVOp8PJyYmef3J+CcDV7XbVmLxSqdDpdMhkMhQKBX3dbrerCXGSfiPSuFQqpdeiyAblnBFm3ebmph6vXC6nqW+tVkvlEAL6xGJzcb6kxuXzeU2863Q6p3ww5JrMZDLs7++rD5Qwl4StKECosAWlcZnNZsTjcZ18iZm7MP3knih+I8KUk+ZPAGVpZl6oH8d0Ok9XfCkTrbW1NT784Q8D8I53vIO///f/Pt/5nd/5NX//0Ucf5du+7dsAePOb38ylS5f03zzPY29vj5//+Z+nXq/zvve9j/e97323vW3LWtaruV7O/ueXdj2cmQ/dBuRKsLEJq6tQ2uR81iCTmQ8dZOovQyFZDAnjSOS+rusqc1OAcvmvYRj6Wr1ej7uyWTYubmnPIxLnzc1NJpMJN27cYDqd8oWnnuXx1bdiN8u4hkkmaHLJS/BTqxvq11csFvF9XxM5ZeglEl4Bs0zT5G+nfT7X8Tho+PzoRpYESQ5PTjA7DfL2OTqdDtVqFd/3OTw8JBgMauqr3PeDwSDFYlHlasLglF6pVqtpOIokg74a/I+W9bXr1QbavNL1SoOdd+p4vFTwa9n/vHFrCRy9BkukNu12+2s2TPD1p3Rfr367PMMFhY1cwL/5X9v0+Z8yHaaDuRRJ0hYGgwG9Xk8ZF6urq6ysrOjiPRqN6mJ/OByyu7tLKBTCtm3C4TAnJyf4vq86eWmyzp8/z8nJCVeuXDmV0lGv12mG5hKkUNDCdUJgGEzNANObgJSANSJPkYW9AAUCtghjx3ImjL74J/iuq0yrW2sxnUlAoVQqpdG64k0kC3OJmRd/H/lsQr0dDAbaOEmyl3x2WdTK5xDQAOa+M6Zp6uJeHgLSbAq7ZzAYqGG1gHPScAPqQTWZTLBtW0EoMfbsdrtqpDkcDpVhBHNwq1gsEo/HiUajmnY2mUwolUrEYjHdJmGnHB4e6lRCTI8FWBsMBspSsSyLXC7HysoKtVqNdrutgNui1j6dTut+chyHer1Ot9tlZWWFTCZDs9nk6aefVgCjWCyqaafjOAr4iIG3bdtsbm4qa0vkboZhkEqllGUkrBXTNDWSWc6JlZUVer2eegvJ/kilUso8CwQC3Lhxg1wup8dE9r1t2yrXms1mHB4eKgiyKMkSBpmcw57nqel8sVjUhn6RPTWdTpWF0+l0OD4+ZmNjQ4+pbdsqL5VUoFAoRCqVYjgcapqbmMEKaywYDKo8QX5f0u6CwSDnzp0jk8moP4AsYATkS6VSCo7KuSgMsHQ6zXg8Vs8rSZYTD63ZbKbXjXxGAVuFpScMO7kHyEJPvr+de+WdbqgXJa1fq0T2ISXpSQJI/9iP/Rg//uM/juu6fOADH+C+++7j7rvvvqPbuaxlvZL1Del/PBcGPWjXobg5p1sHI6RjMX7pboNCxFYA5tYwAwH1F4cJcs+XYdBsNmM2mzEcDmm32zSbTSzL4vz589pPiK+dMHfa7bZ6ux0cHFDvDPEKM3rlfUK2jWmClUxzUC5ztpg7lcopknQBceS+uFi2ZfA9uQDH0ym5pEEwGGcjukarNe/d8vk8Kysr6h0YDAb12Se9mfQZwWCQ1dVV9Vqs1Wr6jBCJsISjJBIJ4vH40t9kWct6gfVKg1ew7H/eyLUEjl5DJYyS52uYFuvFXtxTz2fgwK3uOyHgb6/CT2ZGTFouI8tSQEOAiEqlgmEYFItF9V3Z2NigUqlgWRbVapXHH39c6Y3CePA8jwceeIDHH39cvYJkOtb1TFrnvolRZBXj6Fni0wG+79OYwY3730U7t800uUpo7xKmFcQ6ukZoOmR0c0EJnDLCXTTSFrmMsH0E6Fj0Z5EFNaDeQLJfp9OpRrmLXElSsKbTKfl8HsMwGA6HuoC3LIuNjQ01pZZ9CM95/Ni2rZO4xUWvpK/ItgkIJYynSCSiTA/xGxJAQ4wzpcFLpVLqU1OpVE55E3iepwyORSaTvLb4Fp2cnADzhLbt7W1qtZp+/m63qxH1AqjE43Huvvtu6vU6169fV2aJnAviZyPeCAIcnDlzhnq9rubWMAfR5LXF80b+Zjwe02w21TBb2CWJREKlXOKPI5IqkTAmEglqtRrRaJRUKsVoNKLf7yu4JclnIrWUZnk0GrG+vo5pmhwdHdFoNPA8j/X1dfL5vMrkxJNK5Ga1Wk1NVA8PD5VZEwwGdftERgboPhOvKIlVloVJqVTS80XOKQERL1y4oOeb7NtQKKQPY5HsRSIRrl+/rqwxSSdstVqkUik1/e71eso+Ej8kMboWX6lUKsWZM2fUM0sAJzGUFZ8qMZuXxV4mk+Hk5IREIqFsIAGOFs3i5T5hWdapc0JYboFAQK/1RdnkrRJWed8X25DdyQZOrquvV4lE4hS7cTHCNhqN8oEPfECB1be//e0888wzy8ZpWa+L+kb2P77nQTQG2/dCOAqjPj9xzuZnH/CYddrU+wENEZCBz6KUXIAaua/IsESA8sFgoClnws4WmZcMMTKZDLNwnD+pjRhPetwdmpFwZ2xubrJ7XOPTX7rBk8PHMI4rXHhTkUhmjTPBGYX4HHiSRFYJG5CgjBcC0Mi9cLEnEu/K9fV19VKUZ68M50zTVJ8+kTWvrKwwm83odDoqn5a0VZHSZTIZNWBe+h8t69VaS/bV6Vr2P2/MWgJHr4GSBebXo2R/1lI90QAAIABJREFUtXqxF7Xv+/zNJ8eMv9KzmXMxg/9lCzwvwkHT10WweJrcuHEDgIsXL56KoM9ms5ycnHB4eMhgMCCZTJLNZun3+zQaDe6++262trYwDIPz589zcHCgC7yGY/D4XX+ZfiDCIDMg8eC7Ofsn/xfdkz3q7/1vGEZsQpcfYZzfYrR2F+bH/hXxT/0efd/RxeSt+0Di6uX/RQ4jEjiRvgjTQvyJFpMMQqGQsjiEASJMI0kOabfb1Ot1TY0bj8dqnB0Oh8lms+o9JBIukZ11Op15yspNQ2XbtjUtTiLigVMeP4ACDZLSIukqi15Hsti2LEuZHCK5EtaPfGbf99XUWt5HPueiVDGZTKoMLB6Pq5eMJM6sra1phLzv+7TbbfXDER+k4XCo7LRCoaAgkOM4KpXL5XJ67DzPo91uq4mygAmJREJNvkV6l8vluHjxIoeHh5TLZWXoyOst+hsdHx/juq76QIk/UK/XU0mUmIHK9FYmyZVKRYG2cDisbCz52Xg8plarnQJH6vU65XKZYrFILpfTfSGAVqFQYDAYnPLmkYQRMciGOSsnlUqpAb1cg4sG4+vr67RaLVqtlr6/MI8syyKZTNLpdDQtzjRNNZkW76BOp6NSM2nyxd8in89z9epVlesVi0VWV1cJBoPcuHGD++67j3w+r/tSzrXV1VX29vYolUq6EJPzVj5vLBZTGaacN7JIk0m/AHqL0k1Aj48AbovGiwKO3k4DdCebSFlYPt+i7qGHHuKTn/wk3/d938cTTzzBXXfdpf+2u7vLz/zMz/CRj3wEz/N47LHH+KEf+qE7to3LWtYrUa9I/zObgudCPA7ROGcj8HMPFIlGwwy8OcgusuhFTzRh+cp1LM9RkdkL20YYv5ubmySTSSaTiT57SqUSwWCQ3VqbX7p6SHPk4PoewV6Hv3chyZYd5s/i52jxJew//2O6vkHZj/CQNeXHz6+xUsyTTqf12ST3TGFjClgu7N7F8JCvVrIQ831fn0uSniksakCHIpPJBMdxqNVqhMNhYrGY+vFJ3yPPFcuy9Nhms1kymYwOMJa1rMV6NbBsXg31ark2lv3PG7eWwNFroAzDIBwOv+CGafHvXszFfTDx+VTLI2LC0JvL0wCSJjQcH9f3Cd6c/kciEbrdLsPhkGvXrtHv93nLW96iXiUSU/65z31OPX+SySTtdpvxeMz29rY2WI7jqBwqm82qN0/9/Fvp+gH8kz161SrO2hkub76F0sENalYco3JAp9WGyjHkVkhefYQwLtFYTA14F1k0YtQtvkSAysYEBBH/I5HNidG30NLFwFeAkHA4rJIbATBCoRDZbFbp9IlEQtO2ptMpnudRKpXU3yUcDqs/QCwWU8ClUqlQKpX0OMpCXRb+AnYsloA+0sQNh0M9Hr7v02w2cRxHgRth1SQSCTXkluMqIJthGKTTaQ4PD4nH4+p75DgOg8FAGSHiRyUgnOyrXq+nx+D4+JjBYKBpZZFIRJOvYC5/29vbU2aK4zjE4/FTpssi+ZJtXEyhE/BJwJ9oNEq9XldjagEDxSNHGC3CqpH9K9NjkcfJMRePnUwmw2Qy0fNMXi8QCJDP57nvvvsYj8d6DhiGob5HzWbzlDl8p9NhOBwq2CfTXvFzEhmWmIvKv5VKJWXTCFgp53QsFtNjKiCLbPd4PCaZTOp7FQoFDMPg4OCAbDZLKpViMplwcHBAu92mWCwqkCPG3WJeuLq6Si6Xo1AosLu7q9tqmiZra2skEgmOj4/VKFz8ozqdDrlcjlgsRr1eBzgVTy1pRYvST2GzyXUgsr/F35FrQl5LfMwEkJNUwEgkop5H4XD4Bd8jX64SJt3zNU7vfve7+cxnPsOP/uiP4vs+v/zLv8xv//Zvs7W1xXd913fxnve8hx/5kR8hGAzy3ve+lwsXLnwjNn9Zy3rZ6pXofwaTIXg+9DtY7pSmBYObbFMBYkS2PR6P9fkF6DNTnqdiIC2sWNd1OXv2LOl0GsdxaDab9Pt97ZEkPOQTx11awyl506V/fEBj5vB/P3rIt0YmfPlGh9BkSPeJTxE6fz9r+Rw/8s6Hefhs8VQIB3CK4Q0owCUDsUWAXYCmW/fbojx8MQRFUkIlLW0xQU7YVY1Gg1AopIbYsVhMnz/NZlODG/r9PtVqlWKxyGg0YnV19VVxb17Wshbr1QBgvRq24U7Wsv95bdUSOHqNlG3bt4Xwvpi/cRaYRgbPeRwlLZj54N+8WS1Gyz/11FMMBgM2NjbY2tqiXC5jGAbXrl1T2YpQucV7ZnV1FZjrVdvtNt1uV32GQqGQLgp7ronpe4xvLgZHnSaea7LuzcimbFzDod1qz/0HAhZuv6sGueFwWKdri2BOPB5XergwDUTOIwwSSbCyLEs1/SqduynBEpAnl8upCeSiSbYwhYbDIY1Gg0QiocwjMcOU9xdGkbAnRKoH0Gq1FIARcElYKIuUzcWSxbscf6HIO46jEeX1el2NwYPBIOl0Wplek8lEgSAB9yQ2XthVwlaKxWLqhSQSONkP4oEkEgMBV3zfJx6Pk81m1exb6O2+7+skU1hawvyRfSxfsu3CAFps0qX5lv08HA5V3pROpzX1RsxHRRomTXSlUiEajSpgIrR7SaC7fv06o9GIXC6nEcwCxEkUaDabVaBUkr5OTk7o9/s4jkM0GtWEmcPDQwBNUBOPoF6vp8dQZHGZTIZ0Ok0wGGQwGNButymXy9i2reel+GKIj1O/36fVapHL5XjwwQep1WpUq1UFJhuNhp4v/X5fTUzF20lYToueQsJykutiPB6zsbFBo9FQRh7MmwJJohPfITEHl3NFrn/xxxBWn7CNRNLY6/VUmifHNxqNKji96AMm14wsegR8Ak5tm/z/i5Wq3Y607WuVnHfPtzA2TZNf/MVfPPWzc+fO6f9/8IMf5IMf/OAd2aZlLevVUt/o/odEBoYtiCRJBj38WIpgOKKDJrlOw+HwKYY1POe70e/31ctIhkZra2sUi0UFwTudDoD6zIlHUq/Xoz2ZEQzOhzJG0CLiOIw8k1zKJpqJEoolufiT/wN+q0nvyUf5lFFles8Fzpw5o0xnYW0u3o8FZF9cpMmzX56J/X5fmZvyJVLiRqOhw6FkMkm9XqfT6ZwKVJDBm/Rf0ueFw2GV4sViMdbW1lTGLEEqly9fZjAYaKqmbdtfAYYt641VrxaWzbKeq2X/88at5d34dVwv9qLejhq8KW7yeNfFZ+5zZDIHjb6/YBEOeGpgNhqNuH79Oru7u7zrXe9SxLjVanFwcECxWCSbzepU7uzZs8rWkOSt4XBIOBymXC5TLpfVYFkYEunjZ+lceJhgMk3YAzeRwfzMv2Pv+nVi//bDDL7rxwhv7Mwbus/8EYH6If5N9s9oNFKJjqSyZbNZgsGg+vyIcbMwFRalaMK6kZh4YXU4jqNNoQBetm0r4CPxsyJlisVidDodXbwnEgkFUMQwW1glMs0UszdAF+mycBagyTAMpYTfWiKfE/8f0zSZTqc6XZS4XGEBjUYjqtWqsjxWV1cZDAYKNgnFXowt5fhkMhl831cGk7yPyMuE8SVSJ2FWOY5Dp9NRkE+AMknnM01T4zTFbF0mtbJvxPNHJE/ywBkOh0SjUfVkCoVCKpHLZDJ0Oh31YoD5JLVcLisrSlhJi4bb0nhPJhP29/eVPSNAlGVZFAoFfT0BdAQAarVamogmSXWJREInzuI/NRwO1VdLUtIWY5PD4bACUIvyh3g8Tq/XAyCXy50C/mSyK9srAJnjONx1110KPkqDL95bsl333HMP1WqV8XisqXay/xdT19rtNuvr62QyGb025HxOJpO4rsvh4eFzRvQ3rztZRMhxF9BImGHyMznPBXiVL2EdCQAkqUVyvom0Uc5NOba3ytxut+5047RcIC1rWXemXkr/YwSD+KYFkQh+Is73btrkUnF9bi8ycBaBbnn+CdNTZM7i+yihB5VKRZ+lMvhYTOr0fZ+HUiE+0x4ScDyMZIZpxODd2zEeXrf5W1tD/t04RchO06+W+bbRMW+NjCmXy+zu7lIoFNjY2CCfz2uCmvQw8jyTL2EkiYm3DDSEzXurxE3Y071eD9u22djY0OGFSMXlvivegfJ8azabKknp9XraQ4lETX7WaDR48skn2d/fZ3t7m7W1NbUSWNay3sj1agLRlv3PG7OWR+l1XC+Wqh0wDP7NgxG+84tDugNf09Q84B+cC2J4U12gXbp0icuXL3PmzBlyuRzXr1/nk5/8pLJ6zpw5Q6fTIZ1OUywWVSrS7XaZzWbs7e0Bz5k493o9jo6OME2TdDpNNBpl8+SE0KWPsbfzzUSjMQrP/hnhxlUC29tsmH1O/uNvcbU7IWV6+LtPMbvpyxIOh3XBD+h7iydRv9/XqZ+AR6FQSAEikavVajVlj4iPS6/XIxAIaAxvtVpV36LZbEY+n9ckE2HmlEol6vU6R0dH9Pt9AF2Ii4GzmFmKNEtYGNKwyQ1aouhd11XgR0AvWVwvynWEdSLm2QIcWJZFvV5X/4FGo6GSNGmMQ6GQspRENiTgkzCNZEEu+0lMvCXOXthYAqbItgkzSNLAQqEQhUJBF/6tVktlgMJ2EgBNGlnxD5IJqcigxMBTjrvsk06noyCFeP2IJ4UsCBZj7hfNx0ejkUodJekmm80qc00MtMVXSVhCwtiS61DiikejkSbXJZNJbaxFJjedTpWtJ03/IoBUr9exbZuVlRX93BJ5DKiptmVZnDt3jmw2S6VS4ejoCMdxePjhhwmFQly6dEmlj4tSS5GadbtdNUCVc19Mz2Wy3O/3yefz7OzsUK1WGQwGZDIZvQbPnTvHY489BsyZeCI9rFarOI5DOBxWY3TLsk5J6wDdfwLqyjFZTByU80H2j+u66tslAOWt90UBsl8Ni5EXStVe1rKW9cLqJfc/7gw8Dz8Y5BcuRJVxKYC43ON936fRaOgQSDzg9vf3yWazbGxsaPqmeMSFQiGV6gqTV4ZL8ox5aDLhx134g1oIJxbn/YUQ31eY9zTve+Acb5v4VL0gpTe9ifDx3BrggQceYDAYcHBwwNWrVymXyxQKBfL5vIJBArgvDg0ETBKQXnz65LkrvycspFQqRbVa5eTkhFQqRTqd5sKFC+zv7yuTVfoFYT0JU1ZMshOJhLKvq9WqDtrEl08GTY8//jhXrlxhZ2eHM2fOEI/HX3dSnWUt68XU6+38X/Y/r61aAkfLOlV91+d44muqmg80ZvCjXx7zkysG7ZFHtnzCZz/7WW1SPvvZzxKLxVhdXeXs2bNcunSJWq2mEpx6va5TNGHxiIxNFt8iUZKF8913300wGOSehEPj6T/g+Ph4DoKcP6/pXeeiQbzjXZLJJNVYjJFh6OQO0CStRTaRmOYKS2XR6FoWp4DKqIbDobITBDQTTb9M7IThJL8Xj8dV/tZqtTAMg7W1NU2WE3BDwAvbtnX7FiV7YhwtDBlhX4xGIwWUwuGwSs4E5JHFtJhZChtF/F5s29bvxZ9HPqeAVKZpUq1WAbThk3hgMdqUVK9wOKzMIWk+R6MRjUZDpUyyzdKMyudrtVqMRiMKhYL6I8ViMTWWPjg4UL8m8aBalExJY2vbtppDDwYDrl+/TiqVUhNT8Y7qdDq0Wq1TqXMiDxNwsVic+0SI/5AYdefzeQBNqWm1WspSkrQHAT+FPec4jibkJJNJGo0Gh4eHypIR+ZlIxYRJZhiGpg5ubm4qg07SxzKZjP6ubduaQlar1VhZWdFzTCKPz5w5w3A4VAaXJPg1Gg0mk4mmvrVaLabTqUoM5XO32+1TDLdUKqUAJMD29jb9fp96va4LH8dxKBQKykqSVLtEIsFkMqFWq7Gzs6OG79PplEKhoHI2WaTAcyazctwsyyKTyShIvOjLITI2AY7Ec+RWE+zbTVKTupOTv+XEbVnLeuXrVP8z6ILn0nFN3v9om/cXfHrjKd++4XIuMfc0Gg6H9Pt9HSqMRiNqtRrJZJKLFy/qs1Hu3b7vs729TTqdVsaj+AqKlCufzzOdTgkGg3xPxOFd+bl0Xp4Jwgg+lwjxwM301U5gg6OjI1zXxbZt3va2t+mArlKpaCJmLpfTZ6/cp8UDTu7T/X5fn9nyPF9kJsmQLRqNKnMK5olHa2tr1Ot19vb2yGQy2Latz+9wOEwkEqFUKpHL5VSKnUwmKZVKdDodDQyRNLbxeEyn06HX6/HYY49x+fJldnZ2OH/+/KlY7mUta1nf2Fr2P2/cWh6l10i92OnZ7f5Na+rTdp4zxpb6fMfnytDHcwzG/XW+N7etEzJhqXz+85/nySefVLAkn88rkCENg+M4rK2tYZomu7u75HI5AoEA9Xod13XJZDL0ej0mkwmJRIJ4PM5wOKRYLOL7Pr1ej1QqRT6f5/j4mNFoRLFYpFAokEgklLkk0e0CBgizZzKZaJMkLBhhKiSTSTzPo1arqQdNp9PBcRxlWUQiEfXCWdT+y6JawBJZ+IrhsRgGp9PpU7IqYVsJICKeLsKCkt8TOrtQ4eW4Lk4HBYwA1BxaPBSk5PP7vq8+OHKuiAG1fD75TJZl0W63yWaz6vkj8buysK9UKsocAVQiJuBMMpnUbZWkLJH8LU42hT0jYBagxptiIiqyvsWmV4ykBdgQYAuekyktGkULmCDnVCKRYGNjA8/zVCY2GAzo9/sKBsrXYrS7TGF3d3cJhULaTEsynlwbMrUNBoNqLJ5KpTTpTvx75OcCeMoU2zRNms2mMqFkcgso8DqdTvUYxuNxtra28H2f/f19xuOxgji1Wo1Lly7p+VkoFIjdNJQXthGgwGi1WtXprxynbrdLOp3GdV1t8KvVqso1JWEwEolQLpdPXUOL4Kact1euXCEQCGDbNpVKRT2t5HqD5ybjAkBnMhm9hkXaCChAJKbtIvNcNNJePOfl+9eCx9GylvVGrFek/wnFwO2B7/PF5pQr9SGGD/+kHuafnBtzPvDcfcX3fY6Ojshms+zs7BAOhzW1s16va6hDMpnUe6DcB+X+vrKyovdcAbxlkAVzn6disaigvzCIAWKxmMqEJawjGAxy3333cfHiRcrlMicnJxwcHBCNRslms8pElgGUBCoIe1NA+dlspr6Pcr+T50A6naZWqzEajTQ5LRaLYds25XKZwWCgYRbtdltl2vJ8Eo9DkZafPXuWyWSi3pmyHxOJBN1ul2azySOPPMLVq1e5ePEiZ8+e1RTZZb189WpguLwatuHVUK8Wqdqy/3nj1hI4ep3Xi73JNGc+X+1W4AIRw+O4UoZwlD89820kP/fbDIfDuYfQxYf4/Lf9FIP0KuHZiO/uX+U7itDttE+ZIQuIsrGxoY2B6OqlubJtm/39fXq9Hqurq9pgFQoFKpWKRpqvra1xeHioLAnbttnZ2dFtlqZIFrwipxLfmFu9UarVqrIY5PVkWiZNmQA44hsgMibxbJlMJnS7XWzb1lh0kdosgiOSjiXsFAEBhLotjBqZDC6aIwtQtbgAF3mTMC3E0FhAjsUmWppRkaqJX40AMoPBgFarpfHlAnR4nkehUNBUOvENErmepMZImtmi1G7RVNyyLP2Msr8l2UxYNAcHB7rfxJPKtm2i0aiyxSSpRh5g4qcQj8fVbFyMqEUiJaytbrfLZDJR9o74EIlJuPhSiGfQ2tqaStIkhWw0GnHlyhUFShqNBrFYjK2tLVzXpdFoqNROJHti3C4+UIlEQs/fUqlEJpPR80v8sZrNpoJvuVwOQA23hWFnGAZbW1vs7e0xnU657777SCaTCq7u7e0xm81YWVnB930ODw+ZTCZsbW2pXC8ej6sX0nA4pNPpqOm3SB1F3jAcDllbW1OW2e7uLqlUSs/FdDpNs9nU/SySSZFhyvbLfhSPLNkfAjjKwkpAWpGKyHFPJpP6Hul0Ws3D5doX76ZFg3W5zhYBpFe6llTtZS3rztdL6398yK6B7+E7DpFwGHPSY9Jv8ytXLf71QylNAtszEvxT/y5utG1SXY+/kRnzn5sNOu02lmWRy+V0mCSMGnmehEIhZWH3ej0NJZDnrGVZ5PN58vk8o9GI2WymwM5iybNj0fh/NBoRCoU4f/48W1tbNBoNqtUqrVbr/2fvzYPlOs/zzt85p0/36X1f7oZ7AVwABEGKm3Za3pfYjpWMbI8jZ8ZRTXkcO5PENTWpTGVclagmmoyTKo/HqZqyXWO7UrHjsmXLjsaJrdjavEiiTImkKArEdgHctZfb+95nnT8a78cGBUokBYYQ2W8VCkDfe/t2n/P1Oe/3vM+ihlzZbFYNuHq9Hs1mU8nbhK0LqNcuXoMyjEkkEkqiPBwOyeVyJBIJtra21L1N+hhhBMdiMRUqsbm5qfovkagXCgVWV1dVCIg8JszhRqPBZz7zGS5dusR9993H5uamYoHfC9fzZS3rtaw32hpf9j/fXLUEjt7A9WouLmFDI2tC07mddRQATVfD8XyYTRgQYm9vjzNnznDikXfwHy78MC0/jK/rjIwwf2g9Si7W5/v9y4zH49skYcIaEKqxZc3TShZp0blcjna7zeHhIZFIhFKppCQ0snlstVqkUikikQi9Xk9N08TcUdM05SGwaFopfjESxa3rOul0Whk0ixeSsHYWZVaO45DP5+n1emo6CCimjAACIk0SKrpt22QyGcWKaTabnDhxAl3X6Xa7xONxNS0UoEPYQSKlAhRwJGyPdrutNt+hUAgrFWf1gZNgzAGYxMSmf9Ak5M7j4I+Ojm473+PxmPF4TC6Xo1AoKNBFGFkCUglodXh4qPxthLEBKABIzNAdx1HTSpHSyRoQWZvIrhZNm4WpI+tgNBopmZNEqYvxtmwKhPIvLCNhly1OYwHl5VMqlTh9+jSmaXL9+nX1fhenotlslnw+T6lU4tlnn6XZbJLJZAiCgGvXrqnfKYCgsGWk0RX6/cHBgToOItETaV6r1aJWq5FMJlldXVUAR6lUotFoKMBEant7G9/3qdfrSsYmIKX4XVUqFdLpNO12m6OjIwUKjkYjqtXq/DMeDrO+vq5SfRzHYWNjQ0kSd3Z2iEajyvdKwEQBBKfTKaVSCdd1KRQKCiwcDAYUi0XFBJrNZhwcHFCpVDg+PmY2mykfJgGJLMuiVqsplp0wySSpyPM8hsOhSoyTa5qw78TPSHypBDgVsFhM4UUmsWgyL4DjN9KE3a0GTphyy8ZpWcu6O/UN9z+5ijwTBAHdqEXODBE2wvRxqNfrc9Dn9Hn+x4se+4MhrjGiZU/5lze6VCs6//i+OQNHfBBFsi8AUTKZVPeVo6MjFaggsq1EIkGhUFD3e0kvlYSzxfeqaRq5XE4NhBYl3SJbXltbo1gsKp+hXq/HwcGBSg4tFovKhFrkyTJ0ET9Eua/CC2lssViMarXKaDRSPYskp4kH4aK/3WQyUawqGSiVy2VGo5EKJpnNZsTj8dt6s0XGUrfbpVqt8slPfpJCocCjjz5Kca3MxPLANDCMECF0kn6EKCbL+uate4Vlcy/UvXQslv3Pm7OWwNEbuF4NVfvRpM65uI4/9Bm6ATYaOnPgaOprGKU1jOmQ0sWnCYKAmzdvsjuO0Nya4lkmhueBpuGg8QfDGG9rt+nfSvGS6FbLspSWXaRLgJosCfsgEonQ7/cVQ0kSpYRt1Gw2VcS2pKddv35defhI8omwSkSGJOwUAatE6iUsBrmIycRvZWVFPd7tdpUZsBhJhkIh4vG42ug2m00ajYaKmJfNq2VZynOnXq9z48YNSqWSSiuTv33fVyCCAFMCrAiLwrZtRQkfjUbzdKl4hMd+8ntJFLPk719HC+kcfeEq9mDKpd/7DMP28Lb49MVqt9sKLFpkiMj7k+mmsHxkkinpaGKCubm5qVK2RDLU6XQU80kYOIvm0aPRiEKhoMwxxevIcRwl2RuNRrRaLQUQCKtKnmMwGKivyUQzkUgoAGQwGNxG7+92u6RSKSVPFCaNADICyoTDYZWEJxJGAZmy2az6GQEbxShV5H4ySRFPIEnxqtVqAKytraFpGr1ej7W1NSaTCfV6XbHrZrMZxWJRbTby+Txra2vs7e2pxlqqUqmQSCTY3d3l6OiIeDyuwK3V1VWOjo44ODggl8tRLBY5efIkTz31FLZtK9PrWq1GPB5XjKBF41dhiaXTaXRdJ5vNcnBwwMrKikoSFP8LMSPP5/PK52MxrU2MyMUnSYzOBQgS0/FFo3ExUhdATX6fsM8W0/sEoBQGmzC4xItMnlOuk6+mXguN/7JxWtay7k59w/0POjY6WhDg+x4T16fuhkjNRnx7TqNSqZBMJvl4B4Z+gB9LYnRqMOzg6mH+k5vjQ+Uy1q17p/QTEvBQqVQUA1mGGvF4nOPj49uGORIcIPcwSbe8U4lcXPoJ6WUWU1gty6JUKpHJZBRLqNfrMZ1OuXHjhhpsrK6ukk6nFXNJWNHRaFQNEaT/SiaTRCIRarWauj/GYjElJ2+328q7D+aSFBlaJZNJ9XwyTGi32wpckvcqLG3XdVXoSD6fp9FosLe3x+999COwmeL02y8QrMXQTJ1VLUPUjPCAv0IiiNzxmC1rWd9sdS8wjpb9z5u3lsDRsm4rU9f4jw9H+aU9m08cDfiKa5EJaYy8gI4T4OsGb9P6vDfZY/yud7G5ucnnhjo3jRAO8wlUoGkEaEzdKfv7B7SOG2ozKKwOMYSWjbhsEqWRkshvmVZ1u11lmiwgRzKZpN1uKz2/RI/v7e0Bc6aJxHdLAyN6fQEHwuGw8h3QbplrC+NH/GIkYUqmdvV6XfmqCHNCZGmRSIStrS2azaYCDxzHUayl4XDI5uYmpVKJ4+NjWq0WlmUBL3izSMnxEer6yuYa8QsV0isFji/t03xml1gspkCglUdPE45FmY2nuDMHf+QRssKMj/usvPMsFz/8V4rOLelUi7UIJok5piSmyPeKj5QwusQoW6J7a7Wa8s0xTZNWq6XAKGmY4QW5nEwrBcCTxBnLsigWi+rc9/uEXiXNAAAgAElEQVR95d0jjKfj42MAFTMsUevyvCJ5EvNqmXhGo1EGgwG7u7tqyioJcolEQjXKo9FI/S1N8nQ6VWtJADuR0wmwomkazWZT/U5ho4lpukjyxJBa1nuv11PrWNg+q6urRCIR9vf3MU2Ts2fPqu+zbVsxggSYG41GhMNhJb/rdrtsbm4qI/rd3V1CoRCrq6u0221Onz5NPp/ny1/+smrUT5w4oT6rV69eVedLWIIyOZfjImCseC+J0euLGUlimC4SO2FfiReXyDYFAJTP6+JaFAliKBRSm6PFFDphNImPiEzExVh2scRXbNHj6JVq7JdxtMta1hun7tT/pA2NXr1Db9LHjaX49o08v/hwmmRkPjDIOS6aOR+wUVjDSBXQzAihmIF+654h9yiRkgl7djgcMh6PiUajuK6r7knCdhW2rARwZDIZ5X34UiV9kzAtZXgg9whhgMt9LJFIkE6nmUwmDIdD9vf3FQtXgKhkMqmkyDIYOj4+VuyneDyuDK1rtRrD4VAFTAhLSO7j0u8Mh0Ns26bdbitWsSS/pVIpisWiSjwNhUK0h12q9HDCkDMTrEeyZLNZNjc32djY4Onq8zy7c4n9375JZDPD2Xc/SGolhGnDVb3KA9raUsq2rGXdxVr2P2/OWp6lN3C9mokbQCKk8XOnIjwyrfI/NS08zycSeFRMg7Hr84/jLfIPXmBnZ4fZbMZZd8pZhjynJ/A0A42AsD1m+/BZqocHNBoNut2u2tAJDVkaG9ncy2bVsiyazaaSkQEqsclxHMUS8X1feewspiY5jjP3XbolfVk0MhYDR9u2aTabarO6vb3Nzs4O3W5XmVXL67Jtm3q9DqAaGgFMZDMtvjBCQZfEEgE7LMtiOBzS7/e5evWqSuYaDocKPPE8T4EiUuIHFIqYnPyRt5MoZZgNJuTPr1Et57j2J19UEfKxTALfdgmnLHzPx3c9DDOEO3NIbRTYePw8sWSCyXGfwdNXvuYaEAaOePOI5Mn3fVZWVshmsxwdHdFqtRSQIADJIhvEcRxyuZza8AvYJAwXOW7NZlOdQ0lb293dVUw1AWqk0TZNU7GHxBxT2Ghy3MQTR1gu4s3Q6/XQtPnE2HEcBUrK+5Dz0mw26ff7CvSTlLbhcKhudAJ8ttttJUeT32vbtgLY+v2+Airy+TyWZSmWlPhora2tMRgM6Ha7FItFNXkVL4pkMsmNGzeIRqOcOXOGK1euKBBQ0zSq1SqVSoXV1VUuX76s1q4YxAdBQLFYRNd1Dg8PAXj3u9+NaZpcu3aNw8NDlfZjGAb1el0BYSKlFNP4IAjUZyqVSt3GJBKD+tOnT6tERZGjyhoXk3IBcwQMWjx+ks5nGIYCZcWIVo6lgG4w39AsXkPkfIs0bfF6IO9LQKVXU8uJ27KWde/W3ep/fD8gWtkgHgrjajr/92Mx0uEXAObHMwZvS+n8l5aPqxloIZO0P+O/SYcwtDDWrXu7pJJK0IDcs+RaJbLmYrFIqVRSLF8ZgohP0Mt53yJXlvuDgOhyfREpubweAYASicRtMnSR1fd6PSzLUgER5XJZ3btHo5Fi0C6CRN1uF4BMJoNhGORyOWUrEIlEWF9fV/2SpKc5jqPSN03TJJ/PM51O6Q563EwOsEMB3tihPj6gbbc5oc3vpZubmwSnk+Qf2OTzn/4MF5/5MjefvEQqm+EH3/eDFLZWuaxrGKZB2ohSMFKEjaV87eXUvSSNWta9cz6W/c+bt5bA0Ru8Xu2HOwgCTuozHjYnPDmN4GshQsDfTrukew6l0jxe/vj4GGs45IcufpTH7vsWPheqYFkWZ7tXeW/FJSh8CxcvXmRvb49ut6uMh0VqJRtn0bDLplAaJV3XKZfLKiJW5FyL7038VYSpAC9Qs0WmIk3QdDolkUgoWY+YBzcaDTY3N5XUJ5FIKCBENqz9fp9arab8VhZNrjOZjNroCiggPkW6riszS9HvC6Dk+77yL5J0sUXwaDKZAJBaL2CkIoyOOgSAPZhQfOspvvA7nyR6K1Wrv9Ng610X6He65C0TPWFxfGmfE4/fjxExOfP9bwVNo3X5kMzn1nj2P3wK3/W+7loQ9kgymVQx8wICiWm4eDjJcRYGkrC7otEoqVSKcDjM8fExnU5HNc2LvjXSiMoxdxxHMXsABRJJ7LAAAcKWkWmmABLj8fg2E9Fer0cqlVINaS6Xo9/vK5+p1dVVut2uipUX4En8pCTVTFhmMjWW7xOGjMi52u22StkTOZ+AocJSymazuK7Lzs4OiUSCUqmkQB9d18nlcsoEW8CZ6XTKyZMn6Xa7t7F+ZrMZe3t7yng8l8txfHxMv99nfX2dRCKhjvHp06eVp4SktK2vr9NqtQiCgEajgeM4FItFAGWULsdc3o+AsWLSXa/X1WT82rVrvOUtb1FrJplMKh+PTqfDxsaGMkSVpkHkfYteZCKJCIVCyvtL0zQGg4GSxsl6EsmH4zgKwBQwTNd1NYH/Rv2N4O5P3JaN07KWdffqrvU/IYuQBj9WCVEK385KDOka//5CmH+/P+H3Dyd4QcD3ZTX+lws5QrqmBkrCWpWeotfrKRargPQiwVpkFYlETMIEXk6JZ5F4Nso1cpEdLIbYcg0XACmZTGKapupnZLAhrGHxJhQgqVAoqMACkZ/JgEYkcAI0JRIJxa7t9/vkcrmvkqcLy2gxtXYc8XFmx4QnGr4eIluq0LPHaG1d3b/tsI8dd3nobY9grCToHDaoffE6v/0bv0Xx7CZnv+shkukU5ViG9VCBB7RVLDOiBgrLurdryRR7oe6VY7Hsf96cZXzwgx/84Ov9Ipb19Uum5K+kPM9jPB4rz5+XU0EQMBwOOTg4wPNcfvLCKmtxEz8IuDENuDgL8QU/yeMJl3Iy/kIku++xYXfY3n+KH4pPOKePyWezKrXD931Onz7NiRMnFEDUarWUN4r4FUmj0O/3bwMNNE2jVqspM2KRfcmmUvxc5D0IM0F+PhaLKcmLTN/y+bzyVRGARkAsoW+LF0s0GlXSuEQiocwgZRNaLBYV0CDJWQIayTGSOHihSwvQJcdcDK6F1SHnHcDKJlh5bJtRex7fjq4Rippc+9On1POPWn161RZWNo428xkf97DHU6xsAk3XcUYTpt0R0UycwPfp7zcZt/p3XAcvviEIWCObcUlLicfjqvEUn5l8Pk+lUrnNf0YS7LrdrpIDyvsTME2AAmlyF1NbRE4oUjuRNi5OUBfj2mWiK88pUruTJ08qQE8AMWGMdTodms2mAh4EjJB0L1l3wG1eUQIEisxMDElhDrZ0Oh0Mw+Ds2bPMZjPG4zGTyQRd1zl58qQCmERiNhgMlOm1gHHNZhPbtqlUKgroKRaLqpkXAEw8Js6dO0c4HKbRaCiGnACu5XKZdDqtzqWk4q2trZHNZpXpqMjtJKFPNhQCwFYqFbUuxNvoxo0bhMNhTpw4Qa1Wo9lscvbsWSXPE5ma+JvlcjkFeAm7rHvLE02AM9ncyGdxOBzels4nhqumaarXWigU1EZGJIoiDwGUJNHzPAXyybl+uZuIwWCgzPe/0Wo2m3zkIx/hp37qpxT4uaxlLWte90r/86WBz5+1XL4zZ5A0UNL3wPN4LBvm720l+NsZn7dEPRK3pMlynRCWrNxrxOen3W4r5mYul1PeeYDyPyoUCl9TorYoyZUSCa9UJBJR3yf3Y+lLBKgRprX4E5mmqeThci8VsEv+yIBOvOpE3i4G1vV6XV3T5XUIA1WOTSqVUvdZYSCLIXc0GiWI6HSTLnHT4sozX2E6dTATFqdCRTV8CqYus86QgT1B9+chE6fOb6PFDVo3D7j4p19g7/kdsqdW8B0XfeRiei8MEuCFYQXMAbtMJvOy185rUb1ej3Q6/boCBcPhUPWtr1cJ6CnSzder7oU1If3Ty2Efvpa17H/evLVkHL2B65VStcfjsUps2tjYYG9vDyts8s60z89dtdGBuAE3vTg/17b47c15KkgqlaLVbvOJxFk+Wd7C8QPeNd3nA4M6pzY38TxPbV63trYUM0DMhmezmYpYlYuQaOFF2mKaJpVKRbFbxBdlMpko00VpZESuJptZ13Xp9/tEo1FlUiwSJTH2lU21bMQXk8NKpZKS2+zt7WHbNidPniQUClGtVhmPx1y/fl1JcEQyJ3G70pwJ2yoSiZDP5xVYYhgGkUycM+97B7kzq4xqXb78m5/CrXeVF1F/v0n/oEVqI4/uBoQSFlf+85Pq/Aor5uhLO4xuNrlx6zjmTlVI5tJYp0rYkxmB56MZc9mSEf7qj7+sGWksxYxSGsPRaKTYVhKdvr29rZgmQnEfDAYKPDFNU4EnIu9bjEsXfyIBycSrRiagAuIsprVJQls0GlWSx8XULQGN5D3JRPTatWvE43FKpZKizrfbbQaDgUp3k1SadDqtJHvpdFq9/8lkwv7+vmoyhfK/yHqJRqOMRiNms5kCKK9evYphGMoM1HVdrl+/rqbMsmmRZLF6va7WlPg9iWm1pP5JBL0YhJumqYziFz2dptOpYlVJZL2maVy6dEmxwd7+9rfzuc99TkkBBYCTCXM0GlXsrX6/r9bJolxMzLwFgBXPodlsRjabZTQakc/nOTo6Uh5kmUyGdrut1oaws+RYLso5BPARU1Uxk5eNpQC38nps2yaVSimposhHZbMgj7/a5mc5cVvWsu7Nei36n4gOz/Zs/vsvTvj/Hoqo67Ou6/zbPYdfOZjgeDrvTWr8E79OcAuYlo234zi0220lvxWmtCSazmYz9Xp836fZbCqZ+EtVEAQqAW3xnifvv9VqEYvFVJqpgEkygBHgv9vtqvuwgEqS8hqLxZTZtvgXCcu23+8rJqhI46TXunDhArVaTTGKPM+j1Wqpnk7TNFqtFuFUlIPihEZ2SNCaEepBo9FgOp1SLBaJJ2KkQxat8JATj5yj0+mw5ifJ5+bM4VgsRjgcnie5tVqUZmGGrSFWMYm97tGsNfnS73wcu9nn6NIN/tb7f5RwYcg03FfydEknFZBvWfdO3SvyrHuh7qVjsex/3py1BI7e4PVyLjLT6ZRGo0EQBKysrHxVk/JU3wMCwvr8ImFpAVfsEJo5l5dkMhkuFc7yZ8YpzMAjrPk8Ed8i1Ojys5ketm2TzWaVbEm8ckQqIxKWy5cv47ou8XgcXdeVn006nVaPl8tlbt68CcxNIAUAErBGosPFS0n8UjRNo91uUygU1PdNp1MVEy+MhXw+ryLgJW1NPGfG4zEnT56k0+lwcHBALBajXC6zu7tLJBJRHkbRaFQxmESSZxiGAiHE7ymZTM6/x3F4+8/+LcxsjEGtRbyc5q3/8Af59Ad/G2cybyQ9x+WpX/svrL/rPuKFFIO9FtWnrqlzJGbCk8lEAWMAU89mY/QQ4+6Q5EqOwA+whxO8mUv/sPWS60XSz+S5xaQ7Go2qFDsxSD46OqJQKLCyskKn02E6nXLcaRGENDTHx9RDih0ymUyYTqcqQW1RWrjoO7PYWMukVWSMktIlQIMASwJqLabcOY6jmGkiW7Jtm+Pj49vYTNPpVJ1zkWBOJhMFmMjmQPyzxHtHNgUCAC4mgYlfhaZpKj1OzKUjkYjyxxKwUzy95Gfldwg4lEwmCYfDpFIpxuOxAl88z+P4+Jj19XXC4bCS2aXTafV/y7LIZrMKUHMch0ajoY799vY2e3t7Sm5mmia5XE4dP8dxWFtbo16vs729zdbWFleuXFGpab7vK+PrbDbLzs6OYhR1u10SiYRaY3I+5T2JBFXARpFyeJ6HrusqwlqAvSAIbjMlF780YUMJuCWeVwKAymdcAEjZaAhg+UprqfFf1rLu7brb/U8wm2D5Phd9EzMaI2LMgZrfrzn82z2HqBEQzCZ8uNogH6T4pw+uKBDCtm1arZZi9QgbulAoUKlUVH8gJV58Ykp9p5KBmzCEXpwYqeu6kvdblqVSLGVAJr2QhFIIg1ZCN+R5RJos11S5P0lAA6BALxn4CIgkXkjCnEomk8xmM3q93vw4jEdcirYItaNUSmWCbITumTD56pxlXqvV5kmg2TSuBpqtsZU6zeBqnavHVymXy2poA5DP5+n1euzt7fHsX/45X7j2FfqdLslimiCXZO3UFs7Exu85jGIjxfA9OjqaA0+xGMlkUgWgiMTwlWySXXwcPMIYGCxlcMu6u3UvSNWW/c+bt5bA0Ru4vt7FRTbQtm1TKpVui/ZerEJ4npKmNva6TsT3iBi62rhdS6zDGExdx3FdwqbOjcwW/f5V6vU66XQaL5HlnzWSXLPeTt4b8z+HeyRuJVHlcjk2NjZUCpTo3GU6ZRiGYj4EQcD169eV2bbIUkQOk8lkmE6nanMu3igCKomHjujuh8OhigP3PI9SqYRpmtTrdXRdxzRNTp8+zc7ODuVymUQioXxnhM7d7/eVzE4kVAJGDIdDBTCIoW9qq0imlGNS62O6LlYpidsaEwlbjBo9UusF4uUM3Zt1dR7cqc3xV/ZI/41H2Xj3OcIJi8YXdvA9n+FwCKDYGlLj3pAn/9+Pcf597yK5midRSdO+Muban3wBuzd+ybUxs23W3n6W9HqRWXvIwecvKz8kkZmFwibFEytMByNu3ryp5GqpU2Ue+onvJdDBmcx4/sOf4XjnUJksm6apGspFGYEABUEQKGlUs9lUIJ1I4mQqKr447Xb7NhmgHGN5Tmmo5fgvJroJUCLgj+u66rlgTtMWoEqAL2HyCMtHGEECrom0MplM0ul0gLk0qlAoKFaRJNOJVEso/fJZEImVgDLZbFY13+PxmI2NDQ4PD5VsSwAbSd7RNI0bN24oXynxhBKg7vj4mEajQblcZnt7m8FgwNWrVxWTrNvtKmBWWD1Xr14lk8moGOpGo0G1WiV7S5IqoN7e3p5iOQmbDOYbtGw2S7/fVzJG+ZzEYjHF/PN9X4FFixIKMaQXttBkMiGRSCjjVmGVpdNpNVUXwEgm8QLuCYj4jQBHd7OWjdOylnV367Xofwhb+AHEdU0N0gA+0Z6DS5rvQ6eOmczy1+RuA40u7tf413suF8caZX/EPyy5vO1EmUqlcluyI8xBmG63y9ra2h2ls7PZTCWYbmxsqHvXnb43lUopEEr83oQpKvfbxZCSdrutkt9eLI8TGbbIiIMgUNJrYSnPZjOVlCsgvoBSk8mEVDqFtZYhpKVYceeJq7vTr2DXhzx76UkiVhSjEGclWCMWjdLtdtnZ2SGZTGIkI4wzLnsRn1jBYHzQUvcPGV5Uq1WuXLnC7u4uzWaTtB6heN8Zuv4AV/OJWBGyfoxBq4fmzO+34k/oui6tVgsv8Gn6I77U3SETTbAeLhKPviDfC4VC6CED39QIayFMzVBrrmfOuBntgQYGOtuTHMkgolhgi956L37sxY/LMb8XgIJlLeu1qmX/881VS+Dom6TuZvKPJGWMRiOKxaIyeH6p+raswXfmDD7Z9tCCAE3T+Vlzn9ksrfyIVqMhmOpoeKBp9H2NnlXkZ7Qc7yrs8S2Hf82/W3uQYy9OFJe9IMq/GMX49bUwg9qhYgdJSlY8Hiefz9+WjiWbvEQiQavVUgCQeJWIGbN4zUwmE5LJpAKcJLFjNpvRarWUCaXjOBwfHyuQyHEc0uk0xWJReS0dHh6qBDbR5kvM+dbWFvV6nVarpZrAWq3GbDZT8eIq5c0weNvP/AAb33I/WgB4Ac//xqfm8ht7Am6ApmvoIR13MrvtPFiZOI//rz+MGQ2T217lkb//N+hdq/G5X/wo1z7xNDBnWUg8rjSS7Vqb44v7FO7b4OivLxOywtz/o9/CqNGlt99UgNlinX/fu1h/xzns0ZRw3CJ3aoVLv/cZZrPZ3HizlOHMj7yTeCGN67jsfewZ6s/ehIjBie97C/1GG3fqYMTDnH3fO2n94n/ECkcwM1FS+RKWESbozE2OhREk9PdUKqVSvGKxmGKhiCQrHo8rIGcRxJH1IObcix5FIicTcGk0GinTUdu2VcS9ZVlqehuNRun1etRqNQU8lkollaKWyWSIRCLK7DuZTJJIJNQaEemAAJhyPsQAXVh4h4eHikkjEkaYN9tiui7MN9H6P/fcc8pXazAYKN29eAGJDPTo6IhsNsvGxgapVIpqtUqtVmM8Hqv0niAI2N3dVbJPmBvOi5RLUm6EORSJRDg4OFCm2Y1Gg9lsxiOPPMIzzzwDQLFYpFAocHx8rI6dgFLtdhvXdclmswocSqfTdLtdBfJMJhMFDooET55HzLnFy6jX66nGPxqNKubRonRNwCG5nryYTSfXyldynb2bDb28vmXjtKxlfXXdM/0PAWjwS+fCt/1MJTIHlwzDgJUtWnbAZ3o+Z/9qxH+bcfh7sTb/9LrGjh0iMu5ydTzlX2gFPvVo+TawQF5zvV6/I3Djuq5iw1YqFeX5spjE+uJaHGLIEEHk0ALuz2az25IvxTdukWUszxUOh1WfJH6QIhuWMIpEIoHjOMrLT+T5x81jPn74NEE4TraYJxwyeczZoBxeI1T2cT2HUXdA97iFEy/CrTAKgFavzfP9Gim9RLSYwykbWAWN7KUO1mGHfr9PtVpVQ8Pz588zGo3m4Soxmyee+xIJy8ILNCYlkzPWGnFMDN1gZWVFpYMOh0OuBg1mAxc9MNi12wzcCWecFdV/TrC5Hu5i+z6GrrNpZymTxDMCrkVbRBwTkxAzzeVyqMF9vRw6GhPdYaK7GJ5GzDEgeGGNyv1qkTFm2zb7+/tfc41/PfDp1T4uj4lVweL3fK3vf61AriV4Nq97Raq27H/evLUEjt7A9eIPtWjm+/0++Xyecrn8sj74uqbx6xcifKrtcewE3BeycW5MGI9NyuUy3W6Xv5ue8PFejF4QYmQYzLQQuWCKg85/jp7mL7bWmGo6Rd8m8DwSZoiJb7Djhlm/leTR7A3QrZhiFUiCVTKZVGbJ4s8CsLOzoyRIwlgQyZIYMEu6iFzkBJgQ08pIJKJo4p1OR0nMer0e+XyebrerEtXk6+l0Wk3whHkkv2MymbC1tUWpVOLpp59mOp0qCY7jOKw9us32dz9C/dK8GbCyCVZ/4CG+8uG/4sLfeQ+B7xMyTa788ZOMj/uY0QjRRIxxZ0Dx/AbhRJRoJoaViTM4ahNKRbn//e9h2hzQvHygmBrCtBEm0ua3PsDgsIk7dYjmkmx+6wNkTpY5+OzzPPXrf0bYQwEwRjzMxjvvo329imGEmLaGpM9U8MIaztAhWczw7p/7UUKJCI2Le8x6I7Z+4BGqV/aw4haaoTMdTtB0jWA4I5FPc+rcNpnNMoVvOwO3ltzxF2/QfGJHgRSu6ypD42g0Sj6fV/IiAYQEJBC5nxgEivmxyBsBlR4jYEooFFIeWeKPNBqNFDAp8iUBqMTjSlgrImkQUNG2bZUyJiloAmgJ5d1xHDzPo9/vKyBkEVzsdDqK8SY+E6VSSRliJxIJNE3jueeew7Iscrkc9XpdpaiJZFCA0dlsptg/u7u7anMhUjBd19V6zOVyxONxZXTe6/WIx+O0220qlYqSVQiIVy6X0XWdGzdu0Ov1lGHr5uYmx8fHHBwcqM+KmFgnk0kF6qytrdFqtRRALEAhoCR34qPU6/UUO0rOj3iEyPRaGEgC/ggDMAgCBSYLw0jOoRjTy7mSKfnrXcuJ27KWdXfrtep/HkkanIvfzuz56XWTP2l6NO2AoasxDmDNBHvQ5//aafCbmRQTLcSK3SUIIJ1O4SazfLnn8HhunrQ59WHqBYrxsyhRC4L54yL3WmQpvZySRLPhcKgCCmSQIh51Is0W4F5SX4X9ughiCYAk90sZkiUSibkn4y2Zm4RISHCGndTpzmaEro/ROjZmJsrno2NOUuBquEX8RAEnDOdJU9Kz6JEQ+USJuGnxfHePizfa7O3sMNm7RraQZTIc0b14RPzQIxNLkkzO/4j/4NmzZ4lGo3xq74usr65gxWL0J31udA/wVgOSkzCPpU4r6XqhUMBMRAmCPgU/Q8yyCIUjtKc97OZc3n14XOXGypiwFWczs0IiFKPqjskNE/THQ+qdKtOjHslcmjNvOc8k7JIJ5xjoM/ZDc3l4AKx5MU56+a953vb29lhfX3/JwIYXA013Ap9e/NhLfU3ugy/+Ptd1VQDIy3n+l1OvFMQSQ2jp478eEPZywK07Pf7NUt9Mr/Xl1LL/+eaqJXD0Bq5Fvbs0HdlsllOnTr3i+FFd0/iu/Hy5uK7G5ViM4XDI5uYmmqZRNOEXIjs8aRT5pX6GAOjqc1o3wMAI46HTCyAVuExnNq4ZIRMJkUhn+H+ODP6q/AABAd8ZGXPBvKa8eiRpw7Is1tfXmUwmDIdDVldXOT4+ZjgcKmq0NC5iHiwJUJlMBsMwGAwGFItFNTlqt9vKDDgSiSipjOu6lEol5Z0irIhOp6NSRPb29tje3qZQKNButxXTqVqtUigU2NjYQNM0ms0m1WqVer0OEQND1wmFDFzXY9YfEy+lOfjLi0yqXYy0RTBxaV8+5L73vYsL73ucIAjo7dS58omn0DSIl7LYgwnoGr7r4Xs+Zj6ugA5h54hMyoxFsFIxXDtM/lyGc+99x5zR5LiMG10efP+30b1SJV3K0bi0R/7CBhuPn6f0li3Ge2261+vEsgkSK1ncmcOFD3wH2fNrzLojtr71AfY/f3l+nJIW3WqbwPOJpuLYoynRTBzdDQgcn5XvOE+/0UbzAmzHofDoFuPrTfSxx2Qy+Sp6NqCkSiJLFO+EUqmkpE3D4VCZlwvDSJL2EokEg8GA4XCowCNhMAk4KTetUCikgA8xDJ3cklJGIhEFYopPkjDjxIdJfn+hUFApb9L0iOxLvCHEzFzTNAqFgjJZhTlrLB6Pk8lksG2b6XSq5HnioRW79fkTI1NZfyLdk8mvAGKtVot2u628n2DelAoAJz5G8rMCaGmapkDPzc1NBoMBly5dwvd9qtUqpVKJ9fV1NE3j8uXLSlbX6XTodDrK0F6OsXhoyGdJ/K4cx05H+K4AACAASURBVKHf76sEHzEhTyQSSqYmoFw8Hufo6IhUKqVANzGHFZ8oaTSlEVlkHkUiEWXOvsg+ejV1txo4YQG80RrCZS3r9arXqv+5U5UjOh97NMofHbv8syszAuBg5OEfNyCeoY2J02sRyedZy6bwXYe+6xPxbAYjhw/tTPlow8OZOXx3qMEvvGdbebONRiPq9TrJZPJVvXYpYRSNRiPl6yfsWmFqy9BD7n1iHC33WpEEL5ZpmrcxkISZK9d027YVqNT3fMJamGA845mPf47sagGrlKISOs9KIoQWz9OdQtTWqJ2YclPvYA/HpGZhKnqW8skyrUsdrn36Kca9AZFolK0TW1jFNIx8dS+zLIutrS1M0+SoXqPVbuM7Lt3ZgEEK4kGYaVTH9Fz+8voXKSfzuJ1dNnsrRNez3Aw3aQ32SRzHeOShBwmHZsRCORJ+mCdGV9g52KX32WM+2R3w6MMPE0+liEUnxAKTWTAmkU9SWluh1W5hRMPM/AlfsY4I23PPIytqcWT0KfoJEkHkVZ1PeG0ZPlKe55HNZpXs8G7UKwW3hPm06He5CHh9red5uY+/nFpkgL1WTK+vB3pJLySv+fXsGZb9z5uzlsDRG7hk07izs0MqleLkyZN3BdEV7bpEsUraRilu8RcdC9swIYBbxG70IMAkIBK4jPQwpgmeY3PfsIq+f8wfpc/w+VCSmD3Cc13+0kzjrz7MuzqXlL+NMC/Eq+Xw8JBYLEY+n0fTNGWmLP45gNLwizQol8txdHREs9kkk8koOYuwk0KhEJlMhn6/z/HxMbVaTbE1Wq2WakaCIGBvb4/RaESj0WBtbY1YLKYYR5PJhGvXrinmh/gi6brO4KCFY7tYyTjT0ZiVt55h1h9x+ofeypU/+mvcmTP/mYdPcv8PP053/xgtgOx9q1xIRwknooRiEYxwiMD1OPrCNXTTYNabM2ReTFnPbJV558++l8xmmdKDm8TLGdB13OmU3FYZf+ZSvLBJ68ohgedz5v3vwrM9unvHJMoZCg9tUnz0JLPeiHf8g7/JqN3HjFsMqi00XWc6mlK8f4PWpQNiIQvftLj80c9z4YcfJ5KJofnw/EefIHeugrWeZtgb4I9mZNJprGiUkGXSq3cZjUbKLDuTyShD8fF4TK/XU82nTDrFuFkYPzLRFPNO0zQVCCiPS+Mh52owGACoSWyv12MwGCi5k3g4iE8WQKvVUsCNfBYsy2I0GpFKpcjn82rdCXiZSqWoVCp0u10GgwFHR0cqFSyTySjAKhwOK0BpNpsp34hkMkkoFFLRvMKuKRQKSmZQqVRot9uq8U8kEhSLRcWEqlaryl+qWCzexkASecKZM2eU2ep0OlXMJwGDHn74YZ5++mnl2XV0dMTKygqVSoXr16+zsbFBq9VSoJoATzLJlfUp78e2bZrNJtvb22oqLRNO13XpdDqk02kF7AgAJgxEMbSVTdBgMCCfz6vzKedhOp3i+75iW/m+r/xB0um0MssWppswlL5ecyeeVovf/1Lfe6evLdaiD9OylrWsb7xeq/7npSpjavxx02V8i8Do+x5kyxCKEOkdESsU6YUTWK6GoYX5rrLBW0sRfuPQ4T8NNTIxj0m7yqcTGX6z5vH+XI9qtYqu61QqFTWYELnuq9loSRKqgOyTyeQ28CgSidDpdBTbezqdKvayME9ezD6SWgSQJOlWWMMqHCIcJrtSQE95zNwZu8eH5PUE1diIk0ERY6hBYLEzqTHQJqT8MPFQghYDbu48S71eo9Gqk94sYTaijK43OPIOOPfwO0hnYxwfHxMEASdOnCCXy/H83g5/tf80I3vE0HPwEzrGWGfS7BPMHDbW1rAzHsfVHXwC/vzZz2GEw2Q3ixixMNbpFM9rdQwDvji5xrQxoNVp0zuu49ke2UqR/XYDa7eGR4uVTIGVtRzahRxOWGPWn1E8hKe4zDPD69gHPbLxFO/83m9FQ8Pj9We7vh71SgEvkflLoMzrUSLpX1tbe9VMr8XHF5NgX873yx/phwaDwStieN1tcGvZ/7x5awkcvQErCOYGvI1GA8/z2N7eVrKPu1GaphGNRlWKmEz8w1aUL/lxMni0MHB54WKR9GzcAEqGx48kRkwOrnOifolZaJ0n8NHx0IFA09ACn8takvtu+casra0ppsYikCDpVIssI9M0lcmlbdtqIwrzhJFCoaC8VIQ5In41wnJIp9PMZjP6/T6nTp0il8spKrMAAQI+iBxoc3MTx3Go1WqMRiOGwyGtVotisUitViMSibC+vk6tVuPpX/0YD37gu1h79zl0M8So1uWh/+47KV/Y5DO/8IdkT5bZePd5PMchUc4QLWYonFsj8Ly5j5CuEc0mIAhYefQ0z/3uX1B9+vodz9Vbf/r78V2P5nN7WKkYiZUc3tTG7U/xg4Di/Rs0n9+ne6M+TwnbKBIvZ7n2J19g2imw8uhpwkaI2meuzMHBR7bwbJfqF3dYe8c5oukIeijEzh8/hdOZM7e05pQv/eqfMvVsPMflrX//+0mvF7CyCbb/5lvZ/9RXmI6n+IMxjD22trbY39/Hsix6vR79fl+dS/GVWpQ1iem4AIICAEhTK2l4AgjACylxk8mEfr9PJBJRngYCLIi0TQCfUCikqPYiVZMY4eFwqBg8a2trZDIZxuMxg8GAVCpFt9sllUopPx5h3MhkN5VKEY1G1fMKaJbP5xkOhzSbTcWM0XWdRCLB2tqaSqIplUpomkav11OAyHQ6VQwpAdeEnRMEgUqy2d7eVsbih4eHSva2uCmQyPpIJKJ8n27evIlhGOTzeer1umIvXbx4kel0yurqKmfPnuXJJ5+k0Wio9BzLskilUpimqYAy8cBwXZdcLkcymSQajarEOGHxpVIplc4m/mTRaJRsNovruqRSKQXAVatVisUilUplHqVtWer1F4tFVldXCYJASRTT6TTlcpl2u006nVYg4CJgeKc/0vDJWllkNryS5hHgiSee4CMf+YiSZL7vfe+77fP73ve+lw984APq/77v88EPfpDLly8TDof50Ic+xObmpvr6hz/8YX7nd36HUCjEz/zMz/Ad3/Edr/Yyv6xlfVPWa93/vFR5QcBfdTxyIaiNHXzPBStOSNPIr26AprMR0vjJdZO1iM4PFA10TeOJnk9YB811mdX20EoBH7vU563FCaurq2rotMiMXGQbyPVKfAK/Fqgkm+9+v6/kwi8Gj2SA4TiOAo8EVJf/i2fgnTZ7dwKQUqkUqVSK0WjEme6U580GnM2SiLuExjqXnCO64TFv0TYYhR32RlUi3RzdicOVp59jojsQBJQyJeKleVKnETcpv/0MsY7PwcWb9BNJNjY2KJVKlMtlZrMZ+2aPVCpF2k9x7PTpMcGZ2tQv7+POXIaNDsZUQ69P6LU6HLSqVK/tQtvh9Pc9xuYDp9DMEAU/jhEyGDLD81yMnkPsTJnciSK+pnMhU8DozL0yb968iffZgFwhx8mtk+yUuwyDKXbYJ/RQibMnzjPFxQg0osFXA3DLujdLAI/XG+Dodrto2tdOW1ysVwpMvdT3LvufZUktgaM3WI3HY+r1OqZpsrq6SrVafU2aplgspmjUq6urNBoNMpksUXx8IOPPcEMReoFGFB/HCIPn8OOzK/xQIUEj7VGbzOU7RWvKRS0JrjuPi3c9itiUy2UODw/VBlPMIoXVsDglk82ysH40bZ7gJQ2Xpmlq057NZpVpdSaTUSwNmDc9e3t7mKapPG3E9FhYJclkkrNnz3Lx4kWCIODzn/88a2trnDx5kng8Tq/XY3V1VZkyRyIRisUi3W4Xy7KoX6rz+X/1Eb7t3/wEvd255h1D48L7v5WHPvBdOBObaXdI5lQFMxYhFAmjG3Oz7H61Q7KcIQhgcNQCNOLFDMEdfFqMcIhoLkFv9xgrGmXaGeLZDqNmDzMawQwZBJ6PXR+QiCeYTCcY0TC5M6uc0d/OpNnHHk3p3KjjRjTWv/UBIqkoISvMqNGl+vQOiUqWqx/9a3b+/EvqpmpZ1nwiOXMpXFgnuZKjda1Kb7/J5rvPU3n7Ngef+DJXfu9zOK0RduwFo8/FqGCJJ45Go8q7RlJfxJtGZGWSGDYej9E0TSWp9Xo9JRuTFC1h7LTb7dvARmG9iD+RrAFprNPpNJ7nKYaagEvD4ZBOp0MqlcL3fWKxGCdOnGAymagI5N3dXUajEeFwmHPnzqHrugJ0ZH1LQpuYuotXUBDMk2s8by7pE+BSJHipVIrj42NgLreLRCJKJiBSs2QySbvdxjAMOp0O6+vryr8rCAIymQyNRkMdZzmenueRyWTI5XJUq1Vu3rzJ2bNnbzPSluN44sQJ0uk058+f5/nnn2cwGCjZQ71eJ5fLsbq6Sq/XUzIMz/MUy0tYhWKMDTCZTIhEImojIt5J0WiUdrutjp2sHQHhFo1bJZVNJG9i7rq4ViORiPJYermN4XA4JJ/Pf0ON5ObmJj/2Yz/Gpz/9af75P//n/MEf/IH62p28lz7+8Y9j2za/+7u/yzPPPMPP//zP88u//MvAPCnvN3/zN/nIRz7CbDbjx3/8x3n88cfvyA5Y1rLeiPVfq/+5U+lA3NBw/YBKNMQkCNN1IRGCGTqmpvF/ngnzPQXztp87YWl8tgsxM0x0+0F60ymrxox8Pq+kVyLXWZSoyGOLTATxgxOWrHi6CatVwgEMw6Db7ZLNZm9jWwrjSMyxp9OpYjqJVE2ur1+LfQQvAEhiriw92UOJM6zPSvyJ/WXSVol6q8qsP+Yr+SEXjUM8x2OsdRheqzIdjmlUj4jn04TNMLVaneFsiGfbZLIFkrkYVjggOnXY29tTg4Vut0u722Fvuoffn3Dj0nWMuEnPGTNpdBm0Bxg6DBpRtM6EwUGXfqfLYDKA6Rygax03WZttEnQm3OzViJ4o4vkuk+mUlG8ROuxyZbdBchpi6lvKN0/XdTVEOmjXOerUae5X+bv/+z/ie376hzkOTzjlxbnPLRFm6emyrFdW8rl/ubXI9rmbtex/3ry1BI7eIDWbzVSc98rKCpZlvaamrxJLKr46c8PbED9pVvllZxUHnYgGD2t9HvK7aJEoDwQNNmYtGo2xYm4kEgl+iBrP+UmqWohACygFM76jf4VAC1S6lUjTYrEYjUZDNUXCdhJ2kTRSIksKgrlBo7A3RDaTSqXQtLlBsZgsu65LPp9X5tpixr2/v69keWI2feLECWazGVevXlWpLAIE6LrOzZs32dzc5Pnnn1fSIZkIzmYzJvqcjyU0z8rbTpNcyTHtjNANnXgxTTSbJPB9NCDwfXQzxNpj22jGfJoYSViMm33O/OBb+cy/+X3s/uS2dDTPdhkcdUhvlZh1RzSvV6m8bZtIOko4HoUAnvutT6NrOmYmSjyWJb1RZFTrQBCQ2SoyHU5wxjPW33kOd+qgTwyaVw5JbxSpP3ODyx/9PN3nD1VC2OIUIpVKkUgmCG4ZXbkzh90nLhGJRrj0G59SfjT9fp/hcEgikcCyLFZWVgiHw1SrVcU+mkwm2LZNPp+nUqkoA04BMCRdTY5vtVpVfkixWIzxeMxsNk9xi8fjTCYTNeUQzyxN09QaEy+IVCp1m+EnoBgzi3JNWXPCmpKIZ2HySJNdqVTUOshkMkp6IICRSMrG4zGxWIxsNstkMqHb7SqWDKDAk5WVFW7cuKE8ueLxOP1+X/2cgEC7u7vYts2jjz7KZDJhZ2dHASn5fB7XdZVX0urqqgLMhPIv/gb9fp/Dw0MqlQorKys88cQTiik0HA4VE2l7e5uDgwPa7Ta5XI5arUYymVQAT6PRUH5Dw+GQSCRCMpkkCAJFfzZNU50jTdNUwprIFg3DUMl7vu+TTCbV51Pem0jUFindsgETQBnu3KS8nLqbGv8Xy2ju1JB98Ytf5D3veQ8ADz/8MM8995z62rPPPssjjzyiNnMnTpzg0qVLvOUtb7krr3FZy7pX6792/3On0jSND22H+SeXZ7g+hA2Nb8tqfE/eYOzD9+ZDvC391UDBP9gw+fOmzcHERUtkOVMJ86EHLdLaHHCR65T0CovSEGHDOo7DdDq97XokXwPUMGYxgVYCQeT+JiES4/GY0WikEkTlGqvr+m3po8JWEp86YTm9WIoigNViOpdlWWSyecyET23vgJuNIybNKclECn88pb7fZOpOyW+vkN2uEIlZdHZqXHtmB800CEdCtK5XCRkmRshg2ysodu3Vq1fJZrOEQiGqsxrjmcOoPyRpphj1+vhh0OM6rd0GMS+C59nYjgdhMMMJkhtxIokomfUCs8mMiKbjWzo4Dr4WkCSMHjcJ+ToFO4rpQm/QYzgcMhgMlJ9Wt9tVYSsAT33sL/iJn/kf0HyNR52112oZvmFr6X/zQt0rx2LZ/7w5awkcfZOX4zgqDrtcLiuZFrxgDvlqS37+ThcHmVwBSi9v2zY/mHJY6e3w5MjjVCLNdyccjmtVYnqMgTOgcMuLRTaHtm3Taxzwf5wK8clGm3q9wXeuZzkedugsRGyLNGxxuuZ5nmIp1Go1xTxpNptKkuI4Dul0mnA4rHT2woI4c+aMAi1EUiPvS5I5hG4tDJfRaIRpmkpLLwwIiaQVIEGkOCJVu379ugKQyuUy165do3vxkPT9a2huQHKtgDdzcMZTPNvFyiUIPB/fdXFdn5AVRjd18MAIGUz7YwgCNEMnnIiSWi9Q//LN28+fPmcpbbzrPEY4hD2e8fwffpa3/Pi344xmODObze96iCf/1R9QOrtBuJBmeNBk97PPE80m0EMGQeDTuV5j9dFt3NCMwWGb/uUaVinFtT96kmlnfuxE5iMgWq/Xo9frMfrKjPXveZBEOYNvu8SKaa7+0ZOKNSRyMTEzFraJgBHyb5H/iVQxCOaG1fF4XPnoTCYT5Vsk503o+PF4nFgsRrfbVcbRIl8TBophGIqhJO9HjLRFFilJfbPZTJliCyNKmmfXdVUKXxAExGIxTp06pYyuBcyIRqMqna3T6dDr9dQ6z2QyTKdT9V7FR0l+d6fTYXNzk2g0qgDSdrtNEASUy2X1u3VdV+CYJKgJ1VjXdQXsGIahPIHEb0k8h+RzIeDMaDRSqWrpdJput8vq6uptiWqWZVEqlQiHwzQaDWVA3+12icfjVCoV9VpkvUQikdtkffKaxB9JZIiLYLVcB2azGfF4XAF+lmXRbrfVtWtR2iG/czEC1vO8VzzJ+0aurS+ul6vxl2uNlDDohPm26AEhaXjLWtYbtV6v/uel6kcqJuuGw1/WJ5wuZvmhooGpv/TPT6dThrUav7ISYsdIMxyO+P7tNHFDA8IqFEGYlYtguJjkyhBOpGOLUpI7/S1Aejqdpt/vYxiGkpFJyEgQBIoJKvctub/JvVg8BxfvhS9OXluUzMn/Pc/D6U2JTQIa5ojM6Qq6XUfvuxxfPmQ6mTAbTzALSUaNLtc/8WWm0xm67WIVUmg6jGoDJrMJEd0kno4xjSWw9DClUkkNRjRdx88aTK0AN6VRbdbwuzbkQgQ2eO6MWVynHM+hmToT3SWWSxEPRei3uqwWVwjHosS1MPV0j36tAy5ksgU8G7TulJnj0RmPlSxewlRyudx84BKPUHh4k3e/97s5/+AFGv0WD6dOveo1+XrU3bzPLeuNU8v+581bS+Dom7Rc16XZbDIajZR/x50anNfqom8YhppOCZtCNtjnQiNy/jGJ8YB05RS1W6yGRqOhWD1HR0fs7+9TKBTIZrMUU3G+szjmi3vHzPqQyWRotVocHx+rSZps5oUdISa9mUyGer2ukqni8TjNZlPJUuTnxMRbNPuyuZX4dgEjxNRa/ggjIpVK0ev1yGazCjRKJBJ0u12q1aryyInFYvT7fW7u7bL94Dls32EymJshi/fN2toaz/3aJ6m85yyZ7RWSm3k82yVezjDzAoIAfNfFd7250bjrohvmXFo2nkEAumFgRiP09hoUL2wyrHcZNbrqHK2/8xwrj21z/RNPs/b2c2Q2izz2k9/HtD+hd6NOEPgkKllyj27yif/ttyg9sMlj/+gH0dEY1rvES2n6B02e+rU/pXBunVGzjzOcEs+mCFyPYOoqaROgDKvH4zG6rs/XxNjlqV/5GOff+05CsQg3//hphs9VVaO6eGHv9/vouk6n0yGfzytGjqSXCaNEGGbSRIuMSaRPYnou//Z9/zapm0S/A18lY1hM8RLgUJK7ZIopZqG+7ysvodFoRLPZVHR/SaXRdV2x5OR1AMp7p9vtKraQMGgKhQK2bavXJGCKAD0bGxvEYjF2d3eV35Gky02nU2zbVl5Lk8mERqNBsVgkGo0qry5ZiyLpE2ZXuVym2+2SyWQolUrYtq0M3zVNU2DQ/v6+8hiSzdqi7O/GjRtkMhlOnTrF5cuX6XQ6ysxxMpmwtbWljoUYmQMKwPE8T0kBRWrmOA6RSER5VBmGodLxxuMx2WwW0zRvA6EWwSHZBAoIJRJG2Wy9mrpbEzdhoX29EsnsnX7uxV+T9KRlLeuNVq93//O16qGExvpsxnr5pT/PruuqEAKRaW9MpzQD9xZo9ELpuq4GF8IuErNgAWaEcSQytEX/v8Va9CmJRCK3SfjFp08kZpZlqYHaohefDMVkqCfXGEkLled1A49hMCXshzC129kEruNSPAqod+p4wZiMlaacKlGPW0waQ9zAwTfBHTpkT+Sx/QDDAH8SMBuOmPaHTIZTjEwUdxLiYNyg47Yx0NVGstqt0djvE4vHsHUb1w5wmZE0CqQLJt2DLngeblQjZ0cI+waRZIxpY0Aw9Rg0W8QiCYIBTMJTzEAjmUyjmwZGOEQmncBzXDXgkmMpPlKnT5/m/vvvh5iOfl8OIibRjk/JsMC6S4ttWW+6upeAvGX/8+asJXD0TVa+79Nqtej1euTzecrl8kt+eL/RD/XXmrgJkyEIAuUlMhwOFWAAKCqzsH8EZBGJmzCJLMtSfijRaFT5qaRSKYIgoNVqqYtANBoFUDIhTdMoFosKFBgMBqoBEtaJMJQkHUpAhBs3bmCaJul0WunTZYOcy+VIpVJUq1V1LMRTRhgZ1WqVRCJBpVLh5s2banpn2zbJUyVO/thDhJMWsekFdv/d55jt9fA8j36/TyaTwTAM+l84pPPZG7QvH3Lf+7+FcCZOopyhX23zhV/9Ex77ye8juZqDwKd9rYo9tnEnU7InK6Bp2KMp8VKaB/7Oe7j/h9/Nn//L36H+7A2AuRG27VJ+8CTJ1Tz/P3tvHnRZftb3fc5y7zl3OXdf3vftt7vfXqZHGs2MNhAIQRAIOY4hAYtEIWDZJhVXKiFJRXHsqlSFJIVdGIckxq5UHBdJUbEdjB1WgYkcgcCA0IIGLTOapXt6fde7r+fes5/8cef56b7DjKZHaqm7R/ep6uqu9+27nXPu+T2/7/NdTNtCz2bINzNopExv90lZgVKppXPu/U9Su7LDzjsvM3jugP7NY77wjz+ON3b57D/6KG//8e/DrhTRk5Qv/B+/g6HppHyZ2TWfzxV7Q5q3UqmEjs61X/pjtTkXOVmxWFSggUjOhN0iMb7iKSRU1lwux5UrV3Bdl8FgQL/fV+dY5IWFQkFdG0mS4HmeMkAXUKLZbCrAyXXdU2lsshCJ91WpVML3fQaDgQJIy+UyW1tbauKRyax8KwRo0TRtBYg2m8rQWgAKofLncjn1/RoMBsrLx7ZtqtWqYuaJAb1sHIbDofJgcl1XGblblkWlUmE2m6kUNgEyRa4nMi9hDRmGwXA4BKDVailGXhiG2LatzLr39/epVqtUq1UqlQrD4ZDj42Py+fwpU2sBooS9JUyvs2fPMp1OSZLkVCJcpVIhm80yHA6pVqt0uyvPr3VzVrlmBKiTa0t8ipbLpTqWYn5frVbV/Usm9HKuBMATeasAhfez7nbi9o53vIPf+73f4y/8hb/A5z//ea5cuaJ+9+STT/JzP/dz+L5PEARcv3791O83tamHvR6U/ue1HvdqJXLg8XhMo9Fge3v7dT2/gELw5XukhH/I2inrr8jC1n2NBGiSe42kyIqkOZfL0el01KBM1jNJGpXkWgGlRLomP5PBnFtI+KxzRGikmJrBu71z1D1bybgkaOLttUcAuKn1eS7toFcsjo1DJldP2DIqzLZSgjBiPp5QshyWowmFrIVVtFgOZ9jFHMvZkpm3ZOSHlCOLcW/VLw7dCakXMX3p2BUfbZPoJlEY4k2X+IGPEel4U5dMtYRWzpPYGVw9IN8oUqyVuGhuYzgauyWTQTYgaxmYusF2WCZX+DIYJsMqx3HY3t7m/Pnz1Ot1lsslZ86cIWfk0GKN1EmZTCbYlv3AyI0ehnqQwJIHod5o186m/3m4agMcPUQ1HA7VBvjixYvfEHf/r3TDzufzp4yKZQI1mUyUQfF8PlcpVLZtc/PmTYrFIhcuXFAb7jiOlYRFNvPCHhDPHNM06fV6yghbNqfCxhAvlMVioUAkieIWkErStkzTpFarMRgMKJVKqzSxl8Ajmb7puq4MhIX5kKarRb/b7XLu3Dm1CRUw44UXXlhFjVsZzv34u0l1cHtTEgPO/dV388m//k+xWX0+8ZKRzzL8k30+deNXqO61iZchz/5/f8Llv/gu5p0RcRBiZDP40yWf/gcfYe+7HscbL0iCiOrlbW5/5iqRF5At2rz7v/ohfv2v/j0Apvs9jKxJoVUmW7BJkxR/PMeqFLDKBXLtkNgPeeaX/pB3//W/SPXiFrf+4BlKZ+oYWZM//tlfxRus6Orz610+9bO/RhTHRDOPUq6oGklhfXS7XUXTbrfbAMrQWYC+IAhUWplE1gvQmM1mFY1ePHbEN0jYXcvlUpmXy8/ESFt8iwBFsZdUMgFDBLwSSZWYP0sK23A4PGWQLcCSNOTrDfhsNlPJYoPBgCRJ1EZGGDJHR0dqSiwgicSYyvsETrGlZrOZko/JhLfX6ylZ3Gw2Ux5IjuMo2WS1WlUArDB35PvR6XSUufxwOFRJbbJpSJJE6m97mQAAIABJREFUeRsVi0XFIkzTVRrbYrFQYNvh4SHnzp2jUChwfHzM+fPnmU6n7O7uAqv7lHgnybna2trCNE1lXHv79m1msxmO41Cr1U4BRrIRkmtFTK/lXMt7kvMnf2T6JPIJuebkWhFph0zr5fqU+8j9rFfS+L9Svf/97+cTn/gEP/IjP0Kapvz0T/80v/ALv8C5c+d43/vex4c+9CF+9Ed/lDRN+fCHP6y8qTa1qYe9HrT+5/U8TqRf3W6XUqn0qu//9bye3BvX79HiVSRM6/X+SIAkYSPJOpbP55nP5yoEQnoweX6RLUtIiKznMgiRtUx6Mj8O+Z350yRzKFg2A9flnw6f5Z39NraRUa8vnoK2beNEDvFtj+40wumWSKMMB4s+ZjWLbWSZDBa4esiOWWamLZn1OzCLCNIAhiHj4YDQCzlZRuB6hEFIqqWrHU4E6DC/3oEIkvMVbCePVchi2BnO1HaoPn6GyNYp5YvofoJdKrBnNKjnK6q3rBs6lVIJx3Lw3NWxzmazp1LjhKnrOI5ipwsAJ0PVbDarGMGb2tSmNv3Pw1Yb4OghKUkQunDhwl19we5FvRaqLYvm+qZcmBdiaCuNy/PPP0+tVuPKlStqGrbuHTObzZQxsDBIdnZ2aDQaTKdTFaktho4iQxOKtjRC4oMjrCbxqREZmshj5D2us1lkwywTtPF4TK1WUwDRaDSi0WgQxzE3b95cvfdKAb+dwclVqfS6jIcjaufbZIo2y+4KQDOSlEw2A06Wk2vHtFotALrdLvl8XgFXN67eYPj84erYGiZv/9D3Uj7XRM+YZHJZittVvu3DP8jgmX2e+aU/YLrf5z3/9QeIvFVTEsw9KudbZKwsoR9w+JmrXP3Nz9B6/DyGZRJ7AVEQos09Ij+k+8WbfOJ/+jX6z+1T+xsfUAlv04M+pd0G+UaJeWfElR/6Nt76Y9+zSlz50iGf/gcfIVj4ivYux1kYP0EQnGIUCftnXSokvxcwRAyq5blkeimyK0nBk/MsaWqwmuIKKwhQDCOpdSN2MeMejUZqqirnV9d1JRMTvyTx6xHWnHxO8USSyGcxdp5MVvG/EgUvyW9BELBYLBRbSbx/4jimWq2qz2PbNoZh8Pzzz2OaJo1GA8dxlL+FAGLiyyWbA5ETiOxM2FPy+WGVOiFArYCxpmmqpva5557j7NmzCnTN5/PcuXNHpeEIo0+Oy5vf/GauX7/OcDhUxt/VapV+v6+AOFj5kNTrdXq9nqIOdzodNE1T3+FWq6W+u3IO4cvMRrkG5FoSbw/Z7AjYCCvKspxfWG3G1plhAgTLhkpAPjGdvR91t42Truv81E/91KmfXbp0Sf37gx/8IB/84Afv+fvb1KbuZz2I/c/dPs7zPE5OTjBNk/Pnz6v78r18vUwmo9iZwvoBFBNIXnMdSBLGpQBIi8VCpXJ6nqcS1cQCQJhH+XxegUdJVmOR04m9kGqQwSk46IZNzqyS9hd86Q+eorffwXRsKrpH1VwBReIJOJ1OTw1+HHQK2SpH6ZJZDTq395nPfA5e3EeLYu5EKcksIvUDknlEnNNIo4i566EZoGlQr1TVcRnOxvjJcgUevaT+jnWo7bbJJilGL8bWDGZLl4pd4+TmEZlII5fLYhsr2wO3FHFt3qXUqqFZMYXZap2u1WqKsV4ul8nn81QqFeWvl81maTQaahgm51d8OFX67KY29Trqjci+2vQ/D1dtgKOHpCT56BtdX+kmJSbT63KQ9WSNNE3pdDpKgiSMBvENksjwy5cvk8vlODg4wHVdtre3VVMjU65er8disaDdbpPNZlXsuiRgBUGgkt7EayVJEhaLhTKBFDaMeKLIZns9Qc00TarVKoVCQTVZAmYBis49Go3wShqP/SffS5rR0A2D82+tMfyZjzDvT8maGbysAQHoGRN0jaJu0wtDOp0O58+fV4bIAkaVy2WOj4/VaxYaZTI5C8MySeIEI2Ow9cQe4XjBt/y1P8+Nf/U5dE2nUHVYjOdUzreIFgGP/cC3c/tTzzI+7POFf/Jx0iTh+//hT2BVimSiiGgZsuxP+fUf//t44zm6oZOEEYaVIfZD0DQ0QydwPXbeeZknf+y9jO90SaKE2iNbXPnhd3Ptn//xKQq8yIpECjYejxU4KBt1AWpEyiWgn0To1ut1RqOROrcigZRGNYoila4m007DMNT0U15HGEYCLAkoIAlmpmlSr9cVqDOZTBQbSABHOdcCrAjoINNS13WVlxGgQByRSIksS4Cw7e1tleon7Dxh70gCRK/XYzAYMJ/PVVMqvkVi/Cz+CbZt0+v1FPAkAIjI4sRrKIoiJpMJ5XKZNE2Zz+fqehdQTEDYNE3p9/sUCgVldu26LovFgsceewzTNLl27RqPPfaYAv/e9KY38cUvfpFKpaKS3zRNo9Fo0O12FRNJmFLCkprP55ycnKj3VyqV1ERW/J1ELieAmCSriYGrHHOR34k0tV6v0+/3FSAkMgIpkbqt+x3Jc92vkmt5U5va1J+tB7H/ea3HrfsYbW9vK3bp1+P1pNZZLcJ0Fc/BdRBJgKT15DXP81SwyPpAQdJJXw4eHXh9PmHfIc0apNmUZpDjbZ0GS99jYvbQEo3dxy+Sb5bwo5BLyTkquZK6L08mE4bDoVrb1+XuJycndIYn9IYjnv+9p+B4AVmgYJLJ5kijmKJVIFcrocURxVqZ2NJJ5j4mNnoQEXg+pVyRRZrFzcQQpeSdPPlyES1OaYdl9BK0W21uexN8zyeOQnK1Ahk7T+olRI7OnaBHKVekqGeZaCGFasJj9i75fF4NgWTII0EP0gtIf7AOHMkaPp1OqdfrbzjZ0der7vdxepAAm/t9LO51bfqfh6s2wNGmXrVe6+YkptOyURUvIdnsHRwcUK/XVRLHOvgijJPj42MuXrxIpVKhVqvR6/WU1K1WqwEoc2RN05SZsrzefD5XcjZhDAiYZFmWaprWvXcEiBJT32p1NaESs+bd3V0ajQaHh4fKP6lYLHJ0dESlUiHO62x/6C04T+6gmwb+nTHZOMa6VKfxrosMP32T6W8+T+H7H8HIr0ySb/2zT6MvYyV/GwwGKqlEgDfDMBQzw3VdDj91lcffdIYkijEy5sokO4zRTJ1Fb8rOt1/hEz/z//DtH/5Bmld2KexUWfSnPPkfv5/H/8p7+eiHf55MzuLJD30PwXxJ7IeYuSzL4Yz5yYjy2QbeeE4SJ3zuF36X9/zND5AmKcHc4/q/+lPGtzpc+K7HicOYJFpJeWYnI4oXm4oZItH0s9lMRatLfK8wPmQCuu6vIDIzAWWWy6XyGhK2mgAc6x4OYjotyVpili5AlZwrkW1JUyyNqQA/8u9CoaCafEk8E6liqVRSQIZcU6PRSL1fkQRImpwwlyzLUg27fE/CMKRWqyngxrZt5eE1mUzo9Xo0m02VDCTsG4mv13VdNanyXg4ODjAMg1arRRzH9Pt95aEkrCJJQTs8PFSeUyIxFA8nkYLJ3/KY0WikpBAC8Mn3SCQK9XqdM2fOqKm3mJfv7u4qplUUReo4A4xGI2U23ul0OD4+VuexUChgGIYCFwXYFcBNjoUw0tbT0uT4h2FIoVBQMjw533L9CcAIKHmtyBHuV92txn9Tm9rUN6a+ls2Z7/vcunWLZrN51z5G93oz+Ep+SHIPFxBJmJsCKM3ncwV8aJrGaDRSTFvp93remE9XjtgvTvGXS6pujmAw5+ZgwGRapT63cCKX5zJdUhJSTePCvIKvLTmZrMJUhGkk92PxmvN9n+FwyP7+PsfTI3rzIUgqXQqZYgHLzKJjks0ZnKm1GSdzNMPAjwPyrRqL2RK3P6Dl1AjjCFKPrBnj+yFGRieOE6J5gKf5REufWq2GYxiEO6AVM2imQc7TMEOYxT6BHwMuOSeHlcmjbxU4Wzir+hfxAozjmPl8rnoQYYDBaeAIUCCc67qnUqI2tanXqgcJwLpXtel/Hq7aAEebetV6rThbXdeVsbWY8g6HQ/r9PqZp0mw22dra4urVqziOw2w2o1gsKpPjSqXCrVu36PV6VCoVms0md+7cwfM8JX1bNwGW6YxsLMvlMoVCgfF4rLxM1lkoaZoqaYpIegTEEtBoNpvRbrcJw1BJgObzufKZEfaHmBlns1lyP/Y4S2uVdqalkN0t498ckk0yVM+2mD61z4sf/zxvmaWYeyWSHY3G+x7FLNt0P/YcjUZDTfZ0XWd/f18dl3w+T6PRYDAY8Omf+w0u/TvfQiZvocUr4CZaBqRJSpzGxIuI3hdv86t/6X/mfT/zV2g+cQ4zl2Vyu0t+p8b3/2//Kdc//vmVpCxKmA/H6KZOEidESx/tpYYsV3N48ke/GyNjkslZLPpTnv7Ff70C3roTrNwKsIniiGKjzMnnbuD7Ppqm4bounuep4y2JKsI2EqaRABDCFJrP54pl5fu+YqoIs0dkbiJ3cl2X2WwGcKqJlamogDSAeoz4+Mhzyjm2LEs10AIaSOrWulxJWGnCZpEmO5fLKdnUbDY75Sshzbl8hvX0QQFqxOOgWq3SbreZTCZEUaTkamLo7TgOjuOwXC4ZDAb4vq/AVM/zViDmS+yuRqNBuVxWHmMibRP/MQFwBNitVqsK5HEch2q1qthFcn7G4zGtVkt5mU2nU8X4Ozk5OeXV0G63uXXrlmLL7e/vo2nayvPLNNnf31fHRLykCoWCAnEFQBVgTJhCAg6JX5mARjK1lvuByPh832c+n1OtVhkMBqoZ8TxPTeHX5RkvNy2/X3W3VO1NbWpT35h6rf7n5SU+Rp1OhzRNuXTp0uveDH29NoXrfkgiAZdhwTqT1rZtptOVnbSEkchaHUURcRLzr63rjKZzAjshikK+9OJ1Bh+/hpbLECY1ziQr/8JLVp5FKaZredzWBvQnfSrTDP7SU/fbMAyJ43hlZv1SGIT4Su46bZKaxeXveht3nr5KksRkdAvTT0iDCLvosF2sY490JmYEJYNg4eH2+iSWzTAboM8DyrtVvDgiFyRg6ATjKdHIpXB+CzeM6fZ7LBom4fN98rUKhUKBx5sXiP2IwNBoXdylZBXIWlmSosl2tYmlWbiuq9ZdOZ4yZBILgvXzur6+yNo4Ho9VKMaDXPeb4fKggCX3+zhIPSjv417Vpv95uGoDHG3qqy7xKBFJztHREZqmcebMGQaDgTKlFq8j2eDXajXy+bzyt5lMJmpTXalUFBtCDIFlYRX/oUajwcHBgYpJl8QpaTpk0iNmy4CSFUmKVLFYVL40Qteu1WrKFHi8nNH+wSdp7JRwb/XRP9PnzLc8AmdKaFt50oMRySJELxtoaGAZBIGPOYpot9scHx8zdCfUvv0yVU1jNp5R+eC7KDhFbv/qZ6lUKiqiXCRMIuMSmvP+87f5zb/2v/LnfvbH0U0Tq5IniWPQNAr1En/0M7+MaZq03rrH5R/4VtB1dEPn7He8Gc3QSeKYnW+7wmS/x/hOl9LZBqSQhBHzkzGDq0cAvPUvfy+FdoXhi6sEufK5Jld+4Fv50r/4Qwafu83k2UNqj58lDEJmnRF/8vMfVXIiYedIEyjME/EkEjkaoDb94v/j+75i8IgPFayahOFwqEChSqWivImEfi8eDALmiMn5ZDJRngLCcJPnNAwDx3HU7yXxL45jBVQJkCDX3ToTSX4uYKWkiS2Xy1PSNPFNsm2bra0txZoRT54wDFUKmRiKy7Uo6YQih5xOp9RqNXZ3d5WptphjZ7NZ6vU6aZoyGo3IZrM4jqNkZ0EQMJlMFIsriiKGwyFbW1vK0DsIAkqlkmJ7NRoNJpOJAsMWiwWNRoNbt24pRlmhUFA+GQLmhGHI9vY23W5XsQOn06k6rrPZjOl0qtLogiDg5OREfS8XiwWTyYRcLkcURVSrVY6OjpjP5wogE9mjAEtyX0nTlMVioSb78/mcdrutmF7w5cZErlu5buR8y33gftWmcdrUph7e8jyP4+NjMpkMu7u7dLvd1w0afSM2g7I+y5Bt3Q9JQCTTNJkFC65yjWkxomxmeNxtEhR1OkwZJEssT+foM1fZf/Yaum6Sd2ySMKFk5qgWqqs1yZ/zxckN0hhiP2QR+DRdm63EYbFYKG8jGULJ+iVs1VKpxK7p8qXBPkXDZhkuKNYLFDI2YRhTjXKYpkm+VWZW8smEAVEUY9Qc7KqNezQmSgPi0ZRc3sbZqjAbzik0qmQik2C+SiM9utMhup3Bc+e84z3vJK5V6KQzGuR4y9Zl7pRcplZA8/JZKoUSOy9CbMVKTi6egsIgl95hvV4pnU/6JFnj3mhgwKY2dbe16X8ertoAR5t61brbiVu/3ycIAra3t1Vika7rymRRGBfC0gjDkGKxqFg8vu/j+77a5AkItG7iKIyW6XRKGIZKxy+GjrLhTJJEyYjWpU2yyBcKBSaTCXEcc+fOHZWotb+/z8WLFykWi1g5m/J/+HaM3TKgk2+fJXisjlN4KULVyWKdKaOPfGJTwyzlMOwM43/5PJ1PPoemaTSbTbRzDpg6bneCoWnoXkL9PZe5/i8+pTbo0jTl83n6/T5xHNNqtTg8PKRYLHLnd7/Ib/zo/8Lut1xB1zQSA6IkpvuFW/Sevk02m2Xvu5/AG83JFm0yBRs981LSymRJmqRU9tocfPI5loM5lpPj+kc+y+//nX9O5AU8+v3v4i0//J1gwLwzJo0TIi/A2VnJ90aDIb/7U79Iea9F1s7SvXaAHqNSqNabPpFpyXRSPAAKhYICEtdT2ARskgZ7PZ1PPIviOFamzhL1Lt5VIkMTs2yZmuZyOWq1Gq7rMhgMTnnkiAxO6PrrVH4BJcVHSVg7gAKsxIPh/PnzGIah2G7CXhEgQ5JoJEWw0WiQzWYZDAaMRiMFXIiBNqwayVu3buE4Dq1WS02IZQIs01lJcRHGVxiG6ju1s7NDEASUy2V1vOW7JqCqgDby2cXXKJfL4TgO+/v7zOdzHn/8ccbjMdeuXaNQKFCv11ksFkoiJ+yqVqvF8fEx5XKZSqWC67oKYBPATRhd165d4/u+7/vY2tpiMBgo0PTcuXN0u10WiwXz+ZydnR2VvLdcLpXnhsg61yOlRV6Ypim2batzUqlUuHnz5immkQB40qgIo0muq/tVcpw2talNPRh1N/1PFEV0Oh2CIGBra0uxU+9VGtvXs17uhyTrRZwm/FHhNstII5fm6eTganzCfLqyBZhELuksIhcbFCsVPN8lDeAcNXILncPxShY9KPhEOpixxvCwRxBGDL2QYFlS60O1WlXrnGVZioXT7/cVoPJk/hzds2WODw+p55uYpgZJzMXdcziOw58ePgczn4U3Z3LUxyrmWJzMCOZLSMBLQoylTjJdkIYReSOHMYs4HB2wIGS+9ElHYwhgPJlzvlHCKGYITgJ8z+dt9XPsPnaJpbeAg4BCeeXTJwMXkfTJGiShMevn9NVAoXw+z3g8ViEPm3pw60FhPT0o7+Ne1qb/ebhqAxxt6quqJEkYDAb0ej2q1Sr1eh3DMNjf36dQKKj48eVyqTxThPkgsjOZcAmTAFYbdMuyFAggG0bZAE8mE8USKZfLCihaZ1kUCgVms5mSqskGWWRUkn7R7XZpNBpqUyt+J865BtlzZbRCBjImWpyQrVZJOi56BGGwwGjm0WKN1Es4/lefw//4LSpOedVMJD7xdg49nyFJE6I4JpvJYGRMjFhTn23dEE48XbLZrJIa2ba9MnC+2eX60UQdx8lkspq05fP4vo83dUn8iOELRzSfPL86jn5I6HpoukZk6Hz2H/6/xH7IyRdu4vfn6LrOe/7Lv8ib//33UDnfwqoUKO02uP67XyRbsOk+c0edj4XrsvjSzVe9FsRvZj3qXNg8i8VCMcWEwZPNZpUXgHgciFeWsITWjVBFZibA4stfUx4jrBRhF4VhiOM4Sh62XC45OTlR8sd1c2/HcQjDENd11esJw0f8heT6DYJApaJIRLyAJcJ0kutfTEAltS9JEgXkCJghHk2tVoutrS183+fk5IQgCFS072g0UourpNbV63Ucx1FeUIvFgk6no0y/BWDyPO9UelwURcznc+XDIEBqpVJhMBgocObo6IhGo6FkdsLykfPsuq66TvP5PIPBgGKxqBLT9vb2lAG2TGI9z+OFF15gd3eXZrOpwLTbt28rZpPIReX4TiYTlWy3nt4onkhyHQhgbJqmYjsJ+CieWUmSqPMk50CO6/0EjtZ9lza1qU092CX9z2QyodlsKiAf7l0a2+t97NeyoZR10LIsevGMmZUwd+dce+EFvO6MREspBBnCpYfvebjpEiuwwNA4H1e4lDRXzNmaQ2JAZzFkOZsRxhGxHxNMXNzAJ5/Lq6CH2WymhjnCxt3f3ydNU/b29mi321QqFXU/f8rTSMIE27AJzJXHX7lcpt5qodsOPL9P0AiJFh6kKUkUo5tZjNTAijNYvZhSsYydZpgxw2wWMNKQ5m6O0tkWtVaDqu6QpjC51cHUSjiOQ6VUpvfCPpZlsb29TblcVjJ1GUIUi0U1NJMBj3yurwQcSXqp9B0PumTtm70eFFbYg/I+7lVt+p+HqzZnalOvWq/UjIiOv9vtUi6XuXz5Mv1+H8/zlEmvbFDz+bwyV5QNtWzmJElrPZFtnTWUzWaVkbVsDCWuXQAXMb4WiY1smgU4MAwD13WVzwygEpkkXjyOY5W4JjIxQ9fRy7Z8YFJdA0PDNEy0JCFeLEn6Kf4fH5Lfq1F772XS77qI/4cHOHdsdn/sSYIoBFMnSVOK21WSKCE1NAa/8iXa7baKa5WNuMiwisUig8FA+RwJyBBFEYPBYNVYaF+Ots9kMrz4L59i7/1vw2lVmN7pUn/zWcKlT6Zgk8lnGV7v8PxvfJp0bWOcyVk8+sPfTr5dIdU14jCiuFXl4nuf4LN/7yPot13FiloHbF6p5LgJw0uM7sR3SDwSBDwqFouKoSO+N2JsLbI1md4Jc8n3fUWpl/Mo1+PLr88wDBkOhwowkhQykSdK9K9Iw+RaE68c8dORRjpJEiaTCdlsVvldeZ7HcrlksVhgGAblchlAfSZhTMn0OY5jjo+PlaF3pVJhPp8rc8zFYsHR0ZGSXgqIKDJAMdGu1WoKUAU4OTkhSRIqlQqPPvqoYu3ous54PFb/r1Qqce7cOebzufL+0TSNQqHAYrFQAJd8v2q1GpPJRCW6SeqZJN5J4lwYhoqRdPnyZXUewzDk5OSEra0tlayoaRrlcpn5fM7169cxDEN5Ns1mM3UOZIK7nvwm14vcX9an1K7rnjr30sDLsZbHiRxNmEbrhvnAfQeONhO3TW3qwam76X8uXrz4it/b+8E4ulebScM0SGoZzEWOnJsn8kLCwMdMDYa3Z0yPO5DLcL60DQ2HZV3nxVzMhaBEPPb4g+GXCN0FUZKwmC6J3CVpyaIQmDRmWZYssSxLeR9mMhkVAiHDHpFi5/P5U8beksJpmiZbW1srH8a5z+D2PkkckYl1Qh3svIVh1TF0DdvKsx0UqJQrqs9qtlrY53QqRsq8PyFXr1I8Vyd0Y/bsNm957BzZzIqN9cILL5DL5Wg0Gkpavy71k14XUFL49fcsA4pXK8uy1OBnHYDc1OnaHJc3bm36n4erNsDRpr5irTcywtjIZrOcP39eLZ7iYSITE/ENefkERVgigGIGyaIqm0GJxhamgCR/yFRG0p2KxSLj8VgxCYQ9Iglf4qcj4Mz6BlFYDtvb2wBMp1PFRorjmCSM0ZKU1NBg5WBEGqckWQ2LDFoaQpJSOlcn2M2jL0PiJCH7b+xiauch1dDDlOVsgeFkmH/2ECsxmb3Qo/PUi4rBIWkavV5PmSAPh0PVLOVyOdVY6bpOWjT5zv/hR2g+fp7ZyZBP/e1fZvL8MeF4wcf+i5+n/a2XwdC4+H1v48m//D2rBsYPme/3ae20KWRz3LhxAwDN0DHsLJlclmjhEy18rGKOcLbkS7/4B2R0U7FjYAX+CIAkUi+RC60zNmRDL6wOAQblWpLkOjkPwuARho9IyOS6E2ZLqVRS7B4xcH75NfXyiuNY+WXl83mq1aqSo0VRpEAfkTuKHHI8HqvHi0m1NC2S+FepVE7JMoXtksvlFKNsNpuphLRut6uMz33f5+bNm6p5FklXLpdjuVwqc1UBFeV7Iqk3AuT4vq+igOV9C8OrVCpRKpXo9/unmljxQJJzVSwWyeVynJycqGQ6YSeJNMyyLPr9PsvlquEvl8tomsZiscBxHADu3LmjDKqFxi8G2WfPnuXGjRsKyDMMA8/zODk54ezZs8rs3PM8er0e+XxegXPj8Zhms6lYUbK5kH+vNxzyGddNXiXhTu4nkqYXhqHyOFp/3vtVG43/pjb14NVr9T+vVPeDcXQvy0DDQCeTy+KPPEY3T0h1A922aV9osfO2c2RyNq3E4fayA+MFvYN9vrT/FNFsuUphDWL8pUcUR7StKtlshma2yrkLZ06ljgq4H8cxk8mERqNBpVLBcRySJOHWrVvKdHoZeex7Q+JMSsFx2K3l0Zcp85MJlYXF/nBAXjcolGt4ZZ2cH4EO+TRDw2hhm1kF8ERpwjByybXL+G7A/GaHSr1Mo93kbeVHKBWKTKdT6vU6W1tbStK8WCwYj8cqsKFQKLC1tXUqtAFOm5ELW3c+n6ueeH2TLJYN0t/KkHNTm3qleiNK1Tb9z8NVG+DoIan70VTIa76Sjl9KdPICEBQKBUajkdrQrfubyCRGUrh831d/+76vPE0krQlQDCJJfRKKs23bf0auFEURtVpNbaLXpWm5XE55xUiJvO7ZZ59VrJdcLkdOy5C6IakOWsaEOCWNIuITF71dwsznIEpI3lrASFL0WAMvINF09LIFYUKmZqN5IdHco/O5m+T3AxzHoVwu0+12ARTAAqg0Ktd1lTn09va2Mk3s9/v8ub//H2G3SwQLj/Zb9/j3fvsnGb14zNGfXOOT/+Ov8cwv/yEAT/zYezn4xHMkfgQpODs1Gu+8wPRP93lbP+jEAAAgAElEQVTHO97B9evXmUwmHH/uOtVL26RxglXOo6GRKeXQciaz/kyllpmmSaPRUAyxyWSizKBlIy5m58vlkjiOmc1mCqAQvx0BMMSgWCRWch0Vi8U/Y1ptGAalUkkZYkujKcCCgEbiXbRufvzypl/AklKppMAjkaI5jqOAIPHkEuBLJpzS4KZpynw+V35KlmUpsE8et729rQDKNE2V8bp4IUg8vbCfhNlUqVQ4c+YM+/v79Pt9JpOJmmIKOCrHslqtcny8MjSvVCr0+30FnkoUvYBZvu8rEE3AXUlbcxyHS5cucfPmTZIkwfd9giBQjCsB6uRn+XyeUqmkUuTEk2g+n3Pnzh12dnbI5XIqMW2dqi/XVLlcZjweK1lbo9HAcRyee+45hsMh1WpVfWdFjibnQI6/JCMK4CvJib7vU61WT6XkBUGgPLUEcJPrUc77/WYcbRqnTW3qletB7X9erR4Gj6NXKzvNYCcmUQL181tUm3WsTBbHzzL0J/S6XXovHvBsb0gc+OjLlM6ztzCLNkYph1WxcBc+cRjj7NS5YO7QMle2AsLWymazVCoVcrkcw+GQ2WxGo9FQAwVhV0vfWKlUqH7nJXR/h8lhl6Pbd/iD5CmMIGVxOMF0YwpWnlarRddaknNjMoZFsZSn9KazPF68gDVagVPirRd0priui+1YUMgSGhpe4LPwFlSckvJR3N3dVZLpTqeDba/Y6NPpVAW7lMtl2u22WqelZOAjfa0AZvL/pG+RVFYZfGwka6frK8n9vpHv4UGp+30s7nVt+p+HqzbA0aZetQTAWCwWymvllW5YsjAul0tKpRLdblcBOiJPks2bSHgENJHJi1B6ZSIj7AqJAhep0XA4VJIZ2fDJcwdBQLVaJQgCtVmWtLQgCJRE6Pbt2yu2Qsui+s4LXHrM4dZvf46svwJvzFjHeGpM8M4q+DFxnFC86XP4i5/D+Tcvk3n3GeJFRGJq6LkMmpPFiGIwNDRdR3MyJGGEWcxiFrMwCzk8PCSfz9Nut9V0SYAGke/ouk6j0VDsrcViwe7u7moKVXMonW8SLHwabz6LaWXQTYPqlW0MO0PlQpt/9kN/m0vvfxu733qFyAuY3u6SeCvJTqVZo7O8ynA4xDRNHMfhU3/rlznz9svUH9sFIA5WjIvv/O9/hI/+xD9S/lQCEJVKJarVKo7jMJvNGI/HiqoNK3BGZF7rJtmDwUCxlATEE98qKfHlEQaM+CHJ67zcyFokYBKrnqbpKQnXOgtp3TRb13VGoxHdblddU5KKJs2JyNcErBJwU4BHkThZlkWpVAJgsVhgWRb1ep0wDFXjm8lkFDtIXm86naooZPFPEtbVaDSi1+tRLpfJ5XLYtq38oMrlMtlslul0qnydzp49q+Lup9Mptm1TKBTI5/OK1TYYDPB9XwFB8r0Rls9isaDdblMul8nn8yRJwnA4VM3saDTCtm3CMGQ6ndJqtZjNZtRqNeWBJGbf8rydTofRaMRjjz3G1atXVQJdq9VSfg75fB7btrl27Rq5XI5yuawMR2ezGZZlqdQZYY1VKhV1DADluxRFEeVyWbHI0jRVpuwigV0HLAXoE180ATnvV637nW1qU5u6/3W3/c/L62FhHHX0GfvGBAuDK2ETixVDBj/m0lGeZ0sD8rrFIgwo3VrSPAg4WR4wYkgua5GrFFi6KdmswdnHH0GvZtEKWexmgUwmy2K6YHbcRz/QGM/HanBTrVbVMODw8JA0TRUgJ/f7JEkU08gwDAzLZDyfMOtNGLtzeje7pEZKOF+Sz+UpVRxqpk1/MWRiJhSrDlahQqFcIpi73One5oKzRb1e59KlSxwdHZE+n/L5/ou4/TFxEtN/VqP8jke53Vzy7vPn1aDi4OCAarVKNptle3sb13Xp9/vkcjkqlYoafB4dHak1y7IsJd2XvkICY9a9kMRKYd0DUnqDBwUceJAAk/tdD8I5eSOej03/83DVBjja1J8pSXKaz+dfUccvJQuiAEcCHsCXJy4y+RfvEWEbidxN0tbiOKZarTIajdSmTlgt668jBsECFgjNdzab4Xke2WxWmeEKS0kAgTSrs/2hd1F93yPopkkrOUPxey/xJz/xTyhFJYbDIeVPxnBzRG63wtHzt2GyYqKEFRMzSkiTlHi8RLdN4gyYjk0ymJNkDHQNNF2HFBI3oFyv0ItusVwuFYAkzBQBTAqFgnrPmUyGbreLZVl0Oh0AMnYWTdepXt7GzJjoxksR4lFKJmdhlfO85298gMc+8B2kcUK+VcauFhm/eEwaJxz/6YvKJ0qYGkaQ8szP/jbv+rs/QuAH+GOX2cmI1uPnaV88Q//WsWJxRVGkvKzElyifz6vjLedEmilAMVXWTaCn06mSEEr0/HrN53N1nUiS2nqamsjHZPGU60euIWGdCFAlZtzyemmaUiqVmE6nKulNpI/yWLnehK0mLB2ROIVhqFhR/X6fer2ugAdhMIn8TJh3ch12Oh1qtRrlcln5+IxGI7LZLKVSSaWsSKqMyBXlMwpA4rouvV4PwzDU8RZ/KTGThpV/QrVaVWCVfGey2Sy5XE4ZlIrpvDRGzWaTSqWipHnrktTj42Oq1SqTyYThcEgulyOTyTAej9V0WNhch4eHAFy/fp3t7W2KxSKZTOYUuCiAsLCCSqUSo9GI+XxOq9VSrzsajajX60oOKOw127aJokgZhYtnU6FQOCVpE8BRJIDrqWzrf9+P2kzcNrWpB6Neb//zas/xjaooijg5OVEAvpTc517+JzQSnq4NuF6akAIa8Jn0Fu+9tc1yvPLAm43HmP6Q0WyCFoXESYFlqYyx7bDbqJDL2XzhNz+F3rDIbhcpX3QwvZRZuGB2OGN01GNy0MWplcmX25zZqitpuvhSDodD9vb2lBzedV3u3LmD53lKJnb27Flc12U8HTOdDzi8dgvXD/Cu91YfspWjfLZFoZgnirL4GZ2SU2AZLMiaAZPpCCufIxdrHB4eMpvNVM9lGAb1uMjV4xtMrp0A8LZv+1bSnQJWrUDDb3D58mXG4zFHR0dqqCVybukVxFZAZPfixbnep0g4hJwf8eCUvkh6VWHYbyRrm/pmqk3/83DVBjj6JqjXQ/Nc1/E7jkOlUnnNpmld0pLNZpXZnzBCZPrveZ7ywxEfpHK5TK/Xw3VdxTqCLyegCYggi/G6lEjTNOVHo+s6tVpNSXYcx1Hg1N7eHteuXVs9vpDl8Z/8YazdChgvpaCkBoWLDS598NtxP3ZdSXXS2z7NuEBlZjKZTVam3UcuyZUGURSi6wbhaMn4C/uYz07IjiLs//wdxFGMbhoky5BwvmQyGCsJlqS9DYdDisUirutiWRaTyUQ1JrPZjGazSRRFyoxx+20XyRZtso4N+kvHxQvQMwZ2tUASxVx439vwJgu8wZzimTqFrTJJmvKH/80/pf/ikTpXIr1yXZfenWOWgxmTw/4KcHnpuT13oRhEQRCoG/twOKRQKKjN+nK5VBH1cuMXmdi6v8x6CdNjvbm2bRvLsoBVAynG2nL9SnMp7KJCoaAABTFwFlAJoFgsKiZJFEUqPUsYRZZlcenSJcIwpN/vM5vNFBtKGEVihDqbzRStXiYj0nzGcawAs3VJZLPZVBIzkUaJcfNsNlNm4gIiBkHAZDJhPp8rHyDbthUrSz6fHJft7W3FDJJzkslk1L+XyyWtVotOp6PAP5nkirmneC8JkNhut5nNZiwWC6rVqgJSRC4ZhqFKRhPQRuRzx8fH9Ho9dnd3OT4+plwuc+nSJaIootvtYhgGN27cUImJ8v7Fa6hYLNLtdnFdV4GPk8mE8XhMo9FQNP7BYMByucQ0TQqFAv1+H0DJ7xzHwfM8RqORkguuJ6iJRE8AJbk25Lq6X7VpnDa1qa9Pfb37n5fX18JKeD33oDRNGY1GDIdD6vW6kt7L717+B2BJyK+XnqVvrNaRhevSe+YOs+MBNw5MaoNVoIik1m45DrVGTUnRg7LLHcfFwOQdH3gPbhCQ74eUujrayONPy3OMjIbdcLDyFhlNY3Q8gpGnPO4kiEHWOQFOZOhi27YaMkiK7OGgw1ILSTIGWmLgPHGGWbBk700X0GIIFgGaEaLZNsl0gRaHRPmQTDHHI2YLbbnyOxTW7/b29kpuPrVwqxpn336FwF+QMXUOnnqOZ7ZraGGqGK67u7uMx2Nms5myVFgPoJB1VAYjEhgiYTAiSV8fhglbXpjJsh5OJhO1Tt3PYcaDVveb7fMgMX3u97G417Xpfx6u2gBHb/C62xtMGIZ0Oh3CMFS04aOjo7t6rMhTZKErlUrK60ZuBoVCQcWXSvKU67rYtq18fyRqG1AsE2FvSDy5SJKSJGG5XOK6Lq1WSxkcr4MX8lmiKFKsDJ6skakXQF87Ltpq6tb4jkvon+oqdpKAV3t7e+ybY8JHSwSLJXrXx2ysvFaWL/bwfuUFtCjFPNNAzxho+QykYFgmiRcyvXbCmQvn6B91sCyLo6MjJdeyLItarbZiOZXLqulotVrK/HswGPDmH/8ewoXP8OoR5b0WesbAtLKkpGiAXS0SLQP8yYIoipkf9EmjmC/8/Me4/ann1CbZdV3y+TxhGDKbzbj51PO8+Luf4/L3vYM0jkm0lBd+9VNoXqJ8d4QVJAbDy+VS+ekImCfx6IvFgslkovwJXm0xEDBJ2Die5+F5noqnlY28ABkCOjqOoyRnYigt7CABIQREEbBA5GvyHkUKJWyddrutwCqRnMn7l+cTNkyxWFSAjhiGC9tKTNlt21ZsJjFcNgyDarWqfJl831fX2brf0XqjL9+harWqjpU0oaPRiEqlooAomVgKiyefzyt2l/g0ycRTjo/neVQqFVzX5ejoiMlkQrvdpt1uk8lkFJW+3W4rEFYaYZmoihm2eD3Ise31erRaLd7ylrcoCv7169cZDoekacrJyQmPPfYYo9HoVMKeyMkAlTAznU7VtFquW0CZt/f7farVKvP5nGazqSR4URSpa1iMx0X64Ps+hUJBvbZIMu+27nUTuWmcNrWpe1/fiP7nleqruT+8ns3gcrnk+PiYXC7HhQsXTvn7yXO90vM9nekw11f/r/fiPr3r+1z7rafQdJOxXeDd9qPU63WKxSK7u7sK1OhlXF40x5i6TmluMNRdvOkSexyzMygR+SHLJCEMQrBNSsUy4cIjHiw4W22RpAm5jK3u8efPn1d+P7K+nzlzhnq9juM4dLtdtV4XCgVG5zWuZLdp9Xc4uX2AVSlSubiFDnSfPWBys4NezGFnbQxDI5dCkurkphqL8UrC/eijj3L27FlKpZKyAlh6S240lkwLAfP+mGKrypmlQzJfMaw7nQ7ZbFYNV2StOH/+vOp7xeNwPB7T7XZJ05R8Po9lWcq2oVKpUK1WlSxekmNF2ib9ing4CutK+inbtk+Zar/a+d3UG78eBABr0/98c9cGOHqDl7A/Xm2RSZKEwWDAZDL5Mzr+V4qjfaWSBVS8RkQSJEwLYQnJ+xApmWzec7mc0nwnSaJAI5EbyZ/hcAig0i0qlYqSpQhoJeCBvK9KpaLowI7jYBbtVZx9kqIZa8ckBT1cAVaz2YyTkxMuP/II84VLeLFA+p4LGKRk4pgkSqj+/pjP/s4nMBcJTtFhESyYlVPsZYARxOiWSRzGGAWLb/k//yq6bbDbm/PC3/0o9tA+lTgmZsDSfBQKBSUBymazLBYLMkWb0AtYTuYEC4/aI2cwLRO3OyGYL0m8ELvqQJqSLdhk7CzBZMHJH19VnlDyfMK8yWQymKbJ0z/3URbPd3HONjj64nVufOzzFAoFarWaioqXDbowxiQhRGRg8nmkeRVW0aslngGvuFCsA1ViHL6eWCJ+AoBK9xKWkZSkmAgQoGmaAk0ENLAsS6V4CcAiDKHZbKamg/KehBUj1HTx9JFrVYAbQMmsptMppVJJJbcVCgXK5bJi1vX7fdI0PQWS9no9isUijuNQq9UUQ0hSCOVze57HrVu3lEm1HDeR+Im5uLCgZrOZAuvW7wmVSoVCoaCMPo+Pj2m32+r7WywWTxmXe56ngCz5zL7vK+NyMf6cz+dKqijAWLvdJp/Pk6Yp3W6X5557Tpl8L5dLlaon11Eul6NWqzEejwmC4NTxN4zVZLxWqylWnrCxZHor/hGwikl2XffUuarVauqaEgnt/TLh3Gj8N7Wpe1/fiP7nlV7zq63Xer04jul0Ovi+z87OjpIk3y3o7Wmr9VgD3OMxdr5I64mLOI0SF8tn+F7zCTWgazQbaLrOsT3judIQdBstYxDPdd7+fJFFd0oBi1xjdZ/ulwLGxQaGaXL1j74Ao4Bs1eH2XkqaMckuQlq3QswgYX9/Xw0gSqUSly5dUqxaGUJkMhkuXbrE9vY2ZuUOx4MexRtForlHUsxQrlWJ3ZDl4ZicnaNQLlE708R2cmiaTkY3eCLaIZOswi9kKCeppALCfJe9y1E8Zlyr0Uwc3tQ6R+PNDV588UW2t7fVWi2sZM/zuHHjBu12m52dHTX8k6HEdDplNBqpYUgcxwoEEp8+kVX7vs9kMgFQvZSAWsJ6nk6nDIdDte5Jv3039Wpyxa/0u5f/n/VEuK/2Od4oINeD8jkelPdxr2rT/zxctQGOvgnqlZoRWZB6vR6VSuWr0vFLycZcZE0Spy1SIZEtyeZfpE2maTKfzxV1d31xFGBDNtSO4zCdrlIw9vb2lI/KerS2LMTCRhHmiJhyh2FI+swJ/FuPkfghRn4FTJCkxIuA+HMdms0mvV4P813bRB96DNc0WGoaxClamEAYoeUyDEshlqdRazTVJlmbTGnrOskyJPVj9KyBUbZJ4oRMySZTzfOO//3H+Mx/9n/DMwdqgyu+PtIUyHERYKdSqXD1I5/mWz78b5PJ2+i6RjhfEkxTZgd94jghm7NYDKZ85qd/lYvvfxvxIuDGr38WfzBXLBPxtxHWkIpWR2P/d55WDJtsNqsArN3dl4yz45h2u628AcScfL05Em8g8UESWrqASutx52IIKdeiAFIihQJOJaRFUaTo8nJtiKRQUkgk1U1+J1R4eS65FmXStw64yOeQnwu7R/x9ACXVElmmgBzrnkoCBC0WC1zXZTqd4jiOSm27deuWYu5sbW2xXC5VvK+AIvP5nH6/j6ZpXLhwQUnFjo+PCcOQdrutPttgMFDJcwKeigzR933F0CkWi+o6EMPyXC6Hpq0SzaQZFWNtee+Aenyr1VIG3XI+kiRRrCExvtZ1XV0nR0dH6nx5nkc+n8cwDJrNJvl8nlu3bjEejxWYJt9pYW05jqPYigJGyndaDLPFSHQ0GjGZTMjlckrCKkyxXC6nPJ4EOJQN5bp08vU0MPeyedtM3Da1qa9Pfb37n3tVX+l+IqxR8dQTQOP11vm4yhczx5ipzt53PQHAhe98gmxi8D2LC1zyakwmE57Wjvhk+SZhFJEmCXqqs+iMuPY7n8edzDjJt/iOxuM4dYdisbjq7eIAXdMxU4PdR8+j57ME2ZickWPqTjn54k2Oyz4X3BzpbBXW4DiOCqiQgWKz2WRnZ4ft7W213jxZMBiyIDsqYFdKJDZYpoE3nlNyHOxakWKtxFvsHfrxAsuweKx0nkfPXsKyLEajEZ7n0Ww2lez91q2V7+SwP8AG9O6YwIkZnCngLT0FMknvc/bsWeW5KamnwoiSe7dt29RqNWq1Gr7vM5/Pmc/nFItFNcw4OTmhUChQrVapVCoqrVVY13Ec4zgOAN1ul62tLbVeCYtZPAfXWUivdM2syxRfSb54t7+XodNX+xx3U18JfJIeXgZUXwuAdTe/39Rr16b/+eatDXD0Bq9X+nILzdm2bfb29k7Fh778sXd70xcgyPd9lQgl5r4i+crn80rLHoYh+Xyeg4MDZQCsaZpKkFqPIw2CgOFwSBzHapEVGZLQmQWE0XVdMTTy+bySt4j0Kbk9pfePn6L+gSfQdIOElHC0YPKxawSfOKD5yCO033WZ8l96O0mSovkhWsmGJCX1I/SXQK35wlU+CEEQrKRUzxwT9l0yrSIaQNYg9SMyJRvSlDQGzTR48r/7Qf7oL/0jbNNkMpko5oNInyR5RIwWF4sFN37pDwmTiCf+g+/GzGWJ/JDSmTp2rcj8cECawp/8g98ienHEZ//0N5R5s4AFlmWpqZcADQIAiB+Qbdu4rqv8oYQuLbKfdR+jVqtFGIZKYijXiTyfLPACVAlwMZ/PVYMo5pHiHSRAkJQAUnLdAIodIqCXgBSe5+G6LoACVQTIEVBEmEKFQkFdEyJXm8/njMfjUwae8lhhDQnTTVg00uAJICFMqTAM1SQYVtMUYXzV63V1fYoHQqlUUpsCAbfEA8F1XebzOaVSSQFO4omUzWZVIpskj8n3YN0/QqboYjAtAN1gMMC2bdWEigR0NpspnyEBEY+Pj5VZrExVbdvGNE0F6ojUUI6B+DQsl0sFwIVhqAxG9/b2aDabaJrG7du38TxPff8bjQZpmnLnzh22trYUY0hAaQGixH9LzulkMlHfHfG1knNZLpdVwpzcB8VQfB0kvJsGZkPV3tSmHvz6RvU/X8/yPI/j42Msy+LChQtf033iTFzme/3L/HH2Fi4BKZAnw9ujM7xF20HLaRwaE66VlxT0EqQpJ90TpreHJKMFmVyWrQsXuWjv0o7byg8wSRIaUR7b03GzC4pn6ug5Ey1j4oUeR7//Au5ohttb4GVz/PnLb6dccFgul+qe6ziOCmUQL0gB+s9EBd5lX+aTBZdjLSWKNTwS9vfvkKnnKW5XedzZ40xc4rxh0Gq11POYpkmr1VL3e+m1bNtesdBNk1KpRL/fV95/MlB6+umnlaeipKaWSiWefPJJ5vM5h4eHqqeQIYoML0TGJrLzXC7Hzs4OcRwrw23xdszn84rlLed8PB6rtbfRaCi52rofknh9ys/Xr/d7BYJI8q8wwL8e9Vrg02QyUTYGr/Z/ZPDzlX7/tYBcAtzdvn37qwKvXuv/3e1zrJuo3y+Qa9P/fHPXBjj6Jij5kouOP4qiUzTnu3nsa5UwSITmLBu9er1OHMeKhiumgdPplGq1qhY9QAEZnucpgGi5XDIYDKjVaso7yXVdtXCusyyE2STmjrK5j+OYUqmkmE7Hv/ssPDtib29P6dLFryUIArQrRfSMSeqvaN2JF6LlTDB1dEMjDiN4dqhiwSVGfrlc8uzf+i3e+nd+GG2rAGFCkqbIPEgDSMG0TKxqAa87pdFoqOZJ2EZCURZAaj6fQ5py41c+w+HHv8S/+9s/iaZpTG53KbarWOUCv/83/y+u/sZnVPKcsG7EcHo+nyu/HvElchyH4XCI7/vU63Wm06k6fyJv6na7ChyxLOvUBl0kTL7vK4YNoECH5XJJrVZTPxdPGjnfuVxOaf3XwQUpYZsJsCgAlQAWAtCsN0ymaar49XWDSbk+ZZInoBSgrg+5buT9rvsbiaRyXYYpvkvymuI3BCjgTlhNy+VSMWSy2awCbARsBahWq6ckV/I8uq7T6XSU31epVMI0TQaDAZlMhmazSafTUQuvnGvDMBSA2mg0SJKETqejTL3hy/eEarXKxYsX8X2fg4MDoiji0qVLillWKBSU3FQAN5GY1mo1crmcmuoK60/OoZiYi1G64zgK6Go2m+zu7tJut+n1eoo12O12laeV67qcO3eOMAw5OTlRYLGk1Mn5EZP55XLJcDhUn1/eQ7VaZTgcqnvHuteXgGzyPK/VvEmTKo373TaBr1Zi0L2pTW3q3tY3ov/5elQcx/R6PRaLBdvb2/csZetK1ORK1HzV359kXBItxUTj6d/8JH4YYG85NPe2aL9lD8vK8P3xk2zrK99IuRdGUUQ9bPBbxpfoRTPoxyzdBe5wglUq0L16BIZOYaeEkVkxqR955JFTqWrj8ZjDw0MGgwGtVoutrS213r0rd4m93Sr/bfYLLEYzpp+5Tuf5O7TevMcVfYs9vc7WzmrIID5NwvLJZDIKSAqCQA1igiBQcvowDJlOp+TzeZUk2263VU8ZhiEHBwdquFYul6nVavR6PcIwpNFosL29rbwrhRUrTO/BYECn01EAkUi0JQ1YpNSSANtoNBiNRqp3FTavZVkKcBJPQ/EjlD7n1cDQr7a+3gDFa62Pkp4swNH9KBmU7uzs3BMW192AXK/0e2GS3219reyrTf+zqZfXBjh6g5dsxrvdLtPp9M/o+F/rsXdbkjIBqxtssVhkMpmcSrNa9+4ZDoeKpityM3kO8ZwZDoe0Wi2azaYCgIRBtO5hIjK0dQBJ0zTFbJCFu16vKy8V8yW2TxiGygdpNBqt2BNjayVNUwh/SnAyw5xGZFKD8Ueeweh6tFotbt26heu6nDlzhqOTYx75Oz+Aea4MQGokEK+SytKX8JBwsiSJYpL5/8/ee0dLep91np831ftWjrduvn271WrllpBsbGxLxsIJB1gYbPAwy+wYAwbMDIcZzAxhdmcIB7N4h2UZLybt+ADHhCHYILLBNsgBW8GW3Qqdbr5Vt3IOb9o/qp+f6sotqSW1rW65nnP69A1Vdd966w3P7/t8w0i9d/F7GgwG3HLLLbRaLR599FEFnlmWRTqdZjAYcOKtLyN7dF7dVPp7DUINag9sqiZG0zRWV1eVibVclMWEURgiwnYSdoikjkj6F0Cz2cR1XYrFIq1WS+1j2e/SdMk+FlCwWCyqVBQBS2Tfi6RRZGfiRTWdKDYajZSRdaPRUMdjNBpVAIYcAwISCqtJWCRC65Z95fs+9XpdNSCSriXSKNu2DwFCYtotfjtyPEhzpmmaahCFLSVJgeKFIPHv0/KqbrerTLQFMJz2Y0qn08rPp9fr0ev1GA6HitUn0fXSGDcaDcXaknPI8zw8z8NxHGVWLqw/x3FUGplt23S7XRqNBru7u2qqKPT0eDyu2GGyOJhm/vT7fcWOmpubLEZ2dnZUepp4Hsm1RKR4Yvwtx0MYhiwsLKBpmjpO+v2+8qs6d+4ci9kSwh4AACAASURBVIuLCgzK5XLq2On1egoQFQnAdKpNsVhkcXERy7K49tprVaKhNKHy+Qpz0XGcJ230pr+WqfSlNooXq/e///2cPXuW8XhMu93m27/929X02LIs3v3ud3P8+PEved5wOORHf/RHqdVqxONx3vOe96hptdQ73/lOms2mkmD+xm/8xiVezWc1qxdGfaX6n8tZYfi4jC6XyzE/P/8V3d5YYKGFGqEWcuJ1dxDoEMUk40cxA53bR0vMa8lD1zVd1zEsk7/NbNIzDOJahlapTvULe3SrbQzTYPmOEziaSTQWZdVfIaKbNBoN2u22ukbl83kFjvi+z87Ojuodc7kcO0tj/IRO+aE9Sp/fIJFOkkglOLlyLSevu1kxjYVhJD1Dv99nb29PJe8eHByoIAXxcFxeXlY+Rv1+n3q9jmVZ6h6YSqWUt5RIy8SjSVJFs9msYo1L0p2wdGV41Ol0OH/+vGKsS08rzKZIJEK326XVaimfREmDE08+6cWeCCJJzzMcDpWE/4XC5Hi+zscnbsPlYnI929rf3yefz18SA+xS+pJLfcys/5mV1Aw4egHXNLVSGAXPFNV9JoyjaYPseDyuZFaSgiVAgWmaCpCwbVttk7BadnZ2yOVyrKysqEh3QdkdxzlkwCwLcGFmCBNlWjsugIiwYEQWV6/XlZxNWDqGYbD3t18kdedRnLUcge+j+SG1X/8MscaEMruwsECt11NRvbFYjN3dXVbeeCvOahYu7DNN1yDUaH5+h+haDi0I0Xx4+P/8K2wjQn80Mfgul8t0u10lERMatZgSzs/PEwQBsbk0L37XG+WDAU0jvpSlV2pi+jpYFktLS1QqFba3tzl+/LiaommaRu/CNqdSqUNTrlgsNmE1WTp3/PtvYumlJ+iXW9z7s39A9bNVxSKRtA9hgYgMSkyUxThZPIqmpyryva7rLC8vU61WGY/H6l8YTqJv0+m0ipMX7yd5HQEVxY9IgAHxzgrDUIE1kUhENW8CQk2DTe12+5CfljBTBHiYjtAVvyM5Zi3LIhaLKXBDppkwYQhJSoxMDiXdSxpSkeXJsSlMLGFPyXlrWRZHjx6lXC5Tq9UUkCVNi4A7Ij8T0KPf76ubtWxDs9lUvkSSxiYMPQG3JOFGAJ16va6YgrFYjFgsRr1eVw25fD7C9IlGo/R6PQXcyWcDKKAWJgDeaDRSSXaSrpjL5RR7Sxpp+WwGgwHnz59X56qAv/K+5Zoi57TjOMqnS6SNnuexuLiowFS5ZgnIJQk3MgF/qpL3UCwWL+n6+GT1cz/3cwD8+I//OLFYjJ/5mZ/BdV31L5/PX/R5H/zgBzlx4gQ/9EM/xD333MP73vc+fvInf/LQY7a2trjnnnuuiIZ7VrP6StdXsv+5XBUEAZubm5imyfpTyOi+nHV8lOORyAFtx8WyI+hovHlwI4tBavKAJ1mvfsEs0bUDzDDC3kOPcuoPP0U0k+Lao+toK2niiSjRRIKv94+zFk6AfxkIyoBP7p8iG9c0jVarxfb2NvVukwfiZVq9Jo/89WdJZ1Msv/YE17/2Du46chdJJ06r1aLf73NwcHCIOSqsY0lZlSRQSe48ODggkU5wJl7nfGabuUKRa8xFji8eU+xckYjLwEn+dxyHEydOKFn53NwcvV6ParXK1tYWw+GQQqFAJpMhkUiQyWSU/UKr1VLbo2maklJPs6akF2m1WqTTaRXUoWmPG1fLcEj8QuV30ovJPXLG6rj665lck6bZP5ezZv3PV3fNgKOrpJ7pwd/v9ymVSvi+z9ra2rOiOT+TvylMDGEPySJc9NHTBsbiPyKeKLJoE8aDLOCEqSCMDDFCFiNtQElxxJBZZD9zc3MqkSwMHzdmFolNPB5XkemFQkExPQzDIG5Heex/v4eT3/IKusMenS/uM2en6Wt9BcRInHoqlaJUKk0Aq7yFFgI6cOHarhk65b9/mNonzrJ8/TrlR7ZZSBfYvXBjBxQQYpomOzs7jEYj9bpiNh0EAcu3nCD0AobtHk4qJjueR37n43Sb7UPMFWm2isUiuq4rs+VOp0OhUFATsHa7jZ6yef0HfojFl12Lbpr0qy3iK3ne8IF/y++85qcY1icMEZEKVioVBRhVq1XV5IhUS1hC8Xic9EIe13NxR65i0QiDSKYK8h4lfUS8j0zTZG5uToFGvu/jRB0KN61hRixKnz+votpN01TsFJHUJZNJBQqIJ44ADrLfx+OxAjSkwjBkbm5OMaiEVSPsIznGp1lNIi9LJpOsra3R6XSU2SU8nhoRj8fVMS3gka7r1Go1IpEI0WhUTcWbzSabm5sALC8vK2NOYRjJ8SOG057nqYZW3rMwe0ajEWEYqs9cmFkC2gigJsw0oeUnk0my2ayiijuOQz6fZzgcsru7SzabVee5MPxEGiC+U3JeTsv8RCooqUa6rtNqtUgkEmo/yDbGYjElr2u328o/TRpykcppmsbu7q7yWJMoZQEThVWUzWbV8Smf97Sp/qXU5V5QTpudTvu7PVndd999vOMd7wDgrrvu4n3ve9+h31erVdrtNu985ztpt9t87/d+L6961asu6zbPalZfqbrS+5/nWkEQKMnT8vKyujY9H2Wic3dpjf6Cgav5LPkpkuHTy/oq+kRqpQPNczXW776VwtEFvsG8gaNBgaHhk/RtHOPxZYdhGMqTT9I3RaIsrOZer0en0+FcYwetVKZ6agsqA/T1BTB0/E/s8w+PfkTdX2TwE4vFVGADoOTk5XIZ13VJp9P0ej12a2UeSJc4PdrEzkbx98cEeZv2+ohrA1gqLhKGIZ1ORw0gRB4mMv2DgwNgMszc29tToE9hZZ52p4PDZHBycHCghqiO46h758HBgbq3yhBkY2ODSqXCsWPHVI/c7fcYJoBhm4zrYOnGIQa19KXCohYQSYZc04OW2YL6mdXzKVt9Yj3fn92s//nqrhlw9AKrJ+r4Dw4OnhNV9ZlcIEQmJjf/VCrFwcGBkiVJsposxBuNhpLKiPZcZE2ymJMboPinOI5DLBZTPkCmaeJ5HkEQqMW9ruuH4u1FgiTU40wmg+u6ihUlDKZcLke73VbJap37dqhWKniex3W3H6XT6RCJRNR0LBKJKHPE8XiMXhsRjjw0x7xgaARed0TzH8+R0G0iVY+gN6bu11UTUyqVCMNQJWQ5jkM6nVaNRDw+maJpmkZjswy6xrjVx+uNMGwLQvjcb35EafClCUulUiqlTujSzWZTMTxk0hcEAa/+le8hd+MyhmURhgGxQormxgFWLMI1d53k0T//ZxqNhtrH/X6f3d3dL6HQC8DlOA62Y/Oy//IdHH/ziwGofW6Tj/7w/6dkWsI+klQVAaHCMFTU7Wl54ng8xtdD3viBf0fx5Dq6pjGsdPjb7/lVGjsHipWi67oy1pQ0sFQqpXy2RBooE7kwDA/RxUXOJuy36bQyAaFESiAMIcdxlKFmu91WXlqFQoF0Ok0QBDSbTVqtlkpYk+NUpoLZbFZNA0ulEqVSSRmAi4xyNBqpiHo5ZgeDgfJUABRjSUxAZdoq+zUajSrWnlDiAfL5PPv7+4qxNzc3x/nz5xXrStLNZMoqfmTCMBJWnExThbnjeR7tdlttg7zGNDPRdV2azaYy73Ych2w2i+M4ihUWi8UU02k8Hqtzd2dnR/k/CHtqc3OTtbU1UpZHQusS0wbEWqdYNBN0wzijdI6dvX0Fasu1BFDT5Uupy9m8PZXG/w//8A/5wAc+cOhn+Xxe+XVJ6tx0ua7L29/+dr7ru76LVqvF2972Nk6ePPmkE7xZzeqFUM9n//Nsq9PpUC6XVRjB8wkaSekhHPOf2bUiH8aIhCYjzeOWb3kFIeCEJi/r3YT9NEuNJ+5nkYhNe9q8SBsRxK7ldeF3UPl/KjQ3dmkfdLnh/OQeXa1WlYRrOBwqoER6QRl+wcRPM5fLEYYhfzP8AoOmT6VUIj3I09ypEY/H6MYsHk3O4YSm8ouU4ajIxoVJLJJ/Yf+UyiVO55uULRc9rrNkZrkzcpS8Zh5iV4lczfM8qtUqpVJJDTYTiYQaUnqeRyTu8HFng3qrh2mZpJ0EbwpvJh3G1VBMBj/AoYGWSNpk6CW99aX4IV0JgMmVsA3w/AM2cOn7Qhs20IIxgW5hdDbRx12CaAE/cwL05y5fnPU/X701A45eICU3zna7zfz8vKKywrO/6D7TC4OwR4SJkcvl2N/fZzQaEY/HcRxHLTjFTFfAn+XlZba2tg5dQMTgWLTdIjfSNO2QZEeSwkQ+I9MUYRf1+31s26bZbCoZi0h1lFfQBcmRLFKfqMs9f/68Yr/UajU0TVPyLZkiaZ+r07+pTOREHt008LpDPvcf/hDT10imJ8yN0WjEY489xtrammJD9Xo9xabKZrMTFtCFNK9Wq0Umk6HdbrP98Dk+/XN/xEt//NvQ0cALefA9f8a4O1AAm8iXhG0li2NJf2u324dMGAMd5m5aY9TuE51LXVDAaRi2RRiCP3IVGCHglDRjwujxfZ9Wq6X2q+/7HPvWF3P8zS/CG4wgCMnfdoRb3vVaHvzFexSjRVhPAmLI9G1aCiZyqWg0yonvupPibeu43RG6rhFdzHDbv/1GPvmff59UKkUqlWI8HtNoNBSI1mw2FbghzDfx4BLTbWHliJxRmEUi0TNNk3Q6rVhRgHoePO7vFI/HFbNnNBpRqVQU40vi4GXfy7El4JOwcIRpJ5+TgErTiSrCPBKJn9wMm80m1WpVydHkXGk2m4qyLzfYubk5wjBU7D9h8khTKay3TqdzCNCybVsBu2tra4qpNBgMlFxPAD+Ao0ePsr+/T61WU39HmnBJiZNpk8gfa7UatVqNWCxGPp9neXlZLQYk8U6OH5EY1mo1BSwdO3aM2xdDbr3GIQja3LSwy8BPMWjnmU/3we3RiKdpNBpKCiD/LtV08ssxcXuyBv4tb3kLb3nLWw797F3vepeapPd6PbUgkioUCnzHd3yHkmvecMMNnD9/ftY4zeoFWVdC//NMazwes7+/j67rHDlyBMuyaDabz/r15Hr/fNVN7jybRoMdo0lAiI3Jt/VPPi1oBF+6ry8msUni8PLxUT5hbzBXLJJOpXlFf53cCV35IooVgfgDyiDL93329vYYDAaKiba7u4sfBlTNGm6jR610gB2zyR0tUtrYxrQj7ObzhBvtyd9PJtXQSYAjsUcQcNKyLBKJBGfMKqeam0QGUfLLc5TNHp+PlnjxaPWQn6KwqYQpVSgUVN8mAxXpk77o7rKb65KeK5BfLjAYjfjH1qPc0VlUAyy5h8ugRhj9cu+VwaJYREifI73FTMr2AqgwxKh+DrN1ljAEvbdHEJ8ntLOYjUfB6+MX73iOf2LW/3w11ww4usorDEMV5Z3NZrnmmmsO3WyfSyMxvcC9lBKGg7A5xOiv2WwqRoUYuokfydLSEsvLy1QqFZV2lE6n1d/u9/vKxFAWygIoJZNJZTgoNGWJ1ZbkJTHNFXBCfHDW19fZ3t5WsjpJSJMGQBoRkT11u13a7TYrKytEIhH29vbY2NhgdXVVTYz2d/fgF/cYxEOcRIz+Zp1Bp8fCwgKGYSgK8draGvV6nV6vp96jgGOVSgXLspifn1cMp1qtRr/fJ5vNcvZPP0P7oT1OvOgmamf22Tx1hvW7T7L+5jtg5LP9x/ex+/mJ2Vw+n1fAgWEYFJbn8UKf0Ase9/cJwBuOwdQZ1LtEcxcMphNRBvU28eNF9Acd9Jau5D6SjCZgnOM4zM/P02631VTuyNfdCJpG4Afomkbo+RRvO6oAHPl85ViJRqPKJFPi5zVNU5G50WiU7DWLGJpOaE4aofFgSGItr4AVeb4AAHLsC/ClAL4LvgnRaJRsNsvc3Byj0Ugdk5K4lc1mFaAhMjgpkW4JiCOA2nTzLuDiNKNNQE+RSZqmqRhiAmZOH4ci4RIAdRpckr8pAFYqlVI/azQaagoqoKs0h/I+hBkkTD1JwKtWq2xvbysJoIB5gALEhsMh6XRa+TZM+5vJJLNSqagp+rT8VFh6wljyPI9IJKKkdXIMSANdrVZZWlpC13UFAkvancgYARKJBPv7+7RLZ8mehH+6v8dqMctNKwli5ojKOKAXRMlqLVKJRUoHVbXvpsGjZ3J9vFz1TFNFbr/9dj72sY9x8uRJPv7xj3PHHYcbwU984hP87u/+Lr/2a79Gr9fj9OnTHDt27LJt76xmdSXUldT/XGrJ8En8Ei/FU+1S6nJdj57t6xjovGl4A3W9j0dAPohjcnmBiBu9eVb9DB1tRDp00HyP04kSZ+06bmfINW6aVKArs2s1fMllSeTSE5/JANVPOlGHdvJz1M/skSlV8Rwd0zZxrRHhOKQ8qGONfFKRmAqokKAJYR8LgCQSdE3TKJttDNOienqfMPCIZVNsWD43ewX1+Gg0SiqVUiygXq+nmOzSOwBKwnba70GjQ+XUFr2DFpGEg5HMY9vrKo232WwqBruwiSTAZDo4Q3ppsY+QMA143ELgSmDXXEl1pbCe4KnPUW1Yx2ydJbBzaF4fQh9tWGdgZHGcHEZ3F79wK+jPbfk/63++emsGHF3FJTp+x3Ge1Ejxy9X8XKyEwitSNTG6FZaByFQk0eL48eMq1l22ffq5YmArbAwxUpbHijynUqlQKBTUIl2YPfL/9ESo2+2qha7neepmLwtqAQN6vR5LS0tK3pVKpSiXy1SrVW688UYGgwGPPfYYkUiE48ePs7m5SafTodvtEu/HaW431WJ4YWFBpWgUCgWSySRbW1tqYRyNRllbW2NnZ4fhcKhYEJZl0W631eJWZHrOWGf304/R6XRY+oabuPM9/wrN0EGD9Td8DR/6X95DfmQo4+R4Mc2r3/99FG8+AsBn/q8P84Vf/wiDwYBet8vf/Ohv8aZf/UHMaARv7NI/aBPLJYgVUrziP34bL/6BN/DH3/zzjA86ah8LK0WAPNd1yWazKjGvfmaPhVfeMDkGdR3LjjDYbSpQZ9pIOQgCisWi8r8SBpbQuGUy1j1Txvym27GLk+mCP3I59xf3K+BwcXFReQpN6/ylkRLqt5hcAordJJMJYSmJl5U0VdlinvzXHgVTp/HgFt39hvr8ptPVpHGUlLNms6nATDGMtixLmWEK40eALmG62batgFS5oQr4Jc2qYRgq6UWkntlsVqX0iSRxmrou2yD7RNhRwujJ5ydA3MHBgTI/l3Qz2Vf9fl8ZYO/t7WFZFvl8XiWtCeAq2yZNqIBF0tAWi0WGw6GSQU7T84W91Gg0GAwGnD17VvmQ+b5P1LG5++QCq+l57GSez+1r7BxM5G7zhQx+ENDpdNkLxrj+Ok7oEhDQ63VJO5PX2dkrqVQQOd5Elvh0TczlvqaKaeul1tve9jZ+7Md+jLe97W1YlsV73/teAH7hF36B17/+9bzyla/kn/7pn3jrW9+Kruv8yI/8yJekjsxqVldzXWn9z6VUt9ulVCqRTqeflVn3k9XlXuQ/a5YWGvnguUvtnur9JEObZDjp/R5LNvm74Wn6rS7j/pDHHJvvjH0dOXty/8hms5S7NT7ofppKrEe/0eKu9E281DquWNR3Btfw0euBfBQnn8Tuw+h6l9Z2ncFqhi1M3ji4lsgQ1YPKkEHAFln4yv0j5unotsXC9StAwKDTI+Xp7A33VD8g4JMMVMUHVL4XG4dIJDLxvnKy7C31iBzVMSM6oeuTaGmUeiX194VlL+eC9KDT+1MeJ+CZ9HGyDb7vKy9HGRi5+GyaLXwClv00iQv7/ytZMyBrUmEYQhhg1B9B7+0SmnG8wi1gTc47LRgBOq7ncX5jj2PxAH/U47GDXY6uzJM0Q5SXxnPZhstYs/7n6qoZcHQV1ng8plwu4/s+S0tLOM5TGxc+F6r2s2EcyVRDpiq1Wo3hcMjW1haDwYCVlRW1cBVDP9GLC0giNzXZfqHdinfNNCNDbt6AMgns9/ssLi4qYEomK9N+K9PvTRb2gEq+SqfTbG1tqcdL6lOn01EmusIIEQmQeOJIAtz6+jr7+/vKTycIAiX5EX+ZaDTKYDBQUjiZNIn3k8iDppOfxPPm1h943cQ4ejyR8ZmxCDf+y7t48L/do6ZKr37vv6F4yxG8oYtm6Lzoh99M9/QBj/zVZ9B1nfyJZXRz8tmFQUA0l8D3fLz+GDSwU3G+5vtfz4M//2FFmxbdvaTRSUKYNEWnfvvjLL3iBtLXLkAQ0is3Ofub/0gqlVL0bDFW7na77O3toeu6AoDEXDqVSjE3N8fm5ibj0XgCkF343HRDx75gfry3t0ckEiGTyVAoFJS0S1hp5XKZdruNaZoUCgUVNS8AkQBgqVSKeDyu/LicozmWvvk2rnnDHWhA4Pn4Q5e//jfvI7o7mRjv7e3RarVUEyjASOZIkeRqgcbWAf2dujKmFgBwOipXgDT57EXaJk2eSMji8Tjtdlsdg5ZlKQ8n+bwFfBRfMAHG5JiNxWKHQCVJdXFdV6W8yWchCWw7OzuHjnmh6qfTaWV2LqbbkrAnhuZyHREpooBL0WiUWCzG/Pw85XJZgZLTRuPTgPBgMFBSjruujfHq6xxqnSGFtMdCTONXt7qTCOdKh4i9wJGVRdLZAoPhGMM0MbUeEW9MyT1CwIU0xn6XhDHGHI0JHAvPcy7dQ+B5nLhFo1F++Zd/+Ut+/u53v1t9/RM/8ROXZdtmNasrqa7U/uepynVdSqUSQRCwtrZ2SVHas3r6+qy9i23FOHh0h3FnwOKLjrNj9zniLqiBzCdTO9T7I9xqHz3QOJWpcyzosxbmsG2bLwwP8Ecubm+Ak4yiJaOYQwg6IzQPoutZyj7c7V6rerjp5CfXdRULXmRiGS1H3zlLLehC4BN3DV4yOEbsAutdACgZ2Ij34/Qxp+s65XJZ/b09o0433cBI2USzKUzHIqYlydm5Q8O8arUKoCRqMsiSPhI4NEyVe/l0XyxM6EZkxGdiG1Sd05imgWVYGOh88+AmCk8DEHa0IU19SDKwyYTP3Jz+SqwrBbyyag9hNr5IaMXQ+2WM/j6j9TeAYRNaFwar7ggMh2avhu8HZGMhbqdCd+lWIpo+gY5CH23YAELCSBqMS78uzfqfr96aAUdXUUnyRqfTYX5+XpmDPVU915P7mTZOYpAtjJ5YLEar1WI8HnPixAnm5uY4c+YMrVZLUWV7vZ5iT0iymrB/hN0AKDNnAY5ksS9mvyK3mQZcALV4nl6sl8tlZfQswJMkrYk8rtVqqVQoMf1dX19nb29vIsc6coRer6c+E2HOmKap0qpEWy4Spa2tLXq9nlqoSwJWt9slmUyytLREo9Gg0WjQ6XSUQXahUFCSJZFHxWIxIo5NEE4W9BoTdo9m6CrOVtd15m5bJ3Qnjwn9AD1isnj7NWx89CF83+dl//5b8Mce3nAiYYrmkniDMZquoWsToCaSiir/ANmvYnysaZryOxoMBsRiMRKJBPe9+/exVtKkcxkOPr9BtzHxChA5IqDYMtKsAMogOZ/PK3lhNBpl4cXHCYYuXmcEhKBrzH3NUQBF0R6Px6ytreH7Pul0mrm5OXZ2dojFYso3SlgtQRBw/f96F9d99yvRTYPz99zPQ+/9C7z+JNUtnI9y539/O1bSwYpOtqNbaqDbJrf/hzfzN9/9PmVmLt5Uvu/T7XZZfc1JvvGXvgdCMCImX/zVj/DAr/+18hgYDAbquBM/J/mdYRgK8BSvDpFcttttdW6EYUilUlHH2srKCv1+Xx37IteUJlCYYdVqVUUVdzodkskknU5HPS4ajR4yzczlciQSCWX8GYahMgQH1Pb5vq/MaMVjS7ygRqMRw+GQTCajooUF7JJ9KOezeEXJsSSpcZqmKVDptV+zyJm9Jn4Q0up7HF/OspwxaPfStLstPnrW5xtPZsino3yuBH3dYnHeJvRyBGGSzGBAImaTbD1EMa7BCJxhlYZ5izonv5L1VBr/Wc1qVldH/3Ox59dqNZrN5iVv8/NdV8ri+FL2fUCIbhis3n6CQaeH6diMx64awACUjS6WZVI9aJKYS+N6HlvjKpnRBCx5ILLDsDWkc65CKpfDT2kYeoTkegE7bjNs9agHDZqj5iE7BgFcJNFTbdMFoOfb3TnKQRvf90i5NmZMP9TzyZB12n5BwK5pdr30RpWwS2+/hXtmQGwujePYPBzpcsyMqYGiMHLFLFteq9fr0Ww2FbtfQjPOOy1OR6uEms6RIM3XmcexzQt2EuaIjybOM9TH6JUIpmWRjiawnAj/aJ7jW8a3POnnctqo8jHn7GTYBrx4vMpt7tKX9Vh4IZW83+kBt3ztjseEjS/SN+N0Gj2SiQTRcRe9f0CQWCE0LNyFl+Bv3kvW9vDt6xjaeUJ3TJBbwk2u4vX7xJwIkYPPoA2qgEZoOriLLwcr9hRb9uWpWf9zddXsk7pKyvM8zp07d1Ed/1PVc5maPZsGQiRl4iMjUfXC1olGowr0EXqs3OQzmYySxIjsR5gLchMV4+JpA+toNEqn01HggNB9xRRYKMDCMkkkEtRqNQC1IHddl2QyqYyp0+k05XKZ8XhMOp1mMBiwuLhItVqlVquxsrLCsWPHuPfeexVgIPIdXdc5evSoSswaDAYqSU5kQfF4nEwmo2Rr00wpx3GUsaOmaeTzecVIEjmbMGu6Hz9P9K23oZk66Dr+YMxjf/oplWjV6/Xol5qkjhbRLkyUvLHHoNLh6NGjnDt/Hk3XCadYW/7InaBQukaoQeAHfO6DH1WGxeIZJH4+EuPe7/cVm0WmV/65Gp1HSwyHQ+Vv1Gq11L4JgoD19XX6/b6SNMZiMSVfikQiXHvttWQyGUalNmga2sTBG83U8Wt9FWF7cHBAs9/mZT/4CoovOU7QHbH5/ntpn5ok5TmOoyLlY7EYkZuL3PT9rybwA0I/4NibX4Q+Cti791Gi+SRLd9+EaZuEfiAkJ5xMgn6tTXRuYjYuckcB1DKZDIEJb/i/vxfdtjBtC9/zuf57XsXn/+jjpdIAswAAIABJREFU6KVJIpiApeIvJAbvkvAm3mDTiV8CyEz7DQnA4nme8gnL5XKHjELF62g6wazZbGKa5iHZWqfToV6vo2kahUKBxcVFJS0VDy5N08jlcsRiMQUGaZpGu91mdXWVRCJBtVpV5tye59FsNtU5XalU1GulUil2dnYIw5B0On3I0FTOfXkPAiKr64ypk4hatHpj5W3Wb9X4V187x0q+SGG+yMfPh3jtNHulA1KpCKtBSDYbQHOPaDRGzK8RDTp0/DmCwCfmj4n1NwiC6572OvfloGrPjElnNauL19XS/0xXr9ejVCqRSCQuqyztK1FXy0L9FneBT0Q20C2DWC6FgcbJcI2Y8fjitxDL0kwNuf41L8LzPYIwYGE4R3acJQgDYvE0sWwcJxPFth3GI5cQiCVieOMAbRwwP4jQcCfM2umFvAA/04OGaXCpoE3k21ioflcGoHLfktcTj0PxiZT73uLiIq7rUsNg7DvghoReOGG1j3XVf5qmSWBofD6yR8Ue4qBza7BEgbgCqeTvGYZBLTni0Whtclx6IWfcEoN6l2IQJzBh12hTMQaEUR0sAyNi0jNqxOwYQaJLK7Km2MzT58oYn486Z3DxEVHUP0e2OOblSIVPzQ68kuvJzonp40H+f7Kvn+738vW0T+a0yb/v+/S6XTrdHo1+i4c2DjhxZJm5mI+TqeOUHsTyWoSaiZ+/DW1pjuFgpHy1sCwGw+Ek2bfyGFavDLG5yd8atTEaj+AXb3/W++LZ1qz/ubpqBhxdJWWa5vPSfDwbxpFIzPb39zly5AiGYdDv95XxnwA5wkgAVNKa53mHNOACpojnj0xlAJWiJLK26bh1y7IUyGRZFkEQqBjvXC5HpVJB13UV+Z1KpRR74/jx4+zv77O3t8f8/Dye5ylfpDNnzrCwsEAsFlNyq3a7rQAEeT5MpDuyD+XmLs1Dv99XC/y5uTk8z6PRaCjQSxgf8p4A9V5FBphKpdj50wco75VY/saTuIMR9//SPVQf2lKfg23b/NUPvZ9v/YMfQzM0dMOg+rlNPv/BjxL6AYQhD//RvVz/LV+HhoZmaAybPR74rb/lpre+gsAPeOC//yV7Hz2F7/sKoJs2FRcQSMACMUR2XVdJuOTxApz1+33i8TjZbFbtFzEZTyaTilkmUcXRaJTWH9/Pwl3XY88nCf2AcaPPY7/6DywsLJBKpej3+9z5S/+a5btvmsjZEg7Hf/y1lM9us5paJJ1OK0N027YpvPQaMHW0MMS0bQIt5Oi3v4Qj/+LFk2M5FiEYe3gjFytuq8/Asi32732U5DVFsscXaZ8/oHpq+3HDzLSFk0lMnnPhpu+PXcxCnN7ZPWXwXCwWFTgmhpX1ep1kMonjOMrrShhFQomXxk/keAK2iPxMfJ6CICCZTNLtdgmCgMXFRdVA6LpOp9NRn51I8+T5AjBJEyzHpfzNaDRKsVhUkslyuazYS7LdIkX0fZ9cLkcQBNTrE8memHJns1nFQAKUJE+uJSIFEJmcpsHbX3OCo8Ukd90cp9oacma/y7m9Bi+5NkMubnJ2v0XX1XlxMc6fnx5jWQny+TyVSoVut6sYVTcVA4LAZ9xtYNoxBh4QdtXx8XR1uanas4nbrGZ18bpa+h9ADaIqlQorKyuXdC2Z1bOrk+4ieqjxsHWAic5LxmsUg8Nm468eXsuHol8kYHLfXPYz3KQtYtiTY+lmc5nTThU7FScgJI3Bze4Cp9jHMkxe5K5yk7egXk8W+NPATxAEqi99IjAkX4v/kZT8bvr38nMZqk3fg9fCGOcck57mEmrgWDa3e2tYlql63AdS+9RTHqbmMA5DHjBqvK5bIKs56r4uA5lT3XNURgeEgYZTiBOJO5TyA8rhAN8PGYYe+jggaHiM8fA9H9Mw6Ro6CW2BfzDvxUuarGUXOJFbI5FITBjGmstI8xgTMOr00QydiG3R0oZXBHD0bIEdCeKRUJvp50wDPE/1NTwOLD7Z758IFMmaKAxDIpbJUngex2/iV7b52oUsEccljGQZ7J7CMMaM7RTjQR+rfy/+4jegaZMEW0noleCRuDem2ezSqfSIOHEW8smJmfYl1qz/+eqt2Sd1FdWzaZqe68TtmTw3DEOazSa7u7tYlkWhUFA+Js1mk9FopHxgZCEshsiSrCTyseloeblgi1+STE86nY4CKcRoGVDeSrquK6Pe6SjveDx+yIhYLt6yHWEYUq1WlSQolUrheR7nz59XUqdKpaK2PRqNUigU2NjYUOwTAb12d3cVc0hMtoV9U6vVyGQyLC8vc+7cOQWYiXGhaZosLy+r9y+Gw8K2Ojg4mPj2lEpsfej+L2GowGQhvvmph/nzb3oP19x5En8w5tG/vY9mvcF4PGZ+fp6HfuEewu6Y5btupLvf4GP/+XfZfuA0n/nFDymT52w2Sxg+bqQs+1QW2WEYKjBIfGgE/FpcXFTNc6vVUj5Dg8HgEHV6PB4r8/JYLMZgMKBQKKjHzMfTPPoTHyZ54yJGxKT6wCZa18WIRxTAd/z1d+AORxf2gY9umuS+5gibf39aRXYKkOU2B+gREyM5aWYMgBBGjR6EIYEXYMZtvLGH1x8rIGn3I6cIei7/8q/+yyQ1ztD4zC//OU4hyTWvv51xd4iVsNGmzlfTiXDyW17B3icfVbK03d1dfN9XUixJM/EIuO6dd7P+mlsZNrrc+1//gK1PPaw8roTlI0CPyLlEfid090gkQqPRIBqNks/nlXzRtm2VVDdtvjntU1Wv19F1XUnams2mSlITXzHxgzIMQ7GYJC1Ifp5OpxVgnMlk8H2fVqtFpVKhWq2qz1aAP5F5CgMrk8kov7AwDHnRNRm+6aXrlFpjvBDmUjatvssv/slDvPe7v5bNgx7pmEUhaTKXtBjWt7j/XIObbryR62+8WTXjBwdl1m9NcUt2QLvXRNOSmD5UwgzWBY+op7vWXc6aTdxmNaunrquh/6nX6zQaDXRd58iRI1eM7OuZ1JWwzZfMKEPjFm+RW7zFJ33MfJDkO/u3U9Y7WBgs+2n0KXPgu0fHiYUWm2aTeBDhzvFRckGMI7sWxWJRMXynt02273JJmqeBpWnQKRaLsbi4qMy4j3pH2fEb9EdDsn0LNF+BQcPRkNOlTbwzQzTbJJZOohkaD4cWx7yCksdFIhEikQjLzgpNw8J1R/iez2AwpFNvY4YGeqiBGeLqYPoaIRCEAe5gQKpjUxru8IngAfQQdEfjuL6IlYvhHo+zsLbEyI5gmCbh5ENiPHR5ZLzHopZ4WoDAI+BTkS02zDp2YPDy0Trmhb5G+tvnwvJ5KoBnej0AHErKlf5MUu/keRe7RjzxZ9PfTwOPX/LeL4BE0iNO+0kahoHWPItXPsXWCCLRArbpMwwtWHo5nP5zNkYmB/UtVrM2xYTBoL7DIDKHZWiAxmAwIJlM0mw06Fa3GO89jGFGCO0Y48gq5tIdX7JNF6tZ//PVXTPg6Cqp53Izfy4n+aU+dzAYsL+/TzQa5ciRIypyW4z5wjBUBtFyAwuCQHmwSByoACwCkmxubqoboyyUhYkQhqECpcRnpVarqSQuYfd4nsdwOFQMD5HGlEollaTUaDSYm5uj2WyyublJv99XPkTFYpEHH3wQgPX1dZW6NRgMCMNQJWWtr6/T7XY5d+4chUJBsZokbUNYHZZl0Wq1VBLV9va2SqTa3NwkHo+rxb54NwmAI344jUZD6eCnfaKEQdVqtVQyVyaTIeiMefjDn1Lad/GsGQ6HxONxHvl//55P/Oz/VEl2Iimb9pfK5/OKpSKvKylZ8Xhc6fGfqM0fDocMh8NDbCNhngnjJh6fGC0+8sgjVKtVisWiMoyWZD35u959m0QiEebSWVzHVa8P4A3GGJaB5/roujbR2A899vb22Nvbw7ZtlpaWSKfTxLIJDPsJl0ANDNvEH7gEQxdf16g9sIlmaJz5vU9S/fQ5PBu++S//E6Hvo4UQBhpf95++DX84xh97RHOJQ6CR1G3vfB37n3qMx/7ys3S7XZWY1u12ld+R4zi89he/mxPf+hK8kUsqW+R1v/ED/N4b/yvlhzeVLFA8gcTUvdlsqqQ2AWmFFi8Ja2J2LZ/pysqKMg4fjUYK0PV9n9FoxGOPPUYmkyGVSqHr+iHZWLPZVJ+zyC4lza3b7VKtVjk4OODcuXNKdidS1FQqheu6dLtdZYafy+UIw4l30tzcHLo+8YOQc2s4HNLpdDg6F2c1HyWTcPCDANPQyCdtusMQ1/W5YSXNdStpIpZJOhbhXa9dZaeaw7QCQu0U48CARJLtlsa40eSRcZyMOSaptXHHKWphSLZ+Di2hETr5p7zmXc4F1vPhqzSrWV0tdbX0P7FYjGPHjnHu3LkrAoCZ1aTiYYRj/sWv5wY6Lx8f5eXjr/BGTdX0wHC6EomEuv9KHWH10GOmQafzToKh5zJs9wiGLu5wTLG1QG48GZoJGKHrOpbdwbJsDD+CdgGo0gII+mPGzT5eb4zrjkkMDAzHZDUoMB+m6IdDPhY7jT6AcWdMf7fFx0YbeF0Xrz8mDHyMqEk0n8GNa4DHi//F3TTSZUyvzzp5NVSUHmb6vdwbOc9Zo4aBhk/IBtvcWV+iGMmocA3ZZxc7x6Z/djEWz7Mt8eOUlNrp13vidjzx+ye+T3lMMAWIXWxwLMCU9L6D3XPU97bYKdUxDJ0TqzkCL4Y2DIgD/cY+QXWX1tjG6pvExyN8N4IfsTAsh4arM0rlGTlzRAcV5tZvolPdwh206fUGxKwUZmeb0IrN+p9ZPWnNgKMXeD2Xk/tSnuv7vlp4SsKJsBU0TVPm1QISCdARjUZpNpsKEJG/Z1mWMsUVT5p+v6/kNgI2CJ3Xtm0FXiSTSQ4ODhQoIZ5KtVqNTqejjKuFZSHPFRNvoXFKDLuAIadPn8a2J3RP8Ybp9Xp0u11yuZwCkK6//nrOnDmjDLDDMDwk35mOGY9Go8TjcTY3N5WkaDQaqZvJ0tISg8EA13UpFArK30WiU13XVakZrVaLXC5HrVY75I0k4Fur1WJra0ulhUl62/z8PPv7++zu7pLNZslkMgoYkov4YDAgl8spmZn488h+k+mVRLULXVsADQGv0um0kivGYrFD3lX1ep3RaESxWGR5eZmdnR3q9TqWZZFOp8nlcmxubirvnTAMGQwGikUmDK7BYMAj7/sIN/7wa4nEbUI/xC11mG9GMG6+mUajQbfbpdfr4boux160NpG0PfGGblxIB7RNml/c5SPf934lVYxFoyzeds3E8TGcmJEThhgRA68/8UoK/cnvnph4ajgWb/idf8fqr/8d973nw7QvmJ0LKCqJfMfecDvj3ogwCPBHHpFUlPVX3kx740DtU5FziUxzusmQtDMBZAUMqtfrtNttbNtmZWVFRe7KYwWAs22bbDarjqfpRLdKpaKaIGGgjUYjtre3VYywNHSRSIT9/X36/T7RaJSDgwOSySSpVEoBRQJIiexUWE7SkEmamuu6ExN1kizkYlTbY4IwJB2LcON6gZ95+53cdjzJjSspgiDED0NGbsAtK3FanR6mbXH9YoxH9nrsN0vcUYjT7Hmc3m2wljVZTFssarBMh0ithmXu42dvxM9ee9Hr3pdj4jZrnGY1q8tbz0f/I8+92GLxaqkrwePoStiGq6GmwYav167j44lz2AkHHY104PDG3kl0/3FPRLnPHxjniJgOaBreyAXXw4yYROezOIZNaEI+iHPTqajqIVzXpW2OWIvpaIZB6Lm4A5dBOMbr9Bl1hvT2GlQrFXrVHo/91X2w0eOL7/1bmIvxoROrHF1d52uXbiSdSpNIJHAcR6W+OY7Dp9JnMS0TLQRvOCYyl+JMT8PsBsrH9GLyrif+XMC26f+n/aemH3MpUjMZck4nIl4KeDX9/bSsUdQNYkcxnXQnjLPp1L7BYMCg1aHfaTMMdYrRKNGIiTtu0z//Mcr753DcGtFYyGA4YLdnkm420bNHsfUYWncH38hQ6XWJBKfoGlHqIwO/CynLols+jc6fkc4X0TRm/c+snrRmwNFXQX05qNoiS6vVaspIVy6OAu4IM0iABVnsTy8wxftG/o4wDYR9FIvF6Ha7Kk1MfI5c18WyLIXEO46jJDTTEeeAugDLQlU8ggS8MgyDpaUlKpWKWmgDzM3NsbGxge/7LCwsYBgG1WqVtbU1RqORWqxrmqbMvyuViroJ9Ho92u22MgMWA+zBYKCYFOJFVK1W6fV6yvul3+8ThqEyRhSZn1A6XXeSgCaL7Hq9juu6ynxcmD2yf+UmJRIcYVolEgn6/T6NRoNkMkk6naZWq6nkM4l5BRRVV0AgkToJqCcMMPE6Gg6Hyruo0+ko+ZKUSPeCIGBubo5er0c8Hmd+fl4xUhqNxiFWWq/XA6BerytD6nw+j6ZpzM3NET5QYfe9HyNYS9CvtCj9zReZz82xsrLC8vIyiUQC13XZ2toiGHgXpGYXtkmD0PUJPB/N0ultVHn4Z+9RBpACitXP7RN6PkY0QuD6aJZBGISTfxeOY3cwwrQtNGOKeRROHnPdW1/GwSPbnP69T6iI+kN+CWMPw47guy4hIaEf0Km3FGsoHo8ThqEyfO92u0rqJz+PRqNqoifA7LSMrVQqKbAwHo+TTqdpt9uMx2M1/SoWi4rdJsdgt9tVCyJpouR8FVN8kYlGo1HW1tbY3d09dJz3+30SiQTZbJZodJLW5zgOtVpNnQeapik2nLCagiDgTGlAs+eRikUIwpDuKCDUdL71a+exLYMAjZhj0O576JpGxNJ4+Q0Fqm2XUWizOGex2+3gBQG24TEXdVlKWRC6+KMujfoB9z54mv/tHd+H0XgYP7kK5sV9GWYTt1nN6sqvr3T/c7XXC+V9PNe6GvfDzd4CmTDKttEkHlrc4M5j6Qbok/5tWoK95rTY9WqMBmO8/hBv5BGMxvhDj77mk9MT3OkfwU0OWF1dVbL17rjPKW3EyB1haDrYBoGjYesRNC9k3O7THQ/RIgZvdt5BubzPJ97zR+x/+hx7D5+ndH6Xrcxj3Lh6gvn5eRYXF1UQx3g8ZhT2GRvgjz0GtQ7hbpm5yDqddEylvgrYIv+mQaDpQbTUtDUFPH5NkJ5Ohq3T9UQ7Cwm5kX5L6mLg0/T30tdJXyUAkSQ8y3aI9YP06qLOEMZ9v9+nHTi0xybdTpNSpUks7tB3x1i1z0IwRNNDDhodHjxXZymXpNNt8dP/409JRuCnfuj1+OyTWbqGiNcCdEKtxKBdJZuw6PY6jE7tks4v8bpv/MZZ/zOrJ60ZcPQCr+d6cl+scRoOh+zt7RGNRjl69OiXnPACHBmGwXA4VEa/rVZL+bNYlqUu9qPR6ND3Is8S/5Ner6ckVgKKCAgkQIIkRsl7lgQ1kb6JJwxAt9tVQM7+/j4LCwu02+1DPxcPIjF9brVaLC5OdPTlcplIJEIul6Pdbqsb2f3336+Md6cNoMvlMoZhUCgUgEncvLBGxHtmd3cXz/MU+0NAt0ajQS6Xo1AoUCqV1E0lHo+rmHPTNBW4IbK4IAgYDoeHTIr7/T5BEKipk23bKu59b29PSf5yuZza5+KpI+9RjLtl/ycSCSWbE8Ct1WodSs8TYECSs4IgYG9vT7FJkskk/X6fTCaj5IPTTC4x+Zbtz2QyagImjDV578PhkPGZOq37ztNoNCZSLaujgMhbbrmFTCbD/Pw8tb/fI1zJEMZ0NEODMOT8/7iXzQ/+M6Zj0a1PzM1931esufF4TGOzwcfe9Vu8/L99F3Yqxqjd59Svf4Qb3v4qIokoge/T3jigcbrENW+644JsLYQQgqGLbhqsf/0tnPn9T6rjXJhDvu/z8Z/+fe7++X+NHZ14WXV2apy+5zPq2BWGlbDgBOARZo6cRyJnk4YkkUgoxpqmaSpFzTRNMpmMSuobDoeKBSbnZSaTwbIsKpXKIRN3YdPJOS2fhYBKkUiEYrFIrVZT8jlA+XHJ5zj9eGHUySRSrhHFYpEeDqd2OqQSDp3+mEzcJu6Y5OM2jZ6LhoFjRYg7Bq6vo2k6tqWxMmfhhTp7vSjr6wXMcYP7z1Z5+ZEI/cGIztAlCHUC32fYboB2oRkMPC62dLzcE7dpwHtWs5rV5anno/+Rv/tsGUdXM1PpctVX+/t/LrXip1nx00/7uLvcY3zYGWA5NmE2iQa8dLDGrb15usM+4WjSU2w095XFggyG3py8hb/LnWEYjrFcneP1DA9oO4Q6mLbFQnyOzDjCmfEB2USGN/z0dzPq9zj71/ex8Y+P0T1foVQq0el02N/fJx6PUygUmJ+fZ2U1xt66TzwfJ76UIWx52Gc9dru7yj5BemQJ65D+ftqHSAAa6fuFcSQ+q9PMoyd6Gz3xf0D1XYVC4ZDJuXw97V0kAJD0ndIfSb8j9hnyOHm+AEXTFheDwUAZWreHOs2RQYcYxaUVdlsBqaiJPmrxqceqeL0ucUej2mjz6VPbPLxZowkwhk8+eJr5hUXM3DKm66El56mefZDucES1NuCzj57jU49M0qZbr34NNrP+Z1YXrxlw9AKvp5qaXcpzp8v3fQ4ODlQ0/bTWd7oEWBCWkfwMUIlr0wwOAQaErijbK+CTyNxgcsHyPE8xbQRIKRaLtFotBWwAiqEj2yHAQrfbJZlMqt+LZCwMQ1ZWVoCJqXS5XFZeQJJmZlkW5XKZ48ePK8ZEqVTioYcewjRN5ubm2N/fV4tkAbwKhYJKdIpGo+rnYnQtC2WJZ+90OqRSKcXuEbaVACn9fl+BLoVCgXq9ju/7VCoV5TkkiVqRSIRUKkW5XFbmx3JTSqfTyihZADuRtAkANM2KEaZXJpOhVqspiaDsH/Eacl2XVCqlwJBcLodhGIqlJGCdpHLJZ5TJZGi328qjSZLZhJUkUj4BS1Kp1CGJnW3bCgzJZrPKjFtAwk9/+tOsrKyQSqXIZrM0fuWzaNdl6TbbbP35gwxrE2lhtVoFHjdHnD6GdV3H3WzxZ6/5OexUDG08kRre9/AB2duP0G+0Of+h+2hXGjz8gY9y96+8g+hcCrc3Ihh76BGTfqlFMplUEi15/SAIePh/3kt9o8T6q25hUOtw+k8+jeFrh6jMw+HwUDx9Op1Wn7M0GgDJZBLTNBVrTKSDAtBKYyIeHfPz82QyGXK5HK1WS3kZib/W6uoq1WqV0WiE53lKwibsJ0kUEvApCAIsyyKbzSqfL5ncTU/q+v2+YhBOJwcK0GWa5gVGUshP/fYeP/imG1jMxXlwq0cul+GG5Qm7ajD28YMQU9fwg5AQCNHwvBBd8/AHQ4b1Cpu1Eb/z8W3GdyQxwjG1Vp/vfdOtpGydrzl5E3pnlyBWJLQufo272PXxudRs4jarWV3+ej76n+dSVwpgMpOJvfBr1c/w1sGtnDXrmKHGDV6ReGiDAzHn8WNbQiqkv+v3+/i7Q16lzeNpAY4RIZVMcSw6z5bRwBjD0VYGw4frrBwfi5+np3lEQoNbX/MKrnn5rdgPD2h+7DTb29uHGNHVapX+Vp/+pwO0bISFpXluK16HldUVICRDTGHsCwgkoE2/31dDRqnpEBYZrAnIJCDUNHPpiXI2GcCJr+gTgSUZ1sqaRmwy5DWFkS29lABwwsJ/IrtJvpb1iu/7k3WAr9GIXUdc3ySfjuE7WUqtLrunHuKhcw3a4xFZR6dU71Jp9mi2YDUNLz6xxDWLSUYE9Os14tkiPX2B+jjOmd0m57fqbO/VcIC3fMNx2runKaydmPU/s7pozYCjr4J6ruaQYRjSarWoVqvkcjkWFhae8qIhFwBhHomEKQiCQwbZwmARlsQ0+j8dVep5nlpoCnCSzWZxXVd54cTjcUqlklp0xuNxBcAIA6LT6QATUEOkVpZl0W63qdfrinK+vb1Nt9sllUopFs7Kyopi1kxPLYIgoN1uq/0kN6iDgwMli5peNLdaLRKJBL1eD8uyaDabVCoVotGokoYJnTUMQ2WcLMCAmG7quk4mk1F+QRJpnkqllIxI5HOj0UjFusriXvydqtWqikWPRCIcHBzQbDaxbZtMJqOAGgFxxEsImJhuT4F70yCLAE2xWIxoNKoADQEaPM8jl8sp+ZnI5uRmL9sqfjviFxWJRBRdWFg3Yr4+HA4PvWeRdQn7ZpqhJulfnU4H+wsT9tfOo+fVMRWPxw8ZRssxZRgGyWSSWCxGtVqdfF7WZDvH5xuc+fwWAIVklnDoEWy0+evv+GVe89s/iBW30QydXrnJ5973V3BhnyUSCWzbVv5L8Xic3iNlPvWZMwpoBVTqoIB3krwxHo9VnL2maRSPLJF1bAa9/iHwRt6LsJumkzsk/rdcLlMul7Ftm+XlZbLZrPIFq9fr5PN5rr/+era2tlRzJnJPSQRxHEftIznnxYdJ1/UJ26tWOwQgaZpGImrxnXeuccPKPGdLXX71L07R66OAV2nAzu53+I8fuJ9YLMbX3XaCH31jgcAPyCVMgsCg3h1jGtqE4RUaVDtjohGTgy70xwH/uAFnqya5/BxfqPh879evcKzoYBo6nmERdxJowyreyitBu3gzc7kXVrPGaVaz+vLUV7r/gecGWD0bxlEQBErie6n/ZDtn9eT1QgfQ5oIEc+OnThAVkGM6Dc33fcUYHwwGdDod/NqYpXDSF4e2RyQWY1XL86auw5/ZpxhpPsRt5uMxvsE6hnn93Zw/f5777ruPjY0Ntre3yWazLC8vs7y8POlraz0+t3k/w+GQZDLJ4uIiqVRKpQtL4Ixt25P1hKFjJaMk7Ci2GVH97nSvI2sLGXxNy9emgSO5H0uarcj15TkCEgEKiJI1wXA4pNVqHUqCm1ZVTPfK8nXgDtH3PwPdMr6TopM6SXfoKU8qsWyIpYskV49TvP56Tp96kL3P/wnVVg/PHeKPRuz2AnwvpDtyceKQSMbwNZPC0hrtnk8pzNLZ86k376NRqaF1m1hBnbgd4aUvW+X7v+3r6TTKJG95E/qs/5nVRWoGHF1F9WyakeehNfDQAAAgAElEQVTSGMhCbWNjg0gkwvr6+tNGacJhEzqJPhfZmLBLBByR7RNmkFxYBb2XhbGwDmSBC49f6EVCIzeHbrdLoVCg2WzSbrcVDbJUKikzZZhIqqZ9dGKxGOVyme3tbRYXF2k2m+zs7LCyskKr1VJgSCQSUWwMYUmJZOzg4ICDg4ND4JTcpOQG3Ov1lKm1GE07jkOj0VAgied5iukkLKZut0s6nSadTnNwcHDI7NBxHFKpFLZto+u62t/iDVOtVonH4yQSCSKRCNvb2wAUCgVF5w3DkHw+r2Ld5WIuEiKJSRf2kAB/gGKECRAggIFMdSTtbjpBYvomG4vF6PV6JJNJ5ufn1WM6nYnMbGFhgXw+T7lcVsCYbdv0ej02NjbU3zZNk2QyCUzki+PxWIF/x48fV1KrbDY7aXYuJIjpus7a2pqSt4mmPJVKKUqx3Pzl/TqOo5oXibIX367RaEQ6nVYMq0++/TdJnVym1+2x+dGHsDWL3oXXlXMmm81iGAbtdpter4dt24qVJE2DmK4LODYNnMWWs3znX/4fpFfnCEP47C//GZ//7X/gtb/0DlJHilS/uM1HfuQ38VoTppJMvwT0mT6OXdfl7NmzaJrGwsIC8/PzlMtlarXaIVmanI9CDR8Oh+rYSKfTSm4oHmWGYdBqtQ69B2EN/v/svXnQJOd93/fpY3p6uue+33PfPbBYYEECBEiCh0SJIqjIlOToIGlFsuRSKZVYJcdVStkVpyp2yi6HkS3LURLHdqJKVIocSyIjy4csiWYoiSJIihJFGffuYg+89zv3fXVPd+ePwe/BLAASxy6Ia35VU8C77zszfTzd/Xu+z/f4ez9yF+8+V8DQ4L1ns7z7TJpP/IMvYMbiSqIn98AwDBkMBty3bjCbTfm9R8a8YytJPhnnWt3jl7/c5Sfel+Tu9RRO3GLo6fi6waWWx9PNObmEzg/eW+bB0wlMUyduhkRozOw1xqmzpIwp+rhOFM6J4jki64XN9e2cdK3MIVe1qm9eb5b+51bq1WzvaDTi+PgY27ZvYis839PlxV4vVtJ/SCDFS4FPz/d4eaWvF3vvsjffqt54JezxZdad+PSIF2K321V94Uf1bZquh6kbrIdpdBPmzLnjjjvY2tri5OSEy5cvc+3aNS5fvsz169epVCpcuHCBe++9l263qxaCT05O8H2fVCql5PX5fJ7QNfhiZpfRPIBZyMV5lXtim3wtc8wkF1E1snzX/Dxu9BygpHwlnx1rkmwmC6aAWrgWOwuxF4DnrtflzxEPV2EyyYKZ/F4AJ9kGTVvYJCQO/z9ioyNMQ0PvXSd2cpVo42M3MZWkV5vNZjzyyCPUnnyYa7t1dmtT8CLiMYOZb2IU1rHHV7FiHoWkQzWf5VptSHdq4dlTvOkIx29i6326hEShwUYlw0Pfdj/u1n3o8yGT5i4pLVr1P6t6Qa2Ao7d4vdqVL4moH4/HbG9v4zjOK3r/chy7AAhys5UbqEzEhf0gPjLyms1mN5n/Goah2C6apilPF3mAiT+K67qKeSPMJJGNyd9Xq1WOjo7UTfzUqVNK7ua6rkqQymazagKcz+eVGbAwdbLZLJ1Oh+3tbYIg4MqVK4oNo2katm0rJlK73ca2bcWGajQaDAYDYrGYAnyazaYy4xZqfKPRUH42juNQr9eZTqdMJhOVyCYgUb/fX5hEP7tKKjKvXC6nwCjZLlnJ0DRNMV6y2SzxeJxWq6XAPwGBBAQT4C2VSmHbtgJMRB4Fi3j12WxGv99XwJYwdkajEbPZTDG4Tp06xcnJiQIJBfyxbZvBYKD+bX19nVwux+XLlxXQGI/H1RiS1DuRPPV6PQ4PD9XD3rZt8vm8MgSXEqZSt9vFtm1OnTql9kXGYL/fV7/vdDqKZVUoFBgMBioNTMa1AEhBEFAsFhdA4Vd38TyPrcqGOndCZ5YJioxHYRSNx2PlEbacWCfb73kemq6zdu8ZPv7//jdkT5Wfvd413vc3f5B3/JXvAg3mU5+N95/n+//Fz/Kvvv9TaDyn6zcMQ5nLCx1bpGK+73NwcMDR0ZGic9dqNQXsyX1B9lskj+12WzGRBNAUOeZ4PCaVSinp42g0wjVD3nkqQ9YxKaTiAFTzFf7q99zB//SvnwDge9+zyU99953EDI1//2dH/O5jA1JJh4iIuzdSZJMWhqFTyTv0vRGP7Y2571SGrKWTCyNmHY0/r1nkHY+f+XaHUjqObUJARMIICTWTZHTCYJJDo0VseIBGRGTYzE5/H1HquRjk273itmqcVrWq21+vV/9zK4yjl1uS6OZ5HltbW+p7b7V836der7O+vv6SwNPLecmz4ZW8hIXe7XZfcntvJ2C1/JIFpGX/m2/0/lUtwCTpnfP5PICSt00mE3KjEcPBkMl8wfqWYxePx1lfX6dcLnPhwgWuX7/O4eEhjUaDz3/+80oif9ddd/HOd74TgH6/z8HBAf1+n6eeeop+OOJ6ZoBeckiWszj5NI9nT3gmPiSaRWjDiHbU5FA/4vvn9+AmHBUismxSLWCSnHuRpYmfEiz6XumRli00BGjyPE8tSi7L0GTBTeRx4s8Ui8WwIp9E2MKIBRwcHDENI6aTI6azJOPU3Yt+/ehJktNrhDcO2Y0KjM0ird0jTlpdOp0uph5hWQ5uLKI/i3Czedz5gHxSpz/oosdtzLV3oXtTMsEhYTRmr9lkHIaUsjHOVrOs22NmvSZpq49//feJdRy0mLPqf1Z1U62Ao7dBvZKLXCRB9Xodx3HIZDKvuGkC1MTaNE0mk4lKQZAmQnS+wjqSSbYAAsJeAFQiV7fbVZ8ljJ21tTWq1epNxtgiZ8rn84q1BChGkkzaZXVEZDXClojH4xweHhJFEdlsVsnKksmk8kqaTCZKalatVsnn8zz66KM3GXg7jqPkV8KqEPNtkZfJw0sMpPP5vJq8w8K7RthQlmWp1QYx6Ws0GiplS4AtAeskvU0aMUCxPrLZrPI0Eu8lWBh3ZzKZm+REqVRKgXnPl6MJ48nzPOUxJGyQ5fMsUrVCoaCOuzwsfN+nWCwquZWMgzAMSafT6LpOp9MBFgypixcvcunSJSUH3NjYuEmaeHx8zMbGBtvb25imyeHhIdPplGvXrqn0m0QioQAh0zQZDAYUi0WV5pbL5VSKyHQ6VZp1eZ+MFUCNM8dx1HEQWZ5lWQo88zyPVCpFKpVSErx2u43neSSTSTKZDI1GQxlTy1iKokiNFQFApeGYzKZ84tN/i+1vuxunmF5cfOHC2ScC7FyS0XEHQ9cJp3NyOxWChM7wuKMknoBi+wHKW0iknbLCJtdROp1Wq9uyfcsafhnbqVTqJjmpSDYNw1BpiXJOnVhExomTT8WZeM9RwH/sO8/yv/67J3ngXJG/+cPvpN2fMZ7N+bHvPEPAPn/w6DH/6X13sZazmAcRQbRgCfzFizoP7KQZeRGdSUDB1TmTC/jEXR7pVJbNvM5sHhLTAmxdI9J0NN2EKMAdX0WL2UR2lsiIgz8i/szvML34U6C/No/MVeO0qlW9NvV69D+3Ui9ne/v9PvV6nUKhoEI7lmXNt6NeT1BEFmfS6fQ3/btvxqS6FWALFv2iLAp9s/e/VL1SwGr5NZ/P6ff7L4iafzUA2etRpmmSTCZJJpOUSiXgOTBpMBgwGo0UA1+CT97xjnewsbFBo9Gg0WjQbDZ58sknuXLlCuvr69xzzz2cPXuWBx54gKk35ff1K8y8JvZxg+Fxl/2rlxj1huS3SiQrOUqFAnrcwCmkmJRs/PFzvo4SnCPncjmpTRbUxLdRehtZgF7u6+E55p2w/yUIZJlFJ2bYy6bXAEY4I1Fvc3RwxJcvnbBZcjB1naD5p8QurDP2O1j1r7M7i7j0TBMtOGSe3CKKpUnoIY4ZEmkwm0yZhAbT4TGbuRjxZJJKziFlm/hhn6j1JNl4nGkw4vpBj+F4SiEVI51yeM/FbU6VHLz2FWpGjHyxTN+PkTF8Vv3PqpZrBRy9xeuVPDA8z+P4+BjDMNjZ2VE391dTwpiIxWKMRiPFVpBJ5vJEVbyQhH0jE1S5qYvfkEymRY6mac+lPcm/C4tjMBiofZDfAQp4ETaMMJMkAU7i6LvdrkoqAxSAJDK4WCymJE/ZbJbDw0PlwSO0VWHO9Pt9tXIlsjqRGcn+GoZBoVBQfjXJZJJ0Oq3i08fjsQJUMpkMs9mMMAypVqsK+BGgwfM8BUYJc0sectlsVj3obNtWGnGRQglQUq1WcRyHvb09Rb2VMSIrJfIwlcQ4AYQECJTGb9n8/OTkBNd1KZVKNBoNZe7d7/cVyCYSPTHpFqbK8fGxSlITMKvRaABw4cIFlcw2n8/Z399XjddyZHy9Xlfm161WSz3MJQVPjqXExUsSoMjSJM1OWELdblel48Xjcba2thiPx0r+aFkWh4eHytxcgCHTNCkWi+q4dbtdBe4JW0tS/pab1GX5pud53P9T382pD10knAcQRaBpaLpOFIbA4vpSAJ6uY8RMyrkiDBZMn06no8aD4zhqhUyYaAJCatoibU9A0+FwqMavYRjKi0vANbnO5PM8z1NySZGu2batxnsnDPn6jS4/VN54FmDVaA88vHmIFTP4totVPD9gNPOJmTrjicd7zqb4l3+0RyIWQRShL2yNGHsh59bTJG2NyWxOOmFg6KChcbZkk04ETOcRs7lOwgDLCJlHBoGRYISNEc1JEYJmLtLVYi6aN0Sbj4mstDqmt7MZX2n8V7Wq21+vV//zahlHL7W98/mc4+NjAHaWpHO3kwHwZmLQvJbglixoSe/zauqVgFjwwoQu+X/pKV/q/bcL3Fp+zWYzms2mej7dDoaXJKYuA2STyUTJ9MU4Op1Ok0qlVB/UbDb5D//hPxCPx7nrrruwL1ZonZ2TdLI4mwWIoHHjiN0/fJzRSY9RrUcvdkQULEIzEhmHra0R50/fQSqVUudWemTpkwUkEuma9PWymCm9s9hyyL6JFE0WVJePr1hCiM+kvA/Am82oX83RGV9l7nv8+aUB95zfwDQjut0WrWt/Rv9kj6uHbbqjAYW0Q2Z+gmfm6A0H9AdjerMAW4dCpYprBcxnHs2Ox0Gtw/3nyljxGOW4x2jc4fJ+h3Z/Rt6NERDhJixqw4BNs4QW+eCPaXamTD2NzNm1Vf+zqptqBRy9DeqlHhzigTMYDKhWq4qFcCs3BplwSlS3GB0vG8qJz5GYTQ+Hw5t8UiRJYFmLPB6PqVQqipUkwIdlWdRqNXVDW2bHyMTVNE0ajQZhGKo4XfGmgcXDQwwmJ5PJTXRSQPkRtdttxeyJx+Ncu3ZNpZUJWDQcDlUT4LouTz/9NL7vs7a2xmg0Uqbd5XJZMVT29vYUG0WOU7FYVLGl6XRa7evh4aGSE4lUTVgtEvkpSWJRFJHJZG7ykZKHo67rFIvFm4zDAWVGWCqVaLVa6rujKFJgjbBewjDEtm1lri1+QPIQlnNbLBYVcDgYDJRxtmmaCsATAEnOuRihi/mgMFmy2axa2el2uwoQKpVKSoaXz+cViCjMMmHPFAoFstksN27cIJPJUCgUFGg0Go2UHFHG37lz55jNZjzzzDMUCgW2traYTCbquhFNvxyHbDZLqVSi2+0qbyzx9+n3+wAcHBwoxtWyTEzkfGKsDosV2OFweNPKWBAEFC9soscMwnmAN5xipRKggWboEEV0njkhu13GjMcIg5CnPv0lWod1JaUU5peAk1LiYSCpgiIHXPYvEwq6XAeO46h9EWaUXHfSaEkz1e/3lT+TyEl/4bdv8K4zWdIJk/Zgij8P+dOnm4yncxrdCZapc7qS4tx6GsvUOb8558PvWMONGxi6Rn/kg26wljH4o6dnFGyNhGWQsHSiSMPQI9K2RtyIiKKAQAuY+JAwYeCbzK0s8xCyUQPNn6OFPpGVAj1GFEsSaa/d43K14raqVb029Xr0Py/ne1/J+6Iootvt0mq1KJfLL8nEWdWt1+2YGN8q46fX66lgj9eqXgp4Ekb0SzGvXo0kEZ4Dy6QkXTibzVIul6lWq2SzWeXLOR6P6fV6fOELX6D11QnGdpq1u+/AsHVS20WcnMsdH30XmDrjKzX6/SmaGRDpYO37fOWPvszDf/BFHMdRrEJhFgqTOh6PK4sAWfSeTCZq8VjmFbZtY5qm6oWlN5LPkT5e+t7lBeBlP6V2u83JpMpsaqDFYjgpCzeZouXHONg/olvrEgxHdPoDLH1GONdo1I9oDW4wGfZ4ur44ltUUzI5OcDJFGpM+acckrusMxh7jzojBeE5nMARCNkoOWmRC6JNL58iXNxhhkfIH2IZHXO+Rs000f7Tqf1Z1U62Ao7d4vdQDazAYUKvVyGaznDlz5qa/f7WrZvAci0huupLkJWwN8c2B52LOxdx4+aHS6/UwDINms6mYSolEQrGRZMVNUsLkex3HUZN++XtZCRDmjSRjCZtJfHGWP0e+Q9gTIg0TH5xGo6GYLqJhjqKFxG06nRJFEU888YRiAS37Cq2vrytQQcAu8RKSFQthRQkl1jRNer2eMmUW5ofv+xQKBfb29pT8Sh58YqyXzWYVoJXL5ZQWu9PpsLm5yWAwUMbYAnicO3cO0zTpdDqkUil1cxdGkaRZCINKGCkCCInMS1gmmUxGsVOiaOGJ0263SSQSytRbzr9InGDx4HVdV5loi2eSrBgdHx+rNDSVsKHrjMdjdnZ2yOVyigVUq9XY2tpiMBioYy5jxrIs1tfXSaVS1Ot1dd5qtRqz2Uyl3zWbTUzT5N5772U4HFKv12k2mzSbTRKJBDs7O8rv5+LFiwwGA0WPrlarrK2tMZlM6Ha7tNttBUpKgybHV0A+MVkU9pz8W+PxPUIvADT8yQzDMtEtEw0N0Cie3yQMAvzxDIDTD92LWXaZHC6S88R43jAMBcYKlVyMskXKJw2eXBvCOlvW+gPqs6TRXE5DBBSwJO/ZyFn8wP1V3LjOv/jiEfdsupRSJn9+rc3PfeY/AvBvvrrHj3zoNO+/UMabh4xnc9IJUzGM5oH3rMwtZL8T8sXjFEftE/7Se3LEDJ0QjQCN7hRydkgYaoRhRGeq8fVDjXzWxJm2qSZDxhEkTBNjPkYLpgTOBn71fRC7WbJyO1fcVo3TqlZ1++v16n9e7b3hxd7neR5HR0dYlsXp06e/JfeJ28lgejNvw9uhXoq1JWmsr7Ux/DerWq2m/CUvX77M3t4e9Xqdp+pP80RtlycuP0ykz3FLeSrvOk353AaJUpr4Vg6n0aW312TaHaLrGvlUhrA3pV6vK/BGAj3i8TiZTIZisah6SbFxkJ5HGPHybwKawXMJdOK/Kb2ozIPktazA6NV38a7/Plq7g56/QEE/4PK1fZ488hjYJRrNfWJGCj04Im7MSTs2pgHtVp9ub8JR57njlHFsQs3ATlfQNAPH8rFjEb2Jx3g6w0okSTtxtst5OhMPQ3NJlip4WsRg7BE72mUUs0haPqdiGmV7QhRpq/5nVTfVCjh6i5cAEs8v3/cV5fnUqVNqgn47v1cmvtKAyYRTIjEBxUQSSZqg9dPplHg8rnTQciO2LEsZ0wkzJ4oi9e/L3kqSppVIJFRa1mAwUIbEspIi4IZQUUVTLqwJSeeq1+tKJiXHUJhD4m0DsLa2hmEY7O3t8cd//MdKsmXbNrVajUQiQaVSYTKZqG2WxDTZtn6/rzx3crkc6XSaer2uAIiNjQ3FTJFkq3a7rUAXYXdkMhn1+a1WC9d11aR+OBziOI4yKq5UKkrGt5xKl06naTQanJycsLW1RS6XU6aVIgMTI0HTNHFdV7HNxJtIjtlsNiOZTKrzKis5xWKR8+fP0+/3VXJapVJhf3+fer1OtVpF13XlNSRR8PF4nHK5DCyAx+vXrxOLxdje3qZQKNButxVbSwC44XDI4eEh6XSaarWqfAzEM6ndbpNOpzl16hTb29vU63W63S6u6yoQRfb5qaeeIpVKUa1WVRLbfD5nb2+PZ555hmw2y8WLF9nc3GRvb0+BaYeHh1iWpYAoYftIykYQBGq1y7IsJTkUA3gxanzi17/Ixvvv5OLHv40ojAjnAbppgA4iVdMNA9+fMvfmaLrG+oPnefLXvqgYa5KsJ3RtAYtkjAMKiJVGabn5EcaelDDvRC4pQKnv++qzBajNJTQ+9ckHiJsajmXw8fetc9Kd8kufvcI//q3HCMJFUsh63uHff+2AzaJLazBjMPF48HwF3VgwoAJgMgs56Mz4B79TI0qu8/n9kM89foMffHCD77svS8qKsM2Q2thkOA2J6QH/18MdHtsfY+gRqbjOz318jVIqxnxuo+kxIjQGiR2Gxjras/cTYVsFQfCiEdhy//tmlP3n16tpnD73uc/xe7/3e/zCL/zCC3736U9/ml//9V/HNE1++qd/mg9/+MOv6LNXtaq3Qr1e/Q/cOuMoiiIlm19bW1NMqNe63kxStVV9a+r1HhMiF9vZ2WFra4t+v8/R0RHvr9X4w/FTXO3uUb9yQP3pAy7/1pd5+OQIDj0o2WTW8sRsi3gshulYhGaRU6kKGxsbijG/HNwzm804OjpSLKJ0Ok25XFYMbOlFRW4mfelyzyTzAc/zVHiMyPplvqNpGv3WEfUv/0sGowHeeAL+VXaPBux1DGKhhmW10IBBt0WjPaHZGGEZIT4xpt6UcAZzFhP5ShrclEO2eo7eJMCyt8jns9hBj+OjXeZzjWeOWpxaKzCMYnQnE2LFMnbuDhJ2nKcHHbSTS8Tx2KkWuWfzNBjWqv9Z1QtqBRy9zUp0wr1ej0qloib0L1a3uuImII7cLMRDB56LvRyPx4p9IKa/tm2rhklYKHKj0nVdgS0in8lkMsqYWUARMVSWxC65kYtu3fM8stmsSu0SwEUkOyIBE2mWMKVEIiWRoMnkIqby6OiIcrmMaZpqgt1sNplMJqTT6ZvSt8S0WibPEncvk+t0Oq0MLzVtkSwiaWCiwx4MBsTjcdLptKLPzudzyuUysViMer0OLLyZhFWl67qKedd1nfX1dTqdjtJcz2YzBSQZhsFgMGB/fx/LslSqV7vdZmNjQ63+iPRrPB4r6Zlt24pWnE6nFdNHEutyuRzj8ViBEsKKEqmipNsJ20zYSJJMl8vlqFartFotxuOx0sOLPG0ymXB4eIimaeocS4x8uVy+STonvkmS6ifA0fHxMVtbW4otI2lz4u9TKpWIxWL0ej0lU9N1nVKphK7r7O/vK3bb9evXlZH4smdCo9Gg0+nQ6/XwPI9KpaLkY7LK1Wq1lG5egFj52fd9YqbJb//V/40v/N1fw7RjfN8//xnOfPRdC7Of5evR1MFbpK35w5kCnmTMyXUqoKyMBwFQ5bwtS+3ECF2YR8slAKSUgEvphME//s/v5/13Vah3Jzz8VJNk3GDizankXIIwJOua/Nh37NAbTfntPzngn//MByim4yRtk2QixpN7XdC0BWAUajyy22M9GyfpxPj0oxpDLYP9rBfYOBbja40Uld467841mGoJvIRDLunTDnNs3GOwcQ9cuXKFce1pAm9KfzBjPpixsV5FCzwM/TnW1LIEUwwuXy0lv9/v86lPfUr5dv3cz/0c/+yf/TPVsFarVf7hP/yHL3p//ft//+/z8MMPc9ddd73gd41Gg1/91V/lN3/zN5nNZvzoj/4oH/zgB2/Jq2NVq3or1Ley/7mV902nU46OjnBdlzNnzrymUqU3Yr3eQMWq3li1fB0ahkEulyOVSrG9vc12bZsb9X1m2z5//JFr3Oif8Hu/8u/wD69CY0qvcQRJMHNZXDeOGZ8zN4dqETiVSpFMJtViWCaTUd+jaRq9Xk+lHQOUSiWq1SqFQoFCoaD+XuYRuq6TSCTI5/OKYSQ+Vd6oC9d+F2N0SHMU8VRTx2vUOWwNaTcb6IZJf+xh+xHhyCCghNbfZzYaEo4GxM2I2dzAi3wSGngxsH3IOlAupbHSG3hYOI5GqVQik8lQq1lozpQ1fUSmmOLczhn8aY9RlKSwfWGxUBlGMJ9y+eljfveREx7YhB956B1oRKv+Z1UvqBVw9Bav5eZnNBpxcnJCKpV62c3IrdCFRaIkAJJMQgUsAV4gX1o2xhZgpF6vMx6PFWIvk2gBCyzLUswfQf2XTZpFHrZ8IxMmkgAj4vEj0jYx751MJuzv71OtVsnlcsRiMZrNJrPZTCWgnZycKEnbeDxmNBopEz1hcPT7fYbDIbZtE0WR2t5UKsVoNMLzPPL5PNlsFl3X6fV6ZLNZXNfl+PiY+XxOPp/HcRwFJolBdK/Xo1qtMh6PleeMsIK63S6ZTEalewHKCPzixYsqdtiyLLa3txXjZzKZKNZSp9OhWq1SrVZpNps0Gg02NzeJooharYZpmlQqFTqdjpKdFQoFZYYs0q7NzU3lrSRJcSKhG41GtNttSqWSMhIXAGVra0v5XhmGQbfbVQ/tKFoYjgsw1+v12N7exvM8nnnmGUqlEpZl0el0lHxP0zQ2NjYIgoAzZ87w1a9+VfkeyRiMoojd3V0FBjmOozyXPM+j0+lQLpfJZDK4rsulS5cYjUY4jqMah9lspryJRM4oBur5fJ6dnR3a7bYyMZexEwSBirMVtlu/31cMoUQioWRmcn3HZqB5c774936DnQ/fi27qcgEDGpphoJsmrUsH7H3+UXhWOiZMOxkTcn0ITVu0+bPZTCUKysq3mGa/3Cb/gXMF/tFPvZftUpJ6d0zGsfix7zj1rIF1jCiEMIyIIuiPfT563zrvPF1grZCkM5rTn3jc5ca5eCpPe+hxpTYhjCBpm/SmEf/z5/b40qUW8XicUj7LX/72NT50JoemB+yPajzWK3A2OcKY92mELl888ukNh4ppmM9mqPV8NvMxEraBrgExBytVUs2hlKTMiQfVq61f+7VfA+DBBx/k53/+5/nABz6gAO5vdlzvv/9+HnroIX7jN37jBb979NFHede73qUA6e3tbS5duqSijFe1qrdLvZ79z6t5ryxUTWorEaUAACAASURBVKdT1tfXFcD/ra6VTGxRq+Pwxi3pnxOJBGtra4vQkZpFzw34S3/rJ/B+ZswTv/d1dv/gEYaNPuF0jpVOspmtKkl+v99XffGy/YFlWSocJ5lMLhJsn2VPDwYDms3mTb1SsVikUqlQKpVIpVIqcVkWyHVdx5w2SNW/hBUN6Ew0Hn96j6d3a1w76tEejAn8CZlEnOPWBN1yse0a7mRE4M2YBzCdRUQhRJpP0rAwYgkm4zEpJyTh2JjOJjE3S6FQoNdrM6w9jVkbMxtMKeVKxJPbOOaUYa/NVIujpasqXRrgxtVrXDpczIMCHRw7hmZaq/5nVS+oFXD0NihJmQrDkK2trZeNvN7Kqo8AKcIEEsaBgDmWZSm5mPy/sHri8bgyZRagaFlDLGwh+Q5hLokBr3yOABSDwUD5G4nXSiKRoNvtqr/TdZ1+v8/29jYA169fp91u0+v1FBXVsiza7fZN7I/BYKAkYY1GQ/nviLmePJxGo5F6KAnVUwCseDzO5uameigVCgV0XadSqSgJW6fTUbHusqohUjNZ2Uin08rLKYoi0um0AlocxyGXy6l0iPl8zu7urpIpiSwwn88r8EjkUrIPruty+vRpjo6OqNfrKlZdAA/HcdTfVioVKpUKrVaLra0tZrMZh4eHrK2tqahj13WVRFHOZ7vdpt/vK9NC+b0YL4s8DRYyua2tLVqtljJbDsOQ3d1dzpw5Q6FQoFarAbC5uUmv1+Pg4ECBd47jMJlM2NzcVLTbTCajGGJXr15Vx0ukhSLp6/V6PPPMM6RSKRqNBvV6XY1F8acS9pEwrgC63a7ybwqCgF6vp5oUOa+xWEyNeTHblnMkxuPT6VQ1NiLvBOg+cchv/5Vf5Hv++U+j6RrRPOTwj6+w/8UnmLQGPPIv/5DJYKQe/AKUirxMJKAC+ArLT2jZ8v3LiYCWZTEajZTU7fmViBt89u/9J9x/toBtGfjzkKk3pzvysGIaoGNbOoahgaaz1xhgWwbd0ZzzGxm6Iw9/HrKWS2BZBru7Y/6P3z+kO3fp9vpkHIOpr6FbC5bW8fERP/X+JB+7U8cPPHTd4Gx6wtVunX/6JR3biuFkYvT7bXWN5PN5Ij9B5Hq4OYtcNk0UBUR2iSD/wlWtW70/LpesRi77IMj5/MxnPsOv/Mqv3PT3n/rUp/jYxz7GV7/61Rf9vOFweBOTwnVdFfu7qlW93er16n9eaY1GI8WgPX369NuedbMCbRa1Og7fvGTBOB6PL2wdxgV+u/91prEEH/ixh/juj32U/c8/ypNfeRSvPebw8JBcLsfGxgbValXJ/yVpWXqjTqeDpmm0Wi3VE5mmSaFQUL2r9I1iTaBpGslkkkKhwObmJmtra6Qdm+T138QYnxCEM3brMz795V2u1fsMxjMShokd1+n2dHqjEaZukkuZNPsB42kbM9KpDQcw98g6cWKGTWQXCdHRwxFEAU6xRLa6ATw79xrVSet9miOfQtomZY0Yzwzq1iYTw2XmBeihT7vdJpVKLQy+Exlc1+HjFzf4lf/2B9BjOuGq/1nVi9QKOHoT1SulTkdRxHA4ZDgcsr6+/qqSOG6VcTSdTpXXidwURG4lN2vf9+l0OgwGAwVkyPeKsbMATmK0nUgklCG0JHQNBgNs21YUSgFoBDiS+G/x2CkWi0pCpes6yWSSs2fPsru7S6/Xw/d9xSgRJohIr2zbpt1u0+l0lGRO5FqwWL0Yj8cKGAuCgOFwqNLJJCFMGDWdTkf5/2SzWZXw1uv1SCaTxONxOp0Ok8kE27YpFAoKlBO5mIA/8/mcCxcucO3aNTzPw3VdxVYR9o8kv507d0755wggISs5R0dHGIZBoVBQrCjZxna7rcAd319Eu6+vryuJVa1Wo1AoKFlfqVRiNBrR7/cVq0hkdsIeExCuWCwyHA7VNonReD6fV7JG3/c5Ojri/PnzVCoVLMtiOBwq2Vc+nyeTydzkNyTgzHA4VJK+ZdNpAZRmsxkHBwfKYygMQ46Pjzk8PMS2bcrlsvLgEm+pyWRyk7m0eGVJ5GuhUFD7I2NbpHnLEs5cLodt20rWaJrmczKvdFo1OaPRSK1Mi2eYAKnHf/AUn/ng3yZ/YYNerc3e1y4rwDJuxDCSSWUuLy/HcW4yOAcUW275OpT/F6N6oXLLd4tn2XJC2+/89x/lg3dVANA0iD2bjvbn11uEIfztX/1T3nehzMc/eBpdi0g7MaZewP/ybx/jx7/rDj50TxXXttkqLuJ7z6+l+Ot/4Qz/6PN9esMJR60h69Uyf+2hNR66+wJEIfMgYOoHjCYLCV2lmGU9o5FOp7ASCyloLjdW/lJCf5/YYG3phEGXyC4yrzxAFL95te1W74vPLzmuL8aA+MQnPsEnPvGJV/R5yWSS0WikfpYkwlWt6s1cb7b+5+W+NwgCarUanufhOI5aRHm96u0OWK3qzVnCDnqvfRfnnS32pw2m7QGGM8f8gffQ+Y4OX/jCF3jiiSfodrvs7u5ydHREPp9XINK5c+eYTCb4vq/Y6dL39no99V8BOaTvlt5RPDS73S5XrlxB13XSw0sUrQnVrMNXHr/C16+PqfV8nLhFtegSS5fQNI9syifjunRGHjNvjpEsMBm1GU/6BHOfjGtg6DqD8QRX72FlNvD8+bMLeTaTxjUy2pD96xPceJyTMGIwmkGkETNN5sEQP+4TsxIknMWxyufzFItFHn30UaZTj3d/20P8nZ98CCMbMV/1P6v6BrUCjt6iNR6POT4+JhaLKXPlV1q3uuImZmfLXkdiEieMCTFCtm1bMUwklSsWiykz6FgsdlN6k7AyRK72fA10r9dTSWGDwYBsNku73Vax6yIp6nQ6jEYjyuUyFy5coF6v0+l0FPggzAvxexEvl/F4rIChdDqtWEcCGrTbbfVQWZY/iWmwxMyLhEzTNHaeTeISAGUymeA4jpLCJRIJ5cMEC/8iMQYXym25XKbdbtNut1lbW6NWqymAScyVxYvJ8zxu3LihwDcBxyQRLZfLKWCvXC4TBIFKDcvlciqhTdLixEBaJHTiRRUEAZ1ORx17kUj1+30FCtVqNbUvpmmSTqcV3VdkYQKgnDp1Sh0fYRQJoBMEAYeHh+zv79PtdplOpwowHI/HSu53cnJyE3giTUKr1aJer1MsFhWLRsAg2e79/X3lCyXgTqlUUmNPrhvHcdQ4KJfL5PN55XEl3lqS7gcLzXehUABQpoPLUrJut6uOqwBBAmwK0CT7MffmHHz5EoCSvc1mM2X2KJp9AeGWwVW5vpaTD2XMy3VmmqZ6OAtLanl7xffo/EaaD16s3nRv0DWNmKFTTNv84WMn/Kuv7PKbX97lRm3AL/zUezF0jYkX8D/+lXfzX/6TL3PnepqP3p8lCOGkO+N6bcha3iWv93ii3UbTND5xv8tfuCfJ1A/QtIh80mLiBUy8gLgVRwNMw+Td65DPhtS8PpqbIR6PqwjuyWTC1tYWxsYG3su8x92OWk6rux31zne+k1/8xV9UhvXXrl3j/Pnzt+WzV7WqN0O9Efqfl1P9fp96vU6hUGBtbY2Dg4NX/Z23s1Ysl1W9Wcs0TYrJLFk7ydSeMs1PlQflD/3QD/GBD3yAr3zlKzz99NPKyuLq1atcv36d9fV1dnZ22NjYUAuiwiDa2NhQFhSj0YjBYKCuE+mjZE4iabPhtItfb3I40Pijr9/gD68uFtRcIBb38KIMXhhH02xMS6M7rNPt9Rl70B21Md0MhYSNHfmYwGAyIYg00lZEZ9RhPo9IpVLY4ZCkPqQ7mTMc+YxGY7KOSyIRx7bjxEyw0wmieY9MaJErnsHJrxOGIdeuXaPf73P+/Hl++Id/mNK7373qf1b1TWsFHL3FSuLGfd9nc3NTeZO82rrVBkLYQyJ3ERaDsGcGg4GKfNd1XfmppNNpJUETA2xJRpPPETaN3ODls8UIO5FIcHBwoG7qwiqSxLLLly8ThiGu67KxsUG/31fsI2HhiBmxrEAcHx+Tz+dVjPoyuCSgQb/fV/8maRDCVpLEtFgsRqlUotFokM1mueOOO/B9n/39fbU/4/GYtbU1BoPBYkK7xNaybZtcLsfR0ZGSNbmuq7ygptMp2WxWmUUHQaAkbJJ25jiOSouT5CsBmHK5nJJdiSeTGAkOh0NyuRzZbFY1vZIeoeu6eq+Aa8IAK5VKSo529uxZtdIqOvFKpUIsFrspJS+ZTKJpGsfHx4ol1O12FZB4/fr1m0ysy+Uy9XqdWq2mtlkMtcMwpNFoKNCn1+up75JEv3Q6zWQyod1uq+0RY+1isUgikcBxHCWtbD8LXAirTq43SelJp9NqxWoymVAoFAiCQCXhCVtH0zQlZRyNRoqJJB5JQRCQzWaVz5YYpAtYKedeGH6lUolCoUCn01GA5Wg0wvcX9GRh68l2Sfqd+CYJ6LsM1IpWXxqGZRnpshH2ct13prAw6tYWbCN1XwH+99+9xC/+2yeJIji7luJTP/FuTF1H0yFpx/jIvev8xEfOUc0nCKPFvSjnmsQMCKOQdMLAjeuMvYhvuzNLEEGkGcyDAH8eEjMNimmHWMzECxcGkOczQ0zDZyc7YM/K42zcqTzFRF75ckpkprejxHTzVg1wf/mXf5nt7W0+8pGP8OM//uP86I/+KFEU8bM/+7NK3rmqVb2V643W/3yjms/nKtVtZ2fndY06fyPWrRiTr+qtWa/0eSsMpHg8rhY3h8Mhuq7z/d///bRaLf7sz/6M3d1d1ZPVajUODg5wHIezZ89y8eJFUqmU8g+V+YnrugqMXgaMJOl5Op0uGEr1K4SzLP3hlK8Op8/tC9DqwnG3geuOSSUTVOJ9ZkFEpwN9HxIJ2CjaOGZAozFkNg9p9yGTNjjpDxn7PoEWW8xpukd0fZ/+xCOfsDhVyXHHRpbjfsB6zmavMaOajhOFQzJmkrD+KEe9DsnCtgpmee9738t99933so7tqv95e9fqafUWqSiKlDlxqVRSwIvnvRzs+MXrVlfcZFIuxtgy2Re/m52dHTKZjHLqt21byZnOnz9PrVZTptnC7hBARBLYJF1Nbt7z+Vz5ETUaDWU6vOx/pGmaApSKxSKmadJoNJjNZqyvr9NoNBTN3fd9XNdVx1d8i8TLCFDx4rKfctzj8TjxeFzpoUXylMlkKBaLaJpGtVplY2ND7Wc8HqfValGr1RQYcP78eXzfp9lsEo/HOXv2LLBI3BIWESwm9wJSCZAjbKj19XUODw+VzEgMwcXnR+R2Yros3jUCXgiAI4kHnU6H9fV1isUirVaLfD6vQD6RJSYSCcbjMblcjmazSbfbVeNhOFykWojHFKBu7stMlkQiwXw+JwgCDg4OCMOQYrGo0vfK5bL6XNFrS4mEzHEcOp0OxWJRyfHEV0mOz3LyRTqdVgbUYpgtxucihTNNUyWqlUol+v0+hmFQLpdVmp6MVcuyyGazSo4p511AOmHZSZKdAKQCkp49e1YBeGJOvRz5Kuw8YXiJlA1Qmn1JphPTbl3XabVaqgEQEAhQlOvla1mAMAFQhQ0oJal3y+8DuO90HkPXeP6t5KQ74T13VoCngIh7T+exLQNN1yCKiIgwDZ3/+gcukoib6JqGpmvETI0711IYpsHf/cR5zB+5wB9f7TGahegazzL7wAugO5jz6MGEmRZn6Md4/9kY49BG8zXcdIqLmRGHzwJ1qVRK3QteyT3udpQc91c6eXzwwQd58MEH1c8/+ZM/qf7/k5/8JJ/85Cdvy/atalVv9Hqj9j8vtp3dbpdWq0W5XH5RJtTrDZispGqLWh2HRb3e4/FWt0F6VsuysG2bdDrNYDAgFovxnd/5nfR6Pa5evcrR0ZGyephOp1y5coUnnniCcrnM3XffzcbGxkJ69uy9RXo0YVlPJhPlJ1oul7nzzjuJ7w+ZpNf4wmOHuIkYhfiM1gyMGJTdBCNtsYg5n425XPOYLm/3FAbtGqEdw5tHEEDCAlOPiOsGmFOiYEzYj/B1AycWktJsqjmHdMrl6fqMeLKMVVwnb/mMRscctaeEWoe8a5NMNomiLVzX5e677+Z973vfqv9Z1cuqFXD0FqjJZMLx8bEyVRS2gNStRMre6kNDQBVBk/f39xUbIp/Pc+3aNSUDsixLIfvJZFKBGwLGiJeLTGzFC0hYKiKlicViyiNoMBgolo4AVxJPv729jW3b7O3tMRwOOXXqlGJ3CNVUUuDm87kCJQ4PD3EcR0mghK0TBIECSkQGJVHzuq4rU+5SqYTv+ziOw+bmJsfHx4oxJBIq0zRxHEeleYn/TDabJRaLcXJyokAUoWROJhPy+TzD4fAmdpd4CgnAIJP80WjEfD4nnU4riZMwVETitb6+rqRw8nlyvLvdLsViEd/3qdVqih0lTBhZ8RGzO2FDpVIparUa1WpVybQGgwGXL18mnU6TTqfxfV8lu5mmqY6NjMdGo0EQBGq19uTkhOl0yng8xrIsNjc3FRgoLBoB+8QvS1hXrusqsG352qnValy/fl3J9+LxOKlUCt/3VfN/1113qTEHC8aOUJolVQNQK1ICrsFCi23btvJLEv28GIALOCZMrkQiQRiGHB0dMRqNiMfjakXN933lleT7vvLosm1b+U7JNSQgqgA9/X4f27YViCWSTKEQy3iQn6fTqRrLspovQOOy6XYlm+Avf/gsE29OwjIVeFTrTgjCiDCMlNSvO/IIo2iRZLbUkKQSFhNvThBGOHETXYtIOhZJ2yQC5hF85J4Cf743ZTaPcOMaGjoTL+DvfOYqjx2M+ch963z4Yh7biDOYzUi5Nm4iRhQFKj0xmUySTCZf9n3tdjbTMkaef99e1apW9dL1Ru5/lsvzPI6OjrAs60W3U77z1dbtBDre7GDBqlb1/FoGkCzLIpPJMBgM1CLt9vY2jUaDdrutLBlkUe/hhx9G0zTW19d54IEHVO8qvpbLzOt+v8+NGzd48pGvU+58ASv0+dp/fJyDZkgg2SEhOG4cN1leWD4QkrDGTJdwbk2H8QgGQ5+Wt2ApxYCAAOwAE42sG6NUNDHiGXrdNm6kkUonIAS3eje6m6c2HjHptei0u7R6U6LII5tYw7F1pprGnXfeyd133002m33Zx3LV/7y9awUcvYlLpD7fLLr19Vo1UTHhz5pAd7tder0emUxGRWeKybVMRJPJJI1GA8/zFPtDkq6EcbHczNm2fZNBNKDMn2Wy2+v1FPgiP08mE+644w42NjZ4/PHHabVaVKtVZrOZ8voZj8eKdipxnP1+X000c7kcQRBQr9dVjOdwOCSfz3Pq1Clu3LhBu91W3jHFYpF6va7YIjLZl3j2o6Mjjo+PVRT7xsYGly5dIpVKKe8ZAdYGgwHpdFoZ8SUSCRKJBO12G1hQ31utlgKrBFAQk+ZarabM/UQ+NRwO2djYoNfr0e12b6L4lkoler2eApOq1SrXr19X7LGdnR0VeQ8Lf4n5fE6lUlFJb8lkkuFwSL1eJ51OM5vN2N3dZWdnh9lspoAbSRAbDAaKsaRpGpVKhWQyyWQyUeCQgGVnzpxRyTmdTkeBMKZpMhgMFCtLPKJEJjgejzk6OlKA4DJrrVwuKxaZGHPncjm1GiXSS5HzZbNZDMPg5OSEIAgUs0oARWFLASrBLwgCBYyKZ5d4f8m2+L5PMplUptpi4iyyQmEazedzBUQJs65er6vjJzK4ZrOpQC45nwIuyffL75YlHs9PSxP54XLJe6XWCw5+EHHYGpNPxckn42galDIJZn7Av/nasTpuz/Tj9MZz7MxzzUMUgR+E6LpGFIGugWEaxGOgsWAmmRoLCVrV5uf+wOc9WxHebMYfPnLI+UqMv/4954kbMPFn5C2LUkJnHs1xph5t/Tx2PE7s2Sby9bpXyrFdNU6rWtXLrzdD/wOLSVar1aLb7bK2tobrut/0vSvAZFWreu1KACQJ28lkMsqf03Vd8vk8m5ubDIdDTk5OFNMfFguWn/3sZ0mn02xtbXHHHXdQrVZVcAlAuVxeBPO0rnP08MM8/ESd33xs8Ywvu5AHxj40ujNSxoJpTjxBNq1R0iKuNMAG3AT0RzB89nYQPfvSQhiOYTyLAI/RYQ/0IWbuFNvlBE42SRTPYvsjYoMn0fWIeTQnn4D+2GfS7zGfWgRambsuXKC6tsapU6e+1adB1ar/efPVCjh6E1YURfR6PRqNBsVikbW1tW/YIN3KqtmtrrgJM+jGjRuk02lOnTqljKLFJFhYC+LDImwbmShLUziZTBTLQuQwkjA1nU6ZzWYUi0UGgwHtdlt5HQlgIuwaz/Mol8skk0kODw/p9/tq0ixaZ3mf+O4EQaBAGXlAiPGyABGmaVKtVsnn80qqJB5CktQgjB/f9xV41Gg0gIU8S9d1qtWFkXCr1VISOZmgG4ahvGrEPHoymZDL5Ugmk1QqFTU2hB1Tq9UUCNRsNplOpzf5SAmzZz6fc3BwQLVaVSBPs9lUTCjXdUkkEsqbSpLpBGAQ8E4kV71ej1gsphhSQumV1LZkMkmv11NAj+u6zGYzZVwuxyeTySj2kpiJywNfJH2Hh4eYpkmz2VQG6oVCQa0YCQDU6/VIpVLKUF3TNM6cOaN8lsQLyzAMJUtMJBJKuy6pN2KobhgG+/v7KplPEthklUrGkoCnArYsU3Nlv4vFIkEQkEql1PaKDFPMGIXJs+zHJJ5Zuq6TSqVukoTG43GVeiYyPmGYwcJno9VqKZNuOQ+tVusFkrNXU7v1RQRqzNAZT+fkXIsIjdF0jh+E/MB71vidPz3AsixmnsmXLrX4nndViBk6Ybhok4IgpD30yLoWuq4xGPu4trmQv+kaYRCh6zCaTDkZ6PzOlRjrhTR/7WMusWjGdslm5s158mDAcDIjaZsctodUd+7CCfskogFxd/tlR3Qv1+2alMqxXjVOq1rVS9ebqf+ZTqccHR3hui5nzpx5SR+PlTxqVav61pQASBJUIz6qjUaDer2OaZrk83k0TaNWq3Hp0iXF+o+iiL29PZ5++mmy2Szr6+vcfffdnDp1inw+vwgIYYv5PCJpmbxz2+KZI49KSsO0Ylze85jNJrjPmm27rovrxeh162iMmQJ2Aty4wdOtRb+YASID/BCCZ5lJ/TGUshGOm8BIZ6mN5nRnM4Len+HPZ8S1OZqhM/HAsQyGoxFPHsy4647TvGs7SyyhK4/ZV1qr/uftWyvg6E1W0+mU4+Nj4vE4Z86ceVkX27ciUvbFqtPp4Pu+QuTFS0YkTwKu1Go1tVoofkbCJgmCQElnJOFAwA8BK4SRI8BTp9MhkUiQSqVUgtZoNMKyLAWotFotNVHudDpcu3ZNeSOFYajAisFgoJglwtIR+Zvsm5gVF4tF+v0++/v7FItFUqkU0+lUTfyjKKLdbpNIJMhkMsoHJwgCxWAaDAZKNiNMHDE/FoBL5E22bbO9va0os5LEJclrYlRdq9WIxWI4jqOSucSQWii2cp6z2axi1Yhp9unTp5VkbDKZsLe3RzKZJJVK0el0FEiUTCYVuBEEAa1Wi2KxSDabVRIsAascx1GghgBbkkI2GAzI5XK02+2bPJMGg4GKsBf5m8gDRdYlAICANIZh4Lou8/lcnTc5rpqmKQZOt9tlPB4ruVan0yGbzVKpVNTxHg6HCiSbTCZYlqWOvUgSBQhyXVex6sTgWsZ9FEVKdpbNZhUzrNPpKDmmsO6E7RaPxxVwKuNUxstwOFQU7Ol0iu/7SropQOd4PGY4HDKbzRR4JOdfAD3x/9J1HcuyFOD3jYyvv1FpCzIQ7cGM/+KfPMwv/VcfJJmwiIDj9hhvHqFp8OD5Eo7jqG15/HjOe++YM5z6hMHC1NG1Y1SyCTQNZn7ISWfCZsnFsXRE1RYEEb/02af5rX97Cdd1+es/9AAFO4dl6phahIfGTslF06A38vjyE0f84IUPQDjGNgLsZ6V8r6ReizjaVeO0qlV983oz9j/fiA31Wnzn7ag3Anj1RtiGVb2x6rUaEyJd8zyPQqFAKpWiVCrRbDY5PDxkPB5z6tQpNjY2aDab7O7uqsTGra0tAHZ3d5XVwt13XeBd9z/AYDDgqek2htbmvtMVmp19DloRVswj7cDUQyWz2baNp9lk0i5VZ8zxGDJxB9eJ0Rz28OdQSIERjxPXZow8mMwgn9LZWStgZbboaYsF0ZIDw3FIpGvMAxhOPcLIYDQLuHY4Yw588P67SGWT5KvpVxVVv+p/3t61Ao7eRFWv1+n3+6ytrSnfkpeq10MzPxqNFLvj9OnTiq0DKMZQLBZTEqZlU2YxwRb2ibAnBIwQc98oipQMS/xnJpMJvu8rM+xcLsfx8THtdvsmI21hFM1mM9rtNvV6nfl8riLVhSkkk2jxaZJIdJmk53I5UqkUjUZDpV0J6LGzs6OMtWu1GvP5nG63i2EYTKdTBWYIs0Ym87JKWSgUaDab6qEmgJr4LSUSCba2tlhbW1OfL2lxAjpJ0lgqleLw8BDLsnBd96a0rlgsRr1eZ2trC03TeOKJJ9B1nfF4jOM4jMdj+v3+TYBENpul3+8DC6BJDM03NzdZX19nd3eX8XgRO7q/v8/Zs2fJZrN4nqc8gkRXLiCNgB62bSvTbxkjYRgqAEdAIxkDki5mGIYCE2WciEfVMiAyHA7V8RQfn3Q6TalUwjAMrl+/jm3bCkwTEFNM0QVQHA6H6hhomsb+/r7yc+p2u+o1Ho/VA3E8HqPrupJnTadTGo2G2h/f95WRdhAEOI7DbDZTLC8x5BbTV9d11Qq2AJPi7yVG2r7vq9Q2AR2FaSSyQGHVTadTRqOR8hETE2zP85R80/f9b3jdF9M2/8/f+A7ef6HEPIz4o8dPeO/5EvGYgUZEFEE5Y9MbeXjzkBu1oWLTDYdD/u/f75E0Zvzgg+vE4hZhBE/sd3FtC8vQKGVs0HT8eYRvLBhJ41nA//n7+/zTz15nOBwuvMqcIWk7z3gWoAEZx8CxNEI0hl6c73roo8S0BTMslqq844+sHgAAIABJREFU6kSj220OuWqcVrWqb1xv1v7nlXzOCjB5Y9XrDeKt6ltXslgmoTCu61KtVjk6OmJ3d1ct6n7v934v4/GYRx99lEceeYQoijh37hzlXIrjx36XP/3Xn+NzvzqiPtJJx3zyqQQxw2Ajb3LQmzPpgxdCCKTjcWUZkVtbJxhoJBJt4uOApBsnNGIYEYQxSKbizMM4YRBhWVDNx7Eci0T+NEcjjW7vhI2NDRwaZEs23YGPo5sEhkngz+nPQsJN+MiHHuD8zga2MWd9+85Xfc9Z9T9v31oBR2+iymQyFAqFV3zBfqtW3MRzwPM80ukFki1MHZlwCvtBjHllwh+GoZL/iLeRpHsBKrVKJvOz2YzZbEalUlHMHfEg8n1f+SI1m0313cIMgoUUTOQ/y8lS6XSabrerfIHEI8ZxHPr9Po7jsLa2plIUarUa2WyWbDZLs9nENE02NjZwXZder8doNKLVailmz3Q6VRK7dDpNp9OhVCopzyPxqxEfH5HB+b6votYBCoUC5XJZsYvEC0cAKPG3CYKAo6MjBcQBClA6Pj5WKyzifyNAiWynaZocHCzkRJVKBd/3yWazVKtVnnrqKQUGiTxrNBopwMP3fWazGdevX6dSqShW0TPPPHNTkpgAYuLvI8DV+vq62ofj42Ml+xLjczFiFkBIfhZwJJVKKfmYMIEEKBITcDGTNgxDnWuRqcl4EPaOSMRc16VerwMobytN0xRYJL5Ywh4SIEZM0sWMOpFIKDaTHPdKpaJ8mWKxGJlMhpOTEzqdjmJViTRDTN9lO+XBK+CjpPqJubwAknL/ODk5YTAYKKp2Op3mzJkzCthb9ofK5/NKgrjMUFuuf/E3PsT7LpRw4otr5y8+uE0YwWDikU4sPAK0CAqpOMOpz7/72hEfuqdKLpWgOZhRmzp85hGfT//5Nc7nAv67Hz5HEGqMZgEjNAzT54mjCd1JiG65XBs4XG5qzPLv4+PfW2L3mWf4+qVdNksuUz9gEdC22E4/hMiwSbgxkimTKPQZVT9EPFV6BXfD5+p2TiiEqr2K5F7Vqr5xvVn7n9fyO5//vrcS8LQCbd449XqPq2/VWBBrC7GUGA6H7OzssLm5yeOPP87h4SH7+/ukUim+/du/nYceeog/+ZM/4Utf+hKXv/IYd+Z1vu/ePP/Dbx2wdxIShRCPdalkNXKZBN54TjeEOOAkY+iRT9w08SZDPN8nUzlLNZaj/dh/pD2YEmkefgRGBFEYEZoWWuhjxWximSpOvkz+1B10r14mkyxR2dig8dRVpuMJg+GE0+spNEIsO0YhoXP36XX+sw/fA5FH+V0/iJksvqrjtOp/3t61OlNvohJpziupb9WKW7/fp16vUygUWFtbo16vq5vLMstHJrymaTKfzxV7QqLFBSgZDP5/9t40SLazPvP8nTXPOblnVmVtd9+QroQkJLDUA8KY1caNsRkWMxB0EDE4Arc90Xb0TH+Z8IcJAk93hyPaHZgObNqYwRjT2BAeVtuMDbYss0gCpCuJK+nq3ltrVlblvp59PmT9X9VFArSU5Cspn4iKW7eqMs857zl5zv993ud5/n1lQRIlkdxYZGIsSpGHH35YtToX+49t2+zs7KguVqK26fV6NJtNpbYR4iqfz1MoFKhWq7TbbZUlpGmaasmu6zpnzpxRZJSmaRSLRUXgCCkh9rdut8vu7q6yHUmOU7VaVUqm6667ju3tbUVuSbc46QIn2TtJklCpVBS5kM1meeihhyiXy+i6Trvd5tChQ9TrdS5fvkwYhmxsbKibcjabJQgCWq2WIq5qtZpSdEnBG0UR5XJZdQWT44FpYSyWOOmO1mg0yOfzJEmiiJ0wDJmbm1Pt6g3DYGNjQ2XuCLETRZEqdvv9PpVKRYVGy/kThZUodeR7x3EUYVMsFlV+lRBFpmnS6XRUILZY0IRAEwucEGSZTEadn1wup8LMNzY2KJVKqsvfZDJRCjpRFElYdi6XU0SphHEDKsPLdV0KhYKyJUpGlnwWgiCg3++rLh1BEChCTHKJgiDg8uXLys4o50YIVbHASYaTZEhJhzUZCyG3FhYWriCcOp0OmUxGnaP9hKN0LfxxRcNt19SwDP2K+4auQc6xgBR5laZpFDybD73nBgxdozeO8MOUv72vyX/68jpRFHFvd0gcn8A2pp3TCq7BenPCb//Jfei6riyacejzGz9X4ZpXZ+DVpzm/dZgojXloo89SOUPOteiPI753ocWp626m4hg0l34B3auScbyfmjnykzBbcZthhucOz9f659na5gwzzPDsQAikcrnMZDKh3+9z8uRJVlZW2NnZYWdnh06nQ6VS4ZZbbuF1r30tD3/mN/nyXRu89w/uByCvwaGaxiBIGYYpG4+M6O+9fzkHBTdkFLYxRl3KXpbJziXmqrdw7bXXcvnSBUJ6EMdkXJ3JOGHgW+QqSwyHQ8hk6MUZXM1m0rgPOutUilnixpAo0UhNk3IpTxBpxGmCabusLC3yC684Tnz8FyguHCF3+JkFYs/qnxcvZsTRCxwHEfD4kxBFEVtbW8C0m5eQO/tvKjKZF7JEclXk9UIEybYkzFoIALHPCPEgVrTFxUXVyarRaBDHMYVCgaWlJba2tlQHMgkfFjJEVBjD4VARBRIOLEHJkgcjyp5Wq0W5XFbdUUzTpFgscuLECSzL4tFHHyVNUzzPU8RUkiTq31wup4LATdNUHcuk+5fjOGpfRdWxvr7O/Py86vQgyiNpFSoqrJMnT+L7PltbW3iex+bmpmqfLtlLhUKBnZ0dFYRdLBbJZDLU63WldtnfTl3GaDQakc/nCYJAZQABiryRXCdRUO230zmOQ7vdVu8/GAxYWlpSai55LyGXOp2OyvsRElEsZ6IGymQy6rzC1B/daDSUCk3TNEqlEq7rKutXv99X38tx5HK5K0K4xS5ZLBYVQSZ2QVEKhWFIq9VS168okXK5HMVikXw+r+xco9GISqVCoVBQGUKiLlpfX1eEhZA5YrOTsQjDkHK5rD5Dcm3XajV6vZ4izSRnybZtRYrK2IklT/KZhDjdH0gPKGXf/s6FQoBJd8PJZPK4rmk/iu4wYLF0pYVk/91jek+Y5hulTEOzkxTyjkl/NOb115f5i3+6zLnNgAtrdX79v93J73/gVkpZk9XGkH///9ynigy5Pl9/NsttJzwcSydOElzL5R/Pd3jpkQJYFik6oyDGylbIeh66EWE4RXTTVp1Sng5mHv8ZZrj6cTXUPwe9zRlmmOG5gaZpVyjDTdPkhhtuoN/vc+HCBdrttsqSPHJ4mf/zZI15rcXHv9kk1aFcynEym8FzTbabTb55frpAPJyAYYKtgWVqaIaBwYBxv4G5sIBluwzHEYnfgSghAZZOXEOQaKpG9H2f0e4GW2mLgqVhGCGD1jbZbJWi45H3TLQ4IIwiIqvEDWeWWKqViHJlFhaXr5p71Kz+ef5hRhy9CPBMuor8pPfsdDo0m01qtZpSRDzRdsViJt9L3oooTURRI5NUySYSYqHf7ysFhFi+8vk8c3NzrF++zOrqqgpZXlpaotPpUK/Xr+j4VcrlKPV6hOMx20FAbBjYts3S0hLdblcFDUv3NWnTWavV2NnZUXafra0tDMOgVCpx8uRJFhcXOX/+PLquK+WPtKO3LEtNwKWlved5yrbUarVU17ELFy6ozmtiXfI8T3Vs0HVdFahiLTt8+DDdbpfV1VWVtdTpdBQ5sri4qDJ/DMNgbm4O27ZZW1tjfX0d0zRV4HW/38d1XUajkSK1CoWCyioSKx9MiZ5araZsa6Lq6na7ZLNZZbkT4kc65RmGwc7OzhWqFVFESWizZFbJeZdrUK4V6QIneT6S5WMYBpVKRSlvRJkkapsfPSdyPsV25vs+8/PzisSUTmWFQoF6vc54PFYB72IZ268ckn3r9/vKbre9vQ1MbZGyPSHcJBRRwuJlu6ZpqvdvNBrKdhmGodon27aVNU7GVfZFFEVC1AnRIgomQJFWQhSKUkrUXrKvEsQtnw0ha2Q85YEv+PWP/jOf+T9+FtOYvn+cpOiaxjiIcG0T9lkp0iRF0zWmVBJopERRTM1L+C/vPcm/uuY2dE3jW+d3+P1PnePuRzssLCxQrU5J11qtRrfb5XXX5qjkTEghTXW8jMnLrzvB1y661DIjrtN1ajmdl85nsfWAcfUWNMt9RqSR4KBX3J6J+mmGGWZ4YvxL1z8Htc0nRBzDk5lwRRHa1hYkCenSEjyNLpLPJa4G5dXVsA8zXB2QLrZSv7uuy4033ki73Vbzj2FyHdWNO3j3W17JS89u8/l/voRlGqSJTpAknDmyQhLv8MDqkCSBXg9yHnS2Y5YXAhZKHnrks/vgP5AZ12k2JhgZSE0Ht5Qn1kyazYZS92uahh73yRkJ67sjauEI181x+lABv3QNdtgna/QZdnZZrlU4u1IinruBheWn10X2icbkIDCrf55/mBFHL3A80w/3ExU/QRCwubmJbdscP378CZniK+wqexN7mZTK99IFbT9xlCSJIk8k8Hc8HivVj7z2ZWnK7Z//PFsXLmAMBvzpXiv73d1dGo2Gsvjk83nS8ZhfbrcpdTrTsGHX5f87fJje3qRfVCKShZOmqVKniAJpeXmZ9fV1fN/n+PHjHD16lCiKqNfrqluZTNSlJbtkEontTjqcBUGgFDGNRkOpn6Rzltiv5ufnle1JLGYwJY5kbIIgYGdnRxWuMsG3LIvd3V1OnDhBvV6n2+0q1ZGMraZpikwR1YkobqQtfDabVSSBEGoSrr2ftBHllGTmyFg6jqPyqHK5nCIiJKhciJcoihgOh0p5JgHR/X6farWqQpQlCNvzPEUkymuEFBLLYBAESlmk6zo7OzvqupOH1XA4VKRVu91WmUfdbpdMJqMyfkRtJB3gpMOaXLti0ZNrZ38ml6h4RAUktrskSVSGk6iG5L0kH0Mym8RWKaScnCcJB9/c3FSfV9M0WVpaUr+TzI1yuazUWqZp4nkenucxHo+xLIsjR46oMW40GuoaEYWYPNiz2SyWZSliVvDl765x629/if/rPTfz+puWiOKUS40BW60R/3h/nTfdcohbz8zj2PvvF9PQ7KxjkgIf+PkznF4ukHMsDF3j529Z4dXXL/Jr//0h1vqmykGzLAvLNDiz6KKjkWgphqZhaJDEEd0kz6ETt/FQmhDkIuYLGaziIlrxmLqGnwkOcsVNrsWZx3+GGQ4WV0P9cxDbfNz7f+976J/+NIxGpDfdRPye98CeQvRx255MMD/zGfTV1en7Ly4Svve9sGdznmGG5wOuBiLPsiy1gDgej6lUKhSLRVqtFqurOdpOieHOdymWfF5z0wnu35zgOh52uUba2+bYOGHgR0yiAC0x0bWItpHS6YzoDceYjS5Vz2Jte8IIKMeQJhOMjHOF2t2yLHRdZyln0h8GjKKEcqHIcsWbKsXzVWq1a9mu16kuxCwuV3FPX4+3cOppdVH7Uczqnxc3ZmfqRYCDWnFL01RZtZaWllS+yk/brkw6pWuaBAZblqValjuOw87OjlI1iL2mUCgwHo+VCsKyLJaiiF/a2mIzm+VCEHDW93m7afLX3S4bGxuqeKpWq4xGI86028wXCjwC6JbFMcPgbLPJl/da3csE/ejRoxiGwWAwIJPJ0Gw26fV6KpBTJtiiuNB1nfX1ddUSXkgwCXxO05S5uTkVvCyZQpIbIw8fCaHeTxocOnRIETEXL15UWURpmtLv9ykUCspq5/s+GxsbJElCHMeKtJBsJdn+YDAgn8/T7XaVbTBJEhWsHYYhnuepwGVZ1ZCuZOPxmGKxqGxmmqapibzs2/4AcyGAXNdle3tb5VIJYSJWOrHgydhK5zAhboSckEBsycWSa0xUO0mSKJJIcnokZBxQYy8klwRIi8VOVFNC3EmIeDabxTAM1e0NUOScHGOpVGJzcxPLslhcXFQZTnKOPM9T3dp6vZ7KTBIiaTAYqDGUiYlYBsVmJ3ZPeZ/BYIDruiwtLdFqtRRJJdY5UXCJXbDT6ajVKnnfVquFruv0+306nY767IpNTa4PCYzcb3ETi6U88H3f59Kuz6/+529im/Dt33sLL1kpcP3RErdft8CH/8e9WKbBy09VcSydcRBh6jqmoVP0bAbjkBuPT1VjpvHYvcezDT78zuO88w8eUuo9z/MoWgFoGgmgy70qhaFR4Q1veIMiZa2FI/iuS2bv2jsItZHc1w4CsxW3GWZ49vAvXf88k20+IdbWMP7oj0jn56FaRf/BDwjSlPXXv14tWu3/cu+6i9wDDxCtrKDFMebFi/hf/SqT17zmcX+7vwOn2KGfytdBYmbZm+FqhNjXpB4yDIP5+fm92voQ9fphBsMeBf/PWO6vc3l7i/moy/zpl7M8VyDvWfzzQ3UGo5CMZnJ6IcPATzF02O6MeHQjZLS3rYwBGODqAyxrWTk2LMuiVi6QSbpc6E2oZKBWyJB3MiT5MtXFRbrdLuVKhVKlwsp112Fks1Tn5g6szpjVPy9ezIijFzgO6sM9mUzY3Nwkm81y4sSJn/oh/9HtikJBJv4yCRZiQLJsJMNoMpkQx7HKXUnTlFKxSMX3KQ8GxI7D7mjEifGY1Pe5NQz50z1Fieu6VKtV9folyyLvurx2NMLZU85c8n2SPe+y2Jw0TVOqoUajwc7ODlEUMTc3x+XLl5WVSMiZwWBAvV4HwHVdlcUkShrpuCU2oc3NTXq9HuPxmN3dXTWGMh4S0DwcDul0OgyHQxqNhlLN7A+UBtR772/FLkHjrju148g4z8/Pq8Dk/Rk3QiRJ4LOmTTvIDQYDlSMkGT+6rtPtdnEcR2UHCYEmtiWxWZmmqdq4i7VPAsMlb0oUOr7vq+BTsb6NRiNc1yWXy12RbyQE0/5xy+fz6nhKpZIiDh3HUT+XEOyFhQWlMtu/7f1kmeRRCeEm571arSq1lnToE1uYkHGFQoG1tbUr7HH7Q68BFYb9o10F8/m82pcwDDl69KgaezmPu7u7V+yzKLBEpddutxkMBjQaU0mzHP/+61JeL4SbEJhCOomiS9d1xuMx4/FYkZBib5TrLZfL4TiOsulJQPkv33aYQ9UsKRBECYah8Tvvvgk/SkjSlN44YrM5Ik4SaiUXP4whhZxnoXHlvUXToJKzODTnsTtEqd+yTpZxrGHq8V6WUgqaQeboK2nsBdxLNzjP81TBdRAFyszjP8MMVz+ulvrnQJCmUK+jfec7EEW0h0OG995LwffR6nUW3/veKxodyJcehkzimItf/Sqa77OczeLUaipfb/+XKL/3504+2a+fhqdCQIlqWVTAz+TrWTsfMzxnuBpIxB9V80k+qsxrxNrveR6jS9+mlzcIqwUerfdo9EaYF77DocUyh2olfgaNbz+8Qxwl9HzojcZousHRhTzhfMydDw0BGIewVDDR9ZQ09kGb1i+VSoXlpRq7F1Y5tVSklDWp5gtYjkFm+XoGew6GXC7HysoKjuNQrVZxHOfAxuKgMKt/nn+YEUcvcBxEOOT29jbD4ZDl5eWndOPZv11RZ8g+AcpqI4HRQgR0Oh0VsDwajfA8j8D3+eV+nzevr5MbDilqGkuAkyQU0xTimH/TavERw0DPZtE0jaO5HGe7XarANbu7bIYh28Bh4CWahpfJUK3VaLfbbG9v0+121X7KPkgGkO/76uEwHA7Z2dlhOBwqJYZkAcnE1LIs9V6SSSPh13LMoh4BVGev8XjMYDBQE3QhF/r9/hWT3n6/rwKL5cYrndOEZBFllyhrxuMx9XpdWbzEGra/QOx0OqRpSiaTUaqhcrmslDZyLJJfJGSbkDtCImQyGRU+La3lS6USu7u7NJtN8vm8Gk+xawFKfTYcDun3+1cQjbLCK+Mr1i3J5jFNUwWHS4C6qNckG0iIysFgoIgrIalEWWRZliKC5HwLeSPEVZIkNJtNMpkMOzs7qojY3t5WtsUgCMjuXYuiqtpfXMgYix1RrH3NZvOKcyEqs/1jIStd0uUuDEOlDNJ1XXWmk9Buea10DBSlViaTUQqpfr9/xfsCyuLWbreVWkt+7jiOOtZMJsPy8jKdTofJZEK1nEPXtb37z/RekHVM4jjAD2LQNJarHnGSMvYjlaI98WM85/GPJdfSKTgGHV9TBGOaJjw6NjltdLB10AydTuY4u4ELTMjn83iep0hU6Sx3UDjoFbdZ4TTDDAeLq6X+earbfIIfon/60+gf/zhpvU6v02G1XEbr98kEAZ6uE/7X/0r8wQ9i7T1X4kaD8MEHGaytMb7zThbn58lUKqT1Oq0HHkBrtyntTSZ/lAjr9/vMzT29Vt0/6ZieChEVhuEVdu/9pNZT/fppeCLCaX/u4jMlr54rldazgauBtLla8KPnSxZipc6VHCS341GpFXBtjcEwYHc4Yac9INQ6+EGC61pcf7TAVjOglLNZ3zXp9sfEqc5oMmE5B5sDCGMgjegPIIhaGLbL4cOHpw151jY5Xl3iUCHAtlPiWKe2ci1boUEu7+K6LuVymbm5OfL5PLlc7lkdi6eLWf3z/MOMOHoR4One+IfDobKXHT9+/CndKH70b0VtIaHY8r1MVMWm1ev1OLmzwysffJDxcMg/lkrcPzfH3O4ub9vdJQ0CtpKEAnAaGGgaQ6AO/Gqa8p045jywouv8z5cuMel2yQM24AIWcD8QWRaZIGB1dVUFdJfLZTXBF2VG4vsE+byyf4WjEVaaYiQJXrmMs0eOCLEhljzTNBXZIB0ZRKEix5/JZFSrd8/zAFTGk2EYOI7D0tISYRgq5cT+87L/9c1mk4WFBXzfZ21tjSRJWFxcpN/vkyQJrVZL7adsI02n3bxKpZIia6RzmpwvyS8S25j8znVdRfyJUkwUPGLxcl0X0zQVuZDL5SgUCvR6PUXsSNe5/SHZIgMeDodqnGT7QpIJwSTFpbSO1zRNbV+CrMXqJp+DIAhU4LiMi1gGhXARtY2QRNls9oqOOUJsato0NFxIJt/3WV5eptfrqW5+YsOUDmyi6tqv6NnfXVCuoVwuRz6fV2SVbEeORa4rgEqlosapUqnQ6/VUQLzkWMl1UygUlCVUSC1Rio3HY1qtFv1+n1KppM5JmqaKfDMMg16vR7/fp1KpKMKy1WqpY/vWQx3iJMUydZIkJUk1gigmlntRmmJoOg+udzi1nIcUTFMnISVJ08esZ3vQdfjYvznG91ZHfPZ+Syn/6tmbOGl/DyPtg27gxzpDf0g2O82ism2bXC6nrpeDKnaeDY//rHCaYYaDx9VQ/zyV15l33YXxN38DSULyi79I+upXo50/j/7RjxL5PqNKhVajweLFi5i5HInnkS4skP3CFxjdfDP9l72MYG0N40/+hGg8hn6fQ1HE1nDIVr/P8unTLM7N0d9b/NB1nWw2i+d5KicQmCqcwvDKIO0wRGs2QddJ5+amN+anMB5PdlzkefNEoeMHjR9HNu3u7pLNZrFt+yeSUs8moRUEARsbG+pZ/Vx9wUyl9VQg9Zmo+isnXgHbf4emhdx4psZw5LO247LV9olDn2EUUc46dEYGY3/CctWj6AJoRFGGkGkUQwjsDiCNwB+0yZXGjPt5BoMBr3jFK7j5xus5/43PUE7g+EKWjc4I96irFstqtRqu61IsFg+0vpjVPy9uzIijFziezs0/jmMV4mxZ1tNeedp/c5EQZbHeAErJI8oaTdMoXbrEGx95hPXRCBP4X3Z3+bRlMR4MyIUhW6ZJ5PtsMiWOttOULcBgejGfSlPu9X1OXrxIPwjYZEoY3QA8zJQ0ypomc2FI3Z/ewAXSvtzzPIqjEW/QdQqaRr/b5c98H93zeEsUsWTbZFyXdV3nH/YIIlEMiSVov7pFAo2FeJGOXEmSUCqVrmhPXygU8H3/ii5Wov6wLIt6va6yfBzHUSHWtm2zvb2tPNCSoySWNzmubDarQso9z1Ph0KJAkZwhmWgLIbI/P0jIME3TaLValMtlNE1T1ixR+WiapqxPwNRzvfe3cu5F5SNjI0WYjKWs+snPxDInVi3pwCaZP6JCktwesa9JJpJ0rNvfwUwUV2LNE2VQHMcq90eshxKUHUWRWsHxfZ84jtnd3VWfGZh+9tbX18lkMnS7XcIwVHZGTZt2dIuiiMnkMXVMtVpVuU/FYhHbtul0OozHY0VsSrEqdswkSa7o2CfXiBTeQqoB1Go1leMlxy3nR9Om2U6HDx+m3W6zu7ursqiEOJOCV9Omweq7u7vqmGR1Np/P0/Yj3vl73+J33/tSaoUM/3S+jWmkvOnGhT1iCIIo5rc+/i0+/e9fw7GF3N49A5I9hZKhP3bvSpLp/08tOPy7qsnH7g24/qU3cnNph8zYJ7BKRGHEfLrKYbPM2J3HcRxFworN7iBxUIW1kKEzj/8MMxwsrpb658nCuv9+3I98BGo10DSMP/gDYtsmGY/xm01Wi0W+X69zrFhkYTTiUi5HK5fjcBhStizsc+cwb7oJ91vfYpgkdEslzEKB/oMP0pqbo3jNNfQ0jfFggJ4k5ItFteAjiyeO45BubWF89avogwFptUr0S78EjoP5V3+F1mpBmpKcOEH8pjfB8zzU9scpf4y9zrtSYzzXSNOUtbU1lpaW1GLYU/06CFIrCALW1tYet3/PJZG1/1iuVkJLauogCBgHHu4tv87yhS9gudtc6Oc4XBmRPnQfWpqlOwoY+T514wTD9fuJIx8/Tpn4EYfmPeJownAQTomjx/qP4AUTvKTJqVvexG233cZ3v/7n9Fo9lk6vUB+kGMkWC2aPQZpjfn6eXC6nFoYPGrP658WL5/cdf4afiqcq1e71ejQaDarVKktLS1y4cOFpb3c/hDjar3oJgkAFModhSLvd5mWNBmNgvKf+0KKIm7pdvqhpOFHEIWBk2/hRRJAk6ICjaWTSlHVgvGcByoUhiW3DZMIYOA8sAqM9C9kXMhkcXcfey3ipVqssLi5O90fX+cW1NYJqlQs7OyyEIe8JinmZAAAgAElEQVRzHDYdh7kkYUPTMNOUo+MxJ2ybh/YIJ7GJSVctsW9JfoyE6AmhIqHTongpFAqUSiWazaYiZoRss22bra0tpaIRokaUO2maKhLIcRz1sNc0TREVmqYpu5WQDGJn299eXdM0ZZcTkkFIJbG9bW1tKYJEFDNCAApJI+HnYgPr9Xp0Oh1luRNCTfKNxPLn+76y/gFX5DoJ8SWdxWRFWJRO4/GYXq+n7GDSoj5JEnZ3d1UujyiJZGIgVrD9CiohQbrdripYhPyRjCSBZEuJ2kyyf2Rf5ZzHcYzjOMqCmM1myefzKt9oNBoxHo/Vv67rqm53rusqW56o9SREfv+1JyROFEXYtk0+n1ckkOu6FAoFdV1IjpOs8O5XjAlJJ/lFo9FI5SnJCmgURVcojQqFAmk6tdmd911++T99hzAMAciYGpP3XM/rb6jRHYb8h0/eQ7WQJe9ajIMYzzbRtGmm0ZQ8mn4PYBg6cZzixzpZW+Oao3OcOnUKt/tVMDLEcYKm6yQJVO0R66AysoIgUIq+qxFyHq7WgniGGZ6vuFrqnyeLzN13g+Pgex5BHJPL54m+8Q06r3oV/XabB3d3GRkGdcdhG4iCgDCK2JpM0A4dIgXi1VWiS5fodLtTW7jnUV1awux0KPT7kKaU3vMegkpFKX7lWR/HMaNWC/OLX6RXq5FZWMDqdDC/8AWSY8fQul3SlRUA9EceIT1+nOTs2ad1rD8NL3aLlNRsUjv/S2F1dZVDhw5dMbF/umTU0yW0fN9ne3v7Se3vs0VeSW0ntdaPU2lJs5uJvkRw/b8lb9vUNjcZDXok2qe59OAPyOYLFF7yCpJGk3u378OfpAwGQ5yMzcQPyOfzFLIthqNpLRTvHdtixeRNt5ygcM3xadOTqM+xxQL3r25zaK7ALSfm6XQaVK69nnw+T7lcVnEJVytm9c/zDzPi6EWAJ/MAjqKIra0tAI4dO3Ygq/P7t6tp2hU5RzIBtyyLTCajgpOHaYq+R3QEYUguiohsm3/VbLKbybA8GuGlKb6m8blcjiXfZ9Gy2GGqJvr7PULl+4bBu8KQ2PPIOg6T0Yj/DnQ0DSyLU0nCz4chFzMZLpZKKsul0+mQGQxwmJJQANtRxCuiiOvGY8I0pQ/Ec3PEwLEwZJAkuHHMXKnE0HV5ZB95IKHL0rZT1B+Sw5Om085rYpWT0GmxS0VRRBiGKnOpWCySy+VI0yuzeURlI4SP2Lz2T5iFGCkWi8rmJTYuCXkWBYtY7WTVTTKbkiRR5y2fzysyQ0gYURxJESrnXvZFiIj9xJgQVmEYUigUaDab6nVyvQgBJBY9IZc0TVOd0EQuLDYmmNrcxP5lmibZbJZSqaTGR8gdyVoSy5yQQHKsoqqRwkFUS2ma4nmekrPDlLBYXFxUVjIhx6TDmwRTy75KPlEQBIowkywkQIVX7yewgiBgMpmocSwWi0oVJt1w5Bx0Op0rMpV0XVf5VBIaDigiSjKwZP+kYHRdV10LolqTcy2qOckJk2tdiqrJZEJ3EPAbH/uuIhzDMOTX3nCccs7GNMSCN407iuIE09BJU9A10JgWUAVHxzFTXjVXZ6z16UUu81qPOLHQNLA0jX7yWK6REJoHvZp10FLtmUx7hhmeHVwN9c+Tfo3r4vs+F/dCob1ul3AwoPfnf84gn8fa2OC4rpMJQy699rVUu12OTCYMSiWahw8zPHKE4NIltEqF3PnzzFcqzGcyaJUKw9e8hu7SEqMkoXf//VTOnyd/9iycOqVUs2EYEtXrdFotGq5L1O0yVyhQuOsuor//e7pJws7yMsfOnGEuSXAfegjNdWEwQItj0mqV9PDhZzx2M1zd+HEqrWcLm5ubzM/Pq9rhx0E+c88GqSU1sjQKeTLWQ6nt4jim3+9TvvlXWbeuY3Nzk0FjwCEr4MxCjnqrR7NvEcUpaaJT9UzsDNSnZSpy1L906zU4esjmD79J/tjPUCjPcTznExsGZw7NMQpC7Epp6pooFvE871lpcz+rf17cmBFHzyM8nRv1T3uNqAOazSa1Wu3APOVPtNInk0vp0iRqGdM0uXz5Mr1ejx8eO8ZNP/gB84MBQRji6zr3+D6/GQTsFAqsaRoEARnD4NPFIuuaxrV7lqt1yyITxyyUStiOQ++RR7hpMmEzCPjDJOGcpuEmCb85mXA6ijiUJHjjMf/DtvmzvWybZrOJvZdH5JgmpWKR5cmEs0HAvWnKceANrsvmwgLX9PusBgE/5/vUdJ1zgwHRHnHz/b3gYfEXSyczeSjtbzvf7/dZXl6mXq+rNvCigJFgznK5TD6fVyotsZClaaqyeOThJp3MqtUqw+GQ+fl5RVQ0Gg2lSJGHoHQAEytYmk5b0Eu2kRA7ktOUpo8FflerVbLZLK1WS7W2b7Va5HI5stmsUlVZlnWFLU3IMSFRJpMJrVaL0WiklEv7rx9RPMlxC3Fy9OhRDh06RKPRwLIstra2VGi5rGJEUaTyoETpJiqu/d3CisUi3W6XKIqoVCoqtFtUSUIsFQoFFhcXlerL932lqhGiYjQaKXua2NLkczGZTPB9X1mooihSxI98bkzTZGdnh8FgoMgaIedKpRKu66rw7Z2dHUX2ybWRJIkaA9mGZBtJiLjY9oQMA5TFTWxevV6PNJ3aBCUQXVbcJDRclEqijttP2snnXkLaxfYmFs7/9Y2nMPaROpoGYZzihwkjP2IcxBQ9C8c2sQwN0wA/1qg5E7TmV7hjfD1upkMmHaNpKU19jgvjKoVuF0Ap8H7affCprj76vk+v11Pqvyf7BSi1lpCAQrY+Vfzt3/4tX/va1/i93/u9x/3uQx/6EPfcc4+67j760Y+Sz+ef8jZmmOFqwfO9/nky6L3ylWTuuIPM5ia6YTDWddZcF+2v/opJucykUCBj2+R1nfl3vxt7ZYX19XXynoeey1H2vKlt+dprKa2tUbp0CW1xkfov/ALO2bN4mQzWH/8xzR/+EKPTQfd90je/mcnb3ka0p44dbm+z22rh7tVm3YsX8R94AO/4cebbbc6GIdbyMu277mKwukrxa1/D7XbRXv5yME3i228nufnmAxnHGWaAJ09U7Ff+HDRarZZaMH0qEEW/ZGYdPnyYc+fOce8PfkCyejc5z6IcZXmJZqIlIZNYZ3kuxzV+wmprB4CXLEA31Fnb7mBkMrzkuEOu9z1G+dNstM8xl7Ow9YSRUcIqnlLW02azqTom/yTM6p8ZngpmxNGLAD/upist4m3b5vjx4wfO+j4RcSQ2tcFgwHg8ZmVlhYsXL9JoNAAYFQr815UVFi5fxgc2dZ3/bTjkEGB3uzhJQlPX8cMQM44ZahoPxDFepULetlnMZjl7+DCvu/tuJmnKpmniRBFlyyJjGJwcjTgBHElTYsNAiyI+MB6D7/PZKKLe7ZLP5/nHbJaf63Y5DFxnWTzoOKxpGtZkwjVJwtGtLTbTlHvjmNvTlIZlYfZ6POy63DAa8VCtxplrr1XWJ8mUkU5eMtGfTCYUCgWy2Sz9fl8pi+r1ugp7VrkDaarIE8Mw6HQ6imCRPCD5+yRJlBKo2WximqZS1UgejtysxWYk6h95z2w2S3EvA0HUI9LlTjJ2xNfd6/WUGkgelI7jYNu26ponCivJnRGbVT6fV5lHYpXar1iS74WkkLBnXdfZ3NxUGUbSeU5seKIMEmJseXlZqbEcx1EWyf0tjCWPKEkSZWkTa5qmaSrnZzAYqO5lnU5HWRNl3Pbb3YQIEwJOMqWENIXH7HgytrquUywWsSyL+fl5RR7Ztk2pVELTNHX+Dx06dMW1A6juHpqmUa/X1WdPuurJA38wGACPWUllDNI0Vd3dstmsCsCO45hisajsiaLkCsNQ5UaJ6kmUXOL7F4Vav98nn89jJD5LZY+hH5HNTG1qMFUbDf0I0zAIo5TOOKWggWdp9HyIdRvHyqCnISfmbL43fCULuRTDtBkbJU4Ui8zNzSmi7dlYpRT7phRATydL4s477+Qv//Iv1bX9tre97Yr9esc73sG73/3uJ9znD33oQ9xxxx1ce+21T/j7+++/n49//ONUKpWfeOwzzPBCx9VS//w0jMdjgnKZ9gc/SO/b3wbfxzp8mOynP81oZ4fL4zF+EDAoFBg7Drk4JtR18mfPYpomm+fOUSqVODo3h/3JT2KORlSPHyfq9cDz6JkmXLwIa2sM1tdpaxrZICD+xCdItreZvPGNmJ6H7rpkXvEK5i9exE4SaDQYnj3LbqGAYRjkmk1Kd99NtlRitLLCzt13k3ccWF/H+5mfwb7zTnjpS+Gn3Hd/Eq4G28rVsA8zXD14uiobwzDI5/Oq/jp8+DBnzpzBIuLS5pfJl3Ks7/YwTR00h0yQsNMPqRXz/MzxMfdfHJDxPJxhSNOPiUYTXndrhdXNXdJMj2TlVZSqLkHGZW7xGNlcntOnTysHw5M9rln9M8OTxYw4eoHjiR5+MinsdDosLS0pVvbZ3q6oXobDIZ1OR3WM2tzcVLktcRyz5vv8054i5Hd9n2vjaTcmN46JAC+O6RkGPxtFXN5rN2kYBp7nTdUYly6hNZs8ukfSOGnKG+OYu20bz3FYmEw4DDhxjAv4wL9OEiatFh9jukLwtUaDewyDxWyWhm1TjGMs2+aiaTIZj+k7DuZohKFppMAoSbDCkJGuc6xY5NZbbqG91/FqOBwqNU1pNOKEYTBhmrvU6PUA2NjYUJ3NhsMhg8GAbDZLrVZToc2SkSMTeyFIBoMB7XabTCZDuVxWWT/Snl0URvutY/1+XylWwjBUBIc8CIQskrb0++1zohiTDl3y8/3d8Xzfp9FoKJWRbF/IB1HQiB1Mrg1RAe2H7LeEUsu1lKapymASi52maVfY8ERRIx37pOW9kDjyPqKuEgWSWNlyuZwiRSRfKpvNKrWYkHGirJL279KdTZRNk8lESYeltb3YEIVYkfFbWFhQ30v2hCixBoMBg8FAEVr9fl+RexJmPh6PlcJnf17R/s5/cn4BlXuVzWYpFArKvjg/P6/2YW5ujmazyWg0UudH7h2tVuuKbck1KmSnhL4vLCwwHA7J5/PT8U080DTSFHrjCMsA09D5u/safPYHEb//qyscmbdIUxgGGq3R9Hwb2pR8Ng2dSRCRLZToJQnZTBZrj8jcfy0+2XvVU5ko9Ho98vn8k3r/H4d3vetdvOtd7+LrX/86H/7wh/n85z//pF9788038/rXv57Pfvazj/tdkiRcvnyZ3/md32F3d5e3v/3tvP3tb3/a+znDDM9XXE31z4+DqIajKKLZbFIfDIhe8hKWFxbo/Mf/SOnRR7kQhnhBwAoQjscszM2R3HcfybXXMhqNyGazrKysUK/XGdfrmM0mq/k85wYDKpqG+5WvEP/ar9Hf2UFbX2d3Y4P10Yg5wLEs7DvuII1j0te9DsO22S2XGZfLpOMxFmCPRiSaRnz0KPdqGlGpRDZJ0Dc3CZtNNNfF7XQoLi2x5Pt4zSZetfq4+6O2tYW2tgaOQ3L6NPwLBU/P8NQwI9GeOQqFAsPhkN3dXQqFAoeOnoTFEvXWgFtOHaEz7LO2MyTIVmlEeaLdB6dZlUCzM8Y0LY7OlSgVXQxNZ7M5IH/UJJsvkHolcpUKdsahVquRy+WeFGkEs/pnhqeOGXH0IsB+pnwymbC5uUk2m+XEiRPPapL9jzL00iGs3+thPvAApz2PH3a7pEnCaDRSrcWbzSZJkvB+y+JVe4SMG8cYwADY0TTuzWZZ2VNuDIdDwjBkd3eX9fV1ok6Hl+1ZiHRdJ9E0zD270OpwSGUyIQvYaYrF1D98GPhF4G+AS3sT57HnkTgOdq/HrWFILwy5mCRs+j4/0DRun0wIHYe27zMfRVzIZDhqGAw1jf4997AbhvT21DRBEHBoMuHVwyGhYWADR3SdL+/LnpFW6KJuSZKEfr+vLD4yiRdVkPim2+02gCITRAoqViH5nXS0k3wlCTr2PE+pgoT0kW53QiqIMkbOYbIXKi6t2fdLWGV/xd8tVr3BYKCsXfvbwXc6HeVzFpJIsN+6JflKkl8jpI94yC3LUsSHqHYko0jsUtKeXdRA+0kfuY5M01QdZgBl+xI72WQyUasklmUpss7zPDzPY2dnR411Pp9XAaRpmtJutxVJJGMq9jFRGK2srChySUijZrOpHuyyH5VKhWq1qpRTcizSgtW2bdbX1xmPxyokOpPJqPEWstAwDIrFogrcdl2XSqVCNpslSRLiOFZklVgYRV3V7/cVYSb2NrFLjkYjdF2nVCoRxzH1el11psvn82iaxn/+8jr/4S1H0UmJEvjmQ33+3ace5hu/8wrK3t69SYNsJkXXNTwrARJSLWKYFmikNdw9wlGIsVwup3LEni08Vx7/z33uc3zyk5+84mcf/vCHefOb38y3v/3tJ3zNaDTive99L+9///uJ45j3ve99XH/99VxzzTUHts8zzPB8wdVS/+z7Bdq5c2ibm8S1GsNTp+gPBuzu7nLp0iU0TZsuGP3FX6Ddey+XBgMujkYcAS5oGr7jkDt5kujCBYaXLjEcDplMJiwuLpLJZFh9+GEmu7uMw5DGYEAOCJOE/Pe/T9DrEW1tYfs+PtM8OT0M6TUahN/6FvqRIyQLC6yvr3P48GHKrosdhsTnzlGqVnGXl3GXlmieOkX/n/4J17bJeR52t8tkeZnNRx6hmc9Tu+MOykeO4Bw7phaXjEuXMP76r9FclzQI0B96iOgtb4F9dcqTGr8XEWaEzdWFZ3I+NE2jUqnQaDSmNa1tU7jhLZgPfJFH6l2Kep6+VaOfvRbz7s+z3e6z05mgA2M/pWxGtAdd5ko6D1+8RIiBVT76uBp0bm7uWemith+z+ufFjRlx9AKH3OiSJGFnZ4fhcMjy8vKzfmN5ohusrutkH32Ua//4j3nN+fMk2Swv8X0y1Sp/attowM+lKbd1u+ykKW+cTLjkutwyHGIzJXhywLc0DW88ZiNJOF2vs5rLMdgjPIrFIrtzc4zHY5YnExLTpAx8ZS87aKDrPJjJcHQ0wmMauhsBDWAOuB3oV6tTa42m8dZmEy1NucuyOBOGLE4mjIDTGxv8PXBrmnIxjqnbNm3PoxKGuJ0ON/X7mJrGHWHIuT0lz02+zy4w3Gt1vxAEHHVdLvZ6ypMsxI6EKksYtjwUoihSaqFer6dIE8dxyGQyKtcmk8lcQTZIa/adnR0cxyGXy2GapiJhJBjTtm1s21a5OYDKT9I0TW1PiByx30lIt+M4inCQQGlRFmUyGYbDobI4SSC0PISE/BH7mCiVxKImhJWmaWo85HWSu2TbtrLsiU1JOoxZlqXyoEQBtN9jLXlLkkslyhqxnUmukxy3EE9BECiiCh4LkR4Oh+RyOXX9D4dDpYISgsM0TRzHoVAoqHyk7e1tdnd3KZVK6oEqKqQgCDh79uwVQd1igxTSToie8XjMcDhUK+qiCqtWqwDYtk02m2U4HCqLWpIk+L6vxm5jY0N13JOV7YWFBRqNBv1+X1nZ8vm8ypBqNpsqV2oymdButxXpKYTl8vIyhUKBf16L+Y0/vcR1hwpEZo6HOwX+91+9jZXKY6tlcifxrGlA9jQsOyVEx8mVlMIJUOorIcSeTRxUUS8k5BPhHe94B+94xzue0vu5rsv73vc+RZzddttt/PCHP5wVTjO86HA11T8A2rlz6J/6FPoddxBns/TCkM03vIHNW29lp9Gg/OijpBcvMiyXyd55J7uLizx8110UgR1glKZolQrbjQZNy8L/+tcpnD5NcS8jUdM0dsZjKrpOb2uL2DCY+D6dM2cIW62pQrlUItrepg6sAwXgJdks5mBA+NBDmMvLFItFlkoltC99id5kQubMmWlo9qVLxLUaZhRRvflm7NVV9OVl7JUVKJXQWi38ZpPLX/oSXdel9NrX0rnxxqka/BvfIJPPk7oulmFg1etoGxukJ048q+fimWBGXl09eCGQaKLEjuMYz/Pwj7+SbphlpbbBRmeE3koody8xzhts1RPa/Wn9Y1nguCaPbHRxDYO851Ct1IiSVC04mqbJ0tKSUlw/25jVPy9ezIijFwGSJOHRRx+lVCpx/Pjx5+wG/LiMo89+lvmPfITKffcR7smzdV3nl3o9vn76NK9NU175wAPsjEZ4msZx4HKS0AcMoAiMgOsAJ4q4IU25fTLhkSThI4uL9KpVCoUCuq7z50nCtUlC2TT5YhRxLk0JhkOCIGCcJOzoOrGuUwhDEqAMPAyUdV2FIF+fz5MzDBqZzFQh0+9zwjS5I4rIA682TT6RyRDbNoZlUfB93u37rJomWpJgpCnXD4fcUyphuS5EEX4UEe3ZedI0JQoCBnvExsLCAplMRgVnO46jwqcHg4EibTzPYzKZ4Hke+Xxe2Zj2K5HCMFSTdckQEqXJ/s5n/X5fqXL2E1dxHNPtdpUiSSxIlUpF2aAkZ0hIrlwup2xO+0OnNU1TLdFrtRqtVkvZEiVsUIgq6bLn+74ioCQfSGx18v9+v6/URY7jqMBsIYNkciDnU1RHmqYpYsg0TUqlknpwSYaSZESJaqlUKqn307RpwLt0IZPgbsuyGI1GqrtbHMdqdUkse5lMhnw+j2mairgBVDc8CR0U0klC0UVBI8cI07BGXdfp9Xr0+32Vk9Tv9ykUCorsqlQqilDaf05EBSS5SEIkappGo9FQndyEuBMSUIikfD6vjl3TNJrNprINyjUm16KQcEJwbm1tMRqNqNVqXG6n3Hd5jVwux9zcHK9+5Y8qhTQgJd3ruJagoZGSY6QIQk3TyOfzym74bNhP9uMgJxTyOT0oXLp0id/6rd/iC1/4AkmScM899/Arv/IrB/b+M8zwfMLVUv/on/kMxsc+Bg8+SKjrPGAYrFkW/h/+IYNcjsrqKs7f/R0P+j6uphHU6zzieZwHTgBj4CzQaTTQt7cZpynBhQu4y8t03/pWwkJhan2uVgl/9mexz53D8n1G1SrW8jLD4XCq9jUM0kyGku8TMr2n9tptisePk09TJtq0gcPle++lt7aGXipRzmTIBgF2q4V+8iTGYED4wAOM3/QmEtMkShKyUUThm98kPXSIOAhojMc0v/xlXM8j43kYjz5KLp8H28azbWqjEdnRiCfSG70QSIIZXlg4iGe+1J7b29t4nke5XKa3eIJ2pkytEtFPL+Bv/SOL2QzfDSIqBch50A80XM+k1x4zCRPyRkrs9ynmctRqNcbjMQsLC5TL5SucBs8WZvXPixsz4ugFjDiO2d7eJooiTp069aQ9rweBxz34Ox2MT3yCpFKhH4Z4aUo1DOmaJlYc87bNTU6MRlyMIpw4ZmKajNKUxfEYHfB1nYtAzzQ5EwREQBtwo4izacqbOh0+Z1lMLAtN1xl3OtyfpozDkPsmE7J7Vi3TNFl1HDqjEUYU4eg6A01jF1jVdZq2raxD4zBEZ5qDoycJ5Siiu6eCaQOHooi871MHUt+nACRAGMeYmoaVyeBoGqVsltA02bRt3joYkKQp/TDkom3z6HgMexYrx3GUekQUI0JoCEkQBIFqy14sFtXKwv58IOk8JiSK2Ll6vR62bSsLkah7hKiR4G7f99V7ysRcApAlF0eCsqWNr67rrK+vqxBnUQO5rqvyhsT+JVlOYguL45hyuawC96SjmRy7BIfHcaysUGI7KxQKJEmilEKioIKp+kSIscFgoM6/2CL3K6LkGIRUkW2LRUs60gnhImSZKKlgmlMl5ItlWSrjR4gseV9RKIlaSayDQtqJ3FgykRb2rANxHDM/P88jjzyiSCjJSZLAbTmf0hEtiiJlX8zn88paFgQB4/GYubk5dF2n2WwqglDCvMfjsfq/XCuVSkVlRC0sLABTaymgFGFpmiq7Yi6XU2SU5A5JhlY+n6dWqzGZTKjVati2zWAwIEUnTMDSr7yHpKQIiQQw0fPKRijHJ0qn52Li8VysuD0VfOITn+DIkSO87nWv4y1veQvvfOc7sSyLt771rZw+ffoA9nSGGZ4/uBrrn7Rc5o+6Xf4W6DNVOVcA/VOfwm42GZsm/eGQmuehRxFrOzssAqmmUXYcJsUij9TrTGAaYj0a4W9sMLrzTvRXvYrx3nO+u72NFYbkSiXSUglz71nl+z7DfJ6x46BFkcqNdOfm0BcW2DVNdi9dot/v0x0O0UcjUtum1euRrK0R6jrWpUtUPA+v38c+f55kbzFpVK8TXbyIXS6r56Q9mZBdXeXIyZOUjh5F+8pX8OOYoFRi/ehR3DjGXV+nVCqRzWZnhNEMT4gXkvJL6jOJXZBGHpubm5w4cYILF2w016Gc9xj6PoZpkvgRWV0jWytzZKlIqzvBznscPnxYORMWFhZUrfVcYFb/vHgxI45eoOj1ejQaDdWS/bksmgRX3OyHQ1JNQ8vnSTUNO02JAZKEnqZxfb/PJIq4MY7JA3ocYwL/r+vyyiCgr+uUk4RrwhCXqW3NA2JNgzTlncMhNyUJj4xGfN2yeNvuLlaSEAcB37cs/lzXCfaCkx+wbW6MYx4pl3lZu83J4ZAc4Goan5ufx4kier0eFzWNh5OEE50OQZpipyk/sG0810XbC+vWHIfM3sTVThKWx2OOpimrpombpqzZNhNgLpPh5Y7DpmnCaEQ5SWjpOqHnEYeh6mAlQcxRFGHbNmEYsr29rSxek8lEhRgHQUCn0yGXy+E4jiIFAKV8abVaSh5bKBQUESAZQ9lsVqlmJOhZFEii9un3+8o2NhqNlCVM7GLD4ZBKpaLCmyWkGVB2JlG/5HI5tre3SdOUUqmksnIKhQLlcpnhcEiSJMzNzSnyLIoiRYQI0SJEUKlUUiSHqE0AyuUyzWaTXC6nSAwh5OSzIGMl3d+y2axqOz+ZTFQA9n6FldjghDxJ0/SKgEDf95VdUGxZQhZFUUS1Wr0iH0qIpxtuuAHbthXZk6YpKysrKrsoiiLa7Tau61IoFOj3+0rFtLu7q5Q/knfU6XTQNI3FxcUr9rVUKgFQrfF294gAACAASURBVFaxbVsFXpfL5b2P6ZB2u60e5tKZQ/KNXNdV1r/JZKJsfYPBgFarpa4LIfMA1YmuUCioa0R+3mw2CYJA7ftwOOSL99v82+r0HBna1J72nUtjbjnikDGn5yxMTR4t/By2ZSu1kYRzP5PAxieL58rj/5Nw6623cuutt6r/v//971fff+ADH+ADH/jAgezfDDM833C11j9pNssH935UY6qiXgGKFy5g76mwx4DTbNIGOHIE6nUSx2E8mRDU6/h7r18fjzGBJd/H+Pa3CVdXGZXLcPw4zt13o2saectiMj+Pc/vtSmXsLy6S2dzk0KlTuBcvMmy1CLe28DQN5zWv4XC1Ol0Empsj0+0S1uuESUISx/i1Gug67cmE7V6P8OJFjJ2dqTV4OERrtYjqdZJSCS0I8D2P+N57uff73+d0s8lt5TJ2GJKGIQNdp9PtUmRaJ2QyGYrFIsVi8bk6RTM8CbyQSJtnioMiS4rFIltbW2qhM5vNUi6XCcOQlbOv4pF//hIZy4AEOqMIUpvtVkQhH9AdjBkGCTe94l+rxcP5+XmKxeKBKnd+Emb1z4sbM+LoBYYoitja2gLg2LFjanL2TCAT/6eCx/19rQaLiyQbG9jXX4/5wAPoSYKWpsSahpemXNA0XsZUtaOnKSOgF4b8357Hbw+HVOOYR02Ts1FEypQ8StOUfJpy3nVpZrOcDQJu6vU4nyQUooizwGvDkLlWi9+1bfr9Pt/J5XA8j7cOBiyMRmwyDdwuRhEfWFvjg5kMcZpiui5fKhY5q2nUHIcNXeeGwYBroggDuNu2Geg6WhjijEa8LYoYaxoLScKh4ZCv5HL8Qz5PkqaYnQ5Rv8+DccwEII45EQTEkwnDyYRDkwmvjGP8KOI7acrG3viJAkbInFqtpkKlpbPa3NwcgCKcxLYmgdUysZa2mb7vk8/n1cRfLFjNZlOpf0S9A491HhNbmmEYlEolFfocxzHtdlsRBEIsuK6rSCrJHhoMBmofxd4mneHm5uZYXFxkY2ODKIooFAr0ej16vR6e56lgZlErCeEgBfHOzg6GYbCyskKr1cIwDDqdDpPJBMdxFEklli1N0ygUCliWpXzi0uFNQp0zmYzKRRJVzMbGhlIq7e/EZpom1WpV2eckYFrXdZVh5Xkeo9GIarWqVDISlD0ajRRJFwQB6+vrKhdqc3MTy7LodrtKZbS6uqpIMV3X6Xa7iuTRdZ25uTlFznmepwrywWCgFGNiZRvshbOapsn8/PxjK8Z7ZF+4R27Ka+Q6arfbKgDd8zyVAyX5UZI/VKvV1NiKsknGNY5jRqMRo9GIYrHIXesp/+UbA37+GpuzixZoGi9dzpCkEMSg6TqJbpOmU5mzhJKLIu25wkGuuD0XmQQzzPBCx9Ve//QuX+bdpsl3o4j/Cagzbcwx9H12ikXi8RgNOAfsAvleD21pCfvyZXymi2VDpprLMXCEqfJ66HlM4pjgwgX0hx/G9jzMyYRCp4P18MPg+2i3347ruiTLy8STCa0LF1hqtXAyGeJikVLw/7P35jGT3Od956fu6q6+z/ecmXcODociKVE0RVGXpaVPKZYM24t1ggViOJsNNgkSZOPE2D8SBEqCBAE2CYwg2l0v4mAdQ5ARb9a2DNtZyzrNSKREjkRpyBnOzDvv/b59Vt911/7R/fvxnaxkiRKvEfsBGnO8b1d3V1XX76nv8z0CZn/4h/R/8RfldTV97DGy7TZ6EKC//e3od+4QxTGzMGRy+TLdUmk+3BgMML71LRLPwxsM8A4P6a+uMkpTRk8/jdtuM3BdAuYMq1/8wAd4z/Y2NeZsau34mOzuLhPLov3II+jr65im+X3t+2Ut681epmmSzWYZj8fSk6hQKDAejymef4x8f0RmZ0B60mc6itHTgEEKigF7HY8rW03qjQbjyYTV1VWq1err2vvAsv95K9cSOPohqTRNcV2XbrdLo9GgUCi8Ktv9QS4Op1Hp9CtfYVCpYN66hWNZpJkMSZIwjiKMIKCYJGQNAz2KUJkbVqvAhTBkK0nw45gYWEsSwgVoYgAm4AGHuo7n++wGAe8aj1lNEt632EYM/FIUcRRF/LplMR2PCdOUzGyGlqbEmsZaHKMC74ljVqKIkwVLp1Kv45fL7C7S2/arVZzplEEcs52mGIsb9/dks+Q8jz1V5UBVKQYBszRlsPCksdIUbzYjm8nMgY4oIlFVvDDkkqry055HoGnYScJHk4TfzWZpJYlk3YjkqtMeRoVCgVqtJtlJ1WqVdrstvXcEQCOoscIfSZhP27Ytb/YPDg4kACWMjnd3dyWDZzwe02w2pTH32toacRwzHA6Bl72BBCtFPG8wGLzs5xRFDAYDAMmqEcleURQxHo/JZDLS00cAM2maSimX2I5YbIIgYHV1Vcq+BAOnXq8ThqE0xxYSuE6nIz19RCKf8MMJgkCyi5RFCl+9Xmdvb09GJQu2kGATCS8jsY8FcCSSbsS2M5kMzWZTGomXFg23SLs7OjqSLKLTZuUi6Uy8lpjMiuPqeR6z2Uwml4l0tMFgIKVbjUZDbk8AgNPplEqlQq/Xo9VqEUWRTLvL5XLkcjk6nQ6j0YjpdArMF3jR3IRhKE0eT0sE8/k8Jycn+L5PrVaj2WxKCWCj0aC9mE7rui7ljdVqlbW1NSqVCq7rcvPmTXZ3PP7yo5eJ4gQUFcdSUQDXA900yGgxNf8mHee9ZBbfKQEg3mt1mp21rGUt65XXvdL/uC++yMfOnCG4fZsxcAHYAZQ4ZkPXmTAHhraZB4FYrks2DHGZ9zni5wnzQI/bMPcImk4JXBddVTHDEHU4JFxs2wT8r30N7eQE5dw5wjDEGY/Rjo54CVB8H63VYqooKL0ewaOPMlsMOxRFIanX8RYJruGZM4TjMbGqEjsOgQhmuH2bSadDbFlMTBPSlGg2w18MiLLZLMUowrBttNmMZ7a3+S8vvki23WbDcdgaDDi7uUkpkyH30kvw5JPSs6l6yrvy9awlYPXmqjf6eLzazKtSqcTBwQHZRbKyGOS2222u/MiTbD/9R9xSVY6DmEQFxYfuwKdciHhkq0JwfA3nzHupVqtyUHcv1rL/ufdqCRzdQ/WdLgxBEHB4eIhpmmxtbb2qX0LBbPlBJm7Bf/yPaP/iX5DLZNAUhaBaJbl0iXA2o3X9Ot00JR/H/GgUIbJOVOYN0SXg2LI4iCIeCEOMJEFjDgYdAB1NYwPoTqeMwpBGmjJIEn6M+cmdLn63A/w88Anf58kw5OcNg1VFoQCU4hgfGC9+9xeB/1Ct8hP5PD/S6ZAeH/OVXI7n8nn2VRVt4bMTLLxjbNsmEwQohoG1YPsYtk1W1ykUCnPWSpKwDTyYJJDPkyYJn8/naagqj/Z69H2fSRCgKgorqsr9msbRAvCo1WrSC0j4FwnGi9jXs9lMgimDwYAgCGQ8ujBThvnNv+M4xHEs/ZAmk4k00RbbFSyd4XAogQEBkHQ6Ha5fv06pVMJ1XSmTEvIl0zQl+0jIz0QM/enPIbyD8vk8mUwG13UlfTdNU3kel0olaYSt6/pdBt2CCQPI5wmmS3GRpCeSw3RdJ5vNcufOHcIwlMwtwVhxHGfubbXwlprNZhJkElJAAcA4jiMNxcX+NAyDo6Mj+dqe59HpdLBtm3K5jK7r8j3v7u5Kj6dGoyENrkW6meM4EigUMgshNxN+TuI4C/8pAaAI/6ErV65I/6TBYCDT3I6PjxkMBpK9NJvNKBQKrK6uoigKuq7Lm7DTwJ0w3hYAVL/fl75NrutKsA+Q6WuFQoF8Pk8ul2M6nUogTJxfxWJRMsniOObd734358+f54XnniJjKCRJTCGjIi4n5UxKkEaQaqhKKgG7JEle14nbq03Vfr1vipa1rHut7vX+J2vbjJOElXqdD4xGfHk04tc9jwgoAcVWay6/Zw4SlYA6ECUJpmGghqF0eNOZB4ZYi78HcUyUpkRhyAwYAi5zgInFtjL7+6hJgjqZYA4GOIvnxottFhdy/OSLX2Ry332Ee3tkDw/RkwT9vvuwz5/HWl2VHnVinU3TlDQMCRSFiWUxGY/xfB8zl6P86KPzG9tCAe3FFzFPTrBMk8F0ymG9zjibZfzNb/LVXo8vdTqUHIeaolAYDsleucLR0RHVapVGo8H6+rqUWC9rWW9EvZrgjGEY5HI5ae8wHA7lkLiQUSk5BsWigzNyGY3n9ydF4KEzebKmziiMqNVq1Gq11/07sex/3tq1BI7u4UrTlG63i+u6rK6uvuZJQq+0kiTh6OiI2q//OsbKCqpto0ynaHt7KLZNurGBUShgtNtc2tmZNyG83BhFwBZQm04ZMW+GckCGedOUB6w45inLohKGFJMEb9E0hottiMYpv9ieAXzIMHDTFCNJGDCnTovUtj8AVsOQs90uH+j1cNKUrTjmA8Mhv7mywp/U6xI8EBIu0zTZtW3ePRzOgbEoogx8cSHx0TSNKE15plKhp2lkgHaS0LcsskmCOR7zsKZhxjETTaMfx7T6fXphKD1mkiSRSVYiEv50epoAgQAJ9IiFSbCKstkshmGwubkpAY7j42PpbySSt0ajkQSSBFgQRRGdTod8Pi8Tx8QUULyOkMgJbyZxQz8YDKQxtwBvhOeRSMISANn+/r6UMAnGjkhqEx5LAhQDCMNQsnCEcbPYX8LzSfjyiEW5WCzS7XYxF0bowhNoMBjIzyRAHSED03WdcrlMp9ORzCoBggDSb0j4OzmOQ6PRAMB1XckIshYJfYIBlcvlJFtGAILiddfX17l+/Tr9fl+ykabTKf1+n1KpJOnNqqrS7/dlkprjOKysrNDv9yU7SsgMReqZ0NOL+PpSqYSiKFy/fl0yrwQ4Zpoma2tr0hxcAD+CASZYZCIdwzRNSqUSx8fHHBwcUK/X5fES/kPCpD1JEplad+PGDfb29njHO97Bu9//JIb5AnmTuR/2qTLVmAiVafEBaUwuJHKvV72aEgpxzJe1rGV973Wv9T9TRWHP9wmOjihYFucyGczdXSLmzKMVoM18IJZl3pMcANPZTMrTdOYStYR5jxMDGcfBm04xgETTCBZ9lLr4vQzIgdxoOCQZj1GYg1MKECx+9g3gYU1j9eQEPZfD6nTIqSpWr4d+8ybmT/4kyhNPyOt+HMcS8I/OniXXarGSyVBsNHBmM+L3vY+gWpVs2fzWFuH+PtPhEEtVWctkaLVa1FZWeAyYjMfcmc2YaRqd42PSKGJ3d1f6DxYKBVZWVtja2uLChQs0m80liLSse7rK5TJ7e3uyb+31evPeznLQNBVDgfvWC9w8HHI0gjCBd12o0h56rLztHZRKJelb+XrWsv95a9fyaN2j5Xkeh4eHOI7D+fPnXzPEVkzcXmn5vs9gMJg7/RsGhCHqN74BQYDu+wSPP47leawkCauTCaaiMAMpUxOAz2jx7zVgsPh7D/CZ07B7msahafJbuo4ex4RJwv8axxwnCWtpisq8OTIUhWcrFdZLJXTXxZlMSFWV7TSlkCREzBuxJuBqGlu+TyFNeUccA6CnKX91Z4cvjEZcX4APgAQfXFXlDzMZ3ua6pJrGZ1WVFxegjgAuVFXlNnMpmG3blJhfgNfHYy4PBnR9n9UkYapp/N+VCpXF89vttmRztNttucisr68zHA6ldGk0GsmUhtlshu/7jEajOTtqAbZks1kGrstwMCBKEsIwlNI0YVpsGIaMhD8NSgnfJCEtEwbctm1LYGAymTAajRiPx9Jwud/v3yXrCheAmGCICA8msQAeHx/LFDlhEr23t0exWJTpbOL9CDaV8BASgIQwo46iiHw+j67rUj4mEr4EQDKbzRiNRuTzedmINhoNoii6K4ltMpnI1xf+P4JmnMvlZDKdeC3DMDAMA8uyGI/HWJZFvV6HxXEvlUo8/PDDDAYDbt26JdPIhK/Tc889RzabRVVVRqPRXcCgkAmKND3btuVCLthUKysrJElCsVhkb29vfh7rOisrKzKaeX19HcuyODg4kIbjtm2Ty+WIokiywqIokiCT8GESRtSCRXY6gW88HlOtVhkMBpKFViwWmU6nUop4Wu7W7/flTeDXv/71Obj3SJl/9HNbEjeaZ6opkMLUbBBl18gvTN7v5RuI5cRtWct6ZXUv9j/TZ59ldzajGgQoly9zwfP4gGnyfBCgMfcruskcMNKZD8pM5oBSBJwwB3k05sCSAjiGgWrbqI0GcRRhmybmrVsozHukCnPWtg5EjQZuvc70xo251H3xOzPm8rcMkI9jBlFEsLNDdzAAz8NhPngzf+d30KdT7AXrKJvNUigUqFQq5FdWsM+dw9nehjAkvHiRsNEgc2qdHU8mFM6epbIYSIg1on3zJv7xMSv5PBcNg+M4pv3YY5ws1iPRywwGA/b393n++efJZrPU63UuXLjA1tYW+Xxe+ux913CENJ0/ltfce6Z+WA26xfBPsLHF4DVRdILaFVJuUc5bPHquxKefdwkCGIQJ1WaTbPO89Dy9l2vZ/9x7tQSO7rES4MFkMmFtbU3esL9ZSry/0WhELpejUqmQfOxj6B//OAQB6DrYNmq7jfd3/g5+kpD5J/+EUNNQo0h6G8XMm5k7msZYUXhnFGEpCvuaRjGOIU1pAYGqYicJLy48WqqZDC1NYyVJ2FUU6mmKBfxJs8lv5fPMJhP+Y5LwP8YxJtBUFELxUFU2dZ0XajWsNOWBBcNiwryBU5OEH3NdvroABnRdl2wdwzDomyYvLYzuADYXbBARQy7AI5GcFgQBjq7TiCL+S7lMcHSEGsesqCoXw5B2FKEtEtME0AHIJK7JZAIgI9hLpZJsnsbjMf1+H9d1pcRL13XuUxQuHRyQBgFGJkN5dRU3jvmWprGbydBbGGTbtk0URZTLZeIFeNbv9+VnFbRaAe4IQ2jxEGbVInpefHZhBCimDMKQWrCE+v2+lJZNp1NpwB0EgZRICXNoAd6INDrBVBKa7zAMGQwG+L6P78+zaITHj2AIic8g3o9gJZ2cnEh2jfD0Ea8pWEOC2SUALfG5HcfBcRySBTBXLBap1+uUSiUKhQLtdpt8Pk8Yhnz1q1+Vn6fVauF5HmmayvS42WwmpzvivBIsM8HIymQylMtleRy2trYol8tSajcejyXIU6vVpK/TmTNnGI/H7O7u0mq1pA9TPp+XoJTwxcpms8xmM4bDIblcjo2NDWmMLY6tiFMWDLBWq0WpVJKfwzAMyT4SSXDnz59H0zQmkwn1ep2dnR1c1+Xk5IT/4w+P+e/f0+B8M4uqKJwecOXCNtmwDeTfsGvg0hxyWct6fete7n+aacoFw2AE6IMB4c/8DFeOjmh9+tPMgE8stpHlZYaQzRzcyS/+nWHei8SLf+ezWSzTJHv2LOVymZxpMjk85MXZTEr9LwPxAw+wd+kS2ekUu1xGeeEFxt0uE6AGFJibdCemyWBjgxPDIDo5YbJ4LZ85kJVcvQqzmRwWdbtdjo+PJbNZX6Si5RwHexF6IGTxYRiyv78v+4lisUjBcahEEe0rV7jT77PiOJxTFFbzeWYPPIDhOOzu7rK3tyeDNaJF6q3ruty6dYtiscj6+jobGxvk83ny+byUehcKhbvAJOXWLbQvfQnCEDQNbJs0nyd57DHSZnMOKJ26rv+wAhbLeuX1Wp0LpVJJsvIrlYocfMaZDQzbRlVSMo7FuTI8tFVlNAm4Yk2oWfOQmzeqlv3PW7eWwNE9VJ7nsb29TalUYmtr63WRZrySidtsNuPw8JBiscjq6urLEpZf/mWST3wCZTgE2yY+cwZ6PYgizLe9DbvXm9+Q87IqxQMGmkYJOBNFKMChojBQFFaAHUVhmKacNwx+M5MhWdyY+prGx4F/qGncBxxpGp9sNPjdXA53MGB1OuXDnkeqqvwXy+LhJGEchvRVlWPbJtZ1pmnKs45DrKqYcUyqKESqylhRKOg6xWKRKIokWyJNU3zfl14y4kbfdV3JSqlUKhQKBXK5nAQ7+v0+se+TnpyA4zAuFnl0NuNsmlKbTPj5NOWPs1m+YttECy8ZaXKt6+TimPZkguv75HI5mQYWRZGMqQ8mE9ZPTqiPRuSrVa64LntRxJVcjsv9Prd8n4lhcP9wyIamYSoKB6rKs4UCowVLKAxDKXfzfV82YcL0sl6vU1gYWQoZUxzHnJyckM1mpUeRbdtUKhXMRbpdv9+nXq/LKUuxWJRAk/C9GY/HuK4ro9xFQyhMw4VszLIsfN+XMi+xL+r1OkEQSDDjdJqc8EmaTqcoikKn05FyK+F/pGkavu9LKZTYnmhghZeTkLwJUE+AQQLAGo/H5PN5bty4Qb/fl8CPYBIJidfpZDrBjhL+SeKzwdx0XBid93o9uR9VVaXdbtPv96U8rVKpsL6+LtlVQiZ4584dCeBUq1UURSGXyzEYDJhMJrLpFp5H4v8EiOY4DrZtSxBU7A9N0+h2u3cZh29ubkqgT5hCrq+v4ziO/D6sra1x8eJFgiDg6tWrvPDCC/y1/+2r/Od/+AGU0wMpBVRCqsOvMVu9cs83HcvGaVnL+u51r/c/keuiRhG3ikW02Yyp51G9dImLwLdObSfLHBzSmQM6DrABDBUFfyFTzwJGpUJT07Df/naiM2fkMOnowgWcl14i7/ucz+ep/viP454/j7G3R3E6xWy1mBkG9soKK66LliRoto1ar1PMZik3m5hnz2LeuIE3nTIEHtB1TMchPHuW3o/8COPxGN/35fo5HA4lw1asZYIJms/nyWazcl0Wg7N+v48/m2G3WmSLRaaGwXMvvcS1yYTS9jaOabL+Uz/Fw+9/P48++ij9fp+dnR0ODg4YuS6+6xIqCt1ul93dXRzHYWNjg42NDc6ePYtlWezv7KDfuYOxWH9ze3s4m5vku12sq1eJHnwQzp5F/9SnSEslCEPStTXiD3zg1TuJfgjqXjVefrXrtdgPYvgahiGlUon9/X1OTk7mctPyJWz/NtsHfTKWQpKqRFFKzlY5G78IvPdVfz+vdy37n3uvlsDRPVSGYXDmzJk3nRFamqa0223G4zHr6+t3RZ8DoGmkH/wgPPccNJsoQUCqKKRxjP0v/yXqbIaymEKlzGVq1xWFs2lKMU3xFIWOqjIA/q9SCU/TeFengxpF/IdMht+ZzVifTPifdZ0V3+cq8I/rdZxCgREwCQL8wYDCZMLfnkwIgMi2WQeeK5dpjEbsKgqZXI7NKOIonyewLH6j2eSvHR4yUxQCRQFF4frmJlfW12UkvIg/F9Ib3/claCFi2sMw5Pj4WKZ7CeaNAHmezmZ5YjTibdksZwAvSagAShTx302nFIFPLdguge+zaZr8wmyGGccomsbXz5/nGwsgYzKZcHx8jK7r2KbJEwtZ3iCKeGccYykKaaOBfnzMS2lKNB7TKhT44GDAddtmR1U5kyQY/T6/VypJEGw6nZLJZOh0OtJ3SUSoCymcABDCMJyDYnEsARZVVWU8/WnA4bT/kpCutVotud8sy0JRFDzPI5fLSbmZYPjouj5nhS2MyjudDjCXZAkmzsnJCUmSSFaNpmmcnJzI45YkiTxny+WyZIlVKpW7/Jym06n0/Tk+PiaTychJa7vdlnItIekzDIMwDCVz6fDwUII/xWKRQqEgwZTxeIzjONRqNQaDAXt7e9LPSphPC98owbwSfwoATFVVCoWClAsWCgXJdJpMJmxvb2MYBo7jsLOzI4/tcDjE931UVWU8Hksp4mmZpLgZEB5JMG+iLMuiUCiQpimtVksChzAHFofDoTT1tm2bg4MDkiTB9302NjZQFIXxeMx0OsU0TS5duoTnefzFv/gXuXbtGo8a30BTlYVM7a6rDpnxLRLzu8gS7oFapoosa1nfve71/if86lfZrFRIhkNu7O1Rr1QYfvGLuMCtU9sLWZhZ8zJ4lAWUTIbemTN4isKs06GczVJ+6CFq73kPpuvi/ef/zLcODlgrFDB++qdxcjlWLl1CsyyM4ZBGNov9zDPY2SzO+jracIjzjndQ6fdRVldp5nJM9/aYvv3t6I0GW3/5L8OnPkXJNNEdh1mS4D35JNpjj8n+RoRWCCm3AJGGw6EcvLiuKwMfTNOUTF0hBR+fOcPJSy+RDofE4zFumtLudtGShO1PfQrr619Hf+ABDNMkl8tRtyzKBwd0BgPGsxnTtTWmpkm/3+f27dvoi1CS+y5e5JEwZC0IiLJZRvv7dD2PaZKgfPObWKpK/to1yuUy1WeewX7kEdQLF1Bv3EDpdODHf/w1OJuW9f3WDyt4JYbPpVJJenMKpjnTFooaM/AD8pbFw1tlqkWLlVKG3PQWk3SeOnsv17L/ufdqCRzdQyX8TF7P+m4Xa+E1kMvl7poC/tfPi3/1V9F/5VdQ9vchSfA+8AEy//7foy6YRyItRLRoeUUhSVO+ZZpMkoSpaXJG17lcr9MHmt0uPtAbDtHDkH+0eO4x8AhQGo34p4ubX5gbKz80m6FFEa5lkdF1erpO1fd5Kp/n/b6PFkVcy+f5crGIGgT8Sa2Grij8N+MxYZLw+XqdG4vkKeFxFC/o2KelWEJaJl4XkJR6cVMtwAld17lTKDC0LB4/OmKUJDSjiK6iYCUJ0zjm/jjmR8OQi4MBlqaxZhjs2TZeJkMlk+HdnQ57lQqtBUhh2/bcP8bzaE4mfH0hbbrquvyYqtKLYwZpSkVRGBvGfMKpaZiFAo8NBthhyINhiNntcjVNaek6bd/Htm1ms5mUUQlpVL/fl741gnIr0sAEA6dQKGDbNoZhSLlYmqYcHh6Sz+cZj8cyVSwIAqbTqZQ3FQoF+bpCGijS4oTnkjCfFrI04UMkwAvxXJFgIUyZNU2TrBrh11QoFCQAKIApARiVy2X5PRRePgIkE9uaTCYEQSAZVMIkXPy/2Ob+/j62bUvGUqfTwXXd+fm/8GUSrDUBCopUNgEaCeNQ27aldLFYLFKtVlFVlc3NTbrdLmEYsrm5ieM4HBwcSGmg8J4SEkIBwrAFbgAAIABJREFUPu3s7EhpwOm4WEA25sViEU3T6PV6BEEgj/HBwQE9wSK0LPb392m32xSLRZrNJr1ejyRJsCyLbrdLq9XCMAyZ5Cb2x507d/i5Dzvza0KSoqjKKfRIQVFUlNgD9c1livtKazlxW9ayvnvd6/1P9Lf/NvbBASthyPG73oX2B3+A1e9TZS4XE1Vl7ndUBpR8HlPXsfJ56tMpWjbLDNCShPMLfyMbmPzu73J7OiVfKLA2mzG4cYPkiSfQLAvTNOdrXb+PqWkYjsMoCChXq8SuS+f++2ncvk0mDKm/971MP/IRsoMByQMPUC6VqH7lK1iGgfoX/gLJhz/MbMEEFtct4VsYBIEcWohhhgidEOv76bVLgEn21hbrzSbmCy/gt1q4vR6tRZInikKh36c5GqHu7eEFAdPBAK1Wo762RmY4pHdywmRlRa6Rs9mM27dv89TnP8//ORqhKgp6mvLYxYs80uux2WjQSFPiwYCwWqW3s8PtTodwZwfn6lVWVZXiZIK2v4/6Uz8FFy5AofDqnVTLuifrtZKqidAZgJ2dHXzfl2Euse8xUWMcDTbrOS6tFjFtg7WqM5dURjMwlv3Psl7fWgJHb5H6QVzwv90FUySaDAYD1tbWvm0U9l3PazaJfuM34PiYNJuFf/bPQFVJzp9H3dmBKEJNUwkeXUgSQuCspvF8Pk/RsrBmM9ROh58eDNgJQzTgr4chVeZTuUoc46Qpx8ClRWKTt6CaFwoFTE3DGo8luJNNU3zgqY0Nntd1VKDn++gLJkUul+NLhQLPisQxkCwSYRgtUtMEAGAYhgQzPM8jSRIMw5Dgku/7chInzJAVRWE/iphkMvy3UYQJGGmKE8dspyn16ZQPpSnPAVoc88E0pQN0F9OJRFGYBgFjwyCTych0rjgISIF6rcZJq8Ukk8GNIs6oKmkuRzkIGJbLrIUhimVxLggo6jr7aUouinh/EHDWdenn8/yR4zBbmHp3u12ZohaGIZPJhF6vJz1wstksgAQOhA+PYKMItpJgCPX7fQzDoNVq4TiOXDSFJ49IVhM+B4qi0Gg0ZMqYkEgVCgVc15XsFWFq7fu+BJrE+xBgkQBLBJgjgCYRYx/Hsfx8gpEjAJv/2oy60WhIAET4LIj3LlhTQrYmpkyCKSRMQIU0QkgPz5w5I32YhLxOgDmCxVUqlZhOpxIQKxQK0ktpe3sbz/MkyLO/vy8NvIWBtpDZFQoFCQ6Vy2XJFBLpNcLXanV1lUqlIpPeRNIeIJlfGxsbTCYTeQPheR69Xo80TXEch3K5LOWHjUbjruvH2tqaZCE9t9fhnVvFuZHpqctXrGdRdRv0//91516rZeO0rGW9tvVm6H9mv/ZrmL0eQRhy/hOf4HlVZVyvM+x2eRC4ytzX0QbuY26CPfE8CpubWKpKKY45CUOCW7dITZOJ55F76ikKmsYzrRbKdMoK0MtkmHkexcXQRXgWYtsUgL3RCBUoKArlUonsxz7GaqmEaVkcTCaMjo+5desWFy9eRP3oRxn/7M8yBqI0JTw8lGxaITEW/YwYColQDOF/FwSBfAyHQ8bjMYPBANd1cV2X4+Pj+droecS9HspoRGoYTMZjdtKUb7RalLa3+dFHHuHi2hrq4SGdWo3eom+p5/OsPfAAcSbDZDKh2+3OhzSjEe3nn+ckCBiORnzt4ICnZzOyv/3bVG2btSRhdWODzXabtcmE9cNDcuMxw2YTr9tl/JnPwPXrOBcukP3oR3HOnJEM6R9W9suyXt8SFhcbGxvS0zOXy9HpdObfmdQkGPfJ5fM8dHmdYiHLu+9voNkF0Kxl/7OsN6SWwNFboH6QRe7bPdf3fQ4PD8lms2xtbX1bR/xv+5q6DhsbKMyNplNFQbEswre9DeP550mTRAJHATBWVYphyMaC+XBjY4OVyYTpZMJsYXY8Bt4HvAewFsDTeaAF2JkMjUZDsileOj7m0PM4F4akcUyaJHyyXp83M6fAA/H+BaAh2C7CRDlNUyaTCWmayueI5wm2kbi5VxRFSrkEsyOKIjKZDIZhMBgMZCz5fi7HZw2DjX6fs2HIDdvGUlU8oB/HhMzTVbpJwrk0pWPblKKIS0HAOz2PZ9OUW4s0L9u2wTTp5HJcTBLWt7ZwooivZ7O8aJrEQUCYyVBOUwqKQjEIeHA4xFAUSsCxotA3TXzTJNQ0nogiPnvKA8df+CqlaYrruhwcHDCdTsnlcpI9k81mWV9fp9/vS1aKkDl5nielYqIRFUlrg8FAggoivU3sJ8GoEklswrB6NptJhhDMk9kE3Vckrgh/qTiOGQwGKIoifYLG47GMthcpLgIQms1mWJZFsVhkMBhI4KRWq3F4eChBE8HisW1bAjPiPAHklFVEyAtT7SAIWFlZwfd9XNeVBtlxHEugS5ici0VWyNg8z2N3d5ckSbhw4YJ8XrFYRFEU7ty5Q6lUkkyoRqMhwbJSqSS9ibLZLNPplGKxyNHRkZwKF4tFmeAm5H8C8BIsOnGeCz8LVVVlrKxgFR0cHEgJY7fbZX19nUqlIm+8AHkjIb5r6+vrfHbb5309jfurImcRQiWDppl49/3iPU/ThmWqyLKW9VrWm6X/iQB9bQ1lOJzH3CsKHaDeaKC0WjwEvMC8p/kWsAXEYcjR4SEr2Sy5Rx9l03UZqiqhpuGmKZMw5PYXv4jS7/NuoA0ovj9PSCsUGA6H3Lx5c56gubaGf/06uW6XK+UyjqKg/cRPkAL7CxDM933iOKZer5PJZOj3+9KvD7iL8SXWPUVRpExfgCppmsq1SAwgAClJbzQaUm7teZ5kCk+vXcP93OfouS69Wg1TUTgMQ74xHPL05z9PBrhsWZQHAxrnzlFRVYquC3fukLtwgdL6OufOncN1XcbjMW9zHFaThFKhgBoEbCsKV0cjTg4PuR2GbI/HKK6LMRiQu3qVsqJQNk3OrqxwvtGgoWloQPinf0rnQx8iTVM0TSOTyUjvJmvB6lqCSa9dvVlMyl/tY9xutymXy0RRhOu6Ms02DMN5srFWQMFlNZviqNAsO1SrTVj2P8t6A2sJHL1F6vuduJ02hxSGzr1ej7W1Ncks+fNe8ztV+DM/g/HlL89NsrNZopUVkigC16W7YGGous5BNstnymVm738/8ZkzXPnjP8ZptchaFlPfJ6uqlBUFJY6JmYNOBoCu85PnznHUaDAajZhMJkzSlH9TqfAhyyKTpuzm8wzrdUoLloRt2+TzeTRNk4wYwzDo9/voui5j1QeDAblcjkwmIxspIUcaj8fSRyaXy8lELsEqEdRukRRm27bcjud53CmV+Ke1Gud7PYrjMftpSkZVeczzWF1ZwfM89n2fYpqyMZnwcBBwU1FoJgm/4Pv8lmFwtEhgUxSF/1fXeTCOKfo+R8BLYTiXBaYplm1zEoZ8dDLhuTimretcCgKyQKwo5MKQWRwThyG+qjLUdWq12vwzn5xwJptFyWS4Op1yudPhXC6HZ1k8PR5LEGV7e1vS1IVfkZCsCT8hfzhEiyIGi5Quweip1WrSOHs2m1EoFORUczabybQ40biK1Ddx3gkDaXPhjSCo9IJVI5gwwpOo1WpJ82cBhAiw6bQ/U6PRkJ+hVCrJc0NIAgqFgpRi+b5Pt9uVzDLx/gUIJhbN3d1d8gtGV7FY5Pj4WFKW0zTl4sWL1Ot1ut2uPM8Gg8HcKHWReqZpGrlcjtFoxOc+9zn5/kajEcfHxzSbTbLZLI1GgyAI5PsyTRPbtun3+/T7fQ4ODigWiyRJguu61Ot1KYkTE7FsNks+n5cMO8dxaDab7OzsEEUR1WpVNkH1ep18Pk8QBFy/fp3pdMpXvvIVms0mly9f5qWXXpKgbBzH5PN5HnroIQC2t7f5tS/rfOQnfpRmpYCh6xQzCvWzD5KauVd8PXszlvDqWtaylvXa1Bvd/4i0UcEY9T/0IfKf/zwNRaFt23iWxXnfxwcOABcYAMVcDvvSJWb33Ufy+ONsfeEL9G7dYmLblA2Dg9EIdTjEBF7k5TTaBGh0u8wyGTY2NlhbW8M0TXZsm03XBUVBuf9+4tVVkoXMvlAoEAQB5XJZBl8IAEhIuUUAw+kSrCIx0Dm938S/T4NHgrEtbpDFYzabEVYq1N/5TpIbN/BOThgtBg+j7W0CRaGZyxENh3SGQ3pHR5y4LmSzpM8+S/rlLxOtrqIWCpimSblcpthsEg4GHA+HBI5D0mhw6exZLj/8sJSOT599Fj+fx+/1mA2HTMOQ/U6HL/V6lA8Pqb74IpVajUySUK1WqVarGJMJdq+Hns1ira2Ru3OHfBiSPX8e8/HHMXM5uTZ+1/L9ecpbNjtn1i7rLVGnrQD6/T7j8ZhmsymtFobDITPPw8iskzbqZN7xIUrve4JeTiPfvLjsf5b1htXyaN1D9f2i3a8GSh4EAYeHh1iWxfnz578rQixf0/PQ/tW/QvnCF6BSIf7VXyV9+GGUxx/H/Qf/gMIf/RFxkuD+0i9R+I3fQL92jVKaoug6w2oVMwjoXL7M2558ksTzKAcBV2YzHkgSThSFW5kMM01jOhoRahpKkmBpGollkV00MoIhFAQBAfDZBZhQyufRFk1MPp+XaVgwb4ZyuRyO40iWjPDKKRQK5PP5u5K5fN+nWq2yuroqNf6qqnL+/HnJEhGx9EdHRxK8EFImTdNoNBpS+nZSKvFiv08QBNQch7DV4uJsRqxpnJgmn8zneVcYkg9DCRTpccwTScJ/Whg0i5j7ZzUNMpm535Cqoixi4kXzlk6nzNKUbyUJHvCOIKCUJIyThOpsxtuAW4rCcCHZWg9DPjgcErgu1VyOj8xmXE1T+qMRtdGIc4rCZ0/te0fXKUURoaIQLBYIwa55FPjwYEDe8zhJUz5ZqbC+iGgXLJjj42PCMGR1dRWAfr8vmUNRFElARsjbhD/QaQ8jwQQTiW29Xk9Ks8TxyeVy+P484lR4DQkTbmGGXiqV6Ha7bGxscHR0RBAEVKtVZrMZrVZLAj1CviXYM+PxWKacCUmjqqqSobS5uSn9okQjXigUKJVKOI5DpVKRrKFbt25JY/ZSqYSqqjSbTQzDoN1uS6Pu04wuTdMYjUYyTU18bsEims1m0hh7fX1dAn9xHLOxsUG1WpUgWLPZxLIsKpUKrutKUC0IAsbjMZlMhkqlQrFYxDRNjo+PKRQKjMdj6X91dHTE9evXuXPnDhcuXKBWq1Gr1ajX6zJV7rRh+SzSCI0SeiZDWiz+0DRNsJy4LWtZ30vdy/1P+rnPkWSz+H/zbxJsbmI++ijK3/gb1D77WVrdLu7jj1N66ikeOzjAYw4AlSyLddtmf22NEXDt+eep3rnDoNcjAm4DRrHI+c1NlJs3mTIHnDJArVDgXfffj/ngg3S7XSzLotVqUWw0KD7wALlcThp5C8B+PB5TqVQol8vcuXNHSohFiuppIOw0o0iARiIRVPy/uI6Lvkd4IYn1SAQ/iBK/FwQB7oMPcnR0BEA8nXLmm9/kTBThJQkzx2Hyoz/K8M/+jJOvf51uJkN/OGTQ7xNls3D5spSve57HzDRRFkOrdBEyIXwWFUVBS1M0XSezskI+kyFptUh9H1/TCPp9jg8OaJdKKKYJmQyZIKBweEjOtrHimNx0irG+jprJkPnCFzD+9E8xnniCTCZDsViklMlgRRFWsYhRLMrXVRQF8/nncX7v99C6XZJajekv/zLJmTNy34j+8jSz/ds9lvXa16vJehJS13q9zmQyod/vk8lkpH+qkHWK75HlFFk7d5nS+iX8MCS37H+W9QbWEjh6i9QPctEThscrKyvkct/7BStNU7R//s9Rf//3oVyGO3fQ//pfJ/zkJ9FXVnDf/na09753zgQZDtGfeorCtWsYUUSsquiOw9ceeoiTWo1fuHKF9N/9O0rtNn+maeSThIai8CeLi+zbVJVCmhIqCjpwmMmws/D6CcNQ+uUAkmEhmCGO47C5uSm9iAR4U6/XOTo6khIh13VlClaapjJtSkhyRCKCAC9ElPxpZolgp3ieR7VavcuUOQgCacLsuq6UOyWWxe+Vy6zk8yjAMJ+nYBhoJyeogwH5bJYkTSlEEaGmcbZalXG5gEx3Ewlwgg0DkMvlOLYs3jEe09I0PE3j+SgiO51ycTJhLYo4Aoppyi9OJvyryYQngS4wAqbjMQ8zt5+ZAXvAA4bBVy1r7j8Qx3x4QWH3goA/VRS6pommaTTTlJ8bDnFUlX0g5/v8FdflDzIZRrzsJwVw5swZgiBgcHyMNRwyiCLCxWcRKV25XE4aZAOSPdRut2XzpWkapVIJ3/clI0ckp4n0OLG/BPAkmmdhQG1ZFru7u9L4Wjyn2+1iGIaUdwl5mfA06vV6jEYjstksxWKRbDYrWTnCI0rTNGazGVtbWzz00EO4rkuv1+Pw8FCytgSAJnyRxGvt7u7K757jOFIiWavVOHv2LDdu3GA6nZLNZudT01M3BEJmIGR7uq7L9+j7Pu12myRJ5pHGC8aRSMgRflHC1Lxer0tQKk1TarUa999/P8888wxbW1tS5qYo8yjla9euSePudruNYRgcHh6yubkpWWEiwU0AZT9MtdT4L2tZr2290f1PmM8zOj5G/bt/l/Rf/2vcUgnzkUdQH32U+v4+o1u36Ny4wcrhIW9PU54FDuOYrSeeYOOhh+apbc8+S+v6da4zZxXlgLObmxQvX2bddTFdlwNFIYwirly6xGM/+7N8/eZNmYY5HA5lyubZs2fJ5/MMh0MGg4GUJQtmrmVZdzFKxUOwpcXQRgynPM+TIBEgr9GqqsrQEF3X5Zog1mmxfouB3Wlpm2mabGxssLKyQumjH0VfsHCH+Tyq52Gvr1Ntteg4DrN6nWwQEDgO43e9S/okCm8lAUgJabv4exRFqGfPkuzuEtk2qa6j5POE4zFmu00ymxEXiyhhSLC9TXr5MpO9PSZJgqkoOJqG0Wph5nJkNA3TMFCvX0epVjEsC206xfrWt8iqKgXbJvP44xQeemjugTiZ0Pjt30aZTknqdZROh8wnPoH79/4eiePI/TQajV4+h2czlMmE2LZJFp6G363+PMBJAFR/3s8FqPjdtvNag1lvBoDs1XoPwgZDURTp/Sj6fdH3aouBsGVZ2LbNQw899EMJFC77n3uvlsDRW6C+3wuNMD5O05Stra1X9OUWr6n+8R9DrTb3N7IsaLdRn3sO9SMfkRMVAPsLXyD39NN0LlxgNp3S8DwO77+fqxcvkptO5+aL164x0jQGUYQL+ElCrtXif8/nyVQq/KXpFCeO+erKCv/PAw/gFApYUSQlTGEY0uv1ZNS6MLV2HAfXdWUSmGBqtNttGW0vzImFsa8AmYTPi7jY5/N52QSVy2XpUzMajRgOh7iuKwGkMAyxbVumZokULRGNLqZyhmFgVasMFyCYruuUikWGpok2HlP0fbwgwEhTvrq4sc7lcti2LeVhIqVM3ICLfa8oClctiyAIuOj7jJOEL5XLPAmEccyLmkaSpjieRzMIaACWqpJqGoQhom2xdR2iCGtxjsRpSur7/GQc4ysKQ9smBZ70fT4zGhHYNhmgDpzYNkaa4hsGdd+n2e2i2TaTNOX27dtUq1VGoxFF1+WD/T5xEBCEIZ8FpgtvIEF71zSNyWQimTS6ruMvEuFyC/q4AA09z2MwGGDbtoy7Fw3laRDF931p2q0oimSUZbNZ+f+CQSZARCFTHA6HeJ4nwSh42RvC932ZMFYsFnEch0KhwGQyodPp8Nxzz0nzb0VRqFQqAHclr4lmfTAYSHmiMEcXcknTNDk6OiKTych9JSRhYRgyGAwoFouSeTSdTqlWq5TLZelBoSiKNLv+5je/SbPZlDcFME9aG41GcttBEEgZYKVSkWyqZrMpJXdnz56l1+tx8+ZNmby2trbG6uoqs9kMJ5uhZAbUTI98RpP7VoCJPyy1bJyWtazXrt4M/c/RdMq2rnPB85g99xzVX/gFhsOhvL47d+7Q3t0lPneOi0HAtw4O6OVy3C6XebhSwfM8VsOQfjbL785mAHw4m+UDKys8+ff/PtH99/PV3/xNlPEY67772PzH/5ij4ZCDgwOSBcO4Xq9z5swZNjc3WVlZkZ5GyUKCJfoaVVXp9/ty8CAYSaJfUFVVrrdiAGAYhgSHxO+I5FQBDAkfI+ETBNzFTgqCQO4/0zRpNBqcPXsWwzAIkoR+Pk+4YA7Xcjm8d76T+MYNzjkO+WqVqesy+9jHSLe2pNRnMplIQ27RA4lhovh8U9sGwyA6PkbLZEjW19FeeonU90lWVjDSFD0MSU0Tr1wm6PVI4phxkhAseia/08GOY3KmiRUEGMMhhq7jPP88kWEwyWRoTafwe79Hsr2Nms2iT6fYX/sadqPBehCwlc9TbrfJ3rmDef486kK2VK/X573g7i76Zz4DcQyqSvRjP0Z6/vyfex4KBtj3+xAgnmBKf6+P7/bdeKWPKIqkL+X3A4Cd/k6+0SX8jFZWVuj3+3ieJ8NORBJhLpcj5zjMZhNm0wnnz27QbDYZj8dv9Nt/1WvZ/9x7tQSO3gJ1Wqf/vdZgMKDdbmPbtly4XmmlaUqazaJ43jw60jQhTUkzGXmRFwuTcfMmqaoSpymGZZHkcuSPjhg2GlQqFb7xjW/gTCZcCUM2NzZQh0MeHI24Yhg8mc/zyfvv539ZSIOERMZU5gbXruuiaZqMJS+VSjKGPAgC+R4cx5E0UV3XabVaMhUtjmNyuRyrq6sUi0WiKKJQKKAoCvV6Xd5Ai3QRcSOvaZoEIgqFAs1mU96gi2mbMH8WzBTbtu8CIwAsy0LTNDzPYzqdztkslsVntra43O+jxDFfzmRoKwqFBWtJJIpFUSQbOwHUiWZOURTsQoGdQoHDBdPJ8zyeAR5dyJwyisIMmCkKj6YpNV3nsTQlXjBWEk2jpCicVVX0KOJLikKsKGQBMwxpKwppEGCqKg9EEaVej9Rx6FkWM8/Dn80w83mq2Sy542Pue+EFLhSLHHkeR7UaTrkMQcAHp1NGts3EtsHz+Mko4vfDkEK9zmg0klIqYVwp4pvFcRcGluKza5pGsVjE8zwpU3QcR05RK5UK/X4fmLOXyuWyXNi73a70ARJNtDCk7nQ67O7uSiaQaLBVVcVxHJIkod/vS3BQTHZXV1eZTqey+RbsnXK5zGAwkEwc4Zs1mUykD8XpqbFgS00mE3k8hYRMeCjpui5vKNI0ZTQayTS6YrEoz2HBjhMTZnF+6rouTcyPjo5wXVdGMQt2VKlUYn19nb29PY6PjwmCgHe9613k83kKhQJvf/vbcV2Xa9eucf36da5evcrt27fZ39/n/FqZX33PlL/yP5zD0FQS/ohwOKZnffAVX4fe7JUkybJxWtayXqN6M/Q/9ShipGkYqkq90SBfLEq/vUKhgDYe41kWaBqpaXKlXOZrwyFHR0dcuHBhHjKgqhSAdyxCIy5Np1y6ehXj4x9n8Jf+Eumv/ArZxc/MZpPbt29Lxmen06HRaEhDZ9d12d7ept/vy3ADwdBRlJcTQA3DkEwhEaogJNiCtSp6OQECnWb0CCBBVdW7mNqnw0YEy0isNYIJ3Ov15I2yqqqSBSWGcLmNDap/62+hPvMM3myG+bGP4dx3n9z/p32lfN+X6aij0Yher8dwOMT3/XlPVavhX74spdRerYbx0ktzBpGqEpsma+Uy9UKBSbVK+8UXccNwHvCSzaJVKkwAbzplWK0SnZwQTKews4OSy5GxbfKGQebwEMV1SU2TTLFIHEUEoxGzMGS/3UZvtzF+7dcoVKvkajXCd7+b6OGHyVsWhd//fZJiES2XQw0C9M98hnB1Fb5Not/pc/8HBUyGw6Fk6/+gddov7M8Dqr4TEPWdfv56gFmi9/uvWXiv9CHSgz3PkyEyYkgs+s2cpVINbzJtn5Az4Wcq17C2P82o+v5X5Ti8mWrZ/9x7tQSO3iL1vTZOwn9EURS2trY4Pj7+vmjeYrFKPvIR9I9/HATb4pFHSN/3vrsmV6qq4jeb5KOIZEHVtMOQ/soK5u3bZPJ5Pv3pT1NaX6dxfExlPGZrNsOzbQbnzrE+m/E/3bnDv3zkEcyF/EekeA2HQzkxESZsgonRbDal6XKlUpEa436/Ly/kzWZTMlJqtRobGxsymjybzcqfn5YMieYrDEN5Qy2kPKJJq1ar0jMJkM8RZtnCTFiwaATwIEyZxb4LqlWer1ZxHAcznRtme54npXan2TiqqspGSTSAIr5WePOIhflpTWPNtnm/5zHRNMaWxdpsxjt9n1IQcA7oqCqHwDBN+aJl4WsaHdvm2LLmXkqqSqyq1KKIoapyJQxpMpe0lScTHppM+DrwkK5Dv4+RJBzFMVfjmLd5Hk8oCuthyG+pKsV8nnI+j+I42AtJFCcnKJ0OZy2LKI655vvSq0gwjcbj8TzJbDLBGQ4Jcrm7pFKqqnLx4kWef/75u8ytAelxtb+/T6fT4cqVKwwGA0ktBqRZqGEYGIYh9eqCdSb8fsT0VTTfokE1FpHJ9XqdlZUVOSUVPkkCZAmCgE6nIxuLWq12l/RRgFbtdhvTNKWvkpDoOY4DzFlKKysrHBwc0Gq1pCG3YNsJ1lW73aZUKsnv52AwkGCrYRjynBGSP0G9FobawlxeyAgPDw9ZXV3la1/7Gu12mzRNpUwwn89Tr9e5dOkSN2/epNPp8Cu/dB/r+ZclDxoRHH+ZOMwxdu6ToOcP+jg9pTx93Xo9S4CYy1rWsl6beqP7HyOOKUcR3oMPEj78MPoiqdNeyI2G1Sq5RX8SahqPZbO0Mhm6rRbHu7vU1tY42dzk5OCAd9o2L47H3ADWy2Wax8co//bfkvzcz9Hq9djY2JintO7vk8/n2dnZucvfLwxDdnZ26Ha7VCoV7rvvPilbFuuZYNMKdrK4ToqBVqlUQlEUyd4RgwWxrwQLSawJArgRaxYgWSxiaDOdTu9aR4W0TkjFJ5MJrVYL27bZ2NiQqauTJ5+Uw4xXHuLJAAAgAElEQVTTJd63WCMLhQKrq6uyzwmCgNFohOu6dDodTk5O5KBxkMnQOTpiurtLahjYmQy9O3e4lCRctm3WJhOcUolZpUJX02hfuoQbhiSWxVR4ZaYpUa+HF0WgqgwPDxl1OhhBgBZFTLe3Sep1tMNDUk1DDUNM28aIY5yXXiLz7LMETz3FrZ//eXKZDNZzz+GsruJkMtTzeerTKeadO2QXbPVkcxO+k5Sy10MJAtJyec78f4Pq+11n+/2+7HFe7fpegSch5z/t5fWdwK7vBHAJL8xKpcLBwQFpmkrZf7vdll5kZvtpzpY0vAgqWdhazaEd/hmxn1n2P8t6w2sJHL0F6nu9GAyHQ1qtFo1GQ948f78XEkVRwPfRfud3SLe25qkRgDIaQb8Pp2REcRzTe+970b/8ZTLPPIOZyaDnctRefJG/enKC8vTTFAoFuqUS/+nRR3lnkuB85SscmCbqdPr/sfemQZKd5Z3v75w8J7eT+1ZZWWtXV3erW6K1ISGQ5gK2bGOD7YhhtYAxnrHNtR13jE2Alw83HOMwzBd7iAGGuDeujZcZYzCY6wFsjA0GK0AsElpQS73Vvua+Z5793A+Z70s1CK42jySoJ6JCraysypMnT73v/zzPf6EbBKSaTTpXr6JWKvJmVsi+kskkQRDIuPeZmRlWV1fJ5XIMBgNKpZKUHG1sbDAej+UNuDC7np+flzfrg8FANnJM05Sbmq7rFIvFa1gjlmVJ4BOJRKRnjTDFFibA5XJZAiHRQGq32yiKItlGgJwCplIpCTrFxE5QXgWzJpVK4Xkeo9GIUqlEr9ej3+9Tr9fl6wrpmwB+Rz+/vwuHWXNd8qaJBtwEbFoW/xuTBJekqvKArlNWFDKRCA8HAe0p5VzQTz+t67zK85hzHF7qOCwqCjcFAVVgF5gPhfijeJyw67IElDWN20yTNDBSVeYdh7vbbb5k20S7XSqdDgfTSF81leLuWo3k2hrJZJKzjsPfxOM0BgO5UXuexx2Wxa2uS3hnBz2b5UulEg2QzBtx3sbjsWTfiOZcOp2Wn8UXvvAF5ubmaLVaUgJYr9elt1Epm0U1TYIjfgq5XI5isXjNuRW+SYKmLNhHApDncjkJUHzfp1qtAt/2qkqn05L9JKbh4lo6deoU4/GYfr9/jd/E7OwsyWRSNtOWlpYYj8ey6SX8oIRsTVEUKW0TMszhcMhoNJKsN8HE03VdsuMajcbEhHV6jILJpGka+XyedrtNv9+nUChcc76HwyHJZJKFhQUcc8grz8+gqteuParvkgraONP0w6cK2p7NqaTjOOzv7z8tgCa+dnZ2JPPQtm12d3cnTMlwmEgkQux7TJL7/T7vete7JPPst3/7t7n55puvec7HPvYx/uqv/gpN0/iVX/kVXvnKV37f93Zcx/WDWs8H/NMeDBgHAUXL4qDToT1tqAipceSuu9AvXGBhaws/CNhXFF7U73Pv/j6PPfwwN958M4qu4950EzlFIf+5z+Hlcny102GlUMBuNHC6XVRNY35+nq2tLdn08X2flZUVFhcXMQyDvb09Op0OCwsLlEolKZM5Kj0WMnfRUAJkKqlIORX7i1g3jzKTxI12t9uVv0+wLMRQQeyhg8FAJqSKAYYICxEYrdVqSVau8GcU/kWxWOwpywjFHhyLxSiVSpw+fZogCOQ+V6vVuHrbbbQfeoidtTUu7+6yubHB1y9epNZsUgKKe3uUz58nFwSks1nCJ07A9NjFmq/fdRfaY49h9XoovR5Ot0u/20VLJhnGYrijEd6LX0zguiidDvZwiLu2xvZohB8EuI0G2kc+QmR1lezFi2QuX2Z2ZYVGJsPV4ZDQBz6AEQTEdZ1ENkvs9a8nOU38ExhGvfdetPvvJ1AUAsPA+7f/liCff1rX9fctx4HxGAwDXkCNgCfLyup2u5MB7TRJ+enUzs4O1113Hf1+n3w+Ly0KDg8PWVhYmFhlhAKcBzq0bRMLOFmCmK4e459pHeOf576OG0c/JPX9FgXP8zg4OMD3fZaXl6+Z3CjKU6d5i1Lb7UnUaLH47Qc7HZT9fYJKRd60A3iqyrd+/uepra5yLpPhxo9+FDuZ5HB9nZs9j3/f67HbbmPt7/O+QoHrbRvT81Ach9iU3WKUyyyeOcP8/DyHh4e0Wi1mZmZkYyQej+M4DnNzcxSLRdl8WVpaol6vs7m5SafTkZKhlZUVNE2j3W6jTaPoe72enG5lMhl6vR4wAZ2Cwtrtdtnf35cTOAGiEomEBD1i0RN0buHNAxOQJWLSE4mETAYTC6yglI/HYxzHkXI64UWjKAq9Xo/9/X3pNbO9vS39bgSzRdM0yuWyTJATXjzdblfK3DY9j8dDIZZUlfOtFslEAmswIDMFiLqmseL7nLQsXqrr+OEwn8rluDo1GW94Hn+rqrzesiaxv0AbSAMRoA64uo5z7hx91+Wuep35fp9uOEzCtrkSBCxrGnOmiRMELA0GLHa7fE3TWAuFyADrngedDvOqyinHoTo9x67rshqJ8FLX5bLnEYxGzAcBLw2H+UQ8Tq1WIxaLSfq6YNREIhHJUstms2SzWTqdjoxMnZubkyC4Wq0yGo24KZHgp3d30X2fnqLwP2MxWpEIkUhENoAMw5CR9sI36/DwkGaziaqqkmE0OztLtVpFVVUp/6rX69LvQFxjS0tL8loRHlzhcJjRaCRlaIVCQQLybrcr/bQcxyGbzcrEnXQ6zczMDLu7u2QyGWna7fu+ZNhtbm4yPz9PZOqJlclkGI1G8kt4RhUKBc6cOUMkEpFNr1QqRavVYnd3l1gsxsHBgZRNjkYjeZNyZi7F3/7K3ejX4M7pNAwfPzqRR3wvUPGvVd8JsHZ3dykUCk8akAkfj6NfX/ziF9ne3pbXwHvf+95rfLbe+973sri4+F3H8uEPf5g77riDt73tbayvr/POd76TT37yk/L79Xqdv/iLv+ATn/gElmVxzz33cOeddz4jwHtcx/VCruca//TCYRRVJWaazLouVi4n2UzRaBQrFkN505vwPY/MaET//e8nZhjM+j6PDgZsPPggM9Eog3AY5VWvwolGqYRChCIRsG0yqko9k8GdNvoFM2d3d5dyuUwul5O+e77vs7CwwMrKimzUfGcJNpFYuwQ2iMVi1wwkRKNI7HGWZdHv9wmC4JqgiOFwKH0cBbPbNE3q9TowCXMQPoTCK/Lg4ID9/X1UVZXMI3GDL+TThmE8aywJRVHkjWs2myWXy6HdeedEtv3YY1z94Af5u4MD/nuzySawAUQuXED3PCLf+haReJxoOIxeqaAfOa5QEBCvVkl2OhiADqj9PunxmOjyMlYigZtM4hgG7qOP4g+HJBMJNMvCjsXwxmP6jz5KdTRisL2N+a1voSSTqIkECc+b7Ne6zvlcjqRpEr3llm8HwIzH5L7yFdKLi2RSKSL9PqHPfpbgnnueVXaJsraG9qlPoVgWQSqF+7rXERzF/cclh3lBEMjhcTQapdlsYts2c3NzdPfXMB75v/nqhT3uX2tz16kU//UdryAWC8Mx/gGO8c/zoY4bRz8E9f02iMFgwOHhIYVC4VmlgiqKgpfJTPTXw+FkCmFZE4+juTkA2dARU7HBaES7VALDwPZ9kjMzXOd5pJgsXDaguy4/btt89dQpXrG1hQ9oqso/nD+PM10YqtUqW1tbjEYjcrmcXLgEe0JMnGBiUPzoo4/SarWkxEuwcCKRCPV6nVKpxNmzZyVDQvgbibQOAZpEIpvYCIIp+yYIAgm4BNX7KJAS3jfCfFJMw8TPiklgZNqIEBRyIcUTxyUmZsKjSSzW6XRa0smF2bGYRoqEsSAIZLNA0zTpJWDbNolEgrHrMvI8zto20UKBuWaThqZxczjMXL/PVzMZ+q5Lyvf5iU6H3VQKXdc5oSj8tONwUyhE0XXxgISqovo+HcBUVYaeR2d/n1EmQ9YweGu3i64odAsFxprGectiGA6zFYlw0XUJd7vYikJEUUjo+oTBBvi6TjYaRZs2XHzfJxQEOFP2k+t57I/HnGo0cCsVFEWRRtOj0QjDMCgUCrLxUq1W2dnZYWlujnNzc1zZ26PaanFbJMJPNZuMbZu/GgzoxOP87GDAku+TC4WI6DqVIOCDqRRqKESv1yOTybCQz1PJ5XDjcS6trVGtVuV0uzs9DuGxFAqFcF2XWq1GuVyWvkjJZJLTp09LD6Nut0sul2NmZobNzU0ZjVwqlQiCifeR+OxFOkulUpGTntnZWTlBEuw2cc0Js3YhUxNsOGOa+NJsNjFNk1gsds2EPpvNkslkGA6HFAoFhsMhp06d4vDwkBtvvFHGWSeTSekjYhgG2ANem7kPTQUIEA0j8R8/nGKUvfE5oVN/51RS3GQ8k3r7298OwG/91m9x5swZfv/3f/9J/dzb3vY2+dqe58lmtKhHHnmEm2++Wd4ELS4ucvHiRc6fP/+Mjve4juuFWM8H/HMmmaQ3HjMIAvxiEcMw5OBpPB5PmD2qilsuExwecjoS4VDXiR0ckAS2gZBtk9B1nMuXiZ4+jb+7izYe02i1cF71KnpTzzshhxYy7VKpJPeQXq9HOp2WyZzfaVItvoR/XjgcljdygjktGkVHpcgiMELTNDmgEoME0UQSwQamaUorgUwmIwceQp7veR6NRoNOp8PZs2evaQ4JuY+iKFL2/2yXYF8LKZ2maQTFIivXX89/LJf5pRtuwL7vPh5RVS4HAYfb24zKZQJVxbVtFNPEX1mZrNH9PsHaGma9Tt1xOABiQBxouy6KaeI1mzBl/waFAureHn3fx4lGJ+lt/T4RwyBbKFCcmSEYjbB0nb7v02k2efTxx2kDHwHyX/4yueVlEonExPJAVUnWahjZLOVMhnwySc51SeXzpFIpOTwVLA/B9jrKEBn3+5jVKophoITDqI8+iv75z4Oi4L/61QSzs0Q++lHUrS2UXm9i3t1u4/zO70y8TUWNRmCakEpNwnKOVhBc+9wnqOdi3z9aT7eBDBMJaKPRIJ1Os7OzIxuogh2+tLSEM2rjfO39/OUXH+ebV+vkU1H+26/9G65bmvhLHeOfSR3jn+e+jhtHPwT1RFMzz/OoVqs4jiOTK57szz7ZCsJh3D/6I7R3vEPe3Hu/93swBS2i4SK088IfyFleJhaJoO7uMhcOE0xlbqu2TSOfZzWX47+srrIxM0NiOKRpGBxEo9hTBkgsFsN1XTmlEula/X5fgqmlpSWZmuW6LoVCQXoLXbp0iZMnT5JIJGg2m5JlYZompVKJSqWCbdu0221SqZRk/uzv71OtVqW+PxwOE4/HZYPJcRwSiQSWZZFKpUgmk9JsuFAoSJaIeK4wmRwOh2QyGRl37jiOpHkL4KfrumSrCF8B+HZDpN1uc3h4KD2SwuGw9KLRdV3G0QvpkTE12BbNqb5l8ZlMhnPtNlnP46FKhXoQMKuqqOEwSiRCIRzGsixmHYdSJkN3PObHazWsSIS2olAIAmzPwwuF0AAfuJxI0IrFCE1f+yuqipXNcku/D8MhYdvm4ViMfBDQm6bNeUxYWf1cjpuCgHAqhWlZFH2f9WKRgm1LZo0XCpGwLFKWhe955IFv9ftsbGxIc2rB9MpkMlKa1mw2J/47wyGvunyZ0+UyvSDgq5rG/354SAiIKAp3AO83DM64LnooRE/XSeg6t45GLJbLbE7N2u+KxXj5zg7q7i4dRWG0sEDi5EmwbW7Y3KRYr9N/7DHua7XoLS1Jo/RCocC5c+e49957pfStWq1KU3dN02i1WtTrdQn2BMDvdDqSOSW8jkajEdvb2+TzedkcLJfLDIdD6vW6lBmIqXG73SaTychGZL1eZzweMx6PiUajzMzMSLZau91mYWGBmZkZ5ubmpBlqOBwmk8mQz+cplUq4rks8HqfZbJJMJonFYpimyY8nHpo0jRSQ3SK5EIUYn/9VAvuFQ4F/svX9UkX++q//mj/7sz+75rH3vOc9nD9/nnq9zrve9S5+93d/95rvDwYDksmk/H/Bcjuu4/phrOcD/lG7XTLA+Pd+j71kksGUaVMsFtnZ2aHX66GqKtVqlWQ2y3IiwYndXdaAJeCbgOn73BiNYjsOhZe+lGahwFwigX3+PEPDYGdjg9tvv53xeMxgMKBer7O4uCgT4Q4ODuQ6LNjewitRsJ6PSksEHvE8TyauAfJxwXwWjGghkR+NRvL9CL89cUwiWS0cDjMzMyMHVkK6LcyH4/E4s7OzJI549vi+LyVt33mz+ExKDANF+INooo3HY9nQMnUd/S1vwbvvPqhWOXH33SwYBndtbtL78pfZiERoD4cMHQe3Xqd93XUMRiPUnR3CMzNEQyH8gwPG4zExVcUJAqxwGPfECZSTJ1Gn67+2uIhWLqPv7KDqOvZggLq4iDUeY0YieL5PEAqRjUZZXF7GuHKFw6UlNqtVtms1hlMLBJgMRbu+T6jRIGi1UIFwEKAmk2j1OrFYTHpZCdlUJpPBMAy5L0fHY/jUpwjiccLRKMrp08T+8i9RgZDjEHzmM1i/+quE7r8fz/eJZjLMahqh++7DOTiASgUA9cEH0T796cngOJvFveeeiVzOtgn9/d8TeughiEZxX/1q/BtueNY+2+dLCdVCo9GQbG9hdVAulwmFQnztY3/A45e2uHLQJZWI8vafvIEbVmcmv+AY/8g6xj/PfR03jn5I6ij4GQ6HHBwckMvlJOPg2S4BuILbbsP5h39AOTiYUFczGfkcoacXbIq99XVuUlUyrRb+b/0W6i/+IkEohOK62NEoqueRdxyaP/ETrAAHBwccWBYAzf19IpGIBCONRkNOi0T0uohjdRyHCxcu0Gq1JEDJ5XI4jsPh4aG8Wd7e3qZcLnPDDTdIU2KhzRWeNQJE7ezsSIaTSHULhUJY0+MbDocyEjY/NbMWzA6R+JXP5+l2u7Tb7WsiYwWA0TSNbDYLIA2gRXTu0c81kUhICZNgWZ08eZKZmRnZPBNeNsKcWHgNiIaTaZpSqiSnDfE4V9JpaZAsKLfX9/tgWXRGI7JBQDseJ10skgFKnQ47wNVQiLTjcGI0YhAENMJhPp1I8P9GIoSmDTCxeazPz9MbDomOx1RNk6Gi8MbRCENRQNNIui73J5Ncb5oURiOu833Wkkk+Zxg0slnKikKlVCJVqxFYFuu6zhscBz0UouN5PAaUbZvrDIND4JHp9djpdCQDCUAF7pn+++uHh+SA3wQsIMEEhGWAt43HFDWNw0gEBSaAWlUpx+N4MzOsGAa3XryIYtsku11KQLjR4M/Pn+fHbJuZXo+1RAK73+euzU3+stcjdvo0vV6PUChEtVrl8PAQwzDodDoMBgPi8TjpaTKP4zjMzMyQSqWoVqsMh0PG4zHFYlHS+YXfRCQSkQDctm1SqRTD4ZBsNitfr1wuy2ZrOp3GsizpS+G6LgsLC4RCIfL5PMvLyyiKwvr6OqFQiHa7TSKRIJVK4fs++/v7RKNR9vf3ZbNS0zR6vR7NZpO5uTny+Tyz4S6l7vgJ15JA0Rnd+i6CeAnszhM+539lPZPJ4xPV9wNOr3/963n961//XY9funSJ3/zN3+Td7343t99++zXfSyQSshkKSP+o4zquH9Z6vuAfLZOhMDV+3t3dJTr1K+n1euxtbTFnWVAuM/6lX0J7xzu4DfgEkAO6QKrRYO/22ykWi+zt7dHPZkmePMnFb3xDMoPW1tao1+sUCgXOnj0rJWuRSIRcLsdoNEJRFMkmFscqGKUijVRM9QU+EM0ia5q2KqRlQgotwhhE40f4BY2nRuACT6TTadLpNDAJj/A8j729PQaDgWR+BUEgZWyAZAB9p+/S062jKaFHU53E+/R9n/g0aMWeDqLCiQSNaSpokEiQCIVQV1aIXrgwabgkk9j1Os3lZVp3341tWfh7e2wBNU0j6/ssVqvoiQShbJbgtttwX/YyxtPBjghw8ZNJlNlZsCx828bI5yk8/DC6pqFGIvjDIe5112FXq/jjMUajwWouR/nsWRpTf0V8n8g0LMQwDLSrV3FclyEwzGZxh0O69TptVcWbemUqR3CYiIPPbW2R1DRm5ucJjUYoH/84mq6jeh6zoRCR8ZjgQx8i3Ouhz85iNRrUNY2SbRNsbaFEIuitFrGPfhSv10Pb20M1TbT9fZz3vpfQF75A6P77CebnwbbRPvpRnExm8v/Pw3o6a4UYikciETksC4fDHBwckM1mcV2Xv/nzD9K6eAXHsVFQ+clbK/zcj54BjvHPMf55/tVx4+gFVM/IqBGk/MY0TRYXF58U1fCZTNxkJRIEp05918OCIVGr1WhsbvLGz3yGymBAOBIhtLiIdfvtWOvr+K5LtF5HCwL2briB0Stewas/9CEiDzzAIfDR+Xl8TePEiRPMz89z5coVSqWS9JWJRqNysiUmVSK9anFxUXoaiZj7xcVFms0mtVoNXdd58MEHpUdROByWzR3ByLCmG3QqlZLNokwmQyqVkkBkd3cX0zSlibZIZdM0TYK9hx9+WMa6R6NR2YRqt9usrKzIjd22bWl0bFkWhUKBTqeDYRjSMLLb7Urm0/7+PoeHh1L+JlLkBKgT8iIhhxOfjWg2CG+eIJgkYQlJn+d5+LOzfBl4ZbsNvk87CPhCuUy/3ycej3OQzVI8PKQVj/OtdJpGNMrnDIPdTAanUCDXakl6vKZpkqVyEA4T6DrDqWzv3pkZlg8OiKkq90ajnGq1yHY6PKJpxMNhsoMB24rCOBymmM3yyt1dFoZDLMdhxbI4SCapz81xUKvxlm6X3wHc0QhUlT8Nh/mC71N2XerAZcBIJMiGQiS7XXaZGIOfBJan124NGAKGrjMLbOs66fEYB7CBtViM6nCIbxhYh4dE63VSnkc/HMYMhTjbbHIHcO7KFYauS0bXMWdmSIbDJDodrqyvMz8/z3A4lI3KhYUFarWanOSapsnKlBJfq9UYDAaTqTFQKBaZmZlhOBxiGIaUEhiGIZl+Apjn83larZZkoxmGwczMDPV6HUVRZCrb7OysNFPVdZ1Tp04Rj8fZ39+XLKTDw0Oy2SyJRIJut0uz2WRxcVEmCgqACvAjP/IjFItFnFGX+Usf/Z7Lx+jWdxPEv+2X8FxT1p/tY3iqcbRXr17l13/913nf+97Hdddd913fP3/+PO973/tk7PXa2hqnj8RUH9dxvRDrBwX/BMEkSaxYLDIYDNjc3GTUaHDmU5+iu7eHrao05ufJ3nILyuEh5zsdEp0OG8DDMzNUzp5F/fKX0R96iIFh4K2uSpaJSAiLx+MyAfby5csYhsHCwgKANJMW0nkhPRPsIHGMpmmSTCal3+FR9qgI/3Ach3a7LSXSQmotGLOxWIx0Oi0la8LcWjCVROpsEAQsLy9L/OFMWebw9E2wj9Z3sorEvhYOh69hegvPqXA4jOd5UtoXjUYZjUayUSbX7FwO7Wd/FuOzn8UfDlGTSebe+EbK2Sztdpu1hQVyW1tcf9NNZM6dg/19BnfdxaBcxj7COBfJucLyYDgcYlkWzWZzIuMuFGBjA8eyUM6eJdZooHW7+GfOoM3MYPd6xG++md3RiF6ng/noowTNJr6iEOr1iObz5CoVZtJp4pcuYW1tMVJVBkFA79w5Brkco1YLR1EY6jq9fp/6/j6P7e5SHw7pPfggeSb4pwSkgKV0mvkgIFOtYs7OotVqdDyPg3CYVKlEbGuLkGlOmkWPPILT6RBJJlmMx1H++Z8xP/5xwp/6FGoohOm6nFxaQlfViQfqM2kcBT4o6tP/+We5Go0GmqZxcHBAOByWA75QKMTh4SGPP/owo0v/hBENcTAKePFqnv/jZ19EKDR5D8f459o6xj/PfR03jn5Iajwes7u7SzabpVwuP6U//KcDnJ4M4LJtm/39fQBueuQRctUqwfw8fjgMe3v0FxelpMmdnWWcTvPom9/MDX/yJ2S++U32xmPmRiN+vdvlv955J/Pz89i2LamKsViMbDYrE9D29/ep1WrYts31119PPp+XN7iAlHil02k2NjZYXl5maWmJra0teRMsSqRwhUIhGZl+VP/farXodruYpkmtVkNRFHnTLJojrVZLJpGk02lOnTpFs9mUvkQCdH2nvt+2bRRlktgmKOXCIFs0dEKhkAQ6gkIuPAaazSaZTIZkMikTS3zflylrggUlaOPitQQ4jcfjLC0tSeNn9/rr+Wq9juY47Pf7+J5HZDym1+vx4MIC5x2HhdGIka7zPxcW2JjKw4rTRpUwbRYyOVVVZUS8eL+9VIoHFhcluHvV1hY1TSOk69iqCo7DciTCRUWh0Gox1+9zceqnMDccEhsOaSoKuXCYm4FN4CAIiHse/9Hz+FWAKZD6SCTCFxcWwPPQHIdToxGngIGqUlNVTrgueUUhruvoisJeLMZFVeXHRiM0z6OrKHxS1/ny1haZbhctkyFrmiQVhZzvo4RCOKEQL/3610mZJou6zpJtc2FmBiObZTaf5+sbGxRMk3+XTKLcfz+G47C5vQ1Tb6C5uTnpxzQYDOj1euSjDr901zz5ZJTqWOcr20N5DSYSCe644w452RUsNnFNnz59msFgQLlclqA/HA5jGAbFYpHd3V1pwL69vc3NN9+M67pcvHiRZrMppRH9fp+TJ0/iui6Hh4fk83l6vR6xWIylpSV5zAsLC5O/odGQma2PoATfTp27Zo0ov/Qa0BQEwXMOnP41Jm7ihu3J1B/+4R9i2zZ/8Ad/AEwmbB/60If48Ic/zOLiIj/6oz/KW9/6Vu655x6CIOA3fuM3nlVpx3Ed1wutnk/4R4RlCDlxJpMh/oUv0NzbI51O87hl8ZJ6nejZs6j1Oj+Zy/E3wGA85tFSicUvfQnn0iVsx4F6nf33vx/vzjsJ5/McHh5Sr9dZWVmhUChIhsPS0hIwmb5HIhHZsDgqBTt6rrrdrpT3C98isTcDMp1TNIcURZHDCcE4CofDkuEshlViTxfsJTGUEM2o7zxPwgRbJL89lXoiVjBrIdcAACAASURBVJGmaXKQKIJDAImfRIKt67r0+32i0ajEIoI1JRhWwgvTuPNOxufOwWiEmkhgeR796XBx6ed+jtJXv4p5+TIdVcV805uIra6SmzbBHMeh3+9LKZ8Y9s3NzclmUiaTwZmbwz17VkrJ1Y98hH6xSMdxKGWztEYjkq7L3NwcsSkGsxYW8BwHp9/H7vc5HA6pdTrErl6lWChQLpUoeR7KY4/hKApuKMRQUbBuvRX7JS/BGo1o/9M/8ejGBt3RCB8IMxmYWcB+t0sSmEunmYlEKGxuEvg+0Xic+k03EQfSpkkkGiXabkO/T7fRwIrHKabTpD7+cZRGg/FoRO/qVZrhMFnTJAiHCTwPdX8f/e/+DqXfx5ifh4UF+D7XgDKqoh98FcUd4RuzOOWXgPbsmUg/nXXANE3JxLNtm9nZWZrNJr1ej0ajgW1Z6LtfwnYdVE3l1HyWn7l9gUzaAI7xzxPVMf557uu4cfQDXiKm3TRNFhYWnvIf0L/WItXtdqnX61QqlQk42d/HV1W0aZPD1jTGgwEPvOUtXFerkZ6dpXbbbajtNunPf55+JIKv61iJBOnxmBNTBs+FCxdkTHmlUpE0693dXTY2NrBtm/n5eUnRzmQy0p9oe3sbwzDY2dmRgOvy5csy9SkajQIQDoeluXUulyOfz0v6tJj4DQYD2u02o9EIQHotJRIJkskk8/PzErwIEGIYBpVKRcbBCmr2cDjE8zzpEeBNkzR835eGx77vk0gkMAyDVColAVAkEmEwGNDpdPB9n1KpJCdcopllWRaO40hgZVkW7pTyLCZyQgIoGCuu6xKNRonFYnQ6HaKZDM1mk2yxiK7ruK4rm033Li7SbbcZWxYpTSPwfTzPYzQakUwm5XRRyPrERFDQTYVZpjC8Ho1G7IxG5EIhhpqGOx7jOw696Xm0BgOUUIjc1MOnaVnMeR79wYBCKEQY6Ivrm4mHRE/XsRWFrOPwdiaNpW/2+3wqHuc3bBvD9wlpGvfFYuD7VEyTViTCQ/E4QRBwxrb5Rj6P6nnETZO5acqZoig0g4AAyA2H6L6PGgQ4ikI/keD+YpHzwyFRy2JuNOL+xUVGCwvcFYnwUw8+SKTTIRoEvMV1+fTWFlu33CITIhqNhoy3nyumedPNESwPdtsmmfCImwshvhZMWGvCh+KGG26g3+9TrVYZj8eUSiWazSYPP/yw9AYTzSNhXOo4DvV6ndFodA3YFk2oeDwu/cmEX9nh4SG6rrO0tESv1+PWW28lk8nQ6XTI5XKSMWX0LxI2q0+4RnjRAvap76YpP9fA6dk+BuFV9WTrQx/60BM+/gu/8Avy3294wxt4wxve8IyP7biO64Vcz0f8I4ZGwrMunU7T6vXoaRqu5xFVFHKGwcXBgOS73012a4ufGA5pHhywe/EiX/vGN3hJLsfYNHF1nb5lYTebRItF6vU6mqZRLBZZX1+nVCqxtLQkAzYEo1SwpMXeK/wURRNDDA5Eqit8Wy52tMHhuq6UIwumjpA0i6ZTsVgkHo8zGAwklgmFQmSzWWluKwZgRxlPIvTjyZpgC1aRaBgJVpHAQuI9iGAI8VpiUCXWYCG7E8xe13WJxWJS4hcEgfSdFLgvls0yng7eGo0G3W6X+fl50uk06qlTE2PzKVu81+vJFFfBPBN4TKSTijRVgctE486yrIkFQSJB3rbJp9NEFIVMv0/h+uvxFhdp+z7Vq1cZptMogGGa9Ot1eoUC4eEQHahHIlzq91kIh1lptSglEhjRKJ7r0nr8cWqvfCV7ySTt667jZLVKORpl03VRk0lWxmPirRZuLsdOKkXf9xmsrdEoFolqGlHHIXF4SGd/n16vRy6RIOW6tPf3saes7rORCHHHwbv5ZrTHHiM2HNK97z7817wGr1hEvXoV/YMfRHEclPGY4POfp+d5BK95jTTvFl+hUAjVGxPZ/RJBKEIQyaKOqugH9+Es/Miz+Jf71KtWq2FZFo1Gg2KxSLPZZG1tTaoP3PoVdg72KMbDVAoJfvymCjOFiazqGP88cR3jn+e+jhtHP8BlmiZ7e3soikK5XH7aXddnc+J2NPr2xIkTMmHjoFSi6HloioLr+3idDjunT+OdPYv9Mz9DNxzGPjjg5HveQ7LdJhkKUQiFuDqdmI08D7fZpNFokM/nKZfLVCoV2RDa39+XSQYiyjIWi2EYhrwpbjQatFotmbIi2DpCV9/r9SRjR5hKDwYDaaQs2EowaS7lcjlOnjxJNpuVUzWR7uY4jvRcEoCgVqtRr9fp9XoMBgNs25aeBDMzM1ImJvyHNE2jXC5LPyORrDYajWi1WuRyOWmWbBgG1WqVarVKIpGQbCQRvS7YSoK9Yts2pVKJSCRCJpORjT4hUxPApjiNXI3FYhQKBTY3N6VheKfTkecLJkbdIv5X13XJ2BLsKOH5JAClYINZliWNnUWj7R/jcd5q20SHQxTf50I4zKOWhQbsTBP6wqEQoSBgHItx2TSZsSySiQT1WIycojAYjagwmaJpvk9fUXCAgmmi7u4SGAb70Sj/wzD4d6EQu/E4QSTCbijEruNQncr82qUSlf19bMsiCIdpx+Occl0K2SzxZJKZwYDDRIKSaWIEASoQVRRKjsOVUIgHDIOsadLyPD4RCtHe3uYm0ySvqlRMkwiQDIX4jdGI/2dmBtsysToH6L6HEZ8A3oWCTiyqMh46JEI2phOwkI1wGFvASCRl2o5pmuTzeW644QYee+wxHnnkERnfvL29DTCJIZ4mqolJq/CriEajZLNZgiBgMBgQi8XY29tjOBximqb0XhqNRpw/fx5FUTh16hS5XI5+vy9N62Wk87iBoqgQKEyS1Cblh9OMX/w7zyvKuahne+Im5CLHdVzH9ezV8xX/7O7u0mq1uP3229na2sI0TaLXX4/15S/zomSSnm3zYKtF9mUvw5ybo3H2LDesrnLHxz5G+5/+iceA+VaLItCJxYi5LiPLIu66dLtdbrnlFmnyvLi4SKFQkEEXuq5LSZSqqrJBc7TZArC8vCzZzmJYI4Zg0WhU7u/xeJxyuSx9gQSWEc0WId+vVquMRiMZQCJk8+LGXxyveL1msykHWcJP8onqO1lFotkjwkOAa4Zj4vVEk+moZ5KQrIkGkWCgx+NxyYoQOOuJvJZs22Z9fZ1kMsmLXvSia45Lnx5PEASUSiWKxSLDqddVr9eTDS7hqzQzM4Pv+6yvr5NOp+n3+zIhNRaLkX3Na4j97d/SbTaxXBdneZluNosRBBiLiyzkctSAYj6PZZokkklORCJYQcBwdpZUOEw0ncba3+cq8NhwSMy2Wc5kSB4ckBmNGBQKnH3JSygtLlJ86CF6uRyPtFpo7TbpkydR4nEM1yW7vMz46lU2RiMGQDifJ9TrYbouBwcH1Hs9UpEIdihE3nXJqCqblkVhd5fHMxlOLC9z3WhEP5FA+7EfA99Hu3KFULuNtb5OyrJI2TbhD3yA0V134WXSeMMevufgagkCFOjvE6o12O/YFKIac3MFtOEBBB4oz97e+lQaJr1eT95XRCIRqtUqa2trxGIxZmZm6PV6XLp0gXwyynXzGW4/lZNNo2P8c1zP5zpuHP0AljCH7vV6zM3N0Wq1nvbvejY7y6PDQ4J3vpOlhx5CzWQITp4kvLHByUiEb547R3FlhZsOD7E9j7WTJ7l6992cXVwkCAIee+wxMh/5CKutFuPZWYxGg4hts9jp8LVUiq1SCfNb35L0Yc/zuHLlCuvr6wwGA8myEVH3InJ2bW2NZrPJ/v6+BFdHU6EEU8d1XdrtNt1uV8bYCxNqYYQdi8Wkb5CYKIimjTAAhwnAEEbXYmolvALE+Y5GoywtLREKhdjZ2aHb7ZJIJGSMebFYlI2ioxO8IAjodDqMx2M5XRMJKoJCHovFiEQi1Go1Gb8uwEssFpPMpn6/TyqVwrIs6QklJoCicSAYUICUlQnZm2gmCa+ndrstDbgVRfmuiaLwoCoWi5PUtCNTuVwuh2VZXLx4kW63ix+J8N8HA3KWhRqNshMKkZ4advcdhz8fjfjJdpuY7/NFVeWz4TDOcIjSbvMf0ml+3vO4MRQi5XlYgOZ55IABExq2M015cxyHRwyDhyMRbgT6vR4PKgpfWFzESCToDAbcpCi8ejxm5LpgmuxHo1QzGTyYeBR4Ht3hkK6qEvZ9wqEQVhCQdV3OmSaHvs8Z12UjEuGdnQ6fXl0l0u+zurMDuk5CmSTShW2bn/vnf2bjzS9j/lRiAvqJ8a3RSRR7QFitcq7goaohlMDHwUNzNXn+SqUSQRCwvr7O2toa0WiU1dVV9vb2yGazWJbFxsYG/X6fSqVCpVJBVVUppxRsIlVVeeihhzhz5gyDwYBwOMzc3By1Wk1eg8LnyLIsZmdn6ff7k9S1+XkSja+Tqn4R1bdAjQIKgRZH8UwIfPxIhtGLfwfU7wYTzzZoebr1XGr8j+u4jut71/Md/5S+8Q0yySTamTOYjz9OKp9n93WvI3T6NImrVxkC2dtuY/btb+fxtTUsy2JxcZFX1GpsuC6PA18HrmOy5w6Wl6FQkOt4JBJheXlZ4hExRBLDJsF6EY0P0WTp9XrytWKxGL7vMxwO5VDnKBs5kUjINE7hXycGT8LvUTSYDg4O0DSNSqUiGcuCnRqPx+X5ETjr8PAQ13VZXFxE07Rr1vwgCGTSm+M438UqOvpc8RzxvgV7yHEcdF2X71/gl6NsWk3TGA6HlMtlybQ66ikpQinEzx8eHtLv95mfnycajWJZFpFIRHpDidcQTTvHcaQx+lF8JYYx4vh0XZfpZwLXCtZX66d/GvPgAF9VGUciRKb7SFAqEfqZn6HyxS8yarcJ33or3HAD1nCIoqp4//iPhL/yFYz9fUqDASVgJwjYt20arRZZRcHZ2kKbSuaCfJ64rqNeucLdmQwPGgZzr30tgaLQHw4ZXb7M6X/5F1ZCIdZGI3zHYXZ1lcj585Pr79IlhqEQ3WiUoWUx9H1yQK3ToVivQxDQWV+nVang/ef/jP7mNxMaj3GuXmW/36di26yYJkG7jfrOd6K/83VEjDG6rhFEMgzLL2foGOwfHGL1mqTnsgTNBmMlhj0eo4ejT4nR8myU7/vUajVqtRq9Xk8awJdKJTLWOrV7/5LdapuyEePMYoGX37hEOsYx/jmuF0QdN45+wMqyLPb29kgkEtJQ+Zn8kT8b5pACyBm/+ZukH3gAJZNBWV9Hefhh/NVVooeH/Pv77kOdMk68WIxHbrmFxcVFBoMBjzzyCEEQ8OJwmGQ+j5NKMYhGUep1Nl2X/7NUIjMYcHBwwOzsLK7rcuHCBQlO0uk0iURCmjiKuFixaTcaDQ4PD2WaiGVZVKtVNjY2iMViUqvveR4rKyvkcjlSqZR8rmVZ+L5Pt9uVU7lCoSCnUtFolFQqJVPShG5fJHZ0u135PHsa3y4aW4VCQUrhKtNoUyGxs21b+gB0u112dnYwTZNer4frutRqNYIgkKaS4qZ/bW1NsoYikYgEeUL2JJgpotE0NzdHNptlZ2eHer2OYRjXRPfqui7lUMJwWVEUyTJpNBpYlkUymcS2bZkaJ2J6Y7GYNLLrdDrSpFs0547G/7quK1PrRppGY0p1N6ZMLgHS9mIx/ovrEpqm0YWCAAX45eGQpW6XS0wMr2tMmkUFQAdiisJXYzEG+TyDaZLZ3NIS90Wj3Fevo8TjrHW76N0ut7kuc/0+r+j1qIbD5FSVkKJwxnG4d36e1VyObrdLt9PhwHG4rVYjyqQp1dR1IopCtNdjMQjYSSQIXJdso8FrLIsPra7ih8PM+j5Jx8EB2uEwWd8k9/gVLhRuJBKNko16LHsN7quH0EoBEQ0cX0XVNEYjn7hTIxKZkfR74ZmgaRqHh4coisLKygqO49BqtTAMQ34+4rrb2NiQ0sm5uTlJEc9kMjQaDU6ePMnm5qZsavZ6PWZnZxkOh8zOzkqp4ezsLPnWl0nVvvTtxcGf/L0EaoxANwjCacbX/yKEvrdx7fOBqv1s1lPV+B/XcR3XE9cLAf/0YjHUrS38ixdJzM3Rb7dJvuMdZJkkp3VSKU6+9a3kCwUCXWd9fZ2NjQ2Ke3u8LJ1mw7b5vGkSZRLEULv9djBNdEWRA69oNMrKygq7u7vyvAh/H9HEEExj4TWp6zonTpy4BsuItUkwgUS4h2matNtt4vG4TOYUw6dkMinDF8bjMalUSu7ZgJTBG4ZxzXlyHIfNzU3pySQ+tyfyKhLsnCdaNx3HwXEcaXQtAkVEOMQTpbKJpLhYLEYQBN++yc9k5GAtHA4Tj8clA1cwpff29ohEIpw+fVr+bsEKNwwDx3HksFAwzOPxuJTzK4oicZ5gfPf7fUzTlMM70ZgTTTLDMBgYBuOZmUnDq1aTbKkgCOjH48Re+1qc8ZhWv8/JSgVvMKD+x3/MfLuNVqnQuXSJC5EIHd+nZJrcBDR8n7X5eczhkFSrRSKRmEjY776bweoq87Oz5Gs1DjodVlQVvVrF/trXGOVyzIzHnFRVBq0W6vnzkl2cTia5+vDDhK9coQy0YZIcpyi8aDQiVa2iLi+TV1Xie3s4f/InHP7CL+D6Pr1Oh/1+n1AkQn5mBrW2i/o/PobzhlfjKTbe4CLj7R7tyArFsML1p/KEI1HUUIiwloDxARZzEs9qmvaMDNafbLVaLXZ2dtjc3JTNzqWlJbTDb7J74Z/pmy7LM0lKGYO7zuZJJcIEqn6Mf47rBVHHjaMXWH0vIBMEAc1mk263S6VSkXKso99/LkokisXjcdIPPwzZLCgKTBOtFMdB6/UIeR6+puEqCtl+nzd/4AP0PvYxPvPylzPzUz/F7bffTjadRn3kEUKAl0jgtFp8yXXpbm9T6/eJxWKYpsnu7i6JRIJTp05RqVRkzHq/35f+QaPRiGw2S71eZ319XQIey7KkLEyYWIs4x0qlQqlUks8THkeaptFutxkOh8Tjcel7VCwWpdG08AsS3gLNZlP6EYjGU61Wk1MoYUQtjPSEWbVIQxEsJkGdTqfT5PN5VFWl3+/LyZ6gQoupoGEYslGQzWZl2klrmm4m2EBzc3NSciTkYoJSKswqRcpbNpsFkCaSwhC52WxKFpFohKmqKn0N5ufn6XQ6jEYjMpkMrVYL0zSp1+vEYjEJRP2pJ5JItstkMvK8HvVSsixLGoqL8yyAlOd53KaqnAyFqHkeNwIqUFIU6kHANhO/o66q8qfRKGumSTQaZW5ujna7TWeaIKNpGplCgdtrNX6qXkfRNG7sdlmPxfhaOEw4FGI2EiGSSnGm0eDUeExX1/lsLodq27yp1WKkKFjARjxOQlE40e9TGY3wgoC2rjNnmpxaXKRVqbB09SqO73MYDmNoGsNMnFSjz9g0yUQhEkDGHzLoaGghlZEfYejAyNQx9ABz0KGxtUUymSQSiVCpVHBdV06mo9EojUaDSqVCNpuVNxDtdpt7772XxcVF0uk0zWaTYrEom4zhcJjt7W2uv/56TNOU01Bh2C5kIbFYjHa7TTabJZlIkNj6xhOvE+U7cGZfRhDJPeGk7flUz/Za+lQ1/sd1XD+s9YOAf+zxmGAwwAuFaJsmvanszAceA27r9Qjdcw/WyZMsv+c9GOfPT3xzlpfxXZeXF4tc3NlhHYiFQly5dIlYNsu5c+dYWVnh5MmTDAYDarUayWSS7e1t0uk06XSa5eVleeMs/A+3t7eZmZmR0nDhmyiGWWKgpigKtm3LYU+pVJJMaWG2raqqNANWFIXZ2Vnp9Qff9pw6+hhAv99ne3ubSqVCJpP5//Uq+s4SfpFCjia8lkQim2imPdFNt2jyiM9rf3+fpaUlksmkxH/CZ+hoCl21WqXb7VIul6UtgCjRXBPNKoFNRdiIkMmJ3yn8HVOpFIlEgl6vx/b2NvPz83LoJ4JBQqGQHNYJJrbAYEebU57n0e/3SSQSXL58mcTODvF2GzIZeOABtCAgOhgQjsXoaRqmpoFhYNxxB5Ep66zZbMrXdRwH3fMolcuM77uP+oMPsjJNaXu8UGCvVGI2kUDt9cjmcowuXqS/vk4kkyF7993onsfoi1+kq+sMVZXy/DymrpPd3eXS2hpeELAyO4uysYF7553Y8/Moa2vMqyqX02lOui7ZfJbGVp0LX7/A2bJBRHcYNtrEzp4gpmo8sNlk4Ay4/ZabiAQWOCbR7MSbVDDHxOcjPounUk/m+ePxmEcffZQLFy7gOA75fH6Cddttqg9/iXgYzi2kiEd1zsxnyKZi2Mf451n9ncf1r1vHn9YPQNm2zd7eHrFYjBMnTnxX9/aZTM2eyc96nsfW1hazs7OT6VIqBaYJR0FdKERoPEaZvBiq6xIAiuti+z6v+8pX6L3znVi6ztr588RvvpnK5z5Hpt1G8Tx+OQh4PfA3rssfr65OEkqmLBnP81hfX2dra4t+v8/e7i5zgwEZy8JeWqLmONRqNek/JIDF6dOnJfOm2+1SKBQ4ceIElUpFUpiP6u9brRbtdlsCLeFdtL29fU0ymKZpMuZegDBhPi3YHMJDRphUCnAxGAzI5/NSLiaeo2maNJ10HIdisUgsFpOTMl3XpcRNPLder0sWj/g92WyWcDjMxYsXpVxNTByF1E1VVSmnE5RqZSrpEt5FruuSSqXI5/MYhiGZXcIIW9M04vE43W5XgiqRqibAngCJ2WwWRVHkdDOVSslrOxaLyc+iWCzS7XaZmZm55vzH43EZKd/r9YiaJr6mMeN5BEA/HmfWddE1jbHrsmHb9DyPN/Z6vEpV+Zd8nn/Z22PgOCSTSWZnZycMLs/jx0cjNj2PF5kmccfhVtfFSCS4nM+jhkKc6HY5V63S8X1WXJdKEPB/5fMUmSSNDBWFlOuiOQ4x18VVFDxFIeN5mIbBf7hyhWYoxIGqshoEZBWFy+k0hh2gFwwqhsdC0iaihYhr8M6XuaRjGlEdLD/EZsfFslzWD8e0zIsUCgWWl5dRVZVyuUw6nabdbktvir29PVzXlebphmFQq9UmgDORIJvNyuusUqlQr9elNEDIFQeDAf1+n4WFBXq9HgsLC5Llls/liHYvovj2E64VgZ4iiBWf8HvXPO8HkKotztFxHddxPfV6oeGflVgMS9dxg4ClWIyrrss6UAWuAkmg4Xnc6Lok3v1u4h/7GLFYjMVf+zWczU22P/lJXg18ANj3PLyHH+Z0Ps/5N76Rl77sZWxubqLrOvv7+8zNzbG8vMylS5dIp1KY3/oWcdtGO3OGxpSlPTc3h23b7O7uSsm42NuF75Bo5Oi6Tj6flylqokkh8IxgMwkMcvSGUPgpHW0ACTbWwcEBS0tL6Lp+Db4SmOD7nWPxugJbiBRYgUkMw/ie67UwyoZJ4lyj0WB1dVUys8ZTH0PDMKQH43g8Zm1tDV3XWV1d/Z7eWcJ7UjTa4vG43CsFu1zI5gQuFPvpaDTi1ltvldYDYsAnbBHE88W5F9hSvN9yuSwNugeDAVtbW+w98AAlz2NvbY1ar0egKBQch+VikaiuM0gk2AkCwg8+SPzqVeK33Ya7sECiVJJDoZ2dnUki3EMP0U0keHR9nZlej0S7jWvb9M+cwfE8jEuXqFy6hBkOs/bYY1S/8Q1Kr30tmmmSbLfJJJPsdrtcbjapdbuYoRCK69Kq14lnsyh/+qcoySSDQoHx/j6h4ZD+jTfSGVm0EyoFzSTNiE7HIh41sB/6Cx5ttUiFVc4tlTH7LWxFwbY1gkZDNj/F9WhZ1jXXmTinT3SdHE01Ftf30cePXt+DwYALFy7wzW9+k36/z3XXXUc2m51YZhxeopJQOFvJE4loLM8kKGUnHq3H+OcY/7yQ6rhx9AKuIAhot9u0Wi0qlco1evGj9b+a2ig0357nsbq6+u1Ei//0n9De8Q4YjyGdhuEQpV5HsSc3k4rjII7U13Xi2Sx2r8e9f/ZnPJ7L4TgOlXKZ1083gfB4TAyIAL9smnRaLf7eMHBdl8cff1zKzGzbJvB9frXd5kf6fcLjMcHBAX/1b/4N5tR/J5PJMBgMKJVKrK+vU6vV5MRsbm6OIAi4cuWKjLUXHj17e3v0+30KhYJkbbiuKzd7e/rexAYvzINFDQYDNE0jnU4TnaZy+L4vTbxFk6Ver0v6uKAkx2IxmZQCk83w6tWr0swxm82SzWalKbWgSAuZmzDiFqwfTdOkqaMASiJBzjAMCfgajQYzMzOkUilpsi3O8/7+vmwKiYlXrVaT5uGRSEQCQiGNSiQS5HI5IpHI/8femwdLet/lvZ937X7f3vezb7NrtIw2kCMLb7IFDgTbCPsSwjVwie0YpyoONwHuJbgqhW8gZaoIyeXiFCSGMkthVmPwKqvgSrKskSVZI6TZz7519+l9fdf7R/fvpzOj1dJcXJLOt0qlmTOn+/Tpfvt9n36+z8LZs2ep1+tks1kmJiZkxpNpmhSLRVZWViRpNTc3J2+/vb1NJBKRYc3b29vAKOhZVM+TyxFfWWFS15lwHDzX5duRCBHPo6coBKqKMc4bigN3bG9zQzTK/5NI4LiuzGrIhiEoCofCkBvGJKARhix1u+jRKH//5jdz5/Iyw8lJzDCkPxgwValwxLL4DcvijiDAchwqYch7wxBLVVnwfVAUNEWhn0hg9/tczmbZ0nXa3S5HHQdd01g3bZ5ZmOPemSiKAkMvQFcVJlM6zQF4foCpBkza8IdPRVjfa8rXSWyTRQaXyJQQjXypVIparcbExASGYXDu3DlJvHY6HVKpFLOzs1SrVZn5tbe3Jy1rwk7oui7xeBzbtmm326PtbeUhktUHUcJngZeYUI3Qz91COM6MEODo+cBEEATPAXBiXug8d61BycHG7WAO5rs/r1X8o/b72JkMdLskWy1MoAjMAW9jZOU5CzzU7/Ntx0H/wz+kMTExCrp++9uZ+tu/pQNMAecYEU4f2Nvjro0NrHH+4eXLl0mn0wyHQ4rFIievu46V//SfMB9/nGEkQlLX2f34x7FO3TMK8AAAIABJREFUnZJK50KhQCQSIQgCiVuEQlhVVWzblta2Vqslw6jFIkwQIGLZdfXzLvIWjXEWoSAier0eCwsLstns5ViJhIobnlVGAVeQMS9GGAmLvziX12o1ut0uR48elQuwwVh1LJZ+ws7daDTIZDLy+XqxEXlHvV4P27YlxhOKLNd1pUI8mUzSbrdptVpkMhnq9TrRaFTmEw6HQzqdjrzGirBzESweBAH9fp9UKiWv7aK9NB6Pc/yOO9h66ikKnkcADFyXxswMhq7TDgJ6/T4Ttk20VsPa3qZz+TK5O+4gfM97cMZkXBiGmIkEiqqyu7pKfWWFHWAB0Dc20E2TyHveg//ww6zE47Qch34yiVYus3vhAtbddzNTqZACQkVh+atfZTUSYdDp4AADz2Petum1WmynUhjT00zZNtlqFQfYyxQx3rRIVlthfcslDMFOK2hOh0MTKSbTUYLQxe/s0J7/QbzAQhvbNB3HkQSRyI4S71ehUBclMVcfK4LwE5bNq8dxHPb29qjVajz44IM0m01OnTqFruucPn2aeH+NBW2Lo3M5UrEIs/kYyfjo2DnAPwf457U2B6/Wa3Rc12VzcxPTNFlaWnrJk8M/1sZNkCm5XI5er3fFSTh85zvx/vRPUR5/HNJplLNnUT/1KXqZDEa9jsHILuQDW7EYQbmM7fvsMMoMSqVSHD53bpQdNJYWB+PbhMAPb2/zW+PgRl3XOeL7fKTRIOt5bEciHOp2KWsaUcMgp6q85/RpTl9/PZlMRtaV+75PuVzGNE2mpqaYmJiQIdiCcNmfuVMoFKQf3/M8Njc35Undtm1yuZwEXGIjlEqlGAwGbG9vS4JHPE8C9Oi6LtvaRNB0Op2WoEAQL8JiJ37nwWBAoVCQF8p6vS5v2+/36ff7EtylUik2NjZot9sEQcChQ4dkNawAhaIZrdFoEI/HSSQS1Ot16vU6w+GQWCxGLBYjm81K5ZSwBcbjcSnFFvW1Il9KkEi9Xg9VVVlZWZHAX8jbNU1jOBzSaDQAqNfrRCIR8vk8sViMRqNBvV6XGVT5fJ5OpyPzB4Ttb21tjSAI2NB1nolE+J7BgFQY4gGTisIzts3fmCb/tNNhttPBA7aBnK5zyjB4czTKTrfLT9ZqXB8ElBUF1zS5cThEDUMcoAb4qspWPM7FyUnuHNsfB8Mh4ZgITKdSWKbJV3Z3GQwGmIMBP+i6XDZN4mMJuhoEtHo9GNsagzCkPzHBquvylbe9jc1+n3elugy8kEZvJOOfzhgEIfihStdXiYY+dUen4qdJJkMqlQq+73Px4kXOnj3L0tISc3NzTE1NkUgkaDabRKNRZmdnKZVK0gaZSCRkrfL6+jqO47C7u4vjOFI9JsC3yO9SVVW2hoig1VQyQeryA4BCqFngOyh4oBh4iTn6x/4FaiRxxXnkhRqJer2eJDVf6Puuvp9X8sFx/+3En8XfhXRf2BtebEv5fHP1uVqE2x/MwRzMy5vXE/4Ji0W8cpk4MMPoQ/iNx4/T0TTKzSbrhw/THy8uWufPMwwC9oCbGBFHAEmAz34W7UMfYn5+HlVVOX/ffRS/+lUuNRosHTrEqSef5DHTJPQ8jF6PiU9/mtjv/75UG4saeIFTRPmGsCYDkrgQxItQBwvltLA/Xz3Cji/aUQeDAevr6yQSCa6//vqXdf4TuEtc38USar9NTdf1FyWM4Fnlk3htt7a2ZPunwE2O48jFnLDKX7p0SWYCCmv2yxlBLolln1iiua6LaZoUCgUGgwHLy8sMh0NmZmaIRCJXxBzAiIQSSqh2u02tVpOZmeL+BeEl4gDa7ba0tfUMA3Vhgea5c9wyGKDoOn4kwno+T2t2loWLF6mUy+wOh2RNk6jn0V5fp/7NbzIzN8fMF7/I+fPnaSUSJG2bxPo6PrDKyPa/aBhsJpPomQzJfp+YZbHR6aAGAb7nEQyH6IbB0+OFZn1ri+V2m2Y0yrFej3nLYhgE9FSVZixGdTAgpaq409O0UikG996LVSig7T7C409X2WsHpJIWh9w+9Y5DbbnD951aoBDTUCIJtOwh9PFrLEgfgVFEzML+41eo58VxKjC74zhUq1VmZ2fl+0CM7/tyITcYDDh9+jSNRoNTp07hOA5PPfUUkxMlCjvf5NRSgWI6jq76JGL6Af4ZzwH+ee3NAXH0GhshXa1Wq5LUeKl5tRu3lwOchORYWFUikYisYb/i+06cIDxxAgDtqacgHsdRVS7U60wChq7TGQcHG8CZu+8mceqUbALzk8kRUaRpqK6Lpij4YwVIIhbjnnvuIRaLkRkO+akvfAEzDPFMk4V6HcXzGBoGcU1Dy2RIVyqUikWmZ2aoVquoqsra2hqFQoGTJ08yPT0t83kEkRIEAdvb2zI4W4QWCmWOkHLvz5AxDEMCMaEY8jyPw4cPyzwj0XI2HA7Z2dmReUFhGJJIJDBNU1rINE0jm81SKBRkaHepVMJ1XTqdjsxn0nWdZrOJ53n0ej1523Q6LYkZYTnK5XLSjiYsbcI2l0ql2NnZIQxDcrmcVD4JQmh9fR3DMJicnJRbOPEY3THgvXjxIp1Oh3w+T6FQkDa41dVVDMMgEonIjKhut0uj0cBxHNlsIhRYoo7Wtm1arZYkwfr9vrTRCQueaELJ5/OjoHDH4XbP44FUCl3XKbguBc/j4h13kI1EKHzrWxQAx3VJ6Tqa51EYDPjfd3aY9LxR+4emcVRR2HQcGG+eBkAFKAUB56tVHv3WtyipKu9eXaXY7RJXFPYyGVYUBfbV+2qWxR8EAf+i32dN15nRNJ5Jpbhwxx3cevYsmXKZ0LLI9fv8/ewsD54/z2Aw4H+9cYZy2yNla7jeiDgNwhBdU0BVMXWFjprHNEekYrvdpt1uMxwOpW2zXC5TKpWwLItms0m322VlZYV8Ps/8/DylUokzZ85w3XXXsb6+ztTUFL7vc/78eWzbloTppUuXSKfTNBoNarUa119/vTzmReAngY9COKqWVRRQIxBGcI7+KH7p1pd1EQrDkJ2dHQqFAolE4qVvMJ7n2w6K+3u+r73QuW7/11utlrS1Xn2bl3Ou3P+BQ7QO7e7uvuTtDuZg3ujzesQ/kUSCrm3Tq9fxfB8tkSDr++iuS/HDHybz/d/PVLXKuXPniHe7GLpOnBFxNAA+D/w18MjqKjf/1m9x5513cigeZ/ozn2Gz1yNvWTz2ta8x77ro+TxDVWU6nyddqxGJRGQIs2iG1TRNNpYJ8sR1XZm1KFTRsVhMWswFUbH/g7X4cDkYDK74wCswwczMzOj68BKz344mVNOqqkrCSCiCXigs++rXSairXddlbW2NeDzO9PS0LAURFnqxDGw2mzQaDaLRKIuLizLnUbSqvZwR2UNCuSviA3q9Hnt7exK7TE1NyfwdoYwRv/9wOMQ0TamWmZyclFa4arVKs9mU9sBkMolhGDSbI8Vxs9mkUa2iXrzI3JveRN91ifd6DHZ30b7v+zhaLLJ7/jx5x8E1TXbHuDpeqdD50z+l2W6PIiSiUax2m2ouRz8I5NK2bNswHNIJApRKhb1CgcyFCwSdDorrYhcKeHNzbG1tSbW767pM33kn5gMP4BSL1Ho9urOzxN71LvKPPUZvc5OpbJbJXg/tnnvYzWbZ2tmh9sQZBn0HL/DJ6zHOLNdwfI/F2SJRXafd6+NEk3hj14AgioQqbj/ZKDI9AblsFMo3oQrb3t5mbm7uOce2wJye51GtVllbW2NnZ4fZ2Vm2t7cpl8scO3aMdCrJrakCxVwa01CJmjqKoh7gHw7wz2t1Doij19CEYcj6+jqqqsoL2Hdy21cyL2fjJgIgRcbAywVq4dwcKArpeJx0LAbjDBp/epqVn/gJutPTuLOzTAFmo8GR3/5t4isrEIZ4sRjqYIACKIYBkQjNu+/mx37sx3Bdl4nHHiMbjdKMRCAI6A2HTHe7RDwPzfPwWy1OF4vk8nm5/RJBdqK2vN1u0+v16PV6sk58ZWWFWq0mGzZEKHU0GpUNI2Kb5Pv+FZJuTdNot9s0m03ZOtVoNGi1WnIrIiphNU2j3+9LhY5oK0uNSQ8B4gaDAZFIRDZ7CGva9va2zELKZrOyxURIpWu1Gs1mk6WlJfk6AzSbTRLjxgvREOe6LslkkkqlInOZer2ebFjpdrvs7e1JiXcikZDtW81mk0wmw7FjxyT4FNkBvu+TSqWoVqsyqFMAMhEWPjs7KzN1xIZxenpa1urGYjFUVZWB5CsrK2xvb0troFAplUoluuUyShDQdRxCx6EfiRC1baJBQFNReDKf5529HpO+z0BR6EWjTPf7bAOqomAxUhb1fR9DUVjWNBKqihWGpIKAbhBwv+fRarW4zzR5e71OvNejp6oUajX+z9VV+uk0D586xdNTUzz66KM84Tj8g+dR0jT0iQnMmRmOZtPYbzvO9Ws2xlDl/7WKPKAaJMf5UT1fo+maMFSwjZDOEBp9D0MLsKMGlZ7Og1sWivKs3N40Tan4EqBZ5G9tb2/TaDRYXV0ll8tx8eJF5ufnJcifnJwkl8tJObYgosrlMjddd5g3L5ksRSqc00Zqv1LGZkFdJa+08IYRIpkZ/OwJtNo5IIQwINQiBOnDL+88MQZNsVjsOwJNcO1l2uL9PDk5+Yo+kF4N5D75yU+SSCT44Ac/eK0e4sEczOtyXq/4J6Eo3FIuc6nXQ9N17Lk5ov/hPxAePow2P4/quhRVlf4f/AHZ5WUykQjn02nWGg3+D+BDwDLw7ZMnOX36NI899hhTnscNlQpqPI4ThhxOJOhubPBPtrZQTZNOrUb9zjvZGQdnJxIJWRW/31IuwqEF3vA8D8uyJGkkPmCLBllhURcWaEAWZui6Lhtsl5aWXtBaCM+STkJtc3W4tVC4CqX4yznPCyuXCK5eXV2lUChQLBYl3hFxAoI0unjxIo7jcOjQIZlxBMgl4kvN/oY327bl8kvcfxAE1Ot1dF1nampKWuN6vZ4k5QShJxQn9XpdXsdFaLfAo4LEE4p0VVVlnEKrWqU4Vtg8UquhKgpxwyDW7RIYBu78PFq5TLTX482miZrPU9ndpWJZNIF1oD4YoAOpXg/fsmj5PrHhEGcwYGCauFNT9JtNwnQavdlks1pFMU2m2236//W/0o9G0W68kc7ExOgxplIY73gH3W4XJZ2GRALzyCGqegvl20NSySz1Izewk83SunRppIrzwcOiENeJ2xFumJ3n8MIcVkTH9/r4eo7e4btxiEicKLC1yOoSxON+Ykm0xcKI6BOq/6mpKVmyIpR1zWZzFKreb7LzzDeJRHU2V3bp9XpsLF8gHjb53qOLxIsJFo/dRGlvh0RvGVVTRvhHNQ7wDwf457U6B8TRa2gURaFUKj1HLvlybvdq5sWAk8jfebnbv/0TvO99qF/8IupXvgLDIRgG6vw8qWaTQ2trbL33vSOpbq/HiV/+ZSKbmwS2jRoEBNks5R/5ERJ/N6r23rr1Vp5+29sojgN79ViMiGmOti2NBpnBgGB8ElWUUQj3zpEj5HI5HnzwQSzL4uTJkxw5ckQ2kHQ6Help393dZWNjgyAIpNWnUCjITZAgLvZbzsTmTgRNizC+6elp6XsXOUjCj+44DoqiSHuW2LClUilJxESjURkUvb+mttPpMDk5SSaTIZ/P0+12pZQ2DENisRiO43Dp0iWWl5elJSyVSsnsGxFUqaoqrVZLZhUI/7fYxNXrdQniB4MBtVoNwzBkvpMIsxZSa9/3yefzknQQNridnR3ZKiIq41OpFK1W6wqQmM1mpaorCAKy2SzT09NMTEzQbre5fPmyDP3OZrMyGF2QZIZh4Ok6TcvirkaDlqpi+D4TwyGRM2e4KxrlrxYXeURRuPniRQzHIRqGrOTz2J6H0myiuC5xVR1t2oKArwITqspxw+Co41DXdT7c73PxmWe4ORJh0fd5MhIh4zikfZ+4orClKPyTRx/l7PHjWNHoyMoXjbLcbjMsl7mjZPOTN0wwlY5TPXmcSMRgvuJz5pwKikoiESea0bih0BxlHAUaj2wZrFb7TFpDuk7ApWGKoTKUuVm1Wo3d3V1JGjabTbkdFzlR2WyWer0ubZSPPvoojUaD4XDI3t4eiUSCVColwVYqlaJf3+ajt0xSUv+BI9f5vPvoLGdUjbvUv8fseSh9ULbuZ3DTv8I58RMYF/8CrXGB0EziHLmXMJJ67knheaZWqwGjvKrv5ojnYm5u7hWfU/cDuc9//vN86Utf4rOf/SylUulaPcyDOZjX5bye8Y/hONiaRnt6mnS5TPkLX6D6kY+gX7qEoSjM/tt/y9TKCm3DQA8CTuTzxH7wB8k+/DB932fx1lvJ/dAP8SbP4/Lly2x/4xs8OhigAVqzSb3dZhE44/vcEIYMPY/g1lulMgVGHwrFNV6ojJrNplzoGIYhswiFElvkB4qcGBHULAgP0UirqqrMMzp27Jj8mc95Tq6yo4lWNzECTwhL9MslD4MgoNfrSfvW+vo609PT8poiiBhhK2s2m2xubqKqKidOnJBFHOJYejFCUSxcRKaOINgEiSEwYywWo1qtUigUSKfTUpklFC8iwFmoqPfn7IiAbaGgEQsisTDb2NiQ7cGbm5uk02mShQKkUrRPn+amWIztbpdop0P+G99g8/77ydxzDwulEr377uNSu02nVqOVz7NVrxNnZEeDUabo0PdxZ2dxWy1anQ7dTof6cIj1wAP4iQRWq8Vqq0XZtkm5LpdFs3AsBqdPE9x+O+bcnIxO8C2L/mCAU98hUnmMpUKE6A2TVAyFlrdFs6rR7Y2CzKeKE5xM1ZkrJVmYKmEdeQuKVUTtrBHoNl7pdgIzJZexwmoolpIiZmIwGMjXo9frMRwOJTnqui57e3vYti2Lb0TkhK7ro2Vsp0r39O8xkzb4h7O7PPilp7GnTvCmiR5HJ2Mkw3NM9XbIZm5GX/gZgot/gXKAf+SfD/DPa3cOiKPX2EQike94e/ZqW0Web4Rly/d9FhYWXlm4mWni/Y//gfajP4r62GOQyRBqGpplEdvZoVQqjR73ygpWpYKfTkMY4qdSqN0ujbe9jcrP/iwwOqlFlpfpdDpMT0+zM87rSW5ukglDDMdh17KohiFWLEa030cdDvnKV76C7fvcZZoceuIJggsXWC8UeMiyqDca0i7W7/fJZDIsLS1RLBblxkl8OO92u7TbbdLptLRqOY5DMplkZmaGnZ0dmXkgKl2DICCXy8kaYd/3ZSaSCOyuVqtEo1HpeRdbJhEwmUgkSCaTEqjZti03WYlEAt/3JYkjgqYrlQpTU1MyUFFVVVmtOz8/T7lclvlD+7MAhEcckOBQUZQrbHGiDldY+Pr9PisrKzIPQRAT5XKZra2tKzIEBOCq1WpUKhVs2+bSpUvoui6rfsVGsNVqsbOzQ6fTwbZtKSsW8u6nn36aarUqq3BVVeWY7zPT66H6PicGA+JBQEvXmavXUcKQj29ssBmPs5dMYgUBM56HYdvUFYV8v0/MdYkFAbqi8A+6zh/pOt1olP/L91HCkE1N42bgba5LfThEBY6Lml/TxNR1fE3Darf5l48+SicMecQw+L8NAycMuW4mzi+8e4ojBRUv9JmIw6W6x3wqJK4HpIszfPiWPkW9Dgo4gYbnayQSSSqNCZ5c28bzPLJZk2PHDlEqlUgkElSrVc6fP8/e3p4MEi2Xy6yvr7O3t0csFqNUKsktszjGlpaWZLZRIpGQoak7OztcvHiRT/7EzaQslZ1KnXQ8wmTKZlJ9CjUERRtvhwMH4/IXcG76V7jHPsDLF/ePpt1u0+12mZ2d/UcPud0/vu+ztbXF1NTUNfHjX758mV/91V/l4x//ODfffPM1eIQHczCv/3k9459UPE7N83Ati1y5THKc3aSsrhLf2UFJJnmm18OybSYdh+i7383qT/7kyCYej2Pu7dHpdEZNTvE47uXLNHd26Hge3wIuGAaKaXIuHufmMCQ6VjL39/aIXrrE5O4uXixG/cQJGtPT9MfZOfst+eLDtbAaCaXRfnuVCPBtt9tShby6uko0GuXIkSPPq4LYrwzZb0fb/++CmLqaTHqpEQRXJBKhXq+zu7s7yt4bL0LEvxmGMcpCHOc+Tk5OXvH1q48F8buKxymICc/zpHUOkMpwgU2EKvzSpUvMzMzIshTLsnAch06nI39nkQclFO2C1LMsi3g8LhXpwtZvWRbr6+sEQSAXl1NTUyNFUqVCrFql4Xm4Fy+S8zx6qsqlp58mY5rw6U+zNzWFn83iGgaRcSNtulDAGQzIuS4LQFNRoFgkcvfdKPE4W3/2Z/SDgJUwRGs2UZpNDMAA2r0e1fHz1QdSnQ7xVgvrvvvoWhZOKkXillvwVZVGdYdob5tm0eRbdZ3ewMNOFAjcAdqkTiZb4jr9ItOxHpmkSdo2aDsKjd09gvlThPZYBdMYAuXnfb2EakyUqohjVSjchKprdXVV4vB2u02lUmF3d5dGo4Hv+zQaDdTWChORDhtbW6w2NGZSGh+80SEeTxKJWpQyNoWEibH+ZZzsAf7ZPwf457U9B8TRG2SupVR7fwBkOp1+dSc0TSN817vgzBlCRYEwRPU81O/93mc3eKUSOqAZBqgq+D5oGrnZWQbj2nlVVUkmk1y+fJlsNott2yx/4hMUH3oIvdGgft99zJw9SzYMUQYDutEoZw2D22IxPnb6NMVvfAM9CCAMCRWFnUKBP/uhH2I1k5FV7/Pz82SzWSlZFYBCVVUZzCyatxKJBIZhUC6XOXfunKyrFfYvGDUxiADpUqlEp9NBVN2L51SEPsKzwdmmaZLJZIBnN2UiHDqdTtNqtST4EBlIrVaL5eVlHMdhcXHxipwjIUkXIdgigDGfz0tpqiCRxLZGkAsCLLXbbSmVbjQa8vWIRqMsLS1dcT8i+2h6eppSqcTKygrnzp2jUqnQ6XQkGaRpGqlUisnJSbLZrFQ2id9RNGCsra2xvb2NbdtS2m7bNnNzc7iuSzQapdls8j3Lyzi6Ts0wSHseJhD1PCzfp24YpDyPQq/HTjpNOwiwfR+91yOq6+zGYuxYFs9YFg87DvcFAZ0wxLIsivU6mm1zT71OdizFjY7/ExdZNQio+z4Lu7vMeh4XbJuBbXO36xLRdX6x1eJ933sYXVNQCPFdD8M0iOsuQaAxMzPD2w8p5LUWIRCiYqoBMSNg0nYoFOaluqjdbrOzs0Mmk5HWvmQySbValYHp5XKZy5cvc+HCBdmqUyqV2Nraolqtkslk5LGYTCa5/fbbUVWV22+/nUajwYMPPkgubqBpKsdn07INEWXsXw99UHRARfG6r+jUIBRwr2bDdS0mDEO2t7fJ5XIv2aLzcqbf7/PzP//z3H777fz0T//0NXiEB3MwB/Ni81rAPwnT5AbTJGi1GL7pTShjW4yaTKKEIclolHdGozhjVU5yYoLyuIY+k8kwMTExapANR4UI67OzDP7+79nd2sJ+4gncjQ3yrstat8uqaWK1Wkw9+CAnP/MZptbX0V0XPQypKgrm0hLaL/8y6pEjkqQQiuJOp4OqqrKQQ3zoFpasqxvLms0mlmURhiGrq6tXvCbidoDENiKPRihrhMpGYC6Bj/Zn14j/rv6aKOywLIutrS1arRbT09Oy+EGEYAt11NraGpZlcezYMUkqAFcQRGIEcSQWKmEYStLL933ZXHo1ETYcDtnd3WVmZkYuEEUWlAi7FsHZiURCFo+IUhShohHq7Xq9ThiGtFotarWatKp5nsf8/LxUlEe/+lXOeh4rqooXhiSAehBQGQ4peB6h7+NcusTO9DRmJIKlqui9HkEkQr5QYM9xaOVyZA8fplMqUet2yVsWad9nYJpUGg0qQBNojZ+jIiMcFAMSQNhq0QC6QQBBgLO1xUa7zSCXo1Ndp9oZ4YfZJMxMZTg8HyVlWWSLRaa0Kn5nl5VWwJlll8NTfWKpAd6ehzuclcSPeN3FsSOeO2GhBOSxKv5NEKJBEEiFjzkuKGm327J0pVqtsru7O7I91jZptDq0hvDDN1r85s++m41an8D3OTyRIBqNEDVUggP8c8Uc4J/X/hwQR2+AuVYnnecLgLwW9+l88IMYTz2F/uUvg6IQvOUteB/72LPfVCzivf/96H/yJyPSSFXx77mH2E03YQO+5+HV66jjAOWHHnqIEydOMH3kCOHhwwz7ffJ/+7c440DtMAwJHYdz7TYfffxxrH4fFdAESNB1ir0eP3Lfffz2e9/LkdtuY3Z2VqqPDMMgkUhg27ZsCRkOh1LV02g06HQ6tFotqegQt8nn89KWJoCYACAiQFEAr1arJbcelmUxHA5l/pCoZhVNIqLNrFwuyyY2sfnKZrNXZP+IYMB4PC7DIGEEaIRqqNPpyEwkoWASLR4iSFtsFAXw29vbo1QqEQQB1Wr1iuBAkXskGhTi8TjNZpPt7W25ubQsi729PfbXn66vrxOGIYuLi8CzYXrNZlNaF4SEtlqtEo/HZdDe9PQ0lmXRaDSIRCLYq6sEQDYMcTQNfB8VcICI7+MrCkoYEnFdHMNAsW0evuEGeroOhkFlYoKW4/Dkk0+i1mrMjutcK50O39NqjY5FRps2S1Hoj5/rHdNkYTgk5/tMhCFaGNJktI1zNI3bPY/bbruNkwtJjk4nMTSVWNIgCEIyVsjZusHmXo/4wgAvCNFVhSAMCQkxcBkqzwapi+Px0UcfZWdnh1tvvVW2wHjjjKR8Ps/09DS5XI5Op8Pa2hrtdpt3vvOdnD17Fk3TuHne5q75PrVJl796rMVjjz0mQ8fn5+f58R//cfTOUxST7ed/YweuDMP28zd+x+eF/QGq3+3GDWF1TCaT1+T+fv3Xf512u82v/dqvXfMMgoM5mIO5cl5L+EdRFHjrW9H+zb/BHt+/b1n4996L/7nPEfg+iqoSede70E6dYr5a5dLFi0Q8j+z0NNVxrbxpmtz1zncSvOMd7G5vU3v/+/km0ACyQNR1aadSXP7v/51Lu7tgniy8AAAgAElEQVQkHYcSkALmw5DY9jbhpz6F+j//J5GxPX1/G+uL5RMJ6/1wOGRzc5MjR45cYeMTRItQXgu1tCCd9odqC+Ll6n/frxTZ//f9XxdKH9M0KZfLMotJWLXFUklRFMrlMs1mk2KxSDQaZX19XX6/aFALw/CKnKVutyu/ZpqmjA4Iw1D+XgLjiVydwWDA3t4exWJR3sf29ra8D1GuoqqqxGXi2u04DhsbG3S7XWKxGLZtS2u+UE6126Prcb1el0p4oYbfXV6m3G6jtttENI1t3x+1wQKnfR+DsR1tMCAC9Hwf78gRrFgMx7Lo2zZD3+dcpYLa7RKNRmm1WmhhyHajQQfoAS4jomiREXHUZdT61x3/LBXYAzpj3N1vt2m0r8QR+XSUxZxF6PRx4zk2yzUuXP4G7WaLoevyrptm8HyXbqdNYMwQjnOjdF2Xx4wopNlPAAr7mng9BJEkXt96vT5qDw5b1JcfZa/ZwTOKEI/LvKNbbrllpCzbW+aEtc73nZzCiEbZqQ+AkNuOFDAjGoxxywH+uXIO8M9rfw6Io9fYvBLZ9auVaouLsAiAXFhYeNVv+P1sP7qO91/+C16tBmEI2eyofWnfeL/0SwTf8z2oFy4QLizgv/vdoCio6+tEP/xhlJUVAsOg+9GP0jl6VG7CBoMBQbNJdDBgN5cj3NlhCkh5Hh+6fJl5z0MxTVTfH/3M8eNyPA+l3eZEOo01tszZti0DJNvtttw8CGAhyB7Xddnd3aXdbkuSRUiwk8kkkUhE+vSF11/40z3Pk+SSUCfVajV0XZeZM4IYEq1isVhMKnMEYBMyZdGcJkK8AZLJpMw7SiQScoMn7GsiR2hra0tmFyQSCSYmJmTmQSwWo91uE4lEZNCjpmkyD0lRFGKxGP1+n3g8LgHZYDCQyiTR2FWpVIhGo7JZRNynyHza3d2VBJqoohXe+I2NDVZWVmi1WuTzeXq9Ho7jUCqVMAxDPs+NRoPLiQR3bG4S9TxM36elaSR9HyMMGSoKG+k0pXabuO9jDoeU02meymRITU0Ri8UoRKNw5gw/3GwSUVX+IZnkW+0291kW76rXR8euouCGIToQCUPWkklWFxexdnfpKwrR4ZCJWo1FVcUoFLAdh/o4ED2fLAIK9c6QuB0hFtFpaRnWrcPceFMMrPMoSgU/BE0ZNZq4ocYFb5F0OiqPw7m5OTY3N9nY2JDWtKnx79BoNEin08RiMYrFIslkEl3XOX/+PJ/+9Ke5/vrrOTlp8IHjPQzDoGREOPlDU/zl5Qwb3QhvnelRjKyxWrvM05t9OLKvenn/W1bVCFUDf+J2vNl3fEfnhiAI2NzcZGIcoPndnG63S6fTYW5u7prc35e+9CX+8i//kt/7vd/7rmcWHMzBvNbmjYh/NE2DT3wC9U1vQr1wAW9uDudd78IPAlKtFubP/zzKzg6FRILmhz6E8eY3k8/nWV1dJZPJULRtCkHA7E03cXl1lVajwWYYEv3iF5lqtQhMk4rjsMxo6bEGLIUhh/p9Yt0uxsSEJCaElVk0fF1Nygn8IXDC/jwjQX6ID/YiL3H/cy1IpWDcPvpCWUgvNSITSNd1NjY2sG2bmZkZiXvCsVp4OByysrJCoVDglltukdcbkRkpmuCEgmq/XU88flE2IZZiL6TCEiHjMFqyCawEI2W4WDAKFbfIwRRWNdEs7LquxGgiO7NSqbC8vCyb4VzXpVQqSWV6tVplMxIhVa0yEwR0fJ/u+PUeABkgm0ySb7VIxGL0FQXm5hjeeSfBmATLZrM0NzY4c+ECjW4Xf2KCxnBIyzDoMFrAJYAFIMeIKDJNk0ixiL+5STsM8cY/T3y/Awyf5/VLRHS6Q4+4lWIYmwM/IJXLcWQiwuFighOzo2wuNzQYXvcOXD1xBWm4X3kGz62lF7Y1oUgSYemtVgt10KC68gC6CvMZGytSY1A6TmLiLSjbj7CxcYH85BQnv/9e5upfJhUzuLDVJBEzODSRQte1A/zzAnOAf14fc0AcvUHmlQInQNZ4v5IAyBd6LAI07T+582InEkUhuOcegnvuueLLxkc/irK6ipdIEPT7LP23/0b8M5/h6XqdiYmJURgi4No2yXKZnGmCphF4Hjc6Dr5lEVFVVMcB1wUBFKNRErEYhWPHUBIJLMuSwYO+72NZlmziENsrkf/TbrfJZrPceOON0pOfTCbxxo1b4iImLG8iI0hYw4SaJhKJEIvFZMaPaZrMzs6SSCSIx+NUKhVUVaVWq5HNZonH47TbbSzLolKpyO1Wv98nGo2ysLDA5OSk3K6IjZVQLGmaJiXcGxsbRCIRGc7Y6XTkz221WldU10YiEfr9Pp7nSYLKNE0OHTpEv9/n29/+tmyhmJ2dJZ1OE4/HyefzZLNZNjc3uXDhApZlUSgUqNfrcttoWdYo2HGc49RsNuUGUpBXonElmUyysbGBaZr0+31JsiUSCU5GInz/6ioOI+m0GYZsRqNUPI+053FJVdFdlzNTUzTicaphyLkjR0by7zFInm02+d++8hUKwyGaqtK7fJlPTU/zd8BZRUFXFI4DmqKQCALwPKwgYH5zkz5Qj0bRYjHSvR7p8fvR1XUeeOtbuS0WQ7cddjsDomqIEZh4QZR6ZJFcbIogCDivXE9BeQRb7ROi4KLz0OAU3dBG11XS6bS0R8bjcer1Oo899hj1ep277roL27aljXB6epqZmRkWFhYolUpsbm7y+OOPc9wu85Hb8hhqgIdP0w+xNIXbJga8ww6YjPQIgUM5gzuPJnlWlL5/VAa3fJwwPvOKzg2bm5tkMpkX3Wr/Y4wggK+VVHx1dZVf+ZVf4WMf+xi33377NXiEB3MwB/Ny5vWGf8THSfPf/3sOVyo8GY2yGIYs/vZvs3fbbQSqyuzsLNVqldAwiCWTUK0y3Wpx2DB4m+9ztlLhGV3HB+YZfRgYMvrAv67rbLRaZC9douT7JBIJEomEzGgUi7JIJCLVNkEQ0O122dnZIRqNcvToUWnRF01iIgvp6hF2IYEnXilhBM/a+0Ugt2VZJBIJYrEYw+FQZgSVy2XK5TLFYlEqgMSIRZ8gdsRrJhZiiqIwGAwYDAbSxne1MkQop4fDoWwunZmZkSSQuI0gqdrttnyO4vG4DAfXdV2WpiiKIhXVGxsbrK6uSuWTUCil02kKhQK2bVOtVkeNwRsbRL/1LWxVpdVuczkIaMTj5MOQE66Lls/jKgq1+XkuqCpeJELsxhsZ1OuYpkmr1eL017+O/tBDUlHUuHSJSrGIZ1lMACdUlTAIGAJ1Rsqj0HFwNjZwgTaj3dLIwD46hg0glkjgaRq9RgNn/Nz1QhNbsbDiWSYKJebm5piZeDsTlftQvRZhAK4WwT/8XoxkCXMfOXy18kw8LyJ4XbgBWq2WfH1c10UBFuMDUsOnKNyQIZuOUxsYrG7XSA5WaZ45Q9Td455jJUoZl9B9klwyiqoqXDeX3YcRDvDP880B/nn9zAFx9AaYV7pxE/Ykx3Gk3eXVjjiRC/LkVZ2QBgPUCxdw4nGUMMSIx1E6HTI7O6QWF1lbW2Nubg4zGuXMhz/MzZ/4BEoQgKrSTSZxo1GMVAo1ncZZWUEvlyEIUHSdTLuNr+u86atfpftLv4QLkhwRWTt7e3u0KxWCXo+eYaCNFR+HDx8etWWNLV6u67IzDvs+dOiQDLn2PE82ngnptmVZssVEXODEFq5erwNIECTaxoT1qNlsypwfsVkTQZL5fF5u8KLRqAz7EyBNVVUcx2Fra0v+XQAkUWUqKmJjsRgAU1NTnD17llgshud5sv1D3JdoMcnlcpw6dQrDMGg2m7JRZH19XT5HYgM3NTWFruvScifAWb1eZ3JyksFgwNmzZ+l2u3LLl8vlyOfzDAYDqeiybZter4fv+9i2zc1PPYUVjbIVibAFpHs9Ltg298/N0W+3ibXbeJkMvaNHQVHQKhXuajaxTJNziQSbqsrdDzxAdjCgPw4/t32fn202OT0/zx82GvzzwYBlRWEuDGmoKsvZLHosRnZvb5TRNSb/Wuk0jx8/TiuXozk5SSUSoWAYXGjVuX1CZxjoDFUN1ddYbYCrjWTnoWnyQPBm0sNtwsBjx0vjKVFc15H5CAIkCWtBu93mgQceYHl5mRtuuEG+TvPzo0ykra0t5ubmOHnyJN+7EOUDJx3wR/ZJE4/ppErPC0nFY8xYHRQ1gqppEIKhhARKBnVYv+JtObz+p18RaAJk3pIIDP1uzf6t37U47w2HQ37hF36BG2+8kY985CPX4BEezMEczMuZ1zv+ySWTxHs9VMsiMhiQ391ld25O2phqtRrWJz9J8ad+imEYshkEDItF5tJp5qNRNhSFlZUVhuP2rCSj5ZfjeZR/93dZe/e7iaVSMpMwlUrJgg6v06HvukQKBTpj29XExIRsnBV2+RcKtN5vWxMLoFfznIh2Vs/zqFQqMmdRqJ+FguPChQuEYcjhw4eJRqPPuR+hHhIk1HA4lFlIoi1N4KT9txcK7X6/T7/fB5DLmptuuklaqURj3XA4lBZzcX9CBSyU7Y1GQ/5ftK6JpZ6IQBAZTgsLCzJWoVKpyGXe8l//NZrvsxWJMJycJNXrsXToEPZb34plGFTW1+kqCkGxiO04hL0e3vnz9Pt9aokEPV1Hf+IJ+owIIZeRasgrlwmWltgrFHAqFdqMyEePkS1NB0QBex8Q70JjXK6i2jbGuCE4P1/icA6OLk0zk43Tdhwq5nWo0VEgeHcI2/l7yGl1NEJ6kWl834RqVaqM9oezu64rFejdbpderydzQoVlP5/PE4lERhEMYRl99UvEMymGgx6PXdjGc33MqI3nudxQDDg+dxRFU3HdgJzlgZqFYf2KY/YA/zx3DvDP62sOiKM3yHynwEkEQNq2LX3er/bn79+yXQtvaz8IUCMRNNdFi8VgHLjHmKB55JFHZJBjY2mJL99yC+85dw7Psuh5HnFFQT1yhKf/3b/j0S98gWYQ8N7NTRa/8hX62SxEo0S/9jU6k5M0771Xtis0m008z+P4gw9y/X33oQKtuTke+vEfJzo9LYHK/o2B67rU63UqlcoVNjJh37LGeTnxeJxEIiGtV4PBAM/zRuGG+9rVarWaJJYmJiZotVr446DMcrksCRld1ykWi1KN0m630XWd+fl5KafWNI1msylJLGETq9frMgzbNE22t7clkdNut69oG7Ftm3K5zMbGhsws2trakuGCi4uLqKpKLpejVqtJKftwOKRer1MoFMjlcui6Ti6Xk21wYRjS6/Xo9Xo0xi13YsM2HA7J5/PU63U2NzcJw5BUKsVEMsldKysUajW2EwkeOX6csN+n1e3ij0kfxTBQMxkqhQJ+Nsvlvb2Rxa3d5tZSifedPYvtOARhyM2GwZ++/e1kHYdQ09ANY5Td4/uo3S5vU1UevukmfvHMGf5lv89cGBJRFCzPozUc0rZtzIkJlJkZusMhjy8uMjh1irm5OWLtNrFmk729PXaNI+xEAqaiLRxf45leEXes7Nrb25PefGDcoNfGNIfSPpBIJK5ooHMch3PnzvHII4+wsrLC2toahw8fZnNzU97nysoKOzs7xONxPvbWDJalYeg+AuIpCsQM2NDnIHzm2Q3e+HyyVvynpDtPERts4OkJdoo/gD9Io25uPie49KUCTbvdLsPhkEKhIK2Iz/e9o8f1/29Y5O7uLslk8ppt/X7jN36DarXK7/zO7xz4+g/mYP6R5/WMf8wg4K5sFj8I8IMAL5/HsixqtZokcWqahv6v/zWx3/otFuNxfMvC7XToHzlC6ld+hZPb2+y02+z8wR8Q/frXmU6ncXWd8tmz9GdmcN/yFpaXl1lfXycWi42q7O+/n+TnPocRhuzNz7P1oQ+xcPPNWJZ1xZLp+c7V4vrted7z2tZeyQgFdL/fp9PpkE6n0XUdy7Kk3avVarG9vU02m2ViYuJ5f6ZQAInXXeQNXR10LexnzthqLkgKkW8kWnFjsRjZbJZ2uy1V6ZqmEYlEZIGFaPNqNBqsra1JclEsGU3TJJ/PSzwmcFyhUJALyImJCbLZLFvLy1Q+/3m6y8vUk0k2CgW8RoM0EDUMdFUlZlmEtk0jGqWpKHSLxZFa3XVROh1af/VXRB0Hdfz7aLfcQqPXY4+RxthjpDrSAa3ToalptAsF1EoFkxFp1GdEGpk8WxaSicXQJidRk0my2axU1hQKBZYWFziSHmK7FTzFQJ+6lW5o0+/36fV6IzWWZeFER83DpXE4uyAfRbGKaJoTdkpRXhOLxchkMldkagnHgGEYeI2z2AosbzdY3mkQi5pk41EStkH02CluNC+Mfl4YYpsqgR+wlrvnAP+8jDnAP6+vOSCO3gDznZxkwjBkb2+PVqvF7OyslHa+0tnfSvEcafaruM96vU6z2WT+138d8+d+Drpd8H2897yH4NZbiSgKS0tLrKyssLi4SBAEXE4m0TsdtL09SmGIXypx5v3v58tf/zrJiQneeeedTP3n/4ySy6HFYqPtEdC5/36+mkrheR7xeJx0Os3S7i6n7r8fP5XCUxRSa2u84+/+jr3/+B+lZFtYxMTFa3Z2VjZoJBIJmRsQBAGNRkPW3IqAbbEpFS1nIkg7nU6TSqVkC0SxWJT1r5cvX8Y0TUkqzc3NUSwW6ff7bG1tya3L8vIyuVxOAhFBOuwnqTKZDPV6XbZ1CBAjFE4CoAm5tuM4ErgJy5SiKLRaLZ555hkMw6BYLFIoFOQWb29vj+3tbVKpFMePH6fVaqHrOsePH+eRRx6h0WgwGAxk/lMqlZKS+f05Rjs7O6MMKtPkf/n2t1mo1fBtm8ONBvlKhb80DH4mDIlFo5iGgTEYsHHddRTHbWMiY2l1dZUf3dzE8jy62SyqpmG32xx5+GG+qWn8KBD6Pl4YEh0MUDSN9z39NHdrGk/qOje5LhVG0v+5ZpP1aJSMZVE5cYLGz/wMm5ubuP0+J44epVKpsLe3x3A4ZGlpaWRVDAJ2x9vKkVw+kO0qYpMmAjhFwKMIFrdtW17oxXY3n88zNTXFF7/4RakOO3z48BWyd2GHrHUcKISoV789FThUiqE4h9EalwkZkYuBXWLy2B2Eyj/BG8vCiy8QXvpiXxO5GL1eT5Kmz/e94vtfal4uUHuhr4sPAMlkkn6//5IA8KXm61//On/yJ3/C7/7u71IoFL6jc93BHMzBvLp5Q+CfXg/d9+G97yV6551Ex+co0YqZTqepzs6iNxrEymXCMCQyOYn2i7+IVSrhZrPEXZeZz36WrUSCFcBxXY6YJnatRnVujkajIYmSJ//iL0h+7nOk4nGSmgZPPUX6j/6IxhhriVbOq39Xoa4Wyo9rQRjBs6SRWH4lk0kZE+A4Drqus76+Tr/fZ2FhQaqm94/IJBIZS6I1Vtd1IpEIiUQCGL2WgswQ2EEQSqlUSpJiZ8+exTAMMpkM/X6fSCQiK+AF+SOWOKJgRCiuTNOUailBHIm8StFwK1pUh8Mhk5OTVCoVznz729R///fpbW6yB3j9PlqhQOrkSYqPP44zXnjh+4RHjhCGIbu7uzL0PQxDoqur+I0GjmUxMAyUXo/+mTM0TRPdcRBXMJFPFCmXyQADXafDSInkM1Il2YwUbNlCAfvkSYrFIoPBgFwuRzwex7ZtcrmcbH/TTJNYNks2m5WLSVG00uv1ZKtfrVaj1+tJnCDiI0S8w9TUlGwB208A7n+t6/U6W1tbzMzMoOs6nWaExy6WcfttZvI2SStCOhllMhsjtpRBdY6N8Q8oHOCfA/zzxp0D4ugNMC9Xqu26LpubmzIPR1VVGe73an7ufvvMqwUJvu+zs7ODqqrMz8+jLi4y/Ju/QTl7ljCXIzx1SgZLTk1NsbOzw/b2Nr7r8mMPPUQ/nabf6xEzTQLX5f7772fuzW/mjjvuIJVK4c3O4j38MJ0gwHNdot0utbGsNRaLEYvFME2T0pkzKJ6H5zgopgmZDNYzz0gQIaSmImtHXAQFIKmPveOxMUGVTCZlro8IyF5bW5NbKHE7ASKazSaAzB7Y3d1lZWWFeDwuAxXn5uZk1o2ochUXpEqlwtramvTb1+t1GZoMsLKyIkMkxesmamYVZRTqePjwYXK5HGtra3IjK+TUgmRKJBKkUilKpZIESOK40HVd5jPlcjnq9Tq2bTM/Py+Jk/vuu0+SK2J7qqoq/X6fQ4cOSeLriO/zvuGQ7NNPc3xjg1YySd11cVyXYr3O1Ac+wHlFYf7RR+mHIRfe8hbak5MUxmBRUUYhl5ubm3R3d3EZAefQcVCDAK3X47Ef+AHetLzMzBNPYDsOrqJwMZNhqOskez1+uNPhjGEwcF3SQC4ISDca7E5O8vXZWfxvfpOzZ89y9OhRtra2aDQaJBIJDh06JI8DwzCkrVCEZQrAsz8zodPp0O12aTabtNtt1tfX5UZTURRJJIk633vvvZevfe1rPPDAAyRMn39+R4FBsssT8WnK+jxLS4doah6u+jSj+EqAkFBRUFBA1XCu+0n0ta+httcI7QnchXtA1VB4dRuw4XBIq9VicXHxmmz2XwyovRSAc12XVqtFKpWi0+m85H280GxubvKbv/mbaJrG3t4es7Oz/PEf/zF//ud/jmma5HI5fu7nfu5V/a4HczAH89LzRsU/qVSKSqUy+nMiQeZTn6KSz4+WDZ5HMH58mqbJBUT6xAkmnnySE+k0q/0+l6tV2rpOptNhcnJSklZJ16XveewMBjwVBBQMg9ITTzA1tqh3Oh1M0yQej5PNZmX7qmiBvVaEkQiu9n2fWq2GbdtSTRKJRGTQ9OrqKqlUavSc7SMQhKVJLOEURZEqKMMwrihZabfbkjhTVRXTNEmlUkQiEaleEcrvSqVCsVgkk8lIPFYul+XtheJI0zRprxdNYOIaKJTeQpFUrVZZW1uT9rS1tTUajQYTExPsfOtbnP3yl2lVKvQuXcKMx6npOoFpEtnZwbvlFponThBdWRm1t912G6vdLvVHH5WEkTje++OsISsMCRwHJwwZDgZkjh9nYmODoFbDYUQMDYEao7a+nuddkXi4AKSBhVSKmX/2z+iPf6djx45RLBYlqVYqlaQaSEQ8DAYDqUgXC0pB6Ir3kaZp8vlLpVLEYjHi8bi0RYrjWuRnwTjnqF2he+FrdBpVspljdLsJarUatXaWTCzGobzBbDFG0h5lUEVNA0/VD/DPAf45mPEcEEdvkHkp8NNqtSiXy88JgHylJ0Tx84SC5jthv1+IzR4MBlJmvN8DHM7MEM4811OsKArHjx/noYf+P/bePEqSgkz3/kVERkTulVlZlVWVtfa+0CzdgIDexgVX0Ktz/RAH+NBx3Eb9Zi73qKMii+eoF0VHr4pydVAZGR11Rm0UFxabTYEW6G4BoaGb7uraq3LfM9bvj6gIstum12q6gHjOqdNdlZmRkbE++b7P+zx/JLBnD7FGg4osQyhERRAQGg02Dg7ScdZZTExM8Ic//IFSNMpbQiGS5TKKJKGPjCBffjmndnUBjpLDMk0SO3agTk+jiiJ2MIjR1UVr2TKs3/yG4O9/jxSNor3rXQRPPhlBEDxy4t6cm80mjUbDi011Y1RrtZpnVO0SFnc+u1qten9zY2YjkQjj4+Pkcjm6urq8m+uKFSsYGhrCtm3PM0lVVQzDIJvNEgqFaDQaHtEB2LlzJ4IgeB5K0WjUIzfu2Nvg4KC37mNjY56Ztpve4fpCrFmzxkstcWfto9Go532QzWY9Muemwblm2Lt27fI6qsFgkL1792LV66wOhSju3ctenKJgNptlz549xPbs4eqZGdJAvFJBNE1i9TohWWZHKIQwbwi5dXCQ6UsvJRqNYpomnc0mu3fv9tRaAMlkkt9MTfFyTSMgikiBAEqrxcO9vYyceirfTCTIZzK8fnSUjXv2oMsyImBGIgQNg2VdXdRk2RnRm53lt7EYW885m1N741QaLU477TQCgQBTU1OsWrWK5cuXe90wt9jm+ii4Un63G+nK5d1tBXjk1TU6dztXlUqFQqHA1NQUlmWhqiojIyMIRp2rXmWSiJSwUgHOHFIYC2YwBs6mq6sLWfkbzB03IZV24vTVBGxRxUyvB0nBWHL+UV0PnguGYTAxMUF/f/+CzNK3XzeONMbWNE1GR0cZGRk55jSTkZER1q9fz4c+9CGGh4f50pe+5KUKuamHPnz4eH7wUuU/iUTCaVIViwTzeXqSSbKWhSYIBOp1GB3FalOg6u95D8qDDxKZmGANsOLkk5n61KcYLRYZHR11mhHRKInRUfRymVa5TC9QTqWYSSR45rvfpePxx+np7KT3b/+W1po1XjHO9SJcqKQoV7Gt6zr5fJ5UKuXdH93022w2S61WY3h4eJ/96voM7d8ca0+5ddXXboprLBbz1L9ucaNer3tqo0AgQKPR8AI6xsfH2b17t1dkUlWVRCJBKBTyCkLuseF+Hnf9wbl/uSNL+elpyqOjRBMJGpbFzp07qdVqVCoVtt91F/Xf/556q0UER+2juSq5UIjQPP+piyLm8LCTDJfN0mw6DaJ4PE4oFPIMzxMrViBs2UKu2US3bUQgNDBAIBxmbHCQZiqFvncvrVaLGo7ptetlFJn/WQf0A8pJJ1FYuhTN0tA0gyVLlhKNRqnVah5vcdVcrnJc0zQajQaapnn7x7V1cP91+Wk4HPaOAVcxX6/XvcakW0ByG3B6rYD00NcR6hXCCFi1MYqFCYzYOladdAojr38t6bGfIleecc8in/8cBXz+8+KGXzh6CeBg5MeyLEeRY5qMjIz81cXrcLt17XC7bO5Mtvs+7ojN4VS/939PN8lDlmWnOzA/OnU4Esw1d99N+l//lXCrhTA3RzYWQw8EiEkSWwsFnvr2t5EkiVQqRf/y5Txz3XX0TE8TCYfhtNNIzXfHPEPIzZuJPvQQVjyOVKshNBoE8nlmL7qIns9/HluSwDAQ77qLxz7zGVqDg95NrP2zuT40+XzeM150VaOzkKEAACAASURBVEWWZZFIJLwikUsU2yNfXQXU9PQ0HR0dFAoFWq0Wp59+ujcnHQgEyGQyngG1aZr09vaSyWRoNBqeDLhUKu0z/mZZltcVjEQiXjetVCp5/kxul831SHILYu7Inauaicfj2LbtjaG5JtyNRoM1a9bQ19fnkYd8Po+qqkxPT3spJN25HFfmciR370YeH+ffh4Z4VJY58y9/4axCgZMaDQbrdUKG4Xjv2DayZZEyDE4xDGZSKZa1WowJghdjW6lUmJ2d9STj09PTNJtNwuEwTySTfHZqiqt1naBlsSkeJ7thA8WdOx0Txd5eZppNxNFRosEgcihErFJh59q1dE1N0V8oEKvX0SWJ86plzo7sIdmjoioyD8/VuH8qxJlnnsmSJUu8LmN7PKxbGHLVQ+2PudL59nPTvQm3d40Evco6eyudYpm6IXHLrgDl8h6+fIFEMDD/fBtUUWC1MkZrxQrvXNPW/38E9vwWaeZhkBT0JRdgdSw9omvA4cA1YEyn06iquuDLPxLYtpNm0t3dvSBfbARB4Nvf/jZ79+5l06ZN9Pb2LsBa+vDh40jxUuc/wve+R/Pb3yaSzyPPzpIeHkYPBDAti2xXF/r8vVsURecL9je/ifrUU4iAcOqp9IRCpAyDYrHI5OQkubvuIvnIIySDQfRmkzqglMvU3vhGujZtoiaKjD71FH/ZsoXw3/89mQ0b6O/vJ5vNks1mSSaTXtHgaL8su9yj1WpRLBbp6+vzmnPBYJBWq+V5961evdq7R7pBH5qmefu3PenN5USuKslt6riFJHc7Ad77uSprVx3e19eHLMuegtvlfu3KYcuyvIadu9/cfe4eB25Ayp777kO+8UZirRZzjQYPr1/PRDBIfutWKsUicjaLhJOGN4eTWCbiJJZJjQblQABt927knh7PksC2nVRdl9e6nLPZbLKjVKLR0YGSz5MApEwGoacHbX5ss9VqoakqgVaLFM5Yfg8Q7+0lXCoRnjcFF4HkrqdBrSDacTIhlcJolYlAiqGhIWKxGILgjMtPTU3tw3dcBXgsFiMYDHrKeNt2fKXcbWfbtndvdZVT0WiUiGwhPPETpOoEphSiMvAGiuUatUe+j65pxKIyomkzW6mgNh5n5bn/L93d3Q6/T/8T+PznmODznxc3/MLRSwQHIj+uAaRrUrcQ0mFXFQEsiBzZsiymp6dRVZXe3l7vS7T72KGImPDkk/T/+McUAwEmbJt+IFWpkA2F+I9169gB9GcydHZ2eqljNdNkT0+Pc/PesWOfuWLDMFiyeTMJXafc2UkgGkUwTWxJQr79dpqAKcsIioJSLpO85x7GL7rIW0a7NNwd/4rFYp4kPhgMEovFvLG1wcFBTzXkFp5CoZDnEZDNZunu7mZubo5ischJJ52EJEmMjY15M/q7d+/2kiQikYjnW+TeqN33DIVCJBIJr5vmzl7bts3AwADlcplqter5DUmS5BWU3M6Qu771ep3h4WHPuDkajdLR0UGtVuOee+5hdHSUgYEBcrkchmGwatUqL7Z2fHycdDpNPB7nqR07uGq+MzZlmkQFgYv37KFQr7OkWqUlCCytVpHm97slCEi2jS6KWIJAUNfprtd5yx/+wOTYGD9/9auZmpoCnDE/d+wtEAhQqVTIZrMs6+/nHWNjCPk8tqLwxmKRiSeeYGxwEFVVKZdKSOk0+dNPZ8lTT4GmMbtqFTv+x/9gbs8eXvHtb5Pr7KQiy/TILfp+8xceHorRme5mfcoiNngySrrfI6KlUskjkq7R4/5fBNo7Z+6x5L7GPXZUmiwzn0QV64QDRRRamCjEJItL15YRbYMA7vloIwrzRouWvu9JJ4gYS85f8O5aO2zbZmpqing8viAR18cK16vC9bE4Vtxzzz3cfPPN3HDDDT5p8uHjBOOlzH8S3/kOs7JMtbub6Ows4t69BDIZqh/6EPby5UjzihvXn1DTNIzeXnRdx9izx/sM7n2ov1zGFEWy8wlcnaZJRyBA8bHHKMsyQVnGFkXC+TylRx5hqyDw0EMP0d3dTV9fn+c9EwwGvet/OBxGUZQDFsDc3911aPcIckfy3RSzYDDoqYwGBgZIJBLeOJoXuz5flFAUxeMquVzO+bzzxT1XseQ27tyCkavmdUe7XJVwPB5HkiTWrFnjqbTdfQDPFhPb94+7fLdZBE6hyv3MpVKJ7NwcyZtuImpZTAgCV4+PMzM+jgSoOMbT0vy/IZwvdDKO6siNvMcwiD/zDJFajcaGDV5gTCwWQ1VVT3nuJrdhmgw2GiRxxtEKk5MULIvi/PaPRiIMxON0FgpEczmSwSCRwUGU17+ejnKZvh/+kIIk8bQk8US1RP2RvZQqnSjBIL2dZU479y2kBgbQdd1TRLvFOTdUxuXFrj9Re/FNlmVPRd9sNpmeniYYDBKVbaw9d5HPzzJbnSEqaUiKSr6YZ27r1xCsFrGgSEdYpl7XqbVMRtIxlgx0Qybz7Enn859jhs9/XtzwC0cvAexPXmzbMYAslUoMzn8ZPthrD6fj5t4IF8oAEpzZ38nJSa9D1U4e4PCkmGI2iyjLhGWZuUKB8UCATkniR+96F+KKFaydH8dyo2Dbb1KyLHtkSRAEcrkc8Xic1MknE/jd7xCCQQiFECsVWiMjhEwTRZYx52feRUGANqWI29mxbduTbLrm2C4hdGfzBUHwSJz08MOc+vvfY7ZaPLB8OU+3Wp4iyTRNHnnkEbLZLKtWrWJmZsZL5CiVSp5st9FoeBH2rszX9b9xDRsrlQr5fJ5IJIIkSV5Ebq1WY/fu3XR0dOxz03Zj75PJJI8++ihr1qwhm80iCAI7d+7EsixSqRSpVMpLtnCTI0466SQvUa7ZbHL77bdTLBaJRqNe0oht26zs7aVHktgVCIBhULcseiWJlcUio5JEMBSiWa0StSwMUUSybRAE9GCQoKaRTaVohsOIQO/YGIMTExTnlVUzMzMAnmeAaZrs2bOHvr/8hXW2zahhgGGQDoW4bGyMr61dS1cqxd8+8QTLHn0UW5KQWi2KK1cS6uzklLk59L4+x1w9FCJiGKhiCatYR6hpWDaEQyE6Ai2mSyWvsOceZ66kvb0r6B7r7rkFeITV/ZEkiaCeY3DiF4iWho2EiI4lqkiyimCbiFoJ9jkln/3F7FhyzOfqkSKbzRIIBLwRxxMJdxRhcHBwQZY3PT3NVVddxd/93d/xyle+ckGW6cOHj6PDS53/SKpKSlHIGgbVwUEC5TL6v/87gRUriLWNR7cXaNrhNpD27t2LJEl0btiAsGkT1UiEOVWlUq0SHBkhbVn0hEKUFYWKZVFVFORYDDWT8VJSH3/8cTRNI51Ok8lkvDh0RVGQZdkb43KLOrZto27fTsd//ReYJoXzzyc3P/7vRtg/+eSTXmOtWCwSDofJZDJUq1UKhYKnLnLTzkzTdFQz8ybdbjMvEAh4HjruWI0bJqIoiucbODAw4KkyBEGgVCrRbDYZGBhAEASv2ebyvvZgE/fHPWbcxDaXE7qWBHv37mViYgKjUqGxezfTts0tZcdBKAx0AjGcolF8/v+u0gicgo8MWIJAHWjJMtmZGfQnnyTU0+Ol7rm2A+6oV2dnJ/q8GryAk6BWB4TpacLz437B6WmEXA4Th0UY3d1km030Bx4AVeUPjQazOAqoJo4HUuHpPMszYdYtSVPMz9KSnIKJm9zlJtW5PMi1M9i/eOjynfZ0XQBZKxLY+TPCkoUQCFAt19hR1tFsmd5EiGTQIh4OI0kiumHREZE5eThCsiOI1bUS7TDPyYWCz398vJDhF45eAmgnP+0GkG5E+qFwKOLk3iTbZ8WPFaVSiXw+T19fH8Fg8KiXYy9ZAqZJUFVZtWoVdq2GHYlw8RVXYMzPubs3dpf8td/cZVnGNE1mZ2dZsWKF05k85RTMxx9HvfNOkCTszk6aX/gCgZ07Ua++GlvTwDCgo4Pu972PxPCwJ492R8HcpA7X+LBWq1GtVj0zbTdqVX3sMZb97GfOaw2DZTMz3NrRQePsszn55JPZvXs3nZ2dvO51r0NRFCqVCrlcjmaz6Xn3FItFTNMkFot5o1Huv5qmUSwWiUQiXiEK8ApppmnS09NDaT4y3pV6y7LsrbOqqvT09KDrOul0GnBMsufm5giFQp7ce2ZmhrvuuotYLEZPTw/BYJBSqcTo6Ci2bZNOpx2CJklEDYNaOExsyRKkzk6WyTK1Uoku2yY6X0AKxGIEJImCohAyTZqRCEqrhWSa1CIRTFXFiEaJmyaiZWELAolAgIGBAVqtFvl8nmq1SigUYsWKFaiqyrZt29jwy18ypOtkRJE5QcBKpZB0ndWrV3NGo8Hyxx7DiMeJjI8TKJeJTE1hSxLG5s0UX/EKJEkiZNsIsoxUs5G745y68RwQBWS7RbhzgN5gr0fY288vtyN5sPEDl3B6BU5adD72n4hWE8eXyOleipaGLUQR9MZznx9iEH3lhUd9fh0N2on2iYamaczNzTE0NLQg1y3DMPjUpz7FkiVLuPzyyxdgDX348HEs8PmPiWJZZBQFo1rF7Oqiunw55jz/aU+ncgsybiHJ9Y2Znp6mt7eXRCKBsHw50kMP0f3b39InSeQ7O5n88IfJ79pF4oYb6BUEem0bPZWi/Ld/S34+oCMYDHrj7KVSia1bt3qj9K4no9s0M03TUUDs3Eni6qsRJAkTCDz6KHziEwTOO89rRBWLRVRVpVarcfLJJ5NIJDwFkizLqKrqNeny+bynOnLTo9yUslar5Y2rS5JEKBTywkLcJk+hUPDCRly/yXq9TigUYnx8HMArBrnHhquSavdVchNo3d+bzab3bzGXw2o2CSYSjvG2IDCg63xaktBNEw0nuSyQTjvR8NUqUqNBlmfNqnWcoo8WCICuI2kaEo5JemA+IdgtGImi6Km+bNtGKxSo4BShVJwClADI4TBKq0VvLkdvKITQaFAC5iYmKAL6rl1YsRgykBYEkqpKutlkSQecdOU7yWR6EE0Na8Vb0KNDngrMHcNsV8q1q7MAb3u6iXduo7VWqyGYLaQnf4IitKgj0hGUiUYCrImpCGoHCdUiIJmEFAEbASUgkYyqBAKSz398/uPjKOAXjl5gOBazxucygDza92vvsgGHRcIOBcuyPNXM0NDQMZuo2atWof/zPyN/4QtgmgjhMNqNN9JxgEq/+1ncG5kb2Tk3N0dvby+KolCv1wFofuITyBdeSKDZxFi+HDsaRRgYQPvMZwj99rcQDtO67DKspUsJzM/RR6NRj0S4iiM3oaOzs5Pe3l4s06Tx6KNUZmbIJpP03nYbWBb6vKGg2Gxy6vbtzF1yCTt37mRubo4NGzZ4aSulUsmLzXXn/TOZDOl02vMTcPebIAhOt6/ZpOfGGwk/+SStvj6evugiivE4UrPJ0vvvJzQ7i/iyl1F+9aspzC9/165dFGZmOPuBB1i7dy81ReHB17yG8sqVdHZ20t3dzZNPPkkmk0FVVdLpNFu2bMGyLFavXk25XPaS2yKRiEe2lu7ezRvvugvRMKiGQvzgnHPY0tfH28fGkOfJQx6Imib95TI5w8AMBJjt7MSWJKxwmPsGB7nr1FN5z/btnPrEEwR03fE+EgQEWfZUTp2dnYzMp+fMzs4yMTHB0nKZtzUaYNsEBIEB26aZzzP++tdz7rnnkrnvPpRAAFnTCDQaCJYFgoAty0i1GvFt25j6wAdIfu97REwTvXsAPnAmcsBEsG2q8bWQXEFo/phrT6nb/1xzSXy7Cm5/Q00AafKPiLobGd3+JccGU8O2LUBEECSwDe85VnQI7aTLsIOdx3SOHQnq9Tr5fJ7h4eEFISrHAtdjoK+vb0GMKQFuuOEGdu3axS9+8QvPN8OHDx8LA5//HBn25z+BSATzxhuJHGAk5UD8Z3Z2lmw2S19fnxd8IQgCgSuuQLroIuRWi+TKlSTm+Umus5PabbcRiscJXXop4ZUr6ZxvmGmaxuzsLPl8nkKhQLVapVQqsWfPHh577DGi0SjDw8OcmkyyJJXCXL6c/I9+RE7TCCaTVDWNqKYRu/VWhLe8hbm5OaamprzCTW9vL5ZlMTk56Y2dVatVzzC50Wh46il3PF2WZaJA/Je/JLR7N2ZvL8p73oPQ24tZqSDcfju1yUmE5cuxX/7yfUYFc9kswd/8htiTT6LG42hvfSva0NA+htu2be9TGHE9r8A5fhRFQZIkL02s+uijLN+8mW7LwojHmX7LW4i9/OV0/frX7AV24aiMOgF5bo5yNIomCJQCAaqGgQU0e3sRVq+m889/pms+Aa2BM7ZWmFfOZ7NZ6vW6pxp3k36lVotwpYIA5HDURgEgGQgQCwZJWRYGMNloYOMYYYdwVE9dwFIg9cEPkrz1VlKCQCiVQL50PXZ3GMto0UquxlL7wDC87e9up3aVluvz2B4I4jbM3HPCtm3i8TiVZx4gqFiYKHRFA3R3BFFVBRAIReMERR1RBMMEWbRQlXmPR5//+PzHx1FBsI/U+c/HCYV7EzoSuOa/qqqSyWSO6CLRbDaZm5v7Kxnj8ZBmu6bJ8Xh8wTwHPMzOImSz2ENDcBik0badyPpWq0Umk9mna9ROrtwv/rAvyWw3LXZxoOe5XSdd19GaTXquvZbovfeCJGF2dFBesoToQw9RDQZpzcwQr1apxOP84Z/+ibFwmHXr1nky8kql4sygR6Ok02nS6bSnMnJnw6PRqCezNgwDXdPovPxygo8/jh2NQq2GmUjwzJe+RNcVVxB+5hlsSUKwLCZf/3rGL74YURQZHx9n2Y9/zKqHHqKuKEi6jm2a3PkP/0Bz3ghz06ZNLInHWX/SSQT6+/nTww9z9tlns2vXLubm5shkMgwPD3smiebevVxwww20JAlTloloGnowiFSrITUaJKpVmraNBOwUBNLBIJMrVjCZSPD0a17DCllm3U9+QiSXo7FiBc0zz2Tpt76FoOtYkkQ9HCabTHLL+95HOp2mo6NjH9l6q9Vi6JZbOOXee5ktlxkCIrKMnkhw/3e+gxSLEX36adZeey2CYRCcnUXUNKdgpSgIlkWjr4/tn/wk2pIlBBoN9EgECYOgXcUWFVpiDGFe0eYW7tqLQq4arH104GC+D4IgEN7+NaTy7r86ho2el1GRe7EbeTqLjwA22BYIoI2cjzn0miM8iY4NmqYxPj7O4ODgCScVrsdAOBwmkUgsyDLvv/9+PvKRj/D1r3+d1772tQuyTB8+fDwLn/8cJZ4n/mNZlqcCArxxJEVRvIaZW9DJ5/PMzMx4nosTY2MUf/1r6nv20ClJrOvu5hXr15N5/HFaySTT2SzRfB6hr4/W//7f7J4v4vT39xOJRDzFdqFQoFKpUCqVPL9A0zRRFMUz5A4Gg06zyjCwvvEN2LWLVjiM3WyiRCJoH/kI4k03IUxM0AIigoB47rmY//2/EwgEKBQKJG67jfiDD9KIRgkbBoJtY33qU1iuP5RhYBUK6K0WViyGMO9T6I7MuaEYiqKQy+Uo7tpF5ze/SUiWmZEkquUyBdtmVtPINRpYOEWjBo4SyAKaHR2QTFJOpQjaNubjjyO3WljJJIFUCmHnTnQcz6M8TjHImB8PVFXV83h0R+bFuTmsZpPJ+deEgAEgdsopBKNRgo0Gndu2EbRtOnDG5kLAII5JdkdfH9Mf/Sj28DCKYSB2dCAJJiHqEFCxlSS0Hdfto/guZ3YbafDXjbX24pvLmaJP/4DGzG5CqkgyrGCJEkFFIjTyCurBjM9/DgCf//g4FviKoxc5Go0GU1NTXpT6kZKRAz3/eEizy+Wy19kKhUKHfsGRIp3Gnh+jOhRM02RiYoJQKOTNrcOBO4rtRof7/xyoqLR/cclVk4TDYZQ//pHwPfdgxmLYgoCUzRKKRLBEkdDcHKlKxZE712ps/OpX+b9vfCM//POfkSSJnp4ehoaGWLp0KV1dXZ70uJ0ku3PhhULBM2MU83nSf/4z9WgU2zQRZRlleprQLbcQm5hAT6UwTBMsi8ztt/PUG9/I6MwMoiiy9PHHaYRCWKKIaJqolQrRzZsZf+Mb6U6l+F/FImdu3074kUfYHY0y+6Y3sWXLFgDOOeccksmkJ5VvtVpkZmed0cBwGNGyaIgisUoFSVGQOzuRNI2AbSMYBrFolHo4zJ8+8AEqlQrnrl/Pmssvx8rnsYJBep55BmtiglY8Tj0exzQMRNum17Z5wxve4HUC3WKNm64Sr1SIP/EE0WXLnOJMo4E0NMTJZ53l7NMVK2jW68S//nUEwBZFmP/8lqrSSiRQ166lq7vb29/uPnYJkNs1E0XxoAan7Sk8B3veknoRyVkbb19rUownAy/DskCOLqMqdtJVfgRBgELHBmriSoSJiYOOxB3O354zyWe/a4J7TrmJMycahUIBQRAWjDTNzc3x6U9/mksuucQnTT58LBL4/GcezyP/CQaDJBIJyuUyxWKRcrnsmR27huGxWIyuri6WL1/uqTAKv/oVpXyemY4Odmkat09N8fNKhXS9zlmjo7wGCALNmRn+/KEPUX3/+9FSKbZu3UqhUPBGr9zCjFscah+9a083UxSFoGEQefJJ5PlQEFOSELNZhAceQBofR45EaFkWmihi33032saNzBYKTpDK9u3UgkGy9Tp1XceuVrH+4z8wzjgDURCQ770XaccOx6C6pwf77W9HDIe9USu3AOemu8bKZVrVKk1ZZqZcpjS/fUOAq4+vACVAwynY1EdGAIhLEuaWLVjzj2mFAs1CgSbOyFkJZ3wtAiS6urwCnuuz4ybLCaJIbHSUk3CKVC8Ph4llMqgf/jCJRIJkMknq3ntJ3nQT8b17CQGCLCMAVihELZOh+01vItrV5Y3mGYbh/bSriNo5sqsmAjw/KLex1p5AB896e2maRq1WI1gvI8kis0WNzniIzogKwQRPqmf7/Oc54PMfH8cCv3D0IkW7AWQ6naZerx+TzNv9t73LthDSbNu2mZ2dRdM0hoeHj1mafaxoNptMTk7S3d19WAkD7TeQ/XGwolK78bEgCNBoIO3ejWBZSIGAUwKIRpFyOZ686irWXnklRqvFM/U6NU1jmWXx/ltvpTA4yOhb30rl5JMRRZFisUihUPAURu6Mv1vAcIskrreOYDvx9ZIgIOdyKFNTCLbNyDe+gZlMInZ1odg2pmEgNRqogQAbN24kGo0S/bd/Qy8UCBQKhEolsCxes20b1b4+ZMvilbOzjJomQqVCX73Oy+68k8J/+2+8JZkkOTnJnChSjEYRRZFwOAw9PYiW5WwDSSJoWdjhMC1RRLBthECAoGFgSRJh22ZTdzfG+DgvK5XoHx9HGR9HqdcRJQlTVdFUFVMUEXSdaDRKqFajefrphEIhZFneZ+zLi7y/4AKsn/+c0PS0s/9kmdl3v5taPu/tt8J55zH9ilcQffBBum+8EXV0FFtRKGzYQO3KKxlZudIrFi3EOXIoSKVB7EIDwTbBtrCRaPafhxIIMjg4OP/ZlmDb52HZNlHLIrJfEepAxan2Y/VQz9v/OftD0zQkSWJ6evqoiNjhPO+5Xrs/3CTAoaGhBdn+pmlyxRVX0NfXx8c+9rEFWaYPHz6OHj7/OTosJP+JRqP09vZSLpfJ5XIUCgVqtZpzL56/BwuCQCgUIhUOE5BltFCIYjLJ3kaDQr3OU80mD7z85fzkvvv4PlAEytUqdrWK/PnPO7Hz8ThqKuWFfrhFo3A4jKqqRCIRjwu5xaNAIOAUHjSNsihCq4VeKmG1WgSAwH/9FwFVhVCIpmk6jTFNI/f008S7u5EkiaYgQKtFpFgkqmlEAHXLFoQNG1BsG+WZZ5BSKQKAncuhP/YY9qWXYj/6KFqtRi6RYE4UGRoaIhAIkN+xA1HT0Od5WsayiFkWcjCI0WzSME0kwP2qHzrlFFi+nGihQGFmxhst03DUSB04I2Q1nDG1MDi+j6EQqVSKeDxOZ2cniUSCrq4uR+kWCBC7/npi5TJxSaJDUYh94QuEX/lKT6FknXMO1oc+BHfeifWVr2Du2oWlKOROOw3tE58gqKqUy2XvPGlXU8Nfh3u0H0vtcLnEoe7xaujPSMWnETERsLGRqPj8x+c/Po4b/FG1FxgOR6rdbgCZTqc9I+D+/v4jfj9N05ienmZwcHDBpdnuerrpXguxzGOBS3BcX57jCe+mUygQ/MhHCGzZgq3rYFlY/f0gCFiFAvUzzsC+8Uai73wn4ugoVctCn50lVa1ixWJY8TgIAtnrr8c67TSve2NZlhc/a1mWR5zcgkn7OoS+/nWiN9+MPDnpeAGJIrYgIFgWWk8PoqYh6DrTa9fy56uu8iJEYw88QOZzn0OZmsIWBIxAgHwsRkhRGDvrLDL33ssz5TKtVou+RAIjHkfp6yM9Pu6kcYgiD/7DP1Bfs8YzCe/7+c9ZuXmzMx4nioz+4z/SCodZ+i//glouozYa1Fas4BeRCLfOzvKVqSniokhQ05BLJSxFAUkCTcNQVXa8732s/M1vEEyT5ooV5D7zGeTe3n2KRYZheB4MhmEglMvE77sPGg0aGzZgLl/uER/3x5Wcu+ln4+PjJJNJ4vH4cT1uDgShWUDd/k0w6mDb6NFhdsbPY2h4yQn/ImLbNtPT0yiKQiqVOiQJW+i/HWh9NE3zxgSOtuPophkGAgEefPBBNm3axFe/+lXP4FVVVVKp1Am/pvnw8WKCz3+OH44n/7Ft2/M00nXdSzINaRrKP/4jbNmCpWlYgJXJIABaNkt1/Xr0r34V47LL+NOf/sRPLIuHcDx+ovM/ISBwzjnI80bi7jXaHUlz79nhcNhLRnN9fSRJQr7lFtTbbkMqlwngFF10HENoMRbDNgzqzSblFSuw/uf/9FJolcceQ/7e97ByOVrzzzfTaUTbpnXmmahbtkAkwpSmETAMxFgMwmHk8XGapkkjEEC46CJqySS5XI5cLkfr8ccJPvkk0Xm1jXneeViiiHzHHUQMA1nXaaVS5EZGKIRC9w3dwgAAIABJREFUJB5+GLnVwrAsLPDWfwyYA2qJBIFiEQWIRCL0vuIVLFm9mlQqRVdXFx0dHaiq6inAkskkUdMkdNdd0GyinXEG5rJlHjdy1UKAdy5YlsXU1JRXhGpvxu1/TB+OUudQhY/94fMfn//4eH7hF45eYDgUcTqQAWSj0SCXyx2Vi7+maUxNTdHf37+g0uxKpeKZTofD4WNe3rHAtved538+bzbKhz+MeNttEIs5SWyzsxCJoKsq1sAA2ne/i9nVRWDTJsLXXAOKgjgxgWAYmCMjCMEgQrGI8c53YlxzDdg24n33IUxMYK1ahb1+vect4Pr4WPOKHjcGV5Fl5M9+Fvm665yUuPnCktBqYcuyUxSSZYREgpnPfY7x5csxDMMhvD//Oemvf52mJFEPBqHVImpZPPP2t7P81lsxOzuRZRljdhZraIjIxATNUAhN1xHrdWrJJL+9/HIsy/I6YOlKhXiziTE4SC0WcwpgjQaVPXuYMwyalkWj0WDdF7/ImbOzKKqKYFkozSa2IGDN39y0ri4e27QJRRSJzhtnm/MFtXbJtCtnd0mmmzinKIqnGnqu7rJlWYyNjZ2wopEHU0OsTdMyLMYKJoNDQ4tCEp3L5ZzCYV/fCScRtm2zd+9eurq6vASZI+0kun9rNBr89Kc/JZvN8pe//IVMJkNvb+8+flmf/vSnGR4ePqGf2YePFxN8/rPweD75j1tAKpfL6LpO+OqrSdx3H9FYDME0MWdnMcJh6oqCMTCA9a1voSeT8KtfEbr2WrRAgPDEBDldp9bfTz0QwK5U0M47j8qll9JqNmlt3Yo5N4eRTtMaGPBGpNzRb8DzFlQUBVVRUP/zPxF/+UsAJnF8hAI4Y14CTnFKicfR3vMe7FWriEQiTuNo82bUm29GV1VmQiEkXUdpNJDe+lbk3/2O+vwxaNdqCKkUyswMOVVlotWiXCpRCIWYPv10TNP0GnKBRgNZ07DicULJJJqmgW1jlsvYqoo4XwTru+suBp9+mhZwD/AMzkhaAWfMLASkX/Yy+vr6OGnFCjLDw8Q7OohGo6RSKZLJJKFQyElum2+guallbnHIPdZdtZY7ct9eVJicnPSKRgtRCDoq+PznkPD5j4+Fgj+q9iKBZVlMT0+j6zojIyP7eNscq0S72Wyye/dubznHIqUEhzTpuk53dzeCINBsNo9IarmQeK55/ucL4pYtMO9pIFQqUKthGQb2a1+L/Z3vIMdiqHfeifK5z0GpBIoCiQSWIEAw6Iy0WRaabVOvVIhecw3yrbfCPMltffzjCH/3dwSDQS/W1+06tFotKpWKE327cSO9X/2qsx6CAKbpqJ4iEZrd3UiBAGK1SsePfoRx/fWe+WRnq4XcaCBZFuFSCdEwsCWJ3vvvp7h6NZ27dmHYNkZ3N+a556J///u0JMlZb0Uhns3yN1/8IqFajdrJJzPx8Y+jDw0xa5qOsWW16hRuFIXQyAiByUlqMzOowNnFIqppYjcauFS3pSiYsRgBoHLSSdi2TdMwqLVaBDQNVVUJhUIEg0FUVfVUWAdKNTsU3KJRIpE4sUUjAEmhGexlfHycgUVgvgjOeV6r1Y7KW+R4YHZ2lkgk4kUsH+s6vetd7+Kd73wn5513Hp/5zGeOejmWZXHNNdewY8cOFEXhs5/97D6E68Ybb+TWW29FEAQ++MEP8rrXve6Y1tuHjxcbfP5zdHi++Y8gOP5G0fkUtua2beRlmUKrhV2tIlWrSJoGr3oV9le/iqYoyPfcQ+K66zBLJURZRu7spFsQUMJhdNPEkiR0RSEcChG/6Saku+9GA0zbpnHRRZivfe0+JtntTSNBEDAtC+OMM4j+8pcEcUbB6syrjmQZOZWibNtIuk70vvvQzjjj2XFF03QMtZtNkqWSF1+vbdtGc/lypJ07USUJqauL5tq17HrmGaZ1nR31OiXAajQI3ncfMlALhSivXUs4kXCU4ZpGs1BAURT6+vroWL7cK94ookjjxht5Csfw+kGckTQBxw9pNbAkk2HwwgsZHBwkmUwSDoc9RRbgqdGbzaanng4Gg/ukuLpNs+c6LsfGxhgYGKCjo+O4HjeHhM9/Dgmf//hYKPiFoxcBms0mExMTJJPJ56xsH6mwzLZtz7hu2bJl3jLd5RyqOn2g3zVNo1QqIcsy4XCYWq12xLPC7ThcieVz/a7rOvl8nkQiQTQa9cjFgV5zvGD19iI+9RS0WpDNOp8rFkP5058wr70W4/3vR/nwh0EUIZ2GahU7lUKo1RBKJWe0LBpFuuwyoqOjBH/xC0c1pKpYoojyxS+Su+ACmDelbJ8tj0Qino+BlkhQf8c7CP/oR9jzRSMjkcCe9wuwwRkBm+8YSpLEwLZtdH//++ixGEouh2BZ6KJINhIhNjnJ5Jo1jF98MWa9TufLX87UnXdyum2DrkMgQKheR6nXMYNBiERIPPooweuuY/Yb3/DW1T1uWq0W4+PjyLLM8PAw4rZtYNvYgGHbWIKAAgihEFIkgh2PU7/iCvr7+z0l0dEUh55zv1kW4+PjJBKJE0+acDrx4+PjZDIZz0vgRKLZbJLNZhkaGloUpKlcLqNp2lGpDg4Ey7K48sor6ezs5JOf/OQxLeuOO+5A0zR+/OMfs23bNq699lq+9a1vAc56/+AHP+C2226j0Wjwtre9zSdOPny0wec/Lzz+IwhO+mtycJDGjh1UTBMpnycG2LEYja1baf7Lv6C++92o//zPVEWRajKJXK9TiccR6nXEapUu26YZiRC75BKEWg1582YkWUaUZTRJwvzZz6i84x1osoymaV7ByE0Sc9VI+pIl1DduxL73XhTmI+ZVFWQZS1Up6zqWphEwTSKRCKFQCOmPf0S95RaUZBIKBWI4HkytZBJtdJTiOedgvOc92JpGPhRi58MPUzQMcoZBA6fAFOPZSAu90UB6/HFK69YBeOOCkiQxNja2z4hfpF4nblkYwA/mX98HnAucE40y0tlJ5xe+QGz1ak9F7f60j9of7X72+c/B4fOfw4fPf1548AtHL2DY9rMGkO4X5APhSC9crmzVfW37693/H6mcuVarMTMzQ19fn1fxPhYcyZxv++9ut6nRaFCv14lGoxiGQT6ff87lHAyH02U82O/ylVfS8d73IszOOrlYwSB2NAq6jnD33djnnOPElyqK8280ipDNon33u0i//S12MIh5ySXYy5Yhf/SjCHNzIAjOsrq7QZaJ2jZ2JOJ9HncbuB0n93NYX/kK1gUXELjnHorJJOWhIZZeey12sYgtioiWhX7ZZSSTSWq1GrE77kAQRfRIBLFeR6rX0SXJ6QICoT172BoOk+zvZ8vdd9PQdVpvehOvuOMOFE3DWroUe3wcwZXqx+OEt29HFUVMUfTWTxAEKpUKXV1drF27lkAggKyqqN3dWNUqcrnsHI+RCNx8M2IohLV2LT2HYe55NHBJUzweXxSkyTRNxsbG6Onpec5rwPMJXdeZnJxkYGDghHsMALRaLXK53IKSuJtuuomtW7fys5/97Ji3+cMPP8zGjRsBOO2003jssce8x0KhEJlMhkajQaPRWBQk1IePxQCf/7wI+M9VV9Hx3vcSnpmhAZSCQXKqimSaqH/8I+aGDc7rFIWKrmMpCoFsFuOznyVw332IwSDmm9/spJl+5SsI80liZUBLJglIEvrcHHR1eaNqbpqYKIooikKz2USWZVof/CCF9evR//xnapEIZk8P3Zs2ESiX6RBFZEFAe8tbaOq6M2Z3zz0EgEY0yni5jGKa5IAqEBcElJkZEqeeyt69e3l0yxZ2z86ipdMEZmedJpcoIlgWIZzRuBAQazaRBwfpTKUIBoNEIhFvrEhVVaLRKLquYz/zDMaDD9JstXg18P8AFwaDBP7931HicVi3DuE4qaB9/nNw+PznyODznxce/MLRCxSusaKqqixZsuSgCR+CIBxWx80lCwtpAGnbNtlslnq97qVHLAT2l38fyfrMzc1h2zbLli07pgv7/kTrcDuP7X9rjoww+6//Svc3v0nittuwOjrAshCaTZodHeRMk4ymObHvgoCgaSBJ7BoYwH7f+7xtoWzZwsh//ie07WthZobWunXM2DbC3Nxzkjj3swC0Nm4ku2YNgiCQTCYp9vcTvflmbF2n+jd/Q+3sszGbTUfOnEwi2DaiIDiErl5Htiwy1arjDbBjB1MPP8wfWy06OjpYvXo1iVe/mr3/638hmCaxbdvo/fSnneKVICC0Wk6kvWmiBALEYjFEUWRmZob+/n7S6fSzx+QrXoGwYgXy009DIgGmifXKV2K/8pXYx1MhNk+aYrHYgkWZLsT6dHV1LcgXkoVYn4mJCXp7exdF5880TSYnJ+nr61swErdt2zauv/56Pv/5z7N06dJjXl61WvX8WMD5Uup+uQHo6+vjggsuwDRNPvCBDxzz+/nw8UKHz39enPxH7eigw7ah1aLZ1UU2HCZmGFiBAMOAbZrYisLTJ59M65RTvMaXPDVFx+23YwMqToKYUSjQXL6cmXgcwTQ9lY3rbwTO/SqRSGCaprMtBwfJv+Y16LqOoii0lixB//WvmW21aJ51FvT0EKpWPW9IQ9cJ2TYDoRBd1SodQKVQoBcoT0xwwx/+wKa77iKfzzt2AYkE6uAgXZ2dpFotuu+7j+5IhJQskxYEkqJI7JOfJBaPe2Nlc3NzhMNh0um0N0ZGq4Xyl78gPv00nw4EPP6jveENToPxOMHnP4deH5//HBl8/vPCg184eoHBVV/MzMzQ09NzWJGpcGiptivNtu2FM4A0DIPJyUmCweCikGwu9Dz/sW4nd30iS5cS+trXEN7+dgKjo46/UDxO4LrrSK9Zg3D33QR+9SuHEIgi2pe/zJJly4C2/VooIIVCWKqKODcHhoEty7SuuopoPH5AEud24NpJXaVS8Uwj6/U6laVLmbniCu/YsAoFR9qt6+Re+1pO+v3vEYtFLMAMBJB0HQtn3r5Vq3HWD39I8b3vZcWKFcTjcSqVCq1Wi3A4jLZuHR2nnkp4+3YEAEmies01dMybLIIzlx2LxUgmk88WxAQBVBXt5psJ/J//g7hrF9aGDRgf/OBxJ01uCk4ymTxu73O4sG2biYkJOjo6Dvs68HysTyKROOGGr+76uGkvC9WJLBaLfPKTn+Stb30rb3vb2xZkma7fhwvLsjzSdM899zA7O8udd94JwN///d+zYcMGTjnllAV5bx8+Xkjw+c/R44XCfwIAiQTil7/M4Jo1yPffj+TyH0VB+/KXWX/66UDbft26lVA8jh4OU5iepm5ZyJJE6/LL6UqnPY7j8Zh5LuQWFdtHCQOBwLNjYmvXYq9cScg0kTSNer1OoVBweMzQEOH778ecnoZ55VAXkAa+DPy0UKByww0oikJnZyednZ2sXbuWZcuWMTQ0RDqVYlUgQOqJJwgAsiTRvPpqzOFh70v+7OysZ2S9T0qZz398/nMY6+PzHx/HA37h6AWGXC5HsVhkZD8DyIPhYDf39i6Q+9yFIDj1ep3p6WnS6fQ+1eQThWazyeTkJN3d3YviJqNpGhMTE6RSKc9YuXXLLYh3343QamGedRb09gKgf/nLmBdeiDA7i3XSSdjLl3vL8fbVsmUQCDhJaIODUK9DJIJ87rnIh9GJcWfE0+n0YcuP7VNOwT7tNLj1VkxNQ5ucJPzDHzLTbFLXNLqiUU6VZTre8Q4vwc2ViLvErXL99WibNyPkcrTWrkVbswa7XMY0TWq1GrIse/uuvfDldZEvvdT7vzA5ecRS+cP1hACYmpoiEomQSCS8dThRcElBKBRaFJ0/cEiuqqqLZn3y+TyyLC+YnN62ba655hrC4TBXXnnlgiwTYMOGDWzevJnzzz+fbdu2sXLlSu+xjo4Oz6NLEBxj2XK5vGDv7cPHCwk+/zk6vFT4j2yapJcu9fhP88ILIRLZp3Do/r/9X8MwGBsbY9WqVcRisX2KS+54n23b6PNjarquYxgGzfPPp/K73zFeKpEdH+eJP/yBTZLELaaJArwZeM2113L66aeTyWRQVdUrCtm2jX3jjdibN2PkctRc/lOt+vznEPD5z6Hh8x8fxwuCfTgaXh+LBrque6aNhwu3KDAyMrLP34+XNDuXy1Gr1chkMosi3aBUKpHP570b94mGSyr7+voIzSeqLQTEP/0J5f3vh3IZOjpo3Xgj9vr1h3ydpmmMj4/T09NzTHJfadMm5I9+1EmJE0WoVrE2bED7yU+OaDnuzHoymTyim97RSOcPV17faDS8RBP378+1DkdL0I7kOXNzcwD09PSc8E42QKFQoF6vk8lkFsX61Gq1BTenvPnmm7n++uv56U9/ug+5OVa4qSJPPfUUtm3z+c9/nnvuuYehoSHOO+88vva1r3HvvfciiiIbNmzg4x//+KLYxj58PN/w+c+Rw+c/B4fPf3z+c6zw+c/Rw+c/Lzz4haMXGNwkiCOB201ZsmSJ97fjJc2emppCUZR9/WhOEGzbZnZ2Fk3TyGQyi8KorlQqUSgU6O/vPz6k0rKgUoFYzCEvh0Cj0WBqaopMJnPsclbLQr78cqTf/MZJdksm0f7jP7CHhg57ES7JT6VSi6Iz6sqPQ6EQqVTqsF9zuITsaEicpmlYloUsy/t2H3nWz+NouopH+5p6vc7c3BxDQ0NH7LlxPKDrOmNjYwwuYCzv448/zrvf/W6uueYaLrzwwgVZpg8fPo4MPv85fPj8x+c/xwqf//j8B3z+42Nf+IWjFxiOhjiZpsnevXtZsmTJX0mzF+pC596AF4sU2vUXCIfDpFKpRUHi5ubmaLVa9Pf3L4obTLVaZW5ujv7+/oUz8rNthF27oFrFXrXK6b4dJnRd98blFoPRoW3bTE5OoqoqXV1dJ3p1AGfGvFKpHNKj4lgJ2uE+xzRNNE3zpMT741BkbCE7kYIgYFkWe/fuJZ1OL5jPQLlc5uKLL2b9+vV86UtfOuHXEh8+Xqrw+c/hwec/h4bPfw4On//4/Ad8/uPjr+F7HL1E0H7xW2hpdqFQoFwuMzAwsCiSBBbbPL9lWUxOTqIoyoKYUi4EisUixWKRwcHBBUt6AZxUtzYPgsOFKxfv7e1dVMaCi4k0VSoVSqUSg4ODhzyG2s/v49VpNgyDvXv3MjIycsBurduTONLO49GSONt2vCoEQWB6evqvuo9HQsjK5TIPPvggiqLw+9//Hl3XefOb38z27ds9v65DpTn58OFjccDnPycOPv85NHz+c2j4/MfnPz4WB/zC0UsA7gVkoaXZpmkyNTVFIBBYNDJNd56/v79/Uczzu7HBiURiUZjm2bbjwdBoNBbNPmu1WkxMTCy458HRwiVNsiwvGtJUr9e9mfXFsM/chJV0Ov2cEv/jTdz2R7FY9LxF2q9vR0PQTNOkXC4zOjrK6OgoGzdu5IEHHkDTNFqtFpqmcfnll9Pf33/I9XJn+Hfs2IGiKHz2s59leHjYe/zuu+/m+uuvB2Dt2rVcffXVi+LLlQ8fLwb4/OfEwec/h4bPfw4Nn/8cGj7/8fF8wS8cvcjhXgxM02TPnj37PHa087+iKKLrOoVCgY6ODqLRKJqmHVRC+Xx8ztnZWXRdZ2hoaFHM87udv2M1XVwo2LbNzMwMtm0vms6fu40WC9G1bZvp6WkCgcCiIU3NZpPp6WkGBwcXxXHtEstYLLYoEoPA2UaFQoHh4eG/Oq7br1uHi0QigWEYXHbZZXziE5/gkksuOep1u+OOO9A0jR//+Mds27aNa6+9lm9961uAMy5x3XXX8W//9m90dnbyne98h0KhQGdn51G/nw8fPhz4/OfEwec/h4bPfw4Nn/8cGj7/8fF8wi8cvYjRLs1eunTpAavQRyqfNE2TSqVCs9kkGo1iWRbFYvGgrz0Yjoa07f+7ZVlks1lCoRDd3d3e+7dfLJ9vklCpVMhms4tGvu7KxV3p8WIgTa4vxGLZRi5pkiSJ7u7uRbGNNE1jcnKSgYGBRZHQA5DNZpEkadHc3E3T9LbRQnUjq9UqH//4x3nVq17FxRdffEzLevjhh9m4cSMAp512Go899pj32NatW1m5ciVf+MIXGBsb48ILL1w029WHjxcyfP7j8x8XPv85NHz+c3jw+c+Rwec/Lz74haMXKdql2S7ZaMfRdMIsy/Kk2cuWLTvmi9TRzvy6n8u2bTRNo1arEQwGPQJ1IAnmc+FgM79Halrnbo9yuUy9Xqe/v9+LLz2RN2HTNBkfHycej5NMJk/YerSjVqsxOzu7oMkPxwK3GymK4qIhTW7CSiaTWRTEEpxRiGazycDAwIleFeBZA8/u7u4F20a27UTCmqbJ5z73uWM+FqrV6j6dSUmSMAyDQCBAoVDgwQcf5Be/+AXhcJhLLrmE0047bZ8EKB8+fBwZfP7j8x8XPv85NHz+c3jw+c+Rw+c/Lz74haMXGA51Erd32Y5UnngwtFotJicnSSaTCzarfjQSynaUSiWq1SojIyNHddF0CdXBiNqBHnuuxy3Lol6vA6AoCtPT097jB8OxdBsP9ZibrtLV1UU8Hj/yjXwc4KaZLLgx5VHCJU3AoohRBofsjo2N0dPTc+wxwQuEer1OPp9naGhoUWwjcLp/qqouqAnspk2buP322/nRj360IOdMNBqlVqt5v1uW5R33iUSCk08+me7ubgDOOOMMnnjiCZ84+fBxAPj851n4/MfnPwsBn/8cHnz+c3Tw+c+LDyf+quVjwdDejVrI2fpisUihUCCTySyaOeyFmOd3t89CzE2bpsnExATJZJLOzs7D3vZHK5l3fRsORvIMw6DZbKIoCrlcjlwu95zrsRCS+UP9Do6EPZ/PLyrSNDs7C0BPT8+iIASWZTE+Pk5XV9ei8IYARzK+mHwGwDmWGo0Gg4ODC7bMnTt3cu211/Kxj32MU045ZUGWuWHDBjZv3sz555/Ptm3bWLlypffYunXreOqpp8jn88TjcbZv38473vGOBXlfHz5eSvD5z5HB5z/Pwuc/Pv85GHz+c/Tw+c+LD4J9qHaAj0UFy7LQdf2v/u7eROH/b+/eg6Os7jCOP7lsLgQEQ4xJqKHAyBShGcCOoa3CUKQgpTesgaTcbyKio1iFUihWM1w6U0el3HGwgx0J6KgYHFrkKtRChaYKFegokkAkhIQQkrDZ3ezpH8yuSXiz2SSb5AW+n5lMsu/7bvYkgeyT3/ntOc1rw27osc6fPy9jjJKTk22xm4HH49G5c+cUFxenrl272uKJzjcbmZCQYIvtb6VrsyPnz58PatHF5rbMN/W2x+NRTU2NHA5Hgy8dCFXLfKDra3/dxcXFqqmpUVJSki3+LRljdPbsWXXq1MkWu9BI13635OfnKykpyRa7vkjfbF+cmpoasgBeVVWlCRMmKDU1VWvWrAnZvwffriKnTp3yt4Hv379fqampGjZsmLZv367XXntNkjRy5EjNnDkzJI8L3GzIP+SfYJB/yD+hQv5pGfLPzYfC0Q2mfnCq35odqv/svjDg20bVDk8qvsUEExMTbbObQWVlpYqKipSSkmKbltry8nKVlJTYakHBS5cu6cqVK5YL+DW3Zb45t2vz/T/yfY9aY7axKbvsGHNtt46oqCjb7GhijFFBQYG6dOlim1Z/r9erM2fOhDzIPf/88zp8+LDeeecd26yFAeAb5B/yT2PIP+SfUCH/ANdr/15JNFtrtWaXl5fr4sWLtgoDly9fVmlpqW12oJCuhYHLly+HtOrfUqWlpaqoqLDNlrySVFJSoqqqqgZ3fQhly3ywiouL5Xa7lZycrLCwsFZtmQ92lx23262wsGvrMhQUFLRqy3wwvyuMubbLSocOHWwTmnxjuv3220MamnJzc5Wbm6tNmzYRmoAbAPmnfZF/gkP+If+ECvkHdkDH0Q3G6/XK5XL5Z9mk0LZmX7hwQR6PR8nJybZ44jXm2sJ9Ho9HKSkptmgXN+abNQbsNKbaYcAuY7p48aJcLpdSUlJsMWsrXVtQsLq62lZjKikpkdPpVFJSUrNDXLC3A/3Krx2yPB6PvF6vOnToEPRsYnNa5pvi0qVLcjqdSk5Obu63+jpfffWVsrKyNHv2bNqkARsj/9jjeZ38E9yYyD/BIf8Eh/wDO6BwdIO5fPmyioqK5HA4FBMTo+joaEVFRbX4idLlcqmwsNC/ZakdnlB8r+fv2LFjkxZcbE1er1fnzp1TTEyMEhISbDEmX4tvRESEbXbF8IVLr9drm9fPS/YMTWVlZf429vYcU+2W+StXrvgXhG2NEBdIQ0GrpqZGTqdTt912m8LDw0PSMu90OjVp0iTdcccd2rBhgy3+4ABgjfzTvsg/wY+J/BMc8k9d5B/YHYWjG8zjjz+uDz/88LrjDodDUVFR/iBV++P672ufj46OVnl5ueLj45WSkiK3213neqv71D8XHR0d8l84dnw9v9vt1tmzZxUfH6/OnTu393AkfbMDhW+xTDvwtdOGh4fbJshJ12a1rl69qm7dutlmTLV3WbHLk7bT6dTXX3/dLu3+Dc02ejwe/++D8PDwoIJaoHPr16/XyZMn5XK5VFxcrO7duysyMlLGGEVEROjuu+/W0qVLgxqzb/HHkydPKioqStnZ2erevft118ycOVPDhg1TZmZma3zrgJse+af9kH+CQ/4JHvmnLvIPbgQUjm4w1dXVKi4uVnV1tVwul6qrq+V0Ov0f135zuVyW52rfPnnypKqrq5WamqrKykr/ufrvGxMZGRkwtDUl1J09e1bf+c53FBcXp8jIyAavr32f1v4F7wtySUlJ6tChQ6s+VrA8Ho/Onj2r22+/3TZBzhijwsJC/wKHdgkopaWlqqqqslVoqqqqUlFRka3WY3C73SooKLDVWhrGGOXn56tr164h/SNq586dmj9/vjZu3KhBgwb5j/ta1IP9+v/+979r9+7dWrZsmfLy8rR27VqtXr26zjUvvfSSPv74Y40ZM4bgBDQT+Yf840P+CR75JzjkH/IPGmc7Wnb+AAAUN0lEQVSPFe0QtOjoaH3rW98Kyecyxmj37t0aOnRowGq/MUZut9sftpxOZ5ODW/3zTqdT5eXl11379ddfKyYmRrt27VJVVZX/eGNCGdzqh7Mvv/xSvXv3VufOnf27PrR1cKvPtx3nnXfeqbi4uDZ97IZ4vV4VFhYqNjbWNrN/0rXQVFlZ2e6t0LU5nU6dP39ed911l21Ck+9lCHfeeadtQpMkXbhwQXFxcSENTQUFBfrDH/6g2bNn1wlNkpq80OuRI0f0wAMPSJL69++vY8eO1Tm/Y8cOhYWFafDgwS0bNHCLI/9YI/+0P/JP8Mg/wSP/wG4oHN3CwsLCNGzYsKCu8wWETp06tdp4KioqtGPHDj388MN1nuB8wa12UGsouAUKcY0FN6vrrl69qs6dO6uysjJggPMFN4fD0WhYCxTcal8TExNjef3XX3+tuLg4f3tvTU1Nuz/5+lrGfesx2MWlS5dUWVlpq5k233oadtou2DdT2qVLF9sEcenaDkculytkfyxK177/8+fPV9++fTV79uwWf76Kioo6oS4iIkIej0eRkZE6deqUcnNz9eqrr2rlypUtfiwAoUH+If+ECvkneOSf4JF/YEcUjmAbHTt21K9+9avrjtcObm35ev+ysjK98cYbevTRR2WMaVJwC9Qe73u7cuWKZWCzOlb7FaWdO3dWRESESktL/cciIiKCnmVsaXCrfS46Oloul0v5+fm666671KVLlzb7+TTm0qVL/kUX7fL6eV97fUpKiq1mtYqLixUVFWWrn191dbVKSkqUmpoa0tD7yiuv6Pz583rvvfdC8gdHx44dVVlZ6b/t9Xr9s3bvvvuuioqKNGnSJJ07d04Oh0PdunVj9g1AHeQf8k8okX+CR/5pPvLPrYfCEdCALl26aM6cOf7bbR3cfHyL4129elWLFi3SrFmzFBMTU6fFPdCaDi0Nbr7tjxty2223qVu3bjpz5kzQwa32sUBt8o2FOt+x+u21Fy5ckNPptFVoqqmpUUFBge68807FxMS093D8ysrK5HK51K1bt/Yeil9NTY0KCwtDvi323r17tXnzZq1fv16JiYkh+ZwDBw7Unj17NGrUKOXl5al3797+c88995z/4xUrVighIYHQBMD2yD/kn1Ai/wSP/AM7o3AE2FxYWJgcDoccDodeeeWVNn98X3CrP8tYXV2tNWvWqG/fvurTp0+j4a1+QKuqqrI8ZxXmAgU36dqMY+1QlZiYKLfb7Z+tDRTmmhPcfOcbCm71+VrZExISbNUKXVlZqbKyspDParWEb3vl+Pj4kAbMwsJCLV68WNOnT9f9998fss87fPhwHTx4UOPGjZMxRkuWLNHGjRuVmpoa1EthAADWyD/kn9ZC/mk58s+th13VANieL7jVn2Ws//bFF1/o3XffVWZmpowxAYNbQ+30LQ1u9YOWw+GQ0+lUWlqaSktLgwpuwbTT1w9uTQ0+1dXVOnfunFJTU5u8IGJrKikpkdvtVlJSUsg+p8vl0owZMxQZGalNmzbZ6usFAKAh5B/yT0uQfxBKFI4A3DRqamokKeSLZdaecQwU3KxmHHfu3Kno6Gj16dMnYBt9Q+3yLpdLHo8n4PjCw8ObtL5DWFiYysvL9d3vflculyvgTGRrBTcrlZWVunjxYshnAF9++WW99957evfdd5WcnByyzwsAgB2Qf8g/Vsg/CCUKRwDQioqKipSYmNiiIODxeOqEqaYEN6vz+/btU69evRQTE9Muwc3qvTFGVVVV6tmzp+Vip4HeBwpuBw4c0JNPPqlVq1bpRz/6UbN/BgAAIHjkH/IPbi4UjgDgFuL1evXpp5+qf//+Qd+npqamwTDW0FtDIa6hz3Pq1Cn16NHDvwVt7WsbC27113Ko3Sb/5ZdfKisrS7/73e9a+q0DAAA3KPIP0DIUjgAA7aqiokKHDh1qcDHF5ga3qqoqnTlzRgsXLlRsbGwbf1UAAAANI//gRkLhCACABni9Xj3//PM6efKkoqKilJ2dre7du/vPv/7669q+fbskaciQIXW2sAYAALgRkX9QX3h7DwAAALv68MMP5XK5lJOTo2eeeUbLli3znysoKNC2bdu0efNm5eTk6MCBAzpx4kQ7jhYAAKDlyD+ojz35AABowJEjR/TAAw9Ikvr3769jx475zyUlJWnDhg3+XWw8Ho+io6PbZZwAAAChQv5BfXQc3QJ27typZ555xvLcli1bNGbMGGVkZGjPnj2SpNLSUk2dOlVZWVl66qmndPXq1bYcLgDYRkVFhTp27Oi/HRER4V+s0uFwKD4+XsYYLV++XPfcc4969OjRXkMFUA/5BwCah/yD+ug4usllZ2frwIED6tOnz3XniouLtWnTJr399tuqrq5WVlaWfvjDH2rVqlUaPXq0xowZo3Xr1iknJ0eTJ09u8VicTqeeffZZlZSUKC4uTsuXL1d8fLz//P79+7V+/XpJkjFGR44cUW5urpxOp2bNmqVvf/vbkqTMzEyNGjWqxeMBgMZ07NhRlZWV/tter1eRkd88dVZXV2vBggWKi4vT4sWL22OIACyQfwCg+cg/qI/C0U1u4MCBevDBB5WTk3PduU8//VQDBgxQVFSUoqKilJqaqhMnTujIkSN69NFHJUmDBw/WSy+9FJLg9Oabb6p379564okntH37dq1atUoLFy70nx88eLAGDx4sSdqwYYMGDhyoXr16aevWrZoyZYqmTp3a4jHU1liQk6RZs2aprKxMDodD0dHR2rBhg86cOaP58+crLCxMd999txYvXqzwcJr3gJvRwIEDtWfPHo0aNUp5eXnq3bu3/5wxRrNnz1Z6erpmzpzZjqMEUB/5p2HkHwCNIf+gPgpHN4mtW7fqL3/5S51jS5Ys0ahRo3To0CHL+1RUVKhTp07+23FxcaqoqKhzPC4uTleuXAnJGI8cOaLp06dLuhaSVq1aZXnd+fPn9d577+ntt9+WJB07dkynT5/Wrl271L17dy1YsKBO62RzNRbkJCk/P1/bt29XWFiY/9jSpUv11FNPKT09Xb///e+1a9cuDR8+vMXjCSbILV++XEePHpXH49HYsWOVkZGhsrIyjRgxwv8L/cEHH9SkSZNaPB4A0vDhw3Xw4EGNGzdOxhgtWbJEGzduVGpqqrxerw4fPiyXy6WPPvpIkjR37lwNGDCgnUcN3DrIP01H/gHQGPIP6qNwdJN45JFH9MgjjzTpPvVbECsrK9WpUyf/8ZiYGFVWVuq2225r8nisglzXrl2DCmQbN27U5MmTFRUVJUlKS0vTI488on79+mn16tVauXKl5s2b1+Qx1ddYkLt48aLKy8s1a9YslZeXa+bMmRo6dKiOHz+u++67z3+/gwcPhiQ4NRbk/vnPfyo/P185OTlyuVz6yU9+ohEjRui///2vRo8erUWLFrV4DD6NbcG5ZcsWbd68WZGRkXrsscc0dOhQlZaW6je/+Y2cTqcSExO1dOlSxcbGhmxMQHsIDw/XCy+8UOdYr169/B9/9tlnbT0kALWQf5qO/NMw8g9wDfkH9VE4uoWlpaXp5ZdfVnV1tVwul7744gv17t1bAwcO1L59+zRmzBjt379f9957b5M/t1WQmzNnjj+oNRTIvF6v9u7dq6efftp/bPjw4f5rhw8frhdffLHJ42lOkHO73Zo6daomTpyoy5cvKzMzU2lpaTLG+Gfg2nJGcsCAAXXWaqipqVFkZKSOHTum48ePa/z48YqPj9fChQuVmJjYorHU3oIzLy9Py5Yt0+rVqyW1/doQAACEEvmH/NMQ8g8AWKNwdAvytRkOGzZMEyZMUFZWlowxevrppxUdHa3HHntM8+bN05YtW3T77bfrT3/6U0ge1xfI0tLSGgxkp06dUo8ePRQTE+M/Nm3aNC1atEhpaWn6+OOP1bdv3yY/dnOCXEJCgsaNG6fIyEh17dpVffr00enTp+u8nr8tZySjo6MVHR0tt9ut+fPna+zYsYqLi1PPnj3Vr18//eAHP9C2bduUnZ2tV199tcljqi3QFpxtvTaE1PgM4Ouvv67t27dLkoYMGaI5c+bIGKPBgwf7FxXt379/g7vrAABufuSfa8g/DSP/AIA1Cke3gPT0dKWnp/tvT5kyxf9xRkaGMjIy6lyfkJCg1157LeTjyMzM1Lx585SZmSmHw+EPZH/84x81cuRIpaWl6fTp07rrrrvq3O/555/Xiy++KIfDoYSEhGbNuFlpLMj94x//0F//+letW7dOlZWV+t///qeePXvqnnvu0aFDh5Senq79+/dr0KBBTX7s5s5IXr58WU8++aTuu+8+f0gZNGiQvyV6+PDhLQ5NUsNbcEZGRrb52hBS4BnAgoICbdu2TVu3blVYWJiysrL04IMPKjY2Vn379tWaNWtCNo7aGgtz2dnZOnr0qOLi4iRJq1atktvtpp0dANoI+cca+adh5J/GkX+AWxOFI7SZ2NhYyyf15557zv/xQw89pIceeqjO+b59+2rz5s0hH09jQW7IkCE6cOCAMjIyFB4errlz5yo+Pl7z5s3TokWL9NJLL6lnz54aMWJESMbTWJBzOp2aPHmypkyZop/97Gf+4wsXLtSPf/xjjRo1qtkzkvUF2oKzNdeGaEigGcCkpCRt2LBBERERkiSPx6Po6GgdP35cRUVFmjBhgmJiYvTb3/5WPXv2DNmYAoU5STp+/Lg2bNhQZ4HP7OzsVm1nDxTmPv/8cy1ZssR/bV5enlauXKm0tDQWFwWAVkT+CYz80zDyT3DIP0AbMABsoaqqyjzxxBNm3LhxZsKECebChQvGGGOWL19u/vOf/5iNGzeae++914wfP97/lp+fb/Lz8/23Z8yYYYqKilo8lh07dph58+YZY4z597//baZNm+Y/d+HCBTN69GjjdDpNeXm5GTFihHE6neaFF14wb7/9tjHGmLVr15q1a9e2eBw+CxYsMHv37vXfHjJkiHG73XWu8Xq9ZtmyZWbRokXGGGMOHz5sPvjgA2OMMf/617/MmDFjQjYeY4xZsmSJyc3N9d++//77/R/X1NSY73//++bxxx83Y8eONVu3bjXGGPOLX/zC/3P9/PPPzYwZM0I6pr/97W91fm6zZs2yvO6DDz4wc+fONcYYc/DgQfPCCy+EdBz15eXlmfHjx193fNeuXWbMmDEmIyPD5OTkGGOMuXr1qpkzZ47JzMw006dPNyUlJa06NgBA+yL/NIz8ExzyD9D66DgCbKKxGcm0tLQGZ2c2bdoU0rEE2oKzrdeGkALPAEpSdXW1FixYoLi4OC1evFiS1K9fP/8s3Pe+9z0VFRXVWdizpQK1s1dVVWn8+PGaMmWKampqNHHiRPXr169V29mlwDOTPlVVVVqxYoXeeOMNSWqVxUVrW79+vbZt23ZdS7rb7dbSpUv11ltvKTY2VpmZmRo6dKhyc3Mb3SYaAHDzIP80jPwTHPIP0PooHAG4TmNbcLbl2hDStTb2PXv2aNSoUcrLy/O3FUuSMUazZ89Wenq6Zs6c6T/+5z//WV26dNGMGTN04sQJpaSkhCw0SYHDXGxsrCZOnOgPC4MGDdKJEydatZ1dChzmfN566y2NHDnS30LeGouL1paamqoVK1bUeUmGJH3xxRdKTU1V586dJUn33nuvPvnkk0Z31wEAoLWQfxpH/gkO+Qc3GwpHAGwv0Ayg1+vV4cOH5XK59NFHH0mS5s6dq5kzZ+rZZ5/Vvn37FBERoaVLl4Z0TIHC3FdffaWnn35a77zzjrxer44ePapf/vKXIdnqOZDGZiYl6f33368TjFpjcdHaRowYobNnz153vD0WGQUA4EZC/gkO+QdofRSOANheYzOAn332meX91q1b12pjaqyd/ac//akyMjLkcDj085//XHfffXertrNLgcOcJF25ckUul0vJycn+Y62xuGgwGltk1Hcs1LOSAADcKMg/wSH/AK2PwhEANENjYW7GjBmaMWNGnfOt2c4uNR7mTp8+rW7dutW5zzPPPKMFCxbozTffVGxsrLKzs1ttfLX16tVLZ86cUVlZmTp06KBPPvlE06ZNU2FhYcDddQAAQPsh/7QM+Qc3qjBjjGnvQQAAbl5nz57V3LlztWXLFr3//vuqqqrS2LFjtXv3bq1cuVLGGD388MP69a9/ratXr2revHkqLi72bxN9xx13tPeXAAAA0CTkH9xMKBwBAAAAAADAUnh7DwAAAAAAAAD2ROEIAAAAAAAAligcAQAAAAAAwBKFIwAAAAAAAFiicAQAAAAAAABLFI4AAAAAAABgicIRAAAAAAAALFE4AgAAAAAAgCUKRwAAAAAAALBE4QgAAAAAAACWKBwBAAAAAADAEoUjAAAAAAAAWKJwBAAAAAAAAEsUjgAAAAAAAGCJwhEAAAAAAAAsUTgCAAAAAACAJQpHAAAAAAAAsEThCAAAAAAAAJYoHAEAAAAAAMAShSMAAAAAAABYonAEAAAAAAAASxSOAAAAAAAAYInCEQAAAAAAACxROAIAAAAAAIAlCkcAAAAAAACwROEIAAAAAAAAligcAQAAAAAAwBKFIwAAAAAAAFiicAQAAAAAAABLFI4AAAAAAABgicIRAAAAAAAALFE4AgAAAAAAgCUKRwAAAAAAALBE4QgAAAAAAACWKBwBAAAAAADAEoUjAAAAAAAAWKJwBAAAAAAAAEsUjgAAAAAAAGCJwhEAAAAAAAAsUTgCAAAAAACAJQpHAAAAAAAAsEThCAAAAAAAAJYoHAEAAAAAAMAShSMAAAAAAABYonAEAAAAAAAASxSOAAAAAAAAYInCEQAAAAAAACxROAIAAAAAAIAlCkcAAAAAAACwROEIAAAAAAAAligcAQAAAAAAwBKFIwAAAAAAAFiicAQAAAAAAABLFI4AAAAAAABgicIRAAAAAAAALFE4AgAAAAAAgKX/A48nlXsoWEE+AAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11d01b518>"
+       "<matplotlib.figure.Figure at 0x1a13b93438>"
       ]
      },
      "metadata": {},
@@ -2429,9 +2140,7 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "source": [
     "## K-Means"
@@ -2440,9 +2149,7 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "source": [
     "### Expectation-Maximization\n",
@@ -2454,18 +2161,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 67,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAABBsAAAERCAYAAAA64a8FAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAABBsAAAERCAYAAAA64a8FAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzsnXmUHFXZuJ+q6q6u3qZ7evbsYUsCWWUJMaxBPxDw5xHwHFHB4wLIIosREeUDBD92CEICggJ+B1DiEvkUXAMCkZBAIPsySSaZzL71vlTX/vujJ00mMyGTEEgi9ZzT58xU3a66VfX2rfu+910Ex3EcXFxcXFxcXFxcXFxcXFxcXA4Q4sHugIuLi4uLi4uLi4uLi4uLy38WrrHBxcXFxcXFxcXFxcXFxcXlgOIaG1xcXFxcXFxcXFxcXFxcXA4orrHBxcXFxcXFxcXFxcXFxcXlgOIaG1xcXFxcXFxcXFxcXFxcXA4onj3tKBaLrFu3jpqaGiRJ+jj75OLicphhWRa9vb1MnjwZRVH22t4dXz7ZuPLisi/si7y4suKyr+OLy2Dc35GLi8tw2duYu0djw7p16/jqV7/6kXbOxcXlP4vnn3+eE044Ya/t3PHFBVx5cdk3hiMvrqy47GS444vLYNzfkYuLy76ypzF3j8aGmpqa8hfr6+s/up65uLgc9nR1dfHVr361PG7sjUNhfMmqGtmChkcSqAwF8Hrc1ZuPi8NNXhzHIZUrouoGskciVhFAFISPvR+fVPZFXg62rABYtkMiW8AwLQI+L5GgguDKy8fGvo4vLoM5FH5HLi4uhwd7G3P3aGzY6TZVX1/PqFGjPpreubi4/EcxXHfLgzm+GJbFisZWWnuzCJQUACllctKE0YyqiX6sffmkczjIS6Gos3RDM4msioADgoA/ZzH7uPFUhvwfa18+6QxHXg723CWRKfDm+u0UdRNwcNCpjgjMOnYsftn7sffnk4zr/r//HOzfkYuLy+HHnsZcN0Gki4vLJ4p1zV209aapjYaorSx9wn6ZtzbuIJ0vHuzuuRxCOI7Dso07yBd16ipD1FaGqY2GEAWBf6/dhmFaB7uLLocQmmGyZN02PB6xf2wJU1cZJp1XeXtjy8HunouLi4uLy8eOa2xwcdlHHMc52F3YK4dDHw8GmmGyrSNOVSQwwK1Z9nrwiCLbuuIHsXcuhxqJbIF4pkB0Nw+GoCKj6iadicxB6pnLoUhHXwbdtAn45AHbY+EA3aksqZx6kHrm4uLi4nI48Z80j3eNDZ8QLrnkEiZMmDDgc+yxx3LyySdz5ZVX0tTU9LH0Y9GiRUyYMIFEIvGxnG9XfvjDH3L++efv03fmzJnDHXfcAYCu6/z0pz/llVdeGXL/cNj9+i+55BKuuOKKferT3pg/fz6//vWvy/9/FOc4XCnqJo4Dkjh46PP7vCQzhYPQK5dDFVUzYA+x9l6PSKbgesK4vE86ryJ7hp5WiYJAQTM+5h65uLi4HJoMpZfs/MyePRv46HSGCRMm8NRTT+213dtvv80111zDKaecwvTp0znvvPN4/PHHKRTenysuX76cCRMmsHbt2gPWvy1btvD1r3/9gBxruNf6UbLHnA0u/3l86lOf4qabbir/r+s6mzZtYsGCBXzrW9/i73//Oz6f7yD28NBj/vz5VFRUANDT08Ozzz47INPqrvv3h9tuuw1xCMX3w/Doo4/ygx/84CM9x+GKz+vBAWzHGZTgr2iY1ESCAKi6wdb2PrZ1xrFsh1E1ESaOqqUieOiUUZszZw7t7e1D7luwYAGf+cxnBm03TZMnn3ySP/7xj3R2dlJZWckZZ5zB9ddfT1VVFQD5fJ6///3vXHDBBR9p/w8HfLIH9rC6YJo2IaU0XmbyRTa19dDWm0YSBY5oqOKokdWHVIy+Ky8fPaGAD8O0h9znOOCXS1Ou3lSOjS099KZz+GUvR4+qYXx9DI90aIzTrqy4uAzGsCy6ElnimTwA1RVB6mJhvG5ukP1md71kJ15v6d15xhlnsHDhwg81z95fnnzySR566CHOOussbrnlFiKRCOvWreMXv/gFr7/+Ok8//TSBQOAjOfff/va3A2a8WLhwISNGjDggx9pfXGPDPqDrOolEgp6eHnRdR5ZlamtricViyLK89wMcZCoqKpg+ffqAbSeddBKKovDf//3fLFu2jNNPP/0g9e7Q5Nhjj/1Q+/fGUUcd9aG+f6ic43BBkT2MrYvS0p2kJhoCSoaHZFalO5ll0qha8kWdJWu3kVM1KsN+BEGgoy9NW0+KM2ccfUglBdyTt04kEhmy/YMPPsgbb7zB7bffzrhx4+js7OT+++/nsssu4w9/+AOCIPDMM8/w5ptvugoBUBUOEg74yBaKhAMlQ5Nl2fSkcmRVDZ/XQzJb4F+rtiKKAtGQguM4bG7rpb0vzRnTjkKRD53XrCsvHy0jqyKsaepAM0x83tJz102L9r40Pq8HURRo7UmxdEMzQUUmVhHAMC3e29pGdyrLpyeNQxQPjaoVrqy4uLxPW2+KFZtbMUwLuX/RYkt7H7JH4sQJoxlRNfTvwuWDGUov2ZVYLEYsFvsYe1Ti7bff5qGHHuLyyy/ne9/7Xnn7rFmzOOGEE7j44ot55plnuPrqqz/2vu0rH3R/Py4ODTP6YUA+n2fdunW0tbUhSRKhUAhJkmhra2PdunXk8/mD3cX9JhQKDdq2ZMkSvva1rzFjxgymTJnCF77wBf7xj3+U9z/66KNccMEFvPTSS5x99tlMmTKFCy+8kPfee2/AcV588UXOPvtspk6dymWXXUYqlRp0rn/+859ceOGFTJ8+ndNPP52HH34Yw3jf3XTOnDk8+eST3HLLLRx//PHMnDmTRx55hGw2y/e//31mzJjBmWeeyaJFi/bpui+55BLuvvtu5s2bx+zZs5k2bRpXXXUV3d3dA859xx130NbWxllnnQXAddddxyWXXDJg/07WrFnDZZddxgknnMDkyZM5++yzeeGFFz6wDztDHH74wx/u0aWsra0NgG3btnHttddy8sknM3nyZObMmcOCBQvKsV0TJkwA4L777mPOnDmDzgGQSCS45ZZbOO2005g2bRqXXnrpAAvqokWLmDlzJm+99RZf+MIXmDx5Mueee+6A8JHDCcu2B8S+TTtiBLFwgK5klvZ4miVrtvFOYwuO47B6eye/efU9elI5aqIhPJKEJIpUhgN4PBJrt3WiGQbvbW7j96+v5s9vraepow/DOjiJAkOhEDU1NYM+ezJ+Llq0iO9+97vMnj2bkSNHcsIJJ/DAAw+wfv16Vq9eDfxnxQnuD5b9/sq0KAp8+thxAHQnc2zvTvDKyq2s3d6FJIosWbeN519diSNAZTiAJIp4JInqSJBsQWN7V5xMvsi/125j4Wur+fuKRtr70tj2wbnHrrwcWBzHGfAs/T4vs44dR7ag0ZPMsbGlm1ff20JzVwLTsvjb2xv5w5I1REMK4YAPURDweT3UV4bp6EvTk8rRk8yy+N1GfvvaKl5f00Q8nTso1+bKiotLiY54mjfXNxNQZGorw0RDfipDfmqjIfw+L/9et50uN3/PR8LuYRRz5szhF7/4BbfddhsnnXRS2TMil3t/nMzlcvz0pz/lzDPPZPLkyZx88sncdNNNZDLDf0ZPP/00sVhsSGPCjBkzuPbaaxkzZsyQ3x3KULt48eIBc/ne3l6uu+46Zs6cybRp0/jKV77C22+/DZT0q/nz51MoFJgwYUJZtykUCtx55518+tOfZurUqVxyySVs2LBhwL2aOXMmv/zlL5k5cyZnn302qqoOCKMYru7217/+lfPPP5+pU6dy0UUXlfu/fPnyYd/DXXGNDcNA13UaGxvxer2Ew2E8Hg+CIODxeAiHw3i9XhobG9F1/WB39QNxHAfTNMuffD7P8uXLmTdvHiNGjCiHB6xZs4bLL7+co48+mscee4x58+bh9/uZO3fugLip5uZmHnnkEa655hoeffRRNE3juuuuwzRNoCSsN910E7Nnz2bBggWMHj2ahx56aECfFi5cyDXXXMOUKVOYP38+X/va13j66ae5+eabB7T7+c9/jmVZzJ8/n8997nMsWLCAiy66iJqaGn72s59xxBFHcOutt9LR0bFP9+QPf/gDq1ev5q677uL2229n+fLl3H333YPa1dbWMn/+fAC+973vcdtttw1q09HRwaWXXkogEOBnP/sZCxYsYPz48dx2221s2rRpr3256qqrWLhwYfnz1FNPEYlEOPnkk2loaCCfz3PppZeSSqW49957eeKJJ8qGl3/961/l+wklA8PO/u5KPp/n4osvZunSpcydO5d58+bhOA5f+9rXaGxsHNDuRz/6EV/96ld54oknqKys5IYbbhjSWHSo0t6X4p/vbmbRkrW8tGwDjW09JLIFVjd1kMgWUIsG2zri1ERDnDntKI4bV09dZYiedI6OeHqA0glQEfCxrTPOw79fwsI3VvPO5lZeems9tz/7D+769Sus2dZxWFQnWLZsGdYuxpHRo0fz8ssvM3HiRBYtWsT8+fN57733yoYrXdf5n//5H04++WRmzpzJddddR19fHwBtbW1MmDCBP/3pT5x22mmccMIJ3HHHHQOMhYcDlm2zpb2Pl5ZvYNGStfxtRSMt3Ul6kllWNrWTLxpkC0VauhJMGF3DmdOP4sgRVcTCATrjGboT2UHHjIQUlm/cwbw/vM5LyzfyTmMLC19bzY+f/guPvLiEbZ3xg2Z02BdceRmMZpis297Ji0vX8Ycla3ht1VZ6kllaupOs3d6JZljEM3l6kzk+dfQoTp96JGNqKwkoPrqSWfrSgxcnfF4Pf1+xiXmLlrB45Rbe2rCDp/+2nJue+gvPLl5Bd3KwjB1quLLi8p+GbTus3NpONKSUvZV2xef1UBFQWLm13TWm7Qe76yU7Px/EE088QSaT4aGHHuL666/n5Zdf5vHHHy/vnzt3Lq+++ipz587lqaee4pvf/CYvvfQSjz322LD79Oabb3LyySfvMbT8qquu4vOf//zwL3Q3br75ZlpaWrj77rt57LHH8Pv9XHHFFaRSKb70pS9x0UUXoSgKCxcu5IwzzsBxHK688kpefvllrr/+en72s58hyzKXXHIJLS3vVzrKZrMsWrSIBx54gBtuuAG/f7An7t50tzfeeIMbbriBKVOmsGDBAj796U8zd+7c/b5WcMMohkUikcC27T1a9GVZRtM0EokE9fX1H3Pvhs/rr7/OcccdN2CboijMmjWLm2++mWCwFK++ZcsWPvvZzw5QqEeMGMEXv/hFVq9ezZlnngmUFNJf/epXTJ06FQDLsrjqqqvYtGkTkydP5sknn+TUU0/l1ltvBeDUU0+lo6OjrBjbts3DDz/Meeedx+233w7AKaecQjgc5rbbbuPb3/42EydOBKCuro677roLQRCYMWMGCxcupK6urhzrNW7cOD772c+yYcOGfYpNkiSJJ554ojygbNq0id/+9reD2smyzKRJkwAYO3bskKEJW7ZsYfr06TzwwAPleLNp06Yxc+ZMVqxYUb6WPTFmzJiypdRxHK666ioURWHevHlIksT27dsZM2YMDz/8cNmtbNasWSxevJh33nmHOXPmlN2lGhoahgzxWLRoES0tLfz5z38uX8Mpp5zCOeecw/z583n00UcBMAyDG2+8kXPPPReAqqoqvvCFL7B8+XLOPvvsvdzVg8/W9j5WbGkjEvRRWxlCNy2WbdhBdyrP0SOqqKoI4pFENrcZKLJOQdNp7U2RzKl0J7LIHg/JjEp1NAgO5DUdXTd5d3MrAcVLUPHRmczi9/sI+H20dCdZvHILyazK7MnjD5nY69259NJLeeSRR3j11Vc57bTTmDVrFqeeempZFs4991y2bNnCihUryi/mhx56iFWrVvHEE0/g9/uZP38+V1xxBb///e/Lx12wYAEPPfQQlmVx44034vf7ufHGGw/KNe4rjuPw3pZ2tnXGqQz7CVf6UDWDv76zkaJucuSIauoqQ+iGiaqZZApFwn6ZzmSObL5IOq8CDkfUV+FXvDgO5FWNjKqxdP12RlRHEUWBQkEnGirF9G/Y0U1A9nLSpLFMP/LgxlJ+EK68DMawLJas3UYqV6Qy7EcSBXKqzq9fXYnf52VsXSUjqyuIp3MUDZNsUQMBOhMZMvkihaJGU0ecEVURRFHAsmzyRZ2OeIaVW9oYXxcjnlPRLYuaSJB80eTtTa3YjsOZU49iTF3lwb4FQ+LKist/IvFMnnzRoK5ysAfwTvw+L93JHPFMger+vE8uw2MovQTgrbfe2mP4RH19PQ899BCCIHDKKafw9ttv88Ybb3DjjTeiaRqGYXD77bdz2mmnATBz5kxWrlxZ9hzYG8lkEl3XP9I8BytWrODKK68seyAfffTRPPPMM6iqSkNDA/X19YiiWJ7TL1myhGXLlvHMM8/w6U9/GijpVDsTVu5cJLUsi2uvvZZTTz11j+fem+722GOPceKJJ5aPeeqpp5LP53nuuef2+3pdY8Mw6OnpGdI6tCt+v5+enp5D2thw/PHHlz0GtmzZwr333susWbO47777BhhSLrzwQi688EIKhQJNTU00NzezbNkygAHeGx6Ph8mTJ5f/33ntqqqiqiobN27kRz/60YA+nH322WVjQ1NTE4lEgnPOOWdAm/PPP5/bbrttgII+derUcqlCRVEIBoMDzh2NRgH2yU0KSmEHu1ou6+vrUdX9K092+umnc/rpp6NpGps2baK5ubkcnrCvXi+PPvooS5Ys4dlnny0PuJMnT+bXv/41hmGwdetWmpub2bBhA6ZpDvv477zzDkcdddQAY4ksy3zmM5/h//7v/wa03TXOa9dnezAxTAvHcZCHWGHYiW6YrNneSU0kWFb6ZY9EUTfJ5FUkSUQUBUzbIeT3kc6pLFm3jdpoGEX2EvT72NGdpLGtB78ykqb2OFlVoy+TZ1NbDzXRIIZh4/VIREN+wn4fstdDMqvSlczSlchg2w6NbT1kChqRoJ+Jo2sYWR0ZUG7zQHDHHXdw1113DdgWDod54403hmx/9dVXM378eH7961+zaNEifve73+Hz+bj22mv59re/jaIoBAIBPB4PNTU1qKrKc889x29/+9uy8eq+++5j5syZvPvuu2W5+P73v1/2jLruuuu47777mDt37kFPTKoZJqIofGACr1ROZXtXgrrKUPn5+Lwe0vkiRb0Uey8IApppEqsIsKM7SVtviupIyYXWI4m09KTZ0ZNgRFWExvZeDMOiqb2P1t4UBc1E1Q0CPhmPKBLweSkaJnnNYHNbD6NrI8TTBba096IZJrXRMBNH134kk1ZXXvaMbTsYltUfCrPnfrT3pklk1QHKh9cjki4UMWwLpT8pqGHZVEeCrN7aQUVIoTLkJ6j40IwUzd0JJo6uwUGguSuB7Tis2tpOtqCj6iZ5TScSUPB5/IT8PpK5Ajjw3tZ2KsN+tncl2d4Zx3YcxtZVcvSoGsL+A5vc2ZUVFxcoaMaeChINQBBwq83sB7vqJbvyQQkhp0yZMmAuVV9fz8aNGwHw+Xw8/fTTQMk7qrm5mS1bttDU1DTsBPg7xxbbHjrZ74FgxowZPPLIIzQ2NpZ1h6ESZe5k+fLl+P1+TjzxxAGeH6eccgqvvvrqgLZ7y9P2QbqbpmmsXr16UF/OOecc19jwUaPr+pB5DXZFkqSDrojtjXA4zJQpU4DSj7WhoYFvfOMbyLLMfffdV25XKBS49dZb+etf/wrA+PHjy0r/rm5isiwPeOHv+gPNZDI4jkNl5cBVmOrq6vLf6XQaoJypeiehUAifzzcgBmun18Wu7M0ANBx2P4YgCPvtCmdZFvfccw8LFy7EMAzGjBlTniTtyzEXL17MY489xo9+9CNmzJgxYN/Pf/5zfvnLX5LNZhk5ciQzZszA4/EM+/iZTGbAM9hJdXX1oLwjivJ+5YWPY/D9IDL5Imu3d9KZyOAANRVBphzRQFXFYLlI5lQsy8YjieSLOulcEdO2aI+nCSleEtkCkaCC7JFwHJtMoYhl24T8PnAg7PchCQItPUl00yTgK8l5XzqHzythGBa64RBUfCSzpfJHHlGgqBv4fR7eWLsNURCJhhRiFQFUzeDNdc1MOaKBY8fWHdD7cs011wwy1omiyIoVK7jsssvK26644gq+853vAKUVxnPPPZdMJsPSpUtZuHAh999/P+PGjRuUZb61tRXDMPjqV786YLumaWzfvr38ktpVTidPnkwqlaKvr4/a2toDer3DpTuZZe32LpLZAoIgMLomwnHj6kvPeDd60jl2DmPpfJFsoYiml7wYvF6JbKFIVSRIwCfT2ZchnS8SC/vx+7zYtkMsHKAnlWP9jm66EtlSRQLLIqNqKIqXgm6C4yAI0JvJURcN4xFFNN3AcRwWv7sFBIHKkELAJ5PMFXh11RZOmTz+gCcdc+VlMI7j0NydYMOOblStZJw6akQVE0fXDmnUbO1NEVS8WLZNOl8kX9TJqRqCIGCYNqpmEFC8+H1e+voTiVZHAvi8HkzLJhYK0NyT5J3GNiqCCuGATHcyh2Za+BUPmXwRv8+Ladt0p3LUx8IICBimRUEz+MvyTXg8pfFFQGBHd5KWnhRzph91QKvluLLi4lKaEzKs6ZXAIZLb9bBiV71kuOxt3v7KK69w991309raSmVlJZMnT0ZRlGHPX6PRKIFAgM7Ozj22icfjVFRUlL2Y95V58+axYMEC/vrXv/Lyyy/j9Xq54IILuOWWW4b0ok+lUqiqOsBIsJPd+7C3hJofpLul02ls2x50jN31tH3FNTYMA1mWsSwLj2fPt8uyrMOiIsWuzJo1i4suuojf/e53nHPOOWV3njvvvJM333yTJ598khNPPBFZltm6dSt//vOfh33sSKS0ihuPxwds3zXmf6c3wu5tMpkMmqaV9x8uPP744/z2t7/l3nvv5fTTTycQCKCq6gCX0L3R1NTED37wA84991wuvfTSAftefPFFHn74YW677TbOP/98wuEwUHqOwyUSibBt27ZB23t7ew/Z+51VNV5dtRVBgKpIEAHIqTr/WtXEmdOPHGRwEAQBB4ftnQna42lEQcC2Hdp704QDPupiJYt5OOBDEEUKmkFAkdENk9beFPmigUcSKeomq5s6OXpkNV6PRF00VCpr50DOLGA7PnxeL+l8kaDPy4jqCJph0dKT5MQJY8qro0FFRpE9rN/Rxbi6SgLKgRsnYrEYY8eOHbS9pqaGF198sfx/JBJh06ZN/P73v+eWW24BSisH55xzDmeffTYXXXQRS5cuHaQQ7Iy/fvbZZ8vytuu5dxoMpV08B3a+0A/WymNXIsMba7YRCpRCaGzHoSORoTed56wZR+P37T45KLmyb2jpJplVEUWBolaShapwoLyCUl0RZH1zF7btIIgieVWnrS+NqumE/T66Ell6kznG1sewbYfRNZW09CQRRcgWLCqCIh4glS8iiQJVkRCZgoamG0we31A+T0VAQfZ4eHdLO/WVFQe0OoErL4NpbOtldVM7leEAIb8Py7JpbOslkS1w6pQjkIboV1E3aWztpagbiGLJq6E3maWuMszOpzWiqoKNLT2IooAgCCSzBbqTOfJFncqwn83tfVRV+BkRq0AzTMbWROlMZLFEm6JuEPB50WyLXEErGe7DAVp7U0SDCuNisbK8xCoCJHMq61u6mTVp8LPdX1xZcXGBypCCQ8kouSfPxJKi6xA9hCpVfVJpbm7muuuu44tf/CLPPfdc2Wh53XXX0dTUNOzjzJ49m+XLl5crD+7OzTffzPbt2wckzt+JIAiDDBu7L+ZFo1F+/OMf8+Mf/5iNGzfypz/9iWeeeYZRo0Zx+eWXDzpmOBymqqqKJ554YtjXsD9UVVXh9XoH5OcDBv2/r7gj9jCora3dq9eCqqqHpaX9e9/7HuFwmHvuuafsir9q1SpOPfVUZs+eXf6RLVmyBBj+Cr2iKEyfPp3FixcP2P7666+X/x4/fjyVlZX87W9/G9DmL3/5C1Cqv3soIe2llvKqVauYPHkyn/vc58q1d/flvmWzWa666irq6+u58847B+1fuXIl9fX1XHzxxeXJ2fr160kkEgOO/0ETseOPP56tW7cOGHR1XWfx4sWH3P3eyZa2XmzHJhryIwqliXvIL6PIEuuauwa0dRwHv+wlmVXZ0ZMgElSoCCpEw36qIwHi6XzJYACIgsBRI6rRTQsRWLe9i65ElpyqE/DL6KaF49ikC0USOZVEtljybLBNHAF008SyLNJ5lVSuSE00yJqt7XQlsizf2EJjaw/5Yuk3JYkiONCXKXws90xRFMaOHVv+RKNRLMvi2WefZdWqVQPaCoJAOBwuW7J3nVCNHj0aSZJIJpPlY8ViMe6++27a29vL7XZNgLpu3Tqqq6s/tCV8f3AchzXbOgkHfQT7jTqiIFAZ8lPUDbZ3DXxhWrZNJKjQ2pMimS0QDfmpCChUR4MEFJmedA6rP4mjT/Ywri5GUTfQdYO1zZ3EM3mKhokiezFME8uxUIs6fek8+aKG7BWxbBvbtjAtC8ey6U5ksSwbnyyxvrmLtr4MyzbuYFtnHM0ouUcqsoeiZpAuFD+W+/ZJlRfNMFnf3EVNJFRO/iaKAjWRID3JHD2pgZUgDMuiNhJifXMXpm0TCfkJB3zURkIIAvSl8+X7EQ35qe/P9ZHIFNjYUkpQa9sOXknEtCw0rRROk8gWSuOQCJIoUTRMbMdBNwxae9MEFC85VWPDjm529KR4p7GVtt4UllUayyJBhfbeFKb10XuefVJlxeWTSTigMCIWJp3f81iczBUZWVUxpOecy8fLhg0bMAyDyy+/vGxoKBQKvPvuu/vkYfz1r3+deDw+ZFLJ5cuX8+9//5vzzz9/SANUMBgkHo8PMDi8++675b8TiQRnnHEG//znPwGYNGkSN910EyNGjCh7U+w+jz/++ONJJBIEAgGmTJlS/vz5z3/mT3/607Cva29IksT06dMHhWZ82Gp0rmfDMIjFYnR0dOzRwqXrOqIoHpRasB+WWCzGFVdcwQMPPMCzzz7Lt771LaZMmcKrr77KH//4RxoaGli2bFm5bEqxOPzJ73e/+12+/e1vc/PNN3PuueeybNmyAcYHSZK45pq7W/wNAAAgAElEQVRruPPOO4lEIpx11lk0Njby6KOPcs4553DMMccc8Ov9MOxU8JcuXcq4ceMGJXycMmUKv/jFL3juuec45phjWLt2LQsWLEAQhGHdt+9///u0t7czb948mpqaBgxUY8aMYcqUKbzwwgvMnz+fk046iaampiGPX1FRwbvvvssJJ5zAtGnTBpzjggsu4H//93+57LLLuP766wmHw/zqV7+ir6+v7Ap7qNHakyIS9GM7Dj3JHG19KTTdIuDzElC8zDp2LLLHQ0tPinXNnRSKBk0dcfKahiJ7CSkyhmXj83qJhgO096U5amQ14CAA0aAf03LoSecQEAj6veRUnXgmj0ip7JVjC0iSAIKAJDg4lkNvOg9OyXVyXH2M11dvQ/ZKjKmrpCLoI5UvEs92MHV8AyG/D6e0PnJA700ul6O3t3fQdr/fPyj067jjjuPMM8/kmmuuYe7cuZxwwgmkUikWL17Mxo0bueeeewAIBAL09vbS2trK6NGj+dKXvsSdd97JT37yE2pra3nwwQfZvHkz48aNK2eOv+uuu7jrrrvI5XI88sgjfOUrXzng+SmGQ1E3SReK1EZDmJZFRzxbqixiOQT9XkDg2LF15eoTja09FLWSEcLn9eCXZXyyB8O0CCkyogCtvUlqokFMyyq5r4f9ZAtFEpkCXkkkHFSIZ3JkVR2fV2JbdxzTcvB7vViOjSgIWI5AZyIDDngliVg4wN/e3kQkoDCiqgK/z0tXIksiqzJ1fH3JfV8ADnB2c1deBpLOF7FtB0kSKeoGbX1pepJZQCDg87KtM05Dv+fB+h1dbO9MkC6otPWmqaoI4PNIeCQRy7YIBxQsq+RFc0RDySiVLWi09abZsKMHuz+UJqT4qAj4KBQ1PKJAuq2I1W8kdRwH23EwLZvW3jQODhUBBcGBv69oJBYKEAsHsB2H5u4k6UKRSaPryjHlzgEcX1xZcXEpMePoUby2eivxTIFoSCl7O1m2TTKn4pe9zDhq1LCP5zgOOVXDtGxkr6dsGHf58EyaNAlJkrj//vu5+OKLSSaTPP300/T19e2T9/mJJ57It771LR5//HG2bdvG5z//eQKBACtWrOBXv/oV06dP58orrxzyu6eddhrPPvssP/nJT4bUfXZ6jf30pz8ln8/T0NDAa6+9Rnt7O5/97GeB0jxeVVUWL17M1KlTOfPMM5kyZQqXX34511xzDQ0NDfzjH//g+eef5yc/+cmHu2m7cfXVV/ONb3yDW265hXPOOYdVq1aV8zXsr1eZa2wYBrIsM2HCBBobG9E0Db/fjyRJWJaFqqqIosiECROGLci6rpNIJOjp6SkbMGpra4nFYgclFOPrX/86v/nNb3j88cf54he/yA9/+EOKxWI5OdSRRx7J/Pnzueuuu1i5ciVf/OIXh3Xc2bNn8+ijj/Kzn/2Ml156iSlTpnDjjTdyxx13lNt87WtfQ1EUnn76aX73u99RW1vLN77xDa666qqP5Fo/DKFQiMsuu4znnnuOlStXDgorufzyy+nt7WX+/Plomsa4ceP47//+b1566SVWrly51+O/9tprQClWdnfuvvtuLrjgArZv384LL7zAL3/5S0aOHMm3vvUtmpqaBlhNr7nmGh5++GFWrFjB0qVLB13D888/z7333ssdd9yBZVlMnz6d559/fsjqFYcCoiRiOw6bmrvZ3NaLbtp4JZGgImPYNptbe/H7ZN5pbKEyHKAmGiQaVpC9It2JLMWQgm5aeASRqgo/HX1pXnlvM+GAQtgvEw746IxnEBwBv+whXzTo6Mvi84popk1Bt6gMKRQNE5/Hg+L34fN4SsqFbePxSAR9Mn5ZRvFK5Ao6VeEAQUWmoOns6E4yaWwdAgKxcOCA3pt77rmnPJHflW9+85tDJht6+OGHefLJJ3niiSe47bbbkGWZE088keeff768CvBf//VfvPDCC5x//vm8+uqr3Hzzzdx3333ccMMNaJrGpz71KZ566qkBOT3OO+88vvOd72BZFl/+8pf3+BL+yOnXQUzT4p3NbbT1JrHtUgI/X95DIqsy+7hxtPelaeqMU1URQJG91McqyKkanYkMIcWHYZr4ZQ+iAI2tPSRzKpGAgiQKVCg+mtN5ZK+ERxRL2coLOn6fTL5oICEQCvpQdQPFKxFSZIKKl5Dio2iYVIYDOMCRDVUYpk2moBH0+6gIKqTzRbpTOeqiIWSPdEBj8MGVl90RKK22q5rOm+t30JfOIQoisldEFAREUWTSmDpWbmknmSsQqwggSSINVRXkVJ3uVA7ZI2GaFhUBhUy+yHtbWlnf3MXbjS0UNRNzF6Ox45TCwrKqhiQKmJaDInvwy15U3cAvewn6vFQEFUKKTK5oMLIqTK6oc+yYOpJ5lVReJRYOEA35SWZU0oUioiBQH6v4wESo+4orKy4uJYKKzJzpR7OxpZttnXEc3h87xtfHmDSmbojwvKFp602xoaWbdK6IIIJjQ200yLFj66mJfnBuOJe9M378eO69917mz5/P5ZdfTk1NDaeddhoXXnghd9xxB93d3dTVDS931g9+8AMmT57Mb37zG2699VZUVWX06NFceeWVXHLJJXvU10477TRuuOEGnnvuOV588UVmzZrFPffcMyDXzUMPPcR9993HAw88QCqVYvz48Tz44IPlShPnnXceL774Itdffz3XXXcdl112GU899RQPPPAA999/P7lcjrFjx5Z1gwPJzsIBCxYs4MUXX+TYY49l7ty53H333WWv7X1FcPbgV9LW1sZZZ53FK6+8wqhRw7fY/SdzIIwE+XyexsZGbNveo9FiqGSILi6HMvs6XuxL+/XNnfx7XTPLN+1AEgV8shevVIqZDwcUZhw1EtlbWi32ekqT7VKte5NCsZRJWkTAcmy2tPWRyKmE/TKO45BVdUZXR4hn83Qnc/h9MgKQyhWRJAFBANuGumgIQYRMXiMU8FEZUogE/dRVhhlZHWF1UzseSSLs95HIqcRCfkIBHx5JJJEpcMSIao4dW8enjhp5IG73IcPO5/iPf/xjyPjuvX3vo5CX11Y3sXJrG6u2dqD4vMj9q8/pfJExNREmja0HnFJ8vVDK1/BOYyt+n4d4VsXTX42gUNTZ3NqLZpoEFBnTtCjoJkeNiLG5rZdc0SDkkzFtm3ReRfZ6sGwbAYER1WE03SKn6tRVhvFKIiOrI1RFAsQqgqza0k4o4MPrESlqJtFQqeqAZZcSDI6rr2TWxHGMazj8vOU+iI9DXvalrWFZvLxsI2u2tdPUkSCgePF6JCRRJJVTmTSmlmPH1lPQSs8RIF/UWbW1nXBAoSdVKpPrlST6snma2vuwLJuORBZ7mF4pQcXLyKoKsqqOqpmMb6hENyzG18eojgTxekQ2NPcQDftxbBvHgYqQQtBXMmYqspcRsQrmfOroA27MPJjsr6zs+l13/rr/uPdwaIq6Sb6oARDy+8rhV8NhfXMXa5u7iAR9BHwlnaHk5aCTL+rMmjT2kC1t6/LJYfHixYwZM2aAd/nChQu5/fbbWb58+ZCVQvY2XrieDfuALMvU19fvd3lLXddpbGzE6/UOME54PB7C4XB5/+TJkw+7ZJMuLh8VR46o4Zd/e5vuZI6w30euoGPYdskdOeijrS9FVUWorAwAjKqOsK65i0JRI5FTiQT8bOuMkytqjKyOkFN1PJJEUJHpyxTQDBOvKGHZdslFUii5MluOgwikCkViIT+xsJ+g34fslQj4ShnnW3tSFHUTSbTJFXUc22H0ESPoTefIFYoksgXqVI2m9j7i6TzHja1jRHWpykAqp7KtM04iWyDk93FkQ5W7uvEhOW5MHU++/BYFTUc3TRwHTMumJhpCkkRae1LU7lLmUpJERlRXsKMnRSKT73/+sL0zgWGajKmtpDedJ+xXsB3o7EvjOAKSAJZjYzt2uVqAadqIYimGtzKg4A35qaoIUDQsKoIKtg3tPSk000RQQdMtwkEfDVUVdCWyqEUdVTeor6zgnS2ttMXTHDe2jsp+JbInlaOpo498UacqEuSI+ioiB9j74ZOEV5I4sqGKZ/7+Nh5JRDdLuRIs22FMTRTdtFizvYPjxr3/zg8qMtGwn3SuSGc8S3VFgHS+SGtPCgSH3nRh2IYGgHzRIJVViYQDKF6JaEghldOojgTJqzqqYaD354YpaAZHNFRRVRGgN5UnlVNL/Qn5eW31VsbVxZgwupagImPZNh3xDNu7EuiGycjqCOPqYsNegXVxcRmMIntQ5MGqk207pbwrAkNWselN51jX3EVtNDgg6awgCIQDPhTZw/LGFmIVATf3g8tB5V//+hf//ve/mTt3Lg0NDTQ1NTFv3jz+3//7fx9YkvSDcI0NB4DhejwkEgls296jIUGWZTRNI5FI7LdBw8XlP41ktoBaNKiuCLDTIblCVkoZfx2HZFYdVJGiMhzgiIYq/vTWejTdoieZI57JI3lE2npT+Lye/jhtk5yqoRsWskdCL1oIIli2g+M4OA5IHhHHtktKiOUwsSaKz+elM57uj9eUEQQBzTAJKjJFvZTk7/ijR/HullZqIkGOGFGF7JHIF3XeWLuNEyeMwS97eHNDMx5JJODz0pPKsaM7ybQjRzBx9OGXbPZQoaUnidcjUekt5eIQBKjszxJuO5ApqNTuZtAZVR0lX9R5Z2MLiuwhV9TJFIr4vF62dyUI+GRSeRVV08nkNWwcZEkiXyxVrzDt0nkcwOuRsEwbB7BxmDCymta+NF19WUxM/LIPxwHLcZC9EoZpUeH3MfLoCP9ev40xdZWMrYsiigKJbIFXVm7ljGlH0p3Msq65C7/Pi88r0dyZoKk9zuzjxtFQtX8TABfY3hXH75MJ+rzopoUkivhlL4ZlY5o2Ng6OPdB4cPTIGlZsbqUrkSFX1EhmChR0A1EQMHZL0mjpRZJNq9DSffgi1VQeOR1JHmggyhsGIdtGFCWmjBvBe1vbaGzrRepXXEzDJNDvpZPJF/nUkSOpr6zg3+uaGVcfY3RttFzCsyOe4fSpR7CuuYuWnhQhv4wkiqxv7mJLWx9nTDvygIfnuLh8UlF1g+auBJvbevuTTzvUREMcM6qG+n7vOYCtbX34fd4hq9tA6b0hCgItPakDXiLbxWVf+NGPfsSDDz7Igw8+SDwep7a2li9/+ctcffXV+31M19jwIdk9LCIUCmFZFm1tbXR0dAwIi+jp6RlUH3Z3/H4/PT09rrHBxaWfLe29RIKlePmgIpdf3pbtEE/niYYCVFcEKOoGivz+ql1FwIcoCHg9IllVwxEEJEHEtGxyagGfV8K2HTTDQKC/TrPwfk6+0qSgVObQAfoyeSoCPrZ1xvF5PbT1pQn4Sm7XstdDUTdI5VUmj62nI55GBOKZAqdMHo/cH94RVGR8Xon3trYhUMoiv9MNU5G9hPwya7d1MrKqgnDg0FcIRo0aRWNj48HuRhnbdtjc3kdtNERBMwjtknhLMy160znG11Wh+DxYlo3UX55UFEsVTiSp5NVgGCYIpe2abpBXNRSfTFEzsGwLURRxnPfre5cS+5XOo+oWqm6RL+pEQgpr+5OW9mZK3isesYDP66EvnSeoeJk4ppb2eAYpmUFAZMLo2nK/IkGFnKrx1oZmVN2gZpdVMUX2ohkmbze2cN7MY8ulVg9lDjV5yRd1OhJZ6ivD2LZN9S6r/gXNIJ7Nc9KEMWiGNaD0neyRSh/Zg2FYGJaNKAqomjng+LnObTT95RfgONimjuiRaV/6fxx57mWEGo4ot1OLBqlsAb/iZcWmVjrTGQqqQSggl3JIeESauxLURIOE/F66kpmSV0UkwOjaKKJQSl5bVRGkL5Nn2cYdJLIF6mPvG6H8Pi+pnMrKpnZOn3rkR3xnPzyHmqy4uOxOVtV4fXUTRd0gGvLj9Uil8MyCxmurmzhubB1TxjfgONAez1AV+eAwp3DAR0tPco/GBt0waelNkc6VwvZqoyFqIqEDWh7ZxSUYDHLrrbdy6623HrBjusaGD8G+hkXouj4oi/PuSJI0ZJlNXdfp7u5m+/btJBIJBEGgsrKS8ePHU1dX54ZduPzHklU1RlZHaelJkC/q+GUvgiiQVTW6EhmOHFHNxNF1rGvupKiXVgBTuSKrtrZR1E1UzQABbMtBtQwM08a0bTTdRBDAckAUHBAsLLu02owFHklEkT1YtlMqMSeUytL1pnNEggqVoQCiWIq5LBRLSf4UrwfLAbWgQQ1MPWLEIJdIjySRyRURJGFQyIQkioiiQEciy4TDwNhwqGFYFqIoUBUOYlrZfnnxYDkOuXyRvmyBM6cdyfi6GJs74oQUGa9HIp7O8/bGVkzT6jc0iNiWQ17VKBqlUIyirpbkyAHJscFh0Cr2rpi2QyKjks4VGVNbSSwcKHk/OA65oka039CkmyUX+frKMMcfPbJsmNpJyO9jTVMHtZWhQatiPq+HdL4UqrO7t4bL3lH7DVLRkJ9ENo+qGSj91UiS2QKmbTG2PgYOdCbSRIJ+HMemM5FlfXM3alHH5ylNowzDGlB60tKLNP3lF9iGVt5mm6VSuE1/+QWTL70dyVsaG2ynVEnCtmFHb4JQUMErlVY6LduhoBnEwgEUr5eiZpIpaFQEFSaOrikZGnYhGlR4b0v7gNCPnUSCCj2pHKpmuOEULp9oDMsCGFZS1Z1ejrsq9bbtsHR9M7bjDHiP7wyLCPplNuzoJhoK0FAVBpxBv9XdEQUBvb9fu/d12YYd/GvVVgqaUZ6b1FSEGFFTwcyJY6iNhoc4oovLocEnztiwL0ke99Z2X8MiZFnGsiw8nj3fdsuyBh0vn8+zZs0aurq6kCSpnA00Ho/T1taGoijU1dURDocPalULF5ePgpBfob4qTF4tkvWW3Nt7kqUJMzj0pnL88c21TD2iAZ/Xy5vrt9OdyNKbzpHIFDAsC9lTWh1UdaNcUtQGcPoLGDhgWaUJhd8nY1sWCAKK7MW0LCyplDQw7PcSCfrKq9xeSSSvGQiigKaZNFSGqIkEOGZULTXRIM1diSGvycFBcIaeeIiCgGGaQ+5z+WA8kojP62FcQwzNNCgaJqmsSk8yR9EwCSpeVm/rZHtnguOPGU1vOs+q9dvpyxTojGdI51Usu1SGUJJENN0sVyu1AaH/bwfQP8DQsBOHktGhtTfF+Poq/P0hGiBg2A61oQCjq6OcNHEM3ck9JxU0bRtB2LPngjmMvrgMxid78HklxtVFcRwbzbDK44ZuWlRHgry6cguxigAnHj2aDS3dbGrpIZEt0N6XQu0Pw/LJ3kHlGJNNq/ZcutRxSG1dSdWkk8ubQgEfAdlHQPFi26WyeqIoUFB1LNvB4xGpCPg4ZlQ1p049inc3tyIO4c2yM0eJNMRqpyAICDCgQoaLyyeFnXlMNrV0k86XyoVHggoTRtcysjoywJjrOKXy1pvbeulKZHAolcmeOKaWhlgFiWyBdL5IXeXQRl5REIiG/Gxq6WZUdam8sWaYH5hQUtUNKkMDvR90w+SPb67l3S1t1EVDVEVKntI5VaOxvYc1zZ0sXb+DKePqmHbkCMbWxdycDy6HHIe+3+UBJJ/Ps27dOtra2pAkiVAohCRJtLW1sW7dOvL5/D613ZewCIDa2tohvRZ2RVVVamvfj9fWdZ3169fT19dHIBAgFArh8XiwbRtVVTFNk0wmQyKRwHGcIa/FxeVw5phR1di2w5QjRjCuLoaIgEcS8fs8pRd/VQUeSeSv72zizQ3NGIbVrx+WcjpYjoNu2qi6gWnZDDnNFkAUQBQhm9cAAcXrIRby45dlqiNBJoyuJeT3EQsF8HkkbMcmnlWRPSJhxYftOLTHs2xq6SklgayKlN2vd8W0LIJ+HwGfd9A+KK2W10TcVer9QRJFjhlVWu2ddsQI6qMVmKaF7C0lA500po7qiiCaYfL7N9bQ1NFLcWcYDaXVKttxKOoGmm5i2Ta7PqGdJc/Ygw65JwzLpqUnSSpfqskeVGS0/ljfrkSW8Q1VjKmL9cveQHKqxujayiEVV9txwCmtZrvsO2G/j7rKCiIBP5PHNVAZUrAsG59XIhpUmDS2lsqQn3g6z/OvvEtfOl+SF1EAR8A0TCzLQdUM9N0MhFq6r+zJsDu2qaOl+wZsO7a/fF7Ir+BXvGTyRXKqRkCRS0aqgs7WjjiaYTGqJkJDrIJMv8K0K+l8kUlj6sipg8+tGSY+2UPQ5y5GuHyyMCyLtzbuYOn67Zh2KWFwTTSEadu8taGZtzY0l70dHMdhVVMHr67cQjJXoCoSpDYawrAslq7fzpvrm2nuSuDzfrBXhN/nJZ0vktcMJo6uJZ0b/HvdFbVocvTI6gHb3t3SxtrtXYysjqL0/24LRZ323jSGWcolZds28WyBTa29/GNFI73p3Ie4Uy4uB55PjLFh15CHcDiMx+NBEIRyyIPX66WxsRFd14fdtlAoIO3FBUuSJHS99NKPxWKIolj+f6g+iqJILPZ+ubNEIkE2m0UURbzektujZVkkEglEUcTv9+P1elFVFVVVB12Li8vhTn1lmCnj6ihoBmG/D5/sRZE9jKuvYkxtJYZp05XIksyqLNvQzOptHej9yRplr4hl2ZiWhUcUUTwSXs/7K34iIAiUPBwEEa8k4TilMAtJFOhO5SgaBoZlo3hLJe6qoiEs26Gom9THQmi6SVcyS0bVyKkaqm6yoztJVTjAmNoo3akcmlFSRPJFnb50npkTx3D0yBp6UvlSiAYlxbEvnae6IuAaGz4Ex4yqYXRNBN2wiIQUgn4FRfYycXQtNdEQeU2nJ5WnI55mybptbGmP42ATVLyIgoBpWZiOgySJpbKZu6wQl2qrM6TBytKL9G1cRvuyl+jbuAxLHzix1AyTcEAhoxbpTubIqTqaYdKbztGTzDGurpJQwEdvKlcyijkO6XyRgmZw2pTxxCoCxDP5sveDadn0pnIcObKKgOIqj/vLiRNGE/TLODiEg6WSkiG/wnHj6wkrPtL5In2ZPNu7kyxZ10RbXxqPKBIOyDi7JISUPR529SXwRaoRPUM/F9Ej44u8r1TIHgmBUk6aqrCfvKrh9YhEQ37i2TzxdIF0QcUwLNr7MmQLGpPHN2DZDslsAdt2sGybeKaUD+SUyePwSBLpfLFs0NQMk0RWZcq4BjfG2+UTx4bmbjr6MtTHKsplJwECPpn6WAWd8VICXoCmjjib23qpi4WpCCjl8IegUmrbl8qxYUfXoLA2y7ZJZApsae9lU2sPbb0pdNPEsmxG10QJB3ykckMvOPam8jTEwgPe/YWiztrtnSiyt5yTxzAtWntSeDylilghxUehqJPKFgkqMkG/zJK12ykU3fm/y6HDJyaMYl9CHoBhtdV1fUBYhGmaZLNZUqkUlmUhSRLhcLjs/SDLMhMmTKCxsRFN0/D7/UiShGVZqKqKKIpMmDBhwHl7enrQNG3ANlVVcRynbOjweDyYpkkqlaKystKtauHyH4UgCBw3roExtZVs7YiztaMXvxyltjKEbTvs6E4iiCVvB9OyCfi8FE0TAQFJkvBIpfh707IplwxgF8WxtDiMbdkgiAhCafI/ZfxI4tk8yWyBSFDBdhxOmjiGlt40ircU1+0RJURRJOz3EVR8REMKsUiAZZtaGFEV4cQJY6iqCLK5vZdMvkgsHGD6lCMYURXBqrORvRJb2vvKK9Rj66JMPWKEqwx8CDySyMmTxjJhVC3rmrtobOulJhIgGi4lEW3rTaPInn7Dr0VVxE9W1ZFEEa9HQret/hwdQr+8lARGhHLlid0ZTiJAB+hOZImE/HgCAuGgn5pIkIDPy79WbeHC06ZxxrSj2NzWS1NHH5btMLKqgolj66j8/+y9V4wlWX7m9wsfcb3Je9NnVmXZ7qr208OZ4Whohw4kF9oVH/SyWAmgBMhCEPZ93wQJECBHLLAEBOpREFcURYpczYrk0MxMj+lpV13VXTYrfV5vw0ccPcTN6MxKU9XTrrr7/jCD6rp5TcStkxHnfOf//76cxTevW7x9f4eHjR6SlJTpXlud4+rKNLnko2AZGr/y8iWavTE/fG+D+zttzleqqaHifneIriloijLx2sjQGzsoiowmK8SyIAwjQDo8XChfeJHt7//pyR8qSZQuvnTwnyxU8lQLWearRQZjF9v1MXWNOI7JGDoZXaOYNVmYKSKE4K9+epvf/cZ1fvWlS7y31WCz0UOSJM7PV7iyWCNj6vziCxd44+42zf4ICQlDV/ja1RXOzVVOPqYpU76geEHIne0mM2cYNFaLGe5tt7i8WOPWxj6VQuZUj4VqMcNmu4eha+QzScvC0PZ4b7OBH4Sok2SJzmDMYOxzabHGVy4v863n1njt1kP2u0M0VUFTZPwwJoxiKvkMs5Uc63sdslZSTdkajBk7PnEc4/oBqiwzGLtJ6tGBubEEQpLwwggvCCnlLEaOz0azN021mvLU8KURGz5sy8OTPNe27bSawHVddnZ2UpFC05KJwt7eHtVqlfF4TDabJZvNcv369dQLwnEcJEnCNE183+fWrVupN0Qul6PZbNJqtZBlGUVRyGazjEajI74PkiQRxzHRIWOZaarFlC8a+YzJ9fNz/Pj9TfZ7QyRJYmi7REKQVRMjx6QVQsZQVWzPR5GSdgifkDCOmeRLoKkQhElR/IFpnyJLGIqCUGVkScbxPVZqJXRVwdRVihkTXVNZrBaSRWPWZK87IIohb+nUS1nmqwXcIKSYM7m1uc/KbInLSzUuL9WOuNlDUvL/3Pl5ri7Xcf0AXVPP7Oec8uRIkkSlkOGFCwt8fxIvCtAZ2KiyjCrLyb+5mjxuqApjL0DVFMxYxScRHBQJUGTUSBAKgTTx+DgsN3wYI8DO0CFr6RQzFnOVPHPlPCPHR9cU7u+0eOXyMs+vzfP82vyx8WLqKl+9usLzawsEYYhpaE9kbjbl8SiyzFwlz8uXFvnRexvJ7+Gk0sgwNCSRVA4ospRcPxQF1w8wDAUkQRBGxEKgShJ+lCw9KCYAACAASURBVIwORTe58Fu/f0yEQpK48Fu/n44JSZK4fn4BP4y4slxL4k1NHQTJ52salbzFfLXATDHLYOzhhzG77QHn5ip89coKr15eTt/rgGLW5BdfuIDt+kRxTMbUT43dmzLli0yrP05irM8Y/8okYejBbhvXD8+Mh5UkiUouS3doM1/J4/gB7zzYxdBVirkP1g5CCFbqRR7stTF1lefXFvilFy/SHthst/p4QYgkSTR7IzpDm+7IRiKpcjQ0FS8IebDXwfZ8TEMDJEa2e+QzgMlr4vT3v5AxuLvTOlFsEJO48PX9DiPHQ9cUVupl6qX85yLRaMrnky/NzPbDJkE8yXMNw0CWZWzbZm9vL1nkGB8YswghsCyLYrF4JJVC13Xm5uaYm5tLozNd1z1S6XD//n329/eJoiht4ZAkieFwyGAwoFgsIk8unEKIVIw46VxO+i6e1CRzypSnCU1ReHFtnn/9Dy1KGRPH91FliSCMyBg6uqKiKlIiLMjyZIIt0Q4jdE3F1FW8IEKRwBYhQRSjKmAoKuqkbD4x2xP4QUS5kCFnGazvd9nrDLEMjctLNf6D3/gqP7m9wZ3tFuWciWXo6JqaJFN44WQR6RHGcbogfNRALj0nVUFTp4vGT4Ji1uTyUo0fv7/B4kwR2wvQVAU3CChkDIIwnLg1JKJTIWMwBLwgSseOH0XImoTt+oQiEbQO2yd8GCNAWZZ49coKpq6iqUoiaMgStWKO9tA+8tLTxoupJ+N4ysfPXCXP4kyB/e6IaiFDEEVkFA07CMlnDGxPJo4j1EnEbjFj0YlswigmbxnEkUAOQ1w/aZvKza9x/Z/+C3p338DrtzCKM5QuvpQKDYos8fVnVmn1R2QMjXbf5mvPnOPrz67yw1ubtAcjqoUcpq6iKDKOF5DPGOQs/Ug59mljBZi22Ez50hPFMY8JgkiQwJ2kVD2OvKWjqzLN3pjuyEaWpSObBUEY4YcRK/UyGUvn/a0mFxZmyJpJ1cJMMYvt+vz1m3eJ4viI0WQsBDce7HF7q4ksSRi6RtbQ0+q4IIyol/NpclEYCzRFJjNJmFFVhYF93P/Hn0Ql77QG6FoS2R3ZMZuNPllT5+evn6c49f+Z8gnwpZmxfNgkiCd5rmVZXLhwgR/96EfYtk2hUEjy1uMY3/eRJImlpSUMw2A4HB5razgtOhOg1+thGAa2baNpWnpsuq4jyzLD4ZBSqYQsy4RhiKZplEqlE8/lMAfiRhzHWJZFLpcjiiK2trbY2dnhypUrZLPZJ/5ep0z5tHnl8jL39zq8dX8HLwwZ2h+YqBVyJo4X4AVJjKUqJ1UK5ZzFpcUaqizzsNHBD0I0NaIzHKMpKllTBylJG5BkiaxlpGkDmqZwcbHKdrPPz187x1evriLLEsWsyXZzkIiBioLnh9hewOJMEU1NbuTqdCfxM+fXX7nMbnvAdruPHyQVLoaqkjU1xq6GH0a4vo2YiA6GplIrZnj2/DzDkct+b5jsQMkSw7GHqSk4fpRWN3wYI0BFkVFVGUWWcTwf14+4ulQnjGOK2bOr6aZ88miKwj/+5nP8r//mx0mCiRckcbiKTD5j4HoBfhDh+CGSgBhB1tIo502urc6z0ewytD16I5fuRAxQNONI6gQkO5GyLPGrL19iqVZibHsEccxvf/1aKnL0Rh6v3RyjawqSJDFyPEQseGalnkT8TkWEKV8QgjBipzXgzk6LkeOiayrn5yqs1ssfyzjXVOVUPfgwQkDGerLPC+OYly8tsdvu8/qdLco5iyBMDKETwULi2dVZcpM2CwnYavW4svRBtcHNh/v4YUS1cLS9Y689ZDB2WZuvcvPhHhlDww/CZMPEUIljQWswZr5cIBYxcRSxOltONy2CMDoWbRvHgh+9t8F+b8Rs5WhMZiGTGBF/9617fPvlS9Nry5SPnadGbPikd9vr9TpbW1vk86dn0TqOw9LSEsATPzebzVIoFNA0jfF4jO/7qKpKtVpNzSXh5LaG03wkhsNhWhURhiFxHBMEQeoDkclkGAwG+L6ftmtkMpkjx3v4XA44Tdw4ML48+PlBBcaUKU8jiiLz733rBa4s1/nJ+5vcWN/D8QLKOYsX1ua5v9eh2RuTNVSuLNbYbPeRkLiwUCEIY3q2jaVpzFUKvHZznWjSQmF7QdKjKcB2fEQhy8jxJ47TghhBrZhL/RQuLFT5nW9c49/8+Ba265MxdZ6ZLVPNZ9jvj3jxwsKZO45TPh2ylsF/+Jtf5fX3N/nJ7S1ubzfxgohaKctCtcTd3TadwZiZQpaFmRIP9zuUcxZLM0UGGRMnCCjlMhQyJt+/uY6myNidYfr+B0aAJwkOh40AFVni2uosjhsQa4J8xuDKUpGspdPojfnqleqn9p1MOZ25SoH/9B/9PK/desjrd7bYaHTwI1icKVIv5Xiw12Ew9jk3VySja2w0+1yYrzJbyRMDO80+l5fqjF2P129v4QUhh20+JAlyhs7PPbNKNZ8hjgVBHKPKcrro0BSF33z1Ct1hUm6tawq1Yo6FSgFFkXC8kKWZ4mfzBU2Z8jEycjz+4cYDBrZHIWNQyJqEUczNh/vcerjPN66dY65S+EifMVPMoqlyYhStKIwcj0ZvxMD2kCWo5DOU8xa6KnNhvsqD3faZMZUHJr3LtRIzxSwP9ruEYcTYDVAUmfPzBaqFLKos0xk6iXG057O+1+XSQg1ZlnD9kPX9DtVC9th7b7d75CwdVVUo5S3CMCYMI2IRkDN1+rZLGAnGno/jBZybK7NSL6fvMRi7vHBh8cj7todjttsD5ionr2tylkGrP+b+bpvr5+c/ytc9Zcoxngqx4dPYba9UKuzs7KSJD48aOWazWQzDSJMgDp570qL70dQIIQQzMzPUarUjzwvDkG63S7/fT8WCwwLKaT4S/X4//VzLstL2jG63i6IoKEpiStfv98nlclQqFZaXl1Nh46RUC/hwJplTr4cpTzOqIvPSxUWeOz/P//G3b3FjfY9cxkCSJRZnSlSLWSQBV1bq/O43rvGdn95maHvIksRKvUwcQyFjUq8UcH2f3sijlMuQNTS6I4eB47LT7uEHIY4foMgy9WKOe7ttZiv5NMf65YuLIAT39tqoiowENPojVmolLszPnH0SUz41LF3jm8+t8ZUrS/zLP/sBvbGLpSfpE6u1EgvlPJIE33hmhV9/5TLfffseg7GLPBlPlqFg6Qa1YhYRx/RGDs6kVP5JjQBVReG//r1fYLs1oNUfo6kyfhjh9Mc8d26O2fLp4vaUT5di1uTXv3KFF9bm+Vd/8RoSoGsquqomBouxQFNlvv3KFVqDMW/e3aU/cihYOnE1TzlnUcgYrM6WCfyAoRuQz5gEYYjj+fhhzP3dJtutPraftPScn6twZ7vFhfkqsiyhayr/+JvP8fc37mO7AZoqM3J9JAm+9szKdPdxyueeMIr5hxsP8ILwSBuBIssYxcSz4O9vPODXXrnykcr7NUXh2XNzvP7+FmPXY783Sj5DV1OT6Xfu7/Lrr17B0FSurc7x2nsb1EvZYz4PQgiavTEXFxMTWT+MyJo69dLR1usklaJFOGmVG3s+A9sjjCJ+7upq6lX9qBm064X4YYw1ScyoFXJEUYwbhPTGLlEc4vsRfhgiYsHLl5d4+eJiWtUwcjx0VWW5Vjryvg92O49tvyvlTO7stHhmdXbq7zLlY+UzFxs+rd32gySIt99+m729PRRFwTRNZFnGdV1s22ZhYYEgCMhmsx8qNeKkFg3P89ja2kIIkbY/hGF4REA5zUciDENMM7mwyrKMJElcvHiRbrdLo9FgOBxiGAa+77OwsMDs7CyGYRCG4ampFvDhTDKnYsOUzwNhFKMqMt+8fo7O0MYLIyRgMHbojlzu7bapl/O8emWFZm/ETDGLLEs83OtyZ6fJfKXAxn6Hat6inE/Kl1sDm6VqCUWRGDk+lXwGIQR5S2foePzNm3f5lZeSUkNZlnjl8hJr81X2ukOEiJktF6gWMtOqhqeQoeOzUC1yabFGZzgmigVCZOgOHdpDmzs7LV6+uMRLFxdxvIBqMUsYRtzebrHZ6LI2WRCemyvz/maSIvIkRoCKLHN1ucaVpTqXFmo0+yOa/RGqojBfKUz7ZJ9SRq7P1aU6uq7SnXhqVCKL7sChN3J4b7PJ1ZU618/NIisypayJ7QXcerhPd+iwUi9xf6fDubk8GUNjtzMgjGLOzRVoD2xiETNbzBJEMQszRX56Z5Oh7fLypaQqsZA1+bVXrrDXTaJ9s6bGQrV4rER6ypTPI43ekIHtHREaDmNMWhHv7bTS34mflUsLM7z7YI83721TzlvpwtsLYwRwealOozdip91ndbaM7QXcWN9FUxTyGQNJkhi7SSXB6myZ588vAJC3DCxdO1IJ0Rna3Hy4T9ZKoighabu4uFBFkWX+5q27vHhhAdv1afbHQJKKkzP1xOjx0HELBPPVPLPlAo3ekGZvzKji0+gPmCsXeGFtHlmScP2AwdjD0FS+9fzaMWGhP3Yx9bOvG6qS+Aj5YYSlT8WGKR8fn7nY8GnutmuahqqqzMzMYNs2QRCgqir1ep18Pk8cx6mwcVJqhK7rLC0tHWvteLRF40BUUFU1FSAcx0lbK3zf5+bNm4xGIxqNBkIIVFWlWCymrRdxHKMoSvqnqqrUarW0eiIMQzzPY2FhgUajwWg0OvX4DviwJplTpjztRHHiq5AxdTKmztj1eeveDpqqUMpZk/7JgJHjs1Ivs98dEsVJCfvv/Nw1lusl/vJHtxAkE4TOwGF1NilH7I8cFFnCMlVEDLquUsln6AztI6WGB8kHlcLpsVpTng6iSCDLEvmMQT5j0OyPeG+jkcSWZi2ypkFraBPHMXPVAnvtpF1ioVLgG8+ukrdM/uqNOwRRhKXrvHlvh1iIM40AJUkib+n8d//RbwPJTtZsOT+tZPgcEIQRipp4vpRzFg/2Oux3RxQyJoU4ESB3WgMypkpG12n2x0jApaUav/nqVYIo5ns37uOFEbYb4AYBlXyGMI6JYkHZMlBUBVVV0FWZejnP3Z02lxZnyGcSAUpTFZZrpWM7lVOmfN65v9NOTQ1Po5gzWd/r8PzawkdKS3CDkDAWfPO5NVqDMb2JeFgrZZkt58mZOrbnc2N9j/lKgWdXZ5mvFniw22a7PUgqmAtZLi7OMFPIphUJsizxzEqdn9zeYracQwD3dlpkLR1NkSfVTCGKIlPMWsiyxMB2+dPv3aA9dMgaOrKc+EUUsiYr9RIC0jSiMIopZEwypsa5uUoaXbvXGVAr5ojimKHjkTE0Xr68xNJM8Uj7h+uH7HUG7LX7BLFgrpJPPKpOQEzaQ5TpRsmUj5nPXGz4NHfbO50OkiRRr5+ePXtY2DicGnEWh1s0dF1nOBwShiFhGDIejwmCAIBisUgYhggh2NzcTIWIbDZLHMe02206nQ65XI7hcIhlWfi+T7V6vJf3wJPhccd32Atje3sbTdOoVCpH/CQOc5qx5JQpTyOWrpExNVw/xNRVtpo9FFnGMjQGtstitUjOMoiFIBaC3/76s7h+iK4qGJpKGMWUC1mq+QyyLPHG3W2AJMpq7GDqKpVcllLOxPVD/DCikDF42OhO+xo/hxSzJojELAsJ1ve65CwDTVWwvYBKPllUtvqJh8Orl5fxwyhJj1AU+mOXSj5DvZzj2dXZdMwIAZxgBGhoClnT4J//3i9QK54t9E55+pgpZIkmRrFeELLT6lPKWcgk5pD5jIllaOx3R7xyaZmfy5iEcTxZQEhsNXvMlPLMlnOMHA9ZlsiaOlvNHq3+GFNXma8W0BUVxwuRJQkJQWfopGLDlClfVGw/QNfOTmJSZJlYfFDF+LOy2x4gCZH4QmQMmKsce07G0NnvjuiPXUoTgbF8aYmXL5393ufmKjR6I9b3OkgkC3xFjtnojxiMPUCwOFPi7k6TUs7i/k4b2w9Yrhfpj9w0ZtPxfG5tNMibOmM3+W60iW/DYeI4SaB76cIinZHNTntAHIukRWtSYRHHglsbe9zaaCAEOEHEg70Ou50BlbzFxYUZ9Ec8KUaOR72UP/b4lCkflc98RH2au+2fpLBRLpd55513CIKAwWBAFEVompZGUpZKJfr9fuoTYVnWB8plGCLLMlEUMRwO2d/fR5IkstkslmUdM6o88GTI5XLs7e2daqr5qBdGvV6n2WzSbrfpdrssLCyk7RoHnGQsOWXK04osSzx3foEf3HxAOZ+hPbDJWTqO5yNLMnOT3eO8ZbDbHiBLEnnrg3haVZFZm6uwvt+lWshgaCpj1yNr6Ji6xrnZEtViDhELXEJUWSYScdrP6AdhWj45vUE//ViGxpXlGrc29pPEkTDE1E1GtkfO1CnlkuqUgwXh1eX6kV2iAwOzseuTMXQuLsxwcaHKzYcNbj7cJ5pknYtYUCvl+EffuMZcOc/MRGhw/IAwjLAMfZpp/jmgWshSL+VoTUqdARDQs11mS7m0nUFTZfa7o2PVKjPFHMokmldTEkd8RZbIZQxKOYsLCzNoamJYdzDOBFLagjV2fWIhUvFiypQvEqauMbTdY0aMYRQztN0kwhopiQhWnmz8267PVqtPf+ykbWq1Uhbb81HUx19zZSkRFj8MvZGTXBfGLrc3m2w0e5MEG5O5Sp5KIYOuKnSHLm/c2WFhpoCpaVTyWca2T3doY6gqXdul0x8BSaVD3tL5+rVzR/wT4liw3xtRK2T467fuEgvImhqSBK2tMTcfNri6XCOIYu5uN6mVciiyTDmfoTuy0VWZvu3x7sN9njs/hzqJ5o5jwdgNePXKyoc69ylTnoTPfHZ8kt9BGIZHDBwlSSKXy51q2HiYs1ItPglh4/CCfnV1leFwyM7OTnoeBy0ayuQXutfrMRgMmJ2dZTweY1kWOzs7OI6DYRhks9nUBLLX6yVl4K5LNps94hmxtLTE7du3TzXVPH/+PA8ePDjihVEoFOh2u6iqihCCnZ0dVlZWHmssOWXK08xKvQSc5637O4zdgDCOqWQtzi9UMSZ9i7EQKIqExPEJyzMrszR6IxrdEeWsxU67j6GqzBQyGFqymBg6HvVSDlWV2WsOqBWz/N8/uEFn6JA1dWRJ4sLCDNfOzaIpZ+/UTPlsuX5uHk1VeOf+DkPbAyRqhSzn5ivpgi4WIjXcOowkSbx6eZnvvn0P1w+YKWZ4sNdlbbFCtWAxXykgSRK253NlaZZ6Ocv6Xpeh4/HHf/sWYz8ga+qossyz52a5tDAz9fZ4ipFliW88e44b60mv99BJ7pGPtjXEE8PIRzF1lVcuLfGj9zfQVYWsqdHoJa0WM4UciiITx4Iwipkt5QijiLHrsbHX4e/evockJX3rGVPnxbUFFqYJFFO+QJyfq/DazfXUcDkWgp1Wn81mnziOEZKE7frM5DPc3mzyzMrsqaLbwU7+zY0GEhK6piCE4M52k6xpMFvKJhVtjyERBJ9cCL6z3eKnd7YwdZWrK3UkBK3+iIypY6gKlXwmFVMURSISgv3uCENTCDaSjcYHex26Q5uslVRdOF7AYrWAF0a8t9Hk6kpyPn4QEQvBfDnHbndINZ85ssmRMXTiWPD6nS0GY4/nLyR+DpAIos+uzHJjfQ9ZTqJ093sjFqtFRo7H0PZ47vz8tL1vyifCZy42POp34LouOzs7qY/DQaRkGIbcuHHjzGSKx6VaCCGOCRuP8mHaCE4yt3Qch0KhgGmaqVBwuDLB95N4tJ2dndQEU9d1JEnC8zx6vR65XA7Lsrh+/TqDwYDt7W3q9TqZTIalpSVyuRy3b98+01TzrbfewjTNI9+VqqosLS2lxpVRFDEYDCgUCmcaS06Z8rSzUi+xNFOkXspyb7vNYu3opLw7cjg/VzlxomIZGr/04kU2mz029rv40Qxj12dltszd7RZ926VeyrFQLXJzfY9Gf8z6XoexG2AZKuV8hkuLM9zZbjF2fb7x7Op0AfkUk/TYznJxcYacZeAF0TG/jaHtcX315Oq2SiHDr71ymfW9DjudAVEsQMBiucC9vU6aeJLL6Pzk/S38MGR9v00YC0xNZaFaYKlW4qe3t4gjwdWV09v6pnz26JrKy5eWuLxU489fe5dSLnPEoDGOBVEUnxrPd26uQjFrcn+3jaYoPGx0sYykP3yz0cPUVC4uzhAJwQ9ubmBoKne330NVZAxNZW2+iiJL/P2NB/zC82sfOQZwypSnhcQ/wGBou+QsI/FHaA3QNRlVURAIMrrK2uJMGnH9yuWlE++vNx/u8e7Dfeql3LH7/Nj1eW+riYgFFE9ePwghsF0fgSBnPdkcuNkb8dM7W9SKWZRJpdrA9rAsnVLWwgsjtpo91uarSLKEH0QoskSjN0SVZeYuLuJHEaahsmIVGbshqiqzXCjx/IUFqoUMD3Y7jB2f5VqdYs5kqVrk+zcfUsiYJ1ZTyrKEEEkqVhjF6IdE80LW5MULi+y0++y0B7z3sIEqy8wUcrx8aYn56bVlyifEZy42PBpJubm5ie/7eJ5HPDF/MwyDarWKLMunJlM8SapFv98niiLK5fKR1x6upBiPx9RqNfb29k41WjzgJHPLXq9HoVDAtu20asNxnLSiIggCXNcljmNqtVp63vl8nnw+TxRFaQuGaZqYpollWak/A8De3t5jTTV7vd6xKM6D7/KgAqPT6bC/v082mz3TWHLKlM8Dsizxwtoi3aFDozuikDWRJBiME/OkZ5ZnT32toamTkvgkrrI3ctjtDLi8VGPouAwdn97YwQ8jnlud49ZWIxU0BmOXzWafS4szbLf69EYO5fzULPJpR1MUvn7tPN998y7tgU3e0oliQX/sslApnLmLnLMMrp+f5/r5eeJY0B6M2esOubpSZ2D7OH5Aa2BjGhqLMwXu73Wp5RIBers9IGsa1Es5bm7sszZfmbbgfA7IWQY/f22NH9xaxwtCMqaOH4SMbJ9nVuuUc6e3aJbzGV6ZXBPCKGa/O6DZH9M/5zKyPfwoYr87ZL6SRwhBLGJylkEUx9zbbfOCNU8+Y/DOgz1my/mpmDnlC4GmKHzz+nn+7p373N9pc+PhHlEUE0YCLwwRAlZqJYIwYracRE8v10vHdt9t1+fWZuNEoQGStjg/CGkNbDpDm8qh+3MsBO3+mK1mj73eiKWZIn/5o/c4P1ehkDVx/YCxG5CzdObKBUo5kygWdEc2P7j1kO7I5vU7m9zeatHojfAniVi6ppA19KTaQAgWZooIkdxfojAmlzcwDY2dnSGWpqIqCqauM3IDbM9HAmRJYm0+8YO4ulynkDXpj126I/vMCoQk/lKhOzz+vIypcXFxhnOzFXa7Q7798uXpfGXKJ85nPsM5iKR8//332d/fp9lsomkaipKUQAkh0DSN7e1tlpaWiOP4xGSKJ0m1sCwL13WPtGMcrqSQZRnTNCkWi6yvr3Pr1i1M08RxHGzbxrIsyuVyuoh/66230s8slUqpWGCaJt1ul9FohBCC0WjE/Pw8lmWlYoIkSViWRavVOlJpoSgKQRCkppJw3EfiSbwnZFlmOBwyMzNz7GeqqlIulymVSoxGI55//vkn+JeaMuXpx9RVfunFi6zvd1nf6yAEXD8/x7nZyrEoqLHrc3e7xUajC5LE2lyZtYUZLF2jlLMoPbJ4eP32ZpKr7YdHJvv5jEGjN2J1towkQW88FRs+L5RzFt9+5TL3Jztqmqrw1SsrLNdLxzwVukOb21tN9jpDDEPj0kKV1dkKqiJTK+WoPZKz/pc/usVsKcfD/Q7GxARNmniGbLX6zFWSBKSh41Gdig2fC5brJbLmZe5sN2kPbXKWyUsXl5ivHJ/473WGvL+5T2/kks8YXF6qsThTRFVkFmdKLM580IbhBSF/9oObVAsZfnJ7k4yRzE8UWUZTFPa6Iy4tztDojgjCaCpOTfnCUMia/MpLl/iXf/59OgMby9TRZJnFaoFS1kKS4b2NBmvzFfIZgzvbrWML6M1WD1mSzvQ1KWYtbC9EUxQa3RHFnImmKtzbafNwv4skwcX5KhcXa7T6I/7ke+8wdDxypkEUJwbTqiwzV8mRMXSCKOaP/+5tOkMbEDzaoeF4SQqFRCJwjFwPS9foj2xylkEhY+IFIX4YHkmHyBga3aGdViRIkoQiy+x0BhSyyWvkx4iNkiQhS4lR5WmoqoyhKWROSaaYMuXj5Km4Y2WzWS5fvszt27dRVRVJSgySCoUClmWhKEoaJ7m4uHiigeOTLMAPvBOCIMDzvFTEOFg4CCFYXl5GCEG328W2bQaDAZVKBcMwcByHwWDAvXv3Ug+GQqGAECI1XfQ8D9u2URQlbZmI45her0ez2WQwGBCGIdlsFsdxCMMQwzBOPWY47iPxJN4Tuq6nn38a0+SJKV9EDE3lylKNK0vHK3sOGDkef/3GXcI4ppAxEMCtjQYbjR6/+OJFrBPyqPu2izlJsODQxEKSEieIIIxAgCJ/dM8GLwixvYCsoU0XFp8wOcvg+bUFnl9bOPU5+90hf/fOfXQ1yVwPopif3Nlitz04ZuAFyb1k7PrUSjlUWT7SK6ypCvbYIRYCQSIMT/n8UClk+LnC6pnPeX+rwRt3d8hbOvmMgRuE/MONBzy7Osfza8dTbDw/BJJYVkWWieIYeXIdSZJSfOI4MZSWpkaRU75g9Mcuzf6Yly4uIRAosnTkuljMKjzY6/LihQX2u8Pjrx+5j021kGUJXZV59eoK/ZHD+1sN7m23ebjfYa5SYLleolrI0hvZvL/VRAjB0PYIo5jLk7nEZqPLj97bRNMU3nmwRxhGPM4FQgAj1+fNu7sUMgaSlMzpB2OXnqWncZMHBFGIoSlH3ldVZFwv2YCUJemYsBHFMb2hQ3toE0YxXhAyGHsoZ1wrbM+nmDWPtFlMmfJJ8dTMYrvdLmEYHqloOIyqqgRBgG3baNrxhcCTmj9KksT169fpdDrcvn07bXEol8upt8LGxgaQxGAevEbXdRRFodvtIoSgVqvRBo52lwAAIABJREFUbDbJZDJHqiZarRa6rpPNZjFNE9d1sW2b8Xicpk8ctEcMh0PG4zGyLKeL/iiKUBTlSLXDo6LAo6aaB20g/X6fMAxTA8jD1REnMU2emPJl5eZGkhxQPdSrX5u4zt/dbvHcCbGW5XyG9d0OxYwJEmk1VLJoFMhSMqGplU7uCX0cjh/wnZ/c5o++82M2Gz1URSaMYlZny/yzX/sK337lyrHqjCmfPHEseP32FnnLSHv1FUVmTs+z3R6w3x2yUD3aciFJEoWMieMF1Eo5djoDMkJDkpK+XUvXcLyAvGVQyk4jDr9IOF7A2/f3qB/q484qOpau8d5mg/Nz5WOxlqaebLJEccx8pcD9vQ6lXLII8MOQmWyW7sjh3Gx5akA75QvHOw92cVyfezstBIlYmzV1KoUsOVObiHASzd7wxEhY5RFB9zQEYGoqs0s11uaq/PkPb7IyWyZn6sk9XQju7XaQZYn20KGUy2B7Po4XEMeCkRMggDfv7hCLx3/eYWIh6Nsu1XwmFQ33O0OGro8iyxNxRRBPkoyiQ+cTRjHm5N5TzCUCQRBGSZKN7XFrcx8viDE0GUmScP2AnXaf5VqJhWrxWMWHEILB2OPrJ/hLeUGI54coikzG0KYtW1M+Fp6Kmet4POaNN95Id/kPFsvD4ZDRaJR6Cei6TrfbPXGBfFKqxaMcLNp1XWdubo5Go0G1Wj3ymm63SxzHRFGEEALDMBiPx+RyudREERLvhQPBoFqtAhwRSw5Eg4PWDMuykCSJ3d3d1MfBdV2iKGJ3dzc1cjRNk5mZmSPiwqOiwGFTTc/zUsNHXdcxTZM4jlPhYTgcHovOhJOTJ85K8phWQEz5ohDFMRv7vSNCwwEHRm4niQ3nZyvc3WqBBBfmq9zdaaEpCo4XUMlbDGyPV68sn1gV8TjevLfNf/EHf0oUxziTHQw/jAB4sNfhv/3f/4b//o//lv/5P/t3Tzy2KZ8cQ8dj7PrUy8fF7Iyp8XCve0xsALi6XOcHt9apF/MsVIvstvtomsrY8VmqFXH9kF94fm06mfuC0R4kGwvKI204spyUNjd642MLJl1TubAww52tJvVSltZgTG/koisyjhegKTKmpvLs6um+M1OmfB7pjRz+/p37xHFS6ZUxNATghREb+x1mikn8rKWrbLcGfOv5463B89UC93ZaZ36OF4SYupqaP449Hz8IURWJe3ttfD/ECyO6QxtIImplKflzaHs4fohAcGtj/0MLDQcIAa2BzaKm0hmM8f2Ise8zHDsYuo6pJ4awmqKgT64fQgiiOGZhYt6oKQpXlmu882CPQsbgnQe76JpKKffBHD2KYq6s1NluJ62Bz5774LoRhBGdoc3qbJmlQ61c/bHL+1sNNva76bGWciZXV2ZZmik+9j7VH7s83O/SHoxRZInFmSKLM6XpBskU4CkQGw6MHYUQlMtlRqNR2kpxICB0Oh1qtRqyLOM4DvX6cffuR1MtTuLRRbvv+6m/wkHMZqfTSYWFg+M4MKocj8epMDEejymXyzSbTcIw6eHudDoEQUAURceqIqIoot/vJ/1XikKpVErbLoIgwPd9SqUSsizTbrdZW1tLj/FRUeDAVNO2bXZ3d1FV9YhgEscx+XyeUqnE5uYm8/PzaQvJ4fjMw8kTj0vyOCsF5OA4p0LFlM8DyTxBcNK9MylRPHkiUcpZfO2ZVX58exNJklisFmn0RswUM7xyaZlLSzNUCx++quGtezv8J//T/3lmf6U9ESD+4//hj/lX/9Xvcf3cyUkJUz5+YnHyWIFkvESnjJfleomhM8fNjQZZU6deztPuj1mZLfGVS8usLVTJW2e30E35/BELTgjYPfzz+MTHr52bxfF8Npt9ZopZNEWmO7S5ujzLS5cWWa2XpxP3KV8o4ljw/XfXkSRYqpd4uN9NK4ANVUFTFVr9MaaukTE0HD/g0uLx9sh6KYdlJgkvB34nj9IdOrx0cTFteXM9n3u77Ukstowmy+z1hux3hjh+yNJEQJZliTCOcXyf21vNIxUHPyvdkcPSTAFVkZHkZM6xOFNAV1WavSHFrJV6KbQHNsu1EoVDFXCXFmt0hw7fu/GAMI7JT64LYRQzdn1MTeVrFxcZ2h7vPNglt69jGUnLhqYqPHd+nstLtbTiodkf8Xdv3UdRZaqFbPq47fl878YDnl2d5bnz8ycKDnEseOv+Dne2m6iKQsbQiIXgjbs7vHVvh69eXWHpUEzwlC8nn/md68DY8SAqcjwep1UBwJEFsqZpaJp2ZOF9wOFUi5MWtyct2oUQrK+vpwJAGIaMRiMGgwGu61KpVDBNM61miOM4Pa44jtE0jUwmQ7vdpt1u47ouqqqiKAqZTCb1hlAUBdu205aLbrfLcDjENE0ymQy+72PbNrIsp5URnU4nrcJ4NI7y4LEf//jHadSmEII4jtPzXFhYwDRNJElKhQPHcdB1/VjyxJMkeZyWAgIfXaiYMuXTRFVk5ioFOkOb4iMl7P2xy+ps+ZRXMnHCztHsj4nimELGPGYk+WFw/ZD//A/+ryNCQ+S7dO+9iddvYRRnKF94EUU3P3j+//In/L//ze9PvRw+JfKWgaYq+EF47DsfuwHXTonIlCSJa+fmOTdXpTO0EQKqhcwRM7ApXzzK+eR6EAtxxMgtSZmAmVMESU1R+Pqz53hm5DCwXRRZZqaYxZj+nk/5gtLsjxi5PqV8BhHHlHIWvZFDxtASw0fA0FUa/REZXePSYo166XiFmarI/Pyz5/juW3fxg4hC1kx/9/wgpDN0WKqVuLCQVCFHccyb93YZOh6L1QID22O706dve9hewMB2cf2A5VoJRZbQVQXHDeiN3FPPxeu3aLz1XTp3XicOPGTNoHLpFeov/CJG8Wg1RrJ5IJEzdTK6TntgM3Z9hD7xZZFgpz1I5yqvXDpazS2E4Nq5WX5ye4Oh4/Jwr4OiyOQtg+V6mblKHl1VMIoqz52fZ6Ga5/zcDIoiUcpZR1qx/CDkezfWyVr6kUhfgIyhY+oatx42mClkT0xoevfhHre3GtTL+SPXu4MEkO+/u84vvnCB+hnpGVO++Hzmd7EDY8disUi73aZSqdDpdNKWCElKjGK63S6FQoEXX3zxxAXv4VQLz/NSY8nTdvJ930+FDdM0abfbk9JHBU3TCIKAbreLYRipGaUsy0RRhO/7OI6TigSKomBZFmEYHvFKWFpaotVqpYaQBy0Opmni+35aMaGq6hHPhkIhKZfK5XJcvnz5yDEfrh7odDoIIdLWDFVVmZ2dZXZ2FtNMFicHCRlnJU48SZKH53knpoB8VKFiypTPgmurs/zVG3cZ2C55KzGIHIxdJEni0hnGkpCUPC+eEYt4mCCMuLfb5s5WEy+ImKvkubpcx9AU7my3+LPXbuIHHwgNo9373PuLPwQhiEMfWdXZ/v6fcuG3fp/c/Fr6nn/95l1+49WrT3y+QgiIW4hoFwBJmQd5ZlrC/wSoiswLawv88NYGxZyJZWhEcUx36FDKmo8dC1lTf2KBQcRjRPgehPeSB5RzSNozIFxEcAviBqCDVAVJgKQiqSsgz4KwQbggWUjy2f5Fjz0OEUG8j4gaIOlIyiKS/GRj/stO3jK4uDjD7a0GlXwGXVMnpcsOK/XSY8XJk5JwTkPEHUTwLkTbgArq5eT/cQOC90AMQMqBVAApBkwkdRUhVZHogwhBziNJH803RAgfEW6D6IKUn4yXaSLPlLPZbPYwNIWlapHbW03mKnk0RaY9sBEIJv/D9QLml/P8xlevnJo4USlk+JWXL3NzY5+tZg8JCYHA1FReurjIhYVqWtXQ6I3ojx2WayU2mj0GIwfTUClkDBzPJ2cauH7AbqtPIWuxNl/l9f7o1KrH/sYt1r/zR8RRBJPKpTjwaN16jc7tH3Pu1/4ZxZVnjrym0R8xXymgyBKapqApMqqqUDSSlIzOYMw/+dYLzJZzqWnsdqvPe5sNOgObezst7uy0mS/nyFkGMaR+F4eTlExdRQiJuRMScyARNYIwSkXSR5EliVxG573N5jGxwfEC3ttsUi/lT0zI0DWVrKVzY32PX56KDV9qPnOx4cDYMZ/P0+l0kGWZWq2G4ziMx2PiOE5KqgyDxcVFFhcXT32vbDabmj82Go1Td/IhWWCbpsloNKLRaKRxm3Ec4zgOpmli23b690KhgK7r7O/vI4Qgk8mkQsOBx0OxWMRxHPL5PJqm0ev1UFWV0WiUVkQc+DqUSiXCMEx9Gw6qIa5evYqqqoRheMQY8tHqAVVV6fV6SJKEpmnUajVUVcX3fXZ2dtLKhkeTLE7iSZI8Ho3fPPw9/qxCxZQpnxXlfIZfeeki7zzYo9FL3K0Xq0WePTf3sZW2h1HM9959QLM3opTPkMsYdEc2/88PbyKEoJi1+P6766k3Q+S73PuLPyQOvPQ94jBJlLn3F3/I9X/6L1A0A9sL+IM//R5fvbJC5QTfiUcRIkL4r0G4DiQ7FyJ4B9RzoH8NSZoazj2Oc3MVdFXhxvoejd4YRYLz8xWeXZlD+5jcvEU8RrjfARGAPKmuCdcR/hsgKSBXgSwEb0G8A/ISaGsTEWIESgkkFUSMkOdBMiBaBxTQLiOpl59IhBDCQbh/C3E7eQ8RIqQ3EdqLyNqzH8u5ftF5YW2BnGXw3uY+vbGLrio8vzbPxYWPT+ATURPh/tvk30iaASIIboD3PZCtRJBCB+/7IPqgXgGlnownAoRUBFlOFnTKCggf4i2QsqA9g6SuIUmPvxaKuItw/2YidOnJewc/RejfRFZPn69NmeIHEaoik88YFLomI9ujVsxSyWewvSBJZZEkuiObr1xZYbZ09oK1mDX5+jOrOGsLuH6QRA1njGNpQXe3W2RMHT+MeLDTRlFkJFtCVeRksS4nCVNeGBHFMWGUiMsn4fVbidAQnmDILmLiMGb9O3/E1d/750cqHPwgIm/puH6IrinkLZNffukitufTHth0hw7twZhCxsDQVX546yHbrT45y6A1GBOJREgZ2B4CKRW9NxpdwjBibaE6MZ097h9zmM1mj4x5ts9UzjJo9sY4fnDEk2qn3UeapOic9dpGd8Rg7B5pBZny5eIzFxsOGzsuLS2lZoeWZZHNZtPFvhCCa9euPXZ3/MD88XEL24MFtizLDAYDgHR3Po7jVOQ4qK4YjUbpov2g1eGg6uLAL8F13bQ64qCq4kCM8DwPwzDSlo2DxImDKodcLockSQyHQ3q9HmEYEoYh9XqdXC7H7du30+MLw5Dd3d0jZprdbpdarYZlWQRBwM7ODisrK+l3chZPmuRxkmjxUYSKKVM+S8r5DN96fi2JrJT42F3edzsDGr3RkUzwQsbk3k6LkeOzVCvT6o/Tn3XvvXlgKHEcIejdfYPqM18DYLs94M9++C6//MIllutn90OK8C6ED0D+oOdSCAHhA4Q8g6Rd+Yhn+uVgYabIfLVAEEbJdf+MCdzPggjfBxEgKR9MSIVchuCnIM8hqWuI8AHggHIeRCfZyorbEO2C/DySMouIumD/byC85HmSBOFdhPo+WL+BJJ/eJgQg/J9CPEiqXw4eExH4byTjRTnumTTlKLIscWlxhgvzVYIoQlOUMyfkHxYhBMJ/HaTcIQFJRkgFCH8E2stIShbhv5UIAPJqUu2gLCRjhSHoX0eSS4hwE0b/I5ABdREQENxBaM+C9e0zqx6EiBHe3wMqkjJ36HEP/H9AKL+LJP3sbWZTvtjkMwZ73SE5y+CZlVnu7bZo9e002UmaeCjNlQt89cryEwt1lqEdawk4TH/s4rgBP727haEr+EFEGMeM7MSbwQ+ixG9NUyjnLBrdIY5/crpb463vJhUNZxBHEY23/5blf+efpI85fkAxa2FoIYuWjizLvP1glzCK0bXEePrWw31ubeyjTESDuUphUpXhUs1n6Y2SOfnI9Wn2RsxW8pRyFjvdIfVyPond9UOWa6dXpYVRfEyMOQ3xiF/FyPVRn0Bsl6TEoHPKl5fPXGw4bOxoGAarq6tpjKPv+6iqSi6X49KlSx9r3/9oNKLb7dJut9Mqg4P0i8N+DL7vE0URzWYzjeT0PI/hcEgul2M8HqcXwIOqDCFE6p0QRcnE1PM84jimUqnQ6/VSsSKKolS06PV6KIqCricXHlmW2draYjgcYhhGev7D4TA1gRwOh6lgcxDjqWkajuMwHA5TEecsPkySx6N8FKFiypSngY9rZ/pRNhq9Y2ZVQRhhe8mOS29sI8lSegP3+q20kuFR4tDH63/gti0Bb9/dRULi3//ll84WSsJbya64GCOifYjHIOcAHdw/Jw7vJqXU6uUjC4Ypx0kmoJ/QbTO8B/IjwpEYATqIHkKEEO1MSuIlEPqkWmUAyhzEOwjmwH8NECBnQc5A7EG8DfEAIeeQrN859RCEcCDcAGkGEXch2k92vKUS4CLsP0GoSyDXkLRLjxUuvuzIsoQhfwLjRYxBdJHkR9Ip4h6QgbiBENXk73JpMl4EBOsgRUARon2EpEzGSw5kBaRMUiUT3wcxQijzSMZXTj+OuJmMUamGiJrJeEEkVRWihRj/a4RSBWURSb2AJE+9m6Z8wHKtxK2NxsS4UObqch2nHtAbOQRRhKGqyFKya581dYa2SxDGaJrykSoQPT/g1tY+fhBRL+bpjR06Q5tYJD4FhpZUMwRRzG57gO0Hp+4DdO68nrZOnIqI6dx+/YjYIEQSaxsLgaGrbDf7VPJ1cpZBECa+E7PlPF4Q8tdv3OXqSiLybjX7ZAwNJJgp5Nhu9ciYOp2RTbWYRVVkNEVmrztEliUsQ6N+RkVIMWuy0eieKc5EUYw8afc4jK4qRPFjzp1EE/84xdYpnz8+c7HhUWNHVVUpl8uUy8kkxvd9giCgXC6zt7f3saQd+L5Ps9lE1/U0ntLzvDQ68iC6MjFqkfB9n1arlUZYVioV2u02tm2nEZiGkVz4+v0+Kysrqdmk7/uUy2V6vR65XC71dxgMBshykolbKpVoNBoUCoW0SsBxHKrVKvl8nv39fUajEcViMW2fODjn0WiUCgUHEZ2QCAjtdpv5+fkTDTUP87MkeRzwUYSKKVO+yIgTUgzEZMYiSRKGph7JBjeKM8iqfqLgIKv6kRJMAXSH+7z+3h4r1Q7feuFVZCW5ZorgBsL+k6TUHjnZ4VZfhngvKbOXdPC3JqX4xaS8Omojwv8Pob2ArD/3sX8XU56URydk4tCfAgiTloqD5wp78nclWYCGu5P2h9zk7+8DRvK6cAOideIYJOuXT174CW/yUesQbZL4Q6gQ/ATiFqgXQF2GaAMR3kUYvzAtlX+qOIjCECCiRGRIL0IC6INkgpAAF4IHibggl5NxE78PkgbCgXALwofE/JdI+nNI0gn3cOElC63w3eT1sjURNW5APATja6BUILiJCG+D+atIjwpqU760lHIWK/USW40eM6UskiQdqUrwgpD+pPz+3/70NoOxC0gIEVMpZLm2OsvcJBLyJOJY0BqM6Y4cgiDECyJkRWK73Wdoe8iSxMjxGDke+YzJ4f39geORMVRcNzwzKepw2+NZnPS8OIaVeuIbUS1kUyF77AZcWqiCBCPXI5/R2ekMmC3ncHyfYjZZJxSzJraXoTu0iWKB4/nkMyaGqrLT7lPJZ/ilFy6cWYV3brbC3Z1WugF6Er2xy8WF6rFNjdlSnrcf7J553n4YoatKesxTvpx85mLDkxg7Li0tcfv27Q+ddnDYUNFxHDwv+WV3XTc1eIzjOPVUkA+VEh384um6jm3b5PN56vU6cRzT7SbxPNlsFs/z8DwvFSYkSaLdbjM3N4dlWcRxTLFY5P9n771iZMvSK71v7+PDm/Tm5vWmfHd1V/tukkPWkD3kNKQZcSCJGhEYzIsAvY3eBIIQ9KJ3GYDAPEgzAkSOAE2Dbmi62eyqrrblq27V9SZ9RoZ3x2897IjImzfz3rpVXd0sEwtIZEZmxInIc3acOP/6/7VWr9fDcZxJ6sTY9yGXy9Htas34uNgfR2neW/yPJRblcpkkSbAsCyEE1WqVer1OmqaTyYuxbCMMwyNJFsfhgyR5jPHzEBVTTPFJxupMie16h9w9HRjLNHBMEz+KyHsulXyGxijXu3zmGTZf+vbxGxOC0tnPTG7mXci6EZZh8O6dO1xc2GWulIX+H43GpANg3HGQEL6gu9P2N8CYBzpAZtS1thEig1I5iN9AmSemZoD/EDBPQXQT7pFRILK6oJOLCGGhRG5kBKkgbYCxrPX4yf7o+y6ku0AOVBeMWf14uiCkLjKDv0HRBe+bhwo/lQ5Q0VWIXtLbM5bByKIL1yF6wiIA4SCEOxqV/yHK+BZCPFzzO8WHDJEFUUCl/cOkkSzo9SEvaFIBod/jyh9NNM2Pfm5AIkcEwz6QjtbTijaVJEATlSEM/gMq2QHv1w95OKi0qf1C/O/pbZon0Gukp80ohaFlQcIFw0WlbVT4M4T767/UXTXFRxvPnl9BKTUyizRxbYtUpfSHEVIKFsp53ry1TSnnUS1kafWHDPyEmzsNbu00+NWnz3BmaebIdmutHj+5cpf+MGS/02dzv02S6imCdm9IZxAQRDFhFJN1nUNEQ6oUfT/EEALTlGRcmyBOGAZHpRTSch6JcJDW4UmMjGNxeqnKwA8Jopgzi1VQit4wpOA5zBT1+zpNFUJKBNDoDEZE4QgCKvkMQz/i9l5TPzbrkHVtTsyV+I3PniOfebhPQjnvsTpbYqPWZnZE+NyL3jDAkOLYfVzOe8wWsrR6PqXc0edRStHsDnj6zNKHLjuc4uOFj8TRHxs7rqyskCTJpFu/srLC+fPn2djYwLIsPM+j2+1y584dbt++Tb1ep9/vc/nyZcLwcDew3+/z1ltvsbGxQRzH7O/v02q1aLVa7Ozs4Lou/X6fbrc7KabvhVJqIkOAA9+DOI4xTRPLsuh0OpNO5ThZYvz6x9sdx10+++yzZLNZqtUqp0+f5umnn8Y0TTqdDt1ul9lZ7YA/HA6J45iVlZXJc4/9Hdrt9uT2+PmklBO5R6fTmcguCoUCa2trjyQ9GRM+URTR7XYnqRpjaUkURQ8kLSqVClLKI/t/jIcRFVNM8UnG0myBSj5DrdUnTvT7te+HFLIuxYzHja19zixVJ41Hw3Y5881/jbQcpKnfa9K0kZbDmW/+a4zRxYoh4dySJGP55NyYmUKBXvcN6PyPkNwEhhwQDYx+VtopPvhTiN7RXU+Z6hHrpAmgjSKVgYpvapd7NZU+/TIhzIsgDFRa11p4lerCzVgCIVDRuxDvwvDvwP87iNch3oPoKsRXQc6ArAA5XTiqLnrioQNKF34IW5NOSQsV/EB7MTAiGoK/hfgmiCIgIW1raUeyr5MvpA2YupgFXXiqEBXfGa2X4z8DpvjwIYQA61lQHVTaGTUaEkgHIFch6UJ0BeJNGPwV+C9AUhulVLyh15ExqycaZFbLc1R4QEwoAYSj+zgQr6PC1/WaBFRSRw3/arTGTP2V7GlvmHRfP15qwkuNz0WiAPEOabytiQr1cJ37FJ8OWIbBFy+t8WvPnGOpWkSOpv4+c3aJL1w8wVa9w1w5R98P+emVdS7f2WO91mK/3WOr3uHf/e3L3N1tHtpmrd3je2/cwJCSKElpdgfMlLIsVPK4lkl3GLA6WxwVw0PSe2QQcZLQG4bYhsQyJUEUU8q6ZJ3jm3aVc89qIvdhEJLK+WcPbgpYmS2yXe/QGfiUsx7DIKLV9ylmXS6tzU9MHU1DwihhIogSChmdlAHae+LmTp0oSZgr57h4Yoa12TKGlDiW9UheDEIIPndhldW5EnutHo3ugN4woN332W10EQi+8dSZYxOVhBB84dIatimptXra/2qEYRCx2+hyYq7M2WOIiik+XfgHn2wY40HGjjs7O5Ou/Z07d1BKTeQOaZrS6XSo1WrMzMxw6tQp4HAcY5qmXLt2bTLVYBjGxHNhdnaW27dvEwQBlmVhWdZEQhHHMbZtE0XR5G9xHE+mGJKRIUyappimie/7k0mIJEnY2tpiYWGBubm5yeRFNpudTFpEUcTS0hKO43D16tXJRMJYOnGvLKFUKrG/vz9hHEulEvV6HcMwJvGXlmVRrVYnxMP+/j6rq6uPvP/fT5LH/cft/USOTjHFpwWWYfDVJ09xdaPG9a194jilnM9wZnGGN29t8Vc/vcJ+u3swKQ/kFk/zxL/8Q1rXXyVo7+MUZyid/cyEaAAwZcpjizuEseLMgsvJ4uus5V8AHuXiPYHoRd35NOd1Jzz8Cco8pycekluQbKAMPRqvzNMI+zPHj1BP8aFCyBy4z6Oit0YpEoBcBNOG4EcQ/UQTAAgQFf1d1SDxdSIBEp02kgApKAnJDjAcaYpToAzJDUibkF5HJU2U/RSoGNIBwphDpTN6BJ7+qAve1tuWRS2tCH6EMs9o0iJ6B9KWNrIUBsp6HGFeQrzXxfcUPzekuYASz+tkmXQHMLTBo7A0IZW8raU0WEBZEwlJB1JfJ5cQjzw94tH6MLS0SiVAqLeTtjRxJXuj9bKFsp7UJJRwEbKAMucgaQEDva5UBHhgePp+oYOSJ/XriN8CP0IJF4SLsp9Fmif+oXbhFB8RCCGYKWYn3fwxfvzOHVzbpNkd8u7dPXKeTdY7/Fm03+rxH196k//2+ecoZl3SVPGzK+vkPBspBJfv7BBECdvNHgJQaYofRLR7PmcWq7R6Q2rtPp5tanNG00AIgetYDMIYz7bIZ1wEUO/2j3g3zD39KzSu/pQ0frB3gTQM5p76xuS2aRj80y8+xnMX12j1h/zg7dvMFnNUch7efckQhYyLYUhtTGxo/4q37+ySpimb+y0829YNiyimmM0AililFDIOL12+za89c+49/RLGhM/F1Tnu7LXoDnws02B1tsRcKffQqYSsa/Orz5zj5nada5s1ojhBjV73Fy+dZHWuNPVrmOKjQzY8CONYyo2NDUzTPFSEj/0PpJS88cYbLC8vY9vCp086AAAgAElEQVT2JI5RKcW1a9fodrtkMhmEEJOOfafTIZvNUigUME1zErUppZwQBuOiuVQqTTwc4lhrt8ZxnGNZxDiCUgiB7/ukacrS0hJPP/30pNB+EKGSpulkeuE45PN59vf3j9yu1WpYljV5PZlMZrKdNE2p1WqTffIoeNQkj/vxQYmKKab4uEMpRScaEqmEnOngGofXumOZPHlqkSdOLpAqxbWNfb73+nV+dm0DP4qxLIuZosV+uz/hHAzLmaRO3A8pFF86WyeIDE7NS2Zyfc7N/BhDHiYaur2UP/52l+u3Is6esvgX38qTz40vGFJQu6DmdJEqK7ooDV/Rt52vI4yq7mImN1BBgHC//iHvuU8nEpXSDgekKEpWBlMe1sAKmUc4X0KpLwCgghchuAzRq6OkEkePxws1KhhdTUYIE1Ajv4YCiBjUDqQdfR/hjkbohyNtvTlKqjCg/28h/JmensAadbMXwTinC9P4LtDTBanwNOkQ39RrRpbAPDmSVcQ6sQIQ1uO/3B37CYVSoSZ7hAGidITEEcYswvg1HW+rYvD/AsLXIL0KGEAGpAUIkLNAopMphIA00dNOKg80gC39O0z0mpmDpA50gdmDaNXg7yFtIuyRrEvOor09DC3ViDZA+KCcUYSrDdFrmogwlsBcRSC1DCf4Pin/CGkuMsUU90IpxcZ+m2LO5eWrm+Q8+9jkg1I+Q7vv8+N37/DUqaWR2eOQlZkiP726znajO5pM0NfKqYJWz+fOXotLJ2apFrLUR1GSjmUhpKDVG6BSmK/kKGczpCjOrcxyfbtxJFXBKc5w8vnf1/GXSXLYLFJIpGFw8vnfn3guCQEnZkv86mfOYRkGa/NltusdXNs81nzYMCQnZku8dmObx9Y8ijmXhUqO129sYwiJFIK+H7JQzZOkKa3+kNmRUeTt3Sa7rS6LD/G1OLQvcx6l3Pv3VnBtk8fW5rmwOksQahm4a5sfWszvFB9/fOTJhrFBpFLqgcW4YRh0u11+9KMfkclk2NnZoVAosL29TRAEZDKZiUxCCDHxSdjb2yOTyUymJbLZ7CR9YuzTMCYpxsaVnU6H4XCIYRiEYTjxehj7LAghcF0X27bZ2dk59v8ZF+VjjwQp5cSP4TiMn3sscxj7Vuzt7RHHo4JlZoYkSWg2m/i+T6FQYGtri0wmw/nz53/hBf8HJSqmmOLjinY44Kf1G7Sjge6YAGfzCzxeXDlaRI6moV65ts7lOzv0hgE5z0YBhhRUCh7Nrg9KcVx/xDQkQigeX27z5fN7XFrqYogAVBfPPqwXffHHQ3779zZJU+gPFNmM4N/8YY0/+/fLfPULowsJ1dIaf7k46m72dAfTPAkjo0khJIgFVLKBShsIOZVC/TzYGTR5uXELP41QKExh8ERplbP5o+dMISRp0oDgVUheRReL3mgKRmnvhHh7ZOY41ASA2NFSCvuSvs/wJVDr6KJTjbw8fMDTP6cb4P8HvW3CgwmbdBt4U8sp7OdBRKAKIw+INS3FUAmoOsizk2hEIUyUnIPobZR5bjoN83NAKaWjUKM3gEQTTdJDWV9CmsetFwMV34XwbUguo8mCaGQemmoSgDsjmcRoLbEDhDp5ghQYF1GR/krfQq+dGW0cmT6nvV3kHMRvoXgCgaW9GsJXAEunWcgUVAYYakmHsCAdamLD+AKC8bWYo6M6ozdgSjZMcR+U0t4J3UFAnKSY3vHnkyhK2G/3+O6r16m1+nQHAXf2Guw2u9zebpDPOIcSp6SAmVKW3m6D2ztNgjimmHWZKeZI0pQkTYniGNs0sE2DIIpxbJNSzuO5Cyu88NbtI6+heOISF/+L/4G9N/6extWXSaMAaTlUzj/L3FPfOGTubEjJrz1zlh+8dQuFLtRzrs1uq8dCJX9sgZ7POJxdrhBEMa3ekPlSHsvYoedH9P2QSj4DCrb22xhS0O77tPoBwyDkj//uVb71lSc4OV/5hRf/htT+FlNMcT8+8mSDbdvs7e09sFgeSwbG6Q9jE8ednZ1J3OK4+3/vNsfSB2BCZGQyGTKZzEQikcvlJmTH7OwshmFQKBTodDqTKMsxiZHNZvE8DyEEURRhGAb1ep3Nzc2JvKPf73PlypUjRpfdbpft7e3J9o/7Hz3P4+mnn6bX67G3t0er1WJ2dhbHcYjjGN/36Xa7uK7L3NwclmURRRE3btyYGEV+mNGhU0zxaYafRLyw9w5SCOZc/Z5NVcrVrnZmfrq8NrlvL/a50t7itbs3+e7bb9JaB5nYpPkMMBp+r/XJr9ehnGVQ8ogk6HF5yHk2X7lU5rmTr3GidJnNhs1uI8WybM7NdTHEAT3R7aX89u9t0u0dzHr2B/rn3/69TTZeO00uK/WziowmFtI2JI2R5j+ji5FD1yRKd8inZMMHRjPs8WLtCkU7Q8HWhE+cJrzcuIktDU5kZyf3Vck+KnoDgh+D/x09li5tYGTApcY+DE0gCzhaJ29U0DKZDd2FVj30gWyCsvT9YPS7bV14ct9MMDDx+1ANCP5fnVZinUSvVKVH61Ud5IouJO+BECYqTUYmgdP18kGh4lsQ/hTk3MR8U6khBN9Fyd88RPyl8TqEr0LwAwh/rA+pcEY6cqXXC41RLGYeMDW5SAw04Vh6c4wE2NPt4OQuKrqsCUrlat8HcwUh8ijzKUiuQnIHlAnWsn5ekeiJBrqjiYrDl5xC5lDJLkpFU5PRKQ5BSkE+47K138J8wBi+H0Zc29rHs0wKGYecZ+NYBvVOnxtb+3SHAYVjUhAcy6SU9dhr9ShmXcIoxTIktmUQRAmlrIfn2JhSsFVvc3FtnkQpco5NzrXo+UeNIp3iDKtf+2eH4i3vh2lIvvWlx3js5EFkbRDF7DR7KBS7zR6lnIdr6/dJkqY0e0NMafC73/gMSilu7za5s9ugmPV47NQiOcfGNCW3dhpI4VLIecgRqeDZJkJKfvzuOkGUcHF17n0dgymm+LDwkScb5ubmuHbt2iRa8l4kSUKj0SBJEiqVyqEEiV6vNzFxHJMLY0gpyWaz+L4/8WQYeyaMJxRmZ2fxfR8pJVGkTyy1Wm0S4xhFEVLKCTExnlAYExCZTIY4jnnzzTdZXtb657GPxL3EyXhqwTRN1tfXWVxcJJ/PH+t7kM1myeVyLCwsEIYhuVxuIu24e/cunucdIlYsy5okV1y5coUnnnhiKmmYYooPAZuDBmEaM+sekINSSOacPNe7O1woLOIaNv044Hs7b7O7UaN2eY9oLwTPJgh90r0QYVv46y2iW3WUCZ6fMN8M8DMWhmEwc3aWs0+1+OzaKywVtiln9lnIx2TsGMOAjB0citf84293eVDsdZrqv/+r/6oIKJ024HxZF7PJPsTXmXTBD7ENgo/BR8VHGte6O7iGhWscnJ9NaVCxc1xubbKamdEyv2QP5f+NnlqI90bSiWTkoRCiC8MQGKCPy1h3H42610VQ1yEeAm30JEOk7zdJKOnxaP4e6MfFNyDzLxGyiCLS/g7xTW0IeCSqEy3xmK6XDwylUojfBFk9VIAL4aHEEBVdRThaZpVG72o/j3RrNK0EEI1MHl2dCqGG6DVjoKNTnRFRNeB4sunIKwJqkBQhvgZyb8Q79VFpW8t2ZAE4pX08BGCeO5BKkKJTKvxj/tfkILp1iinuw8WVWa5t1EiPWadKKTZrbZRSLM4UdGqDEGRcmyhJEUJiWzp5YiyhuPexcuQT4VoGbRXQ6g3JuDYLlTz2bImrmzViIO85hFHMza06oFiZLbG+16J/TDLFgyDQcoj/7MtP8OUnTh76m2OZLFTy7Da7nF2eYafRodbyUYAUglMLFc6vzE5SrZ7JeVxcnSOMEmZKWaQQ7Da7BFFCedTAGCNJUgqew1wxy5u3tlmeKZL3jtZSU0zxi8ZH/oqgUqlgWRZhGB4hHMbJDeMC/l4Dxe3tbbLZLJZlMRwOj41mzOVyE7+EKIrwfZ9cLoeUkl6vR6vVQkpJsVik0WggpcRxHIrFIjs7OyilMAwDy7Lo9XqTKQfP8xgMBlQqFaIootFoANqb4UHFfj6fZ3FxcTLt8F6+B2NfCdM06Xa7pGl6ZP+MzStt2yYIAhqNxlTmMMUUHwL2g86hwnEMKXREVS/ycQ2b691thn5A62qDUrVIqdEl6oQIVxKlEvlunaTWI86YKEMiXRvHtsgME6K8gbz6JvNLm+y2LC58o4kkwU9sHCvFtQLuLxau34omkwz3oz9Q3Lg1vkASICQCE4SJMuYgegvkiUO6cKUC3Y00ph2Rnwd7ww5Z8+hFnmtY7EUdgjTGkSYqfBl9TNtgLmgzRxSkgsl4O+PUB4U2/3N0YkCa6u4yQyCHJhdAf8wLNMEgOY5oeLjHRwLBi+D9Ez02LyyUsaTJKXH+0HZ08TmDkI+mEZ7iOAQjs875o38S+ZEZ5MjPIXoNPb3gg7EI4u7Ij2G0VlTIAUlljCYe3FGiyOHzxMPXgAK1BeEA5JKWYWT+CYhg9HokmGfAPA3+X2uSTDCJylTGsn6t8j6paLoP1sWpoegUx2J5tshSpcAr1zco3BfhOAwiWgOf2UIWz7bo+yEZx8YyJXnPZrveppT1uNtvEkQJjnVAaAVRjG2aOFJgGJLfeeoMrm2zsd9iv9Vju94hihPiJMWQgv12HykFnm2Tz7hkXRspBX0/Ir3fMfI+mIakms/wn3/1Sc6vzh57Hym1IWWSpvzW5y/RD0JUqh7o4+DaJkvVAvXugELGYb3WPjYtIoxT5sp5DEN7O9zdbfD4yalkaYpfPj7yZINt2zz55JO89tprk2J9PEHQbDYxDINKpUKSJFSrVYDJZEAcx2QyGdrt9sTwEZiYPZqmOYllXF5ept1uc+fOHeI4xnEclpaW6Ha7tFotPM8jn88TBMEk/WFsDBlFEWmaTmQYaZoShiG9Xo9CocDe3h6gSYiHIZ/PkyQJTz311Hvul7m5OTY2Nsjn87RarWNJjDAMJ/vE8zz29vamZMMUn3pEaczOsEUv9skaLguZErZ8f6dC17CJ0uO7wykKc7S9O/19ZC+FVGmjp/kS/aBGa6DAilGNASkpIhFYQYRbHxKlEAtFux9y/qstwlaMYcW89YJg7pTHzFqMJY/vqpw9ZZHNiGMJh2xGcObUmCAxAHsSZYfqa78G6aLSOuCOOqIJOF/7VOvvh3HIjt8kSGKKdoZZp3DEk+O94BomkUow7+vgJipFAqaQugBUrdGEgq0JBHMZoltokmFMGEysRJkUmspHd6rH6KKnGUbGkaQ8iGh4b4+PCMK/Q9lf0d4QJLqINc+BSFFpC0169AAb4Tz3vvbNJw2daMjusEWqUqpugaqde59aaVMHjaj0aBGuQm3SCaN401THWYqcnhAw5kbeHGOiaSyVEegY1BjUPvcTDY/k88IAlK3NZZMMBH+GKP7Po7+JyWtN7achfAUly3oaQ4X6+c2zkHZHzyz0OUdWENZj72PfTPFpgmUY/NZzF7mz12S32SXj2BiGIIlT9rt98p7N8kyRQRAyX85jmXoNnluZ5d2NGuHIj2HgByBsLEN7MAghKBU8NvfbnF6osjRTxBCSvh/Q6fucWqjguTadvs87d/fo+xE518aQgoLn8NTpRe7sNQjDZOSbEBAlKUl68L5yLBPPNvnipTUWqznOLFVp9312Gh26Q51qN1PIMFfK4zkWBc9he7+DvCAeafrgwuoc33312igSM6J4n1ykPwzJe/aEpMm6NrvNHo+f/PCOzxRTPCo+8mQDwPLyMrVajSAI6Pf7E2PGTCZDsVgEdBd/PL1gmiZra2vcunUL0zRxHIckSSZyCCnlZPqhUCiwsrKCYRj0ej3m5+cPSS6y2SwbGxsTacbs7CyVSoXhcMibb75JHMe4rosQgjRNSUczzKVSiSiKCMNwYijpui7NZpNWqzUhP0ql0iTq0jCMic/Ee6FSqbC1tTUxtLzfl2IsBxnvk/ez7Smm+KSiFfZ5ce9dgjTCFAZRmmA3Tb48d4EZJz+RYr0XTmSrXO1sk6gU456CoBsNKVlZitbBB3+apsSkdMIhhiuYr2TJuBH1zpAoTjCDFDdRhDttgiBmmCrSOEY6FobtE2NSnvEJI4trP4OoJ2DJpjIfk8kZHHS64V98K8+/+cPasa9ZSv13QGvt7W/obiUKjJMI93kg1nrxtA1yFWGeQsjiB9nVnwhs9Pf5Sf0mCn2c4zSlYHl8Ze4iWdN55PVyNr/AT+rXcV3r0P0bQZ/TuTlMaWgTcwWaEBhp3UURjAVI2tqngQDt3VAABrqGVB30NMPYptThQIcfj26PCr778MgeHyoButqYEhOsS2BeQKi2Xi9qCMZZhLGGkJkjz/NpgFKKy+0N3ulsIpFIAXF7nUW3zBdmzupj/AjrRQgLZZzRUpV7JoqUUpqMsr523xPH6ISZSCeJkELi6GKe0fGiCPS0xEW1Dj380X1eFJrgyuppp/AlVOd/A+dJkPMo6R7IN+znIL6GSnc0OeJ8QaefJLuQ3tYkifEkwlydejVM8VBkXJvff/5z/PmP36EzDHBMA8c2qRQy1DsD+n6Ia5uszpUmjylmXZ45vci1zX3SVDFTzNL3Qzr9gLznUMllSEnJOjafO7+CISX1dp+NWptKITN5j2Zdm3LOY7ak/c4E8MVLJzENyUuX7/DCmzcwTUG1kCVKUuZKWQqei+daDMOYUs5FIOgOI65u7rPf7mNbBo5lahnIfof1Wpszi1Xmy/n3nJK4FzPFLF+8tMaLb9+iP4zIe45ufsYJgyAm61pcXJ3jF+wJOcUUj4SPBdlg2zaPP/44V65cwfM8PM/DMAxu3ryJ7/uYpsnKysohkmBmZoZOp0MYhiilyOfzE7JhXJjPzc1RrVZxHIdms3ls4kWSJBSLRSqVCr7vU6lUKJfL5PN5XNdlOBxOiAalFJ7nYdv2ZFumaRIEAZ7ncfv27YmnhGVZpGlKvV6n2WyytLQ0kTw86j65cOECV65cmRhSjrcZhiFCiEP7ZOw1McUUn1bEacIPalcwpUHRPiiIhnHIX2+9zpJXphH2MKXBufwCZ/ILD5x4KNs5niyt8mZrHVsaWNLATyJsafJYcYW/3HqNWtBhZ9iiFrbo9vfJWlkEkOZSTDfltMhzZ+cacT+k0+jpYuIeJEHC639t8vV/HhCWEro1AxWlbF6TqNBmd90kU0i49NkDsiGfk/zZv18+0qWUEv7s3y+PigYDzM+ANMD6ZwhhHOqgCntq7AdaCvPj+g3KdgbrnnXQCPr8p81XKdoZ2uGArOlyvrjIyews8gHj4KvZGXb9Dnf7NTxDS/78OKRkZ7lUXAFAyCxKlCG5DvEVkCNDX6kAD9QMpDfAvATJLR1LORmTH2vyTQ6mF8YF4vj2hM2Y4NE9PlIQDsL7XXQXe3wF6yGM6bQcwI7f4u32OvNu8dA62Bo2+JvtN1DAMA4oOzkuFZZZzByfPgUg7KdQaR2VbGsjV0beC+YZhHlC30lW0BKbNiSbo4QJNeIEipAWtVmjcVInTig5Wi+Hp1sefQ0IoA/KGX3FEHxXm4WqAIjBfAwMF5Bgf220NuTBepEngBPvd9dO8SlHpZDld770OG/c3Gan2UUKwTCI6AwCzi5VOTFfxr4vFvP04gztvk/WtXnq9CKOZWrjRCG01HEYMFcq6GJcwXqtjeccJoO1waRL1nWwLYN2z6cz9KnkMzy+Ns8r1zYAhWXpuPm5Yo4UxcAPyWdc5kt5dppdWt0+fhgxVzo85WSZBkmacm1znyhOWJt/f5+9J+bLfDPj0hkE1EdSj4xjcX55hmohg2EcnIcGQcjq7PEyjimm+EXjY0E2gJ4weOKJJyaxkcPhkFwuRxzHR6YR4GC64fr16ywtLbGwsHDEdPHUqVPcunWLMAxpt9tHivGxCWQ2m51IONrt9sTQcTy9MCYvxkTCeKqgWq0SBAFJktDv90mS5JB3hGEYeJ5HFEVsbW1RLpc5efLk+94ntm1z48aNiYdDtVqdTEuMMRwOWVlZ+QB7foopPhnYD7oM45B573Cn3k9C3mqvkyrFiWyVWKW83d5gZ9jia3OXHjgyf7G4zLxX5G5/n2ESoVTKX269xv9y+dtIIQmTSA8wC4E6rZjrDDmXVkmSlG6vQ///q9HeaKDSB3czGtuC//RvHb7530S4HliuoNcGy1Hs71i8+mKeUjVice0g/vKrX/DYeO00f/ztLjduRZwZ6a810SD0yLX3LYhvj8aYL30Ie/eTh/XBPhJxiGgAGMQ+bzbv8vmZs8x5Rfwk4uX6TZpBn2erp4/dliEkn6+e5mRulo1+nUSlLJXKLHilw+vLmIW0pgtMBeBoeUXaBoQ29ZRFiEfFHcHoS3EQXWigZRfoxzwkbeB9eXzEtyDdm5ILD8C1zjZ50ztENKRK0Qh6vN68w9dnLzHnFenHAS/U3uXZyinOHBN7Cug4UffXUfEWpJuAgTDXRukU4+hIGyVyeoJBWKPUCQGiq4ko8mCu6vWSBCNCIDjyXI++BmAixSDQZpDSg2RdJ4+YVVA1EJ8DQgheAO93EHKagjXFz49SzuPrT52mOwwY+CFJqnjp7VsUs+4RogEg41qszZfZqneQQmKZBoaUDMOIME44uVDh+dVZfvDmbbbqHbp+QDk3SgpKEnqDkHJBJzt0BgG2ZWBbklqrRyWfwTYNZktZ0lQxDCL6UcwwivFsk5XZEvnMyK9EadN42zCOnWoypCTr2dzYrvPrnz1/5O/vuV/yHr/x7HlevrrOfPmoNx3oVIskUZyYezDBOcUUv0h8bMgG0N38hYWFie9AGIa89dZbE+nC/RBCsLq6ysLCAs1m81jTRdu2uXLlCr1ej3w+P0mlCMMQKSVLS0sMh0Pq9Tqu6xKGB11E13UpFAoTAsNxnMkUhed5E4PGKIooFAoMBgPiOD5CjFiWRbfbZTgcUqm8P2bTtm3Onz9PGIZHki7GGP8v73fbU0zxcYZSimbYp+Z3AAhVwv0zhalS3OjtkTW1nlMIgSUM5t0iO36bzUGDtdzRbkCcJtzo7nK9t0OQxPhJwB9d/w5+Eh11zh6Zpe0WB9TiIWs/Nci8GrHx462HEg0aAn8Af/HvcvzOv2oTtiPyZUV9N0OvKVFK8qf/1yq/+9/tU6oejEfnsnLUjbwXEnDB/ec6ck7ZEL2NMi9MDdrQ/gn7fodG2MOWJvt+F9s4fK4Okoi7g33ydgZrRBK4hsWcW+Rmb5cz+XlK9tHiahAHXOvucKun/XtOZGYo2dmjRFa6A85XINnS0w3JHXQBWQaRBWHrdAjVQheOggN5hMtBWoU9+h6hyQePA6PAgzX36B4fMchlVHRlSjaMEKUxu8M2nXhIxrBphn3y1mHddDca0ox65Ex30mXMmg6ONHmzdZfV7Myx01OtsM+VzhabgyamtDmTX+BsropzyLw1BIbgfAOia9qwM93VJpCyBOT1+S6+CqqLXgtH3+ePvgYUel2N0kakBJnT8g2GWi6RNkH1EDKPEgqV3EXIKZk5xYeHvOdMPA2eu7jGDy/fppL3jhgp9oYBnmPz+89/noEfcbfWJE5S5ko5Ti1UKOV0VP0/+uw5Xr22wZu3tzGE0KvcMDi1VGGhnKc3DKl3dKS1FPLAl0EKKnmPZndIPuOwOldivpxH3hPT2en7WIZBJqu9E1o9fd97SQelFH4Q49gWzjFmkI+CE3Ml1vea7Lf6VIqZSfQlQBQn1NsDnjy9SP4+k80ppvhl4WNFNtyPe6UEY6nC/dMLjz32GNlsltXV1WO3MZ4O6PV69Hq9iSTh3ukA0zRpNpuEYXiIKHAch2q1Sr1ex/M8FhYWDkkZpJTMz8+zvb1NPp8nk8mwsbFBFEWHjC7H983lch9I6vAo++HChQtTGcUUnxokKuXl+k3u9PcxpQSlaEVDWkGPWSc/+TD2k5AgjTAw8OTh90fOdNgY1I+QDXGa8FLtCnt+m4qTYxiH/O/X/oYwjXkYFJAYis0vKEp/soeKD5OksYrYZYMBXTLkmWcFU1howkHwF/9nhfJ8wuyyy+ySSRwp9rcE0kz5f/5XwRd/I8eTX2hiGP17tiqYFBjGJbCfmhjMCWGj0nEs4qf73OAnIT/Yu0Iz7GNKSaIUe34LieSx0sFEWC/2te4ecahIlEJgCsme3z5CNgzigO/tvk2QxJQd/bf1wT4bwzq/Mv84hVGBqpQeiRfGAhizKDkP8dujwtGAtK7H4JMETRpYo+/jYxxxQCQk6I93CZRGCQTjCMQDUuqRPT7M89o/QHU+wN795KEV9vnB3hWGaYg18n65299nKVNiOVOd3K8Z9gCBJQ0McUAsmdIgUSmtsM+ce5gUrAddvrd7GUeaVJ0cqUp5t73J1qDBN+YfO1h3aggKhDEDxgwqrOopCFnQnggEekomGZuKuuj3+tjbQ+OR18C93g/0IHXBLB82nJx4jgA4o8jWKab4xeDEXAnBSV65vsFWvUOz79Pt+6RKsVgp8Jufv8BsKQfA2sLxXf2sa/PcxRNs7LfJew7SELiWNSEN8hmHYlZLFSRQLWgJpmuZOmpSCbabHeZM/V5ViSCME4IwplzwsH2Dci7DycUyt7Yb7LZ6miIWMOYtFip5sp5Oo/ggsAyDrzx+ijdubnNzpzFpcKC0VONzF1Y5vThtNk7xD4ePNdkAB2TB7u4ut27dmngvVCoVTp06dcQ48TiMpwPG6Q73wzRNlpaWuHnzJsVikTiOMQyDbDbL7u7uxMNhOBzi+/4hsmI4HJLJZDAMYyLt6Ha7tNvtCXlRrVbJ5XL4/tEc6ve7H+6VmTwsOnOKKT7JuNnd5U6/xrxbPIjEtXO80N/nVnePM4WDWDk/iSjZ2UnRdy+OmzvYGbbY9TsseNqQ6k83Xya6j2hIBgGN77+Dv9XEXSpT+foljIwDAkISmt/08K4cFG4ttc+rvIhCkZIgMbjK63xGfZWSmAGg31F4xVmc/Aku/2ybKBjiZlIyhdGwyc8AACAASURBVDy17Ty9zh1uXB5y9kkPSRcojnT/th5zdp7WxaLUr1upAKSLLlo/3XitcYdu7B+S2GQNhx/sv8ucV2DGOYhy7MUBa9lZPPPoOfU4f69rXT39MuMefLZUnBzNsM877Q2+MHMOGMltZBGlhgjh6SkHkR+NyIf6WCYSbfgIEyPJSQEJB+RDAlggFsFYG0Vion+HwbggfDSPDwuc5/W4vjGNTUtUyg9rV5FSMG8frBcJvNq6TcXOT9ZGqqAf+TxeWsW4b6pKcfz55dXmbTKmTc7UXUgpDObcAnt+h/X+/oH0Qnij1IrRxJba1dGSQupJBlHWsgYjA8l44uVoMfNoa0CgLxebo58tMOc0AZYOwJofFTjiIC0D/2jU5RRTfMhYnimy3+mx1+phGwarc0VynoNA8KN37jIIIi6szD7UmNW2TM4szbC536KcOWxwK4Xg4uoc797dY32/xdpCmSCKiZMUz7ZoiCG/+fmLDIOQWrtPPGoiVIsZMrZFGCXkMw6GlJxdnmF1tkSrNyRKEizDoJTzcGyTvVYP0/jgE4aWafDs+RUeW5un3umTpArbMpgt5n6u7U4xxYeBjz3ZANpboVarkclkqFark67+7u4utVqNCxcukM0+XDd4b7rDcYW5lJLl5WUWFxcnkgzP86hUKpRKJTKjE1QcxxMyYXd3d5IIEQQBrutimiblcply+fCHcBzHPzchcL/MZIopPo1QSnGls03FOWzGZErJM5WTXO1sk/NdrWZPFRnD5lR2DkMe/kDuxQGXCsvEaUKsUhxpIoRgfVAnOyomOtGAa93tQ0VD9611rv7Bn4BSpH6EdC3u/tF3OP8//S75J1ZRAsKv5XD/jz2Er4hVxKu8SMIBYZGOisFXeZGvqd/GFONupqJd6zHsBwghCQYhphnSrkekaYHGfoZuO6VYPqnbkioC1RxttKtd5I05HXmZ7oP9xfcZy/fJwyAO2BzWmb2HUADIWg6XCitsDpokqUIICNKYvOlx8r5pF6UUCYo5r0CYxiilcAxN4tzp1yjZRxMailaGzUGDOE0O5BTmYxC+iJKLQDQqHJU+dsZpkLfBPgf+tdFWxmt2XETaaELBA3ztz5HucBB1EQEloD55HQ/3+DDBekY/t9pHmOc+2E7+BKEedOnHwRHvl1mvyEpYZX2wP5puEaSkVOw8i959n/dpgikkJSuDn0QYQnuDDOKAVtA/sm2AvOVy+x6yQQgbZZ7VMgkxw4RoUskomaKgTSSVDck1DkenptxLPDx8DYBeUydB+kBBEwpK6akGFUMagmqAtYoQDiodABbCnPpETfGLxbXNGlc39jm7NHNIwgCQJCmvXd/CsQxOLVQfsAWNCyuz3N1rMgwiPOcwAW8akrmSjq8s5z06g4CMbfGPP3eR9f0Wu80uS5UipmFwd69FkqRsNzqEUcJytcD1rX1KeQ97lKQxXznc1AyiGM+2jsRXfhB4jsXKbOm97zjFFL9EfOzJhjAMuXLlyhG/AtM0yefzk7+PjRQfhEeRIjz++ONHJBn9fp8rV67Q7XaRUrK9vU2S6ELBsizm5+dptVrcuHGDs2fP4jjH5+dODRynmOLDQaJS/CSkaB/94C5aGU5kqpzNLbA1aJJ1HB4rrvBOd5NuNCRnuiQq1fpr02Fv2OGVxi0UWmv9eHEFhR6jB/hZ/dbh5x4EXP2DPyEdHni7pL42WLv6B3/CM//3f4/h2ZBC9JUc9ne67LKBOrbHCQrFLussc0oXu8OQVq1DHMT4g4BM3iaKhpRn+9x6Z8jiyRmGwxzFmYTO/jbbtxOGA5fqYsD8iWvY+S/rokAB1hMI88yHs9M/xtDyF3Es6VJ1cszYeQq2RyPos5qpciG/xI3uDiUni2fYBElEM+wz6xZ5u7nObtDWj7XzPFHWzvuPSugI8yRKtSG6DEhItvV0g7mqZQzhbUg7YKxC0gS6HPZhSNATLQVdZNIdJRCMzQG90XeHe80CH+jxYZ4H5zeBFthfQhhTN/MgebBcat4tsuiW8dOIQRxwNrdAK+xNJFf2mFAIB5zMzvDC3ju0Ix1JvZKpcDo3/8CoOgFHRmeE9ZQu7JN1QEGyo00bzYt6akkIoAXyjJZUHFovknsJh+PXAKP7SWAfxIKebknqOsZSAcLQZrPGKih3lKDhIpxf0RM6U0zxC0IUJ7x9Z5eZYvYI0QBgGJJqweOtWzucmCsfaSjci0LW5RtPneEHb9+iMwjIuhaGlPgjQ8nVuRKfu7CKZRz22VmbL3N9a5/vvHKVu3stChkXIWCumGNtvkLOs/nJO3f54du3Ob88S73TJ0wSbMtisZyjmPOodwY8eWqBfqBjPO9/jimm+LjjY082NBqNSVLEcbBtmyAIaDQa79nx/yBShHtlHK+88sokkaJUKk08H1zXZTAYcPPmTWZnZ+n1ehOjyFwuRxRFdDod4jhmb2+Pubm5qfRhiik+IAwhyVku7XBANxrSigaY0mDBKZKolDv9ffpJgGvYDJOAPb/NgltCoagFHUxpcCY/z2a/yeawQdXJIYXET0J+uH+NFa9CP/bxTJsdv0msDi7YG99/5/hZegClaHz/HWb/8dPgCtJ53T0Z0J1MMtyPlIQBPQCkISnPF1GpIvBDbM/B8TwMS1Ced4A9bl5O+cxvfIbb167y5kt5DFNgWX027i7gvGnxxd+qUFj4MkrkId1D+X+BUhEYKwjrAvojIQaRQYiP/cfDI8E1bATQiYbUgy692CdjOMx7Rfb9LvWgS8nO4hoWw36IQrGWnaUdDdjzO3iGzYWCJiAsaTLrFBBC0It8/n73MrNOgUbYo2h5RCrBEgamNOhGQxa88iGTSCEEwn4GZZ5BRXch/HudJiAXtMwCC5K7YKyAXIDoNaCPLgbH8ogIEGB/UReh8Q56hN7TKReiCGkEtNHHu8fh8fpUj+Cb58H9rxHOYyiZg/gu6fDbetvGKTDPIsadcpH91JiMeqaNQtEOB+wFbfwkomhlmXXz2lS23yBne3iGzbXuFqY0OZWbZWfYoZUOKNoZLuQXudbboWB5zLkFUqXY9dvUhh08aTOIAyxpTCaqpJB0oiFPlg7HRgphg/M1SBuo6BxEPwa5hDDKKGJIutq00ToPSR7iN9HH+t71IjgwEh2fh5S+LQqgysAAbQJZALmiE1KMtdHUzVDHa0oTrEsIawWFhYqvo4IXtWGleR6MEwh8QCJk7pdyrKb4ZGOv1SNJ0ofKBGzLpNnzaXQGE/+GB2GmmOWbz11ia7/Deq1JNDKUPDlfoZz3jiWNTUOyXC1QLWRZnSsjBNimgWsfTEdcODHHn/7obXaaXU7MlfFsk2EQ8Or1Nv0gYm2uxGUhePduDSkFZ5dmOLtUJeNOa4ApPhn42F9N7u3t4XkPZ889z2Nvb++R5AUfRIpg2zaWZbG8vPxAz4eFhQVef/11er0eMzMzOI7DcDjk8uXLCCF4/PHHKZVKJEnCxsYGW1tbjyT/mGKKTyv8JOJuv8ZGv46UkgW3hJ+E3B3UWe/XudzaYMErUbA9hknI3rDF+qBB0fRIR8WVEJITmSrbfotfmX+MrzoXEQju9GtcS3YOjTO7hs2MI9nxWwyTkL/beXuSdDF5TVvNySTD/Uj9CH9rJGkQOvYeIEMeiXEs4SAxyHBwgXT6qZPs3tmjsdPC8UzcnAsodjcUC6uCKEjoNjZ4+6WE8kIO01CgFHlrkW4z4tXvrfO1/7KIiH4Cyd5I452B6B2U/5dgLI1SDyyU9STCPP+JkVl0oyE3e3vURgTBrJunGfbZHra42tliY9BkOVMha9rsx13u9GpsDBoseiX8RB9Te1Q4bg4b/NbSZ3AMXQi+Ur+JFJLiPXKJnOWiUPRjn61Bk1f9W3iGjRSCnOky4+T56tzxTv1C5hHO4yhrBRW+DPE2Kt3WGnkhIN3Wx4lZJk5gMg9pDEZRF4Ui1hKI+DtMEinE6PUJBcrSUxPGc6A2dNIFSt/HegrSBqSXQX4F/L/R0Ykjvw+CH8LwP6LME9pTQuRQ1ueQ5tIv6Oj98lEPutzs7dIONUFQsDLsDtvsBx1ebd7GjwIWMxUcw2RzUOdya52a3+FErkov8VEKcpbDcqZKLejxzeVnABAI/nr7dYp2Bs/QxYQUgrKdpeZ3KJlZXm7cZJAEOFJ3V3OGy1p2hrXs0ckSIQQYVYRRJTVPQPQyKtnS0wbEQArJBvpybwEtoTG0xEYlYFQAZ6TIURC9O3rcDEhnpLow0SetLqS39c8iDwx05KUxr58j2QRrTa8XMVpfxDD8c1CD0XqRKDmDsD+HmHo6TPFzwA/jB04C3QsJtPtDHX9pSHKu/cDPNcs0WFsoP9BQ8jjc3WtiWwbF7NG0hzBOuLpe4/RilYEfYRmSfhCiUp2GhVIMw4iZYhbDkCRJyrWtGnf2mvzKU6enCRJTfCLwsScbwjAkl3s4W6mUolar8cYbb0w8GT7s6YGHkR5xHFOr1VhYWCAI9OjqYDCg3W5TrVbxPI9ms0mhUHjf8o8ppvikoBf71Pw2qVJUnBxl+8Hv634c8P3dywyTkJzlEkQB39u9jGtYfLZ8ijiNcQyLzWEDJcr6HOC32ezXma+epmDqLkWiUm719ljxqtzu1SbO8JvDJllTS57iNKEXa/PWnOmyPWzhGrrovNOvHfJ2d5fKSNc6lnCQroW7NLqACRSyocmFeVa4yuvH/p8CwTwHsq2znz3F5tUtyvNFUIpeq480BP2OolQ1OP1YxNa1JoblYhrJqAO5AJjkyya1jRbd3XcoFHcRhi4MlYq0i30aAG2Ec1r/LvwJihRhffSi65RStKI+jaCHFIJZtzgx1DsO+0GXF3bfQQhB1nTYHNb5881XWPTKXCwukSowpGBzRC5Eaczdfp160OFcfp68pddLmMZc6+6wkqmyPWxyOq+NRteH9QnRECQRgyREIsgYNj+t32Q5U8I2qtT8DntBl1v9GitehUr9Oo8VV1jKHO8ULmQR4f4aafguhD8A60k9Du9/X8spRBvkmu4qKwFGWf8c34LEBvsCyBjSRRDDUQSi1Dr7cSGq9kfGj0pLLsw17RUhShBvoMLXQUUIY07v+7Sn14sKQcUIYxWlhhB+FyV+A2HMH/u//EMiVSn7QZdONMQWJvNeceKpcRxudHd4paHJIdeweKu5ztXuFpcKK1TdPCYGgYrZGTapOnmGScitXo1UJeTMFdzRtgdxwO1ejeVMmUbYZ8bJM4gDenHAnFuY3CdIY0whcaXFK42bLGfKtMMh9bDL7qBNkESEKiJfz/BEaeWB50ZpLqCMb6KCl/Txsb8E8bsQvAxJC+QQ5Dnt3ZImYC6D6ukJGHkB5CxEd7WhrGiNJmAEWnKjIBno34uZUboJ+jFCaIIrvoYKNZEhpG6UqKR54O2AiZCzqLSN8v8W3N+aTjlM8YFhmZL3So/uDnyube3TGviURmRAIevy2Il5lmeKHwqZvtfqk3GOv07fa/WI03Tix/Dk6UVMKdlqdLiz02CxWqDTD2j0hsyOCIeZQpbOwOeHl+/w6589f6xEZIopPk742JMNtm2TJMmhSMp74fs+6+vrJEnCwsICuVzuFzI98DDSo9vtopTC8/QF66lTp2g2mxiGMSEohsMh3W53Yhz5fuQfU0zxcYZSinc7m7zd3kAo3alLUZzIzPDZyqlDY+apSmkEPV6qXaUWdDiTn8cQ/z97bxYj2ZWf+f3OOXeLNWPJfausvYos7mxWsxeqpW61RmrJAwu2xoJkYQAbsF8E+MHwgw3MAD0PBjwD2DP2zMCyHwYet4HRjCVrg6RutbrFZi9sdpNsFpfas5as3DP25a7n+OFGRlbWxqWKZJEdP6DAqmDeuEucvHHP/3z/75Ns9JtklYM2hvV+A1/HHCtOUw97tKI+lhTEWmMriyvdLUIdM+WN0Yl9GmGXWtCl6GTSWMNBjKHGsNZvcKW7lRoqkgqQN/oNvjLzOGN2hkbY5Wxrdei5UHnhJNf+4Nt3PlEhqLwwmLhLgf1S2h5hCZunzBduS6MQCJ7iC1jCQirJqS8+wulffQqB4G/+7XeJo4R8KUccxQig3XqUqxe2KFQjvEwIlNM+6t3VaGKEUET9G1C6qTc72UpXra0J0A2M8RHCS6MXozMY6whCPDyJFbFO+Gltmeu9bSQCYwxGwKmxBU6Mzd32s5t+k2+tvYGrLGYyFaQQbPktJrwCnbjPRr+JlIKTxTnW/Sb9OG2V0EYjheJ8aw1bWaz1G7TjPtoY8laqWjiYn0QIgUIRa831/jar/fpw/5FOqAddTk8cBWMGCgnBUnacTuLTivq8tHWO56qHWcpP3v2kk0ugphHCxshyqkgxNdLV5hroMsgsqFyqUHCeAXUY3Kchvjpot7BJ4w+jQRTmARC1dNKYWKBK6eRzOPkL09Xv5CLIm65rcj19L1mAZBWsgwiRwZgEE76ByPzyA/mcHxT9OOQHW+eoR10UgsQYLCl5rnrktiJPkESsdHf45vobzGbKFO0MidFsh21mvDJrfoMETcFxmc4ssNqv0UtCtNEINDGas60bFKwMsdH0koBYx/Qjn2erRxh3CwO/F0OYxFzqbFALOoMWGUM/So1fF3LjTHoR3XrAbKZExnLoxSH1oMPfrr/FL049SsW92yQ9BH0d1MIg4WQ6HRumBlqDbqTJJnIsLTqIidQPxPkcyFmI3km9Qsyu50OUjgmTTwsTupsmXIhSWmiQuz5UcVqX0O00vhXS+2aynBYiiEBvgJpAyDFMsoWJLyGcJz6cD37Ep57xYm4QIWmGcdY3s93q8vaVdWJtWJosY9vps0QvCHnpzSucWpri1MH7T9iRUqQqhTuwtt3ca4cw6TEKIVjbaZHPuggh8ByLte0WE2N7c5Fi1mOj3mGn3WVibFSQG/HJ5hNfbJicnLxrZGUcx6yurpIkCVNTU8OCxIehHrhX0aPZbOI4Dlpr1MD4pdFo7Nun4zg0m819KRXvp/1jxIhPKht+kzca15jyxlCDvm9jDFe7WxTtzHAC2Y9D/vzGq7yyfZHz7TVcZVPZyfOFiWNs+k1ylktiNFe6m/SSkFgn6Yqm3+REcY4t0SajbGypaEY9NvwmBTuDIxU7fovl9gav1ZbxpM3F9gYvb52jGfaxpERKScHK4EmbRtglSiJ6QuHrmKpbYCtI2ylU1uXY13/rtjQKhODY138LlXEQCJZaRVq+GOZPlMQ4XzS/zgbX6dEhS54pFtIUCgGZvMfv/eP/hKVHFylPlfjxX75Kt9nDcW0sR5ErZum2+xh5gma7iNbXyVcnBtGWABodNzBqhmzRSVeud9E7aV91euXZ1WkIYWF0MojRe3gyus+317h2S6xpYjRvNK5SdnJMDSJJd4I2f3z1x7xeX2alXyerHKa9Es9PHKUdB5TsdEJ4tbtFM+xhjMFPYjpRl4XcBFtBmyBo8na7gTYGfZOJZzcJ+Jfnv8k3rrzE7y59kUbY5Uz9Kr0kRAmFLRUlJ0eYhPg6IUgi+nFAO/YpDxQQIkknmONugZ/VrzKfre4rrO1iTAKmiZDTGDSEr6fpEnJ6oEZRg6JSFZzHBqvWmwjvBYSaRmd/D1pnwGTShBLhArk0pcT6bJpcQHfQQrObehKln7t1LH1/bnqQ1ztpESL9weHLQuYxyQbGRA9VceonO5foxAFT3l6BLUgifrR9ga/OPjFUxFxub/AnKz/hrcY1toMOecvlYH6Kx0oLaKNxLIt27HO9s0OgI7ST+nxkpEPe8XAsm51el3W/SaxT1ZIg/YzPtdZoxn1+7+Av0I77XGiucamzQagTlBC4ymbcKbLh1xl3iyRas9ZvoI0eRvIa0iKJheRM4yq/MPXonU/Y9MEYhFQY4w8KTZm01UEHQD41HJUHwT44+JXfQbinETKHTv5j6P5LMIV0vMgMGBdMA+wvpekmyPT9du8jug9EoI6R+jvsEqb7VJmBsuEmbxBZGLR3jIoNIz4YWc9haarMtY0G46X9i4ZBFHP++hbaCA7PVIaFBoCs6+DZNm9e3WCyXGDyXbwc3o3pSpEzl9fI3eKxoI0hjDUZTxJGCZ5j4ViKrh8SJXpYhLAthR/eroa0lWS91h4VG0Z84vnEFxvuFVnZbrcJwxDbtu9YjHiQ6oF3K3p4nofv+1SrafxOkiTY9t4DmZSSMAz3baeUot/v39dxjRjxsHO+tUrRygwLDZBW/sfdAudbaxwqTNGJfP7o2o/40dZFlJRkLRdHKOpBm79ae4OlXJUpr8S632THbyOkoB+HrPdTA7eMSieUzahHP4mwkXR1hB+HKASucig7Bf71+W/iKAtjDJc7W/TiACnEUBadVS5lN8vV7g7z2QraGB4bm+e7W+8MVzYKpxZ48hu/T+3Fd/BX63izZSovnExTKABP2fzezBd453eKfPsb3yMO05KDJSzmOLjv2ggpyOQ8fvcf/6eceC6NHRwbL3L6a8/w4798jTiI0NrQbnSpzlZ4/j96htZ2GyHydNs3yBV8EGnE587WBAdOPU2mpCD6WRpfB2lvtdZAkL4mbk7MGRjFPSQkRnOhtZGuEN+0kqWEJG95nG+vUXbzbPtt/s3lv+VSexMlFFnLxUKw0tvhm2t95rIVIuWy0quRaE2oYwIdca27jSVTVclyZ5Nm3LvrscQmYTto8y/O/SVzXplW1Esnj1LgKJurvS1yymPcKbDeb5CYNO6wEfaITYw/SDVIjQATmlGPqnv794cQCiOyGBOkcaXxWcBNCwMyn76GBjpgmumkTi2CTJUSwjmMcZ6B+MJeLCJNsI4OTCSvpO02usawAdpIkDOp+WCykpoMisFkXVhAAsZPV7YHGJMMJp8Pj1FkO+qzETT3FRqAtIUi8lnp7nAgN8H13jb/54W/ZSdso4QkZ3kIDGdbKzTCburboSOu93bwpIWvI+pRl+vdHcpOFjuyONda22cWm5LeE0KT8OLmWV7aOsdjY4t0Yp8bvR0MYAmJJRVXxRYFK0PO8qiHXbaCFra0qIddEqMHBQxB3nLZClqEOsaRd3iEEy5gUlVBeAGSy6R+HfZAhdACY6W+H3oC6IP9xLDtAfc0BH8HemXg1+CDCMF+Lh0zehzMWqqQEHJwjhZYh8F7HoIXMSZMzSuRA38QA/ggbzK4NEmqsBkx4j548vAcXT9kvdamlPeGxowrWw2a3T5L01UW7hAFKaUg59mcX9m672LD4kSJM5fXiOIE29r7vpSIVPWgDV0/4Nj8RKrcNObm8i2JvrPJpZSCKL6zefSIEZ8kPvHFhntFVq6vr6OUYn5+/q5tFg9KPXCvoodlWYRhmK6ODooRSql9Sget9W3HmCTJyK9hxKeeZtQnb90eCWtJxXbQ4i9uvEoj6PKt1TMgYMorEakEgyEvPVqRz3bQIdJpZOV0poQtLdb6NTpRHykk/SSkGfXoxQGtsEuERgCdqIcQkqLl8ac3XiHWmrztESYRfhwQmAhhINIxRTuDEgI/ibna3WLczbHS28EWiiO5KS50NobtFCrjpKkTt+Apm3/69O9yOKwSP90m9EN+9OevEvR8jDbDIAs5ePBYPDHHf/k//S5P/MKjODetmjzy2aN4WYfQjwh6IYVKnupsmSTWuFmX0197nte/8ybbW9sIoYEMBx5d5NTnTyCsCBNfwCTbICvpCmV8NZ2M2I8jBpNFoztpC4YoPtgP/D6ITUKCvqMCwJM251tr7ARtrnS2+enOFVxpMZVJjUMdZWFJRSPskbdcenFIkEQs5SboJD6b/dT4Myc8VvuNexYabkZjWPFrKGRqPJoIwkRTsjO4UtGO+6z0tsnbGa50NrGEAtKWisvtzeHKuuAefbnWSQhegegtQAxk7SYtDlmPgdkBnU3VCO4XEdaRYTqEEArjPAfqBNAcmAJOImQp/Yytg2CfhOAH6QQSkcrunSfTaFRVwfT/GqMHpoBiFuK302Owbopr1jWwDyPEw1Oc8pMIeZfrasvU2POt5gpnalc5316j5OQo2C79JExTShLBVtAko2y2/DZKCBZy46z7Dbb6LcIkop/EXOxs3KHQsJ8ETWLgjeZVylaOQCckJAggYxwKdgZbWmkqhd+iGfaoBWmkdqJTXc1yZ5MTxdRr5W6jRYgMxjoA0TIkbwO5QRtFkv6+i1KqThAFQIPzAsLa84URsohxnwFzOh1XiDQNRebSe4bzBMhnIXwNdG/P38M9jVSTaPtpCL+PkZX0WEQF9OrgXnOTwaVpph4kI0bcB7al+Pypg9zYanL2+iabjS5gqHf6PHZoltlq8Y4tFgCFjMt6rUWUJPcVN5lxbZ45NsfLZ69RymXIuIOFRAHjpRyX13ZYGC8xPmiTcCyFNmbYttkPIg5M3a4ejGI9Mogc8angE19sgLtHVhaLRSYnJ/cpCG7lQakH7lX0sG2bZrPJoUOHhgWFUqnEzs7O0LMhDMOh6mGXfr/P/Pz8bfsaMeLTRMnJ0Y56FOR+g9Va0OFKd5u5bJWm6CGEwLVs6lGHvOXRiX2EVEgh0Uaz6TdxlEXZyWEJyXInJjQJCsPF9gZFJ0PBzrIzaHkwgDaQsyzakY8SkjEn7dGuh116Zk/WGKNpRn1CnbCQrVIL2lxsbxCbhIyyqbh5Trt5zrfXaUTd1EdgsK0lFFIIHhmb5789+escG0wWTp4+yuvfeZNDTxxAKcnOah2daArVPPlSjsmFKl/7r77Kic8cue2aLZ6cZ/nMNSozZbxsWqjR2lBbq3Hi9DEq02W+9A8+T2unTRTE5MayZAu719cC98uY6A1IrqZGcWqO1KHeSc3+dAeEQLhfeajSKGxhYQlFpBPsWwoOV3vbbPktDuUnCXWIBFxlsR20yVku3djHUTZSQKgTdsIuZSdH3nLxlM3Fwcp0J+zRSG7/Tkh6we1qlcG1N6RjBEBgiIipR10SNONukfV+g3zskxiNK20SozmYn8QSkjcb1zlamNmXZHErwjqCdlF04gAAIABJREFUia9B8OJAndAF9GACNwtmDPAQmV9DqLnb38A+Bfo7IA8MI02NidIJn/MM0prDqN9MCwZokGXErsJFVMD7KiZ6DZINECo1HZWF1FPS9IA2yDzCvou0/2Mioxw0ew/1N3OpvYEtLU7lqjTiHhllY4yhGXTxlI2fRLjSwk+iwXjpMJstk7Vcqnae8601tDGs9mrDz36Xe42V2Gi2o/bw/mCAvg6JwiQ1FbVcrna36CYBGlBGYEnFgew4ndjnneYNnq4ewr6TqmGAcJ7BRMup+sTowR/SsaLGIamBNY3I/D2E3K+mEcLBWCchOgPq0LBoZUwfMAj7MEIWMNaRVPGCBFkZjitpH0ILC6I3MMkGqCIQpkobE6WtHaYJ6sC+IseIER8UWymWpiscmCoTxQlCCL792gWkFHctNAADrxQw2ty3gO/gdBVHWbyxvMpGvY0cvHfGtpkcy3NwpoKS6e+S59iU8xl6QYSlBEKIfX4NkH6fGwxz1Yen2D9ixAflU1FsgDtHVr7xxhvv+qD8INUDdyt6HD16lLW1NaTck0kVCgXq9TpRFKXZ6kLsa8HYVUJUKg9Pr/SIER8Gx4oz/N3G22Qtd9hKoY3hXOsGi7kqWcsZPDCk0kNbKgIdM+4WaIQ9Ah0RG4fJzBglO8d20KYedAl0yFJ2nJV+jUQnGAPdqE8y6L5XpKvSUaKJTIIxhm4cogloJf7w+HYnBRpDNwmoRz0eKy0w5uQwQD3sMpUpUbZzHC5Mc7m9gSUVrrIRCBZzVX597hnmbjGjW3xkgVOfP8HyW9fxuwGHHj9AZpDlHQYhzY0mc0furLgqlPOc/tozvPbtN+jUOkP5+5GnDnL06bQVQ0pJaWLsjtsLmUe4n8OYz6RnZiyEWcdEF9Oeb/skwjr00DnFSyE4XpgZenzs3t8jHbPc2eLJ8gEsqVADrwspJNKkKpaSnacV9Qh0OgKWchN4ymbVb6StN0JyMDfBhfb6TU4EKe03r9/mw3HtD77Nsa//FoVT+ydMN4+XetSl6GRZyI4jhUAbCHXMXLZCwfboJxG1oMOhwuS+NqJbEUJh7MfAuZRGEwp3oDoZmPgZk8rV5Z1NJqU1jzanIXot9eGAtB3CeR5pzQ32YaVGgXfav6oi1FfSVg4EIDDxdYgvp2dsHUdYi3sFioeEvO0xmymz6beo3mSo2Ax7bAdtXpg8iRQCSyg0Bkcp/CSmoFxsadGO+oSDpIil3DiesrnS2WTHb1OwsxQtj3Od9X37fC9j5dbxpUmLEJtBk8P2FDPZEr04Yr1fx5KK6UwJV9lEUcJm0OJo/t5KTCG8tHXGbEN0IVUeWMW9FinTBzF2W6FhuL39KIYIonPpsQpAZBDel4bbCOEOkm5uR1qLGLVAmmKhgBgTL0O8knpAqCcR1txDpYIZ8clHCIFjDxb08hk2Gx1c++7TnDBOcG0L6z5UDTczNzHG7HiReruPH8UoKagUsqzX2vzo7FX8IGIsl0FKwdz4GC+fvUbGsXjy8ByOfbMRtmGz0ebk4vSeueSIEZ9gPjXFhjtxLx+FXR60euBORQ9I2yxuVT1MTk5y7do1jDEsLS2hlCKOY/r9PlJKjh8/PmqjGPGpZ8ob46nyEm80rmEwaYuvgIxMDdoAJtwCBTtDM+6TUy6hDnG8YtrjLuBEcZZeHBKbhCAJiUxCxS7gKMVqP+1Fr4UdEpMMH/QTwJiYUKeGlCExOmGYPHEruwaBjbDDUnaCspfnmcpBakGHlX6NbhKQUQ7PVA7yRHmJJypL9zxvx7MZGy/y2BdOsnzmKkE/pN/uoxNNt9XjiS89SqF898n+xHyVL//uCzQ2WyRxQqGSJ3OHnO97sWvkl87Z5+68Kv6QcaQ4QycOWO5uIgwgBEESMZspMTGIE5zPVnClTS8OcaSiF4fMZXNYUqCk5PGxA9zwdxBC0Ax6WEJSsXNkLYdIx/v2l/QCzv+jP0T39zx1dqNNz/+jP+TJb/z+0I9j33aD8dIM+yzlJ/Ash2etDJtBk9Veg04cULSyVAuFe8a87iJkESOL4Hx+II8PBiqHOE0JcH/1nsaM0j6GsZYG6gUGq9Hv7/vl5mKCsA+Bfeh9bf9x8HTlEC9vX2DDb5Kmd2j6SciRwjQZKz3/w8UprnW36UfhcDztFifyVoYjhRmu97cBQT3skrM9XKOpB519+/qgYwXS+4sBIq2ZcscoFXNIcZD1fpP1foNuHDDpjTEvLVzr3Q04hSpj1GSqfokvDYwjI9KUEZWOo7ttK1SqjrBOgGkB1mC8vPdJWVoI3L0f2Qj7EbAfec/bjxhxPxyeqXJ1o87YPb4TG50+jx+aeaDRkkIIKsX9KrWFyRKFrMul1W2WN+oYY1BS8pWnjrLZaOOHMVIGCCHww5g4STi+MMWppZE5/IhPB5/qYsO9fBTgo1UP3E318OyzzwJQr9fpdDo4jsP8/DyVSmVUaBjxc8PR4gzz2SrbQRuDoezk+OHWebTRgCJrecxlK6zuXKIZdtPIQ22wlcWUV6JkZ1nIjXOxvUGkE8pOhlrYYyf06SYBxmiUlCQ3LSlK9lYUJYIYjQODLuq7E+mEvo7IJCFCCKpegaq3V9Dc6DfvKYkf7l9Kjn3mMK/+zRlOfvYo7XqXTqOHAKQlef43nn3X91BKUZ0pv+vPfZpQQvJM9RBHizPUwy5KCApWhr9ZPzOMQCs7OapugXOtVYwx2FKRmARbWCzkqhQcj4PWFKv9GpZSuEKx5bepBV2SW9aday++A3eJNcMYai++c0d/jl0CHeLHEQyOayZTZiaz95lt9JtkrXe/1wuZTaXr8QWwn03TJPTAV0IWEe67u/oL4dx1NfrTiqdsXpg8SS3s0IkDbKFQQvDS1rnhz8x6aXvEWr+GNoac5dKLfVzlsJSbYNwrEJqYRtgloxwsIamH3UEBY4/7HSsG6MY+2hi6UUDVK7CYq7KYGxhLD1q8Muo9pH3IybQFxrTBeRaSnTQZQhiwlhDWgXd9i9Q08v6jwUeM+KipFnPMjRdZ32kzXsrdpnJudn2yrs2ByY9GPVzKZ3jm2AJPHpkjTlJDSCUlYRSzutPixk4LrTUHJkssTpbv6dVgjGG72eXijW3WG20ApkoFjsyNMzF2+7mOGPFx86kuNtzLR+HjUA/cTfUAsLDw/noXwzAcFi52iymTk5OjIsWITywZy2HB2vMtOVyY5tXaZaYzJa73trGl4pnKIS6210mMRkmLuUyFU+UDjHt5MJCxamlsne3SDnu0Yx9POnS0n3o0DCaSex7qAltKYm1whcKRNpGJU9nDHZBA3vJohl0ut9e50a1xojRHyc4ihKAbB7jKZjb73h5gFo7PEQURZ1++iNGQK2RwPIcnf+nUXVsgRqQU7cwwFhBgMTfOjV6NipPjUmeDSW8MT9lcam9hS4kQkmNjMyxmq8zlqnSigOvdbXaCNjnl0or79KJgYPS4NwD81fpwdfpWtB/hr9bv+P/E4E/ZyXG5t0kr6HG4OM3B/ASFwXHXgi7jXoGS/d4mdMJ5Kl3/ji8CKvVNkEWE+znEyNn/rgghqLqFYdqHNpqs5dKNAxxpcam9wfHiNCU7kyZOKAdLKT5TOcSYm2PCKyKBa51tamGHjHJpRt3bVDAfdKxAOlYkULZzvNVcoZ+EPFKaZz5bwVNOOsHw2xwvzt7Tr2HvnCW4L2DCH4LeSFsoLBvkLML97GhCMuJTjZSC0ycO8JPz17m+1cRSEsdSxFoTRDHlXIbPPbqE53y00yAl5dC7AcCxLZamKyxN3/2ZwRjDTqvHVrNDGCVc327Q7PQpZL2hcmO71eX6VoPDM1WePjr/QNUaI0bcL5/qYgPcXVHwSVIP3FpYMMbQ6XTIZDIUCgXy+TxJkrCyssLq6irHjx8nlxutRoz4ZHMgN85m0ORKe5OLrQ3ytocSiucnjg0l0Ft+i52gjSMVlzobYAxjdoZW1KefhLjSwqjUgC3Qe5MAPfyvIdIJnkxXK/OWi68lYRITkpDmBuz1WLtYuMpGYxhzcgQm4oeb55nJlpjNVMhaLl+cPHHnSLo7IITg8BMHWTgxT2unjZSCsfEiyhr1Mr9fTo0t0Ai6LHe2WO83KdouUub4lfw0i/kJPGVxtbtNjOZad5vVXh1X2bjKph37JDrBsxxCExMle8UGb7aM9Ow7TiKlZ+PN7qkUdh8hd8dLhtS3I6dctKPZ8Vus9msczE1QcvKMewVOV4++54mfEDbCPY2xT6Ur1sIBUR5NHN8nUkg+O36E722e5Wp3i3bsk1U2U5kSz44fZtorYQnJxfYGidGcbd6gFnYoOhl2gjaNsINC4igbP94rOLyfsQJg7SaYkBYb8srDSFJlVATL7U2W25scLU6TsVwO5Cc4OfbeW52EzCK8L2N0IzWLFFmEHBnOjfj5wLYUzz+yxMlOn+tbDTr9AM+xmR8fo1rMfSIm5O2ez4/OXqPe7qGUZLPe5sp62h6yNFWhmHURQjCW8yhkXS6v75BxbR4dtWCMeIj41Bcb4N6KgoedbrfLuXPn0FqTyWTwPI/l5WW01vi+TyaTwbIsLMuiUCgQhiHnzp3j1KlTn4hCyogRd8PXEWU7x5blIgQUbY8Jd4yymxua6eWUy+Vwk52gw5iTxRKSA2KCn2xfxtcxnrQo2lkSrdkO2ggEMQlqMC0UgCMtHGUhhaQXByRoPGVjEjM0kxSAJ2wKdoZxt8CEW6QV9ThcmMJTqfz6ycoSB/P3Nvq7G45rMz47MoO9HwIdMZkZY6PfRCEoOXmmvDGKdmY4GbeFYqW3k7bauHkEsJit8mptmSCJydsuk16RdnfPILTywkmu/cG377xTIai8cHL4z90ig0SQly6e7aZtG7aHRvPI2AKRTmhFXb4weWKfyeX7YSRvvz+00UQ6YcYrc72zhSctpr0S45niMIoU0vjda93tYWuOAVpRn41GE42maGVox/3h5/5+xoqFIBkUGiSSosrgWjaH8lPkLJfYJDxdPshm0MKRNl+deWKfkuf9IGTpA203YsSngVI+Qyn/wX53Pk66fsh3Xr+EkDBVLpAkmgsr28xPlADD5fUdDGbw79RAebyY49zKFkfnxodmmSNGfNy8/6fiER8Zu4UD27YpFApYlkWn00FKSaFQQErJ6uoq8U0rK47joLWmVqt9jEc+YsT9ca27xV+v/oy3myv4SUSkYzpRQMZy9k3mYzQF26WfRFiD17MqTa+QCBKd9jh34nTymKBR7CZbCGyhiHVCmMS4wmbMzVGwsigkWeVgY2EhKdk5FvIT5GyXE8XZNABAgKNsxpwM494YsU4+UKFhxP1hjOGN+lW+tXaG5c4GidAEOsJPQrKWu28yb0tr2Eqz+2rO8hAIhIAwiWmEPeRNvh0q63Ls67+FzDhIL+2Vl56NzDgc+/pvDQ3/HBQWEgvJuFNgMlOm5GRZyk9hBn38nrKY8AoU7GzaZjFSJHzkxDrhh1vn+buNd1jz6xigE/tEaLJqf5qGKy26kT9UKgnShAspBFJIEjTypt/59zpWJAIXCwU4WMx4Y5S9PNOZEpNekVgnWELhKJvF3DhSMLq3jBjxc8a5lU1irSkO/BtavSD1JZICKSVjuQxXN+sE0d4cQClJkmi2W92P67BHjLiNUdnrIaZWq6G13qdQaDabw3/btk2/36fdblMu78kzM5kMm5ubn0glx4gRndjnlZ3LlJ0ctlQYY9gMWrSiHudbqzxZXkIIgTaaIIlZyk8SG0Mj6mKh6MQ+rrLIGIduFJARDtpo9ECwrAEbgSUk2qQO8K6yqWbyVN0C7bBPoGNacRdbCIywUUIS6XRfY06WIIlwpDVcaVRCEJm7GD3cB6EfcuPiOptXt7Aci4UTc4zPVfbF6P68s+E3OdtaZcorIoWkaGfZ8Js0wh7XulscLqT3wUjHKClZzE2w4TdohD0sKdny28OCQzf2yVkuVqwIzd4DXOHUAk9+4/epvfgO/modb7ZM5YWT+yaPEoklJWLg1iAlHC3M4EmLTuxTcnJ4au9entzNSPA+6LZ6XD+3Sn2jQW4sy8LxOcqTI++Pm7nQXmOt32A6k14XqyBpx33WenWKVoapweudyKdoZzlWnGUraNEcjJda0KbgePTCgCCJKCiPRtwbvv+7jRWBSD0XDDjGwVaK2GhKyuFYcRqJoJn4LA7iUne30XdJybkfGltNrp29QbfZozxVYuHYDLmxkWJmxIiPmzCKWV6rUS7sKTJirffl5kopEAi2W13mqjfd5wVE8YO/X4wY8UEZFRseYjY3N8lk9ku/4jjG8/Zkno7j0Gg09hUblFL0+/2P7DhHjHiQrPZqgwfy1LdACMHRwjRvNq+z6TfZ8Fu4yiJIIh4Zm0ch6MchrrKpBR20b7ClRSfyiXSMrdOiwi4WkrzloaSiF/s4QlGwPUp2DjXYr0FTsDIcL87SjX0cYdGIelzv7TBmZ3GVxcni/HC1MUhiJt0H2wvdbfX44Z++Qr8TkC1kSOKElfOrLJ6c54kvPfqeCg6hH7Jyfo3r51YxGBaOzbBwfA7nU5Tdfam9Qd5yhyvMtlQcK0xztnmDS51Nqm6BxBgSk3C6eoTl7jZ5yyXWmnrYoRv5KCFoRl0EEl/HiDsUAlTGuS1JQA4mjllpk1E2R4qz9GIfIST1oM317g6OsshbLocHMa7pWDTvKbHk/bC9WuPlv3gVMHg5j8Zmi+Uz1zj1hRMcfnzprtutXFjjT/7Xv+TN75+l3/GxHYtDTy7xma8+wfHnjjB7ePpT4yGijeZCe30YawlQsDMcyE1wqb3BhfYqOdulH4dYUvH5ieN8f+scU5kS7ahPPezgSQujoRn3ceVAvcCeDwzceaykPyeoOHm00ZSdPJNegcRAohN2og7XuztMZ0pMeAVms+l3epBEuNIma7m3vd/9cOXNa/zsxbdxPAfHs6mtNrj42jKnf+1pJuar7/4GpMWK5Tev09hokhvLsHRqkYn56kixM+LngjCKSbTBsiS2erD3yF4QDSMyd0n/vv+7ybYU3V4It/zKWmq0IDHi4WFUbPiAfBRpEGEYks/vz1+3LAutNWpwY5NSEobhvp9JkmTk1zDiE0vqEL//iztruTxZXuJCa42scpjJlFjMT1B18vSSkHfaqwigGffwk4jVfp0gCbGkRTPySUwqnpcIFJLYJJTsPH4c4kp7GJkIsOm3iE1CYgwbvQaubXO8OEc/CbnYXsdTNo+OLZCxHBKjqYVdJrwCE96DLTa89f2zxGHC+Nyel0O+nOPq2yvMHJpiemkSSNsIdKKRSu57yA/6AT/805/QrnfJl9PVyrd+cJ6rb6/wub//HF72wU5ePi66iX+bIWfVLfB05RDnWqtklctUZozF3ARFO4OjbL678TYZZVOPuvhJxFq/TqwTbCloR300ZthIIRBpAgR7j3kCgSstFrNVWpFPkIT0dMiG36BoZzlamGbHzrHWbzDuFjmUn8CWFpFO2AnaHCvOknuAk8ckTvjpN39GtpgZfq67Baq3v3+OqcUJ8qV0DGitMdqws1bnf/ydf875n1xCJ5o42lPmrFxY48U//AHHPnOYf/Df/X1Of+2Z4XfOJ5nEaCIdY91yf1nIjVO0M1zubFG0sxzOT7GQHSdjOZwozvJ6/QoSSS3s0k8itoIWBohNss949m5IBEpIDhem2PbbaAytqI+SktlMmdlMmaudbSITs5SfYMYro4TETyLqYZfT40ceaBtFt9nlzPfeoTJdxrLTa5EtZAh6Aa9+6w2+8p+/MCwwaa3TSc8tn//qpXV+8tev43gOmYJHc7vND//kFY49d4STzx19YMc6YsTDxnazy4WVLW7s7EbfCg5OlzkyNzFMh7hfhBDcWvIey7pIKdHaDM0tjTHcfGtIEo0UgomRQmnEQ8So2PABuNW08cNKg3AchyRJsKy9j2lsbIydnZ2h4uHmwsMu/X6f+fn5+97/iBEfB2Unx6X2BreKv22hGPeKvDB1chgdCJCzXL4wcYJvLL/ETtAi1EkqUVY2nrQJdRdXWPgmwmCISRAa1vt1hBH0dUROeKz260y4RWphh0hrcspBKok2cKO/w4HcJLOZMk+VD9KK+3R8HyEES9kJHi3N7+vdvl/6XZ+Nq1tUbzGNFEKQL+W4+tZ1JhfHufrWChdfW8bv+mSKGY4+fZCF43NIKXnz++e4fvYGkwfGcTMOQgi8rEttrc6l15d59HMnHtjxfpxUnQI3+jVcZe973ZKKA7kJfmHqkX2Ty0lvjKfKB/h/rnwfSA3/lFB4VlqIinSMEmn7jsGgEMhBLokhXV0as7NUnTx5O8tavwFA2c6ijSFMIjb8BjOZCkIKHhmbZ8NvYIzBEorHS4scLc480GtQ32gQ9EOK1cK+15WlkJZk/comiyfnufT6MstnrrGzWuPf/7M/I+iH6OR2uW0cpi0k539ymX/13/wbZo/MsPTI+4tnfhixhCJnefhJuK+lBdKEiifLS3x+4vi+148UpqkFXf7sxk/IKndYJHBIY/QkEguIB3GpEonGDAtUllBUnByzXhkjDP0kRAlJ0XYxRtOM+mQth7lchcQYlnKTrPbrCCCjHJ4fP8pCbvyBXof1K1sIKYaFhl3crEu71qG23iBbzHD+p5e5cX4VYwxTS5Oc+MwRitUCgR/w0h+9jHItCjl3oI5wyBYyXPjpZeaOTFOsFO6y9xEjPrksr+/wyrnreI5NdSyHFAKtDde3Glxer/HFUweZrtz/wkM+4+BaFmGc4AwKf0pJ5sbHuLZZp5TzQAjCOKE8ML80xrDV7PLIgamROeSIh4rRaHyf3GzaeLN64MNIg5icnGRlZYVCYe9Lu1AoUKvViOMYy7IIw5BqdU8/FYYhUkoqlZGz/YhPJjOZMp6y6UQ+eTtdJTDGsBN2mM9U9hUadslbHnPZMofyk7xZv8aB/DitgexZCkmkE2wshEgn7BJIgILtUbAzZC2HZtjjQriOMQYJ5CwHiWDCLRAbzZbfwpKKJ8oHKNgZAh3jSPWeMu/fLzpOEELcUY5s2Qq/F3Lme++wfOYa5akx8uUcQS/gtW+/SX2jyebVbf7i//gWQqZqh8rUGE995TGqMxXGJopceWuFR54//qmQOx8uTLHc2Uzl5oOCgzaanaDNE+UDt61iA4w5OY4X53Ck4pXkIgdz49TCHo2ok0adGo1zk0R+d4VpwilgKYuc5VALu2wGbTBgSYkjbVxpUXXz9OKQHb9F0cnyXPUwBkOoE1xp3fF47pck1nf9LJVS9Np9Xv6Ln9LYapErZvnjf/GX+N1gaFx5N+IwZme1zj//r/+A//nFf/LAj/ujRgjByeIcL+9cYNKzhmqBSCd04oBnq4dv20YKScXNcaq0gDZQDzu40mYnbNOM+hihEQY84WCE2WcuOu2WUErhSIv1oEWsYzCpR4yUaTtX2c5QD7skWnOiOMfzE8fwkwht0lScB1nE3CUKoru3xghBu97h1b95A51oylMlEIL6eoPv/dHLHHlyiW/+2xc5+8NzuNm0IHvo8SVOffEktmOhlGLz2vao2DDiU0e90+eVcytUi1msmxb5pBSUC1mCKOYHb13hV587Sca17/FO746SkuOLE7x+aY3p8p7CeWGiRBDFbNTaSDkofucytHo+vX7EwZkKjxyYuq99jxjxoBkVG94ndzJtvBnHcQiCgFqtdt8GjZVKhdXV1WGbBqRFjfn5eVZWVuj3+yilyOfzxHFMv99HSsnx48dHbRQjPrG4yuYLkyd5efs8m34TBjL2+UyFp6uH7rhNoGOkkJTdHFnbY9KkkYK9JEQbQ58QS0gCnVC0PCyhiE1Cwc7w2YlU8nujV+Ns8wZVt0A39snbGSpOHksqFJLr3W1+ZfYJyoN+7w9j0riLl/ewHZsoiLBveWjptfpMHhjn6tvXmVgYH8op3axLZabCX/zv3ySONV7WJT94SGnX2/zg/3uFX/ztL5Abyw6l0XeaoAb9gLXLGzS32+RLWWYOTZMtvLfYMGNCTHwF4gtAAmoRYR1ByPy7bfqBKTk5Pj9xnFdql2iG/UHMhOFEcY4jhTvfg0MdY0tJyclRGkQaGgS9xEdLTTww44uNpuTk0MaghSHveHx+/Dj1qMuNbp1L3Q0mvQJdHVN0MozZWaSQKCG54df5h7OPD8fJh1GU2iVfzoExd/xMQz9CJ5r6eoOJhXFe+/YZgt7+QkNsIjZYoUebLAWmmMcS6biLw5izL19g4+oWUwcmbtt3t9ll9fIGvVaf8tQY00uT79kTpN/1ufr2CjcurKGUZOHEHAsn5nDu80H9Xizmxgl0xJnGdXbVKpZQPFc9zKR3ZzPNXhxSsNII1apbQBs9SD2JSUyCtFRaSACKTo5Ea6SAMTfL8+NHud6vYXcVq70a414BjaZi58nbHkII4kTTMD0+O57eizz14Z0/QGW6xPmfXLrtdTMYQzurdZJYU57aux7FaoEbF9f5v77+7/GyLsXxAtliliROuPDaZeIo5pmvPolUYqiMudP7N7ZarC9vEIcxEwvjTMxX37MnSGunzfKZq2yt7OBmXZZOLTJ7eOpT0eIz4uHn8uo2jiX3FRpuxrUtWibg2laD4/O33yvfL4dmqqzXOmzW21SKWSwlEQIOz1TJOjbXNutMlfI0uz5T5QKfOTbOZCk/fCYYMeJhYVRseJ/cybTxVh5UGoTjOBw/fpxz584RBAGZTAalFEopKpUKvu+Ty+XwfR/HcZifn3+gnhEjRnxclJwsvzzzOPWwS6QTspZ7z4z5rJXGXSZGU3Fz+DpkTGfx44Bu5CMRxCbBEum6Y5hEFJ0MB3MTzGUqTGbGBoaPiuPFGSKd8NPaZepRL13WFoaqW+A35p/5SM5fKcXx547w+nfepDpbxhpIIrvNHgjIjWWRUg0fKqIgYu3yBtfeWeHsjy8ztVQlW8gQ9kOcjEOhXKC52eLyG1eZWKgileTa2RtMzFe+plUKAAAgAElEQVTJFfeMCusbDX705z8ljhIcLy12vPPyRZ755ccZn6sQ+hFuxhkez80YE2KCv4NkE2QJcCA6j4kvgvfLCPnhpSLMZMv8mvcUtbCDNoYxO0vGuvt9MGe5GJOaSWYtDyEksU4oxlm6cYAgTRdxhEVkNMZopt0SB3ITzOWqHLNmqRd7eFs2z1YOc7W3zfn2GrWoizBpvOLJsXk+O37sQzvnfedTzLJwYo5r76xQna0glcQYQ3OrRbGaJ+iFZAYFo+/9vz8i9Pd8Bhpmm9d4CYNBkyBRnOdnPGW+QEmk8n1j4P/+J/+B3//f/ot9hYRrZ1f42XffQiqJZVtce+cG73gXeP43nsXNOsRRgpdz7zgZ7LZ6vPTHLxMHMflyDqMNb//gHCvnV3n+N5790ExMhRAcK85yIDdBI+yCEFSc3D2LQSUny8X2OhU3jyUl016JpG9oyT4d46dXzhiyyiGIU3XhYmaC2WyZA4VJlgqTrPWb/Kx+heerR/lpbZk1v04QdobeD7829SSHix9NglR1rkJxvEBjo8nYZDFN90k0tbU688dm2Ly2TaGyVyBs1zqsXFjj7MvnWb20wfHnDqN1WqxSlqJQKXDjwhqHnzzIzuoO43NV1q9sMj5XGd4rjDG8/cNzXHr9CpZjoyzJ8plrlKZKnP61p9CJxhjI5L07FkG3b+zwwz//KZZtkRvLEgUxr37rDTavzfLUL50aJfSM+FDR2nBlo06lcG9j30LW5cp67YEUG2yl+NyjBzh/fZPzK9vEWqceQkYzWy3yK585TrU48mYY8fAzKja8T+5k2ngrDzINIpfLcerUqaEZZb/fx3EclpaWRoWFEZ9qpJBU3fcmxXWkxZH8NGfbq0x6Y2z4LapunrxyaYT9VKlguVTcAlGS0Ih7PFZaxJbWcFLqWTbjXp7IaI6PzbKQq7LarxNrjRKSx0qL5O9R8HjQHHhkHp1ozr1yMTXvM4bieIFnf+UJGlut4cp0HCWc+8lF+u0AI0AqgVSSfttHJxohJbZroRzJWz84S7FSoDxd4urbK4xVC3z2N57hxGeOksQJr/zVa7hZl1J+z+Sq3/X5s3/910wuTqAshbIkhx4/wNGnD+1bkTTxVUg2EeomPwI1jtF1TPgawvvSh3q9LKnuujJ9KyU7x4RXpBZ0WMqO81ZrhblsBVfYNMIeiU6o2nnGvQLNsE9kEh4pLWAwuMpGCEHJyaZFLil4bvwwx4ozbPYbIARSSH7xFq+ID5vHvngSy7G48uY1AIw2TC1N8NgLj/DW988B0Nxu0dhsDreJTcRrvETC3kq0HngPvMZLfNH8OpawSOKE7/677zN9aIpf+u3PM3Nwim6zy8+++xalybF9xafaeoN/98/+hKmFcYSSOJ7NieeOsHhift8k8twrF9GxpjKzl6TkZl22Vna4dvYGR548+OFcqN19KZupTOk9/exua1eQRCxkx1lub3IgN4Ex0I77KCSTXoayk2MraJNVDkeK01hSIknboSpOHiUkWdvhyzOn2A7a7AQdlJA4UvLlmcc/1PO9GaUUp7/2DGe+9w4by5sIKTAGlh5b5OTpo3z7G99jt3mosdXi3I8v4GY94kjjeg79lk/oR3TqHbJjWWzHorbe58X/8AMyhQz1jRbWXylmD0/z5d/5IsVKgc1r21x4dXmfGotqgevnb/CH//RPKE2MYYBiNc+jnzuxLxFDa83r33mT/FgOL5caoNqOhZdzWTl3g8UTc+85QWPEiA+CHqh+3k01YClBL3h309j3iq0Ujy7NcGxhkmbHRxtDxrEoZB+MEeWIER8Fo2LD++ROpo238qDTIBzHYXp6+r6VEh83qztNvvXT87xy7jpXNuokiaaQdXn80CzPP3KAFx4/9MDjg0b8/HBybI5IJyx3N5jxSqz0dmjHPguZCt0kAJGmWmQ9By90WPcbPFpaIG+lX9qhjpn2ylhS0gi7FO0sh/JTNKMexhhOjM1+pOcjhODQ4wdYPDlHt9lDKkm+lEMIgbIURhu0Nmxc3WL98haWZxF0fYwxg9VBhd/to2xJv91nZ7VOHMXMHp4hW0gl4fWNBn/2r75J/n/I43oOQS+kUCmgE0273iEKIlbOr7OzVmNycZzxucqguHGJfsfnqV96bO+A44sDRcOtJ1KCZBVjfIR4OB6QhBCcHj/Cj7cvsek3mXJLrPS2CU3M4fwk7djHlRaudDiQz7PRa7DuN3iyfGAYydqLA44WZoh1Qif2KTlZCrZHLehSsD1msx+tb46yFKc+f4KjTx+k3/GHhn0As0emuXFxjSRK9k34N1gZGhneisGwwXXmSCf9URizdmmdP/pf/px/+PX/jLXlzaGiIY5i2rUuoR9y5e0V/HaPAyfnKZTzhEHEa98+g0kMS6cWAYijmNVLG6kfwC2MTRS58ua1D73Y8H64ubXLEoqyl2etV8eWkmPFGZphj5zl4iqbI/kp1v0G20GLZ6uHh9e7G/s8UVmiFnYpO3kmvCIlJ8tO0GExN0HZ+WhXKDM5j+f+3lP02n1CPyST93Az6UR+8cQcl9+4ytjkGOdeuUi33Sfoh/j9ACfrpCoZA07WIfIjQj+idqOO49nMjI/h5VySKOH8K5foNrr89n//m1x58xr5Ug4pBaEf0mn06Lf7XH/nBlqnY8OyLfodnx/+6St84TdPU5lOC1HtWod+x2d8bn9BQQiBl/NYubA6KjaM+FBRUuDaNmEU39N80Q9jipkHn/RkK8X4KGFixCeUUbHhfXIn08ZbGaVB7OfGdpN/8o1v8frFVQyGKN5zP99odLi4usNfvXIWJeX/z96bxsiV5Vd+v3vfFvuekXuSyZ0sLlVkra2q6lK31K3uaWk0klqCZ7FlQx6MPYBheCB4AH+xP9jwAIaBGcCGPAJs2bAHGtmSLMvTrZHcm1TVte/FIpNrMvc19u1t9/rDiwwymUlWVVeTXV0dP6BQZOaLiJfBiMh3zz3/c/iHf+tp/p2ff2w4czbkE2NKg/PFWY5nJ2j6XQwhuVRbYtNtkLbiXG2s0gi6SCGIGw6r3SoJI0bd7+CrEBB8cfQkKTPO5cYyS50KAphMFDicGsPsNxQ87FBF0zLJlnanW6fzKWbPTPPmX77Le39ziWalReAH9NounuuzuVhhbLaMNCSjB0YI/ZD1hS2mT0ztmrt3Eg5by9u8+Cevcu6Lp6htNui2e9x4f4FeK3JG1DYbxFMO2ytVkpkEiWyCkakii3MrHHlslvQgvCoE9oqFUYWXAK3gM/S2jhk2z4+epOZ16IYutjD5wfol4qaFRnO5voKrfKQQSAT1oEtMWtS89iDs8WuT5/GUz8XaEuvdOqaUHEqVOZAaQem9LQ8PAyfuDBaNO5SnixTG87zy568TBLcrLjs0B06Gu1GEdGgN/i4NSXGiwPK1Vd78znsANLZbVNdqzF9cwvcDfNenU+8QT8WprteQUpDIJCiMF7j02lWmjk9gWiZKabTaf5dQSkkY/GSeu/uxM9pV8dr4/XyG761dZDSWpeZ3uNFcI9BR7ZyvwuizAkHVa+OFAXk7yRdGjrPeq3G5scJGr4EtTc7kZphMFAZjOw+bRDq+J5Nl5pEp5j9c4LVvvcXca9dQStHreHTbPUwpyY1mseMWUkaC6K1LSyQycQ6dOUByZ0EUg1jSYf7iElffvsnKjXVUqJi/uMDK9XW0UrTrXcIgJJGOXi/pfIp4KkYYhMy9fo1nfvkJgMihdY/PXWlIQv+z93oZ8vlCCMGx6RLv31hjJHfv92m75/Po4Ye7MTFkyGedodjwCdkvtPFOhm0Qu/mzH37AP/vX38MLwsGM537s2M7+h//nJb712iX+xT/+1eEs2pAfiaTpkDSjxdZlKUhZMeKmzZn8DJ3Qw1MBjjSpex1OZqfQRLPWE4kCif7tniod5XGtaPpdPqwv84ONi/37jnEmN81k4iezi6a1ZunKClffvEFlrcbVd25SWa1GRXthNLtvdj2Wrq7QarTJj2SprtXpdXokM3HGZ8uD+2nXO1TXalRWq7z7/Yu8+70PqG+1aNVaGKakMF4gcH1qG3Uqqwqv59OstrEdi9kz0Q51Y7t5W2wwZsD/EIzy7nNWHZAZEA9vBOWTkLMT5OjP4fbdL1IILhQP0Q56hFoRN2w23QZn8gfwVEDGijORKGD35/zLY1kCFbLtNnm/vsj1tXUASk6Ks/kD5O0HF5B5PwI/4OYHC9x49xbri1us3dzYFQyZII3E2FdwkBgkuH3eiXScm+8vsL6wyR/8F39I+UCJ+laTVqWFk3QoThSobzXoNHuolQrSlJSni8RTcQ4/epDAC2nXO2RLGWzHojCWo13vkMzunoFuVlpMn/hsXqxLISn1R7tafo+YYWEbJmUjQ9FJ0fJ7AJzNRQ04xzLjeCqgHMsyEstgCMnBVJkDyRECFbLcrfBhfYkP65HDZDpZ4nR2evA59LDptntcf2eeWx8usXh5iYVLS7QbbQzTxDAk+VKG6nqNuVevMTJTIldOs35ri16rR2GiQCKToNPo0m136bZ6dJtdVm+s88//0b8kmU3Q2GrSaXVJZRPkR3Nsr1QIghAVamJJh1Q+SW4ky8HT02wtVwiDsJ8JkcIwDQI/2JMX02v3GD346efjhwz5KGbKea4sbdHs9PYdY6i2uuTTcUbzn776csiQzxNDseETcq/QxjAMh20Qd/GH33+bf/EnL9Lz90+m3o+eF3BlaZO//9/+K/73f/p3h4LDkE9F2cly0V0iYToIISIhAodAhdiGxYnsxD2D4bww4MWNy2g0I04UotYLPV7auMIXyseY+gkIDnNvXOfyq1fJjmRACECQSMVoVFrkx/IYpiSVT2LHLJSOBAKv2wMU9UqLy69eZfLYOIEbsLm8TafRpVlpoUKFUop2o0O30aUwWaDb6CCtqDbRidtYjoVhmRiWwZU3rw+cExCJF/XqCNvzLYRsUZwYI1tMoFUbdB3sL/1U1GyOxjLU/A4ZK44UYlCz2g5cRmM5TmQn73nbmt/hbzYuk7JilGMZtNa0gh7fW/uQL4+dJmvfP1jsx41Sijf/6j3W5zfIjeYI3ABpGiSzCdq1DgCjTHGFd/e9vUAwyjQA0oxGeJavr9LcbmHFLDSC2kYDpULShRStWpvQD+k02iRzSXSoiKXihH7I3GvXGDt0+/WilGL0QInv/9HLpPMpxmZHsByLZqWFEJpDfTHrs0zctLGkia8CLBnVaO78G2+5LY6kRu/5ehFCsNDZ4s3KTQp2krQVR2nNSqdK1W3x82OnB0LWw8Lturz8Z6/TbbmkiyncrheNydhRTWe6kEKIyA3VqrXwex4CQbfTiUSti0t88DeXCPvOmR1Ry45ZlCZLpAtpqus1nLiDlFGmjNvzcds9CuMF3J7PaDZJo9Lk6ls3GJ8dRdzhfClN5HnnBx9SnCgwMlVASkl9sxG9foZiw5CHQNy2+OKZQ7z4wU3Wqy0SjoVlSlw/pOcFFNMJvvDIQUxjGFY6ZMidDMWGH4F7hTYO2yBu8+6NlU8sNOwQKs1Wvc0/+b0/53/53d/6qVikDPlsMpMsMddcpel3BwvHUCs23QZncwfum0A/397AUyEjsdsjUzHDJu/AB9VFJuJ5pHg4FxVhGFJZqXLxpUuMHRxFGhK349Jr9cCUdNoucrNBupCMFgeGgdH/2botlzAM0aFi+doqa/MbCASpQjKahW67pAspVKBRQUgs7dCqNDFMk8Z2A98L8boe19+ep13vkCtlMG0TKSXF8TxhGPLu9y+yNLeCEGV0uIgO3uHw2Swnnz6EcL6END+bO9V3czw7yffWPsCW5qB+0A19mn6X50ZO3Pe2H9aWSJj2wFUj+mJFoNtcaa7yRPHwAz//HXzPZ+nKKotXVpg8HGX9dBptdKhI51MDscEUFo/pZ/e0UQgEj/EsZt/Wr0MNQlPbaOB2XUaLKXqtLtKUGFrSqnUIgoBWtYVSGq/r06136bZ7UduJgOJEnlQuSa/j8vpfvB3Z5gtJlq+scO3dm0wdm+D444c59fSx21b8zzCGkJzMTvLW9k1GYulBGGg7cAHNbKp8z9sGKuRibYmSkx5kgEghKDop1rt1ljvbzKZGH8aPAUCv4zL3xjUa1RajMyP4XkC37SJkVGPpdjwMUxJPxREyCrxMZBO0am2owtW3bqLC/UcZ3I7HyvVVPNfDSdioUNFp99heqdJudhBCsHpznfpWg17bJZZwCIOAk08fQ0pJY7vJK//mTbrNHvGUw7W3bnDljescOjvN8cePcPzJo1j2g60KHTJkh0wyxi8+foz1SpP59SquH5BNxpgdKzKSHdZODhmyH0Ox4Ufk8xLa+CDwg5B/+vv/5kcSGnYIlebq8hZ//OL7/MZzDy+le8jni7hp83z5JG9WrrPRayCILurP5g5wLDN+39sudSqkrb1WyZhhs+E36Ib+YGH5oNBaszi3zKWXr7K5tM2tS0vUN5tMHRunU++wubQdBbU5FkqFVNZqOAmHWDKG1gqBxnMDMqUUY0Jy8+ICrVobaRgEYUDgKdCawA1Yv7WJ23GJp2NoqWk1olrARCZGu94hDEK2lreJp2J0ml3smI3WmvkPFli8vMLIdLEvDE4Qhh7XPtwiP3OeySP3f54/S5ScNM+OnOCt6k0aftQoZEuTp0tHGUvk73m7QIVs9OqUY3vtsxkrzkq3Ajx4sSEMQ668cZ0b7y2wOLdMfaNBt9ll7GCZZrXF2q0t0IpY0qHXcUFDTpR4Tn+DdRbp0CJBilGmB0IDRLvTje0mYaAxpKRVaeN2XPyeRyqXpNMPELQcC62h2+yiQs3mUgXzkInbdmnV2mitef+vo4yRkamoVnPmxBTdZpf6VoNTTx8jU/x4DTSfBQ6nRtFac7G+hNIKDaTNOF8snyK1z2fHDs0gajix9mkrSVoOK93aQxEb3K7LxR/OsXx1jatvXgcp8bo+2VKa7eUK6wtbaKUxbYNuq0u71iaRTRJPx1BhSKvWZf3mxj2Fhh200mwubpHMximNF2lWW7j9UErfDXA7Ll2tqKxWyI/n6TW7dJo9wiDktW+9hTQk5ZkS5ZkSh84cpFFpEgYhp75wfCg0DHnoWIbB1EiOqZGP12YzZMjPOkOxYciPne+8fZVm1933e259i413v0/l6pso30VaDoWjFyifewEnW9p1bNfz+b0/f5lf+7kzQ7V4yI9Mzk7wpdHTNIMegQpJWbGPZVE2hYGn9lZYRfZgjfEQHDeLc8u89f+9T34sR2Esx/ZqhY2FLS6+PEfgBagwpNt20WGIEDEs26TT6GJYBol0PAqO9BRrtzZQfkjoR0GYoR/Qa2rSxRQIjeXYtOsteh0PFSrcnrfTfIcONUIKDCnxuh6tWpuTTx9DBYqFy8vcePcW+dHswIGktabb9Glu9/juv/obfuEffJHydGlXTeZnmfFEnq/FszT8LhpNxkpgfISDRQiBISSaKBTwTpRWGPsEZz4ILr40x833FyhO5GlWs3g9j+vvzvPu9z+k2+4S+gF+z8O0TWICeu1IcDCFOWiduBtpCsIwxHcFmWK6H5Iq6dQ7eD0/Cvpr9DBNg1AIQCOkxDAl3UYHIWD29AyhH7J8dZW1m+sUJ29nGiml8FyfrZUqP/jjl3nmG49THM//VDjahBAczYwzmyrTDLpIJBkr/pHnLrn360lphfkQHFNhGPLat9+msd2kMJ4nVUjh93ze+e77hEFAs9LC67gEfohAEM/EQWja9TamnUVrva/QEGifdZbo0CRBmlGmMIUFGtq1LsKo4bZ7GEbUqBOGIVIKhGlQ3Wwwc3KKsZkSG/ObLF9fi1oodtVghvhuwNKVFV799tucffbkT5VANWTIZxGtNegqOlgE3QORQJjTiP0apnZuoyrocBO0DyKNMMcRwr7jPj2iCwkL8ZBcoEM+mwzFhiEDPM8bjIbsBGCWy+V9R0Pud+z/9ldv7NszXF+4xPxf/gEqDKNkekD5LluXXqFy5XUOfuW3yc6c3HWbnufz+twCT5088OB+8CGfe4QQZKxPFlA4mxrh9e3re8LamkGXESdLzHiw41JhGHLp1avkx3LYjgW5BN1Gl+pmA3R0cXDgkRnm3rhGu+ZiWBaGaWDZBlIIqms12rU2wpCoUGGYBioMMS2DMAAnaWM7Fr4bUN9s4Ls+OlS0wg6hH2IaBobdD2VzLHIjmWg3s9pGBYqZk5Msza3i9fzBxb7WmoXLS6zf3EQaMrLMf/sdcqNZnvr6Y3taEj6rSCHJfYIqQkNIDiRLLHS2KTq7wyCrbptTuQffTtRudLh1cZHSVBEpBflylkuvXMHteviuRyzuMHVsgitvXsfr+uRGMsQSMdqNDv7O5/UdGb6WY2La0SWCCkNiCRvLtmg3OvTaPQIvRCtFqxqgwmj3WpoCtCCWsMmWsvQ6PRpbTSaPjFOaKrB6fX1gwwcIg4Crb81T32yglWKh66F8xfSJCc698AjGT0kVsimNTxQCmrHipEyHTuDu+nzRWtMJPA4UHnwGwfZKlepajZHpSOQvTRR449++A0LQrHbIjWYxbZP5D26hFDgpByEFUhr4rsfWcmWP0FDTW3tGcq7wLo/pZ8mJ6HHa1XYkyNkQqqi9I5lNkswmaTfatGstCmM5krk428uVfjZNRK/jMvfaNdyui9vxuP7WTSorVU49c+wzVZU6ZMhPE1p30e7LEK4CFggLtI/230MbMwjnqd0igmqhvVcg3ABk/78A7Rto80wUCB1chnAzuoGIoa0TCPMQQuy+BtCqDbiAGQkWn0GRWasWOrgB4S0gAFFAWMdAjg5FlI/JUGwYAkC73WZubg6lFPF4nFQqRRiGLC0tsbKywvHjx0kmkx957LXr17m6vLXn/t36ViQ0BHtFCLRCBYr5v/wDTnzzd3c5HHpewBtXl36iYsMnEWGGfH6YShRZaG+z1q2RtRJIIWj6PQwpOZd/8K/HXquH3/PJFKKFvB2zkaZB6Ec7gW7HJ1OAdDZJKpPA7XiYtgGYBEFIu9HBc/1o/ahBCD8KgtQaHSpM06C6XsOwTbyuF7kjLCOaz9egtEYqjWFJUtk4/U1r3K5LdiRDbiSLZRvEUw5ez8OO2dQ3G6xd3yAzksHtehSyCUami1TWqlx+9SrnXjj9wJ+3nxQnspOs9+ps9BpkrTgaTcPvkrETHHoIlvhWNRp72XGBxdNxVBiilUYpTeAFOEmHfDlHqEICLySZi5PIxAj9kOpGg9APQBAJAlJEzgWtQWsMO6C3VsU0I6s96EjIUhqlFVIDmBi2QSKTQGsFGlq1DlPHJ4glYzhJB62j85FSsHpzk8Z2g+xIhlatTflAiZHpIouXlylNFpg58fmskBZCcKF4mL9Zv0QvDEhZUWht3etyIDWy7zjOj5vKahXLuT2CkMgkCP0QwzIIg+h1Y1oGxckCgReCENiOiVa63zTR23V/gfZ5mxcJuT0+udNy8jYv8pz+BqaIbq/RSB29Vs2YRSzpoLVCK02z0uLIY4fwet5gHGyH+fcXCIOQTDFDXTcoz5RIF1Jc/OEcxYkC+XL2AT9rQ4Z8vtDaR/d+AKqBMPaOPGq1hHZ9cL6IEEZfmPguaB9hjN11rAfdPwUssE4gjNH+Y3jgv40OroHzJYRMosNNtP8+hGtEv3Q0iCzaPI0wZ3aJDlorUBXAj+5bFh7aIl/58+C9HJ2jzAI2qCq6910wxsF5dpcQM2R/hmLDEDzPY25uDsuydi2eTdMknU4Pvn/6dLRQuNex8Xicd67MYwj2FKltvPv9yNFwH1QYsvHeD5h+7tdvf01r3r66xNra2k9ksf9JRJghny9MafCFkWMsdba53togUCFH0mMcSo8+8KwGAGkaaK37tnWBVhonYXPg1BTL11Zxuz1qmw0My8CwDFqNDl7VRysNQtCpd1Dh7a1qaUQ2f600pmnguT5CSIQRDpwPlm3jxG06zQ7BYMFhEkvFkFIS+CHjh0aZPDJGu9HhyPlH0Frzznc/YGS6xNqtTWKpGFppeq0eBx+J2gxyI1kW51Y4+czxyKXxOSRhOvz82CPcam1yq7OFJMoGOZAaeSjNAoa5++LLd31Kk0VUGOVqtOuRg8GOmYShQbfZwO24SAFhqPBcD/rrOiFByUiUioQHid/1EVLg98UF0zJx4hZWzKK53QYpogaKTJx4MgZEAsfMyUlKEwXqmw1mTkyilWbxygrFsTzr8xskcyl8L0ArTWkiyv3IlDJcf2f+cys2QJQP8uXxM9xorrHeq+NIi2dGpphIFB5K8KzlmLucCSoIGZstE4Qh22s1apt1VKiJp+J0m71BU400BF7Piz5n7mCdqL5zPzSadRYHozrCEIPPtGQqjpOIoVSIk3A48Mg0yWyC0PeZPTPN2vwGje1mlBtSaZIpZui1e8QSDuliGsOQ2DGbxbnlodgwZMgnRAeLoLb3FRoAhBxFh6ug1sGYQPtXQHUQxj4BuGobdAcw4I7MHyFsEGNoVUV7P0Qbx8H7axCpvjugP4KpOuD9NVqfAetc9DXvXfDfIXI/JEEYIONo80zfKfHgnBA6XAfvRZAjCHHHdYuwgAxaraPdVxCx5x/YOXxeGIoNQ6hUKiil7rlwt20b13WpVCoA9zy22WzihVEAH3dddFSuvjkYnbgnWlG58uYusQFgeX2Ll156iXg8Tj6fx7Ksh7LY/yQizNDh8PnElAYHU2UO3idZ/kERT8YoTRZpbDfJFNMIKbAcK5q3T0Tfaze6bK9WCb0Qz/NwElGtXKfRQend78GdhYUViz72w0ART1lIQ2I5IYl0jE7TpduOwv200gRhSKfVQ2zUceIO6VKKicOjNKstRg+MMHF4FMM06NQ7XH9nnu2lCsIUWF2TA6emyI1EO7Q7lYeBF3xuxQaIwkOPZyc5fp+KzAdFfjSH5Zi4XQ8nbmNa0QhCMp8klUtimAbNWouNhW1CP0AFIVbcBjFJvHYAACAASURBVCnpNHoDoQGij2qtFMgoHDL0FaFSpLPRXL8Tt3HiziAIEs2g8rDT6KCCECcZpzRRoDiRZ3utyqEzB8iVsyRzSbyex/K1NeqbzcFu+tHzs8SSkYhnO1Eg5eedjBXn0cJPxv4/eqDMxZfmCEOFYUgMy4gqTlMxcqU0Xs9je61OY7OO1wtA6Oi1EPazPu6iQ3PgZLgbRUiH1u0vaE0YKLRSNKutyMWQijF+qExuJMv2SoVHX3iEWCLGk197jNe+/Tbr85u0ax20hnjS4eiFwxj9zxXbsei19s+JGjJkyH0ILsF9chkAEEm0fxnkCARzIAt7DoncBwvRfek2qA0wdlcYC5lHB7cgWABjco8jQMgEWsfAfx+NBe5LEFwEkY5EBgwwpoAUeC+jdRthP7gAee1/ACK1W2jYdb6j6HAJraoIee8A6SFDsWEIsLGxQTx+/3n2eDzOxsbG4M/7UavViDv2vnsbyv94FwL7HWcaklwuh1KKSqVCtVplamoKIcQDXex/EhFm2Eoy5EFw5rmTvPR/v8b2SpVEJk6unOXSy1dQSnHswiHe+f5FVKBQSmEIA8MwkIZA+dFCkb7uJy1QishypDU7MxF+z8dJRq/vTjOq7NMaTMtAqf79SknghThxKE0WKYwVePTnTzNzcmqQBH/qmeODHcn1xW0mDpWxY7ffN74XYNkWTmIoyj0oDNPgsS+f4bVvv023YRBLx4glHG69v4AVs5g5OclLf/46oCPhyZBYMQuvE43XIBloxNKMcj5QUY6AMAT44HZcTNsk8AN6/WpEraO2At9VkRNHCPxAkTAFhfEcU0fHeeIrjzJ5dBwhBLZj8eTXzlPbrBMGIaZlUpwoDMQRgE6zS2F8mPT+IEnlkpz6wnEuvnSZWDKG6ZgEXsDqzXUKE3liCYeV66+jiTYYTNsglohR327uu2+QII3E2FdwkBgkuJ1pYdoWgR+AEGilCIOQWNImO5LhwCPTnP+Fs5T7WRLJTIIvfvMZ1uY38L2A0kSeTDE9EDABuu0eBx75/Lpghgx5EESjbnWE/IjrV5GMxhh0F3SI2M+ppzugXZBx0A6oBvvmIocNED7C3F9kFUKiVQDt/zX6gnEgstoB6BDCedANME9GooQxgTBK+97Xp0GrFoTrID9qBNJEBwsIeyg23I9hssUQPM/7yCAuwzDwPO++x4ZhSDkTw9+nBktaH892vt9x0/lElPZuGMTjcUzTZGlpCSnlQIB4EHxSEWbIkB83qVyS57/5DCeeOoIdM5k9PcPMqUmS2QTtRhe37VIcz2FaBnbCRilFt+VG44UIDMsAAVqLQQJ+GChMyyJTzJIupACBChWWY0aLx1ChQoUds7Bsi1w5S2mqSLaUJjeS4d/9L3+TI4/O7nEoJDMJHv/qo6Syce40VYShorpW5eiFQz81gX8/rYzOjPDCb36BmVOTWLbBuRdOkytnSBeS1LcaCB0FR5qmQSIVx+8FeD0PAEPKXY0hO/ZUFShsxyJdTJHMJqIMiL7AgBAEfjRuY8dtTNuiNFmgNFEgkU5y5PwhfuOf/ArTxyeRcvflRm4kyzO//Pien8F3fTqNLkceO/QAn6khAEceneXZX3ua8kwJJ2bx5NceI5lJ4sRtttdqxFIOqVwS2zGJxWN0O+7t0Yu73MujTO1pYtlBIBhl+vbfJVgxC9uxGD1YpjBRwLIsnv+NZ/ilf/9LA6FhByklE4fGOP/l03iuvys0stPsYhiCySNDwX/IkE+GAOSuXJT9CftjEWLP+37XMQM09zxQV4F7bzpoAggXInFDpG4LDdAfoShE4xpqHYSDDq5+xLn/qHiA+OgxDWFHTo4+0eirh9b75NP9DDN0NgzBtm3CMMQ07/1yCMNwsMN/r2MNw8AwBGnHpN4Ldn2vcPQCW5deuf8ohZAUjl3YfW6mZHZk95iEaZr4vk+z2SSdTrOxsfFAnAWe55FK3T9h3DAMut3u4PhhkOSQHzfxZIwjj84O0taVUmzNbFNdqxNPx8nkU5iORX2zQa/tYtsWoRegASkFWoq+4BC99+LZOMl0HGEYxBI2za0mnm2ifIVARGMVtoU0JWbGJF1IEc/EKY3nyRYzeF2PWGJ/8TBTTPPk18/zwz97ndUb63SbPeyYxeNfPTfceXxIpPMpHvnCicHf129tYlgGC5eWiKdilGdKBIHC7/l4ro/lWCil2LmwklJAPysEIDuSBTSJdAwQ+L0AyzRRgUYApikxHQspJXbMIlvMYlqSkalilBOi9P47XMDE4THOPH+S1//iHTYXtnB7Pul8kue/+TTF8eFO0cOgOJ4fPNetWpvt1RpCCjrNOdK5NLlyhqvv3EQHChFEridfRwGfoX/797kpLB7Tz+5poxAIHuNZzP4Mt2EbOHEHKQWxZIxMMY1hGhQnCvi9+1+gn3jyKL7n8+4PLlFdqxH6ISPTRb78958nnvpkbUNDhvysI4RAGzNRC4W4z+etaoB1LHI4EENrd0+rBFjc3mVwQd4rRNuL3A/3ItwGoYAuiNju72kdOShUG9xXwDoDqoW2n34A2Q1WFFq589CqA2oN1GbksBApMKeiNY2IRQJDcAuCD0F1otsYIwjrJMiJz2TLxsNkKDYMoVwus7S0RDp9767qbrfL1FS0WLjXsblcju3tbc7PZHnxegX/jnC68rkXqFx5HRXcW2yQhkH57Bd3fU0pzSMTt0OfwjCk2+3SarXY3t6mXC5jWdZgcf/j5E4RJggCms0mtVqNMAwxDINcLkc8Hse27WGQ5JCHRmE8T32jweyZGRbnluk0ehTHC9S2GhimJJlL0m33MAyJNCWGaSINie96hEIRT8WieWk3JHCjWsukARITt9dDa400DFKZJIlsHCduk0jFiKfipPLJwU74vdD9poHRmRHshI1hGqzf2uLK69c5+fSxh/QsDdmhOJGn13E5dPYgy1dXUUpTmsyzNLeK7VhYjonXdQcuGDtmARq364MJtm3i9rwo10FALOlgxSxUGBKGisAPsW2LZC6BHbOxHZNULkEiHcd2bHwvwLT2v9QQQuC7AbZlMnl0HDtmIaTg6hs3yRTSTB7ZP7RsyIMhlnRw4japfIrjFw5RXati2ha5kSybS1vEkg6mZRBUWkjTQAVql4spJ0o8p7/BOot0aJEgxSjTA6FBiChfwY7ZpPIJTMvEMA0KoznS+ST+XZsUexDg9wLiqRiZU1NYjoXQ8N73PyCVTZAtPfgWjyFDPk8I8yg6uInWIULsVYW1DoAAYc5GIw7WSfDejJoY7rwfmUDLDKgmIGGf0QatFYg4iMS9T0hVQPfzGe5como/cjzobvQ93YVgEeih3e+D84V9BJBPgUiByEfVnKoZZVUIGQkuwgY64L0XGTjsC+jed6Jzl3mEMRqJ9aqF7n0PrONgXfiZrsn82f3JhwwoFApIKfG8/RcRnuchpaRQKNz32HQ6jVKKC1OpPSqeky1x8Cu/jTSt3bYoACGRpsXBr/z2rtpLQ8JjM1li/Vlez/PY3Nyk2WwipRzYclutFh988AHtdpsfJ+VymW63S6/XY2Fhge3tbQzDIBaLYRgG29vb3Lhxg1gsNgiSTKfTmKaJEGIQJGlZFnNzc/d8focM+STMnJhEE9nNU7kkW0vbbC5tYdsWSmvcno9pGVHAn4Z42sGKmZimSTIbRyhIpOOkCiliSRs7boOCscMjvPBbP8fBUzNk8yly5UwUFAk4CYfMSJpkOk48FbvnuQV+wNvffZ9cOcvEkTFK/Tq6kakiV9++QX2r8dCepyERxx4/TKvaxjAFdsxm9foarWoH0zIIw/B23WEYIg1BPOVg2AZ2zCKVTRCGilQhRaLfMhHVq8Kpp4/xc7/yBBOzZdKFFKl8CqU0WiucuENpqkgyG++LF/vTqDS58vp1RmfLjB8apThRoDCWJ1fO8N4PPsT3hlbUh4lpmRx+7CCV1QpOykEIweLlJUI/QAqB74VoFeWD6FARS8cQcvfvelOYTIpZjoozTIrZ244GU3L+q+coTRXIlTPEUzF0GAmTpmVSmiqQH7t/m8T6rS1Wrq8zfWyCsYNliuN5ChN5TNvivb++9MCelyFDPq8IYyRqflBr0e79HWjVisYV7CcQMnpvCvMIGONRE4O+K59FjoLeAuMwgt2f+9HiewPsJ7k7QH43YTSWICdB9DPcdAjBPGivLwLE+wv+IHI7dL+Nbvx3KPd1tKp+qudjByEEWKcjgSP4EGQmqr4UZjTOIRL9cwC63wLVRBjjiL4bQwiBkGmQY+DPRbWfP8MMxYYh2LbN8ePHB6MJQRCgtR7s5vu+z/Hjx7Ft+77HdrtdSqUSh6Yn+NsXDuLcVcWWnTnJiW/+LqVTzyCtyJIrrRilU89w4pu/S3bm5K7jHdPgF48XgcjRUKlUIquubfftvpJms0kYhiwuLvKd73yHxcXFH9uivlAooJRiYWEBKSXxeBzDMAb5EZZlYRgGCwsL93VW2Lb9QLMlhvxskcwkeOKr55h7/TqtWpvcaLYfvBfVVoZBQDITJzeSIZ50CP2Q0AuYPTNNYTRHPB3DjjmMTJc4dOYgpckC08cnKY7nmT09w8lnT4IUbC5vo8KQ4niew+cOUprIM3l0nGT23g6d2kadwA12hUNC1EZhmibrtzYf9NMz5C7K0yVOPHWUd773AVKKqNkESGTi0aKRaPQiV0rjxGzcno9AcPTxQySzSZKZBLZjMXl0goOnpynPlJg4FM3ZHzl/iGMXDuG6PlsrFSzbYPRAmcPnZ0lk4hw9P3vfnI7NxW0MU+4K+wOwHIvAD6mu1R7skzNkD0cenWVkusS73/uQRDZBIpNAax2977VCmoJ0IUWmmMa0TOLpGNKU0fjNPkhDYNomX/ntF3j66xeYOT5Js9qiulYnmUswfmiMIxdmiSUcDj968L7ntnR5mWR2765oKpektlGj3ejsc6shQ4bcD2mfBueLUWBruBYJCWoNhAPOl5HW0cGxQpgI57kooFFXouPDdXS4BkYRYv8AhNEXI7po3UOrSjSCYB4E5+fBmEGrtSjfABcdbkb3oar9AGsZLfR3xA9Vj8InRX/8QgegahDeAhkDYzQar/DeQfe+hfI/nfAYnXMzEmJwAK8fjtl3ZmsPVDWqwDTPQHg9Oo99EEKCLIJ/ca848zPEcIxiCADJZJLTp08PMge63S62bTM1NbUnc+CjjgWYObDNxeUqV1dru8YpnGyJ6ed+fU+95d1YhuQ//fpjJFUL3/dxXRet9eDCtdfr4fs+lmUxOjqKZVm0222uXLnC5ubmxxpbiJTWlWgeTdhgTOP77MpdaDQaNBoN0un0wE2hlMLzPIQQHDx4cOBuuB87QZLD1oohPw56HZeJo2McPX+IMAjpdT2uv3ODpasrLF9ZJ9ZfIMaSDrX1OtlSmsJEAbfn06q2CHxF4PkUxnLEUzHyo1kOPjKNVpprr1/DSTggBMlcgolD0c716IERzn7x1H3PS4XqnrlQwpD43kfYpIc8ENx2jxNPHutXF2ratRZX377BrYtL1NZrJDMJLMfCjltU1uqMHyqTyCaobzRoNzpYjsnGwga5cpZULkVuNMPpnzvOrQ+XWbyyQjIdx+v5pPMpJo6MEU86HDp7gNkz95rbjQj8ECH33/PQaMJ9woaHPFiEEPRaPS784rkouwPN5uI28x8ucuPdebqtHslsAidmg5A0ths88oVjdBo9rr97C7ftotFIIUhkE8yenWH2zAGe+Oo5Xv3WW1TWa6QyCcJAkS6mmDwyhu1YnH7uBKXJ4n3PzfeCPcLUHWd+O7xyyJAhnwhpzqCN6ajpQQcg7Ghnfh+EsBD2o2jrVDQ6QJRbgMhHORDqJDpciCouCcCYRpiHQRaj7zvPoN0fgvtiPwjS6PctByATIIogS9EiXVUh3Nyd3xCuAS4YR6I6TiFBpiJHhDgI3hsokUSaM/ud/j3R4SbavwThUv8LLqhlMB8B3ernNRCJMOZRMMoQrAIWhFtg7p/xJoSDVrVIIDHu/xn3eWUoNgwZYNs2Y2NjH2tBfK9jd0IStzY3+cdfPsX/+J1LXFuv4/ofT9ETAiwp+Q9fOMbxiRxKZVhZWaFarWLbNlrrgQiQyWQYHR0dCCHxeHwgQNyrElPrENwfoNv/M/jv9R/UBBRaewT+CG77F7DMr2LbGTY2Nkgmk4NRkp3xiGKxOBiZkFLSarUYGRm55891Z5DkkCGflsVLy2QKaRLpSOm//Oo1bMfGNG1SuSTlmdIg1b8wkcfveKzf3EAakrHZUaprNdyuh5N0OP7EYQpjeerbDa6/M8/U8QnSuWS0yFjY4talFZ79O09z4qmjH3FWkC5GFyeqn9twJ37PY2Rybz/3kAeLUorFuRUKYzmkIQmDgJvvzZPOprD78/kj0yV67R7dVpex2RKN7SadeodkJkE6n6K2UafX8ciVcxw+d4B4Msba/AZLV1Y4ev4wsWSMwPNZvbnOwuVlfue/+XuUZz66jqw4nmPu9b0ClFIaoaPA0SEPl1atTaveYWQquijuNLtU12qkckmcmEMilSCVT9Jr9XB7LpOHx9hcqGDaBkfPz+L1ApqVBqZlcfb5kxw4NQ0SPnhpjmalzZlnT2LaFl7HZenqKhtLW/wH//XfJZ68v2APMDY7woevXN0zyuW5PnbcIpEZhkQOGfKjIoQAcf9Rpt3H22BEawCtg8jJEFYguAFqlah3u4wwp0EW7hqv9sEcAzXar8y0I4EBB/wPIHgvcg0E10BfjcYWtATV6ldfngJz+o6xbBt0CyEMtCyA/x7amP7YwYzKnwf/RSAZnbOQaNWA4DIE18E8Ac5xQCPuSDzWeEThmL2P8Sg/u5stQ7FhyKdmR2BYXFxkcXERKSUjIyNks1n+8799gb946wb/1+s3EULi+vd+szmWwWQhxX/0C4+QMBS9Xg8hBBMTE4Nxjl6vRxiGFItFRkZGdll0d7IkbNvGdV0qlcouMUT7H6Jr/wmorchyNfhG9D8BxKxVJrN/BPyfbHT/IVofJJ1OEwQBSilmZmb2NHHYtv2Roxt3tnkMGfJpUVoPMkt67R6NSgPLttChwjAE8VSMVC6JEIJGpRVlNyQdnJSDE3c4eHqG6lqNyaPjHDp7sD8LvUGiv7iEqK6ufKCMXNnmnR9c3CM2+J4fVR7eMTIRT8Y4fO4gV9+6SX4sh2WbqFBRXa+RH8tRHIoND53IqsqgLrBRaRN4AUrr6FrQNEhmEySzCdbnN2hVO+hQYWcSWLZBKpuiMJ6nslrh8LkDTB6dYOXGGjffX6Q8XYoyPwDTtpg+PsXKjXWuvHVtj9jg9bxonOaOsMjCeJ7SZIGtlQr50RyGIQn8gMpajUNnD5DM3CdIbMgDQSu9K4dhe6WCNA1a2x0QAsOWpAsp0oUUC5eXaGw3kKYkno5jWia5cpaR6SK1jRonnj5GIh1j4dISK9fWmTo6NnCy2AmHQ+cOsnx1hZVraxw+d3DwmEopfNcfBEjuMHl0ghvvLVDfbJAppRFC4HY96ht1zv/i2WG17pAhDxmtamj/SrQgD+chXAdjEoyjkdtANaLwRPMQ2E8hhIkO5iFcQxiz+zYVaetR8N+P8iJkPhqTUBqEH1VfGpNgTvbdELr/u01FDglAiHg01qGrID76mkOrBng/BDmCEHdkTQiz79hIRwGRMo2QdzumY4B3O7/h3o8SOSJ+RhmKDUM+FTstDDvhjclkEikltVqNRqPBxMQEv/zUcZ49NcUPPlji1fkKS5s1pBRIIQiUxjENTk4V+FvnZzk+Edmwms3mYDxiY2MD27ZJpVIUCgU2NzcJw5CtrS2UUkgpSSaT2LY9uNi4e2xBdf4YGv8V8NHqo+yH0pTj/xMXDh/ng8XfwbJsut0uzWaTfH53RVA6nWZra+u+93lnm8eQIZ+WicNjXHrlCrGkQ+AF0S9bIaK6S8McWI1tx6JT75AtpVHA6IGRaJe63cOwDGobNTYWtsiW0nSbHcZmR/c8Vq6UZfHyMmEQYpgGzWqLS69eZeNWZCnMj+c49fQx8qM5AE48dRQnYXPlzRsEfogUMHNyihNPHhkuBn4CGIbB6IERqms1MsU0vuuDEAhAKxXZ4ftIy6C73SSRSSCFYHx2jK3lbYQhkIbB1nIFO2aTL2fRWg+EhjtJZRNcf/sWz/7q0wBsLm1z6dUr1DebCAETR8Y4/sQRkpkEUkoe/+qjzL1+jYUPF1EaTNPg5NNHdy0+hzw8olYRC6/nYcds3I6HaRkIKRFSYNm3L8alIXE7Lk4ihuVYlCYKbK9WMUyJYUg2bm2SKaYpjGa5Zcl9R2ZM22JxbpnD5w6itWZxbpkrb1yn23YxDMmBU1McvXA4GgtLOHzhVx7n4stXWJ/fRPTbUS589RxTRyce5tM0ZMjPJFpV0cENCBchqIJaBGMi2rTTHZBTUb6B/zZYJxFGGa3TENxCizhYj/YDF+8tAghpos0JMI+DzEUVlGEFzJlIzAiugX+N29fz6Wixb97ZdiXQqjn4MyKNEPsveXVwAzB3Cw3QD6JM9sdKjCh3Qh7efYxRBD8YiBpRxbjY5ajQqh2JJn3XiNYK1GaUZYFGyHzfTfH5vT4aig1DPhE7LoaNjQ06nQ4bGxvk8/lBnoFlRW/WnZGGlZUVZmZmyKeTfPn0BP/eLz3Jyuoa9a4PQpKKWWQSe9W+eDxOtVrl7NmzjI2NDeo5bdumUqnsCmjUWg+cD7Ozs0C0m7e5ucl7771Hwvg+Bwv/Eik+WXCkFC7FzGVOTf0+l1f/Y2zbplar7REbDMMglUqxsbFBu93eVY2509Cx0+Zx93O448Qol8t7sjGGDLkXU8fGmb+4SHW9Tjzt9PunNUJCaapAt9klDBWV1Sqe67OxuM3kkTFyI1nS+RRr8+tIKTEdizPPn2Rstsxr334LFaqBY2KHMAj6iw1Bu97mxT95FWlICuPR+6DT6PLin77Ks3/nKfKjOaSUHD43y8FHZnC7HqZtYjv3biQY8uA5/vhhXvzT12hWWjhxe3BBZDs2sZRDt93D73o0N5t0Wj16HY/CRJ78WI5YymH5+hqpQgrLsXjy6+fRKF79f9+8Y1fpNoEf4MSjf++NxS1e+fM3SGaTlCYLKKVZv7XF1nKF5379aeLJGLZjcebZk5x48gi+G+DE7V272UMeLoZhcPrnTvDGX7xDupgmlUtEAoIhojrTuEWv3aPT7NFtdOg0e7hdjwOnpihNFnDiNqs310mXMiSzcZ79tadYvrrCW9+5uO/jKaUw+58P19+d54MXL5MrZyllk4RByI33FqhtNnj6GxcwDINkNsmTv/QYbtclDBSxpLPnM2vIkCE/fpT/Ifhvge5fs/tvRZln/qVojMA4Ea0qRTpaoPuX0CKJkEm0HIlaGYyDoDsIuXdjYxciBaqKdM6jZQbd+7eRMyBcgHC5L0Kk+tc+reg/ZqIsNnrRKIduo0XfiSAstHUKYR7dKyoEN6KmibtPAYE2DkDwAZCJsiLMu8QG1QbjMAQ30EEP8AGJluNRPaiwQdfA/lKUVxFuob0fRuMgfVuHJgQRR9tPIc3Pp2g6FBuGfGx2XAxKKeLx+KCBolqt0mw2yWQy5HK5QWuDZVm73AA7bgMVBowX0vedpbo746BQKLC4uMj8/DymaQ6yEoBBO0QYhjSbTVKpFKurq4RhyNSEycHc739ioWFwHtKjlJmj1HyZzeYze8YlPM9Da43jOGxsbGCa5iAscmNjg9XVVcbGxjh79iy2be95DlOpFGEYsrS0xMrKyscKthwyxIlHO3xX3rjO4twqlmPhdlye/NpjrFxbZ/7iIrXNOkIIkv20eKWiXcPCWD5qoZguksmnONQP8Tv+5FEuvzLH6MHdFwGV1TpPfO1RpJTceH8BrfWuWfpkNkqrv/zaVZ755ScGXzdMY5ApMeQnS7aU4ed+9QnmXr/G+q1NQl+RyMa58EvnWLqyyvz7C3QaHQzTJJ6MEU/FaFXbrF5fI5VPcva5UyQzcY6cP8TEoVGUUhTGc9S3m2RLmcHjKKXpNLqcef4UWms+fHmOVD41mLGXUpAbybC9UmHx8jLHLty+cLNsa9eu+ZCfHJNHxjF/2eTSq1dRStNr9xg7WKZ8YITlKyvc+nAJtxs5H8Iw+jzYWNyK2ikycZ76xuNIKXjq6+cpjudx4haGKXG7Lk789uaC70XVdcfOH8Lrecy9dpXSZGEgNhmmQWmywObiFtvLFcozt3OR7ryfIUOGPFiUPw/em1GVIy3ofgf0ZrTo11Y/yPEaUAXjYNTOIOTADSCEgUZHY8z3QKt2FKKIHzkljHEAhFFC2+eh80eRqCETRDkJGvAABfJYPzjS6Qc8umA8MXAzaO2B9zY6XAXn+bsEh4B95zmIqkG1PtQXL3poraI8B93tn6sTuTTUfNSeIeKAHZ1DcBmMWYh/DWlOolUF3fsrECmEsTvvTuseuN9F8WWkOf4J/3U++wzFhiEfC8/zmJubw7IspJRsbW1x8eJFlFKDasd2u40QglarNdilv9MNsCMg2LZNGIa7sg92ajZrtRphGCKEIJVKDXb+bdumVCqxtLSEZVm4rovjOIPaTSEE5XIZz/MGgsTo6CgTqX/OvUJZrs97/Pe/V+X/+OMmrbYmlRT8vV9P85/9ozyHD952GJiGx4nJf83i28cQMoXWmjAM6Xa7KKUQQpDNZsnn8zSbTer1OkEQ4DgOiUQC0zSxLGvXc3ing8E0TdLp9OD7+wVbDhlyN/FUnHMvnOb0sydxuy6XXrnK8tU1ihN5lq+sUp4uMXpghJHpItsrVWIJh1atzYkno0C/6nqd4185N7i/F37zGRYvL7FyfY1sKY1G09hsUpos8PQ3LgCwfHWVdGFvaF8ym2BruYrv+cMF42eU3EiWp75+Ad/zeeG3erzzvYvUNupki2liSZvsSIbJI2MkMgkalSa2beJ2Pc5+8RFCHsasEwAAIABJREFUP8Ttukwfj3ZdpJR8/Xd+kT/8Z3/K+q1N0oUUgRvQqDQ4/sQRjj9xhF7HpVVtU5zYa5dN5VOsXFvbJTYM+WwxemAkCpr1Auqb/z97bxYkx33feX7+edbdVX2ju9GNGyAAgiAJipR4SKIOW2uPD2ms2Fla4b0Ylmcf7LBn98UP+zTh3dhY2bGOnbBH440J21xP0JYlrS8dFGnrIEWKJEgQV+M+Gn3X0XVXXv99+FclutAHukGQIID8RDBIVGdlZVUnC/n/5fdY4p2XT1Cr1MlfK5DMJhgY72fb/q0EQUCz1kRKSTwZ58CTe6mV6thJm/52Rksqm+KzX3mG7/w/rxBL2iQycRqVJo1Kgye/9DEGxvrITxcIAlZVtVhxi7nLC13DhoiIiA8HKQMV2Kj1qUaG1svgz6hMg2C+vZUOwgN8ld0gdinlgT+zTA0gQAoQMaRsIdoZBlK2wJ1sN1NogKYW8rJI4GxFmPsR+qhSR5AErwJyUS3staSycWCqSkrnVbX4tx7usk2oMMstqnLTPYWwDl1/gyKjrB9i9Rt9wphACltlSMgFNeMQaTCPKNWDSIHxBAQV8KdBVtS+xKhq9dDbFovWz0AkVsl9ACFiSC0H7htI/V+pysx7iGjYELEhCoUCQRAgpeTChQvk83mA8C6+lJJGo0EsFsM0TQqFAgMDA2FoI1wPSexYItJptWhpNptMT0+Hg4tOjaXneRw/fjy821+pVNixYwfVapXz58/TbDYxDCNUNeTz+bASc3R0lFxPk7hxDE2sbML4px/U+PLzM7iupJNZWalK/uyFMn/+YoUXv76FL3zm+heCpsHO0RPMVz5DtVoNqz5d12Vubi4cDuRyuRU2i0qlQqFQAAjf42qsFWwZEbEeSkGQ4NHPPcSeIzuZ/Nk5rLjF1r0jofonP1riyokruC2X+St5Brf289jPHw6r5qSUSAm/8PxnmXzzPFdOTiE0jU/914d46NMHSbWD+nRdRwYBN94FUH/5suHk54g7h2mZmL0mT3/xcUoLZd78zlGGdw4yONavZJ5SMnNhjulzszRqLeYuzTM4McDHf+mxMLDR932S2QT/6rd+jsmfnWX24jyZgTTP/NoTHHxqH4Zp4Ll++7ySK84LGUh04966mLoXEUJg2SYDY/08+9xTFOeWaNUdHvrUAVJZ9fej7/lcOX2N+SuLFGaL5KeLDG0b4PCnDoSDA6flMv7AGP/V859l8s1zlOZKjOwe5tHPHmL3IzvaKfiiLYFeiTpfImtNRMSNSOm1KxkbgK7qJbXVKxhvmaDYlv1LaP2knWFgA+1rWdlQDRFBCkSgMhaCMui9IH01rBBuW3nwllIn+KeR5gG1H/eYaqRoL8qRAWi+qpd030HiqaBGrRdh7kOa29Vz/AoEGshrIF1VfenPgD0AIrv6exH94J1Gmg9cVzcY+9SQgpuoimO/jDC2AxIhNAL3MsgWQm9f82sZ9c8yZFBAupNg7oMgv0LR0HVoIo4MZtUAZ53t7kaiYcNdzofl/5+fn8c0TaampsJ6yU4+g6Zp2LZNo9GgXC6TSCTC4UPHUuF5HnNzcxiGQaPRYHZ2lt7eXjIZVW3Z2QcolUNHmRAEQXi333EcYrEYuq7T29vL3NwclUolVBBomkaz2cTzPKSUpIwfrfpezl9y+PLzM9QbKy9sXA9cT/Ll52d45+XxUOGgiRZb+3/CjgO/3/W5Hjt2jHh8fal4xz7S+e+NbBsNGyJuhXQuRf9YH7MX5rt8zH3DWXIDGabOTHPoU/vZ8+jOMKyxXmnw1vffpTi31F5sBuz/xF4e/dxDK2wQEwfGOPOz8ytaJcr5CqO7hruaBiI+2gghyA320Lslh5y5PigSQjCyc5jB8X6mz8/y5K98jNFdW8KfF2aLvPW9YzRqDYTQ0A2Dx3/hUQ49s7/r9x9LqDvblWItbDjpUClWOfTMAx/em4143+i6Tv9IL7nBDPaynCXd0Nl+cJwtO4aYv7LAs//mqS6b1ZXTUxz/8Wl8Tw390z1JHvnMIfY8uqNrCJUdyGDahqqxXJbxIqXEabkMbx/8EN5lRMTdQ+CeV0GMsoWa9gNSIo3tCOvRUDnw/nHUQMG7rBb1Ig2iAdIHOo0NtgqIlE210A8KoKXV40Ee3BMqV0GfAD2u1A+tV4AeNaAIBw1uu9pyV1tJnFCDBW0rSK8dTnlNvXYwr2wZIt1+rQTog4AE9yjSOowQ3Y1GQhhI6SvlhK6UUsIYRXpZZFBUYY03IIMiaD0IY6z9ndX+3vLPK1XDeogs+JdUhsNGbsZIgQyq3GtZkdGV4V3Mh+n/dxwH13WRUtJqtcJsgnq9roLm2goDz/PCoUetVkPXddLpNOfPn8f3fXbs2IFt25imyaVLl7h69Sq2bZPNZvF9H8dxEEIwNjYW2iw6d/ullFy6dAkhBIZhYFlWOGAolUpkMplwX7FYDD14E024K97L1/6kiOuufgelg+tK/uhPS/zxH1y/wImZM2hm9zeA4zikUut/2SzPn9jMthERt8LAaC9SShX2qF8fOEggkYmzbf/WcNAQBAFv/OPbNOstBsb6wm3LixXe+Ke3eeZff7xraDGxf4ypszMsThfI9KYQmkYlX8WwdPYeiSTxdyNje0aYOjO9YiDguT59W3KM7BwOF4WNaoOf/v1bxJIxBsZUtaWUkmtnZtANnYc+eaBrHwc+sY8ff/N1SnNLJHNJAj+gnK+QG+phdPe950u9Hxjfv5Vzb19YYY9p1Vrsfnh716BhcbrA0R8cD2twAXw/aDfpWEw8sDXc1jANHvrkAd787jvYCZtEJoHbcqkUqozvHwvbbiIiIiBwT4HzpqprXNbsoCwPV1SdY+xZZR943xhKPYGmVAtCVwt88upnaMrO4C+oYQMa4ChFhDTA/QfAV1kOQgJJsD8BrTPgvqLUBkJDXaUYoO8Bfx7Z+KYKhJQ12pMU9br6BGgjoNmg7W63YMSBOPiuan6QEtyTSOtRBDcs8iVAEP5RCBPsTyGdH6vKzFC14ahBjtaLsJ9e+VnKBtwYNnkDQmjIAPX+11BurXJw9xyRjvEuZbn/P51OYxhGuAhPp9OYphlWUt4OLMuiWCyG+QxCCCzLQggRti3EYrEws0FKSbPZpFwuMzk5yeLiYqhq8H2fZDLJ3r17MU2TarVKrVYjCAL6+vqYmJgIVQ6g7vZPT0+HTQ/xeBzHcdA0jVQqRX9/P729vWiaptKqk0kMwyAVm131vbzwjUponVgL14O//Eal6zEhDCXRuuFz8f2VNo3ldOwjm9k2IuJWSfYk2fXoDham8tTbrRS1cp3FqTwPPLGHeOq6WiE/XaRcqHaF/AFk+tOU81UKM8Wux+24zZO//Bj7PrYLz/Fo1VrsODTO0196gmRPFGx6N9I/1tu+K71Iq97Cbw8EqoUqDz6zv2vYdO3cLEEgw8BHUEqI3pFerp66RqPWXS2c6UvzyV/7OGP7RmjWmgSez4FP7OXxX3g0yva4S9l2YCuJTJz8dAHX8fBcn+LcEgjYc2RX17bn37lIIhMPBw0Auq6RHezh7FsXCIKga/uRncM89cXH6duSo16uY1g6j3zuEA99cn9k0YqIaCODGjhHQRtesQAWQkPogyALSO/8Ley7TuCeJmh8n6DxXYLmj5DeFHhTyj4hhbI5iE5IY2eNEWu3Q9TU4t8vg3dV3f0PPBCDSgHhvquqLyVg7WjXWybB2Abmg0qhUPtDqP/n9nZt+waB+rcsg3cCnO+rnAd89ZygBX6pPbSIqRBJWYWgjJSBUjOghuNqYHKD4kFLIOzPImKfAX20nQUxiog9i4h9ftWcBVWL2Vr/85S+OiatM5wP1t0eCDMe7iUiZcNdSidD4Xb7/5fbMhqNBq2W+h+p1WoxPT3NwMBA6OvVNI10Ok2lUsH3lT83l8vheR61Wo1qtRoOP3p7exFCkM/nKRaLjIyMEIvFSCQSxONx+vv7u7IOOoGRhUKBarVKsVgkkUgQBAFBENBoNLoCJnVdDxUXnYtjTaz+P3W1trHJYbV64/M1VK3NdW7Mn1iNRqPB2NgYwKa2jYi4VfY9toue/gzn37lIJV8h05fm4JP7GN7WLUWuLdXQtNUv4oUQ1MoN+ke7H7fjNrsf3sHuh3d8UIcf8SGi6zqPfu4hrk5e48K7l6nkKwyM9bHz4e3kBrvrwIpzJWKrVBVrmpLwNioN4slY18+SPUkefOoBHnwqsk3cC8QSNp/45Y9x6cRVrpy8ShBIxh8YZfuD42GmR4fi3FKY7bAcO25RLVTxHA8r1n0N0zuco3d4pZQ5IiJCIf3LIARiPa296FV39o0962+3jMC9DM5rbZeACd7F9g02H/w5YAFl12iA3g/awLK8CB9ETg0jgoIaNujDgAPmHnU8Wvs4gjx4Z9rBkSZolnpe65/AeV09Z/0jbX8Q8+C8AsZjKuSRBWBYHYvU24GRP1P1k0ikSKhjNLYhtJXX4UJooA8h9JvUcna2N3cjm/8MZNbeKCiBuQtN7yHQx5T1Q6w+TJBBWYVbinvv+y8aNtylzM/P33b//3JbRqdxonMnXgiBpmlhW4Su62HTQk9PD41Gg2azGVoqgiBgaGgIx3FUWnWzSTweJx6P47ou09PTjI+Ph3LupaWlcNjQCYx0HIdKpRIOGIIgoNVqcenSJZrNJrZtd+U1eJ6HpmkUCgWKxSIPbTWIrTKLSSUFlerNBw6p1A3CH+mu6OLt7e0Nj3W1wU9HgdHbq75cNrNtRMStIoRgZMcQIzvW/0vTTtgEwRr/L0iJHY9UNvcDuqGz7cA42w6Mr7tdMpNg4WqeZE9ixc+CQK5YOEbcm8QSNvse28W+x3atu10iE8dpusRT3Ysdz/XQTR3dvMeMyRERHwb+HLC+JVcICykLban/zQMjA28WnB+pO/ACcN5Ri3W9ffPLL6J+4KoFszTAyLYXzhWVoSBiQAnQIXYEVUN5QdVfiiqIrarBQmTBnwd9XNkf/Bq43wLvLDcfNKz4MMB7HfS9bbVCA1pvElo59BEwtqu8hKAC/knQe5GyiRCxm+z7JmhDoOXWznpoD2GEsRsAYT2CbL2E9POg5cLGCSklyBIQIOxP3ZMqrshGcZfiOE64UF8LXdc3bKNYbsuIx+PMzs5imiapVIpUKoVlWaGyQNM0qtVqOEjwPA/Lsti2bRuZTAYhBL7vk81m0TQNTdOoVCosLCzgOA6maRIEAZVKhWw2i+d5eJ7yNXiex/T0NKCGH50sCF3XKZfLFItFWq1WmB3RaDQoFAqUSqXQRtLf30+1WmVmYfWarOe+lOZmOXamAb/+pRsmnyLW5Y0DpSDZu3cvrutSqVTCcMqOMsN1Xfbu3RvaKDa6bUTEh0H/aC+mbdCsd0sBm7UWVswKq+siIkDlO3iOj+d228HKixUGRvtWvYsdcf+y49AE5XxlxUCzNLfE9kMTN72GiYiIWIuNKHQ3sWh13wGRUbYMb0plL2gZtUgXAowJoAXGLhDjqgHCn1Ovoe9SFghqKkvB3A36FjVIEDGVsxDU2/kLQXufulI4aFvBP6uUDpseNHSQ4J9RH4m2RQ1M5GK7RaOoqiiDtiXUfkY1ZLRev8XXuo4QBsJ+BoSN9GeQQQ0pPaRsIoM5ZSmxP4VoN1QILYWwPwvGCATzSH8W6c+pSk2tr23XuDezaSJlw11Kx/+/3EpwI5vx/y+3ZRSLRaSUXfs2TZNEIhFmNQRBQK1Ww7ZtMpkMyWQSx3FYXFxE0zRGR0exLCvMkugcb6cS07IsSqUSW7duZXFxMXydjpKhY8uA65YKz/NU9V772DpKho6to9VqEYvFCIKATCbDwtIeHPcCltn9Bfa7X83x5y9WcL21v6xNU/A7v7n8f3oB5qOrbptMJjl48GCX/aRTjXljK8hmto2I+KAxLZOPfeER3vjHt6gWq5iWieu4GKbB47/wSNQuEdFFpi/NoU/u570fnVQZOYaO23JJZhM89OkDN99BxH3FyM5hdjxU4tLxq+iGjqYJnJbL0MQAuw5vu9OHFxFxd6IPK7XAOuoGKVuoHIWVKrQV2wYlCAoIfVjVTPrTbVvC8tfsAT+uKi1jB8EbUHJ/4QAeeNdADEHsSfAm1XOEDRgq60FLqkW/rLXDJQ010ND7wTum9nED5y85fO1PirzwjQrVmiSVFDz3pTS/+9Vc2BR3nQD8y2A9qFQW+jaV76DF1OuYB9TnJWwV6hhMIYPS+17cCy0FsZ9DejPqfcuyeg3zMEKfQGg3ZkOkEPaTSPOw2hZApG9/XelHjOhK8i5ls1kBN2O5LWNpaWnVRW88Hg+VCv39qpO9v7+fYrEY3pkfGxvDdd0w4DGRSFCpVLAsC13X8X2fRqMRDicMwyCTybC0tMSpU6colUqYpkmr1QoHCx17QcfKIaUkCAIMw8B1XTRNwzTNcLtOC8bc0oNo2ndXvI+d2yxe/PoWvvz8DK4ru8IiTUMNGl78+pbuLzMRRyT/+zU/P8uyGB4e3pBlZTPbRkR80PRtyfHsf/M0s5cWqJZqpHNJhiYGsOO3qzYr4l5i24GtDIz1MntpnmbdITeUZXBrXzSYiliBpmk8+NQDjO8bZe7yIoHvM7C1n97hbFfwaERExMYR+gTSeQcpPRVcvhpBAaxHQ6n+usgmoQpCNoGgHbS4HB2MrSr8MSgodYKmg7EP/AaYOpiHUIL5ZYGO2gAE10CmAautZkgD7drMxrdYTaXxTz+orbhGr1Qlf/ZCmT9/scKLX9/CFz5zo5KuAIHbDq2U7UwIG7xz4M9eD3PUB0EfRXpXENb7VxIIYSLMcTDXtyF2PUdLAvePEjC6OrhL2WxWwM1YXuHoeR6x2EovU2fBPzExQblcZn5+HtM0GRsbY3BwkGvXrmEYBufPn2dubg4pJUKIsM7SNE0Mw6BWqxGPx0NrxMLCAolEgmazSbVaDZ+TTqfDYUVnyNFRO3TUErVaLbRtaJqG67qhrSObHeL8zGfYMfw9TKN7avqFzyR55+Vx/uhPS/zlNypUqwGplMavfynN7/xm9oapqaaqdqyPbfC3ExFxd2HHbSYeiIJJIzZGsifJzoe23+nDiLgLEEKQHeghO9Bz840jIiJuitASSOsIOD9Fav0Icf3GgJQByAXQBxHGRuuoDTZmy9DA2K+qJb2L7RaJ7WCNQutllQ3hF8FfBO9SuxbSVPkOck4pHACwlPogaIF3FDV4uM75Sw5ffn6GemPlMbkeuJ7ky8/P8M7L4ysVDv7p9nFuU6GT/jGlxtCG2o0QEoIl1ZQhQZr7blM9aMR6RMOGu5SO/39ycpJWqxUu3jvKAU3TNuX/X27L6AQ83uin7DzWUSMkk0kOHToU/vzChQvMzs7ieR6+72PbdjhwyOfz4cAA1OAik8lw6dKl8PWy2Syu6yKEoFQq4XkeCwsLYViKZVk4jhPus7MfXdfxPC/MlOgcG8C/vLmbwWdfpydVQNO6v7h2brP44z8Y5I//oDuhf5VPB5H9o3sytOVO0QkenZ1dvZ404t6m83u/WRVsh+h8ub/ZzPkSnSsRm/1+iYhYjyWnzlyzhCsDkrrFcDxHTL+z1b2auZsAC9y3kbKdRyABBBg7ENbDCLHBY9RyICykdNohj1o78PHGTBVfZQtoKaQ+BNYTaOYOVS0J4J6H4Gq7ArMBtAMbg5n2oMFU+/AuodQTQ0opcQNf+5Mirrv+8MN1JX/0p6Ubrt+lUjWY+9QxeMdUsLtItoMphfp8REa9vjeJbP0YEXt2Y59TxC0TDRtuwvIqyI6KYHBw8CPhr7+d/v/ltoyenh7y+fyKtgvHcejr6wNWWjQcx2FhYQHLssjlciwsLIQd2p0wyyAIEEKE1ZiGYeD7PplMBtNUX4qpVIpKpUIqlaJWq9FoNLBtGyEEQghs2w4HEr7vY5omtm2jaRo9PT309vaSzWbJ5/PtSk743hu/xi89/efYZmPFwOHmxBDZ/wNhRHfxbicLCwsAPPfcc3f4SCLuJAsLC0xMTGxoO4jOl/udjZwv0bkS0WGj3y8REavR9B1+tnieueYSmtDQhcCTAXCBfT1jPJAZQduITeEDQjMnkMYYBItt+4MGej9CrN9UdyNC6EjzADhvqYBFfRT8q6o1okNQAZFVgwbpgDAQxlj7+RoSC/xJ0EZBF8qG4U8rywUxEH673WK03UKRAvcYq4VYvvCNSpe9eTVcD/7yG5WVNwtlGbQsuFfVIEPEUcGTywYnUqo/a1lwfkZgHkbTozDsD5Jo2LAOy6sg4/E4qVQK3/eZmppienqavXv3hnfQ7xS3y/+/3JaRTqcpFAp4nheGRHayEdLp9KoWjUKhQCqVotlsous6vb29LC4uUi6X0XUdTdNotVq4rksqlWLnzp3MzMxQr9fDAQaoXIhqtRo+pzOcME0T3/fDxomOzcO2bRqNBlJKTNMkm82STqcpFosUi0Usy6JSN/nO6/8jzz76X0jGihi6u4FPxARhI7JfQ9ifel+fbcRKDh48yAsvvMDAwECUSH4f4vs+CwsLHDx4cEPbR+fL/c1mzpfoXInY7PdLRMSNtHyXH82dpua3GIp3W4B8GXCydBXX9zjcu+3OHGAbIXTQ16+43tB+jL0qKNI7pxbh/pTKOSAGIlBBk+YDqs4xKIL1dGg/kDIAGoAFSDVo0IcgqAJlNQAIGoAH2hhKVXB1ma2im2ptYzcFq9VglUddNcxovQaBB1o7wFJrW8ODAGS+PXBYUEMVXiCwP67eYzCvsh20DMLYAdqAGqbIprKH4KsASG1AffYRGyIaNqzB8irI5QoBwzDCBffk5CQHDx684wqH28FyW4bjOMTjca5evYrruui6TjKZZGJiYk2Lxvz8PP39/UxPT+O6LpZlkUwmaTQa1Ov1UOWg6zojIyNUq1UWFxfDbTp5EZ1BRaFQwLZtms1m+Jr1ej08VsdxyOVyGIZBtVoNKzs7gZmJRIJqtRraLCwry3ff+C12jvyIg9t/gqZJDN3hRmdEIG0goNR4lLna8/TJ3aRSVarV6kdS3XK3EovFOHLkyJ0+jIg7yGbuOEbnS8RGz5foXImAzX2/RETcyOXaAmWvzmBsZdaILjQGYz2crcywLTVI1rreOBDIgLLbxJc+tm6SMlbmn30UEUJDmh+DwAfnZfDzIIvKDiH6wNijVApaCuxPoxmj158sS6gAyX3gnwfiKMtEtb2BpRb7Ig1GH2gJcM+osMhVSCUFlerNBw6p1CqqEmGCP6NUFLKk4iBEAphXxx6UUXaQIWWtAFXHWf8bpb4wH1GVn/4M0rsAWj9SS4N3GTVIUf9CWEjzYYSxI7JYb4Bo2LAGy6sgV8OyLFqtFoVCIVQVfJQtFxshmUyyfft23nnnHZaWlshkMmEFpZSSmZkZDh06FNZaLqcTMDkyMsL09DSNRoNarYbnedimDQI0XcO27dCeIYQIBwj1eh3f99F1nUQiQW9vL47j4Ps+9XodKSW2bYe5EpqmUalUME0T0zTp6ekhl8vRbDaZm5tTr9tuxDBNk3q9Tr0O1doRzk0/yfjQeQaz5+lNX8bQm5hWksJSP/Ol7VjpX8SwBkHzuXDhAnNzcwwODpLNZj+S6paIiIiIiIiIiIj3TyADzpRnyFprX9tpQmBqBpdrC2StCQIZcKm2wOTSNHXfaa9JJQN2D/uzY/TbazfHfWTwTkBwSdW8W+279tIDWVBqBn0MYT+9suFCeoBAGFuRWkotzINF8GZRdoWedt1lSwVICltVXgaz3BgOCfDcl9L82Qvlda0UpgG//qXVPtN2PafIqFpOkWgPFVrg11SWgzYCmtZupxDgXwFjQA0d/EugP4YQcSRpaL2qHrc+gdCuZ2BI6YDzGpIWwty/iQ/5/iQaNqzB8irItYjH48zPzzM8PHxXWC5uhuM4XLx4kf7+fkZGRlb9ebFYZHR0dMXPOgGTsViMhEjx8v/7E47/82kq83VkIEGCnbHIjqfY+cxWJh4eQQgRDiQSiQSmaSKlpFKpqATrbBYhBOPj42SzWTzPw/M8lpaWaDQatFqqxuaZZ55hfHycYrHI0aNHkVISi8UYGxujWCySyai+4FqtRr1eJ51OM50/wHT+ANVqNRwWaZqG53n06RY5W00qS6UStm1TLpfD47lX1S0REREREREREfczTuDRCjx6tMS62yUNi0KripSSd4qXOFeZpddKMWiqa04pJVWvwSuzx3lyYC8jiY9uLoD0F8F9D7Th7mGCsIAEUhtRloMgD/pA95NF2z4BCC0HVg7pTYN7FrRBpY7wpyAoATEILisFhSyishS6Bw6/+9Ucf/5iBddbW91gmoLf+c0bayutdtilpmovfUDkQLOUbcK/otQLYnnNpwAtroIxBUq9EZRA6wV/Xh2bAKXSyF1/y8JCakPgHEXqWxHaXTBMuoNEw4Y1WF4FuRa6rtNoNO4Zy8WtqDk6DA4Ocvq9M/x///tLnPrJWWQg8d3uL5BW2WHueIH82SXejp1i35fGyUyoBomOEkTTtHBwMT09TRAE7Nmzh2w2S6VSoVAohMGQlmWFTRaWZWGaJiMjI6GVotls8s4774T77uROOI5DLBYLsyeSySSVSiUMmlxaWiKXy1GpVJBSEo/HaTQaVCoVcrnchj6PiIiIiIiIiIiIu42NyeJlO55gul7gbHmW4XgWbZmkXghB2oxj6yav58/xBfswMf2juQaQ3lmVU7ZG4KUKgRTI5neRWvs6WBtAGDuRIgdaDhnUEFrnpqqnFA0yr1QOgQeaqUInZQvkIiq4MeC6N0Gxc5vFi1/fwpefn8F1ZZfCwTTUoOHFr29ZWXuJgPhzCM1EyhY0nHYTRo7rAw1PvW7gqdcUCTWgCLHAX1Dv0b+qmiykD94MWLnuVxM6Eh3pXURYh4hYm2jYsAbLqyDXwvd9LMt6X4v0DwtfBryxeI438ud4t3iZitvA0HR2poZ4pHc7nx5jktzzAAAgAElEQVQ+cFM1h+d5NJtN3nzzTYaHh7tsIrOTi/yfX/qPuC1vxZBhxX5aPl7L59hfnGfksT52/vwoS0tLmKZJJpNB07SwwrO/v59sNothGCQSCQqFAolEgmw2i6ZpuK7LuXPnQstFInF9Eh2Lxdi/fz8nT57EcZww8LKjptA0jf3795PP58PfXWcYAbC0tBQ+blkWpVKpa9gA3eqWiIiIiIiIiIiIuxdbM8iYcRqeQ9xYezhQ9VscTA0wWZmhx0p0DRqWY2kGgQy4Vi+wM337rhUDGRBIiSbE+2/F8Ke62yduQPrXVM6CbELs03TsB9I7C+ZuMA6A80OktFTlpnQBo52fINo1mjbIitqH0EGmgApqANDNFz6T5J2Xx/mjPy3xl9+oUK0GpFIav/6lNL/zm9lVBg0GGAdDq4MQNjL+NDT/BYJrILW2JcQHOQ96Rh1zULmh4lNDDSZcdZxaVv03Kys61eZp9R6Jhg3rEQ0b1mB5FeRadOofN2u5uB1sNB9CSsnfXn2DPz37fZzAo+G7yGUTxPPVOX44f4qvnf4HDhpD/HdDnyC7ymnRarWYmpoiCAKCIOiyibz+vTf5+r/9L7TqrU29h8CVTP+sgEDjsef6kFJSKBTo6enBsiwSiQSpVArDMPA8j6mpKQzD6BoAdVoqTNPk8uXL7N69u+s1MpkMhw8fZm5ujnPnztFqtdA0jdHRUYaGhojFYszPz4fVm0EQhPv3PC9svVg+hFhOR90SERERERERERHx0afpu7R8F13TSOp2V8ifEIJ9mRFeWzxLTDdXDQB0A5VnNmD38F7pKoOxzLqvlzJiTN2mYUPVbXKhOseF6jy+9NGFxvbUEDtSg6TNzdVeXkeylqJD+gvgnQHRA0JHiHbopbBVE4V7FkwLrCfAebW9/VXwLigLBT7ItPq38Nuv1Xm9TgBnnuXqBlAKhz/+g8GV9ZarIXpAG0LKFkKovDYhksj458G7Bu6Jto3DBGMX2I8BaXBfbUtUOu/dawdKLsdXz1v3s4tYj/ty2LCRhfryKsjVFAvL6x+npqY2bLm4HWw0H6LQqvLv3v4LzlVnafpr1z02A/Wzd51p/uepb/JbA0/zSHI8/Pnyhb4QoquC0tIs/vPv/s2mBw0dAjdg+meLFB4rs+Nj4zSbTeLxOENDQ0xPT5PP5zl37hzNZhPf91coC4IgaLdNWAghWFpaor+/v2ubWCzGxMQEmUyG+fl5LMvqSqrWdT3cj+M4YRVnx6Kx/Oc30lG3REREREREREREfHRZcupMVqa5Wssriz6SHjPBvswIY4m+cLAwmuhlIjnAldoCfXYaU7t+/dfwHJbcOo/17SRumBsyXWhC4MvVqho3x1yjxKsLZ1SumZVAFxq+DLhYned8ZZZPDOxlOL62QmHtA+xTVZWi+warJAD/ogpWxAW6hypCaCq7wD0F8Z8DEVeBiloPahGeAT0GflVlNIgUSslgtbMeNJWXQAqCKyhbxWaJQfyL4ByD1utIYwL0QYSIIzDAmABjAmlsB+8S2E8gNDXkkKJPqS1Esl2H6bUzKUwVZCkdNTDRt67+0kENzL23cMz3F+9Td3P3UavVOH78OFNTU+i6TiqVQtd1pqamOH78OLVaDbheBem6LpVKBc/zkFLieR6VSgXXdcP6x47lYj1u16J0eT5EOp0OBwCdfAjTNJmcnGSuWuC/fe0/cLp8bd1BQ9cxImlKj/974Ye8Vr0QPt7JLjAMA8dxyGavf5F962vfo1lbfdBQl1VOy7d5RX6Ll+Tf8Ir8Fqfl29RltWs73w149T+9S2+2j7GxMWzbDl8T1LCg1WrRarVYWFjoUhg4jkM6naZYLOK6LqdPn+bixYsUi0U8r1ualU6n8TxvRVBnNpsNbRZCiFDN0tPTE77Wje+7Q6PRYHBwA1PXiIiIiIiIiIiIO8Jis8wPZt9jrlGi304zEMswFOtBSsmrC2d4t3g5vO7UhMaRvh0cyo5TdZvMN8vMN8vMNZcQQvDUwD62pQYxNQND03GD9dcAdc8ht067xUaoeS1eXTxDyozRZ6fQ29YJXWj02SkyZpzXFs5Q9Zqb3rcw94Esr/yBrLXrL20I6mCsXHQLoSmRQv37ICXCfhTsj4OxA3QTSIGRU/vAVqGNWCjFgwBZBdEL+l5UYORG0YE4WJ9Tdgg08GdVEGTrDaR3QSkvOmhpNVBx3kO2foJ03m6/r5rKcJAl0LYgRBKBAH28Xc9pqPaMGz8a6YPwEMb2TRzz/cl9pWzYbJBjMpnk4MGDoQqi0WhgWRZjY2NdKojNWC7eLxvJh2g0m/ze23/BYquMdwuTVEf6/KfFVxmzcmy1cmF2QSdgsfM+G9UmP/3bt/BaK/1Wi3KGY/wUSRDaNnw8rnGRaS5zSD5Bv9gSbh94Aa9/+20Ofn4PpVKJ0dFR4vE4uq6H9Zu2bRMEAYVCgYGBAYIgwPd9isUiQghSqRTVqkoGzufzFItFRkZGQitEEAQMDg7SbDY5depUGEYZj8dD5cS2bdtCG0U6naZQKNBsNrved/g5LVO3RETcDprNJsePH2dgYGBVJU3EvY3v+ywsLHDw4MHwe2stonMlIjpfIjbKZs6VexEn8Hh14QxpM7YipDFuWNi6yZnyNAOxDKPt1ghdaOztGWVnepiSU8OXAbZu0mMmQgWELjT2pLdwYmlqTSuFlBJX+mxLDaz6841ytbao2tb01SX9tm5ScZtcqS2yv2eT6w1tGPRxZHANxNB164h0lUAhKCn1g8it/nzpqYW+9Uj7AQP0YfDngCIEzfa+KmrRL+so9UBLbavZygohGxDMcT08cjWLgoZqkdgG5j6lShCWUiTIBqqVwlYVnAgwtiO9WXDfVfkSQbHt5PCBAgRLatCgb1ctFrQHCWhKqaEPceMQREoXgnkwDyO09S00EffZsOFWghwty2J4eHjdrIXNWC7eLxvJh3jDn+JSY/GWBg0dHOnzf839M//b6C+FOQe6rjMyMhIuxt/9/slVk2vrssoxfkqwSn+uRCLxOcZPeUJ+joRQ9hOv5XPiu+cYOdJPs9nEdV0Mw2B0dJS5ubkw0FHXdVzXDSsp6/V6qCoRQpBMJsNtAa5du8bo6Ciu64b7TKVSxGIxqtUqjuPQarVIp9MkEgkcx0HX9fBirKenh/n5+VC9IKUMwys1TQvVLRERt4Pjx4/z3HPP3enDiLjDvPDCCxw5cmTdbaJzJaJDdL5EbJSNnCv3ItP1Aq70yemrqws0IchYCSbL0+GwoYOh6fSvk8mwLTXAxeo8S06dHqvb7x9IyXxzie2pQbLm+1M2nK/Ordj/jfRYCS5U5jc9bBBCB/sTSOdN8C4iESBM8AtAGbTdYOxas62CYKmd57DcVKKjrBcGEEMNEDwIGuoxoStFhIi37RU6YIK2V9VVarqyPQSL6nno7cFCGuxn2zWViyAq7WOoKTUFzeu1lu4JNRjwr4D1KEIfRuKBv6iGBTIArV+9vrEDgnmkEOq55h6IfQ688+CdR4alGVINN6zHEUZ3TlzE6txXw4YPKsixY7mYnJyk1Wp13ZG/3YvSm1VyBjLgb8vHcOTqkq7mdJHZv32d/CsnCBoOWtyi79MHGP7i48RGuieWRb/O68XzDGgauVwubIXocOb1iziNlaGJVzijfF7rIAm4wln28XD4WOlahVazhWVZ5PN5Dh48GA4GDMNgZmYGwzDQNA0pJY1Gg0ajQSKhpsytViu0laTTaRqNBtVqlaWlJbZv387s7CyxWCz8PQwMXJ8yO45Ds9lkaGiIYrEYqlh27tzJQw89RLVaXVfdEhFxO+icky+88MIdazjx/ICG42JqGjF7vVCkiNvN7Owszz33XNd301p8FM4VgJbr43getmlgGdEd8w+Tu/F8abRcvCAgbpsY2n3n5L1jbOZcuRe5Vi+SuEntZNKwmW8u0fSdTVVUxnSLp4ce4PWFs8w1lzCFji40nMAnkAE7U8Mcyo2vGjS5GZzAI2Wsr0oxhEYr2Jh1+kaEMBH2x5Hmg0h/Wi3YDRPchKq5FKsvGWUn60BbZjX2zqvn61sgmFUDAhkoBQRS2ScIVE6ClgIEyCXAVU0Reh/EPo1A/R6kdwW80231Q1nZJoJZoK/dbNFSry/i6lj0bSAM8PNqQGEeQujqpqHoqC7069+D0p8BYw/CeFopHoSpWjUA9H6k+eD1oYeItT+P6Ppoo9xXw4abLdTh1oMcN2q5eL/crJLzvcY03hqDhtLPznP+33+TwPPBV8OAoO6w8J13yb90nJ2//6tkH9sZbt+SHm8Yc/yvR34xDIhcztWT11Z9nRmudDVerIZEMsPlrmGDpgsq8zX2Prw7VDAAocKhU10JMD09jWmaJBKJsCpT13VyuRxSSqrVahgC2WmrEELcVNVimiaHDq2ssEmlUlG9ZcQHTkdRMzw8fFtsV5shCCSTU/OcujpPECgN0pbeDA/vGiUZi4ZqHyYbkbnfyXMFwHE9jl2Y4eLcEhrqO33Hlj4e3L4FMxo6fKjcDedLpdHi6NlrzJUqCASGLnhgYojdIwNo2vtbhEVsnPvVQuNKL8w4WA+BwJebbxdIGTGeHT5I3qky2yjiBD4pw2Yk0XvTAcFGSeo2TuCtaaMANZBI6vb7eh2hpRDanvDPgQCct5DaltUHJsGiWtxLlXkngzr408rWoGfB1dv1k7K9jd5WNSTA2Kf+TFOFMeoTYO1VwwS/2LYwAMZoe8iwCEFZWTJEAjWkaNdS6tvbYZOOqvK0HwdspY6wHrrJm06B9546XhFbMUgQWgK08TWeHHEz7qthw80W6vD+ghw3Yrl4v9wsH+JEY4aWXJmh0JwuqkFDa5WJpx8Q+AHn//03OfAf/ocuhcPx0lVyD+VWtYk4zdWnp/4qnbkb2U7TNYYGhsOB0NLSUtg+YRgGY2NjTE1NUakoyZSUEiklzWYzHETMz8+HdotSqURfXx+NRmNdVUsn9LNQKDA1NcWOHTtWrRGNiLiXOXF5lpOXZ+nvSWHoSj2UL9f40XsX+MzDu6MFZESIlJLXTl1hcalKfyaBpgmCQHJhOk/D8XjywLY7fYgRHyFarse/vHsePwgY6EkihMDzfY6evYYMYN94FLIc8cGSNZNcdhaIG2tf0/kyQBMatnZrSyMhBP12mn577fy298PO9DDvFC+tO2xYcusczm27ra8rjL3IoATeOaToQWjqGl3Kpso/0PrBfgqa/4SUjrInCK1dJ2mpXAW5VQ0gvCtK8aDlrucs4AE9YD4EwQxqaaq3rRDtY0BHmg+ANwXuaRUoGdQIcx1kRe0fAaJftWH4hbZKgbVVGQTgz7drOqvIoAxCQxq7EMbe8L1GvD/uKw3b4ODgTVULH/V2gd7eXjRN62pkWM5kY25VTcHs376uFA3rEHg+c998o+sxASz6tVWbOazY6l94+gZnWCu2kzC0ZTDMuLixTcK2bSYmJgiCIKz7bLVauK4bWlaq1SqVSoVyucy5c+eo1+tYlhVmMdxIq9Xi8uXL5PN5DMPAMIxV20kiIu5lmo7H5NV5BrJq0ADqwimbilOut7i2uHSHjzDio0S+XGeuWKa/JxneldY0wUAuxbXFJYqV+h0+woiPElMLJRqORzYVD++MGrrOYDbFyStzOO7GblBERNwqE6l+XOmHbROrUXTq7EgNYmgrrxWllHiBj3eT1omN4suA2UaJH82f4ttTP+Pvpt7iaOEiJWfta86xRC8xzaTirr6OqbpNYprFaKLvthxjByE0hPU42J8CEUf6s0h/DvBUbkHs02haEsxHIFhQqoTlygAhlOJA74P4L6sQSb0faKhQSZEC8zAYuwBLqRYI2tWYy3aDrqwS2ijYnwF9VKkcglnAB5JAHOQieCeh9VPABS3bDnzsRhKAewa8U+r1tAH1j+gF9zyy+R01ZIl439xXyoZbDXJ0HCe0R3SeezvufN/Kfm+WD1ENVq+hzL9yIrROrIkfsPjycSb+p58LH9I1jYrbYLSnd4VNZOuBEWbOzq/YzRbGucbFda0UAsEWJroeC/yArXtHmZqawnGcVRUoQRAQi8XYvXs3S0tLnD59OmzJ0DQNIUQY4thqtTh37hwf//jHKRaLK1QtnueF9hAhBNVqlWq1ihACXddJJpOcOHGCw4cPRwqHiHuaSl3dQdBX8VDHbYP5UpVtw1HrSoSiVGugreE/FgLK9Ra59PpBZhH3D7OFCgl75d/nuq4RBJJqw6HXvK8uRyM+ZLJmkq2Jfq7WFhmMZVbYAapuE11o7Ex3K5O9wGeqnud0eZqa1wIkA3YPezJbGIr13FIOgxt4vL54jplGkaRh02MmkFJypbbI+eoch7Lj7MmMrHierZs8PfQAP5k/zVxzibQRw9QM3MCj6rWI6yZPDe5bV/lwqwihIYytYGxV6gUAzK73r5k7CPCg/teq3SH8UQsQoO9XNZfBNGCpHAd9SFkr3HfA2K2sEN7J9g676+allEo1YWxRdodmQeU86H0sezEgBVJTGQ/mVrCeUlaKG+sr/bm2kiIF3lXQYu36TwP0ESCFbP0QYr+4djBmxIa4r77dbyXIsVarMTk5SRAExOPx8I761NQU09PT7N27l2Ry8wmz72e/6+VDJBtxqFVXPCdYJchxNW7cTkow21PeG20ipS/Wee+l0zSq3Z2+4+xhmsvIVdooOgg0xulOce2bUHkLIyMjXLhwgZ6eHjzPW/E7GhsbUzJMz6Ner2PbdtcQofPlJ6WkUqnguu6q9pNKpYKUMqzTbLVaZLNZYrEYQRBQLpdxHIeBgQG2b496dCPuXQxdW3M06PkBlqmH/z1bKHN1QU37xwaybOnNhGqIiPsDU9dWbyRD/Z2ht9UOLddjaqHEbLGKZehMDOVCGX3E/YNtGXjl1W92SCnR298f1UaLK/MlCpU66bjN+FCOXGr9UO+IiI0ghODR3u1oQnCpMo9EfY9paLiBT9Kw+eTgAySN63kHLd/l1YVJFlsVslaCwVhGZYJ5DX44f5Ld6S08lJtA2+RC9GjhEvPNJYbjyxbTAnrtFL4MOFq4REK3GEv2r3huxozz2S0PMl0vcqE63w6zNHm0d4SRRC/WLVpANoMQa99808w9BMl/A41vA+2hh5ZTC31/TrVCaFvbA4eEUjUITQVHeqdBPwAiqwYQQQ3ZeT+yqmotzQfAvQrerMpq0PpQeQ+WyoEA9ZeQ8IAk+DUwJlSbhGwhhPr9KvvEFUBvKxukOi7NVtYLf0rtSx9WAw795vZ4GRSVqgNA60FoPZv8ZO9d7rsrRNM0GRgYoF6vc/bsWSYnJ8nn8wwNDXHw4MGuBb7jOExOTmKaJul0OrwDbhgG6XQa0zSZnJxc09KwFrdjv52F/6FDhzhy5AiHDh1ieHiYXenV/4fQ4hu7M3/jdq3AXVOS9dQXHycIVl5xJkSKQzyBho6g+6JSINDQOcQTYe0lgBU3eeyLDzI1NUUQBIyOjrJ7925836dareL7PmNjYxw8eJCtW7fSaDRYXFwMhweu6xIEQTg8aLVUq0U2m2VqampV+8nS0hK6rlMoFJBSYts2qVQqVDbE43FisRjvvffeTX/HjuMwOzvLsWPHePPNNzl27Bizs7ObPjciIu4EPck4Sdui3uo+XxuOS6nWYDCbwvV8fnz8Aq+euES+XCNfrvHaiUv8+PgF3JtYtD5o9u7dy969e7l69eqKn/3VX/0Ve/fu5Q//8A/X3cdrr73Gc889x+HDh3nkkUf4yle+wmuvvda1zXe+8x0WFhZu67HfjQxm08i27345lXqTluuRS8epNlq89PYZ3j43TalaZzq/xCvvnOPouWvrSpk/DKLz5cNlYjBHo+USLPu9B1IyX6pgGBqpmMVCqcr33pzk1JU5lmoNLszk+f5bk5yfzt/BI1dE58u9gSYEw7EeLN1grlnkfGWOi9V5eu0UTw7uW1Er+VbhAoVWjZQRwwl8mr6r2s7MOEOxLGcrs1yozG3qGCpugyv1xTVzHXShkbOTnFxa+3vS1AwmUgN8evgAXxh9mE8PH2RbavBDGTSshQzKSO8q0ruqGiOM7aCPI8z9CH0LIJS6QPSojAestk2ifc0hDPWYdxSsg5D+TbUPGmqooG9BxD6PsJ4Gcwd4x5RVQx8C0QdCqowH2QKaKjzSekgpLIIG2E9DUEL6i8pSIRvgqxwK0FVQpdYeNAldZT6IOLgXkO65m7z3IkHz+8jGPyKdn6h/mn9P0HwJGUQWVLjPhg21Wo3jx48zNzdHX18f+/btY9euXSQSCRYWFsL2gw5zc3MUi0WuXbvGuXPnuHjxIsViMcwSsCwrvCu+GQqFAkEQrGuVuJX9Ajzcux1bWymh6vv0AbjZ3Uddo//Zg10PDcZ61pRkxRI2v/Rvfw57lUFGv9jCE3yOUXaE2Qw6BqPs4Ak+R7/Y0rW9ETPY89QOGo0GS0tLHDhwgK1bt64YpliWFQ4OKpUKsViMnp4eEgklQ/M8D9/3icfjjIyMkE6nKRQKoaplee6E67rU63VarRZCCHp7e1fkOliWheu66/4uOufV1NQUuq6TSqWi3IeIuwpNEzz+wDiNpku+XKNca/L22Wu8cvQc5WqTn5y4xN+/fpLZQoWh3jTpRIx0IsZQb5qFUo2z1xaRUjK1uMRbZ65y+soc1cbqlq4PCtM0efnll1c8/tJLL930TvqpU6f46le/ys///M/zrW99ixdffJHDhw/z/PPP89577wFw7do1fvu3f5t6PcojiNsmR/aMki/XKVbqFMp1Xj1xiZ8cv0Sj5fL9t87wdz89gecFDGaTpOI22VScwVyKs1OLzBYr+H7AuelF3py8yrlrC7Q+ZN9+dL58ePT3JNkzNsB8oUq53mQmX+aH717g3XMzlGtN/v71k/zj66dIxi36e9T50ptJ0JdJ8Pa5KaqNFo7rcerKHG+ducrVhRKu/+EOOKPz5aODF/hUvSZ1r7XqgtwNPGYbJa7W8sw2SnjtCsqjhUu8tniWuG5xuHc7j/fv5nDvNpbcBv88d5Il5/pnX3RqHC1e4mJtjmOlyxwvXeWtwgVOLU1RdZtoQtBnpzhdnsaXN7EoL2OmUURDW/eciesWZa/B0irZDHWvxZnyNN+beZd/mHqbH86d5Fq9cNuyJDaLDMoEzVeQzb9DOj9GOj+G1ndQoY3F64t7v4jKVfDVAMB8GKwnAEOFTAZFNXDQhsF8CE0fRrMfQ4v/ClriV9HsTyD0QYQQCPNBwFVqCCFAS4M2oqwP2qCyX5j71ONIkA00YwwR/wUw94AstlUWJZXPYO4DbRUFVUfB4a8cMl5//wVk83sQ1BD6FoQ2hNCGQAxDUEY2v48MlpCyReCeJWj8PUH9rwkaf0fgnkLKzbcf3o3cdTaKjeQcrLZNLpdjZmaGeDzetcjvqAk6aoODBw9iWRa1Wo2jR48CEI/HMU2TIAjI5/MUi0VGRkaIxWLE43Hm5+c31UCxXjNCh7X2e7P3/+zQQf7o9D+u2N/wFx8n/9JxgnVyGzRDZ+hXPxb+2dYMfmXsyLrH+a//l1/ke3/xCq1VbBoJkWIfD3fVW66GYet84d89g9BVLVc8Hl/XmtIZHBw9ehTHcbBtG9u2sSwLz/MQQtDX14dpmuGfYaX9pKOayGaz4YDgRjo2l7V+x8tVKjc7r4APJPsjImIzlKoNLs4VKFUaZBI2O7b0kYhZlKoNUnGbfLnGqZl5TEPj4we2kUvGCaTkB0fPMdKXZktfpmt/uXSc9y7O8NrJi5ydyhPIgGrTwTIMPnFggs88vJu+zOatZpvlyJEjvPzyy/zGb/xG+Fi1WuXo0aPs379/3ed++9vf5oknnuArX/lK+Njv/d7v8fbbb/PXf/3XPPjgg3f8bvydQErJ4lKNi7MFak2HwWySiSGV3VFvOu070jUuzuXpy6Q4tHOEVMyi1mzx2snLHNqxhWz6+t91mhAk4iZvnZ3izNUF5peqeF5AtdEkk4jx+SN7efyBCdLx91fdthGi8+X24wcBM/kyl2YL+IFkdKCHrQNZ6k0HJMRsg9lCmamFJcYHc2wdyGJbBnPFCievzJPLJIhZ129uGLqOAF49cZGfnr5KvdnCcX1qLYfhXIZf+vgBDmwbJmZ98Jey0fly56l7Lc5X5jhfnWsv8CUZM8Ge9Ba2JpUC93R5mjPlGXzp0/Hx60Ija8aZay6xJZ7rWujrQqPfTlF1m7y2eIbPbzmEBH4w8x7T9SJbYj1hYKSUkqrb5FjpMgd6ttJjJSgFdUpOjb4NNlA0PAdzlWykG9EQuEH3AHa2UeK1xTNIIGPESBgWNb/Fq4tnyJlJnhzYu27bxu1GBmW10EaAGO6yMCPLIIWyT8h5FQQZVEFPgPEA6IPtHIQhpPRQvjwD5DziJo12QkshzcPgv6RaKNDatZotoKGyIIIqSF3tVyTaz8sgrMNgHSbwqyocUuvvDrNc8WImBKvfbJRSIltvADGE1v37F0KAyCKDErL5Cqo1owUio2wiuOC+i3RPgP0pxI15EvcYd5WyYSN3kNfa5uzZs1y7do0gWH2xvVxN0FkgSilJJpPout4lrdc0jenp6TBP4FZsFDfrOl5tvxt5/712iqcG9mHc4CGLjeTY+fu/imabKxUOuoZmm+z8/V/tqr0Ewa9sfWzd93HpysX/n703j7HsPMt9f9+a97xr7xq6qqu73YPHjofEdowzDzgkNkcKCRedwE2IlBN0IQjBQUG6fyAdhESCFJDgAkJEEbqCgw4nMhwOBEJy4yTE8UDbjodu91jdXfOw5732XvNa3/1j1d5d1VXVg7ttEqceq+Xu2tPaa3+19vc+7/M+D5/905/HzL3GuNCMziP/5T28/2Pv5uDBg1Sr1R0/o43I5XIcOnQI0zSRUg4TKQbntV6vs7a2RqvVoli8VBxtHD956KGHyOVyFIvFHT+PIAgYGRnZ8TO+VpXK4uLirvphF//hmF9r8xq5MqoAACAASURBVM0XznBxuYkfRszX2vzTs6/yN0+8wAvnloiShIRLBn9ZU2elZXNuuYEfBKy1ejgbIm+TRJIkkmdPzTKz2GCkkMENIhRFwfMDvvH8Gf7ue69wemGrkezNxgc/+EGef/75YTQuwHe/+10eeOCBq/rqCCE4c+bMFgnzH/7hH/Jrv/Zrw+cH+NCHPsTf/d3fAWlX87HHHuPee+/lZ37mZ/i3f/u34WM/+clP8sd//Mf8wi/8Avfccw+f+MQnOHfuynLMHzacuLjCEy+eY6Vl44cRpxdqPP7kKzz+5Mucmq+BELhhiB/GVAtZNEWwUGtzcbWFlJKLqy3iDdfzOE6IooRvHDuD7XjkLQM3CNE1jabd5399/zj/+6kTrDS7r/t7210vNxdRnPD0yVm+f+Ii7b5H3w948ewi//1bL/C1Z08yV2uhayot20MC1WKWMI6ZXW2yWO8QxRGzy5tHJqIowXZ8/vfTr6KrCpqq4ocRhqYxv9bif3znB/zrsVNDg9vXE7vr5T8W3dDliZXjnLNXhv4J41YJKSXPNs7xXOM8zzfOc6I9T0nPMG6V1u9TpKBZfGftJN0dUhwA8rpFP/Ko+TYXezWW3CYjRm5TMoUQgqxmklGNTYqG6DqUDZZqEF7DHjfZ4JcG0A4cvl87TUGzGDMLmKqOpqjkNYs9Vol+5POtlVc4213mTHeJJaf1uqsdZPAcIBDKZgJHCJH6FShFIADrZ8B8P+hHQX8Aoe3ZZLgohIYQ62aTUl7yXrgSjHekIxTqAVAqIAPSRIlKSi5ID6IzKemgbDUrVtR8enzyCgpMmQBK6iux7e0tSBpbiIbNyELwfZB+qnoQGYRQEcJCKOOAhfSfQCZv7hrgR4ZsuBafgxMnTvDqq69ue58wDLEsa0gSbIdBB3tQQA6MAi/HQOVg2zZxHF93V9owDOKrSAAvf96rvX8hBMeOHeOFF17gkXA/2jYfbfnBwxz9s88w/pH7ULIGCFCyBuMfuY+jf/YZyg8evnQuVJ3P3fYhRoydM2YH5+mWo/v4jb/+LPlKDn0bx+mdoJsaH/6/3sdjv/rBHd/3lXDkyBF0XadSqTA6Ojp8vKqqw8+o2+0Sx/G2xXylUkHTtB2JhIEqIpvN7nhM16JS0XWdV1555aZ7f+xiF9eDIIw4dmaecs6iUsySMXVGClm6jsf5pQblnEXOMkBKSnmT+bUW33v5PDPLDVq2gxtEXFhpslBvE0YJM8sNnj05y78+d5pTczXW2r2h5NlQFUr5DIpQaPcdXppJ5dIt2+HFmUWePH6BU/NracfzJuHw4cPs3bt304b8W9/6Fj/5kz951cf+7M/+LO12mw984AP80i/9En/5l3/JzMwMExMTw2vLV7/6VQD+9m//lkcffZRTp07x+c9/ns9+9rP84z/+Iz/3cz/Hr/7qr3Ly5Mnh8375y1/mkUce4e///u/Zs2cPn/3sZ/H9N3a85LWiZTucmF1lvJynlLPS9ZLPslhrs9ywqRZz5CyDOJFUCzlemV3h6VdnmVtrY/d9Wj2XC8sNGl0H1ws5NbfKs6fm+Od/P8nF1QbztTYvzSwRhhGGrjJSyOOHMX034NlTcwRhxGrL5t9PzfHUiYtcWG7e1IjE3fVyc7FQa7NU77CnUqCQNclZBoWcycxyg56bkpfpekko5zI89epFXji7yFLDpu8FtHoeJ+bWUp+YnsvL55d59vQc33j+NCvNLucWa5yZXyOREsvQKecz9NyAjpOOfIVxzHytzdOvXuTZk7MsNbqbiK4bxe562RlSSlpBjwWnwYLTuGJR/1qQyIRnamdQhGDUKqBuKFQzmsEeq8QrrTmONWeY2KBEGCCSCZaiU/dt7GgrMZVISSdwWHU7PLFygifXTlLUszuORxiKRpTEtPweUoKxTVTmTtiTKZOQbFGyxDIhSCJimeDFAXk9TakY4Jy9gq6omNuMNbtxwJLb5KnaGZ6qneHVzgJP107ztcUXuNh7fYh+mXTSJAdR3vE+QimuJz7UQNufxl9e6TllnJpFKlfv8gv9FtAOpQqKpJcmSahjKdEg9EuqBu028J/cflxBO0xqLrnN74xM0nEPdQLUka23AyQdrlpGJ3Ug2vF+QsmCjJHRxSs/z484bgrZ8EaY411LB9m2bWzb3vY+URQNu8wbmenBba1Wi/n5ec6ePctzzz2H7/vkcrkd34NhGLTbbVzXZXx8/Lrey/j4OK57aeEPXv/ChQtDb4iVlRVGRi4t8Cu9f9/3WV5eptFo4Loue4uj/JfKw+hsvQBaUyMc+NxPcf/jv8mD//x/c//jv8mBz/3UJkWDqWi8pbSfnzvw8BXfx8ZCe/qOSf7bN/4r9z96N5qhoe1AOgghMDI6E4fG+K///Zf40C+9d9Pt13M+JyYmmJqawnEclpeXgbSwB4ZKh4mJCarV6rbFvGEY3H333biui+u6xHE8jM10XZcoipienh6mWWyHa1GpOI5DGIavi0fHLn684QURp+bX+Mbzp/nmC2c4s1DbsSCrdfrESYKha0RxQqfv0ej2adkulqnTstNrkq6qIAVN26Xn+ZTWSYi9oyXiJOH0Qo0fnFtgtWmjagqrLRukpNX3CKOEIIpZbffwoxhNUbDdAFURPH1ylm++cIYLy006fZcTF1f4+nOnaXRvHqP/gQ98YDhXHYYhTz75JB/4wAeu+rjDhw/z+OOP89hjj/HSSy/xxS9+kUcffZTPfOYzw9/LQSTyyMgIlmXxla98hY9//ON89KMfZf/+/XziE5/gscce46/+6q+Gz/uud72LT3/60xw+fJjf/d3fpd1u873vfe+mvd/rhe36vDSzxNePneLbL55jbq21rckvwHytg6GpKIogCCM6fY/Vlk0iJVJK+uueHLqqEMQxtVaPWEqKOYt81mSyWsTxI165sMwPzi/R6ftICfVuH5lA007no/t+yFq7RyITFEXgBgF+EPOdl2b4zkszLDe7tHoOz52d54kXz91Ugmp3vVwZjW6fZ07O8vVjp/j+8QustbcmXQ1wbqlBMZsWE66fEgZL9S5ZU6fVc4mitHDTVQU/jKh1+miaQiFrMpLPMpLPYDser8wscfzCCkEY4fkhXccnShIatouqKrT7Ho1OD01VCaIYXVNYanT45nNnePrV1Lx2rdPje6+c56njF2+qt8PuetmKpt/jW6vH+dbKcZ6tn+XZ+lm+sfwS/7Z6EvsmkQ5136YbuhT07Rs7Qgjc2KcTONuG5CQk6d5T0VhxW5tu60c+P2he4Hh7nmbQY6Ff56y9wqLToBX0NpmaboShqKx4bYq6RVm/9jHBkpFlOlOhEaS/S3bocqa7xLP1szzXOM8z9bO83J5jf7Y6VAuEScScU6O0zfv344gT7XmcyGfUzBPJiKpZYDxToqBneLZ+jnP2yjUf3zVjvdDezntCIlOvhuDFNNLS/Xvw/7/UYyFe3vk5ZR20266YdjGAEAZk/zOQh3gpTZCQMSRh6v9AA7R7wXgr4G1fzBtvTZURMlj3jXBSM8mku0407E39H7Tbr/GkbINB6saVoFTSJI43MW540O31ioa8HNfSQb4So6tp2rBYb7fbw0Le8zyWlpZIkgRVVYcEQ6uVXpDiOCaKok3RigCKogyjGAdfEteKSqXC0tISQRCQJMnw9Q3DQNd1giCg0+mwsrJCpVIhl8vt+P6jKGJhYQFN0ygWi9i2zejoKA8VDxEJ+Er9KcIrRFBejoyqc7S0jz+4/1NXjfMJgoB8/pLywcqZ/J+/93E+/Kvv45v/73e58NwCjdk2oReiaiqlPUXGbh3hvf/5YY6+4/YtF6kgCK7rfA7Igl6vR6/XQ0pJEAQIIdB1nWw2y759+7AsC9u2aTabW3wXpqenaTQaeJ6H4zgEQYCmaVSrVQqFAkmSXPGYBiqVy9fHRrRardfs0bGLXewE1w/5zkvn6HshhayJlAkvzSwxu9riPfccwrwstz5OEpCw3OxycaVFIhPCMGG+3mainCda7wKW8xm8ICSM4zSyLk5Ybdm0ei5CEcyvtlhtdjk0WcXvx4zkMvhhjKpCtx9SzFnESUK752JoKrmMSRjGnFhd4b7DU8OYu3zGxPEDnj45y0cevAP1GuZYr4YPfvCD/Mqv/ApRFPHMM89w5MiRYedwgMcee4ylpSUApqam+NrXvgbAoUOH+OIXv0gcx7zyyit8/etf52/+5m/47d/+bf70T/90y2vNzMxw5swZHn/88eHPwjDknnvuGf77rW+95FeTz+c5ePAgMzMz19QNvdlodPt89+Xz6bFk0vGFp1+d5cBEl7ffvh9F2Xw99sPUef38cpPl9bEGxwuot/tMVArE65vwiXKBcwuNdDxagh9ErDRtWj0HQxWcuLjCaCHHZLVIz/PZM1Kg3nGIkwQ/jChkTPwopu/6RHFCIWfR7js07T537B8ffk/kMyZN2+Wl80s8fNctN+Wc7K6XnXFhpcGx0/OYukbW1Gn2HL794lnuPbyXO/ZtJd+DdcXoydnVlEgSgka3TxjGjJVyw6Jtslrk30/NpaQmadzlatOm3fMwdJUnT1zk0GSVUtai0/fYM1Kg5/k4fpiuj4yJG4Q4QYgAMobBxdUWUSzZP3Gpy1rMWiw1u1xYbnLb9NhNOSe762UzGr7Nd1dfJaMZTFiXYv6klHRDh++svsr7J46S16/c0d4OfhzixOmefr5fx1B33mNJKXHilIR042BTfCWALtLHWqpOe4MJpBsFvNKeQxcKZSNLN3SpmgUSJAXNpOn3mXVq3JIbH+aqScCLQ1a9Dr3Io2zkebk9xy25sS1pFjvhrZWD+PWznGgvsuq1yWkmBc3CjUO8OKSkZznVXWLULDKeKREmcZrMuM2efMltEiYxRT1DkER48aVmg66ojFtFXmrNMp2t7mj2/tqxlYiRSIjOr8dKZtNRBaW67lXgQ3QWKXxQ9g5JBSm91BdBnVo3f7w2KGqVxHg7iBzEFyFpAwpo+9KITCX1kZCMQHgSqd2xedxDO4BUq+u+EsElFYKYSFUSUgIhQjuw/QGIAqkXw5VOkU8qI9+5BhBCR0ofKZNN4yVvJtwQ2XA95njXM2qwnQlirVZjYmLiio+70qx/qVSi0WhgWdawwx1FEUtLSyiKgmmauK5LtVql0+mgKApJkgxjFAedaUVRCMOQTqczvP+pU6euy+hvYHB44sQJFhcXsSxrOLLheR5CCI4cOYIQYnj+Li/sB7BtGyklmqYNi+0B3lk4xD6zzB8tf5suPl4Sbnn8AKaiAYJfvvVD/NyBh68pN3i7QjuKIjpum3f8/P2851MPEccxcRxz8ODB4fHOz8/TbrcpFAqoqjpUEiiKwu23335dayWXy1GpVMhkMsOxFlVVKZfLw5EF2LmYNwyDu+66i9OnT5PJZMhkMtd1TOPj4ywsLAwjOLeD67pMTU1d8X2oqrpJ7bKLXVwNJ+dWcYOIsfIlMtcydNZaPWaWGtx1YPP1spC1aNp91tp9SjkLVVVIpKTe7bFQ63DXLen9TUNjeqzM+eUGhYzJzGKdnuuTSMlkuchKq4vt+DS6DlGSYOoalqHhBxFJkhDFCZoQdPsuGdNg/1iJs4s1/HUVxlg5T7WQRVUVsqbBWqtH03YYK+08snWteNvb3oaqqjz//PN861vf4pFHHtlyn7/4i78YjtINrg+///u/z6OPPsrdd9+Nqqrcd9993HfffUxPT/MHf/AH275WHMd85jOf4WMf+9imn1/+XXj5Y67mXP96QErJc2cWsAwtHZUBTB2yps7saosDEyNMVjYbf06MFPj+iQv0vJBSzkIRgsz6+lqot3nwjn1ASk6VixmWmh3iJOHMwhpeGKMAU2NlTs/VaPVd8lmTds+hnM+iqR4gcf3UI0RBsNrsMVbOUcll+P6rFxnJZzizUEvHOPIZFCEo5y0W6l28ILoppoC762V7+GHEC2cXqRazaOukgKFr5EyDVy4sMz1aIn+ZieeeSoFvPLduXpezUp8rRXBqLpVxq+tk1mSliLqubnDcgOWWTRTFaJrKWKlEs+ew2rLRVEHP8ylkTWzHQ1cU3CAkbxkgBMv1Dgf2VEgSybmlOkxVCOKIiXI6xgGpee25xfpNIxt218slJDLhWGOGnGaSvay4F0JQMrK0gj4vtWd559i1d4adyOdUZ4kL/TXiJMaJA5acJjnNIlfed0XSQSDSYvcymKpGxcjTDnqb9rYLThNB6qMgSccp9mTK1IMuCMHB/DgXeqvUPZusZmAoGqtehzWvS5BE3DOynzGzwIXeGmftZe4u7eO24tRVPwNT1TlamuZMd5mynsVLQuzIZ9QqsMcqU9QzeHHAU/XT/NTkfahCQSJJpETZ8NxhErPitYdkTpwkZPTNe9XBSMmi0+Rw4co11HVBKWzHNUC8lhINYiQdiUhcEBmE0EGdQgoL4gbQRYr1RqjIgvEQQjuIENd5XRcBGPcgxP1ImQBiy/kXwkAmTdI0DG3DzzNgfQDpPQEiWY/aXI/jlB3AQlgfQOw0/qFUQSkjkz5C2aGpLmMQecROvg+AlCFgvGmJBrhBsuFaRht839+2o7wTBkqJIAiI4xjbtgmCgEajQaPR4PDhw9sW3ZCqDXbCIAJxo+zdtm2SJME0zeF8/qBobDQaZDIZoiiiXC6jqiqdTgfHcYZkxMDQ8LUoOXK5HJOTk/R6PcIwxPO8TR31wZfI4Pzt1EHvdDrD8z9QZ2zEfqPCF6b+Ey86C3xfLnCiM49ApF1ECV4SMm4W+ei+B/novgev6NFwObYrtDeSH5ASR9VqddPnMDk5OVTAuK6LYRhMT0+/5lSGJEmoVqtbOgwbcaVi/vKUius5po0qle3uN1BKZLNXZrxfi/fHLn58kSSSiystyoX0S7DreKy2egRhRMbUeXV2ZUg2tGyHs4t1ap0e55YbKDItECFtRucsE8+PqLcdpkfTzmClkKWUs3C8kNm1FkJAOZel1u2x3Eil0fVunzCISdZ3HEII4iSh1u4hY0kkE8bLeb71g3PIJO06ukHI6YUapazJXQcmUrd5kZrL3QwoisL73vc+nnjiCb797W/z13/911vus3fv3i0/e/LJJ+n3+9x99+auSqFQGKrgLt/AHDx4kPn5eQ4cuNT1+OM//mPK5TKf+tSnADbNV9u2zdzcHLfffgOSzNcI2/GxHZ+xctphbvdc1to2cSwxdY1zizUmK0WklKkh6GC9LDYYLeWG85aaqpA1dbwwotV1KGRMJJJKzsL1I75//CJeEKIogpF8BsePaPUcRotZFuptPD+i1fdSF+8kIYgiVhrddSMzwS3mCP/rqROYuspoKUfH8Vjr9NgzUuTwVBVFpOVEFG/eNL5W7K6X7VHv9EkSiaaqRHFCo9un3umjrBMIy40ut06PEcUJC7U2M0sNlhtdZldb7B8vD9+7oalYuoZQBN2+x0gxm+6zMgan52qcWagRRQmqqjBWytHq9rH7PhldZ6HexfUCWraDEAphFOOFMcutLkGUkDF0kJJ/ePoVspZJItPjXmnYHJ6qMlktoqsqvW2Ssl4rdtfLJTT9Hnbosiez88x+Wc+y7LToRR557erqhl7k8e2V46y4Heb6NWq+jYJAko4bzDt13jV+J1Vz8z5VCEFBz7DmddA3mAvGSUIvSq83FSPPgtNgPJOSqmESUfM7FLQMEmiHDpOZMgXdYsIssbZ+27hVYswqIgVc7K3RCnpMZUZQhcLd5X2Yqo6p6sQy4aX2HKZqcEv+ErkVy4S61+WcvUo/9lCFQkHL8HJzliUvJVEKmokiVJJE0vDTMe+CZmFLjwWnwa3FSSYzFVqBTXGDj4OfhEiZkrUAvow4tEFhMoCl6jT93k0lG4QyglSqyKSbejOwrmqI50BaabEu+6TXaX3D4ypIAjDeiVDW147I3EChrZOSCPqOzyFlkhIf2zgHCGUEMj+NjOZTQ0nZBZEB/e0IbR9C7JyMJIQA46H1eEu2EA4ysdMRiW0MKjchaYF+5USbH3Xc0Lf1jUQ4boeBEiIIAhYWFuj3+yiKgqqqmKZJp9PhxIkTHD16dFvCwTTN4QU7iiJs26bT6QzHIAbjCJVKhSiKaLfbwyJUCMH09PRQldFsNoc+D7Ztc/DgQQqFArOzs4yOjiKEGP7/akqOy5UaQghM02RmZmb4+EFMY6PRoNPpUCqVKBQKw/O3Uwc9iiIsyxq+zsbCfgBd07lTGeOTD3yERCYsu226oYuuqExnK1jqaytytyu0O50OqqrS6/WG5oyDz2RAohQKBeI43iQHvBFcyyjD1Yr5QUrF9Y4xDFQqp0+fxvf9bZURd999N81mc/g5bQfXdZmenr6u197Fjy8SKdMZdyE4v9zg5Owqfhih6xqWrgOS9993BMcLefrkLKauYhoalq5hOwGzq00qhSyuH5ExNG7ZU+HcUg1FCEwj3azlMwZ120kfq2n0PY+e66fEq+vRcX3ylkGUJGRNg4yhoSiZ1IlaSoq5DLmMie+HZCyDMEqwDB3L0NN57obNvrESiZQ3Nerwgx/8IL/1W7/Fvn372Ldv3zU95nOf+xy/8Ru/QSaT4aMf/SiZTIbjx4/zpS99iV/+5V8GGBKGp06dYnR0lE9/+tP8/M//PPfccw/vf//7eeqpp/jzP/9z/uzP/mz4vP/yL//Cww8/zL333ssf/dEfMTExwTve8Y6b9l6vFenIQ5occvziMhdWWinRrmsIkZIR99+6j/PLDY7PrpK3DIQQFLMm9Y5DEMXkTAPHDxgt5/DDmJcvLNPoObx4dpFXZ9dI1p8/fUFYafVYafUwNIXVVoyqqViaTpQkWLqGYRqYuk4iAZkwOVoiiBPKhQwqgiCKqRSyZAydlWaX0WKWXMbE0DQy5s2TA++ul62I1z/HIIx4/uwCKy0bgcAyNMIoIZ+12D8xwrHTcyw1uhSyJqoqyFsGC7U2o34OTVPxg5ADExXq3T4vziyRs3S+88p5Vpo2yEuN0TiKWWykozqGJlisdzANDV1VMTQNXYNcxiCXSQlNRQgOTIzQ6XuMjxQIwpgkkeQzJnGScH4lTcYJopjx8o0rpjZid72kaIfOJqPG7SBE2mW2Q/eayIan1k7zcmuWFa9DIpOhR4ET+0Qyou33+d7aSd47ficjlxEOJT1DN3QxFI04SVh0Wyy5TZL1bneSJIRJhCIFq14nHfmKQ/pRgB26lPQsqqLgRAGT2RHqvo0bB+hKSojfkhun7ttMWGXs0F0fS7i0p1SFQsXIcaIzz/5clX7kc9ZeHnpXVMwCE1aJ+X6dmmdT8zvsz41yzl6h5dtIAXusMhNWmUWnRdnIciA3xoX+GrcWJ7mtOMm3VxpkVXODAeYlgsqNAixF32GUQ/J6CF6E+SDS/QYyURBKPvU8iOYAH2QIRKDsheAYUh0D7dZU4YAJ8QJC20rMXTe0Q6kvxJXMJ2Ub1IM7khFCmAj9COhHrvvlhToK1iPI4FlkvMwlQmM9GSP3s+A/taP6QUoXhEBoh677tX+UcMNjFDupDAa4Hnl4s9mk1+tx8eJFACwrleINxgOiKI1Uu3DhAnfeeeem4jIIgmEqg23brK2tIaXEMIzhiMKAXNi3bx+e52HbNoqiDGf8l5eXh0X+9PQ0CwsLw1EKKSWtVgvXdclms0xNTW0pbjcqOSqVCs1mk/n5eebn51EUhbGxsWEiRhAEtNttcrnckNjQNI2JiQlyuRyNRoNms8nevXsJw3DHDvrAi2LgLbCdnH9joa0Ihb3ZCjfhV3zbQttxHHq9HlEUoes64+PjaJpGo9Gg1WoxNTU1HFm5WbjWUYbXq5i/mjICoN1uX1H98Fq8P3bx4wtNVRgr57m40uKpExdRhMDQVcIwot1zGS/l+P7xC8RJwkjewtA1EpluxkdLOdq2i6ooaJoCSM4s1mh2+7T7HjKR9P2Aw3uq1No9uj0Py1w313UDTF1PDaCShJxl4AYRtuOhKhny60aSlqGxt1ri9EKNkUoRBLR6Lj03IG/p5DMmS/UOpq5xcE9liyT7RvCud72LJEmua275wx/+8NCU7fHHH8f3fQ4dOsSv//qv8/GPfxxIjds+9rGP8Zu/+Zt8/vOf5xd/8Rf50pe+xJ/8yZ/wpS99ib179/J7v/d7vO997xs+70//9E/z1a9+ld/5nd/hgQce4Ctf+crQxPaNRCFjoqkqZxdr/ODcIqauo6upLL3nBpSyGZ45NUe902OinE+NGv2QfMZkfKRAp+cOxyjcIOLcYh3PD3j61VlcP9xWTTtAECWEUULWEkyULbqOR8fxmKoWAIUjUxU0VWW8nOf0fJ1KMYPrh/T6PjnTwDQ0TENjqdGlWszywG37b4q/xwC762UryjkLieSFcwucnq9hmTrGukrA8QNqLZtjp+dZrHfYsz5+4wURI4UME5UCXhgiE7DMNNJ0ZrlOGKXeL/EOhqQDBJEkjCJ0TaVcytLqObhhyIGxMpGUHJ6sYmoa2YzB7EqLajFHu+fSst00HlNTAcFKs0fG1Hj4zusz8L4adtfLJdzM+rXh93i2cQ43DlAQFDZ08AtaBl+PaAd9VEXl1e4iPzF665Ds8OIQQ9F5oHKQFa9Dy+/RDHoU9QyqUEhkQid02Z8bo6hb7LUqLHstlt02eT3DuFUkoxksOy0WnSYTVonDhT3M2CvUfZsz3RX+YeF51rwO8fooQ0nPcDi/h4fHbmV/Nm08muueEC80LnC+v8aF3iqJlJSNHG7s82TtNJoiuCU7xrLb5NnGObKqRV63kMCa18FPIqasMnYoOGsvczCfqhFGzQIPVA/zfPM8hqJR0jNkFD2tTfweQlG4LT9JlMRDX6QB3Djc5KlxsyCUCmQ+hPSfRkZLEJ1eT6gYSX0U1L2g5FLvg6QBYYDU7yYtPXce676uY1APIMOXkdLbdtwhHVHwEPqtN+X1tj+GUbAehaSeKj2EAFECpZLWsOujGjLpgRhJcB8g9AAAIABJREFUxzrkupGlUMB4b0rWvIlxQ2TDzegob8TS0hIrKytIKTfJzoUQWJaFoii02+0hcTAYYRh0kI8ePUoQBHznO99BURSy2ezQe2FQ6I2OjtLr9Th48CAXLlxACEEmkxneb21tjYWFhSFBMTBxbDQaQ9OfTqdDvV7HsqyhZ8Cga5/JZJifnx8SA7VajVwuh6Iow4J7dHSUXC7HysrKkHDI5XLEcczq6irFYpHR0VEURWFubo6pqakdO+iZTIa5uTmSJKFYLDI/P7/Fr+CNKrSXlpZotVrouk61Wh0eI6QKlzAMWVpaGr6fm4VrGWV4vYv5qykjrqZ+uF6vil3s4uiBPfzP77xIvd0nY+ngpp3CnKWjaSrnlxuU81kqxZRNV4Rgqlpkfq2N44e0bJdyIcPMYp1Wz2WyWqTreBiaihCC5WYXBZGqyxSBkAIkhFFEFMs0gaLrkMuaaTGip74xSSIp57MsN7s0un16ro8UAkvXyJs6nXUZfb3rMFkp0HV8Ts2vcWB8ZNix9sOIlYadzmxnTPZUChj6zt8zp0+fHv7dsixefPHFTbdvdHDfCe973/s2beS3wxe+8AW+8IUvDP/96KOP8uijj+54/4mJCb74xS9e9bVfb2iqwp37x/mf332RIIox9AgpJYpQKOcyhHHEi+cW2DtaHhpFZkydUj5D3w1o2i4ZU0dRBDOLdZwgxPVDHP/aNowS0nhD29ngGaHj+iGalipu5msdmj0HJ0iThCarBYSATs/DXx/bqBSyLNTaKEIwPVZC19Lvl74XsNJMvRwqxSzj5fwVCYnd9XJlFHMWlUKW//HEixi6gh/GSCSqUBgr57DdgH8/Ncft+y7JxUtZC01VUYRgbqXF1GgJ2/G4sJyO29bavasSDQNIoOv45CyfnGXiByG6puG6Hrl1ldRirUPD7tP3Q6I45o7pUfwwxvFDun0XmSTceWCC0ws1gihmz0hhuLbbPZfVtk2SSMZKearr4x07YXe9bEVJzw5NYneCXE+uKWiZLT9vBj0WnCZBHJHVDFbdDk7k48fBtkaGVbNALBO6oUvDs1nqNxkx8zhxgCYU3j1+B1WzwBMrx3mxdZGSnqEXekiRNtn250aZzlaJZcL5/ioK6c8KmjVUCqgoNHybJ2unySoGq36HuX49HRHcEIMZS0kz6NNszvBC6wIjRo5PHnw3ezMVlpwmx9vzIGDFbVE1ChiKhipUEhkTxDDXq9OJ0jWqaAJFpIMQGc0kiCPqfo9xRcGNAuLMJcPHg/lxykaW8/Yas049bTIKhVWvS8XMc9ZeScfajBzT2SoFPYMfh+hCveK4y41AKBWwHkVGZyFeAbEPtLGUbBj8Tg2K77gJcQ2ElhpG3pTXzyKN94D/baQwQJQRQklHJ6SdjnIYP5Ee5+sIIQSoYwh1qz/M8BzFFyE6jYybIAzQj6Y+FW9yogFukGy4kY7ydiaQg9GJnebbDcOgUCgMVQamaW6Zrbdtm8nJSeBSN1lV1U1eCK1Wi5deeolKpUK32x0WxGEY0mg0cJzUrXbg1ZDL5Zibm6PVaiGlHBIUruvi+/4wvWJqagopJWfPnqVUKuE4Do7jMDIyMhw3EULQarWGaomN6Qm6rqMoClEU0Ww2GRsbIwgCTDPt+l3eQe90OjSbTYQQQ5PEATEyOB5FUd6wQntwzl3X3Xa8Rtd1XNelXq9z9OjRm/r6P+zF/I34QuxiF9shCCN6XohuKMMvdU0RqELB0FQaXYdibvPv4VS1RKfv8dL5JZCwUO9Q6/RQFcFqu4ehKriJJAoilroOfhChqgp9L0BVFWIpSWJJnEh0TSFMYhRFwVAUjh6YwAtSQ9i51RaFrEnGNBCKQEXg+gFTo0UOm6O8fH6ZkXyGciFLEEWcuLjC6fka773nEHGS8L1XzhPGCZqqEEUJhq7y7rccolK8NrfvXWxF1/GI4wRdVREIEAJtvQMmhKDb99l7me3NkakqPzi3xNxai5xl0O37tHoOmq7S6W3Nq48Dj9bMi/idOmZplJHD96Eal7pN/SCkkDPJKDpvu3WaC8tNXD+gbbvkLR1NEWR0FRdJt+/z4O37ieOEY6cXGB9Jjf/6fsCxM/OcXazxnnsOs9zs8NyZhXUvIkEYJ5RzFu+++9BNHbf4cUOj2wch19WfIGRKWgkl9Unq9N1NhI6qKtyxf5xjp+ZYadt4YcRqq4fjp3uc8DJflqutlUSC4wdkjJT0evD2fRyfXWG11UNRBJqmoCoKWVPD7sd0HI93veUQ3b7Hv5+aY6JSwDJ0Wnaf+bUWt+yp8MBt0xy/uMqZhVpqWCkgjpfZN1bmwdv3D38fdnF1VM08Oc3EjQIy2vb7l+66p8PGNAo3Cni2cZa6b6MLFU1RCd2YY/VzNP0epqphbSN3F8C4VWTNs6maBXwZUjSy3JnZy1S2gqGkZLdE8q6x2wmSiFgmqEKhpGeHhIIiVJbdNmU9y8H8OBf7NcpKFi8OOdldpBe6hEnCq+5CGvOLXE8l2B6xTKj7Nv/P6a9z/8gh7Mhlf3aMWMZkVAMvDpjt1xDr/2UUnYv9OkEU4sQBfTfACnVyqkley5CQYKoaDb+3Tuhs/r0ZMfLcX83z1pFb+EHrIqGM0BWFQMYUNAshoRd6vNye5ZbsOJqi8s6x29GVG/e42QlCCGTSAP0gKGYai7kdeafkIJ4HbS9C23/TXl/RJpHKR5DhGYgvIOX6Z6ZOI/R3bUsAvNEQShah3AX6XcM68scJN7T6XmtHeae4zHq9Tr/fH6oYtsPA22DPnj088MADW25fW1sbkgoD453LEccxnU6HI0eODA0a4zhmdnZ26KcQxzG+76eMfK2GZVm4rksul0PTNMIwJAxDstksjuNgmiazs7M4joPruoyNjdHtdocEyGC0QEpJvV7H87xhUkMYhkOyQdO0Iflg2zamaW5KmBgU9pVKhePHj3P48GGklCwsLOB53nBsJAgCzp8/z969ezl69OgbUsyura1RrVZZXFzcNi4UUoOlXq9308mPH4Vi/rX6QuxiF9vhxOwK1UIGPzKwDG1YbPlRTKPbp5izMA2NJJHDjp6mKuwfK6eJEapCz0ujxUxdo+d4qWGgoRGEEa4fgZCo6zOIcZwSpMn6rHUYJURxiBd2GClkWev0cJyQhUYbS9fRNIWModH3A4pZi/1jIyzUu0yU89S7Du98ywFKuXQTmjUNbMfjmZOzeEGIZeiMbCgU+17A909c4MNvv2MYmbeLa0ecJJycXWVipAhIdF1FQUFRwPFD2j2PyerWTpNl6IyXcwhScsvxA3RNIQi2xin3ls8z889fBilJogBFM1h86h84/OhnyU+m86iOG9BQ+xQsk8Vam8V6m1YvVU0YmoqmqTR7LpV8hmI5T73TxwsjEhlz14GJYZxrzjKotXs8f2aepUaXSjEzTE0AaNoux07P85573txzsK8Xeq7PUr3LnkoRQ9NQ1bT7qgjoeQFtPO7cP07PDTYROqWcRdYyUBD0HJ8witFVla6zOZb8WtYKQLfvpWk3ic7sapuLSw38KMLU02tesk5KVUtZNEWh63icW2pQKmQ4PDU6dO7PZ0xmV1vrHjdNJir54W1SSuZqHUq52pYEn13sDEUoPFg9zHfXXkUityRSdEOXBMk9I5cMLoMk4sm1UzhxsEXWXzQyLDhNnDggp1nbjmgIBKoQ7MtWub00xQPVw5tu9+KQXuQzbu3cNQ+SCDfyyaoGezJlOoFD3beZ6a3iRkGqzHHqQ+Pja0UkE441Zxg3C7y9eoTZfh1dUdGEiiE1lr02SOgAi16TOEnWkzMERBIvCmmHDiU9ux6vGVA18ltGIgZY9TvM9FaYylSYsMrM9+useB1Yf84oSTjfX+OTt7ybyez2tdBNRVJL1QzafgheSKMkxeX7bgOSOVB/4pI55E2CUEYQ5kNI+dbUL0JoVzR3/I/EjxvRADdhjOJ6O8pXi8t0XZdOp8PIyMi2hMNgLGOn4vFafCRs2x4aM05NTQ3HHiAlMwbSL9/30TQNVVWHfx+8/mDswnEcMpkMnufR6XTwPI+JiQlUVSVJkiGB4Ps+tVqNbDaL53mEYSo/HTzP4NgH3hSWZdHv9zl06NAwRmkjLk8COXDgwNAQc5CAUCqVmJycvKZ0jJuBwbkf+F1sjAsdjKQAjI2NvS7F/24xv4sfF0gpadkeo6Ucq+0eURQPCzGZJCw2unzk4CR37h/n7EKdajGLrql4QciJ2VXketdQIIiiBDv2CeOYOJa4QQAoQyO2JEnWN0abGzxy/Tj8MGaladPqOkyPlcmaOrq+Lm/3Qyxdww9jEJKVVheQvOWWCcqXqS4KWYsz8zVMQ2OksFnBkLMMVls96p3+lojGH1Zci7T6jYLjrRP/hQyNbh+ZSBQt/TzDKKbW6fPIg7djqRpr7R7VYhZFCBw/5OT8KpGUJFEMIp3N9y4jG+LAY+afv0wSXioqkyi93s/885d5y6f+G6pupptoP0QmgmdPzVEt5siuj+DEicTzQzRNJYpjkiRhqZEmPz14277h+h6gUsjy/NkF9o6WNhENACN5i5WWTc/1b6ofyOuJH6b10nU8ClmTctai7XhkVR1FpGoD1wvoewFvu3WapXqXlu1QWk+3adsuc2tNwvXrUZwk+GFIsuHCca1rBSCWaVKNGwS8cG6BfMYAJfWnieIYIUAKAUjcIGJ+rQ0C7j8yvSkiUAhBPmPwzMlZjuwd3XJbtZDh7GKNO/aND4nZH3b8MKyXUavIeyeO8kLjfGq6SGoOLIGqledtI4co6peu84tOg07oMJHZ6h9Q0rPkNJOa38XbQS0RJDGmqqMp6o7JaVf69OIkoe6lxo/92AcJt5em6NRnaAc9sqrJhX7tuomGARIka77NsttCEwr+uipBCIGCwpLfIooj4vU9v4pCTEIkEzShEiUxNb9LQctQMjLszVbQxfbqrFOdJQp6GgmsCJVDhQn25Ubphx4JEkPVcEKfQG4lhl8fpP5PQhSQ2j0QnQDpAGbqSyCD9I9SAePtr9tRCGFsQ3Ls4j8aN6yrud6O8pXiMnO53FBBEATBFvf+OI6HsYrj49ub/lzJR2KQULGysgLAxYsXKZVKFItFlpaWUFV1aEKZzWbxfX+YSNHr9VBVFc/zhsX/YERB13Xa7TZCCKIoGhb3qqoOiQvHcVAUBd/3CcNw6NI7kNMMXhfA8zwURaFUKg1HKy7H5UkgAyXHRjVHFEW0Wq1rdky+UQzOvWma25IfAx+HH0dWbxe7uJkQ66kRByZG8MMoNdTzAtrrJoyxTFiudwjjhDv3jbPc7HJ+pcn8apuVZpdW3yWKktTxXVcJwog4liRAug9KN0MDMuFagimDKGax0UkNHy2DTt8jThI01WDvWJnJapG91RKFrEXf2z6OLopjTLZXLgjAD7YSr7u4OlRFwTQ09o4ViaWk7/p0+h5N26Hv+mQsnZfPLbFnpMAteypcWG1yfqnBSqvL/FqbvucjEViauj52uHkD25p5cWepsZS0z/2A6p0/sX4sKqauoqhp9y1rGRha2v2O4oTxcoHRUpbpsTL3Hppiod7ZMg4EqWzf9UN0bRvJtRAIkXp//KiQDT9MUBWFfNZkvFJAqIK+E9DxPVq2S8/zmawW+faL5zgwXmG0mOXUXI2Lqw3WWj0WG128IKTnhZhaqpJiQ/F2PWsFQNfSJJ1yziJKJJaupVGIUbpejkyNUsiY7Bsr8fbb93Nqfm0LMTV4Htv1sXa4LQhjojjGeB3l5m9GjJoFHpm8h0bQox/5CKCoZygbW5tcp7vLO6QlwGRmhPl+k26YKg32aZuT1SKZxljeXpxCU1T2ZreqYw1VQ1c0wiTaNDaQSMmK22beaeBGPotuiyiJea55nn2ZCp2gx3SmypLX2jK2cL1IkHx37SQfnryPnt/GUFX8JMJNApIkxo8jJBKBICFBsG6CL6P1CEtJP3K5ozhFIiUHclsj3f04pBnYjF+mDtEVlbJ56bwrCBacxk2NvNwR6jSEZ0A1EeoIUn0I4nqqeJAxKCUQeVAnUJQrpxju4s2Hm3JVvZ6O8pXiMiuVCq7r4nnecARhUJBHUTT0SqhWqzvK8HfykfB9n4WFhXSWBygWi0PTxkajgWEYZLOXTIKSJBlGYg6OwXXdTSSGlJIwDIcpF+VymVwuN3yObDaLbdtD5YJpmkO/ho3PO/CM2Egq2LbN2NjYFT0vbmYSyM3AxnO/HfkB6fvajXjcxS5uHLfuHePExWXu2D/B3FqLnhuSJKAoglvGqxiGzkrT5vxyk0OTFVw/BCSxlMSRJE4SPD8kSSRBvJVQGFCC17r1kqTF3dxa6hCfz5joukrPC1ist1CFwk8/dBd9L+Tl80tDo8ABojjBMo0dxyQkkLV2OxavBVnLYLycR1dVNE1jca1Fx/FBpmMzt06lM61nl+rMLNeZrBbxg5QUT2JJHCVIAU6SEMdbV4TfqQ+705cjiQL8Th1I19TesRJRnGBoKn4Q0ez2sQyDjKWjawpNu0/f86kWc9y5f5w4Tqh1+8ORmwH6XsBkpUAYbT2eQSc9a+6ul9eCSjGNHD0yNUrG0Fhq2LR6LoI0pvbgxAhRnHDszBwjuQyFrIUfxCiKII5joigGsf73y9bLta4VSNfLWw7uodbpkzFS1elSvYuhK2RNHT+MWWvZNNs9Dk+NcmR6lAurTfww2kI49NyAfWNlHD+kkN1MQPlhhGXqWxQyu7g2CCEYNQuMmjv7t0VJTD/ythTIA5SMLOOZIlImzPRWafp9suvqhlgmIAQVI8+IkePekQPbmkiqQuG2wiSvdOaGYxpSSmb7NRadJoX1BIec2mY8U8ZSdU73lllxuxQNi0W3taOqwVtqsfJ3z9L49gkSN0DJGFTff5Q9H3sIa2rzPjeSCXW/i4aKF4c0/B5uFNCPfEKSDeGIEoXUR0II0FAwFI26b1P3bfbnRzmQ3+o3kMiUrLgaFCGIkzdG2SC0g8jwBFLGCKEi0EGdTP+Qfg4kSwjjrjfkeHbxw4U33A1nYNi4HQqFAtlslunpaXRdx/O8oW9CNpsdjmnce++9O8rwK5UKiqJs8jmIooiFhQU0TUPTNPL5/HA8YtBpdxyHfr9Pu92m0Wiwuro69F/o9Xr4vo+UEl3XyeVymKa5iTCQUlKtVikWi8PXHjx3v98nDMOhbwMwJD2klMTrktHBbaqq0ul0ht4V2xErAxXBlXA9SSA3A9ud+43YjXjcxS5uHo5MVakWc6iK4NBkhWxGx9BVDk6McHhqdL1bF3F+uc7Xnj3Jy+eXiWVC1jQQKoRxkrrDKwJT07hcPawItt12xYFH/eQzLD7zT9RPPkMcXDIKlBIcLyRj6HhBSKPrYDs+9a5LrW0DsG+8jKlrdPqXHhfFMbV2j5+4Yx8jheym2yB1jy/mTEaLb8xI2JsRbz28F0UIihmTAxNV8paOZRrcvm+cvWMlVFXghxE/OLfEN587zZnF1NQsnzWQQhBE8Y4NabM0irKDSZxQNYxies2XSDJaalBZyFqAIIgScqZO3w1odBy6jk+949Do9hBCcPu+8aF6ZwAviLAdn3fdfQgBeMHmVIxGp88tEyO7BpGvEbqq8vbb9+MFEeMjBSZG8mQtnVzG5O6Dk1RLeRIpcf2Qf3vlPE+8eJbFehtdU8llTCIpCQb7mct2mVdaK4pmYJYudXJ1LU23yOgaxZyF64UYmoqp63Qdn5bt0LZdal0XNwhRFYW33LKHpu0SRJf2Rz03Hdl411sO0veCTQRIkkiaXYe79k/8yIxQ/ChCEalBYrLDRUQVCneW9lKx8hzJTzKVLQ+NbE1FI6ca3Frcw3vG7+RIYWtjU0pJ0+8RJhF24HGuu0oYR9ihy6LTpGzkUIBO5HJbcYowiVARlPQsbuSz4DSH+/LL0T42w4lf+Qq1r79E4gQgIXECal9/iRO/8hXax2Y23T+SMa92Fxi3iiy7bVa8Nk7kwzpFkADx+rerBCIZESURkUzWz5FgxWvzUPXIpjGUAQxVS401r0IkuHG4rcLk9YBQSmC8DZJlpNz8/Z3GPC6Ddhsok2/I8ezihwtvuF7sSmMOGz0UqtUqe/bswbbtYfxkqVTivvvu29b4cWO6hed5zM/Pk8/nGR0dxXGcoTmjoigcPHiQtbW1oTEjMDR8HPgvDNQIA1XFRlLAdd3h+INhGMOxENu22bdvH51OZ2iQWCgUWF5eJgzDLSRLkiQoirIeF5cMlQ1RFA3Jh51SFG4kCeT1wo9CKsQudvFmgaFrvPueQyzWOrx8fhlFCPZWi0yOFkHC7GorNYJUVDq+Rz5r0u0HqKpAV0Xa9ZAJSpL+XVXSLrYKCEUQJ3IL2XAtxm4S6PQ9ClkDQ1UpFrIUchblXIZ/OXaa/+M99/Leew7zwrnF1FlepMaVb711L7dOjTE9PsJTJy6y1uoNN2YjeYuH77pltxi4ARRzFo/cfxuzay2eP7OAJCWpRks5gjDm4koLsb4Ouo5PtZil3XfRVGU9FUQQxjGqUFAV2NiwHjl8H4tP/cO2ryvjiKVn/onu3Ckqt9zFrD3B7fe9HU1TCeMYoaRFpaoIsqZOKW8xks8RRpJ/PXaa//TwXbzn7kO8cHaBWruPlJKMqfPOo7cwPVamkDF56tWLdHoeYv37dHqsxH2H975BZ/bNiclqkQ/dfxsXVpos1buoisqdB0bIZyy6fY+FWjo6qqkq3b7HeDlHt+/z/7P35jGSnved3+d576Puq8/p7pmem8NLlEjREkWJtqxjnV3Y2CDBYrNZmDJswwkCSzbs7P6RBIEBA/tHgCBZw97DXqyRDbyRhcTY2I5kWbIsmeIhkkPOkHP3zPR0d3V3Vddd9Z5P/ni7aqanu4fDazgk6wMIYvdUVVdVv/3W+3yf7+/7NdSkKpc4aaBIdjmj0bnkTscKQpA7/Ojoy3zaoZhxSNvJ5s653oBc2kYAmqeQsk1yKYepfJrLK5v86MxVnjq1QBzD60urNMMYkGRdm586uUA+7RDHklcvr+xY9J6cn+Tg5HgT5P1EEQozToGNQWvfUQpbNZh3yjyUd5J8Ba9FPwqYtHIczUxxOD05apW4lXbQ5/naRba8DqpQSOkml9pVLnerSYuKotD0eyhCsOCWmbLzXOlUqQ6aWKqOFFDtN/d0NQxWtrj0O98i3qvmN4qJo5hLv/MtHviXz+5wOGz5Pa53a5TNDO2gjxcnzkKBQIHRzxKAQBm1XvQjD4TgaHoKcw/3BiTCzJH0JG80b1DeJwxTSokfhSyk9h45fz9Q9BPEOBC+gowawHaNDQYYjyG0Y4g9mkbGfPS552LDWy2SLcuiVCqRSqWI43hUb1mpVPZtFbi93aJQKOC6LrVajatXr+L7Po7jUCgURhZ/TdNYWVmh0+mM3BZD94GqqqTT6dEieSguSClpt9s4jjMSKfr9/sjt0Ov1yOVypNPpUTtEs9nEMIyRWHFrXsFQZBg6JIbfk1JimiaZTGbfcMd32gTyfvNhaIUYM+ajgq6qLEwWKGYcLq5sEkYxqqKw1e7hR8mOcTgMoxICU1fp+SGKomIbEi+MiOJ4FOqliiSUTdueHb2VtxPstt7sYGhZHEsnl3KYm8jhhxECwYXlDT557ACff3iRTj+Zu3btm+MTadvki584Sr3dGzVTFNLOWGh4D7BNneMHKmQck4srm2RdCyEEtVYXRSTBe8PPJEURqIqCtz3yIJAMgohYxig7lo+gGhaLX/2lHUKUUHVkFGCkixz66tfob1wnowUoiqCxdIbi0cdQhEATKsu1Fo6hk3YsiukUs5UsfS+g3fe4sdni4FSBL33yOJ2+hyQ5RobHQzmX4qtPnKDW7BFGEWnH2jVyMeadkXEtHl6cJkayUmuSsi2klKw3OpimThzFRHGEEAq6phFEMRKBrRsEIth2T8Uo2+cV2PtYUTQDhGDxq780OocIAU8en0NVFE7MFXntSnVb9IpodAbomkI+bVPJpZgspuj0fVY2mzQ6Axani8xP5On0PVRVIWUZo2uswzMlDlRySVCqhHzKHo9n3SMW05Nc7W6SkhbqHovOII6QAh7IzuJqFraqY6p3/t10wgHfr55FCMGEfbPhYNg08e3V1ziUKnPALZEzXPRtsWIxPUlGd3i9cRUhkjGPvVj70x8n4bh3IA4jqt96nvlf+9Loe6pQ8OIQQ1UJZYSt6aR1i81Bh1iRGFIQyQhl+/lEcYSmqFiqTrzdVPFS7Qp5M0VK230+O5iqcKWzTivokdF3ijdSStYHLebcEvl75GwYoujzSO0AxHXABzRQCggxzkL5OHPPf/t3WiSHYUi9XmdrawtgNFJxp0Xqfu0WlmUxMzOD7/tcvHiRubm5kUAw/Pe5uTlu3LiBqqojV4GqqjtGJIIgGIkCpmmOWhWiKOmXV1V11DDhuu7odvPz89y4cYOtra2Ro8K2bTKZDLVaDUgyGoaPM7yNZVkjh8WFCxewLGtPoeV+dhGMWyHGjLm3pB2LuUqely/ewLUN2j0PXU0aJWxDo6cmnfQIgUCSskw6Mgl1NDUNXVMJwmTmujdInGS3LhDg7QW7SSk5uTBBxjFxLQNFCLwgopJ3ubHZ5JPHktDa/cL7FEVQyo5HJt4vyrkUhbTDVqdHMePS6nlYpk4YRtimnrhaZBLCKANJ2jHZ6kgESaioAIQf4t9ib0hNHeLUP/kfaVx8Ga+5iZkt0autoGgGTr5CPp1C6dWQikqj2WJGejx2dIYrq3X6fsDhqRJp18KxdKRMbNeFjM1qPREbFEWQ2UdE0FWVycL+Lr8x747FySKGptEf+KiqQhBFuJpBNwjRNQ1DAy+MMFQFX0DK0am3Q0CQspPjqTvwibdPH3sdK7nDj46EBkUIFqcKrG616Xk+lWyK43MVZksZLq3WcO0+lYxL2rWwzWRkK2Wb25kfPQoZB01VyKX2zgczdY3p4t7ZAWPeP0q1kLI6AAAgAElEQVRmmgdzB3itcY2s7ozqMqWUbAU9ltrrpHSLH29eBJLj4FBqgqOZ6T0zGgDONVcIZUTR2P33nzUcpp0cg+1xgqHQIKWkGw7oRR79MOCgU+Zad3PPucHaX5/ZaePaiyhm87uv7xAbBDDt5DFUjc1BG1vVKVtZ6v4lwjhCUzRUoYJMgh0DAYpM3GO2ZrDpdbjcqfIXNyLmU2Ueyc/vCL20VIPPVU7yd5vnqfabGKqGKhT8KCQiZiFV5pH8wgcSyC6EAuruYMsxH18+kDGKvRbJvV6PpaUlhBDMzc3hui5RFLG8vMzKygrHjh3bc5f/Tu0Ww58nhKDZbFIq3Tz4h80U1WoVVVVJpVKEYUg6nUZRFAaDAd1uF1VVEUKg6/pICBiOOQCjsMooikin0wRBMHpdcRwzMTFBGIZ4nkcmk0FVVer1+sjBMBQahmMlw+aGdDpNHMeoqrrvezB2EYwZM2bIzz52lEsrm6zVkzT4vh9iaCr5tE3P84llnOwMxzGQWNYRktliDgmsNzrEcXJe6g4CNFUhuiV87+0EuylCMJFPo6kKcSxpdD3KWRdT1wjEvariGrMfuqry9598gH/95z9ms9nBCwKiOHHFFDMpgrBJFMV0ez7x9mdVytKwdJW5iQKNTo9eP2Cr16c3uGkvVnVzR5OA21jnwv/9v3HkU89QMXwCxSaIIqZyWU7OFpg/eJAoilmtd5goprebmSLafY9DU0WkTEZsxnywZFyLL3/qON/64WtYhkbfC5ASdFWhnHWotfqEYUQQJPWoAoWMYyGAhck8N2otUpbORqtHuK1g3n6sDBECHjk8zaOHZ6g1ulimxtMPLzJZyNAb+PzJ919BXd+isi0ueUHIwA85OlNmEITj4+U+50R2lozu8EZzmfVBCwH4cUi13yBnuMy5pdGoRCRjLrarrPa3+Fzl5K46zEEUsNRdv2MwZVZ3WRs0qHltJu0cXhRwvr1Ky+/jRwGtsL9dH6kkrQm3Eff3/sx7q9vFSMI4Ime4HEpN0AkHKEKQN1KsD5qEcdJAJwRJaLNM3Aw53WXGLRASMeMUqFgZrnc38aKAJ8tHdzhCUrrFT0+eouZ1WOnX8aOItG4x4xRI75H1MGbMB8UH4mu5fZHc6XRYW1ujXC5TKBRGC+/honvoXjh16tSuBfSd2i2GlEolNjY2RmLDYDBgZWVlJBgYhrHDaaEoCpqmYds2qVSKra0tPM/bITwUi0ktTzabJZVK0el0MAxjx+vqdru4rks+n0fTNDqdDnEc47ounU5nR0ik2E5utiyLcrk8yoN4q/dg7CIYM2YMJAuCX/m5J/n/fnKeizc2ub6xRRBFKIrGkakyS+t1BgMfU9eYyKXYbPcpZlweOTxD3w/QVRWhQNaxeOnCMrqqsN7sjR5/GOy2n+BQe/N5+rUVjHSBqUPH2Gwcw9m2Lx8oZzlQzrHZ7PLgoXFA1P3A/ESeX/m5J/nOS+eJIkmt1aXv+WRTNvMTBZY3mwx8n1zKxjUNau0eM6UsR2bLbDY7XFtvMDeRozPweeNqlTC+bVtQSnTT5vDjP01B6SFEUncpI0hZxnZQs8LR2QpCKGw2u5i6hq4qHJkpM5FLUW10mJ/YndE05t7zxIk5UrbBj84s0R149L2QTt+jnE2hayrrjS4DP2CykEYiaXY8TsxXmCxkcC2TzWaPI7MVLq3UWKm39jRJmZrKEyfmWJxKrtVUTcEydGbLiT0+41r83KdP8m/+/Hnq7R6qkrRSnJqfxLUMBkFIJXfnlq4xHzwzToFpO08nHBDKiFe2rmKrBgVz5+9OFQplK03N6/Dq1hKfLh/d8e/9yEsyEO6QAzBj51nt1+kEAwIz4kxzeVsEcGgHfQwlqVItm2mu9+u77q/YRhIK+RYo9s61iZSSL0ycRFd1XqpdJh1ZrHuJA6Fopmj6vdGIoyZiVKFQtFJUrCxp3aYV9imaiQBb3g6avNGrk9IsJBJXs7BUHUUolK3MvtkNY8bcD3xgQzS3LpLX1tZGOQn73dbzPOr1+q5F9d1UQOZyOdbX10c5BisrKyiKgmmaaJpGFEWoqkomc/OPdSg0KIqCruujPIghlmURxzHdbnf0OIZh7Fr8q6pKu92mVquNqizb7faO0ElIqoPS6TSlUml7dyfc8boURaHRaPDcc8/hOM5b5liMGTPm40c2ZfMPn3qIWqvLv//OS9yotZguZlAVBV1X2WwlC7rHjsygqgqnL6/S6XvEMsY2NUrZFFnX5vpmEwVo9336fpIqf8dgNyAKfTQ3Q7o0xWdPzvH48Tma3QGFTNLKs9HsUso4HBoHsd03zJSy/OMvPsbyZpN/9Z+eAwHFjIuQEsNQaXYGZB2LJ47Ps9nqcqVap9UdgBS4lsGBcg4pkxpKAazW2ihKkvcQhSFrVy7gZIpstrvISCJUgUWEoucolivEUqLrKs9+5XF+dOYqURyTz9hEUUy10eHQVJFydrx4vF94YGGSIzMlzl6r8u+//RIT+XTSEpN1cU2Ddt9nupThsSOzvHGtSqvr0eoOMHWNjGOwMFkg41oYSxq+H9Dse5iahkQSRcnObq3VodP3CcMIXdN48NAkjU5/NBIxWcjwj376UX74+lVMXSXrWgyCkI1ml08cmR3nL3xIEEKQ1m26oUfda1My918sFwyX5V6dTjjYlV9wq2blRSGbXot2OEBFIWc45AyHvJmiEfSwBg36oU9uO6BSEYJ+5FOxsyiitGf1ZfELD7DxF6/eeZRCVSg9c2rHt8pWhl4ckNcMZpwClztVDqYmCOOYLSGIkfhxiKOYREToQmPBLWOoGg2vy3yqjKkmS7Qgjqj7bf7D0t9yJH1TrJ93yxzPzuBqe48jjhlzv3BfJHbcjTvBtm3W19d3iQ23tlsMRyNubYPIZrPYts2BAwcIgoCtrS2CIBiNaQxHOKampvA8j3Y7qWcbjiR4nkev10PX9VH9ZTqdHo1BDJsrJiYmdmRCwM4wzOHoRCqVYnp6euSWGOYzDMcshuFcqVRqFO7oeR7Ly8uj11SpVO5qxGTMmDEfP4QQ2KbBdDHDdClDdatDEEZMFzPMlDKs1tu0+h6ff2hxu6IyJJeykVLyxrV11httJrIp1rbalLMu1zebyfz+HYLdCsc+RX9zBa+xyWZzg1/93/8njhw9xtX1OtfWG6hCcOxohQPlHLo27rK/n1AVBVPTeGB+Aimh2mgjgcWpEmEYsVJr0g8CPnvqICnHwNQ1XMuk7/m8eX2DRqfHVCHDar3FVDFFGEmCMKTrwaEHPsnq+VdpbKyjqSqKAuliAXf2GGtbHZxtwWK2nOMrT9hcXqlRbbRxHIuHD00zXcyOg0HvMwxdw9Q1PnFkliCKqLW6aJrK0QMVBl7AeqODIgRf/uQJXr54g2zKxDYNNpsdLq/U6Q0CJvMpVmst5itJm0h1q83ADylkHNpdj74WYRoqGiq6qvDtn5znMw8sjHIWDk4WyTgWl1ZqNLp9KrkUi9NjYerDSMPvAkkj0n4kGWqw5XV3iA1pzUYTCkEUUh20uNbbBAGGUJHAhtdEEQp53WXeLfGjjfOoIqmV9KJkFCilWZT1NBNmluc2L+z62ZO/8AS177xOfAexQdFUJn7+8dHXtqrzn899Gj8OCeOICTtHK+yzOWhxwC6iCIWKmWXTb2MpOg2/y4SdIyKmHwVkTZdT2TkA/DjiTOP6dnUmIwdDLGOu92qs9Rs8PXGSlD4OxR1z/3JfiA13405QVZV+v7/r+8MFvWEYLC8vI6XEMIyR86BWq+F5Ho8++igzMzP88Ic/xPM8traSmi/btnEcZ+Rc6HQ6RFFEu93GtpMduaGQEQTBKABSURQURSGTyTA3N0e/36dS2VkxMwzDjOOY2dlZlpeXCYJgNB4BidVKVdVRtkQqlULX9ZGoEYYhy8vLaJqGaZoMBoPRc3qrEZMxY8Z8PPGDEE1VKWVdJvMZ+l7A6SurRFGMYxqEYcyZpSqmrpJxTFo9DyEE08UMc5UcBycKfPvl88SxxLqyxsUbm8RS7hvspigab/zHf8H8Z/4BX314hi98/ml++7d/m1//9V/n2Oy9q94a887wwxBdUynnUsyUs2y1e5y9VkVTVEwzEaRevbJCPuXg+WHibgDmKzlOLUyQTzl875VLSGI2mj2W1mpkHAvHTCNOPY7i91BkiBQaD504wmQ5zxvXN3j44BQPHUx26tK2ycOL0x/k2zDmLun0PdKOSda1ODhZ4MZGk8trNSxDxzI0Gt0Bze4qU8U0ze4A3++jKUlzzqfzKQZhxEvnr6MKQRhLen5I2pE4lkF34DNRSG8HdEeUcimyrsUL567z955IjzIZihmXYma8yfJhJ5Lx/sHDt5DE0+68naaoHM5M8TfVszS8LlnTQeEW0UI16IYe13s1vjzzCJc766z2t/DiEE3RsFWDTjDgXHuVw5lJjqSnON9e5dbSZ2s6z+I///mk/jKMdjocVAVFU1n85z+/o/ZSIPji5EN4ccCL9ctYis5iapKs7nCts0EoI5qhx0G3wqSdZam7iaOZmIpGJGNmnAJZI9mAvdrdYBD5ZHSLbnRznEMRymgc48X6JT4/8cDbfevHjLln3Bdiw63uhP2IomjPxXShUOD69essLS1hWdaOx1BVFU3TiOOYjY0NcrkcjUYD27bJ5XIoijIahdjY2CCTyZBOp7l27RqQiCBxHKPr+sgF4bruyI3gui6Tk5PEcUwcxwRBwOnTp0f5D5VKhYMHD3LlyhXiOGZmZoZer8fW1haapuF5HnNzc0xPT7O6ujp6nVJKZmdn0TRt1GZx67jH7e/dfiMmY8aM+XhimTqxhDiWKIrg2npyHsm4Fu3eIKmMy6dYb3Q4PFumkk0x8ANsM6mZ7HkBl9fqFDMOjx6e4d99+0UurdSTEME9gt0UIVj43D9k0fH4X37nf+C/ffa/4hd/8Rf55je/yR/+4R9y/PjxD+idGHM32KZOvH3BH0vJpZUatmFg6CphJyafdsinLNa3unz21AKqqhBGMWnbJONarNXbrNRbFNI2rY7H9wX0/ZBWt08Ug53JU8y4OKZOL4ho9wboqsLhmdLY9v4hJJdyuFpNWsO8IGSpWifrWqPWmXzawdAUaq0eP/3oEQZ+CEjyKQfb1HnjWpWBH5CxTertHpqqYOoal1Y2ieIYPwyZKmSwdJ1O36eSS9HsDqi3e+NMho8YjmrsVQKxBxJ7j0aKeadI0+8l9Q9SJgmj2/Qjn1BGnMzO8qP1c1ztbjJp5zCUm9fRed1BEXCutcKMXeBSp0p4W1Bk7lOLPPAvn6X6refZ/O7rxH0fxTYoPXOKiZ9/fIfQoAmVn5l8kB9unsNVTeacIhtem9V+HVs1WExP8GT5KH4csum1UYRgEIU0gi6aojBnl5l1Cggh8KKQjUGLjG7RCz0Ke9RYZg2Har9Jw++Su8c1l2PG3C33hdhw67jBfvT7fWZnZ3d93zAMSqXSyDWQ9IMro4pKRVFGzoNXX311lKswXLQPsxoMw6Df7xMEAZZlYRgG3W4XXdcxTRPHcfB9f1Qj43keYRhSKpVGbogLFy6MxiqklCORYRgmOXy+s7OzVCqVUbDk+vo6uq7T6XSYmJggnU6PRJNmszkSWXzf3/FYQ/YbMRkzZszHE9vQWZwqcGm1TiFlsdnqkXFMgjBCSijnknNtzrW4slrj5NzEjvs7pk7atfDCEMcy+OTRAxyaLPLa0iortRaqoozOhXEc8/ixOZ78haeYLiUWz0OHDvHd736X3/u93+Ozn/0sv/Vbv8XXv/71XWLpmPuDYtoln3ZodAZoqsALI7KuTt/zsQyNnGshhMAyNZY3mzx+fG7H/fNpO6nDRJB2Lcq5FIaqcKPWptP3KWdcDEPDDyJsQ+fwTAmBwNDGzQEfRmbLWc4srdHzfLp9H0mSK9XqDihlHWzj5qVlqztg4baclkouxWtXVtE1Fcc0EAhsU6eUcQmiiJNzExi6Rrs3QL1ljCaK36KCcMx9ix+HrPa2aAY9VKFQsjKUzTQFM4WrmQwiH0vdW3j0ogBbNfZsnah5HRbcMr4MWes3kSTHiATSmsWxzDSOZvLXa2coGCkiGQE3P4eEEMw6RRzV5Hq3ziG3zMVOdZeLwprOM/9rX9pRb3k7qlCYtQvEUvLcxvnkuNYMjmdm0IRKVnf5RGGB/HYQphcFbHptjqSmeL52kflUeUfF53B0QspknGLK3jssVwhB3euMxYYx9y33TGzwfX/U0nDrzn+hUBiNG9zaCHH7fRVFGWUY3E673ebQoUP0+30ajQa+76OqKsVicbRw73Q6NJtNJiYmqNVquzIiLMsaZTCUy2Usy6LX69Hr9UbOgmG2QrfbZTAY7BAM6vX6aBwiiiI2NzdH4oeqqszPzxMEAYqisLi4OMpYSKVSTE5O4vs+r7/+Orqu73BnhGE4qtxUFGVPQWa/EZMxY8Z8fHnw0BReEHJlrU675yFjia6pnJybGC0GFEUQ3d4iQHLx8ujiNN8/fZkokkzmUwz8kCdPzHN5rU7etUBJqjGPzZY4Pj9Btd7BNQ1evniD1VqLQRBy6rNf4v/99lP81tf/O/70T/907HK4T1EUwU+dXOC5s1e5trGVHC9S4lg6Jw5MjHITFLH3gs/UNR48NMUrF1bIpiwKaYdGu08uZXGgkmNhIo9QBJ2ux8n5SSbyaVY2WsSx5MdvXqO61SaKY6YLGY4dqIzCAMfcn9iGzlMPHuRHZ6+y0ezS3q79K6ScUZPEkHgPi3wh7XCgnOf6RoOca6GpCt2BTxjH5FwbQ9e2A7QlxbRDLCVBGNHsDri4skmt0UUogoOTRY7MlLDN3TveY+4fljrrvLK1RCQluqIm+UCtG7iqyROlIzycn+dvN85RMhV0ZeeyJIhDtvwuT5aP7tk60QkH2JrBjFlg1inSCz1iJKai4WwHJ9a9DqGMmHJyXOtuYqlGYoSAUa6CoWgEMuRYZppTuTn+7MZLhNt1lHeDisJBt8KnCge51qsTy0SuiIOYlt/jZG6WVtDnBxtv8oWJB0jrNqaqM+MUmHEKaKrK641r5I3USHAY1mc2gx5zTmnfOktl+7Zjxtyv3BOxodvtcu7cuVEuQiqV2hVweOzYMc6dO4fnedi2jaqqRFFEv99HURSOHTu2bybBMPPBsizy+b2Vv3a7PWp8qNfrhGGIEIJ+v0+32x3VYHY6nVFY5DAEchgcqes6tm2PHBaLi4tUq1UajcZ2jVcy6lCv10cZC8Ovi8UipVLpjhWWe70HQoiRw2J6enrPUZP9RkzGjBnz8UVXVZ48ucAD85MYmoofREwW06jKzQu2Vs/btes4ZCKf5guPLHLmyhqdnodAYuoGTx6f59pmA01RcCydhckCV9fqLFUbXFmrsdXu4doGhyaLtDWFtX7Mv/rjP+Hb/8//xVNPPcVv/uZv8o1vfGPscrjPcC2DZx49zHqjA/IsuZRDPu3c6kqm74XMlLJ73v/oTBlb1zl7fZ2UZVLd6lDKulRyLtVGB00oVAoZChmbs0tr1Dt9Lq5u0BsEZFyLo7Ml1rbaXNto8IWHD1PKjnfp7meKGZevPn6cpbU6f/XyBaZLWdL2zVT85PopERZuRwjBp44doJCxOXd9g0LaZnmzycHJAu3egPVGB11ROFDJoWsKL51fJo4lb15bJ4xjShmXIzNFLtzY4Nr6Fs88cng8jnOfstRZ58e1i5TNDLqy85zfCz2+Xz3LFyZP8WTpCC/VrxDJGGu7hWEQhahC8ETpMLPOblcvJGMLw4W2rqhkjd3HWzf0UIVCVneYtgus9OsgYSvs4kUBAF4csu41OWAX6ER9TmZmWOpu0AoHdxQcNKGgCoWnKyeZcQosdTdQhcBWk7+FTuhxsbPGYmaCrOHQ9Hv8pHaZI5lpWkEPQ9GYsvOcyMzgqiZnm8usB/3R+xPKiAcys1Ssvc+7AJGUu1o6xoy5n3jfxYbh4lrX9R0L4r0CDk+dOjVyPwzbIGZnZ9+y3vFuMh+GrglN05idneXKlSs0Go1RtaWqqgwGAzqdDtVqddRA4boujuPgui5hmFTADbMgVFWlWq3iuu7oZ/f7/VHo4/C2qqqytrZGqVTCMAyazSbPP/88jUYDz/MwTZOFhQUWFhZ2vQepVIogCJicnNz39e03YjJmzJgxGdfi8w8f5q9fvUjfC0jZJlJKmt0BihAcmS7te99yNsXnHzlMGMWEYcSNWpPLa3UsU6M7CEjZBtVGhxu1FovTRZaqdQ5UckRScqVa56heppRzOH1ljWe/9kt8+ctf5tlnnx25HE6cOHEP34kxb4UQgol8mqceXOSF89fxghDL0IjimK12Uj84Vdy7ok4IwdxEngOVHGEc4/vJLP/1jWYSShrFpF2Ly6s1ugN/e2d7i9lKDj+MePP6Bo8sTqOpCi9fvMHPfOLIaFRnzP2JqigsTpfYave5tFrD0jV0TSUII+rtPgsT+X1dKpqqcGy2wtGZMmEc0+l5XF6tsVJrsdHsEEtwTYM3r29gaAqWkQRnpxyTvhfwxvUNHj08Q6s34MKNzXG46H1IEIe8snV1T6EBwNFMQhlxpnGNz1SOM2HnWOnV2fSSVriSmWbaKWAo+1/bl60MUSPa998haW4QQuBqJo5mstKv80pjCQnoQsXWDCyhA4LznTX8KMkYmbCyFGWKbujTCvsMtgMaJeBqJlndoWRkeDg/h66o9COfQejvqKJ0NZOa36bp9zGtpHniz1deIaWZ6EpS++pqJo8VDvFU5QRfch+mGfTw4wgNhZe2roye/174cYip6nuOmIwZc7/wvosN9XqdOI73FQtuDzgc/u/tcDeZD3Ecjxovhm6FoXNi2GARxzGu6zIYDIiiaNT+4Hke6XR6JGpsbGxw+PBhoihiMBjsyFHodru7RAFd1+l2u0CSwXDhwgWiKGJ2dhbLsgjDkHPnznHhwgU+85nP7HgPhuMV8T6zim81YjJmzJgxpazLFx4+zOnLq6w3OghgqpDhwYNTpOydHd1BFLFaa7FWb6NrKrPlLKWMi2bqLE6XWNwWJ+JY0vN8Xr60MgqeVBUBQqAKQco2ub7eoJxLEcUx9XafgwcP8p3vfIff//3f53Of+xy/+Zu/yde//vU7CsVj7j2HZ0oYmsrrV9fYaHQRAg5OFjg5P4l+myOl7wcsbzSpt7o4lsFcJU/WtdBtlQcWpnhgIWmbCKKI3iDge69eZGFS5/zyxsj+bmgqgaayUmtydLbC+laHnhfgjnerPxQ8emSGlG1ybnmdIIzQNZUHD05ydLa867bt3oBr6w06fY9c2uZAKYdjGeTTDo+lHR7bvp0XhLR6A7778gXK2TQ/fvPqyDlhmzrN7oBas0sll+Lyam0sNtyHVPtNQhntKTQMSWs2q/0GnXBASrNYSFVYSN19g1HecCmYaZp+b09XA0AoY4pGmiCOeGVriSuddWbtIghBJCN6oceG1ySr2UQyJiLGUDRszSCWEk1oHHTLOJrJutfiU8VFjqQnOdtYpuo1R6/PjyO4TRMYftkO+tS8Dj/ZukwsJUWjSGb7+fYjn79dP8f6oMkvzH2avHEzBPUThYN8b+0MqlB25DkABHFEzevwZOkI2h3e4w8LYRBSvbrBxnINGUty5SxTixNYjvnWdx5zX/O+X+Gtr6/vyke4nXcbcHg3mQ/ZbHbUAHHhwgW63S6u645GOoatD5lMhnY7UVXDMBzVYrbbbbLZmzam4QiGae78I4jjeE978DAP4o033hg9x1v/3zAMBoMBP/zhD/niF784Ekb2G6+42xGTDxN3yvX4KLy+MWM+SEpZl2cePYwXhAjA0Hef/vt+wA9OX6bR7WObOlEsOb+8weGZEo8uzoxm9yGZ80/ZJs1On5Rl0O4NELdcaemaSt8LCMMIIRlZURVF4Vd/9Vf5yle+wrPPPss3v/lN/uiP/mjscrjPmJvIM1tOXAeqKnaJDABb7R5/89oVgjBxQPi1mDeurfOJwzMcntnpmNFVFVOXBGFMLpUce7del1uGRqOTVGoKkXxmjvlwoCoKx+cqHJkt4YcRhqbuGNcacm29wfNvXkMoYGoqy5tNzlxZ46mHDlHO7myZMLfPT6qi3jzv3HLAGJpKqzegkk+Np9XvU5pBD13ceREshEARgl7ovaNRACEEjxcP8/3qWTa9DnnDQd3OdvDjkC2vy4JboRP0eXlriVbQTWomt0c1JCqtILmWjqUklBGG0AjiiEjGqELBVDUaQQ8JTNk5OsGADa/NkcwU1Y3mLc9GcrvaIKUEKejHAW80lnFVM6n7vMWpYKsGE7bGpXaVH29e4JnJU6N/K5lpPls5zgu1SzSCHpaiIRB4cYgqFJ4oHuaAu7878cPC+vVNXvr2qwReiOWYCEVw48IqZ374JieePMKhhxbGTrcPMfdkjGK4cN6PdxtweDcL8kceeYSLFy+ytLSE53k4joOy/WE4HI8YVmSapkkQBIRhiKZp6Lo+qsi0LItKpUKj0WBqaoqpqSna7fboNSqKgpRyxx9FEASk02mq1SpxHI/qOG/Hsiz6/T5LS0ucOnXzZOO67jseMfmwcDe5HsNQzTFjxrxzzD1EhiGvXV6lM/CZyN90icVScmF5k8l8iplSbtd9bEPHj0Jyrs21auPm/W4NnhSQT+3cdVpYWODb3/42f/AHf8DnPvc5fuM3foNvfOMbe7oc2n2Pa9Ut1hsdwijG0FVmyzlmS9k7vp4x7w5FEVjG3u9vHEuee+MauqaQu+UzPoxiXr54g0ouRcbduXjQVAWxHTJZyrgsrdVHolcYxSOByrWMsavhQ4iqKNjG3g0jfS/ghXPXyKYsDC1ZgKaBgR/wozNLfPWJE7sELV1ViaVECChmkrYU106Oi+Q8oNHsDpgr7z4vjfngUYVy1wGLyu2WgLdBSrf4wuQDXGivcrmzjiTJC1GAA26RebfMaq/ODzbeZGPQJImelrEAACAASURBVJaSjjrAVgxUodAOeggU+rFHLCWKEPhxiPDBUvVRDeWkpTNh5VgbNDilH+Ch/Dwv1C7hRQGmqm+HW+58vV4c4qgGNa9FSERateiE3q7REE0o2JrBG41lHi8d3iG8TNo5vjL9COuDFhuDRNzIGS7TTn5XoOaHkfraFs/92YtkShly5Zvn/VTOJQojXvvBm6iqysKpuTs8yntHr91n5dIa1aUNpIwpThc4cGyGVG68BnmnvO9H6d3kKbwXAYe3L8jb7Ta+n8xXmabJ9evXieOYVqtFo9EY5S4YhkG73SYIAkzTHI0lpFKpURuFruvoenLCKRQKhGGI7/scO3aMer3Oiy++SBAEo4yHdrs9ej1RFBFFEZVKhaWlpdHYxH4jH67r7hIbhu/jOxkx+TDwdnI97oWwMnZYjPk44gUh19a3KN4WzKcIQdoxuLhS21NsODxd4rk3lqjk0xSzLrVWj7Rt0PUC8imLervHQ4em91y0KorCr/zKr/DlL3+Zr33tayOXw8mTJ4FkgfLyxWVubLZQFIFrGUlo7sDnJxdu8PKFZY7MlHlgYRJNHdco3ku2Oj06A49KbudmgqYqKKrgRq25p9hwcKrA5ZUa5VyKta0Wrd4A1zToDXxmy1la3QFPPXhovIv1EWO13kLGciQ0DLEMnVbXo9bsMVnYeV2UdS3yKZt2b8CBcp566wbdflLHGkaJg0IgOHZg97jGmA+ekpkmfIu60mg7j2C/poW7xdFMHs4vcCI7S33Q4UJ7leqgyY1enevdGs9vXqAVePRCH0VAICPacsAg9AlkRNF0URF0Y4+ikaYZ9LE1A10oKIqCqeioikoQh8zaRR7KzzNp5zicnmSpsw4kDgVDSVwRmlDw4xCJpGQmuQ+G0PCiEEczdo1EDO/fCLo0/d4ul4emqEw7eaadvUPwP8yc+dE5nKyDae++vlY1leJ0gbPPnWfm6BS68f42zyy9fo3X/vYNhKLgpG2EEFw5fY0LP7nCkccOcfxTh8efTe+A9/3qrFKpvKVrod/vU6nc/YzWfgwX5IuLixiGgeM4FItFstksYRjy+uuvjwIZFUUhiiK63S69Xg/LsrAsC13XRzWTrusyOTmJ67ojcUAIQS6XY35+Htd1mZiYGFVXDh0HkLgZfN8nCALy+Tz5fJ4gCEaPsd9oyXDU4+PE3eR6xHFMvV5/359Lt9vl9ddfZ3l5GVVVSaVSqKrK8vIyr7/++ih7Y8yYjxphFAOJpfV2hjvOe3GgkuPgVJH1RodKzqWcdahudQjDiOlilk8fX+D4gTuf34cuh2effZann36a3/3d36XZ6fHXr1yk2uhQzrmUsi62qWMZGq5lUMm5FDIO55Y3eO6Npe3nP+ZeEYTxjrGZW9EUZd/j5YH5SXIpm3q7y3wlj2sarNRaGJrKbDHPFx45vG8I5ZgPL14Qoqh7Hy+CJNNj1/eF4PHjc8QxdAY+h6aLCGC11iLnWhycKvLMI4dJO+Mk/vuRgpkio9t0wsG+t6n7XQ6lJjD3WHy/E4I44uWtK9T8DmUrTdnKEMQh7WCArgoczSRvpJiwMkyYGUxVRwAKKpqqIeNklMLWdIpmCle3OZ6Z5oBb5Gh6mscKh6hYWRwtcUU8UTrMlJ1HimRsxNUsmkGfVtDHUDVyhstcqkwQR9S9Nqv9LbrBgOu9Ot3Q2+GDEIiP3UhQq95mq9rAzeydtwGg6SphELF+bfN9fS4rl9Z45XtnyFVyFKfy2CkLyzXJTyZfn3v+IpdPL72vz+GjyvvubLibPIX3MuBwr13yMAxZW1sbORQGgwGapmFZ1igA0vd9dF1H0zR6vR5xHI/cDEIILMuiWCyysLBAu91mZmYGSBbCDz30EGfOnKHdbuN5Hq7r0mw2UVWVdDrNwsLCyA3R6/VIpVJsbm7iuu5o5GNIGIa7ciA+6tyLXI+74X5zWIwZcy+xDA1dU0Yz17fSHfjMV/beUVEUwSePHmBhssDyeoOZUo4vffI4lbyLtX0OvRuEEPzyL/8yX/rSl3j2a1/jj/74/+C/+e//Zx588NS+91EVhYl8itV6m9OXV/jEkXErz70iZRtJl/xtY4MAfhBRTO9tOTV1jacfXmSt3ma11mJuIs9MKUsh7YxHYj7C5FI2UbT3UiqGXUG1Q7Kuxc9+8hg3NhtsNrscm60wXcyQTztjN9N9jiIUHi8d5nvVM4RxREZ3RmJ2JGPqXoes7nA8896Fe75SX9p2KiSOqyCOuN6vkTFsYhkTa5JW0GfWKOBFiSDgSZXudkClLyM2vTaublHzOgRxiAqUrCxTTg5fhqiKYLlb42zzBjoqh9IVVnsNImJ0RWXeKXG1t4kfhWR0m4bfZbW/hR+HHHCLmIrGIPS4GvTJGg5Tdg6FZHTDVg0c7eNzfTnoeog98l1uR9M1Oo3eXT3mMO/n7TgQ4jjm7N+dI1fOoOm7c0YUVaE4XeDcC5eYOzH7vjssPmrckzGKexlwuNcuebvdRkqJrusoioKmaYRhOGqTGGYl+L6P7/ujsY/hoj8IAlZXV3nooYfwfR8pJUEQcPr06ZGIMsxv2Nrawvd95ubmRk0b3W6XjY0Nstks7XYb27aRUtJut+l0Ojvs+d1ul2PHjr0n78WHhfcq1+Pdjj+83eaUMWM+SqiKwgPzk7x4fplKzkXdvpAf+AFRJEctFHuhKIJKLrXLUr8fcSypNtpcW28QhBHTxQyzpe0AXivDN37nf+Xf/tt/wz/7tX/Kf/Zf/BP+/n/5X5OyTbrNOv1uF8OyqUxMom0vTktZl0urNY4fqOC8zVl/KfsQbwEKKEWEGF9E3A0p22RhosDV9Qal7M1FRLM7wLF0pkv7uxN0VeVAOceBu5y1lzJAhssQXwcUhLoA6hTIATK6lvz+RAqUPIIIUEAtI4SNlDEQAncvfN3xucRtkG1A3z5exgveu2GY4dHo9Ed1mFJKNptdpvJp8vtUZEIihN7ahPNWSNlHhksQrYFwENpBUMogm8jwKsguiDwoKQQhCAOUCkLoSBkBEUK8+2vSJBxwC+QAhAUi/7GzYOcMl2cmH+Rs4zo3+vXR7r0qBIvpSU5kZ+5Ybfl2aAd9VvtbVKyb556G1yWOJXnDZbXfSJwWwYBW0KcTDTAVjVg1aQU9PD9AFQqaopLWTBShoCsqN/pbqEIljCPebN4gb7hcQmCqGrGM6YdBMuZgF+gGiWjxQG6WnJGi2m9wprHMFyoP8NLWZTQUBAJT1TGQtIIeqhBMWDnawYCHC/Pk9I9PNoCiiNtjLvYkjuM9RYBbqa9tceW1a6xeWUfGkmwpzeFHDzIxX0bV7nzfxnqTfntAaba47200XSUKIzZv1Jk6OPHWT3rMiHuyjXAvAw732iVvNpsYhrErTyGOY4IgQNM0VFWl0+mgaRqO44xCIRVFGQVJrq+voygKqqpSrVZ3BBlWq9WRcHJrkOGwuvLQoUPEccwrr7xCEASjBoooiqjX65TL5dH4xsLCwnv2fnwYeC9yPd6LgMn7xWExZswHxeJ0kTCKOXN1DbndIGEZOk89eJCs+95YleNY8vy5a1ytbmGbOqoiWK23OH15BSkhiGKuVuvMPfIUXy4d5G//9F/z13/5nzj1+NOkMmmEUAiiCNt2eOZnvsjURIXNZpetTp8Xzl3npx5YQH+LCwtIFgIyeA2CM4yudoSO1B9H0effk9f6UefRIzMoQnClWkcAUkIh7fD48QN39Tu4G6QcIAffg7iWCArEyUJSpED2tqsrTAjfhHgdqR4GNQ9SIpU80AMZgJJCqqeShWV8HdAR2uz2IvOtBQMpfaT/AoRLJBOoEpQUmJ9FKOPq6bdCVRSeOnWQF85dZ32rs904ArPl7HvqSJJxAzn4KyAAHKCODC+AyNwUiQCCPwfZR+rHQWyLH0pxWxyQSKUM+qnkGIvWQLgI7QAohbsSDGTcQfo/gmiD0fGilsH4KYTy8VlMAmR0m0+Xj9ILPXqhB0KQ0e33TGQY0gx6CLFzR9uLA1RF4KgWm4M2QRyRMVxMRWPTa6MLiSZUvChEAjN2AVsz6IYDICaKI1QhsFSd762d5UhmkiOZqR0/I6NDJxzQ8Ls8M3lqlLcQyZgLrVUOZyZQhMKG12SpVyOrWWhKkjfiqAZbXhcpJWnd4anyiY+VIJUpZVBUhSiM7igIxGFEYWpvd6WUkjdfuMj5Fy4lYw8TOYSAfmfAi3/5KsXpPJ/68iMYe2xESClpbra4dPoq1eub6JZOKp8abbbcjqIo9Dv7jwWN2Zt75lm8VwGHe+2Sh2GIZVnYtk2n0xmJCOVyGd/38TwPIQRRFGFZFoVCAVVV8TxvNFKRSqXIZDIMBgMmJibu2mZ/+275yZMnOXv2LL7vY1kWiqIQBAHVahXXdfnMZz7zlrv8HzUqlQrLy8v7hmZCkusxO7v3Bcm7GX/wfZ9qtcqVK1c4f/78SJSanJwkl8vtEkDebXPKmDH3M0IIjs9VODRVoNkboAqFXMreUXn5blnebHC1usVEPjW6qErZJj9+4yqaqvLQoSlOXx7Q90Pm5+Yo/NI/46U/+0O+/2f/gSf+wT9lZrJCOWXTbrf4P//jtygefZRc2gUhuLbeoN33+PzDi/vasofI8AIEr4IyidiuZ5PSh+AHSMVBqOPQubdCV1U+eewAJ+cn6Ho+hqaRccz39GJZBmch3kKoUze/J1Mw+EvQjyHUxUR8kANQZkBugjgI0TkIXkwWd+okMqpD/19APAC1CBhItQL6g2A99ZY72dJ/CaKr28dL8vpk3EUOvgv230OIdxdw93HAsQyefniRVneAF4bYhv6Wf6dvBykl0nsOUBHKzYWJjHXw/gqMzyDUEtI/DUIH4UC8AfrD4L8A8Stgfh6h2sjgGvT+GLBAyYCwkOo0mI+D/ok7HuNSRkjv+yAHO4/buI70fgDWz34sHTGOZuJo79+YcJwo5DtQFYVYJs0Ys26Ra91N/Mhn0soSy4h+FNAPfQxF41BqAl1RiYhRhY0XhQhVJ62ZHEpPcL61yoJb3vN3n9KSsYtL7SoP5xOxesvv0o98MkZybvhU6QhqXeFKZ4OYGBWFCEkv8piwcvzjg09Rsva/Dv4oYpg6B08d4NKrVynN7C3atmpt8pM5cuW93XLLF1Y59/xFyrNFlFtEAidt46Rt6mtbnP7+WT75pUd23K96bYMX/+IVLr26xMaNGrWVLc7+6By5iSwnHj/C1OLkLtEhcViMx/3eLh+5d2yvXfJh1aSqqhQKBTY3N4m2w4jy+TytVosoishkMqOwx+FOej6ffGBVKhXCMGRzc5MDBw7s+7Nvt9nfvlueyWR45JFHqFarrK+vMxgMUFWVfD7P008//bETGuDd53q80/GHbrfL6dOnWVtbQ1VVbDtJnu31ely8eJF8Ps/8/DyWdXNH971oThkz5n7H0LVdvffvFZdWaqRvW5AO/BA/igmjmIEf0ej0MY1k7M3vNclNL/DMP3oQw9TpegEZ16bjw1azQarTJDVRJI4l9U6P05dXsEyNn3n06L7PQco4cTQoJSBOFqLSB8WBWEUOvofUj4DIILQZhPh45ei8XRzLeNvjK3eDlBGEF7Z/T7f+Q3PboVBDygWIlkHJglAhlhBdA9lIrPPxOlLNJsJD1Eh+x8oE0EvEA9lDKkWE+cheTyH5cXEXwiugVAAPGTaACJQ0xC3k4G+Q6hRCLYIygRAfuUur95TbW0reM2QL4jpCvW1TK64DJsR1pLCTr9Xt64l4C4IrQAyKC7KOlFkInoc4BFUDZTI5noLzyeiOUklcDvsRb0DcQKhTybETJ3WFqHkIryO9HyGVTPI8ldLHUnh4P3A0M3E63UJWd5GsI0lqLA+lKiz3txACLNWgFwVUrAyaonIiOwMiyXmApI6yE3ospiboRR6motGLPBx978+DnOFwpVPlgews2nZzxa2fc6aq8enSUU5m57jeq9EO+piqhqOafLZ8jEn741nheuSxQzQ2Wmwu18hWsujbzVVRFNPaaKEaKp/46Qf3FHniOOb8i5fIlTM7hIZbyU/kWLlcpb3VIZ1PrmtuXFzl+3/yd6xcWsNJ28ydmCUOYwzToNfs8dJ3TnOs2eXIJxZHgoOUEhlLitMfvUaQ95uP3CfiXrvk2WyWWq2GbdsYhkEmk8GyLKIoQggxCriampoim83ueLwgCIjjmHQ6zfXr10cjFftxu81+L6eFZVnMz88zP5+on1JKOp3Ox1JogHef6/FOxh983+fMmTNsbm6OxmYgyfcYHhvNZpPr169z8ODBkXh1J4fFmDFj3hovCHcFu0VxjCoEUgIyxgtCbDP5m4z8AWEoMVQVTVEZ+CGDIKTV8zB0nTjwqdZbSCCOIy7dWKbRrrI4EbMwdeQW10KQLDJkgMRP/lvkIDwDMgKhQNBJFgpKYdue7yMDY3u38+7mxce8l0QgY4Rym71WRoCWCET/P3tvFiPZlZ/5/c5dY99yz8raq1is4lLNFslmN9mLekZqqyWNPBhLmpH1YIzgB2MwsGEIMGDAgCC/jB88BgTYHr8YA1ieGY1G05KsltxWb2qKzebarCJrZVVmVu4ZkbHHvRF3O8cPJzIqs7L2LrLVVfkBRBYjY8t7T9w4/+///b+PCJSE0X1MLV0XtiYkVFf/f1LVBabyIL6iIxBkoMciklWk+G8R9h0iN1UPEJCsQ3JteKOAsKVl99YJsE+jolCTHu5Xnjip/N8JqHhPsakR6LVAOPxv5/VHgKwOiYYIZE8TELKnFTCqBfHF4XrxIVgC2ULm/znGHa4JSnZACVR0FZK14bUECKqADwzAmNJjXOYcuF/Y94p5BBhzcmQtl34ckh6aLGYsh7KdoxP75K0UEsV0usgL5aNEMuHD1hKrfoOxVH7kO+MOxzv8OMAxLMbcHLVOB9sw72ovYAqDRCkCGWMZJrYwUbc8QghB0UlTdG7uI6uDDinryT3/tmPz8i+9wOKFZa79eIEojBHoY3X4mYMcP3uY9B08XTr1Ln7HZ/zAnb0WhBCYpsHmjRr5co6gH/DeX59ja7VOvpLHSeljX5os0txokS1m8Ts+y5fXKE0UmT6i07Ram20OnJy5a3LGw2Jbcf9pQylFq9bBa+mkvWwxQ2my+MhHeR47suF2XfJ8Pk+j0SCO45FR5IEDB0YFZKfT4cMPPxyNUhiGgZRy1FGfnZ3Fsqw7dt534laZ/aPwI3gS8JP4ejyMwWSj0aDb7WIYxoho2B6zSZJkRHb4vk+326VcLj/y5JTt9/6TmFr+rL/+Pp48TFXyLG40diUPuLZFIiWOZZFJu6QdmzCKNZlg2FjD7+A4SQiiiPV6B68fECcxgTIIo4SMq3DsHinbQCUGP/jgB0xmPiad+xzITV1gbhemsg3hDyHx9GbfOqTJBrUGUoIIh2aDAiV9LYlO/4P9guBThw1GESW93cW7SIPqg3lE30eIIWGk9O1iDO3V0B0SCiuQ1MEY02MWxrg2DKCnCYtkDbz/A5X6JUi9tus8KxWhkiqE57VvhDEDZhEIh88fAmrk26BkExW+hUh99dM7TPvQMHKAQKlkRDJq5AEfjDLas2FYAMpwSFhl9W2yrcdx4kVNMCkHki0wD2ryQfl6PUUXwftXyNSvIOyzuzbmSg0gXofwbX1/8xCIrFbjEOgxHuwReamSFVR0CeE8/8kfn8ccQgheKB/h9eplnSI3jNM8UZjiQmuFetBFAc+XDmEIgUQy7uaJZEwr9BgkoTaCVAlBEpO2HE4XD2AZJoYwUKh7+kwoFMYwErjkZHENm0jG2Hd4nBwmJ0ylnkxVwzYs2+LEZ45y9NlDeB0fFKRyKRz37t+5cZTcV2Fs2iYDPwBgfX6TTr2HkmpENABUpsuE/ZBey8eyLQIvYO36JqXJAt2GR2myyHNfPP2T/aE70G32WLq0wo2LKySxJJ11OXb2CAdOTuM+wvGyO6FVa3Pu+xdob3VG6iqlFIVKjrM//yzlyeI9nuH+8diRDXfqkk9PT7O4uIgQgkOHDmGaJnEc0+/3MU2TV199lZWVFaIoIgxDTNNkbGyMfD4/Igq2FQ53w63EwU/qR/Ak4WF9PR6G0KlWqwRBsOu27XNer9dHpFMURTQaDSzLeuTJKY/C1PJn+fX38WTi+PQYC2t1vEFIdii9V0qRTblYlqDrD6jk07x7dWUYPWwRGxZeqwW2S8axMYQgCQdEyiQyU6RdgzhuMVGwUTLGdVwcK8/a1gbHxf8O1ildaAgToo9BrgMOqA3dqZabYJ3UnU3TGv6uByKPMDKopK3l+MbMvuT5U4QQAmU/D8H3UMq+6asgTN2JxgbZ0XL3+A1NOBg5vbNJtvTv7GOgbE0mJUvo8YdprWDZNgsUZZ0WkFxBRRWEcxYYmkIG34e4CrI1LEBX9DgGju52G2lQAYoYgaXVMnIDmXQQRm5/vXyKEMJFWWcgOofa4cWCsNFmkUKTCUkTog+1EsKc1EqmsAYEYD8FwtXnO54fKiIGQ3WLDSICY04TFeF7egRnOFKhZAc1+PZQHVEdPs8CMA7SAyy9brfHKkATX/EVpHUaIawnyhzwk8BUusRrE6d4pzFPO/RxTL0vnEoVSZs2acMhVpLaoEPOSvHFyaeZShX5j0tvUw06RFKSNm2OZCcpu1nM4ec3b7psAnn7zipaPw4oO7mRqsIyTE4XZnm/uchUqjhSTuxEPehyJDvxiXpZ/CzBtEwKlfv3rXBcGynvHmcR9EPW56uEg4h+t8/GQg2/28e+hcgwTIOZY1N0mz0a6y16HZ/6WoNuo8dzr51h7tTMI4u8XJvf4L2/Po9pmhTG8piWSRhEXHzzCtc+WOCVX/m5BzoOD4r2Voc3/vRt3LTLxNxuhZbX8XnjT9/m1f/05UdGODx2ZAPcuUv+0ksvAdBsNun1ers652EYsr6+zmCgXUb35IaHIaVSCdO8u8P2rcTBT+pHsI97416EThzHbGxsYNs27777Lo7jUKvViON4FG+6Ddu2mZiYoN/v43keQRAQRdEjT075SUwtH4fX38eTi0I2xZeeP867V2+60puG4PljM3xwbYV/+90fU+/49IMI1zbJZ1KMHXuO6+ffJux0SJULhEphGIKxo88hTJMo8hjLdjhS7uKHcGQqRdFNI6IFiLrDgmF4TZdrICpg9MFs6QJVtSA6rw3jjArQhegiyjwOogjxJsr/f8AsokQZ7GcxrH2C+NOAYc0h1asQvY+SEaA0MWC/AuH3of+NYfGmgBwYKYhbOnFCVMAoASmtXlAxWjZf0+MUKgYSoKzHLCQQ/3ukbCPs06hkDWQdYc2ikllIEkBqlYSSWlFhVHRhGV1EmYf1a8UrIP8DykihjAMI57n9xIpPCcJ+VusW4osoKfXHXuTBfkmbiibXNAmFoYkh5YO0NRFlntQqBGNseI5jTVSxBQRDFYQJdCAOAAne/4VMfw1hnUSFbwECrGkwD2g1g0ogXkWnY6T0mE1yHRVXNOkFEF0B9e9QwkGZRxH2GYTxZI7VPgpMZ8r8Uuoz1IIOjaAHQNnJMZkqYAihjR8FuIaOw22FHuOpApc6K6RNl0TFdOP+0NDSIUh0UtzR3CSBjEibe/dEUinaoc+rE7uj64/lp+jFAR9318lYDjkrjQC8JKAbDTiQLo8MJffx4MhXcuTLWQZeQCq7ez+vlGJjocrS5VX8ts/EwQqtaoeFD2+wdn2TykyZdH43eSQMg8JYgUIlT6vWZub4NF/6zz5PaeJm0R2FEdWlLWordZRUlKeKzBybum81Qnurw3vfOkdxorCL8HBcm7HZCr2Wx9t/+T5f+c1XPzEzyvM/uIiTcsgW946EbI+JnPv+Bb78659/JAToY0k2wN275LcaPHqex9WrV7FtW+cioxfp1tYWtVqNSqVCOp3m7NmzLCwsPBBx8JP6Eezj3rgboTMYDFhaWiKKIo4fP47ruiRJQq/Xo9VqjYwhd8I0TXK5HOl0ekQ07FxHj2L04GFNLR8Vftqvv4/HH4mSSCVvKx8dL2b52oun6PgBUko2mh3evHCDy8tV/CBECMilbeJE4bomaTvPmZe/TOB1cJBEGOStFGEk8QYDZNJhstBlq+cyN+4wmRvgGO/iCHTknexB8iZJtIjXGxDGJkK4FAt5LDulxynklu5aEgKxluNHH+qfhGB9AWFMasO34HtI9QqGffJTPqqPL+JtU7Zb/RkAwz6Gsg5pA0AEKrwA4XsQXr5ZAAoHDAcY0+MUxkn9U/qaDECilQxbwzhCW3e8jcNDOf0l9LxOBZJVVHR5OMs/i5LrgKvTLoQCupqcINbFKsPRnORdkH1d4Fpn9LiHbKD634LU399POHmEUMPzvntcAoQwEM7zOtJS9fS0TPgjPQaTLA7Xi63XinBBjKM/36cBC5IOJI3hmM0AaOjRKhwgo0euki1NJBgva6+QaB4VfgQqQNgn9Jy+WQLK+vqRtLUPhIj16A2OJr/i63qsYmRaKiBeRCWrOrFi3/fjoWEZJjPpMjPpvWZ+28oDgGVvi7e2ruGYFj9XOcb13iaRTFjo1ZjvbnI4O0HFzfHFydO4ps3rmxcZJBFFO40xVD34cUAr9DlVmGU2s5tUNITB2fJhZjNlrnU32ei3AEXZyfH8xGGm06WRemIfDw4hBKdeOsE7f/VjbLeyKz6zulznxqUVUHD4mTnGZvS5OXBymma1xdr1DdL5FLni3s9ZkkhM2ySTS5HZQUhs3qjx/rfPE0cxTspBScnylVU+euMKz3z+FEefO3TP97z40RKWa+9RVmwjV8pSW6mzeaPGgRMzxFFMdWmLxQvL+G0fK2Vz+Ok5Zo5Pkco8uCKmvdWhudlmYu7OPhfZQobaSp1WrfNI1A2PLdlwv9jZ4c1ms5RKJbrdLq1WayjhFYRhyNmzZ8nlcjiO88DEwU/iR7CPe+NOhE4QBMzPz2OaJidOnBipGCzLYmpqin6/z9bWFrOzHC30tgAAIABJREFUs7dVrIRhSDqdZnJycnTb9uhBGIbEcUyv1yMMQxYWFigWi5w9e3aUYHI3PKip5aP2VngYU8197ON+0I9DLrVXueHpeK+yk+OZ4hxTtzhtCyEoZlNEScK5d9c5N79KreWRGcoihSGQKqbnBQQixO+H5HJZAgMyaZfZfIb+IGKzWSOfijg+2eOZA6uk7D5ekGAQUsn6kPhaHp80QCZsezuFkYAIBuEUqeyzwyJgSDQYxWHHuqfN4cynYDhjLYwsSjkQ/RhlHb5nZOI+7o5W6HOxvcJ6vwHATLrCM8U5is7ujosQFogKSrZ04Rj+CBholYMQgNQSeba06kD56Fn9Bqj0kKhYRisgFNpzQUByHl1IFnR3W1i6EJR1iC6DMzQUlD7IDTAOgTELqqpn+onBnNVrJqpCsgDuqwhj+P5FESVNVPgeIv2ffApH9PGGjNe0Ckk2QQiUeRzhPLsnelQIR6+XaAnCDyF6BxBD41ALvV487eEhff0gw4bEHo7MLOr7IIfPGAM+xE1urpfrYH0OYY6h4hiSqyj7uPZ6MQ9BfFWP6JjDsQxlabLKGq6XcAvUOji/ejPBxBxHJTVUfBXhvPDJH9AnGO3Q5+36NSpudkSKl90czcCjG/cJkxiF4qtTz5Ifxld+dfo5rnbXWfJq+jwDBTvNqxOnOJCp3LYLLIRgMlVkMlUcNTT3x2UeHWaPT/PsF5/mwg+vYtkW+UoWmUiu/XgBQ8DYgQqHz+xQnM9UyBWzdJs+1aUtcs9m9hjLem2PQiXHkWcP4QzHPbdW67z1zfdI59P4HZ+lS6tDzwhtLvmjb76LYQkOn75zUk0SJyxfWac8dfcCPlNIs3Rphcp0ibe++T6deo9sMYOTcUnihI/euMzltz/m5a9/lrGZB0vH8Nr+fd1PCIHX9vfJhkeBWzu8lmVRLpd3FYzdbneUFvGwxMHD+hHs4/5wu/Pi+z7FYpGpqak9fg75fJ5sNjsygCyVdhdCcRyTJAn5fH6kVNkmpqSUNBoNlFI4jkM2m0VKSbvd5vvf/z5f+cpX7kk4PIip5SfhrfAwppr72Me9ECQRP6hexI/D0byrFwf8oHqJVydO7er6hDJmxa/z4coNvnPxHI2VCFPYCMdGGAaOaRB2PQZrTcK0Q5Ky8WpdzEoOhIEh+pyaK/DqyRoz2Y/pBwn9QYQf2lRSbQ6M9cnYg6E/g+JPvtnlpbMpDh/U3YR/+402v/jlDJPjG6iwjmByGLHoatm1bA2713kwsogdDvZCaG8IHaG3f01/WLRDn+9tfoQtTCbcAgpoBF2+t/kRX51+jsKO+WglPVQ8D8GbMPh/QQXau2F7PAZHF6C00fP5JohgWDwucrNo3IntWd8A3cFGF4iGA2JSF4Sjuf4SJIbuRmPozrc1rUkNYQ2LyTUdt3mLBF4YOVSyiZL+TRJiHw8MGS9B8AMQRYQ5NYxGvY6Sm1oJsIP4U7KJiq5B///Ta4ZYkwlKoM+fCao+XDMZTULEMVBHr4c7IQH6aBVEC5J1lNwCo6BVDLKr/23ODFUNK5Bs6DUiCmiSIxmOadRBTGmFxU4YJe0XsU82fKJY9KqYwtylvjOFwXgqzzh6LLcWdFkfNEdkQ9HJ8NLYcZ4vHSKQMYYQZE33vsmDfZLhk8Hxs0eZmBvnxqUV1q9v0Ky2cVyLp148TqGSRxg3j3sq43Lk2YN06j1a1Q5+r08mP7wuK6UNKgWMz41z/DNHhjcrLvzwKoZl8vF788RRTKaQIWOZKCnp1nsE/YDX/+RHHPjvZu44/hBHmsC6U0znNmzHot8d8NZfvk/gh0wcHNv1u1TGZeAF/Ogv3uUrv/EFsrdRZ9wN97cO7+6F8SB44smGh+nw7hMHfzdx63k5f16br9zOONKyLA4fPkwURTSbTSzLIpXS2d+DwYA4jpmdneXMmTMjAqnRaIwUBpZl7Xpe0zTJ5/N0u10++OADXn311bsqDu7X1NIwjE/EW2E/JWUfnwRW/Dq9eMBk6iYTnrVcTCE431xiOl3CEAaDJOT1zcssb2yw9OM1ttar9E2XpA/pVh+ZcQk32siL60gD3IzLWCFLzxWk+m2mpkpMT9Z45dDrzOTmKaZbBJHENhJMy6Cc6eNYCbow0Lg2H/GNv+zxf/9vMyyvRvzu79W49PoRTFMnDiC2wPoMuK/pIlYFwwKzyc2Cdif2N40/KS53VrGEMVIxCPRmvhl6XOms8dLYcQCUbKAG34F4SZMBsoVOFlFAFkQyVDL00DP1lvbaUM1hCsD9bJoSoKbn9+MlMFq6MJU+GJEuRs1pEDltMmpVIPXF4ahEZ+j/YOrnkcltnv/RbdyeRCglIXofjApC6O9qIUwwJ1HJOipeQtgngB2kRLwE8SXtyUKsySIjM/Ri8NGkgY1eSzawyc5rxt3R1Y+Lb+jrhcgDOZCbKJHV7806gRIFwNHGkNZTQ2Kqq81okYCpyYd9fKpQSrHQq1Fy7k7+FawUC70aTxVmd93umjauuZ9O9HcJhbE8z712mjOvPMV73z5Pt+HRa3qgtLfDzgJ/5tg0Qhi8860fs7FQJZ1PYxgGSknSuTSnXznJ53/1xZF/QafepbHRZGO+imEauzzihGGQKWZwcy6LF1a4/sECp166/YilZVsYhtBjGjveTxIn9HsD3cR0beIoIY5iwlbIxMHbR+ymsi793oDFC8s884Wn7/s45cpZfT29B5SCXOnRkONPPNmw3+F9/LBNCMzPz49IgVKptCtZBMB1XZ566inW19dxXZdGo4EQgnK5zNGjR5mamtqTYLEdn3qnIj2TydBut+/pdbDT1DKO49Hoznbs5rbSIpfLMRgMHrm3wn5Kyj4+CSx5dXJWas/tKdOhGnXw45CcneJKZ42m36V5oc54MU8uk0X1BUFOEiYK43qVYL1DkrbANjHSDnacUIkgLrhw+UOOTd2gs2Jy5oUuphmRSJOxfIRrhdyui/3P/mmJk68s8vv/c50//5bHi2dTuK4mDDTJHw9l9AJhFABQwoJ4Gczju55LkxPm0ExyHw8DqaTOt3f3XoOKdpplr86LlWMAqOAt7YWgWnqEQSyhEwKC4c9Y/wSGhgnDKFOfW4v8bk/yR3/W5dpCxImjNr/5a3nyuZ1dphYkCqRBLAPWtqbpeTfIZS1mZ4YeH6lfgOg9kBJhmsNIRVAMIPpAGw3ugJJdMMb2VQ0/CVQXZB9hFvb+TgxHYOwTKBVA+ObNtWEegGRzWNyHw+jJAdqwUaFHK5zhCM7uov/ea2Uw9P+whmaPCsyvgtrUm3ml9DUi848hfOvmqMcoJrWmry+3ejPIJtj3Xzzs48EhUSRK3tMvwTJM+tHgrvfZx98dbCxW+eB7H7GxWGX143VWP14nHISkcimeffVppg5PjEbkZ45N8fIvfZZDpw/gtX0GfkhlusSRZw5SmS5hGDfXxsAL6LU8wiCkMHabaxC6VnRTDlffm78j2WBaJodOz7FyZY3SZJEkTlhf2GRzsUYSDw1tFQhDcPDULLnS3RULhbEcNy6u8vTnTt4zwGD0mEqesZky3WaPfPn29W+v5VGeLFAcv/3f+qB44smG/Q7v44WdIwemaRKGIZ1Oh/X1dUzT5PDhw4yPj4/OtxCCqakpnn/+3hnXYRiOUkzuBMMwMAzjnl4H26aWnU6Hra2t0SiPbdtIKdnc3ERKydTUFMXi3eelHsZbYT8lZR+3QilFO+oTyoiM6ZKz95IG94JpCO5EmCsUCG0cOd+ropoxKIWbcpiuFBhstAkjEOmIZKtHIpT2ZfMjnFaAYVkkYUJ/Jea5lzfxFgOUmzCvEiaOpXDzCZZIAIPbkQ3nLgS0uwn/479sICVk0nDwhXn+4g8P8Nrn0kACyRXdlR7tMWytbhAWSgU6Wk/2dLfc+fwT7dcglaQZeiRKUrDTpG7j0H43CPSGT20XfDugAGO4IVRyaK6nuoALZhrMMS1N11EDaK+N7UcqtEw+2nG7xt++1edXfnsVKcHzFdmM4Hd/rzZaA0opvvW9GieP9SmXPL757S69fhUj9SJSDsjl4Jd/6QXGKiUt3Y8vooyXdkQspoZS+QSl4uH76GjjQPcLD3R8HjfEMqEVeiig7GRvawR6d4ihOeftIBmtoaSqlQJyU6sNjIweh5F1UAZ6fWwTDeifSgDNXc94r7VyEw1IQlC1Eekhsv9YqxdGoxOgkhuopArGOELoDioip0duVDTsNCq91o0Uwto3n/0kYQqDlGkTyhjnNibG2wiSiOx+LOXPBDZv1Hjrm++RKWQY9AKa1TbZQgbTsug2unz337zO0ecO89yXTpMrZkkSie1YPPfa6ZEvw51gmAbN9dY9EyfslE19rUkURntiMr2OTxRETBwcY/GjJfyOz/yHN6gtN3CzLo5rk86nCbwBURhz/YNFTr9yErgz4WBa2jcwiZL7JhsAnvvSGd74xtt0Gz1y5eyusYpus0cUxHzu6599ZGM/TzzZsN/hfXyw0+xTKUUQBHS7XVKpFKZp4vs+58+fJ5/Pc+zYMcbGxh7o3DqOQxiGd/VH2CYNwnD3Jvd2Bo/ZbJZz586RJAlKKaSUGIaBZVmk02kOHDjA8vIyhcLdmcWHUd7sp6TsYyd68YB36tdoBB6giYG5dIUXKkcfSCp6KDPOO435PZszLw4o2RmypjtKqZBBjGEYDJKIiUqGfhDS8iNajRAjSDD6EW7awmgHmP2IXpwQ9UMSU5DO+igrxdjEgFrVprpm8OznFD1lkCtJTHPYHhii25P8ym+vsvNj6ff1X/orv73KygfHyGWHDEOygBKx/reRg+zv6IIxvqzNCcUYOD+HYR14iCP9eGAr6PLO1jX8JNxuxHAyP82zpYMjh/Z7QQjB4cwES35tj7qhGfocy20nNwy7zWowHG8JtSGjUtozQw1jDBFAgRHhoDZ3Pef2Guj2bq4Lz9f//uX/fIV//QfT/Is/aBJGin/9Bzl++K6HEC5zU02wt8Capt2J+eZfvcE/+fVXsMzDEC+CrKIw9MsbE5D7Z8Okgav6vZtzCPuZJzr6crFX5VzzBvFwXMAUJmfLhzmam7zHI3dA5EEUUNLbm9KgemB+Zvg/Cfr8B9p7Q0mtbsDW6SJqgF4vJlDipgdDNHq6u62Vr//WCv/8d8q88Xafv/7jOWw7BlygokkL/49R1hGENQeihJJdBH2wnwNxTadNbH9q7Kch/asQX4Pkhn5f9nGE9fR+EsWngJP5aT5qLTORuvMeqxsP+NzYiU/0fUQyZrPfxosDLMNg3C3sMcjdx24E/QCv7aMUZIsZbNfi3N9cIFfOMX9+kTiKmThQwev49L0Qr+WTRAkf/fAy1aUap146Qa6U4+nPnbgn0QBQHM8TJ1InXN0DmWKGJJaYlqTX9Kgu1Vj4aJl+d4BhCqRUKKX4m//wI7ZWGuQrWURDIOOEOEqYPDTOy1//LFffuc7lt69x5JmD1FbqREGEm3KYOjJBZbqM5VjIRCIQu1I47geFSp5X/+HLfPj6JbZWG0N1p0ApydhMmee+eIbC2J3r4gfFE082/F3o8D7qpIHHHXc6XlEUjQr2GzdukM1m6ff7tNvtUREvhEBKyfz8PI1Gg6mpqfs+t5OTkywsLIxUE3d6b6VSaUQ4NBoNlpeXWVlZwTAMxsbGKJVKCCGYn5+n3W7vGePZlng5joMQgnq9juu6tNtt4jjGsiyKxeJoLORhlTf7KSn7AN1xfKN6mVDGTA43XUop1votetXLHMiU2Qq6ZEyXw9lxxu+yMZvLjLHo1dgctCnZGSzDpBP1iWTCl6fOMEgiQhnjGg41u8Fip4o5VAcYRUkuLShFGTY6A8oTBbyVFl7HI0wUMpFE/RDDNmiuGWTKIUEAXsMm8iSX37KZmMmQyiWcfqGLtYMj+aM/62qVxG0gpf797/xWES2DHkekvwYYIAoIYQCzYD+NUuqJN/jqxQNer14ia7qj9SKV5EpnjX4SkjJtOlGfkp3lcG5il8njrThVnGWt32Br0KXkZFDodIqUaXEyP6PvJHLDOfcBxFeG8ZaAMfRlkGWQS2AdHHonNIdjFdGu17rbGvB8+Kf/9Sa//AtZzpxy+OM/b3DlesJv//oMEEB0DlSNYtpkZaXF2o0Bhw6Na+LD/UcIowjYCGO4OTMnwfnM/noBNgdt3q5fZ9zNYw/VDJFMeHvrGl40oC9DBknEVKrIwcz4rljCnRBCgPMyavAdlAyHioFtk9YphDWcqTeGJozS12SQsPX/Gw6ICb2OZAes8aGpZ3c4cnET91or73ww4F/+/gS2vX1u+0BXKydUC7r/K8p9Yfi8CmUeB8PQoxapXxxeU1I3x2rMCZR65ebfuY9PBYey41ztrNON+uRvc51qhR4FK33b+MxHAaUU17sbfNReIVEJpjCQSl9PJ1NFXhw7RmZfVbELfW/Ax+/Ns3RpZdROEAqylRzdeg8n7eC3+xTGC9iuxfrfVul3+2QKGZyUjeGHhP2IxY+WqcyU+fJvfP6+XtdJORw8NcPC+RtMHNwbYRwOQqpLNQZeSOAH/NX/+R1klNBu9Fi/toGdsqlMlThwcobyWJ7zr1+ktrzF+GwFYRrIJMHOpShU8iipqC3VKU0W+PD1S0RBxNhsGcfNEEcJixeWWb22wamXThANIg48NfPAZAMMCYdfe5lOo4vX0gkV2WLmkZIM23jiyYafdof3k0gaeJxxt+O1urrKwYMH6Xa7KKWw7b0dWcMwiOMY27YJguCBvtgrlQrFYpF2u71HCZMkySi1xPd9yuUy9Xod27ZptVpkMhkMw6DdbtPpdJienmZra4t0Wkt3JyYmdhEYcRyzsrJCNpvl2rVrTE9P4zgOqVQKKSX1ep1Go8Hc3BxhGD608mbf7HQf1UGHbjxgaoepoxCClGnx/c0LnC4eYNzN0wo95nubPFM6yJni7debZZi8OnGKhV6V691NvCRgKlWkbOe40FqiFnQRCKr9Nj+MrmMVI4qRSS6TxlMB/dhnakGSVVAwbTphhFCg4oQ4iEAqZJBw4Q2TYnZAKkxIInDTgr6nsFMJGwsWs0csxiZvFpvXFqJRZ/JWeL7i+sL2fQ3dkVYxwtzbdd0vBOBGrwZqd1a9IQwUir9YfZ/PlA6Ts1PUgx5Xu+u8Mn6CA5nb53lnLZevTj/Lte4GN7wtQHcbj+enRptsIRyUGAP5PXRH2kV3pZsgAxAVsI6AdQKC7w0FLXt9O+62BpQCqSBOoNuV+AOIE6Xn/4U7JDs8nYJimnheE8QJHX8ZvAHpf3jbTvT+eoGLrRXydmpENABYwqAdeXxj5R1eKB/BNkw+aq9wpbPOlyZP37GrK8xJSH8NFV2GZFWfG+ezCOsEQujve2FUUCQg21ppsO2ToKp6SRgFMKc0UZW8MTQZ3U1M3W2tALx4NsVnn79lzEwOQEj9vEYa4o9BjOv3qDyE8RRKNiB8G1Jfuzl6s/237a+VTx0p0+GLk6f5Ye0Km4M2WcvFFiahjPGTkKKV4QuTpx5i5Of+cLWzzrnmIhOpwp7XaIYeP6he4itTZx54RO1xRd8b8MM/e4fACyhPlUaGjzKRzJ+7wcZilWwxQyqnP5vdRo9sIUMml8Jr+yRhTBREpLMu+UqWM59/ivPfv8DP/9ZrexqISZLQWG/hd/uYpkFhPM8X/sFLrFxeo1PvkC1mRwV+q9pm5coapmMyeXAc27G4+s51ZCJpb3U58uwh3LRD0A+4/PY1KjMlOltdihMF4ijh0MlpUpmb1xOlFMtXVpFSksq4RGGMNaxnbNfAdm0CP+Dim1c4cGKGo8/eOWrzflCo5ClUHj3BsBNPPNkAP70O707Z/6NMGnhcca/jJYRgfX19pArYJovK5TJhGDIYDJBSIqVkcnISx3GwLOu25op3Uk+cOXOGN954g263OyIQBoMBtVoNYKSS8DwtR4+iCMuyyGT05imdThPHMdevXycMQ/L5PFEU0e/3dykcLMtiMBjQ7XYRQmBZ1uhiaJrm6HkWFxeZmZnZ91bYxwMhSCLakY8hDBphF/uWja9UiquddVzDJmulyFguGVykklxorTCTLlF29hoLSSVpBD3aoU/ByTDmZFnyGyx7DXKWy6RbQAhBN/I5lpukerjN2mYTsdXEWA1JL8P6fJdsNk231SMcRIT9EJWMhMcYlkGnIfjgDYfPvCaZPRLS9yTpnKJVz9JpGbRqfSoT0Sg6+8RRm2xG3LaAyGYEx49uE5MCjElU9BHC/OqjPeg/w+jFA7w4wDFMqsNN+U4EScRCr0racsjaw/ViuYQy5p36PBOp4m3nomOZUBt08OKAiVSBg5kxptOlXaZtSiktk7df0HGAcnXo4SCHHgkRkNWqBxUAHrdLfrjbGsik4Td+Lc8bb/VZWYv5n/6HWc5fjDENhY7QtACdNiGVSzYjQfb06yNQ8SLCeeYnOcSPDba9XwIZkTZsGkF3j0y9E/WpBx62MMnbaQwhyFgu3ajPu43rfHXq2dsW34MkZNkLqA7GSJnTHM6OM2bld91XqYGOtXQ+C9ElUFvDRBlDG0Fuzz8n88P1otUHO3G3tQKwvBYhpcIYxek56EQLBwxzaDjp65QUowRyA6WOaiIkWdfjHObMQx3ffTxaFJ0MvzDzPBv9FvPeJkESU7SzvFA5yoS7lwR4VPDigI/ay0ymi7c1qSw7WWqDDtd7VZ65A7n/pOHC314m7IeUp3dH1RumQWEiz+r1dVaurHHy544hE0mr2iFT0CkTuZJuTA66A2ZPzmBaBrlSltpKnfpqg8lDWq0gpeTim1d479sfEvZDMvk0uVIWYQjGpsuc/sJTbMxX6bV9ZJww8ALW5jeZmBujOJHH7wwIBhETc2NsrTeJg5ja8hYHTs7gpl0sx+bim1eYnBsberwJ2tUOqSM3yQYhBANvQBTEzJ2apV3v0G30yBTSmJaJlJI4iunUe7z8yzOUJu7u67YTSin8bp8kSrBdi3Tu7mmMjwr7ZMMQP40Ob6PRGM343+k9PUzSwOOK+zle26TC2NgYnudhWRaGYZBKpUaqACkl+XyewWCwx1wxDENWVlb48MMPieOYdDpNuVzGtu3RKMTLL7/M1atXabfbmv0cplgIIWi1WoyNjZEkCblcjrW1NUATWttkgWVZ+L6vzc+GyRa+7+8Zp0iSBN/3mZiYQEo5IsEMw0BKSRRFJEnC+Pj4fZNR+yM7TzaUUlzprHGhvcL2Brsd+ggEFffm+vPiAYGMcAxz10bIEAa2YbDqN/aQDVJJ3qvPs+jVyFgOiVR8d+MjDASfGz+xy/uhFfaZSBeZzpRpp8e57C0wdXwS0/fpZTO410Kaq03CQI9GBUafMAowsEipDIYwWL9h06q7TM3lcVMB5WmXg8chDhK++40Mc8eu46Z1d/s3fy3P7/5e7bbHxDD07wEtubaeBXn7+z5piGXCj5uL3PBqCARKwVbQZszJ71I2tEM9O2sKgbVjvTiGRawStgZdZjO7pchBEvG31cs0I4+M6aCAZa/OTLrEK+Mnd2zyQ90Ztk+grKNaGh9fAFEedo2HEYTBBlrObjJsYbNT3XC3NWCagv/l9ydIpwT/8S975LMFctk27U5EsRABFSCg3QnI5fLMTmf061ontJxfVoF9ssGLA96pX2Nr0B2Zf674dbK2S3ZHSk01aGMKgSnMXdageTs9UlrdOn7TDn1er14ilDFpy6ERJsz3NjlVmOW50qGbhIPsgmFrJYF1FKKPQKyCOVx/UupRm6SNJhq2iaSbuNtayWS08uFf/EGT//6/qQBpIIeOwgxApUGUNJGhomEqCnrkRtiAhZItxD7Z8HcGlmEylx1jLnt7BdYngRWvjhDirmkYZSfLtc46p/Iznxjp8bMCr+OzPr9JZfb2jbVsIUMqm6K6tMXAGyCG++TtRAlh6OuNYZk4GQeV6O8Gx7WprtSZPDRBY6PJt//wB1x95zrZUgYpYfnKGgNvQGWmTCafZny2zMzxKfqdPoN+wKU3ryKUor7WoLHepFDJk6/kEIZBr94jP57D7/gMvIB0LoUAoiAhihKUAidl02n2mDqyQ0mpFK1qBwRky1meffVphBBsLFQZ+AEomDg0ztHnDtPv3n9SysZilavvXqe91RmaLysmDo7z1IvHqEx/MqNC29gnG36KqFarpNN3Z5UeJmngccW9jlepVBoV0dukwq3SqDiOyefzSClHaoFtc0XP87h48SLLy8uk02nS6TSe53H16lVAqxZKpRKrq6u89NJL1Go13nrrLUBHXmazWVzXpVqtYhjGyHNBKbVHubBNGGyPdMSx3uwkSUKv16PVatFsNkmSBNu2OXjwIEIIarUanuehlCKXyzExMUGz2eTo0aP3PH77Izv7uN7b5HxriclUYbTJSRkOb25dZTyVp+To8y+VIpIJadMlf0uUpW2YDJJoz3Ov+U0WvCrTKe1JstCr4hoWQhgsejVOFWaJ45j6RpXa+jJ22mVieoqwHTCWyuFZMYYMSFVSOCmFkoqYgHW5TCQjhBJIpbBii3Exg43DwFOszJuMTc0wdmiGd75fJw4HGCLm1/+rJdy0nsXO5wz+4g8P7HGXNwz4iz88MDSHtMD9eyBidAGxjx83F1nyaiNFCkCsYj5sL1N2syMCKVIJ/SRiNlPeYygqFCNjwJ243FmjFfm7xncKdpr1fpPFXpUThe1izARhoFSCECZKtcCYAcMddqbzIDfAsCERaIJhaBK4A/e3BuDXf7UEKOZmc3zz23VW1hWG2UYmEbl8jl/+2lEsc5hmYEwDIYh9M7dESd6oXmYgY6bS+pwqpagPurxfX+S1yVOjNRTJhH4c8lRhdo+CQQDJLetFKcV7jXmEELtUEnJIns6myze9ZITFKBJHiCEpNKeLftkFawzCG2Bmhusl4daRm3utlVdfTpGM3qIEWoyMTI28VuLICOzMjvcy/FwICTx40s8+Hi9shV3S9zBftgzfqBCpAAAgAElEQVSTREkGSUTuCScbOvUuSrBDTbQbmUKaXDmLZVusL9TIFtMEfoibcUeEQ+CH5Cs54iBm8qAmloQhUImkWW3z+p/8iJWr60wfnaTX7rO1rPfy6UyK5kYLyzJ491vn2Fqt06p1GXiD4deMwkk5TBwax+/08Xt9pEqQSmJhYVgm3UaPdC4FAmzXwu8MKFSy9Nq+nuFT+vtqc2mLlY9X2VzcwjQNqktbhP2QQ6fncDMO4SBEmAbNzRYyTgj820dX3oqr71/n4g+vkq/kGD+g/3alFN1mj9f/5C1e/NpZDpz45AjQfbLhp4gwDPd0s2/FwyQNPK641/HK5/PUajXiOGZ9fR3P80YjB47jjMy60uk0YRiOFAjbiogrV64wGAxwXRchBFtbWyilRoqIdruNUookSSiVSvR6PfL5PGNjYyNSI0kSoigijuPRCITruvR6vV3v3TS1FEoIQRzHmKZJFEVsbm7S6/UwDGM0PpEkCdeuXUMIQaVSYWZmZkRWdDod6vX6PYmC/ZGdfSRKcqm9yrib29VNKThpTuSnuNbd5Eh2Ase06MUDQhlztnwE09jdeRkkMRPuXpPI+d4mBTuDEIJIJmz0W+QsFyEM6kGPer3Bu995Hd/z6SUDNv025UKR8SNHMS2beMvHL4c8FRTpxz5jc2Xen38HlCBtZPWeXUhiFVMXG8wYh3FcGxlL3HyW9lZMtxFg2Qa2K/n3/+pp/ovf/RDH1Zv91z6XZuWDY/zRn3W5vhBx/KjNb/5aflhkCm1E6H5ZS/Sdlz7JU/EzgV484MYtRAPAbLpMbdDhWneDmXQZyzDoJxGmITh+m3QBJdjTpU6UZKG3yZi793pedrJc626OyAYhLJR5TI9QmJOg+vpcgfZRMA+B8sA8CsnH3IzD3FY43Cwk774GGD6uAsRUKjn+yT+aYK1q4/U8sumI2QPHsWwFJGAd0ySD3EBY9yZ7H3fUBh06UX9ENICWA58qzPJ2/ToLvepIPZVIScZymEnvlkMnSmIIsUsFAToRoBl6I0PSbRhCkDJtbnhbO8iGEhhF1Hb0JAzVBXIYh5rRaSbSAOYZxogwCrgf4l5rRadn57VnCAqMLJDSnhBJFWQIpHVMrjGjvUdUCAiEtd88etJhIG437bUH93GXxxIDP6Cz1UFKRSrrjlIX7gQlFbZj0W32aGy2KE8WadU69Lt9sqUsjmtjOiaVmRKBHzA+pwvucBBSGC/w0d9eJuiHmJZBMIjYWNwknU2NfCHCZo/v/ps3UFISR3vJ86AfsnJlDWEIbNdmbKZEKpciU8iQyaeJI91QNAyDVM4l8EMOnJymvdUdpmfB9XOLrF3fIJVN4bgWlmMxeXiCjcVNrr57nad+7jgHTurvRaUU7a0uW6sN1hc2mTk6dcdjU19vcunNq4zPjWGaN/dzQghypSxu2uHH3/mQ8lSJTP6TabTskw0/RTiOQ5IkWNadT8PDJg38LONOUn/DMO56vLYL/W2fhG0SwfM8ut0uuVyOycnJEemQz+dH0ZfbIxq+72OaJo1GA8MwRiTCdnEPkEqleP/99zly5MjodzvfdxiGo/cohMDzPPr9/q5RhXQ6TRRFVCoVNjY2SKfTbGxs4Ps+lmWNojDL5TKpVIpms4mUkl6vRzarM3FN0xwRI/ciCvZHdvYRJBGRjLGNvV3Yg9lxSk6f2XSFetDlSG6So9kJlvw6iUphCgOlFK3IJ2XYhDLiO+sfEquE2XSFY/kpBjIaSegbQQ+JGsUgJnHCm3/zfWzTYnJ2mnEUjt+k2tji4w/OMffcMwy6A2TBoNhI4UtFL+hiZ03ScZo4TEiiGCkNLMMhUB4qk1Asj9FtegS9AWE/JEkkXnuAmzX43p+4TM9N8fXf2hgWiJDLGsPUiZ0QQAay/6V2pzcPIaxjn+Sp+JmAFwcIxN7OsxAczU2StVwsYdKLB7xQOsxcukw3GmAbFobQKpStoMuYk2O93+Tt+jUEgiPZCWYzZRIlbyshtgyTXrw7HUA4z6PkFirZ0PGXsql/YU6COQZyZTgfP6e71/hoiTyMojCHuP0a2IY9fJwuHC3L4NB0nZtjGRuQZMB9WY9xyA2wn7+tmeiThnboYxl7z6dpGBzNTXAsN0k78gllwpcmTzPvVfGSAYXh9ShRkuqgzbHcNBday2z227imzfHcFGnLuWOZYd2itBJCgPt51OC7ei2oCJKWVhRYh0FkITGGZo5zwzEcn5vE1M1C4u5rxRjed+gFISa0oiG+PvQTSUP0AdgnwRhHJVVAgfsqQuwrp550TKeLrPWb5Ow7q1yCJCJl2HdMaHkcEQ5CLv3oKsuX11AotuMYTdui0+gyfmDvGIWUkuvnFmlV2xx9/jBIydr1TWzHIhxEBOtNxg6MMX1skn53wLGzh8nk0yRxghCCbDFDc7OJlArLtmisN7FdG8PU+57FC8usXl1HJneIqNkBJRVhP2RjscbEoTG9J2n52KmbKpZsIUPUj0akhDAENy4us3RllWwho8c/TINCJY+Tsuk1euRLOZYurlCZLZPOpobfy4ojzx7kvb8+z9/7rdfu6L+w8OESqWxqF9GwE7ar39vKx2s89dnj9z5JD4F9suGniMnJSVZWVvYkG+zEdjH8pOBuUv9er4dt24yPj+953HZ6g2manD59miRJWFxcxPd9bNsmk8mglBoRAXNzc6N5rkqlwuXLl0emi3Eco5QaEQ1SSsIwpN/v0+12KRaLNJtNZmZmRgoFYERQ5HI5+v3+6Hfb5EGj0aBSqRCGIa1WiyiKqFarZDIZMpkMnU5Hm6ENYds2vu/T7/dH3g5BEOwaydhWaEgp70oU7I/s7MM2TBBawtyLbhr+ldwcfhyw5jfx4xBTGHhJgC0sZlJlaqFelxLFuJMnlBEfNG9QdDKYwuBab5MFr8qYk6cWdHBNm148wBE3Y+76tRZhf0B5VrPyBoIDmTIlO8M1f5644VEMXTANsDTzX722RSaXJmNlaVbbxOFQFQ2gBFEUEAYhsyc0o+93+gy8ANu1SeczCCVZ+niWv/q3Jp//xRZjUwMgQQj9GYsjA4Sg3TxC6eBvYNrPgDkHCFT4AQqJsA6AMb3HOf5JgGOYgB6naYUeQaJn5Ut2hm7cZ73fJms7WMLE622SsVwqbo6toDvqEU+nSjSCHpfCVQp2GgWcb91goVclY6bw42BPtFsvGjCd2l3gCZGC1N9HxasQZXURZz0FxoQuGqWCeAWMU2BuQvQxunDcqXCAW4mHm0gN5+xjwAcjpQ38krWhikKCCIdd8xmwXgB7FowDQIAM3gJhI8yDYIw/kckCrmmRKEWQRLRCj1hJclaKvJ2mG/b5qLWMbVpYwuByNKDsZFEoNgdtnRMvDA5mJljqVTENk5ydIpQRb9U/ZiZdQaFuS1D145ATud3fWcKoQOrrqOQGICFeButphFlGKQ9kX5MMzlmIroJc2H4kelu8PYazW+1w8z55oAD4oBpgvwjGEUiu6PWhEiDW1xOV1YSYMQHmNMjWcL2kEdYhhFFiH08eZtMVzokbhDK+rXku6ESKz5SP3NXX4XFCOAj54Z+/g9f2KU/fTJuAoWfDtQ3S2RQzx6aIo4R2rU2v5dFteVQXa4zNVnDSLs9/6Qz1tQbXP1hg/vwNUIpuo0u/V+bMK08xNlshjhLqa3We+9IZ4jAextFCHMb43QHpnP5eWvxoidWP15HJg2lMlFTUbtSZOTGFaZp4LZ++1yfsR1SXahjC4P1vn2P62BQv/sJZ3vjTt0bkQuAHTB4ep1Pr0d7qghDkSpqEqC1tcej0HEE/wHZsJg+N09nqsXZ9g+Nn9yrspJSsL2ze05MhV86xenVjn2x4HFGpVFhbWxt1729FGIajYvhJwL2k/qZpsri4SCaTwXEcut0urVZLO8wOBkRRRC6Xo1wuY1kW4+PjVKtVrl27Rq/XG3k4HDp0CN/3R7Gn2wqIXC6HZVm02+1RysS2KgHAdW/OfiVJwo0bNzh8+DC9Xo8kSUYEhRBi1+hLOp0emT32+/2RV0Q+n6fX66GUYmtraxRt2e12ASiXy/T7/dFzbb+G53nkcjniOB4pNIC7EgX7IztPDqSS1IIuW0EXWxhMuAW8OGCl36AV+ry3NU/OSmGZOtNb9DaoD3pYwqQb6/NfdrJMpYrUwg4/P/kMSihsw2Jr0OGdxjzTO+TPrmnTiXx60YB26LPYq7LarxNJyZRbRKEoqxTXl9dwbIfyxHBWEkHOTjFXGOf4kWMsna/S6PbY2mjQq3ZIBglBGJIt5MkUMjSDOkEyYDo7h0picrkCxfE8tmNx7OxhLr35MaCwHBPHtbEcm2YDSo3g/2fvTWMkSe8zv98bd+SdWffV933MyRnOkMMhR9JQpA5KtC1a0mIFy5Z36Q/eNRaW4TUNQbv2BxteQIKA9cqy4TUMGVoRXiwkanXSosRjNCSHc3X39H1W15GVVXlnxv2+/hCZ0V3TxzTnkJqceoDGTGdnZmRlREXE/3mfg9//V3P83D+eZWv5AqVqjEDHG7psNp+nfiPiwCMRxz71OETfgfjqrZaB6C0gQWkjQlhfRJjHfqgGhEjG1L0OnWhIzrCoWSlhUPc6LA+2eK15nYJho2uCRCk0BKtei4qVww1tBDA1ygAxhMZn5h4lVDGubnGmfZMEuc1n7+hlGn6XCavA2e4KXhISK0nRdJm0C6AEh0rzd3xOISyEuRfMvcjoOESvgKynTQNyY5T+v0k6BE4D66SDYhkIQRsFSuKlVgy5RVp5WE0bA4SZvoeEtF3ATYkGLZe+jzBAPwqqDvgI8xjK/yuQzdHxIlHhqyAsFE4q3TcOIIxDiLuoiX5Q4cUh635KTJbNHHnDZs1v0/C7nG3fJFIJOcNGCJBSoYRibdBixi1jjAJn590qzbDP3sI0z0weIlIxed3ma/UzWZsJpAGjrm6x5jWZtIucbi8TyBilJDWrSMl0cXSTpbsE+wkth9COoozDqOh1iM6i4lVI6qAao329AfpU2izCJikxVQAiEBOkeRwRyCHQJSUaJkeWidHtsxymtZdcS/9dTILw0uBQfQbkGogCwlhI1RaEgAMqQgUvp+cWoafHpnEYYezPajx38MMLWzf5SG0ff7N5kZLpbiNdk1Gr04xTZu9drGk/rLj8xjV6rQGTdwmBzJdyHP7oQU5/8xxJIlm/uoFMEgzTZO3yGsOBz9Z6i6c/+wSaJphcqJHECWEQUb+2QdwPaSxvcjpRlCeLLByc5dFPnmDPiSUay5uAolgtsHzuJihJMAypX2+wfH71XXtZlFKsX65z4PG9hH7I6W+cQzd0CtU8k4sTxGFEEiZ8+99/j/VrDWqzVYJhgGEZuHkXN+dy5fR1NE3Q3eqjG4L6jUZW+3nk6f2YlkmhkmP5/OrdyYZEpi6ve2RdjKHpWrqY2fdS60rOzqo93w/skA1/hxgPu+fPnycIAlzXRdd1kiTJahvHw/CHAe8k9c/lckxPT7OxsZHZHRzHQdM0NjY2sufEcZxlHXiex8zMDFJKBoMBURTRbDYpl8vbcg7GNoJxCGNyK/0JwzBSH3qUSjXHg7tSKiMGut0u5qgHV9M0SqVSRoTkcjkmJydZWVkhCAJKpRLVapWpqSlc18XzPM6dO0e73c5UGK6b1vWYpslgMMgyHDzPI5/P43keQggWFxcz5cT9iIJ3suzEcUyr1aLdbvPKK6/stFQ8RIhlQjdK923JdO+bSh0kES81zrMV9jGFTpDEXOqtUTbz7ClMsuF1aARd+nHAYq6GUpKVYZMbgy0+OrmfspkqgPqRTzfyWXCrNIIuB0f++e/0L1Ea+amVUoQyRhOCouFytrOCJjRCGYPSaIc9brYbdP76LG/9/l8yaHb5+f/ilzOyYQwpJVNzE8zMz/Otb70ON2N2n1hiet8Uf/rVTfrDHvFAUq3WeLXxEhWnRC03xb7FvXQbPfxByNLheU5/4xyVmSq6ngZBhV7E1dMJtVpIacrmyumI1sYxqlPmyOOfDg0T85KrZ+oceOoclnYFtPlRsGsE8kq6um0cBmM/JGuo+AY4LyL0v73k8u8HQRLRi30MoVM23fuusnfCId9snMNLQkyh0489LvXq7MpNMuEU2fR71P02oVVgxikRqoRLvQ064ZA9+Skc3UQqRcPv0o99pu0SgyRg2imTKMn1QSPLZUhDR2N0oVE2XU51ljGFhp9ESAVXvDpvxNd4vLKHut/G0c07VA9jaOYBlLGECk+BfBncT6eZDtFrKYkghqDtSxUKSktJA0FKTmgH0/3p/T5gp6vQygPljwIn/dHKdCcdRNGAAehLoBkgyxC/hQqXQLYRekrwKjmEeBVUe7TSPQnRuXR13X7xoSUchnHAMAlxNPO+km6AtWGLl7cupsFnQmcz6HFz2ORgaQ5L02lFA7qRx6xTpmrlGcqQM52bWJrBodJcFnh3fbjFtFXk+mCT4+UlCmaBTjikF/tZYGiiJLFMMDQdWzM4310DIExCpFKcbl8nkpJPTB9hzWuxmJvAvMsKsRAawnoCZRxCBS+nGQrufwjhyxBdT6sxUaAdAD2f7nttGlQX5CaYzwAC/K+mGR0qSs8fiJSwIIakO1K+TKR/R4I2MSKwbIjeQsk6YCC0dIVRJVuQ3IAkBOvjgAXh91DJKtif/FCqqT5sWMxP8gnN4FT7BnWvk0njdaGxvzjL8fLih6aFIgojrp1evm+N4+R8jepMmVN//RaV6RKWa6f39j2fXCltiqhf3aAyXaK71WflwhoT8zWmFicZdIZ0Gh12H18i9iPKU2WWjqTX+mKtgEwUMo5oLG+xfGENJSWt9c5diYah6nODC6xxg4QYHYM5drGLQ+TE21u6FI2bW8zunSbwAg49uY/5/bPU5muUJ0soKalf22Dlwhq5Ynr+zZfzqYpTpgQIQDAM8AY+SsLS4Tlqc1UsJ70313SNKLgztBtAN3Tcgk3oh9nz3w4pJSsXV+k3BwTDAAUYhs7eR3az5/gSTu7u1+HvBztkw98x8vk8J06cyDIKxvWGi4uLH7pB70Gk/oVCgUajweTkJMPhMMtnyOfzVCoVlFKsrq4yPz/PysoKhmHgOOkv8Lju8sCBA4RhyNWrV8nn81iWRaFQ4PXXX88CGw3DyOolpZRZNoKu6wyHw2z7QggKhQKbm5tAan0YN1CMsyGiKGJ1dRUpJaVSiampqdT/3m5nn2t2dpYgCNB1fVvQ4/jv4zyK8WeamJigWCxm5ME7ZXvcz7ITBAE3b97E8zxmZ2d3WioeIiwPNnm9lUotIV3pe6y6m6X8nVYiPwl5qXGBDb/Lwqhm8Fq/gRCCbuwxSAIQ8FhtD2vDFt3II0xi+nGAQnKl32BBRrTCIa1oSJCEXDBzTNjFjGxIA9w02sGA68MGgzgEpcibDsuDLT41c4zDpTm+dua7/Om//gMu//uXmTq6hxf+0S8SdgY4he03Ev1uj1w+x8TsNImUEEnKZo5itUihkuexI0/y3Te/g5cMMUKdg5WjnNl8g597/JfIF1xkmLD75BJLhxY48Pherp5ZJvIjTFuQRJIkMVm5cQTTXWdrdUC+KNObf30StNR+oesS0PE757EmareG82Qj9WDri+kKqDiAEFWU7KHCVxHuix/QXn93kEpyrrvK+e4qcmTHKhg2T00c2FZrOkYvGvKX66fQhJYNeDeHWziaRSPs4uo2BdNh2t3N2rBJJxriJSHDOCBSkovddRbdKiGpLWeYhHTcIU/W9jHtlNNzIICCut/mxnCLSMYIBK5usua3+czcY8RKcrq9TCRjppwSm1GP0+2bXOzV+dTMsTvCJW/BSjMTjL0I4aLMI5CspAQRKrVEyDhVGOjlNKlSWGAeAeMgBIuQ9ED46XNIUoWCnE4JA9lOyQVhpHaJTM2iAVHqzdduW3VMrqc+HzEFqo4Qs6BPo5INVHwRYT36/uzo9wmRjHm9dZ0bgwaQ1lTO2GWenNh3B8mjlGLD7/CX9dNM2kVyhk0sEy721sjpJpt+h6LpMudWWXCr1P0OzXCAF4dEMiFSMVf6DXblaiAEMom50Ftjn5phGAe4hoUkDYBLRgTomtfKbBNSKqRQfHzqMMM45I3WNap2EUszuDlsom1pXO5t8InpI3e0oWQQRlppaxxKW03Mx1NiKmmNGiK0VKGguamaRdkpSWUeBXIjIkum9SpCATGIcvo8+iAT0F3ABH1P+j4wasHojmw2I2JKSUgupWGSI5WNMPaAPodKVlHJKsJY+iB2+w4eMsy6FWacMu1ogJ9EaEKjauXvaa34YcWgMySOEgzz3uSKlJJBZ8j+x/YwvWuSXqsPQK/VZ3rXJLquE3ohF793hSROKE8WESM1sltw0A2dPcdSW/rGjU1WL6+z68hilgexfG4FJ2+DVCRxklmkb8emWuNNXiY1lqbX2YSYFa6yynUeUc8wKW5rdVDQbnQpVPO4BRfN0Fm/1mDl0jq2Y7Hr2CIT8xMUannWrzeY2TXN+BZEaALTMtB0DbfgYPcsLNeiMl3eRhz4w4DK1J2h3ZBm2Ox/bC+nv3E2C8V8+3d65Y1rXDuzzCOfPM7ESFUSRzGXXr3CzfMrfOxnnn7PwZEfrqP5IYVlWczOzn7ovfIPIvUfDockScL09HZp2bVr17L2Bs/zqNfrWc7BGLdXYd4eiFir1djc3MQ0TcIwpFgsMhgMiOM4UxT4vo+u61iWheu6SCnJ5/NomobneUxNTRFFEZ7nZaGUhmGwsLCA4zisrKzQ7XbpdrvkcjmiKCJJEur1Ovl8nomJiew7eDvG6odxs0a1WqVa3e6/eqdsj3tZdsZZF5CqQiqVSvY97rRU/N2i7nd4efMiNbtAZbQqGsqYlzcvYusm06MBMZIxf9O4wDfq53iru4yjWewrTfN4ZS/rXpuy6eIlEcuDLfw4zKTJy8MtDpfm6cUehmZyY7jJm50b6QLw6CIqEJzqLPPHq6/xy/teIEpiXmteZWNk0bB0k7xmsRo12fQ7nHrpFf7gX/8bXnvpOxz9iY/x9/7PXyO/OMGUXUYfxLzxtZfBizBGeSa5fI5nX/wkhmHQDvrMqiIq8FNr0c0tjMTgiYNPsXztOmEcMTlzgt0Le/jq5a/wj0/+N9Tmqnzui5/m8EcOMrk0wb/4z/4V2GlOimYYFKt54jBmY32awpSOYbVwyovp0AmAQsYdlDaL5USkkvsRZD1dyRT6qL4uHUiEVkQl6yg5fKhWqy921zjdvsG0U848voM44Osbb/Hi3KPkRwNkP/b52toZ/mbrAld7dcpmjsOlBQ4WZ+nFPhUrRycasuptEcgIR6UEaj8OmHerdCOfQRJysb/GK63L25ztjmZS9zr88t5PMZUrMYx9/rp1g82wh6OZWLpJwXC42F3H0AykUnTDIYPYZ8YtIyANIdUNNAGvN6/y/Myxe/zEPsguQp9FISE6d4sYkCN1glFLiQVjCTBBdRHOjyL0WaTyoP9bgAuaAKxU+q71QXsW6KUr0/rCiIxg1GjQA30fCJH5fJVK0kFWlIF4pJAYQatCfCnNB3iI8MrWFda8FpN2CW1EkDfDAd/aOM8Ls8ezFdWG3+XPV1/nu80r1L0OE3aBRyu7mXJKxEpSMXO0wgGDKP2Z86aNn8SYwmDCLtAMe3Qijwu9Vb69dTENjkVgajo3Blss5Cb4kdljtIIBa8MWrzev0ou80XnKIWeaXOitcaCY3h9t+B0UMGWnxHknGlKxcnSjIZf6dY6X73EdlB2AUX1qANFbo2F/FuQNUjXCLFiPgF4DrPR4cX8SoeWR8UXw/zQlIgRALiUjVAeMpyC5mVoo9InbjpcIiNL2C267tqtheoxoFVBh+mcMUUiJqx2y4UMDIQRV68EqDH+Y8U5RN73mgDhMgxUr02Uq0+n1etAZ4g8C9LyO5VqsXl6nWCtkRAOAPwioztxWszxZ5NKrV1k6vMCpr79FoZKnPFmifr3B5OIEl167eoeqYaj6vMnLSO5so1Bpqgxv8jLPqBfvUDiMyZTz37lEsVrALTokUcLyhVVm98wwu2+GN/7yDLN7ts82+Uqe3lYfy9WII8nCoQnajS6z+VsqNL/vs+eFE/f83hYOzHL11HW6Wz1KE9sXHOvXGtw4u8riofmsEhPAMA0m5mt0t3p87y/e4LnPf/Q9ZRHtkA07eGjwIO0crVbrruqHcrnM1tZWVnNZr9eZmdleBTMOUxxjHIgIqfVhfn6eV199NVMQjDMRxs0QY2vDOCPi5MmTrK2t4fs+s7OztFotqtUq6+vrFItFpqenMU2TJEno9/vZezUaDarVKrZto5RiOBzS76cMrZSSJEkyUmT8vQwGA6SU29QMt/9c75TtcS/LTqvVwvM8crkc8/Pzd7z3TkvF3x3eat+kYDrbVjgszaBgOJzt3GTaKRMlMX9487v8+dopQpkQSolSIa81r7E6bDHjVCiYDp1oSMPvkihJKxqw5fdIVMKV/gZrXpNVv51dV2+/vqahbIqXNi/w8uZF9jtTbMV9IpmAAFMzEH5C42unuPLvXsLVTH78l/4jfvyf/ecIO111jBKJQlKpVTjx2Y8zFziYkcLNuUzMTmMYxihNXnF8bjebvU3Wrm5w7cwNlCRd6SlOMGgPmZ2dY455urLD//Xn/zv/03/7L9h9bBcA+07u5vAT+7j21jK6rqObGv7AJ1fM8dGffIrWRhvPb1CI2ujZca5obxVZPPI4TqEzkuCPb0hGAYMqGHnyb1txEXcLjvu7QywTznZXmbJL28LE8oaNF4dcGzQ4VlrASwL+70tf59X2ZWKZ7ttO5PFS4zxrfpOKVSBWkobfw09CQhmzqfVY9zsUdAsvCbnQW2WQbCdFx9+ELyNeaV3hjfZ19uSn0ITg5qCJkhKhp5kOlm6S001m3DQ8shF0cTSTIIky6bwCioZLI+jdNUQyhc44qRy5AdHp0ZAnRvaJKB0eVQs4MCIJpq9CdYAAACAASURBVG6pEayPgfFHkDRTUgGRKlm0GbA/mg6Psp42X4wl7UqCVgP7ExCfQakQcRtxlf7HTy0UGR6uYwVS+8zKsHlHTWXNzlMfWa1mnQqNoMvvXPgqVwcbBEmaldAIenx1/RRHy4s4ukEoY1aHbRSKWCZomqDutZmyy0RezOV+HV/G276FBIiShCuDDf6Xs3/Il69+i2m3zKrfZn3YQqEwdANdaOR0E0sz6UU+/chn3W+TN2yGSZhWUat0hbFq5bncW7832XD77W58GZLLo/2uRpkJalSt2gCWUnuFeRShjVR97mchfj0lBsavowvGETCPpWqp5GaqilGjUFIF6LvBehLClzK1Y4rxtxGB9nbF4Tun3u9gBz9MyBVdhIAkkfdsTQi8gDiSFKrblbZze6c5951LqdxfCPxhQPm2lX4pFXEUMb3r1nnZydlsrTRpb7RZvbROruTi9X2GPQ+ZSJL4TkLhBhdSYvs+UEhucJEjPH7rManoNQfkSi52zs4+n15IF13Wr62TK7jopkav1ac8ceuz54oug/aQdqNHbbZMZapCHMbZvzfXWkwtTd61pWMMy7F45qc+wit//gaN5U0sx0I3dYJhwIVXLjO3b5oDj++9a65DaaJI4+Ym7UaX6vS9LS7vhB2yYQcPDR60nWN+/s7wsGKxSLPZJI5jdF0niqIszBHI/n77e48DETc2NhBCsLGxgaZpmWIhiqLs/XK5XNYuMc7TWF1dJY5jkiQhDEOGwyFBEBBFUTbI53JpguzY/pDP51FKZVYNIQSu6zIcDlFK4ThOpqIYZ0BEUZTZM3K5XJbR8P1me9zNstNut5mdnaVSqdyT5NlpqfjbR7rK2MvUC7cjb9jcGGzyzfo5LvRW+fPVNzA0gxm3jFQJpm5gS4OG38UUqUd63esw51aIZEwvDmiGfXR0Cka4jWi4H4L2gH/7T/5XTv6zX8BcquGtNdn8o9eof/VNph7ZxxP/6Gd57pOfZHdxilOtGySBRyhjNqIOlqZRNvMYpkFtYjrz8UPqGe/HPs9NHWF4ssubzYCNGw2GHR+34CCMtLe6NFWifm0DJ+fwI0c+w59c+rf82amv8B/kfhJIh6Unf/xRFg7NsbG8ReAFTC1OsnR4Dt0wSGLJoY88ylsvvYmgj6YJksSlOjfPiY8fRZgdVPBnKOWmA6Q2kw4lQoFxLOv4VnKQEhLi4VE1DOIg9dHfxd+bN2zOd1ZYGzY51b7BNxvnKRsuNStPohIcPR30r/c3oZAqH7qRx578JFtBH0+GdKMBSiaseu07iIbboRJJ6/R1So/u5lJ/nYrupiQCEhUrXM1CFxqa7tAMeqz7bbwkZGXYTJ+jFIGMmHXKmX0iUXe/uRPCQhm7IF5JJe7I0X6BrJIwuQCiBtoNsB5FWE9magSh51H2J9JmgmS0sm3sBm0J8EaVhU9A9EYqdUcHkQfzGMI8hBIahN9GjdpKlJhImwlQYCzc+qCyDeYHk/D9btGP/XuuUhlC43T7Bq/Kq7zcuMCZ9k2mnBJ526EVDrA1g2Hsc7G3xt7CNFthn0jF7C1Ms+o1GUQB3cjHEibL/lZmAbv9HCPDmAv//e9z+H/+Rbwk5NxgjU48REMjkFGqfpAxOd0iFBp53WZluEk3HNKLPNaGqcUiVgkCjc18jzm3Sizl2wb626BVQcuhZBfC1wF79Dus0pYIIdJWClUGfR3MxxHm8ezlwphFWS8AXprjggXGvlHDxCZYT4Pcl2aHEAJ6SiJYT6OZe5ByFZJrKKZH2zUh6aQqK/02ckoNQHucHezgwwTLsVg6usjNc6tUZ+8ewKyStEGu8rahtzRRYmppgsbNJoVRxsH4HJDECb1Wn7l9M8hEcum1q3SbfYRIFxmvnl5m0B1y5dQNAj+iWM2jGwY3zq7csf01bmTWiXtBoVjj+jayAVJbQr6Ux7B0Ai/EHwTky7nRz1Nh48YmE3M1bMccVW8a6IZBFEZoukZ1usT8gVm8nkccJbQ3OkRhxPSuKZ740ZPb5p27IVd0ee7zT9Oqd1i9vE4wDEmimP2P7WHx0J0z1e3QDYPGzc0dsmEHPxx4kHaOcYDi2zGus7x582Y2rCdJ2qF7+8r/ysoK9Xo9IxEmJiYoFAq0Wi0Gg0FWP6lpGrquZzaKcTikbdv4vp9lLhSLRebn57fZLSzLyoiCTqdDp9PJrAnjLAjf97MsCQDHcRgMBkxOTmYtGr1eL+0AzufZt29flg1hmib9fv9dZXu83bLzyiuvUCgU7iuP2mmp+NuHEAJTGEQySSsrb0MnGnK5v0HVzhMmcebP3/R7OIbFMA4y33KQxNwcbOLoFlW7gI5grXmVMIlxDI23ujfvuHQmw4Dm18/ir7Zw5qvUnj+KMHQu/Q//L7Xnj9HdaFL/P/6CwbkVpj79CI/81n/K3NIiZTvPqtfC0g0GcUDFyiGVomS6+DLmfHeNSbuAMQoF9JOQQMYUDYdPzRxnwi4SHy6wfH6FTqPL5EIN3TIYtPuYlsnkUg1NCAq1Aj/+n7zAPzn2D3nmmWf47d/+bb74xS8CsP/RPWyttnjshRPbWPrNm1sceGIvBx7bx9y+WTZubBIFEdWZChPz1dGFegplPQ/hd1AqJJ1a45R00CbTWlrVS4cB60cfqnpDU9NTB+ldBq2632bd6/BIdRfdcIimBKFMaEdDLM0kTBIszcRPYrw4op90qRh5ylaOnGHzrcZ5pFK0oyHdxN/23m8/VuK+T/e1a5Qe3U2sJM14sG0daCgDkkji6BYWBjcGDQSCQEbkdRtfRSy6E2wGPegJZp3KPUMiAYT5KCq+BskmoI0k6UFKOhi7Rk0RZXA/i2bs2f5aYaY5D/FZhPl89niqlOghrCdTC4V5CJWsp6/RZ0FU0+/YOJgeJ/FplJQgXEj8tJKTfPo+qg1CRxiH38Ve/eBgaPq2muXbsTzcQhcah0pzbIU9LN1gmKShYRqChHT/9SKfQeTTigbMORXKpkuSlPib3iU0Ibg+bBDfYxVwcH6VxA+3HavrQYdRcgaQWrn6SZA2lRgOKLg62KAdDNA1DVPTUVKx6Na4NmgQyJhDpfl7/l4KoYH1LGrwb0bNJYWR3SVIWyO02TSnxVgA92fQ3t44I8pgLqTWHfPW/lQqAhKEeRDE4yA3UEkDhIXQFxDaaPixnkKFIm27Gb+fWgHjcQQmSsWpskqbRBj3v/nfwQ5+GHHw8b1sXGvQ2exSntyeQRAGEYEXMrd/+o5cB6EJ9pzYhZ2zWbtSB6XotwfIRBL6IcWJAutX61x45TJxGBP6EXGUKpd77T71aw2klLTW2gy6aRbb3TiFhPjOB++Cuz5PgWGln1s3UtVlvpxDJglJlIyeonjmpz5Cr9ln/eoGYRCRL+fZc3yR6myVXrPPtVPXWTg4R22uwsKBOSpTpQe+F9E0jYm5KhNzqQ17c7VJ4+bWO75O1zXi4MF+9nthh2zYwUODB2nnOHnyJFtbW9sG9TFs22b37t3U63V0Xc8qLCHNJrh69Sq6rlMoFMjlcvi+T7vd5urVqwRBkBEBcRxnrxkrDzRNwzAMoijKQiHHaoViscjKygr5fJ5+v0+pVML3faSUWUDl7e8vhCBJ0vCZMAwJgoAgCAjDkPX1dZRSma3hdttEGIZUq9X3NT/hQawr7xQ+uYMPBoeKc5zuLGfhfWOc7aww71YpmTkSNkEDS9dJpErrJA2HfuwTKUmsJHnDpWy59COPraBPP/aZsos0gj6R2i4V7J1e5sKvfRmUQvoRmmNy/X/7KvmDc8ggpvnNs7S/c4mZzz3J/n/6s+iOiYHGVtgjb1hMujVCFWPrBt3IYz5XY8LKI1Fc6q4z7ZSwdROBYNatsrcwzYR1i+wyTIOTzx3lyhvXufC9K1i2yezuKUq1ArppEAwDhj2PXUcWKJYL/OEf/iHPPfcchw8f5oUXXmBu3wwHn9jH5TeuousGQkt7s2f3TnPwiX1AWqG198Suu37nmrELpc+n0nkkSnwOoouQXCH1dE8hzI8j9Kn3fX+/F+QMm1mnQjPsU7VuSUxjmXChV+ex6m5yhk2iJAKFa5j4SUTFzOGJtMEikjFSScpGnpKVYyvos+a1UMCEXeTqYGPbNt9+rAjbQAUxe//rn86e8/ZRUwKhilnzWuwvzFA2c/RH7QJ+EjGfq1E2XWIludKr89zUkft2zAutgLKehvhaqkLBGFklyiNLhQbCQOgLd3+9eRwlW6hkDRhL6mMwj4O+kB6XoobQ7pSoCiEQ1gmUeTBVL6ChEGkWgBytium7EebJbOB8WDBhFbB1Ez8JcfRb5/Ze5FP323xi+hjmKFNDFxq2buIlATWrQDf2iFRCqNImmqqVxzEs1rw2NwdNXC39/W4xuGO7Y3Kq8RdvYpRckmGAMA286w3yB2a3OaEVKeHgyYj6sM3u4jSGplMwHTaDHiXTZVdukoKZnu9uDBr81MKT9/25hT6Nsh5LlQjJMpBP8xREYRTumYA+fSfRwGil1HoWFXwtJZ+ESZrPAVgfQ2ij4UifzYIgt7/eRNjPosyTqV1HWKjEg/gUKqmnVg7zKMI8ulN9uYMPJdyCy7M/8xRv/NUZGjc30yYZTSATieWYfPzzT7N8djUlI0Y2iSSRdBpdGsubBF5IEiec/MQxbl5YpbneQjN0Nle36DZ6JInEydtMLk4iBEzM11i5tMalV69SnixhOSZJLO9JxOoYD0Q46HcZrYWA0I+wnNSylyQJrfU2/sAnCCJ6mz0s1+KvvvwSC/tnqcxUmN8/s410icOIZz/3FI/dJ5/h+4HtWij5zrrWKIzJV95bSPwO2bCDhwrv1M4BaW7D7eqHOI7p9Xq0223CMPVx7t27l1OnTmWBi81mE8uy0DSNwWBALpfDNE0qlQrLy8vEcUw+n8c0TZRSme1CSslwOMzyFcaNFJCyhI7j4HkeSqmMlAC25UXU6/VMyTDOg4BU9TC2WIRhmIbaaVr2eBiGNJtNZmZmMrXF+12F+qDWlfuFT+7gg8H+4gwbfpd1r03OSPd5PwqQCg4U0uNr2i5iCYMgiXF0Cy8OWMjVyOk2SnU4UJzFSwJMzWAj6BAnCXNOGUe3WPU727aXDAMu/NqXkd4tmbz0U0VP/9QNzKkixeNLuLsnMSeK6E56QzxevWyGfX6s8AhVO0/RdFkebrEZ9OjFAZoQHCjN8+n5RzhQnON+yJVcJuZrPDtX5cqp65hWuh1/4NOudzj+3JGsDurgwYP83u/9Hr/wC7/AN7/5TQ4cOMDxjx1m6fA8G8ubJLFkciGty3onmeEYQowGVkaKfPsplHoSkOm/PaR4rLaHb9TPUvc65AyLWElaQZ9Ju5CF6c3napzrrRHJZCRZT5iySwziAIHgaHmBDb+LrRvcGGxiaiazdolIJdsWeu52rKjRysf1f/lnVD92CM0x77rikr6TYhAF7MpPUrbyCATXBw26sUc39jGExt7CNJPO3RO2b4fQyihjb+q3T24ADpCAHKZKFOvT9xzehLDA/hTIxmjgMxD6XFZP+CAQwk5XxhkdL/rz6So14qGtLzQ0nWcnD/KNxjl6kY+rWwQypuF32JWbys43806VN4NlbJV+f1IpZp0KW0GfnG5zqDjHTa+JQLAy3KJsueQNm8v99Tu2eQc5Zei8+h//JrprUTg8z8F//oU7jpf0SFEMVIiBxoxT4bHqHvqhzw1vEy+JaEdDcrrNVL5E8R2qO4HU9mAeSkMgZROwgDi10ygJ1kfu+VKhFcD5TEpOyTYIZ6ReePAb8ZR4GqkdNMBcGKkj9Mzis4MdfFiRL+X42OeeorvVo7XRIYkTCuUcE/M1dEOnOlPhb/7gu7TqHeycxaXXruL1fUzbJPQCdEPn2pkbXHvrJk7OolDOs7nSJhwG2DmbJFGsX6mzeGiOUq3AmY0OUil6zT7l6RJuwWbY9e8atTPHLla4el8rhUAwx+47HrdyNjKRDHsew75PEsXYrg1KEXgh+UqO8lSJfCltpUgSSaveYe/JJYrVAsOux9y+aU48d+R9+66L1QLV2QqD7pB86e62UJlIhICZ3e9tgeXhvXPawYcW79TOcbv6QQiR2SIglfyXSiW+/e1vA2kVpe+n0l8pZaYw6PV67N69m06nkw3ycRxjWRa2bWe2CV3XieM4UzGYpkk+n6dUKmXkQafTyQiAUqlEt9ulXL61Gp3P52m1WpkKYmzZuN2mMa7ftCyLSqWStVlEUcTKygqPP/44MzMz77vC4EGsK+8UPrmDDwamZvDx6cPUvQ4rw1Tq9mi1iia0zCIwYReZccqc7ayAEGiArZskSjLlFKlaeYq49KIhKLB0g17k4SURkdzey9z8+lm4B6OPoVE6uRt39yTxICBsdO94ipdE2LpFgsI1LA6V5tgrp4lkgqXpbIV9XP2d+5pt12bx0Byrl9Y59uxh6tcbDDoDnJzF0tEFnvv809ue/yM/8iP8+q//Oj/90z/Nyy+/TLlcpjRRvCN1+b1AjFfJH2IUDIcfnTvJ6rDJut/B1gxOlpf4XvNKNsTtyk1SNnMsDzbREDiGBShiKVnM1SiYDr6MSVSCJQw0IejIkGbQ37at+x0r0g95/Rd/C2uqxMnf+Qf3/Lz92MfRLRIlqdkFTlq7RiGRCls32RxljrwjtMlRq4CbpvsnK2lIoyiAOY+w7z08wmjf6jMIfea+z/t+8DCTUmNMOiU+PfcoNwdbNMM+RdPhSGme0+3l7DmHyvOc7aywOtxCoBHJhDCJSFDsyk2QM5yRYkbh6uZtmTDbVQ13JadGAWwyTNj/333+vlJgBXRjD1e3kEox4RapOQX80TnMFDqdcHhfFcwYQl9EidfA2A9yCpI10trTElgnEPre+79emAhjF3B3ddS7wY6SYQc72I57XcPzpRwf//zTnP32Rb72e98kjhLcgoOME+b3zzLselx58zqze6bw+j6BFxIMfQzTII4iomZEeaaEW8zRbvTw+2PbdYxSCsuxCf3UZv32kMhdHGKV66i7tFGMIdDYxcHtj2kCJ2+nyukoYdgeYOZsQj8iCkKcvIPlWLgFl6nFGuvX6mmgZMHm7MsXeeannuTZz32EyYXaAy+aPCiOPnOIb/67b2NaxrY6TUiDNTdXmhx++kAavvke8PBfEXewg7dhrH6o1+u89tprWbBiuVzGdV0uXryIbdtYlkUcx5lq4PabGdd16Xa7rK6uZtaG8cCtaRqmaWbNEGNUKhV2796NYRgkScJgMKDf7xNFEY7jkM/ncRyHTqeTERPjbTmOQ7/fz2waY2IhDMNMGRHHMbZt0+l0MtvIOAzTNM0PxMrwINaV91tNsYMHhy405nNV5nO3Vlr3FNqsDpvU7AIbQZeSlWNPfooVP01xbwZ9FnM1Hq3sYT5fRQDf3rxEJxpSNnMMooB2NERsc0iDv9rKlAx3IJaYk0XmvvDsXf9ZA1zNZNXboh/5hOWIuVwVSzMwNZ0giTCEztQDrFQDHP/YYYZdj621FrXZCpXJEgrFiY8fpTZ756rzF7/4RU6fPs3P//zP85WvfOW+tqAfZliawZ7CNHsKaeOCVJJz3VW8JMTRTFb8FjN2GSkldb+NUopWOOB4eYk9hSn2FKaYtEu81DhPL/YpmTl6kUc7HG7bzn2PFQWTn36UXf/gR+/5OTWgZLlc6K0Rypjj5SUmnWKWNdKNhtTsQhYSeT8IoYH9HCr4a5AhaPOpFQIDrOcR4gFWuz+kyBs2h8u38gG8OORM5yaJkkil2PC77MpPYvg6W0GfUMZ0Yo9nJw8y6ZTZlZ/A0g1e2ryAJyNcYdEKeiRvM9Dcj5wSIv33qR+/dzWoBuR1h/PdFXQMjlXmKVt53JEFpOF32V+cvWtA6h3b03Io6xMQfiOVFui7SLNZCgj7hYcqi2UHO9jBnXALLtO7pth7cjfFWgFE2i4RRwl//fvfIlfKYbs2MknPOU7BIVdw0kY4qXAcm8byJr1mN1UxKIlKoNfuU6oUcXI2QT5k2Nl+3cuJAo+oZ3iTl1FpSlL2bwKBQOMRnrmj9lKM/ng9HztnUZkqU5osMuh6+AONJJYMu0PcvMPa5TpCE3j9IdWZEqGfNnVNL03yQWBirspHf+IJvvcXbyLjHm7JRQhBMAiI44SDT+zl0JP73vN2Ppx3ZDv4gcc4hHGcazDGWDXgOE5WUymlpFAoZIxgEAT0+308zyOOY0zTzJQRY3JB07QsOwHSFf5arZaREs1mkyAIKJVKmbqh2WyiaVr22FgpoWkalUqFra2tNPjPNLNGiSAIsuaJTqeTZTy4rovv+2xtbSGlRNf1D6wN4p2sKztEw8OFo6UF1r009O9Kf4OqVcDRTBYLk+zOT5I3HPqRR6IkQRxxsZdKmpWCzaBLoGLyhkWkYqLbmHtnvormmHcdIjXHxJnfPuRr3FIZ2hjYuoWfRAQy5kz7Jhd66xwrL2DpJij42NShbTWe94PlWDz7uY/QXGvRrLcxLZPpXZP3lPoB/OZv/iaf/exn+dVf/VV+4zd+44G288MOTWg8UdvLNxrn2JJ9Nrwu026JnGFxtLzAYr6Gq9s0gz6ObrLhd7g+2MTUDGKZsO61QCpc3cCTt1al3+lYye2bRrytvkzc9l+b1GKRSEk/8nm1eYWc4XCsPI9UkDMsnprY/8CDn9Aq4PzESN7eBZFDGAupxWEHDwzXsDhZWeK15jW8JKQf+cznqhQtl4qZZ9otY2k6rWCArelc7W+w5rVxdZNm0KMdDzDQEYhtN+L3I6ekH+GvtrY9Jt72/3nNQQlFpCTduM/LW5eoWQUOFmaJVMKkU+Ro+e65HHeDZsyj9J9BxStp04hWTu0zPwCKlB3sYAdw5c1rVKbLuIVbZHJjeYvAC7Hc9J7Vckxa9TaGrmer9kpBZ7ObNbrppoZSGooEQ9PS1ztm2gZh6ll44xiTYo5n1Ivc4CJrXCchRsdgjt3s4uAdRIOma8zunSaJEuIoxtEcDFsjiROG3SFCE1iWgTcM0AwNt5QS7AqFnbPJl/N8+49e5cjTB1k4cH8L6rvF7J5pXvz7z7N2dYP61Q0SKVk4OMfiwTkK7zGrYYydM+sOfmCxsbGB625f+RqHQmaBc6Ohfhz4Ms5CALI6yTEJMSYClFIUi0U8z8vCHDVNY3Z2lq2tLfr9VFI8bmkYv/c4CHIwGFAoFKhUKnieRxiG+L7Pnj17UEpRr9ez7IfxnzAMsW0bTdMyoiNJElzXJYoilpeXefTRRz+wwf+drCs7eHjg6CYnK0t8b+sKg8jD0UwWchPMuuVsZTiWCdf6DdZGeQ+TRpGkKDnTXk7bKoTJhFWkG99qF6g9f5Qbv/P/3X2jQlB7/ui2hxTpIGCiU7BcqnY6jHSiIQcKMwzigLrf5cXZE+wpTN+3VeBu0DSNyYUJJhcmHuj5hmHw5S9/mY9+9KMcP36cX/mVX/m+tvfDiqpd4GR5F99onMNPAvKmxf7SLDNOOZOdt8Mha14bPwkpmS4Fw8GLQy50V/FlhKVZCIbZ+Pj9HCu3W181wBYWBdNh3q0y6RQxdZ1DpQU2vA7NYMCPzZ1kPld7YGLq1mbH8vYdvBcs5ibwk4g/XX0dqSS6pnO8vMiEXcyuq3UvJaVCGVOx8uQNm34Y0A4HxFJiCp1Q3QpS+36IzNuJBg1BTrPJGRaLuQmm7RI9zeNEZYlL/XUiEj4+fZgpu/RAqobbIYSDeMgqSXewgx08GLyuT76yffFh0Bli2mYmotINHcM0ssYugDiKGPY8itUClmvS3exjWAZxGGHlbCzbAgHTSxNYlkljZeuO7IacKHCEx++ot7wbLNfi5CeP0W102XtyF2deOkd7o0sSSTRdw807RGHMxGyF0Au2v1iBYRk4RZdT3zjL7J5pdOODyQGyHIvdRxfZffSDyWd7uE2oO9jBfRCGYRbWOEYcxxnBAGRtEmOCYaxggHSYsW07Uw7cTkwkSYLjOMRxTBRFTExMUC6X8X0fz/OyWk3DMMjn85mKwjAMXNclSRKGwyFLS0vs2rWLfD7PoUOHOH78OAsLC5RKpSykcqxmGNdqAlmOxPhzappGs9n82/had/AQY9Pv8ierr/O95pWUKBCCip1nMVfLiAYAQ0t1B6GMs6GtYuaJVDIa/hR+EqLfdgnQczaH/vkX0FwLbRT+qDkmmmtx6J9/AX20WqAjsNDQERR0l135SVzd4khpIRsUHN1iX3GGhVyVspX/vomGd4tqtcpXvvIVvvSlL/H1r3/9b2WbDzOu9jf445VXOd25QZBEIAQzdpk5p7LN3+4aJq2wj6kZ6EJDQFqtqmIEYAgN/bb8hAc9VgAcDEx0DAQVM89srkrRdNhTmM7O00XD5lhlgapdoGYXv2+iYQfvHVJJ3mhd509WX+dibx05CkReyNWYdLbXq7m6xUbQpWi62fFRMB0iKUEoyvp260rt+aOpX+JuuI2c0hG4mGgITHSm7RITdoEpp8SsW0YqiakZlKwcj1b3pNasd0E07GAHO/jBhumYxG9THWi6IFd0icOU1JQybZ8o1gp4/bS+3e8HCAGmbVCZKqf3/FLiFty0MS6RBF5A5Efkyi6FSv5dW6tM2+Dv/9rPgVQcfvoAR54+yMd/9qPsPbGbfY/uZm7vNJXpEm7exnItZKKQSWpBUzIlGqIgoljJE3ohW6s/uDPAzhV9Bz+wuFtt43jYHwwGWJaFUop8Ps9gMMiIgzEx4DgOpmmytraW2R+ATIkwDoL0fZ+FhQV838c0TYrFIkqpLDxRKYVt2wyHQ3K5HIZhZEGU6+vrVKtVpqamsG0bIQTz8/NsbW3hum5WmzlWWYybKuI4zuwhYRgyNTXFxsbGjvLgQ4x+7PONjXMUTJuKlaNmFWj4HdaGLXQE+4ppwJ1SilgmzOdq3Bhs0o08XN2kEw7I6RYCwTAO0NHQhUaibvmriyeWeOz/+S9pfv0s/moLZ75K7fmj24ZHHR2QEFFDRgAAIABJREFUGELH1HR0obG/OEPVzhPJGFOk9XSQrkz6Scj7DSklzfU2vWYf0zaZWqylyc6kAbK/+7u/yxe+8AVeeukl9u17737DH0TU/Q7f3brMlF3E0HRyuk0nGnK1t4GlGUy7aYhtLBN0obHg1mhFgzS4UTPphEMKukusEvqxT04z6d6WYfNgx4pGgkKgMDUTQxg4usH+wiyubjKIAypWPiPKBBAmETxAVsP3gziK2VptMegOyRVdJhdqGObO7c/tuNhd40J3lWmnjCYESinOdVc431nFqe2mYKS/08M4oGTlWHIn6EUetmZgaQb92KNg2MQqYZgE2xQtY3Lq7bW6CLGNnDKEntZtomHpJrqmUzBdjlcW0YVGJx6yK596l8fnrlhJDN5fsiH0QzaWt9Ib/VqB2mzlfQ9m28EOdvDusfvYAmdfvoR92/WmMl1h49pmei+dSEI/ojRZZnrXFGdfvsCgO8Trp4s0xYkihqnj5h2GfZ/afIlyrUAcxgRehOUY5Mt5KlMlLNfija+dIQrjB6qKFEJg2gYf/cknyBUclo7MZwrNyYUapYkCbsnFciyuvXUDuC3SRpC1U5i2SWery75H9qBrgl5rwPSuh6t2+0Gxc7XdwQ8s7lbbWC6Xs5aKJElIkoRyuUylUmFlZWVbRoKmaYRhiOu62fNN0ySXyxFFUaZ0OHHiBM8++2xmYXAch/Pnz5MkSUZeVKtVZmZmCMOQwWCA7/uUy2VM0+TEiROcO3cuI0aKxSLNZpM4jnFdd5vNY/w5xoqM8fuPVRU7+PBiebAJpKoBSOvr9hSmudhd5fpgk/ncBKBohX32FmaIkhhXtxgmAVtBj0RJ8rrLlt9DKoVr2uh4d2xHd627hrVpCPK6janrHC7M042HaGgMk4B+5DOIfRIlOVpayFbNJYrC+zw4Bl7Ad/7kNVr1DpqWBj5pusbjP3aS+X0pGffiiy/ypS99ic997nO89NJLlEollpeXqZ9tcualc/RbAwxTZ27/DAef3M/c3mnKk6V3vYLxMOJ8Z4Wi4WSrvnnDZs6tsDzY5Mpggwm7iC8jupHH45U9nNNWmafKZtCjHQ5JlKRoOlwbNLCEjmvY9BN/W/TfvY4VQRpWaZOuQs+5VXwZIpXCS0J60RBbNzA0jb35cZhl6vJ/v1Uw3a0e3/njVxn2fDRDQ8YSt+Dw9E88vq3D/O2QUtJcazHoeoR+SK/ZRymoTBWZ3TNNvvz+eFkfBsQy4Vx3lUm7iDb6HZh0ilT9Aht+h5uDLQ6V5ulFHoGMeGriALFK2CUmWPc79EfVqY5msur3KegOCYpecuuadT9ySgAF3UEgmHXL5E2bRCoilYyOF59IJRQNl1mnAkCQRDi6ifU+qxrWrtZ59aunSOIETRNIqajOlHnqM48/cCJ74AWsX2vQbw8oVPLM7pnKyNAd7GAH7x3zB+Y4/93LBKNKS4DyZBE7ZzMxV6N+fQMpVfqYa3HoI/u58uZ1mqstKjNllJRomsHBJ/exenkdGSf02wMM00ChCIYhxYkih5/az2MvnOC/+u1/yD/9zP/I6qV1kkTelXTQDQ2lYGqxxou/9CmUkrzw955j49omZ146R67oYpgGu44ucvXN6+QqeVzXprfZQzN0TMciiSVKSibnawzaA/Ill9pMmVa9g258sIRnt9lj+dwK61c3kEl63ttzYonaXPU9k607ZMMOfmBxt9rG8SBfKpVotVokSZKFSS4tLXHt2jV838eyLKSULC0tUS6XWV9fp9PpMBwOM8XCxMQEU1NTPPLII9n7W5aFEALHcahUKncMJ5Zl4bouUkp2795Nv9/HsqxtxIhhGCwuLnLz5k2U+v/Ze7Mguc70PPM5+8mT+14rqgpbYSNIgADJ5tZUUy212FosaeR2W9KML2YmxmHNjG/mwrInfDEXMxETjomYGN9MeByOcCgUlh1WtNTd6k3dre5GNzcQBIitUEDta1bu28mzz8UpJFCoAgiyAXBxPhEMkkDlyZOnMvP83/t/3/sGxGIxut0unuehaRqe55FKpfrnMTIy0o/HfJzcNr4slUr9a1ooFAYmkZ8SqlabiLzz9zAcSaFLClfrK2z26uS1OGezB5iI5tnqNVkxqwzpSUzPogysdMuYvoOAgGU3cQK/b/QoIODvkR8tIpBUDKKShunZeIFPx7MwZJ39sQLrZo01s860qDCdGO4Xi3W7Q1IxyGuPLoIS4NLfXaNVbZMfu+PlYFsO579/icTX4n1Doz/5kz/hypUrfP3rX+e//tJ/xx//L1/jV6O/i9P1+luuiiajR3XO/NrTfPV/+DJPvXz0c7ODWbU7pNU7M62CILA/ViQuR7jWXKFstchqcV7JTzBspPHx+aC+zJiRoeP2CPBZ7pZxAhc/8Gl71gPSxe8gACnFQBcVbN/F9h0s3yGjRMnrCeY7W5SsFkeTo4xHc2hS6JNTtppMRPOPVGzwXI+3v/0eCAL58Tvvl27T5O1vX+BXvv7Srg4Hz/VYur7KzffmMTsmtuWyeHmJXsdGkkXimRi5sQzPf/VZJo+NP7Jz/STp+U7YIXBX4S4JIseSo8RkjfVenYrVZiSSYjo5QlqNsdypULZajBppZhrrOL7Leq8WdsJ4PWzf3fU8e4lTAgI5LQ6+j0uA6dpoksyYkUUTVWZb65R6DV4tHmUokup3NFTtDmey+xEfIu7yYek0Opz/7kXiuTiqdmcsrbbZ4OKPr/D8G6c/9BiV9Rpvf/s8ruOhaAqO5XD15zLPvXGa7PDuJJ0BAwZ8dCJRnbNfOcVb334Ps9Ujno0hyRIHTk1w4YeXiSYN4tk4VqeHte2FkB/LYsR1xqdHESSRWDLaj8icOT9HvVTHNm08z2NoosChZw8wPj3CyS8eQ1EV/vhf/gG1jQY//POfUV6t0qq28T0PUZJI5uIUJwvsOzpKIhPj8JkDlNeqRKI6wweKXH3zBnbPRtVVCvtyEAQsXV8lNZRic7lMs9IkmU3g9Gxyo1l6pkU8HePgqSkkWSIIAlKF5GO7nrcuLXDlZ9eRVYVYykAQBSrrNdZubTB6aJhnfuXEL+UXMRAbBnxmuV9s49DQEAsLC0QiEbLZbN+08bYAkEgkKBZ3ZqrHYjFarRb1ep1Op0M+n+fw4cO7Cu3booEkSTiO0+9k8H0fURSJRqP9n7stdMBuYUTTNCYmJmi1WliW1e+4SCaTaJqGJEmkUqm+ONFqtRgbezzGLQCdToeZmRl83ycSiRCLxfA8j5WVFdbW1pienu6/tgGfDFFZp2K3ibKzGEspBgfjQ3xl9Jl+qzNAQU9yJDHC99Yu0nC7OJ6Hh48iyGiiTMszUQQJK/ARCEUFFRlf8PECPzRnkzVGo1lyWpwPaku4vosuqXRdCyfwqDtd9scKKILERDRPy+nRdi2CICCrxXgud+jRFgPNLhvzm2RHMzv+XNUUREFkZXadI2cPUl6tsHRthT949ev8o3/83/Cn3/tTjCDORnuNrHDns+9YLo7V5md/+RbLM2v88z//p4wdHrn3aT+TRGUNe/v3dRtREMhoMZ5JT/HV0VM7fjcH4kOUek1+tHkFANNzCAg7aYQAfN9BRcIOwlGKvcQpQ1LZHy0QVyJ8UF9GABKySse1QIBkEOVIcpSa1SarJ6jb3TCOLAjYF83xdHrikV6DylqVbsskf09smJGIsLVcobJWIzeWYXNhi+Xrq5gdk+p6gyAIyI1miKWjXPnFDdSISmY4QxAEmO0eq7Mb/OQvfk7mf3qDRObRimmfBKooIwihb8Pd7wlZDONqD8aHeakwveMxpzKT/GD9Er8o3yQqaXTcHgRhRKUdeMiCBAE4ePcVqXRR4UCsiCyK3GxtIiIiKxId16ZktdgfK3A4MYQmquiSStlqbUfMwfHUeL8r5lGxenMDQRJ2CA0AqUKCzcUtOo0Oiq6ydnOd1ZubiCKMHR5heH8RWZFxbIc3v/UuuqGTKtzp6Op1LN75zgVe/8NXUFTl3qcdMGDAxyA/luW1v/8iC1eWWby6jO8HCAi88vsvYPcc2rU2tmnj2B6qrvDUK0doVjtsLZVJ5u90tSXzCZL5BFsrFaobdRqlBme/coqnXj1KbjTT34A48PQkFyqXef6rp6lu1DFbJo1ya3vzIuzMW7+1wdDUSbpNk1Q+gSiK6IbGmV97mre+dR49phNLRSlM5MkMp9lc2qLb7IIAoweHUVQFLaqRGUr1/SJa1TbpYvKBnXi/DGu3Nrj8k2tkRzM7BIVENk6QibE6u46iKZx89djHfo6B2DDgM839YhvPnj0LhFGYd+/Sx2Ixbty4saMbAkKvh3Q6TTQaxXEcTpw4sedu/m3RQFEUlpeX+waPkhQqj/V6mF0/OjqKaZp9geB+wkg8Hu93LoyNjfV9I+7mdodDJpPZ9XePAtu2mZmZQVGUXdckHo/3//5+12TAk2EilmO2tY4X+DvM/Wp2l+FIeofQANs72fEihUiSIkku1ZYYiWRpOV3arkkQgB94KEhhwScAQXizzsoxFFkmo8Wo2x3atonne4iIJOQIkiiR12I07C66qKBJCl8qHsfFo7fd3pxSPr6x0v2wuhaCKOx5XM1QaVVbXH/nJjNv30TSRP70f/1n5DvjXPPeI0qCBhWyFHc91rFcFq8s86//53/L//43/+KRnvMnxaH4EG+XbzEUUXZcr6rV5kRqfJcIJIsSB+JFZtsbYadBr8m4kaNqt2g7PbwggCCMOUUICLbLPj8IyKpRFFkmJus07C51uwv4KCgYsooqyWTUKFu9JgKQVKP8xsgzNOwuTuARk3Xij3jcBsDsWAj36VQRJYFOo8PS9VXWbm5gxCPMX1mmvFohlU8QT0e5cm6G89+/CEKY7T52aJj8vhyqrrIyu8Hlc9d58bfOPvLzftKoosykUWChUyKv37kH+YFPx7V4NrPb98SQNfbHimxZLXqeQ0yJMBqVqNktbNfF3RYZNGQQBYLA355LDojJEeKKjiYpNJywq48gICKFPjARSSUmaax3ayTkCAfSw3x19BRVuxPu8KnGDhHtUdGstPsReXcjCAKCKNCotJh55xbtaptoKkrgB1z428ssXl3h8NkD/ODf/4Rf/PW7KIpMZiTFsS9MMzRZQI9qtKotKms1hiYfrUAyYMB/ycRSUU68dISjLxzCczwkWeoXzGbbpNexECWRWDqKJEk0qy3Wb23Q61o7xqIiMZ19R0aJJg1OfekEz79xetc6Y2iqQDIXx2yZrM6uI0kielRHEMOf63V6SBGV9VubOD2H1//o1f5jixN5Xvn9F7hx/halpfK2yA7Z4TR//C//gMUrK3QaXVKFZP/8fc+nXm4iySKnvvTUYxnzDIKA62/Pksgn9uxcEASB7GiWxavLHDw1hRH/ePfpgdgw4DPPg2Ibx8d3t7nuVfR7nodpmoiiyPT09H2LalVVmZqaYn5+Ht/3w0XI9s7c7SSMZDLJ2toaxWJxh0BwP2FkcnKS6elp5ufnabVaH/mcflmq1Sq+7z/wNVuWRbVaHRhUfoKk1Rin0pO8X18MdwBFEct3SckGpzKTez6m61rEZJ2cFmetW0MSRTRRwvZdPDHA8V1EUcQNfOKyjoSAF/gktShPpcbpumFixWJni6is4/guuqSQ0WKoooKAx1KnzBcLx4irj75YvBc9qhP4ocfJvTdey7QQpRQ33r1FbjTD5tIWfllkxnsfCYkqJWx6aEGELi0M4hQZQxbCnUbHdrnww8tsLJT2LAh836deamB1bfSoRqqQfOibfxD44G8ReKuhoCOPglhAeIRdH/eyL5qjYrWZa5dQRBEBAdt3GTOyHIzv/Tluuz3SahRD0ij1GpR6DUQBbN/DJ7zuAeEeTlI2wv8XfLJ6guOpUcq9FkEAG2adqByBwCciq2TUGLIgYQsea2aNr028hCLK5PTHs1Nzm0hM7/vh3Ivv+bTrHdZublDYl6O+1aTb7DI8VaRZbfGDP/sp7UaXrt9B0kXsrkXnfAez02Pi2DjRpMHVczd44avP7jl64zou1Y06nuMRS0eJp2N7nMXeeK7H5lKZymoFWZUZ3l8klX98LbQAx1NjNN0uG2YDTZLxggAv8DiWHKOg7/3cDafLqJGh5zmUe03KdgvPd/H9ANf1wvtY4CEKIgklioePEMBELM9kNM+mVWe5XaEZ2BiShiarxGSdlGogCiKmY9Nwuzyb2Y8iyhTvcx6PikQuxuZCCe7Jlg9CZZa1mxt0m11yd41wGYkIy9dXOfeNt2lW2xgxnWgqRqva4dxfvs2ZX3+ayeP7EEQRy7y/Wa5lWtRLTYIgIJlPEInq9/3Ze7F7NhsLJWqbDaJJg+H9RaIJ48MfOGDA5wTf8yktV1i8vITZ7qFFNSaOjTE0WdghICYycV74rTO88zcXaNfaRJNRHNulWWlimTajB4c5/frOwr7T7FIvNfA9n/1PT7I+t4nneriWgyiLEBB6ASUiDE3laVbatKotMsOpHeeYLqZ4/o1nMdsmds9BkiWiSSPcbDw0wux7cyxcWcH3/DC8J4DR6REOP7v/sX2em5UWnfrO77R7EUUBQRDZXNxi6sTHi5ceiA0DPjc8rOfA3UX/2toatVoN0zQxDINkMkmr1erv8u91TFEUKRaL5PN5FhcXsSwLTdOIxWJ9zwXHccjn87sK+AcJI9FodJcQMTY29tg9E0qlEpHIgwvFSCQySMP4FHAwMcxQJM2aWaXnueS0OAX9/tFvqqjgExbmUUUHQQh3IWWdjmshCKHQAAEi4PguEUVnWEtyJDlGQolQtdv8YnOGI8kRlroV1rp1er6DHXh03dC74Y3RD8+bfhQY8QgjB4fYmC+RuWv+2e7ZBH6ALIvIiowoibz5V+cZCaYYYoIKG8xwkRZ1ZngfHw8RiRtc5FTwMilhu80+CPiL//Mb/I//z3+7Y7HRrnd457vv06q2+4uAVDHJmV97mkjswZ+dIPAI7DfBnQchLCAC9zpIY6C9iCA8nrZqURA5nZliKlZgoxd2XBX1JBktdt/Rloik4vk+qiIhixJFPYkX+EQklZ5rIwgiju+iCiIePh4+GTnKUCTFyfQkELBhNnivOs/J1Dgf1Jdouxam5+C7Nh2vx4HYEM/nDj6W13wv2ZE00aTRN+q7TacRplI0y63+n2/MbyIrMvVSndWbG9y8egsr1abdbqM4MkEQJrH4NzwK4zlcx6PX7bFyY519R0Z3PO/WSoX3vn8JuxcWlwEwenCIp187/qEpGL2uxVvfOk9jq4VmqHiux4135zh0eoqjLxx+bCammqTwSuEo5V6TktVEFSSGImmS6v0XuTFFp2y10KSwuymnxnG9ML0kPMtwJEsVZSzfQURgOJIiryV4Pn+ItttjuVPhemOVE8lxztdu4foBXc/B9T3ajsmvjpxkKvZkHNhHDw5z4905LNPe4XJf32xQmCiwubi1o5W517XYWq5w8e+usD5X4ugLB6mu1xGEcMfVbJlcf/smw/uLdFtdbNPG7PR2CQkLl5e48vPr+H7ongNw6Nn9TJ858KG/70a5yZvfPI9t2qgRFdd2ufbmDU7/6klGDw4/uoszYMCnlHa9w5vfOo/ZMjESBqqh4Vgu7//4Clpklhe++uyOz21uJMOX/uHL3Lwwz8+/8Q7ltSrxdJTcSJZmpcXFH1/l2BcOISkyl396jbVbGyCE41u+57M8s8Yzv3KC2madzcUtJEUiWUigqgpms8fIgSEiMY3KanXPz2AkFtm1blB1leMvHuHQswfo1MMOLiNhPLQp7cfFsRwQP/yeIikSvfbHN6kfiA0DPhd8HM8B0zRZWVnBcRwikQiRSJize/sxt00c7z3mzZs3kSSJ8fFxTp8+TavVotFo4Lpu2HKUzRKJRGi1Wh/pNTxIiHic2LZNLPbgXTdJkjDN3ckFA548MUXnsPJwvgJJJUJGDccdxows1xorTERzRESVmt0JEypEjZRi4AY+VuByKjWJKoW+DooY5tgnNYOYavB6YoTVbpX5TgnP90lGizyXO0BKe3J+Hk+9chTLtNlaqfTj9WRF4uxXTrG1UkGUwtirSz+9SuCHQksqyGET3ih9vB3/vsDPeCX4TWRBxnN9vvNvf8TBZyZ58e89RyqfxHM93vr2e3iut8OUslFq8p3/74ekh5L0ujaZoRQHnpnaZQIXuHOh0CAO7ygcAm+FwJlBUE88tmslbHs0ZLSH21UvRlIoooQb+IxEMix1tpiMFggCaLpdZF8gqhhktDhtx0QRZU5lJwERWRCRRYnhSBpDXqWgp3hjNM9iZ4vVbgUJkYRq8Bsjz/SjLh83kiTx3G+c4u2/ubDj/WIkIjz3xmne+8ElJEXC6lpUN+rUt5p4tkuj3GDdXMZQDCKigRhIqJqM5Vos1G6SeDcZJigko/z5//GfeeGrz/LcG6eJRHU6jQ5vffs9YkmDRC70cwi2zcBKS2UUTcZzfIYPFNl/cmKHCAJw9RczdBrdHYaWvudz4/wcubEshXv8Jx7p9RJEipEUxUjqw3+YsHtmtrVBUjJIqgZNu8tUrIDlu7RcC12UScgKaTVK1WmTVWMcTYyiK2EhH5N1hvUUi50y+xNFhqNp5publKwWEUkhqRp8deT0I/V9eRDRhMHZrzzDe9+/RLPS6r9fcqMZTrx8mB/+Wanfatyud5h5exbP82mWmwSBT2W1htWzkWQJzdDQojqV9RrnvvEObHfSaLrKsS9Mc/KLx5AVmdLSFu//+ArZkQyyEh7b83wu/fgKazfXcayw+2zfsVEmj4/vSLXwfZ93v3cRSZHIZe+8Xxzb5cIPPiBdTH3stucBAz4L2JbDm998F98P+vGSAIoqE4npdJpd3vzmeV79gy+gRVQcy8FzPW5dXOR7/+7HOJa9/RkREGWRVC5BZa3Kj/7DuX4iXW4s2793d1smkiSytVJh/1MTPPPaCZqVFq7jIikS8XQMVVdpVdtsrVQ+suCnagpq8eG+fx8FkiLzMM7PnuOhRj7+pudAbBjwmedhPAeuXr3K0NAQtVqNVqvV7x5IJBKkUqkw5qxapVarMTY2hud5nDt3jsnJyR3RmrIs9/9ZW1tj3759pNNp0ul7CowgoN1uP7Fr8Mugqmo/lvN+3G12OeCzgyAIPJc9yE9L1+h5Njk9wXKnjBN4jBtZak6buBwhrkQIgJrVoetZZPQo0e1UAD/wGTYyeEHYSr8vlmNfLNePpDuW+nhtdR8XVVf5wm+doV5qhFFVqkx2JIOqKfi+z9zFRXqataN9fpOVbfum3QQEbLLMKFNAqPR/8LPrrM5t8od/+nu0qp2w+NsWGizTxnVcSitllq6u8PRrx0kPpahvNfnZX77FmV97eucCw70GYmb3DqWYA3eGQDn+qYncVEWZF3KH+EX5BpooE5cjbPTqyKLIvkiOhtMhqyXQJYW4otN0urQci4OJYr+7xg989hk5Op5FTNE4nBjmcGKYht1FFATGo4+vWN6LeDrGa197kep6nV6nF0ajjaSRJIniRJ65i0tohkpto45lWmiGTsdp44ku8VgM23IRBQHXdhEDiVa7zerKMvsP7Mf1PGobdX7xV++ytVzl9/7pGyzfWEcUBDRDIwjCCDXHsiktlimvVXn+jdMYSYPV2XWWZ9Z4+Xef6++6WabF2uwG6XsEK1ESMRIRFq8uP1ax4aOSVmM8k5rg/doiWTVO17Wo2m2iksY+I0vHsyhoCWRJQpcVeq5Dx7eZitwR1D18JqI56naXjBrlqcwEfhBQsVrktMRDC2WPiuK+PK//0atU1qq4tks0aZAuhslT6aEUnWbYFXPj/C3sbeM5z/WJxA2iqSh+NRw3MlsmjuNRXS0jiQKjh4boNkxa1Tbf/Xc/otMyeeV3n2f2wjyxdBRZkfD9AKtr0etYrN3aYPnGGme/8gwEMPvuHKuz67z4O8/1dzvrpQbdxu4WaEUN7+Ub8yX2n3y0pqsDBnya2JjfpNvq7dgIuJtowqC0tMU737mAbdq0G10WPlhifX6TRDbB8P5wnNHzfDbmS9Q26hx5/hDzHyxTL9V4/qtndh1TUmSiSYPFq8ukiskdXZZ9BPaMx7ybXteiUW4SeD6pYhLdePjRqUdFGBeq9pMy9iIIAnzPpzjx8TvMBmLDgM88H+Y5EAQBy8vLNJtNcrkcjUYDz/OwLItms4miKCiKQiQSwXVdVlZWSCaT+L6PZVkYxs42UlmWwzl316XVau0SGuDDi/N2u83CwgILCwv9MYzJyUkmJyc/tMvgUXN3LOf9uNvscsBni5ii8+Xhk2yYdap2my9kD3GjtU7Pc5AFkRutdfwgQBdlIpJCyWpyOrMfJ/DouTYd1+ZXiscBuFJf3h67CJMHXikcIfWANuvHhSAIpIsp0vfsABTGcyRyMZaurxF4d270XVr9ToZ78fHoslMYzI5m2Jzf4vz3L5Efz2H3bJqVJotXV6mu1/Fcl8p6jUQ2juuEx42nY+iGxqWfXKU4kb/TLh90Qdh9kxYEhSCwAY9P0624GEnxlZFnWO3W6Lg9JEHk7fJNkkqElttjob2FJIgoosSKKVKz22TUA1ieQ8e18AKf3x47Q8lqcrO10d8dzmhRzmQOPLGuhruRJGnPxejEsXEWLi+zeHWJxWsrCAg4tsNWq4zn+fh+gKLI+AQk0lG6rR6iIJAoxknmk7h2uJuVG89x/e0bzF86ztbSFp7vU9uoc/PiAt1mF6tr0ap2SA8lcR2XiKSTKiRp1dpcPnedl37nOQBc2wUhnJG9F1VT6DY/fhvr4+JgYphiJMVat8aR5Aiu7/FudY4hPcmqWaNkNpBFEUmQuNXaxPE8orJGz3NoOSa6pPD7+55ntrnOSreKKAgEBIwZWZ5JT34iQpyqKQxP7TaSnT57kHN/+RbzHyxx9c1ZfMej17XoNk2MpB6uQyIKsVSUVD7ByswaiqEzeWIfieyd+2skFuHcf36Tp14+wuYMOjpOAAAgAElEQVRimXg6xsZ8ibkPFnFtl3q5SeAFpIeS+J6PqqlkRzNUVqssXFnmyNlwDMmxXLjP9ZFVGbPz6Xu/DBjwKJn/YPmBfjiu7bK+UOL627M8/9UzWB0L1/UI/IBWNbzvD08VkCSReCZOt9nl5oUFzLaJH4SdDEY8jLPvdSwcy8H3vP73Um2jvmcRbnUt0sW9PWY6zS7vfOcCl35ylVa1gyCEYwonXz3GF377LKnHlDqxF6IocvjZA7z/o8vkx3N73ntqm3VGDhR3deF9FD49K5wBAz4mD/IcuC0eRCIRHMfBNE2CIMBxHAwjNDirVCrk83kkSUKWZRzHYWNjg2g0SqPRIB6P7xiVsCwLz/OIx+PU6/U9xYYHFeelUolz587h+z7RaBRd13Fdl5mZGWZnZ3nppZcoFJ6cY/W9sZz38rjTMAY8fmRRYiyaZSwaFlzL3Sop1UARw8SJmt3B9l0OJUao2x2KepKe75DVEjyfLfaN/CajeZqOiet7VKwW71XmCQgYj2bZHytiyI93vvBB1DbrLF1bxWz3uPne3I5OBoM4ItKegoOIhMGdxYqsytRLTdr1Nv/xX/0VQxMFqqUa9c0mCJAeStNr9uiZParrNayuzfCBIrmRNKOHhsNiYatJbmT78yLmwG+DsFPMC/wuCAkE4dN3G9YllQPxsNiyfZfrzTXyeoI8SYYiKWp2Bz/wOZwYoWF3SCoGPd9hIppjf3yIhBJh2EgznRih4/awfJetXoOflK6hCBJTsQKTsTyK+Mm8dt/3Ka9UWLy2QrfZ5eqbN+jUu8iaTOD56KqO23ApbUekSYrAuZkfcyT5NIomk86Hv1vP8xAkkep6lfJqlX/zz/4MRVMx213KK1W0qE4qn6C2WSfwA7ZWKnieT7qQYmiqwNBknup6re+MrhkakizhOu4ubwez3WP8Hm+ITwtxJcJ0MrwHV6wW850t0lqMlBplXzTX72qZihWQRRFFkPAJOJYcYyKaJyKrZPNxOq5Fz7MxXZuVboXvr39AVFY5GB9i1Mg8sXGKe3Edl/W5TVZm16lvNbn802s0NuvIqozr+miGGnbOtHuMHhohEtXptnp0WibF8WxfaAh8n26rR7veZuXGOv/3P/l/MVsWVs+islonnokRTRmUVyrIisTGQglRFIklo4wcGiKVT7B8bbUvNkTioQHqXoa5ju2Qyj+5omXAgE8Cs20+sAheuLqCYzro0QgIApuLZRRVQVJkjHiETr1DZb3WH8Ew4hHK61UEBBRNptPo0Ky0WJ/bxLEcBEGgvtUMHzOWpVVt7xIbXCcUI4b37xYsO40O/+n/+iarsxuk8glG9hdBCEXu9394mZl3bvFH/+L3d4yEPG4mjo3Rrre5dWGBSCLSj9w02z1a1TbZkTQnv/jxYy9hIDYM+BzwIM+BVqtFEARomkav16Ner6OqKr7vI0kSoij2Ux9uH0NVVSqVCslkkk6nw+LiIkEQoKoquq4jSRKbm5uYpkkyuVu5fFBx3m63OXfuHJqmoet3WqZUVUVVVXq9HufOnePLX/7yE+twuF8s55NKwxjw5EmpBlW7jSLKaJLC0PaMtuuHN8mXCtN7mk7KooQha/xk8yptt0dCiSAKAjeaGyy0t3ht6PiuCM4nwcLlJS7+3VW0iEplNSzeogmDTqMLQJExbnBxz8cKCBQJU2sEUSBVSDJ3YY7aVgPH8YnGDTbmtrAtl2wxidnsAQH1UgstohAAuqFSWa/TqrYpTOThrhEOx5umufFdJDkgmY8jigJB4EJQA/WLj/vS/NLIgogqyji+iyLKGLLWF5U6rkVajfJqce+FiC4p9DyHt8vXAIGEEsELfC7WFlk1q7ycP3Jfc9PHhe/7XPrJVRYvL2MkDTaXyvhegBJRCDyfaCpKTIxSF8r0OhbdRgfVUHEclxv1Kwwxzl/87b/naeHF/qJS0WQkJXQWnzg2ytL1VSRZRjM0rK6F67g0Ky0SmRie7aHHNNZurtNtdskUU/2RH1mRGZse4dJPrlIYz/Wdyq1uuBu37+inU2y4G11SCbhTACeUCIntWNOy1eZwYpjjyb2F+KisUbNavFm5iS4qRGUN23f5RXmWg/Eip9JTT7zTwbYc3vrWeWobDfSoRmm5TOCHO5GyIpHIJRBFgUhMp1XrsD5XAj/AcTxUXWX15ga33l+kVWvjuz4IYeeEIIuYHZPMUIrFK2skUgau7eK7HlbPoVlpkxvN4Lk+siYxd3GRkYPFHUZ3iUycZC7O0vVVCvtyfePJVq1NJKpT2PfpGbkZMOBxoGgK7nbk5b30uhbV9SrRZJRex6LXCjcbhbt27/WoTr3UIDOUQpSk7U4hgZ5pIasSS9dWcW2PaMromzrqUZ1bFxeYv7SEEdu53nFsl9p6jadfO77DX+U2P/oP51i/ucnQZH5HLLOiKgxNFamsVfnGv/4u/+h/+xqS9GTujYIgcPzFIxQnCsxdWqC0VIEgIJaJcfrLJxmeKnyosfGHMRAbBnzmeZDnQKPR2CEueJ6HoiiIothfDMmyTLfb7Rf3t//OsiwajQZDQ0M7jq2qKsVikc3NTcrlMr1er59C8WHF+cLCAr7v7xAa7kbXdUzTZGFhgRMnHp9x3L3cL5bzSaRhDHjyHIwP8aPNK0RlDWl7tzAIAipWm6OpsQcWgLfam7TcHoW7Ygvzepyq1eZaY5Wz2QOP/fzvptsy+eBn18gMp5EViZWb6xAE5MYyfbFBFhROBS9zgZ8REPTTKAQETvEy8nZ3QRAEqBGF8kYdq2ORGUrhOA6iKCBJAp2miaRYNCstbNPBc13Wbq0TBD7xVAxRAi2qkcjGCYKA2QtzzL57C9+NELjX0A2BU6/lyY7EQH0OUX6yfhcfB1EQOZIY4f3aAgU9ibhd7HmBT9MxOZl/8Gu4WJtHEeV+wakgoUeSbJh1lrtlpmK7d38eJ+XVKguXl/uFWLfZRdUV9IhKbbOBbugomsxk6gA3nRl82cUKfCZi+3lv423yjLPOCkewEQWRgNCXAcDqWBhxA1kJzUZt06bbMmlW2vieR8Nv4fur+J6HkTBoVdvkRtLohoZjO1z+2XWWr6/SbXR55/IFIvEI49MjxDMxnn/jNInM/UfdPi1EZY0xI8t6t0ZOv3O+tu9u+3ncf8fO9T3OV+dJq1HU7a4XWZTQJZW51iYT0TxZ7cleg8Wry9Q3G+THs5jtHr7jo8c0Kusuju2iRTVEVUHVVSJRl1g6BghU1qvMvjuH59zTTRXQj8Bcv1XC8wI0Q6XXs5E1mfVbmzSrbQRB6PtGWJ0R9JjG7Ltz/MZ//6tA+L134YcfUFmvUVmtcvPCPKlCkpEDRTJDKZ798tMo6pMfWRow4EkyeXyMq2/OokX22NyrhWMSZsukOFkI1/yEhf3txkdBFAj8gF7HwtiOl1Q1Gce0+4lAxYmdncaKpnDg6Ulm35tn6doqxcmwGPddD1mVeeb1E0wcHd91Ps1KixvvzpEqJncIDXeTGU6zPrfB6uw6+448udFlQRDIj2XJj2XxfZ8gCB6p2DEQGwZ85nmQ54Druui6Tq/XI5vNUq/X++MLrVYLVVURBAHXdfuP8X2fWCxGvV5H1/U9RQxVVfvjE41GA8MwHqo4X1hY2JWKcS/RaPSJiw3wyaVhDHjy5PUEp9OTXKwvEVokChAEjEdzTMcf7J483yqRVne/h1OqwXKnzKn05BPZra6s15g9P8fM+ZuUFrY4cGo/+bEMru2ytVLBdTwUTQmjnYCUkOOV4DfZZJkubQxiFBnvCw0AkixhdSzsro3neXSaJoIY7lYYiQi26YTO07aHoiv0OhZW1yYIYPSgQLvaIZaOoWhKONf98xvkRjNIcoYgOECvXeHN75l88R+8TsLYw1TqU8qBeJGWYzLXKcG2C4MAPJUaZzhy/9dhujZlq0Ve293OnVQM5ttbT0RsCIKA9blNZt+b5/K5a3iujyRLpIdS9DoWpeUKds9BkESa1RaKpqBFFCZih3AFi832Glv1LQ7yFNc4j4ZOj+6O8RsAz/VZurpMPBcnU0xhtkzaje72HKxEp2HS69oomkKq6NKutjj56jEEQeCDn15jdXaD7Gi27xOytVxFVkW++LUX0ffYJfu0cio9ieU5bPYaiAj4QYAsiryQO0hcuX86QtVu4/p+X2i4jSgIKKLMull7ImKD53osXl1h7tICF/72A9JDKTRDQ9EVaqU6m8tb+F6A5/pUN+pouoKiKUiyhN2zadfaLM+sfahBnGO5rN1YJzOcJpaO0W11adU6yKqCZ7u0qm3srk0kEUGrq/Q6PSRJxHM93vzWeRzTYXiqyPBUEbNtUlosk8on+eIfvPipMZ0dMOBxMnJwmBvv3uqPot2N63j4no8giOTHsniuF3Y6GyqaESZTKFooyPm+f+eBAaSHk9x4d46jzx3e83lFSWR8eoTcaIbh/UWyw2HMcm40c98ugI2FTXrt3i6vqbsRBAFZkbl5Yf6Jig13I95HCPllGIgNAz7zPMhzQJbl/ljDbTGiUqkQiURot9vhzK0g7FDwbNsmm80yNze355gEgOM4KIrCyMgIgiBw8uTJhzpXy7Lu29Vw9zl3Op2HOt6AAR+Xg4lhRo0sW1YTP/BJqVFSe4gI9+Lj93e370ZAeJgEpUfC2twG7/zNBYyEQSwRparWuP72LJf+zqJWatBthaMORjKC2QxboQlAFuR+6sSu8xdC2aVd7xBNGGiShhZRaNW7WO0enuthti0EQUAUwXc8IOyOalfadHMd9h0bxXd9SktbzJ6fIzOc7rd3CoKMrGXotDa48LfX+lGJnwVEQeR0dj8HE8NUrRaiIJLV4v3EkvsRyljCnoWPIAh4gb/Hox49M+/eYuatWeLZOJF4hHa1w4UffYDn+pQWS3TqXSBA1WQCP8Dp2fiuRzwTAzQaGy3a3g1q3ERFx8WlR2eX2ADhBE1zq9WfeZVVicAX8NzwXiOIUFmtkB5KMnF0jPJqjfJaldUb62RH76SWqLpKdjTN6o01brxzk6MvHP7M7FRrksKrhaNU7DYt20SVZHJa/EPNQQMItaw9EAQBz3/87xfP8zj//Yusz5VIFRKohkavY3HuG+8gCAHllQrdphl+BwoBsiTT7VhEAoFYysD3PVYeQmi4TRCEwqnruvTaFpIiEfh+WPwIAoEA67c2OfHyETLDKeYuLVGcyNOudXaYnupRndxYhrXZdRauLLHv6NgTa8MeMOCTIhLVee6NZ3nzm+fpNkwSuTiyIuG5Hr1Oj27L5NTrJ9GjYTpQJKbj9BwK+/KszKz2v29l+XbsrIcfBCSyCfJj2XCcQpN33MMcy6HT7HLgmSl0Q0VRZQ48Pfmh5+o63kOtkURJ6nfLfV4YiA0DPvM8yHNAURQajQb79+/vR2HWajV83yeTyVCtVrEsi1QqnJu1bRvLsigUCkxNTWGaZn+kQBRFfN/vixcjIyNomvaRIi41TcN13QeOJbiui6Z9dnaxBnx2icgq++SPNtc7Fsmy3C3viqRruz0KevKxdzV4nscHP7lGqpBE1cMRqV7XolVp022ZyIrMyIEi8x8sY3ctEvk4VtcORyoCdkRiQthGKWsyoiQQeAGKKhNLGXTaPZpbLayeE0Y/tUxcy0WQRSRRBDFsx0zk4ji2i9kNo6OGJvPMX17Gth0S6p1d2I2FEsvXV3Fsl5Wb67QqbQ4+u5/pMwc+M7uQd8/fPwwRSSUm65ieTUTa+Z3XckyO3Wd2/1HSaXaZffcWubEsoiSSLiRZvbFOp9Gl0+gQT8cBgeWZVXzXJz2cRpIdLDN8z9g9B8GWOCE8RyOocJ0LWJhU2MQMunRpYRCnyBiycKeYblXboQDnB0iSQBCAFlGI5+L0Wj1810eP6cTSUVZm1hDEO6KM7/ssXVultLSF2e7RaXRZubHO068d/8i57Z8UgiCQ0+LkPkInQlIJ25i9wO+Pd93G9ty+t8zjpLJaZX2u1B+zSReS3Hx/gV67R7vWpjhZwJ/fZHNxC0mWiRg6qhp2ULUbHZpbLfx7hAY3cNhk5b7vFYLQZ0FAxA8CJFEgQCCaiGAkDKyOhSCKxDMxBBFWZ9d37J46tsOt9xdpVpp0Gl2Cv3yb4QsLnPnKM6Tye2+YDBjweSE7nOa1r73I0rUVFi4vh8KuJHL0C9OoukYiE65VBEFg/OgYM2/PEk1FGTs8wurNdRzbwbU9mpUWzUqTg09P8vxvn8FIROg2upRXa3eZsAaoEY3Dzx4gM5Si0+jiuQ8ngiZzif4a5EH3fNd2SQ8//HedYztsLGyxMb+J7/okC0lGDw49MKXjSTMQGwZ8Lrif58ChQ4dYX1/vtwXJsszIyAhra2v4vk8ikcA0TWRZpl6vI8syp06dYnR0lOvXr4d52aZJvV7Htm0kSSKbzRKPx5Fl+UOFg3uZnJxkZmbmgY/pdDpMT08/9DFt2+6/7tvdHYVCYeC1MOCxcCgxxHK3TMPu9gvPjmtheg4v5B5/8distLF7Tt/hPZaKYnUtPNdDViR6HYvsSJpYNoqpiHhuQCITJ1VI4NphZOXtxYEoiYiigO/5eB74foBmaNRKDQRJpGda+K6PKN/ZaZAQQIXAh2gmnM/Hh1a5RTwdIzOUxvd9BMLjiaJAvdRg8fIy8Wwcu+cQiemkh1Jcf2uWaCLC+PSn3/jv4yAIAidT+/jp1nUCJcCQNfwgoG530ESFiejHz+1+WGobdSD8XUO44GtWm2iahu8F+L5PMhenUY7T61h4lkskESGaMvAcj2btjpicFLI8F7zONc6zxE0EhL7/xw0ucip4mZQQFqn+7QWoCIIoIQoCsVQMSZIRZYnKWoUzv/YMRlxHEHdmsq/PbbK5sEUiF0cQRfLjWWKpKOe/d4lo0vjcFpC6pHA8Ocal+iIZNYYmKXiBT8Vqk9cT/VScx8na3CZ69I7Yn8wnaFVaxLPx/vdCKp+k2zKxew6u46FFFURZxmybdJrmjuPVg/Iur5h73ysAvhMAHqIo4AGKKmEkDSRJxvdNamtVTn/pBAEgawqee8cLYu7SIu16m0Q2LGbyY1kESeTNb57nS19/GVUfrAMGfL6JJgyOPn+Y6bMH8T1/+94uEk1EuHJuhvy22JzKJzh4ej/zlxZxHI94OkZxKo/vBwgBvPT3znDq9ZN4jse1n8+QP76PscMjoYjnByiaQjQV7UdEWl2LRO7hivqhqQL58Qytaiv8rO6B1bVQIzLTZx7O+6q8VuWd71zAtV30qI4oipRXa9x45xb7n97H0RcOfyo6nAZiw4DPDffzHMhkMju6HjRNY2RkhHK5TLvdZnR0lFgstqtAv+0FkU6n94y3hAdHXO7F5OQks7Oz9Hq9Pccper0eoigyOTn5UMfrdDrMzMzg+z6RSIRYLIbneaysrLC2tsb09PSHekQMGPBRiCsRXise53J9iY1eWMjltDjP5Q7u6nZ4XNw9sOG5HslcAt3QWJsrYXV6VDfqRKMRMkMZautVLNPCsR2C7Z/33e3H+wGBJPQXGoih8VpoHCviOz6CJKKqMlJMx+pYhPYWAUbCIBLV8VwP13XJjmbYd2wUs93jyKGD6IbGxvwW6WKS9blN9JiOIAr0uj0mj4/1Fz43zs8xdnjkM9Pd8FEZMtK8UjjK5cYypV4TgPFolmPJMSLyEyqC7rq0ru1SnChgbncXtOttgkAgXUgSCNAst+g2TTzHC1tqnZ27Vh4um6wQ4PffhbcjVS/wM14JfrPvAyLJAqIcihyJbBxFl/G9cPwmO5plfHqE8mqFselRyqs1uk0TzVDZmC8Ry8TwPZ/AD0gX0yiagqorLFxZ5pnXPp9iA8B0YgRNUrjaWKHhmEiCyMH4EEeTo7u6HR4Hu3Ydg4DiZAGzbRJ4Ps1yE7NlMjRVpNvsYLYtWo0ugRtg9Xo7RCM3cLjAz/C4yxPqPu8VAEEWQAzHOhPZROjP4DlIiszwgSFSxRSNUp39J8ZZ2e6SciyHxlaTRDaB3XNQNJlYOoYkiZQbXTYWSp/Y7PeAAU8aURR3eA4ceHoSp+dw8/0FZEXGiOtEkwb7jo5SLzXJjmYoTuRI5hLIioTdc7h1cYHscGa782GTdDG5p2Dnez6+5z90t5kkSXzx77/If/xXf42qqej3JllYDpWNGi+8cfqhBOX6VoNf/NU7xNIx9PwdgdRIRPD9gFvvL/STJj5pBmLDgM899+t6OH78eF9cuN0dcP369X53QDqd7o9W7NUh8KCIy/sRi8V46aWXOHfuHKZpEo1G+x0SnU4HURR56aWXHir20rZtZmZmUBRlx/ndHhe5/fcnTpwYdDgMeKQkVYOXCkewfTc0XPqQWexHSSITQ942flQ0JfRQkCQKEwUs08X3PDzXo7xexZm3cezQKFKSRHqd3h2hgbDzAD8AAWRNhgD8wMeIR7Yj58L/7nUtRM8PZ8b9gEAAsx2atUWTBvFMjPEjI5itHrGkwdBUkfx4jma5xdZymcpaDT2mY3Z6DE0WSObDXQ3N0CivVre7Mj6/t+OhSIqinsT23b7Z35MiVUgSBHe6TARRQFFl0geHMFsmjXITq+dQWiqHXg3bu1eSJNBr93YdLxQa9p68DQjYZLnvC+L7AdgegR/QbnQI8NENncxwhtFDQ1TWawxNFcgUUzz75ZP84q/PU9uq022aBH7YdTF5Yl9/pz0SD2PaPs8IgsBUrMBENIfte8iC+ETjUYeniixdW9326wBBFInENNLFJO16JzSQtV0q11awujaSJIajVZJAr71zzvqjvFcAAjfAxcW1XDrNDtG4gazKDO/PUBjPUV6pcPSFwySyCU69/hTv/eAS7XoX27RpVVoIksj02QNI2108akSlWXn4Mc8BAz5viKLIsS9MMzY9wvL1VSrrdQQBjr5wmNFDw0QTBovXlrlybqZ/Hw6CgOvOTRRNxupadBpdokljx3F9z6e8UuHwmQNEE8Z9nn0302cO8jv/5Cv8zb/5W6qbNYy4gSCGSUZBAGd//Rle+a++8FCbDzfOz6FFtF3GmOHrFsiN5Zi7tMjUUxMY8Ycff3wcfH5XNwMG3MWDkhbu1x2wubnZFwHu9YL4sIjLB1EoFPjyl7/MwsICCwsLdDodNE1jenqaycnJhxIaAKrVKr7v3/f5VVXFsiyq1eogYWLAY+Fe1/gngSRLHH9xmvPfv0Q8E8OIR0hkYyxdWw27Cp47xIUffoDTc3G3W9kVRSIQwLU9ELbNILc7GQgAn+187QDfCbBNG83QcWyXXtfCc32CIDyObbkEXoDnunSaJr7vc/jMAWJJg+GpIsdfmkbVFNAUXv6959lc3KKyUUMUJYb3F4ilov2FhGM5qLqyZ0b45w1BEJ6oKHWbWCrK/pP7uPX+Isl8AiMRQRAElq6uICkSh88c5K1vv4fnutuGwSJqRKHXMvGc3bO4XVr93el78fHocqe4E2WJwPPxCcKZ/mqAJErsOzpGMptg6ql9TJ8NPTtS+SS/8g9eYunaCqXFMtmRDLnRzI5FomXapIuf366GuxEFEV16/J0M93I7/q28WiVVSJDYHn0qLZXJFNOIMmx89xKB6/fbtaOGTr3c5F5d4aO8VwBERcB3w84Kx7RpOi6FiTzpQhIjZfDUq0eZOhFGzY4eHCaZS3D97Vlq6zWG9hfJjqR37MA6lvuJFxkDBnwaSGTie+7wL1xd5uIPL5MZSe8S/DuNLmZgbkcYd1E1FVESsXsOQeBz+OwBps8e/Mjn8tTLR9l/ch9Xfj7DrfcX8Dyf4ck8J145Fo57PEQahNk22VwokR25/2anuO0DtD63wYGn9zbGflIMxIYB/0XzMN0BpmlSLBap1Wr9rogPi7j8MGKxGCdOnPil4i1LpRKRyIMXEpFIhFKpNBAbBnyuGJ8eRdVVZt65SXm1QrqYYmN+C81QEQQRAkhko9S2mmgRlYBw5wDCnQ5BCPC8cKebQMD3fXzHR9Vl1IiGJIq4toPv+mE0lrS9S42Aosl4rk+mmEaNaqiKRGE8xz/8579PZmjnuJWsyIweHOZX//BVzn//EtHkHaEhCAJqmw1OvDz9uR2h+LRw7AvTxNIxbr43R6vSYuTAMOWVCpnhNK7tomgKRtyg5bTRoyqe4+Na263voQbVxyCOiLRnESki7UioEAUBFBkpgPxYBllRUDSJIy8c4rf/8a9jxHZ+f+tGaDzW61gsXlvZUSh6no/ZNDn9+lOP9NoM2IkkS5z9yjPcurjI/AeLuLbLyMEh6qUm6aEkWyv/f3t31hzHeS52/N/77DsGywz2lSRIgDspkbZ1ZNk6jmRHTpzEcXKVVOUiXyCV75BPkqRyHKcqzqlyysvRkSLRFi1uAEWCJHZiMBtm7+klFw1CggCQlESQAPH+7oRl0Gy909P9vM+SJxAJ0KjUsWwHw6/TNts49s7A1DdZKwCapuHILrIqkcom0Q0NRVO4+ovLXP3g4o6HoVAsyNl3pqiWapiN9rZAg9k0AZfuofSLOTGC8JoxW21ufTi7a6ABIBgNYJleieTgZC+rj3JYpkUkEaZ7KI0/9O0DecFIkAvvnuHCu2e+1e8366Y33egZ9w66T6dSfPXT7USwQTjSnjc7QNO05x5v+bKYpvnMLAhFUWg0Gk/9GUE4jDr7O+js78C2bGRFxvBrlNarrN5fBSAz2g1ImI0WjWoLWZaQFe+DWVIUJMfGsV2e7CEYQZ1A2I9uaEiKTLVUw7IskFyQJCTJRdMVZFVFkiEYC6AZKqnuBJFUhNBTOj9nRrsprpW595c5qqU6rYaJqilMXBhl4ETfPp8pQZZlBo730n8si2M7WG0L13Vot9rcv/4QXVfoHsgy9/k8jmtj1k1kVUFyvF3mrz5IdpLlLn/d9e9ISHTS6/1NRcIIGEiyV+bjrQ+Xzv5OQtHAjkDDV01cHKVaqrF4d5n6RoNWq40voHP+3dOkMsk9f094MTRdY+L8COPnhnFshxqrSUMAABlnSURBVPL6BrIsYzZNHt6cxx/x09GbYH5mGadt0W7bKKqMvdlj40lw6nnXCnhBDt2vgwt6QCMYCWL4NSLJMPGOyJ5lVpIkce5H03z8v64xf2eRRqVB27SIJENc/eeXv9MDkSC8zh4/XHtmCWM4GWb1gTd6dvIAXXsVRX6u8bq27aDqr/5R/+XnqAnCAfJNsgMOGl3Xse3dUzSfsG1b9GsQXmuKqnhp6J0xOjIJTrw5QfdgGs3QSWUTIEkYfo1QPIQkgaLKKIqMbqgYfgNJlVBUmVg6guu4mK02TttG11V8QT+q6o3FVDQVRVPwBTWS3XFCsSCxjijRdBRfQN+1vv8JWZbJjnaDC23TQjc0AhE/xcdFiq95Df5BIkkSiqqg6iqhWJDeiQyTV44RS0fxh/zEu2NIkoQvYBCI+JAkkDV5W4NJVdI4zRUUVGS88hcZBQWV01zZavinaRqqphCM+El2xQlGAnRkU0Q7wpgN86nXbt3Q6BnpxLJsrLaFz68TCPpYvrdKbaO+r+dI+NKT9aL7dILRAKNnhpi4OEo4FiSSihAI+0CRCUWDXoq15I3RfeJ51wqAaiioqkIkFSaWihKMBkhmkiS645Sf0XchGA3Q0Zuk1TCxHRd/yI+iazy6tUjbbO/PyRGEQ668XkH3Pb20T5a9ustG5WBt2oXiQXxB32YG097arTZd/fs/9elZXn24QxBeocOcHfBkWkY4vPcc8286LUMQDquhk/189JtrJLpihOIhHt1ZRNNUZFmh7djosowkK7iS62VChAzsttdQUvWrtOomvpAP27SxLBvV0HAch+7xHhKdURbvLtM2bcLxMGbTxHVdfEEfoZi3S60Ze3+cWm2LT//3dWKdMbqHvyxpatZbfPrbz/jhv/kemv7y+xkcVYqiMHiqn7vX7hNJhTECOo8fPUbTVVzHxXVB1RUvKwEv+NCst7Z2rGNSiqvuezxmgTpVAoTopBdVUpEVmcxIF47tYAQNfEHfZt8PG92vE09HCEaDT63L3ShUuPGHO2RHu7ftum3kK3z2uxtc+eDifp8i4StCsSAdmSTl/AYd2RSuO8vjhzn8kQDlfBVLsVANlWazhSJ5jRnNhvcQ8LS1ApsNMU/1UdtoEE2GUTQFs2kiyaDqKslM3AtqPMXK3GMe3FhgeHpwayQfwPpSgXt/ecCxS2P7d3IE4ZBSFNnr3fQsLgeu1FGWZUbPDHL997dI96V2Pb5qqUYoHiTRvfs0vZdJZDYIR9phzg5IJBJeaqe5e2Tz20zLEITDKt2XYuTMAH/9wy0atSYgUcptoPlUFE3GrLcIRPwYPgMkaDfa2G2HnpEuYqkogbA3yrL3WA8jpwdJZRIkuhN0DaSZfnuKwakhHMehuFaiWTcJRYObpRxpup5Rv5lfLmI2TfxfG3XlCxi0Wxbri4V9PjvC141MD5DoivHZ727gApblUMqV8Uf83n+bFsF4AM3QkFXZmwghfXnTqUoqGWmQUekkGWkQVVKRJIljl8f4J//hHfqOZ2lUGxRXi7iOQ7QjQnash3A8xPD0wFNvXpfvraJo6o703kgyTHG1xEahso9nRtjN1FsnsC2bmx/eQdVVWs0W1UKVUCyAbTkgQTASQNU1FE3eFnzcba0gARJ87xcX+cG/eIN0b5JKoULpcQlFkYmlo/QdyxAI+Z9ZavXgxjzheGhboAEg3hnlwc15bOvp9ziCcBQlMwnaradn/libJVKh+MEbId93PEv/sQy5+XUvGL7JtmyKqyUc2+H8j6efq+HkfhOZDcKRdpizA3RdZ3x8nNnZ2Rc6LUMQDiNJkogkwnT0JukZ7qJVb2E228zPLDI/s0RxtUQg4iccD6MaKusLeaIdEfomMjy4tUCz2kTVZUq5DaKJMMFYgHRvkuGpfurlGq1aE0mScB2b7HgXxy+NEwj7CCdDnLx67KnH9rRUR1mRaTVae35f2B+qpm7NW+8/kaXdbFMt15mfWWLh9gK1jQahWJBwPIxjOxRWigye7MNq28xdf7Q5uWKzBwiQ7k8xeLKPyz89z/L9x5ibN7GyqjBwopfxc8Oohkb3YJqBE71POTKobzT2zJSRZIn2k+aVwkvjCxoYfp2xs8NeeUurTWmtzPzMMvMzS9jtNuFkmFAiRL3apFqs0jPUxdp8jscPc94OqrQZY5BlugbTjJ4d5NL757n7yRe4rovjuAQifkbPDjE42Ycky4xuBj6fprZR3xHIBK/EzN7sUSIIwnbJnjiBkI9Gtbnr+wegtFZmZHrgW2ceeo2gSzy8tUBhuYgkS6T7O+ibyBBNRb7L4SPLMlNvTZLKJvniL3OsL+W9ppGyzMCJ7IEYefmECDYIR1oikWB5eRnTNHd9KH8R2QGmaVIoFFhbW9v6O+l0+jtNs3giGAwyOTm59fovalqGIBxGc58/orM/vTV3evbaPSKJMNFkBKtlE++MUa82MEt1UtkEtmWzMLOEpinIkQDlfBlFUUj2xOkZ7qJ7sBNZkbj90V0Mn8aFn5zBbLRYvv+Ye5894Jf/+ecMHM8+tcEUgD/s//pUvC2O7RD4BnO6hRejbbZZvrdCZqQbWZGxLYub/zBDsjtOcbmI6tMIx0LUKw1c16VrME1rc/doaLqferlOtVzD8BmMnRuid/Pm0TRtlr5YIdkdZ2iyj41ChdUHORbvrfDL//QBqcyzR5vF0lGW7q8Sim3fTXMcF9d197wxFvZPeb1Co9KkZ7MMqlFtkl8u0ZFNklvK4/NFUHSVermBpMh0D6RpVJsEIkHGzkW+khEVYOLCKP3HsvjCfvILeXKLeXonMkycHyG/UmJhZpl0X4qf/PsfEut49qjTeGeU4mqZcGJ7SajZamP4dW+ijiAI2yiKwtkfTfHhrz/FalvbxlLblk1xrUwsHWH49LcbG2nbNjf+dIdHtxYxArr3Oe+6LMwsM/f5IyYujDB2dvg7lWjIskzveIbsWA+NahPXcdD9+oEryxTBBuFI2+/sgFqtxuzsLI7j4Pf7CYVC2LbN4uIiy8vLjI+PEwx+t/QsXdfp6uoS4y2FI69Za209oNUrDcq5DVRd3ew4rRDrjJDojpFbXMcybVoNrxxC1bzGbN2DadaX8oxMDTB6dpjcQt6bVuDTiXfGAPAFfESSUZbur7Ayt8rI1MAzjyvRFSPWEaG8vrFtN2MjXyGcCJHsefU1lUeNZVq4rpdZAlDKbdBqmFhtGxcXTddJ9iRIAsv3VjCbJu1Wm1AihKIodA92YrUtSo9LnPr+JF0DHSzdX+XGH27RkU3iC3oBgWRPkkRXnKV7q1QKNdK9z27W1T3cyeyn97btuLmuS3G1SHas58DsVh0ldtuCr5QprC2sI8sS9Y0GiiRhhHwkOmPYtsPC7CKtponVtghGAuh+nc6BNM1ak3qlwYX3zmAYOg9vLTD3+SMyoz0oqtdAsnuok1Q2waNbi899bMNTA/zp/v/DFzS2AguO7VBcLTH9gxMHIo1aEA6ieGeMqz+/yJ2Pv9h6T7t4D/FDJ/sYPTuM/i2DdXev3efR7UVS2eS2Eqd4ZxTbdrjz8Rf4ggb9x56e6fY8JEk60J8LItggHHn7lR1gmiazs7NomrbtNVRVJRwOb31/cnJSZCAIwguQ6klQWC0RToRoNUxA2hwPJSGrytZNt6ZplB6XCUYDuDgksx1srFfwBQ18AR+Vcp3S2gayKlMt18mMdO/4W/FUhJt/muHqB5cAaDVaLMwus3h3GSSJvvEM2fEedENDlmXOvzvNtb//K7nFdSRJxnVdYukoZ985haIoL/EsCQBGwPAa+bXa6IbmPTSqKm7dBElC0758QJMUhXq5hhH0IcsSsc4I1VIdX9BA1VQa1Rq5RRlVlQF3K9Cw9fuyjBHQufPxLMObwalqqcaj2wuszefRfRoDk710DaZRFAV/0Mel98/x5/9znfXFPEjeOs6MdjF5ZeIlniXhiSe7ko7jIssS1WIN3a/jOC6SIqNuBgsURQYXzLqJoqnofp1AyE+j2kDVNVRNpV6qU7GqaLqCZqhbgYYnNN1rTvvw1iLTP/AyGwqrRR7enKeU2yAUCzJ0qn9rDGqiK87Zd05x4493aJsWkuSN1hy/MELf8YNXAioIB0k0FeHSe2eplWs0qk0kWSacCH3rIAN4pZP3rz8k2ZPY0UsFvOtEvCvG7Kf3yY71vPb3ACLYIAjsT3ZAoVDAcZw9Awm6rtNqtSgUCiIrQRBegOHpAZb++8fofn3z5t9F1TVcxyWcCNM22zi2Q22jTrPWwrFdOgc66OzrIBgNsjK3iiRBtVCle7iTzoEUn//hNrslOUqKjOM4ADRqTf7x159SrzQIx4K4rsutD2eYn1nkjZ+eR/fp+EN+rnxwkfL6Bs1aCyNgEOuIHLgu10eFLMuMnxvm+v+9SaInge7zmgXrPm/tGAEDy7JpN02a1Qa1SgOr7ZDuS9Ez3E3pcZnl+ytoPp1yrsaZt6dwbIfb/zi759+zbW+9FB+X+Oh/XgNJIhj106y3uPbb62QnMpz+m0lkWSaejvLWv75CaW0Dy7Q2+408fXKSsH8CYT99Exke3Vki2ZPA8OtUilV0Q8MX0JEU2cuIrDRp1c3NhrB+hk71kehOsL6cZ/VhjkDIT7VU5/L753hw8xEPbszv+vckJJzN5tXzM4t89rubXjA05KOU2+DDv/uUE2+OMzLtpXhnR3vo7O+g+LgMrks4GcYfFOU2gvC8gtEgweiLaQSZW8zjOK4XfNyDbmhs5DYorW2QPAATI/aTCDYIwj5ZW1vD7396WpPf72dtbU0EGwThBYh3xrj4kzP89fe3aNZbmC0Lq20zcXGE8nqFlfurVAoVbMdBNVQs28JsmeQW1vGHfN7ucl8HiZ4Ep9+axHEc4p1RKsUq4cT2JrLl3Abn3p0G4Is/z9GqtUj1fNnbxRcwWF/KM3djnonzI4CX6hjriMKrH3stAH3Hslhti5lP7ntBqFKNYCzE2LlhyrkNFr9Y8earSxKyLOPgUC1WKawUUTWFE29MEEmFOX55jIkLo1RLVWRFoW22t9XMuq5Lq95i5PQQruty/fe3MAIGgYj3+aD7wB/ysTi7TO9YN+k+b4EoivLa34QeJifenECSZR7dXkDTFQrLRW80ZdRPca3E8r1VzHoLzVAxm22QvEk0qqHhD/i48ONpdJ/OlZ9foGugE4AP/8cn4LrwlaCjbdkgQe94D2bT5MYfbxPviqHp3i27bmgEIgHufHSX7qFOgps9XzRdI92bevknRhCEbZq11lMDDVsk6ZkTMV4HItggCPvENE1CoafvRCmKQqPReElHJAivv66BNB3/NsnGeoWp75/g9keztE0LVVdZmFnEF/IT64wQS0VB8mbZm3WT0bPDhOJBiitFJs4PA95u9Nu/usp/+y+/wXFcIskvJxP4wz7O/Wgax3FYmFkimt7ZyC3aEWX+9sJWsEE4WCRJYnhqkN6JLNVileNvjPHFtTlsy8EybVzHJRQP0ZFNYAQMDJ++tZZOvDGOZqhUCzX6JjIAhGIhLr1/jj/+14+8TueRAO2myfpygcxoF6NnBqmWalSL1a0U+K8eiz/sY2F2eSvYIBwsqqZy6nvHGT07RK1cZ/TcIguzS7gOVIpVZEUm0hGhcyCNBARjQarFKpFEiKFTAzi2A65LR9YLCPQdyzByZogv/jJHRzaF4ddp1Brkl4qcfvskqUyS1YdrOA5bgYYnFEVGkiRyi3mCx0WDWUE4SHSftpXJ9iyq9nqXUIAINgjCvtF1Ly1XVfd+m9m2Lfo1CMILpigK8c4Y8c4YPcOdrD5c4+Y/zKKoKr3j3fjDfiTg4a0F1hfzOLZDKVfGtiyOvTG27WFv8GQ/P/2P7/LRbz5lZW4VWVEYmR7krX/1JvF0FNuycRxnz7rMtilm3B90uqGR6IqT6IrTN5FlZe4xjVqTrsEO0r0pjKAPq21x7y9zVApVauUaG/kKvqCPsz+e2pZ6e+m9s2iGwrW//5zl+6voPo3Tb5/ke794A93QaVSasGthjrduLVOMKTzo/EEf/qCPVE+CkekBlucek1tc59T3jhNNhtH93v/nu9fu4w/6KKyUSPfWCIR9XPjJma0eDZIk8bf/7m+IpSPc/NMdCsttAlE/b/3yCpffO4skSTi2g+vuPstGkiXstri+CMJBk8okkCS2erzsxmpbXuPqXTYqXjci2CAI+ySdTrO4uEg4HN7zZxqNBtmsaOAkCPtF9+n0TWTZyFeRZWnbOMGhU/10DaRZmF3i+KVRxs6NbHV0NpsmM5/cY2FmEceF3vEMb/zsPMNTA/iDX5ZHKapCKpOgWqrvGFVYKVbpHkq/nH+o8EIEwn6GpwZYmF0C12skCV5AYuLiGNVilZW5x0y9dYK+8Qy6zwsWV0s1bn80y9qjdVxcjl8aY+BUH/0TGXTjy4ByKBZE1RXaprVjt7peqTM83f/y/rHCdxZNRQjFgtz78xzJTGKrB0sg4ufk949TXiuTXy5y6b0zJHsSW4GG/EqRWx/OUM5tgCRx7t1pRk4P0T2Q3tYwMpqKgOuV4ny9v4tte2VegiAcLP6Qn97xDIt3l0l+pbzyCdd1KayWOH557Jmjs18HYh6OIOyTRCKBLMuYprnr903TRJZlEomdFyJBEF6sjmwSs7nzvegL+Uj2JBi/MLoVaLBtm09/e535mSVi6RipngShWJD7nz1i7q+PdrzG+PkRmtUm9Y0vS6KqpRpW295q4CYcLl2DndQ26tu+JssSRsAgO9bN0Mn+rUBDo9bkw19/QmG1RKInTiqTRNNVbv1phtxCfttrKKrCsYtjFFaKW+vRcVxKa2X8YT89w6J/z2GjqAqJnvi29z94mU2KpjB5dYJ0X8dWEKH4uMQ//t0ntE2LVDZJKpPAatlc/90NqqXattcIxYL0Hc+QW8hjbWYx2JbN+mKezv6OrZG8giAcLCfeHCeVSbA2v0694l0bXNelWqqRm1+n71h2azrR604EGwRhn+i6zvj4OO12m0qlgmVZuK6LZVlUKhXa7Tbj4+OijEIQXoJUNkG8K0ZhtYjjeGnJVtsiv5Rn6FTfts7t+eUi+eUCye448maTJ1VTSWWTzH3+iEZ1+0NFoivO5Z+dRzNU1pcKrC/l8Yd8vPlPLxBJ7p3ZJBxc/ccyKKrCRr6ylcbeapiU1socuzS2NUYVYPHuMu1Gm2jqy+kiRsAg3hnlzkd3t6aWbL328Sxn3zmF2WizvpSnsFIg3ZvcmlwiHD4TF0apb9RpVJtbX6tt1LFa1o6A4+yn9zGCxlZwEyAYDaAZGvc+e7DjtU9ePcbExVGqxSr55QLl9QpDU/2c+eFJMc1GEA4oTdc4/+5pzr87jaarrC/lya8UCcUCXP7pOaa+f3zb58jr7PXP3RCEVygYDDI5OUmhUGBtbY1Go4Gu62SzWRKJhAg0CMJLoigKF/72NHc+/oKF2WUkaXOX+fLYjt2F/FIBbZeHPq/2UmIjX8Uf2j5pJtWT4Oo/u0Sz3gIQY+cOOX/Izxs/O8+tD2dZX8qDJOEPGpx/d5rMSPe2n12ZWyMY3zkyTffpVApVGpXGtr4OkiTRO54hM9pNs9ZC1RQRZDjkkt1xLr1/jlsfznjrBYloKsyZt09uCzjatk1ucX3X1OpQPMTKg7UdX1cUhfFzwwxP9WM22+g+7UikXgvCYaeoCj3DXfQMd2HbNtLmZKOjRlytBGGf6bpOV1eXGG8pCK+Y4TeYfmuS45fHaLfaGAFj15t2RVdwn9JJWt5jpJUkSSLI8BqJJMJcfv8cjVoTx3bwh3y73ihqukK7uXN8meu6uO7e60WW5W2728Lhlu5N0fEv36ReaXjXgpBvR+aBJEnIioJjO9t6MwA4tv3UzvSqpooggyAcUory+k+d2MvRC68IgiAIR5ru0wlGg3veuHf1p2m3LW9U3VeYrTaqpoimbEeMP+gjGAnsuSPVdyxLrVzb8fVqqUaiO7YjC0Z4fUmSRDASIBD271riIMsy/cezXmPIrymvbTAw2fcyDlMQBOGlEcEGQRAEQfiKSDLM2Nlhcot5qqUaZtOknNugvFZm6q0TYndR2KZrIE3XYJq1Ba8RWKthUlwtYbdtTl499qoPTzhghqcH8Id9rC8VaNZbNOst1hfzhBJBhk6KYIMgCK8XccckCIIgCF8zcWGEZE+chzfnqZUbdA2lGTjRS6xDZDUI2ymqwtl3pliee8z8rQXapsXgqT76j/eKMglhB3/Qx5UPLrIwu8zC3WVkSWLyyjEyY93ohvaqD08QBOGFEsEGQRAEQfgaSZJI96ZI96Ze9aEIh4CiKvSO9dA71vOqD0U4BHSfzvDUwJEZfScIwtG1Z7DBtr15vqurqy/tYARBOJyeXCeeXDeEb0dcd4+2b/I+EmtFEOtFeF7f9DNarBdBEJ7Xs64vewYbcrkcAL/61a/24bAEQXgd5XI5+vv7X/VhHFriuivA872PxFoRnhDrRXhez/sZLdaLIAjf1F7XF8l1XXe3X2g2m9y8eZOOjo4jPa5DEIRns22bXC7H5OQkPp8Y/fdtievu0fZN3kdirQhivQjP65t+Rov1IgjC83rW9WXPYIMgCIIgCIIgCIIgCMK3IUZfCoIgCIIgCIIgCILwQolggyAIgiAIgiAIgiAIL5QINgiCIAiCIAiCIAiC8EKJYIMgCIIgCIIgCIIgCC/U/wcgQqCsk2nY+AAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11bc67dd8>"
+       "<matplotlib.figure.Figure at 0x1a13565e10>"
       ]
      },
      "metadata": {},
@@ -2546,10 +2249,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Interactive K-Means\n",
     "\n",
@@ -2559,18 +2259,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 68,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeIAAAFVCAYAAAAzJuxuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "dcae86b9b6e749388ce9a0dd76969b54",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/html": [
+       "<p>Failed to display Jupyter Widget of type <code>interactive</code>.</p>\n",
+       "<p>\n",
+       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
+       "  that the widgets JavaScript is still loading. If this message persists, it\n",
+       "  likely means that the widgets JavaScript library is either not installed or\n",
+       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
+       "  Widgets Documentation</a> for setup instructions.\n",
+       "</p>\n",
+       "<p>\n",
+       "  If you're reading this message in another frontend (for example, a static\n",
+       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
+       "  it may mean that your frontend doesn't currently support widgets.\n",
+       "</p>\n"
+      ],
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11df6f898>"
+       "interactive(children=(Dropdown(description='frame', options=(0, 50), value=0), Dropdown(description='n_clusters', options=(1, 6), value=1), Output()), _dom_classes=('widget-interact',))"
       ]
      },
      "metadata": {},
@@ -2650,20 +2365,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Gaussian Mixture Models"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Covariance Type\n",
     "\n",
@@ -2672,18 +2381,46 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 69,
+   "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:58: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
+      "  warnings.warn(msg, category=DeprecationWarning)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:77: DeprecationWarning: Function distribute_covar_matrix_to_match_covariance_type is deprecated; The function distribute_covar_matrix_to_match_covariance_typeis deprecated in 0.18 and will be removed in 0.20.\n",
+      "  warnings.warn(msg, category=DeprecationWarning)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:77: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
+      "  warnings.warn(msg, category=DeprecationWarning)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:77: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
+      "  warnings.warn(msg, category=DeprecationWarning)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:58: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
+      "  warnings.warn(msg, category=DeprecationWarning)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:77: DeprecationWarning: Function distribute_covar_matrix_to_match_covariance_type is deprecated; The function distribute_covar_matrix_to_match_covariance_typeis deprecated in 0.18 and will be removed in 0.20.\n",
+      "  warnings.warn(msg, category=DeprecationWarning)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:77: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
+      "  warnings.warn(msg, category=DeprecationWarning)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:77: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
+      "  warnings.warn(msg, category=DeprecationWarning)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:77: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
+      "  warnings.warn(msg, category=DeprecationWarning)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:58: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
+      "  warnings.warn(msg, category=DeprecationWarning)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:77: DeprecationWarning: Function distribute_covar_matrix_to_match_covariance_type is deprecated; The function distribute_covar_matrix_to_match_covariance_typeis deprecated in 0.18 and will be removed in 0.20.\n",
+      "  warnings.warn(msg, category=DeprecationWarning)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:77: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
+      "  warnings.warn(msg, category=DeprecationWarning)\n",
+      "/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:77: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
+      "  warnings.warn(msg, category=DeprecationWarning)\n"
+     ]
+    },
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxsAAAD9CAYAAADUK2rLAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nk4yv0gAAAABJRU5ErkJggg==\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x11bec04a8>"
+       "<matplotlib.figure.Figure at 0x1a134a8438>"
       ]
      },
      "metadata": {},
@@ -2735,10 +2472,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "<!--NAVIGATION-->\n",
     "< [Further Machine Learning Resources](05.15-Learning-More.ipynb) | [Contents](Index.ipynb) |"
@@ -2761,7 +2495,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.1"
+   "version": "3.6.4"
   },
   "widgets": {
    "state": {
@@ -2777,5 +2511,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/notebooks/figures/02.05-broadcasting.png b/notebooks/figures/02.05-broadcasting.png
index 26999961b..18122b842 100644
Binary files a/notebooks/figures/02.05-broadcasting.png and b/notebooks/figures/02.05-broadcasting.png differ
diff --git a/notebooks/figures/03.08-split-apply-combine.png b/notebooks/figures/03.08-split-apply-combine.png
index 034abaf56..a041b4cdc 100644
Binary files a/notebooks/figures/03.08-split-apply-combine.png and b/notebooks/figures/03.08-split-apply-combine.png differ
diff --git a/notebooks/figures/05.01-classification-1.png b/notebooks/figures/05.01-classification-1.png
index 202e129ab..360aa1d99 100644
Binary files a/notebooks/figures/05.01-classification-1.png and b/notebooks/figures/05.01-classification-1.png differ
diff --git a/notebooks/figures/05.01-classification-2.png b/notebooks/figures/05.01-classification-2.png
index 21b790f92..052ae90c2 100644
Binary files a/notebooks/figures/05.01-classification-2.png and b/notebooks/figures/05.01-classification-2.png differ
diff --git a/notebooks/figures/05.01-classification-3.png b/notebooks/figures/05.01-classification-3.png
index e05ed4586..49773b284 100644
Binary files a/notebooks/figures/05.01-classification-3.png and b/notebooks/figures/05.01-classification-3.png differ
diff --git a/notebooks/figures/05.01-clustering-1.png b/notebooks/figures/05.01-clustering-1.png
index 394bb01d5..ee05c3f8e 100644
Binary files a/notebooks/figures/05.01-clustering-1.png and b/notebooks/figures/05.01-clustering-1.png differ
diff --git a/notebooks/figures/05.01-clustering-2.png b/notebooks/figures/05.01-clustering-2.png
index 4ac3cc102..e96ecf066 100644
Binary files a/notebooks/figures/05.01-clustering-2.png and b/notebooks/figures/05.01-clustering-2.png differ
diff --git a/notebooks/figures/05.01-dimesionality-1.png b/notebooks/figures/05.01-dimesionality-1.png
index 1bf864035..61a195497 100644
Binary files a/notebooks/figures/05.01-dimesionality-1.png and b/notebooks/figures/05.01-dimesionality-1.png differ
diff --git a/notebooks/figures/05.01-dimesionality-2.png b/notebooks/figures/05.01-dimesionality-2.png
index 7be22a560..a858e8938 100644
Binary files a/notebooks/figures/05.01-dimesionality-2.png and b/notebooks/figures/05.01-dimesionality-2.png differ
diff --git a/notebooks/figures/05.01-regression-1.png b/notebooks/figures/05.01-regression-1.png
index ac88b593b..a61e580e4 100644
Binary files a/notebooks/figures/05.01-regression-1.png and b/notebooks/figures/05.01-regression-1.png differ
diff --git a/notebooks/figures/05.01-regression-2.png b/notebooks/figures/05.01-regression-2.png
index 8b190e307..4940513af 100644
Binary files a/notebooks/figures/05.01-regression-2.png and b/notebooks/figures/05.01-regression-2.png differ
diff --git a/notebooks/figures/05.01-regression-3.png b/notebooks/figures/05.01-regression-3.png
index b3239e992..50f2e5575 100644
Binary files a/notebooks/figures/05.01-regression-3.png and b/notebooks/figures/05.01-regression-3.png differ
diff --git a/notebooks/figures/05.01-regression-4.png b/notebooks/figures/05.01-regression-4.png
index 86cb979b7..939b37da6 100644
Binary files a/notebooks/figures/05.01-regression-4.png and b/notebooks/figures/05.01-regression-4.png differ
diff --git a/notebooks/figures/05.02-samples-features.png b/notebooks/figures/05.02-samples-features.png
index c37e3e647..a3a5a99b0 100644
Binary files a/notebooks/figures/05.02-samples-features.png and b/notebooks/figures/05.02-samples-features.png differ
diff --git a/notebooks/figures/05.03-2-fold-CV.png b/notebooks/figures/05.03-2-fold-CV.png
index f945b5e66..bfdd0bf56 100644
Binary files a/notebooks/figures/05.03-2-fold-CV.png and b/notebooks/figures/05.03-2-fold-CV.png differ
diff --git a/notebooks/figures/05.03-5-fold-CV.png b/notebooks/figures/05.03-5-fold-CV.png
index fcdd21a6f..88137a156 100644
Binary files a/notebooks/figures/05.03-5-fold-CV.png and b/notebooks/figures/05.03-5-fold-CV.png differ
diff --git a/notebooks/figures/05.03-bias-variance-2.png b/notebooks/figures/05.03-bias-variance-2.png
index f682f261e..995203a80 100644
Binary files a/notebooks/figures/05.03-bias-variance-2.png and b/notebooks/figures/05.03-bias-variance-2.png differ
diff --git a/notebooks/figures/05.03-bias-variance.png b/notebooks/figures/05.03-bias-variance.png
index 873f13d80..6a782d5fd 100644
Binary files a/notebooks/figures/05.03-bias-variance.png and b/notebooks/figures/05.03-bias-variance.png differ
diff --git a/notebooks/figures/05.03-learning-curve.png b/notebooks/figures/05.03-learning-curve.png
index b7d65ebfb..ee0df7232 100644
Binary files a/notebooks/figures/05.03-learning-curve.png and b/notebooks/figures/05.03-learning-curve.png differ
diff --git a/notebooks/figures/05.03-validation-curve.png b/notebooks/figures/05.03-validation-curve.png
index edcfece92..ab6076499 100644
Binary files a/notebooks/figures/05.03-validation-curve.png and b/notebooks/figures/05.03-validation-curve.png differ
diff --git a/notebooks/figures/05.05-gaussian-NB.png b/notebooks/figures/05.05-gaussian-NB.png
index 2b2b1d056..efd56eca8 100644
Binary files a/notebooks/figures/05.05-gaussian-NB.png and b/notebooks/figures/05.05-gaussian-NB.png differ
diff --git a/notebooks/figures/05.06-gaussian-basis.png b/notebooks/figures/05.06-gaussian-basis.png
index c19c4f3e8..60681063e 100644
Binary files a/notebooks/figures/05.06-gaussian-basis.png and b/notebooks/figures/05.06-gaussian-basis.png differ
diff --git a/notebooks/figures/05.08-decision-tree-levels.png b/notebooks/figures/05.08-decision-tree-levels.png
index 62157827e..3be4bcc1f 100644
Binary files a/notebooks/figures/05.08-decision-tree-levels.png and b/notebooks/figures/05.08-decision-tree-levels.png differ
diff --git a/notebooks/figures/05.08-decision-tree-overfitting.png b/notebooks/figures/05.08-decision-tree-overfitting.png
index c051c549f..c39586eac 100644
Binary files a/notebooks/figures/05.08-decision-tree-overfitting.png and b/notebooks/figures/05.08-decision-tree-overfitting.png differ
diff --git a/notebooks/figures/05.08-decision-tree.png b/notebooks/figures/05.08-decision-tree.png
index afcf773a8..4394a681c 100644
Binary files a/notebooks/figures/05.08-decision-tree.png and b/notebooks/figures/05.08-decision-tree.png differ
diff --git a/notebooks/figures/05.09-PCA-rotation.png b/notebooks/figures/05.09-PCA-rotation.png
index fdc678f26..9d5a9f222 100644
Binary files a/notebooks/figures/05.09-PCA-rotation.png and b/notebooks/figures/05.09-PCA-rotation.png differ
diff --git a/notebooks/figures/05.09-digits-pca-components.png b/notebooks/figures/05.09-digits-pca-components.png
index 94e2833ae..961b5a137 100644
Binary files a/notebooks/figures/05.09-digits-pca-components.png and b/notebooks/figures/05.09-digits-pca-components.png differ
diff --git a/notebooks/figures/05.09-digits-pixel-components.png b/notebooks/figures/05.09-digits-pixel-components.png
index 9eadc01ff..d6e8ca645 100644
Binary files a/notebooks/figures/05.09-digits-pixel-components.png and b/notebooks/figures/05.09-digits-pixel-components.png differ
diff --git a/notebooks/figures/05.10-LLE-vs-MDS.png b/notebooks/figures/05.10-LLE-vs-MDS.png
index e9562f66d..167d44a3b 100644
Binary files a/notebooks/figures/05.10-LLE-vs-MDS.png and b/notebooks/figures/05.10-LLE-vs-MDS.png differ
diff --git a/notebooks/figures/05.11-expectation-maximization.png b/notebooks/figures/05.11-expectation-maximization.png
index 9c0a7e4bc..86ff1c1ba 100644
Binary files a/notebooks/figures/05.11-expectation-maximization.png and b/notebooks/figures/05.11-expectation-maximization.png differ
diff --git a/notebooks/figures/05.12-covariance-type.png b/notebooks/figures/05.12-covariance-type.png
index 013425b9c..262c893f2 100644
Binary files a/notebooks/figures/05.12-covariance-type.png and b/notebooks/figures/05.12-covariance-type.png differ
diff --git a/tmp-folder/00.00-nbk.ipynb b/tmp-folder/00.00-nbk.ipynb
new file mode 100644
index 000000000..9ce9a5aca
--- /dev/null
+++ b/tmp-folder/00.00-nbk.ipynb
@@ -0,0 +1,208 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<!--BOOK_INFORMATION-->\n",
+    "<img align=\"left\" style=\"padding-right:10px;\" src=\"figures/PDSH-cover-small.png\">\n",
+    "*This notebook contains an excerpt from the [Python Data Science Handbook](http://shop.oreilly.com/product/0636920034919.do) by Jake VanderPlas; the content is available [on GitHub](https://github.com/jakevdp/PythonDataScienceHandbook).*\n",
+    "\n",
+    "*The text is released under the [CC-BY-NC-ND license](https://creativecommons.org/licenses/by-nc-nd/3.0/us/legalcode), and code is released under the [MIT license](https://opensource.org/licenses/MIT). If you find this content useful, please consider supporting the work by [buying the book](http://shop.oreilly.com/product/0636920034919.do)!*"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let us try to use \\\\$ sign literally and not as a math formula. Here's an actual math formula on the same line as literal dollor signs. $ a = b + c $ The price of this article is \\\\$10.50 and it's totally worth it."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's see if we can create code block in md --   \n",
+    "\n",
+    "            book a = 2 about doing data science\n",
+    "            which immediately begs the question\n",
+    "    what is data science"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Preface"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## What Is Data Science?\n",
+    "\n",
+    "This is a book about doing data science with Python, which immediately begs the question: what is *data science*?\n",
+    "It's a surprisingly hard definition to nail down, especially given how ubiquitous the term has become.\n",
+    "Vocal critics have variously dismissed the term as a superfluous label (after all, what science doesn't involve data?) or a simple buzzword that only exists to salt resumes and catch the eye of overzealous tech recruiters.\n",
+    "\n",
+    "In my mind, these critiques miss something important.\n",
+    "Data science, despite its hype-laden veneer, is perhaps the best label we have for the cross-disciplinary set of skills that are becoming increasingly important in many applications across industry and academia.\n",
+    "This cross-disciplinary piece is key: in my mind, the best extisting definition of data science is illustrated by Drew Conway's Data Science Venn Diagram, first published on his blog in September 2010:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![Data Science Venn Diagram](figures/Data_Science_VD.png)\n",
+    "\n",
+    "<small>(Source: [Drew Conway](http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram). Used by permission.)</small>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "While some of the intersection labels are a bit tongue-in-cheek, this diagram captures the essence of what I think people mean when they say \"data science\": it is fundamentally an *interdisciplinary* subject.\n",
+    "Data science comprises three distinct and overlapping areas: the skills of a *statistician* who knows how to model and summarize datasets (which are growing ever larger); the skills of a *computer scientist* who can design and use algorithms to efficiently store, process, and visualize this data; and the *domain expertise*—what we might think of as \"classical\" training in a subject—necessary both to formulate the right questions and to put their answers in context.\n",
+    "\n",
+    "With this in mind, I would encourage you to think of data science not as a new domain of knowledge to learn, but a new set of skills that you can apply within your current area of expertise.\n",
+    "Whether you are reporting election results, forecasting stock returns, optimizing online ad clicks, identifying microorganisms in microscope photos, seeking new classes of astronomical objects, or working with data in any other field, the goal of this book is to give you the ability to ask and answer new questions about your chosen subject area."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Who Is This Book For?\n",
+    "\n",
+    "In my teaching both at the University of Washington and at various tech-focused conferences and meetups, one of the most common questions I have heard is this: \"how should I learn Python?\"\n",
+    "The people asking are generally technically minded students, developers, or researchers, often with an already strong background in writing code and using computational and numerical tools.\n",
+    "Most of these folks don't want to learn Python *per se*, but want to learn the language with the aim of using it as a tool for data-intensive and computational science.\n",
+    "While a large patchwork of videos, blog posts, and tutorials for this audience is available online, I've long been frustrated by the lack of a single good answer to this question; that is what inspired this book.\n",
+    "\n",
+    "The book is not meant to be an introduction to Python or to programming in general; I assume the reader has familiarity with the Python language, including defining functions, assigning variables, calling methods of objects, controlling the flow of a program, and other basic tasks.\n",
+    "Instead it is meant to help Python users learn to use Python's data science stack–libraries such as IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related tools–to effectively store, manipulate, and gain insight from data."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Why Python?\n",
+    "\n",
+    "Python has emerged over the last couple decades as a first-class tool for scientific computing tasks, including the analysis and visualization of large datasets.\n",
+    "This may have come as a surprise to early proponents of the Python language: the language itself was not specifically designed with data analysis or scientific computing in mind.\n",
+    "The usefulness of Python for data science stems primarily from the large and active ecosystem of third-party packages: *NumPy* for manipulation of homogeneous array-based data, *Pandas* for manipulation of heterogeneous and labeled data, *SciPy* for common scientific computing tasks, *Matplotlib* for publication-quality visualizations, *IPython* for interactive execution and sharing of code, *Scikit-Learn* for machine learning, and many more tools that will be mentioned in the following pages.\n",
+    "\n",
+    "If you are looking for a guide to the Python language itself, I would suggest the sister project to this book, \"[A Whirlwind Tour of the Python Language](https://github.com/jakevdp/WhirlwindTourOfPython)\".\n",
+    "This short report provides a tour of the essential features of the Python language, aimed at data scientists who already are familiar with one or more other programming languages."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Python 2 vs Python 3\n",
+    "\n",
+    "This book uses the syntax of Python 3, which contains language enhancements that are not compatible with the 2.x series of Python.\n",
+    "Though Python 3.0 was first released in 2008, adoption has been relatively slow, particularly in the scientific and web development communities.\n",
+    "This is primarily because it took some time for many of the essential third-party packages and toolkits to be made compatible with the new language internals.\n",
+    "Since early 2014, however, stable releases of the most important tools in the data science ecosystem have been fully compatible with both Python 2 and 3, and so this book will use the newer Python 3 syntax.\n",
+    "However, the vast majority of code snippets in this book will also work without modification in Python 2: in cases where a Py2-incompatible syntax is used, I will make every effort to note it explicitly."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Outline of the Book\n",
+    "\n",
+    "Each chapter of this book focuses on a particular package or tool that contributes a fundamental piece of the Python Data Sciece story.\n",
+    "\n",
+    "1. IPython and Jupyter: these packages provide the computational environment in which many Python-using data scientists work.\n",
+    "2. NumPy: this library provides the ``ndarray`` for efficient storage and manipulation of dense data arrays in Python.\n",
+    "3. Pandas: this library provides the ``DataFrame`` for efficient storage and manipulation of labeled/columnar data in Python.\n",
+    "4. Matplotlib: this library provides capabilities for a flexible range of data visualizations in Python.\n",
+    "5. Scikit-Learn: this library provides efficient & clean Python implementations of the most important and established machine learning algorithms.\n",
+    "\n",
+    "The PyData world is certainly much larger than these five packages, and is growing every day.\n",
+    "With this in mind, I make every attempt through these pages to provide references to other interesting efforts, projects, and packages that are pushing the boundaries of what can be done in Python.\n",
+    "Nevertheless, these five are currently fundamental to much of the work being done in the Python data science space, and I expect they will remain important even as the ecosystem continues growing around them."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Using Code Examples\n",
+    "\n",
+    "Supplemental material (code examples, figures, etc.) is available for download at http://github.com/jakevdp/PythonDataScienceHandbook/. This book is here to help you get your job done. In general, if example code is offered with this book, you may use it in your programs and documentation. You do not need to contact us for permission unless you’re reproducing a significant portion of the code. For example, writing a program that uses several chunks of code from this book does not require permission. Selling or distributing a CD-ROM of examples from O’Reilly books does require permission. Answering a question by citing this book and quoting example code does not require permission. Incorporating a significant amount of example code from this book into your product’s documentation does require permission.\n",
+    "\n",
+    "We appreciate, but do not require, attribution. An attribution usually includes the title, author, publisher, and ISBN. For example:\n",
+    "\n",
+    "> *The Python Data Science Handbook* by Jake VanderPlas (O’Reilly). Copyright 2016 Jake VanderPlas, 978-1-491-91205-8.\n",
+    "\n",
+    "If you feel your use of code examples falls outside fair use or the per‐ mission given above, feel free to contact us at permissions@oreilly.com."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Installation Considerations\n",
+    "\n",
+    "Installing Python and the suite of libraries that enable scientific computing is straightforward . This section will outline some of the considerations when setting up your computer.\n",
+    "\n",
+    "Though there are various ways to install Python, the one I would suggest for use in data science is the Anaconda distribution, which works similarly whether you use Windows, Linux, or Mac OS X.\n",
+    "The Anaconda distribution comes in two flavors:\n",
+    "\n",
+    "- [Miniconda](http://conda.pydata.org/miniconda.html) gives you the Python interpreter itself, along with a command-line tool called ``conda`` which operates as a cross-platform package manager geared toward Python packages, similar in spirit to the apt or yum tools that Linux users might be familiar with.\n",
+    "\n",
+    "- [Anaconda](https://www.continuum.io/downloads) includes both Python and conda, and additionally bundles a suite of other pre-installed packages geared toward scientific computing. Because of the size of this bundle, expect the installation to consume several gigabytes of disk space.\n",
+    "\n",
+    "Any of the packages included with Anaconda can also be installed manually on top of Miniconda; for this reason I suggest starting with Miniconda.\n",
+    "\n",
+    "To get started, download and install the Miniconda package–make sure to choose a version with Python 3–and then install the core packages used in this book:\n",
+    "\n",
+    "```\n",
+    "[~]$ conda install numpy pandas scikit-learn matplotlib seaborn jupyter\n",
+    "```\n",
+    "\n",
+    "Throughout the text, we will also make use of other more specialized tools in Python's scientific ecosystem; installation is usually as easy as typing **``conda install packagename``**.\n",
+    "For more information on conda, including information about creating and using conda environments (which I would *highly* recommend), refer to [conda's online documentation](http://conda.pydata.org/docs/)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<!--NAVIGATION-->\n",
+    "| [Contents](Index.ipynb) | [IPython: Beyond Normal Python](01.00-IPython-Beyond-Normal-Python.ipynb) >"
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}